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/-
Copyright (c) 2022 Stuart Presnell. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Stuart Presnell, Eric Wieser, Yaël Dillies, Patrick Massot, Scott Morrison
-/
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.Algebra.Ring.Regular
import Mathlib.Order.Interval.Set.Basic
#align_import data.set.intervals.instances from "leanprover-community/mathlib"@"d012cd09a9b256d870751284dd6a29882b0be105"
/-!
# Algebraic instances for unit intervals
For suitably structured underlying type `α`, we exhibit the structure of
the unit intervals (`Set.Icc`, `Set.Ioc`, `Set.Ioc`, and `Set.Ioo`) from `0` to `1`.
Note: Instances for the interval `Ici 0` are dealt with in `Algebra/Order/Nonneg.lean`.
## Main definitions
The strongest typeclass provided on each interval is:
* `Set.Icc.cancelCommMonoidWithZero`
* `Set.Ico.commSemigroup`
* `Set.Ioc.commMonoid`
* `Set.Ioo.commSemigroup`
## TODO
* algebraic instances for intervals -1 to 1
* algebraic instances for `Ici 1`
* algebraic instances for `(Ioo (-1) 1)ᶜ`
* provide `distribNeg` instances where applicable
* prove versions of `mul_le_{left,right}` for other intervals
* prove versions of the lemmas in `Topology/UnitInterval` with `ℝ` generalized to
some arbitrary ordered semiring
-/
open Set
variable {α : Type*}
section OrderedSemiring
variable [OrderedSemiring α]
/-! ### Instances for `↥(Set.Icc 0 1)` -/
namespace Set.Icc
instance zero : Zero (Icc (0 : α) 1) where zero := ⟨0, left_mem_Icc.2 zero_le_one⟩
#align set.Icc.has_zero Set.Icc.zero
instance one : One (Icc (0 : α) 1) where one := ⟨1, right_mem_Icc.2 zero_le_one⟩
#align set.Icc.has_one Set.Icc.one
@[simp, norm_cast]
theorem coe_zero : ↑(0 : Icc (0 : α) 1) = (0 : α) :=
rfl
#align set.Icc.coe_zero Set.Icc.coe_zero
@[simp, norm_cast]
theorem coe_one : ↑(1 : Icc (0 : α) 1) = (1 : α) :=
rfl
#align set.Icc.coe_one Set.Icc.coe_one
@[simp]
theorem mk_zero (h : (0 : α) ∈ Icc (0 : α) 1) : (⟨0, h⟩ : Icc (0 : α) 1) = 0 :=
rfl
#align set.Icc.mk_zero Set.Icc.mk_zero
@[simp]
theorem mk_one (h : (1 : α) ∈ Icc (0 : α) 1) : (⟨1, h⟩ : Icc (0 : α) 1) = 1 :=
rfl
#align set.Icc.mk_one Set.Icc.mk_one
@[simp, norm_cast]
theorem coe_eq_zero {x : Icc (0 : α) 1} : (x : α) = 0 ↔ x = 0 := by
symm
exact Subtype.ext_iff
#align set.Icc.coe_eq_zero Set.Icc.coe_eq_zero
theorem coe_ne_zero {x : Icc (0 : α) 1} : (x : α) ≠ 0 ↔ x ≠ 0 :=
not_iff_not.mpr coe_eq_zero
#align set.Icc.coe_ne_zero Set.Icc.coe_ne_zero
@[simp, norm_cast]
theorem coe_eq_one {x : Icc (0 : α) 1} : (x : α) = 1 ↔ x = 1 := by
symm
exact Subtype.ext_iff
#align set.Icc.coe_eq_one Set.Icc.coe_eq_one
theorem coe_ne_one {x : Icc (0 : α) 1} : (x : α) ≠ 1 ↔ x ≠ 1 :=
not_iff_not.mpr coe_eq_one
#align set.Icc.coe_ne_one Set.Icc.coe_ne_one
theorem coe_nonneg (x : Icc (0 : α) 1) : 0 ≤ (x : α) :=
x.2.1
#align set.Icc.coe_nonneg Set.Icc.coe_nonneg
theorem coe_le_one (x : Icc (0 : α) 1) : (x : α) ≤ 1 :=
x.2.2
#align set.Icc.coe_le_one Set.Icc.coe_le_one
/-- like `coe_nonneg`, but with the inequality in `Icc (0:α) 1`. -/
theorem nonneg {t : Icc (0 : α) 1} : 0 ≤ t :=
t.2.1
#align set.Icc.nonneg Set.Icc.nonneg
/-- like `coe_le_one`, but with the inequality in `Icc (0:α) 1`. -/
theorem le_one {t : Icc (0 : α) 1} : t ≤ 1 :=
t.2.2
#align set.Icc.le_one Set.Icc.le_one
instance mul : Mul (Icc (0 : α) 1) where
mul p q := ⟨p * q, ⟨mul_nonneg p.2.1 q.2.1, mul_le_one p.2.2 q.2.1 q.2.2⟩⟩
#align set.Icc.has_mul Set.Icc.mul
instance pow : Pow (Icc (0 : α) 1) ℕ where
pow p n := ⟨p.1 ^ n, ⟨pow_nonneg p.2.1 n, pow_le_one n p.2.1 p.2.2⟩⟩
#align set.Icc.has_pow Set.Icc.pow
@[simp, norm_cast]
theorem coe_mul (x y : Icc (0 : α) 1) : ↑(x * y) = (x * y : α) :=
rfl
#align set.Icc.coe_mul Set.Icc.coe_mul
@[simp, norm_cast]
theorem coe_pow (x : Icc (0 : α) 1) (n : ℕ) : ↑(x ^ n) = ((x : α) ^ n) :=
rfl
#align set.Icc.coe_pow Set.Icc.coe_pow
theorem mul_le_left {x y : Icc (0 : α) 1} : x * y ≤ x :=
(mul_le_mul_of_nonneg_left y.2.2 x.2.1).trans_eq (mul_one _)
#align set.Icc.mul_le_left Set.Icc.mul_le_left
theorem mul_le_right {x y : Icc (0 : α) 1} : x * y ≤ y :=
(mul_le_mul_of_nonneg_right x.2.2 y.2.1).trans_eq (one_mul _)
#align set.Icc.mul_le_right Set.Icc.mul_le_right
instance monoidWithZero : MonoidWithZero (Icc (0 : α) 1) :=
Subtype.coe_injective.monoidWithZero _ coe_zero coe_one coe_mul coe_pow
#align set.Icc.monoid_with_zero Set.Icc.monoidWithZero
instance commMonoidWithZero {α : Type*} [OrderedCommSemiring α] :
CommMonoidWithZero (Icc (0 : α) 1) :=
Subtype.coe_injective.commMonoidWithZero _ coe_zero coe_one coe_mul coe_pow
#align set.Icc.comm_monoid_with_zero Set.Icc.commMonoidWithZero
instance cancelMonoidWithZero {α : Type*} [OrderedRing α] [NoZeroDivisors α] :
CancelMonoidWithZero (Icc (0 : α) 1) :=
@Function.Injective.cancelMonoidWithZero α _ NoZeroDivisors.toCancelMonoidWithZero _ _ _ _
(fun v => v.val) Subtype.coe_injective coe_zero coe_one coe_mul coe_pow
#align set.Icc.cancel_monoid_with_zero Set.Icc.cancelMonoidWithZero
instance cancelCommMonoidWithZero {α : Type*} [OrderedCommRing α] [NoZeroDivisors α] :
CancelCommMonoidWithZero (Icc (0 : α) 1) :=
@Function.Injective.cancelCommMonoidWithZero α _ NoZeroDivisors.toCancelCommMonoidWithZero _ _ _ _
(fun v => v.val) Subtype.coe_injective coe_zero coe_one coe_mul coe_pow
#align set.Icc.cancel_comm_monoid_with_zero Set.Icc.cancelCommMonoidWithZero
variable {β : Type*} [OrderedRing β]
theorem one_sub_mem {t : β} (ht : t ∈ Icc (0 : β) 1) : 1 - t ∈ Icc (0 : β) 1 := by
rw [mem_Icc] at *
exact ⟨sub_nonneg.2 ht.2, (sub_le_self_iff _).2 ht.1⟩
#align set.Icc.one_sub_mem Set.Icc.one_sub_mem
theorem mem_iff_one_sub_mem {t : β} : t ∈ Icc (0 : β) 1 ↔ 1 - t ∈ Icc (0 : β) 1 :=
⟨one_sub_mem, fun h => sub_sub_cancel 1 t ▸ one_sub_mem h⟩
#align set.Icc.mem_iff_one_sub_mem Set.Icc.mem_iff_one_sub_mem
theorem one_sub_nonneg (x : Icc (0 : β) 1) : 0 ≤ 1 - (x : β) := by simpa using x.2.2
#align set.Icc.one_sub_nonneg Set.Icc.one_sub_nonneg
theorem one_sub_le_one (x : Icc (0 : β) 1) : 1 - (x : β) ≤ 1 := by simpa using x.2.1
#align set.Icc.one_sub_le_one Set.Icc.one_sub_le_one
end Set.Icc
/-! ### Instances for `↥(Set.Ico 0 1)` -/
namespace Set.Ico
instance zero [Nontrivial α] : Zero (Ico (0 : α) 1) where zero := ⟨0, left_mem_Ico.2 zero_lt_one⟩
#align set.Ico.has_zero Set.Ico.zero
@[simp, norm_cast]
theorem coe_zero [Nontrivial α] : ↑(0 : Ico (0 : α) 1) = (0 : α) :=
rfl
#align set.Ico.coe_zero Set.Ico.coe_zero
@[simp]
theorem mk_zero [Nontrivial α] (h : (0 : α) ∈ Ico (0 : α) 1) : (⟨0, h⟩ : Ico (0 : α) 1) = 0 :=
rfl
#align set.Ico.mk_zero Set.Ico.mk_zero
@[simp, norm_cast]
theorem coe_eq_zero [Nontrivial α] {x : Ico (0 : α) 1} : (x : α) = 0 ↔ x = 0 := by
symm
exact Subtype.ext_iff
#align set.Ico.coe_eq_zero Set.Ico.coe_eq_zero
theorem coe_ne_zero [Nontrivial α] {x : Ico (0 : α) 1} : (x : α) ≠ 0 ↔ x ≠ 0 :=
not_iff_not.mpr coe_eq_zero
#align set.Ico.coe_ne_zero Set.Ico.coe_ne_zero
theorem coe_nonneg (x : Ico (0 : α) 1) : 0 ≤ (x : α) :=
x.2.1
#align set.Ico.coe_nonneg Set.Ico.coe_nonneg
theorem coe_lt_one (x : Ico (0 : α) 1) : (x : α) < 1 :=
x.2.2
#align set.Ico.coe_lt_one Set.Ico.coe_lt_one
/-- like `coe_nonneg`, but with the inequality in `Ico (0:α) 1`. -/
theorem nonneg [Nontrivial α] {t : Ico (0 : α) 1} : 0 ≤ t :=
t.2.1
#align set.Ico.nonneg Set.Ico.nonneg
instance mul : Mul (Ico (0 : α) 1) where
mul p q :=
⟨p * q, ⟨mul_nonneg p.2.1 q.2.1, mul_lt_one_of_nonneg_of_lt_one_right p.2.2.le q.2.1 q.2.2⟩⟩
#align set.Ico.has_mul Set.Ico.mul
@[simp, norm_cast]
theorem coe_mul (x y : Ico (0 : α) 1) : ↑(x * y) = (x * y : α) :=
rfl
#align set.Ico.coe_mul Set.Ico.coe_mul
instance semigroup : Semigroup (Ico (0 : α) 1) :=
Subtype.coe_injective.semigroup _ coe_mul
#align set.Ico.semigroup Set.Ico.semigroup
instance commSemigroup {α : Type*} [OrderedCommSemiring α] : CommSemigroup (Ico (0 : α) 1) :=
Subtype.coe_injective.commSemigroup _ coe_mul
#align set.Ico.comm_semigroup Set.Ico.commSemigroup
end Set.Ico
end OrderedSemiring
variable [StrictOrderedSemiring α]
/-! ### Instances for `↥(Set.Ioc 0 1)` -/
namespace Set.Ioc
instance one [Nontrivial α] : One (Ioc (0 : α) 1) where one := ⟨1, ⟨zero_lt_one, le_refl 1⟩⟩
#align set.Ioc.has_one Set.Ioc.one
@[simp, norm_cast]
theorem coe_one [Nontrivial α] : ↑(1 : Ioc (0 : α) 1) = (1 : α) :=
rfl
#align set.Ioc.coe_one Set.Ioc.coe_one
@[simp]
theorem mk_one [Nontrivial α] (h : (1 : α) ∈ Ioc (0 : α) 1) : (⟨1, h⟩ : Ioc (0 : α) 1) = 1 :=
rfl
#align set.Ioc.mk_one Set.Ioc.mk_one
@[simp, norm_cast]
| Mathlib/Algebra/Order/Interval/Set/Instances.lean | 266 | 268 | theorem coe_eq_one [Nontrivial α] {x : Ioc (0 : α) 1} : (x : α) = 1 ↔ x = 1 := by |
symm
exact Subtype.ext_iff
|
/-
Copyright (c) 2021 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Data.Finset.Sort
import Mathlib.Data.List.FinRange
import Mathlib.Data.Prod.Lex
import Mathlib.GroupTheory.Perm.Basic
import Mathlib.Order.Interval.Finset.Fin
#align_import data.fin.tuple.sort from "leanprover-community/mathlib"@"8631e2d5ea77f6c13054d9151d82b83069680cb1"
/-!
# Sorting tuples by their values
Given an `n`-tuple `f : Fin n → α` where `α` is ordered,
we may want to turn it into a sorted `n`-tuple.
This file provides an API for doing so, with the sorted `n`-tuple given by
`f ∘ Tuple.sort f`.
## Main declarations
* `Tuple.sort`: given `f : Fin n → α`, produces a permutation on `Fin n`
* `Tuple.monotone_sort`: `f ∘ Tuple.sort f` is `Monotone`
-/
namespace Tuple
variable {n : ℕ}
variable {α : Type*} [LinearOrder α]
/-- `graph f` produces the finset of pairs `(f i, i)`
equipped with the lexicographic order.
-/
def graph (f : Fin n → α) : Finset (α ×ₗ Fin n) :=
Finset.univ.image fun i => (f i, i)
#align tuple.graph Tuple.graph
/-- Given `p : α ×ₗ (Fin n) := (f i, i)` with `p ∈ graph f`,
`graph.proj p` is defined to be `f i`.
-/
def graph.proj {f : Fin n → α} : graph f → α := fun p => p.1.1
#align tuple.graph.proj Tuple.graph.proj
@[simp]
theorem graph.card (f : Fin n → α) : (graph f).card = n := by
rw [graph, Finset.card_image_of_injective]
· exact Finset.card_fin _
· intro _ _
-- porting note (#10745): was `simp`
dsimp only
rw [Prod.ext_iff]
simp
#align tuple.graph.card Tuple.graph.card
/-- `graphEquiv₁ f` is the natural equivalence between `Fin n` and `graph f`,
mapping `i` to `(f i, i)`. -/
def graphEquiv₁ (f : Fin n → α) : Fin n ≃ graph f where
toFun i := ⟨(f i, i), by simp [graph]⟩
invFun p := p.1.2
left_inv i := by simp
right_inv := fun ⟨⟨x, i⟩, h⟩ => by
-- Porting note: was `simpa [graph] using h`
simp only [graph, Finset.mem_image, Finset.mem_univ, true_and] at h
obtain ⟨i', hi'⟩ := h
obtain ⟨-, rfl⟩ := Prod.mk.inj_iff.mp hi'
simpa
#align tuple.graph_equiv₁ Tuple.graphEquiv₁
@[simp]
theorem proj_equiv₁' (f : Fin n → α) : graph.proj ∘ graphEquiv₁ f = f :=
rfl
#align tuple.proj_equiv₁' Tuple.proj_equiv₁'
/-- `graphEquiv₂ f` is an equivalence between `Fin n` and `graph f` that respects the order.
-/
def graphEquiv₂ (f : Fin n → α) : Fin n ≃o graph f :=
Finset.orderIsoOfFin _ (by simp)
#align tuple.graph_equiv₂ Tuple.graphEquiv₂
/-- `sort f` is the permutation that orders `Fin n` according to the order of the outputs of `f`. -/
def sort (f : Fin n → α) : Equiv.Perm (Fin n) :=
(graphEquiv₂ f).toEquiv.trans (graphEquiv₁ f).symm
#align tuple.sort Tuple.sort
theorem graphEquiv₂_apply (f : Fin n → α) (i : Fin n) :
graphEquiv₂ f i = graphEquiv₁ f (sort f i) :=
((graphEquiv₁ f).apply_symm_apply _).symm
#align tuple.graph_equiv₂_apply Tuple.graphEquiv₂_apply
theorem self_comp_sort (f : Fin n → α) : f ∘ sort f = graph.proj ∘ graphEquiv₂ f :=
show graph.proj ∘ (graphEquiv₁ f ∘ (graphEquiv₁ f).symm) ∘ (graphEquiv₂ f).toEquiv = _ by simp
#align tuple.self_comp_sort Tuple.self_comp_sort
theorem monotone_proj (f : Fin n → α) : Monotone (graph.proj : graph f → α) := by
rintro ⟨⟨x, i⟩, hx⟩ ⟨⟨y, j⟩, hy⟩ (_ | h)
· exact le_of_lt ‹_›
· simp [graph.proj]
#align tuple.monotone_proj Tuple.monotone_proj
theorem monotone_sort (f : Fin n → α) : Monotone (f ∘ sort f) := by
rw [self_comp_sort]
exact (monotone_proj f).comp (graphEquiv₂ f).monotone
#align tuple.monotone_sort Tuple.monotone_sort
end Tuple
namespace Tuple
open List
variable {n : ℕ} {α : Type*}
/-- If `f₀ ≤ f₁ ≤ f₂ ≤ ⋯` is a sorted `m`-tuple of elements of `α`, then for any `j : Fin m` and
`a : α` we have `j < #{i | fᵢ ≤ a}` iff `fⱼ ≤ a`. -/
theorem lt_card_le_iff_apply_le_of_monotone [PartialOrder α] [DecidableRel (α := α) LE.le]
{m : ℕ} (f : Fin m → α) (a : α) (h_sorted : Monotone f) (j : Fin m) :
j < Fintype.card {i // f i ≤ a} ↔ f j ≤ a := by
suffices h1 : ∀ k : Fin m, (k < Fintype.card {i // f i ≤ a}) → f k ≤ a by
refine ⟨h1 j, fun h ↦ ?_⟩
by_contra! hc
let p : Fin m → Prop := fun x ↦ f x ≤ a
let q : Fin m → Prop := fun x ↦ x < Fintype.card {i // f i ≤ a}
let q' : {i // f i ≤ a} → Prop := fun x ↦ q x
have hw : 0 < Fintype.card {j : {x : Fin m // f x ≤ a} // ¬ q' j} :=
Fintype.card_pos_iff.2 ⟨⟨⟨j, h⟩, not_lt.2 hc⟩⟩
apply hw.ne'
have he := Fintype.card_congr <| Equiv.sumCompl <| q'
have h4 := (Fintype.card_congr (@Equiv.subtypeSubtypeEquivSubtype _ p q (h1 _)))
have h_le : Fintype.card { i // f i ≤ a } ≤ m := by
conv_rhs => rw [← Fintype.card_fin m]
exact Fintype.card_subtype_le _
rwa [Fintype.card_sum, h4, Fintype.card_fin_lt_of_le h_le, add_right_eq_self] at he
intro _ h
contrapose! h
rw [← Fin.card_Iio, Fintype.card_subtype]
refine Finset.card_mono (fun i => Function.mtr ?_)
simp_rw [Finset.mem_filter, Finset.mem_univ, true_and, Finset.mem_Iio]
intro hij hia
apply h
exact (h_sorted (le_of_not_lt hij)).trans hia
theorem lt_card_ge_iff_apply_ge_of_antitone [PartialOrder α] [DecidableRel (α := α) LE.le]
{m : ℕ} (f : Fin m → α) (a : α) (h_sorted : Antitone f) (j : Fin m) :
j < Fintype.card {i // a ≤ f i} ↔ a ≤ f j :=
lt_card_le_iff_apply_le_of_monotone _ (OrderDual.toDual a) h_sorted.dual_right j
/-- If two permutations of a tuple `f` are both monotone, then they are equal. -/
theorem unique_monotone [PartialOrder α] {f : Fin n → α} {σ τ : Equiv.Perm (Fin n)}
(hfσ : Monotone (f ∘ σ)) (hfτ : Monotone (f ∘ τ)) : f ∘ σ = f ∘ τ :=
ofFn_injective <|
eq_of_perm_of_sorted ((σ.ofFn_comp_perm f).trans (τ.ofFn_comp_perm f).symm)
hfσ.ofFn_sorted hfτ.ofFn_sorted
#align tuple.unique_monotone Tuple.unique_monotone
variable [LinearOrder α] {f : Fin n → α} {σ : Equiv.Perm (Fin n)}
/-- A permutation `σ` equals `sort f` if and only if the map `i ↦ (f (σ i), σ i)` is
strictly monotone (w.r.t. the lexicographic ordering on the target). -/
theorem eq_sort_iff' : σ = sort f ↔ StrictMono (σ.trans <| graphEquiv₁ f) := by
constructor <;> intro h
· rw [h, sort, Equiv.trans_assoc, Equiv.symm_trans_self]
exact (graphEquiv₂ f).strictMono
· have := Subsingleton.elim (graphEquiv₂ f) (h.orderIsoOfSurjective _ <| Equiv.surjective _)
ext1 x
exact (graphEquiv₁ f).apply_eq_iff_eq_symm_apply.1 (DFunLike.congr_fun this x).symm
#align tuple.eq_sort_iff' Tuple.eq_sort_iff'
/-- A permutation `σ` equals `sort f` if and only if `f ∘ σ` is monotone and whenever `i < j`
and `f (σ i) = f (σ j)`, then `σ i < σ j`. This means that `sort f` is the lexicographically
smallest permutation `σ` such that `f ∘ σ` is monotone. -/
theorem eq_sort_iff :
σ = sort f ↔ Monotone (f ∘ σ) ∧ ∀ i j, i < j → f (σ i) = f (σ j) → σ i < σ j := by
rw [eq_sort_iff']
refine ⟨fun h => ⟨(monotone_proj f).comp h.monotone, fun i j hij hfij => ?_⟩, fun h i j hij => ?_⟩
· exact (((Prod.Lex.lt_iff _ _).1 <| h hij).resolve_left hfij.not_lt).2
· obtain he | hl := (h.1 hij.le).eq_or_lt <;> apply (Prod.Lex.lt_iff _ _).2
exacts [Or.inr ⟨he, h.2 i j hij he⟩, Or.inl hl]
#align tuple.eq_sort_iff Tuple.eq_sort_iff
/-- The permutation that sorts `f` is the identity if and only if `f` is monotone. -/
| Mathlib/Data/Fin/Tuple/Sort.lean | 186 | 189 | theorem sort_eq_refl_iff_monotone : sort f = Equiv.refl _ ↔ Monotone f := by |
rw [eq_comm, eq_sort_iff, Equiv.coe_refl, Function.comp_id]
simp only [id, and_iff_left_iff_imp]
exact fun _ _ _ hij _ => hij
|
/-
Copyright (c) 2022 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.FieldTheory.Minpoly.IsIntegrallyClosed
import Mathlib.RingTheory.PowerBasis
#align_import ring_theory.is_adjoin_root from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c"
/-!
# A predicate on adjoining roots of polynomial
This file defines a predicate `IsAdjoinRoot S f`, which states that the ring `S` can be
constructed by adjoining a specified root of the polynomial `f : R[X]` to `R`.
This predicate is useful when the same ring can be generated by adjoining the root of different
polynomials, and you want to vary which polynomial you're considering.
The results in this file are intended to mirror those in `RingTheory.AdjoinRoot`,
in order to provide an easier way to translate results from one to the other.
## Motivation
`AdjoinRoot` presents one construction of a ring `R[α]`. However, it is possible to obtain
rings of this form in many ways, such as `NumberField.ringOfIntegers ℚ(√-5)`,
or `Algebra.adjoin R {α, α^2}`, or `IntermediateField.adjoin R {α, 2 - α}`,
or even if we want to view `ℂ` as adjoining a root of `X^2 + 1` to `ℝ`.
## Main definitions
The two main predicates in this file are:
* `IsAdjoinRoot S f`: `S` is generated by adjoining a specified root of `f : R[X]` to `R`
* `IsAdjoinRootMonic S f`: `S` is generated by adjoining a root of the monic polynomial
`f : R[X]` to `R`
Using `IsAdjoinRoot` to map into `S`:
* `IsAdjoinRoot.map`: inclusion from `R[X]` to `S`
* `IsAdjoinRoot.root`: the specific root adjoined to `R` to give `S`
Using `IsAdjoinRoot` to map out of `S`:
* `IsAdjoinRoot.repr`: choose a non-unique representative in `R[X]`
* `IsAdjoinRoot.lift`, `IsAdjoinRoot.liftHom`: lift a morphism `R →+* T` to `S →+* T`
* `IsAdjoinRootMonic.modByMonicHom`: a unique representative in `R[X]` if `f` is monic
## Main results
* `AdjoinRoot.isAdjoinRoot` and `AdjoinRoot.isAdjoinRootMonic`:
`AdjoinRoot` satisfies the conditions on `IsAdjoinRoot`(`_monic`)
* `IsAdjoinRootMonic.powerBasis`: the `root` generates a power basis on `S` over `R`
* `IsAdjoinRoot.aequiv`: algebra isomorphism showing adjoining a root gives a unique ring
up to isomorphism
* `IsAdjoinRoot.ofEquiv`: transfer `IsAdjoinRoot` across an algebra isomorphism
* `IsAdjoinRootMonic.minpoly_eq`: the minimal polynomial of the adjoined root of `f` is equal to
`f`, if `f` is irreducible and monic, and `R` is a GCD domain
-/
open scoped Polynomial
open Polynomial
noncomputable section
universe u v
-- Porting note: this looks like something that should not be here
-- section MoveMe
--
-- end MoveMe
-- This class doesn't really make sense on a predicate
/-- `IsAdjoinRoot S f` states that the ring `S` can be constructed by adjoining a specified root
of the polynomial `f : R[X]` to `R`.
Compare `PowerBasis R S`, which does not explicitly specify which polynomial we adjoin a root of
(in particular `f` does not need to be the minimal polynomial of the root we adjoin),
and `AdjoinRoot` which constructs a new type.
This is not a typeclass because the choice of root given `S` and `f` is not unique.
-/
-- Porting note(#5171): this linter isn't ported yet.
-- @[nolint has_nonempty_instance]
structure IsAdjoinRoot {R : Type u} (S : Type v) [CommSemiring R] [Semiring S] [Algebra R S]
(f : R[X]) : Type max u v where
map : R[X] →+* S
map_surjective : Function.Surjective map
ker_map : RingHom.ker map = Ideal.span {f}
algebraMap_eq : algebraMap R S = map.comp Polynomial.C
#align is_adjoin_root IsAdjoinRoot
-- This class doesn't really make sense on a predicate
/-- `IsAdjoinRootMonic S f` states that the ring `S` can be constructed by adjoining a specified
root of the monic polynomial `f : R[X]` to `R`.
As long as `f` is monic, there is a well-defined representation of elements of `S` as polynomials
in `R[X]` of degree lower than `deg f` (see `modByMonicHom` and `coeff`). In particular,
we have `IsAdjoinRootMonic.powerBasis`.
Bundling `Monic` into this structure is very useful when working with explicit `f`s such as
`X^2 - C a * X - C b` since it saves you carrying around the proofs of monicity.
-/
-- @[nolint has_nonempty_instance] -- Porting note: This linter does not exist yet.
structure IsAdjoinRootMonic {R : Type u} (S : Type v) [CommSemiring R] [Semiring S] [Algebra R S]
(f : R[X]) extends IsAdjoinRoot S f where
Monic : Monic f
#align is_adjoin_root_monic IsAdjoinRootMonic
section Ring
variable {R : Type u} {S : Type v} [CommRing R] [Ring S] {f : R[X]} [Algebra R S]
namespace IsAdjoinRoot
/-- `(h : IsAdjoinRoot S f).root` is the root of `f` that can be adjoined to generate `S`. -/
def root (h : IsAdjoinRoot S f) : S :=
h.map X
#align is_adjoin_root.root IsAdjoinRoot.root
theorem subsingleton (h : IsAdjoinRoot S f) [Subsingleton R] : Subsingleton S :=
h.map_surjective.subsingleton
#align is_adjoin_root.subsingleton IsAdjoinRoot.subsingleton
theorem algebraMap_apply (h : IsAdjoinRoot S f) (x : R) :
algebraMap R S x = h.map (Polynomial.C x) := by rw [h.algebraMap_eq, RingHom.comp_apply]
#align is_adjoin_root.algebra_map_apply IsAdjoinRoot.algebraMap_apply
@[simp]
theorem mem_ker_map (h : IsAdjoinRoot S f) {p} : p ∈ RingHom.ker h.map ↔ f ∣ p := by
rw [h.ker_map, Ideal.mem_span_singleton]
#align is_adjoin_root.mem_ker_map IsAdjoinRoot.mem_ker_map
theorem map_eq_zero_iff (h : IsAdjoinRoot S f) {p} : h.map p = 0 ↔ f ∣ p := by
rw [← h.mem_ker_map, RingHom.mem_ker]
#align is_adjoin_root.map_eq_zero_iff IsAdjoinRoot.map_eq_zero_iff
@[simp]
theorem map_X (h : IsAdjoinRoot S f) : h.map X = h.root := rfl
set_option linter.uppercaseLean3 false in
#align is_adjoin_root.map_X IsAdjoinRoot.map_X
@[simp]
theorem map_self (h : IsAdjoinRoot S f) : h.map f = 0 := h.map_eq_zero_iff.mpr dvd_rfl
#align is_adjoin_root.map_self IsAdjoinRoot.map_self
@[simp]
theorem aeval_eq (h : IsAdjoinRoot S f) (p : R[X]) : aeval h.root p = h.map p :=
Polynomial.induction_on p (fun x => by rw [aeval_C, h.algebraMap_apply])
(fun p q ihp ihq => by rw [AlgHom.map_add, RingHom.map_add, ihp, ihq]) fun n x _ => by
rw [AlgHom.map_mul, aeval_C, AlgHom.map_pow, aeval_X, RingHom.map_mul, ← h.algebraMap_apply,
RingHom.map_pow, map_X]
#align is_adjoin_root.aeval_eq IsAdjoinRoot.aeval_eq
-- @[simp] -- Porting note (#10618): simp can prove this
theorem aeval_root (h : IsAdjoinRoot S f) : aeval h.root f = 0 := by rw [aeval_eq, map_self]
#align is_adjoin_root.aeval_root IsAdjoinRoot.aeval_root
/-- Choose an arbitrary representative so that `h.map (h.repr x) = x`.
If `f` is monic, use `IsAdjoinRootMonic.modByMonicHom` for a unique choice of representative.
-/
def repr (h : IsAdjoinRoot S f) (x : S) : R[X] :=
(h.map_surjective x).choose
#align is_adjoin_root.repr IsAdjoinRoot.repr
theorem map_repr (h : IsAdjoinRoot S f) (x : S) : h.map (h.repr x) = x :=
(h.map_surjective x).choose_spec
#align is_adjoin_root.map_repr IsAdjoinRoot.map_repr
/-- `repr` preserves zero, up to multiples of `f` -/
theorem repr_zero_mem_span (h : IsAdjoinRoot S f) : h.repr 0 ∈ Ideal.span ({f} : Set R[X]) := by
rw [← h.ker_map, RingHom.mem_ker, h.map_repr]
#align is_adjoin_root.repr_zero_mem_span IsAdjoinRoot.repr_zero_mem_span
/-- `repr` preserves addition, up to multiples of `f` -/
theorem repr_add_sub_repr_add_repr_mem_span (h : IsAdjoinRoot S f) (x y : S) :
h.repr (x + y) - (h.repr x + h.repr y) ∈ Ideal.span ({f} : Set R[X]) := by
rw [← h.ker_map, RingHom.mem_ker, map_sub, h.map_repr, map_add, h.map_repr, h.map_repr, sub_self]
#align is_adjoin_root.repr_add_sub_repr_add_repr_mem_span IsAdjoinRoot.repr_add_sub_repr_add_repr_mem_span
/-- Extensionality of the `IsAdjoinRoot` structure itself. See `IsAdjoinRootMonic.ext_elem`
for extensionality of the ring elements. -/
theorem ext_map (h h' : IsAdjoinRoot S f) (eq : ∀ x, h.map x = h'.map x) : h = h' := by
cases h; cases h'; congr
exact RingHom.ext eq
#align is_adjoin_root.ext_map IsAdjoinRoot.ext_map
/-- Extensionality of the `IsAdjoinRoot` structure itself. See `IsAdjoinRootMonic.ext_elem`
for extensionality of the ring elements. -/
@[ext]
theorem ext (h h' : IsAdjoinRoot S f) (eq : h.root = h'.root) : h = h' :=
h.ext_map h' fun x => by rw [← h.aeval_eq, ← h'.aeval_eq, eq]
#align is_adjoin_root.ext IsAdjoinRoot.ext
section lift
variable {T : Type*} [CommRing T] {i : R →+* T} {x : T} (hx : f.eval₂ i x = 0)
/-- Auxiliary lemma for `IsAdjoinRoot.lift` -/
theorem eval₂_repr_eq_eval₂_of_map_eq (h : IsAdjoinRoot S f) (z : S) (w : R[X])
(hzw : h.map w = z) : (h.repr z).eval₂ i x = w.eval₂ i x := by
rw [eq_comm, ← sub_eq_zero, ← h.map_repr z, ← map_sub, h.map_eq_zero_iff] at hzw
obtain ⟨y, hy⟩ := hzw
rw [← sub_eq_zero, ← eval₂_sub, hy, eval₂_mul, hx, zero_mul]
#align is_adjoin_root.eval₂_repr_eq_eval₂_of_map_eq IsAdjoinRoot.eval₂_repr_eq_eval₂_of_map_eq
variable (i x)
-- To match `AdjoinRoot.lift`
/-- Lift a ring homomorphism `R →+* T` to `S →+* T` by specifying a root `x` of `f` in `T`,
where `S` is given by adjoining a root of `f` to `R`. -/
def lift (h : IsAdjoinRoot S f) : S →+* T where
toFun z := (h.repr z).eval₂ i x
map_zero' := by
dsimp only -- Porting note (#10752): added `dsimp only`
rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ _ (map_zero _), eval₂_zero]
map_add' z w := by
dsimp only -- Porting note (#10752): added `dsimp only`
rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ (h.repr z + h.repr w), eval₂_add]
rw [map_add, map_repr, map_repr]
map_one' := by
beta_reduce -- Porting note (#12129): additional beta reduction needed
rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ _ (map_one _), eval₂_one]
map_mul' z w := by
dsimp only -- Porting note (#10752): added `dsimp only`
rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ (h.repr z * h.repr w), eval₂_mul]
rw [map_mul, map_repr, map_repr]
#align is_adjoin_root.lift IsAdjoinRoot.lift
variable {i x}
@[simp]
theorem lift_map (h : IsAdjoinRoot S f) (z : R[X]) : h.lift i x hx (h.map z) = z.eval₂ i x := by
rw [lift, RingHom.coe_mk]
dsimp -- Porting note (#11227):added a `dsimp`
rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ _ rfl]
#align is_adjoin_root.lift_map IsAdjoinRoot.lift_map
@[simp]
theorem lift_root (h : IsAdjoinRoot S f) : h.lift i x hx h.root = x := by
rw [← h.map_X, lift_map, eval₂_X]
#align is_adjoin_root.lift_root IsAdjoinRoot.lift_root
@[simp]
theorem lift_algebraMap (h : IsAdjoinRoot S f) (a : R) :
h.lift i x hx (algebraMap R S a) = i a := by rw [h.algebraMap_apply, lift_map, eval₂_C]
#align is_adjoin_root.lift_algebra_map IsAdjoinRoot.lift_algebraMap
/-- Auxiliary lemma for `apply_eq_lift` -/
theorem apply_eq_lift (h : IsAdjoinRoot S f) (g : S →+* T) (hmap : ∀ a, g (algebraMap R S a) = i a)
(hroot : g h.root = x) (a : S) : g a = h.lift i x hx a := by
rw [← h.map_repr a, Polynomial.as_sum_range_C_mul_X_pow (h.repr a)]
simp only [map_sum, map_mul, map_pow, h.map_X, hroot, ← h.algebraMap_apply, hmap, lift_root,
lift_algebraMap]
#align is_adjoin_root.apply_eq_lift IsAdjoinRoot.apply_eq_lift
/-- Unicity of `lift`: a map that agrees on `R` and `h.root` agrees with `lift` everywhere. -/
theorem eq_lift (h : IsAdjoinRoot S f) (g : S →+* T) (hmap : ∀ a, g (algebraMap R S a) = i a)
(hroot : g h.root = x) : g = h.lift i x hx :=
RingHom.ext (h.apply_eq_lift hx g hmap hroot)
#align is_adjoin_root.eq_lift IsAdjoinRoot.eq_lift
variable [Algebra R T] (hx' : aeval x f = 0)
variable (x)
-- To match `AdjoinRoot.liftHom`
/-- Lift the algebra map `R → T` to `S →ₐ[R] T` by specifying a root `x` of `f` in `T`,
where `S` is given by adjoining a root of `f` to `R`. -/
def liftHom (h : IsAdjoinRoot S f) : S →ₐ[R] T :=
{ h.lift (algebraMap R T) x hx' with commutes' := fun a => h.lift_algebraMap hx' a }
#align is_adjoin_root.lift_hom IsAdjoinRoot.liftHom
variable {x}
@[simp]
theorem coe_liftHom (h : IsAdjoinRoot S f) :
(h.liftHom x hx' : S →+* T) = h.lift (algebraMap R T) x hx' := rfl
#align is_adjoin_root.coe_lift_hom IsAdjoinRoot.coe_liftHom
theorem lift_algebraMap_apply (h : IsAdjoinRoot S f) (z : S) :
h.lift (algebraMap R T) x hx' z = h.liftHom x hx' z := rfl
#align is_adjoin_root.lift_algebra_map_apply IsAdjoinRoot.lift_algebraMap_apply
@[simp]
theorem liftHom_map (h : IsAdjoinRoot S f) (z : R[X]) : h.liftHom x hx' (h.map z) = aeval x z := by
rw [← lift_algebraMap_apply, lift_map, aeval_def]
#align is_adjoin_root.lift_hom_map IsAdjoinRoot.liftHom_map
@[simp]
theorem liftHom_root (h : IsAdjoinRoot S f) : h.liftHom x hx' h.root = x := by
rw [← lift_algebraMap_apply, lift_root]
#align is_adjoin_root.lift_hom_root IsAdjoinRoot.liftHom_root
/-- Unicity of `liftHom`: a map that agrees on `h.root` agrees with `liftHom` everywhere. -/
theorem eq_liftHom (h : IsAdjoinRoot S f) (g : S →ₐ[R] T) (hroot : g h.root = x) :
g = h.liftHom x hx' :=
AlgHom.ext (h.apply_eq_lift hx' g g.commutes hroot)
#align is_adjoin_root.eq_lift_hom IsAdjoinRoot.eq_liftHom
end lift
end IsAdjoinRoot
namespace AdjoinRoot
variable (f)
/-- `AdjoinRoot f` is indeed given by adjoining a root of `f`. -/
protected def isAdjoinRoot : IsAdjoinRoot (AdjoinRoot f) f where
map := AdjoinRoot.mk f
map_surjective := Ideal.Quotient.mk_surjective
ker_map := by
ext
rw [RingHom.mem_ker, ← @AdjoinRoot.mk_self _ _ f, AdjoinRoot.mk_eq_mk, Ideal.mem_span_singleton,
← dvd_add_left (dvd_refl f), sub_add_cancel]
algebraMap_eq := AdjoinRoot.algebraMap_eq f
#align adjoin_root.is_adjoin_root AdjoinRoot.isAdjoinRoot
/-- `AdjoinRoot f` is indeed given by adjoining a root of `f`. If `f` is monic this is more
powerful than `AdjoinRoot.isAdjoinRoot`. -/
protected def isAdjoinRootMonic (hf : Monic f) : IsAdjoinRootMonic (AdjoinRoot f) f :=
{ AdjoinRoot.isAdjoinRoot f with Monic := hf }
#align adjoin_root.is_adjoin_root_monic AdjoinRoot.isAdjoinRootMonic
@[simp]
theorem isAdjoinRoot_map_eq_mk : (AdjoinRoot.isAdjoinRoot f).map = AdjoinRoot.mk f :=
rfl
#align adjoin_root.is_adjoin_root_map_eq_mk AdjoinRoot.isAdjoinRoot_map_eq_mk
@[simp]
theorem isAdjoinRootMonic_map_eq_mk (hf : f.Monic) :
(AdjoinRoot.isAdjoinRootMonic f hf).map = AdjoinRoot.mk f :=
rfl
#align adjoin_root.is_adjoin_root_monic_map_eq_mk AdjoinRoot.isAdjoinRootMonic_map_eq_mk
@[simp]
theorem isAdjoinRoot_root_eq_root : (AdjoinRoot.isAdjoinRoot f).root = AdjoinRoot.root f := by
simp only [IsAdjoinRoot.root, AdjoinRoot.root, AdjoinRoot.isAdjoinRoot_map_eq_mk]
#align adjoin_root.is_adjoin_root_root_eq_root AdjoinRoot.isAdjoinRoot_root_eq_root
@[simp]
theorem isAdjoinRootMonic_root_eq_root (hf : Monic f) :
(AdjoinRoot.isAdjoinRootMonic f hf).root = AdjoinRoot.root f := by
simp only [IsAdjoinRoot.root, AdjoinRoot.root, AdjoinRoot.isAdjoinRootMonic_map_eq_mk]
#align adjoin_root.is_adjoin_root_monic_root_eq_root AdjoinRoot.isAdjoinRootMonic_root_eq_root
end AdjoinRoot
namespace IsAdjoinRootMonic
open IsAdjoinRoot
theorem map_modByMonic (h : IsAdjoinRootMonic S f) (g : R[X]) : h.map (g %ₘ f) = h.map g := by
rw [← RingHom.sub_mem_ker_iff, mem_ker_map, modByMonic_eq_sub_mul_div _ h.Monic, sub_right_comm,
sub_self, zero_sub, dvd_neg]
exact ⟨_, rfl⟩
#align is_adjoin_root_monic.map_mod_by_monic IsAdjoinRootMonic.map_modByMonic
theorem modByMonic_repr_map (h : IsAdjoinRootMonic S f) (g : R[X]) :
h.repr (h.map g) %ₘ f = g %ₘ f :=
modByMonic_eq_of_dvd_sub h.Monic <| by rw [← h.mem_ker_map, RingHom.sub_mem_ker_iff, map_repr]
#align is_adjoin_root_monic.mod_by_monic_repr_map IsAdjoinRootMonic.modByMonic_repr_map
/-- `IsAdjoinRoot.modByMonicHom` sends the equivalence class of `f` mod `g` to `f %ₘ g`. -/
def modByMonicHom (h : IsAdjoinRootMonic S f) : S →ₗ[R] R[X] where
toFun x := h.repr x %ₘ f
map_add' x y := by
conv_lhs =>
rw [← h.map_repr x, ← h.map_repr y, ← map_add]
beta_reduce -- Porting note (#12129): additional beta reduction needed
rw [h.modByMonic_repr_map, add_modByMonic]
map_smul' c x := by
rw [RingHom.id_apply, ← h.map_repr x, Algebra.smul_def, h.algebraMap_apply, ← map_mul]
dsimp only -- Porting note (#10752): added `dsimp only`
rw [h.modByMonic_repr_map, ← smul_eq_C_mul, smul_modByMonic, h.map_repr]
#align is_adjoin_root_monic.mod_by_monic_hom IsAdjoinRootMonic.modByMonicHom
@[simp]
theorem modByMonicHom_map (h : IsAdjoinRootMonic S f) (g : R[X]) :
h.modByMonicHom (h.map g) = g %ₘ f := h.modByMonic_repr_map g
#align is_adjoin_root_monic.mod_by_monic_hom_map IsAdjoinRootMonic.modByMonicHom_map
@[simp]
theorem map_modByMonicHom (h : IsAdjoinRootMonic S f) (x : S) : h.map (h.modByMonicHom x) = x := by
rw [modByMonicHom, LinearMap.coe_mk]
dsimp -- Porting note (#11227):added a `dsimp`
rw [map_modByMonic, map_repr]
#align is_adjoin_root_monic.map_mod_by_monic_hom IsAdjoinRootMonic.map_modByMonicHom
@[simp]
theorem modByMonicHom_root_pow (h : IsAdjoinRootMonic S f) {n : ℕ} (hdeg : n < natDegree f) :
h.modByMonicHom (h.root ^ n) = X ^ n := by
nontriviality R
rw [← h.map_X, ← map_pow, modByMonicHom_map, modByMonic_eq_self_iff h.Monic, degree_X_pow]
contrapose! hdeg
simpa [natDegree_le_iff_degree_le] using hdeg
#align is_adjoin_root_monic.mod_by_monic_hom_root_pow IsAdjoinRootMonic.modByMonicHom_root_pow
@[simp]
theorem modByMonicHom_root (h : IsAdjoinRootMonic S f) (hdeg : 1 < natDegree f) :
h.modByMonicHom h.root = X := by simpa using modByMonicHom_root_pow h hdeg
#align is_adjoin_root_monic.mod_by_monic_hom_root IsAdjoinRootMonic.modByMonicHom_root
/-- The basis on `S` generated by powers of `h.root`.
Auxiliary definition for `IsAdjoinRootMonic.powerBasis`. -/
def basis (h : IsAdjoinRootMonic S f) : Basis (Fin (natDegree f)) R S :=
Basis.ofRepr
{ toFun := fun x => (h.modByMonicHom x).toFinsupp.comapDomain _ Fin.val_injective.injOn
invFun := fun g => h.map (ofFinsupp (g.mapDomain _))
left_inv := fun x => by
cases subsingleton_or_nontrivial R
· haveI := h.subsingleton
exact Subsingleton.elim _ _
simp only
rw [Finsupp.mapDomain_comapDomain, Polynomial.eta, h.map_modByMonicHom x]
· exact Fin.val_injective
intro i hi
refine Set.mem_range.mpr ⟨⟨i, ?_⟩, rfl⟩
contrapose! hi
simp only [Polynomial.toFinsupp_apply, Classical.not_not, Finsupp.mem_support_iff, Ne,
modByMonicHom, LinearMap.coe_mk, Finset.mem_coe]
by_cases hx : h.toIsAdjoinRoot.repr x %ₘ f = 0
· simp [hx]
refine coeff_eq_zero_of_natDegree_lt (lt_of_lt_of_le ?_ hi)
dsimp -- Porting note (#11227):added a `dsimp`
rw [natDegree_lt_natDegree_iff hx]
exact degree_modByMonic_lt _ h.Monic
right_inv := fun g => by
nontriviality R
ext i
simp only [h.modByMonicHom_map, Finsupp.comapDomain_apply, Polynomial.toFinsupp_apply]
rw [(Polynomial.modByMonic_eq_self_iff h.Monic).mpr, Polynomial.coeff]
· dsimp only -- Porting note (#10752): added `dsimp only`
rw [Finsupp.mapDomain_apply Fin.val_injective]
rw [degree_eq_natDegree h.Monic.ne_zero, degree_lt_iff_coeff_zero]
intro m hm
rw [Polynomial.coeff]
dsimp only -- Porting note (#10752): added `dsimp only`
rw [Finsupp.mapDomain_notin_range]
rw [Set.mem_range, not_exists]
rintro i rfl
exact i.prop.not_le hm
map_add' := fun x y => by
beta_reduce -- Porting note (#12129): additional beta reduction needed
rw [map_add, toFinsupp_add, Finsupp.comapDomain_add_of_injective Fin.val_injective]
-- Porting note: the original simp proof with the same lemmas does not work
-- See https://github.com/leanprover-community/mathlib4/issues/5026
-- simp only [map_add, Finsupp.comapDomain_add_of_injective Fin.val_injective, toFinsupp_add]
map_smul' := fun c x => by
dsimp only -- Porting note (#10752): added `dsimp only`
rw [map_smul, toFinsupp_smul, Finsupp.comapDomain_smul_of_injective Fin.val_injective,
RingHom.id_apply] }
-- Porting note: the original simp proof with the same lemmas does not work
-- See https://github.com/leanprover-community/mathlib4/issues/5026
-- simp only [map_smul, Finsupp.comapDomain_smul_of_injective Fin.val_injective,
-- RingHom.id_apply, toFinsupp_smul] }
#align is_adjoin_root_monic.basis IsAdjoinRootMonic.basis
@[simp]
theorem basis_apply (h : IsAdjoinRootMonic S f) (i) : h.basis i = h.root ^ (i : ℕ) :=
Basis.apply_eq_iff.mpr <|
show (h.modByMonicHom (h.toIsAdjoinRoot.root ^ (i : ℕ))).toFinsupp.comapDomain _
Fin.val_injective.injOn = Finsupp.single _ _ by
ext j
rw [Finsupp.comapDomain_apply, modByMonicHom_root_pow]
· rw [X_pow_eq_monomial, toFinsupp_monomial, Finsupp.single_apply_left Fin.val_injective]
· exact i.is_lt
#align is_adjoin_root_monic.basis_apply IsAdjoinRootMonic.basis_apply
theorem deg_pos [Nontrivial S] (h : IsAdjoinRootMonic S f) : 0 < natDegree f := by
rcases h.basis.index_nonempty with ⟨⟨i, hi⟩⟩
exact (Nat.zero_le _).trans_lt hi
#align is_adjoin_root_monic.deg_pos IsAdjoinRootMonic.deg_pos
theorem deg_ne_zero [Nontrivial S] (h : IsAdjoinRootMonic S f) : natDegree f ≠ 0 :=
h.deg_pos.ne'
#align is_adjoin_root_monic.deg_ne_zero IsAdjoinRootMonic.deg_ne_zero
/-- If `f` is monic, the powers of `h.root` form a basis. -/
@[simps! gen dim basis]
def powerBasis (h : IsAdjoinRootMonic S f) : PowerBasis R S where
gen := h.root
dim := natDegree f
basis := h.basis
basis_eq_pow := h.basis_apply
#align is_adjoin_root_monic.power_basis IsAdjoinRootMonic.powerBasis
@[simp]
| Mathlib/RingTheory/IsAdjoinRoot.lean | 493 | 496 | theorem basis_repr (h : IsAdjoinRootMonic S f) (x : S) (i : Fin (natDegree f)) :
h.basis.repr x i = (h.modByMonicHom x).coeff (i : ℕ) := by |
change (h.modByMonicHom x).toFinsupp.comapDomain _ Fin.val_injective.injOn i = _
rw [Finsupp.comapDomain_apply, Polynomial.toFinsupp_apply]
|
/-
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.Constructions.BorelSpace.Order
#align_import measure_theory.function.simple_func from "leanprover-community/mathlib"@"bf6a01357ff5684b1ebcd0f1a13be314fc82c0bf"
/-!
# Simple functions
A function `f` from a measurable space to any type is called *simple*, if every preimage `f ⁻¹' {x}`
is measurable, and the range is finite. In this file, we define simple functions and establish their
basic properties; and we construct a sequence of simple functions approximating an arbitrary Borel
measurable function `f : α → ℝ≥0∞`.
The theorem `Measurable.ennreal_induction` shows that in order to prove something for an arbitrary
measurable function into `ℝ≥0∞`, it is sufficient to show that the property holds for (multiples of)
characteristic functions and is closed under addition and supremum of increasing sequences of
functions.
-/
noncomputable section
open Set hiding restrict restrict_apply
open Filter ENNReal
open Function (support)
open scoped Classical
open Topology NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β γ δ : Type*}
/-- A function `f` from a measurable space to any type is called *simple*,
if every preimage `f ⁻¹' {x}` is measurable, and the range is finite. This structure bundles
a function with these properties. -/
structure SimpleFunc.{u, v} (α : Type u) [MeasurableSpace α] (β : Type v) where
toFun : α → β
measurableSet_fiber' : ∀ x, MeasurableSet (toFun ⁻¹' {x})
finite_range' : (Set.range toFun).Finite
#align measure_theory.simple_func MeasureTheory.SimpleFunc
#align measure_theory.simple_func.to_fun MeasureTheory.SimpleFunc.toFun
#align measure_theory.simple_func.measurable_set_fiber' MeasureTheory.SimpleFunc.measurableSet_fiber'
#align measure_theory.simple_func.finite_range' MeasureTheory.SimpleFunc.finite_range'
local infixr:25 " →ₛ " => SimpleFunc
namespace SimpleFunc
section Measurable
variable [MeasurableSpace α]
attribute [coe] toFun
instance instCoeFun : CoeFun (α →ₛ β) fun _ => α → β :=
⟨toFun⟩
#align measure_theory.simple_func.has_coe_to_fun MeasureTheory.SimpleFunc.instCoeFun
theorem coe_injective ⦃f g : α →ₛ β⦄ (H : (f : α → β) = g) : f = g := by
cases f; cases g; congr
#align measure_theory.simple_func.coe_injective MeasureTheory.SimpleFunc.coe_injective
@[ext]
theorem ext {f g : α →ₛ β} (H : ∀ a, f a = g a) : f = g :=
coe_injective <| funext H
#align measure_theory.simple_func.ext MeasureTheory.SimpleFunc.ext
theorem finite_range (f : α →ₛ β) : (Set.range f).Finite :=
f.finite_range'
#align measure_theory.simple_func.finite_range MeasureTheory.SimpleFunc.finite_range
theorem measurableSet_fiber (f : α →ₛ β) (x : β) : MeasurableSet (f ⁻¹' {x}) :=
f.measurableSet_fiber' x
#align measure_theory.simple_func.measurable_set_fiber MeasureTheory.SimpleFunc.measurableSet_fiber
-- @[simp] -- Porting note (#10618): simp can prove this
theorem apply_mk (f : α → β) (h h') (x : α) : SimpleFunc.mk f h h' x = f x :=
rfl
#align measure_theory.simple_func.apply_mk MeasureTheory.SimpleFunc.apply_mk
/-- Simple function defined on a finite type. -/
def ofFinite [Finite α] [MeasurableSingletonClass α] (f : α → β) : α →ₛ β where
toFun := f
measurableSet_fiber' x := (toFinite (f ⁻¹' {x})).measurableSet
finite_range' := Set.finite_range f
@[deprecated (since := "2024-02-05")] alias ofFintype := ofFinite
/-- Simple function defined on the empty type. -/
def ofIsEmpty [IsEmpty α] : α →ₛ β := ofFinite isEmptyElim
#align measure_theory.simple_func.of_is_empty MeasureTheory.SimpleFunc.ofIsEmpty
/-- Range of a simple function `α →ₛ β` as a `Finset β`. -/
protected def range (f : α →ₛ β) : Finset β :=
f.finite_range.toFinset
#align measure_theory.simple_func.range MeasureTheory.SimpleFunc.range
@[simp]
theorem mem_range {f : α →ₛ β} {b} : b ∈ f.range ↔ b ∈ range f :=
Finite.mem_toFinset _
#align measure_theory.simple_func.mem_range MeasureTheory.SimpleFunc.mem_range
theorem mem_range_self (f : α →ₛ β) (x : α) : f x ∈ f.range :=
mem_range.2 ⟨x, rfl⟩
#align measure_theory.simple_func.mem_range_self MeasureTheory.SimpleFunc.mem_range_self
@[simp]
theorem coe_range (f : α →ₛ β) : (↑f.range : Set β) = Set.range f :=
f.finite_range.coe_toFinset
#align measure_theory.simple_func.coe_range MeasureTheory.SimpleFunc.coe_range
theorem mem_range_of_measure_ne_zero {f : α →ₛ β} {x : β} {μ : Measure α} (H : μ (f ⁻¹' {x}) ≠ 0) :
x ∈ f.range :=
let ⟨a, ha⟩ := nonempty_of_measure_ne_zero H
mem_range.2 ⟨a, ha⟩
#align measure_theory.simple_func.mem_range_of_measure_ne_zero MeasureTheory.SimpleFunc.mem_range_of_measure_ne_zero
theorem forall_mem_range {f : α →ₛ β} {p : β → Prop} : (∀ y ∈ f.range, p y) ↔ ∀ x, p (f x) := by
simp only [mem_range, Set.forall_mem_range]
#align measure_theory.simple_func.forall_mem_range MeasureTheory.SimpleFunc.forall_mem_range
theorem exists_range_iff {f : α →ₛ β} {p : β → Prop} : (∃ y ∈ f.range, p y) ↔ ∃ x, p (f x) := by
simpa only [mem_range, exists_prop] using Set.exists_range_iff
#align measure_theory.simple_func.exists_range_iff MeasureTheory.SimpleFunc.exists_range_iff
theorem preimage_eq_empty_iff (f : α →ₛ β) (b : β) : f ⁻¹' {b} = ∅ ↔ b ∉ f.range :=
preimage_singleton_eq_empty.trans <| not_congr mem_range.symm
#align measure_theory.simple_func.preimage_eq_empty_iff MeasureTheory.SimpleFunc.preimage_eq_empty_iff
theorem exists_forall_le [Nonempty β] [Preorder β] [IsDirected β (· ≤ ·)] (f : α →ₛ β) :
∃ C, ∀ x, f x ≤ C :=
f.range.exists_le.imp fun _ => forall_mem_range.1
#align measure_theory.simple_func.exists_forall_le MeasureTheory.SimpleFunc.exists_forall_le
/-- Constant function as a `SimpleFunc`. -/
def const (α) {β} [MeasurableSpace α] (b : β) : α →ₛ β :=
⟨fun _ => b, fun _ => MeasurableSet.const _, finite_range_const⟩
#align measure_theory.simple_func.const MeasureTheory.SimpleFunc.const
instance instInhabited [Inhabited β] : Inhabited (α →ₛ β) :=
⟨const _ default⟩
#align measure_theory.simple_func.inhabited MeasureTheory.SimpleFunc.instInhabited
theorem const_apply (a : α) (b : β) : (const α b) a = b :=
rfl
#align measure_theory.simple_func.const_apply MeasureTheory.SimpleFunc.const_apply
@[simp]
theorem coe_const (b : β) : ⇑(const α b) = Function.const α b :=
rfl
#align measure_theory.simple_func.coe_const MeasureTheory.SimpleFunc.coe_const
@[simp]
theorem range_const (α) [MeasurableSpace α] [Nonempty α] (b : β) : (const α b).range = {b} :=
Finset.coe_injective <| by simp (config := { unfoldPartialApp := true }) [Function.const]
#align measure_theory.simple_func.range_const MeasureTheory.SimpleFunc.range_const
theorem range_const_subset (α) [MeasurableSpace α] (b : β) : (const α b).range ⊆ {b} :=
Finset.coe_subset.1 <| by simp
#align measure_theory.simple_func.range_const_subset MeasureTheory.SimpleFunc.range_const_subset
theorem simpleFunc_bot {α} (f : @SimpleFunc α ⊥ β) [Nonempty β] : ∃ c, ∀ x, f x = c := by
have hf_meas := @SimpleFunc.measurableSet_fiber α _ ⊥ f
simp_rw [MeasurableSpace.measurableSet_bot_iff] at hf_meas
exact (exists_eq_const_of_preimage_singleton hf_meas).imp fun c hc ↦ congr_fun hc
#align measure_theory.simple_func.simple_func_bot MeasureTheory.SimpleFunc.simpleFunc_bot
theorem simpleFunc_bot' {α} [Nonempty β] (f : @SimpleFunc α ⊥ β) :
∃ c, f = @SimpleFunc.const α _ ⊥ c :=
letI : MeasurableSpace α := ⊥; (simpleFunc_bot f).imp fun _ ↦ ext
#align measure_theory.simple_func.simple_func_bot' MeasureTheory.SimpleFunc.simpleFunc_bot'
theorem measurableSet_cut (r : α → β → Prop) (f : α →ₛ β) (h : ∀ b, MeasurableSet { a | r a b }) :
MeasurableSet { a | r a (f a) } := by
have : { a | r a (f a) } = ⋃ b ∈ range f, { a | r a b } ∩ f ⁻¹' {b} := by
ext a
suffices r a (f a) ↔ ∃ i, r a (f i) ∧ f a = f i by simpa
exact ⟨fun h => ⟨a, ⟨h, rfl⟩⟩, fun ⟨a', ⟨h', e⟩⟩ => e.symm ▸ h'⟩
rw [this]
exact
MeasurableSet.biUnion f.finite_range.countable fun b _ =>
MeasurableSet.inter (h b) (f.measurableSet_fiber _)
#align measure_theory.simple_func.measurable_set_cut MeasureTheory.SimpleFunc.measurableSet_cut
@[measurability]
theorem measurableSet_preimage (f : α →ₛ β) (s) : MeasurableSet (f ⁻¹' s) :=
measurableSet_cut (fun _ b => b ∈ s) f fun b => MeasurableSet.const (b ∈ s)
#align measure_theory.simple_func.measurable_set_preimage MeasureTheory.SimpleFunc.measurableSet_preimage
/-- A simple function is measurable -/
@[measurability]
protected theorem measurable [MeasurableSpace β] (f : α →ₛ β) : Measurable f := fun s _ =>
measurableSet_preimage f s
#align measure_theory.simple_func.measurable MeasureTheory.SimpleFunc.measurable
@[measurability]
protected theorem aemeasurable [MeasurableSpace β] {μ : Measure α} (f : α →ₛ β) :
AEMeasurable f μ :=
f.measurable.aemeasurable
#align measure_theory.simple_func.ae_measurable MeasureTheory.SimpleFunc.aemeasurable
protected theorem sum_measure_preimage_singleton (f : α →ₛ β) {μ : Measure α} (s : Finset β) :
(∑ y ∈ s, μ (f ⁻¹' {y})) = μ (f ⁻¹' ↑s) :=
sum_measure_preimage_singleton _ fun _ _ => f.measurableSet_fiber _
#align measure_theory.simple_func.sum_measure_preimage_singleton MeasureTheory.SimpleFunc.sum_measure_preimage_singleton
theorem sum_range_measure_preimage_singleton (f : α →ₛ β) (μ : Measure α) :
(∑ y ∈ f.range, μ (f ⁻¹' {y})) = μ univ := by
rw [f.sum_measure_preimage_singleton, coe_range, preimage_range]
#align measure_theory.simple_func.sum_range_measure_preimage_singleton MeasureTheory.SimpleFunc.sum_range_measure_preimage_singleton
/-- If-then-else as a `SimpleFunc`. -/
def piecewise (s : Set α) (hs : MeasurableSet s) (f g : α →ₛ β) : α →ₛ β :=
⟨s.piecewise f g, fun _ =>
letI : MeasurableSpace β := ⊤
f.measurable.piecewise hs g.measurable trivial,
(f.finite_range.union g.finite_range).subset range_ite_subset⟩
#align measure_theory.simple_func.piecewise MeasureTheory.SimpleFunc.piecewise
@[simp]
theorem coe_piecewise {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) :
⇑(piecewise s hs f g) = s.piecewise f g :=
rfl
#align measure_theory.simple_func.coe_piecewise MeasureTheory.SimpleFunc.coe_piecewise
theorem piecewise_apply {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) (a) :
piecewise s hs f g a = if a ∈ s then f a else g a :=
rfl
#align measure_theory.simple_func.piecewise_apply MeasureTheory.SimpleFunc.piecewise_apply
@[simp]
theorem piecewise_compl {s : Set α} (hs : MeasurableSet sᶜ) (f g : α →ₛ β) :
piecewise sᶜ hs f g = piecewise s hs.of_compl g f :=
coe_injective <| by
set_option tactic.skipAssignedInstances false in
simp [hs]; convert Set.piecewise_compl s f g
#align measure_theory.simple_func.piecewise_compl MeasureTheory.SimpleFunc.piecewise_compl
@[simp]
theorem piecewise_univ (f g : α →ₛ β) : piecewise univ MeasurableSet.univ f g = f :=
coe_injective <| by
set_option tactic.skipAssignedInstances false in
simp; convert Set.piecewise_univ f g
#align measure_theory.simple_func.piecewise_univ MeasureTheory.SimpleFunc.piecewise_univ
@[simp]
theorem piecewise_empty (f g : α →ₛ β) : piecewise ∅ MeasurableSet.empty f g = g :=
coe_injective <| by
set_option tactic.skipAssignedInstances false in
simp; convert Set.piecewise_empty f g
#align measure_theory.simple_func.piecewise_empty MeasureTheory.SimpleFunc.piecewise_empty
@[simp]
theorem piecewise_same (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) :
piecewise s hs f f = f :=
coe_injective <| Set.piecewise_same _ _
theorem support_indicator [Zero β] {s : Set α} (hs : MeasurableSet s) (f : α →ₛ β) :
Function.support (f.piecewise s hs (SimpleFunc.const α 0)) = s ∩ Function.support f :=
Set.support_indicator
#align measure_theory.simple_func.support_indicator MeasureTheory.SimpleFunc.support_indicator
theorem range_indicator {s : Set α} (hs : MeasurableSet s) (hs_nonempty : s.Nonempty)
(hs_ne_univ : s ≠ univ) (x y : β) :
(piecewise s hs (const α x) (const α y)).range = {x, y} := by
simp only [← Finset.coe_inj, coe_range, coe_piecewise, range_piecewise, coe_const,
Finset.coe_insert, Finset.coe_singleton, hs_nonempty.image_const,
(nonempty_compl.2 hs_ne_univ).image_const, singleton_union, Function.const]
#align measure_theory.simple_func.range_indicator MeasureTheory.SimpleFunc.range_indicator
theorem measurable_bind [MeasurableSpace γ] (f : α →ₛ β) (g : β → α → γ)
(hg : ∀ b, Measurable (g b)) : Measurable fun a => g (f a) a := fun s hs =>
f.measurableSet_cut (fun a b => g b a ∈ s) fun b => hg b hs
#align measure_theory.simple_func.measurable_bind MeasureTheory.SimpleFunc.measurable_bind
/-- If `f : α →ₛ β` is a simple function and `g : β → α →ₛ γ` is a family of simple functions,
then `f.bind g` binds the first argument of `g` to `f`. In other words, `f.bind g a = g (f a) a`. -/
def bind (f : α →ₛ β) (g : β → α →ₛ γ) : α →ₛ γ :=
⟨fun a => g (f a) a, fun c =>
f.measurableSet_cut (fun a b => g b a = c) fun b => (g b).measurableSet_preimage {c},
(f.finite_range.biUnion fun b _ => (g b).finite_range).subset <| by
rintro _ ⟨a, rfl⟩; simp⟩
#align measure_theory.simple_func.bind MeasureTheory.SimpleFunc.bind
@[simp]
theorem bind_apply (f : α →ₛ β) (g : β → α →ₛ γ) (a) : f.bind g a = g (f a) a :=
rfl
#align measure_theory.simple_func.bind_apply MeasureTheory.SimpleFunc.bind_apply
/-- Given a function `g : β → γ` and a simple function `f : α →ₛ β`, `f.map g` return the simple
function `g ∘ f : α →ₛ γ` -/
def map (g : β → γ) (f : α →ₛ β) : α →ₛ γ :=
bind f (const α ∘ g)
#align measure_theory.simple_func.map MeasureTheory.SimpleFunc.map
theorem map_apply (g : β → γ) (f : α →ₛ β) (a) : f.map g a = g (f a) :=
rfl
#align measure_theory.simple_func.map_apply MeasureTheory.SimpleFunc.map_apply
theorem map_map (g : β → γ) (h : γ → δ) (f : α →ₛ β) : (f.map g).map h = f.map (h ∘ g) :=
rfl
#align measure_theory.simple_func.map_map MeasureTheory.SimpleFunc.map_map
@[simp]
theorem coe_map (g : β → γ) (f : α →ₛ β) : (f.map g : α → γ) = g ∘ f :=
rfl
#align measure_theory.simple_func.coe_map MeasureTheory.SimpleFunc.coe_map
@[simp]
theorem range_map [DecidableEq γ] (g : β → γ) (f : α →ₛ β) : (f.map g).range = f.range.image g :=
Finset.coe_injective <| by simp only [coe_range, coe_map, Finset.coe_image, range_comp]
#align measure_theory.simple_func.range_map MeasureTheory.SimpleFunc.range_map
@[simp]
theorem map_const (g : β → γ) (b : β) : (const α b).map g = const α (g b) :=
rfl
#align measure_theory.simple_func.map_const MeasureTheory.SimpleFunc.map_const
theorem map_preimage (f : α →ₛ β) (g : β → γ) (s : Set γ) :
f.map g ⁻¹' s = f ⁻¹' ↑(f.range.filter fun b => g b ∈ s) := by
simp only [coe_range, sep_mem_eq, coe_map, Finset.coe_filter,
← mem_preimage, inter_comm, preimage_inter_range, ← Finset.mem_coe]
exact preimage_comp
#align measure_theory.simple_func.map_preimage MeasureTheory.SimpleFunc.map_preimage
theorem map_preimage_singleton (f : α →ₛ β) (g : β → γ) (c : γ) :
f.map g ⁻¹' {c} = f ⁻¹' ↑(f.range.filter fun b => g b = c) :=
map_preimage _ _ _
#align measure_theory.simple_func.map_preimage_singleton MeasureTheory.SimpleFunc.map_preimage_singleton
/-- Composition of a `SimpleFun` and a measurable function is a `SimpleFunc`. -/
def comp [MeasurableSpace β] (f : β →ₛ γ) (g : α → β) (hgm : Measurable g) : α →ₛ γ where
toFun := f ∘ g
finite_range' := f.finite_range.subset <| Set.range_comp_subset_range _ _
measurableSet_fiber' z := hgm (f.measurableSet_fiber z)
#align measure_theory.simple_func.comp MeasureTheory.SimpleFunc.comp
@[simp]
theorem coe_comp [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) :
⇑(f.comp g hgm) = f ∘ g :=
rfl
#align measure_theory.simple_func.coe_comp MeasureTheory.SimpleFunc.coe_comp
theorem range_comp_subset_range [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) :
(f.comp g hgm).range ⊆ f.range :=
Finset.coe_subset.1 <| by simp only [coe_range, coe_comp, Set.range_comp_subset_range]
#align measure_theory.simple_func.range_comp_subset_range MeasureTheory.SimpleFunc.range_comp_subset_range
/-- Extend a `SimpleFunc` along a measurable embedding: `f₁.extend g hg f₂` is the function
`F : β →ₛ γ` such that `F ∘ g = f₁` and `F y = f₂ y` whenever `y ∉ range g`. -/
def extend [MeasurableSpace β] (f₁ : α →ₛ γ) (g : α → β) (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : β →ₛ γ where
toFun := Function.extend g f₁ f₂
finite_range' :=
(f₁.finite_range.union <| f₂.finite_range.subset (image_subset_range _ _)).subset
(range_extend_subset _ _ _)
measurableSet_fiber' := by
letI : MeasurableSpace γ := ⊤; haveI : MeasurableSingletonClass γ := ⟨fun _ => trivial⟩
exact fun x => hg.measurable_extend f₁.measurable f₂.measurable (measurableSet_singleton _)
#align measure_theory.simple_func.extend MeasureTheory.SimpleFunc.extend
@[simp]
theorem extend_apply [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) (x : α) : (f₁.extend g hg f₂) (g x) = f₁ x :=
hg.injective.extend_apply _ _ _
#align measure_theory.simple_func.extend_apply MeasureTheory.SimpleFunc.extend_apply
@[simp]
theorem extend_apply' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) {y : β} (h : ¬∃ x, g x = y) : (f₁.extend g hg f₂) y = f₂ y :=
Function.extend_apply' _ _ _ h
#align measure_theory.simple_func.extend_apply' MeasureTheory.SimpleFunc.extend_apply'
@[simp]
theorem extend_comp_eq' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : f₁.extend g hg f₂ ∘ g = f₁ :=
funext fun _ => extend_apply _ _ _ _
#align measure_theory.simple_func.extend_comp_eq' MeasureTheory.SimpleFunc.extend_comp_eq'
@[simp]
theorem extend_comp_eq [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : (f₁.extend g hg f₂).comp g hg.measurable = f₁ :=
coe_injective <| extend_comp_eq' _ hg _
#align measure_theory.simple_func.extend_comp_eq MeasureTheory.SimpleFunc.extend_comp_eq
/-- If `f` is a simple function taking values in `β → γ` and `g` is another simple function
with the same domain and codomain `β`, then `f.seq g = f a (g a)`. -/
def seq (f : α →ₛ β → γ) (g : α →ₛ β) : α →ₛ γ :=
f.bind fun f => g.map f
#align measure_theory.simple_func.seq MeasureTheory.SimpleFunc.seq
@[simp]
theorem seq_apply (f : α →ₛ β → γ) (g : α →ₛ β) (a : α) : f.seq g a = f a (g a) :=
rfl
#align measure_theory.simple_func.seq_apply MeasureTheory.SimpleFunc.seq_apply
/-- Combine two simple functions `f : α →ₛ β` and `g : α →ₛ β`
into `fun a => (f a, g a)`. -/
def pair (f : α →ₛ β) (g : α →ₛ γ) : α →ₛ β × γ :=
(f.map Prod.mk).seq g
#align measure_theory.simple_func.pair MeasureTheory.SimpleFunc.pair
@[simp]
theorem pair_apply (f : α →ₛ β) (g : α →ₛ γ) (a) : pair f g a = (f a, g a) :=
rfl
#align measure_theory.simple_func.pair_apply MeasureTheory.SimpleFunc.pair_apply
theorem pair_preimage (f : α →ₛ β) (g : α →ₛ γ) (s : Set β) (t : Set γ) :
pair f g ⁻¹' s ×ˢ t = f ⁻¹' s ∩ g ⁻¹' t :=
rfl
#align measure_theory.simple_func.pair_preimage MeasureTheory.SimpleFunc.pair_preimage
-- A special form of `pair_preimage`
theorem pair_preimage_singleton (f : α →ₛ β) (g : α →ₛ γ) (b : β) (c : γ) :
pair f g ⁻¹' {(b, c)} = f ⁻¹' {b} ∩ g ⁻¹' {c} := by
rw [← singleton_prod_singleton]
exact pair_preimage _ _ _ _
#align measure_theory.simple_func.pair_preimage_singleton MeasureTheory.SimpleFunc.pair_preimage_singleton
theorem bind_const (f : α →ₛ β) : f.bind (const α) = f := by ext; simp
#align measure_theory.simple_func.bind_const MeasureTheory.SimpleFunc.bind_const
@[to_additive]
instance instOne [One β] : One (α →ₛ β) :=
⟨const α 1⟩
#align measure_theory.simple_func.has_one MeasureTheory.SimpleFunc.instOne
#align measure_theory.simple_func.has_zero MeasureTheory.SimpleFunc.instZero
@[to_additive]
instance instMul [Mul β] : Mul (α →ₛ β) :=
⟨fun f g => (f.map (· * ·)).seq g⟩
#align measure_theory.simple_func.has_mul MeasureTheory.SimpleFunc.instMul
#align measure_theory.simple_func.has_add MeasureTheory.SimpleFunc.instAdd
@[to_additive]
instance instDiv [Div β] : Div (α →ₛ β) :=
⟨fun f g => (f.map (· / ·)).seq g⟩
#align measure_theory.simple_func.has_div MeasureTheory.SimpleFunc.instDiv
#align measure_theory.simple_func.has_sub MeasureTheory.SimpleFunc.instSub
@[to_additive]
instance instInv [Inv β] : Inv (α →ₛ β) :=
⟨fun f => f.map Inv.inv⟩
#align measure_theory.simple_func.has_inv MeasureTheory.SimpleFunc.instInv
#align measure_theory.simple_func.has_neg MeasureTheory.SimpleFunc.instNeg
instance instSup [Sup β] : Sup (α →ₛ β) :=
⟨fun f g => (f.map (· ⊔ ·)).seq g⟩
#align measure_theory.simple_func.has_sup MeasureTheory.SimpleFunc.instSup
instance instInf [Inf β] : Inf (α →ₛ β) :=
⟨fun f g => (f.map (· ⊓ ·)).seq g⟩
#align measure_theory.simple_func.has_inf MeasureTheory.SimpleFunc.instInf
instance instLE [LE β] : LE (α →ₛ β) :=
⟨fun f g => ∀ a, f a ≤ g a⟩
#align measure_theory.simple_func.has_le MeasureTheory.SimpleFunc.instLE
@[to_additive (attr := simp)]
theorem const_one [One β] : const α (1 : β) = 1 :=
rfl
#align measure_theory.simple_func.const_one MeasureTheory.SimpleFunc.const_one
#align measure_theory.simple_func.const_zero MeasureTheory.SimpleFunc.const_zero
@[to_additive (attr := simp, norm_cast)]
theorem coe_one [One β] : ⇑(1 : α →ₛ β) = 1 :=
rfl
#align measure_theory.simple_func.coe_one MeasureTheory.SimpleFunc.coe_one
#align measure_theory.simple_func.coe_zero MeasureTheory.SimpleFunc.coe_zero
@[to_additive (attr := simp, norm_cast)]
theorem coe_mul [Mul β] (f g : α →ₛ β) : ⇑(f * g) = ⇑f * ⇑g :=
rfl
#align measure_theory.simple_func.coe_mul MeasureTheory.SimpleFunc.coe_mul
#align measure_theory.simple_func.coe_add MeasureTheory.SimpleFunc.coe_add
@[to_additive (attr := simp, norm_cast)]
theorem coe_inv [Inv β] (f : α →ₛ β) : ⇑(f⁻¹) = (⇑f)⁻¹ :=
rfl
#align measure_theory.simple_func.coe_inv MeasureTheory.SimpleFunc.coe_inv
#align measure_theory.simple_func.coe_neg MeasureTheory.SimpleFunc.coe_neg
@[to_additive (attr := simp, norm_cast)]
theorem coe_div [Div β] (f g : α →ₛ β) : ⇑(f / g) = ⇑f / ⇑g :=
rfl
#align measure_theory.simple_func.coe_div MeasureTheory.SimpleFunc.coe_div
#align measure_theory.simple_func.coe_sub MeasureTheory.SimpleFunc.coe_sub
@[simp, norm_cast]
theorem coe_le [Preorder β] {f g : α →ₛ β} : (f : α → β) ≤ g ↔ f ≤ g :=
Iff.rfl
#align measure_theory.simple_func.coe_le MeasureTheory.SimpleFunc.coe_le
@[simp, norm_cast]
theorem coe_sup [Sup β] (f g : α →ₛ β) : ⇑(f ⊔ g) = ⇑f ⊔ ⇑g :=
rfl
#align measure_theory.simple_func.coe_sup MeasureTheory.SimpleFunc.coe_sup
@[simp, norm_cast]
theorem coe_inf [Inf β] (f g : α →ₛ β) : ⇑(f ⊓ g) = ⇑f ⊓ ⇑g :=
rfl
#align measure_theory.simple_func.coe_inf MeasureTheory.SimpleFunc.coe_inf
@[to_additive]
theorem mul_apply [Mul β] (f g : α →ₛ β) (a : α) : (f * g) a = f a * g a :=
rfl
#align measure_theory.simple_func.mul_apply MeasureTheory.SimpleFunc.mul_apply
#align measure_theory.simple_func.add_apply MeasureTheory.SimpleFunc.add_apply
@[to_additive]
theorem div_apply [Div β] (f g : α →ₛ β) (x : α) : (f / g) x = f x / g x :=
rfl
#align measure_theory.simple_func.div_apply MeasureTheory.SimpleFunc.div_apply
#align measure_theory.simple_func.sub_apply MeasureTheory.SimpleFunc.sub_apply
@[to_additive]
theorem inv_apply [Inv β] (f : α →ₛ β) (x : α) : f⁻¹ x = (f x)⁻¹ :=
rfl
#align measure_theory.simple_func.inv_apply MeasureTheory.SimpleFunc.inv_apply
#align measure_theory.simple_func.neg_apply MeasureTheory.SimpleFunc.neg_apply
theorem sup_apply [Sup β] (f g : α →ₛ β) (a : α) : (f ⊔ g) a = f a ⊔ g a :=
rfl
#align measure_theory.simple_func.sup_apply MeasureTheory.SimpleFunc.sup_apply
theorem inf_apply [Inf β] (f g : α →ₛ β) (a : α) : (f ⊓ g) a = f a ⊓ g a :=
rfl
#align measure_theory.simple_func.inf_apply MeasureTheory.SimpleFunc.inf_apply
@[to_additive (attr := simp)]
theorem range_one [Nonempty α] [One β] : (1 : α →ₛ β).range = {1} :=
Finset.ext fun x => by simp [eq_comm]
#align measure_theory.simple_func.range_one MeasureTheory.SimpleFunc.range_one
#align measure_theory.simple_func.range_zero MeasureTheory.SimpleFunc.range_zero
@[simp]
theorem range_eq_empty_of_isEmpty {β} [hα : IsEmpty α] (f : α →ₛ β) : f.range = ∅ := by
rw [← Finset.not_nonempty_iff_eq_empty]
by_contra h
obtain ⟨y, hy_mem⟩ := h
rw [SimpleFunc.mem_range, Set.mem_range] at hy_mem
obtain ⟨x, hxy⟩ := hy_mem
rw [isEmpty_iff] at hα
exact hα x
#align measure_theory.simple_func.range_eq_empty_of_is_empty MeasureTheory.SimpleFunc.range_eq_empty_of_isEmpty
theorem eq_zero_of_mem_range_zero [Zero β] : ∀ {y : β}, y ∈ (0 : α →ₛ β).range → y = 0 :=
@(forall_mem_range.2 fun _ => rfl)
#align measure_theory.simple_func.eq_zero_of_mem_range_zero MeasureTheory.SimpleFunc.eq_zero_of_mem_range_zero
@[to_additive]
theorem mul_eq_map₂ [Mul β] (f g : α →ₛ β) : f * g = (pair f g).map fun p : β × β => p.1 * p.2 :=
rfl
#align measure_theory.simple_func.mul_eq_map₂ MeasureTheory.SimpleFunc.mul_eq_map₂
#align measure_theory.simple_func.add_eq_map₂ MeasureTheory.SimpleFunc.add_eq_map₂
theorem sup_eq_map₂ [Sup β] (f g : α →ₛ β) : f ⊔ g = (pair f g).map fun p : β × β => p.1 ⊔ p.2 :=
rfl
#align measure_theory.simple_func.sup_eq_map₂ MeasureTheory.SimpleFunc.sup_eq_map₂
@[to_additive]
theorem const_mul_eq_map [Mul β] (f : α →ₛ β) (b : β) : const α b * f = f.map fun a => b * a :=
rfl
#align measure_theory.simple_func.const_mul_eq_map MeasureTheory.SimpleFunc.const_mul_eq_map
#align measure_theory.simple_func.const_add_eq_map MeasureTheory.SimpleFunc.const_add_eq_map
@[to_additive]
theorem map_mul [Mul β] [Mul γ] {g : β → γ} (hg : ∀ x y, g (x * y) = g x * g y) (f₁ f₂ : α →ₛ β) :
(f₁ * f₂).map g = f₁.map g * f₂.map g :=
ext fun _ => hg _ _
#align measure_theory.simple_func.map_mul MeasureTheory.SimpleFunc.map_mul
#align measure_theory.simple_func.map_add MeasureTheory.SimpleFunc.map_add
variable {K : Type*}
@[to_additive]
instance instSMul [SMul K β] : SMul K (α →ₛ β) :=
⟨fun k f => f.map (k • ·)⟩
#align measure_theory.simple_func.has_smul MeasureTheory.SimpleFunc.instSMul
@[to_additive (attr := simp)]
theorem coe_smul [SMul K β] (c : K) (f : α →ₛ β) : ⇑(c • f) = c • ⇑f :=
rfl
#align measure_theory.simple_func.coe_smul MeasureTheory.SimpleFunc.coe_smul
@[to_additive (attr := simp)]
theorem smul_apply [SMul K β] (k : K) (f : α →ₛ β) (a : α) : (k • f) a = k • f a :=
rfl
#align measure_theory.simple_func.smul_apply MeasureTheory.SimpleFunc.smul_apply
instance hasNatSMul [AddMonoid β] : SMul ℕ (α →ₛ β) := inferInstance
@[to_additive existing hasNatSMul]
instance hasNatPow [Monoid β] : Pow (α →ₛ β) ℕ :=
⟨fun f n => f.map (· ^ n)⟩
#align measure_theory.simple_func.has_nat_pow MeasureTheory.SimpleFunc.hasNatPow
@[simp]
theorem coe_pow [Monoid β] (f : α →ₛ β) (n : ℕ) : ⇑(f ^ n) = (⇑f) ^ n :=
rfl
#align measure_theory.simple_func.coe_pow MeasureTheory.SimpleFunc.coe_pow
theorem pow_apply [Monoid β] (n : ℕ) (f : α →ₛ β) (a : α) : (f ^ n) a = f a ^ n :=
rfl
#align measure_theory.simple_func.pow_apply MeasureTheory.SimpleFunc.pow_apply
instance hasIntPow [DivInvMonoid β] : Pow (α →ₛ β) ℤ :=
⟨fun f n => f.map (· ^ n)⟩
#align measure_theory.simple_func.has_int_pow MeasureTheory.SimpleFunc.hasIntPow
@[simp]
theorem coe_zpow [DivInvMonoid β] (f : α →ₛ β) (z : ℤ) : ⇑(f ^ z) = (⇑f) ^ z :=
rfl
#align measure_theory.simple_func.coe_zpow MeasureTheory.SimpleFunc.coe_zpow
theorem zpow_apply [DivInvMonoid β] (z : ℤ) (f : α →ₛ β) (a : α) : (f ^ z) a = f a ^ z :=
rfl
#align measure_theory.simple_func.zpow_apply MeasureTheory.SimpleFunc.zpow_apply
-- TODO: work out how to generate these instances with `to_additive`, which gets confused by the
-- argument order swap between `coe_smul` and `coe_pow`.
section Additive
instance instAddMonoid [AddMonoid β] : AddMonoid (α →ₛ β) :=
Function.Injective.addMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add
fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_monoid MeasureTheory.SimpleFunc.instAddMonoid
instance instAddCommMonoid [AddCommMonoid β] : AddCommMonoid (α →ₛ β) :=
Function.Injective.addCommMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add
fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_comm_monoid MeasureTheory.SimpleFunc.instAddCommMonoid
instance instAddGroup [AddGroup β] : AddGroup (α →ₛ β) :=
Function.Injective.addGroup (fun f => show α → β from f) coe_injective coe_zero coe_add coe_neg
coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_group MeasureTheory.SimpleFunc.instAddGroup
instance instAddCommGroup [AddCommGroup β] : AddCommGroup (α →ₛ β) :=
Function.Injective.addCommGroup (fun f => show α → β from f) coe_injective coe_zero coe_add
coe_neg coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_comm_group MeasureTheory.SimpleFunc.instAddCommGroup
end Additive
@[to_additive existing]
instance instMonoid [Monoid β] : Monoid (α →ₛ β) :=
Function.Injective.monoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow
#align measure_theory.simple_func.monoid MeasureTheory.SimpleFunc.instMonoid
@[to_additive existing]
instance instCommMonoid [CommMonoid β] : CommMonoid (α →ₛ β) :=
Function.Injective.commMonoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow
#align measure_theory.simple_func.comm_monoid MeasureTheory.SimpleFunc.instCommMonoid
@[to_additive existing]
instance instGroup [Group β] : Group (α →ₛ β) :=
Function.Injective.group (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv
coe_div coe_pow coe_zpow
#align measure_theory.simple_func.group MeasureTheory.SimpleFunc.instGroup
@[to_additive existing]
instance instCommGroup [CommGroup β] : CommGroup (α →ₛ β) :=
Function.Injective.commGroup (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv
coe_div coe_pow coe_zpow
#align measure_theory.simple_func.comm_group MeasureTheory.SimpleFunc.instCommGroup
instance instModule [Semiring K] [AddCommMonoid β] [Module K β] : Module K (α →ₛ β) :=
Function.Injective.module K ⟨⟨fun f => show α → β from f, coe_zero⟩, coe_add⟩
coe_injective coe_smul
#align measure_theory.simple_func.module MeasureTheory.SimpleFunc.instModule
theorem smul_eq_map [SMul K β] (k : K) (f : α →ₛ β) : k • f = f.map (k • ·) :=
rfl
#align measure_theory.simple_func.smul_eq_map MeasureTheory.SimpleFunc.smul_eq_map
instance instPreorder [Preorder β] : Preorder (α →ₛ β) :=
{ SimpleFunc.instLE with
le_refl := fun f a => le_rfl
le_trans := fun f g h hfg hgh a => le_trans (hfg _) (hgh a) }
#align measure_theory.simple_func.preorder MeasureTheory.SimpleFunc.instPreorder
instance instPartialOrder [PartialOrder β] : PartialOrder (α →ₛ β) :=
{ SimpleFunc.instPreorder with
le_antisymm := fun _f _g hfg hgf => ext fun a => le_antisymm (hfg a) (hgf a) }
#align measure_theory.simple_func.partial_order MeasureTheory.SimpleFunc.instPartialOrder
instance instOrderBot [LE β] [OrderBot β] : OrderBot (α →ₛ β) where
bot := const α ⊥
bot_le _ _ := bot_le
#align measure_theory.simple_func.order_bot MeasureTheory.SimpleFunc.instOrderBot
instance instOrderTop [LE β] [OrderTop β] : OrderTop (α →ₛ β) where
top := const α ⊤
le_top _ _ := le_top
#align measure_theory.simple_func.order_top MeasureTheory.SimpleFunc.instOrderTop
instance instSemilatticeInf [SemilatticeInf β] : SemilatticeInf (α →ₛ β) :=
{ SimpleFunc.instPartialOrder with
inf := (· ⊓ ·)
inf_le_left := fun _ _ _ => inf_le_left
inf_le_right := fun _ _ _ => inf_le_right
le_inf := fun _f _g _h hfh hgh a => le_inf (hfh a) (hgh a) }
#align measure_theory.simple_func.semilattice_inf MeasureTheory.SimpleFunc.instSemilatticeInf
instance instSemilatticeSup [SemilatticeSup β] : SemilatticeSup (α →ₛ β) :=
{ SimpleFunc.instPartialOrder with
sup := (· ⊔ ·)
le_sup_left := fun _ _ _ => le_sup_left
le_sup_right := fun _ _ _ => le_sup_right
sup_le := fun _f _g _h hfh hgh a => sup_le (hfh a) (hgh a) }
#align measure_theory.simple_func.semilattice_sup MeasureTheory.SimpleFunc.instSemilatticeSup
instance instLattice [Lattice β] : Lattice (α →ₛ β) :=
{ SimpleFunc.instSemilatticeSup, SimpleFunc.instSemilatticeInf with }
#align measure_theory.simple_func.lattice MeasureTheory.SimpleFunc.instLattice
instance instBoundedOrder [LE β] [BoundedOrder β] : BoundedOrder (α →ₛ β) :=
{ SimpleFunc.instOrderBot, SimpleFunc.instOrderTop with }
#align measure_theory.simple_func.bounded_order MeasureTheory.SimpleFunc.instBoundedOrder
theorem finset_sup_apply [SemilatticeSup β] [OrderBot β] {f : γ → α →ₛ β} (s : Finset γ) (a : α) :
s.sup f a = s.sup fun c => f c a := by
refine Finset.induction_on s rfl ?_
intro a s _ ih
rw [Finset.sup_insert, Finset.sup_insert, sup_apply, ih]
#align measure_theory.simple_func.finset_sup_apply MeasureTheory.SimpleFunc.finset_sup_apply
section Restrict
variable [Zero β]
/-- Restrict a simple function `f : α →ₛ β` to a set `s`. If `s` is measurable,
then `f.restrict s a = if a ∈ s then f a else 0`, otherwise `f.restrict s = const α 0`. -/
def restrict (f : α →ₛ β) (s : Set α) : α →ₛ β :=
if hs : MeasurableSet s then piecewise s hs f 0 else 0
#align measure_theory.simple_func.restrict MeasureTheory.SimpleFunc.restrict
theorem restrict_of_not_measurable {f : α →ₛ β} {s : Set α} (hs : ¬MeasurableSet s) :
restrict f s = 0 :=
dif_neg hs
#align measure_theory.simple_func.restrict_of_not_measurable MeasureTheory.SimpleFunc.restrict_of_not_measurable
@[simp]
theorem coe_restrict (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) :
⇑(restrict f s) = indicator s f := by
rw [restrict, dif_pos hs, coe_piecewise, coe_zero, piecewise_eq_indicator]
#align measure_theory.simple_func.coe_restrict MeasureTheory.SimpleFunc.coe_restrict
@[simp]
theorem restrict_univ (f : α →ₛ β) : restrict f univ = f := by simp [restrict]
#align measure_theory.simple_func.restrict_univ MeasureTheory.SimpleFunc.restrict_univ
@[simp]
theorem restrict_empty (f : α →ₛ β) : restrict f ∅ = 0 := by simp [restrict]
#align measure_theory.simple_func.restrict_empty MeasureTheory.SimpleFunc.restrict_empty
theorem map_restrict_of_zero [Zero γ] {g : β → γ} (hg : g 0 = 0) (f : α →ₛ β) (s : Set α) :
(f.restrict s).map g = (f.map g).restrict s :=
ext fun x =>
if hs : MeasurableSet s then by simp [hs, Set.indicator_comp_of_zero hg]
else by simp [restrict_of_not_measurable hs, hg]
#align measure_theory.simple_func.map_restrict_of_zero MeasureTheory.SimpleFunc.map_restrict_of_zero
theorem map_coe_ennreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) :
(f.restrict s).map ((↑) : ℝ≥0 → ℝ≥0∞) = (f.map (↑)).restrict s :=
map_restrict_of_zero ENNReal.coe_zero _ _
#align measure_theory.simple_func.map_coe_ennreal_restrict MeasureTheory.SimpleFunc.map_coe_ennreal_restrict
theorem map_coe_nnreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) :
(f.restrict s).map ((↑) : ℝ≥0 → ℝ) = (f.map (↑)).restrict s :=
map_restrict_of_zero NNReal.coe_zero _ _
#align measure_theory.simple_func.map_coe_nnreal_restrict MeasureTheory.SimpleFunc.map_coe_nnreal_restrict
theorem restrict_apply (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) (a) :
restrict f s a = indicator s f a := by simp only [f.coe_restrict hs]
#align measure_theory.simple_func.restrict_apply MeasureTheory.SimpleFunc.restrict_apply
theorem restrict_preimage (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {t : Set β}
(ht : (0 : β) ∉ t) : restrict f s ⁻¹' t = s ∩ f ⁻¹' t := by
simp [hs, indicator_preimage_of_not_mem _ _ ht, inter_comm]
#align measure_theory.simple_func.restrict_preimage MeasureTheory.SimpleFunc.restrict_preimage
theorem restrict_preimage_singleton (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {r : β}
(hr : r ≠ 0) : restrict f s ⁻¹' {r} = s ∩ f ⁻¹' {r} :=
f.restrict_preimage hs hr.symm
#align measure_theory.simple_func.restrict_preimage_singleton MeasureTheory.SimpleFunc.restrict_preimage_singleton
theorem mem_restrict_range {r : β} {s : Set α} {f : α →ₛ β} (hs : MeasurableSet s) :
r ∈ (restrict f s).range ↔ r = 0 ∧ s ≠ univ ∨ r ∈ f '' s := by
rw [← Finset.mem_coe, coe_range, coe_restrict _ hs, mem_range_indicator]
#align measure_theory.simple_func.mem_restrict_range MeasureTheory.SimpleFunc.mem_restrict_range
theorem mem_image_of_mem_range_restrict {r : β} {s : Set α} {f : α →ₛ β}
(hr : r ∈ (restrict f s).range) (h0 : r ≠ 0) : r ∈ f '' s :=
if hs : MeasurableSet s then by simpa [mem_restrict_range hs, h0, -mem_range] using hr
else by
rw [restrict_of_not_measurable hs] at hr
exact (h0 <| eq_zero_of_mem_range_zero hr).elim
#align measure_theory.simple_func.mem_image_of_mem_range_restrict MeasureTheory.SimpleFunc.mem_image_of_mem_range_restrict
@[mono]
theorem restrict_mono [Preorder β] (s : Set α) {f g : α →ₛ β} (H : f ≤ g) :
f.restrict s ≤ g.restrict s :=
if hs : MeasurableSet s then fun x => by
simp only [coe_restrict _ hs, indicator_le_indicator (H x)]
else by simp only [restrict_of_not_measurable hs, le_refl]
#align measure_theory.simple_func.restrict_mono MeasureTheory.SimpleFunc.restrict_mono
end Restrict
section Approx
section
variable [SemilatticeSup β] [OrderBot β] [Zero β]
/-- Fix a sequence `i : ℕ → β`. Given a function `α → β`, its `n`-th approximation
by simple functions is defined so that in case `β = ℝ≥0∞` it sends each `a` to the supremum
of the set `{i k | k ≤ n ∧ i k ≤ f a}`, see `approx_apply` and `iSup_approx_apply` for details. -/
def approx (i : ℕ → β) (f : α → β) (n : ℕ) : α →ₛ β :=
(Finset.range n).sup fun k => restrict (const α (i k)) { a : α | i k ≤ f a }
#align measure_theory.simple_func.approx MeasureTheory.SimpleFunc.approx
theorem approx_apply [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β]
[OpensMeasurableSpace β] {i : ℕ → β} {f : α → β} {n : ℕ} (a : α) (hf : Measurable f) :
(approx i f n : α →ₛ β) a = (Finset.range n).sup fun k => if i k ≤ f a then i k else 0 := by
dsimp only [approx]
rw [finset_sup_apply]
congr
funext k
rw [restrict_apply]
· simp only [coe_const, mem_setOf_eq, indicator_apply, Function.const_apply]
· exact hf measurableSet_Ici
#align measure_theory.simple_func.approx_apply MeasureTheory.SimpleFunc.approx_apply
theorem monotone_approx (i : ℕ → β) (f : α → β) : Monotone (approx i f) := fun _ _ h =>
Finset.sup_mono <| Finset.range_subset.2 h
#align measure_theory.simple_func.monotone_approx MeasureTheory.SimpleFunc.monotone_approx
theorem approx_comp [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β]
[OpensMeasurableSpace β] [MeasurableSpace γ] {i : ℕ → β} {f : γ → β} {g : α → γ} {n : ℕ} (a : α)
(hf : Measurable f) (hg : Measurable g) :
(approx i (f ∘ g) n : α →ₛ β) a = (approx i f n : γ →ₛ β) (g a) := by
rw [approx_apply _ hf, approx_apply _ (hf.comp hg), Function.comp_apply]
#align measure_theory.simple_func.approx_comp MeasureTheory.SimpleFunc.approx_comp
end
theorem iSup_approx_apply [TopologicalSpace β] [CompleteLattice β] [OrderClosedTopology β] [Zero β]
[MeasurableSpace β] [OpensMeasurableSpace β] (i : ℕ → β) (f : α → β) (a : α) (hf : Measurable f)
(h_zero : (0 : β) = ⊥) : ⨆ n, (approx i f n : α →ₛ β) a = ⨆ (k) (_ : i k ≤ f a), i k := by
refine le_antisymm (iSup_le fun n => ?_) (iSup_le fun k => iSup_le fun hk => ?_)
· rw [approx_apply a hf, h_zero]
refine Finset.sup_le fun k _ => ?_
split_ifs with h
· exact le_iSup_of_le k (le_iSup (fun _ : i k ≤ f a => i k) h)
· exact bot_le
· refine le_iSup_of_le (k + 1) ?_
rw [approx_apply a hf]
have : k ∈ Finset.range (k + 1) := Finset.mem_range.2 (Nat.lt_succ_self _)
refine le_trans (le_of_eq ?_) (Finset.le_sup this)
rw [if_pos hk]
#align measure_theory.simple_func.supr_approx_apply MeasureTheory.SimpleFunc.iSup_approx_apply
end Approx
section EApprox
/-- A sequence of `ℝ≥0∞`s such that its range is the set of non-negative rational numbers. -/
def ennrealRatEmbed (n : ℕ) : ℝ≥0∞ :=
ENNReal.ofReal ((Encodable.decode (α := ℚ) n).getD (0 : ℚ))
#align measure_theory.simple_func.ennreal_rat_embed MeasureTheory.SimpleFunc.ennrealRatEmbed
theorem ennrealRatEmbed_encode (q : ℚ) :
ennrealRatEmbed (Encodable.encode q) = Real.toNNReal q := by
rw [ennrealRatEmbed, Encodable.encodek]; rfl
#align measure_theory.simple_func.ennreal_rat_embed_encode MeasureTheory.SimpleFunc.ennrealRatEmbed_encode
/-- Approximate a function `α → ℝ≥0∞` by a sequence of simple functions. -/
def eapprox : (α → ℝ≥0∞) → ℕ → α →ₛ ℝ≥0∞ :=
approx ennrealRatEmbed
#align measure_theory.simple_func.eapprox MeasureTheory.SimpleFunc.eapprox
theorem eapprox_lt_top (f : α → ℝ≥0∞) (n : ℕ) (a : α) : eapprox f n a < ∞ := by
simp only [eapprox, approx, finset_sup_apply, Finset.mem_range, ENNReal.bot_eq_zero, restrict]
rw [Finset.sup_lt_iff (α := ℝ≥0∞) WithTop.zero_lt_top]
intro b _
split_ifs
· simp only [coe_zero, coe_piecewise, piecewise_eq_indicator, coe_const]
calc
{ a : α | ennrealRatEmbed b ≤ f a }.indicator (fun _ => ennrealRatEmbed b) a ≤
ennrealRatEmbed b :=
indicator_le_self _ _ a
_ < ⊤ := ENNReal.coe_lt_top
· exact WithTop.zero_lt_top
#align measure_theory.simple_func.eapprox_lt_top MeasureTheory.SimpleFunc.eapprox_lt_top
@[mono]
theorem monotone_eapprox (f : α → ℝ≥0∞) : Monotone (eapprox f) :=
monotone_approx _ f
#align measure_theory.simple_func.monotone_eapprox MeasureTheory.SimpleFunc.monotone_eapprox
theorem iSup_eapprox_apply (f : α → ℝ≥0∞) (hf : Measurable f) (a : α) :
⨆ n, (eapprox f n : α →ₛ ℝ≥0∞) a = f a := by
rw [eapprox, iSup_approx_apply ennrealRatEmbed f a hf rfl]
refine le_antisymm (iSup_le fun i => iSup_le fun hi => hi) (le_of_not_gt ?_)
intro h
rcases ENNReal.lt_iff_exists_rat_btwn.1 h with ⟨q, _, lt_q, q_lt⟩
have :
(Real.toNNReal q : ℝ≥0∞) ≤ ⨆ (k : ℕ) (_ : ennrealRatEmbed k ≤ f a), ennrealRatEmbed k := by
refine le_iSup_of_le (Encodable.encode q) ?_
rw [ennrealRatEmbed_encode q]
exact le_iSup_of_le (le_of_lt q_lt) le_rfl
exact lt_irrefl _ (lt_of_le_of_lt this lt_q)
#align measure_theory.simple_func.supr_eapprox_apply MeasureTheory.SimpleFunc.iSup_eapprox_apply
theorem eapprox_comp [MeasurableSpace γ] {f : γ → ℝ≥0∞} {g : α → γ} {n : ℕ} (hf : Measurable f)
(hg : Measurable g) : (eapprox (f ∘ g) n : α → ℝ≥0∞) = (eapprox f n : γ →ₛ ℝ≥0∞) ∘ g :=
funext fun a => approx_comp a hf hg
#align measure_theory.simple_func.eapprox_comp MeasureTheory.SimpleFunc.eapprox_comp
/-- Approximate a function `α → ℝ≥0∞` by a series of simple functions taking their values
in `ℝ≥0`. -/
def eapproxDiff (f : α → ℝ≥0∞) : ℕ → α →ₛ ℝ≥0
| 0 => (eapprox f 0).map ENNReal.toNNReal
| n + 1 => (eapprox f (n + 1) - eapprox f n).map ENNReal.toNNReal
#align measure_theory.simple_func.eapprox_diff MeasureTheory.SimpleFunc.eapproxDiff
theorem sum_eapproxDiff (f : α → ℝ≥0∞) (n : ℕ) (a : α) :
(∑ k ∈ Finset.range (n + 1), (eapproxDiff f k a : ℝ≥0∞)) = eapprox f n a := by
induction' n with n IH
· simp only [Nat.zero_eq, Nat.zero_add, Finset.sum_singleton, Finset.range_one]
rfl
· erw [Finset.sum_range_succ, IH, eapproxDiff, coe_map, Function.comp_apply,
coe_sub, Pi.sub_apply, ENNReal.coe_toNNReal,
add_tsub_cancel_of_le (monotone_eapprox f (Nat.le_succ _) _)]
apply (lt_of_le_of_lt _ (eapprox_lt_top f (n + 1) a)).ne
rw [tsub_le_iff_right]
exact le_self_add
#align measure_theory.simple_func.sum_eapprox_diff MeasureTheory.SimpleFunc.sum_eapproxDiff
theorem tsum_eapproxDiff (f : α → ℝ≥0∞) (hf : Measurable f) (a : α) :
(∑' n, (eapproxDiff f n a : ℝ≥0∞)) = f a := by
simp_rw [ENNReal.tsum_eq_iSup_nat' (tendsto_add_atTop_nat 1), sum_eapproxDiff,
iSup_eapprox_apply f hf a]
#align measure_theory.simple_func.tsum_eapprox_diff MeasureTheory.SimpleFunc.tsum_eapproxDiff
end EApprox
end Measurable
section Measure
variable {m : MeasurableSpace α} {μ ν : Measure α}
/-- Integral of a simple function whose codomain is `ℝ≥0∞`. -/
def lintegral {_m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (μ : Measure α) : ℝ≥0∞ :=
∑ x ∈ f.range, x * μ (f ⁻¹' {x})
#align measure_theory.simple_func.lintegral MeasureTheory.SimpleFunc.lintegral
theorem lintegral_eq_of_subset (f : α →ₛ ℝ≥0∞) {s : Finset ℝ≥0∞}
(hs : ∀ x, f x ≠ 0 → μ (f ⁻¹' {f x}) ≠ 0 → f x ∈ s) :
f.lintegral μ = ∑ x ∈ s, x * μ (f ⁻¹' {x}) := by
refine Finset.sum_bij_ne_zero (fun r _ _ => r) ?_ ?_ ?_ ?_
· simpa only [forall_mem_range, mul_ne_zero_iff, and_imp]
· intros
assumption
· intro b _ hb
refine ⟨b, ?_, hb, rfl⟩
rw [mem_range, ← preimage_singleton_nonempty]
exact nonempty_of_measure_ne_zero (mul_ne_zero_iff.1 hb).2
· intros
rfl
#align measure_theory.simple_func.lintegral_eq_of_subset MeasureTheory.SimpleFunc.lintegral_eq_of_subset
theorem lintegral_eq_of_subset' (f : α →ₛ ℝ≥0∞) {s : Finset ℝ≥0∞} (hs : f.range \ {0} ⊆ s) :
f.lintegral μ = ∑ x ∈ s, x * μ (f ⁻¹' {x}) :=
f.lintegral_eq_of_subset fun x hfx _ =>
hs <| Finset.mem_sdiff.2 ⟨f.mem_range_self x, mt Finset.mem_singleton.1 hfx⟩
#align measure_theory.simple_func.lintegral_eq_of_subset' MeasureTheory.SimpleFunc.lintegral_eq_of_subset'
/-- Calculate the integral of `(g ∘ f)`, where `g : β → ℝ≥0∞` and `f : α →ₛ β`. -/
theorem map_lintegral (g : β → ℝ≥0∞) (f : α →ₛ β) :
(f.map g).lintegral μ = ∑ x ∈ f.range, g x * μ (f ⁻¹' {x}) := by
simp only [lintegral, range_map]
refine Finset.sum_image' _ fun b hb => ?_
rcases mem_range.1 hb with ⟨a, rfl⟩
rw [map_preimage_singleton, ← f.sum_measure_preimage_singleton, Finset.mul_sum]
refine Finset.sum_congr ?_ ?_
· congr
· intro x
simp only [Finset.mem_filter]
rintro ⟨_, h⟩
rw [h]
#align measure_theory.simple_func.map_lintegral MeasureTheory.SimpleFunc.map_lintegral
theorem add_lintegral (f g : α →ₛ ℝ≥0∞) : (f + g).lintegral μ = f.lintegral μ + g.lintegral μ :=
calc
(f + g).lintegral μ =
∑ x ∈ (pair f g).range, (x.1 * μ (pair f g ⁻¹' {x}) + x.2 * μ (pair f g ⁻¹' {x})) := by
rw [add_eq_map₂, map_lintegral]; exact Finset.sum_congr rfl fun a _ => add_mul _ _ _
_ = (∑ x ∈ (pair f g).range, x.1 * μ (pair f g ⁻¹' {x})) +
∑ x ∈ (pair f g).range, x.2 * μ (pair f g ⁻¹' {x}) := by
rw [Finset.sum_add_distrib]
_ = ((pair f g).map Prod.fst).lintegral μ + ((pair f g).map Prod.snd).lintegral μ := by
rw [map_lintegral, map_lintegral]
_ = lintegral f μ + lintegral g μ := rfl
#align measure_theory.simple_func.add_lintegral MeasureTheory.SimpleFunc.add_lintegral
theorem const_mul_lintegral (f : α →ₛ ℝ≥0∞) (x : ℝ≥0∞) :
(const α x * f).lintegral μ = x * f.lintegral μ :=
calc
(f.map fun a => x * a).lintegral μ = ∑ r ∈ f.range, x * r * μ (f ⁻¹' {r}) := map_lintegral _ _
_ = x * ∑ r ∈ f.range, r * μ (f ⁻¹' {r}) := by simp_rw [Finset.mul_sum, mul_assoc]
#align measure_theory.simple_func.const_mul_lintegral MeasureTheory.SimpleFunc.const_mul_lintegral
/-- Integral of a simple function `α →ₛ ℝ≥0∞` as a bilinear map. -/
def lintegralₗ {m : MeasurableSpace α} : (α →ₛ ℝ≥0∞) →ₗ[ℝ≥0∞] Measure α →ₗ[ℝ≥0∞] ℝ≥0∞ where
toFun f :=
{ toFun := lintegral f
map_add' := by simp [lintegral, mul_add, Finset.sum_add_distrib]
map_smul' := fun c μ => by
simp [lintegral, mul_left_comm _ c, Finset.mul_sum, Measure.smul_apply c] }
map_add' f g := LinearMap.ext fun μ => add_lintegral f g
map_smul' c f := LinearMap.ext fun μ => const_mul_lintegral f c
#align measure_theory.simple_func.lintegralₗ MeasureTheory.SimpleFunc.lintegralₗ
@[simp]
theorem zero_lintegral : (0 : α →ₛ ℝ≥0∞).lintegral μ = 0 :=
LinearMap.ext_iff.1 lintegralₗ.map_zero μ
#align measure_theory.simple_func.zero_lintegral MeasureTheory.SimpleFunc.zero_lintegral
theorem lintegral_add {ν} (f : α →ₛ ℝ≥0∞) : f.lintegral (μ + ν) = f.lintegral μ + f.lintegral ν :=
(lintegralₗ f).map_add μ ν
#align measure_theory.simple_func.lintegral_add MeasureTheory.SimpleFunc.lintegral_add
theorem lintegral_smul (f : α →ₛ ℝ≥0∞) (c : ℝ≥0∞) : f.lintegral (c • μ) = c • f.lintegral μ :=
(lintegralₗ f).map_smul c μ
#align measure_theory.simple_func.lintegral_smul MeasureTheory.SimpleFunc.lintegral_smul
@[simp]
theorem lintegral_zero [MeasurableSpace α] (f : α →ₛ ℝ≥0∞) : f.lintegral 0 = 0 :=
(lintegralₗ f).map_zero
#align measure_theory.simple_func.lintegral_zero MeasureTheory.SimpleFunc.lintegral_zero
theorem lintegral_sum {m : MeasurableSpace α} {ι} (f : α →ₛ ℝ≥0∞) (μ : ι → Measure α) :
f.lintegral (Measure.sum μ) = ∑' i, f.lintegral (μ i) := by
simp only [lintegral, Measure.sum_apply, f.measurableSet_preimage, ← Finset.tsum_subtype, ←
ENNReal.tsum_mul_left]
apply ENNReal.tsum_comm
#align measure_theory.simple_func.lintegral_sum MeasureTheory.SimpleFunc.lintegral_sum
theorem restrict_lintegral (f : α →ₛ ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
(restrict f s).lintegral μ = ∑ r ∈ f.range, r * μ (f ⁻¹' {r} ∩ s) :=
calc
(restrict f s).lintegral μ = ∑ r ∈ f.range, r * μ (restrict f s ⁻¹' {r}) :=
lintegral_eq_of_subset _ fun x hx =>
if hxs : x ∈ s then fun _ => by
simp only [f.restrict_apply hs, indicator_of_mem hxs, mem_range_self]
else False.elim <| hx <| by simp [*]
_ = ∑ r ∈ f.range, r * μ (f ⁻¹' {r} ∩ s) :=
Finset.sum_congr rfl <|
forall_mem_range.2 fun b =>
if hb : f b = 0 then by simp only [hb, zero_mul]
else by rw [restrict_preimage_singleton _ hs hb, inter_comm]
#align measure_theory.simple_func.restrict_lintegral MeasureTheory.SimpleFunc.restrict_lintegral
theorem lintegral_restrict {m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (s : Set α) (μ : Measure α) :
f.lintegral (μ.restrict s) = ∑ y ∈ f.range, y * μ (f ⁻¹' {y} ∩ s) := by
simp only [lintegral, Measure.restrict_apply, f.measurableSet_preimage]
#align measure_theory.simple_func.lintegral_restrict MeasureTheory.SimpleFunc.lintegral_restrict
theorem restrict_lintegral_eq_lintegral_restrict (f : α →ₛ ℝ≥0∞) {s : Set α}
(hs : MeasurableSet s) : (restrict f s).lintegral μ = f.lintegral (μ.restrict s) := by
rw [f.restrict_lintegral hs, lintegral_restrict]
#align measure_theory.simple_func.restrict_lintegral_eq_lintegral_restrict MeasureTheory.SimpleFunc.restrict_lintegral_eq_lintegral_restrict
theorem const_lintegral (c : ℝ≥0∞) : (const α c).lintegral μ = c * μ univ := by
rw [lintegral]
cases isEmpty_or_nonempty α
· simp [μ.eq_zero_of_isEmpty]
· simp; unfold Function.const; rw [preimage_const_of_mem (mem_singleton c)]
#align measure_theory.simple_func.const_lintegral MeasureTheory.SimpleFunc.const_lintegral
theorem const_lintegral_restrict (c : ℝ≥0∞) (s : Set α) :
(const α c).lintegral (μ.restrict s) = c * μ s := by
rw [const_lintegral, Measure.restrict_apply MeasurableSet.univ, univ_inter]
#align measure_theory.simple_func.const_lintegral_restrict MeasureTheory.SimpleFunc.const_lintegral_restrict
theorem restrict_const_lintegral (c : ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
((const α c).restrict s).lintegral μ = c * μ s := by
rw [restrict_lintegral_eq_lintegral_restrict _ hs, const_lintegral_restrict]
#align measure_theory.simple_func.restrict_const_lintegral MeasureTheory.SimpleFunc.restrict_const_lintegral
theorem le_sup_lintegral (f g : α →ₛ ℝ≥0∞) : f.lintegral μ ⊔ g.lintegral μ ≤ (f ⊔ g).lintegral μ :=
calc
f.lintegral μ ⊔ g.lintegral μ =
((pair f g).map Prod.fst).lintegral μ ⊔ ((pair f g).map Prod.snd).lintegral μ :=
rfl
_ ≤ ∑ x ∈ (pair f g).range, (x.1 ⊔ x.2) * μ (pair f g ⁻¹' {x}) := by
rw [map_lintegral, map_lintegral]
refine sup_le ?_ ?_ <;> refine Finset.sum_le_sum fun a _ => mul_le_mul_right' ?_ _
· exact le_sup_left
· exact le_sup_right
_ = (f ⊔ g).lintegral μ := by rw [sup_eq_map₂, map_lintegral]
#align measure_theory.simple_func.le_sup_lintegral MeasureTheory.SimpleFunc.le_sup_lintegral
/-- `SimpleFunc.lintegral` is monotone both in function and in measure. -/
@[mono]
theorem lintegral_mono {f g : α →ₛ ℝ≥0∞} (hfg : f ≤ g) (hμν : μ ≤ ν) :
f.lintegral μ ≤ g.lintegral ν :=
calc
f.lintegral μ ≤ f.lintegral μ ⊔ g.lintegral μ := le_sup_left
_ ≤ (f ⊔ g).lintegral μ := le_sup_lintegral _ _
_ = g.lintegral μ := by rw [sup_of_le_right hfg]
_ ≤ g.lintegral ν := Finset.sum_le_sum fun y _ => ENNReal.mul_left_mono <| hμν _
#align measure_theory.simple_func.lintegral_mono MeasureTheory.SimpleFunc.lintegral_mono
/-- `SimpleFunc.lintegral` depends only on the measures of `f ⁻¹' {y}`. -/
theorem lintegral_eq_of_measure_preimage [MeasurableSpace β] {f : α →ₛ ℝ≥0∞} {g : β →ₛ ℝ≥0∞}
{ν : Measure β} (H : ∀ y, μ (f ⁻¹' {y}) = ν (g ⁻¹' {y})) : f.lintegral μ = g.lintegral ν := by
simp only [lintegral, ← H]
apply lintegral_eq_of_subset
simp only [H]
intros
exact mem_range_of_measure_ne_zero ‹_›
#align measure_theory.simple_func.lintegral_eq_of_measure_preimage MeasureTheory.SimpleFunc.lintegral_eq_of_measure_preimage
/-- If two simple functions are equal a.e., then their `lintegral`s are equal. -/
theorem lintegral_congr {f g : α →ₛ ℝ≥0∞} (h : f =ᵐ[μ] g) : f.lintegral μ = g.lintegral μ :=
lintegral_eq_of_measure_preimage fun y =>
measure_congr <| Eventually.set_eq <| h.mono fun x hx => by simp [hx]
#align measure_theory.simple_func.lintegral_congr MeasureTheory.SimpleFunc.lintegral_congr
theorem lintegral_map' {β} [MeasurableSpace β] {μ' : Measure β} (f : α →ₛ ℝ≥0∞) (g : β →ₛ ℝ≥0∞)
(m' : α → β) (eq : ∀ a, f a = g (m' a)) (h : ∀ s, MeasurableSet s → μ' s = μ (m' ⁻¹' s)) :
f.lintegral μ = g.lintegral μ' :=
lintegral_eq_of_measure_preimage fun y => by
simp only [preimage, eq]
exact (h (g ⁻¹' {y}) (g.measurableSet_preimage _)).symm
#align measure_theory.simple_func.lintegral_map' MeasureTheory.SimpleFunc.lintegral_map'
theorem lintegral_map {β} [MeasurableSpace β] (g : β →ₛ ℝ≥0∞) {f : α → β} (hf : Measurable f) :
g.lintegral (Measure.map f μ) = (g.comp f hf).lintegral μ :=
Eq.symm <| lintegral_map' _ _ f (fun _ => rfl) fun _s hs => Measure.map_apply hf hs
#align measure_theory.simple_func.lintegral_map MeasureTheory.SimpleFunc.lintegral_map
end Measure
section FinMeasSupp
open Finset Function
theorem support_eq [MeasurableSpace α] [Zero β] (f : α →ₛ β) :
support f = ⋃ y ∈ f.range.filter fun y => y ≠ 0, f ⁻¹' {y} :=
Set.ext fun x => by
simp only [mem_support, Set.mem_preimage, mem_filter, mem_range_self, true_and_iff, exists_prop,
mem_iUnion, Set.mem_range, mem_singleton_iff, exists_eq_right']
#align measure_theory.simple_func.support_eq MeasureTheory.SimpleFunc.support_eq
variable {m : MeasurableSpace α} [Zero β] [Zero γ] {μ : Measure α} {f : α →ₛ β}
theorem measurableSet_support [MeasurableSpace α] (f : α →ₛ β) : MeasurableSet (support f) := by
rw [f.support_eq]
exact Finset.measurableSet_biUnion _ fun y _ => measurableSet_fiber _ _
#align measure_theory.simple_func.measurable_set_support MeasureTheory.SimpleFunc.measurableSet_support
/-- A `SimpleFunc` has finite measure support if it is equal to `0` outside of a set of finite
measure. -/
protected def FinMeasSupp {_m : MeasurableSpace α} (f : α →ₛ β) (μ : Measure α) : Prop :=
f =ᶠ[μ.cofinite] 0
#align measure_theory.simple_func.fin_meas_supp MeasureTheory.SimpleFunc.FinMeasSupp
theorem finMeasSupp_iff_support : f.FinMeasSupp μ ↔ μ (support f) < ∞ :=
Iff.rfl
#align measure_theory.simple_func.fin_meas_supp_iff_support MeasureTheory.SimpleFunc.finMeasSupp_iff_support
theorem finMeasSupp_iff : f.FinMeasSupp μ ↔ ∀ y, y ≠ 0 → μ (f ⁻¹' {y}) < ∞ := by
constructor
· refine fun h y hy => lt_of_le_of_lt (measure_mono ?_) h
exact fun x hx (H : f x = 0) => hy <| H ▸ Eq.symm hx
· intro H
rw [finMeasSupp_iff_support, support_eq]
refine lt_of_le_of_lt (measure_biUnion_finset_le _ _) (sum_lt_top ?_)
exact fun y hy => (H y (Finset.mem_filter.1 hy).2).ne
#align measure_theory.simple_func.fin_meas_supp_iff MeasureTheory.SimpleFunc.finMeasSupp_iff
namespace FinMeasSupp
theorem meas_preimage_singleton_ne_zero (h : f.FinMeasSupp μ) {y : β} (hy : y ≠ 0) :
μ (f ⁻¹' {y}) < ∞ :=
finMeasSupp_iff.1 h y hy
#align measure_theory.simple_func.fin_meas_supp.meas_preimage_singleton_ne_zero MeasureTheory.SimpleFunc.FinMeasSupp.meas_preimage_singleton_ne_zero
protected theorem map {g : β → γ} (hf : f.FinMeasSupp μ) (hg : g 0 = 0) : (f.map g).FinMeasSupp μ :=
flip lt_of_le_of_lt hf (measure_mono <| support_comp_subset hg f)
#align measure_theory.simple_func.fin_meas_supp.map MeasureTheory.SimpleFunc.FinMeasSupp.map
theorem of_map {g : β → γ} (h : (f.map g).FinMeasSupp μ) (hg : ∀ b, g b = 0 → b = 0) :
f.FinMeasSupp μ :=
flip lt_of_le_of_lt h <| measure_mono <| support_subset_comp @(hg) _
#align measure_theory.simple_func.fin_meas_supp.of_map MeasureTheory.SimpleFunc.FinMeasSupp.of_map
theorem map_iff {g : β → γ} (hg : ∀ {b}, g b = 0 ↔ b = 0) :
(f.map g).FinMeasSupp μ ↔ f.FinMeasSupp μ :=
⟨fun h => h.of_map fun _ => hg.1, fun h => h.map <| hg.2 rfl⟩
#align measure_theory.simple_func.fin_meas_supp.map_iff MeasureTheory.SimpleFunc.FinMeasSupp.map_iff
protected theorem pair {g : α →ₛ γ} (hf : f.FinMeasSupp μ) (hg : g.FinMeasSupp μ) :
(pair f g).FinMeasSupp μ :=
calc
μ (support <| pair f g) = μ (support f ∪ support g) := congr_arg μ <| support_prod_mk f g
_ ≤ μ (support f) + μ (support g) := measure_union_le _ _
_ < _ := add_lt_top.2 ⟨hf, hg⟩
#align measure_theory.simple_func.fin_meas_supp.pair MeasureTheory.SimpleFunc.FinMeasSupp.pair
protected theorem map₂ [Zero δ] (hf : f.FinMeasSupp μ) {g : α →ₛ γ} (hg : g.FinMeasSupp μ)
{op : β → γ → δ} (H : op 0 0 = 0) : ((pair f g).map (Function.uncurry op)).FinMeasSupp μ :=
(hf.pair hg).map H
#align measure_theory.simple_func.fin_meas_supp.map₂ MeasureTheory.SimpleFunc.FinMeasSupp.map₂
protected theorem add {β} [AddMonoid β] {f g : α →ₛ β} (hf : f.FinMeasSupp μ)
(hg : g.FinMeasSupp μ) : (f + g).FinMeasSupp μ := by
rw [add_eq_map₂]
exact hf.map₂ hg (zero_add 0)
#align measure_theory.simple_func.fin_meas_supp.add MeasureTheory.SimpleFunc.FinMeasSupp.add
protected theorem mul {β} [MonoidWithZero β] {f g : α →ₛ β} (hf : f.FinMeasSupp μ)
(hg : g.FinMeasSupp μ) : (f * g).FinMeasSupp μ := by
rw [mul_eq_map₂]
exact hf.map₂ hg (zero_mul 0)
#align measure_theory.simple_func.fin_meas_supp.mul MeasureTheory.SimpleFunc.FinMeasSupp.mul
theorem lintegral_lt_top {f : α →ₛ ℝ≥0∞} (hm : f.FinMeasSupp μ) (hf : ∀ᵐ a ∂μ, f a ≠ ∞) :
f.lintegral μ < ∞ := by
refine sum_lt_top fun a ha => ?_
rcases eq_or_ne a ∞ with (rfl | ha)
· simp only [ae_iff, Ne, Classical.not_not] at hf
simp [Set.preimage, hf]
· by_cases ha0 : a = 0
· subst a
rwa [zero_mul]
· exact mul_ne_top ha (finMeasSupp_iff.1 hm _ ha0).ne
#align measure_theory.simple_func.fin_meas_supp.lintegral_lt_top MeasureTheory.SimpleFunc.FinMeasSupp.lintegral_lt_top
theorem of_lintegral_ne_top {f : α →ₛ ℝ≥0∞} (h : f.lintegral μ ≠ ∞) : f.FinMeasSupp μ := by
refine finMeasSupp_iff.2 fun b hb => ?_
rw [f.lintegral_eq_of_subset' (Finset.subset_insert b _)] at h
refine ENNReal.lt_top_of_mul_ne_top_right ?_ hb
exact (lt_top_of_sum_ne_top h (Finset.mem_insert_self _ _)).ne
#align measure_theory.simple_func.fin_meas_supp.of_lintegral_ne_top MeasureTheory.SimpleFunc.FinMeasSupp.of_lintegral_ne_top
theorem iff_lintegral_lt_top {f : α →ₛ ℝ≥0∞} (hf : ∀ᵐ a ∂μ, f a ≠ ∞) :
f.FinMeasSupp μ ↔ f.lintegral μ < ∞ :=
⟨fun h => h.lintegral_lt_top hf, fun h => of_lintegral_ne_top h.ne⟩
#align measure_theory.simple_func.fin_meas_supp.iff_lintegral_lt_top MeasureTheory.SimpleFunc.FinMeasSupp.iff_lintegral_lt_top
end FinMeasSupp
end FinMeasSupp
/-- To prove something for an arbitrary simple function, it suffices to show
that the property holds for (multiples of) characteristic functions and is closed under
addition (of functions with disjoint support).
It is possible to make the hypotheses in `h_add` a bit stronger, and such conditions can be added
once we need them (for example it is only necessary to consider the case where `g` is a multiple
of a characteristic function, and that this multiple doesn't appear in the image of `f`) -/
@[elab_as_elim]
protected theorem induction {α γ} [MeasurableSpace α] [AddMonoid γ] {P : SimpleFunc α γ → Prop}
(h_ind :
∀ (c) {s} (hs : MeasurableSet s),
P (SimpleFunc.piecewise s hs (SimpleFunc.const _ c) (SimpleFunc.const _ 0)))
(h_add : ∀ ⦃f g : SimpleFunc α γ⦄, Disjoint (support f) (support g) → P f → P g → P (f + g))
(f : SimpleFunc α γ) : P f := by
generalize h : f.range \ {0} = s
rw [← Finset.coe_inj, Finset.coe_sdiff, Finset.coe_singleton, SimpleFunc.coe_range] at h
induction s using Finset.induction generalizing f with
| empty =>
rw [Finset.coe_empty, diff_eq_empty, range_subset_singleton] at h
convert h_ind 0 MeasurableSet.univ
ext x
simp [h]
| @insert x s hxs ih =>
have mx := f.measurableSet_preimage {x}
let g := SimpleFunc.piecewise (f ⁻¹' {x}) mx 0 f
have Pg : P g := by
apply ih
simp only [g, SimpleFunc.coe_piecewise, range_piecewise]
rw [image_compl_preimage, union_diff_distrib, diff_diff_comm, h, Finset.coe_insert,
insert_diff_self_of_not_mem, diff_eq_empty.mpr, Set.empty_union]
· rw [Set.image_subset_iff]
convert Set.subset_univ _
exact preimage_const_of_mem (mem_singleton _)
· rwa [Finset.mem_coe]
convert h_add _ Pg (h_ind x mx)
· ext1 y
by_cases hy : y ∈ f ⁻¹' {x}
· simpa [g, piecewise_eq_of_mem _ _ _ hy, -piecewise_eq_indicator]
· simp [g, piecewise_eq_of_not_mem _ _ _ hy, -piecewise_eq_indicator]
rw [disjoint_iff_inf_le]
rintro y
by_cases hy : y ∈ f ⁻¹' {x}
· simp [g, piecewise_eq_of_mem _ _ _ hy, -piecewise_eq_indicator]
· simp [piecewise_eq_of_not_mem _ _ _ hy, -piecewise_eq_indicator]
#align measure_theory.simple_func.induction MeasureTheory.SimpleFunc.induction
/-- In a topological vector space, the addition of a measurable function and a simple function is
measurable. -/
theorem _root_.Measurable.add_simpleFunc
{E : Type*} {_ : MeasurableSpace α} [MeasurableSpace E] [AddGroup E] [MeasurableAdd E]
{g : α → E} (hg : Measurable g) (f : SimpleFunc α E) :
Measurable (g + (f : α → E)) := by
classical
induction' f using SimpleFunc.induction with c s hs f f' hff' hf hf'
· simp only [SimpleFunc.const_zero, SimpleFunc.coe_piecewise, SimpleFunc.coe_const,
SimpleFunc.coe_zero]
change Measurable (g + s.piecewise (Function.const α c) (0 : α → E))
rw [← s.piecewise_same g, ← piecewise_add]
exact Measurable.piecewise hs (hg.add_const _) (hg.add_const _)
· have : (g + ↑(f + f'))
= (Function.support f).piecewise (g + (f : α → E)) (g + f') := by
ext x
by_cases hx : x ∈ Function.support f
· simpa only [SimpleFunc.coe_add, Pi.add_apply, Function.mem_support, ne_eq, not_not,
Set.piecewise_eq_of_mem _ _ _ hx, _root_.add_right_inj, add_right_eq_self]
using Set.disjoint_left.1 hff' hx
· simpa only [SimpleFunc.coe_add, Pi.add_apply, Function.mem_support, ne_eq, not_not,
Set.piecewise_eq_of_not_mem _ _ _ hx, _root_.add_right_inj, add_left_eq_self] using hx
rw [this]
exact Measurable.piecewise f.measurableSet_support hf hf'
/-- In a topological vector space, the addition of a simple function and a measurable function is
measurable. -/
| Mathlib/MeasureTheory/Function/SimpleFunc.lean | 1,343 | 1,364 | theorem _root_.Measurable.simpleFunc_add
{E : Type*} {_ : MeasurableSpace α} [MeasurableSpace E] [AddGroup E] [MeasurableAdd E]
{g : α → E} (hg : Measurable g) (f : SimpleFunc α E) :
Measurable ((f : α → E) + g) := by |
classical
induction' f using SimpleFunc.induction with c s hs f f' hff' hf hf'
· simp only [SimpleFunc.const_zero, SimpleFunc.coe_piecewise, SimpleFunc.coe_const,
SimpleFunc.coe_zero]
change Measurable (s.piecewise (Function.const α c) (0 : α → E) + g)
rw [← s.piecewise_same g, ← piecewise_add]
exact Measurable.piecewise hs (hg.const_add _) (hg.const_add _)
· have : (↑(f + f') + g)
= (Function.support f).piecewise ((f : α → E) + g) (f' + g) := by
ext x
by_cases hx : x ∈ Function.support f
· simpa only [coe_add, Pi.add_apply, Function.mem_support, ne_eq, not_not,
Set.piecewise_eq_of_mem _ _ _ hx, _root_.add_left_inj, add_right_eq_self]
using Set.disjoint_left.1 hff' hx
· simpa only [SimpleFunc.coe_add, Pi.add_apply, Function.mem_support, ne_eq, not_not,
Set.piecewise_eq_of_not_mem _ _ _ hx, _root_.add_left_inj, add_left_eq_self] using hx
rw [this]
exact Measurable.piecewise f.measurableSet_support hf hf'
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Scott Morrison
-/
import Mathlib.Algebra.Group.Indicator
import Mathlib.Algebra.Group.Submonoid.Basic
import Mathlib.Data.Set.Finite
#align_import data.finsupp.defs from "leanprover-community/mathlib"@"842328d9df7e96fd90fc424e115679c15fb23a71"
/-!
# Type of functions with finite support
For any type `α` and any type `M` with zero, we define the type `Finsupp α M` (notation: `α →₀ M`)
of finitely supported functions from `α` to `M`, i.e. the functions which are zero everywhere
on `α` except on a finite set.
Functions with finite support are used (at least) in the following parts of the library:
* `MonoidAlgebra R M` and `AddMonoidAlgebra R M` are defined as `M →₀ R`;
* polynomials and multivariate polynomials are defined as `AddMonoidAlgebra`s, hence they use
`Finsupp` under the hood;
* the linear combination of a family of vectors `v i` with coefficients `f i` (as used, e.g., to
define linearly independent family `LinearIndependent`) is defined as a map
`Finsupp.total : (ι → M) → (ι →₀ R) →ₗ[R] M`.
Some other constructions are naturally equivalent to `α →₀ M` with some `α` and `M` but are defined
in a different way in the library:
* `Multiset α ≃+ α →₀ ℕ`;
* `FreeAbelianGroup α ≃+ α →₀ ℤ`.
Most of the theory assumes that the range is a commutative additive monoid. This gives us the big
sum operator as a powerful way to construct `Finsupp` elements, which is defined in
`Algebra/BigOperators/Finsupp`.
-- Porting note: the semireducibility remark no longer applies in Lean 4, afaict.
Many constructions based on `α →₀ M` use `semireducible` type tags to avoid reusing unwanted type
instances. E.g., `MonoidAlgebra`, `AddMonoidAlgebra`, and types based on these two have
non-pointwise multiplication.
## Main declarations
* `Finsupp`: The type of finitely supported functions from `α` to `β`.
* `Finsupp.single`: The `Finsupp` which is nonzero in exactly one point.
* `Finsupp.update`: Changes one value of a `Finsupp`.
* `Finsupp.erase`: Replaces one value of a `Finsupp` by `0`.
* `Finsupp.onFinset`: The restriction of a function to a `Finset` as a `Finsupp`.
* `Finsupp.mapRange`: Composition of a `ZeroHom` with a `Finsupp`.
* `Finsupp.embDomain`: Maps the domain of a `Finsupp` by an embedding.
* `Finsupp.zipWith`: Postcomposition of two `Finsupp`s with a function `f` such that `f 0 0 = 0`.
## Notations
This file adds `α →₀ M` as a global notation for `Finsupp α M`.
We also use the following convention for `Type*` variables in this file
* `α`, `β`, `γ`: types with no additional structure that appear as the first argument to `Finsupp`
somewhere in the statement;
* `ι` : an auxiliary index type;
* `M`, `M'`, `N`, `P`: types with `Zero` or `(Add)(Comm)Monoid` structure; `M` is also used
for a (semi)module over a (semi)ring.
* `G`, `H`: groups (commutative or not, multiplicative or additive);
* `R`, `S`: (semi)rings.
## Implementation notes
This file is a `noncomputable theory` and uses classical logic throughout.
## TODO
* Expand the list of definitions and important lemmas to the module docstring.
-/
noncomputable section
open Finset Function
variable {α β γ ι M M' N P G H R S : Type*}
/-- `Finsupp α M`, denoted `α →₀ M`, is the type of functions `f : α → M` such that
`f x = 0` for all but finitely many `x`. -/
structure Finsupp (α : Type*) (M : Type*) [Zero M] where
/-- The support of a finitely supported function (aka `Finsupp`). -/
support : Finset α
/-- The underlying function of a bundled finitely supported function (aka `Finsupp`). -/
toFun : α → M
/-- The witness that the support of a `Finsupp` is indeed the exact locus where its
underlying function is nonzero. -/
mem_support_toFun : ∀ a, a ∈ support ↔ toFun a ≠ 0
#align finsupp Finsupp
#align finsupp.support Finsupp.support
#align finsupp.to_fun Finsupp.toFun
#align finsupp.mem_support_to_fun Finsupp.mem_support_toFun
@[inherit_doc]
infixr:25 " →₀ " => Finsupp
namespace Finsupp
/-! ### Basic declarations about `Finsupp` -/
section Basic
variable [Zero M]
instance instFunLike : FunLike (α →₀ M) α M :=
⟨toFun, by
rintro ⟨s, f, hf⟩ ⟨t, g, hg⟩ (rfl : f = g)
congr
ext a
exact (hf _).trans (hg _).symm⟩
#align finsupp.fun_like Finsupp.instFunLike
/-- Helper instance for when there are too many metavariables to apply the `DFunLike` instance
directly. -/
instance instCoeFun : CoeFun (α →₀ M) fun _ => α → M :=
inferInstance
#align finsupp.has_coe_to_fun Finsupp.instCoeFun
@[ext]
theorem ext {f g : α →₀ M} (h : ∀ a, f a = g a) : f = g :=
DFunLike.ext _ _ h
#align finsupp.ext Finsupp.ext
#align finsupp.ext_iff DFunLike.ext_iff
lemma ne_iff {f g : α →₀ M} : f ≠ g ↔ ∃ a, f a ≠ g a := DFunLike.ne_iff
#align finsupp.coe_fn_inj DFunLike.coe_fn_eq
#align finsupp.coe_fn_injective DFunLike.coe_injective
#align finsupp.congr_fun DFunLike.congr_fun
@[simp, norm_cast]
theorem coe_mk (f : α → M) (s : Finset α) (h : ∀ a, a ∈ s ↔ f a ≠ 0) : ⇑(⟨s, f, h⟩ : α →₀ M) = f :=
rfl
#align finsupp.coe_mk Finsupp.coe_mk
instance instZero : Zero (α →₀ M) :=
⟨⟨∅, 0, fun _ => ⟨fun h ↦ (not_mem_empty _ h).elim, fun H => (H rfl).elim⟩⟩⟩
#align finsupp.has_zero Finsupp.instZero
@[simp, norm_cast] lemma coe_zero : ⇑(0 : α →₀ M) = 0 := rfl
#align finsupp.coe_zero Finsupp.coe_zero
theorem zero_apply {a : α} : (0 : α →₀ M) a = 0 :=
rfl
#align finsupp.zero_apply Finsupp.zero_apply
@[simp]
theorem support_zero : (0 : α →₀ M).support = ∅ :=
rfl
#align finsupp.support_zero Finsupp.support_zero
instance instInhabited : Inhabited (α →₀ M) :=
⟨0⟩
#align finsupp.inhabited Finsupp.instInhabited
@[simp]
theorem mem_support_iff {f : α →₀ M} : ∀ {a : α}, a ∈ f.support ↔ f a ≠ 0 :=
@(f.mem_support_toFun)
#align finsupp.mem_support_iff Finsupp.mem_support_iff
@[simp, norm_cast]
theorem fun_support_eq (f : α →₀ M) : Function.support f = f.support :=
Set.ext fun _x => mem_support_iff.symm
#align finsupp.fun_support_eq Finsupp.fun_support_eq
theorem not_mem_support_iff {f : α →₀ M} {a} : a ∉ f.support ↔ f a = 0 :=
not_iff_comm.1 mem_support_iff.symm
#align finsupp.not_mem_support_iff Finsupp.not_mem_support_iff
@[simp, norm_cast]
theorem coe_eq_zero {f : α →₀ M} : (f : α → M) = 0 ↔ f = 0 := by rw [← coe_zero, DFunLike.coe_fn_eq]
#align finsupp.coe_eq_zero Finsupp.coe_eq_zero
theorem ext_iff' {f g : α →₀ M} : f = g ↔ f.support = g.support ∧ ∀ x ∈ f.support, f x = g x :=
⟨fun h => h ▸ ⟨rfl, fun _ _ => rfl⟩, fun ⟨h₁, h₂⟩ =>
ext fun a => by
classical
exact if h : a ∈ f.support then h₂ a h else by
have hf : f a = 0 := not_mem_support_iff.1 h
have hg : g a = 0 := by rwa [h₁, not_mem_support_iff] at h
rw [hf, hg]⟩
#align finsupp.ext_iff' Finsupp.ext_iff'
@[simp]
theorem support_eq_empty {f : α →₀ M} : f.support = ∅ ↔ f = 0 :=
mod_cast @Function.support_eq_empty_iff _ _ _ f
#align finsupp.support_eq_empty Finsupp.support_eq_empty
theorem support_nonempty_iff {f : α →₀ M} : f.support.Nonempty ↔ f ≠ 0 := by
simp only [Finsupp.support_eq_empty, Finset.nonempty_iff_ne_empty, Ne]
#align finsupp.support_nonempty_iff Finsupp.support_nonempty_iff
#align finsupp.nonzero_iff_exists Finsupp.ne_iff
theorem card_support_eq_zero {f : α →₀ M} : card f.support = 0 ↔ f = 0 := by simp
#align finsupp.card_support_eq_zero Finsupp.card_support_eq_zero
instance instDecidableEq [DecidableEq α] [DecidableEq M] : DecidableEq (α →₀ M) := fun f g =>
decidable_of_iff (f.support = g.support ∧ ∀ a ∈ f.support, f a = g a) ext_iff'.symm
#align finsupp.decidable_eq Finsupp.instDecidableEq
theorem finite_support (f : α →₀ M) : Set.Finite (Function.support f) :=
f.fun_support_eq.symm ▸ f.support.finite_toSet
#align finsupp.finite_support Finsupp.finite_support
theorem support_subset_iff {s : Set α} {f : α →₀ M} :
↑f.support ⊆ s ↔ ∀ a ∉ s, f a = 0 := by
simp only [Set.subset_def, mem_coe, mem_support_iff]; exact forall_congr' fun a => not_imp_comm
#align finsupp.support_subset_iff Finsupp.support_subset_iff
/-- Given `Finite α`, `equivFunOnFinite` is the `Equiv` between `α →₀ β` and `α → β`.
(All functions on a finite type are finitely supported.) -/
@[simps]
def equivFunOnFinite [Finite α] : (α →₀ M) ≃ (α → M) where
toFun := (⇑)
invFun f := mk (Function.support f).toFinite.toFinset f fun _a => Set.Finite.mem_toFinset _
left_inv _f := ext fun _x => rfl
right_inv _f := rfl
#align finsupp.equiv_fun_on_finite Finsupp.equivFunOnFinite
@[simp]
theorem equivFunOnFinite_symm_coe {α} [Finite α] (f : α →₀ M) : equivFunOnFinite.symm f = f :=
equivFunOnFinite.symm_apply_apply f
#align finsupp.equiv_fun_on_finite_symm_coe Finsupp.equivFunOnFinite_symm_coe
/--
If `α` has a unique term, the type of finitely supported functions `α →₀ β` is equivalent to `β`.
-/
@[simps!]
noncomputable def _root_.Equiv.finsuppUnique {ι : Type*} [Unique ι] : (ι →₀ M) ≃ M :=
Finsupp.equivFunOnFinite.trans (Equiv.funUnique ι M)
#align equiv.finsupp_unique Equiv.finsuppUnique
#align equiv.finsupp_unique_symm_apply_support_val Equiv.finsuppUnique_symm_apply_support_val
#align equiv.finsupp_unique_symm_apply_to_fun Equiv.finsuppUnique_symm_apply_toFun
#align equiv.finsupp_unique_apply Equiv.finsuppUnique_apply
@[ext]
theorem unique_ext [Unique α] {f g : α →₀ M} (h : f default = g default) : f = g :=
ext fun a => by rwa [Unique.eq_default a]
#align finsupp.unique_ext Finsupp.unique_ext
theorem unique_ext_iff [Unique α] {f g : α →₀ M} : f = g ↔ f default = g default :=
⟨fun h => h ▸ rfl, unique_ext⟩
#align finsupp.unique_ext_iff Finsupp.unique_ext_iff
end Basic
/-! ### Declarations about `single` -/
section Single
variable [Zero M] {a a' : α} {b : M}
/-- `single a b` is the finitely supported function with value `b` at `a` and zero otherwise. -/
def single (a : α) (b : M) : α →₀ M where
support :=
haveI := Classical.decEq M
if b = 0 then ∅ else {a}
toFun :=
haveI := Classical.decEq α
Pi.single a b
mem_support_toFun a' := by
classical
obtain rfl | hb := eq_or_ne b 0
· simp [Pi.single, update]
rw [if_neg hb, mem_singleton]
obtain rfl | ha := eq_or_ne a' a
· simp [hb, Pi.single, update]
simp [Pi.single_eq_of_ne' ha.symm, ha]
#align finsupp.single Finsupp.single
theorem single_apply [Decidable (a = a')] : single a b a' = if a = a' then b else 0 := by
classical
simp_rw [@eq_comm _ a a']
convert Pi.single_apply a b a'
#align finsupp.single_apply Finsupp.single_apply
theorem single_apply_left {f : α → β} (hf : Function.Injective f) (x z : α) (y : M) :
single (f x) y (f z) = single x y z := by classical simp only [single_apply, hf.eq_iff]
#align finsupp.single_apply_left Finsupp.single_apply_left
theorem single_eq_set_indicator : ⇑(single a b) = Set.indicator {a} fun _ => b := by
classical
ext
simp [single_apply, Set.indicator, @eq_comm _ a]
#align finsupp.single_eq_set_indicator Finsupp.single_eq_set_indicator
@[simp]
theorem single_eq_same : (single a b : α →₀ M) a = b := by
classical exact Pi.single_eq_same (f := fun _ ↦ M) a b
#align finsupp.single_eq_same Finsupp.single_eq_same
@[simp]
theorem single_eq_of_ne (h : a ≠ a') : (single a b : α →₀ M) a' = 0 := by
classical exact Pi.single_eq_of_ne' h _
#align finsupp.single_eq_of_ne Finsupp.single_eq_of_ne
theorem single_eq_update [DecidableEq α] (a : α) (b : M) :
⇑(single a b) = Function.update (0 : _) a b := by
classical rw [single_eq_set_indicator, ← Set.piecewise_eq_indicator, Set.piecewise_singleton]
#align finsupp.single_eq_update Finsupp.single_eq_update
theorem single_eq_pi_single [DecidableEq α] (a : α) (b : M) : ⇑(single a b) = Pi.single a b :=
single_eq_update a b
#align finsupp.single_eq_pi_single Finsupp.single_eq_pi_single
@[simp]
theorem single_zero (a : α) : (single a 0 : α →₀ M) = 0 :=
DFunLike.coe_injective <| by
classical simpa only [single_eq_update, coe_zero] using Function.update_eq_self a (0 : α → M)
#align finsupp.single_zero Finsupp.single_zero
theorem single_of_single_apply (a a' : α) (b : M) :
single a ((single a' b) a) = single a' (single a' b) a := by
classical
rw [single_apply, single_apply]
ext
split_ifs with h
· rw [h]
· rw [zero_apply, single_apply, ite_self]
#align finsupp.single_of_single_apply Finsupp.single_of_single_apply
theorem support_single_ne_zero (a : α) (hb : b ≠ 0) : (single a b).support = {a} :=
if_neg hb
#align finsupp.support_single_ne_zero Finsupp.support_single_ne_zero
theorem support_single_subset : (single a b).support ⊆ {a} := by
classical show ite _ _ _ ⊆ _; split_ifs <;> [exact empty_subset _; exact Subset.refl _]
#align finsupp.support_single_subset Finsupp.support_single_subset
theorem single_apply_mem (x) : single a b x ∈ ({0, b} : Set M) := by
rcases em (a = x) with (rfl | hx) <;> [simp; simp [single_eq_of_ne hx]]
#align finsupp.single_apply_mem Finsupp.single_apply_mem
theorem range_single_subset : Set.range (single a b) ⊆ {0, b} :=
Set.range_subset_iff.2 single_apply_mem
#align finsupp.range_single_subset Finsupp.range_single_subset
/-- `Finsupp.single a b` is injective in `b`. For the statement that it is injective in `a`, see
`Finsupp.single_left_injective` -/
theorem single_injective (a : α) : Function.Injective (single a : M → α →₀ M) := fun b₁ b₂ eq => by
have : (single a b₁ : α →₀ M) a = (single a b₂ : α →₀ M) a := by rw [eq]
rwa [single_eq_same, single_eq_same] at this
#align finsupp.single_injective Finsupp.single_injective
theorem single_apply_eq_zero {a x : α} {b : M} : single a b x = 0 ↔ x = a → b = 0 := by
simp [single_eq_set_indicator]
#align finsupp.single_apply_eq_zero Finsupp.single_apply_eq_zero
theorem single_apply_ne_zero {a x : α} {b : M} : single a b x ≠ 0 ↔ x = a ∧ b ≠ 0 := by
simp [single_apply_eq_zero]
#align finsupp.single_apply_ne_zero Finsupp.single_apply_ne_zero
theorem mem_support_single (a a' : α) (b : M) : a ∈ (single a' b).support ↔ a = a' ∧ b ≠ 0 := by
simp [single_apply_eq_zero, not_or]
#align finsupp.mem_support_single Finsupp.mem_support_single
theorem eq_single_iff {f : α →₀ M} {a b} : f = single a b ↔ f.support ⊆ {a} ∧ f a = b := by
refine ⟨fun h => h.symm ▸ ⟨support_single_subset, single_eq_same⟩, ?_⟩
rintro ⟨h, rfl⟩
ext x
by_cases hx : a = x <;> simp only [hx, single_eq_same, single_eq_of_ne, Ne, not_false_iff]
exact not_mem_support_iff.1 (mt (fun hx => (mem_singleton.1 (h hx)).symm) hx)
#align finsupp.eq_single_iff Finsupp.eq_single_iff
theorem single_eq_single_iff (a₁ a₂ : α) (b₁ b₂ : M) :
single a₁ b₁ = single a₂ b₂ ↔ a₁ = a₂ ∧ b₁ = b₂ ∨ b₁ = 0 ∧ b₂ = 0 := by
constructor
· intro eq
by_cases h : a₁ = a₂
· refine Or.inl ⟨h, ?_⟩
rwa [h, (single_injective a₂).eq_iff] at eq
· rw [DFunLike.ext_iff] at eq
have h₁ := eq a₁
have h₂ := eq a₂
simp only [single_eq_same, single_eq_of_ne h, single_eq_of_ne (Ne.symm h)] at h₁ h₂
exact Or.inr ⟨h₁, h₂.symm⟩
· rintro (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩)
· rfl
· rw [single_zero, single_zero]
#align finsupp.single_eq_single_iff Finsupp.single_eq_single_iff
/-- `Finsupp.single a b` is injective in `a`. For the statement that it is injective in `b`, see
`Finsupp.single_injective` -/
theorem single_left_injective (h : b ≠ 0) : Function.Injective fun a : α => single a b :=
fun _a _a' H => (((single_eq_single_iff _ _ _ _).mp H).resolve_right fun hb => h hb.1).left
#align finsupp.single_left_injective Finsupp.single_left_injective
theorem single_left_inj (h : b ≠ 0) : single a b = single a' b ↔ a = a' :=
(single_left_injective h).eq_iff
#align finsupp.single_left_inj Finsupp.single_left_inj
theorem support_single_ne_bot (i : α) (h : b ≠ 0) : (single i b).support ≠ ⊥ := by
simpa only [support_single_ne_zero _ h] using singleton_ne_empty _
#align finsupp.support_single_ne_bot Finsupp.support_single_ne_bot
theorem support_single_disjoint {b' : M} (hb : b ≠ 0) (hb' : b' ≠ 0) {i j : α} :
Disjoint (single i b).support (single j b').support ↔ i ≠ j := by
rw [support_single_ne_zero _ hb, support_single_ne_zero _ hb', disjoint_singleton]
#align finsupp.support_single_disjoint Finsupp.support_single_disjoint
@[simp]
theorem single_eq_zero : single a b = 0 ↔ b = 0 := by
simp [DFunLike.ext_iff, single_eq_set_indicator]
#align finsupp.single_eq_zero Finsupp.single_eq_zero
theorem single_swap (a₁ a₂ : α) (b : M) : single a₁ b a₂ = single a₂ b a₁ := by
classical simp only [single_apply, eq_comm]
#align finsupp.single_swap Finsupp.single_swap
instance instNontrivial [Nonempty α] [Nontrivial M] : Nontrivial (α →₀ M) := by
inhabit α
rcases exists_ne (0 : M) with ⟨x, hx⟩
exact nontrivial_of_ne (single default x) 0 (mt single_eq_zero.1 hx)
#align finsupp.nontrivial Finsupp.instNontrivial
theorem unique_single [Unique α] (x : α →₀ M) : x = single default (x default) :=
ext <| Unique.forall_iff.2 single_eq_same.symm
#align finsupp.unique_single Finsupp.unique_single
@[simp]
theorem unique_single_eq_iff [Unique α] {b' : M} : single a b = single a' b' ↔ b = b' := by
rw [unique_ext_iff, Unique.eq_default a, Unique.eq_default a', single_eq_same, single_eq_same]
#align finsupp.unique_single_eq_iff Finsupp.unique_single_eq_iff
lemma apply_single [AddCommMonoid N] [AddCommMonoid P]
{F : Type*} [FunLike F N P] [AddMonoidHomClass F N P] (e : F)
(a : α) (n : N) (b : α) :
e ((single a n) b) = single a (e n) b := by
classical
simp only [single_apply]
split_ifs
· rfl
· exact map_zero e
theorem support_eq_singleton {f : α →₀ M} {a : α} :
f.support = {a} ↔ f a ≠ 0 ∧ f = single a (f a) :=
⟨fun h =>
⟨mem_support_iff.1 <| h.symm ▸ Finset.mem_singleton_self a,
eq_single_iff.2 ⟨subset_of_eq h, rfl⟩⟩,
fun h => h.2.symm ▸ support_single_ne_zero _ h.1⟩
#align finsupp.support_eq_singleton Finsupp.support_eq_singleton
theorem support_eq_singleton' {f : α →₀ M} {a : α} :
f.support = {a} ↔ ∃ b ≠ 0, f = single a b :=
⟨fun h =>
let h := support_eq_singleton.1 h
⟨_, h.1, h.2⟩,
fun ⟨_b, hb, hf⟩ => hf.symm ▸ support_single_ne_zero _ hb⟩
#align finsupp.support_eq_singleton' Finsupp.support_eq_singleton'
theorem card_support_eq_one {f : α →₀ M} :
card f.support = 1 ↔ ∃ a, f a ≠ 0 ∧ f = single a (f a) := by
simp only [card_eq_one, support_eq_singleton]
#align finsupp.card_support_eq_one Finsupp.card_support_eq_one
theorem card_support_eq_one' {f : α →₀ M} :
card f.support = 1 ↔ ∃ a, ∃ b ≠ 0, f = single a b := by
simp only [card_eq_one, support_eq_singleton']
#align finsupp.card_support_eq_one' Finsupp.card_support_eq_one'
theorem support_subset_singleton {f : α →₀ M} {a : α} : f.support ⊆ {a} ↔ f = single a (f a) :=
⟨fun h => eq_single_iff.mpr ⟨h, rfl⟩, fun h => (eq_single_iff.mp h).left⟩
#align finsupp.support_subset_singleton Finsupp.support_subset_singleton
theorem support_subset_singleton' {f : α →₀ M} {a : α} : f.support ⊆ {a} ↔ ∃ b, f = single a b :=
⟨fun h => ⟨f a, support_subset_singleton.mp h⟩, fun ⟨b, hb⟩ => by
rw [hb, support_subset_singleton, single_eq_same]⟩
#align finsupp.support_subset_singleton' Finsupp.support_subset_singleton'
theorem card_support_le_one [Nonempty α] {f : α →₀ M} :
card f.support ≤ 1 ↔ ∃ a, f = single a (f a) := by
simp only [card_le_one_iff_subset_singleton, support_subset_singleton]
#align finsupp.card_support_le_one Finsupp.card_support_le_one
theorem card_support_le_one' [Nonempty α] {f : α →₀ M} :
card f.support ≤ 1 ↔ ∃ a b, f = single a b := by
simp only [card_le_one_iff_subset_singleton, support_subset_singleton']
#align finsupp.card_support_le_one' Finsupp.card_support_le_one'
@[simp]
theorem equivFunOnFinite_single [DecidableEq α] [Finite α] (x : α) (m : M) :
Finsupp.equivFunOnFinite (Finsupp.single x m) = Pi.single x m := by
ext
simp [Finsupp.single_eq_pi_single, equivFunOnFinite]
#align finsupp.equiv_fun_on_finite_single Finsupp.equivFunOnFinite_single
@[simp]
theorem equivFunOnFinite_symm_single [DecidableEq α] [Finite α] (x : α) (m : M) :
Finsupp.equivFunOnFinite.symm (Pi.single x m) = Finsupp.single x m := by
rw [← equivFunOnFinite_single, Equiv.symm_apply_apply]
#align finsupp.equiv_fun_on_finite_symm_single Finsupp.equivFunOnFinite_symm_single
end Single
/-! ### Declarations about `update` -/
section Update
variable [Zero M] (f : α →₀ M) (a : α) (b : M) (i : α)
/-- Replace the value of a `α →₀ M` at a given point `a : α` by a given value `b : M`.
If `b = 0`, this amounts to removing `a` from the `Finsupp.support`.
Otherwise, if `a` was not in the `Finsupp.support`, it is added to it.
This is the finitely-supported version of `Function.update`. -/
def update (f : α →₀ M) (a : α) (b : M) : α →₀ M where
support := by
haveI := Classical.decEq α; haveI := Classical.decEq M
exact if b = 0 then f.support.erase a else insert a f.support
toFun :=
haveI := Classical.decEq α
Function.update f a b
mem_support_toFun i := by
classical
rw [Function.update]
simp only [eq_rec_constant, dite_eq_ite, ne_eq]
split_ifs with hb ha ha <;>
try simp only [*, not_false_iff, iff_true, not_true, iff_false]
· rw [Finset.mem_erase]
simp
· rw [Finset.mem_erase]
simp [ha]
· rw [Finset.mem_insert]
simp [ha]
· rw [Finset.mem_insert]
simp [ha]
#align finsupp.update Finsupp.update
@[simp, norm_cast]
theorem coe_update [DecidableEq α] : (f.update a b : α → M) = Function.update f a b := by
delta update Function.update
ext
dsimp
split_ifs <;> simp
#align finsupp.coe_update Finsupp.coe_update
@[simp]
theorem update_self : f.update a (f a) = f := by
classical
ext
simp
#align finsupp.update_self Finsupp.update_self
@[simp]
theorem zero_update : update 0 a b = single a b := by
classical
ext
rw [single_eq_update]
rfl
#align finsupp.zero_update Finsupp.zero_update
theorem support_update [DecidableEq α] [DecidableEq M] :
support (f.update a b) = if b = 0 then f.support.erase a else insert a f.support := by
classical
dsimp [update]; congr <;> apply Subsingleton.elim
#align finsupp.support_update Finsupp.support_update
@[simp]
theorem support_update_zero [DecidableEq α] : support (f.update a 0) = f.support.erase a := by
classical
simp only [update, ite_true, mem_support_iff, ne_eq, not_not]
congr; apply Subsingleton.elim
#align finsupp.support_update_zero Finsupp.support_update_zero
variable {b}
theorem support_update_ne_zero [DecidableEq α] (h : b ≠ 0) :
support (f.update a b) = insert a f.support := by
classical
simp only [update, h, ite_false, mem_support_iff, ne_eq]
congr; apply Subsingleton.elim
#align finsupp.support_update_ne_zero Finsupp.support_update_ne_zero
theorem support_update_subset [DecidableEq α] [DecidableEq M] :
support (f.update a b) ⊆ insert a f.support := by
rw [support_update]
split_ifs
· exact (erase_subset _ _).trans (subset_insert _ _)
· rfl
theorem update_comm (f : α →₀ M) {a₁ a₂ : α} (h : a₁ ≠ a₂) (m₁ m₂ : M) :
update (update f a₁ m₁) a₂ m₂ = update (update f a₂ m₂) a₁ m₁ :=
letI := Classical.decEq α
DFunLike.coe_injective <| Function.update_comm h _ _ _
@[simp] theorem update_idem (f : α →₀ M) (a : α) (b c : M) :
update (update f a b) a c = update f a c :=
letI := Classical.decEq α
DFunLike.coe_injective <| Function.update_idem _ _ _
end Update
/-! ### Declarations about `erase` -/
section Erase
variable [Zero M]
/--
`erase a f` is the finitely supported function equal to `f` except at `a` where it is equal to `0`.
If `a` is not in the support of `f` then `erase a f = f`.
-/
def erase (a : α) (f : α →₀ M) : α →₀ M where
support :=
haveI := Classical.decEq α
f.support.erase a
toFun a' :=
haveI := Classical.decEq α
if a' = a then 0 else f a'
mem_support_toFun a' := by
classical
rw [mem_erase, mem_support_iff]; dsimp
split_ifs with h
· exact ⟨fun H _ => H.1 h, fun H => (H rfl).elim⟩
· exact and_iff_right h
#align finsupp.erase Finsupp.erase
@[simp]
theorem support_erase [DecidableEq α] {a : α} {f : α →₀ M} :
(f.erase a).support = f.support.erase a := by
classical
dsimp [erase]
congr; apply Subsingleton.elim
#align finsupp.support_erase Finsupp.support_erase
@[simp]
theorem erase_same {a : α} {f : α →₀ M} : (f.erase a) a = 0 := by
classical simp only [erase, coe_mk, ite_true]
#align finsupp.erase_same Finsupp.erase_same
@[simp]
theorem erase_ne {a a' : α} {f : α →₀ M} (h : a' ≠ a) : (f.erase a) a' = f a' := by
classical simp only [erase, coe_mk, h, ite_false]
#align finsupp.erase_ne Finsupp.erase_ne
theorem erase_apply [DecidableEq α] {a a' : α} {f : α →₀ M} :
f.erase a a' = if a' = a then 0 else f a' := by
rw [erase, coe_mk]
convert rfl
@[simp]
theorem erase_single {a : α} {b : M} : erase a (single a b) = 0 := by
ext s; by_cases hs : s = a
· rw [hs, erase_same]
rfl
· rw [erase_ne hs]
exact single_eq_of_ne (Ne.symm hs)
#align finsupp.erase_single Finsupp.erase_single
theorem erase_single_ne {a a' : α} {b : M} (h : a ≠ a') : erase a (single a' b) = single a' b := by
ext s; by_cases hs : s = a
· rw [hs, erase_same, single_eq_of_ne h.symm]
· rw [erase_ne hs]
#align finsupp.erase_single_ne Finsupp.erase_single_ne
@[simp]
theorem erase_of_not_mem_support {f : α →₀ M} {a} (haf : a ∉ f.support) : erase a f = f := by
ext b; by_cases hab : b = a
· rwa [hab, erase_same, eq_comm, ← not_mem_support_iff]
· rw [erase_ne hab]
#align finsupp.erase_of_not_mem_support Finsupp.erase_of_not_mem_support
@[simp, nolint simpNF] -- Porting note: simpNF linter claims simp can prove this, it can not
theorem erase_zero (a : α) : erase a (0 : α →₀ M) = 0 := by
classical rw [← support_eq_empty, support_erase, support_zero, erase_empty]
#align finsupp.erase_zero Finsupp.erase_zero
theorem erase_eq_update_zero (f : α →₀ M) (a : α) : f.erase a = update f a 0 :=
letI := Classical.decEq α
ext fun _ => (Function.update_apply _ _ _ _).symm
-- The name matches `Finset.erase_insert_of_ne`
theorem erase_update_of_ne (f : α →₀ M) {a a' : α} (ha : a ≠ a') (b : M) :
erase a (update f a' b) = update (erase a f) a' b := by
rw [erase_eq_update_zero, erase_eq_update_zero, update_comm _ ha]
-- not `simp` as `erase_of_not_mem_support` can prove this
theorem erase_idem (f : α →₀ M) (a : α) :
erase a (erase a f) = erase a f := by
rw [erase_eq_update_zero, erase_eq_update_zero, update_idem]
@[simp] theorem update_erase_eq_update (f : α →₀ M) (a : α) (b : M) :
update (erase a f) a b = update f a b := by
rw [erase_eq_update_zero, update_idem]
@[simp] theorem erase_update_eq_erase (f : α →₀ M) (a : α) (b : M) :
erase a (update f a b) = erase a f := by
rw [erase_eq_update_zero, erase_eq_update_zero, update_idem]
end Erase
/-! ### Declarations about `onFinset` -/
section OnFinset
variable [Zero M]
/-- `Finsupp.onFinset s f hf` is the finsupp function representing `f` restricted to the finset `s`.
The function must be `0` outside of `s`. Use this when the set needs to be filtered anyways,
otherwise a better set representation is often available. -/
def onFinset (s : Finset α) (f : α → M) (hf : ∀ a, f a ≠ 0 → a ∈ s) : α →₀ M where
support :=
haveI := Classical.decEq M
s.filter (f · ≠ 0)
toFun := f
mem_support_toFun := by classical simpa
#align finsupp.on_finset Finsupp.onFinset
@[simp]
theorem onFinset_apply {s : Finset α} {f : α → M} {hf a} : (onFinset s f hf : α →₀ M) a = f a :=
rfl
#align finsupp.on_finset_apply Finsupp.onFinset_apply
@[simp]
theorem support_onFinset_subset {s : Finset α} {f : α → M} {hf} :
(onFinset s f hf).support ⊆ s := by
classical convert filter_subset (f · ≠ 0) s
#align finsupp.support_on_finset_subset Finsupp.support_onFinset_subset
-- @[simp] -- Porting note (#10618): simp can prove this
theorem mem_support_onFinset {s : Finset α} {f : α → M} (hf : ∀ a : α, f a ≠ 0 → a ∈ s) {a : α} :
a ∈ (Finsupp.onFinset s f hf).support ↔ f a ≠ 0 := by
rw [Finsupp.mem_support_iff, Finsupp.onFinset_apply]
#align finsupp.mem_support_on_finset Finsupp.mem_support_onFinset
theorem support_onFinset [DecidableEq M] {s : Finset α} {f : α → M}
(hf : ∀ a : α, f a ≠ 0 → a ∈ s) :
(Finsupp.onFinset s f hf).support = s.filter fun a => f a ≠ 0 := by
dsimp [onFinset]; congr
#align finsupp.support_on_finset Finsupp.support_onFinset
end OnFinset
section OfSupportFinite
variable [Zero M]
/-- The natural `Finsupp` induced by the function `f` given that it has finite support. -/
noncomputable def ofSupportFinite (f : α → M) (hf : (Function.support f).Finite) : α →₀ M where
support := hf.toFinset
toFun := f
mem_support_toFun _ := hf.mem_toFinset
#align finsupp.of_support_finite Finsupp.ofSupportFinite
theorem ofSupportFinite_coe {f : α → M} {hf : (Function.support f).Finite} :
(ofSupportFinite f hf : α → M) = f :=
rfl
#align finsupp.of_support_finite_coe Finsupp.ofSupportFinite_coe
instance instCanLift : CanLift (α → M) (α →₀ M) (⇑) fun f => (Function.support f).Finite where
prf f hf := ⟨ofSupportFinite f hf, rfl⟩
#align finsupp.can_lift Finsupp.instCanLift
end OfSupportFinite
/-! ### Declarations about `mapRange` -/
section MapRange
variable [Zero M] [Zero N] [Zero P]
/-- The composition of `f : M → N` and `g : α →₀ M` is `mapRange f hf g : α →₀ N`,
which is well-defined when `f 0 = 0`.
This preserves the structure on `f`, and exists in various bundled forms for when `f` is itself
bundled (defined in `Data/Finsupp/Basic`):
* `Finsupp.mapRange.equiv`
* `Finsupp.mapRange.zeroHom`
* `Finsupp.mapRange.addMonoidHom`
* `Finsupp.mapRange.addEquiv`
* `Finsupp.mapRange.linearMap`
* `Finsupp.mapRange.linearEquiv`
-/
def mapRange (f : M → N) (hf : f 0 = 0) (g : α →₀ M) : α →₀ N :=
onFinset g.support (f ∘ g) fun a => by
rw [mem_support_iff, not_imp_not]; exact fun H => (congr_arg f H).trans hf
#align finsupp.map_range Finsupp.mapRange
@[simp]
theorem mapRange_apply {f : M → N} {hf : f 0 = 0} {g : α →₀ M} {a : α} :
mapRange f hf g a = f (g a) :=
rfl
#align finsupp.map_range_apply Finsupp.mapRange_apply
@[simp]
theorem mapRange_zero {f : M → N} {hf : f 0 = 0} : mapRange f hf (0 : α →₀ M) = 0 :=
ext fun _ => by simp only [hf, zero_apply, mapRange_apply]
#align finsupp.map_range_zero Finsupp.mapRange_zero
@[simp]
theorem mapRange_id (g : α →₀ M) : mapRange id rfl g = g :=
ext fun _ => rfl
#align finsupp.map_range_id Finsupp.mapRange_id
theorem mapRange_comp (f : N → P) (hf : f 0 = 0) (f₂ : M → N) (hf₂ : f₂ 0 = 0) (h : (f ∘ f₂) 0 = 0)
(g : α →₀ M) : mapRange (f ∘ f₂) h g = mapRange f hf (mapRange f₂ hf₂ g) :=
ext fun _ => rfl
#align finsupp.map_range_comp Finsupp.mapRange_comp
theorem support_mapRange {f : M → N} {hf : f 0 = 0} {g : α →₀ M} :
(mapRange f hf g).support ⊆ g.support :=
support_onFinset_subset
#align finsupp.support_map_range Finsupp.support_mapRange
@[simp]
theorem mapRange_single {f : M → N} {hf : f 0 = 0} {a : α} {b : M} :
mapRange f hf (single a b) = single a (f b) :=
ext fun a' => by
classical simpa only [single_eq_pi_single] using Pi.apply_single _ (fun _ => hf) a _ a'
#align finsupp.map_range_single Finsupp.mapRange_single
theorem support_mapRange_of_injective {e : M → N} (he0 : e 0 = 0) (f : ι →₀ M)
(he : Function.Injective e) : (Finsupp.mapRange e he0 f).support = f.support := by
ext
simp only [Finsupp.mem_support_iff, Ne, Finsupp.mapRange_apply]
exact he.ne_iff' he0
#align finsupp.support_map_range_of_injective Finsupp.support_mapRange_of_injective
end MapRange
/-! ### Declarations about `embDomain` -/
section EmbDomain
variable [Zero M] [Zero N]
/-- Given `f : α ↪ β` and `v : α →₀ M`, `Finsupp.embDomain f v : β →₀ M`
is the finitely supported function whose value at `f a : β` is `v a`.
For a `b : β` outside the range of `f`, it is zero. -/
def embDomain (f : α ↪ β) (v : α →₀ M) : β →₀ M where
support := v.support.map f
toFun a₂ :=
haveI := Classical.decEq β
if h : a₂ ∈ v.support.map f then
v
(v.support.choose (fun a₁ => f a₁ = a₂)
(by
rcases Finset.mem_map.1 h with ⟨a, ha, rfl⟩
exact ExistsUnique.intro a ⟨ha, rfl⟩ fun b ⟨_, hb⟩ => f.injective hb))
else 0
mem_support_toFun a₂ := by
dsimp
split_ifs with h
· simp only [h, true_iff_iff, Ne]
rw [← not_mem_support_iff, not_not]
classical apply Finset.choose_mem
· simp only [h, Ne, ne_self_iff_false, not_true_eq_false]
#align finsupp.emb_domain Finsupp.embDomain
@[simp]
theorem support_embDomain (f : α ↪ β) (v : α →₀ M) : (embDomain f v).support = v.support.map f :=
rfl
#align finsupp.support_emb_domain Finsupp.support_embDomain
@[simp]
theorem embDomain_zero (f : α ↪ β) : (embDomain f 0 : β →₀ M) = 0 :=
rfl
#align finsupp.emb_domain_zero Finsupp.embDomain_zero
@[simp]
theorem embDomain_apply (f : α ↪ β) (v : α →₀ M) (a : α) : embDomain f v (f a) = v a := by
classical
change dite _ _ _ = _
split_ifs with h <;> rw [Finset.mem_map' f] at h
· refine congr_arg (v : α → M) (f.inj' ?_)
exact Finset.choose_property (fun a₁ => f a₁ = f a) _ _
· exact (not_mem_support_iff.1 h).symm
#align finsupp.emb_domain_apply Finsupp.embDomain_apply
theorem embDomain_notin_range (f : α ↪ β) (v : α →₀ M) (a : β) (h : a ∉ Set.range f) :
embDomain f v a = 0 := by
classical
refine dif_neg (mt (fun h => ?_) h)
rcases Finset.mem_map.1 h with ⟨a, _h, rfl⟩
exact Set.mem_range_self a
#align finsupp.emb_domain_notin_range Finsupp.embDomain_notin_range
theorem embDomain_injective (f : α ↪ β) : Function.Injective (embDomain f : (α →₀ M) → β →₀ M) :=
fun l₁ l₂ h => ext fun a => by simpa only [embDomain_apply] using DFunLike.ext_iff.1 h (f a)
#align finsupp.emb_domain_injective Finsupp.embDomain_injective
@[simp]
theorem embDomain_inj {f : α ↪ β} {l₁ l₂ : α →₀ M} : embDomain f l₁ = embDomain f l₂ ↔ l₁ = l₂ :=
(embDomain_injective f).eq_iff
#align finsupp.emb_domain_inj Finsupp.embDomain_inj
@[simp]
theorem embDomain_eq_zero {f : α ↪ β} {l : α →₀ M} : embDomain f l = 0 ↔ l = 0 :=
(embDomain_injective f).eq_iff' <| embDomain_zero f
#align finsupp.emb_domain_eq_zero Finsupp.embDomain_eq_zero
theorem embDomain_mapRange (f : α ↪ β) (g : M → N) (p : α →₀ M) (hg : g 0 = 0) :
embDomain f (mapRange g hg p) = mapRange g hg (embDomain f p) := by
ext a
by_cases h : a ∈ Set.range f
· rcases h with ⟨a', rfl⟩
rw [mapRange_apply, embDomain_apply, embDomain_apply, mapRange_apply]
· rw [mapRange_apply, embDomain_notin_range, embDomain_notin_range, ← hg] <;> assumption
#align finsupp.emb_domain_map_range Finsupp.embDomain_mapRange
theorem single_of_embDomain_single (l : α →₀ M) (f : α ↪ β) (a : β) (b : M) (hb : b ≠ 0)
(h : l.embDomain f = single a b) : ∃ x, l = single x b ∧ f x = a := by
classical
have h_map_support : Finset.map f l.support = {a} := by
rw [← support_embDomain, h, support_single_ne_zero _ hb]
have ha : a ∈ Finset.map f l.support := by simp only [h_map_support, Finset.mem_singleton]
rcases Finset.mem_map.1 ha with ⟨c, _hc₁, hc₂⟩
use c
constructor
· ext d
rw [← embDomain_apply f l, h]
by_cases h_cases : c = d
· simp only [Eq.symm h_cases, hc₂, single_eq_same]
· rw [single_apply, single_apply, if_neg, if_neg h_cases]
by_contra hfd
exact h_cases (f.injective (hc₂.trans hfd))
· exact hc₂
#align finsupp.single_of_emb_domain_single Finsupp.single_of_embDomain_single
@[simp]
theorem embDomain_single (f : α ↪ β) (a : α) (m : M) :
embDomain f (single a m) = single (f a) m := by
classical
ext b
by_cases h : b ∈ Set.range f
· rcases h with ⟨a', rfl⟩
simp [single_apply]
· simp only [embDomain_notin_range, h, single_apply, not_false_iff]
rw [if_neg]
rintro rfl
simp at h
#align finsupp.emb_domain_single Finsupp.embDomain_single
end EmbDomain
/-! ### Declarations about `zipWith` -/
section ZipWith
variable [Zero M] [Zero N] [Zero P]
/-- Given finitely supported functions `g₁ : α →₀ M` and `g₂ : α →₀ N` and function `f : M → N → P`,
`Finsupp.zipWith f hf g₁ g₂` is the finitely supported function `α →₀ P` satisfying
`zipWith f hf g₁ g₂ a = f (g₁ a) (g₂ a)`, which is well-defined when `f 0 0 = 0`. -/
def zipWith (f : M → N → P) (hf : f 0 0 = 0) (g₁ : α →₀ M) (g₂ : α →₀ N) : α →₀ P :=
onFinset
(haveI := Classical.decEq α; g₁.support ∪ g₂.support)
(fun a => f (g₁ a) (g₂ a))
fun a (H : f _ _ ≠ 0) => by
classical
rw [mem_union, mem_support_iff, mem_support_iff, ← not_and_or]
rintro ⟨h₁, h₂⟩; rw [h₁, h₂] at H; exact H hf
#align finsupp.zip_with Finsupp.zipWith
@[simp]
theorem zipWith_apply {f : M → N → P} {hf : f 0 0 = 0} {g₁ : α →₀ M} {g₂ : α →₀ N} {a : α} :
zipWith f hf g₁ g₂ a = f (g₁ a) (g₂ a) :=
rfl
#align finsupp.zip_with_apply Finsupp.zipWith_apply
| Mathlib/Data/Finsupp/Defs.lean | 984 | 986 | theorem support_zipWith [D : DecidableEq α] {f : M → N → P} {hf : f 0 0 = 0} {g₁ : α →₀ M}
{g₂ : α →₀ N} : (zipWith f hf g₁ g₂).support ⊆ g₁.support ∪ g₂.support := by |
rw [Subsingleton.elim D] <;> exact support_onFinset_subset
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Set.Pairwise.Basic
import Mathlib.Data.Set.Lattice
import Mathlib.Data.SetLike.Basic
#align_import order.chain from "leanprover-community/mathlib"@"c227d107bbada5d0d9d20287e3282c0a7f1651a0"
/-!
# Chains and flags
This file defines chains for an arbitrary relation and flags for an order and proves Hausdorff's
Maximality Principle.
## Main declarations
* `IsChain s`: A chain `s` is a set of comparable elements.
* `maxChain_spec`: Hausdorff's Maximality Principle.
* `Flag`: The type of flags, aka maximal chains, of an order.
## Notes
Originally ported from Isabelle/HOL. The
[original file](https://isabelle.in.tum.de/dist/library/HOL/HOL/Zorn.html) was written by Jacques D.
Fleuriot, Tobias Nipkow, Christian Sternagel.
-/
open scoped Classical
open Set
variable {α β : Type*}
/-! ### Chains -/
section Chain
variable (r : α → α → Prop)
/-- In this file, we use `≺` as a local notation for any relation `r`. -/
local infixl:50 " ≺ " => r
/-- A chain is a set `s` satisfying `x ≺ y ∨ x = y ∨ y ≺ x` for all `x y ∈ s`. -/
def IsChain (s : Set α) : Prop :=
s.Pairwise fun x y => x ≺ y ∨ y ≺ x
#align is_chain IsChain
/-- `SuperChain s t` means that `t` is a chain that strictly includes `s`. -/
def SuperChain (s t : Set α) : Prop :=
IsChain r t ∧ s ⊂ t
#align super_chain SuperChain
/-- A chain `s` is a maximal chain if there does not exists a chain strictly including `s`. -/
def IsMaxChain (s : Set α) : Prop :=
IsChain r s ∧ ∀ ⦃t⦄, IsChain r t → s ⊆ t → s = t
#align is_max_chain IsMaxChain
variable {r} {c c₁ c₂ c₃ s t : Set α} {a b x y : α}
theorem isChain_empty : IsChain r ∅ :=
Set.pairwise_empty _
#align is_chain_empty isChain_empty
theorem Set.Subsingleton.isChain (hs : s.Subsingleton) : IsChain r s :=
hs.pairwise _
#align set.subsingleton.is_chain Set.Subsingleton.isChain
theorem IsChain.mono : s ⊆ t → IsChain r t → IsChain r s :=
Set.Pairwise.mono
#align is_chain.mono IsChain.mono
theorem IsChain.mono_rel {r' : α → α → Prop} (h : IsChain r s) (h_imp : ∀ x y, r x y → r' x y) :
IsChain r' s :=
h.mono' fun x y => Or.imp (h_imp x y) (h_imp y x)
#align is_chain.mono_rel IsChain.mono_rel
/-- This can be used to turn `IsChain (≥)` into `IsChain (≤)` and vice-versa. -/
theorem IsChain.symm (h : IsChain r s) : IsChain (flip r) s :=
h.mono' fun _ _ => Or.symm
#align is_chain.symm IsChain.symm
theorem isChain_of_trichotomous [IsTrichotomous α r] (s : Set α) : IsChain r s :=
fun a _ b _ hab => (trichotomous_of r a b).imp_right fun h => h.resolve_left hab
#align is_chain_of_trichotomous isChain_of_trichotomous
protected theorem IsChain.insert (hs : IsChain r s) (ha : ∀ b ∈ s, a ≠ b → a ≺ b ∨ b ≺ a) :
IsChain r (insert a s) :=
hs.insert_of_symmetric (fun _ _ => Or.symm) ha
#align is_chain.insert IsChain.insert
theorem isChain_univ_iff : IsChain r (univ : Set α) ↔ IsTrichotomous α r := by
refine ⟨fun h => ⟨fun a b => ?_⟩, fun h => @isChain_of_trichotomous _ _ h univ⟩
rw [or_left_comm, or_iff_not_imp_left]
exact h trivial trivial
#align is_chain_univ_iff isChain_univ_iff
theorem IsChain.image (r : α → α → Prop) (s : β → β → Prop) (f : α → β)
(h : ∀ x y, r x y → s (f x) (f y)) {c : Set α} (hrc : IsChain r c) : IsChain s (f '' c) :=
fun _ ⟨_, ha₁, ha₂⟩ _ ⟨_, hb₁, hb₂⟩ =>
ha₂ ▸ hb₂ ▸ fun hxy => (hrc ha₁ hb₁ <| ne_of_apply_ne f hxy).imp (h _ _) (h _ _)
#align is_chain.image IsChain.image
theorem Monotone.isChain_range [LinearOrder α] [Preorder β] {f : α → β} (hf : Monotone f) :
IsChain (· ≤ ·) (range f) := by
rw [← image_univ]
exact (isChain_of_trichotomous _).image (· ≤ ·) _ _ hf
theorem IsChain.lt_of_le [PartialOrder α] {s : Set α} (h : IsChain (· ≤ ·) s) :
IsChain (· < ·) s := fun _a ha _b hb hne ↦
(h ha hb hne).imp hne.lt_of_le hne.lt_of_le'
section Total
variable [IsRefl α r]
theorem IsChain.total (h : IsChain r s) (hx : x ∈ s) (hy : y ∈ s) : x ≺ y ∨ y ≺ x :=
(eq_or_ne x y).elim (fun e => Or.inl <| e ▸ refl _) (h hx hy)
#align is_chain.total IsChain.total
theorem IsChain.directedOn (H : IsChain r s) : DirectedOn r s := fun x hx y hy =>
((H.total hx hy).elim fun h => ⟨y, hy, h, refl _⟩) fun h => ⟨x, hx, refl _, h⟩
#align is_chain.directed_on IsChain.directedOn
protected theorem IsChain.directed {f : β → α} {c : Set β} (h : IsChain (f ⁻¹'o r) c) :
Directed r fun x : { a : β // a ∈ c } => f x :=
fun ⟨a, ha⟩ ⟨b, hb⟩ =>
(by_cases fun hab : a = b => by
simp only [hab, exists_prop, and_self_iff, Subtype.exists]
exact ⟨b, hb, refl _⟩)
fun hab => ((h ha hb hab).elim fun h => ⟨⟨b, hb⟩, h, refl _⟩) fun h => ⟨⟨a, ha⟩, refl _, h⟩
#align is_chain.directed IsChain.directed
theorem IsChain.exists3 (hchain : IsChain r s) [IsTrans α r] {a b c} (mem1 : a ∈ s) (mem2 : b ∈ s)
(mem3 : c ∈ s) : ∃ (z : _) (_ : z ∈ s), r a z ∧ r b z ∧ r c z := by
rcases directedOn_iff_directed.mpr (IsChain.directed hchain) a mem1 b mem2 with ⟨z, mem4, H1, H2⟩
rcases directedOn_iff_directed.mpr (IsChain.directed hchain) z mem4 c mem3 with
⟨z', mem5, H3, H4⟩
exact ⟨z', mem5, _root_.trans H1 H3, _root_.trans H2 H3, H4⟩
#align is_chain.exists3 IsChain.exists3
end Total
theorem IsMaxChain.isChain (h : IsMaxChain r s) : IsChain r s :=
h.1
#align is_max_chain.is_chain IsMaxChain.isChain
theorem IsMaxChain.not_superChain (h : IsMaxChain r s) : ¬SuperChain r s t := fun ht =>
ht.2.ne <| h.2 ht.1 ht.2.1
#align is_max_chain.not_super_chain IsMaxChain.not_superChain
theorem IsMaxChain.bot_mem [LE α] [OrderBot α] (h : IsMaxChain (· ≤ ·) s) : ⊥ ∈ s :=
(h.2 (h.1.insert fun _ _ _ => Or.inl bot_le) <| subset_insert _ _).symm ▸ mem_insert _ _
#align is_max_chain.bot_mem IsMaxChain.bot_mem
theorem IsMaxChain.top_mem [LE α] [OrderTop α] (h : IsMaxChain (· ≤ ·) s) : ⊤ ∈ s :=
(h.2 (h.1.insert fun _ _ _ => Or.inr le_top) <| subset_insert _ _).symm ▸ mem_insert _ _
#align is_max_chain.top_mem IsMaxChain.top_mem
open scoped Classical
/-- Given a set `s`, if there exists a chain `t` strictly including `s`, then `SuccChain s`
is one of these chains. Otherwise it is `s`. -/
def SuccChain (r : α → α → Prop) (s : Set α) : Set α :=
if h : ∃ t, IsChain r s ∧ SuperChain r s t then h.choose else s
#align succ_chain SuccChain
theorem succChain_spec (h : ∃ t, IsChain r s ∧ SuperChain r s t) :
SuperChain r s (SuccChain r s) := by
have : IsChain r s ∧ SuperChain r s h.choose := h.choose_spec
simpa [SuccChain, dif_pos, exists_and_left.mp h] using this.2
#align succ_chain_spec succChain_spec
theorem IsChain.succ (hs : IsChain r s) : IsChain r (SuccChain r s) :=
if h : ∃ t, IsChain r s ∧ SuperChain r s t then (succChain_spec h).1
else by
rw [exists_and_left] at h
simpa [SuccChain, dif_neg, h] using hs
#align is_chain.succ IsChain.succ
theorem IsChain.superChain_succChain (hs₁ : IsChain r s) (hs₂ : ¬IsMaxChain r s) :
SuperChain r s (SuccChain r s) := by
simp only [IsMaxChain, _root_.not_and, not_forall, exists_prop, exists_and_left] at hs₂
obtain ⟨t, ht, hst⟩ := hs₂ hs₁
exact succChain_spec ⟨t, hs₁, ht, ssubset_iff_subset_ne.2 hst⟩
#align is_chain.super_chain_succ_chain IsChain.superChain_succChain
theorem subset_succChain : s ⊆ SuccChain r s :=
if h : ∃ t, IsChain r s ∧ SuperChain r s t then (succChain_spec h).2.1
else by
rw [exists_and_left] at h
simp [SuccChain, dif_neg, h, Subset.rfl]
#align subset_succ_chain subset_succChain
/-- Predicate for whether a set is reachable from `∅` using `SuccChain` and `⋃₀`. -/
inductive ChainClosure (r : α → α → Prop) : Set α → Prop
| succ : ∀ {s}, ChainClosure r s → ChainClosure r (SuccChain r s)
| union : ∀ {s}, (∀ a ∈ s, ChainClosure r a) → ChainClosure r (⋃₀s)
#align chain_closure ChainClosure
/-- An explicit maximal chain. `maxChain` is taken to be the union of all sets in `ChainClosure`.
-/
def maxChain (r : α → α → Prop) : Set α :=
⋃₀ setOf (ChainClosure r)
#align max_chain maxChain
theorem chainClosure_empty : ChainClosure r ∅ := by
have : ChainClosure r (⋃₀∅) := ChainClosure.union fun a h => False.rec h
simpa using this
#align chain_closure_empty chainClosure_empty
theorem chainClosure_maxChain : ChainClosure r (maxChain r) :=
ChainClosure.union fun _ => id
#align chain_closure_max_chain chainClosure_maxChain
private theorem chainClosure_succ_total_aux (hc₁ : ChainClosure r c₁)
(h : ∀ ⦃c₃⦄, ChainClosure r c₃ → c₃ ⊆ c₂ → c₂ = c₃ ∨ SuccChain r c₃ ⊆ c₂) :
SuccChain r c₂ ⊆ c₁ ∨ c₁ ⊆ c₂ := by
induction hc₁ with
| @succ c₃ hc₃ ih =>
cases' ih with ih ih
· exact Or.inl (ih.trans subset_succChain)
· exact (h hc₃ ih).imp_left fun (h : c₂ = c₃) => h ▸ Subset.rfl
| union _ ih =>
refine or_iff_not_imp_left.2 fun hn => sUnion_subset fun a ha => ?_
exact (ih a ha).resolve_left fun h => hn <| h.trans <| subset_sUnion_of_mem ha
private theorem chainClosure_succ_total (hc₁ : ChainClosure r c₁) (hc₂ : ChainClosure r c₂)
(h : c₁ ⊆ c₂) : c₂ = c₁ ∨ SuccChain r c₁ ⊆ c₂ := by
induction hc₂ generalizing c₁ hc₁ with
| succ _ ih =>
refine ((chainClosure_succ_total_aux hc₁) fun c₁ => ih).imp h.antisymm' fun h₁ => ?_
obtain rfl | h₂ := ih hc₁ h₁
· exact Subset.rfl
· exact h₂.trans subset_succChain
| union _ ih =>
apply Or.imp_left h.antisymm'
apply by_contradiction
simp only [sUnion_subset_iff, not_or, not_forall, exists_prop, and_imp, forall_exists_index]
intro c₃ hc₃ h₁ h₂
obtain h | h := chainClosure_succ_total_aux hc₁ fun c₄ => ih _ hc₃
· exact h₁ (subset_succChain.trans h)
obtain h' | h' := ih c₃ hc₃ hc₁ h
· exact h₁ h'.subset
· exact h₂ (h'.trans <| subset_sUnion_of_mem hc₃)
theorem ChainClosure.total (hc₁ : ChainClosure r c₁) (hc₂ : ChainClosure r c₂) :
c₁ ⊆ c₂ ∨ c₂ ⊆ c₁ :=
((chainClosure_succ_total_aux hc₂) fun _ hc₃ => chainClosure_succ_total hc₃ hc₁).imp_left
subset_succChain.trans
#align chain_closure.total ChainClosure.total
theorem ChainClosure.succ_fixpoint (hc₁ : ChainClosure r c₁) (hc₂ : ChainClosure r c₂)
(hc : SuccChain r c₂ = c₂) : c₁ ⊆ c₂ := by
induction hc₁ with
| succ hc₁ h => exact (chainClosure_succ_total hc₁ hc₂ h).elim (fun h => h ▸ hc.subset) id
| union _ ih => exact sUnion_subset ih
#align chain_closure.succ_fixpoint ChainClosure.succ_fixpoint
theorem ChainClosure.succ_fixpoint_iff (hc : ChainClosure r c) :
SuccChain r c = c ↔ c = maxChain r :=
⟨fun h => (subset_sUnion_of_mem hc).antisymm <| chainClosure_maxChain.succ_fixpoint hc h,
fun h => subset_succChain.antisymm' <| (subset_sUnion_of_mem hc.succ).trans h.symm.subset⟩
#align chain_closure.succ_fixpoint_iff ChainClosure.succ_fixpoint_iff
| Mathlib/Order/Chain.lean | 269 | 275 | theorem ChainClosure.isChain (hc : ChainClosure r c) : IsChain r c := by |
induction hc with
| succ _ h => exact h.succ
| union hs h =>
exact fun c₁ ⟨t₁, ht₁, (hc₁ : c₁ ∈ t₁)⟩ c₂ ⟨t₂, ht₂, (hc₂ : c₂ ∈ t₂)⟩ hneq =>
((hs _ ht₁).total <| hs _ ht₂).elim (fun ht => h t₂ ht₂ (ht hc₁) hc₂ hneq) fun ht =>
h t₁ ht₁ hc₁ (ht hc₂) hneq
|
/-
Copyright (c) 2020 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Algebra.Module.BigOperators
import Mathlib.NumberTheory.Divisors
import Mathlib.Data.Nat.Squarefree
import Mathlib.Data.Nat.GCD.BigOperators
import Mathlib.Data.Nat.Factorization.Basic
import Mathlib.Tactic.ArithMult
#align_import number_theory.arithmetic_function from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3"
/-!
# Arithmetic Functions and Dirichlet Convolution
This file defines arithmetic functions, which are functions from `ℕ` to a specified type that map 0
to 0. In the literature, they are often instead defined as functions from `ℕ+`. These arithmetic
functions are endowed with a multiplication, given by Dirichlet convolution, and pointwise addition,
to form the Dirichlet ring.
## Main Definitions
* `ArithmeticFunction R` consists of functions `f : ℕ → R` such that `f 0 = 0`.
* An arithmetic function `f` `IsMultiplicative` when `x.coprime y → f (x * y) = f x * f y`.
* The pointwise operations `pmul` and `ppow` differ from the multiplication
and power instances on `ArithmeticFunction R`, which use Dirichlet multiplication.
* `ζ` is the arithmetic function such that `ζ x = 1` for `0 < x`.
* `σ k` is the arithmetic function such that `σ k x = ∑ y ∈ divisors x, y ^ k` for `0 < x`.
* `pow k` is the arithmetic function such that `pow k x = x ^ k` for `0 < x`.
* `id` is the identity arithmetic function on `ℕ`.
* `ω n` is the number of distinct prime factors of `n`.
* `Ω n` is the number of prime factors of `n` counted with multiplicity.
* `μ` is the Möbius function (spelled `moebius` in code).
## Main Results
* Several forms of Möbius inversion:
* `sum_eq_iff_sum_mul_moebius_eq` for functions to a `CommRing`
* `sum_eq_iff_sum_smul_moebius_eq` for functions to an `AddCommGroup`
* `prod_eq_iff_prod_pow_moebius_eq` for functions to a `CommGroup`
* `prod_eq_iff_prod_pow_moebius_eq_of_nonzero` for functions to a `CommGroupWithZero`
* And variants that apply when the equalities only hold on a set `S : Set ℕ` such that
`m ∣ n → n ∈ S → m ∈ S`:
* `sum_eq_iff_sum_mul_moebius_eq_on` for functions to a `CommRing`
* `sum_eq_iff_sum_smul_moebius_eq_on` for functions to an `AddCommGroup`
* `prod_eq_iff_prod_pow_moebius_eq_on` for functions to a `CommGroup`
* `prod_eq_iff_prod_pow_moebius_eq_on_of_nonzero` for functions to a `CommGroupWithZero`
## Notation
All notation is localized in the namespace `ArithmeticFunction`.
The arithmetic functions `ζ`, `σ`, `ω`, `Ω` and `μ` have Greek letter names.
In addition, there are separate locales `ArithmeticFunction.zeta` for `ζ`,
`ArithmeticFunction.sigma` for `σ`, `ArithmeticFunction.omega` for `ω`,
`ArithmeticFunction.Omega` for `Ω`, and `ArithmeticFunction.Moebius` for `μ`,
to allow for selective access to these notations.
The arithmetic function $$n \mapsto \prod_{p \mid n} f(p)$$ is given custom notation
`∏ᵖ p ∣ n, f p` when applied to `n`.
## Tags
arithmetic functions, dirichlet convolution, divisors
-/
open Finset
open Nat
variable (R : Type*)
/-- An arithmetic function is a function from `ℕ` that maps 0 to 0. In the literature, they are
often instead defined as functions from `ℕ+`. Multiplication on `ArithmeticFunctions` is by
Dirichlet convolution. -/
def ArithmeticFunction [Zero R] :=
ZeroHom ℕ R
#align nat.arithmetic_function ArithmeticFunction
instance ArithmeticFunction.zero [Zero R] : Zero (ArithmeticFunction R) :=
inferInstanceAs (Zero (ZeroHom ℕ R))
instance [Zero R] : Inhabited (ArithmeticFunction R) := inferInstanceAs (Inhabited (ZeroHom ℕ R))
variable {R}
namespace ArithmeticFunction
section Zero
variable [Zero R]
-- porting note: used to be `CoeFun`
instance : FunLike (ArithmeticFunction R) ℕ R :=
inferInstanceAs (FunLike (ZeroHom ℕ R) ℕ R)
@[simp]
theorem toFun_eq (f : ArithmeticFunction R) : f.toFun = f := rfl
#align nat.arithmetic_function.to_fun_eq ArithmeticFunction.toFun_eq
@[simp]
theorem coe_mk (f : ℕ → R) (hf) : @DFunLike.coe (ArithmeticFunction R) _ _ _
(ZeroHom.mk f hf) = f := rfl
@[simp]
theorem map_zero {f : ArithmeticFunction R} : f 0 = 0 :=
ZeroHom.map_zero' f
#align nat.arithmetic_function.map_zero ArithmeticFunction.map_zero
theorem coe_inj {f g : ArithmeticFunction R} : (f : ℕ → R) = g ↔ f = g :=
DFunLike.coe_fn_eq
#align nat.arithmetic_function.coe_inj ArithmeticFunction.coe_inj
@[simp]
theorem zero_apply {x : ℕ} : (0 : ArithmeticFunction R) x = 0 :=
ZeroHom.zero_apply x
#align nat.arithmetic_function.zero_apply ArithmeticFunction.zero_apply
@[ext]
theorem ext ⦃f g : ArithmeticFunction R⦄ (h : ∀ x, f x = g x) : f = g :=
ZeroHom.ext h
#align nat.arithmetic_function.ext ArithmeticFunction.ext
theorem ext_iff {f g : ArithmeticFunction R} : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align nat.arithmetic_function.ext_iff ArithmeticFunction.ext_iff
section One
variable [One R]
instance one : One (ArithmeticFunction R) :=
⟨⟨fun x => ite (x = 1) 1 0, rfl⟩⟩
theorem one_apply {x : ℕ} : (1 : ArithmeticFunction R) x = ite (x = 1) 1 0 :=
rfl
#align nat.arithmetic_function.one_apply ArithmeticFunction.one_apply
@[simp]
theorem one_one : (1 : ArithmeticFunction R) 1 = 1 :=
rfl
#align nat.arithmetic_function.one_one ArithmeticFunction.one_one
@[simp]
theorem one_apply_ne {x : ℕ} (h : x ≠ 1) : (1 : ArithmeticFunction R) x = 0 :=
if_neg h
#align nat.arithmetic_function.one_apply_ne ArithmeticFunction.one_apply_ne
end One
end Zero
/-- Coerce an arithmetic function with values in `ℕ` to one with values in `R`. We cannot inline
this in `natCoe` because it gets unfolded too much. -/
@[coe] -- Porting note: added `coe` tag.
def natToArithmeticFunction [AddMonoidWithOne R] :
(ArithmeticFunction ℕ) → (ArithmeticFunction R) :=
fun f => ⟨fun n => ↑(f n), by simp⟩
instance natCoe [AddMonoidWithOne R] : Coe (ArithmeticFunction ℕ) (ArithmeticFunction R) :=
⟨natToArithmeticFunction⟩
#align nat.arithmetic_function.nat_coe ArithmeticFunction.natCoe
@[simp]
theorem natCoe_nat (f : ArithmeticFunction ℕ) : natToArithmeticFunction f = f :=
ext fun _ => cast_id _
#align nat.arithmetic_function.nat_coe_nat ArithmeticFunction.natCoe_nat
@[simp]
theorem natCoe_apply [AddMonoidWithOne R] {f : ArithmeticFunction ℕ} {x : ℕ} :
(f : ArithmeticFunction R) x = f x :=
rfl
#align nat.arithmetic_function.nat_coe_apply ArithmeticFunction.natCoe_apply
/-- Coerce an arithmetic function with values in `ℤ` to one with values in `R`. We cannot inline
this in `intCoe` because it gets unfolded too much. -/
@[coe]
def ofInt [AddGroupWithOne R] :
(ArithmeticFunction ℤ) → (ArithmeticFunction R) :=
fun f => ⟨fun n => ↑(f n), by simp⟩
instance intCoe [AddGroupWithOne R] : Coe (ArithmeticFunction ℤ) (ArithmeticFunction R) :=
⟨ofInt⟩
#align nat.arithmetic_function.int_coe ArithmeticFunction.intCoe
@[simp]
theorem intCoe_int (f : ArithmeticFunction ℤ) : ofInt f = f :=
ext fun _ => Int.cast_id
#align nat.arithmetic_function.int_coe_int ArithmeticFunction.intCoe_int
@[simp]
theorem intCoe_apply [AddGroupWithOne R] {f : ArithmeticFunction ℤ} {x : ℕ} :
(f : ArithmeticFunction R) x = f x := rfl
#align nat.arithmetic_function.int_coe_apply ArithmeticFunction.intCoe_apply
@[simp]
theorem coe_coe [AddGroupWithOne R] {f : ArithmeticFunction ℕ} :
((f : ArithmeticFunction ℤ) : ArithmeticFunction R) = (f : ArithmeticFunction R) := by
ext
simp
#align nat.arithmetic_function.coe_coe ArithmeticFunction.coe_coe
@[simp]
theorem natCoe_one [AddMonoidWithOne R] :
((1 : ArithmeticFunction ℕ) : ArithmeticFunction R) = 1 := by
ext n
simp [one_apply]
#align nat.arithmetic_function.nat_coe_one ArithmeticFunction.natCoe_one
@[simp]
theorem intCoe_one [AddGroupWithOne R] : ((1 : ArithmeticFunction ℤ) :
ArithmeticFunction R) = 1 := by
ext n
simp [one_apply]
#align nat.arithmetic_function.int_coe_one ArithmeticFunction.intCoe_one
section AddMonoid
variable [AddMonoid R]
instance add : Add (ArithmeticFunction R) :=
⟨fun f g => ⟨fun n => f n + g n, by simp⟩⟩
@[simp]
theorem add_apply {f g : ArithmeticFunction R} {n : ℕ} : (f + g) n = f n + g n :=
rfl
#align nat.arithmetic_function.add_apply ArithmeticFunction.add_apply
instance instAddMonoid : AddMonoid (ArithmeticFunction R) :=
{ ArithmeticFunction.zero R,
ArithmeticFunction.add with
add_assoc := fun _ _ _ => ext fun _ => add_assoc _ _ _
zero_add := fun _ => ext fun _ => zero_add _
add_zero := fun _ => ext fun _ => add_zero _
nsmul := nsmulRec }
#align nat.arithmetic_function.add_monoid ArithmeticFunction.instAddMonoid
end AddMonoid
instance instAddMonoidWithOne [AddMonoidWithOne R] : AddMonoidWithOne (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoid,
ArithmeticFunction.one with
natCast := fun n => ⟨fun x => if x = 1 then (n : R) else 0, by simp⟩
natCast_zero := by ext; simp
natCast_succ := fun n => by ext x; by_cases h : x = 1 <;> simp [h] }
#align nat.arithmetic_function.add_monoid_with_one ArithmeticFunction.instAddMonoidWithOne
instance instAddCommMonoid [AddCommMonoid R] : AddCommMonoid (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoid with add_comm := fun _ _ => ext fun _ => add_comm _ _ }
instance [NegZeroClass R] : Neg (ArithmeticFunction R) where
neg f := ⟨fun n => -f n, by simp⟩
instance [AddGroup R] : AddGroup (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoid with
add_left_neg := fun _ => ext fun _ => add_left_neg _
zsmul := zsmulRec }
instance [AddCommGroup R] : AddCommGroup (ArithmeticFunction R) :=
{ show AddGroup (ArithmeticFunction R) by infer_instance with
add_comm := fun _ _ ↦ add_comm _ _ }
section SMul
variable {M : Type*} [Zero R] [AddCommMonoid M] [SMul R M]
/-- The Dirichlet convolution of two arithmetic functions `f` and `g` is another arithmetic function
such that `(f * g) n` is the sum of `f x * g y` over all `(x,y)` such that `x * y = n`. -/
instance : SMul (ArithmeticFunction R) (ArithmeticFunction M) :=
⟨fun f g => ⟨fun n => ∑ x ∈ divisorsAntidiagonal n, f x.fst • g x.snd, by simp⟩⟩
@[simp]
theorem smul_apply {f : ArithmeticFunction R} {g : ArithmeticFunction M} {n : ℕ} :
(f • g) n = ∑ x ∈ divisorsAntidiagonal n, f x.fst • g x.snd :=
rfl
#align nat.arithmetic_function.smul_apply ArithmeticFunction.smul_apply
end SMul
/-- The Dirichlet convolution of two arithmetic functions `f` and `g` is another arithmetic function
such that `(f * g) n` is the sum of `f x * g y` over all `(x,y)` such that `x * y = n`. -/
instance [Semiring R] : Mul (ArithmeticFunction R) :=
⟨(· • ·)⟩
@[simp]
theorem mul_apply [Semiring R] {f g : ArithmeticFunction R} {n : ℕ} :
(f * g) n = ∑ x ∈ divisorsAntidiagonal n, f x.fst * g x.snd :=
rfl
#align nat.arithmetic_function.mul_apply ArithmeticFunction.mul_apply
theorem mul_apply_one [Semiring R] {f g : ArithmeticFunction R} : (f * g) 1 = f 1 * g 1 := by simp
#align nat.arithmetic_function.mul_apply_one ArithmeticFunction.mul_apply_one
@[simp, norm_cast]
theorem natCoe_mul [Semiring R] {f g : ArithmeticFunction ℕ} :
(↑(f * g) : ArithmeticFunction R) = f * g := by
ext n
simp
#align nat.arithmetic_function.nat_coe_mul ArithmeticFunction.natCoe_mul
@[simp, norm_cast]
theorem intCoe_mul [Ring R] {f g : ArithmeticFunction ℤ} :
(↑(f * g) : ArithmeticFunction R) = ↑f * g := by
ext n
simp
#align nat.arithmetic_function.int_coe_mul ArithmeticFunction.intCoe_mul
section Module
variable {M : Type*} [Semiring R] [AddCommMonoid M] [Module R M]
theorem mul_smul' (f g : ArithmeticFunction R) (h : ArithmeticFunction M) :
(f * g) • h = f • g • h := by
ext n
simp only [mul_apply, smul_apply, sum_smul, mul_smul, smul_sum, Finset.sum_sigma']
apply Finset.sum_nbij' (fun ⟨⟨_i, j⟩, ⟨k, l⟩⟩ ↦ ⟨(k, l * j), (l, j)⟩)
(fun ⟨⟨i, _j⟩, ⟨k, l⟩⟩ ↦ ⟨(i * k, l), (i, k)⟩) <;> aesop (add simp mul_assoc)
#align nat.arithmetic_function.mul_smul' ArithmeticFunction.mul_smul'
theorem one_smul' (b : ArithmeticFunction M) : (1 : ArithmeticFunction R) • b = b := by
ext x
rw [smul_apply]
by_cases x0 : x = 0
· simp [x0]
have h : {(1, x)} ⊆ divisorsAntidiagonal x := by simp [x0]
rw [← sum_subset h]
· simp
intro y ymem ynmem
have y1ne : y.fst ≠ 1 := by
intro con
simp only [Con, mem_divisorsAntidiagonal, one_mul, Ne] at ymem
simp only [mem_singleton, Prod.ext_iff] at ynmem
-- Porting note: `tauto` worked from here.
cases y
subst con
simp only [true_and, one_mul, x0, not_false_eq_true, and_true] at ynmem ymem
tauto
simp [y1ne]
#align nat.arithmetic_function.one_smul' ArithmeticFunction.one_smul'
end Module
section Semiring
variable [Semiring R]
instance instMonoid : Monoid (ArithmeticFunction R) :=
{ one := One.one
mul := Mul.mul
one_mul := one_smul'
mul_one := fun f => by
ext x
rw [mul_apply]
by_cases x0 : x = 0
· simp [x0]
have h : {(x, 1)} ⊆ divisorsAntidiagonal x := by simp [x0]
rw [← sum_subset h]
· simp
intro y ymem ynmem
have y2ne : y.snd ≠ 1 := by
intro con
cases y; subst con -- Porting note: added
simp only [Con, mem_divisorsAntidiagonal, mul_one, Ne] at ymem
simp only [mem_singleton, Prod.ext_iff] at ynmem
tauto
simp [y2ne]
mul_assoc := mul_smul' }
#align nat.arithmetic_function.monoid ArithmeticFunction.instMonoid
instance instSemiring : Semiring (ArithmeticFunction R) :=
-- Porting note: I reorganized this instance
{ ArithmeticFunction.instAddMonoidWithOne,
ArithmeticFunction.instMonoid,
ArithmeticFunction.instAddCommMonoid with
zero_mul := fun f => by
ext
simp only [mul_apply, zero_mul, sum_const_zero, zero_apply]
mul_zero := fun f => by
ext
simp only [mul_apply, sum_const_zero, mul_zero, zero_apply]
left_distrib := fun a b c => by
ext
simp only [← sum_add_distrib, mul_add, mul_apply, add_apply]
right_distrib := fun a b c => by
ext
simp only [← sum_add_distrib, add_mul, mul_apply, add_apply] }
#align nat.arithmetic_function.semiring ArithmeticFunction.instSemiring
end Semiring
instance [CommSemiring R] : CommSemiring (ArithmeticFunction R) :=
{ ArithmeticFunction.instSemiring with
mul_comm := fun f g => by
ext
rw [mul_apply, ← map_swap_divisorsAntidiagonal, sum_map]
simp [mul_comm] }
instance [CommRing R] : CommRing (ArithmeticFunction R) :=
{ ArithmeticFunction.instSemiring with
add_left_neg := add_left_neg
mul_comm := mul_comm
zsmul := (· • ·) }
instance {M : Type*} [Semiring R] [AddCommMonoid M] [Module R M] :
Module (ArithmeticFunction R) (ArithmeticFunction M) where
one_smul := one_smul'
mul_smul := mul_smul'
smul_add r x y := by
ext
simp only [sum_add_distrib, smul_add, smul_apply, add_apply]
smul_zero r := by
ext
simp only [smul_apply, sum_const_zero, smul_zero, zero_apply]
add_smul r s x := by
ext
simp only [add_smul, sum_add_distrib, smul_apply, add_apply]
zero_smul r := by
ext
simp only [smul_apply, sum_const_zero, zero_smul, zero_apply]
section Zeta
/-- `ζ 0 = 0`, otherwise `ζ x = 1`. The Dirichlet Series is the Riemann `ζ`. -/
def zeta : ArithmeticFunction ℕ :=
⟨fun x => ite (x = 0) 0 1, rfl⟩
#align nat.arithmetic_function.zeta ArithmeticFunction.zeta
@[inherit_doc]
scoped[ArithmeticFunction] notation "ζ" => ArithmeticFunction.zeta
@[inherit_doc]
scoped[ArithmeticFunction.zeta] notation "ζ" => ArithmeticFunction.zeta
@[simp]
theorem zeta_apply {x : ℕ} : ζ x = if x = 0 then 0 else 1 :=
rfl
#align nat.arithmetic_function.zeta_apply ArithmeticFunction.zeta_apply
theorem zeta_apply_ne {x : ℕ} (h : x ≠ 0) : ζ x = 1 :=
if_neg h
#align nat.arithmetic_function.zeta_apply_ne ArithmeticFunction.zeta_apply_ne
-- Porting note: removed `@[simp]`, LHS not in normal form
theorem coe_zeta_smul_apply {M} [Semiring R] [AddCommMonoid M] [Module R M]
{f : ArithmeticFunction M} {x : ℕ} :
((↑ζ : ArithmeticFunction R) • f) x = ∑ i ∈ divisors x, f i := by
rw [smul_apply]
trans ∑ i ∈ divisorsAntidiagonal x, f i.snd
· refine sum_congr rfl fun i hi => ?_
rcases mem_divisorsAntidiagonal.1 hi with ⟨rfl, h⟩
rw [natCoe_apply, zeta_apply_ne (left_ne_zero_of_mul h), cast_one, one_smul]
· rw [← map_div_left_divisors, sum_map, Function.Embedding.coeFn_mk]
#align nat.arithmetic_function.coe_zeta_smul_apply ArithmeticFunction.coe_zeta_smul_apply
-- Porting note: removed `@[simp]` to make the linter happy.
theorem coe_zeta_mul_apply [Semiring R] {f : ArithmeticFunction R} {x : ℕ} :
(↑ζ * f) x = ∑ i ∈ divisors x, f i :=
coe_zeta_smul_apply
#align nat.arithmetic_function.coe_zeta_mul_apply ArithmeticFunction.coe_zeta_mul_apply
-- Porting note: removed `@[simp]` to make the linter happy.
theorem coe_mul_zeta_apply [Semiring R] {f : ArithmeticFunction R} {x : ℕ} :
(f * ζ) x = ∑ i ∈ divisors x, f i := by
rw [mul_apply]
trans ∑ i ∈ divisorsAntidiagonal x, f i.1
· refine sum_congr rfl fun i hi => ?_
rcases mem_divisorsAntidiagonal.1 hi with ⟨rfl, h⟩
rw [natCoe_apply, zeta_apply_ne (right_ne_zero_of_mul h), cast_one, mul_one]
· rw [← map_div_right_divisors, sum_map, Function.Embedding.coeFn_mk]
#align nat.arithmetic_function.coe_mul_zeta_apply ArithmeticFunction.coe_mul_zeta_apply
theorem zeta_mul_apply {f : ArithmeticFunction ℕ} {x : ℕ} : (ζ * f) x = ∑ i ∈ divisors x, f i :=
coe_zeta_mul_apply
-- Porting note: was `by rw [← nat_coe_nat ζ, coe_zeta_mul_apply]`. Is this `theorem` obsolete?
#align nat.arithmetic_function.zeta_mul_apply ArithmeticFunction.zeta_mul_apply
theorem mul_zeta_apply {f : ArithmeticFunction ℕ} {x : ℕ} : (f * ζ) x = ∑ i ∈ divisors x, f i :=
coe_mul_zeta_apply
-- Porting note: was `by rw [← natCoe_nat ζ, coe_mul_zeta_apply]`. Is this `theorem` obsolete=
#align nat.arithmetic_function.mul_zeta_apply ArithmeticFunction.mul_zeta_apply
end Zeta
open ArithmeticFunction
section Pmul
/-- This is the pointwise product of `ArithmeticFunction`s. -/
def pmul [MulZeroClass R] (f g : ArithmeticFunction R) : ArithmeticFunction R :=
⟨fun x => f x * g x, by simp⟩
#align nat.arithmetic_function.pmul ArithmeticFunction.pmul
@[simp]
theorem pmul_apply [MulZeroClass R] {f g : ArithmeticFunction R} {x : ℕ} : f.pmul g x = f x * g x :=
rfl
#align nat.arithmetic_function.pmul_apply ArithmeticFunction.pmul_apply
theorem pmul_comm [CommMonoidWithZero R] (f g : ArithmeticFunction R) : f.pmul g = g.pmul f := by
ext
simp [mul_comm]
#align nat.arithmetic_function.pmul_comm ArithmeticFunction.pmul_comm
lemma pmul_assoc [CommMonoidWithZero R] (f₁ f₂ f₃ : ArithmeticFunction R) :
pmul (pmul f₁ f₂) f₃ = pmul f₁ (pmul f₂ f₃) := by
ext
simp only [pmul_apply, mul_assoc]
section NonAssocSemiring
variable [NonAssocSemiring R]
@[simp]
theorem pmul_zeta (f : ArithmeticFunction R) : f.pmul ↑ζ = f := by
ext x
cases x <;> simp [Nat.succ_ne_zero]
#align nat.arithmetic_function.pmul_zeta ArithmeticFunction.pmul_zeta
@[simp]
theorem zeta_pmul (f : ArithmeticFunction R) : (ζ : ArithmeticFunction R).pmul f = f := by
ext x
cases x <;> simp [Nat.succ_ne_zero]
#align nat.arithmetic_function.zeta_pmul ArithmeticFunction.zeta_pmul
end NonAssocSemiring
variable [Semiring R]
/-- This is the pointwise power of `ArithmeticFunction`s. -/
def ppow (f : ArithmeticFunction R) (k : ℕ) : ArithmeticFunction R :=
if h0 : k = 0 then ζ else ⟨fun x ↦ f x ^ k, by simp_rw [map_zero, zero_pow h0]⟩
#align nat.arithmetic_function.ppow ArithmeticFunction.ppow
@[simp]
theorem ppow_zero {f : ArithmeticFunction R} : f.ppow 0 = ζ := by rw [ppow, dif_pos rfl]
#align nat.arithmetic_function.ppow_zero ArithmeticFunction.ppow_zero
@[simp]
theorem ppow_apply {f : ArithmeticFunction R} {k x : ℕ} (kpos : 0 < k) : f.ppow k x = f x ^ k := by
rw [ppow, dif_neg (Nat.ne_of_gt kpos)]
rfl
#align nat.arithmetic_function.ppow_apply ArithmeticFunction.ppow_apply
theorem ppow_succ' {f : ArithmeticFunction R} {k : ℕ} : f.ppow (k + 1) = f.pmul (f.ppow k) := by
ext x
rw [ppow_apply (Nat.succ_pos k), _root_.pow_succ']
induction k <;> simp
#align nat.arithmetic_function.ppow_succ ArithmeticFunction.ppow_succ'
theorem ppow_succ {f : ArithmeticFunction R} {k : ℕ} {kpos : 0 < k} :
f.ppow (k + 1) = (f.ppow k).pmul f := by
ext x
rw [ppow_apply (Nat.succ_pos k), _root_.pow_succ]
induction k <;> simp
#align nat.arithmetic_function.ppow_succ' ArithmeticFunction.ppow_succ
end Pmul
section Pdiv
/-- This is the pointwise division of `ArithmeticFunction`s. -/
def pdiv [GroupWithZero R] (f g : ArithmeticFunction R) : ArithmeticFunction R :=
⟨fun n => f n / g n, by simp only [map_zero, ne_eq, not_true, div_zero]⟩
@[simp]
theorem pdiv_apply [GroupWithZero R] (f g : ArithmeticFunction R) (n : ℕ) :
pdiv f g n = f n / g n := rfl
/-- This result only holds for `DivisionSemiring`s instead of `GroupWithZero`s because zeta takes
values in ℕ, and hence the coercion requires an `AddMonoidWithOne`. TODO: Generalise zeta -/
@[simp]
theorem pdiv_zeta [DivisionSemiring R] (f : ArithmeticFunction R) :
pdiv f zeta = f := by
ext n
cases n <;> simp [succ_ne_zero]
end Pdiv
section ProdPrimeFactors
/-- The map $n \mapsto \prod_{p \mid n} f(p)$ as an arithmetic function -/
def prodPrimeFactors [CommMonoidWithZero R] (f : ℕ → R) : ArithmeticFunction R where
toFun d := if d = 0 then 0 else ∏ p ∈ d.primeFactors, f p
map_zero' := if_pos rfl
open Batteries.ExtendedBinder
/-- `∏ᵖ p ∣ n, f p` is custom notation for `prodPrimeFactors f n` -/
scoped syntax (name := bigproddvd) "∏ᵖ " extBinder " ∣ " term ", " term:67 : term
scoped macro_rules (kind := bigproddvd)
| `(∏ᵖ $x:ident ∣ $n, $r) => `(prodPrimeFactors (fun $x ↦ $r) $n)
@[simp]
theorem prodPrimeFactors_apply [CommMonoidWithZero R] {f: ℕ → R} {n : ℕ} (hn : n ≠ 0) :
∏ᵖ p ∣ n, f p = ∏ p ∈ n.primeFactors, f p :=
if_neg hn
end ProdPrimeFactors
/-- Multiplicative functions -/
def IsMultiplicative [MonoidWithZero R] (f : ArithmeticFunction R) : Prop :=
f 1 = 1 ∧ ∀ {m n : ℕ}, m.Coprime n → f (m * n) = f m * f n
#align nat.arithmetic_function.is_multiplicative ArithmeticFunction.IsMultiplicative
namespace IsMultiplicative
section MonoidWithZero
variable [MonoidWithZero R]
@[simp, arith_mult]
theorem map_one {f : ArithmeticFunction R} (h : f.IsMultiplicative) : f 1 = 1 :=
h.1
#align nat.arithmetic_function.is_multiplicative.map_one ArithmeticFunction.IsMultiplicative.map_one
@[simp]
theorem map_mul_of_coprime {f : ArithmeticFunction R} (hf : f.IsMultiplicative) {m n : ℕ}
(h : m.Coprime n) : f (m * n) = f m * f n :=
hf.2 h
#align nat.arithmetic_function.is_multiplicative.map_mul_of_coprime ArithmeticFunction.IsMultiplicative.map_mul_of_coprime
end MonoidWithZero
theorem map_prod {ι : Type*} [CommMonoidWithZero R] (g : ι → ℕ) {f : ArithmeticFunction R}
(hf : f.IsMultiplicative) (s : Finset ι) (hs : (s : Set ι).Pairwise (Coprime on g)) :
f (∏ i ∈ s, g i) = ∏ i ∈ s, f (g i) := by
classical
induction' s using Finset.induction_on with a s has ih hs
· simp [hf]
rw [coe_insert, Set.pairwise_insert_of_symmetric (Coprime.symmetric.comap g)] at hs
rw [prod_insert has, prod_insert has, hf.map_mul_of_coprime, ih hs.1]
exact .prod_right fun i hi => hs.2 _ hi (hi.ne_of_not_mem has).symm
#align nat.arithmetic_function.is_multiplicative.map_prod ArithmeticFunction.IsMultiplicative.map_prod
theorem map_prod_of_prime [CommSemiring R] {f : ArithmeticFunction R}
(h_mult : ArithmeticFunction.IsMultiplicative f)
(t : Finset ℕ) (ht : ∀ p ∈ t, p.Prime) :
f (∏ a ∈ t, a) = ∏ a ∈ t, f a :=
map_prod _ h_mult t fun x hx y hy hxy => (coprime_primes (ht x hx) (ht y hy)).mpr hxy
theorem map_prod_of_subset_primeFactors [CommSemiring R] {f : ArithmeticFunction R}
(h_mult : ArithmeticFunction.IsMultiplicative f) (l : ℕ)
(t : Finset ℕ) (ht : t ⊆ l.primeFactors) :
f (∏ a ∈ t, a) = ∏ a ∈ t, f a :=
map_prod_of_prime h_mult t fun _ a => prime_of_mem_primeFactors (ht a)
@[arith_mult]
theorem natCast {f : ArithmeticFunction ℕ} [Semiring R] (h : f.IsMultiplicative) :
IsMultiplicative (f : ArithmeticFunction R) :=
-- Porting note: was `by simp [cop, h]`
⟨by simp [h], fun {m n} cop => by simp [h.2 cop]⟩
#align nat.arithmetic_function.is_multiplicative.nat_cast ArithmeticFunction.IsMultiplicative.natCast
@[deprecated (since := "2024-04-17")]
alias nat_cast := natCast
@[arith_mult]
theorem intCast {f : ArithmeticFunction ℤ} [Ring R] (h : f.IsMultiplicative) :
IsMultiplicative (f : ArithmeticFunction R) :=
-- Porting note: was `by simp [cop, h]`
⟨by simp [h], fun {m n} cop => by simp [h.2 cop]⟩
#align nat.arithmetic_function.is_multiplicative.int_cast ArithmeticFunction.IsMultiplicative.intCast
@[deprecated (since := "2024-04-17")]
alias int_cast := intCast
@[arith_mult]
theorem mul [CommSemiring R] {f g : ArithmeticFunction R} (hf : f.IsMultiplicative)
(hg : g.IsMultiplicative) : IsMultiplicative (f * g) := by
refine ⟨by simp [hf.1, hg.1], ?_⟩
simp only [mul_apply]
intro m n cop
rw [sum_mul_sum, ← sum_product']
symm
apply sum_nbij fun ((i, j), k, l) ↦ (i * k, j * l)
· rintro ⟨⟨a1, a2⟩, ⟨b1, b2⟩⟩ h
simp only [mem_divisorsAntidiagonal, Ne, mem_product] at h
rcases h with ⟨⟨rfl, ha⟩, ⟨rfl, hb⟩⟩
simp only [mem_divisorsAntidiagonal, Nat.mul_eq_zero, Ne]
constructor
· ring
rw [Nat.mul_eq_zero] at *
apply not_or_of_not ha hb
· simp only [Set.InjOn, mem_coe, mem_divisorsAntidiagonal, Ne, mem_product, Prod.mk.inj_iff]
rintro ⟨⟨a1, a2⟩, ⟨b1, b2⟩⟩ ⟨⟨rfl, ha⟩, ⟨rfl, hb⟩⟩ ⟨⟨c1, c2⟩, ⟨d1, d2⟩⟩ hcd h
simp only [Prod.mk.inj_iff] at h
ext <;> dsimp only
· trans Nat.gcd (a1 * a2) (a1 * b1)
· rw [Nat.gcd_mul_left, cop.coprime_mul_left.coprime_mul_right_right.gcd_eq_one, mul_one]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.1.1, h.1, Nat.gcd_mul_left,
cop.coprime_mul_left.coprime_mul_right_right.gcd_eq_one, mul_one]
· trans Nat.gcd (a1 * a2) (a2 * b2)
· rw [mul_comm, Nat.gcd_mul_left, cop.coprime_mul_right.coprime_mul_left_right.gcd_eq_one,
mul_one]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.1.1, h.2, mul_comm, Nat.gcd_mul_left,
cop.coprime_mul_right.coprime_mul_left_right.gcd_eq_one, mul_one]
· trans Nat.gcd (b1 * b2) (a1 * b1)
· rw [mul_comm, Nat.gcd_mul_right,
cop.coprime_mul_right.coprime_mul_left_right.symm.gcd_eq_one, one_mul]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.2.1, h.1, mul_comm c1 d1, Nat.gcd_mul_left,
cop.coprime_mul_right.coprime_mul_left_right.symm.gcd_eq_one, mul_one]
· trans Nat.gcd (b1 * b2) (a2 * b2)
· rw [Nat.gcd_mul_right, cop.coprime_mul_left.coprime_mul_right_right.symm.gcd_eq_one,
one_mul]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.2.1, h.2, Nat.gcd_mul_right,
cop.coprime_mul_left.coprime_mul_right_right.symm.gcd_eq_one, one_mul]
· simp only [Set.SurjOn, Set.subset_def, mem_coe, mem_divisorsAntidiagonal, Ne, mem_product,
Set.mem_image, exists_prop, Prod.mk.inj_iff]
rintro ⟨b1, b2⟩ h
dsimp at h
use ((b1.gcd m, b2.gcd m), (b1.gcd n, b2.gcd n))
rw [← cop.gcd_mul _, ← cop.gcd_mul _, ← h.1, Nat.gcd_mul_gcd_of_coprime_of_mul_eq_mul cop h.1,
Nat.gcd_mul_gcd_of_coprime_of_mul_eq_mul cop.symm _]
· rw [Nat.mul_eq_zero, not_or] at h
simp [h.2.1, h.2.2]
rw [mul_comm n m, h.1]
· simp only [mem_divisorsAntidiagonal, Ne, mem_product]
rintro ⟨⟨a1, a2⟩, ⟨b1, b2⟩⟩ ⟨⟨rfl, ha⟩, ⟨rfl, hb⟩⟩
dsimp only
rw [hf.map_mul_of_coprime cop.coprime_mul_right.coprime_mul_right_right,
hg.map_mul_of_coprime cop.coprime_mul_left.coprime_mul_left_right]
ring
#align nat.arithmetic_function.is_multiplicative.mul ArithmeticFunction.IsMultiplicative.mul
@[arith_mult]
theorem pmul [CommSemiring R] {f g : ArithmeticFunction R} (hf : f.IsMultiplicative)
(hg : g.IsMultiplicative) : IsMultiplicative (f.pmul g) :=
⟨by simp [hf, hg], fun {m n} cop => by
simp only [pmul_apply, hf.map_mul_of_coprime cop, hg.map_mul_of_coprime cop]
ring⟩
#align nat.arithmetic_function.is_multiplicative.pmul ArithmeticFunction.IsMultiplicative.pmul
@[arith_mult]
theorem pdiv [CommGroupWithZero R] {f g : ArithmeticFunction R} (hf : IsMultiplicative f)
(hg : IsMultiplicative g) : IsMultiplicative (pdiv f g) :=
⟨ by simp [hf, hg], fun {m n} cop => by
simp only [pdiv_apply, map_mul_of_coprime hf cop, map_mul_of_coprime hg cop,
div_eq_mul_inv, mul_inv]
apply mul_mul_mul_comm ⟩
/-- For any multiplicative function `f` and any `n > 0`,
we can evaluate `f n` by evaluating `f` at `p ^ k` over the factorization of `n` -/
nonrec -- Porting note: added
theorem multiplicative_factorization [CommMonoidWithZero R] (f : ArithmeticFunction R)
(hf : f.IsMultiplicative) {n : ℕ} (hn : n ≠ 0) :
f n = n.factorization.prod fun p k => f (p ^ k) :=
multiplicative_factorization f (fun _ _ => hf.2) hf.1 hn
#align nat.arithmetic_function.is_multiplicative.multiplicative_factorization ArithmeticFunction.IsMultiplicative.multiplicative_factorization
/-- A recapitulation of the definition of multiplicative that is simpler for proofs -/
theorem iff_ne_zero [MonoidWithZero R] {f : ArithmeticFunction R} :
IsMultiplicative f ↔
f 1 = 1 ∧ ∀ {m n : ℕ}, m ≠ 0 → n ≠ 0 → m.Coprime n → f (m * n) = f m * f n := by
refine and_congr_right' (forall₂_congr fun m n => ⟨fun h _ _ => h, fun h hmn => ?_⟩)
rcases eq_or_ne m 0 with (rfl | hm)
· simp
rcases eq_or_ne n 0 with (rfl | hn)
· simp
exact h hm hn hmn
#align nat.arithmetic_function.is_multiplicative.iff_ne_zero ArithmeticFunction.IsMultiplicative.iff_ne_zero
/-- Two multiplicative functions `f` and `g` are equal if and only if
they agree on prime powers -/
theorem eq_iff_eq_on_prime_powers [CommMonoidWithZero R] (f : ArithmeticFunction R)
(hf : f.IsMultiplicative) (g : ArithmeticFunction R) (hg : g.IsMultiplicative) :
f = g ↔ ∀ p i : ℕ, Nat.Prime p → f (p ^ i) = g (p ^ i) := by
constructor
· intro h p i _
rw [h]
intro h
ext n
by_cases hn : n = 0
· rw [hn, ArithmeticFunction.map_zero, ArithmeticFunction.map_zero]
rw [multiplicative_factorization f hf hn, multiplicative_factorization g hg hn]
exact Finset.prod_congr rfl fun p hp ↦ h p _ (Nat.prime_of_mem_primeFactors hp)
#align nat.arithmetic_function.is_multiplicative.eq_iff_eq_on_prime_powers ArithmeticFunction.IsMultiplicative.eq_iff_eq_on_prime_powers
@[arith_mult]
theorem prodPrimeFactors [CommMonoidWithZero R] (f : ℕ → R) :
IsMultiplicative (prodPrimeFactors f) := by
rw [iff_ne_zero]
simp only [ne_eq, one_ne_zero, not_false_eq_true, prodPrimeFactors_apply, primeFactors_one,
prod_empty, true_and]
intro x y hx hy hxy
have hxy₀ : x * y ≠ 0 := mul_ne_zero hx hy
rw [prodPrimeFactors_apply hxy₀, prodPrimeFactors_apply hx, prodPrimeFactors_apply hy,
Nat.primeFactors_mul hx hy, ← Finset.prod_union hxy.disjoint_primeFactors]
theorem prodPrimeFactors_add_of_squarefree [CommSemiring R] {f g : ArithmeticFunction R}
(hf : IsMultiplicative f) (hg : IsMultiplicative g) {n : ℕ} (hn : Squarefree n) :
∏ᵖ p ∣ n, (f + g) p = (f * g) n := by
rw [prodPrimeFactors_apply hn.ne_zero]
simp_rw [add_apply (f:=f) (g:=g)]
rw [Finset.prod_add, mul_apply, sum_divisorsAntidiagonal (f · * g ·),
← divisors_filter_squarefree_of_squarefree hn, sum_divisors_filter_squarefree hn.ne_zero,
factors_eq]
apply Finset.sum_congr rfl
intro t ht
rw [t.prod_val, Function.id_def,
← prod_primeFactors_sdiff_of_squarefree hn (Finset.mem_powerset.mp ht),
hf.map_prod_of_subset_primeFactors n t (Finset.mem_powerset.mp ht),
← hg.map_prod_of_subset_primeFactors n (_ \ t) Finset.sdiff_subset]
theorem lcm_apply_mul_gcd_apply [CommMonoidWithZero R] {f : ArithmeticFunction R}
(hf : f.IsMultiplicative) {x y : ℕ} :
f (x.lcm y) * f (x.gcd y) = f x * f y := by
by_cases hx : x = 0
· simp only [hx, f.map_zero, zero_mul, Nat.lcm_zero_left, Nat.gcd_zero_left]
by_cases hy : y = 0
· simp only [hy, f.map_zero, mul_zero, Nat.lcm_zero_right, Nat.gcd_zero_right, zero_mul]
have hgcd_ne_zero : x.gcd y ≠ 0 := gcd_ne_zero_left hx
have hlcm_ne_zero : x.lcm y ≠ 0 := lcm_ne_zero hx hy
have hfi_zero : ∀ {i}, f (i ^ 0) = 1 := by
intro i; rw [Nat.pow_zero, hf.1]
iterate 4 rw [hf.multiplicative_factorization f (by assumption),
Finsupp.prod_of_support_subset _ _ _ (fun _ _ => hfi_zero)
(s := (x.primeFactors ⊔ y.primeFactors))]
· rw [← Finset.prod_mul_distrib, ← Finset.prod_mul_distrib]
apply Finset.prod_congr rfl
intro p _
rcases Nat.le_or_le (x.factorization p) (y.factorization p) with h | h <;>
simp only [factorization_lcm hx hy, ge_iff_le, Finsupp.sup_apply, h, sup_of_le_right,
sup_of_le_left, inf_of_le_right, Nat.factorization_gcd hx hy, Finsupp.inf_apply,
inf_of_le_left, mul_comm]
· apply Finset.subset_union_right
· apply Finset.subset_union_left
· rw [factorization_gcd hx hy, Finsupp.support_inf, Finset.sup_eq_union]
apply Finset.inter_subset_union
· simp [factorization_lcm hx hy]
end IsMultiplicative
section SpecialFunctions
/-- The identity on `ℕ` as an `ArithmeticFunction`. -/
nonrec -- Porting note (#11445): added
def id : ArithmeticFunction ℕ :=
⟨id, rfl⟩
#align nat.arithmetic_function.id ArithmeticFunction.id
@[simp]
theorem id_apply {x : ℕ} : id x = x :=
rfl
#align nat.arithmetic_function.id_apply ArithmeticFunction.id_apply
/-- `pow k n = n ^ k`, except `pow 0 0 = 0`. -/
def pow (k : ℕ) : ArithmeticFunction ℕ :=
id.ppow k
#align nat.arithmetic_function.pow ArithmeticFunction.pow
@[simp]
theorem pow_apply {k n : ℕ} : pow k n = if k = 0 ∧ n = 0 then 0 else n ^ k := by
cases k
· simp [pow]
rename_i k -- Porting note: added
simp [pow, k.succ_pos.ne']
#align nat.arithmetic_function.pow_apply ArithmeticFunction.pow_apply
theorem pow_zero_eq_zeta : pow 0 = ζ := by
ext n
simp
#align nat.arithmetic_function.pow_zero_eq_zeta ArithmeticFunction.pow_zero_eq_zeta
/-- `σ k n` is the sum of the `k`th powers of the divisors of `n` -/
def sigma (k : ℕ) : ArithmeticFunction ℕ :=
⟨fun n => ∑ d ∈ divisors n, d ^ k, by simp⟩
#align nat.arithmetic_function.sigma ArithmeticFunction.sigma
@[inherit_doc]
scoped[ArithmeticFunction] notation "σ" => ArithmeticFunction.sigma
@[inherit_doc]
scoped[ArithmeticFunction.sigma] notation "σ" => ArithmeticFunction.sigma
theorem sigma_apply {k n : ℕ} : σ k n = ∑ d ∈ divisors n, d ^ k :=
rfl
#align nat.arithmetic_function.sigma_apply ArithmeticFunction.sigma_apply
theorem sigma_one_apply (n : ℕ) : σ 1 n = ∑ d ∈ divisors n, d := by simp [sigma_apply]
#align nat.arithmetic_function.sigma_one_apply ArithmeticFunction.sigma_one_apply
theorem sigma_zero_apply (n : ℕ) : σ 0 n = (divisors n).card := by simp [sigma_apply]
#align nat.arithmetic_function.sigma_zero_apply ArithmeticFunction.sigma_zero_apply
theorem sigma_zero_apply_prime_pow {p i : ℕ} (hp : p.Prime) : σ 0 (p ^ i) = i + 1 := by
rw [sigma_zero_apply, divisors_prime_pow hp, card_map, card_range]
#align nat.arithmetic_function.sigma_zero_apply_prime_pow ArithmeticFunction.sigma_zero_apply_prime_pow
theorem zeta_mul_pow_eq_sigma {k : ℕ} : ζ * pow k = σ k := by
ext
rw [sigma, zeta_mul_apply]
apply sum_congr rfl
intro x hx
rw [pow_apply, if_neg (not_and_of_not_right _ _)]
contrapose! hx
simp [hx]
#align nat.arithmetic_function.zeta_mul_pow_eq_sigma ArithmeticFunction.zeta_mul_pow_eq_sigma
@[arith_mult]
theorem isMultiplicative_one [MonoidWithZero R] : IsMultiplicative (1 : ArithmeticFunction R) :=
IsMultiplicative.iff_ne_zero.2
⟨by simp, by
intro m n hm _hn hmn
rcases eq_or_ne m 1 with (rfl | hm')
· simp
rw [one_apply_ne, one_apply_ne hm', zero_mul]
rw [Ne, mul_eq_one, not_and_or]
exact Or.inl hm'⟩
#align nat.arithmetic_function.is_multiplicative_one ArithmeticFunction.isMultiplicative_one
@[arith_mult]
theorem isMultiplicative_zeta : IsMultiplicative ζ :=
IsMultiplicative.iff_ne_zero.2 ⟨by simp, by simp (config := { contextual := true })⟩
#align nat.arithmetic_function.is_multiplicative_zeta ArithmeticFunction.isMultiplicative_zeta
@[arith_mult]
theorem isMultiplicative_id : IsMultiplicative ArithmeticFunction.id :=
⟨rfl, fun {_ _} _ => rfl⟩
#align nat.arithmetic_function.is_multiplicative_id ArithmeticFunction.isMultiplicative_id
@[arith_mult]
theorem IsMultiplicative.ppow [CommSemiring R] {f : ArithmeticFunction R} (hf : f.IsMultiplicative)
{k : ℕ} : IsMultiplicative (f.ppow k) := by
induction' k with k hi
· exact isMultiplicative_zeta.natCast
· rw [ppow_succ']
apply hf.pmul hi
#align nat.arithmetic_function.is_multiplicative.ppow ArithmeticFunction.IsMultiplicative.ppow
@[arith_mult]
theorem isMultiplicative_pow {k : ℕ} : IsMultiplicative (pow k) :=
isMultiplicative_id.ppow
#align nat.arithmetic_function.is_multiplicative_pow ArithmeticFunction.isMultiplicative_pow
@[arith_mult]
theorem isMultiplicative_sigma {k : ℕ} : IsMultiplicative (σ k) := by
rw [← zeta_mul_pow_eq_sigma]
apply isMultiplicative_zeta.mul isMultiplicative_pow
#align nat.arithmetic_function.is_multiplicative_sigma ArithmeticFunction.isMultiplicative_sigma
/-- `Ω n` is the number of prime factors of `n`. -/
def cardFactors : ArithmeticFunction ℕ :=
⟨fun n => n.factors.length, by simp⟩
#align nat.arithmetic_function.card_factors ArithmeticFunction.cardFactors
@[inherit_doc]
scoped[ArithmeticFunction] notation "Ω" => ArithmeticFunction.cardFactors
@[inherit_doc]
scoped[ArithmeticFunction.Omega] notation "Ω" => ArithmeticFunction.cardFactors
theorem cardFactors_apply {n : ℕ} : Ω n = n.factors.length :=
rfl
#align nat.arithmetic_function.card_factors_apply ArithmeticFunction.cardFactors_apply
lemma cardFactors_zero : Ω 0 = 0 := by simp
@[simp] theorem cardFactors_one : Ω 1 = 0 := by simp [cardFactors_apply]
#align nat.arithmetic_function.card_factors_one ArithmeticFunction.cardFactors_one
@[simp]
theorem cardFactors_eq_one_iff_prime {n : ℕ} : Ω n = 1 ↔ n.Prime := by
refine ⟨fun h => ?_, fun h => List.length_eq_one.2 ⟨n, factors_prime h⟩⟩
cases' n with n
· simp at h
rcases List.length_eq_one.1 h with ⟨x, hx⟩
rw [← prod_factors n.add_one_ne_zero, hx, List.prod_singleton]
apply prime_of_mem_factors
rw [hx, List.mem_singleton]
#align nat.arithmetic_function.card_factors_eq_one_iff_prime ArithmeticFunction.cardFactors_eq_one_iff_prime
theorem cardFactors_mul {m n : ℕ} (m0 : m ≠ 0) (n0 : n ≠ 0) : Ω (m * n) = Ω m + Ω n := by
rw [cardFactors_apply, cardFactors_apply, cardFactors_apply, ← Multiset.coe_card, ← factors_eq,
UniqueFactorizationMonoid.normalizedFactors_mul m0 n0, factors_eq, factors_eq,
Multiset.card_add, Multiset.coe_card, Multiset.coe_card]
#align nat.arithmetic_function.card_factors_mul ArithmeticFunction.cardFactors_mul
theorem cardFactors_multiset_prod {s : Multiset ℕ} (h0 : s.prod ≠ 0) :
Ω s.prod = (Multiset.map Ω s).sum := by
induction s using Multiset.induction_on with
| empty => simp
| cons ih => simp_all [cardFactors_mul, not_or]
#align nat.arithmetic_function.card_factors_multiset_prod ArithmeticFunction.cardFactors_multiset_prod
@[simp]
theorem cardFactors_apply_prime {p : ℕ} (hp : p.Prime) : Ω p = 1 :=
cardFactors_eq_one_iff_prime.2 hp
#align nat.arithmetic_function.card_factors_apply_prime ArithmeticFunction.cardFactors_apply_prime
@[simp]
theorem cardFactors_apply_prime_pow {p k : ℕ} (hp : p.Prime) : Ω (p ^ k) = k := by
rw [cardFactors_apply, hp.factors_pow, List.length_replicate]
#align nat.arithmetic_function.card_factors_apply_prime_pow ArithmeticFunction.cardFactors_apply_prime_pow
/-- `ω n` is the number of distinct prime factors of `n`. -/
def cardDistinctFactors : ArithmeticFunction ℕ :=
⟨fun n => n.factors.dedup.length, by simp⟩
#align nat.arithmetic_function.card_distinct_factors ArithmeticFunction.cardDistinctFactors
@[inherit_doc]
scoped[ArithmeticFunction] notation "ω" => ArithmeticFunction.cardDistinctFactors
@[inherit_doc]
scoped[ArithmeticFunction.omega] notation "ω" => ArithmeticFunction.cardDistinctFactors
theorem cardDistinctFactors_zero : ω 0 = 0 := by simp
#align nat.arithmetic_function.card_distinct_factors_zero ArithmeticFunction.cardDistinctFactors_zero
@[simp]
theorem cardDistinctFactors_one : ω 1 = 0 := by simp [cardDistinctFactors]
#align nat.arithmetic_function.card_distinct_factors_one ArithmeticFunction.cardDistinctFactors_one
theorem cardDistinctFactors_apply {n : ℕ} : ω n = n.factors.dedup.length :=
rfl
#align nat.arithmetic_function.card_distinct_factors_apply ArithmeticFunction.cardDistinctFactors_apply
theorem cardDistinctFactors_eq_cardFactors_iff_squarefree {n : ℕ} (h0 : n ≠ 0) :
ω n = Ω n ↔ Squarefree n := by
rw [squarefree_iff_nodup_factors h0, cardDistinctFactors_apply]
constructor <;> intro h
· rw [← n.factors.dedup_sublist.eq_of_length h]
apply List.nodup_dedup
· rw [h.dedup]
rfl
#align nat.arithmetic_function.card_distinct_factors_eq_card_factors_iff_squarefree ArithmeticFunction.cardDistinctFactors_eq_cardFactors_iff_squarefree
@[simp]
theorem cardDistinctFactors_apply_prime_pow {p k : ℕ} (hp : p.Prime) (hk : k ≠ 0) :
ω (p ^ k) = 1 := by
rw [cardDistinctFactors_apply, hp.factors_pow, List.replicate_dedup hk, List.length_singleton]
#align nat.arithmetic_function.card_distinct_factors_apply_prime_pow ArithmeticFunction.cardDistinctFactors_apply_prime_pow
@[simp]
theorem cardDistinctFactors_apply_prime {p : ℕ} (hp : p.Prime) : ω p = 1 := by
rw [← pow_one p, cardDistinctFactors_apply_prime_pow hp one_ne_zero]
#align nat.arithmetic_function.card_distinct_factors_apply_prime ArithmeticFunction.cardDistinctFactors_apply_prime
/-- `μ` is the Möbius function. If `n` is squarefree with an even number of distinct prime factors,
`μ n = 1`. If `n` is squarefree with an odd number of distinct prime factors, `μ n = -1`.
If `n` is not squarefree, `μ n = 0`. -/
def moebius : ArithmeticFunction ℤ :=
⟨fun n => if Squarefree n then (-1) ^ cardFactors n else 0, by simp⟩
#align nat.arithmetic_function.moebius ArithmeticFunction.moebius
@[inherit_doc]
scoped[ArithmeticFunction] notation "μ" => ArithmeticFunction.moebius
@[inherit_doc]
scoped[ArithmeticFunction.Moebius] notation "μ" => ArithmeticFunction.moebius
@[simp]
theorem moebius_apply_of_squarefree {n : ℕ} (h : Squarefree n) : μ n = (-1) ^ cardFactors n :=
if_pos h
#align nat.arithmetic_function.moebius_apply_of_squarefree ArithmeticFunction.moebius_apply_of_squarefree
@[simp]
theorem moebius_eq_zero_of_not_squarefree {n : ℕ} (h : ¬Squarefree n) : μ n = 0 :=
if_neg h
#align nat.arithmetic_function.moebius_eq_zero_of_not_squarefree ArithmeticFunction.moebius_eq_zero_of_not_squarefree
theorem moebius_apply_one : μ 1 = 1 := by simp
#align nat.arithmetic_function.moebius_apply_one ArithmeticFunction.moebius_apply_one
theorem moebius_ne_zero_iff_squarefree {n : ℕ} : μ n ≠ 0 ↔ Squarefree n := by
constructor <;> intro h
· contrapose! h
simp [h]
· simp [h, pow_ne_zero]
#align nat.arithmetic_function.moebius_ne_zero_iff_squarefree ArithmeticFunction.moebius_ne_zero_iff_squarefree
theorem moebius_eq_or (n : ℕ) : μ n = 0 ∨ μ n = 1 ∨ μ n = -1 := by
simp only [moebius, coe_mk]
split_ifs
· right
exact neg_one_pow_eq_or ..
· left
rfl
theorem moebius_ne_zero_iff_eq_or {n : ℕ} : μ n ≠ 0 ↔ μ n = 1 ∨ μ n = -1 := by
have := moebius_eq_or n
aesop
#align nat.arithmetic_function.moebius_ne_zero_iff_eq_or ArithmeticFunction.moebius_ne_zero_iff_eq_or
theorem moebius_sq_eq_one_of_squarefree {l : ℕ} (hl : Squarefree l) : μ l ^ 2 = 1 := by
rw [moebius_apply_of_squarefree hl, ← pow_mul, mul_comm, pow_mul, neg_one_sq, one_pow]
theorem abs_moebius_eq_one_of_squarefree {l : ℕ} (hl : Squarefree l) : |μ l| = 1 := by
simp only [moebius_apply_of_squarefree hl, abs_pow, abs_neg, abs_one, one_pow]
theorem moebius_sq {n : ℕ} :
μ n ^ 2 = if Squarefree n then 1 else 0 := by
split_ifs with h
· exact moebius_sq_eq_one_of_squarefree h
· simp only [pow_eq_zero_iff, moebius_eq_zero_of_not_squarefree h,
zero_pow (show 2 ≠ 0 by norm_num)]
theorem abs_moebius {n : ℕ} :
|μ n| = if Squarefree n then 1 else 0 := by
split_ifs with h
· exact abs_moebius_eq_one_of_squarefree h
· simp only [moebius_eq_zero_of_not_squarefree h, abs_zero]
theorem abs_moebius_le_one {n : ℕ} : |μ n| ≤ 1 := by
rw [abs_moebius, apply_ite (· ≤ 1)]
simp
theorem moebius_apply_prime {p : ℕ} (hp : p.Prime) : μ p = -1 := by
rw [moebius_apply_of_squarefree hp.squarefree, cardFactors_apply_prime hp, pow_one]
#align nat.arithmetic_function.moebius_apply_prime ArithmeticFunction.moebius_apply_prime
theorem moebius_apply_prime_pow {p k : ℕ} (hp : p.Prime) (hk : k ≠ 0) :
μ (p ^ k) = if k = 1 then -1 else 0 := by
split_ifs with h
· rw [h, pow_one, moebius_apply_prime hp]
rw [moebius_eq_zero_of_not_squarefree]
rw [squarefree_pow_iff hp.ne_one hk, not_and_or]
exact Or.inr h
#align nat.arithmetic_function.moebius_apply_prime_pow ArithmeticFunction.moebius_apply_prime_pow
theorem moebius_apply_isPrimePow_not_prime {n : ℕ} (hn : IsPrimePow n) (hn' : ¬n.Prime) :
μ n = 0 := by
obtain ⟨p, k, hp, hk, rfl⟩ := (isPrimePow_nat_iff _).1 hn
rw [moebius_apply_prime_pow hp hk.ne', if_neg]
rintro rfl
exact hn' (by simpa)
#align nat.arithmetic_function.moebius_apply_is_prime_pow_not_prime ArithmeticFunction.moebius_apply_isPrimePow_not_prime
@[arith_mult]
theorem isMultiplicative_moebius : IsMultiplicative μ := by
rw [IsMultiplicative.iff_ne_zero]
refine ⟨by simp, fun {n m} hn hm hnm => ?_⟩
simp only [moebius, ZeroHom.coe_mk, coe_mk, ZeroHom.toFun_eq_coe, Eq.ndrec, ZeroHom.coe_mk,
IsUnit.mul_iff, Nat.isUnit_iff, squarefree_mul hnm, ite_zero_mul_ite_zero,
cardFactors_mul hn hm, pow_add]
#align nat.arithmetic_function.is_multiplicative_moebius ArithmeticFunction.isMultiplicative_moebius
theorem IsMultiplicative.prodPrimeFactors_one_add_of_squarefree [CommSemiring R]
{f : ArithmeticFunction R} (h_mult : f.IsMultiplicative) {n : ℕ} (hn : Squarefree n) :
∏ p ∈ n.primeFactors, (1 + f p) = ∑ d ∈ n.divisors, f d := by
trans (∏ᵖ p ∣ n, ((ζ:ArithmeticFunction R) + f) p)
· simp_rw [prodPrimeFactors_apply hn.ne_zero, add_apply, natCoe_apply]
apply Finset.prod_congr rfl; intro p hp;
rw [zeta_apply_ne (prime_of_mem_factors <| List.mem_toFinset.mp hp).ne_zero, cast_one]
rw [isMultiplicative_zeta.natCast.prodPrimeFactors_add_of_squarefree h_mult hn,
coe_zeta_mul_apply]
theorem IsMultiplicative.prodPrimeFactors_one_sub_of_squarefree [CommRing R]
(f : ArithmeticFunction R) (hf : f.IsMultiplicative) {n : ℕ} (hn : Squarefree n) :
∏ p ∈ n.primeFactors, (1 - f p) = ∑ d ∈ n.divisors, μ d * f d := by
trans (∏ p ∈ n.primeFactors, (1 + (ArithmeticFunction.pmul (μ:ArithmeticFunction R) f) p))
· apply Finset.prod_congr rfl; intro p hp
rw [pmul_apply, intCoe_apply, ArithmeticFunction.moebius_apply_prime
(prime_of_mem_factors (List.mem_toFinset.mp hp))]
ring
· rw [(isMultiplicative_moebius.intCast.pmul hf).prodPrimeFactors_one_add_of_squarefree hn]
simp_rw [pmul_apply, intCoe_apply]
open UniqueFactorizationMonoid
@[simp]
theorem moebius_mul_coe_zeta : (μ * ζ : ArithmeticFunction ℤ) = 1 := by
ext n
refine recOnPosPrimePosCoprime ?_ ?_ ?_ ?_ n
· intro p n hp hn
rw [coe_mul_zeta_apply, sum_divisors_prime_pow hp, sum_range_succ']
simp_rw [Nat.pow_zero, moebius_apply_one,
moebius_apply_prime_pow hp (Nat.succ_ne_zero _), Nat.succ_inj', sum_ite_eq', mem_range,
if_pos hn, add_left_neg]
rw [one_apply_ne]
rw [Ne, pow_eq_one_iff]
· exact hp.ne_one
· exact hn.ne'
· rw [ZeroHom.map_zero, ZeroHom.map_zero]
· simp
· intro a b _ha _hb hab ha' hb'
rw [IsMultiplicative.map_mul_of_coprime _ hab, ha', hb',
IsMultiplicative.map_mul_of_coprime isMultiplicative_one hab]
exact isMultiplicative_moebius.mul isMultiplicative_zeta.natCast
#align nat.arithmetic_function.moebius_mul_coe_zeta ArithmeticFunction.moebius_mul_coe_zeta
@[simp]
theorem coe_zeta_mul_moebius : (ζ * μ : ArithmeticFunction ℤ) = 1 := by
rw [mul_comm, moebius_mul_coe_zeta]
#align nat.arithmetic_function.coe_zeta_mul_moebius ArithmeticFunction.coe_zeta_mul_moebius
@[simp]
theorem coe_moebius_mul_coe_zeta [Ring R] : (μ * ζ : ArithmeticFunction R) = 1 := by
rw [← coe_coe, ← intCoe_mul, moebius_mul_coe_zeta, intCoe_one]
#align nat.arithmetic_function.coe_moebius_mul_coe_zeta ArithmeticFunction.coe_moebius_mul_coe_zeta
@[simp]
theorem coe_zeta_mul_coe_moebius [Ring R] : (ζ * μ : ArithmeticFunction R) = 1 := by
rw [← coe_coe, ← intCoe_mul, coe_zeta_mul_moebius, intCoe_one]
#align nat.arithmetic_function.coe_zeta_mul_coe_moebius ArithmeticFunction.coe_zeta_mul_coe_moebius
section CommRing
variable [CommRing R]
instance : Invertible (ζ : ArithmeticFunction R) where
invOf := μ
invOf_mul_self := coe_moebius_mul_coe_zeta
mul_invOf_self := coe_zeta_mul_coe_moebius
/-- A unit in `ArithmeticFunction R` that evaluates to `ζ`, with inverse `μ`. -/
def zetaUnit : (ArithmeticFunction R)ˣ :=
⟨ζ, μ, coe_zeta_mul_coe_moebius, coe_moebius_mul_coe_zeta⟩
#align nat.arithmetic_function.zeta_unit ArithmeticFunction.zetaUnit
@[simp]
theorem coe_zetaUnit : ((zetaUnit : (ArithmeticFunction R)ˣ) : ArithmeticFunction R) = ζ :=
rfl
#align nat.arithmetic_function.coe_zeta_unit ArithmeticFunction.coe_zetaUnit
@[simp]
theorem inv_zetaUnit : ((zetaUnit⁻¹ : (ArithmeticFunction R)ˣ) : ArithmeticFunction R) = μ :=
rfl
#align nat.arithmetic_function.inv_zeta_unit ArithmeticFunction.inv_zetaUnit
end CommRing
/-- Möbius inversion for functions to an `AddCommGroup`. -/
theorem sum_eq_iff_sum_smul_moebius_eq [AddCommGroup R] {f g : ℕ → R} :
(∀ n > 0, ∑ i ∈ n.divisors, f i = g n) ↔
∀ n > 0, ∑ x ∈ n.divisorsAntidiagonal, μ x.fst • g x.snd = f n := by
let f' : ArithmeticFunction R := ⟨fun x => if x = 0 then 0 else f x, if_pos rfl⟩
let g' : ArithmeticFunction R := ⟨fun x => if x = 0 then 0 else g x, if_pos rfl⟩
trans (ζ : ArithmeticFunction ℤ) • f' = g'
· rw [ext_iff]
apply forall_congr'
intro n
cases n with
| zero => simp
| succ n =>
rw [coe_zeta_smul_apply]
simp only [n.succ_ne_zero, forall_prop_of_true, succ_pos', if_false, ZeroHom.coe_mk]
simp only [f', g', coe_mk, succ_ne_zero, ite_false]
rw [sum_congr rfl fun x hx => ?_]
rw [if_neg (Nat.pos_of_mem_divisors hx).ne']
trans μ • g' = f'
· constructor <;> intro h
· rw [← h, ← mul_smul, moebius_mul_coe_zeta, one_smul]
· rw [← h, ← mul_smul, coe_zeta_mul_moebius, one_smul]
· rw [ext_iff]
apply forall_congr'
intro n
cases n with
| zero => simp
| succ n =>
simp only [n.succ_ne_zero, forall_prop_of_true, succ_pos', smul_apply, if_false,
ZeroHom.coe_mk]
-- Porting note: added following `simp only`
simp only [f', g', Nat.isUnit_iff, coe_mk, ZeroHom.toFun_eq_coe, succ_ne_zero, ite_false]
rw [sum_congr rfl fun x hx => ?_]
rw [if_neg (Nat.pos_of_mem_divisors (snd_mem_divisors_of_mem_antidiagonal hx)).ne']
#align nat.arithmetic_function.sum_eq_iff_sum_smul_moebius_eq ArithmeticFunction.sum_eq_iff_sum_smul_moebius_eq
/-- Möbius inversion for functions to a `Ring`. -/
theorem sum_eq_iff_sum_mul_moebius_eq [Ring R] {f g : ℕ → R} :
(∀ n > 0, ∑ i ∈ n.divisors, f i = g n) ↔
∀ n > 0, ∑ x ∈ n.divisorsAntidiagonal, (μ x.fst : R) * g x.snd = f n := by
rw [sum_eq_iff_sum_smul_moebius_eq]
apply forall_congr'
refine fun a => imp_congr_right fun _ => (sum_congr rfl fun x _hx => ?_).congr_left
rw [zsmul_eq_mul]
#align nat.arithmetic_function.sum_eq_iff_sum_mul_moebius_eq ArithmeticFunction.sum_eq_iff_sum_mul_moebius_eq
/-- Möbius inversion for functions to a `CommGroup`. -/
theorem prod_eq_iff_prod_pow_moebius_eq [CommGroup R] {f g : ℕ → R} :
(∀ n > 0, ∏ i ∈ n.divisors, f i = g n) ↔
∀ n > 0, ∏ x ∈ n.divisorsAntidiagonal, g x.snd ^ μ x.fst = f n :=
@sum_eq_iff_sum_smul_moebius_eq (Additive R) _ _ _
#align nat.arithmetic_function.prod_eq_iff_prod_pow_moebius_eq ArithmeticFunction.prod_eq_iff_prod_pow_moebius_eq
/-- Möbius inversion for functions to a `CommGroupWithZero`. -/
theorem prod_eq_iff_prod_pow_moebius_eq_of_nonzero [CommGroupWithZero R] {f g : ℕ → R}
(hf : ∀ n : ℕ, 0 < n → f n ≠ 0) (hg : ∀ n : ℕ, 0 < n → g n ≠ 0) :
(∀ n > 0, ∏ i ∈ n.divisors, f i = g n) ↔
∀ n > 0, ∏ x ∈ n.divisorsAntidiagonal, g x.snd ^ μ x.fst = f n := by
refine
Iff.trans
(Iff.trans (forall_congr' fun n => ?_)
(@prod_eq_iff_prod_pow_moebius_eq Rˣ _
(fun n => if h : 0 < n then Units.mk0 (f n) (hf n h) else 1) fun n =>
if h : 0 < n then Units.mk0 (g n) (hg n h) else 1))
(forall_congr' fun n => ?_) <;>
refine imp_congr_right fun hn => ?_
· dsimp
rw [dif_pos hn, ← Units.eq_iff, ← Units.coeHom_apply, map_prod, Units.val_mk0,
prod_congr rfl _]
intro x hx
rw [dif_pos (Nat.pos_of_mem_divisors hx), Units.coeHom_apply, Units.val_mk0]
· dsimp
rw [dif_pos hn, ← Units.eq_iff, ← Units.coeHom_apply, map_prod, Units.val_mk0,
prod_congr rfl _]
intro x hx
rw [dif_pos (Nat.pos_of_mem_divisors (Nat.snd_mem_divisors_of_mem_antidiagonal hx)),
Units.coeHom_apply, Units.val_zpow_eq_zpow_val, Units.val_mk0]
#align nat.arithmetic_function.prod_eq_iff_prod_pow_moebius_eq_of_nonzero ArithmeticFunction.prod_eq_iff_prod_pow_moebius_eq_of_nonzero
/-- Möbius inversion for functions to an `AddCommGroup`, where the equalities only hold on a
well-behaved set. -/
theorem sum_eq_iff_sum_smul_moebius_eq_on [AddCommGroup R] {f g : ℕ → R}
(s : Set ℕ) (hs : ∀ m n, m ∣ n → n ∈ s → m ∈ s) :
(∀ n > 0, n ∈ s → (∑ i ∈ n.divisors, f i) = g n) ↔
∀ n > 0, n ∈ s → (∑ x ∈ n.divisorsAntidiagonal, μ x.fst • g x.snd) = f n := by
constructor
· intro h
let G := fun (n:ℕ) => (∑ i ∈ n.divisors, f i)
intro n hn hnP
suffices ∑ d ∈ n.divisors, μ (n/d) • G d = f n from by
rw [Nat.sum_divisorsAntidiagonal' (f := fun x y => μ x • g y), ← this, sum_congr rfl]
intro d hd
rw [← h d (Nat.pos_of_mem_divisors hd) <| hs d n (Nat.dvd_of_mem_divisors hd) hnP]
rw [← Nat.sum_divisorsAntidiagonal' (f := fun x y => μ x • G y)]
apply sum_eq_iff_sum_smul_moebius_eq.mp _ n hn
intro _ _; rfl
· intro h
let F := fun (n:ℕ) => ∑ x ∈ n.divisorsAntidiagonal, μ x.fst • g x.snd
intro n hn hnP
suffices ∑ d ∈ n.divisors, F d = g n from by
rw [← this, sum_congr rfl]
intro d hd
rw [← h d (Nat.pos_of_mem_divisors hd) <| hs d n (Nat.dvd_of_mem_divisors hd) hnP]
apply sum_eq_iff_sum_smul_moebius_eq.mpr _ n hn
intro _ _; rfl
theorem sum_eq_iff_sum_smul_moebius_eq_on' [AddCommGroup R] {f g : ℕ → R}
(s : Set ℕ) (hs : ∀ m n, m ∣ n → n ∈ s → m ∈ s) (hs₀ : 0 ∉ s) :
(∀ n ∈ s, (∑ i ∈ n.divisors, f i) = g n) ↔
∀ n ∈ s, (∑ x ∈ n.divisorsAntidiagonal, μ x.fst • g x.snd) = f n := by
have : ∀ P : ℕ → Prop, ((∀ n ∈ s, P n) ↔ (∀ n > 0, n ∈ s → P n)) := fun P ↦ by
refine forall_congr' (fun n ↦ ⟨fun h _ ↦ h, fun h hn ↦ h ?_ hn⟩)
contrapose! hs₀
simpa [nonpos_iff_eq_zero.mp hs₀] using hn
simpa only [this] using sum_eq_iff_sum_smul_moebius_eq_on s hs
/-- Möbius inversion for functions to a `Ring`, where the equalities only hold on a well-behaved
set. -/
theorem sum_eq_iff_sum_mul_moebius_eq_on [Ring R] {f g : ℕ → R}
(s : Set ℕ) (hs : ∀ m n, m ∣ n → n ∈ s → m ∈ s) :
(∀ n > 0, n ∈ s → (∑ i ∈ n.divisors, f i) = g n) ↔
∀ n > 0, n ∈ s →
(∑ x ∈ n.divisorsAntidiagonal, (μ x.fst : R) * g x.snd) = f n := by
rw [sum_eq_iff_sum_smul_moebius_eq_on s hs]
apply forall_congr'
intro a; refine imp_congr_right ?_
refine fun _ => imp_congr_right fun _ => (sum_congr rfl fun x _hx => ?_).congr_left
rw [zsmul_eq_mul]
/-- Möbius inversion for functions to a `CommGroup`, where the equalities only hold on a
well-behaved set. -/
theorem prod_eq_iff_prod_pow_moebius_eq_on [CommGroup R] {f g : ℕ → R}
(s : Set ℕ) (hs : ∀ m n, m ∣ n → n ∈ s → m ∈ s) :
(∀ n > 0, n ∈ s → (∏ i ∈ n.divisors, f i) = g n) ↔
∀ n > 0, n ∈ s → (∏ x ∈ n.divisorsAntidiagonal, g x.snd ^ μ x.fst) = f n :=
@sum_eq_iff_sum_smul_moebius_eq_on (Additive R) _ _ _ s hs
/-- Möbius inversion for functions to a `CommGroupWithZero`, where the equalities only hold on
a well-behaved set. -/
| Mathlib/NumberTheory/ArithmeticFunction.lean | 1,370 | 1,394 | theorem prod_eq_iff_prod_pow_moebius_eq_on_of_nonzero [CommGroupWithZero R]
(s : Set ℕ) (hs : ∀ m n, m ∣ n → n ∈ s → m ∈ s) {f g : ℕ → R}
(hf : ∀ n > 0, f n ≠ 0) (hg : ∀ n > 0, g n ≠ 0):
(∀ n > 0, n ∈ s → (∏ i ∈ n.divisors, f i) = g n) ↔
∀ n > 0, n ∈ s → (∏ x ∈ n.divisorsAntidiagonal, g x.snd ^ μ x.fst) = f n := by |
refine
Iff.trans
(Iff.trans (forall_congr' fun n => ?_)
(@prod_eq_iff_prod_pow_moebius_eq_on Rˣ _
(fun n => if h : 0 < n then Units.mk0 (f n) (hf n h) else 1)
(fun n => if h : 0 < n then Units.mk0 (g n) (hg n h) else 1)
s hs) )
(forall_congr' fun n => ?_) <;>
refine imp_congr_right fun hn => ?_
· dsimp
rw [dif_pos hn, ← Units.eq_iff, ← Units.coeHom_apply, map_prod, Units.val_mk0,
prod_congr rfl _]
intro x hx
rw [dif_pos (Nat.pos_of_mem_divisors hx), Units.coeHom_apply, Units.val_mk0]
· dsimp
rw [dif_pos hn, ← Units.eq_iff, ← Units.coeHom_apply, map_prod, Units.val_mk0,
prod_congr rfl _]
intro x hx
rw [dif_pos (Nat.pos_of_mem_divisors (Nat.snd_mem_divisors_of_mem_antidiagonal hx)),
Units.coeHom_apply, Units.val_zpow_eq_zpow_val, Units.val_mk0]
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker, Sébastien Gouëzel, Yury G. Kudryashov, Dylan MacKenzie, Patrick Massot
-/
import Mathlib.Algebra.BigOperators.Module
import Mathlib.Algebra.Order.Field.Basic
import Mathlib.Order.Filter.ModEq
import Mathlib.Analysis.Asymptotics.Asymptotics
import Mathlib.Analysis.SpecificLimits.Basic
import Mathlib.Data.List.TFAE
import Mathlib.Analysis.NormedSpace.Basic
#align_import analysis.specific_limits.normed from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# A collection of specific limit computations
This file contains important specific limit computations in (semi-)normed groups/rings/spaces, as
well as such computations in `ℝ` when the natural proof passes through a fact about normed spaces.
-/
noncomputable section
open scoped Classical
open Set Function Filter Finset Metric Asymptotics
open scoped Classical
open Topology Nat uniformity NNReal ENNReal
variable {α : Type*} {β : Type*} {ι : Type*}
theorem tendsto_norm_atTop_atTop : Tendsto (norm : ℝ → ℝ) atTop atTop :=
tendsto_abs_atTop_atTop
#align tendsto_norm_at_top_at_top tendsto_norm_atTop_atTop
theorem summable_of_absolute_convergence_real {f : ℕ → ℝ} :
(∃ r, Tendsto (fun n ↦ ∑ i ∈ range n, |f i|) atTop (𝓝 r)) → Summable f
| ⟨r, hr⟩ => by
refine .of_norm ⟨r, (hasSum_iff_tendsto_nat_of_nonneg ?_ _).2 ?_⟩
· exact fun i ↦ norm_nonneg _
· simpa only using hr
#align summable_of_absolute_convergence_real summable_of_absolute_convergence_real
/-! ### Powers -/
theorem tendsto_norm_zero' {𝕜 : Type*} [NormedAddCommGroup 𝕜] :
Tendsto (norm : 𝕜 → ℝ) (𝓝[≠] 0) (𝓝[>] 0) :=
tendsto_norm_zero.inf <| tendsto_principal_principal.2 fun _ hx ↦ norm_pos_iff.2 hx
#align tendsto_norm_zero' tendsto_norm_zero'
namespace NormedField
theorem tendsto_norm_inverse_nhdsWithin_0_atTop {𝕜 : Type*} [NormedDivisionRing 𝕜] :
Tendsto (fun x : 𝕜 ↦ ‖x⁻¹‖) (𝓝[≠] 0) atTop :=
(tendsto_inv_zero_atTop.comp tendsto_norm_zero').congr fun x ↦ (norm_inv x).symm
#align normed_field.tendsto_norm_inverse_nhds_within_0_at_top NormedField.tendsto_norm_inverse_nhdsWithin_0_atTop
theorem tendsto_norm_zpow_nhdsWithin_0_atTop {𝕜 : Type*} [NormedDivisionRing 𝕜] {m : ℤ}
(hm : m < 0) :
Tendsto (fun x : 𝕜 ↦ ‖x ^ m‖) (𝓝[≠] 0) atTop := by
rcases neg_surjective m with ⟨m, rfl⟩
rw [neg_lt_zero] at hm; lift m to ℕ using hm.le; rw [Int.natCast_pos] at hm
simp only [norm_pow, zpow_neg, zpow_natCast, ← inv_pow]
exact (tendsto_pow_atTop hm.ne').comp NormedField.tendsto_norm_inverse_nhdsWithin_0_atTop
#align normed_field.tendsto_norm_zpow_nhds_within_0_at_top NormedField.tendsto_norm_zpow_nhdsWithin_0_atTop
/-- The (scalar) product of a sequence that tends to zero with a bounded one also tends to zero. -/
theorem tendsto_zero_smul_of_tendsto_zero_of_bounded {ι 𝕜 𝔸 : Type*} [NormedDivisionRing 𝕜]
[NormedAddCommGroup 𝔸] [Module 𝕜 𝔸] [BoundedSMul 𝕜 𝔸] {l : Filter ι} {ε : ι → 𝕜} {f : ι → 𝔸}
(hε : Tendsto ε l (𝓝 0)) (hf : Filter.IsBoundedUnder (· ≤ ·) l (norm ∘ f)) :
Tendsto (ε • f) l (𝓝 0) := by
rw [← isLittleO_one_iff 𝕜] at hε ⊢
simpa using IsLittleO.smul_isBigO hε (hf.isBigO_const (one_ne_zero : (1 : 𝕜) ≠ 0))
#align normed_field.tendsto_zero_smul_of_tendsto_zero_of_bounded NormedField.tendsto_zero_smul_of_tendsto_zero_of_bounded
@[simp]
theorem continuousAt_zpow {𝕜 : Type*} [NontriviallyNormedField 𝕜] {m : ℤ} {x : 𝕜} :
ContinuousAt (fun x ↦ x ^ m) x ↔ x ≠ 0 ∨ 0 ≤ m := by
refine ⟨?_, continuousAt_zpow₀ _ _⟩
contrapose!; rintro ⟨rfl, hm⟩ hc
exact not_tendsto_atTop_of_tendsto_nhds (hc.tendsto.mono_left nhdsWithin_le_nhds).norm
(tendsto_norm_zpow_nhdsWithin_0_atTop hm)
#align normed_field.continuous_at_zpow NormedField.continuousAt_zpow
@[simp]
theorem continuousAt_inv {𝕜 : Type*} [NontriviallyNormedField 𝕜] {x : 𝕜} :
ContinuousAt Inv.inv x ↔ x ≠ 0 := by
simpa [(zero_lt_one' ℤ).not_le] using @continuousAt_zpow _ _ (-1) x
#align normed_field.continuous_at_inv NormedField.continuousAt_inv
end NormedField
theorem isLittleO_pow_pow_of_lt_left {r₁ r₂ : ℝ} (h₁ : 0 ≤ r₁) (h₂ : r₁ < r₂) :
(fun n : ℕ ↦ r₁ ^ n) =o[atTop] fun n ↦ r₂ ^ n :=
have H : 0 < r₂ := h₁.trans_lt h₂
(isLittleO_of_tendsto fun _ hn ↦ False.elim <| H.ne' <| pow_eq_zero hn) <|
(tendsto_pow_atTop_nhds_zero_of_lt_one
(div_nonneg h₁ (h₁.trans h₂.le)) ((div_lt_one H).2 h₂)).congr fun _ ↦ div_pow _ _ _
#align is_o_pow_pow_of_lt_left isLittleO_pow_pow_of_lt_left
theorem isBigO_pow_pow_of_le_left {r₁ r₂ : ℝ} (h₁ : 0 ≤ r₁) (h₂ : r₁ ≤ r₂) :
(fun n : ℕ ↦ r₁ ^ n) =O[atTop] fun n ↦ r₂ ^ n :=
h₂.eq_or_lt.elim (fun h ↦ h ▸ isBigO_refl _ _) fun h ↦ (isLittleO_pow_pow_of_lt_left h₁ h).isBigO
set_option linter.uppercaseLean3 false in
#align is_O_pow_pow_of_le_left isBigO_pow_pow_of_le_left
theorem isLittleO_pow_pow_of_abs_lt_left {r₁ r₂ : ℝ} (h : |r₁| < |r₂|) :
(fun n : ℕ ↦ r₁ ^ n) =o[atTop] fun n ↦ r₂ ^ n := by
refine (IsLittleO.of_norm_left ?_).of_norm_right
exact (isLittleO_pow_pow_of_lt_left (abs_nonneg r₁) h).congr (pow_abs r₁) (pow_abs r₂)
#align is_o_pow_pow_of_abs_lt_left isLittleO_pow_pow_of_abs_lt_left
open List in
/-- Various statements equivalent to the fact that `f n` grows exponentially slower than `R ^ n`.
* 0: $f n = o(a ^ n)$ for some $-R < a < R$;
* 1: $f n = o(a ^ n)$ for some $0 < a < R$;
* 2: $f n = O(a ^ n)$ for some $-R < a < R$;
* 3: $f n = O(a ^ n)$ for some $0 < a < R$;
* 4: there exist `a < R` and `C` such that one of `C` and `R` is positive and $|f n| ≤ Ca^n$
for all `n`;
* 5: there exists `0 < a < R` and a positive `C` such that $|f n| ≤ Ca^n$ for all `n`;
* 6: there exists `a < R` such that $|f n| ≤ a ^ n$ for sufficiently large `n`;
* 7: there exists `0 < a < R` such that $|f n| ≤ a ^ n$ for sufficiently large `n`.
NB: For backwards compatibility, if you add more items to the list, please append them at the end of
the list. -/
theorem TFAE_exists_lt_isLittleO_pow (f : ℕ → ℝ) (R : ℝ) :
TFAE
[∃ a ∈ Ioo (-R) R, f =o[atTop] (a ^ ·), ∃ a ∈ Ioo 0 R, f =o[atTop] (a ^ ·),
∃ a ∈ Ioo (-R) R, f =O[atTop] (a ^ ·), ∃ a ∈ Ioo 0 R, f =O[atTop] (a ^ ·),
∃ a < R, ∃ C : ℝ, (0 < C ∨ 0 < R) ∧ ∀ n, |f n| ≤ C * a ^ n,
∃ a ∈ Ioo 0 R, ∃ C > 0, ∀ n, |f n| ≤ C * a ^ n, ∃ a < R, ∀ᶠ n in atTop, |f n| ≤ a ^ n,
∃ a ∈ Ioo 0 R, ∀ᶠ n in atTop, |f n| ≤ a ^ n] := by
have A : Ico 0 R ⊆ Ioo (-R) R :=
fun x hx ↦ ⟨(neg_lt_zero.2 (hx.1.trans_lt hx.2)).trans_le hx.1, hx.2⟩
have B : Ioo 0 R ⊆ Ioo (-R) R := Subset.trans Ioo_subset_Ico_self A
-- First we prove that 1-4 are equivalent using 2 → 3 → 4, 1 → 3, and 2 → 1
tfae_have 1 → 3
· exact fun ⟨a, ha, H⟩ ↦ ⟨a, ha, H.isBigO⟩
tfae_have 2 → 1
· exact fun ⟨a, ha, H⟩ ↦ ⟨a, B ha, H⟩
tfae_have 3 → 2
· rintro ⟨a, ha, H⟩
rcases exists_between (abs_lt.2 ha) with ⟨b, hab, hbR⟩
exact ⟨b, ⟨(abs_nonneg a).trans_lt hab, hbR⟩,
H.trans_isLittleO (isLittleO_pow_pow_of_abs_lt_left (hab.trans_le (le_abs_self b)))⟩
tfae_have 2 → 4
· exact fun ⟨a, ha, H⟩ ↦ ⟨a, ha, H.isBigO⟩
tfae_have 4 → 3
· exact fun ⟨a, ha, H⟩ ↦ ⟨a, B ha, H⟩
-- Add 5 and 6 using 4 → 6 → 5 → 3
tfae_have 4 → 6
· rintro ⟨a, ha, H⟩
rcases bound_of_isBigO_nat_atTop H with ⟨C, hC₀, hC⟩
refine ⟨a, ha, C, hC₀, fun n ↦ ?_⟩
simpa only [Real.norm_eq_abs, abs_pow, abs_of_nonneg ha.1.le] using hC (pow_ne_zero n ha.1.ne')
tfae_have 6 → 5
· exact fun ⟨a, ha, C, H₀, H⟩ ↦ ⟨a, ha.2, C, Or.inl H₀, H⟩
tfae_have 5 → 3
· rintro ⟨a, ha, C, h₀, H⟩
rcases sign_cases_of_C_mul_pow_nonneg fun n ↦ (abs_nonneg _).trans (H n) with (rfl | ⟨hC₀, ha₀⟩)
· obtain rfl : f = 0 := by
ext n
simpa using H n
simp only [lt_irrefl, false_or_iff] at h₀
exact ⟨0, ⟨neg_lt_zero.2 h₀, h₀⟩, isBigO_zero _ _⟩
exact ⟨a, A ⟨ha₀, ha⟩,
isBigO_of_le' _ fun n ↦ (H n).trans <| mul_le_mul_of_nonneg_left (le_abs_self _) hC₀.le⟩
-- Add 7 and 8 using 2 → 8 → 7 → 3
tfae_have 2 → 8
· rintro ⟨a, ha, H⟩
refine ⟨a, ha, (H.def zero_lt_one).mono fun n hn ↦ ?_⟩
rwa [Real.norm_eq_abs, Real.norm_eq_abs, one_mul, abs_pow, abs_of_pos ha.1] at hn
tfae_have 8 → 7
· exact fun ⟨a, ha, H⟩ ↦ ⟨a, ha.2, H⟩
tfae_have 7 → 3
· rintro ⟨a, ha, H⟩
have : 0 ≤ a := nonneg_of_eventually_pow_nonneg (H.mono fun n ↦ (abs_nonneg _).trans)
refine ⟨a, A ⟨this, ha⟩, IsBigO.of_bound 1 ?_⟩
simpa only [Real.norm_eq_abs, one_mul, abs_pow, abs_of_nonneg this]
-- Porting note: used to work without explicitly having 6 → 7
tfae_have 6 → 7
· exact fun h ↦ tfae_8_to_7 <| tfae_2_to_8 <| tfae_3_to_2 <| tfae_5_to_3 <| tfae_6_to_5 h
tfae_finish
#align tfae_exists_lt_is_o_pow TFAE_exists_lt_isLittleO_pow
/-- For any natural `k` and a real `r > 1` we have `n ^ k = o(r ^ n)` as `n → ∞`. -/
theorem isLittleO_pow_const_const_pow_of_one_lt {R : Type*} [NormedRing R] (k : ℕ) {r : ℝ}
(hr : 1 < r) : (fun n ↦ (n : R) ^ k : ℕ → R) =o[atTop] fun n ↦ r ^ n := by
have : Tendsto (fun x : ℝ ↦ x ^ k) (𝓝[>] 1) (𝓝 1) :=
((continuous_id.pow k).tendsto' (1 : ℝ) 1 (one_pow _)).mono_left inf_le_left
obtain ⟨r' : ℝ, hr' : r' ^ k < r, h1 : 1 < r'⟩ :=
((this.eventually (gt_mem_nhds hr)).and self_mem_nhdsWithin).exists
have h0 : 0 ≤ r' := zero_le_one.trans h1.le
suffices (fun n ↦ (n : R) ^ k : ℕ → R) =O[atTop] fun n : ℕ ↦ (r' ^ k) ^ n from
this.trans_isLittleO (isLittleO_pow_pow_of_lt_left (pow_nonneg h0 _) hr')
conv in (r' ^ _) ^ _ => rw [← pow_mul, mul_comm, pow_mul]
suffices ∀ n : ℕ, ‖(n : R)‖ ≤ (r' - 1)⁻¹ * ‖(1 : R)‖ * ‖r' ^ n‖ from
(isBigO_of_le' _ this).pow _
intro n
rw [mul_right_comm]
refine n.norm_cast_le.trans (mul_le_mul_of_nonneg_right ?_ (norm_nonneg _))
simpa [_root_.div_eq_inv_mul, Real.norm_eq_abs, abs_of_nonneg h0] using n.cast_le_pow_div_sub h1
#align is_o_pow_const_const_pow_of_one_lt isLittleO_pow_const_const_pow_of_one_lt
/-- For a real `r > 1` we have `n = o(r ^ n)` as `n → ∞`. -/
theorem isLittleO_coe_const_pow_of_one_lt {R : Type*} [NormedRing R] {r : ℝ} (hr : 1 < r) :
((↑) : ℕ → R) =o[atTop] fun n ↦ r ^ n := by
simpa only [pow_one] using @isLittleO_pow_const_const_pow_of_one_lt R _ 1 _ hr
#align is_o_coe_const_pow_of_one_lt isLittleO_coe_const_pow_of_one_lt
/-- If `‖r₁‖ < r₂`, then for any natural `k` we have `n ^ k r₁ ^ n = o (r₂ ^ n)` as `n → ∞`. -/
theorem isLittleO_pow_const_mul_const_pow_const_pow_of_norm_lt {R : Type*} [NormedRing R] (k : ℕ)
{r₁ : R} {r₂ : ℝ} (h : ‖r₁‖ < r₂) :
(fun n ↦ (n : R) ^ k * r₁ ^ n : ℕ → R) =o[atTop] fun n ↦ r₂ ^ n := by
by_cases h0 : r₁ = 0
· refine (isLittleO_zero _ _).congr' (mem_atTop_sets.2 <| ⟨1, fun n hn ↦ ?_⟩) EventuallyEq.rfl
simp [zero_pow (one_le_iff_ne_zero.1 hn), h0]
rw [← Ne, ← norm_pos_iff] at h0
have A : (fun n ↦ (n : R) ^ k : ℕ → R) =o[atTop] fun n ↦ (r₂ / ‖r₁‖) ^ n :=
isLittleO_pow_const_const_pow_of_one_lt k ((one_lt_div h0).2 h)
suffices (fun n ↦ r₁ ^ n) =O[atTop] fun n ↦ ‖r₁‖ ^ n by
simpa [div_mul_cancel₀ _ (pow_pos h0 _).ne'] using A.mul_isBigO this
exact IsBigO.of_bound 1 (by simpa using eventually_norm_pow_le r₁)
#align is_o_pow_const_mul_const_pow_const_pow_of_norm_lt isLittleO_pow_const_mul_const_pow_const_pow_of_norm_lt
theorem tendsto_pow_const_div_const_pow_of_one_lt (k : ℕ) {r : ℝ} (hr : 1 < r) :
Tendsto (fun n ↦ (n : ℝ) ^ k / r ^ n : ℕ → ℝ) atTop (𝓝 0) :=
(isLittleO_pow_const_const_pow_of_one_lt k hr).tendsto_div_nhds_zero
#align tendsto_pow_const_div_const_pow_of_one_lt tendsto_pow_const_div_const_pow_of_one_lt
/-- If `|r| < 1`, then `n ^ k r ^ n` tends to zero for any natural `k`. -/
theorem tendsto_pow_const_mul_const_pow_of_abs_lt_one (k : ℕ) {r : ℝ} (hr : |r| < 1) :
Tendsto (fun n ↦ (n : ℝ) ^ k * r ^ n : ℕ → ℝ) atTop (𝓝 0) := by
by_cases h0 : r = 0
· exact tendsto_const_nhds.congr'
(mem_atTop_sets.2 ⟨1, fun n hn ↦ by simp [zero_lt_one.trans_le hn |>.ne', h0]⟩)
have hr' : 1 < |r|⁻¹ := one_lt_inv (abs_pos.2 h0) hr
rw [tendsto_zero_iff_norm_tendsto_zero]
simpa [div_eq_mul_inv] using tendsto_pow_const_div_const_pow_of_one_lt k hr'
#align tendsto_pow_const_mul_const_pow_of_abs_lt_one tendsto_pow_const_mul_const_pow_of_abs_lt_one
/-- If `0 ≤ r < 1`, then `n ^ k r ^ n` tends to zero for any natural `k`.
This is a specialized version of `tendsto_pow_const_mul_const_pow_of_abs_lt_one`, singled out
for ease of application. -/
theorem tendsto_pow_const_mul_const_pow_of_lt_one (k : ℕ) {r : ℝ} (hr : 0 ≤ r) (h'r : r < 1) :
Tendsto (fun n ↦ (n : ℝ) ^ k * r ^ n : ℕ → ℝ) atTop (𝓝 0) :=
tendsto_pow_const_mul_const_pow_of_abs_lt_one k (abs_lt.2 ⟨neg_one_lt_zero.trans_le hr, h'r⟩)
#align tendsto_pow_const_mul_const_pow_of_lt_one tendsto_pow_const_mul_const_pow_of_lt_one
/-- If `|r| < 1`, then `n * r ^ n` tends to zero. -/
theorem tendsto_self_mul_const_pow_of_abs_lt_one {r : ℝ} (hr : |r| < 1) :
Tendsto (fun n ↦ n * r ^ n : ℕ → ℝ) atTop (𝓝 0) := by
simpa only [pow_one] using tendsto_pow_const_mul_const_pow_of_abs_lt_one 1 hr
#align tendsto_self_mul_const_pow_of_abs_lt_one tendsto_self_mul_const_pow_of_abs_lt_one
/-- If `0 ≤ r < 1`, then `n * r ^ n` tends to zero. This is a specialized version of
`tendsto_self_mul_const_pow_of_abs_lt_one`, singled out for ease of application. -/
theorem tendsto_self_mul_const_pow_of_lt_one {r : ℝ} (hr : 0 ≤ r) (h'r : r < 1) :
Tendsto (fun n ↦ n * r ^ n : ℕ → ℝ) atTop (𝓝 0) := by
simpa only [pow_one] using tendsto_pow_const_mul_const_pow_of_lt_one 1 hr h'r
#align tendsto_self_mul_const_pow_of_lt_one tendsto_self_mul_const_pow_of_lt_one
/-- In a normed ring, the powers of an element x with `‖x‖ < 1` tend to zero. -/
theorem tendsto_pow_atTop_nhds_zero_of_norm_lt_one {R : Type*} [NormedRing R] {x : R}
(h : ‖x‖ < 1) :
Tendsto (fun n : ℕ ↦ x ^ n) atTop (𝓝 0) := by
apply squeeze_zero_norm' (eventually_norm_pow_le x)
exact tendsto_pow_atTop_nhds_zero_of_lt_one (norm_nonneg _) h
#align tendsto_pow_at_top_nhds_0_of_norm_lt_1 tendsto_pow_atTop_nhds_zero_of_norm_lt_one
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhds_0_of_norm_lt_1 := tendsto_pow_atTop_nhds_zero_of_norm_lt_one
theorem tendsto_pow_atTop_nhds_zero_of_abs_lt_one {r : ℝ} (h : |r| < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) :=
tendsto_pow_atTop_nhds_zero_of_norm_lt_one h
#align tendsto_pow_at_top_nhds_0_of_abs_lt_1 tendsto_pow_atTop_nhds_zero_of_abs_lt_one
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhds_0_of_abs_lt_1 := tendsto_pow_atTop_nhds_zero_of_abs_lt_one
/-! ### Geometric series-/
section Geometric
variable {K : Type*} [NormedDivisionRing K] {ξ : K}
| Mathlib/Analysis/SpecificLimits/Normed.lean | 293 | 301 | theorem hasSum_geometric_of_norm_lt_one (h : ‖ξ‖ < 1) : HasSum (fun n : ℕ ↦ ξ ^ n) (1 - ξ)⁻¹ := by |
have xi_ne_one : ξ ≠ 1 := by
contrapose! h
simp [h]
have A : Tendsto (fun n ↦ (ξ ^ n - 1) * (ξ - 1)⁻¹) atTop (𝓝 ((0 - 1) * (ξ - 1)⁻¹)) :=
((tendsto_pow_atTop_nhds_zero_of_norm_lt_one h).sub tendsto_const_nhds).mul tendsto_const_nhds
rw [hasSum_iff_tendsto_nat_of_summable_norm]
· simpa [geom_sum_eq, xi_ne_one, neg_inv, div_eq_mul_inv] using A
· simp [norm_pow, summable_geometric_of_lt_one (norm_nonneg _) h]
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura
-/
import Mathlib.Data.Set.Subsingleton
import Mathlib.Order.WithBot
#align_import data.set.image from "leanprover-community/mathlib"@"001ffdc42920050657fd45bd2b8bfbec8eaaeb29"
/-!
# Images and preimages of sets
## Main definitions
* `preimage f t : Set α` : the preimage f⁻¹(t) (written `f ⁻¹' t` in Lean) of a subset of β.
* `range f : Set β` : the image of `univ` under `f`.
Also works for `{p : Prop} (f : p → α)` (unlike `image`)
## Notation
* `f ⁻¹' t` for `Set.preimage f t`
* `f '' s` for `Set.image f s`
## Tags
set, sets, image, preimage, pre-image, range
-/
universe u v
open Function Set
namespace Set
variable {α β γ : Type*} {ι ι' : Sort*}
/-! ### Inverse image -/
section Preimage
variable {f : α → β} {g : β → γ}
@[simp]
theorem preimage_empty : f ⁻¹' ∅ = ∅ :=
rfl
#align set.preimage_empty Set.preimage_empty
theorem preimage_congr {f g : α → β} {s : Set β} (h : ∀ x : α, f x = g x) : f ⁻¹' s = g ⁻¹' s := by
congr with x
simp [h]
#align set.preimage_congr Set.preimage_congr
@[gcongr]
theorem preimage_mono {s t : Set β} (h : s ⊆ t) : f ⁻¹' s ⊆ f ⁻¹' t := fun _ hx => h hx
#align set.preimage_mono Set.preimage_mono
@[simp, mfld_simps]
theorem preimage_univ : f ⁻¹' univ = univ :=
rfl
#align set.preimage_univ Set.preimage_univ
theorem subset_preimage_univ {s : Set α} : s ⊆ f ⁻¹' univ :=
subset_univ _
#align set.subset_preimage_univ Set.subset_preimage_univ
@[simp, mfld_simps]
theorem preimage_inter {s t : Set β} : f ⁻¹' (s ∩ t) = f ⁻¹' s ∩ f ⁻¹' t :=
rfl
#align set.preimage_inter Set.preimage_inter
@[simp]
theorem preimage_union {s t : Set β} : f ⁻¹' (s ∪ t) = f ⁻¹' s ∪ f ⁻¹' t :=
rfl
#align set.preimage_union Set.preimage_union
@[simp]
theorem preimage_compl {s : Set β} : f ⁻¹' sᶜ = (f ⁻¹' s)ᶜ :=
rfl
#align set.preimage_compl Set.preimage_compl
@[simp]
theorem preimage_diff (f : α → β) (s t : Set β) : f ⁻¹' (s \ t) = f ⁻¹' s \ f ⁻¹' t :=
rfl
#align set.preimage_diff Set.preimage_diff
open scoped symmDiff in
@[simp]
lemma preimage_symmDiff {f : α → β} (s t : Set β) : f ⁻¹' (s ∆ t) = (f ⁻¹' s) ∆ (f ⁻¹' t) :=
rfl
#align set.preimage_symm_diff Set.preimage_symmDiff
@[simp]
theorem preimage_ite (f : α → β) (s t₁ t₂ : Set β) :
f ⁻¹' s.ite t₁ t₂ = (f ⁻¹' s).ite (f ⁻¹' t₁) (f ⁻¹' t₂) :=
rfl
#align set.preimage_ite Set.preimage_ite
@[simp]
theorem preimage_setOf_eq {p : α → Prop} {f : β → α} : f ⁻¹' { a | p a } = { a | p (f a) } :=
rfl
#align set.preimage_set_of_eq Set.preimage_setOf_eq
@[simp]
theorem preimage_id_eq : preimage (id : α → α) = id :=
rfl
#align set.preimage_id_eq Set.preimage_id_eq
@[mfld_simps]
theorem preimage_id {s : Set α} : id ⁻¹' s = s :=
rfl
#align set.preimage_id Set.preimage_id
@[simp, mfld_simps]
theorem preimage_id' {s : Set α} : (fun x => x) ⁻¹' s = s :=
rfl
#align set.preimage_id' Set.preimage_id'
@[simp]
theorem preimage_const_of_mem {b : β} {s : Set β} (h : b ∈ s) : (fun _ : α => b) ⁻¹' s = univ :=
eq_univ_of_forall fun _ => h
#align set.preimage_const_of_mem Set.preimage_const_of_mem
@[simp]
theorem preimage_const_of_not_mem {b : β} {s : Set β} (h : b ∉ s) : (fun _ : α => b) ⁻¹' s = ∅ :=
eq_empty_of_subset_empty fun _ hx => h hx
#align set.preimage_const_of_not_mem Set.preimage_const_of_not_mem
theorem preimage_const (b : β) (s : Set β) [Decidable (b ∈ s)] :
(fun _ : α => b) ⁻¹' s = if b ∈ s then univ else ∅ := by
split_ifs with hb
exacts [preimage_const_of_mem hb, preimage_const_of_not_mem hb]
#align set.preimage_const Set.preimage_const
/-- If preimage of each singleton under `f : α → β` is either empty or the whole type,
then `f` is a constant. -/
lemma exists_eq_const_of_preimage_singleton [Nonempty β] {f : α → β}
(hf : ∀ b : β, f ⁻¹' {b} = ∅ ∨ f ⁻¹' {b} = univ) : ∃ b, f = const α b := by
rcases em (∃ b, f ⁻¹' {b} = univ) with ⟨b, hb⟩ | hf'
· exact ⟨b, funext fun x ↦ eq_univ_iff_forall.1 hb x⟩
· have : ∀ x b, f x ≠ b := fun x b ↦
eq_empty_iff_forall_not_mem.1 ((hf b).resolve_right fun h ↦ hf' ⟨b, h⟩) x
exact ⟨Classical.arbitrary β, funext fun x ↦ absurd rfl (this x _)⟩
theorem preimage_comp {s : Set γ} : g ∘ f ⁻¹' s = f ⁻¹' (g ⁻¹' s) :=
rfl
#align set.preimage_comp Set.preimage_comp
theorem preimage_comp_eq : preimage (g ∘ f) = preimage f ∘ preimage g :=
rfl
#align set.preimage_comp_eq Set.preimage_comp_eq
theorem preimage_iterate_eq {f : α → α} {n : ℕ} : Set.preimage f^[n] = (Set.preimage f)^[n] := by
induction' n with n ih; · simp
rw [iterate_succ, iterate_succ', preimage_comp_eq, ih]
#align set.preimage_iterate_eq Set.preimage_iterate_eq
theorem preimage_preimage {g : β → γ} {f : α → β} {s : Set γ} :
f ⁻¹' (g ⁻¹' s) = (fun x => g (f x)) ⁻¹' s :=
preimage_comp.symm
#align set.preimage_preimage Set.preimage_preimage
theorem eq_preimage_subtype_val_iff {p : α → Prop} {s : Set (Subtype p)} {t : Set α} :
s = Subtype.val ⁻¹' t ↔ ∀ (x) (h : p x), (⟨x, h⟩ : Subtype p) ∈ s ↔ x ∈ t :=
⟨fun s_eq x h => by
rw [s_eq]
simp, fun h => ext fun ⟨x, hx⟩ => by simp [h]⟩
#align set.eq_preimage_subtype_val_iff Set.eq_preimage_subtype_val_iff
theorem nonempty_of_nonempty_preimage {s : Set β} {f : α → β} (hf : (f ⁻¹' s).Nonempty) :
s.Nonempty :=
let ⟨x, hx⟩ := hf
⟨f x, hx⟩
#align set.nonempty_of_nonempty_preimage Set.nonempty_of_nonempty_preimage
@[simp] theorem preimage_singleton_true (p : α → Prop) : p ⁻¹' {True} = {a | p a} := by ext; simp
#align set.preimage_singleton_true Set.preimage_singleton_true
@[simp] theorem preimage_singleton_false (p : α → Prop) : p ⁻¹' {False} = {a | ¬p a} := by ext; simp
#align set.preimage_singleton_false Set.preimage_singleton_false
theorem preimage_subtype_coe_eq_compl {s u v : Set α} (hsuv : s ⊆ u ∪ v)
(H : s ∩ (u ∩ v) = ∅) : ((↑) : s → α) ⁻¹' u = ((↑) ⁻¹' v)ᶜ := by
ext ⟨x, x_in_s⟩
constructor
· intro x_in_u x_in_v
exact eq_empty_iff_forall_not_mem.mp H x ⟨x_in_s, ⟨x_in_u, x_in_v⟩⟩
· intro hx
exact Or.elim (hsuv x_in_s) id fun hx' => hx.elim hx'
#align set.preimage_subtype_coe_eq_compl Set.preimage_subtype_coe_eq_compl
end Preimage
/-! ### Image of a set under a function -/
section Image
variable {f : α → β} {s t : Set α}
-- Porting note: `Set.image` is already defined in `Init.Set`
#align set.image Set.image
@[deprecated mem_image (since := "2024-03-23")]
theorem mem_image_iff_bex {f : α → β} {s : Set α} {y : β} :
y ∈ f '' s ↔ ∃ (x : _) (_ : x ∈ s), f x = y :=
bex_def.symm
#align set.mem_image_iff_bex Set.mem_image_iff_bex
theorem image_eta (f : α → β) : f '' s = (fun x => f x) '' s :=
rfl
#align set.image_eta Set.image_eta
theorem _root_.Function.Injective.mem_set_image {f : α → β} (hf : Injective f) {s : Set α} {a : α} :
f a ∈ f '' s ↔ a ∈ s :=
⟨fun ⟨_, hb, Eq⟩ => hf Eq ▸ hb, mem_image_of_mem f⟩
#align function.injective.mem_set_image Function.Injective.mem_set_image
theorem forall_mem_image {f : α → β} {s : Set α} {p : β → Prop} :
(∀ y ∈ f '' s, p y) ↔ ∀ ⦃x⦄, x ∈ s → p (f x) := by simp
#align set.ball_image_iff Set.forall_mem_image
theorem exists_mem_image {f : α → β} {s : Set α} {p : β → Prop} :
(∃ y ∈ f '' s, p y) ↔ ∃ x ∈ s, p (f x) := by simp
#align set.bex_image_iff Set.exists_mem_image
@[deprecated (since := "2024-02-21")] alias ball_image_iff := forall_mem_image
@[deprecated (since := "2024-02-21")] alias bex_image_iff := exists_mem_image
@[deprecated (since := "2024-02-21")] alias ⟨_, ball_image_of_ball⟩ := forall_mem_image
#align set.ball_image_of_ball Set.ball_image_of_ball
@[deprecated forall_mem_image (since := "2024-02-21")]
theorem mem_image_elim {f : α → β} {s : Set α} {C : β → Prop} (h : ∀ x : α, x ∈ s → C (f x)) :
∀ {y : β}, y ∈ f '' s → C y := forall_mem_image.2 h _
#align set.mem_image_elim Set.mem_image_elim
@[deprecated forall_mem_image (since := "2024-02-21")]
theorem mem_image_elim_on {f : α → β} {s : Set α} {C : β → Prop} {y : β} (h_y : y ∈ f '' s)
(h : ∀ x : α, x ∈ s → C (f x)) : C y := forall_mem_image.2 h _ h_y
#align set.mem_image_elim_on Set.mem_image_elim_on
-- Porting note: used to be `safe`
@[congr]
theorem image_congr {f g : α → β} {s : Set α} (h : ∀ a ∈ s, f a = g a) : f '' s = g '' s := by
ext x
exact exists_congr fun a ↦ and_congr_right fun ha ↦ by rw [h a ha]
#align set.image_congr Set.image_congr
/-- A common special case of `image_congr` -/
theorem image_congr' {f g : α → β} {s : Set α} (h : ∀ x : α, f x = g x) : f '' s = g '' s :=
image_congr fun x _ => h x
#align set.image_congr' Set.image_congr'
@[gcongr]
lemma image_mono (h : s ⊆ t) : f '' s ⊆ f '' t := by
rintro - ⟨a, ha, rfl⟩; exact mem_image_of_mem f (h ha)
theorem image_comp (f : β → γ) (g : α → β) (a : Set α) : f ∘ g '' a = f '' (g '' a) := by aesop
#align set.image_comp Set.image_comp
theorem image_comp_eq {g : β → γ} : image (g ∘ f) = image g ∘ image f := by ext; simp
/-- A variant of `image_comp`, useful for rewriting -/
theorem image_image (g : β → γ) (f : α → β) (s : Set α) : g '' (f '' s) = (fun x => g (f x)) '' s :=
(image_comp g f s).symm
#align set.image_image Set.image_image
theorem image_comm {β'} {f : β → γ} {g : α → β} {f' : α → β'} {g' : β' → γ}
(h_comm : ∀ a, f (g a) = g' (f' a)) : (s.image g).image f = (s.image f').image g' := by
simp_rw [image_image, h_comm]
#align set.image_comm Set.image_comm
theorem _root_.Function.Semiconj.set_image {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (image f) (image ga) (image gb) := fun _ =>
image_comm h
#align function.semiconj.set_image Function.Semiconj.set_image
theorem _root_.Function.Commute.set_image {f g : α → α} (h : Function.Commute f g) :
Function.Commute (image f) (image g) :=
Function.Semiconj.set_image h
#align function.commute.set_image Function.Commute.set_image
/-- Image is monotone with respect to `⊆`. See `Set.monotone_image` for the statement in
terms of `≤`. -/
@[gcongr]
theorem image_subset {a b : Set α} (f : α → β) (h : a ⊆ b) : f '' a ⊆ f '' b := by
simp only [subset_def, mem_image]
exact fun x => fun ⟨w, h1, h2⟩ => ⟨w, h h1, h2⟩
#align set.image_subset Set.image_subset
/-- `Set.image` is monotone. See `Set.image_subset` for the statement in terms of `⊆`. -/
lemma monotone_image {f : α → β} : Monotone (image f) := fun _ _ => image_subset _
#align set.monotone_image Set.monotone_image
theorem image_union (f : α → β) (s t : Set α) : f '' (s ∪ t) = f '' s ∪ f '' t :=
ext fun x =>
⟨by rintro ⟨a, h | h, rfl⟩ <;> [left; right] <;> exact ⟨_, h, rfl⟩, by
rintro (⟨a, h, rfl⟩ | ⟨a, h, rfl⟩) <;> refine ⟨_, ?_, rfl⟩
· exact mem_union_left t h
· exact mem_union_right s h⟩
#align set.image_union Set.image_union
@[simp]
theorem image_empty (f : α → β) : f '' ∅ = ∅ := by
ext
simp
#align set.image_empty Set.image_empty
theorem image_inter_subset (f : α → β) (s t : Set α) : f '' (s ∩ t) ⊆ f '' s ∩ f '' t :=
subset_inter (image_subset _ inter_subset_left) (image_subset _ inter_subset_right)
#align set.image_inter_subset Set.image_inter_subset
theorem image_inter_on {f : α → β} {s t : Set α} (h : ∀ x ∈ t, ∀ y ∈ s, f x = f y → x = y) :
f '' (s ∩ t) = f '' s ∩ f '' t :=
(image_inter_subset _ _ _).antisymm
fun b ⟨⟨a₁, ha₁, h₁⟩, ⟨a₂, ha₂, h₂⟩⟩ ↦
have : a₂ = a₁ := h _ ha₂ _ ha₁ (by simp [*])
⟨a₁, ⟨ha₁, this ▸ ha₂⟩, h₁⟩
#align set.image_inter_on Set.image_inter_on
theorem image_inter {f : α → β} {s t : Set α} (H : Injective f) : f '' (s ∩ t) = f '' s ∩ f '' t :=
image_inter_on fun _ _ _ _ h => H h
#align set.image_inter Set.image_inter
theorem image_univ_of_surjective {ι : Type*} {f : ι → β} (H : Surjective f) : f '' univ = univ :=
eq_univ_of_forall <| by simpa [image]
#align set.image_univ_of_surjective Set.image_univ_of_surjective
@[simp]
theorem image_singleton {f : α → β} {a : α} : f '' {a} = {f a} := by
ext
simp [image, eq_comm]
#align set.image_singleton Set.image_singleton
@[simp]
theorem Nonempty.image_const {s : Set α} (hs : s.Nonempty) (a : β) : (fun _ => a) '' s = {a} :=
ext fun _ =>
⟨fun ⟨_, _, h⟩ => h ▸ mem_singleton _, fun h =>
(eq_of_mem_singleton h).symm ▸ hs.imp fun _ hy => ⟨hy, rfl⟩⟩
#align set.nonempty.image_const Set.Nonempty.image_const
@[simp, mfld_simps]
theorem image_eq_empty {α β} {f : α → β} {s : Set α} : f '' s = ∅ ↔ s = ∅ := by
simp only [eq_empty_iff_forall_not_mem]
exact ⟨fun H a ha => H _ ⟨_, ha, rfl⟩, fun H b ⟨_, ha, _⟩ => H _ ha⟩
#align set.image_eq_empty Set.image_eq_empty
-- Porting note: `compl` is already defined in `Init.Set`
theorem preimage_compl_eq_image_compl [BooleanAlgebra α] (S : Set α) :
HasCompl.compl ⁻¹' S = HasCompl.compl '' S :=
Set.ext fun x =>
⟨fun h => ⟨xᶜ, h, compl_compl x⟩, fun h =>
Exists.elim h fun _ hy => (compl_eq_comm.mp hy.2).symm.subst hy.1⟩
#align set.preimage_compl_eq_image_compl Set.preimage_compl_eq_image_compl
theorem mem_compl_image [BooleanAlgebra α] (t : α) (S : Set α) :
t ∈ HasCompl.compl '' S ↔ tᶜ ∈ S := by
simp [← preimage_compl_eq_image_compl]
#align set.mem_compl_image Set.mem_compl_image
@[simp]
theorem image_id_eq : image (id : α → α) = id := by ext; simp
/-- A variant of `image_id` -/
@[simp]
theorem image_id' (s : Set α) : (fun x => x) '' s = s := by
ext
simp
#align set.image_id' Set.image_id'
theorem image_id (s : Set α) : id '' s = s := by simp
#align set.image_id Set.image_id
lemma image_iterate_eq {f : α → α} {n : ℕ} : image (f^[n]) = (image f)^[n] := by
induction n with
| zero => simp
| succ n ih => rw [iterate_succ', iterate_succ', ← ih, image_comp_eq]
theorem compl_compl_image [BooleanAlgebra α] (S : Set α) :
HasCompl.compl '' (HasCompl.compl '' S) = S := by
rw [← image_comp, compl_comp_compl, image_id]
#align set.compl_compl_image Set.compl_compl_image
theorem image_insert_eq {f : α → β} {a : α} {s : Set α} :
f '' insert a s = insert (f a) (f '' s) := by
ext
simp [and_or_left, exists_or, eq_comm, or_comm, and_comm]
#align set.image_insert_eq Set.image_insert_eq
theorem image_pair (f : α → β) (a b : α) : f '' {a, b} = {f a, f b} := by
simp only [image_insert_eq, image_singleton]
#align set.image_pair Set.image_pair
theorem image_subset_preimage_of_inverse {f : α → β} {g : β → α} (I : LeftInverse g f) (s : Set α) :
f '' s ⊆ g ⁻¹' s := fun _ ⟨a, h, e⟩ => e ▸ ((I a).symm ▸ h : g (f a) ∈ s)
#align set.image_subset_preimage_of_inverse Set.image_subset_preimage_of_inverse
theorem preimage_subset_image_of_inverse {f : α → β} {g : β → α} (I : LeftInverse g f) (s : Set β) :
f ⁻¹' s ⊆ g '' s := fun b h => ⟨f b, h, I b⟩
#align set.preimage_subset_image_of_inverse Set.preimage_subset_image_of_inverse
theorem image_eq_preimage_of_inverse {f : α → β} {g : β → α} (h₁ : LeftInverse g f)
(h₂ : RightInverse g f) : image f = preimage g :=
funext fun s =>
Subset.antisymm (image_subset_preimage_of_inverse h₁ s) (preimage_subset_image_of_inverse h₂ s)
#align set.image_eq_preimage_of_inverse Set.image_eq_preimage_of_inverse
theorem mem_image_iff_of_inverse {f : α → β} {g : β → α} {b : β} {s : Set α} (h₁ : LeftInverse g f)
(h₂ : RightInverse g f) : b ∈ f '' s ↔ g b ∈ s := by
rw [image_eq_preimage_of_inverse h₁ h₂]; rfl
#align set.mem_image_iff_of_inverse Set.mem_image_iff_of_inverse
theorem image_compl_subset {f : α → β} {s : Set α} (H : Injective f) : f '' sᶜ ⊆ (f '' s)ᶜ :=
Disjoint.subset_compl_left <| by simp [disjoint_iff_inf_le, ← image_inter H]
#align set.image_compl_subset Set.image_compl_subset
theorem subset_image_compl {f : α → β} {s : Set α} (H : Surjective f) : (f '' s)ᶜ ⊆ f '' sᶜ :=
compl_subset_iff_union.2 <| by
rw [← image_union]
simp [image_univ_of_surjective H]
#align set.subset_image_compl Set.subset_image_compl
theorem image_compl_eq {f : α → β} {s : Set α} (H : Bijective f) : f '' sᶜ = (f '' s)ᶜ :=
Subset.antisymm (image_compl_subset H.1) (subset_image_compl H.2)
#align set.image_compl_eq Set.image_compl_eq
theorem subset_image_diff (f : α → β) (s t : Set α) : f '' s \ f '' t ⊆ f '' (s \ t) := by
rw [diff_subset_iff, ← image_union, union_diff_self]
exact image_subset f subset_union_right
#align set.subset_image_diff Set.subset_image_diff
open scoped symmDiff in
theorem subset_image_symmDiff : (f '' s) ∆ (f '' t) ⊆ f '' s ∆ t :=
(union_subset_union (subset_image_diff _ _ _) <| subset_image_diff _ _ _).trans
(superset_of_eq (image_union _ _ _))
#align set.subset_image_symm_diff Set.subset_image_symmDiff
theorem image_diff {f : α → β} (hf : Injective f) (s t : Set α) : f '' (s \ t) = f '' s \ f '' t :=
Subset.antisymm
(Subset.trans (image_inter_subset _ _ _) <| inter_subset_inter_right _ <| image_compl_subset hf)
(subset_image_diff f s t)
#align set.image_diff Set.image_diff
open scoped symmDiff in
theorem image_symmDiff (hf : Injective f) (s t : Set α) : f '' s ∆ t = (f '' s) ∆ (f '' t) := by
simp_rw [Set.symmDiff_def, image_union, image_diff hf]
#align set.image_symm_diff Set.image_symmDiff
theorem Nonempty.image (f : α → β) {s : Set α} : s.Nonempty → (f '' s).Nonempty
| ⟨x, hx⟩ => ⟨f x, mem_image_of_mem f hx⟩
#align set.nonempty.image Set.Nonempty.image
theorem Nonempty.of_image {f : α → β} {s : Set α} : (f '' s).Nonempty → s.Nonempty
| ⟨_, x, hx, _⟩ => ⟨x, hx⟩
#align set.nonempty.of_image Set.Nonempty.of_image
@[simp]
theorem image_nonempty {f : α → β} {s : Set α} : (f '' s).Nonempty ↔ s.Nonempty :=
⟨Nonempty.of_image, fun h => h.image f⟩
#align set.nonempty_image_iff Set.image_nonempty
@[deprecated (since := "2024-01-06")] alias nonempty_image_iff := image_nonempty
theorem Nonempty.preimage {s : Set β} (hs : s.Nonempty) {f : α → β} (hf : Surjective f) :
(f ⁻¹' s).Nonempty :=
let ⟨y, hy⟩ := hs
let ⟨x, hx⟩ := hf y
⟨x, mem_preimage.2 <| hx.symm ▸ hy⟩
#align set.nonempty.preimage Set.Nonempty.preimage
instance (f : α → β) (s : Set α) [Nonempty s] : Nonempty (f '' s) :=
(Set.Nonempty.image f nonempty_of_nonempty_subtype).to_subtype
/-- image and preimage are a Galois connection -/
@[simp]
theorem image_subset_iff {s : Set α} {t : Set β} {f : α → β} : f '' s ⊆ t ↔ s ⊆ f ⁻¹' t :=
forall_mem_image
#align set.image_subset_iff Set.image_subset_iff
theorem image_preimage_subset (f : α → β) (s : Set β) : f '' (f ⁻¹' s) ⊆ s :=
image_subset_iff.2 Subset.rfl
#align set.image_preimage_subset Set.image_preimage_subset
theorem subset_preimage_image (f : α → β) (s : Set α) : s ⊆ f ⁻¹' (f '' s) := fun _ =>
mem_image_of_mem f
#align set.subset_preimage_image Set.subset_preimage_image
@[simp]
theorem preimage_image_eq {f : α → β} (s : Set α) (h : Injective f) : f ⁻¹' (f '' s) = s :=
Subset.antisymm (fun _ ⟨_, hy, e⟩ => h e ▸ hy) (subset_preimage_image f s)
#align set.preimage_image_eq Set.preimage_image_eq
@[simp]
theorem image_preimage_eq {f : α → β} (s : Set β) (h : Surjective f) : f '' (f ⁻¹' s) = s :=
Subset.antisymm (image_preimage_subset f s) fun x hx =>
let ⟨y, e⟩ := h x
⟨y, (e.symm ▸ hx : f y ∈ s), e⟩
#align set.image_preimage_eq Set.image_preimage_eq
@[simp]
theorem Nonempty.subset_preimage_const {s : Set α} (hs : Set.Nonempty s) (t : Set β) (a : β) :
s ⊆ (fun _ => a) ⁻¹' t ↔ a ∈ t := by
rw [← image_subset_iff, hs.image_const, singleton_subset_iff]
@[simp]
theorem preimage_eq_preimage {f : β → α} (hf : Surjective f) : f ⁻¹' s = f ⁻¹' t ↔ s = t :=
Iff.intro
fun eq => by rw [← image_preimage_eq s hf, ← image_preimage_eq t hf, eq]
fun eq => eq ▸ rfl
#align set.preimage_eq_preimage Set.preimage_eq_preimage
theorem image_inter_preimage (f : α → β) (s : Set α) (t : Set β) :
f '' (s ∩ f ⁻¹' t) = f '' s ∩ t := by
apply Subset.antisymm
· calc
f '' (s ∩ f ⁻¹' t) ⊆ f '' s ∩ f '' (f ⁻¹' t) := image_inter_subset _ _ _
_ ⊆ f '' s ∩ t := inter_subset_inter_right _ (image_preimage_subset f t)
· rintro _ ⟨⟨x, h', rfl⟩, h⟩
exact ⟨x, ⟨h', h⟩, rfl⟩
#align set.image_inter_preimage Set.image_inter_preimage
theorem image_preimage_inter (f : α → β) (s : Set α) (t : Set β) :
f '' (f ⁻¹' t ∩ s) = t ∩ f '' s := by simp only [inter_comm, image_inter_preimage]
#align set.image_preimage_inter Set.image_preimage_inter
@[simp]
theorem image_inter_nonempty_iff {f : α → β} {s : Set α} {t : Set β} :
(f '' s ∩ t).Nonempty ↔ (s ∩ f ⁻¹' t).Nonempty := by
rw [← image_inter_preimage, image_nonempty]
#align set.image_inter_nonempty_iff Set.image_inter_nonempty_iff
theorem image_diff_preimage {f : α → β} {s : Set α} {t : Set β} :
f '' (s \ f ⁻¹' t) = f '' s \ t := by simp_rw [diff_eq, ← preimage_compl, image_inter_preimage]
#align set.image_diff_preimage Set.image_diff_preimage
theorem compl_image : image (compl : Set α → Set α) = preimage compl :=
image_eq_preimage_of_inverse compl_compl compl_compl
#align set.compl_image Set.compl_image
theorem compl_image_set_of {p : Set α → Prop} : compl '' { s | p s } = { s | p sᶜ } :=
congr_fun compl_image p
#align set.compl_image_set_of Set.compl_image_set_of
theorem inter_preimage_subset (s : Set α) (t : Set β) (f : α → β) :
s ∩ f ⁻¹' t ⊆ f ⁻¹' (f '' s ∩ t) := fun _ h => ⟨mem_image_of_mem _ h.left, h.right⟩
#align set.inter_preimage_subset Set.inter_preimage_subset
theorem union_preimage_subset (s : Set α) (t : Set β) (f : α → β) :
s ∪ f ⁻¹' t ⊆ f ⁻¹' (f '' s ∪ t) := fun _ h =>
Or.elim h (fun l => Or.inl <| mem_image_of_mem _ l) fun r => Or.inr r
#align set.union_preimage_subset Set.union_preimage_subset
theorem subset_image_union (f : α → β) (s : Set α) (t : Set β) : f '' (s ∪ f ⁻¹' t) ⊆ f '' s ∪ t :=
image_subset_iff.2 (union_preimage_subset _ _ _)
#align set.subset_image_union Set.subset_image_union
theorem preimage_subset_iff {A : Set α} {B : Set β} {f : α → β} :
f ⁻¹' B ⊆ A ↔ ∀ a : α, f a ∈ B → a ∈ A :=
Iff.rfl
#align set.preimage_subset_iff Set.preimage_subset_iff
theorem image_eq_image {f : α → β} (hf : Injective f) : f '' s = f '' t ↔ s = t :=
Iff.symm <|
(Iff.intro fun eq => eq ▸ rfl) fun eq => by
rw [← preimage_image_eq s hf, ← preimage_image_eq t hf, eq]
#align set.image_eq_image Set.image_eq_image
theorem subset_image_iff {t : Set β} :
t ⊆ f '' s ↔ ∃ u, u ⊆ s ∧ f '' u = t := by
refine ⟨fun h ↦ ⟨f ⁻¹' t ∩ s, inter_subset_right, ?_⟩,
fun ⟨u, hu, hu'⟩ ↦ hu'.symm ▸ image_mono hu⟩
rwa [image_preimage_inter, inter_eq_left]
theorem image_subset_image_iff {f : α → β} (hf : Injective f) : f '' s ⊆ f '' t ↔ s ⊆ t := by
refine Iff.symm <| (Iff.intro (image_subset f)) fun h => ?_
rw [← preimage_image_eq s hf, ← preimage_image_eq t hf]
exact preimage_mono h
#align set.image_subset_image_iff Set.image_subset_image_iff
theorem prod_quotient_preimage_eq_image [s : Setoid α] (g : Quotient s → β) {h : α → β}
(Hh : h = g ∘ Quotient.mk'') (r : Set (β × β)) :
{ x : Quotient s × Quotient s | (g x.1, g x.2) ∈ r } =
(fun a : α × α => (⟦a.1⟧, ⟦a.2⟧)) '' ((fun a : α × α => (h a.1, h a.2)) ⁻¹' r) :=
Hh.symm ▸
Set.ext fun ⟨a₁, a₂⟩ =>
⟨Quot.induction_on₂ a₁ a₂ fun a₁ a₂ h => ⟨(a₁, a₂), h, rfl⟩, fun ⟨⟨b₁, b₂⟩, h₁, h₂⟩ =>
show (g a₁, g a₂) ∈ r from
have h₃ : ⟦b₁⟧ = a₁ ∧ ⟦b₂⟧ = a₂ := Prod.ext_iff.1 h₂
h₃.1 ▸ h₃.2 ▸ h₁⟩
#align set.prod_quotient_preimage_eq_image Set.prod_quotient_preimage_eq_image
theorem exists_image_iff (f : α → β) (x : Set α) (P : β → Prop) :
(∃ a : f '' x, P a) ↔ ∃ a : x, P (f a) :=
⟨fun ⟨a, h⟩ => ⟨⟨_, a.prop.choose_spec.1⟩, a.prop.choose_spec.2.symm ▸ h⟩, fun ⟨a, h⟩ =>
⟨⟨_, _, a.prop, rfl⟩, h⟩⟩
#align set.exists_image_iff Set.exists_image_iff
theorem imageFactorization_eq {f : α → β} {s : Set α} :
Subtype.val ∘ imageFactorization f s = f ∘ Subtype.val :=
funext fun _ => rfl
#align set.image_factorization_eq Set.imageFactorization_eq
theorem surjective_onto_image {f : α → β} {s : Set α} : Surjective (imageFactorization f s) :=
fun ⟨_, ⟨a, ha, rfl⟩⟩ => ⟨⟨a, ha⟩, rfl⟩
#align set.surjective_onto_image Set.surjective_onto_image
/-- If the only elements outside `s` are those left fixed by `σ`, then mapping by `σ` has no effect.
-/
theorem image_perm {s : Set α} {σ : Equiv.Perm α} (hs : { a : α | σ a ≠ a } ⊆ s) : σ '' s = s := by
ext i
obtain hi | hi := eq_or_ne (σ i) i
· refine ⟨?_, fun h => ⟨i, h, hi⟩⟩
rintro ⟨j, hj, h⟩
rwa [σ.injective (hi.trans h.symm)]
· refine iff_of_true ⟨σ.symm i, hs fun h => hi ?_, σ.apply_symm_apply _⟩ (hs hi)
convert congr_arg σ h <;> exact (σ.apply_symm_apply _).symm
#align set.image_perm Set.image_perm
end Image
/-! ### Lemmas about the powerset and image. -/
/-- The powerset of `{a} ∪ s` is `𝒫 s` together with `{a} ∪ t` for each `t ∈ 𝒫 s`. -/
theorem powerset_insert (s : Set α) (a : α) : 𝒫 insert a s = 𝒫 s ∪ insert a '' 𝒫 s := by
ext t
simp_rw [mem_union, mem_image, mem_powerset_iff]
constructor
· intro h
by_cases hs : a ∈ t
· right
refine ⟨t \ {a}, ?_, ?_⟩
· rw [diff_singleton_subset_iff]
assumption
· rw [insert_diff_singleton, insert_eq_of_mem hs]
· left
exact (subset_insert_iff_of_not_mem hs).mp h
· rintro (h | ⟨s', h₁, rfl⟩)
· exact subset_trans h (subset_insert a s)
· exact insert_subset_insert h₁
#align set.powerset_insert Set.powerset_insert
/-! ### Lemmas about range of a function. -/
section Range
variable {f : ι → α} {s t : Set α}
theorem forall_mem_range {p : α → Prop} : (∀ a ∈ range f, p a) ↔ ∀ i, p (f i) := by simp
#align set.forall_range_iff Set.forall_mem_range
@[deprecated (since := "2024-02-21")] alias forall_range_iff := forall_mem_range
theorem forall_subtype_range_iff {p : range f → Prop} :
(∀ a : range f, p a) ↔ ∀ i, p ⟨f i, mem_range_self _⟩ :=
⟨fun H i => H _, fun H ⟨y, i, hi⟩ => by
subst hi
apply H⟩
#align set.forall_subtype_range_iff Set.forall_subtype_range_iff
theorem exists_range_iff {p : α → Prop} : (∃ a ∈ range f, p a) ↔ ∃ i, p (f i) := by simp
#align set.exists_range_iff Set.exists_range_iff
@[deprecated (since := "2024-03-10")]
alias exists_range_iff' := exists_range_iff
#align set.exists_range_iff' Set.exists_range_iff'
theorem exists_subtype_range_iff {p : range f → Prop} :
(∃ a : range f, p a) ↔ ∃ i, p ⟨f i, mem_range_self _⟩ :=
⟨fun ⟨⟨a, i, hi⟩, ha⟩ => by
subst a
exact ⟨i, ha⟩,
fun ⟨i, hi⟩ => ⟨_, hi⟩⟩
#align set.exists_subtype_range_iff Set.exists_subtype_range_iff
theorem range_iff_surjective : range f = univ ↔ Surjective f :=
eq_univ_iff_forall
#align set.range_iff_surjective Set.range_iff_surjective
alias ⟨_, _root_.Function.Surjective.range_eq⟩ := range_iff_surjective
#align function.surjective.range_eq Function.Surjective.range_eq
@[simp]
theorem subset_range_of_surjective {f : α → β} (h : Surjective f) (s : Set β) :
s ⊆ range f := Surjective.range_eq h ▸ subset_univ s
@[simp]
theorem image_univ {f : α → β} : f '' univ = range f := by
ext
simp [image, range]
#align set.image_univ Set.image_univ
@[simp]
theorem preimage_eq_univ_iff {f : α → β} {s} : f ⁻¹' s = univ ↔ range f ⊆ s := by
rw [← univ_subset_iff, ← image_subset_iff, image_univ]
theorem image_subset_range (f : α → β) (s) : f '' s ⊆ range f := by
rw [← image_univ]; exact image_subset _ (subset_univ _)
#align set.image_subset_range Set.image_subset_range
theorem mem_range_of_mem_image (f : α → β) (s) {x : β} (h : x ∈ f '' s) : x ∈ range f :=
image_subset_range f s h
#align set.mem_range_of_mem_image Set.mem_range_of_mem_image
theorem _root_.Nat.mem_range_succ (i : ℕ) : i ∈ range Nat.succ ↔ 0 < i :=
⟨by
rintro ⟨n, rfl⟩
exact Nat.succ_pos n, fun h => ⟨_, Nat.succ_pred_eq_of_pos h⟩⟩
#align nat.mem_range_succ Nat.mem_range_succ
theorem Nonempty.preimage' {s : Set β} (hs : s.Nonempty) {f : α → β} (hf : s ⊆ range f) :
(f ⁻¹' s).Nonempty :=
let ⟨_, hy⟩ := hs
let ⟨x, hx⟩ := hf hy
⟨x, Set.mem_preimage.2 <| hx.symm ▸ hy⟩
#align set.nonempty.preimage' Set.Nonempty.preimage'
theorem range_comp (g : α → β) (f : ι → α) : range (g ∘ f) = g '' range f := by aesop
#align set.range_comp Set.range_comp
theorem range_subset_iff : range f ⊆ s ↔ ∀ y, f y ∈ s :=
forall_mem_range
#align set.range_subset_iff Set.range_subset_iff
theorem range_subset_range_iff_exists_comp {f : α → γ} {g : β → γ} :
range f ⊆ range g ↔ ∃ h : α → β, f = g ∘ h := by
simp only [range_subset_iff, mem_range, Classical.skolem, Function.funext_iff, (· ∘ ·), eq_comm]
theorem range_eq_iff (f : α → β) (s : Set β) :
range f = s ↔ (∀ a, f a ∈ s) ∧ ∀ b ∈ s, ∃ a, f a = b := by
rw [← range_subset_iff]
exact le_antisymm_iff
#align set.range_eq_iff Set.range_eq_iff
theorem range_comp_subset_range (f : α → β) (g : β → γ) : range (g ∘ f) ⊆ range g := by
rw [range_comp]; apply image_subset_range
#align set.range_comp_subset_range Set.range_comp_subset_range
theorem range_nonempty_iff_nonempty : (range f).Nonempty ↔ Nonempty ι :=
⟨fun ⟨_, x, _⟩ => ⟨x⟩, fun ⟨x⟩ => ⟨f x, mem_range_self x⟩⟩
#align set.range_nonempty_iff_nonempty Set.range_nonempty_iff_nonempty
theorem range_nonempty [h : Nonempty ι] (f : ι → α) : (range f).Nonempty :=
range_nonempty_iff_nonempty.2 h
#align set.range_nonempty Set.range_nonempty
@[simp]
theorem range_eq_empty_iff {f : ι → α} : range f = ∅ ↔ IsEmpty ι := by
rw [← not_nonempty_iff, ← range_nonempty_iff_nonempty, not_nonempty_iff_eq_empty]
#align set.range_eq_empty_iff Set.range_eq_empty_iff
theorem range_eq_empty [IsEmpty ι] (f : ι → α) : range f = ∅ :=
range_eq_empty_iff.2 ‹_›
#align set.range_eq_empty Set.range_eq_empty
instance instNonemptyRange [Nonempty ι] (f : ι → α) : Nonempty (range f) :=
(range_nonempty f).to_subtype
@[simp]
theorem image_union_image_compl_eq_range (f : α → β) : f '' s ∪ f '' sᶜ = range f := by
rw [← image_union, ← image_univ, ← union_compl_self]
#align set.image_union_image_compl_eq_range Set.image_union_image_compl_eq_range
theorem insert_image_compl_eq_range (f : α → β) (x : α) : insert (f x) (f '' {x}ᶜ) = range f := by
rw [← image_insert_eq, insert_eq, union_compl_self, image_univ]
#align set.insert_image_compl_eq_range Set.insert_image_compl_eq_range
theorem image_preimage_eq_range_inter {f : α → β} {t : Set β} : f '' (f ⁻¹' t) = range f ∩ t :=
ext fun x =>
⟨fun ⟨x, hx, HEq⟩ => HEq ▸ ⟨mem_range_self _, hx⟩, fun ⟨⟨y, h_eq⟩, hx⟩ =>
h_eq ▸ mem_image_of_mem f <| show y ∈ f ⁻¹' t by rw [preimage, mem_setOf, h_eq]; exact hx⟩
theorem image_preimage_eq_inter_range {f : α → β} {t : Set β} : f '' (f ⁻¹' t) = t ∩ range f := by
rw [image_preimage_eq_range_inter, inter_comm]
#align set.image_preimage_eq_inter_range Set.image_preimage_eq_inter_range
theorem image_preimage_eq_of_subset {f : α → β} {s : Set β} (hs : s ⊆ range f) :
f '' (f ⁻¹' s) = s := by rw [image_preimage_eq_range_inter, inter_eq_self_of_subset_right hs]
#align set.image_preimage_eq_of_subset Set.image_preimage_eq_of_subset
theorem image_preimage_eq_iff {f : α → β} {s : Set β} : f '' (f ⁻¹' s) = s ↔ s ⊆ range f :=
⟨by
intro h
rw [← h]
apply image_subset_range,
image_preimage_eq_of_subset⟩
#align set.image_preimage_eq_iff Set.image_preimage_eq_iff
theorem subset_range_iff_exists_image_eq {f : α → β} {s : Set β} : s ⊆ range f ↔ ∃ t, f '' t = s :=
⟨fun h => ⟨_, image_preimage_eq_iff.2 h⟩, fun ⟨_, ht⟩ => ht ▸ image_subset_range _ _⟩
#align set.subset_range_iff_exists_image_eq Set.subset_range_iff_exists_image_eq
theorem range_image (f : α → β) : range (image f) = 𝒫 range f :=
ext fun _ => subset_range_iff_exists_image_eq.symm
#align set.range_image Set.range_image
@[simp]
theorem exists_subset_range_and_iff {f : α → β} {p : Set β → Prop} :
(∃ s, s ⊆ range f ∧ p s) ↔ ∃ s, p (f '' s) := by
rw [← exists_range_iff, range_image]; rfl
#align set.exists_subset_range_and_iff Set.exists_subset_range_and_iff
theorem exists_subset_range_iff {f : α → β} {p : Set β → Prop} :
(∃ (s : _) (_ : s ⊆ range f), p s) ↔ ∃ s, p (f '' s) := by simp
#align set.exists_subset_range_iff Set.exists_subset_range_iff
theorem forall_subset_range_iff {f : α → β} {p : Set β → Prop} :
(∀ s, s ⊆ range f → p s) ↔ ∀ s, p (f '' s) := by
rw [← forall_mem_range, range_image]; rfl
@[simp]
theorem preimage_subset_preimage_iff {s t : Set α} {f : β → α} (hs : s ⊆ range f) :
f ⁻¹' s ⊆ f ⁻¹' t ↔ s ⊆ t := by
constructor
· intro h x hx
rcases hs hx with ⟨y, rfl⟩
exact h hx
intro h x; apply h
#align set.preimage_subset_preimage_iff Set.preimage_subset_preimage_iff
theorem preimage_eq_preimage' {s t : Set α} {f : β → α} (hs : s ⊆ range f) (ht : t ⊆ range f) :
f ⁻¹' s = f ⁻¹' t ↔ s = t := by
constructor
· intro h
apply Subset.antisymm
· rw [← preimage_subset_preimage_iff hs, h]
· rw [← preimage_subset_preimage_iff ht, h]
rintro rfl; rfl
#align set.preimage_eq_preimage' Set.preimage_eq_preimage'
-- Porting note:
-- @[simp] `simp` can prove this
theorem preimage_inter_range {f : α → β} {s : Set β} : f ⁻¹' (s ∩ range f) = f ⁻¹' s :=
Set.ext fun x => and_iff_left ⟨x, rfl⟩
#align set.preimage_inter_range Set.preimage_inter_range
-- Porting note:
-- @[simp] `simp` can prove this
theorem preimage_range_inter {f : α → β} {s : Set β} : f ⁻¹' (range f ∩ s) = f ⁻¹' s := by
rw [inter_comm, preimage_inter_range]
#align set.preimage_range_inter Set.preimage_range_inter
theorem preimage_image_preimage {f : α → β} {s : Set β} : f ⁻¹' (f '' (f ⁻¹' s)) = f ⁻¹' s := by
rw [image_preimage_eq_range_inter, preimage_range_inter]
#align set.preimage_image_preimage Set.preimage_image_preimage
@[simp, mfld_simps]
theorem range_id : range (@id α) = univ :=
range_iff_surjective.2 surjective_id
#align set.range_id Set.range_id
@[simp, mfld_simps]
theorem range_id' : (range fun x : α => x) = univ :=
range_id
#align set.range_id' Set.range_id'
@[simp]
theorem _root_.Prod.range_fst [Nonempty β] : range (Prod.fst : α × β → α) = univ :=
Prod.fst_surjective.range_eq
#align prod.range_fst Prod.range_fst
@[simp]
theorem _root_.Prod.range_snd [Nonempty α] : range (Prod.snd : α × β → β) = univ :=
Prod.snd_surjective.range_eq
#align prod.range_snd Prod.range_snd
@[simp]
theorem range_eval {α : ι → Sort _} [∀ i, Nonempty (α i)] (i : ι) :
range (eval i : (∀ i, α i) → α i) = univ :=
(surjective_eval i).range_eq
#align set.range_eval Set.range_eval
theorem range_inl : range (@Sum.inl α β) = {x | Sum.isLeft x} := by ext (_|_) <;> simp
#align set.range_inl Set.range_inl
theorem range_inr : range (@Sum.inr α β) = {x | Sum.isRight x} := by ext (_|_) <;> simp
#align set.range_inr Set.range_inr
theorem isCompl_range_inl_range_inr : IsCompl (range <| @Sum.inl α β) (range Sum.inr) :=
IsCompl.of_le
(by
rintro y ⟨⟨x₁, rfl⟩, ⟨x₂, h⟩⟩
exact Sum.noConfusion h)
(by rintro (x | y) - <;> [left; right] <;> exact mem_range_self _)
#align set.is_compl_range_inl_range_inr Set.isCompl_range_inl_range_inr
@[simp]
theorem range_inl_union_range_inr : range (Sum.inl : α → Sum α β) ∪ range Sum.inr = univ :=
isCompl_range_inl_range_inr.sup_eq_top
#align set.range_inl_union_range_inr Set.range_inl_union_range_inr
@[simp]
theorem range_inl_inter_range_inr : range (Sum.inl : α → Sum α β) ∩ range Sum.inr = ∅ :=
isCompl_range_inl_range_inr.inf_eq_bot
#align set.range_inl_inter_range_inr Set.range_inl_inter_range_inr
@[simp]
theorem range_inr_union_range_inl : range (Sum.inr : β → Sum α β) ∪ range Sum.inl = univ :=
isCompl_range_inl_range_inr.symm.sup_eq_top
#align set.range_inr_union_range_inl Set.range_inr_union_range_inl
@[simp]
theorem range_inr_inter_range_inl : range (Sum.inr : β → Sum α β) ∩ range Sum.inl = ∅ :=
isCompl_range_inl_range_inr.symm.inf_eq_bot
#align set.range_inr_inter_range_inl Set.range_inr_inter_range_inl
@[simp]
theorem preimage_inl_image_inr (s : Set β) : Sum.inl ⁻¹' (@Sum.inr α β '' s) = ∅ := by
ext
simp
#align set.preimage_inl_image_inr Set.preimage_inl_image_inr
@[simp]
theorem preimage_inr_image_inl (s : Set α) : Sum.inr ⁻¹' (@Sum.inl α β '' s) = ∅ := by
ext
simp
#align set.preimage_inr_image_inl Set.preimage_inr_image_inl
@[simp]
theorem preimage_inl_range_inr : Sum.inl ⁻¹' range (Sum.inr : β → Sum α β) = ∅ := by
rw [← image_univ, preimage_inl_image_inr]
#align set.preimage_inl_range_inr Set.preimage_inl_range_inr
@[simp]
| Mathlib/Data/Set/Image.lean | 929 | 930 | theorem preimage_inr_range_inl : Sum.inr ⁻¹' range (Sum.inl : α → Sum α β) = ∅ := by |
rw [← image_univ, preimage_inr_image_inl]
|
/-
Copyright (c) 2021 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Measure.Typeclasses
import Mathlib.Analysis.Complex.Basic
#align_import measure_theory.measure.vector_measure from "leanprover-community/mathlib"@"70a4f2197832bceab57d7f41379b2592d1110570"
/-!
# Vector valued measures
This file defines vector valued measures, which are σ-additive functions from a set to an add monoid
`M` such that it maps the empty set and non-measurable sets to zero. In the case
that `M = ℝ`, we called the vector measure a signed measure and write `SignedMeasure α`.
Similarly, when `M = ℂ`, we call the measure a complex measure and write `ComplexMeasure α`.
## Main definitions
* `MeasureTheory.VectorMeasure` is a vector valued, σ-additive function that maps the empty
and non-measurable set to zero.
* `MeasureTheory.VectorMeasure.map` is the pushforward of a vector measure along a function.
* `MeasureTheory.VectorMeasure.restrict` is the restriction of a vector measure on some set.
## Notation
* `v ≤[i] w` means that the vector measure `v` restricted on the set `i` is less than or equal
to the vector measure `w` restricted on `i`, i.e. `v.restrict i ≤ w.restrict i`.
## Implementation notes
We require all non-measurable sets to be mapped to zero in order for the extensionality lemma
to only compare the underlying functions for measurable sets.
We use `HasSum` instead of `tsum` in the definition of vector measures in comparison to `Measure`
since this provides summability.
## Tags
vector measure, signed measure, complex measure
-/
noncomputable section
open scoped Classical
open NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β : Type*} {m : MeasurableSpace α}
/-- A vector measure on a measurable space `α` is a σ-additive `M`-valued function (for some `M`
an add monoid) such that the empty set and non-measurable sets are mapped to zero. -/
structure VectorMeasure (α : Type*) [MeasurableSpace α] (M : Type*) [AddCommMonoid M]
[TopologicalSpace M] where
measureOf' : Set α → M
empty' : measureOf' ∅ = 0
not_measurable' ⦃i : Set α⦄ : ¬MeasurableSet i → measureOf' i = 0
m_iUnion' ⦃f : ℕ → Set α⦄ : (∀ i, MeasurableSet (f i)) → Pairwise (Disjoint on f) →
HasSum (fun i => measureOf' (f i)) (measureOf' (⋃ i, f i))
#align measure_theory.vector_measure MeasureTheory.VectorMeasure
#align measure_theory.vector_measure.measure_of' MeasureTheory.VectorMeasure.measureOf'
#align measure_theory.vector_measure.empty' MeasureTheory.VectorMeasure.empty'
#align measure_theory.vector_measure.not_measurable' MeasureTheory.VectorMeasure.not_measurable'
#align measure_theory.vector_measure.m_Union' MeasureTheory.VectorMeasure.m_iUnion'
/-- A `SignedMeasure` is an `ℝ`-vector measure. -/
abbrev SignedMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℝ
#align measure_theory.signed_measure MeasureTheory.SignedMeasure
/-- A `ComplexMeasure` is a `ℂ`-vector measure. -/
abbrev ComplexMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℂ
#align measure_theory.complex_measure MeasureTheory.ComplexMeasure
open Set MeasureTheory
namespace VectorMeasure
section
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
attribute [coe] VectorMeasure.measureOf'
instance instCoeFun : CoeFun (VectorMeasure α M) fun _ => Set α → M :=
⟨VectorMeasure.measureOf'⟩
#align measure_theory.vector_measure.has_coe_to_fun MeasureTheory.VectorMeasure.instCoeFun
initialize_simps_projections VectorMeasure (measureOf' → apply)
#noalign measure_theory.vector_measure.measure_of_eq_coe
@[simp]
theorem empty (v : VectorMeasure α M) : v ∅ = 0 :=
v.empty'
#align measure_theory.vector_measure.empty MeasureTheory.VectorMeasure.empty
theorem not_measurable (v : VectorMeasure α M) {i : Set α} (hi : ¬MeasurableSet i) : v i = 0 :=
v.not_measurable' hi
#align measure_theory.vector_measure.not_measurable MeasureTheory.VectorMeasure.not_measurable
theorem m_iUnion (v : VectorMeasure α M) {f : ℕ → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) :=
v.m_iUnion' hf₁ hf₂
#align measure_theory.vector_measure.m_Union MeasureTheory.VectorMeasure.m_iUnion
theorem of_disjoint_iUnion_nat [T2Space M] (v : VectorMeasure α M) {f : ℕ → Set α}
(hf₁ : ∀ i, MeasurableSet (f i)) (hf₂ : Pairwise (Disjoint on f)) :
v (⋃ i, f i) = ∑' i, v (f i) :=
(v.m_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union_nat MeasureTheory.VectorMeasure.of_disjoint_iUnion_nat
theorem coe_injective : @Function.Injective (VectorMeasure α M) (Set α → M) (⇑) := fun v w h => by
cases v
cases w
congr
#align measure_theory.vector_measure.coe_injective MeasureTheory.VectorMeasure.coe_injective
theorem ext_iff' (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, v i = w i := by
rw [← coe_injective.eq_iff, Function.funext_iff]
#align measure_theory.vector_measure.ext_iff' MeasureTheory.VectorMeasure.ext_iff'
theorem ext_iff (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, MeasurableSet i → v i = w i := by
constructor
· rintro rfl _ _
rfl
· rw [ext_iff']
intro h i
by_cases hi : MeasurableSet i
· exact h i hi
· simp_rw [not_measurable _ hi]
#align measure_theory.vector_measure.ext_iff MeasureTheory.VectorMeasure.ext_iff
@[ext]
theorem ext {s t : VectorMeasure α M} (h : ∀ i : Set α, MeasurableSet i → s i = t i) : s = t :=
(ext_iff s t).2 h
#align measure_theory.vector_measure.ext MeasureTheory.VectorMeasure.ext
variable [T2Space M] {v : VectorMeasure α M} {f : ℕ → Set α}
theorem hasSum_of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) := by
cases nonempty_encodable β
set g := fun i : ℕ => ⋃ (b : β) (_ : b ∈ Encodable.decode₂ β i), f b with hg
have hg₁ : ∀ i, MeasurableSet (g i) :=
fun _ => MeasurableSet.iUnion fun b => MeasurableSet.iUnion fun _ => hf₁ b
have hg₂ : Pairwise (Disjoint on g) := Encodable.iUnion_decode₂_disjoint_on hf₂
have := v.of_disjoint_iUnion_nat hg₁ hg₂
rw [hg, Encodable.iUnion_decode₂] at this
have hg₃ : (fun i : β => v (f i)) = fun i => v (g (Encodable.encode i)) := by
ext x
rw [hg]
simp only
congr
ext y
simp only [exists_prop, Set.mem_iUnion, Option.mem_def]
constructor
· intro hy
exact ⟨x, (Encodable.decode₂_is_partial_inv _ _).2 rfl, hy⟩
· rintro ⟨b, hb₁, hb₂⟩
rw [Encodable.decode₂_is_partial_inv _ _] at hb₁
rwa [← Encodable.encode_injective hb₁]
rw [Summable.hasSum_iff, this, ← tsum_iUnion_decode₂]
· exact v.empty
· rw [hg₃]
change Summable ((fun i => v (g i)) ∘ Encodable.encode)
rw [Function.Injective.summable_iff Encodable.encode_injective]
· exact (v.m_iUnion hg₁ hg₂).summable
· intro x hx
convert v.empty
simp only [g, Set.iUnion_eq_empty, Option.mem_def, not_exists, Set.mem_range] at hx ⊢
intro i hi
exact False.elim ((hx i) ((Encodable.decode₂_is_partial_inv _ _).1 hi))
#align measure_theory.vector_measure.has_sum_of_disjoint_Union MeasureTheory.VectorMeasure.hasSum_of_disjoint_iUnion
theorem of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : v (⋃ i, f i) = ∑' i, v (f i) :=
(hasSum_of_disjoint_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union MeasureTheory.VectorMeasure.of_disjoint_iUnion
theorem of_union {A B : Set α} (h : Disjoint A B) (hA : MeasurableSet A) (hB : MeasurableSet B) :
v (A ∪ B) = v A + v B := by
rw [Set.union_eq_iUnion, of_disjoint_iUnion, tsum_fintype, Fintype.sum_bool, cond, cond]
exacts [fun b => Bool.casesOn b hB hA, pairwise_disjoint_on_bool.2 h]
#align measure_theory.vector_measure.of_union MeasureTheory.VectorMeasure.of_union
theorem of_add_of_diff {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B) (h : A ⊆ B) :
v A + v (B \ A) = v B := by
rw [← of_union (@Set.disjoint_sdiff_right _ A B) hA (hB.diff hA), Set.union_diff_cancel h]
#align measure_theory.vector_measure.of_add_of_diff MeasureTheory.VectorMeasure.of_add_of_diff
theorem of_diff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [T2Space M]
{v : VectorMeasure α M} {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h : A ⊆ B) : v (B \ A) = v B - v A := by
rw [← of_add_of_diff hA hB h, add_sub_cancel_left]
#align measure_theory.vector_measure.of_diff MeasureTheory.VectorMeasure.of_diff
theorem of_diff_of_diff_eq_zero {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h' : v (B \ A) = 0) : v (A \ B) + v B = v A := by
symm
calc
v A = v (A \ B ∪ A ∩ B) := by simp only [Set.diff_union_inter]
_ = v (A \ B) + v (A ∩ B) := by
rw [of_union]
· rw [disjoint_comm]
exact Set.disjoint_of_subset_left A.inter_subset_right disjoint_sdiff_self_right
· exact hA.diff hB
· exact hA.inter hB
_ = v (A \ B) + v (A ∩ B ∪ B \ A) := by
rw [of_union, h', add_zero]
· exact Set.disjoint_of_subset_left A.inter_subset_left disjoint_sdiff_self_right
· exact hA.inter hB
· exact hB.diff hA
_ = v (A \ B) + v B := by rw [Set.union_comm, Set.inter_comm, Set.diff_union_inter]
#align measure_theory.vector_measure.of_diff_of_diff_eq_zero MeasureTheory.VectorMeasure.of_diff_of_diff_eq_zero
theorem of_iUnion_nonneg {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, 0 ≤ v (f i)) : 0 ≤ v (⋃ i, f i) :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonneg hf₃
#align measure_theory.vector_measure.of_Union_nonneg MeasureTheory.VectorMeasure.of_iUnion_nonneg
theorem of_iUnion_nonpos {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, v (f i) ≤ 0) : v (⋃ i, f i) ≤ 0 :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonpos hf₃
#align measure_theory.vector_measure.of_Union_nonpos MeasureTheory.VectorMeasure.of_iUnion_nonpos
theorem of_nonneg_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : 0 ≤ s A) (hB₂ : 0 ≤ s B)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonneg_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonneg_disjoint_union_eq_zero
theorem of_nonpos_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : s A ≤ 0) (hB₂ : s B ≤ 0)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonpos_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonpos_disjoint_union_eq_zero
end
section SMul
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
/-- Given a real number `r` and a signed measure `s`, `smul r s` is the signed
measure corresponding to the function `r • s`. -/
def smul (r : R) (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := r • ⇑v
empty' := by rw [Pi.smul_apply, empty, smul_zero]
not_measurable' _ hi := by rw [Pi.smul_apply, v.not_measurable hi, smul_zero]
m_iUnion' _ hf₁ hf₂ := by exact HasSum.const_smul _ (v.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.smul MeasureTheory.VectorMeasure.smul
instance instSMul : SMul R (VectorMeasure α M) :=
⟨smul⟩
#align measure_theory.vector_measure.has_smul MeasureTheory.VectorMeasure.instSMul
@[simp]
theorem coe_smul (r : R) (v : VectorMeasure α M) : ⇑(r • v) = r • ⇑v := rfl
#align measure_theory.vector_measure.coe_smul MeasureTheory.VectorMeasure.coe_smul
theorem smul_apply (r : R) (v : VectorMeasure α M) (i : Set α) : (r • v) i = r • v i := rfl
#align measure_theory.vector_measure.smul_apply MeasureTheory.VectorMeasure.smul_apply
end SMul
section AddCommMonoid
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
instance instZero : Zero (VectorMeasure α M) :=
⟨⟨0, rfl, fun _ _ => rfl, fun _ _ _ => hasSum_zero⟩⟩
#align measure_theory.vector_measure.has_zero MeasureTheory.VectorMeasure.instZero
instance instInhabited : Inhabited (VectorMeasure α M) :=
⟨0⟩
#align measure_theory.vector_measure.inhabited MeasureTheory.VectorMeasure.instInhabited
@[simp]
theorem coe_zero : ⇑(0 : VectorMeasure α M) = 0 := rfl
#align measure_theory.vector_measure.coe_zero MeasureTheory.VectorMeasure.coe_zero
theorem zero_apply (i : Set α) : (0 : VectorMeasure α M) i = 0 := rfl
#align measure_theory.vector_measure.zero_apply MeasureTheory.VectorMeasure.zero_apply
variable [ContinuousAdd M]
/-- The sum of two vector measure is a vector measure. -/
def add (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v + w
empty' := by simp
not_measurable' _ hi := by rw [Pi.add_apply, v.not_measurable hi, w.not_measurable hi, add_zero]
m_iUnion' f hf₁ hf₂ := HasSum.add (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.add MeasureTheory.VectorMeasure.add
instance instAdd : Add (VectorMeasure α M) :=
⟨add⟩
#align measure_theory.vector_measure.has_add MeasureTheory.VectorMeasure.instAdd
@[simp]
theorem coe_add (v w : VectorMeasure α M) : ⇑(v + w) = v + w := rfl
#align measure_theory.vector_measure.coe_add MeasureTheory.VectorMeasure.coe_add
theorem add_apply (v w : VectorMeasure α M) (i : Set α) : (v + w) i = v i + w i := rfl
#align measure_theory.vector_measure.add_apply MeasureTheory.VectorMeasure.add_apply
instance instAddCommMonoid : AddCommMonoid (VectorMeasure α M) :=
Function.Injective.addCommMonoid _ coe_injective coe_zero coe_add fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_monoid MeasureTheory.VectorMeasure.instAddCommMonoid
/-- `(⇑)` is an `AddMonoidHom`. -/
@[simps]
def coeFnAddMonoidHom : VectorMeasure α M →+ Set α → M where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
#align measure_theory.vector_measure.coe_fn_add_monoid_hom MeasureTheory.VectorMeasure.coeFnAddMonoidHom
end AddCommMonoid
section AddCommGroup
variable {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
/-- The negative of a vector measure is a vector measure. -/
def neg (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := -v
empty' := by simp
not_measurable' _ hi := by rw [Pi.neg_apply, neg_eq_zero, v.not_measurable hi]
m_iUnion' f hf₁ hf₂ := HasSum.neg <| v.m_iUnion hf₁ hf₂
#align measure_theory.vector_measure.neg MeasureTheory.VectorMeasure.neg
instance instNeg : Neg (VectorMeasure α M) :=
⟨neg⟩
#align measure_theory.vector_measure.has_neg MeasureTheory.VectorMeasure.instNeg
@[simp]
theorem coe_neg (v : VectorMeasure α M) : ⇑(-v) = -v := rfl
#align measure_theory.vector_measure.coe_neg MeasureTheory.VectorMeasure.coe_neg
theorem neg_apply (v : VectorMeasure α M) (i : Set α) : (-v) i = -v i := rfl
#align measure_theory.vector_measure.neg_apply MeasureTheory.VectorMeasure.neg_apply
/-- The difference of two vector measure is a vector measure. -/
def sub (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v - w
empty' := by simp
not_measurable' _ hi := by rw [Pi.sub_apply, v.not_measurable hi, w.not_measurable hi, sub_zero]
m_iUnion' f hf₁ hf₂ := HasSum.sub (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.sub MeasureTheory.VectorMeasure.sub
instance instSub : Sub (VectorMeasure α M) :=
⟨sub⟩
#align measure_theory.vector_measure.has_sub MeasureTheory.VectorMeasure.instSub
@[simp]
theorem coe_sub (v w : VectorMeasure α M) : ⇑(v - w) = v - w := rfl
#align measure_theory.vector_measure.coe_sub MeasureTheory.VectorMeasure.coe_sub
theorem sub_apply (v w : VectorMeasure α M) (i : Set α) : (v - w) i = v i - w i := rfl
#align measure_theory.vector_measure.sub_apply MeasureTheory.VectorMeasure.sub_apply
instance instAddCommGroup : AddCommGroup (VectorMeasure α M) :=
Function.Injective.addCommGroup _ coe_injective coe_zero coe_add coe_neg coe_sub
(fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_group MeasureTheory.VectorMeasure.instAddCommGroup
end AddCommGroup
section DistribMulAction
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
instance instDistribMulAction [ContinuousAdd M] : DistribMulAction R (VectorMeasure α M) :=
Function.Injective.distribMulAction coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.distrib_mul_action MeasureTheory.VectorMeasure.instDistribMulAction
end DistribMulAction
section Module
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M]
instance instModule [ContinuousAdd M] : Module R (VectorMeasure α M) :=
Function.Injective.module R coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.module MeasureTheory.VectorMeasure.instModule
end Module
end VectorMeasure
namespace Measure
/-- A finite measure coerced into a real function is a signed measure. -/
@[simps]
def toSignedMeasure (μ : Measure α) [hμ : IsFiniteMeasure μ] : SignedMeasure α where
measureOf' := fun s : Set α => if MeasurableSet s then (μ s).toReal else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' f hf₁ hf₂ := by
simp only [*, MeasurableSet.iUnion hf₁, if_true, measure_iUnion hf₂ hf₁]
rw [ENNReal.tsum_toReal_eq]
exacts [(summable_measure_toReal hf₁ hf₂).hasSum, fun _ ↦ measure_ne_top _ _]
#align measure_theory.measure.to_signed_measure MeasureTheory.Measure.toSignedMeasure
theorem toSignedMeasure_apply_measurable {μ : Measure α} [IsFiniteMeasure μ] {i : Set α}
(hi : MeasurableSet i) : μ.toSignedMeasure i = (μ i).toReal :=
if_pos hi
#align measure_theory.measure.to_signed_measure_apply_measurable MeasureTheory.Measure.toSignedMeasure_apply_measurable
-- Without this lemma, `singularPart_neg` in `MeasureTheory.Decomposition.Lebesgue` is
-- extremely slow
theorem toSignedMeasure_congr {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
(h : μ = ν) : μ.toSignedMeasure = ν.toSignedMeasure := by
congr
#align measure_theory.measure.to_signed_measure_congr MeasureTheory.Measure.toSignedMeasure_congr
theorem toSignedMeasure_eq_toSignedMeasure_iff {μ ν : Measure α} [IsFiniteMeasure μ]
[IsFiniteMeasure ν] : μ.toSignedMeasure = ν.toSignedMeasure ↔ μ = ν := by
refine ⟨fun h => ?_, fun h => ?_⟩
· ext1 i hi
have : μ.toSignedMeasure i = ν.toSignedMeasure i := by rw [h]
rwa [toSignedMeasure_apply_measurable hi, toSignedMeasure_apply_measurable hi,
ENNReal.toReal_eq_toReal] at this
<;> exact measure_ne_top _ _
· congr
#align measure_theory.measure.to_signed_measure_eq_to_signed_measure_iff MeasureTheory.Measure.toSignedMeasure_eq_toSignedMeasure_iff
@[simp]
theorem toSignedMeasure_zero : (0 : Measure α).toSignedMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_signed_measure_zero MeasureTheory.Measure.toSignedMeasure_zero
@[simp]
theorem toSignedMeasure_add (μ ν : Measure α) [IsFiniteMeasure μ] [IsFiniteMeasure ν] :
(μ + ν).toSignedMeasure = μ.toSignedMeasure + ν.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, add_apply,
ENNReal.toReal_add (ne_of_lt (measure_lt_top _ _)) (ne_of_lt (measure_lt_top _ _)),
VectorMeasure.add_apply, toSignedMeasure_apply_measurable hi,
toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_add MeasureTheory.Measure.toSignedMeasure_add
@[simp]
theorem toSignedMeasure_smul (μ : Measure α) [IsFiniteMeasure μ] (r : ℝ≥0) :
(r • μ).toSignedMeasure = r • μ.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, VectorMeasure.smul_apply,
toSignedMeasure_apply_measurable hi, coe_smul, Pi.smul_apply, ENNReal.toReal_smul]
#align measure_theory.measure.to_signed_measure_smul MeasureTheory.Measure.toSignedMeasure_smul
/-- A measure is a vector measure over `ℝ≥0∞`. -/
@[simps]
def toENNRealVectorMeasure (μ : Measure α) : VectorMeasure α ℝ≥0∞ where
measureOf' := fun i : Set α => if MeasurableSet i then μ i else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' _ hf₁ hf₂ := by
simp only
rw [Summable.hasSum_iff ENNReal.summable, if_pos (MeasurableSet.iUnion hf₁),
MeasureTheory.measure_iUnion hf₂ hf₁]
exact tsum_congr fun n => if_pos (hf₁ n)
#align measure_theory.measure.to_ennreal_vector_measure MeasureTheory.Measure.toENNRealVectorMeasure
theorem toENNRealVectorMeasure_apply_measurable {μ : Measure α} {i : Set α} (hi : MeasurableSet i) :
μ.toENNRealVectorMeasure i = μ i :=
if_pos hi
#align measure_theory.measure.to_ennreal_vector_measure_apply_measurable MeasureTheory.Measure.toENNRealVectorMeasure_apply_measurable
@[simp]
theorem toENNRealVectorMeasure_zero : (0 : Measure α).toENNRealVectorMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_ennreal_vector_measure_zero MeasureTheory.Measure.toENNRealVectorMeasure_zero
@[simp]
theorem toENNRealVectorMeasure_add (μ ν : Measure α) :
(μ + ν).toENNRealVectorMeasure = μ.toENNRealVectorMeasure + ν.toENNRealVectorMeasure := by
refine MeasureTheory.VectorMeasure.ext fun i hi => ?_
rw [toENNRealVectorMeasure_apply_measurable hi, add_apply, VectorMeasure.add_apply,
toENNRealVectorMeasure_apply_measurable hi, toENNRealVectorMeasure_apply_measurable hi]
#align measure_theory.measure.to_ennreal_vector_measure_add MeasureTheory.Measure.toENNRealVectorMeasure_add
theorem toSignedMeasure_sub_apply {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
{i : Set α} (hi : MeasurableSet i) :
(μ.toSignedMeasure - ν.toSignedMeasure) i = (μ i).toReal - (ν i).toReal := by
rw [VectorMeasure.sub_apply, toSignedMeasure_apply_measurable hi,
Measure.toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_sub_apply MeasureTheory.Measure.toSignedMeasure_sub_apply
end Measure
namespace VectorMeasure
open Measure
section
/-- A vector measure over `ℝ≥0∞` is a measure. -/
def ennrealToMeasure {_ : MeasurableSpace α} (v : VectorMeasure α ℝ≥0∞) : Measure α :=
ofMeasurable (fun s _ => v s) v.empty fun _ hf₁ hf₂ => v.of_disjoint_iUnion_nat hf₁ hf₂
#align measure_theory.vector_measure.ennreal_to_measure MeasureTheory.VectorMeasure.ennrealToMeasure
theorem ennrealToMeasure_apply {m : MeasurableSpace α} {v : VectorMeasure α ℝ≥0∞} {s : Set α}
(hs : MeasurableSet s) : ennrealToMeasure v s = v s := by
rw [ennrealToMeasure, ofMeasurable_apply _ hs]
#align measure_theory.vector_measure.ennreal_to_measure_apply MeasureTheory.VectorMeasure.ennrealToMeasure_apply
@[simp]
theorem _root_.MeasureTheory.Measure.toENNRealVectorMeasure_ennrealToMeasure
(μ : VectorMeasure α ℝ≥0∞) :
toENNRealVectorMeasure (ennrealToMeasure μ) = μ := ext fun s hs => by
rw [toENNRealVectorMeasure_apply_measurable hs, ennrealToMeasure_apply hs]
@[simp]
theorem ennrealToMeasure_toENNRealVectorMeasure (μ : Measure α) :
ennrealToMeasure (toENNRealVectorMeasure μ) = μ := Measure.ext fun s hs => by
rw [ennrealToMeasure_apply hs, toENNRealVectorMeasure_apply_measurable hs]
/-- The equiv between `VectorMeasure α ℝ≥0∞` and `Measure α` formed by
`MeasureTheory.VectorMeasure.ennrealToMeasure` and
`MeasureTheory.Measure.toENNRealVectorMeasure`. -/
@[simps]
def equivMeasure [MeasurableSpace α] : VectorMeasure α ℝ≥0∞ ≃ Measure α where
toFun := ennrealToMeasure
invFun := toENNRealVectorMeasure
left_inv := toENNRealVectorMeasure_ennrealToMeasure
right_inv := ennrealToMeasure_toENNRealVectorMeasure
#align measure_theory.vector_measure.equiv_measure MeasureTheory.VectorMeasure.equivMeasure
end
section
variable [MeasurableSpace α] [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable (v : VectorMeasure α M)
/-- The pushforward of a vector measure along a function. -/
def map (v : VectorMeasure α M) (f : α → β) : VectorMeasure β M :=
if hf : Measurable f then
{ measureOf' := fun s => if MeasurableSet s then v (f ⁻¹' s) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro g hg₁ hg₂
simp only
convert v.m_iUnion (fun i => hf (hg₁ i)) fun i j hij => (hg₂ hij).preimage _
· rw [if_pos (hg₁ _)]
· rw [Set.preimage_iUnion, if_pos (MeasurableSet.iUnion hg₁)] }
else 0
#align measure_theory.vector_measure.map MeasureTheory.VectorMeasure.map
theorem map_not_measurable {f : α → β} (hf : ¬Measurable f) : v.map f = 0 :=
dif_neg hf
#align measure_theory.vector_measure.map_not_measurable MeasureTheory.VectorMeasure.map_not_measurable
theorem map_apply {f : α → β} (hf : Measurable f) {s : Set β} (hs : MeasurableSet s) :
v.map f s = v (f ⁻¹' s) := by
rw [map, dif_pos hf]
exact if_pos hs
#align measure_theory.vector_measure.map_apply MeasureTheory.VectorMeasure.map_apply
@[simp]
theorem map_id : v.map id = v :=
ext fun i hi => by rw [map_apply v measurable_id hi, Set.preimage_id]
#align measure_theory.vector_measure.map_id MeasureTheory.VectorMeasure.map_id
@[simp]
theorem map_zero (f : α → β) : (0 : VectorMeasure α M).map f = 0 := by
by_cases hf : Measurable f
· ext i hi
rw [map_apply _ hf hi, zero_apply, zero_apply]
· exact dif_neg hf
#align measure_theory.vector_measure.map_zero MeasureTheory.VectorMeasure.map_zero
section
variable {N : Type*} [AddCommMonoid N] [TopologicalSpace N]
/-- Given a vector measure `v` on `M` and a continuous `AddMonoidHom` `f : M → N`, `f ∘ v` is a
vector measure on `N`. -/
def mapRange (v : VectorMeasure α M) (f : M →+ N) (hf : Continuous f) : VectorMeasure α N where
measureOf' s := f (v s)
empty' := by simp only; rw [empty, AddMonoidHom.map_zero]
not_measurable' i hi := by simp only; rw [not_measurable v hi, AddMonoidHom.map_zero]
m_iUnion' g hg₁ hg₂ := HasSum.map (v.m_iUnion hg₁ hg₂) f hf
#align measure_theory.vector_measure.map_range MeasureTheory.VectorMeasure.mapRange
@[simp]
theorem mapRange_apply {f : M →+ N} (hf : Continuous f) {s : Set α} : v.mapRange f hf s = f (v s) :=
rfl
#align measure_theory.vector_measure.map_range_apply MeasureTheory.VectorMeasure.mapRange_apply
@[simp]
theorem mapRange_id : v.mapRange (AddMonoidHom.id M) continuous_id = v := by
ext
rfl
#align measure_theory.vector_measure.map_range_id MeasureTheory.VectorMeasure.mapRange_id
@[simp]
theorem mapRange_zero {f : M →+ N} (hf : Continuous f) :
mapRange (0 : VectorMeasure α M) f hf = 0 := by
ext
simp
#align measure_theory.vector_measure.map_range_zero MeasureTheory.VectorMeasure.mapRange_zero
section ContinuousAdd
variable [ContinuousAdd M] [ContinuousAdd N]
@[simp]
theorem mapRange_add {v w : VectorMeasure α M} {f : M →+ N} (hf : Continuous f) :
(v + w).mapRange f hf = v.mapRange f hf + w.mapRange f hf := by
ext
simp
#align measure_theory.vector_measure.map_range_add MeasureTheory.VectorMeasure.mapRange_add
/-- Given a continuous `AddMonoidHom` `f : M → N`, `mapRangeHom` is the `AddMonoidHom` mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeHom (f : M →+ N) (hf : Continuous f) : VectorMeasure α M →+ VectorMeasure α N where
toFun v := v.mapRange f hf
map_zero' := mapRange_zero hf
map_add' _ _ := mapRange_add hf
#align measure_theory.vector_measure.map_range_hom MeasureTheory.VectorMeasure.mapRangeHom
end ContinuousAdd
section Module
variable {R : Type*} [Semiring R] [Module R M] [Module R N]
variable [ContinuousAdd M] [ContinuousAdd N] [ContinuousConstSMul R M] [ContinuousConstSMul R N]
/-- Given a continuous linear map `f : M → N`, `mapRangeₗ` is the linear map mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeₗ (f : M →ₗ[R] N) (hf : Continuous f) : VectorMeasure α M →ₗ[R] VectorMeasure α N where
toFun v := v.mapRange f.toAddMonoidHom hf
map_add' _ _ := mapRange_add hf
map_smul' := by
intros
ext
simp
#align measure_theory.vector_measure.map_rangeₗ MeasureTheory.VectorMeasure.mapRangeₗ
end Module
end
/-- The restriction of a vector measure on some set. -/
def restrict (v : VectorMeasure α M) (i : Set α) : VectorMeasure α M :=
if hi : MeasurableSet i then
{ measureOf' := fun s => if MeasurableSet s then v (s ∩ i) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro f hf₁ hf₂
simp only
convert v.m_iUnion (fun n => (hf₁ n).inter hi)
(hf₂.mono fun i j => Disjoint.mono inf_le_left inf_le_left)
· rw [if_pos (hf₁ _)]
· rw [Set.iUnion_inter, if_pos (MeasurableSet.iUnion hf₁)] }
else 0
#align measure_theory.vector_measure.restrict MeasureTheory.VectorMeasure.restrict
theorem restrict_not_measurable {i : Set α} (hi : ¬MeasurableSet i) : v.restrict i = 0 :=
dif_neg hi
#align measure_theory.vector_measure.restrict_not_measurable MeasureTheory.VectorMeasure.restrict_not_measurable
theorem restrict_apply {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j) :
v.restrict i j = v (j ∩ i) := by
rw [restrict, dif_pos hi]
exact if_pos hj
#align measure_theory.vector_measure.restrict_apply MeasureTheory.VectorMeasure.restrict_apply
theorem restrict_eq_self {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j)
(hij : j ⊆ i) : v.restrict i j = v j := by
rw [restrict_apply v hi hj, Set.inter_eq_left.2 hij]
#align measure_theory.vector_measure.restrict_eq_self MeasureTheory.VectorMeasure.restrict_eq_self
@[simp]
theorem restrict_empty : v.restrict ∅ = 0 :=
ext fun i hi => by
rw [restrict_apply v MeasurableSet.empty hi, Set.inter_empty, v.empty, zero_apply]
#align measure_theory.vector_measure.restrict_empty MeasureTheory.VectorMeasure.restrict_empty
@[simp]
theorem restrict_univ : v.restrict Set.univ = v :=
ext fun i hi => by rw [restrict_apply v MeasurableSet.univ hi, Set.inter_univ]
#align measure_theory.vector_measure.restrict_univ MeasureTheory.VectorMeasure.restrict_univ
@[simp]
theorem restrict_zero {i : Set α} : (0 : VectorMeasure α M).restrict i = 0 := by
by_cases hi : MeasurableSet i
· ext j hj
rw [restrict_apply 0 hi hj, zero_apply, zero_apply]
· exact dif_neg hi
#align measure_theory.vector_measure.restrict_zero MeasureTheory.VectorMeasure.restrict_zero
section ContinuousAdd
variable [ContinuousAdd M]
theorem map_add (v w : VectorMeasure α M) (f : α → β) : (v + w).map f = v.map f + w.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp [map, dif_neg hf]
#align measure_theory.vector_measure.map_add MeasureTheory.VectorMeasure.map_add
/-- `VectorMeasure.map` as an additive monoid homomorphism. -/
@[simps]
def mapGm (f : α → β) : VectorMeasure α M →+ VectorMeasure β M where
toFun v := v.map f
map_zero' := map_zero f
map_add' _ _ := map_add _ _ f
#align measure_theory.vector_measure.map_gm MeasureTheory.VectorMeasure.mapGm
theorem restrict_add (v w : VectorMeasure α M) (i : Set α) :
(v + w).restrict i = v.restrict i + w.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp [restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_add MeasureTheory.VectorMeasure.restrict_add
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictGm (i : Set α) : VectorMeasure α M →+ VectorMeasure α M where
toFun v := v.restrict i
map_zero' := restrict_zero
map_add' _ _ := restrict_add _ _ i
#align measure_theory.vector_measure.restrict_gm MeasureTheory.VectorMeasure.restrictGm
end ContinuousAdd
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
@[simp]
theorem map_smul {v : VectorMeasure α M} {f : α → β} (c : R) : (c • v).map f = c • v.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp only [map, dif_neg hf]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext i
simp
#align measure_theory.vector_measure.map_smul MeasureTheory.VectorMeasure.map_smul
@[simp]
theorem restrict_smul {v : VectorMeasure α M} {i : Set α} (c : R) :
(c • v).restrict i = c • v.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp only [restrict_not_measurable _ hi]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext j
simp
#align measure_theory.vector_measure.restrict_smul MeasureTheory.VectorMeasure.restrict_smul
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M] [ContinuousAdd M]
/-- `VectorMeasure.map` as a linear map. -/
@[simps]
def mapₗ (f : α → β) : VectorMeasure α M →ₗ[R] VectorMeasure β M where
toFun v := v.map f
map_add' _ _ := map_add _ _ f
map_smul' _ _ := map_smul _
#align measure_theory.vector_measure.mapₗ MeasureTheory.VectorMeasure.mapₗ
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictₗ (i : Set α) : VectorMeasure α M →ₗ[R] VectorMeasure α M where
toFun v := v.restrict i
map_add' _ _ := restrict_add _ _ i
map_smul' _ _ := restrict_smul _
#align measure_theory.vector_measure.restrictₗ MeasureTheory.VectorMeasure.restrictₗ
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
/-- Vector measures over a partially ordered monoid is partially ordered.
This definition is consistent with `Measure.instPartialOrder`. -/
instance instPartialOrder : PartialOrder (VectorMeasure α M) where
le v w := ∀ i, MeasurableSet i → v i ≤ w i
le_refl v i _ := le_rfl
le_trans u v w h₁ h₂ i hi := le_trans (h₁ i hi) (h₂ i hi)
le_antisymm v w h₁ h₂ := ext fun i hi => le_antisymm (h₁ i hi) (h₂ i hi)
variable {u v w : VectorMeasure α M}
theorem le_iff : v ≤ w ↔ ∀ i, MeasurableSet i → v i ≤ w i := Iff.rfl
#align measure_theory.vector_measure.le_iff MeasureTheory.VectorMeasure.le_iff
theorem le_iff' : v ≤ w ↔ ∀ i, v i ≤ w i := by
refine ⟨fun h i => ?_, fun h i _ => h i⟩
by_cases hi : MeasurableSet i
· exact h i hi
· rw [v.not_measurable hi, w.not_measurable hi]
#align measure_theory.vector_measure.le_iff' MeasureTheory.VectorMeasure.le_iff'
end
set_option quotPrecheck false in -- Porting note: error message suggested to do this
scoped[MeasureTheory]
notation:50 v " ≤[" i:50 "] " w:50 =>
MeasureTheory.VectorMeasure.restrict v i ≤ MeasureTheory.VectorMeasure.restrict w i
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
variable (v w : VectorMeasure α M)
theorem restrict_le_restrict_iff {i : Set α} (hi : MeasurableSet i) :
v ≤[i] w ↔ ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j :=
⟨fun h j hj₁ hj₂ => restrict_eq_self v hi hj₁ hj₂ ▸ restrict_eq_self w hi hj₁ hj₂ ▸ h j hj₁,
fun h => le_iff.1 fun _ hj =>
(restrict_apply v hi hj).symm ▸ (restrict_apply w hi hj).symm ▸
h (hj.inter hi) Set.inter_subset_right⟩
#align measure_theory.vector_measure.restrict_le_restrict_iff MeasureTheory.VectorMeasure.restrict_le_restrict_iff
theorem subset_le_of_restrict_le_restrict {i : Set α} (hi : MeasurableSet i) (hi₂ : v ≤[i] w)
{j : Set α} (hj : j ⊆ i) : v j ≤ w j := by
by_cases hj₁ : MeasurableSet j
· exact (restrict_le_restrict_iff _ _ hi).1 hi₂ hj₁ hj
· rw [v.not_measurable hj₁, w.not_measurable hj₁]
#align measure_theory.vector_measure.subset_le_of_restrict_le_restrict MeasureTheory.VectorMeasure.subset_le_of_restrict_le_restrict
theorem restrict_le_restrict_of_subset_le {i : Set α}
(h : ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j) : v ≤[i] w := by
by_cases hi : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi).2 h
· rw [restrict_not_measurable v hi, restrict_not_measurable w hi]
#align measure_theory.vector_measure.restrict_le_restrict_of_subset_le MeasureTheory.VectorMeasure.restrict_le_restrict_of_subset_le
theorem restrict_le_restrict_subset {i j : Set α} (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w)
(hij : j ⊆ i) : v ≤[j] w :=
restrict_le_restrict_of_subset_le v w fun _ _ hk₂ =>
subset_le_of_restrict_le_restrict v w hi₁ hi₂ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_restrict_subset MeasureTheory.VectorMeasure.restrict_le_restrict_subset
theorem le_restrict_empty : v ≤[∅] w := by
intro j _
rw [restrict_empty, restrict_empty]
#align measure_theory.vector_measure.le_restrict_empty MeasureTheory.VectorMeasure.le_restrict_empty
theorem le_restrict_univ_iff_le : v ≤[Set.univ] w ↔ v ≤ w := by
constructor
· intro h s hs
have := h s hs
rwa [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ] at this
· intro h s hs
rw [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ]
exact h s hs
#align measure_theory.vector_measure.le_restrict_univ_iff_le MeasureTheory.VectorMeasure.le_restrict_univ_iff_le
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommGroup M] [TopologicalAddGroup M]
variable (v w : VectorMeasure α M)
nonrec theorem neg_le_neg {i : Set α} (hi : MeasurableSet i) (h : v ≤[i] w) : -w ≤[i] -v := by
intro j hj₁
rw [restrict_apply _ hi hj₁, restrict_apply _ hi hj₁, neg_apply, neg_apply]
refine neg_le_neg ?_
rw [← restrict_apply _ hi hj₁, ← restrict_apply _ hi hj₁]
exact h j hj₁
#align measure_theory.vector_measure.neg_le_neg MeasureTheory.VectorMeasure.neg_le_neg
@[simp]
theorem neg_le_neg_iff {i : Set α} (hi : MeasurableSet i) : -w ≤[i] -v ↔ v ≤[i] w :=
⟨fun h => neg_neg v ▸ neg_neg w ▸ neg_le_neg _ _ hi h, fun h => neg_le_neg _ _ hi h⟩
#align measure_theory.vector_measure.neg_le_neg_iff MeasureTheory.VectorMeasure.neg_le_neg_iff
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M] [OrderClosedTopology M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem restrict_le_restrict_iUnion {f : ℕ → Set α} (hf₁ : ∀ n, MeasurableSet (f n))
(hf₂ : ∀ n, v ≤[f n] w) : v ≤[⋃ n, f n] w := by
refine restrict_le_restrict_of_subset_le v w fun a ha₁ ha₂ => ?_
have ha₃ : ⋃ n, a ∩ disjointed f n = a := by
rwa [← Set.inter_iUnion, iUnion_disjointed, Set.inter_eq_left]
have ha₄ : Pairwise (Disjoint on fun n => a ∩ disjointed f n) :=
(disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
rw [← ha₃, v.of_disjoint_iUnion_nat _ ha₄, w.of_disjoint_iUnion_nat _ ha₄]
· refine tsum_le_tsum (fun n => (restrict_le_restrict_iff v w (hf₁ n)).1 (hf₂ n) ?_ ?_) ?_ ?_
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact Set.Subset.trans Set.inter_subset_right (disjointed_subset _ _)
· refine (v.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· refine (w.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· intro n
exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact fun n => ha₁.inter (MeasurableSet.disjointed hf₁ n)
#align measure_theory.vector_measure.restrict_le_restrict_Union MeasureTheory.VectorMeasure.restrict_le_restrict_iUnion
theorem restrict_le_restrict_countable_iUnion [Countable β] {f : β → Set α}
(hf₁ : ∀ b, MeasurableSet (f b)) (hf₂ : ∀ b, v ≤[f b] w) : v ≤[⋃ b, f b] w := by
cases nonempty_encodable β
rw [← Encodable.iUnion_decode₂]
refine restrict_le_restrict_iUnion v w ?_ ?_
· intro n
measurability
· intro n
cases' Encodable.decode₂ β n with b
· simp
· simp [hf₂ b]
#align measure_theory.vector_measure.restrict_le_restrict_countable_Union MeasureTheory.VectorMeasure.restrict_le_restrict_countable_iUnion
theorem restrict_le_restrict_union (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w) (hj₁ : MeasurableSet j)
(hj₂ : v ≤[j] w) : v ≤[i ∪ j] w := by
rw [Set.union_eq_iUnion]
refine restrict_le_restrict_countable_iUnion v w ?_ ?_
· measurability
· rintro (_ | _) <;> simpa
#align measure_theory.vector_measure.restrict_le_restrict_union MeasureTheory.VectorMeasure.restrict_le_restrict_union
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem nonneg_of_zero_le_restrict (hi₂ : 0 ≤[i] v) : 0 ≤ v i := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonneg_of_zero_le_restrict MeasureTheory.VectorMeasure.nonneg_of_zero_le_restrict
theorem nonpos_of_restrict_le_zero (hi₂ : v ≤[i] 0) : v i ≤ 0 := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonpos_of_restrict_le_zero MeasureTheory.VectorMeasure.nonpos_of_restrict_le_zero
theorem zero_le_restrict_not_measurable (hi : ¬MeasurableSet i) : 0 ≤[i] v := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.zero_le_restrict_not_measurable MeasureTheory.VectorMeasure.zero_le_restrict_not_measurable
theorem restrict_le_zero_of_not_measurable (hi : ¬MeasurableSet i) : v ≤[i] 0 := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_le_zero_of_not_measurable MeasureTheory.VectorMeasure.restrict_le_zero_of_not_measurable
theorem measurable_of_not_zero_le_restrict (hi : ¬0 ≤[i] v) : MeasurableSet i :=
Not.imp_symm (zero_le_restrict_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_zero_le_restrict MeasureTheory.VectorMeasure.measurable_of_not_zero_le_restrict
theorem measurable_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) : MeasurableSet i :=
Not.imp_symm (restrict_le_zero_of_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_restrict_le_zero MeasureTheory.VectorMeasure.measurable_of_not_restrict_le_zero
theorem zero_le_restrict_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : 0 ≤[i] v) : 0 ≤[j] v :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.zero_le_restrict_subset MeasureTheory.VectorMeasure.zero_le_restrict_subset
theorem restrict_le_zero_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : v ≤[i] 0) : v ≤[j] 0 :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_zero_subset MeasureTheory.VectorMeasure.restrict_le_zero_subset
end
section
variable {M : Type*} [TopologicalSpace M] [LinearOrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem exists_pos_measure_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) :
∃ j : Set α, MeasurableSet j ∧ j ⊆ i ∧ 0 < v j := by
have hi₁ : MeasurableSet i := measurable_of_not_restrict_le_zero _ hi
rw [restrict_le_restrict_iff _ _ hi₁] at hi
push_neg at hi
exact hi
#align measure_theory.vector_measure.exists_pos_measure_of_not_restrict_le_zero MeasureTheory.VectorMeasure.exists_pos_measure_of_not_restrict_le_zero
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
[CovariantClass M M (· + ·) (· ≤ ·)] [ContinuousAdd M]
instance covariant_add_le :
CovariantClass (VectorMeasure α M) (VectorMeasure α M) (· + ·) (· ≤ ·) :=
⟨fun _ _ _ h i hi => add_le_add_left (h i hi) _⟩
#align measure_theory.vector_measure.covariant_add_le MeasureTheory.VectorMeasure.covariant_add_le
end
section
variable {L M N : Type*}
variable [AddCommMonoid L] [TopologicalSpace L] [AddCommMonoid M] [TopologicalSpace M]
[AddCommMonoid N] [TopologicalSpace N]
/-- A vector measure `v` is absolutely continuous with respect to a measure `μ` if for all sets
`s`, `μ s = 0`, we have `v s = 0`. -/
def AbsolutelyContinuous (v : VectorMeasure α M) (w : VectorMeasure α N) :=
∀ ⦃s : Set α⦄, w s = 0 → v s = 0
#align measure_theory.vector_measure.absolutely_continuous MeasureTheory.VectorMeasure.AbsolutelyContinuous
@[inherit_doc VectorMeasure.AbsolutelyContinuous]
scoped[MeasureTheory] infixl:50 " ≪ᵥ " => MeasureTheory.VectorMeasure.AbsolutelyContinuous
open MeasureTheory
namespace AbsolutelyContinuous
variable {v : VectorMeasure α M} {w : VectorMeasure α N}
theorem mk (h : ∀ ⦃s : Set α⦄, MeasurableSet s → w s = 0 → v s = 0) : v ≪ᵥ w := by
intro s hs
by_cases hmeas : MeasurableSet s
· exact h hmeas hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.mk MeasureTheory.VectorMeasure.AbsolutelyContinuous.mk
theorem eq {w : VectorMeasure α M} (h : v = w) : v ≪ᵥ w :=
fun _ hs => h.symm ▸ hs
#align measure_theory.vector_measure.absolutely_continuous.eq MeasureTheory.VectorMeasure.AbsolutelyContinuous.eq
@[refl]
theorem refl (v : VectorMeasure α M) : v ≪ᵥ v :=
eq rfl
#align measure_theory.vector_measure.absolutely_continuous.refl MeasureTheory.VectorMeasure.AbsolutelyContinuous.refl
@[trans]
theorem trans {u : VectorMeasure α L} {v : VectorMeasure α M} {w : VectorMeasure α N} (huv : u ≪ᵥ v)
(hvw : v ≪ᵥ w) : u ≪ᵥ w :=
fun _ hs => huv <| hvw hs
#align measure_theory.vector_measure.absolutely_continuous.trans MeasureTheory.VectorMeasure.AbsolutelyContinuous.trans
theorem zero (v : VectorMeasure α N) : (0 : VectorMeasure α M) ≪ᵥ v :=
fun s _ => VectorMeasure.zero_apply s
#align measure_theory.vector_measure.absolutely_continuous.zero MeasureTheory.VectorMeasure.AbsolutelyContinuous.zero
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : -v ≪ᵥ w := by
intro s hs
rw [neg_apply, h hs, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.neg_left MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : v ≪ᵥ -w := by
intro s hs
rw [neg_apply, neg_eq_zero] at hs
exact h hs
#align measure_theory.vector_measure.absolutely_continuous.neg_right MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_right
theorem add [ContinuousAdd M] {v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w)
(hv₂ : v₂ ≪ᵥ w) : v₁ + v₂ ≪ᵥ w := by
intro s hs
rw [add_apply, hv₁ hs, hv₂ hs, zero_add]
#align measure_theory.vector_measure.absolutely_continuous.add MeasureTheory.VectorMeasure.AbsolutelyContinuous.add
theorem sub {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w) (hv₂ : v₂ ≪ᵥ w) :
v₁ - v₂ ≪ᵥ w := by
intro s hs
rw [sub_apply, hv₁ hs, hv₂ hs, zero_sub, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.sub MeasureTheory.VectorMeasure.AbsolutelyContinuous.sub
theorem smul {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] {r : R}
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : r • v ≪ᵥ w := by
intro s hs
rw [smul_apply, h hs, smul_zero]
#align measure_theory.vector_measure.absolutely_continuous.smul MeasureTheory.VectorMeasure.AbsolutelyContinuous.smul
theorem map [MeasureSpace β] (h : v ≪ᵥ w) (f : α → β) : v.map f ≪ᵥ w.map f := by
by_cases hf : Measurable f
· refine mk fun s hs hws => ?_
rw [map_apply _ hf hs] at hws ⊢
exact h hws
· intro s _
rw [map_not_measurable v hf, zero_apply]
#align measure_theory.vector_measure.absolutely_continuous.map MeasureTheory.VectorMeasure.AbsolutelyContinuous.map
theorem ennrealToMeasure {μ : VectorMeasure α ℝ≥0∞} :
(∀ ⦃s : Set α⦄, μ.ennrealToMeasure s = 0 → v s = 0) ↔ v ≪ᵥ μ := by
constructor <;> intro h
· refine mk fun s hmeas hs => h ?_
rw [← hs, ennrealToMeasure_apply hmeas]
· intro s hs
by_cases hmeas : MeasurableSet s
· rw [ennrealToMeasure_apply hmeas] at hs
exact h hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.ennreal_to_measure MeasureTheory.VectorMeasure.AbsolutelyContinuous.ennrealToMeasure
end AbsolutelyContinuous
/-- Two vector measures `v` and `w` are said to be mutually singular if there exists a measurable
set `s`, such that for all `t ⊆ s`, `v t = 0` and for all `t ⊆ sᶜ`, `w t = 0`.
We note that we do not require the measurability of `t` in the definition since this makes it easier
to use. This is equivalent to the definition which requires measurability. To prove
`MutuallySingular` with the measurability condition, use
`MeasureTheory.VectorMeasure.MutuallySingular.mk`. -/
def MutuallySingular (v : VectorMeasure α M) (w : VectorMeasure α N) : Prop :=
∃ s : Set α, MeasurableSet s ∧ (∀ t ⊆ s, v t = 0) ∧ ∀ t ⊆ sᶜ, w t = 0
#align measure_theory.vector_measure.mutually_singular MeasureTheory.VectorMeasure.MutuallySingular
@[inherit_doc VectorMeasure.MutuallySingular]
scoped[MeasureTheory] infixl:60 " ⟂ᵥ " => MeasureTheory.VectorMeasure.MutuallySingular
namespace MutuallySingular
variable {v v₁ v₂ : VectorMeasure α M} {w w₁ w₂ : VectorMeasure α N}
theorem mk (s : Set α) (hs : MeasurableSet s) (h₁ : ∀ t ⊆ s, MeasurableSet t → v t = 0)
(h₂ : ∀ t ⊆ sᶜ, MeasurableSet t → w t = 0) : v ⟂ᵥ w := by
refine ⟨s, hs, fun t hst => ?_, fun t hst => ?_⟩ <;> by_cases ht : MeasurableSet t
· exact h₁ t hst ht
· exact not_measurable v ht
· exact h₂ t hst ht
· exact not_measurable w ht
#align measure_theory.vector_measure.mutually_singular.mk MeasureTheory.VectorMeasure.MutuallySingular.mk
theorem symm (h : v ⟂ᵥ w) : w ⟂ᵥ v :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨sᶜ, hmeas.compl, hs₂, fun t ht => hs₁ _ (compl_compl s ▸ ht : t ⊆ s)⟩
#align measure_theory.vector_measure.mutually_singular.symm MeasureTheory.VectorMeasure.MutuallySingular.symm
theorem zero_right : v ⟂ᵥ (0 : VectorMeasure α N) :=
⟨∅, MeasurableSet.empty, fun _ ht => (Set.subset_empty_iff.1 ht).symm ▸ v.empty,
fun _ _ => zero_apply _⟩
#align measure_theory.vector_measure.mutually_singular.zero_right MeasureTheory.VectorMeasure.MutuallySingular.zero_right
theorem zero_left : (0 : VectorMeasure α M) ⟂ᵥ w :=
zero_right.symm
#align measure_theory.vector_measure.mutually_singular.zero_left MeasureTheory.VectorMeasure.MutuallySingular.zero_left
theorem add_left [T2Space N] [ContinuousAdd M] (h₁ : v₁ ⟂ᵥ w) (h₂ : v₂ ⟂ᵥ w) : v₁ + v₂ ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h₁
obtain ⟨v, hmv, hv₁, hv₂⟩ := h₂
refine mk (u ∩ v) (hmu.inter hmv) (fun t ht _ => ?_) fun t ht hmt => ?_
· rw [add_apply, hu₁ _ (Set.subset_inter_iff.1 ht).1, hv₁ _ (Set.subset_inter_iff.1 ht).2,
zero_add]
· rw [Set.compl_inter] at ht
rw [(_ : t = uᶜ ∩ t ∪ vᶜ \ uᶜ ∩ t),
of_union _ (hmu.compl.inter hmt) ((hmv.compl.diff hmu.compl).inter hmt), hu₂, hv₂, add_zero]
· exact Set.Subset.trans Set.inter_subset_left diff_subset
· exact Set.inter_subset_left
· exact disjoint_sdiff_self_right.mono Set.inter_subset_left Set.inter_subset_left
· apply Set.Subset.antisymm <;> intro x hx
· by_cases hxu' : x ∈ uᶜ
· exact Or.inl ⟨hxu', hx⟩
rcases ht hx with (hxu | hxv)
exacts [False.elim (hxu' hxu), Or.inr ⟨⟨hxv, hxu'⟩, hx⟩]
· cases' hx with hx hx <;> exact hx.2
#align measure_theory.vector_measure.mutually_singular.add_left MeasureTheory.VectorMeasure.MutuallySingular.add_left
theorem add_right [T2Space M] [ContinuousAdd N] (h₁ : v ⟂ᵥ w₁) (h₂ : v ⟂ᵥ w₂) : v ⟂ᵥ w₁ + w₂ :=
(add_left h₁.symm h₂.symm).symm
#align measure_theory.vector_measure.mutually_singular.add_right MeasureTheory.VectorMeasure.MutuallySingular.add_right
theorem smul_right {R : Type*} [Semiring R] [DistribMulAction R N] [ContinuousConstSMul R N]
(r : R) (h : v ⟂ᵥ w) : v ⟂ᵥ r • w :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨s, hmeas, hs₁, fun t ht => by simp only [coe_smul, Pi.smul_apply, hs₂ t ht, smul_zero]⟩
#align measure_theory.vector_measure.mutually_singular.smul_right MeasureTheory.VectorMeasure.MutuallySingular.smul_right
theorem smul_left {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] (r : R)
(h : v ⟂ᵥ w) : r • v ⟂ᵥ w :=
(smul_right r h.symm).symm
#align measure_theory.vector_measure.mutually_singular.smul_left MeasureTheory.VectorMeasure.MutuallySingular.smul_left
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : -v ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h
refine ⟨u, hmu, fun s hs => ?_, hu₂⟩
rw [neg_apply v s, neg_eq_zero]
exact hu₁ s hs
#align measure_theory.vector_measure.mutually_singular.neg_left MeasureTheory.VectorMeasure.MutuallySingular.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : v ⟂ᵥ -w :=
h.symm.neg_left.symm
#align measure_theory.vector_measure.mutually_singular.neg_right MeasureTheory.VectorMeasure.MutuallySingular.neg_right
@[simp]
theorem neg_left_iff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} : -v ⟂ᵥ w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg v ▸ h.neg_left, neg_left⟩
#align measure_theory.vector_measure.mutually_singular.neg_left_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_left_iff
@[simp]
theorem neg_right_iff {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} : v ⟂ᵥ -w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg w ▸ h.neg_right, neg_right⟩
#align measure_theory.vector_measure.mutually_singular.neg_right_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_right_iff
end MutuallySingular
section Trim
/-- Restriction of a vector measure onto a sub-σ-algebra. -/
@[simps]
def trim {m n : MeasurableSpace α} (v : VectorMeasure α M) (hle : m ≤ n) :
@VectorMeasure α m M _ _ :=
@VectorMeasure.mk α m M _ _
(fun i => if MeasurableSet[m] i then v i else 0)
(by dsimp only; rw [if_pos (@MeasurableSet.empty _ m), v.empty])
(fun i hi => by dsimp only; rw [if_neg hi])
(fun f hf₁ hf₂ => by
dsimp only
have hf₁' : ∀ k, MeasurableSet[n] (f k) := fun k => hle _ (hf₁ k)
convert v.m_iUnion hf₁' hf₂ using 1
· ext n
rw [if_pos (hf₁ n)]
· rw [if_pos (@MeasurableSet.iUnion _ _ m _ _ hf₁)])
#align measure_theory.vector_measure.trim MeasureTheory.VectorMeasure.trim
variable {n : MeasurableSpace α} {v : VectorMeasure α M}
theorem trim_eq_self : v.trim le_rfl = v := by
ext i hi
exact if_pos hi
#align measure_theory.vector_measure.trim_eq_self MeasureTheory.VectorMeasure.trim_eq_self
@[simp]
theorem zero_trim (hle : m ≤ n) : (0 : VectorMeasure α M).trim hle = 0 := by
ext i hi
exact if_pos hi
#align measure_theory.vector_measure.zero_trim MeasureTheory.VectorMeasure.zero_trim
theorem trim_measurableSet_eq (hle : m ≤ n) {i : Set α} (hi : MeasurableSet[m] i) :
v.trim hle i = v i :=
if_pos hi
#align measure_theory.vector_measure.trim_measurable_set_eq MeasureTheory.VectorMeasure.trim_measurableSet_eq
theorem restrict_trim (hle : m ≤ n) {i : Set α} (hi : MeasurableSet[m] i) :
@VectorMeasure.restrict α m M _ _ (v.trim hle) i = (v.restrict i).trim hle := by
ext j hj
rw [@restrict_apply _ m, trim_measurableSet_eq hle hj, restrict_apply, trim_measurableSet_eq]
all_goals measurability
#align measure_theory.vector_measure.restrict_trim MeasureTheory.VectorMeasure.restrict_trim
end Trim
end
end VectorMeasure
namespace SignedMeasure
open VectorMeasure
open MeasureTheory
/-- The underlying function for `SignedMeasure.toMeasureOfZeroLE`. -/
def toMeasureOfZeroLE' (s : SignedMeasure α) (i : Set α) (hi : 0 ≤[i] s) (j : Set α)
(hj : MeasurableSet j) : ℝ≥0∞ :=
((↑) : ℝ≥0 → ℝ≥0∞) ⟨s.restrict i j, le_trans (by simp) (hi j hj)⟩
#align measure_theory.signed_measure.to_measure_of_zero_le' MeasureTheory.SignedMeasure.toMeasureOfZeroLE'
/-- Given a signed measure `s` and a positive measurable set `i`, `toMeasureOfZeroLE`
provides the measure, mapping measurable sets `j` to `s (i ∩ j)`. -/
def toMeasureOfZeroLE (s : SignedMeasure α) (i : Set α) (hi₁ : MeasurableSet i) (hi₂ : 0 ≤[i] s) :
Measure α := by
refine Measure.ofMeasurable (s.toMeasureOfZeroLE' i hi₂) ?_ ?_
· simp_rw [toMeasureOfZeroLE', s.restrict_apply hi₁ MeasurableSet.empty, Set.empty_inter i,
s.empty]
rfl
· intro f hf₁ hf₂
have h₁ : ∀ n, MeasurableSet (i ∩ f n) := fun n => hi₁.inter (hf₁ n)
have h₂ : Pairwise (Disjoint on fun n : ℕ => i ∩ f n) := by
intro n m hnm
exact ((hf₂ hnm).inf_left' i).inf_right' i
simp only [toMeasureOfZeroLE', s.restrict_apply hi₁ (MeasurableSet.iUnion hf₁), Set.inter_comm,
Set.inter_iUnion, s.of_disjoint_iUnion_nat h₁ h₂, ENNReal.some_eq_coe, id]
have h : ∀ n, 0 ≤ s (i ∩ f n) := fun n =>
s.nonneg_of_zero_le_restrict (s.zero_le_restrict_subset hi₁ Set.inter_subset_left hi₂)
rw [NNReal.coe_tsum_of_nonneg h, ENNReal.coe_tsum]
· refine tsum_congr fun n => ?_
simp_rw [s.restrict_apply hi₁ (hf₁ n), Set.inter_comm]
· exact (NNReal.summable_mk h).2 (s.m_iUnion h₁ h₂).summable
#align measure_theory.signed_measure.to_measure_of_zero_le MeasureTheory.SignedMeasure.toMeasureOfZeroLE
variable (s : SignedMeasure α) {i j : Set α}
theorem toMeasureOfZeroLE_apply (hi : 0 ≤[i] s) (hi₁ : MeasurableSet i) (hj₁ : MeasurableSet j) :
s.toMeasureOfZeroLE i hi₁ hi j = ((↑) : ℝ≥0 → ℝ≥0∞) ⟨s (i ∩ j), nonneg_of_zero_le_restrict
s (zero_le_restrict_subset s hi₁ Set.inter_subset_left hi)⟩ := by
simp_rw [toMeasureOfZeroLE, Measure.ofMeasurable_apply _ hj₁, toMeasureOfZeroLE',
s.restrict_apply hi₁ hj₁, Set.inter_comm]
#align measure_theory.signed_measure.to_measure_of_zero_le_apply MeasureTheory.SignedMeasure.toMeasureOfZeroLE_apply
/-- Given a signed measure `s` and a negative measurable set `i`, `toMeasureOfLEZero`
provides the measure, mapping measurable sets `j` to `-s (i ∩ j)`. -/
def toMeasureOfLEZero (s : SignedMeasure α) (i : Set α) (hi₁ : MeasurableSet i) (hi₂ : s ≤[i] 0) :
Measure α :=
toMeasureOfZeroLE (-s) i hi₁ <| @neg_zero (VectorMeasure α ℝ) _ ▸ neg_le_neg _ _ hi₁ hi₂
#align measure_theory.signed_measure.to_measure_of_le_zero MeasureTheory.SignedMeasure.toMeasureOfLEZero
theorem toMeasureOfLEZero_apply (hi : s ≤[i] 0) (hi₁ : MeasurableSet i) (hj₁ : MeasurableSet j) :
s.toMeasureOfLEZero i hi₁ hi j = ((↑) : ℝ≥0 → ℝ≥0∞) ⟨-s (i ∩ j), neg_apply s (i ∩ j) ▸
nonneg_of_zero_le_restrict _ (zero_le_restrict_subset _ hi₁ Set.inter_subset_left
(@neg_zero (VectorMeasure α ℝ) _ ▸ neg_le_neg _ _ hi₁ hi))⟩ := by
erw [toMeasureOfZeroLE_apply]
· simp
· assumption
#align measure_theory.signed_measure.to_measure_of_le_zero_apply MeasureTheory.SignedMeasure.toMeasureOfLEZero_apply
/-- `SignedMeasure.toMeasureOfZeroLE` is a finite measure. -/
instance toMeasureOfZeroLE_finite (hi : 0 ≤[i] s) (hi₁ : MeasurableSet i) :
IsFiniteMeasure (s.toMeasureOfZeroLE i hi₁ hi) where
measure_univ_lt_top := by
rw [toMeasureOfZeroLE_apply s hi hi₁ MeasurableSet.univ]
exact ENNReal.coe_lt_top
#align measure_theory.signed_measure.to_measure_of_zero_le_finite MeasureTheory.SignedMeasure.toMeasureOfZeroLE_finite
/-- `SignedMeasure.toMeasureOfLEZero` is a finite measure. -/
instance toMeasureOfLEZero_finite (hi : s ≤[i] 0) (hi₁ : MeasurableSet i) :
IsFiniteMeasure (s.toMeasureOfLEZero i hi₁ hi) where
measure_univ_lt_top := by
rw [toMeasureOfLEZero_apply s hi hi₁ MeasurableSet.univ]
exact ENNReal.coe_lt_top
#align measure_theory.signed_measure.to_measure_of_le_zero_finite MeasureTheory.SignedMeasure.toMeasureOfLEZero_finite
| Mathlib/MeasureTheory/Measure/VectorMeasure.lean | 1,363 | 1,366 | theorem toMeasureOfZeroLE_toSignedMeasure (hs : 0 ≤[Set.univ] s) :
(s.toMeasureOfZeroLE Set.univ MeasurableSet.univ hs).toSignedMeasure = s := by |
ext i hi
simp [hi, toMeasureOfZeroLE_apply _ _ _ hi]
|
/-
Copyright (c) 2018 Michael Jendrusch. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Jendrusch, Scott Morrison, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Monoidal.Category
import Mathlib.CategoryTheory.Adjunction.FullyFaithful
import Mathlib.CategoryTheory.Products.Basic
#align_import category_theory.monoidal.functor from "leanprover-community/mathlib"@"3d7987cda72abc473c7cdbbb075170e9ac620042"
/-!
# (Lax) monoidal functors
A lax monoidal functor `F` between monoidal categories `C` and `D`
is a functor between the underlying categories equipped with morphisms
* `ε : 𝟙_ D ⟶ F.obj (𝟙_ C)` (called the unit morphism)
* `μ X Y : (F.obj X) ⊗ (F.obj Y) ⟶ F.obj (X ⊗ Y)` (called the tensorator, or strength).
satisfying various axioms.
A monoidal functor is a lax monoidal functor for which `ε` and `μ` are isomorphisms.
We show that the composition of (lax) monoidal functors gives a (lax) monoidal functor.
See also `CategoryTheory.Monoidal.Functorial` for a typeclass decorating an object-level
function with the additional data of a monoidal functor.
This is useful when stating that a pre-existing functor is monoidal.
See `CategoryTheory.Monoidal.NaturalTransformation` for monoidal natural transformations.
We show in `CategoryTheory.Monoidal.Mon_` that lax monoidal functors take monoid objects
to monoid objects.
## References
See <https://stacks.math.columbia.edu/tag/0FFL>.
-/
open CategoryTheory
universe v₁ v₂ v₃ u₁ u₂ u₃
open CategoryTheory.Category
open CategoryTheory.Functor
namespace CategoryTheory
section
open MonoidalCategory
variable (C : Type u₁) [Category.{v₁} C] [MonoidalCategory.{v₁} C] (D : Type u₂) [Category.{v₂} D]
[MonoidalCategory.{v₂} D]
-- The direction of `left_unitality` and `right_unitality` as simp lemmas may look strange:
-- remember the rule of thumb that component indices of natural transformations
-- "weigh more" than structural maps.
-- (However by this argument `associativity` is currently stated backwards!)
/-- A lax monoidal functor is a functor `F : C ⥤ D` between monoidal categories,
equipped with morphisms `ε : 𝟙 _D ⟶ F.obj (𝟙_ C)` and `μ X Y : F.obj X ⊗ F.obj Y ⟶ F.obj (X ⊗ Y)`,
satisfying the appropriate coherences. -/
structure LaxMonoidalFunctor extends C ⥤ D where
/-- unit morphism -/
ε : 𝟙_ D ⟶ obj (𝟙_ C)
/-- tensorator -/
μ : ∀ X Y : C, obj X ⊗ obj Y ⟶ obj (X ⊗ Y)
μ_natural_left :
∀ {X Y : C} (f : X ⟶ Y) (X' : C),
map f ▷ obj X' ≫ μ Y X' = μ X X' ≫ map (f ▷ X') := by
aesop_cat
μ_natural_right :
∀ {X Y : C} (X' : C) (f : X ⟶ Y) ,
obj X' ◁ map f ≫ μ X' Y = μ X' X ≫ map (X' ◁ f) := by
aesop_cat
/-- associativity of the tensorator -/
associativity :
∀ X Y Z : C,
μ X Y ▷ obj Z ≫ μ (X ⊗ Y) Z ≫ map (α_ X Y Z).hom =
(α_ (obj X) (obj Y) (obj Z)).hom ≫ obj X ◁ μ Y Z ≫ μ X (Y ⊗ Z) := by
aesop_cat
-- unitality
left_unitality : ∀ X : C, (λ_ (obj X)).hom = ε ▷ obj X ≫ μ (𝟙_ C) X ≫ map (λ_ X).hom := by
aesop_cat
right_unitality : ∀ X : C, (ρ_ (obj X)).hom = obj X ◁ ε ≫ μ X (𝟙_ C) ≫ map (ρ_ X).hom := by
aesop_cat
#align category_theory.lax_monoidal_functor CategoryTheory.LaxMonoidalFunctor
-- Porting note (#11215): TODO: remove this configuration and use the default configuration.
-- We keep this to be consistent with Lean 3.
-- See also `initialize_simps_projections MonoidalFunctor` below.
-- This may require waiting on https://github.com/leanprover-community/mathlib4/pull/2936
initialize_simps_projections LaxMonoidalFunctor (+toFunctor, -obj, -map)
attribute [reassoc (attr := simp)] LaxMonoidalFunctor.μ_natural_left
attribute [reassoc (attr := simp)] LaxMonoidalFunctor.μ_natural_right
attribute [simp] LaxMonoidalFunctor.left_unitality
attribute [simp] LaxMonoidalFunctor.right_unitality
attribute [reassoc (attr := simp)] LaxMonoidalFunctor.associativity
-- When `rewrite_search` lands, add @[search] attributes to
-- LaxMonoidalFunctor.μ_natural LaxMonoidalFunctor.left_unitality
-- LaxMonoidalFunctor.right_unitality LaxMonoidalFunctor.associativity
section
variable {C D}
@[reassoc (attr := simp)]
theorem LaxMonoidalFunctor.μ_natural (F : LaxMonoidalFunctor C D) {X Y X' Y' : C}
(f : X ⟶ Y) (g : X' ⟶ Y') :
(F.map f ⊗ F.map g) ≫ F.μ Y Y' = F.μ X X' ≫ F.map (f ⊗ g) := by
simp [tensorHom_def]
/--
A constructor for lax monoidal functors whose axioms are described by `tensorHom` instead of
`whiskerLeft` and `whiskerRight`.
-/
@[simps]
def LaxMonoidalFunctor.ofTensorHom (F : C ⥤ D)
/- unit morphism -/
(ε : 𝟙_ D ⟶ F.obj (𝟙_ C))
/- tensorator -/
(μ : ∀ X Y : C, F.obj X ⊗ F.obj Y ⟶ F.obj (X ⊗ Y))
(μ_natural :
∀ {X Y X' Y' : C} (f : X ⟶ Y) (g : X' ⟶ Y'),
(F.map f ⊗ F.map g) ≫ μ Y Y' = μ X X' ≫ F.map (f ⊗ g) := by
aesop_cat)
/- associativity of the tensorator -/
(associativity :
∀ X Y Z : C,
(μ X Y ⊗ 𝟙 (F.obj Z)) ≫ μ (X ⊗ Y) Z ≫ F.map (α_ X Y Z).hom =
(α_ (F.obj X) (F.obj Y) (F.obj Z)).hom ≫ (𝟙 (F.obj X) ⊗ μ Y Z) ≫ μ X (Y ⊗ Z) := by
aesop_cat)
/- unitality -/
(left_unitality :
∀ X : C, (λ_ (F.obj X)).hom = (ε ⊗ 𝟙 (F.obj X)) ≫ μ (𝟙_ C) X ≫ F.map (λ_ X).hom := by
aesop_cat)
(right_unitality :
∀ X : C, (ρ_ (F.obj X)).hom = (𝟙 (F.obj X) ⊗ ε) ≫ μ X (𝟙_ C) ≫ F.map (ρ_ X).hom := by
aesop_cat) :
LaxMonoidalFunctor C D where
obj := F.obj
map := F.map
map_id := F.map_id
map_comp := F.map_comp
ε := ε
μ := μ
μ_natural_left := fun f X' => by
simp_rw [← tensorHom_id, ← F.map_id, μ_natural]
μ_natural_right := fun X' f => by
simp_rw [← id_tensorHom, ← F.map_id, μ_natural]
associativity := fun X Y Z => by
simp_rw [← tensorHom_id, ← id_tensorHom, associativity]
left_unitality := fun X => by
simp_rw [← tensorHom_id, left_unitality]
right_unitality := fun X => by
simp_rw [← id_tensorHom, right_unitality]
@[reassoc (attr := simp)]
theorem LaxMonoidalFunctor.left_unitality_inv (F : LaxMonoidalFunctor C D) (X : C) :
(λ_ (F.obj X)).inv ≫ F.ε ▷ F.obj X ≫ F.μ (𝟙_ C) X = F.map (λ_ X).inv := by
rw [Iso.inv_comp_eq, F.left_unitality, Category.assoc, Category.assoc, ← F.toFunctor.map_comp,
Iso.hom_inv_id, F.toFunctor.map_id, comp_id]
#align category_theory.lax_monoidal_functor.left_unitality_inv CategoryTheory.LaxMonoidalFunctor.left_unitality_inv
@[reassoc (attr := simp)]
theorem LaxMonoidalFunctor.right_unitality_inv (F : LaxMonoidalFunctor C D) (X : C) :
(ρ_ (F.obj X)).inv ≫ F.obj X ◁ F.ε ≫ F.μ X (𝟙_ C) = F.map (ρ_ X).inv := by
rw [Iso.inv_comp_eq, F.right_unitality, Category.assoc, Category.assoc, ← F.toFunctor.map_comp,
Iso.hom_inv_id, F.toFunctor.map_id, comp_id]
#align category_theory.lax_monoidal_functor.right_unitality_inv CategoryTheory.LaxMonoidalFunctor.right_unitality_inv
@[reassoc (attr := simp)]
theorem LaxMonoidalFunctor.associativity_inv (F : LaxMonoidalFunctor C D) (X Y Z : C) :
F.obj X ◁ F.μ Y Z ≫ F.μ X (Y ⊗ Z) ≫ F.map (α_ X Y Z).inv =
(α_ (F.obj X) (F.obj Y) (F.obj Z)).inv ≫ F.μ X Y ▷ F.obj Z ≫ F.μ (X ⊗ Y) Z := by
rw [Iso.eq_inv_comp, ← F.associativity_assoc, ← F.toFunctor.map_comp, Iso.hom_inv_id,
F.toFunctor.map_id, comp_id]
#align category_theory.lax_monoidal_functor.associativity_inv CategoryTheory.LaxMonoidalFunctor.associativity_inv
end
/-- A oplax monoidal functor is a functor `F : C ⥤ D` between monoidal categories,
equipped with morphisms `η : F.obj (𝟙_ C) ⟶ 𝟙 _D` and `δ X Y : F.obj (X ⊗ Y) ⟶ F.obj X ⊗ F.obj Y`,
satisfying the appropriate coherences. -/
structure OplaxMonoidalFunctor extends C ⥤ D where
/-- counit morphism -/
η : obj (𝟙_ C) ⟶ 𝟙_ D
/-- cotensorator -/
δ : ∀ X Y : C, obj (X ⊗ Y) ⟶ obj X ⊗ obj Y
δ_natural_left :
∀ {X Y : C} (f : X ⟶ Y) (X' : C),
δ X X' ≫ map f ▷ obj X' = map (f ▷ X') ≫ δ Y X' := by
aesop_cat
δ_natural_right :
∀ {X Y : C} (X' : C) (f : X ⟶ Y) ,
δ X' X ≫ obj X' ◁ map f = map (X' ◁ f) ≫ δ X' Y := by
aesop_cat
/-- associativity of the tensorator -/
associativity :
∀ X Y Z : C,
δ (X ⊗ Y) Z ≫ δ X Y ▷ obj Z ≫ (α_ (obj X) (obj Y) (obj Z)).hom =
map (α_ X Y Z).hom ≫ δ X (Y ⊗ Z) ≫ obj X ◁ δ Y Z := by
aesop_cat
-- unitality
left_unitality : ∀ X : C, (λ_ (obj X)).inv = map (λ_ X).inv ≫ δ (𝟙_ C) X ≫ η ▷ obj X := by
aesop_cat
right_unitality : ∀ X : C, (ρ_ (obj X)).inv = map (ρ_ X).inv ≫ δ X (𝟙_ C) ≫ obj X ◁ η := by
aesop_cat
initialize_simps_projections OplaxMonoidalFunctor (+toFunctor, -obj, -map)
attribute [reassoc (attr := simp)] OplaxMonoidalFunctor.δ_natural_left
attribute [reassoc (attr := simp)] OplaxMonoidalFunctor.δ_natural_right
attribute [simp] OplaxMonoidalFunctor.left_unitality
attribute [simp] OplaxMonoidalFunctor.right_unitality
attribute [reassoc (attr := simp)] OplaxMonoidalFunctor.associativity
section
variable {C D}
@[reassoc (attr := simp)]
theorem OplaxMonoidalFunctor.δ_natural (F : OplaxMonoidalFunctor C D) {X Y X' Y' : C}
(f : X ⟶ Y) (g : X' ⟶ Y') :
F.δ X X' ≫ (F.map f ⊗ F.map g) = F.map (f ⊗ g) ≫ F.δ Y Y' := by
simp [tensorHom_def]
@[reassoc (attr := simp)]
theorem OplaxMonoidalFunctor.left_unitality_hom (F : OplaxMonoidalFunctor C D) (X : C) :
F.δ (𝟙_ C) X ≫ F.η ▷ F.obj X ≫ (λ_ (F.obj X)).hom = F.map (λ_ X).hom := by
rw [← Category.assoc, ← Iso.eq_comp_inv, F.left_unitality, ← Category.assoc,
← F.toFunctor.map_comp, Iso.hom_inv_id, F.toFunctor.map_id, id_comp]
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Monoidal/Functor.lean | 243 | 246 | theorem OplaxMonoidalFunctor.right_unitality_hom (F : OplaxMonoidalFunctor C D) (X : C) :
F.δ X (𝟙_ C) ≫ F.obj X ◁ F.η ≫ (ρ_ (F.obj X)).hom = F.map (ρ_ X).hom := by |
rw [← Category.assoc, ← Iso.eq_comp_inv, F.right_unitality, ← Category.assoc,
← F.toFunctor.map_comp, Iso.hom_inv_id, F.toFunctor.map_id, id_comp]
|
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Sébastien Gouëzel
-/
import Mathlib.Analysis.Normed.Group.Hom
import Mathlib.Analysis.SpecialFunctions.Pow.Continuity
import Mathlib.Data.Set.Image
import Mathlib.MeasureTheory.Function.LpSeminorm.ChebyshevMarkov
import Mathlib.MeasureTheory.Function.LpSeminorm.CompareExp
import Mathlib.MeasureTheory.Function.LpSeminorm.TriangleInequality
import Mathlib.MeasureTheory.Measure.OpenPos
import Mathlib.Topology.ContinuousFunction.Compact
import Mathlib.Order.Filter.IndicatorFunction
#align_import measure_theory.function.lp_space from "leanprover-community/mathlib"@"c4015acc0a223449d44061e27ddac1835a3852b9"
/-!
# Lp space
This file provides the space `Lp E p μ` as the subtype of elements of `α →ₘ[μ] E` (see ae_eq_fun)
such that `snorm f p μ` is finite. For `1 ≤ p`, `snorm` defines a norm and `Lp` is a complete metric
space.
## Main definitions
* `Lp E p μ` : elements of `α →ₘ[μ] E` (see ae_eq_fun) such that `snorm f p μ` is finite. Defined
as an `AddSubgroup` of `α →ₘ[μ] E`.
Lipschitz functions vanishing at zero act by composition on `Lp`. We define this action, and prove
that it is continuous. In particular,
* `ContinuousLinearMap.compLp` defines the action on `Lp` of a continuous linear map.
* `Lp.posPart` is the positive part of an `Lp` function.
* `Lp.negPart` is the negative part of an `Lp` function.
When `α` is a topological space equipped with a finite Borel measure, there is a bounded linear map
from the normed space of bounded continuous functions (`α →ᵇ E`) to `Lp E p μ`. We construct this
as `BoundedContinuousFunction.toLp`.
## Notations
* `α →₁[μ] E` : the type `Lp E 1 μ`.
* `α →₂[μ] E` : the type `Lp E 2 μ`.
## Implementation
Since `Lp` is defined as an `AddSubgroup`, dot notation does not work. Use `Lp.Measurable f` to
say that the coercion of `f` to a genuine function is measurable, instead of the non-working
`f.Measurable`.
To prove that two `Lp` elements are equal, it suffices to show that their coercions to functions
coincide almost everywhere (this is registered as an `ext` rule). This can often be done using
`filter_upwards`. For instance, a proof from first principles that `f + (g + h) = (f + g) + h`
could read (in the `Lp` namespace)
```
example (f g h : Lp E p μ) : (f + g) + h = f + (g + h) := by
ext1
filter_upwards [coeFn_add (f + g) h, coeFn_add f g, coeFn_add f (g + h), coeFn_add g h]
with _ ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, add_assoc]
```
The lemma `coeFn_add` states that the coercion of `f + g` coincides almost everywhere with the sum
of the coercions of `f` and `g`. All such lemmas use `coeFn` in their name, to distinguish the
function coercion from the coercion to almost everywhere defined functions.
-/
noncomputable section
set_option linter.uppercaseLean3 false
open TopologicalSpace MeasureTheory Filter
open scoped NNReal ENNReal Topology MeasureTheory Uniformity
variable {α E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G]
namespace MeasureTheory
/-!
### Lp space
The space of equivalence classes of measurable functions for which `snorm f p μ < ∞`.
-/
@[simp]
theorem snorm_aeeqFun {α E : Type*} [MeasurableSpace α] {μ : Measure α} [NormedAddCommGroup E]
{p : ℝ≥0∞} {f : α → E} (hf : AEStronglyMeasurable f μ) :
snorm (AEEqFun.mk f hf) p μ = snorm f p μ :=
snorm_congr_ae (AEEqFun.coeFn_mk _ _)
#align measure_theory.snorm_ae_eq_fun MeasureTheory.snorm_aeeqFun
theorem Memℒp.snorm_mk_lt_top {α E : Type*} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] {p : ℝ≥0∞} {f : α → E} (hfp : Memℒp f p μ) :
snorm (AEEqFun.mk f hfp.1) p μ < ∞ := by simp [hfp.2]
#align measure_theory.mem_ℒp.snorm_mk_lt_top MeasureTheory.Memℒp.snorm_mk_lt_top
/-- Lp space -/
def Lp {α} (E : Type*) {m : MeasurableSpace α} [NormedAddCommGroup E] (p : ℝ≥0∞)
(μ : Measure α := by volume_tac) : AddSubgroup (α →ₘ[μ] E) where
carrier := { f | snorm f p μ < ∞ }
zero_mem' := by simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
add_mem' {f g} hf hg := by
simp [snorm_congr_ae (AEEqFun.coeFn_add f g),
snorm_add_lt_top ⟨f.aestronglyMeasurable, hf⟩ ⟨g.aestronglyMeasurable, hg⟩]
neg_mem' {f} hf := by rwa [Set.mem_setOf_eq, snorm_congr_ae (AEEqFun.coeFn_neg f), snorm_neg]
#align measure_theory.Lp MeasureTheory.Lp
-- Porting note: calling the first argument `α` breaks the `(α := ·)` notation
scoped notation:25 α' " →₁[" μ "] " E => MeasureTheory.Lp (α := α') E 1 μ
scoped notation:25 α' " →₂[" μ "] " E => MeasureTheory.Lp (α := α') E 2 μ
namespace Memℒp
/-- make an element of Lp from a function verifying `Memℒp` -/
def toLp (f : α → E) (h_mem_ℒp : Memℒp f p μ) : Lp E p μ :=
⟨AEEqFun.mk f h_mem_ℒp.1, h_mem_ℒp.snorm_mk_lt_top⟩
#align measure_theory.mem_ℒp.to_Lp MeasureTheory.Memℒp.toLp
theorem coeFn_toLp {f : α → E} (hf : Memℒp f p μ) : hf.toLp f =ᵐ[μ] f :=
AEEqFun.coeFn_mk _ _
#align measure_theory.mem_ℒp.coe_fn_to_Lp MeasureTheory.Memℒp.coeFn_toLp
theorem toLp_congr {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) (hfg : f =ᵐ[μ] g) :
hf.toLp f = hg.toLp g := by simp [toLp, hfg]
#align measure_theory.mem_ℒp.to_Lp_congr MeasureTheory.Memℒp.toLp_congr
@[simp]
theorem toLp_eq_toLp_iff {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
hf.toLp f = hg.toLp g ↔ f =ᵐ[μ] g := by simp [toLp]
#align measure_theory.mem_ℒp.to_Lp_eq_to_Lp_iff MeasureTheory.Memℒp.toLp_eq_toLp_iff
@[simp]
theorem toLp_zero (h : Memℒp (0 : α → E) p μ) : h.toLp 0 = 0 :=
rfl
#align measure_theory.mem_ℒp.to_Lp_zero MeasureTheory.Memℒp.toLp_zero
theorem toLp_add {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.add hg).toLp (f + g) = hf.toLp f + hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_add MeasureTheory.Memℒp.toLp_add
theorem toLp_neg {f : α → E} (hf : Memℒp f p μ) : hf.neg.toLp (-f) = -hf.toLp f :=
rfl
#align measure_theory.mem_ℒp.to_Lp_neg MeasureTheory.Memℒp.toLp_neg
theorem toLp_sub {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.sub hg).toLp (f - g) = hf.toLp f - hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_sub MeasureTheory.Memℒp.toLp_sub
end Memℒp
namespace Lp
instance instCoeFun : CoeFun (Lp E p μ) (fun _ => α → E) :=
⟨fun f => ((f : α →ₘ[μ] E) : α → E)⟩
#align measure_theory.Lp.has_coe_to_fun MeasureTheory.Lp.instCoeFun
@[ext high]
theorem ext {f g : Lp E p μ} (h : f =ᵐ[μ] g) : f = g := by
cases f
cases g
simp only [Subtype.mk_eq_mk]
exact AEEqFun.ext h
#align measure_theory.Lp.ext MeasureTheory.Lp.ext
theorem ext_iff {f g : Lp E p μ} : f = g ↔ f =ᵐ[μ] g :=
⟨fun h => by rw [h], fun h => ext h⟩
#align measure_theory.Lp.ext_iff MeasureTheory.Lp.ext_iff
theorem mem_Lp_iff_snorm_lt_top {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ snorm f p μ < ∞ := Iff.rfl
#align measure_theory.Lp.mem_Lp_iff_snorm_lt_top MeasureTheory.Lp.mem_Lp_iff_snorm_lt_top
theorem mem_Lp_iff_memℒp {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ Memℒp f p μ := by
simp [mem_Lp_iff_snorm_lt_top, Memℒp, f.stronglyMeasurable.aestronglyMeasurable]
#align measure_theory.Lp.mem_Lp_iff_mem_ℒp MeasureTheory.Lp.mem_Lp_iff_memℒp
protected theorem antitone [IsFiniteMeasure μ] {p q : ℝ≥0∞} (hpq : p ≤ q) : Lp E q μ ≤ Lp E p μ :=
fun f hf => (Memℒp.memℒp_of_exponent_le ⟨f.aestronglyMeasurable, hf⟩ hpq).2
#align measure_theory.Lp.antitone MeasureTheory.Lp.antitone
@[simp]
theorem coeFn_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α → E) = f :=
rfl
#align measure_theory.Lp.coe_fn_mk MeasureTheory.Lp.coeFn_mk
-- @[simp] -- Porting note (#10685): dsimp can prove this
theorem coe_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α →ₘ[μ] E) = f :=
rfl
#align measure_theory.Lp.coe_mk MeasureTheory.Lp.coe_mk
@[simp]
theorem toLp_coeFn (f : Lp E p μ) (hf : Memℒp f p μ) : hf.toLp f = f := by
cases f
simp [Memℒp.toLp]
#align measure_theory.Lp.to_Lp_coe_fn MeasureTheory.Lp.toLp_coeFn
theorem snorm_lt_top (f : Lp E p μ) : snorm f p μ < ∞ :=
f.prop
#align measure_theory.Lp.snorm_lt_top MeasureTheory.Lp.snorm_lt_top
theorem snorm_ne_top (f : Lp E p μ) : snorm f p μ ≠ ∞ :=
(snorm_lt_top f).ne
#align measure_theory.Lp.snorm_ne_top MeasureTheory.Lp.snorm_ne_top
@[measurability]
protected theorem stronglyMeasurable (f : Lp E p μ) : StronglyMeasurable f :=
f.val.stronglyMeasurable
#align measure_theory.Lp.strongly_measurable MeasureTheory.Lp.stronglyMeasurable
@[measurability]
protected theorem aestronglyMeasurable (f : Lp E p μ) : AEStronglyMeasurable f μ :=
f.val.aestronglyMeasurable
#align measure_theory.Lp.ae_strongly_measurable MeasureTheory.Lp.aestronglyMeasurable
protected theorem memℒp (f : Lp E p μ) : Memℒp f p μ :=
⟨Lp.aestronglyMeasurable f, f.prop⟩
#align measure_theory.Lp.mem_ℒp MeasureTheory.Lp.memℒp
variable (E p μ)
theorem coeFn_zero : ⇑(0 : Lp E p μ) =ᵐ[μ] 0 :=
AEEqFun.coeFn_zero
#align measure_theory.Lp.coe_fn_zero MeasureTheory.Lp.coeFn_zero
variable {E p μ}
theorem coeFn_neg (f : Lp E p μ) : ⇑(-f) =ᵐ[μ] -f :=
AEEqFun.coeFn_neg _
#align measure_theory.Lp.coe_fn_neg MeasureTheory.Lp.coeFn_neg
theorem coeFn_add (f g : Lp E p μ) : ⇑(f + g) =ᵐ[μ] f + g :=
AEEqFun.coeFn_add _ _
#align measure_theory.Lp.coe_fn_add MeasureTheory.Lp.coeFn_add
theorem coeFn_sub (f g : Lp E p μ) : ⇑(f - g) =ᵐ[μ] f - g :=
AEEqFun.coeFn_sub _ _
#align measure_theory.Lp.coe_fn_sub MeasureTheory.Lp.coeFn_sub
theorem const_mem_Lp (α) {_ : MeasurableSpace α} (μ : Measure α) (c : E) [IsFiniteMeasure μ] :
@AEEqFun.const α _ _ μ _ c ∈ Lp E p μ :=
(memℒp_const c).snorm_mk_lt_top
#align measure_theory.Lp.mem_Lp_const MeasureTheory.Lp.const_mem_Lp
instance instNorm : Norm (Lp E p μ) where norm f := ENNReal.toReal (snorm f p μ)
#align measure_theory.Lp.has_norm MeasureTheory.Lp.instNorm
-- note: we need this to be defeq to the instance from `SeminormedAddGroup.toNNNorm`, so
-- can't use `ENNReal.toNNReal (snorm f p μ)`
instance instNNNorm : NNNorm (Lp E p μ) where nnnorm f := ⟨‖f‖, ENNReal.toReal_nonneg⟩
#align measure_theory.Lp.has_nnnorm MeasureTheory.Lp.instNNNorm
instance instDist : Dist (Lp E p μ) where dist f g := ‖f - g‖
#align measure_theory.Lp.has_dist MeasureTheory.Lp.instDist
instance instEDist : EDist (Lp E p μ) where edist f g := snorm (⇑f - ⇑g) p μ
#align measure_theory.Lp.has_edist MeasureTheory.Lp.instEDist
theorem norm_def (f : Lp E p μ) : ‖f‖ = ENNReal.toReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.norm_def MeasureTheory.Lp.norm_def
theorem nnnorm_def (f : Lp E p μ) : ‖f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.nnnorm_def MeasureTheory.Lp.nnnorm_def
@[simp, norm_cast]
protected theorem coe_nnnorm (f : Lp E p μ) : (‖f‖₊ : ℝ) = ‖f‖ :=
rfl
#align measure_theory.Lp.coe_nnnorm MeasureTheory.Lp.coe_nnnorm
@[simp, norm_cast]
theorem nnnorm_coe_ennreal (f : Lp E p μ) : (‖f‖₊ : ℝ≥0∞) = snorm f p μ :=
ENNReal.coe_toNNReal <| Lp.snorm_ne_top f
@[simp]
theorem norm_toLp (f : α → E) (hf : Memℒp f p μ) : ‖hf.toLp f‖ = ENNReal.toReal (snorm f p μ) := by
erw [norm_def, snorm_congr_ae (Memℒp.coeFn_toLp hf)]
#align measure_theory.Lp.norm_to_Lp MeasureTheory.Lp.norm_toLp
@[simp]
theorem nnnorm_toLp (f : α → E) (hf : Memℒp f p μ) :
‖hf.toLp f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
NNReal.eq <| norm_toLp f hf
#align measure_theory.Lp.nnnorm_to_Lp MeasureTheory.Lp.nnnorm_toLp
theorem coe_nnnorm_toLp {f : α → E} (hf : Memℒp f p μ) : (‖hf.toLp f‖₊ : ℝ≥0∞) = snorm f p μ := by
rw [nnnorm_toLp f hf, ENNReal.coe_toNNReal hf.2.ne]
theorem dist_def (f g : Lp E p μ) : dist f g = (snorm (⇑f - ⇑g) p μ).toReal := by
simp_rw [dist, norm_def]
refine congr_arg _ ?_
apply snorm_congr_ae (coeFn_sub _ _)
#align measure_theory.Lp.dist_def MeasureTheory.Lp.dist_def
theorem edist_def (f g : Lp E p μ) : edist f g = snorm (⇑f - ⇑g) p μ :=
rfl
#align measure_theory.Lp.edist_def MeasureTheory.Lp.edist_def
protected theorem edist_dist (f g : Lp E p μ) : edist f g = .ofReal (dist f g) := by
rw [edist_def, dist_def, ← snorm_congr_ae (coeFn_sub _ _),
ENNReal.ofReal_toReal (snorm_ne_top (f - g))]
protected theorem dist_edist (f g : Lp E p μ) : dist f g = (edist f g).toReal :=
MeasureTheory.Lp.dist_def ..
theorem dist_eq_norm (f g : Lp E p μ) : dist f g = ‖f - g‖ := rfl
@[simp]
theorem edist_toLp_toLp (f g : α → E) (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
edist (hf.toLp f) (hg.toLp g) = snorm (f - g) p μ := by
rw [edist_def]
exact snorm_congr_ae (hf.coeFn_toLp.sub hg.coeFn_toLp)
#align measure_theory.Lp.edist_to_Lp_to_Lp MeasureTheory.Lp.edist_toLp_toLp
@[simp]
theorem edist_toLp_zero (f : α → E) (hf : Memℒp f p μ) : edist (hf.toLp f) 0 = snorm f p μ := by
convert edist_toLp_toLp f 0 hf zero_memℒp
simp
#align measure_theory.Lp.edist_to_Lp_zero MeasureTheory.Lp.edist_toLp_zero
@[simp]
theorem nnnorm_zero : ‖(0 : Lp E p μ)‖₊ = 0 := by
rw [nnnorm_def]
change (snorm (⇑(0 : α →ₘ[μ] E)) p μ).toNNReal = 0
simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
#align measure_theory.Lp.nnnorm_zero MeasureTheory.Lp.nnnorm_zero
@[simp]
theorem norm_zero : ‖(0 : Lp E p μ)‖ = 0 :=
congr_arg ((↑) : ℝ≥0 → ℝ) nnnorm_zero
#align measure_theory.Lp.norm_zero MeasureTheory.Lp.norm_zero
@[simp]
theorem norm_measure_zero (f : Lp E p (0 : MeasureTheory.Measure α)) : ‖f‖ = 0 := by
simp [norm_def]
@[simp] theorem norm_exponent_zero (f : Lp E 0 μ) : ‖f‖ = 0 := by simp [norm_def]
theorem nnnorm_eq_zero_iff {f : Lp E p μ} (hp : 0 < p) : ‖f‖₊ = 0 ↔ f = 0 := by
refine ⟨fun hf => ?_, fun hf => by simp [hf]⟩
rw [nnnorm_def, ENNReal.toNNReal_eq_zero_iff] at hf
cases hf with
| inl hf =>
rw [snorm_eq_zero_iff (Lp.aestronglyMeasurable f) hp.ne.symm] at hf
exact Subtype.eq (AEEqFun.ext (hf.trans AEEqFun.coeFn_zero.symm))
| inr hf =>
exact absurd hf (snorm_ne_top f)
#align measure_theory.Lp.nnnorm_eq_zero_iff MeasureTheory.Lp.nnnorm_eq_zero_iff
theorem norm_eq_zero_iff {f : Lp E p μ} (hp : 0 < p) : ‖f‖ = 0 ↔ f = 0 :=
NNReal.coe_eq_zero.trans (nnnorm_eq_zero_iff hp)
#align measure_theory.Lp.norm_eq_zero_iff MeasureTheory.Lp.norm_eq_zero_iff
theorem eq_zero_iff_ae_eq_zero {f : Lp E p μ} : f = 0 ↔ f =ᵐ[μ] 0 := by
rw [← (Lp.memℒp f).toLp_eq_toLp_iff zero_memℒp, Memℒp.toLp_zero, toLp_coeFn]
#align measure_theory.Lp.eq_zero_iff_ae_eq_zero MeasureTheory.Lp.eq_zero_iff_ae_eq_zero
@[simp]
theorem nnnorm_neg (f : Lp E p μ) : ‖-f‖₊ = ‖f‖₊ := by
rw [nnnorm_def, nnnorm_def, snorm_congr_ae (coeFn_neg _), snorm_neg]
#align measure_theory.Lp.nnnorm_neg MeasureTheory.Lp.nnnorm_neg
@[simp]
theorem norm_neg (f : Lp E p μ) : ‖-f‖ = ‖f‖ :=
congr_arg ((↑) : ℝ≥0 → ℝ) (nnnorm_neg f)
#align measure_theory.Lp.norm_neg MeasureTheory.Lp.norm_neg
theorem nnnorm_le_mul_nnnorm_of_ae_le_mul {c : ℝ≥0} {f : Lp E p μ} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ c * ‖g x‖₊) : ‖f‖₊ ≤ c * ‖g‖₊ := by
simp only [nnnorm_def]
have := snorm_le_nnreal_smul_snorm_of_ae_le_mul h p
rwa [← ENNReal.toNNReal_le_toNNReal, ENNReal.smul_def, smul_eq_mul, ENNReal.toNNReal_mul,
ENNReal.toNNReal_coe] at this
· exact (Lp.memℒp _).snorm_ne_top
· exact ENNReal.mul_ne_top ENNReal.coe_ne_top (Lp.memℒp _).snorm_ne_top
#align measure_theory.Lp.nnnorm_le_mul_nnnorm_of_ae_le_mul MeasureTheory.Lp.nnnorm_le_mul_nnnorm_of_ae_le_mul
theorem norm_le_mul_norm_of_ae_le_mul {c : ℝ} {f : Lp E p μ} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖ ≤ c * ‖g x‖) : ‖f‖ ≤ c * ‖g‖ := by
rcases le_or_lt 0 c with hc | hc
· lift c to ℝ≥0 using hc
exact NNReal.coe_le_coe.mpr (nnnorm_le_mul_nnnorm_of_ae_le_mul h)
· simp only [norm_def]
have := snorm_eq_zero_and_zero_of_ae_le_mul_neg h hc p
simp [this]
#align measure_theory.Lp.norm_le_mul_norm_of_ae_le_mul MeasureTheory.Lp.norm_le_mul_norm_of_ae_le_mul
theorem norm_le_norm_of_ae_le {f : Lp E p μ} {g : Lp F p μ} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
‖f‖ ≤ ‖g‖ := by
rw [norm_def, norm_def, ENNReal.toReal_le_toReal (snorm_ne_top _) (snorm_ne_top _)]
exact snorm_mono_ae h
#align measure_theory.Lp.norm_le_norm_of_ae_le MeasureTheory.Lp.norm_le_norm_of_ae_le
theorem mem_Lp_of_nnnorm_ae_le_mul {c : ℝ≥0} {f : α →ₘ[μ] E} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ c * ‖g x‖₊) : f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_nnnorm_le_mul (Lp.memℒp g) f.aestronglyMeasurable h
#align measure_theory.Lp.mem_Lp_of_nnnorm_ae_le_mul MeasureTheory.Lp.mem_Lp_of_nnnorm_ae_le_mul
theorem mem_Lp_of_ae_le_mul {c : ℝ} {f : α →ₘ[μ] E} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖ ≤ c * ‖g x‖) : f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_le_mul (Lp.memℒp g) f.aestronglyMeasurable h
#align measure_theory.Lp.mem_Lp_of_ae_le_mul MeasureTheory.Lp.mem_Lp_of_ae_le_mul
theorem mem_Lp_of_nnnorm_ae_le {f : α →ₘ[μ] E} {g : Lp F p μ} (h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_le (Lp.memℒp g) f.aestronglyMeasurable h
#align measure_theory.Lp.mem_Lp_of_nnnorm_ae_le MeasureTheory.Lp.mem_Lp_of_nnnorm_ae_le
theorem mem_Lp_of_ae_le {f : α →ₘ[μ] E} {g : Lp F p μ} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
f ∈ Lp E p μ :=
mem_Lp_of_nnnorm_ae_le h
#align measure_theory.Lp.mem_Lp_of_ae_le MeasureTheory.Lp.mem_Lp_of_ae_le
theorem mem_Lp_of_ae_nnnorm_bound [IsFiniteMeasure μ] {f : α →ₘ[μ] E} (C : ℝ≥0)
(hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) : f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_bound f.aestronglyMeasurable _ hfC
#align measure_theory.Lp.mem_Lp_of_ae_nnnorm_bound MeasureTheory.Lp.mem_Lp_of_ae_nnnorm_bound
theorem mem_Lp_of_ae_bound [IsFiniteMeasure μ] {f : α →ₘ[μ] E} (C : ℝ) (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_bound f.aestronglyMeasurable _ hfC
#align measure_theory.Lp.mem_Lp_of_ae_bound MeasureTheory.Lp.mem_Lp_of_ae_bound
theorem nnnorm_le_of_ae_bound [IsFiniteMeasure μ] {f : Lp E p μ} {C : ℝ≥0}
(hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) : ‖f‖₊ ≤ measureUnivNNReal μ ^ p.toReal⁻¹ * C := by
by_cases hμ : μ = 0
· by_cases hp : p.toReal⁻¹ = 0
· simp [hp, hμ, nnnorm_def]
· simp [hμ, nnnorm_def, Real.zero_rpow hp]
rw [← ENNReal.coe_le_coe, nnnorm_def, ENNReal.coe_toNNReal (snorm_ne_top _)]
refine (snorm_le_of_ae_nnnorm_bound hfC).trans_eq ?_
rw [← coe_measureUnivNNReal μ, ENNReal.coe_rpow_of_ne_zero (measureUnivNNReal_pos hμ).ne',
ENNReal.coe_mul, mul_comm, ENNReal.smul_def, smul_eq_mul]
#align measure_theory.Lp.nnnorm_le_of_ae_bound MeasureTheory.Lp.nnnorm_le_of_ae_bound
theorem norm_le_of_ae_bound [IsFiniteMeasure μ] {f : Lp E p μ} {C : ℝ} (hC : 0 ≤ C)
(hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) : ‖f‖ ≤ measureUnivNNReal μ ^ p.toReal⁻¹ * C := by
lift C to ℝ≥0 using hC
have := nnnorm_le_of_ae_bound hfC
rwa [← NNReal.coe_le_coe, NNReal.coe_mul, NNReal.coe_rpow] at this
#align measure_theory.Lp.norm_le_of_ae_bound MeasureTheory.Lp.norm_le_of_ae_bound
instance instNormedAddCommGroup [hp : Fact (1 ≤ p)] : NormedAddCommGroup (Lp E p μ) :=
{ AddGroupNorm.toNormedAddCommGroup
{ toFun := (norm : Lp E p μ → ℝ)
map_zero' := norm_zero
neg' := by simp
add_le' := fun f g => by
suffices (‖f + g‖₊ : ℝ≥0∞) ≤ ‖f‖₊ + ‖g‖₊ from mod_cast this
simp only [Lp.nnnorm_coe_ennreal]
exact (snorm_congr_ae (AEEqFun.coeFn_add _ _)).trans_le
(snorm_add_le (Lp.aestronglyMeasurable _) (Lp.aestronglyMeasurable _) hp.out)
eq_zero_of_map_eq_zero' := fun f =>
(norm_eq_zero_iff <| zero_lt_one.trans_le hp.1).1 } with
edist := edist
edist_dist := Lp.edist_dist }
#align measure_theory.Lp.normed_add_comm_group MeasureTheory.Lp.instNormedAddCommGroup
-- check no diamond is created
example [Fact (1 ≤ p)] : PseudoEMetricSpace.toEDist = (Lp.instEDist : EDist (Lp E p μ)) := by
with_reducible_and_instances rfl
example [Fact (1 ≤ p)] : SeminormedAddGroup.toNNNorm = (Lp.instNNNorm : NNNorm (Lp E p μ)) := by
with_reducible_and_instances rfl
section BoundedSMul
variable {𝕜 𝕜' : Type*}
variable [NormedRing 𝕜] [NormedRing 𝕜'] [Module 𝕜 E] [Module 𝕜' E]
variable [BoundedSMul 𝕜 E] [BoundedSMul 𝕜' E]
theorem const_smul_mem_Lp (c : 𝕜) (f : Lp E p μ) : c • (f : α →ₘ[μ] E) ∈ Lp E p μ := by
rw [mem_Lp_iff_snorm_lt_top, snorm_congr_ae (AEEqFun.coeFn_smul _ _)]
refine (snorm_const_smul_le _ _).trans_lt ?_
rw [ENNReal.smul_def, smul_eq_mul, ENNReal.mul_lt_top_iff]
exact Or.inl ⟨ENNReal.coe_lt_top, f.prop⟩
#align measure_theory.Lp.mem_Lp_const_smul MeasureTheory.Lp.const_smul_mem_Lp
variable (E p μ 𝕜)
/-- The `𝕜`-submodule of elements of `α →ₘ[μ] E` whose `Lp` norm is finite. This is `Lp E p μ`,
with extra structure. -/
def LpSubmodule : Submodule 𝕜 (α →ₘ[μ] E) :=
{ Lp E p μ with smul_mem' := fun c f hf => by simpa using const_smul_mem_Lp c ⟨f, hf⟩ }
#align measure_theory.Lp.Lp_submodule MeasureTheory.Lp.LpSubmodule
variable {E p μ 𝕜}
theorem coe_LpSubmodule : (LpSubmodule E p μ 𝕜).toAddSubgroup = Lp E p μ :=
rfl
#align measure_theory.Lp.coe_Lp_submodule MeasureTheory.Lp.coe_LpSubmodule
instance instModule : Module 𝕜 (Lp E p μ) :=
{ (LpSubmodule E p μ 𝕜).module with }
#align measure_theory.Lp.module MeasureTheory.Lp.instModule
theorem coeFn_smul (c : 𝕜) (f : Lp E p μ) : ⇑(c • f) =ᵐ[μ] c • ⇑f :=
AEEqFun.coeFn_smul _ _
#align measure_theory.Lp.coe_fn_smul MeasureTheory.Lp.coeFn_smul
instance instIsCentralScalar [Module 𝕜ᵐᵒᵖ E] [BoundedSMul 𝕜ᵐᵒᵖ E] [IsCentralScalar 𝕜 E] :
IsCentralScalar 𝕜 (Lp E p μ) where
op_smul_eq_smul k f := Subtype.ext <| op_smul_eq_smul k (f : α →ₘ[μ] E)
#align measure_theory.Lp.is_central_scalar MeasureTheory.Lp.instIsCentralScalar
instance instSMulCommClass [SMulCommClass 𝕜 𝕜' E] : SMulCommClass 𝕜 𝕜' (Lp E p μ) where
smul_comm k k' f := Subtype.ext <| smul_comm k k' (f : α →ₘ[μ] E)
#align measure_theory.Lp.smul_comm_class MeasureTheory.Lp.instSMulCommClass
instance instIsScalarTower [SMul 𝕜 𝕜'] [IsScalarTower 𝕜 𝕜' E] : IsScalarTower 𝕜 𝕜' (Lp E p μ) where
smul_assoc k k' f := Subtype.ext <| smul_assoc k k' (f : α →ₘ[μ] E)
instance instBoundedSMul [Fact (1 ≤ p)] : BoundedSMul 𝕜 (Lp E p μ) :=
-- TODO: add `BoundedSMul.of_nnnorm_smul_le`
BoundedSMul.of_norm_smul_le fun r f => by
suffices (‖r • f‖₊ : ℝ≥0∞) ≤ ‖r‖₊ * ‖f‖₊ from mod_cast this
rw [nnnorm_def, nnnorm_def, ENNReal.coe_toNNReal (Lp.snorm_ne_top _),
snorm_congr_ae (coeFn_smul _ _), ENNReal.coe_toNNReal (Lp.snorm_ne_top _)]
exact snorm_const_smul_le r f
#align measure_theory.Lp.has_bounded_smul MeasureTheory.Lp.instBoundedSMul
end BoundedSMul
section NormedSpace
variable {𝕜 : Type*} [NormedField 𝕜] [NormedSpace 𝕜 E]
instance instNormedSpace [Fact (1 ≤ p)] : NormedSpace 𝕜 (Lp E p μ) where
norm_smul_le _ _ := norm_smul_le _ _
#align measure_theory.Lp.normed_space MeasureTheory.Lp.instNormedSpace
end NormedSpace
end Lp
namespace Memℒp
variable {𝕜 : Type*} [NormedRing 𝕜] [Module 𝕜 E] [BoundedSMul 𝕜 E]
theorem toLp_const_smul {f : α → E} (c : 𝕜) (hf : Memℒp f p μ) :
(hf.const_smul c).toLp (c • f) = c • hf.toLp f :=
rfl
#align measure_theory.mem_ℒp.to_Lp_const_smul MeasureTheory.Memℒp.toLp_const_smul
end Memℒp
/-! ### Indicator of a set as an element of Lᵖ
For a set `s` with `(hs : MeasurableSet s)` and `(hμs : μ s < ∞)`, we build
`indicatorConstLp p hs hμs c`, the element of `Lp` corresponding to `s.indicator (fun _ => c)`.
-/
section Indicator
variable {c : E} {f : α → E} {hf : AEStronglyMeasurable f μ} {s : Set α}
theorem snormEssSup_indicator_le (s : Set α) (f : α → G) :
snormEssSup (s.indicator f) μ ≤ snormEssSup f μ := by
refine essSup_mono_ae (eventually_of_forall fun x => ?_)
rw [ENNReal.coe_le_coe, nnnorm_indicator_eq_indicator_nnnorm]
exact Set.indicator_le_self s _ x
#align measure_theory.snorm_ess_sup_indicator_le MeasureTheory.snormEssSup_indicator_le
theorem snormEssSup_indicator_const_le (s : Set α) (c : G) :
snormEssSup (s.indicator fun _ : α => c) μ ≤ ‖c‖₊ := by
by_cases hμ0 : μ = 0
· rw [hμ0, snormEssSup_measure_zero]
exact zero_le _
· exact (snormEssSup_indicator_le s fun _ => c).trans (snormEssSup_const c hμ0).le
#align measure_theory.snorm_ess_sup_indicator_const_le MeasureTheory.snormEssSup_indicator_const_le
theorem snormEssSup_indicator_const_eq (s : Set α) (c : G) (hμs : μ s ≠ 0) :
snormEssSup (s.indicator fun _ : α => c) μ = ‖c‖₊ := by
refine le_antisymm (snormEssSup_indicator_const_le s c) ?_
by_contra! h
have h' := ae_iff.mp (ae_lt_of_essSup_lt h)
push_neg at h'
refine hμs (measure_mono_null (fun x hx_mem => ?_) h')
rw [Set.mem_setOf_eq, Set.indicator_of_mem hx_mem]
#align measure_theory.snorm_ess_sup_indicator_const_eq MeasureTheory.snormEssSup_indicator_const_eq
theorem snorm_indicator_le (f : α → E) : snorm (s.indicator f) p μ ≤ snorm f p μ := by
refine snorm_mono_ae (eventually_of_forall fun x => ?_)
suffices ‖s.indicator f x‖₊ ≤ ‖f x‖₊ by exact NNReal.coe_mono this
rw [nnnorm_indicator_eq_indicator_nnnorm]
exact s.indicator_le_self _ x
#align measure_theory.snorm_indicator_le MeasureTheory.snorm_indicator_le
theorem snorm_indicator_const₀ {c : G} (hs : NullMeasurableSet s μ) (hp : p ≠ 0) (hp_top : p ≠ ∞) :
snorm (s.indicator fun _ => c) p μ = ‖c‖₊ * μ s ^ (1 / p.toReal) :=
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp hp_top
calc
snorm (s.indicator fun _ => c) p μ
= (∫⁻ x, ((‖(s.indicator fun _ ↦ c) x‖₊ : ℝ≥0∞) ^ p.toReal) ∂μ) ^ (1 / p.toReal) :=
snorm_eq_lintegral_rpow_nnnorm hp hp_top
_ = (∫⁻ x, (s.indicator fun _ ↦ (‖c‖₊ : ℝ≥0∞) ^ p.toReal) x ∂μ) ^ (1 / p.toReal) := by
congr 2
refine (Set.comp_indicator_const c (fun x : G ↦ (‖x‖₊ : ℝ≥0∞) ^ p.toReal) ?_)
simp [hp_pos]
_ = ‖c‖₊ * μ s ^ (1 / p.toReal) := by
rw [lintegral_indicator_const₀ hs, ENNReal.mul_rpow_of_nonneg, ← ENNReal.rpow_mul,
mul_one_div_cancel hp_pos.ne', ENNReal.rpow_one]
positivity
theorem snorm_indicator_const {c : G} (hs : MeasurableSet s) (hp : p ≠ 0) (hp_top : p ≠ ∞) :
snorm (s.indicator fun _ => c) p μ = ‖c‖₊ * μ s ^ (1 / p.toReal) :=
snorm_indicator_const₀ hs.nullMeasurableSet hp hp_top
#align measure_theory.snorm_indicator_const MeasureTheory.snorm_indicator_const
theorem snorm_indicator_const' {c : G} (hs : MeasurableSet s) (hμs : μ s ≠ 0) (hp : p ≠ 0) :
snorm (s.indicator fun _ => c) p μ = ‖c‖₊ * μ s ^ (1 / p.toReal) := by
by_cases hp_top : p = ∞
· simp [hp_top, snormEssSup_indicator_const_eq s c hμs]
· exact snorm_indicator_const hs hp hp_top
#align measure_theory.snorm_indicator_const' MeasureTheory.snorm_indicator_const'
theorem snorm_indicator_const_le (c : G) (p : ℝ≥0∞) :
snorm (s.indicator fun _ => c) p μ ≤ ‖c‖₊ * μ s ^ (1 / p.toReal) := by
rcases eq_or_ne p 0 with (rfl | hp)
· simp only [snorm_exponent_zero, zero_le']
rcases eq_or_ne p ∞ with (rfl | h'p)
· simp only [snorm_exponent_top, ENNReal.top_toReal, _root_.div_zero, ENNReal.rpow_zero, mul_one]
exact snormEssSup_indicator_const_le _ _
let t := toMeasurable μ s
calc
snorm (s.indicator fun _ => c) p μ ≤ snorm (t.indicator fun _ => c) p μ :=
snorm_mono (norm_indicator_le_of_subset (subset_toMeasurable _ _) _)
_ = ‖c‖₊ * μ t ^ (1 / p.toReal) :=
(snorm_indicator_const (measurableSet_toMeasurable _ _) hp h'p)
_ = ‖c‖₊ * μ s ^ (1 / p.toReal) := by rw [measure_toMeasurable]
#align measure_theory.snorm_indicator_const_le MeasureTheory.snorm_indicator_const_le
theorem Memℒp.indicator (hs : MeasurableSet s) (hf : Memℒp f p μ) : Memℒp (s.indicator f) p μ :=
⟨hf.aestronglyMeasurable.indicator hs, lt_of_le_of_lt (snorm_indicator_le f) hf.snorm_lt_top⟩
#align measure_theory.mem_ℒp.indicator MeasureTheory.Memℒp.indicator
theorem snormEssSup_indicator_eq_snormEssSup_restrict {f : α → F} (hs : MeasurableSet s) :
snormEssSup (s.indicator f) μ = snormEssSup f (μ.restrict s) := by
simp_rw [snormEssSup, nnnorm_indicator_eq_indicator_nnnorm, ENNReal.coe_indicator,
ENNReal.essSup_indicator_eq_essSup_restrict hs]
#align measure_theory.snorm_ess_sup_indicator_eq_snorm_ess_sup_restrict MeasureTheory.snormEssSup_indicator_eq_snormEssSup_restrict
theorem snorm_indicator_eq_snorm_restrict {f : α → F} (hs : MeasurableSet s) :
snorm (s.indicator f) p μ = snorm f p (μ.restrict s) := by
by_cases hp_zero : p = 0
· simp only [hp_zero, snorm_exponent_zero]
by_cases hp_top : p = ∞
· simp_rw [hp_top, snorm_exponent_top]
exact snormEssSup_indicator_eq_snormEssSup_restrict hs
simp_rw [snorm_eq_lintegral_rpow_nnnorm hp_zero hp_top]
suffices (∫⁻ x, (‖s.indicator f x‖₊ : ℝ≥0∞) ^ p.toReal ∂μ) =
∫⁻ x in s, (‖f x‖₊ : ℝ≥0∞) ^ p.toReal ∂μ by rw [this]
rw [← lintegral_indicator _ hs]
congr
simp_rw [nnnorm_indicator_eq_indicator_nnnorm, ENNReal.coe_indicator]
have h_zero : (fun x => x ^ p.toReal) (0 : ℝ≥0∞) = 0 := by
simp [ENNReal.toReal_pos hp_zero hp_top]
-- Porting note: The implicit argument should be specified because the elaborator can't deal with
-- `∘` well.
exact (Set.indicator_comp_of_zero (g := fun x : ℝ≥0∞ => x ^ p.toReal) h_zero).symm
#align measure_theory.snorm_indicator_eq_snorm_restrict MeasureTheory.snorm_indicator_eq_snorm_restrict
theorem memℒp_indicator_iff_restrict (hs : MeasurableSet s) :
Memℒp (s.indicator f) p μ ↔ Memℒp f p (μ.restrict s) := by
simp [Memℒp, aestronglyMeasurable_indicator_iff hs, snorm_indicator_eq_snorm_restrict hs]
#align measure_theory.mem_ℒp_indicator_iff_restrict MeasureTheory.memℒp_indicator_iff_restrict
/-- If a function is supported on a finite-measure set and belongs to `ℒ^p`, then it belongs to
`ℒ^q` for any `q ≤ p`. -/
theorem Memℒp.memℒp_of_exponent_le_of_measure_support_ne_top
{p q : ℝ≥0∞} {f : α → E} (hfq : Memℒp f q μ) {s : Set α} (hf : ∀ x, x ∉ s → f x = 0)
(hs : μ s ≠ ∞) (hpq : p ≤ q) : Memℒp f p μ := by
have : (toMeasurable μ s).indicator f = f := by
apply Set.indicator_eq_self.2
apply Function.support_subset_iff'.2 (fun x hx ↦ hf x ?_)
contrapose! hx
exact subset_toMeasurable μ s hx
rw [← this, memℒp_indicator_iff_restrict (measurableSet_toMeasurable μ s)] at hfq ⊢
have : Fact (μ (toMeasurable μ s) < ∞) := ⟨by simpa [lt_top_iff_ne_top] using hs⟩
exact memℒp_of_exponent_le hfq hpq
theorem memℒp_indicator_const (p : ℝ≥0∞) (hs : MeasurableSet s) (c : E) (hμsc : c = 0 ∨ μ s ≠ ∞) :
Memℒp (s.indicator fun _ => c) p μ := by
rw [memℒp_indicator_iff_restrict hs]
rcases hμsc with rfl | hμ
· exact zero_memℒp
· have := Fact.mk hμ.lt_top
apply memℒp_const
#align measure_theory.mem_ℒp_indicator_const MeasureTheory.memℒp_indicator_const
/-- The `ℒ^p` norm of the indicator of a set is uniformly small if the set itself has small measure,
for any `p < ∞`. Given here as an existential `∀ ε > 0, ∃ η > 0, ...` to avoid later
management of `ℝ≥0∞`-arithmetic. -/
theorem exists_snorm_indicator_le (hp : p ≠ ∞) (c : E) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _ => c) p μ ≤ ε := by
rcases eq_or_ne p 0 with (rfl | h'p)
· exact ⟨1, zero_lt_one, fun s _ => by simp⟩
have hp₀ : 0 < p := bot_lt_iff_ne_bot.2 h'p
have hp₀' : 0 ≤ 1 / p.toReal := div_nonneg zero_le_one ENNReal.toReal_nonneg
have hp₀'' : 0 < p.toReal := ENNReal.toReal_pos hp₀.ne' hp
obtain ⟨η, hη_pos, hη_le⟩ :
∃ η : ℝ≥0, 0 < η ∧ (‖c‖₊ : ℝ≥0∞) * (η : ℝ≥0∞) ^ (1 / p.toReal) ≤ ε := by
have :
Filter.Tendsto (fun x : ℝ≥0 => ((‖c‖₊ * x ^ (1 / p.toReal) : ℝ≥0) : ℝ≥0∞)) (𝓝 0)
(𝓝 (0 : ℝ≥0)) := by
rw [ENNReal.tendsto_coe]
convert (NNReal.continuousAt_rpow_const (Or.inr hp₀')).tendsto.const_mul _
simp [hp₀''.ne']
have hε' : 0 < ε := hε.bot_lt
obtain ⟨δ, hδ, hδε'⟩ :=
NNReal.nhds_zero_basis.eventually_iff.mp (eventually_le_of_tendsto_lt hε' this)
obtain ⟨η, hη, hηδ⟩ := exists_between hδ
refine ⟨η, hη, ?_⟩
rw [ENNReal.coe_rpow_of_nonneg _ hp₀', ← ENNReal.coe_mul]
exact hδε' hηδ
refine ⟨η, hη_pos, fun s hs => ?_⟩
refine (snorm_indicator_const_le _ _).trans (le_trans ?_ hη_le)
exact mul_le_mul_left' (ENNReal.rpow_le_rpow hs hp₀') _
#align measure_theory.exists_snorm_indicator_le MeasureTheory.exists_snorm_indicator_le
protected lemma Memℒp.piecewise [DecidablePred (· ∈ s)] {g}
(hs : MeasurableSet s) (hf : Memℒp f p (μ.restrict s)) (hg : Memℒp g p (μ.restrict sᶜ)) :
Memℒp (s.piecewise f g) p μ := by
by_cases hp_zero : p = 0
· simp only [hp_zero, memℒp_zero_iff_aestronglyMeasurable]
exact AEStronglyMeasurable.piecewise hs hf.1 hg.1
refine ⟨AEStronglyMeasurable.piecewise hs hf.1 hg.1, ?_⟩
rcases eq_or_ne p ∞ with rfl | hp_top
· rw [snorm_top_piecewise f g hs]
exact max_lt hf.2 hg.2
rw [snorm_lt_top_iff_lintegral_rpow_nnnorm_lt_top hp_zero hp_top, ← lintegral_add_compl _ hs,
ENNReal.add_lt_top]
constructor
· have h : ∀ᵐ (x : α) ∂μ, x ∈ s →
(‖Set.piecewise s f g x‖₊ : ℝ≥0∞) ^ p.toReal = (‖f x‖₊ : ℝ≥0∞) ^ p.toReal := by
filter_upwards with a ha using by simp [ha]
rw [set_lintegral_congr_fun hs h]
exact lintegral_rpow_nnnorm_lt_top_of_snorm_lt_top hp_zero hp_top hf.2
· have h : ∀ᵐ (x : α) ∂μ, x ∈ sᶜ →
(‖Set.piecewise s f g x‖₊ : ℝ≥0∞) ^ p.toReal = (‖g x‖₊ : ℝ≥0∞) ^ p.toReal := by
filter_upwards with a ha
have ha' : a ∉ s := ha
simp [ha']
rw [set_lintegral_congr_fun hs.compl h]
exact lintegral_rpow_nnnorm_lt_top_of_snorm_lt_top hp_zero hp_top hg.2
end Indicator
section IndicatorConstLp
open Set Function
variable {s : Set α} {hs : MeasurableSet s} {hμs : μ s ≠ ∞} {c : E}
/-- Indicator of a set as an element of `Lp`. -/
def indicatorConstLp (p : ℝ≥0∞) (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : E) : Lp E p μ :=
Memℒp.toLp (s.indicator fun _ => c) (memℒp_indicator_const p hs c (Or.inr hμs))
#align measure_theory.indicator_const_Lp MeasureTheory.indicatorConstLp
/-- A version of `Set.indicator_add` for `MeasureTheory.indicatorConstLp`.-/
theorem indicatorConstLp_add {c' : E} :
indicatorConstLp p hs hμs c + indicatorConstLp p hs hμs c' =
indicatorConstLp p hs hμs (c + c') := by
simp_rw [indicatorConstLp, ← Memℒp.toLp_add, indicator_add]
rfl
/-- A version of `Set.indicator_sub` for `MeasureTheory.indicatorConstLp`.-/
theorem indicatorConstLp_sub {c' : E} :
indicatorConstLp p hs hμs c - indicatorConstLp p hs hμs c' =
indicatorConstLp p hs hμs (c - c') := by
simp_rw [indicatorConstLp, ← Memℒp.toLp_sub, indicator_sub]
rfl
theorem indicatorConstLp_coeFn : ⇑(indicatorConstLp p hs hμs c) =ᵐ[μ] s.indicator fun _ => c :=
Memℒp.coeFn_toLp (memℒp_indicator_const p hs c (Or.inr hμs))
#align measure_theory.indicator_const_Lp_coe_fn MeasureTheory.indicatorConstLp_coeFn
theorem indicatorConstLp_coeFn_mem : ∀ᵐ x : α ∂μ, x ∈ s → indicatorConstLp p hs hμs c x = c :=
indicatorConstLp_coeFn.mono fun _x hx hxs => hx.trans (Set.indicator_of_mem hxs _)
#align measure_theory.indicator_const_Lp_coe_fn_mem MeasureTheory.indicatorConstLp_coeFn_mem
theorem indicatorConstLp_coeFn_nmem : ∀ᵐ x : α ∂μ, x ∉ s → indicatorConstLp p hs hμs c x = 0 :=
indicatorConstLp_coeFn.mono fun _x hx hxs => hx.trans (Set.indicator_of_not_mem hxs _)
#align measure_theory.indicator_const_Lp_coe_fn_nmem MeasureTheory.indicatorConstLp_coeFn_nmem
theorem norm_indicatorConstLp (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
‖indicatorConstLp p hs hμs c‖ = ‖c‖ * (μ s).toReal ^ (1 / p.toReal) := by
rw [Lp.norm_def, snorm_congr_ae indicatorConstLp_coeFn,
snorm_indicator_const hs hp_ne_zero hp_ne_top, ENNReal.toReal_mul, ENNReal.toReal_rpow,
ENNReal.coe_toReal, coe_nnnorm]
#align measure_theory.norm_indicator_const_Lp MeasureTheory.norm_indicatorConstLp
theorem norm_indicatorConstLp_top (hμs_ne_zero : μ s ≠ 0) :
‖indicatorConstLp ∞ hs hμs c‖ = ‖c‖ := by
rw [Lp.norm_def, snorm_congr_ae indicatorConstLp_coeFn,
snorm_indicator_const' hs hμs_ne_zero ENNReal.top_ne_zero, ENNReal.top_toReal, _root_.div_zero,
ENNReal.rpow_zero, mul_one, ENNReal.coe_toReal, coe_nnnorm]
#align measure_theory.norm_indicator_const_Lp_top MeasureTheory.norm_indicatorConstLp_top
theorem norm_indicatorConstLp' (hp_pos : p ≠ 0) (hμs_pos : μ s ≠ 0) :
‖indicatorConstLp p hs hμs c‖ = ‖c‖ * (μ s).toReal ^ (1 / p.toReal) := by
by_cases hp_top : p = ∞
· rw [hp_top, ENNReal.top_toReal, _root_.div_zero, Real.rpow_zero, mul_one]
exact norm_indicatorConstLp_top hμs_pos
· exact norm_indicatorConstLp hp_pos hp_top
#align measure_theory.norm_indicator_const_Lp' MeasureTheory.norm_indicatorConstLp'
theorem norm_indicatorConstLp_le :
‖indicatorConstLp p hs hμs c‖ ≤ ‖c‖ * (μ s).toReal ^ (1 / p.toReal) := by
rw [indicatorConstLp, Lp.norm_toLp]
refine ENNReal.toReal_le_of_le_ofReal (by positivity) ?_
refine (snorm_indicator_const_le _ _).trans_eq ?_
rw [← coe_nnnorm, ENNReal.ofReal_mul (NNReal.coe_nonneg _), ENNReal.ofReal_coe_nnreal,
ENNReal.toReal_rpow, ENNReal.ofReal_toReal]
exact ENNReal.rpow_ne_top_of_nonneg (by positivity) hμs
theorem edist_indicatorConstLp_eq_nnnorm {t : Set α} {ht : MeasurableSet t} {hμt : μ t ≠ ∞} :
edist (indicatorConstLp p hs hμs c) (indicatorConstLp p ht hμt c) =
‖indicatorConstLp p (hs.symmDiff ht) (measure_symmDiff_ne_top hμs hμt) c‖₊ := by
unfold indicatorConstLp
rw [Lp.edist_toLp_toLp, snorm_indicator_sub_indicator, Lp.coe_nnnorm_toLp]
theorem dist_indicatorConstLp_eq_norm {t : Set α} {ht : MeasurableSet t} {hμt : μ t ≠ ∞} :
dist (indicatorConstLp p hs hμs c) (indicatorConstLp p ht hμt c) =
‖indicatorConstLp p (hs.symmDiff ht) (measure_symmDiff_ne_top hμs hμt) c‖ := by
rw [Lp.dist_edist, edist_indicatorConstLp_eq_nnnorm, ENNReal.coe_toReal, Lp.coe_nnnorm]
@[simp]
theorem indicatorConstLp_empty :
indicatorConstLp p MeasurableSet.empty (by simp : μ ∅ ≠ ∞) c = 0 := by
simp only [indicatorConstLp, Set.indicator_empty', Memℒp.toLp_zero]
#align measure_theory.indicator_const_empty MeasureTheory.indicatorConstLp_empty
theorem indicatorConstLp_inj {s t : Set α} (hs : MeasurableSet s) (hsμ : μ s ≠ ∞)
(ht : MeasurableSet t) (htμ : μ t ≠ ∞) {c : E} (hc : c ≠ 0)
(h : indicatorConstLp p hs hsμ c = indicatorConstLp p ht htμ c) : s =ᵐ[μ] t :=
.of_indicator_const hc <|
calc
s.indicator (fun _ ↦ c) =ᵐ[μ] indicatorConstLp p hs hsμ c := indicatorConstLp_coeFn.symm
_ = indicatorConstLp p ht htμ c := by rw [h]
_ =ᵐ[μ] t.indicator (fun _ ↦ c) := indicatorConstLp_coeFn
theorem memℒp_add_of_disjoint {f g : α → E} (h : Disjoint (support f) (support g))
(hf : StronglyMeasurable f) (hg : StronglyMeasurable g) :
Memℒp (f + g) p μ ↔ Memℒp f p μ ∧ Memℒp g p μ := by
borelize E
refine ⟨fun hfg => ⟨?_, ?_⟩, fun h => h.1.add h.2⟩
· rw [← Set.indicator_add_eq_left h]; exact hfg.indicator (measurableSet_support hf.measurable)
· rw [← Set.indicator_add_eq_right h]; exact hfg.indicator (measurableSet_support hg.measurable)
#align measure_theory.mem_ℒp_add_of_disjoint MeasureTheory.memℒp_add_of_disjoint
/-- The indicator of a disjoint union of two sets is the sum of the indicators of the sets. -/
theorem indicatorConstLp_disjoint_union {s t : Set α} (hs : MeasurableSet s) (ht : MeasurableSet t)
(hμs : μ s ≠ ∞) (hμt : μ t ≠ ∞) (hst : s ∩ t = ∅) (c : E) :
indicatorConstLp p (hs.union ht) (measure_union_ne_top hμs hμt) c =
indicatorConstLp p hs hμs c + indicatorConstLp p ht hμt c := by
ext1
refine indicatorConstLp_coeFn.trans (EventuallyEq.trans ?_ (Lp.coeFn_add _ _).symm)
refine
EventuallyEq.trans ?_
(EventuallyEq.add indicatorConstLp_coeFn.symm indicatorConstLp_coeFn.symm)
rw [Set.indicator_union_of_disjoint (Set.disjoint_iff_inter_eq_empty.mpr hst) _]
#align measure_theory.indicator_const_Lp_disjoint_union MeasureTheory.indicatorConstLp_disjoint_union
end IndicatorConstLp
section const
variable (μ p)
variable [IsFiniteMeasure μ] (c : E)
/-- Constant function as an element of `MeasureTheory.Lp` for a finite measure. -/
protected def Lp.const : E →+ Lp E p μ where
toFun c := ⟨AEEqFun.const α c, const_mem_Lp α μ c⟩
map_zero' := rfl
map_add' _ _ := rfl
lemma Lp.coeFn_const : Lp.const p μ c =ᵐ[μ] Function.const α c :=
AEEqFun.coeFn_const α c
@[simp] lemma Lp.const_val : (Lp.const p μ c).1 = AEEqFun.const α c := rfl
@[simp]
lemma Memℒp.toLp_const : Memℒp.toLp _ (memℒp_const c) = Lp.const p μ c := rfl
@[simp]
lemma indicatorConstLp_univ :
indicatorConstLp p .univ (measure_ne_top μ _) c = Lp.const p μ c := by
rw [← Memℒp.toLp_const, indicatorConstLp]
simp only [Set.indicator_univ, Function.const]
theorem Lp.norm_const [NeZero μ] (hp_zero : p ≠ 0) :
‖Lp.const p μ c‖ = ‖c‖ * (μ Set.univ).toReal ^ (1 / p.toReal) := by
have := NeZero.ne μ
rw [← Memℒp.toLp_const, Lp.norm_toLp, snorm_const] <;> try assumption
rw [ENNReal.toReal_mul, ENNReal.coe_toReal, ← ENNReal.toReal_rpow, coe_nnnorm]
theorem Lp.norm_const' (hp_zero : p ≠ 0) (hp_top : p ≠ ∞) :
‖Lp.const p μ c‖ = ‖c‖ * (μ Set.univ).toReal ^ (1 / p.toReal) := by
rw [← Memℒp.toLp_const, Lp.norm_toLp, snorm_const'] <;> try assumption
rw [ENNReal.toReal_mul, ENNReal.coe_toReal, ← ENNReal.toReal_rpow, coe_nnnorm]
theorem Lp.norm_const_le : ‖Lp.const p μ c‖ ≤ ‖c‖ * (μ Set.univ).toReal ^ (1 / p.toReal) := by
rw [← indicatorConstLp_univ]
exact norm_indicatorConstLp_le
/-- `MeasureTheory.Lp.const` as a `LinearMap`. -/
@[simps] protected def Lp.constₗ (𝕜 : Type*) [NormedRing 𝕜] [Module 𝕜 E] [BoundedSMul 𝕜 E] :
E →ₗ[𝕜] Lp E p μ where
toFun := Lp.const p μ
map_add' := map_add _
map_smul' _ _ := rfl
@[simps! apply]
protected def Lp.constL (𝕜 : Type*) [NormedField 𝕜] [NormedSpace 𝕜 E] [Fact (1 ≤ p)] :
E →L[𝕜] Lp E p μ :=
(Lp.constₗ p μ 𝕜).mkContinuous ((μ Set.univ).toReal ^ (1 / p.toReal)) fun _ ↦
(Lp.norm_const_le _ _ _).trans_eq (mul_comm _ _)
theorem Lp.norm_constL_le (𝕜 : Type*) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E]
[Fact (1 ≤ p)] :
‖(Lp.constL p μ 𝕜 : E →L[𝕜] Lp E p μ)‖ ≤ (μ Set.univ).toReal ^ (1 / p.toReal) :=
LinearMap.mkContinuous_norm_le _ (by positivity) _
end const
theorem Memℒp.norm_rpow_div {f : α → E} (hf : Memℒp f p μ) (q : ℝ≥0∞) :
Memℒp (fun x : α => ‖f x‖ ^ q.toReal) (p / q) μ := by
refine ⟨(hf.1.norm.aemeasurable.pow_const q.toReal).aestronglyMeasurable, ?_⟩
by_cases q_top : q = ∞
· simp [q_top]
by_cases q_zero : q = 0
· simp [q_zero]
by_cases p_zero : p = 0
· simp [p_zero]
rw [ENNReal.div_zero p_zero]
exact (memℒp_top_const (1 : ℝ)).2
rw [snorm_norm_rpow _ (ENNReal.toReal_pos q_zero q_top)]
apply ENNReal.rpow_lt_top_of_nonneg ENNReal.toReal_nonneg
rw [ENNReal.ofReal_toReal q_top, div_eq_mul_inv, mul_assoc, ENNReal.inv_mul_cancel q_zero q_top,
mul_one]
exact hf.2.ne
#align measure_theory.mem_ℒp.norm_rpow_div MeasureTheory.Memℒp.norm_rpow_div
theorem memℒp_norm_rpow_iff {q : ℝ≥0∞} {f : α → E} (hf : AEStronglyMeasurable f μ) (q_zero : q ≠ 0)
(q_top : q ≠ ∞) : Memℒp (fun x : α => ‖f x‖ ^ q.toReal) (p / q) μ ↔ Memℒp f p μ := by
refine ⟨fun h => ?_, fun h => h.norm_rpow_div q⟩
apply (memℒp_norm_iff hf).1
convert h.norm_rpow_div q⁻¹ using 1
· ext x
rw [Real.norm_eq_abs, Real.abs_rpow_of_nonneg (norm_nonneg _), ← Real.rpow_mul (abs_nonneg _),
ENNReal.toReal_inv, mul_inv_cancel, abs_of_nonneg (norm_nonneg _), Real.rpow_one]
simp [ENNReal.toReal_eq_zero_iff, not_or, q_zero, q_top]
· rw [div_eq_mul_inv, inv_inv, div_eq_mul_inv, mul_assoc, ENNReal.inv_mul_cancel q_zero q_top,
mul_one]
#align measure_theory.mem_ℒp_norm_rpow_iff MeasureTheory.memℒp_norm_rpow_iff
theorem Memℒp.norm_rpow {f : α → E} (hf : Memℒp f p μ) (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
Memℒp (fun x : α => ‖f x‖ ^ p.toReal) 1 μ := by
convert hf.norm_rpow_div p
rw [div_eq_mul_inv, ENNReal.mul_inv_cancel hp_ne_zero hp_ne_top]
#align measure_theory.mem_ℒp.norm_rpow MeasureTheory.Memℒp.norm_rpow
theorem AEEqFun.compMeasurePreserving_mem_Lp {β : Type*} [MeasurableSpace β]
{μb : MeasureTheory.Measure β} {g : β →ₘ[μb] E} (hg : g ∈ Lp E p μb) {f : α → β}
(hf : MeasurePreserving f μ μb) :
g.compMeasurePreserving f hf ∈ Lp E p μ := by
rw [Lp.mem_Lp_iff_snorm_lt_top] at hg ⊢
rwa [snorm_compMeasurePreserving]
namespace Lp
/-! ### Composition with a measure preserving function -/
variable {β : Type*} [MeasurableSpace β] {μb : MeasureTheory.Measure β} {f : α → β}
/-- Composition of an `L^p` function with a measure preserving function is an `L^p` function. -/
def compMeasurePreserving (f : α → β) (hf : MeasurePreserving f μ μb) :
Lp E p μb →+ Lp E p μ where
toFun g := ⟨g.1.compMeasurePreserving f hf, g.1.compMeasurePreserving_mem_Lp g.2 hf⟩
map_zero' := rfl
map_add' := by rintro ⟨⟨_⟩, _⟩ ⟨⟨_⟩, _⟩; rfl
@[simp]
theorem compMeasurePreserving_val (g : Lp E p μb) (hf : MeasurePreserving f μ μb) :
(compMeasurePreserving f hf g).1 = g.1.compMeasurePreserving f hf :=
rfl
theorem coeFn_compMeasurePreserving (g : Lp E p μb) (hf : MeasurePreserving f μ μb) :
compMeasurePreserving f hf g =ᵐ[μ] g ∘ f :=
g.1.coeFn_compMeasurePreserving hf
@[simp]
theorem norm_compMeasurePreserving (g : Lp E p μb) (hf : MeasurePreserving f μ μb) :
‖compMeasurePreserving f hf g‖ = ‖g‖ :=
congr_arg ENNReal.toReal <| g.1.snorm_compMeasurePreserving hf
variable (𝕜 : Type*) [NormedRing 𝕜] [Module 𝕜 E] [BoundedSMul 𝕜 E]
/-- `MeasureTheory.Lp.compMeasurePreserving` as a linear map. -/
@[simps]
def compMeasurePreservingₗ (f : α → β) (hf : MeasurePreserving f μ μb) :
Lp E p μb →ₗ[𝕜] Lp E p μ where
__ := compMeasurePreserving f hf
map_smul' c g := by rcases g with ⟨⟨_⟩, _⟩; rfl
/-- `MeasureTheory.Lp.compMeasurePreserving` as a linear isometry. -/
@[simps!]
def compMeasurePreservingₗᵢ [Fact (1 ≤ p)] (f : α → β) (hf : MeasurePreserving f μ μb) :
Lp E p μb →ₗᵢ[𝕜] Lp E p μ where
toLinearMap := compMeasurePreservingₗ 𝕜 f hf
norm_map' := (norm_compMeasurePreserving · hf)
end Lp
end MeasureTheory
open MeasureTheory
/-!
### Composition on `L^p`
We show that Lipschitz functions vanishing at zero act by composition on `L^p`, and specialize
this to the composition with continuous linear maps, and to the definition of the positive
part of an `L^p` function.
-/
section Composition
variable {g : E → F} {c : ℝ≥0}
theorem LipschitzWith.comp_memℒp {α E F} {K} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] {f : α → E} {g : E → F} (hg : LipschitzWith K g)
(g0 : g 0 = 0) (hL : Memℒp f p μ) : Memℒp (g ∘ f) p μ :=
have : ∀ x, ‖g (f x)‖ ≤ K * ‖f x‖ := fun x ↦ by
-- TODO: add `LipschitzWith.nnnorm_sub_le` and `LipschitzWith.nnnorm_le`
simpa [g0] using hg.norm_sub_le (f x) 0
hL.of_le_mul (hg.continuous.comp_aestronglyMeasurable hL.1) (eventually_of_forall this)
#align lipschitz_with.comp_mem_ℒp LipschitzWith.comp_memℒp
theorem MeasureTheory.Memℒp.of_comp_antilipschitzWith {α E F} {K'} [MeasurableSpace α]
{μ : Measure α} [NormedAddCommGroup E] [NormedAddCommGroup F] {f : α → E} {g : E → F}
(hL : Memℒp (g ∘ f) p μ) (hg : UniformContinuous g) (hg' : AntilipschitzWith K' g)
(g0 : g 0 = 0) : Memℒp f p μ := by
have A : ∀ x, ‖f x‖ ≤ K' * ‖g (f x)‖ := by
intro x
-- TODO: add `AntilipschitzWith.le_mul_nnnorm_sub` and `AntilipschitzWith.le_mul_norm`
rw [← dist_zero_right, ← dist_zero_right, ← g0]
apply hg'.le_mul_dist
have B : AEStronglyMeasurable f μ :=
(hg'.uniformEmbedding hg).embedding.aestronglyMeasurable_comp_iff.1 hL.1
exact hL.of_le_mul B (Filter.eventually_of_forall A)
#align measure_theory.mem_ℒp.of_comp_antilipschitz_with MeasureTheory.Memℒp.of_comp_antilipschitzWith
namespace LipschitzWith
theorem memℒp_comp_iff_of_antilipschitz {α E F} {K K'} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] {f : α → E} {g : E → F} (hg : LipschitzWith K g)
(hg' : AntilipschitzWith K' g) (g0 : g 0 = 0) : Memℒp (g ∘ f) p μ ↔ Memℒp f p μ :=
⟨fun h => h.of_comp_antilipschitzWith hg.uniformContinuous hg' g0, fun h => hg.comp_memℒp g0 h⟩
#align lipschitz_with.mem_ℒp_comp_iff_of_antilipschitz LipschitzWith.memℒp_comp_iff_of_antilipschitz
/-- When `g` is a Lipschitz function sending `0` to `0` and `f` is in `Lp`, then `g ∘ f` is well
defined as an element of `Lp`. -/
def compLp (hg : LipschitzWith c g) (g0 : g 0 = 0) (f : Lp E p μ) : Lp F p μ :=
⟨AEEqFun.comp g hg.continuous (f : α →ₘ[μ] E), by
suffices ∀ᵐ x ∂μ, ‖AEEqFun.comp g hg.continuous (f : α →ₘ[μ] E) x‖ ≤ c * ‖f x‖ from
Lp.mem_Lp_of_ae_le_mul this
filter_upwards [AEEqFun.coeFn_comp g hg.continuous (f : α →ₘ[μ] E)] with a ha
simp only [ha]
rw [← dist_zero_right, ← dist_zero_right, ← g0]
exact hg.dist_le_mul (f a) 0⟩
#align lipschitz_with.comp_Lp LipschitzWith.compLp
theorem coeFn_compLp (hg : LipschitzWith c g) (g0 : g 0 = 0) (f : Lp E p μ) :
hg.compLp g0 f =ᵐ[μ] g ∘ f :=
AEEqFun.coeFn_comp _ hg.continuous _
#align lipschitz_with.coe_fn_comp_Lp LipschitzWith.coeFn_compLp
@[simp]
theorem compLp_zero (hg : LipschitzWith c g) (g0 : g 0 = 0) : hg.compLp g0 (0 : Lp E p μ) = 0 := by
rw [Lp.eq_zero_iff_ae_eq_zero]
apply (coeFn_compLp _ _ _).trans
filter_upwards [Lp.coeFn_zero E p μ] with _ ha
simp only [ha, g0, Function.comp_apply, Pi.zero_apply]
#align lipschitz_with.comp_Lp_zero LipschitzWith.compLp_zero
theorem norm_compLp_sub_le (hg : LipschitzWith c g) (g0 : g 0 = 0) (f f' : Lp E p μ) :
‖hg.compLp g0 f - hg.compLp g0 f'‖ ≤ c * ‖f - f'‖ := by
apply Lp.norm_le_mul_norm_of_ae_le_mul
filter_upwards [hg.coeFn_compLp g0 f, hg.coeFn_compLp g0 f',
Lp.coeFn_sub (hg.compLp g0 f) (hg.compLp g0 f'), Lp.coeFn_sub f f'] with a ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, ← dist_eq_norm, Pi.sub_apply, Function.comp_apply]
exact hg.dist_le_mul (f a) (f' a)
#align lipschitz_with.norm_comp_Lp_sub_le LipschitzWith.norm_compLp_sub_le
theorem norm_compLp_le (hg : LipschitzWith c g) (g0 : g 0 = 0) (f : Lp E p μ) :
‖hg.compLp g0 f‖ ≤ c * ‖f‖ := by simpa using hg.norm_compLp_sub_le g0 f 0
#align lipschitz_with.norm_comp_Lp_le LipschitzWith.norm_compLp_le
theorem lipschitzWith_compLp [Fact (1 ≤ p)] (hg : LipschitzWith c g) (g0 : g 0 = 0) :
LipschitzWith c (hg.compLp g0 : Lp E p μ → Lp F p μ) :=
LipschitzWith.of_dist_le_mul fun f g => by simp [dist_eq_norm, norm_compLp_sub_le]
#align lipschitz_with.lipschitz_with_comp_Lp LipschitzWith.lipschitzWith_compLp
theorem continuous_compLp [Fact (1 ≤ p)] (hg : LipschitzWith c g) (g0 : g 0 = 0) :
Continuous (hg.compLp g0 : Lp E p μ → Lp F p μ) :=
(lipschitzWith_compLp hg g0).continuous
#align lipschitz_with.continuous_comp_Lp LipschitzWith.continuous_compLp
end LipschitzWith
namespace ContinuousLinearMap
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F]
/-- Composing `f : Lp` with `L : E →L[𝕜] F`. -/
def compLp (L : E →L[𝕜] F) (f : Lp E p μ) : Lp F p μ :=
L.lipschitz.compLp (map_zero L) f
#align continuous_linear_map.comp_Lp ContinuousLinearMap.compLp
theorem coeFn_compLp (L : E →L[𝕜] F) (f : Lp E p μ) : ∀ᵐ a ∂μ, (L.compLp f) a = L (f a) :=
LipschitzWith.coeFn_compLp _ _ _
#align continuous_linear_map.coe_fn_comp_Lp ContinuousLinearMap.coeFn_compLp
theorem coeFn_compLp' (L : E →L[𝕜] F) (f : Lp E p μ) : L.compLp f =ᵐ[μ] fun a => L (f a) :=
L.coeFn_compLp f
#align continuous_linear_map.coe_fn_comp_Lp' ContinuousLinearMap.coeFn_compLp'
theorem comp_memℒp (L : E →L[𝕜] F) (f : Lp E p μ) : Memℒp (L ∘ f) p μ :=
(Lp.memℒp (L.compLp f)).ae_eq (L.coeFn_compLp' f)
#align continuous_linear_map.comp_mem_ℒp ContinuousLinearMap.comp_memℒp
theorem comp_memℒp' (L : E →L[𝕜] F) {f : α → E} (hf : Memℒp f p μ) : Memℒp (L ∘ f) p μ :=
(L.comp_memℒp (hf.toLp f)).ae_eq (EventuallyEq.fun_comp hf.coeFn_toLp _)
#align continuous_linear_map.comp_mem_ℒp' ContinuousLinearMap.comp_memℒp'
section RCLike
variable {K : Type*} [RCLike K]
theorem _root_.MeasureTheory.Memℒp.ofReal {f : α → ℝ} (hf : Memℒp f p μ) :
Memℒp (fun x => (f x : K)) p μ :=
(@RCLike.ofRealCLM K _).comp_memℒp' hf
#align measure_theory.mem_ℒp.of_real MeasureTheory.Memℒp.ofReal
theorem _root_.MeasureTheory.memℒp_re_im_iff {f : α → K} :
Memℒp (fun x ↦ RCLike.re (f x)) p μ ∧ Memℒp (fun x ↦ RCLike.im (f x)) p μ ↔
Memℒp f p μ := by
refine ⟨?_, fun hf => ⟨hf.re, hf.im⟩⟩
rintro ⟨hre, him⟩
convert MeasureTheory.Memℒp.add (E := K) hre.ofReal (him.ofReal.const_mul RCLike.I)
ext1 x
rw [Pi.add_apply, mul_comm, RCLike.re_add_im]
#align measure_theory.mem_ℒp_re_im_iff MeasureTheory.memℒp_re_im_iff
end RCLike
theorem add_compLp (L L' : E →L[𝕜] F) (f : Lp E p μ) :
(L + L').compLp f = L.compLp f + L'.compLp f := by
ext1
refine (coeFn_compLp' (L + L') f).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_add _ _).symm
refine
EventuallyEq.trans ?_ (EventuallyEq.add (L.coeFn_compLp' f).symm (L'.coeFn_compLp' f).symm)
filter_upwards with x
rw [coe_add', Pi.add_def]
#align continuous_linear_map.add_comp_Lp ContinuousLinearMap.add_compLp
theorem smul_compLp {𝕜'} [NormedRing 𝕜'] [Module 𝕜' F] [BoundedSMul 𝕜' F] [SMulCommClass 𝕜 𝕜' F]
(c : 𝕜') (L : E →L[𝕜] F) (f : Lp E p μ) : (c • L).compLp f = c • L.compLp f := by
ext1
refine (coeFn_compLp' (c • L) f).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_smul _ _).symm
refine (L.coeFn_compLp' f).mono fun x hx => ?_
rw [Pi.smul_apply, hx, coe_smul', Pi.smul_def]
#align continuous_linear_map.smul_comp_Lp ContinuousLinearMap.smul_compLp
theorem norm_compLp_le (L : E →L[𝕜] F) (f : Lp E p μ) : ‖L.compLp f‖ ≤ ‖L‖ * ‖f‖ :=
LipschitzWith.norm_compLp_le _ _ _
#align continuous_linear_map.norm_comp_Lp_le ContinuousLinearMap.norm_compLp_le
variable (μ p)
/-- Composing `f : Lp E p μ` with `L : E →L[𝕜] F`, seen as a `𝕜`-linear map on `Lp E p μ`. -/
def compLpₗ (L : E →L[𝕜] F) : Lp E p μ →ₗ[𝕜] Lp F p μ where
toFun f := L.compLp f
map_add' f g := by
ext1
filter_upwards [Lp.coeFn_add f g, coeFn_compLp L (f + g), coeFn_compLp L f,
coeFn_compLp L g, Lp.coeFn_add (L.compLp f) (L.compLp g)]
intro a ha1 ha2 ha3 ha4 ha5
simp only [ha1, ha2, ha3, ha4, ha5, map_add, Pi.add_apply]
map_smul' c f := by
dsimp
ext1
filter_upwards [Lp.coeFn_smul c f, coeFn_compLp L (c • f), Lp.coeFn_smul c (L.compLp f),
coeFn_compLp L f] with _ ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, map_smul, Pi.smul_apply]
#align continuous_linear_map.comp_Lpₗ ContinuousLinearMap.compLpₗ
/-- Composing `f : Lp E p μ` with `L : E →L[𝕜] F`, seen as a continuous `𝕜`-linear map on
`Lp E p μ`. See also the similar
* `LinearMap.compLeft` for functions,
* `ContinuousLinearMap.compLeftContinuous` for continuous functions,
* `ContinuousLinearMap.compLeftContinuousBounded` for bounded continuous functions,
* `ContinuousLinearMap.compLeftContinuousCompact` for continuous functions on compact spaces.
-/
def compLpL [Fact (1 ≤ p)] (L : E →L[𝕜] F) : Lp E p μ →L[𝕜] Lp F p μ :=
LinearMap.mkContinuous (L.compLpₗ p μ) ‖L‖ L.norm_compLp_le
#align continuous_linear_map.comp_LpL ContinuousLinearMap.compLpL
variable {μ p}
theorem coeFn_compLpL [Fact (1 ≤ p)] (L : E →L[𝕜] F) (f : Lp E p μ) :
L.compLpL p μ f =ᵐ[μ] fun a => L (f a) :=
L.coeFn_compLp f
#align continuous_linear_map.coe_fn_comp_LpL ContinuousLinearMap.coeFn_compLpL
theorem add_compLpL [Fact (1 ≤ p)] (L L' : E →L[𝕜] F) :
(L + L').compLpL p μ = L.compLpL p μ + L'.compLpL p μ := by ext1 f; exact add_compLp L L' f
#align continuous_linear_map.add_comp_LpL ContinuousLinearMap.add_compLpL
theorem smul_compLpL [Fact (1 ≤ p)] {𝕜'} [NormedRing 𝕜'] [Module 𝕜' F] [BoundedSMul 𝕜' F]
[SMulCommClass 𝕜 𝕜' F] (c : 𝕜') (L : E →L[𝕜] F) : (c • L).compLpL p μ = c • L.compLpL p μ := by
ext1 f; exact smul_compLp c L f
#align continuous_linear_map.smul_comp_LpL ContinuousLinearMap.smul_compLpL
theorem norm_compLpL_le [Fact (1 ≤ p)] (L : E →L[𝕜] F) : ‖L.compLpL p μ‖ ≤ ‖L‖ :=
LinearMap.mkContinuous_norm_le _ (norm_nonneg _) _
#align continuous_linear_map.norm_compLpL_le ContinuousLinearMap.norm_compLpL_le
end ContinuousLinearMap
namespace MeasureTheory
theorem indicatorConstLp_eq_toSpanSingleton_compLp {s : Set α} [NormedSpace ℝ F]
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : F) :
indicatorConstLp 2 hs hμs x =
(ContinuousLinearMap.toSpanSingleton ℝ x).compLp (indicatorConstLp 2 hs hμs (1 : ℝ)) := by
ext1
refine indicatorConstLp_coeFn.trans ?_
have h_compLp :=
(ContinuousLinearMap.toSpanSingleton ℝ x).coeFn_compLp (indicatorConstLp 2 hs hμs (1 : ℝ))
rw [← EventuallyEq] at h_compLp
refine EventuallyEq.trans ?_ h_compLp.symm
refine (@indicatorConstLp_coeFn _ _ _ 2 μ _ s hs hμs (1 : ℝ)).mono fun y hy => ?_
dsimp only
rw [hy]
simp_rw [ContinuousLinearMap.toSpanSingleton_apply]
by_cases hy_mem : y ∈ s <;> simp [hy_mem, ContinuousLinearMap.lsmul_apply]
#align measure_theory.indicator_const_Lp_eq_to_span_singleton_comp_Lp MeasureTheory.indicatorConstLp_eq_toSpanSingleton_compLp
namespace Lp
section PosPart
theorem lipschitzWith_pos_part : LipschitzWith 1 fun x : ℝ => max x 0 :=
LipschitzWith.of_dist_le_mul fun x y => by simp [Real.dist_eq, abs_max_sub_max_le_abs]
#align measure_theory.Lp.lipschitz_with_pos_part MeasureTheory.Lp.lipschitzWith_pos_part
theorem _root_.MeasureTheory.Memℒp.pos_part {f : α → ℝ} (hf : Memℒp f p μ) :
Memℒp (fun x => max (f x) 0) p μ :=
lipschitzWith_pos_part.comp_memℒp (max_eq_right le_rfl) hf
#align measure_theory.mem_ℒp.pos_part MeasureTheory.Memℒp.pos_part
theorem _root_.MeasureTheory.Memℒp.neg_part {f : α → ℝ} (hf : Memℒp f p μ) :
Memℒp (fun x => max (-f x) 0) p μ :=
lipschitzWith_pos_part.comp_memℒp (max_eq_right le_rfl) hf.neg
#align measure_theory.mem_ℒp.neg_part MeasureTheory.Memℒp.neg_part
/-- Positive part of a function in `L^p`. -/
def posPart (f : Lp ℝ p μ) : Lp ℝ p μ :=
lipschitzWith_pos_part.compLp (max_eq_right le_rfl) f
#align measure_theory.Lp.pos_part MeasureTheory.Lp.posPart
/-- Negative part of a function in `L^p`. -/
def negPart (f : Lp ℝ p μ) : Lp ℝ p μ :=
posPart (-f)
#align measure_theory.Lp.neg_part MeasureTheory.Lp.negPart
@[norm_cast]
theorem coe_posPart (f : Lp ℝ p μ) : (posPart f : α →ₘ[μ] ℝ) = (f : α →ₘ[μ] ℝ).posPart :=
rfl
#align measure_theory.Lp.coe_pos_part MeasureTheory.Lp.coe_posPart
theorem coeFn_posPart (f : Lp ℝ p μ) : ⇑(posPart f) =ᵐ[μ] fun a => max (f a) 0 :=
AEEqFun.coeFn_posPart _
#align measure_theory.Lp.coe_fn_pos_part MeasureTheory.Lp.coeFn_posPart
theorem coeFn_negPart_eq_max (f : Lp ℝ p μ) : ∀ᵐ a ∂μ, negPart f a = max (-f a) 0 := by
rw [negPart]
filter_upwards [coeFn_posPart (-f), coeFn_neg f] with _ h₁ h₂
rw [h₁, h₂, Pi.neg_apply]
#align measure_theory.Lp.coe_fn_neg_part_eq_max MeasureTheory.Lp.coeFn_negPart_eq_max
theorem coeFn_negPart (f : Lp ℝ p μ) : ∀ᵐ a ∂μ, negPart f a = -min (f a) 0 :=
(coeFn_negPart_eq_max f).mono fun a h => by rw [h, ← max_neg_neg, neg_zero]
#align measure_theory.Lp.coe_fn_neg_part MeasureTheory.Lp.coeFn_negPart
theorem continuous_posPart [Fact (1 ≤ p)] : Continuous fun f : Lp ℝ p μ => posPart f :=
LipschitzWith.continuous_compLp _ _
#align measure_theory.Lp.continuous_pos_part MeasureTheory.Lp.continuous_posPart
theorem continuous_negPart [Fact (1 ≤ p)] : Continuous fun f : Lp ℝ p μ => negPart f := by
unfold negPart
exact continuous_posPart.comp continuous_neg
#align measure_theory.Lp.continuous_neg_part MeasureTheory.Lp.continuous_negPart
end PosPart
end Lp
end MeasureTheory
end Composition
/-!
## `L^p` is a complete space
We show that `L^p` is a complete space for `1 ≤ p`.
-/
section CompleteSpace
namespace MeasureTheory
namespace Lp
theorem snorm'_lim_eq_lintegral_liminf {ι} [Nonempty ι] [LinearOrder ι] {f : ι → α → G} {p : ℝ}
(hp_nonneg : 0 ≤ p) {f_lim : α → G}
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm' f_lim p μ = (∫⁻ a, atTop.liminf fun m => (‖f m a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) := by
suffices h_no_pow :
(∫⁻ a, (‖f_lim a‖₊ : ℝ≥0∞) ^ p ∂μ) = ∫⁻ a, atTop.liminf fun m => (‖f m a‖₊ : ℝ≥0∞) ^ p ∂μ by
rw [snorm', h_no_pow]
refine lintegral_congr_ae (h_lim.mono fun a ha => ?_)
dsimp only
rw [Tendsto.liminf_eq]
simp_rw [ENNReal.coe_rpow_of_nonneg _ hp_nonneg, ENNReal.tendsto_coe]
refine ((NNReal.continuous_rpow_const hp_nonneg).tendsto ‖f_lim a‖₊).comp ?_
exact (continuous_nnnorm.tendsto (f_lim a)).comp ha
#align measure_theory.Lp.snorm'_lim_eq_lintegral_liminf MeasureTheory.Lp.snorm'_lim_eq_lintegral_liminf
theorem snorm'_lim_le_liminf_snorm' {E} [NormedAddCommGroup E] {f : ℕ → α → E} {p : ℝ}
(hp_pos : 0 < p) (hf : ∀ n, AEStronglyMeasurable (f n) μ) {f_lim : α → E}
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm' f_lim p μ ≤ atTop.liminf fun n => snorm' (f n) p μ := by
rw [snorm'_lim_eq_lintegral_liminf hp_pos.le h_lim]
rw [← ENNReal.le_rpow_one_div_iff (by simp [hp_pos] : 0 < 1 / p), one_div_one_div]
refine (lintegral_liminf_le' fun m => (hf m).ennnorm.pow_const _).trans_eq ?_
have h_pow_liminf :
(atTop.liminf fun n => snorm' (f n) p μ) ^ p = atTop.liminf fun n => snorm' (f n) p μ ^ p := by
have h_rpow_mono := ENNReal.strictMono_rpow_of_pos hp_pos
have h_rpow_surj := (ENNReal.rpow_left_bijective hp_pos.ne.symm).2
refine (h_rpow_mono.orderIsoOfSurjective _ h_rpow_surj).liminf_apply ?_ ?_ ?_ ?_
all_goals isBoundedDefault
rw [h_pow_liminf]
simp_rw [snorm', ← ENNReal.rpow_mul, one_div, inv_mul_cancel hp_pos.ne.symm, ENNReal.rpow_one]
#align measure_theory.Lp.snorm'_lim_le_liminf_snorm' MeasureTheory.Lp.snorm'_lim_le_liminf_snorm'
theorem snorm_exponent_top_lim_eq_essSup_liminf {ι} [Nonempty ι] [LinearOrder ι] {f : ι → α → G}
{f_lim : α → G} (h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm f_lim ∞ μ = essSup (fun x => atTop.liminf fun m => (‖f m x‖₊ : ℝ≥0∞)) μ := by
rw [snorm_exponent_top, snormEssSup]
refine essSup_congr_ae (h_lim.mono fun x hx => ?_)
dsimp only
apply (Tendsto.liminf_eq ..).symm
rw [ENNReal.tendsto_coe]
exact (continuous_nnnorm.tendsto (f_lim x)).comp hx
#align measure_theory.Lp.snorm_exponent_top_lim_eq_ess_sup_liminf MeasureTheory.Lp.snorm_exponent_top_lim_eq_essSup_liminf
theorem snorm_exponent_top_lim_le_liminf_snorm_exponent_top {ι} [Nonempty ι] [Countable ι]
[LinearOrder ι] {f : ι → α → F} {f_lim : α → F}
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm f_lim ∞ μ ≤ atTop.liminf fun n => snorm (f n) ∞ μ := by
rw [snorm_exponent_top_lim_eq_essSup_liminf h_lim]
simp_rw [snorm_exponent_top, snormEssSup]
exact ENNReal.essSup_liminf_le fun n => fun x => (‖f n x‖₊ : ℝ≥0∞)
#align measure_theory.Lp.snorm_exponent_top_lim_le_liminf_snorm_exponent_top MeasureTheory.Lp.snorm_exponent_top_lim_le_liminf_snorm_exponent_top
theorem snorm_lim_le_liminf_snorm {E} [NormedAddCommGroup E] {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) (f_lim : α → E)
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm f_lim p μ ≤ atTop.liminf fun n => snorm (f n) p μ := by
obtain rfl|hp0 := eq_or_ne p 0
· simp
by_cases hp_top : p = ∞
· simp_rw [hp_top]
exact snorm_exponent_top_lim_le_liminf_snorm_exponent_top h_lim
simp_rw [snorm_eq_snorm' hp0 hp_top]
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0 hp_top
exact snorm'_lim_le_liminf_snorm' hp_pos hf h_lim
#align measure_theory.Lp.snorm_lim_le_liminf_snorm MeasureTheory.Lp.snorm_lim_le_liminf_snorm
/-! ### `Lp` is complete iff Cauchy sequences of `ℒp` have limits in `ℒp` -/
theorem tendsto_Lp_iff_tendsto_ℒp' {ι} {fi : Filter ι} [Fact (1 ≤ p)] (f : ι → Lp E p μ)
(f_lim : Lp E p μ) :
fi.Tendsto f (𝓝 f_lim) ↔ fi.Tendsto (fun n => snorm (⇑(f n) - ⇑f_lim) p μ) (𝓝 0) := by
rw [tendsto_iff_dist_tendsto_zero]
simp_rw [dist_def]
rw [← ENNReal.zero_toReal, ENNReal.tendsto_toReal_iff (fun n => ?_) ENNReal.zero_ne_top]
rw [snorm_congr_ae (Lp.coeFn_sub _ _).symm]
exact Lp.snorm_ne_top _
#align measure_theory.Lp.tendsto_Lp_iff_tendsto_ℒp' MeasureTheory.Lp.tendsto_Lp_iff_tendsto_ℒp'
theorem tendsto_Lp_iff_tendsto_ℒp {ι} {fi : Filter ι} [Fact (1 ≤ p)] (f : ι → Lp E p μ)
(f_lim : α → E) (f_lim_ℒp : Memℒp f_lim p μ) :
fi.Tendsto f (𝓝 (f_lim_ℒp.toLp f_lim)) ↔
fi.Tendsto (fun n => snorm (⇑(f n) - f_lim) p μ) (𝓝 0) := by
rw [tendsto_Lp_iff_tendsto_ℒp']
suffices h_eq :
(fun n => snorm (⇑(f n) - ⇑(Memℒp.toLp f_lim f_lim_ℒp)) p μ) =
(fun n => snorm (⇑(f n) - f_lim) p μ) by
rw [h_eq]
exact funext fun n => snorm_congr_ae (EventuallyEq.rfl.sub (Memℒp.coeFn_toLp f_lim_ℒp))
#align measure_theory.Lp.tendsto_Lp_iff_tendsto_ℒp MeasureTheory.Lp.tendsto_Lp_iff_tendsto_ℒp
theorem tendsto_Lp_iff_tendsto_ℒp'' {ι} {fi : Filter ι} [Fact (1 ≤ p)] (f : ι → α → E)
(f_ℒp : ∀ n, Memℒp (f n) p μ) (f_lim : α → E) (f_lim_ℒp : Memℒp f_lim p μ) :
fi.Tendsto (fun n => (f_ℒp n).toLp (f n)) (𝓝 (f_lim_ℒp.toLp f_lim)) ↔
fi.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0) := by
rw [Lp.tendsto_Lp_iff_tendsto_ℒp' (fun n => (f_ℒp n).toLp (f n)) (f_lim_ℒp.toLp f_lim)]
refine Filter.tendsto_congr fun n => ?_
apply snorm_congr_ae
filter_upwards [((f_ℒp n).sub f_lim_ℒp).coeFn_toLp,
Lp.coeFn_sub ((f_ℒp n).toLp (f n)) (f_lim_ℒp.toLp f_lim)] with _ hx₁ hx₂
rw [← hx₂]
exact hx₁
#align measure_theory.Lp.tendsto_Lp_iff_tendsto_ℒp'' MeasureTheory.Lp.tendsto_Lp_iff_tendsto_ℒp''
theorem tendsto_Lp_of_tendsto_ℒp {ι} {fi : Filter ι} [Fact (1 ≤ p)] {f : ι → Lp E p μ}
(f_lim : α → E) (f_lim_ℒp : Memℒp f_lim p μ)
(h_tendsto : fi.Tendsto (fun n => snorm (⇑(f n) - f_lim) p μ) (𝓝 0)) :
fi.Tendsto f (𝓝 (f_lim_ℒp.toLp f_lim)) :=
(tendsto_Lp_iff_tendsto_ℒp f f_lim f_lim_ℒp).mpr h_tendsto
#align measure_theory.Lp.tendsto_Lp_of_tendsto_ℒp MeasureTheory.Lp.tendsto_Lp_of_tendsto_ℒp
theorem cauchySeq_Lp_iff_cauchySeq_ℒp {ι} [Nonempty ι] [SemilatticeSup ι] [hp : Fact (1 ≤ p)]
(f : ι → Lp E p μ) :
CauchySeq f ↔ Tendsto (fun n : ι × ι => snorm (⇑(f n.fst) - ⇑(f n.snd)) p μ) atTop (𝓝 0) := by
simp_rw [cauchySeq_iff_tendsto_dist_atTop_0, dist_def]
rw [← ENNReal.zero_toReal, ENNReal.tendsto_toReal_iff (fun n => ?_) ENNReal.zero_ne_top]
rw [snorm_congr_ae (Lp.coeFn_sub _ _).symm]
exact snorm_ne_top _
#align measure_theory.Lp.cauchy_seq_Lp_iff_cauchy_seq_ℒp MeasureTheory.Lp.cauchySeq_Lp_iff_cauchySeq_ℒp
theorem completeSpace_lp_of_cauchy_complete_ℒp [hp : Fact (1 ≤ p)]
(H :
∀ (f : ℕ → α → E) (hf : ∀ n, Memℒp (f n) p μ) (B : ℕ → ℝ≥0∞) (hB : ∑' i, B i < ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N),
∃ (f_lim : α → E), Memℒp f_lim p μ ∧
atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0)) :
CompleteSpace (Lp E p μ) := by
let B := fun n : ℕ => ((1 : ℝ) / 2) ^ n
have hB_pos : ∀ n, 0 < B n := fun n => pow_pos (div_pos zero_lt_one zero_lt_two) n
refine Metric.complete_of_convergent_controlled_sequences B hB_pos fun f hf => ?_
rsuffices ⟨f_lim, hf_lim_meas, h_tendsto⟩ :
∃ (f_lim : α → E), Memℒp f_lim p μ ∧
atTop.Tendsto (fun n => snorm (⇑(f n) - f_lim) p μ) (𝓝 0)
· exact ⟨hf_lim_meas.toLp f_lim, tendsto_Lp_of_tendsto_ℒp f_lim hf_lim_meas h_tendsto⟩
obtain ⟨M, hB⟩ : Summable B := summable_geometric_two
let B1 n := ENNReal.ofReal (B n)
have hB1_has : HasSum B1 (ENNReal.ofReal M) := by
have h_tsum_B1 : ∑' i, B1 i = ENNReal.ofReal M := by
change (∑' n : ℕ, ENNReal.ofReal (B n)) = ENNReal.ofReal M
rw [← hB.tsum_eq]
exact (ENNReal.ofReal_tsum_of_nonneg (fun n => le_of_lt (hB_pos n)) hB.summable).symm
have h_sum := (@ENNReal.summable _ B1).hasSum
rwa [h_tsum_B1] at h_sum
have hB1 : ∑' i, B1 i < ∞ := by
rw [hB1_has.tsum_eq]
exact ENNReal.ofReal_lt_top
let f1 : ℕ → α → E := fun n => f n
refine H f1 (fun n => Lp.memℒp (f n)) B1 hB1 fun N n m hn hm => ?_
specialize hf N n m hn hm
rw [dist_def] at hf
dsimp only [f1]
rwa [ENNReal.lt_ofReal_iff_toReal_lt]
rw [snorm_congr_ae (Lp.coeFn_sub _ _).symm]
exact Lp.snorm_ne_top _
#align measure_theory.Lp.complete_space_Lp_of_cauchy_complete_ℒp MeasureTheory.Lp.completeSpace_lp_of_cauchy_complete_ℒp
/-! ### Prove that controlled Cauchy sequences of `ℒp` have limits in `ℒp` -/
private theorem snorm'_sum_norm_sub_le_tsum_of_cauchy_snorm' {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) {p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞}
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm' (f n - f m) p μ < B N) (n : ℕ) :
snorm' (fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) p μ ≤ ∑' i, B i := by
let f_norm_diff i x := ‖f (i + 1) x - f i x‖
have hgf_norm_diff :
∀ n,
(fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) =
∑ i ∈ Finset.range (n + 1), f_norm_diff i :=
fun n => funext fun x => by simp
rw [hgf_norm_diff]
refine (snorm'_sum_le (fun i _ => ((hf (i + 1)).sub (hf i)).norm) hp1).trans ?_
simp_rw [snorm'_norm]
refine (Finset.sum_le_sum ?_).trans (sum_le_tsum _ (fun m _ => zero_le _) ENNReal.summable)
exact fun m _ => (h_cau m (m + 1) m (Nat.le_succ m) (le_refl m)).le
private theorem lintegral_rpow_sum_coe_nnnorm_sub_le_rpow_tsum
{f : ℕ → α → E} {p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞} (n : ℕ)
(hn : snorm' (fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) p μ ≤ ∑' i, B i) :
(∫⁻ a, (∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤
(∑' i, B i) ^ p := by
have hp_pos : 0 < p := zero_lt_one.trans_le hp1
rw [← one_div_one_div p, @ENNReal.le_rpow_one_div_iff _ _ (1 / p) (by simp [hp_pos]),
one_div_one_div p]
simp_rw [snorm'] at hn
have h_nnnorm_nonneg :
(fun a => (‖∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖‖₊ : ℝ≥0∞) ^ p) = fun a =>
(∑ i ∈ Finset.range (n + 1), (‖f (i + 1) a - f i a‖₊ : ℝ≥0∞)) ^ p := by
ext1 a
congr
simp_rw [← ofReal_norm_eq_coe_nnnorm]
rw [← ENNReal.ofReal_sum_of_nonneg]
· rw [Real.norm_of_nonneg _]
exact Finset.sum_nonneg fun x _ => norm_nonneg _
· exact fun x _ => norm_nonneg _
change
(∫⁻ a, (fun x => ↑‖∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖‖₊ ^ p) a ∂μ) ^ (1 / p) ≤
∑' i, B i at hn
rwa [h_nnnorm_nonneg] at hn
private theorem lintegral_rpow_tsum_coe_nnnorm_sub_le_tsum {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) {p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞}
(h :
∀ n,
(∫⁻ a, (∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤
(∑' i, B i) ^ p) :
(∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) ≤ ∑' i, B i := by
have hp_pos : 0 < p := zero_lt_one.trans_le hp1
suffices h_pow : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤ (∑' i, B i) ^ p by
rwa [← ENNReal.le_rpow_one_div_iff (by simp [hp_pos] : 0 < 1 / p), one_div_one_div]
have h_tsum_1 :
∀ g : ℕ → ℝ≥0∞, ∑' i, g i = atTop.liminf fun n => ∑ i ∈ Finset.range (n + 1), g i := by
intro g
rw [ENNReal.tsum_eq_liminf_sum_nat, ← liminf_nat_add _ 1]
simp_rw [h_tsum_1 _]
rw [← h_tsum_1]
have h_liminf_pow :
(∫⁻ a, (atTop.liminf
fun n => ∑ i ∈ Finset.range (n + 1), (‖f (i + 1) a - f i a‖₊ : ℝ≥0∞)) ^ p ∂μ) =
∫⁻ a, atTop.liminf
fun n => (∑ i ∈ Finset.range (n + 1), (‖f (i + 1) a - f i a‖₊ : ℝ≥0∞)) ^ p ∂μ := by
refine lintegral_congr fun x => ?_
have h_rpow_mono := ENNReal.strictMono_rpow_of_pos (zero_lt_one.trans_le hp1)
have h_rpow_surj := (ENNReal.rpow_left_bijective hp_pos.ne.symm).2
refine (h_rpow_mono.orderIsoOfSurjective _ h_rpow_surj).liminf_apply ?_ ?_ ?_ ?_
all_goals isBoundedDefault
rw [h_liminf_pow]
refine (lintegral_liminf_le' ?_).trans ?_
· exact fun n =>
(Finset.aemeasurable_sum (Finset.range (n + 1)) fun i _ =>
((hf (i + 1)).sub (hf i)).ennnorm).pow_const
_
· exact liminf_le_of_frequently_le' (frequently_of_forall h)
private theorem tsum_nnnorm_sub_ae_lt_top {f : ℕ → α → E} (hf : ∀ n, AEStronglyMeasurable (f n) μ)
{p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) ≤ ∑' i, B i) :
∀ᵐ x ∂μ, (∑' i, ‖f (i + 1) x - f i x‖₊ : ℝ≥0∞) < ∞ := by
have hp_pos : 0 < p := zero_lt_one.trans_le hp1
have h_integral : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) < ∞ := by
have h_tsum_lt_top : (∑' i, B i) ^ p < ∞ := ENNReal.rpow_lt_top_of_nonneg hp_pos.le hB
refine lt_of_le_of_lt ?_ h_tsum_lt_top
rwa [← ENNReal.le_rpow_one_div_iff (by simp [hp_pos] : 0 < 1 / p), one_div_one_div] at h
have rpow_ae_lt_top : ∀ᵐ x ∂μ, (∑' i, ‖f (i + 1) x - f i x‖₊ : ℝ≥0∞) ^ p < ∞ := by
refine ae_lt_top' (AEMeasurable.pow_const ?_ _) h_integral.ne
exact AEMeasurable.ennreal_tsum fun n => ((hf (n + 1)).sub (hf n)).ennnorm
refine rpow_ae_lt_top.mono fun x hx => ?_
rwa [← ENNReal.lt_rpow_one_div_iff hp_pos,
ENNReal.top_rpow_of_pos (by simp [hp_pos] : 0 < 1 / p)] at hx
theorem ae_tendsto_of_cauchy_snorm' [CompleteSpace E] {f : ℕ → α → E} {p : ℝ}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm' (f n - f m) p μ < B N) :
∀ᵐ x ∂μ, ∃ l : E, atTop.Tendsto (fun n => f n x) (𝓝 l) := by
have h_summable : ∀ᵐ x ∂μ, Summable fun i : ℕ => f (i + 1) x - f i x := by
have h1 :
∀ n, snorm' (fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) p μ ≤ ∑' i, B i :=
snorm'_sum_norm_sub_le_tsum_of_cauchy_snorm' hf hp1 h_cau
have h2 :
∀ n,
(∫⁻ a, (∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤
(∑' i, B i) ^ p :=
fun n => lintegral_rpow_sum_coe_nnnorm_sub_le_rpow_tsum hp1 n (h1 n)
have h3 : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) ≤ ∑' i, B i :=
lintegral_rpow_tsum_coe_nnnorm_sub_le_tsum hf hp1 h2
have h4 : ∀ᵐ x ∂μ, (∑' i, ‖f (i + 1) x - f i x‖₊ : ℝ≥0∞) < ∞ :=
tsum_nnnorm_sub_ae_lt_top hf hp1 hB h3
exact h4.mono fun x hx => .of_nnnorm <| ENNReal.tsum_coe_ne_top_iff_summable.mp hx.ne
have h :
∀ᵐ x ∂μ, ∃ l : E,
atTop.Tendsto (fun n => ∑ i ∈ Finset.range n, (f (i + 1) x - f i x)) (𝓝 l) := by
refine h_summable.mono fun x hx => ?_
let hx_sum := hx.hasSum.tendsto_sum_nat
exact ⟨∑' i, (f (i + 1) x - f i x), hx_sum⟩
refine h.mono fun x hx => ?_
cases' hx with l hx
have h_rw_sum :
(fun n => ∑ i ∈ Finset.range n, (f (i + 1) x - f i x)) = fun n => f n x - f 0 x := by
ext1 n
change
(∑ i ∈ Finset.range n, ((fun m => f m x) (i + 1) - (fun m => f m x) i)) = f n x - f 0 x
rw [Finset.sum_range_sub (fun m => f m x)]
rw [h_rw_sum] at hx
have hf_rw : (fun n => f n x) = fun n => f n x - f 0 x + f 0 x := by
ext1 n
abel
rw [hf_rw]
exact ⟨l + f 0 x, Tendsto.add_const _ hx⟩
#align measure_theory.Lp.ae_tendsto_of_cauchy_snorm' MeasureTheory.Lp.ae_tendsto_of_cauchy_snorm'
theorem ae_tendsto_of_cauchy_snorm [CompleteSpace E] {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) (hp : 1 ≤ p) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N) :
∀ᵐ x ∂μ, ∃ l : E, atTop.Tendsto (fun n => f n x) (𝓝 l) := by
by_cases hp_top : p = ∞
· simp_rw [hp_top] at *
have h_cau_ae : ∀ᵐ x ∂μ, ∀ N n m, N ≤ n → N ≤ m → (‖(f n - f m) x‖₊ : ℝ≥0∞) < B N := by
simp_rw [ae_all_iff]
exact fun N n m hnN hmN => ae_lt_of_essSup_lt (h_cau N n m hnN hmN)
simp_rw [snorm_exponent_top, snormEssSup] at h_cau
refine h_cau_ae.mono fun x hx => cauchySeq_tendsto_of_complete ?_
refine cauchySeq_of_le_tendsto_0 (fun n => (B n).toReal) ?_ ?_
· intro n m N hnN hmN
specialize hx N n m hnN hmN
rw [_root_.dist_eq_norm, ← ENNReal.toReal_ofReal (norm_nonneg _),
ENNReal.toReal_le_toReal ENNReal.ofReal_ne_top (ENNReal.ne_top_of_tsum_ne_top hB N)]
rw [← ofReal_norm_eq_coe_nnnorm] at hx
exact hx.le
· rw [← ENNReal.zero_toReal]
exact
Tendsto.comp (g := ENNReal.toReal) (ENNReal.tendsto_toReal ENNReal.zero_ne_top)
(ENNReal.tendsto_atTop_zero_of_tsum_ne_top hB)
have hp1 : 1 ≤ p.toReal := by
rw [← ENNReal.ofReal_le_iff_le_toReal hp_top, ENNReal.ofReal_one]
exact hp
have h_cau' : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm' (f n - f m) p.toReal μ < B N := by
intro N n m hn hm
specialize h_cau N n m hn hm
rwa [snorm_eq_snorm' (zero_lt_one.trans_le hp).ne.symm hp_top] at h_cau
exact ae_tendsto_of_cauchy_snorm' hf hp1 hB h_cau'
#align measure_theory.Lp.ae_tendsto_of_cauchy_snorm MeasureTheory.Lp.ae_tendsto_of_cauchy_snorm
theorem cauchy_tendsto_of_tendsto {f : ℕ → α → E} (hf : ∀ n, AEStronglyMeasurable (f n) μ)
(f_lim : α → E) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N)
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0) := by
rw [ENNReal.tendsto_atTop_zero]
intro ε hε
have h_B : ∃ N : ℕ, B N ≤ ε := by
suffices h_tendsto_zero : ∃ N : ℕ, ∀ n : ℕ, N ≤ n → B n ≤ ε from
⟨h_tendsto_zero.choose, h_tendsto_zero.choose_spec _ le_rfl⟩
exact (ENNReal.tendsto_atTop_zero.mp (ENNReal.tendsto_atTop_zero_of_tsum_ne_top hB)) ε hε
cases' h_B with N h_B
refine ⟨N, fun n hn => ?_⟩
have h_sub : snorm (f n - f_lim) p μ ≤ atTop.liminf fun m => snorm (f n - f m) p μ := by
refine snorm_lim_le_liminf_snorm (fun m => (hf n).sub (hf m)) (f n - f_lim) ?_
refine h_lim.mono fun x hx => ?_
simp_rw [sub_eq_add_neg]
exact Tendsto.add tendsto_const_nhds (Tendsto.neg hx)
refine h_sub.trans ?_
refine liminf_le_of_frequently_le' (frequently_atTop.mpr ?_)
refine fun N1 => ⟨max N N1, le_max_right _ _, ?_⟩
exact (h_cau N n (max N N1) hn (le_max_left _ _)).le.trans h_B
#align measure_theory.Lp.cauchy_tendsto_of_tendsto MeasureTheory.Lp.cauchy_tendsto_of_tendsto
theorem memℒp_of_cauchy_tendsto (hp : 1 ≤ p) {f : ℕ → α → E} (hf : ∀ n, Memℒp (f n) p μ)
(f_lim : α → E) (h_lim_meas : AEStronglyMeasurable f_lim μ)
(h_tendsto : atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0)) : Memℒp f_lim p μ := by
refine ⟨h_lim_meas, ?_⟩
rw [ENNReal.tendsto_atTop_zero] at h_tendsto
cases' h_tendsto 1 zero_lt_one with N h_tendsto_1
specialize h_tendsto_1 N (le_refl N)
have h_add : f_lim = f_lim - f N + f N := by abel
rw [h_add]
refine lt_of_le_of_lt (snorm_add_le (h_lim_meas.sub (hf N).1) (hf N).1 hp) ?_
rw [ENNReal.add_lt_top]
constructor
· refine lt_of_le_of_lt ?_ ENNReal.one_lt_top
have h_neg : f_lim - f N = -(f N - f_lim) := by simp
rwa [h_neg, snorm_neg]
· exact (hf N).2
#align measure_theory.Lp.mem_ℒp_of_cauchy_tendsto MeasureTheory.Lp.memℒp_of_cauchy_tendsto
theorem cauchy_complete_ℒp [CompleteSpace E] (hp : 1 ≤ p) {f : ℕ → α → E}
(hf : ∀ n, Memℒp (f n) p μ) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N) :
∃ (f_lim : α → E), Memℒp f_lim p μ ∧
atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0) := by
obtain ⟨f_lim, h_f_lim_meas, h_lim⟩ :
∃ f_lim : α → E, StronglyMeasurable f_lim ∧
∀ᵐ x ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x)) :=
exists_stronglyMeasurable_limit_of_tendsto_ae (fun n => (hf n).1)
(ae_tendsto_of_cauchy_snorm (fun n => (hf n).1) hp hB h_cau)
have h_tendsto' : atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0) :=
cauchy_tendsto_of_tendsto (fun m => (hf m).1) f_lim hB h_cau h_lim
have h_ℒp_lim : Memℒp f_lim p μ :=
memℒp_of_cauchy_tendsto hp hf f_lim h_f_lim_meas.aestronglyMeasurable h_tendsto'
exact ⟨f_lim, h_ℒp_lim, h_tendsto'⟩
#align measure_theory.Lp.cauchy_complete_ℒp MeasureTheory.Lp.cauchy_complete_ℒp
/-! ### `Lp` is complete for `1 ≤ p` -/
instance instCompleteSpace [CompleteSpace E] [hp : Fact (1 ≤ p)] : CompleteSpace (Lp E p μ) :=
completeSpace_lp_of_cauchy_complete_ℒp fun _f hf _B hB h_cau =>
cauchy_complete_ℒp hp.elim hf hB.ne h_cau
#align measure_theory.Lp.complete_space MeasureTheory.Lp.instCompleteSpace
end Lp
end MeasureTheory
end CompleteSpace
/-! ### Continuous functions in `Lp` -/
open scoped BoundedContinuousFunction
open BoundedContinuousFunction
section
variable [TopologicalSpace α] [BorelSpace α] [SecondCountableTopologyEither α E]
variable (E p μ)
/-- An additive subgroup of `Lp E p μ`, consisting of the equivalence classes which contain a
bounded continuous representative. -/
def MeasureTheory.Lp.boundedContinuousFunction : AddSubgroup (Lp E p μ) :=
AddSubgroup.addSubgroupOf
((ContinuousMap.toAEEqFunAddHom μ).comp (toContinuousMapAddHom α E)).range (Lp E p μ)
#align measure_theory.Lp.bounded_continuous_function MeasureTheory.Lp.boundedContinuousFunction
variable {E p μ}
/-- By definition, the elements of `Lp.boundedContinuousFunction E p μ` are the elements of
`Lp E p μ` which contain a bounded continuous representative. -/
theorem MeasureTheory.Lp.mem_boundedContinuousFunction_iff {f : Lp E p μ} :
f ∈ MeasureTheory.Lp.boundedContinuousFunction E p μ ↔
∃ f₀ : α →ᵇ E, f₀.toContinuousMap.toAEEqFun μ = (f : α →ₘ[μ] E) :=
AddSubgroup.mem_addSubgroupOf
#align measure_theory.Lp.mem_bounded_continuous_function_iff MeasureTheory.Lp.mem_boundedContinuousFunction_iff
namespace BoundedContinuousFunction
variable [IsFiniteMeasure μ]
/-- A bounded continuous function on a finite-measure space is in `Lp`. -/
theorem mem_Lp (f : α →ᵇ E) : f.toContinuousMap.toAEEqFun μ ∈ Lp E p μ := by
refine Lp.mem_Lp_of_ae_bound ‖f‖ ?_
filter_upwards [f.toContinuousMap.coeFn_toAEEqFun μ] with x _
convert f.norm_coe_le_norm x using 2
#align bounded_continuous_function.mem_Lp BoundedContinuousFunction.mem_Lp
/-- The `Lp`-norm of a bounded continuous function is at most a constant (depending on the measure
of the whole space) times its sup-norm. -/
theorem Lp_nnnorm_le (f : α →ᵇ E) :
‖(⟨f.toContinuousMap.toAEEqFun μ, mem_Lp f⟩ : Lp E p μ)‖₊ ≤
measureUnivNNReal μ ^ p.toReal⁻¹ * ‖f‖₊ := by
apply Lp.nnnorm_le_of_ae_bound
refine (f.toContinuousMap.coeFn_toAEEqFun μ).mono ?_
intro x hx
rw [← NNReal.coe_le_coe, coe_nnnorm, coe_nnnorm]
convert f.norm_coe_le_norm x using 2
#align bounded_continuous_function.Lp_nnnorm_le BoundedContinuousFunction.Lp_nnnorm_le
/-- The `Lp`-norm of a bounded continuous function is at most a constant (depending on the measure
of the whole space) times its sup-norm. -/
theorem Lp_norm_le (f : α →ᵇ E) :
‖(⟨f.toContinuousMap.toAEEqFun μ, mem_Lp f⟩ : Lp E p μ)‖ ≤
measureUnivNNReal μ ^ p.toReal⁻¹ * ‖f‖ :=
Lp_nnnorm_le f
#align bounded_continuous_function.Lp_norm_le BoundedContinuousFunction.Lp_norm_le
variable (p μ)
/-- The normed group homomorphism of considering a bounded continuous function on a finite-measure
space as an element of `Lp`. -/
def toLpHom [Fact (1 ≤ p)] : NormedAddGroupHom (α →ᵇ E) (Lp E p μ) :=
{ AddMonoidHom.codRestrict ((ContinuousMap.toAEEqFunAddHom μ).comp (toContinuousMapAddHom α E))
(Lp E p μ) mem_Lp with
bound' := ⟨_, Lp_norm_le⟩ }
#align bounded_continuous_function.to_Lp_hom BoundedContinuousFunction.toLpHom
theorem range_toLpHom [Fact (1 ≤ p)] :
((toLpHom p μ).range : AddSubgroup (Lp E p μ)) =
MeasureTheory.Lp.boundedContinuousFunction E p μ := by
symm
convert AddMonoidHom.addSubgroupOf_range_eq_of_le
((ContinuousMap.toAEEqFunAddHom μ).comp (toContinuousMapAddHom α E))
(by rintro - ⟨f, rfl⟩; exact mem_Lp f : _ ≤ Lp E p μ)
#align bounded_continuous_function.range_to_Lp_hom BoundedContinuousFunction.range_toLpHom
variable (𝕜 : Type*) [Fact (1 ≤ p)]
/-- The bounded linear map of considering a bounded continuous function on a finite-measure space
as an element of `Lp`. -/
def toLp [NormedField 𝕜] [NormedSpace 𝕜 E] : (α →ᵇ E) →L[𝕜] Lp E p μ :=
LinearMap.mkContinuous
(LinearMap.codRestrict (Lp.LpSubmodule E p μ 𝕜)
((ContinuousMap.toAEEqFunLinearMap μ).comp (toContinuousMapLinearMap α E 𝕜)) mem_Lp)
_ Lp_norm_le
#align bounded_continuous_function.to_Lp BoundedContinuousFunction.toLp
theorem coeFn_toLp [NormedField 𝕜] [NormedSpace 𝕜 E] (f : α →ᵇ E) :
toLp (E := E) p μ 𝕜 f =ᵐ[μ] f :=
AEEqFun.coeFn_mk f _
#align bounded_continuous_function.coe_fn_to_Lp BoundedContinuousFunction.coeFn_toLp
variable {𝕜}
theorem range_toLp [NormedField 𝕜] [NormedSpace 𝕜 E] :
(LinearMap.range (toLp p μ 𝕜 : (α →ᵇ E) →L[𝕜] Lp E p μ)).toAddSubgroup =
MeasureTheory.Lp.boundedContinuousFunction E p μ :=
range_toLpHom p μ
#align bounded_continuous_function.range_to_Lp BoundedContinuousFunction.range_toLp
variable {p}
theorem toLp_norm_le [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] :
‖(toLp p μ 𝕜 : (α →ᵇ E) →L[𝕜] Lp E p μ)‖ ≤ measureUnivNNReal μ ^ p.toReal⁻¹ :=
LinearMap.mkContinuous_norm_le _ (measureUnivNNReal μ ^ p.toReal⁻¹).coe_nonneg _
#align bounded_continuous_function.to_Lp_norm_le BoundedContinuousFunction.toLp_norm_le
theorem toLp_inj {f g : α →ᵇ E} [μ.IsOpenPosMeasure] [NormedField 𝕜] [NormedSpace 𝕜 E] :
toLp (E := E) p μ 𝕜 f = toLp (E := E) p μ 𝕜 g ↔ f = g := by
refine ⟨fun h => ?_, by tauto⟩
rw [← DFunLike.coe_fn_eq, ← (map_continuous f).ae_eq_iff_eq μ (map_continuous g)]
refine (coeFn_toLp p μ 𝕜 f).symm.trans (EventuallyEq.trans ?_ <| coeFn_toLp p μ 𝕜 g)
rw [h]
#align bounded_continuous_function.to_Lp_inj BoundedContinuousFunction.toLp_inj
theorem toLp_injective [μ.IsOpenPosMeasure] [NormedField 𝕜] [NormedSpace 𝕜 E] :
Function.Injective (⇑(toLp p μ 𝕜 : (α →ᵇ E) →L[𝕜] Lp E p μ)) :=
fun _f _g hfg => (toLp_inj μ).mp hfg
#align bounded_continuous_function.to_Lp_injective BoundedContinuousFunction.toLp_injective
end BoundedContinuousFunction
namespace ContinuousMap
variable [CompactSpace α] [IsFiniteMeasure μ]
variable (𝕜 : Type*) (p μ) [Fact (1 ≤ p)]
/-- The bounded linear map of considering a continuous function on a compact finite-measure
space `α` as an element of `Lp`. By definition, the norm on `C(α, E)` is the sup-norm, transferred
from the space `α →ᵇ E` of bounded continuous functions, so this construction is just a matter of
transferring the structure from `BoundedContinuousFunction.toLp` along the isometry. -/
def toLp [NormedField 𝕜] [NormedSpace 𝕜 E] : C(α, E) →L[𝕜] Lp E p μ :=
(BoundedContinuousFunction.toLp p μ 𝕜).comp
(linearIsometryBoundedOfCompact α E 𝕜).toLinearIsometry.toContinuousLinearMap
#align continuous_map.to_Lp ContinuousMap.toLp
variable {𝕜}
theorem range_toLp [NormedField 𝕜] [NormedSpace 𝕜 E] :
(LinearMap.range (toLp p μ 𝕜 : C(α, E) →L[𝕜] Lp E p μ)).toAddSubgroup =
MeasureTheory.Lp.boundedContinuousFunction E p μ := by
refine SetLike.ext' ?_
have := (linearIsometryBoundedOfCompact α E 𝕜).surjective
convert Function.Surjective.range_comp this (BoundedContinuousFunction.toLp (E := E) p μ 𝕜)
rw [← BoundedContinuousFunction.range_toLp p μ (𝕜 := 𝕜), Submodule.coe_toAddSubgroup,
LinearMap.range_coe]
#align continuous_map.range_to_Lp ContinuousMap.range_toLp
variable {p}
theorem coeFn_toLp [NormedField 𝕜] [NormedSpace 𝕜 E] (f : C(α, E)) :
toLp (E := E) p μ 𝕜 f =ᵐ[μ] f :=
AEEqFun.coeFn_mk f _
#align continuous_map.coe_fn_to_Lp ContinuousMap.coeFn_toLp
theorem toLp_def [NormedField 𝕜] [NormedSpace 𝕜 E] (f : C(α, E)) :
toLp (E := E) p μ 𝕜 f =
BoundedContinuousFunction.toLp (E := E) p μ 𝕜 (linearIsometryBoundedOfCompact α E 𝕜 f) :=
rfl
#align continuous_map.to_Lp_def ContinuousMap.toLp_def
@[simp]
theorem toLp_comp_toContinuousMap [NormedField 𝕜] [NormedSpace 𝕜 E] (f : α →ᵇ E) :
toLp (E := E) p μ 𝕜 f.toContinuousMap = BoundedContinuousFunction.toLp (E := E) p μ 𝕜 f :=
rfl
#align continuous_map.to_Lp_comp_to_continuous_map ContinuousMap.toLp_comp_toContinuousMap
@[simp]
theorem coe_toLp [NormedField 𝕜] [NormedSpace 𝕜 E] (f : C(α, E)) :
(toLp (E := E) p μ 𝕜 f : α →ₘ[μ] E) = f.toAEEqFun μ :=
rfl
#align continuous_map.coe_to_Lp ContinuousMap.coe_toLp
theorem toLp_injective [μ.IsOpenPosMeasure] [NormedField 𝕜] [NormedSpace 𝕜 E] :
Function.Injective (⇑(toLp p μ 𝕜 : C(α, E) →L[𝕜] Lp E p μ)) :=
(BoundedContinuousFunction.toLp_injective _).comp (linearIsometryBoundedOfCompact α E 𝕜).injective
#align continuous_map.to_Lp_injective ContinuousMap.toLp_injective
theorem toLp_inj {f g : C(α, E)} [μ.IsOpenPosMeasure] [NormedField 𝕜] [NormedSpace 𝕜 E] :
toLp (E := E) p μ 𝕜 f = toLp (E := E) p μ 𝕜 g ↔ f = g :=
(toLp_injective μ).eq_iff
#align continuous_map.to_Lp_inj ContinuousMap.toLp_inj
variable {μ}
/-- If a sum of continuous functions `g n` is convergent, and the same sum converges in `Lᵖ` to `h`,
then in fact `g n` converges uniformly to `h`. -/
| Mathlib/MeasureTheory/Function/LpSpace.lean | 1,920 | 1,924 | theorem hasSum_of_hasSum_Lp {β : Type*} [μ.IsOpenPosMeasure] [NormedField 𝕜] [NormedSpace 𝕜 E]
{g : β → C(α, E)} {f : C(α, E)} (hg : Summable g)
(hg2 : HasSum (toLp (E := E) p μ 𝕜 ∘ g) (toLp (E := E) p μ 𝕜 f)) : HasSum g f := by |
convert Summable.hasSum hg
exact toLp_injective μ (hg2.unique ((toLp p μ 𝕜).hasSum <| Summable.hasSum hg))
|
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Violeta Hernández Palacios
-/
import Mathlib.MeasureTheory.MeasurableSpace.Defs
import Mathlib.SetTheory.Cardinal.Cofinality
import Mathlib.SetTheory.Cardinal.Continuum
#align_import measure_theory.card_measurable_space from "leanprover-community/mathlib"@"f2b108e8e97ba393f22bf794989984ddcc1da89b"
/-!
# Cardinal of sigma-algebras
If a sigma-algebra is generated by a set of sets `s`, then the cardinality of the sigma-algebra is
bounded by `(max #s 2) ^ ℵ₀`. This is stated in `MeasurableSpace.cardinal_generate_measurable_le`
and `MeasurableSpace.cardinalMeasurableSet_le`.
In particular, if `#s ≤ 𝔠`, then the generated sigma-algebra has cardinality at most `𝔠`, see
`MeasurableSpace.cardinal_measurableSet_le_continuum`.
For the proof, we rely on an explicit inductive construction of the sigma-algebra generated by
`s` (instead of the inductive predicate `GenerateMeasurable`). This transfinite inductive
construction is parameterized by an ordinal `< ω₁`, and the cardinality bound is preserved along
each step of the construction. We show in `MeasurableSpace.generateMeasurable_eq_rec` that this
indeed generates this sigma-algebra.
-/
universe u
variable {α : Type u}
open Cardinal Set
-- Porting note: fix universe below, not here
local notation "ω₁" => (WellOrder.α <| Quotient.out <| Cardinal.ord (aleph 1 : Cardinal))
namespace MeasurableSpace
/-- Transfinite induction construction of the sigma-algebra generated by a set of sets `s`. At each
step, we add all elements of `s`, the empty set, the complements of already constructed sets, and
countable unions of already constructed sets. We index this construction by an ordinal `< ω₁`, as
this will be enough to generate all sets in the sigma-algebra.
This construction is very similar to that of the Borel hierarchy. -/
def generateMeasurableRec (s : Set (Set α)) : (ω₁ : Type u) → Set (Set α)
| i =>
let S := ⋃ j : Iio i, generateMeasurableRec s (j.1)
s ∪ {∅} ∪ compl '' S ∪ Set.range fun f : ℕ → S => ⋃ n, (f n).1
termination_by i => i
decreasing_by exact j.2
#align measurable_space.generate_measurable_rec MeasurableSpace.generateMeasurableRec
theorem self_subset_generateMeasurableRec (s : Set (Set α)) (i : ω₁) :
s ⊆ generateMeasurableRec s i := by
unfold generateMeasurableRec
apply_rules [subset_union_of_subset_left]
exact subset_rfl
#align measurable_space.self_subset_generate_measurable_rec MeasurableSpace.self_subset_generateMeasurableRec
| Mathlib/MeasureTheory/MeasurableSpace/Card.lean | 62 | 65 | theorem empty_mem_generateMeasurableRec (s : Set (Set α)) (i : ω₁) :
∅ ∈ generateMeasurableRec s i := by |
unfold generateMeasurableRec
exact mem_union_left _ (mem_union_left _ (mem_union_right _ (mem_singleton ∅)))
|
/-
Copyright (c) 2019 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Yury Kudryashov
-/
import Mathlib.Analysis.Normed.Group.InfiniteSum
import Mathlib.Analysis.Normed.MulAction
import Mathlib.Topology.Algebra.Order.LiminfLimsup
import Mathlib.Topology.PartialHomeomorph
#align_import analysis.asymptotics.asymptotics from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Asymptotics
We introduce these relations:
* `IsBigOWith c l f g` : "f is big O of g along l with constant c";
* `f =O[l] g` : "f is big O of g along l";
* `f =o[l] g` : "f is little o of g along l".
Here `l` is any filter on the domain of `f` and `g`, which are assumed to be the same. The codomains
of `f` and `g` do not need to be the same; all that is needed that there is a norm associated with
these types, and it is the norm that is compared asymptotically.
The relation `IsBigOWith c` is introduced to factor out common algebraic arguments in the proofs of
similar properties of `IsBigO` and `IsLittleO`. Usually proofs outside of this file should use
`IsBigO` instead.
Often the ranges of `f` and `g` will be the real numbers, in which case the norm is the absolute
value. In general, we have
`f =O[l] g ↔ (fun x ↦ ‖f x‖) =O[l] (fun x ↦ ‖g x‖)`,
and similarly for `IsLittleO`. But our setup allows us to use the notions e.g. with functions
to the integers, rationals, complex numbers, or any normed vector space without mentioning the
norm explicitly.
If `f` and `g` are functions to a normed field like the reals or complex numbers and `g` is always
nonzero, we have
`f =o[l] g ↔ Tendsto (fun x ↦ f x / (g x)) l (𝓝 0)`.
In fact, the right-to-left direction holds without the hypothesis on `g`, and in the other direction
it suffices to assume that `f` is zero wherever `g` is. (This generalization is useful in defining
the Fréchet derivative.)
-/
open Filter Set
open scoped Classical
open Topology Filter NNReal
namespace Asymptotics
set_option linter.uppercaseLean3 false
variable {α : Type*} {β : Type*} {E : Type*} {F : Type*} {G : Type*} {E' : Type*}
{F' : Type*} {G' : Type*} {E'' : Type*} {F'' : Type*} {G'' : Type*} {E''' : Type*}
{R : Type*} {R' : Type*} {𝕜 : Type*} {𝕜' : Type*}
variable [Norm E] [Norm F] [Norm G]
variable [SeminormedAddCommGroup E'] [SeminormedAddCommGroup F'] [SeminormedAddCommGroup G']
[NormedAddCommGroup E''] [NormedAddCommGroup F''] [NormedAddCommGroup G''] [SeminormedRing R]
[SeminormedAddGroup E''']
[SeminormedRing R']
variable [NormedDivisionRing 𝕜] [NormedDivisionRing 𝕜']
variable {c c' c₁ c₂ : ℝ} {f : α → E} {g : α → F} {k : α → G}
variable {f' : α → E'} {g' : α → F'} {k' : α → G'}
variable {f'' : α → E''} {g'' : α → F''} {k'' : α → G''}
variable {l l' : Filter α}
section Defs
/-! ### Definitions -/
/-- This version of the Landau notation `IsBigOWith C l f g` where `f` and `g` are two functions on
a type `α` and `l` is a filter on `α`, means that eventually for `l`, `‖f‖` is bounded by `C * ‖g‖`.
In other words, `‖f‖ / ‖g‖` is eventually bounded by `C`, modulo division by zero issues that are
avoided by this definition. Probably you want to use `IsBigO` instead of this relation. -/
irreducible_def IsBigOWith (c : ℝ) (l : Filter α) (f : α → E) (g : α → F) : Prop :=
∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖
#align asymptotics.is_O_with Asymptotics.IsBigOWith
/-- Definition of `IsBigOWith`. We record it in a lemma as `IsBigOWith` is irreducible. -/
theorem isBigOWith_iff : IsBigOWith c l f g ↔ ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖ := by rw [IsBigOWith_def]
#align asymptotics.is_O_with_iff Asymptotics.isBigOWith_iff
alias ⟨IsBigOWith.bound, IsBigOWith.of_bound⟩ := isBigOWith_iff
#align asymptotics.is_O_with.bound Asymptotics.IsBigOWith.bound
#align asymptotics.is_O_with.of_bound Asymptotics.IsBigOWith.of_bound
/-- The Landau notation `f =O[l] g` where `f` and `g` are two functions on a type `α` and `l` is
a filter on `α`, means that eventually for `l`, `‖f‖` is bounded by a constant multiple of `‖g‖`.
In other words, `‖f‖ / ‖g‖` is eventually bounded, modulo division by zero issues that are avoided
by this definition. -/
irreducible_def IsBigO (l : Filter α) (f : α → E) (g : α → F) : Prop :=
∃ c : ℝ, IsBigOWith c l f g
#align asymptotics.is_O Asymptotics.IsBigO
@[inherit_doc]
notation:100 f " =O[" l "] " g:100 => IsBigO l f g
/-- Definition of `IsBigO` in terms of `IsBigOWith`. We record it in a lemma as `IsBigO` is
irreducible. -/
theorem isBigO_iff_isBigOWith : f =O[l] g ↔ ∃ c : ℝ, IsBigOWith c l f g := by rw [IsBigO_def]
#align asymptotics.is_O_iff_is_O_with Asymptotics.isBigO_iff_isBigOWith
/-- Definition of `IsBigO` in terms of filters. -/
theorem isBigO_iff : f =O[l] g ↔ ∃ c : ℝ, ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖ := by
simp only [IsBigO_def, IsBigOWith_def]
#align asymptotics.is_O_iff Asymptotics.isBigO_iff
/-- Definition of `IsBigO` in terms of filters, with a positive constant. -/
theorem isBigO_iff' {g : α → E'''} :
f =O[l] g ↔ ∃ c > 0, ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖ := by
refine ⟨fun h => ?mp, fun h => ?mpr⟩
case mp =>
rw [isBigO_iff] at h
obtain ⟨c, hc⟩ := h
refine ⟨max c 1, zero_lt_one.trans_le (le_max_right _ _), ?_⟩
filter_upwards [hc] with x hx
apply hx.trans
gcongr
exact le_max_left _ _
case mpr =>
rw [isBigO_iff]
obtain ⟨c, ⟨_, hc⟩⟩ := h
exact ⟨c, hc⟩
/-- Definition of `IsBigO` in terms of filters, with the constant in the lower bound. -/
theorem isBigO_iff'' {g : α → E'''} :
f =O[l] g ↔ ∃ c > 0, ∀ᶠ x in l, c * ‖f x‖ ≤ ‖g x‖ := by
refine ⟨fun h => ?mp, fun h => ?mpr⟩
case mp =>
rw [isBigO_iff'] at h
obtain ⟨c, ⟨hc_pos, hc⟩⟩ := h
refine ⟨c⁻¹, ⟨by positivity, ?_⟩⟩
filter_upwards [hc] with x hx
rwa [inv_mul_le_iff (by positivity)]
case mpr =>
rw [isBigO_iff']
obtain ⟨c, ⟨hc_pos, hc⟩⟩ := h
refine ⟨c⁻¹, ⟨by positivity, ?_⟩⟩
filter_upwards [hc] with x hx
rwa [← inv_inv c, inv_mul_le_iff (by positivity)] at hx
theorem IsBigO.of_bound (c : ℝ) (h : ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖) : f =O[l] g :=
isBigO_iff.2 ⟨c, h⟩
#align asymptotics.is_O.of_bound Asymptotics.IsBigO.of_bound
theorem IsBigO.of_bound' (h : ∀ᶠ x in l, ‖f x‖ ≤ ‖g x‖) : f =O[l] g :=
IsBigO.of_bound 1 <| by
simp_rw [one_mul]
exact h
#align asymptotics.is_O.of_bound' Asymptotics.IsBigO.of_bound'
theorem IsBigO.bound : f =O[l] g → ∃ c : ℝ, ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖ :=
isBigO_iff.1
#align asymptotics.is_O.bound Asymptotics.IsBigO.bound
/-- The Landau notation `f =o[l] g` where `f` and `g` are two functions on a type `α` and `l` is
a filter on `α`, means that eventually for `l`, `‖f‖` is bounded by an arbitrarily small constant
multiple of `‖g‖`. In other words, `‖f‖ / ‖g‖` tends to `0` along `l`, modulo division by zero
issues that are avoided by this definition. -/
irreducible_def IsLittleO (l : Filter α) (f : α → E) (g : α → F) : Prop :=
∀ ⦃c : ℝ⦄, 0 < c → IsBigOWith c l f g
#align asymptotics.is_o Asymptotics.IsLittleO
@[inherit_doc]
notation:100 f " =o[" l "] " g:100 => IsLittleO l f g
/-- Definition of `IsLittleO` in terms of `IsBigOWith`. -/
theorem isLittleO_iff_forall_isBigOWith : f =o[l] g ↔ ∀ ⦃c : ℝ⦄, 0 < c → IsBigOWith c l f g := by
rw [IsLittleO_def]
#align asymptotics.is_o_iff_forall_is_O_with Asymptotics.isLittleO_iff_forall_isBigOWith
alias ⟨IsLittleO.forall_isBigOWith, IsLittleO.of_isBigOWith⟩ := isLittleO_iff_forall_isBigOWith
#align asymptotics.is_o.forall_is_O_with Asymptotics.IsLittleO.forall_isBigOWith
#align asymptotics.is_o.of_is_O_with Asymptotics.IsLittleO.of_isBigOWith
/-- Definition of `IsLittleO` in terms of filters. -/
theorem isLittleO_iff : f =o[l] g ↔ ∀ ⦃c : ℝ⦄, 0 < c → ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖ := by
simp only [IsLittleO_def, IsBigOWith_def]
#align asymptotics.is_o_iff Asymptotics.isLittleO_iff
alias ⟨IsLittleO.bound, IsLittleO.of_bound⟩ := isLittleO_iff
#align asymptotics.is_o.bound Asymptotics.IsLittleO.bound
#align asymptotics.is_o.of_bound Asymptotics.IsLittleO.of_bound
theorem IsLittleO.def (h : f =o[l] g) (hc : 0 < c) : ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖ :=
isLittleO_iff.1 h hc
#align asymptotics.is_o.def Asymptotics.IsLittleO.def
theorem IsLittleO.def' (h : f =o[l] g) (hc : 0 < c) : IsBigOWith c l f g :=
isBigOWith_iff.2 <| isLittleO_iff.1 h hc
#align asymptotics.is_o.def' Asymptotics.IsLittleO.def'
theorem IsLittleO.eventuallyLE (h : f =o[l] g) : ∀ᶠ x in l, ‖f x‖ ≤ ‖g x‖ := by
simpa using h.def zero_lt_one
end Defs
/-! ### Conversions -/
theorem IsBigOWith.isBigO (h : IsBigOWith c l f g) : f =O[l] g := by rw [IsBigO_def]; exact ⟨c, h⟩
#align asymptotics.is_O_with.is_O Asymptotics.IsBigOWith.isBigO
theorem IsLittleO.isBigOWith (hgf : f =o[l] g) : IsBigOWith 1 l f g :=
hgf.def' zero_lt_one
#align asymptotics.is_o.is_O_with Asymptotics.IsLittleO.isBigOWith
theorem IsLittleO.isBigO (hgf : f =o[l] g) : f =O[l] g :=
hgf.isBigOWith.isBigO
#align asymptotics.is_o.is_O Asymptotics.IsLittleO.isBigO
theorem IsBigO.isBigOWith : f =O[l] g → ∃ c : ℝ, IsBigOWith c l f g :=
isBigO_iff_isBigOWith.1
#align asymptotics.is_O.is_O_with Asymptotics.IsBigO.isBigOWith
theorem IsBigOWith.weaken (h : IsBigOWith c l f g') (hc : c ≤ c') : IsBigOWith c' l f g' :=
IsBigOWith.of_bound <|
mem_of_superset h.bound fun x hx =>
calc
‖f x‖ ≤ c * ‖g' x‖ := hx
_ ≤ _ := by gcongr
#align asymptotics.is_O_with.weaken Asymptotics.IsBigOWith.weaken
theorem IsBigOWith.exists_pos (h : IsBigOWith c l f g') :
∃ c' > 0, IsBigOWith c' l f g' :=
⟨max c 1, lt_of_lt_of_le zero_lt_one (le_max_right c 1), h.weaken <| le_max_left c 1⟩
#align asymptotics.is_O_with.exists_pos Asymptotics.IsBigOWith.exists_pos
theorem IsBigO.exists_pos (h : f =O[l] g') : ∃ c > 0, IsBigOWith c l f g' :=
let ⟨_c, hc⟩ := h.isBigOWith
hc.exists_pos
#align asymptotics.is_O.exists_pos Asymptotics.IsBigO.exists_pos
theorem IsBigOWith.exists_nonneg (h : IsBigOWith c l f g') :
∃ c' ≥ 0, IsBigOWith c' l f g' :=
let ⟨c, cpos, hc⟩ := h.exists_pos
⟨c, le_of_lt cpos, hc⟩
#align asymptotics.is_O_with.exists_nonneg Asymptotics.IsBigOWith.exists_nonneg
theorem IsBigO.exists_nonneg (h : f =O[l] g') : ∃ c ≥ 0, IsBigOWith c l f g' :=
let ⟨_c, hc⟩ := h.isBigOWith
hc.exists_nonneg
#align asymptotics.is_O.exists_nonneg Asymptotics.IsBigO.exists_nonneg
/-- `f = O(g)` if and only if `IsBigOWith c f g` for all sufficiently large `c`. -/
theorem isBigO_iff_eventually_isBigOWith : f =O[l] g' ↔ ∀ᶠ c in atTop, IsBigOWith c l f g' :=
isBigO_iff_isBigOWith.trans
⟨fun ⟨c, hc⟩ => mem_atTop_sets.2 ⟨c, fun _c' hc' => hc.weaken hc'⟩, fun h => h.exists⟩
#align asymptotics.is_O_iff_eventually_is_O_with Asymptotics.isBigO_iff_eventually_isBigOWith
/-- `f = O(g)` if and only if `∀ᶠ x in l, ‖f x‖ ≤ c * ‖g x‖` for all sufficiently large `c`. -/
theorem isBigO_iff_eventually : f =O[l] g' ↔ ∀ᶠ c in atTop, ∀ᶠ x in l, ‖f x‖ ≤ c * ‖g' x‖ :=
isBigO_iff_eventually_isBigOWith.trans <| by simp only [IsBigOWith_def]
#align asymptotics.is_O_iff_eventually Asymptotics.isBigO_iff_eventually
theorem IsBigO.exists_mem_basis {ι} {p : ι → Prop} {s : ι → Set α} (h : f =O[l] g')
(hb : l.HasBasis p s) :
∃ c > 0, ∃ i : ι, p i ∧ ∀ x ∈ s i, ‖f x‖ ≤ c * ‖g' x‖ :=
flip Exists.imp h.exists_pos fun c h => by
simpa only [isBigOWith_iff, hb.eventually_iff, exists_prop] using h
#align asymptotics.is_O.exists_mem_basis Asymptotics.IsBigO.exists_mem_basis
theorem isBigOWith_inv (hc : 0 < c) : IsBigOWith c⁻¹ l f g ↔ ∀ᶠ x in l, c * ‖f x‖ ≤ ‖g x‖ := by
simp only [IsBigOWith_def, ← div_eq_inv_mul, le_div_iff' hc]
#align asymptotics.is_O_with_inv Asymptotics.isBigOWith_inv
-- We prove this lemma with strange assumptions to get two lemmas below automatically
theorem isLittleO_iff_nat_mul_le_aux (h₀ : (∀ x, 0 ≤ ‖f x‖) ∨ ∀ x, 0 ≤ ‖g x‖) :
f =o[l] g ↔ ∀ n : ℕ, ∀ᶠ x in l, ↑n * ‖f x‖ ≤ ‖g x‖ := by
constructor
· rintro H (_ | n)
· refine (H.def one_pos).mono fun x h₀' => ?_
rw [Nat.cast_zero, zero_mul]
refine h₀.elim (fun hf => (hf x).trans ?_) fun hg => hg x
rwa [one_mul] at h₀'
· have : (0 : ℝ) < n.succ := Nat.cast_pos.2 n.succ_pos
exact (isBigOWith_inv this).1 (H.def' <| inv_pos.2 this)
· refine fun H => isLittleO_iff.2 fun ε ε0 => ?_
rcases exists_nat_gt ε⁻¹ with ⟨n, hn⟩
have hn₀ : (0 : ℝ) < n := (inv_pos.2 ε0).trans hn
refine ((isBigOWith_inv hn₀).2 (H n)).bound.mono fun x hfg => ?_
refine hfg.trans (mul_le_mul_of_nonneg_right (inv_le_of_inv_le ε0 hn.le) ?_)
refine h₀.elim (fun hf => nonneg_of_mul_nonneg_right ((hf x).trans hfg) ?_) fun h => h x
exact inv_pos.2 hn₀
#align asymptotics.is_o_iff_nat_mul_le_aux Asymptotics.isLittleO_iff_nat_mul_le_aux
theorem isLittleO_iff_nat_mul_le : f =o[l] g' ↔ ∀ n : ℕ, ∀ᶠ x in l, ↑n * ‖f x‖ ≤ ‖g' x‖ :=
isLittleO_iff_nat_mul_le_aux (Or.inr fun _x => norm_nonneg _)
#align asymptotics.is_o_iff_nat_mul_le Asymptotics.isLittleO_iff_nat_mul_le
theorem isLittleO_iff_nat_mul_le' : f' =o[l] g ↔ ∀ n : ℕ, ∀ᶠ x in l, ↑n * ‖f' x‖ ≤ ‖g x‖ :=
isLittleO_iff_nat_mul_le_aux (Or.inl fun _x => norm_nonneg _)
#align asymptotics.is_o_iff_nat_mul_le' Asymptotics.isLittleO_iff_nat_mul_le'
/-! ### Subsingleton -/
@[nontriviality]
theorem isLittleO_of_subsingleton [Subsingleton E'] : f' =o[l] g' :=
IsLittleO.of_bound fun c hc => by simp [Subsingleton.elim (f' _) 0, mul_nonneg hc.le]
#align asymptotics.is_o_of_subsingleton Asymptotics.isLittleO_of_subsingleton
@[nontriviality]
theorem isBigO_of_subsingleton [Subsingleton E'] : f' =O[l] g' :=
isLittleO_of_subsingleton.isBigO
#align asymptotics.is_O_of_subsingleton Asymptotics.isBigO_of_subsingleton
section congr
variable {f₁ f₂ : α → E} {g₁ g₂ : α → F}
/-! ### Congruence -/
theorem isBigOWith_congr (hc : c₁ = c₂) (hf : f₁ =ᶠ[l] f₂) (hg : g₁ =ᶠ[l] g₂) :
IsBigOWith c₁ l f₁ g₁ ↔ IsBigOWith c₂ l f₂ g₂ := by
simp only [IsBigOWith_def]
subst c₂
apply Filter.eventually_congr
filter_upwards [hf, hg] with _ e₁ e₂
rw [e₁, e₂]
#align asymptotics.is_O_with_congr Asymptotics.isBigOWith_congr
theorem IsBigOWith.congr' (h : IsBigOWith c₁ l f₁ g₁) (hc : c₁ = c₂) (hf : f₁ =ᶠ[l] f₂)
(hg : g₁ =ᶠ[l] g₂) : IsBigOWith c₂ l f₂ g₂ :=
(isBigOWith_congr hc hf hg).mp h
#align asymptotics.is_O_with.congr' Asymptotics.IsBigOWith.congr'
theorem IsBigOWith.congr (h : IsBigOWith c₁ l f₁ g₁) (hc : c₁ = c₂) (hf : ∀ x, f₁ x = f₂ x)
(hg : ∀ x, g₁ x = g₂ x) : IsBigOWith c₂ l f₂ g₂ :=
h.congr' hc (univ_mem' hf) (univ_mem' hg)
#align asymptotics.is_O_with.congr Asymptotics.IsBigOWith.congr
theorem IsBigOWith.congr_left (h : IsBigOWith c l f₁ g) (hf : ∀ x, f₁ x = f₂ x) :
IsBigOWith c l f₂ g :=
h.congr rfl hf fun _ => rfl
#align asymptotics.is_O_with.congr_left Asymptotics.IsBigOWith.congr_left
theorem IsBigOWith.congr_right (h : IsBigOWith c l f g₁) (hg : ∀ x, g₁ x = g₂ x) :
IsBigOWith c l f g₂ :=
h.congr rfl (fun _ => rfl) hg
#align asymptotics.is_O_with.congr_right Asymptotics.IsBigOWith.congr_right
theorem IsBigOWith.congr_const (h : IsBigOWith c₁ l f g) (hc : c₁ = c₂) : IsBigOWith c₂ l f g :=
h.congr hc (fun _ => rfl) fun _ => rfl
#align asymptotics.is_O_with.congr_const Asymptotics.IsBigOWith.congr_const
theorem isBigO_congr (hf : f₁ =ᶠ[l] f₂) (hg : g₁ =ᶠ[l] g₂) : f₁ =O[l] g₁ ↔ f₂ =O[l] g₂ := by
simp only [IsBigO_def]
exact exists_congr fun c => isBigOWith_congr rfl hf hg
#align asymptotics.is_O_congr Asymptotics.isBigO_congr
theorem IsBigO.congr' (h : f₁ =O[l] g₁) (hf : f₁ =ᶠ[l] f₂) (hg : g₁ =ᶠ[l] g₂) : f₂ =O[l] g₂ :=
(isBigO_congr hf hg).mp h
#align asymptotics.is_O.congr' Asymptotics.IsBigO.congr'
theorem IsBigO.congr (h : f₁ =O[l] g₁) (hf : ∀ x, f₁ x = f₂ x) (hg : ∀ x, g₁ x = g₂ x) :
f₂ =O[l] g₂ :=
h.congr' (univ_mem' hf) (univ_mem' hg)
#align asymptotics.is_O.congr Asymptotics.IsBigO.congr
theorem IsBigO.congr_left (h : f₁ =O[l] g) (hf : ∀ x, f₁ x = f₂ x) : f₂ =O[l] g :=
h.congr hf fun _ => rfl
#align asymptotics.is_O.congr_left Asymptotics.IsBigO.congr_left
theorem IsBigO.congr_right (h : f =O[l] g₁) (hg : ∀ x, g₁ x = g₂ x) : f =O[l] g₂ :=
h.congr (fun _ => rfl) hg
#align asymptotics.is_O.congr_right Asymptotics.IsBigO.congr_right
theorem isLittleO_congr (hf : f₁ =ᶠ[l] f₂) (hg : g₁ =ᶠ[l] g₂) : f₁ =o[l] g₁ ↔ f₂ =o[l] g₂ := by
simp only [IsLittleO_def]
exact forall₂_congr fun c _hc => isBigOWith_congr (Eq.refl c) hf hg
#align asymptotics.is_o_congr Asymptotics.isLittleO_congr
theorem IsLittleO.congr' (h : f₁ =o[l] g₁) (hf : f₁ =ᶠ[l] f₂) (hg : g₁ =ᶠ[l] g₂) : f₂ =o[l] g₂ :=
(isLittleO_congr hf hg).mp h
#align asymptotics.is_o.congr' Asymptotics.IsLittleO.congr'
theorem IsLittleO.congr (h : f₁ =o[l] g₁) (hf : ∀ x, f₁ x = f₂ x) (hg : ∀ x, g₁ x = g₂ x) :
f₂ =o[l] g₂ :=
h.congr' (univ_mem' hf) (univ_mem' hg)
#align asymptotics.is_o.congr Asymptotics.IsLittleO.congr
theorem IsLittleO.congr_left (h : f₁ =o[l] g) (hf : ∀ x, f₁ x = f₂ x) : f₂ =o[l] g :=
h.congr hf fun _ => rfl
#align asymptotics.is_o.congr_left Asymptotics.IsLittleO.congr_left
theorem IsLittleO.congr_right (h : f =o[l] g₁) (hg : ∀ x, g₁ x = g₂ x) : f =o[l] g₂ :=
h.congr (fun _ => rfl) hg
#align asymptotics.is_o.congr_right Asymptotics.IsLittleO.congr_right
@[trans]
theorem _root_.Filter.EventuallyEq.trans_isBigO {f₁ f₂ : α → E} {g : α → F} (hf : f₁ =ᶠ[l] f₂)
(h : f₂ =O[l] g) : f₁ =O[l] g :=
h.congr' hf.symm EventuallyEq.rfl
#align filter.eventually_eq.trans_is_O Filter.EventuallyEq.trans_isBigO
instance transEventuallyEqIsBigO :
@Trans (α → E) (α → E) (α → F) (· =ᶠ[l] ·) (· =O[l] ·) (· =O[l] ·) where
trans := Filter.EventuallyEq.trans_isBigO
@[trans]
theorem _root_.Filter.EventuallyEq.trans_isLittleO {f₁ f₂ : α → E} {g : α → F} (hf : f₁ =ᶠ[l] f₂)
(h : f₂ =o[l] g) : f₁ =o[l] g :=
h.congr' hf.symm EventuallyEq.rfl
#align filter.eventually_eq.trans_is_o Filter.EventuallyEq.trans_isLittleO
instance transEventuallyEqIsLittleO :
@Trans (α → E) (α → E) (α → F) (· =ᶠ[l] ·) (· =o[l] ·) (· =o[l] ·) where
trans := Filter.EventuallyEq.trans_isLittleO
@[trans]
theorem IsBigO.trans_eventuallyEq {f : α → E} {g₁ g₂ : α → F} (h : f =O[l] g₁) (hg : g₁ =ᶠ[l] g₂) :
f =O[l] g₂ :=
h.congr' EventuallyEq.rfl hg
#align asymptotics.is_O.trans_eventually_eq Asymptotics.IsBigO.trans_eventuallyEq
instance transIsBigOEventuallyEq :
@Trans (α → E) (α → F) (α → F) (· =O[l] ·) (· =ᶠ[l] ·) (· =O[l] ·) where
trans := IsBigO.trans_eventuallyEq
@[trans]
theorem IsLittleO.trans_eventuallyEq {f : α → E} {g₁ g₂ : α → F} (h : f =o[l] g₁)
(hg : g₁ =ᶠ[l] g₂) : f =o[l] g₂ :=
h.congr' EventuallyEq.rfl hg
#align asymptotics.is_o.trans_eventually_eq Asymptotics.IsLittleO.trans_eventuallyEq
instance transIsLittleOEventuallyEq :
@Trans (α → E) (α → F) (α → F) (· =o[l] ·) (· =ᶠ[l] ·) (· =o[l] ·) where
trans := IsLittleO.trans_eventuallyEq
end congr
/-! ### Filter operations and transitivity -/
theorem IsBigOWith.comp_tendsto (hcfg : IsBigOWith c l f g) {k : β → α} {l' : Filter β}
(hk : Tendsto k l' l) : IsBigOWith c l' (f ∘ k) (g ∘ k) :=
IsBigOWith.of_bound <| hk hcfg.bound
#align asymptotics.is_O_with.comp_tendsto Asymptotics.IsBigOWith.comp_tendsto
theorem IsBigO.comp_tendsto (hfg : f =O[l] g) {k : β → α} {l' : Filter β} (hk : Tendsto k l' l) :
(f ∘ k) =O[l'] (g ∘ k) :=
isBigO_iff_isBigOWith.2 <| hfg.isBigOWith.imp fun _c h => h.comp_tendsto hk
#align asymptotics.is_O.comp_tendsto Asymptotics.IsBigO.comp_tendsto
theorem IsLittleO.comp_tendsto (hfg : f =o[l] g) {k : β → α} {l' : Filter β} (hk : Tendsto k l' l) :
(f ∘ k) =o[l'] (g ∘ k) :=
IsLittleO.of_isBigOWith fun _c cpos => (hfg.forall_isBigOWith cpos).comp_tendsto hk
#align asymptotics.is_o.comp_tendsto Asymptotics.IsLittleO.comp_tendsto
@[simp]
theorem isBigOWith_map {k : β → α} {l : Filter β} :
IsBigOWith c (map k l) f g ↔ IsBigOWith c l (f ∘ k) (g ∘ k) := by
simp only [IsBigOWith_def]
exact eventually_map
#align asymptotics.is_O_with_map Asymptotics.isBigOWith_map
@[simp]
theorem isBigO_map {k : β → α} {l : Filter β} : f =O[map k l] g ↔ (f ∘ k) =O[l] (g ∘ k) := by
simp only [IsBigO_def, isBigOWith_map]
#align asymptotics.is_O_map Asymptotics.isBigO_map
@[simp]
theorem isLittleO_map {k : β → α} {l : Filter β} : f =o[map k l] g ↔ (f ∘ k) =o[l] (g ∘ k) := by
simp only [IsLittleO_def, isBigOWith_map]
#align asymptotics.is_o_map Asymptotics.isLittleO_map
theorem IsBigOWith.mono (h : IsBigOWith c l' f g) (hl : l ≤ l') : IsBigOWith c l f g :=
IsBigOWith.of_bound <| hl h.bound
#align asymptotics.is_O_with.mono Asymptotics.IsBigOWith.mono
theorem IsBigO.mono (h : f =O[l'] g) (hl : l ≤ l') : f =O[l] g :=
isBigO_iff_isBigOWith.2 <| h.isBigOWith.imp fun _c h => h.mono hl
#align asymptotics.is_O.mono Asymptotics.IsBigO.mono
theorem IsLittleO.mono (h : f =o[l'] g) (hl : l ≤ l') : f =o[l] g :=
IsLittleO.of_isBigOWith fun _c cpos => (h.forall_isBigOWith cpos).mono hl
#align asymptotics.is_o.mono Asymptotics.IsLittleO.mono
theorem IsBigOWith.trans (hfg : IsBigOWith c l f g) (hgk : IsBigOWith c' l g k) (hc : 0 ≤ c) :
IsBigOWith (c * c') l f k := by
simp only [IsBigOWith_def] at *
filter_upwards [hfg, hgk] with x hx hx'
calc
‖f x‖ ≤ c * ‖g x‖ := hx
_ ≤ c * (c' * ‖k x‖) := by gcongr
_ = c * c' * ‖k x‖ := (mul_assoc _ _ _).symm
#align asymptotics.is_O_with.trans Asymptotics.IsBigOWith.trans
@[trans]
theorem IsBigO.trans {f : α → E} {g : α → F'} {k : α → G} (hfg : f =O[l] g) (hgk : g =O[l] k) :
f =O[l] k :=
let ⟨_c, cnonneg, hc⟩ := hfg.exists_nonneg
let ⟨_c', hc'⟩ := hgk.isBigOWith
(hc.trans hc' cnonneg).isBigO
#align asymptotics.is_O.trans Asymptotics.IsBigO.trans
instance transIsBigOIsBigO :
@Trans (α → E) (α → F') (α → G) (· =O[l] ·) (· =O[l] ·) (· =O[l] ·) where
trans := IsBigO.trans
theorem IsLittleO.trans_isBigOWith (hfg : f =o[l] g) (hgk : IsBigOWith c l g k) (hc : 0 < c) :
f =o[l] k := by
simp only [IsLittleO_def] at *
intro c' c'pos
have : 0 < c' / c := div_pos c'pos hc
exact ((hfg this).trans hgk this.le).congr_const (div_mul_cancel₀ _ hc.ne')
#align asymptotics.is_o.trans_is_O_with Asymptotics.IsLittleO.trans_isBigOWith
@[trans]
theorem IsLittleO.trans_isBigO {f : α → E} {g : α → F} {k : α → G'} (hfg : f =o[l] g)
(hgk : g =O[l] k) : f =o[l] k :=
let ⟨_c, cpos, hc⟩ := hgk.exists_pos
hfg.trans_isBigOWith hc cpos
#align asymptotics.is_o.trans_is_O Asymptotics.IsLittleO.trans_isBigO
instance transIsLittleOIsBigO :
@Trans (α → E) (α → F) (α → G') (· =o[l] ·) (· =O[l] ·) (· =o[l] ·) where
trans := IsLittleO.trans_isBigO
theorem IsBigOWith.trans_isLittleO (hfg : IsBigOWith c l f g) (hgk : g =o[l] k) (hc : 0 < c) :
f =o[l] k := by
simp only [IsLittleO_def] at *
intro c' c'pos
have : 0 < c' / c := div_pos c'pos hc
exact (hfg.trans (hgk this) hc.le).congr_const (mul_div_cancel₀ _ hc.ne')
#align asymptotics.is_O_with.trans_is_o Asymptotics.IsBigOWith.trans_isLittleO
@[trans]
theorem IsBigO.trans_isLittleO {f : α → E} {g : α → F'} {k : α → G} (hfg : f =O[l] g)
(hgk : g =o[l] k) : f =o[l] k :=
let ⟨_c, cpos, hc⟩ := hfg.exists_pos
hc.trans_isLittleO hgk cpos
#align asymptotics.is_O.trans_is_o Asymptotics.IsBigO.trans_isLittleO
instance transIsBigOIsLittleO :
@Trans (α → E) (α → F') (α → G) (· =O[l] ·) (· =o[l] ·) (· =o[l] ·) where
trans := IsBigO.trans_isLittleO
@[trans]
theorem IsLittleO.trans {f : α → E} {g : α → F} {k : α → G} (hfg : f =o[l] g) (hgk : g =o[l] k) :
f =o[l] k :=
hfg.trans_isBigOWith hgk.isBigOWith one_pos
#align asymptotics.is_o.trans Asymptotics.IsLittleO.trans
instance transIsLittleOIsLittleO :
@Trans (α → E) (α → F) (α → G) (· =o[l] ·) (· =o[l] ·) (· =o[l] ·) where
trans := IsLittleO.trans
theorem _root_.Filter.Eventually.trans_isBigO {f : α → E} {g : α → F'} {k : α → G}
(hfg : ∀ᶠ x in l, ‖f x‖ ≤ ‖g x‖) (hgk : g =O[l] k) : f =O[l] k :=
(IsBigO.of_bound' hfg).trans hgk
#align filter.eventually.trans_is_O Filter.Eventually.trans_isBigO
theorem _root_.Filter.Eventually.isBigO {f : α → E} {g : α → ℝ} {l : Filter α}
(hfg : ∀ᶠ x in l, ‖f x‖ ≤ g x) : f =O[l] g :=
IsBigO.of_bound' <| hfg.mono fun _x hx => hx.trans <| Real.le_norm_self _
#align filter.eventually.is_O Filter.Eventually.isBigO
section
variable (l)
theorem isBigOWith_of_le' (hfg : ∀ x, ‖f x‖ ≤ c * ‖g x‖) : IsBigOWith c l f g :=
IsBigOWith.of_bound <| univ_mem' hfg
#align asymptotics.is_O_with_of_le' Asymptotics.isBigOWith_of_le'
theorem isBigOWith_of_le (hfg : ∀ x, ‖f x‖ ≤ ‖g x‖) : IsBigOWith 1 l f g :=
isBigOWith_of_le' l fun x => by
rw [one_mul]
exact hfg x
#align asymptotics.is_O_with_of_le Asymptotics.isBigOWith_of_le
theorem isBigO_of_le' (hfg : ∀ x, ‖f x‖ ≤ c * ‖g x‖) : f =O[l] g :=
(isBigOWith_of_le' l hfg).isBigO
#align asymptotics.is_O_of_le' Asymptotics.isBigO_of_le'
theorem isBigO_of_le (hfg : ∀ x, ‖f x‖ ≤ ‖g x‖) : f =O[l] g :=
(isBigOWith_of_le l hfg).isBigO
#align asymptotics.is_O_of_le Asymptotics.isBigO_of_le
end
theorem isBigOWith_refl (f : α → E) (l : Filter α) : IsBigOWith 1 l f f :=
isBigOWith_of_le l fun _ => le_rfl
#align asymptotics.is_O_with_refl Asymptotics.isBigOWith_refl
theorem isBigO_refl (f : α → E) (l : Filter α) : f =O[l] f :=
(isBigOWith_refl f l).isBigO
#align asymptotics.is_O_refl Asymptotics.isBigO_refl
theorem _root_.Filter.EventuallyEq.isBigO {f₁ f₂ : α → E} (hf : f₁ =ᶠ[l] f₂) : f₁ =O[l] f₂ :=
hf.trans_isBigO (isBigO_refl _ _)
theorem IsBigOWith.trans_le (hfg : IsBigOWith c l f g) (hgk : ∀ x, ‖g x‖ ≤ ‖k x‖) (hc : 0 ≤ c) :
IsBigOWith c l f k :=
(hfg.trans (isBigOWith_of_le l hgk) hc).congr_const <| mul_one c
#align asymptotics.is_O_with.trans_le Asymptotics.IsBigOWith.trans_le
theorem IsBigO.trans_le (hfg : f =O[l] g') (hgk : ∀ x, ‖g' x‖ ≤ ‖k x‖) : f =O[l] k :=
hfg.trans (isBigO_of_le l hgk)
#align asymptotics.is_O.trans_le Asymptotics.IsBigO.trans_le
theorem IsLittleO.trans_le (hfg : f =o[l] g) (hgk : ∀ x, ‖g x‖ ≤ ‖k x‖) : f =o[l] k :=
hfg.trans_isBigOWith (isBigOWith_of_le _ hgk) zero_lt_one
#align asymptotics.is_o.trans_le Asymptotics.IsLittleO.trans_le
theorem isLittleO_irrefl' (h : ∃ᶠ x in l, ‖f' x‖ ≠ 0) : ¬f' =o[l] f' := by
intro ho
rcases ((ho.bound one_half_pos).and_frequently h).exists with ⟨x, hle, hne⟩
rw [one_div, ← div_eq_inv_mul] at hle
exact (half_lt_self (lt_of_le_of_ne (norm_nonneg _) hne.symm)).not_le hle
#align asymptotics.is_o_irrefl' Asymptotics.isLittleO_irrefl'
theorem isLittleO_irrefl (h : ∃ᶠ x in l, f'' x ≠ 0) : ¬f'' =o[l] f'' :=
isLittleO_irrefl' <| h.mono fun _x => norm_ne_zero_iff.mpr
#align asymptotics.is_o_irrefl Asymptotics.isLittleO_irrefl
theorem IsBigO.not_isLittleO (h : f'' =O[l] g') (hf : ∃ᶠ x in l, f'' x ≠ 0) :
¬g' =o[l] f'' := fun h' =>
isLittleO_irrefl hf (h.trans_isLittleO h')
#align asymptotics.is_O.not_is_o Asymptotics.IsBigO.not_isLittleO
theorem IsLittleO.not_isBigO (h : f'' =o[l] g') (hf : ∃ᶠ x in l, f'' x ≠ 0) :
¬g' =O[l] f'' := fun h' =>
isLittleO_irrefl hf (h.trans_isBigO h')
#align asymptotics.is_o.not_is_O Asymptotics.IsLittleO.not_isBigO
section Bot
variable (c f g)
@[simp]
theorem isBigOWith_bot : IsBigOWith c ⊥ f g :=
IsBigOWith.of_bound <| trivial
#align asymptotics.is_O_with_bot Asymptotics.isBigOWith_bot
@[simp]
theorem isBigO_bot : f =O[⊥] g :=
(isBigOWith_bot 1 f g).isBigO
#align asymptotics.is_O_bot Asymptotics.isBigO_bot
@[simp]
theorem isLittleO_bot : f =o[⊥] g :=
IsLittleO.of_isBigOWith fun c _ => isBigOWith_bot c f g
#align asymptotics.is_o_bot Asymptotics.isLittleO_bot
end Bot
@[simp]
theorem isBigOWith_pure {x} : IsBigOWith c (pure x) f g ↔ ‖f x‖ ≤ c * ‖g x‖ :=
isBigOWith_iff
#align asymptotics.is_O_with_pure Asymptotics.isBigOWith_pure
theorem IsBigOWith.sup (h : IsBigOWith c l f g) (h' : IsBigOWith c l' f g) :
IsBigOWith c (l ⊔ l') f g :=
IsBigOWith.of_bound <| mem_sup.2 ⟨h.bound, h'.bound⟩
#align asymptotics.is_O_with.sup Asymptotics.IsBigOWith.sup
theorem IsBigOWith.sup' (h : IsBigOWith c l f g') (h' : IsBigOWith c' l' f g') :
IsBigOWith (max c c') (l ⊔ l') f g' :=
IsBigOWith.of_bound <|
mem_sup.2 ⟨(h.weaken <| le_max_left c c').bound, (h'.weaken <| le_max_right c c').bound⟩
#align asymptotics.is_O_with.sup' Asymptotics.IsBigOWith.sup'
theorem IsBigO.sup (h : f =O[l] g') (h' : f =O[l'] g') : f =O[l ⊔ l'] g' :=
let ⟨_c, hc⟩ := h.isBigOWith
let ⟨_c', hc'⟩ := h'.isBigOWith
(hc.sup' hc').isBigO
#align asymptotics.is_O.sup Asymptotics.IsBigO.sup
theorem IsLittleO.sup (h : f =o[l] g) (h' : f =o[l'] g) : f =o[l ⊔ l'] g :=
IsLittleO.of_isBigOWith fun _c cpos => (h.forall_isBigOWith cpos).sup (h'.forall_isBigOWith cpos)
#align asymptotics.is_o.sup Asymptotics.IsLittleO.sup
@[simp]
theorem isBigO_sup : f =O[l ⊔ l'] g' ↔ f =O[l] g' ∧ f =O[l'] g' :=
⟨fun h => ⟨h.mono le_sup_left, h.mono le_sup_right⟩, fun h => h.1.sup h.2⟩
#align asymptotics.is_O_sup Asymptotics.isBigO_sup
@[simp]
theorem isLittleO_sup : f =o[l ⊔ l'] g ↔ f =o[l] g ∧ f =o[l'] g :=
⟨fun h => ⟨h.mono le_sup_left, h.mono le_sup_right⟩, fun h => h.1.sup h.2⟩
#align asymptotics.is_o_sup Asymptotics.isLittleO_sup
theorem isBigOWith_insert [TopologicalSpace α] {x : α} {s : Set α} {C : ℝ} {g : α → E} {g' : α → F}
(h : ‖g x‖ ≤ C * ‖g' x‖) : IsBigOWith C (𝓝[insert x s] x) g g' ↔
IsBigOWith C (𝓝[s] x) g g' := by
simp_rw [IsBigOWith_def, nhdsWithin_insert, eventually_sup, eventually_pure, h, true_and_iff]
#align asymptotics.is_O_with_insert Asymptotics.isBigOWith_insert
protected theorem IsBigOWith.insert [TopologicalSpace α] {x : α} {s : Set α} {C : ℝ} {g : α → E}
{g' : α → F} (h1 : IsBigOWith C (𝓝[s] x) g g') (h2 : ‖g x‖ ≤ C * ‖g' x‖) :
IsBigOWith C (𝓝[insert x s] x) g g' :=
(isBigOWith_insert h2).mpr h1
#align asymptotics.is_O_with.insert Asymptotics.IsBigOWith.insert
theorem isLittleO_insert [TopologicalSpace α] {x : α} {s : Set α} {g : α → E'} {g' : α → F'}
(h : g x = 0) : g =o[𝓝[insert x s] x] g' ↔ g =o[𝓝[s] x] g' := by
simp_rw [IsLittleO_def]
refine forall_congr' fun c => forall_congr' fun hc => ?_
rw [isBigOWith_insert]
rw [h, norm_zero]
exact mul_nonneg hc.le (norm_nonneg _)
#align asymptotics.is_o_insert Asymptotics.isLittleO_insert
protected theorem IsLittleO.insert [TopologicalSpace α] {x : α} {s : Set α} {g : α → E'}
{g' : α → F'} (h1 : g =o[𝓝[s] x] g') (h2 : g x = 0) : g =o[𝓝[insert x s] x] g' :=
(isLittleO_insert h2).mpr h1
#align asymptotics.is_o.insert Asymptotics.IsLittleO.insert
/-! ### Simplification : norm, abs -/
section NormAbs
variable {u v : α → ℝ}
@[simp]
theorem isBigOWith_norm_right : (IsBigOWith c l f fun x => ‖g' x‖) ↔ IsBigOWith c l f g' := by
simp only [IsBigOWith_def, norm_norm]
#align asymptotics.is_O_with_norm_right Asymptotics.isBigOWith_norm_right
@[simp]
theorem isBigOWith_abs_right : (IsBigOWith c l f fun x => |u x|) ↔ IsBigOWith c l f u :=
@isBigOWith_norm_right _ _ _ _ _ _ f u l
#align asymptotics.is_O_with_abs_right Asymptotics.isBigOWith_abs_right
alias ⟨IsBigOWith.of_norm_right, IsBigOWith.norm_right⟩ := isBigOWith_norm_right
#align asymptotics.is_O_with.of_norm_right Asymptotics.IsBigOWith.of_norm_right
#align asymptotics.is_O_with.norm_right Asymptotics.IsBigOWith.norm_right
alias ⟨IsBigOWith.of_abs_right, IsBigOWith.abs_right⟩ := isBigOWith_abs_right
#align asymptotics.is_O_with.of_abs_right Asymptotics.IsBigOWith.of_abs_right
#align asymptotics.is_O_with.abs_right Asymptotics.IsBigOWith.abs_right
@[simp]
theorem isBigO_norm_right : (f =O[l] fun x => ‖g' x‖) ↔ f =O[l] g' := by
simp only [IsBigO_def]
exact exists_congr fun _ => isBigOWith_norm_right
#align asymptotics.is_O_norm_right Asymptotics.isBigO_norm_right
@[simp]
theorem isBigO_abs_right : (f =O[l] fun x => |u x|) ↔ f =O[l] u :=
@isBigO_norm_right _ _ ℝ _ _ _ _ _
#align asymptotics.is_O_abs_right Asymptotics.isBigO_abs_right
alias ⟨IsBigO.of_norm_right, IsBigO.norm_right⟩ := isBigO_norm_right
#align asymptotics.is_O.of_norm_right Asymptotics.IsBigO.of_norm_right
#align asymptotics.is_O.norm_right Asymptotics.IsBigO.norm_right
alias ⟨IsBigO.of_abs_right, IsBigO.abs_right⟩ := isBigO_abs_right
#align asymptotics.is_O.of_abs_right Asymptotics.IsBigO.of_abs_right
#align asymptotics.is_O.abs_right Asymptotics.IsBigO.abs_right
@[simp]
theorem isLittleO_norm_right : (f =o[l] fun x => ‖g' x‖) ↔ f =o[l] g' := by
simp only [IsLittleO_def]
exact forall₂_congr fun _ _ => isBigOWith_norm_right
#align asymptotics.is_o_norm_right Asymptotics.isLittleO_norm_right
@[simp]
theorem isLittleO_abs_right : (f =o[l] fun x => |u x|) ↔ f =o[l] u :=
@isLittleO_norm_right _ _ ℝ _ _ _ _ _
#align asymptotics.is_o_abs_right Asymptotics.isLittleO_abs_right
alias ⟨IsLittleO.of_norm_right, IsLittleO.norm_right⟩ := isLittleO_norm_right
#align asymptotics.is_o.of_norm_right Asymptotics.IsLittleO.of_norm_right
#align asymptotics.is_o.norm_right Asymptotics.IsLittleO.norm_right
alias ⟨IsLittleO.of_abs_right, IsLittleO.abs_right⟩ := isLittleO_abs_right
#align asymptotics.is_o.of_abs_right Asymptotics.IsLittleO.of_abs_right
#align asymptotics.is_o.abs_right Asymptotics.IsLittleO.abs_right
@[simp]
theorem isBigOWith_norm_left : IsBigOWith c l (fun x => ‖f' x‖) g ↔ IsBigOWith c l f' g := by
simp only [IsBigOWith_def, norm_norm]
#align asymptotics.is_O_with_norm_left Asymptotics.isBigOWith_norm_left
@[simp]
theorem isBigOWith_abs_left : IsBigOWith c l (fun x => |u x|) g ↔ IsBigOWith c l u g :=
@isBigOWith_norm_left _ _ _ _ _ _ g u l
#align asymptotics.is_O_with_abs_left Asymptotics.isBigOWith_abs_left
alias ⟨IsBigOWith.of_norm_left, IsBigOWith.norm_left⟩ := isBigOWith_norm_left
#align asymptotics.is_O_with.of_norm_left Asymptotics.IsBigOWith.of_norm_left
#align asymptotics.is_O_with.norm_left Asymptotics.IsBigOWith.norm_left
alias ⟨IsBigOWith.of_abs_left, IsBigOWith.abs_left⟩ := isBigOWith_abs_left
#align asymptotics.is_O_with.of_abs_left Asymptotics.IsBigOWith.of_abs_left
#align asymptotics.is_O_with.abs_left Asymptotics.IsBigOWith.abs_left
@[simp]
theorem isBigO_norm_left : (fun x => ‖f' x‖) =O[l] g ↔ f' =O[l] g := by
simp only [IsBigO_def]
exact exists_congr fun _ => isBigOWith_norm_left
#align asymptotics.is_O_norm_left Asymptotics.isBigO_norm_left
@[simp]
theorem isBigO_abs_left : (fun x => |u x|) =O[l] g ↔ u =O[l] g :=
@isBigO_norm_left _ _ _ _ _ g u l
#align asymptotics.is_O_abs_left Asymptotics.isBigO_abs_left
alias ⟨IsBigO.of_norm_left, IsBigO.norm_left⟩ := isBigO_norm_left
#align asymptotics.is_O.of_norm_left Asymptotics.IsBigO.of_norm_left
#align asymptotics.is_O.norm_left Asymptotics.IsBigO.norm_left
alias ⟨IsBigO.of_abs_left, IsBigO.abs_left⟩ := isBigO_abs_left
#align asymptotics.is_O.of_abs_left Asymptotics.IsBigO.of_abs_left
#align asymptotics.is_O.abs_left Asymptotics.IsBigO.abs_left
@[simp]
theorem isLittleO_norm_left : (fun x => ‖f' x‖) =o[l] g ↔ f' =o[l] g := by
simp only [IsLittleO_def]
exact forall₂_congr fun _ _ => isBigOWith_norm_left
#align asymptotics.is_o_norm_left Asymptotics.isLittleO_norm_left
@[simp]
theorem isLittleO_abs_left : (fun x => |u x|) =o[l] g ↔ u =o[l] g :=
@isLittleO_norm_left _ _ _ _ _ g u l
#align asymptotics.is_o_abs_left Asymptotics.isLittleO_abs_left
alias ⟨IsLittleO.of_norm_left, IsLittleO.norm_left⟩ := isLittleO_norm_left
#align asymptotics.is_o.of_norm_left Asymptotics.IsLittleO.of_norm_left
#align asymptotics.is_o.norm_left Asymptotics.IsLittleO.norm_left
alias ⟨IsLittleO.of_abs_left, IsLittleO.abs_left⟩ := isLittleO_abs_left
#align asymptotics.is_o.of_abs_left Asymptotics.IsLittleO.of_abs_left
#align asymptotics.is_o.abs_left Asymptotics.IsLittleO.abs_left
theorem isBigOWith_norm_norm :
(IsBigOWith c l (fun x => ‖f' x‖) fun x => ‖g' x‖) ↔ IsBigOWith c l f' g' :=
isBigOWith_norm_left.trans isBigOWith_norm_right
#align asymptotics.is_O_with_norm_norm Asymptotics.isBigOWith_norm_norm
theorem isBigOWith_abs_abs :
(IsBigOWith c l (fun x => |u x|) fun x => |v x|) ↔ IsBigOWith c l u v :=
isBigOWith_abs_left.trans isBigOWith_abs_right
#align asymptotics.is_O_with_abs_abs Asymptotics.isBigOWith_abs_abs
alias ⟨IsBigOWith.of_norm_norm, IsBigOWith.norm_norm⟩ := isBigOWith_norm_norm
#align asymptotics.is_O_with.of_norm_norm Asymptotics.IsBigOWith.of_norm_norm
#align asymptotics.is_O_with.norm_norm Asymptotics.IsBigOWith.norm_norm
alias ⟨IsBigOWith.of_abs_abs, IsBigOWith.abs_abs⟩ := isBigOWith_abs_abs
#align asymptotics.is_O_with.of_abs_abs Asymptotics.IsBigOWith.of_abs_abs
#align asymptotics.is_O_with.abs_abs Asymptotics.IsBigOWith.abs_abs
theorem isBigO_norm_norm : ((fun x => ‖f' x‖) =O[l] fun x => ‖g' x‖) ↔ f' =O[l] g' :=
isBigO_norm_left.trans isBigO_norm_right
#align asymptotics.is_O_norm_norm Asymptotics.isBigO_norm_norm
theorem isBigO_abs_abs : ((fun x => |u x|) =O[l] fun x => |v x|) ↔ u =O[l] v :=
isBigO_abs_left.trans isBigO_abs_right
#align asymptotics.is_O_abs_abs Asymptotics.isBigO_abs_abs
alias ⟨IsBigO.of_norm_norm, IsBigO.norm_norm⟩ := isBigO_norm_norm
#align asymptotics.is_O.of_norm_norm Asymptotics.IsBigO.of_norm_norm
#align asymptotics.is_O.norm_norm Asymptotics.IsBigO.norm_norm
alias ⟨IsBigO.of_abs_abs, IsBigO.abs_abs⟩ := isBigO_abs_abs
#align asymptotics.is_O.of_abs_abs Asymptotics.IsBigO.of_abs_abs
#align asymptotics.is_O.abs_abs Asymptotics.IsBigO.abs_abs
theorem isLittleO_norm_norm : ((fun x => ‖f' x‖) =o[l] fun x => ‖g' x‖) ↔ f' =o[l] g' :=
isLittleO_norm_left.trans isLittleO_norm_right
#align asymptotics.is_o_norm_norm Asymptotics.isLittleO_norm_norm
theorem isLittleO_abs_abs : ((fun x => |u x|) =o[l] fun x => |v x|) ↔ u =o[l] v :=
isLittleO_abs_left.trans isLittleO_abs_right
#align asymptotics.is_o_abs_abs Asymptotics.isLittleO_abs_abs
alias ⟨IsLittleO.of_norm_norm, IsLittleO.norm_norm⟩ := isLittleO_norm_norm
#align asymptotics.is_o.of_norm_norm Asymptotics.IsLittleO.of_norm_norm
#align asymptotics.is_o.norm_norm Asymptotics.IsLittleO.norm_norm
alias ⟨IsLittleO.of_abs_abs, IsLittleO.abs_abs⟩ := isLittleO_abs_abs
#align asymptotics.is_o.of_abs_abs Asymptotics.IsLittleO.of_abs_abs
#align asymptotics.is_o.abs_abs Asymptotics.IsLittleO.abs_abs
end NormAbs
/-! ### Simplification: negate -/
@[simp]
theorem isBigOWith_neg_right : (IsBigOWith c l f fun x => -g' x) ↔ IsBigOWith c l f g' := by
simp only [IsBigOWith_def, norm_neg]
#align asymptotics.is_O_with_neg_right Asymptotics.isBigOWith_neg_right
alias ⟨IsBigOWith.of_neg_right, IsBigOWith.neg_right⟩ := isBigOWith_neg_right
#align asymptotics.is_O_with.of_neg_right Asymptotics.IsBigOWith.of_neg_right
#align asymptotics.is_O_with.neg_right Asymptotics.IsBigOWith.neg_right
@[simp]
theorem isBigO_neg_right : (f =O[l] fun x => -g' x) ↔ f =O[l] g' := by
simp only [IsBigO_def]
exact exists_congr fun _ => isBigOWith_neg_right
#align asymptotics.is_O_neg_right Asymptotics.isBigO_neg_right
alias ⟨IsBigO.of_neg_right, IsBigO.neg_right⟩ := isBigO_neg_right
#align asymptotics.is_O.of_neg_right Asymptotics.IsBigO.of_neg_right
#align asymptotics.is_O.neg_right Asymptotics.IsBigO.neg_right
@[simp]
theorem isLittleO_neg_right : (f =o[l] fun x => -g' x) ↔ f =o[l] g' := by
simp only [IsLittleO_def]
exact forall₂_congr fun _ _ => isBigOWith_neg_right
#align asymptotics.is_o_neg_right Asymptotics.isLittleO_neg_right
alias ⟨IsLittleO.of_neg_right, IsLittleO.neg_right⟩ := isLittleO_neg_right
#align asymptotics.is_o.of_neg_right Asymptotics.IsLittleO.of_neg_right
#align asymptotics.is_o.neg_right Asymptotics.IsLittleO.neg_right
@[simp]
| Mathlib/Analysis/Asymptotics/Asymptotics.lean | 926 | 927 | theorem isBigOWith_neg_left : IsBigOWith c l (fun x => -f' x) g ↔ IsBigOWith c l f' g := by |
simp only [IsBigOWith_def, norm_neg]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yaël Dillies
-/
import Mathlib.Order.PartialSups
#align_import order.disjointed from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c"
/-!
# Consecutive differences of sets
This file defines the way to make a sequence of elements into a sequence of disjoint elements with
the same partial sups.
For a sequence `f : ℕ → α`, this new sequence will be `f 0`, `f 1 \ f 0`, `f 2 \ (f 0 ⊔ f 1)`.
It is actually unique, as `disjointed_unique` shows.
## Main declarations
* `disjointed f`: The sequence `f 0`, `f 1 \ f 0`, `f 2 \ (f 0 ⊔ f 1)`, ....
* `partialSups_disjointed`: `disjointed f` has the same partial sups as `f`.
* `disjoint_disjointed`: The elements of `disjointed f` are pairwise disjoint.
* `disjointed_unique`: `disjointed f` is the only pairwise disjoint sequence having the same partial
sups as `f`.
* `iSup_disjointed`: `disjointed f` has the same supremum as `f`. Limiting case of
`partialSups_disjointed`.
We also provide set notation variants of some lemmas.
## TODO
Find a useful statement of `disjointedRec_succ`.
One could generalize `disjointed` to any locally finite bot preorder domain, in place of `ℕ`.
Related to the TODO in the module docstring of `Mathlib.Order.PartialSups`.
-/
variable {α β : Type*}
section GeneralizedBooleanAlgebra
variable [GeneralizedBooleanAlgebra α]
/-- If `f : ℕ → α` is a sequence of elements, then `disjointed f` is the sequence formed by
subtracting each element from the nexts. This is the unique disjoint sequence whose partial sups
are the same as the original sequence. -/
def disjointed (f : ℕ → α) : ℕ → α
| 0 => f 0
| n + 1 => f (n + 1) \ partialSups f n
#align disjointed disjointed
@[simp]
theorem disjointed_zero (f : ℕ → α) : disjointed f 0 = f 0 :=
rfl
#align disjointed_zero disjointed_zero
theorem disjointed_succ (f : ℕ → α) (n : ℕ) : disjointed f (n + 1) = f (n + 1) \ partialSups f n :=
rfl
#align disjointed_succ disjointed_succ
theorem disjointed_le_id : disjointed ≤ (id : (ℕ → α) → ℕ → α) := by
rintro f n
cases n
· rfl
· exact sdiff_le
#align disjointed_le_id disjointed_le_id
theorem disjointed_le (f : ℕ → α) : disjointed f ≤ f :=
disjointed_le_id f
#align disjointed_le disjointed_le
theorem disjoint_disjointed (f : ℕ → α) : Pairwise (Disjoint on disjointed f) := by
refine (Symmetric.pairwise_on Disjoint.symm _).2 fun m n h => ?_
cases n
· exact (Nat.not_lt_zero _ h).elim
exact
disjoint_sdiff_self_right.mono_left
((disjointed_le f m).trans (le_partialSups_of_le f (Nat.lt_add_one_iff.1 h)))
#align disjoint_disjointed disjoint_disjointed
-- Porting note: `disjointedRec` had a change in universe level.
/-- An induction principle for `disjointed`. To define/prove something on `disjointed f n`, it's
enough to define/prove it for `f n` and being able to extend through diffs. -/
def disjointedRec {f : ℕ → α} {p : α → Sort*} (hdiff : ∀ ⦃t i⦄, p t → p (t \ f i)) :
∀ ⦃n⦄, p (f n) → p (disjointed f n)
| 0 => id
| n + 1 => fun h => by
suffices H : ∀ k, p (f (n + 1) \ partialSups f k) from H n
rintro k
induction' k with k ih
· exact hdiff h
rw [partialSups_succ, ← sdiff_sdiff_left]
exact hdiff ih
#align disjointed_rec disjointedRec
@[simp]
theorem disjointedRec_zero {f : ℕ → α} {p : α → Sort*} (hdiff : ∀ ⦃t i⦄, p t → p (t \ f i))
(h₀ : p (f 0)) : disjointedRec hdiff h₀ = h₀ :=
rfl
#align disjointed_rec_zero disjointedRec_zero
-- TODO: Find a useful statement of `disjointedRec_succ`.
protected lemma Monotone.disjointed_succ {f : ℕ → α} (hf : Monotone f) (n : ℕ) :
disjointed f (n + 1) = f (n + 1) \ f n := by rw [disjointed_succ, hf.partialSups_eq]
#align monotone.disjointed_eq Monotone.disjointed_succ
protected lemma Monotone.disjointed_succ_sup {f : ℕ → α} (hf : Monotone f) (n : ℕ) :
disjointed f (n + 1) ⊔ f n = f (n + 1) := by
rw [hf.disjointed_succ, sdiff_sup_cancel]; exact hf n.le_succ
@[simp]
| Mathlib/Order/Disjointed.lean | 114 | 118 | theorem partialSups_disjointed (f : ℕ → α) : partialSups (disjointed f) = partialSups f := by |
ext n
induction' n with k ih
· rw [partialSups_zero, partialSups_zero, disjointed_zero]
· rw [partialSups_succ, partialSups_succ, disjointed_succ, ih, sup_sdiff_self_right]
|
/-
Copyright (c) 2021 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
import Mathlib.Analysis.SpecialFunctions.Complex.Circle
import Mathlib.Analysis.InnerProductSpace.l2Space
import Mathlib.MeasureTheory.Function.ContinuousMapDense
import Mathlib.MeasureTheory.Function.L2Space
import Mathlib.MeasureTheory.Group.Integral
import Mathlib.MeasureTheory.Integral.Periodic
import Mathlib.Topology.ContinuousFunction.StoneWeierstrass
import Mathlib.MeasureTheory.Integral.FundThmCalculus
#align_import analysis.fourier.add_circle from "leanprover-community/mathlib"@"8f9fea08977f7e450770933ee6abb20733b47c92"
/-!
# Fourier analysis on the additive circle
This file contains basic results on Fourier series for functions on the additive circle
`AddCircle T = ℝ / ℤ • T`.
## Main definitions
* `haarAddCircle`, Haar measure on `AddCircle T`, normalized to have total measure `1`. (Note
that this is not the same normalisation as the standard measure defined in `Integral.Periodic`,
so we do not declare it as a `MeasureSpace` instance, to avoid confusion.)
* for `n : ℤ`, `fourier n` is the monomial `fun x => exp (2 π i n x / T)`,
bundled as a continuous map from `AddCircle T` to `ℂ`.
* `fourierBasis` is the Hilbert basis of `Lp ℂ 2 haarAddCircle` given by the images of the
monomials `fourier n`.
* `fourierCoeff f n`, for `f : AddCircle T → E` (with `E` a complete normed `ℂ`-vector space), is
the `n`-th Fourier coefficient of `f`, defined as an integral over `AddCircle T`. The lemma
`fourierCoeff_eq_intervalIntegral` expresses this as an integral over `[a, a + T]` for any real
`a`.
* `fourierCoeffOn`, for `f : ℝ → E` and `a < b` reals, is the `n`-th Fourier
coefficient of the unique periodic function of period `b - a` which agrees with `f` on `(a, b]`.
The lemma `fourierCoeffOn_eq_integral` expresses this as an integral over `[a, b]`.
## Main statements
The theorem `span_fourier_closure_eq_top` states that the span of the monomials `fourier n` is
dense in `C(AddCircle T, ℂ)`, i.e. that its `Submodule.topologicalClosure` is `⊤`. This follows
from the Stone-Weierstrass theorem after checking that the span is a subalgebra, is closed under
conjugation, and separates points.
Using this and general theory on approximation of Lᵖ functions by continuous functions, we deduce
(`span_fourierLp_closure_eq_top`) that for any `1 ≤ p < ∞`, the span of the Fourier monomials is
dense in the Lᵖ space of `AddCircle T`. For `p = 2` we show (`orthonormal_fourier`) that the
monomials are also orthonormal, so they form a Hilbert basis for L², which is named as
`fourierBasis`; in particular, for `L²` functions `f`, the Fourier series of `f` converges to `f`
in the `L²` topology (`hasSum_fourier_series_L2`). Parseval's identity, `tsum_sq_fourierCoeff`, is
a direct consequence.
For continuous maps `f : AddCircle T → ℂ`, the theorem
`hasSum_fourier_series_of_summable` states that if the sequence of Fourier
coefficients of `f` is summable, then the Fourier series `∑ (i : ℤ), fourierCoeff f i * fourier i`
converges to `f` in the uniform-convergence topology of `C(AddCircle T, ℂ)`.
-/
noncomputable section
open scoped ENNReal ComplexConjugate Real
open TopologicalSpace ContinuousMap MeasureTheory MeasureTheory.Measure Algebra Submodule Set
variable {T : ℝ}
namespace AddCircle
/-! ### Measure on `AddCircle T`
In this file we use the Haar measure on `AddCircle T` normalised to have total measure 1 (which is
**not** the same as the standard measure defined in `Topology.Instances.AddCircle`). -/
variable [hT : Fact (0 < T)]
/-- Haar measure on the additive circle, normalised to have total measure 1. -/
def haarAddCircle : Measure (AddCircle T) :=
addHaarMeasure ⊤
#align add_circle.haar_add_circle AddCircle.haarAddCircle
-- Porting note: was `deriving IsAddHaarMeasure` on `haarAddCircle`
instance : IsAddHaarMeasure (@haarAddCircle T _) :=
Measure.isAddHaarMeasure_addHaarMeasure ⊤
instance : IsProbabilityMeasure (@haarAddCircle T _) :=
IsProbabilityMeasure.mk addHaarMeasure_self
theorem volume_eq_smul_haarAddCircle :
(volume : Measure (AddCircle T)) = ENNReal.ofReal T • (@haarAddCircle T _) :=
rfl
#align add_circle.volume_eq_smul_haar_add_circle AddCircle.volume_eq_smul_haarAddCircle
end AddCircle
open AddCircle
section Monomials
/-- The family of exponential monomials `fun x => exp (2 π i n x / T)`, parametrized by `n : ℤ` and
considered as bundled continuous maps from `ℝ / ℤ • T` to `ℂ`. -/
def fourier (n : ℤ) : C(AddCircle T, ℂ) where
toFun x := toCircle (n • x :)
continuous_toFun := continuous_induced_dom.comp <| continuous_toCircle.comp <| continuous_zsmul _
#align fourier fourier
@[simp]
theorem fourier_apply {n : ℤ} {x : AddCircle T} : fourier n x = toCircle (n • x :) :=
rfl
#align fourier_apply fourier_apply
-- @[simp] -- Porting note: simp normal form is `fourier_coe_apply'`
theorem fourier_coe_apply {n : ℤ} {x : ℝ} :
fourier n (x : AddCircle T) = Complex.exp (2 * π * Complex.I * n * x / T) := by
rw [fourier_apply, ← QuotientAddGroup.mk_zsmul, toCircle, Function.Periodic.lift_coe,
expMapCircle_apply, Complex.ofReal_mul, Complex.ofReal_div, Complex.ofReal_mul, zsmul_eq_mul,
Complex.ofReal_mul, Complex.ofReal_intCast]
norm_num
congr 1; ring
#align fourier_coe_apply fourier_coe_apply
@[simp]
theorem fourier_coe_apply' {n : ℤ} {x : ℝ} :
toCircle (n • (x : AddCircle T) :) = Complex.exp (2 * π * Complex.I * n * x / T) := by
rw [← fourier_apply]; exact fourier_coe_apply
-- @[simp] -- Porting note: simp normal form is `fourier_zero'`
| Mathlib/Analysis/Fourier/AddCircle.lean | 132 | 135 | theorem fourier_zero {x : AddCircle T} : fourier 0 x = 1 := by |
induction x using QuotientAddGroup.induction_on'
simp only [fourier_coe_apply]
norm_num
|
/-
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, Alexander Bentkamp
-/
import Mathlib.Algebra.BigOperators.Finsupp
import Mathlib.Algebra.BigOperators.Finprod
import Mathlib.Data.Fintype.BigOperators
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.LinearIndependent
import Mathlib.SetTheory.Cardinal.Cofinality
#align_import linear_algebra.basis from "leanprover-community/mathlib"@"13bce9a6b6c44f6b4c91ac1c1d2a816e2533d395"
/-!
# Bases
This file defines bases in a module or vector space.
It is inspired by Isabelle/HOL's linear algebra, and hence indirectly by HOL Light.
## Main definitions
All definitions are given for families of vectors, i.e. `v : ι → M` where `M` is the module or
vector space and `ι : Type*` is an arbitrary indexing type.
* `Basis ι R M` is the type of `ι`-indexed `R`-bases for a module `M`,
represented by a linear equiv `M ≃ₗ[R] ι →₀ R`.
* the basis vectors of a basis `b : Basis ι R M` are available as `b i`, where `i : ι`
* `Basis.repr` is the isomorphism sending `x : M` to its coordinates `Basis.repr x : ι →₀ R`.
The converse, turning this isomorphism into a basis, is called `Basis.ofRepr`.
* If `ι` is finite, there is a variant of `repr` called `Basis.equivFun b : M ≃ₗ[R] ι → R`
(saving you from having to work with `Finsupp`). The converse, turning this isomorphism into
a basis, is called `Basis.ofEquivFun`.
* `Basis.constr b R f` constructs a linear map `M₁ →ₗ[R] M₂` given the values `f : ι → M₂` at the
basis elements `⇑b : ι → M₁`.
* `Basis.reindex` uses an equiv to map a basis to a different indexing set.
* `Basis.map` uses a linear equiv to map a basis to a different module.
## Main statements
* `Basis.mk`: a linear independent set of vectors spanning the whole module determines a basis
* `Basis.ext` states that two linear maps are equal if they coincide on a basis.
Similar results are available for linear equivs (if they coincide on the basis vectors),
elements (if their coordinates coincide) and the functions `b.repr` and `⇑b`.
## Implementation notes
We use families instead of sets because it allows us to say that two identical vectors are linearly
dependent. For bases, this is useful as well because we can easily derive ordered bases by using an
ordered index type `ι`.
## Tags
basis, bases
-/
noncomputable section
universe u
open Function Set Submodule
variable {ι : Type*} {ι' : Type*} {R : Type*} {R₂ : Type*} {K : Type*}
variable {M : Type*} {M' M'' : Type*} {V : Type u} {V' : Type*}
section Module
variable [Semiring R]
variable [AddCommMonoid M] [Module R M] [AddCommMonoid M'] [Module R M']
section
variable (ι R M)
/-- A `Basis ι R M` for a module `M` is the type of `ι`-indexed `R`-bases of `M`.
The basis vectors are available as `DFunLike.coe (b : Basis ι R M) : ι → M`.
To turn a linear independent family of vectors spanning `M` into a basis, use `Basis.mk`.
They are internally represented as linear equivs `M ≃ₗ[R] (ι →₀ R)`,
available as `Basis.repr`.
-/
structure Basis where
/-- `Basis.ofRepr` constructs a basis given an assignment of coordinates to each vector. -/
ofRepr ::
/-- `repr` is the linear equivalence sending a vector `x` to its coordinates:
the `c`s such that `x = ∑ i, c i`. -/
repr : M ≃ₗ[R] ι →₀ R
#align basis Basis
#align basis.repr Basis.repr
#align basis.of_repr Basis.ofRepr
end
instance uniqueBasis [Subsingleton R] : Unique (Basis ι R M) :=
⟨⟨⟨default⟩⟩, fun ⟨b⟩ => by rw [Subsingleton.elim b]⟩
#align unique_basis uniqueBasis
namespace Basis
instance : Inhabited (Basis ι R (ι →₀ R)) :=
⟨.ofRepr (LinearEquiv.refl _ _)⟩
variable (b b₁ : Basis ι R M) (i : ι) (c : R) (x : M)
section repr
theorem repr_injective : Injective (repr : Basis ι R M → M ≃ₗ[R] ι →₀ R) := fun f g h => by
cases f; cases g; congr
#align basis.repr_injective Basis.repr_injective
/-- `b i` is the `i`th basis vector. -/
instance instFunLike : FunLike (Basis ι R M) ι M where
coe b i := b.repr.symm (Finsupp.single i 1)
coe_injective' f g h := repr_injective <| LinearEquiv.symm_bijective.injective <|
LinearEquiv.toLinearMap_injective <| by ext; exact congr_fun h _
#align basis.fun_like Basis.instFunLike
@[simp]
theorem coe_ofRepr (e : M ≃ₗ[R] ι →₀ R) : ⇑(ofRepr e) = fun i => e.symm (Finsupp.single i 1) :=
rfl
#align basis.coe_of_repr Basis.coe_ofRepr
protected theorem injective [Nontrivial R] : Injective b :=
b.repr.symm.injective.comp fun _ _ => (Finsupp.single_left_inj (one_ne_zero : (1 : R) ≠ 0)).mp
#align basis.injective Basis.injective
theorem repr_symm_single_one : b.repr.symm (Finsupp.single i 1) = b i :=
rfl
#align basis.repr_symm_single_one Basis.repr_symm_single_one
theorem repr_symm_single : b.repr.symm (Finsupp.single i c) = c • b i :=
calc
b.repr.symm (Finsupp.single i c) = b.repr.symm (c • Finsupp.single i (1 : R)) := by
{ rw [Finsupp.smul_single', mul_one] }
_ = c • b i := by rw [LinearEquiv.map_smul, repr_symm_single_one]
#align basis.repr_symm_single Basis.repr_symm_single
@[simp]
theorem repr_self : b.repr (b i) = Finsupp.single i 1 :=
LinearEquiv.apply_symm_apply _ _
#align basis.repr_self Basis.repr_self
theorem repr_self_apply (j) [Decidable (i = j)] : b.repr (b i) j = if i = j then 1 else 0 := by
rw [repr_self, Finsupp.single_apply]
#align basis.repr_self_apply Basis.repr_self_apply
@[simp]
theorem repr_symm_apply (v) : b.repr.symm v = Finsupp.total ι M R b v :=
calc
b.repr.symm v = b.repr.symm (v.sum Finsupp.single) := by simp
_ = v.sum fun i vi => b.repr.symm (Finsupp.single i vi) := map_finsupp_sum ..
_ = Finsupp.total ι M R b v := by simp only [repr_symm_single, Finsupp.total_apply]
#align basis.repr_symm_apply Basis.repr_symm_apply
@[simp]
theorem coe_repr_symm : ↑b.repr.symm = Finsupp.total ι M R b :=
LinearMap.ext fun v => b.repr_symm_apply v
#align basis.coe_repr_symm Basis.coe_repr_symm
@[simp]
theorem repr_total (v) : b.repr (Finsupp.total _ _ _ b v) = v := by
rw [← b.coe_repr_symm]
exact b.repr.apply_symm_apply v
#align basis.repr_total Basis.repr_total
@[simp]
theorem total_repr : Finsupp.total _ _ _ b (b.repr x) = x := by
rw [← b.coe_repr_symm]
exact b.repr.symm_apply_apply x
#align basis.total_repr Basis.total_repr
theorem repr_range : LinearMap.range (b.repr : M →ₗ[R] ι →₀ R) = Finsupp.supported R R univ := by
rw [LinearEquiv.range, Finsupp.supported_univ]
#align basis.repr_range Basis.repr_range
theorem mem_span_repr_support (m : M) : m ∈ span R (b '' (b.repr m).support) :=
(Finsupp.mem_span_image_iff_total _).2 ⟨b.repr m, by simp [Finsupp.mem_supported_support]⟩
#align basis.mem_span_repr_support Basis.mem_span_repr_support
theorem repr_support_subset_of_mem_span (s : Set ι) {m : M}
(hm : m ∈ span R (b '' s)) : ↑(b.repr m).support ⊆ s := by
rcases (Finsupp.mem_span_image_iff_total _).1 hm with ⟨l, hl, rfl⟩
rwa [repr_total, ← Finsupp.mem_supported R l]
#align basis.repr_support_subset_of_mem_span Basis.repr_support_subset_of_mem_span
theorem mem_span_image {m : M} {s : Set ι} : m ∈ span R (b '' s) ↔ ↑(b.repr m).support ⊆ s :=
⟨repr_support_subset_of_mem_span _ _, fun h ↦
span_mono (image_subset _ h) (mem_span_repr_support b _)⟩
@[simp]
theorem self_mem_span_image [Nontrivial R] {i : ι} {s : Set ι} :
b i ∈ span R (b '' s) ↔ i ∈ s := by
simp [mem_span_image, Finsupp.support_single_ne_zero]
end repr
section Coord
/-- `b.coord i` is the linear function giving the `i`'th coordinate of a vector
with respect to the basis `b`.
`b.coord i` is an element of the dual space. In particular, for
finite-dimensional spaces it is the `ι`th basis vector of the dual space.
-/
@[simps!]
def coord : M →ₗ[R] R :=
Finsupp.lapply i ∘ₗ ↑b.repr
#align basis.coord Basis.coord
theorem forall_coord_eq_zero_iff {x : M} : (∀ i, b.coord i x = 0) ↔ x = 0 :=
Iff.trans (by simp only [b.coord_apply, DFunLike.ext_iff, Finsupp.zero_apply])
b.repr.map_eq_zero_iff
#align basis.forall_coord_eq_zero_iff Basis.forall_coord_eq_zero_iff
/-- The sum of the coordinates of an element `m : M` with respect to a basis. -/
noncomputable def sumCoords : M →ₗ[R] R :=
(Finsupp.lsum ℕ fun _ => LinearMap.id) ∘ₗ (b.repr : M →ₗ[R] ι →₀ R)
#align basis.sum_coords Basis.sumCoords
@[simp]
theorem coe_sumCoords : (b.sumCoords : M → R) = fun m => (b.repr m).sum fun _ => id :=
rfl
#align basis.coe_sum_coords Basis.coe_sumCoords
theorem coe_sumCoords_eq_finsum : (b.sumCoords : M → R) = fun m => ∑ᶠ i, b.coord i m := by
ext m
simp only [Basis.sumCoords, Basis.coord, Finsupp.lapply_apply, LinearMap.id_coe,
LinearEquiv.coe_coe, Function.comp_apply, Finsupp.coe_lsum, LinearMap.coe_comp,
finsum_eq_sum _ (b.repr m).finite_support, Finsupp.sum, Finset.finite_toSet_toFinset, id,
Finsupp.fun_support_eq]
#align basis.coe_sum_coords_eq_finsum Basis.coe_sumCoords_eq_finsum
@[simp high]
theorem coe_sumCoords_of_fintype [Fintype ι] : (b.sumCoords : M → R) = ∑ i, b.coord i := by
ext m
-- Porting note: - `eq_self_iff_true`
-- + `comp_apply` `LinearMap.coeFn_sum`
simp only [sumCoords, Finsupp.sum_fintype, LinearMap.id_coe, LinearEquiv.coe_coe, coord_apply,
id, Fintype.sum_apply, imp_true_iff, Finsupp.coe_lsum, LinearMap.coe_comp, comp_apply,
LinearMap.coeFn_sum]
#align basis.coe_sum_coords_of_fintype Basis.coe_sumCoords_of_fintype
@[simp]
theorem sumCoords_self_apply : b.sumCoords (b i) = 1 := by
simp only [Basis.sumCoords, LinearMap.id_coe, LinearEquiv.coe_coe, id, Basis.repr_self,
Function.comp_apply, Finsupp.coe_lsum, LinearMap.coe_comp, Finsupp.sum_single_index]
#align basis.sum_coords_self_apply Basis.sumCoords_self_apply
theorem dvd_coord_smul (i : ι) (m : M) (r : R) : r ∣ b.coord i (r • m) :=
⟨b.coord i m, by simp⟩
#align basis.dvd_coord_smul Basis.dvd_coord_smul
theorem coord_repr_symm (b : Basis ι R M) (i : ι) (f : ι →₀ R) :
b.coord i (b.repr.symm f) = f i := by
simp only [repr_symm_apply, coord_apply, repr_total]
#align basis.coord_repr_symm Basis.coord_repr_symm
end Coord
section Ext
variable {R₁ : Type*} [Semiring R₁] {σ : R →+* R₁} {σ' : R₁ →+* R}
variable [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
variable {M₁ : Type*} [AddCommMonoid M₁] [Module R₁ M₁]
/-- Two linear maps are equal if they are equal on basis vectors. -/
theorem ext {f₁ f₂ : M →ₛₗ[σ] M₁} (h : ∀ i, f₁ (b i) = f₂ (b i)) : f₁ = f₂ := by
ext x
rw [← b.total_repr x, Finsupp.total_apply, Finsupp.sum]
simp only [map_sum, LinearMap.map_smulₛₗ, h]
#align basis.ext Basis.ext
/-- Two linear equivs are equal if they are equal on basis vectors. -/
theorem ext' {f₁ f₂ : M ≃ₛₗ[σ] M₁} (h : ∀ i, f₁ (b i) = f₂ (b i)) : f₁ = f₂ := by
ext x
rw [← b.total_repr x, Finsupp.total_apply, Finsupp.sum]
simp only [map_sum, LinearEquiv.map_smulₛₗ, h]
#align basis.ext' Basis.ext'
/-- Two elements are equal iff their coordinates are equal. -/
theorem ext_elem_iff {x y : M} : x = y ↔ ∀ i, b.repr x i = b.repr y i := by
simp only [← DFunLike.ext_iff, EmbeddingLike.apply_eq_iff_eq]
#align basis.ext_elem_iff Basis.ext_elem_iff
alias ⟨_, _root_.Basis.ext_elem⟩ := ext_elem_iff
#align basis.ext_elem Basis.ext_elem
theorem repr_eq_iff {b : Basis ι R M} {f : M →ₗ[R] ι →₀ R} :
↑b.repr = f ↔ ∀ i, f (b i) = Finsupp.single i 1 :=
⟨fun h i => h ▸ b.repr_self i, fun h => b.ext fun i => (b.repr_self i).trans (h i).symm⟩
#align basis.repr_eq_iff Basis.repr_eq_iff
theorem repr_eq_iff' {b : Basis ι R M} {f : M ≃ₗ[R] ι →₀ R} :
b.repr = f ↔ ∀ i, f (b i) = Finsupp.single i 1 :=
⟨fun h i => h ▸ b.repr_self i, fun h => b.ext' fun i => (b.repr_self i).trans (h i).symm⟩
#align basis.repr_eq_iff' Basis.repr_eq_iff'
theorem apply_eq_iff {b : Basis ι R M} {x : M} {i : ι} : b i = x ↔ b.repr x = Finsupp.single i 1 :=
⟨fun h => h ▸ b.repr_self i, fun h => b.repr.injective ((b.repr_self i).trans h.symm)⟩
#align basis.apply_eq_iff Basis.apply_eq_iff
/-- An unbundled version of `repr_eq_iff` -/
theorem repr_apply_eq (f : M → ι → R) (hadd : ∀ x y, f (x + y) = f x + f y)
(hsmul : ∀ (c : R) (x : M), f (c • x) = c • f x) (f_eq : ∀ i, f (b i) = Finsupp.single i 1)
(x : M) (i : ι) : b.repr x i = f x i := by
let f_i : M →ₗ[R] R :=
{ toFun := fun x => f x i
-- Porting note(#12129): additional beta reduction needed
map_add' := fun _ _ => by beta_reduce; rw [hadd, Pi.add_apply]
map_smul' := fun _ _ => by simp [hsmul, Pi.smul_apply] }
have : Finsupp.lapply i ∘ₗ ↑b.repr = f_i := by
refine b.ext fun j => ?_
show b.repr (b j) i = f (b j) i
rw [b.repr_self, f_eq]
calc
b.repr x i = f_i x := by
{ rw [← this]
rfl }
_ = f x i := rfl
#align basis.repr_apply_eq Basis.repr_apply_eq
/-- Two bases are equal if they assign the same coordinates. -/
theorem eq_ofRepr_eq_repr {b₁ b₂ : Basis ι R M} (h : ∀ x i, b₁.repr x i = b₂.repr x i) : b₁ = b₂ :=
repr_injective <| by ext; apply h
#align basis.eq_of_repr_eq_repr Basis.eq_ofRepr_eq_repr
/-- Two bases are equal if their basis vectors are the same. -/
@[ext]
theorem eq_of_apply_eq {b₁ b₂ : Basis ι R M} : (∀ i, b₁ i = b₂ i) → b₁ = b₂ :=
DFunLike.ext _ _
#align basis.eq_of_apply_eq Basis.eq_of_apply_eq
end Ext
section Map
variable (f : M ≃ₗ[R] M')
/-- Apply the linear equivalence `f` to the basis vectors. -/
@[simps]
protected def map : Basis ι R M' :=
ofRepr (f.symm.trans b.repr)
#align basis.map Basis.map
@[simp]
theorem map_apply (i) : b.map f i = f (b i) :=
rfl
#align basis.map_apply Basis.map_apply
theorem coe_map : (b.map f : ι → M') = f ∘ b :=
rfl
end Map
section MapCoeffs
variable {R' : Type*} [Semiring R'] [Module R' M] (f : R ≃+* R')
(h : ∀ (c) (x : M), f c • x = c • x)
attribute [local instance] SMul.comp.isScalarTower
/-- If `R` and `R'` are isomorphic rings that act identically on a module `M`,
then a basis for `M` as `R`-module is also a basis for `M` as `R'`-module.
See also `Basis.algebraMapCoeffs` for the case where `f` is equal to `algebraMap`.
-/
@[simps (config := { simpRhs := true })]
def mapCoeffs : Basis ι R' M := by
letI : Module R' R := Module.compHom R (↑f.symm : R' →+* R)
haveI : IsScalarTower R' R M :=
{ smul_assoc := fun x y z => by
-- Porting note: `dsimp [(· • ·)]` is unavailable because
-- `HSMul.hsmul` becomes `SMul.smul`.
change (f.symm x * y) • z = x • (y • z)
rw [mul_smul, ← h, f.apply_symm_apply] }
exact ofRepr <| (b.repr.restrictScalars R').trans <|
Finsupp.mapRange.linearEquiv (Module.compHom.toLinearEquiv f.symm).symm
#align basis.map_coeffs Basis.mapCoeffs
theorem mapCoeffs_apply (i : ι) : b.mapCoeffs f h i = b i :=
apply_eq_iff.mpr <| by
-- Porting note: in Lean 3, these were automatically inferred from the definition of
-- `mapCoeffs`.
letI : Module R' R := Module.compHom R (↑f.symm : R' →+* R)
haveI : IsScalarTower R' R M :=
{ smul_assoc := fun x y z => by
-- Porting note: `dsimp [(· • ·)]` is unavailable because
-- `HSMul.hsmul` becomes `SMul.smul`.
change (f.symm x * y) • z = x • (y • z)
rw [mul_smul, ← h, f.apply_symm_apply] }
simp
#align basis.map_coeffs_apply Basis.mapCoeffs_apply
@[simp]
theorem coe_mapCoeffs : (b.mapCoeffs f h : ι → M) = b :=
funext <| b.mapCoeffs_apply f h
#align basis.coe_map_coeffs Basis.coe_mapCoeffs
end MapCoeffs
section Reindex
variable (b' : Basis ι' R M')
variable (e : ι ≃ ι')
/-- `b.reindex (e : ι ≃ ι')` is a basis indexed by `ι'` -/
def reindex : Basis ι' R M :=
.ofRepr (b.repr.trans (Finsupp.domLCongr e))
#align basis.reindex Basis.reindex
theorem reindex_apply (i' : ι') : b.reindex e i' = b (e.symm i') :=
show (b.repr.trans (Finsupp.domLCongr e)).symm (Finsupp.single i' 1) =
b.repr.symm (Finsupp.single (e.symm i') 1)
by rw [LinearEquiv.symm_trans_apply, Finsupp.domLCongr_symm, Finsupp.domLCongr_single]
#align basis.reindex_apply Basis.reindex_apply
@[simp]
theorem coe_reindex : (b.reindex e : ι' → M) = b ∘ e.symm :=
funext (b.reindex_apply e)
#align basis.coe_reindex Basis.coe_reindex
theorem repr_reindex_apply (i' : ι') : (b.reindex e).repr x i' = b.repr x (e.symm i') :=
show (Finsupp.domLCongr e : _ ≃ₗ[R] _) (b.repr x) i' = _ by simp
#align basis.repr_reindex_apply Basis.repr_reindex_apply
@[simp]
theorem repr_reindex : (b.reindex e).repr x = (b.repr x).mapDomain e :=
DFunLike.ext _ _ <| by simp [repr_reindex_apply]
#align basis.repr_reindex Basis.repr_reindex
@[simp]
theorem reindex_refl : b.reindex (Equiv.refl ι) = b :=
eq_of_apply_eq fun i => by simp
#align basis.reindex_refl Basis.reindex_refl
/-- `simp` can prove this as `Basis.coe_reindex` + `EquivLike.range_comp` -/
theorem range_reindex : Set.range (b.reindex e) = Set.range b := by
simp [coe_reindex, range_comp]
#align basis.range_reindex Basis.range_reindex
@[simp]
theorem sumCoords_reindex : (b.reindex e).sumCoords = b.sumCoords := by
ext x
simp only [coe_sumCoords, repr_reindex]
exact Finsupp.sum_mapDomain_index (fun _ => rfl) fun _ _ _ => rfl
#align basis.sum_coords_reindex Basis.sumCoords_reindex
/-- `b.reindex_range` is a basis indexed by `range b`, the basis vectors themselves. -/
def reindexRange : Basis (range b) R M :=
haveI := Classical.dec (Nontrivial R)
if h : Nontrivial R then
letI := h
b.reindex (Equiv.ofInjective b (Basis.injective b))
else
letI : Subsingleton R := not_nontrivial_iff_subsingleton.mp h
.ofRepr (Module.subsingletonEquiv R M (range b))
#align basis.reindex_range Basis.reindexRange
theorem reindexRange_self (i : ι) (h := Set.mem_range_self i) : b.reindexRange ⟨b i, h⟩ = b i := by
by_cases htr : Nontrivial R
· letI := htr
simp [htr, reindexRange, reindex_apply, Equiv.apply_ofInjective_symm b.injective,
Subtype.coe_mk]
· letI : Subsingleton R := not_nontrivial_iff_subsingleton.mp htr
letI := Module.subsingleton R M
simp [reindexRange, eq_iff_true_of_subsingleton]
#align basis.reindex_range_self Basis.reindexRange_self
theorem reindexRange_repr_self (i : ι) :
b.reindexRange.repr (b i) = Finsupp.single ⟨b i, mem_range_self i⟩ 1 :=
calc
b.reindexRange.repr (b i) = b.reindexRange.repr (b.reindexRange ⟨b i, mem_range_self i⟩) :=
congr_arg _ (b.reindexRange_self _ _).symm
_ = Finsupp.single ⟨b i, mem_range_self i⟩ 1 := b.reindexRange.repr_self _
#align basis.reindex_range_repr_self Basis.reindexRange_repr_self
@[simp]
theorem reindexRange_apply (x : range b) : b.reindexRange x = x := by
rcases x with ⟨bi, ⟨i, rfl⟩⟩
exact b.reindexRange_self i
#align basis.reindex_range_apply Basis.reindexRange_apply
theorem reindexRange_repr' (x : M) {bi : M} {i : ι} (h : b i = bi) :
b.reindexRange.repr x ⟨bi, ⟨i, h⟩⟩ = b.repr x i := by
nontriviality
subst h
apply (b.repr_apply_eq (fun x i => b.reindexRange.repr x ⟨b i, _⟩) _ _ _ x i).symm
· intro x y
ext i
simp only [Pi.add_apply, LinearEquiv.map_add, Finsupp.coe_add]
· intro c x
ext i
simp only [Pi.smul_apply, LinearEquiv.map_smul, Finsupp.coe_smul]
· intro i
ext j
simp only [reindexRange_repr_self]
apply Finsupp.single_apply_left (f := fun i => (⟨b i, _⟩ : Set.range b))
exact fun i j h => b.injective (Subtype.mk.inj h)
#align basis.reindex_range_repr' Basis.reindexRange_repr'
@[simp]
theorem reindexRange_repr (x : M) (i : ι) (h := Set.mem_range_self i) :
b.reindexRange.repr x ⟨b i, h⟩ = b.repr x i :=
b.reindexRange_repr' _ rfl
#align basis.reindex_range_repr Basis.reindexRange_repr
section Fintype
variable [Fintype ι] [DecidableEq M]
/-- `b.reindexFinsetRange` is a basis indexed by `Finset.univ.image b`,
the finite set of basis vectors themselves. -/
def reindexFinsetRange : Basis (Finset.univ.image b) R M :=
b.reindexRange.reindex ((Equiv.refl M).subtypeEquiv (by simp))
#align basis.reindex_finset_range Basis.reindexFinsetRange
theorem reindexFinsetRange_self (i : ι) (h := Finset.mem_image_of_mem b (Finset.mem_univ i)) :
b.reindexFinsetRange ⟨b i, h⟩ = b i := by
rw [reindexFinsetRange, reindex_apply, reindexRange_apply]
rfl
#align basis.reindex_finset_range_self Basis.reindexFinsetRange_self
@[simp]
theorem reindexFinsetRange_apply (x : Finset.univ.image b) : b.reindexFinsetRange x = x := by
rcases x with ⟨bi, hbi⟩
rcases Finset.mem_image.mp hbi with ⟨i, -, rfl⟩
exact b.reindexFinsetRange_self i
#align basis.reindex_finset_range_apply Basis.reindexFinsetRange_apply
theorem reindexFinsetRange_repr_self (i : ι) :
b.reindexFinsetRange.repr (b i) =
Finsupp.single ⟨b i, Finset.mem_image_of_mem b (Finset.mem_univ i)⟩ 1 := by
ext ⟨bi, hbi⟩
rw [reindexFinsetRange, repr_reindex, Finsupp.mapDomain_equiv_apply, reindexRange_repr_self]
-- Porting note: replaced a `convert; refl` with `simp`
simp [Finsupp.single_apply]
#align basis.reindex_finset_range_repr_self Basis.reindexFinsetRange_repr_self
@[simp]
theorem reindexFinsetRange_repr (x : M) (i : ι)
(h := Finset.mem_image_of_mem b (Finset.mem_univ i)) :
b.reindexFinsetRange.repr x ⟨b i, h⟩ = b.repr x i := by simp [reindexFinsetRange]
#align basis.reindex_finset_range_repr Basis.reindexFinsetRange_repr
end Fintype
end Reindex
protected theorem linearIndependent : LinearIndependent R b :=
linearIndependent_iff.mpr fun l hl =>
calc
l = b.repr (Finsupp.total _ _ _ b l) := (b.repr_total l).symm
_ = 0 := by rw [hl, LinearEquiv.map_zero]
#align basis.linear_independent Basis.linearIndependent
protected theorem ne_zero [Nontrivial R] (i) : b i ≠ 0 :=
b.linearIndependent.ne_zero i
#align basis.ne_zero Basis.ne_zero
protected theorem mem_span (x : M) : x ∈ span R (range b) :=
span_mono (image_subset_range _ _) (mem_span_repr_support b x)
#align basis.mem_span Basis.mem_span
@[simp]
protected theorem span_eq : span R (range b) = ⊤ :=
eq_top_iff.mpr fun x _ => b.mem_span x
#align basis.span_eq Basis.span_eq
theorem index_nonempty (b : Basis ι R M) [Nontrivial M] : Nonempty ι := by
obtain ⟨x, y, ne⟩ : ∃ x y : M, x ≠ y := Nontrivial.exists_pair_ne
obtain ⟨i, _⟩ := not_forall.mp (mt b.ext_elem_iff.2 ne)
exact ⟨i⟩
#align basis.index_nonempty Basis.index_nonempty
/-- If the submodule `P` has a basis, `x ∈ P` iff it is a linear combination of basis vectors. -/
theorem mem_submodule_iff {P : Submodule R M} (b : Basis ι R P) {x : M} :
x ∈ P ↔ ∃ c : ι →₀ R, x = Finsupp.sum c fun i x => x • (b i : M) := by
conv_lhs =>
rw [← P.range_subtype, ← Submodule.map_top, ← b.span_eq, Submodule.map_span, ← Set.range_comp,
← Finsupp.range_total]
simp [@eq_comm _ x, Function.comp, Finsupp.total_apply]
#align basis.mem_submodule_iff Basis.mem_submodule_iff
section Constr
variable (S : Type*) [Semiring S] [Module S M']
variable [SMulCommClass R S M']
/-- Construct a linear map given the value at the basis, called `Basis.constr b S f` where `b` is
a basis, `f` is the value of the linear map over the elements of the basis, and `S` is an
extra semiring (typically `S = R` or `S = ℕ`).
This definition is parameterized over an extra `Semiring S`,
such that `SMulCommClass R S M'` holds.
If `R` is commutative, you can set `S := R`; if `R` is not commutative,
you can recover an `AddEquiv` by setting `S := ℕ`.
See library note [bundled maps over different rings].
-/
def constr : (ι → M') ≃ₗ[S] M →ₗ[R] M' where
toFun f := (Finsupp.total M' M' R id).comp <| Finsupp.lmapDomain R R f ∘ₗ ↑b.repr
invFun f i := f (b i)
left_inv f := by
ext
simp
right_inv f := by
refine b.ext fun i => ?_
simp
map_add' f g := by
refine b.ext fun i => ?_
simp
map_smul' c f := by
refine b.ext fun i => ?_
simp
#align basis.constr Basis.constr
theorem constr_def (f : ι → M') :
constr (M' := M') b S f = Finsupp.total M' M' R id ∘ₗ Finsupp.lmapDomain R R f ∘ₗ ↑b.repr :=
rfl
#align basis.constr_def Basis.constr_def
theorem constr_apply (f : ι → M') (x : M) :
constr (M' := M') b S f x = (b.repr x).sum fun b a => a • f b := by
simp only [constr_def, LinearMap.comp_apply, Finsupp.lmapDomain_apply, Finsupp.total_apply]
rw [Finsupp.sum_mapDomain_index] <;> simp [add_smul]
#align basis.constr_apply Basis.constr_apply
@[simp]
theorem constr_basis (f : ι → M') (i : ι) : (constr (M' := M') b S f : M → M') (b i) = f i := by
simp [Basis.constr_apply, b.repr_self]
#align basis.constr_basis Basis.constr_basis
theorem constr_eq {g : ι → M'} {f : M →ₗ[R] M'} (h : ∀ i, g i = f (b i)) :
constr (M' := M') b S g = f :=
b.ext fun i => (b.constr_basis S g i).trans (h i)
#align basis.constr_eq Basis.constr_eq
theorem constr_self (f : M →ₗ[R] M') : (constr (M' := M') b S fun i => f (b i)) = f :=
b.constr_eq S fun _ => rfl
#align basis.constr_self Basis.constr_self
theorem constr_range {f : ι → M'} :
LinearMap.range (constr (M' := M') b S f) = span R (range f) := by
rw [b.constr_def S f, LinearMap.range_comp, LinearMap.range_comp, LinearEquiv.range, ←
Finsupp.supported_univ, Finsupp.lmapDomain_supported, ← Set.image_univ, ←
Finsupp.span_image_eq_map_total, Set.image_id]
#align basis.constr_range Basis.constr_range
@[simp]
theorem constr_comp (f : M' →ₗ[R] M') (v : ι → M') :
constr (M' := M') b S (f ∘ v) = f.comp (constr (M' := M') b S v) :=
b.ext fun i => by simp only [Basis.constr_basis, LinearMap.comp_apply, Function.comp]
#align basis.constr_comp Basis.constr_comp
end Constr
section Equiv
variable (b' : Basis ι' R M') (e : ι ≃ ι')
variable [AddCommMonoid M''] [Module R M'']
/-- If `b` is a basis for `M` and `b'` a basis for `M'`, and the index types are equivalent,
`b.equiv b' e` is a linear equivalence `M ≃ₗ[R] M'`, mapping `b i` to `b' (e i)`. -/
protected def equiv : M ≃ₗ[R] M' :=
b.repr.trans (b'.reindex e.symm).repr.symm
#align basis.equiv Basis.equiv
@[simp]
theorem equiv_apply : b.equiv b' e (b i) = b' (e i) := by simp [Basis.equiv]
#align basis.equiv_apply Basis.equiv_apply
@[simp]
theorem equiv_refl : b.equiv b (Equiv.refl ι) = LinearEquiv.refl R M :=
b.ext' fun i => by simp
#align basis.equiv_refl Basis.equiv_refl
@[simp]
theorem equiv_symm : (b.equiv b' e).symm = b'.equiv b e.symm :=
b'.ext' fun i => (b.equiv b' e).injective (by simp)
#align basis.equiv_symm Basis.equiv_symm
@[simp]
theorem equiv_trans {ι'' : Type*} (b'' : Basis ι'' R M'') (e : ι ≃ ι') (e' : ι' ≃ ι'') :
(b.equiv b' e).trans (b'.equiv b'' e') = b.equiv b'' (e.trans e') :=
b.ext' fun i => by simp
#align basis.equiv_trans Basis.equiv_trans
@[simp]
theorem map_equiv (b : Basis ι R M) (b' : Basis ι' R M') (e : ι ≃ ι') :
b.map (b.equiv b' e) = b'.reindex e.symm := by
ext i
simp
#align basis.map_equiv Basis.map_equiv
end Equiv
section Prod
variable (b' : Basis ι' R M')
/-- `Basis.prod` maps an `ι`-indexed basis for `M` and an `ι'`-indexed basis for `M'`
to an `ι ⊕ ι'`-index basis for `M × M'`.
For the specific case of `R × R`, see also `Basis.finTwoProd`. -/
protected def prod : Basis (Sum ι ι') R (M × M') :=
ofRepr ((b.repr.prod b'.repr).trans (Finsupp.sumFinsuppLEquivProdFinsupp R).symm)
#align basis.prod Basis.prod
@[simp]
theorem prod_repr_inl (x) (i) : (b.prod b').repr x (Sum.inl i) = b.repr x.1 i :=
rfl
#align basis.prod_repr_inl Basis.prod_repr_inl
@[simp]
theorem prod_repr_inr (x) (i) : (b.prod b').repr x (Sum.inr i) = b'.repr x.2 i :=
rfl
#align basis.prod_repr_inr Basis.prod_repr_inr
theorem prod_apply_inl_fst (i) : (b.prod b' (Sum.inl i)).1 = b i :=
b.repr.injective <| by
ext j
simp only [Basis.prod, Basis.coe_ofRepr, LinearEquiv.symm_trans_apply, LinearEquiv.prod_symm,
LinearEquiv.prod_apply, b.repr.apply_symm_apply, LinearEquiv.symm_symm, repr_self,
Equiv.toFun_as_coe, Finsupp.fst_sumFinsuppLEquivProdFinsupp]
apply Finsupp.single_apply_left Sum.inl_injective
#align basis.prod_apply_inl_fst Basis.prod_apply_inl_fst
theorem prod_apply_inr_fst (i) : (b.prod b' (Sum.inr i)).1 = 0 :=
b.repr.injective <| by
ext i
simp only [Basis.prod, Basis.coe_ofRepr, LinearEquiv.symm_trans_apply, LinearEquiv.prod_symm,
LinearEquiv.prod_apply, b.repr.apply_symm_apply, LinearEquiv.symm_symm, repr_self,
Equiv.toFun_as_coe, Finsupp.fst_sumFinsuppLEquivProdFinsupp, LinearEquiv.map_zero,
Finsupp.zero_apply]
apply Finsupp.single_eq_of_ne Sum.inr_ne_inl
#align basis.prod_apply_inr_fst Basis.prod_apply_inr_fst
theorem prod_apply_inl_snd (i) : (b.prod b' (Sum.inl i)).2 = 0 :=
b'.repr.injective <| by
ext j
simp only [Basis.prod, Basis.coe_ofRepr, LinearEquiv.symm_trans_apply, LinearEquiv.prod_symm,
LinearEquiv.prod_apply, b'.repr.apply_symm_apply, LinearEquiv.symm_symm, repr_self,
Equiv.toFun_as_coe, Finsupp.snd_sumFinsuppLEquivProdFinsupp, LinearEquiv.map_zero,
Finsupp.zero_apply]
apply Finsupp.single_eq_of_ne Sum.inl_ne_inr
#align basis.prod_apply_inl_snd Basis.prod_apply_inl_snd
theorem prod_apply_inr_snd (i) : (b.prod b' (Sum.inr i)).2 = b' i :=
b'.repr.injective <| by
ext i
simp only [Basis.prod, Basis.coe_ofRepr, LinearEquiv.symm_trans_apply, LinearEquiv.prod_symm,
LinearEquiv.prod_apply, b'.repr.apply_symm_apply, LinearEquiv.symm_symm, repr_self,
Equiv.toFun_as_coe, Finsupp.snd_sumFinsuppLEquivProdFinsupp]
apply Finsupp.single_apply_left Sum.inr_injective
#align basis.prod_apply_inr_snd Basis.prod_apply_inr_snd
@[simp]
theorem prod_apply (i) :
b.prod b' i = Sum.elim (LinearMap.inl R M M' ∘ b) (LinearMap.inr R M M' ∘ b') i := by
ext <;> cases i <;>
simp only [prod_apply_inl_fst, Sum.elim_inl, LinearMap.inl_apply, prod_apply_inr_fst,
Sum.elim_inr, LinearMap.inr_apply, prod_apply_inl_snd, prod_apply_inr_snd, Function.comp]
#align basis.prod_apply Basis.prod_apply
end Prod
section NoZeroSMulDivisors
-- Can't be an instance because the basis can't be inferred.
protected theorem noZeroSMulDivisors [NoZeroDivisors R] (b : Basis ι R M) :
NoZeroSMulDivisors R M :=
⟨fun {c x} hcx => by
exact or_iff_not_imp_right.mpr fun hx => by
rw [← b.total_repr x, ← LinearMap.map_smul] at hcx
have := linearIndependent_iff.mp b.linearIndependent (c • b.repr x) hcx
rw [smul_eq_zero] at this
exact this.resolve_right fun hr => hx (b.repr.map_eq_zero_iff.mp hr)⟩
#align basis.no_zero_smul_divisors Basis.noZeroSMulDivisors
protected theorem smul_eq_zero [NoZeroDivisors R] (b : Basis ι R M) {c : R} {x : M} :
c • x = 0 ↔ c = 0 ∨ x = 0 :=
@smul_eq_zero _ _ _ _ _ b.noZeroSMulDivisors _ _
#align basis.smul_eq_zero Basis.smul_eq_zero
theorem eq_bot_of_rank_eq_zero [NoZeroDivisors R] (b : Basis ι R M) (N : Submodule R M)
(rank_eq : ∀ {m : ℕ} (v : Fin m → N), LinearIndependent R ((↑) ∘ v : Fin m → M) → m = 0) :
N = ⊥ := by
rw [Submodule.eq_bot_iff]
intro x hx
contrapose! rank_eq with x_ne
refine ⟨1, fun _ => ⟨x, hx⟩, ?_, one_ne_zero⟩
rw [Fintype.linearIndependent_iff]
rintro g sum_eq i
cases' i with _ hi
simp only [Function.const_apply, Fin.default_eq_zero, Submodule.coe_mk, Finset.univ_unique,
Function.comp_const, Finset.sum_singleton] at sum_eq
convert (b.smul_eq_zero.mp sum_eq).resolve_right x_ne
#align eq_bot_of_rank_eq_zero Basis.eq_bot_of_rank_eq_zero
end NoZeroSMulDivisors
section Singleton
/-- `Basis.singleton ι R` is the basis sending the unique element of `ι` to `1 : R`. -/
protected def singleton (ι R : Type*) [Unique ι] [Semiring R] : Basis ι R R :=
ofRepr
{ toFun := fun x => Finsupp.single default x
invFun := fun f => f default
left_inv := fun x => by simp
right_inv := fun f => Finsupp.unique_ext (by simp)
map_add' := fun x y => by simp
map_smul' := fun c x => by simp }
#align basis.singleton Basis.singleton
@[simp]
theorem singleton_apply (ι R : Type*) [Unique ι] [Semiring R] (i) : Basis.singleton ι R i = 1 :=
apply_eq_iff.mpr (by simp [Basis.singleton])
#align basis.singleton_apply Basis.singleton_apply
@[simp]
theorem singleton_repr (ι R : Type*) [Unique ι] [Semiring R] (x i) :
(Basis.singleton ι R).repr x i = x := by simp [Basis.singleton, Unique.eq_default i]
#align basis.singleton_repr Basis.singleton_repr
theorem basis_singleton_iff {R M : Type*} [Ring R] [Nontrivial R] [AddCommGroup M] [Module R M]
[NoZeroSMulDivisors R M] (ι : Type*) [Unique ι] :
Nonempty (Basis ι R M) ↔ ∃ x ≠ 0, ∀ y : M, ∃ r : R, r • x = y := by
constructor
· rintro ⟨b⟩
refine ⟨b default, b.linearIndependent.ne_zero _, ?_⟩
simpa [span_singleton_eq_top_iff, Set.range_unique] using b.span_eq
· rintro ⟨x, nz, w⟩
refine ⟨ofRepr <| LinearEquiv.symm
{ toFun := fun f => f default • x
invFun := fun y => Finsupp.single default (w y).choose
left_inv := fun f => Finsupp.unique_ext ?_
right_inv := fun y => ?_
map_add' := fun y z => ?_
map_smul' := fun c y => ?_ }⟩
· simp [Finsupp.add_apply, add_smul]
· simp only [Finsupp.coe_smul, Pi.smul_apply, RingHom.id_apply]
rw [← smul_assoc]
· refine smul_left_injective _ nz ?_
simp only [Finsupp.single_eq_same]
exact (w (f default • x)).choose_spec
· simp only [Finsupp.single_eq_same]
exact (w y).choose_spec
#align basis.basis_singleton_iff Basis.basis_singleton_iff
end Singleton
section Empty
variable (M)
/-- If `M` is a subsingleton and `ι` is empty, this is the unique `ι`-indexed basis for `M`. -/
protected def empty [Subsingleton M] [IsEmpty ι] : Basis ι R M :=
ofRepr 0
#align basis.empty Basis.empty
instance emptyUnique [Subsingleton M] [IsEmpty ι] : Unique (Basis ι R M) where
default := Basis.empty M
uniq := fun _ => congr_arg ofRepr <| Subsingleton.elim _ _
#align basis.empty_unique Basis.emptyUnique
end Empty
end Basis
section Fintype
open Basis
open Fintype
/-- A module over `R` with a finite basis is linearly equivalent to functions from its basis to `R`.
-/
def Basis.equivFun [Finite ι] (b : Basis ι R M) : M ≃ₗ[R] ι → R :=
LinearEquiv.trans b.repr
({ Finsupp.equivFunOnFinite with
toFun := (↑)
map_add' := Finsupp.coe_add
map_smul' := Finsupp.coe_smul } :
(ι →₀ R) ≃ₗ[R] ι → R)
#align basis.equiv_fun Basis.equivFun
/-- A module over a finite ring that admits a finite basis is finite. -/
def Module.fintypeOfFintype [Fintype ι] (b : Basis ι R M) [Fintype R] : Fintype M :=
haveI := Classical.decEq ι
Fintype.ofEquiv _ b.equivFun.toEquiv.symm
#align module.fintype_of_fintype Module.fintypeOfFintype
theorem Module.card_fintype [Fintype ι] (b : Basis ι R M) [Fintype R] [Fintype M] :
card M = card R ^ card ι := by
classical
calc
card M = card (ι → R) := card_congr b.equivFun.toEquiv
_ = card R ^ card ι := card_fun
#align module.card_fintype Module.card_fintype
/-- Given a basis `v` indexed by `ι`, the canonical linear equivalence between `ι → R` and `M` maps
a function `x : ι → R` to the linear combination `∑_i x i • v i`. -/
@[simp]
| Mathlib/LinearAlgebra/Basis.lean | 908 | 910 | theorem Basis.equivFun_symm_apply [Fintype ι] (b : Basis ι R M) (x : ι → R) :
b.equivFun.symm x = ∑ i, x i • b i := by |
simp [Basis.equivFun, Finsupp.total_apply, Finsupp.sum_fintype, Finsupp.equivFunOnFinite]
|
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Integral.Bochner
import Mathlib.MeasureTheory.Group.Measure
#align_import measure_theory.group.integration from "leanprover-community/mathlib"@"ec247d43814751ffceb33b758e8820df2372bf6f"
/-!
# Bochner Integration on Groups
We develop properties of integrals with a group as domain.
This file contains properties about integrability and Bochner integration.
-/
namespace MeasureTheory
open Measure TopologicalSpace
open scoped ENNReal
variable {𝕜 M α G E F : Type*} [MeasurableSpace G]
variable [NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E] [NormedAddCommGroup F]
variable {μ : Measure G} {f : G → E} {g : G}
section MeasurableInv
variable [Group G] [MeasurableInv G]
@[to_additive]
theorem Integrable.comp_inv [IsInvInvariant μ] {f : G → F} (hf : Integrable f μ) :
Integrable (fun t => f t⁻¹) μ :=
(hf.mono_measure (map_inv_eq_self μ).le).comp_measurable measurable_inv
#align measure_theory.integrable.comp_inv MeasureTheory.Integrable.comp_inv
#align measure_theory.integrable.comp_neg MeasureTheory.Integrable.comp_neg
@[to_additive]
| Mathlib/MeasureTheory/Group/Integral.lean | 40 | 43 | theorem integral_inv_eq_self (f : G → E) (μ : Measure G) [IsInvInvariant μ] :
∫ x, f x⁻¹ ∂μ = ∫ x, f x ∂μ := by |
have h : MeasurableEmbedding fun x : G => x⁻¹ := (MeasurableEquiv.inv G).measurableEmbedding
rw [← h.integral_map, map_inv_eq_self]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Real
#align_import analysis.special_functions.pow.nnreal from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-!
# Power function on `ℝ≥0` and `ℝ≥0∞`
We construct the power functions `x ^ y` where
* `x` is a nonnegative real number and `y` is a real number;
* `x` is a number from `[0, +∞]` (a.k.a. `ℝ≥0∞`) and `y` is a real number.
We also prove basic properties of these functions.
-/
noncomputable section
open scoped Classical
open Real NNReal ENNReal ComplexConjugate
open Finset Function Set
namespace NNReal
variable {w x y z : ℝ}
/-- The nonnegative real power function `x^y`, defined for `x : ℝ≥0` and `y : ℝ` as the
restriction of the real power function. For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`,
one sets `0 ^ 0 = 1` and `0 ^ y = 0` for `y ≠ 0`. -/
noncomputable def rpow (x : ℝ≥0) (y : ℝ) : ℝ≥0 :=
⟨(x : ℝ) ^ y, Real.rpow_nonneg x.2 y⟩
#align nnreal.rpow NNReal.rpow
noncomputable instance : Pow ℝ≥0 ℝ :=
⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x : ℝ≥0) (y : ℝ) : rpow x y = x ^ y :=
rfl
#align nnreal.rpow_eq_pow NNReal.rpow_eq_pow
@[simp, norm_cast]
theorem coe_rpow (x : ℝ≥0) (y : ℝ) : ((x ^ y : ℝ≥0) : ℝ) = (x : ℝ) ^ y :=
rfl
#align nnreal.coe_rpow NNReal.coe_rpow
@[simp]
theorem rpow_zero (x : ℝ≥0) : x ^ (0 : ℝ) = 1 :=
NNReal.eq <| Real.rpow_zero _
#align nnreal.rpow_zero NNReal.rpow_zero
@[simp]
theorem rpow_eq_zero_iff {x : ℝ≥0} {y : ℝ} : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
rw [← NNReal.coe_inj, coe_rpow, ← NNReal.coe_eq_zero]
exact Real.rpow_eq_zero_iff_of_nonneg x.2
#align nnreal.rpow_eq_zero_iff NNReal.rpow_eq_zero_iff
@[simp]
theorem zero_rpow {x : ℝ} (h : x ≠ 0) : (0 : ℝ≥0) ^ x = 0 :=
NNReal.eq <| Real.zero_rpow h
#align nnreal.zero_rpow NNReal.zero_rpow
@[simp]
theorem rpow_one (x : ℝ≥0) : x ^ (1 : ℝ) = x :=
NNReal.eq <| Real.rpow_one _
#align nnreal.rpow_one NNReal.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ≥0) ^ x = 1 :=
NNReal.eq <| Real.one_rpow _
#align nnreal.one_rpow NNReal.one_rpow
theorem rpow_add {x : ℝ≥0} (hx : x ≠ 0) (y z : ℝ) : x ^ (y + z) = x ^ y * x ^ z :=
NNReal.eq <| Real.rpow_add (pos_iff_ne_zero.2 hx) _ _
#align nnreal.rpow_add NNReal.rpow_add
theorem rpow_add' (x : ℝ≥0) {y z : ℝ} (h : y + z ≠ 0) : x ^ (y + z) = x ^ y * x ^ z :=
NNReal.eq <| Real.rpow_add' x.2 h
#align nnreal.rpow_add' NNReal.rpow_add'
/-- Variant of `NNReal.rpow_add'` that avoids having to prove `y + z = w` twice. -/
lemma rpow_of_add_eq (x : ℝ≥0) (hw : w ≠ 0) (h : y + z = w) : x ^ w = x ^ y * x ^ z := by
rw [← h, rpow_add']; rwa [h]
theorem rpow_mul (x : ℝ≥0) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z :=
NNReal.eq <| Real.rpow_mul x.2 y z
#align nnreal.rpow_mul NNReal.rpow_mul
theorem rpow_neg (x : ℝ≥0) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ :=
NNReal.eq <| Real.rpow_neg x.2 _
#align nnreal.rpow_neg NNReal.rpow_neg
theorem rpow_neg_one (x : ℝ≥0) : x ^ (-1 : ℝ) = x⁻¹ := by simp [rpow_neg]
#align nnreal.rpow_neg_one NNReal.rpow_neg_one
theorem rpow_sub {x : ℝ≥0} (hx : x ≠ 0) (y z : ℝ) : x ^ (y - z) = x ^ y / x ^ z :=
NNReal.eq <| Real.rpow_sub (pos_iff_ne_zero.2 hx) y z
#align nnreal.rpow_sub NNReal.rpow_sub
theorem rpow_sub' (x : ℝ≥0) {y z : ℝ} (h : y - z ≠ 0) : x ^ (y - z) = x ^ y / x ^ z :=
NNReal.eq <| Real.rpow_sub' x.2 h
#align nnreal.rpow_sub' NNReal.rpow_sub'
theorem rpow_inv_rpow_self {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y) ^ (1 / y) = x := by
field_simp [← rpow_mul]
#align nnreal.rpow_inv_rpow_self NNReal.rpow_inv_rpow_self
theorem rpow_self_rpow_inv {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ (1 / y)) ^ y = x := by
field_simp [← rpow_mul]
#align nnreal.rpow_self_rpow_inv NNReal.rpow_self_rpow_inv
theorem inv_rpow (x : ℝ≥0) (y : ℝ) : x⁻¹ ^ y = (x ^ y)⁻¹ :=
NNReal.eq <| Real.inv_rpow x.2 y
#align nnreal.inv_rpow NNReal.inv_rpow
theorem div_rpow (x y : ℝ≥0) (z : ℝ) : (x / y) ^ z = x ^ z / y ^ z :=
NNReal.eq <| Real.div_rpow x.2 y.2 z
#align nnreal.div_rpow NNReal.div_rpow
theorem sqrt_eq_rpow (x : ℝ≥0) : sqrt x = x ^ (1 / (2 : ℝ)) := by
refine NNReal.eq ?_
push_cast
exact Real.sqrt_eq_rpow x.1
#align nnreal.sqrt_eq_rpow NNReal.sqrt_eq_rpow
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ≥0) (n : ℕ) : x ^ (n : ℝ) = x ^ n :=
NNReal.eq <| by simpa only [coe_rpow, coe_pow] using Real.rpow_natCast x n
#align nnreal.rpow_nat_cast NNReal.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
lemma rpow_ofNat (x : ℝ≥0) (n : ℕ) [n.AtLeastTwo] :
x ^ (no_index (OfNat.ofNat n) : ℝ) = x ^ (OfNat.ofNat n : ℕ) :=
rpow_natCast x n
theorem rpow_two (x : ℝ≥0) : x ^ (2 : ℝ) = x ^ 2 := rpow_ofNat x 2
#align nnreal.rpow_two NNReal.rpow_two
theorem mul_rpow {x y : ℝ≥0} {z : ℝ} : (x * y) ^ z = x ^ z * y ^ z :=
NNReal.eq <| Real.mul_rpow x.2 y.2
#align nnreal.mul_rpow NNReal.mul_rpow
/-- `rpow` as a `MonoidHom`-/
@[simps]
def rpowMonoidHom (r : ℝ) : ℝ≥0 →* ℝ≥0 where
toFun := (· ^ r)
map_one' := one_rpow _
map_mul' _x _y := mul_rpow
/-- `rpow` variant of `List.prod_map_pow` for `ℝ≥0`-/
theorem list_prod_map_rpow (l : List ℝ≥0) (r : ℝ) :
(l.map (· ^ r)).prod = l.prod ^ r :=
l.prod_hom (rpowMonoidHom r)
theorem list_prod_map_rpow' {ι} (l : List ι) (f : ι → ℝ≥0) (r : ℝ) :
(l.map (f · ^ r)).prod = (l.map f).prod ^ r := by
rw [← list_prod_map_rpow, List.map_map]; rfl
/-- `rpow` version of `Multiset.prod_map_pow` for `ℝ≥0`. -/
lemma multiset_prod_map_rpow {ι} (s : Multiset ι) (f : ι → ℝ≥0) (r : ℝ) :
(s.map (f · ^ r)).prod = (s.map f).prod ^ r :=
s.prod_hom' (rpowMonoidHom r) _
/-- `rpow` version of `Finset.prod_pow` for `ℝ≥0`. -/
lemma finset_prod_rpow {ι} (s : Finset ι) (f : ι → ℝ≥0) (r : ℝ) :
(∏ i ∈ s, f i ^ r) = (∏ i ∈ s, f i) ^ r :=
multiset_prod_map_rpow _ _ _
-- note: these don't really belong here, but they're much easier to prove in terms of the above
section Real
/-- `rpow` version of `List.prod_map_pow` for `Real`. -/
theorem _root_.Real.list_prod_map_rpow (l : List ℝ) (hl : ∀ x ∈ l, (0 : ℝ) ≤ x) (r : ℝ) :
(l.map (· ^ r)).prod = l.prod ^ r := by
lift l to List ℝ≥0 using hl
have := congr_arg ((↑) : ℝ≥0 → ℝ) (NNReal.list_prod_map_rpow l r)
push_cast at this
rw [List.map_map] at this ⊢
exact mod_cast this
theorem _root_.Real.list_prod_map_rpow' {ι} (l : List ι) (f : ι → ℝ)
(hl : ∀ i ∈ l, (0 : ℝ) ≤ f i) (r : ℝ) :
(l.map (f · ^ r)).prod = (l.map f).prod ^ r := by
rw [← Real.list_prod_map_rpow (l.map f) _ r, List.map_map]
· rfl
simpa using hl
/-- `rpow` version of `Multiset.prod_map_pow`. -/
theorem _root_.Real.multiset_prod_map_rpow {ι} (s : Multiset ι) (f : ι → ℝ)
(hs : ∀ i ∈ s, (0 : ℝ) ≤ f i) (r : ℝ) :
(s.map (f · ^ r)).prod = (s.map f).prod ^ r := by
induction' s using Quotient.inductionOn with l
simpa using Real.list_prod_map_rpow' l f hs r
/-- `rpow` version of `Finset.prod_pow`. -/
theorem _root_.Real.finset_prod_rpow
{ι} (s : Finset ι) (f : ι → ℝ) (hs : ∀ i ∈ s, 0 ≤ f i) (r : ℝ) :
(∏ i ∈ s, f i ^ r) = (∏ i ∈ s, f i) ^ r :=
Real.multiset_prod_map_rpow s.val f hs r
end Real
@[gcongr] theorem rpow_le_rpow {x y : ℝ≥0} {z : ℝ} (h₁ : x ≤ y) (h₂ : 0 ≤ z) : x ^ z ≤ y ^ z :=
Real.rpow_le_rpow x.2 h₁ h₂
#align nnreal.rpow_le_rpow NNReal.rpow_le_rpow
@[gcongr] theorem rpow_lt_rpow {x y : ℝ≥0} {z : ℝ} (h₁ : x < y) (h₂ : 0 < z) : x ^ z < y ^ z :=
Real.rpow_lt_rpow x.2 h₁ h₂
#align nnreal.rpow_lt_rpow NNReal.rpow_lt_rpow
theorem rpow_lt_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ z < y ^ z ↔ x < y :=
Real.rpow_lt_rpow_iff x.2 y.2 hz
#align nnreal.rpow_lt_rpow_iff NNReal.rpow_lt_rpow_iff
theorem rpow_le_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ z ≤ y ^ z ↔ x ≤ y :=
Real.rpow_le_rpow_iff x.2 y.2 hz
#align nnreal.rpow_le_rpow_iff NNReal.rpow_le_rpow_iff
theorem le_rpow_one_div_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ≤ y ^ (1 / z) ↔ x ^ z ≤ y := by
rw [← rpow_le_rpow_iff hz, rpow_self_rpow_inv hz.ne']
#align nnreal.le_rpow_one_div_iff NNReal.le_rpow_one_div_iff
theorem rpow_one_div_le_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ (1 / z) ≤ y ↔ x ≤ y ^ z := by
rw [← rpow_le_rpow_iff hz, rpow_self_rpow_inv hz.ne']
#align nnreal.rpow_one_div_le_iff NNReal.rpow_one_div_le_iff
@[gcongr] theorem rpow_lt_rpow_of_exponent_lt {x : ℝ≥0} {y z : ℝ} (hx : 1 < x) (hyz : y < z) :
x ^ y < x ^ z :=
Real.rpow_lt_rpow_of_exponent_lt hx hyz
#align nnreal.rpow_lt_rpow_of_exponent_lt NNReal.rpow_lt_rpow_of_exponent_lt
@[gcongr] theorem rpow_le_rpow_of_exponent_le {x : ℝ≥0} {y z : ℝ} (hx : 1 ≤ x) (hyz : y ≤ z) :
x ^ y ≤ x ^ z :=
Real.rpow_le_rpow_of_exponent_le hx hyz
#align nnreal.rpow_le_rpow_of_exponent_le NNReal.rpow_le_rpow_of_exponent_le
theorem rpow_lt_rpow_of_exponent_gt {x : ℝ≥0} {y z : ℝ} (hx0 : 0 < x) (hx1 : x < 1) (hyz : z < y) :
x ^ y < x ^ z :=
Real.rpow_lt_rpow_of_exponent_gt hx0 hx1 hyz
#align nnreal.rpow_lt_rpow_of_exponent_gt NNReal.rpow_lt_rpow_of_exponent_gt
theorem rpow_le_rpow_of_exponent_ge {x : ℝ≥0} {y z : ℝ} (hx0 : 0 < x) (hx1 : x ≤ 1) (hyz : z ≤ y) :
x ^ y ≤ x ^ z :=
Real.rpow_le_rpow_of_exponent_ge hx0 hx1 hyz
#align nnreal.rpow_le_rpow_of_exponent_ge NNReal.rpow_le_rpow_of_exponent_ge
theorem rpow_pos {p : ℝ} {x : ℝ≥0} (hx_pos : 0 < x) : 0 < x ^ p := by
have rpow_pos_of_nonneg : ∀ {p : ℝ}, 0 < p → 0 < x ^ p := by
intro p hp_pos
rw [← zero_rpow hp_pos.ne']
exact rpow_lt_rpow hx_pos hp_pos
rcases lt_trichotomy (0 : ℝ) p with (hp_pos | rfl | hp_neg)
· exact rpow_pos_of_nonneg hp_pos
· simp only [zero_lt_one, rpow_zero]
· rw [← neg_neg p, rpow_neg, inv_pos]
exact rpow_pos_of_nonneg (neg_pos.mpr hp_neg)
#align nnreal.rpow_pos NNReal.rpow_pos
theorem rpow_lt_one {x : ℝ≥0} {z : ℝ} (hx1 : x < 1) (hz : 0 < z) : x ^ z < 1 :=
Real.rpow_lt_one (coe_nonneg x) hx1 hz
#align nnreal.rpow_lt_one NNReal.rpow_lt_one
theorem rpow_le_one {x : ℝ≥0} {z : ℝ} (hx2 : x ≤ 1) (hz : 0 ≤ z) : x ^ z ≤ 1 :=
Real.rpow_le_one x.2 hx2 hz
#align nnreal.rpow_le_one NNReal.rpow_le_one
theorem rpow_lt_one_of_one_lt_of_neg {x : ℝ≥0} {z : ℝ} (hx : 1 < x) (hz : z < 0) : x ^ z < 1 :=
Real.rpow_lt_one_of_one_lt_of_neg hx hz
#align nnreal.rpow_lt_one_of_one_lt_of_neg NNReal.rpow_lt_one_of_one_lt_of_neg
theorem rpow_le_one_of_one_le_of_nonpos {x : ℝ≥0} {z : ℝ} (hx : 1 ≤ x) (hz : z ≤ 0) : x ^ z ≤ 1 :=
Real.rpow_le_one_of_one_le_of_nonpos hx hz
#align nnreal.rpow_le_one_of_one_le_of_nonpos NNReal.rpow_le_one_of_one_le_of_nonpos
theorem one_lt_rpow {x : ℝ≥0} {z : ℝ} (hx : 1 < x) (hz : 0 < z) : 1 < x ^ z :=
Real.one_lt_rpow hx hz
#align nnreal.one_lt_rpow NNReal.one_lt_rpow
theorem one_le_rpow {x : ℝ≥0} {z : ℝ} (h : 1 ≤ x) (h₁ : 0 ≤ z) : 1 ≤ x ^ z :=
Real.one_le_rpow h h₁
#align nnreal.one_le_rpow NNReal.one_le_rpow
theorem one_lt_rpow_of_pos_of_lt_one_of_neg {x : ℝ≥0} {z : ℝ} (hx1 : 0 < x) (hx2 : x < 1)
(hz : z < 0) : 1 < x ^ z :=
Real.one_lt_rpow_of_pos_of_lt_one_of_neg hx1 hx2 hz
#align nnreal.one_lt_rpow_of_pos_of_lt_one_of_neg NNReal.one_lt_rpow_of_pos_of_lt_one_of_neg
theorem one_le_rpow_of_pos_of_le_one_of_nonpos {x : ℝ≥0} {z : ℝ} (hx1 : 0 < x) (hx2 : x ≤ 1)
(hz : z ≤ 0) : 1 ≤ x ^ z :=
Real.one_le_rpow_of_pos_of_le_one_of_nonpos hx1 hx2 hz
#align nnreal.one_le_rpow_of_pos_of_le_one_of_nonpos NNReal.one_le_rpow_of_pos_of_le_one_of_nonpos
theorem rpow_le_self_of_le_one {x : ℝ≥0} {z : ℝ} (hx : x ≤ 1) (h_one_le : 1 ≤ z) : x ^ z ≤ x := by
rcases eq_bot_or_bot_lt x with (rfl | (h : 0 < x))
· have : z ≠ 0 := by linarith
simp [this]
nth_rw 2 [← NNReal.rpow_one x]
exact NNReal.rpow_le_rpow_of_exponent_ge h hx h_one_le
#align nnreal.rpow_le_self_of_le_one NNReal.rpow_le_self_of_le_one
theorem rpow_left_injective {x : ℝ} (hx : x ≠ 0) : Function.Injective fun y : ℝ≥0 => y ^ x :=
fun y z hyz => by simpa only [rpow_inv_rpow_self hx] using congr_arg (fun y => y ^ (1 / x)) hyz
#align nnreal.rpow_left_injective NNReal.rpow_left_injective
theorem rpow_eq_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x ^ z = y ^ z ↔ x = y :=
(rpow_left_injective hz).eq_iff
#align nnreal.rpow_eq_rpow_iff NNReal.rpow_eq_rpow_iff
theorem rpow_left_surjective {x : ℝ} (hx : x ≠ 0) : Function.Surjective fun y : ℝ≥0 => y ^ x :=
fun y => ⟨y ^ x⁻¹, by simp_rw [← rpow_mul, _root_.inv_mul_cancel hx, rpow_one]⟩
#align nnreal.rpow_left_surjective NNReal.rpow_left_surjective
theorem rpow_left_bijective {x : ℝ} (hx : x ≠ 0) : Function.Bijective fun y : ℝ≥0 => y ^ x :=
⟨rpow_left_injective hx, rpow_left_surjective hx⟩
#align nnreal.rpow_left_bijective NNReal.rpow_left_bijective
theorem eq_rpow_one_div_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x = y ^ (1 / z) ↔ x ^ z = y := by
rw [← rpow_eq_rpow_iff hz, rpow_self_rpow_inv hz]
#align nnreal.eq_rpow_one_div_iff NNReal.eq_rpow_one_div_iff
theorem rpow_one_div_eq_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x ^ (1 / z) = y ↔ x = y ^ z := by
rw [← rpow_eq_rpow_iff hz, rpow_self_rpow_inv hz]
#align nnreal.rpow_one_div_eq_iff NNReal.rpow_one_div_eq_iff
@[simp] lemma rpow_rpow_inv {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y) ^ y⁻¹ = x := by
rw [← rpow_mul, mul_inv_cancel hy, rpow_one]
@[simp] lemma rpow_inv_rpow {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y⁻¹) ^ y = x := by
rw [← rpow_mul, inv_mul_cancel hy, rpow_one]
theorem pow_rpow_inv_natCast (x : ℝ≥0) {n : ℕ} (hn : n ≠ 0) : (x ^ n) ^ (n⁻¹ : ℝ) = x := by
rw [← NNReal.coe_inj, coe_rpow, NNReal.coe_pow]
exact Real.pow_rpow_inv_natCast x.2 hn
#align nnreal.pow_nat_rpow_nat_inv NNReal.pow_rpow_inv_natCast
theorem rpow_inv_natCast_pow (x : ℝ≥0) {n : ℕ} (hn : n ≠ 0) : (x ^ (n⁻¹ : ℝ)) ^ n = x := by
rw [← NNReal.coe_inj, NNReal.coe_pow, coe_rpow]
exact Real.rpow_inv_natCast_pow x.2 hn
#align nnreal.rpow_nat_inv_pow_nat NNReal.rpow_inv_natCast_pow
theorem _root_.Real.toNNReal_rpow_of_nonneg {x y : ℝ} (hx : 0 ≤ x) :
Real.toNNReal (x ^ y) = Real.toNNReal x ^ y := by
nth_rw 1 [← Real.coe_toNNReal x hx]
rw [← NNReal.coe_rpow, Real.toNNReal_coe]
#align real.to_nnreal_rpow_of_nonneg Real.toNNReal_rpow_of_nonneg
theorem strictMono_rpow_of_pos {z : ℝ} (h : 0 < z) : StrictMono fun x : ℝ≥0 => x ^ z :=
fun x y hxy => by simp only [NNReal.rpow_lt_rpow hxy h, coe_lt_coe]
theorem monotone_rpow_of_nonneg {z : ℝ} (h : 0 ≤ z) : Monotone fun x : ℝ≥0 => x ^ z :=
h.eq_or_lt.elim (fun h0 => h0 ▸ by simp only [rpow_zero, monotone_const]) fun h0 =>
(strictMono_rpow_of_pos h0).monotone
/-- Bundles `fun x : ℝ≥0 => x ^ y` into an order isomorphism when `y : ℝ` is positive,
where the inverse is `fun x : ℝ≥0 => x ^ (1 / y)`. -/
@[simps! apply]
def orderIsoRpow (y : ℝ) (hy : 0 < y) : ℝ≥0 ≃o ℝ≥0 :=
(strictMono_rpow_of_pos hy).orderIsoOfRightInverse (fun x => x ^ y) (fun x => x ^ (1 / y))
fun x => by
dsimp
rw [← rpow_mul, one_div_mul_cancel hy.ne.symm, rpow_one]
theorem orderIsoRpow_symm_eq (y : ℝ) (hy : 0 < y) :
(orderIsoRpow y hy).symm = orderIsoRpow (1 / y) (one_div_pos.2 hy) := by
simp only [orderIsoRpow, one_div_one_div]; rfl
end NNReal
namespace ENNReal
/-- The real power function `x^y` on extended nonnegative reals, defined for `x : ℝ≥0∞` and
`y : ℝ` as the restriction of the real power function if `0 < x < ⊤`, and with the natural values
for `0` and `⊤` (i.e., `0 ^ x = 0` for `x > 0`, `1` for `x = 0` and `⊤` for `x < 0`, and
`⊤ ^ x = 1 / 0 ^ x`). -/
noncomputable def rpow : ℝ≥0∞ → ℝ → ℝ≥0∞
| some x, y => if x = 0 ∧ y < 0 then ⊤ else (x ^ y : ℝ≥0)
| none, y => if 0 < y then ⊤ else if y = 0 then 1 else 0
#align ennreal.rpow ENNReal.rpow
noncomputable instance : Pow ℝ≥0∞ ℝ :=
⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x : ℝ≥0∞) (y : ℝ) : rpow x y = x ^ y :=
rfl
#align ennreal.rpow_eq_pow ENNReal.rpow_eq_pow
@[simp]
theorem rpow_zero {x : ℝ≥0∞} : x ^ (0 : ℝ) = 1 := by
cases x <;>
· dsimp only [(· ^ ·), Pow.pow, rpow]
simp [lt_irrefl]
#align ennreal.rpow_zero ENNReal.rpow_zero
theorem top_rpow_def (y : ℝ) : (⊤ : ℝ≥0∞) ^ y = if 0 < y then ⊤ else if y = 0 then 1 else 0 :=
rfl
#align ennreal.top_rpow_def ENNReal.top_rpow_def
@[simp]
theorem top_rpow_of_pos {y : ℝ} (h : 0 < y) : (⊤ : ℝ≥0∞) ^ y = ⊤ := by simp [top_rpow_def, h]
#align ennreal.top_rpow_of_pos ENNReal.top_rpow_of_pos
@[simp]
theorem top_rpow_of_neg {y : ℝ} (h : y < 0) : (⊤ : ℝ≥0∞) ^ y = 0 := by
simp [top_rpow_def, asymm h, ne_of_lt h]
#align ennreal.top_rpow_of_neg ENNReal.top_rpow_of_neg
@[simp]
theorem zero_rpow_of_pos {y : ℝ} (h : 0 < y) : (0 : ℝ≥0∞) ^ y = 0 := by
rw [← ENNReal.coe_zero, ← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), rpow, Pow.pow]
simp [h, asymm h, ne_of_gt h]
#align ennreal.zero_rpow_of_pos ENNReal.zero_rpow_of_pos
@[simp]
theorem zero_rpow_of_neg {y : ℝ} (h : y < 0) : (0 : ℝ≥0∞) ^ y = ⊤ := by
rw [← ENNReal.coe_zero, ← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), rpow, Pow.pow]
simp [h, ne_of_gt h]
#align ennreal.zero_rpow_of_neg ENNReal.zero_rpow_of_neg
theorem zero_rpow_def (y : ℝ) : (0 : ℝ≥0∞) ^ y = if 0 < y then 0 else if y = 0 then 1 else ⊤ := by
rcases lt_trichotomy (0 : ℝ) y with (H | rfl | H)
· simp [H, ne_of_gt, zero_rpow_of_pos, lt_irrefl]
· simp [lt_irrefl]
· simp [H, asymm H, ne_of_lt, zero_rpow_of_neg]
#align ennreal.zero_rpow_def ENNReal.zero_rpow_def
@[simp]
theorem zero_rpow_mul_self (y : ℝ) : (0 : ℝ≥0∞) ^ y * (0 : ℝ≥0∞) ^ y = (0 : ℝ≥0∞) ^ y := by
rw [zero_rpow_def]
split_ifs
exacts [zero_mul _, one_mul _, top_mul_top]
#align ennreal.zero_rpow_mul_self ENNReal.zero_rpow_mul_self
@[norm_cast]
theorem coe_rpow_of_ne_zero {x : ℝ≥0} (h : x ≠ 0) (y : ℝ) : (x : ℝ≥0∞) ^ y = (x ^ y : ℝ≥0) := by
rw [← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), Pow.pow, rpow]
simp [h]
#align ennreal.coe_rpow_of_ne_zero ENNReal.coe_rpow_of_ne_zero
@[norm_cast]
theorem coe_rpow_of_nonneg (x : ℝ≥0) {y : ℝ} (h : 0 ≤ y) : (x : ℝ≥0∞) ^ y = (x ^ y : ℝ≥0) := by
by_cases hx : x = 0
· rcases le_iff_eq_or_lt.1 h with (H | H)
· simp [hx, H.symm]
· simp [hx, zero_rpow_of_pos H, NNReal.zero_rpow (ne_of_gt H)]
· exact coe_rpow_of_ne_zero hx _
#align ennreal.coe_rpow_of_nonneg ENNReal.coe_rpow_of_nonneg
theorem coe_rpow_def (x : ℝ≥0) (y : ℝ) :
(x : ℝ≥0∞) ^ y = if x = 0 ∧ y < 0 then ⊤ else ↑(x ^ y) :=
rfl
#align ennreal.coe_rpow_def ENNReal.coe_rpow_def
@[simp]
theorem rpow_one (x : ℝ≥0∞) : x ^ (1 : ℝ) = x := by
cases x
· exact dif_pos zero_lt_one
· change ite _ _ _ = _
simp only [NNReal.rpow_one, some_eq_coe, ite_eq_right_iff, top_ne_coe, and_imp]
exact fun _ => zero_le_one.not_lt
#align ennreal.rpow_one ENNReal.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ≥0∞) ^ x = 1 := by
rw [← coe_one, coe_rpow_of_ne_zero one_ne_zero]
simp
#align ennreal.one_rpow ENNReal.one_rpow
@[simp]
theorem rpow_eq_zero_iff {x : ℝ≥0∞} {y : ℝ} : x ^ y = 0 ↔ x = 0 ∧ 0 < y ∨ x = ⊤ ∧ y < 0 := by
cases' x with x
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [H, top_rpow_of_neg, top_rpow_of_pos, le_of_lt]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [h, H, zero_rpow_of_neg, zero_rpow_of_pos, le_of_lt]
· simp [coe_rpow_of_ne_zero h, h]
#align ennreal.rpow_eq_zero_iff ENNReal.rpow_eq_zero_iff
lemma rpow_eq_zero_iff_of_pos {x : ℝ≥0∞} {y : ℝ} (hy : 0 < y) : x ^ y = 0 ↔ x = 0 := by
simp [hy, hy.not_lt]
@[simp]
theorem rpow_eq_top_iff {x : ℝ≥0∞} {y : ℝ} : x ^ y = ⊤ ↔ x = 0 ∧ y < 0 ∨ x = ⊤ ∧ 0 < y := by
cases' x with x
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [H, top_rpow_of_neg, top_rpow_of_pos, le_of_lt]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [h, H, zero_rpow_of_neg, zero_rpow_of_pos, le_of_lt]
· simp [coe_rpow_of_ne_zero h, h]
#align ennreal.rpow_eq_top_iff ENNReal.rpow_eq_top_iff
theorem rpow_eq_top_iff_of_pos {x : ℝ≥0∞} {y : ℝ} (hy : 0 < y) : x ^ y = ⊤ ↔ x = ⊤ := by
simp [rpow_eq_top_iff, hy, asymm hy]
#align ennreal.rpow_eq_top_iff_of_pos ENNReal.rpow_eq_top_iff_of_pos
lemma rpow_lt_top_iff_of_pos {x : ℝ≥0∞} {y : ℝ} (hy : 0 < y) : x ^ y < ∞ ↔ x < ∞ := by
simp only [lt_top_iff_ne_top, Ne, rpow_eq_top_iff_of_pos hy]
theorem rpow_eq_top_of_nonneg (x : ℝ≥0∞) {y : ℝ} (hy0 : 0 ≤ y) : x ^ y = ⊤ → x = ⊤ := by
rw [ENNReal.rpow_eq_top_iff]
rintro (h|h)
· exfalso
rw [lt_iff_not_ge] at h
exact h.right hy0
· exact h.left
#align ennreal.rpow_eq_top_of_nonneg ENNReal.rpow_eq_top_of_nonneg
theorem rpow_ne_top_of_nonneg {x : ℝ≥0∞} {y : ℝ} (hy0 : 0 ≤ y) (h : x ≠ ⊤) : x ^ y ≠ ⊤ :=
mt (ENNReal.rpow_eq_top_of_nonneg x hy0) h
#align ennreal.rpow_ne_top_of_nonneg ENNReal.rpow_ne_top_of_nonneg
theorem rpow_lt_top_of_nonneg {x : ℝ≥0∞} {y : ℝ} (hy0 : 0 ≤ y) (h : x ≠ ⊤) : x ^ y < ⊤ :=
lt_top_iff_ne_top.mpr (ENNReal.rpow_ne_top_of_nonneg hy0 h)
#align ennreal.rpow_lt_top_of_nonneg ENNReal.rpow_lt_top_of_nonneg
theorem rpow_add {x : ℝ≥0∞} (y z : ℝ) (hx : x ≠ 0) (h'x : x ≠ ⊤) : x ^ (y + z) = x ^ y * x ^ z := by
cases' x with x
· exact (h'x rfl).elim
have : x ≠ 0 := fun h => by simp [h] at hx
simp [coe_rpow_of_ne_zero this, NNReal.rpow_add this]
#align ennreal.rpow_add ENNReal.rpow_add
theorem rpow_neg (x : ℝ≥0∞) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ := by
cases' x with x
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [top_rpow_of_pos, top_rpow_of_neg, H, neg_pos.mpr]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [h, zero_rpow_of_pos, zero_rpow_of_neg, H, neg_pos.mpr]
· have A : x ^ y ≠ 0 := by simp [h]
simp [coe_rpow_of_ne_zero h, ← coe_inv A, NNReal.rpow_neg]
#align ennreal.rpow_neg ENNReal.rpow_neg
theorem rpow_sub {x : ℝ≥0∞} (y z : ℝ) (hx : x ≠ 0) (h'x : x ≠ ⊤) : x ^ (y - z) = x ^ y / x ^ z := by
rw [sub_eq_add_neg, rpow_add _ _ hx h'x, rpow_neg, div_eq_mul_inv]
#align ennreal.rpow_sub ENNReal.rpow_sub
| Mathlib/Analysis/SpecialFunctions/Pow/NNReal.lean | 551 | 551 | theorem rpow_neg_one (x : ℝ≥0∞) : x ^ (-1 : ℝ) = x⁻¹ := by | simp [rpow_neg]
|
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, François Dupuis
-/
import Mathlib.Analysis.Convex.Basic
import Mathlib.Order.Filter.Extr
import Mathlib.Tactic.GCongr
#align_import analysis.convex.function from "leanprover-community/mathlib"@"92ca63f0fb391a9ca5f22d2409a6080e786d99f7"
/-!
# Convex and concave functions
This file defines convex and concave functions in vector spaces and proves the finite Jensen
inequality. The integral version can be found in `Analysis.Convex.Integral`.
A function `f : E → β` is `ConvexOn` a set `s` if `s` is itself a convex set, and for any two
points `x y ∈ s`, the segment joining `(x, f x)` to `(y, f y)` is above the graph of `f`.
Equivalently, `ConvexOn 𝕜 f s` means that the epigraph `{p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2}` is
a convex set.
## Main declarations
* `ConvexOn 𝕜 s f`: The function `f` is convex on `s` with scalars `𝕜`.
* `ConcaveOn 𝕜 s f`: The function `f` is concave on `s` with scalars `𝕜`.
* `StrictConvexOn 𝕜 s f`: The function `f` is strictly convex on `s` with scalars `𝕜`.
* `StrictConcaveOn 𝕜 s f`: The function `f` is strictly concave on `s` with scalars `𝕜`.
-/
open scoped Classical
open LinearMap Set Convex Pointwise
variable {𝕜 E F α β ι : Type*}
section OrderedSemiring
variable [OrderedSemiring 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [AddCommMonoid F]
section OrderedAddCommMonoid
variable [OrderedAddCommMonoid α] [OrderedAddCommMonoid β]
section SMul
variable (𝕜) [SMul 𝕜 E] [SMul 𝕜 α] [SMul 𝕜 β] (s : Set E) (f : E → β) {g : β → α}
/-- Convexity of functions -/
def ConvexOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 →
f (a • x + b • y) ≤ a • f x + b • f y
#align convex_on ConvexOn
/-- Concavity of functions -/
def ConcaveOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y)
#align concave_on ConcaveOn
/-- Strict convexity of functions -/
def StrictConvexOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x ≠ y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) < a • f x + b • f y
#align strict_convex_on StrictConvexOn
/-- Strict concavity of functions -/
def StrictConcaveOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x ≠ y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y < f (a • x + b • y)
#align strict_concave_on StrictConcaveOn
variable {𝕜 s f}
open OrderDual (toDual ofDual)
theorem ConvexOn.dual (hf : ConvexOn 𝕜 s f) : ConcaveOn 𝕜 s (toDual ∘ f) := hf
#align convex_on.dual ConvexOn.dual
theorem ConcaveOn.dual (hf : ConcaveOn 𝕜 s f) : ConvexOn 𝕜 s (toDual ∘ f) := hf
#align concave_on.dual ConcaveOn.dual
theorem StrictConvexOn.dual (hf : StrictConvexOn 𝕜 s f) : StrictConcaveOn 𝕜 s (toDual ∘ f) := hf
#align strict_convex_on.dual StrictConvexOn.dual
theorem StrictConcaveOn.dual (hf : StrictConcaveOn 𝕜 s f) : StrictConvexOn 𝕜 s (toDual ∘ f) := hf
#align strict_concave_on.dual StrictConcaveOn.dual
theorem convexOn_id {s : Set β} (hs : Convex 𝕜 s) : ConvexOn 𝕜 s _root_.id :=
⟨hs, by
intros
rfl⟩
#align convex_on_id convexOn_id
theorem concaveOn_id {s : Set β} (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s _root_.id :=
⟨hs, by
intros
rfl⟩
#align concave_on_id concaveOn_id
theorem ConvexOn.subset {t : Set E} (hf : ConvexOn 𝕜 t f) (hst : s ⊆ t) (hs : Convex 𝕜 s) :
ConvexOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align convex_on.subset ConvexOn.subset
theorem ConcaveOn.subset {t : Set E} (hf : ConcaveOn 𝕜 t f) (hst : s ⊆ t) (hs : Convex 𝕜 s) :
ConcaveOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align concave_on.subset ConcaveOn.subset
theorem StrictConvexOn.subset {t : Set E} (hf : StrictConvexOn 𝕜 t f) (hst : s ⊆ t)
(hs : Convex 𝕜 s) : StrictConvexOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align strict_convex_on.subset StrictConvexOn.subset
theorem StrictConcaveOn.subset {t : Set E} (hf : StrictConcaveOn 𝕜 t f) (hst : s ⊆ t)
(hs : Convex 𝕜 s) : StrictConcaveOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align strict_concave_on.subset StrictConcaveOn.subset
theorem ConvexOn.comp (hg : ConvexOn 𝕜 (f '' s) g) (hf : ConvexOn 𝕜 s f)
(hg' : MonotoneOn g (f '' s)) : ConvexOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy _ _ ha hb hab =>
(hg' (mem_image_of_mem f <| hf.1 hx hy ha hb hab)
(hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab) <|
hf.2 hx hy ha hb hab).trans <|
hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab⟩
#align convex_on.comp ConvexOn.comp
theorem ConcaveOn.comp (hg : ConcaveOn 𝕜 (f '' s) g) (hf : ConcaveOn 𝕜 s f)
(hg' : MonotoneOn g (f '' s)) : ConcaveOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy _ _ ha hb hab =>
(hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab).trans <|
hg' (hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab)
(mem_image_of_mem f <| hf.1 hx hy ha hb hab) <|
hf.2 hx hy ha hb hab⟩
#align concave_on.comp ConcaveOn.comp
theorem ConvexOn.comp_concaveOn (hg : ConvexOn 𝕜 (f '' s) g) (hf : ConcaveOn 𝕜 s f)
(hg' : AntitoneOn g (f '' s)) : ConvexOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg'
#align convex_on.comp_concave_on ConvexOn.comp_concaveOn
theorem ConcaveOn.comp_convexOn (hg : ConcaveOn 𝕜 (f '' s) g) (hf : ConvexOn 𝕜 s f)
(hg' : AntitoneOn g (f '' s)) : ConcaveOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg'
#align concave_on.comp_convex_on ConcaveOn.comp_convexOn
theorem StrictConvexOn.comp (hg : StrictConvexOn 𝕜 (f '' s) g) (hf : StrictConvexOn 𝕜 s f)
(hg' : StrictMonoOn g (f '' s)) (hf' : s.InjOn f) : StrictConvexOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab =>
(hg' (mem_image_of_mem f <| hf.1 hx hy ha.le hb.le hab)
(hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha.le hb.le hab) <|
hf.2 hx hy hxy ha hb hab).trans <|
hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) (mt (hf' hx hy) hxy) ha hb hab⟩
#align strict_convex_on.comp StrictConvexOn.comp
theorem StrictConcaveOn.comp (hg : StrictConcaveOn 𝕜 (f '' s) g) (hf : StrictConcaveOn 𝕜 s f)
(hg' : StrictMonoOn g (f '' s)) (hf' : s.InjOn f) : StrictConcaveOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab =>
(hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) (mt (hf' hx hy) hxy) ha hb hab).trans <|
hg' (hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha.le hb.le hab)
(mem_image_of_mem f <| hf.1 hx hy ha.le hb.le hab) <|
hf.2 hx hy hxy ha hb hab⟩
#align strict_concave_on.comp StrictConcaveOn.comp
theorem StrictConvexOn.comp_strictConcaveOn (hg : StrictConvexOn 𝕜 (f '' s) g)
(hf : StrictConcaveOn 𝕜 s f) (hg' : StrictAntiOn g (f '' s)) (hf' : s.InjOn f) :
StrictConvexOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg' hf'
#align strict_convex_on.comp_strict_concave_on StrictConvexOn.comp_strictConcaveOn
theorem StrictConcaveOn.comp_strictConvexOn (hg : StrictConcaveOn 𝕜 (f '' s) g)
(hf : StrictConvexOn 𝕜 s f) (hg' : StrictAntiOn g (f '' s)) (hf' : s.InjOn f) :
StrictConcaveOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg' hf'
#align strict_concave_on.comp_strict_convex_on StrictConcaveOn.comp_strictConvexOn
end SMul
section DistribMulAction
variable [SMul 𝕜 E] [DistribMulAction 𝕜 β] {s : Set E} {f g : E → β}
theorem ConvexOn.add (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) : ConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) ≤ a • f x + b • f y + (a • g x + b • g y) :=
add_le_add (hf.2 hx hy ha hb hab) (hg.2 hx hy ha hb hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]
⟩
#align convex_on.add ConvexOn.add
theorem ConcaveOn.add (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) : ConcaveOn 𝕜 s (f + g) :=
hf.dual.add hg
#align concave_on.add ConcaveOn.add
end DistribMulAction
section Module
variable [SMul 𝕜 E] [Module 𝕜 β] {s : Set E} {f : E → β}
theorem convexOn_const (c : β) (hs : Convex 𝕜 s) : ConvexOn 𝕜 s fun _ : E => c :=
⟨hs, fun _ _ _ _ _ _ _ _ hab => (Convex.combo_self hab c).ge⟩
#align convex_on_const convexOn_const
theorem concaveOn_const (c : β) (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s fun _ => c :=
convexOn_const (β := βᵒᵈ) _ hs
#align concave_on_const concaveOn_const
theorem convexOn_of_convex_epigraph (h : Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 }) :
ConvexOn 𝕜 s f :=
⟨fun x hx y hy a b ha hb hab => (@h (x, f x) ⟨hx, le_rfl⟩ (y, f y) ⟨hy, le_rfl⟩ a b ha hb hab).1,
fun x hx y hy a b ha hb hab => (@h (x, f x) ⟨hx, le_rfl⟩ (y, f y) ⟨hy, le_rfl⟩ a b ha hb hab).2⟩
#align convex_on_of_convex_epigraph convexOn_of_convex_epigraph
theorem concaveOn_of_convex_hypograph (h : Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 }) :
ConcaveOn 𝕜 s f :=
convexOn_of_convex_epigraph (β := βᵒᵈ) h
#align concave_on_of_convex_hypograph concaveOn_of_convex_hypograph
end Module
section OrderedSMul
variable [SMul 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem ConvexOn.convex_le (hf : ConvexOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | f x ≤ r }) :=
fun x hx y hy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha hb hab,
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx.1 hy.1 ha hb hab
_ ≤ a • r + b • r := by
gcongr
· exact hx.2
· exact hy.2
_ = r := Convex.combo_self hab r
⟩
#align convex_on.convex_le ConvexOn.convex_le
theorem ConcaveOn.convex_ge (hf : ConcaveOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | r ≤ f x }) :=
hf.dual.convex_le r
#align concave_on.convex_ge ConcaveOn.convex_ge
theorem ConvexOn.convex_epigraph (hf : ConvexOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } := by
rintro ⟨x, r⟩ ⟨hx, hr⟩ ⟨y, t⟩ ⟨hy, ht⟩ a b ha hb hab
refine ⟨hf.1 hx hy ha hb hab, ?_⟩
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha hb hab
_ ≤ a • r + b • t := by gcongr
#align convex_on.convex_epigraph ConvexOn.convex_epigraph
theorem ConcaveOn.convex_hypograph (hf : ConcaveOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
hf.dual.convex_epigraph
#align concave_on.convex_hypograph ConcaveOn.convex_hypograph
theorem convexOn_iff_convex_epigraph :
ConvexOn 𝕜 s f ↔ Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } :=
⟨ConvexOn.convex_epigraph, convexOn_of_convex_epigraph⟩
#align convex_on_iff_convex_epigraph convexOn_iff_convex_epigraph
theorem concaveOn_iff_convex_hypograph :
ConcaveOn 𝕜 s f ↔ Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
convexOn_iff_convex_epigraph (β := βᵒᵈ)
#align concave_on_iff_convex_hypograph concaveOn_iff_convex_hypograph
end OrderedSMul
section Module
variable [Module 𝕜 E] [SMul 𝕜 β] {s : Set E} {f : E → β}
/-- Right translation preserves convexity. -/
theorem ConvexOn.translate_right (hf : ConvexOn 𝕜 s f) (c : E) :
ConvexOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => c + z) :=
⟨hf.1.translate_preimage_right _, fun x hx y hy a b ha hb hab =>
calc
f (c + (a • x + b • y)) = f (a • (c + x) + b • (c + y)) := by
rw [smul_add, smul_add, add_add_add_comm, Convex.combo_self hab]
_ ≤ a • f (c + x) + b • f (c + y) := hf.2 hx hy ha hb hab
⟩
#align convex_on.translate_right ConvexOn.translate_right
/-- Right translation preserves concavity. -/
theorem ConcaveOn.translate_right (hf : ConcaveOn 𝕜 s f) (c : E) :
ConcaveOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => c + z) :=
hf.dual.translate_right _
#align concave_on.translate_right ConcaveOn.translate_right
/-- Left translation preserves convexity. -/
theorem ConvexOn.translate_left (hf : ConvexOn 𝕜 s f) (c : E) :
ConvexOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => z + c) := by
simpa only [add_comm c] using hf.translate_right c
#align convex_on.translate_left ConvexOn.translate_left
/-- Left translation preserves concavity. -/
theorem ConcaveOn.translate_left (hf : ConcaveOn 𝕜 s f) (c : E) :
ConcaveOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => z + c) :=
hf.dual.translate_left _
#align concave_on.translate_left ConcaveOn.translate_left
end Module
section Module
variable [Module 𝕜 E] [Module 𝕜 β]
theorem convexOn_iff_forall_pos {s : Set E} {f : E → β} :
ConvexOn 𝕜 s f ↔ Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b →
a + b = 1 → f (a • x + b • y) ≤ a • f x + b • f y := by
refine and_congr_right'
⟨fun h x hx y hy a b ha hb hab => h hx hy ha.le hb.le hab, fun h x hx y hy a b ha hb hab => ?_⟩
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_add] at hab
subst b
simp_rw [zero_smul, zero_add, one_smul, le_rfl]
obtain rfl | hb' := hb.eq_or_lt
· rw [add_zero] at hab
subst a
simp_rw [zero_smul, add_zero, one_smul, le_rfl]
exact h hx hy ha' hb' hab
#align convex_on_iff_forall_pos convexOn_iff_forall_pos
theorem concaveOn_iff_forall_pos {s : Set E} {f : E → β} :
ConcaveOn 𝕜 s f ↔
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y) :=
convexOn_iff_forall_pos (β := βᵒᵈ)
#align concave_on_iff_forall_pos concaveOn_iff_forall_pos
theorem convexOn_iff_pairwise_pos {s : Set E} {f : E → β} :
ConvexOn 𝕜 s f ↔
Convex 𝕜 s ∧
s.Pairwise fun x y =>
∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → f (a • x + b • y) ≤ a • f x + b • f y := by
rw [convexOn_iff_forall_pos]
refine
and_congr_right'
⟨fun h x hx y hy _ a b ha hb hab => h hx hy ha hb hab, fun h x hx y hy a b ha hb hab => ?_⟩
obtain rfl | hxy := eq_or_ne x y
· rw [Convex.combo_self hab, Convex.combo_self hab]
exact h hx hy hxy ha hb hab
#align convex_on_iff_pairwise_pos convexOn_iff_pairwise_pos
theorem concaveOn_iff_pairwise_pos {s : Set E} {f : E → β} :
ConcaveOn 𝕜 s f ↔
Convex 𝕜 s ∧
s.Pairwise fun x y =>
∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → a • f x + b • f y ≤ f (a • x + b • y) :=
convexOn_iff_pairwise_pos (β := βᵒᵈ)
#align concave_on_iff_pairwise_pos concaveOn_iff_pairwise_pos
/-- A linear map is convex. -/
theorem LinearMap.convexOn (f : E →ₗ[𝕜] β) {s : Set E} (hs : Convex 𝕜 s) : ConvexOn 𝕜 s f :=
⟨hs, fun _ _ _ _ _ _ _ _ _ => by rw [f.map_add, f.map_smul, f.map_smul]⟩
#align linear_map.convex_on LinearMap.convexOn
/-- A linear map is concave. -/
theorem LinearMap.concaveOn (f : E →ₗ[𝕜] β) {s : Set E} (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s f :=
⟨hs, fun _ _ _ _ _ _ _ _ _ => by rw [f.map_add, f.map_smul, f.map_smul]⟩
#align linear_map.concave_on LinearMap.concaveOn
theorem StrictConvexOn.convexOn {s : Set E} {f : E → β} (hf : StrictConvexOn 𝕜 s f) :
ConvexOn 𝕜 s f :=
convexOn_iff_pairwise_pos.mpr
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab => (hf.2 hx hy hxy ha hb hab).le⟩
#align strict_convex_on.convex_on StrictConvexOn.convexOn
theorem StrictConcaveOn.concaveOn {s : Set E} {f : E → β} (hf : StrictConcaveOn 𝕜 s f) :
ConcaveOn 𝕜 s f :=
hf.dual.convexOn
#align strict_concave_on.concave_on StrictConcaveOn.concaveOn
section OrderedSMul
variable [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem StrictConvexOn.convex_lt (hf : StrictConvexOn 𝕜 s f) (r : β) :
Convex 𝕜 ({ x ∈ s | f x < r }) :=
convex_iff_pairwise_pos.2 fun x hx y hy hxy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha.le hb.le hab,
calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx.1 hy.1 hxy ha hb hab
_ ≤ a • r + b • r := by
gcongr
· exact hx.2.le
· exact hy.2.le
_ = r := Convex.combo_self hab r
⟩
#align strict_convex_on.convex_lt StrictConvexOn.convex_lt
theorem StrictConcaveOn.convex_gt (hf : StrictConcaveOn 𝕜 s f) (r : β) :
Convex 𝕜 ({ x ∈ s | r < f x }) :=
hf.dual.convex_lt r
#align strict_concave_on.convex_gt StrictConcaveOn.convex_gt
end OrderedSMul
section LinearOrder
variable [LinearOrder E] {s : Set E} {f : E → β}
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is convex, it suffices to
verify the inequality `f (a • x + b • y) ≤ a • f x + b • f y` only for `x < y` and positive `a`,
`b`. The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order.
-/
theorem LinearOrder.convexOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) ≤ a • f x + b • f y) :
ConvexOn 𝕜 s f := by
refine convexOn_iff_pairwise_pos.2 ⟨hs, fun x hx y hy hxy a b ha hb hab => ?_⟩
-- Porting note: without clearing the stray variables, `wlog` gives a bad term.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/wlog.20.2316495
clear! α F ι
wlog h : x < y
· rw [add_comm (a • x), add_comm (a • f x)]
rw [add_comm] at hab
exact this hs hf y hy x hx hxy.symm b a hb ha hab (hxy.lt_or_lt.resolve_left h)
exact hf hx hy h ha hb hab
#align linear_order.convex_on_of_lt LinearOrder.convexOn_of_lt
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is concave it suffices to
verify the inequality `a • f x + b • f y ≤ f (a • x + b • y)` for `x < y` and positive `a`, `b`. The
main use case is `E = ℝ` however one can apply it, e.g., to `ℝ^n` with lexicographic order. -/
theorem LinearOrder.concaveOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y)) :
ConcaveOn 𝕜 s f :=
LinearOrder.convexOn_of_lt (β := βᵒᵈ) hs hf
#align linear_order.concave_on_of_lt LinearOrder.concaveOn_of_lt
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is strictly convex, it suffices
to verify the inequality `f (a • x + b • y) < a • f x + b • f y` for `x < y` and positive `a`, `b`.
The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order. -/
theorem LinearOrder.strictConvexOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) < a • f x + b • f y) :
StrictConvexOn 𝕜 s f := by
refine ⟨hs, fun x hx y hy hxy a b ha hb hab => ?_⟩
-- Porting note: without clearing the stray variables, `wlog` gives a bad term.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/wlog.20.2316495
clear! α F ι
wlog h : x < y
· rw [add_comm (a • x), add_comm (a • f x)]
rw [add_comm] at hab
exact this hs hf y hy x hx hxy.symm b a hb ha hab (hxy.lt_or_lt.resolve_left h)
exact hf hx hy h ha hb hab
#align linear_order.strict_convex_on_of_lt LinearOrder.strictConvexOn_of_lt
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is strictly concave it suffices
to verify the inequality `a • f x + b • f y < f (a • x + b • y)` for `x < y` and positive `a`, `b`.
The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order. -/
theorem LinearOrder.strictConcaveOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y < f (a • x + b • y)) :
StrictConcaveOn 𝕜 s f :=
LinearOrder.strictConvexOn_of_lt (β := βᵒᵈ) hs hf
#align linear_order.strict_concave_on_of_lt LinearOrder.strictConcaveOn_of_lt
end LinearOrder
end Module
section Module
variable [Module 𝕜 E] [Module 𝕜 F] [SMul 𝕜 β]
/-- If `g` is convex on `s`, so is `(f ∘ g)` on `f ⁻¹' s` for a linear `f`. -/
theorem ConvexOn.comp_linearMap {f : F → β} {s : Set F} (hf : ConvexOn 𝕜 s f) (g : E →ₗ[𝕜] F) :
ConvexOn 𝕜 (g ⁻¹' s) (f ∘ g) :=
⟨hf.1.linear_preimage _, fun x hx y hy a b ha hb hab =>
calc
f (g (a • x + b • y)) = f (a • g x + b • g y) := by rw [g.map_add, g.map_smul, g.map_smul]
_ ≤ a • f (g x) + b • f (g y) := hf.2 hx hy ha hb hab⟩
#align convex_on.comp_linear_map ConvexOn.comp_linearMap
/-- If `g` is concave on `s`, so is `(g ∘ f)` on `f ⁻¹' s` for a linear `f`. -/
theorem ConcaveOn.comp_linearMap {f : F → β} {s : Set F} (hf : ConcaveOn 𝕜 s f) (g : E →ₗ[𝕜] F) :
ConcaveOn 𝕜 (g ⁻¹' s) (f ∘ g) :=
hf.dual.comp_linearMap g
#align concave_on.comp_linear_map ConcaveOn.comp_linearMap
end Module
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [OrderedCancelAddCommMonoid β]
section DistribMulAction
variable [SMul 𝕜 E] [DistribMulAction 𝕜 β] {s : Set E} {f g : E → β}
theorem StrictConvexOn.add_convexOn (hf : StrictConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) < a • f x + b • f y + (a • g x + b • g y) :=
add_lt_add_of_lt_of_le (hf.2 hx hy hxy ha hb hab) (hg.2 hx hy ha.le hb.le hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]⟩
#align strict_convex_on.add_convex_on StrictConvexOn.add_convexOn
theorem ConvexOn.add_strictConvexOn (hf : ConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
add_comm g f ▸ hg.add_convexOn hf
#align convex_on.add_strict_convex_on ConvexOn.add_strictConvexOn
| Mathlib/Analysis/Convex/Function.lean | 520 | 526 | theorem StrictConvexOn.add (hf : StrictConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) < a • f x + b • f y + (a • g x + b • g y) :=
add_lt_add (hf.2 hx hy hxy ha hb hab) (hg.2 hx hy hxy ha hb hab)
_ = a • (f x + g x) + b • (f y + g y) := by | rw [smul_add, smul_add, add_add_add_comm]⟩
|
/-
Copyright (c) 2021 Yourong Zang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yourong Zang
-/
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Analysis.NormedSpace.LinearIsometry
#align_import analysis.normed_space.conformal_linear_map from "leanprover-community/mathlib"@"d1bd9c5df2867c1cb463bc6364446d57bdd9f7f1"
/-!
# Conformal Linear Maps
A continuous linear map between `R`-normed spaces `X` and `Y` `IsConformalMap` if it is
a nonzero multiple of a linear isometry.
## Main definitions
* `IsConformalMap`: the main definition of conformal linear maps
## Main results
* The conformality of the composition of two conformal linear maps, the identity map
and multiplications by nonzero constants as continuous linear maps
* `isConformalMap_of_subsingleton`: all continuous linear maps on singleton spaces are conformal
See `Analysis.InnerProductSpace.ConformalLinearMap` for
* `isConformalMap_iff`: a map between inner product spaces is conformal
iff it preserves inner products up to a fixed scalar factor.
## Tags
conformal
## Warning
The definition of conformality in this file does NOT require the maps to be orientation-preserving.
-/
noncomputable section
open Function LinearIsometry ContinuousLinearMap
/-- A continuous linear map `f'` is said to be conformal if it's
a nonzero multiple of a linear isometry. -/
def IsConformalMap {R : Type*} {X Y : Type*} [NormedField R] [SeminormedAddCommGroup X]
[SeminormedAddCommGroup Y] [NormedSpace R X] [NormedSpace R Y] (f' : X →L[R] Y) :=
∃ c ≠ (0 : R), ∃ li : X →ₗᵢ[R] Y, f' = c • li.toContinuousLinearMap
#align is_conformal_map IsConformalMap
variable {R M N G M' : Type*} [NormedField R] [SeminormedAddCommGroup M] [SeminormedAddCommGroup N]
[SeminormedAddCommGroup G] [NormedSpace R M] [NormedSpace R N] [NormedSpace R G]
[NormedAddCommGroup M'] [NormedSpace R M'] {f : M →L[R] N} {g : N →L[R] G} {c : R}
theorem isConformalMap_id : IsConformalMap (id R M) :=
⟨1, one_ne_zero, id, by simp⟩
#align is_conformal_map_id isConformalMap_id
theorem IsConformalMap.smul (hf : IsConformalMap f) {c : R} (hc : c ≠ 0) :
IsConformalMap (c • f) := by
rcases hf with ⟨c', hc', li, rfl⟩
exact ⟨c * c', mul_ne_zero hc hc', li, smul_smul _ _ _⟩
#align is_conformal_map.smul IsConformalMap.smul
theorem isConformalMap_const_smul (hc : c ≠ 0) : IsConformalMap (c • id R M) :=
isConformalMap_id.smul hc
#align is_conformal_map_const_smul isConformalMap_const_smul
protected theorem LinearIsometry.isConformalMap (f' : M →ₗᵢ[R] N) :
IsConformalMap f'.toContinuousLinearMap :=
⟨1, one_ne_zero, f', (one_smul _ _).symm⟩
#align linear_isometry.is_conformal_map LinearIsometry.isConformalMap
@[nontriviality]
theorem isConformalMap_of_subsingleton [Subsingleton M] (f' : M →L[R] N) : IsConformalMap f' :=
⟨1, one_ne_zero, ⟨0, fun x => by simp [Subsingleton.elim x 0]⟩, Subsingleton.elim _ _⟩
#align is_conformal_map_of_subsingleton isConformalMap_of_subsingleton
namespace IsConformalMap
theorem comp (hg : IsConformalMap g) (hf : IsConformalMap f) : IsConformalMap (g.comp f) := by
rcases hf with ⟨cf, hcf, lif, rfl⟩
rcases hg with ⟨cg, hcg, lig, rfl⟩
refine ⟨cg * cf, mul_ne_zero hcg hcf, lig.comp lif, ?_⟩
rw [smul_comp, comp_smul, mul_smul]
rfl
#align is_conformal_map.comp IsConformalMap.comp
protected theorem injective {f : M' →L[R] N} (h : IsConformalMap f) : Function.Injective f := by
rcases h with ⟨c, hc, li, rfl⟩
exact (smul_right_injective _ hc).comp li.injective
#align is_conformal_map.injective IsConformalMap.injective
| Mathlib/Analysis/NormedSpace/ConformalLinearMap.lean | 97 | 100 | theorem ne_zero [Nontrivial M'] {f' : M' →L[R] N} (hf' : IsConformalMap f') : f' ≠ 0 := by |
rintro rfl
rcases exists_ne (0 : M') with ⟨a, ha⟩
exact ha (hf'.injective rfl)
|
/-
Copyright (c) 2014 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Ring.Cast
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.PSub
import Mathlib.Data.Nat.Size
import Mathlib.Data.Num.Bitwise
#align_import data.num.lemmas from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Properties of the binary representation of integers
-/
/-
Porting note:
`bit0` and `bit1` are deprecated because it is mainly used to represent number literal in Lean3 but
not in Lean4 anymore. However, this file uses them for encoding numbers so this linter is
unnecessary.
-/
set_option linter.deprecated false
-- Porting note: Required for the notation `-[n+1]`.
open Int Function
attribute [local simp] add_assoc
namespace PosNum
variable {α : Type*}
@[simp, norm_cast]
theorem cast_one [One α] [Add α] : ((1 : PosNum) : α) = 1 :=
rfl
#align pos_num.cast_one PosNum.cast_one
@[simp]
theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 :=
rfl
#align pos_num.cast_one' PosNum.cast_one'
@[simp, norm_cast]
theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = _root_.bit0 (n : α) :=
rfl
#align pos_num.cast_bit0 PosNum.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = _root_.bit1 (n : α) :=
rfl
#align pos_num.cast_bit1 PosNum.cast_bit1
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n
| 1 => Nat.cast_one
| bit0 p => (Nat.cast_bit0 _).trans <| congr_arg _root_.bit0 p.cast_to_nat
| bit1 p => (Nat.cast_bit1 _).trans <| congr_arg _root_.bit1 p.cast_to_nat
#align pos_num.cast_to_nat PosNum.cast_to_nat
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
#align pos_num.to_nat_to_int PosNum.to_nat_to_int
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] (n : PosNum) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
#align pos_num.cast_to_int PosNum.cast_to_int
theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1
| 1 => rfl
| bit0 p => rfl
| bit1 p =>
(congr_arg _root_.bit0 (succ_to_nat p)).trans <|
show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm]
#align pos_num.succ_to_nat PosNum.succ_to_nat
theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl
#align pos_num.one_add PosNum.one_add
theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl
#align pos_num.add_one PosNum.add_one
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : PosNum) : ℕ) = m + n
| 1, b => by rw [one_add b, succ_to_nat, add_comm, cast_one]
| a, 1 => by rw [add_one a, succ_to_nat, cast_one]
| bit0 a, bit0 b => (congr_arg _root_.bit0 (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _
| bit0 a, bit1 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + (b + b + 1) by simp [add_left_comm]
| bit1 a, bit0 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + 1 + (b + b) by simp [add_comm, add_left_comm]
| bit1 a, bit1 b =>
show (succ (a + b) + succ (a + b) : ℕ) = a + a + 1 + (b + b + 1) by
rw [succ_to_nat, add_to_nat a b]; simp [add_left_comm]
#align pos_num.add_to_nat PosNum.add_to_nat
theorem add_succ : ∀ m n : PosNum, m + succ n = succ (m + n)
| 1, b => by simp [one_add]
| bit0 a, 1 => congr_arg bit0 (add_one a)
| bit1 a, 1 => congr_arg bit1 (add_one a)
| bit0 a, bit0 b => rfl
| bit0 a, bit1 b => congr_arg bit0 (add_succ a b)
| bit1 a, bit0 b => rfl
| bit1 a, bit1 b => congr_arg bit1 (add_succ a b)
#align pos_num.add_succ PosNum.add_succ
theorem bit0_of_bit0 : ∀ n, _root_.bit0 n = bit0 n
| 1 => rfl
| bit0 p => congr_arg bit0 (bit0_of_bit0 p)
| bit1 p => show bit0 (succ (_root_.bit0 p)) = _ by rw [bit0_of_bit0 p, succ]
#align pos_num.bit0_of_bit0 PosNum.bit0_of_bit0
theorem bit1_of_bit1 (n : PosNum) : _root_.bit1 n = bit1 n :=
show _root_.bit0 n + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ]
#align pos_num.bit1_of_bit1 PosNum.bit1_of_bit1
@[norm_cast]
theorem mul_to_nat (m) : ∀ n, ((m * n : PosNum) : ℕ) = m * n
| 1 => (mul_one _).symm
| bit0 p => show (↑(m * p) + ↑(m * p) : ℕ) = ↑m * (p + p) by rw [mul_to_nat m p, left_distrib]
| bit1 p =>
(add_to_nat (bit0 (m * p)) m).trans <|
show (↑(m * p) + ↑(m * p) + ↑m : ℕ) = ↑m * (p + p) + m by rw [mul_to_nat m p, left_distrib]
#align pos_num.mul_to_nat PosNum.mul_to_nat
theorem to_nat_pos : ∀ n : PosNum, 0 < (n : ℕ)
| 1 => Nat.zero_lt_one
| bit0 p =>
let h := to_nat_pos p
add_pos h h
| bit1 _p => Nat.succ_pos _
#align pos_num.to_nat_pos PosNum.to_nat_pos
theorem cmp_to_nat_lemma {m n : PosNum} : (m : ℕ) < n → (bit1 m : ℕ) < bit0 n :=
show (m : ℕ) < n → (m + m + 1 + 1 : ℕ) ≤ n + n by
intro h; rw [Nat.add_right_comm m m 1, add_assoc]; exact Nat.add_le_add h h
#align pos_num.cmp_to_nat_lemma PosNum.cmp_to_nat_lemma
| Mathlib/Data/Num/Lemmas.lean | 145 | 147 | theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by |
induction' m with m IH m IH <;> intro n <;> cases' n with n n <;> unfold cmp <;>
try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl
|
/-
Copyright (c) 2021 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa
-/
import Mathlib.Algebra.Group.Basic
import Mathlib.Order.Basic
import Mathlib.Order.Monotone.Basic
#align_import algebra.covariant_and_contravariant from "leanprover-community/mathlib"@"2258b40dacd2942571c8ce136215350c702dc78f"
/-!
# Covariants and contravariants
This file contains general lemmas and instances to work with the interactions between a relation and
an action on a Type.
The intended application is the splitting of the ordering from the algebraic assumptions on the
operations in the `Ordered[...]` hierarchy.
The strategy is to introduce two more flexible typeclasses, `CovariantClass` and
`ContravariantClass`:
* `CovariantClass` models the implication `a ≤ b → c * a ≤ c * b` (multiplication is monotone),
* `ContravariantClass` models the implication `a * b < a * c → b < c`.
Since `Co(ntra)variantClass` takes as input the operation (typically `(+)` or `(*)`) and the order
relation (typically `(≤)` or `(<)`), these are the only two typeclasses that I have used.
The general approach is to formulate the lemma that you are interested in and prove it, with the
`Ordered[...]` typeclass of your liking. After that, you convert the single typeclass,
say `[OrderedCancelMonoid M]`, into three typeclasses, e.g.
`[CancelMonoid M] [PartialOrder M] [CovariantClass M M (Function.swap (*)) (≤)]`
and have a go at seeing if the proof still works!
Note that it is possible to combine several `Co(ntra)variantClass` assumptions together.
Indeed, the usual ordered typeclasses arise from assuming the pair
`[CovariantClass M M (*) (≤)] [ContravariantClass M M (*) (<)]`
on top of order/algebraic assumptions.
A formal remark is that normally `CovariantClass` uses the `(≤)`-relation, while
`ContravariantClass` uses the `(<)`-relation. This need not be the case in general, but seems to be
the most common usage. In the opposite direction, the implication
```lean
[Semigroup α] [PartialOrder α] [ContravariantClass α α (*) (≤)] → LeftCancelSemigroup α
```
holds -- note the `Co*ntra*` assumption on the `(≤)`-relation.
# Formalization notes
We stick to the convention of using `Function.swap (*)` (or `Function.swap (+)`), for the
typeclass assumptions, since `Function.swap` is slightly better behaved than `flip`.
However, sometimes as a **non-typeclass** assumption, we prefer `flip (*)` (or `flip (+)`),
as it is easier to use.
-/
-- TODO: convert `ExistsMulOfLE`, `ExistsAddOfLE`?
-- TODO: relationship with `Con/AddCon`
-- TODO: include equivalence of `LeftCancelSemigroup` with
-- `Semigroup PartialOrder ContravariantClass α α (*) (≤)`?
-- TODO : use ⇒, as per Eric's suggestion? See
-- https://leanprover.zulipchat.com/#narrow/stream/116395-maths/topic/ordered.20stuff/near/236148738
-- for a discussion.
open Function
section Variants
variable {M N : Type*} (μ : M → N → N) (r : N → N → Prop)
variable (M N)
/-- `Covariant` is useful to formulate succinctly statements about the interactions between an
action of a Type on another one and a relation on the acted-upon Type.
See the `CovariantClass` doc-string for its meaning. -/
def Covariant : Prop :=
∀ (m) {n₁ n₂}, r n₁ n₂ → r (μ m n₁) (μ m n₂)
#align covariant Covariant
/-- `Contravariant` is useful to formulate succinctly statements about the interactions between an
action of a Type on another one and a relation on the acted-upon Type.
See the `ContravariantClass` doc-string for its meaning. -/
def Contravariant : Prop :=
∀ (m) {n₁ n₂}, r (μ m n₁) (μ m n₂) → r n₁ n₂
#align contravariant Contravariant
/-- Given an action `μ` of a Type `M` on a Type `N` and a relation `r` on `N`, informally, the
`CovariantClass` says that "the action `μ` preserves the relation `r`."
More precisely, the `CovariantClass` is a class taking two Types `M N`, together with an "action"
`μ : M → N → N` and a relation `r : N → N → Prop`. Its unique field `elim` is the assertion that
for all `m ∈ M` and all elements `n₁, n₂ ∈ N`, if the relation `r` holds for the pair
`(n₁, n₂)`, then, the relation `r` also holds for the pair `(μ m n₁, μ m n₂)`,
obtained from `(n₁, n₂)` by acting upon it by `m`.
If `m : M` and `h : r n₁ n₂`, then `CovariantClass.elim m h : r (μ m n₁) (μ m n₂)`.
-/
class CovariantClass : Prop where
/-- For all `m ∈ M` and all elements `n₁, n₂ ∈ N`, if the relation `r` holds for the pair
`(n₁, n₂)`, then, the relation `r` also holds for the pair `(μ m n₁, μ m n₂)` -/
protected elim : Covariant M N μ r
#align covariant_class CovariantClass
/-- Given an action `μ` of a Type `M` on a Type `N` and a relation `r` on `N`, informally, the
`ContravariantClass` says that "if the result of the action `μ` on a pair satisfies the
relation `r`, then the initial pair satisfied the relation `r`."
More precisely, the `ContravariantClass` is a class taking two Types `M N`, together with an
"action" `μ : M → N → N` and a relation `r : N → N → Prop`. Its unique field `elim` is the
assertion that for all `m ∈ M` and all elements `n₁, n₂ ∈ N`, if the relation `r` holds for the
pair `(μ m n₁, μ m n₂)` obtained from `(n₁, n₂)` by acting upon it by `m`, then, the relation
`r` also holds for the pair `(n₁, n₂)`.
If `m : M` and `h : r (μ m n₁) (μ m n₂)`, then `ContravariantClass.elim m h : r n₁ n₂`.
-/
class ContravariantClass : Prop where
/-- For all `m ∈ M` and all elements `n₁, n₂ ∈ N`, if the relation `r` holds for the
pair `(μ m n₁, μ m n₂)` obtained from `(n₁, n₂)` by acting upon it by `m`, then, the relation
`r` also holds for the pair `(n₁, n₂)`. -/
protected elim : Contravariant M N μ r
#align contravariant_class ContravariantClass
theorem rel_iff_cov [CovariantClass M N μ r] [ContravariantClass M N μ r] (m : M) {a b : N} :
r (μ m a) (μ m b) ↔ r a b :=
⟨ContravariantClass.elim _, CovariantClass.elim _⟩
#align rel_iff_cov rel_iff_cov
section flip
variable {M N μ r}
theorem Covariant.flip (h : Covariant M N μ r) : Covariant M N μ (flip r) :=
fun a _ _ ↦ h a
#align covariant.flip Covariant.flip
theorem Contravariant.flip (h : Contravariant M N μ r) : Contravariant M N μ (flip r) :=
fun a _ _ ↦ h a
#align contravariant.flip Contravariant.flip
end flip
section Covariant
variable {M N μ r} [CovariantClass M N μ r]
theorem act_rel_act_of_rel (m : M) {a b : N} (ab : r a b) : r (μ m a) (μ m b) :=
CovariantClass.elim _ ab
#align act_rel_act_of_rel act_rel_act_of_rel
@[to_additive]
theorem Group.covariant_iff_contravariant [Group N] :
Covariant N N (· * ·) r ↔ Contravariant N N (· * ·) r := by
refine ⟨fun h a b c bc ↦ ?_, fun h a b c bc ↦ ?_⟩
· rw [← inv_mul_cancel_left a b, ← inv_mul_cancel_left a c]
exact h a⁻¹ bc
· rw [← inv_mul_cancel_left a b, ← inv_mul_cancel_left a c] at bc
exact h a⁻¹ bc
#align group.covariant_iff_contravariant Group.covariant_iff_contravariant
#align add_group.covariant_iff_contravariant AddGroup.covariant_iff_contravariant
@[to_additive]
instance (priority := 100) Group.covconv [Group N] [CovariantClass N N (· * ·) r] :
ContravariantClass N N (· * ·) r :=
⟨Group.covariant_iff_contravariant.mp CovariantClass.elim⟩
@[to_additive]
theorem Group.covariant_swap_iff_contravariant_swap [Group N] :
Covariant N N (swap (· * ·)) r ↔ Contravariant N N (swap (· * ·)) r := by
refine ⟨fun h a b c bc ↦ ?_, fun h a b c bc ↦ ?_⟩
· rw [← mul_inv_cancel_right b a, ← mul_inv_cancel_right c a]
exact h a⁻¹ bc
· rw [← mul_inv_cancel_right b a, ← mul_inv_cancel_right c a] at bc
exact h a⁻¹ bc
#align group.covariant_swap_iff_contravariant_swap Group.covariant_swap_iff_contravariant_swap
#align add_group.covariant_swap_iff_contravariant_swap AddGroup.covariant_swap_iff_contravariant_swap
@[to_additive]
instance (priority := 100) Group.covconv_swap [Group N] [CovariantClass N N (swap (· * ·)) r] :
ContravariantClass N N (swap (· * ·)) r :=
⟨Group.covariant_swap_iff_contravariant_swap.mp CovariantClass.elim⟩
section Trans
variable [IsTrans N r] (m n : M) {a b c d : N}
-- Lemmas with 3 elements.
theorem act_rel_of_rel_of_act_rel (ab : r a b) (rl : r (μ m b) c) : r (μ m a) c :=
_root_.trans (act_rel_act_of_rel m ab) rl
#align act_rel_of_rel_of_act_rel act_rel_of_rel_of_act_rel
theorem rel_act_of_rel_of_rel_act (ab : r a b) (rr : r c (μ m a)) : r c (μ m b) :=
_root_.trans rr (act_rel_act_of_rel _ ab)
#align rel_act_of_rel_of_rel_act rel_act_of_rel_of_rel_act
end Trans
end Covariant
-- Lemma with 4 elements.
section MEqN
variable {M N μ r} {mu : N → N → N} [IsTrans N r] [i : CovariantClass N N mu r]
[i' : CovariantClass N N (swap mu) r] {a b c d : N}
theorem act_rel_act_of_rel_of_rel (ab : r a b) (cd : r c d) : r (mu a c) (mu b d) :=
_root_.trans (@act_rel_act_of_rel _ _ (swap mu) r _ c _ _ ab) (act_rel_act_of_rel b cd)
#align act_rel_act_of_rel_of_rel act_rel_act_of_rel_of_rel
end MEqN
section Contravariant
variable {M N μ r} [ContravariantClass M N μ r]
theorem rel_of_act_rel_act (m : M) {a b : N} (ab : r (μ m a) (μ m b)) : r a b :=
ContravariantClass.elim _ ab
#align rel_of_act_rel_act rel_of_act_rel_act
section Trans
variable [IsTrans N r] (m n : M) {a b c d : N}
-- Lemmas with 3 elements.
theorem act_rel_of_act_rel_of_rel_act_rel (ab : r (μ m a) b) (rl : r (μ m b) (μ m c)) :
r (μ m a) c :=
_root_.trans ab (rel_of_act_rel_act m rl)
#align act_rel_of_act_rel_of_rel_act_rel act_rel_of_act_rel_of_rel_act_rel
theorem rel_act_of_act_rel_act_of_rel_act (ab : r (μ m a) (μ m b)) (rr : r b (μ m c)) :
r a (μ m c) :=
_root_.trans (rel_of_act_rel_act m ab) rr
#align rel_act_of_act_rel_act_of_rel_act rel_act_of_act_rel_act_of_rel_act
end Trans
end Contravariant
section Monotone
variable {α : Type*} {M N μ} [Preorder α] [Preorder N]
variable {f : N → α}
/-- The partial application of a constant to a covariant operator is monotone. -/
theorem Covariant.monotone_of_const [CovariantClass M N μ (· ≤ ·)] (m : M) : Monotone (μ m) :=
fun _ _ ↦ CovariantClass.elim m
#align covariant.monotone_of_const Covariant.monotone_of_const
/-- A monotone function remains monotone when composed with the partial application
of a covariant operator. E.g., `∀ (m : ℕ), Monotone f → Monotone (fun n ↦ f (m + n))`. -/
theorem Monotone.covariant_of_const [CovariantClass M N μ (· ≤ ·)] (hf : Monotone f) (m : M) :
Monotone (f <| μ m ·) :=
hf.comp (Covariant.monotone_of_const m)
#align monotone.covariant_of_const Monotone.covariant_of_const
/-- Same as `Monotone.covariant_of_const`, but with the constant on the other side of
the operator. E.g., `∀ (m : ℕ), Monotone f → Monotone (fun n ↦ f (n + m))`. -/
theorem Monotone.covariant_of_const' {μ : N → N → N} [CovariantClass N N (swap μ) (· ≤ ·)]
(hf : Monotone f) (m : N) : Monotone (f <| μ · m) :=
Monotone.covariant_of_const (μ := swap μ) hf m
#align monotone.covariant_of_const' Monotone.covariant_of_const'
/-- Dual of `Monotone.covariant_of_const` -/
theorem Antitone.covariant_of_const [CovariantClass M N μ (· ≤ ·)] (hf : Antitone f) (m : M) :
Antitone (f <| μ m ·) :=
hf.comp_monotone <| Covariant.monotone_of_const m
#align antitone.covariant_of_const Antitone.covariant_of_const
/-- Dual of `Monotone.covariant_of_const'` -/
theorem Antitone.covariant_of_const' {μ : N → N → N} [CovariantClass N N (swap μ) (· ≤ ·)]
(hf : Antitone f) (m : N) : Antitone (f <| μ · m) :=
Antitone.covariant_of_const (μ := swap μ) hf m
#align antitone.covariant_of_const' Antitone.covariant_of_const'
end Monotone
theorem covariant_le_of_covariant_lt [PartialOrder N] :
Covariant M N μ (· < ·) → Covariant M N μ (· ≤ ·) := by
intro h a b c bc
rcases bc.eq_or_lt with (rfl | bc)
· exact le_rfl
· exact (h _ bc).le
#align covariant_le_of_covariant_lt covariant_le_of_covariant_lt
theorem covariantClass_le_of_lt [PartialOrder N] [CovariantClass M N μ (· < ·)] :
CovariantClass M N μ (· ≤ ·) := ⟨covariant_le_of_covariant_lt _ _ _ CovariantClass.elim⟩
theorem contravariant_le_iff_contravariant_lt_and_eq [PartialOrder N] :
Contravariant M N μ (· ≤ ·) ↔ Contravariant M N μ (· < ·) ∧ Contravariant M N μ (· = ·) := by
refine ⟨fun h ↦ ⟨fun a b c bc ↦ ?_, fun a b c bc ↦ ?_⟩, fun h ↦ fun a b c bc ↦ ?_⟩
· exact (h a bc.le).lt_of_ne (by rintro rfl; exact lt_irrefl _ bc)
· exact (h a bc.le).antisymm (h a bc.ge)
· exact bc.lt_or_eq.elim (fun bc ↦ (h.1 a bc).le) (fun bc ↦ (h.2 a bc).le)
theorem contravariant_lt_of_contravariant_le [PartialOrder N] :
Contravariant M N μ (· ≤ ·) → Contravariant M N μ (· < ·) :=
And.left ∘ (contravariant_le_iff_contravariant_lt_and_eq M N μ).mp
#align contravariant_lt_of_contravariant_le contravariant_lt_of_contravariant_le
theorem covariant_le_iff_contravariant_lt [LinearOrder N] :
Covariant M N μ (· ≤ ·) ↔ Contravariant M N μ (· < ·) :=
⟨fun h _ _ _ bc ↦ not_le.mp fun k ↦ bc.not_le (h _ k),
fun h _ _ _ bc ↦ not_lt.mp fun k ↦ bc.not_lt (h _ k)⟩
#align covariant_le_iff_contravariant_lt covariant_le_iff_contravariant_lt
theorem covariant_lt_iff_contravariant_le [LinearOrder N] :
Covariant M N μ (· < ·) ↔ Contravariant M N μ (· ≤ ·) :=
⟨fun h _ _ _ bc ↦ not_lt.mp fun k ↦ bc.not_lt (h _ k),
fun h _ _ _ bc ↦ not_le.mp fun k ↦ bc.not_le (h _ k)⟩
#align covariant_lt_iff_contravariant_le covariant_lt_iff_contravariant_le
variable (mu : N → N → N)
theorem covariant_flip_iff [IsSymmOp N N mu] :
Covariant N N (flip mu) r ↔ Covariant N N mu r := by rw [IsSymmOp.flip_eq]
#noalign covariant_flip_mul_iff
#noalign covariant_flip_add_iff
| Mathlib/Algebra/Order/Monoid/Unbundled/Defs.lean | 323 | 324 | theorem contravariant_flip_iff [IsSymmOp N N mu] :
Contravariant N N (flip mu) r ↔ Contravariant N N mu r := by | rw [IsSymmOp.flip_eq]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Basic
import Mathlib.Data.Nat.SuccPred
#align_import set_theory.ordinal.arithmetic from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Ordinal arithmetic
Ordinals have an addition (corresponding to disjoint union) that turns them into an additive
monoid, and a multiplication (corresponding to the lexicographic order on the product) that turns
them into a monoid. One can also define correspondingly a subtraction, a division, a successor
function, a power function and a logarithm function.
We also define limit ordinals and prove the basic induction principle on ordinals separating
successor ordinals and limit ordinals, in `limitRecOn`.
## Main definitions and results
* `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that
every element of `o₁` is smaller than every element of `o₂`.
* `o₁ - o₂` is the unique ordinal `o` such that `o₂ + o = o₁`, when `o₂ ≤ o₁`.
* `o₁ * o₂` is the lexicographic order on `o₂ × o₁`.
* `o₁ / o₂` is the ordinal `o` such that `o₁ = o₂ * o + o'` with `o' < o₂`. We also define the
divisibility predicate, and a modulo operation.
* `Order.succ o = o + 1` is the successor of `o`.
* `pred o` if the predecessor of `o`. If `o` is not a successor, we set `pred o = o`.
We discuss the properties of casts of natural numbers of and of `ω` with respect to these
operations.
Some properties of the operations are also used to discuss general tools on ordinals:
* `IsLimit o`: an ordinal is a limit ordinal if it is neither `0` nor a successor.
* `limitRecOn` is the main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals.
* `IsNormal`: a function `f : Ordinal → Ordinal` satisfies `IsNormal` if it is strictly increasing
and order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`.
* `enumOrd`: enumerates an unbounded set of ordinals by the ordinals themselves.
* `sup`, `lsub`: the supremum / least strict upper bound of an indexed family of ordinals in
`Type u`, as an ordinal in `Type u`.
* `bsup`, `blsub`: the supremum / least strict upper bound of a set of ordinals indexed by ordinals
less than a given ordinal `o`.
Various other basic arithmetic results are given in `Principal.lean` instead.
-/
assert_not_exists Field
assert_not_exists Module
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal Ordinal
universe u v w
namespace Ordinal
variable {α : Type*} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Further properties of addition on ordinals -/
@[simp]
theorem lift_add (a b : Ordinal.{v}) : lift.{u} (a + b) = lift.{u} a + lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.sumLexCongr (RelIso.preimage Equiv.ulift _) (RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_add Ordinal.lift_add
@[simp]
theorem lift_succ (a : Ordinal.{v}) : lift.{u} (succ a) = succ (lift.{u} a) := by
rw [← add_one_eq_succ, lift_add, lift_one]
rfl
#align ordinal.lift_succ Ordinal.lift_succ
instance add_contravariantClass_le : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· ≤ ·) :=
⟨fun a b c =>
inductionOn a fun α r hr =>
inductionOn b fun β₁ s₁ hs₁ =>
inductionOn c fun β₂ s₂ hs₂ ⟨f⟩ =>
⟨have fl : ∀ a, f (Sum.inl a) = Sum.inl a := fun a => by
simpa only [InitialSeg.trans_apply, InitialSeg.leAdd_apply] using
@InitialSeg.eq _ _ _ _ _
((InitialSeg.leAdd r s₁).trans f) (InitialSeg.leAdd r s₂) a
have : ∀ b, { b' // f (Sum.inr b) = Sum.inr b' } := by
intro b; cases e : f (Sum.inr b)
· rw [← fl] at e
have := f.inj' e
contradiction
· exact ⟨_, rfl⟩
let g (b) := (this b).1
have fr : ∀ b, f (Sum.inr b) = Sum.inr (g b) := fun b => (this b).2
⟨⟨⟨g, fun x y h => by
injection f.inj' (by rw [fr, fr, h] : f (Sum.inr x) = f (Sum.inr y))⟩,
@fun a b => by
-- Porting note:
-- `relEmbedding.coe_fn_to_embedding` & `initial_seg.coe_fn_to_rel_embedding`
-- → `InitialSeg.coe_coe_fn`
simpa only [Sum.lex_inr_inr, fr, InitialSeg.coe_coe_fn, Embedding.coeFn_mk] using
@RelEmbedding.map_rel_iff _ _ _ _ f.toRelEmbedding (Sum.inr a) (Sum.inr b)⟩,
fun a b H => by
rcases f.init (by rw [fr] <;> exact Sum.lex_inr_inr.2 H) with ⟨a' | a', h⟩
· rw [fl] at h
cases h
· rw [fr] at h
exact ⟨a', Sum.inr.inj h⟩⟩⟩⟩
#align ordinal.add_contravariant_class_le Ordinal.add_contravariantClass_le
theorem add_left_cancel (a) {b c : Ordinal} : a + b = a + c ↔ b = c := by
simp only [le_antisymm_iff, add_le_add_iff_left]
#align ordinal.add_left_cancel Ordinal.add_left_cancel
private theorem add_lt_add_iff_left' (a) {b c : Ordinal} : a + b < a + c ↔ b < c := by
rw [← not_le, ← not_le, add_le_add_iff_left]
instance add_covariantClass_lt : CovariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).2⟩
#align ordinal.add_covariant_class_lt Ordinal.add_covariantClass_lt
instance add_contravariantClass_lt : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).1⟩
#align ordinal.add_contravariant_class_lt Ordinal.add_contravariantClass_lt
instance add_swap_contravariantClass_lt :
ContravariantClass Ordinal.{u} Ordinal.{u} (swap (· + ·)) (· < ·) :=
⟨fun _a _b _c => lt_imp_lt_of_le_imp_le fun h => add_le_add_right h _⟩
#align ordinal.add_swap_contravariant_class_lt Ordinal.add_swap_contravariantClass_lt
theorem add_le_add_iff_right {a b : Ordinal} : ∀ n : ℕ, a + n ≤ b + n ↔ a ≤ b
| 0 => by simp
| n + 1 => by
simp only [natCast_succ, add_succ, add_succ, succ_le_succ_iff, add_le_add_iff_right]
#align ordinal.add_le_add_iff_right Ordinal.add_le_add_iff_right
theorem add_right_cancel {a b : Ordinal} (n : ℕ) : a + n = b + n ↔ a = b := by
simp only [le_antisymm_iff, add_le_add_iff_right]
#align ordinal.add_right_cancel Ordinal.add_right_cancel
theorem add_eq_zero_iff {a b : Ordinal} : a + b = 0 ↔ a = 0 ∧ b = 0 :=
inductionOn a fun α r _ =>
inductionOn b fun β s _ => by
simp_rw [← type_sum_lex, type_eq_zero_iff_isEmpty]
exact isEmpty_sum
#align ordinal.add_eq_zero_iff Ordinal.add_eq_zero_iff
theorem left_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : a = 0 :=
(add_eq_zero_iff.1 h).1
#align ordinal.left_eq_zero_of_add_eq_zero Ordinal.left_eq_zero_of_add_eq_zero
theorem right_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : b = 0 :=
(add_eq_zero_iff.1 h).2
#align ordinal.right_eq_zero_of_add_eq_zero Ordinal.right_eq_zero_of_add_eq_zero
/-! ### The predecessor of an ordinal -/
/-- The ordinal predecessor of `o` is `o'` if `o = succ o'`,
and `o` otherwise. -/
def pred (o : Ordinal) : Ordinal :=
if h : ∃ a, o = succ a then Classical.choose h else o
#align ordinal.pred Ordinal.pred
@[simp]
theorem pred_succ (o) : pred (succ o) = o := by
have h : ∃ a, succ o = succ a := ⟨_, rfl⟩;
simpa only [pred, dif_pos h] using (succ_injective <| Classical.choose_spec h).symm
#align ordinal.pred_succ Ordinal.pred_succ
theorem pred_le_self (o) : pred o ≤ o :=
if h : ∃ a, o = succ a then by
let ⟨a, e⟩ := h
rw [e, pred_succ]; exact le_succ a
else by rw [pred, dif_neg h]
#align ordinal.pred_le_self Ordinal.pred_le_self
theorem pred_eq_iff_not_succ {o} : pred o = o ↔ ¬∃ a, o = succ a :=
⟨fun e ⟨a, e'⟩ => by rw [e', pred_succ] at e; exact (lt_succ a).ne e, fun h => dif_neg h⟩
#align ordinal.pred_eq_iff_not_succ Ordinal.pred_eq_iff_not_succ
theorem pred_eq_iff_not_succ' {o} : pred o = o ↔ ∀ a, o ≠ succ a := by
simpa using pred_eq_iff_not_succ
#align ordinal.pred_eq_iff_not_succ' Ordinal.pred_eq_iff_not_succ'
theorem pred_lt_iff_is_succ {o} : pred o < o ↔ ∃ a, o = succ a :=
Iff.trans (by simp only [le_antisymm_iff, pred_le_self, true_and_iff, not_le])
(iff_not_comm.1 pred_eq_iff_not_succ).symm
#align ordinal.pred_lt_iff_is_succ Ordinal.pred_lt_iff_is_succ
@[simp]
theorem pred_zero : pred 0 = 0 :=
pred_eq_iff_not_succ'.2 fun a => (succ_ne_zero a).symm
#align ordinal.pred_zero Ordinal.pred_zero
theorem succ_pred_iff_is_succ {o} : succ (pred o) = o ↔ ∃ a, o = succ a :=
⟨fun e => ⟨_, e.symm⟩, fun ⟨a, e⟩ => by simp only [e, pred_succ]⟩
#align ordinal.succ_pred_iff_is_succ Ordinal.succ_pred_iff_is_succ
theorem succ_lt_of_not_succ {o b : Ordinal} (h : ¬∃ a, o = succ a) : succ b < o ↔ b < o :=
⟨(lt_succ b).trans, fun l => lt_of_le_of_ne (succ_le_of_lt l) fun e => h ⟨_, e.symm⟩⟩
#align ordinal.succ_lt_of_not_succ Ordinal.succ_lt_of_not_succ
theorem lt_pred {a b} : a < pred b ↔ succ a < b :=
if h : ∃ a, b = succ a then by
let ⟨c, e⟩ := h
rw [e, pred_succ, succ_lt_succ_iff]
else by simp only [pred, dif_neg h, succ_lt_of_not_succ h]
#align ordinal.lt_pred Ordinal.lt_pred
theorem pred_le {a b} : pred a ≤ b ↔ a ≤ succ b :=
le_iff_le_iff_lt_iff_lt.2 lt_pred
#align ordinal.pred_le Ordinal.pred_le
@[simp]
theorem lift_is_succ {o : Ordinal.{v}} : (∃ a, lift.{u} o = succ a) ↔ ∃ a, o = succ a :=
⟨fun ⟨a, h⟩ =>
let ⟨b, e⟩ := lift_down <| show a ≤ lift.{u} o from le_of_lt <| h.symm ▸ lt_succ a
⟨b, lift_inj.1 <| by rw [h, ← e, lift_succ]⟩,
fun ⟨a, h⟩ => ⟨lift.{u} a, by simp only [h, lift_succ]⟩⟩
#align ordinal.lift_is_succ Ordinal.lift_is_succ
@[simp]
theorem lift_pred (o : Ordinal.{v}) : lift.{u} (pred o) = pred (lift.{u} o) :=
if h : ∃ a, o = succ a then by cases' h with a e; simp only [e, pred_succ, lift_succ]
else by rw [pred_eq_iff_not_succ.2 h, pred_eq_iff_not_succ.2 (mt lift_is_succ.1 h)]
#align ordinal.lift_pred Ordinal.lift_pred
/-! ### Limit ordinals -/
/-- A limit ordinal is an ordinal which is not zero and not a successor. -/
def IsLimit (o : Ordinal) : Prop :=
o ≠ 0 ∧ ∀ a < o, succ a < o
#align ordinal.is_limit Ordinal.IsLimit
theorem IsLimit.isSuccLimit {o} (h : IsLimit o) : IsSuccLimit o := isSuccLimit_iff_succ_lt.mpr h.2
theorem IsLimit.succ_lt {o a : Ordinal} (h : IsLimit o) : a < o → succ a < o :=
h.2 a
#align ordinal.is_limit.succ_lt Ordinal.IsLimit.succ_lt
theorem isSuccLimit_zero : IsSuccLimit (0 : Ordinal) := isSuccLimit_bot
theorem not_zero_isLimit : ¬IsLimit 0
| ⟨h, _⟩ => h rfl
#align ordinal.not_zero_is_limit Ordinal.not_zero_isLimit
theorem not_succ_isLimit (o) : ¬IsLimit (succ o)
| ⟨_, h⟩ => lt_irrefl _ (h _ (lt_succ o))
#align ordinal.not_succ_is_limit Ordinal.not_succ_isLimit
theorem not_succ_of_isLimit {o} (h : IsLimit o) : ¬∃ a, o = succ a
| ⟨a, e⟩ => not_succ_isLimit a (e ▸ h)
#align ordinal.not_succ_of_is_limit Ordinal.not_succ_of_isLimit
theorem succ_lt_of_isLimit {o a : Ordinal} (h : IsLimit o) : succ a < o ↔ a < o :=
⟨(lt_succ a).trans, h.2 _⟩
#align ordinal.succ_lt_of_is_limit Ordinal.succ_lt_of_isLimit
theorem le_succ_of_isLimit {o} (h : IsLimit o) {a} : o ≤ succ a ↔ o ≤ a :=
le_iff_le_iff_lt_iff_lt.2 <| succ_lt_of_isLimit h
#align ordinal.le_succ_of_is_limit Ordinal.le_succ_of_isLimit
theorem limit_le {o} (h : IsLimit o) {a} : o ≤ a ↔ ∀ x < o, x ≤ a :=
⟨fun h _x l => l.le.trans h, fun H =>
(le_succ_of_isLimit h).1 <| le_of_not_lt fun hn => not_lt_of_le (H _ hn) (lt_succ a)⟩
#align ordinal.limit_le Ordinal.limit_le
theorem lt_limit {o} (h : IsLimit o) {a} : a < o ↔ ∃ x < o, a < x := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@limit_le _ h a)
#align ordinal.lt_limit Ordinal.lt_limit
@[simp]
theorem lift_isLimit (o) : IsLimit (lift o) ↔ IsLimit o :=
and_congr (not_congr <| by simpa only [lift_zero] using @lift_inj o 0)
⟨fun H a h => lift_lt.1 <| by simpa only [lift_succ] using H _ (lift_lt.2 h), fun H a h => by
obtain ⟨a', rfl⟩ := lift_down h.le
rw [← lift_succ, lift_lt]
exact H a' (lift_lt.1 h)⟩
#align ordinal.lift_is_limit Ordinal.lift_isLimit
theorem IsLimit.pos {o : Ordinal} (h : IsLimit o) : 0 < o :=
lt_of_le_of_ne (Ordinal.zero_le _) h.1.symm
#align ordinal.is_limit.pos Ordinal.IsLimit.pos
theorem IsLimit.one_lt {o : Ordinal} (h : IsLimit o) : 1 < o := by
simpa only [succ_zero] using h.2 _ h.pos
#align ordinal.is_limit.one_lt Ordinal.IsLimit.one_lt
theorem IsLimit.nat_lt {o : Ordinal} (h : IsLimit o) : ∀ n : ℕ, (n : Ordinal) < o
| 0 => h.pos
| n + 1 => h.2 _ (IsLimit.nat_lt h n)
#align ordinal.is_limit.nat_lt Ordinal.IsLimit.nat_lt
theorem zero_or_succ_or_limit (o : Ordinal) : o = 0 ∨ (∃ a, o = succ a) ∨ IsLimit o :=
if o0 : o = 0 then Or.inl o0
else
if h : ∃ a, o = succ a then Or.inr (Or.inl h)
else Or.inr <| Or.inr ⟨o0, fun _a => (succ_lt_of_not_succ h).2⟩
#align ordinal.zero_or_succ_or_limit Ordinal.zero_or_succ_or_limit
/-- Main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals. -/
@[elab_as_elim]
def limitRecOn {C : Ordinal → Sort*} (o : Ordinal) (H₁ : C 0) (H₂ : ∀ o, C o → C (succ o))
(H₃ : ∀ o, IsLimit o → (∀ o' < o, C o') → C o) : C o :=
SuccOrder.limitRecOn o (fun o _ ↦ H₂ o) fun o hl ↦
if h : o = 0 then fun _ ↦ h ▸ H₁ else H₃ o ⟨h, fun _ ↦ hl.succ_lt⟩
#align ordinal.limit_rec_on Ordinal.limitRecOn
@[simp]
theorem limitRecOn_zero {C} (H₁ H₂ H₃) : @limitRecOn C 0 H₁ H₂ H₃ = H₁ := by
rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ isSuccLimit_zero, dif_pos rfl]
#align ordinal.limit_rec_on_zero Ordinal.limitRecOn_zero
@[simp]
theorem limitRecOn_succ {C} (o H₁ H₂ H₃) :
@limitRecOn C (succ o) H₁ H₂ H₃ = H₂ o (@limitRecOn C o H₁ H₂ H₃) := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_succ _ _ (not_isMax _)]
#align ordinal.limit_rec_on_succ Ordinal.limitRecOn_succ
@[simp]
theorem limitRecOn_limit {C} (o H₁ H₂ H₃ h) :
@limitRecOn C o H₁ H₂ H₃ = H₃ o h fun x _h => @limitRecOn C x H₁ H₂ H₃ := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ h.isSuccLimit, dif_neg h.1]
#align ordinal.limit_rec_on_limit Ordinal.limitRecOn_limit
instance orderTopOutSucc (o : Ordinal) : OrderTop (succ o).out.α :=
@OrderTop.mk _ _ (Top.mk _) le_enum_succ
#align ordinal.order_top_out_succ Ordinal.orderTopOutSucc
theorem enum_succ_eq_top {o : Ordinal} :
enum (· < ·) o
(by
rw [type_lt]
exact lt_succ o) =
(⊤ : (succ o).out.α) :=
rfl
#align ordinal.enum_succ_eq_top Ordinal.enum_succ_eq_top
theorem has_succ_of_type_succ_lt {α} {r : α → α → Prop} [wo : IsWellOrder α r]
(h : ∀ a < type r, succ a < type r) (x : α) : ∃ y, r x y := by
use enum r (succ (typein r x)) (h _ (typein_lt_type r x))
convert (enum_lt_enum (typein_lt_type r x)
(h _ (typein_lt_type r x))).mpr (lt_succ _); rw [enum_typein]
#align ordinal.has_succ_of_type_succ_lt Ordinal.has_succ_of_type_succ_lt
theorem out_no_max_of_succ_lt {o : Ordinal} (ho : ∀ a < o, succ a < o) : NoMaxOrder o.out.α :=
⟨has_succ_of_type_succ_lt (by rwa [type_lt])⟩
#align ordinal.out_no_max_of_succ_lt Ordinal.out_no_max_of_succ_lt
theorem bounded_singleton {r : α → α → Prop} [IsWellOrder α r] (hr : (type r).IsLimit) (x) :
Bounded r {x} := by
refine ⟨enum r (succ (typein r x)) (hr.2 _ (typein_lt_type r x)), ?_⟩
intro b hb
rw [mem_singleton_iff.1 hb]
nth_rw 1 [← enum_typein r x]
rw [@enum_lt_enum _ r]
apply lt_succ
#align ordinal.bounded_singleton Ordinal.bounded_singleton
-- Porting note: `· < ·` requires a type ascription for an `IsWellOrder` instance.
theorem type_subrel_lt (o : Ordinal.{u}) :
type (Subrel ((· < ·) : Ordinal → Ordinal → Prop) { o' : Ordinal | o' < o })
= Ordinal.lift.{u + 1} o := by
refine Quotient.inductionOn o ?_
rintro ⟨α, r, wo⟩; apply Quotient.sound
-- Porting note: `symm; refine' [term]` → `refine' [term].symm`
constructor; refine ((RelIso.preimage Equiv.ulift r).trans (enumIso r).symm).symm
#align ordinal.type_subrel_lt Ordinal.type_subrel_lt
theorem mk_initialSeg (o : Ordinal.{u}) :
#{ o' : Ordinal | o' < o } = Cardinal.lift.{u + 1} o.card := by
rw [lift_card, ← type_subrel_lt, card_type]
#align ordinal.mk_initial_seg Ordinal.mk_initialSeg
/-! ### Normal ordinal functions -/
/-- A normal ordinal function is a strictly increasing function which is
order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`. -/
def IsNormal (f : Ordinal → Ordinal) : Prop :=
(∀ o, f o < f (succ o)) ∧ ∀ o, IsLimit o → ∀ a, f o ≤ a ↔ ∀ b < o, f b ≤ a
#align ordinal.is_normal Ordinal.IsNormal
theorem IsNormal.limit_le {f} (H : IsNormal f) :
∀ {o}, IsLimit o → ∀ {a}, f o ≤ a ↔ ∀ b < o, f b ≤ a :=
@H.2
#align ordinal.is_normal.limit_le Ordinal.IsNormal.limit_le
theorem IsNormal.limit_lt {f} (H : IsNormal f) {o} (h : IsLimit o) {a} :
a < f o ↔ ∃ b < o, a < f b :=
not_iff_not.1 <| by simpa only [exists_prop, not_exists, not_and, not_lt] using H.2 _ h a
#align ordinal.is_normal.limit_lt Ordinal.IsNormal.limit_lt
theorem IsNormal.strictMono {f} (H : IsNormal f) : StrictMono f := fun a b =>
limitRecOn b (Not.elim (not_lt_of_le <| Ordinal.zero_le _))
(fun _b IH h =>
(lt_or_eq_of_le (le_of_lt_succ h)).elim (fun h => (IH h).trans (H.1 _)) fun e => e ▸ H.1 _)
fun _b l _IH h => lt_of_lt_of_le (H.1 a) ((H.2 _ l _).1 le_rfl _ (l.2 _ h))
#align ordinal.is_normal.strict_mono Ordinal.IsNormal.strictMono
theorem IsNormal.monotone {f} (H : IsNormal f) : Monotone f :=
H.strictMono.monotone
#align ordinal.is_normal.monotone Ordinal.IsNormal.monotone
theorem isNormal_iff_strictMono_limit (f : Ordinal → Ordinal) :
IsNormal f ↔ StrictMono f ∧ ∀ o, IsLimit o → ∀ a, (∀ b < o, f b ≤ a) → f o ≤ a :=
⟨fun hf => ⟨hf.strictMono, fun a ha c => (hf.2 a ha c).2⟩, fun ⟨hs, hl⟩ =>
⟨fun a => hs (lt_succ a), fun a ha c =>
⟨fun hac _b hba => ((hs hba).trans_le hac).le, hl a ha c⟩⟩⟩
#align ordinal.is_normal_iff_strict_mono_limit Ordinal.isNormal_iff_strictMono_limit
theorem IsNormal.lt_iff {f} (H : IsNormal f) {a b} : f a < f b ↔ a < b :=
StrictMono.lt_iff_lt <| H.strictMono
#align ordinal.is_normal.lt_iff Ordinal.IsNormal.lt_iff
theorem IsNormal.le_iff {f} (H : IsNormal f) {a b} : f a ≤ f b ↔ a ≤ b :=
le_iff_le_iff_lt_iff_lt.2 H.lt_iff
#align ordinal.is_normal.le_iff Ordinal.IsNormal.le_iff
theorem IsNormal.inj {f} (H : IsNormal f) {a b} : f a = f b ↔ a = b := by
simp only [le_antisymm_iff, H.le_iff]
#align ordinal.is_normal.inj Ordinal.IsNormal.inj
theorem IsNormal.self_le {f} (H : IsNormal f) (a) : a ≤ f a :=
lt_wf.self_le_of_strictMono H.strictMono a
#align ordinal.is_normal.self_le Ordinal.IsNormal.self_le
theorem IsNormal.le_set {f o} (H : IsNormal f) (p : Set Ordinal) (p0 : p.Nonempty) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f a ≤ o :=
⟨fun h a pa => (H.le_iff.2 ((H₂ _).1 le_rfl _ pa)).trans h, fun h => by
-- Porting note: `refine'` didn't work well so `induction` is used
induction b using limitRecOn with
| H₁ =>
cases' p0 with x px
have := Ordinal.le_zero.1 ((H₂ _).1 (Ordinal.zero_le _) _ px)
rw [this] at px
exact h _ px
| H₂ S _ =>
rcases not_forall₂.1 (mt (H₂ S).2 <| (lt_succ S).not_le) with ⟨a, h₁, h₂⟩
exact (H.le_iff.2 <| succ_le_of_lt <| not_le.1 h₂).trans (h _ h₁)
| H₃ S L _ =>
refine (H.2 _ L _).2 fun a h' => ?_
rcases not_forall₂.1 (mt (H₂ a).2 h'.not_le) with ⟨b, h₁, h₂⟩
exact (H.le_iff.2 <| (not_le.1 h₂).le).trans (h _ h₁)⟩
#align ordinal.is_normal.le_set Ordinal.IsNormal.le_set
| Mathlib/SetTheory/Ordinal/Arithmetic.lean | 460 | 462 | theorem IsNormal.le_set' {f o} (H : IsNormal f) (p : Set α) (p0 : p.Nonempty) (g : α → Ordinal) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, g a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f (g a) ≤ o := by |
simpa [H₂] using H.le_set (g '' p) (p0.image g) b
|
/-
Copyright (c) 2018 Violeta Hernández Palacios, Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Violeta Hernández Palacios, Mario Carneiro
-/
import Mathlib.SetTheory.Ordinal.Arithmetic
import Mathlib.SetTheory.Ordinal.Exponential
#align_import set_theory.ordinal.fixed_point from "leanprover-community/mathlib"@"0dd4319a17376eda5763cd0a7e0d35bbaaa50e83"
/-!
# Fixed points of normal functions
We prove various statements about the fixed points of normal ordinal functions. We state them in
three forms: as statements about type-indexed families of normal functions, as statements about
ordinal-indexed families of normal functions, and as statements about a single normal function. For
the most part, the first case encompasses the others.
Moreover, we prove some lemmas about the fixed points of specific normal functions.
## Main definitions and results
* `nfpFamily`, `nfpBFamily`, `nfp`: the next fixed point of a (family of) normal function(s).
* `fp_family_unbounded`, `fp_bfamily_unbounded`, `fp_unbounded`: the (common) fixed points of a
(family of) normal function(s) are unbounded in the ordinals.
* `deriv_add_eq_mul_omega_add`: a characterization of the derivative of addition.
* `deriv_mul_eq_opow_omega_mul`: a characterization of the derivative of multiplication.
-/
noncomputable section
universe u v
open Function Order
namespace Ordinal
/-! ### Fixed points of type-indexed families of ordinals -/
section
variable {ι : Type u} {f : ι → Ordinal.{max u v} → Ordinal.{max u v}}
/-- The next common fixed point, at least `a`, for a family of normal functions.
This is defined for any family of functions, as the supremum of all values reachable by applying
finitely many functions in the family to `a`.
`Ordinal.nfpFamily_fp` shows this is a fixed point, `Ordinal.le_nfpFamily` shows it's at
least `a`, and `Ordinal.nfpFamily_le_fp` shows this is the least ordinal with these properties. -/
def nfpFamily (f : ι → Ordinal → Ordinal) (a : Ordinal) : Ordinal :=
sup (List.foldr f a)
#align ordinal.nfp_family Ordinal.nfpFamily
theorem nfpFamily_eq_sup (f : ι → Ordinal.{max u v} → Ordinal.{max u v}) (a : Ordinal.{max u v}) :
nfpFamily.{u, v} f a = sup.{u, v} (List.foldr f a) :=
rfl
#align ordinal.nfp_family_eq_sup Ordinal.nfpFamily_eq_sup
theorem foldr_le_nfpFamily (f : ι → Ordinal → Ordinal)
(a l) : List.foldr f a l ≤ nfpFamily.{u, v} f a :=
le_sup.{u, v} _ _
#align ordinal.foldr_le_nfp_family Ordinal.foldr_le_nfpFamily
theorem le_nfpFamily (f : ι → Ordinal → Ordinal) (a) : a ≤ nfpFamily f a :=
le_sup _ []
#align ordinal.le_nfp_family Ordinal.le_nfpFamily
theorem lt_nfpFamily {a b} : a < nfpFamily.{u, v} f b ↔ ∃ l, a < List.foldr f b l :=
lt_sup.{u, v}
#align ordinal.lt_nfp_family Ordinal.lt_nfpFamily
theorem nfpFamily_le_iff {a b} : nfpFamily.{u, v} f a ≤ b ↔ ∀ l, List.foldr f a l ≤ b :=
sup_le_iff
#align ordinal.nfp_family_le_iff Ordinal.nfpFamily_le_iff
theorem nfpFamily_le {a b} : (∀ l, List.foldr f a l ≤ b) → nfpFamily.{u, v} f a ≤ b :=
sup_le.{u, v}
#align ordinal.nfp_family_le Ordinal.nfpFamily_le
theorem nfpFamily_monotone (hf : ∀ i, Monotone (f i)) : Monotone (nfpFamily.{u, v} f) :=
fun _ _ h => sup_le.{u, v} fun l => (List.foldr_monotone hf l h).trans (le_sup.{u, v} _ l)
#align ordinal.nfp_family_monotone Ordinal.nfpFamily_monotone
theorem apply_lt_nfpFamily (H : ∀ i, IsNormal (f i)) {a b} (hb : b < nfpFamily.{u, v} f a) (i) :
f i b < nfpFamily.{u, v} f a :=
let ⟨l, hl⟩ := lt_nfpFamily.1 hb
lt_sup.2 ⟨i::l, (H i).strictMono hl⟩
#align ordinal.apply_lt_nfp_family Ordinal.apply_lt_nfpFamily
theorem apply_lt_nfpFamily_iff [Nonempty ι] (H : ∀ i, IsNormal (f i)) {a b} :
(∀ i, f i b < nfpFamily.{u, v} f a) ↔ b < nfpFamily.{u, v} f a :=
⟨fun h =>
lt_nfpFamily.2 <|
let ⟨l, hl⟩ := lt_sup.1 <| h <| Classical.arbitrary ι
⟨l, ((H _).self_le b).trans_lt hl⟩,
apply_lt_nfpFamily H⟩
#align ordinal.apply_lt_nfp_family_iff Ordinal.apply_lt_nfpFamily_iff
theorem nfpFamily_le_apply [Nonempty ι] (H : ∀ i, IsNormal (f i)) {a b} :
(∃ i, nfpFamily.{u, v} f a ≤ f i b) ↔ nfpFamily.{u, v} f a ≤ b := by
rw [← not_iff_not]
push_neg
exact apply_lt_nfpFamily_iff H
#align ordinal.nfp_family_le_apply Ordinal.nfpFamily_le_apply
theorem nfpFamily_le_fp (H : ∀ i, Monotone (f i)) {a b} (ab : a ≤ b) (h : ∀ i, f i b ≤ b) :
nfpFamily.{u, v} f a ≤ b :=
sup_le fun l => by
by_cases hι : IsEmpty ι
· rwa [Unique.eq_default l]
· induction' l with i l IH generalizing a
· exact ab
exact (H i (IH ab)).trans (h i)
#align ordinal.nfp_family_le_fp Ordinal.nfpFamily_le_fp
theorem nfpFamily_fp {i} (H : IsNormal (f i)) (a) :
f i (nfpFamily.{u, v} f a) = nfpFamily.{u, v} f a := by
unfold nfpFamily
rw [@IsNormal.sup.{u, v, v} _ H _ _ ⟨[]⟩]
apply le_antisymm <;> refine Ordinal.sup_le fun l => ?_
· exact le_sup _ (i::l)
· exact (H.self_le _).trans (le_sup _ _)
#align ordinal.nfp_family_fp Ordinal.nfpFamily_fp
theorem apply_le_nfpFamily [hι : Nonempty ι] {f : ι → Ordinal → Ordinal} (H : ∀ i, IsNormal (f i))
{a b} : (∀ i, f i b ≤ nfpFamily.{u, v} f a) ↔ b ≤ nfpFamily.{u, v} f a := by
refine ⟨fun h => ?_, fun h i => ?_⟩
· cases' hι with i
exact ((H i).self_le b).trans (h i)
rw [← nfpFamily_fp (H i)]
exact (H i).monotone h
#align ordinal.apply_le_nfp_family Ordinal.apply_le_nfpFamily
theorem nfpFamily_eq_self {f : ι → Ordinal → Ordinal} {a} (h : ∀ i, f i a = a) :
nfpFamily f a = a :=
le_antisymm (sup_le fun l => by rw [List.foldr_fixed' h l]) <| le_nfpFamily f a
#align ordinal.nfp_family_eq_self Ordinal.nfpFamily_eq_self
-- Todo: This is actually a special case of the fact the intersection of club sets is a club set.
/-- A generalization of the fixed point lemma for normal functions: any family of normal functions
has an unbounded set of common fixed points. -/
theorem fp_family_unbounded (H : ∀ i, IsNormal (f i)) :
(⋂ i, Function.fixedPoints (f i)).Unbounded (· < ·) := fun a =>
⟨nfpFamily.{u, v} f a, fun s ⟨i, hi⟩ => by
rw [← hi, mem_fixedPoints_iff]
exact nfpFamily_fp.{u, v} (H i) a, (le_nfpFamily f a).not_lt⟩
#align ordinal.fp_family_unbounded Ordinal.fp_family_unbounded
/-- The derivative of a family of normal functions is the sequence of their common fixed points.
This is defined for all functions such that `Ordinal.derivFamily_zero`,
`Ordinal.derivFamily_succ`, and `Ordinal.derivFamily_limit` are satisfied. -/
def derivFamily (f : ι → Ordinal → Ordinal) (o : Ordinal) : Ordinal :=
limitRecOn o (nfpFamily.{u, v} f 0) (fun _ IH => nfpFamily.{u, v} f (succ IH))
fun a _ => bsup.{max u v, u} a
#align ordinal.deriv_family Ordinal.derivFamily
@[simp]
theorem derivFamily_zero (f : ι → Ordinal → Ordinal) :
derivFamily.{u, v} f 0 = nfpFamily.{u, v} f 0 :=
limitRecOn_zero _ _ _
#align ordinal.deriv_family_zero Ordinal.derivFamily_zero
@[simp]
theorem derivFamily_succ (f : ι → Ordinal → Ordinal) (o) :
derivFamily.{u, v} f (succ o) = nfpFamily.{u, v} f (succ (derivFamily.{u, v} f o)) :=
limitRecOn_succ _ _ _ _
#align ordinal.deriv_family_succ Ordinal.derivFamily_succ
theorem derivFamily_limit (f : ι → Ordinal → Ordinal) {o} :
IsLimit o → derivFamily.{u, v} f o = bsup.{max u v, u} o fun a _ => derivFamily.{u, v} f a :=
limitRecOn_limit _ _ _ _
#align ordinal.deriv_family_limit Ordinal.derivFamily_limit
theorem derivFamily_isNormal (f : ι → Ordinal → Ordinal) : IsNormal (derivFamily f) :=
⟨fun o => by rw [derivFamily_succ, ← succ_le_iff]; apply le_nfpFamily, fun o l a => by
rw [derivFamily_limit _ l, bsup_le_iff]⟩
#align ordinal.deriv_family_is_normal Ordinal.derivFamily_isNormal
theorem derivFamily_fp {i} (H : IsNormal (f i)) (o : Ordinal.{max u v}) :
f i (derivFamily.{u, v} f o) = derivFamily.{u, v} f o := by
induction' o using limitRecOn with o _ o l IH
· rw [derivFamily_zero]
exact nfpFamily_fp H 0
· rw [derivFamily_succ]
exact nfpFamily_fp H _
· rw [derivFamily_limit _ l,
IsNormal.bsup.{max u v, u, max u v} H (fun a _ => derivFamily f a) l.1]
refine eq_of_forall_ge_iff fun c => ?_
simp (config := { contextual := true }) only [bsup_le_iff, IH]
#align ordinal.deriv_family_fp Ordinal.derivFamily_fp
theorem le_iff_derivFamily (H : ∀ i, IsNormal (f i)) {a} :
(∀ i, f i a ≤ a) ↔ ∃ o, derivFamily.{u, v} f o = a :=
⟨fun ha => by
suffices ∀ (o) (_ : a ≤ derivFamily.{u, v} f o), ∃ o, derivFamily.{u, v} f o = a from
this a ((derivFamily_isNormal _).self_le _)
intro o
induction' o using limitRecOn with o IH o l IH
· intro h₁
refine ⟨0, le_antisymm ?_ h₁⟩
rw [derivFamily_zero]
exact nfpFamily_le_fp (fun i => (H i).monotone) (Ordinal.zero_le _) ha
· intro h₁
rcases le_or_lt a (derivFamily.{u, v} f o) with h | h
· exact IH h
refine ⟨succ o, le_antisymm ?_ h₁⟩
rw [derivFamily_succ]
exact nfpFamily_le_fp (fun i => (H i).monotone) (succ_le_of_lt h) ha
· intro h₁
cases' eq_or_lt_of_le h₁ with h h
· exact ⟨_, h.symm⟩
rw [derivFamily_limit _ l, ← not_le, bsup_le_iff, not_forall₂] at h
exact
let ⟨o', h, hl⟩ := h
IH o' h (le_of_not_le hl),
fun ⟨o, e⟩ i => e ▸ (derivFamily_fp (H i) _).le⟩
#align ordinal.le_iff_deriv_family Ordinal.le_iff_derivFamily
theorem fp_iff_derivFamily (H : ∀ i, IsNormal (f i)) {a} :
(∀ i, f i a = a) ↔ ∃ o, derivFamily.{u, v} f o = a :=
Iff.trans ⟨fun h i => le_of_eq (h i), fun h i => (H i).le_iff_eq.1 (h i)⟩ (le_iff_derivFamily H)
#align ordinal.fp_iff_deriv_family Ordinal.fp_iff_derivFamily
/-- For a family of normal functions, `Ordinal.derivFamily` enumerates the common fixed points. -/
| Mathlib/SetTheory/Ordinal/FixedPoint.lean | 229 | 239 | theorem derivFamily_eq_enumOrd (H : ∀ i, IsNormal (f i)) :
derivFamily.{u, v} f = enumOrd (⋂ i, Function.fixedPoints (f i)) := by |
rw [← eq_enumOrd _ (fp_family_unbounded.{u, v} H)]
use (derivFamily_isNormal f).strictMono
rw [Set.range_eq_iff]
refine ⟨?_, fun a ha => ?_⟩
· rintro a S ⟨i, hi⟩
rw [← hi]
exact derivFamily_fp (H i) a
rw [Set.mem_iInter] at ha
rwa [← fp_iff_derivFamily H]
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.Algebra.RestrictScalars
import Mathlib.Algebra.Algebra.Subalgebra.Basic
import Mathlib.LinearAlgebra.Quotient
import Mathlib.LinearAlgebra.StdBasis
import Mathlib.GroupTheory.Finiteness
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.RingTheory.Nilpotent.Defs
#align_import ring_theory.finiteness from "leanprover-community/mathlib"@"c813ed7de0f5115f956239124e9b30f3a621966f"
/-!
# Finiteness conditions in commutative algebra
In this file we define a notion of finiteness that is common in commutative algebra.
## Main declarations
- `Submodule.FG`, `Ideal.FG`
These express that some object is finitely generated as *submodule* over some base ring.
- `Module.Finite`, `RingHom.Finite`, `AlgHom.Finite`
all of these express that some object is finitely generated *as module* over some base ring.
## Main results
* `exists_sub_one_mem_and_smul_eq_zero_of_fg_of_le_smul` is Nakayama's lemma, in the following form:
if N is a finitely generated submodule of an ambient R-module M and I is an ideal of R
such that N ⊆ IN, then there exists r ∈ 1 + I such that rN = 0.
-/
open Function (Surjective)
namespace Submodule
variable {R : Type*} {M : Type*} [Semiring R] [AddCommMonoid M] [Module R M]
open Set
/-- A submodule of `M` is finitely generated if it is the span of a finite subset of `M`. -/
def FG (N : Submodule R M) : Prop :=
∃ S : Finset M, Submodule.span R ↑S = N
#align submodule.fg Submodule.FG
theorem fg_def {N : Submodule R M} : N.FG ↔ ∃ S : Set M, S.Finite ∧ span R S = N :=
⟨fun ⟨t, h⟩ => ⟨_, Finset.finite_toSet t, h⟩, by
rintro ⟨t', h, rfl⟩
rcases Finite.exists_finset_coe h with ⟨t, rfl⟩
exact ⟨t, rfl⟩⟩
#align submodule.fg_def Submodule.fg_def
theorem fg_iff_addSubmonoid_fg (P : Submodule ℕ M) : P.FG ↔ P.toAddSubmonoid.FG :=
⟨fun ⟨S, hS⟩ => ⟨S, by simpa [← span_nat_eq_addSubmonoid_closure] using hS⟩, fun ⟨S, hS⟩ =>
⟨S, by simpa [← span_nat_eq_addSubmonoid_closure] using hS⟩⟩
#align submodule.fg_iff_add_submonoid_fg Submodule.fg_iff_addSubmonoid_fg
theorem fg_iff_add_subgroup_fg {G : Type*} [AddCommGroup G] (P : Submodule ℤ G) :
P.FG ↔ P.toAddSubgroup.FG :=
⟨fun ⟨S, hS⟩ => ⟨S, by simpa [← span_int_eq_addSubgroup_closure] using hS⟩, fun ⟨S, hS⟩ =>
⟨S, by simpa [← span_int_eq_addSubgroup_closure] using hS⟩⟩
#align submodule.fg_iff_add_subgroup_fg Submodule.fg_iff_add_subgroup_fg
theorem fg_iff_exists_fin_generating_family {N : Submodule R M} :
N.FG ↔ ∃ (n : ℕ) (s : Fin n → M), span R (range s) = N := by
rw [fg_def]
constructor
· rintro ⟨S, Sfin, hS⟩
obtain ⟨n, f, rfl⟩ := Sfin.fin_embedding
exact ⟨n, f, hS⟩
· rintro ⟨n, s, hs⟩
exact ⟨range s, finite_range s, hs⟩
#align submodule.fg_iff_exists_fin_generating_family Submodule.fg_iff_exists_fin_generating_family
/-- **Nakayama's Lemma**. Atiyah-Macdonald 2.5, Eisenbud 4.7, Matsumura 2.2,
[Stacks 00DV](https://stacks.math.columbia.edu/tag/00DV) -/
theorem exists_sub_one_mem_and_smul_eq_zero_of_fg_of_le_smul {R : Type*} [CommRing R] {M : Type*}
[AddCommGroup M] [Module R M] (I : Ideal R) (N : Submodule R M) (hn : N.FG) (hin : N ≤ I • N) :
∃ r : R, r - 1 ∈ I ∧ ∀ n ∈ N, r • n = (0 : M) := by
rw [fg_def] at hn
rcases hn with ⟨s, hfs, hs⟩
have : ∃ r : R, r - 1 ∈ I ∧ N ≤ (I • span R s).comap (LinearMap.lsmul R M r) ∧ s ⊆ N := by
refine ⟨1, ?_, ?_, ?_⟩
· rw [sub_self]
exact I.zero_mem
· rw [hs]
intro n hn
rw [mem_comap]
change (1 : R) • n ∈ I • N
rw [one_smul]
exact hin hn
· rw [← span_le, hs]
clear hin hs
revert this
refine Set.Finite.dinduction_on _ hfs (fun H => ?_) @fun i s _ _ ih H => ?_
· rcases H with ⟨r, hr1, hrn, _⟩
refine ⟨r, hr1, fun n hn => ?_⟩
specialize hrn hn
rwa [mem_comap, span_empty, smul_bot, mem_bot] at hrn
apply ih
rcases H with ⟨r, hr1, hrn, hs⟩
rw [← Set.singleton_union, span_union, smul_sup] at hrn
rw [Set.insert_subset_iff] at hs
have : ∃ c : R, c - 1 ∈ I ∧ c • i ∈ I • span R s := by
specialize hrn hs.1
rw [mem_comap, mem_sup] at hrn
rcases hrn with ⟨y, hy, z, hz, hyz⟩
dsimp at hyz
rw [mem_smul_span_singleton] at hy
rcases hy with ⟨c, hci, rfl⟩
use r - c
constructor
· rw [sub_right_comm]
exact I.sub_mem hr1 hci
· rw [sub_smul, ← hyz, add_sub_cancel_left]
exact hz
rcases this with ⟨c, hc1, hci⟩
refine ⟨c * r, ?_, ?_, hs.2⟩
· simpa only [mul_sub, mul_one, sub_add_sub_cancel] using I.add_mem (I.mul_mem_left c hr1) hc1
· intro n hn
specialize hrn hn
rw [mem_comap, mem_sup] at hrn
rcases hrn with ⟨y, hy, z, hz, hyz⟩
dsimp at hyz
rw [mem_smul_span_singleton] at hy
rcases hy with ⟨d, _, rfl⟩
simp only [mem_comap, LinearMap.lsmul_apply]
rw [mul_smul, ← hyz, smul_add, smul_smul, mul_comm, mul_smul]
exact add_mem (smul_mem _ _ hci) (smul_mem _ _ hz)
#align submodule.exists_sub_one_mem_and_smul_eq_zero_of_fg_of_le_smul Submodule.exists_sub_one_mem_and_smul_eq_zero_of_fg_of_le_smul
| Mathlib/RingTheory/Finiteness.lean | 137 | 141 | theorem exists_mem_and_smul_eq_self_of_fg_of_le_smul {R : Type*} [CommRing R] {M : Type*}
[AddCommGroup M] [Module R M] (I : Ideal R) (N : Submodule R M) (hn : N.FG) (hin : N ≤ I • N) :
∃ r ∈ I, ∀ n ∈ N, r • n = n := by |
obtain ⟨r, hr, hr'⟩ := exists_sub_one_mem_and_smul_eq_zero_of_fg_of_le_smul I N hn hin
exact ⟨-(r - 1), I.neg_mem hr, fun n hn => by simpa [sub_smul] using hr' n hn⟩
|
/-
Copyright (c) 2020 Hanting Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Hanting Zhang, Johan Commelin
-/
import Mathlib.Algebra.Algebra.Subalgebra.Basic
import Mathlib.Algebra.MvPolynomial.Rename
import Mathlib.Algebra.MvPolynomial.CommRing
#align_import ring_theory.mv_polynomial.symmetric from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Symmetric Polynomials and Elementary Symmetric Polynomials
This file defines symmetric `MvPolynomial`s and elementary symmetric `MvPolynomial`s.
We also prove some basic facts about them.
## Main declarations
* `MvPolynomial.IsSymmetric`
* `MvPolynomial.symmetricSubalgebra`
* `MvPolynomial.esymm`
* `MvPolynomial.psum`
## Notation
+ `esymm σ R n` is the `n`th elementary symmetric polynomial in `MvPolynomial σ R`.
+ `psum σ R n` is the degree-`n` power sum in `MvPolynomial σ R`, i.e. the sum of monomials
`(X i)^n` over `i ∈ σ`.
As in other polynomial files, we typically use the notation:
+ `σ τ : Type*` (indexing the variables)
+ `R S : Type*` `[CommSemiring R]` `[CommSemiring S]` (the coefficients)
+ `r : R` elements of the coefficient ring
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `φ ψ : MvPolynomial σ R`
-/
open Equiv (Perm)
noncomputable section
namespace Multiset
variable {R : Type*} [CommSemiring R]
/-- The `n`th elementary symmetric function evaluated at the elements of `s` -/
def esymm (s : Multiset R) (n : ℕ) : R :=
((s.powersetCard n).map Multiset.prod).sum
#align multiset.esymm Multiset.esymm
theorem _root_.Finset.esymm_map_val {σ} (f : σ → R) (s : Finset σ) (n : ℕ) :
(s.val.map f).esymm n = (s.powersetCard n).sum fun t => t.prod f := by
simp only [esymm, powersetCard_map, ← Finset.map_val_val_powersetCard, map_map]
rfl
#align finset.esymm_map_val Finset.esymm_map_val
end Multiset
namespace MvPolynomial
variable {σ : Type*} {R : Type*}
variable {τ : Type*} {S : Type*}
/-- A `MvPolynomial φ` is symmetric if it is invariant under
permutations of its variables by the `rename` operation -/
def IsSymmetric [CommSemiring R] (φ : MvPolynomial σ R) : Prop :=
∀ e : Perm σ, rename e φ = φ
#align mv_polynomial.is_symmetric MvPolynomial.IsSymmetric
variable (σ R)
/-- The subalgebra of symmetric `MvPolynomial`s. -/
def symmetricSubalgebra [CommSemiring R] : Subalgebra R (MvPolynomial σ R) where
carrier := setOf IsSymmetric
algebraMap_mem' r e := rename_C e r
mul_mem' ha hb e := by rw [AlgHom.map_mul, ha, hb]
add_mem' ha hb e := by rw [AlgHom.map_add, ha, hb]
#align mv_polynomial.symmetric_subalgebra MvPolynomial.symmetricSubalgebra
variable {σ R}
@[simp]
theorem mem_symmetricSubalgebra [CommSemiring R] (p : MvPolynomial σ R) :
p ∈ symmetricSubalgebra σ R ↔ p.IsSymmetric :=
Iff.rfl
#align mv_polynomial.mem_symmetric_subalgebra MvPolynomial.mem_symmetricSubalgebra
namespace IsSymmetric
section CommSemiring
variable [CommSemiring R] [CommSemiring S] {φ ψ : MvPolynomial σ R}
@[simp]
theorem C (r : R) : IsSymmetric (C r : MvPolynomial σ R) :=
(symmetricSubalgebra σ R).algebraMap_mem r
set_option linter.uppercaseLean3 false in
#align mv_polynomial.is_symmetric.C MvPolynomial.IsSymmetric.C
@[simp]
theorem zero : IsSymmetric (0 : MvPolynomial σ R) :=
(symmetricSubalgebra σ R).zero_mem
#align mv_polynomial.is_symmetric.zero MvPolynomial.IsSymmetric.zero
@[simp]
theorem one : IsSymmetric (1 : MvPolynomial σ R) :=
(symmetricSubalgebra σ R).one_mem
#align mv_polynomial.is_symmetric.one MvPolynomial.IsSymmetric.one
theorem add (hφ : IsSymmetric φ) (hψ : IsSymmetric ψ) : IsSymmetric (φ + ψ) :=
(symmetricSubalgebra σ R).add_mem hφ hψ
#align mv_polynomial.is_symmetric.add MvPolynomial.IsSymmetric.add
theorem mul (hφ : IsSymmetric φ) (hψ : IsSymmetric ψ) : IsSymmetric (φ * ψ) :=
(symmetricSubalgebra σ R).mul_mem hφ hψ
#align mv_polynomial.is_symmetric.mul MvPolynomial.IsSymmetric.mul
theorem smul (r : R) (hφ : IsSymmetric φ) : IsSymmetric (r • φ) :=
(symmetricSubalgebra σ R).smul_mem hφ r
#align mv_polynomial.is_symmetric.smul MvPolynomial.IsSymmetric.smul
@[simp]
theorem map (hφ : IsSymmetric φ) (f : R →+* S) : IsSymmetric (map f φ) := fun e => by
rw [← map_rename, hφ]
#align mv_polynomial.is_symmetric.map MvPolynomial.IsSymmetric.map
protected theorem rename (hφ : φ.IsSymmetric) (e : σ ≃ τ) : (rename e φ).IsSymmetric := fun _ => by
apply rename_injective _ e.symm.injective
simp_rw [rename_rename, ← Equiv.coe_trans, Equiv.self_trans_symm, Equiv.coe_refl, rename_id]
rw [hφ]
@[simp]
theorem _root_.MvPolynomial.isSymmetric_rename {e : σ ≃ τ} :
(MvPolynomial.rename e φ).IsSymmetric ↔ φ.IsSymmetric :=
⟨fun h => by simpa using (IsSymmetric.rename (R := R) h e.symm), (IsSymmetric.rename · e)⟩
end CommSemiring
section CommRing
variable [CommRing R] {φ ψ : MvPolynomial σ R}
theorem neg (hφ : IsSymmetric φ) : IsSymmetric (-φ) :=
(symmetricSubalgebra σ R).neg_mem hφ
#align mv_polynomial.is_symmetric.neg MvPolynomial.IsSymmetric.neg
theorem sub (hφ : IsSymmetric φ) (hψ : IsSymmetric ψ) : IsSymmetric (φ - ψ) :=
(symmetricSubalgebra σ R).sub_mem hφ hψ
#align mv_polynomial.is_symmetric.sub MvPolynomial.IsSymmetric.sub
end CommRing
end IsSymmetric
/-- `MvPolynomial.rename` induces an isomorphism between the symmetric subalgebras. -/
@[simps!]
def renameSymmetricSubalgebra [CommSemiring R] (e : σ ≃ τ) :
symmetricSubalgebra σ R ≃ₐ[R] symmetricSubalgebra τ R :=
AlgEquiv.ofAlgHom
(((rename e).comp (symmetricSubalgebra σ R).val).codRestrict _ <| fun x => x.2.rename e)
(((rename e.symm).comp <| Subalgebra.val _).codRestrict _ <| fun x => x.2.rename e.symm)
(AlgHom.ext <| fun p => Subtype.ext <| by simp)
(AlgHom.ext <| fun p => Subtype.ext <| by simp)
section ElementarySymmetric
open Finset
variable (σ R) [CommSemiring R] [CommSemiring S] [Fintype σ] [Fintype τ]
/-- The `n`th elementary symmetric `MvPolynomial σ R`. -/
def esymm (n : ℕ) : MvPolynomial σ R :=
∑ t ∈ powersetCard n univ, ∏ i ∈ t, X i
#align mv_polynomial.esymm MvPolynomial.esymm
/-- The `n`th elementary symmetric `MvPolynomial σ R` is obtained by evaluating the
`n`th elementary symmetric at the `Multiset` of the monomials -/
theorem esymm_eq_multiset_esymm : esymm σ R = (univ.val.map X).esymm := by
exact funext fun n => (esymm_map_val X _ n).symm
#align mv_polynomial.esymm_eq_multiset_esymm MvPolynomial.esymm_eq_multiset_esymm
theorem aeval_esymm_eq_multiset_esymm [Algebra R S] (f : σ → S) (n : ℕ) :
aeval f (esymm σ R n) = (univ.val.map f).esymm n := by
simp_rw [esymm, aeval_sum, aeval_prod, aeval_X, esymm_map_val]
#align mv_polynomial.aeval_esymm_eq_multiset_esymm MvPolynomial.aeval_esymm_eq_multiset_esymm
/-- We can define `esymm σ R n` by summing over a subtype instead of over `powerset_len`. -/
theorem esymm_eq_sum_subtype (n : ℕ) :
esymm σ R n = ∑ t : { s : Finset σ // s.card = n }, ∏ i ∈ (t : Finset σ), X i :=
sum_subtype _ (fun _ => mem_powersetCard_univ) _
#align mv_polynomial.esymm_eq_sum_subtype MvPolynomial.esymm_eq_sum_subtype
/-- We can define `esymm σ R n` as a sum over explicit monomials -/
theorem esymm_eq_sum_monomial (n : ℕ) :
esymm σ R n = ∑ t ∈ powersetCard n univ, monomial (∑ i ∈ t, Finsupp.single i 1) 1 := by
simp_rw [monomial_sum_one]
rfl
#align mv_polynomial.esymm_eq_sum_monomial MvPolynomial.esymm_eq_sum_monomial
@[simp]
theorem esymm_zero : esymm σ R 0 = 1 := by
simp only [esymm, powersetCard_zero, sum_singleton, prod_empty]
#align mv_polynomial.esymm_zero MvPolynomial.esymm_zero
theorem map_esymm (n : ℕ) (f : R →+* S) : map f (esymm σ R n) = esymm σ S n := by
simp_rw [esymm, map_sum, map_prod, map_X]
#align mv_polynomial.map_esymm MvPolynomial.map_esymm
theorem rename_esymm (n : ℕ) (e : σ ≃ τ) : rename e (esymm σ R n) = esymm τ R n :=
calc
rename e (esymm σ R n) = ∑ x ∈ powersetCard n univ, ∏ i ∈ x, X (e i) := by
simp_rw [esymm, map_sum, map_prod, rename_X]
_ = ∑ t ∈ powersetCard n (univ.map e.toEmbedding), ∏ i ∈ t, X i := by
simp [powersetCard_map, -map_univ_equiv]
-- Porting note: Why did `mapEmbedding_apply` not work?
dsimp [mapEmbedding, OrderEmbedding.ofMapLEIff]
simp
_ = ∑ t ∈ powersetCard n univ, ∏ i ∈ t, X i := by rw [map_univ_equiv]
#align mv_polynomial.rename_esymm MvPolynomial.rename_esymm
theorem esymm_isSymmetric (n : ℕ) : IsSymmetric (esymm σ R n) := by
intro
rw [rename_esymm]
#align mv_polynomial.esymm_is_symmetric MvPolynomial.esymm_isSymmetric
theorem support_esymm'' (n : ℕ) [DecidableEq σ] [Nontrivial R] :
(esymm σ R n).support =
(powersetCard n (univ : Finset σ)).biUnion fun t =>
(Finsupp.single (∑ i ∈ t, Finsupp.single i 1) (1 : R)).support := by
rw [esymm_eq_sum_monomial]
simp only [← single_eq_monomial]
refine Finsupp.support_sum_eq_biUnion (powersetCard n (univ : Finset σ)) ?_
intro s t hst
rw [disjoint_left, Finsupp.support_single_ne_zero _ one_ne_zero]
rw [Finsupp.support_single_ne_zero _ one_ne_zero]
simp only [one_ne_zero, mem_singleton, Finsupp.mem_support_iff]
rintro a h rfl
have := congr_arg Finsupp.support h
rw [Finsupp.support_sum_eq_biUnion, Finsupp.support_sum_eq_biUnion] at this
· have hsingle : ∀ s : Finset σ, ∀ x : σ, x ∈ s → (Finsupp.single x 1).support = {x} := by
intros _ x _
rw [Finsupp.support_single_ne_zero x one_ne_zero]
have hs := biUnion_congr (of_eq_true (eq_self s)) (hsingle s)
have ht := biUnion_congr (of_eq_true (eq_self t)) (hsingle t)
rw [hs, ht] at this
· simp only [biUnion_singleton_eq_self] at this
exact absurd this hst.symm
all_goals intro x y; simp [Finsupp.support_single_disjoint]
#align mv_polynomial.support_esymm'' MvPolynomial.support_esymm''
theorem support_esymm' (n : ℕ) [DecidableEq σ] [Nontrivial R] :
(esymm σ R n).support =
(powersetCard n (univ : Finset σ)).biUnion fun t => {∑ i ∈ t, Finsupp.single i 1} := by
rw [support_esymm'']
congr
funext
exact Finsupp.support_single_ne_zero _ one_ne_zero
#align mv_polynomial.support_esymm' MvPolynomial.support_esymm'
| Mathlib/RingTheory/MvPolynomial/Symmetric.lean | 272 | 276 | theorem support_esymm (n : ℕ) [DecidableEq σ] [Nontrivial R] :
(esymm σ R n).support =
(powersetCard n (univ : Finset σ)).image fun t => ∑ i ∈ t, Finsupp.single i 1 := by |
rw [support_esymm']
exact biUnion_singleton
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.Algebra.Tower
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.Regular.Pow
import Mathlib.Algebra.MonoidAlgebra.Support
import Mathlib.Data.Finsupp.Antidiagonal
import Mathlib.Order.SymmDiff
import Mathlib.RingTheory.Adjoin.Basic
#align_import data.mv_polynomial.basic from "leanprover-community/mathlib"@"c8734e8953e4b439147bd6f75c2163f6d27cdce6"
/-!
# Multivariate polynomials
This file defines polynomial rings over a base ring (or even semiring),
with variables from a general type `σ` (which could be infinite).
## Important definitions
Let `R` be a commutative ring (or a semiring) and let `σ` be an arbitrary
type. This file creates the type `MvPolynomial σ R`, which mathematicians
might denote $R[X_i : i \in σ]$. It is the type of multivariate
(a.k.a. multivariable) polynomials, with variables
corresponding to the terms in `σ`, and coefficients in `R`.
### Notation
In the definitions below, we use the following notation:
+ `σ : Type*` (indexing the variables)
+ `R : Type*` `[CommSemiring R]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `a : R`
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ R`
### Definitions
* `MvPolynomial σ R` : the type of polynomials with variables of type `σ` and coefficients
in the commutative semiring `R`
* `monomial s a` : the monomial which mathematically would be denoted `a * X^s`
* `C a` : the constant polynomial with value `a`
* `X i` : the degree one monomial corresponding to i; mathematically this might be denoted `Xᵢ`.
* `coeff s p` : the coefficient of `s` in `p`.
* `eval₂ (f : R → S₁) (g : σ → S₁) p` : given a semiring homomorphism from `R` to another
semiring `S₁`, and a map `σ → S₁`, evaluates `p` at this valuation, returning a term of type `S₁`.
Note that `eval₂` can be made using `eval` and `map` (see below), and it has been suggested
that sticking to `eval` and `map` might make the code less brittle.
* `eval (g : σ → R) p` : given a map `σ → R`, evaluates `p` at this valuation,
returning a term of type `R`
* `map (f : R → S₁) p` : returns the multivariate polynomial obtained from `p` by the change of
coefficient semiring corresponding to `f`
## Implementation notes
Recall that if `Y` has a zero, then `X →₀ Y` is the type of functions from `X` to `Y` with finite
support, i.e. such that only finitely many elements of `X` get sent to non-zero terms in `Y`.
The definition of `MvPolynomial σ R` is `(σ →₀ ℕ) →₀ R`; here `σ →₀ ℕ` denotes the space of all
monomials in the variables, and the function to `R` sends a monomial to its coefficient in
the polynomial being represented.
## Tags
polynomial, multivariate polynomial, multivariable polynomial
-/
noncomputable section
open Set Function Finsupp AddMonoidAlgebra
open scoped Pointwise
universe u v w x
variable {R : Type u} {S₁ : Type v} {S₂ : Type w} {S₃ : Type x}
/-- Multivariate polynomial, where `σ` is the index set of the variables and
`R` is the coefficient ring -/
def MvPolynomial (σ : Type*) (R : Type*) [CommSemiring R] :=
AddMonoidAlgebra R (σ →₀ ℕ)
#align mv_polynomial MvPolynomial
namespace MvPolynomial
-- Porting note: because of `MvPolynomial.C` and `MvPolynomial.X` this linter throws
-- tons of warnings in this file, and it's easier to just disable them globally in the file
set_option linter.uppercaseLean3 false
variable {σ : Type*} {a a' a₁ a₂ : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ}
section CommSemiring
section Instances
instance decidableEqMvPolynomial [CommSemiring R] [DecidableEq σ] [DecidableEq R] :
DecidableEq (MvPolynomial σ R) :=
Finsupp.instDecidableEq
#align mv_polynomial.decidable_eq_mv_polynomial MvPolynomial.decidableEqMvPolynomial
instance commSemiring [CommSemiring R] : CommSemiring (MvPolynomial σ R) :=
AddMonoidAlgebra.commSemiring
instance inhabited [CommSemiring R] : Inhabited (MvPolynomial σ R) :=
⟨0⟩
instance distribuMulAction [Monoid R] [CommSemiring S₁] [DistribMulAction R S₁] :
DistribMulAction R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.distribMulAction
instance smulZeroClass [CommSemiring S₁] [SMulZeroClass R S₁] :
SMulZeroClass R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.smulZeroClass
instance faithfulSMul [CommSemiring S₁] [SMulZeroClass R S₁] [FaithfulSMul R S₁] :
FaithfulSMul R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.faithfulSMul
instance module [Semiring R] [CommSemiring S₁] [Module R S₁] : Module R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.module
instance isScalarTower [CommSemiring S₂] [SMul R S₁] [SMulZeroClass R S₂] [SMulZeroClass S₁ S₂]
[IsScalarTower R S₁ S₂] : IsScalarTower R S₁ (MvPolynomial σ S₂) :=
AddMonoidAlgebra.isScalarTower
instance smulCommClass [CommSemiring S₂] [SMulZeroClass R S₂] [SMulZeroClass S₁ S₂]
[SMulCommClass R S₁ S₂] : SMulCommClass R S₁ (MvPolynomial σ S₂) :=
AddMonoidAlgebra.smulCommClass
instance isCentralScalar [CommSemiring S₁] [SMulZeroClass R S₁] [SMulZeroClass Rᵐᵒᵖ S₁]
[IsCentralScalar R S₁] : IsCentralScalar R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.isCentralScalar
instance algebra [CommSemiring R] [CommSemiring S₁] [Algebra R S₁] :
Algebra R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.algebra
instance isScalarTower_right [CommSemiring S₁] [DistribSMul R S₁] [IsScalarTower R S₁ S₁] :
IsScalarTower R (MvPolynomial σ S₁) (MvPolynomial σ S₁) :=
AddMonoidAlgebra.isScalarTower_self _
#align mv_polynomial.is_scalar_tower_right MvPolynomial.isScalarTower_right
instance smulCommClass_right [CommSemiring S₁] [DistribSMul R S₁] [SMulCommClass R S₁ S₁] :
SMulCommClass R (MvPolynomial σ S₁) (MvPolynomial σ S₁) :=
AddMonoidAlgebra.smulCommClass_self _
#align mv_polynomial.smul_comm_class_right MvPolynomial.smulCommClass_right
/-- If `R` is a subsingleton, then `MvPolynomial σ R` has a unique element -/
instance unique [CommSemiring R] [Subsingleton R] : Unique (MvPolynomial σ R) :=
AddMonoidAlgebra.unique
#align mv_polynomial.unique MvPolynomial.unique
end Instances
variable [CommSemiring R] [CommSemiring S₁] {p q : MvPolynomial σ R}
/-- `monomial s a` is the monomial with coefficient `a` and exponents given by `s` -/
def monomial (s : σ →₀ ℕ) : R →ₗ[R] MvPolynomial σ R :=
lsingle s
#align mv_polynomial.monomial MvPolynomial.monomial
theorem single_eq_monomial (s : σ →₀ ℕ) (a : R) : Finsupp.single s a = monomial s a :=
rfl
#align mv_polynomial.single_eq_monomial MvPolynomial.single_eq_monomial
theorem mul_def : p * q = p.sum fun m a => q.sum fun n b => monomial (m + n) (a * b) :=
AddMonoidAlgebra.mul_def
#align mv_polynomial.mul_def MvPolynomial.mul_def
/-- `C a` is the constant polynomial with value `a` -/
def C : R →+* MvPolynomial σ R :=
{ singleZeroRingHom with toFun := monomial 0 }
#align mv_polynomial.C MvPolynomial.C
variable (R σ)
@[simp]
theorem algebraMap_eq : algebraMap R (MvPolynomial σ R) = C :=
rfl
#align mv_polynomial.algebra_map_eq MvPolynomial.algebraMap_eq
variable {R σ}
/-- `X n` is the degree `1` monomial $X_n$. -/
def X (n : σ) : MvPolynomial σ R :=
monomial (Finsupp.single n 1) 1
#align mv_polynomial.X MvPolynomial.X
theorem monomial_left_injective {r : R} (hr : r ≠ 0) :
Function.Injective fun s : σ →₀ ℕ => monomial s r :=
Finsupp.single_left_injective hr
#align mv_polynomial.monomial_left_injective MvPolynomial.monomial_left_injective
@[simp]
theorem monomial_left_inj {s t : σ →₀ ℕ} {r : R} (hr : r ≠ 0) :
monomial s r = monomial t r ↔ s = t :=
Finsupp.single_left_inj hr
#align mv_polynomial.monomial_left_inj MvPolynomial.monomial_left_inj
theorem C_apply : (C a : MvPolynomial σ R) = monomial 0 a :=
rfl
#align mv_polynomial.C_apply MvPolynomial.C_apply
-- Porting note (#10618): `simp` can prove this
theorem C_0 : C 0 = (0 : MvPolynomial σ R) := map_zero _
#align mv_polynomial.C_0 MvPolynomial.C_0
-- Porting note (#10618): `simp` can prove this
theorem C_1 : C 1 = (1 : MvPolynomial σ R) :=
rfl
#align mv_polynomial.C_1 MvPolynomial.C_1
theorem C_mul_monomial : C a * monomial s a' = monomial s (a * a') := by
-- Porting note: this `show` feels like defeq abuse, but I can't find the appropriate lemmas
show AddMonoidAlgebra.single _ _ * AddMonoidAlgebra.single _ _ = AddMonoidAlgebra.single _ _
simp [C_apply, single_mul_single]
#align mv_polynomial.C_mul_monomial MvPolynomial.C_mul_monomial
-- Porting note (#10618): `simp` can prove this
theorem C_add : (C (a + a') : MvPolynomial σ R) = C a + C a' :=
Finsupp.single_add _ _ _
#align mv_polynomial.C_add MvPolynomial.C_add
-- Porting note (#10618): `simp` can prove this
theorem C_mul : (C (a * a') : MvPolynomial σ R) = C a * C a' :=
C_mul_monomial.symm
#align mv_polynomial.C_mul MvPolynomial.C_mul
-- Porting note (#10618): `simp` can prove this
theorem C_pow (a : R) (n : ℕ) : (C (a ^ n) : MvPolynomial σ R) = C a ^ n :=
map_pow _ _ _
#align mv_polynomial.C_pow MvPolynomial.C_pow
theorem C_injective (σ : Type*) (R : Type*) [CommSemiring R] :
Function.Injective (C : R → MvPolynomial σ R) :=
Finsupp.single_injective _
#align mv_polynomial.C_injective MvPolynomial.C_injective
theorem C_surjective {R : Type*} [CommSemiring R] (σ : Type*) [IsEmpty σ] :
Function.Surjective (C : R → MvPolynomial σ R) := by
refine fun p => ⟨p.toFun 0, Finsupp.ext fun a => ?_⟩
simp only [C_apply, ← single_eq_monomial, (Finsupp.ext isEmptyElim (α := σ) : a = 0),
single_eq_same]
rfl
#align mv_polynomial.C_surjective MvPolynomial.C_surjective
@[simp]
theorem C_inj {σ : Type*} (R : Type*) [CommSemiring R] (r s : R) :
(C r : MvPolynomial σ R) = C s ↔ r = s :=
(C_injective σ R).eq_iff
#align mv_polynomial.C_inj MvPolynomial.C_inj
instance nontrivial_of_nontrivial (σ : Type*) (R : Type*) [CommSemiring R] [Nontrivial R] :
Nontrivial (MvPolynomial σ R) :=
inferInstanceAs (Nontrivial <| AddMonoidAlgebra R (σ →₀ ℕ))
instance infinite_of_infinite (σ : Type*) (R : Type*) [CommSemiring R] [Infinite R] :
Infinite (MvPolynomial σ R) :=
Infinite.of_injective C (C_injective _ _)
#align mv_polynomial.infinite_of_infinite MvPolynomial.infinite_of_infinite
instance infinite_of_nonempty (σ : Type*) (R : Type*) [Nonempty σ] [CommSemiring R]
[Nontrivial R] : Infinite (MvPolynomial σ R) :=
Infinite.of_injective ((fun s : σ →₀ ℕ => monomial s 1) ∘ Finsupp.single (Classical.arbitrary σ))
<| (monomial_left_injective one_ne_zero).comp (Finsupp.single_injective _)
#align mv_polynomial.infinite_of_nonempty MvPolynomial.infinite_of_nonempty
theorem C_eq_coe_nat (n : ℕ) : (C ↑n : MvPolynomial σ R) = n := by
induction n <;> simp [Nat.succ_eq_add_one, *]
#align mv_polynomial.C_eq_coe_nat MvPolynomial.C_eq_coe_nat
theorem C_mul' : MvPolynomial.C a * p = a • p :=
(Algebra.smul_def a p).symm
#align mv_polynomial.C_mul' MvPolynomial.C_mul'
theorem smul_eq_C_mul (p : MvPolynomial σ R) (a : R) : a • p = C a * p :=
C_mul'.symm
#align mv_polynomial.smul_eq_C_mul MvPolynomial.smul_eq_C_mul
theorem C_eq_smul_one : (C a : MvPolynomial σ R) = a • (1 : MvPolynomial σ R) := by
rw [← C_mul', mul_one]
#align mv_polynomial.C_eq_smul_one MvPolynomial.C_eq_smul_one
theorem smul_monomial {S₁ : Type*} [SMulZeroClass S₁ R] (r : S₁) :
r • monomial s a = monomial s (r • a) :=
Finsupp.smul_single _ _ _
#align mv_polynomial.smul_monomial MvPolynomial.smul_monomial
theorem X_injective [Nontrivial R] : Function.Injective (X : σ → MvPolynomial σ R) :=
(monomial_left_injective one_ne_zero).comp (Finsupp.single_left_injective one_ne_zero)
#align mv_polynomial.X_injective MvPolynomial.X_injective
@[simp]
theorem X_inj [Nontrivial R] (m n : σ) : X m = (X n : MvPolynomial σ R) ↔ m = n :=
X_injective.eq_iff
#align mv_polynomial.X_inj MvPolynomial.X_inj
theorem monomial_pow : monomial s a ^ e = monomial (e • s) (a ^ e) :=
AddMonoidAlgebra.single_pow e
#align mv_polynomial.monomial_pow MvPolynomial.monomial_pow
@[simp]
theorem monomial_mul {s s' : σ →₀ ℕ} {a b : R} :
monomial s a * monomial s' b = monomial (s + s') (a * b) :=
AddMonoidAlgebra.single_mul_single
#align mv_polynomial.monomial_mul MvPolynomial.monomial_mul
variable (σ R)
/-- `fun s ↦ monomial s 1` as a homomorphism. -/
def monomialOneHom : Multiplicative (σ →₀ ℕ) →* MvPolynomial σ R :=
AddMonoidAlgebra.of _ _
#align mv_polynomial.monomial_one_hom MvPolynomial.monomialOneHom
variable {σ R}
@[simp]
theorem monomialOneHom_apply : monomialOneHom R σ s = (monomial s 1 : MvPolynomial σ R) :=
rfl
#align mv_polynomial.monomial_one_hom_apply MvPolynomial.monomialOneHom_apply
theorem X_pow_eq_monomial : X n ^ e = monomial (Finsupp.single n e) (1 : R) := by
simp [X, monomial_pow]
#align mv_polynomial.X_pow_eq_monomial MvPolynomial.X_pow_eq_monomial
theorem monomial_add_single : monomial (s + Finsupp.single n e) a = monomial s a * X n ^ e := by
rw [X_pow_eq_monomial, monomial_mul, mul_one]
#align mv_polynomial.monomial_add_single MvPolynomial.monomial_add_single
theorem monomial_single_add : monomial (Finsupp.single n e + s) a = X n ^ e * monomial s a := by
rw [X_pow_eq_monomial, monomial_mul, one_mul]
#align mv_polynomial.monomial_single_add MvPolynomial.monomial_single_add
theorem C_mul_X_pow_eq_monomial {s : σ} {a : R} {n : ℕ} :
C a * X s ^ n = monomial (Finsupp.single s n) a := by
rw [← zero_add (Finsupp.single s n), monomial_add_single, C_apply]
#align mv_polynomial.C_mul_X_pow_eq_monomial MvPolynomial.C_mul_X_pow_eq_monomial
theorem C_mul_X_eq_monomial {s : σ} {a : R} : C a * X s = monomial (Finsupp.single s 1) a := by
rw [← C_mul_X_pow_eq_monomial, pow_one]
#align mv_polynomial.C_mul_X_eq_monomial MvPolynomial.C_mul_X_eq_monomial
-- Porting note (#10618): `simp` can prove this
theorem monomial_zero {s : σ →₀ ℕ} : monomial s (0 : R) = 0 :=
Finsupp.single_zero _
#align mv_polynomial.monomial_zero MvPolynomial.monomial_zero
@[simp]
theorem monomial_zero' : (monomial (0 : σ →₀ ℕ) : R → MvPolynomial σ R) = C :=
rfl
#align mv_polynomial.monomial_zero' MvPolynomial.monomial_zero'
@[simp]
theorem monomial_eq_zero {s : σ →₀ ℕ} {b : R} : monomial s b = 0 ↔ b = 0 :=
Finsupp.single_eq_zero
#align mv_polynomial.monomial_eq_zero MvPolynomial.monomial_eq_zero
@[simp]
theorem sum_monomial_eq {A : Type*} [AddCommMonoid A] {u : σ →₀ ℕ} {r : R} {b : (σ →₀ ℕ) → R → A}
(w : b u 0 = 0) : sum (monomial u r) b = b u r :=
Finsupp.sum_single_index w
#align mv_polynomial.sum_monomial_eq MvPolynomial.sum_monomial_eq
@[simp]
theorem sum_C {A : Type*} [AddCommMonoid A] {b : (σ →₀ ℕ) → R → A} (w : b 0 0 = 0) :
sum (C a) b = b 0 a :=
sum_monomial_eq w
#align mv_polynomial.sum_C MvPolynomial.sum_C
theorem monomial_sum_one {α : Type*} (s : Finset α) (f : α → σ →₀ ℕ) :
(monomial (∑ i ∈ s, f i) 1 : MvPolynomial σ R) = ∏ i ∈ s, monomial (f i) 1 :=
map_prod (monomialOneHom R σ) (fun i => Multiplicative.ofAdd (f i)) s
#align mv_polynomial.monomial_sum_one MvPolynomial.monomial_sum_one
theorem monomial_sum_index {α : Type*} (s : Finset α) (f : α → σ →₀ ℕ) (a : R) :
monomial (∑ i ∈ s, f i) a = C a * ∏ i ∈ s, monomial (f i) 1 := by
rw [← monomial_sum_one, C_mul', ← (monomial _).map_smul, smul_eq_mul, mul_one]
#align mv_polynomial.monomial_sum_index MvPolynomial.monomial_sum_index
theorem monomial_finsupp_sum_index {α β : Type*} [Zero β] (f : α →₀ β) (g : α → β → σ →₀ ℕ)
(a : R) : monomial (f.sum g) a = C a * f.prod fun a b => monomial (g a b) 1 :=
monomial_sum_index _ _ _
#align mv_polynomial.monomial_finsupp_sum_index MvPolynomial.monomial_finsupp_sum_index
theorem monomial_eq_monomial_iff {α : Type*} (a₁ a₂ : α →₀ ℕ) (b₁ b₂ : R) :
monomial a₁ b₁ = monomial a₂ b₂ ↔ a₁ = a₂ ∧ b₁ = b₂ ∨ b₁ = 0 ∧ b₂ = 0 :=
Finsupp.single_eq_single_iff _ _ _ _
#align mv_polynomial.monomial_eq_monomial_iff MvPolynomial.monomial_eq_monomial_iff
theorem monomial_eq : monomial s a = C a * (s.prod fun n e => X n ^ e : MvPolynomial σ R) := by
simp only [X_pow_eq_monomial, ← monomial_finsupp_sum_index, Finsupp.sum_single]
#align mv_polynomial.monomial_eq MvPolynomial.monomial_eq
@[simp]
lemma prod_X_pow_eq_monomial : ∏ x ∈ s.support, X x ^ s x = monomial s (1 : R) := by
simp only [monomial_eq, map_one, one_mul, Finsupp.prod]
theorem induction_on_monomial {M : MvPolynomial σ R → Prop} (h_C : ∀ a, M (C a))
(h_X : ∀ p n, M p → M (p * X n)) : ∀ s a, M (monomial s a) := by
intro s a
apply @Finsupp.induction σ ℕ _ _ s
· show M (monomial 0 a)
exact h_C a
· intro n e p _hpn _he ih
have : ∀ e : ℕ, M (monomial p a * X n ^ e) := by
intro e
induction e with
| zero => simp [ih]
| succ e e_ih => simp [ih, pow_succ, (mul_assoc _ _ _).symm, h_X, e_ih]
simp [add_comm, monomial_add_single, this]
#align mv_polynomial.induction_on_monomial MvPolynomial.induction_on_monomial
/-- Analog of `Polynomial.induction_on'`.
To prove something about mv_polynomials,
it suffices to show the condition is closed under taking sums,
and it holds for monomials. -/
@[elab_as_elim]
theorem induction_on' {P : MvPolynomial σ R → Prop} (p : MvPolynomial σ R)
(h1 : ∀ (u : σ →₀ ℕ) (a : R), P (monomial u a))
(h2 : ∀ p q : MvPolynomial σ R, P p → P q → P (p + q)) : P p :=
Finsupp.induction p
(suffices P (monomial 0 0) by rwa [monomial_zero] at this
show P (monomial 0 0) from h1 0 0)
fun a b f _ha _hb hPf => h2 _ _ (h1 _ _) hPf
#align mv_polynomial.induction_on' MvPolynomial.induction_on'
/-- Similar to `MvPolynomial.induction_on` but only a weak form of `h_add` is required. -/
theorem induction_on''' {M : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (h_C : ∀ a, M (C a))
(h_add_weak :
∀ (a : σ →₀ ℕ) (b : R) (f : (σ →₀ ℕ) →₀ R),
a ∉ f.support → b ≠ 0 → M f → M ((show (σ →₀ ℕ) →₀ R from monomial a b) + f)) :
M p :=
-- Porting note: I had to add the `show ... from ...` above, a type ascription was insufficient.
Finsupp.induction p (C_0.rec <| h_C 0) h_add_weak
#align mv_polynomial.induction_on''' MvPolynomial.induction_on'''
/-- Similar to `MvPolynomial.induction_on` but only a yet weaker form of `h_add` is required. -/
theorem induction_on'' {M : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (h_C : ∀ a, M (C a))
(h_add_weak :
∀ (a : σ →₀ ℕ) (b : R) (f : (σ →₀ ℕ) →₀ R),
a ∉ f.support → b ≠ 0 → M f → M (monomial a b) →
M ((show (σ →₀ ℕ) →₀ R from monomial a b) + f))
(h_X : ∀ (p : MvPolynomial σ R) (n : σ), M p → M (p * MvPolynomial.X n)) : M p :=
-- Porting note: I had to add the `show ... from ...` above, a type ascription was insufficient.
induction_on''' p h_C fun a b f ha hb hf =>
h_add_weak a b f ha hb hf <| induction_on_monomial h_C h_X a b
#align mv_polynomial.induction_on'' MvPolynomial.induction_on''
/-- Analog of `Polynomial.induction_on`. -/
@[recursor 5]
theorem induction_on {M : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (h_C : ∀ a, M (C a))
(h_add : ∀ p q, M p → M q → M (p + q)) (h_X : ∀ p n, M p → M (p * X n)) : M p :=
induction_on'' p h_C (fun a b f _ha _hb hf hm => h_add (monomial a b) f hm hf) h_X
#align mv_polynomial.induction_on MvPolynomial.induction_on
theorem ringHom_ext {A : Type*} [Semiring A] {f g : MvPolynomial σ R →+* A}
(hC : ∀ r, f (C r) = g (C r)) (hX : ∀ i, f (X i) = g (X i)) : f = g := by
refine AddMonoidAlgebra.ringHom_ext' ?_ ?_
-- Porting note: this has high priority, but Lean still chooses `RingHom.ext`, why?
-- probably because of the type synonym
· ext x
exact hC _
· apply Finsupp.mulHom_ext'; intros x
-- Porting note: `Finsupp.mulHom_ext'` needs to have increased priority
apply MonoidHom.ext_mnat
exact hX _
#align mv_polynomial.ring_hom_ext MvPolynomial.ringHom_ext
/-- See note [partially-applied ext lemmas]. -/
@[ext 1100]
theorem ringHom_ext' {A : Type*} [Semiring A] {f g : MvPolynomial σ R →+* A}
(hC : f.comp C = g.comp C) (hX : ∀ i, f (X i) = g (X i)) : f = g :=
ringHom_ext (RingHom.ext_iff.1 hC) hX
#align mv_polynomial.ring_hom_ext' MvPolynomial.ringHom_ext'
theorem hom_eq_hom [Semiring S₂] (f g : MvPolynomial σ R →+* S₂) (hC : f.comp C = g.comp C)
(hX : ∀ n : σ, f (X n) = g (X n)) (p : MvPolynomial σ R) : f p = g p :=
RingHom.congr_fun (ringHom_ext' hC hX) p
#align mv_polynomial.hom_eq_hom MvPolynomial.hom_eq_hom
theorem is_id (f : MvPolynomial σ R →+* MvPolynomial σ R) (hC : f.comp C = C)
(hX : ∀ n : σ, f (X n) = X n) (p : MvPolynomial σ R) : f p = p :=
hom_eq_hom f (RingHom.id _) hC hX p
#align mv_polynomial.is_id MvPolynomial.is_id
@[ext 1100]
theorem algHom_ext' {A B : Type*} [CommSemiring A] [CommSemiring B] [Algebra R A] [Algebra R B]
{f g : MvPolynomial σ A →ₐ[R] B}
(h₁ :
f.comp (IsScalarTower.toAlgHom R A (MvPolynomial σ A)) =
g.comp (IsScalarTower.toAlgHom R A (MvPolynomial σ A)))
(h₂ : ∀ i, f (X i) = g (X i)) : f = g :=
AlgHom.coe_ringHom_injective (MvPolynomial.ringHom_ext' (congr_arg AlgHom.toRingHom h₁) h₂)
#align mv_polynomial.alg_hom_ext' MvPolynomial.algHom_ext'
@[ext 1200]
theorem algHom_ext {A : Type*} [Semiring A] [Algebra R A] {f g : MvPolynomial σ R →ₐ[R] A}
(hf : ∀ i : σ, f (X i) = g (X i)) : f = g :=
AddMonoidAlgebra.algHom_ext' (mulHom_ext' fun X : σ => MonoidHom.ext_mnat (hf X))
#align mv_polynomial.alg_hom_ext MvPolynomial.algHom_ext
@[simp]
theorem algHom_C {τ : Type*} (f : MvPolynomial σ R →ₐ[R] MvPolynomial τ R) (r : R) :
f (C r) = C r :=
f.commutes r
#align mv_polynomial.alg_hom_C MvPolynomial.algHom_C
@[simp]
theorem adjoin_range_X : Algebra.adjoin R (range (X : σ → MvPolynomial σ R)) = ⊤ := by
set S := Algebra.adjoin R (range (X : σ → MvPolynomial σ R))
refine top_unique fun p hp => ?_; clear hp
induction p using MvPolynomial.induction_on with
| h_C => exact S.algebraMap_mem _
| h_add p q hp hq => exact S.add_mem hp hq
| h_X p i hp => exact S.mul_mem hp (Algebra.subset_adjoin <| mem_range_self _)
#align mv_polynomial.adjoin_range_X MvPolynomial.adjoin_range_X
@[ext]
theorem linearMap_ext {M : Type*} [AddCommMonoid M] [Module R M] {f g : MvPolynomial σ R →ₗ[R] M}
(h : ∀ s, f ∘ₗ monomial s = g ∘ₗ monomial s) : f = g :=
Finsupp.lhom_ext' h
#align mv_polynomial.linear_map_ext MvPolynomial.linearMap_ext
section Support
/-- The finite set of all `m : σ →₀ ℕ` such that `X^m` has a non-zero coefficient. -/
def support (p : MvPolynomial σ R) : Finset (σ →₀ ℕ) :=
Finsupp.support p
#align mv_polynomial.support MvPolynomial.support
theorem finsupp_support_eq_support (p : MvPolynomial σ R) : Finsupp.support p = p.support :=
rfl
#align mv_polynomial.finsupp_support_eq_support MvPolynomial.finsupp_support_eq_support
theorem support_monomial [h : Decidable (a = 0)] :
(monomial s a).support = if a = 0 then ∅ else {s} := by
rw [← Subsingleton.elim (Classical.decEq R a 0) h]
rfl
-- Porting note: the proof in Lean 3 wasn't fundamentally better and needed `by convert rfl`
-- the issue is the different decidability instances in the `ite` expressions
#align mv_polynomial.support_monomial MvPolynomial.support_monomial
theorem support_monomial_subset : (monomial s a).support ⊆ {s} :=
support_single_subset
#align mv_polynomial.support_monomial_subset MvPolynomial.support_monomial_subset
theorem support_add [DecidableEq σ] : (p + q).support ⊆ p.support ∪ q.support :=
Finsupp.support_add
#align mv_polynomial.support_add MvPolynomial.support_add
theorem support_X [Nontrivial R] : (X n : MvPolynomial σ R).support = {Finsupp.single n 1} := by
classical rw [X, support_monomial, if_neg]; exact one_ne_zero
#align mv_polynomial.support_X MvPolynomial.support_X
theorem support_X_pow [Nontrivial R] (s : σ) (n : ℕ) :
(X s ^ n : MvPolynomial σ R).support = {Finsupp.single s n} := by
classical
rw [X_pow_eq_monomial, support_monomial, if_neg (one_ne_zero' R)]
#align mv_polynomial.support_X_pow MvPolynomial.support_X_pow
@[simp]
theorem support_zero : (0 : MvPolynomial σ R).support = ∅ :=
rfl
#align mv_polynomial.support_zero MvPolynomial.support_zero
theorem support_smul {S₁ : Type*} [SMulZeroClass S₁ R] {a : S₁} {f : MvPolynomial σ R} :
(a • f).support ⊆ f.support :=
Finsupp.support_smul
#align mv_polynomial.support_smul MvPolynomial.support_smul
theorem support_sum {α : Type*} [DecidableEq σ] {s : Finset α} {f : α → MvPolynomial σ R} :
(∑ x ∈ s, f x).support ⊆ s.biUnion fun x => (f x).support :=
Finsupp.support_finset_sum
#align mv_polynomial.support_sum MvPolynomial.support_sum
end Support
section Coeff
/-- The coefficient of the monomial `m` in the multi-variable polynomial `p`. -/
def coeff (m : σ →₀ ℕ) (p : MvPolynomial σ R) : R :=
@DFunLike.coe ((σ →₀ ℕ) →₀ R) _ _ _ p m
-- Porting note: I changed this from `@CoeFun.coe _ _ (MonoidAlgebra.coeFun _ _) p m` because
-- I think it should work better syntactically. They are defeq.
#align mv_polynomial.coeff MvPolynomial.coeff
@[simp]
theorem mem_support_iff {p : MvPolynomial σ R} {m : σ →₀ ℕ} : m ∈ p.support ↔ p.coeff m ≠ 0 := by
simp [support, coeff]
#align mv_polynomial.mem_support_iff MvPolynomial.mem_support_iff
theorem not_mem_support_iff {p : MvPolynomial σ R} {m : σ →₀ ℕ} : m ∉ p.support ↔ p.coeff m = 0 :=
by simp
#align mv_polynomial.not_mem_support_iff MvPolynomial.not_mem_support_iff
theorem sum_def {A} [AddCommMonoid A] {p : MvPolynomial σ R} {b : (σ →₀ ℕ) → R → A} :
p.sum b = ∑ m ∈ p.support, b m (p.coeff m) := by simp [support, Finsupp.sum, coeff]
#align mv_polynomial.sum_def MvPolynomial.sum_def
theorem support_mul [DecidableEq σ] (p q : MvPolynomial σ R) :
(p * q).support ⊆ p.support + q.support :=
AddMonoidAlgebra.support_mul p q
#align mv_polynomial.support_mul MvPolynomial.support_mul
@[ext]
theorem ext (p q : MvPolynomial σ R) : (∀ m, coeff m p = coeff m q) → p = q :=
Finsupp.ext
#align mv_polynomial.ext MvPolynomial.ext
theorem ext_iff (p q : MvPolynomial σ R) : p = q ↔ ∀ m, coeff m p = coeff m q :=
⟨fun h m => by rw [h], ext p q⟩
#align mv_polynomial.ext_iff MvPolynomial.ext_iff
@[simp]
theorem coeff_add (m : σ →₀ ℕ) (p q : MvPolynomial σ R) : coeff m (p + q) = coeff m p + coeff m q :=
add_apply p q m
#align mv_polynomial.coeff_add MvPolynomial.coeff_add
@[simp]
theorem coeff_smul {S₁ : Type*} [SMulZeroClass S₁ R] (m : σ →₀ ℕ) (C : S₁) (p : MvPolynomial σ R) :
coeff m (C • p) = C • coeff m p :=
smul_apply C p m
#align mv_polynomial.coeff_smul MvPolynomial.coeff_smul
@[simp]
theorem coeff_zero (m : σ →₀ ℕ) : coeff m (0 : MvPolynomial σ R) = 0 :=
rfl
#align mv_polynomial.coeff_zero MvPolynomial.coeff_zero
@[simp]
theorem coeff_zero_X (i : σ) : coeff 0 (X i : MvPolynomial σ R) = 0 :=
single_eq_of_ne fun h => by cases Finsupp.single_eq_zero.1 h
#align mv_polynomial.coeff_zero_X MvPolynomial.coeff_zero_X
/-- `MvPolynomial.coeff m` but promoted to an `AddMonoidHom`. -/
@[simps]
def coeffAddMonoidHom (m : σ →₀ ℕ) : MvPolynomial σ R →+ R where
toFun := coeff m
map_zero' := coeff_zero m
map_add' := coeff_add m
#align mv_polynomial.coeff_add_monoid_hom MvPolynomial.coeffAddMonoidHom
variable (R) in
/-- `MvPolynomial.coeff m` but promoted to a `LinearMap`. -/
@[simps]
def lcoeff (m : σ →₀ ℕ) : MvPolynomial σ R →ₗ[R] R where
toFun := coeff m
map_add' := coeff_add m
map_smul' := coeff_smul m
theorem coeff_sum {X : Type*} (s : Finset X) (f : X → MvPolynomial σ R) (m : σ →₀ ℕ) :
coeff m (∑ x ∈ s, f x) = ∑ x ∈ s, coeff m (f x) :=
map_sum (@coeffAddMonoidHom R σ _ _) _ s
#align mv_polynomial.coeff_sum MvPolynomial.coeff_sum
theorem monic_monomial_eq (m) :
monomial m (1 : R) = (m.prod fun n e => X n ^ e : MvPolynomial σ R) := by simp [monomial_eq]
#align mv_polynomial.monic_monomial_eq MvPolynomial.monic_monomial_eq
@[simp]
theorem coeff_monomial [DecidableEq σ] (m n) (a) :
coeff m (monomial n a : MvPolynomial σ R) = if n = m then a else 0 :=
Finsupp.single_apply
#align mv_polynomial.coeff_monomial MvPolynomial.coeff_monomial
@[simp]
theorem coeff_C [DecidableEq σ] (m) (a) :
coeff m (C a : MvPolynomial σ R) = if 0 = m then a else 0 :=
Finsupp.single_apply
#align mv_polynomial.coeff_C MvPolynomial.coeff_C
lemma eq_C_of_isEmpty [IsEmpty σ] (p : MvPolynomial σ R) :
p = C (p.coeff 0) := by
obtain ⟨x, rfl⟩ := C_surjective σ p
simp
theorem coeff_one [DecidableEq σ] (m) : coeff m (1 : MvPolynomial σ R) = if 0 = m then 1 else 0 :=
coeff_C m 1
#align mv_polynomial.coeff_one MvPolynomial.coeff_one
@[simp]
theorem coeff_zero_C (a) : coeff 0 (C a : MvPolynomial σ R) = a :=
single_eq_same
#align mv_polynomial.coeff_zero_C MvPolynomial.coeff_zero_C
@[simp]
theorem coeff_zero_one : coeff 0 (1 : MvPolynomial σ R) = 1 :=
coeff_zero_C 1
#align mv_polynomial.coeff_zero_one MvPolynomial.coeff_zero_one
theorem coeff_X_pow [DecidableEq σ] (i : σ) (m) (k : ℕ) :
coeff m (X i ^ k : MvPolynomial σ R) = if Finsupp.single i k = m then 1 else 0 := by
have := coeff_monomial m (Finsupp.single i k) (1 : R)
rwa [@monomial_eq _ _ (1 : R) (Finsupp.single i k) _, C_1, one_mul, Finsupp.prod_single_index]
at this
exact pow_zero _
#align mv_polynomial.coeff_X_pow MvPolynomial.coeff_X_pow
theorem coeff_X' [DecidableEq σ] (i : σ) (m) :
coeff m (X i : MvPolynomial σ R) = if Finsupp.single i 1 = m then 1 else 0 := by
rw [← coeff_X_pow, pow_one]
#align mv_polynomial.coeff_X' MvPolynomial.coeff_X'
@[simp]
theorem coeff_X (i : σ) : coeff (Finsupp.single i 1) (X i : MvPolynomial σ R) = 1 := by
classical rw [coeff_X', if_pos rfl]
#align mv_polynomial.coeff_X MvPolynomial.coeff_X
@[simp]
theorem coeff_C_mul (m) (a : R) (p : MvPolynomial σ R) : coeff m (C a * p) = a * coeff m p := by
classical
rw [mul_def, sum_C]
· simp (config := { contextual := true }) [sum_def, coeff_sum]
simp
#align mv_polynomial.coeff_C_mul MvPolynomial.coeff_C_mul
theorem coeff_mul [DecidableEq σ] (p q : MvPolynomial σ R) (n : σ →₀ ℕ) :
coeff n (p * q) = ∑ x ∈ Finset.antidiagonal n, coeff x.1 p * coeff x.2 q :=
AddMonoidAlgebra.mul_apply_antidiagonal p q _ _ Finset.mem_antidiagonal
#align mv_polynomial.coeff_mul MvPolynomial.coeff_mul
@[simp]
theorem coeff_mul_monomial (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff (m + s) (p * monomial s r) = coeff m p * r :=
AddMonoidAlgebra.mul_single_apply_aux p _ _ _ _ fun _a => add_left_inj _
#align mv_polynomial.coeff_mul_monomial MvPolynomial.coeff_mul_monomial
@[simp]
theorem coeff_monomial_mul (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff (s + m) (monomial s r * p) = r * coeff m p :=
AddMonoidAlgebra.single_mul_apply_aux p _ _ _ _ fun _a => add_right_inj _
#align mv_polynomial.coeff_monomial_mul MvPolynomial.coeff_monomial_mul
@[simp]
theorem coeff_mul_X (m) (s : σ) (p : MvPolynomial σ R) :
coeff (m + Finsupp.single s 1) (p * X s) = coeff m p :=
(coeff_mul_monomial _ _ _ _).trans (mul_one _)
#align mv_polynomial.coeff_mul_X MvPolynomial.coeff_mul_X
@[simp]
theorem coeff_X_mul (m) (s : σ) (p : MvPolynomial σ R) :
coeff (Finsupp.single s 1 + m) (X s * p) = coeff m p :=
(coeff_monomial_mul _ _ _ _).trans (one_mul _)
#align mv_polynomial.coeff_X_mul MvPolynomial.coeff_X_mul
lemma coeff_single_X_pow [DecidableEq σ] (s s' : σ) (n n' : ℕ) :
(X (R := R) s ^ n).coeff (Finsupp.single s' n')
= if s = s' ∧ n = n' ∨ n = 0 ∧ n' = 0 then 1 else 0 := by
simp only [coeff_X_pow, single_eq_single_iff]
@[simp]
lemma coeff_single_X [DecidableEq σ] (s s' : σ) (n : ℕ) :
(X s).coeff (R := R) (Finsupp.single s' n) = if n = 1 ∧ s = s' then 1 else 0 := by
simpa [eq_comm, and_comm] using coeff_single_X_pow s s' 1 n
@[simp]
theorem support_mul_X (s : σ) (p : MvPolynomial σ R) :
(p * X s).support = p.support.map (addRightEmbedding (Finsupp.single s 1)) :=
AddMonoidAlgebra.support_mul_single p _ (by simp) _
#align mv_polynomial.support_mul_X MvPolynomial.support_mul_X
@[simp]
theorem support_X_mul (s : σ) (p : MvPolynomial σ R) :
(X s * p).support = p.support.map (addLeftEmbedding (Finsupp.single s 1)) :=
AddMonoidAlgebra.support_single_mul p _ (by simp) _
#align mv_polynomial.support_X_mul MvPolynomial.support_X_mul
@[simp]
theorem support_smul_eq {S₁ : Type*} [Semiring S₁] [Module S₁ R] [NoZeroSMulDivisors S₁ R] {a : S₁}
(h : a ≠ 0) (p : MvPolynomial σ R) : (a • p).support = p.support :=
Finsupp.support_smul_eq h
#align mv_polynomial.support_smul_eq MvPolynomial.support_smul_eq
theorem support_sdiff_support_subset_support_add [DecidableEq σ] (p q : MvPolynomial σ R) :
p.support \ q.support ⊆ (p + q).support := by
intro m hm
simp only [Classical.not_not, mem_support_iff, Finset.mem_sdiff, Ne] at hm
simp [hm.2, hm.1]
#align mv_polynomial.support_sdiff_support_subset_support_add MvPolynomial.support_sdiff_support_subset_support_add
open scoped symmDiff in
theorem support_symmDiff_support_subset_support_add [DecidableEq σ] (p q : MvPolynomial σ R) :
p.support ∆ q.support ⊆ (p + q).support := by
rw [symmDiff_def, Finset.sup_eq_union]
apply Finset.union_subset
· exact support_sdiff_support_subset_support_add p q
· rw [add_comm]
exact support_sdiff_support_subset_support_add q p
#align mv_polynomial.support_symm_diff_support_subset_support_add MvPolynomial.support_symmDiff_support_subset_support_add
theorem coeff_mul_monomial' (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff m (p * monomial s r) = if s ≤ m then coeff (m - s) p * r else 0 := by
classical
split_ifs with h
· conv_rhs => rw [← coeff_mul_monomial _ s]
congr with t
rw [tsub_add_cancel_of_le h]
· contrapose! h
rw [← mem_support_iff] at h
obtain ⟨j, -, rfl⟩ : ∃ j ∈ support p, j + s = m := by
simpa [Finset.add_singleton]
using Finset.add_subset_add_left support_monomial_subset <| support_mul _ _ h
exact le_add_left le_rfl
#align mv_polynomial.coeff_mul_monomial' MvPolynomial.coeff_mul_monomial'
| Mathlib/Algebra/MvPolynomial/Basic.lean | 810 | 814 | theorem coeff_monomial_mul' (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff m (monomial s r * p) = if s ≤ m then r * coeff (m - s) p else 0 := by |
-- note that if we allow `R` to be non-commutative we will have to duplicate the proof above.
rw [mul_comm, mul_comm r]
exact coeff_mul_monomial' _ _ _ _
|
/-
Copyright (c) 2023 Rémi Bottinelli. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémi Bottinelli
-/
import Mathlib.Data.Set.Function
import Mathlib.Analysis.BoundedVariation
#align_import analysis.constant_speed from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Constant speed
This file defines the notion of constant (and unit) speed for a function `f : ℝ → E` with
pseudo-emetric structure on `E` with respect to a set `s : Set ℝ` and "speed" `l : ℝ≥0`, and shows
that if `f` has locally bounded variation on `s`, it can be obtained (up to distance zero, on `s`),
as a composite `φ ∘ (variationOnFromTo f s a)`, where `φ` has unit speed and `a ∈ s`.
## Main definitions
* `HasConstantSpeedOnWith f s l`, stating that the speed of `f` on `s` is `l`.
* `HasUnitSpeedOn f s`, stating that the speed of `f` on `s` is `1`.
* `naturalParameterization f s a : ℝ → E`, the unit speed reparameterization of `f` on `s` relative
to `a`.
## Main statements
* `unique_unit_speed_on_Icc_zero` proves that if `f` and `f ∘ φ` are both naturally
parameterized on closed intervals starting at `0`, then `φ` must be the identity on
those intervals.
* `edist_naturalParameterization_eq_zero` proves that if `f` has locally bounded variation, then
precomposing `naturalParameterization f s a` with `variationOnFromTo f s a` yields a function
at distance zero from `f` on `s`.
* `has_unit_speed_naturalParameterization` proves that if `f` has locally bounded
variation, then `naturalParameterization f s a` has unit speed on `s`.
## Tags
arc-length, parameterization
-/
open scoped NNReal ENNReal
open Set MeasureTheory Classical
variable {α : Type*} [LinearOrder α] {E : Type*} [PseudoEMetricSpace E]
variable (f : ℝ → E) (s : Set ℝ) (l : ℝ≥0)
/-- `f` has constant speed `l` on `s` if the variation of `f` on `s ∩ Icc x y` is equal to
`l * (y - x)` for any `x y` in `s`.
-/
def HasConstantSpeedOnWith :=
∀ ⦃x⦄ (_ : x ∈ s) ⦃y⦄ (_ : y ∈ s), eVariationOn f (s ∩ Icc x y) = ENNReal.ofReal (l * (y - x))
#align has_constant_speed_on_with HasConstantSpeedOnWith
variable {f s l}
theorem HasConstantSpeedOnWith.hasLocallyBoundedVariationOn (h : HasConstantSpeedOnWith f s l) :
LocallyBoundedVariationOn f s := fun x y hx hy => by
simp only [BoundedVariationOn, h hx hy, Ne, ENNReal.ofReal_ne_top, not_false_iff]
#align has_constant_speed_on_with.has_locally_bounded_variation_on HasConstantSpeedOnWith.hasLocallyBoundedVariationOn
theorem hasConstantSpeedOnWith_of_subsingleton (f : ℝ → E) {s : Set ℝ} (hs : s.Subsingleton)
(l : ℝ≥0) : HasConstantSpeedOnWith f s l := by
rintro x hx y hy; cases hs hx hy
rw [eVariationOn.subsingleton f (fun y hy z hz => hs hy.1 hz.1 : (s ∩ Icc x x).Subsingleton)]
simp only [sub_self, mul_zero, ENNReal.ofReal_zero]
#align has_constant_speed_on_with_of_subsingleton hasConstantSpeedOnWith_of_subsingleton
theorem hasConstantSpeedOnWith_iff_ordered :
HasConstantSpeedOnWith f s l ↔ ∀ ⦃x⦄ (_ : x ∈ s) ⦃y⦄ (_ : y ∈ s),
x ≤ y → eVariationOn f (s ∩ Icc x y) = ENNReal.ofReal (l * (y - x)) := by
refine ⟨fun h x xs y ys _ => h xs ys, fun h x xs y ys => ?_⟩
rcases le_total x y with (xy | yx)
· exact h xs ys xy
· rw [eVariationOn.subsingleton, ENNReal.ofReal_of_nonpos]
· exact mul_nonpos_of_nonneg_of_nonpos l.prop (sub_nonpos_of_le yx)
· rintro z ⟨zs, xz, zy⟩ w ⟨ws, xw, wy⟩
cases le_antisymm (zy.trans yx) xz
cases le_antisymm (wy.trans yx) xw
rfl
#align has_constant_speed_on_with_iff_ordered hasConstantSpeedOnWith_iff_ordered
theorem hasConstantSpeedOnWith_iff_variationOnFromTo_eq :
HasConstantSpeedOnWith f s l ↔ LocallyBoundedVariationOn f s ∧
∀ ⦃x⦄ (_ : x ∈ s) ⦃y⦄ (_ : y ∈ s), variationOnFromTo f s x y = l * (y - x) := by
constructor
· rintro h; refine ⟨h.hasLocallyBoundedVariationOn, fun x xs y ys => ?_⟩
rw [hasConstantSpeedOnWith_iff_ordered] at h
rcases le_total x y with (xy | yx)
· rw [variationOnFromTo.eq_of_le f s xy, h xs ys xy]
exact ENNReal.toReal_ofReal (mul_nonneg l.prop (sub_nonneg.mpr xy))
· rw [variationOnFromTo.eq_of_ge f s yx, h ys xs yx]
have := ENNReal.toReal_ofReal (mul_nonneg l.prop (sub_nonneg.mpr yx))
simp_all only [NNReal.val_eq_coe]; ring
· rw [hasConstantSpeedOnWith_iff_ordered]
rintro h x xs y ys xy
rw [← h.2 xs ys, variationOnFromTo.eq_of_le f s xy, ENNReal.ofReal_toReal (h.1 x y xs ys)]
#align has_constant_speed_on_with_iff_variation_on_from_to_eq hasConstantSpeedOnWith_iff_variationOnFromTo_eq
theorem HasConstantSpeedOnWith.union {t : Set ℝ} (hfs : HasConstantSpeedOnWith f s l)
(hft : HasConstantSpeedOnWith f t l) {x : ℝ} (hs : IsGreatest s x) (ht : IsLeast t x) :
HasConstantSpeedOnWith f (s ∪ t) l := by
rw [hasConstantSpeedOnWith_iff_ordered] at hfs hft ⊢
rintro z (zs | zt) y (ys | yt) zy
· have : (s ∪ t) ∩ Icc z y = s ∩ Icc z y := by
ext w; constructor
· rintro ⟨ws | wt, zw, wy⟩
· exact ⟨ws, zw, wy⟩
· exact ⟨(le_antisymm (wy.trans (hs.2 ys)) (ht.2 wt)).symm ▸ hs.1, zw, wy⟩
· rintro ⟨ws, zwy⟩; exact ⟨Or.inl ws, zwy⟩
rw [this, hfs zs ys zy]
· have : (s ∪ t) ∩ Icc z y = s ∩ Icc z x ∪ t ∩ Icc x y := by
ext w; constructor
· rintro ⟨ws | wt, zw, wy⟩
exacts [Or.inl ⟨ws, zw, hs.2 ws⟩, Or.inr ⟨wt, ht.2 wt, wy⟩]
· rintro (⟨ws, zw, wx⟩ | ⟨wt, xw, wy⟩)
exacts [⟨Or.inl ws, zw, wx.trans (ht.2 yt)⟩, ⟨Or.inr wt, (hs.2 zs).trans xw, wy⟩]
rw [this, @eVariationOn.union _ _ _ _ f _ _ x, hfs zs hs.1 (hs.2 zs), hft ht.1 yt (ht.2 yt)]
· have q := ENNReal.ofReal_add (mul_nonneg l.prop (sub_nonneg.mpr (hs.2 zs)))
(mul_nonneg l.prop (sub_nonneg.mpr (ht.2 yt)))
simp only [NNReal.val_eq_coe] at q
rw [← q]
ring_nf
exacts [⟨⟨hs.1, hs.2 zs, le_rfl⟩, fun w ⟨_, _, wx⟩ => wx⟩,
⟨⟨ht.1, le_rfl, ht.2 yt⟩, fun w ⟨_, xw, _⟩ => xw⟩]
· cases le_antisymm zy ((hs.2 ys).trans (ht.2 zt))
simp only [Icc_self, sub_self, mul_zero, ENNReal.ofReal_zero]
exact eVariationOn.subsingleton _ fun _ ⟨_, uz⟩ _ ⟨_, vz⟩ => uz.trans vz.symm
· have : (s ∪ t) ∩ Icc z y = t ∩ Icc z y := by
ext w; constructor
· rintro ⟨ws | wt, zw, wy⟩
· exact ⟨le_antisymm ((ht.2 zt).trans zw) (hs.2 ws) ▸ ht.1, zw, wy⟩
· exact ⟨wt, zw, wy⟩
· rintro ⟨wt, zwy⟩; exact ⟨Or.inr wt, zwy⟩
rw [this, hft zt yt zy]
#align has_constant_speed_on_with.union HasConstantSpeedOnWith.union
| Mathlib/Analysis/ConstantSpeed.lean | 140 | 153 | theorem HasConstantSpeedOnWith.Icc_Icc {x y z : ℝ} (hfs : HasConstantSpeedOnWith f (Icc x y) l)
(hft : HasConstantSpeedOnWith f (Icc y z) l) : HasConstantSpeedOnWith f (Icc x z) l := by |
rcases le_total x y with (xy | yx)
· rcases le_total y z with (yz | zy)
· rw [← Set.Icc_union_Icc_eq_Icc xy yz]
exact hfs.union hft (isGreatest_Icc xy) (isLeast_Icc yz)
· rintro u ⟨xu, uz⟩ v ⟨xv, vz⟩
rw [Icc_inter_Icc, sup_of_le_right xu, inf_of_le_right vz, ←
hfs ⟨xu, uz.trans zy⟩ ⟨xv, vz.trans zy⟩, Icc_inter_Icc, sup_of_le_right xu,
inf_of_le_right (vz.trans zy)]
· rintro u ⟨xu, uz⟩ v ⟨xv, vz⟩
rw [Icc_inter_Icc, sup_of_le_right xu, inf_of_le_right vz, ←
hft ⟨yx.trans xu, uz⟩ ⟨yx.trans xv, vz⟩, Icc_inter_Icc, sup_of_le_right (yx.trans xu),
inf_of_le_right vz]
|
/-
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.Analysis.SpecialFunctions.Trigonometric.Angle
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Inverse
#align_import analysis.special_functions.complex.arg from "leanprover-community/mathlib"@"2c1d8ca2812b64f88992a5294ea3dba144755cd1"
/-!
# The argument of a complex number.
We define `arg : ℂ → ℝ`, returning a real number in the range (-π, π],
such that for `x ≠ 0`, `sin (arg x) = x.im / x.abs` and `cos (arg x) = x.re / x.abs`,
while `arg 0` defaults to `0`
-/
open Filter Metric Set
open scoped ComplexConjugate Real Topology
namespace Complex
variable {a x z : ℂ}
/-- `arg` returns values in the range (-π, π], such that for `x ≠ 0`,
`sin (arg x) = x.im / x.abs` and `cos (arg x) = x.re / x.abs`,
`arg 0` defaults to `0` -/
noncomputable def arg (x : ℂ) : ℝ :=
if 0 ≤ x.re then Real.arcsin (x.im / abs x)
else if 0 ≤ x.im then Real.arcsin ((-x).im / abs x) + π else Real.arcsin ((-x).im / abs x) - π
#align complex.arg Complex.arg
theorem sin_arg (x : ℂ) : Real.sin (arg x) = x.im / abs x := by
unfold arg; split_ifs <;>
simp [sub_eq_add_neg, arg,
Real.sin_arcsin (abs_le.1 (abs_im_div_abs_le_one x)).1 (abs_le.1 (abs_im_div_abs_le_one x)).2,
Real.sin_add, neg_div, Real.arcsin_neg, Real.sin_neg]
#align complex.sin_arg Complex.sin_arg
theorem cos_arg {x : ℂ} (hx : x ≠ 0) : Real.cos (arg x) = x.re / abs x := by
rw [arg]
split_ifs with h₁ h₂
· rw [Real.cos_arcsin]
field_simp [Real.sqrt_sq, (abs.pos hx).le, *]
· rw [Real.cos_add_pi, Real.cos_arcsin]
field_simp [Real.sqrt_div (sq_nonneg _), Real.sqrt_sq_eq_abs,
_root_.abs_of_neg (not_le.1 h₁), *]
· rw [Real.cos_sub_pi, Real.cos_arcsin]
field_simp [Real.sqrt_div (sq_nonneg _), Real.sqrt_sq_eq_abs,
_root_.abs_of_neg (not_le.1 h₁), *]
#align complex.cos_arg Complex.cos_arg
@[simp]
theorem abs_mul_exp_arg_mul_I (x : ℂ) : ↑(abs x) * exp (arg x * I) = x := by
rcases eq_or_ne x 0 with (rfl | hx)
· simp
· have : abs x ≠ 0 := abs.ne_zero hx
apply Complex.ext <;> field_simp [sin_arg, cos_arg hx, this, mul_comm (abs x)]
set_option linter.uppercaseLean3 false in
#align complex.abs_mul_exp_arg_mul_I Complex.abs_mul_exp_arg_mul_I
@[simp]
theorem abs_mul_cos_add_sin_mul_I (x : ℂ) : (abs x * (cos (arg x) + sin (arg x) * I) : ℂ) = x := by
rw [← exp_mul_I, abs_mul_exp_arg_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.abs_mul_cos_add_sin_mul_I Complex.abs_mul_cos_add_sin_mul_I
@[simp]
lemma abs_mul_cos_arg (x : ℂ) : abs x * Real.cos (arg x) = x.re := by
simpa [-abs_mul_cos_add_sin_mul_I] using congr_arg re (abs_mul_cos_add_sin_mul_I x)
@[simp]
lemma abs_mul_sin_arg (x : ℂ) : abs x * Real.sin (arg x) = x.im := by
simpa [-abs_mul_cos_add_sin_mul_I] using congr_arg im (abs_mul_cos_add_sin_mul_I x)
theorem abs_eq_one_iff (z : ℂ) : abs z = 1 ↔ ∃ θ : ℝ, exp (θ * I) = z := by
refine ⟨fun hz => ⟨arg z, ?_⟩, ?_⟩
· calc
exp (arg z * I) = abs z * exp (arg z * I) := by rw [hz, ofReal_one, one_mul]
_ = z := abs_mul_exp_arg_mul_I z
· rintro ⟨θ, rfl⟩
exact Complex.abs_exp_ofReal_mul_I θ
#align complex.abs_eq_one_iff Complex.abs_eq_one_iff
@[simp]
theorem range_exp_mul_I : (Set.range fun x : ℝ => exp (x * I)) = Metric.sphere 0 1 := by
ext x
simp only [mem_sphere_zero_iff_norm, norm_eq_abs, abs_eq_one_iff, Set.mem_range]
set_option linter.uppercaseLean3 false in
#align complex.range_exp_mul_I Complex.range_exp_mul_I
theorem arg_mul_cos_add_sin_mul_I {r : ℝ} (hr : 0 < r) {θ : ℝ} (hθ : θ ∈ Set.Ioc (-π) π) :
arg (r * (cos θ + sin θ * I)) = θ := by
simp only [arg, map_mul, abs_cos_add_sin_mul_I, abs_of_nonneg hr.le, mul_one]
simp only [re_ofReal_mul, im_ofReal_mul, neg_im, ← ofReal_cos, ← ofReal_sin, ←
mk_eq_add_mul_I, neg_div, mul_div_cancel_left₀ _ hr.ne', mul_nonneg_iff_right_nonneg_of_pos hr]
by_cases h₁ : θ ∈ Set.Icc (-(π / 2)) (π / 2)
· rw [if_pos]
exacts [Real.arcsin_sin' h₁, Real.cos_nonneg_of_mem_Icc h₁]
· rw [Set.mem_Icc, not_and_or, not_le, not_le] at h₁
cases' h₁ with h₁ h₁
· replace hθ := hθ.1
have hcos : Real.cos θ < 0 := by
rw [← neg_pos, ← Real.cos_add_pi]
refine Real.cos_pos_of_mem_Ioo ⟨?_, ?_⟩ <;> linarith
have hsin : Real.sin θ < 0 := Real.sin_neg_of_neg_of_neg_pi_lt (by linarith) hθ
rw [if_neg, if_neg, ← Real.sin_add_pi, Real.arcsin_sin, add_sub_cancel_right] <;> [linarith;
linarith; exact hsin.not_le; exact hcos.not_le]
· replace hθ := hθ.2
have hcos : Real.cos θ < 0 := Real.cos_neg_of_pi_div_two_lt_of_lt h₁ (by linarith)
have hsin : 0 ≤ Real.sin θ := Real.sin_nonneg_of_mem_Icc ⟨by linarith, hθ⟩
rw [if_neg, if_pos, ← Real.sin_sub_pi, Real.arcsin_sin, sub_add_cancel] <;> [linarith;
linarith; exact hsin; exact hcos.not_le]
set_option linter.uppercaseLean3 false in
#align complex.arg_mul_cos_add_sin_mul_I Complex.arg_mul_cos_add_sin_mul_I
theorem arg_cos_add_sin_mul_I {θ : ℝ} (hθ : θ ∈ Set.Ioc (-π) π) : arg (cos θ + sin θ * I) = θ := by
rw [← one_mul (_ + _), ← ofReal_one, arg_mul_cos_add_sin_mul_I zero_lt_one hθ]
set_option linter.uppercaseLean3 false in
#align complex.arg_cos_add_sin_mul_I Complex.arg_cos_add_sin_mul_I
lemma arg_exp_mul_I (θ : ℝ) :
arg (exp (θ * I)) = toIocMod (mul_pos two_pos Real.pi_pos) (-π) θ := by
convert arg_cos_add_sin_mul_I (θ := toIocMod (mul_pos two_pos Real.pi_pos) (-π) θ) _ using 2
· rw [← exp_mul_I, eq_sub_of_add_eq $ toIocMod_add_toIocDiv_zsmul _ _ θ, ofReal_sub,
ofReal_zsmul, ofReal_mul, ofReal_ofNat, exp_mul_I_periodic.sub_zsmul_eq]
· convert toIocMod_mem_Ioc _ _ _
ring
@[simp]
theorem arg_zero : arg 0 = 0 := by simp [arg, le_refl]
#align complex.arg_zero Complex.arg_zero
theorem ext_abs_arg {x y : ℂ} (h₁ : abs x = abs y) (h₂ : x.arg = y.arg) : x = y := by
rw [← abs_mul_exp_arg_mul_I x, ← abs_mul_exp_arg_mul_I y, h₁, h₂]
#align complex.ext_abs_arg Complex.ext_abs_arg
theorem ext_abs_arg_iff {x y : ℂ} : x = y ↔ abs x = abs y ∧ arg x = arg y :=
⟨fun h => h ▸ ⟨rfl, rfl⟩, and_imp.2 ext_abs_arg⟩
#align complex.ext_abs_arg_iff Complex.ext_abs_arg_iff
theorem arg_mem_Ioc (z : ℂ) : arg z ∈ Set.Ioc (-π) π := by
have hπ : 0 < π := Real.pi_pos
rcases eq_or_ne z 0 with (rfl | hz)
· simp [hπ, hπ.le]
rcases existsUnique_add_zsmul_mem_Ioc Real.two_pi_pos (arg z) (-π) with ⟨N, hN, -⟩
rw [two_mul, neg_add_cancel_left, ← two_mul, zsmul_eq_mul] at hN
rw [← abs_mul_cos_add_sin_mul_I z, ← cos_add_int_mul_two_pi _ N, ← sin_add_int_mul_two_pi _ N]
have := arg_mul_cos_add_sin_mul_I (abs.pos hz) hN
push_cast at this
rwa [this]
#align complex.arg_mem_Ioc Complex.arg_mem_Ioc
@[simp]
theorem range_arg : Set.range arg = Set.Ioc (-π) π :=
(Set.range_subset_iff.2 arg_mem_Ioc).antisymm fun _ hx => ⟨_, arg_cos_add_sin_mul_I hx⟩
#align complex.range_arg Complex.range_arg
theorem arg_le_pi (x : ℂ) : arg x ≤ π :=
(arg_mem_Ioc x).2
#align complex.arg_le_pi Complex.arg_le_pi
theorem neg_pi_lt_arg (x : ℂ) : -π < arg x :=
(arg_mem_Ioc x).1
#align complex.neg_pi_lt_arg Complex.neg_pi_lt_arg
theorem abs_arg_le_pi (z : ℂ) : |arg z| ≤ π :=
abs_le.2 ⟨(neg_pi_lt_arg z).le, arg_le_pi z⟩
#align complex.abs_arg_le_pi Complex.abs_arg_le_pi
@[simp]
theorem arg_nonneg_iff {z : ℂ} : 0 ≤ arg z ↔ 0 ≤ z.im := by
rcases eq_or_ne z 0 with (rfl | h₀); · simp
calc
0 ≤ arg z ↔ 0 ≤ Real.sin (arg z) :=
⟨fun h => Real.sin_nonneg_of_mem_Icc ⟨h, arg_le_pi z⟩, by
contrapose!
intro h
exact Real.sin_neg_of_neg_of_neg_pi_lt h (neg_pi_lt_arg _)⟩
_ ↔ _ := by rw [sin_arg, le_div_iff (abs.pos h₀), zero_mul]
#align complex.arg_nonneg_iff Complex.arg_nonneg_iff
@[simp]
theorem arg_neg_iff {z : ℂ} : arg z < 0 ↔ z.im < 0 :=
lt_iff_lt_of_le_iff_le arg_nonneg_iff
#align complex.arg_neg_iff Complex.arg_neg_iff
theorem arg_real_mul (x : ℂ) {r : ℝ} (hr : 0 < r) : arg (r * x) = arg x := by
rcases eq_or_ne x 0 with (rfl | hx); · rw [mul_zero]
conv_lhs =>
rw [← abs_mul_cos_add_sin_mul_I x, ← mul_assoc, ← ofReal_mul,
arg_mul_cos_add_sin_mul_I (mul_pos hr (abs.pos hx)) x.arg_mem_Ioc]
#align complex.arg_real_mul Complex.arg_real_mul
theorem arg_mul_real {r : ℝ} (hr : 0 < r) (x : ℂ) : arg (x * r) = arg x :=
mul_comm x r ▸ arg_real_mul x hr
theorem arg_eq_arg_iff {x y : ℂ} (hx : x ≠ 0) (hy : y ≠ 0) :
arg x = arg y ↔ (abs y / abs x : ℂ) * x = y := by
simp only [ext_abs_arg_iff, map_mul, map_div₀, abs_ofReal, abs_abs,
div_mul_cancel₀ _ (abs.ne_zero hx), eq_self_iff_true, true_and_iff]
rw [← ofReal_div, arg_real_mul]
exact div_pos (abs.pos hy) (abs.pos hx)
#align complex.arg_eq_arg_iff Complex.arg_eq_arg_iff
@[simp]
theorem arg_one : arg 1 = 0 := by simp [arg, zero_le_one]
#align complex.arg_one Complex.arg_one
@[simp]
theorem arg_neg_one : arg (-1) = π := by simp [arg, le_refl, not_le.2 (zero_lt_one' ℝ)]
#align complex.arg_neg_one Complex.arg_neg_one
@[simp]
theorem arg_I : arg I = π / 2 := by simp [arg, le_refl]
set_option linter.uppercaseLean3 false in
#align complex.arg_I Complex.arg_I
@[simp]
theorem arg_neg_I : arg (-I) = -(π / 2) := by simp [arg, le_refl]
set_option linter.uppercaseLean3 false in
#align complex.arg_neg_I Complex.arg_neg_I
@[simp]
theorem tan_arg (x : ℂ) : Real.tan (arg x) = x.im / x.re := by
by_cases h : x = 0
· simp only [h, zero_div, Complex.zero_im, Complex.arg_zero, Real.tan_zero, Complex.zero_re]
rw [Real.tan_eq_sin_div_cos, sin_arg, cos_arg h, div_div_div_cancel_right _ (abs.ne_zero h)]
#align complex.tan_arg Complex.tan_arg
theorem arg_ofReal_of_nonneg {x : ℝ} (hx : 0 ≤ x) : arg x = 0 := by simp [arg, hx]
#align complex.arg_of_real_of_nonneg Complex.arg_ofReal_of_nonneg
@[simp, norm_cast]
lemma natCast_arg {n : ℕ} : arg n = 0 :=
ofReal_natCast n ▸ arg_ofReal_of_nonneg n.cast_nonneg
@[simp]
lemma ofNat_arg {n : ℕ} [n.AtLeastTwo] : arg (no_index (OfNat.ofNat n)) = 0 :=
natCast_arg
theorem arg_eq_zero_iff {z : ℂ} : arg z = 0 ↔ 0 ≤ z.re ∧ z.im = 0 := by
refine ⟨fun h => ?_, ?_⟩
· rw [← abs_mul_cos_add_sin_mul_I z, h]
simp [abs.nonneg]
· cases' z with x y
rintro ⟨h, rfl : y = 0⟩
exact arg_ofReal_of_nonneg h
#align complex.arg_eq_zero_iff Complex.arg_eq_zero_iff
open ComplexOrder in
lemma arg_eq_zero_iff_zero_le {z : ℂ} : arg z = 0 ↔ 0 ≤ z := by
rw [arg_eq_zero_iff, eq_comm, nonneg_iff]
theorem arg_eq_pi_iff {z : ℂ} : arg z = π ↔ z.re < 0 ∧ z.im = 0 := by
by_cases h₀ : z = 0
· simp [h₀, lt_irrefl, Real.pi_ne_zero.symm]
constructor
· intro h
rw [← abs_mul_cos_add_sin_mul_I z, h]
simp [h₀]
· cases' z with x y
rintro ⟨h : x < 0, rfl : y = 0⟩
rw [← arg_neg_one, ← arg_real_mul (-1) (neg_pos.2 h)]
simp [← ofReal_def]
#align complex.arg_eq_pi_iff Complex.arg_eq_pi_iff
open ComplexOrder in
lemma arg_eq_pi_iff_lt_zero {z : ℂ} : arg z = π ↔ z < 0 := arg_eq_pi_iff
theorem arg_lt_pi_iff {z : ℂ} : arg z < π ↔ 0 ≤ z.re ∨ z.im ≠ 0 := by
rw [(arg_le_pi z).lt_iff_ne, not_iff_comm, not_or, not_le, Classical.not_not, arg_eq_pi_iff]
#align complex.arg_lt_pi_iff Complex.arg_lt_pi_iff
theorem arg_ofReal_of_neg {x : ℝ} (hx : x < 0) : arg x = π :=
arg_eq_pi_iff.2 ⟨hx, rfl⟩
#align complex.arg_of_real_of_neg Complex.arg_ofReal_of_neg
theorem arg_eq_pi_div_two_iff {z : ℂ} : arg z = π / 2 ↔ z.re = 0 ∧ 0 < z.im := by
by_cases h₀ : z = 0; · simp [h₀, lt_irrefl, Real.pi_div_two_pos.ne]
constructor
· intro h
rw [← abs_mul_cos_add_sin_mul_I z, h]
simp [h₀]
· cases' z with x y
rintro ⟨rfl : x = 0, hy : 0 < y⟩
rw [← arg_I, ← arg_real_mul I hy, ofReal_mul', I_re, I_im, mul_zero, mul_one]
#align complex.arg_eq_pi_div_two_iff Complex.arg_eq_pi_div_two_iff
theorem arg_eq_neg_pi_div_two_iff {z : ℂ} : arg z = -(π / 2) ↔ z.re = 0 ∧ z.im < 0 := by
by_cases h₀ : z = 0; · simp [h₀, lt_irrefl, Real.pi_ne_zero]
constructor
· intro h
rw [← abs_mul_cos_add_sin_mul_I z, h]
simp [h₀]
· cases' z with x y
rintro ⟨rfl : x = 0, hy : y < 0⟩
rw [← arg_neg_I, ← arg_real_mul (-I) (neg_pos.2 hy), mk_eq_add_mul_I]
simp
#align complex.arg_eq_neg_pi_div_two_iff Complex.arg_eq_neg_pi_div_two_iff
theorem arg_of_re_nonneg {x : ℂ} (hx : 0 ≤ x.re) : arg x = Real.arcsin (x.im / abs x) :=
if_pos hx
#align complex.arg_of_re_nonneg Complex.arg_of_re_nonneg
| Mathlib/Analysis/SpecialFunctions/Complex/Arg.lean | 308 | 310 | theorem arg_of_re_neg_of_im_nonneg {x : ℂ} (hx_re : x.re < 0) (hx_im : 0 ≤ x.im) :
arg x = Real.arcsin ((-x).im / abs x) + π := by |
simp only [arg, hx_re.not_le, hx_im, if_true, if_false]
|
/-
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.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEnd`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
abbrev LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.instLieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.instLieRingModule
instance Module.End.instLieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.instLieModule
@[simp] lemma Module.End.lie_apply (f : Module.End R M) (m : M) : ⁅f, m⁆ = f m := rfl
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
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] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEnd : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEnd
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEnd R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEnd_module_end :
LieModule.toEnd R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEnd_module_end
theorem LieSubalgebra.toEnd_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEnd R K M x = LieModule.toEnd R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEnd_eq
@[simp]
theorem LieSubalgebra.toEnd_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEnd R K M ⟨x, hx⟩ = LieModule.toEnd R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEnd_mk
section
open LieAlgebra LieModule
lemma LieSubmodule.coe_toEnd (N : LieSubmodule R L M) (x : L) (y : N) :
(toEnd R L N x y : M) = toEnd R L M x y := rfl
lemma LieSubmodule.coe_toEnd_pow (N : LieSubmodule R L M) (x : L) (y : N) (n : ℕ) :
((toEnd R L N x ^ n) y : M) = (toEnd R L M x ^ n) y := by
induction n generalizing y with
| zero => rfl
| succ n ih => simp only [pow_succ', LinearMap.mul_apply, ih, LieSubmodule.coe_toEnd]
lemma LieSubalgebra.coe_ad (H : LieSubalgebra R L) (x y : H) :
(ad R H x y : L) = ad R L x y := rfl
lemma LieSubalgebra.coe_ad_pow (H : LieSubalgebra R L) (x y : H) (n : ℕ) :
((ad R H x ^ n) y : L) = (ad R L x ^ n) y :=
LieSubmodule.coe_toEnd_pow R H L H.toLieSubmodule x y n
variable {L M}
local notation "φ" => LieModule.toEnd R L M
lemma LieModule.toEnd_lie (x y : L) (z : M) :
(φ x) ⁅y, z⁆ = ⁅ad R L x y, z⁆ + ⁅y, φ x z⁆ := by
simp
lemma LieAlgebra.ad_lie (x y z : L) :
(ad R L x) ⁅y, z⁆ = ⁅ad R L x y, z⁆ + ⁅y, ad R L x z⁆ :=
toEnd_lie _ x y z
open Finset in
lemma LieModule.toEnd_pow_lie (x y : L) (z : M) (n : ℕ) :
((φ x) ^ n) ⁅y, z⁆ =
∑ ij ∈ antidiagonal n, n.choose ij.1 • ⁅((ad R L x) ^ ij.1) y, ((φ x) ^ ij.2) z⁆ := by
induction n with
| zero => simp
| succ n ih =>
rw [Finset.sum_antidiagonal_choose_succ_nsmul
(fun i j ↦ ⁅((ad R L x) ^ i) y, ((φ x) ^ j) z⁆) n]
simp only [pow_succ', LinearMap.mul_apply, ih, map_sum, map_nsmul,
toEnd_lie, nsmul_add, sum_add_distrib]
rw [add_comm, add_left_cancel_iff, sum_congr rfl]
rintro ⟨i, j⟩ hij
rw [mem_antidiagonal] at hij
rw [Nat.choose_symm_of_eq_add hij.symm]
open Finset in
lemma LieAlgebra.ad_pow_lie (x y z : L) (n : ℕ) :
((ad R L x) ^ n) ⁅y, z⁆ =
∑ ij ∈ antidiagonal n, n.choose ij.1 • ⁅((ad R L x) ^ ij.1) y, ((ad R L x) ^ ij.2) z⁆ :=
toEnd_pow_lie _ x y z n
end
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEnd_pow_comp_lieHom :
(toEnd R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEnd R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEnd_pow_apply_map (m : M) :
(toEnd R L M₂ x ^ k) (f m) = f ((toEnd R L M x ^ k) m) :=
LinearMap.congr_fun (toEnd_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEnd_le :
(N : Submodule R M).map (LieModule.toEnd R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEnd_le
variable (N x)
theorem toEnd_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEnd R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEnd_comp_subtype_mem
@[simp]
theorem toEnd_restrict_eq_toEnd (h := N.toEnd_comp_subtype_mem x) :
(toEnd R L M x).restrict h = toEnd R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEnd_restrict_eq_toEnd
lemma mapsTo_pow_toEnd_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEnd R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
exact MapsTo.iterate (fun m hm ↦ N.sub_mem (N.lie_mem hm) (N.smul_mem _ hm)) k
end LieSubmodule
open LieAlgebra
theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
ext a b; simp [LieRing.of_associative_ring_bracket]
#align lie_algebra.ad_eq_lmul_left_sub_lmul_right LieAlgebra.ad_eq_lmul_left_sub_lmul_right
| Mathlib/Algebra/Lie/OfAssociative.lean | 346 | 350 | theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) := by |
ext y
simp only [ad_apply, LieHom.coe_toLinearMap, LieSubalgebra.coe_incl, LinearMap.coe_comp,
LieSubalgebra.coe_bracket, Function.comp_apply]
|
/-
Copyright (c) 2020 Yury Kudryashov, Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Data.Fintype.BigOperators
import Mathlib.Data.Fintype.Fin
import Mathlib.GroupTheory.GroupAction.Pi
import Mathlib.Logic.Equiv.Fin
#align_import algebra.big_operators.fin from "leanprover-community/mathlib"@"cc5dd6244981976cc9da7afc4eee5682b037a013"
/-!
# Big operators and `Fin`
Some results about products and sums over the type `Fin`.
The most important results are the induction formulas `Fin.prod_univ_castSucc`
and `Fin.prod_univ_succ`, and the formula `Fin.prod_const` for the product of a
constant function. These results have variants for sums instead of products.
## Main declarations
* `finFunctionFinEquiv`: An explicit equivalence between `Fin n → Fin m` and `Fin (m ^ n)`.
-/
open Finset
variable {α : Type*} {β : Type*}
namespace Finset
@[to_additive]
theorem prod_range [CommMonoid β] {n : ℕ} (f : ℕ → β) :
∏ i ∈ Finset.range n, f i = ∏ i : Fin n, f i :=
(Fin.prod_univ_eq_prod_range _ _).symm
#align finset.prod_range Finset.prod_range
#align finset.sum_range Finset.sum_range
end Finset
namespace Fin
@[to_additive]
theorem prod_ofFn [CommMonoid β] {n : ℕ} (f : Fin n → β) : (List.ofFn f).prod = ∏ i, f i := by
simp [prod_eq_multiset_prod]
#align fin.prod_of_fn Fin.prod_ofFn
#align fin.sum_of_fn Fin.sum_ofFn
@[to_additive]
theorem prod_univ_def [CommMonoid β] {n : ℕ} (f : Fin n → β) :
∏ i, f i = ((List.finRange n).map f).prod := by
rw [← List.ofFn_eq_map, prod_ofFn]
#align fin.prod_univ_def Fin.prod_univ_def
#align fin.sum_univ_def Fin.sum_univ_def
/-- A product of a function `f : Fin 0 → β` is `1` because `Fin 0` is empty -/
@[to_additive "A sum of a function `f : Fin 0 → β` is `0` because `Fin 0` is empty"]
theorem prod_univ_zero [CommMonoid β] (f : Fin 0 → β) : ∏ i, f i = 1 :=
rfl
#align fin.prod_univ_zero Fin.prod_univ_zero
#align fin.sum_univ_zero Fin.sum_univ_zero
/-- A product of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)`
is the product of `f x`, for some `x : Fin (n + 1)` times the remaining product -/
@[to_additive "A sum of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)` is the sum of
`f x`, for some `x : Fin (n + 1)` plus the remaining product"]
theorem prod_univ_succAbove [CommMonoid β] {n : ℕ} (f : Fin (n + 1) → β) (x : Fin (n + 1)) :
∏ i, f i = f x * ∏ i : Fin n, f (x.succAbove i) := by
rw [univ_succAbove, prod_cons, Finset.prod_map _ x.succAboveEmb]
rfl
#align fin.prod_univ_succ_above Fin.prod_univ_succAbove
#align fin.sum_univ_succ_above Fin.sum_univ_succAbove
/-- A product of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)`
is the product of `f 0` plus the remaining product -/
@[to_additive "A sum of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)` is the sum of
`f 0` plus the remaining product"]
theorem prod_univ_succ [CommMonoid β] {n : ℕ} (f : Fin (n + 1) → β) :
∏ i, f i = f 0 * ∏ i : Fin n, f i.succ :=
prod_univ_succAbove f 0
#align fin.prod_univ_succ Fin.prod_univ_succ
#align fin.sum_univ_succ Fin.sum_univ_succ
/-- A product of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)`
is the product of `f (Fin.last n)` plus the remaining product -/
@[to_additive "A sum of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)` is the sum of
`f (Fin.last n)` plus the remaining sum"]
theorem prod_univ_castSucc [CommMonoid β] {n : ℕ} (f : Fin (n + 1) → β) :
∏ i, f i = (∏ i : Fin n, f (Fin.castSucc i)) * f (last n) := by
simpa [mul_comm] using prod_univ_succAbove f (last n)
#align fin.prod_univ_cast_succ Fin.prod_univ_castSucc
#align fin.sum_univ_cast_succ Fin.sum_univ_castSucc
@[to_additive (attr := simp)]
theorem prod_univ_get [CommMonoid α] (l : List α) : ∏ i, l.get i = l.prod := by
simp [Finset.prod_eq_multiset_prod]
@[to_additive (attr := simp)]
theorem prod_univ_get' [CommMonoid β] (l : List α) (f : α → β) :
∏ i, f (l.get i) = (l.map f).prod := by
simp [Finset.prod_eq_multiset_prod]
@[to_additive]
theorem prod_cons [CommMonoid β] {n : ℕ} (x : β) (f : Fin n → β) :
(∏ i : Fin n.succ, (cons x f : Fin n.succ → β) i) = x * ∏ i : Fin n, f i := by
simp_rw [prod_univ_succ, cons_zero, cons_succ]
#align fin.prod_cons Fin.prod_cons
#align fin.sum_cons Fin.sum_cons
@[to_additive sum_univ_one]
theorem prod_univ_one [CommMonoid β] (f : Fin 1 → β) : ∏ i, f i = f 0 := by simp
#align fin.prod_univ_one Fin.prod_univ_one
#align fin.sum_univ_one Fin.sum_univ_one
@[to_additive (attr := simp)]
theorem prod_univ_two [CommMonoid β] (f : Fin 2 → β) : ∏ i, f i = f 0 * f 1 := by
simp [prod_univ_succ]
#align fin.prod_univ_two Fin.prod_univ_two
#align fin.sum_univ_two Fin.sum_univ_two
@[to_additive]
theorem prod_univ_two' [CommMonoid β] (f : α → β) (a b : α) :
∏ i, f (![a, b] i) = f a * f b :=
prod_univ_two _
@[to_additive]
theorem prod_univ_three [CommMonoid β] (f : Fin 3 → β) : ∏ i, f i = f 0 * f 1 * f 2 := by
rw [prod_univ_castSucc, prod_univ_two]
rfl
#align fin.prod_univ_three Fin.prod_univ_three
#align fin.sum_univ_three Fin.sum_univ_three
@[to_additive]
theorem prod_univ_four [CommMonoid β] (f : Fin 4 → β) : ∏ i, f i = f 0 * f 1 * f 2 * f 3 := by
rw [prod_univ_castSucc, prod_univ_three]
rfl
#align fin.prod_univ_four Fin.prod_univ_four
#align fin.sum_univ_four Fin.sum_univ_four
@[to_additive]
theorem prod_univ_five [CommMonoid β] (f : Fin 5 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 := by
rw [prod_univ_castSucc, prod_univ_four]
rfl
#align fin.prod_univ_five Fin.prod_univ_five
#align fin.sum_univ_five Fin.sum_univ_five
@[to_additive]
theorem prod_univ_six [CommMonoid β] (f : Fin 6 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 * f 5 := by
rw [prod_univ_castSucc, prod_univ_five]
rfl
#align fin.prod_univ_six Fin.prod_univ_six
#align fin.sum_univ_six Fin.sum_univ_six
@[to_additive]
theorem prod_univ_seven [CommMonoid β] (f : Fin 7 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 * f 5 * f 6 := by
rw [prod_univ_castSucc, prod_univ_six]
rfl
#align fin.prod_univ_seven Fin.prod_univ_seven
#align fin.sum_univ_seven Fin.sum_univ_seven
@[to_additive]
theorem prod_univ_eight [CommMonoid β] (f : Fin 8 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 * f 5 * f 6 * f 7 := by
rw [prod_univ_castSucc, prod_univ_seven]
rfl
#align fin.prod_univ_eight Fin.prod_univ_eight
#align fin.sum_univ_eight Fin.sum_univ_eight
theorem sum_pow_mul_eq_add_pow {n : ℕ} {R : Type*} [CommSemiring R] (a b : R) :
(∑ s : Finset (Fin n), a ^ s.card * b ^ (n - s.card)) = (a + b) ^ n := by
simpa using Fintype.sum_pow_mul_eq_add_pow (Fin n) a b
#align fin.sum_pow_mul_eq_add_pow Fin.sum_pow_mul_eq_add_pow
| Mathlib/Algebra/BigOperators/Fin.lean | 179 | 179 | theorem prod_const [CommMonoid α] (n : ℕ) (x : α) : ∏ _i : Fin n, x = x ^ n := by | simp
|
/-
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.Order.MinMax
import Mathlib.Data.Set.Subsingleton
import Mathlib.Tactic.Says
#align_import data.set.intervals.basic from "leanprover-community/mathlib"@"3ba15165bd6927679be7c22d6091a87337e3cd0c"
/-!
# Intervals
In any preorder `α`, 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]`.
This file contains these definitions, and basic facts on inclusion, intersection, difference of
intervals (where the precise statements may depend on the properties of the order, in particular
for some statements it should be `LinearOrder` or `DenselyOrdered`).
TODO: This is just the beginning; a lot of rules are missing
-/
open Function
open OrderDual (toDual ofDual)
variable {α β : Type*}
namespace Set
section Preorder
variable [Preorder α] {a a₁ a₂ b b₁ b₂ c x : α}
/-- Left-open right-open interval -/
def Ioo (a b : α) :=
{ x | a < x ∧ x < b }
#align set.Ioo Set.Ioo
/-- Left-closed right-open interval -/
def Ico (a b : α) :=
{ x | a ≤ x ∧ x < b }
#align set.Ico Set.Ico
/-- Left-infinite right-open interval -/
def Iio (a : α) :=
{ x | x < a }
#align set.Iio Set.Iio
/-- Left-closed right-closed interval -/
def Icc (a b : α) :=
{ x | a ≤ x ∧ x ≤ b }
#align set.Icc Set.Icc
/-- Left-infinite right-closed interval -/
def Iic (b : α) :=
{ x | x ≤ b }
#align set.Iic Set.Iic
/-- Left-open right-closed interval -/
def Ioc (a b : α) :=
{ x | a < x ∧ x ≤ b }
#align set.Ioc Set.Ioc
/-- Left-closed right-infinite interval -/
def Ici (a : α) :=
{ x | a ≤ x }
#align set.Ici Set.Ici
/-- Left-open right-infinite interval -/
def Ioi (a : α) :=
{ x | a < x }
#align set.Ioi Set.Ioi
theorem Ioo_def (a b : α) : { x | a < x ∧ x < b } = Ioo a b :=
rfl
#align set.Ioo_def Set.Ioo_def
theorem Ico_def (a b : α) : { x | a ≤ x ∧ x < b } = Ico a b :=
rfl
#align set.Ico_def Set.Ico_def
theorem Iio_def (a : α) : { x | x < a } = Iio a :=
rfl
#align set.Iio_def Set.Iio_def
theorem Icc_def (a b : α) : { x | a ≤ x ∧ x ≤ b } = Icc a b :=
rfl
#align set.Icc_def Set.Icc_def
theorem Iic_def (b : α) : { x | x ≤ b } = Iic b :=
rfl
#align set.Iic_def Set.Iic_def
theorem Ioc_def (a b : α) : { x | a < x ∧ x ≤ b } = Ioc a b :=
rfl
#align set.Ioc_def Set.Ioc_def
theorem Ici_def (a : α) : { x | a ≤ x } = Ici a :=
rfl
#align set.Ici_def Set.Ici_def
theorem Ioi_def (a : α) : { x | a < x } = Ioi a :=
rfl
#align set.Ioi_def Set.Ioi_def
@[simp]
theorem mem_Ioo : x ∈ Ioo a b ↔ a < x ∧ x < b :=
Iff.rfl
#align set.mem_Ioo Set.mem_Ioo
@[simp]
theorem mem_Ico : x ∈ Ico a b ↔ a ≤ x ∧ x < b :=
Iff.rfl
#align set.mem_Ico Set.mem_Ico
@[simp]
theorem mem_Iio : x ∈ Iio b ↔ x < b :=
Iff.rfl
#align set.mem_Iio Set.mem_Iio
@[simp]
theorem mem_Icc : x ∈ Icc a b ↔ a ≤ x ∧ x ≤ b :=
Iff.rfl
#align set.mem_Icc Set.mem_Icc
@[simp]
theorem mem_Iic : x ∈ Iic b ↔ x ≤ b :=
Iff.rfl
#align set.mem_Iic Set.mem_Iic
@[simp]
theorem mem_Ioc : x ∈ Ioc a b ↔ a < x ∧ x ≤ b :=
Iff.rfl
#align set.mem_Ioc Set.mem_Ioc
@[simp]
theorem mem_Ici : x ∈ Ici a ↔ a ≤ x :=
Iff.rfl
#align set.mem_Ici Set.mem_Ici
@[simp]
theorem mem_Ioi : x ∈ Ioi a ↔ a < x :=
Iff.rfl
#align set.mem_Ioi Set.mem_Ioi
instance decidableMemIoo [Decidable (a < x ∧ x < b)] : Decidable (x ∈ Ioo a b) := by assumption
#align set.decidable_mem_Ioo Set.decidableMemIoo
instance decidableMemIco [Decidable (a ≤ x ∧ x < b)] : Decidable (x ∈ Ico a b) := by assumption
#align set.decidable_mem_Ico Set.decidableMemIco
instance decidableMemIio [Decidable (x < b)] : Decidable (x ∈ Iio b) := by assumption
#align set.decidable_mem_Iio Set.decidableMemIio
instance decidableMemIcc [Decidable (a ≤ x ∧ x ≤ b)] : Decidable (x ∈ Icc a b) := by assumption
#align set.decidable_mem_Icc Set.decidableMemIcc
instance decidableMemIic [Decidable (x ≤ b)] : Decidable (x ∈ Iic b) := by assumption
#align set.decidable_mem_Iic Set.decidableMemIic
instance decidableMemIoc [Decidable (a < x ∧ x ≤ b)] : Decidable (x ∈ Ioc a b) := by assumption
#align set.decidable_mem_Ioc Set.decidableMemIoc
instance decidableMemIci [Decidable (a ≤ x)] : Decidable (x ∈ Ici a) := by assumption
#align set.decidable_mem_Ici Set.decidableMemIci
instance decidableMemIoi [Decidable (a < x)] : Decidable (x ∈ Ioi a) := by assumption
#align set.decidable_mem_Ioi Set.decidableMemIoi
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem left_mem_Ioo : a ∈ Ioo a b ↔ False := by simp [lt_irrefl]
#align set.left_mem_Ioo Set.left_mem_Ioo
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp [le_refl]
#align set.left_mem_Ico Set.left_mem_Ico
-- Porting note (#10618): `simp` can prove this
-- @[simp]
| Mathlib/Order/Interval/Set/Basic.lean | 191 | 191 | theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by | simp [le_refl]
|
/-
Copyright (c) 2021 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Eric Wieser
-/
import Mathlib.RingTheory.Ideal.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.RingTheory.GradedAlgebra.Basic
#align_import ring_theory.graded_algebra.homogeneous_ideal from "leanprover-community/mathlib"@"4e861f25ba5ceef42ba0712d8ffeb32f38ad6441"
/-!
# Homogeneous ideals of a graded algebra
This file defines homogeneous ideals of `GradedRing 𝒜` where `𝒜 : ι → Submodule R A` and
operations on them.
## Main definitions
For any `I : Ideal A`:
* `Ideal.IsHomogeneous 𝒜 I`: The property that an ideal is closed under `GradedRing.proj`.
* `HomogeneousIdeal 𝒜`: The structure extending ideals which satisfy `Ideal.IsHomogeneous`.
* `Ideal.homogeneousCore I 𝒜`: The largest homogeneous ideal smaller than `I`.
* `Ideal.homogeneousHull I 𝒜`: The smallest homogeneous ideal larger than `I`.
## Main statements
* `HomogeneousIdeal.completeLattice`: `Ideal.IsHomogeneous` is preserved by `⊥`, `⊤`, `⊔`, `⊓`,
`⨆`, `⨅`, and so the subtype of homogeneous ideals inherits a complete lattice structure.
* `Ideal.homogeneousCore.gi`: `Ideal.homogeneousCore` forms a galois insertion with coercion.
* `Ideal.homogeneousHull.gi`: `Ideal.homogeneousHull` forms a galois insertion with coercion.
## Implementation notes
We introduce `Ideal.homogeneousCore'` earlier than might be expected so that we can get access
to `Ideal.IsHomogeneous.iff_exists` as quickly as possible.
## Tags
graded algebra, homogeneous
-/
open SetLike DirectSum Set
open Pointwise DirectSum
variable {ι σ R A : Type*}
section HomogeneousDef
variable [Semiring A]
variable [SetLike σ A] [AddSubmonoidClass σ A] (𝒜 : ι → σ)
variable [DecidableEq ι] [AddMonoid ι] [GradedRing 𝒜]
variable (I : Ideal A)
/-- An `I : Ideal A` is homogeneous if for every `r ∈ I`, all homogeneous components
of `r` are in `I`. -/
def Ideal.IsHomogeneous : Prop :=
∀ (i : ι) ⦃r : A⦄, r ∈ I → (DirectSum.decompose 𝒜 r i : A) ∈ I
#align ideal.is_homogeneous Ideal.IsHomogeneous
theorem Ideal.IsHomogeneous.mem_iff {I} (hI : Ideal.IsHomogeneous 𝒜 I) {x} :
x ∈ I ↔ ∀ i, (decompose 𝒜 x i : A) ∈ I := by
classical
refine ⟨fun hx i ↦ hI i hx, fun hx ↦ ?_⟩
rw [← DirectSum.sum_support_decompose 𝒜 x]
exact Ideal.sum_mem _ (fun i _ ↦ hx i)
/-- For any `Semiring A`, we collect the homogeneous ideals of `A` into a type. -/
structure HomogeneousIdeal extends Submodule A A where
is_homogeneous' : Ideal.IsHomogeneous 𝒜 toSubmodule
#align homogeneous_ideal HomogeneousIdeal
variable {𝒜}
/-- Converting a homogeneous ideal to an ideal. -/
def HomogeneousIdeal.toIdeal (I : HomogeneousIdeal 𝒜) : Ideal A :=
I.toSubmodule
#align homogeneous_ideal.to_ideal HomogeneousIdeal.toIdeal
theorem HomogeneousIdeal.isHomogeneous (I : HomogeneousIdeal 𝒜) : I.toIdeal.IsHomogeneous 𝒜 :=
I.is_homogeneous'
#align homogeneous_ideal.is_homogeneous HomogeneousIdeal.isHomogeneous
theorem HomogeneousIdeal.toIdeal_injective :
Function.Injective (HomogeneousIdeal.toIdeal : HomogeneousIdeal 𝒜 → Ideal A) :=
fun ⟨x, hx⟩ ⟨y, hy⟩ => fun (h : x = y) => by simp [h]
#align homogeneous_ideal.to_ideal_injective HomogeneousIdeal.toIdeal_injective
instance HomogeneousIdeal.setLike : SetLike (HomogeneousIdeal 𝒜) A where
coe I := I.toIdeal
coe_injective' _ _ h := HomogeneousIdeal.toIdeal_injective <| SetLike.coe_injective h
#align homogeneous_ideal.set_like HomogeneousIdeal.setLike
@[ext]
theorem HomogeneousIdeal.ext {I J : HomogeneousIdeal 𝒜} (h : I.toIdeal = J.toIdeal) : I = J :=
HomogeneousIdeal.toIdeal_injective h
#align homogeneous_ideal.ext HomogeneousIdeal.ext
theorem HomogeneousIdeal.ext' {I J : HomogeneousIdeal 𝒜} (h : ∀ i, ∀ x ∈ 𝒜 i, x ∈ I ↔ x ∈ J) :
I = J := by
ext
rw [I.isHomogeneous.mem_iff, J.isHomogeneous.mem_iff]
apply forall_congr'
exact fun i ↦ h i _ (decompose 𝒜 _ i).2
@[simp]
theorem HomogeneousIdeal.mem_iff {I : HomogeneousIdeal 𝒜} {x : A} : x ∈ I.toIdeal ↔ x ∈ I :=
Iff.rfl
#align homogeneous_ideal.mem_iff HomogeneousIdeal.mem_iff
end HomogeneousDef
section HomogeneousCore
variable [Semiring A]
variable [SetLike σ A] (𝒜 : ι → σ)
variable (I : Ideal A)
/-- For any `I : Ideal A`, not necessarily homogeneous, `I.homogeneousCore' 𝒜`
is the largest homogeneous ideal of `A` contained in `I`, as an ideal. -/
def Ideal.homogeneousCore' (I : Ideal A) : Ideal A :=
Ideal.span ((↑) '' (((↑) : Subtype (Homogeneous 𝒜) → A) ⁻¹' I))
#align ideal.homogeneous_core' Ideal.homogeneousCore'
theorem Ideal.homogeneousCore'_mono : Monotone (Ideal.homogeneousCore' 𝒜) :=
fun _ _ I_le_J => Ideal.span_mono <| Set.image_subset _ fun _ => @I_le_J _
#align ideal.homogeneous_core'_mono Ideal.homogeneousCore'_mono
theorem Ideal.homogeneousCore'_le : I.homogeneousCore' 𝒜 ≤ I :=
Ideal.span_le.2 <| image_preimage_subset _ _
#align ideal.homogeneous_core'_le Ideal.homogeneousCore'_le
end HomogeneousCore
section IsHomogeneousIdealDefs
variable [Semiring A]
variable [SetLike σ A] [AddSubmonoidClass σ A] (𝒜 : ι → σ)
variable [DecidableEq ι] [AddMonoid ι] [GradedRing 𝒜]
variable (I : Ideal A)
theorem Ideal.isHomogeneous_iff_forall_subset :
I.IsHomogeneous 𝒜 ↔ ∀ i, (I : Set A) ⊆ GradedRing.proj 𝒜 i ⁻¹' I :=
Iff.rfl
#align ideal.is_homogeneous_iff_forall_subset Ideal.isHomogeneous_iff_forall_subset
theorem Ideal.isHomogeneous_iff_subset_iInter :
I.IsHomogeneous 𝒜 ↔ (I : Set A) ⊆ ⋂ i, GradedRing.proj 𝒜 i ⁻¹' ↑I :=
subset_iInter_iff.symm
#align ideal.is_homogeneous_iff_subset_Inter Ideal.isHomogeneous_iff_subset_iInter
theorem Ideal.mul_homogeneous_element_mem_of_mem {I : Ideal A} (r x : A) (hx₁ : Homogeneous 𝒜 x)
(hx₂ : x ∈ I) (j : ι) : GradedRing.proj 𝒜 j (r * x) ∈ I := by
classical
rw [← DirectSum.sum_support_decompose 𝒜 r, Finset.sum_mul, map_sum]
apply Ideal.sum_mem
intro k _
obtain ⟨i, hi⟩ := hx₁
have mem₁ : (DirectSum.decompose 𝒜 r k : A) * x ∈ 𝒜 (k + i) :=
GradedMul.mul_mem (SetLike.coe_mem _) hi
erw [GradedRing.proj_apply, DirectSum.decompose_of_mem 𝒜 mem₁, coe_of_apply]
split_ifs
· exact I.mul_mem_left _ hx₂
· exact I.zero_mem
#align ideal.mul_homogeneous_element_mem_of_mem Ideal.mul_homogeneous_element_mem_of_mem
theorem Ideal.homogeneous_span (s : Set A) (h : ∀ x ∈ s, Homogeneous 𝒜 x) :
(Ideal.span s).IsHomogeneous 𝒜 := by
rintro i r hr
rw [Ideal.span, Finsupp.span_eq_range_total] at hr
rw [LinearMap.mem_range] at hr
obtain ⟨s, rfl⟩ := hr
rw [Finsupp.total_apply, Finsupp.sum, decompose_sum, DFinsupp.finset_sum_apply,
AddSubmonoidClass.coe_finset_sum]
refine Ideal.sum_mem _ ?_
rintro z hz1
rw [smul_eq_mul]
refine Ideal.mul_homogeneous_element_mem_of_mem 𝒜 (s z) z ?_ ?_ i
· rcases z with ⟨z, hz2⟩
apply h _ hz2
· exact Ideal.subset_span z.2
#align ideal.is_homogeneous_span Ideal.homogeneous_span
/-- For any `I : Ideal A`, not necessarily homogeneous, `I.homogeneousCore' 𝒜`
is the largest homogeneous ideal of `A` contained in `I`. -/
def Ideal.homogeneousCore : HomogeneousIdeal 𝒜 :=
⟨Ideal.homogeneousCore' 𝒜 I,
Ideal.homogeneous_span _ _ fun _ h => by
have := Subtype.image_preimage_coe (setOf (Homogeneous 𝒜)) (I : Set A)
exact (cast congr(_ ∈ $this) h).1⟩
#align ideal.homogeneous_core Ideal.homogeneousCore
theorem Ideal.homogeneousCore_mono : Monotone (Ideal.homogeneousCore 𝒜) :=
Ideal.homogeneousCore'_mono 𝒜
#align ideal.homogeneous_core_mono Ideal.homogeneousCore_mono
theorem Ideal.toIdeal_homogeneousCore_le : (I.homogeneousCore 𝒜).toIdeal ≤ I :=
Ideal.homogeneousCore'_le 𝒜 I
#align ideal.to_ideal_homogeneous_core_le Ideal.toIdeal_homogeneousCore_le
variable {𝒜 I}
theorem Ideal.mem_homogeneousCore_of_homogeneous_of_mem {x : A} (h : SetLike.Homogeneous 𝒜 x)
(hmem : x ∈ I) : x ∈ I.homogeneousCore 𝒜 :=
Ideal.subset_span ⟨⟨x, h⟩, hmem, rfl⟩
#align ideal.mem_homogeneous_core_of_is_homogeneous_of_mem Ideal.mem_homogeneousCore_of_homogeneous_of_mem
theorem Ideal.IsHomogeneous.toIdeal_homogeneousCore_eq_self (h : I.IsHomogeneous 𝒜) :
(I.homogeneousCore 𝒜).toIdeal = I := by
apply le_antisymm (I.homogeneousCore'_le 𝒜) _
intro x hx
classical
rw [← DirectSum.sum_support_decompose 𝒜 x]
exact Ideal.sum_mem _ fun j _ => Ideal.subset_span ⟨⟨_, homogeneous_coe _⟩, h _ hx, rfl⟩
#align ideal.is_homogeneous.to_ideal_homogeneous_core_eq_self Ideal.IsHomogeneous.toIdeal_homogeneousCore_eq_self
@[simp]
theorem HomogeneousIdeal.toIdeal_homogeneousCore_eq_self (I : HomogeneousIdeal 𝒜) :
I.toIdeal.homogeneousCore 𝒜 = I := by
ext1
convert Ideal.IsHomogeneous.toIdeal_homogeneousCore_eq_self I.isHomogeneous
#align homogeneous_ideal.to_ideal_homogeneous_core_eq_self HomogeneousIdeal.toIdeal_homogeneousCore_eq_self
variable (𝒜 I)
theorem Ideal.IsHomogeneous.iff_eq : I.IsHomogeneous 𝒜 ↔ (I.homogeneousCore 𝒜).toIdeal = I :=
⟨fun hI => hI.toIdeal_homogeneousCore_eq_self, fun hI => hI ▸ (Ideal.homogeneousCore 𝒜 I).2⟩
#align ideal.is_homogeneous.iff_eq Ideal.IsHomogeneous.iff_eq
| Mathlib/RingTheory/GradedAlgebra/HomogeneousIdeal.lean | 233 | 236 | theorem Ideal.IsHomogeneous.iff_exists :
I.IsHomogeneous 𝒜 ↔ ∃ S : Set (homogeneousSubmonoid 𝒜), I = Ideal.span ((↑) '' S) := by |
rw [Ideal.IsHomogeneous.iff_eq, eq_comm]
exact ((Set.image_preimage.compose (Submodule.gi _ _).gc).exists_eq_l _).symm
|
/-
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.Function.ConditionalExpectation.CondexpL1
#align_import measure_theory.function.conditional_expectation.basic from "leanprover-community/mathlib"@"d8bbb04e2d2a44596798a9207ceefc0fb236e41e"
/-! # Conditional expectation
We build the conditional expectation of an integrable function `f` with value in a Banach space
with respect to a measure `μ` (defined on a measurable space structure `m0`) and a measurable space
structure `m` with `hm : m ≤ m0` (a sub-sigma-algebra). This is an `m`-strongly measurable
function `μ[f|hm]` which is integrable and verifies `∫ x in s, μ[f|hm] x ∂μ = ∫ x in s, f x ∂μ`
for all `m`-measurable sets `s`. It is unique as an element of `L¹`.
The construction is done in four steps:
* Define the conditional expectation of an `L²` function, as an element of `L²`. This is the
orthogonal projection on the subspace of almost everywhere `m`-measurable functions.
* Show that the conditional expectation of the indicator of a measurable set with finite measure
is integrable and define a map `Set α → (E →L[ℝ] (α →₁[μ] E))` which to a set associates a linear
map. That linear map sends `x ∈ E` to the conditional expectation of the indicator of the set
with value `x`.
* Extend that map to `condexpL1CLM : (α →₁[μ] E) →L[ℝ] (α →₁[μ] E)`. This is done using the same
construction as the Bochner integral (see the file `MeasureTheory/Integral/SetToL1`).
* Define the conditional expectation of a function `f : α → E`, which is an integrable function
`α → E` equal to 0 if `f` is not integrable, and equal to an `m`-measurable representative of
`condexpL1CLM` applied to `[f]`, the equivalence class of `f` in `L¹`.
The first step is done in `MeasureTheory.Function.ConditionalExpectation.CondexpL2`, the two
next steps in `MeasureTheory.Function.ConditionalExpectation.CondexpL1` and the final step is
performed in this file.
## Main results
The conditional expectation and its properties
* `condexp (m : MeasurableSpace α) (μ : Measure α) (f : α → E)`: conditional expectation of `f`
with respect to `m`.
* `integrable_condexp` : `condexp` is integrable.
* `stronglyMeasurable_condexp` : `condexp` is `m`-strongly-measurable.
* `setIntegral_condexp (hf : Integrable f μ) (hs : MeasurableSet[m] s)` : if `m ≤ m0` (the
σ-algebra over which the measure is defined), then the conditional expectation verifies
`∫ x in s, condexp m μ f x ∂μ = ∫ x in s, f x ∂μ` for any `m`-measurable set `s`.
While `condexp` is function-valued, we also define `condexpL1` with value in `L1` and a continuous
linear map `condexpL1CLM` from `L1` to `L1`. `condexp` should be used in most cases.
Uniqueness of the conditional expectation
* `ae_eq_condexp_of_forall_setIntegral_eq`: an a.e. `m`-measurable function which verifies the
equality of integrals is a.e. equal to `condexp`.
## Notations
For a measure `μ` defined on a measurable space structure `m0`, another measurable space structure
`m` with `hm : m ≤ m0` (a sub-σ-algebra) and a function `f`, we define the notation
* `μ[f|m] = condexp m μ f`.
## Tags
conditional expectation, conditional expected value
-/
open TopologicalSpace MeasureTheory.Lp Filter
open scoped ENNReal Topology MeasureTheory
namespace MeasureTheory
variable {α F F' 𝕜 : Type*} {p : ℝ≥0∞} [RCLike 𝕜]
-- 𝕜 for ℝ or ℂ
-- F for a Lp submodule
[NormedAddCommGroup F]
[NormedSpace 𝕜 F]
-- F' for integrals on a Lp submodule
[NormedAddCommGroup F']
[NormedSpace 𝕜 F'] [NormedSpace ℝ F'] [CompleteSpace F']
open scoped Classical
variable {m m0 : MeasurableSpace α} {μ : Measure α} {f g : α → F'} {s : Set α}
/-- Conditional expectation of a function. It is defined as 0 if any one of the following conditions
is true:
- `m` is not a sub-σ-algebra of `m0`,
- `μ` is not σ-finite with respect to `m`,
- `f` is not integrable. -/
noncomputable irreducible_def condexp (m : MeasurableSpace α) {m0 : MeasurableSpace α}
(μ : Measure α) (f : α → F') : α → F' :=
if hm : m ≤ m0 then
if h : SigmaFinite (μ.trim hm) ∧ Integrable f μ then
if StronglyMeasurable[m] f then f
else (@aestronglyMeasurable'_condexpL1 _ _ _ _ _ m m0 μ hm h.1 _).mk
(@condexpL1 _ _ _ _ _ _ _ hm μ h.1 f)
else 0
else 0
#align measure_theory.condexp MeasureTheory.condexp
-- We define notation `μ[f|m]` for the conditional expectation of `f` with respect to `m`.
scoped notation μ "[" f "|" m "]" => MeasureTheory.condexp m μ f
theorem condexp_of_not_le (hm_not : ¬m ≤ m0) : μ[f|m] = 0 := by rw [condexp, dif_neg hm_not]
#align measure_theory.condexp_of_not_le MeasureTheory.condexp_of_not_le
theorem condexp_of_not_sigmaFinite (hm : m ≤ m0) (hμm_not : ¬SigmaFinite (μ.trim hm)) :
μ[f|m] = 0 := by rw [condexp, dif_pos hm, dif_neg]; push_neg; exact fun h => absurd h hμm_not
#align measure_theory.condexp_of_not_sigma_finite MeasureTheory.condexp_of_not_sigmaFinite
theorem condexp_of_sigmaFinite (hm : m ≤ m0) [hμm : SigmaFinite (μ.trim hm)] :
μ[f|m] =
if Integrable f μ then
if StronglyMeasurable[m] f then f
else aestronglyMeasurable'_condexpL1.mk (condexpL1 hm μ f)
else 0 := by
rw [condexp, dif_pos hm]
simp only [hμm, Ne, true_and_iff]
by_cases hf : Integrable f μ
· rw [dif_pos hf, if_pos hf]
· rw [dif_neg hf, if_neg hf]
#align measure_theory.condexp_of_sigma_finite MeasureTheory.condexp_of_sigmaFinite
theorem condexp_of_stronglyMeasurable (hm : m ≤ m0) [hμm : SigmaFinite (μ.trim hm)] {f : α → F'}
(hf : StronglyMeasurable[m] f) (hfi : Integrable f μ) : μ[f|m] = f := by
rw [condexp_of_sigmaFinite hm, if_pos hfi, if_pos hf]
#align measure_theory.condexp_of_strongly_measurable MeasureTheory.condexp_of_stronglyMeasurable
theorem condexp_const (hm : m ≤ m0) (c : F') [IsFiniteMeasure μ] :
μ[fun _ : α => c|m] = fun _ => c :=
condexp_of_stronglyMeasurable hm (@stronglyMeasurable_const _ _ m _ _) (integrable_const c)
#align measure_theory.condexp_const MeasureTheory.condexp_const
theorem condexp_ae_eq_condexpL1 (hm : m ≤ m0) [hμm : SigmaFinite (μ.trim hm)] (f : α → F') :
μ[f|m] =ᵐ[μ] condexpL1 hm μ f := by
rw [condexp_of_sigmaFinite hm]
by_cases hfi : Integrable f μ
· rw [if_pos hfi]
by_cases hfm : StronglyMeasurable[m] f
· rw [if_pos hfm]
exact (condexpL1_of_aestronglyMeasurable' (StronglyMeasurable.aeStronglyMeasurable' hfm)
hfi).symm
· rw [if_neg hfm]
exact (AEStronglyMeasurable'.ae_eq_mk aestronglyMeasurable'_condexpL1).symm
rw [if_neg hfi, condexpL1_undef hfi]
exact (coeFn_zero _ _ _).symm
set_option linter.uppercaseLean3 false in
#align measure_theory.condexp_ae_eq_condexp_L1 MeasureTheory.condexp_ae_eq_condexpL1
theorem condexp_ae_eq_condexpL1CLM (hm : m ≤ m0) [SigmaFinite (μ.trim hm)] (hf : Integrable f μ) :
μ[f|m] =ᵐ[μ] condexpL1CLM F' hm μ (hf.toL1 f) := by
refine (condexp_ae_eq_condexpL1 hm f).trans (eventually_of_forall fun x => ?_)
rw [condexpL1_eq hf]
set_option linter.uppercaseLean3 false in
#align measure_theory.condexp_ae_eq_condexp_L1_clm MeasureTheory.condexp_ae_eq_condexpL1CLM
theorem condexp_undef (hf : ¬Integrable f μ) : μ[f|m] = 0 := by
by_cases hm : m ≤ m0
swap; · rw [condexp_of_not_le hm]
by_cases hμm : SigmaFinite (μ.trim hm)
swap; · rw [condexp_of_not_sigmaFinite hm hμm]
haveI : SigmaFinite (μ.trim hm) := hμm
rw [condexp_of_sigmaFinite, if_neg hf]
#align measure_theory.condexp_undef MeasureTheory.condexp_undef
@[simp]
theorem condexp_zero : μ[(0 : α → F')|m] = 0 := by
by_cases hm : m ≤ m0
swap; · rw [condexp_of_not_le hm]
by_cases hμm : SigmaFinite (μ.trim hm)
swap; · rw [condexp_of_not_sigmaFinite hm hμm]
haveI : SigmaFinite (μ.trim hm) := hμm
exact
condexp_of_stronglyMeasurable hm (@stronglyMeasurable_zero _ _ m _ _) (integrable_zero _ _ _)
#align measure_theory.condexp_zero MeasureTheory.condexp_zero
theorem stronglyMeasurable_condexp : StronglyMeasurable[m] (μ[f|m]) := by
by_cases hm : m ≤ m0
swap; · rw [condexp_of_not_le hm]; exact stronglyMeasurable_zero
by_cases hμm : SigmaFinite (μ.trim hm)
swap; · rw [condexp_of_not_sigmaFinite hm hμm]; exact stronglyMeasurable_zero
haveI : SigmaFinite (μ.trim hm) := hμm
rw [condexp_of_sigmaFinite hm]
split_ifs with hfi hfm
· exact hfm
· exact AEStronglyMeasurable'.stronglyMeasurable_mk _
· exact stronglyMeasurable_zero
#align measure_theory.strongly_measurable_condexp MeasureTheory.stronglyMeasurable_condexp
| Mathlib/MeasureTheory/Function/ConditionalExpectation/Basic.lean | 192 | 200 | theorem condexp_congr_ae (h : f =ᵐ[μ] g) : μ[f|m] =ᵐ[μ] μ[g|m] := by |
by_cases hm : m ≤ m0
swap; · simp_rw [condexp_of_not_le hm]; rfl
by_cases hμm : SigmaFinite (μ.trim hm)
swap; · simp_rw [condexp_of_not_sigmaFinite hm hμm]; rfl
haveI : SigmaFinite (μ.trim hm) := hμm
exact (condexp_ae_eq_condexpL1 hm f).trans
(Filter.EventuallyEq.trans (by rw [condexpL1_congr_ae hm h])
(condexp_ae_eq_condexpL1 hm g).symm)
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.RingTheory.WittVector.Frobenius
import Mathlib.RingTheory.WittVector.Verschiebung
import Mathlib.RingTheory.WittVector.MulP
#align_import ring_theory.witt_vector.identities from "leanprover-community/mathlib"@"0798037604b2d91748f9b43925fb7570a5f3256c"
/-!
## Identities between operations on the ring of Witt vectors
In this file we derive common identities between the Frobenius and Verschiebung operators.
## Main declarations
* `frobenius_verschiebung`: the composition of Frobenius and Verschiebung is multiplication by `p`
* `verschiebung_mul_frobenius`: the “projection formula”: `V(x * F y) = V x * y`
* `iterate_verschiebung_mul_coeff`: an identity from [Haze09] 6.2
## References
* [Hazewinkel, *Witt Vectors*][Haze09]
* [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21]
-/
namespace WittVector
variable {p : ℕ} {R : Type*} [hp : Fact p.Prime] [CommRing R]
-- type as `\bbW`
local notation "𝕎" => WittVector p
noncomputable section
-- Porting note: `ghost_calc` failure: `simp only []` and the manual instances had to be added.
/-- The composition of Frobenius and Verschiebung is multiplication by `p`. -/
theorem frobenius_verschiebung (x : 𝕎 R) : frobenius (verschiebung x) = x * p := by
have : IsPoly p fun {R} [CommRing R] x ↦ frobenius (verschiebung x) :=
IsPoly.comp (hg := frobenius_isPoly p) (hf := verschiebung_isPoly)
have : IsPoly p fun {R} [CommRing R] x ↦ x * p := mulN_isPoly p p
ghost_calc x
ghost_simp [mul_comm]
#align witt_vector.frobenius_verschiebung WittVector.frobenius_verschiebung
/-- Verschiebung is the same as multiplication by `p` on the ring of Witt vectors of `ZMod p`. -/
theorem verschiebung_zmod (x : 𝕎 (ZMod p)) : verschiebung x = x * p := by
rw [← frobenius_verschiebung, frobenius_zmodp]
#align witt_vector.verschiebung_zmod WittVector.verschiebung_zmod
variable (p R)
theorem coeff_p_pow [CharP R p] (i : ℕ) : ((p : 𝕎 R) ^ i).coeff i = 1 := by
induction' i with i h
· simp only [Nat.zero_eq, one_coeff_zero, Ne, pow_zero]
· rw [pow_succ, ← frobenius_verschiebung, coeff_frobenius_charP,
verschiebung_coeff_succ, h, one_pow]
#align witt_vector.coeff_p_pow WittVector.coeff_p_pow
theorem coeff_p_pow_eq_zero [CharP R p] {i j : ℕ} (hj : j ≠ i) : ((p : 𝕎 R) ^ i).coeff j = 0 := by
induction' i with i hi generalizing j
· rw [pow_zero, one_coeff_eq_of_pos]
exact Nat.pos_of_ne_zero hj
· rw [pow_succ, ← frobenius_verschiebung, coeff_frobenius_charP]
cases j
· rw [verschiebung_coeff_zero, zero_pow hp.out.ne_zero]
· rw [verschiebung_coeff_succ, hi (ne_of_apply_ne _ hj), zero_pow hp.out.ne_zero]
#align witt_vector.coeff_p_pow_eq_zero WittVector.coeff_p_pow_eq_zero
theorem coeff_p [CharP R p] (i : ℕ) : (p : 𝕎 R).coeff i = if i = 1 then 1 else 0 := by
split_ifs with hi
· simpa only [hi, pow_one] using coeff_p_pow p R 1
· simpa only [pow_one] using coeff_p_pow_eq_zero p R hi
#align witt_vector.coeff_p WittVector.coeff_p
@[simp]
theorem coeff_p_zero [CharP R p] : (p : 𝕎 R).coeff 0 = 0 := by
rw [coeff_p, if_neg]
exact zero_ne_one
#align witt_vector.coeff_p_zero WittVector.coeff_p_zero
@[simp]
| Mathlib/RingTheory/WittVector/Identities.lean | 87 | 87 | theorem coeff_p_one [CharP R p] : (p : 𝕎 R).coeff 1 = 1 := by | rw [coeff_p, if_pos rfl]
|
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris Van Doorn, Yury Kudryashov
-/
import Mathlib.Topology.MetricSpace.HausdorffDistance
import Mathlib.MeasureTheory.Constructions.BorelSpace.Order
#align_import measure_theory.measure.regular from "leanprover-community/mathlib"@"bf6a01357ff5684b1ebcd0f1a13be314fc82c0bf"
/-!
# Regular measures
A measure is `OuterRegular` if the measure of any measurable set `A` is the infimum of `μ U` over
all open sets `U` containing `A`.
A measure is `WeaklyRegular` if it satisfies the following properties:
* it is outer regular;
* it is inner regular for open sets with respect to closed sets: the measure of any open set `U`
is the supremum of `μ F` over all closed sets `F` contained in `U`.
A measure is `Regular` if it satisfies the following properties:
* it is finite on compact sets;
* it is outer regular;
* it is inner regular for open sets with respect to compacts closed sets: the measure of any open
set `U` is the supremum of `μ K` over all compact sets `K` contained in `U`.
A measure is `InnerRegular` if it is inner regular for measurable sets with respect to compact
sets: the measure of any measurable set `s` is the supremum of `μ K` over all compact
sets contained in `s`.
A measure is `InnerRegularCompactLTTop` if it is inner regular for measurable sets of finite
measure with respect to compact sets: the measure of any measurable set `s` is the supremum
of `μ K` over all compact sets contained in `s`.
There is a reason for this zoo of regularity classes:
* A finite measure on a metric space is always weakly regular. Therefore, in probability theory,
weakly regular measures play a prominent role.
* In locally compact topological spaces, there are two competing notions of Radon measures: the
ones that are regular, and the ones that are inner regular. For any of these two notions, there is
a Riesz representation theorem, and an existence and uniqueness statement for the Haar measure in
locally compact topological groups. The two notions coincide in sigma-compact spaces, but they
differ in general, so it is worth having the two of them.
* Both notions of Haar measure satisfy the weaker notion `InnerRegularCompactLTTop`, so it is worth
trying to express theorems using this weaker notion whenever possible, to make sure that it
applies to both Haar measures simultaneously.
While traditional textbooks on measure theory on locally compact spaces emphasize regular measures,
more recent textbooks emphasize that inner regular Haar measures are better behaved than regular
Haar measures, so we will develop both notions.
The five conditions above are registered as typeclasses for a measure `μ`, and implications between
them are recorded as instances. For example, in a Hausdorff topological space, regularity implies
weak regularity. Also, regularity or inner regularity both imply `InnerRegularCompactLTTop`.
In a regular locally compact finite measure space, then regularity, inner regularity
and `InnerRegularCompactLTTop` are all equivalent.
In order to avoid code duplication, we also define a measure `μ` to be `InnerRegularWRT` for sets
satisfying a predicate `q` with respect to sets satisfying a predicate `p` if for any set
`U ∈ {U | q U}` and a number `r < μ U` there exists `F ⊆ U` such that `p F` and `r < μ F`.
There are two main nontrivial results in the development below:
* `InnerRegularWRT.measurableSet_of_isOpen` shows that, for an outer regular measure, inner
regularity for open sets with respect to compact sets or closed sets implies inner regularity for
all measurable sets of finite measure (with respect to compact sets or closed sets respectively).
* `InnerRegularWRT.weaklyRegular_of_finite` shows that a finite measure which is inner regular for
open sets with respect to closed sets (for instance a finite measure on a metric space) is weakly
regular.
All other results are deduced from these ones.
Here is an example showing how regularity and inner regularity may differ even on locally compact
spaces. Consider the group `ℝ × ℝ` where the first factor has the discrete topology and the second
one the usual topology. It is a locally compact Hausdorff topological group, with Haar measure equal
to Lebesgue measure on each vertical fiber. Let us consider the regular version of Haar measure.
Then the set `ℝ × {0}` has infinite measure (by outer regularity), but any compact set it contains
has zero measure (as it is finite). In fact, this set only contains subset with measure zero or
infinity. The inner regular version of Haar measure, on the other hand, gives zero mass to the
set `ℝ × {0}`.
Another interesting example is the sum of the Dirac masses at rational points in the real line.
It is a σ-finite measure on a locally compact metric space, but it is not outer regular: for
outer regularity, one needs additional locally finite assumptions. On the other hand, it is
inner regular.
Several authors require both regularity and inner regularity for their measures. We have opted
for the more fine grained definitions above as they apply more generally.
## Main definitions
* `MeasureTheory.Measure.OuterRegular μ`: a typeclass registering that a measure `μ` on a
topological space is outer regular.
* `MeasureTheory.Measure.Regular μ`: a typeclass registering that a measure `μ` on a topological
space is regular.
* `MeasureTheory.Measure.WeaklyRegular μ`: a typeclass registering that a measure `μ` on a
topological space is weakly regular.
* `MeasureTheory.Measure.InnerRegularWRT μ p q`: a non-typeclass predicate saying that a measure `μ`
is inner regular for sets satisfying `q` with respect to sets satisfying `p`.
* `MeasureTheory.Measure.InnerRegular μ`: a typeclass registering that a measure `μ` on a
topological space is inner regular for measurable sets with respect to compact sets.
* `MeasureTheory.Measure.InnerRegularCompactLTTop μ`: a typeclass registering that a measure `μ`
on a topological space is inner regular for measurable sets of finite measure with respect to
compact sets.
## Main results
### Outer regular measures
* `Set.measure_eq_iInf_isOpen` asserts that, when `μ` is outer regular, the measure of a
set is the infimum of the measure of open sets containing it.
* `Set.exists_isOpen_lt_of_lt` asserts that, when `μ` is outer regular, for every set `s`
and `r > μ s` there exists an open superset `U ⊇ s` of measure less than `r`.
* push forward of an outer regular measure is outer regular, and scalar multiplication of a regular
measure by a finite number is outer regular.
### Weakly regular measures
* `IsOpen.measure_eq_iSup_isClosed` asserts that the measure of an open set is the supremum of
the measure of closed sets it contains.
* `IsOpen.exists_lt_isClosed`: for an open set `U` and `r < μ U`, there exists a closed `F ⊆ U`
of measure greater than `r`;
* `MeasurableSet.measure_eq_iSup_isClosed_of_ne_top` asserts that the measure of a measurable set
of finite measure is the supremum of the measure of closed sets it contains.
* `MeasurableSet.exists_lt_isClosed_of_ne_top` and `MeasurableSet.exists_isClosed_lt_add`:
a measurable set of finite measure can be approximated by a closed subset (stated as
`r < μ F` and `μ s < μ F + ε`, respectively).
* `MeasureTheory.Measure.WeaklyRegular.of_pseudoMetrizableSpace_of_isFiniteMeasure` is an
instance registering that a finite measure on a metric space is weakly regular (in fact, a pseudo
metrizable space is enough);
* `MeasureTheory.Measure.WeaklyRegular.of_pseudoMetrizableSpace_secondCountable_of_locallyFinite`
is an instance registering that a locally finite measure on a second countable metric space (or
even a pseudo metrizable space) is weakly regular.
### Regular measures
* `IsOpen.measure_eq_iSup_isCompact` asserts that the measure of an open set is the supremum of
the measure of compact sets it contains.
* `IsOpen.exists_lt_isCompact`: for an open set `U` and `r < μ U`, there exists a compact `K ⊆ U`
of measure greater than `r`;
* `MeasureTheory.Measure.Regular.of_sigmaCompactSpace_of_isLocallyFiniteMeasure` is an
instance registering that a locally finite measure on a `σ`-compact metric space is regular (in
fact, an emetric space is enough).
### Inner regular measures
* `MeasurableSet.measure_eq_iSup_isCompact` asserts that the measure of a measurable set is the
supremum of the measure of compact sets it contains.
* `MeasurableSet.exists_lt_isCompact`: for a measurable set `s` and `r < μ s`, there exists a
compact `K ⊆ s` of measure greater than `r`;
### Inner regular measures for finite measure sets with respect to compact sets
* `MeasurableSet.measure_eq_iSup_isCompact_of_ne_top` asserts that the measure of a measurable set
of finite measure is the supremum of the measure of compact sets it contains.
* `MeasurableSet.exists_lt_isCompact_of_ne_top` and `MeasurableSet.exists_isCompact_lt_add`:
a measurable set of finite measure can be approximated by a compact subset (stated as
`r < μ K` and `μ s < μ K + ε`, respectively).
## Implementation notes
The main nontrivial statement is `MeasureTheory.Measure.InnerRegular.weaklyRegular_of_finite`,
expressing that in a finite measure space, if every open set can be approximated from inside by
closed sets, then the measure is in fact weakly regular. To prove that we show that any measurable
set can be approximated from inside by closed sets and from outside by open sets. This statement is
proved by measurable induction, starting from open sets and checking that it is stable by taking
complements (this is the point of this condition, being symmetrical between inside and outside) and
countable disjoint unions.
Once this statement is proved, one deduces results for `σ`-finite measures from this statement, by
restricting them to finite measure sets (and proving that this restriction is weakly regular, using
again the same statement).
For non-Hausdorff spaces, one may argue whether the right condition for inner regularity is with
respect to compact sets, or to compact closed sets. For instance,
[Fremlin, *Measure Theory* (volume 4, 411J)][fremlin_vol4] considers measures which are inner
regular with respect to compact closed sets (and calls them *tight*). However, since most of the
literature uses mere compact sets, we have chosen to follow this convention. It doesn't make a
difference in Hausdorff spaces, of course. In locally compact topological groups, the two
conditions coincide, since if a compact set `k` is contained in a measurable set `u`, then the
closure of `k` is a compact closed set still contained in `u`, see
`IsCompact.closure_subset_of_measurableSet_of_group`.
## References
[Halmos, Measure Theory, §52][halmos1950measure]. Note that Halmos uses an unusual definition of
Borel sets (for him, they are elements of the `σ`-algebra generated by compact sets!), so his
proofs or statements do not apply directly.
[Billingsley, Convergence of Probability Measures][billingsley1999]
[Bogachev, Measure Theory, volume 2, Theorem 7.11.1][bogachev2007]
-/
open Set Filter ENNReal Topology NNReal TopologicalSpace
namespace MeasureTheory
namespace Measure
/-- We say that a measure `μ` is *inner regular* with respect to predicates `p q : Set α → Prop`,
if for every `U` such that `q U` and `r < μ U`, there exists a subset `K ⊆ U` satisfying `p K`
of measure greater than `r`.
This definition is used to prove some facts about regular and weakly regular measures without
repeating the proofs. -/
def InnerRegularWRT {α} {_ : MeasurableSpace α} (μ : Measure α) (p q : Set α → Prop) :=
∀ ⦃U⦄, q U → ∀ r < μ U, ∃ K, K ⊆ U ∧ p K ∧ r < μ K
#align measure_theory.measure.inner_regular MeasureTheory.Measure.InnerRegularWRT
namespace InnerRegularWRT
variable {α : Type*} {m : MeasurableSpace α} {μ : Measure α} {p q : Set α → Prop} {U : Set α}
{ε : ℝ≥0∞}
theorem measure_eq_iSup (H : InnerRegularWRT μ p q) (hU : q U) :
μ U = ⨆ (K) (_ : K ⊆ U) (_ : p K), μ K := by
refine
le_antisymm (le_of_forall_lt fun r hr => ?_) (iSup₂_le fun K hK => iSup_le fun _ => μ.mono hK)
simpa only [lt_iSup_iff, exists_prop] using H hU r hr
#align measure_theory.measure.inner_regular.measure_eq_supr MeasureTheory.Measure.InnerRegularWRT.measure_eq_iSup
theorem exists_subset_lt_add (H : InnerRegularWRT μ p q) (h0 : p ∅) (hU : q U) (hμU : μ U ≠ ∞)
(hε : ε ≠ 0) : ∃ K, K ⊆ U ∧ p K ∧ μ U < μ K + ε := by
rcases eq_or_ne (μ U) 0 with h₀ | h₀
· refine ⟨∅, empty_subset _, h0, ?_⟩
rwa [measure_empty, h₀, zero_add, pos_iff_ne_zero]
· rcases H hU _ (ENNReal.sub_lt_self hμU h₀ hε) with ⟨K, hKU, hKc, hrK⟩
exact ⟨K, hKU, hKc, ENNReal.lt_add_of_sub_lt_right (Or.inl hμU) hrK⟩
#align measure_theory.measure.inner_regular.exists_subset_lt_add MeasureTheory.Measure.InnerRegularWRT.exists_subset_lt_add
protected theorem map {α β} [MeasurableSpace α] [MeasurableSpace β]
{μ : Measure α} {pa qa : Set α → Prop}
(H : InnerRegularWRT μ pa qa) {f : α → β} (hf : AEMeasurable f μ) {pb qb : Set β → Prop}
(hAB : ∀ U, qb U → qa (f ⁻¹' U)) (hAB' : ∀ K, pa K → pb (f '' K))
(hB₂ : ∀ U, qb U → MeasurableSet U) :
InnerRegularWRT (map f μ) pb qb := by
intro U hU r hr
rw [map_apply_of_aemeasurable hf (hB₂ _ hU)] at hr
rcases H (hAB U hU) r hr with ⟨K, hKU, hKc, hK⟩
refine ⟨f '' K, image_subset_iff.2 hKU, hAB' _ hKc, ?_⟩
exact hK.trans_le (le_map_apply_image hf _)
#align measure_theory.measure.inner_regular.map MeasureTheory.Measure.InnerRegularWRT.map
| Mathlib/MeasureTheory/Measure/Regular.lean | 244 | 252 | theorem map' {α β} [MeasurableSpace α] [MeasurableSpace β] {μ : Measure α} {pa qa : Set α → Prop}
(H : InnerRegularWRT μ pa qa) (f : α ≃ᵐ β) {pb qb : Set β → Prop}
(hAB : ∀ U, qb U → qa (f ⁻¹' U)) (hAB' : ∀ K, pa K → pb (f '' K)) :
InnerRegularWRT (map f μ) pb qb := by |
intro U hU r hr
rw [f.map_apply U] at hr
rcases H (hAB U hU) r hr with ⟨K, hKU, hKc, hK⟩
refine ⟨f '' K, image_subset_iff.2 hKU, hAB' _ hKc, ?_⟩
rwa [f.map_apply, f.preimage_image]
|
/-
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.Function.ConditionalExpectation.CondexpL2
#align_import measure_theory.function.conditional_expectation.condexp_L1 from "leanprover-community/mathlib"@"d8bbb04e2d2a44596798a9207ceefc0fb236e41e"
/-! # Conditional expectation in L1
This file contains two more steps of the construction of the conditional expectation, which is
completed in `MeasureTheory.Function.ConditionalExpectation.Basic`. See that file for a
description of the full process.
The contitional expectation of an `L²` function is defined in
`MeasureTheory.Function.ConditionalExpectation.CondexpL2`. In this file, we perform two steps.
* Show that the conditional expectation of the indicator of a measurable set with finite measure
is integrable and define a map `Set α → (E →L[ℝ] (α →₁[μ] E))` which to a set associates a linear
map. That linear map sends `x ∈ E` to the conditional expectation of the indicator of the set
with value `x`.
* Extend that map to `condexpL1CLM : (α →₁[μ] E) →L[ℝ] (α →₁[μ] E)`. This is done using the same
construction as the Bochner integral (see the file `MeasureTheory/Integral/SetToL1`).
## Main definitions
* `condexpL1`: Conditional expectation of a function as a linear map from `L1` to itself.
-/
noncomputable section
open TopologicalSpace MeasureTheory.Lp Filter ContinuousLinearMap
open scoped NNReal ENNReal Topology MeasureTheory
namespace MeasureTheory
variable {α β F F' G G' 𝕜 : Type*} {p : ℝ≥0∞} [RCLike 𝕜]
-- 𝕜 for ℝ or ℂ
-- F for a Lp submodule
[NormedAddCommGroup F]
[NormedSpace 𝕜 F]
-- F' for integrals on a Lp submodule
[NormedAddCommGroup F']
[NormedSpace 𝕜 F'] [NormedSpace ℝ F'] [CompleteSpace F']
-- G for a Lp add_subgroup
[NormedAddCommGroup G]
-- G' for integrals on a Lp add_subgroup
[NormedAddCommGroup G']
[NormedSpace ℝ G'] [CompleteSpace G']
section CondexpInd
/-! ## Conditional expectation of an indicator as a continuous linear map.
The goal of this section is to build
`condexpInd (hm : m ≤ m0) (μ : Measure α) (s : Set s) : G →L[ℝ] α →₁[μ] G`, which
takes `x : G` to the conditional expectation of the indicator of the set `s` with value `x`,
seen as an element of `α →₁[μ] G`.
-/
variable {m m0 : MeasurableSpace α} {μ : Measure α} {s t : Set α} [NormedSpace ℝ G]
section CondexpIndL1Fin
set_option linter.uppercaseLean3 false
/-- Conditional expectation of the indicator of a measurable set with finite measure,
as a function in L1. -/
def condexpIndL1Fin (hm : m ≤ m0) [SigmaFinite (μ.trim hm)] (hs : MeasurableSet s) (hμs : μ s ≠ ∞)
(x : G) : α →₁[μ] G :=
(integrable_condexpIndSMul hm hs hμs x).toL1 _
#align measure_theory.condexp_ind_L1_fin MeasureTheory.condexpIndL1Fin
theorem condexpIndL1Fin_ae_eq_condexpIndSMul (hm : m ≤ m0) [SigmaFinite (μ.trim hm)]
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : G) :
condexpIndL1Fin hm hs hμs x =ᵐ[μ] condexpIndSMul hm hs hμs x :=
(integrable_condexpIndSMul hm hs hμs x).coeFn_toL1
#align measure_theory.condexp_ind_L1_fin_ae_eq_condexp_ind_smul MeasureTheory.condexpIndL1Fin_ae_eq_condexpIndSMul
variable {hm : m ≤ m0} [SigmaFinite (μ.trim hm)]
-- Porting note: this lemma fills the hole in `refine' (Memℒp.coeFn_toLp _) ...`
-- which is not automatically filled in Lean 4
private theorem q {hs : MeasurableSet s} {hμs : μ s ≠ ∞} {x : G} :
Memℒp (condexpIndSMul hm hs hμs x) 1 μ := by
rw [memℒp_one_iff_integrable]; apply integrable_condexpIndSMul
theorem condexpIndL1Fin_add (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x y : G) :
condexpIndL1Fin hm hs hμs (x + y) =
condexpIndL1Fin hm hs hμs x + condexpIndL1Fin hm hs hμs y := by
ext1
refine (Memℒp.coeFn_toLp q).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_add _ _).symm
refine EventuallyEq.trans ?_
(EventuallyEq.add (Memℒp.coeFn_toLp q).symm (Memℒp.coeFn_toLp q).symm)
rw [condexpIndSMul_add]
refine (Lp.coeFn_add _ _).trans (eventually_of_forall fun a => ?_)
rfl
#align measure_theory.condexp_ind_L1_fin_add MeasureTheory.condexpIndL1Fin_add
theorem condexpIndL1Fin_smul (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : ℝ) (x : G) :
condexpIndL1Fin hm hs hμs (c • x) = c • condexpIndL1Fin hm hs hμs x := by
ext1
refine (Memℒp.coeFn_toLp q).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_smul _ _).symm
rw [condexpIndSMul_smul hs hμs c x]
refine (Lp.coeFn_smul _ _).trans ?_
refine (condexpIndL1Fin_ae_eq_condexpIndSMul hm hs hμs x).mono fun y hy => ?_
simp only [Pi.smul_apply, hy]
#align measure_theory.condexp_ind_L1_fin_smul MeasureTheory.condexpIndL1Fin_smul
theorem condexpIndL1Fin_smul' [NormedSpace ℝ F] [SMulCommClass ℝ 𝕜 F] (hs : MeasurableSet s)
(hμs : μ s ≠ ∞) (c : 𝕜) (x : F) :
condexpIndL1Fin hm hs hμs (c • x) = c • condexpIndL1Fin hm hs hμs x := by
ext1
refine (Memℒp.coeFn_toLp q).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_smul _ _).symm
rw [condexpIndSMul_smul' hs hμs c x]
refine (Lp.coeFn_smul _ _).trans ?_
refine (condexpIndL1Fin_ae_eq_condexpIndSMul hm hs hμs x).mono fun y hy => ?_
simp only [Pi.smul_apply, hy]
#align measure_theory.condexp_ind_L1_fin_smul' MeasureTheory.condexpIndL1Fin_smul'
theorem norm_condexpIndL1Fin_le (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : G) :
‖condexpIndL1Fin hm hs hμs x‖ ≤ (μ s).toReal * ‖x‖ := by
have : 0 ≤ ∫ a : α, ‖condexpIndL1Fin hm hs hμs x a‖ ∂μ := by positivity
rw [L1.norm_eq_integral_norm, ← ENNReal.toReal_ofReal (norm_nonneg x), ← ENNReal.toReal_mul, ←
ENNReal.toReal_ofReal this,
ENNReal.toReal_le_toReal ENNReal.ofReal_ne_top (ENNReal.mul_ne_top hμs ENNReal.ofReal_ne_top),
ofReal_integral_norm_eq_lintegral_nnnorm]
swap; · rw [← memℒp_one_iff_integrable]; exact Lp.memℒp _
have h_eq :
∫⁻ a, ‖condexpIndL1Fin hm hs hμs x a‖₊ ∂μ = ∫⁻ a, ‖condexpIndSMul hm hs hμs x a‖₊ ∂μ := by
refine lintegral_congr_ae ?_
refine (condexpIndL1Fin_ae_eq_condexpIndSMul hm hs hμs x).mono fun z hz => ?_
dsimp only
rw [hz]
rw [h_eq, ofReal_norm_eq_coe_nnnorm]
exact lintegral_nnnorm_condexpIndSMul_le hm hs hμs x
#align measure_theory.norm_condexp_ind_L1_fin_le MeasureTheory.norm_condexpIndL1Fin_le
theorem condexpIndL1Fin_disjoint_union (hs : MeasurableSet s) (ht : MeasurableSet t) (hμs : μ s ≠ ∞)
(hμt : μ t ≠ ∞) (hst : s ∩ t = ∅) (x : G) :
condexpIndL1Fin hm (hs.union ht) ((measure_union_le s t).trans_lt
(lt_top_iff_ne_top.mpr (ENNReal.add_ne_top.mpr ⟨hμs, hμt⟩))).ne x =
condexpIndL1Fin hm hs hμs x + condexpIndL1Fin hm ht hμt x := by
ext1
have hμst :=
((measure_union_le s t).trans_lt (lt_top_iff_ne_top.mpr (ENNReal.add_ne_top.mpr ⟨hμs, hμt⟩))).ne
refine (condexpIndL1Fin_ae_eq_condexpIndSMul hm (hs.union ht) hμst x).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_add _ _).symm
have hs_eq := condexpIndL1Fin_ae_eq_condexpIndSMul hm hs hμs x
have ht_eq := condexpIndL1Fin_ae_eq_condexpIndSMul hm ht hμt x
refine EventuallyEq.trans ?_ (EventuallyEq.add hs_eq.symm ht_eq.symm)
rw [condexpIndSMul]
rw [indicatorConstLp_disjoint_union hs ht hμs hμt hst (1 : ℝ)]
rw [(condexpL2 ℝ ℝ hm).map_add]
push_cast
rw [((toSpanSingleton ℝ x).compLpL 2 μ).map_add]
refine (Lp.coeFn_add _ _).trans ?_
filter_upwards with y using rfl
#align measure_theory.condexp_ind_L1_fin_disjoint_union MeasureTheory.condexpIndL1Fin_disjoint_union
end CondexpIndL1Fin
open scoped Classical
section CondexpIndL1
set_option linter.uppercaseLean3 false
/-- Conditional expectation of the indicator of a set, as a function in L1. Its value for sets
which are not both measurable and of finite measure is not used: we set it to 0. -/
def condexpIndL1 {m m0 : MeasurableSpace α} (hm : m ≤ m0) (μ : Measure α) (s : Set α)
[SigmaFinite (μ.trim hm)] (x : G) : α →₁[μ] G :=
if hs : MeasurableSet s ∧ μ s ≠ ∞ then condexpIndL1Fin hm hs.1 hs.2 x else 0
#align measure_theory.condexp_ind_L1 MeasureTheory.condexpIndL1
variable {hm : m ≤ m0} [SigmaFinite (μ.trim hm)]
theorem condexpIndL1_of_measurableSet_of_measure_ne_top (hs : MeasurableSet s) (hμs : μ s ≠ ∞)
(x : G) : condexpIndL1 hm μ s x = condexpIndL1Fin hm hs hμs x := by
simp only [condexpIndL1, And.intro hs hμs, dif_pos, Ne, not_false_iff, and_self_iff]
#align measure_theory.condexp_ind_L1_of_measurable_set_of_measure_ne_top MeasureTheory.condexpIndL1_of_measurableSet_of_measure_ne_top
theorem condexpIndL1_of_measure_eq_top (hμs : μ s = ∞) (x : G) : condexpIndL1 hm μ s x = 0 := by
simp only [condexpIndL1, hμs, eq_self_iff_true, not_true, Ne, dif_neg, not_false_iff,
and_false_iff]
#align measure_theory.condexp_ind_L1_of_measure_eq_top MeasureTheory.condexpIndL1_of_measure_eq_top
theorem condexpIndL1_of_not_measurableSet (hs : ¬MeasurableSet s) (x : G) :
condexpIndL1 hm μ s x = 0 := by
simp only [condexpIndL1, hs, dif_neg, not_false_iff, false_and_iff]
#align measure_theory.condexp_ind_L1_of_not_measurable_set MeasureTheory.condexpIndL1_of_not_measurableSet
theorem condexpIndL1_add (x y : G) :
condexpIndL1 hm μ s (x + y) = condexpIndL1 hm μ s x + condexpIndL1 hm μ s y := by
by_cases hs : MeasurableSet s
swap; · simp_rw [condexpIndL1_of_not_measurableSet hs]; rw [zero_add]
by_cases hμs : μ s = ∞
· simp_rw [condexpIndL1_of_measure_eq_top hμs]; rw [zero_add]
· simp_rw [condexpIndL1_of_measurableSet_of_measure_ne_top hs hμs]
exact condexpIndL1Fin_add hs hμs x y
#align measure_theory.condexp_ind_L1_add MeasureTheory.condexpIndL1_add
theorem condexpIndL1_smul (c : ℝ) (x : G) :
condexpIndL1 hm μ s (c • x) = c • condexpIndL1 hm μ s x := by
by_cases hs : MeasurableSet s
swap; · simp_rw [condexpIndL1_of_not_measurableSet hs]; rw [smul_zero]
by_cases hμs : μ s = ∞
· simp_rw [condexpIndL1_of_measure_eq_top hμs]; rw [smul_zero]
· simp_rw [condexpIndL1_of_measurableSet_of_measure_ne_top hs hμs]
exact condexpIndL1Fin_smul hs hμs c x
#align measure_theory.condexp_ind_L1_smul MeasureTheory.condexpIndL1_smul
theorem condexpIndL1_smul' [NormedSpace ℝ F] [SMulCommClass ℝ 𝕜 F] (c : 𝕜) (x : F) :
condexpIndL1 hm μ s (c • x) = c • condexpIndL1 hm μ s x := by
by_cases hs : MeasurableSet s
swap; · simp_rw [condexpIndL1_of_not_measurableSet hs]; rw [smul_zero]
by_cases hμs : μ s = ∞
· simp_rw [condexpIndL1_of_measure_eq_top hμs]; rw [smul_zero]
· simp_rw [condexpIndL1_of_measurableSet_of_measure_ne_top hs hμs]
exact condexpIndL1Fin_smul' hs hμs c x
#align measure_theory.condexp_ind_L1_smul' MeasureTheory.condexpIndL1_smul'
theorem norm_condexpIndL1_le (x : G) : ‖condexpIndL1 hm μ s x‖ ≤ (μ s).toReal * ‖x‖ := by
by_cases hs : MeasurableSet s
swap
· simp_rw [condexpIndL1_of_not_measurableSet hs]; rw [Lp.norm_zero]
exact mul_nonneg ENNReal.toReal_nonneg (norm_nonneg _)
by_cases hμs : μ s = ∞
· rw [condexpIndL1_of_measure_eq_top hμs x, Lp.norm_zero]
exact mul_nonneg ENNReal.toReal_nonneg (norm_nonneg _)
· rw [condexpIndL1_of_measurableSet_of_measure_ne_top hs hμs x]
exact norm_condexpIndL1Fin_le hs hμs x
#align measure_theory.norm_condexp_ind_L1_le MeasureTheory.norm_condexpIndL1_le
theorem continuous_condexpIndL1 : Continuous fun x : G => condexpIndL1 hm μ s x :=
continuous_of_linear_of_bound condexpIndL1_add condexpIndL1_smul norm_condexpIndL1_le
#align measure_theory.continuous_condexp_ind_L1 MeasureTheory.continuous_condexpIndL1
theorem condexpIndL1_disjoint_union (hs : MeasurableSet s) (ht : MeasurableSet t) (hμs : μ s ≠ ∞)
(hμt : μ t ≠ ∞) (hst : s ∩ t = ∅) (x : G) :
condexpIndL1 hm μ (s ∪ t) x = condexpIndL1 hm μ s x + condexpIndL1 hm μ t x := by
have hμst : μ (s ∪ t) ≠ ∞ :=
((measure_union_le s t).trans_lt (lt_top_iff_ne_top.mpr (ENNReal.add_ne_top.mpr ⟨hμs, hμt⟩))).ne
rw [condexpIndL1_of_measurableSet_of_measure_ne_top hs hμs x,
condexpIndL1_of_measurableSet_of_measure_ne_top ht hμt x,
condexpIndL1_of_measurableSet_of_measure_ne_top (hs.union ht) hμst x]
exact condexpIndL1Fin_disjoint_union hs ht hμs hμt hst x
#align measure_theory.condexp_ind_L1_disjoint_union MeasureTheory.condexpIndL1_disjoint_union
end CondexpIndL1
-- Porting note: `G` is not automatically inferred in `condexpInd` in Lean 4;
-- to avoid repeatedly typing `(G := ...)` it is made explicit.
variable (G)
/-- Conditional expectation of the indicator of a set, as a linear map from `G` to L1. -/
def condexpInd {m m0 : MeasurableSpace α} (hm : m ≤ m0) (μ : Measure α) [SigmaFinite (μ.trim hm)]
(s : Set α) : G →L[ℝ] α →₁[μ] G where
toFun := condexpIndL1 hm μ s
map_add' := condexpIndL1_add
map_smul' := condexpIndL1_smul
cont := continuous_condexpIndL1
#align measure_theory.condexp_ind MeasureTheory.condexpInd
variable {G}
theorem condexpInd_ae_eq_condexpIndSMul (hm : m ≤ m0) [SigmaFinite (μ.trim hm)]
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : G) :
condexpInd G hm μ s x =ᵐ[μ] condexpIndSMul hm hs hμs x := by
refine EventuallyEq.trans ?_ (condexpIndL1Fin_ae_eq_condexpIndSMul hm hs hμs x)
simp [condexpInd, condexpIndL1, hs, hμs]
#align measure_theory.condexp_ind_ae_eq_condexp_ind_smul MeasureTheory.condexpInd_ae_eq_condexpIndSMul
variable {hm : m ≤ m0} [SigmaFinite (μ.trim hm)]
theorem aestronglyMeasurable'_condexpInd (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : G) :
AEStronglyMeasurable' m (condexpInd G hm μ s x) μ :=
AEStronglyMeasurable'.congr (aeStronglyMeasurable'_condexpIndSMul hm hs hμs x)
(condexpInd_ae_eq_condexpIndSMul hm hs hμs x).symm
#align measure_theory.ae_strongly_measurable'_condexp_ind MeasureTheory.aestronglyMeasurable'_condexpInd
@[simp]
theorem condexpInd_empty : condexpInd G hm μ ∅ = (0 : G →L[ℝ] α →₁[μ] G) := by
ext1 x
ext1
refine (condexpInd_ae_eq_condexpIndSMul hm MeasurableSet.empty (by simp) x).trans ?_
rw [condexpIndSMul_empty]
refine (Lp.coeFn_zero G 2 μ).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_zero G 1 μ).symm
rfl
#align measure_theory.condexp_ind_empty MeasureTheory.condexpInd_empty
theorem condexpInd_smul' [NormedSpace ℝ F] [SMulCommClass ℝ 𝕜 F] (c : 𝕜) (x : F) :
condexpInd F hm μ s (c • x) = c • condexpInd F hm μ s x :=
condexpIndL1_smul' c x
#align measure_theory.condexp_ind_smul' MeasureTheory.condexpInd_smul'
theorem norm_condexpInd_apply_le (x : G) : ‖condexpInd G hm μ s x‖ ≤ (μ s).toReal * ‖x‖ :=
norm_condexpIndL1_le x
#align measure_theory.norm_condexp_ind_apply_le MeasureTheory.norm_condexpInd_apply_le
theorem norm_condexpInd_le : ‖(condexpInd G hm μ s : G →L[ℝ] α →₁[μ] G)‖ ≤ (μ s).toReal :=
ContinuousLinearMap.opNorm_le_bound _ ENNReal.toReal_nonneg norm_condexpInd_apply_le
#align measure_theory.norm_condexp_ind_le MeasureTheory.norm_condexpInd_le
theorem condexpInd_disjoint_union_apply (hs : MeasurableSet s) (ht : MeasurableSet t)
(hμs : μ s ≠ ∞) (hμt : μ t ≠ ∞) (hst : s ∩ t = ∅) (x : G) :
condexpInd G hm μ (s ∪ t) x = condexpInd G hm μ s x + condexpInd G hm μ t x :=
condexpIndL1_disjoint_union hs ht hμs hμt hst x
#align measure_theory.condexp_ind_disjoint_union_apply MeasureTheory.condexpInd_disjoint_union_apply
theorem condexpInd_disjoint_union (hs : MeasurableSet s) (ht : MeasurableSet t) (hμs : μ s ≠ ∞)
(hμt : μ t ≠ ∞) (hst : s ∩ t = ∅) : (condexpInd G hm μ (s ∪ t) : G →L[ℝ] α →₁[μ] G) =
condexpInd G hm μ s + condexpInd G hm μ t := by
ext1 x; push_cast; exact condexpInd_disjoint_union_apply hs ht hμs hμt hst x
#align measure_theory.condexp_ind_disjoint_union MeasureTheory.condexpInd_disjoint_union
variable (G)
theorem dominatedFinMeasAdditive_condexpInd (hm : m ≤ m0) (μ : Measure α)
[SigmaFinite (μ.trim hm)] :
DominatedFinMeasAdditive μ (condexpInd G hm μ : Set α → G →L[ℝ] α →₁[μ] G) 1 :=
⟨fun _ _ => condexpInd_disjoint_union, fun _ _ _ => norm_condexpInd_le.trans (one_mul _).symm.le⟩
#align measure_theory.dominated_fin_meas_additive_condexp_ind MeasureTheory.dominatedFinMeasAdditive_condexpInd
variable {G}
theorem setIntegral_condexpInd (hs : MeasurableSet[m] s) (ht : MeasurableSet t) (hμs : μ s ≠ ∞)
(hμt : μ t ≠ ∞) (x : G') : ∫ a in s, condexpInd G' hm μ t x a ∂μ = (μ (t ∩ s)).toReal • x :=
calc
∫ a in s, condexpInd G' hm μ t x a ∂μ = ∫ a in s, condexpIndSMul hm ht hμt x a ∂μ :=
setIntegral_congr_ae (hm s hs)
((condexpInd_ae_eq_condexpIndSMul hm ht hμt x).mono fun _ hx _ => hx)
_ = (μ (t ∩ s)).toReal • x := setIntegral_condexpIndSMul hs ht hμs hμt x
#align measure_theory.set_integral_condexp_ind MeasureTheory.setIntegral_condexpInd
@[deprecated (since := "2024-04-17")]
alias set_integral_condexpInd := setIntegral_condexpInd
theorem condexpInd_of_measurable (hs : MeasurableSet[m] s) (hμs : μ s ≠ ∞) (c : G) :
condexpInd G hm μ s c = indicatorConstLp 1 (hm s hs) hμs c := by
ext1
refine EventuallyEq.trans ?_ indicatorConstLp_coeFn.symm
refine (condexpInd_ae_eq_condexpIndSMul hm (hm s hs) hμs c).trans ?_
refine (condexpIndSMul_ae_eq_smul hm (hm s hs) hμs c).trans ?_
rw [lpMeas_coe, condexpL2_indicator_of_measurable hm hs hμs (1 : ℝ)]
refine (@indicatorConstLp_coeFn α _ _ 2 μ _ s (hm s hs) hμs (1 : ℝ)).mono fun x hx => ?_
dsimp only
rw [hx]
by_cases hx_mem : x ∈ s <;> simp [hx_mem]
#align measure_theory.condexp_ind_of_measurable MeasureTheory.condexpInd_of_measurable
theorem condexpInd_nonneg {E} [NormedLatticeAddCommGroup E] [NormedSpace ℝ E] [OrderedSMul ℝ E]
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) (hx : 0 ≤ x) : 0 ≤ condexpInd E hm μ s x := by
rw [← coeFn_le]
refine EventuallyLE.trans_eq ?_ (condexpInd_ae_eq_condexpIndSMul hm hs hμs x).symm
exact (coeFn_zero E 1 μ).trans_le (condexpIndSMul_nonneg hs hμs x hx)
#align measure_theory.condexp_ind_nonneg MeasureTheory.condexpInd_nonneg
end CondexpInd
section CondexpL1
set_option linter.uppercaseLean3 false
variable {m m0 : MeasurableSpace α} {μ : Measure α} {hm : m ≤ m0} [SigmaFinite (μ.trim hm)]
{f g : α → F'} {s : Set α}
-- Porting note: `F'` is not automatically inferred in `condexpL1CLM` in Lean 4;
-- to avoid repeatedly typing `(F' := ...)` it is made explicit.
variable (F')
/-- Conditional expectation of a function as a linear map from `α →₁[μ] F'` to itself. -/
def condexpL1CLM (hm : m ≤ m0) (μ : Measure α) [SigmaFinite (μ.trim hm)] :
(α →₁[μ] F') →L[ℝ] α →₁[μ] F' :=
L1.setToL1 (dominatedFinMeasAdditive_condexpInd F' hm μ)
#align measure_theory.condexp_L1_clm MeasureTheory.condexpL1CLM
variable {F'}
theorem condexpL1CLM_smul (c : 𝕜) (f : α →₁[μ] F') :
condexpL1CLM F' hm μ (c • f) = c • condexpL1CLM F' hm μ f := by
refine L1.setToL1_smul (dominatedFinMeasAdditive_condexpInd F' hm μ) ?_ c f
exact fun c s x => condexpInd_smul' c x
#align measure_theory.condexp_L1_clm_smul MeasureTheory.condexpL1CLM_smul
theorem condexpL1CLM_indicatorConstLp (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : F') :
(condexpL1CLM F' hm μ) (indicatorConstLp 1 hs hμs x) = condexpInd F' hm μ s x :=
L1.setToL1_indicatorConstLp (dominatedFinMeasAdditive_condexpInd F' hm μ) hs hμs x
#align measure_theory.condexp_L1_clm_indicator_const_Lp MeasureTheory.condexpL1CLM_indicatorConstLp
theorem condexpL1CLM_indicatorConst (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : F') :
(condexpL1CLM F' hm μ) ↑(simpleFunc.indicatorConst 1 hs hμs x) = condexpInd F' hm μ s x := by
rw [Lp.simpleFunc.coe_indicatorConst]; exact condexpL1CLM_indicatorConstLp hs hμs x
#align measure_theory.condexp_L1_clm_indicator_const MeasureTheory.condexpL1CLM_indicatorConst
/-- Auxiliary lemma used in the proof of `setIntegral_condexpL1CLM`. -/
theorem setIntegral_condexpL1CLM_of_measure_ne_top (f : α →₁[μ] F') (hs : MeasurableSet[m] s)
(hμs : μ s ≠ ∞) : ∫ x in s, condexpL1CLM F' hm μ f x ∂μ = ∫ x in s, f x ∂μ := by
refine @Lp.induction _ _ _ _ _ _ _ ENNReal.one_ne_top
(fun f : α →₁[μ] F' => ∫ x in s, condexpL1CLM F' hm μ f x ∂μ = ∫ x in s, f x ∂μ) ?_ ?_
(isClosed_eq ?_ ?_) f
· intro x t ht hμt
simp_rw [condexpL1CLM_indicatorConst ht hμt.ne x]
rw [Lp.simpleFunc.coe_indicatorConst, setIntegral_indicatorConstLp (hm _ hs)]
exact setIntegral_condexpInd hs ht hμs hμt.ne x
· intro f g hf_Lp hg_Lp _ hf hg
simp_rw [(condexpL1CLM F' hm μ).map_add]
rw [setIntegral_congr_ae (hm s hs) ((Lp.coeFn_add (condexpL1CLM F' hm μ (hf_Lp.toLp f))
(condexpL1CLM F' hm μ (hg_Lp.toLp g))).mono fun x hx _ => hx)]
rw [setIntegral_congr_ae (hm s hs)
((Lp.coeFn_add (hf_Lp.toLp f) (hg_Lp.toLp g)).mono fun x hx _ => hx)]
simp_rw [Pi.add_apply]
rw [integral_add (L1.integrable_coeFn _).integrableOn (L1.integrable_coeFn _).integrableOn,
integral_add (L1.integrable_coeFn _).integrableOn (L1.integrable_coeFn _).integrableOn, hf,
hg]
· exact (continuous_setIntegral s).comp (condexpL1CLM F' hm μ).continuous
· exact continuous_setIntegral s
#align measure_theory.set_integral_condexp_L1_clm_of_measure_ne_top MeasureTheory.setIntegral_condexpL1CLM_of_measure_ne_top
@[deprecated (since := "2024-04-17")]
alias set_integral_condexpL1CLM_of_measure_ne_top :=
setIntegral_condexpL1CLM_of_measure_ne_top
/-- The integral of the conditional expectation `condexpL1CLM` over an `m`-measurable set is equal
to the integral of `f` on that set. See also `setIntegral_condexp`, the similar statement for
`condexp`. -/
theorem setIntegral_condexpL1CLM (f : α →₁[μ] F') (hs : MeasurableSet[m] s) :
∫ x in s, condexpL1CLM F' hm μ f x ∂μ = ∫ x in s, f x ∂μ := by
let S := spanningSets (μ.trim hm)
have hS_meas : ∀ i, MeasurableSet[m] (S i) := measurable_spanningSets (μ.trim hm)
have hS_meas0 : ∀ i, MeasurableSet (S i) := fun i => hm _ (hS_meas i)
have hs_eq : s = ⋃ i, S i ∩ s := by
simp_rw [Set.inter_comm]
rw [← Set.inter_iUnion, iUnion_spanningSets (μ.trim hm), Set.inter_univ]
have hS_finite : ∀ i, μ (S i ∩ s) < ∞ := by
refine fun i => (measure_mono Set.inter_subset_left).trans_lt ?_
have hS_finite_trim := measure_spanningSets_lt_top (μ.trim hm) i
rwa [trim_measurableSet_eq hm (hS_meas i)] at hS_finite_trim
have h_mono : Monotone fun i => S i ∩ s := by
intro i j hij x
simp_rw [Set.mem_inter_iff]
exact fun h => ⟨monotone_spanningSets (μ.trim hm) hij h.1, h.2⟩
have h_eq_forall :
(fun i => ∫ x in S i ∩ s, condexpL1CLM F' hm μ f x ∂μ) = fun i => ∫ x in S i ∩ s, f x ∂μ :=
funext fun i =>
setIntegral_condexpL1CLM_of_measure_ne_top f (@MeasurableSet.inter α m _ _ (hS_meas i) hs)
(hS_finite i).ne
have h_right : Tendsto (fun i => ∫ x in S i ∩ s, f x ∂μ) atTop (𝓝 (∫ x in s, f x ∂μ)) := by
have h :=
tendsto_setIntegral_of_monotone (fun i => (hS_meas0 i).inter (hm s hs)) h_mono
(L1.integrable_coeFn f).integrableOn
rwa [← hs_eq] at h
have h_left : Tendsto (fun i => ∫ x in S i ∩ s, condexpL1CLM F' hm μ f x ∂μ) atTop
(𝓝 (∫ x in s, condexpL1CLM F' hm μ f x ∂μ)) := by
have h := tendsto_setIntegral_of_monotone (fun i => (hS_meas0 i).inter (hm s hs)) h_mono
(L1.integrable_coeFn (condexpL1CLM F' hm μ f)).integrableOn
rwa [← hs_eq] at h
rw [h_eq_forall] at h_left
exact tendsto_nhds_unique h_left h_right
#align measure_theory.set_integral_condexp_L1_clm MeasureTheory.setIntegral_condexpL1CLM
@[deprecated (since := "2024-04-17")]
alias set_integral_condexpL1CLM := setIntegral_condexpL1CLM
| Mathlib/MeasureTheory/Function/ConditionalExpectation/CondexpL1.lean | 473 | 488 | theorem aestronglyMeasurable'_condexpL1CLM (f : α →₁[μ] F') :
AEStronglyMeasurable' m (condexpL1CLM F' hm μ f) μ := by |
refine @Lp.induction _ _ _ _ _ _ _ ENNReal.one_ne_top
(fun f : α →₁[μ] F' => AEStronglyMeasurable' m (condexpL1CLM F' hm μ f) μ) ?_ ?_ ?_ f
· intro c s hs hμs
rw [condexpL1CLM_indicatorConst hs hμs.ne c]
exact aestronglyMeasurable'_condexpInd hs hμs.ne c
· intro f g hf hg _ hfm hgm
rw [(condexpL1CLM F' hm μ).map_add]
refine AEStronglyMeasurable'.congr ?_ (coeFn_add _ _).symm
exact AEStronglyMeasurable'.add hfm hgm
· have : {f : Lp F' 1 μ | AEStronglyMeasurable' m (condexpL1CLM F' hm μ f) μ} =
condexpL1CLM F' hm μ ⁻¹' {f | AEStronglyMeasurable' m f μ} := rfl
rw [this]
refine IsClosed.preimage (condexpL1CLM F' hm μ).continuous ?_
exact isClosed_aeStronglyMeasurable' hm
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.RingTheory.WittVector.Frobenius
import Mathlib.RingTheory.WittVector.Verschiebung
import Mathlib.RingTheory.WittVector.MulP
#align_import ring_theory.witt_vector.identities from "leanprover-community/mathlib"@"0798037604b2d91748f9b43925fb7570a5f3256c"
/-!
## Identities between operations on the ring of Witt vectors
In this file we derive common identities between the Frobenius and Verschiebung operators.
## Main declarations
* `frobenius_verschiebung`: the composition of Frobenius and Verschiebung is multiplication by `p`
* `verschiebung_mul_frobenius`: the “projection formula”: `V(x * F y) = V x * y`
* `iterate_verschiebung_mul_coeff`: an identity from [Haze09] 6.2
## References
* [Hazewinkel, *Witt Vectors*][Haze09]
* [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21]
-/
namespace WittVector
variable {p : ℕ} {R : Type*} [hp : Fact p.Prime] [CommRing R]
-- type as `\bbW`
local notation "𝕎" => WittVector p
noncomputable section
-- Porting note: `ghost_calc` failure: `simp only []` and the manual instances had to be added.
/-- The composition of Frobenius and Verschiebung is multiplication by `p`. -/
| Mathlib/RingTheory/WittVector/Identities.lean | 42 | 47 | theorem frobenius_verschiebung (x : 𝕎 R) : frobenius (verschiebung x) = x * p := by |
have : IsPoly p fun {R} [CommRing R] x ↦ frobenius (verschiebung x) :=
IsPoly.comp (hg := frobenius_isPoly p) (hf := verschiebung_isPoly)
have : IsPoly p fun {R} [CommRing R] x ↦ x * p := mulN_isPoly p p
ghost_calc x
ghost_simp [mul_comm]
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Data.Rat.Cast.Defs
import Mathlib.Algebra.Field.Basic
#align_import data.rat.cast from "leanprover-community/mathlib"@"acebd8d49928f6ed8920e502a6c90674e75bd441"
/-!
# Some exiled lemmas about casting
These lemmas have been removed from `Mathlib.Data.Rat.Cast.Defs`
to avoiding needing to import `Mathlib.Algebra.Field.Basic` there.
In fact, these lemmas don't appear to be used anywhere in Mathlib,
so perhaps this file can simply be deleted.
-/
namespace Rat
variable {α : Type*} [DivisionRing α]
-- Porting note: rewrote proof
@[simp]
theorem cast_inv_nat (n : ℕ) : ((n⁻¹ : ℚ) : α) = (n : α)⁻¹ := by
cases' n with n
· simp
rw [cast_def, inv_natCast_num, inv_natCast_den, if_neg n.succ_ne_zero,
Int.sign_eq_one_of_pos (Nat.cast_pos.mpr n.succ_pos), Int.cast_one, one_div]
#align rat.cast_inv_nat Rat.cast_inv_nat
-- Porting note: proof got a lot easier - is this still the intended statement?
@[simp]
| Mathlib/Data/Rat/Cast/Lemmas.lean | 37 | 40 | theorem cast_inv_int (n : ℤ) : ((n⁻¹ : ℚ) : α) = (n : α)⁻¹ := by |
cases' n with n n
· simp [ofInt_eq_cast, cast_inv_nat]
· simp only [ofInt_eq_cast, Int.cast_negSucc, ← Nat.cast_succ, cast_neg, inv_neg, cast_inv_nat]
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Thomas Browning, Patrick Lutz
-/
import Mathlib.FieldTheory.Extension
import Mathlib.FieldTheory.SplittingField.Construction
import Mathlib.GroupTheory.Solvable
#align_import field_theory.normal from "leanprover-community/mathlib"@"9fb8964792b4237dac6200193a0d533f1b3f7423"
/-!
# Normal field extensions
In this file we define normal field extensions and prove that for a finite extension, being normal
is the same as being a splitting field (`Normal.of_isSplittingField` and
`Normal.exists_isSplittingField`).
## Main Definitions
- `Normal F K` where `K` is a field extension of `F`.
-/
noncomputable section
open scoped Classical Polynomial
open Polynomial IsScalarTower
variable (F K : Type*) [Field F] [Field K] [Algebra F K]
/-- Typeclass for normal field extension: `K` is a normal extension of `F` iff the minimal
polynomial of every element `x` in `K` splits in `K`, i.e. every conjugate of `x` is in `K`. -/
class Normal extends Algebra.IsAlgebraic F K : Prop where
splits' (x : K) : Splits (algebraMap F K) (minpoly F x)
#align normal Normal
variable {F K}
theorem Normal.isIntegral (_ : Normal F K) (x : K) : IsIntegral F x :=
Algebra.IsIntegral.isIntegral x
#align normal.is_integral Normal.isIntegral
theorem Normal.splits (_ : Normal F K) (x : K) : Splits (algebraMap F K) (minpoly F x) :=
Normal.splits' x
#align normal.splits Normal.splits
theorem normal_iff : Normal F K ↔ ∀ x : K, IsIntegral F x ∧ Splits (algebraMap F K) (minpoly F x) :=
⟨fun h x => ⟨h.isIntegral x, h.splits x⟩, fun h =>
{ isAlgebraic := fun x => (h x).1.isAlgebraic
splits' := fun x => (h x).2 }⟩
#align normal_iff normal_iff
theorem Normal.out : Normal F K → ∀ x : K, IsIntegral F x ∧ Splits (algebraMap F K) (minpoly F x) :=
normal_iff.1
#align normal.out Normal.out
variable (F K)
instance normal_self : Normal F F where
isAlgebraic := fun _ => isIntegral_algebraMap.isAlgebraic
splits' := fun x => (minpoly.eq_X_sub_C' x).symm ▸ splits_X_sub_C _
#align normal_self normal_self
theorem Normal.exists_isSplittingField [h : Normal F K] [FiniteDimensional F K] :
∃ p : F[X], IsSplittingField F K p := by
let s := Basis.ofVectorSpace F K
refine
⟨∏ x, minpoly F (s x), splits_prod _ fun x _ => h.splits (s x),
Subalgebra.toSubmodule.injective ?_⟩
rw [Algebra.top_toSubmodule, eq_top_iff, ← s.span_eq, Submodule.span_le, Set.range_subset_iff]
refine fun x =>
Algebra.subset_adjoin
(Multiset.mem_toFinset.mpr <|
(mem_roots <|
mt (Polynomial.map_eq_zero <| algebraMap F K).1 <|
Finset.prod_ne_zero_iff.2 fun x _ => ?_).2 ?_)
· exact minpoly.ne_zero (h.isIntegral (s x))
rw [IsRoot.def, eval_map, ← aeval_def, AlgHom.map_prod]
exact Finset.prod_eq_zero (Finset.mem_univ _) (minpoly.aeval _ _)
#align normal.exists_is_splitting_field Normal.exists_isSplittingField
section NormalTower
variable (E : Type*) [Field E] [Algebra F E] [Algebra K E] [IsScalarTower F K E]
theorem Normal.tower_top_of_normal [h : Normal F E] : Normal K E :=
normal_iff.2 fun x => by
cases' h.out x with hx hhx
rw [algebraMap_eq F K E] at hhx
exact
⟨hx.tower_top,
Polynomial.splits_of_splits_of_dvd (algebraMap K E)
(Polynomial.map_ne_zero (minpoly.ne_zero hx))
((Polynomial.splits_map_iff (algebraMap F K) (algebraMap K E)).mpr hhx)
(minpoly.dvd_map_of_isScalarTower F K x)⟩
#align normal.tower_top_of_normal Normal.tower_top_of_normal
theorem AlgHom.normal_bijective [h : Normal F E] (ϕ : E →ₐ[F] K) : Function.Bijective ϕ :=
h.toIsAlgebraic.bijective_of_isScalarTower' ϕ
#align alg_hom.normal_bijective AlgHom.normal_bijective
-- Porting note: `[Field F] [Field E] [Algebra F E]` added by hand.
variable {F E} {E' : Type*} [Field F] [Field E] [Algebra F E] [Field E'] [Algebra F E']
theorem Normal.of_algEquiv [h : Normal F E] (f : E ≃ₐ[F] E') : Normal F E' := by
rw [normal_iff] at h ⊢
intro x; specialize h (f.symm x)
rw [← f.apply_symm_apply x, minpoly.algEquiv_eq, ← f.toAlgHom.comp_algebraMap]
exact ⟨h.1.map f, splits_comp_of_splits _ _ h.2⟩
#align normal.of_alg_equiv Normal.of_algEquiv
theorem AlgEquiv.transfer_normal (f : E ≃ₐ[F] E') : Normal F E ↔ Normal F E' :=
⟨fun _ ↦ Normal.of_algEquiv f, fun _ ↦ Normal.of_algEquiv f.symm⟩
#align alg_equiv.transfer_normal AlgEquiv.transfer_normal
open IntermediateField
theorem Normal.of_isSplittingField (p : F[X]) [hFEp : IsSplittingField F E p] : Normal F E := by
rcases eq_or_ne p 0 with (rfl | hp)
· have := hFEp.adjoin_rootSet
rw [rootSet_zero, Algebra.adjoin_empty] at this
exact Normal.of_algEquiv
(AlgEquiv.ofBijective (Algebra.ofId F E) (Algebra.bijective_algebraMap_iff.2 this.symm))
refine normal_iff.mpr fun x ↦ ?_
haveI : FiniteDimensional F E := IsSplittingField.finiteDimensional E p
have hx := IsIntegral.of_finite F x
let L := (p * minpoly F x).SplittingField
have hL := splits_of_splits_mul' _ ?_ (SplittingField.splits (p * minpoly F x))
· let j : E →ₐ[F] L := IsSplittingField.lift E p hL.1
refine ⟨hx, splits_of_comp _ (j : E →+* L) (j.comp_algebraMap ▸ hL.2) fun a ha ↦ ?_⟩
rw [j.comp_algebraMap] at ha
letI : Algebra F⟮x⟯ L := ((algHomAdjoinIntegralEquiv F hx).symm ⟨a, ha⟩).toRingHom.toAlgebra
let j' : E →ₐ[F⟮x⟯] L := IsSplittingField.lift E (p.map (algebraMap F F⟮x⟯)) ?_
· change a ∈ j.range
rw [← IsSplittingField.adjoin_rootSet_eq_range E p j,
IsSplittingField.adjoin_rootSet_eq_range E p (j'.restrictScalars F)]
exact ⟨x, (j'.commutes _).trans (algHomAdjoinIntegralEquiv_symm_apply_gen F hx _)⟩
· rw [splits_map_iff, ← IsScalarTower.algebraMap_eq]; exact hL.1
· rw [Polynomial.map_ne_zero_iff (algebraMap F L).injective, mul_ne_zero_iff]
exact ⟨hp, minpoly.ne_zero hx⟩
#align normal.of_is_splitting_field Normal.of_isSplittingField
instance Polynomial.SplittingField.instNormal (p : F[X]) : Normal F p.SplittingField :=
Normal.of_isSplittingField p
#align polynomial.splitting_field.normal Polynomial.SplittingField.instNormal
end NormalTower
namespace IntermediateField
/-- A compositum of normal extensions is normal -/
instance normal_iSup {ι : Type*} (t : ι → IntermediateField F K) [h : ∀ i, Normal F (t i)] :
Normal F (⨆ i, t i : IntermediateField F K) := by
refine { toIsAlgebraic := isAlgebraic_iSup fun i => (h i).1, splits' := fun x => ?_ }
obtain ⟨s, hx⟩ := exists_finset_of_mem_supr'' (fun i => (h i).1) x.2
let E : IntermediateField F K := ⨆ i ∈ s, adjoin F ((minpoly F (i.2 : _)).rootSet K)
have hF : Normal F E := by
haveI : IsSplittingField F E (∏ i ∈ s, minpoly F i.snd) := by
refine isSplittingField_iSup ?_ fun i _ => adjoin_rootSet_isSplittingField ?_
· exact Finset.prod_ne_zero_iff.mpr fun i _ => minpoly.ne_zero ((h i.1).isIntegral i.2)
· exact Polynomial.splits_comp_of_splits _ (algebraMap (t i.1) K) ((h i.1).splits i.2)
apply Normal.of_isSplittingField (∏ i ∈ s, minpoly F i.2)
have hE : E ≤ ⨆ i, t i := by
refine iSup_le fun i => iSup_le fun _ => le_iSup_of_le i.1 ?_
rw [adjoin_le_iff, ← image_rootSet ((h i.1).splits i.2) (t i.1).val]
exact fun _ ⟨a, _, h⟩ => h ▸ a.2
have := hF.splits ⟨x, hx⟩
rw [minpoly_eq, Subtype.coe_mk, ← minpoly_eq] at this
exact Polynomial.splits_comp_of_splits _ (inclusion hE).toRingHom this
#align intermediate_field.normal_supr IntermediateField.normal_iSup
/-- If a set of algebraic elements in a field extension `K/F` have minimal polynomials that
split in another extension `L/F`, then all minimal polynomials in the intermediate field
generated by the set also split in `L/F`. -/
theorem splits_of_mem_adjoin {L} [Field L] [Algebra F L] {S : Set K}
(splits : ∀ x ∈ S, IsIntegral F x ∧ (minpoly F x).Splits (algebraMap F L)) {x : K}
(hx : x ∈ adjoin F S) : (minpoly F x).Splits (algebraMap F L) := by
let E : IntermediateField F L := ⨆ x : S, adjoin F ((minpoly F x.val).rootSet L)
have normal : Normal F E := normal_iSup (h := fun x ↦
Normal.of_isSplittingField (hFEp := adjoin_rootSet_isSplittingField (splits x x.2).2))
have : ∀ x ∈ S, (minpoly F x).Splits (algebraMap F E) := fun x hx ↦ splits_of_splits
(splits x hx).2 fun y hy ↦ (le_iSup _ ⟨x, hx⟩ : _ ≤ E) (subset_adjoin F _ <| by exact hy)
obtain ⟨φ⟩ := nonempty_algHom_adjoin_of_splits fun x hx ↦ ⟨(splits x hx).1, this x hx⟩
convert splits_comp_of_splits _ E.val.toRingHom (normal.splits <| φ ⟨x, hx⟩)
rw [minpoly.algHom_eq _ φ.injective, ← minpoly.algHom_eq _ (adjoin F S).val.injective, val_mk]
instance normal_sup
(E E' : IntermediateField F K) [Normal F E] [Normal F E'] :
Normal F (E ⊔ E' : IntermediateField F K) :=
iSup_bool_eq (f := Bool.rec E' E) ▸ normal_iSup (h := by rintro (_|_) <;> infer_instance)
-- Porting note `[Field F] [Field K] [Algebra F K]` added by hand.
variable {F K} {L : Type*} [Field F] [Field K] [Field L] [Algebra F L] [Algebra K L]
[Algebra F K] [IsScalarTower F K L]
@[simp]
theorem restrictScalars_normal {E : IntermediateField K L} :
Normal F (E.restrictScalars F) ↔ Normal F E :=
Iff.rfl
#align intermediate_field.restrict_scalars_normal IntermediateField.restrictScalars_normal
end IntermediateField
-- Porting note `[Field F]` added by hand.
variable {F} {K} {K₁ K₂ K₃ : Type*} [Field F] [Field K₁] [Field K₂] [Field K₃] [Algebra F K₁]
[Algebra F K₂] [Algebra F K₃] (ϕ : K₁ →ₐ[F] K₂) (χ : K₁ ≃ₐ[F] K₂) (ψ : K₂ →ₐ[F] K₃)
(ω : K₂ ≃ₐ[F] K₃)
section Restrict
variable (E : Type*) [Field E] [Algebra F E] [Algebra E K₁] [Algebra E K₂] [Algebra E K₃]
[IsScalarTower F E K₁] [IsScalarTower F E K₂] [IsScalarTower F E K₃]
/-- Restrict algebra homomorphism to image of normal subfield -/
def AlgHom.restrictNormalAux [h : Normal F E] :
(toAlgHom F E K₁).range →ₐ[F] (toAlgHom F E K₂).range where
toFun x :=
⟨ϕ x, by
suffices (toAlgHom F E K₁).range.map ϕ ≤ _ by exact this ⟨x, Subtype.mem x, rfl⟩
rintro x ⟨y, ⟨z, hy⟩, hx⟩
rw [← hx, ← hy]
apply minpoly.mem_range_of_degree_eq_one E
refine
Or.resolve_left (h.splits z).def (minpoly.ne_zero (h.isIntegral z)) (minpoly.irreducible ?_)
(minpoly.dvd E _ (by simp [aeval_algHom_apply]))
simp only [AlgHom.toRingHom_eq_coe, AlgHom.coe_toRingHom]
suffices IsIntegral F _ by exact this.tower_top
exact ((h.isIntegral z).map <| toAlgHom F E K₁).map ϕ⟩
map_zero' := Subtype.ext ϕ.map_zero
map_one' := Subtype.ext ϕ.map_one
map_add' x y := Subtype.ext (ϕ.map_add x y)
map_mul' x y := Subtype.ext (ϕ.map_mul x y)
commutes' x := Subtype.ext (ϕ.commutes x)
#align alg_hom.restrict_normal_aux AlgHom.restrictNormalAux
/-- Restrict algebra homomorphism to normal subfield -/
def AlgHom.restrictNormal [Normal F E] : E →ₐ[F] E :=
((AlgEquiv.ofInjectiveField (IsScalarTower.toAlgHom F E K₂)).symm.toAlgHom.comp
(ϕ.restrictNormalAux E)).comp
(AlgEquiv.ofInjectiveField (IsScalarTower.toAlgHom F E K₁)).toAlgHom
#align alg_hom.restrict_normal AlgHom.restrictNormal
/-- Restrict algebra homomorphism to normal subfield (`AlgEquiv` version) -/
def AlgHom.restrictNormal' [Normal F E] : E ≃ₐ[F] E :=
AlgEquiv.ofBijective (AlgHom.restrictNormal ϕ E) (AlgHom.normal_bijective F E E _)
#align alg_hom.restrict_normal' AlgHom.restrictNormal'
@[simp]
theorem AlgHom.restrictNormal_commutes [Normal F E] (x : E) :
algebraMap E K₂ (ϕ.restrictNormal E x) = ϕ (algebraMap E K₁ x) :=
Subtype.ext_iff.mp
(AlgEquiv.apply_symm_apply (AlgEquiv.ofInjectiveField (IsScalarTower.toAlgHom F E K₂))
(ϕ.restrictNormalAux E ⟨IsScalarTower.toAlgHom F E K₁ x, x, rfl⟩))
#align alg_hom.restrict_normal_commutes AlgHom.restrictNormal_commutes
theorem AlgHom.restrictNormal_comp [Normal F E] :
(ψ.restrictNormal E).comp (ϕ.restrictNormal E) = (ψ.comp ϕ).restrictNormal E :=
AlgHom.ext fun _ =>
(algebraMap E K₃).injective (by simp only [AlgHom.comp_apply, AlgHom.restrictNormal_commutes])
#align alg_hom.restrict_normal_comp AlgHom.restrictNormal_comp
-- Porting note `[Algebra F K]` added by hand.
theorem AlgHom.fieldRange_of_normal [Algebra F K] {E : IntermediateField F K} [Normal F E]
(f : E →ₐ[F] K) : f.fieldRange = E := by
-- Porting note: this was `IsScalarTower F E E := by infer_instance`.
letI : Algebra E E := Algebra.id E
let g := f.restrictNormal' E
rw [← show E.val.comp ↑g = f from DFunLike.ext_iff.mpr (f.restrictNormal_commutes E),
← AlgHom.map_fieldRange, AlgEquiv.fieldRange_eq_top g, ← AlgHom.fieldRange_eq_map,
IntermediateField.fieldRange_val]
#align alg_hom.field_range_of_normal AlgHom.fieldRange_of_normal
/-- Restrict algebra isomorphism to a normal subfield -/
def AlgEquiv.restrictNormal [Normal F E] : E ≃ₐ[F] E :=
AlgHom.restrictNormal' χ.toAlgHom E
#align alg_equiv.restrict_normal AlgEquiv.restrictNormal
@[simp]
theorem AlgEquiv.restrictNormal_commutes [Normal F E] (x : E) :
algebraMap E K₂ (χ.restrictNormal E x) = χ (algebraMap E K₁ x) :=
χ.toAlgHom.restrictNormal_commutes E x
#align alg_equiv.restrict_normal_commutes AlgEquiv.restrictNormal_commutes
theorem AlgEquiv.restrictNormal_trans [Normal F E] :
(χ.trans ω).restrictNormal E = (χ.restrictNormal E).trans (ω.restrictNormal E) :=
AlgEquiv.ext fun _ =>
(algebraMap E K₃).injective
(by simp only [AlgEquiv.trans_apply, AlgEquiv.restrictNormal_commutes])
#align alg_equiv.restrict_normal_trans AlgEquiv.restrictNormal_trans
/-- Restriction to a normal subfield as a group homomorphism -/
def AlgEquiv.restrictNormalHom [Normal F E] : (K₁ ≃ₐ[F] K₁) →* E ≃ₐ[F] E :=
MonoidHom.mk' (fun χ => χ.restrictNormal E) fun ω χ => χ.restrictNormal_trans ω E
#align alg_equiv.restrict_normal_hom AlgEquiv.restrictNormalHom
variable (F K₁)
/-- If `K₁/E/F` is a tower of fields with `E/F` normal then `AlgHom.restrictNormal'` is an
equivalence. -/
@[simps]
def Normal.algHomEquivAut [Normal F E] : (E →ₐ[F] K₁) ≃ E ≃ₐ[F] E where
toFun σ := AlgHom.restrictNormal' σ E
invFun σ := (IsScalarTower.toAlgHom F E K₁).comp σ.toAlgHom
left_inv σ := by
ext
simp [AlgHom.restrictNormal']
right_inv σ := by
ext
simp only [AlgHom.restrictNormal', AlgEquiv.toAlgHom_eq_coe, AlgEquiv.coe_ofBijective]
apply NoZeroSMulDivisors.algebraMap_injective E K₁
rw [AlgHom.restrictNormal_commutes]
simp
#align normal.alg_hom_equiv_aut Normal.algHomEquivAut
end Restrict
section lift
variable (E : Type*) [Field E] [Algebra F E] [Algebra K₁ E] [Algebra K₂ E] [IsScalarTower F K₁ E]
[IsScalarTower F K₂ E]
/-- If `E/Kᵢ/F` are towers of fields with `E/F` normal then we can lift
an algebra homomorphism `ϕ : K₁ →ₐ[F] K₂` to `ϕ.liftNormal E : E →ₐ[F] E`. -/
noncomputable def AlgHom.liftNormal [h : Normal F E] : E →ₐ[F] E :=
@AlgHom.restrictScalars F K₁ E E _ _ _ _ _ _
((IsScalarTower.toAlgHom F K₂ E).comp ϕ).toRingHom.toAlgebra _ _ _ _ <|
Nonempty.some <|
@IntermediateField.nonempty_algHom_of_adjoin_splits _ _ _ _ _ _ _
((IsScalarTower.toAlgHom F K₂ E).comp ϕ).toRingHom.toAlgebra _
(fun x _ ↦ ⟨(h.out x).1.tower_top,
splits_of_splits_of_dvd _ (map_ne_zero (minpoly.ne_zero (h.out x).1))
-- Porting note: had to override typeclass inference below using `(_)`
(by rw [splits_map_iff, ← @IsScalarTower.algebraMap_eq _ _ _ _ _ _ (_) (_) (_)];
exact (h.out x).2)
(minpoly.dvd_map_of_isScalarTower F K₁ x)⟩)
(IntermediateField.adjoin_univ _ _)
#align alg_hom.lift_normal AlgHom.liftNormal
@[simp]
theorem AlgHom.liftNormal_commutes [Normal F E] (x : K₁) :
ϕ.liftNormal E (algebraMap K₁ E x) = algebraMap K₂ E (ϕ x) :=
-- Porting note: This seems to have been some sort of typeclass override trickery using `by apply`
-- Now we explicitly specify which typeclass to override, using `(_)` instead of `_`
@AlgHom.commutes K₁ E E _ _ _ _ (_) _ _
#align alg_hom.lift_normal_commutes AlgHom.liftNormal_commutes
@[simp]
theorem AlgHom.restrict_liftNormal (ϕ : K₁ →ₐ[F] K₁) [Normal F K₁] [Normal F E] :
(ϕ.liftNormal E).restrictNormal K₁ = ϕ :=
AlgHom.ext fun x =>
(algebraMap K₁ E).injective
(Eq.trans (AlgHom.restrictNormal_commutes _ K₁ x) (ϕ.liftNormal_commutes E x))
#align alg_hom.restrict_lift_normal AlgHom.restrict_liftNormal
/-- If `E/Kᵢ/F` are towers of fields with `E/F` normal then we can lift
an algebra isomorphism `ϕ : K₁ ≃ₐ[F] K₂` to `ϕ.liftNormal E : E ≃ₐ[F] E`. -/
noncomputable def AlgEquiv.liftNormal [Normal F E] : E ≃ₐ[F] E :=
AlgEquiv.ofBijective (χ.toAlgHom.liftNormal E) (AlgHom.normal_bijective F E E _)
#align alg_equiv.lift_normal AlgEquiv.liftNormal
@[simp]
theorem AlgEquiv.liftNormal_commutes [Normal F E] (x : K₁) :
χ.liftNormal E (algebraMap K₁ E x) = algebraMap K₂ E (χ x) :=
χ.toAlgHom.liftNormal_commutes E x
#align alg_equiv.lift_normal_commutes AlgEquiv.liftNormal_commutes
@[simp]
theorem AlgEquiv.restrict_liftNormal (χ : K₁ ≃ₐ[F] K₁) [Normal F K₁] [Normal F E] :
(χ.liftNormal E).restrictNormal K₁ = χ :=
AlgEquiv.ext fun x =>
(algebraMap K₁ E).injective
(Eq.trans (AlgEquiv.restrictNormal_commutes _ K₁ x) (χ.liftNormal_commutes E x))
#align alg_equiv.restrict_lift_normal AlgEquiv.restrict_liftNormal
theorem AlgEquiv.restrictNormalHom_surjective [Normal F K₁] [Normal F E] :
Function.Surjective (AlgEquiv.restrictNormalHom K₁ : (E ≃ₐ[F] E) → K₁ ≃ₐ[F] K₁) := fun χ =>
⟨χ.liftNormal E, χ.restrict_liftNormal E⟩
#align alg_equiv.restrict_normal_hom_surjective AlgEquiv.restrictNormalHom_surjective
open IntermediateField in
theorem Normal.minpoly_eq_iff_mem_orbit [h : Normal F E] {x y : E} :
minpoly F x = minpoly F y ↔ x ∈ MulAction.orbit (E ≃ₐ[F] E) y := by
refine ⟨fun he ↦ ?_, fun ⟨f, he⟩ ↦ he ▸ minpoly.algEquiv_eq f y⟩
obtain ⟨φ, hφ⟩ := exists_algHom_of_splits_of_aeval (normal_iff.mp h) (he ▸ minpoly.aeval F x)
exact ⟨AlgEquiv.ofBijective φ (φ.normal_bijective F E E), hφ⟩
variable (F K₁)
theorem isSolvable_of_isScalarTower [Normal F K₁] [h1 : IsSolvable (K₁ ≃ₐ[F] K₁)]
[h2 : IsSolvable (E ≃ₐ[K₁] E)] : IsSolvable (E ≃ₐ[F] E) := by
let f : (E ≃ₐ[K₁] E) →* E ≃ₐ[F] E :=
{ toFun := fun ϕ =>
AlgEquiv.ofAlgHom (ϕ.toAlgHom.restrictScalars F) (ϕ.symm.toAlgHom.restrictScalars F)
(AlgHom.ext fun x => ϕ.apply_symm_apply x) (AlgHom.ext fun x => ϕ.symm_apply_apply x)
map_one' := AlgEquiv.ext fun _ => rfl
map_mul' := fun _ _ => AlgEquiv.ext fun _ => rfl }
refine
solvable_of_ker_le_range f (AlgEquiv.restrictNormalHom K₁) fun ϕ hϕ =>
⟨{ ϕ with commutes' := fun x => ?_ }, AlgEquiv.ext fun _ => rfl⟩
exact Eq.trans (ϕ.restrictNormal_commutes K₁ x).symm (congr_arg _ (AlgEquiv.ext_iff.mp hϕ x))
#align is_solvable_of_is_scalar_tower isSolvable_of_isScalarTower
end lift
namespace minpoly
variable {K L : Type _} [Field K] [Field L] [Algebra K L]
open AlgEquiv IntermediateField
/-- If `x : L` is a root of `minpoly K y`, then we can find `(σ : L ≃ₐ[K] L)` with `σ x = y`.
That is, `x` and `y` are Galois conjugates. -/
theorem exists_algEquiv_of_root [Normal K L] {x y : L} (hy : IsAlgebraic K y)
(h_ev : (Polynomial.aeval x) (minpoly K y) = 0) : ∃ σ : L ≃ₐ[K] L, σ x = y := by
have hx : IsAlgebraic K x := ⟨minpoly K y, ne_zero hy.isIntegral, h_ev⟩
set f : K⟮x⟯ ≃ₐ[K] K⟮y⟯ := algEquiv hx (eq_of_root hy h_ev)
have hxy : (liftNormal f L) ((algebraMap (↥K⟮x⟯) L) (AdjoinSimple.gen K x)) = y := by
rw [liftNormal_commutes f L, algEquiv_apply, AdjoinSimple.algebraMap_gen K y]
exact ⟨(liftNormal f L), hxy⟩
/-- If `x : L` is a root of `minpoly K y`, then we can find `(σ : L ≃ₐ[K] L)` with `σ y = x`.
That is, `x` and `y` are Galois conjugates. -/
| Mathlib/FieldTheory/Normal.lean | 425 | 429 | theorem exists_algEquiv_of_root' [Normal K L]{x y : L} (hy : IsAlgebraic K y)
(h_ev : (Polynomial.aeval x) (minpoly K y) = 0) : ∃ σ : L ≃ₐ[K] L, σ y = x := by |
obtain ⟨σ, hσ⟩ := exists_algEquiv_of_root hy h_ev
use σ.symm
rw [← hσ, symm_apply_apply]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, James Gallicchio
-/
import Batteries.Data.List.Count
import Batteries.Data.Fin.Lemmas
/-!
# Pairwise relations on a list
This file provides basic results about `List.Pairwise` and `List.pwFilter` (definitions are in
`Batteries.Data.List.Basic`).
`Pairwise r [a 0, ..., a (n - 1)]` means `∀ i j, i < j → r (a i) (a j)`. For example,
`Pairwise (≠) l` means that all elements of `l` are distinct, and `Pairwise (<) l` means that `l`
is strictly increasing.
`pwFilter r l` is the list obtained by iteratively adding each element of `l` that doesn't break
the pairwiseness of the list we have so far. It thus yields `l'` a maximal sublist of `l` such that
`Pairwise r l'`.
## Tags
sorted, nodup
-/
open Nat Function
namespace List
/-! ### Pairwise -/
theorem rel_of_pairwise_cons (p : (a :: l).Pairwise R) : ∀ {a'}, a' ∈ l → R a a' :=
(pairwise_cons.1 p).1 _
theorem Pairwise.of_cons (p : (a :: l).Pairwise R) : Pairwise R l :=
(pairwise_cons.1 p).2
theorem Pairwise.tail : ∀ {l : List α} (_p : Pairwise R l), Pairwise R l.tail
| [], h => h
| _ :: _, h => h.of_cons
theorem Pairwise.drop : ∀ {l : List α} {n : Nat}, List.Pairwise R l → List.Pairwise R (l.drop n)
| _, 0, h => h
| [], _ + 1, _ => List.Pairwise.nil
| _ :: _, n + 1, h => Pairwise.drop (n := n) (pairwise_cons.mp h).right
theorem Pairwise.imp_of_mem {S : α → α → Prop}
(H : ∀ {a b}, a ∈ l → b ∈ l → R a b → S a b) (p : Pairwise R l) : Pairwise S l := by
induction p with
| nil => constructor
| @cons a l r _ ih =>
constructor
· exact fun x h => H (mem_cons_self ..) (mem_cons_of_mem _ h) <| r x h
· exact ih fun m m' => H (mem_cons_of_mem _ m) (mem_cons_of_mem _ m')
theorem Pairwise.and (hR : Pairwise R l) (hS : Pairwise S l) :
l.Pairwise fun a b => R a b ∧ S a b := by
induction hR with
| nil => simp only [Pairwise.nil]
| cons R1 _ IH =>
simp only [Pairwise.nil, pairwise_cons] at hS ⊢
exact ⟨fun b bl => ⟨R1 b bl, hS.1 b bl⟩, IH hS.2⟩
theorem pairwise_and_iff : l.Pairwise (fun a b => R a b ∧ S a b) ↔ Pairwise R l ∧ Pairwise S l :=
⟨fun h => ⟨h.imp fun h => h.1, h.imp fun h => h.2⟩, fun ⟨hR, hS⟩ => hR.and hS⟩
theorem Pairwise.imp₂ (H : ∀ a b, R a b → S a b → T a b)
(hR : Pairwise R l) (hS : l.Pairwise S) : l.Pairwise T :=
(hR.and hS).imp fun ⟨h₁, h₂⟩ => H _ _ h₁ h₂
theorem Pairwise.iff_of_mem {S : α → α → Prop} {l : List α}
(H : ∀ {a b}, a ∈ l → b ∈ l → (R a b ↔ S a b)) : Pairwise R l ↔ Pairwise S l :=
⟨Pairwise.imp_of_mem fun m m' => (H m m').1, Pairwise.imp_of_mem fun m m' => (H m m').2⟩
theorem Pairwise.iff {S : α → α → Prop} (H : ∀ a b, R a b ↔ S a b) {l : List α} :
Pairwise R l ↔ Pairwise S l :=
Pairwise.iff_of_mem fun _ _ => H ..
theorem pairwise_of_forall {l : List α} (H : ∀ x y, R x y) : Pairwise R l := by
induction l <;> simp [*]
theorem Pairwise.and_mem {l : List α} :
Pairwise R l ↔ Pairwise (fun x y => x ∈ l ∧ y ∈ l ∧ R x y) l :=
Pairwise.iff_of_mem <| by simp (config := { contextual := true })
theorem Pairwise.imp_mem {l : List α} :
Pairwise R l ↔ Pairwise (fun x y => x ∈ l → y ∈ l → R x y) l :=
Pairwise.iff_of_mem <| by simp (config := { contextual := true })
theorem Pairwise.forall_of_forall_of_flip (h₁ : ∀ x ∈ l, R x x) (h₂ : Pairwise R l)
(h₃ : l.Pairwise (flip R)) : ∀ ⦃x⦄, x ∈ l → ∀ ⦃y⦄, y ∈ l → R x y := by
induction l with
| nil => exact forall_mem_nil _
| cons a l ih =>
rw [pairwise_cons] at h₂ h₃
simp only [mem_cons]
rintro x (rfl | hx) y (rfl | hy)
· exact h₁ _ (l.mem_cons_self _)
· exact h₂.1 _ hy
· exact h₃.1 _ hx
· exact ih (fun x hx => h₁ _ <| mem_cons_of_mem _ hx) h₂.2 h₃.2 hx hy
theorem pairwise_singleton (R) (a : α) : Pairwise R [a] := by simp
theorem pairwise_pair {a b : α} : Pairwise R [a, b] ↔ R a b := by simp
theorem pairwise_append_comm {R : α → α → Prop} (s : ∀ {x y}, R x y → R y x) {l₁ l₂ : List α} :
Pairwise R (l₁ ++ l₂) ↔ Pairwise R (l₂ ++ l₁) := by
have (l₁ l₂ : List α) (H : ∀ x : α, x ∈ l₁ → ∀ y : α, y ∈ l₂ → R x y)
(x : α) (xm : x ∈ l₂) (y : α) (ym : y ∈ l₁) : R x y := s (H y ym x xm)
simp only [pairwise_append, and_left_comm]; rw [Iff.intro (this l₁ l₂) (this l₂ l₁)]
theorem pairwise_middle {R : α → α → Prop} (s : ∀ {x y}, R x y → R y x) {a : α} {l₁ l₂ : List α} :
Pairwise R (l₁ ++ a :: l₂) ↔ Pairwise R (a :: (l₁ ++ l₂)) := by
show Pairwise R (l₁ ++ ([a] ++ l₂)) ↔ Pairwise R ([a] ++ l₁ ++ l₂)
rw [← append_assoc, pairwise_append, @pairwise_append _ _ ([a] ++ l₁), pairwise_append_comm s]
simp only [mem_append, or_comm]
theorem Pairwise.of_map {S : β → β → Prop} (f : α → β) (H : ∀ a b : α, S (f a) (f b) → R a b)
(p : Pairwise S (map f l)) : Pairwise R l :=
(pairwise_map.1 p).imp (H _ _)
theorem Pairwise.map {S : β → β → Prop} (f : α → β) (H : ∀ a b : α, R a b → S (f a) (f b))
(p : Pairwise R l) : Pairwise S (map f l) :=
pairwise_map.2 <| p.imp (H _ _)
| .lake/packages/batteries/Batteries/Data/List/Pairwise.lean | 128 | 142 | theorem pairwise_filterMap (f : β → Option α) {l : List β} :
Pairwise R (filterMap f l) ↔ Pairwise (fun a a' : β => ∀ b ∈ f a, ∀ b' ∈ f a', R b b') l := by |
let _S (a a' : β) := ∀ b ∈ f a, ∀ b' ∈ f a', R b b'
simp only [Option.mem_def]
induction l with
| nil => simp only [filterMap, Pairwise.nil]
| cons a l IH => ?_
match e : f a with
| none =>
rw [filterMap_cons_none _ _ e, pairwise_cons]
simp only [e, false_implies, implies_true, true_and, IH]
| some b =>
rw [filterMap_cons_some _ _ _ e]
simpa [IH, e] using fun _ =>
⟨fun h a ha b hab => h _ _ ha hab, fun h a b ha hab => h _ ha _ hab⟩
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Data.Fin.VecNotation
import Mathlib.Logic.Embedding.Set
#align_import logic.equiv.fin from "leanprover-community/mathlib"@"bd835ef554f37ef9b804f0903089211f89cb370b"
/-!
# Equivalences for `Fin n`
-/
assert_not_exists MonoidWithZero
universe u
variable {m n : ℕ}
/-- Equivalence between `Fin 0` and `Empty`. -/
def finZeroEquiv : Fin 0 ≃ Empty :=
Equiv.equivEmpty _
#align fin_zero_equiv finZeroEquiv
/-- Equivalence between `Fin 0` and `PEmpty`. -/
def finZeroEquiv' : Fin 0 ≃ PEmpty.{u} :=
Equiv.equivPEmpty _
#align fin_zero_equiv' finZeroEquiv'
/-- Equivalence between `Fin 1` and `Unit`. -/
def finOneEquiv : Fin 1 ≃ Unit :=
Equiv.equivPUnit _
#align fin_one_equiv finOneEquiv
/-- Equivalence between `Fin 2` and `Bool`. -/
def finTwoEquiv : Fin 2 ≃ Bool where
toFun := ![false, true]
invFun b := b.casesOn 0 1
left_inv := Fin.forall_fin_two.2 <| by simp
right_inv := Bool.forall_bool.2 <| by simp
#align fin_two_equiv finTwoEquiv
/-- `Π i : Fin 2, α i` is equivalent to `α 0 × α 1`. See also `finTwoArrowEquiv` for a
non-dependent version and `prodEquivPiFinTwo` for a version with inputs `α β : Type u`. -/
@[simps (config := .asFn)]
def piFinTwoEquiv (α : Fin 2 → Type u) : (∀ i, α i) ≃ α 0 × α 1 where
toFun f := (f 0, f 1)
invFun p := Fin.cons p.1 <| Fin.cons p.2 finZeroElim
left_inv _ := funext <| Fin.forall_fin_two.2 ⟨rfl, rfl⟩
right_inv := fun _ => rfl
#align pi_fin_two_equiv piFinTwoEquiv
#align pi_fin_two_equiv_symm_apply piFinTwoEquiv_symm_apply
#align pi_fin_two_equiv_apply piFinTwoEquiv_apply
theorem Fin.preimage_apply_01_prod {α : Fin 2 → Type u} (s : Set (α 0)) (t : Set (α 1)) :
(fun f : ∀ i, α i => (f 0, f 1)) ⁻¹' s ×ˢ t =
Set.pi Set.univ (Fin.cons s <| Fin.cons t finZeroElim) := by
ext f
simp [Fin.forall_fin_two]
#align fin.preimage_apply_01_prod Fin.preimage_apply_01_prod
theorem Fin.preimage_apply_01_prod' {α : Type u} (s t : Set α) :
(fun f : Fin 2 → α => (f 0, f 1)) ⁻¹' s ×ˢ t = Set.pi Set.univ ![s, t] :=
@Fin.preimage_apply_01_prod (fun _ => α) s t
#align fin.preimage_apply_01_prod' Fin.preimage_apply_01_prod'
/-- A product space `α × β` is equivalent to the space `Π i : Fin 2, γ i`, where
`γ = Fin.cons α (Fin.cons β finZeroElim)`. See also `piFinTwoEquiv` and
`finTwoArrowEquiv`. -/
@[simps! (config := .asFn)]
def prodEquivPiFinTwo (α β : Type u) : α × β ≃ ∀ i : Fin 2, ![α, β] i :=
(piFinTwoEquiv (Fin.cons α (Fin.cons β finZeroElim))).symm
#align prod_equiv_pi_fin_two prodEquivPiFinTwo
#align prod_equiv_pi_fin_two_apply prodEquivPiFinTwo_apply
#align prod_equiv_pi_fin_two_symm_apply prodEquivPiFinTwo_symm_apply
/-- The space of functions `Fin 2 → α` is equivalent to `α × α`. See also `piFinTwoEquiv` and
`prodEquivPiFinTwo`. -/
@[simps (config := .asFn)]
def finTwoArrowEquiv (α : Type*) : (Fin 2 → α) ≃ α × α :=
{ piFinTwoEquiv fun _ => α with invFun := fun x => ![x.1, x.2] }
#align fin_two_arrow_equiv finTwoArrowEquiv
#align fin_two_arrow_equiv_symm_apply finTwoArrowEquiv_symm_apply
#align fin_two_arrow_equiv_apply finTwoArrowEquiv_apply
/-- `Π i : Fin 2, α i` is order equivalent to `α 0 × α 1`. See also `OrderIso.finTwoArrowEquiv`
for a non-dependent version. -/
def OrderIso.piFinTwoIso (α : Fin 2 → Type u) [∀ i, Preorder (α i)] : (∀ i, α i) ≃o α 0 × α 1 where
toEquiv := piFinTwoEquiv α
map_rel_iff' := Iff.symm Fin.forall_fin_two
#align order_iso.pi_fin_two_iso OrderIso.piFinTwoIso
/-- The space of functions `Fin 2 → α` is order equivalent to `α × α`. See also
`OrderIso.piFinTwoIso`. -/
def OrderIso.finTwoArrowIso (α : Type*) [Preorder α] : (Fin 2 → α) ≃o α × α :=
{ OrderIso.piFinTwoIso fun _ => α with toEquiv := finTwoArrowEquiv α }
#align order_iso.fin_two_arrow_iso OrderIso.finTwoArrowIso
/-- An equivalence that removes `i` and maps it to `none`.
This is a version of `Fin.predAbove` that produces `Option (Fin n)` instead of
mapping both `i.cast_succ` and `i.succ` to `i`. -/
def finSuccEquiv' (i : Fin (n + 1)) : Fin (n + 1) ≃ Option (Fin n) where
toFun := i.insertNth none some
invFun x := x.casesOn' i (Fin.succAbove i)
left_inv x := Fin.succAboveCases i (by simp) (fun j => by simp) x
right_inv x := by cases x <;> dsimp <;> simp
#align fin_succ_equiv' finSuccEquiv'
@[simp]
theorem finSuccEquiv'_at (i : Fin (n + 1)) : (finSuccEquiv' i) i = none := by
simp [finSuccEquiv']
#align fin_succ_equiv'_at finSuccEquiv'_at
@[simp]
theorem finSuccEquiv'_succAbove (i : Fin (n + 1)) (j : Fin n) :
finSuccEquiv' i (i.succAbove j) = some j :=
@Fin.insertNth_apply_succAbove n (fun _ => Option (Fin n)) i _ _ _
#align fin_succ_equiv'_succ_above finSuccEquiv'_succAbove
theorem finSuccEquiv'_below {i : Fin (n + 1)} {m : Fin n} (h : Fin.castSucc m < i) :
(finSuccEquiv' i) (Fin.castSucc m) = m := by
rw [← Fin.succAbove_of_castSucc_lt _ _ h, finSuccEquiv'_succAbove]
#align fin_succ_equiv'_below finSuccEquiv'_below
| Mathlib/Logic/Equiv/Fin.lean | 126 | 128 | theorem finSuccEquiv'_above {i : Fin (n + 1)} {m : Fin n} (h : i ≤ Fin.castSucc m) :
(finSuccEquiv' i) m.succ = some m := by |
rw [← Fin.succAbove_of_le_castSucc _ _ h, finSuccEquiv'_succAbove]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Bool.Set
import Mathlib.Data.Nat.Set
import Mathlib.Data.Set.Prod
import Mathlib.Data.ULift
import Mathlib.Order.Bounds.Basic
import Mathlib.Order.Hom.Set
import Mathlib.Order.SetNotation
#align_import order.complete_lattice from "leanprover-community/mathlib"@"5709b0d8725255e76f47debca6400c07b5c2d8e6"
/-!
# Theory of complete lattices
## Main definitions
* `sSup` and `sInf` are the supremum and the infimum of a set;
* `iSup (f : ι → α)` and `iInf (f : ι → α)` are indexed supremum and infimum of a function,
defined as `sSup` and `sInf` of the range of this function;
* class `CompleteLattice`: a bounded lattice such that `sSup s` is always the least upper boundary
of `s` and `sInf s` is always the greatest lower boundary of `s`;
* class `CompleteLinearOrder`: a linear ordered complete lattice.
## Naming conventions
In lemma names,
* `sSup` is called `sSup`
* `sInf` is called `sInf`
* `⨆ i, s i` is called `iSup`
* `⨅ i, s i` is called `iInf`
* `⨆ i j, s i j` is called `iSup₂`. This is an `iSup` inside an `iSup`.
* `⨅ i j, s i j` is called `iInf₂`. This is an `iInf` inside an `iInf`.
* `⨆ i ∈ s, t i` is called `biSup` for "bounded `iSup`". This is the special case of `iSup₂`
where `j : i ∈ s`.
* `⨅ i ∈ s, t i` is called `biInf` for "bounded `iInf`". This is the special case of `iInf₂`
where `j : i ∈ s`.
## Notation
* `⨆ i, f i` : `iSup f`, the supremum of the range of `f`;
* `⨅ i, f i` : `iInf f`, the infimum of the range of `f`.
-/
open Function OrderDual Set
variable {α β β₂ γ : Type*} {ι ι' : Sort*} {κ : ι → Sort*} {κ' : ι' → Sort*}
instance OrderDual.supSet (α) [InfSet α] : SupSet αᵒᵈ :=
⟨(sInf : Set α → α)⟩
instance OrderDual.infSet (α) [SupSet α] : InfSet αᵒᵈ :=
⟨(sSup : Set α → α)⟩
/-- Note that we rarely use `CompleteSemilatticeSup`
(in fact, any such object is always a `CompleteLattice`, so it's usually best to start there).
Nevertheless it is sometimes a useful intermediate step in constructions.
-/
class CompleteSemilatticeSup (α : Type*) extends PartialOrder α, SupSet α where
/-- Any element of a set is less than the set supremum. -/
le_sSup : ∀ s, ∀ a ∈ s, a ≤ sSup s
/-- Any upper bound is more than the set supremum. -/
sSup_le : ∀ s a, (∀ b ∈ s, b ≤ a) → sSup s ≤ a
#align complete_semilattice_Sup CompleteSemilatticeSup
section
variable [CompleteSemilatticeSup α] {s t : Set α} {a b : α}
theorem le_sSup : a ∈ s → a ≤ sSup s :=
CompleteSemilatticeSup.le_sSup s a
#align le_Sup le_sSup
theorem sSup_le : (∀ b ∈ s, b ≤ a) → sSup s ≤ a :=
CompleteSemilatticeSup.sSup_le s a
#align Sup_le sSup_le
theorem isLUB_sSup (s : Set α) : IsLUB s (sSup s) :=
⟨fun _ ↦ le_sSup, fun _ ↦ sSup_le⟩
#align is_lub_Sup isLUB_sSup
lemma isLUB_iff_sSup_eq : IsLUB s a ↔ sSup s = a :=
⟨(isLUB_sSup s).unique, by rintro rfl; exact isLUB_sSup _⟩
alias ⟨IsLUB.sSup_eq, _⟩ := isLUB_iff_sSup_eq
#align is_lub.Sup_eq IsLUB.sSup_eq
theorem le_sSup_of_le (hb : b ∈ s) (h : a ≤ b) : a ≤ sSup s :=
le_trans h (le_sSup hb)
#align le_Sup_of_le le_sSup_of_le
@[gcongr]
theorem sSup_le_sSup (h : s ⊆ t) : sSup s ≤ sSup t :=
(isLUB_sSup s).mono (isLUB_sSup t) h
#align Sup_le_Sup sSup_le_sSup
@[simp]
theorem sSup_le_iff : sSup s ≤ a ↔ ∀ b ∈ s, b ≤ a :=
isLUB_le_iff (isLUB_sSup s)
#align Sup_le_iff sSup_le_iff
theorem le_sSup_iff : a ≤ sSup s ↔ ∀ b ∈ upperBounds s, a ≤ b :=
⟨fun h _ hb => le_trans h (sSup_le hb), fun hb => hb _ fun _ => le_sSup⟩
#align le_Sup_iff le_sSup_iff
theorem le_iSup_iff {s : ι → α} : a ≤ iSup s ↔ ∀ b, (∀ i, s i ≤ b) → a ≤ b := by
simp [iSup, le_sSup_iff, upperBounds]
#align le_supr_iff le_iSup_iff
theorem sSup_le_sSup_of_forall_exists_le (h : ∀ x ∈ s, ∃ y ∈ t, x ≤ y) : sSup s ≤ sSup t :=
le_sSup_iff.2 fun _ hb =>
sSup_le fun a ha =>
let ⟨_, hct, hac⟩ := h a ha
hac.trans (hb hct)
#align Sup_le_Sup_of_forall_exists_le sSup_le_sSup_of_forall_exists_le
-- We will generalize this to conditionally complete lattices in `csSup_singleton`.
theorem sSup_singleton {a : α} : sSup {a} = a :=
isLUB_singleton.sSup_eq
#align Sup_singleton sSup_singleton
end
/-- Note that we rarely use `CompleteSemilatticeInf`
(in fact, any such object is always a `CompleteLattice`, so it's usually best to start there).
Nevertheless it is sometimes a useful intermediate step in constructions.
-/
class CompleteSemilatticeInf (α : Type*) extends PartialOrder α, InfSet α where
/-- Any element of a set is more than the set infimum. -/
sInf_le : ∀ s, ∀ a ∈ s, sInf s ≤ a
/-- Any lower bound is less than the set infimum. -/
le_sInf : ∀ s a, (∀ b ∈ s, a ≤ b) → a ≤ sInf s
#align complete_semilattice_Inf CompleteSemilatticeInf
section
variable [CompleteSemilatticeInf α] {s t : Set α} {a b : α}
theorem sInf_le : a ∈ s → sInf s ≤ a :=
CompleteSemilatticeInf.sInf_le s a
#align Inf_le sInf_le
theorem le_sInf : (∀ b ∈ s, a ≤ b) → a ≤ sInf s :=
CompleteSemilatticeInf.le_sInf s a
#align le_Inf le_sInf
theorem isGLB_sInf (s : Set α) : IsGLB s (sInf s) :=
⟨fun _ => sInf_le, fun _ => le_sInf⟩
#align is_glb_Inf isGLB_sInf
lemma isGLB_iff_sInf_eq : IsGLB s a ↔ sInf s = a :=
⟨(isGLB_sInf s).unique, by rintro rfl; exact isGLB_sInf _⟩
alias ⟨IsGLB.sInf_eq, _⟩ := isGLB_iff_sInf_eq
#align is_glb.Inf_eq IsGLB.sInf_eq
theorem sInf_le_of_le (hb : b ∈ s) (h : b ≤ a) : sInf s ≤ a :=
le_trans (sInf_le hb) h
#align Inf_le_of_le sInf_le_of_le
@[gcongr]
theorem sInf_le_sInf (h : s ⊆ t) : sInf t ≤ sInf s :=
(isGLB_sInf s).mono (isGLB_sInf t) h
#align Inf_le_Inf sInf_le_sInf
@[simp]
theorem le_sInf_iff : a ≤ sInf s ↔ ∀ b ∈ s, a ≤ b :=
le_isGLB_iff (isGLB_sInf s)
#align le_Inf_iff le_sInf_iff
theorem sInf_le_iff : sInf s ≤ a ↔ ∀ b ∈ lowerBounds s, b ≤ a :=
⟨fun h _ hb => le_trans (le_sInf hb) h, fun hb => hb _ fun _ => sInf_le⟩
#align Inf_le_iff sInf_le_iff
theorem iInf_le_iff {s : ι → α} : iInf s ≤ a ↔ ∀ b, (∀ i, b ≤ s i) → b ≤ a := by
simp [iInf, sInf_le_iff, lowerBounds]
#align infi_le_iff iInf_le_iff
theorem sInf_le_sInf_of_forall_exists_le (h : ∀ x ∈ s, ∃ y ∈ t, y ≤ x) : sInf t ≤ sInf s :=
le_sInf fun x hx ↦ let ⟨_y, hyt, hyx⟩ := h x hx; sInf_le_of_le hyt hyx
#align Inf_le_Inf_of_forall_exists_le sInf_le_sInf_of_forall_exists_le
-- We will generalize this to conditionally complete lattices in `csInf_singleton`.
theorem sInf_singleton {a : α} : sInf {a} = a :=
isGLB_singleton.sInf_eq
#align Inf_singleton sInf_singleton
end
/-- A complete lattice is a bounded lattice which has suprema and infima for every subset. -/
class CompleteLattice (α : Type*) extends Lattice α, CompleteSemilatticeSup α,
CompleteSemilatticeInf α, Top α, Bot α where
/-- Any element is less than the top one. -/
protected le_top : ∀ x : α, x ≤ ⊤
/-- Any element is more than the bottom one. -/
protected bot_le : ∀ x : α, ⊥ ≤ x
#align complete_lattice CompleteLattice
-- see Note [lower instance priority]
instance (priority := 100) CompleteLattice.toBoundedOrder [h : CompleteLattice α] :
BoundedOrder α :=
{ h with }
#align complete_lattice.to_bounded_order CompleteLattice.toBoundedOrder
/-- Create a `CompleteLattice` from a `PartialOrder` and `InfSet`
that returns the greatest lower bound of a set. Usually this constructor provides
poor definitional equalities. If other fields are known explicitly, they should be
provided; for example, if `inf` is known explicitly, construct the `CompleteLattice`
instance as
```
instance : CompleteLattice my_T where
inf := better_inf
le_inf := ...
inf_le_right := ...
inf_le_left := ...
-- don't care to fix sup, sSup, bot, top
__ := completeLatticeOfInf my_T _
```
-/
def completeLatticeOfInf (α : Type*) [H1 : PartialOrder α] [H2 : InfSet α]
(isGLB_sInf : ∀ s : Set α, IsGLB s (sInf s)) : CompleteLattice α where
__ := H1; __ := H2
bot := sInf univ
bot_le x := (isGLB_sInf univ).1 trivial
top := sInf ∅
le_top a := (isGLB_sInf ∅).2 <| by simp
sup a b := sInf { x : α | a ≤ x ∧ b ≤ x }
inf a b := sInf {a, b}
le_inf a b c hab hac := by
apply (isGLB_sInf _).2
simp [*]
inf_le_right a b := (isGLB_sInf _).1 <| mem_insert_of_mem _ <| mem_singleton _
inf_le_left a b := (isGLB_sInf _).1 <| mem_insert _ _
sup_le a b c hac hbc := (isGLB_sInf _).1 <| by simp [*]
le_sup_left a b := (isGLB_sInf _).2 fun x => And.left
le_sup_right a b := (isGLB_sInf _).2 fun x => And.right
le_sInf s a ha := (isGLB_sInf s).2 ha
sInf_le s a ha := (isGLB_sInf s).1 ha
sSup s := sInf (upperBounds s)
le_sSup s a ha := (isGLB_sInf (upperBounds s)).2 fun b hb => hb ha
sSup_le s a ha := (isGLB_sInf (upperBounds s)).1 ha
#align complete_lattice_of_Inf completeLatticeOfInf
/-- Any `CompleteSemilatticeInf` is in fact a `CompleteLattice`.
Note that this construction has bad definitional properties:
see the doc-string on `completeLatticeOfInf`.
-/
def completeLatticeOfCompleteSemilatticeInf (α : Type*) [CompleteSemilatticeInf α] :
CompleteLattice α :=
completeLatticeOfInf α fun s => isGLB_sInf s
#align complete_lattice_of_complete_semilattice_Inf completeLatticeOfCompleteSemilatticeInf
/-- Create a `CompleteLattice` from a `PartialOrder` and `SupSet`
that returns the least upper bound of a set. Usually this constructor provides
poor definitional equalities. If other fields are known explicitly, they should be
provided; for example, if `inf` is known explicitly, construct the `CompleteLattice`
instance as
```
instance : CompleteLattice my_T where
inf := better_inf
le_inf := ...
inf_le_right := ...
inf_le_left := ...
-- don't care to fix sup, sInf, bot, top
__ := completeLatticeOfSup my_T _
```
-/
def completeLatticeOfSup (α : Type*) [H1 : PartialOrder α] [H2 : SupSet α]
(isLUB_sSup : ∀ s : Set α, IsLUB s (sSup s)) : CompleteLattice α where
__ := H1; __ := H2
top := sSup univ
le_top x := (isLUB_sSup univ).1 trivial
bot := sSup ∅
bot_le x := (isLUB_sSup ∅).2 <| by simp
sup a b := sSup {a, b}
sup_le a b c hac hbc := (isLUB_sSup _).2 (by simp [*])
le_sup_left a b := (isLUB_sSup _).1 <| mem_insert _ _
le_sup_right a b := (isLUB_sSup _).1 <| mem_insert_of_mem _ <| mem_singleton _
inf a b := sSup { x | x ≤ a ∧ x ≤ b }
le_inf a b c hab hac := (isLUB_sSup _).1 <| by simp [*]
inf_le_left a b := (isLUB_sSup _).2 fun x => And.left
inf_le_right a b := (isLUB_sSup _).2 fun x => And.right
sInf s := sSup (lowerBounds s)
sSup_le s a ha := (isLUB_sSup s).2 ha
le_sSup s a ha := (isLUB_sSup s).1 ha
sInf_le s a ha := (isLUB_sSup (lowerBounds s)).2 fun b hb => hb ha
le_sInf s a ha := (isLUB_sSup (lowerBounds s)).1 ha
#align complete_lattice_of_Sup completeLatticeOfSup
/-- Any `CompleteSemilatticeSup` is in fact a `CompleteLattice`.
Note that this construction has bad definitional properties:
see the doc-string on `completeLatticeOfSup`.
-/
def completeLatticeOfCompleteSemilatticeSup (α : Type*) [CompleteSemilatticeSup α] :
CompleteLattice α :=
completeLatticeOfSup α fun s => isLUB_sSup s
#align complete_lattice_of_complete_semilattice_Sup completeLatticeOfCompleteSemilatticeSup
-- Porting note: as we cannot rename fields while extending,
-- `CompleteLinearOrder` does not directly extend `LinearOrder`.
-- Instead we add the fields by hand, and write a manual instance.
/-- A complete linear order is a linear order whose lattice structure is complete. -/
class CompleteLinearOrder (α : Type*) extends CompleteLattice α where
/-- A linear order is total. -/
le_total (a b : α) : a ≤ b ∨ b ≤ a
/-- In a linearly ordered type, we assume the order relations are all decidable. -/
decidableLE : DecidableRel (· ≤ · : α → α → Prop)
/-- In a linearly ordered type, we assume the order relations are all decidable. -/
decidableEq : DecidableEq α := @decidableEqOfDecidableLE _ _ decidableLE
/-- In a linearly ordered type, we assume the order relations are all decidable. -/
decidableLT : DecidableRel (· < · : α → α → Prop) :=
@decidableLTOfDecidableLE _ _ decidableLE
#align complete_linear_order CompleteLinearOrder
instance CompleteLinearOrder.toLinearOrder [i : CompleteLinearOrder α] : LinearOrder α where
__ := i
min := Inf.inf
max := Sup.sup
min_def a b := by
split_ifs with h
· simp [h]
· simp [(CompleteLinearOrder.le_total a b).resolve_left h]
max_def a b := by
split_ifs with h
· simp [h]
· simp [(CompleteLinearOrder.le_total a b).resolve_left h]
namespace OrderDual
instance instCompleteLattice [CompleteLattice α] : CompleteLattice αᵒᵈ where
__ := instBoundedOrder α
le_sSup := @CompleteLattice.sInf_le α _
sSup_le := @CompleteLattice.le_sInf α _
sInf_le := @CompleteLattice.le_sSup α _
le_sInf := @CompleteLattice.sSup_le α _
instance instCompleteLinearOrder [CompleteLinearOrder α] : CompleteLinearOrder αᵒᵈ where
__ := instCompleteLattice
__ := instLinearOrder α
end OrderDual
open OrderDual
section
variable [CompleteLattice α] {s t : Set α} {a b : α}
@[simp]
theorem toDual_sSup (s : Set α) : toDual (sSup s) = sInf (ofDual ⁻¹' s) :=
rfl
#align to_dual_Sup toDual_sSup
@[simp]
theorem toDual_sInf (s : Set α) : toDual (sInf s) = sSup (ofDual ⁻¹' s) :=
rfl
#align to_dual_Inf toDual_sInf
@[simp]
theorem ofDual_sSup (s : Set αᵒᵈ) : ofDual (sSup s) = sInf (toDual ⁻¹' s) :=
rfl
#align of_dual_Sup ofDual_sSup
@[simp]
theorem ofDual_sInf (s : Set αᵒᵈ) : ofDual (sInf s) = sSup (toDual ⁻¹' s) :=
rfl
#align of_dual_Inf ofDual_sInf
@[simp]
theorem toDual_iSup (f : ι → α) : toDual (⨆ i, f i) = ⨅ i, toDual (f i) :=
rfl
#align to_dual_supr toDual_iSup
@[simp]
theorem toDual_iInf (f : ι → α) : toDual (⨅ i, f i) = ⨆ i, toDual (f i) :=
rfl
#align to_dual_infi toDual_iInf
@[simp]
theorem ofDual_iSup (f : ι → αᵒᵈ) : ofDual (⨆ i, f i) = ⨅ i, ofDual (f i) :=
rfl
#align of_dual_supr ofDual_iSup
@[simp]
theorem ofDual_iInf (f : ι → αᵒᵈ) : ofDual (⨅ i, f i) = ⨆ i, ofDual (f i) :=
rfl
#align of_dual_infi ofDual_iInf
theorem sInf_le_sSup (hs : s.Nonempty) : sInf s ≤ sSup s :=
isGLB_le_isLUB (isGLB_sInf s) (isLUB_sSup s) hs
#align Inf_le_Sup sInf_le_sSup
theorem sSup_union {s t : Set α} : sSup (s ∪ t) = sSup s ⊔ sSup t :=
((isLUB_sSup s).union (isLUB_sSup t)).sSup_eq
#align Sup_union sSup_union
theorem sInf_union {s t : Set α} : sInf (s ∪ t) = sInf s ⊓ sInf t :=
((isGLB_sInf s).union (isGLB_sInf t)).sInf_eq
#align Inf_union sInf_union
theorem sSup_inter_le {s t : Set α} : sSup (s ∩ t) ≤ sSup s ⊓ sSup t :=
sSup_le fun _ hb => le_inf (le_sSup hb.1) (le_sSup hb.2)
#align Sup_inter_le sSup_inter_le
theorem le_sInf_inter {s t : Set α} : sInf s ⊔ sInf t ≤ sInf (s ∩ t) :=
@sSup_inter_le αᵒᵈ _ _ _
#align le_Inf_inter le_sInf_inter
@[simp]
theorem sSup_empty : sSup ∅ = (⊥ : α) :=
(@isLUB_empty α _ _).sSup_eq
#align Sup_empty sSup_empty
@[simp]
theorem sInf_empty : sInf ∅ = (⊤ : α) :=
(@isGLB_empty α _ _).sInf_eq
#align Inf_empty sInf_empty
@[simp]
theorem sSup_univ : sSup univ = (⊤ : α) :=
(@isLUB_univ α _ _).sSup_eq
#align Sup_univ sSup_univ
@[simp]
theorem sInf_univ : sInf univ = (⊥ : α) :=
(@isGLB_univ α _ _).sInf_eq
#align Inf_univ sInf_univ
-- TODO(Jeremy): get this automatically
@[simp]
theorem sSup_insert {a : α} {s : Set α} : sSup (insert a s) = a ⊔ sSup s :=
((isLUB_sSup s).insert a).sSup_eq
#align Sup_insert sSup_insert
@[simp]
theorem sInf_insert {a : α} {s : Set α} : sInf (insert a s) = a ⊓ sInf s :=
((isGLB_sInf s).insert a).sInf_eq
#align Inf_insert sInf_insert
theorem sSup_le_sSup_of_subset_insert_bot (h : s ⊆ insert ⊥ t) : sSup s ≤ sSup t :=
(sSup_le_sSup h).trans_eq (sSup_insert.trans (bot_sup_eq _))
#align Sup_le_Sup_of_subset_insert_bot sSup_le_sSup_of_subset_insert_bot
theorem sInf_le_sInf_of_subset_insert_top (h : s ⊆ insert ⊤ t) : sInf t ≤ sInf s :=
(sInf_le_sInf h).trans_eq' (sInf_insert.trans (top_inf_eq _)).symm
#align Inf_le_Inf_of_subset_insert_top sInf_le_sInf_of_subset_insert_top
@[simp]
theorem sSup_diff_singleton_bot (s : Set α) : sSup (s \ {⊥}) = sSup s :=
(sSup_le_sSup diff_subset).antisymm <|
sSup_le_sSup_of_subset_insert_bot <| subset_insert_diff_singleton _ _
#align Sup_diff_singleton_bot sSup_diff_singleton_bot
@[simp]
theorem sInf_diff_singleton_top (s : Set α) : sInf (s \ {⊤}) = sInf s :=
@sSup_diff_singleton_bot αᵒᵈ _ s
#align Inf_diff_singleton_top sInf_diff_singleton_top
theorem sSup_pair {a b : α} : sSup {a, b} = a ⊔ b :=
(@isLUB_pair α _ a b).sSup_eq
#align Sup_pair sSup_pair
theorem sInf_pair {a b : α} : sInf {a, b} = a ⊓ b :=
(@isGLB_pair α _ a b).sInf_eq
#align Inf_pair sInf_pair
@[simp]
theorem sSup_eq_bot : sSup s = ⊥ ↔ ∀ a ∈ s, a = ⊥ :=
⟨fun h _ ha => bot_unique <| h ▸ le_sSup ha, fun h =>
bot_unique <| sSup_le fun a ha => le_bot_iff.2 <| h a ha⟩
#align Sup_eq_bot sSup_eq_bot
@[simp]
theorem sInf_eq_top : sInf s = ⊤ ↔ ∀ a ∈ s, a = ⊤ :=
@sSup_eq_bot αᵒᵈ _ _
#align Inf_eq_top sInf_eq_top
| Mathlib/Order/CompleteLattice.lean | 486 | 490 | theorem eq_singleton_bot_of_sSup_eq_bot_of_nonempty {s : Set α} (h_sup : sSup s = ⊥)
(hne : s.Nonempty) : s = {⊥} := by |
rw [Set.eq_singleton_iff_nonempty_unique_mem]
rw [sSup_eq_bot] at h_sup
exact ⟨hne, h_sup⟩
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.SmoothManifoldWithCorners
import Mathlib.Geometry.Manifold.LocalInvariantProperties
#align_import geometry.manifold.cont_mdiff from "leanprover-community/mathlib"@"e5ab837fc252451f3eb9124ae6e7b6f57455e7b9"
/-!
# Smooth functions between smooth manifolds
We define `Cⁿ` functions between smooth manifolds, as functions which are `Cⁿ` in charts, and prove
basic properties of these notions.
## Main definitions and statements
Let `M` and `M'` be two smooth manifolds, with respect to model with corners `I` and `I'`. Let
`f : M → M'`.
* `ContMDiffWithinAt I I' n f s x` states that the function `f` is `Cⁿ` within the set `s`
around the point `x`.
* `ContMDiffAt I I' n f x` states that the function `f` is `Cⁿ` around `x`.
* `ContMDiffOn I I' n f s` states that the function `f` is `Cⁿ` on the set `s`
* `ContMDiff I I' n f` states that the function `f` is `Cⁿ`.
We also give some basic properties of smooth functions between manifolds, following the API of
smooth functions between vector spaces.
See `Basic.lean` for further basic properties of smooth functions between smooth manifolds,
`NormedSpace.lean` for the equivalence of manifold-smoothness to usual smoothness,
`Product.lean` for smoothness results related to the product of manifolds and
`Atlas.lean` for smoothness of atlas members and local structomorphisms.
## Implementation details
Many properties follow for free from the corresponding properties of functions in vector spaces,
as being `Cⁿ` is a local property invariant under the smooth groupoid. We take advantage of the
general machinery developed in `LocalInvariantProperties.lean` to get these properties
automatically. For instance, the fact that being `Cⁿ` does not depend on the chart one considers
is given by `liftPropWithinAt_indep_chart`.
For this to work, the definition of `ContMDiffWithinAt` and friends has to
follow definitionally the setup of local invariant properties. Still, we recast the definition
in terms of extended charts in `contMDiffOn_iff` and `contMDiff_iff`.
-/
open Set Function Filter ChartedSpace SmoothManifoldWithCorners
open scoped Topology Manifold
/-! ### Definition of smooth functions between manifolds -/
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
-- declare a smooth manifold `M` over the pair `(E, H)`.
{E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) {M : Type*} [TopologicalSpace M] [ChartedSpace H M]
[SmoothManifoldWithCorners I M]
-- declare a smooth manifold `M'` over the pair `(E', H')`.
{E' : Type*}
[NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H']
(I' : ModelWithCorners 𝕜 E' H') {M' : Type*} [TopologicalSpace M'] [ChartedSpace H' M']
[SmoothManifoldWithCorners I' M']
-- declare a manifold `M''` over the pair `(E'', H'')`.
{E'' : Type*}
[NormedAddCommGroup E''] [NormedSpace 𝕜 E''] {H'' : Type*} [TopologicalSpace H'']
{I'' : ModelWithCorners 𝕜 E'' H''} {M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M'']
-- declare a smooth manifold `N` over the pair `(F, G)`.
{F : Type*}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type*} [TopologicalSpace G]
{J : ModelWithCorners 𝕜 F G} {N : Type*} [TopologicalSpace N] [ChartedSpace G N]
[SmoothManifoldWithCorners J N]
-- declare a smooth manifold `N'` over the pair `(F', G')`.
{F' : Type*}
[NormedAddCommGroup F'] [NormedSpace 𝕜 F'] {G' : Type*} [TopologicalSpace G']
{J' : ModelWithCorners 𝕜 F' G'} {N' : Type*} [TopologicalSpace N'] [ChartedSpace G' N']
[SmoothManifoldWithCorners J' N']
-- F₁, F₂, F₃, F₄ are normed spaces
{F₁ : Type*}
[NormedAddCommGroup F₁] [NormedSpace 𝕜 F₁] {F₂ : Type*} [NormedAddCommGroup F₂]
[NormedSpace 𝕜 F₂] {F₃ : Type*} [NormedAddCommGroup F₃] [NormedSpace 𝕜 F₃] {F₄ : Type*}
[NormedAddCommGroup F₄] [NormedSpace 𝕜 F₄]
-- declare functions, sets, points and smoothness indices
{e : PartialHomeomorph M H}
{e' : PartialHomeomorph M' H'} {f f₁ : M → M'} {s s₁ t : Set M} {x : M} {m n : ℕ∞}
/-- Property in the model space of a model with corners of being `C^n` within at set at a point,
when read in the model vector space. This property will be lifted to manifolds to define smooth
functions between manifolds. -/
def ContDiffWithinAtProp (n : ℕ∞) (f : H → H') (s : Set H) (x : H) : Prop :=
ContDiffWithinAt 𝕜 n (I' ∘ f ∘ I.symm) (I.symm ⁻¹' s ∩ range I) (I x)
#align cont_diff_within_at_prop ContDiffWithinAtProp
theorem contDiffWithinAtProp_self_source {f : E → H'} {s : Set E} {x : E} :
ContDiffWithinAtProp 𝓘(𝕜, E) I' n f s x ↔ ContDiffWithinAt 𝕜 n (I' ∘ f) s x := by
simp_rw [ContDiffWithinAtProp, modelWithCornersSelf_coe, range_id, inter_univ,
modelWithCornersSelf_coe_symm, CompTriple.comp_eq, preimage_id_eq, id_eq]
#align cont_diff_within_at_prop_self_source contDiffWithinAtProp_self_source
theorem contDiffWithinAtProp_self {f : E → E'} {s : Set E} {x : E} :
ContDiffWithinAtProp 𝓘(𝕜, E) 𝓘(𝕜, E') n f s x ↔ ContDiffWithinAt 𝕜 n f s x :=
contDiffWithinAtProp_self_source 𝓘(𝕜, E')
#align cont_diff_within_at_prop_self contDiffWithinAtProp_self
theorem contDiffWithinAtProp_self_target {f : H → E'} {s : Set H} {x : H} :
ContDiffWithinAtProp I 𝓘(𝕜, E') n f s x ↔
ContDiffWithinAt 𝕜 n (f ∘ I.symm) (I.symm ⁻¹' s ∩ range I) (I x) :=
Iff.rfl
#align cont_diff_within_at_prop_self_target contDiffWithinAtProp_self_target
/-- Being `Cⁿ` in the model space is a local property, invariant under smooth maps. Therefore,
it will lift nicely to manifolds. -/
theorem contDiffWithinAt_localInvariantProp (n : ℕ∞) :
(contDiffGroupoid ∞ I).LocalInvariantProp (contDiffGroupoid ∞ I')
(ContDiffWithinAtProp I I' n) where
is_local {s x u f} u_open xu := by
have : I.symm ⁻¹' (s ∩ u) ∩ range I = I.symm ⁻¹' s ∩ range I ∩ I.symm ⁻¹' u := by
simp only [inter_right_comm, preimage_inter]
rw [ContDiffWithinAtProp, ContDiffWithinAtProp, this]
symm
apply contDiffWithinAt_inter
have : u ∈ 𝓝 (I.symm (I x)) := by
rw [ModelWithCorners.left_inv]
exact u_open.mem_nhds xu
apply ContinuousAt.preimage_mem_nhds I.continuous_symm.continuousAt this
right_invariance' {s x f e} he hx h := by
rw [ContDiffWithinAtProp] at h ⊢
have : I x = (I ∘ e.symm ∘ I.symm) (I (e x)) := by simp only [hx, mfld_simps]
rw [this] at h
have : I (e x) ∈ I.symm ⁻¹' e.target ∩ range I := by simp only [hx, mfld_simps]
have := (mem_groupoid_of_pregroupoid.2 he).2.contDiffWithinAt this
convert (h.comp' _ (this.of_le le_top)).mono_of_mem _ using 1
· ext y; simp only [mfld_simps]
refine mem_nhdsWithin.mpr
⟨I.symm ⁻¹' e.target, e.open_target.preimage I.continuous_symm, by
simp_rw [mem_preimage, I.left_inv, e.mapsTo hx], ?_⟩
mfld_set_tac
congr_of_forall {s x f g} h hx hf := by
apply hf.congr
· intro y hy
simp only [mfld_simps] at hy
simp only [h, hy, mfld_simps]
· simp only [hx, mfld_simps]
left_invariance' {s x f e'} he' hs hx h := by
rw [ContDiffWithinAtProp] at h ⊢
have A : (I' ∘ f ∘ I.symm) (I x) ∈ I'.symm ⁻¹' e'.source ∩ range I' := by
simp only [hx, mfld_simps]
have := (mem_groupoid_of_pregroupoid.2 he').1.contDiffWithinAt A
convert (this.of_le le_top).comp _ h _
· ext y; simp only [mfld_simps]
· intro y hy; simp only [mfld_simps] at hy; simpa only [hy, mfld_simps] using hs hy.1
#align cont_diff_within_at_local_invariant_prop contDiffWithinAt_localInvariantProp
theorem contDiffWithinAtProp_mono_of_mem (n : ℕ∞) ⦃s x t⦄ ⦃f : H → H'⦄ (hts : s ∈ 𝓝[t] x)
(h : ContDiffWithinAtProp I I' n f s x) : ContDiffWithinAtProp I I' n f t x := by
refine h.mono_of_mem ?_
refine inter_mem ?_ (mem_of_superset self_mem_nhdsWithin inter_subset_right)
rwa [← Filter.mem_map, ← I.image_eq, I.symm_map_nhdsWithin_image]
#align cont_diff_within_at_prop_mono_of_mem contDiffWithinAtProp_mono_of_mem
theorem contDiffWithinAtProp_id (x : H) : ContDiffWithinAtProp I I n id univ x := by
simp only [ContDiffWithinAtProp, id_comp, preimage_univ, univ_inter]
have : ContDiffWithinAt 𝕜 n id (range I) (I x) := contDiff_id.contDiffAt.contDiffWithinAt
refine this.congr (fun y hy => ?_) ?_
· simp only [ModelWithCorners.right_inv I hy, mfld_simps]
· simp only [mfld_simps]
#align cont_diff_within_at_prop_id contDiffWithinAtProp_id
/-- A function is `n` times continuously differentiable within a set at a point in a manifold if
it is continuous and it is `n` times continuously differentiable in this set around this point, when
read in the preferred chart at this point. -/
def ContMDiffWithinAt (n : ℕ∞) (f : M → M') (s : Set M) (x : M) :=
LiftPropWithinAt (ContDiffWithinAtProp I I' n) f s x
#align cont_mdiff_within_at ContMDiffWithinAt
/-- Abbreviation for `ContMDiffWithinAt I I' ⊤ f s x`. See also documentation for `Smooth`.
-/
abbrev SmoothWithinAt (f : M → M') (s : Set M) (x : M) :=
ContMDiffWithinAt I I' ⊤ f s x
#align smooth_within_at SmoothWithinAt
/-- A function is `n` times continuously differentiable at a point in a manifold if
it is continuous and it is `n` times continuously differentiable around this point, when
read in the preferred chart at this point. -/
def ContMDiffAt (n : ℕ∞) (f : M → M') (x : M) :=
ContMDiffWithinAt I I' n f univ x
#align cont_mdiff_at ContMDiffAt
theorem contMDiffAt_iff {n : ℕ∞} {f : M → M'} {x : M} :
ContMDiffAt I I' n f x ↔
ContinuousAt f x ∧
ContDiffWithinAt 𝕜 n (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm) (range I)
(extChartAt I x x) :=
liftPropAt_iff.trans <| by rw [ContDiffWithinAtProp, preimage_univ, univ_inter]; rfl
#align cont_mdiff_at_iff contMDiffAt_iff
/-- Abbreviation for `ContMDiffAt I I' ⊤ f x`. See also documentation for `Smooth`. -/
abbrev SmoothAt (f : M → M') (x : M) :=
ContMDiffAt I I' ⊤ f x
#align smooth_at SmoothAt
/-- A function is `n` times continuously differentiable in a set of a manifold if it is continuous
and, for any pair of points, it is `n` times continuously differentiable on this set in the charts
around these points. -/
def ContMDiffOn (n : ℕ∞) (f : M → M') (s : Set M) :=
∀ x ∈ s, ContMDiffWithinAt I I' n f s x
#align cont_mdiff_on ContMDiffOn
/-- Abbreviation for `ContMDiffOn I I' ⊤ f s`. See also documentation for `Smooth`. -/
abbrev SmoothOn (f : M → M') (s : Set M) :=
ContMDiffOn I I' ⊤ f s
#align smooth_on SmoothOn
/-- A function is `n` times continuously differentiable in a manifold if it is continuous
and, for any pair of points, it is `n` times continuously differentiable in the charts
around these points. -/
def ContMDiff (n : ℕ∞) (f : M → M') :=
∀ x, ContMDiffAt I I' n f x
#align cont_mdiff ContMDiff
/-- Abbreviation for `ContMDiff I I' ⊤ f`.
Short note to work with these abbreviations: a lemma of the form `ContMDiffFoo.bar` will
apply fine to an assumption `SmoothFoo` using dot notation or normal notation.
If the consequence `bar` of the lemma involves `ContDiff`, it is still better to restate
the lemma replacing `ContDiff` with `Smooth` both in the assumption and in the conclusion,
to make it possible to use `Smooth` consistently.
This also applies to `SmoothAt`, `SmoothOn` and `SmoothWithinAt`. -/
abbrev Smooth (f : M → M') :=
ContMDiff I I' ⊤ f
#align smooth Smooth
variable {I I'}
/-! ### Deducing smoothness from higher smoothness -/
theorem ContMDiffWithinAt.of_le (hf : ContMDiffWithinAt I I' n f s x) (le : m ≤ n) :
ContMDiffWithinAt I I' m f s x := by
simp only [ContMDiffWithinAt, LiftPropWithinAt] at hf ⊢
exact ⟨hf.1, hf.2.of_le le⟩
#align cont_mdiff_within_at.of_le ContMDiffWithinAt.of_le
theorem ContMDiffAt.of_le (hf : ContMDiffAt I I' n f x) (le : m ≤ n) : ContMDiffAt I I' m f x :=
ContMDiffWithinAt.of_le hf le
#align cont_mdiff_at.of_le ContMDiffAt.of_le
theorem ContMDiffOn.of_le (hf : ContMDiffOn I I' n f s) (le : m ≤ n) : ContMDiffOn I I' m f s :=
fun x hx => (hf x hx).of_le le
#align cont_mdiff_on.of_le ContMDiffOn.of_le
theorem ContMDiff.of_le (hf : ContMDiff I I' n f) (le : m ≤ n) : ContMDiff I I' m f := fun x =>
(hf x).of_le le
#align cont_mdiff.of_le ContMDiff.of_le
/-! ### Basic properties of smooth functions between manifolds -/
theorem ContMDiff.smooth (h : ContMDiff I I' ⊤ f) : Smooth I I' f :=
h
#align cont_mdiff.smooth ContMDiff.smooth
theorem Smooth.contMDiff (h : Smooth I I' f) : ContMDiff I I' n f :=
h.of_le le_top
#align smooth.cont_mdiff Smooth.contMDiff
theorem ContMDiffOn.smoothOn (h : ContMDiffOn I I' ⊤ f s) : SmoothOn I I' f s :=
h
#align cont_mdiff_on.smooth_on ContMDiffOn.smoothOn
theorem SmoothOn.contMDiffOn (h : SmoothOn I I' f s) : ContMDiffOn I I' n f s :=
h.of_le le_top
#align smooth_on.cont_mdiff_on SmoothOn.contMDiffOn
theorem ContMDiffAt.smoothAt (h : ContMDiffAt I I' ⊤ f x) : SmoothAt I I' f x :=
h
#align cont_mdiff_at.smooth_at ContMDiffAt.smoothAt
theorem SmoothAt.contMDiffAt (h : SmoothAt I I' f x) : ContMDiffAt I I' n f x :=
h.of_le le_top
#align smooth_at.cont_mdiff_at SmoothAt.contMDiffAt
theorem ContMDiffWithinAt.smoothWithinAt (h : ContMDiffWithinAt I I' ⊤ f s x) :
SmoothWithinAt I I' f s x :=
h
#align cont_mdiff_within_at.smooth_within_at ContMDiffWithinAt.smoothWithinAt
theorem SmoothWithinAt.contMDiffWithinAt (h : SmoothWithinAt I I' f s x) :
ContMDiffWithinAt I I' n f s x :=
h.of_le le_top
#align smooth_within_at.cont_mdiff_within_at SmoothWithinAt.contMDiffWithinAt
theorem ContMDiff.contMDiffAt (h : ContMDiff I I' n f) : ContMDiffAt I I' n f x :=
h x
#align cont_mdiff.cont_mdiff_at ContMDiff.contMDiffAt
theorem Smooth.smoothAt (h : Smooth I I' f) : SmoothAt I I' f x :=
ContMDiff.contMDiffAt h
#align smooth.smooth_at Smooth.smoothAt
theorem contMDiffWithinAt_univ : ContMDiffWithinAt I I' n f univ x ↔ ContMDiffAt I I' n f x :=
Iff.rfl
#align cont_mdiff_within_at_univ contMDiffWithinAt_univ
theorem smoothWithinAt_univ : SmoothWithinAt I I' f univ x ↔ SmoothAt I I' f x :=
contMDiffWithinAt_univ
#align smooth_within_at_univ smoothWithinAt_univ
theorem contMDiffOn_univ : ContMDiffOn I I' n f univ ↔ ContMDiff I I' n f := by
simp only [ContMDiffOn, ContMDiff, contMDiffWithinAt_univ, forall_prop_of_true, mem_univ]
#align cont_mdiff_on_univ contMDiffOn_univ
theorem smoothOn_univ : SmoothOn I I' f univ ↔ Smooth I I' f :=
contMDiffOn_univ
#align smooth_on_univ smoothOn_univ
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in the corresponding extended chart. -/
theorem contMDiffWithinAt_iff :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x) := by
simp_rw [ContMDiffWithinAt, liftPropWithinAt_iff']; rfl
#align cont_mdiff_within_at_iff contMDiffWithinAt_iff
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in the corresponding extended chart. This form states smoothness of `f`
written in such a way that the set is restricted to lie within the domain/codomain of the
corresponding charts.
Even though this expression is more complicated than the one in `contMDiffWithinAt_iff`, it is
a smaller set, but their germs at `extChartAt I x x` are equal. It is sometimes useful to rewrite
using this in the goal.
-/
theorem contMDiffWithinAt_iff' :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).target ∩
(extChartAt I x).symm ⁻¹' (s ∩ f ⁻¹' (extChartAt I' (f x)).source))
(extChartAt I x x) := by
simp only [ContMDiffWithinAt, liftPropWithinAt_iff']
exact and_congr_right fun hc => contDiffWithinAt_congr_nhds <|
hc.nhdsWithin_extChartAt_symm_preimage_inter_range I I'
#align cont_mdiff_within_at_iff' contMDiffWithinAt_iff'
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in the corresponding extended chart in the target. -/
theorem contMDiffWithinAt_iff_target :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧ ContMDiffWithinAt I 𝓘(𝕜, E') n (extChartAt I' (f x) ∘ f) s x := by
simp_rw [ContMDiffWithinAt, liftPropWithinAt_iff', ← and_assoc]
have cont :
ContinuousWithinAt f s x ∧ ContinuousWithinAt (extChartAt I' (f x) ∘ f) s x ↔
ContinuousWithinAt f s x :=
and_iff_left_of_imp <| (continuousAt_extChartAt _ _).comp_continuousWithinAt
simp_rw [cont, ContDiffWithinAtProp, extChartAt, PartialHomeomorph.extend, PartialEquiv.coe_trans,
ModelWithCorners.toPartialEquiv_coe, PartialHomeomorph.coe_coe, modelWithCornersSelf_coe,
chartAt_self_eq, PartialHomeomorph.refl_apply, id_comp]
rfl
#align cont_mdiff_within_at_iff_target contMDiffWithinAt_iff_target
theorem smoothWithinAt_iff :
SmoothWithinAt I I' f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 ∞ (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x) :=
contMDiffWithinAt_iff
#align smooth_within_at_iff smoothWithinAt_iff
theorem smoothWithinAt_iff_target :
SmoothWithinAt I I' f s x ↔
ContinuousWithinAt f s x ∧ SmoothWithinAt I 𝓘(𝕜, E') (extChartAt I' (f x) ∘ f) s x :=
contMDiffWithinAt_iff_target
#align smooth_within_at_iff_target smoothWithinAt_iff_target
theorem contMDiffAt_iff_target {x : M} :
ContMDiffAt I I' n f x ↔
ContinuousAt f x ∧ ContMDiffAt I 𝓘(𝕜, E') n (extChartAt I' (f x) ∘ f) x := by
rw [ContMDiffAt, ContMDiffAt, contMDiffWithinAt_iff_target, continuousWithinAt_univ]
#align cont_mdiff_at_iff_target contMDiffAt_iff_target
theorem smoothAt_iff_target {x : M} :
SmoothAt I I' f x ↔ ContinuousAt f x ∧ SmoothAt I 𝓘(𝕜, E') (extChartAt I' (f x) ∘ f) x :=
contMDiffAt_iff_target
#align smooth_at_iff_target smoothAt_iff_target
theorem contMDiffWithinAt_iff_of_mem_maximalAtlas {x : M} (he : e ∈ maximalAtlas I M)
(he' : e' ∈ maximalAtlas I' M') (hx : x ∈ e.source) (hy : f x ∈ e'.source) :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (e'.extend I' ∘ f ∘ (e.extend I).symm)
((e.extend I).symm ⁻¹' s ∩ range I) (e.extend I x) :=
(contDiffWithinAt_localInvariantProp I I' n).liftPropWithinAt_indep_chart he hx he' hy
#align cont_mdiff_within_at_iff_of_mem_maximal_atlas contMDiffWithinAt_iff_of_mem_maximalAtlas
/-- An alternative formulation of `contMDiffWithinAt_iff_of_mem_maximalAtlas`
if the set if `s` lies in `e.source`. -/
theorem contMDiffWithinAt_iff_image {x : M} (he : e ∈ maximalAtlas I M)
(he' : e' ∈ maximalAtlas I' M') (hs : s ⊆ e.source) (hx : x ∈ e.source) (hy : f x ∈ e'.source) :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (e'.extend I' ∘ f ∘ (e.extend I).symm) (e.extend I '' s)
(e.extend I x) := by
rw [contMDiffWithinAt_iff_of_mem_maximalAtlas he he' hx hy, and_congr_right_iff]
refine fun _ => contDiffWithinAt_congr_nhds ?_
simp_rw [nhdsWithin_eq_iff_eventuallyEq, e.extend_symm_preimage_inter_range_eventuallyEq I hs hx]
#align cont_mdiff_within_at_iff_image contMDiffWithinAt_iff_image
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in any chart containing that point. -/
theorem contMDiffWithinAt_iff_of_mem_source {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source)
(hy : f x' ∈ (chartAt H' y).source) :
ContMDiffWithinAt I I' n f s x' ↔
ContinuousWithinAt f s x' ∧
ContDiffWithinAt 𝕜 n (extChartAt I' y ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x') :=
contMDiffWithinAt_iff_of_mem_maximalAtlas (chart_mem_maximalAtlas _ x)
(chart_mem_maximalAtlas _ y) hx hy
#align cont_mdiff_within_at_iff_of_mem_source contMDiffWithinAt_iff_of_mem_source
theorem contMDiffWithinAt_iff_of_mem_source' {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source)
(hy : f x' ∈ (chartAt H' y).source) :
ContMDiffWithinAt I I' n f s x' ↔
ContinuousWithinAt f s x' ∧
ContDiffWithinAt 𝕜 n (extChartAt I' y ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' (s ∩ f ⁻¹' (extChartAt I' y).source))
(extChartAt I x x') := by
refine (contMDiffWithinAt_iff_of_mem_source hx hy).trans ?_
rw [← extChartAt_source I] at hx
rw [← extChartAt_source I'] at hy
rw [and_congr_right_iff]
set e := extChartAt I x; set e' := extChartAt I' (f x)
refine fun hc => contDiffWithinAt_congr_nhds ?_
rw [← e.image_source_inter_eq', ← map_extChartAt_nhdsWithin_eq_image' I hx, ←
map_extChartAt_nhdsWithin' I hx, inter_comm, nhdsWithin_inter_of_mem]
exact hc (extChartAt_source_mem_nhds' _ hy)
#align cont_mdiff_within_at_iff_of_mem_source' contMDiffWithinAt_iff_of_mem_source'
theorem contMDiffAt_iff_of_mem_source {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source)
(hy : f x' ∈ (chartAt H' y).source) :
ContMDiffAt I I' n f x' ↔
ContinuousAt f x' ∧
ContDiffWithinAt 𝕜 n (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) (range I)
(extChartAt I x x') :=
(contMDiffWithinAt_iff_of_mem_source hx hy).trans <| by
rw [continuousWithinAt_univ, preimage_univ, univ_inter]
#align cont_mdiff_at_iff_of_mem_source contMDiffAt_iff_of_mem_source
theorem contMDiffWithinAt_iff_target_of_mem_source {x : M} {y : M'}
(hy : f x ∈ (chartAt H' y).source) :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧ ContMDiffWithinAt I 𝓘(𝕜, E') n (extChartAt I' y ∘ f) s x := by
simp_rw [ContMDiffWithinAt]
rw [(contDiffWithinAt_localInvariantProp I I' n).liftPropWithinAt_indep_chart_target
(chart_mem_maximalAtlas I' y) hy,
and_congr_right]
intro hf
simp_rw [StructureGroupoid.liftPropWithinAt_self_target]
simp_rw [((chartAt H' y).continuousAt hy).comp_continuousWithinAt hf]
rw [← extChartAt_source I'] at hy
simp_rw [(continuousAt_extChartAt' I' hy).comp_continuousWithinAt hf]
rfl
#align cont_mdiff_within_at_iff_target_of_mem_source contMDiffWithinAt_iff_target_of_mem_source
theorem contMDiffAt_iff_target_of_mem_source {x : M} {y : M'} (hy : f x ∈ (chartAt H' y).source) :
ContMDiffAt I I' n f x ↔
ContinuousAt f x ∧ ContMDiffAt I 𝓘(𝕜, E') n (extChartAt I' y ∘ f) x := by
rw [ContMDiffAt, contMDiffWithinAt_iff_target_of_mem_source hy, continuousWithinAt_univ,
ContMDiffAt]
#align cont_mdiff_at_iff_target_of_mem_source contMDiffAt_iff_target_of_mem_source
theorem contMDiffWithinAt_iff_source_of_mem_maximalAtlas (he : e ∈ maximalAtlas I M)
(hx : x ∈ e.source) :
ContMDiffWithinAt I I' n f s x ↔
ContMDiffWithinAt 𝓘(𝕜, E) I' n (f ∘ (e.extend I).symm) ((e.extend I).symm ⁻¹' s ∩ range I)
(e.extend I x) := by
have h2x := hx; rw [← e.extend_source I] at h2x
simp_rw [ContMDiffWithinAt,
(contDiffWithinAt_localInvariantProp I I' n).liftPropWithinAt_indep_chart_source he hx,
StructureGroupoid.liftPropWithinAt_self_source,
e.extend_symm_continuousWithinAt_comp_right_iff, contDiffWithinAtProp_self_source,
ContDiffWithinAtProp, Function.comp, e.left_inv hx, (e.extend I).left_inv h2x]
rfl
#align cont_mdiff_within_at_iff_source_of_mem_maximal_atlas contMDiffWithinAt_iff_source_of_mem_maximalAtlas
theorem contMDiffWithinAt_iff_source_of_mem_source {x' : M} (hx' : x' ∈ (chartAt H x).source) :
ContMDiffWithinAt I I' n f s x' ↔
ContMDiffWithinAt 𝓘(𝕜, E) I' n (f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x') :=
contMDiffWithinAt_iff_source_of_mem_maximalAtlas (chart_mem_maximalAtlas I x) hx'
#align cont_mdiff_within_at_iff_source_of_mem_source contMDiffWithinAt_iff_source_of_mem_source
| Mathlib/Geometry/Manifold/ContMDiff/Defs.lean | 494 | 497 | theorem contMDiffAt_iff_source_of_mem_source {x' : M} (hx' : x' ∈ (chartAt H x).source) :
ContMDiffAt I I' n f x' ↔
ContMDiffWithinAt 𝓘(𝕜, E) I' n (f ∘ (extChartAt I x).symm) (range I) (extChartAt I x x') := by |
simp_rw [ContMDiffAt, contMDiffWithinAt_iff_source_of_mem_source hx', preimage_univ, univ_inter]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johannes Hölzl, Yury G. Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.GeomSum
import Mathlib.Order.Filter.Archimedean
import Mathlib.Order.Iterate
import Mathlib.Topology.Algebra.Algebra
import Mathlib.Topology.Algebra.InfiniteSum.Real
#align_import analysis.specific_limits.basic from "leanprover-community/mathlib"@"57ac39bd365c2f80589a700f9fbb664d3a1a30c2"
/-!
# A collection of specific limit computations
This file, by design, is independent of `NormedSpace` in the import hierarchy. It contains
important specific limit computations in metric spaces, in ordered rings/fields, and in specific
instances of these such as `ℝ`, `ℝ≥0` and `ℝ≥0∞`.
-/
noncomputable section
open scoped Classical
open Set Function Filter Finset Metric
open scoped Classical
open Topology Nat uniformity NNReal ENNReal
variable {α : Type*} {β : Type*} {ι : Type*}
theorem tendsto_inverse_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
tendsto_inv_atTop_zero.comp tendsto_natCast_atTop_atTop
#align tendsto_inverse_at_top_nhds_0_nat tendsto_inverse_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_inverse_atTop_nhds_0_nat := tendsto_inverse_atTop_nhds_zero_nat
theorem tendsto_const_div_atTop_nhds_zero_nat (C : ℝ) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
simpa only [mul_zero] using tendsto_const_nhds.mul tendsto_inverse_atTop_nhds_zero_nat
#align tendsto_const_div_at_top_nhds_0_nat tendsto_const_div_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_const_div_atTop_nhds_0_nat := tendsto_const_div_atTop_nhds_zero_nat
theorem tendsto_one_div_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ 1/(n : ℝ)) atTop (𝓝 0) :=
tendsto_const_div_atTop_nhds_zero_nat 1
@[deprecated (since := "2024-01-31")]
alias tendsto_one_div_atTop_nhds_0_nat := tendsto_one_div_atTop_nhds_zero_nat
theorem NNReal.tendsto_inverse_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
rw [← NNReal.tendsto_coe]
exact _root_.tendsto_inverse_atTop_nhds_zero_nat
#align nnreal.tendsto_inverse_at_top_nhds_0_nat NNReal.tendsto_inverse_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_inverse_atTop_nhds_0_nat := NNReal.tendsto_inverse_atTop_nhds_zero_nat
theorem NNReal.tendsto_const_div_atTop_nhds_zero_nat (C : ℝ≥0) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
simpa using tendsto_const_nhds.mul NNReal.tendsto_inverse_atTop_nhds_zero_nat
#align nnreal.tendsto_const_div_at_top_nhds_0_nat NNReal.tendsto_const_div_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_const_div_atTop_nhds_0_nat := NNReal.tendsto_const_div_atTop_nhds_zero_nat
theorem tendsto_one_div_add_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ ↦ 1 / ((n : ℝ) + 1)) atTop (𝓝 0) :=
suffices Tendsto (fun n : ℕ ↦ 1 / (↑(n + 1) : ℝ)) atTop (𝓝 0) by simpa
(tendsto_add_atTop_iff_nat 1).2 (_root_.tendsto_const_div_atTop_nhds_zero_nat 1)
#align tendsto_one_div_add_at_top_nhds_0_nat tendsto_one_div_add_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_one_div_add_atTop_nhds_0_nat := tendsto_one_div_add_atTop_nhds_zero_nat
theorem NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜]
[Algebra ℝ≥0 𝕜] [TopologicalSpace 𝕜] [ContinuousSMul ℝ≥0 𝕜] :
Tendsto (algebraMap ℝ≥0 𝕜 ∘ fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
convert (continuous_algebraMap ℝ≥0 𝕜).continuousAt.tendsto.comp
tendsto_inverse_atTop_nhds_zero_nat
rw [map_zero]
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_algebraMap_inverse_atTop_nhds_0_nat :=
NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat
theorem tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜] [Algebra ℝ 𝕜]
[TopologicalSpace 𝕜] [ContinuousSMul ℝ 𝕜] :
Tendsto (algebraMap ℝ 𝕜 ∘ fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat 𝕜
@[deprecated (since := "2024-01-31")]
alias tendsto_algebraMap_inverse_atTop_nhds_0_nat :=
_root_.tendsto_algebraMap_inverse_atTop_nhds_zero_nat
/-- The limit of `n / (n + x)` is 1, for any constant `x` (valid in `ℝ` or any topological division
algebra over `ℝ`, e.g., `ℂ`).
TODO: introduce a typeclass saying that `1 / n` tends to 0 at top, making it possible to get this
statement simultaneously on `ℚ`, `ℝ` and `ℂ`. -/
theorem tendsto_natCast_div_add_atTop {𝕜 : Type*} [DivisionRing 𝕜] [TopologicalSpace 𝕜]
[CharZero 𝕜] [Algebra ℝ 𝕜] [ContinuousSMul ℝ 𝕜] [TopologicalDivisionRing 𝕜] (x : 𝕜) :
Tendsto (fun n : ℕ ↦ (n : 𝕜) / (n + x)) atTop (𝓝 1) := by
convert Tendsto.congr' ((eventually_ne_atTop 0).mp (eventually_of_forall fun n hn ↦ _)) _
· exact fun n : ℕ ↦ 1 / (1 + x / n)
· field_simp [Nat.cast_ne_zero.mpr hn]
· have : 𝓝 (1 : 𝕜) = 𝓝 (1 / (1 + x * (0 : 𝕜))) := by
rw [mul_zero, add_zero, div_one]
rw [this]
refine tendsto_const_nhds.div (tendsto_const_nhds.add ?_) (by simp)
simp_rw [div_eq_mul_inv]
refine tendsto_const_nhds.mul ?_
have := ((continuous_algebraMap ℝ 𝕜).tendsto _).comp tendsto_inverse_atTop_nhds_zero_nat
rw [map_zero, Filter.tendsto_atTop'] at this
refine Iff.mpr tendsto_atTop' ?_
intros
simp_all only [comp_apply, map_inv₀, map_natCast]
#align tendsto_coe_nat_div_add_at_top tendsto_natCast_div_add_atTop
/-! ### Powers -/
theorem tendsto_add_one_pow_atTop_atTop_of_pos [LinearOrderedSemiring α] [Archimedean α] {r : α}
(h : 0 < r) : Tendsto (fun n : ℕ ↦ (r + 1) ^ n) atTop atTop :=
tendsto_atTop_atTop_of_monotone' (fun _ _ ↦ pow_le_pow_right <| le_add_of_nonneg_left h.le) <|
not_bddAbove_iff.2 fun _ ↦ Set.exists_range_iff.2 <| add_one_pow_unbounded_of_pos _ h
#align tendsto_add_one_pow_at_top_at_top_of_pos tendsto_add_one_pow_atTop_atTop_of_pos
theorem tendsto_pow_atTop_atTop_of_one_lt [LinearOrderedRing α] [Archimedean α] {r : α}
(h : 1 < r) : Tendsto (fun n : ℕ ↦ r ^ n) atTop atTop :=
sub_add_cancel r 1 ▸ tendsto_add_one_pow_atTop_atTop_of_pos (sub_pos.2 h)
#align tendsto_pow_at_top_at_top_of_one_lt tendsto_pow_atTop_atTop_of_one_lt
theorem Nat.tendsto_pow_atTop_atTop_of_one_lt {m : ℕ} (h : 1 < m) :
Tendsto (fun n : ℕ ↦ m ^ n) atTop atTop :=
tsub_add_cancel_of_le (le_of_lt h) ▸ tendsto_add_one_pow_atTop_atTop_of_pos (tsub_pos_of_lt h)
#align nat.tendsto_pow_at_top_at_top_of_one_lt Nat.tendsto_pow_atTop_atTop_of_one_lt
theorem tendsto_pow_atTop_nhds_zero_of_lt_one {𝕜 : Type*} [LinearOrderedField 𝕜] [Archimedean 𝕜]
[TopologicalSpace 𝕜] [OrderTopology 𝕜] {r : 𝕜} (h₁ : 0 ≤ r) (h₂ : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) :=
h₁.eq_or_lt.elim
(fun hr ↦ (tendsto_add_atTop_iff_nat 1).mp <| by
simp [_root_.pow_succ, ← hr, tendsto_const_nhds])
(fun hr ↦
have := one_lt_inv hr h₂ |> tendsto_pow_atTop_atTop_of_one_lt
(tendsto_inv_atTop_zero.comp this).congr fun n ↦ by simp)
#align tendsto_pow_at_top_nhds_0_of_lt_1 tendsto_pow_atTop_nhds_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhds_0_of_lt_1 := tendsto_pow_atTop_nhds_zero_of_lt_one
@[simp] theorem tendsto_pow_atTop_nhds_zero_iff {𝕜 : Type*} [LinearOrderedField 𝕜] [Archimedean 𝕜]
[TopologicalSpace 𝕜] [OrderTopology 𝕜] {r : 𝕜} :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) ↔ |r| < 1 := by
rw [tendsto_zero_iff_abs_tendsto_zero]
refine ⟨fun h ↦ by_contra (fun hr_le ↦ ?_), fun h ↦ ?_⟩
· by_cases hr : 1 = |r|
· replace h : Tendsto (fun n : ℕ ↦ |r|^n) atTop (𝓝 0) := by simpa only [← abs_pow, h]
simp only [hr.symm, one_pow] at h
exact zero_ne_one <| tendsto_nhds_unique h tendsto_const_nhds
· apply @not_tendsto_nhds_of_tendsto_atTop 𝕜 ℕ _ _ _ _ atTop _ (fun n ↦ |r| ^ n) _ 0 _
· refine (pow_right_strictMono <| lt_of_le_of_ne (le_of_not_lt hr_le)
hr).monotone.tendsto_atTop_atTop (fun b ↦ ?_)
obtain ⟨n, hn⟩ := (pow_unbounded_of_one_lt b (lt_of_le_of_ne (le_of_not_lt hr_le) hr))
exact ⟨n, le_of_lt hn⟩
· simpa only [← abs_pow]
· simpa only [← abs_pow] using (tendsto_pow_atTop_nhds_zero_of_lt_one (abs_nonneg r)) h
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhds_0_iff := tendsto_pow_atTop_nhds_zero_iff
theorem tendsto_pow_atTop_nhdsWithin_zero_of_lt_one {𝕜 : Type*} [LinearOrderedField 𝕜]
[Archimedean 𝕜] [TopologicalSpace 𝕜] [OrderTopology 𝕜] {r : 𝕜} (h₁ : 0 < r) (h₂ : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝[>] 0) :=
tendsto_inf.2
⟨tendsto_pow_atTop_nhds_zero_of_lt_one h₁.le h₂,
tendsto_principal.2 <| eventually_of_forall fun _ ↦ pow_pos h₁ _⟩
#align tendsto_pow_at_top_nhds_within_0_of_lt_1 tendsto_pow_atTop_nhdsWithin_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhdsWithin_0_of_lt_1 := tendsto_pow_atTop_nhdsWithin_zero_of_lt_one
theorem uniformity_basis_dist_pow_of_lt_one {α : Type*} [PseudoMetricSpace α] {r : ℝ} (h₀ : 0 < r)
(h₁ : r < 1) :
(uniformity α).HasBasis (fun _ : ℕ ↦ True) fun k ↦ { p : α × α | dist p.1 p.2 < r ^ k } :=
Metric.mk_uniformity_basis (fun _ _ ↦ pow_pos h₀ _) fun _ ε0 ↦
(exists_pow_lt_of_lt_one ε0 h₁).imp fun _ hk ↦ ⟨trivial, hk.le⟩
#align uniformity_basis_dist_pow_of_lt_1 uniformity_basis_dist_pow_of_lt_one
@[deprecated (since := "2024-01-31")]
alias uniformity_basis_dist_pow_of_lt_1 := uniformity_basis_dist_pow_of_lt_one
theorem geom_lt {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) {n : ℕ} (hn : 0 < n)
(h : ∀ k < n, c * u k < u (k + 1)) : c ^ n * u 0 < u n := by
apply (monotone_mul_left_of_nonneg hc).seq_pos_lt_seq_of_le_of_lt hn _ _ h
· simp
· simp [_root_.pow_succ', mul_assoc, le_refl]
#align geom_lt geom_lt
theorem geom_le {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) (n : ℕ) (h : ∀ k < n, c * u k ≤ u (k + 1)) :
c ^ n * u 0 ≤ u n := by
apply (monotone_mul_left_of_nonneg hc).seq_le_seq n _ _ h <;>
simp [_root_.pow_succ', mul_assoc, le_refl]
#align geom_le geom_le
theorem lt_geom {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) {n : ℕ} (hn : 0 < n)
(h : ∀ k < n, u (k + 1) < c * u k) : u n < c ^ n * u 0 := by
apply (monotone_mul_left_of_nonneg hc).seq_pos_lt_seq_of_lt_of_le hn _ h _
· simp
· simp [_root_.pow_succ', mul_assoc, le_refl]
#align lt_geom lt_geom
theorem le_geom {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) (n : ℕ) (h : ∀ k < n, u (k + 1) ≤ c * u k) :
u n ≤ c ^ n * u 0 := by
apply (monotone_mul_left_of_nonneg hc).seq_le_seq n _ h _ <;>
simp [_root_.pow_succ', mul_assoc, le_refl]
#align le_geom le_geom
/-- If a sequence `v` of real numbers satisfies `k * v n ≤ v (n+1)` with `1 < k`,
then it goes to +∞. -/
theorem tendsto_atTop_of_geom_le {v : ℕ → ℝ} {c : ℝ} (h₀ : 0 < v 0) (hc : 1 < c)
(hu : ∀ n, c * v n ≤ v (n + 1)) : Tendsto v atTop atTop :=
(tendsto_atTop_mono fun n ↦ geom_le (zero_le_one.trans hc.le) n fun k _ ↦ hu k) <|
(tendsto_pow_atTop_atTop_of_one_lt hc).atTop_mul_const h₀
#align tendsto_at_top_of_geom_le tendsto_atTop_of_geom_le
theorem NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one {r : ℝ≥0} (hr : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) :=
NNReal.tendsto_coe.1 <| by
simp only [NNReal.coe_pow, NNReal.coe_zero,
_root_.tendsto_pow_atTop_nhds_zero_of_lt_one r.coe_nonneg hr]
#align nnreal.tendsto_pow_at_top_nhds_0_of_lt_1 NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_pow_atTop_nhds_0_of_lt_1 := NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[simp]
protected theorem NNReal.tendsto_pow_atTop_nhds_zero_iff {r : ℝ≥0} :
Tendsto (fun n : ℕ => r ^ n) atTop (𝓝 0) ↔ r < 1 :=
⟨fun h => by simpa [coe_pow, coe_zero, abs_eq, coe_lt_one, val_eq_coe] using
tendsto_pow_atTop_nhds_zero_iff.mp <| tendsto_coe.mpr h, tendsto_pow_atTop_nhds_zero_of_lt_one⟩
theorem ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one {r : ℝ≥0∞} (hr : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) := by
rcases ENNReal.lt_iff_exists_coe.1 hr with ⟨r, rfl, hr'⟩
rw [← ENNReal.coe_zero]
norm_cast at *
apply NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one hr
#align ennreal.tendsto_pow_at_top_nhds_0_of_lt_1 ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias ENNReal.tendsto_pow_atTop_nhds_0_of_lt_1 := ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[simp]
protected theorem ENNReal.tendsto_pow_atTop_nhds_zero_iff {r : ℝ≥0∞} :
Tendsto (fun n : ℕ => r ^ n) atTop (𝓝 0) ↔ r < 1 := by
refine ⟨fun h ↦ ?_, tendsto_pow_atTop_nhds_zero_of_lt_one⟩
lift r to NNReal
· refine fun hr ↦ top_ne_zero (tendsto_nhds_unique (EventuallyEq.tendsto ?_) (hr ▸ h))
exact eventually_atTop.mpr ⟨1, fun _ hn ↦ pow_eq_top_iff.mpr ⟨rfl, Nat.pos_iff_ne_zero.mp hn⟩⟩
rw [← coe_zero] at h
norm_cast at h ⊢
exact NNReal.tendsto_pow_atTop_nhds_zero_iff.mp h
/-! ### Geometric series-/
section Geometric
theorem hasSum_geometric_of_lt_one {r : ℝ} (h₁ : 0 ≤ r) (h₂ : r < 1) :
HasSum (fun n : ℕ ↦ r ^ n) (1 - r)⁻¹ :=
have : r ≠ 1 := ne_of_lt h₂
have : Tendsto (fun n ↦ (r ^ n - 1) * (r - 1)⁻¹) atTop (𝓝 ((0 - 1) * (r - 1)⁻¹)) :=
((tendsto_pow_atTop_nhds_zero_of_lt_one h₁ h₂).sub tendsto_const_nhds).mul tendsto_const_nhds
(hasSum_iff_tendsto_nat_of_nonneg (pow_nonneg h₁) _).mpr <| by
simp_all [neg_inv, geom_sum_eq, div_eq_mul_inv]
#align has_sum_geometric_of_lt_1 hasSum_geometric_of_lt_one
@[deprecated (since := "2024-01-31")] alias hasSum_geometric_of_lt_1 := hasSum_geometric_of_lt_one
theorem summable_geometric_of_lt_one {r : ℝ} (h₁ : 0 ≤ r) (h₂ : r < 1) :
Summable fun n : ℕ ↦ r ^ n :=
⟨_, hasSum_geometric_of_lt_one h₁ h₂⟩
#align summable_geometric_of_lt_1 summable_geometric_of_lt_one
@[deprecated (since := "2024-01-31")]
alias summable_geometric_of_lt_1 := summable_geometric_of_lt_one
theorem tsum_geometric_of_lt_one {r : ℝ} (h₁ : 0 ≤ r) (h₂ : r < 1) : ∑' n : ℕ, r ^ n = (1 - r)⁻¹ :=
(hasSum_geometric_of_lt_one h₁ h₂).tsum_eq
#align tsum_geometric_of_lt_1 tsum_geometric_of_lt_one
@[deprecated (since := "2024-01-31")] alias tsum_geometric_of_lt_1 := tsum_geometric_of_lt_one
theorem hasSum_geometric_two : HasSum (fun n : ℕ ↦ ((1 : ℝ) / 2) ^ n) 2 := by
convert hasSum_geometric_of_lt_one _ _ <;> norm_num
#align has_sum_geometric_two hasSum_geometric_two
theorem summable_geometric_two : Summable fun n : ℕ ↦ ((1 : ℝ) / 2) ^ n :=
⟨_, hasSum_geometric_two⟩
#align summable_geometric_two summable_geometric_two
theorem summable_geometric_two_encode {ι : Type*} [Encodable ι] :
Summable fun i : ι ↦ (1 / 2 : ℝ) ^ Encodable.encode i :=
summable_geometric_two.comp_injective Encodable.encode_injective
#align summable_geometric_two_encode summable_geometric_two_encode
theorem tsum_geometric_two : (∑' n : ℕ, ((1 : ℝ) / 2) ^ n) = 2 :=
hasSum_geometric_two.tsum_eq
#align tsum_geometric_two tsum_geometric_two
theorem sum_geometric_two_le (n : ℕ) : (∑ i ∈ range n, (1 / (2 : ℝ)) ^ i) ≤ 2 := by
have : ∀ i, 0 ≤ (1 / (2 : ℝ)) ^ i := by
intro i
apply pow_nonneg
norm_num
convert sum_le_tsum (range n) (fun i _ ↦ this i) summable_geometric_two
exact tsum_geometric_two.symm
#align sum_geometric_two_le sum_geometric_two_le
theorem tsum_geometric_inv_two : (∑' n : ℕ, (2 : ℝ)⁻¹ ^ n) = 2 :=
(inv_eq_one_div (2 : ℝ)).symm ▸ tsum_geometric_two
#align tsum_geometric_inv_two tsum_geometric_inv_two
/-- The sum of `2⁻¹ ^ i` for `n ≤ i` equals `2 * 2⁻¹ ^ n`. -/
theorem tsum_geometric_inv_two_ge (n : ℕ) :
(∑' i, ite (n ≤ i) ((2 : ℝ)⁻¹ ^ i) 0) = 2 * 2⁻¹ ^ n := by
have A : Summable fun i : ℕ ↦ ite (n ≤ i) ((2⁻¹ : ℝ) ^ i) 0 := by
simpa only [← piecewise_eq_indicator, one_div]
using summable_geometric_two.indicator {i | n ≤ i}
have B : ((Finset.range n).sum fun i : ℕ ↦ ite (n ≤ i) ((2⁻¹ : ℝ) ^ i) 0) = 0 :=
Finset.sum_eq_zero fun i hi ↦
ite_eq_right_iff.2 fun h ↦ (lt_irrefl _ ((Finset.mem_range.1 hi).trans_le h)).elim
simp only [← _root_.sum_add_tsum_nat_add n A, B, if_true, zero_add, zero_le',
le_add_iff_nonneg_left, pow_add, _root_.tsum_mul_right, tsum_geometric_inv_two]
#align tsum_geometric_inv_two_ge tsum_geometric_inv_two_ge
theorem hasSum_geometric_two' (a : ℝ) : HasSum (fun n : ℕ ↦ a / 2 / 2 ^ n) a := by
convert HasSum.mul_left (a / 2)
(hasSum_geometric_of_lt_one (le_of_lt one_half_pos) one_half_lt_one) using 1
· funext n
simp only [one_div, inv_pow]
rfl
· norm_num
#align has_sum_geometric_two' hasSum_geometric_two'
theorem summable_geometric_two' (a : ℝ) : Summable fun n : ℕ ↦ a / 2 / 2 ^ n :=
⟨a, hasSum_geometric_two' a⟩
#align summable_geometric_two' summable_geometric_two'
theorem tsum_geometric_two' (a : ℝ) : ∑' n : ℕ, a / 2 / 2 ^ n = a :=
(hasSum_geometric_two' a).tsum_eq
#align tsum_geometric_two' tsum_geometric_two'
/-- **Sum of a Geometric Series** -/
theorem NNReal.hasSum_geometric {r : ℝ≥0} (hr : r < 1) : HasSum (fun n : ℕ ↦ r ^ n) (1 - r)⁻¹ := by
apply NNReal.hasSum_coe.1
push_cast
rw [NNReal.coe_sub (le_of_lt hr)]
exact hasSum_geometric_of_lt_one r.coe_nonneg hr
#align nnreal.has_sum_geometric NNReal.hasSum_geometric
theorem NNReal.summable_geometric {r : ℝ≥0} (hr : r < 1) : Summable fun n : ℕ ↦ r ^ n :=
⟨_, NNReal.hasSum_geometric hr⟩
#align nnreal.summable_geometric NNReal.summable_geometric
theorem tsum_geometric_nnreal {r : ℝ≥0} (hr : r < 1) : ∑' n : ℕ, r ^ n = (1 - r)⁻¹ :=
(NNReal.hasSum_geometric hr).tsum_eq
#align tsum_geometric_nnreal tsum_geometric_nnreal
/-- The series `pow r` converges to `(1-r)⁻¹`. For `r < 1` the RHS is a finite number,
and for `1 ≤ r` the RHS equals `∞`. -/
@[simp]
theorem ENNReal.tsum_geometric (r : ℝ≥0∞) : ∑' n : ℕ, r ^ n = (1 - r)⁻¹ := by
cases' lt_or_le r 1 with hr hr
· rcases ENNReal.lt_iff_exists_coe.1 hr with ⟨r, rfl, hr'⟩
norm_cast at *
convert ENNReal.tsum_coe_eq (NNReal.hasSum_geometric hr)
rw [ENNReal.coe_inv <| ne_of_gt <| tsub_pos_iff_lt.2 hr, coe_sub, coe_one]
· rw [tsub_eq_zero_iff_le.mpr hr, ENNReal.inv_zero, ENNReal.tsum_eq_iSup_nat, iSup_eq_top]
refine fun a ha ↦
(ENNReal.exists_nat_gt (lt_top_iff_ne_top.1 ha)).imp fun n hn ↦ lt_of_lt_of_le hn ?_
calc
(n : ℝ≥0∞) = ∑ i ∈ range n, 1 := by rw [sum_const, nsmul_one, card_range]
_ ≤ ∑ i ∈ range n, r ^ i := by gcongr; apply one_le_pow_of_one_le' hr
#align ennreal.tsum_geometric ENNReal.tsum_geometric
theorem ENNReal.tsum_geometric_add_one (r : ℝ≥0∞) : ∑' n : ℕ, r ^ (n + 1) = r * (1 - r)⁻¹ := by
simp only [_root_.pow_succ', ENNReal.tsum_mul_left, ENNReal.tsum_geometric]
end Geometric
/-!
### Sequences with geometrically decaying distance in metric spaces
In this paragraph, we discuss sequences in metric spaces or emetric spaces for which the distance
between two consecutive terms decays geometrically. We show that such sequences are Cauchy
sequences, and bound their distances to the limit. We also discuss series with geometrically
decaying terms.
-/
section EdistLeGeometric
variable [PseudoEMetricSpace α] (r C : ℝ≥0∞) (hr : r < 1) (hC : C ≠ ⊤) {f : ℕ → α}
(hu : ∀ n, edist (f n) (f (n + 1)) ≤ C * r ^ n)
/-- If `edist (f n) (f (n+1))` is bounded by `C * r^n`, `C ≠ ∞`, `r < 1`,
then `f` is a Cauchy sequence. -/
theorem cauchySeq_of_edist_le_geometric : CauchySeq f := by
refine cauchySeq_of_edist_le_of_tsum_ne_top _ hu ?_
rw [ENNReal.tsum_mul_left, ENNReal.tsum_geometric]
refine ENNReal.mul_ne_top hC (ENNReal.inv_ne_top.2 ?_)
exact (tsub_pos_iff_lt.2 hr).ne'
#align cauchy_seq_of_edist_le_geometric cauchySeq_of_edist_le_geometric
/-- If `edist (f n) (f (n+1))` is bounded by `C * r^n`, then the distance from
`f n` to the limit of `f` is bounded above by `C * r^n / (1 - r)`. -/
theorem edist_le_of_edist_le_geometric_of_tendsto {a : α} (ha : Tendsto f atTop (𝓝 a)) (n : ℕ) :
edist (f n) a ≤ C * r ^ n / (1 - r) := by
convert edist_le_tsum_of_edist_le_of_tendsto _ hu ha _
simp only [pow_add, ENNReal.tsum_mul_left, ENNReal.tsum_geometric, div_eq_mul_inv, mul_assoc]
#align edist_le_of_edist_le_geometric_of_tendsto edist_le_of_edist_le_geometric_of_tendsto
/-- If `edist (f n) (f (n+1))` is bounded by `C * r^n`, then the distance from
`f 0` to the limit of `f` is bounded above by `C / (1 - r)`. -/
theorem edist_le_of_edist_le_geometric_of_tendsto₀ {a : α} (ha : Tendsto f atTop (𝓝 a)) :
edist (f 0) a ≤ C / (1 - r) := by
simpa only [_root_.pow_zero, mul_one] using edist_le_of_edist_le_geometric_of_tendsto r C hu ha 0
#align edist_le_of_edist_le_geometric_of_tendsto₀ edist_le_of_edist_le_geometric_of_tendsto₀
end EdistLeGeometric
section EdistLeGeometricTwo
variable [PseudoEMetricSpace α] (C : ℝ≥0∞) (hC : C ≠ ⊤) {f : ℕ → α}
(hu : ∀ n, edist (f n) (f (n + 1)) ≤ C / 2 ^ n) {a : α} (ha : Tendsto f atTop (𝓝 a))
/-- If `edist (f n) (f (n+1))` is bounded by `C * 2^-n`, then `f` is a Cauchy sequence. -/
theorem cauchySeq_of_edist_le_geometric_two : CauchySeq f := by
simp only [div_eq_mul_inv, ENNReal.inv_pow] at hu
refine cauchySeq_of_edist_le_geometric 2⁻¹ C ?_ hC hu
simp [ENNReal.one_lt_two]
#align cauchy_seq_of_edist_le_geometric_two cauchySeq_of_edist_le_geometric_two
/-- If `edist (f n) (f (n+1))` is bounded by `C * 2^-n`, then the distance from
`f n` to the limit of `f` is bounded above by `2 * C * 2^-n`. -/
theorem edist_le_of_edist_le_geometric_two_of_tendsto (n : ℕ) : edist (f n) a ≤ 2 * C / 2 ^ n := by
simp only [div_eq_mul_inv, ENNReal.inv_pow] at *
rw [mul_assoc, mul_comm]
convert edist_le_of_edist_le_geometric_of_tendsto 2⁻¹ C hu ha n using 1
rw [ENNReal.one_sub_inv_two, div_eq_mul_inv, inv_inv]
#align edist_le_of_edist_le_geometric_two_of_tendsto edist_le_of_edist_le_geometric_two_of_tendsto
/-- If `edist (f n) (f (n+1))` is bounded by `C * 2^-n`, then the distance from
`f 0` to the limit of `f` is bounded above by `2 * C`. -/
theorem edist_le_of_edist_le_geometric_two_of_tendsto₀ : edist (f 0) a ≤ 2 * C := by
simpa only [_root_.pow_zero, div_eq_mul_inv, inv_one, mul_one] using
edist_le_of_edist_le_geometric_two_of_tendsto C hu ha 0
#align edist_le_of_edist_le_geometric_two_of_tendsto₀ edist_le_of_edist_le_geometric_two_of_tendsto₀
end EdistLeGeometricTwo
section LeGeometric
variable [PseudoMetricSpace α] {r C : ℝ} (hr : r < 1) {f : ℕ → α}
(hu : ∀ n, dist (f n) (f (n + 1)) ≤ C * r ^ n)
theorem aux_hasSum_of_le_geometric : HasSum (fun n : ℕ ↦ C * r ^ n) (C / (1 - r)) := by
rcases sign_cases_of_C_mul_pow_nonneg fun n ↦ dist_nonneg.trans (hu n) with (rfl | ⟨_, r₀⟩)
· simp [hasSum_zero]
· refine HasSum.mul_left C ?_
simpa using hasSum_geometric_of_lt_one r₀ hr
#align aux_has_sum_of_le_geometric aux_hasSum_of_le_geometric
variable (r C)
/-- If `dist (f n) (f (n+1))` is bounded by `C * r^n`, `r < 1`, then `f` is a Cauchy sequence.
Note that this lemma does not assume `0 ≤ C` or `0 ≤ r`. -/
theorem cauchySeq_of_le_geometric : CauchySeq f :=
cauchySeq_of_dist_le_of_summable _ hu ⟨_, aux_hasSum_of_le_geometric hr hu⟩
#align cauchy_seq_of_le_geometric cauchySeq_of_le_geometric
/-- If `dist (f n) (f (n+1))` is bounded by `C * r^n`, `r < 1`, then the distance from
`f n` to the limit of `f` is bounded above by `C * r^n / (1 - r)`. -/
theorem dist_le_of_le_geometric_of_tendsto₀ {a : α} (ha : Tendsto f atTop (𝓝 a)) :
dist (f 0) a ≤ C / (1 - r) :=
(aux_hasSum_of_le_geometric hr hu).tsum_eq ▸
dist_le_tsum_of_dist_le_of_tendsto₀ _ hu ⟨_, aux_hasSum_of_le_geometric hr hu⟩ ha
#align dist_le_of_le_geometric_of_tendsto₀ dist_le_of_le_geometric_of_tendsto₀
/-- If `dist (f n) (f (n+1))` is bounded by `C * r^n`, `r < 1`, then the distance from
`f 0` to the limit of `f` is bounded above by `C / (1 - r)`. -/
theorem dist_le_of_le_geometric_of_tendsto {a : α} (ha : Tendsto f atTop (𝓝 a)) (n : ℕ) :
dist (f n) a ≤ C * r ^ n / (1 - r) := by
have := aux_hasSum_of_le_geometric hr hu
convert dist_le_tsum_of_dist_le_of_tendsto _ hu ⟨_, this⟩ ha n
simp only [pow_add, mul_left_comm C, mul_div_right_comm]
rw [mul_comm]
exact (this.mul_left _).tsum_eq.symm
#align dist_le_of_le_geometric_of_tendsto dist_le_of_le_geometric_of_tendsto
variable (hu₂ : ∀ n, dist (f n) (f (n + 1)) ≤ C / 2 / 2 ^ n)
/-- If `dist (f n) (f (n+1))` is bounded by `(C / 2) / 2^n`, then `f` is a Cauchy sequence. -/
theorem cauchySeq_of_le_geometric_two : CauchySeq f :=
cauchySeq_of_dist_le_of_summable _ hu₂ <| ⟨_, hasSum_geometric_two' C⟩
#align cauchy_seq_of_le_geometric_two cauchySeq_of_le_geometric_two
/-- If `dist (f n) (f (n+1))` is bounded by `(C / 2) / 2^n`, then the distance from
`f 0` to the limit of `f` is bounded above by `C`. -/
theorem dist_le_of_le_geometric_two_of_tendsto₀ {a : α} (ha : Tendsto f atTop (𝓝 a)) :
dist (f 0) a ≤ C :=
tsum_geometric_two' C ▸ dist_le_tsum_of_dist_le_of_tendsto₀ _ hu₂ (summable_geometric_two' C) ha
#align dist_le_of_le_geometric_two_of_tendsto₀ dist_le_of_le_geometric_two_of_tendsto₀
/-- If `dist (f n) (f (n+1))` is bounded by `(C / 2) / 2^n`, then the distance from
`f n` to the limit of `f` is bounded above by `C / 2^n`. -/
theorem dist_le_of_le_geometric_two_of_tendsto {a : α} (ha : Tendsto f atTop (𝓝 a)) (n : ℕ) :
dist (f n) a ≤ C / 2 ^ n := by
convert dist_le_tsum_of_dist_le_of_tendsto _ hu₂ (summable_geometric_two' C) ha n
simp only [add_comm n, pow_add, ← div_div]
symm
exact ((hasSum_geometric_two' C).div_const _).tsum_eq
#align dist_le_of_le_geometric_two_of_tendsto dist_le_of_le_geometric_two_of_tendsto
end LeGeometric
/-! ### Summability tests based on comparison with geometric series -/
/-- A series whose terms are bounded by the terms of a converging geometric series converges. -/
theorem summable_one_div_pow_of_le {m : ℝ} {f : ℕ → ℕ} (hm : 1 < m) (fi : ∀ i, i ≤ f i) :
Summable fun i ↦ 1 / m ^ f i := by
refine .of_nonneg_of_le (fun a ↦ by positivity) (fun a ↦ ?_)
(summable_geometric_of_lt_one (one_div_nonneg.mpr (zero_le_one.trans hm.le))
((one_div_lt (zero_lt_one.trans hm) zero_lt_one).mpr (one_div_one.le.trans_lt hm)))
rw [div_pow, one_pow]
refine (one_div_le_one_div ?_ ?_).mpr (pow_le_pow_right hm.le (fi a)) <;>
exact pow_pos (zero_lt_one.trans hm) _
#align summable_one_div_pow_of_le summable_one_div_pow_of_le
/-! ### Positive sequences with small sums on countable types -/
/-- For any positive `ε`, define on an encodable type a positive sequence with sum less than `ε` -/
def posSumOfEncodable {ε : ℝ} (hε : 0 < ε) (ι) [Encodable ι] :
{ ε' : ι → ℝ // (∀ i, 0 < ε' i) ∧ ∃ c, HasSum ε' c ∧ c ≤ ε } := by
let f n := ε / 2 / 2 ^ n
have hf : HasSum f ε := hasSum_geometric_two' _
have f0 : ∀ n, 0 < f n := fun n ↦ div_pos (half_pos hε) (pow_pos zero_lt_two _)
refine ⟨f ∘ Encodable.encode, fun i ↦ f0 _, ?_⟩
rcases hf.summable.comp_injective (@Encodable.encode_injective ι _) with ⟨c, hg⟩
refine ⟨c, hg, hasSum_le_inj _ (@Encodable.encode_injective ι _) ?_ ?_ hg hf⟩
· intro i _
exact le_of_lt (f0 _)
· intro n
exact le_rfl
#align pos_sum_of_encodable posSumOfEncodable
theorem Set.Countable.exists_pos_hasSum_le {ι : Type*} {s : Set ι} (hs : s.Countable) {ε : ℝ}
(hε : 0 < ε) : ∃ ε' : ι → ℝ, (∀ i, 0 < ε' i) ∧ ∃ c, HasSum (fun i : s ↦ ε' i) c ∧ c ≤ ε := by
haveI := hs.toEncodable
rcases posSumOfEncodable hε s with ⟨f, hf0, ⟨c, hfc, hcε⟩⟩
refine ⟨fun i ↦ if h : i ∈ s then f ⟨i, h⟩ else 1, fun i ↦ ?_, ⟨c, ?_, hcε⟩⟩
· conv_rhs => simp
split_ifs
exacts [hf0 _, zero_lt_one]
· simpa only [Subtype.coe_prop, dif_pos, Subtype.coe_eta]
#align set.countable.exists_pos_has_sum_le Set.Countable.exists_pos_hasSum_le
theorem Set.Countable.exists_pos_forall_sum_le {ι : Type*} {s : Set ι} (hs : s.Countable) {ε : ℝ}
(hε : 0 < ε) : ∃ ε' : ι → ℝ,
(∀ i, 0 < ε' i) ∧ ∀ t : Finset ι, ↑t ⊆ s → ∑ i ∈ t, ε' i ≤ ε := by
rcases hs.exists_pos_hasSum_le hε with ⟨ε', hpos, c, hε'c, hcε⟩
refine ⟨ε', hpos, fun t ht ↦ ?_⟩
rw [← sum_subtype_of_mem _ ht]
refine (sum_le_hasSum _ ?_ hε'c).trans hcε
exact fun _ _ ↦ (hpos _).le
#align set.countable.exists_pos_forall_sum_le Set.Countable.exists_pos_forall_sum_le
namespace NNReal
theorem exists_pos_sum_of_countable {ε : ℝ≥0} (hε : ε ≠ 0) (ι) [Countable ι] :
∃ ε' : ι → ℝ≥0, (∀ i, 0 < ε' i) ∧ ∃ c, HasSum ε' c ∧ c < ε := by
cases nonempty_encodable ι
obtain ⟨a, a0, aε⟩ := exists_between (pos_iff_ne_zero.2 hε)
obtain ⟨ε', hε', c, hc, hcε⟩ := posSumOfEncodable a0 ι
exact
⟨fun i ↦ ⟨ε' i, (hε' i).le⟩, fun i ↦ NNReal.coe_lt_coe.1 <| hε' i,
⟨c, hasSum_le (fun i ↦ (hε' i).le) hasSum_zero hc⟩, NNReal.hasSum_coe.1 hc,
aε.trans_le' <| NNReal.coe_le_coe.1 hcε⟩
#align nnreal.exists_pos_sum_of_countable NNReal.exists_pos_sum_of_countable
end NNReal
namespace ENNReal
theorem exists_pos_sum_of_countable {ε : ℝ≥0∞} (hε : ε ≠ 0) (ι) [Countable ι] :
∃ ε' : ι → ℝ≥0, (∀ i, 0 < ε' i) ∧ (∑' i, (ε' i : ℝ≥0∞)) < ε := by
rcases exists_between (pos_iff_ne_zero.2 hε) with ⟨r, h0r, hrε⟩
rcases lt_iff_exists_coe.1 hrε with ⟨x, rfl, _⟩
rcases NNReal.exists_pos_sum_of_countable (coe_pos.1 h0r).ne' ι with ⟨ε', hp, c, hc, hcr⟩
exact ⟨ε', hp, (ENNReal.tsum_coe_eq hc).symm ▸ lt_trans (coe_lt_coe.2 hcr) hrε⟩
#align ennreal.exists_pos_sum_of_countable ENNReal.exists_pos_sum_of_countable
theorem exists_pos_sum_of_countable' {ε : ℝ≥0∞} (hε : ε ≠ 0) (ι) [Countable ι] :
∃ ε' : ι → ℝ≥0∞, (∀ i, 0 < ε' i) ∧ ∑' i, ε' i < ε :=
let ⟨δ, δpos, hδ⟩ := exists_pos_sum_of_countable hε ι
⟨fun i ↦ δ i, fun i ↦ ENNReal.coe_pos.2 (δpos i), hδ⟩
#align ennreal.exists_pos_sum_of_countable' ENNReal.exists_pos_sum_of_countable'
theorem exists_pos_tsum_mul_lt_of_countable {ε : ℝ≥0∞} (hε : ε ≠ 0) {ι} [Countable ι] (w : ι → ℝ≥0∞)
(hw : ∀ i, w i ≠ ∞) : ∃ δ : ι → ℝ≥0, (∀ i, 0 < δ i) ∧ (∑' i, (w i * δ i : ℝ≥0∞)) < ε := by
lift w to ι → ℝ≥0 using hw
rcases exists_pos_sum_of_countable hε ι with ⟨δ', Hpos, Hsum⟩
have : ∀ i, 0 < max 1 (w i) := fun i ↦ zero_lt_one.trans_le (le_max_left _ _)
refine ⟨fun i ↦ δ' i / max 1 (w i), fun i ↦ div_pos (Hpos _) (this i), ?_⟩
refine lt_of_le_of_lt (ENNReal.tsum_le_tsum fun i ↦ ?_) Hsum
rw [coe_div (this i).ne']
refine mul_le_of_le_div' (mul_le_mul_left' (ENNReal.inv_le_inv.2 ?_) _)
exact coe_le_coe.2 (le_max_right _ _)
#align ennreal.exists_pos_tsum_mul_lt_of_countable ENNReal.exists_pos_tsum_mul_lt_of_countable
end ENNReal
/-!
### Factorial
-/
theorem factorial_tendsto_atTop : Tendsto Nat.factorial atTop atTop :=
tendsto_atTop_atTop_of_monotone (fun _ _ ↦ Nat.factorial_le) fun n ↦ ⟨n, n.self_le_factorial⟩
#align factorial_tendsto_at_top factorial_tendsto_atTop
theorem tendsto_factorial_div_pow_self_atTop :
Tendsto (fun n ↦ n ! / (n : ℝ) ^ n : ℕ → ℝ) atTop (𝓝 0) :=
tendsto_of_tendsto_of_tendsto_of_le_of_le' tendsto_const_nhds
(tendsto_const_div_atTop_nhds_zero_nat 1)
(eventually_of_forall fun n ↦
div_nonneg (mod_cast n.factorial_pos.le)
(pow_nonneg (mod_cast n.zero_le) _))
(by
refine (eventually_gt_atTop 0).mono fun n hn ↦ ?_
rcases Nat.exists_eq_succ_of_ne_zero hn.ne.symm with ⟨k, rfl⟩
rw [← prod_range_add_one_eq_factorial, pow_eq_prod_const, div_eq_mul_inv, ← inv_eq_one_div,
prod_natCast, Nat.cast_succ, ← prod_inv_distrib, ← prod_mul_distrib,
Finset.prod_range_succ']
simp only [prod_range_succ', one_mul, Nat.cast_add, zero_add, Nat.cast_one]
refine
mul_le_of_le_one_left (inv_nonneg.mpr <| mod_cast hn.le) (prod_le_one ?_ ?_) <;>
intro x hx <;>
rw [Finset.mem_range] at hx
· positivity
· refine (div_le_one <| mod_cast hn).mpr ?_
norm_cast
omega)
#align tendsto_factorial_div_pow_self_at_top tendsto_factorial_div_pow_self_atTop
/-!
### Ceil and floor
-/
section
theorem tendsto_nat_floor_atTop {α : Type*} [LinearOrderedSemiring α] [FloorSemiring α] :
Tendsto (fun x : α ↦ ⌊x⌋₊) atTop atTop :=
Nat.floor_mono.tendsto_atTop_atTop fun x ↦ ⟨max 0 (x + 1), by simp [Nat.le_floor_iff]⟩
#align tendsto_nat_floor_at_top tendsto_nat_floor_atTop
lemma tendsto_nat_ceil_atTop {α : Type*} [LinearOrderedSemiring α] [FloorSemiring α] :
Tendsto (fun x : α ↦ ⌈x⌉₊) atTop atTop := by
refine Nat.ceil_mono.tendsto_atTop_atTop (fun x ↦ ⟨x, ?_⟩)
simp only [Nat.ceil_natCast, le_refl]
lemma tendsto_nat_floor_mul_atTop {α : Type _} [LinearOrderedSemifield α] [FloorSemiring α]
[Archimedean α] (a : α) (ha : 0 < a) : Tendsto (fun (x:ℕ) => ⌊a * x⌋₊) atTop atTop :=
Tendsto.comp tendsto_nat_floor_atTop
<| Tendsto.const_mul_atTop ha tendsto_natCast_atTop_atTop
variable {R : Type*} [TopologicalSpace R] [LinearOrderedField R] [OrderTopology R] [FloorRing R]
theorem tendsto_nat_floor_mul_div_atTop {a : R} (ha : 0 ≤ a) :
Tendsto (fun x ↦ (⌊a * x⌋₊ : R) / x) atTop (𝓝 a) := by
have A : Tendsto (fun x : R ↦ a - x⁻¹) atTop (𝓝 (a - 0)) :=
tendsto_const_nhds.sub tendsto_inv_atTop_zero
rw [sub_zero] at A
apply tendsto_of_tendsto_of_tendsto_of_le_of_le' A tendsto_const_nhds
· refine eventually_atTop.2 ⟨1, fun x hx ↦ ?_⟩
simp only [le_div_iff (zero_lt_one.trans_le hx), _root_.sub_mul,
inv_mul_cancel (zero_lt_one.trans_le hx).ne']
have := Nat.lt_floor_add_one (a * x)
linarith
· refine eventually_atTop.2 ⟨1, fun x hx ↦ ?_⟩
rw [div_le_iff (zero_lt_one.trans_le hx)]
simp [Nat.floor_le (mul_nonneg ha (zero_le_one.trans hx))]
#align tendsto_nat_floor_mul_div_at_top tendsto_nat_floor_mul_div_atTop
theorem tendsto_nat_floor_div_atTop : Tendsto (fun x ↦ (⌊x⌋₊ : R) / x) atTop (𝓝 1) := by
simpa using tendsto_nat_floor_mul_div_atTop (zero_le_one' R)
#align tendsto_nat_floor_div_at_top tendsto_nat_floor_div_atTop
theorem tendsto_nat_ceil_mul_div_atTop {a : R} (ha : 0 ≤ a) :
Tendsto (fun x ↦ (⌈a * x⌉₊ : R) / x) atTop (𝓝 a) := by
have A : Tendsto (fun x : R ↦ a + x⁻¹) atTop (𝓝 (a + 0)) :=
tendsto_const_nhds.add tendsto_inv_atTop_zero
rw [add_zero] at A
apply tendsto_of_tendsto_of_tendsto_of_le_of_le' tendsto_const_nhds A
· refine eventually_atTop.2 ⟨1, fun x hx ↦ ?_⟩
rw [le_div_iff (zero_lt_one.trans_le hx)]
exact Nat.le_ceil _
· refine eventually_atTop.2 ⟨1, fun x hx ↦ ?_⟩
simp [div_le_iff (zero_lt_one.trans_le hx), inv_mul_cancel (zero_lt_one.trans_le hx).ne',
(Nat.ceil_lt_add_one (mul_nonneg ha (zero_le_one.trans hx))).le, add_mul]
#align tendsto_nat_ceil_mul_div_at_top tendsto_nat_ceil_mul_div_atTop
| Mathlib/Analysis/SpecificLimits/Basic.lean | 709 | 710 | theorem tendsto_nat_ceil_div_atTop : Tendsto (fun x ↦ (⌈x⌉₊ : R) / x) atTop (𝓝 1) := by |
simpa using tendsto_nat_ceil_mul_div_atTop (zero_le_one' R)
|
/-
Copyright (c) 2021 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Alex Kontorovich
-/
import Mathlib.Order.Filter.Bases
#align_import order.filter.pi from "leanprover-community/mathlib"@"ce64cd319bb6b3e82f31c2d38e79080d377be451"
/-!
# (Co)product of a family of filters
In this file we define two filters on `Π i, α i` and prove some basic properties of these filters.
* `Filter.pi (f : Π i, Filter (α i))` to be the maximal filter on `Π i, α i` such that
`∀ i, Filter.Tendsto (Function.eval i) (Filter.pi f) (f i)`. It is defined as
`Π i, Filter.comap (Function.eval i) (f i)`. This is a generalization of `Filter.prod` to indexed
products.
* `Filter.coprodᵢ (f : Π i, Filter (α i))`: a generalization of `Filter.coprod`; it is the supremum
of `comap (eval i) (f i)`.
-/
open Set Function
open scoped Classical
open Filter
namespace Filter
variable {ι : Type*} {α : ι → Type*} {f f₁ f₂ : (i : ι) → Filter (α i)} {s : (i : ι) → Set (α i)}
{p : ∀ i, α i → Prop}
section Pi
/-- The product of an indexed family of filters. -/
def pi (f : ∀ i, Filter (α i)) : Filter (∀ i, α i) :=
⨅ i, comap (eval i) (f i)
#align filter.pi Filter.pi
instance pi.isCountablyGenerated [Countable ι] [∀ i, IsCountablyGenerated (f i)] :
IsCountablyGenerated (pi f) :=
iInf.isCountablyGenerated _
#align filter.pi.is_countably_generated Filter.pi.isCountablyGenerated
theorem tendsto_eval_pi (f : ∀ i, Filter (α i)) (i : ι) : Tendsto (eval i) (pi f) (f i) :=
tendsto_iInf' i tendsto_comap
#align filter.tendsto_eval_pi Filter.tendsto_eval_pi
theorem tendsto_pi {β : Type*} {m : β → ∀ i, α i} {l : Filter β} :
Tendsto m l (pi f) ↔ ∀ i, Tendsto (fun x => m x i) l (f i) := by
simp only [pi, tendsto_iInf, tendsto_comap_iff]; rfl
#align filter.tendsto_pi Filter.tendsto_pi
/-- If a function tends to a product `Filter.pi f` of filters, then its `i`-th component tends to
`f i`. See also `Filter.Tendsto.apply_nhds` for the special case of converging to a point in a
product of topological spaces. -/
alias ⟨Tendsto.apply, _⟩ := tendsto_pi
theorem le_pi {g : Filter (∀ i, α i)} : g ≤ pi f ↔ ∀ i, Tendsto (eval i) g (f i) :=
tendsto_pi
#align filter.le_pi Filter.le_pi
@[mono]
theorem pi_mono (h : ∀ i, f₁ i ≤ f₂ i) : pi f₁ ≤ pi f₂ :=
iInf_mono fun i => comap_mono <| h i
#align filter.pi_mono Filter.pi_mono
theorem mem_pi_of_mem (i : ι) {s : Set (α i)} (hs : s ∈ f i) : eval i ⁻¹' s ∈ pi f :=
mem_iInf_of_mem i <| preimage_mem_comap hs
#align filter.mem_pi_of_mem Filter.mem_pi_of_mem
theorem pi_mem_pi {I : Set ι} (hI : I.Finite) (h : ∀ i ∈ I, s i ∈ f i) : I.pi s ∈ pi f := by
rw [pi_def, biInter_eq_iInter]
refine mem_iInf_of_iInter hI (fun i => ?_) Subset.rfl
exact preimage_mem_comap (h i i.2)
#align filter.pi_mem_pi Filter.pi_mem_pi
theorem mem_pi {s : Set (∀ i, α i)} :
s ∈ pi f ↔ ∃ I : Set ι, I.Finite ∧ ∃ t : ∀ i, Set (α i), (∀ i, t i ∈ f i) ∧ I.pi t ⊆ s := by
constructor
· simp only [pi, mem_iInf', mem_comap, pi_def]
rintro ⟨I, If, V, hVf, -, rfl, -⟩
choose t htf htV using hVf
exact ⟨I, If, t, htf, iInter₂_mono fun i _ => htV i⟩
· rintro ⟨I, If, t, htf, hts⟩
exact mem_of_superset (pi_mem_pi If fun i _ => htf i) hts
#align filter.mem_pi Filter.mem_pi
theorem mem_pi' {s : Set (∀ i, α i)} :
s ∈ pi f ↔ ∃ I : Finset ι, ∃ t : ∀ i, Set (α i), (∀ i, t i ∈ f i) ∧ Set.pi (↑I) t ⊆ s :=
mem_pi.trans exists_finite_iff_finset
#align filter.mem_pi' Filter.mem_pi'
theorem mem_of_pi_mem_pi [∀ i, NeBot (f i)] {I : Set ι} (h : I.pi s ∈ pi f) {i : ι} (hi : i ∈ I) :
s i ∈ f i := by
rcases mem_pi.1 h with ⟨I', -, t, htf, hts⟩
refine mem_of_superset (htf i) fun x hx => ?_
have : ∀ i, (t i).Nonempty := fun i => nonempty_of_mem (htf i)
choose g hg using this
have : update g i x ∈ I'.pi t := fun j _ => by
rcases eq_or_ne j i with (rfl | hne) <;> simp [*]
simpa using hts this i hi
#align filter.mem_of_pi_mem_pi Filter.mem_of_pi_mem_pi
@[simp]
theorem pi_mem_pi_iff [∀ i, NeBot (f i)] {I : Set ι} (hI : I.Finite) :
I.pi s ∈ pi f ↔ ∀ i ∈ I, s i ∈ f i :=
⟨fun h _i hi => mem_of_pi_mem_pi h hi, pi_mem_pi hI⟩
#align filter.pi_mem_pi_iff Filter.pi_mem_pi_iff
theorem Eventually.eval_pi {i : ι} (hf : ∀ᶠ x : α i in f i, p i x) :
∀ᶠ x : ∀ i : ι, α i in pi f, p i (x i) := (tendsto_eval_pi _ _).eventually hf
#align filter.eventually.eval_pi Filter.Eventually.eval_pi
theorem eventually_pi [Finite ι] (hf : ∀ i, ∀ᶠ x in f i, p i x) :
∀ᶠ x : ∀ i, α i in pi f, ∀ i, p i (x i) := eventually_all.2 fun _i => (hf _).eval_pi
#align filter.eventually_pi Filter.eventually_pi
theorem hasBasis_pi {ι' : ι → Type} {s : ∀ i, ι' i → Set (α i)} {p : ∀ i, ι' i → Prop}
(h : ∀ i, (f i).HasBasis (p i) (s i)) :
(pi f).HasBasis (fun If : Set ι × ∀ i, ι' i => If.1.Finite ∧ ∀ i ∈ If.1, p i (If.2 i))
fun If : Set ι × ∀ i, ι' i => If.1.pi fun i => s i <| If.2 i := by
simpa [Set.pi_def] using hasBasis_iInf' fun i => (h i).comap (eval i : (∀ j, α j) → α i)
#align filter.has_basis_pi Filter.hasBasis_pi
theorem le_pi_principal (s : (i : ι) → Set (α i)) :
𝓟 (univ.pi s) ≤ pi fun i ↦ 𝓟 (s i) :=
le_pi.2 fun i ↦ tendsto_principal_principal.2 fun _f hf ↦ hf i trivial
@[simp]
theorem pi_principal [Finite ι] (s : (i : ι) → Set (α i)) :
pi (fun i ↦ 𝓟 (s i)) = 𝓟 (univ.pi s) := by
simp [Filter.pi, Set.pi_def]
@[simp]
theorem pi_pure [Finite ι] (f : (i : ι) → α i) : pi (pure <| f ·) = pure f := by
simp only [← principal_singleton, pi_principal, univ_pi_singleton]
@[simp]
theorem pi_inf_principal_univ_pi_eq_bot :
pi f ⊓ 𝓟 (Set.pi univ s) = ⊥ ↔ ∃ i, f i ⊓ 𝓟 (s i) = ⊥ := by
constructor
· simp only [inf_principal_eq_bot, mem_pi]
contrapose!
rintro (hsf : ∀ i, ∃ᶠ x in f i, x ∈ s i) I - t htf hts
have : ∀ i, (s i ∩ t i).Nonempty := fun i => ((hsf i).and_eventually (htf i)).exists
choose x hxs hxt using this
exact hts (fun i _ => hxt i) (mem_univ_pi.2 hxs)
· simp only [inf_principal_eq_bot]
rintro ⟨i, hi⟩
filter_upwards [mem_pi_of_mem i hi] with x using mt fun h => h i trivial
#align filter.pi_inf_principal_univ_pi_eq_bot Filter.pi_inf_principal_univ_pi_eq_bot
@[simp]
theorem pi_inf_principal_pi_eq_bot [∀ i, NeBot (f i)] {I : Set ι} :
pi f ⊓ 𝓟 (Set.pi I s) = ⊥ ↔ ∃ i ∈ I, f i ⊓ 𝓟 (s i) = ⊥ := by
rw [← univ_pi_piecewise_univ I, pi_inf_principal_univ_pi_eq_bot]
refine exists_congr fun i => ?_
by_cases hi : i ∈ I <;> simp [hi, NeBot.ne']
#align filter.pi_inf_principal_pi_eq_bot Filter.pi_inf_principal_pi_eq_bot
@[simp]
theorem pi_inf_principal_univ_pi_neBot :
NeBot (pi f ⊓ 𝓟 (Set.pi univ s)) ↔ ∀ i, NeBot (f i ⊓ 𝓟 (s i)) := by simp [neBot_iff]
#align filter.pi_inf_principal_univ_pi_ne_bot Filter.pi_inf_principal_univ_pi_neBot
@[simp]
theorem pi_inf_principal_pi_neBot [∀ i, NeBot (f i)] {I : Set ι} :
NeBot (pi f ⊓ 𝓟 (I.pi s)) ↔ ∀ i ∈ I, NeBot (f i ⊓ 𝓟 (s i)) := by simp [neBot_iff]
#align filter.pi_inf_principal_pi_ne_bot Filter.pi_inf_principal_pi_neBot
instance PiInfPrincipalPi.neBot [h : ∀ i, NeBot (f i ⊓ 𝓟 (s i))] {I : Set ι} :
NeBot (pi f ⊓ 𝓟 (I.pi s)) :=
(pi_inf_principal_univ_pi_neBot.2 ‹_›).mono <|
inf_le_inf_left _ <| principal_mono.2 fun x hx i _ => hx i trivial
#align filter.pi_inf_principal_pi.ne_bot Filter.PiInfPrincipalPi.neBot
@[simp]
theorem pi_eq_bot : pi f = ⊥ ↔ ∃ i, f i = ⊥ := by
simpa using @pi_inf_principal_univ_pi_eq_bot ι α f fun _ => univ
#align filter.pi_eq_bot Filter.pi_eq_bot
@[simp]
theorem pi_neBot : NeBot (pi f) ↔ ∀ i, NeBot (f i) := by simp [neBot_iff]
#align filter.pi_ne_bot Filter.pi_neBot
instance [∀ i, NeBot (f i)] : NeBot (pi f) :=
pi_neBot.2 ‹_›
@[simp]
theorem map_eval_pi (f : ∀ i, Filter (α i)) [∀ i, NeBot (f i)] (i : ι) :
map (eval i) (pi f) = f i := by
refine le_antisymm (tendsto_eval_pi f i) fun s hs => ?_
rcases mem_pi.1 (mem_map.1 hs) with ⟨I, hIf, t, htf, hI⟩
rw [← image_subset_iff] at hI
refine mem_of_superset (htf i) ((subset_eval_image_pi ?_ _).trans hI)
exact nonempty_of_mem (pi_mem_pi hIf fun i _ => htf i)
#align filter.map_eval_pi Filter.map_eval_pi
@[simp]
theorem pi_le_pi [∀ i, NeBot (f₁ i)] : pi f₁ ≤ pi f₂ ↔ ∀ i, f₁ i ≤ f₂ i :=
⟨fun h i => map_eval_pi f₁ i ▸ (tendsto_eval_pi _ _).mono_left h, pi_mono⟩
#align filter.pi_le_pi Filter.pi_le_pi
@[simp]
theorem pi_inj [∀ i, NeBot (f₁ i)] : pi f₁ = pi f₂ ↔ f₁ = f₂ := by
refine ⟨fun h => ?_, congr_arg pi⟩
have hle : f₁ ≤ f₂ := pi_le_pi.1 h.le
haveI : ∀ i, NeBot (f₂ i) := fun i => neBot_of_le (hle i)
exact hle.antisymm (pi_le_pi.1 h.ge)
#align filter.pi_inj Filter.pi_inj
end Pi
/-! ### `n`-ary coproducts of filters -/
section CoprodCat
-- for "Coprod"
set_option linter.uppercaseLean3 false
/-- Coproduct of filters. -/
protected def coprodᵢ (f : ∀ i, Filter (α i)) : Filter (∀ i, α i) :=
⨆ i : ι, comap (eval i) (f i)
#align filter.Coprod Filter.coprodᵢ
theorem mem_coprodᵢ_iff {s : Set (∀ i, α i)} :
s ∈ Filter.coprodᵢ f ↔ ∀ i : ι, ∃ t₁ ∈ f i, eval i ⁻¹' t₁ ⊆ s := by simp [Filter.coprodᵢ]
#align filter.mem_Coprod_iff Filter.mem_coprodᵢ_iff
theorem compl_mem_coprodᵢ {s : Set (∀ i, α i)} :
sᶜ ∈ Filter.coprodᵢ f ↔ ∀ i, (eval i '' s)ᶜ ∈ f i := by
simp only [Filter.coprodᵢ, mem_iSup, compl_mem_comap]
#align filter.compl_mem_Coprod Filter.compl_mem_coprodᵢ
theorem coprodᵢ_neBot_iff' :
NeBot (Filter.coprodᵢ f) ↔ (∀ i, Nonempty (α i)) ∧ ∃ d, NeBot (f d) := by
simp only [Filter.coprodᵢ, iSup_neBot, ← exists_and_left, ← comap_eval_neBot_iff']
#align filter.Coprod_ne_bot_iff' Filter.coprodᵢ_neBot_iff'
@[simp]
theorem coprodᵢ_neBot_iff [∀ i, Nonempty (α i)] : NeBot (Filter.coprodᵢ f) ↔ ∃ d, NeBot (f d) := by
simp [coprodᵢ_neBot_iff', *]
#align filter.Coprod_ne_bot_iff Filter.coprodᵢ_neBot_iff
| Mathlib/Order/Filter/Pi.lean | 248 | 250 | theorem coprodᵢ_eq_bot_iff' : Filter.coprodᵢ f = ⊥ ↔ (∃ i, IsEmpty (α i)) ∨ f = ⊥ := by |
simpa only [not_neBot, not_and_or, funext_iff, not_forall, not_exists, not_nonempty_iff]
using coprodᵢ_neBot_iff'.not
|
/-
Copyright (c) 2022 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang, Jujian Zhang
-/
import Mathlib.Algebra.Algebra.Bilinear
import Mathlib.RingTheory.Localization.Basic
#align_import algebra.module.localized_module from "leanprover-community/mathlib"@"831c494092374cfe9f50591ed0ac81a25efc5b86"
/-!
# Localized Module
Given a commutative semiring `R`, a multiplicative subset `S ⊆ R` and an `R`-module `M`, we can
localize `M` by `S`. This gives us a `Localization S`-module.
## Main definitions
* `LocalizedModule.r` : the equivalence relation defining this localization, namely
`(m, s) ≈ (m', s')` if and only if there is some `u : S` such that `u • s' • m = u • s • m'`.
* `LocalizedModule M S` : the localized module by `S`.
* `LocalizedModule.mk` : the canonical map sending `(m, s) : M × S ↦ m/s : LocalizedModule M S`
* `LocalizedModule.liftOn` : any well defined function `f : M × S → α` respecting `r` descents to
a function `LocalizedModule M S → α`
* `LocalizedModule.liftOn₂` : any well defined function `f : M × S → M × S → α` respecting `r`
descents to a function `LocalizedModule M S → LocalizedModule M S`
* `LocalizedModule.mk_add_mk` : in the localized module
`mk m s + mk m' s' = mk (s' • m + s • m') (s * s')`
* `LocalizedModule.mk_smul_mk` : in the localized module, for any `r : R`, `s t : S`, `m : M`,
we have `mk r s • mk m t = mk (r • m) (s * t)` where `mk r s : Localization S` is localized ring
by `S`.
* `LocalizedModule.isModule` : `LocalizedModule M S` is a `Localization S`-module.
## Future work
* Redefine `Localization` for monoids and rings to coincide with `LocalizedModule`.
-/
namespace LocalizedModule
universe u v
variable {R : Type u} [CommSemiring R] (S : Submonoid R)
variable (M : Type v) [AddCommMonoid M] [Module R M]
variable (T : Type*) [CommSemiring T] [Algebra R T] [IsLocalization S T]
/-- The equivalence relation on `M × S` where `(m1, s1) ≈ (m2, s2)` if and only if
for some (u : S), u * (s2 • m1 - s1 • m2) = 0-/
/- Porting note: We use small letter `r` since `R` is used for a ring. -/
def r (a b : M × S) : Prop :=
∃ u : S, u • b.2 • a.1 = u • a.2 • b.1
#align localized_module.r LocalizedModule.r
theorem r.isEquiv : IsEquiv _ (r S M) :=
{ refl := fun ⟨m, s⟩ => ⟨1, by rw [one_smul]⟩
trans := fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨m3, s3⟩ ⟨u1, hu1⟩ ⟨u2, hu2⟩ => by
use u1 * u2 * s2
-- Put everything in the same shape, sorting the terms using `simp`
have hu1' := congr_arg ((u2 * s3) • ·) hu1.symm
have hu2' := congr_arg ((u1 * s1) • ·) hu2.symm
simp only [← mul_smul, smul_assoc, mul_assoc, mul_comm, mul_left_comm] at hu1' hu2' ⊢
rw [hu2', hu1']
symm := fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨u, hu⟩ => ⟨u, hu.symm⟩ }
#align localized_module.r.is_equiv LocalizedModule.r.isEquiv
instance r.setoid : Setoid (M × S) where
r := r S M
iseqv := ⟨(r.isEquiv S M).refl, (r.isEquiv S M).symm _ _, (r.isEquiv S M).trans _ _ _⟩
#align localized_module.r.setoid LocalizedModule.r.setoid
-- TODO: change `Localization` to use `r'` instead of `r` so that the two types are also defeq,
-- `Localization S = LocalizedModule S R`.
example {R} [CommSemiring R] (S : Submonoid R) : ⇑(Localization.r' S) = LocalizedModule.r S R :=
rfl
/-- If `S` is a multiplicative subset of a ring `R` and `M` an `R`-module, then
we can localize `M` by `S`.
-/
-- Porting note(#5171): @[nolint has_nonempty_instance]
def _root_.LocalizedModule : Type max u v :=
Quotient (r.setoid S M)
#align localized_module LocalizedModule
section
variable {M S}
/-- The canonical map sending `(m, s) ↦ m/s`-/
def mk (m : M) (s : S) : LocalizedModule S M :=
Quotient.mk' ⟨m, s⟩
#align localized_module.mk LocalizedModule.mk
theorem mk_eq {m m' : M} {s s' : S} : mk m s = mk m' s' ↔ ∃ u : S, u • s' • m = u • s • m' :=
Quotient.eq'
#align localized_module.mk_eq LocalizedModule.mk_eq
@[elab_as_elim]
theorem induction_on {β : LocalizedModule S M → Prop} (h : ∀ (m : M) (s : S), β (mk m s)) :
∀ x : LocalizedModule S M, β x := by
rintro ⟨⟨m, s⟩⟩
exact h m s
#align localized_module.induction_on LocalizedModule.induction_on
@[elab_as_elim]
theorem induction_on₂ {β : LocalizedModule S M → LocalizedModule S M → Prop}
(h : ∀ (m m' : M) (s s' : S), β (mk m s) (mk m' s')) : ∀ x y, β x y := by
rintro ⟨⟨m, s⟩⟩ ⟨⟨m', s'⟩⟩
exact h m m' s s'
#align localized_module.induction_on₂ LocalizedModule.induction_on₂
/-- If `f : M × S → α` respects the equivalence relation `LocalizedModule.r`, then
`f` descents to a map `LocalizedModule M S → α`.
-/
def liftOn {α : Type*} (x : LocalizedModule S M) (f : M × S → α)
(wd : ∀ (p p' : M × S), p ≈ p' → f p = f p') : α :=
Quotient.liftOn x f wd
#align localized_module.lift_on LocalizedModule.liftOn
theorem liftOn_mk {α : Type*} {f : M × S → α} (wd : ∀ (p p' : M × S), p ≈ p' → f p = f p')
(m : M) (s : S) : liftOn (mk m s) f wd = f ⟨m, s⟩ := by convert Quotient.liftOn_mk f wd ⟨m, s⟩
#align localized_module.lift_on_mk LocalizedModule.liftOn_mk
/-- If `f : M × S → M × S → α` respects the equivalence relation `LocalizedModule.r`, then
`f` descents to a map `LocalizedModule M S → LocalizedModule M S → α`.
-/
def liftOn₂ {α : Type*} (x y : LocalizedModule S M) (f : M × S → M × S → α)
(wd : ∀ (p q p' q' : M × S), p ≈ p' → q ≈ q' → f p q = f p' q') : α :=
Quotient.liftOn₂ x y f wd
#align localized_module.lift_on₂ LocalizedModule.liftOn₂
theorem liftOn₂_mk {α : Type*} (f : M × S → M × S → α)
(wd : ∀ (p q p' q' : M × S), p ≈ p' → q ≈ q' → f p q = f p' q') (m m' : M)
(s s' : S) : liftOn₂ (mk m s) (mk m' s') f wd = f ⟨m, s⟩ ⟨m', s'⟩ := by
convert Quotient.liftOn₂_mk f wd _ _
#align localized_module.lift_on₂_mk LocalizedModule.liftOn₂_mk
instance : Zero (LocalizedModule S M) :=
⟨mk 0 1⟩
/-- If `S` contains `0` then the localization at `S` is trivial. -/
theorem subsingleton (h : 0 ∈ S) : Subsingleton (LocalizedModule S M) := by
refine ⟨fun a b ↦ ?_⟩
induction a,b using LocalizedModule.induction_on₂
exact mk_eq.mpr ⟨⟨0, h⟩, by simp only [Submonoid.mk_smul, zero_smul]⟩
@[simp]
theorem zero_mk (s : S) : mk (0 : M) s = 0 :=
mk_eq.mpr ⟨1, by rw [one_smul, smul_zero, smul_zero, one_smul]⟩
#align localized_module.zero_mk LocalizedModule.zero_mk
instance : Add (LocalizedModule S M) where
add p1 p2 :=
liftOn₂ p1 p2 (fun x y => mk (y.2 • x.1 + x.2 • y.1) (x.2 * y.2)) <|
fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨m1', s1'⟩ ⟨m2', s2'⟩ ⟨u1, hu1⟩ ⟨u2, hu2⟩ =>
mk_eq.mpr
⟨u1 * u2, by
-- Put everything in the same shape, sorting the terms using `simp`
have hu1' := congr_arg ((u2 * s2 * s2') • ·) hu1
have hu2' := congr_arg ((u1 * s1 * s1') • ·) hu2
simp only [smul_add, ← mul_smul, smul_assoc, mul_assoc, mul_comm,
mul_left_comm] at hu1' hu2' ⊢
rw [hu1', hu2']⟩
theorem mk_add_mk {m1 m2 : M} {s1 s2 : S} :
mk m1 s1 + mk m2 s2 = mk (s2 • m1 + s1 • m2) (s1 * s2) :=
mk_eq.mpr <| ⟨1, rfl⟩
#align localized_module.mk_add_mk LocalizedModule.mk_add_mk
/-- Porting note: Some auxiliary lemmas are declared with `private` in the original mathlib3 file.
We take that policy here as well, and remove the `#align` lines accordingly. -/
private theorem add_assoc' (x y z : LocalizedModule S M) : x + y + z = x + (y + z) := by
induction' x using LocalizedModule.induction_on with mx sx
induction' y using LocalizedModule.induction_on with my sy
induction' z using LocalizedModule.induction_on with mz sz
simp only [mk_add_mk, smul_add]
refine mk_eq.mpr ⟨1, ?_⟩
rw [one_smul, one_smul]
congr 1
· rw [mul_assoc]
· rw [eq_comm, mul_comm, add_assoc, mul_smul, mul_smul, ← mul_smul sx sz, mul_comm, mul_smul]
private theorem add_comm' (x y : LocalizedModule S M) : x + y = y + x :=
LocalizedModule.induction_on₂ (fun m m' s s' => by rw [mk_add_mk, mk_add_mk, add_comm, mul_comm])
x y
private theorem zero_add' (x : LocalizedModule S M) : 0 + x = x :=
induction_on
(fun m s => by
rw [← zero_mk s, mk_add_mk, smul_zero, zero_add, mk_eq];
exact ⟨1, by rw [one_smul, mul_smul, one_smul]⟩)
x
private theorem add_zero' (x : LocalizedModule S M) : x + 0 = x :=
induction_on
(fun m s => by
rw [← zero_mk s, mk_add_mk, smul_zero, add_zero, mk_eq];
exact ⟨1, by rw [one_smul, mul_smul, one_smul]⟩)
x
instance hasNatSMul : SMul ℕ (LocalizedModule S M) where smul n := nsmulRec n
#align localized_module.has_nat_smul LocalizedModule.hasNatSMul
private theorem nsmul_zero' (x : LocalizedModule S M) : (0 : ℕ) • x = 0 :=
LocalizedModule.induction_on (fun _ _ => rfl) x
private theorem nsmul_succ' (n : ℕ) (x : LocalizedModule S M) : n.succ • x = n • x + x :=
LocalizedModule.induction_on (fun _ _ => rfl) x
instance : AddCommMonoid (LocalizedModule S M) where
add := (· + ·)
add_assoc := add_assoc'
zero := 0
zero_add := zero_add'
add_zero := add_zero'
nsmul := (· • ·)
nsmul_zero := nsmul_zero'
nsmul_succ := nsmul_succ'
add_comm := add_comm'
instance {M : Type*} [AddCommGroup M] [Module R M] : Neg (LocalizedModule S M) where
neg p :=
liftOn p (fun x => LocalizedModule.mk (-x.1) x.2) fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨u, hu⟩ => by
rw [mk_eq]
exact ⟨u, by simpa⟩
instance {M : Type*} [AddCommGroup M] [Module R M] : AddCommGroup (LocalizedModule S M) :=
{ show AddCommMonoid (LocalizedModule S M) by infer_instance with
add_left_neg := by
rintro ⟨m, s⟩
change
(liftOn (mk m s) (fun x => mk (-x.1) x.2) fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨u, hu⟩ => by
rw [mk_eq]
exact ⟨u, by simpa⟩) +
mk m s =
0
rw [liftOn_mk, mk_add_mk]
simp
-- TODO: fix the diamond
zsmul := zsmulRec }
theorem mk_neg {M : Type*} [AddCommGroup M] [Module R M] {m : M} {s : S} : mk (-m) s = -mk m s :=
rfl
#align localized_module.mk_neg LocalizedModule.mk_neg
instance {A : Type*} [Semiring A] [Algebra R A] {S : Submonoid R} :
Monoid (LocalizedModule S A) :=
{ mul := fun m₁ m₂ =>
liftOn₂ m₁ m₂ (fun x₁ x₂ => LocalizedModule.mk (x₁.1 * x₂.1) (x₁.2 * x₂.2))
(by
rintro ⟨a₁, s₁⟩ ⟨a₂, s₂⟩ ⟨b₁, t₁⟩ ⟨b₂, t₂⟩ ⟨u₁, e₁⟩ ⟨u₂, e₂⟩
rw [mk_eq]
use u₁ * u₂
dsimp only at e₁ e₂ ⊢
rw [eq_comm]
trans (u₁ • t₁ • a₁) • u₂ • t₂ • a₂
on_goal 1 => rw [e₁, e₂]
on_goal 2 => rw [eq_comm]
all_goals
rw [smul_smul, mul_mul_mul_comm, ← smul_eq_mul, ← smul_eq_mul A, smul_smul_smul_comm,
mul_smul, mul_smul])
one := mk 1 (1 : S)
one_mul := by
rintro ⟨a, s⟩
exact mk_eq.mpr ⟨1, by simp only [one_mul, one_smul]⟩
mul_one := by
rintro ⟨a, s⟩
exact mk_eq.mpr ⟨1, by simp only [mul_one, one_smul]⟩
mul_assoc := by
rintro ⟨a₁, s₁⟩ ⟨a₂, s₂⟩ ⟨a₃, s₃⟩
apply mk_eq.mpr _
use 1
simp only [one_mul, smul_smul, ← mul_assoc, mul_right_comm] }
instance {A : Type*} [Semiring A] [Algebra R A] {S : Submonoid R} :
Semiring (LocalizedModule S A) :=
{ show (AddCommMonoid (LocalizedModule S A)) by infer_instance,
show (Monoid (LocalizedModule S A)) by infer_instance with
left_distrib := by
rintro ⟨a₁, s₁⟩ ⟨a₂, s₂⟩ ⟨a₃, s₃⟩
apply mk_eq.mpr _
use 1
simp only [one_mul, smul_add, mul_add, mul_smul_comm, smul_smul, ← mul_assoc,
mul_right_comm]
right_distrib := by
rintro ⟨a₁, s₁⟩ ⟨a₂, s₂⟩ ⟨a₃, s₃⟩
apply mk_eq.mpr _
use 1
simp only [one_mul, smul_add, add_mul, smul_smul, ← mul_assoc, smul_mul_assoc,
mul_right_comm]
zero_mul := by
rintro ⟨a, s⟩
exact mk_eq.mpr ⟨1, by simp only [zero_mul, smul_zero]⟩
mul_zero := by
rintro ⟨a, s⟩
exact mk_eq.mpr ⟨1, by simp only [mul_zero, smul_zero]⟩ }
instance {A : Type*} [CommSemiring A] [Algebra R A] {S : Submonoid R} :
CommSemiring (LocalizedModule S A) :=
{ show Semiring (LocalizedModule S A) by infer_instance with
mul_comm := by
rintro ⟨a₁, s₁⟩ ⟨a₂, s₂⟩
exact mk_eq.mpr ⟨1, by simp only [one_smul, mul_comm]⟩ }
instance {A : Type*} [Ring A] [Algebra R A] {S : Submonoid R} :
Ring (LocalizedModule S A) :=
{ inferInstanceAs (AddCommGroup (LocalizedModule S A)),
inferInstanceAs (Semiring (LocalizedModule S A)) with }
instance {A : Type*} [CommRing A] [Algebra R A] {S : Submonoid R} :
CommRing (LocalizedModule S A) :=
{ show (Ring (LocalizedModule S A)) by infer_instance with
mul_comm := by
rintro ⟨a₁, s₁⟩ ⟨a₂, s₂⟩
exact mk_eq.mpr ⟨1, by simp only [one_smul, mul_comm]⟩ }
theorem mk_mul_mk {A : Type*} [Semiring A] [Algebra R A] {a₁ a₂ : A} {s₁ s₂ : S} :
mk a₁ s₁ * mk a₂ s₂ = mk (a₁ * a₂) (s₁ * s₂) :=
rfl
#align localized_module.mk_mul_mk LocalizedModule.mk_mul_mk
noncomputable instance : SMul T (LocalizedModule S M) where
smul x p :=
let a := IsLocalization.sec S x
liftOn p (fun p ↦ mk (a.1 • p.1) (a.2 * p.2))
(by
rintro p p' ⟨s, h⟩
refine mk_eq.mpr ⟨s, ?_⟩
calc
_ = a.2 • a.1 • s • p'.2 • p.1 := by
simp_rw [Submonoid.smul_def, Submonoid.coe_mul, ← mul_smul]; ring_nf
_ = a.2 • a.1 • s • p.2 • p'.1 := by rw [h]
_ = s • (a.2 * p.2) • a.1 • p'.1 := by
simp_rw [Submonoid.smul_def, ← mul_smul, Submonoid.coe_mul]; ring_nf )
theorem smul_def (x : T) (m : M) (s : S) :
x • mk m s = mk ((IsLocalization.sec S x).1 • m) ((IsLocalization.sec S x).2 * s) := rfl
theorem mk'_smul_mk (r : R) (m : M) (s s' : S) :
IsLocalization.mk' T r s • mk m s' = mk (r • m) (s * s') := by
rw [smul_def, mk_eq]
obtain ⟨c, hc⟩ := IsLocalization.eq.mp <| IsLocalization.mk'_sec T (IsLocalization.mk' T r s)
use c
simp_rw [← mul_smul, Submonoid.smul_def, Submonoid.coe_mul, ← mul_smul, ← mul_assoc,
mul_comm _ (s':R), mul_assoc, hc]
theorem mk_smul_mk (r : R) (m : M) (s t : S) :
Localization.mk r s • mk m t = mk (r • m) (s * t) := by
rw [Localization.mk_eq_mk']
exact mk'_smul_mk ..
#align localized_module.mk_smul_mk LocalizedModule.mk_smul_mk
variable {T}
private theorem one_smul_aux (p : LocalizedModule S M) : (1 : T) • p = p := by
induction' p using LocalizedModule.induction_on with m s
rw [show (1:T) = IsLocalization.mk' T (1:R) (1:S) by rw [IsLocalization.mk'_one, map_one]]
rw [mk'_smul_mk, one_smul, one_mul]
private theorem mul_smul_aux (x y : T) (p : LocalizedModule S M) :
(x * y) • p = x • y • p := by
induction' p using LocalizedModule.induction_on with m s
rw [← IsLocalization.mk'_sec (M := S) T x, ← IsLocalization.mk'_sec (M := S) T y]
simp_rw [← IsLocalization.mk'_mul, mk'_smul_mk, ← mul_smul, mul_assoc]
private theorem smul_add_aux (x : T) (p q : LocalizedModule S M) :
x • (p + q) = x • p + x • q := by
induction' p using LocalizedModule.induction_on with m s
induction' q using LocalizedModule.induction_on with n t
rw [smul_def, smul_def, mk_add_mk, mk_add_mk]
rw [show x • _ = IsLocalization.mk' T _ _ • _ by rw [IsLocalization.mk'_sec (M := S) T]]
rw [← IsLocalization.mk'_cancel _ _ (IsLocalization.sec S x).2, mk'_smul_mk]
congr 1
· simp only [Submonoid.smul_def, smul_add, ← mul_smul, Submonoid.coe_mul]; ring_nf
· rw [mul_mul_mul_comm] -- ring does not work here
private theorem smul_zero_aux (x : T) : x • (0 : LocalizedModule S M) = 0 := by
erw [smul_def, smul_zero, zero_mk]
private theorem add_smul_aux (x y : T) (p : LocalizedModule S M) :
(x + y) • p = x • p + y • p := by
induction' p using LocalizedModule.induction_on with m s
rw [smul_def T x, smul_def T y, mk_add_mk, show (x + y) • _ = IsLocalization.mk' T _ _ • _ by
rw [← IsLocalization.mk'_sec (M := S) T x, ← IsLocalization.mk'_sec (M := S) T y,
← IsLocalization.mk'_add, IsLocalization.mk'_cancel _ _ s], mk'_smul_mk, ← smul_assoc,
← smul_assoc, ← add_smul]
congr 1
· simp only [Submonoid.smul_def, Submonoid.coe_mul, smul_eq_mul]; ring_nf
· rw [mul_mul_mul_comm, mul_assoc] -- ring does not work here
private theorem zero_smul_aux (p : LocalizedModule S M) : (0 : T) • p = 0 := by
induction' p using LocalizedModule.induction_on with m s
rw [show (0:T) = IsLocalization.mk' T (0:R) (1:S) by rw [IsLocalization.mk'_zero], mk'_smul_mk,
zero_smul, zero_mk]
noncomputable instance isModule : Module T (LocalizedModule S M) where
smul := (· • ·)
one_smul := one_smul_aux
mul_smul := mul_smul_aux
smul_add := smul_add_aux
smul_zero := smul_zero_aux
add_smul := add_smul_aux
zero_smul := zero_smul_aux
@[simp]
theorem mk_cancel_common_left (s' s : S) (m : M) : mk (s' • m) (s' * s) = mk m s :=
mk_eq.mpr
⟨1, by
simp only [mul_smul, one_smul]
rw [smul_comm]⟩
#align localized_module.mk_cancel_common_left LocalizedModule.mk_cancel_common_left
@[simp]
theorem mk_cancel (s : S) (m : M) : mk (s • m) s = mk m 1 :=
mk_eq.mpr ⟨1, by simp⟩
#align localized_module.mk_cancel LocalizedModule.mk_cancel
@[simp]
theorem mk_cancel_common_right (s s' : S) (m : M) : mk (s' • m) (s * s') = mk m s :=
mk_eq.mpr ⟨1, by simp [mul_smul]⟩
#align localized_module.mk_cancel_common_right LocalizedModule.mk_cancel_common_right
noncomputable instance isModule' : Module R (LocalizedModule S M) :=
{ Module.compHom (LocalizedModule S M) <| algebraMap R (Localization S) with }
#align localized_module.is_module' LocalizedModule.isModule'
theorem smul'_mk (r : R) (s : S) (m : M) : r • mk m s = mk (r • m) s := by
erw [mk_smul_mk r m 1 s, one_mul]
#align localized_module.smul'_mk LocalizedModule.smul'_mk
theorem smul'_mul {A : Type*} [Semiring A] [Algebra R A] (x : T) (p₁ p₂ : LocalizedModule S A) :
x • p₁ * p₂ = x • (p₁ * p₂) := by
induction p₁, p₂ using induction_on₂ with | _ a₁ s₁ a₂ s₂ => _
rw [mk_mul_mk, smul_def, smul_def, mk_mul_mk, mul_assoc, smul_mul_assoc]
theorem mul_smul' {A : Type*} [Semiring A] [Algebra R A] (x : T) (p₁ p₂ : LocalizedModule S A) :
p₁ * x • p₂ = x • (p₁ * p₂) := by
induction p₁, p₂ using induction_on₂ with | _ a₁ s₁ a₂ s₂ => _
rw [smul_def, mk_mul_mk, mk_mul_mk, smul_def, mul_left_comm, mul_smul_comm]
variable (T)
noncomputable instance {A : Type*} [Semiring A] [Algebra R A] : Algebra T (LocalizedModule S A) :=
Algebra.ofModule smul'_mul mul_smul'
theorem algebraMap_mk' {A : Type*} [Semiring A] [Algebra R A] (a : R) (s : S) :
algebraMap _ _ (IsLocalization.mk' T a s) = mk (algebraMap R A a) s := by
rw [Algebra.algebraMap_eq_smul_one]
change _ • mk _ _ = _
rw [mk'_smul_mk, Algebra.algebraMap_eq_smul_one, mul_one]
theorem algebraMap_mk {A : Type*} [Semiring A] [Algebra R A] (a : R) (s : S) :
algebraMap _ _ (Localization.mk a s) = mk (algebraMap R A a) s := by
rw [Localization.mk_eq_mk']
exact algebraMap_mk' ..
#align localized_module.algebra_map_mk LocalizedModule.algebraMap_mk
instance : IsScalarTower R T (LocalizedModule S M) where
smul_assoc r x p := by
induction' p using LocalizedModule.induction_on with m s
rw [← IsLocalization.mk'_sec (M := S) T x, IsLocalization.smul_mk', mk'_smul_mk, mk'_smul_mk,
smul'_mk, mul_smul]
noncomputable instance algebra' {A : Type*} [Semiring A] [Algebra R A] :
Algebra R (LocalizedModule S A) :=
{ (algebraMap (Localization S) (LocalizedModule S A)).comp (algebraMap R <| Localization S),
show Module R (LocalizedModule S A) by infer_instance with
commutes' := by
intro r x
induction x using induction_on with | _ a s => _
dsimp
rw [← Localization.mk_one_eq_algebraMap, algebraMap_mk, mk_mul_mk, mk_mul_mk, mul_comm,
Algebra.commutes]
smul_def' := by
intro r x
induction x using induction_on with | _ a s => _
dsimp
rw [← Localization.mk_one_eq_algebraMap, algebraMap_mk, mk_mul_mk, smul'_mk,
Algebra.smul_def, one_mul] }
#align localized_module.algebra' LocalizedModule.algebra'
section
variable (S M)
/-- The function `m ↦ m / 1` as an `R`-linear map.
-/
@[simps]
def mkLinearMap : M →ₗ[R] LocalizedModule S M where
toFun m := mk m 1
map_add' x y := by simp [mk_add_mk]
map_smul' r x := (smul'_mk _ _ _).symm
#align localized_module.mk_linear_map LocalizedModule.mkLinearMap
end
/-- For any `s : S`, there is an `R`-linear map given by `a/b ↦ a/(b*s)`.
-/
@[simps]
def divBy (s : S) : LocalizedModule S M →ₗ[R] LocalizedModule S M where
toFun p :=
p.liftOn (fun p => mk p.1 (p.2 * s)) fun ⟨a, b⟩ ⟨a', b'⟩ ⟨c, eq1⟩ =>
mk_eq.mpr ⟨c, by rw [mul_smul, mul_smul, smul_comm _ s, smul_comm _ s, eq1, smul_comm _ s,
smul_comm _ s]⟩
map_add' x y := by
refine x.induction_on₂ ?_ y
intro m₁ m₂ t₁ t₂
simp_rw [mk_add_mk, LocalizedModule.liftOn_mk, mk_add_mk, mul_smul, mul_comm _ s, mul_assoc,
smul_comm _ s, ← smul_add, mul_left_comm s t₁ t₂, mk_cancel_common_left s]
map_smul' r x := by
refine x.induction_on (fun _ _ ↦ ?_)
dsimp only
change liftOn (mk _ _) _ _ = r • (liftOn (mk _ _) _ _)
simp_rw [liftOn_mk, mul_assoc, ← smul_def]
congr!
#align localized_module.div_by LocalizedModule.divBy
theorem divBy_mul_by (s : S) (p : LocalizedModule S M) :
divBy s (algebraMap R (Module.End R (LocalizedModule S M)) s p) = p :=
p.induction_on fun m t => by
rw [Module.algebraMap_end_apply, divBy_apply]
erw [smul_def]
rw [LocalizedModule.liftOn_mk, mul_assoc, ← smul_def]
erw [smul'_mk]
rw [← Submonoid.smul_def, mk_cancel_common_right _ s]
#align localized_module.div_by_mul_by LocalizedModule.divBy_mul_by
theorem mul_by_divBy (s : S) (p : LocalizedModule S M) :
algebraMap R (Module.End R (LocalizedModule S M)) s (divBy s p) = p :=
p.induction_on fun m t => by
rw [divBy_apply, Module.algebraMap_end_apply, LocalizedModule.liftOn_mk, smul'_mk,
← Submonoid.smul_def, mk_cancel_common_right _ s]
#align localized_module.mul_by_div_by LocalizedModule.mul_by_divBy
end
end LocalizedModule
section IsLocalizedModule
universe u v
variable {R : Type*} [CommSemiring R] (S : Submonoid R)
variable {M M' M'' : Type*} [AddCommMonoid M] [AddCommMonoid M'] [AddCommMonoid M'']
variable {A : Type*} [CommSemiring A] [Algebra R A] [Module A M'] [IsLocalization S A]
variable [Module R M] [Module R M'] [Module R M''] [IsScalarTower R A M']
variable (f : M →ₗ[R] M') (g : M →ₗ[R] M'')
/-- The characteristic predicate for localized module.
`IsLocalizedModule S f` describes that `f : M ⟶ M'` is the localization map identifying `M'` as
`LocalizedModule S M`.
-/
@[mk_iff] class IsLocalizedModule : Prop where
map_units : ∀ x : S, IsUnit (algebraMap R (Module.End R M') x)
surj' : ∀ y : M', ∃ x : M × S, x.2 • y = f x.1
exists_of_eq : ∀ {x₁ x₂}, f x₁ = f x₂ → ∃ c : S, c • x₁ = c • x₂
#align is_localized_module IsLocalizedModule
attribute [nolint docBlame] IsLocalizedModule.map_units IsLocalizedModule.surj'
IsLocalizedModule.exists_of_eq
-- Porting note: Manually added to make `S` and `f` explicit.
lemma IsLocalizedModule.surj [IsLocalizedModule S f] (y : M') : ∃ x : M × S, x.2 • y = f x.1 :=
surj' y
-- Porting note: Manually added to make `S` and `f` explicit.
lemma IsLocalizedModule.eq_iff_exists [IsLocalizedModule S f] {x₁ x₂} :
f x₁ = f x₂ ↔ ∃ c : S, c • x₁ = c • x₂ :=
Iff.intro exists_of_eq fun ⟨c, h⟩ ↦ by
apply_fun f at h
simp_rw [f.map_smul_of_tower, Submonoid.smul_def, ← Module.algebraMap_end_apply R R] at h
exact ((Module.End_isUnit_iff _).mp <| map_units f c).1 h
theorem IsLocalizedModule.of_linearEquiv (e : M' ≃ₗ[R] M'') [hf : IsLocalizedModule S f] :
IsLocalizedModule S (e ∘ₗ f : M →ₗ[R] M'') where
map_units s := by
rw [show algebraMap R (Module.End R M'') s = e ∘ₗ (algebraMap R (Module.End R M') s) ∘ₗ e.symm
by ext; simp, Module.End_isUnit_iff, LinearMap.coe_comp, LinearMap.coe_comp,
LinearEquiv.coe_coe, LinearEquiv.coe_coe, EquivLike.comp_bijective, EquivLike.bijective_comp]
exact (Module.End_isUnit_iff _).mp <| hf.map_units s
surj' x := by
obtain ⟨p, h⟩ := hf.surj' (e.symm x)
exact ⟨p, by rw [LinearMap.coe_comp, LinearEquiv.coe_coe, Function.comp_apply, ← e.congr_arg h,
Submonoid.smul_def, Submonoid.smul_def, LinearEquiv.map_smul, LinearEquiv.apply_symm_apply]⟩
exists_of_eq h := by
simp_rw [LinearMap.coe_comp, LinearEquiv.coe_coe, Function.comp_apply,
EmbeddingLike.apply_eq_iff_eq] at h
exact hf.exists_of_eq h
variable (M) in
lemma isLocalizedModule_id (R') [CommSemiring R'] [Algebra R R'] [IsLocalization S R'] [Module R' M]
[IsScalarTower R R' M] : IsLocalizedModule S (.id : M →ₗ[R] M) where
map_units s := by
rw [← (Algebra.lsmul R (A := R') R M).commutes]; exact (IsLocalization.map_units R' s).map _
surj' m := ⟨(m, 1), one_smul _ _⟩
exists_of_eq h := ⟨1, congr_arg _ h⟩
variable {S} in
theorem isLocalizedModule_iff_isLocalization {A Aₛ} [CommSemiring A] [Algebra R A] [CommSemiring Aₛ]
[Algebra A Aₛ] [Algebra R Aₛ] [IsScalarTower R A Aₛ] :
IsLocalizedModule S (IsScalarTower.toAlgHom R A Aₛ).toLinearMap ↔
IsLocalization (Algebra.algebraMapSubmonoid A S) Aₛ := by
rw [isLocalizedModule_iff, isLocalization_iff]
refine and_congr ?_ (and_congr (forall_congr' fun _ ↦ ?_) (forall₂_congr fun _ _ ↦ ?_))
· simp_rw [← (Algebra.lmul R Aₛ).commutes, Algebra.lmul_isUnit_iff, Subtype.forall,
Algebra.algebraMapSubmonoid, ← SetLike.mem_coe, Submonoid.coe_map,
Set.forall_mem_image, ← IsScalarTower.algebraMap_apply]
· simp_rw [Prod.exists, Subtype.exists, Algebra.algebraMapSubmonoid]
simp [← IsScalarTower.algebraMap_apply, Submonoid.mk_smul, Algebra.smul_def, mul_comm]
· congr!; simp_rw [Subtype.exists, Algebra.algebraMapSubmonoid]; simp [Algebra.smul_def]
instance {A Aₛ} [CommSemiring A] [Algebra R A][CommSemiring Aₛ] [Algebra A Aₛ] [Algebra R Aₛ]
[IsScalarTower R A Aₛ] [h : IsLocalization (Algebra.algebraMapSubmonoid A S) Aₛ] :
IsLocalizedModule S (IsScalarTower.toAlgHom R A Aₛ).toLinearMap :=
isLocalizedModule_iff_isLocalization.mpr h
lemma isLocalizedModule_iff_isLocalization' (R') [CommSemiring R'] [Algebra R R'] :
IsLocalizedModule S (Algebra.ofId R R').toLinearMap ↔ IsLocalization S R' := by
convert isLocalizedModule_iff_isLocalization (S := S) (A := R) (Aₛ := R')
exact (Submonoid.map_id S).symm
namespace LocalizedModule
/--
If `g` is a linear map `M → M''` such that all scalar multiplication by `s : S` is invertible, then
there is a linear map `LocalizedModule S M → M''`.
-/
noncomputable def lift' (g : M →ₗ[R] M'')
(h : ∀ x : S, IsUnit (algebraMap R (Module.End R M'') x)) : LocalizedModule S M → M'' :=
fun m =>
m.liftOn (fun p => (h p.2).unit⁻¹.val <| g p.1) fun ⟨m, s⟩ ⟨m', s'⟩ ⟨c, eq1⟩ => by
-- Porting note: We remove `generalize_proofs h1 h2`. This does nothing here.
dsimp only
simp only [Submonoid.smul_def] at eq1
rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, ← map_smul, eq_comm,
Module.End_algebraMap_isUnit_inv_apply_eq_iff]
have : c • s • g m' = c • s' • g m := by
simp only [Submonoid.smul_def, ← g.map_smul, eq1]
have : Function.Injective (h c).unit.inv := by
rw [Function.injective_iff_hasLeftInverse]
refine ⟨(h c).unit, ?_⟩
intro x
change ((h c).unit.1 * (h c).unit.inv) x = x
simp only [Units.inv_eq_val_inv, IsUnit.mul_val_inv, LinearMap.one_apply]
apply_fun (h c).unit.inv
erw [Units.inv_eq_val_inv, Module.End_algebraMap_isUnit_inv_apply_eq_iff, ←
(h c).unit⁻¹.val.map_smul]
symm
rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, ← g.map_smul, ← g.map_smul, ← g.map_smul, ←
g.map_smul, eq1]
#align localized_module.lift' LocalizedModule.lift'
theorem lift'_mk (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x))
(m : M) (s : S) :
LocalizedModule.lift' S g h (LocalizedModule.mk m s) = (h s).unit⁻¹.val (g m) :=
rfl
#align localized_module.lift'_mk LocalizedModule.lift'_mk
theorem lift'_add (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x))
(x y) :
LocalizedModule.lift' S g h (x + y) =
LocalizedModule.lift' S g h x + LocalizedModule.lift' S g h y :=
LocalizedModule.induction_on₂
(by
intro a a' b b'
erw [LocalizedModule.lift'_mk, LocalizedModule.lift'_mk, LocalizedModule.lift'_mk]
-- Porting note: We remove `generalize_proofs h1 h2 h3`. This only generalize `h1`.
erw [map_add, Module.End_algebraMap_isUnit_inv_apply_eq_iff, smul_add, ← map_smul,
← map_smul, ← map_smul]
congr 1 <;> symm
· erw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, mul_smul, ← map_smul]
rfl
· dsimp
erw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, mul_comm, mul_smul, ← map_smul]
rfl)
x y
#align localized_module.lift'_add LocalizedModule.lift'_add
theorem lift'_smul (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x))
(r : R) (m) : r • LocalizedModule.lift' S g h m = LocalizedModule.lift' S g h (r • m) :=
m.induction_on fun a b => by
rw [LocalizedModule.lift'_mk, LocalizedModule.smul'_mk, LocalizedModule.lift'_mk]
-- Porting note: We remove `generalize_proofs h1 h2`. This does nothing here.
rw [← map_smul, ← g.map_smul]
#align localized_module.lift'_smul LocalizedModule.lift'_smul
/--
If `g` is a linear map `M → M''` such that all scalar multiplication by `s : S` is invertible, then
there is a linear map `LocalizedModule S M → M''`.
-/
noncomputable def lift (g : M →ₗ[R] M'')
(h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x)) :
LocalizedModule S M →ₗ[R] M'' where
toFun := LocalizedModule.lift' S g h
map_add' := LocalizedModule.lift'_add S g h
map_smul' r x := by rw [LocalizedModule.lift'_smul, RingHom.id_apply]
#align localized_module.lift LocalizedModule.lift
/--
If `g` is a linear map `M → M''` such that all scalar multiplication by `s : S` is invertible, then
`lift g m s = s⁻¹ • g m`.
-/
theorem lift_mk
(g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit (algebraMap R (Module.End R M'') x)) (m : M) (s : S) :
LocalizedModule.lift S g h (LocalizedModule.mk m s) = (h s).unit⁻¹.val (g m) :=
rfl
#align localized_module.lift_mk LocalizedModule.lift_mk
/--
If `g` is a linear map `M → M''` such that all scalar multiplication by `s : S` is invertible, then
there is a linear map `lift g ∘ mkLinearMap = g`.
-/
theorem lift_comp (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x)) :
(lift S g h).comp (mkLinearMap S M) = g := by
ext x; dsimp; rw [LocalizedModule.lift_mk]
erw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, one_smul]
#align localized_module.lift_comp LocalizedModule.lift_comp
/--
If `g` is a linear map `M → M''` such that all scalar multiplication by `s : S` is invertible and
`l` is another linear map `LocalizedModule S M ⟶ M''` such that `l ∘ mkLinearMap = g` then
`l = lift g`
-/
theorem lift_unique (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x))
(l : LocalizedModule S M →ₗ[R] M'') (hl : l.comp (LocalizedModule.mkLinearMap S M) = g) :
LocalizedModule.lift S g h = l := by
ext x; induction' x using LocalizedModule.induction_on with m s
rw [LocalizedModule.lift_mk]
rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, ← hl, LinearMap.coe_comp,
Function.comp_apply, LocalizedModule.mkLinearMap_apply, ← l.map_smul, LocalizedModule.smul'_mk]
congr 1; rw [LocalizedModule.mk_eq]
refine ⟨1, ?_⟩; simp only [one_smul, Submonoid.smul_def]
#align localized_module.lift_unique LocalizedModule.lift_unique
end LocalizedModule
instance localizedModuleIsLocalizedModule :
IsLocalizedModule S (LocalizedModule.mkLinearMap S M) where
map_units s :=
⟨⟨algebraMap R (Module.End R (LocalizedModule S M)) s, LocalizedModule.divBy s,
DFunLike.ext _ _ <| LocalizedModule.mul_by_divBy s,
DFunLike.ext _ _ <| LocalizedModule.divBy_mul_by s⟩,
DFunLike.ext _ _ fun p =>
p.induction_on <| by
intros
rfl⟩
surj' p :=
p.induction_on fun m t => by
refine ⟨⟨m, t⟩, ?_⟩
erw [LocalizedModule.smul'_mk, LocalizedModule.mkLinearMap_apply, Submonoid.coe_subtype,
LocalizedModule.mk_cancel t]
exists_of_eq eq1 := by simpa only [eq_comm, one_smul] using LocalizedModule.mk_eq.mp eq1
#align localized_module_is_localized_module localizedModuleIsLocalizedModule
namespace IsLocalizedModule
variable [IsLocalizedModule S f]
/-- If `(M', f : M ⟶ M')` satisfies universal property of localized module, there is a canonical
map `LocalizedModule S M ⟶ M'`.
-/
noncomputable def fromLocalizedModule' : LocalizedModule S M → M' := fun p =>
p.liftOn (fun x => (IsLocalizedModule.map_units f x.2).unit⁻¹.val (f x.1))
(by
rintro ⟨a, b⟩ ⟨a', b'⟩ ⟨c, eq1⟩
dsimp
-- Porting note: We remove `generalize_proofs h1 h2`.
rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, ← map_smul, ← map_smul,
Module.End_algebraMap_isUnit_inv_apply_eq_iff', ← map_smul]
exact (IsLocalizedModule.eq_iff_exists S f).mpr ⟨c, eq1.symm⟩)
#align is_localized_module.from_localized_module' IsLocalizedModule.fromLocalizedModule'
@[simp]
theorem fromLocalizedModule'_mk (m : M) (s : S) :
fromLocalizedModule' S f (LocalizedModule.mk m s) =
(IsLocalizedModule.map_units f s).unit⁻¹.val (f m) :=
rfl
#align is_localized_module.from_localized_module'_mk IsLocalizedModule.fromLocalizedModule'_mk
theorem fromLocalizedModule'_add (x y : LocalizedModule S M) :
fromLocalizedModule' S f (x + y) = fromLocalizedModule' S f x + fromLocalizedModule' S f y :=
LocalizedModule.induction_on₂
(by
intro a a' b b'
simp only [LocalizedModule.mk_add_mk, fromLocalizedModule'_mk]
-- Porting note: We remove `generalize_proofs h1 h2 h3`.
rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, smul_add, ← map_smul, ← map_smul,
← map_smul, map_add]
congr 1
all_goals rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff']
· simp [mul_smul, Submonoid.smul_def]
· rw [Submonoid.coe_mul, LinearMap.map_smul_of_tower, mul_comm, mul_smul, Submonoid.smul_def])
x y
#align is_localized_module.from_localized_module'_add IsLocalizedModule.fromLocalizedModule'_add
theorem fromLocalizedModule'_smul (r : R) (x : LocalizedModule S M) :
r • fromLocalizedModule' S f x = fromLocalizedModule' S f (r • x) :=
LocalizedModule.induction_on
(by
intro a b
rw [fromLocalizedModule'_mk, LocalizedModule.smul'_mk, fromLocalizedModule'_mk]
-- Porting note: We remove `generalize_proofs h1`.
rw [f.map_smul, map_smul])
x
#align is_localized_module.from_localized_module'_smul IsLocalizedModule.fromLocalizedModule'_smul
/-- If `(M', f : M ⟶ M')` satisfies universal property of localized module, there is a canonical
map `LocalizedModule S M ⟶ M'`.
-/
noncomputable def fromLocalizedModule : LocalizedModule S M →ₗ[R] M' where
toFun := fromLocalizedModule' S f
map_add' := fromLocalizedModule'_add S f
map_smul' r x := by rw [fromLocalizedModule'_smul, RingHom.id_apply]
#align is_localized_module.from_localized_module IsLocalizedModule.fromLocalizedModule
theorem fromLocalizedModule_mk (m : M) (s : S) :
fromLocalizedModule S f (LocalizedModule.mk m s) =
(IsLocalizedModule.map_units f s).unit⁻¹.val (f m) :=
rfl
#align is_localized_module.from_localized_module_mk IsLocalizedModule.fromLocalizedModule_mk
theorem fromLocalizedModule.inj : Function.Injective <| fromLocalizedModule S f := fun x y eq1 => by
induction' x using LocalizedModule.induction_on with a b
induction' y using LocalizedModule.induction_on with a' b'
simp only [fromLocalizedModule_mk] at eq1
-- Porting note: We remove `generalize_proofs h1 h2`.
rw [Module.End_algebraMap_isUnit_inv_apply_eq_iff, ← LinearMap.map_smul,
Module.End_algebraMap_isUnit_inv_apply_eq_iff'] at eq1
rw [LocalizedModule.mk_eq, ← IsLocalizedModule.eq_iff_exists S f, Submonoid.smul_def,
Submonoid.smul_def, f.map_smul, f.map_smul, eq1]
#align is_localized_module.from_localized_module.inj IsLocalizedModule.fromLocalizedModule.inj
theorem fromLocalizedModule.surj : Function.Surjective <| fromLocalizedModule S f := fun x =>
let ⟨⟨m, s⟩, eq1⟩ := IsLocalizedModule.surj S f x
⟨LocalizedModule.mk m s, by
rw [fromLocalizedModule_mk, Module.End_algebraMap_isUnit_inv_apply_eq_iff, ← eq1,
Submonoid.smul_def]⟩
#align is_localized_module.from_localized_module.surj IsLocalizedModule.fromLocalizedModule.surj
theorem fromLocalizedModule.bij : Function.Bijective <| fromLocalizedModule S f :=
⟨fromLocalizedModule.inj _ _, fromLocalizedModule.surj _ _⟩
#align is_localized_module.from_localized_module.bij IsLocalizedModule.fromLocalizedModule.bij
/--
If `(M', f : M ⟶ M')` satisfies universal property of localized module, then `M'` is isomorphic to
`LocalizedModule S M` as an `R`-module.
-/
@[simps!]
noncomputable def iso : LocalizedModule S M ≃ₗ[R] M' :=
{ fromLocalizedModule S f,
Equiv.ofBijective (fromLocalizedModule S f) <| fromLocalizedModule.bij _ _ with }
#align is_localized_module.iso IsLocalizedModule.iso
theorem iso_apply_mk (m : M) (s : S) :
iso S f (LocalizedModule.mk m s) = (IsLocalizedModule.map_units f s).unit⁻¹.val (f m) :=
rfl
#align is_localized_module.iso_apply_mk IsLocalizedModule.iso_apply_mk
theorem iso_symm_apply_aux (m : M') :
(iso S f).symm m =
LocalizedModule.mk (IsLocalizedModule.surj S f m).choose.1
(IsLocalizedModule.surj S f m).choose.2 := by
-- Porting note: We remove `generalize_proofs _ h2`.
apply_fun iso S f using LinearEquiv.injective (iso S f)
rw [LinearEquiv.apply_symm_apply]
simp only [iso_apply, LinearMap.toFun_eq_coe, fromLocalizedModule_mk]
erw [Module.End_algebraMap_isUnit_inv_apply_eq_iff', (surj' _).choose_spec]
#align is_localized_module.iso_symm_apply_aux IsLocalizedModule.iso_symm_apply_aux
theorem iso_symm_apply' (m : M') (a : M) (b : S) (eq1 : b • m = f a) :
(iso S f).symm m = LocalizedModule.mk a b :=
(iso_symm_apply_aux S f m).trans <|
LocalizedModule.mk_eq.mpr <| by
-- Porting note: We remove `generalize_proofs h1`.
rw [← IsLocalizedModule.eq_iff_exists S f, Submonoid.smul_def, Submonoid.smul_def, f.map_smul,
f.map_smul, ← (surj' _).choose_spec, ← Submonoid.smul_def, ← Submonoid.smul_def, ← mul_smul,
mul_comm, mul_smul, eq1]
#align is_localized_module.iso_symm_apply' IsLocalizedModule.iso_symm_apply'
theorem iso_symm_comp : (iso S f).symm.toLinearMap.comp f = LocalizedModule.mkLinearMap S M := by
ext m
rw [LinearMap.comp_apply, LocalizedModule.mkLinearMap_apply, LinearEquiv.coe_coe, iso_symm_apply']
exact one_smul _ _
#align is_localized_module.iso_symm_comp IsLocalizedModule.iso_symm_comp
/--
If `M'` is a localized module and `g` is a linear map `M' → M''` such that all scalar multiplication
by `s : S` is invertible, then there is a linear map `M' → M''`.
-/
noncomputable def lift (g : M →ₗ[R] M'')
(h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x)) : M' →ₗ[R] M'' :=
(LocalizedModule.lift S g h).comp (iso S f).symm.toLinearMap
#align is_localized_module.lift IsLocalizedModule.lift
theorem lift_comp (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x)) :
(lift S f g h).comp f = g := by
dsimp only [IsLocalizedModule.lift]
rw [LinearMap.comp_assoc, iso_symm_comp, LocalizedModule.lift_comp S g h]
#align is_localized_module.lift_comp IsLocalizedModule.lift_comp
@[simp]
theorem lift_apply (g : M →ₗ[R] M'') (h) (x) :
lift S f g h (f x) = g x := LinearMap.congr_fun (lift_comp S f g h) x
theorem lift_unique (g : M →ₗ[R] M'') (h : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x))
(l : M' →ₗ[R] M'') (hl : l.comp f = g) : lift S f g h = l := by
dsimp only [IsLocalizedModule.lift]
rw [LocalizedModule.lift_unique S g h (l.comp (iso S f).toLinearMap), LinearMap.comp_assoc,
LinearEquiv.comp_coe, LinearEquiv.symm_trans_self, LinearEquiv.refl_toLinearMap,
LinearMap.comp_id]
rw [LinearMap.comp_assoc, ← hl]
congr 1
ext x
rw [LinearMap.comp_apply, LocalizedModule.mkLinearMap_apply, LinearEquiv.coe_coe, iso_apply,
fromLocalizedModule'_mk, Module.End_algebraMap_isUnit_inv_apply_eq_iff, OneMemClass.coe_one,
one_smul]
#align is_localized_module.lift_unique IsLocalizedModule.lift_unique
/-- Universal property from localized module:
If `(M', f : M ⟶ M')` is a localized module then it satisfies the following universal property:
For every `R`-module `M''` which every `s : S`-scalar multiplication is invertible and for every
`R`-linear map `g : M ⟶ M''`, there is a unique `R`-linear map `l : M' ⟶ M''` such that
`l ∘ f = g`.
```
M -----f----> M'
| /
|g /
| / l
v /
M''
```
-/
theorem is_universal :
∀ (g : M →ₗ[R] M'') (_ : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x)),
∃! l : M' →ₗ[R] M'', l.comp f = g :=
fun g h => ⟨lift S f g h, lift_comp S f g h, fun l hl => (lift_unique S f g h l hl).symm⟩
#align is_localized_module.is_universal IsLocalizedModule.is_universal
theorem ringHom_ext (map_unit : ∀ x : S, IsUnit ((algebraMap R (Module.End R M'')) x))
⦃j k : M' →ₗ[R] M''⦄ (h : j.comp f = k.comp f) : j = k := by
rw [← lift_unique S f (k.comp f) map_unit j h, lift_unique]
rfl
#align is_localized_module.ring_hom_ext IsLocalizedModule.ringHom_ext
/-- If `(M', f)` and `(M'', g)` both satisfy universal property of localized module, then `M', M''`
are isomorphic as `R`-module
-/
noncomputable def linearEquiv [IsLocalizedModule S g] : M' ≃ₗ[R] M'' :=
(iso S f).symm.trans (iso S g)
#align is_localized_module.linear_equiv IsLocalizedModule.linearEquiv
variable {S}
theorem smul_injective (s : S) : Function.Injective fun m : M' => s • m :=
((Module.End_isUnit_iff _).mp (IsLocalizedModule.map_units f s)).injective
#align is_localized_module.smul_injective IsLocalizedModule.smul_injective
theorem smul_inj (s : S) (m₁ m₂ : M') : s • m₁ = s • m₂ ↔ m₁ = m₂ :=
(smul_injective f s).eq_iff
#align is_localized_module.smul_inj IsLocalizedModule.smul_inj
/-- `mk' f m s` is the fraction `m/s` with respect to the localization map `f`. -/
noncomputable def mk' (m : M) (s : S) : M' :=
fromLocalizedModule S f (LocalizedModule.mk m s)
#align is_localized_module.mk' IsLocalizedModule.mk'
theorem mk'_smul (r : R) (m : M) (s : S) : mk' f (r • m) s = r • mk' f m s := by
delta mk'
rw [← LocalizedModule.smul'_mk, LinearMap.map_smul]
#align is_localized_module.mk'_smul IsLocalizedModule.mk'_smul
theorem mk'_add_mk' (m₁ m₂ : M) (s₁ s₂ : S) :
mk' f m₁ s₁ + mk' f m₂ s₂ = mk' f (s₂ • m₁ + s₁ • m₂) (s₁ * s₂) := by
delta mk'
rw [← map_add, LocalizedModule.mk_add_mk]
#align is_localized_module.mk'_add_mk' IsLocalizedModule.mk'_add_mk'
@[simp]
theorem mk'_zero (s : S) : mk' f 0 s = 0 := by rw [← zero_smul R (0 : M), mk'_smul, zero_smul]
#align is_localized_module.mk'_zero IsLocalizedModule.mk'_zero
variable (S)
@[simp]
theorem mk'_one (m : M) : mk' f m (1 : S) = f m := by
delta mk'
rw [fromLocalizedModule_mk, Module.End_algebraMap_isUnit_inv_apply_eq_iff, Submonoid.coe_one,
one_smul]
#align is_localized_module.mk'_one IsLocalizedModule.mk'_one
variable {S}
@[simp]
theorem mk'_cancel (m : M) (s : S) : mk' f (s • m) s = f m := by
delta mk'
rw [LocalizedModule.mk_cancel, ← mk'_one S f, fromLocalizedModule_mk,
Module.End_algebraMap_isUnit_inv_apply_eq_iff, OneMemClass.coe_one, mk'_one, one_smul]
#align is_localized_module.mk'_cancel IsLocalizedModule.mk'_cancel
@[simp]
theorem mk'_cancel' (m : M) (s : S) : s • mk' f m s = f m := by
rw [Submonoid.smul_def, ← mk'_smul, ← Submonoid.smul_def, mk'_cancel]
#align is_localized_module.mk'_cancel' IsLocalizedModule.mk'_cancel'
@[simp]
theorem mk'_cancel_left (m : M) (s₁ s₂ : S) : mk' f (s₁ • m) (s₁ * s₂) = mk' f m s₂ := by
delta mk'
rw [LocalizedModule.mk_cancel_common_left]
#align is_localized_module.mk'_cancel_left IsLocalizedModule.mk'_cancel_left
@[simp]
theorem mk'_cancel_right (m : M) (s₁ s₂ : S) : mk' f (s₂ • m) (s₁ * s₂) = mk' f m s₁ := by
delta mk'
rw [LocalizedModule.mk_cancel_common_right]
#align is_localized_module.mk'_cancel_right IsLocalizedModule.mk'_cancel_right
theorem mk'_add (m₁ m₂ : M) (s : S) : mk' f (m₁ + m₂) s = mk' f m₁ s + mk' f m₂ s := by
rw [mk'_add_mk', ← smul_add, mk'_cancel_left]
#align is_localized_module.mk'_add IsLocalizedModule.mk'_add
theorem mk'_eq_mk'_iff (m₁ m₂ : M) (s₁ s₂ : S) :
mk' f m₁ s₁ = mk' f m₂ s₂ ↔ ∃ s : S, s • s₁ • m₂ = s • s₂ • m₁ := by
delta mk'
rw [(fromLocalizedModule.inj S f).eq_iff, LocalizedModule.mk_eq]
simp_rw [eq_comm]
#align is_localized_module.mk'_eq_mk'_iff IsLocalizedModule.mk'_eq_mk'_iff
theorem mk'_neg {M M' : Type*} [AddCommGroup M] [AddCommGroup M'] [Module R M] [Module R M']
(f : M →ₗ[R] M') [IsLocalizedModule S f] (m : M) (s : S) : mk' f (-m) s = -mk' f m s := by
delta mk'
rw [LocalizedModule.mk_neg, map_neg]
#align is_localized_module.mk'_neg IsLocalizedModule.mk'_neg
theorem mk'_sub {M M' : Type*} [AddCommGroup M] [AddCommGroup M'] [Module R M] [Module R M']
(f : M →ₗ[R] M') [IsLocalizedModule S f] (m₁ m₂ : M) (s : S) :
mk' f (m₁ - m₂) s = mk' f m₁ s - mk' f m₂ s := by
rw [sub_eq_add_neg, sub_eq_add_neg, mk'_add, mk'_neg]
#align is_localized_module.mk'_sub IsLocalizedModule.mk'_sub
theorem mk'_sub_mk' {M M' : Type*} [AddCommGroup M] [AddCommGroup M'] [Module R M] [Module R M']
(f : M →ₗ[R] M') [IsLocalizedModule S f] (m₁ m₂ : M) (s₁ s₂ : S) :
mk' f m₁ s₁ - mk' f m₂ s₂ = mk' f (s₂ • m₁ - s₁ • m₂) (s₁ * s₂) := by
rw [sub_eq_add_neg, ← mk'_neg, mk'_add_mk', smul_neg, ← sub_eq_add_neg]
#align is_localized_module.mk'_sub_mk' IsLocalizedModule.mk'_sub_mk'
theorem mk'_mul_mk'_of_map_mul {M M' : Type*} [Semiring M] [Semiring M'] [Module R M]
[Algebra R M'] (f : M →ₗ[R] M') (hf : ∀ m₁ m₂, f (m₁ * m₂) = f m₁ * f m₂)
[IsLocalizedModule S f] (m₁ m₂ : M) (s₁ s₂ : S) :
mk' f m₁ s₁ * mk' f m₂ s₂ = mk' f (m₁ * m₂) (s₁ * s₂) := by
symm
apply (Module.End_algebraMap_isUnit_inv_apply_eq_iff _ _ _ _).mpr
simp_rw [Submonoid.coe_mul, ← smul_eq_mul]
rw [smul_smul_smul_comm, ← mk'_smul, ← mk'_smul]
simp_rw [← Submonoid.smul_def, mk'_cancel, smul_eq_mul, hf]
#align is_localized_module.mk'_mul_mk'_of_map_mul IsLocalizedModule.mk'_mul_mk'_of_map_mul
theorem mk'_mul_mk' {M M' : Type*} [Semiring M] [Semiring M'] [Algebra R M] [Algebra R M']
(f : M →ₐ[R] M') [IsLocalizedModule S f.toLinearMap] (m₁ m₂ : M) (s₁ s₂ : S) :
mk' f.toLinearMap m₁ s₁ * mk' f.toLinearMap m₂ s₂ = mk' f.toLinearMap (m₁ * m₂) (s₁ * s₂) :=
mk'_mul_mk'_of_map_mul f.toLinearMap f.map_mul m₁ m₂ s₁ s₂
#align is_localized_module.mk'_mul_mk' IsLocalizedModule.mk'_mul_mk'
variable {f}
/-- Porting note (#10618): simp can prove this
@[simp] -/
theorem mk'_eq_iff {m : M} {s : S} {m' : M'} : mk' f m s = m' ↔ f m = s • m' := by
rw [← smul_inj f s, Submonoid.smul_def, ← mk'_smul, ← Submonoid.smul_def, mk'_cancel]
#align is_localized_module.mk'_eq_iff IsLocalizedModule.mk'_eq_iff
@[simp]
theorem mk'_eq_zero {m : M} (s : S) : mk' f m s = 0 ↔ f m = 0 := by rw [mk'_eq_iff, smul_zero]
#align is_localized_module.mk'_eq_zero IsLocalizedModule.mk'_eq_zero
variable (f)
theorem mk'_eq_zero' {m : M} (s : S) : mk' f m s = 0 ↔ ∃ s' : S, s' • m = 0 := by
simp_rw [← mk'_zero f (1 : S), mk'_eq_mk'_iff, smul_zero, one_smul, eq_comm]
#align is_localized_module.mk'_eq_zero' IsLocalizedModule.mk'_eq_zero'
theorem mk_eq_mk' (s : S) (m : M) :
LocalizedModule.mk m s = mk' (LocalizedModule.mkLinearMap S M) m s := by
rw [eq_comm, mk'_eq_iff, Submonoid.smul_def, LocalizedModule.smul'_mk, ← Submonoid.smul_def,
LocalizedModule.mk_cancel, LocalizedModule.mkLinearMap_apply]
#align is_localized_module.mk_eq_mk' IsLocalizedModule.mk_eq_mk'
variable (A) in
lemma mk'_smul_mk' (x : R) (m : M) (s t : S) :
IsLocalization.mk' A x s • mk' f m t = mk' f (x • m) (s * t) := by
apply smul_injective f (s * t)
conv_lhs => simp only [smul_assoc, mul_smul, smul_comm t]
simp only [mk'_cancel', map_smul, Submonoid.smul_def s]
rw [← smul_assoc, IsLocalization.smul_mk'_self, algebraMap_smul]
variable (S)
theorem eq_zero_iff {m : M} : f m = 0 ↔ ∃ s' : S, s' • m = 0 :=
(mk'_eq_zero (1 : S)).symm.trans (mk'_eq_zero' f _)
#align is_localized_module.eq_zero_iff IsLocalizedModule.eq_zero_iff
| Mathlib/Algebra/Module/LocalizedModule.lean | 1,102 | 1,105 | theorem mk'_surjective : Function.Surjective (Function.uncurry <| mk' f : M × S → M') := by |
intro x
obtain ⟨⟨m, s⟩, e : s • x = f m⟩ := IsLocalizedModule.surj S f x
exact ⟨⟨m, s⟩, mk'_eq_iff.mpr e.symm⟩
|
/-
Copyright (c) 2021 Bryan Gin-ge Chen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bryan Gin-ge Chen, Yaël Dillies
-/
import Mathlib.Algebra.PUnitInstances
import Mathlib.Tactic.Abel
import Mathlib.Tactic.Ring
import Mathlib.Order.Hom.Lattice
#align_import algebra.ring.boolean_ring from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3"
/-!
# Boolean rings
A Boolean ring is a ring where multiplication is idempotent. They are equivalent to Boolean
algebras.
## Main declarations
* `BooleanRing`: a typeclass for rings where multiplication is idempotent.
* `BooleanRing.toBooleanAlgebra`: Turn a Boolean ring into a Boolean algebra.
* `BooleanAlgebra.toBooleanRing`: Turn a Boolean algebra into a Boolean ring.
* `AsBoolAlg`: Type-synonym for the Boolean algebra associated to a Boolean ring.
* `AsBoolRing`: Type-synonym for the Boolean ring associated to a Boolean algebra.
## Implementation notes
We provide two ways of turning a Boolean algebra/ring into a Boolean ring/algebra:
* Instances on the same type accessible in locales `BooleanAlgebraOfBooleanRing` and
`BooleanRingOfBooleanAlgebra`.
* Type-synonyms `AsBoolAlg` and `AsBoolRing`.
At this point in time, it is not clear the first way is useful, but we keep it for educational
purposes and because it is easier than dealing with
`ofBoolAlg`/`toBoolAlg`/`ofBoolRing`/`toBoolRing` explicitly.
## Tags
boolean ring, boolean algebra
-/
open scoped symmDiff
variable {α β γ : Type*}
/-- A Boolean ring is a ring where multiplication is idempotent. -/
class BooleanRing (α) extends Ring α where
/-- Multiplication in a boolean ring is idempotent. -/
mul_self : ∀ a : α, a * a = a
#align boolean_ring BooleanRing
section BooleanRing
variable [BooleanRing α] (a b : α)
instance : Std.IdempotentOp (α := α) (· * ·) :=
⟨BooleanRing.mul_self⟩
@[simp]
theorem mul_self : a * a = a :=
BooleanRing.mul_self _
#align mul_self mul_self
@[simp]
theorem add_self : a + a = 0 := by
have : a + a = a + a + (a + a) :=
calc
a + a = (a + a) * (a + a) := by rw [mul_self]
_ = a * a + a * a + (a * a + a * a) := by rw [add_mul, mul_add]
_ = a + a + (a + a) := by rw [mul_self]
rwa [self_eq_add_left] at this
#align add_self add_self
@[simp]
theorem neg_eq : -a = a :=
calc
-a = -a + 0 := by rw [add_zero]
_ = -a + -a + a := by rw [← neg_add_self, add_assoc]
_ = a := by rw [add_self, zero_add]
#align neg_eq neg_eq
theorem add_eq_zero' : a + b = 0 ↔ a = b :=
calc
a + b = 0 ↔ a = -b := add_eq_zero_iff_eq_neg
_ ↔ a = b := by rw [neg_eq]
#align add_eq_zero' add_eq_zero'
@[simp]
theorem mul_add_mul : a * b + b * a = 0 := by
have : a + b = a + b + (a * b + b * a) :=
calc
a + b = (a + b) * (a + b) := by rw [mul_self]
_ = a * a + a * b + (b * a + b * b) := by rw [add_mul, mul_add, mul_add]
_ = a + a * b + (b * a + b) := by simp only [mul_self]
_ = a + b + (a * b + b * a) := by abel
rwa [self_eq_add_right] at this
#align mul_add_mul mul_add_mul
@[simp]
theorem sub_eq_add : a - b = a + b := by rw [sub_eq_add_neg, add_right_inj, neg_eq]
#align sub_eq_add sub_eq_add
@[simp]
theorem mul_one_add_self : a * (1 + a) = 0 := by rw [mul_add, mul_one, mul_self, add_self]
#align mul_one_add_self mul_one_add_self
-- Note [lower instance priority]
instance (priority := 100) BooleanRing.toCommRing : CommRing α :=
{ (inferInstance : BooleanRing α) with
mul_comm := fun a b => by rw [← add_eq_zero', mul_add_mul] }
#align boolean_ring.to_comm_ring BooleanRing.toCommRing
end BooleanRing
instance : BooleanRing PUnit :=
⟨fun _ => Subsingleton.elim _ _⟩
/-! ### Turning a Boolean ring into a Boolean algebra -/
section RingToAlgebra
/-- Type synonym to view a Boolean ring as a Boolean algebra. -/
def AsBoolAlg (α : Type*) :=
α
#align as_boolalg AsBoolAlg
/-- The "identity" equivalence between `AsBoolAlg α` and `α`. -/
def toBoolAlg : α ≃ AsBoolAlg α :=
Equiv.refl _
#align to_boolalg toBoolAlg
/-- The "identity" equivalence between `α` and `AsBoolAlg α`. -/
def ofBoolAlg : AsBoolAlg α ≃ α :=
Equiv.refl _
#align of_boolalg ofBoolAlg
@[simp]
theorem toBoolAlg_symm_eq : (@toBoolAlg α).symm = ofBoolAlg :=
rfl
#align to_boolalg_symm_eq toBoolAlg_symm_eq
@[simp]
theorem ofBoolAlg_symm_eq : (@ofBoolAlg α).symm = toBoolAlg :=
rfl
#align of_boolalg_symm_eq ofBoolAlg_symm_eq
@[simp]
theorem toBoolAlg_ofBoolAlg (a : AsBoolAlg α) : toBoolAlg (ofBoolAlg a) = a :=
rfl
#align to_boolalg_of_boolalg toBoolAlg_ofBoolAlg
@[simp]
theorem ofBoolAlg_toBoolAlg (a : α) : ofBoolAlg (toBoolAlg a) = a :=
rfl
#align of_boolalg_to_boolalg ofBoolAlg_toBoolAlg
-- Porting note (#10618): simp can prove this -- @[simp]
theorem toBoolAlg_inj {a b : α} : toBoolAlg a = toBoolAlg b ↔ a = b :=
Iff.rfl
#align to_boolalg_inj toBoolAlg_inj
-- Porting note (#10618): simp can prove this -- @[simp]
theorem ofBoolAlg_inj {a b : AsBoolAlg α} : ofBoolAlg a = ofBoolAlg b ↔ a = b :=
Iff.rfl
#align of_boolalg_inj ofBoolAlg_inj
instance [Inhabited α] : Inhabited (AsBoolAlg α) :=
‹Inhabited α›
variable [BooleanRing α] [BooleanRing β] [BooleanRing γ]
namespace BooleanRing
/-- The join operation in a Boolean ring is `x + y + x * y`. -/
def sup : Sup α :=
⟨fun x y => x + y + x * y⟩
#align boolean_ring.has_sup BooleanRing.sup
/-- The meet operation in a Boolean ring is `x * y`. -/
def inf : Inf α :=
⟨(· * ·)⟩
#align boolean_ring.has_inf BooleanRing.inf
-- Porting note (#11215): TODO: add priority 100. lower instance priority
scoped [BooleanAlgebraOfBooleanRing] attribute [instance] BooleanRing.sup
scoped [BooleanAlgebraOfBooleanRing] attribute [instance] BooleanRing.inf
open BooleanAlgebraOfBooleanRing
theorem sup_comm (a b : α) : a ⊔ b = b ⊔ a := by
dsimp only [(· ⊔ ·)]
ring
#align boolean_ring.sup_comm BooleanRing.sup_comm
theorem inf_comm (a b : α) : a ⊓ b = b ⊓ a := by
dsimp only [(· ⊓ ·)]
ring
#align boolean_ring.inf_comm BooleanRing.inf_comm
theorem sup_assoc (a b c : α) : a ⊔ b ⊔ c = a ⊔ (b ⊔ c) := by
dsimp only [(· ⊔ ·)]
ring
#align boolean_ring.sup_assoc BooleanRing.sup_assoc
theorem inf_assoc (a b c : α) : a ⊓ b ⊓ c = a ⊓ (b ⊓ c) := by
dsimp only [(· ⊓ ·)]
ring
#align boolean_ring.inf_assoc BooleanRing.inf_assoc
theorem sup_inf_self (a b : α) : a ⊔ a ⊓ b = a := by
dsimp only [(· ⊔ ·), (· ⊓ ·)]
rw [← mul_assoc, mul_self, add_assoc, add_self, add_zero]
#align boolean_ring.sup_inf_self BooleanRing.sup_inf_self
theorem inf_sup_self (a b : α) : a ⊓ (a ⊔ b) = a := by
dsimp only [(· ⊔ ·), (· ⊓ ·)]
rw [mul_add, mul_add, mul_self, ← mul_assoc, mul_self, add_assoc, add_self, add_zero]
#align boolean_ring.inf_sup_self BooleanRing.inf_sup_self
theorem le_sup_inf_aux (a b c : α) : (a + b + a * b) * (a + c + a * c) = a + b * c + a * (b * c) :=
calc
(a + b + a * b) * (a + c + a * c) =
a * a + b * c + a * (b * c) + (a * b + a * a * b) + (a * c + a * a * c) +
(a * b * c + a * a * b * c) := by ring
_ = a + b * c + a * (b * c) := by simp only [mul_self, add_self, add_zero]
#align boolean_ring.le_sup_inf_aux BooleanRing.le_sup_inf_aux
| Mathlib/Algebra/Ring/BooleanRing.lean | 230 | 232 | theorem le_sup_inf (a b c : α) : (a ⊔ b) ⊓ (a ⊔ c) ⊔ (a ⊔ b ⊓ c) = a ⊔ b ⊓ c := by |
dsimp only [(· ⊔ ·), (· ⊓ ·)]
rw [le_sup_inf_aux, add_self, mul_self, zero_add]
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.MFDeriv.Defs
#align_import geometry.manifold.mfderiv from "leanprover-community/mathlib"@"e473c3198bb41f68560cab68a0529c854b618833"
/-!
# Basic properties of the manifold Fréchet derivative
In this file, we show various properties of the manifold Fréchet derivative,
mimicking the API for Fréchet derivatives.
- basic properties of unique differentiability sets
- various general lemmas about the manifold Fréchet derivative
- deducing differentiability from smoothness,
- deriving continuity from differentiability on manifolds,
- congruence lemmas for derivatives on manifolds
- composition lemmas and the chain rule
-/
noncomputable section
open scoped Topology Manifold
open Set Bundle
section DerivativesProperties
/-! ### Unique differentiability sets in manifolds -/
variable
{𝕜 : Type*} [NontriviallyNormedField 𝕜]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
{H : Type*} [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H)
{M : Type*} [TopologicalSpace M] [ChartedSpace H M]
{E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E']
{H' : Type*} [TopologicalSpace H'] {I' : ModelWithCorners 𝕜 E' H'}
{M' : Type*} [TopologicalSpace M'] [ChartedSpace H' M']
{E'' : Type*} [NormedAddCommGroup E''] [NormedSpace 𝕜 E'']
{H'' : Type*} [TopologicalSpace H''] {I'' : ModelWithCorners 𝕜 E'' H''}
{M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M'']
{f f₀ f₁ : M → M'} {x : M} {s t : Set M} {g : M' → M''} {u : Set M'}
theorem uniqueMDiffWithinAt_univ : UniqueMDiffWithinAt I univ x := by
unfold UniqueMDiffWithinAt
simp only [preimage_univ, univ_inter]
exact I.unique_diff _ (mem_range_self _)
#align unique_mdiff_within_at_univ uniqueMDiffWithinAt_univ
variable {I}
theorem uniqueMDiffWithinAt_iff {s : Set M} {x : M} :
UniqueMDiffWithinAt I s x ↔
UniqueDiffWithinAt 𝕜 ((extChartAt I x).symm ⁻¹' s ∩ (extChartAt I x).target)
((extChartAt I x) x) := by
apply uniqueDiffWithinAt_congr
rw [nhdsWithin_inter, nhdsWithin_inter, nhdsWithin_extChartAt_target_eq]
#align unique_mdiff_within_at_iff uniqueMDiffWithinAt_iff
nonrec theorem UniqueMDiffWithinAt.mono_nhds {s t : Set M} {x : M} (hs : UniqueMDiffWithinAt I s x)
(ht : 𝓝[s] x ≤ 𝓝[t] x) : UniqueMDiffWithinAt I t x :=
hs.mono_nhds <| by simpa only [← map_extChartAt_nhdsWithin] using Filter.map_mono ht
theorem UniqueMDiffWithinAt.mono_of_mem {s t : Set M} {x : M} (hs : UniqueMDiffWithinAt I s x)
(ht : t ∈ 𝓝[s] x) : UniqueMDiffWithinAt I t x :=
hs.mono_nhds (nhdsWithin_le_iff.2 ht)
theorem UniqueMDiffWithinAt.mono (h : UniqueMDiffWithinAt I s x) (st : s ⊆ t) :
UniqueMDiffWithinAt I t x :=
UniqueDiffWithinAt.mono h <| inter_subset_inter (preimage_mono st) (Subset.refl _)
#align unique_mdiff_within_at.mono UniqueMDiffWithinAt.mono
theorem UniqueMDiffWithinAt.inter' (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝[s] x) :
UniqueMDiffWithinAt I (s ∩ t) x :=
hs.mono_of_mem (Filter.inter_mem self_mem_nhdsWithin ht)
#align unique_mdiff_within_at.inter' UniqueMDiffWithinAt.inter'
theorem UniqueMDiffWithinAt.inter (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝 x) :
UniqueMDiffWithinAt I (s ∩ t) x :=
hs.inter' (nhdsWithin_le_nhds ht)
#align unique_mdiff_within_at.inter UniqueMDiffWithinAt.inter
theorem IsOpen.uniqueMDiffWithinAt (hs : IsOpen s) (xs : x ∈ s) : UniqueMDiffWithinAt I s x :=
(uniqueMDiffWithinAt_univ I).mono_of_mem <| nhdsWithin_le_nhds <| hs.mem_nhds xs
#align is_open.unique_mdiff_within_at IsOpen.uniqueMDiffWithinAt
theorem UniqueMDiffOn.inter (hs : UniqueMDiffOn I s) (ht : IsOpen t) : UniqueMDiffOn I (s ∩ t) :=
fun _x hx => UniqueMDiffWithinAt.inter (hs _ hx.1) (ht.mem_nhds hx.2)
#align unique_mdiff_on.inter UniqueMDiffOn.inter
theorem IsOpen.uniqueMDiffOn (hs : IsOpen s) : UniqueMDiffOn I s :=
fun _x hx => hs.uniqueMDiffWithinAt hx
#align is_open.unique_mdiff_on IsOpen.uniqueMDiffOn
theorem uniqueMDiffOn_univ : UniqueMDiffOn I (univ : Set M) :=
isOpen_univ.uniqueMDiffOn
#align unique_mdiff_on_univ uniqueMDiffOn_univ
/- We name the typeclass variables related to `SmoothManifoldWithCorners` structure as they are
necessary in lemmas mentioning the derivative, but not in lemmas about differentiability, so we
want to include them or omit them when necessary. -/
variable [Is : SmoothManifoldWithCorners I M] [I's : SmoothManifoldWithCorners I' M']
[I''s : SmoothManifoldWithCorners I'' M'']
{f' f₀' f₁' : TangentSpace I x →L[𝕜] TangentSpace I' (f x)}
{g' : TangentSpace I' (f x) →L[𝕜] TangentSpace I'' (g (f x))}
/-- `UniqueMDiffWithinAt` achieves its goal: it implies the uniqueness of the derivative. -/
nonrec theorem UniqueMDiffWithinAt.eq (U : UniqueMDiffWithinAt I s x)
(h : HasMFDerivWithinAt I I' f s x f') (h₁ : HasMFDerivWithinAt I I' f s x f₁') : f' = f₁' := by
-- Porting note: didn't need `convert` because of finding instances by unification
convert U.eq h.2 h₁.2
#align unique_mdiff_within_at.eq UniqueMDiffWithinAt.eq
theorem UniqueMDiffOn.eq (U : UniqueMDiffOn I s) (hx : x ∈ s) (h : HasMFDerivWithinAt I I' f s x f')
(h₁ : HasMFDerivWithinAt I I' f s x f₁') : f' = f₁' :=
UniqueMDiffWithinAt.eq (U _ hx) h h₁
#align unique_mdiff_on.eq UniqueMDiffOn.eq
nonrec theorem UniqueMDiffWithinAt.prod {x : M} {y : M'} {s t} (hs : UniqueMDiffWithinAt I s x)
(ht : UniqueMDiffWithinAt I' t y) : UniqueMDiffWithinAt (I.prod I') (s ×ˢ t) (x, y) := by
refine (hs.prod ht).mono ?_
rw [ModelWithCorners.range_prod, ← prod_inter_prod]
rfl
theorem UniqueMDiffOn.prod {s : Set M} {t : Set M'} (hs : UniqueMDiffOn I s)
(ht : UniqueMDiffOn I' t) : UniqueMDiffOn (I.prod I') (s ×ˢ t) := fun x h ↦
(hs x.1 h.1).prod (ht x.2 h.2)
/-!
### General lemmas on derivatives of functions between manifolds
We mimick the API for functions between vector spaces
-/
theorem mdifferentiableWithinAt_iff {f : M → M'} {s : Set M} {x : M} :
MDifferentiableWithinAt I I' f s x ↔
ContinuousWithinAt f s x ∧
DifferentiableWithinAt 𝕜 (writtenInExtChartAt I I' x f)
((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' s) ((extChartAt I x) x) := by
rw [mdifferentiableWithinAt_iff']
refine and_congr Iff.rfl (exists_congr fun f' => ?_)
rw [inter_comm]
simp only [HasFDerivWithinAt, nhdsWithin_inter, nhdsWithin_extChartAt_target_eq]
#align mdifferentiable_within_at_iff mdifferentiableWithinAt_iff
/-- One can reformulate differentiability within a set at a point as continuity within this set at
this point, and differentiability in any chart containing that point. -/
theorem mdifferentiableWithinAt_iff_of_mem_source {x' : M} {y : M'}
(hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) :
MDifferentiableWithinAt I I' f s x' ↔
ContinuousWithinAt f s x' ∧
DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ Set.range I) ((extChartAt I x) x') :=
(differentiable_within_at_localInvariantProp I I').liftPropWithinAt_indep_chart
(StructureGroupoid.chart_mem_maximalAtlas _ x) hx (StructureGroupoid.chart_mem_maximalAtlas _ y)
hy
#align mdifferentiable_within_at_iff_of_mem_source mdifferentiableWithinAt_iff_of_mem_source
theorem mfderivWithin_zero_of_not_mdifferentiableWithinAt
(h : ¬MDifferentiableWithinAt I I' f s x) : mfderivWithin I I' f s x = 0 := by
simp only [mfderivWithin, h, if_neg, not_false_iff]
#align mfderiv_within_zero_of_not_mdifferentiable_within_at mfderivWithin_zero_of_not_mdifferentiableWithinAt
theorem mfderiv_zero_of_not_mdifferentiableAt (h : ¬MDifferentiableAt I I' f x) :
mfderiv I I' f x = 0 := by simp only [mfderiv, h, if_neg, not_false_iff]
#align mfderiv_zero_of_not_mdifferentiable_at mfderiv_zero_of_not_mdifferentiableAt
theorem HasMFDerivWithinAt.mono (h : HasMFDerivWithinAt I I' f t x f') (hst : s ⊆ t) :
HasMFDerivWithinAt I I' f s x f' :=
⟨ContinuousWithinAt.mono h.1 hst,
HasFDerivWithinAt.mono h.2 (inter_subset_inter (preimage_mono hst) (Subset.refl _))⟩
#align has_mfderiv_within_at.mono HasMFDerivWithinAt.mono
theorem HasMFDerivAt.hasMFDerivWithinAt (h : HasMFDerivAt I I' f x f') :
HasMFDerivWithinAt I I' f s x f' :=
⟨ContinuousAt.continuousWithinAt h.1, HasFDerivWithinAt.mono h.2 inter_subset_right⟩
#align has_mfderiv_at.has_mfderiv_within_at HasMFDerivAt.hasMFDerivWithinAt
theorem HasMFDerivWithinAt.mdifferentiableWithinAt (h : HasMFDerivWithinAt I I' f s x f') :
MDifferentiableWithinAt I I' f s x :=
⟨h.1, ⟨f', h.2⟩⟩
#align has_mfderiv_within_at.mdifferentiable_within_at HasMFDerivWithinAt.mdifferentiableWithinAt
theorem HasMFDerivAt.mdifferentiableAt (h : HasMFDerivAt I I' f x f') :
MDifferentiableAt I I' f x := by
rw [mdifferentiableAt_iff]
exact ⟨h.1, ⟨f', h.2⟩⟩
#align has_mfderiv_at.mdifferentiable_at HasMFDerivAt.mdifferentiableAt
@[simp, mfld_simps]
theorem hasMFDerivWithinAt_univ :
HasMFDerivWithinAt I I' f univ x f' ↔ HasMFDerivAt I I' f x f' := by
simp only [HasMFDerivWithinAt, HasMFDerivAt, continuousWithinAt_univ, mfld_simps]
#align has_mfderiv_within_at_univ hasMFDerivWithinAt_univ
theorem hasMFDerivAt_unique (h₀ : HasMFDerivAt I I' f x f₀') (h₁ : HasMFDerivAt I I' f x f₁') :
f₀' = f₁' := by
rw [← hasMFDerivWithinAt_univ] at h₀ h₁
exact (uniqueMDiffWithinAt_univ I).eq h₀ h₁
#align has_mfderiv_at_unique hasMFDerivAt_unique
| Mathlib/Geometry/Manifold/MFDeriv/Basic.lean | 204 | 208 | theorem hasMFDerivWithinAt_inter' (h : t ∈ 𝓝[s] x) :
HasMFDerivWithinAt I I' f (s ∩ t) x f' ↔ HasMFDerivWithinAt I I' f s x f' := by |
rw [HasMFDerivWithinAt, HasMFDerivWithinAt, extChartAt_preimage_inter_eq,
hasFDerivWithinAt_inter', continuousWithinAt_inter' h]
exact extChartAt_preimage_mem_nhdsWithin I h
|
/-
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.Balanced
import Mathlib.CategoryTheory.Limits.EssentiallySmall
import Mathlib.CategoryTheory.Limits.Opposites
import Mathlib.CategoryTheory.Limits.Shapes.ZeroMorphisms
import Mathlib.CategoryTheory.Subobject.Lattice
import Mathlib.CategoryTheory.Subobject.WellPowered
import Mathlib.Data.Set.Opposite
import Mathlib.Data.Set.Subsingleton
#align_import category_theory.generator from "leanprover-community/mathlib"@"f187f1074fa1857c94589cc653c786cadc4c35ff"
/-!
# Separating and detecting sets
There are several non-equivalent notions of a generator of a category. Here, we consider two of
them:
* We say that `𝒢` is a separating set if the functors `C(G, -)` for `G ∈ 𝒢` are collectively
faithful, i.e., if `h ≫ f = h ≫ g` for all `h` with domain in `𝒢` implies `f = g`.
* We say that `𝒢` is a detecting set if the functors `C(G, -)` collectively reflect isomorphisms,
i.e., if any `h` with domain in `𝒢` uniquely factors through `f`, then `f` is an isomorphism.
There are, of course, also the dual notions of coseparating and codetecting sets.
## Main results
We
* define predicates `IsSeparating`, `IsCoseparating`, `IsDetecting` and `IsCodetecting` on
sets of objects;
* show that separating and coseparating are dual notions;
* show that detecting and codetecting are dual notions;
* show that if `C` has equalizers, then detecting implies separating;
* show that if `C` has coequalizers, then codetecting implies separating;
* show that if `C` is balanced, then separating implies detecting and coseparating implies
codetecting;
* show that `∅` is separating if and only if `∅` is coseparating if and only if `C` is thin;
* show that `∅` is detecting if and only if `∅` is codetecting if and only if `C` is a groupoid;
* define predicates `IsSeparator`, `IsCoseparator`, `IsDetector` and `IsCodetector` as the
singleton counterparts to the definitions for sets above and restate the above results in this
situation;
* show that `G` is a separator if and only if `coyoneda.obj (op G)` is faithful (and the dual);
* show that `G` is a detector if and only if `coyoneda.obj (op G)` reflects isomorphisms (and the
dual).
## Future work
* We currently don't have any examples yet.
* We will want typeclasses `HasSeparator C` and similar.
-/
universe w v₁ v₂ u₁ u₂
open CategoryTheory.Limits Opposite
namespace CategoryTheory
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D]
/-- We say that `𝒢` is a separating set if the functors `C(G, -)` for `G ∈ 𝒢` are collectively
faithful, i.e., if `h ≫ f = h ≫ g` for all `h` with domain in `𝒢` implies `f = g`. -/
def IsSeparating (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : G ⟶ X), h ≫ f = h ≫ g) → f = g
#align category_theory.is_separating CategoryTheory.IsSeparating
/-- We say that `𝒢` is a coseparating set if the functors `C(-, G)` for `G ∈ 𝒢` are collectively
faithful, i.e., if `f ≫ h = g ≫ h` for all `h` with codomain in `𝒢` implies `f = g`. -/
def IsCoseparating (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : Y ⟶ G), f ≫ h = g ≫ h) → f = g
#align category_theory.is_coseparating CategoryTheory.IsCoseparating
/-- We say that `𝒢` is a detecting set if the functors `C(G, -)` collectively reflect isomorphisms,
i.e., if any `h` with domain in `𝒢` uniquely factors through `f`, then `f` is an isomorphism. -/
def IsDetecting (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : G ⟶ Y), ∃! h' : G ⟶ X, h' ≫ f = h) → IsIso f
#align category_theory.is_detecting CategoryTheory.IsDetecting
/-- We say that `𝒢` is a codetecting set if the functors `C(-, G)` collectively reflect
isomorphisms, i.e., if any `h` with codomain in `G` uniquely factors through `f`, then `f` is
an isomorphism. -/
def IsCodetecting (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : X ⟶ G), ∃! h' : Y ⟶ G, f ≫ h' = h) → IsIso f
#align category_theory.is_codetecting CategoryTheory.IsCodetecting
section Dual
theorem isSeparating_op_iff (𝒢 : Set C) : IsSeparating 𝒢.op ↔ IsCoseparating 𝒢 := by
refine ⟨fun h𝒢 X Y f g hfg => ?_, fun h𝒢 X Y f g hfg => ?_⟩
· refine Quiver.Hom.op_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.unop_inj ?_)
simpa only [unop_comp, Quiver.Hom.unop_op] using hfg _ (Set.mem_op.1 hG) _
· refine Quiver.Hom.unop_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.op_inj ?_)
simpa only [op_comp, Quiver.Hom.op_unop] using hfg _ (Set.op_mem_op.2 hG) _
#align category_theory.is_separating_op_iff CategoryTheory.isSeparating_op_iff
theorem isCoseparating_op_iff (𝒢 : Set C) : IsCoseparating 𝒢.op ↔ IsSeparating 𝒢 := by
refine ⟨fun h𝒢 X Y f g hfg => ?_, fun h𝒢 X Y f g hfg => ?_⟩
· refine Quiver.Hom.op_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.unop_inj ?_)
simpa only [unop_comp, Quiver.Hom.unop_op] using hfg _ (Set.mem_op.1 hG) _
· refine Quiver.Hom.unop_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.op_inj ?_)
simpa only [op_comp, Quiver.Hom.op_unop] using hfg _ (Set.op_mem_op.2 hG) _
#align category_theory.is_coseparating_op_iff CategoryTheory.isCoseparating_op_iff
theorem isCoseparating_unop_iff (𝒢 : Set Cᵒᵖ) : IsCoseparating 𝒢.unop ↔ IsSeparating 𝒢 := by
rw [← isSeparating_op_iff, Set.unop_op]
#align category_theory.is_coseparating_unop_iff CategoryTheory.isCoseparating_unop_iff
theorem isSeparating_unop_iff (𝒢 : Set Cᵒᵖ) : IsSeparating 𝒢.unop ↔ IsCoseparating 𝒢 := by
rw [← isCoseparating_op_iff, Set.unop_op]
#align category_theory.is_separating_unop_iff CategoryTheory.isSeparating_unop_iff
theorem isDetecting_op_iff (𝒢 : Set C) : IsDetecting 𝒢.op ↔ IsCodetecting 𝒢 := by
refine ⟨fun h𝒢 X Y f hf => ?_, fun h𝒢 X Y f hf => ?_⟩
· refine (isIso_op_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (unop G) (Set.mem_op.1 hG) h.unop
exact
⟨t.op, Quiver.Hom.unop_inj ht, fun y hy => Quiver.Hom.unop_inj (ht' _ (Quiver.Hom.op_inj hy))⟩
· refine (isIso_unop_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (op G) (Set.op_mem_op.2 hG) h.op
refine ⟨t.unop, Quiver.Hom.op_inj ht, fun y hy => Quiver.Hom.op_inj (ht' _ ?_)⟩
exact Quiver.Hom.unop_inj (by simpa only using hy)
#align category_theory.is_detecting_op_iff CategoryTheory.isDetecting_op_iff
theorem isCodetecting_op_iff (𝒢 : Set C) : IsCodetecting 𝒢.op ↔ IsDetecting 𝒢 := by
refine ⟨fun h𝒢 X Y f hf => ?_, fun h𝒢 X Y f hf => ?_⟩
· refine (isIso_op_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (unop G) (Set.mem_op.1 hG) h.unop
exact
⟨t.op, Quiver.Hom.unop_inj ht, fun y hy => Quiver.Hom.unop_inj (ht' _ (Quiver.Hom.op_inj hy))⟩
· refine (isIso_unop_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (op G) (Set.op_mem_op.2 hG) h.op
refine ⟨t.unop, Quiver.Hom.op_inj ht, fun y hy => Quiver.Hom.op_inj (ht' _ ?_)⟩
exact Quiver.Hom.unop_inj (by simpa only using hy)
#align category_theory.is_codetecting_op_iff CategoryTheory.isCodetecting_op_iff
theorem isDetecting_unop_iff (𝒢 : Set Cᵒᵖ) : IsDetecting 𝒢.unop ↔ IsCodetecting 𝒢 := by
rw [← isCodetecting_op_iff, Set.unop_op]
#align category_theory.is_detecting_unop_iff CategoryTheory.isDetecting_unop_iff
theorem isCodetecting_unop_iff {𝒢 : Set Cᵒᵖ} : IsCodetecting 𝒢.unop ↔ IsDetecting 𝒢 := by
rw [← isDetecting_op_iff, Set.unop_op]
#align category_theory.is_codetecting_unop_iff CategoryTheory.isCodetecting_unop_iff
end Dual
theorem IsDetecting.isSeparating [HasEqualizers C] {𝒢 : Set C} (h𝒢 : IsDetecting 𝒢) :
IsSeparating 𝒢 := fun _ _ f g hfg =>
have : IsIso (equalizer.ι f g) := h𝒢 _ fun _ hG _ => equalizer.existsUnique _ (hfg _ hG _)
eq_of_epi_equalizer
#align category_theory.is_detecting.is_separating CategoryTheory.IsDetecting.isSeparating
section
theorem IsCodetecting.isCoseparating [HasCoequalizers C] {𝒢 : Set C} :
IsCodetecting 𝒢 → IsCoseparating 𝒢 := by
simpa only [← isSeparating_op_iff, ← isDetecting_op_iff] using IsDetecting.isSeparating
#align category_theory.is_codetecting.is_coseparating CategoryTheory.IsCodetecting.isCoseparating
end
theorem IsSeparating.isDetecting [Balanced C] {𝒢 : Set C} (h𝒢 : IsSeparating 𝒢) :
IsDetecting 𝒢 := by
intro X Y f hf
refine
(isIso_iff_mono_and_epi _).2 ⟨⟨fun g h hgh => h𝒢 _ _ fun G hG i => ?_⟩, ⟨fun g h hgh => ?_⟩⟩
· obtain ⟨t, -, ht⟩ := hf G hG (i ≫ g ≫ f)
rw [ht (i ≫ g) (Category.assoc _ _ _), ht (i ≫ h) (hgh.symm ▸ Category.assoc _ _ _)]
· refine h𝒢 _ _ fun G hG i => ?_
obtain ⟨t, rfl, -⟩ := hf G hG i
rw [Category.assoc, hgh, Category.assoc]
#align category_theory.is_separating.is_detecting CategoryTheory.IsSeparating.isDetecting
section
attribute [local instance] balanced_opposite
| Mathlib/CategoryTheory/Generator.lean | 182 | 184 | theorem IsCoseparating.isCodetecting [Balanced C] {𝒢 : Set C} :
IsCoseparating 𝒢 → IsCodetecting 𝒢 := by |
simpa only [← isDetecting_op_iff, ← isSeparating_op_iff] using IsSeparating.isDetecting
|
/-
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
import Mathlib.Analysis.Calculus.Deriv.Polynomial
import Mathlib.Analysis.Fourier.AddCircle
import Mathlib.Analysis.PSeries
#align_import number_theory.zeta_values from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# 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
#align bernoulli_fun bernoulliFun
theorem bernoulliFun_eval_zero (k : ℕ) : bernoulliFun k 0 = bernoulli k := by
rw [bernoulliFun, Polynomial.eval_zero_map, Polynomial.bernoulli_eval_zero, eq_ratCast]
#align bernoulli_fun_eval_zero bernoulliFun_eval_zero
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]
#align bernoulli_fun_endpoints_eq_of_ne_one bernoulliFun_endpoints_eq_of_ne_one
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]
#align bernoulli_fun_eval_one bernoulliFun_eval_one
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,
Polynomial.map_mul, Polynomial.map_natCast, Polynomial.eval_mul, Polynomial.eval_natCast]
#align has_deriv_at_bernoulli_fun hasDerivAt_bernoulliFun
theorem antideriv_bernoulliFun (k : ℕ) (x : ℝ) :
HasDerivAt (fun x => bernoulliFun (k + 1) x / (k + 1)) (bernoulliFun k x) x := by
convert (hasDerivAt_bernoulliFun (k + 1) x).div_const _ using 1
field_simp [Nat.cast_add_one_ne_zero k]
#align antideriv_bernoulli_fun antideriv_bernoulliFun
theorem integral_bernoulliFun_eq_zero {k : ℕ} (hk : k ≠ 0) :
∫ x : ℝ in (0)..1, bernoulliFun k x = 0 := by
rw [integral_eq_sub_of_hasDerivAt (fun x _ => antideriv_bernoulliFun k x)
((Polynomial.continuous _).intervalIntegrable _ _)]
rw [bernoulliFun_eval_one]
split_ifs with h
· exfalso; exact hk (Nat.succ_inj'.mp h)
· simp
#align integral_bernoulli_fun_eq_zero integral_bernoulliFun_eq_zero
end BernoulliFunProps
section BernoulliFourierCoeffs
/-! Compute the Fourier coefficients of the Bernoulli functions via integration by parts. -/
/-- The `n`-th Fourier coefficient of the `k`-th Bernoulli function on the interval `[0, 1]`. -/
def bernoulliFourierCoeff (k : ℕ) (n : ℤ) : ℂ :=
fourierCoeffOn zero_lt_one (fun x => bernoulliFun k x) n
#align bernoulli_fourier_coeff bernoulliFourierCoeff
/-- Recurrence relation (in `k`) for the `n`-th Fourier coefficient of `Bₖ`. -/
theorem bernoulliFourierCoeff_recurrence (k : ℕ) {n : ℤ} (hn : n ≠ 0) :
bernoulliFourierCoeff k n =
1 / (-2 * π * I * n) * (ite (k = 1) 1 0 - k * bernoulliFourierCoeff (k - 1) n) := by
unfold bernoulliFourierCoeff
rw [fourierCoeffOn_of_hasDerivAt zero_lt_one hn
(fun x _ => (hasDerivAt_bernoulliFun k x).ofReal_comp)
((continuous_ofReal.comp <|
continuous_const.mul <| Polynomial.continuous _).intervalIntegrable
_ _)]
simp_rw [ofReal_one, ofReal_zero, sub_zero, one_mul]
rw [QuotientAddGroup.mk_zero, fourier_eval_zero, one_mul, ← ofReal_sub, bernoulliFun_eval_one,
add_sub_cancel_left]
congr 2
· split_ifs <;> simp only [ofReal_one, ofReal_zero, one_mul]
· simp_rw [ofReal_mul, ofReal_natCast, fourierCoeffOn.const_mul]
#align bernoulli_fourier_coeff_recurrence bernoulliFourierCoeff_recurrence
/-- The Fourier coefficients of `B₀(x) = 1`. -/
theorem bernoulli_zero_fourier_coeff {n : ℤ} (hn : n ≠ 0) : bernoulliFourierCoeff 0 n = 0 := by
simpa using bernoulliFourierCoeff_recurrence 0 hn
#align bernoulli_zero_fourier_coeff bernoulli_zero_fourier_coeff
/-- The `0`-th Fourier coefficient of `Bₖ(x)`. -/
theorem bernoulliFourierCoeff_zero {k : ℕ} (hk : k ≠ 0) : bernoulliFourierCoeff k 0 = 0 := by
simp_rw [bernoulliFourierCoeff, fourierCoeffOn_eq_integral, neg_zero, fourier_zero, sub_zero,
div_one, one_smul, intervalIntegral.integral_ofReal, integral_bernoulliFun_eq_zero hk,
ofReal_zero]
#align bernoulli_fourier_coeff_zero bernoulliFourierCoeff_zero
theorem bernoulliFourierCoeff_eq {k : ℕ} (hk : k ≠ 0) (n : ℤ) :
bernoulliFourierCoeff k n = -k ! / (2 * π * I * n) ^ k := by
rcases eq_or_ne n 0 with (rfl | hn)
· rw [bernoulliFourierCoeff_zero hk, Int.cast_zero, mul_zero, zero_pow hk,
div_zero]
refine Nat.le_induction ?_ (fun k hk h'k => ?_) k (Nat.one_le_iff_ne_zero.mpr hk)
· rw [bernoulliFourierCoeff_recurrence 1 hn]
simp only [Nat.cast_one, tsub_self, neg_mul, one_mul, eq_self_iff_true, if_true,
Nat.factorial_one, pow_one, inv_I, mul_neg]
rw [bernoulli_zero_fourier_coeff hn, sub_zero, mul_one, div_neg, neg_div]
· rw [bernoulliFourierCoeff_recurrence (k + 1) hn, Nat.add_sub_cancel k 1]
split_ifs with h
· exfalso; exact (ne_of_gt (Nat.lt_succ_iff.mpr hk)) h
· rw [h'k, Nat.factorial_succ, zero_sub, Nat.cast_mul, pow_add, pow_one, neg_div, mul_neg,
mul_neg, mul_neg, neg_neg, neg_mul, neg_mul, neg_mul, div_neg]
field_simp [Int.cast_ne_zero.mpr hn, I_ne_zero]
ring_nf
#align bernoulli_fourier_coeff_eq bernoulliFourierCoeff_eq
end BernoulliFourierCoeffs
section BernoulliPeriodized
/-! In this section we use the above evaluations of the Fourier coefficients of Bernoulli
polynomials, together with the theorem `has_pointwise_sum_fourier_series_of_summable` from Fourier
theory, to obtain an explicit formula for `∑ (n:ℤ), 1 / n ^ k * fourier n x`. -/
/-- The Bernoulli polynomial, extended from `[0, 1)` to the unit circle. -/
def periodizedBernoulli (k : ℕ) : 𝕌 → ℝ :=
AddCircle.liftIco 1 0 (bernoulliFun k)
#align periodized_bernoulli periodizedBernoulli
theorem periodizedBernoulli.continuous {k : ℕ} (hk : k ≠ 1) : Continuous (periodizedBernoulli k) :=
AddCircle.liftIco_zero_continuous
(mod_cast (bernoulliFun_endpoints_eq_of_ne_one hk).symm)
(Polynomial.continuous _).continuousOn
#align periodized_bernoulli.continuous periodizedBernoulli.continuous
theorem fourierCoeff_bernoulli_eq {k : ℕ} (hk : k ≠ 0) (n : ℤ) :
fourierCoeff ((↑) ∘ periodizedBernoulli k : 𝕌 → ℂ) n = -k ! / (2 * π * I * n) ^ k := by
have : ((↑) ∘ periodizedBernoulli k : 𝕌 → ℂ) = AddCircle.liftIco 1 0 ((↑) ∘ bernoulliFun k) := by
ext1 x; rfl
rw [this, fourierCoeff_liftIco_eq]
simpa only [zero_add] using bernoulliFourierCoeff_eq hk n
#align fourier_coeff_bernoulli_eq fourierCoeff_bernoulli_eq
theorem summable_bernoulli_fourier {k : ℕ} (hk : 2 ≤ k) :
Summable (fun n => -k ! / (2 * π * I * n) ^ k : ℤ → ℂ) := by
have :
∀ n : ℤ, -(k ! : ℂ) / (2 * π * I * n) ^ k = -k ! / (2 * π * I) ^ k * (1 / (n : ℂ) ^ k) := by
intro n; rw [mul_one_div, div_div, ← mul_pow]
simp_rw [this]
refine Summable.mul_left _ <| .of_norm ?_
have : (fun x : ℤ => ‖1 / (x : ℂ) ^ k‖) = fun x : ℤ => |1 / (x : ℝ) ^ k| := by
ext1 x
rw [norm_eq_abs, ← Complex.abs_ofReal]
congr 1
norm_cast
simp_rw [this]
rwa [summable_abs_iff, Real.summable_one_div_int_pow]
#align summable_bernoulli_fourier summable_bernoulli_fourier
theorem hasSum_one_div_pow_mul_fourier_mul_bernoulliFun {k : ℕ} (hk : 2 ≤ k) {x : ℝ}
(hx : x ∈ Icc (0 : ℝ) 1) :
HasSum (fun n : ℤ => 1 / (n : ℂ) ^ k * fourier n (x : 𝕌))
(-(2 * π * I) ^ k / k ! * bernoulliFun k x) := by
-- first show it suffices to prove result for `Ico 0 1`
suffices ∀ {y : ℝ}, y ∈ Ico (0 : ℝ) 1 →
HasSum (fun (n : ℤ) ↦ 1 / (n : ℂ) ^ k * fourier n y)
(-(2 * (π : ℂ) * I) ^ k / k ! * bernoulliFun k y) by
rw [← Ico_insert_right (zero_le_one' ℝ), mem_insert_iff, or_comm] at hx
rcases hx with (hx | rfl)
· exact this hx
· convert this (left_mem_Ico.mpr zero_lt_one) using 1
· rw [AddCircle.coe_period, QuotientAddGroup.mk_zero]
· rw [bernoulliFun_endpoints_eq_of_ne_one (by omega : k ≠ 1)]
intro y hy
let B : C(𝕌, ℂ) :=
ContinuousMap.mk ((↑) ∘ periodizedBernoulli k)
(continuous_ofReal.comp (periodizedBernoulli.continuous (by omega)))
have step1 : ∀ n : ℤ, fourierCoeff B n = -k ! / (2 * π * I * n) ^ k := by
rw [ContinuousMap.coe_mk]; exact fourierCoeff_bernoulli_eq (by omega : k ≠ 0)
have step2 :=
has_pointwise_sum_fourier_series_of_summable
((summable_bernoulli_fourier hk).congr fun n => (step1 n).symm) y
simp_rw [step1] at step2
convert step2.mul_left (-(2 * ↑π * I) ^ k / (k ! : ℂ)) using 2 with n
· rw [smul_eq_mul, ← mul_assoc, mul_div, mul_neg, div_mul_cancel₀, neg_neg, mul_pow _ (n : ℂ),
← div_div, div_self]
· rw [Ne, pow_eq_zero_iff', not_and_or]
exact Or.inl two_pi_I_ne_zero
· exact Nat.cast_ne_zero.mpr (Nat.factorial_ne_zero _)
· rw [ContinuousMap.coe_mk, Function.comp_apply, ofReal_inj, periodizedBernoulli,
AddCircle.liftIco_coe_apply (show y ∈ Ico 0 (0 + 1) by rwa [zero_add])]
#align has_sum_one_div_pow_mul_fourier_mul_bernoulli_fun hasSum_one_div_pow_mul_fourier_mul_bernoulliFun
end BernoulliPeriodized
section Cleanup
-- This section is just reformulating the results in a nicer form.
theorem hasSum_one_div_nat_pow_mul_fourier {k : ℕ} (hk : 2 ≤ k) {x : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) :
HasSum
(fun n : ℕ =>
(1 : ℂ) / (n : ℂ) ^ k * (fourier n (x : 𝕌) + (-1 : ℂ) ^ k * fourier (-n) (x : 𝕌)))
(-(2 * π * I) ^ k / k ! * bernoulliFun k x) := by
convert (hasSum_one_div_pow_mul_fourier_mul_bernoulliFun hk hx).nat_add_neg using 1
· ext1 n
rw [Int.cast_neg, mul_add, ← mul_assoc]
conv_rhs => rw [neg_eq_neg_one_mul, mul_pow, ← div_div]
congr 2
rw [div_mul_eq_mul_div₀, one_mul]
congr 1
rw [eq_div_iff, ← mul_pow, ← neg_eq_neg_one_mul, neg_neg, one_pow]
apply pow_ne_zero; rw [neg_ne_zero]; exact one_ne_zero
· rw [Int.cast_zero, zero_pow (by positivity : k ≠ 0), div_zero, zero_mul, add_zero]
#align has_sum_one_div_nat_pow_mul_fourier hasSum_one_div_nat_pow_mul_fourier
theorem hasSum_one_div_nat_pow_mul_cos {k : ℕ} (hk : k ≠ 0) {x : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) :
HasSum (fun n : ℕ => 1 / (n : ℝ) ^ (2 * k) * Real.cos (2 * π * n * x))
((-1 : ℝ) ^ (k + 1) * (2 * π) ^ (2 * k) / 2 / (2 * k)! *
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli (2 * k))).eval x) := by
have :
HasSum (fun n : ℕ => 1 / (n : ℂ) ^ (2 * k) * (fourier n (x : 𝕌) + fourier (-n) (x : 𝕌)))
((-1 : ℂ) ^ (k + 1) * (2 * (π : ℂ)) ^ (2 * k) / (2 * k)! * bernoulliFun (2 * k) x) := by
convert
hasSum_one_div_nat_pow_mul_fourier (by omega : 2 ≤ 2 * k)
hx using 3
· rw [pow_mul (-1 : ℂ), neg_one_sq, one_pow, one_mul]
· rw [pow_add, pow_one]
conv_rhs =>
rw [mul_pow]
congr
congr
· skip
· rw [pow_mul, I_sq]
ring
have ofReal_two : ((2 : ℝ) : ℂ) = 2 := by norm_cast
convert ((hasSum_iff _ _).mp (this.div_const 2)).1 with n
· convert (ofReal_re _).symm
rw [ofReal_mul]; rw [← mul_div]; congr
· rw [ofReal_div, ofReal_one, ofReal_pow]; rfl
· rw [ofReal_cos, ofReal_mul, fourier_coe_apply, fourier_coe_apply, cos, ofReal_one, div_one,
div_one, ofReal_mul, ofReal_mul, ofReal_two, Int.cast_neg, Int.cast_natCast,
ofReal_natCast]
congr 3
· ring
· ring
· convert (ofReal_re _).symm
rw [ofReal_mul, ofReal_div, ofReal_div, ofReal_mul, ofReal_pow, ofReal_pow, ofReal_neg,
ofReal_natCast, ofReal_mul, ofReal_two, ofReal_one]
rw [bernoulliFun]
ring
#align has_sum_one_div_nat_pow_mul_cos hasSum_one_div_nat_pow_mul_cos
theorem hasSum_one_div_nat_pow_mul_sin {k : ℕ} (hk : k ≠ 0) {x : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) :
HasSum (fun n : ℕ => 1 / (n : ℝ) ^ (2 * k + 1) * Real.sin (2 * π * n * x))
((-1 : ℝ) ^ (k + 1) * (2 * π) ^ (2 * k + 1) / 2 / (2 * k + 1)! *
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli (2 * k + 1))).eval x) := by
have :
HasSum (fun n : ℕ => 1 / (n : ℂ) ^ (2 * k + 1) * (fourier n (x : 𝕌) - fourier (-n) (x : 𝕌)))
((-1 : ℂ) ^ (k + 1) * I * (2 * π : ℂ) ^ (2 * k + 1) / (2 * k + 1)! *
bernoulliFun (2 * k + 1) x) := by
convert
hasSum_one_div_nat_pow_mul_fourier
(by omega : 2 ≤ 2 * k + 1) hx using 1
· ext1 n
rw [pow_add (-1 : ℂ), pow_mul (-1 : ℂ), neg_one_sq, one_pow, one_mul, pow_one, ←
neg_eq_neg_one_mul, ← sub_eq_add_neg]
· congr
rw [pow_add, pow_one]
conv_rhs =>
rw [mul_pow]
congr
congr
· skip
· rw [pow_add, pow_one, pow_mul, I_sq]
ring
have ofReal_two : ((2 : ℝ) : ℂ) = 2 := by norm_cast
convert ((hasSum_iff _ _).mp (this.div_const (2 * I))).1
· convert (ofReal_re _).symm
rw [ofReal_mul]; rw [← mul_div]; congr
· rw [ofReal_div, ofReal_one, ofReal_pow]; rfl
· rw [ofReal_sin, ofReal_mul, fourier_coe_apply, fourier_coe_apply, sin, ofReal_one, div_one,
div_one, ofReal_mul, ofReal_mul, ofReal_two, Int.cast_neg, Int.cast_natCast,
ofReal_natCast, ← div_div, div_I, div_mul_eq_mul_div₀, ← neg_div, ← neg_mul, neg_sub]
congr 4
· ring
· ring
· convert (ofReal_re _).symm
rw [ofReal_mul, ofReal_div, ofReal_div, ofReal_mul, ofReal_pow, ofReal_pow, ofReal_neg,
ofReal_natCast, ofReal_mul, ofReal_two, ofReal_one, ← div_div, div_I,
div_mul_eq_mul_div₀]
have : ∀ α β γ δ : ℂ, α * I * β / γ * δ * I = I ^ 2 * α * β / γ * δ := by intros; ring
rw [this, I_sq]
rw [bernoulliFun]
ring
#align has_sum_one_div_nat_pow_mul_sin hasSum_one_div_nat_pow_mul_sin
| Mathlib/NumberTheory/ZetaValues.lean | 332 | 348 | theorem hasSum_zeta_nat {k : ℕ} (hk : k ≠ 0) :
HasSum (fun n : ℕ => 1 / (n : ℝ) ^ (2 * k))
((-1 : ℝ) ^ (k + 1) * (2 : ℝ) ^ (2 * k - 1) * π ^ (2 * k) *
bernoulli (2 * k) / (2 * k)!) := by |
convert hasSum_one_div_nat_pow_mul_cos hk (left_mem_Icc.mpr zero_le_one) using 1
· ext1 n; rw [mul_zero, Real.cos_zero, mul_one]
rw [Polynomial.eval_zero_map, Polynomial.bernoulli_eval_zero, eq_ratCast]
have : (2 : ℝ) ^ (2 * k - 1) = (2 : ℝ) ^ (2 * k) / 2 := by
rw [eq_div_iff (two_ne_zero' ℝ)]
conv_lhs =>
congr
· skip
· rw [← pow_one (2 : ℝ)]
rw [← pow_add, Nat.sub_add_cancel]
omega
rw [this, mul_pow]
ring
|
/-
Copyright (c) 2021 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Topology.ContinuousOn
#align_import topology.algebra.order.left_right from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Left and right continuity
In this file we prove a few lemmas about left and right continuous functions:
* `continuousWithinAt_Ioi_iff_Ici`: two definitions of right continuity
(with `(a, ∞)` and with `[a, ∞)`) are equivalent;
* `continuousWithinAt_Iio_iff_Iic`: two definitions of left continuity
(with `(-∞, a)` and with `(-∞, a]`) are equivalent;
* `continuousAt_iff_continuous_left_right`, `continuousAt_iff_continuous_left'_right'` :
a function is continuous at `a` if and only if it is left and right continuous at `a`.
## Tags
left continuous, right continuous
-/
open Set Filter Topology
section Preorder
variable {α : Type*} [TopologicalSpace α] [Preorder α]
lemma frequently_lt_nhds (a : α) [NeBot (𝓝[<] a)] : ∃ᶠ x in 𝓝 a, x < a :=
frequently_iff_neBot.2 ‹_›
lemma frequently_gt_nhds (a : α) [NeBot (𝓝[>] a)] : ∃ᶠ x in 𝓝 a, a < x :=
frequently_iff_neBot.2 ‹_›
theorem Filter.Eventually.exists_lt {a : α} [NeBot (𝓝[<] a)] {p : α → Prop}
(h : ∀ᶠ x in 𝓝 a, p x) : ∃ b < a, p b :=
((frequently_lt_nhds a).and_eventually h).exists
#align filter.eventually.exists_lt Filter.Eventually.exists_lt
theorem Filter.Eventually.exists_gt {a : α} [NeBot (𝓝[>] a)] {p : α → Prop}
(h : ∀ᶠ x in 𝓝 a, p x) : ∃ b > a, p b :=
((frequently_gt_nhds a).and_eventually h).exists
#align filter.eventually.exists_gt Filter.Eventually.exists_gt
theorem nhdsWithin_Ici_neBot {a b : α} (H₂ : a ≤ b) : NeBot (𝓝[Ici a] b) :=
nhdsWithin_neBot_of_mem H₂
#align nhds_within_Ici_ne_bot nhdsWithin_Ici_neBot
instance nhdsWithin_Ici_self_neBot (a : α) : NeBot (𝓝[≥] a) :=
nhdsWithin_Ici_neBot (le_refl a)
#align nhds_within_Ici_self_ne_bot nhdsWithin_Ici_self_neBot
theorem nhdsWithin_Iic_neBot {a b : α} (H : a ≤ b) : NeBot (𝓝[Iic b] a) :=
nhdsWithin_neBot_of_mem H
#align nhds_within_Iic_ne_bot nhdsWithin_Iic_neBot
instance nhdsWithin_Iic_self_neBot (a : α) : NeBot (𝓝[≤] a) :=
nhdsWithin_Iic_neBot (le_refl a)
#align nhds_within_Iic_self_ne_bot nhdsWithin_Iic_self_neBot
theorem nhds_left'_le_nhds_ne (a : α) : 𝓝[<] a ≤ 𝓝[≠] a :=
nhdsWithin_mono a fun _ => ne_of_lt
#align nhds_left'_le_nhds_ne nhds_left'_le_nhds_ne
theorem nhds_right'_le_nhds_ne (a : α) : 𝓝[>] a ≤ 𝓝[≠] a :=
nhdsWithin_mono a fun _ => ne_of_gt
#align nhds_right'_le_nhds_ne nhds_right'_le_nhds_ne
-- TODO: add instances for `NeBot (𝓝[<] x)` on (indexed) product types
lemma IsAntichain.interior_eq_empty [∀ x : α, (𝓝[<] x).NeBot] {s : Set α}
(hs : IsAntichain (· ≤ ·) s) : interior s = ∅ := by
refine eq_empty_of_forall_not_mem fun x hx ↦ ?_
have : ∀ᶠ y in 𝓝 x, y ∈ s := mem_interior_iff_mem_nhds.1 hx
rcases this.exists_lt with ⟨y, hyx, hys⟩
exact hs hys (interior_subset hx) hyx.ne hyx.le
#align is_antichain.interior_eq_empty IsAntichain.interior_eq_empty
lemma IsAntichain.interior_eq_empty' [∀ x : α, (𝓝[>] x).NeBot] {s : Set α}
(hs : IsAntichain (· ≤ ·) s) : interior s = ∅ :=
have : ∀ x : αᵒᵈ, NeBot (𝓝[<] x) := ‹_›
hs.to_dual.interior_eq_empty
end Preorder
section PartialOrder
variable {α β : Type*} [TopologicalSpace α] [PartialOrder α] [TopologicalSpace β]
theorem continuousWithinAt_Ioi_iff_Ici {a : α} {f : α → β} :
ContinuousWithinAt f (Ioi a) a ↔ ContinuousWithinAt f (Ici a) a := by
simp only [← Ici_diff_left, continuousWithinAt_diff_self]
#align continuous_within_at_Ioi_iff_Ici continuousWithinAt_Ioi_iff_Ici
theorem continuousWithinAt_Iio_iff_Iic {a : α} {f : α → β} :
ContinuousWithinAt f (Iio a) a ↔ ContinuousWithinAt f (Iic a) a :=
@continuousWithinAt_Ioi_iff_Ici αᵒᵈ _ _ _ _ _ f
#align continuous_within_at_Iio_iff_Iic continuousWithinAt_Iio_iff_Iic
end PartialOrder
section TopologicalSpace
variable {α β : Type*} [TopologicalSpace α] [LinearOrder α] [TopologicalSpace β]
| Mathlib/Topology/Order/LeftRight.lean | 111 | 112 | theorem nhds_left_sup_nhds_right (a : α) : 𝓝[≤] a ⊔ 𝓝[≥] a = 𝓝 a := by |
rw [← nhdsWithin_union, Iic_union_Ici, nhdsWithin_univ]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Complex.Module
import Mathlib.Data.Complex.Order
import Mathlib.Data.Complex.Exponential
import Mathlib.Analysis.RCLike.Basic
import Mathlib.Topology.Algebra.InfiniteSum.Module
import Mathlib.Topology.Instances.RealVectorSpace
#align_import analysis.complex.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Normed space structure on `ℂ`.
This file gathers basic facts on complex numbers of an analytic nature.
## Main results
This file registers `ℂ` as a normed field, expresses basic properties of the norm, and gives
tools on the real vector space structure of `ℂ`. Notably, in the namespace `Complex`,
it defines functions:
* `reCLM`
* `imCLM`
* `ofRealCLM`
* `conjCLE`
They are bundled versions of the real part, the imaginary part, the embedding of `ℝ` in `ℂ`, and
the complex conjugate as continuous `ℝ`-linear maps. The last two are also bundled as linear
isometries in `ofRealLI` and `conjLIE`.
We also register the fact that `ℂ` is an `RCLike` field.
-/
assert_not_exists Absorbs
noncomputable section
namespace Complex
variable {z : ℂ}
open ComplexConjugate Topology Filter
instance : Norm ℂ :=
⟨abs⟩
@[simp]
theorem norm_eq_abs (z : ℂ) : ‖z‖ = abs z :=
rfl
#align complex.norm_eq_abs Complex.norm_eq_abs
lemma norm_I : ‖I‖ = 1 := abs_I
theorem norm_exp_ofReal_mul_I (t : ℝ) : ‖exp (t * I)‖ = 1 := by
simp only [norm_eq_abs, abs_exp_ofReal_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.norm_exp_of_real_mul_I Complex.norm_exp_ofReal_mul_I
instance instNormedAddCommGroup : NormedAddCommGroup ℂ :=
AddGroupNorm.toNormedAddCommGroup
{ abs with
map_zero' := map_zero abs
neg' := abs.map_neg
eq_zero_of_map_eq_zero' := fun _ => abs.eq_zero.1 }
instance : NormedField ℂ where
dist_eq _ _ := rfl
norm_mul' := map_mul abs
instance : DenselyNormedField ℂ where
lt_norm_lt r₁ r₂ h₀ hr :=
let ⟨x, h⟩ := exists_between hr
⟨x, by rwa [norm_eq_abs, abs_ofReal, abs_of_pos (h₀.trans_lt h.1)]⟩
instance {R : Type*} [NormedField R] [NormedAlgebra R ℝ] : NormedAlgebra R ℂ where
norm_smul_le r x := by
rw [← algebraMap_smul ℝ r x, real_smul, norm_mul, norm_eq_abs, abs_ofReal, ← Real.norm_eq_abs,
norm_algebraMap']
variable {E : Type*} [SeminormedAddCommGroup E] [NormedSpace ℂ E]
-- see Note [lower instance priority]
/-- The module structure from `Module.complexToReal` is a normed space. -/
instance (priority := 900) _root_.NormedSpace.complexToReal : NormedSpace ℝ E :=
NormedSpace.restrictScalars ℝ ℂ E
#align normed_space.complex_to_real NormedSpace.complexToReal
-- see Note [lower instance priority]
/-- The algebra structure from `Algebra.complexToReal` is a normed algebra. -/
instance (priority := 900) _root_.NormedAlgebra.complexToReal {A : Type*} [SeminormedRing A]
[NormedAlgebra ℂ A] : NormedAlgebra ℝ A :=
NormedAlgebra.restrictScalars ℝ ℂ A
theorem dist_eq (z w : ℂ) : dist z w = abs (z - w) :=
rfl
#align complex.dist_eq Complex.dist_eq
theorem dist_eq_re_im (z w : ℂ) : dist z w = √((z.re - w.re) ^ 2 + (z.im - w.im) ^ 2) := by
rw [sq, sq]
rfl
#align complex.dist_eq_re_im Complex.dist_eq_re_im
@[simp]
theorem dist_mk (x₁ y₁ x₂ y₂ : ℝ) :
dist (mk x₁ y₁) (mk x₂ y₂) = √((x₁ - x₂) ^ 2 + (y₁ - y₂) ^ 2) :=
dist_eq_re_im _ _
#align complex.dist_mk Complex.dist_mk
theorem dist_of_re_eq {z w : ℂ} (h : z.re = w.re) : dist z w = dist z.im w.im := by
rw [dist_eq_re_im, h, sub_self, zero_pow two_ne_zero, zero_add, Real.sqrt_sq_eq_abs, Real.dist_eq]
#align complex.dist_of_re_eq Complex.dist_of_re_eq
theorem nndist_of_re_eq {z w : ℂ} (h : z.re = w.re) : nndist z w = nndist z.im w.im :=
NNReal.eq <| dist_of_re_eq h
#align complex.nndist_of_re_eq Complex.nndist_of_re_eq
theorem edist_of_re_eq {z w : ℂ} (h : z.re = w.re) : edist z w = edist z.im w.im := by
rw [edist_nndist, edist_nndist, nndist_of_re_eq h]
#align complex.edist_of_re_eq Complex.edist_of_re_eq
theorem dist_of_im_eq {z w : ℂ} (h : z.im = w.im) : dist z w = dist z.re w.re := by
rw [dist_eq_re_im, h, sub_self, zero_pow two_ne_zero, add_zero, Real.sqrt_sq_eq_abs, Real.dist_eq]
#align complex.dist_of_im_eq Complex.dist_of_im_eq
theorem nndist_of_im_eq {z w : ℂ} (h : z.im = w.im) : nndist z w = nndist z.re w.re :=
NNReal.eq <| dist_of_im_eq h
#align complex.nndist_of_im_eq Complex.nndist_of_im_eq
theorem edist_of_im_eq {z w : ℂ} (h : z.im = w.im) : edist z w = edist z.re w.re := by
rw [edist_nndist, edist_nndist, nndist_of_im_eq h]
#align complex.edist_of_im_eq Complex.edist_of_im_eq
| Mathlib/Analysis/Complex/Basic.lean | 137 | 139 | theorem dist_conj_self (z : ℂ) : dist (conj z) z = 2 * |z.im| := by |
rw [dist_of_re_eq (conj_re z), conj_im, dist_comm, Real.dist_eq, sub_neg_eq_add, ← two_mul,
_root_.abs_mul, abs_of_pos (zero_lt_two' ℝ)]
|
/-
Copyright (c) 2021 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.Algebra.Module.Equiv
import Mathlib.Data.DFinsupp.Basic
import Mathlib.Data.Finsupp.Basic
#align_import data.finsupp.to_dfinsupp from "leanprover-community/mathlib"@"59694bd07f0a39c5beccba34bd9f413a160782bf"
/-!
# Conversion between `Finsupp` and homogenous `DFinsupp`
This module provides conversions between `Finsupp` and `DFinsupp`.
It is in its own file since neither `Finsupp` or `DFinsupp` depend on each other.
## Main definitions
* "identity" maps between `Finsupp` and `DFinsupp`:
* `Finsupp.toDFinsupp : (ι →₀ M) → (Π₀ i : ι, M)`
* `DFinsupp.toFinsupp : (Π₀ i : ι, M) → (ι →₀ M)`
* Bundled equiv versions of the above:
* `finsuppEquivDFinsupp : (ι →₀ M) ≃ (Π₀ i : ι, M)`
* `finsuppAddEquivDFinsupp : (ι →₀ M) ≃+ (Π₀ i : ι, M)`
* `finsuppLequivDFinsupp R : (ι →₀ M) ≃ₗ[R] (Π₀ i : ι, M)`
* stronger versions of `Finsupp.split`:
* `sigmaFinsuppEquivDFinsupp : ((Σ i, η i) →₀ N) ≃ (Π₀ i, (η i →₀ N))`
* `sigmaFinsuppAddEquivDFinsupp : ((Σ i, η i) →₀ N) ≃+ (Π₀ i, (η i →₀ N))`
* `sigmaFinsuppLequivDFinsupp : ((Σ i, η i) →₀ N) ≃ₗ[R] (Π₀ i, (η i →₀ N))`
## Theorems
The defining features of these operations is that they preserve the function and support:
* `Finsupp.toDFinsupp_coe`
* `Finsupp.toDFinsupp_support`
* `DFinsupp.toFinsupp_coe`
* `DFinsupp.toFinsupp_support`
and therefore map `Finsupp.single` to `DFinsupp.single` and vice versa:
* `Finsupp.toDFinsupp_single`
* `DFinsupp.toFinsupp_single`
as well as preserving arithmetic operations.
For the bundled equivalences, we provide lemmas that they reduce to `Finsupp.toDFinsupp`:
* `finsupp_add_equiv_dfinsupp_apply`
* `finsupp_lequiv_dfinsupp_apply`
* `finsupp_add_equiv_dfinsupp_symm_apply`
* `finsupp_lequiv_dfinsupp_symm_apply`
## Implementation notes
We provide `DFinsupp.toFinsupp` and `finsuppEquivDFinsupp` computably by adding
`[DecidableEq ι]` and `[Π m : M, Decidable (m ≠ 0)]` arguments. To aid with definitional unfolding,
these arguments are also present on the `noncomputable` equivs.
-/
variable {ι : Type*} {R : Type*} {M : Type*}
/-! ### Basic definitions and lemmas -/
section Defs
/-- Interpret a `Finsupp` as a homogenous `DFinsupp`. -/
def Finsupp.toDFinsupp [Zero M] (f : ι →₀ M) : Π₀ _ : ι, M where
toFun := f
support' :=
Trunc.mk
⟨f.support.1, fun i => (Classical.em (f i = 0)).symm.imp_left Finsupp.mem_support_iff.mpr⟩
#align finsupp.to_dfinsupp Finsupp.toDFinsupp
@[simp]
theorem Finsupp.toDFinsupp_coe [Zero M] (f : ι →₀ M) : ⇑f.toDFinsupp = f :=
rfl
#align finsupp.to_dfinsupp_coe Finsupp.toDFinsupp_coe
section
variable [DecidableEq ι] [Zero M]
@[simp]
theorem Finsupp.toDFinsupp_single (i : ι) (m : M) :
(Finsupp.single i m).toDFinsupp = DFinsupp.single i m := by
ext
simp [Finsupp.single_apply, DFinsupp.single_apply]
#align finsupp.to_dfinsupp_single Finsupp.toDFinsupp_single
variable [∀ m : M, Decidable (m ≠ 0)]
@[simp]
theorem toDFinsupp_support (f : ι →₀ M) : f.toDFinsupp.support = f.support := by
ext
simp
#align to_dfinsupp_support toDFinsupp_support
/-- Interpret a homogenous `DFinsupp` as a `Finsupp`.
Note that the elaborator has a lot of trouble with this definition - it is often necessary to
write `(DFinsupp.toFinsupp f : ι →₀ M)` instead of `f.toFinsupp`, as for some unknown reason
using dot notation or omitting the type ascription prevents the type being resolved correctly. -/
def DFinsupp.toFinsupp (f : Π₀ _ : ι, M) : ι →₀ M :=
⟨f.support, f, fun i => by simp only [DFinsupp.mem_support_iff]⟩
#align dfinsupp.to_finsupp DFinsupp.toFinsupp
@[simp]
theorem DFinsupp.toFinsupp_coe (f : Π₀ _ : ι, M) : ⇑f.toFinsupp = f :=
rfl
#align dfinsupp.to_finsupp_coe DFinsupp.toFinsupp_coe
@[simp]
theorem DFinsupp.toFinsupp_support (f : Π₀ _ : ι, M) : f.toFinsupp.support = f.support := by
ext
simp
#align dfinsupp.to_finsupp_support DFinsupp.toFinsupp_support
@[simp]
theorem DFinsupp.toFinsupp_single (i : ι) (m : M) :
(DFinsupp.single i m : Π₀ _ : ι, M).toFinsupp = Finsupp.single i m := by
ext
simp [Finsupp.single_apply, DFinsupp.single_apply]
#align dfinsupp.to_finsupp_single DFinsupp.toFinsupp_single
@[simp]
theorem Finsupp.toDFinsupp_toFinsupp (f : ι →₀ M) : f.toDFinsupp.toFinsupp = f :=
DFunLike.coe_injective rfl
#align finsupp.to_dfinsupp_to_finsupp Finsupp.toDFinsupp_toFinsupp
@[simp]
theorem DFinsupp.toFinsupp_toDFinsupp (f : Π₀ _ : ι, M) : f.toFinsupp.toDFinsupp = f :=
DFunLike.coe_injective rfl
#align dfinsupp.to_finsupp_to_dfinsupp DFinsupp.toFinsupp_toDFinsupp
end
end Defs
/-! ### Lemmas about arithmetic operations -/
section Lemmas
namespace Finsupp
@[simp]
theorem toDFinsupp_zero [Zero M] : (0 : ι →₀ M).toDFinsupp = 0 :=
DFunLike.coe_injective rfl
#align finsupp.to_dfinsupp_zero Finsupp.toDFinsupp_zero
@[simp]
theorem toDFinsupp_add [AddZeroClass M] (f g : ι →₀ M) :
(f + g).toDFinsupp = f.toDFinsupp + g.toDFinsupp :=
DFunLike.coe_injective rfl
#align finsupp.to_dfinsupp_add Finsupp.toDFinsupp_add
@[simp]
theorem toDFinsupp_neg [AddGroup M] (f : ι →₀ M) : (-f).toDFinsupp = -f.toDFinsupp :=
DFunLike.coe_injective rfl
#align finsupp.to_dfinsupp_neg Finsupp.toDFinsupp_neg
@[simp]
theorem toDFinsupp_sub [AddGroup M] (f g : ι →₀ M) :
(f - g).toDFinsupp = f.toDFinsupp - g.toDFinsupp :=
DFunLike.coe_injective rfl
#align finsupp.to_dfinsupp_sub Finsupp.toDFinsupp_sub
@[simp]
theorem toDFinsupp_smul [Monoid R] [AddMonoid M] [DistribMulAction R M] (r : R) (f : ι →₀ M) :
(r • f).toDFinsupp = r • f.toDFinsupp :=
DFunLike.coe_injective rfl
#align finsupp.to_dfinsupp_smul Finsupp.toDFinsupp_smul
end Finsupp
namespace DFinsupp
variable [DecidableEq ι]
@[simp]
theorem toFinsupp_zero [Zero M] [∀ m : M, Decidable (m ≠ 0)] : toFinsupp 0 = (0 : ι →₀ M) :=
DFunLike.coe_injective rfl
#align dfinsupp.to_finsupp_zero DFinsupp.toFinsupp_zero
@[simp]
theorem toFinsupp_add [AddZeroClass M] [∀ m : M, Decidable (m ≠ 0)] (f g : Π₀ _ : ι, M) :
(toFinsupp (f + g) : ι →₀ M) = toFinsupp f + toFinsupp g :=
DFunLike.coe_injective <| DFinsupp.coe_add _ _
#align dfinsupp.to_finsupp_add DFinsupp.toFinsupp_add
@[simp]
theorem toFinsupp_neg [AddGroup M] [∀ m : M, Decidable (m ≠ 0)] (f : Π₀ _ : ι, M) :
(toFinsupp (-f) : ι →₀ M) = -toFinsupp f :=
DFunLike.coe_injective <| DFinsupp.coe_neg _
#align dfinsupp.to_finsupp_neg DFinsupp.toFinsupp_neg
@[simp]
theorem toFinsupp_sub [AddGroup M] [∀ m : M, Decidable (m ≠ 0)] (f g : Π₀ _ : ι, M) :
(toFinsupp (f - g) : ι →₀ M) = toFinsupp f - toFinsupp g :=
DFunLike.coe_injective <| DFinsupp.coe_sub _ _
#align dfinsupp.to_finsupp_sub DFinsupp.toFinsupp_sub
@[simp]
theorem toFinsupp_smul [Monoid R] [AddMonoid M] [DistribMulAction R M] [∀ m : M, Decidable (m ≠ 0)]
(r : R) (f : Π₀ _ : ι, M) : (toFinsupp (r • f) : ι →₀ M) = r • toFinsupp f :=
DFunLike.coe_injective <| DFinsupp.coe_smul _ _
#align dfinsupp.to_finsupp_smul DFinsupp.toFinsupp_smul
end DFinsupp
end Lemmas
/-! ### Bundled `Equiv`s -/
section Equivs
/-- `Finsupp.toDFinsupp` and `DFinsupp.toFinsupp` together form an equiv. -/
@[simps (config := .asFn)]
def finsuppEquivDFinsupp [DecidableEq ι] [Zero M] [∀ m : M, Decidable (m ≠ 0)] :
(ι →₀ M) ≃ Π₀ _ : ι, M where
toFun := Finsupp.toDFinsupp
invFun := DFinsupp.toFinsupp
left_inv := Finsupp.toDFinsupp_toFinsupp
right_inv := DFinsupp.toFinsupp_toDFinsupp
#align finsupp_equiv_dfinsupp finsuppEquivDFinsupp
/-- The additive version of `finsupp.toFinsupp`. Note that this is `noncomputable` because
`Finsupp.add` is noncomputable. -/
@[simps (config := .asFn)]
def finsuppAddEquivDFinsupp [DecidableEq ι] [AddZeroClass M] [∀ m : M, Decidable (m ≠ 0)] :
(ι →₀ M) ≃+ Π₀ _ : ι, M :=
{ finsuppEquivDFinsupp with
toFun := Finsupp.toDFinsupp
invFun := DFinsupp.toFinsupp
map_add' := Finsupp.toDFinsupp_add }
#align finsupp_add_equiv_dfinsupp finsuppAddEquivDFinsupp
variable (R)
/-- The additive version of `Finsupp.toFinsupp`. Note that this is `noncomputable` because
`Finsupp.add` is noncomputable. -/
-- Porting note: `simps` generated lemmas that did not pass `simpNF` lints, manually added below
--@[simps? (config := .asFn)]
def finsuppLequivDFinsupp [DecidableEq ι] [Semiring R] [AddCommMonoid M]
[∀ m : M, Decidable (m ≠ 0)] [Module R M] : (ι →₀ M) ≃ₗ[R] Π₀ _ : ι, M :=
{ finsuppEquivDFinsupp with
toFun := Finsupp.toDFinsupp
invFun := DFinsupp.toFinsupp
map_smul' := Finsupp.toDFinsupp_smul
map_add' := Finsupp.toDFinsupp_add }
#align finsupp_lequiv_dfinsupp finsuppLequivDFinsupp
-- Porting note: `simps` generated as `↑(finsuppLequivDFinsupp R).toLinearMap = Finsupp.toDFinsupp`
@[simp]
theorem finsuppLequivDFinsupp_apply_apply [DecidableEq ι] [Semiring R] [AddCommMonoid M]
[∀ m : M, Decidable (m ≠ 0)] [Module R M] :
(↑(finsuppLequivDFinsupp (M := M) R) : (ι →₀ M) → _) = Finsupp.toDFinsupp := by
simp only [@LinearEquiv.coe_coe]; rfl
@[simp]
theorem finsuppLequivDFinsupp_symm_apply [DecidableEq ι] [Semiring R] [AddCommMonoid M]
[∀ m : M, Decidable (m ≠ 0)] [Module R M] :
↑(LinearEquiv.symm (finsuppLequivDFinsupp (ι := ι) (M := M) R)) = DFinsupp.toFinsupp :=
rfl
-- Porting note: moved noncomputable declaration into section begin
noncomputable section Sigma
/-! ### Stronger versions of `Finsupp.split` -/
--noncomputable section
variable {η : ι → Type*} {N : Type*} [Semiring R]
open Finsupp
/-- `Finsupp.split` is an equivalence between `(Σ i, η i) →₀ N` and `Π₀ i, (η i →₀ N)`. -/
def sigmaFinsuppEquivDFinsupp [Zero N] : ((Σi, η i) →₀ N) ≃ Π₀ i, η i →₀ N where
toFun f := ⟨split f, Trunc.mk ⟨(splitSupport f : Finset ι).val, fun i => by
rw [← Finset.mem_def, mem_splitSupport_iff_nonzero]
exact (em _).symm⟩⟩
invFun f := by
haveI := Classical.decEq ι
haveI := fun i => Classical.decEq (η i →₀ N)
refine
onFinset (Finset.sigma f.support fun j => (f j).support) (fun ji => f ji.1 ji.2) fun g hg =>
Finset.mem_sigma.mpr ⟨?_, mem_support_iff.mpr hg⟩
simp only [Ne, DFinsupp.mem_support_toFun]
intro h
dsimp at hg
rw [h] at hg
simp only [coe_zero, Pi.zero_apply, not_true] at hg
left_inv f := by ext; simp [split]
right_inv f := by ext; simp [split]
#align sigma_finsupp_equiv_dfinsupp sigmaFinsuppEquivDFinsupp
@[simp]
theorem sigmaFinsuppEquivDFinsupp_apply [Zero N] (f : (Σi, η i) →₀ N) :
(sigmaFinsuppEquivDFinsupp f : ∀ i, η i →₀ N) = Finsupp.split f :=
rfl
#align sigma_finsupp_equiv_dfinsupp_apply sigmaFinsuppEquivDFinsupp_apply
@[simp]
theorem sigmaFinsuppEquivDFinsupp_symm_apply [Zero N] (f : Π₀ i, η i →₀ N) (s : Σi, η i) :
(sigmaFinsuppEquivDFinsupp.symm f : (Σi, η i) →₀ N) s = f s.1 s.2 :=
rfl
#align sigma_finsupp_equiv_dfinsupp_symm_apply sigmaFinsuppEquivDFinsupp_symm_apply
@[simp]
theorem sigmaFinsuppEquivDFinsupp_support [DecidableEq ι] [Zero N]
[∀ (i : ι) (x : η i →₀ N), Decidable (x ≠ 0)] (f : (Σi, η i) →₀ N) :
(sigmaFinsuppEquivDFinsupp f).support = Finsupp.splitSupport f := by
ext
rw [DFinsupp.mem_support_toFun]
exact (Finsupp.mem_splitSupport_iff_nonzero _ _).symm
#align sigma_finsupp_equiv_dfinsupp_support sigmaFinsuppEquivDFinsupp_support
@[simp]
theorem sigmaFinsuppEquivDFinsupp_single [DecidableEq ι] [Zero N] (a : Σi, η i) (n : N) :
sigmaFinsuppEquivDFinsupp (Finsupp.single a n) =
@DFinsupp.single _ (fun i => η i →₀ N) _ _ a.1 (Finsupp.single a.2 n) := by
obtain ⟨i, a⟩ := a
ext j b
by_cases h : i = j
· subst h
classical simp [split_apply, Finsupp.single_apply]
suffices Finsupp.single (⟨i, a⟩ : Σi, η i) n ⟨j, b⟩ = 0 by simp [split_apply, dif_neg h, this]
have H : (⟨i, a⟩ : Σi, η i) ≠ ⟨j, b⟩ := by simp [h]
classical rw [Finsupp.single_apply, if_neg H]
#align sigma_finsupp_equiv_dfinsupp_single sigmaFinsuppEquivDFinsupp_single
-- Without this Lean fails to find the `AddZeroClass` instance on `Π₀ i, (η i →₀ N)`.
attribute [-instance] Finsupp.instZero
@[simp]
theorem sigmaFinsuppEquivDFinsupp_add [AddZeroClass N] (f g : (Σi, η i) →₀ N) :
sigmaFinsuppEquivDFinsupp (f + g) =
(sigmaFinsuppEquivDFinsupp f + sigmaFinsuppEquivDFinsupp g : Π₀ i : ι, η i →₀ N) := by
ext
rfl
#align sigma_finsupp_equiv_dfinsupp_add sigmaFinsuppEquivDFinsupp_add
/-- `Finsupp.split` is an additive equivalence between `(Σ i, η i) →₀ N` and `Π₀ i, (η i →₀ N)`. -/
@[simps]
def sigmaFinsuppAddEquivDFinsupp [AddZeroClass N] : ((Σi, η i) →₀ N) ≃+ Π₀ i, η i →₀ N :=
{ sigmaFinsuppEquivDFinsupp with
toFun := sigmaFinsuppEquivDFinsupp
invFun := sigmaFinsuppEquivDFinsupp.symm
map_add' := sigmaFinsuppEquivDFinsupp_add }
#align sigma_finsupp_add_equiv_dfinsupp sigmaFinsuppAddEquivDFinsupp
attribute [-instance] Finsupp.instAddZeroClass
@[simp]
| Mathlib/Data/Finsupp/ToDFinsupp.lean | 359 | 363 | theorem sigmaFinsuppEquivDFinsupp_smul {R} [Monoid R] [AddMonoid N] [DistribMulAction R N] (r : R)
(f : (Σ i, η i) →₀ N) :
sigmaFinsuppEquivDFinsupp (r • f) = r • sigmaFinsuppEquivDFinsupp f := by |
ext
rfl
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Robert Y. Lewis
-/
import Mathlib.Algebra.MvPolynomial.Monad
#align_import data.mv_polynomial.expand from "leanprover-community/mathlib"@"5da451b4c96b4c2e122c0325a7fce17d62ee46c6"
/-!
## Expand multivariate polynomials
Given a multivariate polynomial `φ`, one may replace every occurrence of `X i` by `X i ^ n`,
for some natural number `n`.
This operation is called `MvPolynomial.expand` and it is an algebra homomorphism.
### Main declaration
* `MvPolynomial.expand`: expand a polynomial by a factor of p, so `∑ aₙ xⁿ` becomes `∑ aₙ xⁿᵖ`.
-/
namespace MvPolynomial
variable {σ τ R S : Type*} [CommSemiring R] [CommSemiring S]
/-- Expand the polynomial by a factor of p, so `∑ aₙ xⁿ` becomes `∑ aₙ xⁿᵖ`.
See also `Polynomial.expand`. -/
noncomputable def expand (p : ℕ) : MvPolynomial σ R →ₐ[R] MvPolynomial σ R :=
{ (eval₂Hom C fun i ↦ X i ^ p : MvPolynomial σ R →+* MvPolynomial σ R) with
commutes' := fun _ ↦ eval₂Hom_C _ _ _ }
#align mv_polynomial.expand MvPolynomial.expand
-- @[simp] -- Porting note (#10618): simp can prove this
theorem expand_C (p : ℕ) (r : R) : expand p (C r : MvPolynomial σ R) = C r :=
eval₂Hom_C _ _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.expand_C MvPolynomial.expand_C
@[simp]
theorem expand_X (p : ℕ) (i : σ) : expand p (X i : MvPolynomial σ R) = X i ^ p :=
eval₂Hom_X' _ _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.expand_X MvPolynomial.expand_X
@[simp]
theorem expand_monomial (p : ℕ) (d : σ →₀ ℕ) (r : R) :
expand p (monomial d r) = C r * ∏ i ∈ d.support, (X i ^ p) ^ d i :=
bind₁_monomial _ _ _
#align mv_polynomial.expand_monomial MvPolynomial.expand_monomial
theorem expand_one_apply (f : MvPolynomial σ R) : expand 1 f = f := by
simp only [expand, pow_one, eval₂Hom_eq_bind₂, bind₂_C_left, RingHom.toMonoidHom_eq_coe,
RingHom.coe_monoidHom_id, AlgHom.coe_mk, RingHom.coe_mk, MonoidHom.id_apply, RingHom.id_apply]
#align mv_polynomial.expand_one_apply MvPolynomial.expand_one_apply
@[simp]
theorem expand_one : expand 1 = AlgHom.id R (MvPolynomial σ R) := by
ext1 f
rw [expand_one_apply, AlgHom.id_apply]
#align mv_polynomial.expand_one MvPolynomial.expand_one
theorem expand_comp_bind₁ (p : ℕ) (f : σ → MvPolynomial τ R) :
(expand p).comp (bind₁ f) = bind₁ fun i ↦ expand p (f i) := by
apply algHom_ext
intro i
simp only [AlgHom.comp_apply, bind₁_X_right]
#align mv_polynomial.expand_comp_bind₁ MvPolynomial.expand_comp_bind₁
theorem expand_bind₁ (p : ℕ) (f : σ → MvPolynomial τ R) (φ : MvPolynomial σ R) :
expand p (bind₁ f φ) = bind₁ (fun i ↦ expand p (f i)) φ := by
rw [← AlgHom.comp_apply, expand_comp_bind₁]
#align mv_polynomial.expand_bind₁ MvPolynomial.expand_bind₁
@[simp]
theorem map_expand (f : R →+* S) (p : ℕ) (φ : MvPolynomial σ R) :
map f (expand p φ) = expand p (map f φ) := by simp [expand, map_bind₁]
#align mv_polynomial.map_expand MvPolynomial.map_expand
@[simp]
theorem rename_expand (f : σ → τ) (p : ℕ) (φ : MvPolynomial σ R) :
rename f (expand p φ) = expand p (rename f φ) := by
simp [expand, bind₁_rename, rename_bind₁, Function.comp]
#align mv_polynomial.rename_expand MvPolynomial.rename_expand
@[simp]
| Mathlib/Algebra/MvPolynomial/Expand.lean | 88 | 92 | theorem rename_comp_expand (f : σ → τ) (p : ℕ) :
(rename f).comp (expand p) =
(expand p).comp (rename f : MvPolynomial σ R →ₐ[R] MvPolynomial τ R) := by |
ext1 φ
simp only [rename_expand, AlgHom.comp_apply]
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Algebra.Algebra.Equiv
import Mathlib.LinearAlgebra.Dimension.StrongRankCondition
import Mathlib.LinearAlgebra.FreeModule.Basic
import Mathlib.LinearAlgebra.FreeModule.Finite.Basic
import Mathlib.SetTheory.Cardinal.Ordinal
#align_import algebra.quaternion from "leanprover-community/mathlib"@"cf7a7252c1989efe5800e0b3cdfeb4228ac6b40e"
/-!
# Quaternions
In this file we define quaternions `ℍ[R]` over a commutative ring `R`, and define some
algebraic structures on `ℍ[R]`.
## Main definitions
* `QuaternionAlgebra R a b`, `ℍ[R, a, b]` :
[quaternion algebra](https://en.wikipedia.org/wiki/Quaternion_algebra) with coefficients `a`, `b`
* `Quaternion R`, `ℍ[R]` : the space of quaternions, a.k.a. `QuaternionAlgebra R (-1) (-1)`;
* `Quaternion.normSq` : square of the norm of a quaternion;
We also define the following algebraic structures on `ℍ[R]`:
* `Ring ℍ[R, a, b]`, `StarRing ℍ[R, a, b]`, and `Algebra R ℍ[R, a, b]` : for any commutative ring
`R`;
* `Ring ℍ[R]`, `StarRing ℍ[R]`, and `Algebra R ℍ[R]` : for any commutative ring `R`;
* `IsDomain ℍ[R]` : for a linear ordered commutative ring `R`;
* `DivisionRing ℍ[R]` : for a linear ordered field `R`.
## Notation
The following notation is available with `open Quaternion` or `open scoped Quaternion`.
* `ℍ[R, c₁, c₂]` : `QuaternionAlgebra R c₁ c₂`
* `ℍ[R]` : quaternions over `R`.
## Implementation notes
We define quaternions over any ring `R`, not just `ℝ` to be able to deal with, e.g., integer
or rational quaternions without using real numbers. In particular, all definitions in this file
are computable.
## Tags
quaternion
-/
/-- Quaternion algebra over a type with fixed coefficients $a=i^2$ and $b=j^2$.
Implemented as a structure with four fields: `re`, `imI`, `imJ`, and `imK`. -/
@[ext]
structure QuaternionAlgebra (R : Type*) (a b : R) where
/-- Real part of a quaternion. -/
re : R
imI : R
imJ : R
imK : R
#align quaternion_algebra QuaternionAlgebra
#align quaternion_algebra.re QuaternionAlgebra.re
#align quaternion_algebra.im_i QuaternionAlgebra.imI
#align quaternion_algebra.im_j QuaternionAlgebra.imJ
#align quaternion_algebra.im_k QuaternionAlgebra.imK
@[inherit_doc]
scoped[Quaternion] notation "ℍ[" R "," a "," b "]" => QuaternionAlgebra R a b
open Quaternion
namespace QuaternionAlgebra
/-- The equivalence between a quaternion algebra over `R` and `R × R × R × R`. -/
@[simps]
def equivProd {R : Type*} (c₁ c₂ : R) : ℍ[R,c₁,c₂] ≃ R × R × R × R where
toFun a := ⟨a.1, a.2, a.3, a.4⟩
invFun a := ⟨a.1, a.2.1, a.2.2.1, a.2.2.2⟩
left_inv _ := rfl
right_inv _ := rfl
#align quaternion_algebra.equiv_prod QuaternionAlgebra.equivProd
/-- The equivalence between a quaternion algebra over `R` and `Fin 4 → R`. -/
@[simps symm_apply]
def equivTuple {R : Type*} (c₁ c₂ : R) : ℍ[R,c₁,c₂] ≃ (Fin 4 → R) where
toFun a := ![a.1, a.2, a.3, a.4]
invFun a := ⟨a 0, a 1, a 2, a 3⟩
left_inv _ := rfl
right_inv f := by ext ⟨_, _ | _ | _ | _ | _ | ⟨⟩⟩ <;> rfl
#align quaternion_algebra.equiv_tuple QuaternionAlgebra.equivTuple
@[simp]
theorem equivTuple_apply {R : Type*} (c₁ c₂ : R) (x : ℍ[R,c₁,c₂]) :
equivTuple c₁ c₂ x = ![x.re, x.imI, x.imJ, x.imK] :=
rfl
#align quaternion_algebra.equiv_tuple_apply QuaternionAlgebra.equivTuple_apply
@[simp]
theorem mk.eta {R : Type*} {c₁ c₂} (a : ℍ[R,c₁,c₂]) : mk a.1 a.2 a.3 a.4 = a := rfl
#align quaternion_algebra.mk.eta QuaternionAlgebra.mk.eta
variable {S T R : Type*} [CommRing R] {c₁ c₂ : R} (r x y z : R) (a b c : ℍ[R,c₁,c₂])
instance [Subsingleton R] : Subsingleton ℍ[R, c₁, c₂] := (equivTuple c₁ c₂).subsingleton
instance [Nontrivial R] : Nontrivial ℍ[R, c₁, c₂] := (equivTuple c₁ c₂).surjective.nontrivial
/-- The imaginary part of a quaternion. -/
def im (x : ℍ[R,c₁,c₂]) : ℍ[R,c₁,c₂] :=
⟨0, x.imI, x.imJ, x.imK⟩
#align quaternion_algebra.im QuaternionAlgebra.im
@[simp]
theorem im_re : a.im.re = 0 :=
rfl
#align quaternion_algebra.im_re QuaternionAlgebra.im_re
@[simp]
theorem im_imI : a.im.imI = a.imI :=
rfl
#align quaternion_algebra.im_im_i QuaternionAlgebra.im_imI
@[simp]
theorem im_imJ : a.im.imJ = a.imJ :=
rfl
#align quaternion_algebra.im_im_j QuaternionAlgebra.im_imJ
@[simp]
theorem im_imK : a.im.imK = a.imK :=
rfl
#align quaternion_algebra.im_im_k QuaternionAlgebra.im_imK
@[simp]
theorem im_idem : a.im.im = a.im :=
rfl
#align quaternion_algebra.im_idem QuaternionAlgebra.im_idem
/-- Coercion `R → ℍ[R,c₁,c₂]`. -/
@[coe] def coe (x : R) : ℍ[R,c₁,c₂] := ⟨x, 0, 0, 0⟩
instance : CoeTC R ℍ[R,c₁,c₂] := ⟨coe⟩
@[simp, norm_cast]
theorem coe_re : (x : ℍ[R,c₁,c₂]).re = x := rfl
#align quaternion_algebra.coe_re QuaternionAlgebra.coe_re
@[simp, norm_cast]
theorem coe_imI : (x : ℍ[R,c₁,c₂]).imI = 0 := rfl
#align quaternion_algebra.coe_im_i QuaternionAlgebra.coe_imI
@[simp, norm_cast]
theorem coe_imJ : (x : ℍ[R,c₁,c₂]).imJ = 0 := rfl
#align quaternion_algebra.coe_im_j QuaternionAlgebra.coe_imJ
@[simp, norm_cast]
theorem coe_imK : (x : ℍ[R,c₁,c₂]).imK = 0 := rfl
#align quaternion_algebra.coe_im_k QuaternionAlgebra.coe_imK
theorem coe_injective : Function.Injective (coe : R → ℍ[R,c₁,c₂]) := fun _ _ h => congr_arg re h
#align quaternion_algebra.coe_injective QuaternionAlgebra.coe_injective
@[simp]
theorem coe_inj {x y : R} : (x : ℍ[R,c₁,c₂]) = y ↔ x = y :=
coe_injective.eq_iff
#align quaternion_algebra.coe_inj QuaternionAlgebra.coe_inj
-- Porting note: removed `simps`, added simp lemmas manually
instance : Zero ℍ[R,c₁,c₂] := ⟨⟨0, 0, 0, 0⟩⟩
@[simp] theorem zero_re : (0 : ℍ[R,c₁,c₂]).re = 0 := rfl
#align quaternion_algebra.has_zero_zero_re QuaternionAlgebra.zero_re
@[simp] theorem zero_imI : (0 : ℍ[R,c₁,c₂]).imI = 0 := rfl
#align quaternion_algebra.has_zero_zero_im_i QuaternionAlgebra.zero_imI
@[simp] theorem zero_imJ : (0 : ℍ[R,c₁,c₂]).imJ = 0 := rfl
#align quaternion_algebra.zero_zero_im_j QuaternionAlgebra.zero_imJ
@[simp] theorem zero_imK : (0 : ℍ[R,c₁,c₂]).imK = 0 := rfl
#align quaternion_algebra.zero_zero_im_k QuaternionAlgebra.zero_imK
@[simp] theorem zero_im : (0 : ℍ[R,c₁,c₂]).im = 0 := rfl
@[simp, norm_cast]
theorem coe_zero : ((0 : R) : ℍ[R,c₁,c₂]) = 0 := rfl
#align quaternion_algebra.coe_zero QuaternionAlgebra.coe_zero
instance : Inhabited ℍ[R,c₁,c₂] := ⟨0⟩
-- Porting note: removed `simps`, added simp lemmas manually
instance : One ℍ[R,c₁,c₂] := ⟨⟨1, 0, 0, 0⟩⟩
@[simp] theorem one_re : (1 : ℍ[R,c₁,c₂]).re = 1 := rfl
#align quaternion_algebra.has_one_one_re QuaternionAlgebra.one_re
@[simp] theorem one_imI : (1 : ℍ[R,c₁,c₂]).imI = 0 := rfl
#align quaternion_algebra.has_one_one_im_i QuaternionAlgebra.one_imI
@[simp] theorem one_imJ : (1 : ℍ[R,c₁,c₂]).imJ = 0 := rfl
#align quaternion_algebra.one_one_im_j QuaternionAlgebra.one_imJ
@[simp] theorem one_imK : (1 : ℍ[R,c₁,c₂]).imK = 0 := rfl
#align quaternion_algebra.one_one_im_k QuaternionAlgebra.one_imK
@[simp] theorem one_im : (1 : ℍ[R,c₁,c₂]).im = 0 := rfl
@[simp, norm_cast]
theorem coe_one : ((1 : R) : ℍ[R,c₁,c₂]) = 1 := rfl
#align quaternion_algebra.coe_one QuaternionAlgebra.coe_one
-- Porting note: removed `simps`, added simp lemmas manually
instance : Add ℍ[R,c₁,c₂] :=
⟨fun a b => ⟨a.1 + b.1, a.2 + b.2, a.3 + b.3, a.4 + b.4⟩⟩
@[simp] theorem add_re : (a + b).re = a.re + b.re := rfl
#align quaternion_algebra.has_add_add_re QuaternionAlgebra.add_re
@[simp] theorem add_imI : (a + b).imI = a.imI + b.imI := rfl
#align quaternion_algebra.has_add_add_im_i QuaternionAlgebra.add_imI
@[simp] theorem add_imJ : (a + b).imJ = a.imJ + b.imJ := rfl
#align quaternion_algebra.has_add_add_im_j QuaternionAlgebra.add_imJ
@[simp] theorem add_imK : (a + b).imK = a.imK + b.imK := rfl
#align quaternion_algebra.has_add_add_im_k QuaternionAlgebra.add_imK
@[simp] theorem add_im : (a + b).im = a.im + b.im :=
QuaternionAlgebra.ext _ _ (zero_add _).symm rfl rfl rfl
@[simp]
theorem mk_add_mk (a₁ a₂ a₃ a₄ b₁ b₂ b₃ b₄ : R) :
(mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂]) + mk b₁ b₂ b₃ b₄ = mk (a₁ + b₁) (a₂ + b₂) (a₃ + b₃) (a₄ + b₄) :=
rfl
#align quaternion_algebra.mk_add_mk QuaternionAlgebra.mk_add_mk
@[simp, norm_cast]
theorem coe_add : ((x + y : R) : ℍ[R,c₁,c₂]) = x + y := by ext <;> simp
#align quaternion_algebra.coe_add QuaternionAlgebra.coe_add
-- Porting note: removed `simps`, added simp lemmas manually
instance : Neg ℍ[R,c₁,c₂] := ⟨fun a => ⟨-a.1, -a.2, -a.3, -a.4⟩⟩
@[simp] theorem neg_re : (-a).re = -a.re := rfl
#align quaternion_algebra.has_neg_neg_re QuaternionAlgebra.neg_re
@[simp] theorem neg_imI : (-a).imI = -a.imI := rfl
#align quaternion_algebra.has_neg_neg_im_i QuaternionAlgebra.neg_imI
@[simp] theorem neg_imJ : (-a).imJ = -a.imJ := rfl
#align quaternion_algebra.has_neg_neg_im_j QuaternionAlgebra.neg_imJ
@[simp] theorem neg_imK : (-a).imK = -a.imK := rfl
#align quaternion_algebra.has_neg_neg_im_k QuaternionAlgebra.neg_imK
@[simp] theorem neg_im : (-a).im = -a.im :=
QuaternionAlgebra.ext _ _ neg_zero.symm rfl rfl rfl
@[simp]
theorem neg_mk (a₁ a₂ a₃ a₄ : R) : -(mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂]) = ⟨-a₁, -a₂, -a₃, -a₄⟩ :=
rfl
#align quaternion_algebra.neg_mk QuaternionAlgebra.neg_mk
@[simp, norm_cast]
theorem coe_neg : ((-x : R) : ℍ[R,c₁,c₂]) = -x := by ext <;> simp
#align quaternion_algebra.coe_neg QuaternionAlgebra.coe_neg
instance : Sub ℍ[R,c₁,c₂] :=
⟨fun a b => ⟨a.1 - b.1, a.2 - b.2, a.3 - b.3, a.4 - b.4⟩⟩
@[simp] theorem sub_re : (a - b).re = a.re - b.re := rfl
#align quaternion_algebra.has_sub_sub_re QuaternionAlgebra.sub_re
@[simp] theorem sub_imI : (a - b).imI = a.imI - b.imI := rfl
#align quaternion_algebra.has_sub_sub_im_i QuaternionAlgebra.sub_imI
@[simp] theorem sub_imJ : (a - b).imJ = a.imJ - b.imJ := rfl
#align quaternion_algebra.has_sub_sub_im_j QuaternionAlgebra.sub_imJ
@[simp] theorem sub_imK : (a - b).imK = a.imK - b.imK := rfl
#align quaternion_algebra.has_sub_sub_im_k QuaternionAlgebra.sub_imK
@[simp] theorem sub_im : (a - b).im = a.im - b.im :=
QuaternionAlgebra.ext _ _ (sub_zero _).symm rfl rfl rfl
@[simp]
theorem mk_sub_mk (a₁ a₂ a₃ a₄ b₁ b₂ b₃ b₄ : R) :
(mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂]) - mk b₁ b₂ b₃ b₄ = mk (a₁ - b₁) (a₂ - b₂) (a₃ - b₃) (a₄ - b₄) :=
rfl
#align quaternion_algebra.mk_sub_mk QuaternionAlgebra.mk_sub_mk
@[simp, norm_cast]
theorem coe_im : (x : ℍ[R,c₁,c₂]).im = 0 :=
rfl
#align quaternion_algebra.coe_im QuaternionAlgebra.coe_im
@[simp]
theorem re_add_im : ↑a.re + a.im = a :=
QuaternionAlgebra.ext _ _ (add_zero _) (zero_add _) (zero_add _) (zero_add _)
#align quaternion_algebra.re_add_im QuaternionAlgebra.re_add_im
@[simp]
theorem sub_self_im : a - a.im = a.re :=
QuaternionAlgebra.ext _ _ (sub_zero _) (sub_self _) (sub_self _) (sub_self _)
#align quaternion_algebra.sub_self_im QuaternionAlgebra.sub_self_im
@[simp]
theorem sub_self_re : a - a.re = a.im :=
QuaternionAlgebra.ext _ _ (sub_self _) (sub_zero _) (sub_zero _) (sub_zero _)
#align quaternion_algebra.sub_self_re QuaternionAlgebra.sub_self_re
/-- Multiplication is given by
* `1 * x = x * 1 = x`;
* `i * i = c₁`;
* `j * j = c₂`;
* `i * j = k`, `j * i = -k`;
* `k * k = -c₁ * c₂`;
* `i * k = c₁ * j`, `k * i = -c₁ * j`;
* `j * k = -c₂ * i`, `k * j = c₂ * i`. -/
instance : Mul ℍ[R,c₁,c₂] :=
⟨fun a b =>
⟨a.1 * b.1 + c₁ * a.2 * b.2 + c₂ * a.3 * b.3 - c₁ * c₂ * a.4 * b.4,
a.1 * b.2 + a.2 * b.1 - c₂ * a.3 * b.4 + c₂ * a.4 * b.3,
a.1 * b.3 + c₁ * a.2 * b.4 + a.3 * b.1 - c₁ * a.4 * b.2,
a.1 * b.4 + a.2 * b.3 - a.3 * b.2 + a.4 * b.1⟩⟩
@[simp]
theorem mul_re : (a * b).re = a.1 * b.1 + c₁ * a.2 * b.2 + c₂ * a.3 * b.3 - c₁ * c₂ * a.4 * b.4 :=
rfl
#align quaternion_algebra.has_mul_mul_re QuaternionAlgebra.mul_re
@[simp]
theorem mul_imI : (a * b).imI = a.1 * b.2 + a.2 * b.1 - c₂ * a.3 * b.4 + c₂ * a.4 * b.3 := rfl
#align quaternion_algebra.has_mul_mul_im_i QuaternionAlgebra.mul_imI
@[simp]
theorem mul_imJ : (a * b).imJ = a.1 * b.3 + c₁ * a.2 * b.4 + a.3 * b.1 - c₁ * a.4 * b.2 := rfl
#align quaternion_algebra.has_mul_mul_im_j QuaternionAlgebra.mul_imJ
@[simp] theorem mul_imK : (a * b).imK = a.1 * b.4 + a.2 * b.3 - a.3 * b.2 + a.4 * b.1 := rfl
#align quaternion_algebra.has_mul_mul_im_k QuaternionAlgebra.mul_imK
@[simp]
theorem mk_mul_mk (a₁ a₂ a₃ a₄ b₁ b₂ b₃ b₄ : R) :
(mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂]) * mk b₁ b₂ b₃ b₄ =
⟨a₁ * b₁ + c₁ * a₂ * b₂ + c₂ * a₃ * b₃ - c₁ * c₂ * a₄ * b₄,
a₁ * b₂ + a₂ * b₁ - c₂ * a₃ * b₄ + c₂ * a₄ * b₃,
a₁ * b₃ + c₁ * a₂ * b₄ + a₃ * b₁ - c₁ * a₄ * b₂, a₁ * b₄ + a₂ * b₃ - a₃ * b₂ + a₄ * b₁⟩ :=
rfl
#align quaternion_algebra.mk_mul_mk QuaternionAlgebra.mk_mul_mk
section
variable [SMul S R] [SMul T R] (s : S)
-- Porting note: Lean 4 auto drops the unused `[Ring R]` argument
instance : SMul S ℍ[R,c₁,c₂] where smul s a := ⟨s • a.1, s • a.2, s • a.3, s • a.4⟩
instance [SMul S T] [IsScalarTower S T R] : IsScalarTower S T ℍ[R,c₁,c₂] where
smul_assoc s t x := by ext <;> exact smul_assoc _ _ _
instance [SMulCommClass S T R] : SMulCommClass S T ℍ[R,c₁,c₂] where
smul_comm s t x := by ext <;> exact smul_comm _ _ _
@[simp] theorem smul_re : (s • a).re = s • a.re := rfl
#align quaternion_algebra.smul_re QuaternionAlgebra.smul_re
@[simp] theorem smul_imI : (s • a).imI = s • a.imI := rfl
#align quaternion_algebra.smul_im_i QuaternionAlgebra.smul_imI
@[simp] theorem smul_imJ : (s • a).imJ = s • a.imJ := rfl
#align quaternion_algebra.smul_im_j QuaternionAlgebra.smul_imJ
@[simp] theorem smul_imK : (s • a).imK = s • a.imK := rfl
#align quaternion_algebra.smul_im_k QuaternionAlgebra.smul_imK
@[simp] theorem smul_im {S} [SMulZeroClass S R] (s : S) : (s • a).im = s • a.im :=
QuaternionAlgebra.ext _ _ (smul_zero s).symm rfl rfl rfl
@[simp]
theorem smul_mk (re im_i im_j im_k : R) :
s • (⟨re, im_i, im_j, im_k⟩ : ℍ[R,c₁,c₂]) = ⟨s • re, s • im_i, s • im_j, s • im_k⟩ :=
rfl
#align quaternion_algebra.smul_mk QuaternionAlgebra.smul_mk
end
@[simp, norm_cast]
theorem coe_smul [SMulZeroClass S R] (s : S) (r : R) :
(↑(s • r) : ℍ[R,c₁,c₂]) = s • (r : ℍ[R,c₁,c₂]) :=
QuaternionAlgebra.ext _ _ rfl (smul_zero s).symm (smul_zero s).symm (smul_zero s).symm
#align quaternion_algebra.coe_smul QuaternionAlgebra.coe_smul
instance : AddCommGroup ℍ[R,c₁,c₂] :=
(equivProd c₁ c₂).injective.addCommGroup _ rfl (fun _ _ ↦ rfl) (fun _ ↦ rfl) (fun _ _ ↦ rfl)
(fun _ _ ↦ rfl) (fun _ _ ↦ rfl)
instance : AddCommGroupWithOne ℍ[R,c₁,c₂] where
natCast n := ((n : R) : ℍ[R,c₁,c₂])
natCast_zero := by simp
natCast_succ := by simp
intCast n := ((n : R) : ℍ[R,c₁,c₂])
intCast_ofNat _ := congr_arg coe (Int.cast_natCast _)
intCast_negSucc n := by
change coe _ = -coe _
rw [Int.cast_negSucc, coe_neg]
@[simp, norm_cast]
theorem natCast_re (n : ℕ) : (n : ℍ[R,c₁,c₂]).re = n :=
rfl
#align quaternion_algebra.nat_cast_re QuaternionAlgebra.natCast_re
@[deprecated (since := "2024-04-17")]
alias nat_cast_re := natCast_re
@[simp, norm_cast]
theorem natCast_imI (n : ℕ) : (n : ℍ[R,c₁,c₂]).imI = 0 :=
rfl
#align quaternion_algebra.nat_cast_im_i QuaternionAlgebra.natCast_imI
@[deprecated (since := "2024-04-17")]
alias nat_cast_imI := natCast_imI
@[simp, norm_cast]
theorem natCast_imJ (n : ℕ) : (n : ℍ[R,c₁,c₂]).imJ = 0 :=
rfl
#align quaternion_algebra.nat_cast_im_j QuaternionAlgebra.natCast_imJ
@[deprecated (since := "2024-04-17")]
alias nat_cast_imJ := natCast_imJ
@[simp, norm_cast]
theorem natCast_imK (n : ℕ) : (n : ℍ[R,c₁,c₂]).imK = 0 :=
rfl
#align quaternion_algebra.nat_cast_im_k QuaternionAlgebra.natCast_imK
@[deprecated (since := "2024-04-17")]
alias nat_cast_imK := natCast_imK
@[simp, norm_cast]
theorem natCast_im (n : ℕ) : (n : ℍ[R,c₁,c₂]).im = 0 :=
rfl
#align quaternion_algebra.nat_cast_im QuaternionAlgebra.natCast_im
@[deprecated (since := "2024-04-17")]
alias nat_cast_im := natCast_im
@[norm_cast]
theorem coe_natCast (n : ℕ) : ↑(n : R) = (n : ℍ[R,c₁,c₂]) :=
rfl
#align quaternion_algebra.coe_nat_cast QuaternionAlgebra.coe_natCast
@[deprecated (since := "2024-04-17")]
alias coe_nat_cast := coe_natCast
@[simp, norm_cast]
theorem intCast_re (z : ℤ) : (z : ℍ[R,c₁,c₂]).re = z :=
rfl
#align quaternion_algebra.int_cast_re QuaternionAlgebra.intCast_re
@[deprecated (since := "2024-04-17")]
alias int_cast_re := intCast_re
@[simp, norm_cast]
theorem intCast_imI (z : ℤ) : (z : ℍ[R,c₁,c₂]).imI = 0 :=
rfl
#align quaternion_algebra.int_cast_im_i QuaternionAlgebra.intCast_imI
@[deprecated (since := "2024-04-17")]
alias int_cast_imI := intCast_imI
@[simp, norm_cast]
theorem intCast_imJ (z : ℤ) : (z : ℍ[R,c₁,c₂]).imJ = 0 :=
rfl
#align quaternion_algebra.int_cast_im_j QuaternionAlgebra.intCast_imJ
@[deprecated (since := "2024-04-17")]
alias int_cast_imJ := intCast_imJ
@[simp, norm_cast]
theorem intCast_imK (z : ℤ) : (z : ℍ[R,c₁,c₂]).imK = 0 :=
rfl
#align quaternion_algebra.int_cast_im_k QuaternionAlgebra.intCast_imK
@[deprecated (since := "2024-04-17")]
alias int_cast_imK := intCast_imK
@[simp, norm_cast]
theorem intCast_im (z : ℤ) : (z : ℍ[R,c₁,c₂]).im = 0 :=
rfl
#align quaternion_algebra.int_cast_im QuaternionAlgebra.intCast_im
@[deprecated (since := "2024-04-17")]
alias int_cast_im := intCast_im
@[norm_cast]
theorem coe_intCast (z : ℤ) : ↑(z : R) = (z : ℍ[R,c₁,c₂]) :=
rfl
#align quaternion_algebra.coe_int_cast QuaternionAlgebra.coe_intCast
@[deprecated (since := "2024-04-17")]
alias coe_int_cast := coe_intCast
instance instRing : Ring ℍ[R,c₁,c₂] where
__ := inferInstanceAs (AddCommGroupWithOne ℍ[R,c₁,c₂])
left_distrib _ _ _ := by ext <;> simp <;> ring
right_distrib _ _ _ := by ext <;> simp <;> ring
zero_mul _ := by ext <;> simp
mul_zero _ := by ext <;> simp
mul_assoc _ _ _ := by ext <;> simp <;> ring
one_mul _ := by ext <;> simp
mul_one _ := by ext <;> simp
@[norm_cast, simp]
theorem coe_mul : ((x * y : R) : ℍ[R,c₁,c₂]) = x * y := by ext <;> simp
#align quaternion_algebra.coe_mul QuaternionAlgebra.coe_mul
-- TODO: add weaker `MulAction`, `DistribMulAction`, and `Module` instances (and repeat them
-- for `ℍ[R]`)
instance [CommSemiring S] [Algebra S R] : Algebra S ℍ[R,c₁,c₂] where
smul := (· • ·)
toFun s := coe (algebraMap S R s)
map_one' := by simp only [map_one, coe_one]
map_zero' := by simp only [map_zero, coe_zero]
map_mul' x y := by simp only [map_mul, coe_mul]
map_add' x y := by simp only [map_add, coe_add]
smul_def' s x := by ext <;> simp [Algebra.smul_def]
commutes' s x := by ext <;> simp [Algebra.commutes]
theorem algebraMap_eq (r : R) : algebraMap R ℍ[R,c₁,c₂] r = ⟨r, 0, 0, 0⟩ :=
rfl
#align quaternion_algebra.algebra_map_eq QuaternionAlgebra.algebraMap_eq
theorem algebraMap_injective : (algebraMap R ℍ[R,c₁,c₂] : _ → _).Injective :=
fun _ _ ↦ by simp [algebraMap_eq]
instance [NoZeroDivisors R] : NoZeroSMulDivisors R ℍ[R,c₁,c₂] := ⟨by
rintro t ⟨a, b, c, d⟩ h
rw [or_iff_not_imp_left]
intro ht
simpa [QuaternionAlgebra.ext_iff, ht] using h⟩
section
variable (c₁ c₂)
/-- `QuaternionAlgebra.re` as a `LinearMap`-/
@[simps]
def reₗ : ℍ[R,c₁,c₂] →ₗ[R] R where
toFun := re
map_add' _ _ := rfl
map_smul' _ _ := rfl
#align quaternion_algebra.re_lm QuaternionAlgebra.reₗ
/-- `QuaternionAlgebra.imI` as a `LinearMap`-/
@[simps]
def imIₗ : ℍ[R,c₁,c₂] →ₗ[R] R where
toFun := imI
map_add' _ _ := rfl
map_smul' _ _ := rfl
#align quaternion_algebra.im_i_lm QuaternionAlgebra.imIₗ
/-- `QuaternionAlgebra.imJ` as a `LinearMap`-/
@[simps]
def imJₗ : ℍ[R,c₁,c₂] →ₗ[R] R where
toFun := imJ
map_add' _ _ := rfl
map_smul' _ _ := rfl
#align quaternion_algebra.im_j_lm QuaternionAlgebra.imJₗ
/-- `QuaternionAlgebra.imK` as a `LinearMap`-/
@[simps]
def imKₗ : ℍ[R,c₁,c₂] →ₗ[R] R where
toFun := imK
map_add' _ _ := rfl
map_smul' _ _ := rfl
#align quaternion_algebra.im_k_lm QuaternionAlgebra.imKₗ
/-- `QuaternionAlgebra.equivTuple` as a linear equivalence. -/
def linearEquivTuple : ℍ[R,c₁,c₂] ≃ₗ[R] Fin 4 → R :=
LinearEquiv.symm -- proofs are not `rfl` in the forward direction
{ (equivTuple c₁ c₂).symm with
toFun := (equivTuple c₁ c₂).symm
invFun := equivTuple c₁ c₂
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align quaternion_algebra.linear_equiv_tuple QuaternionAlgebra.linearEquivTuple
@[simp]
theorem coe_linearEquivTuple : ⇑(linearEquivTuple c₁ c₂) = equivTuple c₁ c₂ :=
rfl
#align quaternion_algebra.coe_linear_equiv_tuple QuaternionAlgebra.coe_linearEquivTuple
@[simp]
theorem coe_linearEquivTuple_symm : ⇑(linearEquivTuple c₁ c₂).symm = (equivTuple c₁ c₂).symm :=
rfl
#align quaternion_algebra.coe_linear_equiv_tuple_symm QuaternionAlgebra.coe_linearEquivTuple_symm
/-- `ℍ[R, c₁, c₂]` has a basis over `R` given by `1`, `i`, `j`, and `k`. -/
noncomputable def basisOneIJK : Basis (Fin 4) R ℍ[R,c₁,c₂] :=
.ofEquivFun <| linearEquivTuple c₁ c₂
#align quaternion_algebra.basis_one_i_j_k QuaternionAlgebra.basisOneIJK
@[simp]
theorem coe_basisOneIJK_repr (q : ℍ[R,c₁,c₂]) :
⇑((basisOneIJK c₁ c₂).repr q) = ![q.re, q.imI, q.imJ, q.imK] :=
rfl
#align quaternion_algebra.coe_basis_one_i_j_k_repr QuaternionAlgebra.coe_basisOneIJK_repr
instance : Module.Finite R ℍ[R,c₁,c₂] := .of_basis (basisOneIJK c₁ c₂)
instance : Module.Free R ℍ[R,c₁,c₂] := .of_basis (basisOneIJK c₁ c₂)
theorem rank_eq_four [StrongRankCondition R] : Module.rank R ℍ[R,c₁,c₂] = 4 := by
rw [rank_eq_card_basis (basisOneIJK c₁ c₂), Fintype.card_fin]
norm_num
#align quaternion_algebra.rank_eq_four QuaternionAlgebra.rank_eq_four
theorem finrank_eq_four [StrongRankCondition R] : FiniteDimensional.finrank R ℍ[R,c₁,c₂] = 4 := by
rw [FiniteDimensional.finrank, rank_eq_four, Cardinal.toNat_ofNat]
#align quaternion_algebra.finrank_eq_four QuaternionAlgebra.finrank_eq_four
/-- There is a natural equivalence when swapping the coefficients of a quaternion algebra. -/
@[simps]
def swapEquiv : ℍ[R,c₁,c₂] ≃ₐ[R] ℍ[R, c₂, c₁] where
toFun t := ⟨t.1, t.3, t.2, -t.4⟩
invFun t := ⟨t.1, t.3, t.2, -t.4⟩
left_inv _ := by simp
right_inv _ := by simp
map_mul' _ _ := by
ext
<;> simp only [mul_re, mul_imJ, mul_imI, add_left_inj, mul_imK, neg_mul, neg_add_rev,
neg_sub, mk_mul_mk, mul_neg, neg_neg, sub_neg_eq_add]
<;> ring
map_add' _ _ := by ext <;> simp [add_comm]
commutes' _ := by simp [algebraMap_eq]
end
@[norm_cast, simp]
theorem coe_sub : ((x - y : R) : ℍ[R,c₁,c₂]) = x - y :=
(algebraMap R ℍ[R,c₁,c₂]).map_sub x y
#align quaternion_algebra.coe_sub QuaternionAlgebra.coe_sub
@[norm_cast, simp]
theorem coe_pow (n : ℕ) : (↑(x ^ n) : ℍ[R,c₁,c₂]) = (x : ℍ[R,c₁,c₂]) ^ n :=
(algebraMap R ℍ[R,c₁,c₂]).map_pow x n
#align quaternion_algebra.coe_pow QuaternionAlgebra.coe_pow
theorem coe_commutes : ↑r * a = a * r :=
Algebra.commutes r a
#align quaternion_algebra.coe_commutes QuaternionAlgebra.coe_commutes
theorem coe_commute : Commute (↑r) a :=
coe_commutes r a
#align quaternion_algebra.coe_commute QuaternionAlgebra.coe_commute
theorem coe_mul_eq_smul : ↑r * a = r • a :=
(Algebra.smul_def r a).symm
#align quaternion_algebra.coe_mul_eq_smul QuaternionAlgebra.coe_mul_eq_smul
theorem mul_coe_eq_smul : a * r = r • a := by rw [← coe_commutes, coe_mul_eq_smul]
#align quaternion_algebra.mul_coe_eq_smul QuaternionAlgebra.mul_coe_eq_smul
@[norm_cast, simp]
theorem coe_algebraMap : ⇑(algebraMap R ℍ[R,c₁,c₂]) = coe :=
rfl
#align quaternion_algebra.coe_algebra_map QuaternionAlgebra.coe_algebraMap
theorem smul_coe : x • (y : ℍ[R,c₁,c₂]) = ↑(x * y) := by rw [coe_mul, coe_mul_eq_smul]
#align quaternion_algebra.smul_coe QuaternionAlgebra.smul_coe
/-- Quaternion conjugate. -/
instance instStarQuaternionAlgebra : Star ℍ[R,c₁,c₂] where star a := ⟨a.1, -a.2, -a.3, -a.4⟩
@[simp] theorem re_star : (star a).re = a.re := rfl
#align quaternion_algebra.re_star QuaternionAlgebra.re_star
@[simp]
theorem imI_star : (star a).imI = -a.imI :=
rfl
#align quaternion_algebra.im_i_star QuaternionAlgebra.imI_star
@[simp]
theorem imJ_star : (star a).imJ = -a.imJ :=
rfl
#align quaternion_algebra.im_j_star QuaternionAlgebra.imJ_star
@[simp]
theorem imK_star : (star a).imK = -a.imK :=
rfl
#align quaternion_algebra.im_k_star QuaternionAlgebra.imK_star
@[simp]
theorem im_star : (star a).im = -a.im :=
QuaternionAlgebra.ext _ _ neg_zero.symm rfl rfl rfl
#align quaternion_algebra.im_star QuaternionAlgebra.im_star
@[simp]
theorem star_mk (a₁ a₂ a₃ a₄ : R) : star (mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂]) = ⟨a₁, -a₂, -a₃, -a₄⟩ :=
rfl
#align quaternion_algebra.star_mk QuaternionAlgebra.star_mk
instance instStarRing : StarRing ℍ[R,c₁,c₂] where
star_involutive x := by simp [Star.star]
star_add a b := by ext <;> simp [add_comm]
star_mul a b := by ext <;> simp <;> ring
theorem self_add_star' : a + star a = ↑(2 * a.re) := by ext <;> simp [two_mul]
#align quaternion_algebra.self_add_star' QuaternionAlgebra.self_add_star'
theorem self_add_star : a + star a = 2 * a.re := by simp only [self_add_star', two_mul, coe_add]
#align quaternion_algebra.self_add_star QuaternionAlgebra.self_add_star
theorem star_add_self' : star a + a = ↑(2 * a.re) := by rw [add_comm, self_add_star']
#align quaternion_algebra.star_add_self' QuaternionAlgebra.star_add_self'
theorem star_add_self : star a + a = 2 * a.re := by rw [add_comm, self_add_star]
#align quaternion_algebra.star_add_self QuaternionAlgebra.star_add_self
theorem star_eq_two_re_sub : star a = ↑(2 * a.re) - a :=
eq_sub_iff_add_eq.2 a.star_add_self'
#align quaternion_algebra.star_eq_two_re_sub QuaternionAlgebra.star_eq_two_re_sub
instance : IsStarNormal a :=
⟨by
rw [a.star_eq_two_re_sub]
exact (coe_commute (2 * a.re) a).sub_left (Commute.refl a)⟩
@[simp, norm_cast]
theorem star_coe : star (x : ℍ[R,c₁,c₂]) = x := by ext <;> simp
#align quaternion_algebra.star_coe QuaternionAlgebra.star_coe
@[simp] theorem star_im : star a.im = -a.im := im_star _
#align quaternion_algebra.star_im QuaternionAlgebra.star_im
@[simp]
theorem star_smul [Monoid S] [DistribMulAction S R] (s : S) (a : ℍ[R,c₁,c₂]) :
star (s • a) = s • star a :=
QuaternionAlgebra.ext _ _ rfl (smul_neg _ _).symm (smul_neg _ _).symm (smul_neg _ _).symm
#align quaternion_algebra.star_smul QuaternionAlgebra.star_smul
theorem eq_re_of_eq_coe {a : ℍ[R,c₁,c₂]} {x : R} (h : a = x) : a = a.re := by rw [h, coe_re]
#align quaternion_algebra.eq_re_of_eq_coe QuaternionAlgebra.eq_re_of_eq_coe
theorem eq_re_iff_mem_range_coe {a : ℍ[R,c₁,c₂]} :
a = a.re ↔ a ∈ Set.range (coe : R → ℍ[R,c₁,c₂]) :=
⟨fun h => ⟨a.re, h.symm⟩, fun ⟨_, h⟩ => eq_re_of_eq_coe h.symm⟩
#align quaternion_algebra.eq_re_iff_mem_range_coe QuaternionAlgebra.eq_re_iff_mem_range_coe
section CharZero
variable [NoZeroDivisors R] [CharZero R]
@[simp]
theorem star_eq_self {c₁ c₂ : R} {a : ℍ[R,c₁,c₂]} : star a = a ↔ a = a.re := by
simp [QuaternionAlgebra.ext_iff, neg_eq_iff_add_eq_zero, add_self_eq_zero]
#align quaternion_algebra.star_eq_self QuaternionAlgebra.star_eq_self
theorem star_eq_neg {c₁ c₂ : R} {a : ℍ[R,c₁,c₂]} : star a = -a ↔ a.re = 0 := by
simp [QuaternionAlgebra.ext_iff, eq_neg_iff_add_eq_zero]
#align quaternion_algebra.star_eq_neg QuaternionAlgebra.star_eq_neg
end CharZero
-- Can't use `rw ← star_eq_self` in the proof without additional assumptions
theorem star_mul_eq_coe : star a * a = (star a * a).re := by ext <;> simp <;> ring
#align quaternion_algebra.star_mul_eq_coe QuaternionAlgebra.star_mul_eq_coe
theorem mul_star_eq_coe : a * star a = (a * star a).re := by
rw [← star_comm_self']
exact a.star_mul_eq_coe
#align quaternion_algebra.mul_star_eq_coe QuaternionAlgebra.mul_star_eq_coe
open MulOpposite
/-- Quaternion conjugate as an `AlgEquiv` to the opposite ring. -/
def starAe : ℍ[R,c₁,c₂] ≃ₐ[R] ℍ[R,c₁,c₂]ᵐᵒᵖ :=
{ starAddEquiv.trans opAddEquiv with
toFun := op ∘ star
invFun := star ∘ unop
map_mul' := fun x y => by simp
commutes' := fun r => by simp }
#align quaternion_algebra.star_ae QuaternionAlgebra.starAe
@[simp]
theorem coe_starAe : ⇑(starAe : ℍ[R,c₁,c₂] ≃ₐ[R] _) = op ∘ star :=
rfl
#align quaternion_algebra.coe_star_ae QuaternionAlgebra.coe_starAe
end QuaternionAlgebra
/-- Space of quaternions over a type. Implemented as a structure with four fields:
`re`, `im_i`, `im_j`, and `im_k`. -/
def Quaternion (R : Type*) [One R] [Neg R] :=
QuaternionAlgebra R (-1) (-1)
#align quaternion Quaternion
scoped[Quaternion] notation "ℍ[" R "]" => Quaternion R
/-- The equivalence between the quaternions over `R` and `R × R × R × R`. -/
@[simps!]
def Quaternion.equivProd (R : Type*) [One R] [Neg R] : ℍ[R] ≃ R × R × R × R :=
QuaternionAlgebra.equivProd _ _
#align quaternion.equiv_prod Quaternion.equivProd
/-- The equivalence between the quaternions over `R` and `Fin 4 → R`. -/
@[simps! symm_apply]
def Quaternion.equivTuple (R : Type*) [One R] [Neg R] : ℍ[R] ≃ (Fin 4 → R) :=
QuaternionAlgebra.equivTuple _ _
#align quaternion.equiv_tuple Quaternion.equivTuple
@[simp]
theorem Quaternion.equivTuple_apply (R : Type*) [One R] [Neg R] (x : ℍ[R]) :
Quaternion.equivTuple R x = ![x.re, x.imI, x.imJ, x.imK] :=
rfl
#align quaternion.equiv_tuple_apply Quaternion.equivTuple_apply
instance {R : Type*} [One R] [Neg R] [Subsingleton R] : Subsingleton ℍ[R] :=
inferInstanceAs (Subsingleton <| ℍ[R, -1, -1])
instance {R : Type*} [One R] [Neg R] [Nontrivial R] : Nontrivial ℍ[R] :=
inferInstanceAs (Nontrivial <| ℍ[R, -1, -1])
namespace Quaternion
variable {S T R : Type*} [CommRing R] (r x y z : R) (a b c : ℍ[R])
export QuaternionAlgebra (re imI imJ imK)
/-- Coercion `R → ℍ[R]`. -/
@[coe] def coe : R → ℍ[R] := QuaternionAlgebra.coe
instance : CoeTC R ℍ[R] := ⟨coe⟩
instance instRing : Ring ℍ[R] := QuaternionAlgebra.instRing
instance : Inhabited ℍ[R] := inferInstanceAs <| Inhabited ℍ[R,-1,-1]
instance [SMul S R] : SMul S ℍ[R] := inferInstanceAs <| SMul S ℍ[R,-1,-1]
instance [SMul S T] [SMul S R] [SMul T R] [IsScalarTower S T R] : IsScalarTower S T ℍ[R] :=
inferInstanceAs <| IsScalarTower S T ℍ[R,-1,-1]
instance [SMul S R] [SMul T R] [SMulCommClass S T R] : SMulCommClass S T ℍ[R] :=
inferInstanceAs <| SMulCommClass S T ℍ[R,-1,-1]
protected instance algebra [CommSemiring S] [Algebra S R] : Algebra S ℍ[R] :=
inferInstanceAs <| Algebra S ℍ[R,-1,-1]
-- Porting note: added shortcut
instance : Star ℍ[R] := QuaternionAlgebra.instStarQuaternionAlgebra
instance : StarRing ℍ[R] := QuaternionAlgebra.instStarRing
instance : IsStarNormal a := inferInstanceAs <| IsStarNormal (R := ℍ[R,-1,-1]) a
@[ext]
theorem ext : a.re = b.re → a.imI = b.imI → a.imJ = b.imJ → a.imK = b.imK → a = b :=
QuaternionAlgebra.ext a b
#align quaternion.ext Quaternion.ext
theorem ext_iff {a b : ℍ[R]} :
a = b ↔ a.re = b.re ∧ a.imI = b.imI ∧ a.imJ = b.imJ ∧ a.imK = b.imK :=
QuaternionAlgebra.ext_iff a b
#align quaternion.ext_iff Quaternion.ext_iff
/-- The imaginary part of a quaternion. -/
nonrec def im (x : ℍ[R]) : ℍ[R] := x.im
#align quaternion.im Quaternion.im
@[simp] theorem im_re : a.im.re = 0 := rfl
#align quaternion.im_re Quaternion.im_re
@[simp] theorem im_imI : a.im.imI = a.imI := rfl
#align quaternion.im_im_i Quaternion.im_imI
@[simp] theorem im_imJ : a.im.imJ = a.imJ := rfl
#align quaternion.im_im_j Quaternion.im_imJ
@[simp] theorem im_imK : a.im.imK = a.imK := rfl
#align quaternion.im_im_k Quaternion.im_imK
@[simp] theorem im_idem : a.im.im = a.im := rfl
#align quaternion.im_idem Quaternion.im_idem
@[simp] nonrec theorem re_add_im : ↑a.re + a.im = a := a.re_add_im
#align quaternion.re_add_im Quaternion.re_add_im
@[simp] nonrec theorem sub_self_im : a - a.im = a.re := a.sub_self_im
#align quaternion.sub_self_im Quaternion.sub_self_im
@[simp] nonrec theorem sub_self_re : a - ↑a.re = a.im := a.sub_self_re
#align quaternion.sub_self_re Quaternion.sub_self_re
@[simp, norm_cast]
theorem coe_re : (x : ℍ[R]).re = x := rfl
#align quaternion.coe_re Quaternion.coe_re
@[simp, norm_cast]
theorem coe_imI : (x : ℍ[R]).imI = 0 := rfl
#align quaternion.coe_im_i Quaternion.coe_imI
@[simp, norm_cast]
theorem coe_imJ : (x : ℍ[R]).imJ = 0 := rfl
#align quaternion.coe_im_j Quaternion.coe_imJ
@[simp, norm_cast]
theorem coe_imK : (x : ℍ[R]).imK = 0 := rfl
#align quaternion.coe_im_k Quaternion.coe_imK
@[simp, norm_cast]
theorem coe_im : (x : ℍ[R]).im = 0 := rfl
#align quaternion.coe_im Quaternion.coe_im
@[simp] theorem zero_re : (0 : ℍ[R]).re = 0 := rfl
#align quaternion.zero_re Quaternion.zero_re
@[simp] theorem zero_imI : (0 : ℍ[R]).imI = 0 := rfl
#align quaternion.zero_im_i Quaternion.zero_imI
@[simp] theorem zero_imJ : (0 : ℍ[R]).imJ = 0 := rfl
#align quaternion.zero_im_j Quaternion.zero_imJ
@[simp] theorem zero_imK : (0 : ℍ[R]).imK = 0 := rfl
#align quaternion.zero_im_k Quaternion.zero_imK
@[simp] theorem zero_im : (0 : ℍ[R]).im = 0 := rfl
#align quaternion.zero_im Quaternion.zero_im
@[simp, norm_cast]
theorem coe_zero : ((0 : R) : ℍ[R]) = 0 := rfl
#align quaternion.coe_zero Quaternion.coe_zero
@[simp] theorem one_re : (1 : ℍ[R]).re = 1 := rfl
#align quaternion.one_re Quaternion.one_re
@[simp] theorem one_imI : (1 : ℍ[R]).imI = 0 := rfl
#align quaternion.one_im_i Quaternion.one_imI
@[simp] theorem one_imJ : (1 : ℍ[R]).imJ = 0 := rfl
#align quaternion.one_im_j Quaternion.one_imJ
@[simp] theorem one_imK : (1 : ℍ[R]).imK = 0 := rfl
#align quaternion.one_im_k Quaternion.one_imK
@[simp] theorem one_im : (1 : ℍ[R]).im = 0 := rfl
#align quaternion.one_im Quaternion.one_im
@[simp, norm_cast]
theorem coe_one : ((1 : R) : ℍ[R]) = 1 := rfl
#align quaternion.coe_one Quaternion.coe_one
@[simp] theorem add_re : (a + b).re = a.re + b.re := rfl
#align quaternion.add_re Quaternion.add_re
@[simp] theorem add_imI : (a + b).imI = a.imI + b.imI := rfl
#align quaternion.add_im_i Quaternion.add_imI
@[simp] theorem add_imJ : (a + b).imJ = a.imJ + b.imJ := rfl
#align quaternion.add_im_j Quaternion.add_imJ
@[simp] theorem add_imK : (a + b).imK = a.imK + b.imK := rfl
#align quaternion.add_im_k Quaternion.add_imK
@[simp] nonrec theorem add_im : (a + b).im = a.im + b.im := a.add_im b
#align quaternion.add_im Quaternion.add_im
@[simp, norm_cast]
theorem coe_add : ((x + y : R) : ℍ[R]) = x + y :=
QuaternionAlgebra.coe_add x y
#align quaternion.coe_add Quaternion.coe_add
@[simp] theorem neg_re : (-a).re = -a.re := rfl
#align quaternion.neg_re Quaternion.neg_re
@[simp] theorem neg_imI : (-a).imI = -a.imI := rfl
#align quaternion.neg_im_i Quaternion.neg_imI
@[simp] theorem neg_imJ : (-a).imJ = -a.imJ := rfl
#align quaternion.neg_im_j Quaternion.neg_imJ
@[simp] theorem neg_imK : (-a).imK = -a.imK := rfl
#align quaternion.neg_im_k Quaternion.neg_imK
@[simp] nonrec theorem neg_im : (-a).im = -a.im := a.neg_im
#align quaternion.neg_im Quaternion.neg_im
@[simp, norm_cast]
theorem coe_neg : ((-x : R) : ℍ[R]) = -x :=
QuaternionAlgebra.coe_neg x
#align quaternion.coe_neg Quaternion.coe_neg
@[simp] theorem sub_re : (a - b).re = a.re - b.re := rfl
#align quaternion.sub_re Quaternion.sub_re
@[simp] theorem sub_imI : (a - b).imI = a.imI - b.imI := rfl
#align quaternion.sub_im_i Quaternion.sub_imI
@[simp] theorem sub_imJ : (a - b).imJ = a.imJ - b.imJ := rfl
#align quaternion.sub_im_j Quaternion.sub_imJ
@[simp] theorem sub_imK : (a - b).imK = a.imK - b.imK := rfl
#align quaternion.sub_im_k Quaternion.sub_imK
@[simp] nonrec theorem sub_im : (a - b).im = a.im - b.im := a.sub_im b
#align quaternion.sub_im Quaternion.sub_im
@[simp, norm_cast]
theorem coe_sub : ((x - y : R) : ℍ[R]) = x - y :=
QuaternionAlgebra.coe_sub x y
#align quaternion.coe_sub Quaternion.coe_sub
@[simp]
theorem mul_re : (a * b).re = a.re * b.re - a.imI * b.imI - a.imJ * b.imJ - a.imK * b.imK :=
(QuaternionAlgebra.mul_re a b).trans <| by simp only [one_mul, neg_mul, sub_eq_add_neg, neg_neg]
#align quaternion.mul_re Quaternion.mul_re
@[simp]
theorem mul_imI : (a * b).imI = a.re * b.imI + a.imI * b.re + a.imJ * b.imK - a.imK * b.imJ :=
(QuaternionAlgebra.mul_imI a b).trans <| by simp only [one_mul, neg_mul, sub_eq_add_neg, neg_neg]
#align quaternion.mul_im_i Quaternion.mul_imI
@[simp]
theorem mul_imJ : (a * b).imJ = a.re * b.imJ - a.imI * b.imK + a.imJ * b.re + a.imK * b.imI :=
(QuaternionAlgebra.mul_imJ a b).trans <| by simp only [one_mul, neg_mul, sub_eq_add_neg, neg_neg]
#align quaternion.mul_im_j Quaternion.mul_imJ
@[simp]
theorem mul_imK : (a * b).imK = a.re * b.imK + a.imI * b.imJ - a.imJ * b.imI + a.imK * b.re :=
(QuaternionAlgebra.mul_imK a b).trans <| by simp only [one_mul, neg_mul, sub_eq_add_neg, neg_neg]
#align quaternion.mul_im_k Quaternion.mul_imK
@[simp, norm_cast]
theorem coe_mul : ((x * y : R) : ℍ[R]) = x * y := QuaternionAlgebra.coe_mul x y
#align quaternion.coe_mul Quaternion.coe_mul
@[norm_cast, simp]
theorem coe_pow (n : ℕ) : (↑(x ^ n) : ℍ[R]) = (x : ℍ[R]) ^ n :=
QuaternionAlgebra.coe_pow x n
#align quaternion.coe_pow Quaternion.coe_pow
@[simp, norm_cast]
theorem natCast_re (n : ℕ) : (n : ℍ[R]).re = n := rfl
#align quaternion.nat_cast_re Quaternion.natCast_re
@[deprecated (since := "2024-04-17")]
alias nat_cast_re := natCast_re
@[simp, norm_cast]
theorem natCast_imI (n : ℕ) : (n : ℍ[R]).imI = 0 := rfl
#align quaternion.nat_cast_im_i Quaternion.natCast_imI
@[deprecated (since := "2024-04-17")]
alias nat_cast_imI := natCast_imI
@[simp, norm_cast]
theorem natCast_imJ (n : ℕ) : (n : ℍ[R]).imJ = 0 := rfl
#align quaternion.nat_cast_im_j Quaternion.natCast_imJ
@[deprecated (since := "2024-04-17")]
alias nat_cast_imJ := natCast_imJ
@[simp, norm_cast]
theorem natCast_imK (n : ℕ) : (n : ℍ[R]).imK = 0 := rfl
#align quaternion.nat_cast_im_k Quaternion.natCast_imK
@[deprecated (since := "2024-04-17")]
alias nat_cast_imK := natCast_imK
@[simp, norm_cast]
theorem natCast_im (n : ℕ) : (n : ℍ[R]).im = 0 := rfl
#align quaternion.nat_cast_im Quaternion.natCast_im
@[deprecated (since := "2024-04-17")]
alias nat_cast_im := natCast_im
@[norm_cast]
theorem coe_natCast (n : ℕ) : ↑(n : R) = (n : ℍ[R]) := rfl
#align quaternion.coe_nat_cast Quaternion.coe_natCast
@[deprecated (since := "2024-04-17")]
alias coe_nat_cast := coe_natCast
@[simp, norm_cast]
theorem intCast_re (z : ℤ) : (z : ℍ[R]).re = z := rfl
#align quaternion.int_cast_re Quaternion.intCast_re
@[deprecated (since := "2024-04-17")]
alias int_cast_re := intCast_re
@[simp, norm_cast]
theorem intCast_imI (z : ℤ) : (z : ℍ[R]).imI = 0 := rfl
#align quaternion.int_cast_im_i Quaternion.intCast_imI
@[deprecated (since := "2024-04-17")]
alias int_cast_imI := intCast_imI
@[simp, norm_cast]
theorem intCast_imJ (z : ℤ) : (z : ℍ[R]).imJ = 0 := rfl
#align quaternion.int_cast_im_j Quaternion.intCast_imJ
@[deprecated (since := "2024-04-17")]
alias int_cast_imJ := intCast_imJ
@[simp, norm_cast]
theorem intCast_imK (z : ℤ) : (z : ℍ[R]).imK = 0 := rfl
#align quaternion.int_cast_im_k Quaternion.intCast_imK
@[deprecated (since := "2024-04-17")]
alias int_cast_imK := intCast_imK
@[simp, norm_cast]
theorem intCast_im (z : ℤ) : (z : ℍ[R]).im = 0 := rfl
#align quaternion.int_cast_im Quaternion.intCast_im
@[deprecated (since := "2024-04-17")]
alias int_cast_im := intCast_im
@[norm_cast]
theorem coe_intCast (z : ℤ) : ↑(z : R) = (z : ℍ[R]) := rfl
#align quaternion.coe_int_cast Quaternion.coe_intCast
@[deprecated (since := "2024-04-17")]
alias coe_int_cast := coe_intCast
theorem coe_injective : Function.Injective (coe : R → ℍ[R]) :=
QuaternionAlgebra.coe_injective
#align quaternion.coe_injective Quaternion.coe_injective
@[simp]
theorem coe_inj {x y : R} : (x : ℍ[R]) = y ↔ x = y :=
coe_injective.eq_iff
#align quaternion.coe_inj Quaternion.coe_inj
@[simp]
theorem smul_re [SMul S R] (s : S) : (s • a).re = s • a.re :=
rfl
#align quaternion.smul_re Quaternion.smul_re
@[simp] theorem smul_imI [SMul S R] (s : S) : (s • a).imI = s • a.imI := rfl
#align quaternion.smul_im_i Quaternion.smul_imI
@[simp] theorem smul_imJ [SMul S R] (s : S) : (s • a).imJ = s • a.imJ := rfl
#align quaternion.smul_im_j Quaternion.smul_imJ
@[simp] theorem smul_imK [SMul S R] (s : S) : (s • a).imK = s • a.imK := rfl
#align quaternion.smul_im_k Quaternion.smul_imK
@[simp]
nonrec theorem smul_im [SMulZeroClass S R] (s : S) : (s • a).im = s • a.im :=
a.smul_im s
#align quaternion.smul_im Quaternion.smul_im
@[simp, norm_cast]
theorem coe_smul [SMulZeroClass S R] (s : S) (r : R) : (↑(s • r) : ℍ[R]) = s • (r : ℍ[R]) :=
QuaternionAlgebra.coe_smul _ _
#align quaternion.coe_smul Quaternion.coe_smul
theorem coe_commutes : ↑r * a = a * r :=
QuaternionAlgebra.coe_commutes r a
#align quaternion.coe_commutes Quaternion.coe_commutes
theorem coe_commute : Commute (↑r) a :=
QuaternionAlgebra.coe_commute r a
#align quaternion.coe_commute Quaternion.coe_commute
theorem coe_mul_eq_smul : ↑r * a = r • a :=
QuaternionAlgebra.coe_mul_eq_smul r a
#align quaternion.coe_mul_eq_smul Quaternion.coe_mul_eq_smul
theorem mul_coe_eq_smul : a * r = r • a :=
QuaternionAlgebra.mul_coe_eq_smul r a
#align quaternion.mul_coe_eq_smul Quaternion.mul_coe_eq_smul
@[simp]
theorem algebraMap_def : ⇑(algebraMap R ℍ[R]) = coe :=
rfl
#align quaternion.algebra_map_def Quaternion.algebraMap_def
theorem algebraMap_injective : (algebraMap R ℍ[R] : _ → _).Injective :=
QuaternionAlgebra.algebraMap_injective
theorem smul_coe : x • (y : ℍ[R]) = ↑(x * y) :=
QuaternionAlgebra.smul_coe x y
#align quaternion.smul_coe Quaternion.smul_coe
instance : Module.Finite R ℍ[R] := inferInstanceAs <| Module.Finite R ℍ[R,-1,-1]
instance : Module.Free R ℍ[R] := inferInstanceAs <| Module.Free R ℍ[R,-1,-1]
theorem rank_eq_four [StrongRankCondition R] : Module.rank R ℍ[R] = 4 :=
QuaternionAlgebra.rank_eq_four _ _
#align quaternion.rank_eq_four Quaternion.rank_eq_four
theorem finrank_eq_four [StrongRankCondition R] : FiniteDimensional.finrank R ℍ[R] = 4 :=
QuaternionAlgebra.finrank_eq_four _ _
#align quaternion.finrank_eq_four Quaternion.finrank_eq_four
@[simp] theorem star_re : (star a).re = a.re := rfl
#align quaternion.star_re Quaternion.star_re
@[simp] theorem star_imI : (star a).imI = -a.imI := rfl
#align quaternion.star_im_i Quaternion.star_imI
@[simp] theorem star_imJ : (star a).imJ = -a.imJ := rfl
#align quaternion.star_im_j Quaternion.star_imJ
@[simp] theorem star_imK : (star a).imK = -a.imK := rfl
#align quaternion.star_im_k Quaternion.star_imK
@[simp] theorem star_im : (star a).im = -a.im := a.im_star
#align quaternion.star_im Quaternion.star_im
nonrec theorem self_add_star' : a + star a = ↑(2 * a.re) :=
a.self_add_star'
#align quaternion.self_add_star' Quaternion.self_add_star'
nonrec theorem self_add_star : a + star a = 2 * a.re :=
a.self_add_star
#align quaternion.self_add_star Quaternion.self_add_star
nonrec theorem star_add_self' : star a + a = ↑(2 * a.re) :=
a.star_add_self'
#align quaternion.star_add_self' Quaternion.star_add_self'
nonrec theorem star_add_self : star a + a = 2 * a.re :=
a.star_add_self
#align quaternion.star_add_self Quaternion.star_add_self
nonrec theorem star_eq_two_re_sub : star a = ↑(2 * a.re) - a :=
a.star_eq_two_re_sub
#align quaternion.star_eq_two_re_sub Quaternion.star_eq_two_re_sub
@[simp, norm_cast]
theorem star_coe : star (x : ℍ[R]) = x :=
QuaternionAlgebra.star_coe x
#align quaternion.star_coe Quaternion.star_coe
@[simp]
theorem im_star : star a.im = -a.im :=
QuaternionAlgebra.im_star _
#align quaternion.im_star Quaternion.im_star
@[simp]
theorem star_smul [Monoid S] [DistribMulAction S R] (s : S) (a : ℍ[R]) :
star (s • a) = s • star a :=
QuaternionAlgebra.star_smul _ _
#align quaternion.star_smul Quaternion.star_smul
theorem eq_re_of_eq_coe {a : ℍ[R]} {x : R} (h : a = x) : a = a.re :=
QuaternionAlgebra.eq_re_of_eq_coe h
#align quaternion.eq_re_of_eq_coe Quaternion.eq_re_of_eq_coe
theorem eq_re_iff_mem_range_coe {a : ℍ[R]} : a = a.re ↔ a ∈ Set.range (coe : R → ℍ[R]) :=
QuaternionAlgebra.eq_re_iff_mem_range_coe
#align quaternion.eq_re_iff_mem_range_coe Quaternion.eq_re_iff_mem_range_coe
section CharZero
variable [NoZeroDivisors R] [CharZero R]
@[simp]
theorem star_eq_self {a : ℍ[R]} : star a = a ↔ a = a.re :=
QuaternionAlgebra.star_eq_self
#align quaternion.star_eq_self Quaternion.star_eq_self
@[simp]
theorem star_eq_neg {a : ℍ[R]} : star a = -a ↔ a.re = 0 :=
QuaternionAlgebra.star_eq_neg
#align quaternion.star_eq_neg Quaternion.star_eq_neg
end CharZero
nonrec theorem star_mul_eq_coe : star a * a = (star a * a).re :=
a.star_mul_eq_coe
#align quaternion.star_mul_eq_coe Quaternion.star_mul_eq_coe
nonrec theorem mul_star_eq_coe : a * star a = (a * star a).re :=
a.mul_star_eq_coe
#align quaternion.mul_star_eq_coe Quaternion.mul_star_eq_coe
open MulOpposite
/-- Quaternion conjugate as an `AlgEquiv` to the opposite ring. -/
def starAe : ℍ[R] ≃ₐ[R] ℍ[R]ᵐᵒᵖ :=
QuaternionAlgebra.starAe
#align quaternion.star_ae Quaternion.starAe
@[simp]
theorem coe_starAe : ⇑(starAe : ℍ[R] ≃ₐ[R] ℍ[R]ᵐᵒᵖ) = op ∘ star :=
rfl
#align quaternion.coe_star_ae Quaternion.coe_starAe
/-- Square of the norm. -/
def normSq : ℍ[R] →*₀ R where
toFun a := (a * star a).re
map_zero' := by simp only [star_zero, zero_mul, zero_re]
map_one' := by simp only [star_one, one_mul, one_re]
map_mul' x y := coe_injective <| by
conv_lhs => rw [← mul_star_eq_coe, star_mul, mul_assoc, ← mul_assoc y, y.mul_star_eq_coe,
coe_commutes, ← mul_assoc, x.mul_star_eq_coe, ← coe_mul]
#align quaternion.norm_sq Quaternion.normSq
theorem normSq_def : normSq a = (a * star a).re := rfl
#align quaternion.norm_sq_def Quaternion.normSq_def
theorem normSq_def' : normSq a = a.1 ^ 2 + a.2 ^ 2 + a.3 ^ 2 + a.4 ^ 2 := by
simp only [normSq_def, sq, mul_neg, sub_neg_eq_add, mul_re, star_re, star_imI, star_imJ,
star_imK]
#align quaternion.norm_sq_def' Quaternion.normSq_def'
| Mathlib/Algebra/Quaternion.lean | 1,309 | 1,310 | theorem normSq_coe : normSq (x : ℍ[R]) = x ^ 2 := by |
rw [normSq_def, star_coe, ← coe_mul, coe_re, sq]
|
/-
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.Separation
import Mathlib.Topology.Sets.Opens
#align_import topology.alexandroff from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988"
/-!
# 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, 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 : Type*}
/-- The OnePoint extension of an arbitrary topological space `X` -/
def OnePoint (X : Type*) :=
Option X
#align alexandroff OnePoint
/-- 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
#align alexandroff.infty OnePoint.infty
@[inherit_doc]
scoped notation "∞" => OnePoint.infty
/-- Coercion from `X` to `OnePoint X`. -/
@[coe, match_pattern] def some : X → OnePoint X := Option.some
instance : CoeTC X (OnePoint X) := ⟨some⟩
instance : Inhabited (OnePoint X) := ⟨∞⟩
instance [Fintype X] : Fintype (OnePoint X) :=
inferInstanceAs (Fintype (Option X))
instance infinite [Infinite X] : Infinite (OnePoint X) :=
inferInstanceAs (Infinite (Option X))
#align alexandroff.infinite OnePoint.infinite
theorem coe_injective : Function.Injective ((↑) : X → OnePoint X) :=
Option.some_injective X
#align alexandroff.coe_injective OnePoint.coe_injective
@[norm_cast]
theorem coe_eq_coe {x y : X} : (x : OnePoint X) = y ↔ x = y :=
coe_injective.eq_iff
#align alexandroff.coe_eq_coe OnePoint.coe_eq_coe
@[simp]
theorem coe_ne_infty (x : X) : (x : OnePoint X) ≠ ∞ :=
nofun
#align alexandroff.coe_ne_infty OnePoint.coe_ne_infty
@[simp]
theorem infty_ne_coe (x : X) : ∞ ≠ (x : OnePoint X) :=
nofun
#align alexandroff.infty_ne_coe OnePoint.infty_ne_coe
/-- Recursor for `OnePoint` using the preferred forms `∞` and `↑x`. -/
@[elab_as_elim]
protected def rec {C : OnePoint X → Sort*} (h₁ : C ∞) (h₂ : ∀ x : X, C x) :
∀ z : OnePoint X, C z
| ∞ => h₁
| (x : X) => h₂ x
#align alexandroff.rec OnePoint.rec
theorem isCompl_range_coe_infty : IsCompl (range ((↑) : X → OnePoint X)) {∞} :=
isCompl_range_some_none X
#align alexandroff.is_compl_range_coe_infty OnePoint.isCompl_range_coe_infty
-- Porting note: moved @[simp] to a new lemma
theorem range_coe_union_infty : range ((↑) : X → OnePoint X) ∪ {∞} = univ :=
range_some_union_none X
#align alexandroff.range_coe_union_infty OnePoint.range_coe_union_infty
@[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
#align alexandroff.range_coe_inter_infty OnePoint.range_coe_inter_infty
@[simp]
theorem compl_range_coe : (range ((↑) : X → OnePoint X))ᶜ = {∞} :=
compl_range_some X
#align alexandroff.compl_range_coe OnePoint.compl_range_coe
theorem compl_infty : ({∞}ᶜ : Set (OnePoint X)) = range ((↑) : X → OnePoint X) :=
(@isCompl_range_coe_infty X).symm.compl_eq
#align alexandroff.compl_infty OnePoint.compl_infty
theorem compl_image_coe (s : Set X) : ((↑) '' s : Set (OnePoint X))ᶜ = (↑) '' sᶜ ∪ {∞} := by
rw [coe_injective.compl_image_eq, compl_range_coe]
#align alexandroff.compl_image_coe OnePoint.compl_image_coe
theorem ne_infty_iff_exists {x : OnePoint X} : x ≠ ∞ ↔ ∃ y : X, (y : OnePoint X) = x := by
induction x using OnePoint.rec <;> simp
#align alexandroff.ne_infty_iff_exists OnePoint.ne_infty_iff_exists
instance canLift : CanLift (OnePoint X) X (↑) fun x => x ≠ ∞ :=
WithTop.canLift
#align alexandroff.can_lift OnePoint.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]
#align alexandroff.not_mem_range_coe_iff OnePoint.not_mem_range_coe_iff
theorem infty_not_mem_range_coe : ∞ ∉ range ((↑) : X → OnePoint X) :=
not_mem_range_coe_iff.2 rfl
#align alexandroff.infty_not_mem_range_coe OnePoint.infty_not_mem_range_coe
theorem infty_not_mem_image_coe {s : Set X} : ∞ ∉ ((↑) : X → OnePoint X) '' s :=
not_mem_subset (image_subset_range _ _) infty_not_mem_range_coe
#align alexandroff.infty_not_mem_image_coe OnePoint.infty_not_mem_image_coe
@[simp]
theorem coe_preimage_infty : ((↑) : X → OnePoint X) ⁻¹' {∞} = ∅ := by
ext
simp
#align alexandroff.coe_preimage_infty OnePoint.coe_preimage_infty
/-!
### 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)} {t : Set X}
theorem isOpen_def :
IsOpen s ↔ (∞ ∈ s → IsCompact ((↑) ⁻¹' s : Set X)ᶜ) ∧ IsOpen ((↑) ⁻¹' s : Set X) :=
Iff.rfl
#align alexandroff.is_open_def OnePoint.isOpen_def
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]
#align alexandroff.is_open_iff_of_mem' OnePoint.isOpen_iff_of_mem'
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]
#align alexandroff.is_open_iff_of_mem OnePoint.isOpen_iff_of_mem
theorem isOpen_iff_of_not_mem (h : ∞ ∉ s) : IsOpen s ↔ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
#align alexandroff.is_open_iff_of_not_mem OnePoint.isOpen_iff_of_not_mem
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]
#align alexandroff.is_closed_iff_of_mem OnePoint.isClosed_iff_of_mem
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]
#align alexandroff.is_closed_iff_of_not_mem OnePoint.isClosed_iff_of_not_mem
@[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]
#align alexandroff.is_open_image_coe OnePoint.isOpen_image_coe
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
#align alexandroff.is_open_compl_image_coe OnePoint.isOpen_compl_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]
#align alexandroff.is_closed_image_coe OnePoint.isClosed_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⟩⟩
#align alexandroff.opens_of_compl OnePoint.opensOfCompl
theorem infty_mem_opensOfCompl {s : Set X} (h₁ : IsClosed s) (h₂ : IsCompact s) :
∞ ∈ opensOfCompl s h₁ h₂ :=
mem_compl infty_not_mem_image_coe
#align alexandroff.infty_mem_opens_of_compl OnePoint.infty_mem_opensOfCompl
@[continuity]
theorem continuous_coe : Continuous ((↑) : X → OnePoint X) :=
continuous_def.mpr fun _s hs => hs.right
#align alexandroff.continuous_coe OnePoint.continuous_coe
theorem isOpenMap_coe : IsOpenMap ((↑) : X → OnePoint X) := fun _ => isOpen_image_coe.2
#align alexandroff.is_open_map_coe OnePoint.isOpenMap_coe
theorem openEmbedding_coe : OpenEmbedding ((↑) : X → OnePoint X) :=
openEmbedding_of_continuous_injective_open continuous_coe coe_injective isOpenMap_coe
#align alexandroff.open_embedding_coe OnePoint.openEmbedding_coe
theorem isOpen_range_coe : IsOpen (range ((↑) : X → OnePoint X)) :=
openEmbedding_coe.isOpen_range
#align alexandroff.is_open_range_coe OnePoint.isOpen_range_coe
theorem isClosed_infty : IsClosed ({∞} : Set (OnePoint X)) := by
rw [← compl_range_coe, isClosed_compl_iff]
exact isOpen_range_coe
#align alexandroff.is_closed_infty OnePoint.isClosed_infty
theorem nhds_coe_eq (x : X) : 𝓝 ↑x = map ((↑) : X → OnePoint X) (𝓝 x) :=
(openEmbedding_coe.map_nhds_eq x).symm
#align alexandroff.nhds_coe_eq OnePoint.nhds_coe_eq
theorem nhdsWithin_coe_image (s : Set X) (x : X) :
𝓝[(↑) '' s] (x : OnePoint X) = map (↑) (𝓝[s] x) :=
(openEmbedding_coe.toEmbedding.map_nhdsWithin_eq _ _).symm
#align alexandroff.nhds_within_coe_image OnePoint.nhdsWithin_coe_image
theorem nhdsWithin_coe (s : Set (OnePoint X)) (x : X) : 𝓝[s] ↑x = map (↑) (𝓝[(↑) ⁻¹' s] x) :=
(openEmbedding_coe.map_nhdsWithin_preimage_eq _ _).symm
#align alexandroff.nhds_within_coe OnePoint.nhdsWithin_coe
theorem comap_coe_nhds (x : X) : comap ((↑) : X → OnePoint X) (𝓝 x) = 𝓝 x :=
(openEmbedding_coe.toInducing.nhds_eq_comap x).symm
#align alexandroff.comap_coe_nhds OnePoint.comap_coe_nhds
/-- If `x` is not an isolated point of `X`, then `x : OnePoint X` is not an isolated point
of `OnePoint X`. -/
instance nhdsWithin_compl_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
#align alexandroff.nhds_within_compl_coe_ne_bot OnePoint.nhdsWithin_compl_coe_neBot
theorem nhdsWithin_compl_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]
#align alexandroff.nhds_within_compl_infty_eq OnePoint.nhdsWithin_compl_infty_eq
/-- If `X` is a non-compact space, then `∞` is not an isolated point of `OnePoint X`. -/
instance nhdsWithin_compl_infty_neBot [NoncompactSpace X] : NeBot (𝓝[≠] (∞ : OnePoint X)) := by
rw [nhdsWithin_compl_infty_eq]
infer_instance
#align alexandroff.nhds_within_compl_infty_ne_bot OnePoint.nhdsWithin_compl_infty_neBot
instance (priority := 900) nhdsWithin_compl_neBot [∀ x : X, NeBot (𝓝[≠] x)] [NoncompactSpace X]
(x : OnePoint X) : NeBot (𝓝[≠] x) :=
OnePoint.rec OnePoint.nhdsWithin_compl_infty_neBot
(fun y => OnePoint.nhdsWithin_compl_coe_neBot y) x
#align alexandroff.nhds_within_compl_ne_bot OnePoint.nhdsWithin_compl_neBot
theorem nhds_infty_eq : 𝓝 (∞ : OnePoint X) = map (↑) (coclosedCompact X) ⊔ pure ∞ := by
rw [← nhdsWithin_compl_infty_eq, nhdsWithin_compl_singleton_sup_pure]
#align alexandroff.nhds_infty_eq OnePoint.nhds_infty_eq
| Mathlib/Topology/Compactification/OnePoint.lean | 334 | 338 | 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 _
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Kevin Buzzard, Yury Kudryashov, Frédéric Dupuis,
Heather Macbeth
-/
import Mathlib.Algebra.Module.Submodule.EqLocus
import Mathlib.Algebra.Module.Submodule.RestrictScalars
import Mathlib.Algebra.Ring.Idempotents
import Mathlib.Data.Set.Pointwise.SMul
import Mathlib.LinearAlgebra.Basic
import Mathlib.Order.CompactlyGenerated.Basic
import Mathlib.Order.OmegaCompletePartialOrder
#align_import linear_algebra.span from "leanprover-community/mathlib"@"10878f6bf1dab863445907ab23fbfcefcb5845d0"
/-!
# The span of a set of vectors, as a submodule
* `Submodule.span s` is defined to be the smallest submodule containing the set `s`.
## Notations
* We introduce the notation `R ∙ v` for the span of a singleton, `Submodule.span R {v}`. This is
`\span`, not the same as the scalar multiplication `•`/`\bub`.
-/
variable {R R₂ K M M₂ V S : Type*}
namespace Submodule
open Function Set
open Pointwise
section AddCommMonoid
variable [Semiring R] [AddCommMonoid M] [Module R M]
variable {x : M} (p p' : Submodule R M)
variable [Semiring R₂] {σ₁₂ : R →+* R₂}
variable [AddCommMonoid M₂] [Module R₂ M₂]
variable {F : Type*} [FunLike F M M₂] [SemilinearMapClass F σ₁₂ M M₂]
section
variable (R)
/-- The span of a set `s ⊆ M` is the smallest submodule of M that contains `s`. -/
def span (s : Set M) : Submodule R M :=
sInf { p | s ⊆ p }
#align submodule.span Submodule.span
variable {R}
-- Porting note: renamed field to `principal'` and added `principal` to fix explicit argument
/-- An `R`-submodule of `M` is principal if it is generated by one element. -/
@[mk_iff]
class IsPrincipal (S : Submodule R M) : Prop where
principal' : ∃ a, S = span R {a}
#align submodule.is_principal Submodule.IsPrincipal
theorem IsPrincipal.principal (S : Submodule R M) [S.IsPrincipal] :
∃ a, S = span R {a} :=
Submodule.IsPrincipal.principal'
#align submodule.is_principal.principal Submodule.IsPrincipal.principal
end
variable {s t : Set M}
theorem mem_span : x ∈ span R s ↔ ∀ p : Submodule R M, s ⊆ p → x ∈ p :=
mem_iInter₂
#align submodule.mem_span Submodule.mem_span
@[aesop safe 20 apply (rule_sets := [SetLike])]
theorem subset_span : s ⊆ span R s := fun _ h => mem_span.2 fun _ hp => hp h
#align submodule.subset_span Submodule.subset_span
theorem span_le {p} : span R s ≤ p ↔ s ⊆ p :=
⟨Subset.trans subset_span, fun ss _ h => mem_span.1 h _ ss⟩
#align submodule.span_le Submodule.span_le
theorem span_mono (h : s ⊆ t) : span R s ≤ span R t :=
span_le.2 <| Subset.trans h subset_span
#align submodule.span_mono Submodule.span_mono
theorem span_monotone : Monotone (span R : Set M → Submodule R M) := fun _ _ => span_mono
#align submodule.span_monotone Submodule.span_monotone
theorem span_eq_of_le (h₁ : s ⊆ p) (h₂ : p ≤ span R s) : span R s = p :=
le_antisymm (span_le.2 h₁) h₂
#align submodule.span_eq_of_le Submodule.span_eq_of_le
theorem span_eq : span R (p : Set M) = p :=
span_eq_of_le _ (Subset.refl _) subset_span
#align submodule.span_eq Submodule.span_eq
theorem span_eq_span (hs : s ⊆ span R t) (ht : t ⊆ span R s) : span R s = span R t :=
le_antisymm (span_le.2 hs) (span_le.2 ht)
#align submodule.span_eq_span Submodule.span_eq_span
/-- A version of `Submodule.span_eq` for subobjects closed under addition and scalar multiplication
and containing zero. In general, this should not be used directly, but can be used to quickly
generate proofs for specific types of subobjects. -/
lemma coe_span_eq_self [SetLike S M] [AddSubmonoidClass S M] [SMulMemClass S R M] (s : S) :
(span R (s : Set M) : Set M) = s := by
refine le_antisymm ?_ subset_span
let s' : Submodule R M :=
{ carrier := s
add_mem' := add_mem
zero_mem' := zero_mem _
smul_mem' := SMulMemClass.smul_mem }
exact span_le (p := s') |>.mpr le_rfl
/-- A version of `Submodule.span_eq` for when the span is by a smaller ring. -/
@[simp]
theorem span_coe_eq_restrictScalars [Semiring S] [SMul S R] [Module S M] [IsScalarTower S R M] :
span S (p : Set M) = p.restrictScalars S :=
span_eq (p.restrictScalars S)
#align submodule.span_coe_eq_restrict_scalars Submodule.span_coe_eq_restrictScalars
/-- A version of `Submodule.map_span_le` that does not require the `RingHomSurjective`
assumption. -/
theorem image_span_subset (f : F) (s : Set M) (N : Submodule R₂ M₂) :
f '' span R s ⊆ N ↔ ∀ m ∈ s, f m ∈ N := image_subset_iff.trans <| span_le (p := N.comap f)
theorem image_span_subset_span (f : F) (s : Set M) : f '' span R s ⊆ span R₂ (f '' s) :=
(image_span_subset f s _).2 fun x hx ↦ subset_span ⟨x, hx, rfl⟩
theorem map_span [RingHomSurjective σ₁₂] (f : F) (s : Set M) :
(span R s).map f = span R₂ (f '' s) :=
Eq.symm <| span_eq_of_le _ (Set.image_subset f subset_span) (image_span_subset_span f s)
#align submodule.map_span Submodule.map_span
alias _root_.LinearMap.map_span := Submodule.map_span
#align linear_map.map_span LinearMap.map_span
theorem map_span_le [RingHomSurjective σ₁₂] (f : F) (s : Set M) (N : Submodule R₂ M₂) :
map f (span R s) ≤ N ↔ ∀ m ∈ s, f m ∈ N := image_span_subset f s N
#align submodule.map_span_le Submodule.map_span_le
alias _root_.LinearMap.map_span_le := Submodule.map_span_le
#align linear_map.map_span_le LinearMap.map_span_le
@[simp]
theorem span_insert_zero : span R (insert (0 : M) s) = span R s := by
refine le_antisymm ?_ (Submodule.span_mono (Set.subset_insert 0 s))
rw [span_le, Set.insert_subset_iff]
exact ⟨by simp only [SetLike.mem_coe, Submodule.zero_mem], Submodule.subset_span⟩
#align submodule.span_insert_zero Submodule.span_insert_zero
-- See also `span_preimage_eq` below.
theorem span_preimage_le (f : F) (s : Set M₂) :
span R (f ⁻¹' s) ≤ (span R₂ s).comap f := by
rw [span_le, comap_coe]
exact preimage_mono subset_span
#align submodule.span_preimage_le Submodule.span_preimage_le
alias _root_.LinearMap.span_preimage_le := Submodule.span_preimage_le
#align linear_map.span_preimage_le LinearMap.span_preimage_le
theorem closure_subset_span {s : Set M} : (AddSubmonoid.closure s : Set M) ⊆ span R s :=
(@AddSubmonoid.closure_le _ _ _ (span R s).toAddSubmonoid).mpr subset_span
#align submodule.closure_subset_span Submodule.closure_subset_span
theorem closure_le_toAddSubmonoid_span {s : Set M} :
AddSubmonoid.closure s ≤ (span R s).toAddSubmonoid :=
closure_subset_span
#align submodule.closure_le_to_add_submonoid_span Submodule.closure_le_toAddSubmonoid_span
@[simp]
theorem span_closure {s : Set M} : span R (AddSubmonoid.closure s : Set M) = span R s :=
le_antisymm (span_le.mpr closure_subset_span) (span_mono AddSubmonoid.subset_closure)
#align submodule.span_closure Submodule.span_closure
/-- An induction principle for span membership. If `p` holds for 0 and all elements of `s`, and is
preserved under addition and scalar multiplication, then `p` holds for all elements of the span of
`s`. -/
@[elab_as_elim]
theorem span_induction {p : M → Prop} (h : x ∈ span R s) (mem : ∀ x ∈ s, p x) (zero : p 0)
(add : ∀ x y, p x → p y → p (x + y)) (smul : ∀ (a : R) (x), p x → p (a • x)) : p x :=
((@span_le (p := ⟨⟨⟨p, by intros x y; exact add x y⟩, zero⟩, smul⟩)) s).2 mem h
#align submodule.span_induction Submodule.span_induction
/-- An induction principle for span membership. This is a version of `Submodule.span_induction`
for binary predicates. -/
theorem span_induction₂ {p : M → M → Prop} {a b : M} (ha : a ∈ Submodule.span R s)
(hb : b ∈ Submodule.span R s) (mem_mem : ∀ x ∈ s, ∀ y ∈ s, p x y)
(zero_left : ∀ y, p 0 y) (zero_right : ∀ x, p x 0)
(add_left : ∀ x₁ x₂ y, p x₁ y → p x₂ y → p (x₁ + x₂) y)
(add_right : ∀ x y₁ y₂, p x y₁ → p x y₂ → p x (y₁ + y₂))
(smul_left : ∀ (r : R) x y, p x y → p (r • x) y)
(smul_right : ∀ (r : R) x y, p x y → p x (r • y)) : p a b :=
Submodule.span_induction ha
(fun x hx => Submodule.span_induction hb (mem_mem x hx) (zero_right x) (add_right x) fun r =>
smul_right r x)
(zero_left b) (fun x₁ x₂ => add_left x₁ x₂ b) fun r x => smul_left r x b
/-- A dependent version of `Submodule.span_induction`. -/
@[elab_as_elim]
theorem span_induction' {p : ∀ x, x ∈ span R s → Prop}
(mem : ∀ (x) (h : x ∈ s), p x (subset_span h))
(zero : p 0 (Submodule.zero_mem _))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›))
(smul : ∀ (a : R) (x hx), p x hx → p (a • x) (Submodule.smul_mem _ _ ‹_›)) {x}
(hx : x ∈ span R s) : p x hx := by
refine Exists.elim ?_ fun (hx : x ∈ span R s) (hc : p x hx) => hc
refine
span_induction hx (fun m hm => ⟨subset_span hm, mem m hm⟩) ⟨zero_mem _, zero⟩
(fun x y hx hy =>
Exists.elim hx fun hx' hx =>
Exists.elim hy fun hy' hy => ⟨add_mem hx' hy', add _ _ _ _ hx hy⟩)
fun r x hx => Exists.elim hx fun hx' hx => ⟨smul_mem _ _ hx', smul r _ _ hx⟩
#align submodule.span_induction' Submodule.span_induction'
open AddSubmonoid in
theorem span_eq_closure {s : Set M} : (span R s).toAddSubmonoid = closure (@univ R • s) := by
refine le_antisymm
(fun x hx ↦ span_induction hx (fun x hx ↦ subset_closure ⟨1, trivial, x, hx, one_smul R x⟩)
(zero_mem _) (fun _ _ ↦ add_mem) fun r m hm ↦ closure_induction hm ?_ ?_ fun _ _ h h' ↦ ?_)
(closure_le.2 ?_)
· rintro _ ⟨r, -, m, hm, rfl⟩; exact smul_mem _ _ (subset_span hm)
· rintro _ ⟨r', -, m, hm, rfl⟩; exact subset_closure ⟨r * r', trivial, m, hm, mul_smul r r' m⟩
· rw [smul_zero]; apply zero_mem
· rw [smul_add]; exact add_mem h h'
/-- A variant of `span_induction` that combines `∀ x ∈ s, p x` and `∀ r x, p x → p (r • x)`
into a single condition `∀ r, ∀ x ∈ s, p (r • x)`, which can be easier to verify. -/
@[elab_as_elim]
theorem closure_induction {p : M → Prop} (h : x ∈ span R s) (zero : p 0)
(add : ∀ x y, p x → p y → p (x + y)) (smul_mem : ∀ r : R, ∀ x ∈ s, p (r • x)) : p x := by
rw [← mem_toAddSubmonoid, span_eq_closure] at h
refine AddSubmonoid.closure_induction h ?_ zero add
rintro _ ⟨r, -, m, hm, rfl⟩
exact smul_mem r m hm
/-- A dependent version of `Submodule.closure_induction`. -/
@[elab_as_elim]
theorem closure_induction' {p : ∀ x, x ∈ span R s → Prop}
(zero : p 0 (Submodule.zero_mem _))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›))
(smul_mem : ∀ (r x) (h : x ∈ s), p (r • x) (Submodule.smul_mem _ _ <| subset_span h)) {x}
(hx : x ∈ span R s) : p x hx := by
refine Exists.elim ?_ fun (hx : x ∈ span R s) (hc : p x hx) ↦ hc
refine closure_induction hx ⟨zero_mem _, zero⟩
(fun x y hx hy ↦ Exists.elim hx fun hx' hx ↦
Exists.elim hy fun hy' hy ↦ ⟨add_mem hx' hy', add _ _ _ _ hx hy⟩)
fun r x hx ↦ ⟨Submodule.smul_mem _ _ (subset_span hx), smul_mem r x hx⟩
@[simp]
theorem span_span_coe_preimage : span R (((↑) : span R s → M) ⁻¹' s) = ⊤ :=
eq_top_iff.2 fun x ↦ Subtype.recOn x fun x hx _ ↦ by
refine span_induction' (p := fun x hx ↦ (⟨x, hx⟩ : span R s) ∈ span R (Subtype.val ⁻¹' s))
(fun x' hx' ↦ subset_span hx') ?_ (fun x _ y _ ↦ ?_) (fun r x _ ↦ ?_) hx
· exact zero_mem _
· exact add_mem
· exact smul_mem _ _
#align submodule.span_span_coe_preimage Submodule.span_span_coe_preimage
@[simp]
lemma span_setOf_mem_eq_top :
span R {x : span R s | (x : M) ∈ s} = ⊤ :=
span_span_coe_preimage
theorem span_nat_eq_addSubmonoid_closure (s : Set M) :
(span ℕ s).toAddSubmonoid = AddSubmonoid.closure s := by
refine Eq.symm (AddSubmonoid.closure_eq_of_le subset_span ?_)
apply (OrderIso.to_galoisConnection (AddSubmonoid.toNatSubmodule (M := M)).symm).l_le
(a := span ℕ s) (b := AddSubmonoid.closure s)
rw [span_le]
exact AddSubmonoid.subset_closure
#align submodule.span_nat_eq_add_submonoid_closure Submodule.span_nat_eq_addSubmonoid_closure
@[simp]
theorem span_nat_eq (s : AddSubmonoid M) : (span ℕ (s : Set M)).toAddSubmonoid = s := by
rw [span_nat_eq_addSubmonoid_closure, s.closure_eq]
#align submodule.span_nat_eq Submodule.span_nat_eq
theorem span_int_eq_addSubgroup_closure {M : Type*} [AddCommGroup M] (s : Set M) :
(span ℤ s).toAddSubgroup = AddSubgroup.closure s :=
Eq.symm <|
AddSubgroup.closure_eq_of_le _ subset_span fun x hx =>
span_induction hx (fun x hx => AddSubgroup.subset_closure hx) (AddSubgroup.zero_mem _)
(fun _ _ => AddSubgroup.add_mem _) fun _ _ _ => AddSubgroup.zsmul_mem _ ‹_› _
#align submodule.span_int_eq_add_subgroup_closure Submodule.span_int_eq_addSubgroup_closure
@[simp]
theorem span_int_eq {M : Type*} [AddCommGroup M] (s : AddSubgroup M) :
(span ℤ (s : Set M)).toAddSubgroup = s := by rw [span_int_eq_addSubgroup_closure, s.closure_eq]
#align submodule.span_int_eq Submodule.span_int_eq
section
variable (R M)
/-- `span` forms a Galois insertion with the coercion from submodule to set. -/
protected def gi : GaloisInsertion (@span R M _ _ _) (↑) where
choice s _ := span R s
gc _ _ := span_le
le_l_u _ := subset_span
choice_eq _ _ := rfl
#align submodule.gi Submodule.gi
end
@[simp]
theorem span_empty : span R (∅ : Set M) = ⊥ :=
(Submodule.gi R M).gc.l_bot
#align submodule.span_empty Submodule.span_empty
@[simp]
theorem span_univ : span R (univ : Set M) = ⊤ :=
eq_top_iff.2 <| SetLike.le_def.2 <| subset_span
#align submodule.span_univ Submodule.span_univ
theorem span_union (s t : Set M) : span R (s ∪ t) = span R s ⊔ span R t :=
(Submodule.gi R M).gc.l_sup
#align submodule.span_union Submodule.span_union
theorem span_iUnion {ι} (s : ι → Set M) : span R (⋃ i, s i) = ⨆ i, span R (s i) :=
(Submodule.gi R M).gc.l_iSup
#align submodule.span_Union Submodule.span_iUnion
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem span_iUnion₂ {ι} {κ : ι → Sort*} (s : ∀ i, κ i → Set M) :
span R (⋃ (i) (j), s i j) = ⨆ (i) (j), span R (s i j) :=
(Submodule.gi R M).gc.l_iSup₂
#align submodule.span_Union₂ Submodule.span_iUnion₂
theorem span_attach_biUnion [DecidableEq M] {α : Type*} (s : Finset α) (f : s → Finset M) :
span R (s.attach.biUnion f : Set M) = ⨆ x, span R (f x) := by simp [span_iUnion]
#align submodule.span_attach_bUnion Submodule.span_attach_biUnion
theorem sup_span : p ⊔ span R s = span R (p ∪ s) := by rw [Submodule.span_union, p.span_eq]
#align submodule.sup_span Submodule.sup_span
theorem span_sup : span R s ⊔ p = span R (s ∪ p) := by rw [Submodule.span_union, p.span_eq]
#align submodule.span_sup Submodule.span_sup
notation:1000
/- Note that the character `∙` U+2219 used below is different from the scalar multiplication
character `•` U+2022. -/
R " ∙ " x => span R (singleton x)
theorem span_eq_iSup_of_singleton_spans (s : Set M) : span R s = ⨆ x ∈ s, R ∙ x := by
simp only [← span_iUnion, Set.biUnion_of_singleton s]
#align submodule.span_eq_supr_of_singleton_spans Submodule.span_eq_iSup_of_singleton_spans
theorem span_range_eq_iSup {ι : Sort*} {v : ι → M} : span R (range v) = ⨆ i, R ∙ v i := by
rw [span_eq_iSup_of_singleton_spans, iSup_range]
#align submodule.span_range_eq_supr Submodule.span_range_eq_iSup
theorem span_smul_le (s : Set M) (r : R) : span R (r • s) ≤ span R s := by
rw [span_le]
rintro _ ⟨x, hx, rfl⟩
exact smul_mem (span R s) r (subset_span hx)
#align submodule.span_smul_le Submodule.span_smul_le
theorem subset_span_trans {U V W : Set M} (hUV : U ⊆ Submodule.span R V)
(hVW : V ⊆ Submodule.span R W) : U ⊆ Submodule.span R W :=
(Submodule.gi R M).gc.le_u_l_trans hUV hVW
#align submodule.subset_span_trans Submodule.subset_span_trans
/-- See `Submodule.span_smul_eq` (in `RingTheory.Ideal.Operations`) for
`span R (r • s) = r • span R s` that holds for arbitrary `r` in a `CommSemiring`. -/
theorem span_smul_eq_of_isUnit (s : Set M) (r : R) (hr : IsUnit r) : span R (r • s) = span R s := by
apply le_antisymm
· apply span_smul_le
· convert span_smul_le (r • s) ((hr.unit⁻¹ : _) : R)
rw [smul_smul]
erw [hr.unit.inv_val]
rw [one_smul]
#align submodule.span_smul_eq_of_is_unit Submodule.span_smul_eq_of_isUnit
@[simp]
theorem coe_iSup_of_directed {ι} [Nonempty ι] (S : ι → Submodule R M)
(H : Directed (· ≤ ·) S) : ((iSup S: Submodule R M) : Set M) = ⋃ i, S i :=
let s : Submodule R M :=
{ __ := AddSubmonoid.copy _ _ (AddSubmonoid.coe_iSup_of_directed H).symm
smul_mem' := fun r _ hx ↦ have ⟨i, hi⟩ := Set.mem_iUnion.mp hx
Set.mem_iUnion.mpr ⟨i, (S i).smul_mem' r hi⟩ }
have : iSup S = s := le_antisymm
(iSup_le fun i ↦ le_iSup (fun i ↦ (S i : Set M)) i) (Set.iUnion_subset fun _ ↦ le_iSup S _)
this.symm ▸ rfl
#align submodule.coe_supr_of_directed Submodule.coe_iSup_of_directed
@[simp]
theorem mem_iSup_of_directed {ι} [Nonempty ι] (S : ι → Submodule R M) (H : Directed (· ≤ ·) S) {x} :
x ∈ iSup S ↔ ∃ i, x ∈ S i := by
rw [← SetLike.mem_coe, coe_iSup_of_directed S H, mem_iUnion]
rfl
#align submodule.mem_supr_of_directed Submodule.mem_iSup_of_directed
theorem mem_sSup_of_directed {s : Set (Submodule R M)} {z} (hs : s.Nonempty)
(hdir : DirectedOn (· ≤ ·) s) : z ∈ sSup s ↔ ∃ y ∈ s, z ∈ y := by
have : Nonempty s := hs.to_subtype
simp only [sSup_eq_iSup', mem_iSup_of_directed _ hdir.directed_val, SetCoe.exists, Subtype.coe_mk,
exists_prop]
#align submodule.mem_Sup_of_directed Submodule.mem_sSup_of_directed
@[norm_cast, simp]
theorem coe_iSup_of_chain (a : ℕ →o Submodule R M) : (↑(⨆ k, a k) : Set M) = ⋃ k, (a k : Set M) :=
coe_iSup_of_directed a a.monotone.directed_le
#align submodule.coe_supr_of_chain Submodule.coe_iSup_of_chain
/-- We can regard `coe_iSup_of_chain` as the statement that `(↑) : (Submodule R M) → Set M` is
Scott continuous for the ω-complete partial order induced by the complete lattice structures. -/
theorem coe_scott_continuous :
OmegaCompletePartialOrder.Continuous' ((↑) : Submodule R M → Set M) :=
⟨SetLike.coe_mono, coe_iSup_of_chain⟩
#align submodule.coe_scott_continuous Submodule.coe_scott_continuous
@[simp]
theorem mem_iSup_of_chain (a : ℕ →o Submodule R M) (m : M) : (m ∈ ⨆ k, a k) ↔ ∃ k, m ∈ a k :=
mem_iSup_of_directed a a.monotone.directed_le
#align submodule.mem_supr_of_chain Submodule.mem_iSup_of_chain
section
variable {p p'}
theorem mem_sup : x ∈ p ⊔ p' ↔ ∃ y ∈ p, ∃ z ∈ p', y + z = x :=
⟨fun h => by
rw [← span_eq p, ← span_eq p', ← span_union] at h
refine span_induction h ?_ ?_ ?_ ?_
· rintro y (h | h)
· exact ⟨y, h, 0, by simp, by simp⟩
· exact ⟨0, by simp, y, h, by simp⟩
· exact ⟨0, by simp, 0, by simp⟩
· rintro _ _ ⟨y₁, hy₁, z₁, hz₁, rfl⟩ ⟨y₂, hy₂, z₂, hz₂, rfl⟩
exact ⟨_, add_mem hy₁ hy₂, _, add_mem hz₁ hz₂, by
rw [add_assoc, add_assoc, ← add_assoc y₂, ← add_assoc z₁, add_comm y₂]⟩
· rintro a _ ⟨y, hy, z, hz, rfl⟩
exact ⟨_, smul_mem _ a hy, _, smul_mem _ a hz, by simp [smul_add]⟩, by
rintro ⟨y, hy, z, hz, rfl⟩
exact add_mem ((le_sup_left : p ≤ p ⊔ p') hy) ((le_sup_right : p' ≤ p ⊔ p') hz)⟩
#align submodule.mem_sup Submodule.mem_sup
theorem mem_sup' : x ∈ p ⊔ p' ↔ ∃ (y : p) (z : p'), (y : M) + z = x :=
mem_sup.trans <| by simp only [Subtype.exists, exists_prop]
#align submodule.mem_sup' Submodule.mem_sup'
lemma exists_add_eq_of_codisjoint (h : Codisjoint p p') (x : M) :
∃ y ∈ p, ∃ z ∈ p', y + z = x := by
suffices x ∈ p ⊔ p' by exact Submodule.mem_sup.mp this
simpa only [h.eq_top] using Submodule.mem_top
variable (p p')
theorem coe_sup : ↑(p ⊔ p') = (p + p' : Set M) := by
ext
rw [SetLike.mem_coe, mem_sup, Set.mem_add]
simp
#align submodule.coe_sup Submodule.coe_sup
theorem sup_toAddSubmonoid : (p ⊔ p').toAddSubmonoid = p.toAddSubmonoid ⊔ p'.toAddSubmonoid := by
ext x
rw [mem_toAddSubmonoid, mem_sup, AddSubmonoid.mem_sup]
rfl
#align submodule.sup_to_add_submonoid Submodule.sup_toAddSubmonoid
theorem sup_toAddSubgroup {R M : Type*} [Ring R] [AddCommGroup M] [Module R M]
(p p' : Submodule R M) : (p ⊔ p').toAddSubgroup = p.toAddSubgroup ⊔ p'.toAddSubgroup := by
ext x
rw [mem_toAddSubgroup, mem_sup, AddSubgroup.mem_sup]
rfl
#align submodule.sup_to_add_subgroup Submodule.sup_toAddSubgroup
end
theorem mem_span_singleton_self (x : M) : x ∈ R ∙ x :=
subset_span rfl
#align submodule.mem_span_singleton_self Submodule.mem_span_singleton_self
theorem nontrivial_span_singleton {x : M} (h : x ≠ 0) : Nontrivial (R ∙ x) :=
⟨by
use 0, ⟨x, Submodule.mem_span_singleton_self x⟩
intro H
rw [eq_comm, Submodule.mk_eq_zero] at H
exact h H⟩
#align submodule.nontrivial_span_singleton Submodule.nontrivial_span_singleton
theorem mem_span_singleton {y : M} : (x ∈ R ∙ y) ↔ ∃ a : R, a • y = x :=
⟨fun h => by
refine span_induction h ?_ ?_ ?_ ?_
· rintro y (rfl | ⟨⟨_⟩⟩)
exact ⟨1, by simp⟩
· exact ⟨0, by simp⟩
· rintro _ _ ⟨a, rfl⟩ ⟨b, rfl⟩
exact ⟨a + b, by simp [add_smul]⟩
· rintro a _ ⟨b, rfl⟩
exact ⟨a * b, by simp [smul_smul]⟩, by
rintro ⟨a, y, rfl⟩; exact smul_mem _ _ (subset_span <| by simp)⟩
#align submodule.mem_span_singleton Submodule.mem_span_singleton
theorem le_span_singleton_iff {s : Submodule R M} {v₀ : M} :
(s ≤ R ∙ v₀) ↔ ∀ v ∈ s, ∃ r : R, r • v₀ = v := by simp_rw [SetLike.le_def, mem_span_singleton]
#align submodule.le_span_singleton_iff Submodule.le_span_singleton_iff
variable (R)
theorem span_singleton_eq_top_iff (x : M) : (R ∙ x) = ⊤ ↔ ∀ v, ∃ r : R, r • x = v := by
rw [eq_top_iff, le_span_singleton_iff]
tauto
#align submodule.span_singleton_eq_top_iff Submodule.span_singleton_eq_top_iff
@[simp]
theorem span_zero_singleton : (R ∙ (0 : M)) = ⊥ := by
ext
simp [mem_span_singleton, eq_comm]
#align submodule.span_zero_singleton Submodule.span_zero_singleton
theorem span_singleton_eq_range (y : M) : ↑(R ∙ y) = range ((· • y) : R → M) :=
Set.ext fun _ => mem_span_singleton
#align submodule.span_singleton_eq_range Submodule.span_singleton_eq_range
theorem span_singleton_smul_le {S} [Monoid S] [SMul S R] [MulAction S M] [IsScalarTower S R M]
(r : S) (x : M) : (R ∙ r • x) ≤ R ∙ x := by
rw [span_le, Set.singleton_subset_iff, SetLike.mem_coe]
exact smul_of_tower_mem _ _ (mem_span_singleton_self _)
#align submodule.span_singleton_smul_le Submodule.span_singleton_smul_le
theorem span_singleton_group_smul_eq {G} [Group G] [SMul G R] [MulAction G M] [IsScalarTower G R M]
(g : G) (x : M) : (R ∙ g • x) = R ∙ x := by
refine le_antisymm (span_singleton_smul_le R g x) ?_
convert span_singleton_smul_le R g⁻¹ (g • x)
exact (inv_smul_smul g x).symm
#align submodule.span_singleton_group_smul_eq Submodule.span_singleton_group_smul_eq
variable {R}
theorem span_singleton_smul_eq {r : R} (hr : IsUnit r) (x : M) : (R ∙ r • x) = R ∙ x := by
lift r to Rˣ using hr
rw [← Units.smul_def]
exact span_singleton_group_smul_eq R r x
#align submodule.span_singleton_smul_eq Submodule.span_singleton_smul_eq
theorem disjoint_span_singleton {K E : Type*} [DivisionRing K] [AddCommGroup E] [Module K E]
{s : Submodule K E} {x : E} : Disjoint s (K ∙ x) ↔ x ∈ s → x = 0 := by
refine disjoint_def.trans ⟨fun H hx => H x hx <| subset_span <| mem_singleton x, ?_⟩
intro H y hy hyx
obtain ⟨c, rfl⟩ := mem_span_singleton.1 hyx
by_cases hc : c = 0
· rw [hc, zero_smul]
· rw [s.smul_mem_iff hc] at hy
rw [H hy, smul_zero]
#align submodule.disjoint_span_singleton Submodule.disjoint_span_singleton
theorem disjoint_span_singleton' {K E : Type*} [DivisionRing K] [AddCommGroup E] [Module K E]
{p : Submodule K E} {x : E} (x0 : x ≠ 0) : Disjoint p (K ∙ x) ↔ x ∉ p :=
disjoint_span_singleton.trans ⟨fun h₁ h₂ => x0 (h₁ h₂), fun h₁ h₂ => (h₁ h₂).elim⟩
#align submodule.disjoint_span_singleton' Submodule.disjoint_span_singleton'
theorem mem_span_singleton_trans {x y z : M} (hxy : x ∈ R ∙ y) (hyz : y ∈ R ∙ z) : x ∈ R ∙ z := by
rw [← SetLike.mem_coe, ← singleton_subset_iff] at *
exact Submodule.subset_span_trans hxy hyz
#align submodule.mem_span_singleton_trans Submodule.mem_span_singleton_trans
theorem span_insert (x) (s : Set M) : span R (insert x s) = (R ∙ x) ⊔ span R s := by
rw [insert_eq, span_union]
#align submodule.span_insert Submodule.span_insert
theorem span_insert_eq_span (h : x ∈ span R s) : span R (insert x s) = span R s :=
span_eq_of_le _ (Set.insert_subset_iff.mpr ⟨h, subset_span⟩) (span_mono <| subset_insert _ _)
#align submodule.span_insert_eq_span Submodule.span_insert_eq_span
theorem span_span : span R (span R s : Set M) = span R s :=
span_eq _
#align submodule.span_span Submodule.span_span
theorem mem_span_insert {y} :
x ∈ span R (insert y s) ↔ ∃ a : R, ∃ z ∈ span R s, x = a • y + z := by
simp [span_insert, mem_sup, mem_span_singleton, eq_comm (a := x)]
#align submodule.mem_span_insert Submodule.mem_span_insert
theorem mem_span_pair {x y z : M} :
z ∈ span R ({x, y} : Set M) ↔ ∃ a b : R, a • x + b • y = z := by
simp_rw [mem_span_insert, mem_span_singleton, exists_exists_eq_and, eq_comm]
#align submodule.mem_span_pair Submodule.mem_span_pair
variable (R S s)
/-- If `R` is "smaller" ring than `S` then the span by `R` is smaller than the span by `S`. -/
theorem span_le_restrictScalars [Semiring S] [SMul R S] [Module S M] [IsScalarTower R S M] :
span R s ≤ (span S s).restrictScalars R :=
Submodule.span_le.2 Submodule.subset_span
#align submodule.span_le_restrict_scalars Submodule.span_le_restrictScalars
/-- A version of `Submodule.span_le_restrictScalars` with coercions. -/
@[simp]
theorem span_subset_span [Semiring S] [SMul R S] [Module S M] [IsScalarTower R S M] :
↑(span R s) ⊆ (span S s : Set M) :=
span_le_restrictScalars R S s
#align submodule.span_subset_span Submodule.span_subset_span
/-- Taking the span by a large ring of the span by the small ring is the same as taking the span
by just the large ring. -/
theorem span_span_of_tower [Semiring S] [SMul R S] [Module S M] [IsScalarTower R S M] :
span S (span R s : Set M) = span S s :=
le_antisymm (span_le.2 <| span_subset_span R S s) (span_mono subset_span)
#align submodule.span_span_of_tower Submodule.span_span_of_tower
variable {R S s}
theorem span_eq_bot : span R (s : Set M) = ⊥ ↔ ∀ x ∈ s, (x : M) = 0 :=
eq_bot_iff.trans
⟨fun H _ h => (mem_bot R).1 <| H <| subset_span h, fun H =>
span_le.2 fun x h => (mem_bot R).2 <| H x h⟩
#align submodule.span_eq_bot Submodule.span_eq_bot
@[simp]
theorem span_singleton_eq_bot : (R ∙ x) = ⊥ ↔ x = 0 :=
span_eq_bot.trans <| by simp
#align submodule.span_singleton_eq_bot Submodule.span_singleton_eq_bot
@[simp]
theorem span_zero : span R (0 : Set M) = ⊥ := by rw [← singleton_zero, span_singleton_eq_bot]
#align submodule.span_zero Submodule.span_zero
@[simp]
theorem span_singleton_le_iff_mem (m : M) (p : Submodule R M) : (R ∙ m) ≤ p ↔ m ∈ p := by
rw [span_le, singleton_subset_iff, SetLike.mem_coe]
#align submodule.span_singleton_le_iff_mem Submodule.span_singleton_le_iff_mem
theorem span_singleton_eq_span_singleton {R M : Type*} [Ring R] [AddCommGroup M] [Module R M]
[NoZeroSMulDivisors R M] {x y : M} : ((R ∙ x) = R ∙ y) ↔ ∃ z : Rˣ, z • x = y := by
constructor
· simp only [le_antisymm_iff, span_singleton_le_iff_mem, mem_span_singleton]
rintro ⟨⟨a, rfl⟩, b, hb⟩
rcases eq_or_ne y 0 with rfl | hy; · simp
refine ⟨⟨b, a, ?_, ?_⟩, hb⟩
· apply smul_left_injective R hy
simpa only [mul_smul, one_smul]
· rw [← hb] at hy
apply smul_left_injective R (smul_ne_zero_iff.1 hy).2
simp only [mul_smul, one_smul, hb]
· rintro ⟨u, rfl⟩
exact (span_singleton_group_smul_eq _ _ _).symm
#align submodule.span_singleton_eq_span_singleton Submodule.span_singleton_eq_span_singleton
-- Should be `@[simp]` but doesn't fire due to `lean4#3701`.
theorem span_image [RingHomSurjective σ₁₂] (f : F) :
span R₂ (f '' s) = map f (span R s) :=
(map_span f s).symm
#align submodule.span_image Submodule.span_image
@[simp] -- Should be replaced with `Submodule.span_image` when `lean4#3701` is fixed.
theorem span_image' [RingHomSurjective σ₁₂] (f : M →ₛₗ[σ₁₂] M₂) :
span R₂ (f '' s) = map f (span R s) :=
span_image _
theorem apply_mem_span_image_of_mem_span [RingHomSurjective σ₁₂] (f : F) {x : M}
{s : Set M} (h : x ∈ Submodule.span R s) : f x ∈ Submodule.span R₂ (f '' s) := by
rw [Submodule.span_image]
exact Submodule.mem_map_of_mem h
#align submodule.apply_mem_span_image_of_mem_span Submodule.apply_mem_span_image_of_mem_span
theorem apply_mem_span_image_iff_mem_span [RingHomSurjective σ₁₂] {f : F} {x : M}
{s : Set M} (hf : Function.Injective f) :
f x ∈ Submodule.span R₂ (f '' s) ↔ x ∈ Submodule.span R s := by
rw [← Submodule.mem_comap, ← Submodule.map_span, Submodule.comap_map_eq_of_injective hf]
@[simp]
theorem map_subtype_span_singleton {p : Submodule R M} (x : p) :
map p.subtype (R ∙ x) = R ∙ (x : M) := by simp [← span_image]
#align submodule.map_subtype_span_singleton Submodule.map_subtype_span_singleton
/-- `f` is an explicit argument so we can `apply` this theorem and obtain `h` as a new goal. -/
theorem not_mem_span_of_apply_not_mem_span_image [RingHomSurjective σ₁₂] (f : F) {x : M}
{s : Set M} (h : f x ∉ Submodule.span R₂ (f '' s)) : x ∉ Submodule.span R s :=
h.imp (apply_mem_span_image_of_mem_span f)
#align submodule.not_mem_span_of_apply_not_mem_span_image Submodule.not_mem_span_of_apply_not_mem_span_image
theorem iSup_span {ι : Sort*} (p : ι → Set M) : ⨆ i, span R (p i) = span R (⋃ i, p i) :=
le_antisymm (iSup_le fun i => span_mono <| subset_iUnion _ i) <|
span_le.mpr <| iUnion_subset fun i _ hm => mem_iSup_of_mem i <| subset_span hm
#align submodule.supr_span Submodule.iSup_span
theorem iSup_eq_span {ι : Sort*} (p : ι → Submodule R M) : ⨆ i, p i = span R (⋃ i, ↑(p i)) := by
simp_rw [← iSup_span, span_eq]
#align submodule.supr_eq_span Submodule.iSup_eq_span
theorem iSup_toAddSubmonoid {ι : Sort*} (p : ι → Submodule R M) :
(⨆ i, p i).toAddSubmonoid = ⨆ i, (p i).toAddSubmonoid := by
refine le_antisymm (fun x => ?_) (iSup_le fun i => toAddSubmonoid_mono <| le_iSup _ i)
simp_rw [iSup_eq_span, AddSubmonoid.iSup_eq_closure, mem_toAddSubmonoid, coe_toAddSubmonoid]
intro hx
refine Submodule.span_induction hx (fun x hx => ?_) ?_ (fun x y hx hy => ?_) fun r x hx => ?_
· exact AddSubmonoid.subset_closure hx
· exact AddSubmonoid.zero_mem _
· exact AddSubmonoid.add_mem _ hx hy
· refine AddSubmonoid.closure_induction hx ?_ ?_ ?_
· rintro x ⟨_, ⟨i, rfl⟩, hix : x ∈ p i⟩
apply AddSubmonoid.subset_closure (Set.mem_iUnion.mpr ⟨i, _⟩)
exact smul_mem _ r hix
· rw [smul_zero]
exact AddSubmonoid.zero_mem _
· intro x y hx hy
rw [smul_add]
exact AddSubmonoid.add_mem _ hx hy
#align submodule.supr_to_add_submonoid Submodule.iSup_toAddSubmonoid
/-- An induction principle for elements of `⨆ i, p i`.
If `C` holds for `0` and all elements of `p i` for all `i`, and is preserved under addition,
then it holds for all elements of the supremum of `p`. -/
@[elab_as_elim]
theorem iSup_induction {ι : Sort*} (p : ι → Submodule R M) {C : M → Prop} {x : M}
(hx : x ∈ ⨆ i, p i) (hp : ∀ (i), ∀ x ∈ p i, C x) (h0 : C 0)
(hadd : ∀ x y, C x → C y → C (x + y)) : C x := by
rw [← mem_toAddSubmonoid, iSup_toAddSubmonoid] at hx
exact AddSubmonoid.iSup_induction (x := x) _ hx hp h0 hadd
#align submodule.supr_induction Submodule.iSup_induction
/-- A dependent version of `submodule.iSup_induction`. -/
@[elab_as_elim]
theorem iSup_induction' {ι : Sort*} (p : ι → Submodule R M) {C : ∀ x, (x ∈ ⨆ i, p i) → Prop}
(mem : ∀ (i) (x) (hx : x ∈ p i), C x (mem_iSup_of_mem i hx)) (zero : C 0 (zero_mem _))
(add : ∀ x y hx hy, C x hx → C y hy → C (x + y) (add_mem ‹_› ‹_›)) {x : M}
(hx : x ∈ ⨆ i, p i) : C x hx := by
refine Exists.elim ?_ fun (hx : x ∈ ⨆ i, p i) (hc : C x hx) => hc
refine iSup_induction p (C := fun x : M ↦ ∃ (hx : x ∈ ⨆ i, p i), C x hx) hx
(fun i x hx => ?_) ?_ fun x y => ?_
· exact ⟨_, mem _ _ hx⟩
· exact ⟨_, zero⟩
· rintro ⟨_, Cx⟩ ⟨_, Cy⟩
exact ⟨_, add _ _ _ _ Cx Cy⟩
#align submodule.supr_induction' Submodule.iSup_induction'
theorem singleton_span_isCompactElement (x : M) :
CompleteLattice.IsCompactElement (span R {x} : Submodule R M) := by
rw [CompleteLattice.isCompactElement_iff_le_of_directed_sSup_le]
intro d hemp hdir hsup
have : x ∈ (sSup d) := (SetLike.le_def.mp hsup) (mem_span_singleton_self x)
obtain ⟨y, ⟨hyd, hxy⟩⟩ := (mem_sSup_of_directed hemp hdir).mp this
exact ⟨y, ⟨hyd, by simpa only [span_le, singleton_subset_iff] ⟩⟩
#align submodule.singleton_span_is_compact_element Submodule.singleton_span_isCompactElement
/-- The span of a finite subset is compact in the lattice of submodules. -/
theorem finset_span_isCompactElement (S : Finset M) :
CompleteLattice.IsCompactElement (span R S : Submodule R M) := by
rw [span_eq_iSup_of_singleton_spans]
simp only [Finset.mem_coe]
rw [← Finset.sup_eq_iSup]
exact
CompleteLattice.isCompactElement_finsetSup S fun x _ => singleton_span_isCompactElement x
#align submodule.finset_span_is_compact_element Submodule.finset_span_isCompactElement
/-- The span of a finite subset is compact in the lattice of submodules. -/
theorem finite_span_isCompactElement (S : Set M) (h : S.Finite) :
CompleteLattice.IsCompactElement (span R S : Submodule R M) :=
Finite.coe_toFinset h ▸ finset_span_isCompactElement h.toFinset
#align submodule.finite_span_is_compact_element Submodule.finite_span_isCompactElement
instance : IsCompactlyGenerated (Submodule R M) :=
⟨fun s =>
⟨(fun x => span R {x}) '' s,
⟨fun t ht => by
rcases (Set.mem_image _ _ _).1 ht with ⟨x, _, rfl⟩
apply singleton_span_isCompactElement, by
rw [sSup_eq_iSup, iSup_image, ← span_eq_iSup_of_singleton_spans, span_eq]⟩⟩⟩
/-- A submodule is equal to the supremum of the spans of the submodule's nonzero elements. -/
theorem submodule_eq_sSup_le_nonzero_spans (p : Submodule R M) :
p = sSup { T : Submodule R M | ∃ m ∈ p, m ≠ 0 ∧ T = span R {m} } := by
let S := { T : Submodule R M | ∃ m ∈ p, m ≠ 0 ∧ T = span R {m} }
apply le_antisymm
· intro m hm
by_cases h : m = 0
· rw [h]
simp
· exact @le_sSup _ _ S _ ⟨m, ⟨hm, ⟨h, rfl⟩⟩⟩ m (mem_span_singleton_self m)
· rw [sSup_le_iff]
rintro S ⟨_, ⟨_, ⟨_, rfl⟩⟩⟩
rwa [span_singleton_le_iff_mem]
#align submodule.submodule_eq_Sup_le_nonzero_spans Submodule.submodule_eq_sSup_le_nonzero_spans
theorem lt_sup_iff_not_mem {I : Submodule R M} {a : M} : (I < I ⊔ R ∙ a) ↔ a ∉ I := by simp
#align submodule.lt_sup_iff_not_mem Submodule.lt_sup_iff_not_mem
theorem mem_iSup {ι : Sort*} (p : ι → Submodule R M) {m : M} :
(m ∈ ⨆ i, p i) ↔ ∀ N, (∀ i, p i ≤ N) → m ∈ N := by
rw [← span_singleton_le_iff_mem, le_iSup_iff]
simp only [span_singleton_le_iff_mem]
#align submodule.mem_supr Submodule.mem_iSup
theorem mem_sSup {s : Set (Submodule R M)} {m : M} :
(m ∈ sSup s) ↔ ∀ N, (∀ p ∈ s, p ≤ N) → m ∈ N := by
simp_rw [sSup_eq_iSup, Submodule.mem_iSup, iSup_le_iff]
section
/-- For every element in the span of a set, there exists a finite subset of the set
such that the element is contained in the span of the subset. -/
theorem mem_span_finite_of_mem_span {S : Set M} {x : M} (hx : x ∈ span R S) :
∃ T : Finset M, ↑T ⊆ S ∧ x ∈ span R (T : Set M) := by
classical
refine span_induction hx (fun x hx => ?_) ?_ ?_ ?_
· refine ⟨{x}, ?_, ?_⟩
· rwa [Finset.coe_singleton, Set.singleton_subset_iff]
· rw [Finset.coe_singleton]
exact Submodule.mem_span_singleton_self x
· use ∅
simp
· rintro x y ⟨X, hX, hxX⟩ ⟨Y, hY, hyY⟩
refine ⟨X ∪ Y, ?_, ?_⟩
· rw [Finset.coe_union]
exact Set.union_subset hX hY
rw [Finset.coe_union, span_union, mem_sup]
exact ⟨x, hxX, y, hyY, rfl⟩
· rintro a x ⟨T, hT, h2⟩
exact ⟨T, hT, smul_mem _ _ h2⟩
#align submodule.mem_span_finite_of_mem_span Submodule.mem_span_finite_of_mem_span
end
variable {M' : Type*} [AddCommMonoid M'] [Module R M'] (q₁ q₁' : Submodule R M')
/-- The product of two submodules is a submodule. -/
def prod : Submodule R (M × M') :=
{ p.toAddSubmonoid.prod q₁.toAddSubmonoid with
carrier := p ×ˢ q₁
smul_mem' := by rintro a ⟨x, y⟩ ⟨hx, hy⟩; exact ⟨smul_mem _ a hx, smul_mem _ a hy⟩ }
#align submodule.prod Submodule.prod
@[simp]
theorem prod_coe : (prod p q₁ : Set (M × M')) = (p : Set M) ×ˢ (q₁ : Set M') :=
rfl
#align submodule.prod_coe Submodule.prod_coe
@[simp]
theorem mem_prod {p : Submodule R M} {q : Submodule R M'} {x : M × M'} :
x ∈ prod p q ↔ x.1 ∈ p ∧ x.2 ∈ q :=
Set.mem_prod
#align submodule.mem_prod Submodule.mem_prod
theorem span_prod_le (s : Set M) (t : Set M') : span R (s ×ˢ t) ≤ prod (span R s) (span R t) :=
span_le.2 <| Set.prod_mono subset_span subset_span
#align submodule.span_prod_le Submodule.span_prod_le
@[simp]
theorem prod_top : (prod ⊤ ⊤ : Submodule R (M × M')) = ⊤ := by ext; simp
#align submodule.prod_top Submodule.prod_top
@[simp]
| Mathlib/LinearAlgebra/Span.lean | 847 | 847 | theorem prod_bot : (prod ⊥ ⊥ : Submodule R (M × M')) = ⊥ := by | ext ⟨x, y⟩; simp [Prod.zero_eq_mk]
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Logic.Pairwise
import Mathlib.Order.CompleteBooleanAlgebra
import Mathlib.Order.Directed
import Mathlib.Order.GaloisConnection
#align_import data.set.lattice from "leanprover-community/mathlib"@"b86832321b586c6ac23ef8cdef6a7a27e42b13bd"
/-!
# The set lattice
This file provides usual set notation for unions and intersections, a `CompleteLattice` instance
for `Set α`, and some more set constructions.
## Main declarations
* `Set.iUnion`: **i**ndexed **union**. Union of an indexed family of sets.
* `Set.iInter`: **i**ndexed **inter**section. Intersection of an indexed family of sets.
* `Set.sInter`: **s**et **inter**section. Intersection of sets belonging to a set of sets.
* `Set.sUnion`: **s**et **union**. Union of sets belonging to a set of sets.
* `Set.sInter_eq_biInter`, `Set.sUnion_eq_biInter`: Shows that `⋂₀ s = ⋂ x ∈ s, x` and
`⋃₀ s = ⋃ x ∈ s, x`.
* `Set.completeAtomicBooleanAlgebra`: `Set α` is a `CompleteAtomicBooleanAlgebra` with `≤ = ⊆`,
`< = ⊂`, `⊓ = ∩`, `⊔ = ∪`, `⨅ = ⋂`, `⨆ = ⋃` and `\` as the set difference.
See `Set.BooleanAlgebra`.
* `Set.kernImage`: For a function `f : α → β`, `s.kernImage f` is the set of `y` such that
`f ⁻¹ y ⊆ s`.
* `Set.seq`: Union of the image of a set under a **seq**uence of functions. `seq s t` is the union
of `f '' t` over all `f ∈ s`, where `t : Set α` and `s : Set (α → β)`.
* `Set.unionEqSigmaOfDisjoint`: Equivalence between `⋃ i, t i` and `Σ i, t i`, where `t` is an
indexed family of disjoint sets.
## Naming convention
In lemma names,
* `⋃ i, s i` is called `iUnion`
* `⋂ i, s i` is called `iInter`
* `⋃ i j, s i j` is called `iUnion₂`. This is an `iUnion` inside an `iUnion`.
* `⋂ i j, s i j` is called `iInter₂`. This is an `iInter` inside an `iInter`.
* `⋃ i ∈ s, t i` is called `biUnion` for "bounded `iUnion`". This is the special case of `iUnion₂`
where `j : i ∈ s`.
* `⋂ i ∈ s, t i` is called `biInter` for "bounded `iInter`". This is the special case of `iInter₂`
where `j : i ∈ s`.
## Notation
* `⋃`: `Set.iUnion`
* `⋂`: `Set.iInter`
* `⋃₀`: `Set.sUnion`
* `⋂₀`: `Set.sInter`
-/
open Function Set
universe u
variable {α β γ : Type*} {ι ι' ι₂ : Sort*} {κ κ₁ κ₂ : ι → Sort*} {κ' : ι' → Sort*}
namespace Set
/-! ### Complete lattice and complete Boolean algebra instances -/
theorem mem_iUnion₂ {x : γ} {s : ∀ i, κ i → Set γ} : (x ∈ ⋃ (i) (j), s i j) ↔ ∃ i j, x ∈ s i j := by
simp_rw [mem_iUnion]
#align set.mem_Union₂ Set.mem_iUnion₂
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem mem_iInter₂ {x : γ} {s : ∀ i, κ i → Set γ} : (x ∈ ⋂ (i) (j), s i j) ↔ ∀ i j, x ∈ s i j := by
simp_rw [mem_iInter]
#align set.mem_Inter₂ Set.mem_iInter₂
theorem mem_iUnion_of_mem {s : ι → Set α} {a : α} (i : ι) (ha : a ∈ s i) : a ∈ ⋃ i, s i :=
mem_iUnion.2 ⟨i, ha⟩
#align set.mem_Union_of_mem Set.mem_iUnion_of_mem
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem mem_iUnion₂_of_mem {s : ∀ i, κ i → Set α} {a : α} {i : ι} (j : κ i) (ha : a ∈ s i j) :
a ∈ ⋃ (i) (j), s i j :=
mem_iUnion₂.2 ⟨i, j, ha⟩
#align set.mem_Union₂_of_mem Set.mem_iUnion₂_of_mem
theorem mem_iInter_of_mem {s : ι → Set α} {a : α} (h : ∀ i, a ∈ s i) : a ∈ ⋂ i, s i :=
mem_iInter.2 h
#align set.mem_Inter_of_mem Set.mem_iInter_of_mem
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem mem_iInter₂_of_mem {s : ∀ i, κ i → Set α} {a : α} (h : ∀ i j, a ∈ s i j) :
a ∈ ⋂ (i) (j), s i j :=
mem_iInter₂.2 h
#align set.mem_Inter₂_of_mem Set.mem_iInter₂_of_mem
instance completeAtomicBooleanAlgebra : CompleteAtomicBooleanAlgebra (Set α) :=
{ instBooleanAlgebraSet with
le_sSup := fun s t t_in a a_in => ⟨t, t_in, a_in⟩
sSup_le := fun s t h a ⟨t', ⟨t'_in, a_in⟩⟩ => h t' t'_in a_in
le_sInf := fun s t h a a_in t' t'_in => h t' t'_in a_in
sInf_le := fun s t t_in a h => h _ t_in
iInf_iSup_eq := by intros; ext; simp [Classical.skolem] }
section GaloisConnection
variable {f : α → β}
protected theorem image_preimage : GaloisConnection (image f) (preimage f) := fun _ _ =>
image_subset_iff
#align set.image_preimage Set.image_preimage
protected theorem preimage_kernImage : GaloisConnection (preimage f) (kernImage f) := fun _ _ =>
subset_kernImage_iff.symm
#align set.preimage_kern_image Set.preimage_kernImage
end GaloisConnection
section kernImage
variable {f : α → β}
lemma kernImage_mono : Monotone (kernImage f) :=
Set.preimage_kernImage.monotone_u
lemma kernImage_eq_compl {s : Set α} : kernImage f s = (f '' sᶜ)ᶜ :=
Set.preimage_kernImage.u_unique (Set.image_preimage.compl)
(fun t ↦ compl_compl (f ⁻¹' t) ▸ Set.preimage_compl)
lemma kernImage_compl {s : Set α} : kernImage f (sᶜ) = (f '' s)ᶜ := by
rw [kernImage_eq_compl, compl_compl]
lemma kernImage_empty : kernImage f ∅ = (range f)ᶜ := by
rw [kernImage_eq_compl, compl_empty, image_univ]
lemma kernImage_preimage_eq_iff {s : Set β} : kernImage f (f ⁻¹' s) = s ↔ (range f)ᶜ ⊆ s := by
rw [kernImage_eq_compl, ← preimage_compl, compl_eq_comm, eq_comm, image_preimage_eq_iff,
compl_subset_comm]
lemma compl_range_subset_kernImage {s : Set α} : (range f)ᶜ ⊆ kernImage f s := by
rw [← kernImage_empty]
exact kernImage_mono (empty_subset _)
lemma kernImage_union_preimage {s : Set α} {t : Set β} :
kernImage f (s ∪ f ⁻¹' t) = kernImage f s ∪ t := by
rw [kernImage_eq_compl, kernImage_eq_compl, compl_union, ← preimage_compl, image_inter_preimage,
compl_inter, compl_compl]
lemma kernImage_preimage_union {s : Set α} {t : Set β} :
kernImage f (f ⁻¹' t ∪ s) = t ∪ kernImage f s := by
rw [union_comm, kernImage_union_preimage, union_comm]
end kernImage
/-! ### Union and intersection over an indexed family of sets -/
instance : OrderTop (Set α) where
top := univ
le_top := by simp
@[congr]
theorem iUnion_congr_Prop {p q : Prop} {f₁ : p → Set α} {f₂ : q → Set α} (pq : p ↔ q)
(f : ∀ x, f₁ (pq.mpr x) = f₂ x) : iUnion f₁ = iUnion f₂ :=
iSup_congr_Prop pq f
#align set.Union_congr_Prop Set.iUnion_congr_Prop
@[congr]
theorem iInter_congr_Prop {p q : Prop} {f₁ : p → Set α} {f₂ : q → Set α} (pq : p ↔ q)
(f : ∀ x, f₁ (pq.mpr x) = f₂ x) : iInter f₁ = iInter f₂ :=
iInf_congr_Prop pq f
#align set.Inter_congr_Prop Set.iInter_congr_Prop
theorem iUnion_plift_up (f : PLift ι → Set α) : ⋃ i, f (PLift.up i) = ⋃ i, f i :=
iSup_plift_up _
#align set.Union_plift_up Set.iUnion_plift_up
theorem iUnion_plift_down (f : ι → Set α) : ⋃ i, f (PLift.down i) = ⋃ i, f i :=
iSup_plift_down _
#align set.Union_plift_down Set.iUnion_plift_down
theorem iInter_plift_up (f : PLift ι → Set α) : ⋂ i, f (PLift.up i) = ⋂ i, f i :=
iInf_plift_up _
#align set.Inter_plift_up Set.iInter_plift_up
theorem iInter_plift_down (f : ι → Set α) : ⋂ i, f (PLift.down i) = ⋂ i, f i :=
iInf_plift_down _
#align set.Inter_plift_down Set.iInter_plift_down
theorem iUnion_eq_if {p : Prop} [Decidable p] (s : Set α) : ⋃ _ : p, s = if p then s else ∅ :=
iSup_eq_if _
#align set.Union_eq_if Set.iUnion_eq_if
theorem iUnion_eq_dif {p : Prop} [Decidable p] (s : p → Set α) :
⋃ h : p, s h = if h : p then s h else ∅ :=
iSup_eq_dif _
#align set.Union_eq_dif Set.iUnion_eq_dif
theorem iInter_eq_if {p : Prop} [Decidable p] (s : Set α) : ⋂ _ : p, s = if p then s else univ :=
iInf_eq_if _
#align set.Inter_eq_if Set.iInter_eq_if
theorem iInf_eq_dif {p : Prop} [Decidable p] (s : p → Set α) :
⋂ h : p, s h = if h : p then s h else univ :=
_root_.iInf_eq_dif _
#align set.Infi_eq_dif Set.iInf_eq_dif
theorem exists_set_mem_of_union_eq_top {ι : Type*} (t : Set ι) (s : ι → Set β)
(w : ⋃ i ∈ t, s i = ⊤) (x : β) : ∃ i ∈ t, x ∈ s i := by
have p : x ∈ ⊤ := Set.mem_univ x
rw [← w, Set.mem_iUnion] at p
simpa using p
#align set.exists_set_mem_of_union_eq_top Set.exists_set_mem_of_union_eq_top
theorem nonempty_of_union_eq_top_of_nonempty {ι : Type*} (t : Set ι) (s : ι → Set α)
(H : Nonempty α) (w : ⋃ i ∈ t, s i = ⊤) : t.Nonempty := by
obtain ⟨x, m, -⟩ := exists_set_mem_of_union_eq_top t s w H.some
exact ⟨x, m⟩
#align set.nonempty_of_union_eq_top_of_nonempty Set.nonempty_of_union_eq_top_of_nonempty
theorem nonempty_of_nonempty_iUnion
{s : ι → Set α} (h_Union : (⋃ i, s i).Nonempty) : Nonempty ι := by
obtain ⟨x, hx⟩ := h_Union
exact ⟨Classical.choose <| mem_iUnion.mp hx⟩
theorem nonempty_of_nonempty_iUnion_eq_univ
{s : ι → Set α} [Nonempty α] (h_Union : ⋃ i, s i = univ) : Nonempty ι :=
nonempty_of_nonempty_iUnion (s := s) (by simpa only [h_Union] using univ_nonempty)
theorem setOf_exists (p : ι → β → Prop) : { x | ∃ i, p i x } = ⋃ i, { x | p i x } :=
ext fun _ => mem_iUnion.symm
#align set.set_of_exists Set.setOf_exists
theorem setOf_forall (p : ι → β → Prop) : { x | ∀ i, p i x } = ⋂ i, { x | p i x } :=
ext fun _ => mem_iInter.symm
#align set.set_of_forall Set.setOf_forall
theorem iUnion_subset {s : ι → Set α} {t : Set α} (h : ∀ i, s i ⊆ t) : ⋃ i, s i ⊆ t :=
iSup_le h
#align set.Union_subset Set.iUnion_subset
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem iUnion₂_subset {s : ∀ i, κ i → Set α} {t : Set α} (h : ∀ i j, s i j ⊆ t) :
⋃ (i) (j), s i j ⊆ t :=
iUnion_subset fun x => iUnion_subset (h x)
#align set.Union₂_subset Set.iUnion₂_subset
theorem subset_iInter {t : Set β} {s : ι → Set β} (h : ∀ i, t ⊆ s i) : t ⊆ ⋂ i, s i :=
le_iInf h
#align set.subset_Inter Set.subset_iInter
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem subset_iInter₂ {s : Set α} {t : ∀ i, κ i → Set α} (h : ∀ i j, s ⊆ t i j) :
s ⊆ ⋂ (i) (j), t i j :=
subset_iInter fun x => subset_iInter <| h x
#align set.subset_Inter₂ Set.subset_iInter₂
@[simp]
theorem iUnion_subset_iff {s : ι → Set α} {t : Set α} : ⋃ i, s i ⊆ t ↔ ∀ i, s i ⊆ t :=
⟨fun h _ => Subset.trans (le_iSup s _) h, iUnion_subset⟩
#align set.Union_subset_iff Set.iUnion_subset_iff
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem iUnion₂_subset_iff {s : ∀ i, κ i → Set α} {t : Set α} :
⋃ (i) (j), s i j ⊆ t ↔ ∀ i j, s i j ⊆ t := by simp_rw [iUnion_subset_iff]
#align set.Union₂_subset_iff Set.iUnion₂_subset_iff
@[simp]
theorem subset_iInter_iff {s : Set α} {t : ι → Set α} : (s ⊆ ⋂ i, t i) ↔ ∀ i, s ⊆ t i :=
le_iInf_iff
#align set.subset_Inter_iff Set.subset_iInter_iff
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
-- Porting note (#10618): removing `simp`. `simp` can prove it
theorem subset_iInter₂_iff {s : Set α} {t : ∀ i, κ i → Set α} :
(s ⊆ ⋂ (i) (j), t i j) ↔ ∀ i j, s ⊆ t i j := by simp_rw [subset_iInter_iff]
#align set.subset_Inter₂_iff Set.subset_iInter₂_iff
theorem subset_iUnion : ∀ (s : ι → Set β) (i : ι), s i ⊆ ⋃ i, s i :=
le_iSup
#align set.subset_Union Set.subset_iUnion
theorem iInter_subset : ∀ (s : ι → Set β) (i : ι), ⋂ i, s i ⊆ s i :=
iInf_le
#align set.Inter_subset Set.iInter_subset
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem subset_iUnion₂ {s : ∀ i, κ i → Set α} (i : ι) (j : κ i) : s i j ⊆ ⋃ (i') (j'), s i' j' :=
le_iSup₂ i j
#align set.subset_Union₂ Set.subset_iUnion₂
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem iInter₂_subset {s : ∀ i, κ i → Set α} (i : ι) (j : κ i) : ⋂ (i) (j), s i j ⊆ s i j :=
iInf₂_le i j
#align set.Inter₂_subset Set.iInter₂_subset
/-- This rather trivial consequence of `subset_iUnion`is convenient with `apply`, and has `i`
explicit for this purpose. -/
theorem subset_iUnion_of_subset {s : Set α} {t : ι → Set α} (i : ι) (h : s ⊆ t i) : s ⊆ ⋃ i, t i :=
le_iSup_of_le i h
#align set.subset_Union_of_subset Set.subset_iUnion_of_subset
/-- This rather trivial consequence of `iInter_subset`is convenient with `apply`, and has `i`
explicit for this purpose. -/
theorem iInter_subset_of_subset {s : ι → Set α} {t : Set α} (i : ι) (h : s i ⊆ t) :
⋂ i, s i ⊆ t :=
iInf_le_of_le i h
#align set.Inter_subset_of_subset Set.iInter_subset_of_subset
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/-- This rather trivial consequence of `subset_iUnion₂` is convenient with `apply`, and has `i` and
`j` explicit for this purpose. -/
theorem subset_iUnion₂_of_subset {s : Set α} {t : ∀ i, κ i → Set α} (i : ι) (j : κ i)
(h : s ⊆ t i j) : s ⊆ ⋃ (i) (j), t i j :=
le_iSup₂_of_le i j h
#align set.subset_Union₂_of_subset Set.subset_iUnion₂_of_subset
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/-- This rather trivial consequence of `iInter₂_subset` is convenient with `apply`, and has `i` and
`j` explicit for this purpose. -/
theorem iInter₂_subset_of_subset {s : ∀ i, κ i → Set α} {t : Set α} (i : ι) (j : κ i)
(h : s i j ⊆ t) : ⋂ (i) (j), s i j ⊆ t :=
iInf₂_le_of_le i j h
#align set.Inter₂_subset_of_subset Set.iInter₂_subset_of_subset
theorem iUnion_mono {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : ⋃ i, s i ⊆ ⋃ i, t i :=
iSup_mono h
#align set.Union_mono Set.iUnion_mono
@[gcongr]
theorem iUnion_mono'' {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : iUnion s ⊆ iUnion t :=
iSup_mono h
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem iUnion₂_mono {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j ⊆ t i j) :
⋃ (i) (j), s i j ⊆ ⋃ (i) (j), t i j :=
iSup₂_mono h
#align set.Union₂_mono Set.iUnion₂_mono
theorem iInter_mono {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : ⋂ i, s i ⊆ ⋂ i, t i :=
iInf_mono h
#align set.Inter_mono Set.iInter_mono
@[gcongr]
theorem iInter_mono'' {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : iInter s ⊆ iInter t :=
iInf_mono h
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem iInter₂_mono {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j ⊆ t i j) :
⋂ (i) (j), s i j ⊆ ⋂ (i) (j), t i j :=
iInf₂_mono h
#align set.Inter₂_mono Set.iInter₂_mono
theorem iUnion_mono' {s : ι → Set α} {t : ι₂ → Set α} (h : ∀ i, ∃ j, s i ⊆ t j) :
⋃ i, s i ⊆ ⋃ i, t i :=
iSup_mono' h
#align set.Union_mono' Set.iUnion_mono'
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i' j') -/
theorem iUnion₂_mono' {s : ∀ i, κ i → Set α} {t : ∀ i', κ' i' → Set α}
(h : ∀ i j, ∃ i' j', s i j ⊆ t i' j') : ⋃ (i) (j), s i j ⊆ ⋃ (i') (j'), t i' j' :=
iSup₂_mono' h
#align set.Union₂_mono' Set.iUnion₂_mono'
theorem iInter_mono' {s : ι → Set α} {t : ι' → Set α} (h : ∀ j, ∃ i, s i ⊆ t j) :
⋂ i, s i ⊆ ⋂ j, t j :=
Set.subset_iInter fun j =>
let ⟨i, hi⟩ := h j
iInter_subset_of_subset i hi
#align set.Inter_mono' Set.iInter_mono'
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i' j') -/
theorem iInter₂_mono' {s : ∀ i, κ i → Set α} {t : ∀ i', κ' i' → Set α}
(h : ∀ i' j', ∃ i j, s i j ⊆ t i' j') : ⋂ (i) (j), s i j ⊆ ⋂ (i') (j'), t i' j' :=
subset_iInter₂_iff.2 fun i' j' =>
let ⟨_, _, hst⟩ := h i' j'
(iInter₂_subset _ _).trans hst
#align set.Inter₂_mono' Set.iInter₂_mono'
theorem iUnion₂_subset_iUnion (κ : ι → Sort*) (s : ι → Set α) :
⋃ (i) (_ : κ i), s i ⊆ ⋃ i, s i :=
iUnion_mono fun _ => iUnion_subset fun _ => Subset.rfl
#align set.Union₂_subset_Union Set.iUnion₂_subset_iUnion
theorem iInter_subset_iInter₂ (κ : ι → Sort*) (s : ι → Set α) :
⋂ i, s i ⊆ ⋂ (i) (_ : κ i), s i :=
iInter_mono fun _ => subset_iInter fun _ => Subset.rfl
#align set.Inter_subset_Inter₂ Set.iInter_subset_iInter₂
theorem iUnion_setOf (P : ι → α → Prop) : ⋃ i, { x : α | P i x } = { x : α | ∃ i, P i x } := by
ext
exact mem_iUnion
#align set.Union_set_of Set.iUnion_setOf
theorem iInter_setOf (P : ι → α → Prop) : ⋂ i, { x : α | P i x } = { x : α | ∀ i, P i x } := by
ext
exact mem_iInter
#align set.Inter_set_of Set.iInter_setOf
theorem iUnion_congr_of_surjective {f : ι → Set α} {g : ι₂ → Set α} (h : ι → ι₂) (h1 : Surjective h)
(h2 : ∀ x, g (h x) = f x) : ⋃ x, f x = ⋃ y, g y :=
h1.iSup_congr h h2
#align set.Union_congr_of_surjective Set.iUnion_congr_of_surjective
theorem iInter_congr_of_surjective {f : ι → Set α} {g : ι₂ → Set α} (h : ι → ι₂) (h1 : Surjective h)
(h2 : ∀ x, g (h x) = f x) : ⋂ x, f x = ⋂ y, g y :=
h1.iInf_congr h h2
#align set.Inter_congr_of_surjective Set.iInter_congr_of_surjective
lemma iUnion_congr {s t : ι → Set α} (h : ∀ i, s i = t i) : ⋃ i, s i = ⋃ i, t i := iSup_congr h
#align set.Union_congr Set.iUnion_congr
lemma iInter_congr {s t : ι → Set α} (h : ∀ i, s i = t i) : ⋂ i, s i = ⋂ i, t i := iInf_congr h
#align set.Inter_congr Set.iInter_congr
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
lemma iUnion₂_congr {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j = t i j) :
⋃ (i) (j), s i j = ⋃ (i) (j), t i j :=
iUnion_congr fun i => iUnion_congr <| h i
#align set.Union₂_congr Set.iUnion₂_congr
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
lemma iInter₂_congr {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j = t i j) :
⋂ (i) (j), s i j = ⋂ (i) (j), t i j :=
iInter_congr fun i => iInter_congr <| h i
#align set.Inter₂_congr Set.iInter₂_congr
section Nonempty
variable [Nonempty ι] {f : ι → Set α} {s : Set α}
lemma iUnion_const (s : Set β) : ⋃ _ : ι, s = s := iSup_const
#align set.Union_const Set.iUnion_const
lemma iInter_const (s : Set β) : ⋂ _ : ι, s = s := iInf_const
#align set.Inter_const Set.iInter_const
lemma iUnion_eq_const (hf : ∀ i, f i = s) : ⋃ i, f i = s :=
(iUnion_congr hf).trans <| iUnion_const _
#align set.Union_eq_const Set.iUnion_eq_const
lemma iInter_eq_const (hf : ∀ i, f i = s) : ⋂ i, f i = s :=
(iInter_congr hf).trans <| iInter_const _
#align set.Inter_eq_const Set.iInter_eq_const
end Nonempty
@[simp]
theorem compl_iUnion (s : ι → Set β) : (⋃ i, s i)ᶜ = ⋂ i, (s i)ᶜ :=
compl_iSup
#align set.compl_Union Set.compl_iUnion
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem compl_iUnion₂ (s : ∀ i, κ i → Set α) : (⋃ (i) (j), s i j)ᶜ = ⋂ (i) (j), (s i j)ᶜ := by
simp_rw [compl_iUnion]
#align set.compl_Union₂ Set.compl_iUnion₂
@[simp]
theorem compl_iInter (s : ι → Set β) : (⋂ i, s i)ᶜ = ⋃ i, (s i)ᶜ :=
compl_iInf
#align set.compl_Inter Set.compl_iInter
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem compl_iInter₂ (s : ∀ i, κ i → Set α) : (⋂ (i) (j), s i j)ᶜ = ⋃ (i) (j), (s i j)ᶜ := by
simp_rw [compl_iInter]
#align set.compl_Inter₂ Set.compl_iInter₂
-- classical -- complete_boolean_algebra
theorem iUnion_eq_compl_iInter_compl (s : ι → Set β) : ⋃ i, s i = (⋂ i, (s i)ᶜ)ᶜ := by
simp only [compl_iInter, compl_compl]
#align set.Union_eq_compl_Inter_compl Set.iUnion_eq_compl_iInter_compl
-- classical -- complete_boolean_algebra
theorem iInter_eq_compl_iUnion_compl (s : ι → Set β) : ⋂ i, s i = (⋃ i, (s i)ᶜ)ᶜ := by
simp only [compl_iUnion, compl_compl]
#align set.Inter_eq_compl_Union_compl Set.iInter_eq_compl_iUnion_compl
theorem inter_iUnion (s : Set β) (t : ι → Set β) : (s ∩ ⋃ i, t i) = ⋃ i, s ∩ t i :=
inf_iSup_eq _ _
#align set.inter_Union Set.inter_iUnion
theorem iUnion_inter (s : Set β) (t : ι → Set β) : (⋃ i, t i) ∩ s = ⋃ i, t i ∩ s :=
iSup_inf_eq _ _
#align set.Union_inter Set.iUnion_inter
theorem iUnion_union_distrib (s : ι → Set β) (t : ι → Set β) :
⋃ i, s i ∪ t i = (⋃ i, s i) ∪ ⋃ i, t i :=
iSup_sup_eq
#align set.Union_union_distrib Set.iUnion_union_distrib
theorem iInter_inter_distrib (s : ι → Set β) (t : ι → Set β) :
⋂ i, s i ∩ t i = (⋂ i, s i) ∩ ⋂ i, t i :=
iInf_inf_eq
#align set.Inter_inter_distrib Set.iInter_inter_distrib
theorem union_iUnion [Nonempty ι] (s : Set β) (t : ι → Set β) : (s ∪ ⋃ i, t i) = ⋃ i, s ∪ t i :=
sup_iSup
#align set.union_Union Set.union_iUnion
theorem iUnion_union [Nonempty ι] (s : Set β) (t : ι → Set β) : (⋃ i, t i) ∪ s = ⋃ i, t i ∪ s :=
iSup_sup
#align set.Union_union Set.iUnion_union
theorem inter_iInter [Nonempty ι] (s : Set β) (t : ι → Set β) : (s ∩ ⋂ i, t i) = ⋂ i, s ∩ t i :=
inf_iInf
#align set.inter_Inter Set.inter_iInter
theorem iInter_inter [Nonempty ι] (s : Set β) (t : ι → Set β) : (⋂ i, t i) ∩ s = ⋂ i, t i ∩ s :=
iInf_inf
#align set.Inter_inter Set.iInter_inter
-- classical
theorem union_iInter (s : Set β) (t : ι → Set β) : (s ∪ ⋂ i, t i) = ⋂ i, s ∪ t i :=
sup_iInf_eq _ _
#align set.union_Inter Set.union_iInter
theorem iInter_union (s : ι → Set β) (t : Set β) : (⋂ i, s i) ∪ t = ⋂ i, s i ∪ t :=
iInf_sup_eq _ _
#align set.Inter_union Set.iInter_union
theorem iUnion_diff (s : Set β) (t : ι → Set β) : (⋃ i, t i) \ s = ⋃ i, t i \ s :=
iUnion_inter _ _
#align set.Union_diff Set.iUnion_diff
theorem diff_iUnion [Nonempty ι] (s : Set β) (t : ι → Set β) : (s \ ⋃ i, t i) = ⋂ i, s \ t i := by
rw [diff_eq, compl_iUnion, inter_iInter]; rfl
#align set.diff_Union Set.diff_iUnion
theorem diff_iInter (s : Set β) (t : ι → Set β) : (s \ ⋂ i, t i) = ⋃ i, s \ t i := by
rw [diff_eq, compl_iInter, inter_iUnion]; rfl
#align set.diff_Inter Set.diff_iInter
theorem iUnion_inter_subset {ι α} {s t : ι → Set α} : ⋃ i, s i ∩ t i ⊆ (⋃ i, s i) ∩ ⋃ i, t i :=
le_iSup_inf_iSup s t
#align set.Union_inter_subset Set.iUnion_inter_subset
theorem iUnion_inter_of_monotone {ι α} [Preorder ι] [IsDirected ι (· ≤ ·)] {s t : ι → Set α}
(hs : Monotone s) (ht : Monotone t) : ⋃ i, s i ∩ t i = (⋃ i, s i) ∩ ⋃ i, t i :=
iSup_inf_of_monotone hs ht
#align set.Union_inter_of_monotone Set.iUnion_inter_of_monotone
theorem iUnion_inter_of_antitone {ι α} [Preorder ι] [IsDirected ι (swap (· ≤ ·))] {s t : ι → Set α}
(hs : Antitone s) (ht : Antitone t) : ⋃ i, s i ∩ t i = (⋃ i, s i) ∩ ⋃ i, t i :=
iSup_inf_of_antitone hs ht
#align set.Union_inter_of_antitone Set.iUnion_inter_of_antitone
theorem iInter_union_of_monotone {ι α} [Preorder ι] [IsDirected ι (swap (· ≤ ·))] {s t : ι → Set α}
(hs : Monotone s) (ht : Monotone t) : ⋂ i, s i ∪ t i = (⋂ i, s i) ∪ ⋂ i, t i :=
iInf_sup_of_monotone hs ht
#align set.Inter_union_of_monotone Set.iInter_union_of_monotone
theorem iInter_union_of_antitone {ι α} [Preorder ι] [IsDirected ι (· ≤ ·)] {s t : ι → Set α}
(hs : Antitone s) (ht : Antitone t) : ⋂ i, s i ∪ t i = (⋂ i, s i) ∪ ⋂ i, t i :=
iInf_sup_of_antitone hs ht
#align set.Inter_union_of_antitone Set.iInter_union_of_antitone
/-- An equality version of this lemma is `iUnion_iInter_of_monotone` in `Data.Set.Finite`. -/
theorem iUnion_iInter_subset {s : ι → ι' → Set α} : (⋃ j, ⋂ i, s i j) ⊆ ⋂ i, ⋃ j, s i j :=
iSup_iInf_le_iInf_iSup (flip s)
#align set.Union_Inter_subset Set.iUnion_iInter_subset
theorem iUnion_option {ι} (s : Option ι → Set α) : ⋃ o, s o = s none ∪ ⋃ i, s (some i) :=
iSup_option s
#align set.Union_option Set.iUnion_option
theorem iInter_option {ι} (s : Option ι → Set α) : ⋂ o, s o = s none ∩ ⋂ i, s (some i) :=
iInf_option s
#align set.Inter_option Set.iInter_option
section
variable (p : ι → Prop) [DecidablePred p]
theorem iUnion_dite (f : ∀ i, p i → Set α) (g : ∀ i, ¬p i → Set α) :
⋃ i, (if h : p i then f i h else g i h) = (⋃ (i) (h : p i), f i h) ∪ ⋃ (i) (h : ¬p i), g i h :=
iSup_dite _ _ _
#align set.Union_dite Set.iUnion_dite
theorem iUnion_ite (f g : ι → Set α) :
⋃ i, (if p i then f i else g i) = (⋃ (i) (_ : p i), f i) ∪ ⋃ (i) (_ : ¬p i), g i :=
iUnion_dite _ _ _
#align set.Union_ite Set.iUnion_ite
theorem iInter_dite (f : ∀ i, p i → Set α) (g : ∀ i, ¬p i → Set α) :
⋂ i, (if h : p i then f i h else g i h) = (⋂ (i) (h : p i), f i h) ∩ ⋂ (i) (h : ¬p i), g i h :=
iInf_dite _ _ _
#align set.Inter_dite Set.iInter_dite
theorem iInter_ite (f g : ι → Set α) :
⋂ i, (if p i then f i else g i) = (⋂ (i) (_ : p i), f i) ∩ ⋂ (i) (_ : ¬p i), g i :=
iInter_dite _ _ _
#align set.Inter_ite Set.iInter_ite
end
theorem image_projection_prod {ι : Type*} {α : ι → Type*} {v : ∀ i : ι, Set (α i)}
(hv : (pi univ v).Nonempty) (i : ι) :
((fun x : ∀ i : ι, α i => x i) '' ⋂ k, (fun x : ∀ j : ι, α j => x k) ⁻¹' v k) = v i := by
classical
apply Subset.antisymm
· simp [iInter_subset]
· intro y y_in
simp only [mem_image, mem_iInter, mem_preimage]
rcases hv with ⟨z, hz⟩
refine ⟨Function.update z i y, ?_, update_same i y z⟩
rw [@forall_update_iff ι α _ z i y fun i t => t ∈ v i]
exact ⟨y_in, fun j _ => by simpa using hz j⟩
#align set.image_projection_prod Set.image_projection_prod
/-! ### Unions and intersections indexed by `Prop` -/
theorem iInter_false {s : False → Set α} : iInter s = univ :=
iInf_false
#align set.Inter_false Set.iInter_false
theorem iUnion_false {s : False → Set α} : iUnion s = ∅ :=
iSup_false
#align set.Union_false Set.iUnion_false
@[simp]
theorem iInter_true {s : True → Set α} : iInter s = s trivial :=
iInf_true
#align set.Inter_true Set.iInter_true
@[simp]
theorem iUnion_true {s : True → Set α} : iUnion s = s trivial :=
iSup_true
#align set.Union_true Set.iUnion_true
@[simp]
theorem iInter_exists {p : ι → Prop} {f : Exists p → Set α} :
⋂ x, f x = ⋂ (i) (h : p i), f ⟨i, h⟩ :=
iInf_exists
#align set.Inter_exists Set.iInter_exists
@[simp]
theorem iUnion_exists {p : ι → Prop} {f : Exists p → Set α} :
⋃ x, f x = ⋃ (i) (h : p i), f ⟨i, h⟩ :=
iSup_exists
#align set.Union_exists Set.iUnion_exists
@[simp]
theorem iUnion_empty : (⋃ _ : ι, ∅ : Set α) = ∅ :=
iSup_bot
#align set.Union_empty Set.iUnion_empty
@[simp]
theorem iInter_univ : (⋂ _ : ι, univ : Set α) = univ :=
iInf_top
#align set.Inter_univ Set.iInter_univ
section
variable {s : ι → Set α}
@[simp]
theorem iUnion_eq_empty : ⋃ i, s i = ∅ ↔ ∀ i, s i = ∅ :=
iSup_eq_bot
#align set.Union_eq_empty Set.iUnion_eq_empty
@[simp]
theorem iInter_eq_univ : ⋂ i, s i = univ ↔ ∀ i, s i = univ :=
iInf_eq_top
#align set.Inter_eq_univ Set.iInter_eq_univ
@[simp]
theorem nonempty_iUnion : (⋃ i, s i).Nonempty ↔ ∃ i, (s i).Nonempty := by
simp [nonempty_iff_ne_empty]
#align set.nonempty_Union Set.nonempty_iUnion
-- Porting note (#10618): removing `simp`. `simp` can prove it
theorem nonempty_biUnion {t : Set α} {s : α → Set β} :
(⋃ i ∈ t, s i).Nonempty ↔ ∃ i ∈ t, (s i).Nonempty := by simp
#align set.nonempty_bUnion Set.nonempty_biUnion
theorem iUnion_nonempty_index (s : Set α) (t : s.Nonempty → Set β) :
⋃ h, t h = ⋃ x ∈ s, t ⟨x, ‹_›⟩ :=
iSup_exists
#align set.Union_nonempty_index Set.iUnion_nonempty_index
end
@[simp]
theorem iInter_iInter_eq_left {b : β} {s : ∀ x : β, x = b → Set α} :
⋂ (x) (h : x = b), s x h = s b rfl :=
iInf_iInf_eq_left
#align set.Inter_Inter_eq_left Set.iInter_iInter_eq_left
@[simp]
theorem iInter_iInter_eq_right {b : β} {s : ∀ x : β, b = x → Set α} :
⋂ (x) (h : b = x), s x h = s b rfl :=
iInf_iInf_eq_right
#align set.Inter_Inter_eq_right Set.iInter_iInter_eq_right
@[simp]
theorem iUnion_iUnion_eq_left {b : β} {s : ∀ x : β, x = b → Set α} :
⋃ (x) (h : x = b), s x h = s b rfl :=
iSup_iSup_eq_left
#align set.Union_Union_eq_left Set.iUnion_iUnion_eq_left
@[simp]
theorem iUnion_iUnion_eq_right {b : β} {s : ∀ x : β, b = x → Set α} :
⋃ (x) (h : b = x), s x h = s b rfl :=
iSup_iSup_eq_right
#align set.Union_Union_eq_right Set.iUnion_iUnion_eq_right
theorem iInter_or {p q : Prop} (s : p ∨ q → Set α) :
⋂ h, s h = (⋂ h : p, s (Or.inl h)) ∩ ⋂ h : q, s (Or.inr h) :=
iInf_or
#align set.Inter_or Set.iInter_or
theorem iUnion_or {p q : Prop} (s : p ∨ q → Set α) :
⋃ h, s h = (⋃ i, s (Or.inl i)) ∪ ⋃ j, s (Or.inr j) :=
iSup_or
#align set.Union_or Set.iUnion_or
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (hp hq) -/
theorem iUnion_and {p q : Prop} (s : p ∧ q → Set α) : ⋃ h, s h = ⋃ (hp) (hq), s ⟨hp, hq⟩ :=
iSup_and
#align set.Union_and Set.iUnion_and
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (hp hq) -/
theorem iInter_and {p q : Prop} (s : p ∧ q → Set α) : ⋂ h, s h = ⋂ (hp) (hq), s ⟨hp, hq⟩ :=
iInf_and
#align set.Inter_and Set.iInter_and
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i i') -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i' i) -/
theorem iUnion_comm (s : ι → ι' → Set α) : ⋃ (i) (i'), s i i' = ⋃ (i') (i), s i i' :=
iSup_comm
#align set.Union_comm Set.iUnion_comm
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i i') -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i' i) -/
theorem iInter_comm (s : ι → ι' → Set α) : ⋂ (i) (i'), s i i' = ⋂ (i') (i), s i i' :=
iInf_comm
#align set.Inter_comm Set.iInter_comm
theorem iUnion_sigma {γ : α → Type*} (s : Sigma γ → Set β) : ⋃ ia, s ia = ⋃ i, ⋃ a, s ⟨i, a⟩ :=
iSup_sigma
theorem iUnion_sigma' {γ : α → Type*} (s : ∀ i, γ i → Set β) :
⋃ i, ⋃ a, s i a = ⋃ ia : Sigma γ, s ia.1 ia.2 :=
iSup_sigma' _
theorem iInter_sigma {γ : α → Type*} (s : Sigma γ → Set β) : ⋂ ia, s ia = ⋂ i, ⋂ a, s ⟨i, a⟩ :=
iInf_sigma
theorem iInter_sigma' {γ : α → Type*} (s : ∀ i, γ i → Set β) :
⋂ i, ⋂ a, s i a = ⋂ ia : Sigma γ, s ia.1 ia.2 :=
iInf_sigma' _
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i₁ j₁ i₂ j₂) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i₂ j₂ i₁ j₁) -/
theorem iUnion₂_comm (s : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Set α) :
⋃ (i₁) (j₁) (i₂) (j₂), s i₁ j₁ i₂ j₂ = ⋃ (i₂) (j₂) (i₁) (j₁), s i₁ j₁ i₂ j₂ :=
iSup₂_comm _
#align set.Union₂_comm Set.iUnion₂_comm
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i₁ j₁ i₂ j₂) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i₂ j₂ i₁ j₁) -/
theorem iInter₂_comm (s : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Set α) :
⋂ (i₁) (j₁) (i₂) (j₂), s i₁ j₁ i₂ j₂ = ⋂ (i₂) (j₂) (i₁) (j₁), s i₁ j₁ i₂ j₂ :=
iInf₂_comm _
#align set.Inter₂_comm Set.iInter₂_comm
@[simp]
theorem biUnion_and (p : ι → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p x ∧ q x y → Set α) :
⋃ (x : ι) (y : ι') (h : p x ∧ q x y), s x y h =
⋃ (x : ι) (hx : p x) (y : ι') (hy : q x y), s x y ⟨hx, hy⟩ := by
simp only [iUnion_and, @iUnion_comm _ ι']
#align set.bUnion_and Set.biUnion_and
@[simp]
theorem biUnion_and' (p : ι' → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p y ∧ q x y → Set α) :
⋃ (x : ι) (y : ι') (h : p y ∧ q x y), s x y h =
⋃ (y : ι') (hy : p y) (x : ι) (hx : q x y), s x y ⟨hy, hx⟩ := by
simp only [iUnion_and, @iUnion_comm _ ι]
#align set.bUnion_and' Set.biUnion_and'
@[simp]
theorem biInter_and (p : ι → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p x ∧ q x y → Set α) :
⋂ (x : ι) (y : ι') (h : p x ∧ q x y), s x y h =
⋂ (x : ι) (hx : p x) (y : ι') (hy : q x y), s x y ⟨hx, hy⟩ := by
simp only [iInter_and, @iInter_comm _ ι']
#align set.bInter_and Set.biInter_and
@[simp]
theorem biInter_and' (p : ι' → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p y ∧ q x y → Set α) :
⋂ (x : ι) (y : ι') (h : p y ∧ q x y), s x y h =
⋂ (y : ι') (hy : p y) (x : ι) (hx : q x y), s x y ⟨hy, hx⟩ := by
simp only [iInter_and, @iInter_comm _ ι]
#align set.bInter_and' Set.biInter_and'
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (x h) -/
@[simp]
theorem iUnion_iUnion_eq_or_left {b : β} {p : β → Prop} {s : ∀ x : β, x = b ∨ p x → Set α} :
⋃ (x) (h), s x h = s b (Or.inl rfl) ∪ ⋃ (x) (h : p x), s x (Or.inr h) := by
simp only [iUnion_or, iUnion_union_distrib, iUnion_iUnion_eq_left]
#align set.Union_Union_eq_or_left Set.iUnion_iUnion_eq_or_left
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (x h) -/
@[simp]
theorem iInter_iInter_eq_or_left {b : β} {p : β → Prop} {s : ∀ x : β, x = b ∨ p x → Set α} :
⋂ (x) (h), s x h = s b (Or.inl rfl) ∩ ⋂ (x) (h : p x), s x (Or.inr h) := by
simp only [iInter_or, iInter_inter_distrib, iInter_iInter_eq_left]
#align set.Inter_Inter_eq_or_left Set.iInter_iInter_eq_or_left
/-! ### Bounded unions and intersections -/
/-- A specialization of `mem_iUnion₂`. -/
theorem mem_biUnion {s : Set α} {t : α → Set β} {x : α} {y : β} (xs : x ∈ s) (ytx : y ∈ t x) :
y ∈ ⋃ x ∈ s, t x :=
mem_iUnion₂_of_mem xs ytx
#align set.mem_bUnion Set.mem_biUnion
/-- A specialization of `mem_iInter₂`. -/
theorem mem_biInter {s : Set α} {t : α → Set β} {y : β} (h : ∀ x ∈ s, y ∈ t x) :
y ∈ ⋂ x ∈ s, t x :=
mem_iInter₂_of_mem h
#align set.mem_bInter Set.mem_biInter
/-- A specialization of `subset_iUnion₂`. -/
theorem subset_biUnion_of_mem {s : Set α} {u : α → Set β} {x : α} (xs : x ∈ s) :
u x ⊆ ⋃ x ∈ s, u x :=
-- Porting note: Why is this not just `subset_iUnion₂ x xs`?
@subset_iUnion₂ β α (· ∈ s) (fun i _ => u i) x xs
#align set.subset_bUnion_of_mem Set.subset_biUnion_of_mem
/-- A specialization of `iInter₂_subset`. -/
theorem biInter_subset_of_mem {s : Set α} {t : α → Set β} {x : α} (xs : x ∈ s) :
⋂ x ∈ s, t x ⊆ t x :=
iInter₂_subset x xs
#align set.bInter_subset_of_mem Set.biInter_subset_of_mem
theorem biUnion_subset_biUnion_left {s s' : Set α} {t : α → Set β} (h : s ⊆ s') :
⋃ x ∈ s, t x ⊆ ⋃ x ∈ s', t x :=
iUnion₂_subset fun _ hx => subset_biUnion_of_mem <| h hx
#align set.bUnion_subset_bUnion_left Set.biUnion_subset_biUnion_left
theorem biInter_subset_biInter_left {s s' : Set α} {t : α → Set β} (h : s' ⊆ s) :
⋂ x ∈ s, t x ⊆ ⋂ x ∈ s', t x :=
subset_iInter₂ fun _ hx => biInter_subset_of_mem <| h hx
#align set.bInter_subset_bInter_left Set.biInter_subset_biInter_left
theorem biUnion_mono {s s' : Set α} {t t' : α → Set β} (hs : s' ⊆ s) (h : ∀ x ∈ s, t x ⊆ t' x) :
⋃ x ∈ s', t x ⊆ ⋃ x ∈ s, t' x :=
(biUnion_subset_biUnion_left hs).trans <| iUnion₂_mono h
#align set.bUnion_mono Set.biUnion_mono
theorem biInter_mono {s s' : Set α} {t t' : α → Set β} (hs : s ⊆ s') (h : ∀ x ∈ s, t x ⊆ t' x) :
⋂ x ∈ s', t x ⊆ ⋂ x ∈ s, t' x :=
(biInter_subset_biInter_left hs).trans <| iInter₂_mono h
#align set.bInter_mono Set.biInter_mono
theorem biUnion_eq_iUnion (s : Set α) (t : ∀ x ∈ s, Set β) :
⋃ x ∈ s, t x ‹_› = ⋃ x : s, t x x.2 :=
iSup_subtype'
#align set.bUnion_eq_Union Set.biUnion_eq_iUnion
theorem biInter_eq_iInter (s : Set α) (t : ∀ x ∈ s, Set β) :
⋂ x ∈ s, t x ‹_› = ⋂ x : s, t x x.2 :=
iInf_subtype'
#align set.bInter_eq_Inter Set.biInter_eq_iInter
theorem iUnion_subtype (p : α → Prop) (s : { x // p x } → Set β) :
⋃ x : { x // p x }, s x = ⋃ (x) (hx : p x), s ⟨x, hx⟩ :=
iSup_subtype
#align set.Union_subtype Set.iUnion_subtype
theorem iInter_subtype (p : α → Prop) (s : { x // p x } → Set β) :
⋂ x : { x // p x }, s x = ⋂ (x) (hx : p x), s ⟨x, hx⟩ :=
iInf_subtype
#align set.Inter_subtype Set.iInter_subtype
theorem biInter_empty (u : α → Set β) : ⋂ x ∈ (∅ : Set α), u x = univ :=
iInf_emptyset
#align set.bInter_empty Set.biInter_empty
theorem biInter_univ (u : α → Set β) : ⋂ x ∈ @univ α, u x = ⋂ x, u x :=
iInf_univ
#align set.bInter_univ Set.biInter_univ
@[simp]
theorem biUnion_self (s : Set α) : ⋃ x ∈ s, s = s :=
Subset.antisymm (iUnion₂_subset fun _ _ => Subset.refl s) fun _ hx => mem_biUnion hx hx
#align set.bUnion_self Set.biUnion_self
@[simp]
theorem iUnion_nonempty_self (s : Set α) : ⋃ _ : s.Nonempty, s = s := by
rw [iUnion_nonempty_index, biUnion_self]
#align set.Union_nonempty_self Set.iUnion_nonempty_self
theorem biInter_singleton (a : α) (s : α → Set β) : ⋂ x ∈ ({a} : Set α), s x = s a :=
iInf_singleton
#align set.bInter_singleton Set.biInter_singleton
theorem biInter_union (s t : Set α) (u : α → Set β) :
⋂ x ∈ s ∪ t, u x = (⋂ x ∈ s, u x) ∩ ⋂ x ∈ t, u x :=
iInf_union
#align set.bInter_union Set.biInter_union
theorem biInter_insert (a : α) (s : Set α) (t : α → Set β) :
⋂ x ∈ insert a s, t x = t a ∩ ⋂ x ∈ s, t x := by simp
#align set.bInter_insert Set.biInter_insert
| Mathlib/Data/Set/Lattice.lean | 913 | 914 | theorem biInter_pair (a b : α) (s : α → Set β) : ⋂ x ∈ ({a, b} : Set α), s x = s a ∩ s b := by |
rw [biInter_insert, biInter_singleton]
|
/-
Copyright (c) 2021 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth, Eric Wieser
-/
import Mathlib.Analysis.NormedSpace.PiLp
import Mathlib.Analysis.InnerProductSpace.PiL2
#align_import analysis.matrix from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Matrices as a normed space
In this file we provide the following non-instances for norms on matrices:
* The elementwise norm:
* `Matrix.seminormedAddCommGroup`
* `Matrix.normedAddCommGroup`
* `Matrix.normedSpace`
* `Matrix.boundedSMul`
* The Frobenius norm:
* `Matrix.frobeniusSeminormedAddCommGroup`
* `Matrix.frobeniusNormedAddCommGroup`
* `Matrix.frobeniusNormedSpace`
* `Matrix.frobeniusNormedRing`
* `Matrix.frobeniusNormedAlgebra`
* `Matrix.frobeniusBoundedSMul`
* The $L^\infty$ operator norm:
* `Matrix.linftyOpSeminormedAddCommGroup`
* `Matrix.linftyOpNormedAddCommGroup`
* `Matrix.linftyOpNormedSpace`
* `Matrix.linftyOpBoundedSMul`
* `Matrix.linftyOpNonUnitalSemiNormedRing`
* `Matrix.linftyOpSemiNormedRing`
* `Matrix.linftyOpNonUnitalNormedRing`
* `Matrix.linftyOpNormedRing`
* `Matrix.linftyOpNormedAlgebra`
These are not declared as instances because there are several natural choices for defining the norm
of a matrix.
The norm induced by the identification of `Matrix m n 𝕜` with
`EuclideanSpace n 𝕜 →L[𝕜] EuclideanSpace m 𝕜` (i.e., the ℓ² operator norm) can be found in
`Analysis.NormedSpace.Star.Matrix`. It is separated to avoid extraneous imports in this file.
-/
noncomputable section
open scoped NNReal Matrix
namespace Matrix
variable {R l m n α β : Type*} [Fintype l] [Fintype m] [Fintype n]
/-! ### The elementwise supremum norm -/
section LinfLinf
section SeminormedAddCommGroup
variable [SeminormedAddCommGroup α] [SeminormedAddCommGroup β]
/-- Seminormed group instance (using sup norm of sup norm) for matrices over a seminormed group. Not
declared as an instance because there are several natural choices for defining the norm of a
matrix. -/
protected def seminormedAddCommGroup : SeminormedAddCommGroup (Matrix m n α) :=
Pi.seminormedAddCommGroup
#align matrix.seminormed_add_comm_group Matrix.seminormedAddCommGroup
attribute [local instance] Matrix.seminormedAddCommGroup
-- Porting note (#10756): new theorem (along with all the uses of this lemma below)
theorem norm_def (A : Matrix m n α) : ‖A‖ = ‖fun i j => A i j‖ := rfl
/-- The norm of a matrix is the sup of the sup of the nnnorm of the entries -/
lemma norm_eq_sup_sup_nnnorm (A : Matrix m n α) :
‖A‖ = Finset.sup Finset.univ fun i ↦ Finset.sup Finset.univ fun j ↦ ‖A i j‖₊ := by
simp_rw [Matrix.norm_def, Pi.norm_def, Pi.nnnorm_def]
-- Porting note (#10756): new theorem (along with all the uses of this lemma below)
theorem nnnorm_def (A : Matrix m n α) : ‖A‖₊ = ‖fun i j => A i j‖₊ := rfl
theorem norm_le_iff {r : ℝ} (hr : 0 ≤ r) {A : Matrix m n α} : ‖A‖ ≤ r ↔ ∀ i j, ‖A i j‖ ≤ r := by
simp_rw [norm_def, pi_norm_le_iff_of_nonneg hr]
#align matrix.norm_le_iff Matrix.norm_le_iff
theorem nnnorm_le_iff {r : ℝ≥0} {A : Matrix m n α} : ‖A‖₊ ≤ r ↔ ∀ i j, ‖A i j‖₊ ≤ r := by
simp_rw [nnnorm_def, pi_nnnorm_le_iff]
#align matrix.nnnorm_le_iff Matrix.nnnorm_le_iff
theorem norm_lt_iff {r : ℝ} (hr : 0 < r) {A : Matrix m n α} : ‖A‖ < r ↔ ∀ i j, ‖A i j‖ < r := by
simp_rw [norm_def, pi_norm_lt_iff hr]
#align matrix.norm_lt_iff Matrix.norm_lt_iff
| Mathlib/Analysis/Matrix.lean | 102 | 104 | theorem nnnorm_lt_iff {r : ℝ≥0} (hr : 0 < r) {A : Matrix m n α} :
‖A‖₊ < r ↔ ∀ i j, ‖A i j‖₊ < r := by |
simp_rw [nnnorm_def, pi_nnnorm_lt_iff hr]
|
/-
Copyright (c) 2022 Jireh Loreaux. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jireh Loreaux
-/
import Mathlib.Algebra.Group.Subsemigroup.Basic
#align_import group_theory.subsemigroup.membership from "leanprover-community/mathlib"@"6cb77a8eaff0ddd100e87b1591c6d3ad319514ff"
/-!
# Subsemigroups: membership criteria
In this file we prove various facts about membership in a subsemigroup.
The intent is to mimic `GroupTheory/Submonoid/Membership`, but currently this file is mostly a
stub and only provides rudimentary support.
* `mem_iSup_of_directed`, `coe_iSup_of_directed`, `mem_sSup_of_directed_on`,
`coe_sSup_of_directed_on`: the supremum of a directed collection of subsemigroup is their union.
## TODO
* Define the `FreeSemigroup` generated by a set. This might require some rather substantial
additions to low-level API. For example, developing the subtype of nonempty lists, then defining
a product on nonempty lists, powers where the exponent is a positive natural, et cetera.
Another option would be to define the `FreeSemigroup` as the subsemigroup (pushed to be a
semigroup) of the `FreeMonoid` consisting of non-identity elements.
## Tags
subsemigroup
-/
assert_not_exists MonoidWithZero
variable {ι : Sort*} {M A B : Type*}
section NonAssoc
variable [Mul M]
open Set
namespace Subsemigroup
-- TODO: this section can be generalized to `[MulMemClass B M] [CompleteLattice B]`
-- such that `complete_lattice.le` coincides with `set_like.le`
@[to_additive]
theorem mem_iSup_of_directed {S : ι → Subsemigroup M} (hS : Directed (· ≤ ·) S) {x : M} :
(x ∈ ⨆ i, S i) ↔ ∃ i, x ∈ S i := by
refine ⟨?_, fun ⟨i, hi⟩ ↦ le_iSup S i hi⟩
suffices x ∈ closure (⋃ i, (S i : Set M)) → ∃ i, x ∈ S i by
simpa only [closure_iUnion, closure_eq (S _)] using this
refine fun hx ↦ closure_induction hx (fun y hy ↦ mem_iUnion.mp hy) ?_
rintro x y ⟨i, hi⟩ ⟨j, hj⟩
rcases hS i j with ⟨k, hki, hkj⟩
exact ⟨k, (S k).mul_mem (hki hi) (hkj hj)⟩
#align subsemigroup.mem_supr_of_directed Subsemigroup.mem_iSup_of_directed
#align add_subsemigroup.mem_supr_of_directed AddSubsemigroup.mem_iSup_of_directed
@[to_additive]
theorem coe_iSup_of_directed {S : ι → Subsemigroup M} (hS : Directed (· ≤ ·) S) :
((⨆ i, S i : Subsemigroup M) : Set M) = ⋃ i, S i :=
Set.ext fun x => by simp [mem_iSup_of_directed hS]
#align subsemigroup.coe_supr_of_directed Subsemigroup.coe_iSup_of_directed
#align add_subsemigroup.coe_supr_of_directed AddSubsemigroup.coe_iSup_of_directed
@[to_additive]
| Mathlib/Algebra/Group/Subsemigroup/Membership.lean | 67 | 70 | theorem mem_sSup_of_directed_on {S : Set (Subsemigroup M)} (hS : DirectedOn (· ≤ ·) S) {x : M} :
x ∈ sSup S ↔ ∃ s ∈ S, x ∈ s := by |
simp only [sSup_eq_iSup', mem_iSup_of_directed hS.directed_val, SetCoe.exists, Subtype.coe_mk,
exists_prop]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Devon Tuma
-/
import Mathlib.Probability.ProbabilityMassFunction.Monad
#align_import probability.probability_mass_function.constructions from "leanprover-community/mathlib"@"4ac69b290818724c159de091daa3acd31da0ee6d"
/-!
# Specific Constructions of Probability Mass Functions
This file gives a number of different `PMF` constructions for common probability distributions.
`map` and `seq` allow pushing a `PMF α` along a function `f : α → β` (or distribution of
functions `f : PMF (α → β)`) to get a `PMF β`.
`ofFinset` and `ofFintype` simplify the construction of a `PMF α` from a function `f : α → ℝ≥0∞`,
by allowing the "sum equals 1" constraint to be in terms of `Finset.sum` instead of `tsum`.
`normalize` constructs a `PMF α` by normalizing a function `f : α → ℝ≥0∞` by its sum,
and `filter` uses this to filter the support of a `PMF` and re-normalize the new distribution.
`bernoulli` represents the bernoulli distribution on `Bool`.
-/
universe u
namespace PMF
noncomputable section
variable {α β γ : Type*}
open scoped Classical
open NNReal ENNReal
section Map
/-- The functorial action of a function on a `PMF`. -/
def map (f : α → β) (p : PMF α) : PMF β :=
bind p (pure ∘ f)
#align pmf.map PMF.map
variable (f : α → β) (p : PMF α) (b : β)
theorem monad_map_eq_map {α β : Type u} (f : α → β) (p : PMF α) : f <$> p = p.map f := rfl
#align pmf.monad_map_eq_map PMF.monad_map_eq_map
@[simp]
theorem map_apply : (map f p) b = ∑' a, if b = f a then p a else 0 := by simp [map]
#align pmf.map_apply PMF.map_apply
@[simp]
theorem support_map : (map f p).support = f '' p.support :=
Set.ext fun b => by simp [map, @eq_comm β b]
#align pmf.support_map PMF.support_map
theorem mem_support_map_iff : b ∈ (map f p).support ↔ ∃ a ∈ p.support, f a = b := by simp
#align pmf.mem_support_map_iff PMF.mem_support_map_iff
theorem bind_pure_comp : bind p (pure ∘ f) = map f p := rfl
#align pmf.bind_pure_comp PMF.bind_pure_comp
theorem map_id : map id p = p :=
bind_pure _
#align pmf.map_id PMF.map_id
theorem map_comp (g : β → γ) : (p.map f).map g = p.map (g ∘ f) := by simp [map, Function.comp]
#align pmf.map_comp PMF.map_comp
theorem pure_map (a : α) : (pure a).map f = pure (f a) :=
pure_bind _ _
#align pmf.pure_map PMF.pure_map
theorem map_bind (q : α → PMF β) (f : β → γ) : (p.bind q).map f = p.bind fun a => (q a).map f :=
bind_bind _ _ _
#align pmf.map_bind PMF.map_bind
@[simp]
theorem bind_map (p : PMF α) (f : α → β) (q : β → PMF γ) : (p.map f).bind q = p.bind (q ∘ f) :=
(bind_bind _ _ _).trans (congr_arg _ (funext fun _ => pure_bind _ _))
#align pmf.bind_map PMF.bind_map
@[simp]
theorem map_const : p.map (Function.const α b) = pure b := by
simp only [map, Function.comp, bind_const, Function.const]
#align pmf.map_const PMF.map_const
section Measure
variable (s : Set β)
@[simp]
theorem toOuterMeasure_map_apply : (p.map f).toOuterMeasure s = p.toOuterMeasure (f ⁻¹' s) := by
simp [map, Set.indicator, toOuterMeasure_apply p (f ⁻¹' s)]
#align pmf.to_outer_measure_map_apply PMF.toOuterMeasure_map_apply
@[simp]
theorem toMeasure_map_apply [MeasurableSpace α] [MeasurableSpace β] (hf : Measurable f)
(hs : MeasurableSet s) : (p.map f).toMeasure s = p.toMeasure (f ⁻¹' s) := by
rw [toMeasure_apply_eq_toOuterMeasure_apply _ s hs,
toMeasure_apply_eq_toOuterMeasure_apply _ (f ⁻¹' s) (measurableSet_preimage hf hs)]
exact toOuterMeasure_map_apply f p s
#align pmf.to_measure_map_apply PMF.toMeasure_map_apply
end Measure
end Map
section Seq
/-- The monadic sequencing operation for `PMF`. -/
def seq (q : PMF (α → β)) (p : PMF α) : PMF β :=
q.bind fun m => p.bind fun a => pure (m a)
#align pmf.seq PMF.seq
variable (q : PMF (α → β)) (p : PMF α) (b : β)
theorem monad_seq_eq_seq {α β : Type u} (q : PMF (α → β)) (p : PMF α) : q <*> p = q.seq p := rfl
#align pmf.monad_seq_eq_seq PMF.monad_seq_eq_seq
@[simp]
theorem seq_apply : (seq q p) b = ∑' (f : α → β) (a : α), if b = f a then q f * p a else 0 := by
simp only [seq, mul_boole, bind_apply, pure_apply]
refine tsum_congr fun f => ENNReal.tsum_mul_left.symm.trans (tsum_congr fun a => ?_)
simpa only [mul_zero] using mul_ite (b = f a) (q f) (p a) 0
#align pmf.seq_apply PMF.seq_apply
@[simp]
theorem support_seq : (seq q p).support = ⋃ f ∈ q.support, f '' p.support :=
Set.ext fun b => by simp [-mem_support_iff, seq, @eq_comm β b]
#align pmf.support_seq PMF.support_seq
theorem mem_support_seq_iff : b ∈ (seq q p).support ↔ ∃ f ∈ q.support, b ∈ f '' p.support := by simp
#align pmf.mem_support_seq_iff PMF.mem_support_seq_iff
end Seq
instance : LawfulFunctor PMF where
map_const := rfl
id_map := bind_pure
comp_map _ _ _ := (map_comp _ _ _).symm
instance : LawfulMonad PMF := LawfulMonad.mk'
(bind_pure_comp := fun f x => rfl)
(id_map := id_map)
(pure_bind := pure_bind)
(bind_assoc := bind_bind)
section OfFinset
/-- Given a finset `s` and a function `f : α → ℝ≥0∞` with sum `1` on `s`,
such that `f a = 0` for `a ∉ s`, we get a `PMF`. -/
def ofFinset (f : α → ℝ≥0∞) (s : Finset α) (h : ∑ a ∈ s, f a = 1)
(h' : ∀ (a) (_ : a ∉ s), f a = 0) : PMF α :=
⟨f, h ▸ hasSum_sum_of_ne_finset_zero h'⟩
#align pmf.of_finset PMF.ofFinset
variable {f : α → ℝ≥0∞} {s : Finset α} (h : ∑ a ∈ s, f a = 1) (h' : ∀ (a) (_ : a ∉ s), f a = 0)
@[simp]
theorem ofFinset_apply (a : α) : ofFinset f s h h' a = f a := rfl
#align pmf.of_finset_apply PMF.ofFinset_apply
@[simp]
theorem support_ofFinset : (ofFinset f s h h').support = ↑s ∩ Function.support f :=
Set.ext fun a => by simpa [mem_support_iff] using mt (h' a)
#align pmf.support_of_finset PMF.support_ofFinset
theorem mem_support_ofFinset_iff (a : α) : a ∈ (ofFinset f s h h').support ↔ a ∈ s ∧ f a ≠ 0 := by
simp
#align pmf.mem_support_of_finset_iff PMF.mem_support_ofFinset_iff
theorem ofFinset_apply_of_not_mem {a : α} (ha : a ∉ s) : ofFinset f s h h' a = 0 :=
h' a ha
#align pmf.of_finset_apply_of_not_mem PMF.ofFinset_apply_of_not_mem
section Measure
variable (t : Set α)
@[simp]
theorem toOuterMeasure_ofFinset_apply :
(ofFinset f s h h').toOuterMeasure t = ∑' x, t.indicator f x :=
toOuterMeasure_apply (ofFinset f s h h') t
#align pmf.to_outer_measure_of_finset_apply PMF.toOuterMeasure_ofFinset_apply
@[simp]
theorem toMeasure_ofFinset_apply [MeasurableSpace α] (ht : MeasurableSet t) :
(ofFinset f s h h').toMeasure t = ∑' x, t.indicator f x :=
(toMeasure_apply_eq_toOuterMeasure_apply _ t ht).trans (toOuterMeasure_ofFinset_apply h h' t)
#align pmf.to_measure_of_finset_apply PMF.toMeasure_ofFinset_apply
end Measure
end OfFinset
section OfFintype
/-- Given a finite type `α` and a function `f : α → ℝ≥0∞` with sum 1, we get a `PMF`. -/
def ofFintype [Fintype α] (f : α → ℝ≥0∞) (h : ∑ a, f a = 1) : PMF α :=
ofFinset f Finset.univ h fun a ha => absurd (Finset.mem_univ a) ha
#align pmf.of_fintype PMF.ofFintype
variable [Fintype α] {f : α → ℝ≥0∞} (h : ∑ a, f a = 1)
@[simp]
theorem ofFintype_apply (a : α) : ofFintype f h a = f a := rfl
#align pmf.of_fintype_apply PMF.ofFintype_apply
@[simp]
theorem support_ofFintype : (ofFintype f h).support = Function.support f := rfl
#align pmf.support_of_fintype PMF.support_ofFintype
theorem mem_support_ofFintype_iff (a : α) : a ∈ (ofFintype f h).support ↔ f a ≠ 0 := Iff.rfl
#align pmf.mem_support_of_fintype_iff PMF.mem_support_ofFintype_iff
section Measure
variable (s : Set α)
@[simp high]
theorem toOuterMeasure_ofFintype_apply : (ofFintype f h).toOuterMeasure s = ∑' x, s.indicator f x :=
toOuterMeasure_apply (ofFintype f h) s
#align pmf.to_outer_measure_of_fintype_apply PMF.toOuterMeasure_ofFintype_apply
@[simp]
theorem toMeasure_ofFintype_apply [MeasurableSpace α] (hs : MeasurableSet s) :
(ofFintype f h).toMeasure s = ∑' x, s.indicator f x :=
(toMeasure_apply_eq_toOuterMeasure_apply _ s hs).trans (toOuterMeasure_ofFintype_apply h s)
#align pmf.to_measure_of_fintype_apply PMF.toMeasure_ofFintype_apply
end Measure
end OfFintype
section normalize
/-- Given an `f` with non-zero and non-infinite sum, get a `PMF` by normalizing `f` by its `tsum`.
-/
def normalize (f : α → ℝ≥0∞) (hf0 : tsum f ≠ 0) (hf : tsum f ≠ ∞) : PMF α :=
⟨fun a => f a * (∑' x, f x)⁻¹,
ENNReal.summable.hasSum_iff.2 (ENNReal.tsum_mul_right.trans (ENNReal.mul_inv_cancel hf0 hf))⟩
#align pmf.normalize PMF.normalize
variable {f : α → ℝ≥0∞} (hf0 : tsum f ≠ 0) (hf : tsum f ≠ ∞)
@[simp]
theorem normalize_apply (a : α) : (normalize f hf0 hf) a = f a * (∑' x, f x)⁻¹ := rfl
#align pmf.normalize_apply PMF.normalize_apply
@[simp]
theorem support_normalize : (normalize f hf0 hf).support = Function.support f :=
Set.ext fun a => by simp [hf, mem_support_iff]
#align pmf.support_normalize PMF.support_normalize
theorem mem_support_normalize_iff (a : α) : a ∈ (normalize f hf0 hf).support ↔ f a ≠ 0 := by simp
#align pmf.mem_support_normalize_iff PMF.mem_support_normalize_iff
end normalize
section Filter
/-- Create new `PMF` by filtering on a set with non-zero measure and normalizing. -/
def filter (p : PMF α) (s : Set α) (h : ∃ a ∈ s, a ∈ p.support) : PMF α :=
PMF.normalize (s.indicator p) (by simpa using h) (p.tsum_coe_indicator_ne_top s)
#align pmf.filter PMF.filter
variable {p : PMF α} {s : Set α} (h : ∃ a ∈ s, a ∈ p.support)
@[simp]
theorem filter_apply (a : α) :
(p.filter s h) a = s.indicator p a * (∑' a', (s.indicator p) a')⁻¹ := by
rw [filter, normalize_apply]
#align pmf.filter_apply PMF.filter_apply
theorem filter_apply_eq_zero_of_not_mem {a : α} (ha : a ∉ s) : (p.filter s h) a = 0 := by
rw [filter_apply, Set.indicator_apply_eq_zero.mpr fun ha' => absurd ha' ha, zero_mul]
#align pmf.filter_apply_eq_zero_of_not_mem PMF.filter_apply_eq_zero_of_not_mem
theorem mem_support_filter_iff {a : α} : a ∈ (p.filter s h).support ↔ a ∈ s ∧ a ∈ p.support :=
(mem_support_normalize_iff _ _ _).trans Set.indicator_apply_ne_zero
#align pmf.mem_support_filter_iff PMF.mem_support_filter_iff
@[simp]
theorem support_filter : (p.filter s h).support = s ∩ p.support :=
Set.ext fun _ => mem_support_filter_iff _
#align pmf.support_filter PMF.support_filter
theorem filter_apply_eq_zero_iff (a : α) : (p.filter s h) a = 0 ↔ a ∉ s ∨ a ∉ p.support := by
erw [apply_eq_zero_iff, support_filter, Set.mem_inter_iff, not_and_or]
#align pmf.filter_apply_eq_zero_iff PMF.filter_apply_eq_zero_iff
theorem filter_apply_ne_zero_iff (a : α) : (p.filter s h) a ≠ 0 ↔ a ∈ s ∧ a ∈ p.support := by
rw [Ne, filter_apply_eq_zero_iff, not_or, Classical.not_not, Classical.not_not]
#align pmf.filter_apply_ne_zero_iff PMF.filter_apply_ne_zero_iff
end Filter
section bernoulli
/-- A `PMF` which assigns probability `p` to `true` and `1 - p` to `false`. -/
def bernoulli (p : ℝ≥0∞) (h : p ≤ 1) : PMF Bool :=
ofFintype (fun b => cond b p (1 - p)) (by simp [h])
#align pmf.bernoulli PMF.bernoulli
variable {p : ℝ≥0∞} (h : p ≤ 1) (b : Bool)
@[simp]
theorem bernoulli_apply : bernoulli p h b = cond b p (1 - p) := rfl
#align pmf.bernoulli_apply PMF.bernoulli_apply
@[simp]
| Mathlib/Probability/ProbabilityMassFunction/Constructions.lean | 316 | 321 | theorem support_bernoulli : (bernoulli p h).support = { b | cond b (p ≠ 0) (p ≠ 1) } := by |
refine Set.ext fun b => ?_
induction b
· simp_rw [mem_support_iff, bernoulli_apply, Bool.cond_false, Ne, tsub_eq_zero_iff_le, not_le]
exact ⟨ne_of_lt, lt_of_le_of_ne h⟩
· simp only [mem_support_iff, bernoulli_apply, Bool.cond_true, Set.mem_setOf_eq]
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Sébastien Gouëzel, Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.Projection
import Mathlib.Analysis.NormedSpace.PiLp
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.UnitaryGroup
#align_import analysis.inner_product_space.pi_L2 from "leanprover-community/mathlib"@"13bce9a6b6c44f6b4c91ac1c1d2a816e2533d395"
/-!
# `L²` inner product space structure on finite products of inner product spaces
The `L²` norm on a finite product of inner product spaces is compatible with an inner product
$$
\langle x, y\rangle = \sum \langle x_i, y_i \rangle.
$$
This is recorded in this file as an inner product space instance on `PiLp 2`.
This file develops the notion of a finite dimensional Hilbert space over `𝕜 = ℂ, ℝ`, referred to as
`E`. We define an `OrthonormalBasis 𝕜 ι E` as a linear isometric equivalence
between `E` and `EuclideanSpace 𝕜 ι`. Then `stdOrthonormalBasis` shows that such an equivalence
always exists if `E` is finite dimensional. We provide language for converting between a basis
that is orthonormal and an orthonormal basis (e.g. `Basis.toOrthonormalBasis`). We show that
orthonormal bases for each summand in a direct sum of spaces can be combined into an orthonormal
basis for the whole sum in `DirectSum.IsInternal.subordinateOrthonormalBasis`. In
the last section, various properties of matrices are explored.
## Main definitions
- `EuclideanSpace 𝕜 n`: defined to be `PiLp 2 (n → 𝕜)` for any `Fintype n`, i.e., the space
from functions to `n` to `𝕜` with the `L²` norm. We register several instances on it (notably
that it is a finite-dimensional inner product space).
- `OrthonormalBasis 𝕜 ι`: defined to be an isometry to Euclidean space from a given
finite-dimensional inner product space, `E ≃ₗᵢ[𝕜] EuclideanSpace 𝕜 ι`.
- `Basis.toOrthonormalBasis`: constructs an `OrthonormalBasis` for a finite-dimensional
Euclidean space from a `Basis` which is `Orthonormal`.
- `Orthonormal.exists_orthonormalBasis_extension`: provides an existential result of an
`OrthonormalBasis` extending a given orthonormal set
- `exists_orthonormalBasis`: provides an orthonormal basis on a finite dimensional vector space
- `stdOrthonormalBasis`: provides an arbitrarily-chosen `OrthonormalBasis` of a given finite
dimensional inner product space
For consequences in infinite dimension (Hilbert bases, etc.), see the file
`Analysis.InnerProductSpace.L2Space`.
-/
set_option linter.uppercaseLean3 false
open Real Set Filter RCLike Submodule Function Uniformity Topology NNReal ENNReal
ComplexConjugate DirectSum
noncomputable section
variable {ι ι' 𝕜 : Type*} [RCLike 𝕜]
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable {E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E']
variable {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
variable {F' : Type*} [NormedAddCommGroup F'] [InnerProductSpace ℝ F']
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
/-
If `ι` is a finite type and each space `f i`, `i : ι`, is an inner product space,
then `Π i, f i` is an inner product space as well. Since `Π i, f i` is endowed with the sup norm,
we use instead `PiLp 2 f` for the product space, which is endowed with the `L^2` norm.
-/
instance PiLp.innerProductSpace {ι : Type*} [Fintype ι] (f : ι → Type*)
[∀ i, NormedAddCommGroup (f i)] [∀ i, InnerProductSpace 𝕜 (f i)] :
InnerProductSpace 𝕜 (PiLp 2 f) where
inner x y := ∑ i, inner (x i) (y i)
norm_sq_eq_inner x := by
simp only [PiLp.norm_sq_eq_of_L2, map_sum, ← norm_sq_eq_inner, one_div]
conj_symm := by
intro x y
unfold inner
rw [map_sum]
apply Finset.sum_congr rfl
rintro z -
apply inner_conj_symm
add_left x y z :=
show (∑ i, inner (x i + y i) (z i)) = (∑ i, inner (x i) (z i)) + ∑ i, inner (y i) (z i) by
simp only [inner_add_left, Finset.sum_add_distrib]
smul_left x y r :=
show (∑ i : ι, inner (r • x i) (y i)) = conj r * ∑ i, inner (x i) (y i) by
simp only [Finset.mul_sum, inner_smul_left]
#align pi_Lp.inner_product_space PiLp.innerProductSpace
@[simp]
theorem PiLp.inner_apply {ι : Type*} [Fintype ι] {f : ι → Type*} [∀ i, NormedAddCommGroup (f i)]
[∀ i, InnerProductSpace 𝕜 (f i)] (x y : PiLp 2 f) : ⟪x, y⟫ = ∑ i, ⟪x i, y i⟫ :=
rfl
#align pi_Lp.inner_apply PiLp.inner_apply
/-- The standard real/complex Euclidean space, functions on a finite type. For an `n`-dimensional
space use `EuclideanSpace 𝕜 (Fin n)`. -/
abbrev EuclideanSpace (𝕜 : Type*) (n : Type*) : Type _ :=
PiLp 2 fun _ : n => 𝕜
#align euclidean_space EuclideanSpace
theorem EuclideanSpace.nnnorm_eq {𝕜 : Type*} [RCLike 𝕜] {n : Type*} [Fintype n]
(x : EuclideanSpace 𝕜 n) : ‖x‖₊ = NNReal.sqrt (∑ i, ‖x i‖₊ ^ 2) :=
PiLp.nnnorm_eq_of_L2 x
#align euclidean_space.nnnorm_eq EuclideanSpace.nnnorm_eq
theorem EuclideanSpace.norm_eq {𝕜 : Type*} [RCLike 𝕜] {n : Type*} [Fintype n]
(x : EuclideanSpace 𝕜 n) : ‖x‖ = √(∑ i, ‖x i‖ ^ 2) := by
simpa only [Real.coe_sqrt, NNReal.coe_sum] using congr_arg ((↑) : ℝ≥0 → ℝ) x.nnnorm_eq
#align euclidean_space.norm_eq EuclideanSpace.norm_eq
theorem EuclideanSpace.dist_eq {𝕜 : Type*} [RCLike 𝕜] {n : Type*} [Fintype n]
(x y : EuclideanSpace 𝕜 n) : dist x y = √(∑ i, dist (x i) (y i) ^ 2) :=
PiLp.dist_eq_of_L2 x y
#align euclidean_space.dist_eq EuclideanSpace.dist_eq
theorem EuclideanSpace.nndist_eq {𝕜 : Type*} [RCLike 𝕜] {n : Type*} [Fintype n]
(x y : EuclideanSpace 𝕜 n) : nndist x y = NNReal.sqrt (∑ i, nndist (x i) (y i) ^ 2) :=
PiLp.nndist_eq_of_L2 x y
#align euclidean_space.nndist_eq EuclideanSpace.nndist_eq
theorem EuclideanSpace.edist_eq {𝕜 : Type*} [RCLike 𝕜] {n : Type*} [Fintype n]
(x y : EuclideanSpace 𝕜 n) : edist x y = (∑ i, edist (x i) (y i) ^ 2) ^ (1 / 2 : ℝ) :=
PiLp.edist_eq_of_L2 x y
#align euclidean_space.edist_eq EuclideanSpace.edist_eq
theorem EuclideanSpace.ball_zero_eq {n : Type*} [Fintype n] (r : ℝ) (hr : 0 ≤ r) :
Metric.ball (0 : EuclideanSpace ℝ n) r = {x | ∑ i, x i ^ 2 < r ^ 2} := by
ext x
have : (0 : ℝ) ≤ ∑ i, x i ^ 2 := Finset.sum_nonneg fun _ _ => sq_nonneg _
simp_rw [mem_setOf, mem_ball_zero_iff, norm_eq, norm_eq_abs, sq_abs, sqrt_lt this hr]
theorem EuclideanSpace.closedBall_zero_eq {n : Type*} [Fintype n] (r : ℝ) (hr : 0 ≤ r) :
Metric.closedBall (0 : EuclideanSpace ℝ n) r = {x | ∑ i, x i ^ 2 ≤ r ^ 2} := by
ext
simp_rw [mem_setOf, mem_closedBall_zero_iff, norm_eq, norm_eq_abs, sq_abs, sqrt_le_left hr]
theorem EuclideanSpace.sphere_zero_eq {n : Type*} [Fintype n] (r : ℝ) (hr : 0 ≤ r) :
Metric.sphere (0 : EuclideanSpace ℝ n) r = {x | ∑ i, x i ^ 2 = r ^ 2} := by
ext x
have : (0 : ℝ) ≤ ∑ i, x i ^ 2 := Finset.sum_nonneg fun _ _ => sq_nonneg _
simp_rw [mem_setOf, mem_sphere_zero_iff_norm, norm_eq, norm_eq_abs, sq_abs,
Real.sqrt_eq_iff_sq_eq this hr, eq_comm]
section
#align euclidean_space.finite_dimensional WithLp.instModuleFinite
variable [Fintype ι]
#align euclidean_space.inner_product_space PiLp.innerProductSpace
@[simp]
theorem finrank_euclideanSpace :
FiniteDimensional.finrank 𝕜 (EuclideanSpace 𝕜 ι) = Fintype.card ι := by
simp [EuclideanSpace, PiLp, WithLp]
#align finrank_euclidean_space finrank_euclideanSpace
theorem finrank_euclideanSpace_fin {n : ℕ} :
FiniteDimensional.finrank 𝕜 (EuclideanSpace 𝕜 (Fin n)) = n := by simp
#align finrank_euclidean_space_fin finrank_euclideanSpace_fin
theorem EuclideanSpace.inner_eq_star_dotProduct (x y : EuclideanSpace 𝕜 ι) :
⟪x, y⟫ = Matrix.dotProduct (star <| WithLp.equiv _ _ x) (WithLp.equiv _ _ y) :=
rfl
#align euclidean_space.inner_eq_star_dot_product EuclideanSpace.inner_eq_star_dotProduct
theorem EuclideanSpace.inner_piLp_equiv_symm (x y : ι → 𝕜) :
⟪(WithLp.equiv 2 _).symm x, (WithLp.equiv 2 _).symm y⟫ = Matrix.dotProduct (star x) y :=
rfl
#align euclidean_space.inner_pi_Lp_equiv_symm EuclideanSpace.inner_piLp_equiv_symm
/-- A finite, mutually orthogonal family of subspaces of `E`, which span `E`, induce an isometry
from `E` to `PiLp 2` of the subspaces equipped with the `L2` inner product. -/
def DirectSum.IsInternal.isometryL2OfOrthogonalFamily [DecidableEq ι] {V : ι → Submodule 𝕜 E}
(hV : DirectSum.IsInternal V)
(hV' : OrthogonalFamily 𝕜 (fun i => V i) fun i => (V i).subtypeₗᵢ) :
E ≃ₗᵢ[𝕜] PiLp 2 fun i => V i := by
let e₁ := DirectSum.linearEquivFunOnFintype 𝕜 ι fun i => V i
let e₂ := LinearEquiv.ofBijective (DirectSum.coeLinearMap V) hV
refine LinearEquiv.isometryOfInner (e₂.symm.trans e₁) ?_
suffices ∀ (v w : PiLp 2 fun i => V i), ⟪v, w⟫ = ⟪e₂ (e₁.symm v), e₂ (e₁.symm w)⟫ by
intro v₀ w₀
convert this (e₁ (e₂.symm v₀)) (e₁ (e₂.symm w₀)) <;>
simp only [LinearEquiv.symm_apply_apply, LinearEquiv.apply_symm_apply]
intro v w
trans ⟪∑ i, (V i).subtypeₗᵢ (v i), ∑ i, (V i).subtypeₗᵢ (w i)⟫
· simp only [sum_inner, hV'.inner_right_fintype, PiLp.inner_apply]
· congr <;> simp
#align direct_sum.is_internal.isometry_L2_of_orthogonal_family DirectSum.IsInternal.isometryL2OfOrthogonalFamily
@[simp]
theorem DirectSum.IsInternal.isometryL2OfOrthogonalFamily_symm_apply [DecidableEq ι]
{V : ι → Submodule 𝕜 E} (hV : DirectSum.IsInternal V)
(hV' : OrthogonalFamily 𝕜 (fun i => V i) fun i => (V i).subtypeₗᵢ) (w : PiLp 2 fun i => V i) :
(hV.isometryL2OfOrthogonalFamily hV').symm w = ∑ i, (w i : E) := by
classical
let e₁ := DirectSum.linearEquivFunOnFintype 𝕜 ι fun i => V i
let e₂ := LinearEquiv.ofBijective (DirectSum.coeLinearMap V) hV
suffices ∀ v : ⨁ i, V i, e₂ v = ∑ i, e₁ v i by exact this (e₁.symm w)
intro v
-- Porting note: added `DFinsupp.lsum`
simp [e₁, e₂, DirectSum.coeLinearMap, DirectSum.toModule, DFinsupp.lsum,
DFinsupp.sumAddHom_apply]
#align direct_sum.is_internal.isometry_L2_of_orthogonal_family_symm_apply DirectSum.IsInternal.isometryL2OfOrthogonalFamily_symm_apply
end
variable (ι 𝕜)
/-- A shorthand for `PiLp.continuousLinearEquiv`. -/
abbrev EuclideanSpace.equiv : EuclideanSpace 𝕜 ι ≃L[𝕜] ι → 𝕜 :=
PiLp.continuousLinearEquiv 2 𝕜 _
#align euclidean_space.equiv EuclideanSpace.equiv
#noalign euclidean_space.equiv_to_linear_equiv_apply
#noalign euclidean_space.equiv_apply
#noalign euclidean_space.equiv_to_linear_equiv_symm_apply
#noalign euclidean_space.equiv_symm_apply
variable {ι 𝕜}
-- TODO : This should be generalized to `PiLp`.
/-- The projection on the `i`-th coordinate of `EuclideanSpace 𝕜 ι`, as a linear map. -/
@[simps!]
def EuclideanSpace.projₗ (i : ι) : EuclideanSpace 𝕜 ι →ₗ[𝕜] 𝕜 :=
(LinearMap.proj i).comp (WithLp.linearEquiv 2 𝕜 (ι → 𝕜) : EuclideanSpace 𝕜 ι →ₗ[𝕜] ι → 𝕜)
#align euclidean_space.projₗ EuclideanSpace.projₗ
#align euclidean_space.projₗ_apply EuclideanSpace.projₗ_apply
-- TODO : This should be generalized to `PiLp`.
/-- The projection on the `i`-th coordinate of `EuclideanSpace 𝕜 ι`,
as a continuous linear map. -/
@[simps! apply coe]
def EuclideanSpace.proj (i : ι) : EuclideanSpace 𝕜 ι →L[𝕜] 𝕜 :=
⟨EuclideanSpace.projₗ i, continuous_apply i⟩
#align euclidean_space.proj EuclideanSpace.proj
#align euclidean_space.proj_coe EuclideanSpace.proj_coe
#align euclidean_space.proj_apply EuclideanSpace.proj_apply
section DecEq
variable [DecidableEq ι]
-- TODO : This should be generalized to `PiLp`.
/-- The vector given in euclidean space by being `a : 𝕜` at coordinate `i : ι` and `0 : 𝕜` at
all other coordinates. -/
def EuclideanSpace.single (i : ι) (a : 𝕜) : EuclideanSpace 𝕜 ι :=
(WithLp.equiv _ _).symm (Pi.single i a)
#align euclidean_space.single EuclideanSpace.single
@[simp]
theorem WithLp.equiv_single (i : ι) (a : 𝕜) :
WithLp.equiv _ _ (EuclideanSpace.single i a) = Pi.single i a :=
rfl
#align pi_Lp.equiv_single WithLp.equiv_single
@[simp]
theorem WithLp.equiv_symm_single (i : ι) (a : 𝕜) :
(WithLp.equiv _ _).symm (Pi.single i a) = EuclideanSpace.single i a :=
rfl
#align pi_Lp.equiv_symm_single WithLp.equiv_symm_single
@[simp]
theorem EuclideanSpace.single_apply (i : ι) (a : 𝕜) (j : ι) :
(EuclideanSpace.single i a) j = ite (j = i) a 0 := by
rw [EuclideanSpace.single, WithLp.equiv_symm_pi_apply, ← Pi.single_apply i a j]
#align euclidean_space.single_apply EuclideanSpace.single_apply
variable [Fintype ι]
theorem EuclideanSpace.inner_single_left (i : ι) (a : 𝕜) (v : EuclideanSpace 𝕜 ι) :
⟪EuclideanSpace.single i (a : 𝕜), v⟫ = conj a * v i := by simp [apply_ite conj]
#align euclidean_space.inner_single_left EuclideanSpace.inner_single_left
theorem EuclideanSpace.inner_single_right (i : ι) (a : 𝕜) (v : EuclideanSpace 𝕜 ι) :
⟪v, EuclideanSpace.single i (a : 𝕜)⟫ = a * conj (v i) := by simp [apply_ite conj, mul_comm]
#align euclidean_space.inner_single_right EuclideanSpace.inner_single_right
@[simp]
theorem EuclideanSpace.norm_single (i : ι) (a : 𝕜) :
‖EuclideanSpace.single i (a : 𝕜)‖ = ‖a‖ :=
PiLp.norm_equiv_symm_single 2 (fun _ => 𝕜) i a
#align euclidean_space.norm_single EuclideanSpace.norm_single
@[simp]
theorem EuclideanSpace.nnnorm_single (i : ι) (a : 𝕜) :
‖EuclideanSpace.single i (a : 𝕜)‖₊ = ‖a‖₊ :=
PiLp.nnnorm_equiv_symm_single 2 (fun _ => 𝕜) i a
#align euclidean_space.nnnorm_single EuclideanSpace.nnnorm_single
@[simp]
theorem EuclideanSpace.dist_single_same (i : ι) (a b : 𝕜) :
dist (EuclideanSpace.single i (a : 𝕜)) (EuclideanSpace.single i (b : 𝕜)) = dist a b :=
PiLp.dist_equiv_symm_single_same 2 (fun _ => 𝕜) i a b
#align euclidean_space.dist_single_same EuclideanSpace.dist_single_same
@[simp]
theorem EuclideanSpace.nndist_single_same (i : ι) (a b : 𝕜) :
nndist (EuclideanSpace.single i (a : 𝕜)) (EuclideanSpace.single i (b : 𝕜)) = nndist a b :=
PiLp.nndist_equiv_symm_single_same 2 (fun _ => 𝕜) i a b
#align euclidean_space.nndist_single_same EuclideanSpace.nndist_single_same
@[simp]
theorem EuclideanSpace.edist_single_same (i : ι) (a b : 𝕜) :
edist (EuclideanSpace.single i (a : 𝕜)) (EuclideanSpace.single i (b : 𝕜)) = edist a b :=
PiLp.edist_equiv_symm_single_same 2 (fun _ => 𝕜) i a b
#align euclidean_space.edist_single_same EuclideanSpace.edist_single_same
/-- `EuclideanSpace.single` forms an orthonormal family. -/
| Mathlib/Analysis/InnerProductSpace/PiL2.lean | 317 | 322 | theorem EuclideanSpace.orthonormal_single :
Orthonormal 𝕜 fun i : ι => EuclideanSpace.single i (1 : 𝕜) := by |
simp_rw [orthonormal_iff_ite, EuclideanSpace.inner_single_left, map_one, one_mul,
EuclideanSpace.single_apply]
intros
trivial
|
/-
Copyright (c) 2021 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Algebra.Group.Subgroup.Basic
import Mathlib.Algebra.Group.Submonoid.Operations
import Mathlib.Data.Finset.Preimage
import Mathlib.Data.Set.Pointwise.Finite
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.SetTheory.Cardinal.Finite
#align_import group_theory.finiteness from "leanprover-community/mathlib"@"dde670c9a3f503647fd5bfdf1037bad526d3397a"
/-!
# Finitely generated monoids and groups
We define finitely generated monoids and groups. See also `Submodule.FG` and `Module.Finite` for
finitely-generated modules.
## Main definition
* `Submonoid.FG S`, `AddSubmonoid.FG S` : A submonoid `S` is finitely generated.
* `Monoid.FG M`, `AddMonoid.FG M` : A typeclass indicating a type `M` is finitely generated as a
monoid.
* `Subgroup.FG S`, `AddSubgroup.FG S` : A subgroup `S` is finitely generated.
* `Group.FG M`, `AddGroup.FG M` : A typeclass indicating a type `M` is finitely generated as a
group.
-/
/-! ### Monoids and submonoids -/
open Pointwise
variable {M N : Type*} [Monoid M] [AddMonoid N]
section Submonoid
/-- A submonoid of `M` is finitely generated if it is the closure of a finite subset of `M`. -/
@[to_additive]
def Submonoid.FG (P : Submonoid M) : Prop :=
∃ S : Finset M, Submonoid.closure ↑S = P
#align submonoid.fg Submonoid.FG
#align add_submonoid.fg AddSubmonoid.FG
/-- An additive submonoid of `N` is finitely generated if it is the closure of a finite subset of
`M`. -/
add_decl_doc AddSubmonoid.FG
/-- An equivalent expression of `Submonoid.FG` in terms of `Set.Finite` instead of `Finset`. -/
@[to_additive "An equivalent expression of `AddSubmonoid.FG` in terms of `Set.Finite` instead of
`Finset`."]
theorem Submonoid.fg_iff (P : Submonoid M) :
Submonoid.FG P ↔ ∃ S : Set M, Submonoid.closure S = P ∧ S.Finite :=
⟨fun ⟨S, hS⟩ => ⟨S, hS, Finset.finite_toSet S⟩, fun ⟨S, hS, hf⟩ =>
⟨Set.Finite.toFinset hf, by simp [hS]⟩⟩
#align submonoid.fg_iff Submonoid.fg_iff
#align add_submonoid.fg_iff AddSubmonoid.fg_iff
theorem Submonoid.fg_iff_add_fg (P : Submonoid M) : P.FG ↔ P.toAddSubmonoid.FG :=
⟨fun h =>
let ⟨S, hS, hf⟩ := (Submonoid.fg_iff _).1 h
(AddSubmonoid.fg_iff _).mpr
⟨Additive.toMul ⁻¹' S, by simp [← Submonoid.toAddSubmonoid_closure, hS], hf⟩,
fun h =>
let ⟨T, hT, hf⟩ := (AddSubmonoid.fg_iff _).1 h
(Submonoid.fg_iff _).mpr
⟨Multiplicative.ofAdd ⁻¹' T, by simp [← AddSubmonoid.toSubmonoid'_closure, hT], hf⟩⟩
#align submonoid.fg_iff_add_fg Submonoid.fg_iff_add_fg
theorem AddSubmonoid.fg_iff_mul_fg (P : AddSubmonoid N) : P.FG ↔ P.toSubmonoid.FG := by
convert (Submonoid.fg_iff_add_fg (toSubmonoid P)).symm
#align add_submonoid.fg_iff_mul_fg AddSubmonoid.fg_iff_mul_fg
end Submonoid
section Monoid
variable (M N)
/-- A monoid is finitely generated if it is finitely generated as a submonoid of itself. -/
class Monoid.FG : Prop where
out : (⊤ : Submonoid M).FG
#align monoid.fg Monoid.FG
/-- An additive monoid is finitely generated if it is finitely generated as an additive submonoid of
itself. -/
class AddMonoid.FG : Prop where
out : (⊤ : AddSubmonoid N).FG
#align add_monoid.fg AddMonoid.FG
attribute [to_additive] Monoid.FG
variable {M N}
theorem Monoid.fg_def : Monoid.FG M ↔ (⊤ : Submonoid M).FG :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align monoid.fg_def Monoid.fg_def
theorem AddMonoid.fg_def : AddMonoid.FG N ↔ (⊤ : AddSubmonoid N).FG :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align add_monoid.fg_def AddMonoid.fg_def
/-- An equivalent expression of `Monoid.FG` in terms of `Set.Finite` instead of `Finset`. -/
@[to_additive
"An equivalent expression of `AddMonoid.FG` in terms of `Set.Finite` instead of `Finset`."]
theorem Monoid.fg_iff :
Monoid.FG M ↔ ∃ S : Set M, Submonoid.closure S = (⊤ : Submonoid M) ∧ S.Finite :=
⟨fun h => (Submonoid.fg_iff ⊤).1 h.out, fun h => ⟨(Submonoid.fg_iff ⊤).2 h⟩⟩
#align monoid.fg_iff Monoid.fg_iff
#align add_monoid.fg_iff AddMonoid.fg_iff
theorem Monoid.fg_iff_add_fg : Monoid.FG M ↔ AddMonoid.FG (Additive M) :=
⟨fun h => ⟨(Submonoid.fg_iff_add_fg ⊤).1 h.out⟩, fun h => ⟨(Submonoid.fg_iff_add_fg ⊤).2 h.out⟩⟩
#align monoid.fg_iff_add_fg Monoid.fg_iff_add_fg
theorem AddMonoid.fg_iff_mul_fg : AddMonoid.FG N ↔ Monoid.FG (Multiplicative N) :=
⟨fun h => ⟨(AddSubmonoid.fg_iff_mul_fg ⊤).1 h.out⟩, fun h =>
⟨(AddSubmonoid.fg_iff_mul_fg ⊤).2 h.out⟩⟩
#align add_monoid.fg_iff_mul_fg AddMonoid.fg_iff_mul_fg
instance AddMonoid.fg_of_monoid_fg [Monoid.FG M] : AddMonoid.FG (Additive M) :=
Monoid.fg_iff_add_fg.1 ‹_›
#align add_monoid.fg_of_monoid_fg AddMonoid.fg_of_monoid_fg
instance Monoid.fg_of_addMonoid_fg [AddMonoid.FG N] : Monoid.FG (Multiplicative N) :=
AddMonoid.fg_iff_mul_fg.1 ‹_›
#align monoid.fg_of_add_monoid_fg Monoid.fg_of_addMonoid_fg
@[to_additive]
instance (priority := 100) Monoid.fg_of_finite [Finite M] : Monoid.FG M := by
cases nonempty_fintype M
exact ⟨⟨Finset.univ, by rw [Finset.coe_univ]; exact Submonoid.closure_univ⟩⟩
#align monoid.fg_of_finite Monoid.fg_of_finite
#align add_monoid.fg_of_finite AddMonoid.fg_of_finite
end Monoid
@[to_additive]
theorem Submonoid.FG.map {M' : Type*} [Monoid M'] {P : Submonoid M} (h : P.FG) (e : M →* M') :
(P.map e).FG := by
classical
obtain ⟨s, rfl⟩ := h
exact ⟨s.image e, by rw [Finset.coe_image, MonoidHom.map_mclosure]⟩
#align submonoid.fg.map Submonoid.FG.map
#align add_submonoid.fg.map AddSubmonoid.FG.map
@[to_additive]
theorem Submonoid.FG.map_injective {M' : Type*} [Monoid M'] {P : Submonoid M} (e : M →* M')
(he : Function.Injective e) (h : (P.map e).FG) : P.FG := by
obtain ⟨s, hs⟩ := h
use s.preimage e he.injOn
apply Submonoid.map_injective_of_injective he
rw [← hs, MonoidHom.map_mclosure e, Finset.coe_preimage]
congr
rw [Set.image_preimage_eq_iff, ← MonoidHom.coe_mrange e, ← Submonoid.closure_le, hs,
MonoidHom.mrange_eq_map e]
exact Submonoid.monotone_map le_top
#align submonoid.fg.map_injective Submonoid.FG.map_injective
#align add_submonoid.fg.map_injective AddSubmonoid.FG.map_injective
@[to_additive (attr := simp)]
theorem Monoid.fg_iff_submonoid_fg (N : Submonoid M) : Monoid.FG N ↔ N.FG := by
conv_rhs => rw [← N.range_subtype, MonoidHom.mrange_eq_map]
exact ⟨fun h => h.out.map N.subtype, fun h => ⟨h.map_injective N.subtype Subtype.coe_injective⟩⟩
#align monoid.fg_iff_submonoid_fg Monoid.fg_iff_submonoid_fg
#align add_monoid.fg_iff_add_submonoid_fg AddMonoid.fg_iff_addSubmonoid_fg
@[to_additive]
| Mathlib/GroupTheory/Finiteness.lean | 173 | 179 | theorem Monoid.fg_of_surjective {M' : Type*} [Monoid M'] [Monoid.FG M] (f : M →* M')
(hf : Function.Surjective f) : Monoid.FG M' := by |
classical
obtain ⟨s, hs⟩ := Monoid.fg_def.mp ‹_›
use s.image f
rwa [Finset.coe_image, ← MonoidHom.map_mclosure, hs, ← MonoidHom.mrange_eq_map,
MonoidHom.mrange_top_iff_surjective]
|
/-
Copyright (c) 2021 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.MvPolynomial.Variables
#align_import data.mv_polynomial.supported from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Polynomials supported by a set of variables
This file contains the definition and lemmas about `MvPolynomial.supported`.
## Main definitions
* `MvPolynomial.supported` : Given a set `s : Set σ`, `supported R s` is the subalgebra of
`MvPolynomial σ R` consisting of polynomials whose set of variables is contained in `s`.
This subalgebra is isomorphic to `MvPolynomial s R`.
## Tags
variables, polynomial, vars
-/
universe u v w
namespace MvPolynomial
variable {σ τ : Type*} {R : Type u} {S : Type v} {r : R} {e : ℕ} {n m : σ}
section CommSemiring
variable [CommSemiring R] {p q : MvPolynomial σ R}
variable (R)
/-- The set of polynomials whose variables are contained in `s` as a `Subalgebra` over `R`. -/
noncomputable def supported (s : Set σ) : Subalgebra R (MvPolynomial σ R) :=
Algebra.adjoin R (X '' s)
#align mv_polynomial.supported MvPolynomial.supported
variable {R}
open Algebra
theorem supported_eq_range_rename (s : Set σ) : supported R s = (rename ((↑) : s → σ)).range := by
rw [supported, Set.image_eq_range, adjoin_range_eq_range_aeval, rename]
congr
#align mv_polynomial.supported_eq_range_rename MvPolynomial.supported_eq_range_rename
/-- The isomorphism between the subalgebra of polynomials supported by `s` and
`MvPolynomial s R`. -/
noncomputable def supportedEquivMvPolynomial (s : Set σ) : supported R s ≃ₐ[R] MvPolynomial s R :=
(Subalgebra.equivOfEq _ _ (supported_eq_range_rename s)).trans
(AlgEquiv.ofInjective (rename ((↑) : s → σ)) (rename_injective _ Subtype.val_injective)).symm
#align mv_polynomial.supported_equiv_mv_polynomial MvPolynomial.supportedEquivMvPolynomial
@[simp, nolint simpNF] -- Porting note: the `simpNF` linter complained about this lemma.
theorem supportedEquivMvPolynomial_symm_C (s : Set σ) (x : R) :
(supportedEquivMvPolynomial s).symm (C x) = algebraMap R (supported R s) x := by
ext1
simp [supportedEquivMvPolynomial, MvPolynomial.algebraMap_eq]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.supported_equiv_mv_polynomial_symm_C MvPolynomial.supportedEquivMvPolynomial_symm_C
@[simp, nolint simpNF] -- Porting note: the `simpNF` linter complained about this lemma.
theorem supportedEquivMvPolynomial_symm_X (s : Set σ) (i : s) :
(↑((supportedEquivMvPolynomial s).symm (X i : MvPolynomial s R)) : MvPolynomial σ R) = X ↑i :=
by simp [supportedEquivMvPolynomial]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.supported_equiv_mv_polynomial_symm_X MvPolynomial.supportedEquivMvPolynomial_symm_X
variable {s t : Set σ}
theorem mem_supported : p ∈ supported R s ↔ ↑p.vars ⊆ s := by
classical
rw [supported_eq_range_rename, AlgHom.mem_range]
constructor
· rintro ⟨p, rfl⟩
refine _root_.trans (Finset.coe_subset.2 (vars_rename _ _)) ?_
simp
· intro hs
exact exists_rename_eq_of_vars_subset_range p ((↑) : s → σ) Subtype.val_injective (by simpa)
#align mv_polynomial.mem_supported MvPolynomial.mem_supported
theorem supported_eq_vars_subset : (supported R s : Set (MvPolynomial σ R)) = { p | ↑p.vars ⊆ s } :=
Set.ext fun _ ↦ mem_supported
#align mv_polynomial.supported_eq_vars_subset MvPolynomial.supported_eq_vars_subset
@[simp]
theorem mem_supported_vars (p : MvPolynomial σ R) : p ∈ supported R (↑p.vars : Set σ) := by
rw [mem_supported]
#align mv_polynomial.mem_supported_vars MvPolynomial.mem_supported_vars
variable (s)
theorem supported_eq_adjoin_X : supported R s = Algebra.adjoin R (X '' s) := rfl
set_option linter.uppercaseLean3 false in
#align mv_polynomial.supported_eq_adjoin_X MvPolynomial.supported_eq_adjoin_X
@[simp]
theorem supported_univ : supported R (Set.univ : Set σ) = ⊤ := by
simp [Algebra.eq_top_iff, mem_supported]
#align mv_polynomial.supported_univ MvPolynomial.supported_univ
@[simp]
theorem supported_empty : supported R (∅ : Set σ) = ⊥ := by simp [supported_eq_adjoin_X]
#align mv_polynomial.supported_empty MvPolynomial.supported_empty
variable {s}
theorem supported_mono (st : s ⊆ t) : supported R s ≤ supported R t :=
Algebra.adjoin_mono (Set.image_subset _ st)
#align mv_polynomial.supported_mono MvPolynomial.supported_mono
@[simp]
| Mathlib/Algebra/MvPolynomial/Supported.lean | 117 | 118 | theorem X_mem_supported [Nontrivial R] {i : σ} : X i ∈ supported R s ↔ i ∈ s := by |
simp [mem_supported]
|
/-
Copyright (c) 2022 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Batteries.Data.Nat.Gcd
import Batteries.Data.Int.DivMod
import Batteries.Lean.Float
/-! # Basics for the Rational Numbers -/
/--
Rational numbers, implemented as a pair of integers `num / den` such that the
denominator is positive and the numerator and denominator are coprime.
-/
-- `Rat` is not tagged with the `ext` attribute, since this is more often than not undesirable
structure Rat where
/-- Constructs a rational number from components.
We rename the constructor to `mk'` to avoid a clash with the smart constructor. -/
mk' ::
/-- The numerator of the rational number is an integer. -/
num : Int
/-- The denominator of the rational number is a natural number. -/
den : Nat := 1
/-- The denominator is nonzero. -/
den_nz : den ≠ 0 := by decide
/-- The numerator and denominator are coprime: it is in "reduced form". -/
reduced : num.natAbs.Coprime den := by decide
deriving DecidableEq
instance : Inhabited Rat := ⟨{ num := 0 }⟩
instance : ToString Rat where
toString a := if a.den = 1 then toString a.num else s!"{a.num}/{a.den}"
instance : Repr Rat where
reprPrec a _ := if a.den = 1 then repr a.num else s!"({a.num} : Rat)/{a.den}"
theorem Rat.den_pos (self : Rat) : 0 < self.den := Nat.pos_of_ne_zero self.den_nz
-- Note: `Rat.normalize` uses `Int.div` internally,
-- but we may want to refactor to use `/` (`Int.ediv`)
/--
Auxiliary definition for `Rat.normalize`. Constructs `num / den` as a rational number,
dividing both `num` and `den` by `g` (which is the gcd of the two) if it is not 1.
-/
@[inline] def Rat.maybeNormalize (num : Int) (den g : Nat)
(den_nz : den / g ≠ 0) (reduced : (num.div g).natAbs.Coprime (den / g)) : Rat :=
if hg : g = 1 then
{ num, den
den_nz := by simp [hg] at den_nz; exact den_nz
reduced := by simp [hg, Int.natAbs_ofNat] at reduced; exact reduced }
else { num := num.div g, den := den / g, den_nz, reduced }
theorem Rat.normalize.den_nz {num : Int} {den g : Nat} (den_nz : den ≠ 0)
(e : g = num.natAbs.gcd den) : den / g ≠ 0 :=
e ▸ Nat.ne_of_gt (Nat.div_gcd_pos_of_pos_right _ (Nat.pos_of_ne_zero den_nz))
theorem Rat.normalize.reduced {num : Int} {den g : Nat} (den_nz : den ≠ 0)
(e : g = num.natAbs.gcd den) : (num.div g).natAbs.Coprime (den / g) :=
have : Int.natAbs (num.div ↑g) = num.natAbs / g := by
match num, num.eq_nat_or_neg with
| _, ⟨_, .inl rfl⟩ => rfl
| _, ⟨_, .inr rfl⟩ => rw [Int.neg_div, Int.natAbs_neg, Int.natAbs_neg]; rfl
this ▸ e ▸ Nat.coprime_div_gcd_div_gcd (Nat.gcd_pos_of_pos_right _ (Nat.pos_of_ne_zero den_nz))
/--
Construct a normalized `Rat` from a numerator and nonzero denominator.
This is a "smart constructor" that divides the numerator and denominator by
the gcd to ensure that the resulting rational number is normalized.
-/
@[inline] def Rat.normalize (num : Int) (den : Nat := 1) (den_nz : den ≠ 0 := by decide) : Rat :=
Rat.maybeNormalize num den (num.natAbs.gcd den)
(normalize.den_nz den_nz rfl) (normalize.reduced den_nz rfl)
/--
Construct a rational number from a numerator and denominator.
This is a "smart constructor" that divides the numerator and denominator by
the gcd to ensure that the resulting rational number is normalized, and returns
zero if `den` is zero.
-/
def mkRat (num : Int) (den : Nat) : Rat :=
if den_nz : den = 0 then { num := 0 } else Rat.normalize num den den_nz
namespace Rat
/-- Embedding of `Int` in the rational numbers. -/
def ofInt (num : Int) : Rat := { num, reduced := Nat.coprime_one_right _ }
instance : NatCast Rat where
natCast n := ofInt n
instance : IntCast Rat := ⟨ofInt⟩
instance : OfNat Rat n := ⟨n⟩
/-- Is this rational number integral? -/
@[inline] protected def isInt (a : Rat) : Bool := a.den == 1
/-- Form the quotient `n / d` where `n d : Int`. -/
def divInt : Int → Int → Rat
| n, .ofNat d => inline (mkRat n d)
| n, .negSucc d => normalize (-n) d.succ nofun
@[inherit_doc] scoped infixl:70 " /. " => Rat.divInt
/-- Implements "scientific notation" `123.4e-5` for rational numbers. (This definition is
`@[irreducible]` because you don't want to unfold it. Use `Rat.ofScientific_def`,
`Rat.ofScientific_true_def`, or `Rat.ofScientific_false_def` instead.) -/
@[irreducible] protected def ofScientific (m : Nat) (s : Bool) (e : Nat) : Rat :=
if s then
Rat.normalize m (10 ^ e) <| Nat.ne_of_gt <| Nat.pos_pow_of_pos _ (by decide)
else
(m * 10 ^ e : Nat)
instance : OfScientific Rat where ofScientific := Rat.ofScientific
/-- Rational number strictly less than relation, as a `Bool`. -/
protected def blt (a b : Rat) : Bool :=
if a.num < 0 && 0 ≤ b.num then
true
else if a.num = 0 then
0 < b.num
else if 0 < a.num && b.num ≤ 0 then
false
else
-- `a` and `b` must have the same sign
a.num * b.den < b.num * a.den
instance : LT Rat := ⟨(·.blt ·)⟩
instance (a b : Rat) : Decidable (a < b) :=
inferInstanceAs (Decidable (_ = true))
instance : LE Rat := ⟨fun a b => b.blt a = false⟩
instance (a b : Rat) : Decidable (a ≤ b) :=
inferInstanceAs (Decidable (_ = false))
/-- Multiplication of rational numbers. (This definition is `@[irreducible]` because you don't
want to unfold it. Use `Rat.mul_def` instead.) -/
@[irreducible] protected def mul (a b : Rat) : Rat :=
let g1 := Nat.gcd a.num.natAbs b.den
let g2 := Nat.gcd b.num.natAbs a.den
{ num := (a.num.div g1) * (b.num.div g2)
den := (a.den / g2) * (b.den / g1)
den_nz := Nat.ne_of_gt <| Nat.mul_pos
(Nat.div_gcd_pos_of_pos_right _ a.den_pos) (Nat.div_gcd_pos_of_pos_right _ b.den_pos)
reduced := by
simp only [Int.natAbs_mul, Int.natAbs_div, Nat.coprime_mul_iff_left]
refine ⟨Nat.coprime_mul_iff_right.2 ⟨?_, ?_⟩, Nat.coprime_mul_iff_right.2 ⟨?_, ?_⟩⟩
· exact a.reduced.coprime_div_left (Nat.gcd_dvd_left ..)
|>.coprime_div_right (Nat.gcd_dvd_right ..)
· exact Nat.coprime_div_gcd_div_gcd (Nat.gcd_pos_of_pos_right _ b.den_pos)
· exact Nat.coprime_div_gcd_div_gcd (Nat.gcd_pos_of_pos_right _ a.den_pos)
· exact b.reduced.coprime_div_left (Nat.gcd_dvd_left ..)
|>.coprime_div_right (Nat.gcd_dvd_right ..) }
instance : Mul Rat := ⟨Rat.mul⟩
/--
The inverse of a rational number. Note: `inv 0 = 0`. (This definition is `@[irreducible]`
because you don't want to unfold it. Use `Rat.inv_def` instead.)
-/
@[irreducible] protected def inv (a : Rat) : Rat :=
if h : a.num < 0 then
{ num := -a.den, den := a.num.natAbs
den_nz := Nat.ne_of_gt (Int.natAbs_pos.2 (Int.ne_of_lt h))
reduced := Int.natAbs_neg a.den ▸ a.reduced.symm }
else if h : a.num > 0 then
{ num := a.den, den := a.num.natAbs
den_nz := Nat.ne_of_gt (Int.natAbs_pos.2 (Int.ne_of_gt h))
reduced := a.reduced.symm }
else
a
/-- Division of rational numbers. Note: `div a 0 = 0`. -/
protected def div : Rat → Rat → Rat := (· * ·.inv)
/-- Division of rational numbers. Note: `div a 0 = 0`. Written with a separate function `Rat.div`
as a wrapper so that the definition is not unfolded at `.instance` transparency. -/
instance : Div Rat := ⟨Rat.div⟩
theorem add.aux (a b : Rat) {g ad bd} (hg : g = a.den.gcd b.den)
(had : ad = a.den / g) (hbd : bd = b.den / g) :
let den := ad * b.den; let num := a.num * bd + b.num * ad
num.natAbs.gcd g = num.natAbs.gcd den := by
intro den num
have ae : ad * g = a.den := had ▸ Nat.div_mul_cancel (hg ▸ Nat.gcd_dvd_left ..)
have be : bd * g = b.den := hbd ▸ Nat.div_mul_cancel (hg ▸ Nat.gcd_dvd_right ..)
have hden : den = ad * bd * g := by rw [Nat.mul_assoc, be]
rw [hden, Nat.Coprime.gcd_mul_left_cancel_right]
have cop : ad.Coprime bd := had ▸ hbd ▸ hg ▸
Nat.coprime_div_gcd_div_gcd (Nat.gcd_pos_of_pos_left _ a.den_pos)
have H1 (d : Nat) :
d.gcd num.natAbs ∣ a.num.natAbs * bd ↔ d.gcd num.natAbs ∣ b.num.natAbs * ad := by
have := d.gcd_dvd_right num.natAbs
rw [← Int.ofNat_dvd, Int.dvd_natAbs] at this
have := Int.dvd_iff_dvd_of_dvd_add this
rwa [← Int.dvd_natAbs, Int.ofNat_dvd, Int.natAbs_mul,
← Int.dvd_natAbs, Int.ofNat_dvd, Int.natAbs_mul] at this
apply Nat.Coprime.mul
· have := (H1 ad).2 <| Nat.dvd_trans (Nat.gcd_dvd_left ..) (Nat.dvd_mul_left ..)
have := (cop.coprime_dvd_left <| Nat.gcd_dvd_left ..).dvd_of_dvd_mul_right this
exact Nat.eq_one_of_dvd_one <| a.reduced.gcd_eq_one ▸ Nat.dvd_gcd this <|
Nat.dvd_trans (Nat.gcd_dvd_left ..) (ae ▸ Nat.dvd_mul_right ..)
· have := (H1 bd).1 <| Nat.dvd_trans (Nat.gcd_dvd_left ..) (Nat.dvd_mul_left ..)
have := (cop.symm.coprime_dvd_left <| Nat.gcd_dvd_left ..).dvd_of_dvd_mul_right this
exact Nat.eq_one_of_dvd_one <| b.reduced.gcd_eq_one ▸ Nat.dvd_gcd this <|
Nat.dvd_trans (Nat.gcd_dvd_left ..) (be ▸ Nat.dvd_mul_right ..)
/--
Addition of rational numbers. (This definition is `@[irreducible]` because you don't want to
unfold it. Use `Rat.add_def` instead.)
-/
@[irreducible] protected def add (a b : Rat) : Rat :=
let g := a.den.gcd b.den
if hg : g = 1 then
have den_nz := Nat.ne_of_gt <| Nat.mul_pos a.den_pos b.den_pos
have reduced := add.aux a b hg.symm (Nat.div_one _).symm (Nat.div_one _).symm
|>.symm.trans (Nat.gcd_one_right _)
{ num := a.num * b.den + b.num * a.den, den := a.den * b.den, den_nz, reduced }
else
let den := (a.den / g) * b.den
let num := a.num * ↑(b.den / g) + b.num * ↑(a.den / g)
let g1 := num.natAbs.gcd g
have den_nz := Nat.ne_of_gt <| Nat.mul_pos (Nat.div_gcd_pos_of_pos_left _ a.den_pos) b.den_pos
have e : g1 = num.natAbs.gcd den := add.aux a b rfl rfl rfl
Rat.maybeNormalize num den g1 (normalize.den_nz den_nz e) (normalize.reduced den_nz e)
instance : Add Rat := ⟨Rat.add⟩
/-- Negation of rational numbers. -/
protected def neg (a : Rat) : Rat :=
{ a with num := -a.num, reduced := by rw [Int.natAbs_neg]; exact a.reduced }
instance : Neg Rat := ⟨Rat.neg⟩
| .lake/packages/batteries/Batteries/Data/Rat/Basic.lean | 239 | 245 | theorem sub.aux (a b : Rat) {g ad bd} (hg : g = a.den.gcd b.den)
(had : ad = a.den / g) (hbd : bd = b.den / g) :
let den := ad * b.den; let num := a.num * bd - b.num * ad
num.natAbs.gcd g = num.natAbs.gcd den := by |
have := add.aux a (-b) hg had hbd
simp only [show (-b).num = -b.num from rfl, Int.neg_mul] at this
exact this
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot
-/
import Mathlib.Order.Filter.SmallSets
import Mathlib.Tactic.Monotonicity
import Mathlib.Topology.Compactness.Compact
import Mathlib.Topology.NhdsSet
import Mathlib.Algebra.Group.Defs
#align_import topology.uniform_space.basic from "leanprover-community/mathlib"@"195fcd60ff2bfe392543bceb0ec2adcdb472db4c"
/-!
# Uniform spaces
Uniform spaces are a generalization of metric spaces and topological groups. Many concepts directly
generalize to uniform spaces, e.g.
* uniform continuity (in this file)
* completeness (in `Cauchy.lean`)
* extension of uniform continuous functions to complete spaces (in `UniformEmbedding.lean`)
* totally bounded sets (in `Cauchy.lean`)
* totally bounded complete sets are compact (in `Cauchy.lean`)
A uniform structure on a type `X` is a filter `𝓤 X` on `X × X` satisfying some conditions
which makes it reasonable to say that `∀ᶠ (p : X × X) in 𝓤 X, ...` means
"for all p.1 and p.2 in X close enough, ...". Elements of this filter are called entourages
of `X`. The two main examples are:
* If `X` is a metric space, `V ∈ 𝓤 X ↔ ∃ ε > 0, { p | dist p.1 p.2 < ε } ⊆ V`
* If `G` is an additive topological group, `V ∈ 𝓤 G ↔ ∃ U ∈ 𝓝 (0 : G), {p | p.2 - p.1 ∈ U} ⊆ V`
Those examples are generalizations in two different directions of the elementary example where
`X = ℝ` and `V ∈ 𝓤 ℝ ↔ ∃ ε > 0, { p | |p.2 - p.1| < ε } ⊆ V` which features both the topological
group structure on `ℝ` and its metric space structure.
Each uniform structure on `X` induces a topology on `X` characterized by
> `nhds_eq_comap_uniformity : ∀ {x : X}, 𝓝 x = comap (Prod.mk x) (𝓤 X)`
where `Prod.mk x : X → X × X := (fun y ↦ (x, y))` is the partial evaluation of the product
constructor.
The dictionary with metric spaces includes:
* an upper bound for `dist x y` translates into `(x, y) ∈ V` for some `V ∈ 𝓤 X`
* a ball `ball x r` roughly corresponds to `UniformSpace.ball x V := {y | (x, y) ∈ V}`
for some `V ∈ 𝓤 X`, but the later is more general (it includes in
particular both open and closed balls for suitable `V`).
In particular we have:
`isOpen_iff_ball_subset {s : Set X} : IsOpen s ↔ ∀ x ∈ s, ∃ V ∈ 𝓤 X, ball x V ⊆ s`
The triangle inequality is abstracted to a statement involving the composition of relations in `X`.
First note that the triangle inequality in a metric space is equivalent to
`∀ (x y z : X) (r r' : ℝ), dist x y ≤ r → dist y z ≤ r' → dist x z ≤ r + r'`.
Then, for any `V` and `W` with type `Set (X × X)`, the composition `V ○ W : Set (X × X)` is
defined as `{ p : X × X | ∃ z, (p.1, z) ∈ V ∧ (z, p.2) ∈ W }`.
In the metric space case, if `V = { p | dist p.1 p.2 ≤ r }` and `W = { p | dist p.1 p.2 ≤ r' }`
then the triangle inequality, as reformulated above, says `V ○ W` is contained in
`{p | dist p.1 p.2 ≤ r + r'}` which is the entourage associated to the radius `r + r'`.
In general we have `mem_ball_comp (h : y ∈ ball x V) (h' : z ∈ ball y W) : z ∈ ball x (V ○ W)`.
Note that this discussion does not depend on any axiom imposed on the uniformity filter,
it is simply captured by the definition of composition.
The uniform space axioms ask the filter `𝓤 X` to satisfy the following:
* every `V ∈ 𝓤 X` contains the diagonal `idRel = { p | p.1 = p.2 }`. This abstracts the fact
that `dist x x ≤ r` for every non-negative radius `r` in the metric space case and also that
`x - x` belongs to every neighborhood of zero in the topological group case.
* `V ∈ 𝓤 X → Prod.swap '' V ∈ 𝓤 X`. This is tightly related the fact that `dist x y = dist y x`
in a metric space, and to continuity of negation in the topological group case.
* `∀ V ∈ 𝓤 X, ∃ W ∈ 𝓤 X, W ○ W ⊆ V`. In the metric space case, it corresponds
to cutting the radius of a ball in half and applying the triangle inequality.
In the topological group case, it comes from continuity of addition at `(0, 0)`.
These three axioms are stated more abstractly in the definition below, in terms of
operations on filters, without directly manipulating entourages.
## Main definitions
* `UniformSpace X` is a uniform space structure on a type `X`
* `UniformContinuous f` is a predicate saying a function `f : α → β` between uniform spaces
is uniformly continuous : `∀ r ∈ 𝓤 β, ∀ᶠ (x : α × α) in 𝓤 α, (f x.1, f x.2) ∈ r`
In this file we also define a complete lattice structure on the type `UniformSpace X`
of uniform structures on `X`, as well as the pullback (`UniformSpace.comap`) of uniform structures
coming from the pullback of filters.
Like distance functions, uniform structures cannot be pushed forward in general.
## Notations
Localized in `Uniformity`, we have the notation `𝓤 X` for the uniformity on a uniform space `X`,
and `○` for composition of relations, seen as terms with type `Set (X × X)`.
## Implementation notes
There is already a theory of relations in `Data/Rel.lean` where the main definition is
`def Rel (α β : Type*) := α → β → Prop`.
The relations used in the current file involve only one type, but this is not the reason why
we don't reuse `Data/Rel.lean`. We use `Set (α × α)`
instead of `Rel α α` because we really need sets to use the filter library, and elements
of filters on `α × α` have type `Set (α × α)`.
The structure `UniformSpace X` bundles a uniform structure on `X`, a topology on `X` and
an assumption saying those are compatible. This may not seem mathematically reasonable at first,
but is in fact an instance of the forgetful inheritance pattern. See Note [forgetful inheritance]
below.
## References
The formalization uses the books:
* [N. Bourbaki, *General Topology*][bourbaki1966]
* [I. M. James, *Topologies and Uniformities*][james1999]
But it makes a more systematic use of the filter library.
-/
open Set Filter Topology
universe u v ua ub uc ud
/-!
### Relations, seen as `Set (α × α)`
-/
variable {α : Type ua} {β : Type ub} {γ : Type uc} {δ : Type ud} {ι : Sort*}
/-- The identity relation, or the graph of the identity function -/
def idRel {α : Type*} :=
{ p : α × α | p.1 = p.2 }
#align id_rel idRel
@[simp]
theorem mem_idRel {a b : α} : (a, b) ∈ @idRel α ↔ a = b :=
Iff.rfl
#align mem_id_rel mem_idRel
@[simp]
theorem idRel_subset {s : Set (α × α)} : idRel ⊆ s ↔ ∀ a, (a, a) ∈ s := by
simp [subset_def]
#align id_rel_subset idRel_subset
/-- The composition of relations -/
def compRel (r₁ r₂ : Set (α × α)) :=
{ p : α × α | ∃ z : α, (p.1, z) ∈ r₁ ∧ (z, p.2) ∈ r₂ }
#align comp_rel compRel
@[inherit_doc]
scoped[Uniformity] infixl:62 " ○ " => compRel
open Uniformity
@[simp]
theorem mem_compRel {α : Type u} {r₁ r₂ : Set (α × α)} {x y : α} :
(x, y) ∈ r₁ ○ r₂ ↔ ∃ z, (x, z) ∈ r₁ ∧ (z, y) ∈ r₂ :=
Iff.rfl
#align mem_comp_rel mem_compRel
@[simp]
theorem swap_idRel : Prod.swap '' idRel = @idRel α :=
Set.ext fun ⟨a, b⟩ => by simpa [image_swap_eq_preimage_swap] using eq_comm
#align swap_id_rel swap_idRel
theorem Monotone.compRel [Preorder β] {f g : β → Set (α × α)} (hf : Monotone f) (hg : Monotone g) :
Monotone fun x => f x ○ g x := fun _ _ h _ ⟨z, h₁, h₂⟩ => ⟨z, hf h h₁, hg h h₂⟩
#align monotone.comp_rel Monotone.compRel
@[mono]
theorem compRel_mono {f g h k : Set (α × α)} (h₁ : f ⊆ h) (h₂ : g ⊆ k) : f ○ g ⊆ h ○ k :=
fun _ ⟨z, h, h'⟩ => ⟨z, h₁ h, h₂ h'⟩
#align comp_rel_mono compRel_mono
theorem prod_mk_mem_compRel {a b c : α} {s t : Set (α × α)} (h₁ : (a, c) ∈ s) (h₂ : (c, b) ∈ t) :
(a, b) ∈ s ○ t :=
⟨c, h₁, h₂⟩
#align prod_mk_mem_comp_rel prod_mk_mem_compRel
@[simp]
theorem id_compRel {r : Set (α × α)} : idRel ○ r = r :=
Set.ext fun ⟨a, b⟩ => by simp
#align id_comp_rel id_compRel
theorem compRel_assoc {r s t : Set (α × α)} : r ○ s ○ t = r ○ (s ○ t) := by
ext ⟨a, b⟩; simp only [mem_compRel]; tauto
#align comp_rel_assoc compRel_assoc
theorem left_subset_compRel {s t : Set (α × α)} (h : idRel ⊆ t) : s ⊆ s ○ t := fun ⟨_x, y⟩ xy_in =>
⟨y, xy_in, h <| rfl⟩
#align left_subset_comp_rel left_subset_compRel
theorem right_subset_compRel {s t : Set (α × α)} (h : idRel ⊆ s) : t ⊆ s ○ t := fun ⟨x, _y⟩ xy_in =>
⟨x, h <| rfl, xy_in⟩
#align right_subset_comp_rel right_subset_compRel
theorem subset_comp_self {s : Set (α × α)} (h : idRel ⊆ s) : s ⊆ s ○ s :=
left_subset_compRel h
#align subset_comp_self subset_comp_self
theorem subset_iterate_compRel {s t : Set (α × α)} (h : idRel ⊆ s) (n : ℕ) :
t ⊆ (s ○ ·)^[n] t := by
induction' n with n ihn generalizing t
exacts [Subset.rfl, (right_subset_compRel h).trans ihn]
#align subset_iterate_comp_rel subset_iterate_compRel
/-- The relation is invariant under swapping factors. -/
def SymmetricRel (V : Set (α × α)) : Prop :=
Prod.swap ⁻¹' V = V
#align symmetric_rel SymmetricRel
/-- The maximal symmetric relation contained in a given relation. -/
def symmetrizeRel (V : Set (α × α)) : Set (α × α) :=
V ∩ Prod.swap ⁻¹' V
#align symmetrize_rel symmetrizeRel
theorem symmetric_symmetrizeRel (V : Set (α × α)) : SymmetricRel (symmetrizeRel V) := by
simp [SymmetricRel, symmetrizeRel, preimage_inter, inter_comm, ← preimage_comp]
#align symmetric_symmetrize_rel symmetric_symmetrizeRel
theorem symmetrizeRel_subset_self (V : Set (α × α)) : symmetrizeRel V ⊆ V :=
sep_subset _ _
#align symmetrize_rel_subset_self symmetrizeRel_subset_self
@[mono]
theorem symmetrize_mono {V W : Set (α × α)} (h : V ⊆ W) : symmetrizeRel V ⊆ symmetrizeRel W :=
inter_subset_inter h <| preimage_mono h
#align symmetrize_mono symmetrize_mono
theorem SymmetricRel.mk_mem_comm {V : Set (α × α)} (hV : SymmetricRel V) {x y : α} :
(x, y) ∈ V ↔ (y, x) ∈ V :=
Set.ext_iff.1 hV (y, x)
#align symmetric_rel.mk_mem_comm SymmetricRel.mk_mem_comm
theorem SymmetricRel.eq {U : Set (α × α)} (hU : SymmetricRel U) : Prod.swap ⁻¹' U = U :=
hU
#align symmetric_rel.eq SymmetricRel.eq
theorem SymmetricRel.inter {U V : Set (α × α)} (hU : SymmetricRel U) (hV : SymmetricRel V) :
SymmetricRel (U ∩ V) := by rw [SymmetricRel, preimage_inter, hU.eq, hV.eq]
#align symmetric_rel.inter SymmetricRel.inter
/-- This core description of a uniform space is outside of the type class hierarchy. It is useful
for constructions of uniform spaces, when the topology is derived from the uniform space. -/
structure UniformSpace.Core (α : Type u) where
/-- The uniformity filter. Once `UniformSpace` is defined, `𝓤 α` (`_root_.uniformity`) becomes the
normal form. -/
uniformity : Filter (α × α)
/-- Every set in the uniformity filter includes the diagonal. -/
refl : 𝓟 idRel ≤ uniformity
/-- If `s ∈ uniformity`, then `Prod.swap ⁻¹' s ∈ uniformity`. -/
symm : Tendsto Prod.swap uniformity uniformity
/-- For every set `u ∈ uniformity`, there exists `v ∈ uniformity` such that `v ○ v ⊆ u`. -/
comp : (uniformity.lift' fun s => s ○ s) ≤ uniformity
#align uniform_space.core UniformSpace.Core
protected theorem UniformSpace.Core.comp_mem_uniformity_sets {c : Core α} {s : Set (α × α)}
(hs : s ∈ c.uniformity) : ∃ t ∈ c.uniformity, t ○ t ⊆ s :=
(mem_lift'_sets <| monotone_id.compRel monotone_id).mp <| c.comp hs
/-- An alternative constructor for `UniformSpace.Core`. This version unfolds various
`Filter`-related definitions. -/
def UniformSpace.Core.mk' {α : Type u} (U : Filter (α × α)) (refl : ∀ r ∈ U, ∀ (x), (x, x) ∈ r)
(symm : ∀ r ∈ U, Prod.swap ⁻¹' r ∈ U) (comp : ∀ r ∈ U, ∃ t ∈ U, t ○ t ⊆ r) :
UniformSpace.Core α :=
⟨U, fun _r ru => idRel_subset.2 (refl _ ru), symm, fun _r ru =>
let ⟨_s, hs, hsr⟩ := comp _ ru
mem_of_superset (mem_lift' hs) hsr⟩
#align uniform_space.core.mk' UniformSpace.Core.mk'
/-- Defining a `UniformSpace.Core` from a filter basis satisfying some uniformity-like axioms. -/
def UniformSpace.Core.mkOfBasis {α : Type u} (B : FilterBasis (α × α))
(refl : ∀ r ∈ B, ∀ (x), (x, x) ∈ r) (symm : ∀ r ∈ B, ∃ t ∈ B, t ⊆ Prod.swap ⁻¹' r)
(comp : ∀ r ∈ B, ∃ t ∈ B, t ○ t ⊆ r) : UniformSpace.Core α where
uniformity := B.filter
refl := B.hasBasis.ge_iff.mpr fun _r ru => idRel_subset.2 <| refl _ ru
symm := (B.hasBasis.tendsto_iff B.hasBasis).mpr symm
comp := (HasBasis.le_basis_iff (B.hasBasis.lift' (monotone_id.compRel monotone_id))
B.hasBasis).2 comp
#align uniform_space.core.mk_of_basis UniformSpace.Core.mkOfBasis
/-- A uniform space generates a topological space -/
def UniformSpace.Core.toTopologicalSpace {α : Type u} (u : UniformSpace.Core α) :
TopologicalSpace α :=
.mkOfNhds fun x ↦ .comap (Prod.mk x) u.uniformity
#align uniform_space.core.to_topological_space UniformSpace.Core.toTopologicalSpace
theorem UniformSpace.Core.ext :
∀ {u₁ u₂ : UniformSpace.Core α}, u₁.uniformity = u₂.uniformity → u₁ = u₂
| ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, rfl => rfl
#align uniform_space.core_eq UniformSpace.Core.ext
theorem UniformSpace.Core.nhds_toTopologicalSpace {α : Type u} (u : Core α) (x : α) :
@nhds α u.toTopologicalSpace x = comap (Prod.mk x) u.uniformity := by
apply TopologicalSpace.nhds_mkOfNhds_of_hasBasis (fun _ ↦ (basis_sets _).comap _)
· exact fun a U hU ↦ u.refl hU rfl
· intro a U hU
rcases u.comp_mem_uniformity_sets hU with ⟨V, hV, hVU⟩
filter_upwards [preimage_mem_comap hV] with b hb
filter_upwards [preimage_mem_comap hV] with c hc
exact hVU ⟨b, hb, hc⟩
-- the topological structure is embedded in the uniform structure
-- to avoid instance diamond issues. See Note [forgetful inheritance].
/-- A uniform space is a generalization of the "uniform" topological aspects of a
metric space. It consists of a filter on `α × α` called the "uniformity", which
satisfies properties analogous to the reflexivity, symmetry, and triangle properties
of a metric.
A metric space has a natural uniformity, and a uniform space has a natural topology.
A topological group also has a natural uniformity, even when it is not metrizable. -/
class UniformSpace (α : Type u) extends TopologicalSpace α where
/-- The uniformity filter. -/
protected uniformity : Filter (α × α)
/-- If `s ∈ uniformity`, then `Prod.swap ⁻¹' s ∈ uniformity`. -/
protected symm : Tendsto Prod.swap uniformity uniformity
/-- For every set `u ∈ uniformity`, there exists `v ∈ uniformity` such that `v ○ v ⊆ u`. -/
protected comp : (uniformity.lift' fun s => s ○ s) ≤ uniformity
/-- The uniformity agrees with the topology: the neighborhoods filter of each point `x`
is equal to `Filter.comap (Prod.mk x) (𝓤 α)`. -/
protected nhds_eq_comap_uniformity (x : α) : 𝓝 x = comap (Prod.mk x) uniformity
#align uniform_space UniformSpace
#noalign uniform_space.mk' -- Can't be a `match_pattern`, so not useful anymore
/-- The uniformity is a filter on α × α (inferred from an ambient uniform space
structure on α). -/
def uniformity (α : Type u) [UniformSpace α] : Filter (α × α) :=
@UniformSpace.uniformity α _
#align uniformity uniformity
/-- Notation for the uniformity filter with respect to a non-standard `UniformSpace` instance. -/
scoped[Uniformity] notation "𝓤[" u "]" => @uniformity _ u
@[inherit_doc] -- Porting note (#11215): TODO: should we drop the `uniformity` def?
scoped[Uniformity] notation "𝓤" => uniformity
/-- Construct a `UniformSpace` from a `u : UniformSpace.Core` and a `TopologicalSpace` structure
that is equal to `u.toTopologicalSpace`. -/
abbrev UniformSpace.ofCoreEq {α : Type u} (u : UniformSpace.Core α) (t : TopologicalSpace α)
(h : t = u.toTopologicalSpace) : UniformSpace α where
__ := u
toTopologicalSpace := t
nhds_eq_comap_uniformity x := by rw [h, u.nhds_toTopologicalSpace]
#align uniform_space.of_core_eq UniformSpace.ofCoreEq
/-- Construct a `UniformSpace` from a `UniformSpace.Core`. -/
abbrev UniformSpace.ofCore {α : Type u} (u : UniformSpace.Core α) : UniformSpace α :=
.ofCoreEq u _ rfl
#align uniform_space.of_core UniformSpace.ofCore
/-- Construct a `UniformSpace.Core` from a `UniformSpace`. -/
abbrev UniformSpace.toCore (u : UniformSpace α) : UniformSpace.Core α where
__ := u
refl := by
rintro U hU ⟨x, y⟩ (rfl : x = y)
have : Prod.mk x ⁻¹' U ∈ 𝓝 x := by
rw [UniformSpace.nhds_eq_comap_uniformity]
exact preimage_mem_comap hU
convert mem_of_mem_nhds this
theorem UniformSpace.toCore_toTopologicalSpace (u : UniformSpace α) :
u.toCore.toTopologicalSpace = u.toTopologicalSpace :=
TopologicalSpace.ext_nhds fun a ↦ by
rw [u.nhds_eq_comap_uniformity, u.toCore.nhds_toTopologicalSpace]
#align uniform_space.to_core_to_topological_space UniformSpace.toCore_toTopologicalSpace
/-- Build a `UniformSpace` from a `UniformSpace.Core` and a compatible topology.
Use `UniformSpace.mk` instead to avoid proving
the unnecessary assumption `UniformSpace.Core.refl`.
The main constructor used to use a different compatibility assumption.
This definition was created as a step towards porting to a new definition.
Now the main definition is ported,
so this constructor will be removed in a few months. -/
@[deprecated UniformSpace.mk (since := "2024-03-20")]
def UniformSpace.ofNhdsEqComap (u : UniformSpace.Core α) (_t : TopologicalSpace α)
(h : ∀ x, 𝓝 x = u.uniformity.comap (Prod.mk x)) : UniformSpace α where
__ := u
nhds_eq_comap_uniformity := h
@[ext]
protected theorem UniformSpace.ext {u₁ u₂ : UniformSpace α} (h : 𝓤[u₁] = 𝓤[u₂]) : u₁ = u₂ := by
have : u₁.toTopologicalSpace = u₂.toTopologicalSpace := TopologicalSpace.ext_nhds fun x ↦ by
rw [u₁.nhds_eq_comap_uniformity, u₂.nhds_eq_comap_uniformity]
exact congr_arg (comap _) h
cases u₁; cases u₂; congr
#align uniform_space_eq UniformSpace.ext
protected theorem UniformSpace.ext_iff {u₁ u₂ : UniformSpace α} :
u₁ = u₂ ↔ ∀ s, s ∈ 𝓤[u₁] ↔ s ∈ 𝓤[u₂] :=
⟨fun h _ => h ▸ Iff.rfl, fun h => by ext; exact h _⟩
theorem UniformSpace.ofCoreEq_toCore (u : UniformSpace α) (t : TopologicalSpace α)
(h : t = u.toCore.toTopologicalSpace) : .ofCoreEq u.toCore t h = u :=
UniformSpace.ext rfl
#align uniform_space.of_core_eq_to_core UniformSpace.ofCoreEq_toCore
/-- Replace topology in a `UniformSpace` instance with a propositionally (but possibly not
definitionally) equal one. -/
abbrev UniformSpace.replaceTopology {α : Type*} [i : TopologicalSpace α] (u : UniformSpace α)
(h : i = u.toTopologicalSpace) : UniformSpace α where
__ := u
toTopologicalSpace := i
nhds_eq_comap_uniformity x := by rw [h, u.nhds_eq_comap_uniformity]
#align uniform_space.replace_topology UniformSpace.replaceTopology
theorem UniformSpace.replaceTopology_eq {α : Type*} [i : TopologicalSpace α] (u : UniformSpace α)
(h : i = u.toTopologicalSpace) : u.replaceTopology h = u :=
UniformSpace.ext rfl
#align uniform_space.replace_topology_eq UniformSpace.replaceTopology_eq
-- Porting note: rfc: use `UniformSpace.Core.mkOfBasis`? This will change defeq here and there
/-- Define a `UniformSpace` using a "distance" function. The function can be, e.g., the
distance in a (usual or extended) metric space or an absolute value on a ring. -/
def UniformSpace.ofFun {α : Type u} {β : Type v} [OrderedAddCommMonoid β]
(d : α → α → β) (refl : ∀ x, d x x = 0) (symm : ∀ x y, d x y = d y x)
(triangle : ∀ x y z, d x z ≤ d x y + d y z)
(half : ∀ ε > (0 : β), ∃ δ > (0 : β), ∀ x < δ, ∀ y < δ, x + y < ε) :
UniformSpace α :=
.ofCore
{ uniformity := ⨅ r > 0, 𝓟 { x | d x.1 x.2 < r }
refl := le_iInf₂ fun r hr => principal_mono.2 <| idRel_subset.2 fun x => by simpa [refl]
symm := tendsto_iInf_iInf fun r => tendsto_iInf_iInf fun _ => tendsto_principal_principal.2
fun x hx => by rwa [mem_setOf, symm]
comp := le_iInf₂ fun r hr => let ⟨δ, h0, hδr⟩ := half r hr; le_principal_iff.2 <|
mem_of_superset
(mem_lift' <| mem_iInf_of_mem δ <| mem_iInf_of_mem h0 <| mem_principal_self _)
fun (x, z) ⟨y, h₁, h₂⟩ => (triangle _ _ _).trans_lt (hδr _ h₁ _ h₂) }
#align uniform_space.of_fun UniformSpace.ofFun
theorem UniformSpace.hasBasis_ofFun {α : Type u} {β : Type v} [LinearOrderedAddCommMonoid β]
(h₀ : ∃ x : β, 0 < x) (d : α → α → β) (refl : ∀ x, d x x = 0) (symm : ∀ x y, d x y = d y x)
(triangle : ∀ x y z, d x z ≤ d x y + d y z)
(half : ∀ ε > (0 : β), ∃ δ > (0 : β), ∀ x < δ, ∀ y < δ, x + y < ε) :
𝓤[.ofFun d refl symm triangle half].HasBasis ((0 : β) < ·) (fun ε => { x | d x.1 x.2 < ε }) :=
hasBasis_biInf_principal'
(fun ε₁ h₁ ε₂ h₂ => ⟨min ε₁ ε₂, lt_min h₁ h₂, fun _x hx => lt_of_lt_of_le hx (min_le_left _ _),
fun _x hx => lt_of_lt_of_le hx (min_le_right _ _)⟩) h₀
#align uniform_space.has_basis_of_fun UniformSpace.hasBasis_ofFun
section UniformSpace
variable [UniformSpace α]
theorem nhds_eq_comap_uniformity {x : α} : 𝓝 x = (𝓤 α).comap (Prod.mk x) :=
UniformSpace.nhds_eq_comap_uniformity x
#align nhds_eq_comap_uniformity nhds_eq_comap_uniformity
theorem isOpen_uniformity {s : Set α} :
IsOpen s ↔ ∀ x ∈ s, { p : α × α | p.1 = x → p.2 ∈ s } ∈ 𝓤 α := by
simp only [isOpen_iff_mem_nhds, nhds_eq_comap_uniformity, mem_comap_prod_mk]
#align is_open_uniformity isOpen_uniformity
theorem refl_le_uniformity : 𝓟 idRel ≤ 𝓤 α :=
(@UniformSpace.toCore α _).refl
#align refl_le_uniformity refl_le_uniformity
instance uniformity.neBot [Nonempty α] : NeBot (𝓤 α) :=
diagonal_nonempty.principal_neBot.mono refl_le_uniformity
#align uniformity.ne_bot uniformity.neBot
theorem refl_mem_uniformity {x : α} {s : Set (α × α)} (h : s ∈ 𝓤 α) : (x, x) ∈ s :=
refl_le_uniformity h rfl
#align refl_mem_uniformity refl_mem_uniformity
theorem mem_uniformity_of_eq {x y : α} {s : Set (α × α)} (h : s ∈ 𝓤 α) (hx : x = y) : (x, y) ∈ s :=
refl_le_uniformity h hx
#align mem_uniformity_of_eq mem_uniformity_of_eq
theorem symm_le_uniformity : map (@Prod.swap α α) (𝓤 _) ≤ 𝓤 _ :=
UniformSpace.symm
#align symm_le_uniformity symm_le_uniformity
theorem comp_le_uniformity : ((𝓤 α).lift' fun s : Set (α × α) => s ○ s) ≤ 𝓤 α :=
UniformSpace.comp
#align comp_le_uniformity comp_le_uniformity
theorem lift'_comp_uniformity : ((𝓤 α).lift' fun s : Set (α × α) => s ○ s) = 𝓤 α :=
comp_le_uniformity.antisymm <| le_lift'.2 fun _s hs ↦ mem_of_superset hs <|
subset_comp_self <| idRel_subset.2 fun _ ↦ refl_mem_uniformity hs
theorem tendsto_swap_uniformity : Tendsto (@Prod.swap α α) (𝓤 α) (𝓤 α) :=
symm_le_uniformity
#align tendsto_swap_uniformity tendsto_swap_uniformity
theorem comp_mem_uniformity_sets {s : Set (α × α)} (hs : s ∈ 𝓤 α) : ∃ t ∈ 𝓤 α, t ○ t ⊆ s :=
(mem_lift'_sets <| monotone_id.compRel monotone_id).mp <| comp_le_uniformity hs
#align comp_mem_uniformity_sets comp_mem_uniformity_sets
/-- If `s ∈ 𝓤 α`, then for any natural `n`, for a subset `t` of a sufficiently small set in `𝓤 α`,
we have `t ○ t ○ ... ○ t ⊆ s` (`n` compositions). -/
theorem eventually_uniformity_iterate_comp_subset {s : Set (α × α)} (hs : s ∈ 𝓤 α) (n : ℕ) :
∀ᶠ t in (𝓤 α).smallSets, (t ○ ·)^[n] t ⊆ s := by
suffices ∀ᶠ t in (𝓤 α).smallSets, t ⊆ s ∧ (t ○ ·)^[n] t ⊆ s from (eventually_and.1 this).2
induction' n with n ihn generalizing s
· simpa
rcases comp_mem_uniformity_sets hs with ⟨t, htU, hts⟩
refine (ihn htU).mono fun U hU => ?_
rw [Function.iterate_succ_apply']
exact
⟨hU.1.trans <| (subset_comp_self <| refl_le_uniformity htU).trans hts,
(compRel_mono hU.1 hU.2).trans hts⟩
#align eventually_uniformity_iterate_comp_subset eventually_uniformity_iterate_comp_subset
/-- If `s ∈ 𝓤 α`, then for a subset `t` of a sufficiently small set in `𝓤 α`,
we have `t ○ t ⊆ s`. -/
theorem eventually_uniformity_comp_subset {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∀ᶠ t in (𝓤 α).smallSets, t ○ t ⊆ s :=
eventually_uniformity_iterate_comp_subset hs 1
#align eventually_uniformity_comp_subset eventually_uniformity_comp_subset
/-- Relation `fun f g ↦ Tendsto (fun x ↦ (f x, g x)) l (𝓤 α)` is transitive. -/
theorem Filter.Tendsto.uniformity_trans {l : Filter β} {f₁ f₂ f₃ : β → α}
(h₁₂ : Tendsto (fun x => (f₁ x, f₂ x)) l (𝓤 α))
(h₂₃ : Tendsto (fun x => (f₂ x, f₃ x)) l (𝓤 α)) : Tendsto (fun x => (f₁ x, f₃ x)) l (𝓤 α) := by
refine le_trans (le_lift'.2 fun s hs => mem_map.2 ?_) comp_le_uniformity
filter_upwards [mem_map.1 (h₁₂ hs), mem_map.1 (h₂₃ hs)] with x hx₁₂ hx₂₃ using ⟨_, hx₁₂, hx₂₃⟩
#align filter.tendsto.uniformity_trans Filter.Tendsto.uniformity_trans
/-- Relation `fun f g ↦ Tendsto (fun x ↦ (f x, g x)) l (𝓤 α)` is symmetric. -/
theorem Filter.Tendsto.uniformity_symm {l : Filter β} {f : β → α × α} (h : Tendsto f l (𝓤 α)) :
Tendsto (fun x => ((f x).2, (f x).1)) l (𝓤 α) :=
tendsto_swap_uniformity.comp h
#align filter.tendsto.uniformity_symm Filter.Tendsto.uniformity_symm
/-- Relation `fun f g ↦ Tendsto (fun x ↦ (f x, g x)) l (𝓤 α)` is reflexive. -/
theorem tendsto_diag_uniformity (f : β → α) (l : Filter β) :
Tendsto (fun x => (f x, f x)) l (𝓤 α) := fun _s hs =>
mem_map.2 <| univ_mem' fun _ => refl_mem_uniformity hs
#align tendsto_diag_uniformity tendsto_diag_uniformity
theorem tendsto_const_uniformity {a : α} {f : Filter β} : Tendsto (fun _ => (a, a)) f (𝓤 α) :=
tendsto_diag_uniformity (fun _ => a) f
#align tendsto_const_uniformity tendsto_const_uniformity
theorem symm_of_uniformity {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∃ t ∈ 𝓤 α, (∀ a b, (a, b) ∈ t → (b, a) ∈ t) ∧ t ⊆ s :=
have : preimage Prod.swap s ∈ 𝓤 α := symm_le_uniformity hs
⟨s ∩ preimage Prod.swap s, inter_mem hs this, fun _ _ ⟨h₁, h₂⟩ => ⟨h₂, h₁⟩, inter_subset_left⟩
#align symm_of_uniformity symm_of_uniformity
theorem comp_symm_of_uniformity {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∃ t ∈ 𝓤 α, (∀ {a b}, (a, b) ∈ t → (b, a) ∈ t) ∧ t ○ t ⊆ s :=
let ⟨_t, ht₁, ht₂⟩ := comp_mem_uniformity_sets hs
let ⟨t', ht', ht'₁, ht'₂⟩ := symm_of_uniformity ht₁
⟨t', ht', ht'₁ _ _, Subset.trans (monotone_id.compRel monotone_id ht'₂) ht₂⟩
#align comp_symm_of_uniformity comp_symm_of_uniformity
theorem uniformity_le_symm : 𝓤 α ≤ @Prod.swap α α <$> 𝓤 α := by
rw [map_swap_eq_comap_swap]; exact tendsto_swap_uniformity.le_comap
#align uniformity_le_symm uniformity_le_symm
theorem uniformity_eq_symm : 𝓤 α = @Prod.swap α α <$> 𝓤 α :=
le_antisymm uniformity_le_symm symm_le_uniformity
#align uniformity_eq_symm uniformity_eq_symm
@[simp]
theorem comap_swap_uniformity : comap (@Prod.swap α α) (𝓤 α) = 𝓤 α :=
(congr_arg _ uniformity_eq_symm).trans <| comap_map Prod.swap_injective
#align comap_swap_uniformity comap_swap_uniformity
theorem symmetrize_mem_uniformity {V : Set (α × α)} (h : V ∈ 𝓤 α) : symmetrizeRel V ∈ 𝓤 α := by
apply (𝓤 α).inter_sets h
rw [← image_swap_eq_preimage_swap, uniformity_eq_symm]
exact image_mem_map h
#align symmetrize_mem_uniformity symmetrize_mem_uniformity
/-- Symmetric entourages form a basis of `𝓤 α` -/
theorem UniformSpace.hasBasis_symmetric :
(𝓤 α).HasBasis (fun s : Set (α × α) => s ∈ 𝓤 α ∧ SymmetricRel s) id :=
hasBasis_self.2 fun t t_in =>
⟨symmetrizeRel t, symmetrize_mem_uniformity t_in, symmetric_symmetrizeRel t,
symmetrizeRel_subset_self t⟩
#align uniform_space.has_basis_symmetric UniformSpace.hasBasis_symmetric
theorem uniformity_lift_le_swap {g : Set (α × α) → Filter β} {f : Filter β} (hg : Monotone g)
(h : ((𝓤 α).lift fun s => g (preimage Prod.swap s)) ≤ f) : (𝓤 α).lift g ≤ f :=
calc
(𝓤 α).lift g ≤ (Filter.map (@Prod.swap α α) <| 𝓤 α).lift g :=
lift_mono uniformity_le_symm le_rfl
_ ≤ _ := by rw [map_lift_eq2 hg, image_swap_eq_preimage_swap]; exact h
#align uniformity_lift_le_swap uniformity_lift_le_swap
theorem uniformity_lift_le_comp {f : Set (α × α) → Filter β} (h : Monotone f) :
((𝓤 α).lift fun s => f (s ○ s)) ≤ (𝓤 α).lift f :=
calc
((𝓤 α).lift fun s => f (s ○ s)) = ((𝓤 α).lift' fun s : Set (α × α) => s ○ s).lift f := by
rw [lift_lift'_assoc]
· exact monotone_id.compRel monotone_id
· exact h
_ ≤ (𝓤 α).lift f := lift_mono comp_le_uniformity le_rfl
#align uniformity_lift_le_comp uniformity_lift_le_comp
-- Porting note (#10756): new lemma
theorem comp3_mem_uniformity {s : Set (α × α)} (hs : s ∈ 𝓤 α) : ∃ t ∈ 𝓤 α, t ○ (t ○ t) ⊆ s :=
let ⟨_t', ht', ht's⟩ := comp_mem_uniformity_sets hs
let ⟨t, ht, htt'⟩ := comp_mem_uniformity_sets ht'
⟨t, ht, (compRel_mono ((subset_comp_self (refl_le_uniformity ht)).trans htt') htt').trans ht's⟩
/-- See also `comp3_mem_uniformity`. -/
theorem comp_le_uniformity3 : ((𝓤 α).lift' fun s : Set (α × α) => s ○ (s ○ s)) ≤ 𝓤 α := fun _ h =>
let ⟨_t, htU, ht⟩ := comp3_mem_uniformity h
mem_of_superset (mem_lift' htU) ht
#align comp_le_uniformity3 comp_le_uniformity3
/-- See also `comp_open_symm_mem_uniformity_sets`. -/
theorem comp_symm_mem_uniformity_sets {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∃ t ∈ 𝓤 α, SymmetricRel t ∧ t ○ t ⊆ s := by
obtain ⟨w, w_in, w_sub⟩ : ∃ w ∈ 𝓤 α, w ○ w ⊆ s := comp_mem_uniformity_sets hs
use symmetrizeRel w, symmetrize_mem_uniformity w_in, symmetric_symmetrizeRel w
have : symmetrizeRel w ⊆ w := symmetrizeRel_subset_self w
calc symmetrizeRel w ○ symmetrizeRel w
_ ⊆ w ○ w := by mono
_ ⊆ s := w_sub
#align comp_symm_mem_uniformity_sets comp_symm_mem_uniformity_sets
theorem subset_comp_self_of_mem_uniformity {s : Set (α × α)} (h : s ∈ 𝓤 α) : s ⊆ s ○ s :=
subset_comp_self (refl_le_uniformity h)
#align subset_comp_self_of_mem_uniformity subset_comp_self_of_mem_uniformity
theorem comp_comp_symm_mem_uniformity_sets {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∃ t ∈ 𝓤 α, SymmetricRel t ∧ t ○ t ○ t ⊆ s := by
rcases comp_symm_mem_uniformity_sets hs with ⟨w, w_in, _, w_sub⟩
rcases comp_symm_mem_uniformity_sets w_in with ⟨t, t_in, t_symm, t_sub⟩
use t, t_in, t_symm
have : t ⊆ t ○ t := subset_comp_self_of_mem_uniformity t_in
-- Porting note: Needed the following `have`s to make `mono` work
have ht := Subset.refl t
have hw := Subset.refl w
calc
t ○ t ○ t ⊆ w ○ t := by mono
_ ⊆ w ○ (t ○ t) := by mono
_ ⊆ w ○ w := by mono
_ ⊆ s := w_sub
#align comp_comp_symm_mem_uniformity_sets comp_comp_symm_mem_uniformity_sets
/-!
### Balls in uniform spaces
-/
/-- The ball around `(x : β)` with respect to `(V : Set (β × β))`. Intended to be
used for `V ∈ 𝓤 β`, but this is not needed for the definition. Recovers the
notions of metric space ball when `V = {p | dist p.1 p.2 < r }`. -/
def UniformSpace.ball (x : β) (V : Set (β × β)) : Set β :=
Prod.mk x ⁻¹' V
#align uniform_space.ball UniformSpace.ball
open UniformSpace (ball)
theorem UniformSpace.mem_ball_self (x : α) {V : Set (α × α)} (hV : V ∈ 𝓤 α) : x ∈ ball x V :=
refl_mem_uniformity hV
#align uniform_space.mem_ball_self UniformSpace.mem_ball_self
/-- The triangle inequality for `UniformSpace.ball` -/
theorem mem_ball_comp {V W : Set (β × β)} {x y z} (h : y ∈ ball x V) (h' : z ∈ ball y W) :
z ∈ ball x (V ○ W) :=
prod_mk_mem_compRel h h'
#align mem_ball_comp mem_ball_comp
theorem ball_subset_of_comp_subset {V W : Set (β × β)} {x y} (h : x ∈ ball y W) (h' : W ○ W ⊆ V) :
ball x W ⊆ ball y V := fun _z z_in => h' (mem_ball_comp h z_in)
#align ball_subset_of_comp_subset ball_subset_of_comp_subset
theorem ball_mono {V W : Set (β × β)} (h : V ⊆ W) (x : β) : ball x V ⊆ ball x W :=
preimage_mono h
#align ball_mono ball_mono
theorem ball_inter (x : β) (V W : Set (β × β)) : ball x (V ∩ W) = ball x V ∩ ball x W :=
preimage_inter
#align ball_inter ball_inter
theorem ball_inter_left (x : β) (V W : Set (β × β)) : ball x (V ∩ W) ⊆ ball x V :=
ball_mono inter_subset_left x
#align ball_inter_left ball_inter_left
theorem ball_inter_right (x : β) (V W : Set (β × β)) : ball x (V ∩ W) ⊆ ball x W :=
ball_mono inter_subset_right x
#align ball_inter_right ball_inter_right
theorem mem_ball_symmetry {V : Set (β × β)} (hV : SymmetricRel V) {x y} :
x ∈ ball y V ↔ y ∈ ball x V :=
show (x, y) ∈ Prod.swap ⁻¹' V ↔ (x, y) ∈ V by
unfold SymmetricRel at hV
rw [hV]
#align mem_ball_symmetry mem_ball_symmetry
theorem ball_eq_of_symmetry {V : Set (β × β)} (hV : SymmetricRel V) {x} :
ball x V = { y | (y, x) ∈ V } := by
ext y
rw [mem_ball_symmetry hV]
exact Iff.rfl
#align ball_eq_of_symmetry ball_eq_of_symmetry
theorem mem_comp_of_mem_ball {V W : Set (β × β)} {x y z : β} (hV : SymmetricRel V)
(hx : x ∈ ball z V) (hy : y ∈ ball z W) : (x, y) ∈ V ○ W := by
rw [mem_ball_symmetry hV] at hx
exact ⟨z, hx, hy⟩
#align mem_comp_of_mem_ball mem_comp_of_mem_ball
theorem UniformSpace.isOpen_ball (x : α) {V : Set (α × α)} (hV : IsOpen V) : IsOpen (ball x V) :=
hV.preimage <| continuous_const.prod_mk continuous_id
#align uniform_space.is_open_ball UniformSpace.isOpen_ball
theorem UniformSpace.isClosed_ball (x : α) {V : Set (α × α)} (hV : IsClosed V) :
IsClosed (ball x V) :=
hV.preimage <| continuous_const.prod_mk continuous_id
theorem mem_comp_comp {V W M : Set (β × β)} (hW' : SymmetricRel W) {p : β × β} :
p ∈ V ○ M ○ W ↔ (ball p.1 V ×ˢ ball p.2 W ∩ M).Nonempty := by
cases' p with x y
constructor
· rintro ⟨z, ⟨w, hpw, hwz⟩, hzy⟩
exact ⟨(w, z), ⟨hpw, by rwa [mem_ball_symmetry hW']⟩, hwz⟩
· rintro ⟨⟨w, z⟩, ⟨w_in, z_in⟩, hwz⟩
rw [mem_ball_symmetry hW'] at z_in
exact ⟨z, ⟨w, w_in, hwz⟩, z_in⟩
#align mem_comp_comp mem_comp_comp
/-!
### Neighborhoods in uniform spaces
-/
theorem mem_nhds_uniformity_iff_right {x : α} {s : Set α} :
s ∈ 𝓝 x ↔ { p : α × α | p.1 = x → p.2 ∈ s } ∈ 𝓤 α := by
simp only [nhds_eq_comap_uniformity, mem_comap_prod_mk]
#align mem_nhds_uniformity_iff_right mem_nhds_uniformity_iff_right
theorem mem_nhds_uniformity_iff_left {x : α} {s : Set α} :
s ∈ 𝓝 x ↔ { p : α × α | p.2 = x → p.1 ∈ s } ∈ 𝓤 α := by
rw [uniformity_eq_symm, mem_nhds_uniformity_iff_right]
simp only [map_def, mem_map, preimage_setOf_eq, Prod.snd_swap, Prod.fst_swap]
#align mem_nhds_uniformity_iff_left mem_nhds_uniformity_iff_left
theorem nhdsWithin_eq_comap_uniformity_of_mem {x : α} {T : Set α} (hx : x ∈ T) (S : Set α) :
𝓝[S] x = (𝓤 α ⊓ 𝓟 (T ×ˢ S)).comap (Prod.mk x) := by
simp [nhdsWithin, nhds_eq_comap_uniformity, hx]
theorem nhdsWithin_eq_comap_uniformity {x : α} (S : Set α) :
𝓝[S] x = (𝓤 α ⊓ 𝓟 (univ ×ˢ S)).comap (Prod.mk x) :=
nhdsWithin_eq_comap_uniformity_of_mem (mem_univ _) S
/-- See also `isOpen_iff_open_ball_subset`. -/
theorem isOpen_iff_ball_subset {s : Set α} : IsOpen s ↔ ∀ x ∈ s, ∃ V ∈ 𝓤 α, ball x V ⊆ s := by
simp_rw [isOpen_iff_mem_nhds, nhds_eq_comap_uniformity, mem_comap, ball]
#align is_open_iff_ball_subset isOpen_iff_ball_subset
theorem nhds_basis_uniformity' {p : ι → Prop} {s : ι → Set (α × α)} (h : (𝓤 α).HasBasis p s)
{x : α} : (𝓝 x).HasBasis p fun i => ball x (s i) := by
rw [nhds_eq_comap_uniformity]
exact h.comap (Prod.mk x)
#align nhds_basis_uniformity' nhds_basis_uniformity'
theorem nhds_basis_uniformity {p : ι → Prop} {s : ι → Set (α × α)} (h : (𝓤 α).HasBasis p s)
{x : α} : (𝓝 x).HasBasis p fun i => { y | (y, x) ∈ s i } := by
replace h := h.comap Prod.swap
rw [comap_swap_uniformity] at h
exact nhds_basis_uniformity' h
#align nhds_basis_uniformity nhds_basis_uniformity
theorem nhds_eq_comap_uniformity' {x : α} : 𝓝 x = (𝓤 α).comap fun y => (y, x) :=
(nhds_basis_uniformity (𝓤 α).basis_sets).eq_of_same_basis <| (𝓤 α).basis_sets.comap _
#align nhds_eq_comap_uniformity' nhds_eq_comap_uniformity'
theorem UniformSpace.mem_nhds_iff {x : α} {s : Set α} : s ∈ 𝓝 x ↔ ∃ V ∈ 𝓤 α, ball x V ⊆ s := by
rw [nhds_eq_comap_uniformity, mem_comap]
simp_rw [ball]
#align uniform_space.mem_nhds_iff UniformSpace.mem_nhds_iff
theorem UniformSpace.ball_mem_nhds (x : α) ⦃V : Set (α × α)⦄ (V_in : V ∈ 𝓤 α) : ball x V ∈ 𝓝 x := by
rw [UniformSpace.mem_nhds_iff]
exact ⟨V, V_in, Subset.rfl⟩
#align uniform_space.ball_mem_nhds UniformSpace.ball_mem_nhds
theorem UniformSpace.ball_mem_nhdsWithin {x : α} {S : Set α} ⦃V : Set (α × α)⦄ (x_in : x ∈ S)
(V_in : V ∈ 𝓤 α ⊓ 𝓟 (S ×ˢ S)) : ball x V ∈ 𝓝[S] x := by
rw [nhdsWithin_eq_comap_uniformity_of_mem x_in, mem_comap]
exact ⟨V, V_in, Subset.rfl⟩
theorem UniformSpace.mem_nhds_iff_symm {x : α} {s : Set α} :
s ∈ 𝓝 x ↔ ∃ V ∈ 𝓤 α, SymmetricRel V ∧ ball x V ⊆ s := by
rw [UniformSpace.mem_nhds_iff]
constructor
· rintro ⟨V, V_in, V_sub⟩
use symmetrizeRel V, symmetrize_mem_uniformity V_in, symmetric_symmetrizeRel V
exact Subset.trans (ball_mono (symmetrizeRel_subset_self V) x) V_sub
· rintro ⟨V, V_in, _, V_sub⟩
exact ⟨V, V_in, V_sub⟩
#align uniform_space.mem_nhds_iff_symm UniformSpace.mem_nhds_iff_symm
theorem UniformSpace.hasBasis_nhds (x : α) :
HasBasis (𝓝 x) (fun s : Set (α × α) => s ∈ 𝓤 α ∧ SymmetricRel s) fun s => ball x s :=
⟨fun t => by simp [UniformSpace.mem_nhds_iff_symm, and_assoc]⟩
#align uniform_space.has_basis_nhds UniformSpace.hasBasis_nhds
open UniformSpace
theorem UniformSpace.mem_closure_iff_symm_ball {s : Set α} {x} :
x ∈ closure s ↔ ∀ {V}, V ∈ 𝓤 α → SymmetricRel V → (s ∩ ball x V).Nonempty := by
simp [mem_closure_iff_nhds_basis (hasBasis_nhds x), Set.Nonempty]
#align uniform_space.mem_closure_iff_symm_ball UniformSpace.mem_closure_iff_symm_ball
theorem UniformSpace.mem_closure_iff_ball {s : Set α} {x} :
x ∈ closure s ↔ ∀ {V}, V ∈ 𝓤 α → (ball x V ∩ s).Nonempty := by
simp [mem_closure_iff_nhds_basis' (nhds_basis_uniformity' (𝓤 α).basis_sets)]
#align uniform_space.mem_closure_iff_ball UniformSpace.mem_closure_iff_ball
theorem UniformSpace.hasBasis_nhds_prod (x y : α) :
HasBasis (𝓝 (x, y)) (fun s => s ∈ 𝓤 α ∧ SymmetricRel s) fun s => ball x s ×ˢ ball y s := by
rw [nhds_prod_eq]
apply (hasBasis_nhds x).prod_same_index (hasBasis_nhds y)
rintro U V ⟨U_in, U_symm⟩ ⟨V_in, V_symm⟩
exact
⟨U ∩ V, ⟨(𝓤 α).inter_sets U_in V_in, U_symm.inter V_symm⟩, ball_inter_left x U V,
ball_inter_right y U V⟩
#align uniform_space.has_basis_nhds_prod UniformSpace.hasBasis_nhds_prod
theorem nhds_eq_uniformity {x : α} : 𝓝 x = (𝓤 α).lift' (ball x) :=
(nhds_basis_uniformity' (𝓤 α).basis_sets).eq_biInf
#align nhds_eq_uniformity nhds_eq_uniformity
theorem nhds_eq_uniformity' {x : α} : 𝓝 x = (𝓤 α).lift' fun s => { y | (y, x) ∈ s } :=
(nhds_basis_uniformity (𝓤 α).basis_sets).eq_biInf
#align nhds_eq_uniformity' nhds_eq_uniformity'
theorem mem_nhds_left (x : α) {s : Set (α × α)} (h : s ∈ 𝓤 α) : { y : α | (x, y) ∈ s } ∈ 𝓝 x :=
ball_mem_nhds x h
#align mem_nhds_left mem_nhds_left
theorem mem_nhds_right (y : α) {s : Set (α × α)} (h : s ∈ 𝓤 α) : { x : α | (x, y) ∈ s } ∈ 𝓝 y :=
mem_nhds_left _ (symm_le_uniformity h)
#align mem_nhds_right mem_nhds_right
theorem exists_mem_nhds_ball_subset_of_mem_nhds {a : α} {U : Set α} (h : U ∈ 𝓝 a) :
∃ V ∈ 𝓝 a, ∃ t ∈ 𝓤 α, ∀ a' ∈ V, UniformSpace.ball a' t ⊆ U :=
let ⟨t, ht, htU⟩ := comp_mem_uniformity_sets (mem_nhds_uniformity_iff_right.1 h)
⟨_, mem_nhds_left a ht, t, ht, fun a₁ h₁ a₂ h₂ => @htU (a, a₂) ⟨a₁, h₁, h₂⟩ rfl⟩
#align exists_mem_nhds_ball_subset_of_mem_nhds exists_mem_nhds_ball_subset_of_mem_nhds
theorem tendsto_right_nhds_uniformity {a : α} : Tendsto (fun a' => (a', a)) (𝓝 a) (𝓤 α) := fun _ =>
mem_nhds_right a
#align tendsto_right_nhds_uniformity tendsto_right_nhds_uniformity
theorem tendsto_left_nhds_uniformity {a : α} : Tendsto (fun a' => (a, a')) (𝓝 a) (𝓤 α) := fun _ =>
mem_nhds_left a
#align tendsto_left_nhds_uniformity tendsto_left_nhds_uniformity
theorem lift_nhds_left {x : α} {g : Set α → Filter β} (hg : Monotone g) :
(𝓝 x).lift g = (𝓤 α).lift fun s : Set (α × α) => g (ball x s) := by
rw [nhds_eq_comap_uniformity, comap_lift_eq2 hg]
simp_rw [ball, Function.comp]
#align lift_nhds_left lift_nhds_left
theorem lift_nhds_right {x : α} {g : Set α → Filter β} (hg : Monotone g) :
(𝓝 x).lift g = (𝓤 α).lift fun s : Set (α × α) => g { y | (y, x) ∈ s } := by
rw [nhds_eq_comap_uniformity', comap_lift_eq2 hg]
simp_rw [Function.comp, preimage]
#align lift_nhds_right lift_nhds_right
theorem nhds_nhds_eq_uniformity_uniformity_prod {a b : α} :
𝓝 a ×ˢ 𝓝 b = (𝓤 α).lift fun s : Set (α × α) =>
(𝓤 α).lift' fun t => { y : α | (y, a) ∈ s } ×ˢ { y : α | (b, y) ∈ t } := by
rw [nhds_eq_uniformity', nhds_eq_uniformity, prod_lift'_lift']
exacts [rfl, monotone_preimage, monotone_preimage]
#align nhds_nhds_eq_uniformity_uniformity_prod nhds_nhds_eq_uniformity_uniformity_prod
theorem nhds_eq_uniformity_prod {a b : α} :
𝓝 (a, b) =
(𝓤 α).lift' fun s : Set (α × α) => { y : α | (y, a) ∈ s } ×ˢ { y : α | (b, y) ∈ s } := by
rw [nhds_prod_eq, nhds_nhds_eq_uniformity_uniformity_prod, lift_lift'_same_eq_lift']
· exact fun s => monotone_const.set_prod monotone_preimage
· refine fun t => Monotone.set_prod ?_ monotone_const
exact monotone_preimage (f := fun y => (y, a))
#align nhds_eq_uniformity_prod nhds_eq_uniformity_prod
theorem nhdset_of_mem_uniformity {d : Set (α × α)} (s : Set (α × α)) (hd : d ∈ 𝓤 α) :
∃ t : Set (α × α), IsOpen t ∧ s ⊆ t ∧
t ⊆ { p | ∃ x y, (p.1, x) ∈ d ∧ (x, y) ∈ s ∧ (y, p.2) ∈ d } := by
let cl_d := { p : α × α | ∃ x y, (p.1, x) ∈ d ∧ (x, y) ∈ s ∧ (y, p.2) ∈ d }
have : ∀ p ∈ s, ∃ t, t ⊆ cl_d ∧ IsOpen t ∧ p ∈ t := fun ⟨x, y⟩ hp =>
mem_nhds_iff.mp <|
show cl_d ∈ 𝓝 (x, y) by
rw [nhds_eq_uniformity_prod, mem_lift'_sets]
· exact ⟨d, hd, fun ⟨a, b⟩ ⟨ha, hb⟩ => ⟨x, y, ha, hp, hb⟩⟩
· exact fun _ _ h _ h' => ⟨h h'.1, h h'.2⟩
choose t ht using this
exact ⟨(⋃ p : α × α, ⋃ h : p ∈ s, t p h : Set (α × α)),
isOpen_iUnion fun p : α × α => isOpen_iUnion fun hp => (ht p hp).right.left,
fun ⟨a, b⟩ hp => by
simp only [mem_iUnion, Prod.exists]; exact ⟨a, b, hp, (ht (a, b) hp).right.right⟩,
iUnion_subset fun p => iUnion_subset fun hp => (ht p hp).left⟩
#align nhdset_of_mem_uniformity nhdset_of_mem_uniformity
/-- Entourages are neighborhoods of the diagonal. -/
theorem nhds_le_uniformity (x : α) : 𝓝 (x, x) ≤ 𝓤 α := by
intro V V_in
rcases comp_symm_mem_uniformity_sets V_in with ⟨w, w_in, w_symm, w_sub⟩
have : ball x w ×ˢ ball x w ∈ 𝓝 (x, x) := by
rw [nhds_prod_eq]
exact prod_mem_prod (ball_mem_nhds x w_in) (ball_mem_nhds x w_in)
apply mem_of_superset this
rintro ⟨u, v⟩ ⟨u_in, v_in⟩
exact w_sub (mem_comp_of_mem_ball w_symm u_in v_in)
#align nhds_le_uniformity nhds_le_uniformity
/-- Entourages are neighborhoods of the diagonal. -/
theorem iSup_nhds_le_uniformity : ⨆ x : α, 𝓝 (x, x) ≤ 𝓤 α :=
iSup_le nhds_le_uniformity
#align supr_nhds_le_uniformity iSup_nhds_le_uniformity
/-- Entourages are neighborhoods of the diagonal. -/
theorem nhdsSet_diagonal_le_uniformity : 𝓝ˢ (diagonal α) ≤ 𝓤 α :=
(nhdsSet_diagonal α).trans_le iSup_nhds_le_uniformity
#align nhds_set_diagonal_le_uniformity nhdsSet_diagonal_le_uniformity
/-!
### Closure and interior in uniform spaces
-/
theorem closure_eq_uniformity (s : Set <| α × α) :
closure s = ⋂ V ∈ { V | V ∈ 𝓤 α ∧ SymmetricRel V }, V ○ s ○ V := by
ext ⟨x, y⟩
simp (config := { contextual := true }) only
[mem_closure_iff_nhds_basis (UniformSpace.hasBasis_nhds_prod x y), mem_iInter, mem_setOf_eq,
and_imp, mem_comp_comp, exists_prop, ← mem_inter_iff, inter_comm, Set.Nonempty]
#align closure_eq_uniformity closure_eq_uniformity
theorem uniformity_hasBasis_closed :
HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsClosed V) id := by
refine Filter.hasBasis_self.2 fun t h => ?_
rcases comp_comp_symm_mem_uniformity_sets h with ⟨w, w_in, w_symm, r⟩
refine ⟨closure w, mem_of_superset w_in subset_closure, isClosed_closure, ?_⟩
refine Subset.trans ?_ r
rw [closure_eq_uniformity]
apply iInter_subset_of_subset
apply iInter_subset
exact ⟨w_in, w_symm⟩
#align uniformity_has_basis_closed uniformity_hasBasis_closed
theorem uniformity_eq_uniformity_closure : 𝓤 α = (𝓤 α).lift' closure :=
Eq.symm <| uniformity_hasBasis_closed.lift'_closure_eq_self fun _ => And.right
#align uniformity_eq_uniformity_closure uniformity_eq_uniformity_closure
theorem Filter.HasBasis.uniformity_closure {p : ι → Prop} {U : ι → Set (α × α)}
(h : (𝓤 α).HasBasis p U) : (𝓤 α).HasBasis p fun i => closure (U i) :=
(@uniformity_eq_uniformity_closure α _).symm ▸ h.lift'_closure
#align filter.has_basis.uniformity_closure Filter.HasBasis.uniformity_closure
/-- Closed entourages form a basis of the uniformity filter. -/
theorem uniformity_hasBasis_closure : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α) closure :=
(𝓤 α).basis_sets.uniformity_closure
#align uniformity_has_basis_closure uniformity_hasBasis_closure
theorem closure_eq_inter_uniformity {t : Set (α × α)} : closure t = ⋂ d ∈ 𝓤 α, d ○ (t ○ d) :=
calc
closure t = ⋂ (V) (_ : V ∈ 𝓤 α ∧ SymmetricRel V), V ○ t ○ V := closure_eq_uniformity t
_ = ⋂ V ∈ 𝓤 α, V ○ t ○ V :=
Eq.symm <|
UniformSpace.hasBasis_symmetric.biInter_mem fun V₁ V₂ hV =>
compRel_mono (compRel_mono hV Subset.rfl) hV
_ = ⋂ V ∈ 𝓤 α, V ○ (t ○ V) := by simp only [compRel_assoc]
#align closure_eq_inter_uniformity closure_eq_inter_uniformity
theorem uniformity_eq_uniformity_interior : 𝓤 α = (𝓤 α).lift' interior :=
le_antisymm
(le_iInf₂ fun d hd => by
let ⟨s, hs, hs_comp⟩ := comp3_mem_uniformity hd
let ⟨t, ht, hst, ht_comp⟩ := nhdset_of_mem_uniformity s hs
have : s ⊆ interior d :=
calc
s ⊆ t := hst
_ ⊆ interior d :=
ht.subset_interior_iff.mpr fun x (hx : x ∈ t) =>
let ⟨x, y, h₁, h₂, h₃⟩ := ht_comp hx
hs_comp ⟨x, h₁, y, h₂, h₃⟩
have : interior d ∈ 𝓤 α := by filter_upwards [hs] using this
simp [this])
fun s hs => ((𝓤 α).lift' interior).sets_of_superset (mem_lift' hs) interior_subset
#align uniformity_eq_uniformity_interior uniformity_eq_uniformity_interior
theorem interior_mem_uniformity {s : Set (α × α)} (hs : s ∈ 𝓤 α) : interior s ∈ 𝓤 α := by
rw [uniformity_eq_uniformity_interior]; exact mem_lift' hs
#align interior_mem_uniformity interior_mem_uniformity
theorem mem_uniformity_isClosed {s : Set (α × α)} (h : s ∈ 𝓤 α) : ∃ t ∈ 𝓤 α, IsClosed t ∧ t ⊆ s :=
let ⟨t, ⟨ht_mem, htc⟩, hts⟩ := uniformity_hasBasis_closed.mem_iff.1 h
⟨t, ht_mem, htc, hts⟩
#align mem_uniformity_is_closed mem_uniformity_isClosed
theorem isOpen_iff_open_ball_subset {s : Set α} :
IsOpen s ↔ ∀ x ∈ s, ∃ V ∈ 𝓤 α, IsOpen V ∧ ball x V ⊆ s := by
rw [isOpen_iff_ball_subset]
constructor <;> intro h x hx
· obtain ⟨V, hV, hV'⟩ := h x hx
exact
⟨interior V, interior_mem_uniformity hV, isOpen_interior,
(ball_mono interior_subset x).trans hV'⟩
· obtain ⟨V, hV, -, hV'⟩ := h x hx
exact ⟨V, hV, hV'⟩
#align is_open_iff_open_ball_subset isOpen_iff_open_ball_subset
/-- The uniform neighborhoods of all points of a dense set cover the whole space. -/
theorem Dense.biUnion_uniformity_ball {s : Set α} {U : Set (α × α)} (hs : Dense s) (hU : U ∈ 𝓤 α) :
⋃ x ∈ s, ball x U = univ := by
refine iUnion₂_eq_univ_iff.2 fun y => ?_
rcases hs.inter_nhds_nonempty (mem_nhds_right y hU) with ⟨x, hxs, hxy : (x, y) ∈ U⟩
exact ⟨x, hxs, hxy⟩
#align dense.bUnion_uniformity_ball Dense.biUnion_uniformity_ball
/-- The uniform neighborhoods of all points of a dense indexed collection cover the whole space. -/
lemma DenseRange.iUnion_uniformity_ball {ι : Type*} {xs : ι → α}
(xs_dense : DenseRange xs) {U : Set (α × α)} (hU : U ∈ uniformity α) :
⋃ i, UniformSpace.ball (xs i) U = univ := by
rw [← biUnion_range (f := xs) (g := fun x ↦ UniformSpace.ball x U)]
exact Dense.biUnion_uniformity_ball xs_dense hU
/-!
### Uniformity bases
-/
/-- Open elements of `𝓤 α` form a basis of `𝓤 α`. -/
theorem uniformity_hasBasis_open : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsOpen V) id :=
hasBasis_self.2 fun s hs =>
⟨interior s, interior_mem_uniformity hs, isOpen_interior, interior_subset⟩
#align uniformity_has_basis_open uniformity_hasBasis_open
theorem Filter.HasBasis.mem_uniformity_iff {p : β → Prop} {s : β → Set (α × α)}
(h : (𝓤 α).HasBasis p s) {t : Set (α × α)} :
t ∈ 𝓤 α ↔ ∃ i, p i ∧ ∀ a b, (a, b) ∈ s i → (a, b) ∈ t :=
h.mem_iff.trans <| by simp only [Prod.forall, subset_def]
#align filter.has_basis.mem_uniformity_iff Filter.HasBasis.mem_uniformity_iff
/-- Open elements `s : Set (α × α)` of `𝓤 α` such that `(x, y) ∈ s ↔ (y, x) ∈ s` form a basis
of `𝓤 α`. -/
theorem uniformity_hasBasis_open_symmetric :
HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsOpen V ∧ SymmetricRel V) id := by
simp only [← and_assoc]
refine uniformity_hasBasis_open.restrict fun s hs => ⟨symmetrizeRel s, ?_⟩
exact
⟨⟨symmetrize_mem_uniformity hs.1, IsOpen.inter hs.2 (hs.2.preimage continuous_swap)⟩,
symmetric_symmetrizeRel s, symmetrizeRel_subset_self s⟩
#align uniformity_has_basis_open_symmetric uniformity_hasBasis_open_symmetric
theorem comp_open_symm_mem_uniformity_sets {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∃ t ∈ 𝓤 α, IsOpen t ∧ SymmetricRel t ∧ t ○ t ⊆ s := by
obtain ⟨t, ht₁, ht₂⟩ := comp_mem_uniformity_sets hs
obtain ⟨u, ⟨hu₁, hu₂, hu₃⟩, hu₄ : u ⊆ t⟩ := uniformity_hasBasis_open_symmetric.mem_iff.mp ht₁
exact ⟨u, hu₁, hu₂, hu₃, (compRel_mono hu₄ hu₄).trans ht₂⟩
#align comp_open_symm_mem_uniformity_sets comp_open_symm_mem_uniformity_sets
section
variable (α)
theorem UniformSpace.has_seq_basis [IsCountablyGenerated <| 𝓤 α] :
∃ V : ℕ → Set (α × α), HasAntitoneBasis (𝓤 α) V ∧ ∀ n, SymmetricRel (V n) :=
let ⟨U, hsym, hbasis⟩ := (@UniformSpace.hasBasis_symmetric α _).exists_antitone_subbasis
⟨U, hbasis, fun n => (hsym n).2⟩
#align uniform_space.has_seq_basis UniformSpace.has_seq_basis
end
theorem Filter.HasBasis.biInter_biUnion_ball {p : ι → Prop} {U : ι → Set (α × α)}
(h : HasBasis (𝓤 α) p U) (s : Set α) :
(⋂ (i) (_ : p i), ⋃ x ∈ s, ball x (U i)) = closure s := by
ext x
simp [mem_closure_iff_nhds_basis (nhds_basis_uniformity h), ball]
#align filter.has_basis.bInter_bUnion_ball Filter.HasBasis.biInter_biUnion_ball
/-! ### Uniform continuity -/
/-- A function `f : α → β` is *uniformly continuous* if `(f x, f y)` tends to the diagonal
as `(x, y)` tends to the diagonal. In other words, if `x` is sufficiently close to `y`, then
`f x` is close to `f y` no matter where `x` and `y` are located in `α`. -/
def UniformContinuous [UniformSpace β] (f : α → β) :=
Tendsto (fun x : α × α => (f x.1, f x.2)) (𝓤 α) (𝓤 β)
#align uniform_continuous UniformContinuous
/-- Notation for uniform continuity with respect to non-standard `UniformSpace` instances. -/
scoped[Uniformity] notation "UniformContinuous[" u₁ ", " u₂ "]" => @UniformContinuous _ _ u₁ u₂
/-- A function `f : α → β` is *uniformly continuous* on `s : Set α` if `(f x, f y)` tends to
the diagonal as `(x, y)` tends to the diagonal while remaining in `s ×ˢ s`.
In other words, if `x` is sufficiently close to `y`, then `f x` is close to
`f y` no matter where `x` and `y` are located in `s`. -/
def UniformContinuousOn [UniformSpace β] (f : α → β) (s : Set α) : Prop :=
Tendsto (fun x : α × α => (f x.1, f x.2)) (𝓤 α ⊓ 𝓟 (s ×ˢ s)) (𝓤 β)
#align uniform_continuous_on UniformContinuousOn
theorem uniformContinuous_def [UniformSpace β] {f : α → β} :
UniformContinuous f ↔ ∀ r ∈ 𝓤 β, { x : α × α | (f x.1, f x.2) ∈ r } ∈ 𝓤 α :=
Iff.rfl
#align uniform_continuous_def uniformContinuous_def
theorem uniformContinuous_iff_eventually [UniformSpace β] {f : α → β} :
UniformContinuous f ↔ ∀ r ∈ 𝓤 β, ∀ᶠ x : α × α in 𝓤 α, (f x.1, f x.2) ∈ r :=
Iff.rfl
#align uniform_continuous_iff_eventually uniformContinuous_iff_eventually
theorem uniformContinuousOn_univ [UniformSpace β] {f : α → β} :
UniformContinuousOn f univ ↔ UniformContinuous f := by
rw [UniformContinuousOn, UniformContinuous, univ_prod_univ, principal_univ, inf_top_eq]
#align uniform_continuous_on_univ uniformContinuousOn_univ
theorem uniformContinuous_of_const [UniformSpace β] {c : α → β} (h : ∀ a b, c a = c b) :
UniformContinuous c :=
have : (fun x : α × α => (c x.fst, c x.snd)) ⁻¹' idRel = univ :=
eq_univ_iff_forall.2 fun ⟨a, b⟩ => h a b
le_trans (map_le_iff_le_comap.2 <| by simp [comap_principal, this, univ_mem]) refl_le_uniformity
#align uniform_continuous_of_const uniformContinuous_of_const
theorem uniformContinuous_id : UniformContinuous (@id α) := tendsto_id
#align uniform_continuous_id uniformContinuous_id
theorem uniformContinuous_const [UniformSpace β] {b : β} : UniformContinuous fun _ : α => b :=
uniformContinuous_of_const fun _ _ => rfl
#align uniform_continuous_const uniformContinuous_const
nonrec theorem UniformContinuous.comp [UniformSpace β] [UniformSpace γ] {g : β → γ} {f : α → β}
(hg : UniformContinuous g) (hf : UniformContinuous f) : UniformContinuous (g ∘ f) :=
hg.comp hf
#align uniform_continuous.comp UniformContinuous.comp
theorem Filter.HasBasis.uniformContinuous_iff {ι'} [UniformSpace β] {p : ι → Prop}
{s : ι → Set (α × α)} (ha : (𝓤 α).HasBasis p s) {q : ι' → Prop} {t : ι' → Set (β × β)}
(hb : (𝓤 β).HasBasis q t) {f : α → β} :
UniformContinuous f ↔ ∀ i, q i → ∃ j, p j ∧ ∀ x y, (x, y) ∈ s j → (f x, f y) ∈ t i :=
(ha.tendsto_iff hb).trans <| by simp only [Prod.forall]
#align filter.has_basis.uniform_continuous_iff Filter.HasBasis.uniformContinuous_iff
theorem Filter.HasBasis.uniformContinuousOn_iff {ι'} [UniformSpace β] {p : ι → Prop}
{s : ι → Set (α × α)} (ha : (𝓤 α).HasBasis p s) {q : ι' → Prop} {t : ι' → Set (β × β)}
(hb : (𝓤 β).HasBasis q t) {f : α → β} {S : Set α} :
UniformContinuousOn f S ↔
∀ i, q i → ∃ j, p j ∧ ∀ x, x ∈ S → ∀ y, y ∈ S → (x, y) ∈ s j → (f x, f y) ∈ t i :=
((ha.inf_principal (S ×ˢ S)).tendsto_iff hb).trans <| by
simp_rw [Prod.forall, Set.inter_comm (s _), forall_mem_comm, mem_inter_iff, mem_prod, and_imp]
#align filter.has_basis.uniform_continuous_on_iff Filter.HasBasis.uniformContinuousOn_iff
end UniformSpace
open uniformity
section Constructions
instance : PartialOrder (UniformSpace α) :=
PartialOrder.lift (fun u => 𝓤[u]) fun _ _ => UniformSpace.ext
protected theorem UniformSpace.le_def {u₁ u₂ : UniformSpace α} : u₁ ≤ u₂ ↔ 𝓤[u₁] ≤ 𝓤[u₂] := Iff.rfl
instance : InfSet (UniformSpace α) :=
⟨fun s =>
UniformSpace.ofCore
{ uniformity := ⨅ u ∈ s, 𝓤[u]
refl := le_iInf fun u => le_iInf fun _ => u.toCore.refl
symm := le_iInf₂ fun u hu =>
le_trans (map_mono <| iInf_le_of_le _ <| iInf_le _ hu) u.symm
comp := le_iInf₂ fun u hu =>
le_trans (lift'_mono (iInf_le_of_le _ <| iInf_le _ hu) <| le_rfl) u.comp }⟩
protected theorem UniformSpace.sInf_le {tt : Set (UniformSpace α)} {t : UniformSpace α}
(h : t ∈ tt) : sInf tt ≤ t :=
show ⨅ u ∈ tt, 𝓤[u] ≤ 𝓤[t] from iInf₂_le t h
protected theorem UniformSpace.le_sInf {tt : Set (UniformSpace α)} {t : UniformSpace α}
(h : ∀ t' ∈ tt, t ≤ t') : t ≤ sInf tt :=
show 𝓤[t] ≤ ⨅ u ∈ tt, 𝓤[u] from le_iInf₂ h
instance : Top (UniformSpace α) :=
⟨@UniformSpace.mk α ⊤ ⊤ le_top le_top fun x ↦ by simp only [nhds_top, comap_top]⟩
instance : Bot (UniformSpace α) :=
⟨{ toTopologicalSpace := ⊥
uniformity := 𝓟 idRel
symm := by simp [Tendsto]
comp := lift'_le (mem_principal_self _) <| principal_mono.2 id_compRel.subset
nhds_eq_comap_uniformity := fun s => by
let _ : TopologicalSpace α := ⊥; have := discreteTopology_bot α
simp [idRel] }⟩
instance : Inf (UniformSpace α) :=
⟨fun u₁ u₂ =>
{ uniformity := 𝓤[u₁] ⊓ 𝓤[u₂]
symm := u₁.symm.inf u₂.symm
comp := (lift'_inf_le _ _ _).trans <| inf_le_inf u₁.comp u₂.comp
toTopologicalSpace := u₁.toTopologicalSpace ⊓ u₂.toTopologicalSpace
nhds_eq_comap_uniformity := fun _ ↦ by
rw [@nhds_inf _ u₁.toTopologicalSpace _, @nhds_eq_comap_uniformity _ u₁,
@nhds_eq_comap_uniformity _ u₂, comap_inf] }⟩
instance : CompleteLattice (UniformSpace α) :=
{ inferInstanceAs (PartialOrder (UniformSpace α)) with
sup := fun a b => sInf { x | a ≤ x ∧ b ≤ x }
le_sup_left := fun _ _ => UniformSpace.le_sInf fun _ ⟨h, _⟩ => h
le_sup_right := fun _ _ => UniformSpace.le_sInf fun _ ⟨_, h⟩ => h
sup_le := fun _ _ _ h₁ h₂ => UniformSpace.sInf_le ⟨h₁, h₂⟩
inf := (· ⊓ ·)
le_inf := fun a _ _ h₁ h₂ => show a.uniformity ≤ _ from le_inf h₁ h₂
inf_le_left := fun a _ => show _ ≤ a.uniformity from inf_le_left
inf_le_right := fun _ b => show _ ≤ b.uniformity from inf_le_right
top := ⊤
le_top := fun a => show a.uniformity ≤ ⊤ from le_top
bot := ⊥
bot_le := fun u => u.toCore.refl
sSup := fun tt => sInf { t | ∀ t' ∈ tt, t' ≤ t }
le_sSup := fun _ _ h => UniformSpace.le_sInf fun _ h' => h' _ h
sSup_le := fun _ _ h => UniformSpace.sInf_le h
sInf := sInf
le_sInf := fun _ _ hs => UniformSpace.le_sInf hs
sInf_le := fun _ _ ha => UniformSpace.sInf_le ha }
theorem iInf_uniformity {ι : Sort*} {u : ι → UniformSpace α} : 𝓤[iInf u] = ⨅ i, 𝓤[u i] :=
iInf_range
#align infi_uniformity iInf_uniformity
theorem inf_uniformity {u v : UniformSpace α} : 𝓤[u ⊓ v] = 𝓤[u] ⊓ 𝓤[v] := rfl
#align inf_uniformity inf_uniformity
lemma bot_uniformity : 𝓤[(⊥ : UniformSpace α)] = 𝓟 idRel := rfl
lemma top_uniformity : 𝓤[(⊤ : UniformSpace α)] = ⊤ := rfl
instance inhabitedUniformSpace : Inhabited (UniformSpace α) :=
⟨⊥⟩
#align inhabited_uniform_space inhabitedUniformSpace
instance inhabitedUniformSpaceCore : Inhabited (UniformSpace.Core α) :=
⟨@UniformSpace.toCore _ default⟩
#align inhabited_uniform_space_core inhabitedUniformSpaceCore
instance [Subsingleton α] : Unique (UniformSpace α) where
uniq u := bot_unique <| le_principal_iff.2 <| by
rw [idRel, ← diagonal, diagonal_eq_univ]; exact univ_mem
/-- Given `f : α → β` and a uniformity `u` on `β`, the inverse image of `u` under `f`
is the inverse image in the filter sense of the induced function `α × α → β × β`.
See note [reducible non-instances]. -/
abbrev UniformSpace.comap (f : α → β) (u : UniformSpace β) : UniformSpace α where
uniformity := 𝓤[u].comap fun p : α × α => (f p.1, f p.2)
symm := by
simp only [tendsto_comap_iff, Prod.swap, (· ∘ ·)]
exact tendsto_swap_uniformity.comp tendsto_comap
comp := le_trans
(by
rw [comap_lift'_eq, comap_lift'_eq2]
· exact lift'_mono' fun s _ ⟨a₁, a₂⟩ ⟨x, h₁, h₂⟩ => ⟨f x, h₁, h₂⟩
· exact monotone_id.compRel monotone_id)
(comap_mono u.comp)
toTopologicalSpace := u.toTopologicalSpace.induced f
nhds_eq_comap_uniformity x := by
simp only [nhds_induced, nhds_eq_comap_uniformity, comap_comap, Function.comp]
#align uniform_space.comap UniformSpace.comap
theorem uniformity_comap {_ : UniformSpace β} (f : α → β) :
𝓤[UniformSpace.comap f ‹_›] = comap (Prod.map f f) (𝓤 β) :=
rfl
#align uniformity_comap uniformity_comap
@[simp]
theorem uniformSpace_comap_id {α : Type*} : UniformSpace.comap (id : α → α) = id := by
ext : 2
rw [uniformity_comap, Prod.map_id, comap_id]
#align uniform_space_comap_id uniformSpace_comap_id
theorem UniformSpace.comap_comap {α β γ} {uγ : UniformSpace γ} {f : α → β} {g : β → γ} :
UniformSpace.comap (g ∘ f) uγ = UniformSpace.comap f (UniformSpace.comap g uγ) := by
ext1
simp only [uniformity_comap, Filter.comap_comap, Prod.map_comp_map]
#align uniform_space.comap_comap UniformSpace.comap_comap
theorem UniformSpace.comap_inf {α γ} {u₁ u₂ : UniformSpace γ} {f : α → γ} :
(u₁ ⊓ u₂).comap f = u₁.comap f ⊓ u₂.comap f :=
UniformSpace.ext Filter.comap_inf
#align uniform_space.comap_inf UniformSpace.comap_inf
theorem UniformSpace.comap_iInf {ι α γ} {u : ι → UniformSpace γ} {f : α → γ} :
(⨅ i, u i).comap f = ⨅ i, (u i).comap f := by
ext : 1
simp [uniformity_comap, iInf_uniformity]
#align uniform_space.comap_infi UniformSpace.comap_iInf
theorem UniformSpace.comap_mono {α γ} {f : α → γ} :
Monotone fun u : UniformSpace γ => u.comap f := fun _ _ hu =>
Filter.comap_mono hu
#align uniform_space.comap_mono UniformSpace.comap_mono
theorem uniformContinuous_iff {α β} {uα : UniformSpace α} {uβ : UniformSpace β} {f : α → β} :
UniformContinuous f ↔ uα ≤ uβ.comap f :=
Filter.map_le_iff_le_comap
#align uniform_continuous_iff uniformContinuous_iff
theorem le_iff_uniformContinuous_id {u v : UniformSpace α} :
u ≤ v ↔ @UniformContinuous _ _ u v id := by
rw [uniformContinuous_iff, uniformSpace_comap_id, id]
#align le_iff_uniform_continuous_id le_iff_uniformContinuous_id
theorem uniformContinuous_comap {f : α → β} [u : UniformSpace β] :
@UniformContinuous α β (UniformSpace.comap f u) u f :=
tendsto_comap
#align uniform_continuous_comap uniformContinuous_comap
theorem uniformContinuous_comap' {f : γ → β} {g : α → γ} [v : UniformSpace β] [u : UniformSpace α]
(h : UniformContinuous (f ∘ g)) : @UniformContinuous α γ u (UniformSpace.comap f v) g :=
tendsto_comap_iff.2 h
#align uniform_continuous_comap' uniformContinuous_comap'
namespace UniformSpace
theorem to_nhds_mono {u₁ u₂ : UniformSpace α} (h : u₁ ≤ u₂) (a : α) :
@nhds _ (@UniformSpace.toTopologicalSpace _ u₁) a ≤
@nhds _ (@UniformSpace.toTopologicalSpace _ u₂) a := by
rw [@nhds_eq_uniformity α u₁ a, @nhds_eq_uniformity α u₂ a]; exact lift'_mono h le_rfl
#align to_nhds_mono UniformSpace.to_nhds_mono
theorem toTopologicalSpace_mono {u₁ u₂ : UniformSpace α} (h : u₁ ≤ u₂) :
@UniformSpace.toTopologicalSpace _ u₁ ≤ @UniformSpace.toTopologicalSpace _ u₂ :=
le_of_nhds_le_nhds <| to_nhds_mono h
#align to_topological_space_mono UniformSpace.toTopologicalSpace_mono
theorem toTopologicalSpace_comap {f : α → β} {u : UniformSpace β} :
@UniformSpace.toTopologicalSpace _ (UniformSpace.comap f u) =
TopologicalSpace.induced f (@UniformSpace.toTopologicalSpace β u) :=
rfl
#align to_topological_space_comap UniformSpace.toTopologicalSpace_comap
theorem toTopologicalSpace_bot : @UniformSpace.toTopologicalSpace α ⊥ = ⊥ := rfl
#align to_topological_space_bot UniformSpace.toTopologicalSpace_bot
theorem toTopologicalSpace_top : @UniformSpace.toTopologicalSpace α ⊤ = ⊤ := rfl
#align to_topological_space_top UniformSpace.toTopologicalSpace_top
theorem toTopologicalSpace_iInf {ι : Sort*} {u : ι → UniformSpace α} :
(iInf u).toTopologicalSpace = ⨅ i, (u i).toTopologicalSpace :=
TopologicalSpace.ext_nhds fun a ↦ by simp only [@nhds_eq_comap_uniformity _ (iInf u), nhds_iInf,
iInf_uniformity, @nhds_eq_comap_uniformity _ (u _), Filter.comap_iInf]
#align to_topological_space_infi UniformSpace.toTopologicalSpace_iInf
theorem toTopologicalSpace_sInf {s : Set (UniformSpace α)} :
(sInf s).toTopologicalSpace = ⨅ i ∈ s, @UniformSpace.toTopologicalSpace α i := by
rw [sInf_eq_iInf]
simp only [← toTopologicalSpace_iInf]
#align to_topological_space_Inf UniformSpace.toTopologicalSpace_sInf
theorem toTopologicalSpace_inf {u v : UniformSpace α} :
(u ⊓ v).toTopologicalSpace = u.toTopologicalSpace ⊓ v.toTopologicalSpace :=
rfl
#align to_topological_space_inf UniformSpace.toTopologicalSpace_inf
end UniformSpace
theorem UniformContinuous.continuous [UniformSpace α] [UniformSpace β] {f : α → β}
(hf : UniformContinuous f) : Continuous f :=
continuous_iff_le_induced.mpr <| UniformSpace.toTopologicalSpace_mono <|
uniformContinuous_iff.1 hf
#align uniform_continuous.continuous UniformContinuous.continuous
/-- Uniform space structure on `ULift α`. -/
instance ULift.uniformSpace [UniformSpace α] : UniformSpace (ULift α) :=
UniformSpace.comap ULift.down ‹_›
#align ulift.uniform_space ULift.uniformSpace
section UniformContinuousInfi
-- Porting note: renamed for dot notation; add an `iff` lemma?
theorem UniformContinuous.inf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ u₃ : UniformSpace β}
(h₁ : UniformContinuous[u₁, u₂] f) (h₂ : UniformContinuous[u₁, u₃] f) :
UniformContinuous[u₁, u₂ ⊓ u₃] f :=
tendsto_inf.mpr ⟨h₁, h₂⟩
#align uniform_continuous_inf_rng UniformContinuous.inf_rng
-- Porting note: renamed for dot notation
theorem UniformContinuous.inf_dom_left {f : α → β} {u₁ u₂ : UniformSpace α} {u₃ : UniformSpace β}
(hf : UniformContinuous[u₁, u₃] f) : UniformContinuous[u₁ ⊓ u₂, u₃] f :=
tendsto_inf_left hf
#align uniform_continuous_inf_dom_left UniformContinuous.inf_dom_left
-- Porting note: renamed for dot notation
theorem UniformContinuous.inf_dom_right {f : α → β} {u₁ u₂ : UniformSpace α} {u₃ : UniformSpace β}
(hf : UniformContinuous[u₂, u₃] f) : UniformContinuous[u₁ ⊓ u₂, u₃] f :=
tendsto_inf_right hf
#align uniform_continuous_inf_dom_right UniformContinuous.inf_dom_right
theorem uniformContinuous_sInf_dom {f : α → β} {u₁ : Set (UniformSpace α)} {u₂ : UniformSpace β}
{u : UniformSpace α} (h₁ : u ∈ u₁) (hf : UniformContinuous[u, u₂] f) :
UniformContinuous[sInf u₁, u₂] f := by
delta UniformContinuous
rw [sInf_eq_iInf', iInf_uniformity]
exact tendsto_iInf' ⟨u, h₁⟩ hf
#align uniform_continuous_Inf_dom uniformContinuous_sInf_dom
theorem uniformContinuous_sInf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ : Set (UniformSpace β)} :
UniformContinuous[u₁, sInf u₂] f ↔ ∀ u ∈ u₂, UniformContinuous[u₁, u] f := by
delta UniformContinuous
rw [sInf_eq_iInf', iInf_uniformity, tendsto_iInf, SetCoe.forall]
#align uniform_continuous_Inf_rng uniformContinuous_sInf_rng
theorem uniformContinuous_iInf_dom {f : α → β} {u₁ : ι → UniformSpace α} {u₂ : UniformSpace β}
{i : ι} (hf : UniformContinuous[u₁ i, u₂] f) : UniformContinuous[iInf u₁, u₂] f := by
delta UniformContinuous
rw [iInf_uniformity]
exact tendsto_iInf' i hf
#align uniform_continuous_infi_dom uniformContinuous_iInf_dom
| Mathlib/Topology/UniformSpace/Basic.lean | 1,404 | 1,407 | theorem uniformContinuous_iInf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ : ι → UniformSpace β} :
UniformContinuous[u₁, iInf u₂] f ↔ ∀ i, UniformContinuous[u₁, u₂ i] f := by |
delta UniformContinuous
rw [iInf_uniformity, tendsto_iInf]
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.Deriv.Add
import Mathlib.Analysis.Calculus.Deriv.Mul
import Mathlib.Analysis.Calculus.LocalExtr.Basic
#align_import analysis.calculus.darboux from "leanprover-community/mathlib"@"61b5e2755ccb464b68d05a9acf891ae04992d09d"
/-!
# Darboux's theorem
In this file we prove that the derivative of a differentiable function on an interval takes all
intermediate values. The proof is based on the
[Wikipedia](https://en.wikipedia.org/wiki/Darboux%27s_theorem_(analysis)) page about this theorem.
-/
open Filter Set
open scoped Topology Classical
variable {a b : ℝ} {f f' : ℝ → ℝ}
/-- **Darboux's theorem**: if `a ≤ b` and `f' a < m < f' b`, then `f' c = m` for some
`c ∈ (a, b)`. -/
theorem exists_hasDerivWithinAt_eq_of_gt_of_lt (hab : a ≤ b)
(hf : ∀ x ∈ Icc a b, HasDerivWithinAt f (f' x) (Icc a b) x) {m : ℝ} (hma : f' a < m)
(hmb : m < f' b) : m ∈ f' '' Ioo a b := by
rcases hab.eq_or_lt with (rfl | hab')
· exact (lt_asymm hma hmb).elim
set g : ℝ → ℝ := fun x => f x - m * x
have hg : ∀ x ∈ Icc a b, HasDerivWithinAt g (f' x - m) (Icc a b) x := by
intro x hx
simpa using (hf x hx).sub ((hasDerivWithinAt_id x _).const_mul m)
obtain ⟨c, cmem, hc⟩ : ∃ c ∈ Icc a b, IsMinOn g (Icc a b) c :=
isCompact_Icc.exists_isMinOn (nonempty_Icc.2 <| hab) fun x hx => (hg x hx).continuousWithinAt
have cmem' : c ∈ Ioo a b := by
rcases cmem.1.eq_or_lt with (rfl | hac)
-- Show that `c` can't be equal to `a`
· refine absurd (sub_nonneg.1 <| nonneg_of_mul_nonneg_right ?_ (sub_pos.2 hab'))
(not_le_of_lt hma)
have : b - a ∈ posTangentConeAt (Icc a b) a :=
mem_posTangentConeAt_of_segment_subset (segment_eq_Icc hab ▸ Subset.refl _)
simpa only [ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply]
using hc.localize.hasFDerivWithinAt_nonneg (hg a (left_mem_Icc.2 hab)) this
rcases cmem.2.eq_or_gt with (rfl | hcb)
-- Show that `c` can't be equal to `b`
· refine absurd (sub_nonpos.1 <| nonpos_of_mul_nonneg_right ?_ (sub_lt_zero.2 hab'))
(not_le_of_lt hmb)
have : a - b ∈ posTangentConeAt (Icc a b) b :=
mem_posTangentConeAt_of_segment_subset (by rw [segment_symm, segment_eq_Icc hab])
simpa only [ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply]
using hc.localize.hasFDerivWithinAt_nonneg (hg b (right_mem_Icc.2 hab)) this
exact ⟨hac, hcb⟩
use c, cmem'
rw [← sub_eq_zero]
have : Icc a b ∈ 𝓝 c := by rwa [← mem_interior_iff_mem_nhds, interior_Icc]
exact (hc.isLocalMin this).hasDerivAt_eq_zero ((hg c cmem).hasDerivAt this)
#align exists_has_deriv_within_at_eq_of_gt_of_lt exists_hasDerivWithinAt_eq_of_gt_of_lt
/-- **Darboux's theorem**: if `a ≤ b` and `f' b < m < f' a`, then `f' c = m` for some `c ∈ (a, b)`.
-/
theorem exists_hasDerivWithinAt_eq_of_lt_of_gt (hab : a ≤ b)
(hf : ∀ x ∈ Icc a b, HasDerivWithinAt f (f' x) (Icc a b) x) {m : ℝ} (hma : m < f' a)
(hmb : f' b < m) : m ∈ f' '' Ioo a b :=
let ⟨c, cmem, hc⟩ :=
exists_hasDerivWithinAt_eq_of_gt_of_lt hab (fun x hx => (hf x hx).neg) (neg_lt_neg hma)
(neg_lt_neg hmb)
⟨c, cmem, neg_injective hc⟩
#align exists_has_deriv_within_at_eq_of_lt_of_gt exists_hasDerivWithinAt_eq_of_lt_of_gt
/-- **Darboux's theorem**: the image of a `Set.OrdConnected` set under `f'` is a `Set.OrdConnected`
set, `HasDerivWithinAt` version. -/
| Mathlib/Analysis/Calculus/Darboux.lean | 76 | 90 | theorem Set.OrdConnected.image_hasDerivWithinAt {s : Set ℝ} (hs : OrdConnected s)
(hf : ∀ x ∈ s, HasDerivWithinAt f (f' x) s x) : OrdConnected (f' '' s) := by |
apply ordConnected_of_Ioo
rintro _ ⟨a, ha, rfl⟩ _ ⟨b, hb, rfl⟩ - m ⟨hma, hmb⟩
rcases le_total a b with hab | hab
· have : Icc a b ⊆ s := hs.out ha hb
rcases exists_hasDerivWithinAt_eq_of_gt_of_lt hab (fun x hx => (hf x <| this hx).mono this) hma
hmb with
⟨c, cmem, hc⟩
exact ⟨c, this <| Ioo_subset_Icc_self cmem, hc⟩
· have : Icc b a ⊆ s := hs.out hb ha
rcases exists_hasDerivWithinAt_eq_of_lt_of_gt hab (fun x hx => (hf x <| this hx).mono this) hmb
hma with
⟨c, cmem, hc⟩
exact ⟨c, this <| Ioo_subset_Icc_self cmem, hc⟩
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.AffineScheme
import Mathlib.AlgebraicGeometry.Pullbacks
import Mathlib.CategoryTheory.MorphismProperty.Limits
import Mathlib.Data.List.TFAE
#align_import algebraic_geometry.morphisms.basic from "leanprover-community/mathlib"@"434e2fd21c1900747afc6d13d8be7f4eedba7218"
/-!
# Properties of morphisms between Schemes
We provide the basic framework for talking about properties of morphisms between Schemes.
A `MorphismProperty Scheme` is a predicate on morphisms between schemes, and an
`AffineTargetMorphismProperty` is a predicate on morphisms into affine schemes. Given a
`P : AffineTargetMorphismProperty`, we may construct a `MorphismProperty` called
`targetAffineLocally P` that holds for `f : X ⟶ Y` whenever `P` holds for the
restriction of `f` on every affine open subset of `Y`.
## Main definitions
- `AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal`: We say that `P.IsLocal` if `P`
satisfies the assumptions of the affine communication lemma
(`AlgebraicGeometry.of_affine_open_cover`). That is,
1. `P` respects isomorphisms.
2. If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ Y.basicOpen r` for any
global section `r`.
3. If `P` holds for `f ∣_ Y.basicOpen r` for all `r` in a spanning set of the global sections,
then `P` holds for `f`.
- `AlgebraicGeometry.PropertyIsLocalAtTarget`: We say that `PropertyIsLocalAtTarget P` for
`P : MorphismProperty Scheme` if
1. `P` respects isomorphisms.
2. If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ U` for any `U`.
3. If `P` holds for `f ∣_ U` for an open cover `U` of `Y`, then `P` holds for `f`.
## Main results
- `AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.affine_openCover_TFAE`:
If `P.IsLocal`, then `targetAffineLocally P f` iff there exists an affine cover `{ Uᵢ }` of `Y`
such that `P` holds for `f ∣_ Uᵢ`.
- `AlgebraicGeometry.AffineTargetMorphismProperty.isLocalOfOpenCoverImply`:
If the existence of an affine cover `{ Uᵢ }` of `Y` such that `P` holds for `f ∣_ Uᵢ` implies
`targetAffineLocally P f`, then `P.IsLocal`.
- `AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.affine_target_iff`:
If `Y` is affine and `f : X ⟶ Y`, then `targetAffineLocally P f ↔ P f` provided `P.IsLocal`.
- `AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.targetAffineLocallyIsLocal` :
If `P.IsLocal`, then `PropertyIsLocalAtTarget (targetAffineLocally P)`.
- `AlgebraicGeometry.PropertyIsLocalAtTarget.openCover_TFAE`:
If `PropertyIsLocalAtTarget P`, then `P f` iff there exists an open cover `{ Uᵢ }` of `Y`
such that `P` holds for `f ∣_ Uᵢ`.
These results should not be used directly, and should be ported to each property that is local.
-/
set_option linter.uppercaseLean3 false
universe u
open TopologicalSpace CategoryTheory CategoryTheory.Limits Opposite
noncomputable section
namespace AlgebraicGeometry
/-- An `AffineTargetMorphismProperty` is a class of morphisms from an arbitrary scheme into an
affine scheme. -/
def AffineTargetMorphismProperty :=
∀ ⦃X Y : Scheme⦄ (_ : X ⟶ Y) [IsAffine Y], Prop
#align algebraic_geometry.affine_target_morphism_property AlgebraicGeometry.AffineTargetMorphismProperty
/-- `IsIso` as a `MorphismProperty`. -/
protected def Scheme.isIso : MorphismProperty Scheme :=
@IsIso Scheme _
#align algebraic_geometry.Scheme.is_iso AlgebraicGeometry.Scheme.isIso
/-- `IsIso` as an `AffineTargetMorphismProperty`. -/
protected def Scheme.affineTargetIsIso : AffineTargetMorphismProperty := fun _ _ f _ => IsIso f
#align algebraic_geometry.Scheme.affine_target_is_iso AlgebraicGeometry.Scheme.affineTargetIsIso
instance : Inhabited AffineTargetMorphismProperty := ⟨Scheme.affineTargetIsIso⟩
/-- An `AffineTargetMorphismProperty` can be extended to a `MorphismProperty` such that it
*never* holds when the target is not affine -/
def AffineTargetMorphismProperty.toProperty (P : AffineTargetMorphismProperty) :
MorphismProperty Scheme := fun _ _ f => ∃ h, @P _ _ f h
#align algebraic_geometry.affine_target_morphism_property.to_property AlgebraicGeometry.AffineTargetMorphismProperty.toProperty
theorem AffineTargetMorphismProperty.toProperty_apply (P : AffineTargetMorphismProperty)
{X Y : Scheme} (f : X ⟶ Y) [i : IsAffine Y] : P.toProperty f ↔ P f := by
delta AffineTargetMorphismProperty.toProperty; simp [*]
#align algebraic_geometry.affine_target_morphism_property.to_property_apply AlgebraicGeometry.AffineTargetMorphismProperty.toProperty_apply
theorem affine_cancel_left_isIso {P : AffineTargetMorphismProperty} (hP : P.toProperty.RespectsIso)
{X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [IsAffine Z] : P (f ≫ g) ↔ P g := by
rw [← P.toProperty_apply, ← P.toProperty_apply, hP.cancel_left_isIso]
#align algebraic_geometry.affine_cancel_left_is_iso AlgebraicGeometry.affine_cancel_left_isIso
theorem affine_cancel_right_isIso {P : AffineTargetMorphismProperty} (hP : P.toProperty.RespectsIso)
{X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso g] [IsAffine Z] [IsAffine Y] :
P (f ≫ g) ↔ P f := by rw [← P.toProperty_apply, ← P.toProperty_apply, hP.cancel_right_isIso]
#align algebraic_geometry.affine_cancel_right_is_iso AlgebraicGeometry.affine_cancel_right_isIso
theorem AffineTargetMorphismProperty.respectsIso_mk {P : AffineTargetMorphismProperty}
(h₁ : ∀ {X Y Z} (e : X ≅ Y) (f : Y ⟶ Z) [IsAffine Z], P f → P (e.hom ≫ f))
(h₂ : ∀ {X Y Z} (e : Y ≅ Z) (f : X ⟶ Y) [h : IsAffine Y],
P f → @P _ _ (f ≫ e.hom) (isAffineOfIso e.inv)) :
P.toProperty.RespectsIso := by
constructor
· rintro X Y Z e f ⟨a, h⟩; exact ⟨a, h₁ e f h⟩
· rintro X Y Z e f ⟨a, h⟩; exact ⟨isAffineOfIso e.inv, h₂ e f h⟩
#align algebraic_geometry.affine_target_morphism_property.respects_iso_mk AlgebraicGeometry.AffineTargetMorphismProperty.respectsIso_mk
/-- For a `P : AffineTargetMorphismProperty`, `targetAffineLocally P` holds for
`f : X ⟶ Y` whenever `P` holds for the restriction of `f` on every affine open subset of `Y`. -/
def targetAffineLocally (P : AffineTargetMorphismProperty) : MorphismProperty Scheme :=
fun {X Y : Scheme} (f : X ⟶ Y) => ∀ U : Y.affineOpens, @P _ _ (f ∣_ U) U.prop
#align algebraic_geometry.target_affine_locally AlgebraicGeometry.targetAffineLocally
theorem IsAffineOpen.map_isIso {X Y : Scheme} {U : Opens Y.carrier} (hU : IsAffineOpen U)
(f : X ⟶ Y) [IsIso f] : IsAffineOpen ((Opens.map f.1.base).obj U) :=
haveI : IsAffine _ := hU
isAffineOfIso (f ∣_ U)
#align algebraic_geometry.is_affine_open.map_is_iso AlgebraicGeometry.IsAffineOpen.map_isIso
theorem targetAffineLocally_respectsIso {P : AffineTargetMorphismProperty}
(hP : P.toProperty.RespectsIso) : (targetAffineLocally P).RespectsIso := by
constructor
· introv H U
rw [morphismRestrict_comp, affine_cancel_left_isIso hP]
exact H U
· introv H
rintro ⟨U, hU : IsAffineOpen U⟩; dsimp
haveI : IsAffine _ := hU.map_isIso e.hom
rw [morphismRestrict_comp, affine_cancel_right_isIso hP]
exact H ⟨(Opens.map e.hom.val.base).obj U, hU.map_isIso e.hom⟩
#align algebraic_geometry.target_affine_locally_respects_iso AlgebraicGeometry.targetAffineLocally_respectsIso
/-- We say that `P : AffineTargetMorphismProperty` is a local property if
1. `P` respects isomorphisms.
2. If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ Y.basicOpen r` for any
global section `r`.
3. If `P` holds for `f ∣_ Y.basicOpen r` for all `r` in a spanning set of the global sections,
then `P` holds for `f`.
-/
structure AffineTargetMorphismProperty.IsLocal (P : AffineTargetMorphismProperty) : Prop where
/-- `P` as a morphism property respects isomorphisms -/
RespectsIso : P.toProperty.RespectsIso
/-- `P` is stable under restriction to basic open set of global sections. -/
toBasicOpen :
∀ {X Y : Scheme} [IsAffine Y] (f : X ⟶ Y) (r : Y.presheaf.obj <| op ⊤),
P f → @P _ _ (f ∣_ Y.basicOpen r) ((topIsAffineOpen Y).basicOpenIsAffine _)
/-- `P` for `f` if `P` holds for `f` restricted to basic sets of a spanning set of the global
sections -/
ofBasicOpenCover :
∀ {X Y : Scheme} [IsAffine Y] (f : X ⟶ Y) (s : Finset (Y.presheaf.obj <| op ⊤))
(_ : Ideal.span (s : Set (Y.presheaf.obj <| op ⊤)) = ⊤),
(∀ r : s, @P _ _ (f ∣_ Y.basicOpen r.1) ((topIsAffineOpen Y).basicOpenIsAffine _)) → P f
#align algebraic_geometry.affine_target_morphism_property.is_local AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal
/-- Specialization of `ConcreteCategory.id_apply` because `simp` can't see through the defeq. -/
@[local simp] lemma CommRingCat.id_apply (R : CommRingCat) (x : R) : 𝟙 R x = x := rfl
theorem targetAffineLocallyOfOpenCover {P : AffineTargetMorphismProperty} (hP : P.IsLocal)
{X Y : Scheme} (f : X ⟶ Y) (𝒰 : Y.OpenCover) [∀ i, IsAffine (𝒰.obj i)]
(h𝒰 : ∀ i, P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i)) :
targetAffineLocally P f := by
classical
let S i := (⟨⟨Set.range (𝒰.map i).1.base, (𝒰.IsOpen i).base_open.isOpen_range⟩,
rangeIsAffineOpenOfOpenImmersion (𝒰.map i)⟩ : Y.affineOpens)
intro U
apply of_affine_open_cover (P := _) U (Set.range S)
· intro U r h
haveI : IsAffine _ := U.2
have := hP.2 (f ∣_ U.1)
replace this := this (Y.presheaf.map (eqToHom U.1.openEmbedding_obj_top).op r) h
rw [← P.toProperty_apply] at this ⊢
exact (hP.1.arrow_mk_iso_iff (morphismRestrictRestrictBasicOpen f _ r)).mp this
· intro U s hs H
haveI : IsAffine _ := U.2
apply hP.3 (f ∣_ U.1) (s.image (Y.presheaf.map (eqToHom U.1.openEmbedding_obj_top).op))
· apply_fun Ideal.comap (Y.presheaf.map (eqToHom U.1.openEmbedding_obj_top.symm).op) at hs
rw [Ideal.comap_top] at hs
rw [← hs]
simp only [eqToHom_op, eqToHom_map, Finset.coe_image]
have : ∀ {R S : CommRingCat} (e : S = R) (s : Set S),
Ideal.span (eqToHom e '' s) = Ideal.comap (eqToHom e.symm) (Ideal.span s) := by
intro _ S e _
subst e
simp only [eqToHom_refl, CommRingCat.id_apply, Set.image_id']
-- Porting note: Lean didn't see `𝟙 _` is just ring hom id
exact (Ideal.comap_id _).symm
apply this
· rintro ⟨r, hr⟩
obtain ⟨r, hr', rfl⟩ := Finset.mem_image.mp hr
specialize H ⟨r, hr'⟩
rw [← P.toProperty_apply] at H ⊢
exact (hP.1.arrow_mk_iso_iff (morphismRestrictRestrictBasicOpen f _ r)).mpr H
· rw [Set.eq_univ_iff_forall]
simp only [Set.mem_iUnion]
intro x
exact ⟨⟨_, ⟨𝒰.f x, rfl⟩⟩, 𝒰.Covers x⟩
· rintro ⟨_, i, rfl⟩
specialize h𝒰 i
rw [← P.toProperty_apply] at h𝒰 ⊢
exact (hP.1.arrow_mk_iso_iff (morphismRestrictOpensRange f _)).mpr h𝒰
#align algebraic_geometry.target_affine_locally_of_open_cover AlgebraicGeometry.targetAffineLocallyOfOpenCover
open List in
theorem AffineTargetMorphismProperty.IsLocal.affine_openCover_TFAE
{P : AffineTargetMorphismProperty} (hP : P.IsLocal) {X Y : Scheme.{u}} (f : X ⟶ Y) :
TFAE
[targetAffineLocally P f,
∃ (𝒰 : Scheme.OpenCover.{u} Y) (_ : ∀ i, IsAffine (𝒰.obj i)),
∀ i : 𝒰.J, P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i),
∀ (𝒰 : Scheme.OpenCover.{u} Y) [∀ i, IsAffine (𝒰.obj i)] (i : 𝒰.J),
P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i),
∀ {U : Scheme} (g : U ⟶ Y) [IsAffine U] [IsOpenImmersion g],
P (pullback.snd : pullback f g ⟶ U),
∃ (ι : Type u) (U : ι → Opens Y.carrier) (_ : iSup U = ⊤) (hU' : ∀ i, IsAffineOpen (U i)),
∀ i, @P _ _ (f ∣_ U i) (hU' i)] := by
tfae_have 1 → 4
· intro H U g h₁ h₂
replace H := H ⟨⟨_, h₂.base_open.isOpen_range⟩, rangeIsAffineOpenOfOpenImmersion g⟩
rw [← P.toProperty_apply] at H ⊢
rwa [← hP.1.arrow_mk_iso_iff (morphismRestrictOpensRange f _)]
tfae_have 4 → 3
· intro H 𝒰 h𝒰 i
apply H
tfae_have 3 → 2
· exact fun H => ⟨Y.affineCover, inferInstance, H Y.affineCover⟩
tfae_have 2 → 1
· rintro ⟨𝒰, h𝒰, H⟩; exact targetAffineLocallyOfOpenCover hP f 𝒰 H
tfae_have 5 → 2
· rintro ⟨ι, U, hU, hU', H⟩
refine ⟨Y.openCoverOfSuprEqTop U hU, hU', ?_⟩
intro i
specialize H i
rw [← P.toProperty_apply, ← hP.1.arrow_mk_iso_iff (morphismRestrictOpensRange f _)]
rw [← P.toProperty_apply] at H
convert H
all_goals ext1; exact Subtype.range_coe
tfae_have 1 → 5
· intro H
refine ⟨Y.carrier, fun x => (Scheme.Hom.opensRange <| Y.affineCover.map x),
?_, fun i => rangeIsAffineOpenOfOpenImmersion _, ?_⟩
· rw [eq_top_iff]; intro x _; erw [Opens.mem_iSup]; exact ⟨x, Y.affineCover.Covers x⟩
· intro i; exact H ⟨_, rangeIsAffineOpenOfOpenImmersion _⟩
tfae_finish
#align algebraic_geometry.affine_target_morphism_property.is_local.affine_open_cover_tfae AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.affine_openCover_TFAE
theorem AffineTargetMorphismProperty.isLocalOfOpenCoverImply (P : AffineTargetMorphismProperty)
(hP : P.toProperty.RespectsIso)
(H : ∀ {X Y : Scheme.{u}} (f : X ⟶ Y),
(∃ (𝒰 : Scheme.OpenCover.{u} Y) (_ : ∀ i, IsAffine (𝒰.obj i)),
∀ i : 𝒰.J, P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i)) →
∀ {U : Scheme} (g : U ⟶ Y) [IsAffine U] [IsOpenImmersion g],
P (pullback.snd : pullback f g ⟶ U)) :
P.IsLocal := by
refine ⟨hP, ?_, ?_⟩
· introv h
haveI : IsAffine _ := (topIsAffineOpen Y).basicOpenIsAffine r
delta morphismRestrict
rw [affine_cancel_left_isIso hP]
refine @H _ _ f ⟨Scheme.openCoverOfIsIso (𝟙 Y), ?_, ?_⟩ _ (Y.ofRestrict _) _ _
· intro i; dsimp; infer_instance
· intro i; dsimp
rwa [← Category.comp_id pullback.snd, ← pullback.condition, affine_cancel_left_isIso hP]
· introv hs hs'
replace hs := ((topIsAffineOpen Y).basicOpen_union_eq_self_iff _).mpr hs
have := H f ⟨Y.openCoverOfSuprEqTop _ hs, ?_, ?_⟩ (𝟙 _)
· rwa [← Category.comp_id pullback.snd, ← pullback.condition, affine_cancel_left_isIso hP]
at this
· intro i; exact (topIsAffineOpen Y).basicOpenIsAffine _
· rintro (i : s)
specialize hs' i
haveI : IsAffine _ := (topIsAffineOpen Y).basicOpenIsAffine i.1
delta morphismRestrict at hs'
rwa [affine_cancel_left_isIso hP] at hs'
#align algebraic_geometry.affine_target_morphism_property.is_local_of_open_cover_imply AlgebraicGeometry.AffineTargetMorphismProperty.isLocalOfOpenCoverImply
theorem AffineTargetMorphismProperty.IsLocal.affine_openCover_iff {P : AffineTargetMorphismProperty}
(hP : P.IsLocal) {X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} Y)
[h𝒰 : ∀ i, IsAffine (𝒰.obj i)] :
targetAffineLocally P f ↔ ∀ i, @P _ _ (pullback.snd : pullback f (𝒰.map i) ⟶ _) (h𝒰 i) := by
refine ⟨fun H => let h := ((hP.affine_openCover_TFAE f).out 0 2).mp H; ?_,
fun H => let h := ((hP.affine_openCover_TFAE f).out 1 0).mp; ?_⟩
· exact fun i => h 𝒰 i
· exact h ⟨𝒰, inferInstance, H⟩
#align algebraic_geometry.affine_target_morphism_property.is_local.affine_open_cover_iff AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.affine_openCover_iff
theorem AffineTargetMorphismProperty.IsLocal.affine_target_iff {P : AffineTargetMorphismProperty}
(hP : P.IsLocal) {X Y : Scheme.{u}} (f : X ⟶ Y) [IsAffine Y] :
targetAffineLocally P f ↔ P f := by
haveI : ∀ i, IsAffine (Scheme.OpenCover.obj (Scheme.openCoverOfIsIso (𝟙 Y)) i) := fun i => by
dsimp; infer_instance
rw [hP.affine_openCover_iff f (Scheme.openCoverOfIsIso (𝟙 Y))]
trans P (pullback.snd : pullback f (𝟙 _) ⟶ _)
· exact ⟨fun H => H PUnit.unit, fun H _ => H⟩
rw [← Category.comp_id pullback.snd, ← pullback.condition, affine_cancel_left_isIso hP.1]
#align algebraic_geometry.affine_target_morphism_property.is_local.affine_target_iff AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.affine_target_iff
/-- We say that `P : MorphismProperty Scheme` is local at the target if
1. `P` respects isomorphisms.
2. If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ U` for any `U`.
3. If `P` holds for `f ∣_ U` for an open cover `U` of `Y`, then `P` holds for `f`.
-/
structure PropertyIsLocalAtTarget (P : MorphismProperty Scheme) : Prop where
/-- `P` respects isomorphisms. -/
RespectsIso : P.RespectsIso
/-- If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ U` for any `U`. -/
restrict : ∀ {X Y : Scheme} (f : X ⟶ Y) (U : Opens Y.carrier), P f → P (f ∣_ U)
/-- If `P` holds for `f ∣_ U` for an open cover `U` of `Y`, then `P` holds for `f`. -/
of_openCover :
∀ {X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} Y),
(∀ i : 𝒰.J, P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i)) → P f
#align algebraic_geometry.property_is_local_at_target AlgebraicGeometry.PropertyIsLocalAtTarget
lemma propertyIsLocalAtTarget_of_morphismRestrict (P : MorphismProperty Scheme)
(hP₁ : P.RespectsIso)
(hP₂ : ∀ {X Y : Scheme.{u}} (f : X ⟶ Y) (U : Opens Y.carrier), P f → P (f ∣_ U))
(hP₃ : ∀ {X Y : Scheme.{u}} (f : X ⟶ Y) {ι : Type u} (U : ι → Opens Y.carrier)
(_ : iSup U = ⊤), (∀ i, P (f ∣_ U i)) → P f) :
PropertyIsLocalAtTarget P where
RespectsIso := hP₁
restrict := hP₂
of_openCover {X Y} f 𝒰 h𝒰 := by
apply hP₃ f (fun i : 𝒰.J => Scheme.Hom.opensRange (𝒰.map i)) 𝒰.iSup_opensRange
simp_rw [hP₁.arrow_mk_iso_iff (morphismRestrictOpensRange f _)]
exact h𝒰
theorem AffineTargetMorphismProperty.IsLocal.targetAffineLocallyIsLocal
{P : AffineTargetMorphismProperty} (hP : P.IsLocal) :
PropertyIsLocalAtTarget (targetAffineLocally P) := by
constructor
· exact targetAffineLocally_respectsIso hP.1
· intro X Y f U H V
rw [← P.toProperty_apply (i := V.2), hP.1.arrow_mk_iso_iff (morphismRestrictRestrict f _ _)]
convert H ⟨_, IsAffineOpen.imageIsOpenImmersion V.2 (Y.ofRestrict _)⟩
rw [← P.toProperty_apply]
· rintro X Y f 𝒰 h𝒰
-- Porting note: rewrite `[(hP.affine_openCover_TFAE f).out 0 1` directly complains about
-- metavariables
have h01 := (hP.affine_openCover_TFAE f).out 0 1
rw [h01]
refine ⟨𝒰.bind fun _ => Scheme.affineCover _, ?_, ?_⟩
· intro i; dsimp [Scheme.OpenCover.bind]; infer_instance
· intro i
specialize h𝒰 i.1
-- Porting note: rewrite `[(hP.affine_openCover_TFAE pullback.snd).out 0 1` directly
-- complains about metavariables
have h02 := (hP.affine_openCover_TFAE (pullback.snd : pullback f (𝒰.map i.fst) ⟶ _)).out 0 2
rw [h02] at h𝒰
specialize h𝒰 (Scheme.affineCover _) i.2
let e : pullback f ((𝒰.obj i.fst).affineCover.map i.snd ≫ 𝒰.map i.fst) ⟶
pullback (pullback.snd : pullback f (𝒰.map i.fst) ⟶ _)
((𝒰.obj i.fst).affineCover.map i.snd) := by
refine (pullbackSymmetry _ _).hom ≫ ?_
refine (pullbackRightPullbackFstIso _ _ _).inv ≫ ?_
refine (pullbackSymmetry _ _).hom ≫ ?_
refine pullback.map _ _ _ _ (pullbackSymmetry _ _).hom (𝟙 _) (𝟙 _) ?_ ?_ <;>
simp only [Category.comp_id, Category.id_comp, pullbackSymmetry_hom_comp_snd]
rw [← affine_cancel_left_isIso hP.1 e] at h𝒰
convert h𝒰 using 1
simp [e]
#align algebraic_geometry.affine_target_morphism_property.is_local.target_affine_locally_is_local AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal.targetAffineLocallyIsLocal
open List in
theorem PropertyIsLocalAtTarget.openCover_TFAE {P : MorphismProperty Scheme}
(hP : PropertyIsLocalAtTarget P) {X Y : Scheme.{u}} (f : X ⟶ Y) :
TFAE
[P f,
∃ 𝒰 : Scheme.OpenCover.{u} Y,
∀ i : 𝒰.J, P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i),
∀ (𝒰 : Scheme.OpenCover.{u} Y) (i : 𝒰.J),
P (pullback.snd : (𝒰.pullbackCover f).obj i ⟶ 𝒰.obj i),
∀ U : Opens Y.carrier, P (f ∣_ U),
∀ {U : Scheme} (g : U ⟶ Y) [IsOpenImmersion g], P (pullback.snd : pullback f g ⟶ U),
∃ (ι : Type u) (U : ι → Opens Y.carrier) (_ : iSup U = ⊤), ∀ i, P (f ∣_ U i)] := by
tfae_have 2 → 1
· rintro ⟨𝒰, H⟩; exact hP.3 f 𝒰 H
tfae_have 1 → 4
· intro H U; exact hP.2 f U H
tfae_have 4 → 3
· intro H 𝒰 i
rw [← hP.1.arrow_mk_iso_iff (morphismRestrictOpensRange f _)]
exact H <| Scheme.Hom.opensRange (𝒰.map i)
tfae_have 3 → 2
· exact fun H => ⟨Y.affineCover, H Y.affineCover⟩
tfae_have 4 → 5
· intro H U g hg
rw [← hP.1.arrow_mk_iso_iff (morphismRestrictOpensRange f _)]
apply H
tfae_have 5 → 4
· intro H U
erw [hP.1.cancel_left_isIso]
apply H
tfae_have 4 → 6
· intro H; exact ⟨PUnit, fun _ => ⊤, ciSup_const, fun _ => H _⟩
tfae_have 6 → 2
· rintro ⟨ι, U, hU, H⟩
refine ⟨Y.openCoverOfSuprEqTop U hU, ?_⟩
intro i
rw [← hP.1.arrow_mk_iso_iff (morphismRestrictOpensRange f _)]
convert H i
all_goals ext1; exact Subtype.range_coe
tfae_finish
#align algebraic_geometry.property_is_local_at_target.open_cover_tfae AlgebraicGeometry.PropertyIsLocalAtTarget.openCover_TFAE
| Mathlib/AlgebraicGeometry/Morphisms/Basic.lean | 415 | 422 | theorem PropertyIsLocalAtTarget.openCover_iff {P : MorphismProperty Scheme}
(hP : PropertyIsLocalAtTarget P) {X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} Y) :
P f ↔ ∀ i, P (pullback.snd : pullback f (𝒰.map i) ⟶ _) := by |
-- Porting note: couldn't get the term mode proof work
refine ⟨fun H => let h := ((hP.openCover_TFAE f).out 0 2).mp H; fun i => ?_,
fun H => let h := ((hP.openCover_TFAE f).out 1 0).mp; ?_⟩
· exact h 𝒰 i
· exact h ⟨𝒰, H⟩
|
/-
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, Mario Carneiro
-/
import Mathlib.Algebra.BigOperators.Ring.List
import Mathlib.Data.Nat.Prime
import Mathlib.Data.List.Prime
import Mathlib.Data.List.Sort
import Mathlib.Data.List.Chain
#align_import data.nat.factors from "leanprover-community/mathlib"@"008205aa645b3f194c1da47025c5f110c8406eab"
/-!
# Prime numbers
This file deals with the factors of natural numbers.
## Important declarations
- `Nat.factors n`: the prime factorization of `n`
- `Nat.factors_unique`: uniqueness of the prime factorisation
-/
open Bool Subtype
open Nat
namespace Nat
attribute [instance 0] instBEqNat
/-- `factors n` is the prime factorization of `n`, listed in increasing order. -/
def factors : ℕ → List ℕ
| 0 => []
| 1 => []
| k + 2 =>
let m := minFac (k + 2)
m :: factors ((k + 2) / m)
decreasing_by show (k + 2) / m < (k + 2); exact factors_lemma
#align nat.factors Nat.factors
@[simp]
theorem factors_zero : factors 0 = [] := by rw [factors]
#align nat.factors_zero Nat.factors_zero
@[simp]
theorem factors_one : factors 1 = [] := by rw [factors]
#align nat.factors_one Nat.factors_one
@[simp]
| Mathlib/Data/Nat/Factors.lean | 53 | 53 | theorem factors_two : factors 2 = [2] := by | simp [factors]
|
/-
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.Fintype.Basic
import Mathlib.Data.Finset.Card
import Mathlib.Data.List.NodupEquivFin
import Mathlib.Data.Set.Image
#align_import data.fintype.card from "leanprover-community/mathlib"@"bf2428c9486c407ca38b5b3fb10b87dad0bc99fa"
/-!
# Cardinalities of finite types
## Main declarations
* `Fintype.card α`: Cardinality of a fintype. Equal to `Finset.univ.card`.
* `Fintype.truncEquivFin`: A fintype `α` is computably equivalent to `Fin (card α)`. The
`Trunc`-free, noncomputable version is `Fintype.equivFin`.
* `Fintype.truncEquivOfCardEq` `Fintype.equivOfCardEq`: Two fintypes of same cardinality are
equivalent. See above.
* `Fin.equiv_iff_eq`: `Fin m ≃ Fin n` iff `m = n`.
* `Infinite.natEmbedding`: An embedding of `ℕ` into an infinite type.
We also provide the following versions of the pigeonholes principle.
* `Fintype.exists_ne_map_eq_of_card_lt` and `isEmpty_of_card_lt`: Finitely many pigeons and
pigeonholes. Weak formulation.
* `Finite.exists_ne_map_eq_of_infinite`: Infinitely many pigeons in finitely many pigeonholes.
Weak formulation.
* `Finite.exists_infinite_fiber`: Infinitely many pigeons in finitely many pigeonholes. Strong
formulation.
Some more pigeonhole-like statements can be found in `Data.Fintype.CardEmbedding`.
Types which have an injection from/a surjection to an `Infinite` type are themselves `Infinite`.
See `Infinite.of_injective` and `Infinite.of_surjective`.
## Instances
We provide `Infinite` instances for
* specific types: `ℕ`, `ℤ`, `String`
* type constructors: `Multiset α`, `List α`
-/
assert_not_exists MonoidWithZero
assert_not_exists MulAction
open Function
open Nat
universe u v
variable {α β γ : Type*}
open Finset Function
namespace Fintype
/-- `card α` is the number of elements in `α`, defined when `α` is a fintype. -/
def card (α) [Fintype α] : ℕ :=
(@univ α _).card
#align fintype.card Fintype.card
/-- There is (computably) an equivalence between `α` and `Fin (card α)`.
Since it is not unique and depends on which permutation
of the universe list is used, the equivalence is wrapped in `Trunc` to
preserve computability.
See `Fintype.equivFin` for the noncomputable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq`
for an equiv `α ≃ Fin n` given `Fintype.card α = n`.
See `Fintype.truncFinBijection` for a version without `[DecidableEq α]`.
-/
def truncEquivFin (α) [DecidableEq α] [Fintype α] : Trunc (α ≃ Fin (card α)) := by
unfold card Finset.card
exact
Quot.recOnSubsingleton'
(motive := fun s : Multiset α =>
(∀ x : α, x ∈ s) → s.Nodup → Trunc (α ≃ Fin (Multiset.card s)))
univ.val
(fun l (h : ∀ x : α, x ∈ l) (nd : l.Nodup) => Trunc.mk (nd.getEquivOfForallMemList _ h).symm)
mem_univ_val univ.2
#align fintype.trunc_equiv_fin Fintype.truncEquivFin
/-- There is (noncomputably) an equivalence between `α` and `Fin (card α)`.
See `Fintype.truncEquivFin` for the computable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq`
for an equiv `α ≃ Fin n` given `Fintype.card α = n`.
-/
noncomputable def equivFin (α) [Fintype α] : α ≃ Fin (card α) :=
letI := Classical.decEq α
(truncEquivFin α).out
#align fintype.equiv_fin Fintype.equivFin
/-- There is (computably) a bijection between `Fin (card α)` and `α`.
Since it is not unique and depends on which permutation
of the universe list is used, the bijection is wrapped in `Trunc` to
preserve computability.
See `Fintype.truncEquivFin` for a version that gives an equivalence
given `[DecidableEq α]`.
-/
def truncFinBijection (α) [Fintype α] : Trunc { f : Fin (card α) → α // Bijective f } := by
unfold card Finset.card
refine
Quot.recOnSubsingleton'
(motive := fun s : Multiset α =>
(∀ x : α, x ∈ s) → s.Nodup → Trunc {f : Fin (Multiset.card s) → α // Bijective f})
univ.val
(fun l (h : ∀ x : α, x ∈ l) (nd : l.Nodup) => Trunc.mk (nd.getBijectionOfForallMemList _ h))
mem_univ_val univ.2
#align fintype.trunc_fin_bijection Fintype.truncFinBijection
theorem subtype_card {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x) :
@card { x // p x } (Fintype.subtype s H) = s.card :=
Multiset.card_pmap _ _ _
#align fintype.subtype_card Fintype.subtype_card
theorem card_of_subtype {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x)
[Fintype { x // p x }] : card { x // p x } = s.card := by
rw [← subtype_card s H]
congr
apply Subsingleton.elim
#align fintype.card_of_subtype Fintype.card_of_subtype
@[simp]
theorem card_ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) :
@Fintype.card p (ofFinset s H) = s.card :=
Fintype.subtype_card s H
#align fintype.card_of_finset Fintype.card_ofFinset
theorem card_of_finset' {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) [Fintype p] :
Fintype.card p = s.card := by rw [← card_ofFinset s H]; congr; apply Subsingleton.elim
#align fintype.card_of_finset' Fintype.card_of_finset'
end Fintype
namespace Fintype
theorem ofEquiv_card [Fintype α] (f : α ≃ β) : @card β (ofEquiv α f) = card α :=
Multiset.card_map _ _
#align fintype.of_equiv_card Fintype.ofEquiv_card
theorem card_congr {α β} [Fintype α] [Fintype β] (f : α ≃ β) : card α = card β := by
rw [← ofEquiv_card f]; congr; apply Subsingleton.elim
#align fintype.card_congr Fintype.card_congr
@[congr]
theorem card_congr' {α β} [Fintype α] [Fintype β] (h : α = β) : card α = card β :=
card_congr (by rw [h])
#align fintype.card_congr' Fintype.card_congr'
section
variable [Fintype α] [Fintype β]
/-- If the cardinality of `α` is `n`, there is computably a bijection between `α` and `Fin n`.
See `Fintype.equivFinOfCardEq` for the noncomputable definition,
and `Fintype.truncEquivFin` and `Fintype.equivFin` for the bijection `α ≃ Fin (card α)`.
-/
def truncEquivFinOfCardEq [DecidableEq α] {n : ℕ} (h : Fintype.card α = n) : Trunc (α ≃ Fin n) :=
(truncEquivFin α).map fun e => e.trans (finCongr h)
#align fintype.trunc_equiv_fin_of_card_eq Fintype.truncEquivFinOfCardEq
/-- If the cardinality of `α` is `n`, there is noncomputably a bijection between `α` and `Fin n`.
See `Fintype.truncEquivFinOfCardEq` for the computable definition,
and `Fintype.truncEquivFin` and `Fintype.equivFin` for the bijection `α ≃ Fin (card α)`.
-/
noncomputable def equivFinOfCardEq {n : ℕ} (h : Fintype.card α = n) : α ≃ Fin n :=
letI := Classical.decEq α
(truncEquivFinOfCardEq h).out
#align fintype.equiv_fin_of_card_eq Fintype.equivFinOfCardEq
/-- Two `Fintype`s with the same cardinality are (computably) in bijection.
See `Fintype.equivOfCardEq` for the noncomputable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq` for
the specialization to `Fin`.
-/
def truncEquivOfCardEq [DecidableEq α] [DecidableEq β] (h : card α = card β) : Trunc (α ≃ β) :=
(truncEquivFinOfCardEq h).bind fun e => (truncEquivFin β).map fun e' => e.trans e'.symm
#align fintype.trunc_equiv_of_card_eq Fintype.truncEquivOfCardEq
/-- Two `Fintype`s with the same cardinality are (noncomputably) in bijection.
See `Fintype.truncEquivOfCardEq` for the computable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq` for
the specialization to `Fin`.
-/
noncomputable def equivOfCardEq (h : card α = card β) : α ≃ β := by
letI := Classical.decEq α
letI := Classical.decEq β
exact (truncEquivOfCardEq h).out
#align fintype.equiv_of_card_eq Fintype.equivOfCardEq
end
theorem card_eq {α β} [_F : Fintype α] [_G : Fintype β] : card α = card β ↔ Nonempty (α ≃ β) :=
⟨fun h =>
haveI := Classical.propDecidable
(truncEquivOfCardEq h).nonempty,
fun ⟨f⟩ => card_congr f⟩
#align fintype.card_eq Fintype.card_eq
/-- Note: this lemma is specifically about `Fintype.ofSubsingleton`. For a statement about
arbitrary `Fintype` instances, use either `Fintype.card_le_one_iff_subsingleton` or
`Fintype.card_unique`. -/
@[simp]
theorem card_ofSubsingleton (a : α) [Subsingleton α] : @Fintype.card _ (ofSubsingleton a) = 1 :=
rfl
#align fintype.card_of_subsingleton Fintype.card_ofSubsingleton
@[simp]
theorem card_unique [Unique α] [h : Fintype α] : Fintype.card α = 1 :=
Subsingleton.elim (ofSubsingleton default) h ▸ card_ofSubsingleton _
#align fintype.card_unique Fintype.card_unique
/-- Note: this lemma is specifically about `Fintype.ofIsEmpty`. For a statement about
arbitrary `Fintype` instances, use `Fintype.card_eq_zero`. -/
@[simp]
theorem card_ofIsEmpty [IsEmpty α] : @Fintype.card α Fintype.ofIsEmpty = 0 :=
rfl
#align fintype.card_of_is_empty Fintype.card_ofIsEmpty
end Fintype
namespace Set
variable {s t : Set α}
-- We use an arbitrary `[Fintype s]` instance here,
-- not necessarily coming from a `[Fintype α]`.
@[simp]
theorem toFinset_card {α : Type*} (s : Set α) [Fintype s] : s.toFinset.card = Fintype.card s :=
Multiset.card_map Subtype.val Finset.univ.val
#align set.to_finset_card Set.toFinset_card
end Set
@[simp]
theorem Finset.card_univ [Fintype α] : (Finset.univ : Finset α).card = Fintype.card α :=
rfl
#align finset.card_univ Finset.card_univ
theorem Finset.eq_univ_of_card [Fintype α] (s : Finset α) (hs : s.card = Fintype.card α) :
s = univ :=
eq_of_subset_of_card_le (subset_univ _) <| by rw [hs, Finset.card_univ]
#align finset.eq_univ_of_card Finset.eq_univ_of_card
theorem Finset.card_eq_iff_eq_univ [Fintype α] (s : Finset α) :
s.card = Fintype.card α ↔ s = Finset.univ :=
⟨s.eq_univ_of_card, by
rintro rfl
exact Finset.card_univ⟩
#align finset.card_eq_iff_eq_univ Finset.card_eq_iff_eq_univ
theorem Finset.card_le_univ [Fintype α] (s : Finset α) : s.card ≤ Fintype.card α :=
card_le_card (subset_univ s)
#align finset.card_le_univ Finset.card_le_univ
theorem Finset.card_lt_univ_of_not_mem [Fintype α] {s : Finset α} {x : α} (hx : x ∉ s) :
s.card < Fintype.card α :=
card_lt_card ⟨subset_univ s, not_forall.2 ⟨x, fun hx' => hx (hx' <| mem_univ x)⟩⟩
#align finset.card_lt_univ_of_not_mem Finset.card_lt_univ_of_not_mem
theorem Finset.card_lt_iff_ne_univ [Fintype α] (s : Finset α) :
s.card < Fintype.card α ↔ s ≠ Finset.univ :=
s.card_le_univ.lt_iff_ne.trans (not_congr s.card_eq_iff_eq_univ)
#align finset.card_lt_iff_ne_univ Finset.card_lt_iff_ne_univ
theorem Finset.card_compl_lt_iff_nonempty [Fintype α] [DecidableEq α] (s : Finset α) :
sᶜ.card < Fintype.card α ↔ s.Nonempty :=
sᶜ.card_lt_iff_ne_univ.trans s.compl_ne_univ_iff_nonempty
#align finset.card_compl_lt_iff_nonempty Finset.card_compl_lt_iff_nonempty
theorem Finset.card_univ_diff [DecidableEq α] [Fintype α] (s : Finset α) :
(Finset.univ \ s).card = Fintype.card α - s.card :=
Finset.card_sdiff (subset_univ s)
#align finset.card_univ_diff Finset.card_univ_diff
theorem Finset.card_compl [DecidableEq α] [Fintype α] (s : Finset α) :
sᶜ.card = Fintype.card α - s.card :=
Finset.card_univ_diff s
#align finset.card_compl Finset.card_compl
@[simp]
theorem Finset.card_add_card_compl [DecidableEq α] [Fintype α] (s : Finset α) :
s.card + sᶜ.card = Fintype.card α := by
rw [Finset.card_compl, ← Nat.add_sub_assoc (card_le_univ s), Nat.add_sub_cancel_left]
@[simp]
theorem Finset.card_compl_add_card [DecidableEq α] [Fintype α] (s : Finset α) :
sᶜ.card + s.card = Fintype.card α := by
rw [add_comm, card_add_card_compl]
theorem Fintype.card_compl_set [Fintype α] (s : Set α) [Fintype s] [Fintype (↥sᶜ : Sort _)] :
Fintype.card (↥sᶜ : Sort _) = Fintype.card α - Fintype.card s := by
classical rw [← Set.toFinset_card, ← Set.toFinset_card, ← Finset.card_compl, Set.toFinset_compl]
#align fintype.card_compl_set Fintype.card_compl_set
@[simp]
theorem Fintype.card_fin (n : ℕ) : Fintype.card (Fin n) = n :=
List.length_finRange n
#align fintype.card_fin Fintype.card_fin
theorem Fintype.card_fin_lt_of_le {m n : ℕ} (h : m ≤ n) :
Fintype.card {i : Fin n // i < m} = m := by
conv_rhs => rw [← Fintype.card_fin m]
apply Fintype.card_congr
exact { toFun := fun ⟨⟨i, _⟩, hi⟩ ↦ ⟨i, hi⟩
invFun := fun ⟨i, hi⟩ ↦ ⟨⟨i, lt_of_lt_of_le hi h⟩, hi⟩
left_inv := fun i ↦ rfl
right_inv := fun i ↦ rfl }
theorem Finset.card_fin (n : ℕ) : Finset.card (Finset.univ : Finset (Fin n)) = n := by simp
#align finset.card_fin Finset.card_fin
/-- `Fin` as a map from `ℕ` to `Type` is injective. Note that since this is a statement about
equality of types, using it should be avoided if possible. -/
theorem fin_injective : Function.Injective Fin := fun m n h =>
(Fintype.card_fin m).symm.trans <| (Fintype.card_congr <| Equiv.cast h).trans (Fintype.card_fin n)
#align fin_injective fin_injective
/-- A reversed version of `Fin.cast_eq_cast` that is easier to rewrite with. -/
theorem Fin.cast_eq_cast' {n m : ℕ} (h : Fin n = Fin m) :
_root_.cast h = Fin.cast (fin_injective h) := by
cases fin_injective h
rfl
#align fin.cast_eq_cast' Fin.cast_eq_cast'
| Mathlib/Data/Fintype/Card.lean | 340 | 341 | theorem card_finset_fin_le {n : ℕ} (s : Finset (Fin n)) : s.card ≤ n := by |
simpa only [Fintype.card_fin] using s.card_le_univ
|
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Order.Antichain
import Mathlib.Order.UpperLower.Basic
import Mathlib.Order.Interval.Set.Basic
import Mathlib.Order.RelIso.Set
#align_import order.minimal from "leanprover-community/mathlib"@"59694bd07f0a39c5beccba34bd9f413a160782bf"
/-!
# Minimal/maximal elements of a set
This file defines minimal and maximal of a set with respect to an arbitrary relation.
## Main declarations
* `maximals r s`: Maximal elements of `s` with respect to `r`.
* `minimals r s`: Minimal elements of `s` with respect to `r`.
## TODO
Do we need a `Finset` version?
-/
open Function Set
variable {α : Type*} (r r₁ r₂ : α → α → Prop) (s t : Set α) (a b : α)
/-- Turns a set into an antichain by keeping only the "maximal" elements. -/
def maximals : Set α :=
{ a ∈ s | ∀ ⦃b⦄, b ∈ s → r a b → r b a }
#align maximals maximals
/-- Turns a set into an antichain by keeping only the "minimal" elements. -/
def minimals : Set α :=
{ a ∈ s | ∀ ⦃b⦄, b ∈ s → r b a → r a b }
#align minimals minimals
theorem maximals_subset : maximals r s ⊆ s :=
sep_subset _ _
#align maximals_subset maximals_subset
theorem minimals_subset : minimals r s ⊆ s :=
sep_subset _ _
#align minimals_subset minimals_subset
@[simp]
theorem maximals_empty : maximals r ∅ = ∅ :=
sep_empty _
#align maximals_empty maximals_empty
@[simp]
theorem minimals_empty : minimals r ∅ = ∅ :=
sep_empty _
#align minimals_empty minimals_empty
@[simp]
theorem maximals_singleton : maximals r {a} = {a} :=
(maximals_subset _ _).antisymm <|
singleton_subset_iff.2 <|
⟨rfl, by
rintro b (rfl : b = a)
exact id⟩
#align maximals_singleton maximals_singleton
@[simp]
theorem minimals_singleton : minimals r {a} = {a} :=
maximals_singleton _ _
#align minimals_singleton minimals_singleton
theorem maximals_swap : maximals (swap r) s = minimals r s :=
rfl
#align maximals_swap maximals_swap
theorem minimals_swap : minimals (swap r) s = maximals r s :=
rfl
#align minimals_swap minimals_swap
section IsAntisymm
variable {r s t a b} [IsAntisymm α r]
theorem eq_of_mem_maximals (ha : a ∈ maximals r s) (hb : b ∈ s) (h : r a b) : a = b :=
antisymm h <| ha.2 hb h
#align eq_of_mem_maximals eq_of_mem_maximals
theorem eq_of_mem_minimals (ha : a ∈ minimals r s) (hb : b ∈ s) (h : r b a) : a = b :=
antisymm (ha.2 hb h) h
#align eq_of_mem_minimals eq_of_mem_minimals
set_option autoImplicit true
theorem mem_maximals_iff : x ∈ maximals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, y ∈ s → r x y → x = y := by
simp only [maximals, Set.mem_sep_iff, and_congr_right_iff]
refine fun _ ↦ ⟨fun h y hys hxy ↦ antisymm hxy (h hys hxy), fun h y hys hxy ↦ ?_⟩
convert hxy <;> rw [h hys hxy]
theorem mem_maximals_setOf_iff : x ∈ maximals r (setOf P) ↔ P x ∧ ∀ ⦃y⦄, P y → r x y → x = y :=
mem_maximals_iff
theorem mem_minimals_iff : x ∈ minimals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, y ∈ s → r y x → x = y :=
@mem_maximals_iff _ _ _ (IsAntisymm.swap r) _
theorem mem_minimals_setOf_iff : x ∈ minimals r (setOf P) ↔ P x ∧ ∀ ⦃y⦄, P y → r y x → x = y :=
mem_minimals_iff
/-- This theorem can't be used to rewrite without specifying `rlt`, since `rlt` would have to be
guessed. See `mem_minimals_iff_forall_ssubset_not_mem` and `mem_minimals_iff_forall_lt_not_mem`
for `⊆` and `≤` versions. -/
theorem mem_minimals_iff_forall_lt_not_mem' (rlt : α → α → Prop) [IsNonstrictStrictOrder α r rlt] :
x ∈ minimals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, rlt y x → y ∉ s := by
simp [minimals, right_iff_left_not_left_of r rlt, not_imp_not, imp.swap (a := _ ∈ _)]
theorem mem_maximals_iff_forall_lt_not_mem' (rlt : α → α → Prop) [IsNonstrictStrictOrder α r rlt] :
x ∈ maximals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, rlt x y → y ∉ s := by
simp [maximals, right_iff_left_not_left_of r rlt, not_imp_not, imp.swap (a := _ ∈ _)]
theorem minimals_eq_minimals_of_subset_of_forall [IsTrans α r] (hts : t ⊆ s)
(h : ∀ x ∈ s, ∃ y ∈ t, r y x) : minimals r s = minimals r t := by
refine Set.ext fun a ↦ ⟨fun ⟨has, hmin⟩ ↦ ⟨?_,fun b hbt ↦ hmin (hts hbt)⟩,
fun ⟨hat, hmin⟩ ↦ ⟨hts hat, fun b hbs hba ↦ ?_⟩⟩
· obtain ⟨a', ha', haa'⟩ := h _ has
rwa [antisymm (hmin (hts ha') haa') haa']
obtain ⟨b', hb't, hb'b⟩ := h b hbs
rwa [antisymm (hmin hb't (Trans.trans hb'b hba)) (Trans.trans hb'b hba)]
theorem maximals_eq_maximals_of_subset_of_forall [IsTrans α r] (hts : t ⊆ s)
(h : ∀ x ∈ s, ∃ y ∈ t, r x y) : maximals r s = maximals r t :=
@minimals_eq_minimals_of_subset_of_forall _ _ _ _ (IsAntisymm.swap r) (IsTrans.swap r) hts h
variable (r s)
theorem maximals_antichain : IsAntichain r (maximals r s) := fun _a ha _b hb hab h =>
hab <| eq_of_mem_maximals ha hb.1 h
#align maximals_antichain maximals_antichain
theorem minimals_antichain : IsAntichain r (minimals r s) :=
haveI := IsAntisymm.swap r
(maximals_antichain _ _).swap
#align minimals_antichain minimals_antichain
end IsAntisymm
set_option autoImplicit true
theorem mem_minimals_iff_forall_ssubset_not_mem (s : Set (Set α)) :
x ∈ minimals (· ⊆ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, y ⊂ x → y ∉ s :=
mem_minimals_iff_forall_lt_not_mem' (· ⊂ ·)
theorem mem_minimals_iff_forall_lt_not_mem [PartialOrder α] {s : Set α} :
x ∈ minimals (· ≤ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, y < x → y ∉ s :=
mem_minimals_iff_forall_lt_not_mem' (· < ·)
theorem mem_maximals_iff_forall_ssubset_not_mem {s : Set (Set α)} :
x ∈ maximals (· ⊆ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, x ⊂ y → y ∉ s :=
mem_maximals_iff_forall_lt_not_mem' (· ⊂ ·)
theorem mem_maximals_iff_forall_lt_not_mem [PartialOrder α] {s : Set α} :
x ∈ maximals (· ≤ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, x < y → y ∉ s :=
mem_maximals_iff_forall_lt_not_mem' (· < ·)
-- Porting note (#10756): new theorem
theorem maximals_of_symm [IsSymm α r] : maximals r s = s :=
sep_eq_self_iff_mem_true.2 fun _ _ _ _ => symm
-- Porting note (#10756): new theorem
theorem minimals_of_symm [IsSymm α r] : minimals r s = s :=
sep_eq_self_iff_mem_true.2 fun _ _ _ _ => symm
theorem maximals_eq_minimals [IsSymm α r] : maximals r s = minimals r s := by
rw [minimals_of_symm, maximals_of_symm]
#align maximals_eq_minimals maximals_eq_minimals
variable {r r₁ r₂ s t a}
-- Porting note (#11215): TODO: use `h.induction_on`
theorem Set.Subsingleton.maximals_eq (h : s.Subsingleton) : maximals r s = s := by
rcases h.eq_empty_or_singleton with (rfl | ⟨x, rfl⟩)
exacts [minimals_empty _, maximals_singleton _ _]
#align set.subsingleton.maximals_eq Set.Subsingleton.maximals_eq
theorem Set.Subsingleton.minimals_eq (h : s.Subsingleton) : minimals r s = s :=
h.maximals_eq
#align set.subsingleton.minimals_eq Set.Subsingleton.minimals_eq
theorem maximals_mono [IsAntisymm α r₂] (h : ∀ a b, r₁ a b → r₂ a b) :
maximals r₂ s ⊆ maximals r₁ s := fun a ha =>
⟨ha.1, fun b hb hab => by
have := eq_of_mem_maximals ha hb (h _ _ hab)
subst this
exact hab⟩
#align maximals_mono maximals_mono
theorem minimals_mono [IsAntisymm α r₂] (h : ∀ a b, r₁ a b → r₂ a b) :
minimals r₂ s ⊆ minimals r₁ s := fun a ha =>
⟨ha.1, fun b hb hab => by
have := eq_of_mem_minimals ha hb (h _ _ hab)
subst this
exact hab⟩
#align minimals_mono minimals_mono
theorem maximals_union : maximals r (s ∪ t) ⊆ maximals r s ∪ maximals r t := by
intro a ha
obtain h | h := ha.1
· exact Or.inl ⟨h, fun b hb => ha.2 <| Or.inl hb⟩
· exact Or.inr ⟨h, fun b hb => ha.2 <| Or.inr hb⟩
#align maximals_union maximals_union
theorem minimals_union : minimals r (s ∪ t) ⊆ minimals r s ∪ minimals r t :=
maximals_union
#align minimals_union minimals_union
theorem maximals_inter_subset : maximals r s ∩ t ⊆ maximals r (s ∩ t) := fun _a ha =>
⟨⟨ha.1.1, ha.2⟩, fun _b hb => ha.1.2 hb.1⟩
#align maximals_inter_subset maximals_inter_subset
theorem minimals_inter_subset : minimals r s ∩ t ⊆ minimals r (s ∩ t) :=
maximals_inter_subset
#align minimals_inter_subset minimals_inter_subset
theorem inter_maximals_subset : s ∩ maximals r t ⊆ maximals r (s ∩ t) := fun _a ha =>
⟨⟨ha.1, ha.2.1⟩, fun _b hb => ha.2.2 hb.2⟩
#align inter_maximals_subset inter_maximals_subset
theorem inter_minimals_subset : s ∩ minimals r t ⊆ minimals r (s ∩ t) :=
inter_maximals_subset
#align inter_minimals_subset inter_minimals_subset
theorem IsAntichain.maximals_eq (h : IsAntichain r s) : maximals r s = s :=
(maximals_subset _ _).antisymm fun a ha =>
⟨ha, fun b hb hab => by
obtain rfl := h.eq ha hb hab
exact hab⟩
#align is_antichain.maximals_eq IsAntichain.maximals_eq
theorem IsAntichain.minimals_eq (h : IsAntichain r s) : minimals r s = s :=
h.flip.maximals_eq
#align is_antichain.minimals_eq IsAntichain.minimals_eq
@[simp]
theorem maximals_idem : maximals r (maximals r s) = maximals r s :=
(maximals_subset _ _).antisymm fun _a ha => ⟨ha, fun _b hb => ha.2 hb.1⟩
#align maximals_idem maximals_idem
@[simp]
theorem minimals_idem : minimals r (minimals r s) = minimals r s :=
maximals_idem
#align minimals_idem minimals_idem
/-- If `maximals r s` is included in but *shadows* the antichain `t`, then it is actually
equal to `t`. -/
theorem IsAntichain.max_maximals (ht : IsAntichain r t) (h : maximals r s ⊆ t)
(hs : ∀ ⦃a⦄, a ∈ t → ∃ b ∈ maximals r s, r b a) : maximals r s = t := by
refine h.antisymm fun a ha => ?_
obtain ⟨b, hb, hr⟩ := hs ha
rwa [of_not_not fun hab => ht (h hb) ha (Ne.symm hab) hr]
#align is_antichain.max_maximals IsAntichain.max_maximals
/-- If `minimals r s` is included in but *shadows* the antichain `t`, then it is actually
equal to `t`. -/
theorem IsAntichain.max_minimals (ht : IsAntichain r t) (h : minimals r s ⊆ t)
(hs : ∀ ⦃a⦄, a ∈ t → ∃ b ∈ minimals r s, r a b) : minimals r s = t := by
refine h.antisymm fun a ha => ?_
obtain ⟨b, hb, hr⟩ := hs ha
rwa [of_not_not fun hab => ht ha (h hb) hab hr]
#align is_antichain.max_minimals IsAntichain.max_minimals
variable [PartialOrder α]
theorem IsLeast.mem_minimals (h : IsLeast s a) : a ∈ minimals (· ≤ ·) s :=
⟨h.1, fun _b hb _ => h.2 hb⟩
#align is_least.mem_minimals IsLeast.mem_minimals
theorem IsGreatest.mem_maximals (h : IsGreatest s a) : a ∈ maximals (· ≤ ·) s :=
⟨h.1, fun _b hb _ => h.2 hb⟩
#align is_greatest.mem_maximals IsGreatest.mem_maximals
theorem IsLeast.minimals_eq (h : IsLeast s a) : minimals (· ≤ ·) s = {a} :=
eq_singleton_iff_unique_mem.2 ⟨h.mem_minimals, fun _b hb => eq_of_mem_minimals hb h.1 <| h.2 hb.1⟩
#align is_least.minimals_eq IsLeast.minimals_eq
theorem IsGreatest.maximals_eq (h : IsGreatest s a) : maximals (· ≤ ·) s = {a} :=
eq_singleton_iff_unique_mem.2 ⟨h.mem_maximals, fun _b hb => eq_of_mem_maximals hb h.1 <| h.2 hb.1⟩
#align is_greatest.maximals_eq IsGreatest.maximals_eq
theorem IsAntichain.minimals_upperClosure (hs : IsAntichain (· ≤ ·) s) :
minimals (· ≤ ·) (upperClosure s : Set α) = s :=
hs.max_minimals
(fun a ⟨⟨b, hb, hba⟩, _⟩ => by rwa [eq_of_mem_minimals ‹a ∈ _› (subset_upperClosure hb) hba])
fun a ha =>
⟨a, ⟨subset_upperClosure ha, fun b ⟨c, hc, hcb⟩ hba => by rwa [hs.eq' ha hc (hcb.trans hba)]⟩,
le_rfl⟩
#align is_antichain.minimals_upper_closure IsAntichain.minimals_upperClosure
theorem IsAntichain.maximals_lowerClosure (hs : IsAntichain (· ≤ ·) s) :
maximals (· ≤ ·) (lowerClosure s : Set α) = s :=
hs.to_dual.minimals_upperClosure
#align is_antichain.maximals_lower_closure IsAntichain.maximals_lowerClosure
section Image
variable {f : α → β} {r : α → α → Prop} {s : β → β → Prop}
section
variable {x : Set α} (hf : ∀ ⦃a a'⦄, a ∈ x → a' ∈ x → (r a a' ↔ s (f a) (f a'))) {a : α}
theorem map_mem_minimals (ha : a ∈ minimals r x) : f a ∈ minimals s (f '' x) :=
⟨⟨a, ha.1, rfl⟩, by rintro _ ⟨a', h', rfl⟩; rw [← hf ha.1 h', ← hf h' ha.1]; exact ha.2 h'⟩
theorem map_mem_maximals (ha : a ∈ maximals r x) : f a ∈ maximals s (f '' x) :=
map_mem_minimals (fun _ _ h₁ h₂ ↦ by exact hf h₂ h₁) ha
theorem map_mem_minimals_iff (ha : a ∈ x) : f a ∈ minimals s (f '' x) ↔ a ∈ minimals r x :=
⟨fun ⟨_, hmin⟩ ↦ ⟨ha, fun a' h' ↦ by
simpa only [hf h' ha, hf ha h'] using hmin ⟨a', h', rfl⟩⟩, map_mem_minimals hf⟩
theorem map_mem_maximals_iff (ha : a ∈ x) : f a ∈ maximals s (f '' x) ↔ a ∈ maximals r x :=
map_mem_minimals_iff (fun _ _ h₁ h₂ ↦ by exact hf h₂ h₁) ha
theorem image_minimals_of_rel_iff_rel : f '' minimals r x = minimals s (f '' x) := by
ext b; refine ⟨?_, fun h ↦ ?_⟩
· rintro ⟨a, ha, rfl⟩; exact map_mem_minimals hf ha
· obtain ⟨a, ha, rfl⟩ := h.1; exact ⟨a, (map_mem_minimals_iff hf ha).mp h, rfl⟩
theorem image_maximals_of_rel_iff_rel : f '' maximals r x = maximals s (f '' x) :=
image_minimals_of_rel_iff_rel fun _ _ h₁ h₂ ↦ hf h₂ h₁
end
theorem RelEmbedding.image_minimals_eq (f : r ↪r s) (x : Set α) :
f '' minimals r x = minimals s (f '' x) := by
rw [image_minimals_of_rel_iff_rel]; simp [f.map_rel_iff]
theorem RelEmbedding.image_maximals_eq (f : r ↪r s) (x : Set α) :
f '' maximals r x = maximals s (f '' x) :=
f.swap.image_minimals_eq x
section
variable [LE α] [LE β] {s : Set α} {t : Set β}
theorem image_minimals_univ :
Subtype.val '' minimals (· ≤ ·) (univ : Set s) = minimals (· ≤ ·) s := by
rw [image_minimals_of_rel_iff_rel, image_univ, Subtype.range_val]; intros; rfl
theorem image_maximals_univ :
Subtype.val '' maximals (· ≤ ·) (univ : Set s) = maximals (· ≤ ·) s :=
image_minimals_univ (α := αᵒᵈ)
nonrec theorem OrderIso.map_mem_minimals (f : s ≃o t) {x : α}
(hx : x ∈ minimals (· ≤ ·) s) : (f ⟨x, hx.1⟩).val ∈ minimals (· ≤ ·) t := by
rw [← image_minimals_univ] at hx
obtain ⟨x, h, rfl⟩ := hx
convert map_mem_minimals (f := Subtype.val ∘ f) (fun _ _ _ _ ↦ f.map_rel_iff.symm) h
rw [image_comp, image_univ, f.range_eq, image_univ, Subtype.range_val]
theorem OrderIso.map_mem_maximals (f : s ≃o t) {x : α}
(hx : x ∈ maximals (· ≤ ·) s) : (f ⟨x, hx.1⟩).val ∈ maximals (· ≤ ·) t :=
(show OrderDual.ofDual ⁻¹' s ≃o OrderDual.ofDual ⁻¹' t from f.dual).map_mem_minimals hx
/-- If two sets are order isomorphic, their minimals are also order isomorphic. -/
def OrderIso.mapMinimals (f : s ≃o t) : minimals (· ≤ ·) s ≃o minimals (· ≤ ·) t where
toFun x := ⟨f ⟨x, x.2.1⟩, f.map_mem_minimals x.2⟩
invFun x := ⟨f.symm ⟨x, x.2.1⟩, f.symm.map_mem_minimals x.2⟩
left_inv x := Subtype.ext (by apply congr_arg Subtype.val <| f.left_inv ⟨x, x.2.1⟩)
right_inv x := Subtype.ext (by apply congr_arg Subtype.val <| f.right_inv ⟨x, x.2.1⟩)
map_rel_iff' {_ _} := f.map_rel_iff
/-- If two sets are order isomorphic, their maximals are also order isomorphic. -/
def OrderIso.mapMaximals (f : s ≃o t) : maximals (· ≤ ·) s ≃o maximals (· ≤ ·) t where
toFun x := ⟨f ⟨x, x.2.1⟩, f.map_mem_maximals x.2⟩
invFun x := ⟨f.symm ⟨x, x.2.1⟩, f.symm.map_mem_maximals x.2⟩
__ := (show OrderDual.ofDual ⁻¹' s ≃o OrderDual.ofDual ⁻¹' t from f.dual).mapMinimals
-- defeq abuse to fill in the proof fields.
-- If OrderDual ever becomes a structure, just copy the last three lines from OrderIso.mapMinimals
open OrderDual in
/-- If two sets are antitonically order isomorphic, their minimals are too. -/
def OrderIso.minimalsIsoMaximals (f : s ≃o tᵒᵈ) :
minimals (· ≤ ·) s ≃o (maximals (· ≤ ·) t)ᵒᵈ where
toFun x := toDual ⟨↑(ofDual (f ⟨x, x.2.1⟩)), (show s ≃o ofDual ⁻¹' t from f).map_mem_minimals x.2⟩
invFun x := ⟨f.symm (toDual ⟨_, (ofDual x).2.1⟩),
(show ofDual ⁻¹' t ≃o s from f.symm).map_mem_minimals x.2⟩
__ := (show s ≃o ofDual⁻¹' t from f).mapMinimals
open OrderDual in
/-- If two sets are antitonically order isomorphic, their minimals are too. -/
def OrderIso.maximalsIsoMinimals (f : s ≃o tᵒᵈ) :
maximals (· ≤ ·) s ≃o (minimals (· ≤ ·) t)ᵒᵈ where
toFun x := toDual ⟨↑(ofDual (f ⟨x, x.2.1⟩)), (show s ≃o ofDual ⁻¹' t from f).map_mem_maximals x.2⟩
invFun x := ⟨f.symm (toDual ⟨_, (ofDual x).2.1⟩),
(show ofDual ⁻¹' t ≃o s from f.symm).map_mem_maximals x.2⟩
__ := (show s ≃o ofDual⁻¹' t from f).mapMaximals
end
theorem inter_minimals_preimage_inter_eq_of_rel_iff_rel_on
(hf : ∀ ⦃a a'⦄, a ∈ x → a' ∈ x → (r a a' ↔ s (f a) (f a'))) (y : Set β) :
x ∩ f ⁻¹' (minimals s ((f '' x) ∩ y)) = minimals r (x ∩ f ⁻¹' y) := by
ext a
simp only [minimals, mem_inter_iff, mem_image, and_imp, forall_exists_index,
forall_apply_eq_imp_iff₂, preimage_setOf_eq, mem_setOf_eq, mem_preimage]
exact ⟨fun ⟨hax,⟨_,hay⟩,h2⟩ ↦ ⟨⟨hax, hay⟩, fun a₁ ha₁ ha₁y ha₁a ↦
(hf hax ha₁).mpr (h2 _ ha₁ ha₁y ((hf ha₁ hax).mp ha₁a))⟩ ,
fun ⟨⟨hax,hay⟩,h⟩ ↦ ⟨hax, ⟨⟨_, hax, rfl⟩, hay⟩, fun a' ha' ha'y hsa' ↦
(hf hax ha').mp (h ha' ha'y ((hf ha' hax).mpr hsa'))⟩⟩
theorem inter_preimage_minimals_eq_of_rel_iff_rel_on_of_subset
(hf : ∀ ⦃a a'⦄, a ∈ x → a' ∈ x → (r a a' ↔ s (f a) (f a'))) (hy : y ⊆ f '' x) :
x ∩ f ⁻¹' (minimals s y) = minimals r (x ∩ f ⁻¹' y) := by
rw [← inter_eq_self_of_subset_right hy, inter_minimals_preimage_inter_eq_of_rel_iff_rel_on hf,
preimage_inter, ← inter_assoc, inter_eq_self_of_subset_left (subset_preimage_image f x)]
theorem RelEmbedding.inter_preimage_minimals_eq (f : r ↪r s) (x : Set α) (y : Set β) :
x ∩ f⁻¹' (minimals s ((f '' x) ∩ y)) = minimals r (x ∩ f ⁻¹' y) :=
inter_minimals_preimage_inter_eq_of_rel_iff_rel_on (by simp [f.map_rel_iff]) y
theorem RelEmbedding.inter_preimage_minimals_eq_of_subset (f : r ↪r s) (h : y ⊆ f '' x) :
x ∩ f ⁻¹' (minimals s y) = minimals r (x ∩ f ⁻¹' y) := by
rw [inter_preimage_minimals_eq_of_rel_iff_rel_on_of_subset _ h]; simp [f.map_rel_iff]
theorem RelEmbedding.minimals_preimage_eq (f : r ↪r s) (y : Set β) :
minimals r (f ⁻¹' y) = f ⁻¹' minimals s (y ∩ range f) := by
convert (f.inter_preimage_minimals_eq univ y).symm
· simp [univ_inter]
· simp [inter_comm]
theorem RelIso.minimals_preimage_eq (f : r ≃r s) (y : Set β) :
minimals r (f ⁻¹' y) = f ⁻¹' (minimals s y) := by
convert f.toRelEmbedding.minimals_preimage_eq y; simp
theorem RelIso.maximals_preimage_eq (f : r ≃r s) (y : Set β) :
maximals r (f ⁻¹' y) = f ⁻¹' (maximals s y) :=
f.swap.minimals_preimage_eq y
theorem inter_maximals_preimage_inter_eq_of_rel_iff_rel_on
(hf : ∀ ⦃a a'⦄, a ∈ x → a' ∈ x → (r a a' ↔ s (f a) (f a'))) (y : Set β) :
x ∩ f ⁻¹' (maximals s ((f '' x) ∩ y)) = maximals r (x ∩ f ⁻¹' y) := by
apply inter_minimals_preimage_inter_eq_of_rel_iff_rel_on
exact fun _ _ a b ↦ hf b a
theorem inter_preimage_maximals_eq_of_rel_iff_rel_on_of_subset
(hf : ∀ ⦃a a'⦄, a ∈ x → a' ∈ x → (r a a' ↔ s (f a) (f a'))) (hy : y ⊆ f '' x) :
x ∩ f ⁻¹' (maximals s y) = maximals r (x ∩ f ⁻¹' y) := by
apply inter_preimage_minimals_eq_of_rel_iff_rel_on_of_subset _ hy
exact fun _ _ a b ↦ hf b a
theorem RelEmbedding.inter_preimage_maximals_eq (f : r ↪r s) (x : Set α) (y : Set β) :
x ∩ f⁻¹' (maximals s ((f '' x) ∩ y)) = maximals r (x ∩ f ⁻¹' y) :=
inter_minimals_preimage_inter_eq_of_rel_iff_rel_on (by simp [f.map_rel_iff]) y
theorem RelEmbedding.inter_preimage_maximals_eq_of_subset (f : r ↪r s) (h : y ⊆ f '' x) :
x ∩ f ⁻¹' (maximals s y) = maximals r (x ∩ f ⁻¹' y) := by
rw [inter_preimage_maximals_eq_of_rel_iff_rel_on_of_subset _ h]; simp [f.map_rel_iff]
theorem RelEmbedding.maximals_preimage_eq (f : r ↪r s) (y : Set β) :
maximals r (f ⁻¹' y) = f ⁻¹' maximals s (y ∩ range f) := by
convert (f.inter_preimage_maximals_eq univ y).symm
· simp [univ_inter]
· simp [inter_comm]
end Image
section Interval
variable [PartialOrder α] {a b : α}
@[simp] theorem maximals_Iic (a : α) : maximals (· ≤ ·) (Iic a) = {a} :=
Set.ext fun _ ↦ ⟨fun h ↦ h.1.antisymm (h.2 rfl.le h.1),
fun h ↦ ⟨h.trans_le rfl.le, fun _ hba _ ↦ le_trans hba h.symm.le⟩⟩
@[simp] theorem minimals_Ici (a : α) : minimals (· ≤ ·) (Ici a) = {a} :=
maximals_Iic (α := αᵒᵈ) a
theorem maximals_Icc (hab : a ≤ b) : maximals (· ≤ ·) (Icc a b) = {b} :=
Set.ext fun x ↦ ⟨fun h ↦ h.1.2.antisymm (h.2 ⟨hab, rfl.le⟩ h.1.2),
fun (h : x = b) ↦ ⟨⟨hab.trans_eq h.symm, h.le⟩, fun _ hy _ ↦ hy.2.trans_eq h.symm⟩⟩
theorem minimals_Icc (hab : a ≤ b) : minimals (· ≤ ·) (Icc a b) = {a} := by
simp_rw [Icc, and_comm (a := (a ≤ _))]; exact maximals_Icc (α := αᵒᵈ) hab
theorem maximals_Ioc (hab : a < b) : maximals (· ≤ ·) (Ioc a b) = {b} :=
Set.ext fun x ↦ ⟨fun h ↦ h.1.2.antisymm (h.2 ⟨hab, rfl.le⟩ h.1.2),
fun (h : x = b) ↦ ⟨⟨hab.trans_eq h.symm, h.le⟩, fun _ hy _ ↦ hy.2.trans_eq h.symm⟩⟩
| Mathlib/Order/Minimal.lean | 489 | 490 | theorem minimals_Ico (hab : a < b) : minimals (· ≤ ·) (Ico a b) = {a} := by |
simp_rw [Ico, and_comm (a := _ ≤ _)]; exact maximals_Ioc (α := αᵒᵈ) hab
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.LinearAlgebra.Matrix.BilinearForm
import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Vandermonde
import Mathlib.LinearAlgebra.Trace
import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure
import Mathlib.FieldTheory.PrimitiveElement
import Mathlib.FieldTheory.Galois
import Mathlib.RingTheory.PowerBasis
import Mathlib.FieldTheory.Minpoly.MinpolyDiv
#align_import ring_theory.trace from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1"
/-!
# Trace for (finite) ring extensions.
Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`,
the trace of the linear map given by multiplying by `s` gives information about
the roots of the minimal polynomial of `s` over `R`.
## Main definitions
* `Algebra.trace R S x`: the trace of an element `s` of an `R`-algebra `S`
* `Algebra.traceForm R S`: bilinear form sending `x`, `y` to the trace of `x * y`
* `Algebra.traceMatrix R b`: the matrix whose `(i j)`-th element is the trace of `b i * b j`.
* `Algebra.embeddingsMatrix A C b : Matrix κ (B →ₐ[A] C) C` is the matrix whose
`(i, σ)` coefficient is `σ (b i)`.
* `Algebra.embeddingsMatrixReindex A C b e : Matrix κ κ C` is the matrix whose `(i, j)`
coefficient is `σⱼ (b i)`, where `σⱼ : B →ₐ[A] C` is the embedding corresponding to `j : κ`
given by a bijection `e : κ ≃ (B →ₐ[A] C)`.
## Main results
* `trace_algebraMap_of_basis`, `trace_algebraMap`: if `x : K`, then `Tr_{L/K} x = [L : K] x`
* `trace_trace_of_basis`, `trace_trace`: `Tr_{L/K} (Tr_{F/L} x) = Tr_{F/K} x`
* `trace_eq_sum_roots`: the trace of `x : K(x)` is the sum of all conjugate roots of `x`
* `trace_eq_sum_embeddings`: the trace of `x : K(x)` is the sum of all embeddings of `x` into an
algebraically closed field
* `traceForm_nondegenerate`: the trace form over a separable extension is a nondegenerate
bilinear form
* `traceForm_dualBasis_powerBasis_eq`: The dual basis of a powerbasis `{1, x, x²...}` under the
trace form is `aᵢ / f'(x)`, with `f` being the minpoly of `x` and `f / (X - x) = ∑ aᵢxⁱ`.
## Implementation notes
Typically, the trace is defined specifically for finite field extensions.
The definition is as general as possible and the assumption that we have
fields or that the extension is finite is added to the lemmas as needed.
We only define the trace for left multiplication (`Algebra.leftMulMatrix`,
i.e. `LinearMap.mulLeft`).
For now, the definitions assume `S` is commutative, so the choice doesn't matter anyway.
## References
* https://en.wikipedia.org/wiki/Field_trace
-/
universe u v w z
variable {R S T : Type*} [CommRing R] [CommRing S] [CommRing T]
variable [Algebra R S] [Algebra R T]
variable {K L : Type*} [Field K] [Field L] [Algebra K L]
variable {ι κ : Type w} [Fintype ι]
open FiniteDimensional
open LinearMap (BilinForm)
open LinearMap
open Matrix
open scoped Matrix
namespace Algebra
variable (b : Basis ι R S)
variable (R S)
/-- The trace of an element `s` of an `R`-algebra is the trace of `(s * ·)`,
as an `R`-linear map. -/
noncomputable def trace : S →ₗ[R] R :=
(LinearMap.trace R S).comp (lmul R S).toLinearMap
#align algebra.trace Algebra.trace
variable {S}
-- Not a `simp` lemma since there are more interesting ways to rewrite `trace R S x`,
-- for example `trace_trace`
theorem trace_apply (x) : trace R S x = LinearMap.trace R S (lmul R S x) :=
rfl
#align algebra.trace_apply Algebra.trace_apply
theorem trace_eq_zero_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) :
trace R S = 0 := by ext s; simp [trace_apply, LinearMap.trace, h]
#align algebra.trace_eq_zero_of_not_exists_basis Algebra.trace_eq_zero_of_not_exists_basis
variable {R}
-- Can't be a `simp` lemma because it depends on a choice of basis
| Mathlib/RingTheory/Trace.lean | 109 | 111 | theorem trace_eq_matrix_trace [DecidableEq ι] (b : Basis ι R S) (s : S) :
trace R S s = Matrix.trace (Algebra.leftMulMatrix b s) := by |
rw [trace_apply, LinearMap.trace_eq_matrix_trace _ b, ← toMatrix_lmul_eq]; rfl
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Integral.SetToL1
#align_import measure_theory.integral.bochner from "leanprover-community/mathlib"@"48fb5b5280e7c81672afc9524185ae994553ebf4"
/-!
# Bochner integral
The Bochner integral extends the definition of the Lebesgue integral to functions that map from a
measure space into a Banach space (complete normed vector space). It is constructed here by
extending the integral on simple functions.
## Main definitions
The Bochner integral is defined through the extension process described in the file `SetToL1`,
which follows these steps:
1. Define the integral of the indicator of a set. This is `weightedSMul μ s x = (μ s).toReal * x`.
`weightedSMul μ` is shown to be linear in the value `x` and `DominatedFinMeasAdditive`
(defined in the file `SetToL1`) with respect to the set `s`.
2. Define the integral on simple functions of the type `SimpleFunc α E` (notation : `α →ₛ E`)
where `E` is a real normed space. (See `SimpleFunc.integral` for details.)
3. Transfer this definition to define the integral on `L1.simpleFunc α E` (notation :
`α →₁ₛ[μ] E`), see `L1.simpleFunc.integral`. Show that this integral is a continuous linear
map from `α →₁ₛ[μ] E` to `E`.
4. Define the Bochner integral on L1 functions by extending the integral on integrable simple
functions `α →₁ₛ[μ] E` using `ContinuousLinearMap.extend` and the fact that the embedding of
`α →₁ₛ[μ] E` into `α →₁[μ] E` is dense.
5. Define the Bochner integral on functions as the Bochner integral of its equivalence class in L1
space, if it is in L1, and 0 otherwise.
The result of that construction is `∫ a, f a ∂μ`, which is definitionally equal to
`setToFun (dominatedFinMeasAdditive_weightedSMul μ) f`. Some basic properties of the integral
(like linearity) are particular cases of the properties of `setToFun` (which are described in the
file `SetToL1`).
## Main statements
1. Basic properties of the Bochner integral on functions of type `α → E`, where `α` is a measure
space and `E` is a real normed space.
* `integral_zero` : `∫ 0 ∂μ = 0`
* `integral_add` : `∫ x, f x + g x ∂μ = ∫ x, f ∂μ + ∫ x, g x ∂μ`
* `integral_neg` : `∫ x, - f x ∂μ = - ∫ x, f x ∂μ`
* `integral_sub` : `∫ x, f x - g x ∂μ = ∫ x, f x ∂μ - ∫ x, g x ∂μ`
* `integral_smul` : `∫ x, r • f x ∂μ = r • ∫ x, f x ∂μ`
* `integral_congr_ae` : `f =ᵐ[μ] g → ∫ x, f x ∂μ = ∫ x, g x ∂μ`
* `norm_integral_le_integral_norm` : `‖∫ x, f x ∂μ‖ ≤ ∫ x, ‖f x‖ ∂μ`
2. Basic properties of the Bochner integral on functions of type `α → ℝ`, where `α` is a measure
space.
* `integral_nonneg_of_ae` : `0 ≤ᵐ[μ] f → 0 ≤ ∫ x, f x ∂μ`
* `integral_nonpos_of_ae` : `f ≤ᵐ[μ] 0 → ∫ x, f x ∂μ ≤ 0`
* `integral_mono_ae` : `f ≤ᵐ[μ] g → ∫ x, f x ∂μ ≤ ∫ x, g x ∂μ`
* `integral_nonneg` : `0 ≤ f → 0 ≤ ∫ x, f x ∂μ`
* `integral_nonpos` : `f ≤ 0 → ∫ x, f x ∂μ ≤ 0`
* `integral_mono` : `f ≤ᵐ[μ] g → ∫ x, f x ∂μ ≤ ∫ x, g x ∂μ`
3. Propositions connecting the Bochner integral with the integral on `ℝ≥0∞`-valued functions,
which is called `lintegral` and has the notation `∫⁻`.
* `integral_eq_lintegral_pos_part_sub_lintegral_neg_part` :
`∫ x, f x ∂μ = ∫⁻ x, f⁺ x ∂μ - ∫⁻ x, f⁻ x ∂μ`,
where `f⁺` is the positive part of `f` and `f⁻` is the negative part of `f`.
* `integral_eq_lintegral_of_nonneg_ae` : `0 ≤ᵐ[μ] f → ∫ x, f x ∂μ = ∫⁻ x, f x ∂μ`
4. (In the file `DominatedConvergence`)
`tendsto_integral_of_dominated_convergence` : the Lebesgue dominated convergence theorem
5. (In the file `SetIntegral`) integration commutes with continuous linear maps.
* `ContinuousLinearMap.integral_comp_comm`
* `LinearIsometry.integral_comp_comm`
## Notes
Some tips on how to prove a proposition if the API for the Bochner integral is not enough so that
you need to unfold the definition of the Bochner integral and go back to simple functions.
One method is to use the theorem `Integrable.induction` in the file `SimpleFuncDenseLp` (or one
of the related results, like `Lp.induction` for functions in `Lp`), which allows you to prove
something for an arbitrary integrable function.
Another method is using the following steps.
See `integral_eq_lintegral_pos_part_sub_lintegral_neg_part` for a complicated example, which proves
that `∫ f = ∫⁻ f⁺ - ∫⁻ f⁻`, with the first integral sign being the Bochner integral of a real-valued
function `f : α → ℝ`, and second and third integral sign being the integral on `ℝ≥0∞`-valued
functions (called `lintegral`). The proof of `integral_eq_lintegral_pos_part_sub_lintegral_neg_part`
is scattered in sections with the name `posPart`.
Here are the usual steps of proving that a property `p`, say `∫ f = ∫⁻ f⁺ - ∫⁻ f⁻`, holds for all
functions :
1. First go to the `L¹` space.
For example, if you see `ENNReal.toReal (∫⁻ a, ENNReal.ofReal <| ‖f a‖)`, that is the norm of
`f` in `L¹` space. Rewrite using `L1.norm_of_fun_eq_lintegral_norm`.
2. Show that the set `{f ∈ L¹ | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻}` is closed in `L¹` using `isClosed_eq`.
3. Show that the property holds for all simple functions `s` in `L¹` space.
Typically, you need to convert various notions to their `SimpleFunc` counterpart, using lemmas
like `L1.integral_coe_eq_integral`.
4. Since simple functions are dense in `L¹`,
```
univ = closure {s simple}
= closure {s simple | ∫ s = ∫⁻ s⁺ - ∫⁻ s⁻} : the property holds for all simple functions
⊆ closure {f | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻}
= {f | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻} : closure of a closed set is itself
```
Use `isClosed_property` or `DenseRange.induction_on` for this argument.
## Notations
* `α →ₛ E` : simple functions (defined in `MeasureTheory/Integration`)
* `α →₁[μ] E` : functions in L1 space, i.e., equivalence classes of integrable functions (defined in
`MeasureTheory/LpSpace`)
* `α →₁ₛ[μ] E` : simple functions in L1 space, i.e., equivalence classes of integrable simple
functions (defined in `MeasureTheory/SimpleFuncDense`)
* `∫ a, f a ∂μ` : integral of `f` with respect to a measure `μ`
* `∫ a, f a` : integral of `f` with respect to `volume`, the default measure on the ambient type
We also define notations for integral on a set, which are described in the file
`MeasureTheory/SetIntegral`.
Note : `ₛ` is typed using `\_s`. Sometimes it shows as a box if the font is missing.
## Tags
Bochner integral, simple function, function space, Lebesgue dominated convergence theorem
-/
assert_not_exists Differentiable
noncomputable section
open scoped Topology NNReal ENNReal MeasureTheory
open Set Filter TopologicalSpace ENNReal EMetric
namespace MeasureTheory
variable {α E F 𝕜 : Type*}
section WeightedSMul
open ContinuousLinearMap
variable [NormedAddCommGroup F] [NormedSpace ℝ F] {m : MeasurableSpace α} {μ : Measure α}
/-- Given a set `s`, return the continuous linear map `fun x => (μ s).toReal • x`. The extension
of that set function through `setToL1` gives the Bochner integral of L1 functions. -/
def weightedSMul {_ : MeasurableSpace α} (μ : Measure α) (s : Set α) : F →L[ℝ] F :=
(μ s).toReal • ContinuousLinearMap.id ℝ F
#align measure_theory.weighted_smul MeasureTheory.weightedSMul
theorem weightedSMul_apply {m : MeasurableSpace α} (μ : Measure α) (s : Set α) (x : F) :
weightedSMul μ s x = (μ s).toReal • x := by simp [weightedSMul]
#align measure_theory.weighted_smul_apply MeasureTheory.weightedSMul_apply
@[simp]
theorem weightedSMul_zero_measure {m : MeasurableSpace α} :
weightedSMul (0 : Measure α) = (0 : Set α → F →L[ℝ] F) := by ext1; simp [weightedSMul]
#align measure_theory.weighted_smul_zero_measure MeasureTheory.weightedSMul_zero_measure
@[simp]
theorem weightedSMul_empty {m : MeasurableSpace α} (μ : Measure α) :
weightedSMul μ ∅ = (0 : F →L[ℝ] F) := by ext1 x; rw [weightedSMul_apply]; simp
#align measure_theory.weighted_smul_empty MeasureTheory.weightedSMul_empty
theorem weightedSMul_add_measure {m : MeasurableSpace α} (μ ν : Measure α) {s : Set α}
(hμs : μ s ≠ ∞) (hνs : ν s ≠ ∞) :
(weightedSMul (μ + ν) s : F →L[ℝ] F) = weightedSMul μ s + weightedSMul ν s := by
ext1 x
push_cast
simp_rw [Pi.add_apply, weightedSMul_apply]
push_cast
rw [Pi.add_apply, ENNReal.toReal_add hμs hνs, add_smul]
#align measure_theory.weighted_smul_add_measure MeasureTheory.weightedSMul_add_measure
theorem weightedSMul_smul_measure {m : MeasurableSpace α} (μ : Measure α) (c : ℝ≥0∞) {s : Set α} :
(weightedSMul (c • μ) s : F →L[ℝ] F) = c.toReal • weightedSMul μ s := by
ext1 x
push_cast
simp_rw [Pi.smul_apply, weightedSMul_apply]
push_cast
simp_rw [Pi.smul_apply, smul_eq_mul, toReal_mul, smul_smul]
#align measure_theory.weighted_smul_smul_measure MeasureTheory.weightedSMul_smul_measure
theorem weightedSMul_congr (s t : Set α) (hst : μ s = μ t) :
(weightedSMul μ s : F →L[ℝ] F) = weightedSMul μ t := by
ext1 x; simp_rw [weightedSMul_apply]; congr 2
#align measure_theory.weighted_smul_congr MeasureTheory.weightedSMul_congr
theorem weightedSMul_null {s : Set α} (h_zero : μ s = 0) : (weightedSMul μ s : F →L[ℝ] F) = 0 := by
ext1 x; rw [weightedSMul_apply, h_zero]; simp
#align measure_theory.weighted_smul_null MeasureTheory.weightedSMul_null
theorem weightedSMul_union' (s t : Set α) (ht : MeasurableSet t) (hs_finite : μ s ≠ ∞)
(ht_finite : μ t ≠ ∞) (h_inter : s ∩ t = ∅) :
(weightedSMul μ (s ∪ t) : F →L[ℝ] F) = weightedSMul μ s + weightedSMul μ t := by
ext1 x
simp_rw [add_apply, weightedSMul_apply,
measure_union (Set.disjoint_iff_inter_eq_empty.mpr h_inter) ht,
ENNReal.toReal_add hs_finite ht_finite, add_smul]
#align measure_theory.weighted_smul_union' MeasureTheory.weightedSMul_union'
@[nolint unusedArguments]
theorem weightedSMul_union (s t : Set α) (_hs : MeasurableSet s) (ht : MeasurableSet t)
(hs_finite : μ s ≠ ∞) (ht_finite : μ t ≠ ∞) (h_inter : s ∩ t = ∅) :
(weightedSMul μ (s ∪ t) : F →L[ℝ] F) = weightedSMul μ s + weightedSMul μ t :=
weightedSMul_union' s t ht hs_finite ht_finite h_inter
#align measure_theory.weighted_smul_union MeasureTheory.weightedSMul_union
theorem weightedSMul_smul [NormedField 𝕜] [NormedSpace 𝕜 F] [SMulCommClass ℝ 𝕜 F] (c : 𝕜)
(s : Set α) (x : F) : weightedSMul μ s (c • x) = c • weightedSMul μ s x := by
simp_rw [weightedSMul_apply, smul_comm]
#align measure_theory.weighted_smul_smul MeasureTheory.weightedSMul_smul
theorem norm_weightedSMul_le (s : Set α) : ‖(weightedSMul μ s : F →L[ℝ] F)‖ ≤ (μ s).toReal :=
calc
‖(weightedSMul μ s : F →L[ℝ] F)‖ = ‖(μ s).toReal‖ * ‖ContinuousLinearMap.id ℝ F‖ :=
norm_smul (μ s).toReal (ContinuousLinearMap.id ℝ F)
_ ≤ ‖(μ s).toReal‖ :=
((mul_le_mul_of_nonneg_left norm_id_le (norm_nonneg _)).trans (mul_one _).le)
_ = abs (μ s).toReal := Real.norm_eq_abs _
_ = (μ s).toReal := abs_eq_self.mpr ENNReal.toReal_nonneg
#align measure_theory.norm_weighted_smul_le MeasureTheory.norm_weightedSMul_le
theorem dominatedFinMeasAdditive_weightedSMul {_ : MeasurableSpace α} (μ : Measure α) :
DominatedFinMeasAdditive μ (weightedSMul μ : Set α → F →L[ℝ] F) 1 :=
⟨weightedSMul_union, fun s _ _ => (norm_weightedSMul_le s).trans (one_mul _).symm.le⟩
#align measure_theory.dominated_fin_meas_additive_weighted_smul MeasureTheory.dominatedFinMeasAdditive_weightedSMul
theorem weightedSMul_nonneg (s : Set α) (x : ℝ) (hx : 0 ≤ x) : 0 ≤ weightedSMul μ s x := by
simp only [weightedSMul, Algebra.id.smul_eq_mul, coe_smul', _root_.id, coe_id', Pi.smul_apply]
exact mul_nonneg toReal_nonneg hx
#align measure_theory.weighted_smul_nonneg MeasureTheory.weightedSMul_nonneg
end WeightedSMul
local infixr:25 " →ₛ " => SimpleFunc
namespace SimpleFunc
section PosPart
variable [LinearOrder E] [Zero E] [MeasurableSpace α]
/-- Positive part of a simple function. -/
def posPart (f : α →ₛ E) : α →ₛ E :=
f.map fun b => max b 0
#align measure_theory.simple_func.pos_part MeasureTheory.SimpleFunc.posPart
/-- Negative part of a simple function. -/
def negPart [Neg E] (f : α →ₛ E) : α →ₛ E :=
posPart (-f)
#align measure_theory.simple_func.neg_part MeasureTheory.SimpleFunc.negPart
theorem posPart_map_norm (f : α →ₛ ℝ) : (posPart f).map norm = posPart f := by
ext; rw [map_apply, Real.norm_eq_abs, abs_of_nonneg]; exact le_max_right _ _
#align measure_theory.simple_func.pos_part_map_norm MeasureTheory.SimpleFunc.posPart_map_norm
theorem negPart_map_norm (f : α →ₛ ℝ) : (negPart f).map norm = negPart f := by
rw [negPart]; exact posPart_map_norm _
#align measure_theory.simple_func.neg_part_map_norm MeasureTheory.SimpleFunc.negPart_map_norm
theorem posPart_sub_negPart (f : α →ₛ ℝ) : f.posPart - f.negPart = f := by
simp only [posPart, negPart]
ext a
rw [coe_sub]
exact max_zero_sub_eq_self (f a)
#align measure_theory.simple_func.pos_part_sub_neg_part MeasureTheory.SimpleFunc.posPart_sub_negPart
end PosPart
section Integral
/-!
### The Bochner integral of simple functions
Define the Bochner integral of simple functions of the type `α →ₛ β` where `β` is a normed group,
and prove basic property of this integral.
-/
open Finset
variable [NormedAddCommGroup E] [NormedAddCommGroup F] [NormedSpace ℝ F] {p : ℝ≥0∞} {G F' : Type*}
[NormedAddCommGroup G] [NormedAddCommGroup F'] [NormedSpace ℝ F'] {m : MeasurableSpace α}
{μ : Measure α}
/-- Bochner integral of simple functions whose codomain is a real `NormedSpace`.
This is equal to `∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal • x` (see `integral_eq`). -/
def integral {_ : MeasurableSpace α} (μ : Measure α) (f : α →ₛ F) : F :=
f.setToSimpleFunc (weightedSMul μ)
#align measure_theory.simple_func.integral MeasureTheory.SimpleFunc.integral
theorem integral_def {_ : MeasurableSpace α} (μ : Measure α) (f : α →ₛ F) :
f.integral μ = f.setToSimpleFunc (weightedSMul μ) := rfl
#align measure_theory.simple_func.integral_def MeasureTheory.SimpleFunc.integral_def
theorem integral_eq {m : MeasurableSpace α} (μ : Measure α) (f : α →ₛ F) :
f.integral μ = ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal • x := by
simp [integral, setToSimpleFunc, weightedSMul_apply]
#align measure_theory.simple_func.integral_eq MeasureTheory.SimpleFunc.integral_eq
theorem integral_eq_sum_filter [DecidablePred fun x : F => x ≠ 0] {m : MeasurableSpace α}
(f : α →ₛ F) (μ : Measure α) :
f.integral μ = ∑ x ∈ f.range.filter fun x => x ≠ 0, (μ (f ⁻¹' {x})).toReal • x := by
rw [integral_def, setToSimpleFunc_eq_sum_filter]; simp_rw [weightedSMul_apply]; congr
#align measure_theory.simple_func.integral_eq_sum_filter MeasureTheory.SimpleFunc.integral_eq_sum_filter
/-- The Bochner integral is equal to a sum over any set that includes `f.range` (except `0`). -/
theorem integral_eq_sum_of_subset [DecidablePred fun x : F => x ≠ 0] {f : α →ₛ F} {s : Finset F}
(hs : (f.range.filter fun x => x ≠ 0) ⊆ s) :
f.integral μ = ∑ x ∈ s, (μ (f ⁻¹' {x})).toReal • x := by
rw [SimpleFunc.integral_eq_sum_filter, Finset.sum_subset hs]
rintro x - hx; rw [Finset.mem_filter, not_and_or, Ne, Classical.not_not] at hx
-- Porting note: reordered for clarity
rcases hx.symm with (rfl | hx)
· simp
rw [SimpleFunc.mem_range] at hx
-- Porting note: added
simp only [Set.mem_range, not_exists] at hx
rw [preimage_eq_empty] <;> simp [Set.disjoint_singleton_left, hx]
#align measure_theory.simple_func.integral_eq_sum_of_subset MeasureTheory.SimpleFunc.integral_eq_sum_of_subset
@[simp]
theorem integral_const {m : MeasurableSpace α} (μ : Measure α) (y : F) :
(const α y).integral μ = (μ univ).toReal • y := by
classical
calc
(const α y).integral μ = ∑ z ∈ {y}, (μ (const α y ⁻¹' {z})).toReal • z :=
integral_eq_sum_of_subset <| (filter_subset _ _).trans (range_const_subset _ _)
_ = (μ univ).toReal • y := by simp [Set.preimage] -- Porting note: added `Set.preimage`
#align measure_theory.simple_func.integral_const MeasureTheory.SimpleFunc.integral_const
@[simp]
theorem integral_piecewise_zero {m : MeasurableSpace α} (f : α →ₛ F) (μ : Measure α) {s : Set α}
(hs : MeasurableSet s) : (piecewise s hs f 0).integral μ = f.integral (μ.restrict s) := by
classical
refine (integral_eq_sum_of_subset ?_).trans
((sum_congr rfl fun y hy => ?_).trans (integral_eq_sum_filter _ _).symm)
· intro y hy
simp only [mem_filter, mem_range, coe_piecewise, coe_zero, piecewise_eq_indicator,
mem_range_indicator] at *
rcases hy with ⟨⟨rfl, -⟩ | ⟨x, -, rfl⟩, h₀⟩
exacts [(h₀ rfl).elim, ⟨Set.mem_range_self _, h₀⟩]
· dsimp
rw [Set.piecewise_eq_indicator, indicator_preimage_of_not_mem,
Measure.restrict_apply (f.measurableSet_preimage _)]
exact fun h₀ => (mem_filter.1 hy).2 (Eq.symm h₀)
#align measure_theory.simple_func.integral_piecewise_zero MeasureTheory.SimpleFunc.integral_piecewise_zero
/-- Calculate the integral of `g ∘ f : α →ₛ F`, where `f` is an integrable function from `α` to `E`
and `g` is a function from `E` to `F`. We require `g 0 = 0` so that `g ∘ f` is integrable. -/
theorem map_integral (f : α →ₛ E) (g : E → F) (hf : Integrable f μ) (hg : g 0 = 0) :
(f.map g).integral μ = ∑ x ∈ f.range, ENNReal.toReal (μ (f ⁻¹' {x})) • g x :=
map_setToSimpleFunc _ weightedSMul_union hf hg
#align measure_theory.simple_func.map_integral MeasureTheory.SimpleFunc.map_integral
/-- `SimpleFunc.integral` and `SimpleFunc.lintegral` agree when the integrand has type
`α →ₛ ℝ≥0∞`. But since `ℝ≥0∞` is not a `NormedSpace`, we need some form of coercion.
See `integral_eq_lintegral` for a simpler version. -/
theorem integral_eq_lintegral' {f : α →ₛ E} {g : E → ℝ≥0∞} (hf : Integrable f μ) (hg0 : g 0 = 0)
(ht : ∀ b, g b ≠ ∞) :
(f.map (ENNReal.toReal ∘ g)).integral μ = ENNReal.toReal (∫⁻ a, g (f a) ∂μ) := by
have hf' : f.FinMeasSupp μ := integrable_iff_finMeasSupp.1 hf
simp only [← map_apply g f, lintegral_eq_lintegral]
rw [map_integral f _ hf, map_lintegral, ENNReal.toReal_sum]
· refine Finset.sum_congr rfl fun b _ => ?_
-- Porting note: added `Function.comp_apply`
rw [smul_eq_mul, toReal_mul, mul_comm, Function.comp_apply]
· rintro a -
by_cases a0 : a = 0
· rw [a0, hg0, zero_mul]; exact WithTop.zero_ne_top
· apply mul_ne_top (ht a) (hf'.meas_preimage_singleton_ne_zero a0).ne
· simp [hg0]
#align measure_theory.simple_func.integral_eq_lintegral' MeasureTheory.SimpleFunc.integral_eq_lintegral'
variable [NormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace ℝ E] [SMulCommClass ℝ 𝕜 E]
theorem integral_congr {f g : α →ₛ E} (hf : Integrable f μ) (h : f =ᵐ[μ] g) :
f.integral μ = g.integral μ :=
setToSimpleFunc_congr (weightedSMul μ) (fun _ _ => weightedSMul_null) weightedSMul_union hf h
#align measure_theory.simple_func.integral_congr MeasureTheory.SimpleFunc.integral_congr
/-- `SimpleFunc.bintegral` and `SimpleFunc.integral` agree when the integrand has type
`α →ₛ ℝ≥0∞`. But since `ℝ≥0∞` is not a `NormedSpace`, we need some form of coercion. -/
theorem integral_eq_lintegral {f : α →ₛ ℝ} (hf : Integrable f μ) (h_pos : 0 ≤ᵐ[μ] f) :
f.integral μ = ENNReal.toReal (∫⁻ a, ENNReal.ofReal (f a) ∂μ) := by
have : f =ᵐ[μ] f.map (ENNReal.toReal ∘ ENNReal.ofReal) :=
h_pos.mono fun a h => (ENNReal.toReal_ofReal h).symm
rw [← integral_eq_lintegral' hf]
exacts [integral_congr hf this, ENNReal.ofReal_zero, fun b => ENNReal.ofReal_ne_top]
#align measure_theory.simple_func.integral_eq_lintegral MeasureTheory.SimpleFunc.integral_eq_lintegral
theorem integral_add {f g : α →ₛ E} (hf : Integrable f μ) (hg : Integrable g μ) :
integral μ (f + g) = integral μ f + integral μ g :=
setToSimpleFunc_add _ weightedSMul_union hf hg
#align measure_theory.simple_func.integral_add MeasureTheory.SimpleFunc.integral_add
theorem integral_neg {f : α →ₛ E} (hf : Integrable f μ) : integral μ (-f) = -integral μ f :=
setToSimpleFunc_neg _ weightedSMul_union hf
#align measure_theory.simple_func.integral_neg MeasureTheory.SimpleFunc.integral_neg
theorem integral_sub {f g : α →ₛ E} (hf : Integrable f μ) (hg : Integrable g μ) :
integral μ (f - g) = integral μ f - integral μ g :=
setToSimpleFunc_sub _ weightedSMul_union hf hg
#align measure_theory.simple_func.integral_sub MeasureTheory.SimpleFunc.integral_sub
theorem integral_smul (c : 𝕜) {f : α →ₛ E} (hf : Integrable f μ) :
integral μ (c • f) = c • integral μ f :=
setToSimpleFunc_smul _ weightedSMul_union weightedSMul_smul c hf
#align measure_theory.simple_func.integral_smul MeasureTheory.SimpleFunc.integral_smul
theorem norm_setToSimpleFunc_le_integral_norm (T : Set α → E →L[ℝ] F) {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal) {f : α →ₛ E}
(hf : Integrable f μ) : ‖f.setToSimpleFunc T‖ ≤ C * (f.map norm).integral μ :=
calc
‖f.setToSimpleFunc T‖ ≤ C * ∑ x ∈ f.range, ENNReal.toReal (μ (f ⁻¹' {x})) * ‖x‖ :=
norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm f hf
_ = C * (f.map norm).integral μ := by
rw [map_integral f norm hf norm_zero]; simp_rw [smul_eq_mul]
#align measure_theory.simple_func.norm_set_to_simple_func_le_integral_norm MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_integral_norm
theorem norm_integral_le_integral_norm (f : α →ₛ E) (hf : Integrable f μ) :
‖f.integral μ‖ ≤ (f.map norm).integral μ := by
refine (norm_setToSimpleFunc_le_integral_norm _ (fun s _ _ => ?_) hf).trans (one_mul _).le
exact (norm_weightedSMul_le s).trans (one_mul _).symm.le
#align measure_theory.simple_func.norm_integral_le_integral_norm MeasureTheory.SimpleFunc.norm_integral_le_integral_norm
theorem integral_add_measure {ν} (f : α →ₛ E) (hf : Integrable f (μ + ν)) :
f.integral (μ + ν) = f.integral μ + f.integral ν := by
simp_rw [integral_def]
refine setToSimpleFunc_add_left'
(weightedSMul μ) (weightedSMul ν) (weightedSMul (μ + ν)) (fun s _ hμνs => ?_) hf
rw [lt_top_iff_ne_top, Measure.coe_add, Pi.add_apply, ENNReal.add_ne_top] at hμνs
rw [weightedSMul_add_measure _ _ hμνs.1 hμνs.2]
#align measure_theory.simple_func.integral_add_measure MeasureTheory.SimpleFunc.integral_add_measure
end Integral
end SimpleFunc
namespace L1
set_option linter.uppercaseLean3 false -- `L1`
open AEEqFun Lp.simpleFunc Lp
variable [NormedAddCommGroup E] [NormedAddCommGroup F] {m : MeasurableSpace α} {μ : Measure α}
namespace SimpleFunc
theorem norm_eq_integral (f : α →₁ₛ[μ] E) : ‖f‖ = ((toSimpleFunc f).map norm).integral μ := by
rw [norm_eq_sum_mul f, (toSimpleFunc f).map_integral norm (SimpleFunc.integrable f) norm_zero]
simp_rw [smul_eq_mul]
#align measure_theory.L1.simple_func.norm_eq_integral MeasureTheory.L1.SimpleFunc.norm_eq_integral
section PosPart
/-- Positive part of a simple function in L1 space. -/
nonrec def posPart (f : α →₁ₛ[μ] ℝ) : α →₁ₛ[μ] ℝ :=
⟨Lp.posPart (f : α →₁[μ] ℝ), by
rcases f with ⟨f, s, hsf⟩
use s.posPart
simp only [Subtype.coe_mk, Lp.coe_posPart, ← hsf, AEEqFun.posPart_mk,
SimpleFunc.coe_map, mk_eq_mk]
-- Porting note: added
simp [SimpleFunc.posPart, Function.comp, EventuallyEq.rfl] ⟩
#align measure_theory.L1.simple_func.pos_part MeasureTheory.L1.SimpleFunc.posPart
/-- Negative part of a simple function in L1 space. -/
def negPart (f : α →₁ₛ[μ] ℝ) : α →₁ₛ[μ] ℝ :=
posPart (-f)
#align measure_theory.L1.simple_func.neg_part MeasureTheory.L1.SimpleFunc.negPart
@[norm_cast]
theorem coe_posPart (f : α →₁ₛ[μ] ℝ) : (posPart f : α →₁[μ] ℝ) = Lp.posPart (f : α →₁[μ] ℝ) := rfl
#align measure_theory.L1.simple_func.coe_pos_part MeasureTheory.L1.SimpleFunc.coe_posPart
@[norm_cast]
theorem coe_negPart (f : α →₁ₛ[μ] ℝ) : (negPart f : α →₁[μ] ℝ) = Lp.negPart (f : α →₁[μ] ℝ) := rfl
#align measure_theory.L1.simple_func.coe_neg_part MeasureTheory.L1.SimpleFunc.coe_negPart
end PosPart
section SimpleFuncIntegral
/-!
### The Bochner integral of `L1`
Define the Bochner integral on `α →₁ₛ[μ] E` by extension from the simple functions `α →₁ₛ[μ] E`,
and prove basic properties of this integral. -/
variable [NormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace ℝ E] [SMulCommClass ℝ 𝕜 E] {F' : Type*}
[NormedAddCommGroup F'] [NormedSpace ℝ F']
attribute [local instance] simpleFunc.normedSpace
/-- The Bochner integral over simple functions in L1 space. -/
def integral (f : α →₁ₛ[μ] E) : E :=
(toSimpleFunc f).integral μ
#align measure_theory.L1.simple_func.integral MeasureTheory.L1.SimpleFunc.integral
theorem integral_eq_integral (f : α →₁ₛ[μ] E) : integral f = (toSimpleFunc f).integral μ := rfl
#align measure_theory.L1.simple_func.integral_eq_integral MeasureTheory.L1.SimpleFunc.integral_eq_integral
nonrec theorem integral_eq_lintegral {f : α →₁ₛ[μ] ℝ} (h_pos : 0 ≤ᵐ[μ] toSimpleFunc f) :
integral f = ENNReal.toReal (∫⁻ a, ENNReal.ofReal ((toSimpleFunc f) a) ∂μ) := by
rw [integral, SimpleFunc.integral_eq_lintegral (SimpleFunc.integrable f) h_pos]
#align measure_theory.L1.simple_func.integral_eq_lintegral MeasureTheory.L1.SimpleFunc.integral_eq_lintegral
theorem integral_eq_setToL1S (f : α →₁ₛ[μ] E) : integral f = setToL1S (weightedSMul μ) f := rfl
#align measure_theory.L1.simple_func.integral_eq_set_to_L1s MeasureTheory.L1.SimpleFunc.integral_eq_setToL1S
nonrec theorem integral_congr {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) :
integral f = integral g :=
SimpleFunc.integral_congr (SimpleFunc.integrable f) h
#align measure_theory.L1.simple_func.integral_congr MeasureTheory.L1.SimpleFunc.integral_congr
theorem integral_add (f g : α →₁ₛ[μ] E) : integral (f + g) = integral f + integral g :=
setToL1S_add _ (fun _ _ => weightedSMul_null) weightedSMul_union _ _
#align measure_theory.L1.simple_func.integral_add MeasureTheory.L1.SimpleFunc.integral_add
theorem integral_smul (c : 𝕜) (f : α →₁ₛ[μ] E) : integral (c • f) = c • integral f :=
setToL1S_smul _ (fun _ _ => weightedSMul_null) weightedSMul_union weightedSMul_smul c f
#align measure_theory.L1.simple_func.integral_smul MeasureTheory.L1.SimpleFunc.integral_smul
theorem norm_integral_le_norm (f : α →₁ₛ[μ] E) : ‖integral f‖ ≤ ‖f‖ := by
rw [integral, norm_eq_integral]
exact (toSimpleFunc f).norm_integral_le_integral_norm (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.norm_integral_le_norm MeasureTheory.L1.SimpleFunc.norm_integral_le_norm
variable {E' : Type*} [NormedAddCommGroup E'] [NormedSpace ℝ E'] [NormedSpace 𝕜 E']
variable (α E μ 𝕜)
/-- The Bochner integral over simple functions in L1 space as a continuous linear map. -/
def integralCLM' : (α →₁ₛ[μ] E) →L[𝕜] E :=
LinearMap.mkContinuous ⟨⟨integral, integral_add⟩, integral_smul⟩ 1 fun f =>
le_trans (norm_integral_le_norm _) <| by rw [one_mul]
#align measure_theory.L1.simple_func.integral_clm' MeasureTheory.L1.SimpleFunc.integralCLM'
/-- The Bochner integral over simple functions in L1 space as a continuous linear map over ℝ. -/
def integralCLM : (α →₁ₛ[μ] E) →L[ℝ] E :=
integralCLM' α E ℝ μ
#align measure_theory.L1.simple_func.integral_clm MeasureTheory.L1.SimpleFunc.integralCLM
variable {α E μ 𝕜}
local notation "Integral" => integralCLM α E μ
open ContinuousLinearMap
theorem norm_Integral_le_one : ‖Integral‖ ≤ 1 :=
-- Porting note: Old proof was `LinearMap.mkContinuous_norm_le _ zero_le_one _`
LinearMap.mkContinuous_norm_le _ zero_le_one (fun f => by
rw [one_mul]
exact norm_integral_le_norm f)
#align measure_theory.L1.simple_func.norm_Integral_le_one MeasureTheory.L1.SimpleFunc.norm_Integral_le_one
section PosPart
theorem posPart_toSimpleFunc (f : α →₁ₛ[μ] ℝ) :
toSimpleFunc (posPart f) =ᵐ[μ] (toSimpleFunc f).posPart := by
have eq : ∀ a, (toSimpleFunc f).posPart a = max ((toSimpleFunc f) a) 0 := fun a => rfl
have ae_eq : ∀ᵐ a ∂μ, toSimpleFunc (posPart f) a = max ((toSimpleFunc f) a) 0 := by
filter_upwards [toSimpleFunc_eq_toFun (posPart f), Lp.coeFn_posPart (f : α →₁[μ] ℝ),
toSimpleFunc_eq_toFun f] with _ _ h₂ h₃
convert h₂ using 1
-- Porting note: added
rw [h₃]
refine ae_eq.mono fun a h => ?_
rw [h, eq]
#align measure_theory.L1.simple_func.pos_part_to_simple_func MeasureTheory.L1.SimpleFunc.posPart_toSimpleFunc
theorem negPart_toSimpleFunc (f : α →₁ₛ[μ] ℝ) :
toSimpleFunc (negPart f) =ᵐ[μ] (toSimpleFunc f).negPart := by
rw [SimpleFunc.negPart, MeasureTheory.SimpleFunc.negPart]
filter_upwards [posPart_toSimpleFunc (-f), neg_toSimpleFunc f]
intro a h₁ h₂
rw [h₁]
show max _ _ = max _ _
rw [h₂]
rfl
#align measure_theory.L1.simple_func.neg_part_to_simple_func MeasureTheory.L1.SimpleFunc.negPart_toSimpleFunc
theorem integral_eq_norm_posPart_sub (f : α →₁ₛ[μ] ℝ) : integral f = ‖posPart f‖ - ‖negPart f‖ := by
-- Convert things in `L¹` to their `SimpleFunc` counterpart
have ae_eq₁ : (toSimpleFunc f).posPart =ᵐ[μ] (toSimpleFunc (posPart f)).map norm := by
filter_upwards [posPart_toSimpleFunc f] with _ h
rw [SimpleFunc.map_apply, h]
conv_lhs => rw [← SimpleFunc.posPart_map_norm, SimpleFunc.map_apply]
-- Convert things in `L¹` to their `SimpleFunc` counterpart
have ae_eq₂ : (toSimpleFunc f).negPart =ᵐ[μ] (toSimpleFunc (negPart f)).map norm := by
filter_upwards [negPart_toSimpleFunc f] with _ h
rw [SimpleFunc.map_apply, h]
conv_lhs => rw [← SimpleFunc.negPart_map_norm, SimpleFunc.map_apply]
rw [integral, norm_eq_integral, norm_eq_integral, ← SimpleFunc.integral_sub]
· show (toSimpleFunc f).integral μ =
((toSimpleFunc (posPart f)).map norm - (toSimpleFunc (negPart f)).map norm).integral μ
apply MeasureTheory.SimpleFunc.integral_congr (SimpleFunc.integrable f)
filter_upwards [ae_eq₁, ae_eq₂] with _ h₁ h₂
show _ = _ - _
rw [← h₁, ← h₂]
have := (toSimpleFunc f).posPart_sub_negPart
conv_lhs => rw [← this]
rfl
· exact (SimpleFunc.integrable f).pos_part.congr ae_eq₁
· exact (SimpleFunc.integrable f).neg_part.congr ae_eq₂
#align measure_theory.L1.simple_func.integral_eq_norm_pos_part_sub MeasureTheory.L1.SimpleFunc.integral_eq_norm_posPart_sub
end PosPart
end SimpleFuncIntegral
end SimpleFunc
open SimpleFunc
local notation "Integral" => @integralCLM α E _ _ _ _ _ μ _
variable [NormedSpace ℝ E] [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [SMulCommClass ℝ 𝕜 E]
[NormedSpace ℝ F] [CompleteSpace E]
section IntegrationInL1
attribute [local instance] simpleFunc.normedSpace
open ContinuousLinearMap
variable (𝕜)
/-- The Bochner integral in L1 space as a continuous linear map. -/
nonrec def integralCLM' : (α →₁[μ] E) →L[𝕜] E :=
(integralCLM' α E 𝕜 μ).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top)
simpleFunc.uniformInducing
#align measure_theory.L1.integral_clm' MeasureTheory.L1.integralCLM'
variable {𝕜}
/-- The Bochner integral in L1 space as a continuous linear map over ℝ. -/
def integralCLM : (α →₁[μ] E) →L[ℝ] E :=
integralCLM' ℝ
#align measure_theory.L1.integral_clm MeasureTheory.L1.integralCLM
-- Porting note: added `(E := E)` in several places below.
/-- The Bochner integral in L1 space -/
irreducible_def integral (f : α →₁[μ] E) : E :=
integralCLM (E := E) f
#align measure_theory.L1.integral MeasureTheory.L1.integral
theorem integral_eq (f : α →₁[μ] E) : integral f = integralCLM (E := E) f := by
simp only [integral]
#align measure_theory.L1.integral_eq MeasureTheory.L1.integral_eq
theorem integral_eq_setToL1 (f : α →₁[μ] E) :
integral f = setToL1 (E := E) (dominatedFinMeasAdditive_weightedSMul μ) f := by
simp only [integral]; rfl
#align measure_theory.L1.integral_eq_set_to_L1 MeasureTheory.L1.integral_eq_setToL1
@[norm_cast]
theorem SimpleFunc.integral_L1_eq_integral (f : α →₁ₛ[μ] E) :
L1.integral (f : α →₁[μ] E) = SimpleFunc.integral f := by
simp only [integral, L1.integral]
exact setToL1_eq_setToL1SCLM (dominatedFinMeasAdditive_weightedSMul μ) f
#align measure_theory.L1.simple_func.integral_L1_eq_integral MeasureTheory.L1.SimpleFunc.integral_L1_eq_integral
variable (α E)
@[simp]
theorem integral_zero : integral (0 : α →₁[μ] E) = 0 := by
simp only [integral]
exact map_zero integralCLM
#align measure_theory.L1.integral_zero MeasureTheory.L1.integral_zero
variable {α E}
@[integral_simps]
theorem integral_add (f g : α →₁[μ] E) : integral (f + g) = integral f + integral g := by
simp only [integral]
exact map_add integralCLM f g
#align measure_theory.L1.integral_add MeasureTheory.L1.integral_add
@[integral_simps]
theorem integral_neg (f : α →₁[μ] E) : integral (-f) = -integral f := by
simp only [integral]
exact map_neg integralCLM f
#align measure_theory.L1.integral_neg MeasureTheory.L1.integral_neg
@[integral_simps]
theorem integral_sub (f g : α →₁[μ] E) : integral (f - g) = integral f - integral g := by
simp only [integral]
exact map_sub integralCLM f g
#align measure_theory.L1.integral_sub MeasureTheory.L1.integral_sub
@[integral_simps]
| Mathlib/MeasureTheory/Integral/Bochner.lean | 714 | 717 | theorem integral_smul (c : 𝕜) (f : α →₁[μ] E) : integral (c • f) = c • integral f := by |
simp only [integral]
show (integralCLM' (E := E) 𝕜) (c • f) = c • (integralCLM' (E := E) 𝕜) f
exact map_smul (integralCLM' (E := E) 𝕜) c f
|
/-
Copyright (c) 2022 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johanes Hölzl, Patrick Massot, Yury Kudryashov, Kevin Wilson, Heather Macbeth
-/
import Mathlib.Order.Filter.Basic
#align_import order.filter.prod from "leanprover-community/mathlib"@"d6fad0e5bf2d6f48da9175d25c3dc5706b3834ce"
/-!
# Product and coproduct filters
In this file we define `Filter.prod f g` (notation: `f ×ˢ g`) and `Filter.coprod f g`. The product
of two filters is the largest filter `l` such that `Filter.Tendsto Prod.fst l f` and
`Filter.Tendsto Prod.snd l g`.
## Implementation details
The product filter cannot be defined using the monad structure on filters. For example:
```lean
F := do {x ← seq, y ← top, return (x, y)}
G := do {y ← top, x ← seq, return (x, y)}
```
hence:
```lean
s ∈ F ↔ ∃ n, [n..∞] × univ ⊆ s
s ∈ G ↔ ∀ i:ℕ, ∃ n, [n..∞] × {i} ⊆ s
```
Now `⋃ i, [i..∞] × {i}` is in `G` but not in `F`.
As product filter we want to have `F` as result.
## Notations
* `f ×ˢ g` : `Filter.prod f g`, localized in `Filter`.
-/
open Set
open Filter
namespace Filter
variable {α β γ δ : Type*} {ι : Sort*}
section Prod
variable {s : Set α} {t : Set β} {f : Filter α} {g : Filter β}
/-- Product of filters. This is the filter generated by cartesian products
of elements of the component filters. -/
protected def prod (f : Filter α) (g : Filter β) : Filter (α × β) :=
f.comap Prod.fst ⊓ g.comap Prod.snd
#align filter.prod Filter.prod
instance instSProd : SProd (Filter α) (Filter β) (Filter (α × β)) where
sprod := Filter.prod
theorem prod_mem_prod (hs : s ∈ f) (ht : t ∈ g) : s ×ˢ t ∈ f ×ˢ g :=
inter_mem_inf (preimage_mem_comap hs) (preimage_mem_comap ht)
#align filter.prod_mem_prod Filter.prod_mem_prod
theorem mem_prod_iff {s : Set (α × β)} {f : Filter α} {g : Filter β} :
s ∈ f ×ˢ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ×ˢ t₂ ⊆ s := by
simp only [SProd.sprod, Filter.prod]
constructor
· rintro ⟨t₁, ⟨s₁, hs₁, hts₁⟩, t₂, ⟨s₂, hs₂, hts₂⟩, rfl⟩
exact ⟨s₁, hs₁, s₂, hs₂, fun p ⟨h, h'⟩ => ⟨hts₁ h, hts₂ h'⟩⟩
· rintro ⟨t₁, ht₁, t₂, ht₂, h⟩
exact mem_inf_of_inter (preimage_mem_comap ht₁) (preimage_mem_comap ht₂) h
#align filter.mem_prod_iff Filter.mem_prod_iff
@[simp]
theorem prod_mem_prod_iff [f.NeBot] [g.NeBot] : s ×ˢ t ∈ f ×ˢ g ↔ s ∈ f ∧ t ∈ g :=
⟨fun h =>
let ⟨_s', hs', _t', ht', H⟩ := mem_prod_iff.1 h
(prod_subset_prod_iff.1 H).elim
(fun ⟨hs's, ht't⟩ => ⟨mem_of_superset hs' hs's, mem_of_superset ht' ht't⟩) fun h =>
h.elim (fun hs'e => absurd hs'e (nonempty_of_mem hs').ne_empty) fun ht'e =>
absurd ht'e (nonempty_of_mem ht').ne_empty,
fun h => prod_mem_prod h.1 h.2⟩
#align filter.prod_mem_prod_iff Filter.prod_mem_prod_iff
theorem mem_prod_principal {s : Set (α × β)} :
s ∈ f ×ˢ 𝓟 t ↔ { a | ∀ b ∈ t, (a, b) ∈ s } ∈ f := by
rw [← @exists_mem_subset_iff _ f, mem_prod_iff]
refine exists_congr fun u => Iff.rfl.and ⟨?_, fun h => ⟨t, mem_principal_self t, ?_⟩⟩
· rintro ⟨v, v_in, hv⟩ a a_in b b_in
exact hv (mk_mem_prod a_in <| v_in b_in)
· rintro ⟨x, y⟩ ⟨hx, hy⟩
exact h hx y hy
#align filter.mem_prod_principal Filter.mem_prod_principal
theorem mem_prod_top {s : Set (α × β)} :
s ∈ f ×ˢ (⊤ : Filter β) ↔ { a | ∀ b, (a, b) ∈ s } ∈ f := by
rw [← principal_univ, mem_prod_principal]
simp only [mem_univ, forall_true_left]
#align filter.mem_prod_top Filter.mem_prod_top
theorem eventually_prod_principal_iff {p : α × β → Prop} {s : Set β} :
(∀ᶠ x : α × β in f ×ˢ 𝓟 s, p x) ↔ ∀ᶠ x : α in f, ∀ y : β, y ∈ s → p (x, y) := by
rw [eventually_iff, eventually_iff, mem_prod_principal]
simp only [mem_setOf_eq]
#align filter.eventually_prod_principal_iff Filter.eventually_prod_principal_iff
theorem comap_prod (f : α → β × γ) (b : Filter β) (c : Filter γ) :
comap f (b ×ˢ c) = comap (Prod.fst ∘ f) b ⊓ comap (Prod.snd ∘ f) c := by
erw [comap_inf, Filter.comap_comap, Filter.comap_comap]
#align filter.comap_prod Filter.comap_prod
theorem prod_top : f ×ˢ (⊤ : Filter β) = f.comap Prod.fst := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_top, inf_top_eq]
#align filter.prod_top Filter.prod_top
theorem top_prod : (⊤ : Filter α) ×ˢ g = g.comap Prod.snd := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_top, top_inf_eq]
theorem sup_prod (f₁ f₂ : Filter α) (g : Filter β) : (f₁ ⊔ f₂) ×ˢ g = (f₁ ×ˢ g) ⊔ (f₂ ×ˢ g) := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_sup, inf_sup_right, ← Filter.prod, ← Filter.prod]
#align filter.sup_prod Filter.sup_prod
theorem prod_sup (f : Filter α) (g₁ g₂ : Filter β) : f ×ˢ (g₁ ⊔ g₂) = (f ×ˢ g₁) ⊔ (f ×ˢ g₂) := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_sup, inf_sup_left, ← Filter.prod, ← Filter.prod]
#align filter.prod_sup Filter.prod_sup
theorem eventually_prod_iff {p : α × β → Prop} :
(∀ᶠ x in f ×ˢ g, p x) ↔
∃ pa : α → Prop, (∀ᶠ x in f, pa x) ∧ ∃ pb : β → Prop, (∀ᶠ y in g, pb y) ∧
∀ {x}, pa x → ∀ {y}, pb y → p (x, y) := by
simpa only [Set.prod_subset_iff] using @mem_prod_iff α β p f g
#align filter.eventually_prod_iff Filter.eventually_prod_iff
theorem tendsto_fst : Tendsto Prod.fst (f ×ˢ g) f :=
tendsto_inf_left tendsto_comap
#align filter.tendsto_fst Filter.tendsto_fst
theorem tendsto_snd : Tendsto Prod.snd (f ×ˢ g) g :=
tendsto_inf_right tendsto_comap
#align filter.tendsto_snd Filter.tendsto_snd
/-- If a function tends to a product `g ×ˢ h` of filters, then its first component tends to
`g`. See also `Filter.Tendsto.fst_nhds` for the special case of converging to a point in a
product of two topological spaces. -/
theorem Tendsto.fst {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) :
Tendsto (fun a ↦ (m a).1) f g :=
tendsto_fst.comp H
/-- If a function tends to a product `g ×ˢ h` of filters, then its second component tends to
`h`. See also `Filter.Tendsto.snd_nhds` for the special case of converging to a point in a
product of two topological spaces. -/
theorem Tendsto.snd {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) :
Tendsto (fun a ↦ (m a).2) f h :=
tendsto_snd.comp H
theorem Tendsto.prod_mk {h : Filter γ} {m₁ : α → β} {m₂ : α → γ}
(h₁ : Tendsto m₁ f g) (h₂ : Tendsto m₂ f h) : Tendsto (fun x => (m₁ x, m₂ x)) f (g ×ˢ h) :=
tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩
#align filter.tendsto.prod_mk Filter.Tendsto.prod_mk
theorem tendsto_prod_swap : Tendsto (Prod.swap : α × β → β × α) (f ×ˢ g) (g ×ˢ f) :=
tendsto_snd.prod_mk tendsto_fst
#align filter.tendsto_prod_swap Filter.tendsto_prod_swap
theorem Eventually.prod_inl {la : Filter α} {p : α → Prop} (h : ∀ᶠ x in la, p x) (lb : Filter β) :
∀ᶠ x in la ×ˢ lb, p (x : α × β).1 :=
tendsto_fst.eventually h
#align filter.eventually.prod_inl Filter.Eventually.prod_inl
theorem Eventually.prod_inr {lb : Filter β} {p : β → Prop} (h : ∀ᶠ x in lb, p x) (la : Filter α) :
∀ᶠ x in la ×ˢ lb, p (x : α × β).2 :=
tendsto_snd.eventually h
#align filter.eventually.prod_inr Filter.Eventually.prod_inr
theorem Eventually.prod_mk {la : Filter α} {pa : α → Prop} (ha : ∀ᶠ x in la, pa x) {lb : Filter β}
{pb : β → Prop} (hb : ∀ᶠ y in lb, pb y) : ∀ᶠ p in la ×ˢ lb, pa (p : α × β).1 ∧ pb p.2 :=
(ha.prod_inl lb).and (hb.prod_inr la)
#align filter.eventually.prod_mk Filter.Eventually.prod_mk
theorem EventuallyEq.prod_map {δ} {la : Filter α} {fa ga : α → γ} (ha : fa =ᶠ[la] ga)
{lb : Filter β} {fb gb : β → δ} (hb : fb =ᶠ[lb] gb) :
Prod.map fa fb =ᶠ[la ×ˢ lb] Prod.map ga gb :=
(Eventually.prod_mk ha hb).mono fun _ h => Prod.ext h.1 h.2
#align filter.eventually_eq.prod_map Filter.EventuallyEq.prod_map
theorem EventuallyLE.prod_map {δ} [LE γ] [LE δ] {la : Filter α} {fa ga : α → γ} (ha : fa ≤ᶠ[la] ga)
{lb : Filter β} {fb gb : β → δ} (hb : fb ≤ᶠ[lb] gb) :
Prod.map fa fb ≤ᶠ[la ×ˢ lb] Prod.map ga gb :=
Eventually.prod_mk ha hb
#align filter.eventually_le.prod_map Filter.EventuallyLE.prod_map
theorem Eventually.curry {la : Filter α} {lb : Filter β} {p : α × β → Prop}
(h : ∀ᶠ x in la ×ˢ lb, p x) : ∀ᶠ x in la, ∀ᶠ y in lb, p (x, y) := by
rcases eventually_prod_iff.1 h with ⟨pa, ha, pb, hb, h⟩
exact ha.mono fun a ha => hb.mono fun b hb => h ha hb
#align filter.eventually.curry Filter.Eventually.curry
protected lemma Frequently.uncurry {la : Filter α} {lb : Filter β} {p : α → β → Prop}
(h : ∃ᶠ x in la, ∃ᶠ y in lb, p x y) : ∃ᶠ xy in la ×ˢ lb, p xy.1 xy.2 :=
mt (fun h ↦ by simpa only [not_frequently] using h.curry) h
/-- A fact that is eventually true about all pairs `l ×ˢ l` is eventually true about
all diagonal pairs `(i, i)` -/
| Mathlib/Order/Filter/Prod.lean | 208 | 211 | theorem Eventually.diag_of_prod {p : α × α → Prop} (h : ∀ᶠ i in f ×ˢ f, p i) :
∀ᶠ i in f, p (i, i) := by |
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
apply (ht.and hs).mono fun x hx => hst hx.1 hx.2
|
/-
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.Convex.Topology
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Analysis.SpecificLimits.Basic
#align_import analysis.calculus.tangent_cone from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Tangent cone
In this file, we define two predicates `UniqueDiffWithinAt 𝕜 s x` and `UniqueDiffOn 𝕜 s`
ensuring that, if a function has two derivatives, then they have to coincide. As a direct
definition of this fact (quantifying on all target types and all functions) would depend on
universes, we use a more intrinsic definition: if all the possible tangent directions to the set
`s` at the point `x` span a dense subset of the whole subset, it is easy to check that the
derivative has to be unique.
Therefore, we introduce the set of all tangent directions, named `tangentConeAt`,
and express `UniqueDiffWithinAt` and `UniqueDiffOn` in terms of it.
One should however think of this definition as an implementation detail: the only reason to
introduce the predicates `UniqueDiffWithinAt` and `UniqueDiffOn` is to ensure the uniqueness
of the derivative. This is why their names reflect their uses, and not how they are defined.
## Implementation details
Note that this file is imported by `Fderiv.Basic`. Hence, derivatives are not defined yet. The
property of uniqueness of the derivative is therefore proved in `Fderiv.Basic`, but based on the
properties of the tangent cone we prove here.
-/
variable (𝕜 : Type*) [NontriviallyNormedField 𝕜]
open Filter Set
open Topology
section TangentCone
variable {E : Type*} [AddCommMonoid E] [Module 𝕜 E] [TopologicalSpace E]
/-- The set of all tangent directions to the set `s` at the point `x`. -/
def tangentConeAt (s : Set E) (x : E) : Set E :=
{ y : E | ∃ (c : ℕ → 𝕜) (d : ℕ → E),
(∀ᶠ n in atTop, x + d n ∈ s) ∧
Tendsto (fun n => ‖c n‖) atTop atTop ∧
Tendsto (fun n => c n • d n) atTop (𝓝 y) }
#align tangent_cone_at tangentConeAt
/-- A property ensuring that the tangent cone to `s` at `x` spans a dense subset of the whole space.
The main role of this property is to ensure that the differential within `s` at `x` is unique,
hence this name. The uniqueness it asserts is proved in `UniqueDiffWithinAt.eq` in `Fderiv.Basic`.
To avoid pathologies in dimension 0, we also require that `x` belongs to the closure of `s` (which
is automatic when `E` is not `0`-dimensional). -/
@[mk_iff]
structure UniqueDiffWithinAt (s : Set E) (x : E) : Prop where
dense_tangentCone : Dense (Submodule.span 𝕜 (tangentConeAt 𝕜 s x) : Set E)
mem_closure : x ∈ closure s
#align unique_diff_within_at UniqueDiffWithinAt
/-- A property ensuring that the tangent cone to `s` at any of its points spans a dense subset of
the whole space. The main role of this property is to ensure that the differential along `s` is
unique, hence this name. The uniqueness it asserts is proved in `UniqueDiffOn.eq` in
`Fderiv.Basic`. -/
def UniqueDiffOn (s : Set E) : Prop :=
∀ x ∈ s, UniqueDiffWithinAt 𝕜 s x
#align unique_diff_on UniqueDiffOn
end TangentCone
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace ℝ G]
variable {𝕜} {x y : E} {s t : Set E}
section TangentCone
-- This section is devoted to the properties of the tangent cone.
open NormedField
theorem mem_tangentConeAt_of_pow_smul {r : 𝕜} (hr₀ : r ≠ 0) (hr : ‖r‖ < 1)
(hs : ∀ᶠ n : ℕ in atTop, x + r ^ n • y ∈ s) : y ∈ tangentConeAt 𝕜 s x := by
refine ⟨fun n ↦ (r ^ n)⁻¹, fun n ↦ r ^ n • y, hs, ?_, ?_⟩
· simp only [norm_inv, norm_pow, ← inv_pow]
exact tendsto_pow_atTop_atTop_of_one_lt <| one_lt_inv (norm_pos_iff.2 hr₀) hr
· simp only [inv_smul_smul₀ (pow_ne_zero _ hr₀), tendsto_const_nhds]
theorem tangentCone_univ : tangentConeAt 𝕜 univ x = univ :=
let ⟨_r, hr₀, hr⟩ := exists_norm_lt_one 𝕜
eq_univ_of_forall fun _ ↦ mem_tangentConeAt_of_pow_smul (norm_pos_iff.1 hr₀) hr <|
eventually_of_forall fun _ ↦ mem_univ _
#align tangent_cone_univ tangentCone_univ
theorem tangentCone_mono (h : s ⊆ t) : tangentConeAt 𝕜 s x ⊆ tangentConeAt 𝕜 t x := by
rintro y ⟨c, d, ds, ctop, clim⟩
exact ⟨c, d, mem_of_superset ds fun n hn => h hn, ctop, clim⟩
#align tangent_cone_mono tangentCone_mono
/-- Auxiliary lemma ensuring that, under the assumptions defining the tangent cone,
the sequence `d` tends to 0 at infinity. -/
theorem tangentConeAt.lim_zero {α : Type*} (l : Filter α) {c : α → 𝕜} {d : α → E}
(hc : Tendsto (fun n => ‖c n‖) l atTop) (hd : Tendsto (fun n => c n • d n) l (𝓝 y)) :
Tendsto d l (𝓝 0) := by
have A : Tendsto (fun n => ‖c n‖⁻¹) l (𝓝 0) := tendsto_inv_atTop_zero.comp hc
have B : Tendsto (fun n => ‖c n • d n‖) l (𝓝 ‖y‖) := (continuous_norm.tendsto _).comp hd
have C : Tendsto (fun n => ‖c n‖⁻¹ * ‖c n • d n‖) l (𝓝 (0 * ‖y‖)) := A.mul B
rw [zero_mul] at C
have : ∀ᶠ n in l, ‖c n‖⁻¹ * ‖c n • d n‖ = ‖d n‖ := by
refine (eventually_ne_of_tendsto_norm_atTop hc 0).mono fun n hn => ?_
rw [norm_smul, ← mul_assoc, inv_mul_cancel, one_mul]
rwa [Ne, norm_eq_zero]
have D : Tendsto (fun n => ‖d n‖) l (𝓝 0) := Tendsto.congr' this C
rw [tendsto_zero_iff_norm_tendsto_zero]
exact D
#align tangent_cone_at.lim_zero tangentConeAt.lim_zero
theorem tangentCone_mono_nhds (h : 𝓝[s] x ≤ 𝓝[t] x) :
tangentConeAt 𝕜 s x ⊆ tangentConeAt 𝕜 t x := by
rintro y ⟨c, d, ds, ctop, clim⟩
refine ⟨c, d, ?_, ctop, clim⟩
suffices Tendsto (fun n => x + d n) atTop (𝓝[t] x) from
tendsto_principal.1 (tendsto_inf.1 this).2
refine (tendsto_inf.2 ⟨?_, tendsto_principal.2 ds⟩).mono_right h
simpa only [add_zero] using tendsto_const_nhds.add (tangentConeAt.lim_zero atTop ctop clim)
#align tangent_cone_mono_nhds tangentCone_mono_nhds
/-- Tangent cone of `s` at `x` depends only on `𝓝[s] x`. -/
theorem tangentCone_congr (h : 𝓝[s] x = 𝓝[t] x) : tangentConeAt 𝕜 s x = tangentConeAt 𝕜 t x :=
Subset.antisymm (tangentCone_mono_nhds <| le_of_eq h) (tangentCone_mono_nhds <| le_of_eq h.symm)
#align tangent_cone_congr tangentCone_congr
/-- Intersecting with a neighborhood of the point does not change the tangent cone. -/
theorem tangentCone_inter_nhds (ht : t ∈ 𝓝 x) : tangentConeAt 𝕜 (s ∩ t) x = tangentConeAt 𝕜 s x :=
tangentCone_congr (nhdsWithin_restrict' _ ht).symm
#align tangent_cone_inter_nhds tangentCone_inter_nhds
/-- The tangent cone of a product contains the tangent cone of its left factor. -/
theorem subset_tangentCone_prod_left {t : Set F} {y : F} (ht : y ∈ closure t) :
LinearMap.inl 𝕜 E F '' tangentConeAt 𝕜 s x ⊆ tangentConeAt 𝕜 (s ×ˢ t) (x, y) := by
rintro _ ⟨v, ⟨c, d, hd, hc, hy⟩, rfl⟩
have : ∀ n, ∃ d', y + d' ∈ t ∧ ‖c n • d'‖ < ((1 : ℝ) / 2) ^ n := by
intro n
rcases mem_closure_iff_nhds.1 ht _
(eventually_nhds_norm_smul_sub_lt (c n) y (pow_pos one_half_pos n)) with
⟨z, hz, hzt⟩
exact ⟨z - y, by simpa using hzt, by simpa using hz⟩
choose d' hd' using this
refine ⟨c, fun n => (d n, d' n), ?_, hc, ?_⟩
· show ∀ᶠ n in atTop, (x, y) + (d n, d' n) ∈ s ×ˢ t
filter_upwards [hd] with n hn
simp [hn, (hd' n).1]
· apply Tendsto.prod_mk_nhds hy _
refine squeeze_zero_norm (fun n => (hd' n).2.le) ?_
exact tendsto_pow_atTop_nhds_zero_of_lt_one one_half_pos.le one_half_lt_one
#align subset_tangent_cone_prod_left subset_tangentCone_prod_left
/-- The tangent cone of a product contains the tangent cone of its right factor. -/
theorem subset_tangentCone_prod_right {t : Set F} {y : F} (hs : x ∈ closure s) :
LinearMap.inr 𝕜 E F '' tangentConeAt 𝕜 t y ⊆ tangentConeAt 𝕜 (s ×ˢ t) (x, y) := by
rintro _ ⟨w, ⟨c, d, hd, hc, hy⟩, rfl⟩
have : ∀ n, ∃ d', x + d' ∈ s ∧ ‖c n • d'‖ < ((1 : ℝ) / 2) ^ n := by
intro n
rcases mem_closure_iff_nhds.1 hs _
(eventually_nhds_norm_smul_sub_lt (c n) x (pow_pos one_half_pos n)) with
⟨z, hz, hzs⟩
exact ⟨z - x, by simpa using hzs, by simpa using hz⟩
choose d' hd' using this
refine ⟨c, fun n => (d' n, d n), ?_, hc, ?_⟩
· show ∀ᶠ n in atTop, (x, y) + (d' n, d n) ∈ s ×ˢ t
filter_upwards [hd] with n hn
simp [hn, (hd' n).1]
· apply Tendsto.prod_mk_nhds _ hy
refine squeeze_zero_norm (fun n => (hd' n).2.le) ?_
exact tendsto_pow_atTop_nhds_zero_of_lt_one one_half_pos.le one_half_lt_one
#align subset_tangent_cone_prod_right subset_tangentCone_prod_right
/-- The tangent cone of a product contains the tangent cone of each factor. -/
theorem mapsTo_tangentCone_pi {ι : Type*} [DecidableEq ι] {E : ι → Type*}
[∀ i, NormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)] {s : ∀ i, Set (E i)} {x : ∀ i, E i}
{i : ι} (hi : ∀ j ≠ i, x j ∈ closure (s j)) :
MapsTo (LinearMap.single i : E i →ₗ[𝕜] ∀ j, E j) (tangentConeAt 𝕜 (s i) (x i))
(tangentConeAt 𝕜 (Set.pi univ s) x) := by
rintro w ⟨c, d, hd, hc, hy⟩
have : ∀ n, ∀ j ≠ i, ∃ d', x j + d' ∈ s j ∧ ‖c n • d'‖ < (1 / 2 : ℝ) ^ n := fun n j hj ↦ by
rcases mem_closure_iff_nhds.1 (hi j hj) _
(eventually_nhds_norm_smul_sub_lt (c n) (x j) (pow_pos one_half_pos n)) with
⟨z, hz, hzs⟩
exact ⟨z - x j, by simpa using hzs, by simpa using hz⟩
choose! d' hd's hcd' using this
refine ⟨c, fun n => Function.update (d' n) i (d n), hd.mono fun n hn j _ => ?_, hc,
tendsto_pi_nhds.2 fun j => ?_⟩
· rcases em (j = i) with (rfl | hj) <;> simp [*]
· rcases em (j = i) with (rfl | hj)
· simp [hy]
· suffices Tendsto (fun n => c n • d' n j) atTop (𝓝 0) by simpa [hj]
refine squeeze_zero_norm (fun n => (hcd' n j hj).le) ?_
exact tendsto_pow_atTop_nhds_zero_of_lt_one one_half_pos.le one_half_lt_one
#align maps_to_tangent_cone_pi mapsTo_tangentCone_pi
/-- If a subset of a real vector space contains an open segment, then the direction of this
segment belongs to the tangent cone at its endpoints. -/
theorem mem_tangentCone_of_openSegment_subset {s : Set G} {x y : G} (h : openSegment ℝ x y ⊆ s) :
y - x ∈ tangentConeAt ℝ s x := by
refine mem_tangentConeAt_of_pow_smul one_half_pos.ne' (by norm_num) ?_
refine (eventually_ne_atTop 0).mono fun n hn ↦ (h ?_)
rw [openSegment_eq_image]
refine ⟨(1 / 2) ^ n, ⟨?_, ?_⟩, ?_⟩
· exact pow_pos one_half_pos _
· exact pow_lt_one one_half_pos.le one_half_lt_one hn
· simp only [sub_smul, one_smul, smul_sub]; abel
#align mem_tangent_cone_of_open_segment_subset mem_tangentCone_of_openSegment_subset
/-- If a subset of a real vector space contains a segment, then the direction of this
segment belongs to the tangent cone at its endpoints. -/
theorem mem_tangentCone_of_segment_subset {s : Set G} {x y : G} (h : segment ℝ x y ⊆ s) :
y - x ∈ tangentConeAt ℝ s x :=
mem_tangentCone_of_openSegment_subset ((openSegment_subset_segment ℝ x y).trans h)
#align mem_tangent_cone_of_segment_subset mem_tangentCone_of_segment_subset
end TangentCone
section UniqueDiff
/-!
### Properties of `UniqueDiffWithinAt` and `UniqueDiffOn`
This section is devoted to properties of the predicates `UniqueDiffWithinAt` and `UniqueDiffOn`. -/
theorem UniqueDiffOn.uniqueDiffWithinAt {s : Set E} {x} (hs : UniqueDiffOn 𝕜 s) (h : x ∈ s) :
UniqueDiffWithinAt 𝕜 s x :=
hs x h
#align unique_diff_on.unique_diff_within_at UniqueDiffOn.uniqueDiffWithinAt
theorem uniqueDiffWithinAt_univ : UniqueDiffWithinAt 𝕜 univ x := by
rw [uniqueDiffWithinAt_iff, tangentCone_univ]
simp
#align unique_diff_within_at_univ uniqueDiffWithinAt_univ
theorem uniqueDiffOn_univ : UniqueDiffOn 𝕜 (univ : Set E) :=
fun _ _ => uniqueDiffWithinAt_univ
#align unique_diff_on_univ uniqueDiffOn_univ
theorem uniqueDiffOn_empty : UniqueDiffOn 𝕜 (∅ : Set E) :=
fun _ hx => hx.elim
#align unique_diff_on_empty uniqueDiffOn_empty
theorem UniqueDiffWithinAt.congr_pt (h : UniqueDiffWithinAt 𝕜 s x) (hy : x = y) :
UniqueDiffWithinAt 𝕜 s y := hy ▸ h
theorem UniqueDiffWithinAt.mono_nhds (h : UniqueDiffWithinAt 𝕜 s x) (st : 𝓝[s] x ≤ 𝓝[t] x) :
UniqueDiffWithinAt 𝕜 t x := by
simp only [uniqueDiffWithinAt_iff] at *
rw [mem_closure_iff_nhdsWithin_neBot] at h ⊢
exact ⟨h.1.mono <| Submodule.span_mono <| tangentCone_mono_nhds st, h.2.mono st⟩
#align unique_diff_within_at.mono_nhds UniqueDiffWithinAt.mono_nhds
theorem UniqueDiffWithinAt.mono (h : UniqueDiffWithinAt 𝕜 s x) (st : s ⊆ t) :
UniqueDiffWithinAt 𝕜 t x :=
h.mono_nhds <| nhdsWithin_mono _ st
#align unique_diff_within_at.mono UniqueDiffWithinAt.mono
theorem uniqueDiffWithinAt_congr (st : 𝓝[s] x = 𝓝[t] x) :
UniqueDiffWithinAt 𝕜 s x ↔ UniqueDiffWithinAt 𝕜 t x :=
⟨fun h => h.mono_nhds <| le_of_eq st, fun h => h.mono_nhds <| le_of_eq st.symm⟩
#align unique_diff_within_at_congr uniqueDiffWithinAt_congr
theorem uniqueDiffWithinAt_inter (ht : t ∈ 𝓝 x) :
UniqueDiffWithinAt 𝕜 (s ∩ t) x ↔ UniqueDiffWithinAt 𝕜 s x :=
uniqueDiffWithinAt_congr <| (nhdsWithin_restrict' _ ht).symm
#align unique_diff_within_at_inter uniqueDiffWithinAt_inter
theorem UniqueDiffWithinAt.inter (hs : UniqueDiffWithinAt 𝕜 s x) (ht : t ∈ 𝓝 x) :
UniqueDiffWithinAt 𝕜 (s ∩ t) x :=
(uniqueDiffWithinAt_inter ht).2 hs
#align unique_diff_within_at.inter UniqueDiffWithinAt.inter
theorem uniqueDiffWithinAt_inter' (ht : t ∈ 𝓝[s] x) :
UniqueDiffWithinAt 𝕜 (s ∩ t) x ↔ UniqueDiffWithinAt 𝕜 s x :=
uniqueDiffWithinAt_congr <| (nhdsWithin_restrict'' _ ht).symm
#align unique_diff_within_at_inter' uniqueDiffWithinAt_inter'
theorem UniqueDiffWithinAt.inter' (hs : UniqueDiffWithinAt 𝕜 s x) (ht : t ∈ 𝓝[s] x) :
UniqueDiffWithinAt 𝕜 (s ∩ t) x :=
(uniqueDiffWithinAt_inter' ht).2 hs
#align unique_diff_within_at.inter' UniqueDiffWithinAt.inter'
theorem uniqueDiffWithinAt_of_mem_nhds (h : s ∈ 𝓝 x) : UniqueDiffWithinAt 𝕜 s x := by
simpa only [univ_inter] using uniqueDiffWithinAt_univ.inter h
#align unique_diff_within_at_of_mem_nhds uniqueDiffWithinAt_of_mem_nhds
theorem IsOpen.uniqueDiffWithinAt (hs : IsOpen s) (xs : x ∈ s) : UniqueDiffWithinAt 𝕜 s x :=
uniqueDiffWithinAt_of_mem_nhds (IsOpen.mem_nhds hs xs)
#align is_open.unique_diff_within_at IsOpen.uniqueDiffWithinAt
theorem UniqueDiffOn.inter (hs : UniqueDiffOn 𝕜 s) (ht : IsOpen t) : UniqueDiffOn 𝕜 (s ∩ t) :=
fun x hx => (hs x hx.1).inter (IsOpen.mem_nhds ht hx.2)
#align unique_diff_on.inter UniqueDiffOn.inter
theorem IsOpen.uniqueDiffOn (hs : IsOpen s) : UniqueDiffOn 𝕜 s :=
fun _ hx => IsOpen.uniqueDiffWithinAt hs hx
#align is_open.unique_diff_on IsOpen.uniqueDiffOn
/-- The product of two sets of unique differentiability at points `x` and `y` has unique
differentiability at `(x, y)`. -/
theorem UniqueDiffWithinAt.prod {t : Set F} {y : F} (hs : UniqueDiffWithinAt 𝕜 s x)
(ht : UniqueDiffWithinAt 𝕜 t y) : UniqueDiffWithinAt 𝕜 (s ×ˢ t) (x, y) := by
rw [uniqueDiffWithinAt_iff] at hs ht ⊢
rw [closure_prod_eq]
refine ⟨?_, hs.2, ht.2⟩
have : _ ≤ Submodule.span 𝕜 (tangentConeAt 𝕜 (s ×ˢ t) (x, y)) := Submodule.span_mono
(union_subset (subset_tangentCone_prod_left ht.2) (subset_tangentCone_prod_right hs.2))
rw [LinearMap.span_inl_union_inr, SetLike.le_def] at this
exact (hs.1.prod ht.1).mono this
#align unique_diff_within_at.prod UniqueDiffWithinAt.prod
theorem UniqueDiffWithinAt.univ_pi (ι : Type*) [Finite ι] (E : ι → Type*)
[∀ i, NormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)] (s : ∀ i, Set (E i)) (x : ∀ i, E i)
(h : ∀ i, UniqueDiffWithinAt 𝕜 (s i) (x i)) : UniqueDiffWithinAt 𝕜 (Set.pi univ s) x := by
classical
simp only [uniqueDiffWithinAt_iff, closure_pi_set] at h ⊢
refine ⟨(dense_pi univ fun i _ => (h i).1).mono ?_, fun i _ => (h i).2⟩
norm_cast
simp only [← Submodule.iSup_map_single, iSup_le_iff, LinearMap.map_span, Submodule.span_le,
← mapsTo']
exact fun i => (mapsTo_tangentCone_pi fun j _ => (h j).2).mono Subset.rfl Submodule.subset_span
#align unique_diff_within_at.univ_pi UniqueDiffWithinAt.univ_pi
| Mathlib/Analysis/Calculus/TangentCone.lean | 333 | 340 | theorem UniqueDiffWithinAt.pi (ι : Type*) [Finite ι] (E : ι → Type*)
[∀ i, NormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)] (s : ∀ i, Set (E i)) (x : ∀ i, E i)
(I : Set ι) (h : ∀ i ∈ I, UniqueDiffWithinAt 𝕜 (s i) (x i)) :
UniqueDiffWithinAt 𝕜 (Set.pi I s) x := by |
classical
rw [← Set.univ_pi_piecewise_univ]
refine UniqueDiffWithinAt.univ_pi ι E _ _ fun i => ?_
by_cases hi : i ∈ I <;> simp [*, uniqueDiffWithinAt_univ]
|
/-
Copyright (c) 2022 Jon Eugster. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jon Eugster
-/
import Mathlib.Algebra.CharP.LocalRing
import Mathlib.RingTheory.Ideal.Quotient
import Mathlib.Tactic.FieldSimp
#align_import algebra.char_p.mixed_char_zero from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Equal and mixed characteristic
In commutative algebra, some statements are simpler when working over a `ℚ`-algebra `R`, in which
case one also says that the ring has "equal characteristic zero". A ring that is not a
`ℚ`-algebra has either positive characteristic or there exists a prime ideal `I ⊂ R` such that
the quotient `R ⧸ I` has positive characteristic `p > 0`. In this case one speaks of
"mixed characteristic `(0, p)`", where `p` is only unique if `R` is local.
Examples of mixed characteristic rings are `ℤ` or the `p`-adic integers/numbers.
This file provides the main theorem `split_by_characteristic` that splits any proposition `P` into
the following three cases:
1) Positive characteristic: `CharP R p` (where `p ≠ 0`)
2) Equal characteristic zero: `Algebra ℚ R`
3) Mixed characteristic: `MixedCharZero R p` (where `p` is prime)
## Main definitions
- `MixedCharZero` : A ring has mixed characteristic `(0, p)` if it has characteristic zero
and there exists an ideal such that the quotient `R ⧸ I` has characteristic `p`.
## Main results
- `split_equalCharZero_mixedCharZero` : Split a statement into equal/mixed characteristic zero.
This main theorem has the following three corollaries which include the positive
characteristic case for convenience:
- `split_by_characteristic` : Generally consider positive char `p ≠ 0`.
- `split_by_characteristic_domain` : In a domain we can assume that `p` is prime.
- `split_by_characteristic_localRing` : In a local ring we can assume that `p` is a prime power.
## Implementation Notes
We use the terms `EqualCharZero` and `AlgebraRat` despite not being such definitions in mathlib.
The former refers to the statement `∀ I : Ideal R, I ≠ ⊤ → CharZero (R ⧸ I)`, the latter
refers to the existence of an instance `[Algebra ℚ R]`. The two are shown to be
equivalent conditions.
## TODO
- Relate mixed characteristic in a local ring to p-adic numbers [NumberTheory.PAdics].
-/
variable (R : Type*) [CommRing R]
/-!
### Mixed characteristic
-/
/--
A ring of characteristic zero is of "mixed characteristic `(0, p)`" if there exists an ideal
such that the quotient `R ⧸ I` has characteristic `p`.
**Remark:** For `p = 0`, `MixedChar R 0` is a meaningless definition (i.e. satisfied by any ring)
as `R ⧸ ⊥ ≅ R` has by definition always characteristic zero.
One could require `(I ≠ ⊥)` in the definition, but then `MixedChar R 0` would mean something
like `ℤ`-algebra of extension degree `≥ 1` and would be completely independent from
whether something is a `ℚ`-algebra or not (e.g. `ℚ[X]` would satisfy it but `ℚ` wouldn't).
-/
class MixedCharZero (p : ℕ) : Prop where
[toCharZero : CharZero R]
charP_quotient : ∃ I : Ideal R, I ≠ ⊤ ∧ CharP (R ⧸ I) p
#align mixed_char_zero MixedCharZero
namespace MixedCharZero
/--
Reduction to `p` prime: When proving any statement `P` about mixed characteristic rings we
can always assume that `p` is prime.
-/
| Mathlib/Algebra/CharP/MixedCharZero.lean | 85 | 105 | theorem reduce_to_p_prime {P : Prop} :
(∀ p > 0, MixedCharZero R p → P) ↔ ∀ p : ℕ, p.Prime → MixedCharZero R p → P := by |
constructor
· intro h q q_prime q_mixedChar
exact h q (Nat.Prime.pos q_prime) q_mixedChar
· intro h q q_pos q_mixedChar
rcases q_mixedChar.charP_quotient with ⟨I, hI_ne_top, _⟩
-- Krull's Thm: There exists a prime ideal `P` such that `I ≤ P`
rcases Ideal.exists_le_maximal I hI_ne_top with ⟨M, hM_max, h_IM⟩
let r := ringChar (R ⧸ M)
have r_pos : r ≠ 0 := by
have q_zero :=
congr_arg (Ideal.Quotient.factor I M h_IM) (CharP.cast_eq_zero (R ⧸ I) q)
simp only [map_natCast, map_zero] at q_zero
apply ne_zero_of_dvd_ne_zero (ne_of_gt q_pos)
exact (CharP.cast_eq_zero_iff (R ⧸ M) r q).mp q_zero
have r_prime : Nat.Prime r :=
or_iff_not_imp_right.1 (CharP.char_is_prime_or_zero (R ⧸ M) r) r_pos
apply h r r_prime
have : CharZero R := q_mixedChar.toCharZero
exact ⟨⟨M, hM_max.ne_top, ringChar.of_eq rfl⟩⟩
|
/-
Copyright (c) 2021 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Measure.Typeclasses
import Mathlib.Analysis.Complex.Basic
#align_import measure_theory.measure.vector_measure from "leanprover-community/mathlib"@"70a4f2197832bceab57d7f41379b2592d1110570"
/-!
# Vector valued measures
This file defines vector valued measures, which are σ-additive functions from a set to an add monoid
`M` such that it maps the empty set and non-measurable sets to zero. In the case
that `M = ℝ`, we called the vector measure a signed measure and write `SignedMeasure α`.
Similarly, when `M = ℂ`, we call the measure a complex measure and write `ComplexMeasure α`.
## Main definitions
* `MeasureTheory.VectorMeasure` is a vector valued, σ-additive function that maps the empty
and non-measurable set to zero.
* `MeasureTheory.VectorMeasure.map` is the pushforward of a vector measure along a function.
* `MeasureTheory.VectorMeasure.restrict` is the restriction of a vector measure on some set.
## Notation
* `v ≤[i] w` means that the vector measure `v` restricted on the set `i` is less than or equal
to the vector measure `w` restricted on `i`, i.e. `v.restrict i ≤ w.restrict i`.
## Implementation notes
We require all non-measurable sets to be mapped to zero in order for the extensionality lemma
to only compare the underlying functions for measurable sets.
We use `HasSum` instead of `tsum` in the definition of vector measures in comparison to `Measure`
since this provides summability.
## Tags
vector measure, signed measure, complex measure
-/
noncomputable section
open scoped Classical
open NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β : Type*} {m : MeasurableSpace α}
/-- A vector measure on a measurable space `α` is a σ-additive `M`-valued function (for some `M`
an add monoid) such that the empty set and non-measurable sets are mapped to zero. -/
structure VectorMeasure (α : Type*) [MeasurableSpace α] (M : Type*) [AddCommMonoid M]
[TopologicalSpace M] where
measureOf' : Set α → M
empty' : measureOf' ∅ = 0
not_measurable' ⦃i : Set α⦄ : ¬MeasurableSet i → measureOf' i = 0
m_iUnion' ⦃f : ℕ → Set α⦄ : (∀ i, MeasurableSet (f i)) → Pairwise (Disjoint on f) →
HasSum (fun i => measureOf' (f i)) (measureOf' (⋃ i, f i))
#align measure_theory.vector_measure MeasureTheory.VectorMeasure
#align measure_theory.vector_measure.measure_of' MeasureTheory.VectorMeasure.measureOf'
#align measure_theory.vector_measure.empty' MeasureTheory.VectorMeasure.empty'
#align measure_theory.vector_measure.not_measurable' MeasureTheory.VectorMeasure.not_measurable'
#align measure_theory.vector_measure.m_Union' MeasureTheory.VectorMeasure.m_iUnion'
/-- A `SignedMeasure` is an `ℝ`-vector measure. -/
abbrev SignedMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℝ
#align measure_theory.signed_measure MeasureTheory.SignedMeasure
/-- A `ComplexMeasure` is a `ℂ`-vector measure. -/
abbrev ComplexMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℂ
#align measure_theory.complex_measure MeasureTheory.ComplexMeasure
open Set MeasureTheory
namespace VectorMeasure
section
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
attribute [coe] VectorMeasure.measureOf'
instance instCoeFun : CoeFun (VectorMeasure α M) fun _ => Set α → M :=
⟨VectorMeasure.measureOf'⟩
#align measure_theory.vector_measure.has_coe_to_fun MeasureTheory.VectorMeasure.instCoeFun
initialize_simps_projections VectorMeasure (measureOf' → apply)
#noalign measure_theory.vector_measure.measure_of_eq_coe
@[simp]
theorem empty (v : VectorMeasure α M) : v ∅ = 0 :=
v.empty'
#align measure_theory.vector_measure.empty MeasureTheory.VectorMeasure.empty
theorem not_measurable (v : VectorMeasure α M) {i : Set α} (hi : ¬MeasurableSet i) : v i = 0 :=
v.not_measurable' hi
#align measure_theory.vector_measure.not_measurable MeasureTheory.VectorMeasure.not_measurable
theorem m_iUnion (v : VectorMeasure α M) {f : ℕ → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) :=
v.m_iUnion' hf₁ hf₂
#align measure_theory.vector_measure.m_Union MeasureTheory.VectorMeasure.m_iUnion
theorem of_disjoint_iUnion_nat [T2Space M] (v : VectorMeasure α M) {f : ℕ → Set α}
(hf₁ : ∀ i, MeasurableSet (f i)) (hf₂ : Pairwise (Disjoint on f)) :
v (⋃ i, f i) = ∑' i, v (f i) :=
(v.m_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union_nat MeasureTheory.VectorMeasure.of_disjoint_iUnion_nat
theorem coe_injective : @Function.Injective (VectorMeasure α M) (Set α → M) (⇑) := fun v w h => by
cases v
cases w
congr
#align measure_theory.vector_measure.coe_injective MeasureTheory.VectorMeasure.coe_injective
theorem ext_iff' (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, v i = w i := by
rw [← coe_injective.eq_iff, Function.funext_iff]
#align measure_theory.vector_measure.ext_iff' MeasureTheory.VectorMeasure.ext_iff'
theorem ext_iff (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, MeasurableSet i → v i = w i := by
constructor
· rintro rfl _ _
rfl
· rw [ext_iff']
intro h i
by_cases hi : MeasurableSet i
· exact h i hi
· simp_rw [not_measurable _ hi]
#align measure_theory.vector_measure.ext_iff MeasureTheory.VectorMeasure.ext_iff
@[ext]
theorem ext {s t : VectorMeasure α M} (h : ∀ i : Set α, MeasurableSet i → s i = t i) : s = t :=
(ext_iff s t).2 h
#align measure_theory.vector_measure.ext MeasureTheory.VectorMeasure.ext
variable [T2Space M] {v : VectorMeasure α M} {f : ℕ → Set α}
theorem hasSum_of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) := by
cases nonempty_encodable β
set g := fun i : ℕ => ⋃ (b : β) (_ : b ∈ Encodable.decode₂ β i), f b with hg
have hg₁ : ∀ i, MeasurableSet (g i) :=
fun _ => MeasurableSet.iUnion fun b => MeasurableSet.iUnion fun _ => hf₁ b
have hg₂ : Pairwise (Disjoint on g) := Encodable.iUnion_decode₂_disjoint_on hf₂
have := v.of_disjoint_iUnion_nat hg₁ hg₂
rw [hg, Encodable.iUnion_decode₂] at this
have hg₃ : (fun i : β => v (f i)) = fun i => v (g (Encodable.encode i)) := by
ext x
rw [hg]
simp only
congr
ext y
simp only [exists_prop, Set.mem_iUnion, Option.mem_def]
constructor
· intro hy
exact ⟨x, (Encodable.decode₂_is_partial_inv _ _).2 rfl, hy⟩
· rintro ⟨b, hb₁, hb₂⟩
rw [Encodable.decode₂_is_partial_inv _ _] at hb₁
rwa [← Encodable.encode_injective hb₁]
rw [Summable.hasSum_iff, this, ← tsum_iUnion_decode₂]
· exact v.empty
· rw [hg₃]
change Summable ((fun i => v (g i)) ∘ Encodable.encode)
rw [Function.Injective.summable_iff Encodable.encode_injective]
· exact (v.m_iUnion hg₁ hg₂).summable
· intro x hx
convert v.empty
simp only [g, Set.iUnion_eq_empty, Option.mem_def, not_exists, Set.mem_range] at hx ⊢
intro i hi
exact False.elim ((hx i) ((Encodable.decode₂_is_partial_inv _ _).1 hi))
#align measure_theory.vector_measure.has_sum_of_disjoint_Union MeasureTheory.VectorMeasure.hasSum_of_disjoint_iUnion
theorem of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : v (⋃ i, f i) = ∑' i, v (f i) :=
(hasSum_of_disjoint_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union MeasureTheory.VectorMeasure.of_disjoint_iUnion
theorem of_union {A B : Set α} (h : Disjoint A B) (hA : MeasurableSet A) (hB : MeasurableSet B) :
v (A ∪ B) = v A + v B := by
rw [Set.union_eq_iUnion, of_disjoint_iUnion, tsum_fintype, Fintype.sum_bool, cond, cond]
exacts [fun b => Bool.casesOn b hB hA, pairwise_disjoint_on_bool.2 h]
#align measure_theory.vector_measure.of_union MeasureTheory.VectorMeasure.of_union
theorem of_add_of_diff {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B) (h : A ⊆ B) :
v A + v (B \ A) = v B := by
rw [← of_union (@Set.disjoint_sdiff_right _ A B) hA (hB.diff hA), Set.union_diff_cancel h]
#align measure_theory.vector_measure.of_add_of_diff MeasureTheory.VectorMeasure.of_add_of_diff
theorem of_diff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [T2Space M]
{v : VectorMeasure α M} {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h : A ⊆ B) : v (B \ A) = v B - v A := by
rw [← of_add_of_diff hA hB h, add_sub_cancel_left]
#align measure_theory.vector_measure.of_diff MeasureTheory.VectorMeasure.of_diff
theorem of_diff_of_diff_eq_zero {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h' : v (B \ A) = 0) : v (A \ B) + v B = v A := by
symm
calc
v A = v (A \ B ∪ A ∩ B) := by simp only [Set.diff_union_inter]
_ = v (A \ B) + v (A ∩ B) := by
rw [of_union]
· rw [disjoint_comm]
exact Set.disjoint_of_subset_left A.inter_subset_right disjoint_sdiff_self_right
· exact hA.diff hB
· exact hA.inter hB
_ = v (A \ B) + v (A ∩ B ∪ B \ A) := by
rw [of_union, h', add_zero]
· exact Set.disjoint_of_subset_left A.inter_subset_left disjoint_sdiff_self_right
· exact hA.inter hB
· exact hB.diff hA
_ = v (A \ B) + v B := by rw [Set.union_comm, Set.inter_comm, Set.diff_union_inter]
#align measure_theory.vector_measure.of_diff_of_diff_eq_zero MeasureTheory.VectorMeasure.of_diff_of_diff_eq_zero
theorem of_iUnion_nonneg {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, 0 ≤ v (f i)) : 0 ≤ v (⋃ i, f i) :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonneg hf₃
#align measure_theory.vector_measure.of_Union_nonneg MeasureTheory.VectorMeasure.of_iUnion_nonneg
theorem of_iUnion_nonpos {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, v (f i) ≤ 0) : v (⋃ i, f i) ≤ 0 :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonpos hf₃
#align measure_theory.vector_measure.of_Union_nonpos MeasureTheory.VectorMeasure.of_iUnion_nonpos
theorem of_nonneg_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : 0 ≤ s A) (hB₂ : 0 ≤ s B)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonneg_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonneg_disjoint_union_eq_zero
theorem of_nonpos_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : s A ≤ 0) (hB₂ : s B ≤ 0)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonpos_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonpos_disjoint_union_eq_zero
end
section SMul
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
/-- Given a real number `r` and a signed measure `s`, `smul r s` is the signed
measure corresponding to the function `r • s`. -/
def smul (r : R) (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := r • ⇑v
empty' := by rw [Pi.smul_apply, empty, smul_zero]
not_measurable' _ hi := by rw [Pi.smul_apply, v.not_measurable hi, smul_zero]
m_iUnion' _ hf₁ hf₂ := by exact HasSum.const_smul _ (v.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.smul MeasureTheory.VectorMeasure.smul
instance instSMul : SMul R (VectorMeasure α M) :=
⟨smul⟩
#align measure_theory.vector_measure.has_smul MeasureTheory.VectorMeasure.instSMul
@[simp]
theorem coe_smul (r : R) (v : VectorMeasure α M) : ⇑(r • v) = r • ⇑v := rfl
#align measure_theory.vector_measure.coe_smul MeasureTheory.VectorMeasure.coe_smul
theorem smul_apply (r : R) (v : VectorMeasure α M) (i : Set α) : (r • v) i = r • v i := rfl
#align measure_theory.vector_measure.smul_apply MeasureTheory.VectorMeasure.smul_apply
end SMul
section AddCommMonoid
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
instance instZero : Zero (VectorMeasure α M) :=
⟨⟨0, rfl, fun _ _ => rfl, fun _ _ _ => hasSum_zero⟩⟩
#align measure_theory.vector_measure.has_zero MeasureTheory.VectorMeasure.instZero
instance instInhabited : Inhabited (VectorMeasure α M) :=
⟨0⟩
#align measure_theory.vector_measure.inhabited MeasureTheory.VectorMeasure.instInhabited
@[simp]
theorem coe_zero : ⇑(0 : VectorMeasure α M) = 0 := rfl
#align measure_theory.vector_measure.coe_zero MeasureTheory.VectorMeasure.coe_zero
theorem zero_apply (i : Set α) : (0 : VectorMeasure α M) i = 0 := rfl
#align measure_theory.vector_measure.zero_apply MeasureTheory.VectorMeasure.zero_apply
variable [ContinuousAdd M]
/-- The sum of two vector measure is a vector measure. -/
def add (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v + w
empty' := by simp
not_measurable' _ hi := by rw [Pi.add_apply, v.not_measurable hi, w.not_measurable hi, add_zero]
m_iUnion' f hf₁ hf₂ := HasSum.add (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.add MeasureTheory.VectorMeasure.add
instance instAdd : Add (VectorMeasure α M) :=
⟨add⟩
#align measure_theory.vector_measure.has_add MeasureTheory.VectorMeasure.instAdd
@[simp]
theorem coe_add (v w : VectorMeasure α M) : ⇑(v + w) = v + w := rfl
#align measure_theory.vector_measure.coe_add MeasureTheory.VectorMeasure.coe_add
theorem add_apply (v w : VectorMeasure α M) (i : Set α) : (v + w) i = v i + w i := rfl
#align measure_theory.vector_measure.add_apply MeasureTheory.VectorMeasure.add_apply
instance instAddCommMonoid : AddCommMonoid (VectorMeasure α M) :=
Function.Injective.addCommMonoid _ coe_injective coe_zero coe_add fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_monoid MeasureTheory.VectorMeasure.instAddCommMonoid
/-- `(⇑)` is an `AddMonoidHom`. -/
@[simps]
def coeFnAddMonoidHom : VectorMeasure α M →+ Set α → M where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
#align measure_theory.vector_measure.coe_fn_add_monoid_hom MeasureTheory.VectorMeasure.coeFnAddMonoidHom
end AddCommMonoid
section AddCommGroup
variable {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
/-- The negative of a vector measure is a vector measure. -/
def neg (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := -v
empty' := by simp
not_measurable' _ hi := by rw [Pi.neg_apply, neg_eq_zero, v.not_measurable hi]
m_iUnion' f hf₁ hf₂ := HasSum.neg <| v.m_iUnion hf₁ hf₂
#align measure_theory.vector_measure.neg MeasureTheory.VectorMeasure.neg
instance instNeg : Neg (VectorMeasure α M) :=
⟨neg⟩
#align measure_theory.vector_measure.has_neg MeasureTheory.VectorMeasure.instNeg
@[simp]
theorem coe_neg (v : VectorMeasure α M) : ⇑(-v) = -v := rfl
#align measure_theory.vector_measure.coe_neg MeasureTheory.VectorMeasure.coe_neg
theorem neg_apply (v : VectorMeasure α M) (i : Set α) : (-v) i = -v i := rfl
#align measure_theory.vector_measure.neg_apply MeasureTheory.VectorMeasure.neg_apply
/-- The difference of two vector measure is a vector measure. -/
def sub (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v - w
empty' := by simp
not_measurable' _ hi := by rw [Pi.sub_apply, v.not_measurable hi, w.not_measurable hi, sub_zero]
m_iUnion' f hf₁ hf₂ := HasSum.sub (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.sub MeasureTheory.VectorMeasure.sub
instance instSub : Sub (VectorMeasure α M) :=
⟨sub⟩
#align measure_theory.vector_measure.has_sub MeasureTheory.VectorMeasure.instSub
@[simp]
theorem coe_sub (v w : VectorMeasure α M) : ⇑(v - w) = v - w := rfl
#align measure_theory.vector_measure.coe_sub MeasureTheory.VectorMeasure.coe_sub
theorem sub_apply (v w : VectorMeasure α M) (i : Set α) : (v - w) i = v i - w i := rfl
#align measure_theory.vector_measure.sub_apply MeasureTheory.VectorMeasure.sub_apply
instance instAddCommGroup : AddCommGroup (VectorMeasure α M) :=
Function.Injective.addCommGroup _ coe_injective coe_zero coe_add coe_neg coe_sub
(fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_group MeasureTheory.VectorMeasure.instAddCommGroup
end AddCommGroup
section DistribMulAction
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
instance instDistribMulAction [ContinuousAdd M] : DistribMulAction R (VectorMeasure α M) :=
Function.Injective.distribMulAction coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.distrib_mul_action MeasureTheory.VectorMeasure.instDistribMulAction
end DistribMulAction
section Module
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M]
instance instModule [ContinuousAdd M] : Module R (VectorMeasure α M) :=
Function.Injective.module R coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.module MeasureTheory.VectorMeasure.instModule
end Module
end VectorMeasure
namespace Measure
/-- A finite measure coerced into a real function is a signed measure. -/
@[simps]
def toSignedMeasure (μ : Measure α) [hμ : IsFiniteMeasure μ] : SignedMeasure α where
measureOf' := fun s : Set α => if MeasurableSet s then (μ s).toReal else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' f hf₁ hf₂ := by
simp only [*, MeasurableSet.iUnion hf₁, if_true, measure_iUnion hf₂ hf₁]
rw [ENNReal.tsum_toReal_eq]
exacts [(summable_measure_toReal hf₁ hf₂).hasSum, fun _ ↦ measure_ne_top _ _]
#align measure_theory.measure.to_signed_measure MeasureTheory.Measure.toSignedMeasure
theorem toSignedMeasure_apply_measurable {μ : Measure α} [IsFiniteMeasure μ] {i : Set α}
(hi : MeasurableSet i) : μ.toSignedMeasure i = (μ i).toReal :=
if_pos hi
#align measure_theory.measure.to_signed_measure_apply_measurable MeasureTheory.Measure.toSignedMeasure_apply_measurable
-- Without this lemma, `singularPart_neg` in `MeasureTheory.Decomposition.Lebesgue` is
-- extremely slow
theorem toSignedMeasure_congr {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
(h : μ = ν) : μ.toSignedMeasure = ν.toSignedMeasure := by
congr
#align measure_theory.measure.to_signed_measure_congr MeasureTheory.Measure.toSignedMeasure_congr
theorem toSignedMeasure_eq_toSignedMeasure_iff {μ ν : Measure α} [IsFiniteMeasure μ]
[IsFiniteMeasure ν] : μ.toSignedMeasure = ν.toSignedMeasure ↔ μ = ν := by
refine ⟨fun h => ?_, fun h => ?_⟩
· ext1 i hi
have : μ.toSignedMeasure i = ν.toSignedMeasure i := by rw [h]
rwa [toSignedMeasure_apply_measurable hi, toSignedMeasure_apply_measurable hi,
ENNReal.toReal_eq_toReal] at this
<;> exact measure_ne_top _ _
· congr
#align measure_theory.measure.to_signed_measure_eq_to_signed_measure_iff MeasureTheory.Measure.toSignedMeasure_eq_toSignedMeasure_iff
@[simp]
theorem toSignedMeasure_zero : (0 : Measure α).toSignedMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_signed_measure_zero MeasureTheory.Measure.toSignedMeasure_zero
@[simp]
theorem toSignedMeasure_add (μ ν : Measure α) [IsFiniteMeasure μ] [IsFiniteMeasure ν] :
(μ + ν).toSignedMeasure = μ.toSignedMeasure + ν.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, add_apply,
ENNReal.toReal_add (ne_of_lt (measure_lt_top _ _)) (ne_of_lt (measure_lt_top _ _)),
VectorMeasure.add_apply, toSignedMeasure_apply_measurable hi,
toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_add MeasureTheory.Measure.toSignedMeasure_add
@[simp]
theorem toSignedMeasure_smul (μ : Measure α) [IsFiniteMeasure μ] (r : ℝ≥0) :
(r • μ).toSignedMeasure = r • μ.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, VectorMeasure.smul_apply,
toSignedMeasure_apply_measurable hi, coe_smul, Pi.smul_apply, ENNReal.toReal_smul]
#align measure_theory.measure.to_signed_measure_smul MeasureTheory.Measure.toSignedMeasure_smul
/-- A measure is a vector measure over `ℝ≥0∞`. -/
@[simps]
def toENNRealVectorMeasure (μ : Measure α) : VectorMeasure α ℝ≥0∞ where
measureOf' := fun i : Set α => if MeasurableSet i then μ i else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' _ hf₁ hf₂ := by
simp only
rw [Summable.hasSum_iff ENNReal.summable, if_pos (MeasurableSet.iUnion hf₁),
MeasureTheory.measure_iUnion hf₂ hf₁]
exact tsum_congr fun n => if_pos (hf₁ n)
#align measure_theory.measure.to_ennreal_vector_measure MeasureTheory.Measure.toENNRealVectorMeasure
theorem toENNRealVectorMeasure_apply_measurable {μ : Measure α} {i : Set α} (hi : MeasurableSet i) :
μ.toENNRealVectorMeasure i = μ i :=
if_pos hi
#align measure_theory.measure.to_ennreal_vector_measure_apply_measurable MeasureTheory.Measure.toENNRealVectorMeasure_apply_measurable
@[simp]
theorem toENNRealVectorMeasure_zero : (0 : Measure α).toENNRealVectorMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_ennreal_vector_measure_zero MeasureTheory.Measure.toENNRealVectorMeasure_zero
@[simp]
theorem toENNRealVectorMeasure_add (μ ν : Measure α) :
(μ + ν).toENNRealVectorMeasure = μ.toENNRealVectorMeasure + ν.toENNRealVectorMeasure := by
refine MeasureTheory.VectorMeasure.ext fun i hi => ?_
rw [toENNRealVectorMeasure_apply_measurable hi, add_apply, VectorMeasure.add_apply,
toENNRealVectorMeasure_apply_measurable hi, toENNRealVectorMeasure_apply_measurable hi]
#align measure_theory.measure.to_ennreal_vector_measure_add MeasureTheory.Measure.toENNRealVectorMeasure_add
theorem toSignedMeasure_sub_apply {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
{i : Set α} (hi : MeasurableSet i) :
(μ.toSignedMeasure - ν.toSignedMeasure) i = (μ i).toReal - (ν i).toReal := by
rw [VectorMeasure.sub_apply, toSignedMeasure_apply_measurable hi,
Measure.toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_sub_apply MeasureTheory.Measure.toSignedMeasure_sub_apply
end Measure
namespace VectorMeasure
open Measure
section
/-- A vector measure over `ℝ≥0∞` is a measure. -/
def ennrealToMeasure {_ : MeasurableSpace α} (v : VectorMeasure α ℝ≥0∞) : Measure α :=
ofMeasurable (fun s _ => v s) v.empty fun _ hf₁ hf₂ => v.of_disjoint_iUnion_nat hf₁ hf₂
#align measure_theory.vector_measure.ennreal_to_measure MeasureTheory.VectorMeasure.ennrealToMeasure
theorem ennrealToMeasure_apply {m : MeasurableSpace α} {v : VectorMeasure α ℝ≥0∞} {s : Set α}
(hs : MeasurableSet s) : ennrealToMeasure v s = v s := by
rw [ennrealToMeasure, ofMeasurable_apply _ hs]
#align measure_theory.vector_measure.ennreal_to_measure_apply MeasureTheory.VectorMeasure.ennrealToMeasure_apply
@[simp]
theorem _root_.MeasureTheory.Measure.toENNRealVectorMeasure_ennrealToMeasure
(μ : VectorMeasure α ℝ≥0∞) :
toENNRealVectorMeasure (ennrealToMeasure μ) = μ := ext fun s hs => by
rw [toENNRealVectorMeasure_apply_measurable hs, ennrealToMeasure_apply hs]
@[simp]
theorem ennrealToMeasure_toENNRealVectorMeasure (μ : Measure α) :
ennrealToMeasure (toENNRealVectorMeasure μ) = μ := Measure.ext fun s hs => by
rw [ennrealToMeasure_apply hs, toENNRealVectorMeasure_apply_measurable hs]
/-- The equiv between `VectorMeasure α ℝ≥0∞` and `Measure α` formed by
`MeasureTheory.VectorMeasure.ennrealToMeasure` and
`MeasureTheory.Measure.toENNRealVectorMeasure`. -/
@[simps]
def equivMeasure [MeasurableSpace α] : VectorMeasure α ℝ≥0∞ ≃ Measure α where
toFun := ennrealToMeasure
invFun := toENNRealVectorMeasure
left_inv := toENNRealVectorMeasure_ennrealToMeasure
right_inv := ennrealToMeasure_toENNRealVectorMeasure
#align measure_theory.vector_measure.equiv_measure MeasureTheory.VectorMeasure.equivMeasure
end
section
variable [MeasurableSpace α] [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable (v : VectorMeasure α M)
/-- The pushforward of a vector measure along a function. -/
def map (v : VectorMeasure α M) (f : α → β) : VectorMeasure β M :=
if hf : Measurable f then
{ measureOf' := fun s => if MeasurableSet s then v (f ⁻¹' s) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro g hg₁ hg₂
simp only
convert v.m_iUnion (fun i => hf (hg₁ i)) fun i j hij => (hg₂ hij).preimage _
· rw [if_pos (hg₁ _)]
· rw [Set.preimage_iUnion, if_pos (MeasurableSet.iUnion hg₁)] }
else 0
#align measure_theory.vector_measure.map MeasureTheory.VectorMeasure.map
theorem map_not_measurable {f : α → β} (hf : ¬Measurable f) : v.map f = 0 :=
dif_neg hf
#align measure_theory.vector_measure.map_not_measurable MeasureTheory.VectorMeasure.map_not_measurable
theorem map_apply {f : α → β} (hf : Measurable f) {s : Set β} (hs : MeasurableSet s) :
v.map f s = v (f ⁻¹' s) := by
rw [map, dif_pos hf]
exact if_pos hs
#align measure_theory.vector_measure.map_apply MeasureTheory.VectorMeasure.map_apply
@[simp]
theorem map_id : v.map id = v :=
ext fun i hi => by rw [map_apply v measurable_id hi, Set.preimage_id]
#align measure_theory.vector_measure.map_id MeasureTheory.VectorMeasure.map_id
@[simp]
theorem map_zero (f : α → β) : (0 : VectorMeasure α M).map f = 0 := by
by_cases hf : Measurable f
· ext i hi
rw [map_apply _ hf hi, zero_apply, zero_apply]
· exact dif_neg hf
#align measure_theory.vector_measure.map_zero MeasureTheory.VectorMeasure.map_zero
section
variable {N : Type*} [AddCommMonoid N] [TopologicalSpace N]
/-- Given a vector measure `v` on `M` and a continuous `AddMonoidHom` `f : M → N`, `f ∘ v` is a
vector measure on `N`. -/
def mapRange (v : VectorMeasure α M) (f : M →+ N) (hf : Continuous f) : VectorMeasure α N where
measureOf' s := f (v s)
empty' := by simp only; rw [empty, AddMonoidHom.map_zero]
not_measurable' i hi := by simp only; rw [not_measurable v hi, AddMonoidHom.map_zero]
m_iUnion' g hg₁ hg₂ := HasSum.map (v.m_iUnion hg₁ hg₂) f hf
#align measure_theory.vector_measure.map_range MeasureTheory.VectorMeasure.mapRange
@[simp]
theorem mapRange_apply {f : M →+ N} (hf : Continuous f) {s : Set α} : v.mapRange f hf s = f (v s) :=
rfl
#align measure_theory.vector_measure.map_range_apply MeasureTheory.VectorMeasure.mapRange_apply
@[simp]
theorem mapRange_id : v.mapRange (AddMonoidHom.id M) continuous_id = v := by
ext
rfl
#align measure_theory.vector_measure.map_range_id MeasureTheory.VectorMeasure.mapRange_id
@[simp]
theorem mapRange_zero {f : M →+ N} (hf : Continuous f) :
mapRange (0 : VectorMeasure α M) f hf = 0 := by
ext
simp
#align measure_theory.vector_measure.map_range_zero MeasureTheory.VectorMeasure.mapRange_zero
section ContinuousAdd
variable [ContinuousAdd M] [ContinuousAdd N]
@[simp]
theorem mapRange_add {v w : VectorMeasure α M} {f : M →+ N} (hf : Continuous f) :
(v + w).mapRange f hf = v.mapRange f hf + w.mapRange f hf := by
ext
simp
#align measure_theory.vector_measure.map_range_add MeasureTheory.VectorMeasure.mapRange_add
/-- Given a continuous `AddMonoidHom` `f : M → N`, `mapRangeHom` is the `AddMonoidHom` mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeHom (f : M →+ N) (hf : Continuous f) : VectorMeasure α M →+ VectorMeasure α N where
toFun v := v.mapRange f hf
map_zero' := mapRange_zero hf
map_add' _ _ := mapRange_add hf
#align measure_theory.vector_measure.map_range_hom MeasureTheory.VectorMeasure.mapRangeHom
end ContinuousAdd
section Module
variable {R : Type*} [Semiring R] [Module R M] [Module R N]
variable [ContinuousAdd M] [ContinuousAdd N] [ContinuousConstSMul R M] [ContinuousConstSMul R N]
/-- Given a continuous linear map `f : M → N`, `mapRangeₗ` is the linear map mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeₗ (f : M →ₗ[R] N) (hf : Continuous f) : VectorMeasure α M →ₗ[R] VectorMeasure α N where
toFun v := v.mapRange f.toAddMonoidHom hf
map_add' _ _ := mapRange_add hf
map_smul' := by
intros
ext
simp
#align measure_theory.vector_measure.map_rangeₗ MeasureTheory.VectorMeasure.mapRangeₗ
end Module
end
/-- The restriction of a vector measure on some set. -/
def restrict (v : VectorMeasure α M) (i : Set α) : VectorMeasure α M :=
if hi : MeasurableSet i then
{ measureOf' := fun s => if MeasurableSet s then v (s ∩ i) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro f hf₁ hf₂
simp only
convert v.m_iUnion (fun n => (hf₁ n).inter hi)
(hf₂.mono fun i j => Disjoint.mono inf_le_left inf_le_left)
· rw [if_pos (hf₁ _)]
· rw [Set.iUnion_inter, if_pos (MeasurableSet.iUnion hf₁)] }
else 0
#align measure_theory.vector_measure.restrict MeasureTheory.VectorMeasure.restrict
theorem restrict_not_measurable {i : Set α} (hi : ¬MeasurableSet i) : v.restrict i = 0 :=
dif_neg hi
#align measure_theory.vector_measure.restrict_not_measurable MeasureTheory.VectorMeasure.restrict_not_measurable
theorem restrict_apply {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j) :
v.restrict i j = v (j ∩ i) := by
rw [restrict, dif_pos hi]
exact if_pos hj
#align measure_theory.vector_measure.restrict_apply MeasureTheory.VectorMeasure.restrict_apply
theorem restrict_eq_self {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j)
(hij : j ⊆ i) : v.restrict i j = v j := by
rw [restrict_apply v hi hj, Set.inter_eq_left.2 hij]
#align measure_theory.vector_measure.restrict_eq_self MeasureTheory.VectorMeasure.restrict_eq_self
@[simp]
theorem restrict_empty : v.restrict ∅ = 0 :=
ext fun i hi => by
rw [restrict_apply v MeasurableSet.empty hi, Set.inter_empty, v.empty, zero_apply]
#align measure_theory.vector_measure.restrict_empty MeasureTheory.VectorMeasure.restrict_empty
@[simp]
theorem restrict_univ : v.restrict Set.univ = v :=
ext fun i hi => by rw [restrict_apply v MeasurableSet.univ hi, Set.inter_univ]
#align measure_theory.vector_measure.restrict_univ MeasureTheory.VectorMeasure.restrict_univ
@[simp]
theorem restrict_zero {i : Set α} : (0 : VectorMeasure α M).restrict i = 0 := by
by_cases hi : MeasurableSet i
· ext j hj
rw [restrict_apply 0 hi hj, zero_apply, zero_apply]
· exact dif_neg hi
#align measure_theory.vector_measure.restrict_zero MeasureTheory.VectorMeasure.restrict_zero
section ContinuousAdd
variable [ContinuousAdd M]
theorem map_add (v w : VectorMeasure α M) (f : α → β) : (v + w).map f = v.map f + w.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp [map, dif_neg hf]
#align measure_theory.vector_measure.map_add MeasureTheory.VectorMeasure.map_add
/-- `VectorMeasure.map` as an additive monoid homomorphism. -/
@[simps]
def mapGm (f : α → β) : VectorMeasure α M →+ VectorMeasure β M where
toFun v := v.map f
map_zero' := map_zero f
map_add' _ _ := map_add _ _ f
#align measure_theory.vector_measure.map_gm MeasureTheory.VectorMeasure.mapGm
theorem restrict_add (v w : VectorMeasure α M) (i : Set α) :
(v + w).restrict i = v.restrict i + w.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp [restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_add MeasureTheory.VectorMeasure.restrict_add
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictGm (i : Set α) : VectorMeasure α M →+ VectorMeasure α M where
toFun v := v.restrict i
map_zero' := restrict_zero
map_add' _ _ := restrict_add _ _ i
#align measure_theory.vector_measure.restrict_gm MeasureTheory.VectorMeasure.restrictGm
end ContinuousAdd
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
@[simp]
theorem map_smul {v : VectorMeasure α M} {f : α → β} (c : R) : (c • v).map f = c • v.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp only [map, dif_neg hf]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext i
simp
#align measure_theory.vector_measure.map_smul MeasureTheory.VectorMeasure.map_smul
@[simp]
theorem restrict_smul {v : VectorMeasure α M} {i : Set α} (c : R) :
(c • v).restrict i = c • v.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp only [restrict_not_measurable _ hi]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext j
simp
#align measure_theory.vector_measure.restrict_smul MeasureTheory.VectorMeasure.restrict_smul
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M] [ContinuousAdd M]
/-- `VectorMeasure.map` as a linear map. -/
@[simps]
def mapₗ (f : α → β) : VectorMeasure α M →ₗ[R] VectorMeasure β M where
toFun v := v.map f
map_add' _ _ := map_add _ _ f
map_smul' _ _ := map_smul _
#align measure_theory.vector_measure.mapₗ MeasureTheory.VectorMeasure.mapₗ
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictₗ (i : Set α) : VectorMeasure α M →ₗ[R] VectorMeasure α M where
toFun v := v.restrict i
map_add' _ _ := restrict_add _ _ i
map_smul' _ _ := restrict_smul _
#align measure_theory.vector_measure.restrictₗ MeasureTheory.VectorMeasure.restrictₗ
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
/-- Vector measures over a partially ordered monoid is partially ordered.
This definition is consistent with `Measure.instPartialOrder`. -/
instance instPartialOrder : PartialOrder (VectorMeasure α M) where
le v w := ∀ i, MeasurableSet i → v i ≤ w i
le_refl v i _ := le_rfl
le_trans u v w h₁ h₂ i hi := le_trans (h₁ i hi) (h₂ i hi)
le_antisymm v w h₁ h₂ := ext fun i hi => le_antisymm (h₁ i hi) (h₂ i hi)
variable {u v w : VectorMeasure α M}
theorem le_iff : v ≤ w ↔ ∀ i, MeasurableSet i → v i ≤ w i := Iff.rfl
#align measure_theory.vector_measure.le_iff MeasureTheory.VectorMeasure.le_iff
theorem le_iff' : v ≤ w ↔ ∀ i, v i ≤ w i := by
refine ⟨fun h i => ?_, fun h i _ => h i⟩
by_cases hi : MeasurableSet i
· exact h i hi
· rw [v.not_measurable hi, w.not_measurable hi]
#align measure_theory.vector_measure.le_iff' MeasureTheory.VectorMeasure.le_iff'
end
set_option quotPrecheck false in -- Porting note: error message suggested to do this
scoped[MeasureTheory]
notation:50 v " ≤[" i:50 "] " w:50 =>
MeasureTheory.VectorMeasure.restrict v i ≤ MeasureTheory.VectorMeasure.restrict w i
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
variable (v w : VectorMeasure α M)
theorem restrict_le_restrict_iff {i : Set α} (hi : MeasurableSet i) :
v ≤[i] w ↔ ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j :=
⟨fun h j hj₁ hj₂ => restrict_eq_self v hi hj₁ hj₂ ▸ restrict_eq_self w hi hj₁ hj₂ ▸ h j hj₁,
fun h => le_iff.1 fun _ hj =>
(restrict_apply v hi hj).symm ▸ (restrict_apply w hi hj).symm ▸
h (hj.inter hi) Set.inter_subset_right⟩
#align measure_theory.vector_measure.restrict_le_restrict_iff MeasureTheory.VectorMeasure.restrict_le_restrict_iff
theorem subset_le_of_restrict_le_restrict {i : Set α} (hi : MeasurableSet i) (hi₂ : v ≤[i] w)
{j : Set α} (hj : j ⊆ i) : v j ≤ w j := by
by_cases hj₁ : MeasurableSet j
· exact (restrict_le_restrict_iff _ _ hi).1 hi₂ hj₁ hj
· rw [v.not_measurable hj₁, w.not_measurable hj₁]
#align measure_theory.vector_measure.subset_le_of_restrict_le_restrict MeasureTheory.VectorMeasure.subset_le_of_restrict_le_restrict
theorem restrict_le_restrict_of_subset_le {i : Set α}
(h : ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j) : v ≤[i] w := by
by_cases hi : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi).2 h
· rw [restrict_not_measurable v hi, restrict_not_measurable w hi]
#align measure_theory.vector_measure.restrict_le_restrict_of_subset_le MeasureTheory.VectorMeasure.restrict_le_restrict_of_subset_le
theorem restrict_le_restrict_subset {i j : Set α} (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w)
(hij : j ⊆ i) : v ≤[j] w :=
restrict_le_restrict_of_subset_le v w fun _ _ hk₂ =>
subset_le_of_restrict_le_restrict v w hi₁ hi₂ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_restrict_subset MeasureTheory.VectorMeasure.restrict_le_restrict_subset
theorem le_restrict_empty : v ≤[∅] w := by
intro j _
rw [restrict_empty, restrict_empty]
#align measure_theory.vector_measure.le_restrict_empty MeasureTheory.VectorMeasure.le_restrict_empty
theorem le_restrict_univ_iff_le : v ≤[Set.univ] w ↔ v ≤ w := by
constructor
· intro h s hs
have := h s hs
rwa [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ] at this
· intro h s hs
rw [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ]
exact h s hs
#align measure_theory.vector_measure.le_restrict_univ_iff_le MeasureTheory.VectorMeasure.le_restrict_univ_iff_le
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommGroup M] [TopologicalAddGroup M]
variable (v w : VectorMeasure α M)
nonrec theorem neg_le_neg {i : Set α} (hi : MeasurableSet i) (h : v ≤[i] w) : -w ≤[i] -v := by
intro j hj₁
rw [restrict_apply _ hi hj₁, restrict_apply _ hi hj₁, neg_apply, neg_apply]
refine neg_le_neg ?_
rw [← restrict_apply _ hi hj₁, ← restrict_apply _ hi hj₁]
exact h j hj₁
#align measure_theory.vector_measure.neg_le_neg MeasureTheory.VectorMeasure.neg_le_neg
@[simp]
theorem neg_le_neg_iff {i : Set α} (hi : MeasurableSet i) : -w ≤[i] -v ↔ v ≤[i] w :=
⟨fun h => neg_neg v ▸ neg_neg w ▸ neg_le_neg _ _ hi h, fun h => neg_le_neg _ _ hi h⟩
#align measure_theory.vector_measure.neg_le_neg_iff MeasureTheory.VectorMeasure.neg_le_neg_iff
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M] [OrderClosedTopology M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem restrict_le_restrict_iUnion {f : ℕ → Set α} (hf₁ : ∀ n, MeasurableSet (f n))
(hf₂ : ∀ n, v ≤[f n] w) : v ≤[⋃ n, f n] w := by
refine restrict_le_restrict_of_subset_le v w fun a ha₁ ha₂ => ?_
have ha₃ : ⋃ n, a ∩ disjointed f n = a := by
rwa [← Set.inter_iUnion, iUnion_disjointed, Set.inter_eq_left]
have ha₄ : Pairwise (Disjoint on fun n => a ∩ disjointed f n) :=
(disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
rw [← ha₃, v.of_disjoint_iUnion_nat _ ha₄, w.of_disjoint_iUnion_nat _ ha₄]
· refine tsum_le_tsum (fun n => (restrict_le_restrict_iff v w (hf₁ n)).1 (hf₂ n) ?_ ?_) ?_ ?_
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact Set.Subset.trans Set.inter_subset_right (disjointed_subset _ _)
· refine (v.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· refine (w.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· intro n
exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact fun n => ha₁.inter (MeasurableSet.disjointed hf₁ n)
#align measure_theory.vector_measure.restrict_le_restrict_Union MeasureTheory.VectorMeasure.restrict_le_restrict_iUnion
theorem restrict_le_restrict_countable_iUnion [Countable β] {f : β → Set α}
(hf₁ : ∀ b, MeasurableSet (f b)) (hf₂ : ∀ b, v ≤[f b] w) : v ≤[⋃ b, f b] w := by
cases nonempty_encodable β
rw [← Encodable.iUnion_decode₂]
refine restrict_le_restrict_iUnion v w ?_ ?_
· intro n
measurability
· intro n
cases' Encodable.decode₂ β n with b
· simp
· simp [hf₂ b]
#align measure_theory.vector_measure.restrict_le_restrict_countable_Union MeasureTheory.VectorMeasure.restrict_le_restrict_countable_iUnion
theorem restrict_le_restrict_union (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w) (hj₁ : MeasurableSet j)
(hj₂ : v ≤[j] w) : v ≤[i ∪ j] w := by
rw [Set.union_eq_iUnion]
refine restrict_le_restrict_countable_iUnion v w ?_ ?_
· measurability
· rintro (_ | _) <;> simpa
#align measure_theory.vector_measure.restrict_le_restrict_union MeasureTheory.VectorMeasure.restrict_le_restrict_union
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem nonneg_of_zero_le_restrict (hi₂ : 0 ≤[i] v) : 0 ≤ v i := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonneg_of_zero_le_restrict MeasureTheory.VectorMeasure.nonneg_of_zero_le_restrict
theorem nonpos_of_restrict_le_zero (hi₂ : v ≤[i] 0) : v i ≤ 0 := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonpos_of_restrict_le_zero MeasureTheory.VectorMeasure.nonpos_of_restrict_le_zero
theorem zero_le_restrict_not_measurable (hi : ¬MeasurableSet i) : 0 ≤[i] v := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.zero_le_restrict_not_measurable MeasureTheory.VectorMeasure.zero_le_restrict_not_measurable
theorem restrict_le_zero_of_not_measurable (hi : ¬MeasurableSet i) : v ≤[i] 0 := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_le_zero_of_not_measurable MeasureTheory.VectorMeasure.restrict_le_zero_of_not_measurable
theorem measurable_of_not_zero_le_restrict (hi : ¬0 ≤[i] v) : MeasurableSet i :=
Not.imp_symm (zero_le_restrict_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_zero_le_restrict MeasureTheory.VectorMeasure.measurable_of_not_zero_le_restrict
theorem measurable_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) : MeasurableSet i :=
Not.imp_symm (restrict_le_zero_of_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_restrict_le_zero MeasureTheory.VectorMeasure.measurable_of_not_restrict_le_zero
theorem zero_le_restrict_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : 0 ≤[i] v) : 0 ≤[j] v :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.zero_le_restrict_subset MeasureTheory.VectorMeasure.zero_le_restrict_subset
theorem restrict_le_zero_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : v ≤[i] 0) : v ≤[j] 0 :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_zero_subset MeasureTheory.VectorMeasure.restrict_le_zero_subset
end
section
variable {M : Type*} [TopologicalSpace M] [LinearOrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem exists_pos_measure_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) :
∃ j : Set α, MeasurableSet j ∧ j ⊆ i ∧ 0 < v j := by
have hi₁ : MeasurableSet i := measurable_of_not_restrict_le_zero _ hi
rw [restrict_le_restrict_iff _ _ hi₁] at hi
push_neg at hi
exact hi
#align measure_theory.vector_measure.exists_pos_measure_of_not_restrict_le_zero MeasureTheory.VectorMeasure.exists_pos_measure_of_not_restrict_le_zero
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
[CovariantClass M M (· + ·) (· ≤ ·)] [ContinuousAdd M]
instance covariant_add_le :
CovariantClass (VectorMeasure α M) (VectorMeasure α M) (· + ·) (· ≤ ·) :=
⟨fun _ _ _ h i hi => add_le_add_left (h i hi) _⟩
#align measure_theory.vector_measure.covariant_add_le MeasureTheory.VectorMeasure.covariant_add_le
end
section
variable {L M N : Type*}
variable [AddCommMonoid L] [TopologicalSpace L] [AddCommMonoid M] [TopologicalSpace M]
[AddCommMonoid N] [TopologicalSpace N]
/-- A vector measure `v` is absolutely continuous with respect to a measure `μ` if for all sets
`s`, `μ s = 0`, we have `v s = 0`. -/
def AbsolutelyContinuous (v : VectorMeasure α M) (w : VectorMeasure α N) :=
∀ ⦃s : Set α⦄, w s = 0 → v s = 0
#align measure_theory.vector_measure.absolutely_continuous MeasureTheory.VectorMeasure.AbsolutelyContinuous
@[inherit_doc VectorMeasure.AbsolutelyContinuous]
scoped[MeasureTheory] infixl:50 " ≪ᵥ " => MeasureTheory.VectorMeasure.AbsolutelyContinuous
open MeasureTheory
namespace AbsolutelyContinuous
variable {v : VectorMeasure α M} {w : VectorMeasure α N}
theorem mk (h : ∀ ⦃s : Set α⦄, MeasurableSet s → w s = 0 → v s = 0) : v ≪ᵥ w := by
intro s hs
by_cases hmeas : MeasurableSet s
· exact h hmeas hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.mk MeasureTheory.VectorMeasure.AbsolutelyContinuous.mk
theorem eq {w : VectorMeasure α M} (h : v = w) : v ≪ᵥ w :=
fun _ hs => h.symm ▸ hs
#align measure_theory.vector_measure.absolutely_continuous.eq MeasureTheory.VectorMeasure.AbsolutelyContinuous.eq
@[refl]
theorem refl (v : VectorMeasure α M) : v ≪ᵥ v :=
eq rfl
#align measure_theory.vector_measure.absolutely_continuous.refl MeasureTheory.VectorMeasure.AbsolutelyContinuous.refl
@[trans]
theorem trans {u : VectorMeasure α L} {v : VectorMeasure α M} {w : VectorMeasure α N} (huv : u ≪ᵥ v)
(hvw : v ≪ᵥ w) : u ≪ᵥ w :=
fun _ hs => huv <| hvw hs
#align measure_theory.vector_measure.absolutely_continuous.trans MeasureTheory.VectorMeasure.AbsolutelyContinuous.trans
theorem zero (v : VectorMeasure α N) : (0 : VectorMeasure α M) ≪ᵥ v :=
fun s _ => VectorMeasure.zero_apply s
#align measure_theory.vector_measure.absolutely_continuous.zero MeasureTheory.VectorMeasure.AbsolutelyContinuous.zero
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : -v ≪ᵥ w := by
intro s hs
rw [neg_apply, h hs, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.neg_left MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : v ≪ᵥ -w := by
intro s hs
rw [neg_apply, neg_eq_zero] at hs
exact h hs
#align measure_theory.vector_measure.absolutely_continuous.neg_right MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_right
theorem add [ContinuousAdd M] {v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w)
(hv₂ : v₂ ≪ᵥ w) : v₁ + v₂ ≪ᵥ w := by
intro s hs
rw [add_apply, hv₁ hs, hv₂ hs, zero_add]
#align measure_theory.vector_measure.absolutely_continuous.add MeasureTheory.VectorMeasure.AbsolutelyContinuous.add
theorem sub {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w) (hv₂ : v₂ ≪ᵥ w) :
v₁ - v₂ ≪ᵥ w := by
intro s hs
rw [sub_apply, hv₁ hs, hv₂ hs, zero_sub, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.sub MeasureTheory.VectorMeasure.AbsolutelyContinuous.sub
theorem smul {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] {r : R}
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : r • v ≪ᵥ w := by
intro s hs
rw [smul_apply, h hs, smul_zero]
#align measure_theory.vector_measure.absolutely_continuous.smul MeasureTheory.VectorMeasure.AbsolutelyContinuous.smul
theorem map [MeasureSpace β] (h : v ≪ᵥ w) (f : α → β) : v.map f ≪ᵥ w.map f := by
by_cases hf : Measurable f
· refine mk fun s hs hws => ?_
rw [map_apply _ hf hs] at hws ⊢
exact h hws
· intro s _
rw [map_not_measurable v hf, zero_apply]
#align measure_theory.vector_measure.absolutely_continuous.map MeasureTheory.VectorMeasure.AbsolutelyContinuous.map
theorem ennrealToMeasure {μ : VectorMeasure α ℝ≥0∞} :
(∀ ⦃s : Set α⦄, μ.ennrealToMeasure s = 0 → v s = 0) ↔ v ≪ᵥ μ := by
constructor <;> intro h
· refine mk fun s hmeas hs => h ?_
rw [← hs, ennrealToMeasure_apply hmeas]
· intro s hs
by_cases hmeas : MeasurableSet s
· rw [ennrealToMeasure_apply hmeas] at hs
exact h hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.ennreal_to_measure MeasureTheory.VectorMeasure.AbsolutelyContinuous.ennrealToMeasure
end AbsolutelyContinuous
/-- Two vector measures `v` and `w` are said to be mutually singular if there exists a measurable
set `s`, such that for all `t ⊆ s`, `v t = 0` and for all `t ⊆ sᶜ`, `w t = 0`.
We note that we do not require the measurability of `t` in the definition since this makes it easier
to use. This is equivalent to the definition which requires measurability. To prove
`MutuallySingular` with the measurability condition, use
`MeasureTheory.VectorMeasure.MutuallySingular.mk`. -/
def MutuallySingular (v : VectorMeasure α M) (w : VectorMeasure α N) : Prop :=
∃ s : Set α, MeasurableSet s ∧ (∀ t ⊆ s, v t = 0) ∧ ∀ t ⊆ sᶜ, w t = 0
#align measure_theory.vector_measure.mutually_singular MeasureTheory.VectorMeasure.MutuallySingular
@[inherit_doc VectorMeasure.MutuallySingular]
scoped[MeasureTheory] infixl:60 " ⟂ᵥ " => MeasureTheory.VectorMeasure.MutuallySingular
namespace MutuallySingular
variable {v v₁ v₂ : VectorMeasure α M} {w w₁ w₂ : VectorMeasure α N}
theorem mk (s : Set α) (hs : MeasurableSet s) (h₁ : ∀ t ⊆ s, MeasurableSet t → v t = 0)
(h₂ : ∀ t ⊆ sᶜ, MeasurableSet t → w t = 0) : v ⟂ᵥ w := by
refine ⟨s, hs, fun t hst => ?_, fun t hst => ?_⟩ <;> by_cases ht : MeasurableSet t
· exact h₁ t hst ht
· exact not_measurable v ht
· exact h₂ t hst ht
· exact not_measurable w ht
#align measure_theory.vector_measure.mutually_singular.mk MeasureTheory.VectorMeasure.MutuallySingular.mk
theorem symm (h : v ⟂ᵥ w) : w ⟂ᵥ v :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨sᶜ, hmeas.compl, hs₂, fun t ht => hs₁ _ (compl_compl s ▸ ht : t ⊆ s)⟩
#align measure_theory.vector_measure.mutually_singular.symm MeasureTheory.VectorMeasure.MutuallySingular.symm
theorem zero_right : v ⟂ᵥ (0 : VectorMeasure α N) :=
⟨∅, MeasurableSet.empty, fun _ ht => (Set.subset_empty_iff.1 ht).symm ▸ v.empty,
fun _ _ => zero_apply _⟩
#align measure_theory.vector_measure.mutually_singular.zero_right MeasureTheory.VectorMeasure.MutuallySingular.zero_right
theorem zero_left : (0 : VectorMeasure α M) ⟂ᵥ w :=
zero_right.symm
#align measure_theory.vector_measure.mutually_singular.zero_left MeasureTheory.VectorMeasure.MutuallySingular.zero_left
theorem add_left [T2Space N] [ContinuousAdd M] (h₁ : v₁ ⟂ᵥ w) (h₂ : v₂ ⟂ᵥ w) : v₁ + v₂ ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h₁
obtain ⟨v, hmv, hv₁, hv₂⟩ := h₂
refine mk (u ∩ v) (hmu.inter hmv) (fun t ht _ => ?_) fun t ht hmt => ?_
· rw [add_apply, hu₁ _ (Set.subset_inter_iff.1 ht).1, hv₁ _ (Set.subset_inter_iff.1 ht).2,
zero_add]
· rw [Set.compl_inter] at ht
rw [(_ : t = uᶜ ∩ t ∪ vᶜ \ uᶜ ∩ t),
of_union _ (hmu.compl.inter hmt) ((hmv.compl.diff hmu.compl).inter hmt), hu₂, hv₂, add_zero]
· exact Set.Subset.trans Set.inter_subset_left diff_subset
· exact Set.inter_subset_left
· exact disjoint_sdiff_self_right.mono Set.inter_subset_left Set.inter_subset_left
· apply Set.Subset.antisymm <;> intro x hx
· by_cases hxu' : x ∈ uᶜ
· exact Or.inl ⟨hxu', hx⟩
rcases ht hx with (hxu | hxv)
exacts [False.elim (hxu' hxu), Or.inr ⟨⟨hxv, hxu'⟩, hx⟩]
· cases' hx with hx hx <;> exact hx.2
#align measure_theory.vector_measure.mutually_singular.add_left MeasureTheory.VectorMeasure.MutuallySingular.add_left
theorem add_right [T2Space M] [ContinuousAdd N] (h₁ : v ⟂ᵥ w₁) (h₂ : v ⟂ᵥ w₂) : v ⟂ᵥ w₁ + w₂ :=
(add_left h₁.symm h₂.symm).symm
#align measure_theory.vector_measure.mutually_singular.add_right MeasureTheory.VectorMeasure.MutuallySingular.add_right
theorem smul_right {R : Type*} [Semiring R] [DistribMulAction R N] [ContinuousConstSMul R N]
(r : R) (h : v ⟂ᵥ w) : v ⟂ᵥ r • w :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨s, hmeas, hs₁, fun t ht => by simp only [coe_smul, Pi.smul_apply, hs₂ t ht, smul_zero]⟩
#align measure_theory.vector_measure.mutually_singular.smul_right MeasureTheory.VectorMeasure.MutuallySingular.smul_right
theorem smul_left {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] (r : R)
(h : v ⟂ᵥ w) : r • v ⟂ᵥ w :=
(smul_right r h.symm).symm
#align measure_theory.vector_measure.mutually_singular.smul_left MeasureTheory.VectorMeasure.MutuallySingular.smul_left
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : -v ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h
refine ⟨u, hmu, fun s hs => ?_, hu₂⟩
rw [neg_apply v s, neg_eq_zero]
exact hu₁ s hs
#align measure_theory.vector_measure.mutually_singular.neg_left MeasureTheory.VectorMeasure.MutuallySingular.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : v ⟂ᵥ -w :=
h.symm.neg_left.symm
#align measure_theory.vector_measure.mutually_singular.neg_right MeasureTheory.VectorMeasure.MutuallySingular.neg_right
@[simp]
theorem neg_left_iff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} : -v ⟂ᵥ w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg v ▸ h.neg_left, neg_left⟩
#align measure_theory.vector_measure.mutually_singular.neg_left_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_left_iff
@[simp]
theorem neg_right_iff {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} : v ⟂ᵥ -w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg w ▸ h.neg_right, neg_right⟩
#align measure_theory.vector_measure.mutually_singular.neg_right_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_right_iff
end MutuallySingular
section Trim
/-- Restriction of a vector measure onto a sub-σ-algebra. -/
@[simps]
def trim {m n : MeasurableSpace α} (v : VectorMeasure α M) (hle : m ≤ n) :
@VectorMeasure α m M _ _ :=
@VectorMeasure.mk α m M _ _
(fun i => if MeasurableSet[m] i then v i else 0)
(by dsimp only; rw [if_pos (@MeasurableSet.empty _ m), v.empty])
(fun i hi => by dsimp only; rw [if_neg hi])
(fun f hf₁ hf₂ => by
dsimp only
have hf₁' : ∀ k, MeasurableSet[n] (f k) := fun k => hle _ (hf₁ k)
convert v.m_iUnion hf₁' hf₂ using 1
· ext n
rw [if_pos (hf₁ n)]
· rw [if_pos (@MeasurableSet.iUnion _ _ m _ _ hf₁)])
#align measure_theory.vector_measure.trim MeasureTheory.VectorMeasure.trim
variable {n : MeasurableSpace α} {v : VectorMeasure α M}
theorem trim_eq_self : v.trim le_rfl = v := by
ext i hi
exact if_pos hi
#align measure_theory.vector_measure.trim_eq_self MeasureTheory.VectorMeasure.trim_eq_self
@[simp]
| Mathlib/MeasureTheory/Measure/VectorMeasure.lean | 1,264 | 1,266 | theorem zero_trim (hle : m ≤ n) : (0 : VectorMeasure α M).trim hle = 0 := by |
ext i hi
exact if_pos hi
|
/-
Copyright (c) 2021 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Winston Yin
-/
import Mathlib.Analysis.SpecialFunctions.Integrals
import Mathlib.Topology.MetricSpace.Contracting
#align_import analysis.ODE.picard_lindelof from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Picard-Lindelöf (Cauchy-Lipschitz) Theorem
In this file we prove that an ordinary differential equation $\dot x=v(t, x)$ such that $v$ is
Lipschitz continuous in $x$ and continuous in $t$ has a local solution, see
`IsPicardLindelof.exists_forall_hasDerivWithinAt_Icc_eq`.
As a corollary, we prove that a time-independent locally continuously differentiable ODE has a
local solution.
## Implementation notes
In order to split the proof into small lemmas, we introduce a structure `PicardLindelof` that holds
all assumptions of the main theorem. This structure and lemmas in the `PicardLindelof` namespace
should be treated as private implementation details. This is not to be confused with the `Prop`-
valued structure `IsPicardLindelof`, which holds the long hypotheses of the Picard-Lindelöf
theorem for actual use as part of the public API.
We only prove existence of a solution in this file. For uniqueness see `ODE_solution_unique` and
related theorems in `Mathlib/Analysis/ODE/Gronwall.lean`.
## Tags
differential equation
-/
open Filter Function Set Metric TopologicalSpace intervalIntegral MeasureTheory
open MeasureTheory.MeasureSpace (volume)
open scoped Filter Topology NNReal ENNReal Nat Interval
noncomputable section
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
/-- `Prop` structure holding the hypotheses of the Picard-Lindelöf theorem.
The similarly named `PicardLindelof` structure is part of the internal API for convenience, so as
not to constantly invoke choice, but is not intended for public use. -/
structure IsPicardLindelof {E : Type*} [NormedAddCommGroup E] (v : ℝ → E → E) (tMin t₀ tMax : ℝ)
(x₀ : E) (L : ℝ≥0) (R C : ℝ) : Prop where
ht₀ : t₀ ∈ Icc tMin tMax
hR : 0 ≤ R
lipschitz : ∀ t ∈ Icc tMin tMax, LipschitzOnWith L (v t) (closedBall x₀ R)
cont : ∀ x ∈ closedBall x₀ R, ContinuousOn (fun t : ℝ => v t x) (Icc tMin tMax)
norm_le : ∀ t ∈ Icc tMin tMax, ∀ x ∈ closedBall x₀ R, ‖v t x‖ ≤ C
C_mul_le_R : (C : ℝ) * max (tMax - t₀) (t₀ - tMin) ≤ R
#align is_picard_lindelof IsPicardLindelof
/-- This structure holds arguments of the Picard-Lipschitz (Cauchy-Lipschitz) theorem. It is part of
the internal API for convenience, so as not to constantly invoke choice. Unless you want to use one
of the auxiliary lemmas, use `IsPicardLindelof.exists_forall_hasDerivWithinAt_Icc_eq` instead
of using this structure.
The similarly named `IsPicardLindelof` is a bundled `Prop` holding the long hypotheses of the
Picard-Lindelöf theorem as named arguments. It is used as part of the public API.
-/
structure PicardLindelof (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E] where
toFun : ℝ → E → E
(tMin tMax : ℝ)
t₀ : Icc tMin tMax
x₀ : E
(C R L : ℝ≥0)
isPicardLindelof : IsPicardLindelof toFun tMin t₀ tMax x₀ L R C
#align picard_lindelof PicardLindelof
namespace PicardLindelof
variable (v : PicardLindelof E)
instance : CoeFun (PicardLindelof E) fun _ => ℝ → E → E :=
⟨toFun⟩
instance : Inhabited (PicardLindelof E) :=
⟨⟨0, 0, 0, ⟨0, le_rfl, le_rfl⟩, 0, 0, 0, 0,
{ ht₀ := by rw [Subtype.coe_mk, Icc_self]; exact mem_singleton _
hR := le_rfl
lipschitz := fun t _ => (LipschitzWith.const 0).lipschitzOnWith _
cont := fun _ _ => by simpa only [Pi.zero_apply] using continuousOn_const
norm_le := fun t _ x _ => norm_zero.le
C_mul_le_R := (zero_mul _).le }⟩⟩
theorem tMin_le_tMax : v.tMin ≤ v.tMax :=
v.t₀.2.1.trans v.t₀.2.2
#align picard_lindelof.t_min_le_t_max PicardLindelof.tMin_le_tMax
protected theorem nonempty_Icc : (Icc v.tMin v.tMax).Nonempty :=
nonempty_Icc.2 v.tMin_le_tMax
#align picard_lindelof.nonempty_Icc PicardLindelof.nonempty_Icc
protected theorem lipschitzOnWith {t} (ht : t ∈ Icc v.tMin v.tMax) :
LipschitzOnWith v.L (v t) (closedBall v.x₀ v.R) :=
v.isPicardLindelof.lipschitz t ht
#align picard_lindelof.lipschitz_on_with PicardLindelof.lipschitzOnWith
protected theorem continuousOn :
ContinuousOn (uncurry v) (Icc v.tMin v.tMax ×ˢ closedBall v.x₀ v.R) :=
have : ContinuousOn (uncurry (flip v)) (closedBall v.x₀ v.R ×ˢ Icc v.tMin v.tMax) :=
continuousOn_prod_of_continuousOn_lipschitzOnWith _ v.L v.isPicardLindelof.cont
v.isPicardLindelof.lipschitz
this.comp continuous_swap.continuousOn (preimage_swap_prod _ _).symm.subset
#align picard_lindelof.continuous_on PicardLindelof.continuousOn
theorem norm_le {t : ℝ} (ht : t ∈ Icc v.tMin v.tMax) {x : E} (hx : x ∈ closedBall v.x₀ v.R) :
‖v t x‖ ≤ v.C :=
v.isPicardLindelof.norm_le _ ht _ hx
#align picard_lindelof.norm_le PicardLindelof.norm_le
/-- The maximum of distances from `t₀` to the endpoints of `[tMin, tMax]`. -/
def tDist : ℝ :=
max (v.tMax - v.t₀) (v.t₀ - v.tMin)
#align picard_lindelof.t_dist PicardLindelof.tDist
theorem tDist_nonneg : 0 ≤ v.tDist :=
le_max_iff.2 <| Or.inl <| sub_nonneg.2 v.t₀.2.2
#align picard_lindelof.t_dist_nonneg PicardLindelof.tDist_nonneg
theorem dist_t₀_le (t : Icc v.tMin v.tMax) : dist t v.t₀ ≤ v.tDist := by
rw [Subtype.dist_eq, Real.dist_eq]
rcases le_total t v.t₀ with ht | ht
· rw [abs_of_nonpos (sub_nonpos.2 <| Subtype.coe_le_coe.2 ht), neg_sub]
exact (sub_le_sub_left t.2.1 _).trans (le_max_right _ _)
· rw [abs_of_nonneg (sub_nonneg.2 <| Subtype.coe_le_coe.2 ht)]
exact (sub_le_sub_right t.2.2 _).trans (le_max_left _ _)
#align picard_lindelof.dist_t₀_le PicardLindelof.dist_t₀_le
/-- Projection $ℝ → [t_{\min}, t_{\max}]$ sending $(-∞, t_{\min}]$ to $t_{\min}$ and $[t_{\max}, ∞)$
to $t_{\max}$. -/
def proj : ℝ → Icc v.tMin v.tMax :=
projIcc v.tMin v.tMax v.tMin_le_tMax
#align picard_lindelof.proj PicardLindelof.proj
theorem proj_coe (t : Icc v.tMin v.tMax) : v.proj t = t :=
projIcc_val _ _
#align picard_lindelof.proj_coe PicardLindelof.proj_coe
theorem proj_of_mem {t : ℝ} (ht : t ∈ Icc v.tMin v.tMax) : ↑(v.proj t) = t := by
simp only [proj, projIcc_of_mem v.tMin_le_tMax ht]
#align picard_lindelof.proj_of_mem PicardLindelof.proj_of_mem
@[continuity]
theorem continuous_proj : Continuous v.proj :=
continuous_projIcc
#align picard_lindelof.continuous_proj PicardLindelof.continuous_proj
/-- The space of curves $γ \colon [t_{\min}, t_{\max}] \to E$ such that $γ(t₀) = x₀$ and $γ$ is
Lipschitz continuous with constant $C$. The map sending $γ$ to
$\mathbf Pγ(t)=x₀ + ∫_{t₀}^{t} v(τ, γ(τ))\,dτ$ is a contracting map on this space, and its fixed
point is a solution of the ODE $\dot x=v(t, x)$. -/
structure FunSpace where
toFun : Icc v.tMin v.tMax → E
map_t₀' : toFun v.t₀ = v.x₀
lipschitz' : LipschitzWith v.C toFun
#align picard_lindelof.fun_space PicardLindelof.FunSpace
namespace FunSpace
variable {v} (f : FunSpace v)
instance : CoeFun (FunSpace v) fun _ => Icc v.tMin v.tMax → E :=
⟨toFun⟩
instance : Inhabited v.FunSpace :=
⟨⟨fun _ => v.x₀, rfl, (LipschitzWith.const _).weaken (zero_le _)⟩⟩
protected theorem lipschitz : LipschitzWith v.C f :=
f.lipschitz'
#align picard_lindelof.fun_space.lipschitz PicardLindelof.FunSpace.lipschitz
protected theorem continuous : Continuous f :=
f.lipschitz.continuous
#align picard_lindelof.fun_space.continuous PicardLindelof.FunSpace.continuous
/-- Each curve in `PicardLindelof.FunSpace` is continuous. -/
def toContinuousMap : v.FunSpace ↪ C(Icc v.tMin v.tMax, E) :=
⟨fun f => ⟨f, f.continuous⟩, fun f g h => by cases f; cases g; simpa using h⟩
#align picard_lindelof.fun_space.to_continuous_map PicardLindelof.FunSpace.toContinuousMap
instance : MetricSpace v.FunSpace :=
MetricSpace.induced toContinuousMap toContinuousMap.injective inferInstance
theorem uniformInducing_toContinuousMap : UniformInducing (@toContinuousMap _ _ _ v) :=
⟨rfl⟩
#align picard_lindelof.fun_space.uniform_inducing_to_continuous_map PicardLindelof.FunSpace.uniformInducing_toContinuousMap
theorem range_toContinuousMap :
range toContinuousMap =
{f : C(Icc v.tMin v.tMax, E) | f v.t₀ = v.x₀ ∧ LipschitzWith v.C f} := by
ext f; constructor
· rintro ⟨⟨f, hf₀, hf_lip⟩, rfl⟩; exact ⟨hf₀, hf_lip⟩
· rcases f with ⟨f, hf⟩; rintro ⟨hf₀, hf_lip⟩; exact ⟨⟨f, hf₀, hf_lip⟩, rfl⟩
#align picard_lindelof.fun_space.range_to_continuous_map PicardLindelof.FunSpace.range_toContinuousMap
theorem map_t₀ : f v.t₀ = v.x₀ :=
f.map_t₀'
#align picard_lindelof.fun_space.map_t₀ PicardLindelof.FunSpace.map_t₀
protected theorem mem_closedBall (t : Icc v.tMin v.tMax) : f t ∈ closedBall v.x₀ v.R :=
calc
dist (f t) v.x₀ = dist (f t) (f.toFun v.t₀) := by rw [f.map_t₀']
_ ≤ v.C * dist t v.t₀ := f.lipschitz.dist_le_mul _ _
_ ≤ v.C * v.tDist := mul_le_mul_of_nonneg_left (v.dist_t₀_le _) v.C.2
_ ≤ v.R := v.isPicardLindelof.C_mul_le_R
#align picard_lindelof.fun_space.mem_closed_ball PicardLindelof.FunSpace.mem_closedBall
/-- Given a curve $γ \colon [t_{\min}, t_{\max}] → E$, `PicardLindelof.vComp` is the function
$F(t)=v(π t, γ(π t))$, where `π` is the projection $ℝ → [t_{\min}, t_{\max}]$. The integral of this
function is the image of `γ` under the contracting map we are going to define below. -/
def vComp (t : ℝ) : E :=
v (v.proj t) (f (v.proj t))
#align picard_lindelof.fun_space.v_comp PicardLindelof.FunSpace.vComp
theorem vComp_apply_coe (t : Icc v.tMin v.tMax) : f.vComp t = v t (f t) := by
simp only [vComp, proj_coe]
#align picard_lindelof.fun_space.v_comp_apply_coe PicardLindelof.FunSpace.vComp_apply_coe
| Mathlib/Analysis/ODE/PicardLindelof.lean | 226 | 229 | theorem continuous_vComp : Continuous f.vComp := by |
have := (continuous_subtype_val.prod_mk f.continuous).comp v.continuous_proj
refine ContinuousOn.comp_continuous v.continuousOn this fun x => ?_
exact ⟨(v.proj x).2, f.mem_closedBall _⟩
|
/-
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.Data.Finset.Sort
import Mathlib.Data.Fin.VecNotation
import Mathlib.Data.Sign
import Mathlib.LinearAlgebra.AffineSpace.Combination
import Mathlib.LinearAlgebra.AffineSpace.AffineEquiv
import Mathlib.LinearAlgebra.Basis.VectorSpace
#align_import linear_algebra.affine_space.independent from "leanprover-community/mathlib"@"2de9c37fa71dde2f1c6feff19876dd6a7b1519f0"
/-!
# Affine independence
This file defines affinely independent families of points.
## Main definitions
* `AffineIndependent` defines affinely independent families of points
as those where no nontrivial weighted subtraction is `0`. This is
proved equivalent to two other formulations: linear independence of
the results of subtracting a base point in the family from the other
points in the family, or any equal affine combinations having the
same weights. A bundled type `Simplex` is provided for finite
affinely independent families of points, with an abbreviation
`Triangle` for the case of three points.
## References
* https://en.wikipedia.org/wiki/Affine_space
-/
noncomputable section
open Finset Function
open scoped Affine
section AffineIndependent
variable (k : Type*) {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
variable [AffineSpace V P] {ι : Type*}
/-- An indexed family is said to be affinely independent if no
nontrivial weighted subtractions (where the sum of weights is 0) are
0. -/
def AffineIndependent (p : ι → P) : Prop :=
∀ (s : Finset ι) (w : ι → k),
∑ i ∈ s, w i = 0 → s.weightedVSub p w = (0 : V) → ∀ i ∈ s, w i = 0
#align affine_independent AffineIndependent
/-- The definition of `AffineIndependent`. -/
theorem affineIndependent_def (p : ι → P) :
AffineIndependent k p ↔
∀ (s : Finset ι) (w : ι → k),
∑ i ∈ s, w i = 0 → s.weightedVSub p w = (0 : V) → ∀ i ∈ s, w i = 0 :=
Iff.rfl
#align affine_independent_def affineIndependent_def
/-- A family with at most one point is affinely independent. -/
theorem affineIndependent_of_subsingleton [Subsingleton ι] (p : ι → P) : AffineIndependent k p :=
fun _ _ h _ i hi => Fintype.eq_of_subsingleton_of_sum_eq h i hi
#align affine_independent_of_subsingleton affineIndependent_of_subsingleton
/-- A family indexed by a `Fintype` is affinely independent if and
only if no nontrivial weighted subtractions over `Finset.univ` (where
the sum of the weights is 0) are 0. -/
theorem affineIndependent_iff_of_fintype [Fintype ι] (p : ι → P) :
AffineIndependent k p ↔
∀ w : ι → k, ∑ i, w i = 0 → Finset.univ.weightedVSub p w = (0 : V) → ∀ i, w i = 0 := by
constructor
· exact fun h w hw hs i => h Finset.univ w hw hs i (Finset.mem_univ _)
· intro h s w hw hs i hi
rw [Finset.weightedVSub_indicator_subset _ _ (Finset.subset_univ s)] at hs
rw [← Finset.sum_indicator_subset _ (Finset.subset_univ s)] at hw
replace h := h ((↑s : Set ι).indicator w) hw hs i
simpa [hi] using h
#align affine_independent_iff_of_fintype affineIndependent_iff_of_fintype
/-- A family is affinely independent if and only if the differences
from a base point in that family are linearly independent. -/
theorem affineIndependent_iff_linearIndependent_vsub (p : ι → P) (i1 : ι) :
AffineIndependent k p ↔ LinearIndependent k fun i : { x // x ≠ i1 } => (p i -ᵥ p i1 : V) := by
classical
constructor
· intro h
rw [linearIndependent_iff']
intro s g hg i hi
set f : ι → k := fun x => if hx : x = i1 then -∑ y ∈ s, g y else g ⟨x, hx⟩ with hfdef
let s2 : Finset ι := insert i1 (s.map (Embedding.subtype _))
have hfg : ∀ x : { x // x ≠ i1 }, g x = f x := by
intro x
rw [hfdef]
dsimp only
erw [dif_neg x.property, Subtype.coe_eta]
rw [hfg]
have hf : ∑ ι ∈ s2, f ι = 0 := by
rw [Finset.sum_insert
(Finset.not_mem_map_subtype_of_not_property s (Classical.not_not.2 rfl)),
Finset.sum_subtype_map_embedding fun x _ => (hfg x).symm]
rw [hfdef]
dsimp only
rw [dif_pos rfl]
exact neg_add_self _
have hs2 : s2.weightedVSub p f = (0 : V) := by
set f2 : ι → V := fun x => f x • (p x -ᵥ p i1) with hf2def
set g2 : { x // x ≠ i1 } → V := fun x => g x • (p x -ᵥ p i1)
have hf2g2 : ∀ x : { x // x ≠ i1 }, f2 x = g2 x := by
simp only [g2, hf2def]
refine fun x => ?_
rw [hfg]
rw [Finset.weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero s2 f p hf (p i1),
Finset.weightedVSubOfPoint_insert, Finset.weightedVSubOfPoint_apply,
Finset.sum_subtype_map_embedding fun x _ => hf2g2 x]
exact hg
exact h s2 f hf hs2 i (Finset.mem_insert_of_mem (Finset.mem_map.2 ⟨i, hi, rfl⟩))
· intro h
rw [linearIndependent_iff'] at h
intro s w hw hs i hi
rw [Finset.weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero s w p hw (p i1), ←
s.weightedVSubOfPoint_erase w p i1, Finset.weightedVSubOfPoint_apply] at hs
let f : ι → V := fun i => w i • (p i -ᵥ p i1)
have hs2 : (∑ i ∈ (s.erase i1).subtype fun i => i ≠ i1, f i) = 0 := by
rw [← hs]
convert Finset.sum_subtype_of_mem f fun x => Finset.ne_of_mem_erase
have h2 := h ((s.erase i1).subtype fun i => i ≠ i1) (fun x => w x) hs2
simp_rw [Finset.mem_subtype] at h2
have h2b : ∀ i ∈ s, i ≠ i1 → w i = 0 := fun i his hi =>
h2 ⟨i, hi⟩ (Finset.mem_erase_of_ne_of_mem hi his)
exact Finset.eq_zero_of_sum_eq_zero hw h2b i hi
#align affine_independent_iff_linear_independent_vsub affineIndependent_iff_linearIndependent_vsub
/-- A set is affinely independent if and only if the differences from
a base point in that set are linearly independent. -/
theorem affineIndependent_set_iff_linearIndependent_vsub {s : Set P} {p₁ : P} (hp₁ : p₁ ∈ s) :
AffineIndependent k (fun p => p : s → P) ↔
LinearIndependent k (fun v => v : (fun p => (p -ᵥ p₁ : V)) '' (s \ {p₁}) → V) := by
rw [affineIndependent_iff_linearIndependent_vsub k (fun p => p : s → P) ⟨p₁, hp₁⟩]
constructor
· intro h
have hv : ∀ v : (fun p => (p -ᵥ p₁ : V)) '' (s \ {p₁}), (v : V) +ᵥ p₁ ∈ s \ {p₁} := fun v =>
(vsub_left_injective p₁).mem_set_image.1 ((vadd_vsub (v : V) p₁).symm ▸ v.property)
let f : (fun p : P => (p -ᵥ p₁ : V)) '' (s \ {p₁}) → { x : s // x ≠ ⟨p₁, hp₁⟩ } := fun x =>
⟨⟨(x : V) +ᵥ p₁, Set.mem_of_mem_diff (hv x)⟩, fun hx =>
Set.not_mem_of_mem_diff (hv x) (Subtype.ext_iff.1 hx)⟩
convert h.comp f fun x1 x2 hx =>
Subtype.ext (vadd_right_cancel p₁ (Subtype.ext_iff.1 (Subtype.ext_iff.1 hx)))
ext v
exact (vadd_vsub (v : V) p₁).symm
· intro h
let f : { x : s // x ≠ ⟨p₁, hp₁⟩ } → (fun p : P => (p -ᵥ p₁ : V)) '' (s \ {p₁}) := fun x =>
⟨((x : s) : P) -ᵥ p₁, ⟨x, ⟨⟨(x : s).property, fun hx => x.property (Subtype.ext hx)⟩, rfl⟩⟩⟩
convert h.comp f fun x1 x2 hx =>
Subtype.ext (Subtype.ext (vsub_left_cancel (Subtype.ext_iff.1 hx)))
#align affine_independent_set_iff_linear_independent_vsub affineIndependent_set_iff_linearIndependent_vsub
/-- A set of nonzero vectors is linearly independent if and only if,
given a point `p₁`, the vectors added to `p₁` and `p₁` itself are
affinely independent. -/
theorem linearIndependent_set_iff_affineIndependent_vadd_union_singleton {s : Set V}
(hs : ∀ v ∈ s, v ≠ (0 : V)) (p₁ : P) : LinearIndependent k (fun v => v : s → V) ↔
AffineIndependent k (fun p => p : ({p₁} ∪ (fun v => v +ᵥ p₁) '' s : Set P) → P) := by
rw [affineIndependent_set_iff_linearIndependent_vsub k
(Set.mem_union_left _ (Set.mem_singleton p₁))]
have h : (fun p => (p -ᵥ p₁ : V)) '' (({p₁} ∪ (fun v => v +ᵥ p₁) '' s) \ {p₁}) = s := by
simp_rw [Set.union_diff_left, Set.image_diff (vsub_left_injective p₁), Set.image_image,
Set.image_singleton, vsub_self, vadd_vsub, Set.image_id']
exact Set.diff_singleton_eq_self fun h => hs 0 h rfl
rw [h]
#align linear_independent_set_iff_affine_independent_vadd_union_singleton linearIndependent_set_iff_affineIndependent_vadd_union_singleton
/-- A family is affinely independent if and only if any affine
combinations (with sum of weights 1) that evaluate to the same point
have equal `Set.indicator`. -/
theorem affineIndependent_iff_indicator_eq_of_affineCombination_eq (p : ι → P) :
AffineIndependent k p ↔
∀ (s1 s2 : Finset ι) (w1 w2 : ι → k),
∑ i ∈ s1, w1 i = 1 →
∑ i ∈ s2, w2 i = 1 →
s1.affineCombination k p w1 = s2.affineCombination k p w2 →
Set.indicator (↑s1) w1 = Set.indicator (↑s2) w2 := by
classical
constructor
· intro ha s1 s2 w1 w2 hw1 hw2 heq
ext i
by_cases hi : i ∈ s1 ∪ s2
· rw [← sub_eq_zero]
rw [← Finset.sum_indicator_subset w1 (s1.subset_union_left (s₂:=s2))] at hw1
rw [← Finset.sum_indicator_subset w2 (s1.subset_union_right)] at hw2
have hws : (∑ i ∈ s1 ∪ s2, (Set.indicator (↑s1) w1 - Set.indicator (↑s2) w2) i) = 0 := by
simp [hw1, hw2]
rw [Finset.affineCombination_indicator_subset w1 p (s1.subset_union_left (s₂:=s2)),
Finset.affineCombination_indicator_subset w2 p s1.subset_union_right,
← @vsub_eq_zero_iff_eq V, Finset.affineCombination_vsub] at heq
exact ha (s1 ∪ s2) (Set.indicator (↑s1) w1 - Set.indicator (↑s2) w2) hws heq i hi
· rw [← Finset.mem_coe, Finset.coe_union] at hi
have h₁ : Set.indicator (↑s1) w1 i = 0 := by
simp only [Set.indicator, Finset.mem_coe, ite_eq_right_iff]
intro h
by_contra
exact (mt (@Set.mem_union_left _ i ↑s1 ↑s2) hi) h
have h₂ : Set.indicator (↑s2) w2 i = 0 := by
simp only [Set.indicator, Finset.mem_coe, ite_eq_right_iff]
intro h
by_contra
exact (mt (@Set.mem_union_right _ i ↑s2 ↑s1) hi) h
simp [h₁, h₂]
· intro ha s w hw hs i0 hi0
let w1 : ι → k := Function.update (Function.const ι 0) i0 1
have hw1 : ∑ i ∈ s, w1 i = 1 := by
rw [Finset.sum_update_of_mem hi0]
simp only [Finset.sum_const_zero, add_zero, const_apply]
have hw1s : s.affineCombination k p w1 = p i0 :=
s.affineCombination_of_eq_one_of_eq_zero w1 p hi0 (Function.update_same _ _ _)
fun _ _ hne => Function.update_noteq hne _ _
let w2 := w + w1
have hw2 : ∑ i ∈ s, w2 i = 1 := by
simp_all only [w2, Pi.add_apply, Finset.sum_add_distrib, zero_add]
have hw2s : s.affineCombination k p w2 = p i0 := by
simp_all only [w2, ← Finset.weightedVSub_vadd_affineCombination, zero_vadd]
replace ha := ha s s w2 w1 hw2 hw1 (hw1s.symm ▸ hw2s)
have hws : w2 i0 - w1 i0 = 0 := by
rw [← Finset.mem_coe] at hi0
rw [← Set.indicator_of_mem hi0 w2, ← Set.indicator_of_mem hi0 w1, ha, sub_self]
simpa [w2] using hws
#align affine_independent_iff_indicator_eq_of_affine_combination_eq affineIndependent_iff_indicator_eq_of_affineCombination_eq
/-- A finite family is affinely independent if and only if any affine
combinations (with sum of weights 1) that evaluate to the same point are equal. -/
theorem affineIndependent_iff_eq_of_fintype_affineCombination_eq [Fintype ι] (p : ι → P) :
AffineIndependent k p ↔ ∀ w1 w2 : ι → k, ∑ i, w1 i = 1 → ∑ i, w2 i = 1 →
Finset.univ.affineCombination k p w1 = Finset.univ.affineCombination k p w2 → w1 = w2 := by
rw [affineIndependent_iff_indicator_eq_of_affineCombination_eq]
constructor
· intro h w1 w2 hw1 hw2 hweq
simpa only [Set.indicator_univ, Finset.coe_univ] using h _ _ w1 w2 hw1 hw2 hweq
· intro h s1 s2 w1 w2 hw1 hw2 hweq
have hw1' : (∑ i, (s1 : Set ι).indicator w1 i) = 1 := by
rwa [Finset.sum_indicator_subset _ (Finset.subset_univ s1)]
have hw2' : (∑ i, (s2 : Set ι).indicator w2 i) = 1 := by
rwa [Finset.sum_indicator_subset _ (Finset.subset_univ s2)]
rw [Finset.affineCombination_indicator_subset w1 p (Finset.subset_univ s1),
Finset.affineCombination_indicator_subset w2 p (Finset.subset_univ s2)] at hweq
exact h _ _ hw1' hw2' hweq
#align affine_independent_iff_eq_of_fintype_affine_combination_eq affineIndependent_iff_eq_of_fintype_affineCombination_eq
variable {k}
/-- If we single out one member of an affine-independent family of points and affinely transport
all others along the line joining them to this member, the resulting new family of points is affine-
independent.
This is the affine version of `LinearIndependent.units_smul`. -/
theorem AffineIndependent.units_lineMap {p : ι → P} (hp : AffineIndependent k p) (j : ι)
(w : ι → Units k) : AffineIndependent k fun i => AffineMap.lineMap (p j) (p i) (w i : k) := by
rw [affineIndependent_iff_linearIndependent_vsub k _ j] at hp ⊢
simp only [AffineMap.lineMap_vsub_left, AffineMap.coe_const, AffineMap.lineMap_same, const_apply]
exact hp.units_smul fun i => w i
#align affine_independent.units_line_map AffineIndependent.units_lineMap
theorem AffineIndependent.indicator_eq_of_affineCombination_eq {p : ι → P}
(ha : AffineIndependent k p) (s₁ s₂ : Finset ι) (w₁ w₂ : ι → k) (hw₁ : ∑ i ∈ s₁, w₁ i = 1)
(hw₂ : ∑ i ∈ s₂, w₂ i = 1) (h : s₁.affineCombination k p w₁ = s₂.affineCombination k p w₂) :
Set.indicator (↑s₁) w₁ = Set.indicator (↑s₂) w₂ :=
(affineIndependent_iff_indicator_eq_of_affineCombination_eq k p).1 ha s₁ s₂ w₁ w₂ hw₁ hw₂ h
#align affine_independent.indicator_eq_of_affine_combination_eq AffineIndependent.indicator_eq_of_affineCombination_eq
/-- An affinely independent family is injective, if the underlying
ring is nontrivial. -/
protected theorem AffineIndependent.injective [Nontrivial k] {p : ι → P}
(ha : AffineIndependent k p) : Function.Injective p := by
intro i j hij
rw [affineIndependent_iff_linearIndependent_vsub _ _ j] at ha
by_contra hij'
refine ha.ne_zero ⟨i, hij'⟩ (vsub_eq_zero_iff_eq.mpr ?_)
simp_all only [ne_eq]
#align affine_independent.injective AffineIndependent.injective
/-- If a family is affinely independent, so is any subfamily given by
composition of an embedding into index type with the original
family. -/
| Mathlib/LinearAlgebra/AffineSpace/Independent.lean | 286 | 304 | theorem AffineIndependent.comp_embedding {ι2 : Type*} (f : ι2 ↪ ι) {p : ι → P}
(ha : AffineIndependent k p) : AffineIndependent k (p ∘ f) := by |
classical
intro fs w hw hs i0 hi0
let fs' := fs.map f
let w' i := if h : ∃ i2, f i2 = i then w h.choose else 0
have hw' : ∀ i2 : ι2, w' (f i2) = w i2 := by
intro i2
have h : ∃ i : ι2, f i = f i2 := ⟨i2, rfl⟩
have hs : h.choose = i2 := f.injective h.choose_spec
simp_rw [w', dif_pos h, hs]
have hw's : ∑ i ∈ fs', w' i = 0 := by
rw [← hw, Finset.sum_map]
simp [hw']
have hs' : fs'.weightedVSub p w' = (0 : V) := by
rw [← hs, Finset.weightedVSub_map]
congr with i
simp_all only [comp_apply, EmbeddingLike.apply_eq_iff_eq, exists_eq, dite_true]
rw [← ha fs' w' hw's hs' (f i0) ((Finset.mem_map' _).2 hi0), hw']
|
/-
Copyright (c) 2022 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Batteries.Data.Rat.Basic
import Batteries.Tactic.SeqFocus
/-! # Additional lemmas about the Rational Numbers -/
namespace Rat
theorem ext : {p q : Rat} → p.num = q.num → p.den = q.den → p = q
| ⟨_,_,_,_⟩, ⟨_,_,_,_⟩, rfl, rfl => rfl
@[simp] theorem mk_den_one {r : Int} :
⟨r, 1, Nat.one_ne_zero, (Nat.coprime_one_right _)⟩ = (r : Rat) := rfl
@[simp] theorem zero_num : (0 : Rat).num = 0 := rfl
@[simp] theorem zero_den : (0 : Rat).den = 1 := rfl
@[simp] theorem one_num : (1 : Rat).num = 1 := rfl
@[simp] theorem one_den : (1 : Rat).den = 1 := rfl
@[simp] theorem maybeNormalize_eq {num den g} (den_nz reduced) :
maybeNormalize num den g den_nz reduced =
{ num := num.div g, den := den / g, den_nz, reduced } := by
unfold maybeNormalize; split
· subst g; simp
· rfl
theorem normalize.reduced' {num : Int} {den g : Nat} (den_nz : den ≠ 0)
(e : g = num.natAbs.gcd den) : (num / g).natAbs.Coprime (den / g) := by
rw [← Int.div_eq_ediv_of_dvd (e ▸ Int.ofNat_dvd_left.2 (Nat.gcd_dvd_left ..))]
exact normalize.reduced den_nz e
theorem normalize_eq {num den} (den_nz) : normalize num den den_nz =
{ num := num / num.natAbs.gcd den
den := den / num.natAbs.gcd den
den_nz := normalize.den_nz den_nz rfl
reduced := normalize.reduced' den_nz rfl } := by
simp only [normalize, maybeNormalize_eq,
Int.div_eq_ediv_of_dvd (Int.ofNat_dvd_left.2 (Nat.gcd_dvd_left ..))]
@[simp] theorem normalize_zero (nz) : normalize 0 d nz = 0 := by
simp [normalize, Int.zero_div, Int.natAbs_zero, Nat.div_self (Nat.pos_of_ne_zero nz)]; rfl
theorem mk_eq_normalize (num den nz c) : ⟨num, den, nz, c⟩ = normalize num den nz := by
simp [normalize_eq, c.gcd_eq_one]
theorem normalize_self (r : Rat) : normalize r.num r.den r.den_nz = r := (mk_eq_normalize ..).symm
theorem normalize_mul_left {a : Nat} (d0 : d ≠ 0) (a0 : a ≠ 0) :
normalize (↑a * n) (a * d) (Nat.mul_ne_zero a0 d0) = normalize n d d0 := by
simp [normalize_eq, mk'.injEq, Int.natAbs_mul, Nat.gcd_mul_left,
Nat.mul_div_mul_left _ _ (Nat.pos_of_ne_zero a0), Int.ofNat_mul,
Int.mul_ediv_mul_of_pos _ _ (Int.ofNat_pos.2 <| Nat.pos_of_ne_zero a0)]
theorem normalize_mul_right {a : Nat} (d0 : d ≠ 0) (a0 : a ≠ 0) :
normalize (n * a) (d * a) (Nat.mul_ne_zero d0 a0) = normalize n d d0 := by
rw [← normalize_mul_left (d0 := d0) a0]; congr 1 <;> [apply Int.mul_comm; apply Nat.mul_comm]
theorem normalize_eq_iff (z₁ : d₁ ≠ 0) (z₂ : d₂ ≠ 0) :
normalize n₁ d₁ z₁ = normalize n₂ d₂ z₂ ↔ n₁ * d₂ = n₂ * d₁ := by
constructor <;> intro h
· simp only [normalize_eq, mk'.injEq] at h
have' hn₁ := Int.ofNat_dvd_left.2 <| Nat.gcd_dvd_left n₁.natAbs d₁
have' hn₂ := Int.ofNat_dvd_left.2 <| Nat.gcd_dvd_left n₂.natAbs d₂
have' hd₁ := Int.ofNat_dvd.2 <| Nat.gcd_dvd_right n₁.natAbs d₁
have' hd₂ := Int.ofNat_dvd.2 <| Nat.gcd_dvd_right n₂.natAbs d₂
rw [← Int.ediv_mul_cancel (Int.dvd_trans hd₂ (Int.dvd_mul_left ..)),
Int.mul_ediv_assoc _ hd₂, ← Int.ofNat_ediv, ← h.2, Int.ofNat_ediv,
← Int.mul_ediv_assoc _ hd₁, Int.mul_ediv_assoc' _ hn₁,
Int.mul_right_comm, h.1, Int.ediv_mul_cancel hn₂]
· rw [← normalize_mul_right _ z₂, ← normalize_mul_left z₂ z₁, Int.mul_comm d₁, h]
theorem maybeNormalize_eq_normalize {num : Int} {den g : Nat} (den_nz reduced)
(hn : ↑g ∣ num) (hd : g ∣ den) :
maybeNormalize num den g den_nz reduced = normalize num den (mt (by simp [·]) den_nz) := by
simp only [maybeNormalize_eq, mk_eq_normalize, Int.div_eq_ediv_of_dvd hn]
have : g ≠ 0 := mt (by simp [·]) den_nz
rw [← normalize_mul_right _ this, Int.ediv_mul_cancel hn]
congr 1; exact Nat.div_mul_cancel hd
@[simp] theorem normalize_eq_zero (d0 : d ≠ 0) : normalize n d d0 = 0 ↔ n = 0 := by
have' := normalize_eq_iff d0 Nat.one_ne_zero
rw [normalize_zero (d := 1)] at this; rw [this]; simp
theorem normalize_num_den' (num den nz) : ∃ d : Nat, d ≠ 0 ∧
num = (normalize num den nz).num * d ∧ den = (normalize num den nz).den * d := by
refine ⟨num.natAbs.gcd den, Nat.gcd_ne_zero_right nz, ?_⟩
simp [normalize_eq, Int.ediv_mul_cancel (Int.ofNat_dvd_left.2 <| Nat.gcd_dvd_left ..),
Nat.div_mul_cancel (Nat.gcd_dvd_right ..)]
theorem normalize_num_den (h : normalize n d z = ⟨n', d', z', c⟩) :
∃ m : Nat, m ≠ 0 ∧ n = n' * m ∧ d = d' * m := by
have := normalize_num_den' n d z; rwa [h] at this
theorem normalize_eq_mkRat {num den} (den_nz) : normalize num den den_nz = mkRat num den := by
simp [mkRat, den_nz]
theorem mkRat_num_den (z : d ≠ 0) (h : mkRat n d = ⟨n', d', z', c⟩) :
∃ m : Nat, m ≠ 0 ∧ n = n' * m ∧ d = d' * m :=
normalize_num_den ((normalize_eq_mkRat z).symm ▸ h)
theorem mkRat_def (n d) : mkRat n d = if d0 : d = 0 then 0 else normalize n d d0 := rfl
theorem mkRat_self (a : Rat) : mkRat a.num a.den = a := by
rw [← normalize_eq_mkRat a.den_nz, normalize_self]
theorem mk_eq_mkRat (num den nz c) : ⟨num, den, nz, c⟩ = mkRat num den := by
simp [mk_eq_normalize, normalize_eq_mkRat]
@[simp] theorem zero_mkRat (n) : mkRat 0 n = 0 := by simp [mkRat_def]
@[simp] theorem mkRat_zero (n) : mkRat n 0 = 0 := by simp [mkRat_def]
theorem mkRat_eq_zero (d0 : d ≠ 0) : mkRat n d = 0 ↔ n = 0 := by simp [mkRat_def, d0]
theorem mkRat_ne_zero (d0 : d ≠ 0) : mkRat n d ≠ 0 ↔ n ≠ 0 := not_congr (mkRat_eq_zero d0)
| .lake/packages/batteries/Batteries/Data/Rat/Lemmas.lean | 121 | 123 | theorem mkRat_mul_left {a : Nat} (a0 : a ≠ 0) : mkRat (↑a * n) (a * d) = mkRat n d := by |
if d0 : d = 0 then simp [d0] else
rw [← normalize_eq_mkRat d0, ← normalize_mul_left d0 a0, normalize_eq_mkRat]
|
/-
Copyright (c) 2022 Junyan Xu. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Junyan Xu
-/
import Mathlib.Data.DFinsupp.Basic
#align_import data.dfinsupp.ne_locus from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c"
/-!
# Locus of unequal values of finitely supported dependent functions
Let `N : α → Type*` be a type family, assume that `N a` has a `0` for all `a : α` and let
`f g : Π₀ a, N a` be finitely supported dependent functions.
## Main definition
* `DFinsupp.neLocus f g : Finset α`, the finite subset of `α` where `f` and `g` differ.
In the case in which `N a` is an additive group for all `a`, `DFinsupp.neLocus f g` coincides with
`DFinsupp.support (f - g)`.
-/
variable {α : Type*} {N : α → Type*}
namespace DFinsupp
variable [DecidableEq α]
section NHasZero
variable [∀ a, DecidableEq (N a)] [∀ a, Zero (N a)] (f g : Π₀ a, N a)
/-- 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 : Π₀ a, N a) : Finset α :=
(f.support ∪ g.support).filter fun x ↦ f x ≠ g x
#align dfinsupp.ne_locus DFinsupp.neLocus
@[simp]
theorem mem_neLocus {f g : Π₀ a, N a} {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 _
#align dfinsupp.mem_ne_locus DFinsupp.mem_neLocus
theorem not_mem_neLocus {f g : Π₀ a, N a} {a : α} : a ∉ f.neLocus g ↔ f a = g a :=
mem_neLocus.not.trans not_ne_iff
#align dfinsupp.not_mem_ne_locus DFinsupp.not_mem_neLocus
@[simp]
theorem coe_neLocus : ↑(f.neLocus g) = { x | f x ≠ g x } :=
Set.ext fun _x ↦ mem_neLocus
#align dfinsupp.coe_ne_locus DFinsupp.coe_neLocus
@[simp]
theorem neLocus_eq_empty {f g : Π₀ a, N a} : 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]⟩
#align dfinsupp.ne_locus_eq_empty DFinsupp.neLocus_eq_empty
@[simp]
theorem nonempty_neLocus_iff {f g : Π₀ a, N a} : (f.neLocus g).Nonempty ↔ f ≠ g :=
Finset.nonempty_iff_ne_empty.trans neLocus_eq_empty.not
#align dfinsupp.nonempty_ne_locus_iff DFinsupp.nonempty_neLocus_iff
theorem neLocus_comm : f.neLocus g = g.neLocus f := by
simp_rw [neLocus, Finset.union_comm, ne_comm]
#align dfinsupp.ne_locus_comm DFinsupp.neLocus_comm
@[simp]
theorem neLocus_zero_right : f.neLocus 0 = f.support := by
ext
rw [mem_neLocus, mem_support_iff, coe_zero, Pi.zero_apply]
#align dfinsupp.ne_locus_zero_right DFinsupp.neLocus_zero_right
@[simp]
theorem neLocus_zero_left : (0 : Π₀ a, N a).neLocus f = f.support :=
(neLocus_comm _ _).trans (neLocus_zero_right _)
#align dfinsupp.ne_locus_zero_left DFinsupp.neLocus_zero_left
end NHasZero
section NeLocusAndMaps
variable {M P : α → Type*} [∀ a, Zero (N a)] [∀ a, Zero (M a)] [∀ a, Zero (P a)]
theorem subset_mapRange_neLocus [∀ a, DecidableEq (N a)] [∀ a, DecidableEq (M a)] (f g : Π₀ a, N a)
{F : ∀ a, N a → M a} (F0 : ∀ a, F a 0 = 0) :
(f.mapRange F F0).neLocus (g.mapRange F F0) ⊆ f.neLocus g := fun a ↦ by
simpa only [mem_neLocus, mapRange_apply, not_imp_not] using congr_arg (F a)
#align dfinsupp.subset_map_range_ne_locus DFinsupp.subset_mapRange_neLocus
theorem zipWith_neLocus_eq_left [∀ a, DecidableEq (N a)] [∀ a, DecidableEq (P a)]
{F : ∀ a, M a → N a → P a} (F0 : ∀ a, F a 0 0 = 0) (f : Π₀ a, M a) (g₁ g₂ : Π₀ a, N a)
(hF : ∀ a f, Function.Injective fun g ↦ F a f g) :
(zipWith F F0 f g₁).neLocus (zipWith F F0 f g₂) = g₁.neLocus g₂ := by
ext a
simpa only [mem_neLocus] using (hF a _).ne_iff
#align dfinsupp.zip_with_ne_locus_eq_left DFinsupp.zipWith_neLocus_eq_left
theorem zipWith_neLocus_eq_right [∀ a, DecidableEq (M a)] [∀ a, DecidableEq (P a)]
{F : ∀ a, M a → N a → P a} (F0 : ∀ a, F a 0 0 = 0) (f₁ f₂ : Π₀ a, M a) (g : Π₀ a, N a)
(hF : ∀ a g, Function.Injective fun f ↦ F a f g) :
(zipWith F F0 f₁ g).neLocus (zipWith F F0 f₂ g) = f₁.neLocus f₂ := by
ext a
simpa only [mem_neLocus] using (hF a _).ne_iff
#align dfinsupp.zip_with_ne_locus_eq_right DFinsupp.zipWith_neLocus_eq_right
theorem mapRange_neLocus_eq [∀ a, DecidableEq (N a)] [∀ a, DecidableEq (M a)] (f g : Π₀ a, N a)
{F : ∀ a, N a → M a} (F0 : ∀ a, F a 0 = 0) (hF : ∀ a, Function.Injective (F a)) :
(f.mapRange F F0).neLocus (g.mapRange F F0) = f.neLocus g := by
ext a
simpa only [mem_neLocus] using (hF a).ne_iff
#align dfinsupp.map_range_ne_locus_eq DFinsupp.mapRange_neLocus_eq
end NeLocusAndMaps
variable [∀ a, DecidableEq (N a)]
@[simp]
theorem neLocus_add_left [∀ a, AddLeftCancelMonoid (N a)] (f g h : Π₀ a, N a) :
(f + g).neLocus (f + h) = g.neLocus h :=
zipWith_neLocus_eq_left _ _ _ _ fun _a ↦ add_right_injective
#align dfinsupp.ne_locus_add_left DFinsupp.neLocus_add_left
@[simp]
theorem neLocus_add_right [∀ a, AddRightCancelMonoid (N a)] (f g h : Π₀ a, N a) :
(f + h).neLocus (g + h) = f.neLocus g :=
zipWith_neLocus_eq_right _ _ _ _ fun _a ↦ add_left_injective
#align dfinsupp.ne_locus_add_right DFinsupp.neLocus_add_right
section AddGroup
variable [∀ a, AddGroup (N a)] (f f₁ f₂ g g₁ g₂ : Π₀ a, N a)
@[simp]
theorem neLocus_neg_neg : neLocus (-f) (-g) = f.neLocus g :=
mapRange_neLocus_eq _ _ (fun _a ↦ neg_zero) fun _a ↦ neg_injective
#align dfinsupp.ne_locus_neg_neg DFinsupp.neLocus_neg_neg
theorem neLocus_neg : neLocus (-f) g = f.neLocus (-g) := by rw [← neLocus_neg_neg, neg_neg]
#align dfinsupp.ne_locus_neg DFinsupp.neLocus_neg
theorem neLocus_eq_support_sub : f.neLocus g = (f - g).support := by
rw [← @neLocus_add_right α N _ _ _ _ _ (-g), add_right_neg, neLocus_zero_right, sub_eq_add_neg]
#align dfinsupp.ne_locus_eq_support_sub DFinsupp.neLocus_eq_support_sub
@[simp]
theorem neLocus_sub_left : neLocus (f - g₁) (f - g₂) = neLocus g₁ g₂ := by
simp only [sub_eq_add_neg, @neLocus_add_left α N _ _ _, neLocus_neg_neg]
#align dfinsupp.ne_locus_sub_left DFinsupp.neLocus_sub_left
@[simp]
theorem neLocus_sub_right : neLocus (f₁ - g) (f₂ - g) = neLocus f₁ f₂ := by
simpa only [sub_eq_add_neg] using @neLocus_add_right α N _ _ _ _ _ _
#align dfinsupp.ne_locus_sub_right DFinsupp.neLocus_sub_right
@[simp]
theorem neLocus_self_add_right : neLocus f (f + g) = g.support := by
rw [← neLocus_zero_left, ← @neLocus_add_left α N _ _ _ f 0 g, add_zero]
#align dfinsupp.ne_locus_self_add_right DFinsupp.neLocus_self_add_right
@[simp]
| Mathlib/Data/DFinsupp/NeLocus.lean | 165 | 166 | theorem neLocus_self_add_left : neLocus (f + g) f = g.support := by |
rw [neLocus_comm, neLocus_self_add_right]
|
/-
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.Dynamics.Ergodic.MeasurePreserving
import Mathlib.MeasureTheory.Function.SimpleFunc
import Mathlib.MeasureTheory.Measure.MutuallySingular
import Mathlib.MeasureTheory.Measure.Count
import Mathlib.Topology.IndicatorConstPointwise
import Mathlib.MeasureTheory.Constructions.BorelSpace.Real
#align_import measure_theory.integral.lebesgue from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520"
/-!
# Lower Lebesgue integral for `ℝ≥0∞`-valued functions
We define the lower Lebesgue integral of an `ℝ≥0∞`-valued function.
## Notation
We introduce the following notation for the lower Lebesgue integral of a function `f : α → ℝ≥0∞`.
* `∫⁻ x, f x ∂μ`: integral of a function `f : α → ℝ≥0∞` with respect to a measure `μ`;
* `∫⁻ x, f x`: integral of a function `f : α → ℝ≥0∞` with respect to the canonical measure
`volume` on `α`;
* `∫⁻ x in s, f x ∂μ`: integral of a function `f : α → ℝ≥0∞` over a set `s` with respect
to a measure `μ`, defined as `∫⁻ x, f x ∂(μ.restrict s)`;
* `∫⁻ x in s, f x`: integral of a function `f : α → ℝ≥0∞` over a set `s` with respect
to the canonical measure `volume`, defined as `∫⁻ x, f x ∂(volume.restrict s)`.
-/
assert_not_exists NormedSpace
set_option autoImplicit true
noncomputable section
open Set hiding restrict restrict_apply
open Filter ENNReal
open Function (support)
open scoped Classical
open Topology NNReal ENNReal MeasureTheory
namespace MeasureTheory
local infixr:25 " →ₛ " => SimpleFunc
variable {α β γ δ : Type*}
section Lintegral
open SimpleFunc
variable {m : MeasurableSpace α} {μ ν : Measure α}
/-- The **lower Lebesgue integral** of a function `f` with respect to a measure `μ`. -/
irreducible_def lintegral {_ : MeasurableSpace α} (μ : Measure α) (f : α → ℝ≥0∞) : ℝ≥0∞ :=
⨆ (g : α →ₛ ℝ≥0∞) (_ : ⇑g ≤ f), g.lintegral μ
#align measure_theory.lintegral MeasureTheory.lintegral
/-! In the notation for integrals, an expression like `∫⁻ x, g ‖x‖ ∂μ` will not be parsed correctly,
and needs parentheses. We do not set the binding power of `r` to `0`, because then
`∫⁻ x, f x = 0` will be parsed incorrectly. -/
@[inherit_doc MeasureTheory.lintegral]
notation3 "∫⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => lintegral μ r
@[inherit_doc MeasureTheory.lintegral]
notation3 "∫⁻ "(...)", "r:60:(scoped f => lintegral volume f) => r
@[inherit_doc MeasureTheory.lintegral]
notation3"∫⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => lintegral (Measure.restrict μ s) r
@[inherit_doc MeasureTheory.lintegral]
notation3"∫⁻ "(...)" in "s", "r:60:(scoped f => lintegral (Measure.restrict volume s) f) => r
theorem SimpleFunc.lintegral_eq_lintegral {m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (μ : Measure α) :
∫⁻ a, f a ∂μ = f.lintegral μ := by
rw [MeasureTheory.lintegral]
exact le_antisymm (iSup₂_le fun g hg => lintegral_mono hg <| le_rfl)
(le_iSup₂_of_le f le_rfl le_rfl)
#align measure_theory.simple_func.lintegral_eq_lintegral MeasureTheory.SimpleFunc.lintegral_eq_lintegral
@[mono]
theorem lintegral_mono' {m : MeasurableSpace α} ⦃μ ν : Measure α⦄ (hμν : μ ≤ ν) ⦃f g : α → ℝ≥0∞⦄
(hfg : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂ν := by
rw [lintegral, lintegral]
exact iSup_mono fun φ => iSup_mono' fun hφ => ⟨le_trans hφ hfg, lintegral_mono (le_refl φ) hμν⟩
#align measure_theory.lintegral_mono' MeasureTheory.lintegral_mono'
-- workaround for the known eta-reduction issue with `@[gcongr]`
@[gcongr] theorem lintegral_mono_fn' ⦃f g : α → ℝ≥0∞⦄ (hfg : ∀ x, f x ≤ g x) (h2 : μ ≤ ν) :
lintegral μ f ≤ lintegral ν g :=
lintegral_mono' h2 hfg
theorem lintegral_mono ⦃f g : α → ℝ≥0∞⦄ (hfg : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ :=
lintegral_mono' (le_refl μ) hfg
#align measure_theory.lintegral_mono MeasureTheory.lintegral_mono
-- workaround for the known eta-reduction issue with `@[gcongr]`
@[gcongr] theorem lintegral_mono_fn ⦃f g : α → ℝ≥0∞⦄ (hfg : ∀ x, f x ≤ g x) :
lintegral μ f ≤ lintegral μ g :=
lintegral_mono hfg
theorem lintegral_mono_nnreal {f g : α → ℝ≥0} (h : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ :=
lintegral_mono fun a => ENNReal.coe_le_coe.2 (h a)
#align measure_theory.lintegral_mono_nnreal MeasureTheory.lintegral_mono_nnreal
theorem iSup_lintegral_measurable_le_eq_lintegral (f : α → ℝ≥0∞) :
⨆ (g : α → ℝ≥0∞) (_ : Measurable g) (_ : g ≤ f), ∫⁻ a, g a ∂μ = ∫⁻ a, f a ∂μ := by
apply le_antisymm
· exact iSup_le fun i => iSup_le fun _ => iSup_le fun h'i => lintegral_mono h'i
· rw [lintegral]
refine iSup₂_le fun i hi => le_iSup₂_of_le i i.measurable <| le_iSup_of_le hi ?_
exact le_of_eq (i.lintegral_eq_lintegral _).symm
#align measure_theory.supr_lintegral_measurable_le_eq_lintegral MeasureTheory.iSup_lintegral_measurable_le_eq_lintegral
theorem lintegral_mono_set {_ : MeasurableSpace α} ⦃μ : Measure α⦄ {s t : Set α} {f : α → ℝ≥0∞}
(hst : s ⊆ t) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in t, f x ∂μ :=
lintegral_mono' (Measure.restrict_mono hst (le_refl μ)) (le_refl f)
#align measure_theory.lintegral_mono_set MeasureTheory.lintegral_mono_set
theorem lintegral_mono_set' {_ : MeasurableSpace α} ⦃μ : Measure α⦄ {s t : Set α} {f : α → ℝ≥0∞}
(hst : s ≤ᵐ[μ] t) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in t, f x ∂μ :=
lintegral_mono' (Measure.restrict_mono' hst (le_refl μ)) (le_refl f)
#align measure_theory.lintegral_mono_set' MeasureTheory.lintegral_mono_set'
theorem monotone_lintegral {_ : MeasurableSpace α} (μ : Measure α) : Monotone (lintegral μ) :=
lintegral_mono
#align measure_theory.monotone_lintegral MeasureTheory.monotone_lintegral
@[simp]
theorem lintegral_const (c : ℝ≥0∞) : ∫⁻ _, c ∂μ = c * μ univ := by
rw [← SimpleFunc.const_lintegral, ← SimpleFunc.lintegral_eq_lintegral, SimpleFunc.coe_const]
rfl
#align measure_theory.lintegral_const MeasureTheory.lintegral_const
theorem lintegral_zero : ∫⁻ _ : α, 0 ∂μ = 0 := by simp
#align measure_theory.lintegral_zero MeasureTheory.lintegral_zero
theorem lintegral_zero_fun : lintegral μ (0 : α → ℝ≥0∞) = 0 :=
lintegral_zero
#align measure_theory.lintegral_zero_fun MeasureTheory.lintegral_zero_fun
-- @[simp] -- Porting note (#10618): simp can prove this
theorem lintegral_one : ∫⁻ _, (1 : ℝ≥0∞) ∂μ = μ univ := by rw [lintegral_const, one_mul]
#align measure_theory.lintegral_one MeasureTheory.lintegral_one
theorem set_lintegral_const (s : Set α) (c : ℝ≥0∞) : ∫⁻ _ in s, c ∂μ = c * μ s := by
rw [lintegral_const, Measure.restrict_apply_univ]
#align measure_theory.set_lintegral_const MeasureTheory.set_lintegral_const
theorem set_lintegral_one (s) : ∫⁻ _ in s, 1 ∂μ = μ s := by rw [set_lintegral_const, one_mul]
#align measure_theory.set_lintegral_one MeasureTheory.set_lintegral_one
theorem set_lintegral_const_lt_top [IsFiniteMeasure μ] (s : Set α) {c : ℝ≥0∞} (hc : c ≠ ∞) :
∫⁻ _ in s, c ∂μ < ∞ := by
rw [lintegral_const]
exact ENNReal.mul_lt_top hc (measure_ne_top (μ.restrict s) univ)
#align measure_theory.set_lintegral_const_lt_top MeasureTheory.set_lintegral_const_lt_top
theorem lintegral_const_lt_top [IsFiniteMeasure μ] {c : ℝ≥0∞} (hc : c ≠ ∞) : ∫⁻ _, c ∂μ < ∞ := by
simpa only [Measure.restrict_univ] using set_lintegral_const_lt_top (univ : Set α) hc
#align measure_theory.lintegral_const_lt_top MeasureTheory.lintegral_const_lt_top
section
variable (μ)
/-- For any function `f : α → ℝ≥0∞`, there exists a measurable function `g ≤ f` with the same
integral. -/
theorem exists_measurable_le_lintegral_eq (f : α → ℝ≥0∞) :
∃ g : α → ℝ≥0∞, Measurable g ∧ g ≤ f ∧ ∫⁻ a, f a ∂μ = ∫⁻ a, g a ∂μ := by
rcases eq_or_ne (∫⁻ a, f a ∂μ) 0 with h₀ | h₀
· exact ⟨0, measurable_zero, zero_le f, h₀.trans lintegral_zero.symm⟩
rcases exists_seq_strictMono_tendsto' h₀.bot_lt with ⟨L, _, hLf, hL_tendsto⟩
have : ∀ n, ∃ g : α → ℝ≥0∞, Measurable g ∧ g ≤ f ∧ L n < ∫⁻ a, g a ∂μ := by
intro n
simpa only [← iSup_lintegral_measurable_le_eq_lintegral f, lt_iSup_iff, exists_prop] using
(hLf n).2
choose g hgm hgf hLg using this
refine
⟨fun x => ⨆ n, g n x, measurable_iSup hgm, fun x => iSup_le fun n => hgf n x, le_antisymm ?_ ?_⟩
· refine le_of_tendsto' hL_tendsto fun n => (hLg n).le.trans <| lintegral_mono fun x => ?_
exact le_iSup (fun n => g n x) n
· exact lintegral_mono fun x => iSup_le fun n => hgf n x
#align measure_theory.exists_measurable_le_lintegral_eq MeasureTheory.exists_measurable_le_lintegral_eq
end
/-- `∫⁻ a in s, f a ∂μ` is defined as the supremum of integrals of simple functions
`φ : α →ₛ ℝ≥0∞` such that `φ ≤ f`. This lemma says that it suffices to take
functions `φ : α →ₛ ℝ≥0`. -/
theorem lintegral_eq_nnreal {m : MeasurableSpace α} (f : α → ℝ≥0∞) (μ : Measure α) :
∫⁻ a, f a ∂μ =
⨆ (φ : α →ₛ ℝ≥0) (_ : ∀ x, ↑(φ x) ≤ f x), (φ.map ((↑) : ℝ≥0 → ℝ≥0∞)).lintegral μ := by
rw [lintegral]
refine
le_antisymm (iSup₂_le fun φ hφ => ?_) (iSup_mono' fun φ => ⟨φ.map ((↑) : ℝ≥0 → ℝ≥0∞), le_rfl⟩)
by_cases h : ∀ᵐ a ∂μ, φ a ≠ ∞
· let ψ := φ.map ENNReal.toNNReal
replace h : ψ.map ((↑) : ℝ≥0 → ℝ≥0∞) =ᵐ[μ] φ := h.mono fun a => ENNReal.coe_toNNReal
have : ∀ x, ↑(ψ x) ≤ f x := fun x => le_trans ENNReal.coe_toNNReal_le_self (hφ x)
exact
le_iSup_of_le (φ.map ENNReal.toNNReal) (le_iSup_of_le this (ge_of_eq <| lintegral_congr h))
· have h_meas : μ (φ ⁻¹' {∞}) ≠ 0 := mt measure_zero_iff_ae_nmem.1 h
refine le_trans le_top (ge_of_eq <| (iSup_eq_top _).2 fun b hb => ?_)
obtain ⟨n, hn⟩ : ∃ n : ℕ, b < n * μ (φ ⁻¹' {∞}) := exists_nat_mul_gt h_meas (ne_of_lt hb)
use (const α (n : ℝ≥0)).restrict (φ ⁻¹' {∞})
simp only [lt_iSup_iff, exists_prop, coe_restrict, φ.measurableSet_preimage, coe_const,
ENNReal.coe_indicator, map_coe_ennreal_restrict, SimpleFunc.map_const, ENNReal.coe_natCast,
restrict_const_lintegral]
refine ⟨indicator_le fun x hx => le_trans ?_ (hφ _), hn⟩
simp only [mem_preimage, mem_singleton_iff] at hx
simp only [hx, le_top]
#align measure_theory.lintegral_eq_nnreal MeasureTheory.lintegral_eq_nnreal
theorem exists_simpleFunc_forall_lintegral_sub_lt_of_pos {f : α → ℝ≥0∞} (h : ∫⁻ x, f x ∂μ ≠ ∞)
{ε : ℝ≥0∞} (hε : ε ≠ 0) :
∃ φ : α →ₛ ℝ≥0,
(∀ x, ↑(φ x) ≤ f x) ∧
∀ ψ : α →ₛ ℝ≥0, (∀ x, ↑(ψ x) ≤ f x) → (map (↑) (ψ - φ)).lintegral μ < ε := by
rw [lintegral_eq_nnreal] at h
have := ENNReal.lt_add_right h hε
erw [ENNReal.biSup_add] at this <;> [skip; exact ⟨0, fun x => zero_le _⟩]
simp_rw [lt_iSup_iff, iSup_lt_iff, iSup_le_iff] at this
rcases this with ⟨φ, hle : ∀ x, ↑(φ x) ≤ f x, b, hbφ, hb⟩
refine ⟨φ, hle, fun ψ hψ => ?_⟩
have : (map (↑) φ).lintegral μ ≠ ∞ := ne_top_of_le_ne_top h (by exact le_iSup₂ (α := ℝ≥0∞) φ hle)
rw [← ENNReal.add_lt_add_iff_left this, ← add_lintegral, ← SimpleFunc.map_add @ENNReal.coe_add]
refine (hb _ fun x => le_trans ?_ (max_le (hle x) (hψ x))).trans_lt hbφ
norm_cast
simp only [add_apply, sub_apply, add_tsub_eq_max]
rfl
#align measure_theory.exists_simple_func_forall_lintegral_sub_lt_of_pos MeasureTheory.exists_simpleFunc_forall_lintegral_sub_lt_of_pos
theorem iSup_lintegral_le {ι : Sort*} (f : ι → α → ℝ≥0∞) :
⨆ i, ∫⁻ a, f i a ∂μ ≤ ∫⁻ a, ⨆ i, f i a ∂μ := by
simp only [← iSup_apply]
exact (monotone_lintegral μ).le_map_iSup
#align measure_theory.supr_lintegral_le MeasureTheory.iSup_lintegral_le
theorem iSup₂_lintegral_le {ι : Sort*} {ι' : ι → Sort*} (f : ∀ i, ι' i → α → ℝ≥0∞) :
⨆ (i) (j), ∫⁻ a, f i j a ∂μ ≤ ∫⁻ a, ⨆ (i) (j), f i j a ∂μ := by
convert (monotone_lintegral μ).le_map_iSup₂ f with a
simp only [iSup_apply]
#align measure_theory.supr₂_lintegral_le MeasureTheory.iSup₂_lintegral_le
theorem le_iInf_lintegral {ι : Sort*} (f : ι → α → ℝ≥0∞) :
∫⁻ a, ⨅ i, f i a ∂μ ≤ ⨅ i, ∫⁻ a, f i a ∂μ := by
simp only [← iInf_apply]
exact (monotone_lintegral μ).map_iInf_le
#align measure_theory.le_infi_lintegral MeasureTheory.le_iInf_lintegral
theorem le_iInf₂_lintegral {ι : Sort*} {ι' : ι → Sort*} (f : ∀ i, ι' i → α → ℝ≥0∞) :
∫⁻ a, ⨅ (i) (h : ι' i), f i h a ∂μ ≤ ⨅ (i) (h : ι' i), ∫⁻ a, f i h a ∂μ := by
convert (monotone_lintegral μ).map_iInf₂_le f with a
simp only [iInf_apply]
#align measure_theory.le_infi₂_lintegral MeasureTheory.le_iInf₂_lintegral
theorem lintegral_mono_ae {f g : α → ℝ≥0∞} (h : ∀ᵐ a ∂μ, f a ≤ g a) :
∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ := by
rcases exists_measurable_superset_of_null h with ⟨t, hts, ht, ht0⟩
have : ∀ᵐ x ∂μ, x ∉ t := measure_zero_iff_ae_nmem.1 ht0
rw [lintegral, lintegral]
refine iSup_le fun s => iSup_le fun hfs => le_iSup_of_le (s.restrict tᶜ) <| le_iSup_of_le ?_ ?_
· intro a
by_cases h : a ∈ t <;>
simp only [restrict_apply s ht.compl, mem_compl_iff, h, not_true, not_false_eq_true,
indicator_of_not_mem, zero_le, not_false_eq_true, indicator_of_mem]
exact le_trans (hfs a) (_root_.by_contradiction fun hnfg => h (hts hnfg))
· refine le_of_eq (SimpleFunc.lintegral_congr <| this.mono fun a hnt => ?_)
by_cases hat : a ∈ t <;> simp only [restrict_apply s ht.compl, mem_compl_iff, hat, not_true,
not_false_eq_true, indicator_of_not_mem, not_false_eq_true, indicator_of_mem]
exact (hnt hat).elim
#align measure_theory.lintegral_mono_ae MeasureTheory.lintegral_mono_ae
theorem set_lintegral_mono_ae {s : Set α} {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g)
(hfg : ∀ᵐ x ∂μ, x ∈ s → f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
lintegral_mono_ae <| (ae_restrict_iff <| measurableSet_le hf hg).2 hfg
#align measure_theory.set_lintegral_mono_ae MeasureTheory.set_lintegral_mono_ae
theorem set_lintegral_mono {s : Set α} {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g)
(hfg : ∀ x ∈ s, f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
set_lintegral_mono_ae hf hg (ae_of_all _ hfg)
#align measure_theory.set_lintegral_mono MeasureTheory.set_lintegral_mono
theorem set_lintegral_mono_ae' {s : Set α} {f g : α → ℝ≥0∞} (hs : MeasurableSet s)
(hfg : ∀ᵐ x ∂μ, x ∈ s → f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
lintegral_mono_ae <| (ae_restrict_iff' hs).2 hfg
theorem set_lintegral_mono' {s : Set α} {f g : α → ℝ≥0∞} (hs : MeasurableSet s)
(hfg : ∀ x ∈ s, f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
set_lintegral_mono_ae' hs (ae_of_all _ hfg)
theorem set_lintegral_le_lintegral (s : Set α) (f : α → ℝ≥0∞) :
∫⁻ x in s, f x ∂μ ≤ ∫⁻ x, f x ∂μ :=
lintegral_mono' Measure.restrict_le_self le_rfl
theorem lintegral_congr_ae {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) : ∫⁻ a, f a ∂μ = ∫⁻ a, g a ∂μ :=
le_antisymm (lintegral_mono_ae <| h.le) (lintegral_mono_ae <| h.symm.le)
#align measure_theory.lintegral_congr_ae MeasureTheory.lintegral_congr_ae
theorem lintegral_congr {f g : α → ℝ≥0∞} (h : ∀ a, f a = g a) : ∫⁻ a, f a ∂μ = ∫⁻ a, g a ∂μ := by
simp only [h]
#align measure_theory.lintegral_congr MeasureTheory.lintegral_congr
theorem set_lintegral_congr {f : α → ℝ≥0∞} {s t : Set α} (h : s =ᵐ[μ] t) :
∫⁻ x in s, f x ∂μ = ∫⁻ x in t, f x ∂μ := by rw [Measure.restrict_congr_set h]
#align measure_theory.set_lintegral_congr MeasureTheory.set_lintegral_congr
theorem set_lintegral_congr_fun {f g : α → ℝ≥0∞} {s : Set α} (hs : MeasurableSet s)
(hfg : ∀ᵐ x ∂μ, x ∈ s → f x = g x) : ∫⁻ x in s, f x ∂μ = ∫⁻ x in s, g x ∂μ := by
rw [lintegral_congr_ae]
rw [EventuallyEq]
rwa [ae_restrict_iff' hs]
#align measure_theory.set_lintegral_congr_fun MeasureTheory.set_lintegral_congr_fun
theorem lintegral_ofReal_le_lintegral_nnnorm (f : α → ℝ) :
∫⁻ x, ENNReal.ofReal (f x) ∂μ ≤ ∫⁻ x, ‖f x‖₊ ∂μ := by
simp_rw [← ofReal_norm_eq_coe_nnnorm]
refine lintegral_mono fun x => ENNReal.ofReal_le_ofReal ?_
rw [Real.norm_eq_abs]
exact le_abs_self (f x)
#align measure_theory.lintegral_of_real_le_lintegral_nnnorm MeasureTheory.lintegral_ofReal_le_lintegral_nnnorm
theorem lintegral_nnnorm_eq_of_ae_nonneg {f : α → ℝ} (h_nonneg : 0 ≤ᵐ[μ] f) :
∫⁻ x, ‖f x‖₊ ∂μ = ∫⁻ x, ENNReal.ofReal (f x) ∂μ := by
apply lintegral_congr_ae
filter_upwards [h_nonneg] with x hx
rw [Real.nnnorm_of_nonneg hx, ENNReal.ofReal_eq_coe_nnreal hx]
#align measure_theory.lintegral_nnnorm_eq_of_ae_nonneg MeasureTheory.lintegral_nnnorm_eq_of_ae_nonneg
theorem lintegral_nnnorm_eq_of_nonneg {f : α → ℝ} (h_nonneg : 0 ≤ f) :
∫⁻ x, ‖f x‖₊ ∂μ = ∫⁻ x, ENNReal.ofReal (f x) ∂μ :=
lintegral_nnnorm_eq_of_ae_nonneg (Filter.eventually_of_forall h_nonneg)
#align measure_theory.lintegral_nnnorm_eq_of_nonneg MeasureTheory.lintegral_nnnorm_eq_of_nonneg
/-- **Monotone convergence theorem** -- sometimes called **Beppo-Levi convergence**.
See `lintegral_iSup_directed` for a more general form. -/
theorem lintegral_iSup {f : ℕ → α → ℝ≥0∞} (hf : ∀ n, Measurable (f n)) (h_mono : Monotone f) :
∫⁻ a, ⨆ n, f n a ∂μ = ⨆ n, ∫⁻ a, f n a ∂μ := by
set c : ℝ≥0 → ℝ≥0∞ := (↑)
set F := fun a : α => ⨆ n, f n a
refine le_antisymm ?_ (iSup_lintegral_le _)
rw [lintegral_eq_nnreal]
refine iSup_le fun s => iSup_le fun hsf => ?_
refine ENNReal.le_of_forall_lt_one_mul_le fun a ha => ?_
rcases ENNReal.lt_iff_exists_coe.1 ha with ⟨r, rfl, _⟩
have ha : r < 1 := ENNReal.coe_lt_coe.1 ha
let rs := s.map fun a => r * a
have eq_rs : rs.map c = (const α r : α →ₛ ℝ≥0∞) * map c s := rfl
have eq : ∀ p, rs.map c ⁻¹' {p} = ⋃ n, rs.map c ⁻¹' {p} ∩ { a | p ≤ f n a } := by
intro p
rw [← inter_iUnion]; nth_rw 1 [← inter_univ (map c rs ⁻¹' {p})]
refine Set.ext fun x => and_congr_right fun hx => true_iff_iff.2 ?_
by_cases p_eq : p = 0
· simp [p_eq]
simp only [coe_map, mem_preimage, Function.comp_apply, mem_singleton_iff] at hx
subst hx
have : r * s x ≠ 0 := by rwa [Ne, ← ENNReal.coe_eq_zero]
have : s x ≠ 0 := right_ne_zero_of_mul this
have : (rs.map c) x < ⨆ n : ℕ, f n x := by
refine lt_of_lt_of_le (ENNReal.coe_lt_coe.2 ?_) (hsf x)
suffices r * s x < 1 * s x by simpa
exact mul_lt_mul_of_pos_right ha (pos_iff_ne_zero.2 this)
rcases lt_iSup_iff.1 this with ⟨i, hi⟩
exact mem_iUnion.2 ⟨i, le_of_lt hi⟩
have mono : ∀ r : ℝ≥0∞, Monotone fun n => rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a } := by
intro r i j h
refine inter_subset_inter_right _ ?_
simp_rw [subset_def, mem_setOf]
intro x hx
exact le_trans hx (h_mono h x)
have h_meas : ∀ n, MeasurableSet {a : α | map c rs a ≤ f n a} := fun n =>
measurableSet_le (SimpleFunc.measurable _) (hf n)
calc
(r : ℝ≥0∞) * (s.map c).lintegral μ = ∑ r ∈ (rs.map c).range, r * μ (rs.map c ⁻¹' {r}) := by
rw [← const_mul_lintegral, eq_rs, SimpleFunc.lintegral]
_ = ∑ r ∈ (rs.map c).range, r * μ (⋃ n, rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a }) := by
simp only [(eq _).symm]
_ = ∑ r ∈ (rs.map c).range, ⨆ n, r * μ (rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a }) :=
(Finset.sum_congr rfl fun x _ => by
rw [measure_iUnion_eq_iSup (mono x).directed_le, ENNReal.mul_iSup])
_ = ⨆ n, ∑ r ∈ (rs.map c).range, r * μ (rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a }) := by
refine ENNReal.finset_sum_iSup_nat fun p i j h ↦ ?_
gcongr _ * μ ?_
exact mono p h
_ ≤ ⨆ n : ℕ, ((rs.map c).restrict { a | (rs.map c) a ≤ f n a }).lintegral μ := by
gcongr with n
rw [restrict_lintegral _ (h_meas n)]
refine le_of_eq (Finset.sum_congr rfl fun r _ => ?_)
congr 2 with a
refine and_congr_right ?_
simp (config := { contextual := true })
_ ≤ ⨆ n, ∫⁻ a, f n a ∂μ := by
simp only [← SimpleFunc.lintegral_eq_lintegral]
gcongr with n a
simp only [map_apply] at h_meas
simp only [coe_map, restrict_apply _ (h_meas _), (· ∘ ·)]
exact indicator_apply_le id
#align measure_theory.lintegral_supr MeasureTheory.lintegral_iSup
/-- Monotone convergence theorem -- sometimes called Beppo-Levi convergence. Version with
ae_measurable functions. -/
theorem lintegral_iSup' {f : ℕ → α → ℝ≥0∞} (hf : ∀ n, AEMeasurable (f n) μ)
(h_mono : ∀ᵐ x ∂μ, Monotone fun n => f n x) : ∫⁻ a, ⨆ n, f n a ∂μ = ⨆ n, ∫⁻ a, f n a ∂μ := by
simp_rw [← iSup_apply]
let p : α → (ℕ → ℝ≥0∞) → Prop := fun _ f' => Monotone f'
have hp : ∀ᵐ x ∂μ, p x fun i => f i x := h_mono
have h_ae_seq_mono : Monotone (aeSeq hf p) := by
intro n m hnm x
by_cases hx : x ∈ aeSeqSet hf p
· exact aeSeq.prop_of_mem_aeSeqSet hf hx hnm
· simp only [aeSeq, hx, if_false, le_rfl]
rw [lintegral_congr_ae (aeSeq.iSup hf hp).symm]
simp_rw [iSup_apply]
rw [lintegral_iSup (aeSeq.measurable hf p) h_ae_seq_mono]
congr with n
exact lintegral_congr_ae (aeSeq.aeSeq_n_eq_fun_n_ae hf hp n)
#align measure_theory.lintegral_supr' MeasureTheory.lintegral_iSup'
/-- Monotone convergence theorem expressed with limits -/
theorem lintegral_tendsto_of_tendsto_of_monotone {f : ℕ → α → ℝ≥0∞} {F : α → ℝ≥0∞}
(hf : ∀ n, AEMeasurable (f n) μ) (h_mono : ∀ᵐ x ∂μ, Monotone fun n => f n x)
(h_tendsto : ∀ᵐ x ∂μ, Tendsto (fun n => f n x) atTop (𝓝 <| F x)) :
Tendsto (fun n => ∫⁻ x, f n x ∂μ) atTop (𝓝 <| ∫⁻ x, F x ∂μ) := by
have : Monotone fun n => ∫⁻ x, f n x ∂μ := fun i j hij =>
lintegral_mono_ae (h_mono.mono fun x hx => hx hij)
suffices key : ∫⁻ x, F x ∂μ = ⨆ n, ∫⁻ x, f n x ∂μ by
rw [key]
exact tendsto_atTop_iSup this
rw [← lintegral_iSup' hf h_mono]
refine lintegral_congr_ae ?_
filter_upwards [h_mono, h_tendsto] with _ hx_mono hx_tendsto using
tendsto_nhds_unique hx_tendsto (tendsto_atTop_iSup hx_mono)
#align measure_theory.lintegral_tendsto_of_tendsto_of_monotone MeasureTheory.lintegral_tendsto_of_tendsto_of_monotone
theorem lintegral_eq_iSup_eapprox_lintegral {f : α → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, f a ∂μ = ⨆ n, (eapprox f n).lintegral μ :=
calc
∫⁻ a, f a ∂μ = ∫⁻ a, ⨆ n, (eapprox f n : α → ℝ≥0∞) a ∂μ := by
congr; ext a; rw [iSup_eapprox_apply f hf]
_ = ⨆ n, ∫⁻ a, (eapprox f n : α → ℝ≥0∞) a ∂μ := by
apply lintegral_iSup
· measurability
· intro i j h
exact monotone_eapprox f h
_ = ⨆ n, (eapprox f n).lintegral μ := by
congr; ext n; rw [(eapprox f n).lintegral_eq_lintegral]
#align measure_theory.lintegral_eq_supr_eapprox_lintegral MeasureTheory.lintegral_eq_iSup_eapprox_lintegral
/-- If `f` has finite integral, then `∫⁻ x in s, f x ∂μ` is absolutely continuous in `s`: it tends
to zero as `μ s` tends to zero. This lemma states this fact in terms of `ε` and `δ`. -/
theorem exists_pos_set_lintegral_lt_of_measure_lt {f : α → ℝ≥0∞} (h : ∫⁻ x, f x ∂μ ≠ ∞) {ε : ℝ≥0∞}
(hε : ε ≠ 0) : ∃ δ > 0, ∀ s, μ s < δ → ∫⁻ x in s, f x ∂μ < ε := by
rcases exists_between (pos_iff_ne_zero.mpr hε) with ⟨ε₂, hε₂0, hε₂ε⟩
rcases exists_between hε₂0 with ⟨ε₁, hε₁0, hε₁₂⟩
rcases exists_simpleFunc_forall_lintegral_sub_lt_of_pos h hε₁0.ne' with ⟨φ, _, hφ⟩
rcases φ.exists_forall_le with ⟨C, hC⟩
use (ε₂ - ε₁) / C, ENNReal.div_pos_iff.2 ⟨(tsub_pos_iff_lt.2 hε₁₂).ne', ENNReal.coe_ne_top⟩
refine fun s hs => lt_of_le_of_lt ?_ hε₂ε
simp only [lintegral_eq_nnreal, iSup_le_iff]
intro ψ hψ
calc
(map (↑) ψ).lintegral (μ.restrict s) ≤
(map (↑) φ).lintegral (μ.restrict s) + (map (↑) (ψ - φ)).lintegral (μ.restrict s) := by
rw [← SimpleFunc.add_lintegral, ← SimpleFunc.map_add @ENNReal.coe_add]
refine SimpleFunc.lintegral_mono (fun x => ?_) le_rfl
simp only [add_tsub_eq_max, le_max_right, coe_map, Function.comp_apply, SimpleFunc.coe_add,
SimpleFunc.coe_sub, Pi.add_apply, Pi.sub_apply, ENNReal.coe_max (φ x) (ψ x)]
_ ≤ (map (↑) φ).lintegral (μ.restrict s) + ε₁ := by
gcongr
refine le_trans ?_ (hφ _ hψ).le
exact SimpleFunc.lintegral_mono le_rfl Measure.restrict_le_self
_ ≤ (SimpleFunc.const α (C : ℝ≥0∞)).lintegral (μ.restrict s) + ε₁ := by
gcongr
exact SimpleFunc.lintegral_mono (fun x ↦ ENNReal.coe_le_coe.2 (hC x)) le_rfl
_ = C * μ s + ε₁ := by
simp only [← SimpleFunc.lintegral_eq_lintegral, coe_const, lintegral_const,
Measure.restrict_apply, MeasurableSet.univ, univ_inter, Function.const]
_ ≤ C * ((ε₂ - ε₁) / C) + ε₁ := by gcongr
_ ≤ ε₂ - ε₁ + ε₁ := by gcongr; apply mul_div_le
_ = ε₂ := tsub_add_cancel_of_le hε₁₂.le
#align measure_theory.exists_pos_set_lintegral_lt_of_measure_lt MeasureTheory.exists_pos_set_lintegral_lt_of_measure_lt
/-- If `f` has finite integral, then `∫⁻ x in s, f x ∂μ` is absolutely continuous in `s`: it tends
to zero as `μ s` tends to zero. -/
theorem tendsto_set_lintegral_zero {ι} {f : α → ℝ≥0∞} (h : ∫⁻ x, f x ∂μ ≠ ∞) {l : Filter ι}
{s : ι → Set α} (hl : Tendsto (μ ∘ s) l (𝓝 0)) :
Tendsto (fun i => ∫⁻ x in s i, f x ∂μ) l (𝓝 0) := by
simp only [ENNReal.nhds_zero, tendsto_iInf, tendsto_principal, mem_Iio,
← pos_iff_ne_zero] at hl ⊢
intro ε ε0
rcases exists_pos_set_lintegral_lt_of_measure_lt h ε0.ne' with ⟨δ, δ0, hδ⟩
exact (hl δ δ0).mono fun i => hδ _
#align measure_theory.tendsto_set_lintegral_zero MeasureTheory.tendsto_set_lintegral_zero
/-- The sum of the lower Lebesgue integrals of two functions is less than or equal to the integral
of their sum. The other inequality needs one of these functions to be (a.e.-)measurable. -/
theorem le_lintegral_add (f g : α → ℝ≥0∞) :
∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ ≤ ∫⁻ a, f a + g a ∂μ := by
simp only [lintegral]
refine ENNReal.biSup_add_biSup_le' (p := fun h : α →ₛ ℝ≥0∞ => h ≤ f)
(q := fun h : α →ₛ ℝ≥0∞ => h ≤ g) ⟨0, zero_le f⟩ ⟨0, zero_le g⟩ fun f' hf' g' hg' => ?_
exact le_iSup₂_of_le (f' + g') (add_le_add hf' hg') (add_lintegral _ _).ge
#align measure_theory.le_lintegral_add MeasureTheory.le_lintegral_add
-- Use stronger lemmas `lintegral_add_left`/`lintegral_add_right` instead
theorem lintegral_add_aux {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ :=
calc
∫⁻ a, f a + g a ∂μ =
∫⁻ a, (⨆ n, (eapprox f n : α → ℝ≥0∞) a) + ⨆ n, (eapprox g n : α → ℝ≥0∞) a ∂μ := by
simp only [iSup_eapprox_apply, hf, hg]
_ = ∫⁻ a, ⨆ n, (eapprox f n + eapprox g n : α → ℝ≥0∞) a ∂μ := by
congr; funext a
rw [ENNReal.iSup_add_iSup_of_monotone]
· simp only [Pi.add_apply]
· intro i j h
exact monotone_eapprox _ h a
· intro i j h
exact monotone_eapprox _ h a
_ = ⨆ n, (eapprox f n).lintegral μ + (eapprox g n).lintegral μ := by
rw [lintegral_iSup]
· congr
funext n
rw [← SimpleFunc.add_lintegral, ← SimpleFunc.lintegral_eq_lintegral]
simp only [Pi.add_apply, SimpleFunc.coe_add]
· measurability
· intro i j h a
dsimp
gcongr <;> exact monotone_eapprox _ h _
_ = (⨆ n, (eapprox f n).lintegral μ) + ⨆ n, (eapprox g n).lintegral μ := by
refine (ENNReal.iSup_add_iSup_of_monotone ?_ ?_).symm <;>
· intro i j h
exact SimpleFunc.lintegral_mono (monotone_eapprox _ h) le_rfl
_ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
rw [lintegral_eq_iSup_eapprox_lintegral hf, lintegral_eq_iSup_eapprox_lintegral hg]
#align measure_theory.lintegral_add_aux MeasureTheory.lintegral_add_aux
/-- If `f g : α → ℝ≥0∞` are two functions and one of them is (a.e.) measurable, then the Lebesgue
integral of `f + g` equals the sum of integrals. This lemma assumes that `f` is integrable, see also
`MeasureTheory.lintegral_add_right` and primed versions of these lemmas. -/
@[simp]
theorem lintegral_add_left {f : α → ℝ≥0∞} (hf : Measurable f) (g : α → ℝ≥0∞) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
refine le_antisymm ?_ (le_lintegral_add _ _)
rcases exists_measurable_le_lintegral_eq μ fun a => f a + g a with ⟨φ, hφm, hφ_le, hφ_eq⟩
calc
∫⁻ a, f a + g a ∂μ = ∫⁻ a, φ a ∂μ := hφ_eq
_ ≤ ∫⁻ a, f a + (φ a - f a) ∂μ := lintegral_mono fun a => le_add_tsub
_ = ∫⁻ a, f a ∂μ + ∫⁻ a, φ a - f a ∂μ := lintegral_add_aux hf (hφm.sub hf)
_ ≤ ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ :=
add_le_add_left (lintegral_mono fun a => tsub_le_iff_left.2 <| hφ_le a) _
#align measure_theory.lintegral_add_left MeasureTheory.lintegral_add_left
theorem lintegral_add_left' {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (g : α → ℝ≥0∞) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
rw [lintegral_congr_ae hf.ae_eq_mk, ← lintegral_add_left hf.measurable_mk,
lintegral_congr_ae (hf.ae_eq_mk.add (ae_eq_refl g))]
#align measure_theory.lintegral_add_left' MeasureTheory.lintegral_add_left'
theorem lintegral_add_right' (f : α → ℝ≥0∞) {g : α → ℝ≥0∞} (hg : AEMeasurable g μ) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
simpa only [add_comm] using lintegral_add_left' hg f
#align measure_theory.lintegral_add_right' MeasureTheory.lintegral_add_right'
/-- If `f g : α → ℝ≥0∞` are two functions and one of them is (a.e.) measurable, then the Lebesgue
integral of `f + g` equals the sum of integrals. This lemma assumes that `g` is integrable, see also
`MeasureTheory.lintegral_add_left` and primed versions of these lemmas. -/
@[simp]
theorem lintegral_add_right (f : α → ℝ≥0∞) {g : α → ℝ≥0∞} (hg : Measurable g) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ :=
lintegral_add_right' f hg.aemeasurable
#align measure_theory.lintegral_add_right MeasureTheory.lintegral_add_right
@[simp]
theorem lintegral_smul_measure (c : ℝ≥0∞) (f : α → ℝ≥0∞) : ∫⁻ a, f a ∂c • μ = c * ∫⁻ a, f a ∂μ := by
simp only [lintegral, iSup_subtype', SimpleFunc.lintegral_smul, ENNReal.mul_iSup, smul_eq_mul]
#align measure_theory.lintegral_smul_measure MeasureTheory.lintegral_smul_measure
lemma set_lintegral_smul_measure (c : ℝ≥0∞) (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ a in s, f a ∂(c • μ) = c * ∫⁻ a in s, f a ∂μ := by
rw [Measure.restrict_smul, lintegral_smul_measure]
@[simp]
theorem lintegral_sum_measure {m : MeasurableSpace α} {ι} (f : α → ℝ≥0∞) (μ : ι → Measure α) :
∫⁻ a, f a ∂Measure.sum μ = ∑' i, ∫⁻ a, f a ∂μ i := by
simp only [lintegral, iSup_subtype', SimpleFunc.lintegral_sum, ENNReal.tsum_eq_iSup_sum]
rw [iSup_comm]
congr; funext s
induction' s using Finset.induction_on with i s hi hs
· simp
simp only [Finset.sum_insert hi, ← hs]
refine (ENNReal.iSup_add_iSup ?_).symm
intro φ ψ
exact
⟨⟨φ ⊔ ψ, fun x => sup_le (φ.2 x) (ψ.2 x)⟩,
add_le_add (SimpleFunc.lintegral_mono le_sup_left le_rfl)
(Finset.sum_le_sum fun j _ => SimpleFunc.lintegral_mono le_sup_right le_rfl)⟩
#align measure_theory.lintegral_sum_measure MeasureTheory.lintegral_sum_measure
theorem hasSum_lintegral_measure {ι} {_ : MeasurableSpace α} (f : α → ℝ≥0∞) (μ : ι → Measure α) :
HasSum (fun i => ∫⁻ a, f a ∂μ i) (∫⁻ a, f a ∂Measure.sum μ) :=
(lintegral_sum_measure f μ).symm ▸ ENNReal.summable.hasSum
#align measure_theory.has_sum_lintegral_measure MeasureTheory.hasSum_lintegral_measure
@[simp]
theorem lintegral_add_measure {m : MeasurableSpace α} (f : α → ℝ≥0∞) (μ ν : Measure α) :
∫⁻ a, f a ∂(μ + ν) = ∫⁻ a, f a ∂μ + ∫⁻ a, f a ∂ν := by
simpa [tsum_fintype] using lintegral_sum_measure f fun b => cond b μ ν
#align measure_theory.lintegral_add_measure MeasureTheory.lintegral_add_measure
@[simp]
theorem lintegral_finset_sum_measure {ι} {m : MeasurableSpace α} (s : Finset ι) (f : α → ℝ≥0∞)
(μ : ι → Measure α) : ∫⁻ a, f a ∂(∑ i ∈ s, μ i) = ∑ i ∈ s, ∫⁻ a, f a ∂μ i := by
rw [← Measure.sum_coe_finset, lintegral_sum_measure, ← Finset.tsum_subtype']
simp only [Finset.coe_sort_coe]
#align measure_theory.lintegral_finset_sum_measure MeasureTheory.lintegral_finset_sum_measure
@[simp]
theorem lintegral_zero_measure {m : MeasurableSpace α} (f : α → ℝ≥0∞) :
∫⁻ a, f a ∂(0 : Measure α) = 0 := by
simp [lintegral]
#align measure_theory.lintegral_zero_measure MeasureTheory.lintegral_zero_measure
@[simp]
theorem lintegral_of_isEmpty {α} [MeasurableSpace α] [IsEmpty α] (μ : Measure α) (f : α → ℝ≥0∞) :
∫⁻ x, f x ∂μ = 0 := by
have : Subsingleton (Measure α) := inferInstance
convert lintegral_zero_measure f
theorem set_lintegral_empty (f : α → ℝ≥0∞) : ∫⁻ x in ∅, f x ∂μ = 0 := by
rw [Measure.restrict_empty, lintegral_zero_measure]
#align measure_theory.set_lintegral_empty MeasureTheory.set_lintegral_empty
theorem set_lintegral_univ (f : α → ℝ≥0∞) : ∫⁻ x in univ, f x ∂μ = ∫⁻ x, f x ∂μ := by
rw [Measure.restrict_univ]
#align measure_theory.set_lintegral_univ MeasureTheory.set_lintegral_univ
theorem set_lintegral_measure_zero (s : Set α) (f : α → ℝ≥0∞) (hs' : μ s = 0) :
∫⁻ x in s, f x ∂μ = 0 := by
convert lintegral_zero_measure _
exact Measure.restrict_eq_zero.2 hs'
#align measure_theory.set_lintegral_measure_zero MeasureTheory.set_lintegral_measure_zero
theorem lintegral_finset_sum' (s : Finset β) {f : β → α → ℝ≥0∞}
(hf : ∀ b ∈ s, AEMeasurable (f b) μ) :
∫⁻ a, ∑ b ∈ s, f b a ∂μ = ∑ b ∈ s, ∫⁻ a, f b a ∂μ := by
induction' s using Finset.induction_on with a s has ih
· simp
· simp only [Finset.sum_insert has]
rw [Finset.forall_mem_insert] at hf
rw [lintegral_add_left' hf.1, ih hf.2]
#align measure_theory.lintegral_finset_sum' MeasureTheory.lintegral_finset_sum'
theorem lintegral_finset_sum (s : Finset β) {f : β → α → ℝ≥0∞} (hf : ∀ b ∈ s, Measurable (f b)) :
∫⁻ a, ∑ b ∈ s, f b a ∂μ = ∑ b ∈ s, ∫⁻ a, f b a ∂μ :=
lintegral_finset_sum' s fun b hb => (hf b hb).aemeasurable
#align measure_theory.lintegral_finset_sum MeasureTheory.lintegral_finset_sum
@[simp]
theorem lintegral_const_mul (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, r * f a ∂μ = r * ∫⁻ a, f a ∂μ :=
calc
∫⁻ a, r * f a ∂μ = ∫⁻ a, ⨆ n, (const α r * eapprox f n) a ∂μ := by
congr
funext a
rw [← iSup_eapprox_apply f hf, ENNReal.mul_iSup]
simp
_ = ⨆ n, r * (eapprox f n).lintegral μ := by
rw [lintegral_iSup]
· congr
funext n
rw [← SimpleFunc.const_mul_lintegral, ← SimpleFunc.lintegral_eq_lintegral]
· intro n
exact SimpleFunc.measurable _
· intro i j h a
exact mul_le_mul_left' (monotone_eapprox _ h _) _
_ = r * ∫⁻ a, f a ∂μ := by rw [← ENNReal.mul_iSup, lintegral_eq_iSup_eapprox_lintegral hf]
#align measure_theory.lintegral_const_mul MeasureTheory.lintegral_const_mul
theorem lintegral_const_mul'' (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) :
∫⁻ a, r * f a ∂μ = r * ∫⁻ a, f a ∂μ := by
have A : ∫⁻ a, f a ∂μ = ∫⁻ a, hf.mk f a ∂μ := lintegral_congr_ae hf.ae_eq_mk
have B : ∫⁻ a, r * f a ∂μ = ∫⁻ a, r * hf.mk f a ∂μ :=
lintegral_congr_ae (EventuallyEq.fun_comp hf.ae_eq_mk _)
rw [A, B, lintegral_const_mul _ hf.measurable_mk]
#align measure_theory.lintegral_const_mul'' MeasureTheory.lintegral_const_mul''
theorem lintegral_const_mul_le (r : ℝ≥0∞) (f : α → ℝ≥0∞) :
r * ∫⁻ a, f a ∂μ ≤ ∫⁻ a, r * f a ∂μ := by
rw [lintegral, ENNReal.mul_iSup]
refine iSup_le fun s => ?_
rw [ENNReal.mul_iSup, iSup_le_iff]
intro hs
rw [← SimpleFunc.const_mul_lintegral, lintegral]
refine le_iSup_of_le (const α r * s) (le_iSup_of_le (fun x => ?_) le_rfl)
exact mul_le_mul_left' (hs x) _
#align measure_theory.lintegral_const_mul_le MeasureTheory.lintegral_const_mul_le
theorem lintegral_const_mul' (r : ℝ≥0∞) (f : α → ℝ≥0∞) (hr : r ≠ ∞) :
∫⁻ a, r * f a ∂μ = r * ∫⁻ a, f a ∂μ := by
by_cases h : r = 0
· simp [h]
apply le_antisymm _ (lintegral_const_mul_le r f)
have rinv : r * r⁻¹ = 1 := ENNReal.mul_inv_cancel h hr
have rinv' : r⁻¹ * r = 1 := by
rw [mul_comm]
exact rinv
have := lintegral_const_mul_le (μ := μ) r⁻¹ fun x => r * f x
simp? [(mul_assoc _ _ _).symm, rinv'] at this says
simp only [(mul_assoc _ _ _).symm, rinv', one_mul] at this
simpa [(mul_assoc _ _ _).symm, rinv] using mul_le_mul_left' this r
#align measure_theory.lintegral_const_mul' MeasureTheory.lintegral_const_mul'
theorem lintegral_mul_const (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, f a * r ∂μ = (∫⁻ a, f a ∂μ) * r := by simp_rw [mul_comm, lintegral_const_mul r hf]
#align measure_theory.lintegral_mul_const MeasureTheory.lintegral_mul_const
theorem lintegral_mul_const'' (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) :
∫⁻ a, f a * r ∂μ = (∫⁻ a, f a ∂μ) * r := by simp_rw [mul_comm, lintegral_const_mul'' r hf]
#align measure_theory.lintegral_mul_const'' MeasureTheory.lintegral_mul_const''
theorem lintegral_mul_const_le (r : ℝ≥0∞) (f : α → ℝ≥0∞) :
(∫⁻ a, f a ∂μ) * r ≤ ∫⁻ a, f a * r ∂μ := by
simp_rw [mul_comm, lintegral_const_mul_le r f]
#align measure_theory.lintegral_mul_const_le MeasureTheory.lintegral_mul_const_le
theorem lintegral_mul_const' (r : ℝ≥0∞) (f : α → ℝ≥0∞) (hr : r ≠ ∞) :
∫⁻ a, f a * r ∂μ = (∫⁻ a, f a ∂μ) * r := by simp_rw [mul_comm, lintegral_const_mul' r f hr]
#align measure_theory.lintegral_mul_const' MeasureTheory.lintegral_mul_const'
/- A double integral of a product where each factor contains only one variable
is a product of integrals -/
theorem lintegral_lintegral_mul {β} [MeasurableSpace β] {ν : Measure β} {f : α → ℝ≥0∞}
{g : β → ℝ≥0∞} (hf : AEMeasurable f μ) (hg : AEMeasurable g ν) :
∫⁻ x, ∫⁻ y, f x * g y ∂ν ∂μ = (∫⁻ x, f x ∂μ) * ∫⁻ y, g y ∂ν := by
simp [lintegral_const_mul'' _ hg, lintegral_mul_const'' _ hf]
#align measure_theory.lintegral_lintegral_mul MeasureTheory.lintegral_lintegral_mul
-- TODO: Need a better way of rewriting inside of an integral
theorem lintegral_rw₁ {f f' : α → β} (h : f =ᵐ[μ] f') (g : β → ℝ≥0∞) :
∫⁻ a, g (f a) ∂μ = ∫⁻ a, g (f' a) ∂μ :=
lintegral_congr_ae <| h.mono fun a h => by dsimp only; rw [h]
#align measure_theory.lintegral_rw₁ MeasureTheory.lintegral_rw₁
-- TODO: Need a better way of rewriting inside of an integral
theorem lintegral_rw₂ {f₁ f₁' : α → β} {f₂ f₂' : α → γ} (h₁ : f₁ =ᵐ[μ] f₁') (h₂ : f₂ =ᵐ[μ] f₂')
(g : β → γ → ℝ≥0∞) : ∫⁻ a, g (f₁ a) (f₂ a) ∂μ = ∫⁻ a, g (f₁' a) (f₂' a) ∂μ :=
lintegral_congr_ae <| h₁.mp <| h₂.mono fun _ h₂ h₁ => by dsimp only; rw [h₁, h₂]
#align measure_theory.lintegral_rw₂ MeasureTheory.lintegral_rw₂
theorem lintegral_indicator_le (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ a, s.indicator f a ∂μ ≤ ∫⁻ a in s, f a ∂μ := by
simp only [lintegral]
apply iSup_le (fun g ↦ (iSup_le (fun hg ↦ ?_)))
have : g ≤ f := hg.trans (indicator_le_self s f)
refine le_iSup_of_le g (le_iSup_of_le this (le_of_eq ?_))
rw [lintegral_restrict, SimpleFunc.lintegral]
congr with t
by_cases H : t = 0
· simp [H]
congr with x
simp only [mem_preimage, mem_singleton_iff, mem_inter_iff, iff_self_and]
rintro rfl
contrapose! H
simpa [H] using hg x
@[simp]
theorem lintegral_indicator (f : α → ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
∫⁻ a, s.indicator f a ∂μ = ∫⁻ a in s, f a ∂μ := by
apply le_antisymm (lintegral_indicator_le f s)
simp only [lintegral, ← restrict_lintegral_eq_lintegral_restrict _ hs, iSup_subtype']
refine iSup_mono' (Subtype.forall.2 fun φ hφ => ?_)
refine ⟨⟨φ.restrict s, fun x => ?_⟩, le_rfl⟩
simp [hφ x, hs, indicator_le_indicator]
#align measure_theory.lintegral_indicator MeasureTheory.lintegral_indicator
theorem lintegral_indicator₀ (f : α → ℝ≥0∞) {s : Set α} (hs : NullMeasurableSet s μ) :
∫⁻ a, s.indicator f a ∂μ = ∫⁻ a in s, f a ∂μ := by
rw [← lintegral_congr_ae (indicator_ae_eq_of_ae_eq_set hs.toMeasurable_ae_eq),
lintegral_indicator _ (measurableSet_toMeasurable _ _),
Measure.restrict_congr_set hs.toMeasurable_ae_eq]
#align measure_theory.lintegral_indicator₀ MeasureTheory.lintegral_indicator₀
theorem lintegral_indicator_const_le (s : Set α) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) a ∂μ ≤ c * μ s :=
(lintegral_indicator_le _ _).trans (set_lintegral_const s c).le
theorem lintegral_indicator_const₀ {s : Set α} (hs : NullMeasurableSet s μ) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) a ∂μ = c * μ s := by
rw [lintegral_indicator₀ _ hs, set_lintegral_const]
theorem lintegral_indicator_const {s : Set α} (hs : MeasurableSet s) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) a ∂μ = c * μ s :=
lintegral_indicator_const₀ hs.nullMeasurableSet c
#align measure_theory.lintegral_indicator_const MeasureTheory.lintegral_indicator_const
theorem set_lintegral_eq_const {f : α → ℝ≥0∞} (hf : Measurable f) (r : ℝ≥0∞) :
∫⁻ x in { x | f x = r }, f x ∂μ = r * μ { x | f x = r } := by
have : ∀ᵐ x ∂μ, x ∈ { x | f x = r } → f x = r := ae_of_all μ fun _ hx => hx
rw [set_lintegral_congr_fun _ this]
· rw [lintegral_const, Measure.restrict_apply MeasurableSet.univ, Set.univ_inter]
· exact hf (measurableSet_singleton r)
#align measure_theory.set_lintegral_eq_const MeasureTheory.set_lintegral_eq_const
theorem lintegral_indicator_one_le (s : Set α) : ∫⁻ a, s.indicator 1 a ∂μ ≤ μ s :=
(lintegral_indicator_const_le _ _).trans <| (one_mul _).le
@[simp]
theorem lintegral_indicator_one₀ (hs : NullMeasurableSet s μ) : ∫⁻ a, s.indicator 1 a ∂μ = μ s :=
(lintegral_indicator_const₀ hs _).trans <| one_mul _
@[simp]
theorem lintegral_indicator_one (hs : MeasurableSet s) : ∫⁻ a, s.indicator 1 a ∂μ = μ s :=
(lintegral_indicator_const hs _).trans <| one_mul _
#align measure_theory.lintegral_indicator_one MeasureTheory.lintegral_indicator_one
/-- A version of **Markov's inequality** for two functions. It doesn't follow from the standard
Markov's inequality because we only assume measurability of `g`, not `f`. -/
theorem lintegral_add_mul_meas_add_le_le_lintegral {f g : α → ℝ≥0∞} (hle : f ≤ᵐ[μ] g)
(hg : AEMeasurable g μ) (ε : ℝ≥0∞) :
∫⁻ a, f a ∂μ + ε * μ { x | f x + ε ≤ g x } ≤ ∫⁻ a, g a ∂μ := by
rcases exists_measurable_le_lintegral_eq μ f with ⟨φ, hφm, hφ_le, hφ_eq⟩
calc
∫⁻ x, f x ∂μ + ε * μ { x | f x + ε ≤ g x } = ∫⁻ x, φ x ∂μ + ε * μ { x | f x + ε ≤ g x } := by
rw [hφ_eq]
_ ≤ ∫⁻ x, φ x ∂μ + ε * μ { x | φ x + ε ≤ g x } := by
gcongr
exact fun x => (add_le_add_right (hφ_le _) _).trans
_ = ∫⁻ x, φ x + indicator { x | φ x + ε ≤ g x } (fun _ => ε) x ∂μ := by
rw [lintegral_add_left hφm, lintegral_indicator₀, set_lintegral_const]
exact measurableSet_le (hφm.nullMeasurable.measurable'.add_const _) hg.nullMeasurable
_ ≤ ∫⁻ x, g x ∂μ := lintegral_mono_ae (hle.mono fun x hx₁ => ?_)
simp only [indicator_apply]; split_ifs with hx₂
exacts [hx₂, (add_zero _).trans_le <| (hφ_le x).trans hx₁]
#align measure_theory.lintegral_add_mul_meas_add_le_le_lintegral MeasureTheory.lintegral_add_mul_meas_add_le_le_lintegral
/-- **Markov's inequality** also known as **Chebyshev's first inequality**. -/
theorem mul_meas_ge_le_lintegral₀ {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (ε : ℝ≥0∞) :
ε * μ { x | ε ≤ f x } ≤ ∫⁻ a, f a ∂μ := by
simpa only [lintegral_zero, zero_add] using
lintegral_add_mul_meas_add_le_le_lintegral (ae_of_all _ fun x => zero_le (f x)) hf ε
#align measure_theory.mul_meas_ge_le_lintegral₀ MeasureTheory.mul_meas_ge_le_lintegral₀
/-- **Markov's inequality** also known as **Chebyshev's first inequality**. For a version assuming
`AEMeasurable`, see `mul_meas_ge_le_lintegral₀`. -/
theorem mul_meas_ge_le_lintegral {f : α → ℝ≥0∞} (hf : Measurable f) (ε : ℝ≥0∞) :
ε * μ { x | ε ≤ f x } ≤ ∫⁻ a, f a ∂μ :=
mul_meas_ge_le_lintegral₀ hf.aemeasurable ε
#align measure_theory.mul_meas_ge_le_lintegral MeasureTheory.mul_meas_ge_le_lintegral
lemma meas_le_lintegral₀ {f : α → ℝ≥0∞} (hf : AEMeasurable f μ)
{s : Set α} (hs : ∀ x ∈ s, 1 ≤ f x) : μ s ≤ ∫⁻ a, f a ∂μ := by
apply le_trans _ (mul_meas_ge_le_lintegral₀ hf 1)
rw [one_mul]
exact measure_mono hs
lemma lintegral_le_meas {s : Set α} {f : α → ℝ≥0∞} (hf : ∀ a, f a ≤ 1) (h'f : ∀ a ∈ sᶜ, f a = 0) :
∫⁻ a, f a ∂μ ≤ μ s := by
apply (lintegral_mono (fun x ↦ ?_)).trans (lintegral_indicator_one_le s)
by_cases hx : x ∈ s
· simpa [hx] using hf x
· simpa [hx] using h'f x hx
theorem lintegral_eq_top_of_measure_eq_top_ne_zero {f : α → ℝ≥0∞} (hf : AEMeasurable f μ)
(hμf : μ {x | f x = ∞} ≠ 0) : ∫⁻ x, f x ∂μ = ∞ :=
eq_top_iff.mpr <|
calc
∞ = ∞ * μ { x | ∞ ≤ f x } := by simp [mul_eq_top, hμf]
_ ≤ ∫⁻ x, f x ∂μ := mul_meas_ge_le_lintegral₀ hf ∞
#align measure_theory.lintegral_eq_top_of_measure_eq_top_ne_zero MeasureTheory.lintegral_eq_top_of_measure_eq_top_ne_zero
theorem setLintegral_eq_top_of_measure_eq_top_ne_zero (hf : AEMeasurable f (μ.restrict s))
(hμf : μ ({x ∈ s | f x = ∞}) ≠ 0) : ∫⁻ x in s, f x ∂μ = ∞ :=
lintegral_eq_top_of_measure_eq_top_ne_zero hf <|
mt (eq_bot_mono <| by rw [← setOf_inter_eq_sep]; exact Measure.le_restrict_apply _ _) hμf
#align measure_theory.set_lintegral_eq_top_of_measure_eq_top_ne_zero MeasureTheory.setLintegral_eq_top_of_measure_eq_top_ne_zero
theorem measure_eq_top_of_lintegral_ne_top (hf : AEMeasurable f μ) (hμf : ∫⁻ x, f x ∂μ ≠ ∞) :
μ {x | f x = ∞} = 0 :=
of_not_not fun h => hμf <| lintegral_eq_top_of_measure_eq_top_ne_zero hf h
#align measure_theory.measure_eq_top_of_lintegral_ne_top MeasureTheory.measure_eq_top_of_lintegral_ne_top
theorem measure_eq_top_of_setLintegral_ne_top (hf : AEMeasurable f (μ.restrict s))
(hμf : ∫⁻ x in s, f x ∂μ ≠ ∞) : μ ({x ∈ s | f x = ∞}) = 0 :=
of_not_not fun h => hμf <| setLintegral_eq_top_of_measure_eq_top_ne_zero hf h
#align measure_theory.measure_eq_top_of_set_lintegral_ne_top MeasureTheory.measure_eq_top_of_setLintegral_ne_top
/-- **Markov's inequality** also known as **Chebyshev's first inequality**. -/
theorem meas_ge_le_lintegral_div {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) {ε : ℝ≥0∞} (hε : ε ≠ 0)
(hε' : ε ≠ ∞) : μ { x | ε ≤ f x } ≤ (∫⁻ a, f a ∂μ) / ε :=
(ENNReal.le_div_iff_mul_le (Or.inl hε) (Or.inl hε')).2 <| by
rw [mul_comm]
exact mul_meas_ge_le_lintegral₀ hf ε
#align measure_theory.meas_ge_le_lintegral_div MeasureTheory.meas_ge_le_lintegral_div
theorem ae_eq_of_ae_le_of_lintegral_le {f g : α → ℝ≥0∞} (hfg : f ≤ᵐ[μ] g) (hf : ∫⁻ x, f x ∂μ ≠ ∞)
(hg : AEMeasurable g μ) (hgf : ∫⁻ x, g x ∂μ ≤ ∫⁻ x, f x ∂μ) : f =ᵐ[μ] g := by
have : ∀ n : ℕ, ∀ᵐ x ∂μ, g x < f x + (n : ℝ≥0∞)⁻¹ := by
intro n
simp only [ae_iff, not_lt]
have : ∫⁻ x, f x ∂μ + (↑n)⁻¹ * μ { x : α | f x + (n : ℝ≥0∞)⁻¹ ≤ g x } ≤ ∫⁻ x, f x ∂μ :=
(lintegral_add_mul_meas_add_le_le_lintegral hfg hg n⁻¹).trans hgf
rw [(ENNReal.cancel_of_ne hf).add_le_iff_nonpos_right, nonpos_iff_eq_zero, mul_eq_zero] at this
exact this.resolve_left (ENNReal.inv_ne_zero.2 (ENNReal.natCast_ne_top _))
refine hfg.mp ((ae_all_iff.2 this).mono fun x hlt hle => hle.antisymm ?_)
suffices Tendsto (fun n : ℕ => f x + (n : ℝ≥0∞)⁻¹) atTop (𝓝 (f x)) from
ge_of_tendsto' this fun i => (hlt i).le
simpa only [inv_top, add_zero] using
tendsto_const_nhds.add (ENNReal.tendsto_inv_iff.2 ENNReal.tendsto_nat_nhds_top)
#align measure_theory.ae_eq_of_ae_le_of_lintegral_le MeasureTheory.ae_eq_of_ae_le_of_lintegral_le
@[simp]
theorem lintegral_eq_zero_iff' {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) :
∫⁻ a, f a ∂μ = 0 ↔ f =ᵐ[μ] 0 :=
have : ∫⁻ _ : α, 0 ∂μ ≠ ∞ := by simp [lintegral_zero, zero_ne_top]
⟨fun h =>
(ae_eq_of_ae_le_of_lintegral_le (ae_of_all _ <| zero_le f) this hf
(h.trans lintegral_zero.symm).le).symm,
fun h => (lintegral_congr_ae h).trans lintegral_zero⟩
#align measure_theory.lintegral_eq_zero_iff' MeasureTheory.lintegral_eq_zero_iff'
@[simp]
theorem lintegral_eq_zero_iff {f : α → ℝ≥0∞} (hf : Measurable f) : ∫⁻ a, f a ∂μ = 0 ↔ f =ᵐ[μ] 0 :=
lintegral_eq_zero_iff' hf.aemeasurable
#align measure_theory.lintegral_eq_zero_iff MeasureTheory.lintegral_eq_zero_iff
theorem lintegral_pos_iff_support {f : α → ℝ≥0∞} (hf : Measurable f) :
(0 < ∫⁻ a, f a ∂μ) ↔ 0 < μ (Function.support f) := by
simp [pos_iff_ne_zero, hf, Filter.EventuallyEq, ae_iff, Function.support]
#align measure_theory.lintegral_pos_iff_support MeasureTheory.lintegral_pos_iff_support
theorem setLintegral_pos_iff {f : α → ℝ≥0∞} (hf : Measurable f) {s : Set α} :
0 < ∫⁻ a in s, f a ∂μ ↔ 0 < μ (Function.support f ∩ s) := by
rw [lintegral_pos_iff_support hf, Measure.restrict_apply (measurableSet_support hf)]
/-- Weaker version of the monotone convergence theorem-/
theorem lintegral_iSup_ae {f : ℕ → α → ℝ≥0∞} (hf : ∀ n, Measurable (f n))
(h_mono : ∀ n, ∀ᵐ a ∂μ, f n a ≤ f n.succ a) : ∫⁻ a, ⨆ n, f n a ∂μ = ⨆ n, ∫⁻ a, f n a ∂μ := by
let ⟨s, hs⟩ := exists_measurable_superset_of_null (ae_iff.1 (ae_all_iff.2 h_mono))
let g n a := if a ∈ s then 0 else f n a
have g_eq_f : ∀ᵐ a ∂μ, ∀ n, g n a = f n a :=
(measure_zero_iff_ae_nmem.1 hs.2.2).mono fun a ha n => if_neg ha
calc
∫⁻ a, ⨆ n, f n a ∂μ = ∫⁻ a, ⨆ n, g n a ∂μ :=
lintegral_congr_ae <| g_eq_f.mono fun a ha => by simp only [ha]
_ = ⨆ n, ∫⁻ a, g n a ∂μ :=
(lintegral_iSup (fun n => measurable_const.piecewise hs.2.1 (hf n))
(monotone_nat_of_le_succ fun n a => ?_))
_ = ⨆ n, ∫⁻ a, f n a ∂μ := by simp only [lintegral_congr_ae (g_eq_f.mono fun _a ha => ha _)]
simp only [g]
split_ifs with h
· rfl
· have := Set.not_mem_subset hs.1 h
simp only [not_forall, not_le, mem_setOf_eq, not_exists, not_lt] at this
exact this n
#align measure_theory.lintegral_supr_ae MeasureTheory.lintegral_iSup_ae
theorem lintegral_sub' {f g : α → ℝ≥0∞} (hg : AEMeasurable g μ) (hg_fin : ∫⁻ a, g a ∂μ ≠ ∞)
(h_le : g ≤ᵐ[μ] f) : ∫⁻ a, f a - g a ∂μ = ∫⁻ a, f a ∂μ - ∫⁻ a, g a ∂μ := by
refine ENNReal.eq_sub_of_add_eq hg_fin ?_
rw [← lintegral_add_right' _ hg]
exact lintegral_congr_ae (h_le.mono fun x hx => tsub_add_cancel_of_le hx)
#align measure_theory.lintegral_sub' MeasureTheory.lintegral_sub'
theorem lintegral_sub {f g : α → ℝ≥0∞} (hg : Measurable g) (hg_fin : ∫⁻ a, g a ∂μ ≠ ∞)
(h_le : g ≤ᵐ[μ] f) : ∫⁻ a, f a - g a ∂μ = ∫⁻ a, f a ∂μ - ∫⁻ a, g a ∂μ :=
lintegral_sub' hg.aemeasurable hg_fin h_le
#align measure_theory.lintegral_sub MeasureTheory.lintegral_sub
theorem lintegral_sub_le' (f g : α → ℝ≥0∞) (hf : AEMeasurable f μ) :
∫⁻ x, g x ∂μ - ∫⁻ x, f x ∂μ ≤ ∫⁻ x, g x - f x ∂μ := by
rw [tsub_le_iff_right]
by_cases hfi : ∫⁻ x, f x ∂μ = ∞
· rw [hfi, add_top]
exact le_top
· rw [← lintegral_add_right' _ hf]
gcongr
exact le_tsub_add
#align measure_theory.lintegral_sub_le' MeasureTheory.lintegral_sub_le'
theorem lintegral_sub_le (f g : α → ℝ≥0∞) (hf : Measurable f) :
∫⁻ x, g x ∂μ - ∫⁻ x, f x ∂μ ≤ ∫⁻ x, g x - f x ∂μ :=
lintegral_sub_le' f g hf.aemeasurable
#align measure_theory.lintegral_sub_le MeasureTheory.lintegral_sub_le
theorem lintegral_strict_mono_of_ae_le_of_frequently_ae_lt {f g : α → ℝ≥0∞} (hg : AEMeasurable g μ)
(hfi : ∫⁻ x, f x ∂μ ≠ ∞) (h_le : f ≤ᵐ[μ] g) (h : ∃ᵐ x ∂μ, f x ≠ g x) :
∫⁻ x, f x ∂μ < ∫⁻ x, g x ∂μ := by
contrapose! h
simp only [not_frequently, Ne, Classical.not_not]
exact ae_eq_of_ae_le_of_lintegral_le h_le hfi hg h
#align measure_theory.lintegral_strict_mono_of_ae_le_of_frequently_ae_lt MeasureTheory.lintegral_strict_mono_of_ae_le_of_frequently_ae_lt
theorem lintegral_strict_mono_of_ae_le_of_ae_lt_on {f g : α → ℝ≥0∞} (hg : AEMeasurable g μ)
(hfi : ∫⁻ x, f x ∂μ ≠ ∞) (h_le : f ≤ᵐ[μ] g) {s : Set α} (hμs : μ s ≠ 0)
(h : ∀ᵐ x ∂μ, x ∈ s → f x < g x) : ∫⁻ x, f x ∂μ < ∫⁻ x, g x ∂μ :=
lintegral_strict_mono_of_ae_le_of_frequently_ae_lt hg hfi h_le <|
((frequently_ae_mem_iff.2 hμs).and_eventually h).mono fun _x hx => (hx.2 hx.1).ne
#align measure_theory.lintegral_strict_mono_of_ae_le_of_ae_lt_on MeasureTheory.lintegral_strict_mono_of_ae_le_of_ae_lt_on
theorem lintegral_strict_mono {f g : α → ℝ≥0∞} (hμ : μ ≠ 0) (hg : AEMeasurable g μ)
(hfi : ∫⁻ x, f x ∂μ ≠ ∞) (h : ∀ᵐ x ∂μ, f x < g x) : ∫⁻ x, f x ∂μ < ∫⁻ x, g x ∂μ := by
rw [Ne, ← Measure.measure_univ_eq_zero] at hμ
refine lintegral_strict_mono_of_ae_le_of_ae_lt_on hg hfi (ae_le_of_ae_lt h) hμ ?_
simpa using h
#align measure_theory.lintegral_strict_mono MeasureTheory.lintegral_strict_mono
theorem set_lintegral_strict_mono {f g : α → ℝ≥0∞} {s : Set α} (hsm : MeasurableSet s)
(hs : μ s ≠ 0) (hg : Measurable g) (hfi : ∫⁻ x in s, f x ∂μ ≠ ∞)
(h : ∀ᵐ x ∂μ, x ∈ s → f x < g x) : ∫⁻ x in s, f x ∂μ < ∫⁻ x in s, g x ∂μ :=
lintegral_strict_mono (by simp [hs]) hg.aemeasurable hfi ((ae_restrict_iff' hsm).mpr h)
#align measure_theory.set_lintegral_strict_mono MeasureTheory.set_lintegral_strict_mono
/-- Monotone convergence theorem for nonincreasing sequences of functions -/
theorem lintegral_iInf_ae {f : ℕ → α → ℝ≥0∞} (h_meas : ∀ n, Measurable (f n))
(h_mono : ∀ n : ℕ, f n.succ ≤ᵐ[μ] f n) (h_fin : ∫⁻ a, f 0 a ∂μ ≠ ∞) :
∫⁻ a, ⨅ n, f n a ∂μ = ⨅ n, ∫⁻ a, f n a ∂μ :=
have fn_le_f0 : ∫⁻ a, ⨅ n, f n a ∂μ ≤ ∫⁻ a, f 0 a ∂μ :=
lintegral_mono fun a => iInf_le_of_le 0 le_rfl
have fn_le_f0' : ⨅ n, ∫⁻ a, f n a ∂μ ≤ ∫⁻ a, f 0 a ∂μ := iInf_le_of_le 0 le_rfl
(ENNReal.sub_right_inj h_fin fn_le_f0 fn_le_f0').1 <|
show ∫⁻ a, f 0 a ∂μ - ∫⁻ a, ⨅ n, f n a ∂μ = ∫⁻ a, f 0 a ∂μ - ⨅ n, ∫⁻ a, f n a ∂μ from
calc
∫⁻ a, f 0 a ∂μ - ∫⁻ a, ⨅ n, f n a ∂μ = ∫⁻ a, f 0 a - ⨅ n, f n a ∂μ :=
(lintegral_sub (measurable_iInf h_meas)
(ne_top_of_le_ne_top h_fin <| lintegral_mono fun a => iInf_le _ _)
(ae_of_all _ fun a => iInf_le _ _)).symm
_ = ∫⁻ a, ⨆ n, f 0 a - f n a ∂μ := congr rfl (funext fun a => ENNReal.sub_iInf)
_ = ⨆ n, ∫⁻ a, f 0 a - f n a ∂μ :=
(lintegral_iSup_ae (fun n => (h_meas 0).sub (h_meas n)) fun n =>
(h_mono n).mono fun a ha => tsub_le_tsub le_rfl ha)
_ = ⨆ n, ∫⁻ a, f 0 a ∂μ - ∫⁻ a, f n a ∂μ :=
(have h_mono : ∀ᵐ a ∂μ, ∀ n : ℕ, f n.succ a ≤ f n a := ae_all_iff.2 h_mono
have h_mono : ∀ n, ∀ᵐ a ∂μ, f n a ≤ f 0 a := fun n =>
h_mono.mono fun a h => by
induction' n with n ih
· exact le_rfl
· exact le_trans (h n) ih
congr_arg iSup <|
funext fun n =>
lintegral_sub (h_meas _) (ne_top_of_le_ne_top h_fin <| lintegral_mono_ae <| h_mono n)
(h_mono n))
_ = ∫⁻ a, f 0 a ∂μ - ⨅ n, ∫⁻ a, f n a ∂μ := ENNReal.sub_iInf.symm
#align measure_theory.lintegral_infi_ae MeasureTheory.lintegral_iInf_ae
/-- Monotone convergence theorem for nonincreasing sequences of functions -/
theorem lintegral_iInf {f : ℕ → α → ℝ≥0∞} (h_meas : ∀ n, Measurable (f n)) (h_anti : Antitone f)
(h_fin : ∫⁻ a, f 0 a ∂μ ≠ ∞) : ∫⁻ a, ⨅ n, f n a ∂μ = ⨅ n, ∫⁻ a, f n a ∂μ :=
lintegral_iInf_ae h_meas (fun n => ae_of_all _ <| h_anti n.le_succ) h_fin
#align measure_theory.lintegral_infi MeasureTheory.lintegral_iInf
theorem lintegral_iInf' {f : ℕ → α → ℝ≥0∞} (h_meas : ∀ n, AEMeasurable (f n) μ)
(h_anti : ∀ᵐ a ∂μ, Antitone (fun i ↦ f i a)) (h_fin : ∫⁻ a, f 0 a ∂μ ≠ ∞) :
∫⁻ a, ⨅ n, f n a ∂μ = ⨅ n, ∫⁻ a, f n a ∂μ := by
simp_rw [← iInf_apply]
let p : α → (ℕ → ℝ≥0∞) → Prop := fun _ f' => Antitone f'
have hp : ∀ᵐ x ∂μ, p x fun i => f i x := h_anti
have h_ae_seq_mono : Antitone (aeSeq h_meas p) := by
intro n m hnm x
by_cases hx : x ∈ aeSeqSet h_meas p
· exact aeSeq.prop_of_mem_aeSeqSet h_meas hx hnm
· simp only [aeSeq, hx, if_false]
exact le_rfl
rw [lintegral_congr_ae (aeSeq.iInf h_meas hp).symm]
simp_rw [iInf_apply]
rw [lintegral_iInf (aeSeq.measurable h_meas p) h_ae_seq_mono]
· congr
exact funext fun n ↦ lintegral_congr_ae (aeSeq.aeSeq_n_eq_fun_n_ae h_meas hp n)
· rwa [lintegral_congr_ae (aeSeq.aeSeq_n_eq_fun_n_ae h_meas hp 0)]
/-- Monotone convergence for an infimum over a directed family and indexed by a countable type -/
theorem lintegral_iInf_directed_of_measurable {mα : MeasurableSpace α} [Countable β]
{f : β → α → ℝ≥0∞} {μ : Measure α} (hμ : μ ≠ 0) (hf : ∀ b, Measurable (f b))
(hf_int : ∀ b, ∫⁻ a, f b a ∂μ ≠ ∞) (h_directed : Directed (· ≥ ·) f) :
∫⁻ a, ⨅ b, f b a ∂μ = ⨅ b, ∫⁻ a, f b a ∂μ := by
cases nonempty_encodable β
cases isEmpty_or_nonempty β
· simp only [iInf_of_empty, lintegral_const,
ENNReal.top_mul (Measure.measure_univ_ne_zero.mpr hμ)]
inhabit β
have : ∀ a, ⨅ b, f b a = ⨅ n, f (h_directed.sequence f n) a := by
refine fun a =>
le_antisymm (le_iInf fun n => iInf_le _ _)
(le_iInf fun b => iInf_le_of_le (Encodable.encode b + 1) ?_)
exact h_directed.sequence_le b a
-- Porting note: used `∘` below to deal with its reduced reducibility
calc
∫⁻ a, ⨅ b, f b a ∂μ
_ = ∫⁻ a, ⨅ n, (f ∘ h_directed.sequence f) n a ∂μ := by simp only [this, Function.comp_apply]
_ = ⨅ n, ∫⁻ a, (f ∘ h_directed.sequence f) n a ∂μ := by
rw [lintegral_iInf ?_ h_directed.sequence_anti]
· exact hf_int _
· exact fun n => hf _
_ = ⨅ b, ∫⁻ a, f b a ∂μ := by
refine le_antisymm (le_iInf fun b => ?_) (le_iInf fun n => ?_)
· exact iInf_le_of_le (Encodable.encode b + 1) (lintegral_mono <| h_directed.sequence_le b)
· exact iInf_le (fun b => ∫⁻ a, f b a ∂μ) _
#align lintegral_infi_directed_of_measurable MeasureTheory.lintegral_iInf_directed_of_measurable
/-- Known as Fatou's lemma, version with `AEMeasurable` functions -/
theorem lintegral_liminf_le' {f : ℕ → α → ℝ≥0∞} (h_meas : ∀ n, AEMeasurable (f n) μ) :
∫⁻ a, liminf (fun n => f n a) atTop ∂μ ≤ liminf (fun n => ∫⁻ a, f n a ∂μ) atTop :=
calc
∫⁻ a, liminf (fun n => f n a) atTop ∂μ = ∫⁻ a, ⨆ n : ℕ, ⨅ i ≥ n, f i a ∂μ := by
simp only [liminf_eq_iSup_iInf_of_nat]
_ = ⨆ n : ℕ, ∫⁻ a, ⨅ i ≥ n, f i a ∂μ :=
(lintegral_iSup' (fun n => aemeasurable_biInf _ (to_countable _) (fun i _ ↦ h_meas i))
(ae_of_all μ fun a n m hnm => iInf_le_iInf_of_subset fun i hi => le_trans hnm hi))
_ ≤ ⨆ n : ℕ, ⨅ i ≥ n, ∫⁻ a, f i a ∂μ := iSup_mono fun n => le_iInf₂_lintegral _
_ = atTop.liminf fun n => ∫⁻ a, f n a ∂μ := Filter.liminf_eq_iSup_iInf_of_nat.symm
#align measure_theory.lintegral_liminf_le' MeasureTheory.lintegral_liminf_le'
/-- Known as Fatou's lemma -/
theorem lintegral_liminf_le {f : ℕ → α → ℝ≥0∞} (h_meas : ∀ n, Measurable (f n)) :
∫⁻ a, liminf (fun n => f n a) atTop ∂μ ≤ liminf (fun n => ∫⁻ a, f n a ∂μ) atTop :=
lintegral_liminf_le' fun n => (h_meas n).aemeasurable
#align measure_theory.lintegral_liminf_le MeasureTheory.lintegral_liminf_le
theorem limsup_lintegral_le {f : ℕ → α → ℝ≥0∞} {g : α → ℝ≥0∞} (hf_meas : ∀ n, Measurable (f n))
(h_bound : ∀ n, f n ≤ᵐ[μ] g) (h_fin : ∫⁻ a, g a ∂μ ≠ ∞) :
limsup (fun n => ∫⁻ a, f n a ∂μ) atTop ≤ ∫⁻ a, limsup (fun n => f n a) atTop ∂μ :=
calc
limsup (fun n => ∫⁻ a, f n a ∂μ) atTop = ⨅ n : ℕ, ⨆ i ≥ n, ∫⁻ a, f i a ∂μ :=
limsup_eq_iInf_iSup_of_nat
_ ≤ ⨅ n : ℕ, ∫⁻ a, ⨆ i ≥ n, f i a ∂μ := iInf_mono fun n => iSup₂_lintegral_le _
_ = ∫⁻ a, ⨅ n : ℕ, ⨆ i ≥ n, f i a ∂μ := by
refine (lintegral_iInf ?_ ?_ ?_).symm
· intro n
exact measurable_biSup _ (to_countable _) (fun i _ ↦ hf_meas i)
· intro n m hnm a
exact iSup_le_iSup_of_subset fun i hi => le_trans hnm hi
· refine ne_top_of_le_ne_top h_fin (lintegral_mono_ae ?_)
refine (ae_all_iff.2 h_bound).mono fun n hn => ?_
exact iSup_le fun i => iSup_le fun _ => hn i
_ = ∫⁻ a, limsup (fun n => f n a) atTop ∂μ := by simp only [limsup_eq_iInf_iSup_of_nat]
#align measure_theory.limsup_lintegral_le MeasureTheory.limsup_lintegral_le
/-- Dominated convergence theorem for nonnegative functions -/
theorem tendsto_lintegral_of_dominated_convergence {F : ℕ → α → ℝ≥0∞} {f : α → ℝ≥0∞}
(bound : α → ℝ≥0∞) (hF_meas : ∀ n, Measurable (F n)) (h_bound : ∀ n, F n ≤ᵐ[μ] bound)
(h_fin : ∫⁻ a, bound a ∂μ ≠ ∞) (h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) :
Tendsto (fun n => ∫⁻ a, F n a ∂μ) atTop (𝓝 (∫⁻ a, f a ∂μ)) :=
tendsto_of_le_liminf_of_limsup_le
(calc
∫⁻ a, f a ∂μ = ∫⁻ a, liminf (fun n : ℕ => F n a) atTop ∂μ :=
lintegral_congr_ae <| h_lim.mono fun a h => h.liminf_eq.symm
_ ≤ liminf (fun n => ∫⁻ a, F n a ∂μ) atTop := lintegral_liminf_le hF_meas
)
(calc
limsup (fun n : ℕ => ∫⁻ a, F n a ∂μ) atTop ≤ ∫⁻ a, limsup (fun n => F n a) atTop ∂μ :=
limsup_lintegral_le hF_meas h_bound h_fin
_ = ∫⁻ a, f a ∂μ := lintegral_congr_ae <| h_lim.mono fun a h => h.limsup_eq
)
#align measure_theory.tendsto_lintegral_of_dominated_convergence MeasureTheory.tendsto_lintegral_of_dominated_convergence
/-- Dominated convergence theorem for nonnegative functions which are just almost everywhere
measurable. -/
theorem tendsto_lintegral_of_dominated_convergence' {F : ℕ → α → ℝ≥0∞} {f : α → ℝ≥0∞}
(bound : α → ℝ≥0∞) (hF_meas : ∀ n, AEMeasurable (F n) μ) (h_bound : ∀ n, F n ≤ᵐ[μ] bound)
(h_fin : ∫⁻ a, bound a ∂μ ≠ ∞) (h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) :
Tendsto (fun n => ∫⁻ a, F n a ∂μ) atTop (𝓝 (∫⁻ a, f a ∂μ)) := by
have : ∀ n, ∫⁻ a, F n a ∂μ = ∫⁻ a, (hF_meas n).mk (F n) a ∂μ := fun n =>
lintegral_congr_ae (hF_meas n).ae_eq_mk
simp_rw [this]
apply
tendsto_lintegral_of_dominated_convergence bound (fun n => (hF_meas n).measurable_mk) _ h_fin
· have : ∀ n, ∀ᵐ a ∂μ, (hF_meas n).mk (F n) a = F n a := fun n => (hF_meas n).ae_eq_mk.symm
have : ∀ᵐ a ∂μ, ∀ n, (hF_meas n).mk (F n) a = F n a := ae_all_iff.mpr this
filter_upwards [this, h_lim] with a H H'
simp_rw [H]
exact H'
· intro n
filter_upwards [h_bound n, (hF_meas n).ae_eq_mk] with a H H'
rwa [H'] at H
#align measure_theory.tendsto_lintegral_of_dominated_convergence' MeasureTheory.tendsto_lintegral_of_dominated_convergence'
/-- Dominated convergence theorem for filters with a countable basis -/
theorem tendsto_lintegral_filter_of_dominated_convergence {ι} {l : Filter ι}
[l.IsCountablyGenerated] {F : ι → α → ℝ≥0∞} {f : α → ℝ≥0∞} (bound : α → ℝ≥0∞)
(hF_meas : ∀ᶠ n in l, Measurable (F n)) (h_bound : ∀ᶠ n in l, ∀ᵐ a ∂μ, F n a ≤ bound a)
(h_fin : ∫⁻ a, bound a ∂μ ≠ ∞) (h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) l (𝓝 (f a))) :
Tendsto (fun n => ∫⁻ a, F n a ∂μ) l (𝓝 <| ∫⁻ a, f a ∂μ) := by
rw [tendsto_iff_seq_tendsto]
intro x xl
have hxl := by
rw [tendsto_atTop'] at xl
exact xl
have h := inter_mem hF_meas h_bound
replace h := hxl _ h
rcases h with ⟨k, h⟩
rw [← tendsto_add_atTop_iff_nat k]
refine tendsto_lintegral_of_dominated_convergence ?_ ?_ ?_ ?_ ?_
· exact bound
· intro
refine (h _ ?_).1
exact Nat.le_add_left _ _
· intro
refine (h _ ?_).2
exact Nat.le_add_left _ _
· assumption
· refine h_lim.mono fun a h_lim => ?_
apply @Tendsto.comp _ _ _ (fun n => x (n + k)) fun n => F n a
· assumption
rw [tendsto_add_atTop_iff_nat]
assumption
#align measure_theory.tendsto_lintegral_filter_of_dominated_convergence MeasureTheory.tendsto_lintegral_filter_of_dominated_convergence
theorem lintegral_tendsto_of_tendsto_of_antitone {f : ℕ → α → ℝ≥0∞} {F : α → ℝ≥0∞}
(hf : ∀ n, AEMeasurable (f n) μ) (h_anti : ∀ᵐ x ∂μ, Antitone fun n ↦ f n x)
(h0 : ∫⁻ a, f 0 a ∂μ ≠ ∞)
(h_tendsto : ∀ᵐ x ∂μ, Tendsto (fun n ↦ f n x) atTop (𝓝 (F x))) :
Tendsto (fun n ↦ ∫⁻ x, f n x ∂μ) atTop (𝓝 (∫⁻ x, F x ∂μ)) := by
have : Antitone fun n ↦ ∫⁻ x, f n x ∂μ := fun i j hij ↦
lintegral_mono_ae (h_anti.mono fun x hx ↦ hx hij)
suffices key : ∫⁻ x, F x ∂μ = ⨅ n, ∫⁻ x, f n x ∂μ by
rw [key]
exact tendsto_atTop_iInf this
rw [← lintegral_iInf' hf h_anti h0]
refine lintegral_congr_ae ?_
filter_upwards [h_anti, h_tendsto] with _ hx_anti hx_tendsto
using tendsto_nhds_unique hx_tendsto (tendsto_atTop_iInf hx_anti)
section
open Encodable
/-- Monotone convergence for a supremum over a directed family and indexed by a countable type -/
theorem lintegral_iSup_directed_of_measurable [Countable β] {f : β → α → ℝ≥0∞}
(hf : ∀ b, Measurable (f b)) (h_directed : Directed (· ≤ ·) f) :
∫⁻ a, ⨆ b, f b a ∂μ = ⨆ b, ∫⁻ a, f b a ∂μ := by
cases nonempty_encodable β
cases isEmpty_or_nonempty β
· simp [iSup_of_empty]
inhabit β
have : ∀ a, ⨆ b, f b a = ⨆ n, f (h_directed.sequence f n) a := by
intro a
refine le_antisymm (iSup_le fun b => ?_) (iSup_le fun n => le_iSup (fun n => f n a) _)
exact le_iSup_of_le (encode b + 1) (h_directed.le_sequence b a)
calc
∫⁻ a, ⨆ b, f b a ∂μ = ∫⁻ a, ⨆ n, f (h_directed.sequence f n) a ∂μ := by simp only [this]
_ = ⨆ n, ∫⁻ a, f (h_directed.sequence f n) a ∂μ :=
(lintegral_iSup (fun n => hf _) h_directed.sequence_mono)
_ = ⨆ b, ∫⁻ a, f b a ∂μ := by
refine le_antisymm (iSup_le fun n => ?_) (iSup_le fun b => ?_)
· exact le_iSup (fun b => ∫⁻ a, f b a ∂μ) _
· exact le_iSup_of_le (encode b + 1) (lintegral_mono <| h_directed.le_sequence b)
#align measure_theory.lintegral_supr_directed_of_measurable MeasureTheory.lintegral_iSup_directed_of_measurable
/-- Monotone convergence for a supremum over a directed family and indexed by a countable type. -/
theorem lintegral_iSup_directed [Countable β] {f : β → α → ℝ≥0∞} (hf : ∀ b, AEMeasurable (f b) μ)
(h_directed : Directed (· ≤ ·) f) : ∫⁻ a, ⨆ b, f b a ∂μ = ⨆ b, ∫⁻ a, f b a ∂μ := by
simp_rw [← iSup_apply]
let p : α → (β → ENNReal) → Prop := fun x f' => Directed LE.le f'
have hp : ∀ᵐ x ∂μ, p x fun i => f i x := by
filter_upwards [] with x i j
obtain ⟨z, hz₁, hz₂⟩ := h_directed i j
exact ⟨z, hz₁ x, hz₂ x⟩
have h_ae_seq_directed : Directed LE.le (aeSeq hf p) := by
intro b₁ b₂
obtain ⟨z, hz₁, hz₂⟩ := h_directed b₁ b₂
refine ⟨z, ?_, ?_⟩ <;>
· intro x
by_cases hx : x ∈ aeSeqSet hf p
· repeat rw [aeSeq.aeSeq_eq_fun_of_mem_aeSeqSet hf hx]
apply_rules [hz₁, hz₂]
· simp only [aeSeq, hx, if_false]
exact le_rfl
convert lintegral_iSup_directed_of_measurable (aeSeq.measurable hf p) h_ae_seq_directed using 1
· simp_rw [← iSup_apply]
rw [lintegral_congr_ae (aeSeq.iSup hf hp).symm]
· congr 1
ext1 b
rw [lintegral_congr_ae]
apply EventuallyEq.symm
exact aeSeq.aeSeq_n_eq_fun_n_ae hf hp _
#align measure_theory.lintegral_supr_directed MeasureTheory.lintegral_iSup_directed
end
theorem lintegral_tsum [Countable β] {f : β → α → ℝ≥0∞} (hf : ∀ i, AEMeasurable (f i) μ) :
∫⁻ a, ∑' i, f i a ∂μ = ∑' i, ∫⁻ a, f i a ∂μ := by
simp only [ENNReal.tsum_eq_iSup_sum]
rw [lintegral_iSup_directed]
· simp [lintegral_finset_sum' _ fun i _ => hf i]
· intro b
exact Finset.aemeasurable_sum _ fun i _ => hf i
· intro s t
use s ∪ t
constructor
· exact fun a => Finset.sum_le_sum_of_subset Finset.subset_union_left
· exact fun a => Finset.sum_le_sum_of_subset Finset.subset_union_right
#align measure_theory.lintegral_tsum MeasureTheory.lintegral_tsum
open Measure
theorem lintegral_iUnion₀ [Countable β] {s : β → Set α} (hm : ∀ i, NullMeasurableSet (s i) μ)
(hd : Pairwise (AEDisjoint μ on s)) (f : α → ℝ≥0∞) :
∫⁻ a in ⋃ i, s i, f a ∂μ = ∑' i, ∫⁻ a in s i, f a ∂μ := by
simp only [Measure.restrict_iUnion_ae hd hm, lintegral_sum_measure]
#align measure_theory.lintegral_Union₀ MeasureTheory.lintegral_iUnion₀
theorem lintegral_iUnion [Countable β] {s : β → Set α} (hm : ∀ i, MeasurableSet (s i))
(hd : Pairwise (Disjoint on s)) (f : α → ℝ≥0∞) :
∫⁻ a in ⋃ i, s i, f a ∂μ = ∑' i, ∫⁻ a in s i, f a ∂μ :=
lintegral_iUnion₀ (fun i => (hm i).nullMeasurableSet) hd.aedisjoint f
#align measure_theory.lintegral_Union MeasureTheory.lintegral_iUnion
theorem lintegral_biUnion₀ {t : Set β} {s : β → Set α} (ht : t.Countable)
(hm : ∀ i ∈ t, NullMeasurableSet (s i) μ) (hd : t.Pairwise (AEDisjoint μ on s)) (f : α → ℝ≥0∞) :
∫⁻ a in ⋃ i ∈ t, s i, f a ∂μ = ∑' i : t, ∫⁻ a in s i, f a ∂μ := by
haveI := ht.toEncodable
rw [biUnion_eq_iUnion, lintegral_iUnion₀ (SetCoe.forall'.1 hm) (hd.subtype _ _)]
#align measure_theory.lintegral_bUnion₀ MeasureTheory.lintegral_biUnion₀
theorem lintegral_biUnion {t : Set β} {s : β → Set α} (ht : t.Countable)
(hm : ∀ i ∈ t, MeasurableSet (s i)) (hd : t.PairwiseDisjoint s) (f : α → ℝ≥0∞) :
∫⁻ a in ⋃ i ∈ t, s i, f a ∂μ = ∑' i : t, ∫⁻ a in s i, f a ∂μ :=
lintegral_biUnion₀ ht (fun i hi => (hm i hi).nullMeasurableSet) hd.aedisjoint f
#align measure_theory.lintegral_bUnion MeasureTheory.lintegral_biUnion
theorem lintegral_biUnion_finset₀ {s : Finset β} {t : β → Set α}
(hd : Set.Pairwise (↑s) (AEDisjoint μ on t)) (hm : ∀ b ∈ s, NullMeasurableSet (t b) μ)
(f : α → ℝ≥0∞) : ∫⁻ a in ⋃ b ∈ s, t b, f a ∂μ = ∑ b ∈ s, ∫⁻ a in t b, f a ∂μ := by
simp only [← Finset.mem_coe, lintegral_biUnion₀ s.countable_toSet hm hd, ← Finset.tsum_subtype']
#align measure_theory.lintegral_bUnion_finset₀ MeasureTheory.lintegral_biUnion_finset₀
theorem lintegral_biUnion_finset {s : Finset β} {t : β → Set α} (hd : Set.PairwiseDisjoint (↑s) t)
(hm : ∀ b ∈ s, MeasurableSet (t b)) (f : α → ℝ≥0∞) :
∫⁻ a in ⋃ b ∈ s, t b, f a ∂μ = ∑ b ∈ s, ∫⁻ a in t b, f a ∂μ :=
lintegral_biUnion_finset₀ hd.aedisjoint (fun b hb => (hm b hb).nullMeasurableSet) f
#align measure_theory.lintegral_bUnion_finset MeasureTheory.lintegral_biUnion_finset
theorem lintegral_iUnion_le [Countable β] (s : β → Set α) (f : α → ℝ≥0∞) :
∫⁻ a in ⋃ i, s i, f a ∂μ ≤ ∑' i, ∫⁻ a in s i, f a ∂μ := by
rw [← lintegral_sum_measure]
exact lintegral_mono' restrict_iUnion_le le_rfl
#align measure_theory.lintegral_Union_le MeasureTheory.lintegral_iUnion_le
theorem lintegral_union {f : α → ℝ≥0∞} {A B : Set α} (hB : MeasurableSet B) (hAB : Disjoint A B) :
∫⁻ a in A ∪ B, f a ∂μ = ∫⁻ a in A, f a ∂μ + ∫⁻ a in B, f a ∂μ := by
rw [restrict_union hAB hB, lintegral_add_measure]
#align measure_theory.lintegral_union MeasureTheory.lintegral_union
theorem lintegral_union_le (f : α → ℝ≥0∞) (s t : Set α) :
∫⁻ a in s ∪ t, f a ∂μ ≤ ∫⁻ a in s, f a ∂μ + ∫⁻ a in t, f a ∂μ := by
rw [← lintegral_add_measure]
exact lintegral_mono' (restrict_union_le _ _) le_rfl
theorem lintegral_inter_add_diff {B : Set α} (f : α → ℝ≥0∞) (A : Set α) (hB : MeasurableSet B) :
∫⁻ x in A ∩ B, f x ∂μ + ∫⁻ x in A \ B, f x ∂μ = ∫⁻ x in A, f x ∂μ := by
rw [← lintegral_add_measure, restrict_inter_add_diff _ hB]
#align measure_theory.lintegral_inter_add_diff MeasureTheory.lintegral_inter_add_diff
theorem lintegral_add_compl (f : α → ℝ≥0∞) {A : Set α} (hA : MeasurableSet A) :
∫⁻ x in A, f x ∂μ + ∫⁻ x in Aᶜ, f x ∂μ = ∫⁻ x, f x ∂μ := by
rw [← lintegral_add_measure, Measure.restrict_add_restrict_compl hA]
#align measure_theory.lintegral_add_compl MeasureTheory.lintegral_add_compl
theorem lintegral_max {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g) :
∫⁻ x, max (f x) (g x) ∂μ =
∫⁻ x in { x | f x ≤ g x }, g x ∂μ + ∫⁻ x in { x | g x < f x }, f x ∂μ := by
have hm : MeasurableSet { x | f x ≤ g x } := measurableSet_le hf hg
rw [← lintegral_add_compl (fun x => max (f x) (g x)) hm]
simp only [← compl_setOf, ← not_le]
refine congr_arg₂ (· + ·) (set_lintegral_congr_fun hm ?_) (set_lintegral_congr_fun hm.compl ?_)
exacts [ae_of_all _ fun x => max_eq_right (a := f x) (b := g x),
ae_of_all _ fun x (hx : ¬ f x ≤ g x) => max_eq_left (not_le.1 hx).le]
#align measure_theory.lintegral_max MeasureTheory.lintegral_max
theorem set_lintegral_max {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g) (s : Set α) :
∫⁻ x in s, max (f x) (g x) ∂μ =
∫⁻ x in s ∩ { x | f x ≤ g x }, g x ∂μ + ∫⁻ x in s ∩ { x | g x < f x }, f x ∂μ := by
rw [lintegral_max hf hg, restrict_restrict, restrict_restrict, inter_comm s, inter_comm s]
exacts [measurableSet_lt hg hf, measurableSet_le hf hg]
#align measure_theory.set_lintegral_max MeasureTheory.set_lintegral_max
theorem lintegral_map {mβ : MeasurableSpace β} {f : β → ℝ≥0∞} {g : α → β} (hf : Measurable f)
(hg : Measurable g) : ∫⁻ a, f a ∂map g μ = ∫⁻ a, f (g a) ∂μ := by
erw [lintegral_eq_iSup_eapprox_lintegral hf, lintegral_eq_iSup_eapprox_lintegral (hf.comp hg)]
congr with n : 1
convert SimpleFunc.lintegral_map _ hg
ext1 x; simp only [eapprox_comp hf hg, coe_comp]
#align measure_theory.lintegral_map MeasureTheory.lintegral_map
theorem lintegral_map' {mβ : MeasurableSpace β} {f : β → ℝ≥0∞} {g : α → β}
(hf : AEMeasurable f (Measure.map g μ)) (hg : AEMeasurable g μ) :
∫⁻ a, f a ∂Measure.map g μ = ∫⁻ a, f (g a) ∂μ :=
calc
∫⁻ a, f a ∂Measure.map g μ = ∫⁻ a, hf.mk f a ∂Measure.map g μ :=
lintegral_congr_ae hf.ae_eq_mk
_ = ∫⁻ a, hf.mk f a ∂Measure.map (hg.mk g) μ := by
congr 1
exact Measure.map_congr hg.ae_eq_mk
_ = ∫⁻ a, hf.mk f (hg.mk g a) ∂μ := lintegral_map hf.measurable_mk hg.measurable_mk
_ = ∫⁻ a, hf.mk f (g a) ∂μ := lintegral_congr_ae <| hg.ae_eq_mk.symm.fun_comp _
_ = ∫⁻ a, f (g a) ∂μ := lintegral_congr_ae (ae_eq_comp hg hf.ae_eq_mk.symm)
#align measure_theory.lintegral_map' MeasureTheory.lintegral_map'
theorem lintegral_map_le {mβ : MeasurableSpace β} (f : β → ℝ≥0∞) {g : α → β} (hg : Measurable g) :
∫⁻ a, f a ∂Measure.map g μ ≤ ∫⁻ a, f (g a) ∂μ := by
rw [← iSup_lintegral_measurable_le_eq_lintegral, ← iSup_lintegral_measurable_le_eq_lintegral]
refine iSup₂_le fun i hi => iSup_le fun h'i => ?_
refine le_iSup₂_of_le (i ∘ g) (hi.comp hg) ?_
exact le_iSup_of_le (fun x => h'i (g x)) (le_of_eq (lintegral_map hi hg))
#align measure_theory.lintegral_map_le MeasureTheory.lintegral_map_le
theorem lintegral_comp [MeasurableSpace β] {f : β → ℝ≥0∞} {g : α → β} (hf : Measurable f)
(hg : Measurable g) : lintegral μ (f ∘ g) = ∫⁻ a, f a ∂map g μ :=
(lintegral_map hf hg).symm
#align measure_theory.lintegral_comp MeasureTheory.lintegral_comp
theorem set_lintegral_map [MeasurableSpace β] {f : β → ℝ≥0∞} {g : α → β} {s : Set β}
(hs : MeasurableSet s) (hf : Measurable f) (hg : Measurable g) :
∫⁻ y in s, f y ∂map g μ = ∫⁻ x in g ⁻¹' s, f (g x) ∂μ := by
rw [restrict_map hg hs, lintegral_map hf hg]
#align measure_theory.set_lintegral_map MeasureTheory.set_lintegral_map
theorem lintegral_indicator_const_comp {mβ : MeasurableSpace β} {f : α → β} {s : Set β}
(hf : Measurable f) (hs : MeasurableSet s) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) (f a) ∂μ = c * μ (f ⁻¹' s) := by
erw [lintegral_comp (measurable_const.indicator hs) hf, lintegral_indicator_const hs,
Measure.map_apply hf hs]
#align measure_theory.lintegral_indicator_const_comp MeasureTheory.lintegral_indicator_const_comp
/-- If `g : α → β` is a measurable embedding and `f : β → ℝ≥0∞` is any function (not necessarily
measurable), then `∫⁻ a, f a ∂(map g μ) = ∫⁻ a, f (g a) ∂μ`. Compare with `lintegral_map` which
applies to any measurable `g : α → β` but requires that `f` is measurable as well. -/
theorem _root_.MeasurableEmbedding.lintegral_map [MeasurableSpace β] {g : α → β}
(hg : MeasurableEmbedding g) (f : β → ℝ≥0∞) : ∫⁻ a, f a ∂map g μ = ∫⁻ a, f (g a) ∂μ := by
rw [lintegral, lintegral]
refine le_antisymm (iSup₂_le fun f₀ hf₀ => ?_) (iSup₂_le fun f₀ hf₀ => ?_)
· rw [SimpleFunc.lintegral_map _ hg.measurable]
have : (f₀.comp g hg.measurable : α → ℝ≥0∞) ≤ f ∘ g := fun x => hf₀ (g x)
exact le_iSup_of_le (comp f₀ g hg.measurable) (by exact le_iSup (α := ℝ≥0∞) _ this)
· rw [← f₀.extend_comp_eq hg (const _ 0), ← SimpleFunc.lintegral_map, ←
SimpleFunc.lintegral_eq_lintegral, ← lintegral]
refine lintegral_mono_ae (hg.ae_map_iff.2 <| eventually_of_forall fun x => ?_)
exact (extend_apply _ _ _ _).trans_le (hf₀ _)
#align measurable_embedding.lintegral_map MeasurableEmbedding.lintegral_map
/-- The `lintegral` transforms appropriately under a measurable equivalence `g : α ≃ᵐ β`.
(Compare `lintegral_map`, which applies to a wider class of functions `g : α → β`, but requires
measurability of the function being integrated.) -/
theorem lintegral_map_equiv [MeasurableSpace β] (f : β → ℝ≥0∞) (g : α ≃ᵐ β) :
∫⁻ a, f a ∂map g μ = ∫⁻ a, f (g a) ∂μ :=
g.measurableEmbedding.lintegral_map f
#align measure_theory.lintegral_map_equiv MeasureTheory.lintegral_map_equiv
protected theorem MeasurePreserving.lintegral_map_equiv [MeasurableSpace β] {ν : Measure β}
(f : β → ℝ≥0∞) (g : α ≃ᵐ β) (hg : MeasurePreserving g μ ν) :
∫⁻ a, f a ∂ν = ∫⁻ a, f (g a) ∂μ := by
rw [← MeasureTheory.lintegral_map_equiv f g, hg.map_eq]
theorem MeasurePreserving.lintegral_comp {mb : MeasurableSpace β} {ν : Measure β} {g : α → β}
(hg : MeasurePreserving g μ ν) {f : β → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, f (g a) ∂μ = ∫⁻ b, f b ∂ν := by rw [← hg.map_eq, lintegral_map hf hg.measurable]
#align measure_theory.measure_preserving.lintegral_comp MeasureTheory.MeasurePreserving.lintegral_comp
theorem MeasurePreserving.lintegral_comp_emb {mb : MeasurableSpace β} {ν : Measure β} {g : α → β}
(hg : MeasurePreserving g μ ν) (hge : MeasurableEmbedding g) (f : β → ℝ≥0∞) :
∫⁻ a, f (g a) ∂μ = ∫⁻ b, f b ∂ν := by rw [← hg.map_eq, hge.lintegral_map]
#align measure_theory.measure_preserving.lintegral_comp_emb MeasureTheory.MeasurePreserving.lintegral_comp_emb
theorem MeasurePreserving.set_lintegral_comp_preimage {mb : MeasurableSpace β} {ν : Measure β}
{g : α → β} (hg : MeasurePreserving g μ ν) {s : Set β} (hs : MeasurableSet s) {f : β → ℝ≥0∞}
(hf : Measurable f) : ∫⁻ a in g ⁻¹' s, f (g a) ∂μ = ∫⁻ b in s, f b ∂ν := by
rw [← hg.map_eq, set_lintegral_map hs hf hg.measurable]
#align measure_theory.measure_preserving.set_lintegral_comp_preimage MeasureTheory.MeasurePreserving.set_lintegral_comp_preimage
theorem MeasurePreserving.set_lintegral_comp_preimage_emb {mb : MeasurableSpace β} {ν : Measure β}
{g : α → β} (hg : MeasurePreserving g μ ν) (hge : MeasurableEmbedding g) (f : β → ℝ≥0∞)
(s : Set β) : ∫⁻ a in g ⁻¹' s, f (g a) ∂μ = ∫⁻ b in s, f b ∂ν := by
rw [← hg.map_eq, hge.restrict_map, hge.lintegral_map]
#align measure_theory.measure_preserving.set_lintegral_comp_preimage_emb MeasureTheory.MeasurePreserving.set_lintegral_comp_preimage_emb
theorem MeasurePreserving.set_lintegral_comp_emb {mb : MeasurableSpace β} {ν : Measure β}
{g : α → β} (hg : MeasurePreserving g μ ν) (hge : MeasurableEmbedding g) (f : β → ℝ≥0∞)
(s : Set α) : ∫⁻ a in s, f (g a) ∂μ = ∫⁻ b in g '' s, f b ∂ν := by
rw [← hg.set_lintegral_comp_preimage_emb hge, preimage_image_eq _ hge.injective]
#align measure_theory.measure_preserving.set_lintegral_comp_emb MeasureTheory.MeasurePreserving.set_lintegral_comp_emb
theorem lintegral_subtype_comap {s : Set α} (hs : MeasurableSet s) (f : α → ℝ≥0∞) :
∫⁻ x : s, f x ∂(μ.comap (↑)) = ∫⁻ x in s, f x ∂μ := by
rw [← (MeasurableEmbedding.subtype_coe hs).lintegral_map, map_comap_subtype_coe hs]
theorem set_lintegral_subtype {s : Set α} (hs : MeasurableSet s) (t : Set s) (f : α → ℝ≥0∞) :
∫⁻ x in t, f x ∂(μ.comap (↑)) = ∫⁻ x in (↑) '' t, f x ∂μ := by
rw [(MeasurableEmbedding.subtype_coe hs).restrict_comap, lintegral_subtype_comap hs,
restrict_restrict hs, inter_eq_right.2 (Subtype.coe_image_subset _ _)]
section DiracAndCount
variable [MeasurableSpace α]
theorem lintegral_dirac' (a : α) {f : α → ℝ≥0∞} (hf : Measurable f) : ∫⁻ a, f a ∂dirac a = f a := by
simp [lintegral_congr_ae (ae_eq_dirac' hf)]
#align measure_theory.lintegral_dirac' MeasureTheory.lintegral_dirac'
theorem lintegral_dirac [MeasurableSingletonClass α] (a : α) (f : α → ℝ≥0∞) :
∫⁻ a, f a ∂dirac a = f a := by simp [lintegral_congr_ae (ae_eq_dirac f)]
#align measure_theory.lintegral_dirac MeasureTheory.lintegral_dirac
theorem set_lintegral_dirac' {a : α} {f : α → ℝ≥0∞} (hf : Measurable f) {s : Set α}
(hs : MeasurableSet s) [Decidable (a ∈ s)] :
∫⁻ x in s, f x ∂Measure.dirac a = if a ∈ s then f a else 0 := by
rw [restrict_dirac' hs]
split_ifs
· exact lintegral_dirac' _ hf
· exact lintegral_zero_measure _
#align measure_theory.set_lintegral_dirac' MeasureTheory.set_lintegral_dirac'
theorem set_lintegral_dirac {a : α} (f : α → ℝ≥0∞) (s : Set α) [MeasurableSingletonClass α]
[Decidable (a ∈ s)] : ∫⁻ x in s, f x ∂Measure.dirac a = if a ∈ s then f a else 0 := by
rw [restrict_dirac]
split_ifs
· exact lintegral_dirac _ _
· exact lintegral_zero_measure _
#align measure_theory.set_lintegral_dirac MeasureTheory.set_lintegral_dirac
theorem lintegral_count' {f : α → ℝ≥0∞} (hf : Measurable f) : ∫⁻ a, f a ∂count = ∑' a, f a := by
rw [count, lintegral_sum_measure]
congr
exact funext fun a => lintegral_dirac' a hf
#align measure_theory.lintegral_count' MeasureTheory.lintegral_count'
theorem lintegral_count [MeasurableSingletonClass α] (f : α → ℝ≥0∞) :
∫⁻ a, f a ∂count = ∑' a, f a := by
rw [count, lintegral_sum_measure]
congr
exact funext fun a => lintegral_dirac a f
#align measure_theory.lintegral_count MeasureTheory.lintegral_count
theorem _root_.ENNReal.tsum_const_eq [MeasurableSingletonClass α] (c : ℝ≥0∞) :
∑' _ : α, c = c * Measure.count (univ : Set α) := by rw [← lintegral_count, lintegral_const]
#align ennreal.tsum_const_eq ENNReal.tsum_const_eq
/-- Markov's inequality for the counting measure with hypothesis using `tsum` in `ℝ≥0∞`. -/
theorem _root_.ENNReal.count_const_le_le_of_tsum_le [MeasurableSingletonClass α] {a : α → ℝ≥0∞}
(a_mble : Measurable a) {c : ℝ≥0∞} (tsum_le_c : ∑' i, a i ≤ c) {ε : ℝ≥0∞} (ε_ne_zero : ε ≠ 0)
(ε_ne_top : ε ≠ ∞) : Measure.count { i : α | ε ≤ a i } ≤ c / ε := by
rw [← lintegral_count] at tsum_le_c
apply (MeasureTheory.meas_ge_le_lintegral_div a_mble.aemeasurable ε_ne_zero ε_ne_top).trans
exact ENNReal.div_le_div tsum_le_c rfl.le
#align ennreal.count_const_le_le_of_tsum_le ENNReal.count_const_le_le_of_tsum_le
/-- Markov's inequality for counting measure with hypothesis using `tsum` in `ℝ≥0`. -/
theorem _root_.NNReal.count_const_le_le_of_tsum_le [MeasurableSingletonClass α] {a : α → ℝ≥0}
(a_mble : Measurable a) (a_summable : Summable a) {c : ℝ≥0} (tsum_le_c : ∑' i, a i ≤ c)
{ε : ℝ≥0} (ε_ne_zero : ε ≠ 0) : Measure.count { i : α | ε ≤ a i } ≤ c / ε := by
rw [show (fun i => ε ≤ a i) = fun i => (ε : ℝ≥0∞) ≤ ((↑) ∘ a) i by
funext i
simp only [ENNReal.coe_le_coe, Function.comp]]
apply
ENNReal.count_const_le_le_of_tsum_le (measurable_coe_nnreal_ennreal.comp a_mble) _
(mod_cast ε_ne_zero) (@ENNReal.coe_ne_top ε)
convert ENNReal.coe_le_coe.mpr tsum_le_c
simp_rw [Function.comp_apply]
rw [ENNReal.tsum_coe_eq a_summable.hasSum]
#align nnreal.count_const_le_le_of_tsum_le NNReal.count_const_le_le_of_tsum_le
end DiracAndCount
section Countable
/-!
### Lebesgue integral over finite and countable types and sets
-/
theorem lintegral_countable' [Countable α] [MeasurableSingletonClass α] (f : α → ℝ≥0∞) :
∫⁻ a, f a ∂μ = ∑' a, f a * μ {a} := by
conv_lhs => rw [← sum_smul_dirac μ, lintegral_sum_measure]
congr 1 with a : 1
rw [lintegral_smul_measure, lintegral_dirac, mul_comm]
#align measure_theory.lintegral_countable' MeasureTheory.lintegral_countable'
theorem lintegral_singleton' {f : α → ℝ≥0∞} (hf : Measurable f) (a : α) :
∫⁻ x in {a}, f x ∂μ = f a * μ {a} := by
simp only [restrict_singleton, lintegral_smul_measure, lintegral_dirac' _ hf, mul_comm]
#align measure_theory.lintegral_singleton' MeasureTheory.lintegral_singleton'
theorem lintegral_singleton [MeasurableSingletonClass α] (f : α → ℝ≥0∞) (a : α) :
∫⁻ x in {a}, f x ∂μ = f a * μ {a} := by
simp only [restrict_singleton, lintegral_smul_measure, lintegral_dirac, mul_comm]
#align measure_theory.lintegral_singleton MeasureTheory.lintegral_singleton
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 1,595 | 1,601 | theorem lintegral_countable [MeasurableSingletonClass α] (f : α → ℝ≥0∞) {s : Set α}
(hs : s.Countable) : ∫⁻ a in s, f a ∂μ = ∑' a : s, f a * μ {(a : α)} :=
calc
∫⁻ a in s, f a ∂μ = ∫⁻ a in ⋃ x ∈ s, {x}, f a ∂μ := by | rw [biUnion_of_singleton]
_ = ∑' a : s, ∫⁻ x in {(a : α)}, f x ∂μ :=
(lintegral_biUnion hs (fun _ _ => measurableSet_singleton _) (pairwiseDisjoint_fiber id s) _)
_ = ∑' a : s, f a * μ {(a : α)} := by simp only [lintegral_singleton]
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Simon Hudon, Scott Morrison
-/
import Mathlib.CategoryTheory.EqToHom
import Mathlib.CategoryTheory.NatIso
import Mathlib.CategoryTheory.Products.Basic
#align_import category_theory.pi.basic from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988"
/-!
# Categories of indexed families of objects.
We define the pointwise category structure on indexed families of objects in a category
(and also the dependent generalization).
-/
namespace CategoryTheory
universe w₀ w₁ w₂ v₁ v₂ v₃ u₁ u₂ u₃
variable {I : Type w₀} {J : Type w₁} (C : I → Type u₁) [∀ i, Category.{v₁} (C i)]
/-- `pi C` gives the cartesian product of an indexed family of categories.
-/
instance pi : Category.{max w₀ v₁} (∀ i, C i) where
Hom X Y := ∀ i, X i ⟶ Y i
id X i := 𝟙 (X i)
comp f g i := f i ≫ g i
#align category_theory.pi CategoryTheory.pi
/-- This provides some assistance to typeclass search in a common situation,
which otherwise fails. (Without this `CategoryTheory.Pi.has_limit_of_has_limit_comp_eval` fails.)
-/
abbrev pi' {I : Type v₁} (C : I → Type u₁) [∀ i, Category.{v₁} (C i)] : Category.{v₁} (∀ i, C i) :=
CategoryTheory.pi C
#align category_theory.pi' CategoryTheory.pi'
attribute [instance] pi'
namespace Pi
@[simp]
theorem id_apply (X : ∀ i, C i) (i) : (𝟙 X : ∀ i, X i ⟶ X i) i = 𝟙 (X i) :=
rfl
#align category_theory.pi.id_apply CategoryTheory.Pi.id_apply
@[simp]
theorem comp_apply {X Y Z : ∀ i, C i} (f : X ⟶ Y) (g : Y ⟶ Z) (i) :
(f ≫ g : ∀ i, X i ⟶ Z i) i = f i ≫ g i :=
rfl
#align category_theory.pi.comp_apply CategoryTheory.Pi.comp_apply
-- Porting note: need to add an additional `ext` lemma.
@[ext]
lemma ext {X Y : ∀ i, C i} {f g : X ⟶ Y} (w : ∀ i, f i = g i) : f = g :=
funext (w ·)
/--
The evaluation functor at `i : I`, sending an `I`-indexed family of objects to the object over `i`.
-/
@[simps]
def eval (i : I) : (∀ i, C i) ⥤ C i where
obj f := f i
map α := α i
#align category_theory.pi.eval CategoryTheory.Pi.eval
section
variable {J : Type w₁}
/- Porting note: add this because Lean cannot see directly through the `∘` for
`Function.comp` -/
instance (f : J → I) : (j : J) → Category ((C ∘ f) j) := by
dsimp
infer_instance
/-- Pull back an `I`-indexed family of objects to a `J`-indexed family, along a function `J → I`.
-/
@[simps]
def comap (h : J → I) : (∀ i, C i) ⥤ (∀ j, C (h j)) where
obj f i := f (h i)
map α i := α (h i)
#align category_theory.pi.comap CategoryTheory.Pi.comap
variable (I)
/-- The natural isomorphism between
pulling back a grading along the identity function,
and the identity functor. -/
@[simps]
def comapId : comap C (id : I → I) ≅ 𝟭 (∀ i, C i) where
hom := { app := fun X => 𝟙 X }
inv := { app := fun X => 𝟙 X }
#align category_theory.pi.comap_id CategoryTheory.Pi.comapId
example (g : J → I) : (j : J) → Category (C (g j)) := by infer_instance
variable {I}
variable {K : Type w₂}
/-- The natural isomorphism comparing between
pulling back along two successive functions, and
pulling back along their composition
-/
@[simps!]
def comapComp (f : K → J) (g : J → I) : comap C g ⋙ comap (C ∘ g) f ≅ comap C (g ∘ f) where
hom :=
{ app := fun X b => 𝟙 (X (g (f b)))
naturality := fun X Y f' => by simp only [comap, Function.comp]; funext; simp }
inv :=
{ app := fun X b => 𝟙 (X (g (f b)))
naturality := fun X Y f' => by simp only [comap, Function.comp]; funext; simp }
#align category_theory.pi.comap_comp CategoryTheory.Pi.comapComp
/-- The natural isomorphism between pulling back then evaluating, and just evaluating. -/
@[simps!]
def comapEvalIsoEval (h : J → I) (j : J) : comap C h ⋙ eval (C ∘ h) j ≅ eval C (h j) :=
NatIso.ofComponents (fun f => Iso.refl _) (by simp only [Iso.refl]; aesop_cat)
#align category_theory.pi.comap_eval_iso_eval CategoryTheory.Pi.comapEvalIsoEval
end
section
variable {J : Type w₀} {D : J → Type u₁} [∀ j, Category.{v₁} (D j)]
/- Porting note: maybe mixing up universes -/
instance sumElimCategory : ∀ s : Sum I J, Category.{v₁} (Sum.elim C D s)
| Sum.inl i => by
dsimp
infer_instance
| Sum.inr j => by
dsimp
infer_instance
#align category_theory.pi.sum_elim_category CategoryTheory.Pi.sumElimCategoryₓ
/- Porting note: replaced `Sum.rec` with `match`'s per the error about
current state of code generation -/
/-- The bifunctor combining an `I`-indexed family of objects with a `J`-indexed family of objects
to obtain an `I ⊕ J`-indexed family of objects.
-/
@[simps]
def sum : (∀ i, C i) ⥤ (∀ j, D j) ⥤ ∀ s : Sum I J, Sum.elim C D s where
obj X :=
{ obj := fun Y s =>
match s with
| .inl i => X i
| .inr j => Y j
map := fun {Y} {Y'} f s =>
match s with
| .inl i => 𝟙 (X i)
| .inr j => f j }
map {X} {X'} f :=
{ app := fun Y s =>
match s with
| .inl i => f i
| .inr j => 𝟙 (Y j) }
#align category_theory.pi.sum CategoryTheory.Pi.sum
end
variable {C}
/-- An isomorphism between `I`-indexed objects gives an isomorphism between each
pair of corresponding components. -/
@[simps]
def isoApp {X Y : ∀ i, C i} (f : X ≅ Y) (i : I) : X i ≅ Y i :=
⟨f.hom i, f.inv i,
by rw [← comp_apply, Iso.hom_inv_id, id_apply], by rw [← comp_apply, Iso.inv_hom_id, id_apply]⟩
#align category_theory.pi.iso_app CategoryTheory.Pi.isoApp
@[simp]
theorem isoApp_refl (X : ∀ i, C i) (i : I) : isoApp (Iso.refl X) i = Iso.refl (X i) :=
rfl
#align category_theory.pi.iso_app_refl CategoryTheory.Pi.isoApp_refl
@[simp]
theorem isoApp_symm {X Y : ∀ i, C i} (f : X ≅ Y) (i : I) : isoApp f.symm i = (isoApp f i).symm :=
rfl
#align category_theory.pi.iso_app_symm CategoryTheory.Pi.isoApp_symm
@[simp]
theorem isoApp_trans {X Y Z : ∀ i, C i} (f : X ≅ Y) (g : Y ≅ Z) (i : I) :
isoApp (f ≪≫ g) i = isoApp f i ≪≫ isoApp g i :=
rfl
#align category_theory.pi.iso_app_trans CategoryTheory.Pi.isoApp_trans
end Pi
namespace Functor
variable {C}
variable {D : I → Type u₂} [∀ i, Category.{v₂} (D i)] {A : Type u₃} [Category.{v₃} A]
/-- Assemble an `I`-indexed family of functors into a functor between the pi types.
-/
@[simps]
def pi (F : ∀ i, C i ⥤ D i) : (∀ i, C i) ⥤ ∀ i, D i where
obj f i := (F i).obj (f i)
map α i := (F i).map (α i)
#align category_theory.functor.pi CategoryTheory.Functor.pi
/-- Similar to `pi`, but all functors come from the same category `A`
-/
@[simps]
def pi' (f : ∀ i, A ⥤ C i) : A ⥤ ∀ i, C i where
obj a i := (f i).obj a
map h i := (f i).map h
#align category_theory.functor.pi' CategoryTheory.Functor.pi'
/-- The projections of `Functor.pi' F` are isomorphic to the functors of the family `F` -/
@[simps!]
def pi'CompEval {A : Type*} [Category A] (F : ∀ i, A ⥤ C i) (i : I) :
pi' F ⋙ Pi.eval C i ≅ F i :=
Iso.refl _
section EqToHom
@[simp]
theorem eqToHom_proj {x x' : ∀ i, C i} (h : x = x') (i : I) :
(eqToHom h : x ⟶ x') i = eqToHom (Function.funext_iff.mp h i) := by
subst h
rfl
#align category_theory.functor.eq_to_hom_proj CategoryTheory.Functor.eqToHom_proj
end EqToHom
-- One could add some natural isomorphisms showing
-- how `Functor.pi` commutes with `Pi.eval` and `Pi.comap`.
@[simp]
| Mathlib/CategoryTheory/Pi/Basic.lean | 237 | 242 | theorem pi'_eval (f : ∀ i, A ⥤ C i) (i : I) : pi' f ⋙ Pi.eval C i = f i := by |
apply Functor.ext
· intro _ _ _
simp
· intro _
rfl
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Mario Carneiro, Johan Commelin, Amelia Livingston, Anne Baanen
-/
import Mathlib.Algebra.Algebra.Tower
import Mathlib.Algebra.GroupWithZero.NonZeroDivisors
import Mathlib.GroupTheory.MonoidLocalization
import Mathlib.RingTheory.Ideal.Basic
import Mathlib.GroupTheory.GroupAction.Ring
#align_import ring_theory.localization.basic from "leanprover-community/mathlib"@"b69c9a770ecf37eb21f7b8cf4fa00de3b62694ec"
/-!
# Localizations of commutative rings
We characterize the localization of a commutative ring `R` at a submonoid `M` up to
isomorphism; that is, a commutative ring `S` is the localization of `R` at `M` iff we can find a
ring homomorphism `f : R →+* S` satisfying 3 properties:
1. For all `y ∈ M`, `f y` is a unit;
2. For all `z : S`, there exists `(x, y) : R × M` such that `z * f y = f x`;
3. For all `x, y : R` such that `f x = f y`, there exists `c ∈ M` such that `x * c = y * c`.
(The converse is a consequence of 1.)
In the following, let `R, P` be commutative rings, `S, Q` be `R`- and `P`-algebras
and `M, T` be submonoids of `R` and `P` respectively, e.g.:
```
variable (R S P Q : Type*) [CommRing R] [CommRing S] [CommRing P] [CommRing Q]
variable [Algebra R S] [Algebra P Q] (M : Submonoid R) (T : Submonoid P)
```
## Main definitions
* `IsLocalization (M : Submonoid R) (S : Type*)` is a typeclass expressing that `S` is a
localization of `R` at `M`, i.e. the canonical map `algebraMap R S : R →+* S` is a
localization map (satisfying the above properties).
* `IsLocalization.mk' S` is a surjection sending `(x, y) : R × M` to `f x * (f y)⁻¹`
* `IsLocalization.lift` is the ring homomorphism from `S` induced by a homomorphism from `R`
which maps elements of `M` to invertible elements of the codomain.
* `IsLocalization.map S Q` is the ring homomorphism from `S` to `Q` which maps elements
of `M` to elements of `T`
* `IsLocalization.ringEquivOfRingEquiv`: if `R` and `P` are isomorphic by an isomorphism
sending `M` to `T`, then `S` and `Q` are isomorphic
* `IsLocalization.algEquiv`: if `Q` is another localization of `R` at `M`, then `S` and `Q`
are isomorphic as `R`-algebras
## Main results
* `Localization M S`, a construction of the localization as a quotient type, defined in
`GroupTheory.MonoidLocalization`, has `CommRing`, `Algebra R` and `IsLocalization M`
instances if `R` is a ring. `Localization.Away`, `Localization.AtPrime` and `FractionRing`
are abbreviations for `Localization`s and have their corresponding `IsLocalization` instances
## Implementation notes
In maths it is natural to reason up to isomorphism, but in Lean we cannot naturally `rewrite` one
structure with an isomorphic one; one way around this is to isolate a predicate characterizing
a structure up to isomorphism, and reason about things that satisfy the predicate.
A previous version of this file used a fully bundled type of ring localization maps,
then used a type synonym `f.codomain` for `f : LocalizationMap M S` to instantiate the
`R`-algebra structure on `S`. This results in defining ad-hoc copies for everything already
defined on `S`. By making `IsLocalization` a predicate on the `algebraMap R S`,
we can ensure the localization map commutes nicely with other `algebraMap`s.
To prove most lemmas about a localization map `algebraMap R S` in this file we invoke the
corresponding proof for the underlying `CommMonoid` localization map
`IsLocalization.toLocalizationMap M S`, which can be found in `GroupTheory.MonoidLocalization`
and the namespace `Submonoid.LocalizationMap`.
To reason about the localization as a quotient type, use `mk_eq_of_mk'` and associated lemmas.
These show the quotient map `mk : R → M → Localization M` equals the surjection
`LocalizationMap.mk'` induced by the map `algebraMap : R →+* Localization M`.
The lemma `mk_eq_of_mk'` hence gives you access to the results in the rest of the file,
which are about the `LocalizationMap.mk'` induced by any localization map.
The proof that "a `CommRing` `K` which is the localization of an integral domain `R` at `R \ {0}`
is a field" is a `def` rather than an `instance`, so if you want to reason about a field of
fractions `K`, assume `[Field K]` instead of just `[CommRing K]`.
## Tags
localization, ring localization, commutative ring localization, characteristic predicate,
commutative ring, field of fractions
-/
open Function
section CommSemiring
variable {R : Type*} [CommSemiring R] (M : Submonoid R) (S : Type*) [CommSemiring S]
variable [Algebra R S] {P : Type*} [CommSemiring P]
/-- The typeclass `IsLocalization (M : Submonoid R) S` where `S` is an `R`-algebra
expresses that `S` is isomorphic to the localization of `R` at `M`. -/
@[mk_iff] class IsLocalization : Prop where
-- Porting note: add ' to fields, and made new versions of these with either `S` or `M` explicit.
/-- Everything in the image of `algebraMap` is a unit -/
map_units' : ∀ y : M, IsUnit (algebraMap R S y)
/-- The `algebraMap` is surjective -/
surj' : ∀ z : S, ∃ x : R × M, z * algebraMap R S x.2 = algebraMap R S x.1
/-- The kernel of `algebraMap` is contained in the annihilator of `M`;
it is then equal to the annihilator by `map_units'` -/
exists_of_eq : ∀ {x y}, algebraMap R S x = algebraMap R S y → ∃ c : M, ↑c * x = ↑c * y
#align is_localization IsLocalization
variable {M}
namespace IsLocalization
section IsLocalization
variable [IsLocalization M S]
section
@[inherit_doc IsLocalization.map_units']
theorem map_units : ∀ y : M, IsUnit (algebraMap R S y) :=
IsLocalization.map_units'
variable (M) {S}
@[inherit_doc IsLocalization.surj']
theorem surj : ∀ z : S, ∃ x : R × M, z * algebraMap R S x.2 = algebraMap R S x.1 :=
IsLocalization.surj'
variable (S)
@[inherit_doc IsLocalization.exists_of_eq]
theorem eq_iff_exists {x y} : algebraMap R S x = algebraMap R S y ↔ ∃ c : M, ↑c * x = ↑c * y :=
Iff.intro IsLocalization.exists_of_eq fun ⟨c, h⟩ ↦ by
apply_fun algebraMap R S at h
rw [map_mul, map_mul] at h
exact (IsLocalization.map_units S c).mul_right_inj.mp h
variable {S}
theorem of_le (N : Submonoid R) (h₁ : M ≤ N) (h₂ : ∀ r ∈ N, IsUnit (algebraMap R S r)) :
IsLocalization N S where
map_units' r := h₂ r r.2
surj' s :=
have ⟨⟨x, y, hy⟩, H⟩ := IsLocalization.surj M s
⟨⟨x, y, h₁ hy⟩, H⟩
exists_of_eq {x y} := by
rw [IsLocalization.eq_iff_exists M]
rintro ⟨c, hc⟩
exact ⟨⟨c, h₁ c.2⟩, hc⟩
#align is_localization.of_le IsLocalization.of_le
variable (S)
/-- `IsLocalization.toLocalizationWithZeroMap M S` shows `S` is the monoid localization of
`R` at `M`. -/
@[simps]
def toLocalizationWithZeroMap : Submonoid.LocalizationWithZeroMap M S where
__ := algebraMap R S
toFun := algebraMap R S
map_units' := IsLocalization.map_units _
surj' := IsLocalization.surj _
exists_of_eq _ _ := IsLocalization.exists_of_eq
#align is_localization.to_localization_with_zero_map IsLocalization.toLocalizationWithZeroMap
/-- `IsLocalization.toLocalizationMap M S` shows `S` is the monoid localization of `R` at `M`. -/
abbrev toLocalizationMap : Submonoid.LocalizationMap M S :=
(toLocalizationWithZeroMap M S).toLocalizationMap
#align is_localization.to_localization_map IsLocalization.toLocalizationMap
@[simp]
theorem toLocalizationMap_toMap : (toLocalizationMap M S).toMap = (algebraMap R S : R →*₀ S) :=
rfl
#align is_localization.to_localization_map_to_map IsLocalization.toLocalizationMap_toMap
theorem toLocalizationMap_toMap_apply (x) : (toLocalizationMap M S).toMap x = algebraMap R S x :=
rfl
#align is_localization.to_localization_map_to_map_apply IsLocalization.toLocalizationMap_toMap_apply
theorem surj₂ : ∀ z w : S, ∃ z' w' : R, ∃ d : M,
(z * algebraMap R S d = algebraMap R S z') ∧ (w * algebraMap R S d = algebraMap R S w') :=
(toLocalizationMap M S).surj₂
end
variable (M) {S}
/-- Given a localization map `f : M →* N`, a section function sending `z : N` to some
`(x, y) : M × S` such that `f x * (f y)⁻¹ = z`. -/
noncomputable def sec (z : S) : R × M :=
Classical.choose <| IsLocalization.surj _ z
#align is_localization.sec IsLocalization.sec
@[simp]
theorem toLocalizationMap_sec : (toLocalizationMap M S).sec = sec M :=
rfl
#align is_localization.to_localization_map_sec IsLocalization.toLocalizationMap_sec
/-- Given `z : S`, `IsLocalization.sec M z` is defined to be a pair `(x, y) : R × M` such
that `z * f y = f x` (so this lemma is true by definition). -/
theorem sec_spec (z : S) :
z * algebraMap R S (IsLocalization.sec M z).2 = algebraMap R S (IsLocalization.sec M z).1 :=
Classical.choose_spec <| IsLocalization.surj _ z
#align is_localization.sec_spec IsLocalization.sec_spec
/-- Given `z : S`, `IsLocalization.sec M z` is defined to be a pair `(x, y) : R × M` such
that `z * f y = f x`, so this lemma is just an application of `S`'s commutativity. -/
theorem sec_spec' (z : S) :
algebraMap R S (IsLocalization.sec M z).1 = algebraMap R S (IsLocalization.sec M z).2 * z := by
rw [mul_comm, sec_spec]
#align is_localization.sec_spec' IsLocalization.sec_spec'
variable {M}
/-- If `M` contains `0` then the localization at `M` is trivial. -/
theorem subsingleton (h : 0 ∈ M) : Subsingleton S := (toLocalizationMap M S).subsingleton h
theorem map_right_cancel {x y} {c : M} (h : algebraMap R S (c * x) = algebraMap R S (c * y)) :
algebraMap R S x = algebraMap R S y :=
(toLocalizationMap M S).map_right_cancel h
#align is_localization.map_right_cancel IsLocalization.map_right_cancel
theorem map_left_cancel {x y} {c : M} (h : algebraMap R S (x * c) = algebraMap R S (y * c)) :
algebraMap R S x = algebraMap R S y :=
(toLocalizationMap M S).map_left_cancel h
#align is_localization.map_left_cancel IsLocalization.map_left_cancel
theorem eq_zero_of_fst_eq_zero {z x} {y : M} (h : z * algebraMap R S y = algebraMap R S x)
(hx : x = 0) : z = 0 := by
rw [hx, (algebraMap R S).map_zero] at h
exact (IsUnit.mul_left_eq_zero (IsLocalization.map_units S y)).1 h
#align is_localization.eq_zero_of_fst_eq_zero IsLocalization.eq_zero_of_fst_eq_zero
variable (M S)
theorem map_eq_zero_iff (r : R) : algebraMap R S r = 0 ↔ ∃ m : M, ↑m * r = 0 := by
constructor
· intro h
obtain ⟨m, hm⟩ := (IsLocalization.eq_iff_exists M S).mp ((algebraMap R S).map_zero.trans h.symm)
exact ⟨m, by simpa using hm.symm⟩
· rintro ⟨m, hm⟩
rw [← (IsLocalization.map_units S m).mul_right_inj, mul_zero, ← RingHom.map_mul, hm,
RingHom.map_zero]
#align is_localization.map_eq_zero_iff IsLocalization.map_eq_zero_iff
variable {M}
/-- `IsLocalization.mk' S` is the surjection sending `(x, y) : R × M` to
`f x * (f y)⁻¹`. -/
noncomputable def mk' (x : R) (y : M) : S :=
(toLocalizationMap M S).mk' x y
#align is_localization.mk' IsLocalization.mk'
@[simp]
theorem mk'_sec (z : S) : mk' S (IsLocalization.sec M z).1 (IsLocalization.sec M z).2 = z :=
(toLocalizationMap M S).mk'_sec _
#align is_localization.mk'_sec IsLocalization.mk'_sec
theorem mk'_mul (x₁ x₂ : R) (y₁ y₂ : M) : mk' S (x₁ * x₂) (y₁ * y₂) = mk' S x₁ y₁ * mk' S x₂ y₂ :=
(toLocalizationMap M S).mk'_mul _ _ _ _
#align is_localization.mk'_mul IsLocalization.mk'_mul
theorem mk'_one (x) : mk' S x (1 : M) = algebraMap R S x :=
(toLocalizationMap M S).mk'_one _
#align is_localization.mk'_one IsLocalization.mk'_one
@[simp]
theorem mk'_spec (x) (y : M) : mk' S x y * algebraMap R S y = algebraMap R S x :=
(toLocalizationMap M S).mk'_spec _ _
#align is_localization.mk'_spec IsLocalization.mk'_spec
@[simp]
theorem mk'_spec' (x) (y : M) : algebraMap R S y * mk' S x y = algebraMap R S x :=
(toLocalizationMap M S).mk'_spec' _ _
#align is_localization.mk'_spec' IsLocalization.mk'_spec'
@[simp]
theorem mk'_spec_mk (x) (y : R) (hy : y ∈ M) :
mk' S x ⟨y, hy⟩ * algebraMap R S y = algebraMap R S x :=
mk'_spec S x ⟨y, hy⟩
#align is_localization.mk'_spec_mk IsLocalization.mk'_spec_mk
@[simp]
theorem mk'_spec'_mk (x) (y : R) (hy : y ∈ M) :
algebraMap R S y * mk' S x ⟨y, hy⟩ = algebraMap R S x :=
mk'_spec' S x ⟨y, hy⟩
#align is_localization.mk'_spec'_mk IsLocalization.mk'_spec'_mk
variable {S}
theorem eq_mk'_iff_mul_eq {x} {y : M} {z} :
z = mk' S x y ↔ z * algebraMap R S y = algebraMap R S x :=
(toLocalizationMap M S).eq_mk'_iff_mul_eq
#align is_localization.eq_mk'_iff_mul_eq IsLocalization.eq_mk'_iff_mul_eq
theorem mk'_eq_iff_eq_mul {x} {y : M} {z} :
mk' S x y = z ↔ algebraMap R S x = z * algebraMap R S y :=
(toLocalizationMap M S).mk'_eq_iff_eq_mul
#align is_localization.mk'_eq_iff_eq_mul IsLocalization.mk'_eq_iff_eq_mul
theorem mk'_add_eq_iff_add_mul_eq_mul {x} {y : M} {z₁ z₂} :
mk' S x y + z₁ = z₂ ↔ algebraMap R S x + z₁ * algebraMap R S y = z₂ * algebraMap R S y := by
rw [← mk'_spec S x y, ← IsUnit.mul_left_inj (IsLocalization.map_units S y), right_distrib]
#align is_localization.mk'_add_eq_iff_add_mul_eq_mul IsLocalization.mk'_add_eq_iff_add_mul_eq_mul
variable (M)
theorem mk'_surjective (z : S) : ∃ (x : _) (y : M), mk' S x y = z :=
let ⟨r, hr⟩ := IsLocalization.surj _ z
⟨r.1, r.2, (eq_mk'_iff_mul_eq.2 hr).symm⟩
#align is_localization.mk'_surjective IsLocalization.mk'_surjective
variable (S)
/-- The localization of a `Fintype` is a `Fintype`. Cannot be an instance. -/
noncomputable def fintype' [Fintype R] : Fintype S :=
have := Classical.propDecidable
Fintype.ofSurjective (Function.uncurry <| IsLocalization.mk' S) fun a =>
Prod.exists'.mpr <| IsLocalization.mk'_surjective M a
#align is_localization.fintype' IsLocalization.fintype'
variable {M S}
/-- Localizing at a submonoid with 0 inside it leads to the trivial ring. -/
def uniqueOfZeroMem (h : (0 : R) ∈ M) : Unique S :=
uniqueOfZeroEqOne <| by simpa using IsLocalization.map_units S ⟨0, h⟩
#align is_localization.unique_of_zero_mem IsLocalization.uniqueOfZeroMem
theorem mk'_eq_iff_eq {x₁ x₂} {y₁ y₂ : M} :
mk' S x₁ y₁ = mk' S x₂ y₂ ↔ algebraMap R S (y₂ * x₁) = algebraMap R S (y₁ * x₂) :=
(toLocalizationMap M S).mk'_eq_iff_eq
#align is_localization.mk'_eq_iff_eq IsLocalization.mk'_eq_iff_eq
theorem mk'_eq_iff_eq' {x₁ x₂} {y₁ y₂ : M} :
mk' S x₁ y₁ = mk' S x₂ y₂ ↔ algebraMap R S (x₁ * y₂) = algebraMap R S (x₂ * y₁) :=
(toLocalizationMap M S).mk'_eq_iff_eq'
#align is_localization.mk'_eq_iff_eq' IsLocalization.mk'_eq_iff_eq'
theorem mk'_mem_iff {x} {y : M} {I : Ideal S} : mk' S x y ∈ I ↔ algebraMap R S x ∈ I := by
constructor <;> intro h
· rw [← mk'_spec S x y, mul_comm]
exact I.mul_mem_left ((algebraMap R S) y) h
· rw [← mk'_spec S x y] at h
obtain ⟨b, hb⟩ := isUnit_iff_exists_inv.1 (map_units S y)
have := I.mul_mem_left b h
rwa [mul_comm, mul_assoc, hb, mul_one] at this
#align is_localization.mk'_mem_iff IsLocalization.mk'_mem_iff
protected theorem eq {a₁ b₁} {a₂ b₂ : M} :
mk' S a₁ a₂ = mk' S b₁ b₂ ↔ ∃ c : M, ↑c * (↑b₂ * a₁) = c * (a₂ * b₁) :=
(toLocalizationMap M S).eq
#align is_localization.eq IsLocalization.eq
theorem mk'_eq_zero_iff (x : R) (s : M) : mk' S x s = 0 ↔ ∃ m : M, ↑m * x = 0 := by
rw [← (map_units S s).mul_left_inj, mk'_spec, zero_mul, map_eq_zero_iff M]
#align is_localization.mk'_eq_zero_iff IsLocalization.mk'_eq_zero_iff
@[simp]
theorem mk'_zero (s : M) : IsLocalization.mk' S 0 s = 0 := by
rw [eq_comm, IsLocalization.eq_mk'_iff_mul_eq, zero_mul, map_zero]
#align is_localization.mk'_zero IsLocalization.mk'_zero
theorem ne_zero_of_mk'_ne_zero {x : R} {y : M} (hxy : IsLocalization.mk' S x y ≠ 0) : x ≠ 0 := by
rintro rfl
exact hxy (IsLocalization.mk'_zero _)
#align is_localization.ne_zero_of_mk'_ne_zero IsLocalization.ne_zero_of_mk'_ne_zero
section Ext
variable [Algebra R P] [IsLocalization M P]
theorem eq_iff_eq {x y} :
algebraMap R S x = algebraMap R S y ↔ algebraMap R P x = algebraMap R P y :=
(toLocalizationMap M S).eq_iff_eq (toLocalizationMap M P)
#align is_localization.eq_iff_eq IsLocalization.eq_iff_eq
theorem mk'_eq_iff_mk'_eq {x₁ x₂} {y₁ y₂ : M} :
mk' S x₁ y₁ = mk' S x₂ y₂ ↔ mk' P x₁ y₁ = mk' P x₂ y₂ :=
(toLocalizationMap M S).mk'_eq_iff_mk'_eq (toLocalizationMap M P)
#align is_localization.mk'_eq_iff_mk'_eq IsLocalization.mk'_eq_iff_mk'_eq
theorem mk'_eq_of_eq {a₁ b₁ : R} {a₂ b₂ : M} (H : ↑a₂ * b₁ = ↑b₂ * a₁) :
mk' S a₁ a₂ = mk' S b₁ b₂ :=
(toLocalizationMap M S).mk'_eq_of_eq H
#align is_localization.mk'_eq_of_eq IsLocalization.mk'_eq_of_eq
theorem mk'_eq_of_eq' {a₁ b₁ : R} {a₂ b₂ : M} (H : b₁ * ↑a₂ = a₁ * ↑b₂) :
mk' S a₁ a₂ = mk' S b₁ b₂ :=
(toLocalizationMap M S).mk'_eq_of_eq' H
#align is_localization.mk'_eq_of_eq' IsLocalization.mk'_eq_of_eq'
theorem mk'_cancel (a : R) (b c : M) :
mk' S (a * c) (b * c) = mk' S a b := (toLocalizationMap M S).mk'_cancel _ _ _
variable (S)
@[simp]
theorem mk'_self {x : R} (hx : x ∈ M) : mk' S x ⟨x, hx⟩ = 1 :=
(toLocalizationMap M S).mk'_self _ hx
#align is_localization.mk'_self IsLocalization.mk'_self
@[simp]
theorem mk'_self' {x : M} : mk' S (x : R) x = 1 :=
(toLocalizationMap M S).mk'_self' _
#align is_localization.mk'_self' IsLocalization.mk'_self'
theorem mk'_self'' {x : M} : mk' S x.1 x = 1 :=
mk'_self' _
#align is_localization.mk'_self'' IsLocalization.mk'_self''
end Ext
theorem mul_mk'_eq_mk'_of_mul (x y : R) (z : M) :
(algebraMap R S) x * mk' S y z = mk' S (x * y) z :=
(toLocalizationMap M S).mul_mk'_eq_mk'_of_mul _ _ _
#align is_localization.mul_mk'_eq_mk'_of_mul IsLocalization.mul_mk'_eq_mk'_of_mul
theorem mk'_eq_mul_mk'_one (x : R) (y : M) : mk' S x y = (algebraMap R S) x * mk' S 1 y :=
((toLocalizationMap M S).mul_mk'_one_eq_mk' _ _).symm
#align is_localization.mk'_eq_mul_mk'_one IsLocalization.mk'_eq_mul_mk'_one
@[simp]
theorem mk'_mul_cancel_left (x : R) (y : M) : mk' S (y * x : R) y = (algebraMap R S) x :=
(toLocalizationMap M S).mk'_mul_cancel_left _ _
#align is_localization.mk'_mul_cancel_left IsLocalization.mk'_mul_cancel_left
theorem mk'_mul_cancel_right (x : R) (y : M) : mk' S (x * y) y = (algebraMap R S) x :=
(toLocalizationMap M S).mk'_mul_cancel_right _ _
#align is_localization.mk'_mul_cancel_right IsLocalization.mk'_mul_cancel_right
@[simp]
theorem mk'_mul_mk'_eq_one (x y : M) : mk' S (x : R) y * mk' S (y : R) x = 1 := by
rw [← mk'_mul, mul_comm]; exact mk'_self _ _
#align is_localization.mk'_mul_mk'_eq_one IsLocalization.mk'_mul_mk'_eq_one
theorem mk'_mul_mk'_eq_one' (x : R) (y : M) (h : x ∈ M) : mk' S x y * mk' S (y : R) ⟨x, h⟩ = 1 :=
mk'_mul_mk'_eq_one ⟨x, h⟩ _
#align is_localization.mk'_mul_mk'_eq_one' IsLocalization.mk'_mul_mk'_eq_one'
theorem smul_mk' (x y : R) (m : M) : x • mk' S y m = mk' S (x * y) m := by
nth_rw 2 [← one_mul m]
rw [mk'_mul, mk'_one, Algebra.smul_def]
@[simp] theorem smul_mk'_one (x : R) (m : M) : x • mk' S 1 m = mk' S x m := by
rw [smul_mk', mul_one]
@[simp] lemma smul_mk'_self {m : M} {r : R} :
(m : R) • mk' S r m = algebraMap R S r := by
rw [smul_mk', mk'_mul_cancel_left]
@[simps]
instance invertible_mk'_one (s : M) : Invertible (IsLocalization.mk' S (1 : R) s) where
invOf := algebraMap R S s
invOf_mul_self := by simp
mul_invOf_self := by simp
section
variable (M)
theorem isUnit_comp (j : S →+* P) (y : M) : IsUnit (j.comp (algebraMap R S) y) :=
(toLocalizationMap M S).isUnit_comp j.toMonoidHom _
#align is_localization.is_unit_comp IsLocalization.isUnit_comp
end
/-- Given a localization map `f : R →+* S` for a submonoid `M ⊆ R` and a map of `CommSemiring`s
`g : R →+* P` such that `g(M) ⊆ Units P`, `f x = f y → g x = g y` for all `x y : R`. -/
theorem eq_of_eq {g : R →+* P} (hg : ∀ y : M, IsUnit (g y)) {x y}
(h : (algebraMap R S) x = (algebraMap R S) y) : g x = g y :=
Submonoid.LocalizationMap.eq_of_eq (toLocalizationMap M S) (g := g.toMonoidHom) hg h
#align is_localization.eq_of_eq IsLocalization.eq_of_eq
theorem mk'_add (x₁ x₂ : R) (y₁ y₂ : M) :
mk' S (x₁ * y₂ + x₂ * y₁) (y₁ * y₂) = mk' S x₁ y₁ + mk' S x₂ y₂ :=
mk'_eq_iff_eq_mul.2 <|
Eq.symm
(by
rw [mul_comm (_ + _), mul_add, mul_mk'_eq_mk'_of_mul, mk'_add_eq_iff_add_mul_eq_mul,
mul_comm (_ * _), ← mul_assoc, add_comm, ← map_mul, mul_mk'_eq_mk'_of_mul,
mk'_add_eq_iff_add_mul_eq_mul]
simp only [map_add, Submonoid.coe_mul, map_mul]
ring)
#align is_localization.mk'_add IsLocalization.mk'_add
theorem mul_add_inv_left {g : R →+* P} (h : ∀ y : M, IsUnit (g y)) (y : M) (w z₁ z₂ : P) :
w * ↑(IsUnit.liftRight (g.toMonoidHom.restrict M) h y)⁻¹ + z₁ =
z₂ ↔ w + g y * z₁ = g y * z₂ := by
rw [mul_comm, ← one_mul z₁, ← Units.inv_mul (IsUnit.liftRight (g.toMonoidHom.restrict M) h y),
mul_assoc, ← mul_add, Units.inv_mul_eq_iff_eq_mul, Units.inv_mul_cancel_left,
IsUnit.coe_liftRight]
simp [RingHom.toMonoidHom_eq_coe, MonoidHom.restrict_apply]
#align is_localization.mul_add_inv_left IsLocalization.mul_add_inv_left
theorem lift_spec_mul_add {g : R →+* P} (hg : ∀ y : M, IsUnit (g y)) (z w w' v) :
((toLocalizationWithZeroMap M S).lift g.toMonoidWithZeroHom hg) z * w + w' = v ↔
g ((toLocalizationMap M S).sec z).1 * w + g ((toLocalizationMap M S).sec z).2 * w' =
g ((toLocalizationMap M S).sec z).2 * v := by
erw [mul_comm, ← mul_assoc, mul_add_inv_left hg, mul_comm]
rfl
#align is_localization.lift_spec_mul_add IsLocalization.lift_spec_mul_add
/-- Given a localization map `f : R →+* S` for a submonoid `M ⊆ R` and a map of `CommSemiring`s
`g : R →+* P` such that `g y` is invertible for all `y : M`, the homomorphism induced from
`S` to `P` sending `z : S` to `g x * (g y)⁻¹`, where `(x, y) : R × M` are such that
`z = f x * (f y)⁻¹`. -/
noncomputable def lift {g : R →+* P} (hg : ∀ y : M, IsUnit (g y)) : S →+* P :=
{ Submonoid.LocalizationWithZeroMap.lift (toLocalizationWithZeroMap M S)
g.toMonoidWithZeroHom hg with
map_add' := by
intro x y
erw [(toLocalizationMap M S).lift_spec, mul_add, mul_comm, eq_comm, lift_spec_mul_add,
add_comm, mul_comm, mul_assoc, mul_comm, mul_assoc, lift_spec_mul_add]
simp_rw [← mul_assoc]
show g _ * g _ * g _ + g _ * g _ * g _ = g _ * g _ * g _
simp_rw [← map_mul g, ← map_add g]
apply eq_of_eq (S := S) hg
simp only [sec_spec', toLocalizationMap_sec, map_add, map_mul]
ring }
#align is_localization.lift IsLocalization.lift
variable {g : R →+* P} (hg : ∀ y : M, IsUnit (g y))
/-- Given a localization map `f : R →+* S` for a submonoid `M ⊆ R` and a map of `CommSemiring`s
`g : R →* P` such that `g y` is invertible for all `y : M`, the homomorphism induced from
`S` to `P` maps `f x * (f y)⁻¹` to `g x * (g y)⁻¹` for all `x : R, y ∈ M`. -/
theorem lift_mk' (x y) :
lift hg (mk' S x y) = g x * ↑(IsUnit.liftRight (g.toMonoidHom.restrict M) hg y)⁻¹ :=
(toLocalizationMap M S).lift_mk' _ _ _
#align is_localization.lift_mk' IsLocalization.lift_mk'
theorem lift_mk'_spec (x v) (y : M) : lift hg (mk' S x y) = v ↔ g x = g y * v :=
(toLocalizationMap M S).lift_mk'_spec _ _ _ _
#align is_localization.lift_mk'_spec IsLocalization.lift_mk'_spec
@[simp]
theorem lift_eq (x : R) : lift hg ((algebraMap R S) x) = g x :=
(toLocalizationMap M S).lift_eq _ _
#align is_localization.lift_eq IsLocalization.lift_eq
theorem lift_eq_iff {x y : R × M} :
lift hg (mk' S x.1 x.2) = lift hg (mk' S y.1 y.2) ↔ g (x.1 * y.2) = g (y.1 * x.2) :=
(toLocalizationMap M S).lift_eq_iff _
#align is_localization.lift_eq_iff IsLocalization.lift_eq_iff
@[simp]
theorem lift_comp : (lift hg).comp (algebraMap R S) = g :=
RingHom.ext <| (DFunLike.ext_iff (F := MonoidHom _ _)).1 <| (toLocalizationMap M S).lift_comp _
#align is_localization.lift_comp IsLocalization.lift_comp
@[simp]
theorem lift_of_comp (j : S →+* P) : lift (isUnit_comp M j) = j :=
RingHom.ext <| (DFunLike.ext_iff (F := MonoidHom _ _)).1 <|
(toLocalizationMap M S).lift_of_comp j.toMonoidHom
#align is_localization.lift_of_comp IsLocalization.lift_of_comp
variable (M)
/-- See note [partially-applied ext lemmas] -/
theorem monoidHom_ext ⦃j k : S →* P⦄
(h : j.comp (algebraMap R S : R →* S) = k.comp (algebraMap R S)) : j = k :=
Submonoid.LocalizationMap.epic_of_localizationMap (toLocalizationMap M S) <| DFunLike.congr_fun h
#align is_localization.monoid_hom_ext IsLocalization.monoidHom_ext
/-- See note [partially-applied ext lemmas] -/
theorem ringHom_ext ⦃j k : S →+* P⦄ (h : j.comp (algebraMap R S) = k.comp (algebraMap R S)) :
j = k :=
RingHom.coe_monoidHom_injective <| monoidHom_ext M <| MonoidHom.ext <| RingHom.congr_fun h
#align is_localization.ring_hom_ext IsLocalization.ringHom_ext
/- This is not an instance because the submonoid `M` would become a metavariable
in typeclass search. -/
theorem algHom_subsingleton [Algebra R P] : Subsingleton (S →ₐ[R] P) :=
⟨fun f g =>
AlgHom.coe_ringHom_injective <|
IsLocalization.ringHom_ext M <| by rw [f.comp_algebraMap, g.comp_algebraMap]⟩
#align is_localization.alg_hom_subsingleton IsLocalization.algHom_subsingleton
/-- To show `j` and `k` agree on the whole localization, it suffices to show they agree
on the image of the base ring, if they preserve `1` and `*`. -/
protected theorem ext (j k : S → P) (hj1 : j 1 = 1) (hk1 : k 1 = 1)
(hjm : ∀ a b, j (a * b) = j a * j b) (hkm : ∀ a b, k (a * b) = k a * k b)
(h : ∀ a, j (algebraMap R S a) = k (algebraMap R S a)) : j = k :=
let j' : MonoidHom S P :=
{ toFun := j, map_one' := hj1, map_mul' := hjm }
let k' : MonoidHom S P :=
{ toFun := k, map_one' := hk1, map_mul' := hkm }
have : j' = k' := monoidHom_ext M (MonoidHom.ext h)
show j'.toFun = k'.toFun by rw [this]
#align is_localization.ext IsLocalization.ext
variable {M}
theorem lift_unique {j : S →+* P} (hj : ∀ x, j ((algebraMap R S) x) = g x) : lift hg = j :=
RingHom.ext <|
(DFunLike.ext_iff (F := MonoidHom _ _)).1 <|
Submonoid.LocalizationMap.lift_unique (toLocalizationMap M S) (g := g.toMonoidHom) hg
(j := j.toMonoidHom) hj
#align is_localization.lift_unique IsLocalization.lift_unique
@[simp]
theorem lift_id (x) : lift (map_units S : ∀ _ : M, IsUnit _) x = x :=
(toLocalizationMap M S).lift_id _
#align is_localization.lift_id IsLocalization.lift_id
theorem lift_surjective_iff :
Surjective (lift hg : S → P) ↔ ∀ v : P, ∃ x : R × M, v * g x.2 = g x.1 :=
(toLocalizationMap M S).lift_surjective_iff hg
#align is_localization.lift_surjective_iff IsLocalization.lift_surjective_iff
theorem lift_injective_iff :
Injective (lift hg : S → P) ↔ ∀ x y, algebraMap R S x = algebraMap R S y ↔ g x = g y :=
(toLocalizationMap M S).lift_injective_iff hg
#align is_localization.lift_injective_iff IsLocalization.lift_injective_iff
section Map
variable {T : Submonoid P} {Q : Type*} [CommSemiring Q] (hy : M ≤ T.comap g)
variable [Algebra P Q] [IsLocalization T Q]
section
variable (Q)
/-- Map a homomorphism `g : R →+* P` to `S →+* Q`, where `S` and `Q` are
localizations of `R` and `P` at `M` and `T` respectively,
such that `g(M) ⊆ T`.
We send `z : S` to `algebraMap P Q (g x) * (algebraMap P Q (g y))⁻¹`, where
`(x, y) : R × M` are such that `z = f x * (f y)⁻¹`. -/
noncomputable def map (g : R →+* P) (hy : M ≤ T.comap g) : S →+* Q :=
lift (M := M) (g := (algebraMap P Q).comp g) fun y => map_units _ ⟨g y, hy y.2⟩
#align is_localization.map IsLocalization.map
end
-- Porting note: added `simp` attribute, since it proves very similar lemmas marked `simp`
@[simp]
theorem map_eq (x) : map Q g hy ((algebraMap R S) x) = algebraMap P Q (g x) :=
lift_eq (fun y => map_units _ ⟨g y, hy y.2⟩) x
#align is_localization.map_eq IsLocalization.map_eq
@[simp]
theorem map_comp : (map Q g hy).comp (algebraMap R S) = (algebraMap P Q).comp g :=
lift_comp fun y => map_units _ ⟨g y, hy y.2⟩
#align is_localization.map_comp IsLocalization.map_comp
theorem map_mk' (x) (y : M) : map Q g hy (mk' S x y) = mk' Q (g x) ⟨g y, hy y.2⟩ :=
Submonoid.LocalizationMap.map_mk' (toLocalizationMap M S) (g := g.toMonoidHom)
(fun y => hy y.2) (k := toLocalizationMap T Q) ..
#align is_localization.map_mk' IsLocalization.map_mk'
-- Porting note (#10756): new theorem
@[simp]
theorem map_id_mk' {Q : Type*} [CommSemiring Q] [Algebra R Q] [IsLocalization M Q] (x) (y : M) :
map Q (RingHom.id R) (le_refl M) (mk' S x y) = mk' Q x y :=
map_mk' ..
@[simp]
theorem map_id (z : S) (h : M ≤ M.comap (RingHom.id R) := le_refl M) :
map S (RingHom.id _) h z = z :=
lift_id _
#align is_localization.map_id IsLocalization.map_id
theorem map_unique (j : S →+* Q) (hj : ∀ x : R, j (algebraMap R S x) = algebraMap P Q (g x)) :
map Q g hy = j :=
lift_unique (fun y => map_units _ ⟨g y, hy y.2⟩) hj
#align is_localization.map_unique IsLocalization.map_unique
/-- If `CommSemiring` homs `g : R →+* P, l : P →+* A` induce maps of localizations, the composition
of the induced maps equals the map of localizations induced by `l ∘ g`. -/
theorem map_comp_map {A : Type*} [CommSemiring A] {U : Submonoid A} {W} [CommSemiring W]
[Algebra A W] [IsLocalization U W] {l : P →+* A} (hl : T ≤ U.comap l) :
(map W l hl).comp (map Q g hy : S →+* _) = map W (l.comp g) fun _ hx => hl (hy hx) :=
RingHom.ext fun x =>
Submonoid.LocalizationMap.map_map (P := P) (toLocalizationMap M S) (fun y => hy y.2)
(toLocalizationMap U W) (fun w => hl w.2) x
#align is_localization.map_comp_map IsLocalization.map_comp_map
/-- If `CommSemiring` homs `g : R →+* P, l : P →+* A` induce maps of localizations, the composition
of the induced maps equals the map of localizations induced by `l ∘ g`. -/
theorem map_map {A : Type*} [CommSemiring A] {U : Submonoid A} {W} [CommSemiring W] [Algebra A W]
[IsLocalization U W] {l : P →+* A} (hl : T ≤ U.comap l) (x : S) :
map W l hl (map Q g hy x) = map W (l.comp g) (fun x hx => hl (hy hx)) x := by
rw [← map_comp_map (Q := Q) hy hl]; rfl
#align is_localization.map_map IsLocalization.map_map
theorem map_smul (x : S) (z : R) : map Q g hy (z • x : S) = g z • map Q g hy x := by
rw [Algebra.smul_def, Algebra.smul_def, RingHom.map_mul, map_eq]
#align is_localization.map_smul IsLocalization.map_smul
section
variable (S Q)
/-- If `S`, `Q` are localizations of `R` and `P` at submonoids `M, T` respectively, an
isomorphism `j : R ≃+* P` such that `j(M) = T` induces an isomorphism of localizations
`S ≃+* Q`. -/
@[simps]
noncomputable def ringEquivOfRingEquiv (h : R ≃+* P) (H : M.map h.toMonoidHom = T) : S ≃+* Q :=
have H' : T.map h.symm.toMonoidHom = M := by
rw [← M.map_id, ← H, Submonoid.map_map]
congr
ext
apply h.symm_apply_apply
{ map Q (h : R →+* P) (M.le_comap_of_map_le (le_of_eq H)) with
toFun := map Q (h : R →+* P) (M.le_comap_of_map_le (le_of_eq H))
invFun := map S (h.symm : P →+* R) (T.le_comap_of_map_le (le_of_eq H'))
left_inv := fun x => by
rw [map_map, map_unique _ (RingHom.id _), RingHom.id_apply]
simp
right_inv := fun x => by
rw [map_map, map_unique _ (RingHom.id _), RingHom.id_apply]
simp }
#align is_localization.ring_equiv_of_ring_equiv IsLocalization.ringEquivOfRingEquiv
end
theorem ringEquivOfRingEquiv_eq_map {j : R ≃+* P} (H : M.map j.toMonoidHom = T) :
(ringEquivOfRingEquiv S Q j H : S →+* Q) =
map Q (j : R →+* P) (M.le_comap_of_map_le (le_of_eq H)) :=
rfl
#align is_localization.ring_equiv_of_ring_equiv_eq_map IsLocalization.ringEquivOfRingEquiv_eq_map
-- Porting note (#10618): removed `simp`, `simp` can prove it
theorem ringEquivOfRingEquiv_eq {j : R ≃+* P} (H : M.map j.toMonoidHom = T) (x) :
ringEquivOfRingEquiv S Q j H ((algebraMap R S) x) = algebraMap P Q (j x) := by
simp
#align is_localization.ring_equiv_of_ring_equiv_eq IsLocalization.ringEquivOfRingEquiv_eq
theorem ringEquivOfRingEquiv_mk' {j : R ≃+* P} (H : M.map j.toMonoidHom = T) (x : R) (y : M) :
ringEquivOfRingEquiv S Q j H (mk' S x y) =
mk' Q (j x) ⟨j y, show j y ∈ T from H ▸ Set.mem_image_of_mem j y.2⟩ := by
simp [map_mk']
#align is_localization.ring_equiv_of_ring_equiv_mk' IsLocalization.ringEquivOfRingEquiv_mk'
end Map
section AlgEquiv
variable {Q : Type*} [CommSemiring Q] [Algebra R Q] [IsLocalization M Q]
section
variable (M S Q)
/-- If `S`, `Q` are localizations of `R` at the submonoid `M` respectively,
there is an isomorphism of localizations `S ≃ₐ[R] Q`. -/
@[simps!]
noncomputable def algEquiv : S ≃ₐ[R] Q :=
{ ringEquivOfRingEquiv S Q (RingEquiv.refl R) M.map_id with
commutes' := ringEquivOfRingEquiv_eq _ }
#align is_localization.alg_equiv IsLocalization.algEquiv
end
-- Porting note (#10618): removed `simp`, `simp` can prove it
theorem algEquiv_mk' (x : R) (y : M) : algEquiv M S Q (mk' S x y) = mk' Q x y := by
simp
#align is_localization.alg_equiv_mk' IsLocalization.algEquiv_mk'
-- Porting note (#10618): removed `simp`, `simp` can prove it
theorem algEquiv_symm_mk' (x : R) (y : M) : (algEquiv M S Q).symm (mk' Q x y) = mk' S x y := by simp
#align is_localization.alg_equiv_symm_mk' IsLocalization.algEquiv_symm_mk'
end AlgEquiv
section at_units
lemma at_units {R : Type*} [CommSemiring R] (S : Submonoid R)
(hS : S ≤ IsUnit.submonoid R) : IsLocalization S R where
map_units' y := hS y.prop
surj' := fun s ↦ ⟨⟨s, 1⟩, by simp⟩
exists_of_eq := fun {x y} (e : x = y) ↦ ⟨1, e ▸ rfl⟩
variable (R M)
/-- The localization at a module of units is isomorphic to the ring. -/
noncomputable def atUnits (H : M ≤ IsUnit.submonoid R) : R ≃ₐ[R] S := by
refine AlgEquiv.ofBijective (Algebra.ofId R S) ⟨?_, ?_⟩
· intro x y hxy
obtain ⟨c, eq⟩ := (IsLocalization.eq_iff_exists M S).mp hxy
obtain ⟨u, hu⟩ := H c.prop
rwa [← hu, Units.mul_right_inj] at eq
· intro y
obtain ⟨⟨x, s⟩, eq⟩ := IsLocalization.surj M y
obtain ⟨u, hu⟩ := H s.prop
use x * u.inv
dsimp [Algebra.ofId, RingHom.toFun_eq_coe, AlgHom.coe_mks]
rw [RingHom.map_mul, ← eq, ← hu, mul_assoc, ← RingHom.map_mul]
simp
#align is_localization.at_units IsLocalization.atUnits
end at_units
section
variable (M S) (Q : Type*) [CommSemiring Q] [Algebra P Q]
/-- Injectivity of a map descends to the map induced on localizations. -/
theorem map_injective_of_injective (h : Function.Injective g) [IsLocalization (M.map g) Q] :
Function.Injective (map Q g M.le_comap_map : S → Q) :=
(toLocalizationMap M S).map_injective_of_injective h (toLocalizationMap (M.map g) Q)
end
end IsLocalization
section
variable (M) {S}
theorem isLocalization_of_algEquiv [Algebra R P] [IsLocalization M S] (h : S ≃ₐ[R] P) :
IsLocalization M P := by
constructor
· intro y
convert (IsLocalization.map_units S y).map h.toAlgHom.toRingHom.toMonoidHom
exact (h.commutes y).symm
· intro y
obtain ⟨⟨x, s⟩, e⟩ := IsLocalization.surj M (h.symm y)
apply_fun (show S → P from h) at e
simp only [h.map_mul, h.apply_symm_apply, h.commutes] at e
exact ⟨⟨x, s⟩, e⟩
· intro x y
rw [← h.symm.toEquiv.injective.eq_iff, ← IsLocalization.eq_iff_exists M S, ← h.symm.commutes, ←
h.symm.commutes]
exact id
#align is_localization.is_localization_of_alg_equiv IsLocalization.isLocalization_of_algEquiv
theorem isLocalization_iff_of_algEquiv [Algebra R P] (h : S ≃ₐ[R] P) :
IsLocalization M S ↔ IsLocalization M P :=
⟨fun _ => isLocalization_of_algEquiv M h, fun _ => isLocalization_of_algEquiv M h.symm⟩
#align is_localization.is_localization_iff_of_alg_equiv IsLocalization.isLocalization_iff_of_algEquiv
theorem isLocalization_iff_of_ringEquiv (h : S ≃+* P) :
IsLocalization M S ↔
haveI := (h.toRingHom.comp <| algebraMap R S).toAlgebra; IsLocalization M P :=
letI := (h.toRingHom.comp <| algebraMap R S).toAlgebra
isLocalization_iff_of_algEquiv M { h with commutes' := fun _ => rfl }
#align is_localization.is_localization_iff_of_ring_equiv IsLocalization.isLocalization_iff_of_ringEquiv
variable (S)
theorem isLocalization_of_base_ringEquiv [IsLocalization M S] (h : R ≃+* P) :
haveI := ((algebraMap R S).comp h.symm.toRingHom).toAlgebra
IsLocalization (M.map h.toMonoidHom) S := by
letI : Algebra P S := ((algebraMap R S).comp h.symm.toRingHom).toAlgebra
constructor
· rintro ⟨_, ⟨y, hy, rfl⟩⟩
convert IsLocalization.map_units S ⟨y, hy⟩
dsimp only [RingHom.algebraMap_toAlgebra, RingHom.comp_apply]
exact congr_arg _ (h.symm_apply_apply _)
· intro y
obtain ⟨⟨x, s⟩, e⟩ := IsLocalization.surj M y
refine ⟨⟨h x, _, _, s.prop, rfl⟩, ?_⟩
dsimp only [RingHom.algebraMap_toAlgebra, RingHom.comp_apply] at e ⊢
convert e <;> exact h.symm_apply_apply _
· intro x y
rw [RingHom.algebraMap_toAlgebra, RingHom.comp_apply, RingHom.comp_apply,
IsLocalization.eq_iff_exists M S]
simp_rw [← h.toEquiv.apply_eq_iff_eq]
change (∃ c : M, h (c * h.symm x) = h (c * h.symm y)) → _
simp only [RingEquiv.apply_symm_apply, RingEquiv.map_mul]
exact fun ⟨c, e⟩ ↦ ⟨⟨_, _, c.prop, rfl⟩, e⟩
#align is_localization.is_localization_of_base_ring_equiv IsLocalization.isLocalization_of_base_ringEquiv
theorem isLocalization_iff_of_base_ringEquiv (h : R ≃+* P) :
IsLocalization M S ↔
haveI := ((algebraMap R S).comp h.symm.toRingHom).toAlgebra
IsLocalization (M.map h.toMonoidHom) S := by
letI : Algebra P S := ((algebraMap R S).comp h.symm.toRingHom).toAlgebra
refine ⟨fun _ => isLocalization_of_base_ringEquiv M S h, ?_⟩
intro H
convert isLocalization_of_base_ringEquiv (Submonoid.map (RingEquiv.toMonoidHom h) M) S h.symm
· erw [Submonoid.map_equiv_eq_comap_symm, Submonoid.comap_map_eq_of_injective]
exact h.toEquiv.injective
rw [RingHom.algebraMap_toAlgebra, RingHom.comp_assoc]
simp only [RingHom.comp_id, RingEquiv.symm_symm, RingEquiv.symm_toRingHom_comp_toRingHom]
apply Algebra.algebra_ext
intro r
rw [RingHom.algebraMap_toAlgebra]
#align is_localization.is_localization_iff_of_base_ring_equiv IsLocalization.isLocalization_iff_of_base_ringEquiv
end
variable (M)
theorem nonZeroDivisors_le_comap [IsLocalization M S] :
nonZeroDivisors R ≤ (nonZeroDivisors S).comap (algebraMap R S) := by
rintro a ha b (e : b * algebraMap R S a = 0)
obtain ⟨x, s, rfl⟩ := mk'_surjective M b
rw [← @mk'_one R _ M, ← mk'_mul, ← (algebraMap R S).map_zero, ← @mk'_one R _ M,
IsLocalization.eq] at e
obtain ⟨c, e⟩ := e
rw [mul_zero, mul_zero, Submonoid.coe_one, one_mul, ← mul_assoc] at e
rw [mk'_eq_zero_iff]
exact ⟨c, ha _ e⟩
#align is_localization.non_zero_divisors_le_comap IsLocalization.nonZeroDivisors_le_comap
theorem map_nonZeroDivisors_le [IsLocalization M S] :
(nonZeroDivisors R).map (algebraMap R S) ≤ nonZeroDivisors S :=
Submonoid.map_le_iff_le_comap.mpr (nonZeroDivisors_le_comap M S)
#align is_localization.map_non_zero_divisors_le IsLocalization.map_nonZeroDivisors_le
end IsLocalization
namespace Localization
open IsLocalization
/-! ### Constructing a localization at a given submonoid -/
section
instance instUniqueLocalization [Subsingleton R] : Unique (Localization M) where
uniq a := show a = mk 1 1 from
Localization.induction_on a fun _ => by
congr <;> apply Subsingleton.elim
/-- Addition in a ring localization is defined as `⟨a, b⟩ + ⟨c, d⟩ = ⟨b * c + d * a, b * d⟩`.
Should not be confused with `AddLocalization.add`, which is defined as
`⟨a, b⟩ + ⟨c, d⟩ = ⟨a + c, b + d⟩`.
-/
protected irreducible_def add (z w : Localization M) : Localization M :=
Localization.liftOn₂ z w (fun a b c d => mk ((b : R) * c + d * a) (b * d))
fun {a a' b b' c c' d d'} h1 h2 =>
mk_eq_mk_iff.2
(by
rw [r_eq_r'] at h1 h2 ⊢
cases' h1 with t₅ ht₅
cases' h2 with t₆ ht₆
use t₅ * t₆
dsimp only
calc ↑t₅ * ↑t₆ * (↑b' * ↑d' * ((b : R) * c + d * a))
_ = t₆ * (d' * c) * (t₅ * (b' * b)) + t₅ * (b' * a) * (t₆ * (d' * d)) := by ring
_ = t₅ * t₆ * (b * d * (b' * c' + d' * a')) := by rw [ht₆, ht₅]; ring
)
#align localization.add Localization.add
instance : Add (Localization M) :=
⟨Localization.add⟩
theorem add_mk (a b c d) : (mk a b : Localization M) + mk c d =
mk ((b : R) * c + (d : R) * a) (b * d) := by
show Localization.add (mk a b) (mk c d) = mk _ _
simp [Localization.add_def]
#align localization.add_mk Localization.add_mk
theorem add_mk_self (a b c) : (mk a b : Localization M) + mk c b = mk (a + c) b := by
rw [add_mk, mk_eq_mk_iff, r_eq_r']
refine (r' M).symm ⟨1, ?_⟩
simp only [Submonoid.coe_one, Submonoid.coe_mul]
ring
#align localization.add_mk_self Localization.add_mk_self
local macro "localization_tac" : tactic =>
`(tactic|
{ intros
simp only [add_mk, Localization.mk_mul, ← Localization.mk_zero 1]
refine mk_eq_mk_iff.mpr (r_of_eq ?_)
simp only [Submonoid.coe_mul]
ring })
instance : CommSemiring (Localization M) :=
{ (show CommMonoidWithZero (Localization M) by infer_instance) with
add := (· + ·)
nsmul := (· • ·)
nsmul_zero := fun x =>
Localization.induction_on x fun x => by simp only [smul_mk, zero_nsmul, mk_zero]
nsmul_succ := fun n x =>
Localization.induction_on x fun x => by simp only [smul_mk, succ_nsmul, add_mk_self]
add_assoc := fun m n k =>
Localization.induction_on₃ m n k
(by localization_tac)
zero_add := fun y =>
Localization.induction_on y
(by localization_tac)
add_zero := fun y =>
Localization.induction_on y
(by localization_tac)
add_comm := fun y z =>
Localization.induction_on₂ z y
(by localization_tac)
left_distrib := fun m n k =>
Localization.induction_on₃ m n k
(by localization_tac)
right_distrib := fun m n k =>
Localization.induction_on₃ m n k
(by localization_tac) }
/-- For any given denominator `b : M`, the map `a ↦ a / b` is an `AddMonoidHom` from `R` to
`Localization M`-/
@[simps]
def mkAddMonoidHom (b : M) : R →+ Localization M where
toFun a := mk a b
map_zero' := mk_zero _
map_add' _ _ := (add_mk_self _ _ _).symm
#align localization.mk_add_monoid_hom Localization.mkAddMonoidHom
theorem mk_sum {ι : Type*} (f : ι → R) (s : Finset ι) (b : M) :
mk (∑ i ∈ s, f i) b = ∑ i ∈ s, mk (f i) b :=
map_sum (mkAddMonoidHom b) f s
#align localization.mk_sum Localization.mk_sum
theorem mk_list_sum (l : List R) (b : M) : mk l.sum b = (l.map fun a => mk a b).sum :=
map_list_sum (mkAddMonoidHom b) l
#align localization.mk_list_sum Localization.mk_list_sum
theorem mk_multiset_sum (l : Multiset R) (b : M) : mk l.sum b = (l.map fun a => mk a b).sum :=
(mkAddMonoidHom b).map_multiset_sum l
#align localization.mk_multiset_sum Localization.mk_multiset_sum
instance {S : Type*} [Monoid S] [DistribMulAction S R] [IsScalarTower S R R] :
DistribMulAction S (Localization M) where
smul_zero s := by simp only [← Localization.mk_zero 1, Localization.smul_mk, smul_zero]
smul_add s x y :=
Localization.induction_on₂ x y <|
Prod.rec fun r₁ x₁ =>
Prod.rec fun r₂ x₂ => by
simp only [Localization.smul_mk, Localization.add_mk, smul_add, mul_comm _ (s • _),
mul_comm _ r₁, mul_comm _ r₂, smul_mul_assoc]
instance {S : Type*} [Semiring S] [MulSemiringAction S R] [IsScalarTower S R R] :
MulSemiringAction S (Localization M) :=
{ inferInstanceAs (MulDistribMulAction S (Localization M)),
inferInstanceAs (DistribMulAction S (Localization M)) with }
instance {S : Type*} [Semiring S] [Module S R] [IsScalarTower S R R] : Module S (Localization M) :=
{ inferInstanceAs (DistribMulAction S (Localization M)) with
zero_smul :=
Localization.ind <|
Prod.rec <| by
intros
simp only [Localization.smul_mk, zero_smul, mk_zero]
add_smul := fun s₁ s₂ =>
Localization.ind <|
Prod.rec <| by
intros
simp only [Localization.smul_mk, add_smul, add_mk_self] }
instance algebra {S : Type*} [CommSemiring S] [Algebra S R] : Algebra S (Localization M) where
toRingHom :=
RingHom.comp
{ Localization.monoidOf M with
toFun := (monoidOf M).toMap
map_zero' := by rw [← mk_zero (1 : M), mk_one_eq_monoidOf_mk]
map_add' := fun x y => by
simp only [← mk_one_eq_monoidOf_mk, add_mk, Submonoid.coe_one, one_mul, add_comm] }
(algebraMap S R)
smul_def' s :=
Localization.ind <|
Prod.rec <| by
intro r x
dsimp
simp only [← mk_one_eq_monoidOf_mk, mk_mul, Localization.smul_mk, one_mul,
Algebra.smul_def]
commutes' s :=
Localization.ind <|
Prod.rec <| by
intro r x
dsimp
simp only [← mk_one_eq_monoidOf_mk, mk_mul, Localization.smul_mk, one_mul, mul_one,
Algebra.commutes]
instance isLocalization : IsLocalization M (Localization M) where
map_units' := (Localization.monoidOf M).map_units
surj' := (Localization.monoidOf M).surj
exists_of_eq := (Localization.monoidOf M).eq_iff_exists.mp
end
@[simp]
theorem toLocalizationMap_eq_monoidOf : toLocalizationMap M (Localization M) = monoidOf M :=
rfl
#align localization.to_localization_map_eq_monoid_of Localization.toLocalizationMap_eq_monoidOf
theorem monoidOf_eq_algebraMap (x) : (monoidOf M).toMap x = algebraMap R (Localization M) x :=
rfl
#align localization.monoid_of_eq_algebra_map Localization.monoidOf_eq_algebraMap
theorem mk_one_eq_algebraMap (x) : mk x 1 = algebraMap R (Localization M) x :=
rfl
#align localization.mk_one_eq_algebra_map Localization.mk_one_eq_algebraMap
theorem mk_eq_mk'_apply (x y) : mk x y = IsLocalization.mk' (Localization M) x y := by
rw [mk_eq_monoidOf_mk'_apply, mk', toLocalizationMap_eq_monoidOf]
#align localization.mk_eq_mk'_apply Localization.mk_eq_mk'_apply
-- Porting note: removed `simp`. Left hand side can be simplified; not clear what normal form should
--be.
theorem mk_eq_mk' : (mk : R → M → Localization M) = IsLocalization.mk' (Localization M) :=
mk_eq_monoidOf_mk'
#align localization.mk_eq_mk' Localization.mk_eq_mk'
theorem mk_algebraMap {A : Type*} [CommSemiring A] [Algebra A R] (m : A) :
mk (algebraMap A R m) 1 = algebraMap A (Localization M) m := by
rw [mk_eq_mk', mk'_eq_iff_eq_mul, Submonoid.coe_one, map_one, mul_one]; rfl
#align localization.mk_algebra_map Localization.mk_algebraMap
theorem mk_natCast (m : ℕ) : (mk m 1 : Localization M) = m := by
simpa using mk_algebraMap (R := R) (A := ℕ) _
#align localization.mk_nat_cast Localization.mk_natCast
@[deprecated (since := "2024-04-17")]
alias mk_nat_cast := mk_natCast
variable [IsLocalization M S]
section
variable (M)
/-- The localization of `R` at `M` as a quotient type is isomorphic to any other localization. -/
@[simps!]
noncomputable def algEquiv : Localization M ≃ₐ[R] S :=
IsLocalization.algEquiv M _ _
#align localization.alg_equiv Localization.algEquiv
/-- The localization of a singleton is a singleton. Cannot be an instance due to metavariables. -/
noncomputable def _root_.IsLocalization.unique (R Rₘ) [CommSemiring R] [CommSemiring Rₘ]
(M : Submonoid R) [Subsingleton R] [Algebra R Rₘ] [IsLocalization M Rₘ] : Unique Rₘ :=
have : Inhabited Rₘ := ⟨1⟩
(algEquiv M Rₘ).symm.injective.unique
#align is_localization.unique IsLocalization.unique
end
-- Porting note (#10618): removed `simp`, `simp` can prove it
nonrec theorem algEquiv_mk' (x : R) (y : M) : algEquiv M S (mk' (Localization M) x y) = mk' S x y :=
algEquiv_mk' _ _
#align localization.alg_equiv_mk' Localization.algEquiv_mk'
-- Porting note (#10618): removed `simp`, `simp` can prove it
nonrec theorem algEquiv_symm_mk' (x : R) (y : M) :
(algEquiv M S).symm (mk' S x y) = mk' (Localization M) x y :=
algEquiv_symm_mk' _ _
#align localization.alg_equiv_symm_mk' Localization.algEquiv_symm_mk'
theorem algEquiv_mk (x y) : algEquiv M S (mk x y) = mk' S x y := by rw [mk_eq_mk', algEquiv_mk']
#align localization.alg_equiv_mk Localization.algEquiv_mk
theorem algEquiv_symm_mk (x : R) (y : M) : (algEquiv M S).symm (mk' S x y) = mk x y := by
rw [mk_eq_mk', algEquiv_symm_mk']
#align localization.alg_equiv_symm_mk Localization.algEquiv_symm_mk
lemma coe_algEquiv :
(Localization.algEquiv M S : Localization M →+* S) =
IsLocalization.map (M := M) (T := M) _ (RingHom.id R) le_rfl := rfl
lemma coe_algEquiv_symm :
((Localization.algEquiv M S).symm : S →+* Localization M) =
IsLocalization.map (M := M) (T := M) _ (RingHom.id R) le_rfl := rfl
end Localization
end CommSemiring
section CommRing
variable {R : Type*} [CommRing R] {M : Submonoid R} (S : Type*) [CommRing S]
variable [Algebra R S] {P : Type*} [CommRing P]
namespace Localization
/-- Negation in a ring localization is defined as `-⟨a, b⟩ = ⟨-a, b⟩`. -/
protected irreducible_def neg (z : Localization M) : Localization M :=
Localization.liftOn z (fun a b => mk (-a) b) fun {a b c d} h =>
mk_eq_mk_iff.2
(by
rw [r_eq_r'] at h ⊢
cases' h with t ht
use t
rw [mul_neg, mul_neg, ht]
ring_nf)
#align localization.neg Localization.neg
instance : Neg (Localization M) :=
⟨Localization.neg⟩
theorem neg_mk (a b) : -(mk a b : Localization M) = mk (-a) b := by
show Localization.neg (mk a b) = mk (-a) b
rw [Localization.neg_def]
apply liftOn_mk
#align localization.neg_mk Localization.neg_mk
instance : CommRing (Localization M) :=
{ inferInstanceAs (CommSemiring (Localization M)) with
zsmul := (· • ·)
zsmul_zero' := fun x =>
Localization.induction_on x fun x => by simp only [smul_mk, zero_zsmul, mk_zero]
zsmul_succ' := fun n x =>
Localization.induction_on x fun x => by
simp [smul_mk, add_mk_self, -mk_eq_monoidOf_mk', add_smul]
zsmul_neg' := fun n x =>
Localization.induction_on x fun x => by
dsimp only
rw [smul_mk, smul_mk, neg_mk, ← neg_smul]
rfl
neg := Neg.neg
sub := fun x y => x + -y
sub_eq_add_neg := fun x y => rfl
add_left_neg := fun y =>
Localization.induction_on y
(by
intros
simp only [add_mk, Localization.mk_mul, neg_mk, ← mk_zero 1]
refine mk_eq_mk_iff.mpr (r_of_eq ?_)
simp only [Submonoid.coe_mul]
ring) }
theorem sub_mk (a c) (b d) : (mk a b : Localization M) - mk c d =
mk ((d : R) * a - b * c) (b * d) :=
calc
mk a b - mk c d = mk a b + -mk c d := sub_eq_add_neg _ _
_ = mk a b + mk (-c) d := by rw [neg_mk]
_ = mk (b * -c + d * a) (b * d) := add_mk _ _ _ _
_ = mk (d * a - b * c) (b * d) := by congr; ring
#align localization.sub_mk Localization.sub_mk
theorem mk_intCast (m : ℤ) : (mk m 1 : Localization M) = m := by
simpa using mk_algebraMap (R := R) (A := ℤ) _
#align localization.mk_int_cast Localization.mk_intCast
@[deprecated (since := "2024-04-17")]
alias mk_int_cast := mk_intCast
end Localization
namespace IsLocalization
variable {K : Type*} [IsLocalization M S]
theorem to_map_eq_zero_iff {x : R} (hM : M ≤ nonZeroDivisors R) : algebraMap R S x = 0 ↔ x = 0 := by
rw [← (algebraMap R S).map_zero]
constructor <;> intro h
· cases' (eq_iff_exists M S).mp h with c hc
rw [mul_zero, mul_comm] at hc
exact hM c.2 x hc
· rw [h]
#align is_localization.to_map_eq_zero_iff IsLocalization.to_map_eq_zero_iff
protected theorem injective (hM : M ≤ nonZeroDivisors R) : Injective (algebraMap R S) := by
rw [injective_iff_map_eq_zero (algebraMap R S)]
intro a ha
rwa [to_map_eq_zero_iff S hM] at ha
#align is_localization.injective IsLocalization.injective
protected theorem to_map_ne_zero_of_mem_nonZeroDivisors [Nontrivial R] (hM : M ≤ nonZeroDivisors R)
{x : R} (hx : x ∈ nonZeroDivisors R) : algebraMap R S x ≠ 0 :=
show (algebraMap R S).toMonoidWithZeroHom x ≠ 0 from
map_ne_zero_of_mem_nonZeroDivisors (algebraMap R S) (IsLocalization.injective S hM) hx
#align is_localization.to_map_ne_zero_of_mem_non_zero_divisors IsLocalization.to_map_ne_zero_of_mem_nonZeroDivisors
variable {S}
theorem sec_snd_ne_zero [Nontrivial R] (hM : M ≤ nonZeroDivisors R) (x : S) :
((sec M x).snd : R) ≠ 0 :=
nonZeroDivisors.coe_ne_zero ⟨(sec M x).snd.val, hM (sec M x).snd.property⟩
#align is_localization.sec_snd_ne_zero IsLocalization.sec_snd_ne_zero
theorem sec_fst_ne_zero [Nontrivial R] [NoZeroDivisors S] (hM : M ≤ nonZeroDivisors R) {x : S}
(hx : x ≠ 0) : (sec M x).fst ≠ 0 := by
have hsec := sec_spec M x
intro hfst
rw [hfst, map_zero, mul_eq_zero, _root_.map_eq_zero_iff] at hsec
· exact Or.elim hsec hx (sec_snd_ne_zero hM x)
· exact IsLocalization.injective S hM
#align is_localization.sec_fst_ne_zero IsLocalization.sec_fst_ne_zero
variable {Q : Type*} [CommRing Q] {g : R →+* P} [Algebra P Q]
variable (A : Type*) [CommRing A] [IsDomain A]
/-- A `CommRing` `S` which is the localization of a ring `R` without zero divisors at a subset of
non-zero elements does not have zero divisors. -/
| Mathlib/RingTheory/Localization/Basic.lean | 1,270 | 1,282 | theorem noZeroDivisors_of_le_nonZeroDivisors [Algebra A S] {M : Submonoid A} [IsLocalization M S]
(hM : M ≤ nonZeroDivisors A) : NoZeroDivisors S :=
{ eq_zero_or_eq_zero_of_mul_eq_zero := by |
intro z w h
cases' surj M z with x hx
cases' surj M w with y hy
have :
z * w * algebraMap A S y.2 * algebraMap A S x.2 = algebraMap A S x.1 * algebraMap A S y.1 :=
by rw [mul_assoc z, hy, ← hx]; ring
rw [h, zero_mul, zero_mul, ← (algebraMap A S).map_mul] at this
cases' eq_zero_or_eq_zero_of_mul_eq_zero ((to_map_eq_zero_iff S hM).mp this.symm) with H H
· exact Or.inl (eq_zero_of_fst_eq_zero hx H)
· exact Or.inr (eq_zero_of_fst_eq_zero hy H) }
|
/-
Copyright (c) 2023 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.MFDeriv.Basic
import Mathlib.Topology.ContinuousFunction.Basic
import Mathlib.Geometry.Manifold.Algebra.LieGroup
#align_import geometry.manifold.vector_bundle.smooth_section from "leanprover-community/mathlib"@"e473c3198bb41f68560cab68a0529c854b618833"
/-!
# Smooth sections
In this file we define the type `ContMDiffSection` of `n` times continuously differentiable
sections of a smooth vector bundle over a manifold `M` and prove that it's a module.
-/
open Bundle Filter Function
open scoped Bundle Manifold
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H : Type*}
[TopologicalSpace H] {H' : Type*} [TopologicalSpace H'] (I : ModelWithCorners 𝕜 E H)
(I' : ModelWithCorners 𝕜 E' H') {M : Type*} [TopologicalSpace M] [ChartedSpace H M] {M' : Type*}
[TopologicalSpace M'] [ChartedSpace H' M'] {E'' : Type*} [NormedAddCommGroup E'']
[NormedSpace 𝕜 E''] {H'' : Type*} [TopologicalSpace H''] {I'' : ModelWithCorners 𝕜 E'' H''}
{M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M''] [SmoothManifoldWithCorners I M]
variable (F : Type*) [NormedAddCommGroup F] [NormedSpace 𝕜 F]
-- `F` model fiber
(n : ℕ∞)
(V : M → Type*) [TopologicalSpace (TotalSpace F V)]
-- `V` vector bundle
[∀ x, AddCommGroup (V x)]
[∀ x, Module 𝕜 (V x)]
variable [∀ x : M, TopologicalSpace (V x)] [FiberBundle F V] [VectorBundle 𝕜 F V]
[SmoothVectorBundle F V I]
/-- Bundled `n` times continuously differentiable sections of a vector bundle. -/
structure ContMDiffSection where
/-- the underlying function of this section -/
protected toFun : ∀ x, V x
/-- proof that this section is `C^n` -/
protected contMDiff_toFun : ContMDiff I (I.prod 𝓘(𝕜, F)) n fun x ↦
TotalSpace.mk' F x (toFun x)
#align cont_mdiff_section ContMDiffSection
/-- Bundled smooth sections of a vector bundle. -/
abbrev SmoothSection :=
ContMDiffSection I F ⊤ V
#align smooth_section SmoothSection
@[inherit_doc] scoped[Manifold] notation "Cₛ^" n "⟮" I "; " F ", " V "⟯" => ContMDiffSection I F n V
namespace ContMDiffSection
variable {I} {I'} {n} {F} {V}
instance : DFunLike Cₛ^n⟮I; F, V⟯ M V where
coe := ContMDiffSection.toFun
coe_injective' := by rintro ⟨⟩ ⟨⟩ h; congr
variable {s t : Cₛ^n⟮I; F, V⟯}
@[simp]
theorem coeFn_mk (s : ∀ x, V x)
(hs : ContMDiff I (I.prod 𝓘(𝕜, F)) n fun x => TotalSpace.mk x (s x)) :
(mk s hs : ∀ x, V x) = s :=
rfl
#align cont_mdiff_section.coe_fn_mk ContMDiffSection.coeFn_mk
protected theorem contMDiff (s : Cₛ^n⟮I; F, V⟯) :
ContMDiff I (I.prod 𝓘(𝕜, F)) n fun x => TotalSpace.mk' F x (s x : V x) :=
s.contMDiff_toFun
#align cont_mdiff_section.cont_mdiff ContMDiffSection.contMDiff
protected theorem smooth (s : Cₛ^∞⟮I; F, V⟯) :
Smooth I (I.prod 𝓘(𝕜, F)) fun x => TotalSpace.mk' F x (s x : V x) :=
s.contMDiff_toFun
#align cont_mdiff_section.smooth ContMDiffSection.smooth
protected theorem mdifferentiable' (s : Cₛ^n⟮I; F, V⟯) (hn : 1 ≤ n) :
MDifferentiable I (I.prod 𝓘(𝕜, F)) fun x => TotalSpace.mk' F x (s x : V x) :=
s.contMDiff.mdifferentiable hn
#align cont_mdiff_section.mdifferentiable' ContMDiffSection.mdifferentiable'
protected theorem mdifferentiable (s : Cₛ^∞⟮I; F, V⟯) :
MDifferentiable I (I.prod 𝓘(𝕜, F)) fun x => TotalSpace.mk' F x (s x : V x) :=
s.contMDiff.mdifferentiable le_top
#align cont_mdiff_section.mdifferentiable ContMDiffSection.mdifferentiable
protected theorem mdifferentiableAt (s : Cₛ^∞⟮I; F, V⟯) {x} :
MDifferentiableAt I (I.prod 𝓘(𝕜, F)) (fun x => TotalSpace.mk' F x (s x : V x)) x :=
s.mdifferentiable x
#align cont_mdiff_section.mdifferentiable_at ContMDiffSection.mdifferentiableAt
theorem coe_inj ⦃s t : Cₛ^n⟮I; F, V⟯⦄ (h : (s : ∀ x, V x) = t) : s = t :=
DFunLike.ext' h
#align cont_mdiff_section.coe_inj ContMDiffSection.coe_inj
theorem coe_injective : Injective ((↑) : Cₛ^n⟮I; F, V⟯ → ∀ x, V x) :=
coe_inj
#align cont_mdiff_section.coe_injective ContMDiffSection.coe_injective
@[ext]
theorem ext (h : ∀ x, s x = t x) : s = t := DFunLike.ext _ _ h
#align cont_mdiff_section.ext ContMDiffSection.ext
instance instAdd : Add Cₛ^n⟮I; F, V⟯ := by
refine ⟨fun s t => ⟨s + t, ?_⟩⟩
intro x₀
have hs := s.contMDiff x₀
have ht := t.contMDiff x₀
rw [contMDiffAt_section] at hs ht ⊢
set e := trivializationAt F V x₀
refine (hs.add ht).congr_of_eventuallyEq ?_
refine eventually_of_mem (e.open_baseSet.mem_nhds <| mem_baseSet_trivializationAt F V x₀) ?_
intro x hx
apply (e.linear 𝕜 hx).1
#align cont_mdiff_section.has_add ContMDiffSection.instAdd
@[simp]
theorem coe_add (s t : Cₛ^n⟮I; F, V⟯) : ⇑(s + t) = ⇑s + t :=
rfl
#align cont_mdiff_section.coe_add ContMDiffSection.coe_add
instance instSub : Sub Cₛ^n⟮I; F, V⟯ := by
refine ⟨fun s t => ⟨s - t, ?_⟩⟩
intro x₀
have hs := s.contMDiff x₀
have ht := t.contMDiff x₀
rw [contMDiffAt_section] at hs ht ⊢
set e := trivializationAt F V x₀
refine (hs.sub ht).congr_of_eventuallyEq ?_
refine eventually_of_mem (e.open_baseSet.mem_nhds <| mem_baseSet_trivializationAt F V x₀) ?_
intro x hx
apply (e.linear 𝕜 hx).map_sub
#align cont_mdiff_section.has_sub ContMDiffSection.instSub
@[simp]
theorem coe_sub (s t : Cₛ^n⟮I; F, V⟯) : ⇑(s - t) = s - t :=
rfl
#align cont_mdiff_section.coe_sub ContMDiffSection.coe_sub
instance instZero : Zero Cₛ^n⟮I; F, V⟯ :=
⟨⟨fun _ => 0, (smooth_zeroSection 𝕜 V).of_le le_top⟩⟩
#align cont_mdiff_section.has_zero ContMDiffSection.instZero
instance inhabited : Inhabited Cₛ^n⟮I; F, V⟯ :=
⟨0⟩
#align cont_mdiff_section.inhabited ContMDiffSection.inhabited
@[simp]
theorem coe_zero : ⇑(0 : Cₛ^n⟮I; F, V⟯) = 0 :=
rfl
#align cont_mdiff_section.coe_zero ContMDiffSection.coe_zero
instance instSMul : SMul 𝕜 Cₛ^n⟮I; F, V⟯ := by
refine ⟨fun c s => ⟨c • ⇑s, ?_⟩⟩
intro x₀
have hs := s.contMDiff x₀
rw [contMDiffAt_section] at hs ⊢
set e := trivializationAt F V x₀
refine ((contMDiffAt_const (c := c)).smul hs).congr_of_eventuallyEq ?_
refine eventually_of_mem (e.open_baseSet.mem_nhds <| mem_baseSet_trivializationAt F V x₀) ?_
intro x hx
apply (e.linear 𝕜 hx).2
#align cont_mdiff_section.has_smul ContMDiffSection.instSMul
@[simp]
theorem coe_smul (r : 𝕜) (s : Cₛ^n⟮I; F, V⟯) : ⇑(r • s : Cₛ^n⟮I; F, V⟯) = r • ⇑s :=
rfl
#align cont_mdiff_section.coe_smul ContMDiffSection.coe_smul
instance instNeg : Neg Cₛ^n⟮I; F, V⟯ := by
refine ⟨fun s => ⟨-s, ?_⟩⟩
intro x₀
have hs := s.contMDiff x₀
rw [contMDiffAt_section] at hs ⊢
set e := trivializationAt F V x₀
refine hs.neg.congr_of_eventuallyEq ?_
refine eventually_of_mem (e.open_baseSet.mem_nhds <| mem_baseSet_trivializationAt F V x₀) ?_
intro x hx
apply (e.linear 𝕜 hx).map_neg
#align cont_mdiff_section.has_neg ContMDiffSection.instNeg
@[simp]
theorem coe_neg (s : Cₛ^n⟮I; F, V⟯) : ⇑(-s : Cₛ^n⟮I; F, V⟯) = -s :=
rfl
#align cont_mdiff_section.coe_neg ContMDiffSection.coe_neg
instance instNSMul : SMul ℕ Cₛ^n⟮I; F, V⟯ :=
⟨nsmulRec⟩
#align cont_mdiff_section.has_nsmul ContMDiffSection.instNSMul
@[simp]
| Mathlib/Geometry/Manifold/VectorBundle/SmoothSection.lean | 201 | 204 | theorem coe_nsmul (s : Cₛ^n⟮I; F, V⟯) (k : ℕ) : ⇑(k • s : Cₛ^n⟮I; F, V⟯) = k • ⇑s := by |
induction' k with k ih
· simp_rw [zero_smul]; rfl
simp_rw [succ_nsmul, ← ih]; rfl
|
/-
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.Data.Set.Pointwise.Interval
import Mathlib.LinearAlgebra.AffineSpace.Basic
import Mathlib.LinearAlgebra.BilinearMap
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Prod
#align_import linear_algebra.affine_space.affine_map from "leanprover-community/mathlib"@"bd1fc183335ea95a9519a1630bcf901fe9326d83"
/-!
# Affine maps
This file defines affine maps.
## Main definitions
* `AffineMap` is the type of affine maps between two affine spaces with the same ring `k`. Various
basic examples of affine maps are defined, including `const`, `id`, `lineMap` and `homothety`.
## Notations
* `P1 →ᵃ[k] P2` is a notation for `AffineMap k P1 P2`;
* `AffineSpace V P`: a localized notation for `AddTorsor V P` defined in
`LinearAlgebra.AffineSpace.Basic`.
## Implementation notes
`outParam` is used in the definition of `[AddTorsor V P]` to make `V` an implicit argument
(deduced from `P`) in most cases. As for modules, `k` is an explicit argument rather than implied by
`P` or `V`.
This file only provides purely algebraic definitions and results. Those depending on analysis or
topology are defined elsewhere; see `Analysis.NormedSpace.AddTorsor` and
`Topology.Algebra.Affine`.
## References
* https://en.wikipedia.org/wiki/Affine_space
* https://en.wikipedia.org/wiki/Principal_homogeneous_space
-/
open Affine
/-- An `AffineMap k P1 P2` (notation: `P1 →ᵃ[k] P2`) is a map from `P1` to `P2` that
induces a corresponding linear map from `V1` to `V2`. -/
structure AffineMap (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*) [Ring k]
[AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] where
toFun : P1 → P2
linear : V1 →ₗ[k] V2
map_vadd' : ∀ (p : P1) (v : V1), toFun (v +ᵥ p) = linear v +ᵥ toFun p
#align affine_map AffineMap
/-- An `AffineMap k P1 P2` (notation: `P1 →ᵃ[k] P2`) is a map from `P1` to `P2` that
induces a corresponding linear map from `V1` to `V2`. -/
notation:25 P1 " →ᵃ[" k:25 "] " P2:0 => AffineMap k P1 P2
instance AffineMap.instFunLike (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*)
[Ring k] [AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] : FunLike (P1 →ᵃ[k] P2) P1 P2 where
coe := AffineMap.toFun
coe_injective' := fun ⟨f, f_linear, f_add⟩ ⟨g, g_linear, g_add⟩ => fun (h : f = g) => by
cases' (AddTorsor.nonempty : Nonempty P1) with p
congr with v
apply vadd_right_cancel (f p)
erw [← f_add, h, ← g_add]
#align affine_map.fun_like AffineMap.instFunLike
instance AffineMap.hasCoeToFun (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*)
[Ring k] [AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] : CoeFun (P1 →ᵃ[k] P2) fun _ => P1 → P2 :=
DFunLike.hasCoeToFun
#align affine_map.has_coe_to_fun AffineMap.hasCoeToFun
namespace LinearMap
variable {k : Type*} {V₁ : Type*} {V₂ : Type*} [Ring k] [AddCommGroup V₁] [Module k V₁]
[AddCommGroup V₂] [Module k V₂] (f : V₁ →ₗ[k] V₂)
/-- Reinterpret a linear map as an affine map. -/
def toAffineMap : V₁ →ᵃ[k] V₂ where
toFun := f
linear := f
map_vadd' p v := f.map_add v p
#align linear_map.to_affine_map LinearMap.toAffineMap
@[simp]
theorem coe_toAffineMap : ⇑f.toAffineMap = f :=
rfl
#align linear_map.coe_to_affine_map LinearMap.coe_toAffineMap
@[simp]
theorem toAffineMap_linear : f.toAffineMap.linear = f :=
rfl
#align linear_map.to_affine_map_linear LinearMap.toAffineMap_linear
end LinearMap
namespace AffineMap
variable {k : Type*} {V1 : Type*} {P1 : Type*} {V2 : Type*} {P2 : Type*} {V3 : Type*}
{P3 : Type*} {V4 : Type*} {P4 : Type*} [Ring k] [AddCommGroup V1] [Module k V1]
[AffineSpace V1 P1] [AddCommGroup V2] [Module k V2] [AffineSpace V2 P2] [AddCommGroup V3]
[Module k V3] [AffineSpace V3 P3] [AddCommGroup V4] [Module k V4] [AffineSpace V4 P4]
/-- Constructing an affine map and coercing back to a function
produces the same map. -/
@[simp]
theorem coe_mk (f : P1 → P2) (linear add) : ((mk f linear add : P1 →ᵃ[k] P2) : P1 → P2) = f :=
rfl
#align affine_map.coe_mk AffineMap.coe_mk
/-- `toFun` is the same as the result of coercing to a function. -/
@[simp]
theorem toFun_eq_coe (f : P1 →ᵃ[k] P2) : f.toFun = ⇑f :=
rfl
#align affine_map.to_fun_eq_coe AffineMap.toFun_eq_coe
/-- An affine map on the result of adding a vector to a point produces
the same result as the linear map applied to that vector, added to the
affine map applied to that point. -/
@[simp]
theorem map_vadd (f : P1 →ᵃ[k] P2) (p : P1) (v : V1) : f (v +ᵥ p) = f.linear v +ᵥ f p :=
f.map_vadd' p v
#align affine_map.map_vadd AffineMap.map_vadd
/-- The linear map on the result of subtracting two points is the
result of subtracting the result of the affine map on those two
points. -/
@[simp]
theorem linearMap_vsub (f : P1 →ᵃ[k] P2) (p1 p2 : P1) : f.linear (p1 -ᵥ p2) = f p1 -ᵥ f p2 := by
conv_rhs => rw [← vsub_vadd p1 p2, map_vadd, vadd_vsub]
#align affine_map.linear_map_vsub AffineMap.linearMap_vsub
/-- Two affine maps are equal if they coerce to the same function. -/
@[ext]
theorem ext {f g : P1 →ᵃ[k] P2} (h : ∀ p, f p = g p) : f = g :=
DFunLike.ext _ _ h
#align affine_map.ext AffineMap.ext
theorem ext_iff {f g : P1 →ᵃ[k] P2} : f = g ↔ ∀ p, f p = g p :=
⟨fun h _ => h ▸ rfl, ext⟩
#align affine_map.ext_iff AffineMap.ext_iff
theorem coeFn_injective : @Function.Injective (P1 →ᵃ[k] P2) (P1 → P2) (⇑) :=
DFunLike.coe_injective
#align affine_map.coe_fn_injective AffineMap.coeFn_injective
protected theorem congr_arg (f : P1 →ᵃ[k] P2) {x y : P1} (h : x = y) : f x = f y :=
congr_arg _ h
#align affine_map.congr_arg AffineMap.congr_arg
protected theorem congr_fun {f g : P1 →ᵃ[k] P2} (h : f = g) (x : P1) : f x = g x :=
h ▸ rfl
#align affine_map.congr_fun AffineMap.congr_fun
/-- Two affine maps are equal if they have equal linear maps and are equal at some point. -/
theorem ext_linear {f g : P1 →ᵃ[k] P2} (h₁ : f.linear = g.linear) {p : P1} (h₂ : f p = g p) :
f = g := by
ext q
have hgl : g.linear (q -ᵥ p) = toFun g ((q -ᵥ p) +ᵥ q) -ᵥ toFun g q := by simp
have := f.map_vadd' q (q -ᵥ p)
rw [h₁, hgl, toFun_eq_coe, map_vadd, linearMap_vsub, h₂] at this
simp at this
exact this
/-- Two affine maps are equal if they have equal linear maps and are equal at some point. -/
theorem ext_linear_iff {f g : P1 →ᵃ[k] P2} : f = g ↔ (f.linear = g.linear) ∧ (∃ p, f p = g p) :=
⟨fun h ↦ ⟨congrArg _ h, by inhabit P1; exact default, by rw [h]⟩,
fun h ↦ Exists.casesOn h.2 fun _ hp ↦ ext_linear h.1 hp⟩
variable (k P1)
/-- The constant function as an `AffineMap`. -/
def const (p : P2) : P1 →ᵃ[k] P2 where
toFun := Function.const P1 p
linear := 0
map_vadd' _ _ :=
letI : AddAction V2 P2 := inferInstance
by simp
#align affine_map.const AffineMap.const
@[simp]
theorem coe_const (p : P2) : ⇑(const k P1 p) = Function.const P1 p :=
rfl
#align affine_map.coe_const AffineMap.coe_const
-- Porting note (#10756): new theorem
@[simp]
theorem const_apply (p : P2) (q : P1) : (const k P1 p) q = p := rfl
@[simp]
theorem const_linear (p : P2) : (const k P1 p).linear = 0 :=
rfl
#align affine_map.const_linear AffineMap.const_linear
variable {k P1}
theorem linear_eq_zero_iff_exists_const (f : P1 →ᵃ[k] P2) :
f.linear = 0 ↔ ∃ q, f = const k P1 q := by
refine ⟨fun h => ?_, fun h => ?_⟩
· use f (Classical.arbitrary P1)
ext
rw [coe_const, Function.const_apply, ← @vsub_eq_zero_iff_eq V2, ← f.linearMap_vsub, h,
LinearMap.zero_apply]
· rcases h with ⟨q, rfl⟩
exact const_linear k P1 q
#align affine_map.linear_eq_zero_iff_exists_const AffineMap.linear_eq_zero_iff_exists_const
instance nonempty : Nonempty (P1 →ᵃ[k] P2) :=
(AddTorsor.nonempty : Nonempty P2).map <| const k P1
#align affine_map.nonempty AffineMap.nonempty
/-- Construct an affine map by verifying the relation between the map and its linear part at one
base point. Namely, this function takes a map `f : P₁ → P₂`, a linear map `f' : V₁ →ₗ[k] V₂`, and
a point `p` such that for any other point `p'` we have `f p' = f' (p' -ᵥ p) +ᵥ f p`. -/
def mk' (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p : P1) (h : ∀ p' : P1, f p' = f' (p' -ᵥ p) +ᵥ f p) :
P1 →ᵃ[k] P2 where
toFun := f
linear := f'
map_vadd' p' v := by rw [h, h p', vadd_vsub_assoc, f'.map_add, vadd_vadd]
#align affine_map.mk' AffineMap.mk'
@[simp]
theorem coe_mk' (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p h) : ⇑(mk' f f' p h) = f :=
rfl
#align affine_map.coe_mk' AffineMap.coe_mk'
@[simp]
theorem mk'_linear (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p h) : (mk' f f' p h).linear = f' :=
rfl
#align affine_map.mk'_linear AffineMap.mk'_linear
section SMul
variable {R : Type*} [Monoid R] [DistribMulAction R V2] [SMulCommClass k R V2]
/-- The space of affine maps to a module inherits an `R`-action from the action on its codomain. -/
instance mulAction : MulAction R (P1 →ᵃ[k] V2) where
-- Porting note: `map_vadd` is `simp`, but we still have to pass it explicitly
smul c f := ⟨c • ⇑f, c • f.linear, fun p v => by simp [smul_add, map_vadd f]⟩
one_smul f := ext fun p => one_smul _ _
mul_smul c₁ c₂ f := ext fun p => mul_smul _ _ _
@[simp, norm_cast]
theorem coe_smul (c : R) (f : P1 →ᵃ[k] V2) : ⇑(c • f) = c • ⇑f :=
rfl
#align affine_map.coe_smul AffineMap.coe_smul
@[simp]
theorem smul_linear (t : R) (f : P1 →ᵃ[k] V2) : (t • f).linear = t • f.linear :=
rfl
#align affine_map.smul_linear AffineMap.smul_linear
instance isCentralScalar [DistribMulAction Rᵐᵒᵖ V2] [IsCentralScalar R V2] :
IsCentralScalar R (P1 →ᵃ[k] V2) where
op_smul_eq_smul _r _x := ext fun _ => op_smul_eq_smul _ _
end SMul
instance : Zero (P1 →ᵃ[k] V2) where zero := ⟨0, 0, fun _ _ => (zero_vadd _ _).symm⟩
instance : Add (P1 →ᵃ[k] V2) where
add f g := ⟨f + g, f.linear + g.linear, fun p v => by simp [add_add_add_comm]⟩
instance : Sub (P1 →ᵃ[k] V2) where
sub f g := ⟨f - g, f.linear - g.linear, fun p v => by simp [sub_add_sub_comm]⟩
instance : Neg (P1 →ᵃ[k] V2) where
neg f := ⟨-f, -f.linear, fun p v => by simp [add_comm, map_vadd f]⟩
@[simp, norm_cast]
theorem coe_zero : ⇑(0 : P1 →ᵃ[k] V2) = 0 :=
rfl
#align affine_map.coe_zero AffineMap.coe_zero
@[simp, norm_cast]
theorem coe_add (f g : P1 →ᵃ[k] V2) : ⇑(f + g) = f + g :=
rfl
#align affine_map.coe_add AffineMap.coe_add
@[simp, norm_cast]
theorem coe_neg (f : P1 →ᵃ[k] V2) : ⇑(-f) = -f :=
rfl
#align affine_map.coe_neg AffineMap.coe_neg
@[simp, norm_cast]
theorem coe_sub (f g : P1 →ᵃ[k] V2) : ⇑(f - g) = f - g :=
rfl
#align affine_map.coe_sub AffineMap.coe_sub
@[simp]
theorem zero_linear : (0 : P1 →ᵃ[k] V2).linear = 0 :=
rfl
#align affine_map.zero_linear AffineMap.zero_linear
@[simp]
theorem add_linear (f g : P1 →ᵃ[k] V2) : (f + g).linear = f.linear + g.linear :=
rfl
#align affine_map.add_linear AffineMap.add_linear
@[simp]
theorem sub_linear (f g : P1 →ᵃ[k] V2) : (f - g).linear = f.linear - g.linear :=
rfl
#align affine_map.sub_linear AffineMap.sub_linear
@[simp]
theorem neg_linear (f : P1 →ᵃ[k] V2) : (-f).linear = -f.linear :=
rfl
#align affine_map.neg_linear AffineMap.neg_linear
/-- The set of affine maps to a vector space is an additive commutative group. -/
instance : AddCommGroup (P1 →ᵃ[k] V2) :=
coeFn_injective.addCommGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_smul _ _)
fun _ _ => coe_smul _ _
/-- The space of affine maps from `P1` to `P2` is an affine space over the space of affine maps
from `P1` to the vector space `V2` corresponding to `P2`. -/
instance : AffineSpace (P1 →ᵃ[k] V2) (P1 →ᵃ[k] P2) where
vadd f g :=
⟨fun p => f p +ᵥ g p, f.linear + g.linear,
fun p v => by simp [vadd_vadd, add_right_comm]⟩
zero_vadd f := ext fun p => zero_vadd _ (f p)
add_vadd f₁ f₂ f₃ := ext fun p => add_vadd (f₁ p) (f₂ p) (f₃ p)
vsub f g :=
⟨fun p => f p -ᵥ g p, f.linear - g.linear, fun p v => by
simp [vsub_vadd_eq_vsub_sub, vadd_vsub_assoc, add_sub, sub_add_eq_add_sub]⟩
vsub_vadd' f g := ext fun p => vsub_vadd (f p) (g p)
vadd_vsub' f g := ext fun p => vadd_vsub (f p) (g p)
@[simp]
theorem vadd_apply (f : P1 →ᵃ[k] V2) (g : P1 →ᵃ[k] P2) (p : P1) : (f +ᵥ g) p = f p +ᵥ g p :=
rfl
#align affine_map.vadd_apply AffineMap.vadd_apply
@[simp]
theorem vsub_apply (f g : P1 →ᵃ[k] P2) (p : P1) : (f -ᵥ g : P1 →ᵃ[k] V2) p = f p -ᵥ g p :=
rfl
#align affine_map.vsub_apply AffineMap.vsub_apply
/-- `Prod.fst` as an `AffineMap`. -/
def fst : P1 × P2 →ᵃ[k] P1 where
toFun := Prod.fst
linear := LinearMap.fst k V1 V2
map_vadd' _ _ := rfl
#align affine_map.fst AffineMap.fst
@[simp]
theorem coe_fst : ⇑(fst : P1 × P2 →ᵃ[k] P1) = Prod.fst :=
rfl
#align affine_map.coe_fst AffineMap.coe_fst
@[simp]
theorem fst_linear : (fst : P1 × P2 →ᵃ[k] P1).linear = LinearMap.fst k V1 V2 :=
rfl
#align affine_map.fst_linear AffineMap.fst_linear
/-- `Prod.snd` as an `AffineMap`. -/
def snd : P1 × P2 →ᵃ[k] P2 where
toFun := Prod.snd
linear := LinearMap.snd k V1 V2
map_vadd' _ _ := rfl
#align affine_map.snd AffineMap.snd
@[simp]
theorem coe_snd : ⇑(snd : P1 × P2 →ᵃ[k] P2) = Prod.snd :=
rfl
#align affine_map.coe_snd AffineMap.coe_snd
@[simp]
theorem snd_linear : (snd : P1 × P2 →ᵃ[k] P2).linear = LinearMap.snd k V1 V2 :=
rfl
#align affine_map.snd_linear AffineMap.snd_linear
variable (k P1)
/-- Identity map as an affine map. -/
nonrec def id : P1 →ᵃ[k] P1 where
toFun := id
linear := LinearMap.id
map_vadd' _ _ := rfl
#align affine_map.id AffineMap.id
/-- The identity affine map acts as the identity. -/
@[simp]
theorem coe_id : ⇑(id k P1) = _root_.id :=
rfl
#align affine_map.coe_id AffineMap.coe_id
@[simp]
theorem id_linear : (id k P1).linear = LinearMap.id :=
rfl
#align affine_map.id_linear AffineMap.id_linear
variable {P1}
/-- The identity affine map acts as the identity. -/
theorem id_apply (p : P1) : id k P1 p = p :=
rfl
#align affine_map.id_apply AffineMap.id_apply
variable {k}
instance : Inhabited (P1 →ᵃ[k] P1) :=
⟨id k P1⟩
/-- Composition of affine maps. -/
def comp (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) : P1 →ᵃ[k] P3 where
toFun := f ∘ g
linear := f.linear.comp g.linear
map_vadd' := by
intro p v
rw [Function.comp_apply, g.map_vadd, f.map_vadd]
rfl
#align affine_map.comp AffineMap.comp
/-- Composition of affine maps acts as applying the two functions. -/
@[simp]
theorem coe_comp (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) : ⇑(f.comp g) = f ∘ g :=
rfl
#align affine_map.coe_comp AffineMap.coe_comp
/-- Composition of affine maps acts as applying the two functions. -/
theorem comp_apply (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) (p : P1) : f.comp g p = f (g p) :=
rfl
#align affine_map.comp_apply AffineMap.comp_apply
@[simp]
theorem comp_id (f : P1 →ᵃ[k] P2) : f.comp (id k P1) = f :=
ext fun _ => rfl
#align affine_map.comp_id AffineMap.comp_id
@[simp]
theorem id_comp (f : P1 →ᵃ[k] P2) : (id k P2).comp f = f :=
ext fun _ => rfl
#align affine_map.id_comp AffineMap.id_comp
theorem comp_assoc (f₃₄ : P3 →ᵃ[k] P4) (f₂₃ : P2 →ᵃ[k] P3) (f₁₂ : P1 →ᵃ[k] P2) :
(f₃₄.comp f₂₃).comp f₁₂ = f₃₄.comp (f₂₃.comp f₁₂) :=
rfl
#align affine_map.comp_assoc AffineMap.comp_assoc
instance : Monoid (P1 →ᵃ[k] P1) where
one := id k P1
mul := comp
one_mul := id_comp
mul_one := comp_id
mul_assoc := comp_assoc
@[simp]
theorem coe_mul (f g : P1 →ᵃ[k] P1) : ⇑(f * g) = f ∘ g :=
rfl
#align affine_map.coe_mul AffineMap.coe_mul
@[simp]
theorem coe_one : ⇑(1 : P1 →ᵃ[k] P1) = _root_.id :=
rfl
#align affine_map.coe_one AffineMap.coe_one
/-- `AffineMap.linear` on endomorphisms is a `MonoidHom`. -/
@[simps]
def linearHom : (P1 →ᵃ[k] P1) →* V1 →ₗ[k] V1 where
toFun := linear
map_one' := rfl
map_mul' _ _ := rfl
#align affine_map.linear_hom AffineMap.linearHom
@[simp]
theorem linear_injective_iff (f : P1 →ᵃ[k] P2) :
Function.Injective f.linear ↔ Function.Injective f := by
obtain ⟨p⟩ := (inferInstance : Nonempty P1)
have h : ⇑f.linear = (Equiv.vaddConst (f p)).symm ∘ f ∘ Equiv.vaddConst p := by
ext v
simp [f.map_vadd, vadd_vsub_assoc]
rw [h, Equiv.comp_injective, Equiv.injective_comp]
#align affine_map.linear_injective_iff AffineMap.linear_injective_iff
@[simp]
theorem linear_surjective_iff (f : P1 →ᵃ[k] P2) :
Function.Surjective f.linear ↔ Function.Surjective f := by
obtain ⟨p⟩ := (inferInstance : Nonempty P1)
have h : ⇑f.linear = (Equiv.vaddConst (f p)).symm ∘ f ∘ Equiv.vaddConst p := by
ext v
simp [f.map_vadd, vadd_vsub_assoc]
rw [h, Equiv.comp_surjective, Equiv.surjective_comp]
#align affine_map.linear_surjective_iff AffineMap.linear_surjective_iff
@[simp]
theorem linear_bijective_iff (f : P1 →ᵃ[k] P2) :
Function.Bijective f.linear ↔ Function.Bijective f :=
and_congr f.linear_injective_iff f.linear_surjective_iff
#align affine_map.linear_bijective_iff AffineMap.linear_bijective_iff
theorem image_vsub_image {s t : Set P1} (f : P1 →ᵃ[k] P2) :
f '' s -ᵥ f '' t = f.linear '' (s -ᵥ t) := by
ext v
-- Porting note: `simp` needs `Set.mem_vsub` to be an expression
simp only [(Set.mem_vsub), Set.mem_image,
exists_exists_and_eq_and, exists_and_left, ← f.linearMap_vsub]
constructor
· rintro ⟨x, hx, y, hy, hv⟩
exact ⟨x -ᵥ y, ⟨x, hx, y, hy, rfl⟩, hv⟩
· rintro ⟨-, ⟨x, hx, y, hy, rfl⟩, rfl⟩
exact ⟨x, hx, y, hy, rfl⟩
#align affine_map.image_vsub_image AffineMap.image_vsub_image
/-! ### Definition of `AffineMap.lineMap` and lemmas about it -/
/-- The affine map from `k` to `P1` sending `0` to `p₀` and `1` to `p₁`. -/
def lineMap (p₀ p₁ : P1) : k →ᵃ[k] P1 :=
((LinearMap.id : k →ₗ[k] k).smulRight (p₁ -ᵥ p₀)).toAffineMap +ᵥ const k k p₀
#align affine_map.line_map AffineMap.lineMap
theorem coe_lineMap (p₀ p₁ : P1) : (lineMap p₀ p₁ : k → P1) = fun c => c • (p₁ -ᵥ p₀) +ᵥ p₀ :=
rfl
#align affine_map.coe_line_map AffineMap.coe_lineMap
theorem lineMap_apply (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c = c • (p₁ -ᵥ p₀) +ᵥ p₀ :=
rfl
#align affine_map.line_map_apply AffineMap.lineMap_apply
theorem lineMap_apply_module' (p₀ p₁ : V1) (c : k) : lineMap p₀ p₁ c = c • (p₁ - p₀) + p₀ :=
rfl
#align affine_map.line_map_apply_module' AffineMap.lineMap_apply_module'
theorem lineMap_apply_module (p₀ p₁ : V1) (c : k) : lineMap p₀ p₁ c = (1 - c) • p₀ + c • p₁ := by
simp [lineMap_apply_module', smul_sub, sub_smul]; abel
#align affine_map.line_map_apply_module AffineMap.lineMap_apply_module
theorem lineMap_apply_ring' (a b c : k) : lineMap a b c = c * (b - a) + a :=
rfl
#align affine_map.line_map_apply_ring' AffineMap.lineMap_apply_ring'
theorem lineMap_apply_ring (a b c : k) : lineMap a b c = (1 - c) * a + c * b :=
lineMap_apply_module a b c
#align affine_map.line_map_apply_ring AffineMap.lineMap_apply_ring
theorem lineMap_vadd_apply (p : P1) (v : V1) (c : k) : lineMap p (v +ᵥ p) c = c • v +ᵥ p := by
rw [lineMap_apply, vadd_vsub]
#align affine_map.line_map_vadd_apply AffineMap.lineMap_vadd_apply
@[simp]
theorem lineMap_linear (p₀ p₁ : P1) :
(lineMap p₀ p₁ : k →ᵃ[k] P1).linear = LinearMap.id.smulRight (p₁ -ᵥ p₀) :=
add_zero _
#align affine_map.line_map_linear AffineMap.lineMap_linear
theorem lineMap_same_apply (p : P1) (c : k) : lineMap p p c = p := by
simp [lineMap_apply]
#align affine_map.line_map_same_apply AffineMap.lineMap_same_apply
@[simp]
theorem lineMap_same (p : P1) : lineMap p p = const k k p :=
ext <| lineMap_same_apply p
#align affine_map.line_map_same AffineMap.lineMap_same
@[simp]
theorem lineMap_apply_zero (p₀ p₁ : P1) : lineMap p₀ p₁ (0 : k) = p₀ := by
simp [lineMap_apply]
#align affine_map.line_map_apply_zero AffineMap.lineMap_apply_zero
@[simp]
theorem lineMap_apply_one (p₀ p₁ : P1) : lineMap p₀ p₁ (1 : k) = p₁ := by
simp [lineMap_apply]
#align affine_map.line_map_apply_one AffineMap.lineMap_apply_one
@[simp]
| Mathlib/LinearAlgebra/AffineSpace/AffineMap.lean | 570 | 573 | theorem lineMap_eq_lineMap_iff [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} {c₁ c₂ : k} :
lineMap p₀ p₁ c₁ = lineMap p₀ p₁ c₂ ↔ p₀ = p₁ ∨ c₁ = c₂ := by |
rw [lineMap_apply, lineMap_apply, ← @vsub_eq_zero_iff_eq V1, vadd_vsub_vadd_cancel_right, ←
sub_smul, smul_eq_zero, sub_eq_zero, vsub_eq_zero_iff_eq, or_comm, eq_comm]
|
/-
Copyright (c) 2020 Aaron Anderson, Jalex Stark, Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jalex Stark, Kyle Miller, Alena Gusakov
-/
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Combinatorics.SimpleGraph.Basic
import Mathlib.Data.Sym.Card
/-!
# Definitions for finite and locally finite graphs
This file defines finite versions of `edgeSet`, `neighborSet` and `incidenceSet` and proves some
of their basic properties. It also defines the notion of a locally finite graph, which is one
whose vertices have finite degree.
The design for finiteness is that each definition takes the smallest finiteness assumption
necessary. For example, `SimpleGraph.neighborFinset v` only requires that `v` have
finitely many neighbors.
## Main definitions
* `SimpleGraph.edgeFinset` is the `Finset` of edges in a graph, if `edgeSet` is finite
* `SimpleGraph.neighborFinset` is the `Finset` of vertices adjacent to a given vertex,
if `neighborSet` is finite
* `SimpleGraph.incidenceFinset` is the `Finset` of edges containing a given vertex,
if `incidenceSet` is finite
## Naming conventions
If the vertex type of a graph is finite, we refer to its cardinality as `CardVerts`
or `card_verts`.
## Implementation notes
* A locally finite graph is one with instances `Π v, Fintype (G.neighborSet v)`.
* Given instances `DecidableRel G.Adj` and `Fintype V`, then the graph
is locally finite, too.
-/
open Finset Function
namespace SimpleGraph
variable {V : Type*} (G : SimpleGraph V) {e : Sym2 V}
section EdgeFinset
variable {G₁ G₂ : SimpleGraph V} [Fintype G.edgeSet] [Fintype G₁.edgeSet] [Fintype G₂.edgeSet]
/-- The `edgeSet` of the graph as a `Finset`. -/
abbrev edgeFinset : Finset (Sym2 V) :=
Set.toFinset G.edgeSet
#align simple_graph.edge_finset SimpleGraph.edgeFinset
@[norm_cast]
theorem coe_edgeFinset : (G.edgeFinset : Set (Sym2 V)) = G.edgeSet :=
Set.coe_toFinset _
#align simple_graph.coe_edge_finset SimpleGraph.coe_edgeFinset
variable {G}
theorem mem_edgeFinset : e ∈ G.edgeFinset ↔ e ∈ G.edgeSet :=
Set.mem_toFinset
#align simple_graph.mem_edge_finset SimpleGraph.mem_edgeFinset
theorem not_isDiag_of_mem_edgeFinset : e ∈ G.edgeFinset → ¬e.IsDiag :=
not_isDiag_of_mem_edgeSet _ ∘ mem_edgeFinset.1
#align simple_graph.not_is_diag_of_mem_edge_finset SimpleGraph.not_isDiag_of_mem_edgeFinset
theorem edgeFinset_inj : G₁.edgeFinset = G₂.edgeFinset ↔ G₁ = G₂ := by simp
#align simple_graph.edge_finset_inj SimpleGraph.edgeFinset_inj
theorem edgeFinset_subset_edgeFinset : G₁.edgeFinset ⊆ G₂.edgeFinset ↔ G₁ ≤ G₂ := by simp
#align simple_graph.edge_finset_subset_edge_finset SimpleGraph.edgeFinset_subset_edgeFinset
theorem edgeFinset_ssubset_edgeFinset : G₁.edgeFinset ⊂ G₂.edgeFinset ↔ G₁ < G₂ := by simp
#align simple_graph.edge_finset_ssubset_edge_finset SimpleGraph.edgeFinset_ssubset_edgeFinset
@[gcongr] alias ⟨_, edgeFinset_mono⟩ := edgeFinset_subset_edgeFinset
#align simple_graph.edge_finset_mono SimpleGraph.edgeFinset_mono
alias ⟨_, edgeFinset_strict_mono⟩ := edgeFinset_ssubset_edgeFinset
#align simple_graph.edge_finset_strict_mono SimpleGraph.edgeFinset_strict_mono
attribute [mono] edgeFinset_mono edgeFinset_strict_mono
@[simp]
theorem edgeFinset_bot : (⊥ : SimpleGraph V).edgeFinset = ∅ := by simp [edgeFinset]
#align simple_graph.edge_finset_bot SimpleGraph.edgeFinset_bot
@[simp]
theorem edgeFinset_sup [Fintype (edgeSet (G₁ ⊔ G₂))] [DecidableEq V] :
(G₁ ⊔ G₂).edgeFinset = G₁.edgeFinset ∪ G₂.edgeFinset := by simp [edgeFinset]
#align simple_graph.edge_finset_sup SimpleGraph.edgeFinset_sup
@[simp]
theorem edgeFinset_inf [DecidableEq V] : (G₁ ⊓ G₂).edgeFinset = G₁.edgeFinset ∩ G₂.edgeFinset := by
simp [edgeFinset]
#align simple_graph.edge_finset_inf SimpleGraph.edgeFinset_inf
@[simp]
theorem edgeFinset_sdiff [DecidableEq V] :
(G₁ \ G₂).edgeFinset = G₁.edgeFinset \ G₂.edgeFinset := by simp [edgeFinset]
#align simple_graph.edge_finset_sdiff SimpleGraph.edgeFinset_sdiff
theorem edgeFinset_card : G.edgeFinset.card = Fintype.card G.edgeSet :=
Set.toFinset_card _
#align simple_graph.edge_finset_card SimpleGraph.edgeFinset_card
@[simp]
theorem edgeSet_univ_card : (univ : Finset G.edgeSet).card = G.edgeFinset.card :=
Fintype.card_of_subtype G.edgeFinset fun _ => mem_edgeFinset
#align simple_graph.edge_set_univ_card SimpleGraph.edgeSet_univ_card
variable [Fintype V]
@[simp]
theorem edgeFinset_top [DecidableEq V] :
(⊤ : SimpleGraph V).edgeFinset = univ.filter fun e => ¬e.IsDiag := by
rw [← coe_inj]; simp
/-- The complete graph on `n` vertices has `n.choose 2` edges. -/
theorem card_edgeFinset_top_eq_card_choose_two [DecidableEq V] :
(⊤ : SimpleGraph V).edgeFinset.card = (Fintype.card V).choose 2 := by
simp_rw [Set.toFinset_card, edgeSet_top, Set.coe_setOf, ← Sym2.card_subtype_not_diag]
/-- Any graph on `n` vertices has at most `n.choose 2` edges. -/
theorem card_edgeFinset_le_card_choose_two : G.edgeFinset.card ≤ (Fintype.card V).choose 2 := by
classical
rw [← card_edgeFinset_top_eq_card_choose_two]
exact card_le_card (edgeFinset_mono le_top)
end EdgeFinset
theorem edgeFinset_deleteEdges [DecidableEq V] [Fintype G.edgeSet] (s : Finset (Sym2 V))
[Fintype (G.deleteEdges s).edgeSet] :
(G.deleteEdges s).edgeFinset = G.edgeFinset \ s := by
ext e
simp [edgeSet_deleteEdges]
#align simple_graph.edge_finset_delete_edges SimpleGraph.edgeFinset_deleteEdges
section DeleteFar
-- Porting note: added `Fintype (Sym2 V)` argument.
variable {𝕜 : Type*} [OrderedRing 𝕜] [Fintype V] [Fintype (Sym2 V)]
[Fintype G.edgeSet] {p : SimpleGraph V → Prop} {r r₁ r₂ : 𝕜}
/-- A graph is `r`-*delete-far* from a property `p` if we must delete at least `r` edges from it to
get a graph with the property `p`. -/
def DeleteFar (p : SimpleGraph V → Prop) (r : 𝕜) : Prop :=
∀ ⦃s⦄, s ⊆ G.edgeFinset → p (G.deleteEdges s) → r ≤ s.card
#align simple_graph.delete_far SimpleGraph.DeleteFar
variable {G}
theorem deleteFar_iff :
G.DeleteFar p r ↔ ∀ ⦃H : SimpleGraph _⦄ [DecidableRel H.Adj],
H ≤ G → p H → r ≤ G.edgeFinset.card - H.edgeFinset.card := by
classical
refine ⟨fun h H _ hHG hH ↦ ?_, fun h s hs hG ↦ ?_⟩
· have := h (sdiff_subset (t := H.edgeFinset))
simp only [deleteEdges_sdiff_eq_of_le hHG, edgeFinset_mono hHG, card_sdiff,
card_le_card, coe_sdiff, coe_edgeFinset, Nat.cast_sub] at this
exact this hH
· classical
simpa [card_sdiff hs, edgeFinset_deleteEdges, -Set.toFinset_card, Nat.cast_sub,
card_le_card hs] using h (G.deleteEdges_le s) hG
#align simple_graph.delete_far_iff SimpleGraph.deleteFar_iff
alias ⟨DeleteFar.le_card_sub_card, _⟩ := deleteFar_iff
#align simple_graph.delete_far.le_card_sub_card SimpleGraph.DeleteFar.le_card_sub_card
theorem DeleteFar.mono (h : G.DeleteFar p r₂) (hr : r₁ ≤ r₂) : G.DeleteFar p r₁ := fun _ hs hG =>
hr.trans <| h hs hG
#align simple_graph.delete_far.mono SimpleGraph.DeleteFar.mono
end DeleteFar
section FiniteAt
/-!
## Finiteness at a vertex
This section contains definitions and lemmas concerning vertices that
have finitely many adjacent vertices. We denote this condition by
`Fintype (G.neighborSet v)`.
We define `G.neighborFinset v` to be the `Finset` version of `G.neighborSet v`.
Use `neighborFinset_eq_filter` to rewrite this definition as a `Finset.filter` expression.
-/
variable (v) [Fintype (G.neighborSet v)]
/-- `G.neighbors v` is the `Finset` version of `G.Adj v` in case `G` is
locally finite at `v`. -/
def neighborFinset : Finset V :=
(G.neighborSet v).toFinset
#align simple_graph.neighbor_finset SimpleGraph.neighborFinset
theorem neighborFinset_def : G.neighborFinset v = (G.neighborSet v).toFinset :=
rfl
#align simple_graph.neighbor_finset_def SimpleGraph.neighborFinset_def
@[simp]
theorem mem_neighborFinset (w : V) : w ∈ G.neighborFinset v ↔ G.Adj v w :=
Set.mem_toFinset
#align simple_graph.mem_neighbor_finset SimpleGraph.mem_neighborFinset
theorem not_mem_neighborFinset_self : v ∉ G.neighborFinset v := by simp
#align simple_graph.not_mem_neighbor_finset_self SimpleGraph.not_mem_neighborFinset_self
theorem neighborFinset_disjoint_singleton : Disjoint (G.neighborFinset v) {v} :=
Finset.disjoint_singleton_right.mpr <| not_mem_neighborFinset_self _ _
#align simple_graph.neighbor_finset_disjoint_singleton SimpleGraph.neighborFinset_disjoint_singleton
theorem singleton_disjoint_neighborFinset : Disjoint {v} (G.neighborFinset v) :=
Finset.disjoint_singleton_left.mpr <| not_mem_neighborFinset_self _ _
#align simple_graph.singleton_disjoint_neighbor_finset SimpleGraph.singleton_disjoint_neighborFinset
/-- `G.degree v` is the number of vertices adjacent to `v`. -/
def degree : ℕ :=
(G.neighborFinset v).card
#align simple_graph.degree SimpleGraph.degree
-- Porting note: in Lean 3 we could do `simp [← degree]`, but that gives
-- "invalid '←' modifier, 'SimpleGraph.degree' is a declaration name to be unfolded".
-- In any case, having this lemma is good since there's no guarantee we won't still change
-- the definition of `degree`.
@[simp]
theorem card_neighborFinset_eq_degree : (G.neighborFinset v).card = G.degree v := rfl
@[simp]
theorem card_neighborSet_eq_degree : Fintype.card (G.neighborSet v) = G.degree v :=
(Set.toFinset_card _).symm
#align simple_graph.card_neighbor_set_eq_degree SimpleGraph.card_neighborSet_eq_degree
theorem degree_pos_iff_exists_adj : 0 < G.degree v ↔ ∃ w, G.Adj v w := by
simp only [degree, card_pos, Finset.Nonempty, mem_neighborFinset]
#align simple_graph.degree_pos_iff_exists_adj SimpleGraph.degree_pos_iff_exists_adj
theorem degree_compl [Fintype (Gᶜ.neighborSet v)] [Fintype V] :
Gᶜ.degree v = Fintype.card V - 1 - G.degree v := by
classical
rw [← card_neighborSet_union_compl_neighborSet G v, Set.toFinset_union]
simp [card_union_of_disjoint (Set.disjoint_toFinset.mpr (compl_neighborSet_disjoint G v))]
#align simple_graph.degree_compl SimpleGraph.degree_compl
instance incidenceSetFintype [DecidableEq V] : Fintype (G.incidenceSet v) :=
Fintype.ofEquiv (G.neighborSet v) (G.incidenceSetEquivNeighborSet v).symm
#align simple_graph.incidence_set_fintype SimpleGraph.incidenceSetFintype
/-- This is the `Finset` version of `incidenceSet`. -/
def incidenceFinset [DecidableEq V] : Finset (Sym2 V) :=
(G.incidenceSet v).toFinset
#align simple_graph.incidence_finset SimpleGraph.incidenceFinset
@[simp]
| Mathlib/Combinatorics/SimpleGraph/Finite.lean | 260 | 263 | theorem card_incidenceSet_eq_degree [DecidableEq V] :
Fintype.card (G.incidenceSet v) = G.degree v := by |
rw [Fintype.card_congr (G.incidenceSetEquivNeighborSet v)]
simp
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.DirectSum.Module
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Convex.Uniform
import Mathlib.Analysis.NormedSpace.Completion
import Mathlib.Analysis.NormedSpace.BoundedLinearMaps
#align_import analysis.inner_product_space.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Inner product space
This file defines inner product spaces and proves the basic properties. We do not formally
define Hilbert spaces, but they can be obtained using the set of assumptions
`[NormedAddCommGroup E] [InnerProductSpace 𝕜 E] [CompleteSpace E]`.
An inner product space is a vector space endowed with an inner product. It generalizes the notion of
dot product in `ℝ^n` and provides the means of defining the length of a vector and the angle between
two vectors. In particular vectors `x` and `y` are orthogonal if their inner product equals zero.
We define both the real and complex cases at the same time using the `RCLike` typeclass.
This file proves general results on inner product spaces. For the specific construction of an inner
product structure on `n → 𝕜` for `𝕜 = ℝ` or `ℂ`, see `EuclideanSpace` in
`Analysis.InnerProductSpace.PiL2`.
## Main results
- We define the class `InnerProductSpace 𝕜 E` extending `NormedSpace 𝕜 E` with a number of basic
properties, most notably the Cauchy-Schwarz inequality. Here `𝕜` is understood to be either `ℝ`
or `ℂ`, through the `RCLike` typeclass.
- We show that the inner product is continuous, `continuous_inner`, and bundle it as the
continuous sesquilinear map `innerSL` (see also `innerₛₗ` for the non-continuous version).
- We define `Orthonormal`, a predicate on a function `v : ι → E`, and prove the existence of a
maximal orthonormal set, `exists_maximal_orthonormal`. Bessel's inequality,
`Orthonormal.tsum_inner_products_le`, states that given an orthonormal set `v` and a vector `x`,
the sum of the norm-squares of the inner products `⟪v i, x⟫` is no more than the norm-square of
`x`. For the existence of orthonormal bases, Hilbert bases, etc., see the file
`Analysis.InnerProductSpace.projection`.
## Notation
We globally denote the real and complex inner products by `⟪·, ·⟫_ℝ` and `⟪·, ·⟫_ℂ` respectively.
We also provide two notation namespaces: `RealInnerProductSpace`, `ComplexInnerProductSpace`,
which respectively introduce the plain notation `⟪·, ·⟫` for the real and complex inner product.
## Implementation notes
We choose the convention that inner products are conjugate linear in the first argument and linear
in the second.
## Tags
inner product space, Hilbert space, norm
## References
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open RCLike Real Filter
open Topology ComplexConjugate
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
/-- Syntactic typeclass for types endowed with an inner product -/
class Inner (𝕜 E : Type*) where
/-- The inner product function. -/
inner : E → E → 𝕜
#align has_inner Inner
export Inner (inner)
/-- The inner product with values in `𝕜`. -/
notation3:max "⟪" x ", " y "⟫_" 𝕜:max => @inner 𝕜 _ _ x y
section Notations
/-- The inner product with values in `ℝ`. -/
scoped[RealInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℝ _ _ x y
/-- The inner product with values in `ℂ`. -/
scoped[ComplexInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℂ _ _ x y
end Notations
/-- An inner product space is a vector space with an additional operation called inner product.
The norm could be derived from the inner product, instead we require the existence of a norm and
the fact that `‖x‖^2 = re ⟪x, x⟫` to be able to put instances on `𝕂` or product
spaces.
To construct a norm from an inner product, see `InnerProductSpace.ofCore`.
-/
class InnerProductSpace (𝕜 : Type*) (E : Type*) [RCLike 𝕜] [NormedAddCommGroup E] extends
NormedSpace 𝕜 E, Inner 𝕜 E where
/-- The inner product induces the norm. -/
norm_sq_eq_inner : ∀ x : E, ‖x‖ ^ 2 = re (inner x x)
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space InnerProductSpace
/-!
### Constructing a normed space structure from an inner product
In the definition of an inner product space, we require the existence of a norm, which is equal
(but maybe not defeq) to the square root of the scalar product. This makes it possible to put
an inner product space structure on spaces with a preexisting norm (for instance `ℝ`), with good
properties. However, sometimes, one would like to define the norm starting only from a well-behaved
scalar product. This is what we implement in this paragraph, starting from a structure
`InnerProductSpace.Core` stating that we have a nice scalar product.
Our goal here is not to develop a whole theory with all the supporting API, as this will be done
below for `InnerProductSpace`. Instead, we implement the bare minimum to go as directly as
possible to the construction of the norm and the proof of the triangular inequality.
Warning: Do not use this `Core` structure if the space you are interested in already has a norm
instance defined on it, otherwise this will create a second non-defeq norm instance!
-/
/-- A structure requiring that a scalar product is positive definite and symmetric, from which one
can construct an `InnerProductSpace` instance in `InnerProductSpace.ofCore`. -/
-- @[nolint HasNonemptyInstance] porting note: I don't think we have this linter anymore
structure InnerProductSpace.Core (𝕜 : Type*) (F : Type*) [RCLike 𝕜] [AddCommGroup F]
[Module 𝕜 F] extends Inner 𝕜 F where
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is positive (semi)definite. -/
nonneg_re : ∀ x, 0 ≤ re (inner x x)
/-- The inner product is positive definite. -/
definite : ∀ x, inner x x = 0 → x = 0
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space.core InnerProductSpace.Core
/- We set `InnerProductSpace.Core` to be a class as we will use it as such in the construction
of the normed space structure that it produces. However, all the instances we will use will be
local to this proof. -/
attribute [class] InnerProductSpace.Core
/-- Define `InnerProductSpace.Core` from `InnerProductSpace`. Defined to reuse lemmas about
`InnerProductSpace.Core` for `InnerProductSpace`s. Note that the `Norm` instance provided by
`InnerProductSpace.Core.norm` is propositionally but not definitionally equal to the original
norm. -/
def InnerProductSpace.toCore [NormedAddCommGroup E] [c : InnerProductSpace 𝕜 E] :
InnerProductSpace.Core 𝕜 E :=
{ c with
nonneg_re := fun x => by
rw [← InnerProductSpace.norm_sq_eq_inner]
apply sq_nonneg
definite := fun x hx =>
norm_eq_zero.1 <| pow_eq_zero (n := 2) <| by
rw [InnerProductSpace.norm_sq_eq_inner (𝕜 := 𝕜) x, hx, map_zero] }
#align inner_product_space.to_core InnerProductSpace.toCore
namespace InnerProductSpace.Core
variable [AddCommGroup F] [Module 𝕜 F] [c : InnerProductSpace.Core 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 F _ x y
local notation "normSqK" => @RCLike.normSq 𝕜 _
local notation "reK" => @RCLike.re 𝕜 _
local notation "ext_iff" => @RCLike.ext_iff 𝕜 _
local postfix:90 "†" => starRingEnd _
/-- Inner product defined by the `InnerProductSpace.Core` structure. We can't reuse
`InnerProductSpace.Core.toInner` because it takes `InnerProductSpace.Core` as an explicit
argument. -/
def toInner' : Inner 𝕜 F :=
c.toInner
#align inner_product_space.core.to_has_inner' InnerProductSpace.Core.toInner'
attribute [local instance] toInner'
/-- The norm squared function for `InnerProductSpace.Core` structure. -/
def normSq (x : F) :=
reK ⟪x, x⟫
#align inner_product_space.core.norm_sq InnerProductSpace.Core.normSq
local notation "normSqF" => @normSq 𝕜 F _ _ _ _
theorem inner_conj_symm (x y : F) : ⟪y, x⟫† = ⟪x, y⟫ :=
c.conj_symm x y
#align inner_product_space.core.inner_conj_symm InnerProductSpace.Core.inner_conj_symm
theorem inner_self_nonneg {x : F} : 0 ≤ re ⟪x, x⟫ :=
c.nonneg_re _
#align inner_product_space.core.inner_self_nonneg InnerProductSpace.Core.inner_self_nonneg
theorem inner_self_im (x : F) : im ⟪x, x⟫ = 0 := by
rw [← @ofReal_inj 𝕜, im_eq_conj_sub]
simp [inner_conj_symm]
#align inner_product_space.core.inner_self_im InnerProductSpace.Core.inner_self_im
theorem inner_add_left (x y z : F) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
c.add_left _ _ _
#align inner_product_space.core.inner_add_left InnerProductSpace.Core.inner_add_left
theorem inner_add_right (x y z : F) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]; simp only [inner_conj_symm]
#align inner_product_space.core.inner_add_right InnerProductSpace.Core.inner_add_right
theorem ofReal_normSq_eq_inner_self (x : F) : (normSqF x : 𝕜) = ⟪x, x⟫ := by
rw [ext_iff]
exact ⟨by simp only [ofReal_re]; rfl, by simp only [inner_self_im, ofReal_im]⟩
#align inner_product_space.core.coe_norm_sq_eq_inner_self InnerProductSpace.Core.ofReal_normSq_eq_inner_self
theorem inner_re_symm (x y : F) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_product_space.core.inner_re_symm InnerProductSpace.Core.inner_re_symm
theorem inner_im_symm (x y : F) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_product_space.core.inner_im_symm InnerProductSpace.Core.inner_im_symm
theorem inner_smul_left (x y : F) {r : 𝕜} : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
c.smul_left _ _ _
#align inner_product_space.core.inner_smul_left InnerProductSpace.Core.inner_smul_left
theorem inner_smul_right (x y : F) {r : 𝕜} : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left];
simp only [conj_conj, inner_conj_symm, RingHom.map_mul]
#align inner_product_space.core.inner_smul_right InnerProductSpace.Core.inner_smul_right
theorem inner_zero_left (x : F) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : F), inner_smul_left];
simp only [zero_mul, RingHom.map_zero]
#align inner_product_space.core.inner_zero_left InnerProductSpace.Core.inner_zero_left
theorem inner_zero_right (x : F) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left]; simp only [RingHom.map_zero]
#align inner_product_space.core.inner_zero_right InnerProductSpace.Core.inner_zero_right
theorem inner_self_eq_zero {x : F} : ⟪x, x⟫ = 0 ↔ x = 0 :=
⟨c.definite _, by
rintro rfl
exact inner_zero_left _⟩
#align inner_product_space.core.inner_self_eq_zero InnerProductSpace.Core.inner_self_eq_zero
theorem normSq_eq_zero {x : F} : normSqF x = 0 ↔ x = 0 :=
Iff.trans
(by simp only [normSq, ext_iff, map_zero, inner_self_im, eq_self_iff_true, and_true_iff])
(@inner_self_eq_zero 𝕜 _ _ _ _ _ x)
#align inner_product_space.core.norm_sq_eq_zero InnerProductSpace.Core.normSq_eq_zero
theorem inner_self_ne_zero {x : F} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_product_space.core.inner_self_ne_zero InnerProductSpace.Core.inner_self_ne_zero
theorem inner_self_ofReal_re (x : F) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ := by
norm_num [ext_iff, inner_self_im]
set_option linter.uppercaseLean3 false in
#align inner_product_space.core.inner_self_re_to_K InnerProductSpace.Core.inner_self_ofReal_re
theorem norm_inner_symm (x y : F) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align inner_product_space.core.norm_inner_symm InnerProductSpace.Core.norm_inner_symm
theorem inner_neg_left (x y : F) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_product_space.core.inner_neg_left InnerProductSpace.Core.inner_neg_left
theorem inner_neg_right (x y : F) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_product_space.core.inner_neg_right InnerProductSpace.Core.inner_neg_right
theorem inner_sub_left (x y z : F) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left, inner_neg_left]
#align inner_product_space.core.inner_sub_left InnerProductSpace.Core.inner_sub_left
theorem inner_sub_right (x y z : F) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right, inner_neg_right]
#align inner_product_space.core.inner_sub_right InnerProductSpace.Core.inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : F) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_product_space.core.inner_mul_symm_re_eq_norm InnerProductSpace.Core.inner_mul_symm_re_eq_norm
/-- Expand `inner (x + y) (x + y)` -/
theorem inner_add_add_self (x y : F) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_product_space.core.inner_add_add_self InnerProductSpace.Core.inner_add_add_self
-- Expand `inner (x - y) (x - y)`
theorem inner_sub_sub_self (x y : F) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_product_space.core.inner_sub_sub_self InnerProductSpace.Core.inner_sub_sub_self
/-- An auxiliary equality useful to prove the **Cauchy–Schwarz inequality**: the square of the norm
of `⟪x, y⟫ • x - ⟪x, x⟫ • y` is equal to `‖x‖ ^ 2 * (‖x‖ ^ 2 * ‖y‖ ^ 2 - ‖⟪x, y⟫‖ ^ 2)`. We use
`InnerProductSpace.ofCore.normSq x` etc (defeq to `is_R_or_C.re ⟪x, x⟫`) instead of `‖x‖ ^ 2`
etc to avoid extra rewrites when applying it to an `InnerProductSpace`. -/
theorem cauchy_schwarz_aux (x y : F) :
normSqF (⟪x, y⟫ • x - ⟪x, x⟫ • y) = normSqF x * (normSqF x * normSqF y - ‖⟪x, y⟫‖ ^ 2) := by
rw [← @ofReal_inj 𝕜, ofReal_normSq_eq_inner_self]
simp only [inner_sub_sub_self, inner_smul_left, inner_smul_right, conj_ofReal, mul_sub, ←
ofReal_normSq_eq_inner_self x, ← ofReal_normSq_eq_inner_self y]
rw [← mul_assoc, mul_conj, RCLike.conj_mul, mul_left_comm, ← inner_conj_symm y, mul_conj]
push_cast
ring
#align inner_product_space.core.cauchy_schwarz_aux InnerProductSpace.Core.cauchy_schwarz_aux
/-- **Cauchy–Schwarz inequality**.
We need this for the `Core` structure to prove the triangle inequality below when
showing the core is a normed group.
-/
theorem inner_mul_inner_self_le (x y : F) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := by
rcases eq_or_ne x 0 with (rfl | hx)
· simpa only [inner_zero_left, map_zero, zero_mul, norm_zero] using le_rfl
· have hx' : 0 < normSqF x := inner_self_nonneg.lt_of_ne' (mt normSq_eq_zero.1 hx)
rw [← sub_nonneg, ← mul_nonneg_iff_right_nonneg_of_pos hx', ← normSq, ← normSq,
norm_inner_symm y, ← sq, ← cauchy_schwarz_aux]
exact inner_self_nonneg
#align inner_product_space.core.inner_mul_inner_self_le InnerProductSpace.Core.inner_mul_inner_self_le
/-- Norm constructed from an `InnerProductSpace.Core` structure, defined to be the square root
of the scalar product. -/
def toNorm : Norm F where norm x := √(re ⟪x, x⟫)
#align inner_product_space.core.to_has_norm InnerProductSpace.Core.toNorm
attribute [local instance] toNorm
theorem norm_eq_sqrt_inner (x : F) : ‖x‖ = √(re ⟪x, x⟫) := rfl
#align inner_product_space.core.norm_eq_sqrt_inner InnerProductSpace.Core.norm_eq_sqrt_inner
theorem inner_self_eq_norm_mul_norm (x : F) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [norm_eq_sqrt_inner, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫), sqrt_mul_self inner_self_nonneg]
#align inner_product_space.core.inner_self_eq_norm_mul_norm InnerProductSpace.Core.inner_self_eq_norm_mul_norm
theorem sqrt_normSq_eq_norm (x : F) : √(normSqF x) = ‖x‖ := rfl
#align inner_product_space.core.sqrt_norm_sq_eq_norm InnerProductSpace.Core.sqrt_normSq_eq_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : F) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ :=
nonneg_le_nonneg_of_sq_le_sq (mul_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) <|
calc
‖⟪x, y⟫‖ * ‖⟪x, y⟫‖ = ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ := by rw [norm_inner_symm]
_ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := inner_mul_inner_self_le x y
_ = ‖x‖ * ‖y‖ * (‖x‖ * ‖y‖) := by simp only [inner_self_eq_norm_mul_norm]; ring
#align inner_product_space.core.norm_inner_le_norm InnerProductSpace.Core.norm_inner_le_norm
/-- Normed group structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedAddCommGroup : NormedAddCommGroup F :=
AddGroupNorm.toNormedAddCommGroup
{ toFun := fun x => √(re ⟪x, x⟫)
map_zero' := by simp only [sqrt_zero, inner_zero_right, map_zero]
neg' := fun x => by simp only [inner_neg_left, neg_neg, inner_neg_right]
add_le' := fun x y => by
have h₁ : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := norm_inner_le_norm _ _
have h₂ : re ⟪x, y⟫ ≤ ‖⟪x, y⟫‖ := re_le_norm _
have h₃ : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ := h₂.trans h₁
have h₄ : re ⟪y, x⟫ ≤ ‖x‖ * ‖y‖ := by rwa [← inner_conj_symm, conj_re]
have : ‖x + y‖ * ‖x + y‖ ≤ (‖x‖ + ‖y‖) * (‖x‖ + ‖y‖) := by
simp only [← inner_self_eq_norm_mul_norm, inner_add_add_self, mul_add, mul_comm, map_add]
linarith
exact nonneg_le_nonneg_of_sq_le_sq (add_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) this
eq_zero_of_map_eq_zero' := fun x hx =>
normSq_eq_zero.1 <| (sqrt_eq_zero inner_self_nonneg).1 hx }
#align inner_product_space.core.to_normed_add_comm_group InnerProductSpace.Core.toNormedAddCommGroup
attribute [local instance] toNormedAddCommGroup
/-- Normed space structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedSpace : NormedSpace 𝕜 F where
norm_smul_le r x := by
rw [norm_eq_sqrt_inner, inner_smul_left, inner_smul_right, ← mul_assoc]
rw [RCLike.conj_mul, ← ofReal_pow, re_ofReal_mul, sqrt_mul, ← ofReal_normSq_eq_inner_self,
ofReal_re]
· simp [sqrt_normSq_eq_norm, RCLike.sqrt_normSq_eq_norm]
· positivity
#align inner_product_space.core.to_normed_space InnerProductSpace.Core.toNormedSpace
end InnerProductSpace.Core
section
attribute [local instance] InnerProductSpace.Core.toNormedAddCommGroup
/-- Given an `InnerProductSpace.Core` structure on a space, one can use it to turn
the space into an inner product space. The `NormedAddCommGroup` structure is expected
to already be defined with `InnerProductSpace.ofCore.toNormedAddCommGroup`. -/
def InnerProductSpace.ofCore [AddCommGroup F] [Module 𝕜 F] (c : InnerProductSpace.Core 𝕜 F) :
InnerProductSpace 𝕜 F :=
letI : NormedSpace 𝕜 F := @InnerProductSpace.Core.toNormedSpace 𝕜 F _ _ _ c
{ c with
norm_sq_eq_inner := fun x => by
have h₁ : ‖x‖ ^ 2 = √(re (c.inner x x)) ^ 2 := rfl
have h₂ : 0 ≤ re (c.inner x x) := InnerProductSpace.Core.inner_self_nonneg
simp [h₁, sq_sqrt, h₂] }
#align inner_product_space.of_core InnerProductSpace.ofCore
end
/-! ### Properties of inner product spaces -/
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "IK" => @RCLike.I 𝕜 _
local postfix:90 "†" => starRingEnd _
export InnerProductSpace (norm_sq_eq_inner)
section BasicProperties
@[simp]
theorem inner_conj_symm (x y : E) : ⟪y, x⟫† = ⟪x, y⟫ :=
InnerProductSpace.conj_symm _ _
#align inner_conj_symm inner_conj_symm
theorem real_inner_comm (x y : F) : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ :=
@inner_conj_symm ℝ _ _ _ _ x y
#align real_inner_comm real_inner_comm
theorem inner_eq_zero_symm {x y : E} : ⟪x, y⟫ = 0 ↔ ⟪y, x⟫ = 0 := by
rw [← inner_conj_symm]
exact star_eq_zero
#align inner_eq_zero_symm inner_eq_zero_symm
@[simp]
theorem inner_self_im (x : E) : im ⟪x, x⟫ = 0 := by rw [← @ofReal_inj 𝕜, im_eq_conj_sub]; simp
#align inner_self_im inner_self_im
theorem inner_add_left (x y z : E) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
InnerProductSpace.add_left _ _ _
#align inner_add_left inner_add_left
theorem inner_add_right (x y z : E) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]
simp only [inner_conj_symm]
#align inner_add_right inner_add_right
theorem inner_re_symm (x y : E) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_re_symm inner_re_symm
theorem inner_im_symm (x y : E) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_im_symm inner_im_symm
theorem inner_smul_left (x y : E) (r : 𝕜) : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
InnerProductSpace.smul_left _ _ _
#align inner_smul_left inner_smul_left
theorem real_inner_smul_left (x y : F) (r : ℝ) : ⟪r • x, y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_left _ _ _
#align real_inner_smul_left real_inner_smul_left
theorem inner_smul_real_left (x y : E) (r : ℝ) : ⟪(r : 𝕜) • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left, conj_ofReal, Algebra.smul_def]
rfl
#align inner_smul_real_left inner_smul_real_left
theorem inner_smul_right (x y : E) (r : 𝕜) : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left, RingHom.map_mul, conj_conj, inner_conj_symm]
#align inner_smul_right inner_smul_right
theorem real_inner_smul_right (x y : F) (r : ℝ) : ⟪x, r • y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_right _ _ _
#align real_inner_smul_right real_inner_smul_right
theorem inner_smul_real_right (x y : E) (r : ℝ) : ⟪x, (r : 𝕜) • y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_right, Algebra.smul_def]
rfl
#align inner_smul_real_right inner_smul_real_right
/-- The inner product as a sesquilinear form.
Note that in the case `𝕜 = ℝ` this is a bilinear form. -/
@[simps!]
def sesqFormOfInner : E →ₗ[𝕜] E →ₗ⋆[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ (RingHom.id 𝕜) (starRingEnd _) (fun x y => ⟪y, x⟫)
(fun _x _y _z => inner_add_right _ _ _) (fun _r _x _y => inner_smul_right _ _ _)
(fun _x _y _z => inner_add_left _ _ _) fun _r _x _y => inner_smul_left _ _ _
#align sesq_form_of_inner sesqFormOfInner
/-- The real inner product as a bilinear form.
Note that unlike `sesqFormOfInner`, this does not reverse the order of the arguments. -/
@[simps!]
def bilinFormOfRealInner : BilinForm ℝ F := sesqFormOfInner.flip
#align bilin_form_of_real_inner bilinFormOfRealInner
/-- An inner product with a sum on the left. -/
theorem sum_inner {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪∑ i ∈ s, f i, x⟫ = ∑ i ∈ s, ⟪f i, x⟫ :=
map_sum (sesqFormOfInner (𝕜 := 𝕜) (E := E) x) _ _
#align sum_inner sum_inner
/-- An inner product with a sum on the right. -/
theorem inner_sum {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪x, ∑ i ∈ s, f i⟫ = ∑ i ∈ s, ⟪x, f i⟫ :=
map_sum (LinearMap.flip sesqFormOfInner x) _ _
#align inner_sum inner_sum
/-- An inner product with a sum on the left, `Finsupp` version. -/
theorem Finsupp.sum_inner {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪l.sum fun (i : ι) (a : 𝕜) => a • v i, x⟫ = l.sum fun (i : ι) (a : 𝕜) => conj a • ⟪v i, x⟫ := by
convert _root_.sum_inner (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_left, Finsupp.sum, smul_eq_mul]
#align finsupp.sum_inner Finsupp.sum_inner
/-- An inner product with a sum on the right, `Finsupp` version. -/
theorem Finsupp.inner_sum {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪x, l.sum fun (i : ι) (a : 𝕜) => a • v i⟫ = l.sum fun (i : ι) (a : 𝕜) => a • ⟪x, v i⟫ := by
convert _root_.inner_sum (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_right, Finsupp.sum, smul_eq_mul]
#align finsupp.inner_sum Finsupp.inner_sum
theorem DFinsupp.sum_inner {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪l.sum f, x⟫ = l.sum fun i a => ⟪f i a, x⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.sum_inner, smul_eq_mul]
#align dfinsupp.sum_inner DFinsupp.sum_inner
theorem DFinsupp.inner_sum {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪x, l.sum f⟫ = l.sum fun i a => ⟪x, f i a⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.inner_sum, smul_eq_mul]
#align dfinsupp.inner_sum DFinsupp.inner_sum
@[simp]
theorem inner_zero_left (x : E) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : E), inner_smul_left, RingHom.map_zero, zero_mul]
#align inner_zero_left inner_zero_left
theorem inner_re_zero_left (x : E) : re ⟪0, x⟫ = 0 := by
simp only [inner_zero_left, AddMonoidHom.map_zero]
#align inner_re_zero_left inner_re_zero_left
@[simp]
theorem inner_zero_right (x : E) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left, RingHom.map_zero]
#align inner_zero_right inner_zero_right
theorem inner_re_zero_right (x : E) : re ⟪x, 0⟫ = 0 := by
simp only [inner_zero_right, AddMonoidHom.map_zero]
#align inner_re_zero_right inner_re_zero_right
theorem inner_self_nonneg {x : E} : 0 ≤ re ⟪x, x⟫ :=
InnerProductSpace.toCore.nonneg_re x
#align inner_self_nonneg inner_self_nonneg
theorem real_inner_self_nonneg {x : F} : 0 ≤ ⟪x, x⟫_ℝ :=
@inner_self_nonneg ℝ F _ _ _ x
#align real_inner_self_nonneg real_inner_self_nonneg
@[simp]
theorem inner_self_ofReal_re (x : E) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ :=
((RCLike.is_real_TFAE (⟪x, x⟫ : 𝕜)).out 2 3).2 (inner_self_im _)
set_option linter.uppercaseLean3 false in
#align inner_self_re_to_K inner_self_ofReal_re
theorem inner_self_eq_norm_sq_to_K (x : E) : ⟪x, x⟫ = (‖x‖ : 𝕜) ^ 2 := by
rw [← inner_self_ofReal_re, ← norm_sq_eq_inner, ofReal_pow]
set_option linter.uppercaseLean3 false in
#align inner_self_eq_norm_sq_to_K inner_self_eq_norm_sq_to_K
theorem inner_self_re_eq_norm (x : E) : re ⟪x, x⟫ = ‖⟪x, x⟫‖ := by
conv_rhs => rw [← inner_self_ofReal_re]
symm
exact norm_of_nonneg inner_self_nonneg
#align inner_self_re_eq_norm inner_self_re_eq_norm
theorem inner_self_ofReal_norm (x : E) : (‖⟪x, x⟫‖ : 𝕜) = ⟪x, x⟫ := by
rw [← inner_self_re_eq_norm]
exact inner_self_ofReal_re _
set_option linter.uppercaseLean3 false in
#align inner_self_norm_to_K inner_self_ofReal_norm
theorem real_inner_self_abs (x : F) : |⟪x, x⟫_ℝ| = ⟪x, x⟫_ℝ :=
@inner_self_ofReal_norm ℝ F _ _ _ x
#align real_inner_self_abs real_inner_self_abs
@[simp]
theorem inner_self_eq_zero {x : E} : ⟪x, x⟫ = 0 ↔ x = 0 := by
rw [inner_self_eq_norm_sq_to_K, sq_eq_zero_iff, ofReal_eq_zero, norm_eq_zero]
#align inner_self_eq_zero inner_self_eq_zero
theorem inner_self_ne_zero {x : E} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_self_ne_zero inner_self_ne_zero
@[simp]
theorem inner_self_nonpos {x : E} : re ⟪x, x⟫ ≤ 0 ↔ x = 0 := by
rw [← norm_sq_eq_inner, (sq_nonneg _).le_iff_eq, sq_eq_zero_iff, norm_eq_zero]
#align inner_self_nonpos inner_self_nonpos
theorem real_inner_self_nonpos {x : F} : ⟪x, x⟫_ℝ ≤ 0 ↔ x = 0 :=
@inner_self_nonpos ℝ F _ _ _ x
#align real_inner_self_nonpos real_inner_self_nonpos
theorem norm_inner_symm (x y : E) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align norm_inner_symm norm_inner_symm
@[simp]
theorem inner_neg_left (x y : E) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_neg_left inner_neg_left
@[simp]
theorem inner_neg_right (x y : E) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_neg_right inner_neg_right
theorem inner_neg_neg (x y : E) : ⟪-x, -y⟫ = ⟪x, y⟫ := by simp
#align inner_neg_neg inner_neg_neg
-- Porting note: removed `simp` because it can prove it using `inner_conj_symm`
theorem inner_self_conj (x : E) : ⟪x, x⟫† = ⟪x, x⟫ := inner_conj_symm _ _
#align inner_self_conj inner_self_conj
theorem inner_sub_left (x y z : E) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left]
#align inner_sub_left inner_sub_left
theorem inner_sub_right (x y z : E) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right]
#align inner_sub_right inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : E) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_mul_symm_re_eq_norm inner_mul_symm_re_eq_norm
/-- Expand `⟪x + y, x + y⟫` -/
theorem inner_add_add_self (x y : E) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_add_add_self inner_add_add_self
/-- Expand `⟪x + y, x + y⟫_ℝ` -/
theorem real_inner_add_add_self (x y : F) :
⟪x + y, x + y⟫_ℝ = ⟪x, x⟫_ℝ + 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_add_add_self, this, add_left_inj]
ring
#align real_inner_add_add_self real_inner_add_add_self
-- Expand `⟪x - y, x - y⟫`
theorem inner_sub_sub_self (x y : E) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_sub_sub_self inner_sub_sub_self
/-- Expand `⟪x - y, x - y⟫_ℝ` -/
theorem real_inner_sub_sub_self (x y : F) :
⟪x - y, x - y⟫_ℝ = ⟪x, x⟫_ℝ - 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_sub_sub_self, this, add_left_inj]
ring
#align real_inner_sub_sub_self real_inner_sub_sub_self
variable (𝕜)
theorem ext_inner_left {x y : E} (h : ∀ v, ⟪v, x⟫ = ⟪v, y⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_right, sub_eq_zero, h (x - y)]
#align ext_inner_left ext_inner_left
theorem ext_inner_right {x y : E} (h : ∀ v, ⟪x, v⟫ = ⟪y, v⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_left, sub_eq_zero, h (x - y)]
#align ext_inner_right ext_inner_right
variable {𝕜}
/-- Parallelogram law -/
theorem parallelogram_law {x y : E} : ⟪x + y, x + y⟫ + ⟪x - y, x - y⟫ = 2 * (⟪x, x⟫ + ⟪y, y⟫) := by
simp only [inner_add_add_self, inner_sub_sub_self]
ring
#align parallelogram_law parallelogram_law
/-- **Cauchy–Schwarz inequality**. -/
theorem inner_mul_inner_self_le (x y : E) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ :=
letI c : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
InnerProductSpace.Core.inner_mul_inner_self_le x y
#align inner_mul_inner_self_le inner_mul_inner_self_le
/-- Cauchy–Schwarz inequality for real inner products. -/
theorem real_inner_mul_inner_self_le (x y : F) : ⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ :=
calc
⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ‖⟪x, y⟫_ℝ‖ * ‖⟪y, x⟫_ℝ‖ := by
rw [real_inner_comm y, ← norm_mul]
exact le_abs_self _
_ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ := @inner_mul_inner_self_le ℝ _ _ _ _ x y
#align real_inner_mul_inner_self_le real_inner_mul_inner_self_le
/-- A family of vectors is linearly independent if they are nonzero
and orthogonal. -/
theorem linearIndependent_of_ne_zero_of_inner_eq_zero {ι : Type*} {v : ι → E} (hz : ∀ i, v i ≠ 0)
(ho : Pairwise fun i j => ⟪v i, v j⟫ = 0) : LinearIndependent 𝕜 v := by
rw [linearIndependent_iff']
intro s g hg i hi
have h' : g i * inner (v i) (v i) = inner (v i) (∑ j ∈ s, g j • v j) := by
rw [inner_sum]
symm
convert Finset.sum_eq_single (β := 𝕜) i ?_ ?_
· rw [inner_smul_right]
· intro j _hj hji
rw [inner_smul_right, ho hji.symm, mul_zero]
· exact fun h => False.elim (h hi)
simpa [hg, hz] using h'
#align linear_independent_of_ne_zero_of_inner_eq_zero linearIndependent_of_ne_zero_of_inner_eq_zero
end BasicProperties
section OrthonormalSets
variable {ι : Type*} (𝕜)
/-- An orthonormal set of vectors in an `InnerProductSpace` -/
def Orthonormal (v : ι → E) : Prop :=
(∀ i, ‖v i‖ = 1) ∧ Pairwise fun i j => ⟪v i, v j⟫ = 0
#align orthonormal Orthonormal
variable {𝕜}
/-- `if ... then ... else` characterization of an indexed set of vectors being orthonormal. (Inner
product equals Kronecker delta.) -/
theorem orthonormal_iff_ite [DecidableEq ι] {v : ι → E} :
Orthonormal 𝕜 v ↔ ∀ i j, ⟪v i, v j⟫ = if i = j then (1 : 𝕜) else (0 : 𝕜) := by
constructor
· intro hv i j
split_ifs with h
· simp [h, inner_self_eq_norm_sq_to_K, hv.1]
· exact hv.2 h
· intro h
constructor
· intro i
have h' : ‖v i‖ ^ 2 = 1 ^ 2 := by simp [@norm_sq_eq_inner 𝕜, h i i]
have h₁ : 0 ≤ ‖v i‖ := norm_nonneg _
have h₂ : (0 : ℝ) ≤ 1 := zero_le_one
rwa [sq_eq_sq h₁ h₂] at h'
· intro i j hij
simpa [hij] using h i j
#align orthonormal_iff_ite orthonormal_iff_ite
/-- `if ... then ... else` characterization of a set of vectors being orthonormal. (Inner product
equals Kronecker delta.) -/
theorem orthonormal_subtype_iff_ite [DecidableEq E] {s : Set E} :
Orthonormal 𝕜 (Subtype.val : s → E) ↔ ∀ v ∈ s, ∀ w ∈ s, ⟪v, w⟫ = if v = w then 1 else 0 := by
rw [orthonormal_iff_ite]
constructor
· intro h v hv w hw
convert h ⟨v, hv⟩ ⟨w, hw⟩ using 1
simp
· rintro h ⟨v, hv⟩ ⟨w, hw⟩
convert h v hv w hw using 1
simp
#align orthonormal_subtype_iff_ite orthonormal_subtype_iff_ite
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_finsupp {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι →₀ 𝕜) (i : ι) :
⟪v i, Finsupp.total ι E 𝕜 v l⟫ = l i := by
classical
simpa [Finsupp.total_apply, Finsupp.inner_sum, orthonormal_iff_ite.mp hv] using Eq.symm
#align orthonormal.inner_right_finsupp Orthonormal.inner_right_finsupp
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜) {s : Finset ι}
{i : ι} (hi : i ∈ s) : ⟪v i, ∑ i ∈ s, l i • v i⟫ = l i := by
classical
simp [inner_sum, inner_smul_right, orthonormal_iff_ite.mp hv, hi]
#align orthonormal.inner_right_sum Orthonormal.inner_right_sum
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_fintype [Fintype ι] {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜)
(i : ι) : ⟪v i, ∑ i : ι, l i • v i⟫ = l i :=
hv.inner_right_sum l (Finset.mem_univ _)
#align orthonormal.inner_right_fintype Orthonormal.inner_right_fintype
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_finsupp {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι →₀ 𝕜) (i : ι) :
⟪Finsupp.total ι E 𝕜 v l, v i⟫ = conj (l i) := by rw [← inner_conj_symm, hv.inner_right_finsupp]
#align orthonormal.inner_left_finsupp Orthonormal.inner_left_finsupp
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜) {s : Finset ι}
{i : ι} (hi : i ∈ s) : ⟪∑ i ∈ s, l i • v i, v i⟫ = conj (l i) := by
classical
simp only [sum_inner, inner_smul_left, orthonormal_iff_ite.mp hv, hi, mul_boole,
Finset.sum_ite_eq', if_true]
#align orthonormal.inner_left_sum Orthonormal.inner_left_sum
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_fintype [Fintype ι] {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜)
(i : ι) : ⟪∑ i : ι, l i • v i, v i⟫ = conj (l i) :=
hv.inner_left_sum l (Finset.mem_univ _)
#align orthonormal.inner_left_fintype Orthonormal.inner_left_fintype
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum over the first `Finsupp`. -/
theorem Orthonormal.inner_finsupp_eq_sum_left {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι →₀ 𝕜) :
⟪Finsupp.total ι E 𝕜 v l₁, Finsupp.total ι E 𝕜 v l₂⟫ = l₁.sum fun i y => conj y * l₂ i := by
simp only [l₁.total_apply _, Finsupp.sum_inner, hv.inner_right_finsupp, smul_eq_mul]
#align orthonormal.inner_finsupp_eq_sum_left Orthonormal.inner_finsupp_eq_sum_left
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum over the second `Finsupp`. -/
theorem Orthonormal.inner_finsupp_eq_sum_right {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι →₀ 𝕜) :
⟪Finsupp.total ι E 𝕜 v l₁, Finsupp.total ι E 𝕜 v l₂⟫ = l₂.sum fun i y => conj (l₁ i) * y := by
simp only [l₂.total_apply _, Finsupp.inner_sum, hv.inner_left_finsupp, mul_comm, smul_eq_mul]
#align orthonormal.inner_finsupp_eq_sum_right Orthonormal.inner_finsupp_eq_sum_right
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum. -/
theorem Orthonormal.inner_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι → 𝕜) (s : Finset ι) :
⟪∑ i ∈ s, l₁ i • v i, ∑ i ∈ s, l₂ i • v i⟫ = ∑ i ∈ s, conj (l₁ i) * l₂ i := by
simp_rw [sum_inner, inner_smul_left]
refine Finset.sum_congr rfl fun i hi => ?_
rw [hv.inner_right_sum l₂ hi]
#align orthonormal.inner_sum Orthonormal.inner_sum
/--
The double sum of weighted inner products of pairs of vectors from an orthonormal sequence is the
sum of the weights.
-/
theorem Orthonormal.inner_left_right_finset {s : Finset ι} {v : ι → E} (hv : Orthonormal 𝕜 v)
{a : ι → ι → 𝕜} : (∑ i ∈ s, ∑ j ∈ s, a i j • ⟪v j, v i⟫) = ∑ k ∈ s, a k k := by
classical
simp [orthonormal_iff_ite.mp hv, Finset.sum_ite_of_true]
#align orthonormal.inner_left_right_finset Orthonormal.inner_left_right_finset
/-- An orthonormal set is linearly independent. -/
theorem Orthonormal.linearIndependent {v : ι → E} (hv : Orthonormal 𝕜 v) :
LinearIndependent 𝕜 v := by
rw [linearIndependent_iff]
intro l hl
ext i
have key : ⟪v i, Finsupp.total ι E 𝕜 v l⟫ = ⟪v i, 0⟫ := by rw [hl]
simpa only [hv.inner_right_finsupp, inner_zero_right] using key
#align orthonormal.linear_independent Orthonormal.linearIndependent
/-- A subfamily of an orthonormal family (i.e., a composition with an injective map) is an
orthonormal family. -/
theorem Orthonormal.comp {ι' : Type*} {v : ι → E} (hv : Orthonormal 𝕜 v) (f : ι' → ι)
(hf : Function.Injective f) : Orthonormal 𝕜 (v ∘ f) := by
classical
rw [orthonormal_iff_ite] at hv ⊢
intro i j
convert hv (f i) (f j) using 1
simp [hf.eq_iff]
#align orthonormal.comp Orthonormal.comp
/-- An injective family `v : ι → E` is orthonormal if and only if `Subtype.val : (range v) → E` is
orthonormal. -/
theorem orthonormal_subtype_range {v : ι → E} (hv : Function.Injective v) :
Orthonormal 𝕜 (Subtype.val : Set.range v → E) ↔ Orthonormal 𝕜 v := by
let f : ι ≃ Set.range v := Equiv.ofInjective v hv
refine ⟨fun h => h.comp f f.injective, fun h => ?_⟩
rw [← Equiv.self_comp_ofInjective_symm hv]
exact h.comp f.symm f.symm.injective
#align orthonormal_subtype_range orthonormal_subtype_range
/-- If `v : ι → E` is an orthonormal family, then `Subtype.val : (range v) → E` is an orthonormal
family. -/
theorem Orthonormal.toSubtypeRange {v : ι → E} (hv : Orthonormal 𝕜 v) :
Orthonormal 𝕜 (Subtype.val : Set.range v → E) :=
(orthonormal_subtype_range hv.linearIndependent.injective).2 hv
#align orthonormal.to_subtype_range Orthonormal.toSubtypeRange
/-- A linear combination of some subset of an orthonormal set is orthogonal to other members of the
set. -/
theorem Orthonormal.inner_finsupp_eq_zero {v : ι → E} (hv : Orthonormal 𝕜 v) {s : Set ι} {i : ι}
(hi : i ∉ s) {l : ι →₀ 𝕜} (hl : l ∈ Finsupp.supported 𝕜 𝕜 s) :
⟪Finsupp.total ι E 𝕜 v l, v i⟫ = 0 := by
rw [Finsupp.mem_supported'] at hl
simp only [hv.inner_left_finsupp, hl i hi, map_zero]
#align orthonormal.inner_finsupp_eq_zero Orthonormal.inner_finsupp_eq_zero
/-- Given an orthonormal family, a second family of vectors is orthonormal if every vector equals
the corresponding vector in the original family or its negation. -/
theorem Orthonormal.orthonormal_of_forall_eq_or_eq_neg {v w : ι → E} (hv : Orthonormal 𝕜 v)
(hw : ∀ i, w i = v i ∨ w i = -v i) : Orthonormal 𝕜 w := by
classical
rw [orthonormal_iff_ite] at *
intro i j
cases' hw i with hi hi <;> cases' hw j with hj hj <;>
replace hv := hv i j <;> split_ifs at hv ⊢ with h <;>
simpa only [hi, hj, h, inner_neg_right, inner_neg_left, neg_neg, eq_self_iff_true,
neg_eq_zero] using hv
#align orthonormal.orthonormal_of_forall_eq_or_eq_neg Orthonormal.orthonormal_of_forall_eq_or_eq_neg
/- The material that follows, culminating in the existence of a maximal orthonormal subset, is
adapted from the corresponding development of the theory of linearly independents sets. See
`exists_linearIndependent` in particular. -/
variable (𝕜 E)
theorem orthonormal_empty : Orthonormal 𝕜 (fun x => x : (∅ : Set E) → E) := by
classical
simp [orthonormal_subtype_iff_ite]
#align orthonormal_empty orthonormal_empty
variable {𝕜 E}
theorem orthonormal_iUnion_of_directed {η : Type*} {s : η → Set E} (hs : Directed (· ⊆ ·) s)
(h : ∀ i, Orthonormal 𝕜 (fun x => x : s i → E)) :
Orthonormal 𝕜 (fun x => x : (⋃ i, s i) → E) := by
classical
rw [orthonormal_subtype_iff_ite]
rintro x ⟨_, ⟨i, rfl⟩, hxi⟩ y ⟨_, ⟨j, rfl⟩, hyj⟩
obtain ⟨k, hik, hjk⟩ := hs i j
have h_orth : Orthonormal 𝕜 (fun x => x : s k → E) := h k
rw [orthonormal_subtype_iff_ite] at h_orth
exact h_orth x (hik hxi) y (hjk hyj)
#align orthonormal_Union_of_directed orthonormal_iUnion_of_directed
theorem orthonormal_sUnion_of_directed {s : Set (Set E)} (hs : DirectedOn (· ⊆ ·) s)
(h : ∀ a ∈ s, Orthonormal 𝕜 (fun x => ((x : a) : E))) :
Orthonormal 𝕜 (fun x => x : ⋃₀ s → E) := by
rw [Set.sUnion_eq_iUnion]; exact orthonormal_iUnion_of_directed hs.directed_val (by simpa using h)
#align orthonormal_sUnion_of_directed orthonormal_sUnion_of_directed
/-- Given an orthonormal set `v` of vectors in `E`, there exists a maximal orthonormal set
containing it. -/
theorem exists_maximal_orthonormal {s : Set E} (hs : Orthonormal 𝕜 (Subtype.val : s → E)) :
∃ w ⊇ s, Orthonormal 𝕜 (Subtype.val : w → E) ∧
∀ u ⊇ w, Orthonormal 𝕜 (Subtype.val : u → E) → u = w := by
have := zorn_subset_nonempty { b | Orthonormal 𝕜 (Subtype.val : b → E) } ?_ _ hs
· obtain ⟨b, bi, sb, h⟩ := this
refine ⟨b, sb, bi, ?_⟩
exact fun u hus hu => h u hu hus
· refine fun c hc cc _c0 => ⟨⋃₀ c, ?_, ?_⟩
· exact orthonormal_sUnion_of_directed cc.directedOn fun x xc => hc xc
· exact fun _ => Set.subset_sUnion_of_mem
#align exists_maximal_orthonormal exists_maximal_orthonormal
theorem Orthonormal.ne_zero {v : ι → E} (hv : Orthonormal 𝕜 v) (i : ι) : v i ≠ 0 := by
have : ‖v i‖ ≠ 0 := by
rw [hv.1 i]
norm_num
simpa using this
#align orthonormal.ne_zero Orthonormal.ne_zero
open FiniteDimensional
/-- A family of orthonormal vectors with the correct cardinality forms a basis. -/
def basisOfOrthonormalOfCardEqFinrank [Fintype ι] [Nonempty ι] {v : ι → E} (hv : Orthonormal 𝕜 v)
(card_eq : Fintype.card ι = finrank 𝕜 E) : Basis ι 𝕜 E :=
basisOfLinearIndependentOfCardEqFinrank hv.linearIndependent card_eq
#align basis_of_orthonormal_of_card_eq_finrank basisOfOrthonormalOfCardEqFinrank
@[simp]
theorem coe_basisOfOrthonormalOfCardEqFinrank [Fintype ι] [Nonempty ι] {v : ι → E}
(hv : Orthonormal 𝕜 v) (card_eq : Fintype.card ι = finrank 𝕜 E) :
(basisOfOrthonormalOfCardEqFinrank hv card_eq : ι → E) = v :=
coe_basisOfLinearIndependentOfCardEqFinrank _ _
#align coe_basis_of_orthonormal_of_card_eq_finrank coe_basisOfOrthonormalOfCardEqFinrank
end OrthonormalSets
section Norm
theorem norm_eq_sqrt_inner (x : E) : ‖x‖ = √(re ⟪x, x⟫) :=
calc
‖x‖ = √(‖x‖ ^ 2) := (sqrt_sq (norm_nonneg _)).symm
_ = √(re ⟪x, x⟫) := congr_arg _ (norm_sq_eq_inner _)
#align norm_eq_sqrt_inner norm_eq_sqrt_inner
theorem norm_eq_sqrt_real_inner (x : F) : ‖x‖ = √⟪x, x⟫_ℝ :=
@norm_eq_sqrt_inner ℝ _ _ _ _ x
#align norm_eq_sqrt_real_inner norm_eq_sqrt_real_inner
theorem inner_self_eq_norm_mul_norm (x : E) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [@norm_eq_sqrt_inner 𝕜, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫),
sqrt_mul_self inner_self_nonneg]
#align inner_self_eq_norm_mul_norm inner_self_eq_norm_mul_norm
theorem inner_self_eq_norm_sq (x : E) : re ⟪x, x⟫ = ‖x‖ ^ 2 := by
rw [pow_two, inner_self_eq_norm_mul_norm]
#align inner_self_eq_norm_sq inner_self_eq_norm_sq
theorem real_inner_self_eq_norm_mul_norm (x : F) : ⟪x, x⟫_ℝ = ‖x‖ * ‖x‖ := by
have h := @inner_self_eq_norm_mul_norm ℝ F _ _ _ x
simpa using h
#align real_inner_self_eq_norm_mul_norm real_inner_self_eq_norm_mul_norm
theorem real_inner_self_eq_norm_sq (x : F) : ⟪x, x⟫_ℝ = ‖x‖ ^ 2 := by
rw [pow_two, real_inner_self_eq_norm_mul_norm]
#align real_inner_self_eq_norm_sq real_inner_self_eq_norm_sq
-- Porting note: this was present in mathlib3 but seemingly didn't do anything.
-- variable (𝕜)
/-- Expand the square -/
theorem norm_add_sq (x y : E) : ‖x + y‖ ^ 2 = ‖x‖ ^ 2 + 2 * re ⟪x, y⟫ + ‖y‖ ^ 2 := by
repeat' rw [sq (M := ℝ), ← @inner_self_eq_norm_mul_norm 𝕜]
rw [inner_add_add_self, two_mul]
simp only [add_assoc, add_left_inj, add_right_inj, AddMonoidHom.map_add]
rw [← inner_conj_symm, conj_re]
#align norm_add_sq norm_add_sq
alias norm_add_pow_two := norm_add_sq
#align norm_add_pow_two norm_add_pow_two
/-- Expand the square -/
theorem norm_add_sq_real (x y : F) : ‖x + y‖ ^ 2 = ‖x‖ ^ 2 + 2 * ⟪x, y⟫_ℝ + ‖y‖ ^ 2 := by
have h := @norm_add_sq ℝ _ _ _ _ x y
simpa using h
#align norm_add_sq_real norm_add_sq_real
alias norm_add_pow_two_real := norm_add_sq_real
#align norm_add_pow_two_real norm_add_pow_two_real
/-- Expand the square -/
theorem norm_add_mul_self (x y : E) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + 2 * re ⟪x, y⟫ + ‖y‖ * ‖y‖ := by
repeat' rw [← sq (M := ℝ)]
exact norm_add_sq _ _
#align norm_add_mul_self norm_add_mul_self
/-- Expand the square -/
theorem norm_add_mul_self_real (x y : F) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + 2 * ⟪x, y⟫_ℝ + ‖y‖ * ‖y‖ := by
have h := @norm_add_mul_self ℝ _ _ _ _ x y
simpa using h
#align norm_add_mul_self_real norm_add_mul_self_real
/-- Expand the square -/
theorem norm_sub_sq (x y : E) : ‖x - y‖ ^ 2 = ‖x‖ ^ 2 - 2 * re ⟪x, y⟫ + ‖y‖ ^ 2 := by
rw [sub_eq_add_neg, @norm_add_sq 𝕜 _ _ _ _ x (-y), norm_neg, inner_neg_right, map_neg, mul_neg,
sub_eq_add_neg]
#align norm_sub_sq norm_sub_sq
alias norm_sub_pow_two := norm_sub_sq
#align norm_sub_pow_two norm_sub_pow_two
/-- Expand the square -/
theorem norm_sub_sq_real (x y : F) : ‖x - y‖ ^ 2 = ‖x‖ ^ 2 - 2 * ⟪x, y⟫_ℝ + ‖y‖ ^ 2 :=
@norm_sub_sq ℝ _ _ _ _ _ _
#align norm_sub_sq_real norm_sub_sq_real
alias norm_sub_pow_two_real := norm_sub_sq_real
#align norm_sub_pow_two_real norm_sub_pow_two_real
/-- Expand the square -/
theorem norm_sub_mul_self (x y : E) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ - 2 * re ⟪x, y⟫ + ‖y‖ * ‖y‖ := by
repeat' rw [← sq (M := ℝ)]
exact norm_sub_sq _ _
#align norm_sub_mul_self norm_sub_mul_self
/-- Expand the square -/
theorem norm_sub_mul_self_real (x y : F) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ - 2 * ⟪x, y⟫_ℝ + ‖y‖ * ‖y‖ := by
have h := @norm_sub_mul_self ℝ _ _ _ _ x y
simpa using h
#align norm_sub_mul_self_real norm_sub_mul_self_real
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : E) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := by
rw [norm_eq_sqrt_inner (𝕜 := 𝕜) x, norm_eq_sqrt_inner (𝕜 := 𝕜) y]
letI : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
exact InnerProductSpace.Core.norm_inner_le_norm x y
#align norm_inner_le_norm norm_inner_le_norm
theorem nnnorm_inner_le_nnnorm (x y : E) : ‖⟪x, y⟫‖₊ ≤ ‖x‖₊ * ‖y‖₊ :=
norm_inner_le_norm x y
#align nnnorm_inner_le_nnnorm nnnorm_inner_le_nnnorm
theorem re_inner_le_norm (x y : E) : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ :=
le_trans (re_le_norm (inner x y)) (norm_inner_le_norm x y)
#align re_inner_le_norm re_inner_le_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem abs_real_inner_le_norm (x y : F) : |⟪x, y⟫_ℝ| ≤ ‖x‖ * ‖y‖ :=
(Real.norm_eq_abs _).ge.trans (norm_inner_le_norm x y)
#align abs_real_inner_le_norm abs_real_inner_le_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem real_inner_le_norm (x y : F) : ⟪x, y⟫_ℝ ≤ ‖x‖ * ‖y‖ :=
le_trans (le_abs_self _) (abs_real_inner_le_norm _ _)
#align real_inner_le_norm real_inner_le_norm
variable (𝕜)
theorem parallelogram_law_with_norm (x y : E) :
‖x + y‖ * ‖x + y‖ + ‖x - y‖ * ‖x - y‖ = 2 * (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) := by
simp only [← @inner_self_eq_norm_mul_norm 𝕜]
rw [← re.map_add, parallelogram_law, two_mul, two_mul]
simp only [re.map_add]
#align parallelogram_law_with_norm parallelogram_law_with_norm
theorem parallelogram_law_with_nnnorm (x y : E) :
‖x + y‖₊ * ‖x + y‖₊ + ‖x - y‖₊ * ‖x - y‖₊ = 2 * (‖x‖₊ * ‖x‖₊ + ‖y‖₊ * ‖y‖₊) :=
Subtype.ext <| parallelogram_law_with_norm 𝕜 x y
#align parallelogram_law_with_nnnorm parallelogram_law_with_nnnorm
variable {𝕜}
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two (x y : E) :
re ⟪x, y⟫ = (‖x + y‖ * ‖x + y‖ - ‖x‖ * ‖x‖ - ‖y‖ * ‖y‖) / 2 := by
rw [@norm_add_mul_self 𝕜]
ring
#align re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two (x y : E) :
re ⟪x, y⟫ = (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ - ‖x - y‖ * ‖x - y‖) / 2 := by
rw [@norm_sub_mul_self 𝕜]
ring
#align re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four (x y : E) :
re ⟪x, y⟫ = (‖x + y‖ * ‖x + y‖ - ‖x - y‖ * ‖x - y‖) / 4 := by
rw [@norm_add_mul_self 𝕜, @norm_sub_mul_self 𝕜]
ring
#align re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four
/-- Polarization identity: The imaginary part of the inner product, in terms of the norm. -/
theorem im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four (x y : E) :
im ⟪x, y⟫ = (‖x - IK • y‖ * ‖x - IK • y‖ - ‖x + IK • y‖ * ‖x + IK • y‖) / 4 := by
simp only [@norm_add_mul_self 𝕜, @norm_sub_mul_self 𝕜, inner_smul_right, I_mul_re]
ring
set_option linter.uppercaseLean3 false in
#align im_inner_eq_norm_sub_I_smul_mul_self_sub_norm_add_I_smul_mul_self_div_four im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four
/-- Polarization identity: The inner product, in terms of the norm. -/
theorem inner_eq_sum_norm_sq_div_four (x y : E) :
⟪x, y⟫ = ((‖x + y‖ : 𝕜) ^ 2 - (‖x - y‖ : 𝕜) ^ 2 +
((‖x - IK • y‖ : 𝕜) ^ 2 - (‖x + IK • y‖ : 𝕜) ^ 2) * IK) / 4 := by
rw [← re_add_im ⟪x, y⟫, re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four,
im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four]
push_cast
simp only [sq, ← mul_div_right_comm, ← add_div]
#align inner_eq_sum_norm_sq_div_four inner_eq_sum_norm_sq_div_four
/-- Formula for the distance between the images of two nonzero points under an inversion with center
zero. See also `EuclideanGeometry.dist_inversion_inversion` for inversions around a general
point. -/
theorem dist_div_norm_sq_smul {x y : F} (hx : x ≠ 0) (hy : y ≠ 0) (R : ℝ) :
dist ((R / ‖x‖) ^ 2 • x) ((R / ‖y‖) ^ 2 • y) = R ^ 2 / (‖x‖ * ‖y‖) * dist x y :=
have hx' : ‖x‖ ≠ 0 := norm_ne_zero_iff.2 hx
have hy' : ‖y‖ ≠ 0 := norm_ne_zero_iff.2 hy
calc
dist ((R / ‖x‖) ^ 2 • x) ((R / ‖y‖) ^ 2 • y) =
√(‖(R / ‖x‖) ^ 2 • x - (R / ‖y‖) ^ 2 • y‖ ^ 2) := by
rw [dist_eq_norm, sqrt_sq (norm_nonneg _)]
_ = √((R ^ 2 / (‖x‖ * ‖y‖)) ^ 2 * ‖x - y‖ ^ 2) :=
congr_arg sqrt <| by
field_simp [sq, norm_sub_mul_self_real, norm_smul, real_inner_smul_left, inner_smul_right,
Real.norm_of_nonneg (mul_self_nonneg _)]
ring
_ = R ^ 2 / (‖x‖ * ‖y‖) * dist x y := by
rw [sqrt_mul, sqrt_sq, sqrt_sq, dist_eq_norm] <;> positivity
#align dist_div_norm_sq_smul dist_div_norm_sq_smul
-- See note [lower instance priority]
instance (priority := 100) InnerProductSpace.toUniformConvexSpace : UniformConvexSpace F :=
⟨fun ε hε => by
refine
⟨2 - √(4 - ε ^ 2), sub_pos_of_lt <| (sqrt_lt' zero_lt_two).2 ?_, fun x hx y hy hxy => ?_⟩
· norm_num
exact pow_pos hε _
rw [sub_sub_cancel]
refine le_sqrt_of_sq_le ?_
rw [sq, eq_sub_iff_add_eq.2 (parallelogram_law_with_norm ℝ x y), ← sq ‖x - y‖, hx, hy]
ring_nf
exact sub_le_sub_left (pow_le_pow_left hε.le hxy _) 4⟩
#align inner_product_space.to_uniform_convex_space InnerProductSpace.toUniformConvexSpace
section Complex
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V]
/-- A complex polarization identity, with a linear map
-/
theorem inner_map_polarization (T : V →ₗ[ℂ] V) (x y : V) :
⟪T y, x⟫_ℂ =
(⟪T (x + y), x + y⟫_ℂ - ⟪T (x - y), x - y⟫_ℂ +
Complex.I * ⟪T (x + Complex.I • y), x + Complex.I • y⟫_ℂ -
Complex.I * ⟪T (x - Complex.I • y), x - Complex.I • y⟫_ℂ) /
4 := by
simp only [map_add, map_sub, inner_add_left, inner_add_right, LinearMap.map_smul, inner_smul_left,
inner_smul_right, Complex.conj_I, ← pow_two, Complex.I_sq, inner_sub_left, inner_sub_right,
mul_add, ← mul_assoc, mul_neg, neg_neg, sub_neg_eq_add, one_mul, neg_one_mul, mul_sub, sub_sub]
ring
#align inner_map_polarization inner_map_polarization
theorem inner_map_polarization' (T : V →ₗ[ℂ] V) (x y : V) :
⟪T x, y⟫_ℂ =
(⟪T (x + y), x + y⟫_ℂ - ⟪T (x - y), x - y⟫_ℂ -
Complex.I * ⟪T (x + Complex.I • y), x + Complex.I • y⟫_ℂ +
Complex.I * ⟪T (x - Complex.I • y), x - Complex.I • y⟫_ℂ) /
4 := by
simp only [map_add, map_sub, inner_add_left, inner_add_right, LinearMap.map_smul, inner_smul_left,
inner_smul_right, Complex.conj_I, ← pow_two, Complex.I_sq, inner_sub_left, inner_sub_right,
mul_add, ← mul_assoc, mul_neg, neg_neg, sub_neg_eq_add, one_mul, neg_one_mul, mul_sub, sub_sub]
ring
#align inner_map_polarization' inner_map_polarization'
/-- A linear map `T` is zero, if and only if the identity `⟪T x, x⟫_ℂ = 0` holds for all `x`.
-/
theorem inner_map_self_eq_zero (T : V →ₗ[ℂ] V) : (∀ x : V, ⟪T x, x⟫_ℂ = 0) ↔ T = 0 := by
constructor
· intro hT
ext x
rw [LinearMap.zero_apply, ← @inner_self_eq_zero ℂ V, inner_map_polarization]
simp only [hT]
norm_num
· rintro rfl x
simp only [LinearMap.zero_apply, inner_zero_left]
#align inner_map_self_eq_zero inner_map_self_eq_zero
/--
Two linear maps `S` and `T` are equal, if and only if the identity `⟪S x, x⟫_ℂ = ⟪T x, x⟫_ℂ` holds
for all `x`.
-/
theorem ext_inner_map (S T : V →ₗ[ℂ] V) : (∀ x : V, ⟪S x, x⟫_ℂ = ⟪T x, x⟫_ℂ) ↔ S = T := by
rw [← sub_eq_zero, ← inner_map_self_eq_zero]
refine forall_congr' fun x => ?_
rw [LinearMap.sub_apply, inner_sub_left, sub_eq_zero]
#align ext_inner_map ext_inner_map
end Complex
section
variable {ι : Type*} {ι' : Type*} {ι'' : Type*}
variable {E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E']
variable {E'' : Type*} [NormedAddCommGroup E''] [InnerProductSpace 𝕜 E'']
/-- A linear isometry preserves the inner product. -/
@[simp]
theorem LinearIsometry.inner_map_map (f : E →ₗᵢ[𝕜] E') (x y : E) : ⟪f x, f y⟫ = ⟪x, y⟫ := by
simp [inner_eq_sum_norm_sq_div_four, ← f.norm_map]
#align linear_isometry.inner_map_map LinearIsometry.inner_map_map
/-- A linear isometric equivalence preserves the inner product. -/
@[simp]
theorem LinearIsometryEquiv.inner_map_map (f : E ≃ₗᵢ[𝕜] E') (x y : E) : ⟪f x, f y⟫ = ⟪x, y⟫ :=
f.toLinearIsometry.inner_map_map x y
#align linear_isometry_equiv.inner_map_map LinearIsometryEquiv.inner_map_map
/-- The adjoint of a linear isometric equivalence is its inverse. -/
theorem LinearIsometryEquiv.inner_map_eq_flip (f : E ≃ₗᵢ[𝕜] E') (x : E) (y : E') :
⟪f x, y⟫_𝕜 = ⟪x, f.symm y⟫_𝕜 := by
conv_lhs => rw [← f.apply_symm_apply y, f.inner_map_map]
/-- A linear map that preserves the inner product is a linear isometry. -/
def LinearMap.isometryOfInner (f : E →ₗ[𝕜] E') (h : ∀ x y, ⟪f x, f y⟫ = ⟪x, y⟫) : E →ₗᵢ[𝕜] E' :=
⟨f, fun x => by simp only [@norm_eq_sqrt_inner 𝕜, h]⟩
#align linear_map.isometry_of_inner LinearMap.isometryOfInner
@[simp]
theorem LinearMap.coe_isometryOfInner (f : E →ₗ[𝕜] E') (h) : ⇑(f.isometryOfInner h) = f :=
rfl
#align linear_map.coe_isometry_of_inner LinearMap.coe_isometryOfInner
@[simp]
theorem LinearMap.isometryOfInner_toLinearMap (f : E →ₗ[𝕜] E') (h) :
(f.isometryOfInner h).toLinearMap = f :=
rfl
#align linear_map.isometry_of_inner_to_linear_map LinearMap.isometryOfInner_toLinearMap
/-- A linear equivalence that preserves the inner product is a linear isometric equivalence. -/
def LinearEquiv.isometryOfInner (f : E ≃ₗ[𝕜] E') (h : ∀ x y, ⟪f x, f y⟫ = ⟪x, y⟫) : E ≃ₗᵢ[𝕜] E' :=
⟨f, ((f : E →ₗ[𝕜] E').isometryOfInner h).norm_map⟩
#align linear_equiv.isometry_of_inner LinearEquiv.isometryOfInner
@[simp]
theorem LinearEquiv.coe_isometryOfInner (f : E ≃ₗ[𝕜] E') (h) : ⇑(f.isometryOfInner h) = f :=
rfl
#align linear_equiv.coe_isometry_of_inner LinearEquiv.coe_isometryOfInner
@[simp]
theorem LinearEquiv.isometryOfInner_toLinearEquiv (f : E ≃ₗ[𝕜] E') (h) :
(f.isometryOfInner h).toLinearEquiv = f :=
rfl
#align linear_equiv.isometry_of_inner_to_linear_equiv LinearEquiv.isometryOfInner_toLinearEquiv
/-- A linear map is an isometry if and it preserves the inner product. -/
theorem LinearMap.norm_map_iff_inner_map_map {F : Type*} [FunLike F E E'] [LinearMapClass F 𝕜 E E']
(f : F) : (∀ x, ‖f x‖ = ‖x‖) ↔ (∀ x y, ⟪f x, f y⟫_𝕜 = ⟪x, y⟫_𝕜) :=
⟨({ toLinearMap := LinearMapClass.linearMap f, norm_map' := · : E →ₗᵢ[𝕜] E' }.inner_map_map),
(LinearMapClass.linearMap f |>.isometryOfInner · |>.norm_map)⟩
/-- A linear isometry preserves the property of being orthonormal. -/
theorem LinearIsometry.orthonormal_comp_iff {v : ι → E} (f : E →ₗᵢ[𝕜] E') :
Orthonormal 𝕜 (f ∘ v) ↔ Orthonormal 𝕜 v := by
classical simp_rw [orthonormal_iff_ite, Function.comp_apply, LinearIsometry.inner_map_map]
#align linear_isometry.orthonormal_comp_iff LinearIsometry.orthonormal_comp_iff
/-- A linear isometry preserves the property of being orthonormal. -/
theorem Orthonormal.comp_linearIsometry {v : ι → E} (hv : Orthonormal 𝕜 v) (f : E →ₗᵢ[𝕜] E') :
Orthonormal 𝕜 (f ∘ v) := by rwa [f.orthonormal_comp_iff]
#align orthonormal.comp_linear_isometry Orthonormal.comp_linearIsometry
/-- A linear isometric equivalence preserves the property of being orthonormal. -/
theorem Orthonormal.comp_linearIsometryEquiv {v : ι → E} (hv : Orthonormal 𝕜 v) (f : E ≃ₗᵢ[𝕜] E') :
Orthonormal 𝕜 (f ∘ v) :=
hv.comp_linearIsometry f.toLinearIsometry
#align orthonormal.comp_linear_isometry_equiv Orthonormal.comp_linearIsometryEquiv
/-- A linear isometric equivalence, applied with `Basis.map`, preserves the property of being
orthonormal. -/
theorem Orthonormal.mapLinearIsometryEquiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
(f : E ≃ₗᵢ[𝕜] E') : Orthonormal 𝕜 (v.map f.toLinearEquiv) :=
hv.comp_linearIsometryEquiv f
#align orthonormal.map_linear_isometry_equiv Orthonormal.mapLinearIsometryEquiv
/-- A linear map that sends an orthonormal basis to orthonormal vectors is a linear isometry. -/
def LinearMap.isometryOfOrthonormal (f : E →ₗ[𝕜] E') {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
(hf : Orthonormal 𝕜 (f ∘ v)) : E →ₗᵢ[𝕜] E' :=
f.isometryOfInner fun x y => by
classical rw [← v.total_repr x, ← v.total_repr y, Finsupp.apply_total, Finsupp.apply_total,
hv.inner_finsupp_eq_sum_left, hf.inner_finsupp_eq_sum_left]
#align linear_map.isometry_of_orthonormal LinearMap.isometryOfOrthonormal
@[simp]
theorem LinearMap.coe_isometryOfOrthonormal (f : E →ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) : ⇑(f.isometryOfOrthonormal hv hf) = f :=
rfl
#align linear_map.coe_isometry_of_orthonormal LinearMap.coe_isometryOfOrthonormal
@[simp]
theorem LinearMap.isometryOfOrthonormal_toLinearMap (f : E →ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) :
(f.isometryOfOrthonormal hv hf).toLinearMap = f :=
rfl
#align linear_map.isometry_of_orthonormal_to_linear_map LinearMap.isometryOfOrthonormal_toLinearMap
/-- A linear equivalence that sends an orthonormal basis to orthonormal vectors is a linear
isometric equivalence. -/
def LinearEquiv.isometryOfOrthonormal (f : E ≃ₗ[𝕜] E') {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
(hf : Orthonormal 𝕜 (f ∘ v)) : E ≃ₗᵢ[𝕜] E' :=
f.isometryOfInner fun x y => by
rw [← LinearEquiv.coe_coe] at hf
classical rw [← v.total_repr x, ← v.total_repr y, ← LinearEquiv.coe_coe f, Finsupp.apply_total,
Finsupp.apply_total, hv.inner_finsupp_eq_sum_left, hf.inner_finsupp_eq_sum_left]
#align linear_equiv.isometry_of_orthonormal LinearEquiv.isometryOfOrthonormal
@[simp]
theorem LinearEquiv.coe_isometryOfOrthonormal (f : E ≃ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) : ⇑(f.isometryOfOrthonormal hv hf) = f :=
rfl
#align linear_equiv.coe_isometry_of_orthonormal LinearEquiv.coe_isometryOfOrthonormal
@[simp]
theorem LinearEquiv.isometryOfOrthonormal_toLinearEquiv (f : E ≃ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) :
(f.isometryOfOrthonormal hv hf).toLinearEquiv = f :=
rfl
#align linear_equiv.isometry_of_orthonormal_to_linear_equiv LinearEquiv.isometryOfOrthonormal_toLinearEquiv
/-- A linear isometric equivalence that sends an orthonormal basis to a given orthonormal basis. -/
def Orthonormal.equiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') : E ≃ₗᵢ[𝕜] E' :=
(v.equiv v' e).isometryOfOrthonormal hv
(by
have h : v.equiv v' e ∘ v = v' ∘ e := by
ext i
simp
rw [h]
classical exact hv'.comp _ e.injective)
#align orthonormal.equiv Orthonormal.equiv
@[simp]
theorem Orthonormal.equiv_toLinearEquiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
{v' : Basis ι' 𝕜 E'} (hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') :
(hv.equiv hv' e).toLinearEquiv = v.equiv v' e :=
rfl
#align orthonormal.equiv_to_linear_equiv Orthonormal.equiv_toLinearEquiv
@[simp]
theorem Orthonormal.equiv_apply {ι' : Type*} {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
{v' : Basis ι' 𝕜 E'} (hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') (i : ι) :
hv.equiv hv' e (v i) = v' (e i) :=
Basis.equiv_apply _ _ _ _
#align orthonormal.equiv_apply Orthonormal.equiv_apply
@[simp]
theorem Orthonormal.equiv_refl {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) :
hv.equiv hv (Equiv.refl ι) = LinearIsometryEquiv.refl 𝕜 E :=
v.ext_linearIsometryEquiv fun i => by
simp only [Orthonormal.equiv_apply, Equiv.coe_refl, id, LinearIsometryEquiv.coe_refl]
#align orthonormal.equiv_refl Orthonormal.equiv_refl
@[simp]
theorem Orthonormal.equiv_symm {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') : (hv.equiv hv' e).symm = hv'.equiv hv e.symm :=
v'.ext_linearIsometryEquiv fun i =>
(hv.equiv hv' e).injective <| by
simp only [LinearIsometryEquiv.apply_symm_apply, Orthonormal.equiv_apply, e.apply_symm_apply]
#align orthonormal.equiv_symm Orthonormal.equiv_symm
@[simp]
theorem Orthonormal.equiv_trans {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') {v'' : Basis ι'' 𝕜 E''} (hv'' : Orthonormal 𝕜 v'')
(e' : ι' ≃ ι'') : (hv.equiv hv' e).trans (hv'.equiv hv'' e') = hv.equiv hv'' (e.trans e') :=
v.ext_linearIsometryEquiv fun i => by
simp only [LinearIsometryEquiv.trans_apply, Orthonormal.equiv_apply, e.coe_trans,
Function.comp_apply]
#align orthonormal.equiv_trans Orthonormal.equiv_trans
theorem Orthonormal.map_equiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') :
v.map (hv.equiv hv' e).toLinearEquiv = v'.reindex e.symm :=
v.map_equiv _ _
#align orthonormal.map_equiv Orthonormal.map_equiv
end
/-- Polarization identity: The real inner product, in terms of the norm. -/
theorem real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two (x y : F) :
⟪x, y⟫_ℝ = (‖x + y‖ * ‖x + y‖ - ‖x‖ * ‖x‖ - ‖y‖ * ‖y‖) / 2 :=
re_to_real.symm.trans <|
re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two x y
#align real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two
/-- Polarization identity: The real inner product, in terms of the norm. -/
theorem real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two (x y : F) :
⟪x, y⟫_ℝ = (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ - ‖x - y‖ * ‖x - y‖) / 2 :=
re_to_real.symm.trans <|
re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two x y
#align real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two
/-- Pythagorean theorem, if-and-only-if vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero (x y : F) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ = 0 := by
rw [@norm_add_mul_self ℝ, add_right_cancel_iff, add_right_eq_self, mul_eq_zero]
norm_num
#align norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero
/-- Pythagorean theorem, if-and-if vector inner product form using square roots. -/
theorem norm_add_eq_sqrt_iff_real_inner_eq_zero {x y : F} :
‖x + y‖ = √(‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) ↔ ⟪x, y⟫_ℝ = 0 := by
rw [← norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero, eq_comm,
sqrt_eq_iff_mul_self_eq (add_nonneg (mul_self_nonneg _) (mul_self_nonneg _)) (norm_nonneg _)]
#align norm_add_eq_sqrt_iff_real_inner_eq_zero norm_add_eq_sqrt_iff_real_inner_eq_zero
/-- Pythagorean theorem, vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero (x y : E) (h : ⟪x, y⟫ = 0) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ := by
rw [@norm_add_mul_self 𝕜, add_right_cancel_iff, add_right_eq_self, mul_eq_zero]
apply Or.inr
simp only [h, zero_re']
#align norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero
/-- Pythagorean theorem, vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_real {x y : F} (h : ⟪x, y⟫_ℝ = 0) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero x y).2 h
#align norm_add_sq_eq_norm_sq_add_norm_sq_real norm_add_sq_eq_norm_sq_add_norm_sq_real
/-- Pythagorean theorem, subtracting vectors, if-and-only-if vector
inner product form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero (x y : F) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ = 0 := by
rw [@norm_sub_mul_self ℝ, add_right_cancel_iff, sub_eq_add_neg, add_right_eq_self, neg_eq_zero,
mul_eq_zero]
norm_num
#align norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero
/-- Pythagorean theorem, subtracting vectors, if-and-if vector inner product form using square
roots. -/
theorem norm_sub_eq_sqrt_iff_real_inner_eq_zero {x y : F} :
‖x - y‖ = √(‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) ↔ ⟪x, y⟫_ℝ = 0 := by
rw [← norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero, eq_comm,
sqrt_eq_iff_mul_self_eq (add_nonneg (mul_self_nonneg _) (mul_self_nonneg _)) (norm_nonneg _)]
#align norm_sub_eq_sqrt_iff_real_inner_eq_zero norm_sub_eq_sqrt_iff_real_inner_eq_zero
/-- Pythagorean theorem, subtracting vectors, vector inner product
form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_real {x y : F} (h : ⟪x, y⟫_ℝ = 0) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero x y).2 h
#align norm_sub_sq_eq_norm_sq_add_norm_sq_real norm_sub_sq_eq_norm_sq_add_norm_sq_real
/-- The sum and difference of two vectors are orthogonal if and only
if they have the same norm. -/
theorem real_inner_add_sub_eq_zero_iff (x y : F) : ⟪x + y, x - y⟫_ℝ = 0 ↔ ‖x‖ = ‖y‖ := by
conv_rhs => rw [← mul_self_inj_of_nonneg (norm_nonneg _) (norm_nonneg _)]
simp only [← @inner_self_eq_norm_mul_norm ℝ, inner_add_left, inner_sub_right, real_inner_comm y x,
sub_eq_zero, re_to_real]
constructor
· intro h
rw [add_comm] at h
linarith
· intro h
linarith
#align real_inner_add_sub_eq_zero_iff real_inner_add_sub_eq_zero_iff
/-- Given two orthogonal vectors, their sum and difference have equal norms. -/
theorem norm_sub_eq_norm_add {v w : E} (h : ⟪v, w⟫ = 0) : ‖w - v‖ = ‖w + v‖ := by
rw [← mul_self_inj_of_nonneg (norm_nonneg _) (norm_nonneg _)]
simp only [h, ← @inner_self_eq_norm_mul_norm 𝕜, sub_neg_eq_add, sub_zero, map_sub, zero_re',
zero_sub, add_zero, map_add, inner_add_right, inner_sub_left, inner_sub_right, inner_re_symm,
zero_add]
#align norm_sub_eq_norm_add norm_sub_eq_norm_add
/-- The real inner product of two vectors, divided by the product of their
norms, has absolute value at most 1. -/
theorem abs_real_inner_div_norm_mul_norm_le_one (x y : F) : |⟪x, y⟫_ℝ / (‖x‖ * ‖y‖)| ≤ 1 := by
rw [abs_div, abs_mul, abs_norm, abs_norm]
exact div_le_one_of_le (abs_real_inner_le_norm x y) (by positivity)
#align abs_real_inner_div_norm_mul_norm_le_one abs_real_inner_div_norm_mul_norm_le_one
/-- The inner product of a vector with a multiple of itself. -/
theorem real_inner_smul_self_left (x : F) (r : ℝ) : ⟪r • x, x⟫_ℝ = r * (‖x‖ * ‖x‖) := by
rw [real_inner_smul_left, ← real_inner_self_eq_norm_mul_norm]
#align real_inner_smul_self_left real_inner_smul_self_left
/-- The inner product of a vector with a multiple of itself. -/
theorem real_inner_smul_self_right (x : F) (r : ℝ) : ⟪x, r • x⟫_ℝ = r * (‖x‖ * ‖x‖) := by
rw [inner_smul_right, ← real_inner_self_eq_norm_mul_norm]
#align real_inner_smul_self_right real_inner_smul_self_right
/-- The inner product of a nonzero vector with a nonzero multiple of
itself, divided by the product of their norms, has absolute value
1. -/
theorem norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul {x : E} {r : 𝕜} (hx : x ≠ 0)
(hr : r ≠ 0) : ‖⟪x, r • x⟫‖ / (‖x‖ * ‖r • x‖) = 1 := by
have hx' : ‖x‖ ≠ 0 := by simp [hx]
have hr' : ‖r‖ ≠ 0 := by simp [hr]
rw [inner_smul_right, norm_mul, ← inner_self_re_eq_norm, inner_self_eq_norm_mul_norm, norm_smul]
rw [← mul_assoc, ← div_div, mul_div_cancel_right₀ _ hx', ← div_div, mul_comm,
mul_div_cancel_right₀ _ hr', div_self hx']
#align norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul
/-- The inner product of a nonzero vector with a nonzero multiple of
itself, divided by the product of their norms, has absolute value
1. -/
theorem abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul {x : F} {r : ℝ}
(hx : x ≠ 0) (hr : r ≠ 0) : |⟪x, r • x⟫_ℝ| / (‖x‖ * ‖r • x‖) = 1 :=
norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul hx hr
#align abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul
/-- The inner product of a nonzero vector with a positive multiple of
itself, divided by the product of their norms, has value 1. -/
theorem real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul {x : F} {r : ℝ} (hx : x ≠ 0)
(hr : 0 < r) : ⟪x, r • x⟫_ℝ / (‖x‖ * ‖r • x‖) = 1 := by
rw [real_inner_smul_self_right, norm_smul, Real.norm_eq_abs, ← mul_assoc ‖x‖, mul_comm _ |r|,
mul_assoc, abs_of_nonneg hr.le, div_self]
exact mul_ne_zero hr.ne' (mul_self_ne_zero.2 (norm_ne_zero_iff.2 hx))
#align real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul
/-- The inner product of a nonzero vector with a negative multiple of
itself, divided by the product of their norms, has value -1. -/
theorem real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul {x : F} {r : ℝ} (hx : x ≠ 0)
(hr : r < 0) : ⟪x, r • x⟫_ℝ / (‖x‖ * ‖r • x‖) = -1 := by
rw [real_inner_smul_self_right, norm_smul, Real.norm_eq_abs, ← mul_assoc ‖x‖, mul_comm _ |r|,
mul_assoc, abs_of_neg hr, neg_mul, div_neg_eq_neg_div, div_self]
exact mul_ne_zero hr.ne (mul_self_ne_zero.2 (norm_ne_zero_iff.2 hx))
#align real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul
theorem norm_inner_eq_norm_tfae (x y : E) :
List.TFAE [‖⟪x, y⟫‖ = ‖x‖ * ‖y‖,
x = 0 ∨ y = (⟪x, y⟫ / ⟪x, x⟫) • x,
x = 0 ∨ ∃ r : 𝕜, y = r • x,
x = 0 ∨ y ∈ 𝕜 ∙ x] := by
tfae_have 1 → 2
· refine fun h => or_iff_not_imp_left.2 fun hx₀ => ?_
have : ‖x‖ ^ 2 ≠ 0 := pow_ne_zero _ (norm_ne_zero_iff.2 hx₀)
rw [← sq_eq_sq, mul_pow, ← mul_right_inj' this, eq_comm, ← sub_eq_zero, ← mul_sub] at h <;>
try positivity
simp only [@norm_sq_eq_inner 𝕜] at h
letI : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
erw [← InnerProductSpace.Core.cauchy_schwarz_aux, InnerProductSpace.Core.normSq_eq_zero,
sub_eq_zero] at h
rw [div_eq_inv_mul, mul_smul, h, inv_smul_smul₀]
rwa [inner_self_ne_zero]
tfae_have 2 → 3
· exact fun h => h.imp_right fun h' => ⟨_, h'⟩
tfae_have 3 → 1
· rintro (rfl | ⟨r, rfl⟩) <;>
simp [inner_smul_right, norm_smul, inner_self_eq_norm_sq_to_K, inner_self_eq_norm_mul_norm,
sq, mul_left_comm]
tfae_have 3 ↔ 4; · simp only [Submodule.mem_span_singleton, eq_comm]
tfae_finish
#align norm_inner_eq_norm_tfae norm_inner_eq_norm_tfae
/-- If the inner product of two vectors is equal to the product of their norms, then the two vectors
are multiples of each other. One form of the equality case for Cauchy-Schwarz.
Compare `inner_eq_norm_mul_iff`, which takes the stronger hypothesis `⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem norm_inner_eq_norm_iff {x y : E} (hx₀ : x ≠ 0) (hy₀ : y ≠ 0) :
‖⟪x, y⟫‖ = ‖x‖ * ‖y‖ ↔ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x :=
calc
‖⟪x, y⟫‖ = ‖x‖ * ‖y‖ ↔ x = 0 ∨ ∃ r : 𝕜, y = r • x :=
(@norm_inner_eq_norm_tfae 𝕜 _ _ _ _ x y).out 0 2
_ ↔ ∃ r : 𝕜, y = r • x := or_iff_right hx₀
_ ↔ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x :=
⟨fun ⟨r, h⟩ => ⟨r, fun hr₀ => hy₀ <| h.symm ▸ smul_eq_zero.2 <| Or.inl hr₀, h⟩,
fun ⟨r, _hr₀, h⟩ => ⟨r, h⟩⟩
#align norm_inner_eq_norm_iff norm_inner_eq_norm_iff
/-- The inner product of two vectors, divided by the product of their
norms, has absolute value 1 if and only if they are nonzero and one is
a multiple of the other. One form of equality case for Cauchy-Schwarz. -/
theorem norm_inner_div_norm_mul_norm_eq_one_iff (x y : E) :
‖⟪x, y⟫ / (‖x‖ * ‖y‖)‖ = 1 ↔ x ≠ 0 ∧ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x := by
constructor
· intro h
have hx₀ : x ≠ 0 := fun h₀ => by simp [h₀] at h
have hy₀ : y ≠ 0 := fun h₀ => by simp [h₀] at h
refine ⟨hx₀, (norm_inner_eq_norm_iff hx₀ hy₀).1 <| eq_of_div_eq_one ?_⟩
simpa using h
· rintro ⟨hx, ⟨r, ⟨hr, rfl⟩⟩⟩
simp only [norm_div, norm_mul, norm_ofReal, abs_norm]
exact norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul hx hr
#align norm_inner_div_norm_mul_norm_eq_one_iff norm_inner_div_norm_mul_norm_eq_one_iff
/-- The inner product of two vectors, divided by the product of their
norms, has absolute value 1 if and only if they are nonzero and one is
a multiple of the other. One form of equality case for Cauchy-Schwarz. -/
theorem abs_real_inner_div_norm_mul_norm_eq_one_iff (x y : F) :
|⟪x, y⟫_ℝ / (‖x‖ * ‖y‖)| = 1 ↔ x ≠ 0 ∧ ∃ r : ℝ, r ≠ 0 ∧ y = r • x :=
@norm_inner_div_norm_mul_norm_eq_one_iff ℝ F _ _ _ x y
#align abs_real_inner_div_norm_mul_norm_eq_one_iff abs_real_inner_div_norm_mul_norm_eq_one_iff
theorem inner_eq_norm_mul_iff_div {x y : E} (h₀ : x ≠ 0) :
⟪x, y⟫ = (‖x‖ : 𝕜) * ‖y‖ ↔ (‖y‖ / ‖x‖ : 𝕜) • x = y := by
have h₀' := h₀
rw [← norm_ne_zero_iff, Ne, ← @ofReal_eq_zero 𝕜] at h₀'
constructor <;> intro h
· have : x = 0 ∨ y = (⟪x, y⟫ / ⟪x, x⟫ : 𝕜) • x :=
((@norm_inner_eq_norm_tfae 𝕜 _ _ _ _ x y).out 0 1).1 (by simp [h])
rw [this.resolve_left h₀, h]
simp [norm_smul, inner_self_ofReal_norm, mul_div_cancel_right₀ _ h₀']
· conv_lhs => rw [← h, inner_smul_right, inner_self_eq_norm_sq_to_K]
field_simp [sq, mul_left_comm]
#align inner_eq_norm_mul_iff_div inner_eq_norm_mul_iff_div
/-- If the inner product of two vectors is equal to the product of their norms (i.e.,
`⟪x, y⟫ = ‖x‖ * ‖y‖`), then the two vectors are nonnegative real multiples of each other. One form
of the equality case for Cauchy-Schwarz.
Compare `norm_inner_eq_norm_iff`, which takes the weaker hypothesis `abs ⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem inner_eq_norm_mul_iff {x y : E} :
⟪x, y⟫ = (‖x‖ : 𝕜) * ‖y‖ ↔ (‖y‖ : 𝕜) • x = (‖x‖ : 𝕜) • y := by
rcases eq_or_ne x 0 with (rfl | h₀)
· simp
· rw [inner_eq_norm_mul_iff_div h₀, div_eq_inv_mul, mul_smul, inv_smul_eq_iff₀]
rwa [Ne, ofReal_eq_zero, norm_eq_zero]
#align inner_eq_norm_mul_iff inner_eq_norm_mul_iff
/-- If the inner product of two vectors is equal to the product of their norms (i.e.,
`⟪x, y⟫ = ‖x‖ * ‖y‖`), then the two vectors are nonnegative real multiples of each other. One form
of the equality case for Cauchy-Schwarz.
Compare `norm_inner_eq_norm_iff`, which takes the weaker hypothesis `abs ⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem inner_eq_norm_mul_iff_real {x y : F} : ⟪x, y⟫_ℝ = ‖x‖ * ‖y‖ ↔ ‖y‖ • x = ‖x‖ • y :=
inner_eq_norm_mul_iff
#align inner_eq_norm_mul_iff_real inner_eq_norm_mul_iff_real
/-- The inner product of two vectors, divided by the product of their
norms, has value 1 if and only if they are nonzero and one is
a positive multiple of the other. -/
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 1,677 | 1,686 | theorem real_inner_div_norm_mul_norm_eq_one_iff (x y : F) :
⟪x, y⟫_ℝ / (‖x‖ * ‖y‖) = 1 ↔ x ≠ 0 ∧ ∃ r : ℝ, 0 < r ∧ y = r • x := by |
constructor
· intro h
have hx₀ : x ≠ 0 := fun h₀ => by simp [h₀] at h
have hy₀ : y ≠ 0 := fun h₀ => by simp [h₀] at h
refine ⟨hx₀, ‖y‖ / ‖x‖, div_pos (norm_pos_iff.2 hy₀) (norm_pos_iff.2 hx₀), ?_⟩
exact ((inner_eq_norm_mul_iff_div hx₀).1 (eq_of_div_eq_one h)).symm
· rintro ⟨hx, ⟨r, ⟨hr, rfl⟩⟩⟩
exact real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul hx hr
|
/-
Copyright (c) 2022 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.ModelTheory.Semantics
#align_import model_theory.order from "leanprover-community/mathlib"@"1ed3a113dbc6f5b33eae3b96211d4e26ca3a5e9d"
/-!
# Ordered First-Ordered Structures
This file defines ordered first-order languages and structures, as well as their theories.
## Main Definitions
* `FirstOrder.Language.order` is the language consisting of a single relation representing `≤`.
* `FirstOrder.Language.orderStructure` is the structure on an ordered type, assigning the symbol
representing `≤` to the actual relation `≤`.
* `FirstOrder.Language.IsOrdered` points out a specific symbol in a language as representing `≤`.
* `FirstOrder.Language.OrderedStructure` indicates that the `≤` symbol in an ordered language
is interpreted as the actual relation `≤` in a particular structure.
* `FirstOrder.Language.linearOrderTheory` and similar define the theories of preorders,
partial orders, and linear orders.
* `FirstOrder.Language.dlo` defines the theory of dense linear orders without endpoints, a
particularly useful example in model theory.
## Main Results
* `PartialOrder`s model the theory of partial orders, `LinearOrder`s model the theory of
linear orders, and dense linear orders without endpoints model `Language.dlo`.
-/
universe u v w w'
namespace FirstOrder
namespace Language
set_option linter.uppercaseLean3 false
open FirstOrder Structure
variable {L : Language.{u, v}} {α : Type w} {M : Type w'} {n : ℕ}
/-- The language consisting of a single relation representing `≤`. -/
protected def order : Language :=
Language.mk₂ Empty Empty Empty Empty Unit
#align first_order.language.order FirstOrder.Language.order
instance orderStructure [LE M] : Language.order.Structure M :=
Structure.mk₂ Empty.elim Empty.elim Empty.elim Empty.elim fun _ => (· ≤ ·)
#align first_order.language.order_Structure FirstOrder.Language.orderStructure
namespace Order
instance Language.instIsRelational : IsRelational Language.order :=
Language.isRelational_mk₂
#align first_order.language.order.first_order.language.is_relational FirstOrder.Language.Order.Language.instIsRelational
instance Language.instSubsingleton : Subsingleton (Language.order.Relations n) :=
Language.subsingleton_mk₂_relations
#align first_order.language.order.relations.subsingleton FirstOrder.Language.Order.Language.instSubsingleton
end Order
/-- A language is ordered if it has a symbol representing `≤`. -/
class IsOrdered (L : Language.{u, v}) where
leSymb : L.Relations 2
#align first_order.language.is_ordered FirstOrder.Language.IsOrdered
export IsOrdered (leSymb)
section IsOrdered
variable [IsOrdered L]
/-- Joins two terms `t₁, t₂` in a formula representing `t₁ ≤ t₂`. -/
def Term.le (t₁ t₂ : L.Term (Sum α (Fin n))) : L.BoundedFormula α n :=
leSymb.boundedFormula₂ t₁ t₂
#align first_order.language.term.le FirstOrder.Language.Term.le
/-- Joins two terms `t₁, t₂` in a formula representing `t₁ < t₂`. -/
def Term.lt (t₁ t₂ : L.Term (Sum α (Fin n))) : L.BoundedFormula α n :=
t₁.le t₂ ⊓ ∼(t₂.le t₁)
#align first_order.language.term.lt FirstOrder.Language.Term.lt
variable (L)
/-- The language homomorphism sending the unique symbol `≤` of `Language.order` to `≤` in an ordered
language. -/
def orderLHom : Language.order →ᴸ L :=
LHom.mk₂ Empty.elim Empty.elim Empty.elim Empty.elim fun _ => leSymb
#align first_order.language.order_Lhom FirstOrder.Language.orderLHom
end IsOrdered
instance : IsOrdered Language.order :=
⟨Unit.unit⟩
@[simp]
theorem orderLHom_leSymb [L.IsOrdered] :
(orderLHom L).onRelation leSymb = (leSymb : L.Relations 2) :=
rfl
#align first_order.language.order_Lhom_le_symb FirstOrder.Language.orderLHom_leSymb
@[simp]
theorem orderLHom_order : orderLHom Language.order = LHom.id Language.order :=
LHom.funext (Subsingleton.elim _ _) (Subsingleton.elim _ _)
#align first_order.language.order_Lhom_order FirstOrder.Language.orderLHom_order
instance sum.instIsOrdered : IsOrdered (L.sum Language.order) :=
⟨Sum.inr IsOrdered.leSymb⟩
#align first_order.language.sum.is_ordered FirstOrder.Language.sum.instIsOrdered
section
variable (L) [IsOrdered L]
/-- The theory of preorders. -/
def preorderTheory : L.Theory :=
{leSymb.reflexive, leSymb.transitive}
#align first_order.language.preorder_theory FirstOrder.Language.preorderTheory
/-- The theory of partial orders. -/
def partialOrderTheory : L.Theory :=
{leSymb.reflexive, leSymb.antisymmetric, leSymb.transitive}
#align first_order.language.partial_order_theory FirstOrder.Language.partialOrderTheory
/-- The theory of linear orders. -/
def linearOrderTheory : L.Theory :=
{leSymb.reflexive, leSymb.antisymmetric, leSymb.transitive, leSymb.total}
#align first_order.language.linear_order_theory FirstOrder.Language.linearOrderTheory
/-- A sentence indicating that an order has no top element:
$\forall x, \exists y, \neg y \le x$. -/
def noTopOrderSentence : L.Sentence :=
∀'∃'∼((&1).le &0)
#align first_order.language.no_top_order_sentence FirstOrder.Language.noTopOrderSentence
/-- A sentence indicating that an order has no bottom element:
$\forall x, \exists y, \neg x \le y$. -/
def noBotOrderSentence : L.Sentence :=
∀'∃'∼((&0).le &1)
#align first_order.language.no_bot_order_sentence FirstOrder.Language.noBotOrderSentence
/-- A sentence indicating that an order is dense:
$\forall x, \forall y, x < y \to \exists z, x < z \wedge z < y$. -/
def denselyOrderedSentence : L.Sentence :=
∀'∀'((&0).lt &1 ⟹ ∃'((&0).lt &2 ⊓ (&2).lt &1))
#align first_order.language.densely_ordered_sentence FirstOrder.Language.denselyOrderedSentence
/-- The theory of dense linear orders without endpoints. -/
def dlo : L.Theory :=
L.linearOrderTheory ∪ {L.noTopOrderSentence, L.noBotOrderSentence, L.denselyOrderedSentence}
#align first_order.language.DLO FirstOrder.Language.dlo
end
variable (L M)
/-- A structure is ordered if its language has a `≤` symbol whose interpretation is -/
abbrev OrderedStructure [IsOrdered L] [LE M] [L.Structure M] : Prop :=
LHom.IsExpansionOn (orderLHom L) M
#align first_order.language.ordered_structure FirstOrder.Language.OrderedStructure
variable {L M}
@[simp]
theorem orderedStructure_iff [IsOrdered L] [LE M] [L.Structure M] :
L.OrderedStructure M ↔ LHom.IsExpansionOn (orderLHom L) M :=
Iff.rfl
#align first_order.language.ordered_structure_iff FirstOrder.Language.orderedStructure_iff
instance orderedStructure_LE [LE M] : OrderedStructure Language.order M := by
rw [orderedStructure_iff, orderLHom_order]
exact LHom.id_isExpansionOn M
#align first_order.language.ordered_structure_has_le FirstOrder.Language.orderedStructure_LE
instance model_preorder [Preorder M] : M ⊨ Language.order.preorderTheory := by
simp only [preorderTheory, Theory.model_iff, Set.mem_insert_iff, Set.mem_singleton_iff,
forall_eq_or_imp, Relations.realize_reflexive, relMap_apply₂, forall_eq,
Relations.realize_transitive]
exact ⟨le_refl, fun _ _ _ => le_trans⟩
#align first_order.language.model_preorder FirstOrder.Language.model_preorder
instance model_partialOrder [PartialOrder M] : M ⊨ Language.order.partialOrderTheory := by
simp only [partialOrderTheory, Theory.model_iff, Set.mem_insert_iff, Set.mem_singleton_iff,
forall_eq_or_imp, Relations.realize_reflexive, relMap_apply₂, Relations.realize_antisymmetric,
forall_eq, Relations.realize_transitive]
exact ⟨le_refl, fun _ _ => le_antisymm, fun _ _ _ => le_trans⟩
#align first_order.language.model_partial_order FirstOrder.Language.model_partialOrder
instance model_linearOrder [LinearOrder M] : M ⊨ Language.order.linearOrderTheory := by
simp only [linearOrderTheory, Theory.model_iff, Set.mem_insert_iff, Set.mem_singleton_iff,
forall_eq_or_imp, Relations.realize_reflexive, relMap_apply₂, Relations.realize_antisymmetric,
Relations.realize_transitive, forall_eq, Relations.realize_total]
exact ⟨le_refl, fun _ _ => le_antisymm, fun _ _ _ => le_trans, le_total⟩
#align first_order.language.model_linear_order FirstOrder.Language.model_linearOrder
section OrderedStructure
variable [IsOrdered L] [L.Structure M]
@[simp]
theorem relMap_leSymb [LE M] [L.OrderedStructure M] {a b : M} :
RelMap (leSymb : L.Relations 2) ![a, b] ↔ a ≤ b := by
rw [← orderLHom_leSymb, LHom.map_onRelation]
rfl
#align first_order.language.rel_map_le_symb FirstOrder.Language.relMap_leSymb
@[simp]
theorem Term.realize_le [LE M] [L.OrderedStructure M] {t₁ t₂ : L.Term (Sum α (Fin n))} {v : α → M}
{xs : Fin n → M} :
(t₁.le t₂).Realize v xs ↔ t₁.realize (Sum.elim v xs) ≤ t₂.realize (Sum.elim v xs) := by
simp [Term.le]
#align first_order.language.term.realize_le FirstOrder.Language.Term.realize_le
@[simp]
| Mathlib/ModelTheory/Order.lean | 219 | 222 | theorem Term.realize_lt [Preorder M] [L.OrderedStructure M] {t₁ t₂ : L.Term (Sum α (Fin n))}
{v : α → M} {xs : Fin n → M} :
(t₁.lt t₂).Realize v xs ↔ t₁.realize (Sum.elim v xs) < t₂.realize (Sum.elim v xs) := by |
simp [Term.lt, lt_iff_le_not_le]
|
/-
Copyright (c) 2020 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.Group.Subgroup.Basic
import Mathlib.Data.Countable.Basic
import Mathlib.Data.Set.Image
import Mathlib.Data.Set.Subsingleton
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.GroupTheory.Subgroup.Centralizer
#align_import group_theory.subgroup.zpowers from "leanprover-community/mathlib"@"4be589053caf347b899a494da75410deb55fb3ef"
/-!
# Subgroups generated by an element
## Tags
subgroup, subgroups
-/
variable {G : Type*} [Group G]
variable {A : Type*} [AddGroup A]
variable {N : Type*} [Group N]
namespace Subgroup
/-- The subgroup generated by an element. -/
def zpowers (g : G) : Subgroup G :=
Subgroup.copy (zpowersHom G g).range (Set.range (g ^ · : ℤ → G)) rfl
#align subgroup.zpowers Subgroup.zpowers
theorem mem_zpowers (g : G) : g ∈ zpowers g :=
⟨1, zpow_one _⟩
#align subgroup.mem_zpowers Subgroup.mem_zpowers
theorem coe_zpowers (g : G) : ↑(zpowers g) = Set.range (g ^ · : ℤ → G) :=
rfl
#align subgroup.coe_zpowers Subgroup.coe_zpowers
noncomputable instance decidableMemZPowers {a : G} : DecidablePred (· ∈ Subgroup.zpowers a) :=
Classical.decPred _
#align decidable_zpowers Subgroup.decidableMemZPowers
theorem zpowers_eq_closure (g : G) : zpowers g = closure {g} := by
ext
exact mem_closure_singleton.symm
#align subgroup.zpowers_eq_closure Subgroup.zpowers_eq_closure
theorem range_zpowersHom (g : G) : (zpowersHom G g).range = zpowers g :=
rfl
#align subgroup.range_zpowers_hom Subgroup.range_zpowersHom
theorem mem_zpowers_iff {g h : G} : h ∈ zpowers g ↔ ∃ k : ℤ, g ^ k = h :=
Iff.rfl
#align subgroup.mem_zpowers_iff Subgroup.mem_zpowers_iff
theorem zpow_mem_zpowers (g : G) (k : ℤ) : g ^ k ∈ zpowers g :=
mem_zpowers_iff.mpr ⟨k, rfl⟩
#align subgroup.zpow_mem_zpowers Subgroup.zpow_mem_zpowers
theorem npow_mem_zpowers (g : G) (k : ℕ) : g ^ k ∈ zpowers g :=
zpow_natCast g k ▸ zpow_mem_zpowers g k
#align subgroup.npow_mem_zpowers Subgroup.npow_mem_zpowers
theorem forall_zpowers {x : G} {p : zpowers x → Prop} : (∀ g, p g) ↔ ∀ m : ℤ, p ⟨x ^ m, m, rfl⟩ :=
Set.forall_subtype_range_iff
#align subgroup.forall_zpowers Subgroup.forall_zpowers
theorem exists_zpowers {x : G} {p : zpowers x → Prop} : (∃ g, p g) ↔ ∃ m : ℤ, p ⟨x ^ m, m, rfl⟩ :=
Set.exists_subtype_range_iff
#align subgroup.exists_zpowers Subgroup.exists_zpowers
theorem forall_mem_zpowers {x : G} {p : G → Prop} : (∀ g ∈ zpowers x, p g) ↔ ∀ m : ℤ, p (x ^ m) :=
Set.forall_mem_range
#align subgroup.forall_mem_zpowers Subgroup.forall_mem_zpowers
theorem exists_mem_zpowers {x : G} {p : G → Prop} : (∃ g ∈ zpowers x, p g) ↔ ∃ m : ℤ, p (x ^ m) :=
Set.exists_range_iff
#align subgroup.exists_mem_zpowers Subgroup.exists_mem_zpowers
instance (a : G) : Countable (zpowers a) :=
((zpowersHom G a).rangeRestrict_surjective.comp Multiplicative.ofAdd.surjective).countable
end Subgroup
namespace AddSubgroup
/-- The subgroup generated by an element. -/
def zmultiples (a : A) : AddSubgroup A :=
AddSubgroup.copy (zmultiplesHom A a).range (Set.range ((· • a) : ℤ → A)) rfl
#align add_subgroup.zmultiples AddSubgroup.zmultiples
@[simp]
theorem range_zmultiplesHom (a : A) : (zmultiplesHom A a).range = zmultiples a :=
rfl
#align add_subgroup.range_zmultiples_hom AddSubgroup.range_zmultiplesHom
attribute [to_additive existing] Subgroup.zpowers
attribute [to_additive (attr := simp)] Subgroup.mem_zpowers
#align add_subgroup.mem_zmultiples AddSubgroup.mem_zmultiples
attribute [to_additive (attr := norm_cast)] Subgroup.coe_zpowers
attribute [to_additive] Subgroup.decidableMemZPowers
#align decidable_zmultiples AddSubgroup.decidableMemZMultiples
attribute [to_additive] Subgroup.zpowers_eq_closure
#align add_subgroup.zmultiples_eq_closure AddSubgroup.zmultiples_eq_closure
attribute [to_additive existing (attr := simp)]
Subgroup.range_zpowersHom
attribute [to_additive] Subgroup.mem_zpowers_iff
#align add_subgroup.mem_zmultiples_iff AddSubgroup.mem_zmultiples_iff
attribute [to_additive (attr := simp)] Subgroup.zpow_mem_zpowers
#align add_subgroup.zsmul_mem_zmultiples AddSubgroup.zsmul_mem_zmultiples
attribute [to_additive (attr := simp)] Subgroup.npow_mem_zpowers
#align add_subgroup.nsmul_mem_zmultiples AddSubgroup.nsmul_mem_zmultiples
-- Porting note: increasing simp priority. Better lemma than `Subtype.forall`
attribute [to_additive (attr := simp 1100)] Subgroup.forall_zpowers
#align add_subgroup.forall_zmultiples AddSubgroup.forall_zmultiples
attribute [to_additive] Subgroup.forall_mem_zpowers
#align add_subgroup.forall_mem_zmultiples AddSubgroup.forall_mem_zmultiples
-- Porting note: increasing simp priority. Better lemma than `Subtype.exists`
attribute [to_additive (attr := simp 1100)] Subgroup.exists_zpowers
#align add_subgroup.exists_zmultiples AddSubgroup.exists_zmultiples
attribute [to_additive] Subgroup.exists_mem_zpowers
#align add_subgroup.exists_mem_zmultiples AddSubgroup.exists_mem_zmultiples
instance (a : A) : Countable (zmultiples a) :=
(zmultiplesHom A a).rangeRestrict_surjective.countable
section Ring
variable {R : Type*} [Ring R] (r : R) (k : ℤ)
@[simp]
theorem intCast_mul_mem_zmultiples : ↑(k : ℤ) * r ∈ zmultiples r := by
simpa only [← zsmul_eq_mul] using zsmul_mem_zmultiples r k
#align add_subgroup.int_cast_mul_mem_zmultiples AddSubgroup.intCast_mul_mem_zmultiples
@[deprecated (since := "2024-04-17")]
alias int_cast_mul_mem_zmultiples := intCast_mul_mem_zmultiples
@[simp]
theorem intCast_mem_zmultiples_one : ↑(k : ℤ) ∈ zmultiples (1 : R) :=
mem_zmultiples_iff.mp ⟨k, by simp⟩
#align add_subgroup.int_cast_mem_zmultiples_one AddSubgroup.intCast_mem_zmultiples_one
@[deprecated (since := "2024-04-17")]
alias int_cast_mem_zmultiples_one := intCast_mem_zmultiples_one
end Ring
end AddSubgroup
@[simp] lemma Int.range_castAddHom {A : Type*} [AddGroupWithOne A] :
(Int.castAddHom A).range = AddSubgroup.zmultiples 1 := by
ext a
simp_rw [AddMonoidHom.mem_range, Int.coe_castAddHom, AddSubgroup.mem_zmultiples_iff, zsmul_one]
@[to_additive (attr := simp)]
| Mathlib/Algebra/Group/Subgroup/ZPowers.lean | 173 | 175 | theorem MonoidHom.map_zpowers (f : G →* N) (x : G) :
(Subgroup.zpowers x).map f = Subgroup.zpowers (f x) := by |
rw [Subgroup.zpowers_eq_closure, Subgroup.zpowers_eq_closure, f.map_closure, Set.image_singleton]
|
/-
Copyright (c) 2021 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Gabin Kolly
-/
import Mathlib.Order.Closure
import Mathlib.ModelTheory.Semantics
import Mathlib.ModelTheory.Encoding
#align_import model_theory.substructures from "leanprover-community/mathlib"@"0602c59878ff3d5f71dea69c2d32ccf2e93e5398"
/-!
# First-Order Substructures
This file defines substructures of first-order structures in a similar manner to the various
substructures appearing in the algebra library.
## Main Definitions
* A `FirstOrder.Language.Substructure` is defined so that `L.Substructure M` is the type of all
substructures of the `L`-structure `M`.
* `FirstOrder.Language.Substructure.closure` is defined so that if `s : Set M`, `closure L s` is
the least substructure of `M` containing `s`.
* `FirstOrder.Language.Substructure.comap` is defined so that `s.comap f` is the preimage of the
substructure `s` under the homomorphism `f`, as a substructure.
* `FirstOrder.Language.Substructure.map` is defined so that `s.map f` is the image of the
substructure `s` under the homomorphism `f`, as a substructure.
* `FirstOrder.Language.Hom.range` is defined so that `f.range` is the range of the
homomorphism `f`, as a substructure.
* `FirstOrder.Language.Hom.domRestrict` and `FirstOrder.Language.Hom.codRestrict` restrict
the domain and codomain respectively of first-order homomorphisms to substructures.
* `FirstOrder.Language.Embedding.domRestrict` and `FirstOrder.Language.Embedding.codRestrict`
restrict the domain and codomain respectively of first-order embeddings to substructures.
* `FirstOrder.Language.Substructure.inclusion` is the inclusion embedding between substructures.
## Main Results
* `L.Substructure M` forms a `CompleteLattice`.
-/
universe u v w
namespace FirstOrder
namespace Language
variable {L : Language.{u, v}} {M : Type w} {N P : Type*}
variable [L.Structure M] [L.Structure N] [L.Structure P]
open FirstOrder Cardinal
open Structure Cardinal
section ClosedUnder
open Set
variable {n : ℕ} (f : L.Functions n) (s : Set M)
/-- Indicates that a set in a given structure is a closed under a function symbol. -/
def ClosedUnder : Prop :=
∀ x : Fin n → M, (∀ i : Fin n, x i ∈ s) → funMap f x ∈ s
#align first_order.language.closed_under FirstOrder.Language.ClosedUnder
variable (L)
@[simp]
theorem closedUnder_univ : ClosedUnder f (univ : Set M) := fun _ _ => mem_univ _
#align first_order.language.closed_under_univ FirstOrder.Language.closedUnder_univ
variable {L f s} {t : Set M}
namespace ClosedUnder
theorem inter (hs : ClosedUnder f s) (ht : ClosedUnder f t) : ClosedUnder f (s ∩ t) := fun x h =>
mem_inter (hs x fun i => mem_of_mem_inter_left (h i)) (ht x fun i => mem_of_mem_inter_right (h i))
#align first_order.language.closed_under.inter FirstOrder.Language.ClosedUnder.inter
theorem inf (hs : ClosedUnder f s) (ht : ClosedUnder f t) : ClosedUnder f (s ⊓ t) :=
hs.inter ht
#align first_order.language.closed_under.inf FirstOrder.Language.ClosedUnder.inf
variable {S : Set (Set M)}
theorem sInf (hS : ∀ s, s ∈ S → ClosedUnder f s) : ClosedUnder f (sInf S) := fun x h s hs =>
hS s hs x fun i => h i s hs
#align first_order.language.closed_under.Inf FirstOrder.Language.ClosedUnder.sInf
end ClosedUnder
end ClosedUnder
variable (L) (M)
/-- A substructure of a structure `M` is a set closed under application of function symbols. -/
structure Substructure where
carrier : Set M
fun_mem : ∀ {n}, ∀ f : L.Functions n, ClosedUnder f carrier
#align first_order.language.substructure FirstOrder.Language.Substructure
#align first_order.language.substructure.carrier FirstOrder.Language.Substructure.carrier
#align first_order.language.substructure.fun_mem FirstOrder.Language.Substructure.fun_mem
variable {L} {M}
namespace Substructure
attribute [coe] Substructure.carrier
instance instSetLike : SetLike (L.Substructure M) M :=
⟨Substructure.carrier, fun p q h => by cases p; cases q; congr⟩
#align first_order.language.substructure.set_like FirstOrder.Language.Substructure.instSetLike
/-- See Note [custom simps projection] -/
def Simps.coe (S : L.Substructure M) : Set M :=
S
#align first_order.language.substructure.simps.coe FirstOrder.Language.Substructure.Simps.coe
initialize_simps_projections Substructure (carrier → coe)
@[simp]
theorem mem_carrier {s : L.Substructure M} {x : M} : x ∈ s.carrier ↔ x ∈ s :=
Iff.rfl
#align first_order.language.substructure.mem_carrier FirstOrder.Language.Substructure.mem_carrier
/-- Two substructures are equal if they have the same elements. -/
@[ext]
theorem ext {S T : L.Substructure M} (h : ∀ x, x ∈ S ↔ x ∈ T) : S = T :=
SetLike.ext h
#align first_order.language.substructure.ext FirstOrder.Language.Substructure.ext
/-- Copy a substructure replacing `carrier` with a set that is equal to it. -/
protected def copy (S : L.Substructure M) (s : Set M) (hs : s = S) : L.Substructure M where
carrier := s
fun_mem _ f := hs.symm ▸ S.fun_mem _ f
#align first_order.language.substructure.copy FirstOrder.Language.Substructure.copy
end Substructure
variable {S : L.Substructure M}
theorem Term.realize_mem {α : Type*} (t : L.Term α) (xs : α → M) (h : ∀ a, xs a ∈ S) :
t.realize xs ∈ S := by
induction' t with a n f ts ih
· exact h a
· exact Substructure.fun_mem _ _ _ ih
#align first_order.language.term.realize_mem FirstOrder.Language.Term.realize_mem
namespace Substructure
@[simp]
theorem coe_copy {s : Set M} (hs : s = S) : (S.copy s hs : Set M) = s :=
rfl
#align first_order.language.substructure.coe_copy FirstOrder.Language.Substructure.coe_copy
theorem copy_eq {s : Set M} (hs : s = S) : S.copy s hs = S :=
SetLike.coe_injective hs
#align first_order.language.substructure.copy_eq FirstOrder.Language.Substructure.copy_eq
theorem constants_mem (c : L.Constants) : (c : M) ∈ S :=
mem_carrier.2 (S.fun_mem c _ finZeroElim)
#align first_order.language.substructure.constants_mem FirstOrder.Language.Substructure.constants_mem
/-- The substructure `M` of the structure `M`. -/
instance instTop : Top (L.Substructure M) :=
⟨{ carrier := Set.univ
fun_mem := fun {_} _ _ _ => Set.mem_univ _ }⟩
#align first_order.language.substructure.has_top FirstOrder.Language.Substructure.instTop
instance instInhabited : Inhabited (L.Substructure M) :=
⟨⊤⟩
#align first_order.language.substructure.inhabited FirstOrder.Language.Substructure.instInhabited
@[simp]
theorem mem_top (x : M) : x ∈ (⊤ : L.Substructure M) :=
Set.mem_univ x
#align first_order.language.substructure.mem_top FirstOrder.Language.Substructure.mem_top
@[simp]
theorem coe_top : ((⊤ : L.Substructure M) : Set M) = Set.univ :=
rfl
#align first_order.language.substructure.coe_top FirstOrder.Language.Substructure.coe_top
/-- The inf of two substructures is their intersection. -/
instance instInf : Inf (L.Substructure M) :=
⟨fun S₁ S₂ =>
{ carrier := (S₁ : Set M) ∩ (S₂ : Set M)
fun_mem := fun {_} f => (S₁.fun_mem f).inf (S₂.fun_mem f) }⟩
#align first_order.language.substructure.has_inf FirstOrder.Language.Substructure.instInf
@[simp]
theorem coe_inf (p p' : L.Substructure M) :
((p ⊓ p' : L.Substructure M) : Set M) = (p : Set M) ∩ (p' : Set M) :=
rfl
#align first_order.language.substructure.coe_inf FirstOrder.Language.Substructure.coe_inf
@[simp]
theorem mem_inf {p p' : L.Substructure M} {x : M} : x ∈ p ⊓ p' ↔ x ∈ p ∧ x ∈ p' :=
Iff.rfl
#align first_order.language.substructure.mem_inf FirstOrder.Language.Substructure.mem_inf
instance instInfSet : InfSet (L.Substructure M) :=
⟨fun s =>
{ carrier := ⋂ t ∈ s, (t : Set M)
fun_mem := fun {n} f =>
ClosedUnder.sInf
(by
rintro _ ⟨t, rfl⟩
by_cases h : t ∈ s
· simpa [h] using t.fun_mem f
· simp [h]) }⟩
#align first_order.language.substructure.has_Inf FirstOrder.Language.Substructure.instInfSet
@[simp, norm_cast]
theorem coe_sInf (S : Set (L.Substructure M)) :
((sInf S : L.Substructure M) : Set M) = ⋂ s ∈ S, (s : Set M) :=
rfl
#align first_order.language.substructure.coe_Inf FirstOrder.Language.Substructure.coe_sInf
theorem mem_sInf {S : Set (L.Substructure M)} {x : M} : x ∈ sInf S ↔ ∀ p ∈ S, x ∈ p :=
Set.mem_iInter₂
#align first_order.language.substructure.mem_Inf FirstOrder.Language.Substructure.mem_sInf
theorem mem_iInf {ι : Sort*} {S : ι → L.Substructure M} {x : M} :
(x ∈ ⨅ i, S i) ↔ ∀ i, x ∈ S i := by simp only [iInf, mem_sInf, Set.forall_mem_range]
#align first_order.language.substructure.mem_infi FirstOrder.Language.Substructure.mem_iInf
@[simp, norm_cast]
theorem coe_iInf {ι : Sort*} {S : ι → L.Substructure M} :
((⨅ i, S i : L.Substructure M) : Set M) = ⋂ i, (S i : Set M) := by
simp only [iInf, coe_sInf, Set.biInter_range]
#align first_order.language.substructure.coe_infi FirstOrder.Language.Substructure.coe_iInf
/-- Substructures of a structure form a complete lattice. -/
instance instCompleteLattice : CompleteLattice (L.Substructure M) :=
{ completeLatticeOfInf (L.Substructure M) fun _ =>
IsGLB.of_image
(fun {S T : L.Substructure M} => show (S : Set M) ≤ T ↔ S ≤ T from SetLike.coe_subset_coe)
isGLB_biInf with
le := (· ≤ ·)
lt := (· < ·)
top := ⊤
le_top := fun _ x _ => mem_top x
inf := (· ⊓ ·)
sInf := InfSet.sInf
le_inf := fun _a _b _c ha hb _x hx => ⟨ha hx, hb hx⟩
inf_le_left := fun _ _ _ => And.left
inf_le_right := fun _ _ _ => And.right }
#align first_order.language.substructure.complete_lattice FirstOrder.Language.Substructure.instCompleteLattice
variable (L)
/-- The `L.Substructure` generated by a set. -/
def closure : LowerAdjoint ((↑) : L.Substructure M → Set M) :=
⟨fun s => sInf { S | s ⊆ S }, fun _ _ =>
⟨Set.Subset.trans fun _x hx => mem_sInf.2 fun _S hS => hS hx, fun h => sInf_le h⟩⟩
#align first_order.language.substructure.closure FirstOrder.Language.Substructure.closure
variable {L} {s : Set M}
theorem mem_closure {x : M} : x ∈ closure L s ↔ ∀ S : L.Substructure M, s ⊆ S → x ∈ S :=
mem_sInf
#align first_order.language.substructure.mem_closure FirstOrder.Language.Substructure.mem_closure
/-- The substructure generated by a set includes the set. -/
@[simp]
theorem subset_closure : s ⊆ closure L s :=
(closure L).le_closure s
#align first_order.language.substructure.subset_closure FirstOrder.Language.Substructure.subset_closure
theorem not_mem_of_not_mem_closure {P : M} (hP : P ∉ closure L s) : P ∉ s := fun h =>
hP (subset_closure h)
#align first_order.language.substructure.not_mem_of_not_mem_closure FirstOrder.Language.Substructure.not_mem_of_not_mem_closure
@[simp]
theorem closed (S : L.Substructure M) : (closure L).closed (S : Set M) :=
congr rfl ((closure L).eq_of_le Set.Subset.rfl fun _x xS => mem_closure.2 fun _T hT => hT xS)
#align first_order.language.substructure.closed FirstOrder.Language.Substructure.closed
open Set
/-- A substructure `S` includes `closure L s` if and only if it includes `s`. -/
@[simp]
theorem closure_le : closure L s ≤ S ↔ s ⊆ S :=
(closure L).closure_le_closed_iff_le s S.closed
#align first_order.language.substructure.closure_le FirstOrder.Language.Substructure.closure_le
/-- Substructure closure of a set is monotone in its argument: if `s ⊆ t`,
then `closure L s ≤ closure L t`. -/
theorem closure_mono ⦃s t : Set M⦄ (h : s ⊆ t) : closure L s ≤ closure L t :=
(closure L).monotone h
#align first_order.language.substructure.closure_mono FirstOrder.Language.Substructure.closure_mono
theorem closure_eq_of_le (h₁ : s ⊆ S) (h₂ : S ≤ closure L s) : closure L s = S :=
(closure L).eq_of_le h₁ h₂
#align first_order.language.substructure.closure_eq_of_le FirstOrder.Language.Substructure.closure_eq_of_le
theorem coe_closure_eq_range_term_realize :
(closure L s : Set M) = range (@Term.realize L _ _ _ ((↑) : s → M)) := by
let S : L.Substructure M := ⟨range (Term.realize (L := L) ((↑) : s → M)), fun {n} f x hx => by
simp only [mem_range] at *
refine ⟨func f fun i => Classical.choose (hx i), ?_⟩
simp only [Term.realize, fun i => Classical.choose_spec (hx i)]⟩
change _ = (S : Set M)
rw [← SetLike.ext'_iff]
refine closure_eq_of_le (fun x hx => ⟨var ⟨x, hx⟩, rfl⟩) (le_sInf fun S' hS' => ?_)
rintro _ ⟨t, rfl⟩
exact t.realize_mem _ fun i => hS' i.2
#align first_order.language.substructure.coe_closure_eq_range_term_realize FirstOrder.Language.Substructure.coe_closure_eq_range_term_realize
instance small_closure [Small.{u} s] : Small.{u} (closure L s) := by
rw [← SetLike.coe_sort_coe, Substructure.coe_closure_eq_range_term_realize]
exact small_range _
#align first_order.language.substructure.small_closure FirstOrder.Language.Substructure.small_closure
theorem mem_closure_iff_exists_term {x : M} :
x ∈ closure L s ↔ ∃ t : L.Term s, t.realize ((↑) : s → M) = x := by
rw [← SetLike.mem_coe, coe_closure_eq_range_term_realize, mem_range]
#align first_order.language.substructure.mem_closure_iff_exists_term FirstOrder.Language.Substructure.mem_closure_iff_exists_term
theorem lift_card_closure_le_card_term : Cardinal.lift.{max u w} #(closure L s) ≤ #(L.Term s) := by
rw [← SetLike.coe_sort_coe, coe_closure_eq_range_term_realize]
rw [← Cardinal.lift_id'.{w, max u w} #(L.Term s)]
exact Cardinal.mk_range_le_lift
#align first_order.language.substructure.lift_card_closure_le_card_term FirstOrder.Language.Substructure.lift_card_closure_le_card_term
theorem lift_card_closure_le :
Cardinal.lift.{u, w} #(closure L s) ≤
max ℵ₀ (Cardinal.lift.{u, w} #s + Cardinal.lift.{w, u} #(Σi, L.Functions i)) := by
rw [← lift_umax]
refine lift_card_closure_le_card_term.trans (Term.card_le.trans ?_)
rw [mk_sum, lift_umax.{w, u}]
#align first_order.language.substructure.lift_card_closure_le FirstOrder.Language.Substructure.lift_card_closure_le
variable (L)
theorem _root_.Set.Countable.substructure_closure
[Countable (Σl, L.Functions l)] (h : s.Countable) : Countable.{w + 1} (closure L s) := by
haveI : Countable s := h.to_subtype
rw [← mk_le_aleph0_iff, ← lift_le_aleph0]
exact lift_card_closure_le_card_term.trans mk_le_aleph0
#align set.countable.substructure_closure Set.Countable.substructure_closure
variable {L} (S)
/-- An induction principle for closure membership. If `p` holds for all elements of `s`, and
is preserved under function symbols, then `p` holds for all elements of the closure of `s`. -/
@[elab_as_elim]
theorem closure_induction {p : M → Prop} {x} (h : x ∈ closure L s) (Hs : ∀ x ∈ s, p x)
(Hfun : ∀ {n : ℕ} (f : L.Functions n), ClosedUnder f (setOf p)) : p x :=
(@closure_le L M _ ⟨setOf p, fun {_} => Hfun⟩ _).2 Hs h
#align first_order.language.substructure.closure_induction FirstOrder.Language.Substructure.closure_induction
/-- If `s` is a dense set in a structure `M`, `Substructure.closure L s = ⊤`, then in order to prove
that some predicate `p` holds for all `x : M` it suffices to verify `p x` for `x ∈ s`, and verify
that `p` is preserved under function symbols. -/
@[elab_as_elim]
theorem dense_induction {p : M → Prop} (x : M) {s : Set M} (hs : closure L s = ⊤)
(Hs : ∀ x ∈ s, p x) (Hfun : ∀ {n : ℕ} (f : L.Functions n), ClosedUnder f (setOf p)) : p x := by
have : ∀ x ∈ closure L s, p x := fun x hx => closure_induction hx Hs fun {n} => Hfun
simpa [hs] using this x
#align first_order.language.substructure.dense_induction FirstOrder.Language.Substructure.dense_induction
variable (L) (M)
/-- `closure` forms a Galois insertion with the coercion to set. -/
protected def gi : GaloisInsertion (@closure L M _) (↑) where
choice s _ := closure L s
gc := (closure L).gc
le_l_u _ := subset_closure
choice_eq _ _ := rfl
#align first_order.language.substructure.gi FirstOrder.Language.Substructure.gi
variable {L} {M}
/-- Closure of a substructure `S` equals `S`. -/
@[simp]
theorem closure_eq : closure L (S : Set M) = S :=
(Substructure.gi L M).l_u_eq S
#align first_order.language.substructure.closure_eq FirstOrder.Language.Substructure.closure_eq
@[simp]
theorem closure_empty : closure L (∅ : Set M) = ⊥ :=
(Substructure.gi L M).gc.l_bot
#align first_order.language.substructure.closure_empty FirstOrder.Language.Substructure.closure_empty
@[simp]
theorem closure_univ : closure L (univ : Set M) = ⊤ :=
@coe_top L M _ ▸ closure_eq ⊤
#align first_order.language.substructure.closure_univ FirstOrder.Language.Substructure.closure_univ
theorem closure_union (s t : Set M) : closure L (s ∪ t) = closure L s ⊔ closure L t :=
(Substructure.gi L M).gc.l_sup
#align first_order.language.substructure.closure_union FirstOrder.Language.Substructure.closure_union
theorem closure_unionᵢ {ι} (s : ι → Set M) : closure L (⋃ i, s i) = ⨆ i, closure L (s i) :=
(Substructure.gi L M).gc.l_iSup
#align first_order.language.substructure.closure_Union FirstOrder.Language.Substructure.closure_unionᵢ
instance small_bot : Small.{u} (⊥ : L.Substructure M) := by
rw [← closure_empty]
haveI : Small.{u} (∅ : Set M) := small_subsingleton _
exact Substructure.small_closure
#align first_order.language.substructure.small_bot FirstOrder.Language.Substructure.small_bot
/-!
### `comap` and `map`
-/
/-- The preimage of a substructure along a homomorphism is a substructure. -/
@[simps]
def comap (φ : M →[L] N) (S : L.Substructure N) : L.Substructure M where
carrier := φ ⁻¹' S
fun_mem {n} f x hx := by
rw [mem_preimage, φ.map_fun]
exact S.fun_mem f (φ ∘ x) hx
#align first_order.language.substructure.comap FirstOrder.Language.Substructure.comap
#align first_order.language.substructure.comap_coe FirstOrder.Language.Substructure.comap_coe
@[simp]
theorem mem_comap {S : L.Substructure N} {f : M →[L] N} {x : M} : x ∈ S.comap f ↔ f x ∈ S :=
Iff.rfl
#align first_order.language.substructure.mem_comap FirstOrder.Language.Substructure.mem_comap
theorem comap_comap (S : L.Substructure P) (g : N →[L] P) (f : M →[L] N) :
(S.comap g).comap f = S.comap (g.comp f) :=
rfl
#align first_order.language.substructure.comap_comap FirstOrder.Language.Substructure.comap_comap
@[simp]
theorem comap_id (S : L.Substructure P) : S.comap (Hom.id _ _) = S :=
ext (by simp)
#align first_order.language.substructure.comap_id FirstOrder.Language.Substructure.comap_id
/-- The image of a substructure along a homomorphism is a substructure. -/
@[simps]
def map (φ : M →[L] N) (S : L.Substructure M) : L.Substructure N where
carrier := φ '' S
fun_mem {n} f x hx :=
(mem_image _ _ _).1
⟨funMap f fun i => Classical.choose (hx i),
S.fun_mem f _ fun i => (Classical.choose_spec (hx i)).1, by
simp only [Hom.map_fun, SetLike.mem_coe]
exact congr rfl (funext fun i => (Classical.choose_spec (hx i)).2)⟩
#align first_order.language.substructure.map FirstOrder.Language.Substructure.map
#align first_order.language.substructure.map_coe FirstOrder.Language.Substructure.map_coe
@[simp]
theorem mem_map {f : M →[L] N} {S : L.Substructure M} {y : N} :
y ∈ S.map f ↔ ∃ x ∈ S, f x = y :=
Iff.rfl
#align first_order.language.substructure.mem_map FirstOrder.Language.Substructure.mem_map
theorem mem_map_of_mem (f : M →[L] N) {S : L.Substructure M} {x : M} (hx : x ∈ S) : f x ∈ S.map f :=
mem_image_of_mem f hx
#align first_order.language.substructure.mem_map_of_mem FirstOrder.Language.Substructure.mem_map_of_mem
theorem apply_coe_mem_map (f : M →[L] N) (S : L.Substructure M) (x : S) : f x ∈ S.map f :=
mem_map_of_mem f x.prop
#align first_order.language.substructure.apply_coe_mem_map FirstOrder.Language.Substructure.apply_coe_mem_map
theorem map_map (g : N →[L] P) (f : M →[L] N) : (S.map f).map g = S.map (g.comp f) :=
SetLike.coe_injective <| image_image _ _ _
#align first_order.language.substructure.map_map FirstOrder.Language.Substructure.map_map
theorem map_le_iff_le_comap {f : M →[L] N} {S : L.Substructure M} {T : L.Substructure N} :
S.map f ≤ T ↔ S ≤ T.comap f :=
image_subset_iff
#align first_order.language.substructure.map_le_iff_le_comap FirstOrder.Language.Substructure.map_le_iff_le_comap
theorem gc_map_comap (f : M →[L] N) : GaloisConnection (map f) (comap f) := fun _ _ =>
map_le_iff_le_comap
#align first_order.language.substructure.gc_map_comap FirstOrder.Language.Substructure.gc_map_comap
theorem map_le_of_le_comap {T : L.Substructure N} {f : M →[L] N} : S ≤ T.comap f → S.map f ≤ T :=
(gc_map_comap f).l_le
#align first_order.language.substructure.map_le_of_le_comap FirstOrder.Language.Substructure.map_le_of_le_comap
theorem le_comap_of_map_le {T : L.Substructure N} {f : M →[L] N} : S.map f ≤ T → S ≤ T.comap f :=
(gc_map_comap f).le_u
#align first_order.language.substructure.le_comap_of_map_le FirstOrder.Language.Substructure.le_comap_of_map_le
theorem le_comap_map {f : M →[L] N} : S ≤ (S.map f).comap f :=
(gc_map_comap f).le_u_l _
#align first_order.language.substructure.le_comap_map FirstOrder.Language.Substructure.le_comap_map
theorem map_comap_le {S : L.Substructure N} {f : M →[L] N} : (S.comap f).map f ≤ S :=
(gc_map_comap f).l_u_le _
#align first_order.language.substructure.map_comap_le FirstOrder.Language.Substructure.map_comap_le
theorem monotone_map {f : M →[L] N} : Monotone (map f) :=
(gc_map_comap f).monotone_l
#align first_order.language.substructure.monotone_map FirstOrder.Language.Substructure.monotone_map
theorem monotone_comap {f : M →[L] N} : Monotone (comap f) :=
(gc_map_comap f).monotone_u
#align first_order.language.substructure.monotone_comap FirstOrder.Language.Substructure.monotone_comap
@[simp]
theorem map_comap_map {f : M →[L] N} : ((S.map f).comap f).map f = S.map f :=
(gc_map_comap f).l_u_l_eq_l _
#align first_order.language.substructure.map_comap_map FirstOrder.Language.Substructure.map_comap_map
@[simp]
theorem comap_map_comap {S : L.Substructure N} {f : M →[L] N} :
((S.comap f).map f).comap f = S.comap f :=
(gc_map_comap f).u_l_u_eq_u _
#align first_order.language.substructure.comap_map_comap FirstOrder.Language.Substructure.comap_map_comap
theorem map_sup (S T : L.Substructure M) (f : M →[L] N) : (S ⊔ T).map f = S.map f ⊔ T.map f :=
(gc_map_comap f).l_sup
#align first_order.language.substructure.map_sup FirstOrder.Language.Substructure.map_sup
theorem map_iSup {ι : Sort*} (f : M →[L] N) (s : ι → L.Substructure M) :
(iSup s).map f = ⨆ i, (s i).map f :=
(gc_map_comap f).l_iSup
#align first_order.language.substructure.map_supr FirstOrder.Language.Substructure.map_iSup
theorem comap_inf (S T : L.Substructure N) (f : M →[L] N) :
(S ⊓ T).comap f = S.comap f ⊓ T.comap f :=
(gc_map_comap f).u_inf
#align first_order.language.substructure.comap_inf FirstOrder.Language.Substructure.comap_inf
theorem comap_iInf {ι : Sort*} (f : M →[L] N) (s : ι → L.Substructure N) :
(iInf s).comap f = ⨅ i, (s i).comap f :=
(gc_map_comap f).u_iInf
#align first_order.language.substructure.comap_infi FirstOrder.Language.Substructure.comap_iInf
@[simp]
theorem map_bot (f : M →[L] N) : (⊥ : L.Substructure M).map f = ⊥ :=
(gc_map_comap f).l_bot
#align first_order.language.substructure.map_bot FirstOrder.Language.Substructure.map_bot
@[simp]
theorem comap_top (f : M →[L] N) : (⊤ : L.Substructure N).comap f = ⊤ :=
(gc_map_comap f).u_top
#align first_order.language.substructure.comap_top FirstOrder.Language.Substructure.comap_top
@[simp]
theorem map_id (S : L.Substructure M) : S.map (Hom.id L M) = S :=
ext fun _ => ⟨fun ⟨_, h, rfl⟩ => h, fun h => ⟨_, h, rfl⟩⟩
#align first_order.language.substructure.map_id FirstOrder.Language.Substructure.map_id
theorem map_closure (f : M →[L] N) (s : Set M) : (closure L s).map f = closure L (f '' s) :=
Eq.symm <|
closure_eq_of_le (Set.image_subset f subset_closure) <|
map_le_iff_le_comap.2 <| closure_le.2 fun x hx => subset_closure ⟨x, hx, rfl⟩
#align first_order.language.substructure.map_closure FirstOrder.Language.Substructure.map_closure
@[simp]
theorem closure_image (f : M →[L] N) : closure L (f '' s) = map f (closure L s) :=
(map_closure f s).symm
#align first_order.language.substructure.closure_image FirstOrder.Language.Substructure.closure_image
section GaloisCoinsertion
variable {ι : Type*} {f : M →[L] N} (hf : Function.Injective f)
/-- `map f` and `comap f` form a `GaloisCoinsertion` when `f` is injective. -/
def gciMapComap : GaloisCoinsertion (map f) (comap f) :=
(gc_map_comap f).toGaloisCoinsertion fun S x => by simp [mem_comap, mem_map, hf.eq_iff]
#align first_order.language.substructure.gci_map_comap FirstOrder.Language.Substructure.gciMapComap
theorem comap_map_eq_of_injective (S : L.Substructure M) : (S.map f).comap f = S :=
(gciMapComap hf).u_l_eq _
#align first_order.language.substructure.comap_map_eq_of_injective FirstOrder.Language.Substructure.comap_map_eq_of_injective
theorem comap_surjective_of_injective : Function.Surjective (comap f) :=
(gciMapComap hf).u_surjective
#align first_order.language.substructure.comap_surjective_of_injective FirstOrder.Language.Substructure.comap_surjective_of_injective
theorem map_injective_of_injective : Function.Injective (map f) :=
(gciMapComap hf).l_injective
#align first_order.language.substructure.map_injective_of_injective FirstOrder.Language.Substructure.map_injective_of_injective
theorem comap_inf_map_of_injective (S T : L.Substructure M) : (S.map f ⊓ T.map f).comap f = S ⊓ T :=
(gciMapComap hf).u_inf_l _ _
#align first_order.language.substructure.comap_inf_map_of_injective FirstOrder.Language.Substructure.comap_inf_map_of_injective
theorem comap_iInf_map_of_injective (S : ι → L.Substructure M) :
(⨅ i, (S i).map f).comap f = iInf S :=
(gciMapComap hf).u_iInf_l _
#align first_order.language.substructure.comap_infi_map_of_injective FirstOrder.Language.Substructure.comap_iInf_map_of_injective
theorem comap_sup_map_of_injective (S T : L.Substructure M) : (S.map f ⊔ T.map f).comap f = S ⊔ T :=
(gciMapComap hf).u_sup_l _ _
#align first_order.language.substructure.comap_sup_map_of_injective FirstOrder.Language.Substructure.comap_sup_map_of_injective
theorem comap_iSup_map_of_injective (S : ι → L.Substructure M) :
(⨆ i, (S i).map f).comap f = iSup S :=
(gciMapComap hf).u_iSup_l _
#align first_order.language.substructure.comap_supr_map_of_injective FirstOrder.Language.Substructure.comap_iSup_map_of_injective
theorem map_le_map_iff_of_injective {S T : L.Substructure M} : S.map f ≤ T.map f ↔ S ≤ T :=
(gciMapComap hf).l_le_l_iff
#align first_order.language.substructure.map_le_map_iff_of_injective FirstOrder.Language.Substructure.map_le_map_iff_of_injective
theorem map_strictMono_of_injective : StrictMono (map f) :=
(gciMapComap hf).strictMono_l
#align first_order.language.substructure.map_strict_mono_of_injective FirstOrder.Language.Substructure.map_strictMono_of_injective
end GaloisCoinsertion
section GaloisInsertion
variable {ι : Type*} {f : M →[L] N} (hf : Function.Surjective f)
/-- `map f` and `comap f` form a `GaloisInsertion` when `f` is surjective. -/
def giMapComap : GaloisInsertion (map f) (comap f) :=
(gc_map_comap f).toGaloisInsertion fun S x h =>
let ⟨y, hy⟩ := hf x
mem_map.2 ⟨y, by simp [hy, h]⟩
#align first_order.language.substructure.gi_map_comap FirstOrder.Language.Substructure.giMapComap
theorem map_comap_eq_of_surjective (S : L.Substructure N) : (S.comap f).map f = S :=
(giMapComap hf).l_u_eq _
#align first_order.language.substructure.map_comap_eq_of_surjective FirstOrder.Language.Substructure.map_comap_eq_of_surjective
theorem map_surjective_of_surjective : Function.Surjective (map f) :=
(giMapComap hf).l_surjective
#align first_order.language.substructure.map_surjective_of_surjective FirstOrder.Language.Substructure.map_surjective_of_surjective
theorem comap_injective_of_surjective : Function.Injective (comap f) :=
(giMapComap hf).u_injective
#align first_order.language.substructure.comap_injective_of_surjective FirstOrder.Language.Substructure.comap_injective_of_surjective
theorem map_inf_comap_of_surjective (S T : L.Substructure N) :
(S.comap f ⊓ T.comap f).map f = S ⊓ T :=
(giMapComap hf).l_inf_u _ _
#align first_order.language.substructure.map_inf_comap_of_surjective FirstOrder.Language.Substructure.map_inf_comap_of_surjective
theorem map_iInf_comap_of_surjective (S : ι → L.Substructure N) :
(⨅ i, (S i).comap f).map f = iInf S :=
(giMapComap hf).l_iInf_u _
#align first_order.language.substructure.map_infi_comap_of_surjective FirstOrder.Language.Substructure.map_iInf_comap_of_surjective
theorem map_sup_comap_of_surjective (S T : L.Substructure N) :
(S.comap f ⊔ T.comap f).map f = S ⊔ T :=
(giMapComap hf).l_sup_u _ _
#align first_order.language.substructure.map_sup_comap_of_surjective FirstOrder.Language.Substructure.map_sup_comap_of_surjective
theorem map_iSup_comap_of_surjective (S : ι → L.Substructure N) :
(⨆ i, (S i).comap f).map f = iSup S :=
(giMapComap hf).l_iSup_u _
#align first_order.language.substructure.map_supr_comap_of_surjective FirstOrder.Language.Substructure.map_iSup_comap_of_surjective
theorem comap_le_comap_iff_of_surjective {S T : L.Substructure N} : S.comap f ≤ T.comap f ↔ S ≤ T :=
(giMapComap hf).u_le_u_iff
#align first_order.language.substructure.comap_le_comap_iff_of_surjective FirstOrder.Language.Substructure.comap_le_comap_iff_of_surjective
theorem comap_strictMono_of_surjective : StrictMono (comap f) :=
(giMapComap hf).strictMono_u
#align first_order.language.substructure.comap_strict_mono_of_surjective FirstOrder.Language.Substructure.comap_strictMono_of_surjective
end GaloisInsertion
instance inducedStructure {S : L.Substructure M} : L.Structure S where
funMap {_} f x := ⟨funMap f fun i => x i, S.fun_mem f (fun i => x i) fun i => (x i).2⟩
RelMap {_} r x := RelMap r fun i => (x i : M)
set_option linter.uppercaseLean3 false in
#align first_order.language.substructure.induced_Structure FirstOrder.Language.Substructure.inducedStructure
/-- The natural embedding of an `L.Substructure` of `M` into `M`. -/
def subtype (S : L.Substructure M) : S ↪[L] M where
toFun := (↑)
inj' := Subtype.coe_injective
#align first_order.language.substructure.subtype FirstOrder.Language.Substructure.subtype
@[simp]
theorem coeSubtype : ⇑S.subtype = ((↑) : S → M) :=
rfl
#align first_order.language.substructure.coe_subtype FirstOrder.Language.Substructure.coeSubtype
/-- The equivalence between the maximal substructure of a structure and the structure itself. -/
def topEquiv : (⊤ : L.Substructure M) ≃[L] M where
toFun := subtype ⊤
invFun m := ⟨m, mem_top m⟩
left_inv m := by simp
right_inv m := rfl
#align first_order.language.substructure.top_equiv FirstOrder.Language.Substructure.topEquiv
@[simp]
theorem coe_topEquiv :
⇑(topEquiv : (⊤ : L.Substructure M) ≃[L] M) = ((↑) : (⊤ : L.Substructure M) → M) :=
rfl
#align first_order.language.substructure.coe_top_equiv FirstOrder.Language.Substructure.coe_topEquiv
@[simp]
theorem realize_boundedFormula_top {α : Type*} {n : ℕ} {φ : L.BoundedFormula α n}
{v : α → (⊤ : L.Substructure M)} {xs : Fin n → (⊤ : L.Substructure M)} :
φ.Realize v xs ↔ φ.Realize (((↑) : _ → M) ∘ v) ((↑) ∘ xs) := by
rw [← Substructure.topEquiv.realize_boundedFormula φ]
simp
#align first_order.language.substructure.realize_bounded_formula_top FirstOrder.Language.Substructure.realize_boundedFormula_top
@[simp]
theorem realize_formula_top {α : Type*} {φ : L.Formula α} {v : α → (⊤ : L.Substructure M)} :
φ.Realize v ↔ φ.Realize (((↑) : (⊤ : L.Substructure M) → M) ∘ v) := by
rw [← Substructure.topEquiv.realize_formula φ]
simp
#align first_order.language.substructure.realize_formula_top FirstOrder.Language.Substructure.realize_formula_top
/-- A dependent version of `Substructure.closure_induction`. -/
@[elab_as_elim]
theorem closure_induction' (s : Set M) {p : ∀ x, x ∈ closure L s → Prop}
(Hs : ∀ (x) (h : x ∈ s), p x (subset_closure h))
(Hfun : ∀ {n : ℕ} (f : L.Functions n), ClosedUnder f { x | ∃ hx, p x hx }) {x}
(hx : x ∈ closure L s) : p x hx := by
refine Exists.elim ?_ fun (hx : x ∈ closure L s) (hc : p x hx) => hc
exact closure_induction hx (fun x hx => ⟨subset_closure hx, Hs x hx⟩) @Hfun
#align first_order.language.substructure.closure_induction' FirstOrder.Language.Substructure.closure_induction'
end Substructure
namespace LHom
set_option linter.uppercaseLean3 false
open Substructure
variable {L' : Language} [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M]
/-- Reduces the language of a substructure along a language hom. -/
def substructureReduct : L'.Substructure M ↪o L.Substructure M where
toFun S :=
{ carrier := S
fun_mem := fun {n} f x hx => by
have h := S.fun_mem (φ.onFunction f) x hx
simp only [LHom.map_onFunction, Substructure.mem_carrier] at h
exact h }
inj' S T h := by
simp only [SetLike.coe_set_eq, Substructure.mk.injEq] at h
exact h
map_rel_iff' {S T} := Iff.rfl
#align first_order.language.Lhom.substructure_reduct FirstOrder.Language.LHom.substructureReduct
@[simp]
theorem mem_substructureReduct {x : M} {S : L'.Substructure M} :
x ∈ φ.substructureReduct S ↔ x ∈ S :=
Iff.rfl
#align first_order.language.Lhom.mem_substructure_reduct FirstOrder.Language.LHom.mem_substructureReduct
@[simp]
theorem coe_substructureReduct {S : L'.Substructure M} : (φ.substructureReduct S : Set M) = ↑S :=
rfl
#align first_order.language.Lhom.coe_substructure_reduct FirstOrder.Language.LHom.coe_substructureReduct
end LHom
namespace Substructure
/-- Turns any substructure containing a constant set `A` into a `L[[A]]`-substructure. -/
def withConstants (S : L.Substructure M) {A : Set M} (h : A ⊆ S) : L[[A]].Substructure M where
carrier := S
fun_mem {n} f := by
cases' f with f f
· exact S.fun_mem f
· cases n
· exact fun _ _ => h f.2
· exact isEmptyElim f
#align first_order.language.substructure.with_constants FirstOrder.Language.Substructure.withConstants
variable {A : Set M} {s : Set M} (h : A ⊆ S)
@[simp]
theorem mem_withConstants {x : M} : x ∈ S.withConstants h ↔ x ∈ S :=
Iff.rfl
#align first_order.language.substructure.mem_with_constants FirstOrder.Language.Substructure.mem_withConstants
@[simp]
theorem coe_withConstants : (S.withConstants h : Set M) = ↑S :=
rfl
#align first_order.language.substructure.coe_with_constants FirstOrder.Language.Substructure.coe_withConstants
@[simp]
| Mathlib/ModelTheory/Substructures.lean | 775 | 778 | theorem reduct_withConstants :
(L.lhomWithConstants A).substructureReduct (S.withConstants h) = S := by |
ext
simp
|
/-
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.Topology.Order.IsLUB
/-!
# Order topology on a densely ordered set
-/
open Set Filter TopologicalSpace Topology Function
open OrderDual (toDual ofDual)
variable {α β γ : Type*}
section DenselyOrdered
variable [TopologicalSpace α] [LinearOrder α] [OrderTopology α] [DenselyOrdered α] {a b : α}
{s : Set α}
/-- The closure of the interval `(a, +∞)` is the closed interval `[a, +∞)`, unless `a` is a top
element. -/
theorem closure_Ioi' {a : α} (h : (Ioi a).Nonempty) : closure (Ioi a) = Ici a := by
apply Subset.antisymm
· exact closure_minimal Ioi_subset_Ici_self isClosed_Ici
· rw [← diff_subset_closure_iff, Ici_diff_Ioi_same, singleton_subset_iff]
exact isGLB_Ioi.mem_closure h
#align closure_Ioi' closure_Ioi'
/-- The closure of the interval `(a, +∞)` is the closed interval `[a, +∞)`. -/
@[simp]
theorem closure_Ioi (a : α) [NoMaxOrder α] : closure (Ioi a) = Ici a :=
closure_Ioi' nonempty_Ioi
#align closure_Ioi closure_Ioi
/-- The closure of the interval `(-∞, a)` is the closed interval `(-∞, a]`, unless `a` is a bottom
element. -/
theorem closure_Iio' (h : (Iio a).Nonempty) : closure (Iio a) = Iic a :=
closure_Ioi' (α := αᵒᵈ) h
#align closure_Iio' closure_Iio'
/-- The closure of the interval `(-∞, a)` is the interval `(-∞, a]`. -/
@[simp]
theorem closure_Iio (a : α) [NoMinOrder α] : closure (Iio a) = Iic a :=
closure_Iio' nonempty_Iio
#align closure_Iio closure_Iio
/-- The closure of the open interval `(a, b)` is the closed interval `[a, b]`. -/
@[simp]
theorem closure_Ioo {a b : α} (hab : a ≠ b) : closure (Ioo a b) = Icc a b := by
apply Subset.antisymm
· exact closure_minimal Ioo_subset_Icc_self isClosed_Icc
· cases' hab.lt_or_lt with hab hab
· rw [← diff_subset_closure_iff, Icc_diff_Ioo_same hab.le]
have hab' : (Ioo a b).Nonempty := nonempty_Ioo.2 hab
simp only [insert_subset_iff, singleton_subset_iff]
exact ⟨(isGLB_Ioo hab).mem_closure hab', (isLUB_Ioo hab).mem_closure hab'⟩
· rw [Icc_eq_empty_of_lt hab]
exact empty_subset _
#align closure_Ioo closure_Ioo
/-- The closure of the interval `(a, b]` is the closed interval `[a, b]`. -/
@[simp]
theorem closure_Ioc {a b : α} (hab : a ≠ b) : closure (Ioc a b) = Icc a b := by
apply Subset.antisymm
· exact closure_minimal Ioc_subset_Icc_self isClosed_Icc
· apply Subset.trans _ (closure_mono Ioo_subset_Ioc_self)
rw [closure_Ioo hab]
#align closure_Ioc closure_Ioc
/-- The closure of the interval `[a, b)` is the closed interval `[a, b]`. -/
@[simp]
theorem closure_Ico {a b : α} (hab : a ≠ b) : closure (Ico a b) = Icc a b := by
apply Subset.antisymm
· exact closure_minimal Ico_subset_Icc_self isClosed_Icc
· apply Subset.trans _ (closure_mono Ioo_subset_Ico_self)
rw [closure_Ioo hab]
#align closure_Ico closure_Ico
@[simp]
theorem interior_Ici' {a : α} (ha : (Iio a).Nonempty) : interior (Ici a) = Ioi a := by
rw [← compl_Iio, interior_compl, closure_Iio' ha, compl_Iic]
#align interior_Ici' interior_Ici'
theorem interior_Ici [NoMinOrder α] {a : α} : interior (Ici a) = Ioi a :=
interior_Ici' nonempty_Iio
#align interior_Ici interior_Ici
@[simp]
theorem interior_Iic' {a : α} (ha : (Ioi a).Nonempty) : interior (Iic a) = Iio a :=
interior_Ici' (α := αᵒᵈ) ha
#align interior_Iic' interior_Iic'
theorem interior_Iic [NoMaxOrder α] {a : α} : interior (Iic a) = Iio a :=
interior_Iic' nonempty_Ioi
#align interior_Iic interior_Iic
@[simp]
theorem interior_Icc [NoMinOrder α] [NoMaxOrder α] {a b : α} : interior (Icc a b) = Ioo a b := by
rw [← Ici_inter_Iic, interior_inter, interior_Ici, interior_Iic, Ioi_inter_Iio]
#align interior_Icc interior_Icc
@[simp]
theorem Icc_mem_nhds_iff [NoMinOrder α] [NoMaxOrder α] {a b x : α} :
Icc a b ∈ 𝓝 x ↔ x ∈ Ioo a b := by
rw [← interior_Icc, mem_interior_iff_mem_nhds]
@[simp]
theorem interior_Ico [NoMinOrder α] {a b : α} : interior (Ico a b) = Ioo a b := by
rw [← Ici_inter_Iio, interior_inter, interior_Ici, interior_Iio, Ioi_inter_Iio]
#align interior_Ico interior_Ico
@[simp]
theorem Ico_mem_nhds_iff [NoMinOrder α] {a b x : α} : Ico a b ∈ 𝓝 x ↔ x ∈ Ioo a b := by
rw [← interior_Ico, mem_interior_iff_mem_nhds]
@[simp]
theorem interior_Ioc [NoMaxOrder α] {a b : α} : interior (Ioc a b) = Ioo a b := by
rw [← Ioi_inter_Iic, interior_inter, interior_Ioi, interior_Iic, Ioi_inter_Iio]
#align interior_Ioc interior_Ioc
@[simp]
theorem Ioc_mem_nhds_iff [NoMaxOrder α] {a b x : α} : Ioc a b ∈ 𝓝 x ↔ x ∈ Ioo a b := by
rw [← interior_Ioc, mem_interior_iff_mem_nhds]
theorem closure_interior_Icc {a b : α} (h : a ≠ b) : closure (interior (Icc a b)) = Icc a b :=
(closure_minimal interior_subset isClosed_Icc).antisymm <|
calc
Icc a b = closure (Ioo a b) := (closure_Ioo h).symm
_ ⊆ closure (interior (Icc a b)) :=
closure_mono (interior_maximal Ioo_subset_Icc_self isOpen_Ioo)
#align closure_interior_Icc closure_interior_Icc
theorem Ioc_subset_closure_interior (a b : α) : Ioc a b ⊆ closure (interior (Ioc a b)) := by
rcases eq_or_ne a b with (rfl | h)
· simp
· calc
Ioc a b ⊆ Icc a b := Ioc_subset_Icc_self
_ = closure (Ioo a b) := (closure_Ioo h).symm
_ ⊆ closure (interior (Ioc a b)) :=
closure_mono (interior_maximal Ioo_subset_Ioc_self isOpen_Ioo)
#align Ioc_subset_closure_interior Ioc_subset_closure_interior
theorem Ico_subset_closure_interior (a b : α) : Ico a b ⊆ closure (interior (Ico a b)) := by
simpa only [dual_Ioc] using Ioc_subset_closure_interior (OrderDual.toDual b) (OrderDual.toDual a)
#align Ico_subset_closure_interior Ico_subset_closure_interior
@[simp]
theorem frontier_Ici' {a : α} (ha : (Iio a).Nonempty) : frontier (Ici a) = {a} := by
simp [frontier, ha]
#align frontier_Ici' frontier_Ici'
theorem frontier_Ici [NoMinOrder α] {a : α} : frontier (Ici a) = {a} :=
frontier_Ici' nonempty_Iio
#align frontier_Ici frontier_Ici
@[simp]
theorem frontier_Iic' {a : α} (ha : (Ioi a).Nonempty) : frontier (Iic a) = {a} := by
simp [frontier, ha]
#align frontier_Iic' frontier_Iic'
theorem frontier_Iic [NoMaxOrder α] {a : α} : frontier (Iic a) = {a} :=
frontier_Iic' nonempty_Ioi
#align frontier_Iic frontier_Iic
@[simp]
theorem frontier_Ioi' {a : α} (ha : (Ioi a).Nonempty) : frontier (Ioi a) = {a} := by
simp [frontier, closure_Ioi' ha, Iic_diff_Iio, Icc_self]
#align frontier_Ioi' frontier_Ioi'
theorem frontier_Ioi [NoMaxOrder α] {a : α} : frontier (Ioi a) = {a} :=
frontier_Ioi' nonempty_Ioi
#align frontier_Ioi frontier_Ioi
@[simp]
theorem frontier_Iio' {a : α} (ha : (Iio a).Nonempty) : frontier (Iio a) = {a} := by
simp [frontier, closure_Iio' ha, Iic_diff_Iio, Icc_self]
#align frontier_Iio' frontier_Iio'
theorem frontier_Iio [NoMinOrder α] {a : α} : frontier (Iio a) = {a} :=
frontier_Iio' nonempty_Iio
#align frontier_Iio frontier_Iio
@[simp]
theorem frontier_Icc [NoMinOrder α] [NoMaxOrder α] {a b : α} (h : a ≤ b) :
frontier (Icc a b) = {a, b} := by simp [frontier, h, Icc_diff_Ioo_same]
#align frontier_Icc frontier_Icc
@[simp]
theorem frontier_Ioo {a b : α} (h : a < b) : frontier (Ioo a b) = {a, b} := by
rw [frontier, closure_Ioo h.ne, interior_Ioo, Icc_diff_Ioo_same h.le]
#align frontier_Ioo frontier_Ioo
@[simp]
theorem frontier_Ico [NoMinOrder α] {a b : α} (h : a < b) : frontier (Ico a b) = {a, b} := by
rw [frontier, closure_Ico h.ne, interior_Ico, Icc_diff_Ioo_same h.le]
#align frontier_Ico frontier_Ico
@[simp]
theorem frontier_Ioc [NoMaxOrder α] {a b : α} (h : a < b) : frontier (Ioc a b) = {a, b} := by
rw [frontier, closure_Ioc h.ne, interior_Ioc, Icc_diff_Ioo_same h.le]
#align frontier_Ioc frontier_Ioc
theorem nhdsWithin_Ioi_neBot' {a b : α} (H₁ : (Ioi a).Nonempty) (H₂ : a ≤ b) :
NeBot (𝓝[Ioi a] b) :=
mem_closure_iff_nhdsWithin_neBot.1 <| by rwa [closure_Ioi' H₁]
#align nhds_within_Ioi_ne_bot' nhdsWithin_Ioi_neBot'
theorem nhdsWithin_Ioi_neBot [NoMaxOrder α] {a b : α} (H : a ≤ b) : NeBot (𝓝[Ioi a] b) :=
nhdsWithin_Ioi_neBot' nonempty_Ioi H
#align nhds_within_Ioi_ne_bot nhdsWithin_Ioi_neBot
theorem nhdsWithin_Ioi_self_neBot' {a : α} (H : (Ioi a).Nonempty) : NeBot (𝓝[>] a) :=
nhdsWithin_Ioi_neBot' H (le_refl a)
#align nhds_within_Ioi_self_ne_bot' nhdsWithin_Ioi_self_neBot'
instance nhdsWithin_Ioi_self_neBot [NoMaxOrder α] (a : α) : NeBot (𝓝[>] a) :=
nhdsWithin_Ioi_neBot (le_refl a)
#align nhds_within_Ioi_self_ne_bot nhdsWithin_Ioi_self_neBot
theorem nhdsWithin_Iio_neBot' {b c : α} (H₁ : (Iio c).Nonempty) (H₂ : b ≤ c) :
NeBot (𝓝[Iio c] b) :=
mem_closure_iff_nhdsWithin_neBot.1 <| by rwa [closure_Iio' H₁]
#align nhds_within_Iio_ne_bot' nhdsWithin_Iio_neBot'
theorem nhdsWithin_Iio_neBot [NoMinOrder α] {a b : α} (H : a ≤ b) : NeBot (𝓝[Iio b] a) :=
nhdsWithin_Iio_neBot' nonempty_Iio H
#align nhds_within_Iio_ne_bot nhdsWithin_Iio_neBot
theorem nhdsWithin_Iio_self_neBot' {b : α} (H : (Iio b).Nonempty) : NeBot (𝓝[<] b) :=
nhdsWithin_Iio_neBot' H (le_refl b)
#align nhds_within_Iio_self_ne_bot' nhdsWithin_Iio_self_neBot'
instance nhdsWithin_Iio_self_neBot [NoMinOrder α] (a : α) : NeBot (𝓝[<] a) :=
nhdsWithin_Iio_neBot (le_refl a)
#align nhds_within_Iio_self_ne_bot nhdsWithin_Iio_self_neBot
theorem right_nhdsWithin_Ico_neBot {a b : α} (H : a < b) : NeBot (𝓝[Ico a b] b) :=
(isLUB_Ico H).nhdsWithin_neBot (nonempty_Ico.2 H)
#align right_nhds_within_Ico_ne_bot right_nhdsWithin_Ico_neBot
theorem left_nhdsWithin_Ioc_neBot {a b : α} (H : a < b) : NeBot (𝓝[Ioc a b] a) :=
(isGLB_Ioc H).nhdsWithin_neBot (nonempty_Ioc.2 H)
#align left_nhds_within_Ioc_ne_bot left_nhdsWithin_Ioc_neBot
theorem left_nhdsWithin_Ioo_neBot {a b : α} (H : a < b) : NeBot (𝓝[Ioo a b] a) :=
(isGLB_Ioo H).nhdsWithin_neBot (nonempty_Ioo.2 H)
#align left_nhds_within_Ioo_ne_bot left_nhdsWithin_Ioo_neBot
theorem right_nhdsWithin_Ioo_neBot {a b : α} (H : a < b) : NeBot (𝓝[Ioo a b] b) :=
(isLUB_Ioo H).nhdsWithin_neBot (nonempty_Ioo.2 H)
#align right_nhds_within_Ioo_ne_bot right_nhdsWithin_Ioo_neBot
theorem comap_coe_nhdsWithin_Iio_of_Ioo_subset (hb : s ⊆ Iio b)
(hs : s.Nonempty → ∃ a < b, Ioo a b ⊆ s) : comap ((↑) : s → α) (𝓝[<] b) = atTop := by
nontriviality
haveI : Nonempty s := nontrivial_iff_nonempty.1 ‹_›
rcases hs (nonempty_subtype.1 ‹_›) with ⟨a, h, hs⟩
ext u; constructor
· rintro ⟨t, ht, hts⟩
obtain ⟨x, ⟨hxa : a ≤ x, hxb : x < b⟩, hxt : Ioo x b ⊆ t⟩ :=
(mem_nhdsWithin_Iio_iff_exists_mem_Ico_Ioo_subset h).mp ht
obtain ⟨y, hxy, hyb⟩ := exists_between hxb
refine mem_of_superset (mem_atTop ⟨y, hs ⟨hxa.trans_lt hxy, hyb⟩⟩) ?_
rintro ⟨z, hzs⟩ (hyz : y ≤ z)
exact hts (hxt ⟨hxy.trans_le hyz, hb hzs⟩)
· intro hu
obtain ⟨x : s, hx : ∀ z, x ≤ z → z ∈ u⟩ := mem_atTop_sets.1 hu
exact ⟨Ioo x b, Ioo_mem_nhdsWithin_Iio' (hb x.2), fun z hz => hx _ hz.1.le⟩
#align comap_coe_nhds_within_Iio_of_Ioo_subset comap_coe_nhdsWithin_Iio_of_Ioo_subset
set_option backward.isDefEq.lazyWhnfCore false in -- See https://github.com/leanprover-community/mathlib4/issues/12534
theorem comap_coe_nhdsWithin_Ioi_of_Ioo_subset (ha : s ⊆ Ioi a)
(hs : s.Nonempty → ∃ b > a, Ioo a b ⊆ s) : comap ((↑) : s → α) (𝓝[>] a) = atBot :=
comap_coe_nhdsWithin_Iio_of_Ioo_subset (show ofDual ⁻¹' s ⊆ Iio (toDual a) from ha) fun h => by
simpa only [OrderDual.exists, dual_Ioo] using hs h
#align comap_coe_nhds_within_Ioi_of_Ioo_subset comap_coe_nhdsWithin_Ioi_of_Ioo_subset
theorem map_coe_atTop_of_Ioo_subset (hb : s ⊆ Iio b) (hs : ∀ a' < b, ∃ a < b, Ioo a b ⊆ s) :
map ((↑) : s → α) atTop = 𝓝[<] b := by
rcases eq_empty_or_nonempty (Iio b) with (hb' | ⟨a, ha⟩)
· have : IsEmpty s := ⟨fun x => hb'.subset (hb x.2)⟩
rw [filter_eq_bot_of_isEmpty atTop, Filter.map_bot, hb', nhdsWithin_empty]
· rw [← comap_coe_nhdsWithin_Iio_of_Ioo_subset hb fun _ => hs a ha, map_comap_of_mem]
rw [Subtype.range_val]
exact (mem_nhdsWithin_Iio_iff_exists_Ioo_subset' ha).2 (hs a ha)
#align map_coe_at_top_of_Ioo_subset map_coe_atTop_of_Ioo_subset
theorem map_coe_atBot_of_Ioo_subset (ha : s ⊆ Ioi a) (hs : ∀ b' > a, ∃ b > a, Ioo a b ⊆ s) :
map ((↑) : s → α) atBot = 𝓝[>] a := by
-- the elaborator gets stuck without `(... : _)`
refine (map_coe_atTop_of_Ioo_subset (show ofDual ⁻¹' s ⊆ Iio (toDual a) from ha)
fun b' hb' => ?_ : _)
simpa only [OrderDual.exists, dual_Ioo] using hs b' hb'
#align map_coe_at_bot_of_Ioo_subset map_coe_atBot_of_Ioo_subset
/-- The `atTop` filter for an open interval `Ioo a b` comes from the left-neighbourhoods filter at
the right endpoint in the ambient order. -/
theorem comap_coe_Ioo_nhdsWithin_Iio (a b : α) : comap ((↑) : Ioo a b → α) (𝓝[<] b) = atTop :=
comap_coe_nhdsWithin_Iio_of_Ioo_subset Ioo_subset_Iio_self fun h =>
⟨a, nonempty_Ioo.1 h, Subset.refl _⟩
#align comap_coe_Ioo_nhds_within_Iio comap_coe_Ioo_nhdsWithin_Iio
/-- The `atBot` filter for an open interval `Ioo a b` comes from the right-neighbourhoods filter at
the left endpoint in the ambient order. -/
theorem comap_coe_Ioo_nhdsWithin_Ioi (a b : α) : comap ((↑) : Ioo a b → α) (𝓝[>] a) = atBot :=
comap_coe_nhdsWithin_Ioi_of_Ioo_subset Ioo_subset_Ioi_self fun h =>
⟨b, nonempty_Ioo.1 h, Subset.refl _⟩
#align comap_coe_Ioo_nhds_within_Ioi comap_coe_Ioo_nhdsWithin_Ioi
theorem comap_coe_Ioi_nhdsWithin_Ioi (a : α) : comap ((↑) : Ioi a → α) (𝓝[>] a) = atBot :=
comap_coe_nhdsWithin_Ioi_of_Ioo_subset (Subset.refl _) fun ⟨x, hx⟩ => ⟨x, hx, Ioo_subset_Ioi_self⟩
#align comap_coe_Ioi_nhds_within_Ioi comap_coe_Ioi_nhdsWithin_Ioi
theorem comap_coe_Iio_nhdsWithin_Iio (a : α) : comap ((↑) : Iio a → α) (𝓝[<] a) = atTop :=
comap_coe_Ioi_nhdsWithin_Ioi (α := αᵒᵈ) a
#align comap_coe_Iio_nhds_within_Iio comap_coe_Iio_nhdsWithin_Iio
@[simp]
theorem map_coe_Ioo_atTop {a b : α} (h : a < b) : map ((↑) : Ioo a b → α) atTop = 𝓝[<] b :=
map_coe_atTop_of_Ioo_subset Ioo_subset_Iio_self fun _ _ => ⟨_, h, Subset.refl _⟩
#align map_coe_Ioo_at_top map_coe_Ioo_atTop
@[simp]
theorem map_coe_Ioo_atBot {a b : α} (h : a < b) : map ((↑) : Ioo a b → α) atBot = 𝓝[>] a :=
map_coe_atBot_of_Ioo_subset Ioo_subset_Ioi_self fun _ _ => ⟨_, h, Subset.refl _⟩
#align map_coe_Ioo_at_bot map_coe_Ioo_atBot
@[simp]
theorem map_coe_Ioi_atBot (a : α) : map ((↑) : Ioi a → α) atBot = 𝓝[>] a :=
map_coe_atBot_of_Ioo_subset (Subset.refl _) fun b hb => ⟨b, hb, Ioo_subset_Ioi_self⟩
#align map_coe_Ioi_at_bot map_coe_Ioi_atBot
@[simp]
theorem map_coe_Iio_atTop (a : α) : map ((↑) : Iio a → α) atTop = 𝓝[<] a :=
map_coe_Ioi_atBot (α := αᵒᵈ) _
#align map_coe_Iio_at_top map_coe_Iio_atTop
variable {l : Filter β} {f : α → β}
@[simp]
theorem tendsto_comp_coe_Ioo_atTop (h : a < b) :
Tendsto (fun x : Ioo a b => f x) atTop l ↔ Tendsto f (𝓝[<] b) l := by
rw [← map_coe_Ioo_atTop h, tendsto_map'_iff]; rfl
#align tendsto_comp_coe_Ioo_at_top tendsto_comp_coe_Ioo_atTop
@[simp]
theorem tendsto_comp_coe_Ioo_atBot (h : a < b) :
Tendsto (fun x : Ioo a b => f x) atBot l ↔ Tendsto f (𝓝[>] a) l := by
rw [← map_coe_Ioo_atBot h, tendsto_map'_iff]; rfl
#align tendsto_comp_coe_Ioo_at_bot tendsto_comp_coe_Ioo_atBot
-- Porting note (#11215): TODO: `simpNF` claims that `simp` can't use
-- this lemma to simplify LHS but it can
@[simp, nolint simpNF]
theorem tendsto_comp_coe_Ioi_atBot :
Tendsto (fun x : Ioi a => f x) atBot l ↔ Tendsto f (𝓝[>] a) l := by
rw [← map_coe_Ioi_atBot, tendsto_map'_iff]; rfl
#align tendsto_comp_coe_Ioi_at_bot tendsto_comp_coe_Ioi_atBot
-- Porting note (#11215): TODO: `simpNF` claims that `simp` can't use
-- this lemma to simplify LHS but it can
@[simp, nolint simpNF]
theorem tendsto_comp_coe_Iio_atTop :
Tendsto (fun x : Iio a => f x) atTop l ↔ Tendsto f (𝓝[<] a) l := by
rw [← map_coe_Iio_atTop, tendsto_map'_iff]; rfl
#align tendsto_comp_coe_Iio_at_top tendsto_comp_coe_Iio_atTop
@[simp]
| Mathlib/Topology/Order/DenselyOrdered.lean | 372 | 374 | theorem tendsto_Ioo_atTop {f : β → Ioo a b} :
Tendsto f l atTop ↔ Tendsto (fun x => (f x : α)) l (𝓝[<] b) := by |
rw [← comap_coe_Ioo_nhdsWithin_Iio, tendsto_comap_iff]; rfl
|
/-
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.Data.Complex.Basic
import Mathlib.Data.Real.Sqrt
#align_import data.complex.basic from "leanprover-community/mathlib"@"31c24aa72e7b3e5ed97a8412470e904f82b81004"
/-!
# Absolute values of complex numbers
-/
open Set ComplexConjugate
namespace Complex
/-! ### Absolute value -/
namespace AbsTheory
-- We develop enough theory to bundle `abs` into an `AbsoluteValue` before making things public;
-- this is so there's not two versions of it hanging around.
local notation "abs" z => Real.sqrt (normSq z)
private theorem mul_self_abs (z : ℂ) : ((abs z) * abs z) = normSq z :=
Real.mul_self_sqrt (normSq_nonneg _)
private theorem abs_nonneg' (z : ℂ) : 0 ≤ abs z :=
Real.sqrt_nonneg _
theorem abs_conj (z : ℂ) : (abs conj z) = abs z := by simp
#align complex.abs_theory.abs_conj Complex.AbsTheory.abs_conj
private theorem abs_re_le_abs (z : ℂ) : |z.re| ≤ abs z := by
rw [mul_self_le_mul_self_iff (abs_nonneg z.re) (abs_nonneg' _), abs_mul_abs_self, mul_self_abs]
apply re_sq_le_normSq
private theorem re_le_abs (z : ℂ) : z.re ≤ abs z :=
(abs_le.1 (abs_re_le_abs _)).2
private theorem abs_mul (z w : ℂ) : (abs z * w) = (abs z) * abs w := by
rw [normSq_mul, Real.sqrt_mul (normSq_nonneg _)]
private theorem abs_add (z w : ℂ) : (abs z + w) ≤ (abs z) + abs w :=
(mul_self_le_mul_self_iff (abs_nonneg' (z + w))
(add_nonneg (abs_nonneg' z) (abs_nonneg' w))).2 <| by
rw [mul_self_abs, add_mul_self_eq, mul_self_abs, mul_self_abs, add_right_comm, normSq_add,
add_le_add_iff_left, mul_assoc, mul_le_mul_left (zero_lt_two' ℝ), ←
Real.sqrt_mul <| normSq_nonneg z, ← normSq_conj w, ← map_mul]
exact re_le_abs (z * conj w)
/-- The complex absolute value function, defined as the square root of the norm squared. -/
noncomputable def _root_.Complex.abs : AbsoluteValue ℂ ℝ where
toFun x := abs x
map_mul' := abs_mul
nonneg' := abs_nonneg'
eq_zero' _ := (Real.sqrt_eq_zero <| normSq_nonneg _).trans normSq_eq_zero
add_le' := abs_add
#align complex.abs Complex.abs
end AbsTheory
theorem abs_def : (Complex.abs : ℂ → ℝ) = fun z => (normSq z).sqrt :=
rfl
#align complex.abs_def Complex.abs_def
theorem abs_apply {z : ℂ} : Complex.abs z = (normSq z).sqrt :=
rfl
#align complex.abs_apply Complex.abs_apply
@[simp, norm_cast]
theorem abs_ofReal (r : ℝ) : Complex.abs r = |r| := by
simp [Complex.abs, normSq_ofReal, Real.sqrt_mul_self_eq_abs]
#align complex.abs_of_real Complex.abs_ofReal
nonrec theorem abs_of_nonneg {r : ℝ} (h : 0 ≤ r) : Complex.abs r = r :=
(Complex.abs_ofReal _).trans (abs_of_nonneg h)
#align complex.abs_of_nonneg Complex.abs_of_nonneg
-- Porting note: removed `norm_cast` attribute because the RHS can't start with `↑`
@[simp]
theorem abs_natCast (n : ℕ) : Complex.abs n = n := Complex.abs_of_nonneg (Nat.cast_nonneg n)
#align complex.abs_of_nat Complex.abs_natCast
#align complex.abs_cast_nat Complex.abs_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem abs_ofNat (n : ℕ) [n.AtLeastTwo] :
Complex.abs (no_index (OfNat.ofNat n : ℂ)) = OfNat.ofNat n :=
abs_natCast n
theorem mul_self_abs (z : ℂ) : Complex.abs z * Complex.abs z = normSq z :=
Real.mul_self_sqrt (normSq_nonneg _)
#align complex.mul_self_abs Complex.mul_self_abs
theorem sq_abs (z : ℂ) : Complex.abs z ^ 2 = normSq z :=
Real.sq_sqrt (normSq_nonneg _)
#align complex.sq_abs Complex.sq_abs
@[simp]
theorem sq_abs_sub_sq_re (z : ℂ) : Complex.abs z ^ 2 - z.re ^ 2 = z.im ^ 2 := by
rw [sq_abs, normSq_apply, ← sq, ← sq, add_sub_cancel_left]
#align complex.sq_abs_sub_sq_re Complex.sq_abs_sub_sq_re
@[simp]
| Mathlib/Data/Complex/Abs.lean | 109 | 110 | theorem sq_abs_sub_sq_im (z : ℂ) : Complex.abs z ^ 2 - z.im ^ 2 = z.re ^ 2 := by |
rw [← sq_abs_sub_sq_re, sub_sub_cancel]
|
/-
Copyright (c) 2020 Nicolò Cavalleri. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nicolò Cavalleri
-/
import Mathlib.Geometry.Manifold.Algebra.Monoid
#align_import geometry.manifold.algebra.lie_group from "leanprover-community/mathlib"@"f9ec187127cc5b381dfcf5f4a22dacca4c20b63d"
/-!
# Lie groups
A Lie group is a group that is also a smooth manifold, in which the group operations of
multiplication and inversion are smooth maps. Smoothness of the group multiplication means that
multiplication is a smooth mapping of the product manifold `G` × `G` into `G`.
Note that, since a manifold here is not second-countable and Hausdorff a Lie group here is not
guaranteed to be second-countable (even though it can be proved it is Hausdorff). Note also that Lie
groups here are not necessarily finite dimensional.
## Main definitions
* `LieAddGroup I G` : a Lie additive group where `G` is a manifold on the model with corners `I`.
* `LieGroup I G` : a Lie multiplicative group where `G` is a manifold on the model with corners `I`.
* `SmoothInv₀`: typeclass for smooth manifolds with `0` and `Inv` such that inversion is a smooth
map at each non-zero point. This includes complete normed fields and (multiplicative) Lie groups.
## Main results
* `ContMDiff.inv`, `ContMDiff.div` and variants: point-wise inversion and division of maps `M → G`
is smooth
* `ContMDiff.inv₀` and variants: if `SmoothInv₀ N`, point-wise inversion of smooth maps `f : M → N`
is smooth at all points at which `f` doesn't vanish.
* `ContMDiff.div₀` and variants: if also `SmoothMul N` (i.e., `N` is a Lie group except possibly
for smoothness of inversion at `0`), similar results hold for point-wise division.
* `normedSpaceLieAddGroup` : a normed vector space over a nontrivially normed field
is an additive Lie group.
* `Instances/UnitsOfNormedAlgebra` shows that the group of units of a complete normed `𝕜`-algebra
is a multiplicative Lie group.
## Implementation notes
A priori, a Lie group here is a manifold with corners.
The definition of Lie group cannot require `I : ModelWithCorners 𝕜 E E` with the same space as the
model space and as the model vector space, as one might hope, beause in the product situation,
the model space is `ModelProd E E'` and the model vector space is `E × E'`, which are not the same,
so the definition does not apply. Hence the definition should be more general, allowing
`I : ModelWithCorners 𝕜 E H`.
-/
noncomputable section
open scoped Manifold
-- See note [Design choices about smooth algebraic structures]
/-- An additive Lie group is a group and a smooth manifold at the same time in which
the addition and negation operations are smooth. -/
class LieAddGroup {𝕜 : Type*} [NontriviallyNormedField 𝕜] {H : Type*} [TopologicalSpace H]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] (I : ModelWithCorners 𝕜 E H) (G : Type*)
[AddGroup G] [TopologicalSpace G] [ChartedSpace H G] extends SmoothAdd I G : Prop where
/-- Negation is smooth in an additive Lie group. -/
smooth_neg : Smooth I I fun a : G => -a
#align lie_add_group LieAddGroup
-- See note [Design choices about smooth algebraic structures]
/-- A (multiplicative) Lie group is a group and a smooth manifold at the same time in which
the multiplication and inverse operations are smooth. -/
@[to_additive]
class LieGroup {𝕜 : Type*} [NontriviallyNormedField 𝕜] {H : Type*} [TopologicalSpace H]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] (I : ModelWithCorners 𝕜 E H) (G : Type*)
[Group G] [TopologicalSpace G] [ChartedSpace H G] extends SmoothMul I G : Prop where
/-- Inversion is smooth in a Lie group. -/
smooth_inv : Smooth I I fun a : G => a⁻¹
#align lie_group LieGroup
/-!
### Smoothness of inversion, negation, division and subtraction
Let `f : M → G` be a `C^n` or smooth functions into a Lie group, then `f` is point-wise
invertible with smooth inverse `f`. If `f` and `g` are two such functions, the quotient
`f / g` (i.e., the point-wise product of `f` and the point-wise inverse of `g`) is also smooth. -/
section PointwiseDivision
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {H : Type*} [TopologicalSpace H] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {I : ModelWithCorners 𝕜 E H} {F : Type*}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {J : ModelWithCorners 𝕜 F F} {G : Type*}
[TopologicalSpace G] [ChartedSpace H G] [Group G] [LieGroup I G] {E' : Type*}
[NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H']
{I' : ModelWithCorners 𝕜 E' H'} {M : Type*} [TopologicalSpace M] [ChartedSpace H' M]
{E'' : Type*} [NormedAddCommGroup E''] [NormedSpace 𝕜 E''] {H'' : Type*} [TopologicalSpace H'']
{I'' : ModelWithCorners 𝕜 E'' H''} {M' : Type*} [TopologicalSpace M'] [ChartedSpace H'' M']
{n : ℕ∞}
section
variable (I)
/-- In a Lie group, inversion is a smooth map. -/
@[to_additive "In an additive Lie group, inversion is a smooth map."]
theorem smooth_inv : Smooth I I fun x : G => x⁻¹ :=
LieGroup.smooth_inv
#align smooth_inv smooth_inv
#align smooth_neg smooth_neg
/-- A Lie group is a topological group. This is not an instance for technical reasons,
see note [Design choices about smooth algebraic structures]. -/
@[to_additive "An additive Lie group is an additive topological group. This is not an instance for
technical reasons, see note [Design choices about smooth algebraic structures]."]
theorem topologicalGroup_of_lieGroup : TopologicalGroup G :=
{ continuousMul_of_smooth I with continuous_inv := (smooth_inv I).continuous }
#align topological_group_of_lie_group topologicalGroup_of_lieGroup
#align topological_add_group_of_lie_add_group topologicalAddGroup_of_lieAddGroup
end
@[to_additive]
theorem ContMDiffWithinAt.inv {f : M → G} {s : Set M} {x₀ : M}
(hf : ContMDiffWithinAt I' I n f s x₀) : ContMDiffWithinAt I' I n (fun x => (f x)⁻¹) s x₀ :=
((smooth_inv I).of_le le_top).contMDiffAt.contMDiffWithinAt.comp x₀ hf <| Set.mapsTo_univ _ _
#align cont_mdiff_within_at.inv ContMDiffWithinAt.inv
#align cont_mdiff_within_at.neg ContMDiffWithinAt.neg
@[to_additive]
theorem ContMDiffAt.inv {f : M → G} {x₀ : M} (hf : ContMDiffAt I' I n f x₀) :
ContMDiffAt I' I n (fun x => (f x)⁻¹) x₀ :=
((smooth_inv I).of_le le_top).contMDiffAt.comp x₀ hf
#align cont_mdiff_at.inv ContMDiffAt.inv
#align cont_mdiff_at.neg ContMDiffAt.neg
@[to_additive]
theorem ContMDiffOn.inv {f : M → G} {s : Set M} (hf : ContMDiffOn I' I n f s) :
ContMDiffOn I' I n (fun x => (f x)⁻¹) s := fun x hx => (hf x hx).inv
#align cont_mdiff_on.inv ContMDiffOn.inv
#align cont_mdiff_on.neg ContMDiffOn.neg
@[to_additive]
theorem ContMDiff.inv {f : M → G} (hf : ContMDiff I' I n f) : ContMDiff I' I n fun x => (f x)⁻¹ :=
fun x => (hf x).inv
#align cont_mdiff.inv ContMDiff.inv
#align cont_mdiff.neg ContMDiff.neg
@[to_additive]
nonrec theorem SmoothWithinAt.inv {f : M → G} {s : Set M} {x₀ : M}
(hf : SmoothWithinAt I' I f s x₀) : SmoothWithinAt I' I (fun x => (f x)⁻¹) s x₀ :=
hf.inv
#align smooth_within_at.inv SmoothWithinAt.inv
#align smooth_within_at.neg SmoothWithinAt.neg
@[to_additive]
nonrec theorem SmoothAt.inv {f : M → G} {x₀ : M} (hf : SmoothAt I' I f x₀) :
SmoothAt I' I (fun x => (f x)⁻¹) x₀ :=
hf.inv
#align smooth_at.inv SmoothAt.inv
#align smooth_at.neg SmoothAt.neg
@[to_additive]
nonrec theorem SmoothOn.inv {f : M → G} {s : Set M} (hf : SmoothOn I' I f s) :
SmoothOn I' I (fun x => (f x)⁻¹) s :=
hf.inv
#align smooth_on.inv SmoothOn.inv
#align smooth_on.neg SmoothOn.neg
@[to_additive]
nonrec theorem Smooth.inv {f : M → G} (hf : Smooth I' I f) : Smooth I' I fun x => (f x)⁻¹ :=
hf.inv
#align smooth.inv Smooth.inv
#align smooth.neg Smooth.neg
@[to_additive]
| Mathlib/Geometry/Manifold/Algebra/LieGroup.lean | 171 | 174 | theorem ContMDiffWithinAt.div {f g : M → G} {s : Set M} {x₀ : M}
(hf : ContMDiffWithinAt I' I n f s x₀) (hg : ContMDiffWithinAt I' I n g s x₀) :
ContMDiffWithinAt I' I n (fun x => f x / g x) s x₀ := by |
simp_rw [div_eq_mul_inv]; exact hf.mul hg.inv
|
/-
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.List.Cycle
import Mathlib.GroupTheory.Perm.Cycle.Type
import Mathlib.GroupTheory.Perm.List
#align_import group_theory.perm.cycle.concrete from "leanprover-community/mathlib"@"00638177efd1b2534fc5269363ebf42a7871df9a"
/-!
# Properties of cyclic permutations constructed from lists/cycles
In the following, `{α : Type*} [Fintype α] [DecidableEq α]`.
## Main definitions
* `Cycle.formPerm`: the cyclic permutation created by looping over a `Cycle α`
* `Equiv.Perm.toList`: the list formed by iterating application of a permutation
* `Equiv.Perm.toCycle`: the cycle formed by iterating application of a permutation
* `Equiv.Perm.isoCycle`: the equivalence between cyclic permutations `f : Perm α`
and the terms of `Cycle α` that correspond to them
* `Equiv.Perm.isoCycle'`: the same equivalence as `Equiv.Perm.isoCycle`
but with evaluation via choosing over fintypes
* The notation `c[1, 2, 3]` to emulate notation of cyclic permutations `(1 2 3)`
* A `Repr` instance for any `Perm α`, by representing the `Finset` of
`Cycle α` that correspond to the cycle factors.
## Main results
* `List.isCycle_formPerm`: a nontrivial list without duplicates, when interpreted as
a permutation, is cyclic
* `Equiv.Perm.IsCycle.existsUnique_cycle`: there is only one nontrivial `Cycle α`
corresponding to each cyclic `f : Perm α`
## Implementation details
The forward direction of `Equiv.Perm.isoCycle'` uses `Fintype.choose` of the uniqueness
result, relying on the `Fintype` instance of a `Cycle.nodup` subtype.
It is unclear if this works faster than the `Equiv.Perm.toCycle`, which relies
on recursion over `Finset.univ`.
Running `#eval` on even a simple noncyclic permutation `c[(1 : Fin 7), 2, 3] * c[0, 5]`
to show it takes a long time. TODO: is this because computing the cycle factors is slow?
-/
open Equiv Equiv.Perm List
variable {α : Type*}
namespace List
variable [DecidableEq α] {l l' : List α}
theorem formPerm_disjoint_iff (hl : Nodup l) (hl' : Nodup l') (hn : 2 ≤ l.length)
(hn' : 2 ≤ l'.length) : Perm.Disjoint (formPerm l) (formPerm l') ↔ l.Disjoint l' := by
rw [disjoint_iff_eq_or_eq, List.Disjoint]
constructor
· rintro h x hx hx'
specialize h x
rw [formPerm_apply_mem_eq_self_iff _ hl _ hx, formPerm_apply_mem_eq_self_iff _ hl' _ hx'] at h
omega
· intro h x
by_cases hx : x ∈ l
on_goal 1 => by_cases hx' : x ∈ l'
· exact (h hx hx').elim
all_goals have := formPerm_eq_self_of_not_mem _ _ ‹_›; tauto
#align list.form_perm_disjoint_iff List.formPerm_disjoint_iff
theorem isCycle_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) : IsCycle (formPerm l) := by
cases' l with x l
· set_option tactic.skipAssignedInstances false in norm_num at hn
induction' l with y l generalizing x
· set_option tactic.skipAssignedInstances false in norm_num at hn
· use x
constructor
· rwa [formPerm_apply_mem_ne_self_iff _ hl _ (mem_cons_self _ _)]
· intro w hw
have : w ∈ x::y::l := mem_of_formPerm_ne_self _ _ hw
obtain ⟨k, hk⟩ := get_of_mem this
use k
rw [← hk]
simp only [zpow_natCast, formPerm_pow_apply_head _ _ hl k, Nat.mod_eq_of_lt k.isLt]
#align list.is_cycle_form_perm List.isCycle_formPerm
theorem pairwise_sameCycle_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) :
Pairwise l.formPerm.SameCycle l :=
Pairwise.imp_mem.mpr
(pairwise_of_forall fun _ _ hx hy =>
(isCycle_formPerm hl hn).sameCycle ((formPerm_apply_mem_ne_self_iff _ hl _ hx).mpr hn)
((formPerm_apply_mem_ne_self_iff _ hl _ hy).mpr hn))
#align list.pairwise_same_cycle_form_perm List.pairwise_sameCycle_formPerm
theorem cycleOf_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) (x) :
cycleOf l.attach.formPerm x = l.attach.formPerm :=
have hn : 2 ≤ l.attach.length := by rwa [← length_attach] at hn
have hl : l.attach.Nodup := by rwa [← nodup_attach] at hl
(isCycle_formPerm hl hn).cycleOf_eq
((formPerm_apply_mem_ne_self_iff _ hl _ (mem_attach _ _)).mpr hn)
#align list.cycle_of_form_perm List.cycleOf_formPerm
theorem cycleType_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) :
cycleType l.attach.formPerm = {l.length} := by
rw [← length_attach] at hn
rw [← nodup_attach] at hl
rw [cycleType_eq [l.attach.formPerm]]
· simp only [map, Function.comp_apply]
rw [support_formPerm_of_nodup _ hl, card_toFinset, dedup_eq_self.mpr hl]
· simp
· intro x h
simp [h, Nat.succ_le_succ_iff] at hn
· simp
· simpa using isCycle_formPerm hl hn
· simp
#align list.cycle_type_form_perm List.cycleType_formPerm
theorem formPerm_apply_mem_eq_next (hl : Nodup l) (x : α) (hx : x ∈ l) :
formPerm l x = next l x hx := by
obtain ⟨k, rfl⟩ := get_of_mem hx
rw [next_get _ hl, formPerm_apply_get _ hl]
#align list.form_perm_apply_mem_eq_next List.formPerm_apply_mem_eq_next
end List
namespace Cycle
variable [DecidableEq α] (s s' : Cycle α)
/-- A cycle `s : Cycle α`, given `Nodup s` can be interpreted as an `Equiv.Perm α`
where each element in the list is permuted to the next one, defined as `formPerm`.
-/
def formPerm : ∀ s : Cycle α, Nodup s → Equiv.Perm α :=
fun s => Quotient.hrecOn s (fun l _ => List.formPerm l) fun l₁ l₂ (h : l₁ ~r l₂) => by
apply Function.hfunext
· ext
exact h.nodup_iff
· intro h₁ h₂ _
exact heq_of_eq (formPerm_eq_of_isRotated h₁ h)
#align cycle.form_perm Cycle.formPerm
@[simp]
theorem formPerm_coe (l : List α) (hl : l.Nodup) : formPerm (l : Cycle α) hl = l.formPerm :=
rfl
#align cycle.form_perm_coe Cycle.formPerm_coe
theorem formPerm_subsingleton (s : Cycle α) (h : Subsingleton s) : formPerm s h.nodup = 1 := by
induction' s using Quot.inductionOn with s
simp only [formPerm_coe, mk_eq_coe]
simp only [length_subsingleton_iff, length_coe, mk_eq_coe] at h
cases' s with hd tl
· simp
· simp only [length_eq_zero, add_le_iff_nonpos_left, List.length, nonpos_iff_eq_zero] at h
simp [h]
#align cycle.form_perm_subsingleton Cycle.formPerm_subsingleton
theorem isCycle_formPerm (s : Cycle α) (h : Nodup s) (hn : Nontrivial s) :
IsCycle (formPerm s h) := by
induction s using Quot.inductionOn
exact List.isCycle_formPerm h (length_nontrivial hn)
#align cycle.is_cycle_form_perm Cycle.isCycle_formPerm
theorem support_formPerm [Fintype α] (s : Cycle α) (h : Nodup s) (hn : Nontrivial s) :
support (formPerm s h) = s.toFinset := by
induction' s using Quot.inductionOn with s
refine support_formPerm_of_nodup s h ?_
rintro _ rfl
simpa [Nat.succ_le_succ_iff] using length_nontrivial hn
#align cycle.support_form_perm Cycle.support_formPerm
theorem formPerm_eq_self_of_not_mem (s : Cycle α) (h : Nodup s) (x : α) (hx : x ∉ s) :
formPerm s h x = x := by
induction s using Quot.inductionOn
simpa using List.formPerm_eq_self_of_not_mem _ _ hx
#align cycle.form_perm_eq_self_of_not_mem Cycle.formPerm_eq_self_of_not_mem
theorem formPerm_apply_mem_eq_next (s : Cycle α) (h : Nodup s) (x : α) (hx : x ∈ s) :
formPerm s h x = next s h x hx := by
induction s using Quot.inductionOn
simpa using List.formPerm_apply_mem_eq_next h _ (by simp_all)
#align cycle.form_perm_apply_mem_eq_next Cycle.formPerm_apply_mem_eq_next
nonrec theorem formPerm_reverse (s : Cycle α) (h : Nodup s) :
formPerm s.reverse (nodup_reverse_iff.mpr h) = (formPerm s h)⁻¹ := by
induction s using Quot.inductionOn
simpa using formPerm_reverse _
#align cycle.form_perm_reverse Cycle.formPerm_reverse
nonrec theorem formPerm_eq_formPerm_iff {α : Type*} [DecidableEq α] {s s' : Cycle α} {hs : s.Nodup}
{hs' : s'.Nodup} :
s.formPerm hs = s'.formPerm hs' ↔ s = s' ∨ s.Subsingleton ∧ s'.Subsingleton := by
rw [Cycle.length_subsingleton_iff, Cycle.length_subsingleton_iff]
revert s s'
intro s s'
apply @Quotient.inductionOn₂' _ _ _ _ _ s s'
intro l l'
-- Porting note: was `simpa using formPerm_eq_formPerm_iff`
simp_all
intro hs hs'
constructor <;> intro h <;> simp_all only [formPerm_eq_formPerm_iff]
#align cycle.form_perm_eq_form_perm_iff Cycle.formPerm_eq_formPerm_iff
end Cycle
namespace Equiv.Perm
section Fintype
variable [Fintype α] [DecidableEq α] (p : Equiv.Perm α) (x : α)
/-- `Equiv.Perm.toList (f : Perm α) (x : α)` generates the list `[x, f x, f (f x), ...]`
until looping. That means when `f x = x`, `toList f x = []`.
-/
def toList : List α :=
(List.range (cycleOf p x).support.card).map fun k => (p ^ k) x
#align equiv.perm.to_list Equiv.Perm.toList
@[simp]
theorem toList_one : toList (1 : Perm α) x = [] := by simp [toList, cycleOf_one]
#align equiv.perm.to_list_one Equiv.Perm.toList_one
@[simp]
theorem toList_eq_nil_iff {p : Perm α} {x} : toList p x = [] ↔ x ∉ p.support := by simp [toList]
#align equiv.perm.to_list_eq_nil_iff Equiv.Perm.toList_eq_nil_iff
@[simp]
theorem length_toList : length (toList p x) = (cycleOf p x).support.card := by simp [toList]
#align equiv.perm.length_to_list Equiv.Perm.length_toList
theorem toList_ne_singleton (y : α) : toList p x ≠ [y] := by
intro H
simpa [card_support_ne_one] using congr_arg length H
#align equiv.perm.to_list_ne_singleton Equiv.Perm.toList_ne_singleton
theorem two_le_length_toList_iff_mem_support {p : Perm α} {x : α} :
2 ≤ length (toList p x) ↔ x ∈ p.support := by simp
#align equiv.perm.two_le_length_to_list_iff_mem_support Equiv.Perm.two_le_length_toList_iff_mem_support
theorem length_toList_pos_of_mem_support (h : x ∈ p.support) : 0 < length (toList p x) :=
zero_lt_two.trans_le (two_le_length_toList_iff_mem_support.mpr h)
#align equiv.perm.length_to_list_pos_of_mem_support Equiv.Perm.length_toList_pos_of_mem_support
theorem get_toList (n : ℕ) (hn : n < length (toList p x)) :
(toList p x).get ⟨n, hn⟩ = (p ^ n) x := by simp [toList]
theorem toList_get_zero (h : x ∈ p.support) :
(toList p x).get ⟨0, (length_toList_pos_of_mem_support _ _ h)⟩ = x := by simp [toList]
set_option linter.deprecated false in
@[deprecated get_toList (since := "2024-05-08")]
theorem nthLe_toList (n : ℕ) (hn : n < length (toList p x)) :
(toList p x).nthLe n hn = (p ^ n) x := by simp [toList]
#align equiv.perm.nth_le_to_list Equiv.Perm.nthLe_toList
set_option linter.deprecated false in
@[deprecated toList_get_zero (since := "2024-05-08")]
theorem toList_nthLe_zero (h : x ∈ p.support) :
(toList p x).nthLe 0 (length_toList_pos_of_mem_support _ _ h) = x := by simp [toList]
#align equiv.perm.to_list_nth_le_zero Equiv.Perm.toList_nthLe_zero
variable {p} {x}
theorem mem_toList_iff {y : α} : y ∈ toList p x ↔ SameCycle p x y ∧ x ∈ p.support := by
simp only [toList, mem_range, mem_map]
constructor
· rintro ⟨n, hx, rfl⟩
refine ⟨⟨n, rfl⟩, ?_⟩
contrapose! hx
rw [← support_cycleOf_eq_nil_iff] at hx
simp [hx]
· rintro ⟨h, hx⟩
simpa using h.exists_pow_eq_of_mem_support hx
#align equiv.perm.mem_to_list_iff Equiv.Perm.mem_toList_iff
set_option linter.deprecated false in
theorem nodup_toList (p : Perm α) (x : α) : Nodup (toList p x) := by
by_cases hx : p x = x
· rw [← not_mem_support, ← toList_eq_nil_iff] at hx
simp [hx]
have hc : IsCycle (cycleOf p x) := isCycle_cycleOf p hx
rw [nodup_iff_nthLe_inj]
rintro n m hn hm
rw [length_toList, ← hc.orderOf] at hm hn
rw [← cycleOf_apply_self, ← Ne, ← mem_support] at hx
rw [nthLe_toList, nthLe_toList, ← cycleOf_pow_apply_self p x n, ←
cycleOf_pow_apply_self p x m]
cases' n with n <;> cases' m with m
· simp
· rw [← hc.support_pow_of_pos_of_lt_orderOf m.zero_lt_succ hm, mem_support,
cycleOf_pow_apply_self] at hx
simp [hx.symm]
· rw [← hc.support_pow_of_pos_of_lt_orderOf n.zero_lt_succ hn, mem_support,
cycleOf_pow_apply_self] at hx
simp [hx]
intro h
have hn' : ¬orderOf (p.cycleOf x) ∣ n.succ := Nat.not_dvd_of_pos_of_lt n.zero_lt_succ hn
have hm' : ¬orderOf (p.cycleOf x) ∣ m.succ := Nat.not_dvd_of_pos_of_lt m.zero_lt_succ hm
rw [← hc.support_pow_eq_iff] at hn' hm'
rw [← Nat.mod_eq_of_lt hn, ← Nat.mod_eq_of_lt hm, ← pow_inj_mod]
refine support_congr ?_ ?_
· rw [hm', hn']
· rw [hm']
intro y hy
obtain ⟨k, rfl⟩ := hc.exists_pow_eq (mem_support.mp hx) (mem_support.mp hy)
rw [← mul_apply, (Commute.pow_pow_self _ _ _).eq, mul_apply, h, ← mul_apply, ← mul_apply,
(Commute.pow_pow_self _ _ _).eq]
#align equiv.perm.nodup_to_list Equiv.Perm.nodup_toList
set_option linter.deprecated false in
theorem next_toList_eq_apply (p : Perm α) (x y : α) (hy : y ∈ toList p x) :
next (toList p x) y hy = p y := by
rw [mem_toList_iff] at hy
obtain ⟨k, hk, hk'⟩ := hy.left.exists_pow_eq_of_mem_support hy.right
rw [← nthLe_toList p x k (by simpa using hk)] at hk'
simp_rw [← hk']
rw [next_nthLe _ (nodup_toList _ _), nthLe_toList, nthLe_toList, ← mul_apply, ← pow_succ',
length_toList, ← pow_mod_orderOf_cycleOf_apply p (k + 1), IsCycle.orderOf]
exact isCycle_cycleOf _ (mem_support.mp hy.right)
#align equiv.perm.next_to_list_eq_apply Equiv.Perm.next_toList_eq_apply
set_option linter.deprecated false in
theorem toList_pow_apply_eq_rotate (p : Perm α) (x : α) (k : ℕ) :
p.toList ((p ^ k) x) = (p.toList x).rotate k := by
apply ext_nthLe
· simp only [length_toList, cycleOf_self_apply_pow, length_rotate]
· intro n hn hn'
rw [nthLe_toList, nthLe_rotate, nthLe_toList, length_toList,
pow_mod_card_support_cycleOf_self_apply, pow_add, mul_apply]
#align equiv.perm.to_list_pow_apply_eq_rotate Equiv.Perm.toList_pow_apply_eq_rotate
theorem SameCycle.toList_isRotated {f : Perm α} {x y : α} (h : SameCycle f x y) :
toList f x ~r toList f y := by
by_cases hx : x ∈ f.support
· obtain ⟨_ | k, _, hy⟩ := h.exists_pow_eq_of_mem_support hx
· simp only [coe_one, id, pow_zero, Nat.zero_eq] at hy
-- Porting note: added `IsRotated.refl`
simp [hy, IsRotated.refl]
use k.succ
rw [← toList_pow_apply_eq_rotate, hy]
· rw [toList_eq_nil_iff.mpr hx, isRotated_nil_iff', eq_comm, toList_eq_nil_iff]
rwa [← h.mem_support_iff]
#align equiv.perm.same_cycle.to_list_is_rotated Equiv.Perm.SameCycle.toList_isRotated
theorem pow_apply_mem_toList_iff_mem_support {n : ℕ} : (p ^ n) x ∈ p.toList x ↔ x ∈ p.support := by
rw [mem_toList_iff, and_iff_right_iff_imp]
refine fun _ => SameCycle.symm ?_
rw [sameCycle_pow_left]
#align equiv.perm.pow_apply_mem_to_list_iff_mem_support Equiv.Perm.pow_apply_mem_toList_iff_mem_support
theorem toList_formPerm_nil (x : α) : toList (formPerm ([] : List α)) x = [] := by simp
#align equiv.perm.to_list_form_perm_nil Equiv.Perm.toList_formPerm_nil
theorem toList_formPerm_singleton (x y : α) : toList (formPerm [x]) y = [] := by simp
#align equiv.perm.to_list_form_perm_singleton Equiv.Perm.toList_formPerm_singleton
theorem toList_formPerm_nontrivial (l : List α) (hl : 2 ≤ l.length) (hn : Nodup l) :
toList (formPerm l) (l.get ⟨0, (zero_lt_two.trans_le hl)⟩) = l := by
have hc : l.formPerm.IsCycle := List.isCycle_formPerm hn hl
have hs : l.formPerm.support = l.toFinset := by
refine support_formPerm_of_nodup _ hn ?_
rintro _ rfl
simp [Nat.succ_le_succ_iff] at hl
rw [toList, hc.cycleOf_eq (mem_support.mp _), hs, card_toFinset, dedup_eq_self.mpr hn]
· refine ext_get (by simp) fun k hk hk' => ?_
simp only [Nat.zero_eq, get_map, get_range, formPerm_pow_apply_get _ hn, zero_add,
Nat.mod_eq_of_lt hk']
· simpa [hs] using get_mem _ _ _
#align equiv.perm.to_list_form_perm_nontrivial Equiv.Perm.toList_formPerm_nontrivial
theorem toList_formPerm_isRotated_self (l : List α) (hl : 2 ≤ l.length) (hn : Nodup l) (x : α)
(hx : x ∈ l) : toList (formPerm l) x ~r l := by
obtain ⟨k, hk, rfl⟩ := get_of_mem hx
have hr : l ~r l.rotate k := ⟨k, rfl⟩
rw [formPerm_eq_of_isRotated hn hr]
rw [get_eq_get_rotate l k k]
simp only [Nat.mod_eq_of_lt k.2, tsub_add_cancel_of_le (le_of_lt k.2), Nat.mod_self]
erw [toList_formPerm_nontrivial]
· simp
· simpa using hl
· simpa using hn
#align equiv.perm.to_list_form_perm_is_rotated_self Equiv.Perm.toList_formPerm_isRotated_self
| Mathlib/GroupTheory/Perm/Cycle/Concrete.lean | 385 | 397 | theorem formPerm_toList (f : Perm α) (x : α) : formPerm (toList f x) = f.cycleOf x := by |
by_cases hx : f x = x
· rw [(cycleOf_eq_one_iff f).mpr hx, toList_eq_nil_iff.mpr (not_mem_support.mpr hx),
formPerm_nil]
ext y
by_cases hy : SameCycle f x y
· obtain ⟨k, _, rfl⟩ := hy.exists_pow_eq_of_mem_support (mem_support.mpr hx)
rw [cycleOf_apply_apply_pow_self, List.formPerm_apply_mem_eq_next (nodup_toList f x),
next_toList_eq_apply, pow_succ', mul_apply]
rw [mem_toList_iff]
exact ⟨⟨k, rfl⟩, mem_support.mpr hx⟩
· rw [cycleOf_apply_of_not_sameCycle hy, formPerm_apply_of_not_mem]
simp [mem_toList_iff, hy]
|
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Convex.Between
import Mathlib.MeasureTheory.Constructions.BorelSpace.Basic
import Mathlib.MeasureTheory.Measure.Lebesgue.Basic
import Mathlib.Topology.MetricSpace.Holder
import Mathlib.Topology.MetricSpace.MetricSeparated
#align_import measure_theory.measure.hausdorff from "leanprover-community/mathlib"@"3d5c4a7a5fb0d982f97ed953161264f1dbd90ead"
/-!
# Hausdorff measure and metric (outer) measures
In this file we define the `d`-dimensional Hausdorff measure on an (extended) metric space `X` and
the Hausdorff dimension of a set in an (extended) metric space. Let `μ d δ` be the maximal outer
measure such that `μ d δ s ≤ (EMetric.diam s) ^ d` for every set of diameter less than `δ`. Then
the Hausdorff measure `μH[d] s` of `s` is defined as `⨆ δ > 0, μ d δ s`. By Caratheodory theorem
`MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`, this is a Borel measure on `X`.
The value of `μH[d]`, `d > 0`, on a set `s` (measurable or not) is given by
```
μH[d] s = ⨆ (r : ℝ≥0∞) (hr : 0 < r), ⨅ (t : ℕ → Set X) (hts : s ⊆ ⋃ n, t n)
(ht : ∀ n, EMetric.diam (t n) ≤ r), ∑' n, EMetric.diam (t n) ^ d
```
For every set `s` for any `d < d'` we have either `μH[d] s = ∞` or `μH[d'] s = 0`, see
`MeasureTheory.Measure.hausdorffMeasure_zero_or_top`. In
`Mathlib.Topology.MetricSpace.HausdorffDimension` we use this fact to define the Hausdorff dimension
`dimH` of a set in an (extended) metric space.
We also define two generalizations of the Hausdorff measure. In one generalization (see
`MeasureTheory.Measure.mkMetric`) we take any function `m (diam s)` instead of `(diam s) ^ d`. In
an even more general definition (see `MeasureTheory.Measure.mkMetric'`) we use any function
of `m : Set X → ℝ≥0∞`. Some authors start with a partial function `m` defined only on some sets
`s : Set X` (e.g., only on balls or only on measurable sets). This is equivalent to our definition
applied to `MeasureTheory.extend m`.
We also define a predicate `MeasureTheory.OuterMeasure.IsMetric` which says that an outer measure
is additive on metric separated pairs of sets: `μ (s ∪ t) = μ s + μ t` provided that
`⨅ (x ∈ s) (y ∈ t), edist x y ≠ 0`. This is the property required for the Caratheodory theorem
`MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`, so we prove this theorem for any
metric outer measure, then prove that outer measures constructed using `mkMetric'` are metric outer
measures.
## Main definitions
* `MeasureTheory.OuterMeasure.IsMetric`: an outer measure `μ` is called *metric* if
`μ (s ∪ t) = μ s + μ t` for any two metric separated sets `s` and `t`. A metric outer measure in a
Borel extended metric space is guaranteed to satisfy the Caratheodory condition, see
`MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`.
* `MeasureTheory.OuterMeasure.mkMetric'` and its particular case
`MeasureTheory.OuterMeasure.mkMetric`: a construction of an outer measure that is guaranteed to
be metric. Both constructions are generalizations of the Hausdorff measure. The same measures
interpreted as Borel measures are called `MeasureTheory.Measure.mkMetric'` and
`MeasureTheory.Measure.mkMetric`.
* `MeasureTheory.Measure.hausdorffMeasure` a.k.a. `μH[d]`: the `d`-dimensional Hausdorff measure.
There are many definitions of the Hausdorff measure that differ from each other by a
multiplicative constant. We put
`μH[d] s = ⨆ r > 0, ⨅ (t : ℕ → Set X) (hts : s ⊆ ⋃ n, t n) (ht : ∀ n, EMetric.diam (t n) ≤ r),
∑' n, ⨆ (ht : ¬Set.Subsingleton (t n)), (EMetric.diam (t n)) ^ d`,
see `MeasureTheory.Measure.hausdorffMeasure_apply`. In the most interesting case `0 < d` one
can omit the `⨆ (ht : ¬Set.Subsingleton (t n))` part.
## Main statements
### Basic properties
* `MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`: if `μ` is a metric outer measure
on an extended metric space `X` (that is, it is additive on pairs of metric separated sets), then
every Borel set is Caratheodory measurable (hence, `μ` defines an actual
`MeasureTheory.Measure`). See also `MeasureTheory.Measure.mkMetric`.
* `MeasureTheory.Measure.hausdorffMeasure_mono`: `μH[d] s` is an antitone function
of `d`.
* `MeasureTheory.Measure.hausdorffMeasure_zero_or_top`: if `d₁ < d₂`, then for any `s`, either
`μH[d₂] s = 0` or `μH[d₁] s = ∞`. Together with the previous lemma, this means that `μH[d] s` is
equal to infinity on some ray `(-∞, D)` and is equal to zero on `(D, +∞)`, where `D` is a possibly
infinite number called the *Hausdorff dimension* of `s`; `μH[D] s` can be zero, infinity, or
anything in between.
* `MeasureTheory.Measure.noAtoms_hausdorff`: Hausdorff measure has no atoms.
### Hausdorff measure in `ℝⁿ`
* `MeasureTheory.hausdorffMeasure_pi_real`: for a nonempty `ι`, `μH[card ι]` on `ι → ℝ` equals
Lebesgue measure.
## Notations
We use the following notation localized in `MeasureTheory`.
- `μH[d]` : `MeasureTheory.Measure.hausdorffMeasure d`
## Implementation notes
There are a few similar constructions called the `d`-dimensional Hausdorff measure. E.g., some
sources only allow coverings by balls and use `r ^ d` instead of `(diam s) ^ d`. While these
construction lead to different Hausdorff measures, they lead to the same notion of the Hausdorff
dimension.
## References
* [Herbert Federer, Geometric Measure Theory, Chapter 2.10][Federer1996]
## Tags
Hausdorff measure, measure, metric measure
-/
open scoped NNReal ENNReal Topology
open EMetric Set Function Filter Encodable FiniteDimensional TopologicalSpace
noncomputable section
variable {ι X Y : Type*} [EMetricSpace X] [EMetricSpace Y]
namespace MeasureTheory
namespace OuterMeasure
/-!
### Metric outer measures
In this section we define metric outer measures and prove Caratheodory theorem: a metric outer
measure has the Caratheodory property.
-/
/-- We say that an outer measure `μ` in an (e)metric space is *metric* if `μ (s ∪ t) = μ s + μ t`
for any two metric separated sets `s`, `t`. -/
def IsMetric (μ : OuterMeasure X) : Prop :=
∀ s t : Set X, IsMetricSeparated s t → μ (s ∪ t) = μ s + μ t
#align measure_theory.outer_measure.is_metric MeasureTheory.OuterMeasure.IsMetric
namespace IsMetric
variable {μ : OuterMeasure X}
/-- A metric outer measure is additive on a finite set of pairwise metric separated sets. -/
theorem finset_iUnion_of_pairwise_separated (hm : IsMetric μ) {I : Finset ι} {s : ι → Set X}
(hI : ∀ i ∈ I, ∀ j ∈ I, i ≠ j → IsMetricSeparated (s i) (s j)) :
μ (⋃ i ∈ I, s i) = ∑ i ∈ I, μ (s i) := by
classical
induction' I using Finset.induction_on with i I hiI ihI hI
· simp
simp only [Finset.mem_insert] at hI
rw [Finset.set_biUnion_insert, hm, ihI, Finset.sum_insert hiI]
exacts [fun i hi j hj hij => hI i (Or.inr hi) j (Or.inr hj) hij,
IsMetricSeparated.finset_iUnion_right fun j hj =>
hI i (Or.inl rfl) j (Or.inr hj) (ne_of_mem_of_not_mem hj hiI).symm]
#align measure_theory.outer_measure.is_metric.finset_Union_of_pairwise_separated MeasureTheory.OuterMeasure.IsMetric.finset_iUnion_of_pairwise_separated
/-- Caratheodory theorem. If `m` is a metric outer measure, then every Borel measurable set `t` is
Caratheodory measurable: for any (not necessarily measurable) set `s` we have
`μ (s ∩ t) + μ (s \ t) = μ s`. -/
theorem borel_le_caratheodory (hm : IsMetric μ) : borel X ≤ μ.caratheodory := by
rw [borel_eq_generateFrom_isClosed]
refine MeasurableSpace.generateFrom_le fun t ht => μ.isCaratheodory_iff_le.2 fun s => ?_
set S : ℕ → Set X := fun n => {x ∈ s | (↑n)⁻¹ ≤ infEdist x t}
have Ssep (n) : IsMetricSeparated (S n) t :=
⟨n⁻¹, ENNReal.inv_ne_zero.2 (ENNReal.natCast_ne_top _),
fun x hx y hy ↦ hx.2.trans <| infEdist_le_edist_of_mem hy⟩
have Ssep' : ∀ n, IsMetricSeparated (S n) (s ∩ t) := fun n =>
(Ssep n).mono Subset.rfl inter_subset_right
have S_sub : ∀ n, S n ⊆ s \ t := fun n =>
subset_inter inter_subset_left (Ssep n).subset_compl_right
have hSs : ∀ n, μ (s ∩ t) + μ (S n) ≤ μ s := fun n =>
calc
μ (s ∩ t) + μ (S n) = μ (s ∩ t ∪ S n) := Eq.symm <| hm _ _ <| (Ssep' n).symm
_ ≤ μ (s ∩ t ∪ s \ t) := μ.mono <| union_subset_union_right _ <| S_sub n
_ = μ s := by rw [inter_union_diff]
have iUnion_S : ⋃ n, S n = s \ t := by
refine Subset.antisymm (iUnion_subset S_sub) ?_
rintro x ⟨hxs, hxt⟩
rw [mem_iff_infEdist_zero_of_closed ht] at hxt
rcases ENNReal.exists_inv_nat_lt hxt with ⟨n, hn⟩
exact mem_iUnion.2 ⟨n, hxs, hn.le⟩
/- Now we have `∀ n, μ (s ∩ t) + μ (S n) ≤ μ s` and we need to prove
`μ (s ∩ t) + μ (⋃ n, S n) ≤ μ s`. We can't pass to the limit because
`μ` is only an outer measure. -/
by_cases htop : μ (s \ t) = ∞
· rw [htop, add_top, ← htop]
exact μ.mono diff_subset
suffices μ (⋃ n, S n) ≤ ⨆ n, μ (S n) by calc
μ (s ∩ t) + μ (s \ t) = μ (s ∩ t) + μ (⋃ n, S n) := by rw [iUnion_S]
_ ≤ μ (s ∩ t) + ⨆ n, μ (S n) := by gcongr
_ = ⨆ n, μ (s ∩ t) + μ (S n) := ENNReal.add_iSup
_ ≤ μ s := iSup_le hSs
/- It suffices to show that `∑' k, μ (S (k + 1) \ S k) ≠ ∞`. Indeed, if we have this,
then for all `N` we have `μ (⋃ n, S n) ≤ μ (S N) + ∑' k, m (S (N + k + 1) \ S (N + k))`
and the second term tends to zero, see `OuterMeasure.iUnion_nat_of_monotone_of_tsum_ne_top`
for details. -/
have : ∀ n, S n ⊆ S (n + 1) := fun n x hx =>
⟨hx.1, le_trans (ENNReal.inv_le_inv.2 <| Nat.cast_le.2 n.le_succ) hx.2⟩
classical -- Porting note: Added this to get the next tactic to work
refine (μ.iUnion_nat_of_monotone_of_tsum_ne_top this ?_).le; clear this
/- While the sets `S (k + 1) \ S k` are not pairwise metric separated, the sets in each
subsequence `S (2 * k + 1) \ S (2 * k)` and `S (2 * k + 2) \ S (2 * k)` are metric separated,
so `m` is additive on each of those sequences. -/
rw [← tsum_even_add_odd ENNReal.summable ENNReal.summable, ENNReal.add_ne_top]
suffices ∀ a, (∑' k : ℕ, μ (S (2 * k + 1 + a) \ S (2 * k + a))) ≠ ∞ from
⟨by simpa using this 0, by simpa using this 1⟩
refine fun r => ne_top_of_le_ne_top htop ?_
rw [← iUnion_S, ENNReal.tsum_eq_iSup_nat, iSup_le_iff]
intro n
rw [← hm.finset_iUnion_of_pairwise_separated]
· exact μ.mono (iUnion_subset fun i => iUnion_subset fun _ x hx => mem_iUnion.2 ⟨_, hx.1⟩)
suffices ∀ i j, i < j → IsMetricSeparated (S (2 * i + 1 + r)) (s \ S (2 * j + r)) from
fun i _ j _ hij => hij.lt_or_lt.elim
(fun h => (this i j h).mono inter_subset_left fun x hx => by exact ⟨hx.1.1, hx.2⟩)
fun h => (this j i h).symm.mono (fun x hx => by exact ⟨hx.1.1, hx.2⟩) inter_subset_left
intro i j hj
have A : ((↑(2 * j + r))⁻¹ : ℝ≥0∞) < (↑(2 * i + 1 + r))⁻¹ := by
rw [ENNReal.inv_lt_inv, Nat.cast_lt]; omega
refine ⟨(↑(2 * i + 1 + r))⁻¹ - (↑(2 * j + r))⁻¹, by simpa [tsub_eq_zero_iff_le] using A,
fun x hx y hy => ?_⟩
have : infEdist y t < (↑(2 * j + r))⁻¹ := not_le.1 fun hle => hy.2 ⟨hy.1, hle⟩
rcases infEdist_lt_iff.mp this with ⟨z, hzt, hyz⟩
have hxz : (↑(2 * i + 1 + r))⁻¹ ≤ edist x z := le_infEdist.1 hx.2 _ hzt
apply ENNReal.le_of_add_le_add_right hyz.ne_top
refine le_trans ?_ (edist_triangle _ _ _)
refine (add_le_add le_rfl hyz.le).trans (Eq.trans_le ?_ hxz)
rw [tsub_add_cancel_of_le A.le]
#align measure_theory.outer_measure.is_metric.borel_le_caratheodory MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory
theorem le_caratheodory [MeasurableSpace X] [BorelSpace X] (hm : IsMetric μ) :
‹MeasurableSpace X› ≤ μ.caratheodory := by
rw [BorelSpace.measurable_eq (α := X)]
exact hm.borel_le_caratheodory
#align measure_theory.outer_measure.is_metric.le_caratheodory MeasureTheory.OuterMeasure.IsMetric.le_caratheodory
end IsMetric
/-!
### Constructors of metric outer measures
In this section we provide constructors `MeasureTheory.OuterMeasure.mkMetric'` and
`MeasureTheory.OuterMeasure.mkMetric` and prove that these outer measures are metric outer
measures. We also prove basic lemmas about `map`/`comap` of these measures.
-/
/-- Auxiliary definition for `OuterMeasure.mkMetric'`: given a function on sets
`m : Set X → ℝ≥0∞`, returns the maximal outer measure `μ` such that `μ s ≤ m s`
for any set `s` of diameter at most `r`. -/
def mkMetric'.pre (m : Set X → ℝ≥0∞) (r : ℝ≥0∞) : OuterMeasure X :=
boundedBy <| extend fun s (_ : diam s ≤ r) => m s
#align measure_theory.outer_measure.mk_metric'.pre MeasureTheory.OuterMeasure.mkMetric'.pre
/-- Given a function `m : Set X → ℝ≥0∞`, `mkMetric' m` is the supremum of `mkMetric'.pre m r`
over `r > 0`. Equivalently, it is the limit of `mkMetric'.pre m r` as `r` tends to zero from
the right. -/
def mkMetric' (m : Set X → ℝ≥0∞) : OuterMeasure X :=
⨆ r > 0, mkMetric'.pre m r
#align measure_theory.outer_measure.mk_metric' MeasureTheory.OuterMeasure.mkMetric'
/-- Given a function `m : ℝ≥0∞ → ℝ≥0∞` and `r > 0`, let `μ r` be the maximal outer measure such that
`μ s ≤ m (EMetric.diam s)` whenever `EMetric.diam s < r`. Then `mkMetric m = ⨆ r > 0, μ r`. -/
def mkMetric (m : ℝ≥0∞ → ℝ≥0∞) : OuterMeasure X :=
mkMetric' fun s => m (diam s)
#align measure_theory.outer_measure.mk_metric MeasureTheory.OuterMeasure.mkMetric
namespace mkMetric'
variable {m : Set X → ℝ≥0∞} {r : ℝ≥0∞} {μ : OuterMeasure X} {s : Set X}
theorem le_pre : μ ≤ pre m r ↔ ∀ s : Set X, diam s ≤ r → μ s ≤ m s := by
simp only [pre, le_boundedBy, extend, le_iInf_iff]
#align measure_theory.outer_measure.mk_metric'.le_pre MeasureTheory.OuterMeasure.mkMetric'.le_pre
theorem pre_le (hs : diam s ≤ r) : pre m r s ≤ m s :=
(boundedBy_le _).trans <| iInf_le _ hs
#align measure_theory.outer_measure.mk_metric'.pre_le MeasureTheory.OuterMeasure.mkMetric'.pre_le
theorem mono_pre (m : Set X → ℝ≥0∞) {r r' : ℝ≥0∞} (h : r ≤ r') : pre m r' ≤ pre m r :=
le_pre.2 fun _ hs => pre_le (hs.trans h)
#align measure_theory.outer_measure.mk_metric'.mono_pre MeasureTheory.OuterMeasure.mkMetric'.mono_pre
theorem mono_pre_nat (m : Set X → ℝ≥0∞) : Monotone fun k : ℕ => pre m k⁻¹ :=
fun k l h => le_pre.2 fun s hs => pre_le (hs.trans <| by simpa)
#align measure_theory.outer_measure.mk_metric'.mono_pre_nat MeasureTheory.OuterMeasure.mkMetric'.mono_pre_nat
theorem tendsto_pre (m : Set X → ℝ≥0∞) (s : Set X) :
Tendsto (fun r => pre m r s) (𝓝[>] 0) (𝓝 <| mkMetric' m s) := by
rw [← map_coe_Ioi_atBot, tendsto_map'_iff]
simp only [mkMetric', OuterMeasure.iSup_apply, iSup_subtype']
exact tendsto_atBot_iSup fun r r' hr => mono_pre _ hr _
#align measure_theory.outer_measure.mk_metric'.tendsto_pre MeasureTheory.OuterMeasure.mkMetric'.tendsto_pre
theorem tendsto_pre_nat (m : Set X → ℝ≥0∞) (s : Set X) :
Tendsto (fun n : ℕ => pre m n⁻¹ s) atTop (𝓝 <| mkMetric' m s) := by
refine (tendsto_pre m s).comp (tendsto_inf.2 ⟨ENNReal.tendsto_inv_nat_nhds_zero, ?_⟩)
refine tendsto_principal.2 (eventually_of_forall fun n => ?_)
simp
#align measure_theory.outer_measure.mk_metric'.tendsto_pre_nat MeasureTheory.OuterMeasure.mkMetric'.tendsto_pre_nat
theorem eq_iSup_nat (m : Set X → ℝ≥0∞) : mkMetric' m = ⨆ n : ℕ, mkMetric'.pre m n⁻¹ := by
ext1 s
rw [iSup_apply]
refine tendsto_nhds_unique (mkMetric'.tendsto_pre_nat m s)
(tendsto_atTop_iSup fun k l hkl => mkMetric'.mono_pre_nat m hkl s)
#align measure_theory.outer_measure.mk_metric'.eq_supr_nat MeasureTheory.OuterMeasure.mkMetric'.eq_iSup_nat
/-- `MeasureTheory.OuterMeasure.mkMetric'.pre m r` is a trimmed measure provided that
`m (closure s) = m s` for any set `s`. -/
theorem trim_pre [MeasurableSpace X] [OpensMeasurableSpace X] (m : Set X → ℝ≥0∞)
(hcl : ∀ s, m (closure s) = m s) (r : ℝ≥0∞) : (pre m r).trim = pre m r := by
refine le_antisymm (le_pre.2 fun s hs => ?_) (le_trim _)
rw [trim_eq_iInf]
refine iInf_le_of_le (closure s) <| iInf_le_of_le subset_closure <|
iInf_le_of_le measurableSet_closure ((pre_le ?_).trans_eq (hcl _))
rwa [diam_closure]
#align measure_theory.outer_measure.mk_metric'.trim_pre MeasureTheory.OuterMeasure.mkMetric'.trim_pre
end mkMetric'
/-- An outer measure constructed using `OuterMeasure.mkMetric'` is a metric outer measure. -/
theorem mkMetric'_isMetric (m : Set X → ℝ≥0∞) : (mkMetric' m).IsMetric := by
rintro s t ⟨r, r0, hr⟩
refine tendsto_nhds_unique_of_eventuallyEq
(mkMetric'.tendsto_pre _ _) ((mkMetric'.tendsto_pre _ _).add (mkMetric'.tendsto_pre _ _)) ?_
rw [← pos_iff_ne_zero] at r0
filter_upwards [Ioo_mem_nhdsWithin_Ioi ⟨le_rfl, r0⟩]
rintro ε ⟨_, εr⟩
refine boundedBy_union_of_top_of_nonempty_inter ?_
rintro u ⟨x, hxs, hxu⟩ ⟨y, hyt, hyu⟩
have : ε < diam u := εr.trans_le ((hr x hxs y hyt).trans <| edist_le_diam_of_mem hxu hyu)
exact iInf_eq_top.2 fun h => (this.not_le h).elim
#align measure_theory.outer_measure.mk_metric'_is_metric MeasureTheory.OuterMeasure.mkMetric'_isMetric
/-- If `c ∉ {0, ∞}` and `m₁ d ≤ c * m₂ d` for `d < ε` for some `ε > 0`
(we use `≤ᶠ[𝓝[≥] 0]` to state this), then `mkMetric m₁ hm₁ ≤ c • mkMetric m₂ hm₂`. -/
theorem mkMetric_mono_smul {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} {c : ℝ≥0∞} (hc : c ≠ ∞) (h0 : c ≠ 0)
(hle : m₁ ≤ᶠ[𝓝[≥] 0] c • m₂) : (mkMetric m₁ : OuterMeasure X) ≤ c • mkMetric m₂ := by
classical
rcases (mem_nhdsWithin_Ici_iff_exists_Ico_subset' zero_lt_one).1 hle with ⟨r, hr0, hr⟩
refine fun s =>
le_of_tendsto_of_tendsto (mkMetric'.tendsto_pre _ s)
(ENNReal.Tendsto.const_mul (mkMetric'.tendsto_pre _ s) (Or.inr hc))
(mem_of_superset (Ioo_mem_nhdsWithin_Ioi ⟨le_rfl, hr0⟩) fun r' hr' => ?_)
simp only [mem_setOf_eq, mkMetric'.pre, RingHom.id_apply]
rw [← smul_eq_mul, ← smul_apply, smul_boundedBy hc]
refine le_boundedBy.2 (fun t => (boundedBy_le _).trans ?_) _
simp only [smul_eq_mul, Pi.smul_apply, extend, iInf_eq_if]
split_ifs with ht
· apply hr
exact ⟨zero_le _, ht.trans_lt hr'.2⟩
· simp [h0]
#align measure_theory.outer_measure.mk_metric_mono_smul MeasureTheory.OuterMeasure.mkMetric_mono_smul
@[simp]
theorem mkMetric_top : (mkMetric (fun _ => ∞ : ℝ≥0∞ → ℝ≥0∞) : OuterMeasure X) = ⊤ := by
simp_rw [mkMetric, mkMetric', mkMetric'.pre, extend_top, boundedBy_top, eq_top_iff]
rw [le_iSup_iff]
intro b hb
simpa using hb ⊤
#align measure_theory.outer_measure.mk_metric_top MeasureTheory.OuterMeasure.mkMetric_top
/-- If `m₁ d ≤ m₂ d` for `d < ε` for some `ε > 0` (we use `≤ᶠ[𝓝[≥] 0]` to state this), then
`mkMetric m₁ hm₁ ≤ mkMetric m₂ hm₂`. -/
theorem mkMetric_mono {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} (hle : m₁ ≤ᶠ[𝓝[≥] 0] m₂) :
(mkMetric m₁ : OuterMeasure X) ≤ mkMetric m₂ := by
convert @mkMetric_mono_smul X _ _ m₂ _ ENNReal.one_ne_top one_ne_zero _ <;> simp [*]
#align measure_theory.outer_measure.mk_metric_mono MeasureTheory.OuterMeasure.mkMetric_mono
theorem isometry_comap_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) {f : X → Y} (hf : Isometry f)
(H : Monotone m ∨ Surjective f) : comap f (mkMetric m) = mkMetric m := by
simp only [mkMetric, mkMetric', mkMetric'.pre, inducedOuterMeasure, comap_iSup]
refine surjective_id.iSup_congr id fun ε => surjective_id.iSup_congr id fun hε => ?_
rw [comap_boundedBy _ (H.imp _ id)]
· congr with s : 1
apply extend_congr
· simp [hf.ediam_image]
· intros; simp [hf.injective.subsingleton_image_iff, hf.ediam_image]
· intro h_mono s t hst
simp only [extend, le_iInf_iff]
intro ht
apply le_trans _ (h_mono (diam_mono hst))
simp only [(diam_mono hst).trans ht, le_refl, ciInf_pos]
#align measure_theory.outer_measure.isometry_comap_mk_metric MeasureTheory.OuterMeasure.isometry_comap_mkMetric
theorem mkMetric_smul (m : ℝ≥0∞ → ℝ≥0∞) {c : ℝ≥0∞} (hc : c ≠ ∞) (hc' : c ≠ 0) :
(mkMetric (c • m) : OuterMeasure X) = c • mkMetric m := by
simp only [mkMetric, mkMetric', mkMetric'.pre, inducedOuterMeasure, ENNReal.smul_iSup]
simp_rw [smul_iSup, smul_boundedBy hc, smul_extend _ hc', Pi.smul_apply]
#align measure_theory.outer_measure.mk_metric_smul MeasureTheory.OuterMeasure.mkMetric_smul
theorem mkMetric_nnreal_smul (m : ℝ≥0∞ → ℝ≥0∞) {c : ℝ≥0} (hc : c ≠ 0) :
(mkMetric (c • m) : OuterMeasure X) = c • mkMetric m := by
rw [ENNReal.smul_def, ENNReal.smul_def,
mkMetric_smul m ENNReal.coe_ne_top (ENNReal.coe_ne_zero.mpr hc)]
#align measure_theory.outer_measure.mk_metric_nnreal_smul MeasureTheory.OuterMeasure.mkMetric_nnreal_smul
theorem isometry_map_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) {f : X → Y} (hf : Isometry f)
(H : Monotone m ∨ Surjective f) : map f (mkMetric m) = restrict (range f) (mkMetric m) := by
rw [← isometry_comap_mkMetric _ hf H, map_comap]
#align measure_theory.outer_measure.isometry_map_mk_metric MeasureTheory.OuterMeasure.isometry_map_mkMetric
theorem isometryEquiv_comap_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (f : X ≃ᵢ Y) :
comap f (mkMetric m) = mkMetric m :=
isometry_comap_mkMetric _ f.isometry (Or.inr f.surjective)
#align measure_theory.outer_measure.isometry_equiv_comap_mk_metric MeasureTheory.OuterMeasure.isometryEquiv_comap_mkMetric
theorem isometryEquiv_map_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (f : X ≃ᵢ Y) :
map f (mkMetric m) = mkMetric m := by
rw [← isometryEquiv_comap_mkMetric _ f, map_comap_of_surjective f.surjective]
#align measure_theory.outer_measure.isometry_equiv_map_mk_metric MeasureTheory.OuterMeasure.isometryEquiv_map_mkMetric
theorem trim_mkMetric [MeasurableSpace X] [BorelSpace X] (m : ℝ≥0∞ → ℝ≥0∞) :
(mkMetric m : OuterMeasure X).trim = mkMetric m := by
simp only [mkMetric, mkMetric'.eq_iSup_nat, trim_iSup]
congr 1 with n : 1
refine mkMetric'.trim_pre _ (fun s => ?_) _
simp
#align measure_theory.outer_measure.trim_mk_metric MeasureTheory.OuterMeasure.trim_mkMetric
theorem le_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (μ : OuterMeasure X) (r : ℝ≥0∞) (h0 : 0 < r)
(hr : ∀ s, diam s ≤ r → μ s ≤ m (diam s)) : μ ≤ mkMetric m :=
le_iSup₂_of_le r h0 <| mkMetric'.le_pre.2 fun _ hs => hr _ hs
#align measure_theory.outer_measure.le_mk_metric MeasureTheory.OuterMeasure.le_mkMetric
end OuterMeasure
/-!
### Metric measures
In this section we use `MeasureTheory.OuterMeasure.toMeasure` and theorems about
`MeasureTheory.OuterMeasure.mkMetric'`/`MeasureTheory.OuterMeasure.mkMetric` to define
`MeasureTheory.Measure.mkMetric'`/`MeasureTheory.Measure.mkMetric`. We also restate some lemmas
about metric outer measures for metric measures.
-/
namespace Measure
variable [MeasurableSpace X] [BorelSpace X]
/-- Given a function `m : Set X → ℝ≥0∞`, `mkMetric' m` is the supremum of `μ r`
over `r > 0`, where `μ r` is the maximal outer measure `μ` such that `μ s ≤ m s`
for all `s`. While each `μ r` is an *outer* measure, the supremum is a measure. -/
def mkMetric' (m : Set X → ℝ≥0∞) : Measure X :=
(OuterMeasure.mkMetric' m).toMeasure (OuterMeasure.mkMetric'_isMetric _).le_caratheodory
#align measure_theory.measure.mk_metric' MeasureTheory.Measure.mkMetric'
/-- Given a function `m : ℝ≥0∞ → ℝ≥0∞`, `mkMetric m` is the supremum of `μ r` over `r > 0`, where
`μ r` is the maximal outer measure `μ` such that `μ s ≤ m s` for all sets `s` that contain at least
two points. While each `mkMetric'.pre` is an *outer* measure, the supremum is a measure. -/
def mkMetric (m : ℝ≥0∞ → ℝ≥0∞) : Measure X :=
(OuterMeasure.mkMetric m).toMeasure (OuterMeasure.mkMetric'_isMetric _).le_caratheodory
#align measure_theory.measure.mk_metric MeasureTheory.Measure.mkMetric
@[simp]
theorem mkMetric'_toOuterMeasure (m : Set X → ℝ≥0∞) :
(mkMetric' m).toOuterMeasure = (OuterMeasure.mkMetric' m).trim :=
rfl
#align measure_theory.measure.mk_metric'_to_outer_measure MeasureTheory.Measure.mkMetric'_toOuterMeasure
@[simp]
theorem mkMetric_toOuterMeasure (m : ℝ≥0∞ → ℝ≥0∞) :
(mkMetric m : Measure X).toOuterMeasure = OuterMeasure.mkMetric m :=
OuterMeasure.trim_mkMetric m
#align measure_theory.measure.mk_metric_to_outer_measure MeasureTheory.Measure.mkMetric_toOuterMeasure
end Measure
theorem OuterMeasure.coe_mkMetric [MeasurableSpace X] [BorelSpace X] (m : ℝ≥0∞ → ℝ≥0∞) :
⇑(OuterMeasure.mkMetric m : OuterMeasure X) = Measure.mkMetric m := by
rw [← Measure.mkMetric_toOuterMeasure, Measure.coe_toOuterMeasure]
#align measure_theory.outer_measure.coe_mk_metric MeasureTheory.OuterMeasure.coe_mkMetric
namespace Measure
variable [MeasurableSpace X] [BorelSpace X]
/-- If `c ∉ {0, ∞}` and `m₁ d ≤ c * m₂ d` for `d < ε` for some `ε > 0`
(we use `≤ᶠ[𝓝[≥] 0]` to state this), then `mkMetric m₁ hm₁ ≤ c • mkMetric m₂ hm₂`. -/
theorem mkMetric_mono_smul {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} {c : ℝ≥0∞} (hc : c ≠ ∞) (h0 : c ≠ 0)
(hle : m₁ ≤ᶠ[𝓝[≥] 0] c • m₂) : (mkMetric m₁ : Measure X) ≤ c • mkMetric m₂ := fun s ↦ by
rw [← OuterMeasure.coe_mkMetric, coe_smul, ← OuterMeasure.coe_mkMetric]
exact OuterMeasure.mkMetric_mono_smul hc h0 hle s
#align measure_theory.measure.mk_metric_mono_smul MeasureTheory.Measure.mkMetric_mono_smul
@[simp]
theorem mkMetric_top : (mkMetric (fun _ => ∞ : ℝ≥0∞ → ℝ≥0∞) : Measure X) = ⊤ := by
apply toOuterMeasure_injective
rw [mkMetric_toOuterMeasure, OuterMeasure.mkMetric_top, toOuterMeasure_top]
#align measure_theory.measure.mk_metric_top MeasureTheory.Measure.mkMetric_top
/-- If `m₁ d ≤ m₂ d` for `d < ε` for some `ε > 0` (we use `≤ᶠ[𝓝[≥] 0]` to state this), then
`mkMetric m₁ hm₁ ≤ mkMetric m₂ hm₂`. -/
theorem mkMetric_mono {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} (hle : m₁ ≤ᶠ[𝓝[≥] 0] m₂) :
(mkMetric m₁ : Measure X) ≤ mkMetric m₂ := by
convert @mkMetric_mono_smul X _ _ _ _ m₂ _ ENNReal.one_ne_top one_ne_zero _ <;> simp [*]
#align measure_theory.measure.mk_metric_mono MeasureTheory.Measure.mkMetric_mono
/-- A formula for `MeasureTheory.Measure.mkMetric`. -/
theorem mkMetric_apply (m : ℝ≥0∞ → ℝ≥0∞) (s : Set X) :
mkMetric m s =
⨆ (r : ℝ≥0∞) (_ : 0 < r),
⨅ (t : ℕ → Set X) (_ : s ⊆ iUnion t) (_ : ∀ n, diam (t n) ≤ r),
∑' n, ⨆ _ : (t n).Nonempty, m (diam (t n)) := by
classical
-- We mostly unfold the definitions but we need to switch the order of `∑'` and `⨅`
simp only [← OuterMeasure.coe_mkMetric, OuterMeasure.mkMetric, OuterMeasure.mkMetric',
OuterMeasure.iSup_apply, OuterMeasure.mkMetric'.pre, OuterMeasure.boundedBy_apply, extend]
refine
surjective_id.iSup_congr (fun r => r) fun r =>
iSup_congr_Prop Iff.rfl fun _ =>
surjective_id.iInf_congr _ fun t => iInf_congr_Prop Iff.rfl fun ht => ?_
dsimp
by_cases htr : ∀ n, diam (t n) ≤ r
· rw [iInf_eq_if, if_pos htr]
congr 1 with n : 1
simp only [iInf_eq_if, htr n, id, if_true, iSup_and']
· rw [iInf_eq_if, if_neg htr]
push_neg at htr; rcases htr with ⟨n, hn⟩
refine ENNReal.tsum_eq_top_of_eq_top ⟨n, ?_⟩
rw [iSup_eq_if, if_pos, iInf_eq_if, if_neg]
· exact hn.not_le
rcases diam_pos_iff.1 ((zero_le r).trans_lt hn) with ⟨x, hx, -⟩
exact ⟨x, hx⟩
#align measure_theory.measure.mk_metric_apply MeasureTheory.Measure.mkMetric_apply
theorem le_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (μ : Measure X) (ε : ℝ≥0∞) (h₀ : 0 < ε)
(h : ∀ s : Set X, diam s ≤ ε → μ s ≤ m (diam s)) : μ ≤ mkMetric m := by
rw [← toOuterMeasure_le, mkMetric_toOuterMeasure]
exact OuterMeasure.le_mkMetric m μ.toOuterMeasure ε h₀ h
#align measure_theory.measure.le_mk_metric MeasureTheory.Measure.le_mkMetric
/-- To bound the Hausdorff measure (or, more generally, for a measure defined using
`MeasureTheory.Measure.mkMetric`) of a set, one may use coverings with maximum diameter tending to
`0`, indexed by any sequence of countable types. -/
theorem mkMetric_le_liminf_tsum {β : Type*} {ι : β → Type*} [∀ n, Countable (ι n)] (s : Set X)
{l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0)) (t : ∀ n : β, ι n → Set X)
(ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n) (hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) (m : ℝ≥0∞ → ℝ≥0∞) :
mkMetric m s ≤ liminf (fun n => ∑' i, m (diam (t n i))) l := by
haveI : ∀ n, Encodable (ι n) := fun n => Encodable.ofCountable _
simp only [mkMetric_apply]
refine iSup₂_le fun ε hε => ?_
refine le_of_forall_le_of_dense fun c hc => ?_
rcases ((frequently_lt_of_liminf_lt (by isBoundedDefault) hc).and_eventually
((hr.eventually (gt_mem_nhds hε)).and (ht.and hst))).exists with
⟨n, hn, hrn, htn, hstn⟩
set u : ℕ → Set X := fun j => ⋃ b ∈ decode₂ (ι n) j, t n b
refine iInf₂_le_of_le u (by rwa [iUnion_decode₂]) ?_
refine iInf_le_of_le (fun j => ?_) ?_
· rw [EMetric.diam_iUnion_mem_option]
exact iSup₂_le fun _ _ => (htn _).trans hrn.le
· calc
(∑' j : ℕ, ⨆ _ : (u j).Nonempty, m (diam (u j))) = _ :=
tsum_iUnion_decode₂ (fun t : Set X => ⨆ _ : t.Nonempty, m (diam t)) (by simp) _
_ ≤ ∑' i : ι n, m (diam (t n i)) := ENNReal.tsum_le_tsum fun b => iSup_le fun _ => le_rfl
_ ≤ c := hn.le
#align measure_theory.measure.mk_metric_le_liminf_tsum MeasureTheory.Measure.mkMetric_le_liminf_tsum
/-- To bound the Hausdorff measure (or, more generally, for a measure defined using
`MeasureTheory.Measure.mkMetric`) of a set, one may use coverings with maximum diameter tending to
`0`, indexed by any sequence of finite types. -/
theorem mkMetric_le_liminf_sum {β : Type*} {ι : β → Type*} [hι : ∀ n, Fintype (ι n)] (s : Set X)
{l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0)) (t : ∀ n : β, ι n → Set X)
(ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n) (hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) (m : ℝ≥0∞ → ℝ≥0∞) :
mkMetric m s ≤ liminf (fun n => ∑ i, m (diam (t n i))) l := by
simpa only [tsum_fintype] using mkMetric_le_liminf_tsum s r hr t ht hst m
#align measure_theory.measure.mk_metric_le_liminf_sum MeasureTheory.Measure.mkMetric_le_liminf_sum
/-!
### Hausdorff measure and Hausdorff dimension
-/
/-- Hausdorff measure on an (e)metric space. -/
def hausdorffMeasure (d : ℝ) : Measure X :=
mkMetric fun r => r ^ d
#align measure_theory.measure.hausdorff_measure MeasureTheory.Measure.hausdorffMeasure
scoped[MeasureTheory] notation "μH[" d "]" => MeasureTheory.Measure.hausdorffMeasure d
theorem le_hausdorffMeasure (d : ℝ) (μ : Measure X) (ε : ℝ≥0∞) (h₀ : 0 < ε)
(h : ∀ s : Set X, diam s ≤ ε → μ s ≤ diam s ^ d) : μ ≤ μH[d] :=
le_mkMetric _ μ ε h₀ h
#align measure_theory.measure.le_hausdorff_measure MeasureTheory.Measure.le_hausdorffMeasure
/-- A formula for `μH[d] s`. -/
theorem hausdorffMeasure_apply (d : ℝ) (s : Set X) :
μH[d] s =
⨆ (r : ℝ≥0∞) (_ : 0 < r),
⨅ (t : ℕ → Set X) (_ : s ⊆ ⋃ n, t n) (_ : ∀ n, diam (t n) ≤ r),
∑' n, ⨆ _ : (t n).Nonempty, diam (t n) ^ d :=
mkMetric_apply _ _
#align measure_theory.measure.hausdorff_measure_apply MeasureTheory.Measure.hausdorffMeasure_apply
/-- To bound the Hausdorff measure of a set, one may use coverings with maximum diameter tending
to `0`, indexed by any sequence of countable types. -/
theorem hausdorffMeasure_le_liminf_tsum {β : Type*} {ι : β → Type*} [∀ n, Countable (ι n)]
(d : ℝ) (s : Set X) {l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0))
(t : ∀ n : β, ι n → Set X) (ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n)
(hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) : μH[d] s ≤ liminf (fun n => ∑' i, diam (t n i) ^ d) l :=
mkMetric_le_liminf_tsum s r hr t ht hst _
#align measure_theory.measure.hausdorff_measure_le_liminf_tsum MeasureTheory.Measure.hausdorffMeasure_le_liminf_tsum
/-- To bound the Hausdorff measure of a set, one may use coverings with maximum diameter tending
to `0`, indexed by any sequence of finite types. -/
theorem hausdorffMeasure_le_liminf_sum {β : Type*} {ι : β → Type*} [∀ n, Fintype (ι n)]
(d : ℝ) (s : Set X) {l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0))
(t : ∀ n : β, ι n → Set X) (ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n)
(hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) : μH[d] s ≤ liminf (fun n => ∑ i, diam (t n i) ^ d) l :=
mkMetric_le_liminf_sum s r hr t ht hst _
#align measure_theory.measure.hausdorff_measure_le_liminf_sum MeasureTheory.Measure.hausdorffMeasure_le_liminf_sum
/-- If `d₁ < d₂`, then for any set `s` we have either `μH[d₂] s = 0`, or `μH[d₁] s = ∞`. -/
theorem hausdorffMeasure_zero_or_top {d₁ d₂ : ℝ} (h : d₁ < d₂) (s : Set X) :
μH[d₂] s = 0 ∨ μH[d₁] s = ∞ := by
by_contra! H
suffices ∀ c : ℝ≥0, c ≠ 0 → μH[d₂] s ≤ c * μH[d₁] s by
rcases ENNReal.exists_nnreal_pos_mul_lt H.2 H.1 with ⟨c, hc0, hc⟩
exact hc.not_le (this c (pos_iff_ne_zero.1 hc0))
intro c hc
refine le_iff'.1 (mkMetric_mono_smul ENNReal.coe_ne_top (mod_cast hc) ?_) s
have : 0 < ((c : ℝ≥0∞) ^ (d₂ - d₁)⁻¹) := by
rw [ENNReal.coe_rpow_of_ne_zero hc, pos_iff_ne_zero, Ne, ENNReal.coe_eq_zero,
NNReal.rpow_eq_zero_iff]
exact mt And.left hc
filter_upwards [Ico_mem_nhdsWithin_Ici ⟨le_rfl, this⟩]
rintro r ⟨hr₀, hrc⟩
lift r to ℝ≥0 using ne_top_of_lt hrc
rw [Pi.smul_apply, smul_eq_mul,
← ENNReal.div_le_iff_le_mul (Or.inr ENNReal.coe_ne_top) (Or.inr <| mt ENNReal.coe_eq_zero.1 hc)]
rcases eq_or_ne r 0 with (rfl | hr₀)
· rcases lt_or_le 0 d₂ with (h₂ | h₂)
· simp only [h₂, ENNReal.zero_rpow_of_pos, zero_le, ENNReal.zero_div, ENNReal.coe_zero]
· simp only [h.trans_le h₂, ENNReal.div_top, zero_le, ENNReal.zero_rpow_of_neg,
ENNReal.coe_zero]
· have : (r : ℝ≥0∞) ≠ 0 := by simpa only [ENNReal.coe_eq_zero, Ne] using hr₀
rw [← ENNReal.rpow_sub _ _ this ENNReal.coe_ne_top]
refine (ENNReal.rpow_lt_rpow hrc (sub_pos.2 h)).le.trans ?_
rw [← ENNReal.rpow_mul, inv_mul_cancel (sub_pos.2 h).ne', ENNReal.rpow_one]
#align measure_theory.measure.hausdorff_measure_zero_or_top MeasureTheory.Measure.hausdorffMeasure_zero_or_top
/-- Hausdorff measure `μH[d] s` is monotone in `d`. -/
theorem hausdorffMeasure_mono {d₁ d₂ : ℝ} (h : d₁ ≤ d₂) (s : Set X) : μH[d₂] s ≤ μH[d₁] s := by
rcases h.eq_or_lt with (rfl | h); · exact le_rfl
cases' hausdorffMeasure_zero_or_top h s with hs hs
· rw [hs]; exact zero_le _
· rw [hs]; exact le_top
#align measure_theory.measure.hausdorff_measure_mono MeasureTheory.Measure.hausdorffMeasure_mono
variable (X)
theorem noAtoms_hausdorff {d : ℝ} (hd : 0 < d) : NoAtoms (hausdorffMeasure d : Measure X) := by
refine ⟨fun x => ?_⟩
rw [← nonpos_iff_eq_zero, hausdorffMeasure_apply]
refine iSup₂_le fun ε _ => iInf₂_le_of_le (fun _ => {x}) ?_ <| iInf_le_of_le (fun _ => ?_) ?_
· exact subset_iUnion (fun _ => {x} : ℕ → Set X) 0
· simp only [EMetric.diam_singleton, zero_le]
· simp [hd]
#align measure_theory.measure.no_atoms_hausdorff MeasureTheory.Measure.noAtoms_hausdorff
variable {X}
@[simp]
theorem hausdorffMeasure_zero_singleton (x : X) : μH[0] ({x} : Set X) = 1 := by
apply le_antisymm
· let r : ℕ → ℝ≥0∞ := fun _ => 0
let t : ℕ → Unit → Set X := fun _ _ => {x}
have ht : ∀ᶠ n in atTop, ∀ i, diam (t n i) ≤ r n := by
simp only [t, r, imp_true_iff, eq_self_iff_true, diam_singleton, eventually_atTop,
nonpos_iff_eq_zero, exists_const]
simpa [t, liminf_const] using hausdorffMeasure_le_liminf_sum 0 {x} r tendsto_const_nhds t ht
· rw [hausdorffMeasure_apply]
suffices
(1 : ℝ≥0∞) ≤
⨅ (t : ℕ → Set X) (_ : {x} ⊆ ⋃ n, t n) (_ : ∀ n, diam (t n) ≤ 1),
∑' n, ⨆ _ : (t n).Nonempty, diam (t n) ^ (0 : ℝ) by
apply le_trans this _
convert le_iSup₂ (α := ℝ≥0∞) (1 : ℝ≥0∞) zero_lt_one
rfl
simp only [ENNReal.rpow_zero, le_iInf_iff]
intro t hst _
rcases mem_iUnion.1 (hst (mem_singleton x)) with ⟨m, hm⟩
have A : (t m).Nonempty := ⟨x, hm⟩
calc
(1 : ℝ≥0∞) = ⨆ h : (t m).Nonempty, 1 := by simp only [A, ciSup_pos]
_ ≤ ∑' n, ⨆ h : (t n).Nonempty, 1 := ENNReal.le_tsum _
#align measure_theory.measure.hausdorff_measure_zero_singleton MeasureTheory.Measure.hausdorffMeasure_zero_singleton
theorem one_le_hausdorffMeasure_zero_of_nonempty {s : Set X} (h : s.Nonempty) : 1 ≤ μH[0] s := by
rcases h with ⟨x, hx⟩
calc
(1 : ℝ≥0∞) = μH[0] ({x} : Set X) := (hausdorffMeasure_zero_singleton x).symm
_ ≤ μH[0] s := measure_mono (singleton_subset_iff.2 hx)
#align measure_theory.measure.one_le_hausdorff_measure_zero_of_nonempty MeasureTheory.Measure.one_le_hausdorffMeasure_zero_of_nonempty
theorem hausdorffMeasure_le_one_of_subsingleton {s : Set X} (hs : s.Subsingleton) {d : ℝ}
(hd : 0 ≤ d) : μH[d] s ≤ 1 := by
rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩)
· simp only [measure_empty, zero_le]
· rw [(subsingleton_iff_singleton hx).1 hs]
rcases eq_or_lt_of_le hd with (rfl | dpos)
· simp only [le_refl, hausdorffMeasure_zero_singleton]
· haveI := noAtoms_hausdorff X dpos
simp only [zero_le, measure_singleton]
#align measure_theory.measure.hausdorff_measure_le_one_of_subsingleton MeasureTheory.Measure.hausdorffMeasure_le_one_of_subsingleton
end Measure
end MeasureTheory
/-!
### Hausdorff measure, Hausdorff dimension, and Hölder or Lipschitz continuous maps
-/
open scoped MeasureTheory
open MeasureTheory MeasureTheory.Measure
variable [MeasurableSpace X] [BorelSpace X] [MeasurableSpace Y] [BorelSpace Y]
namespace HolderOnWith
variable {C r : ℝ≥0} {f : X → Y} {s t : Set X}
/-- If `f : X → Y` is Hölder continuous on `s` with a positive exponent `r`, then
`μH[d] (f '' s) ≤ C ^ d * μH[r * d] s`. -/
theorem hausdorffMeasure_image_le (h : HolderOnWith C r f s) (hr : 0 < r) {d : ℝ} (hd : 0 ≤ d) :
μH[d] (f '' s) ≤ (C : ℝ≥0∞) ^ d * μH[r * d] s := by
-- We start with the trivial case `C = 0`
rcases (zero_le C).eq_or_lt with (rfl | hC0)
· rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩)
· simp only [measure_empty, nonpos_iff_eq_zero, mul_zero, image_empty]
have : f '' s = {f x} :=
have : (f '' s).Subsingleton := by simpa [diam_eq_zero_iff] using h.ediam_image_le
(subsingleton_iff_singleton (mem_image_of_mem f hx)).1 this
rw [this]
rcases eq_or_lt_of_le hd with (rfl | h'd)
· simp only [ENNReal.rpow_zero, one_mul, mul_zero]
rw [hausdorffMeasure_zero_singleton]
exact one_le_hausdorffMeasure_zero_of_nonempty ⟨x, hx⟩
· haveI := noAtoms_hausdorff Y h'd
simp only [zero_le, measure_singleton]
-- Now assume `C ≠ 0`
· have hCd0 : (C : ℝ≥0∞) ^ d ≠ 0 := by simp [hC0.ne']
have hCd : (C : ℝ≥0∞) ^ d ≠ ∞ := by simp [hd]
simp only [hausdorffMeasure_apply, ENNReal.mul_iSup, ENNReal.mul_iInf_of_ne hCd0 hCd,
← ENNReal.tsum_mul_left]
refine iSup_le fun R => iSup_le fun hR => ?_
have : Tendsto (fun d : ℝ≥0∞ => (C : ℝ≥0∞) * d ^ (r : ℝ)) (𝓝 0) (𝓝 0) :=
ENNReal.tendsto_const_mul_rpow_nhds_zero_of_pos ENNReal.coe_ne_top hr
rcases ENNReal.nhds_zero_basis_Iic.eventually_iff.1 (this.eventually (gt_mem_nhds hR)) with
⟨δ, δ0, H⟩
refine le_iSup₂_of_le δ δ0 <| iInf₂_mono' fun t hst ↦
⟨fun n => f '' (t n ∩ s), ?_, iInf_mono' fun htδ ↦
⟨fun n => (h.ediam_image_inter_le (t n)).trans (H (htδ n)).le, ?_⟩⟩
· rw [← image_iUnion, ← iUnion_inter]
exact image_subset _ (subset_inter hst Subset.rfl)
· refine ENNReal.tsum_le_tsum fun n => ?_
simp only [iSup_le_iff, image_nonempty]
intro hft
simp only [Nonempty.mono ((t n).inter_subset_left) hft, ciSup_pos]
rw [ENNReal.rpow_mul, ← ENNReal.mul_rpow_of_nonneg _ _ hd]
exact ENNReal.rpow_le_rpow (h.ediam_image_inter_le _) hd
#align holder_on_with.hausdorff_measure_image_le HolderOnWith.hausdorffMeasure_image_le
end HolderOnWith
namespace LipschitzOnWith
variable {K : ℝ≥0} {f : X → Y} {s t : Set X}
/-- If `f : X → Y` is `K`-Lipschitz on `s`, then `μH[d] (f '' s) ≤ K ^ d * μH[d] s`. -/
theorem hausdorffMeasure_image_le (h : LipschitzOnWith K f s) {d : ℝ} (hd : 0 ≤ d) :
μH[d] (f '' s) ≤ (K : ℝ≥0∞) ^ d * μH[d] s := by
simpa only [NNReal.coe_one, one_mul] using h.holderOnWith.hausdorffMeasure_image_le zero_lt_one hd
#align lipschitz_on_with.hausdorff_measure_image_le LipschitzOnWith.hausdorffMeasure_image_le
end LipschitzOnWith
namespace LipschitzWith
variable {K : ℝ≥0} {f : X → Y}
/-- If `f` is a `K`-Lipschitz map, then it increases the Hausdorff `d`-measures of sets at most
by the factor of `K ^ d`. -/
theorem hausdorffMeasure_image_le (h : LipschitzWith K f) {d : ℝ} (hd : 0 ≤ d) (s : Set X) :
μH[d] (f '' s) ≤ (K : ℝ≥0∞) ^ d * μH[d] s :=
(h.lipschitzOnWith s).hausdorffMeasure_image_le hd
#align lipschitz_with.hausdorff_measure_image_le LipschitzWith.hausdorffMeasure_image_le
end LipschitzWith
open scoped Pointwise
theorem MeasureTheory.Measure.hausdorffMeasure_smul₀ {𝕜 E : Type*} [NormedAddCommGroup E]
[NormedField 𝕜] [NormedSpace 𝕜 E] [MeasurableSpace E] [BorelSpace E] {d : ℝ} (hd : 0 ≤ d)
{r : 𝕜} (hr : r ≠ 0) (s : Set E) : μH[d] (r • s) = ‖r‖₊ ^ d • μH[d] s := by
suffices ∀ {r : 𝕜}, r ≠ 0 → ∀ s : Set E, μH[d] (r • s) ≤ ‖r‖₊ ^ d • μH[d] s by
refine le_antisymm (this hr s) ?_
rw [← le_inv_smul_iff_of_pos]
· dsimp
rw [← NNReal.inv_rpow, ← nnnorm_inv]
· refine Eq.trans_le ?_ (this (inv_ne_zero hr) (r • s))
rw [inv_smul_smul₀ hr]
· simp [pos_iff_ne_zero, hr]
intro r _ s
simp only [NNReal.rpow_eq_pow, ENNReal.smul_def, ← ENNReal.coe_rpow_of_nonneg _ hd, smul_eq_mul]
exact (lipschitzWith_smul (β := E) r).hausdorffMeasure_image_le hd s
#align measure_theory.measure.hausdorff_measure_smul₀ MeasureTheory.Measure.hausdorffMeasure_smul₀
/-!
### Antilipschitz maps do not decrease Hausdorff measures and dimension
-/
namespace AntilipschitzWith
variable {f : X → Y} {K : ℝ≥0} {d : ℝ}
| Mathlib/MeasureTheory/Measure/Hausdorff.lean | 820 | 849 | theorem hausdorffMeasure_preimage_le (hf : AntilipschitzWith K f) (hd : 0 ≤ d) (s : Set Y) :
μH[d] (f ⁻¹' s) ≤ (K : ℝ≥0∞) ^ d * μH[d] s := by |
rcases eq_or_ne K 0 with (rfl | h0)
· rcases eq_empty_or_nonempty (f ⁻¹' s) with (hs | ⟨x, hx⟩)
· simp only [hs, measure_empty, zero_le]
have : f ⁻¹' s = {x} := by
haveI : Subsingleton X := hf.subsingleton
have : (f ⁻¹' s).Subsingleton := subsingleton_univ.anti (subset_univ _)
exact (subsingleton_iff_singleton hx).1 this
rw [this]
rcases eq_or_lt_of_le hd with (rfl | h'd)
· simp only [ENNReal.rpow_zero, one_mul, mul_zero]
rw [hausdorffMeasure_zero_singleton]
exact one_le_hausdorffMeasure_zero_of_nonempty ⟨f x, hx⟩
· haveI := noAtoms_hausdorff X h'd
simp only [zero_le, measure_singleton]
have hKd0 : (K : ℝ≥0∞) ^ d ≠ 0 := by simp [h0]
have hKd : (K : ℝ≥0∞) ^ d ≠ ∞ := by simp [hd]
simp only [hausdorffMeasure_apply, ENNReal.mul_iSup, ENNReal.mul_iInf_of_ne hKd0 hKd,
← ENNReal.tsum_mul_left]
refine iSup₂_le fun ε ε0 => ?_
refine le_iSup₂_of_le (ε / K) (by simp [ε0.ne']) ?_
refine le_iInf₂ fun t hst => le_iInf fun htε => ?_
replace hst : f ⁻¹' s ⊆ _ := preimage_mono hst; rw [preimage_iUnion] at hst
refine iInf₂_le_of_le _ hst (iInf_le_of_le (fun n => ?_) ?_)
· exact (hf.ediam_preimage_le _).trans (ENNReal.mul_le_of_le_div' <| htε n)
· refine ENNReal.tsum_le_tsum fun n => iSup_le_iff.2 fun hft => ?_
simp only [nonempty_of_nonempty_preimage hft, ciSup_pos]
rw [← ENNReal.mul_rpow_of_nonneg _ _ hd]
exact ENNReal.rpow_le_rpow (hf.ediam_preimage_le _) hd
|
/-
Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel
-/
import Mathlib.Topology.EMetricSpace.Basic
import Mathlib.Topology.Bornology.Constructions
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.Topology.Order.DenselyOrdered
/-!
## Pseudo-metric spaces
This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the
condition `dist x y = 0 → x = y`.
Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform
spaces and topological spaces. For example: open and closed sets, compactness, completeness,
continuity and uniform continuity.
## Main definitions
* `Dist α`: Endows a space `α` with a function `dist a b`.
* `PseudoMetricSpace α`: A space endowed with a distance function, which can
be zero even if the two elements are non-equal.
* `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`.
* `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded.
* `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`.
Additional useful definitions:
* `nndist a b`: `dist` as a function to the non-negative reals.
* `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`.
* `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`.
TODO (anyone): Add "Main results" section.
## Tags
pseudo_metric, dist
-/
open Set Filter TopologicalSpace Bornology
open scoped ENNReal NNReal Uniformity Topology
universe u v w
variable {α : Type u} {β : Type v} {X ι : Type*}
theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε :=
⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩
/-- Construct a uniform structure from a distance function and metric space axioms -/
def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0)
(dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α :=
.ofFun dist dist_self dist_comm dist_triangle ofDist_aux
#align uniform_space_of_dist UniformSpace.ofDist
-- Porting note: dropped the `dist_self` argument
/-- Construct a bornology from a distance function and metric space axioms. -/
abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x)
(dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α :=
Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C }
⟨0, fun x hx y => hx.elim⟩ (fun s ⟨c, hc⟩ t h => ⟨c, fun x hx y hy => hc (h hx) (h hy)⟩)
(fun s hs t ht => by
rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩
· rwa [empty_union]
rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩
· rwa [union_empty]
rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C
· refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩
simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb)
rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩
refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim
(fun hz => (hs hx hz).trans (le_max_left _ _))
(fun hz => (dist_triangle x y z).trans <|
(add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩)
fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩
#align bornology.of_dist Bornology.ofDistₓ
/-- The distance function (given an ambient metric space on `α`), which returns
a nonnegative real number `dist x y` given `x y : α`. -/
@[ext]
class Dist (α : Type*) where
dist : α → α → ℝ
#align has_dist Dist
export Dist (dist)
-- the uniform structure and the emetric space structure are embedded in the metric space structure
-- to avoid instance diamond issues. See Note [forgetful inheritance].
/-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/
private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y :=
have : 0 ≤ 2 * dist x y :=
calc 0 = dist x x := (dist_self _).symm
_ ≤ dist x y + dist y x := dist_triangle _ _ _
_ = 2 * dist x y := by rw [two_mul, dist_comm]
nonneg_of_mul_nonneg_right this two_pos
#noalign pseudo_metric_space.edist_dist_tac -- Porting note (#11215): TODO: restore
/-- Pseudo metric and Metric spaces
A pseudo metric space is endowed with a distance for which the requirement `d(x,y)=0 → x = y` might
not hold. A metric space is a pseudo metric space such that `d(x,y)=0 → x = y`.
Each pseudo metric space induces a canonical `UniformSpace` and hence a canonical
`TopologicalSpace` This is enforced in the type class definition, by extending the `UniformSpace`
structure. When instantiating a `PseudoMetricSpace` structure, the uniformity fields are not
necessary, they will be filled in by default. In the same way, each (pseudo) metric space induces a
(pseudo) emetric space structure. It is included in the structure, but filled in by default.
-/
class PseudoMetricSpace (α : Type u) extends Dist α : Type u where
dist_self : ∀ x : α, dist x x = 0
dist_comm : ∀ x y : α, dist x y = dist y x
dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z
edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩
edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y)
-- Porting note (#11215): TODO: add := by _
toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle
uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl
toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets : (Bornology.cobounded α).sets =
{ s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl
#align pseudo_metric_space PseudoMetricSpace
/-- Two pseudo metric space structures with the same distance function coincide. -/
@[ext]
theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α}
(h : m.toDist = m'.toDist) : m = m' := by
cases' m with d _ _ _ ed hed U hU B hB
cases' m' with d' _ _ _ ed' hed' U' hU' B' hB'
obtain rfl : d = d' := h
congr
· ext x y : 2
rw [hed, hed']
· exact UniformSpace.ext (hU.trans hU'.symm)
· ext : 2
rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB']
#align pseudo_metric_space.ext PseudoMetricSpace.ext
variable [PseudoMetricSpace α]
attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology
-- see Note [lower instance priority]
instance (priority := 200) PseudoMetricSpace.toEDist : EDist α :=
⟨PseudoMetricSpace.edist⟩
#align pseudo_metric_space.to_has_edist PseudoMetricSpace.toEDist
/-- Construct a pseudo-metric space structure whose underlying topological space structure
(definitionally) agrees which a pre-existing topology which is compatible with a given distance
function. -/
def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z)
(H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) :
PseudoMetricSpace α :=
{ dist := dist
dist_self := dist_self
dist_comm := dist_comm
dist_triangle := dist_triangle
edist_dist := fun x y => by exact ENNReal.coe_nnreal_eq _
toUniformSpace :=
(UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <|
TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦
((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle
UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm
uniformity_dist := rfl
toBornology := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets := rfl }
#align pseudo_metric_space.of_dist_topology PseudoMetricSpace.ofDistTopology
@[simp]
theorem dist_self (x : α) : dist x x = 0 :=
PseudoMetricSpace.dist_self x
#align dist_self dist_self
theorem dist_comm (x y : α) : dist x y = dist y x :=
PseudoMetricSpace.dist_comm x y
#align dist_comm dist_comm
theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) :=
PseudoMetricSpace.edist_dist x y
#align edist_dist edist_dist
theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z :=
PseudoMetricSpace.dist_triangle x y z
#align dist_triangle dist_triangle
theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by
rw [dist_comm z]; apply dist_triangle
#align dist_triangle_left dist_triangle_left
theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by
rw [dist_comm y]; apply dist_triangle
#align dist_triangle_right dist_triangle_right
theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w :=
calc
dist x w ≤ dist x z + dist z w := dist_triangle x z w
_ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _
#align dist_triangle4 dist_triangle4
theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) :
dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by
rw [add_left_comm, dist_comm x₁, ← add_assoc]
apply dist_triangle4
#align dist_triangle4_left dist_triangle4_left
theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) :
dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by
rw [add_right_comm, dist_comm y₁]
apply dist_triangle4
#align dist_triangle4_right dist_triangle4_right
/-- The triangle (polygon) inequality for sequences of points; `Finset.Ico` version. -/
theorem dist_le_Ico_sum_dist (f : ℕ → α) {m n} (h : m ≤ n) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, dist (f i) (f (i + 1)) := by
induction n, h using Nat.le_induction with
| base => rw [Finset.Ico_self, Finset.sum_empty, dist_self]
| succ n hle ihn =>
calc
dist (f m) (f (n + 1)) ≤ dist (f m) (f n) + dist (f n) (f (n + 1)) := dist_triangle _ _ _
_ ≤ (∑ i ∈ Finset.Ico m n, _) + _ := add_le_add ihn le_rfl
_ = ∑ i ∈ Finset.Ico m (n + 1), _ := by
{ rw [Nat.Ico_succ_right_eq_insert_Ico hle, Finset.sum_insert, add_comm]; simp }
#align dist_le_Ico_sum_dist dist_le_Ico_sum_dist
/-- The triangle (polygon) inequality for sequences of points; `Finset.range` version. -/
theorem dist_le_range_sum_dist (f : ℕ → α) (n : ℕ) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, dist (f i) (f (i + 1)) :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_dist f (Nat.zero_le n)
#align dist_le_range_sum_dist dist_le_range_sum_dist
/-- A version of `dist_le_Ico_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_Ico_sum_of_dist_le {f : ℕ → α} {m n} (hmn : m ≤ n) {d : ℕ → ℝ}
(hd : ∀ {k}, m ≤ k → k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, d i :=
le_trans (dist_le_Ico_sum_dist f hmn) <|
Finset.sum_le_sum fun _k hk => hd (Finset.mem_Ico.1 hk).1 (Finset.mem_Ico.1 hk).2
#align dist_le_Ico_sum_of_dist_le dist_le_Ico_sum_of_dist_le
/-- A version of `dist_le_range_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_range_sum_of_dist_le {f : ℕ → α} (n : ℕ) {d : ℕ → ℝ}
(hd : ∀ {k}, k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, d i :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_of_dist_le (zero_le n) fun _ => hd
#align dist_le_range_sum_of_dist_le dist_le_range_sum_of_dist_le
theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _
#align swap_dist swap_dist
theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y :=
abs_sub_le_iff.2
⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩
#align abs_dist_sub_le abs_dist_sub_le
theorem dist_nonneg {x y : α} : 0 ≤ dist x y :=
dist_nonneg' dist dist_self dist_comm dist_triangle
#align dist_nonneg dist_nonneg
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
/-- Extension for the `positivity` tactic: distances are nonnegative. -/
@[positivity Dist.dist _ _]
def evalDist : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) =>
let _inst ← synthInstanceQ q(PseudoMetricSpace $β)
assertInstancesCommute
pure (.nonnegative q(dist_nonneg))
| _, _, _ => throwError "not dist"
end Mathlib.Meta.Positivity
example {x y : α} : 0 ≤ dist x y := by positivity
@[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg
#align abs_dist abs_dist
/-- A version of `Dist` that takes value in `ℝ≥0`. -/
class NNDist (α : Type*) where
nndist : α → α → ℝ≥0
#align has_nndist NNDist
export NNDist (nndist)
-- see Note [lower instance priority]
/-- Distance as a nonnegative real number. -/
instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α :=
⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩
#align pseudo_metric_space.to_has_nndist PseudoMetricSpace.toNNDist
/-- Express `dist` in terms of `nndist`-/
theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl
#align dist_nndist dist_nndist
@[simp, norm_cast]
theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl
#align coe_nndist coe_nndist
/-- Express `edist` in terms of `nndist`-/
theorem edist_nndist (x y : α) : edist x y = nndist x y := by
rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal]
#align edist_nndist edist_nndist
/-- Express `nndist` in terms of `edist`-/
theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by
simp [edist_nndist]
#align nndist_edist nndist_edist
@[simp, norm_cast]
theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y :=
(edist_nndist x y).symm
#align coe_nnreal_ennreal_nndist coe_nnreal_ennreal_nndist
@[simp, norm_cast]
theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by
rw [edist_nndist, ENNReal.coe_lt_coe]
#align edist_lt_coe edist_lt_coe
@[simp, norm_cast]
| Mathlib/Topology/MetricSpace/PseudoMetric.lean | 329 | 330 | 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]
|
/-
Copyright (c) 2019 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Yury Kudryashov, Sébastien Gouëzel, Chris Hughes
-/
import Mathlib.Algebra.Group.Basic
import Mathlib.Algebra.Group.Pi.Basic
import Mathlib.Order.Fin
import Mathlib.Order.PiLex
import Mathlib.Order.Interval.Set.Basic
#align_import data.fin.tuple.basic from "leanprover-community/mathlib"@"ef997baa41b5c428be3fb50089a7139bf4ee886b"
/-!
# Operation on tuples
We interpret maps `∀ i : Fin n, α i` as `n`-tuples of elements of possibly varying type `α i`,
`(α 0, …, α (n-1))`. A particular case is `Fin n → α` of elements with all the same type.
In this case when `α i` is a constant map, then tuples are isomorphic (but not definitionally equal)
to `Vector`s.
We define the following operations:
* `Fin.tail` : the tail of an `n+1` tuple, i.e., its last `n` entries;
* `Fin.cons` : adding an element at the beginning of an `n`-tuple, to get an `n+1`-tuple;
* `Fin.init` : the beginning of an `n+1` tuple, i.e., its first `n` entries;
* `Fin.snoc` : adding an element at the end of an `n`-tuple, to get an `n+1`-tuple. The name `snoc`
comes from `cons` (i.e., adding an element to the left of a tuple) read in reverse order.
* `Fin.insertNth` : insert an element to a tuple at a given position.
* `Fin.find p` : returns the first index `n` where `p n` is satisfied, and `none` if it is never
satisfied.
* `Fin.append a b` : append two tuples.
* `Fin.repeat n a` : repeat a tuple `n` times.
-/
assert_not_exists MonoidWithZero
universe u v
namespace Fin
variable {m n : ℕ}
open Function
section Tuple
/-- There is exactly one tuple of size zero. -/
example (α : Fin 0 → Sort u) : Unique (∀ i : Fin 0, α i) := by infer_instance
theorem tuple0_le {α : Fin 0 → Type*} [∀ i, Preorder (α i)] (f g : ∀ i, α i) : f ≤ g :=
finZeroElim
#align fin.tuple0_le Fin.tuple0_le
variable {α : Fin (n + 1) → Type u} (x : α 0) (q : ∀ i, α i) (p : ∀ i : Fin n, α i.succ) (i : Fin n)
(y : α i.succ) (z : α 0)
/-- The tail of an `n+1` tuple, i.e., its last `n` entries. -/
def tail (q : ∀ i, α i) : ∀ i : Fin n, α i.succ := fun i ↦ q i.succ
#align fin.tail Fin.tail
theorem tail_def {n : ℕ} {α : Fin (n + 1) → Type*} {q : ∀ i, α i} :
(tail fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q k.succ :=
rfl
#align fin.tail_def Fin.tail_def
/-- Adding an element at the beginning of an `n`-tuple, to get an `n+1`-tuple. -/
def cons (x : α 0) (p : ∀ i : Fin n, α i.succ) : ∀ i, α i := fun j ↦ Fin.cases x p j
#align fin.cons Fin.cons
@[simp]
theorem tail_cons : tail (cons x p) = p := by
simp (config := { unfoldPartialApp := true }) [tail, cons]
#align fin.tail_cons Fin.tail_cons
@[simp]
theorem cons_succ : cons x p i.succ = p i := by simp [cons]
#align fin.cons_succ Fin.cons_succ
@[simp]
theorem cons_zero : cons x p 0 = x := by simp [cons]
#align fin.cons_zero Fin.cons_zero
@[simp]
theorem cons_one {α : Fin (n + 2) → Type*} (x : α 0) (p : ∀ i : Fin n.succ, α i.succ) :
cons x p 1 = p 0 := by
rw [← cons_succ x p]; rfl
/-- Updating a tuple and adding an element at the beginning commute. -/
@[simp]
theorem cons_update : cons x (update p i y) = update (cons x p) i.succ y := by
ext j
by_cases h : j = 0
· rw [h]
simp [Ne.symm (succ_ne_zero i)]
· let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this, cons_succ]
by_cases h' : j' = i
· rw [h']
simp
· have : j'.succ ≠ i.succ := by rwa [Ne, succ_inj]
rw [update_noteq h', update_noteq this, cons_succ]
#align fin.cons_update Fin.cons_update
/-- As a binary function, `Fin.cons` is injective. -/
theorem cons_injective2 : Function.Injective2 (@cons n α) := fun x₀ y₀ x y h ↦
⟨congr_fun h 0, funext fun i ↦ by simpa using congr_fun h (Fin.succ i)⟩
#align fin.cons_injective2 Fin.cons_injective2
@[simp]
theorem cons_eq_cons {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} :
cons x₀ x = cons y₀ y ↔ x₀ = y₀ ∧ x = y :=
cons_injective2.eq_iff
#align fin.cons_eq_cons Fin.cons_eq_cons
theorem cons_left_injective (x : ∀ i : Fin n, α i.succ) : Function.Injective fun x₀ ↦ cons x₀ x :=
cons_injective2.left _
#align fin.cons_left_injective Fin.cons_left_injective
theorem cons_right_injective (x₀ : α 0) : Function.Injective (cons x₀) :=
cons_injective2.right _
#align fin.cons_right_injective Fin.cons_right_injective
/-- Adding an element at the beginning of a tuple and then updating it amounts to adding it
directly. -/
theorem update_cons_zero : update (cons x p) 0 z = cons z p := by
ext j
by_cases h : j = 0
· rw [h]
simp
· simp only [h, update_noteq, Ne, not_false_iff]
let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this, cons_succ, cons_succ]
#align fin.update_cons_zero Fin.update_cons_zero
/-- Concatenating the first element of a tuple with its tail gives back the original tuple -/
@[simp, nolint simpNF] -- Porting note: linter claims LHS doesn't simplify
theorem cons_self_tail : cons (q 0) (tail q) = q := by
ext j
by_cases h : j = 0
· rw [h]
simp
· let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this]
unfold tail
rw [cons_succ]
#align fin.cons_self_tail Fin.cons_self_tail
-- Porting note: Mathport removes `_root_`?
/-- Recurse on an `n+1`-tuple by splitting it into a single element and an `n`-tuple. -/
@[elab_as_elim]
def consCases {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x))
(x : ∀ i : Fin n.succ, α i) : P x :=
_root_.cast (by rw [cons_self_tail]) <| h (x 0) (tail x)
#align fin.cons_cases Fin.consCases
@[simp]
theorem consCases_cons {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x))
(x₀ : α 0) (x : ∀ i : Fin n, α i.succ) : @consCases _ _ _ h (cons x₀ x) = h x₀ x := by
rw [consCases, cast_eq]
congr
#align fin.cons_cases_cons Fin.consCases_cons
/-- Recurse on a tuple by splitting into `Fin.elim0` and `Fin.cons`. -/
@[elab_as_elim]
def consInduction {α : Type*} {P : ∀ {n : ℕ}, (Fin n → α) → Sort v} (h0 : P Fin.elim0)
(h : ∀ {n} (x₀) (x : Fin n → α), P x → P (Fin.cons x₀ x)) : ∀ {n : ℕ} (x : Fin n → α), P x
| 0, x => by convert h0
| n + 1, x => consCases (fun x₀ x ↦ h _ _ <| consInduction h0 h _) x
#align fin.cons_induction Fin.consInductionₓ -- Porting note: universes
theorem cons_injective_of_injective {α} {x₀ : α} {x : Fin n → α} (hx₀ : x₀ ∉ Set.range x)
(hx : Function.Injective x) : Function.Injective (cons x₀ x : Fin n.succ → α) := by
refine Fin.cases ?_ ?_
· refine Fin.cases ?_ ?_
· intro
rfl
· intro j h
rw [cons_zero, cons_succ] at h
exact hx₀.elim ⟨_, h.symm⟩
· intro i
refine Fin.cases ?_ ?_
· intro h
rw [cons_zero, cons_succ] at h
exact hx₀.elim ⟨_, h⟩
· intro j h
rw [cons_succ, cons_succ] at h
exact congr_arg _ (hx h)
#align fin.cons_injective_of_injective Fin.cons_injective_of_injective
theorem cons_injective_iff {α} {x₀ : α} {x : Fin n → α} :
Function.Injective (cons x₀ x : Fin n.succ → α) ↔ x₀ ∉ Set.range x ∧ Function.Injective x := by
refine ⟨fun h ↦ ⟨?_, ?_⟩, fun h ↦ cons_injective_of_injective h.1 h.2⟩
· rintro ⟨i, hi⟩
replace h := @h i.succ 0
simp [hi, succ_ne_zero] at h
· simpa [Function.comp] using h.comp (Fin.succ_injective _)
#align fin.cons_injective_iff Fin.cons_injective_iff
@[simp]
theorem forall_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} :
(∀ x, P x) ↔ P finZeroElim :=
⟨fun h ↦ h _, fun h x ↦ Subsingleton.elim finZeroElim x ▸ h⟩
#align fin.forall_fin_zero_pi Fin.forall_fin_zero_pi
@[simp]
theorem exists_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} :
(∃ x, P x) ↔ P finZeroElim :=
⟨fun ⟨x, h⟩ ↦ Subsingleton.elim x finZeroElim ▸ h, fun h ↦ ⟨_, h⟩⟩
#align fin.exists_fin_zero_pi Fin.exists_fin_zero_pi
theorem forall_fin_succ_pi {P : (∀ i, α i) → Prop} : (∀ x, P x) ↔ ∀ a v, P (Fin.cons a v) :=
⟨fun h a v ↦ h (Fin.cons a v), consCases⟩
#align fin.forall_fin_succ_pi Fin.forall_fin_succ_pi
theorem exists_fin_succ_pi {P : (∀ i, α i) → Prop} : (∃ x, P x) ↔ ∃ a v, P (Fin.cons a v) :=
⟨fun ⟨x, h⟩ ↦ ⟨x 0, tail x, (cons_self_tail x).symm ▸ h⟩, fun ⟨_, _, h⟩ ↦ ⟨_, h⟩⟩
#align fin.exists_fin_succ_pi Fin.exists_fin_succ_pi
/-- Updating the first element of a tuple does not change the tail. -/
@[simp]
theorem tail_update_zero : tail (update q 0 z) = tail q := by
ext j
simp [tail, Fin.succ_ne_zero]
#align fin.tail_update_zero Fin.tail_update_zero
/-- Updating a nonzero element and taking the tail commute. -/
@[simp]
theorem tail_update_succ : tail (update q i.succ y) = update (tail q) i y := by
ext j
by_cases h : j = i
· rw [h]
simp [tail]
· simp [tail, (Fin.succ_injective n).ne h, h]
#align fin.tail_update_succ Fin.tail_update_succ
theorem comp_cons {α : Type*} {β : Type*} (g : α → β) (y : α) (q : Fin n → α) :
g ∘ cons y q = cons (g y) (g ∘ q) := by
ext j
by_cases h : j = 0
· rw [h]
rfl
· let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this, cons_succ, comp_apply, comp_apply, cons_succ]
#align fin.comp_cons Fin.comp_cons
theorem comp_tail {α : Type*} {β : Type*} (g : α → β) (q : Fin n.succ → α) :
g ∘ tail q = tail (g ∘ q) := by
ext j
simp [tail]
#align fin.comp_tail Fin.comp_tail
theorem le_cons [∀ i, Preorder (α i)] {x : α 0} {q : ∀ i, α i} {p : ∀ i : Fin n, α i.succ} :
q ≤ cons x p ↔ q 0 ≤ x ∧ tail q ≤ p :=
forall_fin_succ.trans <| and_congr Iff.rfl <| forall_congr' fun j ↦ by simp [tail]
#align fin.le_cons Fin.le_cons
theorem cons_le [∀ i, Preorder (α i)] {x : α 0} {q : ∀ i, α i} {p : ∀ i : Fin n, α i.succ} :
cons x p ≤ q ↔ x ≤ q 0 ∧ p ≤ tail q :=
@le_cons _ (fun i ↦ (α i)ᵒᵈ) _ x q p
#align fin.cons_le Fin.cons_le
theorem cons_le_cons [∀ i, Preorder (α i)] {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} :
cons x₀ x ≤ cons y₀ y ↔ x₀ ≤ y₀ ∧ x ≤ y :=
forall_fin_succ.trans <| and_congr_right' <| by simp only [cons_succ, Pi.le_def]
#align fin.cons_le_cons Fin.cons_le_cons
theorem pi_lex_lt_cons_cons {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ}
(s : ∀ {i : Fin n.succ}, α i → α i → Prop) :
Pi.Lex (· < ·) (@s) (Fin.cons x₀ x) (Fin.cons y₀ y) ↔
s x₀ y₀ ∨ x₀ = y₀ ∧ Pi.Lex (· < ·) (@fun i : Fin n ↦ @s i.succ) x y := by
simp_rw [Pi.Lex, Fin.exists_fin_succ, Fin.cons_succ, Fin.cons_zero, Fin.forall_fin_succ]
simp [and_assoc, exists_and_left]
#align fin.pi_lex_lt_cons_cons Fin.pi_lex_lt_cons_cons
theorem range_fin_succ {α} (f : Fin (n + 1) → α) :
Set.range f = insert (f 0) (Set.range (Fin.tail f)) :=
Set.ext fun _ ↦ exists_fin_succ.trans <| eq_comm.or Iff.rfl
#align fin.range_fin_succ Fin.range_fin_succ
@[simp]
theorem range_cons {α : Type*} {n : ℕ} (x : α) (b : Fin n → α) :
Set.range (Fin.cons x b : Fin n.succ → α) = insert x (Set.range b) := by
rw [range_fin_succ, cons_zero, tail_cons]
#align fin.range_cons Fin.range_cons
section Append
/-- Append a tuple of length `m` to a tuple of length `n` to get a tuple of length `m + n`.
This is a non-dependent version of `Fin.add_cases`. -/
def append {α : Type*} (a : Fin m → α) (b : Fin n → α) : Fin (m + n) → α :=
@Fin.addCases _ _ (fun _ => α) a b
#align fin.append Fin.append
@[simp]
theorem append_left {α : Type*} (u : Fin m → α) (v : Fin n → α) (i : Fin m) :
append u v (Fin.castAdd n i) = u i :=
addCases_left _
#align fin.append_left Fin.append_left
@[simp]
theorem append_right {α : Type*} (u : Fin m → α) (v : Fin n → α) (i : Fin n) :
append u v (natAdd m i) = v i :=
addCases_right _
#align fin.append_right Fin.append_right
theorem append_right_nil {α : Type*} (u : Fin m → α) (v : Fin n → α) (hv : n = 0) :
append u v = u ∘ Fin.cast (by rw [hv, Nat.add_zero]) := by
refine funext (Fin.addCases (fun l => ?_) fun r => ?_)
· rw [append_left, Function.comp_apply]
refine congr_arg u (Fin.ext ?_)
simp
· exact (Fin.cast hv r).elim0
#align fin.append_right_nil Fin.append_right_nil
@[simp]
theorem append_elim0 {α : Type*} (u : Fin m → α) :
append u Fin.elim0 = u ∘ Fin.cast (Nat.add_zero _) :=
append_right_nil _ _ rfl
#align fin.append_elim0 Fin.append_elim0
theorem append_left_nil {α : Type*} (u : Fin m → α) (v : Fin n → α) (hu : m = 0) :
append u v = v ∘ Fin.cast (by rw [hu, Nat.zero_add]) := by
refine funext (Fin.addCases (fun l => ?_) fun r => ?_)
· exact (Fin.cast hu l).elim0
· rw [append_right, Function.comp_apply]
refine congr_arg v (Fin.ext ?_)
simp [hu]
#align fin.append_left_nil Fin.append_left_nil
@[simp]
theorem elim0_append {α : Type*} (v : Fin n → α) :
append Fin.elim0 v = v ∘ Fin.cast (Nat.zero_add _) :=
append_left_nil _ _ rfl
#align fin.elim0_append Fin.elim0_append
theorem append_assoc {p : ℕ} {α : Type*} (a : Fin m → α) (b : Fin n → α) (c : Fin p → α) :
append (append a b) c = append a (append b c) ∘ Fin.cast (Nat.add_assoc ..) := by
ext i
rw [Function.comp_apply]
refine Fin.addCases (fun l => ?_) (fun r => ?_) i
· rw [append_left]
refine Fin.addCases (fun ll => ?_) (fun lr => ?_) l
· rw [append_left]
simp [castAdd_castAdd]
· rw [append_right]
simp [castAdd_natAdd]
· rw [append_right]
simp [← natAdd_natAdd]
#align fin.append_assoc Fin.append_assoc
/-- Appending a one-tuple to the left is the same as `Fin.cons`. -/
theorem append_left_eq_cons {α : Type*} {n : ℕ} (x₀ : Fin 1 → α) (x : Fin n → α) :
Fin.append x₀ x = Fin.cons (x₀ 0) x ∘ Fin.cast (Nat.add_comm ..) := by
ext i
refine Fin.addCases ?_ ?_ i <;> clear i
· intro i
rw [Subsingleton.elim i 0, Fin.append_left, Function.comp_apply, eq_comm]
exact Fin.cons_zero _ _
· intro i
rw [Fin.append_right, Function.comp_apply, Fin.cast_natAdd, eq_comm, Fin.addNat_one]
exact Fin.cons_succ _ _ _
#align fin.append_left_eq_cons Fin.append_left_eq_cons
/-- `Fin.cons` is the same as appending a one-tuple to the left. -/
theorem cons_eq_append {α : Type*} (x : α) (xs : Fin n → α) :
cons x xs = append (cons x Fin.elim0) xs ∘ Fin.cast (Nat.add_comm ..) := by
funext i; simp [append_left_eq_cons]
@[simp] lemma append_cast_left {n m} {α : Type*} (xs : Fin n → α) (ys : Fin m → α) (n' : ℕ)
(h : n' = n) :
Fin.append (xs ∘ Fin.cast h) ys = Fin.append xs ys ∘ (Fin.cast <| by rw [h]) := by
subst h; simp
@[simp] lemma append_cast_right {n m} {α : Type*} (xs : Fin n → α) (ys : Fin m → α) (m' : ℕ)
(h : m' = m) :
Fin.append xs (ys ∘ Fin.cast h) = Fin.append xs ys ∘ (Fin.cast <| by rw [h]) := by
subst h; simp
lemma append_rev {m n} {α : Type*} (xs : Fin m → α) (ys : Fin n → α) (i : Fin (m + n)) :
append xs ys (rev i) = append (ys ∘ rev) (xs ∘ rev) (cast (Nat.add_comm ..) i) := by
rcases rev_surjective i with ⟨i, rfl⟩
rw [rev_rev]
induction i using Fin.addCases
· simp [rev_castAdd]
· simp [cast_rev, rev_addNat]
lemma append_comp_rev {m n} {α : Type*} (xs : Fin m → α) (ys : Fin n → α) :
append xs ys ∘ rev = append (ys ∘ rev) (xs ∘ rev) ∘ cast (Nat.add_comm ..) :=
funext <| append_rev xs ys
end Append
section Repeat
/-- Repeat `a` `m` times. For example `Fin.repeat 2 ![0, 3, 7] = ![0, 3, 7, 0, 3, 7]`. -/
-- Porting note: removed @[simp]
def «repeat» {α : Type*} (m : ℕ) (a : Fin n → α) : Fin (m * n) → α
| i => a i.modNat
#align fin.repeat Fin.repeat
-- Porting note: added (leanprover/lean4#2042)
@[simp]
theorem repeat_apply {α : Type*} (a : Fin n → α) (i : Fin (m * n)) :
Fin.repeat m a i = a i.modNat :=
rfl
@[simp]
theorem repeat_zero {α : Type*} (a : Fin n → α) :
Fin.repeat 0 a = Fin.elim0 ∘ cast (Nat.zero_mul _) :=
funext fun x => (cast (Nat.zero_mul _) x).elim0
#align fin.repeat_zero Fin.repeat_zero
@[simp]
theorem repeat_one {α : Type*} (a : Fin n → α) : Fin.repeat 1 a = a ∘ cast (Nat.one_mul _) := by
generalize_proofs h
apply funext
rw [(Fin.rightInverse_cast h.symm).surjective.forall]
intro i
simp [modNat, Nat.mod_eq_of_lt i.is_lt]
#align fin.repeat_one Fin.repeat_one
theorem repeat_succ {α : Type*} (a : Fin n → α) (m : ℕ) :
Fin.repeat m.succ a =
append a (Fin.repeat m a) ∘ cast ((Nat.succ_mul _ _).trans (Nat.add_comm ..)) := by
generalize_proofs h
apply funext
rw [(Fin.rightInverse_cast h.symm).surjective.forall]
refine Fin.addCases (fun l => ?_) fun r => ?_
· simp [modNat, Nat.mod_eq_of_lt l.is_lt]
· simp [modNat]
#align fin.repeat_succ Fin.repeat_succ
@[simp]
theorem repeat_add {α : Type*} (a : Fin n → α) (m₁ m₂ : ℕ) : Fin.repeat (m₁ + m₂) a =
append (Fin.repeat m₁ a) (Fin.repeat m₂ a) ∘ cast (Nat.add_mul ..) := by
generalize_proofs h
apply funext
rw [(Fin.rightInverse_cast h.symm).surjective.forall]
refine Fin.addCases (fun l => ?_) fun r => ?_
· simp [modNat, Nat.mod_eq_of_lt l.is_lt]
· simp [modNat, Nat.add_mod]
#align fin.repeat_add Fin.repeat_add
theorem repeat_rev {α : Type*} (a : Fin n → α) (k : Fin (m * n)) :
Fin.repeat m a k.rev = Fin.repeat m (a ∘ Fin.rev) k :=
congr_arg a k.modNat_rev
theorem repeat_comp_rev {α} (a : Fin n → α) :
Fin.repeat m a ∘ Fin.rev = Fin.repeat m (a ∘ Fin.rev) :=
funext <| repeat_rev a
end Repeat
end Tuple
section TupleRight
/-! In the previous section, we have discussed inserting or removing elements on the left of a
tuple. In this section, we do the same on the right. A difference is that `Fin (n+1)` is constructed
inductively from `Fin n` starting from the left, not from the right. This implies that Lean needs
more help to realize that elements belong to the right types, i.e., we need to insert casts at
several places. -/
-- Porting note: `i.castSucc` does not work like it did in Lean 3;
-- `(castSucc i)` must be used.
variable {α : Fin (n + 1) → Type u} (x : α (last n)) (q : ∀ i, α i)
(p : ∀ i : Fin n, α (castSucc i)) (i : Fin n) (y : α (castSucc i)) (z : α (last n))
/-- The beginning of an `n+1` tuple, i.e., its first `n` entries -/
def init (q : ∀ i, α i) (i : Fin n) : α (castSucc i) :=
q (castSucc i)
#align fin.init Fin.init
theorem init_def {n : ℕ} {α : Fin (n + 1) → Type*} {q : ∀ i, α i} :
(init fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q (castSucc k) :=
rfl
#align fin.init_def Fin.init_def
/-- Adding an element at the end of an `n`-tuple, to get an `n+1`-tuple. The name `snoc` comes from
`cons` (i.e., adding an element to the left of a tuple) read in reverse order. -/
def snoc (p : ∀ i : Fin n, α (castSucc i)) (x : α (last n)) (i : Fin (n + 1)) : α i :=
if h : i.val < n then _root_.cast (by rw [Fin.castSucc_castLT i h]) (p (castLT i h))
else _root_.cast (by rw [eq_last_of_not_lt h]) x
#align fin.snoc Fin.snoc
@[simp]
theorem init_snoc : init (snoc p x) = p := by
ext i
simp only [init, snoc, coe_castSucc, is_lt, cast_eq, dite_true]
convert cast_eq rfl (p i)
#align fin.init_snoc Fin.init_snoc
@[simp]
theorem snoc_castSucc : snoc p x (castSucc i) = p i := by
simp only [snoc, coe_castSucc, is_lt, cast_eq, dite_true]
convert cast_eq rfl (p i)
#align fin.snoc_cast_succ Fin.snoc_castSucc
@[simp]
theorem snoc_comp_castSucc {n : ℕ} {α : Sort _} {a : α} {f : Fin n → α} :
(snoc f a : Fin (n + 1) → α) ∘ castSucc = f :=
funext fun i ↦ by rw [Function.comp_apply, snoc_castSucc]
#align fin.snoc_comp_cast_succ Fin.snoc_comp_castSucc
@[simp]
theorem snoc_last : snoc p x (last n) = x := by simp [snoc]
#align fin.snoc_last Fin.snoc_last
lemma snoc_zero {α : Type*} (p : Fin 0 → α) (x : α) :
Fin.snoc p x = fun _ ↦ x := by
ext y
have : Subsingleton (Fin (0 + 1)) := Fin.subsingleton_one
simp only [Subsingleton.elim y (Fin.last 0), snoc_last]
@[simp]
theorem snoc_comp_nat_add {n m : ℕ} {α : Sort _} (f : Fin (m + n) → α) (a : α) :
(snoc f a : Fin _ → α) ∘ (natAdd m : Fin (n + 1) → Fin (m + n + 1)) =
snoc (f ∘ natAdd m) a := by
ext i
refine Fin.lastCases ?_ (fun i ↦ ?_) i
· simp only [Function.comp_apply]
rw [snoc_last, natAdd_last, snoc_last]
· simp only [comp_apply, snoc_castSucc]
rw [natAdd_castSucc, snoc_castSucc]
#align fin.snoc_comp_nat_add Fin.snoc_comp_nat_add
@[simp]
theorem snoc_cast_add {α : Fin (n + m + 1) → Type*} (f : ∀ i : Fin (n + m), α (castSucc i))
(a : α (last (n + m))) (i : Fin n) : (snoc f a) (castAdd (m + 1) i) = f (castAdd m i) :=
dif_pos _
#align fin.snoc_cast_add Fin.snoc_cast_add
-- Porting note: Had to `unfold comp`
@[simp]
theorem snoc_comp_cast_add {n m : ℕ} {α : Sort _} (f : Fin (n + m) → α) (a : α) :
(snoc f a : Fin _ → α) ∘ castAdd (m + 1) = f ∘ castAdd m :=
funext (by unfold comp; exact snoc_cast_add _ _)
#align fin.snoc_comp_cast_add Fin.snoc_comp_cast_add
/-- Updating a tuple and adding an element at the end commute. -/
@[simp]
theorem snoc_update : snoc (update p i y) x = update (snoc p x) (castSucc i) y := by
ext j
by_cases h : j.val < n
· rw [snoc]
simp only [h]
simp only [dif_pos]
by_cases h' : j = castSucc i
· have C1 : α (castSucc i) = α j := by rw [h']
have E1 : update (snoc p x) (castSucc i) y j = _root_.cast C1 y := by
have : update (snoc p x) j (_root_.cast C1 y) j = _root_.cast C1 y := by simp
convert this
· exact h'.symm
· exact heq_of_cast_eq (congr_arg α (Eq.symm h')) rfl
have C2 : α (castSucc i) = α (castSucc (castLT j h)) := by rw [castSucc_castLT, h']
have E2 : update p i y (castLT j h) = _root_.cast C2 y := by
have : update p (castLT j h) (_root_.cast C2 y) (castLT j h) = _root_.cast C2 y := by simp
convert this
· simp [h, h']
· exact heq_of_cast_eq C2 rfl
rw [E1, E2]
exact eq_rec_compose (Eq.trans C2.symm C1) C2 y
· have : ¬castLT j h = i := by
intro E
apply h'
rw [← E, castSucc_castLT]
simp [h', this, snoc, h]
· rw [eq_last_of_not_lt h]
simp [Ne.symm (ne_of_lt (castSucc_lt_last i))]
#align fin.snoc_update Fin.snoc_update
/-- Adding an element at the beginning of a tuple and then updating it amounts to adding it
directly. -/
theorem update_snoc_last : update (snoc p x) (last n) z = snoc p z := by
ext j
by_cases h : j.val < n
· have : j ≠ last n := ne_of_lt h
simp [h, update_noteq, this, snoc]
· rw [eq_last_of_not_lt h]
simp
#align fin.update_snoc_last Fin.update_snoc_last
/-- Concatenating the first element of a tuple with its tail gives back the original tuple -/
@[simp]
theorem snoc_init_self : snoc (init q) (q (last n)) = q := by
ext j
by_cases h : j.val < n
· simp only [init, snoc, h, cast_eq, dite_true, castSucc_castLT]
· rw [eq_last_of_not_lt h]
simp
#align fin.snoc_init_self Fin.snoc_init_self
/-- Updating the last element of a tuple does not change the beginning. -/
@[simp]
| Mathlib/Data/Fin/Tuple/Basic.lean | 601 | 603 | theorem init_update_last : init (update q (last n) z) = init q := by |
ext j
simp [init, ne_of_lt, castSucc_lt_last]
|
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