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/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura
-/
import Mathlib.Init.Logic
import Mathlib.Init.Function
import Mathlib.Init.Algebra.Classes
import Batteries.Util.LibraryNote
import Batteries.Tactic.Lint.Basic
#align_import logic.basic from "leanprover-community/mathlib"@"3365b20c2ffa7c35e47e5209b89ba9abdddf3ffe"
#align_import init.ite_simp from "leanprover-community/lean"@"4a03bdeb31b3688c31d02d7ff8e0ff2e5d6174db"
/-!
# Basic logic properties
This file is one of the earliest imports in mathlib.
## Implementation notes
Theorems that require decidability hypotheses are in the namespace `Decidable`.
Classical versions are in the namespace `Classical`.
-/
open Function
attribute [local instance 10] Classical.propDecidable
section Miscellany
-- Porting note: the following `inline` attributes have been omitted,
-- on the assumption that this issue has been dealt with properly in Lean 4.
-- /- We add the `inline` attribute to optimize VM computation using these declarations.
-- For example, `if p ∧ q then ... else ...` will not evaluate the decidability
-- of `q` if `p` is false. -/
-- attribute [inline]
-- And.decidable Or.decidable Decidable.false Xor.decidable Iff.decidable Decidable.true
-- Implies.decidable Not.decidable Ne.decidable Bool.decidableEq Decidable.toBool
attribute [simp] cast_eq cast_heq imp_false
/-- An identity function with its main argument implicit. This will be printed as `hidden` even
if it is applied to a large term, so it can be used for elision,
as done in the `elide` and `unelide` tactics. -/
abbrev hidden {α : Sort*} {a : α} := a
#align hidden hidden
variable {α : Sort*}
instance (priority := 10) decidableEq_of_subsingleton [Subsingleton α] : DecidableEq α :=
fun a b ↦ isTrue (Subsingleton.elim a b)
#align decidable_eq_of_subsingleton decidableEq_of_subsingleton
instance [Subsingleton α] (p : α → Prop) : Subsingleton (Subtype p) :=
⟨fun ⟨x, _⟩ ⟨y, _⟩ ↦ by cases Subsingleton.elim x y; rfl⟩
#align pempty PEmpty
theorem congr_heq {α β γ : Sort _} {f : α → γ} {g : β → γ} {x : α} {y : β}
(h₁ : HEq f g) (h₂ : HEq x y) : f x = g y := by
cases h₂; cases h₁; rfl
#align congr_heq congr_heq
theorem congr_arg_heq {β : α → Sort*} (f : ∀ a, β a) :
∀ {a₁ a₂ : α}, a₁ = a₂ → HEq (f a₁) (f a₂)
| _, _, rfl => HEq.rfl
#align congr_arg_heq congr_arg_heq
theorem ULift.down_injective {α : Sort _} : Function.Injective (@ULift.down α)
| ⟨a⟩, ⟨b⟩, _ => by congr
#align ulift.down_injective ULift.down_injective
@[simp] theorem ULift.down_inj {α : Sort _} {a b : ULift α} : a.down = b.down ↔ a = b :=
⟨fun h ↦ ULift.down_injective h, fun h ↦ by rw [h]⟩
#align ulift.down_inj ULift.down_inj
theorem PLift.down_injective : Function.Injective (@PLift.down α)
| ⟨a⟩, ⟨b⟩, _ => by congr
#align plift.down_injective PLift.down_injective
@[simp] theorem PLift.down_inj {a b : PLift α} : a.down = b.down ↔ a = b :=
⟨fun h ↦ PLift.down_injective h, fun h ↦ by rw [h]⟩
#align plift.down_inj PLift.down_inj
@[simp] theorem eq_iff_eq_cancel_left {b c : α} : (∀ {a}, a = b ↔ a = c) ↔ b = c :=
⟨fun h ↦ by rw [← h], fun h a ↦ by rw [h]⟩
#align eq_iff_eq_cancel_left eq_iff_eq_cancel_left
@[simp] theorem eq_iff_eq_cancel_right {a b : α} : (∀ {c}, a = c ↔ b = c) ↔ a = b :=
⟨fun h ↦ by rw [h], fun h a ↦ by rw [h]⟩
#align eq_iff_eq_cancel_right eq_iff_eq_cancel_right
lemma ne_and_eq_iff_right {a b c : α} (h : b ≠ c) : a ≠ b ∧ a = c ↔ a = c :=
and_iff_right_of_imp (fun h2 => h2.symm ▸ h.symm)
#align ne_and_eq_iff_right ne_and_eq_iff_right
/-- Wrapper for adding elementary propositions to the type class systems.
Warning: this can easily be abused. See the rest of this docstring for details.
Certain propositions should not be treated as a class globally,
but sometimes it is very convenient to be able to use the type class system
in specific circumstances.
For example, `ZMod p` is a field if and only if `p` is a prime number.
In order to be able to find this field instance automatically by type class search,
we have to turn `p.prime` into an instance implicit assumption.
On the other hand, making `Nat.prime` a class would require a major refactoring of the library,
and it is questionable whether making `Nat.prime` a class is desirable at all.
The compromise is to add the assumption `[Fact p.prime]` to `ZMod.field`.
In particular, this class is not intended for turning the type class system
into an automated theorem prover for first order logic. -/
class Fact (p : Prop) : Prop where
/-- `Fact.out` contains the unwrapped witness for the fact represented by the instance of
`Fact p`. -/
out : p
#align fact Fact
library_note "fact non-instances"/--
In most cases, we should not have global instances of `Fact`; typeclass search only reads the head
symbol and then tries any instances, which means that adding any such instance will cause slowdowns
everywhere. We instead make them as lemmata and make them local instances as required.
-/
theorem Fact.elim {p : Prop} (h : Fact p) : p := h.1
theorem fact_iff {p : Prop} : Fact p ↔ p := ⟨fun h ↦ h.1, fun h ↦ ⟨h⟩⟩
#align fact_iff fact_iff
#align fact.elim Fact.elim
instance {p : Prop} [Decidable p] : Decidable (Fact p) :=
decidable_of_iff _ fact_iff.symm
/-- Swaps two pairs of arguments to a function. -/
abbrev Function.swap₂ {ι₁ ι₂ : Sort*} {κ₁ : ι₁ → Sort*} {κ₂ : ι₂ → Sort*}
{φ : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Sort*} (f : ∀ i₁ j₁ i₂ j₂, φ i₁ j₁ i₂ j₂)
(i₂ j₂ i₁ j₁) : φ i₁ j₁ i₂ j₂ := f i₁ j₁ i₂ j₂
#align function.swap₂ Function.swap₂
-- Porting note: these don't work as intended any more
-- /-- If `x : α . tac_name` then `x.out : α`. These are definitionally equal, but this can
-- nevertheless be useful for various reasons, e.g. to apply further projection notation or in an
-- argument to `simp`. -/
-- def autoParam'.out {α : Sort*} {n : Name} (x : autoParam' α n) : α := x
-- /-- If `x : α := d` then `x.out : α`. These are definitionally equal, but this can
-- nevertheless be useful for various reasons, e.g. to apply further projection notation or in an
-- argument to `simp`. -/
-- def optParam.out {α : Sort*} {d : α} (x : α := d) : α := x
end Miscellany
open Function
/-!
### Declarations about propositional connectives
-/
section Propositional
/-! ### Declarations about `implies` -/
instance : IsRefl Prop Iff := ⟨Iff.refl⟩
instance : IsTrans Prop Iff := ⟨fun _ _ _ ↦ Iff.trans⟩
alias Iff.imp := imp_congr
#align iff.imp Iff.imp
#align eq_true_eq_id eq_true_eq_id
#align imp_and_distrib imp_and
#align imp_iff_right imp_iff_rightₓ -- reorder implicits
#align imp_iff_not imp_iff_notₓ -- reorder implicits
-- This is a duplicate of `Classical.imp_iff_right_iff`. Deprecate?
theorem imp_iff_right_iff {a b : Prop} : (a → b ↔ b) ↔ a ∨ b := Decidable.imp_iff_right_iff
#align imp_iff_right_iff imp_iff_right_iff
-- This is a duplicate of `Classical.and_or_imp`. Deprecate?
theorem and_or_imp {a b c : Prop} : a ∧ b ∨ (a → c) ↔ a → b ∨ c := Decidable.and_or_imp
#align and_or_imp and_or_imp
/-- Provide modus tollens (`mt`) as dot notation for implications. -/
protected theorem Function.mt {a b : Prop} : (a → b) → ¬b → ¬a := mt
#align function.mt Function.mt
/-! ### Declarations about `not` -/
alias dec_em := Decidable.em
#align dec_em dec_em
theorem dec_em' (p : Prop) [Decidable p] : ¬p ∨ p := (dec_em p).symm
#align dec_em' dec_em'
alias em := Classical.em
#align em em
theorem em' (p : Prop) : ¬p ∨ p := (em p).symm
#align em' em'
theorem or_not {p : Prop} : p ∨ ¬p := em _
#align or_not or_not
theorem Decidable.eq_or_ne {α : Sort*} (x y : α) [Decidable (x = y)] : x = y ∨ x ≠ y :=
dec_em <| x = y
#align decidable.eq_or_ne Decidable.eq_or_ne
theorem Decidable.ne_or_eq {α : Sort*} (x y : α) [Decidable (x = y)] : x ≠ y ∨ x = y :=
dec_em' <| x = y
#align decidable.ne_or_eq Decidable.ne_or_eq
theorem eq_or_ne {α : Sort*} (x y : α) : x = y ∨ x ≠ y := em <| x = y
#align eq_or_ne eq_or_ne
theorem ne_or_eq {α : Sort*} (x y : α) : x ≠ y ∨ x = y := em' <| x = y
#align ne_or_eq ne_or_eq
theorem by_contradiction {p : Prop} : (¬p → False) → p := Decidable.by_contradiction
#align classical.by_contradiction by_contradiction
#align by_contradiction by_contradiction
theorem by_cases {p q : Prop} (hpq : p → q) (hnpq : ¬p → q) : q :=
if hp : p then hpq hp else hnpq hp
#align classical.by_cases by_cases
alias by_contra := by_contradiction
#align by_contra by_contra
library_note "decidable namespace"/--
In most of mathlib, we use the law of excluded middle (LEM) and the axiom of choice (AC) freely.
The `Decidable` namespace contains versions of lemmas from the root namespace that explicitly
attempt to avoid the axiom of choice, usually by adding decidability assumptions on the inputs.
You can check if a lemma uses the axiom of choice by using `#print axioms foo` and seeing if
`Classical.choice` appears in the list.
-/
library_note "decidable arguments"/--
As mathlib is primarily classical,
if the type signature of a `def` or `lemma` does not require any `Decidable` instances to state,
it is preferable not to introduce any `Decidable` instances that are needed in the proof
as arguments, but rather to use the `classical` tactic as needed.
In the other direction, when `Decidable` instances do appear in the type signature,
it is better to use explicitly introduced ones rather than allowing Lean to automatically infer
classical ones, as these may cause instance mismatch errors later.
-/
export Classical (not_not)
attribute [simp] not_not
#align not_not Classical.not_not
variable {a b : Prop}
theorem of_not_not {a : Prop} : ¬¬a → a := by_contra
#align of_not_not of_not_not
theorem not_ne_iff {α : Sort*} {a b : α} : ¬a ≠ b ↔ a = b := not_not
#align not_ne_iff not_ne_iff
theorem of_not_imp : ¬(a → b) → a := Decidable.of_not_imp
#align of_not_imp of_not_imp
alias Not.decidable_imp_symm := Decidable.not_imp_symm
#align not.decidable_imp_symm Not.decidable_imp_symm
theorem Not.imp_symm : (¬a → b) → ¬b → a := Not.decidable_imp_symm
#align not.imp_symm Not.imp_symm
theorem not_imp_comm : ¬a → b ↔ ¬b → a := Decidable.not_imp_comm
#align not_imp_comm not_imp_comm
@[simp] theorem not_imp_self : ¬a → a ↔ a := Decidable.not_imp_self
#align not_imp_self not_imp_self
theorem Imp.swap {a b : Sort*} {c : Prop} : a → b → c ↔ b → a → c := ⟨Function.swap, Function.swap⟩
#align imp.swap Imp.swap
alias Iff.not := not_congr
#align iff.not Iff.not
theorem Iff.not_left (h : a ↔ ¬b) : ¬a ↔ b := h.not.trans not_not
#align iff.not_left Iff.not_left
theorem Iff.not_right (h : ¬a ↔ b) : a ↔ ¬b := not_not.symm.trans h.not
#align iff.not_right Iff.not_right
protected lemma Iff.ne {α β : Sort*} {a b : α} {c d : β} : (a = b ↔ c = d) → (a ≠ b ↔ c ≠ d) :=
Iff.not
#align iff.ne Iff.ne
lemma Iff.ne_left {α β : Sort*} {a b : α} {c d : β} : (a = b ↔ c ≠ d) → (a ≠ b ↔ c = d) :=
Iff.not_left
#align iff.ne_left Iff.ne_left
lemma Iff.ne_right {α β : Sort*} {a b : α} {c d : β} : (a ≠ b ↔ c = d) → (a = b ↔ c ≠ d) :=
Iff.not_right
#align iff.ne_right Iff.ne_right
/-! ### Declarations about `Xor'` -/
@[simp] theorem xor_true : Xor' True = Not := by
simp (config := { unfoldPartialApp := true }) [Xor']
#align xor_true xor_true
@[simp] theorem xor_false : Xor' False = id := by ext; simp [Xor']
#align xor_false xor_false
theorem xor_comm (a b : Prop) : Xor' a b = Xor' b a := by simp [Xor', and_comm, or_comm]
#align xor_comm xor_comm
instance : Std.Commutative Xor' := ⟨xor_comm⟩
@[simp] theorem xor_self (a : Prop) : Xor' a a = False := by simp [Xor']
#align xor_self xor_self
@[simp] theorem xor_not_left : Xor' (¬a) b ↔ (a ↔ b) := by by_cases a <;> simp [*]
#align xor_not_left xor_not_left
@[simp] theorem xor_not_right : Xor' a (¬b) ↔ (a ↔ b) := by by_cases a <;> simp [*]
#align xor_not_right xor_not_right
theorem xor_not_not : Xor' (¬a) (¬b) ↔ Xor' a b := by simp [Xor', or_comm, and_comm]
#align xor_not_not xor_not_not
protected theorem Xor'.or (h : Xor' a b) : a ∨ b := h.imp And.left And.left
#align xor.or Xor'.or
/-! ### Declarations about `and` -/
alias Iff.and := and_congr
#align iff.and Iff.and
#align and_congr_left and_congr_leftₓ -- reorder implicits
#align and_congr_right' and_congr_right'ₓ -- reorder implicits
#align and.right_comm and_right_comm
#align and_and_distrib_left and_and_left
#align and_and_distrib_right and_and_right
alias ⟨And.rotate, _⟩ := and_rotate
#align and.rotate And.rotate
#align and.congr_right_iff and_congr_right_iff
#align and.congr_left_iff and_congr_left_iffₓ -- reorder implicits
theorem and_symm_right {α : Sort*} (a b : α) (p : Prop) : p ∧ a = b ↔ p ∧ b = a := by simp [eq_comm]
theorem and_symm_left {α : Sort*} (a b : α) (p : Prop) : a = b ∧ p ↔ b = a ∧ p := by simp [eq_comm]
/-! ### Declarations about `or` -/
alias Iff.or := or_congr
#align iff.or Iff.or
#align or_congr_left' or_congr_left
#align or_congr_right' or_congr_rightₓ -- reorder implicits
#align or.right_comm or_right_comm
alias ⟨Or.rotate, _⟩ := or_rotate
#align or.rotate Or.rotate
@[deprecated Or.imp]
theorem or_of_or_of_imp_of_imp {a b c d : Prop} (h₁ : a ∨ b) (h₂ : a → c) (h₃ : b → d) :
c ∨ d :=
Or.imp h₂ h₃ h₁
#align or_of_or_of_imp_of_imp or_of_or_of_imp_of_imp
@[deprecated Or.imp_left]
theorem or_of_or_of_imp_left {a c b : Prop} (h₁ : a ∨ c) (h : a → b) : b ∨ c := Or.imp_left h h₁
#align or_of_or_of_imp_left or_of_or_of_imp_left
@[deprecated Or.imp_right]
theorem or_of_or_of_imp_right {c a b : Prop} (h₁ : c ∨ a) (h : a → b) : c ∨ b := Or.imp_right h h₁
#align or_of_or_of_imp_right or_of_or_of_imp_right
theorem Or.elim3 {c d : Prop} (h : a ∨ b ∨ c) (ha : a → d) (hb : b → d) (hc : c → d) : d :=
Or.elim h ha fun h₂ ↦ Or.elim h₂ hb hc
#align or.elim3 Or.elim3
theorem Or.imp3 {d e c f : Prop} (had : a → d) (hbe : b → e) (hcf : c → f) :
a ∨ b ∨ c → d ∨ e ∨ f :=
Or.imp had <| Or.imp hbe hcf
#align or.imp3 Or.imp3
#align or_imp_distrib or_imp
export Classical (or_iff_not_imp_left or_iff_not_imp_right)
#align or_iff_not_imp_left Classical.or_iff_not_imp_left
#align or_iff_not_imp_right Classical.or_iff_not_imp_right
theorem not_or_of_imp : (a → b) → ¬a ∨ b := Decidable.not_or_of_imp
#align not_or_of_imp not_or_of_imp
-- See Note [decidable namespace]
protected theorem Decidable.or_not_of_imp [Decidable a] (h : a → b) : b ∨ ¬a :=
dite _ (Or.inl ∘ h) Or.inr
#align decidable.or_not_of_imp Decidable.or_not_of_imp
theorem or_not_of_imp : (a → b) → b ∨ ¬a := Decidable.or_not_of_imp
#align or_not_of_imp or_not_of_imp
theorem imp_iff_not_or : a → b ↔ ¬a ∨ b := Decidable.imp_iff_not_or
#align imp_iff_not_or imp_iff_not_or
theorem imp_iff_or_not {b a : Prop} : b → a ↔ a ∨ ¬b := Decidable.imp_iff_or_not
#align imp_iff_or_not imp_iff_or_not
theorem not_imp_not : ¬a → ¬b ↔ b → a := Decidable.not_imp_not
#align not_imp_not not_imp_not
theorem imp_and_neg_imp_iff (p q : Prop) : (p → q) ∧ (¬p → q) ↔ q := by simp
/-- Provide the reverse of modus tollens (`mt`) as dot notation for implications. -/
protected theorem Function.mtr : (¬a → ¬b) → b → a := not_imp_not.mp
#align function.mtr Function.mtr
#align decidable.or_congr_left Decidable.or_congr_left'
#align decidable.or_congr_right Decidable.or_congr_right'
#align decidable.or_iff_not_imp_right Decidable.or_iff_not_imp_rightₓ -- reorder implicits
#align decidable.imp_iff_or_not Decidable.imp_iff_or_notₓ -- reorder implicits
theorem or_congr_left' {c a b : Prop} (h : ¬c → (a ↔ b)) : a ∨ c ↔ b ∨ c :=
Decidable.or_congr_left' h
#align or_congr_left or_congr_left'
theorem or_congr_right' {c : Prop} (h : ¬a → (b ↔ c)) : a ∨ b ↔ a ∨ c := Decidable.or_congr_right' h
#align or_congr_right or_congr_right'ₓ -- reorder implicits
#align or_iff_left or_iff_leftₓ -- reorder implicits
/-! ### Declarations about distributivity -/
#align and_or_distrib_left and_or_left
#align or_and_distrib_right or_and_right
#align or_and_distrib_left or_and_left
#align and_or_distrib_right and_or_right
/-! Declarations about `iff` -/
alias Iff.iff := iff_congr
#align iff.iff Iff.iff
-- @[simp] -- FIXME simp ignores proof rewrites
theorem iff_mpr_iff_true_intro {P : Prop} (h : P) : Iff.mpr (iff_true_intro h) True.intro = h := rfl
#align iff_mpr_iff_true_intro iff_mpr_iff_true_intro
#align decidable.imp_or_distrib Decidable.imp_or
theorem imp_or {a b c : Prop} : a → b ∨ c ↔ (a → b) ∨ (a → c) := Decidable.imp_or
#align imp_or_distrib imp_or
#align decidable.imp_or_distrib' Decidable.imp_or'
theorem imp_or' {a : Sort*} {b c : Prop} : a → b ∨ c ↔ (a → b) ∨ (a → c) := Decidable.imp_or'
#align imp_or_distrib' imp_or'ₓ -- universes
theorem not_imp : ¬(a → b) ↔ a ∧ ¬b := Decidable.not_imp_iff_and_not
#align not_imp not_imp
theorem peirce (a b : Prop) : ((a → b) → a) → a := Decidable.peirce _ _
#align peirce peirce
theorem not_iff_not : (¬a ↔ ¬b) ↔ (a ↔ b) := Decidable.not_iff_not
#align not_iff_not not_iff_not
theorem not_iff_comm : (¬a ↔ b) ↔ (¬b ↔ a) := Decidable.not_iff_comm
#align not_iff_comm not_iff_comm
theorem not_iff : ¬(a ↔ b) ↔ (¬a ↔ b) := Decidable.not_iff
#align not_iff not_iff
theorem iff_not_comm : (a ↔ ¬b) ↔ (b ↔ ¬a) := Decidable.iff_not_comm
#align iff_not_comm iff_not_comm
theorem iff_iff_and_or_not_and_not : (a ↔ b) ↔ a ∧ b ∨ ¬a ∧ ¬b :=
Decidable.iff_iff_and_or_not_and_not
#align iff_iff_and_or_not_and_not iff_iff_and_or_not_and_not
theorem iff_iff_not_or_and_or_not : (a ↔ b) ↔ (¬a ∨ b) ∧ (a ∨ ¬b) :=
Decidable.iff_iff_not_or_and_or_not
#align iff_iff_not_or_and_or_not iff_iff_not_or_and_or_not
theorem not_and_not_right : ¬(a ∧ ¬b) ↔ a → b := Decidable.not_and_not_right
#align not_and_not_right not_and_not_right
#align decidable_of_iff decidable_of_iff
#align decidable_of_iff' decidable_of_iff'
#align decidable_of_bool decidable_of_bool
/-! ### De Morgan's laws -/
#align decidable.not_and_distrib Decidable.not_and_iff_or_not_not
#align decidable.not_and_distrib' Decidable.not_and_iff_or_not_not'
/-- One of **de Morgan's laws**: the negation of a conjunction is logically equivalent to the
disjunction of the negations. -/
theorem not_and_or : ¬(a ∧ b) ↔ ¬a ∨ ¬b := Decidable.not_and_iff_or_not_not
#align not_and_distrib not_and_or
#align not_or_distrib not_or
theorem or_iff_not_and_not : a ∨ b ↔ ¬(¬a ∧ ¬b) := Decidable.or_iff_not_and_not
#align or_iff_not_and_not or_iff_not_and_not
theorem and_iff_not_or_not : a ∧ b ↔ ¬(¬a ∨ ¬b) := Decidable.and_iff_not_or_not
#align and_iff_not_or_not and_iff_not_or_not
@[simp] theorem not_xor (P Q : Prop) : ¬Xor' P Q ↔ (P ↔ Q) := by
simp only [not_and, Xor', not_or, not_not, ← iff_iff_implies_and_implies]
#align not_xor not_xor
theorem xor_iff_not_iff (P Q : Prop) : Xor' P Q ↔ ¬ (P ↔ Q) := (not_xor P Q).not_right
#align xor_iff_not_iff xor_iff_not_iff
theorem xor_iff_iff_not : Xor' a b ↔ (a ↔ ¬b) := by simp only [← @xor_not_right a, not_not]
#align xor_iff_iff_not xor_iff_iff_not
theorem xor_iff_not_iff' : Xor' a b ↔ (¬a ↔ b) := by simp only [← @xor_not_left _ b, not_not]
#align xor_iff_not_iff' xor_iff_not_iff'
end Propositional
/-! ### Declarations about equality -/
alias Membership.mem.ne_of_not_mem := ne_of_mem_of_not_mem
alias Membership.mem.ne_of_not_mem' := ne_of_mem_of_not_mem'
#align has_mem.mem.ne_of_not_mem Membership.mem.ne_of_not_mem
#align has_mem.mem.ne_of_not_mem' Membership.mem.ne_of_not_mem'
section Equality
-- todo: change name
theorem forall_cond_comm {α} {s : α → Prop} {p : α → α → Prop} :
(∀ a, s a → ∀ b, s b → p a b) ↔ ∀ a b, s a → s b → p a b :=
⟨fun h a b ha hb ↦ h a ha b hb, fun h a ha b hb ↦ h a b ha hb⟩
#align ball_cond_comm forall_cond_comm
theorem forall_mem_comm {α β} [Membership α β] {s : β} {p : α → α → Prop} :
(∀ a (_ : a ∈ s) b (_ : b ∈ s), p a b) ↔ ∀ a b, a ∈ s → b ∈ s → p a b :=
forall_cond_comm
#align ball_mem_comm forall_mem_comm
@[deprecated (since := "2024-03-23")] alias ball_cond_comm := forall_cond_comm
@[deprecated (since := "2024-03-23")] alias ball_mem_comm := forall_mem_comm
#align ne_of_apply_ne ne_of_apply_ne
lemma ne_of_eq_of_ne {α : Sort*} {a b c : α} (h₁ : a = b) (h₂ : b ≠ c) : a ≠ c := h₁.symm ▸ h₂
lemma ne_of_ne_of_eq {α : Sort*} {a b c : α} (h₁ : a ≠ b) (h₂ : b = c) : a ≠ c := h₂ ▸ h₁
alias Eq.trans_ne := ne_of_eq_of_ne
alias Ne.trans_eq := ne_of_ne_of_eq
#align eq.trans_ne Eq.trans_ne
#align ne.trans_eq Ne.trans_eq
theorem eq_equivalence {α : Sort*} : Equivalence (@Eq α) :=
⟨Eq.refl, @Eq.symm _, @Eq.trans _⟩
#align eq_equivalence eq_equivalence
-- These were migrated to Batteries but the `@[simp]` attributes were (mysteriously?) removed.
attribute [simp] eq_mp_eq_cast eq_mpr_eq_cast
#align eq_mp_eq_cast eq_mp_eq_cast
#align eq_mpr_eq_cast eq_mpr_eq_cast
#align cast_cast cast_cast
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_refl_left {α β : Sort*} (f : α → β) {a b : α} (h : a = b) :
congr (Eq.refl f) h = congr_arg f h := rfl
#align congr_refl_left congr_refl_left
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_refl_right {α β : Sort*} {f g : α → β} (h : f = g) (a : α) :
congr h (Eq.refl a) = congr_fun h a := rfl
#align congr_refl_right congr_refl_right
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_arg_refl {α β : Sort*} (f : α → β) (a : α) :
congr_arg f (Eq.refl a) = Eq.refl (f a) :=
rfl
#align congr_arg_refl congr_arg_refl
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_fun_rfl {α β : Sort*} (f : α → β) (a : α) : congr_fun (Eq.refl f) a = Eq.refl (f a) :=
rfl
#align congr_fun_rfl congr_fun_rfl
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_fun_congr_arg {α β γ : Sort*} (f : α → β → γ) {a a' : α} (p : a = a') (b : β) :
congr_fun (congr_arg f p) b = congr_arg (fun a ↦ f a b) p := rfl
#align congr_fun_congr_arg congr_fun_congr_arg
#align heq_of_cast_eq heq_of_cast_eq
#align cast_eq_iff_heq cast_eq_iff_heq
| Mathlib/Logic/Basic.lean | 591 | 592 | theorem Eq.rec_eq_cast {α : Sort _} {P : α → Sort _} {x y : α} (h : x = y) (z : P x) :
h ▸ z = cast (congr_arg P h) z := by | induction h; rfl
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Data.ENNReal.Real
#align_import data.real.conjugate_exponents from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Real conjugate exponents
This file defines conjugate exponents in `ℝ` and `ℝ≥0`. Real numbers `p` and `q` are *conjugate* if
they are both greater than `1` and satisfy `p⁻¹ + q⁻¹ = 1`. This property shows up often in
analysis, especially when dealing with `L^p` spaces.
## Main declarations
* `Real.IsConjExponent`: Predicate for two real numbers to be conjugate.
* `Real.conjExponent`: Conjugate exponent of a real number.
* `NNReal.IsConjExponent`: Predicate for two nonnegative real numbers to be conjugate.
* `NNReal.conjExponent`: Conjugate exponent of a nonnegative real number.
## TODO
* Eradicate the `1 / p` spelling in lemmas.
* Do we want an `ℝ≥0∞` version?
-/
noncomputable section
open scoped ENNReal
namespace Real
/-- Two real exponents `p, q` are conjugate if they are `> 1` and satisfy the equality
`1/p + 1/q = 1`. This condition shows up in many theorems in analysis, notably related to `L^p`
norms. -/
@[mk_iff]
structure IsConjExponent (p q : ℝ) : Prop where
one_lt : 1 < p
inv_add_inv_conj : p⁻¹ + q⁻¹ = 1
#align real.is_conjugate_exponent Real.IsConjExponent
/-- The conjugate exponent of `p` is `q = p/(p-1)`, so that `1/p + 1/q = 1`. -/
def conjExponent (p : ℝ) : ℝ := p / (p - 1)
#align real.conjugate_exponent Real.conjExponent
variable {a b p q : ℝ} (h : p.IsConjExponent q)
namespace IsConjExponent
/- Register several non-vanishing results following from the fact that `p` has a conjugate exponent
`q`: many computations using these exponents require clearing out denominators, which can be done
with `field_simp` given a proof that these denominators are non-zero, so we record the most usual
ones. -/
theorem pos : 0 < p := lt_trans zero_lt_one h.one_lt
#align real.is_conjugate_exponent.pos Real.IsConjExponent.pos
theorem nonneg : 0 ≤ p := le_of_lt h.pos
#align real.is_conjugate_exponent.nonneg Real.IsConjExponent.nonneg
theorem ne_zero : p ≠ 0 := ne_of_gt h.pos
#align real.is_conjugate_exponent.ne_zero Real.IsConjExponent.ne_zero
theorem sub_one_pos : 0 < p - 1 := sub_pos.2 h.one_lt
#align real.is_conjugate_exponent.sub_one_pos Real.IsConjExponent.sub_one_pos
theorem sub_one_ne_zero : p - 1 ≠ 0 := ne_of_gt h.sub_one_pos
#align real.is_conjugate_exponent.sub_one_ne_zero Real.IsConjExponent.sub_one_ne_zero
protected lemma inv_pos : 0 < p⁻¹ := inv_pos.2 h.pos
protected lemma inv_nonneg : 0 ≤ p⁻¹ := h.inv_pos.le
protected lemma inv_ne_zero : p⁻¹ ≠ 0 := h.inv_pos.ne'
theorem one_div_pos : 0 < 1 / p := _root_.one_div_pos.2 h.pos
#align real.is_conjugate_exponent.one_div_pos Real.IsConjExponent.one_div_pos
theorem one_div_nonneg : 0 ≤ 1 / p := le_of_lt h.one_div_pos
#align real.is_conjugate_exponent.one_div_nonneg Real.IsConjExponent.one_div_nonneg
theorem one_div_ne_zero : 1 / p ≠ 0 := ne_of_gt h.one_div_pos
#align real.is_conjugate_exponent.one_div_ne_zero Real.IsConjExponent.one_div_ne_zero
theorem conj_eq : q = p / (p - 1) := by
have := h.inv_add_inv_conj
rw [← eq_sub_iff_add_eq', inv_eq_iff_eq_inv] at this
field_simp [this, h.ne_zero]
#align real.is_conjugate_exponent.conj_eq Real.IsConjExponent.conj_eq
lemma conjExponent_eq : conjExponent p = q := h.conj_eq.symm
#align real.is_conjugate_exponent.conjugate_eq Real.IsConjExponent.conjExponent_eq
lemma one_sub_inv : 1 - p⁻¹ = q⁻¹ := sub_eq_of_eq_add' h.inv_add_inv_conj.symm
lemma inv_sub_one : p⁻¹ - 1 = -q⁻¹ := by rw [← h.inv_add_inv_conj, sub_add_cancel_left]
theorem sub_one_mul_conj : (p - 1) * q = p :=
mul_comm q (p - 1) ▸ (eq_div_iff h.sub_one_ne_zero).1 h.conj_eq
#align real.is_conjugate_exponent.sub_one_mul_conj Real.IsConjExponent.sub_one_mul_conj
theorem mul_eq_add : p * q = p + q := by
simpa only [sub_mul, sub_eq_iff_eq_add, one_mul] using h.sub_one_mul_conj
#align real.is_conjugate_exponent.mul_eq_add Real.IsConjExponent.mul_eq_add
@[symm] protected lemma symm : q.IsConjExponent p where
one_lt := by simpa only [h.conj_eq] using (one_lt_div h.sub_one_pos).mpr (sub_one_lt p)
inv_add_inv_conj := by simpa [add_comm] using h.inv_add_inv_conj
#align real.is_conjugate_exponent.symm Real.IsConjExponent.symm
theorem div_conj_eq_sub_one : p / q = p - 1 := by
field_simp [h.symm.ne_zero]
rw [h.sub_one_mul_conj]
#align real.is_conjugate_exponent.div_conj_eq_sub_one Real.IsConjExponent.div_conj_eq_sub_one
| Mathlib/Data/Real/ConjExponents.lean | 115 | 118 | theorem inv_add_inv_conj_ennreal : (ENNReal.ofReal p)⁻¹ + (ENNReal.ofReal q)⁻¹ = 1 := by |
rw [← ENNReal.ofReal_one, ← ENNReal.ofReal_inv_of_pos h.pos,
← ENNReal.ofReal_inv_of_pos h.symm.pos, ← ENNReal.ofReal_add h.inv_nonneg h.symm.inv_nonneg,
h.inv_add_inv_conj]
|
/-
Copyright (c) 2019 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.CharP.ExpChar
import Mathlib.Algebra.GeomSum
import Mathlib.Algebra.MvPolynomial.CommRing
import Mathlib.Algebra.MvPolynomial.Equiv
import Mathlib.RingTheory.Polynomial.Content
import Mathlib.RingTheory.UniqueFactorizationDomain
#align_import ring_theory.polynomial.basic from "leanprover-community/mathlib"@"da420a8c6dd5bdfb85c4ced85c34388f633bc6ff"
/-!
# Ring-theoretic supplement of Algebra.Polynomial.
## Main results
* `MvPolynomial.isDomain`:
If a ring is an integral domain, then so is its polynomial ring over finitely many variables.
* `Polynomial.isNoetherianRing`:
Hilbert basis theorem, that if a ring is noetherian then so is its polynomial ring.
* `Polynomial.wfDvdMonoid`:
If an integral domain is a `WFDvdMonoid`, then so is its polynomial ring.
* `Polynomial.uniqueFactorizationMonoid`, `MvPolynomial.uniqueFactorizationMonoid`:
If an integral domain is a `UniqueFactorizationMonoid`, then so is its polynomial ring (of any
number of variables).
-/
noncomputable section
open Polynomial
open Finset
universe u v w
variable {R : Type u} {S : Type*}
namespace Polynomial
section Semiring
variable [Semiring R]
instance instCharP (p : ℕ) [h : CharP R p] : CharP R[X] p :=
let ⟨h⟩ := h
⟨fun n => by rw [← map_natCast C, ← C_0, C_inj, h]⟩
instance instExpChar (p : ℕ) [h : ExpChar R p] : ExpChar R[X] p := by
cases h; exacts [ExpChar.zero, ExpChar.prime ‹_›]
variable (R)
/-- The `R`-submodule of `R[X]` consisting of polynomials of degree ≤ `n`. -/
def degreeLE (n : WithBot ℕ) : Submodule R R[X] :=
⨅ k : ℕ, ⨅ _ : ↑k > n, LinearMap.ker (lcoeff R k)
#align polynomial.degree_le Polynomial.degreeLE
/-- The `R`-submodule of `R[X]` consisting of polynomials of degree < `n`. -/
def degreeLT (n : ℕ) : Submodule R R[X] :=
⨅ k : ℕ, ⨅ (_ : k ≥ n), LinearMap.ker (lcoeff R k)
#align polynomial.degree_lt Polynomial.degreeLT
variable {R}
theorem mem_degreeLE {n : WithBot ℕ} {f : R[X]} : f ∈ degreeLE R n ↔ degree f ≤ n := by
simp only [degreeLE, Submodule.mem_iInf, degree_le_iff_coeff_zero, LinearMap.mem_ker]; rfl
#align polynomial.mem_degree_le Polynomial.mem_degreeLE
@[mono]
theorem degreeLE_mono {m n : WithBot ℕ} (H : m ≤ n) : degreeLE R m ≤ degreeLE R n := fun _ hf =>
mem_degreeLE.2 (le_trans (mem_degreeLE.1 hf) H)
#align polynomial.degree_le_mono Polynomial.degreeLE_mono
theorem degreeLE_eq_span_X_pow [DecidableEq R] {n : ℕ} :
degreeLE R n = Submodule.span R ↑((Finset.range (n + 1)).image fun n => (X : R[X]) ^ n) := by
apply le_antisymm
· intro p hp
replace hp := mem_degreeLE.1 hp
rw [← Polynomial.sum_monomial_eq p, Polynomial.sum]
refine Submodule.sum_mem _ fun k hk => ?_
have := WithBot.coe_le_coe.1 (Finset.sup_le_iff.1 hp k hk)
rw [← C_mul_X_pow_eq_monomial, C_mul']
refine
Submodule.smul_mem _ _
(Submodule.subset_span <|
Finset.mem_coe.2 <|
Finset.mem_image.2 ⟨_, Finset.mem_range.2 (Nat.lt_succ_of_le this), rfl⟩)
rw [Submodule.span_le, Finset.coe_image, Set.image_subset_iff]
intro k hk
apply mem_degreeLE.2
exact
(degree_X_pow_le _).trans (WithBot.coe_le_coe.2 <| Nat.le_of_lt_succ <| Finset.mem_range.1 hk)
set_option linter.uppercaseLean3 false in
#align polynomial.degree_le_eq_span_X_pow Polynomial.degreeLE_eq_span_X_pow
| Mathlib/RingTheory/Polynomial/Basic.lean | 98 | 109 | theorem mem_degreeLT {n : ℕ} {f : R[X]} : f ∈ degreeLT R n ↔ degree f < n := by |
rw [degreeLT, Submodule.mem_iInf]
conv_lhs => intro i; rw [Submodule.mem_iInf]
rw [degree, Finset.max_eq_sup_coe]
rw [Finset.sup_lt_iff ?_]
rotate_left
· apply WithBot.bot_lt_coe
conv_rhs =>
simp only [mem_support_iff]
intro b
rw [Nat.cast_withBot, WithBot.coe_lt_coe, lt_iff_not_le, Ne, not_imp_not]
rfl
|
/-
Copyright (c) 2021 Kevin Kappelmann. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Kappelmann
-/
import Mathlib.Algebra.ContinuedFractions.Computation.Approximations
import Mathlib.Algebra.ContinuedFractions.ConvergentsEquiv
import Mathlib.Algebra.Order.Archimedean
import Mathlib.Tactic.GCongr
import Mathlib.Topology.Order.LeftRightNhds
#align_import algebra.continued_fractions.computation.approximation_corollaries from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Corollaries From Approximation Lemmas (`Algebra.ContinuedFractions.Computation.Approximations`)
## Summary
We show that the generalized_continued_fraction given by `GeneralizedContinuedFraction.of` in fact
is a (regular) continued fraction. Using the equivalence of the convergents computations
(`GeneralizedContinuedFraction.convergents` and `GeneralizedContinuedFraction.convergents'`) for
continued fractions (see `Algebra.ContinuedFractions.ConvergentsEquiv`), it follows that the
convergents computations for `GeneralizedContinuedFraction.of` are equivalent.
Moreover, we show the convergence of the continued fractions computations, that is
`(GeneralizedContinuedFraction.of v).convergents` indeed computes `v` in the limit.
## Main Definitions
- `ContinuedFraction.of` returns the (regular) continued fraction of a value.
## Main Theorems
- `GeneralizedContinuedFraction.of_convergents_eq_convergents'` shows that the convergents
computations for `GeneralizedContinuedFraction.of` are equivalent.
- `GeneralizedContinuedFraction.of_convergence` shows that
`(GeneralizedContinuedFraction.of v).convergents` converges to `v`.
## Tags
convergence, fractions
-/
variable {K : Type*} (v : K) [LinearOrderedField K] [FloorRing K]
open GeneralizedContinuedFraction (of)
open GeneralizedContinuedFraction
open scoped Topology
theorem GeneralizedContinuedFraction.of_isSimpleContinuedFraction :
(of v).IsSimpleContinuedFraction := fun _ _ nth_part_num_eq =>
of_part_num_eq_one nth_part_num_eq
#align generalized_continued_fraction.of_is_simple_continued_fraction GeneralizedContinuedFraction.of_isSimpleContinuedFraction
/-- Creates the simple continued fraction of a value. -/
nonrec def SimpleContinuedFraction.of : SimpleContinuedFraction K :=
⟨of v, GeneralizedContinuedFraction.of_isSimpleContinuedFraction v⟩
#align simple_continued_fraction.of SimpleContinuedFraction.of
theorem SimpleContinuedFraction.of_isContinuedFraction :
(SimpleContinuedFraction.of v).IsContinuedFraction := fun _ _ nth_part_denom_eq =>
lt_of_lt_of_le zero_lt_one (of_one_le_get?_part_denom nth_part_denom_eq)
#align simple_continued_fraction.of_is_continued_fraction SimpleContinuedFraction.of_isContinuedFraction
/-- Creates the continued fraction of a value. -/
def ContinuedFraction.of : ContinuedFraction K :=
⟨SimpleContinuedFraction.of v, SimpleContinuedFraction.of_isContinuedFraction v⟩
#align continued_fraction.of ContinuedFraction.of
namespace GeneralizedContinuedFraction
theorem of_convergents_eq_convergents' : (of v).convergents = (of v).convergents' :=
@ContinuedFraction.convergents_eq_convergents' _ _ (ContinuedFraction.of v)
#align generalized_continued_fraction.of_convergents_eq_convergents' GeneralizedContinuedFraction.of_convergents_eq_convergents'
/-- The recurrence relation for the `convergents` of the continued fraction expansion
of an element `v` of `K` in terms of the convergents of the inverse of its fractional part.
-/
| Mathlib/Algebra/ContinuedFractions/Computation/ApproximationCorollaries.lean | 80 | 82 | theorem convergents_succ (n : ℕ) :
(of v).convergents (n + 1) = ⌊v⌋ + 1 / (of (Int.fract v)⁻¹).convergents n := by |
rw [of_convergents_eq_convergents', convergents'_succ, of_convergents_eq_convergents']
|
/-
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.RingTheory.Ideal.QuotientOperations
import Mathlib.RingTheory.Localization.Basic
#align_import ring_theory.localization.ideal from "leanprover-community/mathlib"@"e7f0ddbf65bd7181a85edb74b64bdc35ba4bdc74"
/-!
# Ideals in localizations of commutative rings
## Implementation notes
See `Mathlib/RingTheory/Localization/Basic.lean` for a design overview.
## Tags
localization, ring localization, commutative ring localization, characteristic predicate,
commutative ring, field of fractions
-/
namespace IsLocalization
section CommSemiring
variable {R : Type*} [CommSemiring R] (M : Submonoid R) (S : Type*) [CommSemiring S]
variable [Algebra R S] [IsLocalization M S]
/-- Explicit characterization of the ideal given by `Ideal.map (algebraMap R S) I`.
In practice, this ideal differs only in that the carrier set is defined explicitly.
This definition is only meant to be used in proving `mem_map_algebraMap_iff`,
and any proof that needs to refer to the explicit carrier set should use that theorem. -/
private def map_ideal (I : Ideal R) : Ideal S where
carrier := { z : S | ∃ x : I × M, z * algebraMap R S x.2 = algebraMap R S x.1 }
zero_mem' := ⟨⟨0, 1⟩, by simp⟩
add_mem' := by
rintro a b ⟨a', ha⟩ ⟨b', hb⟩
let Z : { x // x ∈ I } := ⟨(a'.2 : R) * (b'.1 : R) + (b'.2 : R) * (a'.1 : R),
I.add_mem (I.mul_mem_left _ b'.1.2) (I.mul_mem_left _ a'.1.2)⟩
use ⟨Z, a'.2 * b'.2⟩
simp only [RingHom.map_add, Submodule.coe_mk, Submonoid.coe_mul, RingHom.map_mul]
rw [add_mul, ← mul_assoc a, ha, mul_comm (algebraMap R S a'.2) (algebraMap R S b'.2), ←
mul_assoc b, hb]
ring
smul_mem' := by
rintro c x ⟨x', hx⟩
obtain ⟨c', hc⟩ := IsLocalization.surj M c
let Z : { x // x ∈ I } := ⟨c'.1 * x'.1, I.mul_mem_left c'.1 x'.1.2⟩
use ⟨Z, c'.2 * x'.2⟩
simp only [← hx, ← hc, smul_eq_mul, Submodule.coe_mk, Submonoid.coe_mul, RingHom.map_mul]
ring
-- Porting note: removed #align declaration since it is a private def
theorem mem_map_algebraMap_iff {I : Ideal R} {z} : z ∈ Ideal.map (algebraMap R S) I ↔
∃ x : I × M, z * algebraMap R S x.2 = algebraMap R S x.1 := by
constructor
· change _ → z ∈ map_ideal M S I
refine fun h => Ideal.mem_sInf.1 h fun z hz => ?_
obtain ⟨y, hy⟩ := hz
let Z : { x // x ∈ I } := ⟨y, hy.left⟩
use ⟨Z, 1⟩
simp [hy.right]
· rintro ⟨⟨a, s⟩, h⟩
rw [← Ideal.unit_mul_mem_iff_mem _ (map_units S s), mul_comm]
exact h.symm ▸ Ideal.mem_map_of_mem _ a.2
#align is_localization.mem_map_algebra_map_iff IsLocalization.mem_map_algebraMap_iff
theorem map_comap (J : Ideal S) : Ideal.map (algebraMap R S) (Ideal.comap (algebraMap R S) J) = J :=
le_antisymm (Ideal.map_le_iff_le_comap.2 le_rfl) fun x hJ => by
obtain ⟨r, s, hx⟩ := mk'_surjective M x
rw [← hx] at hJ ⊢
exact
Ideal.mul_mem_right _ _
(Ideal.mem_map_of_mem _
(show (algebraMap R S) r ∈ J from
mk'_spec S r s ▸ J.mul_mem_right ((algebraMap R S) s) hJ))
#align is_localization.map_comap IsLocalization.map_comap
theorem comap_map_of_isPrime_disjoint (I : Ideal R) (hI : I.IsPrime) (hM : Disjoint (M : Set R) I) :
Ideal.comap (algebraMap R S) (Ideal.map (algebraMap R S) I) = I := by
refine le_antisymm ?_ Ideal.le_comap_map
refine (fun a ha => ?_)
obtain ⟨⟨b, s⟩, h⟩ := (mem_map_algebraMap_iff M S).1 (Ideal.mem_comap.1 ha)
replace h : algebraMap R S (s * a) = algebraMap R S b := by
simpa only [← map_mul, mul_comm] using h
obtain ⟨c, hc⟩ := (eq_iff_exists M S).1 h
have : ↑c * ↑s * a ∈ I := by
rw [mul_assoc, hc]
exact I.mul_mem_left c b.2
exact (hI.mem_or_mem this).resolve_left fun hsc => hM.le_bot ⟨(c * s).2, hsc⟩
#align is_localization.comap_map_of_is_prime_disjoint IsLocalization.comap_map_of_isPrime_disjoint
/-- If `S` is the localization of `R` at a submonoid, the ordering of ideals of `S` is
embedded in the ordering of ideals of `R`. -/
def orderEmbedding : Ideal S ↪o Ideal R where
toFun J := Ideal.comap (algebraMap R S) J
inj' := Function.LeftInverse.injective (map_comap M S)
map_rel_iff' := by
rintro J₁ J₂
constructor
· exact fun hJ => (map_comap M S) J₁ ▸ (map_comap M S) J₂ ▸ Ideal.map_mono hJ
· exact fun hJ => Ideal.comap_mono hJ
#align is_localization.order_embedding IsLocalization.orderEmbedding
/-- If `R` is a ring, then prime ideals in the localization at `M`
correspond to prime ideals in the original ring `R` that are disjoint from `M`.
This lemma gives the particular case for an ideal and its comap,
see `le_rel_iso_of_prime` for the more general relation isomorphism -/
theorem isPrime_iff_isPrime_disjoint (J : Ideal S) :
J.IsPrime ↔
(Ideal.comap (algebraMap R S) J).IsPrime ∧
Disjoint (M : Set R) ↑(Ideal.comap (algebraMap R S) J) := by
constructor
· refine fun h =>
⟨⟨?_, ?_⟩,
Set.disjoint_left.mpr fun m hm1 hm2 =>
h.ne_top (Ideal.eq_top_of_isUnit_mem _ hm2 (map_units S ⟨m, hm1⟩))⟩
· refine fun hJ => h.ne_top ?_
rw [eq_top_iff, ← (orderEmbedding M S).le_iff_le]
exact le_of_eq hJ.symm
· intro x y hxy
rw [Ideal.mem_comap, RingHom.map_mul] at hxy
exact h.mem_or_mem hxy
· refine fun h => ⟨fun hJ => h.left.ne_top (eq_top_iff.2 ?_), ?_⟩
· rwa [eq_top_iff, ← (orderEmbedding M S).le_iff_le] at hJ
· intro x y hxy
obtain ⟨a, s, ha⟩ := mk'_surjective M x
obtain ⟨b, t, hb⟩ := mk'_surjective M y
have : mk' S (a * b) (s * t) ∈ J := by rwa [mk'_mul, ha, hb]
rw [mk'_mem_iff, ← Ideal.mem_comap] at this
have this₂ := (h.1).mul_mem_iff_mem_or_mem.1 this
rw [Ideal.mem_comap, Ideal.mem_comap] at this₂
rwa [← ha, ← hb, mk'_mem_iff, mk'_mem_iff]
#align is_localization.is_prime_iff_is_prime_disjoint IsLocalization.isPrime_iff_isPrime_disjoint
/-- If `R` is a ring, then prime ideals in the localization at `M`
correspond to prime ideals in the original ring `R` that are disjoint from `M`.
This lemma gives the particular case for an ideal and its map,
see `le_rel_iso_of_prime` for the more general relation isomorphism, and the reverse implication -/
| Mathlib/RingTheory/Localization/Ideal.lean | 139 | 142 | theorem isPrime_of_isPrime_disjoint (I : Ideal R) (hp : I.IsPrime) (hd : Disjoint (M : Set R) ↑I) :
(Ideal.map (algebraMap R S) I).IsPrime := by |
rw [isPrime_iff_isPrime_disjoint M S, comap_map_of_isPrime_disjoint M S I hp hd]
exact ⟨hp, hd⟩
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Set.Lattice
import Mathlib.Logic.Small.Basic
import Mathlib.Logic.Function.OfArity
import Mathlib.Order.WellFounded
#align_import set_theory.zfc.basic from "leanprover-community/mathlib"@"f0b3759a8ef0bd8239ecdaa5e1089add5feebe1a"
/-!
# A model of ZFC
In this file, we model Zermelo-Fraenkel set theory (+ Choice) using Lean's underlying type theory.
We do this in four main steps:
* Define pre-sets inductively.
* Define extensional equivalence on pre-sets and give it a `setoid` instance.
* Define ZFC sets by quotienting pre-sets by extensional equivalence.
* Define classes as sets of ZFC sets.
Then the rest is usual set theory.
## The model
* `PSet`: Pre-set. A pre-set is inductively defined by its indexing type and its members, which are
themselves pre-sets.
* `ZFSet`: ZFC set. Defined as `PSet` quotiented by `PSet.Equiv`, the extensional equivalence.
* `Class`: Class. Defined as `Set ZFSet`.
* `ZFSet.choice`: Axiom of choice. Proved from Lean's axiom of choice.
## Other definitions
* `PSet.Type`: Underlying type of a pre-set.
* `PSet.Func`: Underlying family of pre-sets of a pre-set.
* `PSet.Equiv`: Extensional equivalence of pre-sets. Defined inductively.
* `PSet.omega`, `ZFSet.omega`: The von Neumann ordinal `ω` as a `PSet`, as a `Set`.
* `PSet.Arity.Equiv`: Extensional equivalence of `n`-ary `PSet`-valued functions. Extension of
`PSet.Equiv`.
* `PSet.Resp`: Collection of `n`-ary `PSet`-valued functions that respect extensional equivalence.
* `PSet.eval`: Turns a `PSet`-valued function that respect extensional equivalence into a
`ZFSet`-valued function.
* `Classical.allDefinable`: All functions are classically definable.
* `ZFSet.IsFunc` : Predicate that a ZFC set is a subset of `x × y` that can be considered as a ZFC
function `x → y`. That is, each member of `x` is related by the ZFC set to exactly one member of
`y`.
* `ZFSet.funs`: ZFC set of ZFC functions `x → y`.
* `ZFSet.Hereditarily p x`: Predicate that every set in the transitive closure of `x` has property
`p`.
* `Class.iota`: Definite description operator.
## Notes
To avoid confusion between the Lean `Set` and the ZFC `Set`, docstrings in this file refer to them
respectively as "`Set`" and "ZFC set".
## TODO
Prove `ZFSet.mapDefinableAux` computably.
-/
-- Porting note: Lean 3 uses `Set` for `ZFSet`.
set_option linter.uppercaseLean3 false
universe u v
open Function (OfArity)
/-- The type of pre-sets in universe `u`. A pre-set
is a family of pre-sets indexed by a type in `Type u`.
The ZFC universe is defined as a quotient of this
to ensure extensionality. -/
inductive PSet : Type (u + 1)
| mk (α : Type u) (A : α → PSet) : PSet
#align pSet PSet
namespace PSet
/-- The underlying type of a pre-set -/
def «Type» : PSet → Type u
| ⟨α, _⟩ => α
#align pSet.type PSet.Type
/-- The underlying pre-set family of a pre-set -/
def Func : ∀ x : PSet, x.Type → PSet
| ⟨_, A⟩ => A
#align pSet.func PSet.Func
@[simp]
theorem mk_type (α A) : «Type» ⟨α, A⟩ = α :=
rfl
#align pSet.mk_type PSet.mk_type
@[simp]
theorem mk_func (α A) : Func ⟨α, A⟩ = A :=
rfl
#align pSet.mk_func PSet.mk_func
@[simp]
theorem eta : ∀ x : PSet, mk x.Type x.Func = x
| ⟨_, _⟩ => rfl
#align pSet.eta PSet.eta
/-- Two pre-sets are extensionally equivalent if every element of the first family is extensionally
equivalent to some element of the second family and vice-versa. -/
def Equiv : PSet → PSet → Prop
| ⟨_, A⟩, ⟨_, B⟩ => (∀ a, ∃ b, Equiv (A a) (B b)) ∧ (∀ b, ∃ a, Equiv (A a) (B b))
#align pSet.equiv PSet.Equiv
theorem equiv_iff :
∀ {x y : PSet},
Equiv x y ↔ (∀ i, ∃ j, Equiv (x.Func i) (y.Func j)) ∧ ∀ j, ∃ i, Equiv (x.Func i) (y.Func j)
| ⟨_, _⟩, ⟨_, _⟩ => Iff.rfl
#align pSet.equiv_iff PSet.equiv_iff
theorem Equiv.exists_left {x y : PSet} (h : Equiv x y) : ∀ i, ∃ j, Equiv (x.Func i) (y.Func j) :=
(equiv_iff.1 h).1
#align pSet.equiv.exists_left PSet.Equiv.exists_left
theorem Equiv.exists_right {x y : PSet} (h : Equiv x y) : ∀ j, ∃ i, Equiv (x.Func i) (y.Func j) :=
(equiv_iff.1 h).2
#align pSet.equiv.exists_right PSet.Equiv.exists_right
@[refl]
protected theorem Equiv.refl : ∀ x, Equiv x x
| ⟨_, _⟩ => ⟨fun a => ⟨a, Equiv.refl _⟩, fun a => ⟨a, Equiv.refl _⟩⟩
#align pSet.equiv.refl PSet.Equiv.refl
protected theorem Equiv.rfl {x} : Equiv x x :=
Equiv.refl x
#align pSet.equiv.rfl PSet.Equiv.rfl
protected theorem Equiv.euc : ∀ {x y z}, Equiv x y → Equiv z y → Equiv x z
| ⟨_, _⟩, ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩, ⟨γβ, βγ⟩ =>
⟨ fun a =>
let ⟨b, ab⟩ := αβ a
let ⟨c, bc⟩ := βγ b
⟨c, Equiv.euc ab bc⟩,
fun c =>
let ⟨b, cb⟩ := γβ c
let ⟨a, ba⟩ := βα b
⟨a, Equiv.euc ba cb⟩ ⟩
#align pSet.equiv.euc PSet.Equiv.euc
@[symm]
protected theorem Equiv.symm {x y} : Equiv x y → Equiv y x :=
(Equiv.refl y).euc
#align pSet.equiv.symm PSet.Equiv.symm
protected theorem Equiv.comm {x y} : Equiv x y ↔ Equiv y x :=
⟨Equiv.symm, Equiv.symm⟩
#align pSet.equiv.comm PSet.Equiv.comm
@[trans]
protected theorem Equiv.trans {x y z} (h1 : Equiv x y) (h2 : Equiv y z) : Equiv x z :=
h1.euc h2.symm
#align pSet.equiv.trans PSet.Equiv.trans
protected theorem equiv_of_isEmpty (x y : PSet) [IsEmpty x.Type] [IsEmpty y.Type] : Equiv x y :=
equiv_iff.2 <| by simp
#align pSet.equiv_of_is_empty PSet.equiv_of_isEmpty
instance setoid : Setoid PSet :=
⟨PSet.Equiv, Equiv.refl, Equiv.symm, Equiv.trans⟩
#align pSet.setoid PSet.setoid
/-- A pre-set is a subset of another pre-set if every element of the first family is extensionally
equivalent to some element of the second family. -/
protected def Subset (x y : PSet) : Prop :=
∀ a, ∃ b, Equiv (x.Func a) (y.Func b)
#align pSet.subset PSet.Subset
instance : HasSubset PSet :=
⟨PSet.Subset⟩
instance : IsRefl PSet (· ⊆ ·) :=
⟨fun _ a => ⟨a, Equiv.refl _⟩⟩
instance : IsTrans PSet (· ⊆ ·) :=
⟨fun x y z hxy hyz a => by
cases' hxy a with b hb
cases' hyz b with c hc
exact ⟨c, hb.trans hc⟩⟩
theorem Equiv.ext : ∀ x y : PSet, Equiv x y ↔ x ⊆ y ∧ y ⊆ x
| ⟨_, _⟩, ⟨_, _⟩ =>
⟨fun ⟨αβ, βα⟩ =>
⟨αβ, fun b =>
let ⟨a, h⟩ := βα b
⟨a, Equiv.symm h⟩⟩,
fun ⟨αβ, βα⟩ =>
⟨αβ, fun b =>
let ⟨a, h⟩ := βα b
⟨a, Equiv.symm h⟩⟩⟩
#align pSet.equiv.ext PSet.Equiv.ext
theorem Subset.congr_left : ∀ {x y z : PSet}, Equiv x y → (x ⊆ z ↔ y ⊆ z)
| ⟨_, _⟩, ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩ =>
⟨fun αγ b =>
let ⟨a, ba⟩ := βα b
let ⟨c, ac⟩ := αγ a
⟨c, (Equiv.symm ba).trans ac⟩,
fun βγ a =>
let ⟨b, ab⟩ := αβ a
let ⟨c, bc⟩ := βγ b
⟨c, Equiv.trans ab bc⟩⟩
#align pSet.subset.congr_left PSet.Subset.congr_left
theorem Subset.congr_right : ∀ {x y z : PSet}, Equiv x y → (z ⊆ x ↔ z ⊆ y)
| ⟨_, _⟩, ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩ =>
⟨fun γα c =>
let ⟨a, ca⟩ := γα c
let ⟨b, ab⟩ := αβ a
⟨b, ca.trans ab⟩,
fun γβ c =>
let ⟨b, cb⟩ := γβ c
let ⟨a, ab⟩ := βα b
⟨a, cb.trans (Equiv.symm ab)⟩⟩
#align pSet.subset.congr_right PSet.Subset.congr_right
/-- `x ∈ y` as pre-sets if `x` is extensionally equivalent to a member of the family `y`. -/
protected def Mem (x y : PSet.{u}) : Prop :=
∃ b, Equiv x (y.Func b)
#align pSet.mem PSet.Mem
instance : Membership PSet PSet :=
⟨PSet.Mem⟩
theorem Mem.mk {α : Type u} (A : α → PSet) (a : α) : A a ∈ mk α A :=
⟨a, Equiv.refl (A a)⟩
#align pSet.mem.mk PSet.Mem.mk
| Mathlib/SetTheory/ZFC/Basic.lean | 233 | 235 | theorem func_mem (x : PSet) (i : x.Type) : x.Func i ∈ x := by |
cases x
apply Mem.mk
|
/-
Copyright (c) 2020 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jalex Stark, Kyle Miller, Lu-Ming Zhang
-/
import Mathlib.Combinatorics.SimpleGraph.Basic
import Mathlib.Combinatorics.SimpleGraph.Connectivity
import Mathlib.LinearAlgebra.Matrix.Trace
import Mathlib.LinearAlgebra.Matrix.Symmetric
#align_import combinatorics.simple_graph.adj_matrix from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1"
/-!
# Adjacency Matrices
This module defines the adjacency matrix of a graph, and provides theorems connecting graph
properties to computational properties of the matrix.
## Main definitions
* `Matrix.IsAdjMatrix`: `A : Matrix V V α` is qualified as an "adjacency matrix" if
(1) every entry of `A` is `0` or `1`,
(2) `A` is symmetric,
(3) every diagonal entry of `A` is `0`.
* `Matrix.IsAdjMatrix.to_graph`: for `A : Matrix V V α` and `h : A.IsAdjMatrix`,
`h.to_graph` is the simple graph induced by `A`.
* `Matrix.compl`: for `A : Matrix V V α`, `A.compl` is supposed to be
the adjacency matrix of the complement graph of the graph induced by `A`.
* `SimpleGraph.adjMatrix`: the adjacency matrix of a `SimpleGraph`.
* `SimpleGraph.adjMatrix_pow_apply_eq_card_walk`: each entry of the `n`th power of
a graph's adjacency matrix counts the number of length-`n` walks between the corresponding
pair of vertices.
-/
open Matrix
open Finset Matrix SimpleGraph
variable {V α β : Type*}
namespace Matrix
/-- `A : Matrix V V α` is qualified as an "adjacency matrix" if
(1) every entry of `A` is `0` or `1`,
(2) `A` is symmetric,
(3) every diagonal entry of `A` is `0`. -/
structure IsAdjMatrix [Zero α] [One α] (A : Matrix V V α) : Prop where
zero_or_one : ∀ i j, A i j = 0 ∨ A i j = 1 := by aesop
symm : A.IsSymm := by aesop
apply_diag : ∀ i, A i i = 0 := by aesop
#align matrix.is_adj_matrix Matrix.IsAdjMatrix
namespace IsAdjMatrix
variable {A : Matrix V V α}
@[simp]
theorem apply_diag_ne [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) (i : V) :
¬A i i = 1 := by simp [h.apply_diag i]
#align matrix.is_adj_matrix.apply_diag_ne Matrix.IsAdjMatrix.apply_diag_ne
@[simp]
theorem apply_ne_one_iff [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) (i j : V) :
¬A i j = 1 ↔ A i j = 0 := by obtain h | h := h.zero_or_one i j <;> simp [h]
#align matrix.is_adj_matrix.apply_ne_one_iff Matrix.IsAdjMatrix.apply_ne_one_iff
@[simp]
theorem apply_ne_zero_iff [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) (i j : V) :
¬A i j = 0 ↔ A i j = 1 := by rw [← apply_ne_one_iff h, Classical.not_not]
#align matrix.is_adj_matrix.apply_ne_zero_iff Matrix.IsAdjMatrix.apply_ne_zero_iff
/-- For `A : Matrix V V α` and `h : IsAdjMatrix A`,
`h.toGraph` is the simple graph whose adjacency matrix is `A`. -/
@[simps]
def toGraph [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) : SimpleGraph V where
Adj i j := A i j = 1
symm i j hij := by simp only; rwa [h.symm.apply i j]
loopless i := by simp [h]
#align matrix.is_adj_matrix.to_graph Matrix.IsAdjMatrix.toGraph
instance [MulZeroOneClass α] [Nontrivial α] [DecidableEq α] (h : IsAdjMatrix A) :
DecidableRel h.toGraph.Adj := by
simp only [toGraph]
infer_instance
end IsAdjMatrix
/-- For `A : Matrix V V α`, `A.compl` is supposed to be the adjacency matrix of
the complement graph of the graph induced by `A.adjMatrix`. -/
def compl [Zero α] [One α] [DecidableEq α] [DecidableEq V] (A : Matrix V V α) : Matrix V V α :=
fun i j => ite (i = j) 0 (ite (A i j = 0) 1 0)
#align matrix.compl Matrix.compl
section Compl
variable [DecidableEq α] [DecidableEq V] (A : Matrix V V α)
@[simp]
theorem compl_apply_diag [Zero α] [One α] (i : V) : A.compl i i = 0 := by simp [compl]
#align matrix.compl_apply_diag Matrix.compl_apply_diag
@[simp]
theorem compl_apply [Zero α] [One α] (i j : V) : A.compl i j = 0 ∨ A.compl i j = 1 := by
unfold compl
split_ifs <;> simp
#align matrix.compl_apply Matrix.compl_apply
@[simp]
theorem isSymm_compl [Zero α] [One α] (h : A.IsSymm) : A.compl.IsSymm := by
ext
simp [compl, h.apply, eq_comm]
#align matrix.is_symm_compl Matrix.isSymm_compl
@[simp]
theorem isAdjMatrix_compl [Zero α] [One α] (h : A.IsSymm) : IsAdjMatrix A.compl :=
{ symm := by simp [h] }
#align matrix.is_adj_matrix_compl Matrix.isAdjMatrix_compl
namespace IsAdjMatrix
variable {A}
@[simp]
theorem compl [Zero α] [One α] (h : IsAdjMatrix A) : IsAdjMatrix A.compl :=
isAdjMatrix_compl A h.symm
#align matrix.is_adj_matrix.compl Matrix.IsAdjMatrix.compl
theorem toGraph_compl_eq [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) :
h.compl.toGraph = h.toGraphᶜ := by
ext v w
cases' h.zero_or_one v w with h h <;> by_cases hvw : v = w <;> simp [Matrix.compl, h, hvw]
#align matrix.is_adj_matrix.to_graph_compl_eq Matrix.IsAdjMatrix.toGraph_compl_eq
end IsAdjMatrix
end Compl
end Matrix
open Matrix
namespace SimpleGraph
variable (G : SimpleGraph V) [DecidableRel G.Adj]
variable (α)
/-- `adjMatrix G α` is the matrix `A` such that `A i j = (1 : α)` if `i` and `j` are
adjacent in the simple graph `G`, and otherwise `A i j = 0`. -/
def adjMatrix [Zero α] [One α] : Matrix V V α :=
of fun i j => if G.Adj i j then (1 : α) else 0
#align simple_graph.adj_matrix SimpleGraph.adjMatrix
variable {α}
-- TODO: set as an equation lemma for `adjMatrix`, see mathlib4#3024
@[simp]
theorem adjMatrix_apply (v w : V) [Zero α] [One α] :
G.adjMatrix α v w = if G.Adj v w then 1 else 0 :=
rfl
#align simple_graph.adj_matrix_apply SimpleGraph.adjMatrix_apply
@[simp]
theorem transpose_adjMatrix [Zero α] [One α] : (G.adjMatrix α)ᵀ = G.adjMatrix α := by
ext
simp [adj_comm]
#align simple_graph.transpose_adj_matrix SimpleGraph.transpose_adjMatrix
@[simp]
theorem isSymm_adjMatrix [Zero α] [One α] : (G.adjMatrix α).IsSymm :=
transpose_adjMatrix G
#align simple_graph.is_symm_adj_matrix SimpleGraph.isSymm_adjMatrix
variable (α)
/-- The adjacency matrix of `G` is an adjacency matrix. -/
@[simp]
theorem isAdjMatrix_adjMatrix [Zero α] [One α] : (G.adjMatrix α).IsAdjMatrix :=
{ zero_or_one := fun i j => by by_cases h : G.Adj i j <;> simp [h] }
#align simple_graph.is_adj_matrix_adj_matrix SimpleGraph.isAdjMatrix_adjMatrix
/-- The graph induced by the adjacency matrix of `G` is `G` itself. -/
theorem toGraph_adjMatrix_eq [MulZeroOneClass α] [Nontrivial α] :
(G.isAdjMatrix_adjMatrix α).toGraph = G := by
ext
simp only [IsAdjMatrix.toGraph_adj, adjMatrix_apply, ite_eq_left_iff, zero_ne_one]
apply Classical.not_not
#align simple_graph.to_graph_adj_matrix_eq SimpleGraph.toGraph_adjMatrix_eq
variable {α} [Fintype V]
@[simp]
theorem adjMatrix_dotProduct [NonAssocSemiring α] (v : V) (vec : V → α) :
dotProduct (G.adjMatrix α v) vec = ∑ u ∈ G.neighborFinset v, vec u := by
simp [neighborFinset_eq_filter, dotProduct, sum_filter]
#align simple_graph.adj_matrix_dot_product SimpleGraph.adjMatrix_dotProduct
@[simp]
theorem dotProduct_adjMatrix [NonAssocSemiring α] (v : V) (vec : V → α) :
dotProduct vec (G.adjMatrix α v) = ∑ u ∈ G.neighborFinset v, vec u := by
simp [neighborFinset_eq_filter, dotProduct, sum_filter, Finset.sum_apply]
#align simple_graph.dot_product_adj_matrix SimpleGraph.dotProduct_adjMatrix
@[simp]
theorem adjMatrix_mulVec_apply [NonAssocSemiring α] (v : V) (vec : V → α) :
(G.adjMatrix α *ᵥ vec) v = ∑ u ∈ G.neighborFinset v, vec u := by
rw [mulVec, adjMatrix_dotProduct]
#align simple_graph.adj_matrix_mul_vec_apply SimpleGraph.adjMatrix_mulVec_apply
@[simp]
theorem adjMatrix_vecMul_apply [NonAssocSemiring α] (v : V) (vec : V → α) :
(vec ᵥ* G.adjMatrix α) v = ∑ u ∈ G.neighborFinset v, vec u := by
simp only [← dotProduct_adjMatrix, vecMul]
refine congr rfl ?_; ext x
rw [← transpose_apply (adjMatrix α G) x v, transpose_adjMatrix]
#align simple_graph.adj_matrix_vec_mul_apply SimpleGraph.adjMatrix_vecMul_apply
@[simp]
theorem adjMatrix_mul_apply [NonAssocSemiring α] (M : Matrix V V α) (v w : V) :
(G.adjMatrix α * M) v w = ∑ u ∈ G.neighborFinset v, M u w := by
simp [mul_apply, neighborFinset_eq_filter, sum_filter]
#align simple_graph.adj_matrix_mul_apply SimpleGraph.adjMatrix_mul_apply
@[simp]
| Mathlib/Combinatorics/SimpleGraph/AdjMatrix.lean | 230 | 232 | theorem mul_adjMatrix_apply [NonAssocSemiring α] (M : Matrix V V α) (v w : V) :
(M * G.adjMatrix α) v w = ∑ u ∈ G.neighborFinset w, M v u := by |
simp [mul_apply, neighborFinset_eq_filter, sum_filter, adj_comm]
|
/-
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.Algebra.Algebra.Operations
import Mathlib.Data.Fintype.Lattice
import Mathlib.RingTheory.Coprime.Lemmas
#align_import ring_theory.ideal.operations from "leanprover-community/mathlib"@"e7f0ddbf65bd7181a85edb74b64bdc35ba4bdc74"
/-!
# More operations on modules and ideals
-/
assert_not_exists Basis -- See `RingTheory.Ideal.Basis`
assert_not_exists Submodule.hasQuotient -- See `RingTheory.Ideal.QuotientOperations`
universe u v w x
open Pointwise
namespace Submodule
variable {R : Type u} {M : Type v} {M' F G : Type*}
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M'] [Module R M']
open Pointwise
instance hasSMul' : SMul (Ideal R) (Submodule R M) :=
⟨Submodule.map₂ (LinearMap.lsmul R M)⟩
#align submodule.has_smul' Submodule.hasSMul'
/-- This duplicates the global `smul_eq_mul`, but doesn't have to unfold anywhere near as much to
apply. -/
protected theorem _root_.Ideal.smul_eq_mul (I J : Ideal R) : I • J = I * J :=
rfl
#align ideal.smul_eq_mul Ideal.smul_eq_mul
variable (R M) in
/-- `Module.annihilator R M` is the ideal of all elements `r : R` such that `r • M = 0`. -/
def _root_.Module.annihilator : Ideal R := LinearMap.ker (LinearMap.lsmul R M)
theorem _root_.Module.mem_annihilator {r} : r ∈ Module.annihilator R M ↔ ∀ m : M, r • m = 0 :=
⟨fun h ↦ (congr($h ·)), (LinearMap.ext ·)⟩
theorem _root_.LinearMap.annihilator_le_of_injective (f : M →ₗ[R] M') (hf : Function.Injective f) :
Module.annihilator R M' ≤ Module.annihilator R M := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢; exact fun m ↦ hf (by rw [map_smul, h, f.map_zero])
theorem _root_.LinearMap.annihilator_le_of_surjective (f : M →ₗ[R] M')
(hf : Function.Surjective f) : Module.annihilator R M ≤ Module.annihilator R M' := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢
intro m; obtain ⟨m, rfl⟩ := hf m
rw [← map_smul, h, f.map_zero]
theorem _root_.LinearEquiv.annihilator_eq (e : M ≃ₗ[R] M') :
Module.annihilator R M = Module.annihilator R M' :=
(e.annihilator_le_of_surjective e.surjective).antisymm (e.annihilator_le_of_injective e.injective)
/-- `N.annihilator` is the ideal of all elements `r : R` such that `r • N = 0`. -/
abbrev annihilator (N : Submodule R M) : Ideal R :=
Module.annihilator R N
#align submodule.annihilator Submodule.annihilator
theorem annihilator_top : (⊤ : Submodule R M).annihilator = Module.annihilator R M :=
topEquiv.annihilator_eq
variable {I J : Ideal R} {N P : Submodule R M}
theorem mem_annihilator {r} : r ∈ N.annihilator ↔ ∀ n ∈ N, r • n = (0 : M) := by
simp_rw [annihilator, Module.mem_annihilator, Subtype.forall, Subtype.ext_iff]; rfl
#align submodule.mem_annihilator Submodule.mem_annihilator
theorem mem_annihilator' {r} : r ∈ N.annihilator ↔ N ≤ comap (r • (LinearMap.id : M →ₗ[R] M)) ⊥ :=
mem_annihilator.trans ⟨fun H n hn => (mem_bot R).2 <| H n hn, fun H _ hn => (mem_bot R).1 <| H hn⟩
#align submodule.mem_annihilator' Submodule.mem_annihilator'
theorem mem_annihilator_span (s : Set M) (r : R) :
r ∈ (Submodule.span R s).annihilator ↔ ∀ n : s, r • (n : M) = 0 := by
rw [Submodule.mem_annihilator]
constructor
· intro h n
exact h _ (Submodule.subset_span n.prop)
· intro h n hn
refine Submodule.span_induction hn ?_ ?_ ?_ ?_
· intro x hx
exact h ⟨x, hx⟩
· exact smul_zero _
· intro x y hx hy
rw [smul_add, hx, hy, zero_add]
· intro a x hx
rw [smul_comm, hx, smul_zero]
#align submodule.mem_annihilator_span Submodule.mem_annihilator_span
theorem mem_annihilator_span_singleton (g : M) (r : R) :
r ∈ (Submodule.span R ({g} : Set M)).annihilator ↔ r • g = 0 := by simp [mem_annihilator_span]
#align submodule.mem_annihilator_span_singleton Submodule.mem_annihilator_span_singleton
theorem annihilator_bot : (⊥ : Submodule R M).annihilator = ⊤ :=
(Ideal.eq_top_iff_one _).2 <| mem_annihilator'.2 bot_le
#align submodule.annihilator_bot Submodule.annihilator_bot
theorem annihilator_eq_top_iff : N.annihilator = ⊤ ↔ N = ⊥ :=
⟨fun H =>
eq_bot_iff.2 fun (n : M) hn =>
(mem_bot R).2 <| one_smul R n ▸ mem_annihilator.1 ((Ideal.eq_top_iff_one _).1 H) n hn,
fun H => H.symm ▸ annihilator_bot⟩
#align submodule.annihilator_eq_top_iff Submodule.annihilator_eq_top_iff
theorem annihilator_mono (h : N ≤ P) : P.annihilator ≤ N.annihilator := fun _ hrp =>
mem_annihilator.2 fun n hn => mem_annihilator.1 hrp n <| h hn
#align submodule.annihilator_mono Submodule.annihilator_mono
theorem annihilator_iSup (ι : Sort w) (f : ι → Submodule R M) :
annihilator (⨆ i, f i) = ⨅ i, annihilator (f i) :=
le_antisymm (le_iInf fun _ => annihilator_mono <| le_iSup _ _) fun _ H =>
mem_annihilator'.2 <|
iSup_le fun i =>
have := (mem_iInf _).1 H i
mem_annihilator'.1 this
#align submodule.annihilator_supr Submodule.annihilator_iSup
theorem smul_mem_smul {r} {n} (hr : r ∈ I) (hn : n ∈ N) : r • n ∈ I • N :=
apply_mem_map₂ _ hr hn
#align submodule.smul_mem_smul Submodule.smul_mem_smul
theorem smul_le {P : Submodule R M} : I • N ≤ P ↔ ∀ r ∈ I, ∀ n ∈ N, r • n ∈ P :=
map₂_le
#align submodule.smul_le Submodule.smul_le
@[simp, norm_cast]
lemma coe_set_smul : (I : Set R) • N = I • N :=
Submodule.set_smul_eq_of_le _ _ _
(fun _ _ hr hx => smul_mem_smul hr hx)
(smul_le.mpr fun _ hr _ hx => mem_set_smul_of_mem_mem hr hx)
@[elab_as_elim]
theorem smul_induction_on {p : M → Prop} {x} (H : x ∈ I • N) (smul : ∀ r ∈ I, ∀ n ∈ N, p (r • n))
(add : ∀ x y, p x → p y → p (x + y)) : p x := by
have H0 : p 0 := by simpa only [zero_smul] using smul 0 I.zero_mem 0 N.zero_mem
refine Submodule.iSup_induction (x := x) _ H ?_ H0 add
rintro ⟨i, hi⟩ m ⟨j, hj, hj'⟩
rw [← hj']
exact smul _ hi _ hj
#align submodule.smul_induction_on Submodule.smul_induction_on
/-- Dependent version of `Submodule.smul_induction_on`. -/
@[elab_as_elim]
theorem smul_induction_on' {x : M} (hx : x ∈ I • N) {p : ∀ x, x ∈ I • N → Prop}
(smul : ∀ (r : R) (hr : r ∈ I) (n : M) (hn : n ∈ N), p (r • n) (smul_mem_smul hr hn))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›)) : p x hx := by
refine Exists.elim ?_ fun (h : x ∈ I • N) (H : p x h) => H
exact
smul_induction_on hx (fun a ha x hx => ⟨_, smul _ ha _ hx⟩) fun x y ⟨_, hx⟩ ⟨_, hy⟩ =>
⟨_, add _ _ _ _ hx hy⟩
#align submodule.smul_induction_on' Submodule.smul_induction_on'
theorem mem_smul_span_singleton {I : Ideal R} {m : M} {x : M} :
x ∈ I • span R ({m} : Set M) ↔ ∃ y ∈ I, y • m = x :=
⟨fun hx =>
smul_induction_on hx
(fun r hri n hnm =>
let ⟨s, hs⟩ := mem_span_singleton.1 hnm
⟨r * s, I.mul_mem_right _ hri, hs ▸ mul_smul r s m⟩)
fun m1 m2 ⟨y1, hyi1, hy1⟩ ⟨y2, hyi2, hy2⟩ =>
⟨y1 + y2, I.add_mem hyi1 hyi2, by rw [add_smul, hy1, hy2]⟩,
fun ⟨y, hyi, hy⟩ => hy ▸ smul_mem_smul hyi (subset_span <| Set.mem_singleton m)⟩
#align submodule.mem_smul_span_singleton Submodule.mem_smul_span_singleton
theorem smul_le_right : I • N ≤ N :=
smul_le.2 fun r _ _ => N.smul_mem r
#align submodule.smul_le_right Submodule.smul_le_right
theorem smul_mono (hij : I ≤ J) (hnp : N ≤ P) : I • N ≤ J • P :=
map₂_le_map₂ hij hnp
#align submodule.smul_mono Submodule.smul_mono
theorem smul_mono_left (h : I ≤ J) : I • N ≤ J • N :=
map₂_le_map₂_left h
#align submodule.smul_mono_left Submodule.smul_mono_left
instance : CovariantClass (Ideal R) (Submodule R M) HSMul.hSMul LE.le :=
⟨fun _ _ => map₂_le_map₂_right⟩
@[deprecated smul_mono_right (since := "2024-03-31")]
protected theorem smul_mono_right (h : N ≤ P) : I • N ≤ I • P :=
_root_.smul_mono_right I h
#align submodule.smul_mono_right Submodule.smul_mono_right
theorem map_le_smul_top (I : Ideal R) (f : R →ₗ[R] M) :
Submodule.map f I ≤ I • (⊤ : Submodule R M) := by
rintro _ ⟨y, hy, rfl⟩
rw [← mul_one y, ← smul_eq_mul, f.map_smul]
exact smul_mem_smul hy mem_top
#align submodule.map_le_smul_top Submodule.map_le_smul_top
@[simp]
theorem annihilator_smul (N : Submodule R M) : annihilator N • N = ⊥ :=
eq_bot_iff.2 (smul_le.2 fun _ => mem_annihilator.1)
#align submodule.annihilator_smul Submodule.annihilator_smul
@[simp]
theorem annihilator_mul (I : Ideal R) : annihilator I * I = ⊥ :=
annihilator_smul I
#align submodule.annihilator_mul Submodule.annihilator_mul
@[simp]
theorem mul_annihilator (I : Ideal R) : I * annihilator I = ⊥ := by rw [mul_comm, annihilator_mul]
#align submodule.mul_annihilator Submodule.mul_annihilator
variable (I J N P)
@[simp]
theorem smul_bot : I • (⊥ : Submodule R M) = ⊥ :=
map₂_bot_right _ _
#align submodule.smul_bot Submodule.smul_bot
@[simp]
theorem bot_smul : (⊥ : Ideal R) • N = ⊥ :=
map₂_bot_left _ _
#align submodule.bot_smul Submodule.bot_smul
@[simp]
theorem top_smul : (⊤ : Ideal R) • N = N :=
le_antisymm smul_le_right fun r hri => one_smul R r ▸ smul_mem_smul mem_top hri
#align submodule.top_smul Submodule.top_smul
theorem smul_sup : I • (N ⊔ P) = I • N ⊔ I • P :=
map₂_sup_right _ _ _ _
#align submodule.smul_sup Submodule.smul_sup
theorem sup_smul : (I ⊔ J) • N = I • N ⊔ J • N :=
map₂_sup_left _ _ _ _
#align submodule.sup_smul Submodule.sup_smul
protected theorem smul_assoc : (I • J) • N = I • J • N :=
le_antisymm
(smul_le.2 fun _ hrsij t htn =>
smul_induction_on hrsij
(fun r hr s hs =>
(@smul_eq_mul R _ r s).symm ▸ smul_smul r s t ▸ smul_mem_smul hr (smul_mem_smul hs htn))
fun x y => (add_smul x y t).symm ▸ Submodule.add_mem _)
(smul_le.2 fun r hr _ hsn =>
suffices J • N ≤ Submodule.comap (r • (LinearMap.id : M →ₗ[R] M)) ((I • J) • N) from this hsn
smul_le.2 fun s hs n hn =>
show r • s • n ∈ (I • J) • N from mul_smul r s n ▸ smul_mem_smul (smul_mem_smul hr hs) hn)
#align submodule.smul_assoc Submodule.smul_assoc
@[deprecated smul_inf_le (since := "2024-03-31")]
protected theorem smul_inf_le (M₁ M₂ : Submodule R M) :
I • (M₁ ⊓ M₂) ≤ I • M₁ ⊓ I • M₂ := smul_inf_le _ _ _
#align submodule.smul_inf_le Submodule.smul_inf_le
theorem smul_iSup {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} : I • iSup t = ⨆ i, I • t i :=
map₂_iSup_right _ _ _
#align submodule.smul_supr Submodule.smul_iSup
@[deprecated smul_iInf_le (since := "2024-03-31")]
protected theorem smul_iInf_le {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} :
I • iInf t ≤ ⨅ i, I • t i :=
smul_iInf_le
#align submodule.smul_infi_le Submodule.smul_iInf_le
variable (S : Set R) (T : Set M)
theorem span_smul_span : Ideal.span S • span R T = span R (⋃ (s ∈ S) (t ∈ T), {s • t}) :=
(map₂_span_span _ _ _ _).trans <| congr_arg _ <| Set.image2_eq_iUnion _ _ _
#align submodule.span_smul_span Submodule.span_smul_span
theorem ideal_span_singleton_smul (r : R) (N : Submodule R M) :
(Ideal.span {r} : Ideal R) • N = r • N := by
have : span R (⋃ (t : M) (_ : t ∈ N), {r • t}) = r • N := by
convert span_eq (r • N)
exact (Set.image_eq_iUnion _ (N : Set M)).symm
conv_lhs => rw [← span_eq N, span_smul_span]
simpa
#align submodule.ideal_span_singleton_smul Submodule.ideal_span_singleton_smul
theorem mem_of_span_top_of_smul_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤) (x : M)
(H : ∀ r : s, (r : R) • x ∈ M') : x ∈ M' := by
suffices (⊤ : Ideal R) • span R ({x} : Set M) ≤ M' by
rw [top_smul] at this
exact this (subset_span (Set.mem_singleton x))
rw [← hs, span_smul_span, span_le]
simpa using H
#align submodule.mem_of_span_top_of_smul_mem Submodule.mem_of_span_top_of_smul_mem
/-- Given `s`, a generating set of `R`, to check that an `x : M` falls in a
submodule `M'` of `x`, we only need to show that `r ^ n • x ∈ M'` for some `n` for each `r : s`. -/
theorem mem_of_span_eq_top_of_smul_pow_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤)
(x : M) (H : ∀ r : s, ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M') : x ∈ M' := by
obtain ⟨s', hs₁, hs₂⟩ := (Ideal.span_eq_top_iff_finite _).mp hs
replace H : ∀ r : s', ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M' := fun r => H ⟨_, hs₁ r.2⟩
choose n₁ n₂ using H
let N := s'.attach.sup n₁
have hs' := Ideal.span_pow_eq_top (s' : Set R) hs₂ N
apply M'.mem_of_span_top_of_smul_mem _ hs'
rintro ⟨_, r, hr, rfl⟩
convert M'.smul_mem (r ^ (N - n₁ ⟨r, hr⟩)) (n₂ ⟨r, hr⟩) using 1
simp only [Subtype.coe_mk, smul_smul, ← pow_add]
rw [tsub_add_cancel_of_le (Finset.le_sup (s'.mem_attach _) : n₁ ⟨r, hr⟩ ≤ N)]
#align submodule.mem_of_span_eq_top_of_smul_pow_mem Submodule.mem_of_span_eq_top_of_smul_pow_mem
variable {M' : Type w} [AddCommMonoid M'] [Module R M']
@[simp]
theorem map_smul'' (f : M →ₗ[R] M') : (I • N).map f = I • N.map f :=
le_antisymm
(map_le_iff_le_comap.2 <|
smul_le.2 fun r hr n hn =>
show f (r • n) ∈ I • N.map f from
(f.map_smul r n).symm ▸ smul_mem_smul hr (mem_map_of_mem hn)) <|
smul_le.2 fun r hr _ hn =>
let ⟨p, hp, hfp⟩ := mem_map.1 hn
hfp ▸ f.map_smul r p ▸ mem_map_of_mem (smul_mem_smul hr hp)
#align submodule.map_smul'' Submodule.map_smul''
open Pointwise in
@[simp]
theorem map_pointwise_smul (r : R) (N : Submodule R M) (f : M →ₗ[R] M') :
(r • N).map f = r • N.map f := by
simp_rw [← ideal_span_singleton_smul, map_smul'']
variable {I}
theorem mem_smul_span {s : Set M} {x : M} :
x ∈ I • Submodule.span R s ↔ x ∈ Submodule.span R (⋃ (a ∈ I) (b ∈ s), ({a • b} : Set M)) := by
rw [← I.span_eq, Submodule.span_smul_span, I.span_eq]
rfl
#align submodule.mem_smul_span Submodule.mem_smul_span
variable (I)
/-- If `x` is an `I`-multiple of the submodule spanned by `f '' s`,
then we can write `x` as an `I`-linear combination of the elements of `f '' s`. -/
theorem mem_ideal_smul_span_iff_exists_sum {ι : Type*} (f : ι → M) (x : M) :
x ∈ I • span R (Set.range f) ↔
∃ (a : ι →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
constructor; swap
· rintro ⟨a, ha, rfl⟩
exact Submodule.sum_mem _ fun c _ => smul_mem_smul (ha c) <| subset_span <| Set.mem_range_self _
refine fun hx => span_induction (mem_smul_span.mp hx) ?_ ?_ ?_ ?_
· simp only [Set.mem_iUnion, Set.mem_range, Set.mem_singleton_iff]
rintro x ⟨y, hy, x, ⟨i, rfl⟩, rfl⟩
refine ⟨Finsupp.single i y, fun j => ?_, ?_⟩
· letI := Classical.decEq ι
rw [Finsupp.single_apply]
split_ifs
· assumption
· exact I.zero_mem
refine @Finsupp.sum_single_index ι R M _ _ i _ (fun i y => y • f i) ?_
simp
· exact ⟨0, fun _ => I.zero_mem, Finsupp.sum_zero_index⟩
· rintro x y ⟨ax, hax, rfl⟩ ⟨ay, hay, rfl⟩
refine ⟨ax + ay, fun i => I.add_mem (hax i) (hay i), Finsupp.sum_add_index' ?_ ?_⟩ <;>
intros <;> simp only [zero_smul, add_smul]
· rintro c x ⟨a, ha, rfl⟩
refine ⟨c • a, fun i => I.mul_mem_left c (ha i), ?_⟩
rw [Finsupp.sum_smul_index, Finsupp.smul_sum] <;> intros <;> simp only [zero_smul, mul_smul]
#align submodule.mem_ideal_smul_span_iff_exists_sum Submodule.mem_ideal_smul_span_iff_exists_sum
theorem mem_ideal_smul_span_iff_exists_sum' {ι : Type*} (s : Set ι) (f : ι → M) (x : M) :
x ∈ I • span R (f '' s) ↔
∃ (a : s →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
rw [← Submodule.mem_ideal_smul_span_iff_exists_sum, ← Set.image_eq_range]
#align submodule.mem_ideal_smul_span_iff_exists_sum' Submodule.mem_ideal_smul_span_iff_exists_sum'
theorem mem_smul_top_iff (N : Submodule R M) (x : N) :
x ∈ I • (⊤ : Submodule R N) ↔ (x : M) ∈ I • N := by
change _ ↔ N.subtype x ∈ I • N
have : Submodule.map N.subtype (I • ⊤) = I • N := by
rw [Submodule.map_smul'', Submodule.map_top, Submodule.range_subtype]
rw [← this]
exact (Function.Injective.mem_set_image N.injective_subtype).symm
#align submodule.mem_smul_top_iff Submodule.mem_smul_top_iff
@[simp]
theorem smul_comap_le_comap_smul (f : M →ₗ[R] M') (S : Submodule R M') (I : Ideal R) :
I • S.comap f ≤ (I • S).comap f := by
refine Submodule.smul_le.mpr fun r hr x hx => ?_
rw [Submodule.mem_comap] at hx ⊢
rw [f.map_smul]
exact Submodule.smul_mem_smul hr hx
#align submodule.smul_comap_le_comap_smul Submodule.smul_comap_le_comap_smul
end CommSemiring
end Submodule
namespace Ideal
section Add
variable {R : Type u} [Semiring R]
@[simp]
theorem add_eq_sup {I J : Ideal R} : I + J = I ⊔ J :=
rfl
#align ideal.add_eq_sup Ideal.add_eq_sup
@[simp]
theorem zero_eq_bot : (0 : Ideal R) = ⊥ :=
rfl
#align ideal.zero_eq_bot Ideal.zero_eq_bot
@[simp]
theorem sum_eq_sup {ι : Type*} (s : Finset ι) (f : ι → Ideal R) : s.sum f = s.sup f :=
rfl
#align ideal.sum_eq_sup Ideal.sum_eq_sup
end Add
section MulAndRadical
variable {R : Type u} {ι : Type*} [CommSemiring R]
variable {I J K L : Ideal R}
instance : Mul (Ideal R) :=
⟨(· • ·)⟩
@[simp]
theorem one_eq_top : (1 : Ideal R) = ⊤ := by erw [Submodule.one_eq_range, LinearMap.range_id]
#align ideal.one_eq_top Ideal.one_eq_top
theorem add_eq_one_iff : I + J = 1 ↔ ∃ i ∈ I, ∃ j ∈ J, i + j = 1 := by
rw [one_eq_top, eq_top_iff_one, add_eq_sup, Submodule.mem_sup]
theorem mul_mem_mul {r s} (hr : r ∈ I) (hs : s ∈ J) : r * s ∈ I * J :=
Submodule.smul_mem_smul hr hs
#align ideal.mul_mem_mul Ideal.mul_mem_mul
theorem mul_mem_mul_rev {r s} (hr : r ∈ I) (hs : s ∈ J) : s * r ∈ I * J :=
mul_comm r s ▸ mul_mem_mul hr hs
#align ideal.mul_mem_mul_rev Ideal.mul_mem_mul_rev
theorem pow_mem_pow {x : R} (hx : x ∈ I) (n : ℕ) : x ^ n ∈ I ^ n :=
Submodule.pow_mem_pow _ hx _
#align ideal.pow_mem_pow Ideal.pow_mem_pow
theorem prod_mem_prod {ι : Type*} {s : Finset ι} {I : ι → Ideal R} {x : ι → R} :
(∀ i ∈ s, x i ∈ I i) → (∏ i ∈ s, x i) ∈ ∏ i ∈ s, I i := by
classical
refine Finset.induction_on s ?_ ?_
· intro
rw [Finset.prod_empty, Finset.prod_empty, one_eq_top]
exact Submodule.mem_top
· intro a s ha IH h
rw [Finset.prod_insert ha, Finset.prod_insert ha]
exact
mul_mem_mul (h a <| Finset.mem_insert_self a s)
(IH fun i hi => h i <| Finset.mem_insert_of_mem hi)
#align ideal.prod_mem_prod Ideal.prod_mem_prod
theorem mul_le : I * J ≤ K ↔ ∀ r ∈ I, ∀ s ∈ J, r * s ∈ K :=
Submodule.smul_le
#align ideal.mul_le Ideal.mul_le
theorem mul_le_left : I * J ≤ J :=
Ideal.mul_le.2 fun _ _ _ => J.mul_mem_left _
#align ideal.mul_le_left Ideal.mul_le_left
theorem mul_le_right : I * J ≤ I :=
Ideal.mul_le.2 fun _ hr _ _ => I.mul_mem_right _ hr
#align ideal.mul_le_right Ideal.mul_le_right
@[simp]
theorem sup_mul_right_self : I ⊔ I * J = I :=
sup_eq_left.2 Ideal.mul_le_right
#align ideal.sup_mul_right_self Ideal.sup_mul_right_self
@[simp]
theorem sup_mul_left_self : I ⊔ J * I = I :=
sup_eq_left.2 Ideal.mul_le_left
#align ideal.sup_mul_left_self Ideal.sup_mul_left_self
@[simp]
theorem mul_right_self_sup : I * J ⊔ I = I :=
sup_eq_right.2 Ideal.mul_le_right
#align ideal.mul_right_self_sup Ideal.mul_right_self_sup
@[simp]
theorem mul_left_self_sup : J * I ⊔ I = I :=
sup_eq_right.2 Ideal.mul_le_left
#align ideal.mul_left_self_sup Ideal.mul_left_self_sup
variable (I J K)
protected theorem mul_comm : I * J = J * I :=
le_antisymm (mul_le.2 fun _ hrI _ hsJ => mul_mem_mul_rev hsJ hrI)
(mul_le.2 fun _ hrJ _ hsI => mul_mem_mul_rev hsI hrJ)
#align ideal.mul_comm Ideal.mul_comm
protected theorem mul_assoc : I * J * K = I * (J * K) :=
Submodule.smul_assoc I J K
#align ideal.mul_assoc Ideal.mul_assoc
theorem span_mul_span (S T : Set R) : span S * span T = span (⋃ (s ∈ S) (t ∈ T), {s * t}) :=
Submodule.span_smul_span S T
#align ideal.span_mul_span Ideal.span_mul_span
variable {I J K}
theorem span_mul_span' (S T : Set R) : span S * span T = span (S * T) := by
unfold span
rw [Submodule.span_mul_span]
#align ideal.span_mul_span' Ideal.span_mul_span'
theorem span_singleton_mul_span_singleton (r s : R) :
span {r} * span {s} = (span {r * s} : Ideal R) := by
unfold span
rw [Submodule.span_mul_span, Set.singleton_mul_singleton]
#align ideal.span_singleton_mul_span_singleton Ideal.span_singleton_mul_span_singleton
theorem span_singleton_pow (s : R) (n : ℕ) : span {s} ^ n = (span {s ^ n} : Ideal R) := by
induction' n with n ih; · simp [Set.singleton_one]
simp only [pow_succ, ih, span_singleton_mul_span_singleton]
#align ideal.span_singleton_pow Ideal.span_singleton_pow
theorem mem_mul_span_singleton {x y : R} {I : Ideal R} : x ∈ I * span {y} ↔ ∃ z ∈ I, z * y = x :=
Submodule.mem_smul_span_singleton
#align ideal.mem_mul_span_singleton Ideal.mem_mul_span_singleton
theorem mem_span_singleton_mul {x y : R} {I : Ideal R} : x ∈ span {y} * I ↔ ∃ z ∈ I, y * z = x := by
simp only [mul_comm, mem_mul_span_singleton]
#align ideal.mem_span_singleton_mul Ideal.mem_span_singleton_mul
theorem le_span_singleton_mul_iff {x : R} {I J : Ideal R} :
I ≤ span {x} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI :=
show (∀ {zI} (_ : zI ∈ I), zI ∈ span {x} * J) ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI by
simp only [mem_span_singleton_mul]
#align ideal.le_span_singleton_mul_iff Ideal.le_span_singleton_mul_iff
theorem span_singleton_mul_le_iff {x : R} {I J : Ideal R} :
span {x} * I ≤ J ↔ ∀ z ∈ I, x * z ∈ J := by
simp only [mul_le, mem_span_singleton_mul, mem_span_singleton]
constructor
· intro h zI hzI
exact h x (dvd_refl x) zI hzI
· rintro h _ ⟨z, rfl⟩ zI hzI
rw [mul_comm x z, mul_assoc]
exact J.mul_mem_left _ (h zI hzI)
#align ideal.span_singleton_mul_le_iff Ideal.span_singleton_mul_le_iff
theorem span_singleton_mul_le_span_singleton_mul {x y : R} {I J : Ideal R} :
span {x} * I ≤ span {y} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ := by
simp only [span_singleton_mul_le_iff, mem_span_singleton_mul, eq_comm]
#align ideal.span_singleton_mul_le_span_singleton_mul Ideal.span_singleton_mul_le_span_singleton_mul
theorem span_singleton_mul_right_mono [IsDomain R] {x : R} (hx : x ≠ 0) :
span {x} * I ≤ span {x} * J ↔ I ≤ J := by
simp_rw [span_singleton_mul_le_span_singleton_mul, mul_right_inj' hx,
exists_eq_right', SetLike.le_def]
#align ideal.span_singleton_mul_right_mono Ideal.span_singleton_mul_right_mono
theorem span_singleton_mul_left_mono [IsDomain R] {x : R} (hx : x ≠ 0) :
I * span {x} ≤ J * span {x} ↔ I ≤ J := by
simpa only [mul_comm I, mul_comm J] using span_singleton_mul_right_mono hx
#align ideal.span_singleton_mul_left_mono Ideal.span_singleton_mul_left_mono
theorem span_singleton_mul_right_inj [IsDomain R] {x : R} (hx : x ≠ 0) :
span {x} * I = span {x} * J ↔ I = J := by
simp only [le_antisymm_iff, span_singleton_mul_right_mono hx]
#align ideal.span_singleton_mul_right_inj Ideal.span_singleton_mul_right_inj
theorem span_singleton_mul_left_inj [IsDomain R] {x : R} (hx : x ≠ 0) :
I * span {x} = J * span {x} ↔ I = J := by
simp only [le_antisymm_iff, span_singleton_mul_left_mono hx]
#align ideal.span_singleton_mul_left_inj Ideal.span_singleton_mul_left_inj
theorem span_singleton_mul_right_injective [IsDomain R] {x : R} (hx : x ≠ 0) :
Function.Injective ((span {x} : Ideal R) * ·) := fun _ _ =>
(span_singleton_mul_right_inj hx).mp
#align ideal.span_singleton_mul_right_injective Ideal.span_singleton_mul_right_injective
theorem span_singleton_mul_left_injective [IsDomain R] {x : R} (hx : x ≠ 0) :
Function.Injective fun I : Ideal R => I * span {x} := fun _ _ =>
(span_singleton_mul_left_inj hx).mp
#align ideal.span_singleton_mul_left_injective Ideal.span_singleton_mul_left_injective
theorem eq_span_singleton_mul {x : R} (I J : Ideal R) :
I = span {x} * J ↔ (∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI) ∧ ∀ z ∈ J, x * z ∈ I := by
simp only [le_antisymm_iff, le_span_singleton_mul_iff, span_singleton_mul_le_iff]
#align ideal.eq_span_singleton_mul Ideal.eq_span_singleton_mul
theorem span_singleton_mul_eq_span_singleton_mul {x y : R} (I J : Ideal R) :
span {x} * I = span {y} * J ↔
(∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ) ∧ ∀ zJ ∈ J, ∃ zI ∈ I, x * zI = y * zJ := by
simp only [le_antisymm_iff, span_singleton_mul_le_span_singleton_mul, eq_comm]
#align ideal.span_singleton_mul_eq_span_singleton_mul Ideal.span_singleton_mul_eq_span_singleton_mul
theorem prod_span {ι : Type*} (s : Finset ι) (I : ι → Set R) :
(∏ i ∈ s, Ideal.span (I i)) = Ideal.span (∏ i ∈ s, I i) :=
Submodule.prod_span s I
#align ideal.prod_span Ideal.prod_span
theorem prod_span_singleton {ι : Type*} (s : Finset ι) (I : ι → R) :
(∏ i ∈ s, Ideal.span ({I i} : Set R)) = Ideal.span {∏ i ∈ s, I i} :=
Submodule.prod_span_singleton s I
#align ideal.prod_span_singleton Ideal.prod_span_singleton
@[simp]
theorem multiset_prod_span_singleton (m : Multiset R) :
(m.map fun x => Ideal.span {x}).prod = Ideal.span ({Multiset.prod m} : Set R) :=
Multiset.induction_on m (by simp) fun a m ih => by
simp only [Multiset.map_cons, Multiset.prod_cons, ih, ← Ideal.span_singleton_mul_span_singleton]
#align ideal.multiset_prod_span_singleton Ideal.multiset_prod_span_singleton
theorem finset_inf_span_singleton {ι : Type*} (s : Finset ι) (I : ι → R)
(hI : Set.Pairwise (↑s) (IsCoprime on I)) :
(s.inf fun i => Ideal.span ({I i} : Set R)) = Ideal.span {∏ i ∈ s, I i} := by
ext x
simp only [Submodule.mem_finset_inf, Ideal.mem_span_singleton]
exact ⟨Finset.prod_dvd_of_coprime hI, fun h i hi => (Finset.dvd_prod_of_mem _ hi).trans h⟩
#align ideal.finset_inf_span_singleton Ideal.finset_inf_span_singleton
theorem iInf_span_singleton {ι : Type*} [Fintype ι] {I : ι → R}
(hI : ∀ (i j) (_ : i ≠ j), IsCoprime (I i) (I j)) :
⨅ i, span ({I i} : Set R) = span {∏ i, I i} := by
rw [← Finset.inf_univ_eq_iInf, finset_inf_span_singleton]
rwa [Finset.coe_univ, Set.pairwise_univ]
#align ideal.infi_span_singleton Ideal.iInf_span_singleton
theorem iInf_span_singleton_natCast {R : Type*} [CommRing R] {ι : Type*} [Fintype ι]
{I : ι → ℕ} (hI : Pairwise fun i j => (I i).Coprime (I j)) :
⨅ (i : ι), span {(I i : R)} = span {((∏ i : ι, I i : ℕ) : R)} := by
rw [iInf_span_singleton, Nat.cast_prod]
exact fun i j h ↦ (hI h).cast
theorem sup_eq_top_iff_isCoprime {R : Type*} [CommSemiring R] (x y : R) :
span ({x} : Set R) ⊔ span {y} = ⊤ ↔ IsCoprime x y := by
rw [eq_top_iff_one, Submodule.mem_sup]
constructor
· rintro ⟨u, hu, v, hv, h1⟩
rw [mem_span_singleton'] at hu hv
rw [← hu.choose_spec, ← hv.choose_spec] at h1
exact ⟨_, _, h1⟩
· exact fun ⟨u, v, h1⟩ =>
⟨_, mem_span_singleton'.mpr ⟨_, rfl⟩, _, mem_span_singleton'.mpr ⟨_, rfl⟩, h1⟩
#align ideal.sup_eq_top_iff_is_coprime Ideal.sup_eq_top_iff_isCoprime
theorem mul_le_inf : I * J ≤ I ⊓ J :=
mul_le.2 fun r hri s hsj => ⟨I.mul_mem_right s hri, J.mul_mem_left r hsj⟩
#align ideal.mul_le_inf Ideal.mul_le_inf
theorem multiset_prod_le_inf {s : Multiset (Ideal R)} : s.prod ≤ s.inf := by
classical
refine s.induction_on ?_ ?_
· rw [Multiset.inf_zero]
exact le_top
intro a s ih
rw [Multiset.prod_cons, Multiset.inf_cons]
exact le_trans mul_le_inf (inf_le_inf le_rfl ih)
#align ideal.multiset_prod_le_inf Ideal.multiset_prod_le_inf
theorem prod_le_inf {s : Finset ι} {f : ι → Ideal R} : s.prod f ≤ s.inf f :=
multiset_prod_le_inf
#align ideal.prod_le_inf Ideal.prod_le_inf
theorem mul_eq_inf_of_coprime (h : I ⊔ J = ⊤) : I * J = I ⊓ J :=
le_antisymm mul_le_inf fun r ⟨hri, hrj⟩ =>
let ⟨s, hsi, t, htj, hst⟩ := Submodule.mem_sup.1 ((eq_top_iff_one _).1 h)
mul_one r ▸
hst ▸
(mul_add r s t).symm ▸ Ideal.add_mem (I * J) (mul_mem_mul_rev hsi hrj) (mul_mem_mul hri htj)
#align ideal.mul_eq_inf_of_coprime Ideal.mul_eq_inf_of_coprime
theorem sup_mul_eq_of_coprime_left (h : I ⊔ J = ⊤) : I ⊔ J * K = I ⊔ K :=
le_antisymm (sup_le_sup_left mul_le_left _) fun i hi => by
rw [eq_top_iff_one] at h; rw [Submodule.mem_sup] at h hi ⊢
obtain ⟨i1, hi1, j, hj, h⟩ := h; obtain ⟨i', hi', k, hk, hi⟩ := hi
refine ⟨_, add_mem hi' (mul_mem_right k _ hi1), _, mul_mem_mul hj hk, ?_⟩
rw [add_assoc, ← add_mul, h, one_mul, hi]
#align ideal.sup_mul_eq_of_coprime_left Ideal.sup_mul_eq_of_coprime_left
theorem sup_mul_eq_of_coprime_right (h : I ⊔ K = ⊤) : I ⊔ J * K = I ⊔ J := by
rw [mul_comm]
exact sup_mul_eq_of_coprime_left h
#align ideal.sup_mul_eq_of_coprime_right Ideal.sup_mul_eq_of_coprime_right
theorem mul_sup_eq_of_coprime_left (h : I ⊔ J = ⊤) : I * K ⊔ J = K ⊔ J := by
rw [sup_comm] at h
rw [sup_comm, sup_mul_eq_of_coprime_left h, sup_comm]
#align ideal.mul_sup_eq_of_coprime_left Ideal.mul_sup_eq_of_coprime_left
theorem mul_sup_eq_of_coprime_right (h : K ⊔ J = ⊤) : I * K ⊔ J = I ⊔ J := by
rw [sup_comm] at h
rw [sup_comm, sup_mul_eq_of_coprime_right h, sup_comm]
#align ideal.mul_sup_eq_of_coprime_right Ideal.mul_sup_eq_of_coprime_right
theorem sup_prod_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → I ⊔ J i = ⊤) :
(I ⊔ ∏ i ∈ s, J i) = ⊤ :=
Finset.prod_induction _ (fun J => I ⊔ J = ⊤)
(fun J K hJ hK => (sup_mul_eq_of_coprime_left hJ).trans hK)
(by simp_rw [one_eq_top, sup_top_eq]) h
#align ideal.sup_prod_eq_top Ideal.sup_prod_eq_top
theorem sup_iInf_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → I ⊔ J i = ⊤) :
(I ⊔ ⨅ i ∈ s, J i) = ⊤ :=
eq_top_iff.mpr <|
le_of_eq_of_le (sup_prod_eq_top h).symm <|
sup_le_sup_left (le_of_le_of_eq prod_le_inf <| Finset.inf_eq_iInf _ _) _
#align ideal.sup_infi_eq_top Ideal.sup_iInf_eq_top
theorem prod_sup_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → J i ⊔ I = ⊤) :
(∏ i ∈ s, J i) ⊔ I = ⊤ := by rw [sup_comm, sup_prod_eq_top]; intro i hi; rw [sup_comm, h i hi]
#align ideal.prod_sup_eq_top Ideal.prod_sup_eq_top
theorem iInf_sup_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → J i ⊔ I = ⊤) :
(⨅ i ∈ s, J i) ⊔ I = ⊤ := by rw [sup_comm, sup_iInf_eq_top]; intro i hi; rw [sup_comm, h i hi]
#align ideal.infi_sup_eq_top Ideal.iInf_sup_eq_top
theorem sup_pow_eq_top {n : ℕ} (h : I ⊔ J = ⊤) : I ⊔ J ^ n = ⊤ := by
rw [← Finset.card_range n, ← Finset.prod_const]
exact sup_prod_eq_top fun _ _ => h
#align ideal.sup_pow_eq_top Ideal.sup_pow_eq_top
theorem pow_sup_eq_top {n : ℕ} (h : I ⊔ J = ⊤) : I ^ n ⊔ J = ⊤ := by
rw [← Finset.card_range n, ← Finset.prod_const]
exact prod_sup_eq_top fun _ _ => h
#align ideal.pow_sup_eq_top Ideal.pow_sup_eq_top
theorem pow_sup_pow_eq_top {m n : ℕ} (h : I ⊔ J = ⊤) : I ^ m ⊔ J ^ n = ⊤ :=
sup_pow_eq_top (pow_sup_eq_top h)
#align ideal.pow_sup_pow_eq_top Ideal.pow_sup_pow_eq_top
variable (I)
-- @[simp] -- Porting note (#10618): simp can prove this
theorem mul_bot : I * ⊥ = ⊥ := by simp
#align ideal.mul_bot Ideal.mul_bot
-- @[simp] -- Porting note (#10618): simp can prove thisrove this
theorem bot_mul : ⊥ * I = ⊥ := by simp
#align ideal.bot_mul Ideal.bot_mul
@[simp]
theorem mul_top : I * ⊤ = I :=
Ideal.mul_comm ⊤ I ▸ Submodule.top_smul I
#align ideal.mul_top Ideal.mul_top
@[simp]
theorem top_mul : ⊤ * I = I :=
Submodule.top_smul I
#align ideal.top_mul Ideal.top_mul
variable {I}
theorem mul_mono (hik : I ≤ K) (hjl : J ≤ L) : I * J ≤ K * L :=
Submodule.smul_mono hik hjl
#align ideal.mul_mono Ideal.mul_mono
theorem mul_mono_left (h : I ≤ J) : I * K ≤ J * K :=
Submodule.smul_mono_left h
#align ideal.mul_mono_left Ideal.mul_mono_left
theorem mul_mono_right (h : J ≤ K) : I * J ≤ I * K :=
smul_mono_right _ h
#align ideal.mul_mono_right Ideal.mul_mono_right
variable (I J K)
theorem mul_sup : I * (J ⊔ K) = I * J ⊔ I * K :=
Submodule.smul_sup I J K
#align ideal.mul_sup Ideal.mul_sup
theorem sup_mul : (I ⊔ J) * K = I * K ⊔ J * K :=
Submodule.sup_smul I J K
#align ideal.sup_mul Ideal.sup_mul
variable {I J K}
theorem pow_le_pow_right {m n : ℕ} (h : m ≤ n) : I ^ n ≤ I ^ m := by
cases' Nat.exists_eq_add_of_le h with k hk
rw [hk, pow_add]
exact le_trans mul_le_inf inf_le_left
#align ideal.pow_le_pow_right Ideal.pow_le_pow_right
theorem pow_le_self {n : ℕ} (hn : n ≠ 0) : I ^ n ≤ I :=
calc
I ^ n ≤ I ^ 1 := pow_le_pow_right (Nat.pos_of_ne_zero hn)
_ = I := pow_one _
#align ideal.pow_le_self Ideal.pow_le_self
theorem pow_right_mono {I J : Ideal R} (e : I ≤ J) (n : ℕ) : I ^ n ≤ J ^ n := by
induction' n with _ hn
· rw [pow_zero, pow_zero]
· rw [pow_succ, pow_succ]
exact Ideal.mul_mono hn e
#align ideal.pow_right_mono Ideal.pow_right_mono
@[simp]
theorem mul_eq_bot {R : Type*} [CommSemiring R] [NoZeroDivisors R] {I J : Ideal R} :
I * J = ⊥ ↔ I = ⊥ ∨ J = ⊥ :=
⟨fun hij =>
or_iff_not_imp_left.mpr fun I_ne_bot =>
J.eq_bot_iff.mpr fun j hj =>
let ⟨i, hi, ne0⟩ := I.ne_bot_iff.mp I_ne_bot
Or.resolve_left (mul_eq_zero.mp ((I * J).eq_bot_iff.mp hij _ (mul_mem_mul hi hj))) ne0,
fun h => by cases' h with h h <;> rw [← Ideal.mul_bot, h, Ideal.mul_comm]⟩
#align ideal.mul_eq_bot Ideal.mul_eq_bot
instance {R : Type*} [CommSemiring R] [NoZeroDivisors R] : NoZeroDivisors (Ideal R) where
eq_zero_or_eq_zero_of_mul_eq_zero := mul_eq_bot.1
instance {R : Type*} [CommSemiring R] {S : Type*} [CommRing S] [Algebra R S]
[NoZeroSMulDivisors R S] {I : Ideal S} : NoZeroSMulDivisors R I :=
Submodule.noZeroSMulDivisors (Submodule.restrictScalars R I)
/-- A product of ideals in an integral domain is zero if and only if one of the terms is zero. -/
@[simp]
lemma multiset_prod_eq_bot {R : Type*} [CommRing R] [IsDomain R] {s : Multiset (Ideal R)} :
s.prod = ⊥ ↔ ⊥ ∈ s :=
Multiset.prod_eq_zero_iff
/-- A product of ideals in an integral domain is zero if and only if one of the terms is zero. -/
@[deprecated multiset_prod_eq_bot (since := "2023-12-26")]
theorem prod_eq_bot {R : Type*} [CommRing R] [IsDomain R] {s : Multiset (Ideal R)} :
s.prod = ⊥ ↔ ∃ I ∈ s, I = ⊥ := by
simp
#align ideal.prod_eq_bot Ideal.prod_eq_bot
theorem span_pair_mul_span_pair (w x y z : R) :
(span {w, x} : Ideal R) * span {y, z} = span {w * y, w * z, x * y, x * z} := by
simp_rw [span_insert, sup_mul, mul_sup, span_singleton_mul_span_singleton, sup_assoc]
#align ideal.span_pair_mul_span_pair Ideal.span_pair_mul_span_pair
theorem isCoprime_iff_codisjoint : IsCoprime I J ↔ Codisjoint I J := by
rw [IsCoprime, codisjoint_iff]
constructor
· rintro ⟨x, y, hxy⟩
rw [eq_top_iff_one]
apply (show x * I + y * J ≤ I ⊔ J from
sup_le (mul_le_left.trans le_sup_left) (mul_le_left.trans le_sup_right))
rw [hxy]
simp only [one_eq_top, Submodule.mem_top]
· intro h
refine ⟨1, 1, ?_⟩
simpa only [one_eq_top, top_mul, Submodule.add_eq_sup]
theorem isCoprime_iff_add : IsCoprime I J ↔ I + J = 1 := by
rw [isCoprime_iff_codisjoint, codisjoint_iff, add_eq_sup, one_eq_top]
theorem isCoprime_iff_exists : IsCoprime I J ↔ ∃ i ∈ I, ∃ j ∈ J, i + j = 1 := by
rw [← add_eq_one_iff, isCoprime_iff_add]
theorem isCoprime_iff_sup_eq : IsCoprime I J ↔ I ⊔ J = ⊤ := by
rw [isCoprime_iff_codisjoint, codisjoint_iff]
open List in
theorem isCoprime_tfae : TFAE [IsCoprime I J, Codisjoint I J, I + J = 1,
∃ i ∈ I, ∃ j ∈ J, i + j = 1, I ⊔ J = ⊤] := by
rw [← isCoprime_iff_codisjoint, ← isCoprime_iff_add, ← isCoprime_iff_exists,
← isCoprime_iff_sup_eq]
simp
theorem _root_.IsCoprime.codisjoint (h : IsCoprime I J) : Codisjoint I J :=
isCoprime_iff_codisjoint.mp h
theorem _root_.IsCoprime.add_eq (h : IsCoprime I J) : I + J = 1 := isCoprime_iff_add.mp h
theorem _root_.IsCoprime.exists (h : IsCoprime I J) : ∃ i ∈ I, ∃ j ∈ J, i + j = 1 :=
isCoprime_iff_exists.mp h
theorem _root_.IsCoprime.sup_eq (h : IsCoprime I J) : I ⊔ J = ⊤ := isCoprime_iff_sup_eq.mp h
theorem inf_eq_mul_of_isCoprime (coprime : IsCoprime I J) : I ⊓ J = I * J :=
(Ideal.mul_eq_inf_of_coprime coprime.sup_eq).symm
#align ideal.inf_eq_mul_of_coprime Ideal.inf_eq_mul_of_isCoprime
@[deprecated (since := "2024-05-28")]
alias inf_eq_mul_of_coprime := inf_eq_mul_of_isCoprime
theorem isCoprime_span_singleton_iff (x y : R) :
IsCoprime (span <| singleton x) (span <| singleton y) ↔ IsCoprime x y := by
simp_rw [isCoprime_iff_codisjoint, codisjoint_iff, eq_top_iff_one, mem_span_singleton_sup,
mem_span_singleton]
constructor
· rintro ⟨a, _, ⟨b, rfl⟩, e⟩; exact ⟨a, b, mul_comm b y ▸ e⟩
· rintro ⟨a, b, e⟩; exact ⟨a, _, ⟨b, rfl⟩, mul_comm y b ▸ e⟩
theorem isCoprime_biInf {J : ι → Ideal R} {s : Finset ι}
(hf : ∀ j ∈ s, IsCoprime I (J j)) : IsCoprime I (⨅ j ∈ s, J j) := by
classical
simp_rw [isCoprime_iff_add] at *
induction s using Finset.induction with
| empty =>
simp
| @insert i s _ hs =>
rw [Finset.iInf_insert, inf_comm, one_eq_top, eq_top_iff, ← one_eq_top]
set K := ⨅ j ∈ s, J j
calc
1 = I + K := (hs fun j hj ↦ hf j (Finset.mem_insert_of_mem hj)).symm
_ = I + K*(I + J i) := by rw [hf i (Finset.mem_insert_self i s), mul_one]
_ = (1+K)*I + K*J i := by ring
_ ≤ I + K ⊓ J i := add_le_add mul_le_left mul_le_inf
/-- The radical of an ideal `I` consists of the elements `r` such that `r ^ n ∈ I` for some `n`. -/
def radical (I : Ideal R) : Ideal R where
carrier := { r | ∃ n : ℕ, r ^ n ∈ I }
zero_mem' := ⟨1, (pow_one (0 : R)).symm ▸ I.zero_mem⟩
add_mem' := fun {_ _} ⟨m, hxmi⟩ ⟨n, hyni⟩ =>
⟨m + n - 1, add_pow_add_pred_mem_of_pow_mem I hxmi hyni⟩
smul_mem' {r s} := fun ⟨n, h⟩ ↦ ⟨n, (mul_pow r s n).symm ▸ I.mul_mem_left (r ^ n) h⟩
#align ideal.radical Ideal.radical
theorem mem_radical_iff {r : R} : r ∈ I.radical ↔ ∃ n : ℕ, r ^ n ∈ I := Iff.rfl
/-- An ideal is radical if it contains its radical. -/
def IsRadical (I : Ideal R) : Prop :=
I.radical ≤ I
#align ideal.is_radical Ideal.IsRadical
theorem le_radical : I ≤ radical I := fun r hri => ⟨1, (pow_one r).symm ▸ hri⟩
#align ideal.le_radical Ideal.le_radical
/-- An ideal is radical iff it is equal to its radical. -/
theorem radical_eq_iff : I.radical = I ↔ I.IsRadical := by
rw [le_antisymm_iff, and_iff_left le_radical, IsRadical]
#align ideal.radical_eq_iff Ideal.radical_eq_iff
alias ⟨_, IsRadical.radical⟩ := radical_eq_iff
#align ideal.is_radical.radical Ideal.IsRadical.radical
theorem isRadical_iff_pow_one_lt (k : ℕ) (hk : 1 < k) : I.IsRadical ↔ ∀ r, r ^ k ∈ I → r ∈ I :=
⟨fun h _r hr ↦ h ⟨k, hr⟩, fun h x ⟨n, hx⟩ ↦
k.pow_imp_self_of_one_lt hk _ (fun _ _ ↦ .inr ∘ I.smul_mem _) h n x hx⟩
variable (R)
theorem radical_top : (radical ⊤ : Ideal R) = ⊤ :=
(eq_top_iff_one _).2 ⟨0, Submodule.mem_top⟩
#align ideal.radical_top Ideal.radical_top
variable {R}
theorem radical_mono (H : I ≤ J) : radical I ≤ radical J := fun _ ⟨n, hrni⟩ => ⟨n, H hrni⟩
#align ideal.radical_mono Ideal.radical_mono
variable (I)
theorem radical_isRadical : (radical I).IsRadical := fun r ⟨n, k, hrnki⟩ =>
⟨n * k, (pow_mul r n k).symm ▸ hrnki⟩
#align ideal.radical_is_radical Ideal.radical_isRadical
@[simp]
theorem radical_idem : radical (radical I) = radical I :=
(radical_isRadical I).radical
#align ideal.radical_idem Ideal.radical_idem
variable {I}
theorem IsRadical.radical_le_iff (hJ : J.IsRadical) : I.radical ≤ J ↔ I ≤ J :=
⟨le_trans le_radical, fun h => hJ.radical ▸ radical_mono h⟩
#align ideal.is_radical.radical_le_iff Ideal.IsRadical.radical_le_iff
theorem radical_le_radical_iff : radical I ≤ radical J ↔ I ≤ radical J :=
(radical_isRadical J).radical_le_iff
#align ideal.radical_le_radical_iff Ideal.radical_le_radical_iff
theorem radical_eq_top : radical I = ⊤ ↔ I = ⊤ :=
⟨fun h =>
(eq_top_iff_one _).2 <|
let ⟨n, hn⟩ := (eq_top_iff_one _).1 h
@one_pow R _ n ▸ hn,
fun h => h.symm ▸ radical_top R⟩
#align ideal.radical_eq_top Ideal.radical_eq_top
theorem IsPrime.isRadical (H : IsPrime I) : I.IsRadical := fun _ ⟨n, hrni⟩ =>
H.mem_of_pow_mem n hrni
#align ideal.is_prime.is_radical Ideal.IsPrime.isRadical
theorem IsPrime.radical (H : IsPrime I) : radical I = I :=
IsRadical.radical H.isRadical
#align ideal.is_prime.radical Ideal.IsPrime.radical
theorem mem_radical_of_pow_mem {I : Ideal R} {x : R} {m : ℕ} (hx : x ^ m ∈ radical I) :
x ∈ radical I :=
radical_idem I ▸ ⟨m, hx⟩
#align ideal.mem_radical_of_pow_mem Ideal.mem_radical_of_pow_mem
theorem disjoint_powers_iff_not_mem (y : R) (hI : I.IsRadical) :
Disjoint (Submonoid.powers y : Set R) ↑I ↔ y ∉ I.1 := by
refine ⟨fun h => Set.disjoint_left.1 h (Submonoid.mem_powers _),
fun h => disjoint_iff.mpr (eq_bot_iff.mpr ?_)⟩
rintro x ⟨⟨n, rfl⟩, hx'⟩
exact h (hI <| mem_radical_of_pow_mem <| le_radical hx')
#align ideal.disjoint_powers_iff_not_mem Ideal.disjoint_powers_iff_not_mem
variable (I J)
theorem radical_sup : radical (I ⊔ J) = radical (radical I ⊔ radical J) :=
le_antisymm (radical_mono <| sup_le_sup le_radical le_radical) <|
radical_le_radical_iff.2 <| sup_le (radical_mono le_sup_left) (radical_mono le_sup_right)
#align ideal.radical_sup Ideal.radical_sup
theorem radical_inf : radical (I ⊓ J) = radical I ⊓ radical J :=
le_antisymm (le_inf (radical_mono inf_le_left) (radical_mono inf_le_right))
fun r ⟨⟨m, hrm⟩, ⟨n, hrn⟩⟩ =>
⟨m + n, (pow_add r m n).symm ▸ I.mul_mem_right _ hrm,
(pow_add r m n).symm ▸ J.mul_mem_left _ hrn⟩
#align ideal.radical_inf Ideal.radical_inf
variable {I J} in
theorem IsRadical.inf (hI : IsRadical I) (hJ : IsRadical J) : IsRadical (I ⊓ J) := by
rw [IsRadical, radical_inf]; exact inf_le_inf hI hJ
/-- The reverse inclusion does not hold for e.g. `I := fun n : ℕ ↦ Ideal.span {(2 ^ n : ℤ)}`. -/
theorem radical_iInf_le {ι} (I : ι → Ideal R) : radical (⨅ i, I i) ≤ ⨅ i, radical (I i) :=
le_iInf fun _ ↦ radical_mono (iInf_le _ _)
theorem isRadical_iInf {ι} (I : ι → Ideal R) (hI : ∀ i, IsRadical (I i)) : IsRadical (⨅ i, I i) :=
(radical_iInf_le I).trans (iInf_mono hI)
theorem radical_mul : radical (I * J) = radical I ⊓ radical J := by
refine le_antisymm ?_ fun r ⟨⟨m, hrm⟩, ⟨n, hrn⟩⟩ =>
⟨m + n, (pow_add r m n).symm ▸ mul_mem_mul hrm hrn⟩
have := radical_mono <| @mul_le_inf _ _ I J
simp_rw [radical_inf I J] at this
assumption
#align ideal.radical_mul Ideal.radical_mul
variable {I J}
theorem IsPrime.radical_le_iff (hJ : IsPrime J) : I.radical ≤ J ↔ I ≤ J :=
IsRadical.radical_le_iff hJ.isRadical
#align ideal.is_prime.radical_le_iff Ideal.IsPrime.radical_le_iff
theorem radical_eq_sInf (I : Ideal R) : radical I = sInf { J : Ideal R | I ≤ J ∧ IsPrime J } :=
le_antisymm (le_sInf fun J hJ ↦ hJ.2.radical_le_iff.2 hJ.1) fun r hr ↦
by_contradiction fun hri ↦
let ⟨m, (hrm : r ∉ radical m), him, hm⟩ :=
zorn_nonempty_partialOrder₀ { K : Ideal R | r ∉ radical K }
(fun c hc hcc y hyc =>
⟨sSup c, fun ⟨n, hrnc⟩ =>
let ⟨y, hyc, hrny⟩ := (Submodule.mem_sSup_of_directed ⟨y, hyc⟩ hcc.directedOn).1 hrnc
hc hyc ⟨n, hrny⟩,
fun z => le_sSup⟩)
I hri
have : ∀ x ∉ m, r ∈ radical (m ⊔ span {x}) := fun x hxm =>
by_contradiction fun hrmx =>
hxm <|
hm (m ⊔ span {x}) hrmx le_sup_left ▸
(le_sup_right : _ ≤ m ⊔ span {x}) (subset_span <| Set.mem_singleton _)
have : IsPrime m :=
⟨by rintro rfl; rw [radical_top] at hrm; exact hrm trivial, fun {x y} hxym =>
or_iff_not_imp_left.2 fun hxm =>
by_contradiction fun hym =>
let ⟨n, hrn⟩ := this _ hxm
let ⟨p, hpm, q, hq, hpqrn⟩ := Submodule.mem_sup.1 hrn
let ⟨c, hcxq⟩ := mem_span_singleton'.1 hq
let ⟨k, hrk⟩ := this _ hym
let ⟨f, hfm, g, hg, hfgrk⟩ := Submodule.mem_sup.1 hrk
let ⟨d, hdyg⟩ := mem_span_singleton'.1 hg
hrm
⟨n + k, by
rw [pow_add, ← hpqrn, ← hcxq, ← hfgrk, ← hdyg, add_mul, mul_add (c * x),
mul_assoc c x (d * y), mul_left_comm x, ← mul_assoc];
refine
m.add_mem (m.mul_mem_right _ hpm)
(m.add_mem (m.mul_mem_left _ hfm) (m.mul_mem_left _ hxym))⟩⟩
hrm <|
this.radical.symm ▸ (sInf_le ⟨him, this⟩ : sInf { J : Ideal R | I ≤ J ∧ IsPrime J } ≤ m) hr
#align ideal.radical_eq_Inf Ideal.radical_eq_sInf
theorem isRadical_bot_of_noZeroDivisors {R} [CommSemiring R] [NoZeroDivisors R] :
(⊥ : Ideal R).IsRadical := fun _ hx => hx.recOn fun _ hn => pow_eq_zero hn
#align ideal.is_radical_bot_of_no_zero_divisors Ideal.isRadical_bot_of_noZeroDivisors
@[simp]
theorem radical_bot_of_noZeroDivisors {R : Type u} [CommSemiring R] [NoZeroDivisors R] :
radical (⊥ : Ideal R) = ⊥ :=
eq_bot_iff.2 isRadical_bot_of_noZeroDivisors
#align ideal.radical_bot_of_no_zero_divisors Ideal.radical_bot_of_noZeroDivisors
instance : IdemCommSemiring (Ideal R) :=
inferInstance
variable (R)
theorem top_pow (n : ℕ) : (⊤ ^ n : Ideal R) = ⊤ :=
Nat.recOn n one_eq_top fun n ih => by rw [pow_succ, ih, top_mul]
#align ideal.top_pow Ideal.top_pow
variable {R}
variable (I)
lemma radical_pow : ∀ {n}, n ≠ 0 → radical (I ^ n) = radical I
| 1, _ => by simp
| n + 2, _ => by rw [pow_succ, radical_mul, radical_pow n.succ_ne_zero, inf_idem]
#align ideal.radical_pow Ideal.radical_pow
theorem IsPrime.mul_le {I J P : Ideal R} (hp : IsPrime P) : I * J ≤ P ↔ I ≤ P ∨ J ≤ P := by
rw [or_comm, Ideal.mul_le]
simp_rw [hp.mul_mem_iff_mem_or_mem, SetLike.le_def, ← forall_or_left, or_comm, forall_or_left]
#align ideal.is_prime.mul_le Ideal.IsPrime.mul_le
theorem IsPrime.inf_le {I J P : Ideal R} (hp : IsPrime P) : I ⊓ J ≤ P ↔ I ≤ P ∨ J ≤ P :=
⟨fun h ↦ hp.mul_le.1 <| mul_le_inf.trans h, fun h ↦ h.elim inf_le_left.trans inf_le_right.trans⟩
#align ideal.is_prime.inf_le Ideal.IsPrime.inf_le
theorem IsPrime.multiset_prod_le {s : Multiset (Ideal R)} {P : Ideal R} (hp : IsPrime P) :
s.prod ≤ P ↔ ∃ I ∈ s, I ≤ P :=
s.induction_on (by simp [hp.ne_top]) fun I s ih ↦ by simp [hp.mul_le, ih]
#align ideal.is_prime.multiset_prod_le Ideal.IsPrime.multiset_prod_le
theorem IsPrime.multiset_prod_map_le {s : Multiset ι} (f : ι → Ideal R) {P : Ideal R}
(hp : IsPrime P) : (s.map f).prod ≤ P ↔ ∃ i ∈ s, f i ≤ P := by
simp_rw [hp.multiset_prod_le, Multiset.mem_map, exists_exists_and_eq_and]
#align ideal.is_prime.multiset_prod_map_le Ideal.IsPrime.multiset_prod_map_le
theorem IsPrime.multiset_prod_mem_iff_exists_mem {I : Ideal R} (hI : I.IsPrime) (s : Multiset R) :
s.prod ∈ I ↔ ∃ p ∈ s, p ∈ I := by
simpa [span_singleton_le_iff_mem] using (hI.multiset_prod_map_le (span {·}))
theorem IsPrime.prod_le {s : Finset ι} {f : ι → Ideal R} {P : Ideal R} (hp : IsPrime P) :
s.prod f ≤ P ↔ ∃ i ∈ s, f i ≤ P :=
hp.multiset_prod_map_le f
#align ideal.is_prime.prod_le Ideal.IsPrime.prod_le
theorem IsPrime.prod_mem_iff_exists_mem {I : Ideal R} (hI : I.IsPrime) (s : Finset R) :
s.prod (fun x ↦ x) ∈ I ↔ ∃ p ∈ s, p ∈ I := by
rw [Finset.prod_eq_multiset_prod, Multiset.map_id']
exact hI.multiset_prod_mem_iff_exists_mem s.val
theorem IsPrime.inf_le' {s : Finset ι} {f : ι → Ideal R} {P : Ideal R} (hp : IsPrime P) :
s.inf f ≤ P ↔ ∃ i ∈ s, f i ≤ P :=
⟨fun h ↦ hp.prod_le.1 <| prod_le_inf.trans h, fun ⟨_, his, hip⟩ ↦ (Finset.inf_le his).trans hip⟩
#align ideal.is_prime.inf_le' Ideal.IsPrime.inf_le'
-- Porting note: needed to add explicit coercions (· : Set R).
theorem subset_union {R : Type u} [Ring R] {I J K : Ideal R} :
(I : Set R) ⊆ J ∪ K ↔ I ≤ J ∨ I ≤ K :=
AddSubgroupClass.subset_union
#align ideal.subset_union Ideal.subset_union
theorem subset_union_prime' {R : Type u} [CommRing R] {s : Finset ι} {f : ι → Ideal R} {a b : ι}
(hp : ∀ i ∈ s, IsPrime (f i)) {I : Ideal R} :
((I : Set R) ⊆ f a ∪ f b ∪ ⋃ i ∈ (↑s : Set ι), f i) ↔ I ≤ f a ∨ I ≤ f b ∨ ∃ i ∈ s, I ≤ f i := by
suffices
((I : Set R) ⊆ f a ∪ f b ∪ ⋃ i ∈ (↑s : Set ι), f i) → I ≤ f a ∨ I ≤ f b ∨ ∃ i ∈ s, I ≤ f i from
⟨this, fun h =>
Or.casesOn h
(fun h =>
Set.Subset.trans h <|
Set.Subset.trans Set.subset_union_left Set.subset_union_left)
fun h =>
Or.casesOn h
(fun h =>
Set.Subset.trans h <|
Set.Subset.trans Set.subset_union_right Set.subset_union_left)
fun ⟨i, his, hi⟩ => by
refine Set.Subset.trans hi <| Set.Subset.trans ?_ Set.subset_union_right;
exact Set.subset_biUnion_of_mem (u := fun x ↦ (f x : Set R)) (Finset.mem_coe.2 his)⟩
generalize hn : s.card = n; intro h
induction' n with n ih generalizing a b s
· clear hp
rw [Finset.card_eq_zero] at hn
subst hn
rw [Finset.coe_empty, Set.biUnion_empty, Set.union_empty, subset_union] at h
simpa only [exists_prop, Finset.not_mem_empty, false_and_iff, exists_false, or_false_iff]
classical
replace hn : ∃ (i : ι) (t : Finset ι), i ∉ t ∧ insert i t = s ∧ t.card = n :=
Finset.card_eq_succ.1 hn
rcases hn with ⟨i, t, hit, rfl, hn⟩
replace hp : IsPrime (f i) ∧ ∀ x ∈ t, IsPrime (f x) := (t.forall_mem_insert _ _).1 hp
by_cases Ht : ∃ j ∈ t, f j ≤ f i
· obtain ⟨j, hjt, hfji⟩ : ∃ j ∈ t, f j ≤ f i := Ht
obtain ⟨u, hju, rfl⟩ : ∃ u, j ∉ u ∧ insert j u = t :=
⟨t.erase j, t.not_mem_erase j, Finset.insert_erase hjt⟩
have hp' : ∀ k ∈ insert i u, IsPrime (f k) := by
rw [Finset.forall_mem_insert] at hp ⊢
exact ⟨hp.1, hp.2.2⟩
have hiu : i ∉ u := mt Finset.mem_insert_of_mem hit
have hn' : (insert i u).card = n := by
rwa [Finset.card_insert_of_not_mem] at hn ⊢
exacts [hiu, hju]
have h' : (I : Set R) ⊆ f a ∪ f b ∪ ⋃ k ∈ (↑(insert i u) : Set ι), f k := by
rw [Finset.coe_insert] at h ⊢
rw [Finset.coe_insert] at h
simp only [Set.biUnion_insert] at h ⊢
rw [← Set.union_assoc (f i : Set R)] at h
erw [Set.union_eq_self_of_subset_right hfji] at h
exact h
specialize ih hp' hn' h'
refine ih.imp id (Or.imp id (Exists.imp fun k => ?_))
exact And.imp (fun hk => Finset.insert_subset_insert i (Finset.subset_insert j u) hk) id
by_cases Ha : f a ≤ f i
· have h' : (I : Set R) ⊆ f i ∪ f b ∪ ⋃ j ∈ (↑t : Set ι), f j := by
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_assoc,
Set.union_right_comm (f a : Set R)] at h
erw [Set.union_eq_self_of_subset_left Ha] at h
exact h
specialize ih hp.2 hn h'
right
rcases ih with (ih | ih | ⟨k, hkt, ih⟩)
· exact Or.inr ⟨i, Finset.mem_insert_self i t, ih⟩
· exact Or.inl ih
· exact Or.inr ⟨k, Finset.mem_insert_of_mem hkt, ih⟩
by_cases Hb : f b ≤ f i
· have h' : (I : Set R) ⊆ f a ∪ f i ∪ ⋃ j ∈ (↑t : Set ι), f j := by
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_assoc,
Set.union_assoc (f a : Set R)] at h
erw [Set.union_eq_self_of_subset_left Hb] at h
exact h
specialize ih hp.2 hn h'
rcases ih with (ih | ih | ⟨k, hkt, ih⟩)
· exact Or.inl ih
· exact Or.inr (Or.inr ⟨i, Finset.mem_insert_self i t, ih⟩)
· exact Or.inr (Or.inr ⟨k, Finset.mem_insert_of_mem hkt, ih⟩)
by_cases Hi : I ≤ f i
· exact Or.inr (Or.inr ⟨i, Finset.mem_insert_self i t, Hi⟩)
have : ¬I ⊓ f a ⊓ f b ⊓ t.inf f ≤ f i := by
simp only [hp.1.inf_le, hp.1.inf_le', not_or]
exact ⟨⟨⟨Hi, Ha⟩, Hb⟩, Ht⟩
rcases Set.not_subset.1 this with ⟨r, ⟨⟨⟨hrI, hra⟩, hrb⟩, hr⟩, hri⟩
by_cases HI : (I : Set R) ⊆ f a ∪ f b ∪ ⋃ j ∈ (↑t : Set ι), f j
· specialize ih hp.2 hn HI
rcases ih with (ih | ih | ⟨k, hkt, ih⟩)
· left
exact ih
· right
left
exact ih
· right
right
exact ⟨k, Finset.mem_insert_of_mem hkt, ih⟩
exfalso
rcases Set.not_subset.1 HI with ⟨s, hsI, hs⟩
rw [Finset.coe_insert, Set.biUnion_insert] at h
have hsi : s ∈ f i := ((h hsI).resolve_left (mt Or.inl hs)).resolve_right (mt Or.inr hs)
rcases h (I.add_mem hrI hsI) with (⟨ha | hb⟩ | hi | ht)
· exact hs (Or.inl <| Or.inl <| add_sub_cancel_left r s ▸ (f a).sub_mem ha hra)
· exact hs (Or.inl <| Or.inr <| add_sub_cancel_left r s ▸ (f b).sub_mem hb hrb)
· exact hri (add_sub_cancel_right r s ▸ (f i).sub_mem hi hsi)
· rw [Set.mem_iUnion₂] at ht
rcases ht with ⟨j, hjt, hj⟩
simp only [Finset.inf_eq_iInf, SetLike.mem_coe, Submodule.mem_iInf] at hr
exact hs $ Or.inr $ Set.mem_biUnion hjt <|
add_sub_cancel_left r s ▸ (f j).sub_mem hj <| hr j hjt
#align ideal.subset_union_prime' Ideal.subset_union_prime'
/-- Prime avoidance. Atiyah-Macdonald 1.11, Eisenbud 3.3, Stacks 00DS, Matsumura Ex.1.6. -/
theorem subset_union_prime {R : Type u} [CommRing R] {s : Finset ι} {f : ι → Ideal R} (a b : ι)
(hp : ∀ i ∈ s, i ≠ a → i ≠ b → IsPrime (f i)) {I : Ideal R} :
((I : Set R) ⊆ ⋃ i ∈ (↑s : Set ι), f i) ↔ ∃ i ∈ s, I ≤ f i :=
suffices ((I : Set R) ⊆ ⋃ i ∈ (↑s : Set ι), f i) → ∃ i, i ∈ s ∧ I ≤ f i by
have aux := fun h => (bex_def.2 <| this h)
simp_rw [exists_prop] at aux
refine ⟨aux, fun ⟨i, his, hi⟩ ↦ Set.Subset.trans hi ?_⟩
apply Set.subset_biUnion_of_mem (show i ∈ (↑s : Set ι) from his)
fun h : (I : Set R) ⊆ ⋃ i ∈ (↑s : Set ι), f i => by
classical
by_cases has : a ∈ s
· obtain ⟨t, hat, rfl⟩ : ∃ t, a ∉ t ∧ insert a t = s :=
⟨s.erase a, Finset.not_mem_erase a s, Finset.insert_erase has⟩
by_cases hbt : b ∈ t
· obtain ⟨u, hbu, rfl⟩ : ∃ u, b ∉ u ∧ insert b u = t :=
⟨t.erase b, Finset.not_mem_erase b t, Finset.insert_erase hbt⟩
have hp' : ∀ i ∈ u, IsPrime (f i) := by
intro i hiu
refine hp i (Finset.mem_insert_of_mem (Finset.mem_insert_of_mem hiu)) ?_ ?_ <;>
rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Finset.coe_insert, Set.biUnion_insert, Set.biUnion_insert, ←
Set.union_assoc, subset_union_prime' hp'] at h
rwa [Finset.exists_mem_insert, Finset.exists_mem_insert]
· have hp' : ∀ j ∈ t, IsPrime (f j) := by
intro j hj
refine hp j (Finset.mem_insert_of_mem hj) ?_ ?_ <;> rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_self (f a : Set R),
subset_union_prime' hp', ← or_assoc, or_self_iff] at h
rwa [Finset.exists_mem_insert]
· by_cases hbs : b ∈ s
· obtain ⟨t, hbt, rfl⟩ : ∃ t, b ∉ t ∧ insert b t = s :=
⟨s.erase b, Finset.not_mem_erase b s, Finset.insert_erase hbs⟩
have hp' : ∀ j ∈ t, IsPrime (f j) := by
intro j hj
refine hp j (Finset.mem_insert_of_mem hj) ?_ ?_ <;> rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_self (f b : Set R),
subset_union_prime' hp', ← or_assoc, or_self_iff] at h
rwa [Finset.exists_mem_insert]
rcases s.eq_empty_or_nonempty with hse | hsne
· subst hse
rw [Finset.coe_empty, Set.biUnion_empty, Set.subset_empty_iff] at h
have : (I : Set R) ≠ ∅ := Set.Nonempty.ne_empty (Set.nonempty_of_mem I.zero_mem)
exact absurd h this
· cases' hsne with i his
obtain ⟨t, _, rfl⟩ : ∃ t, i ∉ t ∧ insert i t = s :=
⟨s.erase i, Finset.not_mem_erase i s, Finset.insert_erase his⟩
have hp' : ∀ j ∈ t, IsPrime (f j) := by
intro j hj
refine hp j (Finset.mem_insert_of_mem hj) ?_ ?_ <;> rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_self (f i : Set R),
subset_union_prime' hp', ← or_assoc, or_self_iff] at h
rwa [Finset.exists_mem_insert]
#align ideal.subset_union_prime Ideal.subset_union_prime
section Dvd
/-- If `I` divides `J`, then `I` contains `J`.
In a Dedekind domain, to divide and contain are equivalent, see `Ideal.dvd_iff_le`.
-/
theorem le_of_dvd {I J : Ideal R} : I ∣ J → J ≤ I
| ⟨_, h⟩ => h.symm ▸ le_trans mul_le_inf inf_le_left
#align ideal.le_of_dvd Ideal.le_of_dvd
@[simp]
theorem isUnit_iff {I : Ideal R} : IsUnit I ↔ I = ⊤ :=
isUnit_iff_dvd_one.trans
((@one_eq_top R _).symm ▸
⟨fun h => eq_top_iff.mpr (Ideal.le_of_dvd h), fun h => ⟨⊤, by rw [mul_top, h]⟩⟩)
#align ideal.is_unit_iff Ideal.isUnit_iff
instance uniqueUnits : Unique (Ideal R)ˣ where
default := 1
uniq u := Units.ext (show (u : Ideal R) = 1 by rw [isUnit_iff.mp u.isUnit, one_eq_top])
#align ideal.unique_units Ideal.uniqueUnits
end Dvd
end MulAndRadical
section Total
variable (ι : Type*)
variable (M : Type*) [AddCommGroup M] {R : Type*} [CommRing R] [Module R M] (I : Ideal R)
variable (v : ι → M) (hv : Submodule.span R (Set.range v) = ⊤)
/-- A variant of `Finsupp.total` that takes in vectors valued in `I`. -/
noncomputable def finsuppTotal : (ι →₀ I) →ₗ[R] M :=
(Finsupp.total ι M R v).comp (Finsupp.mapRange.linearMap I.subtype)
#align ideal.finsupp_total Ideal.finsuppTotal
variable {ι M v}
theorem finsuppTotal_apply (f : ι →₀ I) :
finsuppTotal ι M I v f = f.sum fun i x => (x : R) • v i := by
dsimp [finsuppTotal]
rw [Finsupp.total_apply, Finsupp.sum_mapRange_index]
exact fun _ => zero_smul _ _
#align ideal.finsupp_total_apply Ideal.finsuppTotal_apply
theorem finsuppTotal_apply_eq_of_fintype [Fintype ι] (f : ι →₀ I) :
finsuppTotal ι M I v f = ∑ i, (f i : R) • v i := by
rw [finsuppTotal_apply, Finsupp.sum_fintype]
exact fun _ => zero_smul _ _
#align ideal.finsupp_total_apply_eq_of_fintype Ideal.finsuppTotal_apply_eq_of_fintype
| Mathlib/RingTheory/Ideal/Operations.lean | 1,359 | 1,371 | theorem range_finsuppTotal :
LinearMap.range (finsuppTotal ι M I v) = I • Submodule.span R (Set.range v) := by |
ext
rw [Submodule.mem_ideal_smul_span_iff_exists_sum]
refine ⟨fun ⟨f, h⟩ => ⟨Finsupp.mapRange.linearMap I.subtype f, fun i => (f i).2, h⟩, ?_⟩
rintro ⟨a, ha, rfl⟩
classical
refine ⟨a.mapRange (fun r => if h : r ∈ I then ⟨r, h⟩ else 0) (by simp), ?_⟩
rw [finsuppTotal_apply, Finsupp.sum_mapRange_index]
· apply Finsupp.sum_congr
intro i _
rw [dif_pos (ha i)]
· exact fun _ => zero_smul _ _
|
/-
Copyright (c) 2021 Jakob von Raumer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jakob von Raumer
-/
import Mathlib.CategoryTheory.Monoidal.Free.Coherence
import Mathlib.Tactic.CategoryTheory.Coherence
import Mathlib.CategoryTheory.Closed.Monoidal
import Mathlib.Tactic.ApplyFun
#align_import category_theory.monoidal.rigid.basic from "leanprover-community/mathlib"@"3d7987cda72abc473c7cdbbb075170e9ac620042"
/-!
# Rigid (autonomous) monoidal categories
This file defines rigid (autonomous) monoidal categories and the necessary theory about
exact pairings and duals.
## Main definitions
* `ExactPairing` of two objects of a monoidal category
* Type classes `HasLeftDual` and `HasRightDual` that capture that a pairing exists
* The `rightAdjointMate f` as a morphism `fᘁ : Yᘁ ⟶ Xᘁ` for a morphism `f : X ⟶ Y`
* The classes of `RightRigidCategory`, `LeftRigidCategory` and `RigidCategory`
## Main statements
* `comp_rightAdjointMate`: The adjoint mates of the composition is the composition of
adjoint mates.
## Notations
* `η_` and `ε_` denote the coevaluation and evaluation morphism of an exact pairing.
* `Xᘁ` and `ᘁX` denote the right and left dual of an object, as well as the adjoint
mate of a morphism.
## Future work
* Show that `X ⊗ Y` and `Yᘁ ⊗ Xᘁ` form an exact pairing.
* Show that the left adjoint mate of the right adjoint mate of a morphism is the morphism itself.
* Simplify constructions in the case where a symmetry or braiding is present.
* Show that `ᘁ` gives an equivalence of categories `C ≅ (Cᵒᵖ)ᴹᵒᵖ`.
* Define pivotal categories (rigid categories equipped with a natural isomorphism `ᘁᘁ ≅ 𝟙 C`).
## Notes
Although we construct the adjunction `tensorLeft Y ⊣ tensorLeft X` from `ExactPairing X Y`,
this is not a bijective correspondence.
I think the correct statement is that `tensorLeft Y` and `tensorLeft X` are
module endofunctors of `C` as a right `C` module category,
and `ExactPairing X Y` is in bijection with adjunctions compatible with this right `C` action.
## References
* <https://ncatlab.org/nlab/show/rigid+monoidal+category>
## Tags
rigid category, monoidal category
-/
open CategoryTheory MonoidalCategory
universe v v₁ v₂ v₃ u u₁ u₂ u₃
noncomputable section
namespace CategoryTheory
variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory C]
/-- An exact pairing is a pair of objects `X Y : C` which admit
a coevaluation and evaluation morphism which fulfill two triangle equalities. -/
class ExactPairing (X Y : C) where
/-- Coevaluation of an exact pairing.
Do not use directly. Use `ExactPairing.coevaluation` instead. -/
coevaluation' : 𝟙_ C ⟶ X ⊗ Y
/-- Evaluation of an exact pairing.
Do not use directly. Use `ExactPairing.evaluation` instead. -/
evaluation' : Y ⊗ X ⟶ 𝟙_ C
coevaluation_evaluation' :
Y ◁ coevaluation' ≫ (α_ _ _ _).inv ≫ evaluation' ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv := by
aesop_cat
evaluation_coevaluation' :
coevaluation' ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ evaluation' = (λ_ X).hom ≫ (ρ_ X).inv := by
aesop_cat
#align category_theory.exact_pairing CategoryTheory.ExactPairing
namespace ExactPairing
-- Porting note: as there is no mechanism equivalent to `[]` in Lean 3 to make
-- arguments for class fields explicit,
-- we now repeat all the fields without primes.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Making.20variable.20in.20class.20field.20explicit
variable (X Y : C)
variable [ExactPairing X Y]
/-- Coevaluation of an exact pairing. -/
def coevaluation : 𝟙_ C ⟶ X ⊗ Y := @coevaluation' _ _ _ X Y _
/-- Evaluation of an exact pairing. -/
def evaluation : Y ⊗ X ⟶ 𝟙_ C := @evaluation' _ _ _ X Y _
@[inherit_doc] notation "η_" => ExactPairing.coevaluation
@[inherit_doc] notation "ε_" => ExactPairing.evaluation
lemma coevaluation_evaluation :
Y ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ ε_ X _ ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv :=
coevaluation_evaluation'
lemma evaluation_coevaluation :
η_ _ _ ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ ε_ _ Y = (λ_ X).hom ≫ (ρ_ X).inv :=
evaluation_coevaluation'
lemma coevaluation_evaluation'' :
Y ◁ η_ X Y ⊗≫ ε_ X Y ▷ Y = ⊗𝟙 := by
convert coevaluation_evaluation X Y <;> simp [monoidalComp]
lemma evaluation_coevaluation'' :
η_ X Y ▷ X ⊗≫ X ◁ ε_ X Y = ⊗𝟙 := by
convert evaluation_coevaluation X Y <;> simp [monoidalComp]
end ExactPairing
attribute [reassoc (attr := simp)] ExactPairing.coevaluation_evaluation
attribute [reassoc (attr := simp)] ExactPairing.evaluation_coevaluation
instance exactPairingUnit : ExactPairing (𝟙_ C) (𝟙_ C) where
coevaluation' := (ρ_ _).inv
evaluation' := (ρ_ _).hom
coevaluation_evaluation' := by rw [← id_tensorHom, ← tensorHom_id]; coherence
evaluation_coevaluation' := by rw [← id_tensorHom, ← tensorHom_id]; coherence
#align category_theory.exact_pairing_unit CategoryTheory.exactPairingUnit
/-- A class of objects which have a right dual. -/
class HasRightDual (X : C) where
/-- The right dual of the object `X`. -/
rightDual : C
[exact : ExactPairing X rightDual]
#align category_theory.has_right_dual CategoryTheory.HasRightDual
/-- A class of objects which have a left dual. -/
class HasLeftDual (Y : C) where
/-- The left dual of the object `X`. -/
leftDual : C
[exact : ExactPairing leftDual Y]
#align category_theory.has_left_dual CategoryTheory.HasLeftDual
attribute [instance] HasRightDual.exact
attribute [instance] HasLeftDual.exact
open ExactPairing HasRightDual HasLeftDual MonoidalCategory
@[inherit_doc] prefix:1024 "ᘁ" => leftDual
@[inherit_doc] postfix:1024 "ᘁ" => rightDual
instance hasRightDualUnit : HasRightDual (𝟙_ C) where
rightDual := 𝟙_ C
#align category_theory.has_right_dual_unit CategoryTheory.hasRightDualUnit
instance hasLeftDualUnit : HasLeftDual (𝟙_ C) where
leftDual := 𝟙_ C
#align category_theory.has_left_dual_unit CategoryTheory.hasLeftDualUnit
instance hasRightDualLeftDual {X : C} [HasLeftDual X] : HasRightDual ᘁX where
rightDual := X
#align category_theory.has_right_dual_left_dual CategoryTheory.hasRightDualLeftDual
instance hasLeftDualRightDual {X : C} [HasRightDual X] : HasLeftDual Xᘁ where
leftDual := X
#align category_theory.has_left_dual_right_dual CategoryTheory.hasLeftDualRightDual
@[simp]
theorem leftDual_rightDual {X : C} [HasRightDual X] : ᘁXᘁ = X :=
rfl
#align category_theory.left_dual_right_dual CategoryTheory.leftDual_rightDual
@[simp]
theorem rightDual_leftDual {X : C} [HasLeftDual X] : (ᘁX)ᘁ = X :=
rfl
#align category_theory.right_dual_left_dual CategoryTheory.rightDual_leftDual
/-- The right adjoint mate `fᘁ : Xᘁ ⟶ Yᘁ` of a morphism `f : X ⟶ Y`. -/
def rightAdjointMate {X Y : C} [HasRightDual X] [HasRightDual Y] (f : X ⟶ Y) : Yᘁ ⟶ Xᘁ :=
(ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ _ ◁ f ▷ _ ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom
#align category_theory.right_adjoint_mate CategoryTheory.rightAdjointMate
/-- The left adjoint mate `ᘁf : ᘁY ⟶ ᘁX` of a morphism `f : X ⟶ Y`. -/
def leftAdjointMate {X Y : C} [HasLeftDual X] [HasLeftDual Y] (f : X ⟶ Y) : ᘁY ⟶ ᘁX :=
(λ_ _).inv ≫ η_ (ᘁX) X ▷ _ ≫ (_ ◁ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom
#align category_theory.left_adjoint_mate CategoryTheory.leftAdjointMate
@[inherit_doc] notation f "ᘁ" => rightAdjointMate f
@[inherit_doc] notation "ᘁ" f => leftAdjointMate f
@[simp]
theorem rightAdjointMate_id {X : C} [HasRightDual X] : (𝟙 X)ᘁ = 𝟙 (Xᘁ) := by
simp [rightAdjointMate]
#align category_theory.right_adjoint_mate_id CategoryTheory.rightAdjointMate_id
@[simp]
theorem leftAdjointMate_id {X : C} [HasLeftDual X] : (ᘁ(𝟙 X)) = 𝟙 (ᘁX) := by
simp [leftAdjointMate]
#align category_theory.left_adjoint_mate_id CategoryTheory.leftAdjointMate_id
theorem rightAdjointMate_comp {X Y Z : C} [HasRightDual X] [HasRightDual Y] {f : X ⟶ Y}
{g : Xᘁ ⟶ Z} :
fᘁ ≫ g =
(ρ_ (Yᘁ)).inv ≫
_ ◁ η_ X (Xᘁ) ≫ _ ◁ (f ⊗ g) ≫ (α_ (Yᘁ) Y Z).inv ≫ ε_ Y (Yᘁ) ▷ _ ≫ (λ_ Z).hom :=
calc
_ = 𝟙 _ ⊗≫ Yᘁ ◁ η_ X Xᘁ ≫ Yᘁ ◁ f ▷ Xᘁ ⊗≫ (ε_ Y Yᘁ ▷ Xᘁ ≫ 𝟙_ C ◁ g) ⊗≫ 𝟙 _ := by
dsimp only [rightAdjointMate]; coherence
_ = _ := by
rw [← whisker_exchange, tensorHom_def]; coherence
#align category_theory.right_adjoint_mate_comp CategoryTheory.rightAdjointMate_comp
theorem leftAdjointMate_comp {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] {f : X ⟶ Y}
{g : (ᘁX) ⟶ Z} :
(ᘁf) ≫ g =
(λ_ _).inv ≫
η_ (ᘁX) X ▷ _ ≫ (g ⊗ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom :=
calc
_ = 𝟙 _ ⊗≫ η_ (ᘁX) X ▷ (ᘁY) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ⊗≫ ((ᘁX) ◁ ε_ (ᘁY) Y ≫ g ▷ 𝟙_ C) ⊗≫ 𝟙 _ := by
dsimp only [leftAdjointMate]; coherence
_ = _ := by
rw [whisker_exchange, tensorHom_def']; coherence
#align category_theory.left_adjoint_mate_comp CategoryTheory.leftAdjointMate_comp
/-- The composition of right adjoint mates is the adjoint mate of the composition. -/
@[reassoc]
theorem comp_rightAdjointMate {X Y Z : C} [HasRightDual X] [HasRightDual Y] [HasRightDual Z]
{f : X ⟶ Y} {g : Y ⟶ Z} : (f ≫ g)ᘁ = gᘁ ≫ fᘁ := by
rw [rightAdjointMate_comp]
simp only [rightAdjointMate, comp_whiskerRight]
simp only [← Category.assoc]; congr 3; simp only [Category.assoc]
simp only [← MonoidalCategory.whiskerLeft_comp]; congr 2
symm
calc
_ = 𝟙 _ ⊗≫ (η_ Y Yᘁ ▷ 𝟙_ C ≫ (Y ⊗ Yᘁ) ◁ η_ X Xᘁ) ⊗≫ Y ◁ Yᘁ ◁ f ▷ Xᘁ ⊗≫
Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by
rw [tensorHom_def']; coherence
_ = η_ X Xᘁ ⊗≫ (η_ Y Yᘁ ▷ (X ⊗ Xᘁ) ≫ (Y ⊗ Yᘁ) ◁ f ▷ Xᘁ) ⊗≫
Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by
rw [← whisker_exchange]; coherence
_ = η_ X Xᘁ ⊗≫ f ▷ Xᘁ ⊗≫ (η_ Y Yᘁ ▷ Y ⊗≫ Y ◁ ε_ Y Yᘁ) ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by
rw [← whisker_exchange]; coherence
_ = η_ X Xᘁ ≫ f ▷ Xᘁ ≫ g ▷ Xᘁ := by
rw [evaluation_coevaluation'']; coherence
#align category_theory.comp_right_adjoint_mate CategoryTheory.comp_rightAdjointMate
/-- The composition of left adjoint mates is the adjoint mate of the composition. -/
@[reassoc]
theorem comp_leftAdjointMate {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] [HasLeftDual Z] {f : X ⟶ Y}
{g : Y ⟶ Z} : (ᘁf ≫ g) = (ᘁg) ≫ ᘁf := by
rw [leftAdjointMate_comp]
simp only [leftAdjointMate, MonoidalCategory.whiskerLeft_comp]
simp only [← Category.assoc]; congr 3; simp only [Category.assoc]
simp only [← comp_whiskerRight]; congr 2
symm
calc
_ = 𝟙 _ ⊗≫ ((𝟙_ C) ◁ η_ (ᘁY) Y ≫ η_ (ᘁX) X ▷ ((ᘁY) ⊗ Y)) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ▷ Y ⊗≫
(ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by
rw [tensorHom_def]; coherence
_ = η_ (ᘁX) X ⊗≫ (((ᘁX) ⊗ X) ◁ η_ (ᘁY) Y ≫ ((ᘁX) ◁ f) ▷ ((ᘁY) ⊗ Y)) ⊗≫
(ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by
rw [whisker_exchange]; coherence
_ = η_ (ᘁX) X ⊗≫ ((ᘁX) ◁ f) ⊗≫ (ᘁX) ◁ (Y ◁ η_ (ᘁY) Y ⊗≫ ε_ (ᘁY) Y ▷ Y) ⊗≫ (ᘁX) ◁ g := by
rw [whisker_exchange]; coherence
_ = η_ (ᘁX) X ≫ (ᘁX) ◁ f ≫ (ᘁX) ◁ g := by
rw [coevaluation_evaluation'']; coherence
#align category_theory.comp_left_adjoint_mate CategoryTheory.comp_leftAdjointMate
/-- Given an exact pairing on `Y Y'`,
we get a bijection on hom-sets `(Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z)`
by "pulling the string on the left" up or down.
This gives the adjunction `tensorLeftAdjunction Y Y' : tensorLeft Y' ⊣ tensorLeft Y`.
This adjunction is often referred to as "Frobenius reciprocity" in the
fusion categories / planar algebras / subfactors literature.
-/
def tensorLeftHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z) where
toFun f := (λ_ _).inv ≫ η_ _ _ ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ f
invFun f := Y' ◁ f ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom
left_inv f := by
calc
_ = 𝟙 _ ⊗≫ Y' ◁ η_ Y Y' ▷ X ⊗≫ ((Y' ⊗ Y) ◁ f ≫ ε_ Y Y' ▷ Z) ⊗≫ 𝟙 _ := by
coherence
_ = 𝟙 _ ⊗≫ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ▷ X ⊗≫ f := by
rw [whisker_exchange]; coherence
_ = f := by
rw [coevaluation_evaluation'']; coherence
right_inv f := by
calc
_ = 𝟙 _ ⊗≫ (η_ Y Y' ▷ X ≫ (Y ⊗ Y') ◁ f) ⊗≫ Y ◁ ε_ Y Y' ▷ Z ⊗≫ 𝟙 _ := by
coherence
_ = f ⊗≫ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ▷ Z ⊗≫ 𝟙 _ := by
rw [← whisker_exchange]; coherence
_ = f := by
rw [evaluation_coevaluation'']; coherence
#align category_theory.tensor_left_hom_equiv CategoryTheory.tensorLeftHomEquiv
/-- Given an exact pairing on `Y Y'`,
we get a bijection on hom-sets `(X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y')`
by "pulling the string on the right" up or down.
-/
def tensorRightHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y') where
toFun f := (ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ f ▷ _
invFun f := f ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom
left_inv f := by
calc
_ = 𝟙 _ ⊗≫ X ◁ η_ Y Y' ▷ Y ⊗≫ (f ▷ (Y' ⊗ Y) ≫ Z ◁ ε_ Y Y') ⊗≫ 𝟙 _ := by
coherence
_ = 𝟙 _ ⊗≫ X ◁ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ⊗≫ f := by
rw [← whisker_exchange]; coherence
_ = f := by
rw [evaluation_coevaluation'']; coherence
right_inv f := by
calc
_ = 𝟙 _ ⊗≫ (X ◁ η_ Y Y' ≫ f ▷ (Y ⊗ Y')) ⊗≫ Z ◁ ε_ Y Y' ▷ Y' ⊗≫ 𝟙 _ := by
coherence
_ = f ⊗≫ Z ◁ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ⊗≫ 𝟙 _ := by
rw [whisker_exchange]; coherence
_ = f := by
rw [coevaluation_evaluation'']; coherence
#align category_theory.tensor_right_hom_equiv CategoryTheory.tensorRightHomEquiv
theorem tensorLeftHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : Y' ⊗ X ⟶ Z)
(g : Z ⟶ Z') :
(tensorLeftHomEquiv X Y Y' Z') (f ≫ g) = (tensorLeftHomEquiv X Y Y' Z) f ≫ Y ◁ g := by
simp [tensorLeftHomEquiv]
#align category_theory.tensor_left_hom_equiv_naturality CategoryTheory.tensorLeftHomEquiv_naturality
theorem tensorLeftHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X')
(g : X' ⟶ Y ⊗ Z) :
(tensorLeftHomEquiv X Y Y' Z).symm (f ≫ g) =
_ ◁ f ≫ (tensorLeftHomEquiv X' Y Y' Z).symm g := by
simp [tensorLeftHomEquiv]
#align category_theory.tensor_left_hom_equiv_symm_naturality CategoryTheory.tensorLeftHomEquiv_symm_naturality
theorem tensorRightHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⊗ Y ⟶ Z)
(g : Z ⟶ Z') :
(tensorRightHomEquiv X Y Y' Z') (f ≫ g) = (tensorRightHomEquiv X Y Y' Z) f ≫ g ▷ Y' := by
simp [tensorRightHomEquiv]
#align category_theory.tensor_right_hom_equiv_naturality CategoryTheory.tensorRightHomEquiv_naturality
theorem tensorRightHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X')
(g : X' ⟶ Z ⊗ Y') :
(tensorRightHomEquiv X Y Y' Z).symm (f ≫ g) =
f ▷ Y ≫ (tensorRightHomEquiv X' Y Y' Z).symm g := by
simp [tensorRightHomEquiv]
#align category_theory.tensor_right_hom_equiv_symm_naturality CategoryTheory.tensorRightHomEquiv_symm_naturality
/-- If `Y Y'` have an exact pairing,
then the functor `tensorLeft Y'` is left adjoint to `tensorLeft Y`.
-/
def tensorLeftAdjunction (Y Y' : C) [ExactPairing Y Y'] : tensorLeft Y' ⊣ tensorLeft Y :=
Adjunction.mkOfHomEquiv
{ homEquiv := fun X Z => tensorLeftHomEquiv X Y Y' Z
homEquiv_naturality_left_symm := fun f g => tensorLeftHomEquiv_symm_naturality f g
homEquiv_naturality_right := fun f g => tensorLeftHomEquiv_naturality f g }
#align category_theory.tensor_left_adjunction CategoryTheory.tensorLeftAdjunction
/-- If `Y Y'` have an exact pairing,
then the functor `tensor_right Y` is left adjoint to `tensor_right Y'`.
-/
def tensorRightAdjunction (Y Y' : C) [ExactPairing Y Y'] : tensorRight Y ⊣ tensorRight Y' :=
Adjunction.mkOfHomEquiv
{ homEquiv := fun X Z => tensorRightHomEquiv X Y Y' Z
homEquiv_naturality_left_symm := fun f g => tensorRightHomEquiv_symm_naturality f g
homEquiv_naturality_right := fun f g => tensorRightHomEquiv_naturality f g }
#align category_theory.tensor_right_adjunction CategoryTheory.tensorRightAdjunction
/--
If `Y` has a left dual `ᘁY`, then it is a closed object, with the internal hom functor `Y ⟶[C] -`
given by left tensoring by `ᘁY`.
This has to be a definition rather than an instance to avoid diamonds, for example between
`category_theory.monoidal_closed.functor_closed` and
`CategoryTheory.Monoidal.functorHasLeftDual`. Moreover, in concrete applications there is often
a more useful definition of the internal hom object than `ᘁY ⊗ X`, in which case the closed
structure shouldn't come from `has_left_dual` (e.g. in the category `FinVect k`, it is more
convenient to define the internal hom as `Y →ₗ[k] X` rather than `ᘁY ⊗ X` even though these are
naturally isomorphic).
-/
def closedOfHasLeftDual (Y : C) [HasLeftDual Y] : Closed Y where
adj := tensorLeftAdjunction (ᘁY) Y
#align category_theory.closed_of_has_left_dual CategoryTheory.closedOfHasLeftDual
/-- `tensorLeftHomEquiv` commutes with tensoring on the right -/
theorem tensorLeftHomEquiv_tensor {X X' Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⟶ Y ⊗ Z)
(g : X' ⟶ Z') :
(tensorLeftHomEquiv (X ⊗ X') Y Y' (Z ⊗ Z')).symm ((f ⊗ g) ≫ (α_ _ _ _).hom) =
(α_ _ _ _).inv ≫ ((tensorLeftHomEquiv X Y Y' Z).symm f ⊗ g) := by
simp [tensorLeftHomEquiv, tensorHom_def']
#align category_theory.tensor_left_hom_equiv_tensor CategoryTheory.tensorLeftHomEquiv_tensor
/-- `tensorRightHomEquiv` commutes with tensoring on the left -/
theorem tensorRightHomEquiv_tensor {X X' Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⟶ Z ⊗ Y')
(g : X' ⟶ Z') :
(tensorRightHomEquiv (X' ⊗ X) Y Y' (Z' ⊗ Z)).symm ((g ⊗ f) ≫ (α_ _ _ _).inv) =
(α_ _ _ _).hom ≫ (g ⊗ (tensorRightHomEquiv X Y Y' Z).symm f) := by
simp [tensorRightHomEquiv, tensorHom_def]
#align category_theory.tensor_right_hom_equiv_tensor CategoryTheory.tensorRightHomEquiv_tensor
@[simp]
theorem tensorLeftHomEquiv_symm_coevaluation_comp_whiskerLeft {Y Y' Z : C} [ExactPairing Y Y']
(f : Y' ⟶ Z) : (tensorLeftHomEquiv _ _ _ _).symm (η_ _ _ ≫ Y ◁ f) = (ρ_ _).hom ≫ f := by
calc
_ = Y' ◁ η_ Y Y' ⊗≫ ((Y' ⊗ Y) ◁ f ≫ ε_ Y Y' ▷ Z) ⊗≫ 𝟙 _ := by
dsimp [tensorLeftHomEquiv]; coherence
_ = (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ⊗≫ f := by
rw [whisker_exchange]; coherence
_ = _ := by rw [coevaluation_evaluation'']; coherence
#align category_theory.tensor_left_hom_equiv_symm_coevaluation_comp_id_tensor CategoryTheory.tensorLeftHomEquiv_symm_coevaluation_comp_whiskerLeft
@[simp]
theorem tensorLeftHomEquiv_symm_coevaluation_comp_whiskerRight {X Y : C} [HasRightDual X]
[HasRightDual Y] (f : X ⟶ Y) :
(tensorLeftHomEquiv _ _ _ _).symm (η_ _ _ ≫ f ▷ (Xᘁ)) = (ρ_ _).hom ≫ fᘁ := by
dsimp [tensorLeftHomEquiv, rightAdjointMate]
simp
#align category_theory.tensor_left_hom_equiv_symm_coevaluation_comp_tensor_id CategoryTheory.tensorLeftHomEquiv_symm_coevaluation_comp_whiskerRight
@[simp]
theorem tensorRightHomEquiv_symm_coevaluation_comp_whiskerLeft {X Y : C} [HasLeftDual X]
[HasLeftDual Y] (f : X ⟶ Y) :
(tensorRightHomEquiv _ (ᘁY) _ _).symm (η_ (ᘁX) X ≫ (ᘁX) ◁ f) = (λ_ _).hom ≫ ᘁf := by
dsimp [tensorRightHomEquiv, leftAdjointMate]
simp
#align category_theory.tensor_right_hom_equiv_symm_coevaluation_comp_id_tensor CategoryTheory.tensorRightHomEquiv_symm_coevaluation_comp_whiskerLeft
@[simp]
theorem tensorRightHomEquiv_symm_coevaluation_comp_whiskerRight {Y Y' Z : C} [ExactPairing Y Y']
(f : Y ⟶ Z) : (tensorRightHomEquiv _ Y _ _).symm (η_ Y Y' ≫ f ▷ Y') = (λ_ _).hom ≫ f :=
calc
_ = η_ Y Y' ▷ Y ⊗≫ (f ▷ (Y' ⊗ Y) ≫ Z ◁ ε_ Y Y') ⊗≫ 𝟙 _ := by
dsimp [tensorRightHomEquiv]; coherence
_ = (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ⊗≫ f := by
rw [← whisker_exchange]; coherence
_ = _ := by
rw [evaluation_coevaluation'']; coherence
#align category_theory.tensor_right_hom_equiv_symm_coevaluation_comp_tensor_id CategoryTheory.tensorRightHomEquiv_symm_coevaluation_comp_whiskerRight
@[simp]
theorem tensorLeftHomEquiv_whiskerLeft_comp_evaluation {Y Z : C} [HasLeftDual Z] (f : Y ⟶ ᘁZ) :
(tensorLeftHomEquiv _ _ _ _) (Z ◁ f ≫ ε_ _ _) = f ≫ (ρ_ _).inv :=
calc
_ = 𝟙 _ ⊗≫ (η_ (ᘁZ) Z ▷ Y ≫ ((ᘁZ) ⊗ Z) ◁ f) ⊗≫ (ᘁZ) ◁ ε_ (ᘁZ) Z := by
dsimp [tensorLeftHomEquiv]; coherence
_ = f ⊗≫ (η_ (ᘁZ) Z ▷ (ᘁZ) ⊗≫ (ᘁZ) ◁ ε_ (ᘁZ) Z) := by
rw [← whisker_exchange]; coherence
_ = _ := by
rw [evaluation_coevaluation'']; coherence
#align category_theory.tensor_left_hom_equiv_id_tensor_comp_evaluation CategoryTheory.tensorLeftHomEquiv_whiskerLeft_comp_evaluation
@[simp]
| Mathlib/CategoryTheory/Monoidal/Rigid/Basic.lean | 462 | 465 | theorem tensorLeftHomEquiv_whiskerRight_comp_evaluation {X Y : C} [HasLeftDual X] [HasLeftDual Y]
(f : X ⟶ Y) : (tensorLeftHomEquiv _ _ _ _) (f ▷ _ ≫ ε_ _ _) = (ᘁf) ≫ (ρ_ _).inv := by |
dsimp [tensorLeftHomEquiv, leftAdjointMate]
simp
|
/-
Copyright (c) 2021 Benjamin Davidson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Benjamin Davidson
-/
import Mathlib.Algebra.Field.Opposite
import Mathlib.Algebra.Group.Subgroup.ZPowers
import Mathlib.Algebra.Group.Submonoid.Membership
import Mathlib.Algebra.Ring.NegOnePow
import Mathlib.Algebra.Order.Archimedean
import Mathlib.GroupTheory.Coset
#align_import algebra.periodic from "leanprover-community/mathlib"@"30413fc89f202a090a54d78e540963ed3de0056e"
/-!
# Periodicity
In this file we define and then prove facts about periodic and antiperiodic functions.
## Main definitions
* `Function.Periodic`: A function `f` is *periodic* if `∀ x, f (x + c) = f x`.
`f` is referred to as periodic with period `c` or `c`-periodic.
* `Function.Antiperiodic`: A function `f` is *antiperiodic* if `∀ x, f (x + c) = -f x`.
`f` is referred to as antiperiodic with antiperiod `c` or `c`-antiperiodic.
Note that any `c`-antiperiodic function will necessarily also be `2 • c`-periodic.
## Tags
period, periodic, periodicity, antiperiodic
-/
variable {α β γ : Type*} {f g : α → β} {c c₁ c₂ x : α}
open Set
namespace Function
/-! ### Periodicity -/
/-- A function `f` is said to be `Periodic` with period `c` if for all `x`, `f (x + c) = f x`. -/
@[simp]
def Periodic [Add α] (f : α → β) (c : α) : Prop :=
∀ x : α, f (x + c) = f x
#align function.periodic Function.Periodic
protected theorem Periodic.funext [Add α] (h : Periodic f c) : (fun x => f (x + c)) = f :=
funext h
#align function.periodic.funext Function.Periodic.funext
protected theorem Periodic.comp [Add α] (h : Periodic f c) (g : β → γ) : Periodic (g ∘ f) c := by
simp_all
#align function.periodic.comp Function.Periodic.comp
theorem Periodic.comp_addHom [Add α] [Add γ] (h : Periodic f c) (g : AddHom γ α) (g_inv : α → γ)
(hg : RightInverse g_inv g) : Periodic (f ∘ g) (g_inv c) := fun x => by
simp only [hg c, h (g x), map_add, comp_apply]
#align function.periodic.comp_add_hom Function.Periodic.comp_addHom
@[to_additive]
protected theorem Periodic.mul [Add α] [Mul β] (hf : Periodic f c) (hg : Periodic g c) :
Periodic (f * g) c := by simp_all
#align function.periodic.mul Function.Periodic.mul
#align function.periodic.add Function.Periodic.add
@[to_additive]
protected theorem Periodic.div [Add α] [Div β] (hf : Periodic f c) (hg : Periodic g c) :
Periodic (f / g) c := by simp_all
#align function.periodic.div Function.Periodic.div
#align function.periodic.sub Function.Periodic.sub
@[to_additive]
theorem _root_.List.periodic_prod [Add α] [Monoid β] (l : List (α → β))
(hl : ∀ f ∈ l, Periodic f c) : Periodic l.prod c := by
induction' l with g l ih hl
· simp
· rw [List.forall_mem_cons] at hl
simpa only [List.prod_cons] using hl.1.mul (ih hl.2)
#align list.periodic_prod List.periodic_prod
#align list.periodic_sum List.periodic_sum
@[to_additive]
theorem _root_.Multiset.periodic_prod [Add α] [CommMonoid β] (s : Multiset (α → β))
(hs : ∀ f ∈ s, Periodic f c) : Periodic s.prod c :=
(s.prod_toList ▸ s.toList.periodic_prod) fun f hf => hs f <| Multiset.mem_toList.mp hf
#align multiset.periodic_prod Multiset.periodic_prod
#align multiset.periodic_sum Multiset.periodic_sum
@[to_additive]
theorem _root_.Finset.periodic_prod [Add α] [CommMonoid β] {ι : Type*} {f : ι → α → β}
(s : Finset ι) (hs : ∀ i ∈ s, Periodic (f i) c) : Periodic (∏ i ∈ s, f i) c :=
s.prod_to_list f ▸ (s.toList.map f).periodic_prod (by simpa [-Periodic] )
#align finset.periodic_prod Finset.periodic_prod
#align finset.periodic_sum Finset.periodic_sum
@[to_additive]
protected theorem Periodic.smul [Add α] [SMul γ β] (h : Periodic f c) (a : γ) :
Periodic (a • f) c := by simp_all
#align function.periodic.smul Function.Periodic.smul
#align function.periodic.vadd Function.Periodic.vadd
protected theorem Periodic.const_smul [AddMonoid α] [Group γ] [DistribMulAction γ α]
(h : Periodic f c) (a : γ) : Periodic (fun x => f (a • x)) (a⁻¹ • c) := fun x => by
simpa only [smul_add, smul_inv_smul] using h (a • x)
#align function.periodic.const_smul Function.Periodic.const_smul
protected theorem Periodic.const_smul₀ [AddCommMonoid α] [DivisionSemiring γ] [Module γ α]
(h : Periodic f c) (a : γ) : Periodic (fun x => f (a • x)) (a⁻¹ • c) := fun x => by
by_cases ha : a = 0
· simp only [ha, zero_smul]
· simpa only [smul_add, smul_inv_smul₀ ha] using h (a • x)
#align function.periodic.const_smul₀ Function.Periodic.const_smul₀
protected theorem Periodic.const_mul [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (a * x)) (a⁻¹ * c) :=
Periodic.const_smul₀ h a
#align function.periodic.const_mul Function.Periodic.const_mul
theorem Periodic.const_inv_smul [AddMonoid α] [Group γ] [DistribMulAction γ α] (h : Periodic f c)
(a : γ) : Periodic (fun x => f (a⁻¹ • x)) (a • c) := by
simpa only [inv_inv] using h.const_smul a⁻¹
#align function.periodic.const_inv_smul Function.Periodic.const_inv_smul
theorem Periodic.const_inv_smul₀ [AddCommMonoid α] [DivisionSemiring γ] [Module γ α]
(h : Periodic f c) (a : γ) : Periodic (fun x => f (a⁻¹ • x)) (a • c) := by
simpa only [inv_inv] using h.const_smul₀ a⁻¹
#align function.periodic.const_inv_smul₀ Function.Periodic.const_inv_smul₀
theorem Periodic.const_inv_mul [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (a⁻¹ * x)) (a * c) :=
h.const_inv_smul₀ a
#align function.periodic.const_inv_mul Function.Periodic.const_inv_mul
theorem Periodic.mul_const [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x * a)) (c * a⁻¹) :=
h.const_smul₀ (MulOpposite.op a)
#align function.periodic.mul_const Function.Periodic.mul_const
theorem Periodic.mul_const' [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x * a)) (c / a) := by simpa only [div_eq_mul_inv] using h.mul_const a
#align function.periodic.mul_const' Function.Periodic.mul_const'
theorem Periodic.mul_const_inv [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x * a⁻¹)) (c * a) :=
h.const_inv_smul₀ (MulOpposite.op a)
#align function.periodic.mul_const_inv Function.Periodic.mul_const_inv
theorem Periodic.div_const [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x / a)) (c * a) := by simpa only [div_eq_mul_inv] using h.mul_const_inv a
#align function.periodic.div_const Function.Periodic.div_const
theorem Periodic.add_period [AddSemigroup α] (h1 : Periodic f c₁) (h2 : Periodic f c₂) :
Periodic f (c₁ + c₂) := by simp_all [← add_assoc]
#align function.periodic.add_period Function.Periodic.add_period
theorem Periodic.sub_eq [AddGroup α] (h : Periodic f c) (x : α) : f (x - c) = f x := by
simpa only [sub_add_cancel] using (h (x - c)).symm
#align function.periodic.sub_eq Function.Periodic.sub_eq
theorem Periodic.sub_eq' [AddCommGroup α] (h : Periodic f c) : f (c - x) = f (-x) := by
simpa only [sub_eq_neg_add] using h (-x)
#align function.periodic.sub_eq' Function.Periodic.sub_eq'
protected theorem Periodic.neg [AddGroup α] (h : Periodic f c) : Periodic f (-c) := by
simpa only [sub_eq_add_neg, Periodic] using h.sub_eq
#align function.periodic.neg Function.Periodic.neg
theorem Periodic.sub_period [AddGroup α] (h1 : Periodic f c₁) (h2 : Periodic f c₂) :
Periodic f (c₁ - c₂) := fun x => by
rw [sub_eq_add_neg, ← add_assoc, h2.neg, h1]
#align function.periodic.sub_period Function.Periodic.sub_period
theorem Periodic.const_add [AddSemigroup α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (a + x)) c := fun x => by simpa [add_assoc] using h (a + x)
#align function.periodic.const_add Function.Periodic.const_add
theorem Periodic.add_const [AddCommSemigroup α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x + a)) c := fun x => by
simpa only [add_right_comm] using h (x + a)
#align function.periodic.add_const Function.Periodic.add_const
theorem Periodic.const_sub [AddCommGroup α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (a - x)) c := fun x => by
simp only [← sub_sub, h.sub_eq]
#align function.periodic.const_sub Function.Periodic.const_sub
theorem Periodic.sub_const [AddCommGroup α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x - a)) c := by
simpa only [sub_eq_add_neg] using h.add_const (-a)
#align function.periodic.sub_const Function.Periodic.sub_const
theorem Periodic.nsmul [AddMonoid α] (h : Periodic f c) (n : ℕ) : Periodic f (n • c) := by
induction n <;> simp_all [Nat.succ_eq_add_one, add_nsmul, ← add_assoc, zero_nsmul]
#align function.periodic.nsmul Function.Periodic.nsmul
theorem Periodic.nat_mul [Semiring α] (h : Periodic f c) (n : ℕ) : Periodic f (n * c) := by
simpa only [nsmul_eq_mul] using h.nsmul n
#align function.periodic.nat_mul Function.Periodic.nat_mul
theorem Periodic.neg_nsmul [AddGroup α] (h : Periodic f c) (n : ℕ) : Periodic f (-(n • c)) :=
(h.nsmul n).neg
#align function.periodic.neg_nsmul Function.Periodic.neg_nsmul
theorem Periodic.neg_nat_mul [Ring α] (h : Periodic f c) (n : ℕ) : Periodic f (-(n * c)) :=
(h.nat_mul n).neg
#align function.periodic.neg_nat_mul Function.Periodic.neg_nat_mul
theorem Periodic.sub_nsmul_eq [AddGroup α] (h : Periodic f c) (n : ℕ) : f (x - n • c) = f x := by
simpa only [sub_eq_add_neg] using h.neg_nsmul n x
#align function.periodic.sub_nsmul_eq Function.Periodic.sub_nsmul_eq
theorem Periodic.sub_nat_mul_eq [Ring α] (h : Periodic f c) (n : ℕ) : f (x - n * c) = f x := by
simpa only [nsmul_eq_mul] using h.sub_nsmul_eq n
#align function.periodic.sub_nat_mul_eq Function.Periodic.sub_nat_mul_eq
theorem Periodic.nsmul_sub_eq [AddCommGroup α] (h : Periodic f c) (n : ℕ) :
f (n • c - x) = f (-x) :=
(h.nsmul n).sub_eq'
#align function.periodic.nsmul_sub_eq Function.Periodic.nsmul_sub_eq
theorem Periodic.nat_mul_sub_eq [Ring α] (h : Periodic f c) (n : ℕ) : f (n * c - x) = f (-x) := by
simpa only [sub_eq_neg_add] using h.nat_mul n (-x)
#align function.periodic.nat_mul_sub_eq Function.Periodic.nat_mul_sub_eq
protected theorem Periodic.zsmul [AddGroup α] (h : Periodic f c) (n : ℤ) : Periodic f (n • c) := by
cases' n with n n
· simpa only [Int.ofNat_eq_coe, natCast_zsmul] using h.nsmul n
· simpa only [negSucc_zsmul] using (h.nsmul (n + 1)).neg
#align function.periodic.zsmul Function.Periodic.zsmul
protected theorem Periodic.int_mul [Ring α] (h : Periodic f c) (n : ℤ) : Periodic f (n * c) := by
simpa only [zsmul_eq_mul] using h.zsmul n
#align function.periodic.int_mul Function.Periodic.int_mul
theorem Periodic.sub_zsmul_eq [AddGroup α] (h : Periodic f c) (n : ℤ) : f (x - n • c) = f x :=
(h.zsmul n).sub_eq x
#align function.periodic.sub_zsmul_eq Function.Periodic.sub_zsmul_eq
theorem Periodic.sub_int_mul_eq [Ring α] (h : Periodic f c) (n : ℤ) : f (x - n * c) = f x :=
(h.int_mul n).sub_eq x
#align function.periodic.sub_int_mul_eq Function.Periodic.sub_int_mul_eq
theorem Periodic.zsmul_sub_eq [AddCommGroup α] (h : Periodic f c) (n : ℤ) :
f (n • c - x) = f (-x) :=
(h.zsmul _).sub_eq'
#align function.periodic.zsmul_sub_eq Function.Periodic.zsmul_sub_eq
theorem Periodic.int_mul_sub_eq [Ring α] (h : Periodic f c) (n : ℤ) : f (n * c - x) = f (-x) :=
(h.int_mul _).sub_eq'
#align function.periodic.int_mul_sub_eq Function.Periodic.int_mul_sub_eq
protected theorem Periodic.eq [AddZeroClass α] (h : Periodic f c) : f c = f 0 := by
simpa only [zero_add] using h 0
#align function.periodic.eq Function.Periodic.eq
protected theorem Periodic.neg_eq [AddGroup α] (h : Periodic f c) : f (-c) = f 0 :=
h.neg.eq
#align function.periodic.neg_eq Function.Periodic.neg_eq
protected theorem Periodic.nsmul_eq [AddMonoid α] (h : Periodic f c) (n : ℕ) : f (n • c) = f 0 :=
(h.nsmul n).eq
#align function.periodic.nsmul_eq Function.Periodic.nsmul_eq
theorem Periodic.nat_mul_eq [Semiring α] (h : Periodic f c) (n : ℕ) : f (n * c) = f 0 :=
(h.nat_mul n).eq
#align function.periodic.nat_mul_eq Function.Periodic.nat_mul_eq
theorem Periodic.zsmul_eq [AddGroup α] (h : Periodic f c) (n : ℤ) : f (n • c) = f 0 :=
(h.zsmul n).eq
#align function.periodic.zsmul_eq Function.Periodic.zsmul_eq
theorem Periodic.int_mul_eq [Ring α] (h : Periodic f c) (n : ℤ) : f (n * c) = f 0 :=
(h.int_mul n).eq
#align function.periodic.int_mul_eq Function.Periodic.int_mul_eq
/-- If a function `f` is `Periodic` with positive period `c`, then for all `x` there exists some
`y ∈ Ico 0 c` such that `f x = f y`. -/
theorem Periodic.exists_mem_Ico₀ [LinearOrderedAddCommGroup α] [Archimedean α] (h : Periodic f c)
(hc : 0 < c) (x) : ∃ y ∈ Ico 0 c, f x = f y :=
let ⟨n, H, _⟩ := existsUnique_zsmul_near_of_pos' hc x
⟨x - n • c, H, (h.sub_zsmul_eq n).symm⟩
#align function.periodic.exists_mem_Ico₀ Function.Periodic.exists_mem_Ico₀
/-- If a function `f` is `Periodic` with positive period `c`, then for all `x` there exists some
`y ∈ Ico a (a + c)` such that `f x = f y`. -/
theorem Periodic.exists_mem_Ico [LinearOrderedAddCommGroup α] [Archimedean α] (h : Periodic f c)
(hc : 0 < c) (x a) : ∃ y ∈ Ico a (a + c), f x = f y :=
let ⟨n, H, _⟩ := existsUnique_add_zsmul_mem_Ico hc x a
⟨x + n • c, H, (h.zsmul n x).symm⟩
#align function.periodic.exists_mem_Ico Function.Periodic.exists_mem_Ico
/-- If a function `f` is `Periodic` with positive period `c`, then for all `x` there exists some
`y ∈ Ioc a (a + c)` such that `f x = f y`. -/
theorem Periodic.exists_mem_Ioc [LinearOrderedAddCommGroup α] [Archimedean α] (h : Periodic f c)
(hc : 0 < c) (x a) : ∃ y ∈ Ioc a (a + c), f x = f y :=
let ⟨n, H, _⟩ := existsUnique_add_zsmul_mem_Ioc hc x a
⟨x + n • c, H, (h.zsmul n x).symm⟩
#align function.periodic.exists_mem_Ioc Function.Periodic.exists_mem_Ioc
theorem Periodic.image_Ioc [LinearOrderedAddCommGroup α] [Archimedean α] (h : Periodic f c)
(hc : 0 < c) (a : α) : f '' Ioc a (a + c) = range f :=
(image_subset_range _ _).antisymm <| range_subset_iff.2 fun x =>
let ⟨y, hy, hyx⟩ := h.exists_mem_Ioc hc x a
⟨y, hy, hyx.symm⟩
#align function.periodic.image_Ioc Function.Periodic.image_Ioc
theorem Periodic.image_Icc [LinearOrderedAddCommGroup α] [Archimedean α] (h : Periodic f c)
(hc : 0 < c) (a : α) : f '' Icc a (a + c) = range f :=
(image_subset_range _ _).antisymm <| h.image_Ioc hc a ▸ image_subset _ Ioc_subset_Icc_self
theorem Periodic.image_uIcc [LinearOrderedAddCommGroup α] [Archimedean α] (h : Periodic f c)
(hc : c ≠ 0) (a : α) : f '' uIcc a (a + c) = range f := by
cases hc.lt_or_lt with
| inl hc =>
rw [uIcc_of_ge (add_le_of_nonpos_right hc.le), ← h.neg.image_Icc (neg_pos.2 hc) (a + c),
add_neg_cancel_right]
| inr hc => rw [uIcc_of_le (le_add_of_nonneg_right hc.le), h.image_Icc hc]
theorem periodic_with_period_zero [AddZeroClass α] (f : α → β) : Periodic f 0 := fun x => by
rw [add_zero]
#align function.periodic_with_period_zero Function.periodic_with_period_zero
theorem Periodic.map_vadd_zmultiples [AddCommGroup α] (hf : Periodic f c)
(a : AddSubgroup.zmultiples c) (x : α) : f (a +ᵥ x) = f x := by
rcases a with ⟨_, m, rfl⟩
simp [AddSubgroup.vadd_def, add_comm _ x, hf.zsmul m x]
#align function.periodic.map_vadd_zmultiples Function.Periodic.map_vadd_zmultiples
theorem Periodic.map_vadd_multiples [AddCommMonoid α] (hf : Periodic f c)
(a : AddSubmonoid.multiples c) (x : α) : f (a +ᵥ x) = f x := by
rcases a with ⟨_, m, rfl⟩
simp [AddSubmonoid.vadd_def, add_comm _ x, hf.nsmul m x]
#align function.periodic.map_vadd_multiples Function.Periodic.map_vadd_multiples
/-- Lift a periodic function to a function from the quotient group. -/
def Periodic.lift [AddGroup α] (h : Periodic f c) (x : α ⧸ AddSubgroup.zmultiples c) : β :=
Quotient.liftOn' x f fun a b h' => by
rw [QuotientAddGroup.leftRel_apply] at h'
obtain ⟨k, hk⟩ := h'
exact (h.zsmul k _).symm.trans (congr_arg f (add_eq_of_eq_neg_add hk))
#align function.periodic.lift Function.Periodic.lift
@[simp]
theorem Periodic.lift_coe [AddGroup α] (h : Periodic f c) (a : α) :
h.lift (a : α ⧸ AddSubgroup.zmultiples c) = f a :=
rfl
#align function.periodic.lift_coe Function.Periodic.lift_coe
/-- A periodic function `f : R → X` on a semiring (or, more generally, `AddZeroClass`)
of non-zero period is not injective. -/
lemma Periodic.not_injective {R X : Type*} [AddZeroClass R] {f : R → X} {c : R}
(hf : Periodic f c) (hc : c ≠ 0) : ¬ Injective f := fun h ↦ hc <| h hf.eq
/-! ### Antiperiodicity -/
/-- A function `f` is said to be `antiperiodic` with antiperiod `c` if for all `x`,
`f (x + c) = -f x`. -/
@[simp]
def Antiperiodic [Add α] [Neg β] (f : α → β) (c : α) : Prop :=
∀ x : α, f (x + c) = -f x
#align function.antiperiodic Function.Antiperiodic
protected theorem Antiperiodic.funext [Add α] [Neg β] (h : Antiperiodic f c) :
(fun x => f (x + c)) = -f :=
funext h
#align function.antiperiodic.funext Function.Antiperiodic.funext
protected theorem Antiperiodic.funext' [Add α] [InvolutiveNeg β] (h : Antiperiodic f c) :
(fun x => -f (x + c)) = f :=
neg_eq_iff_eq_neg.mpr h.funext
#align function.antiperiodic.funext' Function.Antiperiodic.funext'
/-- If a function is `antiperiodic` with antiperiod `c`, then it is also `Periodic` with period
`2 • c`. -/
protected theorem Antiperiodic.periodic [AddMonoid α] [InvolutiveNeg β]
(h : Antiperiodic f c) : Periodic f (2 • c) := by simp [two_nsmul, ← add_assoc, h _]
/-- If a function is `antiperiodic` with antiperiod `c`, then it is also `Periodic` with period
`2 * c`. -/
protected theorem Antiperiodic.periodic_two_mul [Semiring α] [InvolutiveNeg β]
(h : Antiperiodic f c) : Periodic f (2 * c) := nsmul_eq_mul 2 c ▸ h.periodic
#align function.antiperiodic.periodic Function.Antiperiodic.periodic_two_mul
protected theorem Antiperiodic.eq [AddZeroClass α] [Neg β] (h : Antiperiodic f c) : f c = -f 0 := by
simpa only [zero_add] using h 0
#align function.antiperiodic.eq Function.Antiperiodic.eq
theorem Antiperiodic.even_nsmul_periodic [AddMonoid α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℕ) : Periodic f ((2 * n) • c) := mul_nsmul c 2 n ▸ h.periodic.nsmul n
theorem Antiperiodic.nat_even_mul_periodic [Semiring α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℕ) : Periodic f (n * (2 * c)) :=
h.periodic_two_mul.nat_mul n
#align function.antiperiodic.nat_even_mul_periodic Function.Antiperiodic.nat_even_mul_periodic
theorem Antiperiodic.odd_nsmul_antiperiodic [AddMonoid α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℕ) : Antiperiodic f ((2 * n + 1) • c) := fun x => by
rw [add_nsmul, one_nsmul, ← add_assoc, h, h.even_nsmul_periodic]
theorem Antiperiodic.nat_odd_mul_antiperiodic [Semiring α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℕ) : Antiperiodic f (n * (2 * c) + c) := fun x => by
rw [← add_assoc, h, h.nat_even_mul_periodic]
#align function.antiperiodic.nat_odd_mul_antiperiodic Function.Antiperiodic.nat_odd_mul_antiperiodic
theorem Antiperiodic.even_zsmul_periodic [AddGroup α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℤ) : Periodic f ((2 * n) • c) := by
rw [mul_comm, mul_zsmul, two_zsmul, ← two_nsmul]
exact h.periodic.zsmul n
theorem Antiperiodic.int_even_mul_periodic [Ring α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℤ) : Periodic f (n * (2 * c)) :=
h.periodic_two_mul.int_mul n
#align function.antiperiodic.int_even_mul_periodic Function.Antiperiodic.int_even_mul_periodic
theorem Antiperiodic.odd_zsmul_antiperiodic [AddGroup α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℤ) : Antiperiodic f ((2 * n + 1) • c) := by
intro x
rw [add_zsmul, one_zsmul, ← add_assoc, h, h.even_zsmul_periodic]
theorem Antiperiodic.int_odd_mul_antiperiodic [Ring α] [InvolutiveNeg β] (h : Antiperiodic f c)
(n : ℤ) : Antiperiodic f (n * (2 * c) + c) := fun x => by
rw [← add_assoc, h, h.int_even_mul_periodic]
#align function.antiperiodic.int_odd_mul_antiperiodic Function.Antiperiodic.int_odd_mul_antiperiodic
theorem Antiperiodic.sub_eq [AddGroup α] [InvolutiveNeg β] (h : Antiperiodic f c) (x : α) :
f (x - c) = -f x := by simp only [← neg_eq_iff_eq_neg, ← h (x - c), sub_add_cancel]
#align function.antiperiodic.sub_eq Function.Antiperiodic.sub_eq
theorem Antiperiodic.sub_eq' [AddCommGroup α] [Neg β] (h : Antiperiodic f c) :
f (c - x) = -f (-x) := by simpa only [sub_eq_neg_add] using h (-x)
#align function.antiperiodic.sub_eq' Function.Antiperiodic.sub_eq'
protected theorem Antiperiodic.neg [AddGroup α] [InvolutiveNeg β] (h : Antiperiodic f c) :
Antiperiodic f (-c) := by simpa only [sub_eq_add_neg, Antiperiodic] using h.sub_eq
#align function.antiperiodic.neg Function.Antiperiodic.neg
theorem Antiperiodic.neg_eq [AddGroup α] [InvolutiveNeg β] (h : Antiperiodic f c) :
f (-c) = -f 0 := by
simpa only [zero_add] using h.neg 0
#align function.antiperiodic.neg_eq Function.Antiperiodic.neg_eq
theorem Antiperiodic.nat_mul_eq_of_eq_zero [Semiring α] [NegZeroClass β] (h : Antiperiodic f c)
(hi : f 0 = 0) : ∀ n : ℕ, f (n * c) = 0
| 0 => by rwa [Nat.cast_zero, zero_mul]
| n + 1 => by simp [add_mul, h _, Antiperiodic.nat_mul_eq_of_eq_zero h hi n]
#align function.antiperiodic.nat_mul_eq_of_eq_zero Function.Antiperiodic.nat_mul_eq_of_eq_zero
theorem Antiperiodic.int_mul_eq_of_eq_zero [Ring α] [SubtractionMonoid β] (h : Antiperiodic f c)
(hi : f 0 = 0) : ∀ n : ℤ, f (n * c) = 0
| (n : ℕ) => by rw [Int.cast_natCast, h.nat_mul_eq_of_eq_zero hi n]
| .negSucc n => by rw [Int.cast_negSucc, neg_mul, ← mul_neg, h.neg.nat_mul_eq_of_eq_zero hi]
#align function.antiperiodic.int_mul_eq_of_eq_zero Function.Antiperiodic.int_mul_eq_of_eq_zero
theorem Antiperiodic.add_zsmul_eq [AddGroup α] [AddGroup β] (h : Antiperiodic f c) (n : ℤ) :
f (x + n • c) = (n.negOnePow : ℤ) • f x := by
rcases Int.even_or_odd' n with ⟨k, rfl | rfl⟩
· rw [h.even_zsmul_periodic, Int.negOnePow_two_mul, Units.val_one, one_zsmul]
· rw [h.odd_zsmul_antiperiodic, Int.negOnePow_two_mul_add_one, Units.val_neg,
Units.val_one, neg_zsmul, one_zsmul]
theorem Antiperiodic.sub_zsmul_eq [AddGroup α] [AddGroup β] (h : Antiperiodic f c) (n : ℤ) :
f (x - n • c) = (n.negOnePow : ℤ) • f x := by
simpa only [sub_eq_add_neg, neg_zsmul, Int.negOnePow_neg] using h.add_zsmul_eq (-n)
theorem Antiperiodic.zsmul_sub_eq [AddCommGroup α] [AddGroup β] (h : Antiperiodic f c) (n : ℤ) :
f (n • c - x) = (n.negOnePow : ℤ) • f (-x) := by
rw [sub_eq_add_neg, add_comm]
exact h.add_zsmul_eq n
theorem Antiperiodic.add_int_mul_eq [Ring α] [Ring β] (h : Antiperiodic f c) (n : ℤ) :
f (x + n * c) = (n.negOnePow : ℤ) * f x := by simpa only [zsmul_eq_mul] using h.add_zsmul_eq n
theorem Antiperiodic.sub_int_mul_eq [Ring α] [Ring β] (h : Antiperiodic f c) (n : ℤ) :
f (x - n * c) = (n.negOnePow : ℤ) * f x := by simpa only [zsmul_eq_mul] using h.sub_zsmul_eq n
theorem Antiperiodic.int_mul_sub_eq [Ring α] [Ring β] (h : Antiperiodic f c) (n : ℤ) :
f (n * c - x) = (n.negOnePow : ℤ) * f (-x) := by
simpa only [zsmul_eq_mul] using h.zsmul_sub_eq n
theorem Antiperiodic.add_nsmul_eq [AddMonoid α] [AddGroup β] (h : Antiperiodic f c) (n : ℕ) :
f (x + n • c) = (-1) ^ n • f x := by
rcases Nat.even_or_odd' n with ⟨k, rfl | rfl⟩
· rw [h.even_nsmul_periodic, pow_mul, (by norm_num : (-1) ^ 2 = 1), one_pow, one_zsmul]
· rw [h.odd_nsmul_antiperiodic, pow_add, pow_mul, (by norm_num : (-1) ^ 2 = 1), one_pow,
pow_one, one_mul, neg_zsmul, one_zsmul]
theorem Antiperiodic.sub_nsmul_eq [AddGroup α] [AddGroup β] (h : Antiperiodic f c) (n : ℕ) :
f (x - n • c) = (-1) ^ n • f x := by
simpa only [Int.reduceNeg, natCast_zsmul] using h.sub_zsmul_eq n
theorem Antiperiodic.nsmul_sub_eq [AddCommGroup α] [AddGroup β] (h : Antiperiodic f c) (n : ℕ) :
f (n • c - x) = (-1) ^ n • f (-x) := by
simpa only [Int.reduceNeg, natCast_zsmul] using h.zsmul_sub_eq n
theorem Antiperiodic.add_nat_mul_eq [Semiring α] [Ring β] (h : Antiperiodic f c) (n : ℕ) :
f (x + n * c) = (-1) ^ n * f x := by
simpa only [nsmul_eq_mul, zsmul_eq_mul, Int.cast_pow, Int.cast_neg,
Int.cast_one] using h.add_nsmul_eq n
theorem Antiperiodic.sub_nat_mul_eq [Ring α] [Ring β] (h : Antiperiodic f c) (n : ℕ) :
f (x - n * c) = (-1) ^ n * f x := by
simpa only [nsmul_eq_mul, zsmul_eq_mul, Int.cast_pow, Int.cast_neg,
Int.cast_one] using h.sub_nsmul_eq n
theorem Antiperiodic.nat_mul_sub_eq [Ring α] [Ring β] (h : Antiperiodic f c) (n : ℕ) :
f (n * c - x) = (-1) ^ n * f (-x) := by
simpa only [nsmul_eq_mul, zsmul_eq_mul, Int.cast_pow, Int.cast_neg,
Int.cast_one] using h.nsmul_sub_eq n
theorem Antiperiodic.const_add [AddSemigroup α] [Neg β] (h : Antiperiodic f c) (a : α) :
Antiperiodic (fun x => f (a + x)) c := fun x => by simpa [add_assoc] using h (a + x)
#align function.antiperiodic.const_add Function.Antiperiodic.const_add
theorem Antiperiodic.add_const [AddCommSemigroup α] [Neg β] (h : Antiperiodic f c) (a : α) :
Antiperiodic (fun x => f (x + a)) c := fun x => by
simpa only [add_right_comm] using h (x + a)
#align function.antiperiodic.add_const Function.Antiperiodic.add_const
theorem Antiperiodic.const_sub [AddCommGroup α] [InvolutiveNeg β] (h : Antiperiodic f c) (a : α) :
Antiperiodic (fun x => f (a - x)) c := fun x => by
simp only [← sub_sub, h.sub_eq]
#align function.antiperiodic.const_sub Function.Antiperiodic.const_sub
theorem Antiperiodic.sub_const [AddCommGroup α] [Neg β] (h : Antiperiodic f c) (a : α) :
Antiperiodic (fun x => f (x - a)) c := by
simpa only [sub_eq_add_neg] using h.add_const (-a)
#align function.antiperiodic.sub_const Function.Antiperiodic.sub_const
theorem Antiperiodic.smul [Add α] [Monoid γ] [AddGroup β] [DistribMulAction γ β]
(h : Antiperiodic f c) (a : γ) : Antiperiodic (a • f) c := by simp_all
#align function.antiperiodic.smul Function.Antiperiodic.smul
theorem Antiperiodic.const_smul [AddMonoid α] [Neg β] [Group γ] [DistribMulAction γ α]
(h : Antiperiodic f c) (a : γ) : Antiperiodic (fun x => f (a • x)) (a⁻¹ • c) := fun x => by
simpa only [smul_add, smul_inv_smul] using h (a • x)
#align function.antiperiodic.const_smul Function.Antiperiodic.const_smul
theorem Antiperiodic.const_smul₀ [AddCommMonoid α] [Neg β] [DivisionSemiring γ] [Module γ α]
(h : Antiperiodic f c) {a : γ} (ha : a ≠ 0) : Antiperiodic (fun x => f (a • x)) (a⁻¹ • c) :=
fun x => by simpa only [smul_add, smul_inv_smul₀ ha] using h (a • x)
#align function.antiperiodic.const_smul₀ Function.Antiperiodic.const_smul₀
theorem Antiperiodic.const_mul [DivisionSemiring α] [Neg β] (h : Antiperiodic f c) {a : α}
(ha : a ≠ 0) : Antiperiodic (fun x => f (a * x)) (a⁻¹ * c) :=
h.const_smul₀ ha
#align function.antiperiodic.const_mul Function.Antiperiodic.const_mul
theorem Antiperiodic.const_inv_smul [AddMonoid α] [Neg β] [Group γ] [DistribMulAction γ α]
(h : Antiperiodic f c) (a : γ) : Antiperiodic (fun x => f (a⁻¹ • x)) (a • c) := by
simpa only [inv_inv] using h.const_smul a⁻¹
#align function.antiperiodic.const_inv_smul Function.Antiperiodic.const_inv_smul
theorem Antiperiodic.const_inv_smul₀ [AddCommMonoid α] [Neg β] [DivisionSemiring γ] [Module γ α]
(h : Antiperiodic f c) {a : γ} (ha : a ≠ 0) : Antiperiodic (fun x => f (a⁻¹ • x)) (a • c) := by
simpa only [inv_inv] using h.const_smul₀ (inv_ne_zero ha)
#align function.antiperiodic.const_inv_smul₀ Function.Antiperiodic.const_inv_smul₀
theorem Antiperiodic.const_inv_mul [DivisionSemiring α] [Neg β] (h : Antiperiodic f c) {a : α}
(ha : a ≠ 0) : Antiperiodic (fun x => f (a⁻¹ * x)) (a * c) :=
h.const_inv_smul₀ ha
#align function.antiperiodic.const_inv_mul Function.Antiperiodic.const_inv_mul
theorem Antiperiodic.mul_const [DivisionSemiring α] [Neg β] (h : Antiperiodic f c) {a : α}
(ha : a ≠ 0) : Antiperiodic (fun x => f (x * a)) (c * a⁻¹) :=
h.const_smul₀ <| (MulOpposite.op_ne_zero_iff a).mpr ha
#align function.antiperiodic.mul_const Function.Antiperiodic.mul_const
theorem Antiperiodic.mul_const' [DivisionSemiring α] [Neg β] (h : Antiperiodic f c) {a : α}
(ha : a ≠ 0) : Antiperiodic (fun x => f (x * a)) (c / a) := by
simpa only [div_eq_mul_inv] using h.mul_const ha
#align function.antiperiodic.mul_const' Function.Antiperiodic.mul_const'
theorem Antiperiodic.mul_const_inv [DivisionSemiring α] [Neg β] (h : Antiperiodic f c) {a : α}
(ha : a ≠ 0) : Antiperiodic (fun x => f (x * a⁻¹)) (c * a) :=
h.const_inv_smul₀ <| (MulOpposite.op_ne_zero_iff a).mpr ha
#align function.antiperiodic.mul_const_inv Function.Antiperiodic.mul_const_inv
theorem Antiperiodic.div_inv [DivisionSemiring α] [Neg β] (h : Antiperiodic f c) {a : α}
(ha : a ≠ 0) : Antiperiodic (fun x => f (x / a)) (c * a) := by
simpa only [div_eq_mul_inv] using h.mul_const_inv ha
#align function.antiperiodic.div_inv Function.Antiperiodic.div_inv
theorem Antiperiodic.add [AddGroup α] [InvolutiveNeg β] (h1 : Antiperiodic f c₁)
(h2 : Antiperiodic f c₂) : Periodic f (c₁ + c₂) := by simp_all [← add_assoc]
#align function.antiperiodic.add Function.Antiperiodic.add
theorem Antiperiodic.sub [AddGroup α] [InvolutiveNeg β] (h1 : Antiperiodic f c₁)
(h2 : Antiperiodic f c₂) : Periodic f (c₁ - c₂) := by
simpa only [sub_eq_add_neg] using h1.add h2.neg
#align function.antiperiodic.sub Function.Antiperiodic.sub
| Mathlib/Algebra/Periodic.lean | 596 | 597 | theorem Periodic.add_antiperiod [AddGroup α] [Neg β] (h1 : Periodic f c₁) (h2 : Antiperiodic f c₂) :
Antiperiodic f (c₁ + c₂) := by | simp_all [← add_assoc]
|
/-
Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn
-/
import Mathlib.Data.Finset.Basic
import Mathlib.ModelTheory.Syntax
import Mathlib.Data.List.ProdSigma
#align_import model_theory.semantics from "leanprover-community/mathlib"@"d565b3df44619c1498326936be16f1a935df0728"
/-!
# Basics on First-Order Semantics
This file defines the interpretations of first-order terms, formulas, sentences, and theories
in a style inspired by the [Flypitch project](https://flypitch.github.io/).
## Main Definitions
* `FirstOrder.Language.Term.realize` is defined so that `t.realize v` is the term `t` evaluated at
variables `v`.
* `FirstOrder.Language.BoundedFormula.Realize` is defined so that `φ.Realize v xs` is the bounded
formula `φ` evaluated at tuples of variables `v` and `xs`.
* `FirstOrder.Language.Formula.Realize` is defined so that `φ.Realize v` is the formula `φ`
evaluated at variables `v`.
* `FirstOrder.Language.Sentence.Realize` is defined so that `φ.Realize M` is the sentence `φ`
evaluated in the structure `M`. Also denoted `M ⊨ φ`.
* `FirstOrder.Language.Theory.Model` is defined so that `T.Model M` is true if and only if every
sentence of `T` is realized in `M`. Also denoted `T ⊨ φ`.
## Main Results
* `FirstOrder.Language.BoundedFormula.realize_toPrenex` shows that the prenex normal form of a
formula has the same realization as the original formula.
* Several results in this file show that syntactic constructions such as `relabel`, `castLE`,
`liftAt`, `subst`, and the actions of language maps commute with realization of terms, formulas,
sentences, and theories.
## Implementation Notes
* Formulas use a modified version of de Bruijn variables. Specifically, a `L.BoundedFormula α n`
is a formula with some variables indexed by a type `α`, which cannot be quantified over, and some
indexed by `Fin n`, which can. For any `φ : L.BoundedFormula α (n + 1)`, we define the formula
`∀' φ : L.BoundedFormula α n` by universally quantifying over the variable indexed by
`n : Fin (n + 1)`.
## References
For the Flypitch project:
- [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*]
[flypitch_cpp]
- [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of
the continuum hypothesis*][flypitch_itp]
-/
universe u v w u' v'
namespace FirstOrder
namespace Language
variable {L : Language.{u, v}} {L' : Language}
variable {M : Type w} {N P : Type*} [L.Structure M] [L.Structure N] [L.Structure P]
variable {α : Type u'} {β : Type v'} {γ : Type*}
open FirstOrder Cardinal
open Structure Cardinal Fin
namespace Term
-- Porting note: universes in different order
/-- A term `t` with variables indexed by `α` can be evaluated by giving a value to each variable. -/
def realize (v : α → M) : ∀ _t : L.Term α, M
| var k => v k
| func f ts => funMap f fun i => (ts i).realize v
#align first_order.language.term.realize FirstOrder.Language.Term.realize
/- Porting note: The equation lemma of `realize` is too strong; it simplifies terms like the LHS of
`realize_functions_apply₁`. Even `eqns` can't fix this. We removed `simp` attr from `realize` and
prepare new simp lemmas for `realize`. -/
@[simp]
theorem realize_var (v : α → M) (k) : realize v (var k : L.Term α) = v k := rfl
@[simp]
theorem realize_func (v : α → M) {n} (f : L.Functions n) (ts) :
realize v (func f ts : L.Term α) = funMap f fun i => (ts i).realize v := rfl
@[simp]
theorem realize_relabel {t : L.Term α} {g : α → β} {v : β → M} :
(t.relabel g).realize v = t.realize (v ∘ g) := by
induction' t with _ n f ts ih
· rfl
· simp [ih]
#align first_order.language.term.realize_relabel FirstOrder.Language.Term.realize_relabel
@[simp]
theorem realize_liftAt {n n' m : ℕ} {t : L.Term (Sum α (Fin n))} {v : Sum α (Fin (n + n')) → M} :
(t.liftAt n' m).realize v =
t.realize (v ∘ Sum.map id fun i : Fin _ =>
if ↑i < m then Fin.castAdd n' i else Fin.addNat i n') :=
realize_relabel
#align first_order.language.term.realize_lift_at FirstOrder.Language.Term.realize_liftAt
@[simp]
theorem realize_constants {c : L.Constants} {v : α → M} : c.term.realize v = c :=
funMap_eq_coe_constants
#align first_order.language.term.realize_constants FirstOrder.Language.Term.realize_constants
@[simp]
theorem realize_functions_apply₁ {f : L.Functions 1} {t : L.Term α} {v : α → M} :
(f.apply₁ t).realize v = funMap f ![t.realize v] := by
rw [Functions.apply₁, Term.realize]
refine congr rfl (funext fun i => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.term.realize_functions_apply₁ FirstOrder.Language.Term.realize_functions_apply₁
@[simp]
theorem realize_functions_apply₂ {f : L.Functions 2} {t₁ t₂ : L.Term α} {v : α → M} :
(f.apply₂ t₁ t₂).realize v = funMap f ![t₁.realize v, t₂.realize v] := by
rw [Functions.apply₂, Term.realize]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.term.realize_functions_apply₂ FirstOrder.Language.Term.realize_functions_apply₂
theorem realize_con {A : Set M} {a : A} {v : α → M} : (L.con a).term.realize v = a :=
rfl
#align first_order.language.term.realize_con FirstOrder.Language.Term.realize_con
@[simp]
theorem realize_subst {t : L.Term α} {tf : α → L.Term β} {v : β → M} :
(t.subst tf).realize v = t.realize fun a => (tf a).realize v := by
induction' t with _ _ _ _ ih
· rfl
· simp [ih]
#align first_order.language.term.realize_subst FirstOrder.Language.Term.realize_subst
@[simp]
theorem realize_restrictVar [DecidableEq α] {t : L.Term α} {s : Set α} (h : ↑t.varFinset ⊆ s)
{v : α → M} : (t.restrictVar (Set.inclusion h)).realize (v ∘ (↑)) = t.realize v := by
induction' t with _ _ _ _ ih
· rfl
· simp_rw [varFinset, Finset.coe_biUnion, Set.iUnion_subset_iff] at h
exact congr rfl (funext fun i => ih i (h i (Finset.mem_univ i)))
#align first_order.language.term.realize_restrict_var FirstOrder.Language.Term.realize_restrictVar
@[simp]
theorem realize_restrictVarLeft [DecidableEq α] {γ : Type*} {t : L.Term (Sum α γ)} {s : Set α}
(h : ↑t.varFinsetLeft ⊆ s) {v : α → M} {xs : γ → M} :
(t.restrictVarLeft (Set.inclusion h)).realize (Sum.elim (v ∘ (↑)) xs) =
t.realize (Sum.elim v xs) := by
induction' t with a _ _ _ ih
· cases a <;> rfl
· simp_rw [varFinsetLeft, Finset.coe_biUnion, Set.iUnion_subset_iff] at h
exact congr rfl (funext fun i => ih i (h i (Finset.mem_univ i)))
#align first_order.language.term.realize_restrict_var_left FirstOrder.Language.Term.realize_restrictVarLeft
@[simp]
theorem realize_constantsToVars [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{t : L[[α]].Term β} {v : β → M} :
t.constantsToVars.realize (Sum.elim (fun a => ↑(L.con a)) v) = t.realize v := by
induction' t with _ n f ts ih
· simp
· cases n
· cases f
· simp only [realize, ih, Nat.zero_eq, constantsOn, mk₂_Functions]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
· simp only [realize, constantsToVars, Sum.elim_inl, funMap_eq_coe_constants]
rfl
· cases' f with _ f
· simp only [realize, ih, constantsOn, mk₂_Functions]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
· exact isEmptyElim f
#align first_order.language.term.realize_constants_to_vars FirstOrder.Language.Term.realize_constantsToVars
@[simp]
| Mathlib/ModelTheory/Semantics.lean | 178 | 188 | theorem realize_varsToConstants [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{t : L.Term (Sum α β)} {v : β → M} :
t.varsToConstants.realize v = t.realize (Sum.elim (fun a => ↑(L.con a)) v) := by |
induction' t with ab n f ts ih
· cases' ab with a b
-- Porting note: both cases were `simp [Language.con]`
· simp [Language.con, realize, funMap_eq_coe_constants]
· simp [realize, constantMap]
· simp only [realize, constantsOn, mk₂_Functions, ih]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
|
/-
Copyright (c) 2021 Chris Birkbeck. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Birkbeck
-/
import Mathlib.Algebra.Group.Subgroup.Pointwise
import Mathlib.Data.Set.Basic
import Mathlib.Data.Setoid.Basic
import Mathlib.GroupTheory.Coset
#align_import group_theory.double_coset from "leanprover-community/mathlib"@"4c19a16e4b705bf135cf9a80ac18fcc99c438514"
/-!
# Double cosets
This file defines double cosets for two subgroups `H K` of a group `G` and the quotient of `G` by
the double coset relation, i.e. `H \ G / K`. We also prove that `G` can be written as a disjoint
union of the double cosets and that if one of `H` or `K` is the trivial group (i.e. `⊥` ) then
this is the usual left or right quotient of a group by a subgroup.
## Main definitions
* `rel`: The double coset relation defined by two subgroups `H K` of `G`.
* `Doset.quotient`: The quotient of `G` by the double coset relation, i.e, `H \ G / K`.
-/
-- Porting note: removed import
-- import Mathlib.Tactic.Group
variable {G : Type*} [Group G] {α : Type*} [Mul α] (J : Subgroup G) (g : G)
open MulOpposite
open scoped Pointwise
namespace Doset
/-- The double coset as an element of `Set α` corresponding to `s a t` -/
def doset (a : α) (s t : Set α) : Set α :=
s * {a} * t
#align doset Doset.doset
lemma doset_eq_image2 (a : α) (s t : Set α) : doset a s t = Set.image2 (· * a * ·) s t := by
simp_rw [doset, Set.mul_singleton, ← Set.image2_mul, Set.image2_image_left]
theorem mem_doset {s t : Set α} {a b : α} : b ∈ doset a s t ↔ ∃ x ∈ s, ∃ y ∈ t, b = x * a * y := by
simp only [doset_eq_image2, Set.mem_image2, eq_comm]
#align doset.mem_doset Doset.mem_doset
theorem mem_doset_self (H K : Subgroup G) (a : G) : a ∈ doset a H K :=
mem_doset.mpr ⟨1, H.one_mem, 1, K.one_mem, (one_mul a).symm.trans (mul_one (1 * a)).symm⟩
#align doset.mem_doset_self Doset.mem_doset_self
theorem doset_eq_of_mem {H K : Subgroup G} {a b : G} (hb : b ∈ doset a H K) :
doset b H K = doset a H K := by
obtain ⟨h, hh, k, hk, rfl⟩ := mem_doset.1 hb
rw [doset, doset, ← Set.singleton_mul_singleton, ← Set.singleton_mul_singleton, mul_assoc,
mul_assoc, Subgroup.singleton_mul_subgroup hk, ← mul_assoc, ← mul_assoc,
Subgroup.subgroup_mul_singleton hh]
#align doset.doset_eq_of_mem Doset.doset_eq_of_mem
theorem mem_doset_of_not_disjoint {H K : Subgroup G} {a b : G}
(h : ¬Disjoint (doset a H K) (doset b H K)) : b ∈ doset a H K := by
rw [Set.not_disjoint_iff] at h
simp only [mem_doset] at *
obtain ⟨x, ⟨l, hl, r, hr, hrx⟩, y, hy, ⟨r', hr', rfl⟩⟩ := h
refine ⟨y⁻¹ * l, H.mul_mem (H.inv_mem hy) hl, r * r'⁻¹, K.mul_mem hr (K.inv_mem hr'), ?_⟩
rwa [mul_assoc, mul_assoc, eq_inv_mul_iff_mul_eq, ← mul_assoc, ← mul_assoc, eq_mul_inv_iff_mul_eq]
#align doset.mem_doset_of_not_disjoint Doset.mem_doset_of_not_disjoint
theorem eq_of_not_disjoint {H K : Subgroup G} {a b : G}
(h : ¬Disjoint (doset a H K) (doset b H K)) : doset a H K = doset b H K := by
rw [disjoint_comm] at h
have ha : a ∈ doset b H K := mem_doset_of_not_disjoint h
apply doset_eq_of_mem ha
#align doset.eq_of_not_disjoint Doset.eq_of_not_disjoint
/-- The setoid defined by the double_coset relation -/
def setoid (H K : Set G) : Setoid G :=
Setoid.ker fun x => doset x H K
#align doset.setoid Doset.setoid
/-- Quotient of `G` by the double coset relation, i.e. `H \ G / K` -/
def Quotient (H K : Set G) : Type _ :=
_root_.Quotient (setoid H K)
#align doset.quotient Doset.Quotient
theorem rel_iff {H K : Subgroup G} {x y : G} :
(setoid ↑H ↑K).Rel x y ↔ ∃ a ∈ H, ∃ b ∈ K, y = a * x * b :=
Iff.trans
⟨fun hxy => (congr_arg _ hxy).mpr (mem_doset_self H K y), fun hxy => (doset_eq_of_mem hxy).symm⟩
mem_doset
#align doset.rel_iff Doset.rel_iff
theorem bot_rel_eq_leftRel (H : Subgroup G) :
(setoid ↑(⊥ : Subgroup G) ↑H).Rel = (QuotientGroup.leftRel H).Rel := by
ext a b
rw [rel_iff, Setoid.Rel, QuotientGroup.leftRel_apply]
constructor
· rintro ⟨a, rfl : a = 1, b, hb, rfl⟩
change a⁻¹ * (1 * a * b) ∈ H
rwa [one_mul, inv_mul_cancel_left]
· rintro (h : a⁻¹ * b ∈ H)
exact ⟨1, rfl, a⁻¹ * b, h, by rw [one_mul, mul_inv_cancel_left]⟩
#align doset.bot_rel_eq_left_rel Doset.bot_rel_eq_leftRel
theorem rel_bot_eq_right_group_rel (H : Subgroup G) :
(setoid ↑H ↑(⊥ : Subgroup G)).Rel = (QuotientGroup.rightRel H).Rel := by
ext a b
rw [rel_iff, Setoid.Rel, QuotientGroup.rightRel_apply]
constructor
· rintro ⟨b, hb, a, rfl : a = 1, rfl⟩
change b * a * 1 * a⁻¹ ∈ H
rwa [mul_one, mul_inv_cancel_right]
· rintro (h : b * a⁻¹ ∈ H)
exact ⟨b * a⁻¹, h, 1, rfl, by rw [mul_one, inv_mul_cancel_right]⟩
#align doset.rel_bot_eq_right_group_rel Doset.rel_bot_eq_right_group_rel
/-- Create a doset out of an element of `H \ G / K`-/
def quotToDoset (H K : Subgroup G) (q : Quotient (H : Set G) K) : Set G :=
doset q.out' H K
#align doset.quot_to_doset Doset.quotToDoset
/-- Map from `G` to `H \ G / K`-/
abbrev mk (H K : Subgroup G) (a : G) : Quotient (H : Set G) K :=
Quotient.mk'' a
#align doset.mk Doset.mk
instance (H K : Subgroup G) : Inhabited (Quotient (H : Set G) K) :=
⟨mk H K (1 : G)⟩
theorem eq (H K : Subgroup G) (a b : G) :
mk H K a = mk H K b ↔ ∃ h ∈ H, ∃ k ∈ K, b = h * a * k := by
rw [Quotient.eq'']
apply rel_iff
#align doset.eq Doset.eq
theorem out_eq' (H K : Subgroup G) (q : Quotient ↑H ↑K) : mk H K q.out' = q :=
Quotient.out_eq' q
#align doset.out_eq' Doset.out_eq'
theorem mk_out'_eq_mul (H K : Subgroup G) (g : G) :
∃ h k : G, h ∈ H ∧ k ∈ K ∧ (mk H K g : Quotient ↑H ↑K).out' = h * g * k := by
have := eq H K (mk H K g : Quotient ↑H ↑K).out' g
rw [out_eq'] at this
obtain ⟨h, h_h, k, hk, T⟩ := this.1 rfl
refine ⟨h⁻¹, k⁻¹, H.inv_mem h_h, K.inv_mem hk, eq_mul_inv_of_mul_eq (eq_inv_mul_of_mul_eq ?_)⟩
rw [← mul_assoc, ← T]
#align doset.mk_out'_eq_mul Doset.mk_out'_eq_mul
theorem mk_eq_of_doset_eq {H K : Subgroup G} {a b : G} (h : doset a H K = doset b H K) :
mk H K a = mk H K b := by
rw [eq]
exact mem_doset.mp (h.symm ▸ mem_doset_self H K b)
#align doset.mk_eq_of_doset_eq Doset.mk_eq_of_doset_eq
| Mathlib/GroupTheory/DoubleCoset.lean | 155 | 159 | theorem disjoint_out' {H K : Subgroup G} {a b : Quotient H.1 K} :
a ≠ b → Disjoint (doset a.out' H K) (doset b.out' (H : Set G) K) := by |
contrapose!
intro h
simpa [out_eq'] using mk_eq_of_doset_eq (eq_of_not_disjoint h)
|
/-
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}
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
#align antilipschitz_with.hausdorff_measure_preimage_le AntilipschitzWith.hausdorffMeasure_preimage_le
theorem le_hausdorffMeasure_image (hf : AntilipschitzWith K f) (hd : 0 ≤ d) (s : Set X) :
μH[d] s ≤ (K : ℝ≥0∞) ^ d * μH[d] (f '' s) :=
calc
μH[d] s ≤ μH[d] (f ⁻¹' (f '' s)) := measure_mono (subset_preimage_image _ _)
_ ≤ (K : ℝ≥0∞) ^ d * μH[d] (f '' s) := hf.hausdorffMeasure_preimage_le hd (f '' s)
#align antilipschitz_with.le_hausdorff_measure_image AntilipschitzWith.le_hausdorffMeasure_image
end AntilipschitzWith
/-!
### Isometries preserve the Hausdorff measure and Hausdorff dimension
-/
namespace Isometry
variable {f : X → Y} {d : ℝ}
theorem hausdorffMeasure_image (hf : Isometry f) (hd : 0 ≤ d ∨ Surjective f) (s : Set X) :
μH[d] (f '' s) = μH[d] s := by
simp only [hausdorffMeasure, ← OuterMeasure.coe_mkMetric, ← OuterMeasure.comap_apply]
rw [OuterMeasure.isometry_comap_mkMetric _ hf (hd.imp_left _)]
exact ENNReal.monotone_rpow_of_nonneg
#align isometry.hausdorff_measure_image Isometry.hausdorffMeasure_image
theorem hausdorffMeasure_preimage (hf : Isometry f) (hd : 0 ≤ d ∨ Surjective f) (s : Set Y) :
μH[d] (f ⁻¹' s) = μH[d] (s ∩ range f) := by
rw [← hf.hausdorffMeasure_image hd, image_preimage_eq_inter_range]
#align isometry.hausdorff_measure_preimage Isometry.hausdorffMeasure_preimage
theorem map_hausdorffMeasure (hf : Isometry f) (hd : 0 ≤ d ∨ Surjective f) :
Measure.map f μH[d] = μH[d].restrict (range f) := by
ext1 s hs
rw [map_apply hf.continuous.measurable hs, Measure.restrict_apply hs,
hf.hausdorffMeasure_preimage hd]
#align isometry.map_hausdorff_measure Isometry.map_hausdorffMeasure
end Isometry
namespace IsometryEquiv
@[simp]
theorem hausdorffMeasure_image (e : X ≃ᵢ Y) (d : ℝ) (s : Set X) : μH[d] (e '' s) = μH[d] s :=
e.isometry.hausdorffMeasure_image (Or.inr e.surjective) s
#align isometry_equiv.hausdorff_measure_image IsometryEquiv.hausdorffMeasure_image
@[simp]
theorem hausdorffMeasure_preimage (e : X ≃ᵢ Y) (d : ℝ) (s : Set Y) : μH[d] (e ⁻¹' s) = μH[d] s := by
rw [← e.image_symm, e.symm.hausdorffMeasure_image]
#align isometry_equiv.hausdorff_measure_preimage IsometryEquiv.hausdorffMeasure_preimage
@[simp]
theorem map_hausdorffMeasure (e : X ≃ᵢ Y) (d : ℝ) : Measure.map e μH[d] = μH[d] := by
rw [e.isometry.map_hausdorffMeasure (Or.inr e.surjective), e.surjective.range_eq, restrict_univ]
#align isometry_equiv.map_hausdorff_measure IsometryEquiv.map_hausdorffMeasure
theorem measurePreserving_hausdorffMeasure (e : X ≃ᵢ Y) (d : ℝ) : MeasurePreserving e μH[d] μH[d] :=
⟨e.continuous.measurable, map_hausdorffMeasure _ _⟩
#align isometry_equiv.measure_preserving_hausdorff_measure IsometryEquiv.measurePreserving_hausdorffMeasure
end IsometryEquiv
namespace MeasureTheory
@[to_additive]
theorem hausdorffMeasure_smul {α : Type*} [SMul α X] [IsometricSMul α X] {d : ℝ} (c : α)
(h : 0 ≤ d ∨ Surjective (c • · : X → X)) (s : Set X) : μH[d] (c • s) = μH[d] s :=
(isometry_smul X c).hausdorffMeasure_image h _
#align measure_theory.hausdorff_measure_smul MeasureTheory.hausdorffMeasure_smul
#align measure_theory.hausdorff_measure_vadd MeasureTheory.hausdorffMeasure_vadd
@[to_additive]
instance {d : ℝ} [Group X] [IsometricSMul X X] : IsMulLeftInvariant (μH[d] : Measure X) where
map_mul_left_eq_self x := (IsometryEquiv.constSMul x).map_hausdorffMeasure _
@[to_additive]
instance {d : ℝ} [Group X] [IsometricSMul Xᵐᵒᵖ X] : IsMulRightInvariant (μH[d] : Measure X) where
map_mul_right_eq_self x := (IsometryEquiv.constSMul (MulOpposite.op x)).map_hausdorffMeasure _
/-!
### Hausdorff measure and Lebesgue measure
-/
/-- In the space `ι → ℝ`, the Hausdorff measure coincides exactly with the Lebesgue measure. -/
@[simp]
theorem hausdorffMeasure_pi_real {ι : Type*} [Fintype ι] :
(μH[Fintype.card ι] : Measure (ι → ℝ)) = volume := by
classical
-- it suffices to check that the two measures coincide on products of rational intervals
refine (pi_eq_generateFrom (fun _ => Real.borel_eq_generateFrom_Ioo_rat.symm)
(fun _ => Real.isPiSystem_Ioo_rat) (fun _ => Real.finiteSpanningSetsInIooRat _) ?_).symm
simp only [mem_iUnion, mem_singleton_iff]
-- fix such a product `s` of rational intervals, of the form `Π (a i, b i)`.
intro s hs
choose a b H using hs
obtain rfl : s = fun i => Ioo (α := ℝ) (a i) (b i) := funext fun i => (H i).2
replace H := fun i => (H i).1
apply le_antisymm _
-- first check that `volume s ≤ μH s`
· have Hle : volume ≤ (μH[Fintype.card ι] : Measure (ι → ℝ)) := by
refine le_hausdorffMeasure _ _ ∞ ENNReal.coe_lt_top fun s _ => ?_
rw [ENNReal.rpow_natCast]
exact Real.volume_pi_le_diam_pow s
rw [← volume_pi_pi fun i => Ioo (a i : ℝ) (b i)]
exact Measure.le_iff'.1 Hle _
/- For the other inequality `μH s ≤ volume s`, we use a covering of `s` by sets of small diameter
`1/n`, namely cubes with left-most point of the form `a i + f i / n` with `f i` ranging between
`0` and `⌈(b i - a i) * n⌉`. Their number is asymptotic to `n^d * Π (b i - a i)`. -/
have I : ∀ i, 0 ≤ (b i : ℝ) - a i := fun i => by
simpa only [sub_nonneg, Rat.cast_le] using (H i).le
let γ := fun n : ℕ => ∀ i : ι, Fin ⌈((b i : ℝ) - a i) * n⌉₊
let t : ∀ n : ℕ, γ n → Set (ι → ℝ) := fun n f =>
Set.pi univ fun i => Icc (a i + f i / n) (a i + (f i + 1) / n)
have A : Tendsto (fun n : ℕ => 1 / (n : ℝ≥0∞)) atTop (𝓝 0) := by
simp only [one_div, ENNReal.tendsto_inv_nat_nhds_zero]
have B : ∀ᶠ n in atTop, ∀ i : γ n, diam (t n i) ≤ 1 / n := by
refine eventually_atTop.2 ⟨1, fun n hn => ?_⟩
intro f
refine diam_pi_le_of_le fun b => ?_
simp only [Real.ediam_Icc, add_div, ENNReal.ofReal_div_of_pos (Nat.cast_pos.mpr hn), le_refl,
add_sub_add_left_eq_sub, add_sub_cancel_left, ENNReal.ofReal_one, ENNReal.ofReal_natCast]
have C : ∀ᶠ n in atTop, (Set.pi univ fun i : ι => Ioo (a i : ℝ) (b i)) ⊆ ⋃ i : γ n, t n i := by
refine eventually_atTop.2 ⟨1, fun n hn => ?_⟩
have npos : (0 : ℝ) < n := Nat.cast_pos.2 hn
intro x hx
simp only [mem_Ioo, mem_univ_pi] at hx
simp only [t, mem_iUnion, mem_Ioo, mem_univ_pi]
let f : γ n := fun i =>
⟨⌊(x i - a i) * n⌋₊, by
apply Nat.floor_lt_ceil_of_lt_of_pos
· refine (mul_lt_mul_right npos).2 ?_
simp only [(hx i).right, sub_lt_sub_iff_right]
· refine mul_pos ?_ npos
simpa only [Rat.cast_lt, sub_pos] using H i⟩
refine ⟨f, fun i => ⟨?_, ?_⟩⟩
· calc
(a i : ℝ) + ⌊(x i - a i) * n⌋₊ / n ≤ (a i : ℝ) + (x i - a i) * n / n := by
gcongr
exact Nat.floor_le (mul_nonneg (sub_nonneg.2 (hx i).1.le) npos.le)
_ = x i := by field_simp [npos.ne']
· calc
x i = (a i : ℝ) + (x i - a i) * n / n := by field_simp [npos.ne']
_ ≤ (a i : ℝ) + (⌊(x i - a i) * n⌋₊ + 1) / n := by
gcongr
exact (Nat.lt_floor_add_one _).le
calc
μH[Fintype.card ι] (Set.pi univ fun i : ι => Ioo (a i : ℝ) (b i)) ≤
liminf (fun n : ℕ => ∑ i : γ n, diam (t n i) ^ ((Fintype.card ι) : ℝ)) atTop :=
hausdorffMeasure_le_liminf_sum _ (Set.pi univ fun i => Ioo (a i : ℝ) (b i))
(fun n : ℕ => 1 / (n : ℝ≥0∞)) A t B C
_ ≤ liminf (fun n : ℕ => ∑ i : γ n, (1 / (n : ℝ≥0∞)) ^ Fintype.card ι) atTop := by
refine liminf_le_liminf ?_ ?_
· filter_upwards [B] with _ hn
apply Finset.sum_le_sum fun i _ => _
simp only [ENNReal.rpow_natCast]
intros i _
exact pow_le_pow_left' (hn i) _
· isBoundedDefault
_ = liminf (fun n : ℕ => ∏ i : ι, (⌈((b i : ℝ) - a i) * n⌉₊ : ℝ≥0∞) / n) atTop := by
simp only [γ, Finset.card_univ, Nat.cast_prod, one_mul, Fintype.card_fin, Finset.sum_const,
nsmul_eq_mul, Fintype.card_pi, div_eq_mul_inv, Finset.prod_mul_distrib, Finset.prod_const]
_ = ∏ i : ι, volume (Ioo (a i : ℝ) (b i)) := by
simp only [Real.volume_Ioo]
apply Tendsto.liminf_eq
refine ENNReal.tendsto_finset_prod_of_ne_top _ (fun i _ => ?_) fun i _ => ?_
· apply
Tendsto.congr' _
((ENNReal.continuous_ofReal.tendsto _).comp
((tendsto_nat_ceil_mul_div_atTop (I i)).comp tendsto_natCast_atTop_atTop))
apply eventually_atTop.2 ⟨1, fun n hn => _⟩
intros n hn
simp only [ENNReal.ofReal_div_of_pos (Nat.cast_pos.mpr hn), comp_apply,
ENNReal.ofReal_natCast]
· simp only [ENNReal.ofReal_ne_top, Ne, not_false_iff]
#align measure_theory.hausdorff_measure_pi_real MeasureTheory.hausdorffMeasure_pi_real
variable (ι X)
theorem hausdorffMeasure_measurePreserving_funUnique [Unique ι]
[SecondCountableTopology X] (d : ℝ) :
MeasurePreserving (MeasurableEquiv.funUnique ι X) μH[d] μH[d] :=
(IsometryEquiv.funUnique ι X).measurePreserving_hausdorffMeasure _
#align measure_theory.hausdorff_measure_measure_preserving_fun_unique MeasureTheory.hausdorffMeasure_measurePreserving_funUnique
theorem hausdorffMeasure_measurePreserving_piFinTwo (α : Fin 2 → Type*)
[∀ i, MeasurableSpace (α i)] [∀ i, EMetricSpace (α i)] [∀ i, BorelSpace (α i)]
[∀ i, SecondCountableTopology (α i)] (d : ℝ) :
MeasurePreserving (MeasurableEquiv.piFinTwo α) μH[d] μH[d] :=
(IsometryEquiv.piFinTwo α).measurePreserving_hausdorffMeasure _
#align measure_theory.hausdorff_measure_measure_preserving_pi_fin_two MeasureTheory.hausdorffMeasure_measurePreserving_piFinTwo
/-- In the space `ℝ`, the Hausdorff measure coincides exactly with the Lebesgue measure. -/
@[simp]
theorem hausdorffMeasure_real : (μH[1] : Measure ℝ) = volume := by
rw [← (volume_preserving_funUnique Unit ℝ).map_eq,
← (hausdorffMeasure_measurePreserving_funUnique Unit ℝ 1).map_eq,
← hausdorffMeasure_pi_real, Fintype.card_unit, Nat.cast_one]
#align measure_theory.hausdorff_measure_real MeasureTheory.hausdorffMeasure_real
/-- In the space `ℝ × ℝ`, the Hausdorff measure coincides exactly with the Lebesgue measure. -/
@[simp]
theorem hausdorffMeasure_prod_real : (μH[2] : Measure (ℝ × ℝ)) = volume := by
rw [← (volume_preserving_piFinTwo fun _ => ℝ).map_eq,
← (hausdorffMeasure_measurePreserving_piFinTwo (fun _ => ℝ) _).map_eq,
← hausdorffMeasure_pi_real, Fintype.card_fin, Nat.cast_two]
#align measure_theory.hausdorff_measure_prod_real MeasureTheory.hausdorffMeasure_prod_real
/-! ### Geometric results in affine spaces -/
section Geometric
variable {𝕜 E P : Type*}
theorem hausdorffMeasure_smul_right_image [NormedAddCommGroup E] [NormedSpace ℝ E]
[MeasurableSpace E] [BorelSpace E] (v : E) (s : Set ℝ) :
μH[1] ((fun r => r • v) '' s) = ‖v‖₊ • μH[1] s := by
obtain rfl | hv := eq_or_ne v 0
· haveI := noAtoms_hausdorff E one_pos
obtain rfl | hs := s.eq_empty_or_nonempty
· simp
simp [hs]
have hn : ‖v‖ ≠ 0 := norm_ne_zero_iff.mpr hv
-- break lineMap into pieces
suffices
μH[1] ((‖v‖ • ·) '' (LinearMap.toSpanSingleton ℝ E (‖v‖⁻¹ • v) '' s)) = ‖v‖₊ • μH[1] s by
-- Porting note: proof was shorter, could need some golf
simp only [hausdorffMeasure_real, nnreal_smul_coe_apply]
convert this
· simp only [image_smul, LinearMap.toSpanSingleton_apply, Set.image_image]
ext e
simp only [mem_image]
refine ⟨fun ⟨x, h⟩ => ⟨x, ?_⟩, fun ⟨x, h⟩ => ⟨x, ?_⟩⟩
· rw [smul_comm (norm _), smul_comm (norm _), inv_smul_smul₀ hn]
exact h
· rw [smul_comm (norm _), smul_comm (norm _), inv_smul_smul₀ hn] at h
exact h
· exact hausdorffMeasure_real.symm
have iso_smul : Isometry (LinearMap.toSpanSingleton ℝ E (‖v‖⁻¹ • v)) := by
refine AddMonoidHomClass.isometry_of_norm _ fun x => (norm_smul _ _).trans ?_
rw [norm_smul, norm_inv, norm_norm, inv_mul_cancel hn, mul_one, LinearMap.id_apply]
rw [Set.image_smul, Measure.hausdorffMeasure_smul₀ zero_le_one hn, nnnorm_norm,
NNReal.rpow_one, iso_smul.hausdorffMeasure_image (Or.inl <| zero_le_one' ℝ)]
#align measure_theory.hausdorff_measure_smul_right_image MeasureTheory.hausdorffMeasure_smul_right_image
section NormedFieldAffine
variable [NormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [MeasurableSpace P]
variable [MetricSpace P] [NormedAddTorsor E P] [BorelSpace P]
/-- Scaling by `c` around `x` scales the measure by `‖c‖₊ ^ d`. -/
theorem hausdorffMeasure_homothety_image {d : ℝ} (hd : 0 ≤ d) (x : P) {c : 𝕜} (hc : c ≠ 0)
(s : Set P) : μH[d] (AffineMap.homothety x c '' s) = ‖c‖₊ ^ d • μH[d] s := by
suffices
μH[d] (IsometryEquiv.vaddConst x '' ((c • ·) '' ((IsometryEquiv.vaddConst x).symm '' s))) =
‖c‖₊ ^ d • μH[d] s by
simpa only [Set.image_image]
borelize E
rw [IsometryEquiv.hausdorffMeasure_image, Set.image_smul, Measure.hausdorffMeasure_smul₀ hd hc,
IsometryEquiv.hausdorffMeasure_image]
#align measure_theory.hausdorff_measure_homothety_image MeasureTheory.hausdorffMeasure_homothety_image
theorem hausdorffMeasure_homothety_preimage {d : ℝ} (hd : 0 ≤ d) (x : P) {c : 𝕜} (hc : c ≠ 0)
(s : Set P) : μH[d] (AffineMap.homothety x c ⁻¹' s) = ‖c‖₊⁻¹ ^ d • μH[d] s := by
change μH[d] (AffineEquiv.homothetyUnitsMulHom x (Units.mk0 c hc) ⁻¹' s) = _
rw [← AffineEquiv.image_symm, AffineEquiv.coe_homothetyUnitsMulHom_apply_symm,
hausdorffMeasure_homothety_image hd x (_ : 𝕜ˣ).isUnit.ne_zero, Units.val_inv_eq_inv_val,
Units.val_mk0, nnnorm_inv]
#align measure_theory.hausdorff_measure_homothety_preimage MeasureTheory.hausdorffMeasure_homothety_preimage
/-! TODO: prove `Measure.map (AffineMap.homothety x c) μH[d] = ‖c‖₊⁻¹ ^ d • μH[d]`, which needs a
more general version of `AffineMap.homothety_continuous`. -/
end NormedFieldAffine
section RealAffine
variable [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace P]
variable [MetricSpace P] [NormedAddTorsor E P] [BorelSpace P]
/-- Mapping a set of reals along a line segment scales the measure by the length of a segment.
This is an auxiliary result used to prove `hausdorffMeasure_affineSegment`. -/
| Mathlib/MeasureTheory/Measure/Hausdorff.lean | 1,136 | 1,142 | theorem hausdorffMeasure_lineMap_image (x y : P) (s : Set ℝ) :
μH[1] (AffineMap.lineMap x y '' s) = nndist x y • μH[1] s := by |
suffices μH[1] (IsometryEquiv.vaddConst x '' ((· • (y -ᵥ x)) '' s)) = nndist x y • μH[1] s by
simpa only [Set.image_image]
borelize E
rw [IsometryEquiv.hausdorffMeasure_image, hausdorffMeasure_smul_right_image,
nndist_eq_nnnorm_vsub' E]
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Yury Kudryashov
-/
import Mathlib.Algebra.CharP.Invertible
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Analysis.Normed.Group.AddTorsor
import Mathlib.LinearAlgebra.AffineSpace.AffineSubspace
import Mathlib.Topology.Instances.RealVectorSpace
#align_import analysis.normed_space.add_torsor from "leanprover-community/mathlib"@"837f72de63ad6cd96519cde5f1ffd5ed8d280ad0"
/-!
# Torsors of normed space actions.
This file contains lemmas about normed additive torsors over normed spaces.
-/
noncomputable section
open NNReal Topology
open Filter
variable {α V P W Q : Type*} [SeminormedAddCommGroup V] [PseudoMetricSpace P] [NormedAddTorsor V P]
[NormedAddCommGroup W] [MetricSpace Q] [NormedAddTorsor W Q]
section NormedSpace
variable {𝕜 : Type*} [NormedField 𝕜] [NormedSpace 𝕜 V] [NormedSpace 𝕜 W]
open AffineMap
theorem AffineSubspace.isClosed_direction_iff (s : AffineSubspace 𝕜 Q) :
IsClosed (s.direction : Set W) ↔ IsClosed (s : Set Q) := by
rcases s.eq_bot_or_nonempty with (rfl | ⟨x, hx⟩); · simp [isClosed_singleton]
rw [← (IsometryEquiv.vaddConst x).toHomeomorph.symm.isClosed_image,
AffineSubspace.coe_direction_eq_vsub_set_right hx]
rfl
#align affine_subspace.is_closed_direction_iff AffineSubspace.isClosed_direction_iff
@[simp]
theorem dist_center_homothety (p₁ p₂ : P) (c : 𝕜) :
dist p₁ (homothety p₁ c p₂) = ‖c‖ * dist p₁ p₂ := by
simp [homothety_def, norm_smul, ← dist_eq_norm_vsub, dist_comm]
#align dist_center_homothety dist_center_homothety
@[simp]
theorem nndist_center_homothety (p₁ p₂ : P) (c : 𝕜) :
nndist p₁ (homothety p₁ c p₂) = ‖c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_center_homothety _ _ _
#align nndist_center_homothety nndist_center_homothety
@[simp]
theorem dist_homothety_center (p₁ p₂ : P) (c : 𝕜) :
dist (homothety p₁ c p₂) p₁ = ‖c‖ * dist p₁ p₂ := by rw [dist_comm, dist_center_homothety]
#align dist_homothety_center dist_homothety_center
@[simp]
theorem nndist_homothety_center (p₁ p₂ : P) (c : 𝕜) :
nndist (homothety p₁ c p₂) p₁ = ‖c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_homothety_center _ _ _
#align nndist_homothety_center nndist_homothety_center
@[simp]
theorem dist_lineMap_lineMap (p₁ p₂ : P) (c₁ c₂ : 𝕜) :
dist (lineMap p₁ p₂ c₁) (lineMap p₁ p₂ c₂) = dist c₁ c₂ * dist p₁ p₂ := by
rw [dist_comm p₁ p₂]
simp only [lineMap_apply, dist_eq_norm_vsub, vadd_vsub_vadd_cancel_right,
← sub_smul, norm_smul, vsub_eq_sub]
#align dist_line_map_line_map dist_lineMap_lineMap
@[simp]
theorem nndist_lineMap_lineMap (p₁ p₂ : P) (c₁ c₂ : 𝕜) :
nndist (lineMap p₁ p₂ c₁) (lineMap p₁ p₂ c₂) = nndist c₁ c₂ * nndist p₁ p₂ :=
NNReal.eq <| dist_lineMap_lineMap _ _ _ _
#align nndist_line_map_line_map nndist_lineMap_lineMap
theorem lipschitzWith_lineMap (p₁ p₂ : P) : LipschitzWith (nndist p₁ p₂) (lineMap p₁ p₂ : 𝕜 → P) :=
LipschitzWith.of_dist_le_mul fun c₁ c₂ =>
((dist_lineMap_lineMap p₁ p₂ c₁ c₂).trans (mul_comm _ _)).le
#align lipschitz_with_line_map lipschitzWith_lineMap
@[simp]
theorem dist_lineMap_left (p₁ p₂ : P) (c : 𝕜) : dist (lineMap p₁ p₂ c) p₁ = ‖c‖ * dist p₁ p₂ := by
simpa only [lineMap_apply_zero, dist_zero_right] using dist_lineMap_lineMap p₁ p₂ c 0
#align dist_line_map_left dist_lineMap_left
@[simp]
theorem nndist_lineMap_left (p₁ p₂ : P) (c : 𝕜) :
nndist (lineMap p₁ p₂ c) p₁ = ‖c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_lineMap_left _ _ _
#align nndist_line_map_left nndist_lineMap_left
@[simp]
theorem dist_left_lineMap (p₁ p₂ : P) (c : 𝕜) : dist p₁ (lineMap p₁ p₂ c) = ‖c‖ * dist p₁ p₂ :=
(dist_comm _ _).trans (dist_lineMap_left _ _ _)
#align dist_left_line_map dist_left_lineMap
@[simp]
theorem nndist_left_lineMap (p₁ p₂ : P) (c : 𝕜) :
nndist p₁ (lineMap p₁ p₂ c) = ‖c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_left_lineMap _ _ _
#align nndist_left_line_map nndist_left_lineMap
@[simp]
theorem dist_lineMap_right (p₁ p₂ : P) (c : 𝕜) :
dist (lineMap p₁ p₂ c) p₂ = ‖1 - c‖ * dist p₁ p₂ := by
simpa only [lineMap_apply_one, dist_eq_norm'] using dist_lineMap_lineMap p₁ p₂ c 1
#align dist_line_map_right dist_lineMap_right
@[simp]
theorem nndist_lineMap_right (p₁ p₂ : P) (c : 𝕜) :
nndist (lineMap p₁ p₂ c) p₂ = ‖1 - c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_lineMap_right _ _ _
#align nndist_line_map_right nndist_lineMap_right
@[simp]
theorem dist_right_lineMap (p₁ p₂ : P) (c : 𝕜) : dist p₂ (lineMap p₁ p₂ c) = ‖1 - c‖ * dist p₁ p₂ :=
(dist_comm _ _).trans (dist_lineMap_right _ _ _)
#align dist_right_line_map dist_right_lineMap
@[simp]
theorem nndist_right_lineMap (p₁ p₂ : P) (c : 𝕜) :
nndist p₂ (lineMap p₁ p₂ c) = ‖1 - c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_right_lineMap _ _ _
#align nndist_right_line_map nndist_right_lineMap
@[simp]
theorem dist_homothety_self (p₁ p₂ : P) (c : 𝕜) :
dist (homothety p₁ c p₂) p₂ = ‖1 - c‖ * dist p₁ p₂ := by
rw [homothety_eq_lineMap, dist_lineMap_right]
#align dist_homothety_self dist_homothety_self
@[simp]
theorem nndist_homothety_self (p₁ p₂ : P) (c : 𝕜) :
nndist (homothety p₁ c p₂) p₂ = ‖1 - c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_homothety_self _ _ _
#align nndist_homothety_self nndist_homothety_self
@[simp]
theorem dist_self_homothety (p₁ p₂ : P) (c : 𝕜) :
dist p₂ (homothety p₁ c p₂) = ‖1 - c‖ * dist p₁ p₂ := by rw [dist_comm, dist_homothety_self]
#align dist_self_homothety dist_self_homothety
@[simp]
theorem nndist_self_homothety (p₁ p₂ : P) (c : 𝕜) :
nndist p₂ (homothety p₁ c p₂) = ‖1 - c‖₊ * nndist p₁ p₂ :=
NNReal.eq <| dist_self_homothety _ _ _
#align nndist_self_homothety nndist_self_homothety
section invertibleTwo
variable [Invertible (2 : 𝕜)]
@[simp]
theorem dist_left_midpoint (p₁ p₂ : P) : dist p₁ (midpoint 𝕜 p₁ p₂) = ‖(2 : 𝕜)‖⁻¹ * dist p₁ p₂ := by
rw [midpoint, dist_comm, dist_lineMap_left, invOf_eq_inv, ← norm_inv]
#align dist_left_midpoint dist_left_midpoint
@[simp]
theorem nndist_left_midpoint (p₁ p₂ : P) :
nndist p₁ (midpoint 𝕜 p₁ p₂) = ‖(2 : 𝕜)‖₊⁻¹ * nndist p₁ p₂ :=
NNReal.eq <| dist_left_midpoint _ _
#align nndist_left_midpoint nndist_left_midpoint
@[simp]
| Mathlib/Analysis/NormedSpace/AddTorsor.lean | 170 | 171 | theorem dist_midpoint_left (p₁ p₂ : P) : dist (midpoint 𝕜 p₁ p₂) p₁ = ‖(2 : 𝕜)‖⁻¹ * dist p₁ p₂ := by |
rw [dist_comm, dist_left_midpoint]
|
/-
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]
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]
#align affine_map.line_map_eq_line_map_iff AffineMap.lineMap_eq_lineMap_iff
@[simp]
theorem lineMap_eq_left_iff [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} {c : k} :
lineMap p₀ p₁ c = p₀ ↔ p₀ = p₁ ∨ c = 0 := by
rw [← @lineMap_eq_lineMap_iff k V1, lineMap_apply_zero]
#align affine_map.line_map_eq_left_iff AffineMap.lineMap_eq_left_iff
@[simp]
theorem lineMap_eq_right_iff [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} {c : k} :
lineMap p₀ p₁ c = p₁ ↔ p₀ = p₁ ∨ c = 1 := by
rw [← @lineMap_eq_lineMap_iff k V1, lineMap_apply_one]
#align affine_map.line_map_eq_right_iff AffineMap.lineMap_eq_right_iff
variable (k)
theorem lineMap_injective [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} (h : p₀ ≠ p₁) :
Function.Injective (lineMap p₀ p₁ : k → P1) := fun _c₁ _c₂ hc =>
(lineMap_eq_lineMap_iff.mp hc).resolve_left h
#align affine_map.line_map_injective AffineMap.lineMap_injective
variable {k}
@[simp]
theorem apply_lineMap (f : P1 →ᵃ[k] P2) (p₀ p₁ : P1) (c : k) :
f (lineMap p₀ p₁ c) = lineMap (f p₀) (f p₁) c := by
simp [lineMap_apply]
#align affine_map.apply_line_map AffineMap.apply_lineMap
@[simp]
theorem comp_lineMap (f : P1 →ᵃ[k] P2) (p₀ p₁ : P1) :
f.comp (lineMap p₀ p₁) = lineMap (f p₀) (f p₁) :=
ext <| f.apply_lineMap p₀ p₁
#align affine_map.comp_line_map AffineMap.comp_lineMap
@[simp]
theorem fst_lineMap (p₀ p₁ : P1 × P2) (c : k) : (lineMap p₀ p₁ c).1 = lineMap p₀.1 p₁.1 c :=
fst.apply_lineMap p₀ p₁ c
#align affine_map.fst_line_map AffineMap.fst_lineMap
@[simp]
theorem snd_lineMap (p₀ p₁ : P1 × P2) (c : k) : (lineMap p₀ p₁ c).2 = lineMap p₀.2 p₁.2 c :=
snd.apply_lineMap p₀ p₁ c
#align affine_map.snd_line_map AffineMap.snd_lineMap
theorem lineMap_symm (p₀ p₁ : P1) :
lineMap p₀ p₁ = (lineMap p₁ p₀).comp (lineMap (1 : k) (0 : k)) := by
rw [comp_lineMap]
simp
#align affine_map.line_map_symm AffineMap.lineMap_symm
theorem lineMap_apply_one_sub (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ (1 - c) = lineMap p₁ p₀ c := by
rw [lineMap_symm p₀, comp_apply]
congr
simp [lineMap_apply]
#align affine_map.line_map_apply_one_sub AffineMap.lineMap_apply_one_sub
@[simp]
theorem lineMap_vsub_left (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c -ᵥ p₀ = c • (p₁ -ᵥ p₀) :=
vadd_vsub _ _
#align affine_map.line_map_vsub_left AffineMap.lineMap_vsub_left
@[simp]
theorem left_vsub_lineMap (p₀ p₁ : P1) (c : k) : p₀ -ᵥ lineMap p₀ p₁ c = c • (p₀ -ᵥ p₁) := by
rw [← neg_vsub_eq_vsub_rev, lineMap_vsub_left, ← smul_neg, neg_vsub_eq_vsub_rev]
#align affine_map.left_vsub_line_map AffineMap.left_vsub_lineMap
@[simp]
theorem lineMap_vsub_right (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c -ᵥ p₁ = (1 - c) • (p₀ -ᵥ p₁) := by
rw [← lineMap_apply_one_sub, lineMap_vsub_left]
#align affine_map.line_map_vsub_right AffineMap.lineMap_vsub_right
@[simp]
theorem right_vsub_lineMap (p₀ p₁ : P1) (c : k) : p₁ -ᵥ lineMap p₀ p₁ c = (1 - c) • (p₁ -ᵥ p₀) := by
rw [← lineMap_apply_one_sub, left_vsub_lineMap]
#align affine_map.right_vsub_line_map AffineMap.right_vsub_lineMap
theorem lineMap_vadd_lineMap (v₁ v₂ : V1) (p₁ p₂ : P1) (c : k) :
lineMap v₁ v₂ c +ᵥ lineMap p₁ p₂ c = lineMap (v₁ +ᵥ p₁) (v₂ +ᵥ p₂) c :=
((fst : V1 × P1 →ᵃ[k] V1) +ᵥ (snd : V1 × P1 →ᵃ[k] P1)).apply_lineMap (v₁, p₁) (v₂, p₂) c
#align affine_map.line_map_vadd_line_map AffineMap.lineMap_vadd_lineMap
theorem lineMap_vsub_lineMap (p₁ p₂ p₃ p₄ : P1) (c : k) :
lineMap p₁ p₂ c -ᵥ lineMap p₃ p₄ c = lineMap (p₁ -ᵥ p₃) (p₂ -ᵥ p₄) c :=
((fst : P1 × P1 →ᵃ[k] P1) -ᵥ (snd : P1 × P1 →ᵃ[k] P1)).apply_lineMap (_, _) (_, _) c
#align affine_map.line_map_vsub_line_map AffineMap.lineMap_vsub_lineMap
/-- Decomposition of an affine map in the special case when the point space and vector space
are the same. -/
theorem decomp (f : V1 →ᵃ[k] V2) : (f : V1 → V2) = ⇑f.linear + fun _ => f 0 := by
ext x
calc
f x = f.linear x +ᵥ f 0 := by rw [← f.map_vadd, vadd_eq_add, add_zero]
_ = (f.linear + fun _ : V1 => f 0) x := rfl
#align affine_map.decomp AffineMap.decomp
/-- Decomposition of an affine map in the special case when the point space and vector space
are the same. -/
theorem decomp' (f : V1 →ᵃ[k] V2) : (f.linear : V1 → V2) = ⇑f - fun _ => f 0 := by
rw [decomp]
simp only [LinearMap.map_zero, Pi.add_apply, add_sub_cancel_right, zero_add]
#align affine_map.decomp' AffineMap.decomp'
theorem image_uIcc {k : Type*} [LinearOrderedField k] (f : k →ᵃ[k] k) (a b : k) :
f '' Set.uIcc a b = Set.uIcc (f a) (f b) := by
have : ⇑f = (fun x => x + f 0) ∘ fun x => x * (f 1 - f 0) := by
ext x
change f x = x • (f 1 -ᵥ f 0) +ᵥ f 0
rw [← f.linearMap_vsub, ← f.linear.map_smul, ← f.map_vadd]
simp only [vsub_eq_sub, add_zero, mul_one, vadd_eq_add, sub_zero, smul_eq_mul]
rw [this, Set.image_comp]
simp only [Set.image_add_const_uIcc, Set.image_mul_const_uIcc, Function.comp_apply]
#align affine_map.image_uIcc AffineMap.image_uIcc
section
variable {ι : Type*} {V : ι → Type*} {P : ι → Type*} [∀ i, AddCommGroup (V i)]
[∀ i, Module k (V i)] [∀ i, AddTorsor (V i) (P i)]
/-- Evaluation at a point as an affine map. -/
def proj (i : ι) : (∀ i : ι, P i) →ᵃ[k] P i where
toFun f := f i
linear := @LinearMap.proj k ι _ V _ _ i
map_vadd' _ _ := rfl
#align affine_map.proj AffineMap.proj
@[simp]
theorem proj_apply (i : ι) (f : ∀ i, P i) : @proj k _ ι V P _ _ _ i f = f i :=
rfl
#align affine_map.proj_apply AffineMap.proj_apply
@[simp]
theorem proj_linear (i : ι) : (@proj k _ ι V P _ _ _ i).linear = @LinearMap.proj k ι _ V _ _ i :=
rfl
#align affine_map.proj_linear AffineMap.proj_linear
theorem pi_lineMap_apply (f g : ∀ i, P i) (c : k) (i : ι) :
lineMap f g c i = lineMap (f i) (g i) c :=
(proj i : (∀ i, P i) →ᵃ[k] P i).apply_lineMap f g c
#align affine_map.pi_line_map_apply AffineMap.pi_lineMap_apply
end
end AffineMap
namespace AffineMap
variable {R k V1 P1 V2 P2 V3 P3 : Type*}
section Ring
variable [Ring k] [AddCommGroup V1] [AffineSpace V1 P1] [AddCommGroup V2] [AffineSpace V2 P2]
variable [AddCommGroup V3] [AffineSpace V3 P3] [Module k V1] [Module k V2] [Module k V3]
section DistribMulAction
variable [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 distribMulAction : DistribMulAction R (P1 →ᵃ[k] V2) where
smul_add _ _ _ := ext fun _ => smul_add _ _ _
smul_zero _ := ext fun _ => smul_zero _
end DistribMulAction
section Module
variable [Semiring R] [Module R V2] [SMulCommClass k R V2]
/-- The space of affine maps taking values in an `R`-module is an `R`-module. -/
instance : Module R (P1 →ᵃ[k] V2) :=
{ AffineMap.distribMulAction with
add_smul := fun _ _ _ => ext fun _ => add_smul _ _ _
zero_smul := fun _ => ext fun _ => zero_smul _ _ }
variable (R)
/-- The space of affine maps between two modules is linearly equivalent to the product of the
domain with the space of linear maps, by taking the value of the affine map at `(0 : V1)` and the
linear part.
See note [bundled maps over different rings]-/
@[simps]
def toConstProdLinearMap : (V1 →ᵃ[k] V2) ≃ₗ[R] V2 × (V1 →ₗ[k] V2) where
toFun f := ⟨f 0, f.linear⟩
invFun p := p.2.toAffineMap + const k V1 p.1
left_inv f := by
ext
rw [f.decomp]
simp [const_apply _ _] -- Porting note: `simp` needs `_`s to use this lemma
right_inv := by
rintro ⟨v, f⟩
ext <;> simp [const_apply _ _, const_linear _ _] -- Porting note: `simp` needs `_`s
map_add' := by simp
map_smul' := by simp
#align affine_map.to_const_prod_linear_map AffineMap.toConstProdLinearMap
end Module
section Pi
variable {ι : Type*} {φv φp : ι → Type*} [(i : ι) → AddCommGroup (φv i)]
[(i : ι) → Module k (φv i)] [(i : ι) → AffineSpace (φv i) (φp i)]
/-- `pi` construction for affine maps. From a family of affine maps it produces an affine
map into a family of affine spaces.
This is the affine version of `LinearMap.pi`.
-/
def pi (f : (i : ι) → (P1 →ᵃ[k] φp i)) : P1 →ᵃ[k] ((i : ι) → φp i) where
toFun m a := f a m
linear := LinearMap.pi (fun a ↦ (f a).linear)
map_vadd' _ _ := funext fun _ ↦ map_vadd _ _ _
--fp for when the image is a dependent AffineSpace φp i, fv for when the
--image is a Module φv i, f' for when the image isn't dependent.
variable (fp : (i : ι) → (P1 →ᵃ[k] φp i)) (fv : (i : ι) → (P1 →ᵃ[k] φv i))
(f' : ι → P1 →ᵃ[k] P2)
@[simp]
theorem pi_apply (c : P1) (i : ι) : pi fp c i = fp i c :=
rfl
theorem pi_comp (g : P3 →ᵃ[k] P1) : (pi fp).comp g = pi (fun i => (fp i).comp g) :=
rfl
theorem pi_eq_zero : pi fv = 0 ↔ ∀ i, fv i = 0 := by
simp only [AffineMap.ext_iff, Function.funext_iff, pi_apply]
exact forall_comm
| Mathlib/LinearAlgebra/AffineSpace/AffineMap.lean | 803 | 804 | theorem pi_zero : pi (fun _ ↦ 0 : (i : ι) → P1 →ᵃ[k] φv i) = 0 := by |
ext; rfl
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Algebra.Constructions
import Mathlib.Topology.Bases
import Mathlib.Topology.UniformSpace.Basic
#align_import topology.uniform_space.cauchy from "leanprover-community/mathlib"@"22131150f88a2d125713ffa0f4693e3355b1eb49"
/-!
# Theory of Cauchy filters in uniform spaces. Complete uniform spaces. Totally bounded subsets.
-/
universe u v
open scoped Classical
open Filter TopologicalSpace Set UniformSpace Function
open scoped Classical
open Uniformity Topology Filter
variable {α : Type u} {β : Type v} [uniformSpace : UniformSpace α]
/-- A filter `f` is Cauchy if for every entourage `r`, there exists an
`s ∈ f` such that `s × s ⊆ r`. This is a generalization of Cauchy
sequences, because if `a : ℕ → α` then the filter of sets containing
cofinitely many of the `a n` is Cauchy iff `a` is a Cauchy sequence. -/
def Cauchy (f : Filter α) :=
NeBot f ∧ f ×ˢ f ≤ 𝓤 α
#align cauchy Cauchy
/-- A set `s` is called *complete*, if any Cauchy filter `f` such that `s ∈ f`
has a limit in `s` (formally, it satisfies `f ≤ 𝓝 x` for some `x ∈ s`). -/
def IsComplete (s : Set α) :=
∀ f, Cauchy f → f ≤ 𝓟 s → ∃ x ∈ s, f ≤ 𝓝 x
#align is_complete IsComplete
theorem Filter.HasBasis.cauchy_iff {ι} {p : ι → Prop} {s : ι → Set (α × α)} (h : (𝓤 α).HasBasis p s)
{f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ i, p i → ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s i :=
and_congr Iff.rfl <|
(f.basis_sets.prod_self.le_basis_iff h).trans <| by
simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm]
#align filter.has_basis.cauchy_iff Filter.HasBasis.cauchy_iff
theorem cauchy_iff' {f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s :=
(𝓤 α).basis_sets.cauchy_iff
#align cauchy_iff' cauchy_iff'
theorem cauchy_iff {f : Filter α} : Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s :=
cauchy_iff'.trans <| by
simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm]
#align cauchy_iff cauchy_iff
lemma cauchy_iff_le {l : Filter α} [hl : l.NeBot] :
Cauchy l ↔ l ×ˢ l ≤ 𝓤 α := by
simp only [Cauchy, hl, true_and]
theorem Cauchy.ultrafilter_of {l : Filter α} (h : Cauchy l) :
Cauchy (@Ultrafilter.of _ l h.1 : Filter α) := by
haveI := h.1
have := Ultrafilter.of_le l
exact ⟨Ultrafilter.neBot _, (Filter.prod_mono this this).trans h.2⟩
#align cauchy.ultrafilter_of Cauchy.ultrafilter_of
theorem cauchy_map_iff {l : Filter β} {f : β → α} :
Cauchy (l.map f) ↔ NeBot l ∧ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) := by
rw [Cauchy, map_neBot_iff, prod_map_map_eq, Tendsto]
#align cauchy_map_iff cauchy_map_iff
theorem cauchy_map_iff' {l : Filter β} [hl : NeBot l] {f : β → α} :
Cauchy (l.map f) ↔ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) :=
cauchy_map_iff.trans <| and_iff_right hl
#align cauchy_map_iff' cauchy_map_iff'
theorem Cauchy.mono {f g : Filter α} [hg : NeBot g] (h_c : Cauchy f) (h_le : g ≤ f) : Cauchy g :=
⟨hg, le_trans (Filter.prod_mono h_le h_le) h_c.right⟩
#align cauchy.mono Cauchy.mono
theorem Cauchy.mono' {f g : Filter α} (h_c : Cauchy f) (_ : NeBot g) (h_le : g ≤ f) : Cauchy g :=
h_c.mono h_le
#align cauchy.mono' Cauchy.mono'
theorem cauchy_nhds {a : α} : Cauchy (𝓝 a) :=
⟨nhds_neBot, nhds_prod_eq.symm.trans_le (nhds_le_uniformity a)⟩
#align cauchy_nhds cauchy_nhds
theorem cauchy_pure {a : α} : Cauchy (pure a) :=
cauchy_nhds.mono (pure_le_nhds a)
#align cauchy_pure cauchy_pure
theorem Filter.Tendsto.cauchy_map {l : Filter β} [NeBot l] {f : β → α} {a : α}
(h : Tendsto f l (𝓝 a)) : Cauchy (map f l) :=
cauchy_nhds.mono h
#align filter.tendsto.cauchy_map Filter.Tendsto.cauchy_map
lemma Cauchy.mono_uniformSpace {u v : UniformSpace β} {F : Filter β} (huv : u ≤ v)
(hF : Cauchy (uniformSpace := u) F) : Cauchy (uniformSpace := v) F :=
⟨hF.1, hF.2.trans huv⟩
lemma cauchy_inf_uniformSpace {u v : UniformSpace β} {F : Filter β} :
Cauchy (uniformSpace := u ⊓ v) F ↔
Cauchy (uniformSpace := u) F ∧ Cauchy (uniformSpace := v) F := by
unfold Cauchy
rw [inf_uniformity (u := u), le_inf_iff, and_and_left]
lemma cauchy_iInf_uniformSpace {ι : Sort*} [Nonempty ι] {u : ι → UniformSpace β}
{l : Filter β} :
Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by
unfold Cauchy
rw [iInf_uniformity, le_iInf_iff, forall_and, forall_const]
lemma cauchy_iInf_uniformSpace' {ι : Sort*} {u : ι → UniformSpace β}
{l : Filter β} [l.NeBot] :
Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by
simp_rw [cauchy_iff_le (uniformSpace := _), iInf_uniformity, le_iInf_iff]
lemma cauchy_comap_uniformSpace {u : UniformSpace β} {f : α → β} {l : Filter α} :
Cauchy (uniformSpace := comap f u) l ↔ Cauchy (map f l) := by
simp only [Cauchy, map_neBot_iff, prod_map_map_eq, map_le_iff_le_comap]
rfl
lemma cauchy_prod_iff [UniformSpace β] {F : Filter (α × β)} :
Cauchy F ↔ Cauchy (map Prod.fst F) ∧ Cauchy (map Prod.snd F) := by
simp_rw [instUniformSpaceProd, ← cauchy_comap_uniformSpace, ← cauchy_inf_uniformSpace]
theorem Cauchy.prod [UniformSpace β] {f : Filter α} {g : Filter β} (hf : Cauchy f) (hg : Cauchy g) :
Cauchy (f ×ˢ g) := by
have := hf.1; have := hg.1
simpa [cauchy_prod_iff, hf.1] using ⟨hf, hg⟩
#align cauchy.prod Cauchy.prod
/-- The common part of the proofs of `le_nhds_of_cauchy_adhp` and
`SequentiallyComplete.le_nhds_of_seq_tendsto_nhds`: if for any entourage `s`
one can choose a set `t ∈ f` of diameter `s` such that it contains a point `y`
with `(x, y) ∈ s`, then `f` converges to `x`. -/
theorem le_nhds_of_cauchy_adhp_aux {f : Filter α} {x : α}
(adhs : ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s ∧ ∃ y, (x, y) ∈ s ∧ y ∈ t) : f ≤ 𝓝 x := by
-- Consider a neighborhood `s` of `x`
intro s hs
-- Take an entourage twice smaller than `s`
rcases comp_mem_uniformity_sets (mem_nhds_uniformity_iff_right.1 hs) with ⟨U, U_mem, hU⟩
-- Take a set `t ∈ f`, `t × t ⊆ U`, and a point `y ∈ t` such that `(x, y) ∈ U`
rcases adhs U U_mem with ⟨t, t_mem, ht, y, hxy, hy⟩
apply mem_of_superset t_mem
-- Given a point `z ∈ t`, we have `(x, y) ∈ U` and `(y, z) ∈ t × t ⊆ U`, hence `z ∈ s`
exact fun z hz => hU (prod_mk_mem_compRel hxy (ht <| mk_mem_prod hy hz)) rfl
#align le_nhds_of_cauchy_adhp_aux le_nhds_of_cauchy_adhp_aux
/-- If `x` is an adherent (cluster) point for a Cauchy filter `f`, then it is a limit point
for `f`. -/
theorem le_nhds_of_cauchy_adhp {f : Filter α} {x : α} (hf : Cauchy f) (adhs : ClusterPt x f) :
f ≤ 𝓝 x :=
le_nhds_of_cauchy_adhp_aux
(fun s hs => by
obtain ⟨t, t_mem, ht⟩ : ∃ t ∈ f, t ×ˢ t ⊆ s := (cauchy_iff.1 hf).2 s hs
use t, t_mem, ht
exact forall_mem_nonempty_iff_neBot.2 adhs _ (inter_mem_inf (mem_nhds_left x hs) t_mem))
#align le_nhds_of_cauchy_adhp le_nhds_of_cauchy_adhp
theorem le_nhds_iff_adhp_of_cauchy {f : Filter α} {x : α} (hf : Cauchy f) :
f ≤ 𝓝 x ↔ ClusterPt x f :=
⟨fun h => ClusterPt.of_le_nhds' h hf.1, le_nhds_of_cauchy_adhp hf⟩
#align le_nhds_iff_adhp_of_cauchy le_nhds_iff_adhp_of_cauchy
nonrec theorem Cauchy.map [UniformSpace β] {f : Filter α} {m : α → β} (hf : Cauchy f)
(hm : UniformContinuous m) : Cauchy (map m f) :=
⟨hf.1.map _,
calc
map m f ×ˢ map m f = map (Prod.map m m) (f ×ˢ f) := Filter.prod_map_map_eq
_ ≤ Filter.map (Prod.map m m) (𝓤 α) := map_mono hf.right
_ ≤ 𝓤 β := hm⟩
#align cauchy.map Cauchy.map
nonrec theorem Cauchy.comap [UniformSpace β] {f : Filter β} {m : α → β} (hf : Cauchy f)
(hm : comap (fun p : α × α => (m p.1, m p.2)) (𝓤 β) ≤ 𝓤 α) [NeBot (comap m f)] :
Cauchy (comap m f) :=
⟨‹_›,
calc
comap m f ×ˢ comap m f = comap (Prod.map m m) (f ×ˢ f) := prod_comap_comap_eq
_ ≤ comap (Prod.map m m) (𝓤 β) := comap_mono hf.right
_ ≤ 𝓤 α := hm⟩
#align cauchy.comap Cauchy.comap
theorem Cauchy.comap' [UniformSpace β] {f : Filter β} {m : α → β} (hf : Cauchy f)
(hm : Filter.comap (fun p : α × α => (m p.1, m p.2)) (𝓤 β) ≤ 𝓤 α)
(_ : NeBot (Filter.comap m f)) : Cauchy (Filter.comap m f) :=
hf.comap hm
#align cauchy.comap' Cauchy.comap'
/-- Cauchy sequences. Usually defined on ℕ, but often it is also useful to say that a function
defined on ℝ is Cauchy at +∞ to deduce convergence. Therefore, we define it in a type class that
is general enough to cover both ℕ and ℝ, which are the main motivating examples. -/
def CauchySeq [Preorder β] (u : β → α) :=
Cauchy (atTop.map u)
#align cauchy_seq CauchySeq
theorem CauchySeq.tendsto_uniformity [Preorder β] {u : β → α} (h : CauchySeq u) :
Tendsto (Prod.map u u) atTop (𝓤 α) := by
simpa only [Tendsto, prod_map_map_eq', prod_atTop_atTop_eq] using h.right
#align cauchy_seq.tendsto_uniformity CauchySeq.tendsto_uniformity
theorem CauchySeq.nonempty [Preorder β] {u : β → α} (hu : CauchySeq u) : Nonempty β :=
@nonempty_of_neBot _ _ <| (map_neBot_iff _).1 hu.1
#align cauchy_seq.nonempty CauchySeq.nonempty
theorem CauchySeq.mem_entourage {β : Type*} [SemilatticeSup β] {u : β → α} (h : CauchySeq u)
{V : Set (α × α)} (hV : V ∈ 𝓤 α) : ∃ k₀, ∀ i j, k₀ ≤ i → k₀ ≤ j → (u i, u j) ∈ V := by
haveI := h.nonempty
have := h.tendsto_uniformity; rw [← prod_atTop_atTop_eq] at this
simpa [MapsTo] using atTop_basis.prod_self.tendsto_left_iff.1 this V hV
#align cauchy_seq.mem_entourage CauchySeq.mem_entourage
theorem Filter.Tendsto.cauchySeq [SemilatticeSup β] [Nonempty β] {f : β → α} {x}
(hx : Tendsto f atTop (𝓝 x)) : CauchySeq f :=
hx.cauchy_map
#align filter.tendsto.cauchy_seq Filter.Tendsto.cauchySeq
theorem cauchySeq_const [SemilatticeSup β] [Nonempty β] (x : α) : CauchySeq fun _ : β => x :=
tendsto_const_nhds.cauchySeq
#align cauchy_seq_const cauchySeq_const
theorem cauchySeq_iff_tendsto [Nonempty β] [SemilatticeSup β] {u : β → α} :
CauchySeq u ↔ Tendsto (Prod.map u u) atTop (𝓤 α) :=
cauchy_map_iff'.trans <| by simp only [prod_atTop_atTop_eq, Prod.map_def]
#align cauchy_seq_iff_tendsto cauchySeq_iff_tendsto
theorem CauchySeq.comp_tendsto {γ} [Preorder β] [SemilatticeSup γ] [Nonempty γ] {f : β → α}
(hf : CauchySeq f) {g : γ → β} (hg : Tendsto g atTop atTop) : CauchySeq (f ∘ g) :=
⟨inferInstance, le_trans (prod_le_prod.mpr ⟨Tendsto.comp le_rfl hg, Tendsto.comp le_rfl hg⟩) hf.2⟩
#align cauchy_seq.comp_tendsto CauchySeq.comp_tendsto
theorem CauchySeq.comp_injective [SemilatticeSup β] [NoMaxOrder β] [Nonempty β] {u : ℕ → α}
(hu : CauchySeq u) {f : β → ℕ} (hf : Injective f) : CauchySeq (u ∘ f) :=
hu.comp_tendsto <| Nat.cofinite_eq_atTop ▸ hf.tendsto_cofinite.mono_left atTop_le_cofinite
#align cauchy_seq.comp_injective CauchySeq.comp_injective
theorem Function.Bijective.cauchySeq_comp_iff {f : ℕ → ℕ} (hf : Bijective f) (u : ℕ → α) :
CauchySeq (u ∘ f) ↔ CauchySeq u := by
refine ⟨fun H => ?_, fun H => H.comp_injective hf.injective⟩
lift f to ℕ ≃ ℕ using hf
simpa only [(· ∘ ·), f.apply_symm_apply] using H.comp_injective f.symm.injective
#align function.bijective.cauchy_seq_comp_iff Function.Bijective.cauchySeq_comp_iff
theorem CauchySeq.subseq_subseq_mem {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α}
(hu : CauchySeq u) {f g : ℕ → ℕ} (hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, ((u ∘ f ∘ φ) n, (u ∘ g ∘ φ) n) ∈ V n := by
rw [cauchySeq_iff_tendsto] at hu
exact ((hu.comp <| hf.prod_atTop hg).comp tendsto_atTop_diagonal).subseq_mem hV
#align cauchy_seq.subseq_subseq_mem CauchySeq.subseq_subseq_mem
-- todo: generalize this and other lemmas to a nonempty semilattice
theorem cauchySeq_iff' {u : ℕ → α} :
CauchySeq u ↔ ∀ V ∈ 𝓤 α, ∀ᶠ k in atTop, k ∈ Prod.map u u ⁻¹' V :=
cauchySeq_iff_tendsto
#align cauchy_seq_iff' cauchySeq_iff'
theorem cauchySeq_iff {u : ℕ → α} :
CauchySeq u ↔ ∀ V ∈ 𝓤 α, ∃ N, ∀ k ≥ N, ∀ l ≥ N, (u k, u l) ∈ V := by
simp only [cauchySeq_iff', Filter.eventually_atTop_prod_self', mem_preimage, Prod.map_apply]
#align cauchy_seq_iff cauchySeq_iff
theorem CauchySeq.prod_map {γ δ} [UniformSpace β] [Preorder γ] [Preorder δ] {u : γ → α}
{v : δ → β} (hu : CauchySeq u) (hv : CauchySeq v) : CauchySeq (Prod.map u v) := by
simpa only [CauchySeq, prod_map_map_eq', prod_atTop_atTop_eq] using hu.prod hv
#align cauchy_seq.prod_map CauchySeq.prod_map
theorem CauchySeq.prod {γ} [UniformSpace β] [Preorder γ] {u : γ → α} {v : γ → β}
(hu : CauchySeq u) (hv : CauchySeq v) : CauchySeq fun x => (u x, v x) :=
haveI := hu.1.of_map
(Cauchy.prod hu hv).mono (Tendsto.prod_mk le_rfl le_rfl)
#align cauchy_seq.prod CauchySeq.prod
theorem CauchySeq.eventually_eventually [SemilatticeSup β] {u : β → α} (hu : CauchySeq u)
{V : Set (α × α)} (hV : V ∈ 𝓤 α) : ∀ᶠ k in atTop, ∀ᶠ l in atTop, (u k, u l) ∈ V :=
eventually_atTop_curry <| hu.tendsto_uniformity hV
#align cauchy_seq.eventually_eventually CauchySeq.eventually_eventually
theorem UniformContinuous.comp_cauchySeq {γ} [UniformSpace β] [Preorder γ] {f : α → β}
(hf : UniformContinuous f) {u : γ → α} (hu : CauchySeq u) : CauchySeq (f ∘ u) :=
hu.map hf
#align uniform_continuous.comp_cauchy_seq UniformContinuous.comp_cauchySeq
theorem CauchySeq.subseq_mem {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α}
(hu : CauchySeq u) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, (u <| φ (n + 1), u <| φ n) ∈ V n := by
have : ∀ n, ∃ N, ∀ k ≥ N, ∀ l ≥ k, (u l, u k) ∈ V n := fun n => by
rw [cauchySeq_iff] at hu
rcases hu _ (hV n) with ⟨N, H⟩
exact ⟨N, fun k hk l hl => H _ (le_trans hk hl) _ hk⟩
obtain ⟨φ : ℕ → ℕ, φ_extr : StrictMono φ, hφ : ∀ n, ∀ l ≥ φ n, (u l, u <| φ n) ∈ V n⟩ :=
extraction_forall_of_eventually' this
exact ⟨φ, φ_extr, fun n => hφ _ _ (φ_extr <| lt_add_one n).le⟩
#align cauchy_seq.subseq_mem CauchySeq.subseq_mem
theorem Filter.Tendsto.subseq_mem_entourage {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α}
{a : α} (hu : Tendsto u atTop (𝓝 a)) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ (u (φ 0), a) ∈ V 0 ∧
∀ n, (u <| φ (n + 1), u <| φ n) ∈ V (n + 1) := by
rcases mem_atTop_sets.1 (hu (ball_mem_nhds a (symm_le_uniformity <| hV 0))) with ⟨n, hn⟩
rcases (hu.comp (tendsto_add_atTop_nat n)).cauchySeq.subseq_mem fun n => hV (n + 1) with
⟨φ, φ_mono, hφV⟩
exact ⟨fun k => φ k + n, φ_mono.add_const _, hn _ le_add_self, hφV⟩
#align filter.tendsto.subseq_mem_entourage Filter.Tendsto.subseq_mem_entourage
/-- If a Cauchy sequence has a convergent subsequence, then it converges. -/
theorem tendsto_nhds_of_cauchySeq_of_subseq [Preorder β] {u : β → α} (hu : CauchySeq u)
{ι : Type*} {f : ι → β} {p : Filter ι} [NeBot p] (hf : Tendsto f p atTop) {a : α}
(ha : Tendsto (u ∘ f) p (𝓝 a)) : Tendsto u atTop (𝓝 a) :=
le_nhds_of_cauchy_adhp hu (mapClusterPt_of_comp hf ha)
#align tendsto_nhds_of_cauchy_seq_of_subseq tendsto_nhds_of_cauchySeq_of_subseq
/-- Any shift of a Cauchy sequence is also a Cauchy sequence. -/
theorem cauchySeq_shift {u : ℕ → α} (k : ℕ) : CauchySeq (fun n ↦ u (n + k)) ↔ CauchySeq u := by
constructor <;> intro h
· rw [cauchySeq_iff] at h ⊢
intro V mV
obtain ⟨N, h⟩ := h V mV
use N + k
intro a ha b hb
convert h (a - k) (Nat.le_sub_of_add_le ha) (b - k) (Nat.le_sub_of_add_le hb) <;> omega
· exact h.comp_tendsto (tendsto_add_atTop_nat k)
theorem Filter.HasBasis.cauchySeq_iff {γ} [Nonempty β] [SemilatticeSup β] {u : β → α} {p : γ → Prop}
{s : γ → Set (α × α)} (h : (𝓤 α).HasBasis p s) :
CauchySeq u ↔ ∀ i, p i → ∃ N, ∀ m, N ≤ m → ∀ n, N ≤ n → (u m, u n) ∈ s i := by
rw [cauchySeq_iff_tendsto, ← prod_atTop_atTop_eq]
refine (atTop_basis.prod_self.tendsto_iff h).trans ?_
simp only [exists_prop, true_and_iff, MapsTo, preimage, subset_def, Prod.forall, mem_prod_eq,
mem_setOf_eq, mem_Ici, and_imp, Prod.map, ge_iff_le, @forall_swap (_ ≤ _) β]
#align filter.has_basis.cauchy_seq_iff Filter.HasBasis.cauchySeq_iff
theorem Filter.HasBasis.cauchySeq_iff' {γ} [Nonempty β] [SemilatticeSup β] {u : β → α}
{p : γ → Prop} {s : γ → Set (α × α)} (H : (𝓤 α).HasBasis p s) :
CauchySeq u ↔ ∀ i, p i → ∃ N, ∀ n ≥ N, (u n, u N) ∈ s i := by
refine H.cauchySeq_iff.trans ⟨fun h i hi => ?_, fun h i hi => ?_⟩
· exact (h i hi).imp fun N hN n hn => hN n hn N le_rfl
· rcases comp_symm_of_uniformity (H.mem_of_mem hi) with ⟨t, ht, ht', hts⟩
rcases H.mem_iff.1 ht with ⟨j, hj, hjt⟩
refine (h j hj).imp fun N hN m hm n hn => hts ⟨u N, hjt ?_, ht' <| hjt ?_⟩
exacts [hN m hm, hN n hn]
#align filter.has_basis.cauchy_seq_iff' Filter.HasBasis.cauchySeq_iff'
theorem cauchySeq_of_controlled [SemilatticeSup β] [Nonempty β] (U : β → Set (α × α))
(hU : ∀ s ∈ 𝓤 α, ∃ n, U n ⊆ s) {f : β → α}
(hf : ∀ ⦃N m n : β⦄, N ≤ m → N ≤ n → (f m, f n) ∈ U N) : CauchySeq f :=
-- Porting note: changed to semi-implicit arguments
cauchySeq_iff_tendsto.2
(by
intro s hs
rw [mem_map, mem_atTop_sets]
cases' hU s hs with N hN
refine ⟨(N, N), fun mn hmn => ?_⟩
cases' mn with m n
exact hN (hf hmn.1 hmn.2))
#align cauchy_seq_of_controlled cauchySeq_of_controlled
theorem isComplete_iff_clusterPt {s : Set α} :
IsComplete s ↔ ∀ l, Cauchy l → l ≤ 𝓟 s → ∃ x ∈ s, ClusterPt x l :=
forall₃_congr fun _ hl _ => exists_congr fun _ => and_congr_right fun _ =>
le_nhds_iff_adhp_of_cauchy hl
#align is_complete_iff_cluster_pt isComplete_iff_clusterPt
theorem isComplete_iff_ultrafilter {s : Set α} :
IsComplete s ↔ ∀ l : Ultrafilter α, Cauchy (l : Filter α) → ↑l ≤ 𝓟 s → ∃ x ∈ s, ↑l ≤ 𝓝 x := by
refine ⟨fun h l => h l, fun H => isComplete_iff_clusterPt.2 fun l hl hls => ?_⟩
haveI := hl.1
rcases H (Ultrafilter.of l) hl.ultrafilter_of ((Ultrafilter.of_le l).trans hls) with ⟨x, hxs, hxl⟩
exact ⟨x, hxs, (ClusterPt.of_le_nhds hxl).mono (Ultrafilter.of_le l)⟩
#align is_complete_iff_ultrafilter isComplete_iff_ultrafilter
theorem isComplete_iff_ultrafilter' {s : Set α} :
IsComplete s ↔ ∀ l : Ultrafilter α, Cauchy (l : Filter α) → s ∈ l → ∃ x ∈ s, ↑l ≤ 𝓝 x :=
isComplete_iff_ultrafilter.trans <| by simp only [le_principal_iff, Ultrafilter.mem_coe]
#align is_complete_iff_ultrafilter' isComplete_iff_ultrafilter'
protected theorem IsComplete.union {s t : Set α} (hs : IsComplete s) (ht : IsComplete t) :
IsComplete (s ∪ t) := by
simp only [isComplete_iff_ultrafilter', Ultrafilter.union_mem_iff, or_imp] at *
exact fun l hl =>
⟨fun hsl => (hs l hl hsl).imp fun x hx => ⟨Or.inl hx.1, hx.2⟩, fun htl =>
(ht l hl htl).imp fun x hx => ⟨Or.inr hx.1, hx.2⟩⟩
#align is_complete.union IsComplete.union
theorem isComplete_iUnion_separated {ι : Sort*} {s : ι → Set α} (hs : ∀ i, IsComplete (s i))
{U : Set (α × α)} (hU : U ∈ 𝓤 α) (hd : ∀ (i j : ι), ∀ x ∈ s i, ∀ y ∈ s j, (x, y) ∈ U → i = j) :
IsComplete (⋃ i, s i) := by
set S := ⋃ i, s i
intro l hl hls
rw [le_principal_iff] at hls
cases' cauchy_iff.1 hl with hl_ne hl'
obtain ⟨t, htS, htl, htU⟩ : ∃ t, t ⊆ S ∧ t ∈ l ∧ t ×ˢ t ⊆ U := by
rcases hl' U hU with ⟨t, htl, htU⟩
refine ⟨t ∩ S, inter_subset_right, inter_mem htl hls, Subset.trans ?_ htU⟩
gcongr <;> apply inter_subset_left
obtain ⟨i, hi⟩ : ∃ i, t ⊆ s i := by
rcases Filter.nonempty_of_mem htl with ⟨x, hx⟩
rcases mem_iUnion.1 (htS hx) with ⟨i, hi⟩
refine ⟨i, fun y hy => ?_⟩
rcases mem_iUnion.1 (htS hy) with ⟨j, hj⟩
rwa [hd i j x hi y hj (htU <| mk_mem_prod hx hy)]
rcases hs i l hl (le_principal_iff.2 <| mem_of_superset htl hi) with ⟨x, hxs, hlx⟩
exact ⟨x, mem_iUnion.2 ⟨i, hxs⟩, hlx⟩
#align is_complete_Union_separated isComplete_iUnion_separated
/-- A complete space is defined here using uniformities. A uniform space
is complete if every Cauchy filter converges. -/
class CompleteSpace (α : Type u) [UniformSpace α] : Prop where
/-- In a complete uniform space, every Cauchy filter converges. -/
complete : ∀ {f : Filter α}, Cauchy f → ∃ x, f ≤ 𝓝 x
#align complete_space CompleteSpace
theorem complete_univ {α : Type u} [UniformSpace α] [CompleteSpace α] :
IsComplete (univ : Set α) := fun f hf _ => by
rcases CompleteSpace.complete hf with ⟨x, hx⟩
exact ⟨x, mem_univ x, hx⟩
#align complete_univ complete_univ
instance CompleteSpace.prod [UniformSpace β] [CompleteSpace α] [CompleteSpace β] :
CompleteSpace (α × β) where
complete hf :=
let ⟨x1, hx1⟩ := CompleteSpace.complete <| hf.map uniformContinuous_fst
let ⟨x2, hx2⟩ := CompleteSpace.complete <| hf.map uniformContinuous_snd
⟨(x1, x2), by rw [nhds_prod_eq, le_prod]; constructor <;> assumption⟩
#align complete_space.prod CompleteSpace.prod
lemma CompleteSpace.fst_of_prod [UniformSpace β] [CompleteSpace (α × β)] [h : Nonempty β] :
CompleteSpace α where
complete hf :=
let ⟨y⟩ := h
let ⟨(a, b), hab⟩ := CompleteSpace.complete <| hf.prod <| cauchy_pure (a := y)
⟨a, by simpa only [map_fst_prod, nhds_prod_eq] using map_mono (m := Prod.fst) hab⟩
lemma CompleteSpace.snd_of_prod [UniformSpace β] [CompleteSpace (α × β)] [h : Nonempty α] :
CompleteSpace β where
complete hf :=
let ⟨x⟩ := h
let ⟨(a, b), hab⟩ := CompleteSpace.complete <| (cauchy_pure (a := x)).prod hf
⟨b, by simpa only [map_snd_prod, nhds_prod_eq] using map_mono (m := Prod.snd) hab⟩
lemma completeSpace_prod_of_nonempty [UniformSpace β] [Nonempty α] [Nonempty β] :
CompleteSpace (α × β) ↔ CompleteSpace α ∧ CompleteSpace β :=
⟨fun _ ↦ ⟨.fst_of_prod (β := β), .snd_of_prod (α := α)⟩, fun ⟨_, _⟩ ↦ .prod⟩
@[to_additive]
instance CompleteSpace.mulOpposite [CompleteSpace α] : CompleteSpace αᵐᵒᵖ where
complete hf :=
MulOpposite.op_surjective.exists.mpr <|
let ⟨x, hx⟩ := CompleteSpace.complete (hf.map MulOpposite.uniformContinuous_unop)
⟨x, (map_le_iff_le_comap.mp hx).trans_eq <| MulOpposite.comap_unop_nhds _⟩
#align complete_space.mul_opposite CompleteSpace.mulOpposite
#align complete_space.add_opposite CompleteSpace.addOpposite
/-- If `univ` is complete, the space is a complete space -/
theorem completeSpace_of_isComplete_univ (h : IsComplete (univ : Set α)) : CompleteSpace α :=
⟨fun hf => let ⟨x, _, hx⟩ := h _ hf ((@principal_univ α).symm ▸ le_top); ⟨x, hx⟩⟩
#align complete_space_of_is_complete_univ completeSpace_of_isComplete_univ
theorem completeSpace_iff_isComplete_univ : CompleteSpace α ↔ IsComplete (univ : Set α) :=
⟨@complete_univ α _, completeSpace_of_isComplete_univ⟩
#align complete_space_iff_is_complete_univ completeSpace_iff_isComplete_univ
theorem completeSpace_iff_ultrafilter :
CompleteSpace α ↔ ∀ l : Ultrafilter α, Cauchy (l : Filter α) → ∃ x : α, ↑l ≤ 𝓝 x := by
simp [completeSpace_iff_isComplete_univ, isComplete_iff_ultrafilter]
#align complete_space_iff_ultrafilter completeSpace_iff_ultrafilter
theorem cauchy_iff_exists_le_nhds [CompleteSpace α] {l : Filter α} [NeBot l] :
Cauchy l ↔ ∃ x, l ≤ 𝓝 x :=
⟨CompleteSpace.complete, fun ⟨_, hx⟩ => cauchy_nhds.mono hx⟩
#align cauchy_iff_exists_le_nhds cauchy_iff_exists_le_nhds
theorem cauchy_map_iff_exists_tendsto [CompleteSpace α] {l : Filter β} {f : β → α} [NeBot l] :
Cauchy (l.map f) ↔ ∃ x, Tendsto f l (𝓝 x) :=
cauchy_iff_exists_le_nhds
#align cauchy_map_iff_exists_tendsto cauchy_map_iff_exists_tendsto
/-- A Cauchy sequence in a complete space converges -/
theorem cauchySeq_tendsto_of_complete [Preorder β] [CompleteSpace α] {u : β → α}
(H : CauchySeq u) : ∃ x, Tendsto u atTop (𝓝 x) :=
CompleteSpace.complete H
#align cauchy_seq_tendsto_of_complete cauchySeq_tendsto_of_complete
/-- If `K` is a complete subset, then any cauchy sequence in `K` converges to a point in `K` -/
theorem cauchySeq_tendsto_of_isComplete [Preorder β] {K : Set α} (h₁ : IsComplete K)
{u : β → α} (h₂ : ∀ n, u n ∈ K) (h₃ : CauchySeq u) : ∃ v ∈ K, Tendsto u atTop (𝓝 v) :=
h₁ _ h₃ <| le_principal_iff.2 <| mem_map_iff_exists_image.2
⟨univ, univ_mem, by rwa [image_univ, range_subset_iff]⟩
#align cauchy_seq_tendsto_of_is_complete cauchySeq_tendsto_of_isComplete
theorem Cauchy.le_nhds_lim [CompleteSpace α] {f : Filter α} (hf : Cauchy f) :
haveI := hf.1.nonempty; f ≤ 𝓝 (lim f) :=
_root_.le_nhds_lim (CompleteSpace.complete hf)
set_option linter.uppercaseLean3 false in
#align cauchy.le_nhds_Lim Cauchy.le_nhds_lim
theorem CauchySeq.tendsto_limUnder [Preorder β] [CompleteSpace α] {u : β → α} (h : CauchySeq u) :
haveI := h.1.nonempty; Tendsto u atTop (𝓝 <| limUnder atTop u) :=
h.le_nhds_lim
#align cauchy_seq.tendsto_lim CauchySeq.tendsto_limUnder
theorem IsClosed.isComplete [CompleteSpace α] {s : Set α} (h : IsClosed s) : IsComplete s :=
fun _ cf fs =>
let ⟨x, hx⟩ := CompleteSpace.complete cf
⟨x, isClosed_iff_clusterPt.mp h x (cf.left.mono (le_inf hx fs)), hx⟩
#align is_closed.is_complete IsClosed.isComplete
/-- A set `s` is totally bounded if for every entourage `d` there is a finite
set of points `t` such that every element of `s` is `d`-near to some element of `t`. -/
def TotallyBounded (s : Set α) : Prop :=
∀ d ∈ 𝓤 α, ∃ t : Set α, t.Finite ∧ s ⊆ ⋃ y ∈ t, { x | (x, y) ∈ d }
#align totally_bounded TotallyBounded
theorem TotallyBounded.exists_subset {s : Set α} (hs : TotallyBounded s) {U : Set (α × α)}
(hU : U ∈ 𝓤 α) : ∃ t, t ⊆ s ∧ Set.Finite t ∧ s ⊆ ⋃ y ∈ t, { x | (x, y) ∈ U } := by
rcases comp_symm_of_uniformity hU with ⟨r, hr, rs, rU⟩
rcases hs r hr with ⟨k, fk, ks⟩
let u := k ∩ { y | ∃ x ∈ s, (x, y) ∈ r }
choose f hfs hfr using fun x : u => x.coe_prop.2
refine ⟨range f, ?_, ?_, ?_⟩
· exact range_subset_iff.2 hfs
· haveI : Fintype u := (fk.inter_of_left _).fintype
exact finite_range f
· intro x xs
obtain ⟨y, hy, xy⟩ := mem_iUnion₂.1 (ks xs)
rw [biUnion_range, mem_iUnion]
set z : ↥u := ⟨y, hy, ⟨x, xs, xy⟩⟩
exact ⟨z, rU <| mem_compRel.2 ⟨y, xy, rs (hfr z)⟩⟩
#align totally_bounded.exists_subset TotallyBounded.exists_subset
theorem totallyBounded_iff_subset {s : Set α} :
TotallyBounded s ↔
∀ d ∈ 𝓤 α, ∃ t, t ⊆ s ∧ Set.Finite t ∧ s ⊆ ⋃ y ∈ t, { x | (x, y) ∈ d } :=
⟨fun H _ hd => H.exists_subset hd, fun H d hd =>
let ⟨t, _, ht⟩ := H d hd
⟨t, ht⟩⟩
#align totally_bounded_iff_subset totallyBounded_iff_subset
theorem Filter.HasBasis.totallyBounded_iff {ι} {p : ι → Prop} {U : ι → Set (α × α)}
(H : (𝓤 α).HasBasis p U) {s : Set α} :
TotallyBounded s ↔ ∀ i, p i → ∃ t : Set α, Set.Finite t ∧ s ⊆ ⋃ y ∈ t, { x | (x, y) ∈ U i } :=
H.forall_iff fun _ _ hUV h =>
h.imp fun _ ht => ⟨ht.1, ht.2.trans <| iUnion₂_mono fun _ _ _ hy => hUV hy⟩
#align filter.has_basis.totally_bounded_iff Filter.HasBasis.totallyBounded_iff
theorem totallyBounded_of_forall_symm {s : Set α}
(h : ∀ V ∈ 𝓤 α, SymmetricRel V → ∃ t : Set α, Set.Finite t ∧ s ⊆ ⋃ y ∈ t, ball y V) :
TotallyBounded s :=
UniformSpace.hasBasis_symmetric.totallyBounded_iff.2 fun V hV => by
simpa only [ball_eq_of_symmetry hV.2] using h V hV.1 hV.2
#align totally_bounded_of_forall_symm totallyBounded_of_forall_symm
theorem totallyBounded_subset {s₁ s₂ : Set α} (hs : s₁ ⊆ s₂) (h : TotallyBounded s₂) :
TotallyBounded s₁ := fun d hd =>
let ⟨t, ht₁, ht₂⟩ := h d hd
⟨t, ht₁, Subset.trans hs ht₂⟩
#align totally_bounded_subset totallyBounded_subset
theorem totallyBounded_empty : TotallyBounded (∅ : Set α) := fun _ _ =>
⟨∅, finite_empty, empty_subset _⟩
#align totally_bounded_empty totallyBounded_empty
/-- The closure of a totally bounded set is totally bounded. -/
theorem TotallyBounded.closure {s : Set α} (h : TotallyBounded s) : TotallyBounded (closure s) :=
uniformity_hasBasis_closed.totallyBounded_iff.2 fun V hV =>
let ⟨t, htf, hst⟩ := h V hV.1
⟨t, htf,
closure_minimal hst <|
htf.isClosed_biUnion fun _ _ => hV.2.preimage (continuous_id.prod_mk continuous_const)⟩
#align totally_bounded.closure TotallyBounded.closure
/-- The image of a totally bounded set under a uniformly continuous map is totally bounded. -/
theorem TotallyBounded.image [UniformSpace β] {f : α → β} {s : Set α} (hs : TotallyBounded s)
(hf : UniformContinuous f) : TotallyBounded (f '' s) := fun t ht =>
have : { p : α × α | (f p.1, f p.2) ∈ t } ∈ 𝓤 α := hf ht
let ⟨c, hfc, hct⟩ := hs _ this
⟨f '' c, hfc.image f, by
simp only [mem_image, iUnion_exists, biUnion_and', iUnion_iUnion_eq_right, image_subset_iff,
preimage_iUnion, preimage_setOf_eq]
simp? [subset_def] at hct says
simp only [mem_setOf_eq, subset_def, mem_iUnion, exists_prop] at hct
intro x hx; simp
exact hct x hx⟩
#align totally_bounded.image TotallyBounded.image
theorem Ultrafilter.cauchy_of_totallyBounded {s : Set α} (f : Ultrafilter α) (hs : TotallyBounded s)
(h : ↑f ≤ 𝓟 s) : Cauchy (f : Filter α) :=
⟨f.neBot', fun _ ht =>
let ⟨t', ht'₁, ht'_symm, ht'_t⟩ := comp_symm_of_uniformity ht
let ⟨i, hi, hs_union⟩ := hs t' ht'₁
have : (⋃ y ∈ i, { x | (x, y) ∈ t' }) ∈ f := mem_of_superset (le_principal_iff.mp h) hs_union
have : ∃ y ∈ i, { x | (x, y) ∈ t' } ∈ f := (Ultrafilter.finite_biUnion_mem_iff hi).1 this
let ⟨y, _, hif⟩ := this
have : { x | (x, y) ∈ t' } ×ˢ { x | (x, y) ∈ t' } ⊆ compRel t' t' :=
fun ⟨_, _⟩ ⟨(h₁ : (_, y) ∈ t'), (h₂ : (_, y) ∈ t')⟩ => ⟨y, h₁, ht'_symm h₂⟩
mem_of_superset (prod_mem_prod hif hif) (Subset.trans this ht'_t)⟩
#align ultrafilter.cauchy_of_totally_bounded Ultrafilter.cauchy_of_totallyBounded
theorem totallyBounded_iff_filter {s : Set α} :
TotallyBounded s ↔ ∀ f, NeBot f → f ≤ 𝓟 s → ∃ c ≤ f, Cauchy c := by
constructor
· exact fun H f hf hfs => ⟨Ultrafilter.of f, Ultrafilter.of_le f,
(Ultrafilter.of f).cauchy_of_totallyBounded H ((Ultrafilter.of_le f).trans hfs)⟩
· intro H d hd
contrapose! H with hd_cover
set f := ⨅ t : Finset α, 𝓟 (s \ ⋃ y ∈ t, { x | (x, y) ∈ d })
have hb : HasAntitoneBasis f fun t : Finset α ↦ s \ ⋃ y ∈ t, { x | (x, y) ∈ d } :=
.iInf_principal fun _ _ ↦ diff_subset_diff_right ∘ biUnion_subset_biUnion_left
have : Filter.NeBot f := hb.1.neBot_iff.2 fun _ ↦
nonempty_diff.2 <| hd_cover _ (Finset.finite_toSet _)
have : f ≤ 𝓟 s := iInf_le_of_le ∅ (by simp)
refine ⟨f, ‹_›, ‹_›, fun c hcf hc => ?_⟩
rcases mem_prod_same_iff.1 (hc.2 hd) with ⟨m, hm, hmd⟩
rcases hc.1.nonempty_of_mem hm with ⟨y, hym⟩
have : s \ {x | (x, y) ∈ d} ∈ c := by simpa using hcf (hb.mem {y})
rcases hc.1.nonempty_of_mem (inter_mem hm this) with ⟨z, hzm, -, hyz⟩
exact hyz (hmd ⟨hzm, hym⟩)
#align totally_bounded_iff_filter totallyBounded_iff_filter
theorem totallyBounded_iff_ultrafilter {s : Set α} :
TotallyBounded s ↔ ∀ f : Ultrafilter α, ↑f ≤ 𝓟 s → Cauchy (f : Filter α) := by
refine ⟨fun hs f => f.cauchy_of_totallyBounded hs, fun H => totallyBounded_iff_filter.2 ?_⟩
intro f hf hfs
exact ⟨Ultrafilter.of f, Ultrafilter.of_le f, H _ ((Ultrafilter.of_le f).trans hfs)⟩
#align totally_bounded_iff_ultrafilter totallyBounded_iff_ultrafilter
theorem isCompact_iff_totallyBounded_isComplete {s : Set α} :
IsCompact s ↔ TotallyBounded s ∧ IsComplete s :=
⟨fun hs =>
⟨totallyBounded_iff_ultrafilter.2 fun f hf =>
let ⟨_, _, fx⟩ := isCompact_iff_ultrafilter_le_nhds.1 hs f hf
cauchy_nhds.mono fx,
fun f fc fs =>
let ⟨a, as, fa⟩ := @hs f fc.1 fs
⟨a, as, le_nhds_of_cauchy_adhp fc fa⟩⟩,
fun ⟨ht, hc⟩ =>
isCompact_iff_ultrafilter_le_nhds.2 fun f hf =>
hc _ (totallyBounded_iff_ultrafilter.1 ht f hf) hf⟩
#align is_compact_iff_totally_bounded_is_complete isCompact_iff_totallyBounded_isComplete
protected theorem IsCompact.totallyBounded {s : Set α} (h : IsCompact s) : TotallyBounded s :=
(isCompact_iff_totallyBounded_isComplete.1 h).1
#align is_compact.totally_bounded IsCompact.totallyBounded
protected theorem IsCompact.isComplete {s : Set α} (h : IsCompact s) : IsComplete s :=
(isCompact_iff_totallyBounded_isComplete.1 h).2
#align is_compact.is_complete IsCompact.isComplete
-- see Note [lower instance priority]
instance (priority := 100) complete_of_compact {α : Type u} [UniformSpace α] [CompactSpace α] :
CompleteSpace α :=
⟨fun hf => by simpa using (isCompact_iff_totallyBounded_isComplete.1 isCompact_univ).2 _ hf⟩
#align complete_of_compact complete_of_compact
theorem isCompact_of_totallyBounded_isClosed [CompleteSpace α] {s : Set α} (ht : TotallyBounded s)
(hc : IsClosed s) : IsCompact s :=
(@isCompact_iff_totallyBounded_isComplete α _ s).2 ⟨ht, hc.isComplete⟩
#align is_compact_of_totally_bounded_is_closed isCompact_of_totallyBounded_isClosed
/-- Every Cauchy sequence over `ℕ` is totally bounded. -/
theorem CauchySeq.totallyBounded_range {s : ℕ → α} (hs : CauchySeq s) :
TotallyBounded (range s) := by
refine totallyBounded_iff_subset.2 fun a ha => ?_
cases' cauchySeq_iff.1 hs a ha with n hn
refine ⟨s '' { k | k ≤ n }, image_subset_range _ _, (finite_le_nat _).image _, ?_⟩
rw [range_subset_iff, biUnion_image]
intro m
rw [mem_iUnion₂]
rcases le_total m n with hm | hm
exacts [⟨m, hm, refl_mem_uniformity ha⟩, ⟨n, le_refl n, hn m hm n le_rfl⟩]
#align cauchy_seq.totally_bounded_range CauchySeq.totallyBounded_range
/-!
### Sequentially complete space
In this section we prove that a uniform space is complete provided that it is sequentially complete
(i.e., any Cauchy sequence converges) and its uniformity filter admits a countable generating set.
In particular, this applies to (e)metric spaces, see the files `Topology/MetricSpace/EmetricSpace`
and `Topology/MetricSpace/Basic`.
More precisely, we assume that there is a sequence of entourages `U_n` such that any other
entourage includes one of `U_n`. Then any Cauchy filter `f` generates a decreasing sequence of
sets `s_n ∈ f` such that `s_n × s_n ⊆ U_n`. Choose a sequence `x_n∈s_n`. It is easy to show
that this is a Cauchy sequence. If this sequence converges to some `a`, then `f ≤ 𝓝 a`. -/
namespace SequentiallyComplete
variable {f : Filter α} (hf : Cauchy f) {U : ℕ → Set (α × α)} (U_mem : ∀ n, U n ∈ 𝓤 α)
(U_le : ∀ s ∈ 𝓤 α, ∃ n, U n ⊆ s)
open Set Finset
noncomputable section
/-- An auxiliary sequence of sets approximating a Cauchy filter. -/
def setSeqAux (n : ℕ) : { s : Set α // s ∈ f ∧ s ×ˢ s ⊆ U n } :=
-- Porting note: changed `∃ _ : s ∈ f, ..` to `s ∈ f ∧ ..`
Classical.indefiniteDescription _ <| (cauchy_iff.1 hf).2 (U n) (U_mem n)
#align sequentially_complete.set_seq_aux SequentiallyComplete.setSeqAux
/-- Given a Cauchy filter `f` and a sequence `U` of entourages, `set_seq` provides
an antitone sequence of sets `s n ∈ f` such that `s n ×ˢ s n ⊆ U`. -/
def setSeq (n : ℕ) : Set α :=
⋂ m ∈ Set.Iic n, (setSeqAux hf U_mem m).val
#align sequentially_complete.set_seq SequentiallyComplete.setSeq
theorem setSeq_mem (n : ℕ) : setSeq hf U_mem n ∈ f :=
(biInter_mem (finite_le_nat n)).2 fun m _ => (setSeqAux hf U_mem m).2.1
#align sequentially_complete.set_seq_mem SequentiallyComplete.setSeq_mem
theorem setSeq_mono ⦃m n : ℕ⦄ (h : m ≤ n) : setSeq hf U_mem n ⊆ setSeq hf U_mem m :=
biInter_subset_biInter_left <| Iic_subset_Iic.2 h
#align sequentially_complete.set_seq_mono SequentiallyComplete.setSeq_mono
theorem setSeq_sub_aux (n : ℕ) : setSeq hf U_mem n ⊆ setSeqAux hf U_mem n :=
biInter_subset_of_mem right_mem_Iic
#align sequentially_complete.set_seq_sub_aux SequentiallyComplete.setSeq_sub_aux
theorem setSeq_prod_subset {N m n} (hm : N ≤ m) (hn : N ≤ n) :
setSeq hf U_mem m ×ˢ setSeq hf U_mem n ⊆ U N := fun p hp => by
refine (setSeqAux hf U_mem N).2.2 ⟨?_, ?_⟩ <;> apply setSeq_sub_aux
· exact setSeq_mono hf U_mem hm hp.1
· exact setSeq_mono hf U_mem hn hp.2
#align sequentially_complete.set_seq_prod_subset SequentiallyComplete.setSeq_prod_subset
/-- A sequence of points such that `seq n ∈ setSeq n`. Here `setSeq` is an antitone
sequence of sets `setSeq n ∈ f` with diameters controlled by a given sequence
of entourages. -/
def seq (n : ℕ) : α :=
(hf.1.nonempty_of_mem (setSeq_mem hf U_mem n)).choose
#align sequentially_complete.seq SequentiallyComplete.seq
theorem seq_mem (n : ℕ) : seq hf U_mem n ∈ setSeq hf U_mem n :=
(hf.1.nonempty_of_mem (setSeq_mem hf U_mem n)).choose_spec
#align sequentially_complete.seq_mem SequentiallyComplete.seq_mem
theorem seq_pair_mem ⦃N m n : ℕ⦄ (hm : N ≤ m) (hn : N ≤ n) :
(seq hf U_mem m, seq hf U_mem n) ∈ U N :=
setSeq_prod_subset hf U_mem hm hn ⟨seq_mem hf U_mem m, seq_mem hf U_mem n⟩
#align sequentially_complete.seq_pair_mem SequentiallyComplete.seq_pair_mem
theorem seq_is_cauchySeq : CauchySeq <| seq hf U_mem :=
cauchySeq_of_controlled U U_le <| seq_pair_mem hf U_mem
#align sequentially_complete.seq_is_cauchy_seq SequentiallyComplete.seq_is_cauchySeq
/-- If the sequence `SequentiallyComplete.seq` converges to `a`, then `f ≤ 𝓝 a`. -/
theorem le_nhds_of_seq_tendsto_nhds ⦃a : α⦄ (ha : Tendsto (seq hf U_mem) atTop (𝓝 a)) : f ≤ 𝓝 a :=
le_nhds_of_cauchy_adhp_aux
(fun s hs => by
rcases U_le s hs with ⟨m, hm⟩
rcases tendsto_atTop'.1 ha _ (mem_nhds_left a (U_mem m)) with ⟨n, hn⟩
refine
⟨setSeq hf U_mem (max m n), setSeq_mem hf U_mem _, ?_, seq hf U_mem (max m n), ?_,
seq_mem hf U_mem _⟩
· have := le_max_left m n
exact Set.Subset.trans (setSeq_prod_subset hf U_mem this this) hm
· exact hm (hn _ <| le_max_right m n))
#align sequentially_complete.le_nhds_of_seq_tendsto_nhds SequentiallyComplete.le_nhds_of_seq_tendsto_nhds
end
end SequentiallyComplete
namespace UniformSpace
open SequentiallyComplete
variable [IsCountablyGenerated (𝓤 α)]
/-- A uniform space is complete provided that (a) its uniformity filter has a countable basis;
(b) any sequence satisfying a "controlled" version of the Cauchy condition converges. -/
theorem complete_of_convergent_controlled_sequences (U : ℕ → Set (α × α)) (U_mem : ∀ n, U n ∈ 𝓤 α)
(HU : ∀ u : ℕ → α, (∀ N m n, N ≤ m → N ≤ n → (u m, u n) ∈ U N) → ∃ a, Tendsto u atTop (𝓝 a)) :
CompleteSpace α := by
obtain ⟨U', -, hU'⟩ := (𝓤 α).exists_antitone_seq
have Hmem : ∀ n, U n ∩ U' n ∈ 𝓤 α := fun n => inter_mem (U_mem n) (hU'.2 ⟨n, Subset.refl _⟩)
refine ⟨fun hf => (HU (seq hf Hmem) fun N m n hm hn => ?_).imp <|
le_nhds_of_seq_tendsto_nhds _ _ fun s hs => ?_⟩
· exact inter_subset_left (seq_pair_mem hf Hmem hm hn)
· rcases hU'.1 hs with ⟨N, hN⟩
exact ⟨N, Subset.trans inter_subset_right hN⟩
#align uniform_space.complete_of_convergent_controlled_sequences UniformSpace.complete_of_convergent_controlled_sequences
/-- A sequentially complete uniform space with a countable basis of the uniformity filter is
complete. -/
theorem complete_of_cauchySeq_tendsto (H' : ∀ u : ℕ → α, CauchySeq u → ∃ a, Tendsto u atTop (𝓝 a)) :
CompleteSpace α :=
let ⟨U', _, hU'⟩ := (𝓤 α).exists_antitone_seq
complete_of_convergent_controlled_sequences U' (fun n => hU'.2 ⟨n, Subset.refl _⟩) fun u hu =>
H' u <| cauchySeq_of_controlled U' (fun _ hs => hU'.1 hs) hu
#align uniform_space.complete_of_cauchy_seq_tendsto UniformSpace.complete_of_cauchySeq_tendsto
variable (α)
-- Porting note (#11215): TODO: move to `Topology.UniformSpace.Basic`
instance (priority := 100) firstCountableTopology : FirstCountableTopology α :=
⟨fun a => by rw [nhds_eq_comap_uniformity]; infer_instance⟩
#align uniform_space.first_countable_topology UniformSpace.firstCountableTopology
/-- A separable uniform space with countably generated uniformity filter is second countable:
one obtains a countable basis by taking the balls centered at points in a dense subset,
and with rational "radii" from a countable open symmetric antitone basis of `𝓤 α`. We do not
register this as an instance, as there is already an instance going in the other direction
from second countable spaces to separable spaces, and we want to avoid loops. -/
| Mathlib/Topology/UniformSpace/Cauchy.lean | 808 | 829 | theorem secondCountable_of_separable [SeparableSpace α] : SecondCountableTopology α := by |
rcases exists_countable_dense α with ⟨s, hsc, hsd⟩
obtain
⟨t : ℕ → Set (α × α), hto : ∀ i : ℕ, t i ∈ (𝓤 α).sets ∧ IsOpen (t i) ∧ SymmetricRel (t i),
h_basis : (𝓤 α).HasAntitoneBasis t⟩ :=
(@uniformity_hasBasis_open_symmetric α _).exists_antitone_subbasis
choose ht_mem hto hts using hto
refine ⟨⟨⋃ x ∈ s, range fun k => ball x (t k), hsc.biUnion fun x _ => countable_range _, ?_⟩⟩
refine (isTopologicalBasis_of_isOpen_of_nhds ?_ ?_).eq_generateFrom
· simp only [mem_iUnion₂, mem_range]
rintro _ ⟨x, _, k, rfl⟩
exact isOpen_ball x (hto k)
· intro x V hxV hVo
simp only [mem_iUnion₂, mem_range, exists_prop]
rcases UniformSpace.mem_nhds_iff.1 (IsOpen.mem_nhds hVo hxV) with ⟨U, hU, hUV⟩
rcases comp_symm_of_uniformity hU with ⟨U', hU', _, hUU'⟩
rcases h_basis.toHasBasis.mem_iff.1 hU' with ⟨k, -, hk⟩
rcases hsd.inter_open_nonempty (ball x <| t k) (isOpen_ball x (hto k))
⟨x, UniformSpace.mem_ball_self _ (ht_mem k)⟩ with
⟨y, hxy, hys⟩
refine ⟨_, ⟨y, hys, k, rfl⟩, (hts k).subset hxy, fun z hz => ?_⟩
exact hUV (ball_subset_of_comp_subset (hk hxy) hUU' (hk hz))
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Floris van Doorn, Gabriel Ebner, Yury Kudryashov
-/
import Mathlib.Order.ConditionallyCompleteLattice.Finset
import Mathlib.Order.Interval.Finset.Nat
#align_import data.nat.lattice from "leanprover-community/mathlib"@"52fa514ec337dd970d71d8de8d0fd68b455a1e54"
/-!
# Conditionally complete linear order structure on `ℕ`
In this file we
* define a `ConditionallyCompleteLinearOrderBot` structure on `ℕ`;
* prove a few lemmas about `iSup`/`iInf`/`Set.iUnion`/`Set.iInter` and natural numbers.
-/
assert_not_exists MonoidWithZero
open Set
namespace Nat
open scoped Classical
noncomputable instance : InfSet ℕ :=
⟨fun s ↦ if h : ∃ n, n ∈ s then @Nat.find (fun n ↦ n ∈ s) _ h else 0⟩
noncomputable instance : SupSet ℕ :=
⟨fun s ↦ if h : ∃ n, ∀ a ∈ s, a ≤ n then @Nat.find (fun n ↦ ∀ a ∈ s, a ≤ n) _ h else 0⟩
theorem sInf_def {s : Set ℕ} (h : s.Nonempty) : sInf s = @Nat.find (fun n ↦ n ∈ s) _ h :=
dif_pos _
#align nat.Inf_def Nat.sInf_def
theorem sSup_def {s : Set ℕ} (h : ∃ n, ∀ a ∈ s, a ≤ n) :
sSup s = @Nat.find (fun n ↦ ∀ a ∈ s, a ≤ n) _ h :=
dif_pos _
#align nat.Sup_def Nat.sSup_def
theorem _root_.Set.Infinite.Nat.sSup_eq_zero {s : Set ℕ} (h : s.Infinite) : sSup s = 0 :=
dif_neg fun ⟨n, hn⟩ ↦
let ⟨k, hks, hk⟩ := h.exists_gt n
(hn k hks).not_lt hk
#align set.infinite.nat.Sup_eq_zero Set.Infinite.Nat.sSup_eq_zero
@[simp]
theorem sInf_eq_zero {s : Set ℕ} : sInf s = 0 ↔ 0 ∈ s ∨ s = ∅ := by
cases eq_empty_or_nonempty s with
| inl h => subst h
simp only [or_true_iff, eq_self_iff_true, iff_true_iff, iInf, InfSet.sInf,
mem_empty_iff_false, exists_false, dif_neg, not_false_iff]
| inr h => simp only [h.ne_empty, or_false_iff, Nat.sInf_def, h, Nat.find_eq_zero]
#align nat.Inf_eq_zero Nat.sInf_eq_zero
@[simp]
theorem sInf_empty : sInf ∅ = 0 := by
rw [sInf_eq_zero]
right
rfl
#align nat.Inf_empty Nat.sInf_empty
@[simp]
theorem iInf_of_empty {ι : Sort*} [IsEmpty ι] (f : ι → ℕ) : iInf f = 0 := by
rw [iInf_of_isEmpty, sInf_empty]
#align nat.infi_of_empty Nat.iInf_of_empty
/-- This combines `Nat.iInf_of_empty` with `ciInf_const`. -/
@[simp]
lemma iInf_const_zero {ι : Sort*} : ⨅ i : ι, 0 = 0 :=
(isEmpty_or_nonempty ι).elim (fun h ↦ by simp) fun h ↦ sInf_eq_zero.2 <| by simp
theorem sInf_mem {s : Set ℕ} (h : s.Nonempty) : sInf s ∈ s := by
rw [Nat.sInf_def h]
exact Nat.find_spec h
#align nat.Inf_mem Nat.sInf_mem
| Mathlib/Data/Nat/Lattice.lean | 80 | 83 | theorem not_mem_of_lt_sInf {s : Set ℕ} {m : ℕ} (hm : m < sInf s) : m ∉ s := by |
cases eq_empty_or_nonempty s with
| inl h => subst h; apply not_mem_empty
| inr h => rw [Nat.sInf_def h] at hm; exact Nat.find_min h hm
|
/-
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
| Mathlib/Order/Minimal.lean | 96 | 99 | 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]
|
/-
Copyright (c) 2021 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Analysis.Convex.Hull
#align_import analysis.convex.extreme from "leanprover-community/mathlib"@"c5773405394e073885e2a144c9ca14637e8eb963"
/-!
# Extreme sets
This file defines extreme sets and extreme points for sets in a module.
An extreme set of `A` is a subset of `A` that is as far as it can get in any outward direction: If
point `x` is in it and point `y ∈ A`, then the line passing through `x` and `y` leaves `A` at `x`.
This is an analytic notion of "being on the side of". It is weaker than being exposed (see
`IsExposed.isExtreme`).
## Main declarations
* `IsExtreme 𝕜 A B`: States that `B` is an extreme set of `A` (in the literature, `A` is often
implicit).
* `Set.extremePoints 𝕜 A`: Set of extreme points of `A` (corresponding to extreme singletons).
* `Convex.mem_extremePoints_iff_convex_diff`: A useful equivalent condition to being an extreme
point: `x` is an extreme point iff `A \ {x}` is convex.
## Implementation notes
The exact definition of extremeness has been carefully chosen so as to make as many lemmas
unconditional (in particular, the Krein-Milman theorem doesn't need the set to be convex!).
In practice, `A` is often assumed to be a convex set.
## References
See chapter 8 of [Barry Simon, *Convexity*][simon2011]
## TODO
Prove lemmas relating extreme sets and points to the intrinsic frontier.
More not-yet-PRed stuff is available on the mathlib3 branch `sperner_again`.
-/
open Function Set
open scoped Classical
open Affine
variable {𝕜 E F ι : Type*} {π : ι → Type*}
section SMul
variable (𝕜) [OrderedSemiring 𝕜] [AddCommMonoid E] [SMul 𝕜 E]
/-- A set `B` is an extreme subset of `A` if `B ⊆ A` and all points of `B` only belong to open
segments whose ends are in `B`. -/
def IsExtreme (A B : Set E) : Prop :=
B ⊆ A ∧ ∀ ⦃x₁⦄, x₁ ∈ A → ∀ ⦃x₂⦄, x₂ ∈ A → ∀ ⦃x⦄, x ∈ B → x ∈ openSegment 𝕜 x₁ x₂ → x₁ ∈ B ∧ x₂ ∈ B
#align is_extreme IsExtreme
/-- A point `x` is an extreme point of a set `A` if `x` belongs to no open segment with ends in
`A`, except for the obvious `openSegment x x`. -/
def Set.extremePoints (A : Set E) : Set E :=
{ x ∈ A | ∀ ⦃x₁⦄, x₁ ∈ A → ∀ ⦃x₂⦄, x₂ ∈ A → x ∈ openSegment 𝕜 x₁ x₂ → x₁ = x ∧ x₂ = x }
#align set.extreme_points Set.extremePoints
@[refl]
protected theorem IsExtreme.refl (A : Set E) : IsExtreme 𝕜 A A :=
⟨Subset.rfl, fun _ hx₁A _ hx₂A _ _ _ ↦ ⟨hx₁A, hx₂A⟩⟩
#align is_extreme.refl IsExtreme.refl
variable {𝕜} {A B C : Set E} {x : E}
protected theorem IsExtreme.rfl : IsExtreme 𝕜 A A :=
IsExtreme.refl 𝕜 A
#align is_extreme.rfl IsExtreme.rfl
@[trans]
protected theorem IsExtreme.trans (hAB : IsExtreme 𝕜 A B) (hBC : IsExtreme 𝕜 B C) :
IsExtreme 𝕜 A C := by
refine ⟨Subset.trans hBC.1 hAB.1, fun x₁ hx₁A x₂ hx₂A x hxC hx ↦ ?_⟩
obtain ⟨hx₁B, hx₂B⟩ := hAB.2 hx₁A hx₂A (hBC.1 hxC) hx
exact hBC.2 hx₁B hx₂B hxC hx
#align is_extreme.trans IsExtreme.trans
protected theorem IsExtreme.antisymm : AntiSymmetric (IsExtreme 𝕜 : Set E → Set E → Prop) :=
fun _ _ hAB hBA ↦ Subset.antisymm hBA.1 hAB.1
#align is_extreme.antisymm IsExtreme.antisymm
instance : IsPartialOrder (Set E) (IsExtreme 𝕜) where
refl := IsExtreme.refl 𝕜
trans _ _ _ := IsExtreme.trans
antisymm := IsExtreme.antisymm
theorem IsExtreme.inter (hAB : IsExtreme 𝕜 A B) (hAC : IsExtreme 𝕜 A C) :
IsExtreme 𝕜 A (B ∩ C) := by
use Subset.trans inter_subset_left hAB.1
rintro x₁ hx₁A x₂ hx₂A x ⟨hxB, hxC⟩ hx
obtain ⟨hx₁B, hx₂B⟩ := hAB.2 hx₁A hx₂A hxB hx
obtain ⟨hx₁C, hx₂C⟩ := hAC.2 hx₁A hx₂A hxC hx
exact ⟨⟨hx₁B, hx₁C⟩, hx₂B, hx₂C⟩
#align is_extreme.inter IsExtreme.inter
protected theorem IsExtreme.mono (hAC : IsExtreme 𝕜 A C) (hBA : B ⊆ A) (hCB : C ⊆ B) :
IsExtreme 𝕜 B C :=
⟨hCB, fun _ hx₁B _ hx₂B _ hxC hx ↦ hAC.2 (hBA hx₁B) (hBA hx₂B) hxC hx⟩
#align is_extreme.mono IsExtreme.mono
theorem isExtreme_iInter {ι : Sort*} [Nonempty ι] {F : ι → Set E}
(hAF : ∀ i : ι, IsExtreme 𝕜 A (F i)) : IsExtreme 𝕜 A (⋂ i : ι, F i) := by
obtain i := Classical.arbitrary ι
refine ⟨iInter_subset_of_subset i (hAF i).1, fun x₁ hx₁A x₂ hx₂A x hxF hx ↦ ?_⟩
simp_rw [mem_iInter] at hxF ⊢
have h := fun i ↦ (hAF i).2 hx₁A hx₂A (hxF i) hx
exact ⟨fun i ↦ (h i).1, fun i ↦ (h i).2⟩
#align is_extreme_Inter isExtreme_iInter
theorem isExtreme_biInter {F : Set (Set E)} (hF : F.Nonempty) (hA : ∀ B ∈ F, IsExtreme 𝕜 A B) :
IsExtreme 𝕜 A (⋂ B ∈ F, B) := by
haveI := hF.to_subtype
simpa only [iInter_subtype] using isExtreme_iInter fun i : F ↦ hA _ i.2
#align is_extreme_bInter isExtreme_biInter
theorem isExtreme_sInter {F : Set (Set E)} (hF : F.Nonempty) (hAF : ∀ B ∈ F, IsExtreme 𝕜 A B) :
IsExtreme 𝕜 A (⋂₀ F) := by simpa [sInter_eq_biInter] using isExtreme_biInter hF hAF
#align is_extreme_sInter isExtreme_sInter
theorem mem_extremePoints : x ∈ A.extremePoints 𝕜 ↔
x ∈ A ∧ ∀ᵉ (x₁ ∈ A) (x₂ ∈ A), x ∈ openSegment 𝕜 x₁ x₂ → x₁ = x ∧ x₂ = x :=
Iff.rfl
#align mem_extreme_points mem_extremePoints
/-- x is an extreme point to A iff {x} is an extreme set of A. -/
@[simp] lemma isExtreme_singleton : IsExtreme 𝕜 A {x} ↔ x ∈ A.extremePoints 𝕜 := by
refine ⟨fun hx ↦ ⟨singleton_subset_iff.1 hx.1, fun x₁ hx₁ x₂ hx₂ ↦ hx.2 hx₁ hx₂ rfl⟩, ?_⟩
rintro ⟨hxA, hAx⟩
use singleton_subset_iff.2 hxA
rintro x₁ hx₁A x₂ hx₂A y (rfl : y = x)
exact hAx hx₁A hx₂A
#align mem_extreme_points_iff_extreme_singleton isExtreme_singleton
alias ⟨IsExtreme.mem_extremePoints, _⟩ := isExtreme_singleton
theorem extremePoints_subset : A.extremePoints 𝕜 ⊆ A :=
fun _ hx ↦ hx.1
#align extreme_points_subset extremePoints_subset
@[simp]
theorem extremePoints_empty : (∅ : Set E).extremePoints 𝕜 = ∅ :=
subset_empty_iff.1 extremePoints_subset
#align extreme_points_empty extremePoints_empty
@[simp]
theorem extremePoints_singleton : ({x} : Set E).extremePoints 𝕜 = {x} :=
extremePoints_subset.antisymm <|
singleton_subset_iff.2 ⟨mem_singleton x, fun _ hx₁ _ hx₂ _ ↦ ⟨hx₁, hx₂⟩⟩
#align extreme_points_singleton extremePoints_singleton
theorem inter_extremePoints_subset_extremePoints_of_subset (hBA : B ⊆ A) :
B ∩ A.extremePoints 𝕜 ⊆ B.extremePoints 𝕜 :=
fun _ ⟨hxB, hxA⟩ ↦ ⟨hxB, fun _ hx₁ _ hx₂ hx ↦ hxA.2 (hBA hx₁) (hBA hx₂) hx⟩
#align inter_extreme_points_subset_extreme_points_of_subset inter_extremePoints_subset_extremePoints_of_subset
theorem IsExtreme.extremePoints_subset_extremePoints (hAB : IsExtreme 𝕜 A B) :
B.extremePoints 𝕜 ⊆ A.extremePoints 𝕜 :=
fun _ ↦ by simpa only [← isExtreme_singleton] using hAB.trans
#align is_extreme.extreme_points_subset_extreme_points IsExtreme.extremePoints_subset_extremePoints
theorem IsExtreme.extremePoints_eq (hAB : IsExtreme 𝕜 A B) :
B.extremePoints 𝕜 = B ∩ A.extremePoints 𝕜 :=
Subset.antisymm (fun _ hx ↦ ⟨hx.1, hAB.extremePoints_subset_extremePoints hx⟩)
(inter_extremePoints_subset_extremePoints_of_subset hAB.1)
#align is_extreme.extreme_points_eq IsExtreme.extremePoints_eq
end SMul
section OrderedSemiring
variable [OrderedSemiring 𝕜] [AddCommGroup E] [AddCommGroup F] [∀ i, AddCommGroup (π i)]
[Module 𝕜 E] [Module 𝕜 F] [∀ i, Module 𝕜 (π i)] {A B : Set E} {x : E}
theorem IsExtreme.convex_diff (hA : Convex 𝕜 A) (hAB : IsExtreme 𝕜 A B) : Convex 𝕜 (A \ B) :=
convex_iff_openSegment_subset.2 fun _ ⟨hx₁A, hx₁B⟩ _ ⟨hx₂A, _⟩ _ hx ↦
⟨hA.openSegment_subset hx₁A hx₂A hx, fun hxB ↦ hx₁B (hAB.2 hx₁A hx₂A hxB hx).1⟩
#align is_extreme.convex_diff IsExtreme.convex_diff
@[simp]
theorem extremePoints_prod (s : Set E) (t : Set F) :
(s ×ˢ t).extremePoints 𝕜 = s.extremePoints 𝕜 ×ˢ t.extremePoints 𝕜 := by
ext
refine (and_congr_right fun hx ↦ ⟨fun h ↦ ?_, fun h ↦ ?_⟩).trans and_and_and_comm
constructor
· rintro x₁ hx₁ x₂ hx₂ hx_fst
refine (h (mk_mem_prod hx₁ hx.2) (mk_mem_prod hx₂ hx.2) ?_).imp (congr_arg Prod.fst)
(congr_arg Prod.fst)
rw [← Prod.image_mk_openSegment_left]
exact ⟨_, hx_fst, rfl⟩
· rintro x₁ hx₁ x₂ hx₂ hx_snd
refine (h (mk_mem_prod hx.1 hx₁) (mk_mem_prod hx.1 hx₂) ?_).imp (congr_arg Prod.snd)
(congr_arg Prod.snd)
rw [← Prod.image_mk_openSegment_right]
exact ⟨_, hx_snd, rfl⟩
· rintro x₁ hx₁ x₂ hx₂ ⟨a, b, ha, hb, hab, hx'⟩
simp_rw [Prod.ext_iff]
exact and_and_and_comm.1
⟨h.1 hx₁.1 hx₂.1 ⟨a, b, ha, hb, hab, congr_arg Prod.fst hx'⟩,
h.2 hx₁.2 hx₂.2 ⟨a, b, ha, hb, hab, congr_arg Prod.snd hx'⟩⟩
#align extreme_points_prod extremePoints_prod
@[simp]
theorem extremePoints_pi (s : ∀ i, Set (π i)) :
(univ.pi s).extremePoints 𝕜 = univ.pi fun i ↦ (s i).extremePoints 𝕜 := by
ext x
simp only [mem_extremePoints, mem_pi, mem_univ, true_imp_iff, @forall_and ι]
refine and_congr_right fun hx ↦ ⟨fun h i ↦ ?_, fun h ↦ ?_⟩
· rintro x₁ hx₁ x₂ hx₂ hi
refine (h (update x i x₁) ?_ (update x i x₂) ?_ ?_).imp (fun h₁ ↦ by rw [← h₁, update_same])
fun h₂ ↦ by rw [← h₂, update_same]
iterate 2
rintro j
obtain rfl | hji := eq_or_ne j i
· rwa [update_same]
· rw [update_noteq hji]
exact hx _
rw [← Pi.image_update_openSegment]
exact ⟨_, hi, update_eq_self _ _⟩
· rintro x₁ hx₁ x₂ hx₂ ⟨a, b, ha, hb, hab, hx'⟩
simp_rw [funext_iff, ← forall_and]
exact fun i ↦ h _ _ (hx₁ _) _ (hx₂ _) ⟨a, b, ha, hb, hab, congr_fun hx' _⟩
#align extreme_points_pi extremePoints_pi
end OrderedSemiring
section OrderedRing
variable {L : Type*} [OrderedRing 𝕜] [AddCommGroup E] [Module 𝕜 E] [AddCommGroup F] [Module 𝕜 F]
[EquivLike L E F] [LinearEquivClass L 𝕜 E F]
lemma image_extremePoints (f : L) (s : Set E) :
f '' extremePoints 𝕜 s = extremePoints 𝕜 (f '' s) := by
ext b
obtain ⟨a, rfl⟩ := EquivLike.surjective f b
have : ∀ x y, f '' openSegment 𝕜 x y = openSegment 𝕜 (f x) (f y) :=
image_openSegment _ (LinearMapClass.linearMap f).toAffineMap
simp only [mem_extremePoints, (EquivLike.surjective f).forall,
(EquivLike.injective f).mem_set_image, (EquivLike.injective f).eq_iff, ← this]
end OrderedRing
section LinearOrderedRing
variable [LinearOrderedRing 𝕜] [AddCommGroup E] [Module 𝕜 E]
variable [DenselyOrdered 𝕜] [NoZeroSMulDivisors 𝕜 E] {A B : Set E} {x : E}
/-- A useful restatement using `segment`: `x` is an extreme point iff the only (closed) segments
that contain it are those with `x` as one of their endpoints. -/
| Mathlib/Analysis/Convex/Extreme.lean | 258 | 267 | theorem mem_extremePoints_iff_forall_segment : x ∈ A.extremePoints 𝕜 ↔
x ∈ A ∧ ∀ᵉ (x₁ ∈ A) (x₂ ∈ A), x ∈ segment 𝕜 x₁ x₂ → x₁ = x ∨ x₂ = x := by |
refine and_congr_right fun hxA ↦ forall₄_congr fun x₁ h₁ x₂ h₂ ↦ ?_
constructor
· rw [← insert_endpoints_openSegment]
rintro H (rfl | rfl | hx)
exacts [Or.inl rfl, Or.inr rfl, Or.inl <| (H hx).1]
· intro H hx
rcases H (openSegment_subset_segment _ _ _ hx) with (rfl | rfl)
exacts [⟨rfl, (left_mem_openSegment_iff.1 hx).symm⟩, ⟨right_mem_openSegment_iff.1 hx, rfl⟩]
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.FieldTheory.Finiteness
import Mathlib.LinearAlgebra.Dimension.FreeAndStrongRankCondition
import Mathlib.LinearAlgebra.Dimension.DivisionRing
#align_import linear_algebra.finite_dimensional from "leanprover-community/mathlib"@"e95e4f92c8f8da3c7f693c3ec948bcf9b6683f51"
/-!
# Finite dimensional vector spaces
Definition and basic properties of finite dimensional vector spaces, of their dimensions, and
of linear maps on such spaces.
## Main definitions
Assume `V` is a vector space over a division ring `K`. There are (at least) three equivalent
definitions of finite-dimensionality of `V`:
- it admits a finite basis.
- it is finitely generated.
- it is noetherian, i.e., every subspace is finitely generated.
We introduce a typeclass `FiniteDimensional K V` capturing this property. For ease of transfer of
proof, it is defined using the second point of view, i.e., as `Finite`. However, we prove
that all these points of view are equivalent, with the following lemmas
(in the namespace `FiniteDimensional`):
- `fintypeBasisIndex` states that a finite-dimensional
vector space has a finite basis
- `FiniteDimensional.finBasis` and `FiniteDimensional.finBasisOfFinrankEq`
are bases for finite dimensional vector spaces, where the index type
is `Fin`
- `of_fintype_basis` states that the existence of a basis indexed by a
finite type implies finite-dimensionality
- `of_finite_basis` states that the existence of a basis indexed by a
finite set implies finite-dimensionality
- `IsNoetherian.iff_fg` states that the space is finite-dimensional if and only if
it is noetherian
We make use of `finrank`, the dimension of a finite dimensional space, returning a `Nat`, as
opposed to `Module.rank`, which returns a `Cardinal`. When the space has infinite dimension, its
`finrank` is by convention set to `0`. `finrank` is not defined using `FiniteDimensional`.
For basic results that do not need the `FiniteDimensional` class, import
`Mathlib.LinearAlgebra.Finrank`.
Preservation of finite-dimensionality and formulas for the dimension are given for
- submodules
- quotients (for the dimension of a quotient, see `finrank_quotient_add_finrank`)
- linear equivs, in `LinearEquiv.finiteDimensional`
- image under a linear map (the rank-nullity formula is in `finrank_range_add_finrank_ker`)
Basic properties of linear maps of a finite-dimensional vector space are given. Notably, the
equivalence of injectivity and surjectivity is proved in `LinearMap.injective_iff_surjective`,
and the equivalence between left-inverse and right-inverse in `LinearMap.mul_eq_one_comm`
and `LinearMap.comp_eq_id_comm`.
## Implementation notes
Most results are deduced from the corresponding results for the general dimension (as a cardinal),
in `Mathlib.LinearAlgebra.Dimension`. Not all results have been ported yet.
You should not assume that there has been any effort to state lemmas as generally as possible.
Plenty of the results hold for general fg modules or notherian modules, and they can be found in
`Mathlib.LinearAlgebra.FreeModule.Finite.Rank` and `Mathlib.RingTheory.Noetherian`.
-/
universe u v v' w
open Cardinal Submodule Module Function
/-- `FiniteDimensional` vector spaces are defined to be finite modules.
Use `FiniteDimensional.of_fintype_basis` to prove finite dimension from another definition. -/
abbrev FiniteDimensional (K V : Type*) [DivisionRing K] [AddCommGroup V] [Module K V] :=
Module.Finite K V
#align finite_dimensional FiniteDimensional
variable {K : Type u} {V : Type v}
namespace FiniteDimensional
open IsNoetherian
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- If the codomain of an injective linear map is finite dimensional, the domain must be as well. -/
theorem of_injective (f : V →ₗ[K] V₂) (w : Function.Injective f) [FiniteDimensional K V₂] :
FiniteDimensional K V :=
have : IsNoetherian K V₂ := IsNoetherian.iff_fg.mpr ‹_›
Module.Finite.of_injective f w
#align finite_dimensional.of_injective FiniteDimensional.of_injective
/-- If the domain of a surjective linear map is finite dimensional, the codomain must be as well. -/
theorem of_surjective (f : V →ₗ[K] V₂) (w : Function.Surjective f) [FiniteDimensional K V] :
FiniteDimensional K V₂ :=
Module.Finite.of_surjective f w
#align finite_dimensional.of_surjective FiniteDimensional.of_surjective
variable (K V)
instance finiteDimensional_pi {ι : Type*} [Finite ι] : FiniteDimensional K (ι → K) :=
Finite.pi
#align finite_dimensional.finite_dimensional_pi FiniteDimensional.finiteDimensional_pi
instance finiteDimensional_pi' {ι : Type*} [Finite ι] (M : ι → Type*) [∀ i, AddCommGroup (M i)]
[∀ i, Module K (M i)] [∀ i, FiniteDimensional K (M i)] : FiniteDimensional K (∀ i, M i) :=
Finite.pi
#align finite_dimensional.finite_dimensional_pi' FiniteDimensional.finiteDimensional_pi'
/-- A finite dimensional vector space over a finite field is finite -/
noncomputable def fintypeOfFintype [Fintype K] [FiniteDimensional K V] : Fintype V :=
Module.fintypeOfFintype (@finsetBasis K V _ _ _ (iff_fg.2 inferInstance))
#align finite_dimensional.fintype_of_fintype FiniteDimensional.fintypeOfFintype
theorem finite_of_finite [Finite K] [FiniteDimensional K V] : Finite V := by
cases nonempty_fintype K
haveI := fintypeOfFintype K V
infer_instance
#align finite_dimensional.finite_of_finite FiniteDimensional.finite_of_finite
variable {K V}
/-- If a vector space has a finite basis, then it is finite-dimensional. -/
theorem of_fintype_basis {ι : Type w} [Finite ι] (h : Basis ι K V) : FiniteDimensional K V :=
Module.Finite.of_basis h
#align finite_dimensional.of_fintype_basis FiniteDimensional.of_fintype_basis
/-- If a vector space is `FiniteDimensional`, all bases are indexed by a finite type -/
noncomputable def fintypeBasisIndex {ι : Type*} [FiniteDimensional K V] (b : Basis ι K V) :
Fintype ι :=
@Fintype.ofFinite _ (Module.Finite.finite_basis b)
#align finite_dimensional.fintype_basis_index FiniteDimensional.fintypeBasisIndex
/-- If a vector space is `FiniteDimensional`, `Basis.ofVectorSpace` is indexed by
a finite type. -/
noncomputable instance [FiniteDimensional K V] : Fintype (Basis.ofVectorSpaceIndex K V) := by
letI : IsNoetherian K V := IsNoetherian.iff_fg.2 inferInstance
infer_instance
/-- If a vector space has a basis indexed by elements of a finite set, then it is
finite-dimensional. -/
theorem of_finite_basis {ι : Type w} {s : Set ι} (h : Basis s K V) (hs : Set.Finite s) :
FiniteDimensional K V :=
haveI := hs.fintype
of_fintype_basis h
#align finite_dimensional.of_finite_basis FiniteDimensional.of_finite_basis
/-- A subspace of a finite-dimensional space is also finite-dimensional. -/
instance finiteDimensional_submodule [FiniteDimensional K V] (S : Submodule K V) :
FiniteDimensional K S := by
letI : IsNoetherian K V := iff_fg.2 ?_
· exact
iff_fg.1
(IsNoetherian.iff_rank_lt_aleph0.2
(lt_of_le_of_lt (rank_submodule_le _) (_root_.rank_lt_aleph0 K V)))
· infer_instance
#align finite_dimensional.finite_dimensional_submodule FiniteDimensional.finiteDimensional_submodule
/-- A quotient of a finite-dimensional space is also finite-dimensional. -/
instance finiteDimensional_quotient [FiniteDimensional K V] (S : Submodule K V) :
FiniteDimensional K (V ⧸ S) :=
Module.Finite.quotient K S
#align finite_dimensional.finite_dimensional_quotient FiniteDimensional.finiteDimensional_quotient
variable (K V)
/-- In a finite-dimensional space, its dimension (seen as a cardinal) coincides with its
`finrank`. This is a copy of `finrank_eq_rank _ _` which creates easier typeclass searches. -/
theorem finrank_eq_rank' [FiniteDimensional K V] : (finrank K V : Cardinal.{v}) = Module.rank K V :=
finrank_eq_rank _ _
#align finite_dimensional.finrank_eq_rank' FiniteDimensional.finrank_eq_rank'
variable {K V}
theorem finrank_of_infinite_dimensional (h : ¬FiniteDimensional K V) : finrank K V = 0 :=
FiniteDimensional.finrank_of_not_finite h
#align finite_dimensional.finrank_of_infinite_dimensional FiniteDimensional.finrank_of_infinite_dimensional
theorem of_finrank_pos (h : 0 < finrank K V) : FiniteDimensional K V :=
Module.finite_of_finrank_pos h
#align finite_dimensional.finite_dimensional_of_finrank FiniteDimensional.of_finrank_pos
theorem of_finrank_eq_succ {n : ℕ} (hn : finrank K V = n.succ) :
FiniteDimensional K V :=
Module.finite_of_finrank_eq_succ hn
#align finite_dimensional.finite_dimensional_of_finrank_eq_succ FiniteDimensional.of_finrank_eq_succ
/-- We can infer `FiniteDimensional K V` in the presence of `[Fact (finrank K V = n + 1)]`. Declare
this as a local instance where needed. -/
theorem of_fact_finrank_eq_succ (n : ℕ) [hn : Fact (finrank K V = n + 1)] :
FiniteDimensional K V :=
of_finrank_eq_succ hn.out
#align finite_dimensional.fact_finite_dimensional_of_finrank_eq_succ FiniteDimensional.of_fact_finrank_eq_succ
theorem finiteDimensional_iff_of_rank_eq_nsmul {W} [AddCommGroup W] [Module K W] {n : ℕ}
(hn : n ≠ 0) (hVW : Module.rank K V = n • Module.rank K W) :
FiniteDimensional K V ↔ FiniteDimensional K W :=
Module.finite_iff_of_rank_eq_nsmul hn hVW
#align finite_dimensional.finite_dimensional_iff_of_rank_eq_nsmul FiniteDimensional.finiteDimensional_iff_of_rank_eq_nsmul
/-- If a vector space is finite-dimensional, then the cardinality of any basis is equal to its
`finrank`. -/
theorem finrank_eq_card_basis' [FiniteDimensional K V] {ι : Type w} (h : Basis ι K V) :
(finrank K V : Cardinal.{w}) = #ι :=
Module.mk_finrank_eq_card_basis h
#align finite_dimensional.finrank_eq_card_basis' FiniteDimensional.finrank_eq_card_basis'
theorem _root_.LinearIndependent.lt_aleph0_of_finiteDimensional {ι : Type w} [FiniteDimensional K V]
{v : ι → V} (h : LinearIndependent K v) : #ι < ℵ₀ :=
h.lt_aleph0_of_finite
#align finite_dimensional.lt_aleph_0_of_linear_independent LinearIndependent.lt_aleph0_of_finiteDimensional
@[deprecated (since := "2023-12-27")]
alias lt_aleph0_of_linearIndependent := LinearIndependent.lt_aleph0_of_finiteDimensional
/-- If a submodule has maximal dimension in a finite dimensional space, then it is equal to the
whole space. -/
theorem _root_.Submodule.eq_top_of_finrank_eq [FiniteDimensional K V] {S : Submodule K V}
(h : finrank K S = finrank K V) : S = ⊤ := by
haveI : IsNoetherian K V := iff_fg.2 inferInstance
set bS := Basis.ofVectorSpace K S with bS_eq
have : LinearIndependent K ((↑) : ((↑) '' Basis.ofVectorSpaceIndex K S : Set V) → V) :=
LinearIndependent.image_subtype (f := Submodule.subtype S)
(by simpa [bS] using bS.linearIndependent) (by simp)
set b := Basis.extend this with b_eq
-- Porting note: `letI` now uses `this` so we need to give different names
letI i1 : Fintype (this.extend _) :=
(LinearIndependent.set_finite_of_isNoetherian (by simpa [b] using b.linearIndependent)).fintype
letI i2 : Fintype (((↑) : S → V) '' Basis.ofVectorSpaceIndex K S) :=
(LinearIndependent.set_finite_of_isNoetherian this).fintype
letI i3 : Fintype (Basis.ofVectorSpaceIndex K S) :=
(LinearIndependent.set_finite_of_isNoetherian
(by simpa [bS] using bS.linearIndependent)).fintype
have : (↑) '' Basis.ofVectorSpaceIndex K S = this.extend (Set.subset_univ _) :=
Set.eq_of_subset_of_card_le (this.subset_extend _)
(by
rw [Set.card_image_of_injective _ Subtype.coe_injective, ← finrank_eq_card_basis bS, ←
finrank_eq_card_basis b, h])
rw [← b.span_eq, b_eq, Basis.coe_extend, Subtype.range_coe, ← this, ← Submodule.coeSubtype,
span_image]
have := bS.span_eq
rw [bS_eq, Basis.coe_ofVectorSpace, Subtype.range_coe] at this
rw [this, Submodule.map_top (Submodule.subtype S), range_subtype]
#align finite_dimensional.eq_top_of_finrank_eq Submodule.eq_top_of_finrank_eq
#align submodule.eq_top_of_finrank_eq Submodule.eq_top_of_finrank_eq
variable (K)
instance finiteDimensional_self : FiniteDimensional K K := inferInstance
#align finite_dimensional.finite_dimensional_self FiniteDimensional.finiteDimensional_self
/-- The submodule generated by a finite set is finite-dimensional. -/
theorem span_of_finite {A : Set V} (hA : Set.Finite A) : FiniteDimensional K (Submodule.span K A) :=
Module.Finite.span_of_finite K hA
#align finite_dimensional.span_of_finite FiniteDimensional.span_of_finite
/-- The submodule generated by a single element is finite-dimensional. -/
instance span_singleton (x : V) : FiniteDimensional K (K ∙ x) :=
Module.Finite.span_singleton K x
#align finite_dimensional.span_singleton FiniteDimensional.span_singleton
/-- The submodule generated by a finset is finite-dimensional. -/
instance span_finset (s : Finset V) : FiniteDimensional K (span K (s : Set V)) :=
Module.Finite.span_finset K s
#align finite_dimensional.span_finset FiniteDimensional.span_finset
/-- Pushforwards of finite-dimensional submodules are finite-dimensional. -/
instance (f : V →ₗ[K] V₂) (p : Submodule K V) [FiniteDimensional K p] :
FiniteDimensional K (p.map f) :=
Module.Finite.map _ _
variable {K}
section
open Finset
section
variable {L : Type*} [LinearOrderedField L]
variable {W : Type v} [AddCommGroup W] [Module L W]
/-- A slight strengthening of `exists_nontrivial_relation_sum_zero_of_rank_succ_lt_card`
available when working over an ordered field:
we can ensure a positive coefficient, not just a nonzero coefficient.
-/
theorem exists_relation_sum_zero_pos_coefficient_of_finrank_succ_lt_card [FiniteDimensional L W]
{t : Finset W} (h : finrank L W + 1 < t.card) :
∃ f : W → L, ∑ e ∈ t, f e • e = 0 ∧ ∑ e ∈ t, f e = 0 ∧ ∃ x ∈ t, 0 < f x := by
obtain ⟨f, sum, total, nonzero⟩ :=
Module.exists_nontrivial_relation_sum_zero_of_finrank_succ_lt_card h
exact ⟨f, sum, total, exists_pos_of_sum_zero_of_exists_nonzero f total nonzero⟩
#align finite_dimensional.exists_relation_sum_zero_pos_coefficient_of_rank_succ_lt_card FiniteDimensional.exists_relation_sum_zero_pos_coefficient_of_finrank_succ_lt_card
end
end
/-- In a vector space with dimension 1, each set {v} is a basis for `v ≠ 0`. -/
@[simps repr_apply]
noncomputable def basisSingleton (ι : Type*) [Unique ι] (h : finrank K V = 1) (v : V)
(hv : v ≠ 0) : Basis ι K V :=
let b := FiniteDimensional.basisUnique ι h
let h : b.repr v default ≠ 0 := mt FiniteDimensional.basisUnique_repr_eq_zero_iff.mp hv
Basis.ofRepr
{ toFun := fun w => Finsupp.single default (b.repr w default / b.repr v default)
invFun := fun f => f default • v
map_add' := by simp [add_div]
map_smul' := by simp [mul_div]
left_inv := fun w => by
apply_fun b.repr using b.repr.toEquiv.injective
apply_fun Equiv.finsuppUnique
simp only [LinearEquiv.map_smulₛₗ, Finsupp.coe_smul, Finsupp.single_eq_same,
smul_eq_mul, Pi.smul_apply, Equiv.finsuppUnique_apply]
exact div_mul_cancel₀ _ h
right_inv := fun f => by
ext
simp only [LinearEquiv.map_smulₛₗ, Finsupp.coe_smul, Finsupp.single_eq_same,
RingHom.id_apply, smul_eq_mul, Pi.smul_apply]
exact mul_div_cancel_right₀ _ h }
#align finite_dimensional.basis_singleton FiniteDimensional.basisSingleton
@[simp]
theorem basisSingleton_apply (ι : Type*) [Unique ι] (h : finrank K V = 1) (v : V) (hv : v ≠ 0)
(i : ι) : basisSingleton ι h v hv i = v := by
cases Unique.uniq ‹Unique ι› i
simp [basisSingleton]
#align finite_dimensional.basis_singleton_apply FiniteDimensional.basisSingleton_apply
@[simp]
theorem range_basisSingleton (ι : Type*) [Unique ι] (h : finrank K V = 1) (v : V) (hv : v ≠ 0) :
Set.range (basisSingleton ι h v hv) = {v} := by rw [Set.range_unique, basisSingleton_apply]
#align finite_dimensional.range_basis_singleton FiniteDimensional.range_basisSingleton
end DivisionRing
section Tower
variable (F K A : Type*) [DivisionRing F] [DivisionRing K] [AddCommGroup A]
variable [Module F K] [Module K A] [Module F A] [IsScalarTower F K A]
theorem trans [FiniteDimensional F K] [FiniteDimensional K A] : FiniteDimensional F A :=
Module.Finite.trans K A
#align finite_dimensional.trans FiniteDimensional.trans
end Tower
end FiniteDimensional
section ZeroRank
variable [DivisionRing K] [AddCommGroup V] [Module K V]
open FiniteDimensional
theorem FiniteDimensional.of_rank_eq_nat {n : ℕ} (h : Module.rank K V = n) :
FiniteDimensional K V :=
Module.finite_of_rank_eq_nat h
#align finite_dimensional_of_rank_eq_nat FiniteDimensional.of_rank_eq_nat
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_rank_eq_nat := FiniteDimensional.of_rank_eq_nat
theorem FiniteDimensional.of_rank_eq_zero (h : Module.rank K V = 0) : FiniteDimensional K V :=
Module.finite_of_rank_eq_zero h
#align finite_dimensional_of_rank_eq_zero FiniteDimensional.of_rank_eq_zero
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_rank_eq_zero := FiniteDimensional.of_rank_eq_zero
theorem FiniteDimensional.of_rank_eq_one (h : Module.rank K V = 1) : FiniteDimensional K V :=
Module.finite_of_rank_eq_one h
#align finite_dimensional_of_rank_eq_one FiniteDimensional.of_rank_eq_one
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_rank_eq_one := FiniteDimensional.of_rank_eq_one
variable (K V)
instance finiteDimensional_bot : FiniteDimensional K (⊥ : Submodule K V) :=
of_rank_eq_zero <| by simp
#align finite_dimensional_bot finiteDimensional_bot
variable {K V}
end ZeroRank
namespace Submodule
open IsNoetherian FiniteDimensional
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V]
/-- A submodule is finitely generated if and only if it is finite-dimensional -/
theorem fg_iff_finiteDimensional (s : Submodule K V) : s.FG ↔ FiniteDimensional K s :=
⟨fun h => Module.finite_def.2 <| (fg_top s).2 h, fun h => (fg_top s).1 <| Module.finite_def.1 h⟩
#align submodule.fg_iff_finite_dimensional Submodule.fg_iff_finiteDimensional
/-- A submodule contained in a finite-dimensional submodule is
finite-dimensional. -/
theorem finiteDimensional_of_le {S₁ S₂ : Submodule K V} [FiniteDimensional K S₂] (h : S₁ ≤ S₂) :
FiniteDimensional K S₁ :=
haveI : IsNoetherian K S₂ := iff_fg.2 inferInstance
iff_fg.1
(IsNoetherian.iff_rank_lt_aleph0.2
(lt_of_le_of_lt (rank_le_of_submodule _ _ h) (rank_lt_aleph0 K S₂)))
#align submodule.finite_dimensional_of_le Submodule.finiteDimensional_of_le
/-- The inf of two submodules, the first finite-dimensional, is
finite-dimensional. -/
instance finiteDimensional_inf_left (S₁ S₂ : Submodule K V) [FiniteDimensional K S₁] :
FiniteDimensional K (S₁ ⊓ S₂ : Submodule K V) :=
finiteDimensional_of_le inf_le_left
#align submodule.finite_dimensional_inf_left Submodule.finiteDimensional_inf_left
/-- The inf of two submodules, the second finite-dimensional, is
finite-dimensional. -/
instance finiteDimensional_inf_right (S₁ S₂ : Submodule K V) [FiniteDimensional K S₂] :
FiniteDimensional K (S₁ ⊓ S₂ : Submodule K V) :=
finiteDimensional_of_le inf_le_right
#align submodule.finite_dimensional_inf_right Submodule.finiteDimensional_inf_right
/-- The sup of two finite-dimensional submodules is
finite-dimensional. -/
instance finiteDimensional_sup (S₁ S₂ : Submodule K V) [h₁ : FiniteDimensional K S₁]
[h₂ : FiniteDimensional K S₂] : FiniteDimensional K (S₁ ⊔ S₂ : Submodule K V) := by
unfold FiniteDimensional at *
rw [finite_def] at *
exact (fg_top _).2 (((fg_top S₁).1 h₁).sup ((fg_top S₂).1 h₂))
#align submodule.finite_dimensional_sup Submodule.finiteDimensional_sup
/-- The submodule generated by a finite supremum of finite dimensional submodules is
finite-dimensional.
Note that strictly this only needs `∀ i ∈ s, FiniteDimensional K (S i)`, but that doesn't
work well with typeclass search. -/
instance finiteDimensional_finset_sup {ι : Type*} (s : Finset ι) (S : ι → Submodule K V)
[∀ i, FiniteDimensional K (S i)] : FiniteDimensional K (s.sup S : Submodule K V) := by
refine
@Finset.sup_induction _ _ _ _ s S (fun i => FiniteDimensional K ↑i) (finiteDimensional_bot K V)
?_ fun i _ => by infer_instance
intro S₁ hS₁ S₂ hS₂
exact Submodule.finiteDimensional_sup S₁ S₂
#align submodule.finite_dimensional_finset_sup Submodule.finiteDimensional_finset_sup
/-- The submodule generated by a supremum of finite dimensional submodules, indexed by a finite
sort is finite-dimensional. -/
instance finiteDimensional_iSup {ι : Sort*} [Finite ι] (S : ι → Submodule K V)
[∀ i, FiniteDimensional K (S i)] : FiniteDimensional K ↑(⨆ i, S i) := by
cases nonempty_fintype (PLift ι)
rw [← iSup_plift_down, ← Finset.sup_univ_eq_iSup]
exact Submodule.finiteDimensional_finset_sup _ _
#align submodule.finite_dimensional_supr Submodule.finiteDimensional_iSup
/-- In a finite-dimensional vector space, the dimensions of a submodule and of the corresponding
quotient add up to the dimension of the space. -/
theorem finrank_quotient_add_finrank [FiniteDimensional K V] (s : Submodule K V) :
finrank K (V ⧸ s) + finrank K s = finrank K V := by
have := rank_quotient_add_rank s
rw [← finrank_eq_rank, ← finrank_eq_rank, ← finrank_eq_rank] at this
exact mod_cast this
#align submodule.finrank_quotient_add_finrank Submodule.finrank_quotient_add_finrank
/-- The dimension of a strict submodule is strictly bounded by the dimension of the ambient
space. -/
theorem finrank_lt [FiniteDimensional K V] {s : Submodule K V} (h : s < ⊤) :
finrank K s < finrank K V := by
rw [← s.finrank_quotient_add_finrank, add_comm]
exact Nat.lt_add_of_pos_right (finrank_pos_iff.mpr (Quotient.nontrivial_of_lt_top _ h))
#align submodule.finrank_lt Submodule.finrank_lt
/-- The sum of the dimensions of s + t and s ∩ t is the sum of the dimensions of s and t -/
theorem finrank_sup_add_finrank_inf_eq (s t : Submodule K V) [FiniteDimensional K s]
[FiniteDimensional K t] :
finrank K ↑(s ⊔ t) + finrank K ↑(s ⊓ t) = finrank K ↑s + finrank K ↑t := by
have key : Module.rank K ↑(s ⊔ t) + Module.rank K ↑(s ⊓ t) = Module.rank K s + Module.rank K t :=
rank_sup_add_rank_inf_eq s t
repeat rw [← finrank_eq_rank] at key
norm_cast at key
#align submodule.finrank_sup_add_finrank_inf_eq Submodule.finrank_sup_add_finrank_inf_eq
theorem finrank_add_le_finrank_add_finrank (s t : Submodule K V) [FiniteDimensional K s]
[FiniteDimensional K t] : finrank K (s ⊔ t : Submodule K V) ≤ finrank K s + finrank K t := by
rw [← finrank_sup_add_finrank_inf_eq]
exact self_le_add_right _ _
#align submodule.finrank_add_le_finrank_add_finrank Submodule.finrank_add_le_finrank_add_finrank
theorem eq_top_of_disjoint [FiniteDimensional K V] (s t : Submodule K V)
(hdim : finrank K s + finrank K t = finrank K V) (hdisjoint : Disjoint s t) : s ⊔ t = ⊤ := by
have h_finrank_inf : finrank K ↑(s ⊓ t) = 0 := by
rw [disjoint_iff_inf_le, le_bot_iff] at hdisjoint
rw [hdisjoint, finrank_bot]
apply eq_top_of_finrank_eq
rw [← hdim]
convert s.finrank_sup_add_finrank_inf_eq t
rw [h_finrank_inf]
rfl
#align submodule.eq_top_of_disjoint Submodule.eq_top_of_disjoint
theorem finrank_add_finrank_le_of_disjoint [FiniteDimensional K V]
{s t : Submodule K V} (hdisjoint : Disjoint s t) :
finrank K s + finrank K t ≤ finrank K V := by
rw [← Submodule.finrank_sup_add_finrank_inf_eq s t, hdisjoint.eq_bot, finrank_bot, add_zero]
exact Submodule.finrank_le _
end DivisionRing
end Submodule
namespace LinearEquiv
open FiniteDimensional
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- Finite dimensionality is preserved under linear equivalence. -/
protected theorem finiteDimensional (f : V ≃ₗ[K] V₂) [FiniteDimensional K V] :
FiniteDimensional K V₂ :=
Module.Finite.equiv f
#align linear_equiv.finite_dimensional LinearEquiv.finiteDimensional
variable {R M M₂ : Type*} [Ring R] [AddCommGroup M] [AddCommGroup M₂]
variable [Module R M] [Module R M₂]
end LinearEquiv
section
variable [DivisionRing K] [AddCommGroup V] [Module K V]
instance finiteDimensional_finsupp {ι : Type*} [Finite ι] [FiniteDimensional K V] :
FiniteDimensional K (ι →₀ V) :=
Module.Finite.finsupp
#align finite_dimensional_finsupp finiteDimensional_finsupp
end
namespace FiniteDimensional
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- If a submodule is contained in a finite-dimensional
submodule with the same or smaller dimension, they are equal. -/
theorem eq_of_le_of_finrank_le {S₁ S₂ : Submodule K V} [FiniteDimensional K S₂] (hle : S₁ ≤ S₂)
(hd : finrank K S₂ ≤ finrank K S₁) : S₁ = S₂ := by
rw [← LinearEquiv.finrank_eq (Submodule.comapSubtypeEquivOfLe hle)] at hd
exact le_antisymm hle (Submodule.comap_subtype_eq_top.1
(eq_top_of_finrank_eq (le_antisymm (comap (Submodule.subtype S₂) S₁).finrank_le hd)))
#align finite_dimensional.eq_of_le_of_finrank_le FiniteDimensional.eq_of_le_of_finrank_le
/-- If a submodule is contained in a finite-dimensional
submodule with the same dimension, they are equal. -/
theorem eq_of_le_of_finrank_eq {S₁ S₂ : Submodule K V} [FiniteDimensional K S₂] (hle : S₁ ≤ S₂)
(hd : finrank K S₁ = finrank K S₂) : S₁ = S₂ :=
eq_of_le_of_finrank_le hle hd.ge
#align finite_dimensional.eq_of_le_of_finrank_eq FiniteDimensional.eq_of_le_of_finrank_eq
section Subalgebra
variable {K L : Type*} [Field K] [Ring L] [Algebra K L] {F E : Subalgebra K L}
[hfin : FiniteDimensional K E] (h_le : F ≤ E)
/-- If a subalgebra is contained in a finite-dimensional
subalgebra with the same or smaller dimension, they are equal. -/
theorem _root_.Subalgebra.eq_of_le_of_finrank_le (h_finrank : finrank K E ≤ finrank K F) : F = E :=
haveI : Module.Finite K (Subalgebra.toSubmodule E) := hfin
Subalgebra.toSubmodule_injective <| FiniteDimensional.eq_of_le_of_finrank_le h_le h_finrank
/-- If a subalgebra is contained in a finite-dimensional
subalgebra with the same dimension, they are equal. -/
theorem _root_.Subalgebra.eq_of_le_of_finrank_eq (h_finrank : finrank K F = finrank K E) : F = E :=
Subalgebra.eq_of_le_of_finrank_le h_le h_finrank.ge
end Subalgebra
variable [FiniteDimensional K V] [FiniteDimensional K V₂]
/-- Given isomorphic subspaces `p q` of vector spaces `V` and `V₁` respectively,
`p.quotient` is isomorphic to `q.quotient`. -/
noncomputable def LinearEquiv.quotEquivOfEquiv {p : Subspace K V} {q : Subspace K V₂}
(f₁ : p ≃ₗ[K] q) (f₂ : V ≃ₗ[K] V₂) : (V ⧸ p) ≃ₗ[K] V₂ ⧸ q :=
LinearEquiv.ofFinrankEq _ _
(by
rw [← @add_right_cancel_iff _ _ _ (finrank K p), Submodule.finrank_quotient_add_finrank,
LinearEquiv.finrank_eq f₁, Submodule.finrank_quotient_add_finrank,
LinearEquiv.finrank_eq f₂])
#align finite_dimensional.linear_equiv.quot_equiv_of_equiv FiniteDimensional.LinearEquiv.quotEquivOfEquiv
-- TODO: generalize to the case where one of `p` and `q` is finite-dimensional.
/-- Given the subspaces `p q`, if `p.quotient ≃ₗ[K] q`, then `q.quotient ≃ₗ[K] p` -/
noncomputable def LinearEquiv.quotEquivOfQuotEquiv {p q : Subspace K V} (f : (V ⧸ p) ≃ₗ[K] q) :
(V ⧸ q) ≃ₗ[K] p :=
LinearEquiv.ofFinrankEq _ _ <|
add_right_cancel <| by
rw [Submodule.finrank_quotient_add_finrank, ← LinearEquiv.finrank_eq f, add_comm,
Submodule.finrank_quotient_add_finrank]
#align finite_dimensional.linear_equiv.quot_equiv_of_quot_equiv FiniteDimensional.LinearEquiv.quotEquivOfQuotEquiv
end DivisionRing
end FiniteDimensional
namespace LinearMap
open FiniteDimensional
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- On a finite-dimensional space, an injective linear map is surjective. -/
theorem surjective_of_injective [FiniteDimensional K V] {f : V →ₗ[K] V} (hinj : Injective f) :
Surjective f := by
have h := rank_range_of_injective _ hinj
rw [← finrank_eq_rank, ← finrank_eq_rank, natCast_inj] at h
exact range_eq_top.1 (eq_top_of_finrank_eq h)
#align linear_map.surjective_of_injective LinearMap.surjective_of_injective
/-- The image under an onto linear map of a finite-dimensional space is also finite-dimensional. -/
theorem finiteDimensional_of_surjective [FiniteDimensional K V] (f : V →ₗ[K] V₂)
(hf : LinearMap.range f = ⊤) : FiniteDimensional K V₂ :=
Module.Finite.of_surjective f <| range_eq_top.1 hf
#align linear_map.finite_dimensional_of_surjective LinearMap.finiteDimensional_of_surjective
/-- The range of a linear map defined on a finite-dimensional space is also finite-dimensional. -/
instance finiteDimensional_range [FiniteDimensional K V] (f : V →ₗ[K] V₂) :
FiniteDimensional K (LinearMap.range f) :=
Module.Finite.range f
#align linear_map.finite_dimensional_range LinearMap.finiteDimensional_range
/-- On a finite-dimensional space, a linear map is injective if and only if it is surjective. -/
theorem injective_iff_surjective [FiniteDimensional K V] {f : V →ₗ[K] V} :
Injective f ↔ Surjective f :=
⟨surjective_of_injective, fun hsurj =>
let ⟨g, hg⟩ := f.exists_rightInverse_of_surjective (range_eq_top.2 hsurj)
have : Function.RightInverse g f := LinearMap.ext_iff.1 hg
(leftInverse_of_surjective_of_rightInverse (surjective_of_injective this.injective)
this).injective⟩
#align linear_map.injective_iff_surjective LinearMap.injective_iff_surjective
lemma injOn_iff_surjOn {p : Submodule K V} [FiniteDimensional K p]
{f : V →ₗ[K] V} (h : ∀ x ∈ p, f x ∈ p) :
Set.InjOn f p ↔ Set.SurjOn f p p := by
rw [Set.injOn_iff_injective, ← Set.MapsTo.restrict_surjective_iff h]
change Injective (f.domRestrict p) ↔ Surjective (f.restrict h)
simp [disjoint_iff, ← injective_iff_surjective]
theorem ker_eq_bot_iff_range_eq_top [FiniteDimensional K V] {f : V →ₗ[K] V} :
LinearMap.ker f = ⊥ ↔ LinearMap.range f = ⊤ := by
rw [range_eq_top, ker_eq_bot, injective_iff_surjective]
#align linear_map.ker_eq_bot_iff_range_eq_top LinearMap.ker_eq_bot_iff_range_eq_top
/-- In a finite-dimensional space, if linear maps are inverse to each other on one side then they
are also inverse to each other on the other side. -/
theorem mul_eq_one_of_mul_eq_one [FiniteDimensional K V] {f g : V →ₗ[K] V} (hfg : f * g = 1) :
g * f = 1 := by
have ginj : Injective g :=
HasLeftInverse.injective ⟨f, fun x => show (f * g) x = (1 : V →ₗ[K] V) x by rw [hfg]⟩
let ⟨i, hi⟩ :=
g.exists_rightInverse_of_surjective (range_eq_top.2 (injective_iff_surjective.1 ginj))
have : f * (g * i) = f * 1 := congr_arg _ hi
rw [← mul_assoc, hfg, one_mul, mul_one] at this; rwa [← this]
#align linear_map.mul_eq_one_of_mul_eq_one LinearMap.mul_eq_one_of_mul_eq_one
/-- In a finite-dimensional space, linear maps are inverse to each other on one side if and only if
they are inverse to each other on the other side. -/
theorem mul_eq_one_comm [FiniteDimensional K V] {f g : V →ₗ[K] V} : f * g = 1 ↔ g * f = 1 :=
⟨mul_eq_one_of_mul_eq_one, mul_eq_one_of_mul_eq_one⟩
#align linear_map.mul_eq_one_comm LinearMap.mul_eq_one_comm
/-- In a finite-dimensional space, linear maps are inverse to each other on one side if and only if
they are inverse to each other on the other side. -/
theorem comp_eq_id_comm [FiniteDimensional K V] {f g : V →ₗ[K] V} : f.comp g = id ↔ g.comp f = id :=
mul_eq_one_comm
#align linear_map.comp_eq_id_comm LinearMap.comp_eq_id_comm
/-- rank-nullity theorem : the dimensions of the kernel and the range of a linear map add up to
the dimension of the source space. -/
theorem finrank_range_add_finrank_ker [FiniteDimensional K V] (f : V →ₗ[K] V₂) :
finrank K (LinearMap.range f) + finrank K (LinearMap.ker f) = finrank K V := by
rw [← f.quotKerEquivRange.finrank_eq]
exact Submodule.finrank_quotient_add_finrank _
#align linear_map.finrank_range_add_finrank_ker LinearMap.finrank_range_add_finrank_ker
lemma ker_ne_bot_of_finrank_lt [FiniteDimensional K V] [FiniteDimensional K V₂] {f : V →ₗ[K] V₂}
(h : finrank K V₂ < finrank K V) :
LinearMap.ker f ≠ ⊥ := by
have h₁ := f.finrank_range_add_finrank_ker
have h₂ : finrank K (LinearMap.range f) ≤ finrank K V₂ := (LinearMap.range f).finrank_le
suffices 0 < finrank K (LinearMap.ker f) from Submodule.one_le_finrank_iff.mp this
omega
theorem comap_eq_sup_ker_of_disjoint {p : Submodule K V} [FiniteDimensional K p] {f : V →ₗ[K] V}
(h : ∀ x ∈ p, f x ∈ p) (h' : Disjoint p (ker f)) :
p.comap f = p ⊔ ker f := by
refine le_antisymm (fun x hx ↦ ?_) (sup_le_iff.mpr ⟨h, ker_le_comap _⟩)
obtain ⟨⟨y, hy⟩, hxy⟩ :=
surjective_of_injective ((injective_restrict_iff_disjoint h).mpr h') ⟨f x, hx⟩
replace hxy : f y = f x := by simpa [Subtype.ext_iff] using hxy
exact Submodule.mem_sup.mpr ⟨y, hy, x - y, by simp [hxy], add_sub_cancel y x⟩
theorem ker_comp_eq_of_commute_of_disjoint_ker [FiniteDimensional K V] {f g : V →ₗ[K] V}
(h : Commute f g) (h' : Disjoint (ker f) (ker g)) :
ker (f ∘ₗ g) = ker f ⊔ ker g := by
suffices ∀ x, f x = 0 → f (g x) = 0 by rw [ker_comp, comap_eq_sup_ker_of_disjoint _ h']; simpa
intro x hx
rw [← comp_apply, ← mul_eq_comp, h.eq, mul_apply, hx, _root_.map_zero]
| Mathlib/LinearAlgebra/FiniteDimensional.lean | 724 | 739 | theorem ker_noncommProd_eq_of_supIndep_ker [FiniteDimensional K V] {ι : Type*} {f : ι → V →ₗ[K] V}
(s : Finset ι) (comm) (h : s.SupIndep fun i ↦ ker (f i)) :
ker (s.noncommProd f comm) = ⨆ i ∈ s, ker (f i) := by |
classical
induction' s using Finset.induction_on with i s hi ih
· set_option tactic.skipAssignedInstances false in
simpa using LinearMap.ker_id
replace ih : ker (Finset.noncommProd s f <| Set.Pairwise.mono (s.subset_insert i) comm) =
⨆ x ∈ s, ker (f x) := ih _ (h.subset (s.subset_insert i))
rw [Finset.noncommProd_insert_of_not_mem _ _ _ _ hi, mul_eq_comp,
ker_comp_eq_of_commute_of_disjoint_ker]
· simp_rw [Finset.mem_insert_coe, iSup_insert, Finset.mem_coe, ih]
· exact s.noncommProd_commute _ _ _ fun j hj ↦
comm (s.mem_insert_self i) (Finset.mem_insert_of_mem hj) (by aesop)
· replace h := Finset.supIndep_iff_disjoint_erase.mp h i (s.mem_insert_self i)
simpa [ih, hi, Finset.sup_eq_iSup] using h
|
/-
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
theorem rpow_neg_one (x : ℝ≥0∞) : x ^ (-1 : ℝ) = x⁻¹ := by simp [rpow_neg]
#align ennreal.rpow_neg_one ENNReal.rpow_neg_one
theorem rpow_mul (x : ℝ≥0∞) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z := by
cases' x with x
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [Hy, Hz, zero_rpow_of_neg, zero_rpow_of_pos, top_rpow_of_neg, top_rpow_of_pos,
mul_pos_of_neg_of_neg, mul_neg_of_neg_of_pos, mul_neg_of_pos_of_neg]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [h, Hy, Hz, zero_rpow_of_neg, zero_rpow_of_pos, top_rpow_of_neg, top_rpow_of_pos,
mul_pos_of_neg_of_neg, mul_neg_of_neg_of_pos, mul_neg_of_pos_of_neg]
· have : x ^ y ≠ 0 := by simp [h]
simp [coe_rpow_of_ne_zero h, coe_rpow_of_ne_zero this, NNReal.rpow_mul]
#align ennreal.rpow_mul ENNReal.rpow_mul
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ≥0∞) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by
cases x
· cases n <;> simp [top_rpow_of_pos (Nat.cast_add_one_pos _), top_pow (Nat.succ_pos _)]
· simp [coe_rpow_of_nonneg _ (Nat.cast_nonneg n)]
#align ennreal.rpow_nat_cast ENNReal.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) :=
rpow_natCast x n
@[simp, norm_cast]
lemma rpow_intCast (x : ℝ≥0∞) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by
cases n <;> simp only [Int.ofNat_eq_coe, Int.cast_natCast, rpow_natCast, zpow_natCast,
Int.cast_negSucc, rpow_neg, zpow_negSucc]
@[deprecated (since := "2024-04-17")]
alias rpow_int_cast := rpow_intCast
theorem rpow_two (x : ℝ≥0∞) : x ^ (2 : ℝ) = x ^ 2 := rpow_ofNat x 2
#align ennreal.rpow_two ENNReal.rpow_two
theorem mul_rpow_eq_ite (x y : ℝ≥0∞) (z : ℝ) :
(x * y) ^ z = if (x = 0 ∧ y = ⊤ ∨ x = ⊤ ∧ y = 0) ∧ z < 0 then ⊤ else x ^ z * y ^ z := by
rcases eq_or_ne z 0 with (rfl | hz); · simp
replace hz := hz.lt_or_lt
wlog hxy : x ≤ y
· convert this y x z hz (le_of_not_le hxy) using 2 <;> simp only [mul_comm, and_comm, or_comm]
rcases eq_or_ne x 0 with (rfl | hx0)
· induction y <;> cases' hz with hz hz <;> simp [*, hz.not_lt]
rcases eq_or_ne y 0 with (rfl | hy0)
· exact (hx0 (bot_unique hxy)).elim
induction x
· cases' hz with hz hz <;> simp [hz, top_unique hxy]
induction y
· rw [ne_eq, coe_eq_zero] at hx0
cases' hz with hz hz <;> simp [*]
simp only [*, false_and_iff, and_false_iff, false_or_iff, if_false]
norm_cast at *
rw [coe_rpow_of_ne_zero (mul_ne_zero hx0 hy0), NNReal.mul_rpow]
norm_cast
#align ennreal.mul_rpow_eq_ite ENNReal.mul_rpow_eq_ite
theorem mul_rpow_of_ne_top {x y : ℝ≥0∞} (hx : x ≠ ⊤) (hy : y ≠ ⊤) (z : ℝ) :
(x * y) ^ z = x ^ z * y ^ z := by simp [*, mul_rpow_eq_ite]
#align ennreal.mul_rpow_of_ne_top ENNReal.mul_rpow_of_ne_top
@[norm_cast]
theorem coe_mul_rpow (x y : ℝ≥0) (z : ℝ) : ((x : ℝ≥0∞) * y) ^ z = (x : ℝ≥0∞) ^ z * (y : ℝ≥0∞) ^ z :=
mul_rpow_of_ne_top coe_ne_top coe_ne_top z
#align ennreal.coe_mul_rpow ENNReal.coe_mul_rpow
theorem prod_coe_rpow {ι} (s : Finset ι) (f : ι → ℝ≥0) (r : ℝ) :
∏ i ∈ s, (f i : ℝ≥0∞) ^ r = ((∏ i ∈ s, f i : ℝ≥0) : ℝ≥0∞) ^ r := by
induction s using Finset.induction with
| empty => simp
| insert hi ih => simp_rw [prod_insert hi, ih, ← coe_mul_rpow, coe_mul]
theorem mul_rpow_of_ne_zero {x y : ℝ≥0∞} (hx : x ≠ 0) (hy : y ≠ 0) (z : ℝ) :
(x * y) ^ z = x ^ z * y ^ z := by simp [*, mul_rpow_eq_ite]
#align ennreal.mul_rpow_of_ne_zero ENNReal.mul_rpow_of_ne_zero
theorem mul_rpow_of_nonneg (x y : ℝ≥0∞) {z : ℝ} (hz : 0 ≤ z) : (x * y) ^ z = x ^ z * y ^ z := by
simp [hz.not_lt, mul_rpow_eq_ite]
#align ennreal.mul_rpow_of_nonneg ENNReal.mul_rpow_of_nonneg
theorem prod_rpow_of_ne_top {ι} {s : Finset ι} {f : ι → ℝ≥0∞} (hf : ∀ i ∈ s, f i ≠ ∞) (r : ℝ) :
∏ i ∈ s, f i ^ r = (∏ i ∈ s, f i) ^ r := by
induction s using Finset.induction with
| empty => simp
| @insert i s hi ih =>
have h2f : ∀ i ∈ s, f i ≠ ∞ := fun i hi ↦ hf i <| mem_insert_of_mem hi
rw [prod_insert hi, prod_insert hi, ih h2f, ← mul_rpow_of_ne_top <| hf i <| mem_insert_self ..]
apply prod_lt_top h2f |>.ne
theorem prod_rpow_of_nonneg {ι} {s : Finset ι} {f : ι → ℝ≥0∞} {r : ℝ} (hr : 0 ≤ r) :
∏ i ∈ s, f i ^ r = (∏ i ∈ s, f i) ^ r := by
induction s using Finset.induction with
| empty => simp
| insert hi ih => simp_rw [prod_insert hi, ih, ← mul_rpow_of_nonneg _ _ hr]
theorem inv_rpow (x : ℝ≥0∞) (y : ℝ) : x⁻¹ ^ y = (x ^ y)⁻¹ := by
rcases eq_or_ne y 0 with (rfl | hy); · simp only [rpow_zero, inv_one]
replace hy := hy.lt_or_lt
rcases eq_or_ne x 0 with (rfl | h0); · cases hy <;> simp [*]
rcases eq_or_ne x ⊤ with (rfl | h_top); · cases hy <;> simp [*]
apply ENNReal.eq_inv_of_mul_eq_one_left
rw [← mul_rpow_of_ne_zero (ENNReal.inv_ne_zero.2 h_top) h0, ENNReal.inv_mul_cancel h0 h_top,
one_rpow]
#align ennreal.inv_rpow ENNReal.inv_rpow
theorem div_rpow_of_nonneg (x y : ℝ≥0∞) {z : ℝ} (hz : 0 ≤ z) : (x / y) ^ z = x ^ z / y ^ z := by
rw [div_eq_mul_inv, mul_rpow_of_nonneg _ _ hz, inv_rpow, div_eq_mul_inv]
#align ennreal.div_rpow_of_nonneg ENNReal.div_rpow_of_nonneg
theorem strictMono_rpow_of_pos {z : ℝ} (h : 0 < z) : StrictMono fun x : ℝ≥0∞ => x ^ z := by
intro x y hxy
lift x to ℝ≥0 using ne_top_of_lt hxy
rcases eq_or_ne y ∞ with (rfl | hy)
· simp only [top_rpow_of_pos h, coe_rpow_of_nonneg _ h.le, coe_lt_top]
· lift y to ℝ≥0 using hy
simp only [coe_rpow_of_nonneg _ h.le, NNReal.rpow_lt_rpow (coe_lt_coe.1 hxy) h, coe_lt_coe]
#align ennreal.strict_mono_rpow_of_pos ENNReal.strictMono_rpow_of_pos
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
#align ennreal.monotone_rpow_of_nonneg ENNReal.monotone_rpow_of_nonneg
/-- 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]
#align ennreal.order_iso_rpow ENNReal.orderIsoRpow
theorem orderIsoRpow_symm_apply (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
#align ennreal.order_iso_rpow_symm_apply ENNReal.orderIsoRpow_symm_apply
@[gcongr] theorem rpow_le_rpow {x y : ℝ≥0∞} {z : ℝ} (h₁ : x ≤ y) (h₂ : 0 ≤ z) : x ^ z ≤ y ^ z :=
monotone_rpow_of_nonneg h₂ h₁
#align ennreal.rpow_le_rpow ENNReal.rpow_le_rpow
@[gcongr] theorem rpow_lt_rpow {x y : ℝ≥0∞} {z : ℝ} (h₁ : x < y) (h₂ : 0 < z) : x ^ z < y ^ z :=
strictMono_rpow_of_pos h₂ h₁
#align ennreal.rpow_lt_rpow ENNReal.rpow_lt_rpow
theorem rpow_le_rpow_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x ^ z ≤ y ^ z ↔ x ≤ y :=
(strictMono_rpow_of_pos hz).le_iff_le
#align ennreal.rpow_le_rpow_iff ENNReal.rpow_le_rpow_iff
theorem rpow_lt_rpow_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x ^ z < y ^ z ↔ x < y :=
(strictMono_rpow_of_pos hz).lt_iff_lt
#align ennreal.rpow_lt_rpow_iff ENNReal.rpow_lt_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
nth_rw 1 [← rpow_one x]
nth_rw 1 [← @_root_.mul_inv_cancel _ _ z hz.ne']
rw [rpow_mul, ← one_div, @rpow_le_rpow_iff _ _ (1 / z) (by simp [hz])]
#align ennreal.le_rpow_one_div_iff ENNReal.le_rpow_one_div_iff
theorem lt_rpow_one_div_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x < y ^ (1 / z) ↔ x ^ z < y := by
nth_rw 1 [← rpow_one x]
nth_rw 1 [← @_root_.mul_inv_cancel _ _ z (ne_of_lt hz).symm]
rw [rpow_mul, ← one_div, @rpow_lt_rpow_iff _ _ (1 / z) (by simp [hz])]
#align ennreal.lt_rpow_one_div_iff ENNReal.lt_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
nth_rw 1 [← ENNReal.rpow_one y]
nth_rw 2 [← @_root_.mul_inv_cancel _ _ z hz.ne.symm]
rw [ENNReal.rpow_mul, ← one_div, ENNReal.rpow_le_rpow_iff (one_div_pos.2 hz)]
#align ennreal.rpow_one_div_le_iff ENNReal.rpow_one_div_le_iff
theorem rpow_lt_rpow_of_exponent_lt {x : ℝ≥0∞} {y z : ℝ} (hx : 1 < x) (hx' : x ≠ ⊤) (hyz : y < z) :
x ^ y < x ^ z := by
lift x to ℝ≥0 using hx'
rw [one_lt_coe_iff] at hx
simp [coe_rpow_of_ne_zero (ne_of_gt (lt_trans zero_lt_one hx)),
NNReal.rpow_lt_rpow_of_exponent_lt hx hyz]
#align ennreal.rpow_lt_rpow_of_exponent_lt ENNReal.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 := by
cases x
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [Hy, Hz, top_rpow_of_neg, top_rpow_of_pos, le_refl] <;>
linarith
· simp only [one_le_coe_iff, some_eq_coe] at hx
simp [coe_rpow_of_ne_zero (ne_of_gt (lt_of_lt_of_le zero_lt_one hx)),
NNReal.rpow_le_rpow_of_exponent_le hx hyz]
#align ennreal.rpow_le_rpow_of_exponent_le ENNReal.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 := by
lift x to ℝ≥0 using ne_of_lt (lt_of_lt_of_le hx1 le_top)
simp only [coe_lt_one_iff, coe_pos] at hx0 hx1
simp [coe_rpow_of_ne_zero (ne_of_gt hx0), NNReal.rpow_lt_rpow_of_exponent_gt hx0 hx1 hyz]
#align ennreal.rpow_lt_rpow_of_exponent_gt ENNReal.rpow_lt_rpow_of_exponent_gt
theorem rpow_le_rpow_of_exponent_ge {x : ℝ≥0∞} {y z : ℝ} (hx1 : x ≤ 1) (hyz : z ≤ y) :
x ^ y ≤ x ^ z := by
lift x to ℝ≥0 using ne_of_lt (lt_of_le_of_lt hx1 coe_lt_top)
by_cases h : x = 0
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [Hy, Hz, h, zero_rpow_of_neg, zero_rpow_of_pos, le_refl] <;>
linarith
· rw [coe_le_one_iff] at hx1
simp [coe_rpow_of_ne_zero h,
NNReal.rpow_le_rpow_of_exponent_ge (bot_lt_iff_ne_bot.mpr h) hx1 hyz]
#align ennreal.rpow_le_rpow_of_exponent_ge ENNReal.rpow_le_rpow_of_exponent_ge
theorem rpow_le_self_of_le_one {x : ℝ≥0∞} {z : ℝ} (hx : x ≤ 1) (h_one_le : 1 ≤ z) : x ^ z ≤ x := by
nth_rw 2 [← ENNReal.rpow_one x]
exact ENNReal.rpow_le_rpow_of_exponent_ge hx h_one_le
#align ennreal.rpow_le_self_of_le_one ENNReal.rpow_le_self_of_le_one
theorem le_rpow_self_of_one_le {x : ℝ≥0∞} {z : ℝ} (hx : 1 ≤ x) (h_one_le : 1 ≤ z) : x ≤ x ^ z := by
nth_rw 1 [← ENNReal.rpow_one x]
exact ENNReal.rpow_le_rpow_of_exponent_le hx h_one_le
#align ennreal.le_rpow_self_of_one_le ENNReal.le_rpow_self_of_one_le
theorem rpow_pos_of_nonneg {p : ℝ} {x : ℝ≥0∞} (hx_pos : 0 < x) (hp_nonneg : 0 ≤ p) : 0 < x ^ p := by
by_cases hp_zero : p = 0
· simp [hp_zero, zero_lt_one]
· rw [← Ne] at hp_zero
have hp_pos := lt_of_le_of_ne hp_nonneg hp_zero.symm
rw [← zero_rpow_of_pos hp_pos]
exact rpow_lt_rpow hx_pos hp_pos
#align ennreal.rpow_pos_of_nonneg ENNReal.rpow_pos_of_nonneg
theorem rpow_pos {p : ℝ} {x : ℝ≥0∞} (hx_pos : 0 < x) (hx_ne_top : x ≠ ⊤) : 0 < x ^ p := by
cases' lt_or_le 0 p with hp_pos hp_nonpos
· exact rpow_pos_of_nonneg hx_pos (le_of_lt hp_pos)
· rw [← neg_neg p, rpow_neg, ENNReal.inv_pos]
exact rpow_ne_top_of_nonneg (Right.nonneg_neg_iff.mpr hp_nonpos) hx_ne_top
#align ennreal.rpow_pos ENNReal.rpow_pos
theorem rpow_lt_one {x : ℝ≥0∞} {z : ℝ} (hx : x < 1) (hz : 0 < z) : x ^ z < 1 := by
lift x to ℝ≥0 using ne_of_lt (lt_of_lt_of_le hx le_top)
simp only [coe_lt_one_iff] at hx
simp [coe_rpow_of_nonneg _ (le_of_lt hz), NNReal.rpow_lt_one hx hz]
#align ennreal.rpow_lt_one ENNReal.rpow_lt_one
theorem rpow_le_one {x : ℝ≥0∞} {z : ℝ} (hx : x ≤ 1) (hz : 0 ≤ z) : x ^ z ≤ 1 := by
lift x to ℝ≥0 using ne_of_lt (lt_of_le_of_lt hx coe_lt_top)
simp only [coe_le_one_iff] at hx
simp [coe_rpow_of_nonneg _ hz, NNReal.rpow_le_one hx hz]
#align ennreal.rpow_le_one ENNReal.rpow_le_one
| Mathlib/Analysis/SpecialFunctions/Pow/NNReal.lean | 810 | 815 | theorem rpow_lt_one_of_one_lt_of_neg {x : ℝ≥0∞} {z : ℝ} (hx : 1 < x) (hz : z < 0) : x ^ z < 1 := by |
cases x
· simp [top_rpow_of_neg hz, zero_lt_one]
· simp only [some_eq_coe, one_lt_coe_iff] at hx
simp [coe_rpow_of_ne_zero (ne_of_gt (lt_trans zero_lt_one hx)),
NNReal.rpow_lt_one_of_one_lt_of_neg hx hz]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Basic
import Mathlib.Data.Nat.SuccPred
#align_import set_theory.ordinal.arithmetic from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Ordinal arithmetic
Ordinals have an addition (corresponding to disjoint union) that turns them into an additive
monoid, and a multiplication (corresponding to the lexicographic order on the product) that turns
them into a monoid. One can also define correspondingly a subtraction, a division, a successor
function, a power function and a logarithm function.
We also define limit ordinals and prove the basic induction principle on ordinals separating
successor ordinals and limit ordinals, in `limitRecOn`.
## Main definitions and results
* `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that
every element of `o₁` is smaller than every element of `o₂`.
* `o₁ - o₂` is the unique ordinal `o` such that `o₂ + o = o₁`, when `o₂ ≤ o₁`.
* `o₁ * o₂` is the lexicographic order on `o₂ × o₁`.
* `o₁ / o₂` is the ordinal `o` such that `o₁ = o₂ * o + o'` with `o' < o₂`. We also define the
divisibility predicate, and a modulo operation.
* `Order.succ o = o + 1` is the successor of `o`.
* `pred o` if the predecessor of `o`. If `o` is not a successor, we set `pred o = o`.
We discuss the properties of casts of natural numbers of and of `ω` with respect to these
operations.
Some properties of the operations are also used to discuss general tools on ordinals:
* `IsLimit o`: an ordinal is a limit ordinal if it is neither `0` nor a successor.
* `limitRecOn` is the main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals.
* `IsNormal`: a function `f : Ordinal → Ordinal` satisfies `IsNormal` if it is strictly increasing
and order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`.
* `enumOrd`: enumerates an unbounded set of ordinals by the ordinals themselves.
* `sup`, `lsub`: the supremum / least strict upper bound of an indexed family of ordinals in
`Type u`, as an ordinal in `Type u`.
* `bsup`, `blsub`: the supremum / least strict upper bound of a set of ordinals indexed by ordinals
less than a given ordinal `o`.
Various other basic arithmetic results are given in `Principal.lean` instead.
-/
assert_not_exists Field
assert_not_exists Module
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal Ordinal
universe u v w
namespace Ordinal
variable {α : Type*} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Further properties of addition on ordinals -/
@[simp]
theorem lift_add (a b : Ordinal.{v}) : lift.{u} (a + b) = lift.{u} a + lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.sumLexCongr (RelIso.preimage Equiv.ulift _) (RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_add Ordinal.lift_add
@[simp]
theorem lift_succ (a : Ordinal.{v}) : lift.{u} (succ a) = succ (lift.{u} a) := by
rw [← add_one_eq_succ, lift_add, lift_one]
rfl
#align ordinal.lift_succ Ordinal.lift_succ
instance add_contravariantClass_le : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· ≤ ·) :=
⟨fun a b c =>
inductionOn a fun α r hr =>
inductionOn b fun β₁ s₁ hs₁ =>
inductionOn c fun β₂ s₂ hs₂ ⟨f⟩ =>
⟨have fl : ∀ a, f (Sum.inl a) = Sum.inl a := fun a => by
simpa only [InitialSeg.trans_apply, InitialSeg.leAdd_apply] using
@InitialSeg.eq _ _ _ _ _
((InitialSeg.leAdd r s₁).trans f) (InitialSeg.leAdd r s₂) a
have : ∀ b, { b' // f (Sum.inr b) = Sum.inr b' } := by
intro b; cases e : f (Sum.inr b)
· rw [← fl] at e
have := f.inj' e
contradiction
· exact ⟨_, rfl⟩
let g (b) := (this b).1
have fr : ∀ b, f (Sum.inr b) = Sum.inr (g b) := fun b => (this b).2
⟨⟨⟨g, fun x y h => by
injection f.inj' (by rw [fr, fr, h] : f (Sum.inr x) = f (Sum.inr y))⟩,
@fun a b => by
-- Porting note:
-- `relEmbedding.coe_fn_to_embedding` & `initial_seg.coe_fn_to_rel_embedding`
-- → `InitialSeg.coe_coe_fn`
simpa only [Sum.lex_inr_inr, fr, InitialSeg.coe_coe_fn, Embedding.coeFn_mk] using
@RelEmbedding.map_rel_iff _ _ _ _ f.toRelEmbedding (Sum.inr a) (Sum.inr b)⟩,
fun a b H => by
rcases f.init (by rw [fr] <;> exact Sum.lex_inr_inr.2 H) with ⟨a' | a', h⟩
· rw [fl] at h
cases h
· rw [fr] at h
exact ⟨a', Sum.inr.inj h⟩⟩⟩⟩
#align ordinal.add_contravariant_class_le Ordinal.add_contravariantClass_le
theorem add_left_cancel (a) {b c : Ordinal} : a + b = a + c ↔ b = c := by
simp only [le_antisymm_iff, add_le_add_iff_left]
#align ordinal.add_left_cancel Ordinal.add_left_cancel
private theorem add_lt_add_iff_left' (a) {b c : Ordinal} : a + b < a + c ↔ b < c := by
rw [← not_le, ← not_le, add_le_add_iff_left]
instance add_covariantClass_lt : CovariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).2⟩
#align ordinal.add_covariant_class_lt Ordinal.add_covariantClass_lt
instance add_contravariantClass_lt : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).1⟩
#align ordinal.add_contravariant_class_lt Ordinal.add_contravariantClass_lt
instance add_swap_contravariantClass_lt :
ContravariantClass Ordinal.{u} Ordinal.{u} (swap (· + ·)) (· < ·) :=
⟨fun _a _b _c => lt_imp_lt_of_le_imp_le fun h => add_le_add_right h _⟩
#align ordinal.add_swap_contravariant_class_lt Ordinal.add_swap_contravariantClass_lt
theorem add_le_add_iff_right {a b : Ordinal} : ∀ n : ℕ, a + n ≤ b + n ↔ a ≤ b
| 0 => by simp
| n + 1 => by
simp only [natCast_succ, add_succ, add_succ, succ_le_succ_iff, add_le_add_iff_right]
#align ordinal.add_le_add_iff_right Ordinal.add_le_add_iff_right
theorem add_right_cancel {a b : Ordinal} (n : ℕ) : a + n = b + n ↔ a = b := by
simp only [le_antisymm_iff, add_le_add_iff_right]
#align ordinal.add_right_cancel Ordinal.add_right_cancel
theorem add_eq_zero_iff {a b : Ordinal} : a + b = 0 ↔ a = 0 ∧ b = 0 :=
inductionOn a fun α r _ =>
inductionOn b fun β s _ => by
simp_rw [← type_sum_lex, type_eq_zero_iff_isEmpty]
exact isEmpty_sum
#align ordinal.add_eq_zero_iff Ordinal.add_eq_zero_iff
theorem left_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : a = 0 :=
(add_eq_zero_iff.1 h).1
#align ordinal.left_eq_zero_of_add_eq_zero Ordinal.left_eq_zero_of_add_eq_zero
theorem right_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : b = 0 :=
(add_eq_zero_iff.1 h).2
#align ordinal.right_eq_zero_of_add_eq_zero Ordinal.right_eq_zero_of_add_eq_zero
/-! ### The predecessor of an ordinal -/
/-- The ordinal predecessor of `o` is `o'` if `o = succ o'`,
and `o` otherwise. -/
def pred (o : Ordinal) : Ordinal :=
if h : ∃ a, o = succ a then Classical.choose h else o
#align ordinal.pred Ordinal.pred
@[simp]
theorem pred_succ (o) : pred (succ o) = o := by
have h : ∃ a, succ o = succ a := ⟨_, rfl⟩;
simpa only [pred, dif_pos h] using (succ_injective <| Classical.choose_spec h).symm
#align ordinal.pred_succ Ordinal.pred_succ
theorem pred_le_self (o) : pred o ≤ o :=
if h : ∃ a, o = succ a then by
let ⟨a, e⟩ := h
rw [e, pred_succ]; exact le_succ a
else by rw [pred, dif_neg h]
#align ordinal.pred_le_self Ordinal.pred_le_self
theorem pred_eq_iff_not_succ {o} : pred o = o ↔ ¬∃ a, o = succ a :=
⟨fun e ⟨a, e'⟩ => by rw [e', pred_succ] at e; exact (lt_succ a).ne e, fun h => dif_neg h⟩
#align ordinal.pred_eq_iff_not_succ Ordinal.pred_eq_iff_not_succ
theorem pred_eq_iff_not_succ' {o} : pred o = o ↔ ∀ a, o ≠ succ a := by
simpa using pred_eq_iff_not_succ
#align ordinal.pred_eq_iff_not_succ' Ordinal.pred_eq_iff_not_succ'
theorem pred_lt_iff_is_succ {o} : pred o < o ↔ ∃ a, o = succ a :=
Iff.trans (by simp only [le_antisymm_iff, pred_le_self, true_and_iff, not_le])
(iff_not_comm.1 pred_eq_iff_not_succ).symm
#align ordinal.pred_lt_iff_is_succ Ordinal.pred_lt_iff_is_succ
@[simp]
theorem pred_zero : pred 0 = 0 :=
pred_eq_iff_not_succ'.2 fun a => (succ_ne_zero a).symm
#align ordinal.pred_zero Ordinal.pred_zero
theorem succ_pred_iff_is_succ {o} : succ (pred o) = o ↔ ∃ a, o = succ a :=
⟨fun e => ⟨_, e.symm⟩, fun ⟨a, e⟩ => by simp only [e, pred_succ]⟩
#align ordinal.succ_pred_iff_is_succ Ordinal.succ_pred_iff_is_succ
theorem succ_lt_of_not_succ {o b : Ordinal} (h : ¬∃ a, o = succ a) : succ b < o ↔ b < o :=
⟨(lt_succ b).trans, fun l => lt_of_le_of_ne (succ_le_of_lt l) fun e => h ⟨_, e.symm⟩⟩
#align ordinal.succ_lt_of_not_succ Ordinal.succ_lt_of_not_succ
theorem lt_pred {a b} : a < pred b ↔ succ a < b :=
if h : ∃ a, b = succ a then by
let ⟨c, e⟩ := h
rw [e, pred_succ, succ_lt_succ_iff]
else by simp only [pred, dif_neg h, succ_lt_of_not_succ h]
#align ordinal.lt_pred Ordinal.lt_pred
theorem pred_le {a b} : pred a ≤ b ↔ a ≤ succ b :=
le_iff_le_iff_lt_iff_lt.2 lt_pred
#align ordinal.pred_le Ordinal.pred_le
@[simp]
theorem lift_is_succ {o : Ordinal.{v}} : (∃ a, lift.{u} o = succ a) ↔ ∃ a, o = succ a :=
⟨fun ⟨a, h⟩ =>
let ⟨b, e⟩ := lift_down <| show a ≤ lift.{u} o from le_of_lt <| h.symm ▸ lt_succ a
⟨b, lift_inj.1 <| by rw [h, ← e, lift_succ]⟩,
fun ⟨a, h⟩ => ⟨lift.{u} a, by simp only [h, lift_succ]⟩⟩
#align ordinal.lift_is_succ Ordinal.lift_is_succ
@[simp]
theorem lift_pred (o : Ordinal.{v}) : lift.{u} (pred o) = pred (lift.{u} o) :=
if h : ∃ a, o = succ a then by cases' h with a e; simp only [e, pred_succ, lift_succ]
else by rw [pred_eq_iff_not_succ.2 h, pred_eq_iff_not_succ.2 (mt lift_is_succ.1 h)]
#align ordinal.lift_pred Ordinal.lift_pred
/-! ### Limit ordinals -/
/-- A limit ordinal is an ordinal which is not zero and not a successor. -/
def IsLimit (o : Ordinal) : Prop :=
o ≠ 0 ∧ ∀ a < o, succ a < o
#align ordinal.is_limit Ordinal.IsLimit
theorem IsLimit.isSuccLimit {o} (h : IsLimit o) : IsSuccLimit o := isSuccLimit_iff_succ_lt.mpr h.2
theorem IsLimit.succ_lt {o a : Ordinal} (h : IsLimit o) : a < o → succ a < o :=
h.2 a
#align ordinal.is_limit.succ_lt Ordinal.IsLimit.succ_lt
theorem isSuccLimit_zero : IsSuccLimit (0 : Ordinal) := isSuccLimit_bot
theorem not_zero_isLimit : ¬IsLimit 0
| ⟨h, _⟩ => h rfl
#align ordinal.not_zero_is_limit Ordinal.not_zero_isLimit
theorem not_succ_isLimit (o) : ¬IsLimit (succ o)
| ⟨_, h⟩ => lt_irrefl _ (h _ (lt_succ o))
#align ordinal.not_succ_is_limit Ordinal.not_succ_isLimit
theorem not_succ_of_isLimit {o} (h : IsLimit o) : ¬∃ a, o = succ a
| ⟨a, e⟩ => not_succ_isLimit a (e ▸ h)
#align ordinal.not_succ_of_is_limit Ordinal.not_succ_of_isLimit
theorem succ_lt_of_isLimit {o a : Ordinal} (h : IsLimit o) : succ a < o ↔ a < o :=
⟨(lt_succ a).trans, h.2 _⟩
#align ordinal.succ_lt_of_is_limit Ordinal.succ_lt_of_isLimit
theorem le_succ_of_isLimit {o} (h : IsLimit o) {a} : o ≤ succ a ↔ o ≤ a :=
le_iff_le_iff_lt_iff_lt.2 <| succ_lt_of_isLimit h
#align ordinal.le_succ_of_is_limit Ordinal.le_succ_of_isLimit
theorem limit_le {o} (h : IsLimit o) {a} : o ≤ a ↔ ∀ x < o, x ≤ a :=
⟨fun h _x l => l.le.trans h, fun H =>
(le_succ_of_isLimit h).1 <| le_of_not_lt fun hn => not_lt_of_le (H _ hn) (lt_succ a)⟩
#align ordinal.limit_le Ordinal.limit_le
theorem lt_limit {o} (h : IsLimit o) {a} : a < o ↔ ∃ x < o, a < x := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@limit_le _ h a)
#align ordinal.lt_limit Ordinal.lt_limit
@[simp]
theorem lift_isLimit (o) : IsLimit (lift o) ↔ IsLimit o :=
and_congr (not_congr <| by simpa only [lift_zero] using @lift_inj o 0)
⟨fun H a h => lift_lt.1 <| by simpa only [lift_succ] using H _ (lift_lt.2 h), fun H a h => by
obtain ⟨a', rfl⟩ := lift_down h.le
rw [← lift_succ, lift_lt]
exact H a' (lift_lt.1 h)⟩
#align ordinal.lift_is_limit Ordinal.lift_isLimit
theorem IsLimit.pos {o : Ordinal} (h : IsLimit o) : 0 < o :=
lt_of_le_of_ne (Ordinal.zero_le _) h.1.symm
#align ordinal.is_limit.pos Ordinal.IsLimit.pos
theorem IsLimit.one_lt {o : Ordinal} (h : IsLimit o) : 1 < o := by
simpa only [succ_zero] using h.2 _ h.pos
#align ordinal.is_limit.one_lt Ordinal.IsLimit.one_lt
theorem IsLimit.nat_lt {o : Ordinal} (h : IsLimit o) : ∀ n : ℕ, (n : Ordinal) < o
| 0 => h.pos
| n + 1 => h.2 _ (IsLimit.nat_lt h n)
#align ordinal.is_limit.nat_lt Ordinal.IsLimit.nat_lt
theorem zero_or_succ_or_limit (o : Ordinal) : o = 0 ∨ (∃ a, o = succ a) ∨ IsLimit o :=
if o0 : o = 0 then Or.inl o0
else
if h : ∃ a, o = succ a then Or.inr (Or.inl h)
else Or.inr <| Or.inr ⟨o0, fun _a => (succ_lt_of_not_succ h).2⟩
#align ordinal.zero_or_succ_or_limit Ordinal.zero_or_succ_or_limit
/-- Main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals. -/
@[elab_as_elim]
def limitRecOn {C : Ordinal → Sort*} (o : Ordinal) (H₁ : C 0) (H₂ : ∀ o, C o → C (succ o))
(H₃ : ∀ o, IsLimit o → (∀ o' < o, C o') → C o) : C o :=
SuccOrder.limitRecOn o (fun o _ ↦ H₂ o) fun o hl ↦
if h : o = 0 then fun _ ↦ h ▸ H₁ else H₃ o ⟨h, fun _ ↦ hl.succ_lt⟩
#align ordinal.limit_rec_on Ordinal.limitRecOn
@[simp]
theorem limitRecOn_zero {C} (H₁ H₂ H₃) : @limitRecOn C 0 H₁ H₂ H₃ = H₁ := by
rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ isSuccLimit_zero, dif_pos rfl]
#align ordinal.limit_rec_on_zero Ordinal.limitRecOn_zero
@[simp]
theorem limitRecOn_succ {C} (o H₁ H₂ H₃) :
@limitRecOn C (succ o) H₁ H₂ H₃ = H₂ o (@limitRecOn C o H₁ H₂ H₃) := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_succ _ _ (not_isMax _)]
#align ordinal.limit_rec_on_succ Ordinal.limitRecOn_succ
@[simp]
theorem limitRecOn_limit {C} (o H₁ H₂ H₃ h) :
@limitRecOn C o H₁ H₂ H₃ = H₃ o h fun x _h => @limitRecOn C x H₁ H₂ H₃ := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ h.isSuccLimit, dif_neg h.1]
#align ordinal.limit_rec_on_limit Ordinal.limitRecOn_limit
instance orderTopOutSucc (o : Ordinal) : OrderTop (succ o).out.α :=
@OrderTop.mk _ _ (Top.mk _) le_enum_succ
#align ordinal.order_top_out_succ Ordinal.orderTopOutSucc
theorem enum_succ_eq_top {o : Ordinal} :
enum (· < ·) o
(by
rw [type_lt]
exact lt_succ o) =
(⊤ : (succ o).out.α) :=
rfl
#align ordinal.enum_succ_eq_top Ordinal.enum_succ_eq_top
theorem has_succ_of_type_succ_lt {α} {r : α → α → Prop} [wo : IsWellOrder α r]
(h : ∀ a < type r, succ a < type r) (x : α) : ∃ y, r x y := by
use enum r (succ (typein r x)) (h _ (typein_lt_type r x))
convert (enum_lt_enum (typein_lt_type r x)
(h _ (typein_lt_type r x))).mpr (lt_succ _); rw [enum_typein]
#align ordinal.has_succ_of_type_succ_lt Ordinal.has_succ_of_type_succ_lt
theorem out_no_max_of_succ_lt {o : Ordinal} (ho : ∀ a < o, succ a < o) : NoMaxOrder o.out.α :=
⟨has_succ_of_type_succ_lt (by rwa [type_lt])⟩
#align ordinal.out_no_max_of_succ_lt Ordinal.out_no_max_of_succ_lt
theorem bounded_singleton {r : α → α → Prop} [IsWellOrder α r] (hr : (type r).IsLimit) (x) :
Bounded r {x} := by
refine ⟨enum r (succ (typein r x)) (hr.2 _ (typein_lt_type r x)), ?_⟩
intro b hb
rw [mem_singleton_iff.1 hb]
nth_rw 1 [← enum_typein r x]
rw [@enum_lt_enum _ r]
apply lt_succ
#align ordinal.bounded_singleton Ordinal.bounded_singleton
-- Porting note: `· < ·` requires a type ascription for an `IsWellOrder` instance.
theorem type_subrel_lt (o : Ordinal.{u}) :
type (Subrel ((· < ·) : Ordinal → Ordinal → Prop) { o' : Ordinal | o' < o })
= Ordinal.lift.{u + 1} o := by
refine Quotient.inductionOn o ?_
rintro ⟨α, r, wo⟩; apply Quotient.sound
-- Porting note: `symm; refine' [term]` → `refine' [term].symm`
constructor; refine ((RelIso.preimage Equiv.ulift r).trans (enumIso r).symm).symm
#align ordinal.type_subrel_lt Ordinal.type_subrel_lt
theorem mk_initialSeg (o : Ordinal.{u}) :
#{ o' : Ordinal | o' < o } = Cardinal.lift.{u + 1} o.card := by
rw [lift_card, ← type_subrel_lt, card_type]
#align ordinal.mk_initial_seg Ordinal.mk_initialSeg
/-! ### Normal ordinal functions -/
/-- A normal ordinal function is a strictly increasing function which is
order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`. -/
def IsNormal (f : Ordinal → Ordinal) : Prop :=
(∀ o, f o < f (succ o)) ∧ ∀ o, IsLimit o → ∀ a, f o ≤ a ↔ ∀ b < o, f b ≤ a
#align ordinal.is_normal Ordinal.IsNormal
theorem IsNormal.limit_le {f} (H : IsNormal f) :
∀ {o}, IsLimit o → ∀ {a}, f o ≤ a ↔ ∀ b < o, f b ≤ a :=
@H.2
#align ordinal.is_normal.limit_le Ordinal.IsNormal.limit_le
theorem IsNormal.limit_lt {f} (H : IsNormal f) {o} (h : IsLimit o) {a} :
a < f o ↔ ∃ b < o, a < f b :=
not_iff_not.1 <| by simpa only [exists_prop, not_exists, not_and, not_lt] using H.2 _ h a
#align ordinal.is_normal.limit_lt Ordinal.IsNormal.limit_lt
theorem IsNormal.strictMono {f} (H : IsNormal f) : StrictMono f := fun a b =>
limitRecOn b (Not.elim (not_lt_of_le <| Ordinal.zero_le _))
(fun _b IH h =>
(lt_or_eq_of_le (le_of_lt_succ h)).elim (fun h => (IH h).trans (H.1 _)) fun e => e ▸ H.1 _)
fun _b l _IH h => lt_of_lt_of_le (H.1 a) ((H.2 _ l _).1 le_rfl _ (l.2 _ h))
#align ordinal.is_normal.strict_mono Ordinal.IsNormal.strictMono
theorem IsNormal.monotone {f} (H : IsNormal f) : Monotone f :=
H.strictMono.monotone
#align ordinal.is_normal.monotone Ordinal.IsNormal.monotone
theorem isNormal_iff_strictMono_limit (f : Ordinal → Ordinal) :
IsNormal f ↔ StrictMono f ∧ ∀ o, IsLimit o → ∀ a, (∀ b < o, f b ≤ a) → f o ≤ a :=
⟨fun hf => ⟨hf.strictMono, fun a ha c => (hf.2 a ha c).2⟩, fun ⟨hs, hl⟩ =>
⟨fun a => hs (lt_succ a), fun a ha c =>
⟨fun hac _b hba => ((hs hba).trans_le hac).le, hl a ha c⟩⟩⟩
#align ordinal.is_normal_iff_strict_mono_limit Ordinal.isNormal_iff_strictMono_limit
theorem IsNormal.lt_iff {f} (H : IsNormal f) {a b} : f a < f b ↔ a < b :=
StrictMono.lt_iff_lt <| H.strictMono
#align ordinal.is_normal.lt_iff Ordinal.IsNormal.lt_iff
theorem IsNormal.le_iff {f} (H : IsNormal f) {a b} : f a ≤ f b ↔ a ≤ b :=
le_iff_le_iff_lt_iff_lt.2 H.lt_iff
#align ordinal.is_normal.le_iff Ordinal.IsNormal.le_iff
theorem IsNormal.inj {f} (H : IsNormal f) {a b} : f a = f b ↔ a = b := by
simp only [le_antisymm_iff, H.le_iff]
#align ordinal.is_normal.inj Ordinal.IsNormal.inj
theorem IsNormal.self_le {f} (H : IsNormal f) (a) : a ≤ f a :=
lt_wf.self_le_of_strictMono H.strictMono a
#align ordinal.is_normal.self_le Ordinal.IsNormal.self_le
theorem IsNormal.le_set {f o} (H : IsNormal f) (p : Set Ordinal) (p0 : p.Nonempty) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f a ≤ o :=
⟨fun h a pa => (H.le_iff.2 ((H₂ _).1 le_rfl _ pa)).trans h, fun h => by
-- Porting note: `refine'` didn't work well so `induction` is used
induction b using limitRecOn with
| H₁ =>
cases' p0 with x px
have := Ordinal.le_zero.1 ((H₂ _).1 (Ordinal.zero_le _) _ px)
rw [this] at px
exact h _ px
| H₂ S _ =>
rcases not_forall₂.1 (mt (H₂ S).2 <| (lt_succ S).not_le) with ⟨a, h₁, h₂⟩
exact (H.le_iff.2 <| succ_le_of_lt <| not_le.1 h₂).trans (h _ h₁)
| H₃ S L _ =>
refine (H.2 _ L _).2 fun a h' => ?_
rcases not_forall₂.1 (mt (H₂ a).2 h'.not_le) with ⟨b, h₁, h₂⟩
exact (H.le_iff.2 <| (not_le.1 h₂).le).trans (h _ h₁)⟩
#align ordinal.is_normal.le_set Ordinal.IsNormal.le_set
theorem IsNormal.le_set' {f o} (H : IsNormal f) (p : Set α) (p0 : p.Nonempty) (g : α → Ordinal) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, g a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f (g a) ≤ o := by
simpa [H₂] using H.le_set (g '' p) (p0.image g) b
#align ordinal.is_normal.le_set' Ordinal.IsNormal.le_set'
theorem IsNormal.refl : IsNormal id :=
⟨lt_succ, fun _o l _a => Ordinal.limit_le l⟩
#align ordinal.is_normal.refl Ordinal.IsNormal.refl
theorem IsNormal.trans {f g} (H₁ : IsNormal f) (H₂ : IsNormal g) : IsNormal (f ∘ g) :=
⟨fun _x => H₁.lt_iff.2 (H₂.1 _), fun o l _a =>
H₁.le_set' (· < o) ⟨0, l.pos⟩ g _ fun _c => H₂.2 _ l _⟩
#align ordinal.is_normal.trans Ordinal.IsNormal.trans
theorem IsNormal.isLimit {f} (H : IsNormal f) {o} (l : IsLimit o) : IsLimit (f o) :=
⟨ne_of_gt <| (Ordinal.zero_le _).trans_lt <| H.lt_iff.2 l.pos, fun _ h =>
let ⟨_b, h₁, h₂⟩ := (H.limit_lt l).1 h
(succ_le_of_lt h₂).trans_lt (H.lt_iff.2 h₁)⟩
#align ordinal.is_normal.is_limit Ordinal.IsNormal.isLimit
theorem IsNormal.le_iff_eq {f} (H : IsNormal f) {a} : f a ≤ a ↔ f a = a :=
(H.self_le a).le_iff_eq
#align ordinal.is_normal.le_iff_eq Ordinal.IsNormal.le_iff_eq
theorem add_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a + b ≤ c ↔ ∀ b' < b, a + b' ≤ c :=
⟨fun h b' l => (add_le_add_left l.le _).trans h, fun H =>
le_of_not_lt <| by
-- Porting note: `induction` tactics are required because of the parser bug.
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
intro l
suffices ∀ x : β, Sum.Lex r s (Sum.inr x) (enum _ _ l) by
-- Porting note: `revert` & `intro` is required because `cases'` doesn't replace
-- `enum _ _ l` in `this`.
revert this; cases' enum _ _ l with x x <;> intro this
· cases this (enum s 0 h.pos)
· exact irrefl _ (this _)
intro x
rw [← typein_lt_typein (Sum.Lex r s), typein_enum]
have := H _ (h.2 _ (typein_lt_type s x))
rw [add_succ, succ_le_iff] at this
refine
(RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨a | b, h⟩
· exact Sum.inl a
· exact Sum.inr ⟨b, by cases h; assumption⟩
· rcases a with ⟨a | a, h₁⟩ <;> rcases b with ⟨b | b, h₂⟩ <;> cases h₁ <;> cases h₂ <;>
rintro ⟨⟩ <;> constructor <;> assumption⟩
#align ordinal.add_le_of_limit Ordinal.add_le_of_limit
theorem add_isNormal (a : Ordinal) : IsNormal (a + ·) :=
⟨fun b => (add_lt_add_iff_left a).2 (lt_succ b), fun _b l _c => add_le_of_limit l⟩
#align ordinal.add_is_normal Ordinal.add_isNormal
theorem add_isLimit (a) {b} : IsLimit b → IsLimit (a + b) :=
(add_isNormal a).isLimit
#align ordinal.add_is_limit Ordinal.add_isLimit
alias IsLimit.add := add_isLimit
#align ordinal.is_limit.add Ordinal.IsLimit.add
/-! ### Subtraction on ordinals-/
/-- The set in the definition of subtraction is nonempty. -/
theorem sub_nonempty {a b : Ordinal} : { o | a ≤ b + o }.Nonempty :=
⟨a, le_add_left _ _⟩
#align ordinal.sub_nonempty Ordinal.sub_nonempty
/-- `a - b` is the unique ordinal satisfying `b + (a - b) = a` when `b ≤ a`. -/
instance sub : Sub Ordinal :=
⟨fun a b => sInf { o | a ≤ b + o }⟩
theorem le_add_sub (a b : Ordinal) : a ≤ b + (a - b) :=
csInf_mem sub_nonempty
#align ordinal.le_add_sub Ordinal.le_add_sub
theorem sub_le {a b c : Ordinal} : a - b ≤ c ↔ a ≤ b + c :=
⟨fun h => (le_add_sub a b).trans (add_le_add_left h _), fun h => csInf_le' h⟩
#align ordinal.sub_le Ordinal.sub_le
theorem lt_sub {a b c : Ordinal} : a < b - c ↔ c + a < b :=
lt_iff_lt_of_le_iff_le sub_le
#align ordinal.lt_sub Ordinal.lt_sub
theorem add_sub_cancel (a b : Ordinal) : a + b - a = b :=
le_antisymm (sub_le.2 <| le_rfl) ((add_le_add_iff_left a).1 <| le_add_sub _ _)
#align ordinal.add_sub_cancel Ordinal.add_sub_cancel
theorem sub_eq_of_add_eq {a b c : Ordinal} (h : a + b = c) : c - a = b :=
h ▸ add_sub_cancel _ _
#align ordinal.sub_eq_of_add_eq Ordinal.sub_eq_of_add_eq
theorem sub_le_self (a b : Ordinal) : a - b ≤ a :=
sub_le.2 <| le_add_left _ _
#align ordinal.sub_le_self Ordinal.sub_le_self
protected theorem add_sub_cancel_of_le {a b : Ordinal} (h : b ≤ a) : b + (a - b) = a :=
(le_add_sub a b).antisymm'
(by
rcases zero_or_succ_or_limit (a - b) with (e | ⟨c, e⟩ | l)
· simp only [e, add_zero, h]
· rw [e, add_succ, succ_le_iff, ← lt_sub, e]
exact lt_succ c
· exact (add_le_of_limit l).2 fun c l => (lt_sub.1 l).le)
#align ordinal.add_sub_cancel_of_le Ordinal.add_sub_cancel_of_le
theorem le_sub_of_le {a b c : Ordinal} (h : b ≤ a) : c ≤ a - b ↔ b + c ≤ a := by
rw [← add_le_add_iff_left b, Ordinal.add_sub_cancel_of_le h]
#align ordinal.le_sub_of_le Ordinal.le_sub_of_le
theorem sub_lt_of_le {a b c : Ordinal} (h : b ≤ a) : a - b < c ↔ a < b + c :=
lt_iff_lt_of_le_iff_le (le_sub_of_le h)
#align ordinal.sub_lt_of_le Ordinal.sub_lt_of_le
instance existsAddOfLE : ExistsAddOfLE Ordinal :=
⟨fun h => ⟨_, (Ordinal.add_sub_cancel_of_le h).symm⟩⟩
@[simp]
theorem sub_zero (a : Ordinal) : a - 0 = a := by simpa only [zero_add] using add_sub_cancel 0 a
#align ordinal.sub_zero Ordinal.sub_zero
@[simp]
theorem zero_sub (a : Ordinal) : 0 - a = 0 := by rw [← Ordinal.le_zero]; apply sub_le_self
#align ordinal.zero_sub Ordinal.zero_sub
@[simp]
theorem sub_self (a : Ordinal) : a - a = 0 := by simpa only [add_zero] using add_sub_cancel a 0
#align ordinal.sub_self Ordinal.sub_self
protected theorem sub_eq_zero_iff_le {a b : Ordinal} : a - b = 0 ↔ a ≤ b :=
⟨fun h => by simpa only [h, add_zero] using le_add_sub a b, fun h => by
rwa [← Ordinal.le_zero, sub_le, add_zero]⟩
#align ordinal.sub_eq_zero_iff_le Ordinal.sub_eq_zero_iff_le
theorem sub_sub (a b c : Ordinal) : a - b - c = a - (b + c) :=
eq_of_forall_ge_iff fun d => by rw [sub_le, sub_le, sub_le, add_assoc]
#align ordinal.sub_sub Ordinal.sub_sub
@[simp]
theorem add_sub_add_cancel (a b c : Ordinal) : a + b - (a + c) = b - c := by
rw [← sub_sub, add_sub_cancel]
#align ordinal.add_sub_add_cancel Ordinal.add_sub_add_cancel
theorem sub_isLimit {a b} (l : IsLimit a) (h : b < a) : IsLimit (a - b) :=
⟨ne_of_gt <| lt_sub.2 <| by rwa [add_zero], fun c h => by
rw [lt_sub, add_succ]; exact l.2 _ (lt_sub.1 h)⟩
#align ordinal.sub_is_limit Ordinal.sub_isLimit
-- @[simp] -- Porting note (#10618): simp can prove this
theorem one_add_omega : 1 + ω = ω := by
refine le_antisymm ?_ (le_add_left _ _)
rw [omega, ← lift_one.{_, 0}, ← lift_add, lift_le, ← type_unit, ← type_sum_lex]
refine ⟨RelEmbedding.collapse (RelEmbedding.ofMonotone ?_ ?_)⟩
· apply Sum.rec
· exact fun _ => 0
· exact Nat.succ
· intro a b
cases a <;> cases b <;> intro H <;> cases' H with _ _ H _ _ H <;>
[exact H.elim; exact Nat.succ_pos _; exact Nat.succ_lt_succ H]
#align ordinal.one_add_omega Ordinal.one_add_omega
@[simp]
theorem one_add_of_omega_le {o} (h : ω ≤ o) : 1 + o = o := by
rw [← Ordinal.add_sub_cancel_of_le h, ← add_assoc, one_add_omega]
#align ordinal.one_add_of_omega_le Ordinal.one_add_of_omega_le
/-! ### Multiplication of ordinals-/
/-- The multiplication of ordinals `o₁` and `o₂` is the (well founded) lexicographic order on
`o₂ × o₁`. -/
instance monoid : Monoid Ordinal.{u} where
mul a b :=
Quotient.liftOn₂ a b
(fun ⟨α, r, wo⟩ ⟨β, s, wo'⟩ => ⟦⟨β × α, Prod.Lex s r, inferInstance⟩⟧ :
WellOrder → WellOrder → Ordinal)
fun ⟨α₁, r₁, o₁⟩ ⟨α₂, r₂, o₂⟩ ⟨β₁, s₁, p₁⟩ ⟨β₂, s₂, p₂⟩ ⟨f⟩ ⟨g⟩ =>
Quot.sound ⟨RelIso.prodLexCongr g f⟩
one := 1
mul_assoc a b c :=
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Eq.symm <|
Quotient.sound
⟨⟨prodAssoc _ _ _, @fun a b => by
rcases a with ⟨⟨a₁, a₂⟩, a₃⟩
rcases b with ⟨⟨b₁, b₂⟩, b₃⟩
simp [Prod.lex_def, and_or_left, or_assoc, and_assoc]⟩⟩
mul_one a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨punitProd _, @fun a b => by
rcases a with ⟨⟨⟨⟩⟩, a⟩; rcases b with ⟨⟨⟨⟩⟩, b⟩
simp only [Prod.lex_def, EmptyRelation, false_or_iff]
simp only [eq_self_iff_true, true_and_iff]
rfl⟩⟩
one_mul a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨prodPUnit _, @fun a b => by
rcases a with ⟨a, ⟨⟨⟩⟩⟩; rcases b with ⟨b, ⟨⟨⟩⟩⟩
simp only [Prod.lex_def, EmptyRelation, and_false_iff, or_false_iff]
rfl⟩⟩
@[simp]
theorem type_prod_lex {α β : Type u} (r : α → α → Prop) (s : β → β → Prop) [IsWellOrder α r]
[IsWellOrder β s] : type (Prod.Lex s r) = type r * type s :=
rfl
#align ordinal.type_prod_lex Ordinal.type_prod_lex
private theorem mul_eq_zero' {a b : Ordinal} : a * b = 0 ↔ a = 0 ∨ b = 0 :=
inductionOn a fun α _ _ =>
inductionOn b fun β _ _ => by
simp_rw [← type_prod_lex, type_eq_zero_iff_isEmpty]
rw [or_comm]
exact isEmpty_prod
instance monoidWithZero : MonoidWithZero Ordinal :=
{ Ordinal.monoid with
zero := 0
mul_zero := fun _a => mul_eq_zero'.2 <| Or.inr rfl
zero_mul := fun _a => mul_eq_zero'.2 <| Or.inl rfl }
instance noZeroDivisors : NoZeroDivisors Ordinal :=
⟨fun {_ _} => mul_eq_zero'.1⟩
@[simp]
theorem lift_mul (a b : Ordinal.{v}) : lift.{u} (a * b) = lift.{u} a * lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.prodLexCongr (RelIso.preimage Equiv.ulift _)
(RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_mul Ordinal.lift_mul
@[simp]
theorem card_mul (a b) : card (a * b) = card a * card b :=
Quotient.inductionOn₂ a b fun ⟨α, _r, _⟩ ⟨β, _s, _⟩ => mul_comm #β #α
#align ordinal.card_mul Ordinal.card_mul
instance leftDistribClass : LeftDistribClass Ordinal.{u} :=
⟨fun a b c =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Quotient.sound
⟨⟨sumProdDistrib _ _ _, by
rintro ⟨a₁ | a₁, a₂⟩ ⟨b₁ | b₁, b₂⟩ <;>
simp only [Prod.lex_def, Sum.lex_inl_inl, Sum.Lex.sep, Sum.lex_inr_inl,
Sum.lex_inr_inr, sumProdDistrib_apply_left, sumProdDistrib_apply_right] <;>
-- Porting note: `Sum.inr.inj_iff` is required.
simp only [Sum.inl.inj_iff, Sum.inr.inj_iff,
true_or_iff, false_and_iff, false_or_iff]⟩⟩⟩
theorem mul_succ (a b : Ordinal) : a * succ b = a * b + a :=
mul_add_one a b
#align ordinal.mul_succ Ordinal.mul_succ
instance mul_covariantClass_le : CovariantClass Ordinal.{u} Ordinal.{u} (· * ·) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : α × γ => (f a.1, a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ (f.toRelEmbedding.map_rel_iff.2 h')
· exact Prod.Lex.right _ h'⟩
#align ordinal.mul_covariant_class_le Ordinal.mul_covariantClass_le
instance mul_swap_covariantClass_le :
CovariantClass Ordinal.{u} Ordinal.{u} (swap (· * ·)) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : γ × α => (a.1, f a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ h'
· exact Prod.Lex.right _ (f.toRelEmbedding.map_rel_iff.2 h')⟩
#align ordinal.mul_swap_covariant_class_le Ordinal.mul_swap_covariantClass_le
theorem le_mul_left (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ a * b := by
convert mul_le_mul_left' (one_le_iff_pos.2 hb) a
rw [mul_one a]
#align ordinal.le_mul_left Ordinal.le_mul_left
theorem le_mul_right (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ b * a := by
convert mul_le_mul_right' (one_le_iff_pos.2 hb) a
rw [one_mul a]
#align ordinal.le_mul_right Ordinal.le_mul_right
private theorem mul_le_of_limit_aux {α β r s} [IsWellOrder α r] [IsWellOrder β s] {c}
(h : IsLimit (type s)) (H : ∀ b' < type s, type r * b' ≤ c) (l : c < type r * type s) :
False := by
suffices ∀ a b, Prod.Lex s r (b, a) (enum _ _ l) by
cases' enum _ _ l with b a
exact irrefl _ (this _ _)
intro a b
rw [← typein_lt_typein (Prod.Lex s r), typein_enum]
have := H _ (h.2 _ (typein_lt_type s b))
rw [mul_succ] at this
have := ((add_lt_add_iff_left _).2 (typein_lt_type _ a)).trans_le this
refine (RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨⟨b', a'⟩, h⟩
by_cases e : b = b'
· refine Sum.inr ⟨a', ?_⟩
subst e
cases' h with _ _ _ _ h _ _ _ h
· exact (irrefl _ h).elim
· exact h
· refine Sum.inl (⟨b', ?_⟩, a')
cases' h with _ _ _ _ h _ _ _ h
· exact h
· exact (e rfl).elim
· rcases a with ⟨⟨b₁, a₁⟩, h₁⟩
rcases b with ⟨⟨b₂, a₂⟩, h₂⟩
intro h
by_cases e₁ : b = b₁ <;> by_cases e₂ : b = b₂
· substs b₁ b₂
simpa only [subrel_val, Prod.lex_def, @irrefl _ s _ b, true_and_iff, false_or_iff,
eq_self_iff_true, dif_pos, Sum.lex_inr_inr] using h
· subst b₁
simp only [subrel_val, Prod.lex_def, e₂, Prod.lex_def, dif_pos, subrel_val, eq_self_iff_true,
or_false_iff, dif_neg, not_false_iff, Sum.lex_inr_inl, false_and_iff] at h ⊢
cases' h₂ with _ _ _ _ h₂_h h₂_h <;> [exact asymm h h₂_h; exact e₂ rfl]
-- Porting note: `cc` hadn't ported yet.
· simp [e₂, dif_neg e₁, show b₂ ≠ b₁ from e₂ ▸ e₁]
· simpa only [dif_neg e₁, dif_neg e₂, Prod.lex_def, subrel_val, Subtype.mk_eq_mk,
Sum.lex_inl_inl] using h
theorem mul_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a * b ≤ c ↔ ∀ b' < b, a * b' ≤ c :=
⟨fun h b' l => (mul_le_mul_left' l.le _).trans h, fun H =>
-- Porting note: `induction` tactics are required because of the parser bug.
le_of_not_lt <| by
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
exact mul_le_of_limit_aux h H⟩
#align ordinal.mul_le_of_limit Ordinal.mul_le_of_limit
theorem mul_isNormal {a : Ordinal} (h : 0 < a) : IsNormal (a * ·) :=
-- Porting note(#12129): additional beta reduction needed
⟨fun b => by
beta_reduce
rw [mul_succ]
simpa only [add_zero] using (add_lt_add_iff_left (a * b)).2 h,
fun b l c => mul_le_of_limit l⟩
#align ordinal.mul_is_normal Ordinal.mul_isNormal
theorem lt_mul_of_limit {a b c : Ordinal} (h : IsLimit c) : a < b * c ↔ ∃ c' < c, a < b * c' := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@mul_le_of_limit b c a h)
#align ordinal.lt_mul_of_limit Ordinal.lt_mul_of_limit
theorem mul_lt_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b < a * c ↔ b < c :=
(mul_isNormal a0).lt_iff
#align ordinal.mul_lt_mul_iff_left Ordinal.mul_lt_mul_iff_left
theorem mul_le_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
(mul_isNormal a0).le_iff
#align ordinal.mul_le_mul_iff_left Ordinal.mul_le_mul_iff_left
theorem mul_lt_mul_of_pos_left {a b c : Ordinal} (h : a < b) (c0 : 0 < c) : c * a < c * b :=
(mul_lt_mul_iff_left c0).2 h
#align ordinal.mul_lt_mul_of_pos_left Ordinal.mul_lt_mul_of_pos_left
theorem mul_pos {a b : Ordinal} (h₁ : 0 < a) (h₂ : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left h₂ h₁
#align ordinal.mul_pos Ordinal.mul_pos
theorem mul_ne_zero {a b : Ordinal} : a ≠ 0 → b ≠ 0 → a * b ≠ 0 := by
simpa only [Ordinal.pos_iff_ne_zero] using mul_pos
#align ordinal.mul_ne_zero Ordinal.mul_ne_zero
theorem le_of_mul_le_mul_left {a b c : Ordinal} (h : c * a ≤ c * b) (h0 : 0 < c) : a ≤ b :=
le_imp_le_of_lt_imp_lt (fun h' => mul_lt_mul_of_pos_left h' h0) h
#align ordinal.le_of_mul_le_mul_left Ordinal.le_of_mul_le_mul_left
theorem mul_right_inj {a b c : Ordinal} (a0 : 0 < a) : a * b = a * c ↔ b = c :=
(mul_isNormal a0).inj
#align ordinal.mul_right_inj Ordinal.mul_right_inj
theorem mul_isLimit {a b : Ordinal} (a0 : 0 < a) : IsLimit b → IsLimit (a * b) :=
(mul_isNormal a0).isLimit
#align ordinal.mul_is_limit Ordinal.mul_isLimit
theorem mul_isLimit_left {a b : Ordinal} (l : IsLimit a) (b0 : 0 < b) : IsLimit (a * b) := by
rcases zero_or_succ_or_limit b with (rfl | ⟨b, rfl⟩ | lb)
· exact b0.false.elim
· rw [mul_succ]
exact add_isLimit _ l
· exact mul_isLimit l.pos lb
#align ordinal.mul_is_limit_left Ordinal.mul_isLimit_left
theorem smul_eq_mul : ∀ (n : ℕ) (a : Ordinal), n • a = a * n
| 0, a => by rw [zero_nsmul, Nat.cast_zero, mul_zero]
| n + 1, a => by rw [succ_nsmul, Nat.cast_add, mul_add, Nat.cast_one, mul_one, smul_eq_mul n]
#align ordinal.smul_eq_mul Ordinal.smul_eq_mul
/-! ### Division on ordinals -/
/-- The set in the definition of division is nonempty. -/
theorem div_nonempty {a b : Ordinal} (h : b ≠ 0) : { o | a < b * succ o }.Nonempty :=
⟨a, (succ_le_iff (a := a) (b := b * succ a)).1 <| by
simpa only [succ_zero, one_mul] using
mul_le_mul_right' (succ_le_of_lt (Ordinal.pos_iff_ne_zero.2 h)) (succ a)⟩
#align ordinal.div_nonempty Ordinal.div_nonempty
/-- `a / b` is the unique ordinal `o` satisfying `a = b * o + o'` with `o' < b`. -/
instance div : Div Ordinal :=
⟨fun a b => if _h : b = 0 then 0 else sInf { o | a < b * succ o }⟩
@[simp]
theorem div_zero (a : Ordinal) : a / 0 = 0 :=
dif_pos rfl
#align ordinal.div_zero Ordinal.div_zero
theorem div_def (a) {b : Ordinal} (h : b ≠ 0) : a / b = sInf { o | a < b * succ o } :=
dif_neg h
#align ordinal.div_def Ordinal.div_def
theorem lt_mul_succ_div (a) {b : Ordinal} (h : b ≠ 0) : a < b * succ (a / b) := by
rw [div_def a h]; exact csInf_mem (div_nonempty h)
#align ordinal.lt_mul_succ_div Ordinal.lt_mul_succ_div
theorem lt_mul_div_add (a) {b : Ordinal} (h : b ≠ 0) : a < b * (a / b) + b := by
simpa only [mul_succ] using lt_mul_succ_div a h
#align ordinal.lt_mul_div_add Ordinal.lt_mul_div_add
theorem div_le {a b c : Ordinal} (b0 : b ≠ 0) : a / b ≤ c ↔ a < b * succ c :=
⟨fun h => (lt_mul_succ_div a b0).trans_le (mul_le_mul_left' (succ_le_succ_iff.2 h) _), fun h => by
rw [div_def a b0]; exact csInf_le' h⟩
#align ordinal.div_le Ordinal.div_le
theorem lt_div {a b c : Ordinal} (h : c ≠ 0) : a < b / c ↔ c * succ a ≤ b := by
rw [← not_le, div_le h, not_lt]
#align ordinal.lt_div Ordinal.lt_div
theorem div_pos {b c : Ordinal} (h : c ≠ 0) : 0 < b / c ↔ c ≤ b := by simp [lt_div h]
#align ordinal.div_pos Ordinal.div_pos
theorem le_div {a b c : Ordinal} (c0 : c ≠ 0) : a ≤ b / c ↔ c * a ≤ b := by
induction a using limitRecOn with
| H₁ => simp only [mul_zero, Ordinal.zero_le]
| H₂ _ _ => rw [succ_le_iff, lt_div c0]
| H₃ _ h₁ h₂ =>
revert h₁ h₂
simp (config := { contextual := true }) only [mul_le_of_limit, limit_le, iff_self_iff,
forall_true_iff]
#align ordinal.le_div Ordinal.le_div
theorem div_lt {a b c : Ordinal} (b0 : b ≠ 0) : a / b < c ↔ a < b * c :=
lt_iff_lt_of_le_iff_le <| le_div b0
#align ordinal.div_lt Ordinal.div_lt
theorem div_le_of_le_mul {a b c : Ordinal} (h : a ≤ b * c) : a / b ≤ c :=
if b0 : b = 0 then by simp only [b0, div_zero, Ordinal.zero_le]
else
(div_le b0).2 <| h.trans_lt <| mul_lt_mul_of_pos_left (lt_succ c) (Ordinal.pos_iff_ne_zero.2 b0)
#align ordinal.div_le_of_le_mul Ordinal.div_le_of_le_mul
theorem mul_lt_of_lt_div {a b c : Ordinal} : a < b / c → c * a < b :=
lt_imp_lt_of_le_imp_le div_le_of_le_mul
#align ordinal.mul_lt_of_lt_div Ordinal.mul_lt_of_lt_div
@[simp]
theorem zero_div (a : Ordinal) : 0 / a = 0 :=
Ordinal.le_zero.1 <| div_le_of_le_mul <| Ordinal.zero_le _
#align ordinal.zero_div Ordinal.zero_div
theorem mul_div_le (a b : Ordinal) : b * (a / b) ≤ a :=
if b0 : b = 0 then by simp only [b0, zero_mul, Ordinal.zero_le] else (le_div b0).1 le_rfl
#align ordinal.mul_div_le Ordinal.mul_div_le
theorem mul_add_div (a) {b : Ordinal} (b0 : b ≠ 0) (c) : (b * a + c) / b = a + c / b := by
apply le_antisymm
· apply (div_le b0).2
rw [mul_succ, mul_add, add_assoc, add_lt_add_iff_left]
apply lt_mul_div_add _ b0
· rw [le_div b0, mul_add, add_le_add_iff_left]
apply mul_div_le
#align ordinal.mul_add_div Ordinal.mul_add_div
theorem div_eq_zero_of_lt {a b : Ordinal} (h : a < b) : a / b = 0 := by
rw [← Ordinal.le_zero, div_le <| Ordinal.pos_iff_ne_zero.1 <| (Ordinal.zero_le _).trans_lt h]
simpa only [succ_zero, mul_one] using h
#align ordinal.div_eq_zero_of_lt Ordinal.div_eq_zero_of_lt
@[simp]
theorem mul_div_cancel (a) {b : Ordinal} (b0 : b ≠ 0) : b * a / b = a := by
simpa only [add_zero, zero_div] using mul_add_div a b0 0
#align ordinal.mul_div_cancel Ordinal.mul_div_cancel
@[simp]
theorem div_one (a : Ordinal) : a / 1 = a := by
simpa only [one_mul] using mul_div_cancel a Ordinal.one_ne_zero
#align ordinal.div_one Ordinal.div_one
@[simp]
theorem div_self {a : Ordinal} (h : a ≠ 0) : a / a = 1 := by
simpa only [mul_one] using mul_div_cancel 1 h
#align ordinal.div_self Ordinal.div_self
theorem mul_sub (a b c : Ordinal) : a * (b - c) = a * b - a * c :=
if a0 : a = 0 then by simp only [a0, zero_mul, sub_self]
else
eq_of_forall_ge_iff fun d => by rw [sub_le, ← le_div a0, sub_le, ← le_div a0, mul_add_div _ a0]
#align ordinal.mul_sub Ordinal.mul_sub
theorem isLimit_add_iff {a b} : IsLimit (a + b) ↔ IsLimit b ∨ b = 0 ∧ IsLimit a := by
constructor <;> intro h
· by_cases h' : b = 0
· rw [h', add_zero] at h
right
exact ⟨h', h⟩
left
rw [← add_sub_cancel a b]
apply sub_isLimit h
suffices a + 0 < a + b by simpa only [add_zero] using this
rwa [add_lt_add_iff_left, Ordinal.pos_iff_ne_zero]
rcases h with (h | ⟨rfl, h⟩)
· exact add_isLimit a h
· simpa only [add_zero]
#align ordinal.is_limit_add_iff Ordinal.isLimit_add_iff
theorem dvd_add_iff : ∀ {a b c : Ordinal}, a ∣ b → (a ∣ b + c ↔ a ∣ c)
| a, _, c, ⟨b, rfl⟩ =>
⟨fun ⟨d, e⟩ => ⟨d - b, by rw [mul_sub, ← e, add_sub_cancel]⟩, fun ⟨d, e⟩ => by
rw [e, ← mul_add]
apply dvd_mul_right⟩
#align ordinal.dvd_add_iff Ordinal.dvd_add_iff
theorem div_mul_cancel : ∀ {a b : Ordinal}, a ≠ 0 → a ∣ b → a * (b / a) = b
| a, _, a0, ⟨b, rfl⟩ => by rw [mul_div_cancel _ a0]
#align ordinal.div_mul_cancel Ordinal.div_mul_cancel
theorem le_of_dvd : ∀ {a b : Ordinal}, b ≠ 0 → a ∣ b → a ≤ b
-- Porting note: `⟨b, rfl⟩ => by` → `⟨b, e⟩ => by subst e`
| a, _, b0, ⟨b, e⟩ => by
subst e
-- Porting note: `Ne` is required.
simpa only [mul_one] using
mul_le_mul_left'
(one_le_iff_ne_zero.2 fun h : b = 0 => by
simp only [h, mul_zero, Ne, not_true_eq_false] at b0) a
#align ordinal.le_of_dvd Ordinal.le_of_dvd
theorem dvd_antisymm {a b : Ordinal} (h₁ : a ∣ b) (h₂ : b ∣ a) : a = b :=
if a0 : a = 0 then by subst a; exact (eq_zero_of_zero_dvd h₁).symm
else
if b0 : b = 0 then by subst b; exact eq_zero_of_zero_dvd h₂
else (le_of_dvd b0 h₁).antisymm (le_of_dvd a0 h₂)
#align ordinal.dvd_antisymm Ordinal.dvd_antisymm
instance isAntisymm : IsAntisymm Ordinal (· ∣ ·) :=
⟨@dvd_antisymm⟩
/-- `a % b` is the unique ordinal `o'` satisfying
`a = b * o + o'` with `o' < b`. -/
instance mod : Mod Ordinal :=
⟨fun a b => a - b * (a / b)⟩
theorem mod_def (a b : Ordinal) : a % b = a - b * (a / b) :=
rfl
#align ordinal.mod_def Ordinal.mod_def
theorem mod_le (a b : Ordinal) : a % b ≤ a :=
sub_le_self a _
#align ordinal.mod_le Ordinal.mod_le
@[simp]
theorem mod_zero (a : Ordinal) : a % 0 = a := by simp only [mod_def, div_zero, zero_mul, sub_zero]
#align ordinal.mod_zero Ordinal.mod_zero
theorem mod_eq_of_lt {a b : Ordinal} (h : a < b) : a % b = a := by
simp only [mod_def, div_eq_zero_of_lt h, mul_zero, sub_zero]
#align ordinal.mod_eq_of_lt Ordinal.mod_eq_of_lt
@[simp]
theorem zero_mod (b : Ordinal) : 0 % b = 0 := by simp only [mod_def, zero_div, mul_zero, sub_self]
#align ordinal.zero_mod Ordinal.zero_mod
theorem div_add_mod (a b : Ordinal) : b * (a / b) + a % b = a :=
Ordinal.add_sub_cancel_of_le <| mul_div_le _ _
#align ordinal.div_add_mod Ordinal.div_add_mod
theorem mod_lt (a) {b : Ordinal} (h : b ≠ 0) : a % b < b :=
(add_lt_add_iff_left (b * (a / b))).1 <| by rw [div_add_mod]; exact lt_mul_div_add a h
#align ordinal.mod_lt Ordinal.mod_lt
@[simp]
theorem mod_self (a : Ordinal) : a % a = 0 :=
if a0 : a = 0 then by simp only [a0, zero_mod]
else by simp only [mod_def, div_self a0, mul_one, sub_self]
#align ordinal.mod_self Ordinal.mod_self
@[simp]
theorem mod_one (a : Ordinal) : a % 1 = 0 := by simp only [mod_def, div_one, one_mul, sub_self]
#align ordinal.mod_one Ordinal.mod_one
theorem dvd_of_mod_eq_zero {a b : Ordinal} (H : a % b = 0) : b ∣ a :=
⟨a / b, by simpa [H] using (div_add_mod a b).symm⟩
#align ordinal.dvd_of_mod_eq_zero Ordinal.dvd_of_mod_eq_zero
theorem mod_eq_zero_of_dvd {a b : Ordinal} (H : b ∣ a) : a % b = 0 := by
rcases H with ⟨c, rfl⟩
rcases eq_or_ne b 0 with (rfl | hb)
· simp
· simp [mod_def, hb]
#align ordinal.mod_eq_zero_of_dvd Ordinal.mod_eq_zero_of_dvd
theorem dvd_iff_mod_eq_zero {a b : Ordinal} : b ∣ a ↔ a % b = 0 :=
⟨mod_eq_zero_of_dvd, dvd_of_mod_eq_zero⟩
#align ordinal.dvd_iff_mod_eq_zero Ordinal.dvd_iff_mod_eq_zero
@[simp]
theorem mul_add_mod_self (x y z : Ordinal) : (x * y + z) % x = z % x := by
rcases eq_or_ne x 0 with rfl | hx
· simp
· rwa [mod_def, mul_add_div, mul_add, ← sub_sub, add_sub_cancel, mod_def]
#align ordinal.mul_add_mod_self Ordinal.mul_add_mod_self
@[simp]
theorem mul_mod (x y : Ordinal) : x * y % x = 0 := by
simpa using mul_add_mod_self x y 0
#align ordinal.mul_mod Ordinal.mul_mod
theorem mod_mod_of_dvd (a : Ordinal) {b c : Ordinal} (h : c ∣ b) : a % b % c = a % c := by
nth_rw 2 [← div_add_mod a b]
rcases h with ⟨d, rfl⟩
rw [mul_assoc, mul_add_mod_self]
#align ordinal.mod_mod_of_dvd Ordinal.mod_mod_of_dvd
@[simp]
theorem mod_mod (a b : Ordinal) : a % b % b = a % b :=
mod_mod_of_dvd a dvd_rfl
#align ordinal.mod_mod Ordinal.mod_mod
/-! ### Families of ordinals
There are two kinds of indexed families that naturally arise when dealing with ordinals: those
indexed by some type in the appropriate universe, and those indexed by ordinals less than another.
The following API allows one to convert from one kind of family to the other.
In many cases, this makes it easy to prove claims about one kind of family via the corresponding
claim on the other. -/
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a specified
well-ordering. -/
def bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
∀ a < type r, α := fun a ha => f (enum r a ha)
#align ordinal.bfamily_of_family' Ordinal.bfamilyOfFamily'
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a well-ordering
given by the axiom of choice. -/
def bfamilyOfFamily {ι : Type u} : (ι → α) → ∀ a < type (@WellOrderingRel ι), α :=
bfamilyOfFamily' WellOrderingRel
#align ordinal.bfamily_of_family Ordinal.bfamilyOfFamily
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a specified
well-ordering. -/
def familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, α) : ι → α := fun i =>
f (typein r i)
(by
rw [← ho]
exact typein_lt_type r i)
#align ordinal.family_of_bfamily' Ordinal.familyOfBFamily'
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a well-ordering
given by the axiom of choice. -/
def familyOfBFamily (o : Ordinal) (f : ∀ a < o, α) : o.out.α → α :=
familyOfBFamily' (· < ·) (type_lt o) f
#align ordinal.family_of_bfamily Ordinal.familyOfBFamily
@[simp]
theorem bfamilyOfFamily'_typein {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) (i) :
bfamilyOfFamily' r f (typein r i) (typein_lt_type r i) = f i := by
simp only [bfamilyOfFamily', enum_typein]
#align ordinal.bfamily_of_family'_typein Ordinal.bfamilyOfFamily'_typein
@[simp]
theorem bfamilyOfFamily_typein {ι} (f : ι → α) (i) :
bfamilyOfFamily f (typein _ i) (typein_lt_type _ i) = f i :=
bfamilyOfFamily'_typein _ f i
#align ordinal.bfamily_of_family_typein Ordinal.bfamilyOfFamily_typein
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily'_enum {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (i hi) :
familyOfBFamily' r ho f (enum r i (by rwa [ho])) = f i hi := by
simp only [familyOfBFamily', typein_enum]
#align ordinal.family_of_bfamily'_enum Ordinal.familyOfBFamily'_enum
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily_enum (o : Ordinal) (f : ∀ a < o, α) (i hi) :
familyOfBFamily o f
(enum (· < ·) i
(by
convert hi
exact type_lt _)) =
f i hi :=
familyOfBFamily'_enum _ (type_lt o) f _ _
#align ordinal.family_of_bfamily_enum Ordinal.familyOfBFamily_enum
/-- The range of a family indexed by ordinals. -/
def brange (o : Ordinal) (f : ∀ a < o, α) : Set α :=
{ a | ∃ i hi, f i hi = a }
#align ordinal.brange Ordinal.brange
theorem mem_brange {o : Ordinal} {f : ∀ a < o, α} {a} : a ∈ brange o f ↔ ∃ i hi, f i hi = a :=
Iff.rfl
#align ordinal.mem_brange Ordinal.mem_brange
theorem mem_brange_self {o} (f : ∀ a < o, α) (i hi) : f i hi ∈ brange o f :=
⟨i, hi, rfl⟩
#align ordinal.mem_brange_self Ordinal.mem_brange_self
@[simp]
theorem range_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) : range (familyOfBFamily' r ho f) = brange o f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨b, rfl⟩
apply mem_brange_self
· rintro ⟨i, hi, rfl⟩
exact ⟨_, familyOfBFamily'_enum _ _ _ _ _⟩
#align ordinal.range_family_of_bfamily' Ordinal.range_familyOfBFamily'
@[simp]
theorem range_familyOfBFamily {o} (f : ∀ a < o, α) : range (familyOfBFamily o f) = brange o f :=
range_familyOfBFamily' _ _ f
#align ordinal.range_family_of_bfamily Ordinal.range_familyOfBFamily
@[simp]
theorem brange_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
brange _ (bfamilyOfFamily' r f) = range f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨i, hi, rfl⟩
apply mem_range_self
· rintro ⟨b, rfl⟩
exact ⟨_, _, bfamilyOfFamily'_typein _ _ _⟩
#align ordinal.brange_bfamily_of_family' Ordinal.brange_bfamilyOfFamily'
@[simp]
theorem brange_bfamilyOfFamily {ι : Type u} (f : ι → α) : brange _ (bfamilyOfFamily f) = range f :=
brange_bfamilyOfFamily' _ _
#align ordinal.brange_bfamily_of_family Ordinal.brange_bfamilyOfFamily
@[simp]
theorem brange_const {o : Ordinal} (ho : o ≠ 0) {c : α} : (brange o fun _ _ => c) = {c} := by
rw [← range_familyOfBFamily]
exact @Set.range_const _ o.out.α (out_nonempty_iff_ne_zero.2 ho) c
#align ordinal.brange_const Ordinal.brange_const
theorem comp_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α)
(g : α → β) : (fun i hi => g (bfamilyOfFamily' r f i hi)) = bfamilyOfFamily' r (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family' Ordinal.comp_bfamilyOfFamily'
theorem comp_bfamilyOfFamily {ι : Type u} (f : ι → α) (g : α → β) :
(fun i hi => g (bfamilyOfFamily f i hi)) = bfamilyOfFamily (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family Ordinal.comp_bfamilyOfFamily
theorem comp_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily' r ho f = familyOfBFamily' r ho fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily' Ordinal.comp_familyOfBFamily'
theorem comp_familyOfBFamily {o} (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily o f = familyOfBFamily o fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily Ordinal.comp_familyOfBFamily
/-! ### Supremum of a family of ordinals -/
-- Porting note: Universes should be specified in `sup`s.
/-- The supremum of a family of ordinals -/
def sup {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal.{max u v} :=
iSup f
#align ordinal.sup Ordinal.sup
@[simp]
theorem sSup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : sSup (Set.range f) = sup.{_, v} f :=
rfl
#align ordinal.Sup_eq_sup Ordinal.sSup_eq_sup
/-- The range of an indexed ordinal function, whose outputs live in a higher universe than the
inputs, is always bounded above. See `Ordinal.lsub` for an explicit bound. -/
theorem bddAbove_range {ι : Type u} (f : ι → Ordinal.{max u v}) : BddAbove (Set.range f) :=
⟨(iSup (succ ∘ card ∘ f)).ord, by
rintro a ⟨i, rfl⟩
exact le_of_lt (Cardinal.lt_ord.2 ((lt_succ _).trans_le
(le_ciSup (Cardinal.bddAbove_range.{_, v} _) _)))⟩
#align ordinal.bdd_above_range Ordinal.bddAbove_range
theorem le_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : ∀ i, f i ≤ sup.{_, v} f := fun i =>
le_csSup (bddAbove_range.{_, v} f) (mem_range_self i)
#align ordinal.le_sup Ordinal.le_sup
theorem sup_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : sup.{_, v} f ≤ a ↔ ∀ i, f i ≤ a :=
(csSup_le_iff' (bddAbove_range.{_, v} f)).trans (by simp)
#align ordinal.sup_le_iff Ordinal.sup_le_iff
theorem sup_le {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : (∀ i, f i ≤ a) → sup.{_, v} f ≤ a :=
sup_le_iff.2
#align ordinal.sup_le Ordinal.sup_le
theorem lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : a < sup.{_, v} f ↔ ∃ i, a < f i := by
simpa only [not_forall, not_le] using not_congr (@sup_le_iff.{_, v} _ f a)
#align ordinal.lt_sup Ordinal.lt_sup
theorem ne_sup_iff_lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} :
(∀ i, f i ≠ sup.{_, v} f) ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun hf _ => lt_of_le_of_ne (le_sup _ _) (hf _), fun hf _ => ne_of_lt (hf _)⟩
#align ordinal.ne_sup_iff_lt_sup Ordinal.ne_sup_iff_lt_sup
theorem sup_not_succ_of_ne_sup {ι : Type u} {f : ι → Ordinal.{max u v}}
(hf : ∀ i, f i ≠ sup.{_, v} f) {a} (hao : a < sup.{_, v} f) : succ a < sup.{_, v} f := by
by_contra! hoa
exact
hao.not_le (sup_le fun i => le_of_lt_succ <| (lt_of_le_of_ne (le_sup _ _) (hf i)).trans_le hoa)
#align ordinal.sup_not_succ_of_ne_sup Ordinal.sup_not_succ_of_ne_sup
@[simp]
theorem sup_eq_zero_iff {ι : Type u} {f : ι → Ordinal.{max u v}} :
sup.{_, v} f = 0 ↔ ∀ i, f i = 0 := by
refine
⟨fun h i => ?_, fun h =>
le_antisymm (sup_le fun i => Ordinal.le_zero.2 (h i)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_sup f i
#align ordinal.sup_eq_zero_iff Ordinal.sup_eq_zero_iff
theorem IsNormal.sup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f) {ι : Type u}
(g : ι → Ordinal.{max u v}) [Nonempty ι] : f (sup.{_, v} g) = sup.{_, w} (f ∘ g) :=
eq_of_forall_ge_iff fun a => by
rw [sup_le_iff]; simp only [comp]; rw [H.le_set' Set.univ Set.univ_nonempty g] <;>
simp [sup_le_iff]
#align ordinal.is_normal.sup Ordinal.IsNormal.sup
@[simp]
theorem sup_empty {ι} [IsEmpty ι] (f : ι → Ordinal) : sup f = 0 :=
ciSup_of_empty f
#align ordinal.sup_empty Ordinal.sup_empty
@[simp]
theorem sup_const {ι} [_hι : Nonempty ι] (o : Ordinal) : (sup fun _ : ι => o) = o :=
ciSup_const
#align ordinal.sup_const Ordinal.sup_const
@[simp]
theorem sup_unique {ι} [Unique ι] (f : ι → Ordinal) : sup f = f default :=
ciSup_unique
#align ordinal.sup_unique Ordinal.sup_unique
theorem sup_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : sup.{u, max v w} f ≤ sup.{v, max u w} g :=
sup_le fun i =>
match h (mem_range_self i) with
| ⟨_j, hj⟩ => hj ▸ le_sup _ _
#align ordinal.sup_le_of_range_subset Ordinal.sup_le_of_range_subset
theorem sup_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : sup.{u, max v w} f = sup.{v, max u w} g :=
(sup_le_of_range_subset.{u, v, w} h.le).antisymm (sup_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.sup_eq_of_range_eq Ordinal.sup_eq_of_range_eq
@[simp]
theorem sup_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
sup.{max u v, w} f =
max (sup.{u, max v w} fun a => f (Sum.inl a)) (sup.{v, max u w} fun b => f (Sum.inr b)) := by
apply (sup_le_iff.2 _).antisymm (max_le_iff.2 ⟨_, _⟩)
· rintro (i | i)
· exact le_max_of_le_left (le_sup _ i)
· exact le_max_of_le_right (le_sup _ i)
all_goals
apply sup_le_of_range_subset.{_, max u v, w}
rintro i ⟨a, rfl⟩
apply mem_range_self
#align ordinal.sup_sum Ordinal.sup_sum
theorem unbounded_range_of_sup_ge {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β → α)
(h : type r ≤ sup.{u, u} (typein r ∘ f)) : Unbounded r (range f) :=
(not_bounded_iff _).1 fun ⟨x, hx⟩ =>
not_lt_of_le h <|
lt_of_le_of_lt
(sup_le fun y => le_of_lt <| (typein_lt_typein r).2 <| hx _ <| mem_range_self y)
(typein_lt_type r x)
#align ordinal.unbounded_range_of_sup_ge Ordinal.unbounded_range_of_sup_ge
theorem le_sup_shrink_equiv {s : Set Ordinal.{u}} (hs : Small.{u} s) (a) (ha : a ∈ s) :
a ≤ sup.{u, u} fun x => ((@equivShrink s hs).symm x).val := by
convert le_sup.{u, u} (fun x => ((@equivShrink s hs).symm x).val) ((@equivShrink s hs) ⟨a, ha⟩)
rw [symm_apply_apply]
#align ordinal.le_sup_shrink_equiv Ordinal.le_sup_shrink_equiv
instance small_Iio (o : Ordinal.{u}) : Small.{u} (Set.Iio o) :=
let f : o.out.α → Set.Iio o :=
fun x => ⟨typein ((· < ·) : o.out.α → o.out.α → Prop) x, typein_lt_self x⟩
let hf : Surjective f := fun b =>
⟨enum (· < ·) b.val
(by
rw [type_lt]
exact b.prop),
Subtype.ext (typein_enum _ _)⟩
small_of_surjective hf
#align ordinal.small_Iio Ordinal.small_Iio
instance small_Iic (o : Ordinal.{u}) : Small.{u} (Set.Iic o) := by
rw [← Iio_succ]
infer_instance
#align ordinal.small_Iic Ordinal.small_Iic
theorem bddAbove_iff_small {s : Set Ordinal.{u}} : BddAbove s ↔ Small.{u} s :=
⟨fun ⟨a, h⟩ => small_subset <| show s ⊆ Iic a from fun _x hx => h hx, fun h =>
⟨sup.{u, u} fun x => ((@equivShrink s h).symm x).val, le_sup_shrink_equiv h⟩⟩
#align ordinal.bdd_above_iff_small Ordinal.bddAbove_iff_small
theorem bddAbove_of_small (s : Set Ordinal.{u}) [h : Small.{u} s] : BddAbove s :=
bddAbove_iff_small.2 h
#align ordinal.bdd_above_of_small Ordinal.bddAbove_of_small
theorem sup_eq_sSup {s : Set Ordinal.{u}} (hs : Small.{u} s) :
(sup.{u, u} fun x => (@equivShrink s hs).symm x) = sSup s :=
let hs' := bddAbove_iff_small.2 hs
((csSup_le_iff' hs').2 (le_sup_shrink_equiv hs)).antisymm'
(sup_le fun _x => le_csSup hs' (Subtype.mem _))
#align ordinal.sup_eq_Sup Ordinal.sup_eq_sSup
theorem sSup_ord {s : Set Cardinal.{u}} (hs : BddAbove s) : (sSup s).ord = sSup (ord '' s) :=
eq_of_forall_ge_iff fun a => by
rw [csSup_le_iff'
(bddAbove_iff_small.2 (@small_image _ _ _ s (Cardinal.bddAbove_iff_small.1 hs))),
ord_le, csSup_le_iff' hs]
simp [ord_le]
#align ordinal.Sup_ord Ordinal.sSup_ord
theorem iSup_ord {ι} {f : ι → Cardinal} (hf : BddAbove (range f)) :
(iSup f).ord = ⨆ i, (f i).ord := by
unfold iSup
convert sSup_ord hf
-- Porting note: `change` is required.
conv_lhs => change range (ord ∘ f)
rw [range_comp]
#align ordinal.supr_ord Ordinal.iSup_ord
private theorem sup_le_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop)
[IsWellOrder ι r] [IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) ≤ sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_le fun i => by
cases'
typein_surj r'
(by
rw [ho', ← ho]
exact typein_lt_type r i) with
j hj
simp_rw [familyOfBFamily', ← hj]
apply le_sup
theorem sup_eq_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o : Ordinal.{u}} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) = sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_eq_of_range_eq.{u, u, v} (by simp)
#align ordinal.sup_eq_sup Ordinal.sup_eq_sup
/-- The supremum of a family of ordinals indexed by the set of ordinals less than some
`o : Ordinal.{u}`. This is a special case of `sup` over the family provided by
`familyOfBFamily`. -/
def bsup (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
sup.{_, v} (familyOfBFamily o f)
#align ordinal.bsup Ordinal.bsup
@[simp]
theorem sup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily o f) = bsup.{_, v} o f :=
rfl
#align ordinal.sup_eq_bsup Ordinal.sup_eq_bsup
@[simp]
theorem sup_eq_bsup' {o : Ordinal.{u}} {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : sup.{_, v} (familyOfBFamily' r ho f) = bsup.{_, v} o f :=
sup_eq_sup r _ ho _ f
#align ordinal.sup_eq_bsup' Ordinal.sup_eq_bsup'
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem sSup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sSup (brange o f) = bsup.{_, v} o f := by
congr
rw [range_familyOfBFamily]
#align ordinal.Sup_eq_bsup Ordinal.sSup_eq_bsup
@[simp]
theorem bsup_eq_sup' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = sup.{_, v} f := by
simp (config := { unfoldPartialApp := true }) only [← sup_eq_bsup' r, enum_typein,
familyOfBFamily', bfamilyOfFamily']
#align ordinal.bsup_eq_sup' Ordinal.bsup_eq_sup'
theorem bsup_eq_bsup {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = bsup.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [bsup_eq_sup', bsup_eq_sup']
#align ordinal.bsup_eq_bsup Ordinal.bsup_eq_bsup
@[simp]
theorem bsup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily f) = sup.{_, v} f :=
bsup_eq_sup' _ f
#align ordinal.bsup_eq_sup Ordinal.bsup_eq_sup
@[congr]
theorem bsup_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
bsup.{_, v} o₁ f = bsup.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.bsup_congr Ordinal.bsup_congr
theorem bsup_le_iff {o f a} : bsup.{u, v} o f ≤ a ↔ ∀ i h, f i h ≤ a :=
sup_le_iff.trans
⟨fun h i hi => by
rw [← familyOfBFamily_enum o f]
exact h _, fun h i => h _ _⟩
#align ordinal.bsup_le_iff Ordinal.bsup_le_iff
theorem bsup_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} :
(∀ i h, f i h ≤ a) → bsup.{u, v} o f ≤ a :=
bsup_le_iff.2
#align ordinal.bsup_le Ordinal.bsup_le
theorem le_bsup {o} (f : ∀ a < o, Ordinal) (i h) : f i h ≤ bsup o f :=
bsup_le_iff.1 le_rfl _ _
#align ordinal.le_bsup Ordinal.le_bsup
theorem lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) {a} :
a < bsup.{_, v} o f ↔ ∃ i hi, a < f i hi := by
simpa only [not_forall, not_le] using not_congr (@bsup_le_iff.{_, v} _ f a)
#align ordinal.lt_bsup Ordinal.lt_bsup
theorem IsNormal.bsup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f)
{o : Ordinal.{u}} :
∀ (g : ∀ a < o, Ordinal), o ≠ 0 → f (bsup.{_, v} o g) = bsup.{_, w} o fun a h => f (g a h) :=
inductionOn o fun α r _ g h => by
haveI := type_ne_zero_iff_nonempty.1 h
rw [← sup_eq_bsup' r, IsNormal.sup.{_, v, w} H, ← sup_eq_bsup' r] <;> rfl
#align ordinal.is_normal.bsup Ordinal.IsNormal.bsup
theorem lt_bsup_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} :
(∀ i h, f i h ≠ bsup.{_, v} o f) ↔ ∀ i h, f i h < bsup.{_, v} o f :=
⟨fun hf _ _ => lt_of_le_of_ne (le_bsup _ _ _) (hf _ _), fun hf _ _ => ne_of_lt (hf _ _)⟩
#align ordinal.lt_bsup_of_ne_bsup Ordinal.lt_bsup_of_ne_bsup
theorem bsup_not_succ_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}}
(hf : ∀ {i : Ordinal} (h : i < o), f i h ≠ bsup.{_, v} o f) (a) :
a < bsup.{_, v} o f → succ a < bsup.{_, v} o f := by
rw [← sup_eq_bsup] at *
exact sup_not_succ_of_ne_sup fun i => hf _
#align ordinal.bsup_not_succ_of_ne_bsup Ordinal.bsup_not_succ_of_ne_bsup
@[simp]
theorem bsup_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : bsup o f = 0 ↔ ∀ i hi, f i hi = 0 := by
refine
⟨fun h i hi => ?_, fun h =>
le_antisymm (bsup_le fun i hi => Ordinal.le_zero.2 (h i hi)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_bsup f i hi
#align ordinal.bsup_eq_zero_iff Ordinal.bsup_eq_zero_iff
theorem lt_bsup_of_limit {o : Ordinal} {f : ∀ a < o, Ordinal}
(hf : ∀ {a a'} (ha : a < o) (ha' : a' < o), a < a' → f a ha < f a' ha')
(ho : ∀ a < o, succ a < o) (i h) : f i h < bsup o f :=
(hf _ _ <| lt_succ i).trans_le (le_bsup f (succ i) <| ho _ h)
#align ordinal.lt_bsup_of_limit Ordinal.lt_bsup_of_limit
theorem bsup_succ_of_mono {o : Ordinal} {f : ∀ a < succ o, Ordinal}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : bsup _ f = f o (lt_succ o) :=
le_antisymm (bsup_le fun _i hi => hf _ _ <| le_of_lt_succ hi) (le_bsup _ _ _)
#align ordinal.bsup_succ_of_mono Ordinal.bsup_succ_of_mono
@[simp]
theorem bsup_zero (f : ∀ a < (0 : Ordinal), Ordinal) : bsup 0 f = 0 :=
bsup_eq_zero_iff.2 fun i hi => (Ordinal.not_lt_zero i hi).elim
#align ordinal.bsup_zero Ordinal.bsup_zero
theorem bsup_const {o : Ordinal.{u}} (ho : o ≠ 0) (a : Ordinal.{max u v}) :
(bsup.{_, v} o fun _ _ => a) = a :=
le_antisymm (bsup_le fun _ _ => le_rfl) (le_bsup _ 0 (Ordinal.pos_iff_ne_zero.2 ho))
#align ordinal.bsup_const Ordinal.bsup_const
@[simp]
theorem bsup_one (f : ∀ a < (1 : Ordinal), Ordinal) : bsup 1 f = f 0 zero_lt_one := by
simp_rw [← sup_eq_bsup, sup_unique, familyOfBFamily, familyOfBFamily', typein_one_out]
#align ordinal.bsup_one Ordinal.bsup_one
theorem bsup_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : bsup.{u, max v w} o f ≤ bsup.{v, max u w} o' g :=
bsup_le fun i hi => by
obtain ⟨j, hj, hj'⟩ := h ⟨i, hi, rfl⟩
rw [← hj']
apply le_bsup
#align ordinal.bsup_le_of_brange_subset Ordinal.bsup_le_of_brange_subset
theorem bsup_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f = brange o' g) : bsup.{u, max v w} o f = bsup.{v, max u w} o' g :=
(bsup_le_of_brange_subset.{u, v, w} h.le).antisymm (bsup_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.bsup_eq_of_brange_eq Ordinal.bsup_eq_of_brange_eq
/-- The least strict upper bound of a family of ordinals. -/
def lsub {ι} (f : ι → Ordinal) : Ordinal :=
sup (succ ∘ f)
#align ordinal.lsub Ordinal.lsub
@[simp]
theorem sup_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} (succ ∘ f) = lsub.{_, v} f :=
rfl
#align ordinal.sup_eq_lsub Ordinal.sup_eq_lsub
| Mathlib/SetTheory/Ordinal/Arithmetic.lean | 1,584 | 1,588 | theorem lsub_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
lsub.{_, v} f ≤ a ↔ ∀ i, f i < a := by |
convert sup_le_iff.{_, v} (f := succ ∘ f) (a := a) using 2
-- Porting note: `comp_apply` is required.
simp only [comp_apply, succ_le_iff]
|
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Probability.Martingale.Convergence
import Mathlib.Probability.Martingale.OptionalStopping
import Mathlib.Probability.Martingale.Centering
#align_import probability.martingale.borel_cantelli from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Generalized Borel-Cantelli lemma
This file proves Lévy's generalized Borel-Cantelli lemma which is a generalization of the
Borel-Cantelli lemmas. With this generalization, one can easily deduce the Borel-Cantelli lemmas
by choosing appropriate filtrations. This file also contains the one sided martingale bound which
is required to prove the generalized Borel-Cantelli.
**Note**: the usual Borel-Cantelli lemmas are not in this file. See
`MeasureTheory.measure_limsup_eq_zero` for the first (which does not depend on the results here),
and `ProbabilityTheory.measure_limsup_eq_one` for the second (which does).
## Main results
- `MeasureTheory.Submartingale.bddAbove_iff_exists_tendsto`: the one sided martingale bound: given
a submartingale `f` with uniformly bounded differences, the set for which `f` converges is almost
everywhere equal to the set for which it is bounded.
- `MeasureTheory.ae_mem_limsup_atTop_iff`: Lévy's generalized Borel-Cantelli:
given a filtration `ℱ` and a sequence of sets `s` such that `s n ∈ ℱ n` for all `n`,
`limsup atTop s` is almost everywhere equal to the set for which `∑ ℙ[s (n + 1)∣ℱ n] = ∞`.
-/
open Filter
open scoped NNReal ENNReal MeasureTheory ProbabilityTheory BigOperators Topology
namespace MeasureTheory
variable {Ω : Type*} {m0 : MeasurableSpace Ω} {μ : Measure Ω} {ℱ : Filtration ℕ m0} {f : ℕ → Ω → ℝ}
{ω : Ω}
/-!
### One sided martingale bound
-/
-- TODO: `leastGE` should be defined taking values in `WithTop ℕ` once the `stoppedProcess`
-- refactor is complete
/-- `leastGE f r n` is the stopping time corresponding to the first time `f ≥ r`. -/
noncomputable def leastGE (f : ℕ → Ω → ℝ) (r : ℝ) (n : ℕ) :=
hitting f (Set.Ici r) 0 n
#align measure_theory.least_ge MeasureTheory.leastGE
theorem Adapted.isStoppingTime_leastGE (r : ℝ) (n : ℕ) (hf : Adapted ℱ f) :
IsStoppingTime ℱ (leastGE f r n) :=
hitting_isStoppingTime hf measurableSet_Ici
#align measure_theory.adapted.is_stopping_time_least_ge MeasureTheory.Adapted.isStoppingTime_leastGE
theorem leastGE_le {i : ℕ} {r : ℝ} (ω : Ω) : leastGE f r i ω ≤ i :=
hitting_le ω
#align measure_theory.least_ge_le MeasureTheory.leastGE_le
-- The following four lemmas shows `leastGE` behaves like a stopped process. Ideally we should
-- define `leastGE` as a stopping time and take its stopped process. However, we can't do that
-- with our current definition since a stopping time takes only finite indicies. An upcomming
-- refactor should hopefully make it possible to have stopping times taking infinity as a value
theorem leastGE_mono {n m : ℕ} (hnm : n ≤ m) (r : ℝ) (ω : Ω) : leastGE f r n ω ≤ leastGE f r m ω :=
hitting_mono hnm
#align measure_theory.least_ge_mono MeasureTheory.leastGE_mono
theorem leastGE_eq_min (π : Ω → ℕ) (r : ℝ) (ω : Ω) {n : ℕ} (hπn : ∀ ω, π ω ≤ n) :
leastGE f r (π ω) ω = min (π ω) (leastGE f r n ω) := by
classical
refine le_antisymm (le_min (leastGE_le _) (leastGE_mono (hπn ω) r ω)) ?_
by_cases hle : π ω ≤ leastGE f r n ω
· rw [min_eq_left hle, leastGE]
by_cases h : ∃ j ∈ Set.Icc 0 (π ω), f j ω ∈ Set.Ici r
· refine hle.trans (Eq.le ?_)
rw [leastGE, ← hitting_eq_hitting_of_exists (hπn ω) h]
· simp only [hitting, if_neg h, le_rfl]
· rw [min_eq_right (not_le.1 hle).le, leastGE, leastGE, ←
hitting_eq_hitting_of_exists (hπn ω) _]
rw [not_le, leastGE, hitting_lt_iff _ (hπn ω)] at hle
exact
let ⟨j, hj₁, hj₂⟩ := hle
⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩
#align measure_theory.least_ge_eq_min MeasureTheory.leastGE_eq_min
theorem stoppedValue_stoppedValue_leastGE (f : ℕ → Ω → ℝ) (π : Ω → ℕ) (r : ℝ) {n : ℕ}
(hπn : ∀ ω, π ω ≤ n) : stoppedValue (fun i => stoppedValue f (leastGE f r i)) π =
stoppedValue (stoppedProcess f (leastGE f r n)) π := by
ext1 ω
simp (config := { unfoldPartialApp := true }) only [stoppedProcess, stoppedValue]
rw [leastGE_eq_min _ _ _ hπn]
#align measure_theory.stopped_value_stopped_value_least_ge MeasureTheory.stoppedValue_stoppedValue_leastGE
theorem Submartingale.stoppedValue_leastGE [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) (r : ℝ) :
Submartingale (fun i => stoppedValue f (leastGE f r i)) ℱ μ := by
rw [submartingale_iff_expected_stoppedValue_mono]
· intro σ π hσ hπ hσ_le_π hπ_bdd
obtain ⟨n, hπ_le_n⟩ := hπ_bdd
simp_rw [stoppedValue_stoppedValue_leastGE f σ r fun i => (hσ_le_π i).trans (hπ_le_n i)]
simp_rw [stoppedValue_stoppedValue_leastGE f π r hπ_le_n]
refine hf.expected_stoppedValue_mono ?_ ?_ ?_ fun ω => (min_le_left _ _).trans (hπ_le_n ω)
· exact hσ.min (hf.adapted.isStoppingTime_leastGE _ _)
· exact hπ.min (hf.adapted.isStoppingTime_leastGE _ _)
· exact fun ω => min_le_min (hσ_le_π ω) le_rfl
· exact fun i => stronglyMeasurable_stoppedValue_of_le hf.adapted.progMeasurable_of_discrete
(hf.adapted.isStoppingTime_leastGE _ _) leastGE_le
· exact fun i => integrable_stoppedValue _ (hf.adapted.isStoppingTime_leastGE _ _) hf.integrable
leastGE_le
#align measure_theory.submartingale.stopped_value_least_ge MeasureTheory.Submartingale.stoppedValue_leastGE
variable {r : ℝ} {R : ℝ≥0}
theorem norm_stoppedValue_leastGE_le (hr : 0 ≤ r) (hf0 : f 0 = 0)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) (i : ℕ) :
∀ᵐ ω ∂μ, stoppedValue f (leastGE f r i) ω ≤ r + R := by
filter_upwards [hbdd] with ω hbddω
change f (leastGE f r i ω) ω ≤ r + R
by_cases heq : leastGE f r i ω = 0
· rw [heq, hf0, Pi.zero_apply]
exact add_nonneg hr R.coe_nonneg
· obtain ⟨k, hk⟩ := Nat.exists_eq_succ_of_ne_zero heq
rw [hk, add_comm, ← sub_le_iff_le_add]
have := not_mem_of_lt_hitting (hk.symm ▸ k.lt_succ_self : k < leastGE f r i ω) (zero_le _)
simp only [Set.mem_union, Set.mem_Iic, Set.mem_Ici, not_or, not_le] at this
exact (sub_lt_sub_left this _).le.trans ((le_abs_self _).trans (hbddω _))
#align measure_theory.norm_stopped_value_least_ge_le MeasureTheory.norm_stoppedValue_leastGE_le
theorem Submartingale.stoppedValue_leastGE_snorm_le [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hr : 0 ≤ r) (hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) (i : ℕ) :
snorm (stoppedValue f (leastGE f r i)) 1 μ ≤ 2 * μ Set.univ * ENNReal.ofReal (r + R) := by
refine snorm_one_le_of_le' ((hf.stoppedValue_leastGE r).integrable _) ?_
(norm_stoppedValue_leastGE_le hr hf0 hbdd i)
rw [← integral_univ]
refine le_trans ?_ ((hf.stoppedValue_leastGE r).setIntegral_le (zero_le _) MeasurableSet.univ)
simp_rw [stoppedValue, leastGE, hitting_of_le le_rfl, hf0, integral_zero', le_rfl]
#align measure_theory.submartingale.stopped_value_least_ge_snorm_le MeasureTheory.Submartingale.stoppedValue_leastGE_snorm_le
theorem Submartingale.stoppedValue_leastGE_snorm_le' [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hr : 0 ≤ r) (hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) (i : ℕ) :
snorm (stoppedValue f (leastGE f r i)) 1 μ ≤
ENNReal.toNNReal (2 * μ Set.univ * ENNReal.ofReal (r + R)) := by
refine (hf.stoppedValue_leastGE_snorm_le hr hf0 hbdd i).trans ?_
simp [ENNReal.coe_toNNReal (measure_ne_top μ _), ENNReal.coe_toNNReal]
#align measure_theory.submartingale.stopped_value_least_ge_snorm_le' MeasureTheory.Submartingale.stoppedValue_leastGE_snorm_le'
/-- This lemma is superseded by `Submartingale.bddAbove_iff_exists_tendsto`. -/
theorem Submartingale.exists_tendsto_of_abs_bddAbove_aux [IsFiniteMeasure μ]
(hf : Submartingale f ℱ μ) (hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) → ∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c) := by
have ht :
∀ᵐ ω ∂μ, ∀ i : ℕ, ∃ c, Tendsto (fun n => stoppedValue f (leastGE f i n) ω) atTop (𝓝 c) := by
rw [ae_all_iff]
exact fun i => Submartingale.exists_ae_tendsto_of_bdd (hf.stoppedValue_leastGE i)
(hf.stoppedValue_leastGE_snorm_le' i.cast_nonneg hf0 hbdd)
filter_upwards [ht] with ω hω hωb
rw [BddAbove] at hωb
obtain ⟨i, hi⟩ := exists_nat_gt hωb.some
have hib : ∀ n, f n ω < i := by
intro n
exact lt_of_le_of_lt ((mem_upperBounds.1 hωb.some_mem) _ ⟨n, rfl⟩) hi
have heq : ∀ n, stoppedValue f (leastGE f i n) ω = f n ω := by
intro n
rw [leastGE]; unfold hitting; rw [stoppedValue]
rw [if_neg]
simp only [Set.mem_Icc, Set.mem_union, Set.mem_Ici]
push_neg
exact fun j _ => hib j
simp only [← heq, hω i]
#align measure_theory.submartingale.exists_tendsto_of_abs_bdd_above_aux MeasureTheory.Submartingale.exists_tendsto_of_abs_bddAbove_aux
theorem Submartingale.bddAbove_iff_exists_tendsto_aux [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) ↔ ∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c) := by
filter_upwards [hf.exists_tendsto_of_abs_bddAbove_aux hf0 hbdd] with ω hω using
⟨hω, fun ⟨c, hc⟩ => hc.bddAbove_range⟩
#align measure_theory.submartingale.bdd_above_iff_exists_tendsto_aux MeasureTheory.Submartingale.bddAbove_iff_exists_tendsto_aux
/-- One sided martingale bound: If `f` is a submartingale which has uniformly bounded differences,
then for almost every `ω`, `f n ω` is bounded above (in `n`) if and only if it converges. -/
| Mathlib/Probability/Martingale/BorelCantelli.lean | 187 | 209 | theorem Submartingale.bddAbove_iff_exists_tendsto [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) ↔ ∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c) := by |
set g : ℕ → Ω → ℝ := fun n ω => f n ω - f 0 ω
have hg : Submartingale g ℱ μ :=
hf.sub_martingale (martingale_const_fun _ _ (hf.adapted 0) (hf.integrable 0))
have hg0 : g 0 = 0 := by
ext ω
simp only [g, sub_self, Pi.zero_apply]
have hgbdd : ∀ᵐ ω ∂μ, ∀ i : ℕ, |g (i + 1) ω - g i ω| ≤ ↑R := by
simpa only [g, sub_sub_sub_cancel_right]
filter_upwards [hg.bddAbove_iff_exists_tendsto_aux hg0 hgbdd] with ω hω
convert hω using 1
· refine ⟨fun h => ?_, fun h => ?_⟩ <;> obtain ⟨b, hb⟩ := h <;>
refine ⟨b + |f 0 ω|, fun y hy => ?_⟩ <;> obtain ⟨n, rfl⟩ := hy
· simp_rw [g, sub_eq_add_neg]
exact add_le_add (hb ⟨n, rfl⟩) (neg_le_abs _)
· exact sub_le_iff_le_add.1 (le_trans (sub_le_sub_left (le_abs_self _) _) (hb ⟨n, rfl⟩))
· refine ⟨fun h => ?_, fun h => ?_⟩ <;> obtain ⟨c, hc⟩ := h
· exact ⟨c - f 0 ω, hc.sub_const _⟩
· refine ⟨c + f 0 ω, ?_⟩
have := hc.add_const (f 0 ω)
simpa only [g, sub_add_cancel]
|
/-
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.BaseChange
import Mathlib.Algebra.Lie.Solvable
import Mathlib.Algebra.Lie.Quotient
import Mathlib.Algebra.Lie.Normalizer
import Mathlib.LinearAlgebra.Eigenspace.Basic
import Mathlib.Order.Filter.AtTopBot
import Mathlib.RingTheory.Artinian
import Mathlib.RingTheory.Nilpotent.Lemmas
import Mathlib.Tactic.Monotonicity
#align_import algebra.lie.nilpotent from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1"
/-!
# Nilpotent Lie algebras
Like groups, Lie algebras admit a natural concept of nilpotency. More generally, any Lie module
carries a natural concept of nilpotency. We define these here via the lower central series.
## Main definitions
* `LieModule.lowerCentralSeries`
* `LieModule.IsNilpotent`
## Tags
lie algebra, lower central series, nilpotent
-/
universe u v w w₁ w₂
section NilpotentModules
variable {R : Type u} {L : Type v} {M : Type w}
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
variable (k : ℕ) (N : LieSubmodule R L M)
namespace LieSubmodule
/-- A generalisation of the lower central series. The zeroth term is a specified Lie submodule of
a Lie module. In the case when we specify the top ideal `⊤` of the Lie algebra, regarded as a Lie
module over itself, we get the usual lower central series of a Lie algebra.
It can be more convenient to work with this generalisation when considering the lower central series
of a Lie submodule, regarded as a Lie module in its own right, since it provides a type-theoretic
expression of the fact that the terms of the Lie submodule's lower central series are also Lie
submodules of the enclosing Lie module.
See also `LieSubmodule.lowerCentralSeries_eq_lcs_comap` and
`LieSubmodule.lowerCentralSeries_map_eq_lcs` below, as well as `LieSubmodule.ucs`. -/
def lcs : LieSubmodule R L M → LieSubmodule R L M :=
(fun N => ⁅(⊤ : LieIdeal R L), N⁆)^[k]
#align lie_submodule.lcs LieSubmodule.lcs
@[simp]
theorem lcs_zero (N : LieSubmodule R L M) : N.lcs 0 = N :=
rfl
#align lie_submodule.lcs_zero LieSubmodule.lcs_zero
@[simp]
theorem lcs_succ : N.lcs (k + 1) = ⁅(⊤ : LieIdeal R L), N.lcs k⁆ :=
Function.iterate_succ_apply' (fun N' => ⁅⊤, N'⁆) k N
#align lie_submodule.lcs_succ LieSubmodule.lcs_succ
@[simp]
lemma lcs_sup {N₁ N₂ : LieSubmodule R L M} {k : ℕ} :
(N₁ ⊔ N₂).lcs k = N₁.lcs k ⊔ N₂.lcs k := by
induction' k with k ih
· simp
· simp only [LieSubmodule.lcs_succ, ih, LieSubmodule.lie_sup]
end LieSubmodule
namespace LieModule
variable (R L M)
/-- The lower central series of Lie submodules of a Lie module. -/
def lowerCentralSeries : LieSubmodule R L M :=
(⊤ : LieSubmodule R L M).lcs k
#align lie_module.lower_central_series LieModule.lowerCentralSeries
@[simp]
theorem lowerCentralSeries_zero : lowerCentralSeries R L M 0 = ⊤ :=
rfl
#align lie_module.lower_central_series_zero LieModule.lowerCentralSeries_zero
@[simp]
theorem lowerCentralSeries_succ :
lowerCentralSeries R L M (k + 1) = ⁅(⊤ : LieIdeal R L), lowerCentralSeries R L M k⁆ :=
(⊤ : LieSubmodule R L M).lcs_succ k
#align lie_module.lower_central_series_succ LieModule.lowerCentralSeries_succ
end LieModule
namespace LieSubmodule
open LieModule
theorem lcs_le_self : N.lcs k ≤ N := by
induction' k with k ih
· simp
· simp only [lcs_succ]
exact (LieSubmodule.mono_lie_right _ _ ⊤ ih).trans (N.lie_le_right ⊤)
#align lie_submodule.lcs_le_self LieSubmodule.lcs_le_self
theorem lowerCentralSeries_eq_lcs_comap : lowerCentralSeries R L N k = (N.lcs k).comap N.incl := by
induction' k with k ih
· simp
· simp only [lcs_succ, lowerCentralSeries_succ] at ih ⊢
have : N.lcs k ≤ N.incl.range := by
rw [N.range_incl]
apply lcs_le_self
rw [ih, LieSubmodule.comap_bracket_eq _ _ N.incl N.ker_incl this]
#align lie_submodule.lower_central_series_eq_lcs_comap LieSubmodule.lowerCentralSeries_eq_lcs_comap
theorem lowerCentralSeries_map_eq_lcs : (lowerCentralSeries R L N k).map N.incl = N.lcs k := by
rw [lowerCentralSeries_eq_lcs_comap, LieSubmodule.map_comap_incl, inf_eq_right]
apply lcs_le_self
#align lie_submodule.lower_central_series_map_eq_lcs LieSubmodule.lowerCentralSeries_map_eq_lcs
end LieSubmodule
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
variable (R L M)
theorem antitone_lowerCentralSeries : Antitone <| lowerCentralSeries R L M := by
intro l k
induction' k with k ih generalizing l <;> intro h
· exact (Nat.le_zero.mp h).symm ▸ le_rfl
· rcases Nat.of_le_succ h with (hk | hk)
· rw [lowerCentralSeries_succ]
exact (LieSubmodule.mono_lie_right _ _ ⊤ (ih hk)).trans (LieSubmodule.lie_le_right _ _)
· exact hk.symm ▸ le_rfl
#align lie_module.antitone_lower_central_series LieModule.antitone_lowerCentralSeries
theorem eventually_iInf_lowerCentralSeries_eq [IsArtinian R M] :
∀ᶠ l in Filter.atTop, ⨅ k, lowerCentralSeries R L M k = lowerCentralSeries R L M l := by
have h_wf : WellFounded ((· > ·) : (LieSubmodule R L M)ᵒᵈ → (LieSubmodule R L M)ᵒᵈ → Prop) :=
LieSubmodule.wellFounded_of_isArtinian R L M
obtain ⟨n, hn : ∀ m, n ≤ m → lowerCentralSeries R L M n = lowerCentralSeries R L M m⟩ :=
WellFounded.monotone_chain_condition.mp h_wf ⟨_, antitone_lowerCentralSeries R L M⟩
refine Filter.eventually_atTop.mpr ⟨n, fun l hl ↦ le_antisymm (iInf_le _ _) (le_iInf fun m ↦ ?_)⟩
rcases le_or_lt l m with h | h
· rw [← hn _ hl, ← hn _ (hl.trans h)]
· exact antitone_lowerCentralSeries R L M (le_of_lt h)
theorem trivial_iff_lower_central_eq_bot : IsTrivial L M ↔ lowerCentralSeries R L M 1 = ⊥ := by
constructor <;> intro h
· erw [eq_bot_iff, LieSubmodule.lieSpan_le]; rintro m ⟨x, n, hn⟩; rw [← hn, h.trivial]; simp
· rw [LieSubmodule.eq_bot_iff] at h; apply IsTrivial.mk; intro x m; apply h
apply LieSubmodule.subset_lieSpan
-- Porting note: was `use x, m; rfl`
simp only [LieSubmodule.top_coe, Subtype.exists, LieSubmodule.mem_top, exists_prop, true_and,
Set.mem_setOf]
exact ⟨x, m, rfl⟩
#align lie_module.trivial_iff_lower_central_eq_bot LieModule.trivial_iff_lower_central_eq_bot
theorem iterate_toEnd_mem_lowerCentralSeries (x : L) (m : M) (k : ℕ) :
(toEnd R L M x)^[k] m ∈ lowerCentralSeries R L M k := by
induction' k with k ih
· simp only [Nat.zero_eq, Function.iterate_zero, lowerCentralSeries_zero, LieSubmodule.mem_top]
· simp only [lowerCentralSeries_succ, Function.comp_apply, Function.iterate_succ',
toEnd_apply_apply]
exact LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top x) ih
#align lie_module.iterate_to_endomorphism_mem_lower_central_series LieModule.iterate_toEnd_mem_lowerCentralSeries
theorem iterate_toEnd_mem_lowerCentralSeries₂ (x y : L) (m : M) (k : ℕ) :
(toEnd R L M x ∘ₗ toEnd R L M y)^[k] m ∈
lowerCentralSeries R L M (2 * k) := by
induction' k with k ih
· simp
have hk : 2 * k.succ = (2 * k + 1) + 1 := rfl
simp only [lowerCentralSeries_succ, Function.comp_apply, Function.iterate_succ', hk,
toEnd_apply_apply, LinearMap.coe_comp, toEnd_apply_apply]
refine LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top x) ?_
exact LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top y) ih
variable {R L M}
theorem map_lowerCentralSeries_le (f : M →ₗ⁅R,L⁆ M₂) :
(lowerCentralSeries R L M k).map f ≤ lowerCentralSeries R L M₂ k := by
induction' k with k ih
· simp only [Nat.zero_eq, lowerCentralSeries_zero, le_top]
· simp only [LieModule.lowerCentralSeries_succ, LieSubmodule.map_bracket_eq]
exact LieSubmodule.mono_lie_right _ _ ⊤ ih
#align lie_module.map_lower_central_series_le LieModule.map_lowerCentralSeries_le
lemma map_lowerCentralSeries_eq {f : M →ₗ⁅R,L⁆ M₂} (hf : Function.Surjective f) :
(lowerCentralSeries R L M k).map f = lowerCentralSeries R L M₂ k := by
apply le_antisymm (map_lowerCentralSeries_le k f)
induction' k with k ih
· rwa [lowerCentralSeries_zero, lowerCentralSeries_zero, top_le_iff, f.map_top, f.range_eq_top]
· simp only [lowerCentralSeries_succ, LieSubmodule.map_bracket_eq]
apply LieSubmodule.mono_lie_right
assumption
variable (R L M)
open LieAlgebra
theorem derivedSeries_le_lowerCentralSeries (k : ℕ) :
derivedSeries R L k ≤ lowerCentralSeries R L L k := by
induction' k with k h
· rw [derivedSeries_def, derivedSeriesOfIdeal_zero, lowerCentralSeries_zero]
· have h' : derivedSeries R L k ≤ ⊤ := by simp only [le_top]
rw [derivedSeries_def, derivedSeriesOfIdeal_succ, lowerCentralSeries_succ]
exact LieSubmodule.mono_lie _ _ _ _ h' h
#align lie_module.derived_series_le_lower_central_series LieModule.derivedSeries_le_lowerCentralSeries
/-- A Lie module is nilpotent if its lower central series reaches 0 (in a finite number of
steps). -/
class IsNilpotent : Prop where
nilpotent : ∃ k, lowerCentralSeries R L M k = ⊥
#align lie_module.is_nilpotent LieModule.IsNilpotent
theorem exists_lowerCentralSeries_eq_bot_of_isNilpotent [IsNilpotent R L M] :
∃ k, lowerCentralSeries R L M k = ⊥ :=
IsNilpotent.nilpotent
@[simp] lemma iInf_lowerCentralSeries_eq_bot_of_isNilpotent [IsNilpotent R L M] :
⨅ k, lowerCentralSeries R L M k = ⊥ := by
obtain ⟨k, hk⟩ := exists_lowerCentralSeries_eq_bot_of_isNilpotent R L M
rw [eq_bot_iff, ← hk]
exact iInf_le _ _
/-- See also `LieModule.isNilpotent_iff_exists_ucs_eq_top`. -/
theorem isNilpotent_iff : IsNilpotent R L M ↔ ∃ k, lowerCentralSeries R L M k = ⊥ :=
⟨fun h => h.nilpotent, fun h => ⟨h⟩⟩
#align lie_module.is_nilpotent_iff LieModule.isNilpotent_iff
variable {R L M}
theorem _root_.LieSubmodule.isNilpotent_iff_exists_lcs_eq_bot (N : LieSubmodule R L M) :
LieModule.IsNilpotent R L N ↔ ∃ k, N.lcs k = ⊥ := by
rw [isNilpotent_iff]
refine exists_congr fun k => ?_
rw [N.lowerCentralSeries_eq_lcs_comap k, LieSubmodule.comap_incl_eq_bot,
inf_eq_right.mpr (N.lcs_le_self k)]
#align lie_submodule.is_nilpotent_iff_exists_lcs_eq_bot LieSubmodule.isNilpotent_iff_exists_lcs_eq_bot
variable (R L M)
instance (priority := 100) trivialIsNilpotent [IsTrivial L M] : IsNilpotent R L M :=
⟨by use 1; change ⁅⊤, ⊤⁆ = ⊥; simp⟩
#align lie_module.trivial_is_nilpotent LieModule.trivialIsNilpotent
theorem exists_forall_pow_toEnd_eq_zero [hM : IsNilpotent R L M] :
∃ k : ℕ, ∀ x : L, toEnd R L M x ^ k = 0 := by
obtain ⟨k, hM⟩ := hM
use k
intro x; ext m
rw [LinearMap.pow_apply, LinearMap.zero_apply, ← @LieSubmodule.mem_bot R L M, ← hM]
exact iterate_toEnd_mem_lowerCentralSeries R L M x m k
#align lie_module.nilpotent_endo_of_nilpotent_module LieModule.exists_forall_pow_toEnd_eq_zero
theorem isNilpotent_toEnd_of_isNilpotent [IsNilpotent R L M] (x : L) :
_root_.IsNilpotent (toEnd R L M x) := by
change ∃ k, toEnd R L M x ^ k = 0
have := exists_forall_pow_toEnd_eq_zero R L M
tauto
theorem isNilpotent_toEnd_of_isNilpotent₂ [IsNilpotent R L M] (x y : L) :
_root_.IsNilpotent (toEnd R L M x ∘ₗ toEnd R L M y) := by
obtain ⟨k, hM⟩ := exists_lowerCentralSeries_eq_bot_of_isNilpotent R L M
replace hM : lowerCentralSeries R L M (2 * k) = ⊥ := by
rw [eq_bot_iff, ← hM]; exact antitone_lowerCentralSeries R L M (by omega)
use k
ext m
rw [LinearMap.pow_apply, LinearMap.zero_apply, ← LieSubmodule.mem_bot (R := R) (L := L), ← hM]
exact iterate_toEnd_mem_lowerCentralSeries₂ R L M x y m k
@[simp] lemma maxGenEigenSpace_toEnd_eq_top [IsNilpotent R L M] (x : L) :
((toEnd R L M x).maxGenEigenspace 0) = ⊤ := by
ext m
simp only [Module.End.mem_maxGenEigenspace, zero_smul, sub_zero, Submodule.mem_top,
iff_true]
obtain ⟨k, hk⟩ := exists_forall_pow_toEnd_eq_zero R L M
exact ⟨k, by simp [hk x]⟩
/-- If the quotient of a Lie module `M` by a Lie submodule on which the Lie algebra acts trivially
is nilpotent then `M` is nilpotent.
This is essentially the Lie module equivalent of the fact that a central
extension of nilpotent Lie algebras is nilpotent. See `LieAlgebra.nilpotent_of_nilpotent_quotient`
below for the corresponding result for Lie algebras. -/
theorem nilpotentOfNilpotentQuotient {N : LieSubmodule R L M} (h₁ : N ≤ maxTrivSubmodule R L M)
(h₂ : IsNilpotent R L (M ⧸ N)) : IsNilpotent R L M := by
obtain ⟨k, hk⟩ := h₂
use k + 1
simp only [lowerCentralSeries_succ]
suffices lowerCentralSeries R L M k ≤ N by
replace this := LieSubmodule.mono_lie_right _ _ ⊤ (le_trans this h₁)
rwa [ideal_oper_maxTrivSubmodule_eq_bot, le_bot_iff] at this
rw [← LieSubmodule.Quotient.map_mk'_eq_bot_le, ← le_bot_iff, ← hk]
exact map_lowerCentralSeries_le k (LieSubmodule.Quotient.mk' N)
#align lie_module.nilpotent_of_nilpotent_quotient LieModule.nilpotentOfNilpotentQuotient
theorem isNilpotent_quotient_iff :
IsNilpotent R L (M ⧸ N) ↔ ∃ k, lowerCentralSeries R L M k ≤ N := by
rw [LieModule.isNilpotent_iff]
refine exists_congr fun k ↦ ?_
rw [← LieSubmodule.Quotient.map_mk'_eq_bot_le, map_lowerCentralSeries_eq k
(LieSubmodule.Quotient.surjective_mk' N)]
theorem iInf_lcs_le_of_isNilpotent_quot (h : IsNilpotent R L (M ⧸ N)) :
⨅ k, lowerCentralSeries R L M k ≤ N := by
obtain ⟨k, hk⟩ := (isNilpotent_quotient_iff R L M N).mp h
exact iInf_le_of_le k hk
/-- Given a nilpotent Lie module `M` with lower central series `M = C₀ ≥ C₁ ≥ ⋯ ≥ Cₖ = ⊥`, this is
the natural number `k` (the number of inclusions).
For a non-nilpotent module, we use the junk value 0. -/
noncomputable def nilpotencyLength : ℕ :=
sInf {k | lowerCentralSeries R L M k = ⊥}
#align lie_module.nilpotency_length LieModule.nilpotencyLength
@[simp]
| Mathlib/Algebra/Lie/Nilpotent.lean | 327 | 338 | theorem nilpotencyLength_eq_zero_iff [IsNilpotent R L M] :
nilpotencyLength R L M = 0 ↔ Subsingleton M := by |
let s := {k | lowerCentralSeries R L M k = ⊥}
have hs : s.Nonempty := by
obtain ⟨k, hk⟩ := (by infer_instance : IsNilpotent R L M)
exact ⟨k, hk⟩
change sInf s = 0 ↔ _
rw [← LieSubmodule.subsingleton_iff R L M, ← subsingleton_iff_bot_eq_top, ←
lowerCentralSeries_zero, @eq_comm (LieSubmodule R L M)]
refine ⟨fun h => h ▸ Nat.sInf_mem hs, fun h => ?_⟩
rw [Nat.sInf_eq_zero]
exact Or.inl h
|
/-
Copyright (c) 2020 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Constructions.Prod.Basic
import Mathlib.MeasureTheory.Group.Measure
import Mathlib.Topology.Constructions
#align_import measure_theory.constructions.pi from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Product measures
In this file we define and prove properties about finite products of measures
(and at some point, countable products of measures).
## Main definition
* `MeasureTheory.Measure.pi`: The product of finitely many σ-finite measures.
Given `μ : (i : ι) → Measure (α i)` for `[Fintype ι]` it has type `Measure ((i : ι) → α i)`.
To apply Fubini's theorem or Tonelli's theorem along some subset, we recommend using the marginal
construction `MeasureTheory.lmarginal` and (todo) `MeasureTheory.marginal`. This allows you to
apply the theorems without any bookkeeping with measurable equivalences.
## Implementation Notes
We define `MeasureTheory.OuterMeasure.pi`, the product of finitely many outer measures, as the
maximal outer measure `n` with the property that `n (pi univ s) ≤ ∏ i, m i (s i)`,
where `pi univ s` is the product of the sets `{s i | i : ι}`.
We then show that this induces a product of measures, called `MeasureTheory.Measure.pi`.
For a collection of σ-finite measures `μ` and a collection of measurable sets `s` we show that
`Measure.pi μ (pi univ s) = ∏ i, m i (s i)`. To do this, we follow the following steps:
* We know that there is some ordering on `ι`, given by an element of `[Countable ι]`.
* Using this, we have an equivalence `MeasurableEquiv.piMeasurableEquivTProd` between
`∀ ι, α i` and an iterated product of `α i`, called `List.tprod α l` for some list `l`.
* On this iterated product we can easily define a product measure `MeasureTheory.Measure.tprod`
by iterating `MeasureTheory.Measure.prod`
* Using the previous two steps we construct `MeasureTheory.Measure.pi'` on `(i : ι) → α i` for
countable `ι`.
* We know that `MeasureTheory.Measure.pi'` sends products of sets to products of measures, and
since `MeasureTheory.Measure.pi` is the maximal such measure (or at least, it comes from an outer
measure which is the maximal such outer measure), we get the same rule for
`MeasureTheory.Measure.pi`.
## Tags
finitary product measure
-/
noncomputable section
open Function Set MeasureTheory.OuterMeasure Filter MeasurableSpace Encodable
open scoped Classical Topology ENNReal
universe u v
variable {ι ι' : Type*} {α : ι → Type*}
/-! We start with some measurability properties -/
/-- Boxes formed by π-systems form a π-system. -/
theorem IsPiSystem.pi {C : ∀ i, Set (Set (α i))} (hC : ∀ i, IsPiSystem (C i)) :
IsPiSystem (pi univ '' pi univ C) := by
rintro _ ⟨s₁, hs₁, rfl⟩ _ ⟨s₂, hs₂, rfl⟩ hst
rw [← pi_inter_distrib] at hst ⊢; rw [univ_pi_nonempty_iff] at hst
exact mem_image_of_mem _ fun i _ => hC i _ (hs₁ i (mem_univ i)) _ (hs₂ i (mem_univ i)) (hst i)
#align is_pi_system.pi IsPiSystem.pi
/-- Boxes form a π-system. -/
theorem isPiSystem_pi [∀ i, MeasurableSpace (α i)] :
IsPiSystem (pi univ '' pi univ fun i => { s : Set (α i) | MeasurableSet s }) :=
IsPiSystem.pi fun _ => isPiSystem_measurableSet
#align is_pi_system_pi isPiSystem_pi
section Finite
variable [Finite ι] [Finite ι']
/-- Boxes of countably spanning sets are countably spanning. -/
theorem IsCountablySpanning.pi {C : ∀ i, Set (Set (α i))} (hC : ∀ i, IsCountablySpanning (C i)) :
IsCountablySpanning (pi univ '' pi univ C) := by
choose s h1s h2s using hC
cases nonempty_encodable (ι → ℕ)
let e : ℕ → ι → ℕ := fun n => (@decode (ι → ℕ) _ n).iget
refine ⟨fun n => Set.pi univ fun i => s i (e n i), fun n =>
mem_image_of_mem _ fun i _ => h1s i _, ?_⟩
simp_rw [(surjective_decode_iget (ι → ℕ)).iUnion_comp fun x => Set.pi univ fun i => s i (x i),
iUnion_univ_pi s, h2s, pi_univ]
#align is_countably_spanning.pi IsCountablySpanning.pi
/-- The product of generated σ-algebras is the one generated by boxes, if both generating sets
are countably spanning. -/
theorem generateFrom_pi_eq {C : ∀ i, Set (Set (α i))} (hC : ∀ i, IsCountablySpanning (C i)) :
(@MeasurableSpace.pi _ _ fun i => generateFrom (C i)) =
generateFrom (pi univ '' pi univ C) := by
cases nonempty_encodable ι
apply le_antisymm
· refine iSup_le ?_; intro i; rw [comap_generateFrom]
apply generateFrom_le; rintro _ ⟨s, hs, rfl⟩; dsimp
choose t h1t h2t using hC
simp_rw [eval_preimage, ← h2t]
rw [← @iUnion_const _ ℕ _ s]
have : Set.pi univ (update (fun i' : ι => iUnion (t i')) i (⋃ _ : ℕ, s)) =
Set.pi univ fun k => ⋃ j : ℕ,
@update ι (fun i' => Set (α i')) _ (fun i' => t i' j) i s k := by
ext; simp_rw [mem_univ_pi]; apply forall_congr'; intro i'
by_cases h : i' = i
· subst h; simp
· rw [← Ne] at h; simp [h]
rw [this, ← iUnion_univ_pi]
apply MeasurableSet.iUnion
intro n; apply measurableSet_generateFrom
apply mem_image_of_mem; intro j _; dsimp only
by_cases h : j = i
· subst h; rwa [update_same]
· rw [update_noteq h]; apply h1t
· apply generateFrom_le; rintro _ ⟨s, hs, rfl⟩
rw [univ_pi_eq_iInter]; apply MeasurableSet.iInter; intro i
apply @measurable_pi_apply _ _ (fun i => generateFrom (C i))
exact measurableSet_generateFrom (hs i (mem_univ i))
#align generate_from_pi_eq generateFrom_pi_eq
/-- If `C` and `D` generate the σ-algebras on `α` resp. `β`, then rectangles formed by `C` and `D`
generate the σ-algebra on `α × β`. -/
theorem generateFrom_eq_pi [h : ∀ i, MeasurableSpace (α i)] {C : ∀ i, Set (Set (α i))}
(hC : ∀ i, generateFrom (C i) = h i) (h2C : ∀ i, IsCountablySpanning (C i)) :
generateFrom (pi univ '' pi univ C) = MeasurableSpace.pi := by
simp only [← funext hC, generateFrom_pi_eq h2C]
#align generate_from_eq_pi generateFrom_eq_pi
/-- The product σ-algebra is generated from boxes, i.e. `s ×ˢ t` for sets `s : set α` and
`t : set β`. -/
theorem generateFrom_pi [∀ i, MeasurableSpace (α i)] :
generateFrom (pi univ '' pi univ fun i => { s : Set (α i) | MeasurableSet s }) =
MeasurableSpace.pi :=
generateFrom_eq_pi (fun _ => generateFrom_measurableSet) fun _ =>
isCountablySpanning_measurableSet
#align generate_from_pi generateFrom_pi
end Finite
namespace MeasureTheory
variable [Fintype ι] {m : ∀ i, OuterMeasure (α i)}
/-- An upper bound for the measure in a finite product space.
It is defined to by taking the image of the set under all projections, and taking the product
of the measures of these images.
For measurable boxes it is equal to the correct measure. -/
@[simp]
def piPremeasure (m : ∀ i, OuterMeasure (α i)) (s : Set (∀ i, α i)) : ℝ≥0∞ :=
∏ i, m i (eval i '' s)
#align measure_theory.pi_premeasure MeasureTheory.piPremeasure
theorem piPremeasure_pi {s : ∀ i, Set (α i)} (hs : (pi univ s).Nonempty) :
piPremeasure m (pi univ s) = ∏ i, m i (s i) := by simp [hs, piPremeasure]
#align measure_theory.pi_premeasure_pi MeasureTheory.piPremeasure_pi
theorem piPremeasure_pi' {s : ∀ i, Set (α i)} : piPremeasure m (pi univ s) = ∏ i, m i (s i) := by
cases isEmpty_or_nonempty ι
· simp [piPremeasure]
rcases (pi univ s).eq_empty_or_nonempty with h | h
· rcases univ_pi_eq_empty_iff.mp h with ⟨i, hi⟩
have : ∃ i, m i (s i) = 0 := ⟨i, by simp [hi]⟩
simpa [h, Finset.card_univ, zero_pow Fintype.card_ne_zero, @eq_comm _ (0 : ℝ≥0∞),
Finset.prod_eq_zero_iff, piPremeasure]
· simp [h, piPremeasure]
#align measure_theory.pi_premeasure_pi' MeasureTheory.piPremeasure_pi'
theorem piPremeasure_pi_mono {s t : Set (∀ i, α i)} (h : s ⊆ t) :
piPremeasure m s ≤ piPremeasure m t :=
Finset.prod_le_prod' fun _ _ => measure_mono (image_subset _ h)
#align measure_theory.pi_premeasure_pi_mono MeasureTheory.piPremeasure_pi_mono
theorem piPremeasure_pi_eval {s : Set (∀ i, α i)} :
piPremeasure m (pi univ fun i => eval i '' s) = piPremeasure m s := by
simp only [eval, piPremeasure_pi']; rfl
#align measure_theory.pi_premeasure_pi_eval MeasureTheory.piPremeasure_pi_eval
namespace OuterMeasure
/-- `OuterMeasure.pi m` is the finite product of the outer measures `{m i | i : ι}`.
It is defined to be the maximal outer measure `n` with the property that
`n (pi univ s) ≤ ∏ i, m i (s i)`, where `pi univ s` is the product of the sets
`{s i | i : ι}`. -/
protected def pi (m : ∀ i, OuterMeasure (α i)) : OuterMeasure (∀ i, α i) :=
boundedBy (piPremeasure m)
#align measure_theory.outer_measure.pi MeasureTheory.OuterMeasure.pi
theorem pi_pi_le (m : ∀ i, OuterMeasure (α i)) (s : ∀ i, Set (α i)) :
OuterMeasure.pi m (pi univ s) ≤ ∏ i, m i (s i) := by
rcases (pi univ s).eq_empty_or_nonempty with h | h
· simp [h]
exact (boundedBy_le _).trans_eq (piPremeasure_pi h)
#align measure_theory.outer_measure.pi_pi_le MeasureTheory.OuterMeasure.pi_pi_le
| Mathlib/MeasureTheory/Constructions/Pi.lean | 204 | 210 | theorem le_pi {m : ∀ i, OuterMeasure (α i)} {n : OuterMeasure (∀ i, α i)} :
n ≤ OuterMeasure.pi m ↔
∀ s : ∀ i, Set (α i), (pi univ s).Nonempty → n (pi univ s) ≤ ∏ i, m i (s i) := by |
rw [OuterMeasure.pi, le_boundedBy']; constructor
· intro h s hs; refine (h _ hs).trans_eq (piPremeasure_pi hs)
· intro h s hs; refine le_trans (n.mono <| subset_pi_eval_image univ s) (h _ ?_)
simp [univ_pi_nonempty_iff, hs]
|
/-
Copyright (c) 2021 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.CategoryTheory.Preadditive.AdditiveFunctor
import Mathlib.CategoryTheory.Monoidal.Functor
#align_import category_theory.monoidal.preadditive from "leanprover-community/mathlib"@"986c4d5761f938b2e1c43c01f001b6d9d88c2055"
/-!
# Preadditive monoidal categories
A monoidal category is `MonoidalPreadditive` if it is preadditive and tensor product of morphisms
is linear in both factors.
-/
noncomputable section
open scoped Classical
namespace CategoryTheory
open CategoryTheory.Limits
open CategoryTheory.MonoidalCategory
variable (C : Type*) [Category C] [Preadditive C] [MonoidalCategory C]
/-- A category is `MonoidalPreadditive` if tensoring is additive in both factors.
Note we don't `extend Preadditive C` here, as `Abelian C` already extends it,
and we'll need to have both typeclasses sometimes.
-/
class MonoidalPreadditive : Prop where
whiskerLeft_zero : ∀ {X Y Z : C}, X ◁ (0 : Y ⟶ Z) = 0 := by aesop_cat
zero_whiskerRight : ∀ {X Y Z : C}, (0 : Y ⟶ Z) ▷ X = 0 := by aesop_cat
whiskerLeft_add : ∀ {X Y Z : C} (f g : Y ⟶ Z), X ◁ (f + g) = X ◁ f + X ◁ g := by aesop_cat
add_whiskerRight : ∀ {X Y Z : C} (f g : Y ⟶ Z), (f + g) ▷ X = f ▷ X + g ▷ X := by aesop_cat
#align category_theory.monoidal_preadditive CategoryTheory.MonoidalPreadditive
attribute [simp] MonoidalPreadditive.whiskerLeft_zero MonoidalPreadditive.zero_whiskerRight
attribute [simp] MonoidalPreadditive.whiskerLeft_add MonoidalPreadditive.add_whiskerRight
variable {C}
variable [MonoidalPreadditive C]
namespace MonoidalPreadditive
-- The priority setting will not be needed when we replace `𝟙 X ⊗ f` by `X ◁ f`.
@[simp (low)]
theorem tensor_zero {W X Y Z : C} (f : W ⟶ X) : f ⊗ (0 : Y ⟶ Z) = 0 := by
simp [tensorHom_def]
-- The priority setting will not be needed when we replace `f ⊗ 𝟙 X` by `f ▷ X`.
@[simp (low)]
theorem zero_tensor {W X Y Z : C} (f : Y ⟶ Z) : (0 : W ⟶ X) ⊗ f = 0 := by
simp [tensorHom_def]
theorem tensor_add {W X Y Z : C} (f : W ⟶ X) (g h : Y ⟶ Z) : f ⊗ (g + h) = f ⊗ g + f ⊗ h := by
simp [tensorHom_def]
theorem add_tensor {W X Y Z : C} (f g : W ⟶ X) (h : Y ⟶ Z) : (f + g) ⊗ h = f ⊗ h + g ⊗ h := by
simp [tensorHom_def]
end MonoidalPreadditive
instance tensorLeft_additive (X : C) : (tensorLeft X).Additive where
#align category_theory.tensor_left_additive CategoryTheory.tensorLeft_additive
instance tensorRight_additive (X : C) : (tensorRight X).Additive where
#align category_theory.tensor_right_additive CategoryTheory.tensorRight_additive
instance tensoringLeft_additive (X : C) : ((tensoringLeft C).obj X).Additive where
#align category_theory.tensoring_left_additive CategoryTheory.tensoringLeft_additive
instance tensoringRight_additive (X : C) : ((tensoringRight C).obj X).Additive where
#align category_theory.tensoring_right_additive CategoryTheory.tensoringRight_additive
/-- A faithful additive monoidal functor to a monoidal preadditive category
ensures that the domain is monoidal preadditive. -/
theorem monoidalPreadditive_of_faithful {D} [Category D] [Preadditive D] [MonoidalCategory D]
(F : MonoidalFunctor D C) [F.Faithful] [F.Additive] :
MonoidalPreadditive D :=
{ whiskerLeft_zero := by
intros
apply F.toFunctor.map_injective
simp [F.map_whiskerLeft]
zero_whiskerRight := by
intros
apply F.toFunctor.map_injective
simp [F.map_whiskerRight]
whiskerLeft_add := by
intros
apply F.toFunctor.map_injective
simp only [F.map_whiskerLeft, Functor.map_add, Preadditive.comp_add, Preadditive.add_comp,
MonoidalPreadditive.whiskerLeft_add]
add_whiskerRight := by
intros
apply F.toFunctor.map_injective
simp only [F.map_whiskerRight, Functor.map_add, Preadditive.comp_add, Preadditive.add_comp,
MonoidalPreadditive.add_whiskerRight] }
#align category_theory.monoidal_preadditive_of_faithful CategoryTheory.monoidalPreadditive_of_faithful
theorem whiskerLeft_sum (P : C) {Q R : C} {J : Type*} (s : Finset J) (g : J → (Q ⟶ R)) :
P ◁ ∑ j ∈ s, g j = ∑ j ∈ s, P ◁ g j :=
map_sum ((tensoringLeft C).obj P).mapAddHom g s
theorem sum_whiskerRight {Q R : C} {J : Type*} (s : Finset J) (g : J → (Q ⟶ R)) (P : C) :
(∑ j ∈ s, g j) ▷ P = ∑ j ∈ s, g j ▷ P :=
map_sum ((tensoringRight C).obj P).mapAddHom g s
theorem tensor_sum {P Q R S : C} {J : Type*} (s : Finset J) (f : P ⟶ Q) (g : J → (R ⟶ S)) :
(f ⊗ ∑ j ∈ s, g j) = ∑ j ∈ s, f ⊗ g j := by
simp only [tensorHom_def, whiskerLeft_sum, Preadditive.comp_sum]
#align category_theory.tensor_sum CategoryTheory.tensor_sum
theorem sum_tensor {P Q R S : C} {J : Type*} (s : Finset J) (f : P ⟶ Q) (g : J → (R ⟶ S)) :
(∑ j ∈ s, g j) ⊗ f = ∑ j ∈ s, g j ⊗ f := by
simp only [tensorHom_def, sum_whiskerRight, Preadditive.sum_comp]
#align category_theory.sum_tensor CategoryTheory.sum_tensor
-- In a closed monoidal category, this would hold because
-- `tensorLeft X` is a left adjoint and hence preserves all colimits.
-- In any case it is true in any preadditive category.
instance (X : C) : PreservesFiniteBiproducts (tensorLeft X) where
preserves {J} :=
{ preserves := fun {f} =>
{ preserves := fun {b} i => isBilimitOfTotal _ (by
dsimp
simp_rw [← id_tensorHom]
simp only [← tensor_comp, Category.comp_id, ← tensor_sum, ← tensor_id,
IsBilimit.total i]) } }
instance (X : C) : PreservesFiniteBiproducts (tensorRight X) where
preserves {J} :=
{ preserves := fun {f} =>
{ preserves := fun {b} i => isBilimitOfTotal _ (by
dsimp
simp_rw [← tensorHom_id]
simp only [← tensor_comp, Category.comp_id, ← sum_tensor, ← tensor_id,
IsBilimit.total i]) } }
variable [HasFiniteBiproducts C]
/-- The isomorphism showing how tensor product on the left distributes over direct sums. -/
def leftDistributor {J : Type} [Fintype J] (X : C) (f : J → C) : X ⊗ ⨁ f ≅ ⨁ fun j => X ⊗ f j :=
(tensorLeft X).mapBiproduct f
#align category_theory.left_distributor CategoryTheory.leftDistributor
theorem leftDistributor_hom {J : Type} [Fintype J] (X : C) (f : J → C) :
(leftDistributor X f).hom =
∑ j : J, (X ◁ biproduct.π f j) ≫ biproduct.ι (fun j => X ⊗ f j) j := by
ext
dsimp [leftDistributor, Functor.mapBiproduct, Functor.mapBicone]
erw [biproduct.lift_π]
simp only [Preadditive.sum_comp, Category.assoc, biproduct.ι_π, comp_dite, comp_zero,
Finset.sum_dite_eq', Finset.mem_univ, ite_true, eqToHom_refl, Category.comp_id]
#align category_theory.left_distributor_hom CategoryTheory.leftDistributor_hom
theorem leftDistributor_inv {J : Type} [Fintype J] (X : C) (f : J → C) :
(leftDistributor X f).inv = ∑ j : J, biproduct.π _ j ≫ (X ◁ biproduct.ι f j) := by
ext
dsimp [leftDistributor, Functor.mapBiproduct, Functor.mapBicone]
simp only [Preadditive.comp_sum, biproduct.ι_π_assoc, dite_comp, zero_comp,
Finset.sum_dite_eq, Finset.mem_univ, ite_true, eqToHom_refl, Category.id_comp,
biproduct.ι_desc]
#align category_theory.left_distributor_inv CategoryTheory.leftDistributor_inv
@[reassoc (attr := simp)]
theorem leftDistributor_hom_comp_biproduct_π {J : Type} [Fintype J] (X : C) (f : J → C) (j : J) :
(leftDistributor X f).hom ≫ biproduct.π _ j = X ◁ biproduct.π _ j := by
simp [leftDistributor_hom, Preadditive.sum_comp, biproduct.ι_π, comp_dite]
@[reassoc (attr := simp)]
theorem biproduct_ι_comp_leftDistributor_hom {J : Type} [Fintype J] (X : C) (f : J → C) (j : J) :
(X ◁ biproduct.ι _ j) ≫ (leftDistributor X f).hom = biproduct.ι (fun j => X ⊗ f j) j := by
simp [leftDistributor_hom, Preadditive.comp_sum, ← MonoidalCategory.whiskerLeft_comp_assoc,
biproduct.ι_π, whiskerLeft_dite, dite_comp]
@[reassoc (attr := simp)]
theorem leftDistributor_inv_comp_biproduct_π {J : Type} [Fintype J] (X : C) (f : J → C) (j : J) :
(leftDistributor X f).inv ≫ (X ◁ biproduct.π _ j) = biproduct.π _ j := by
simp [leftDistributor_inv, Preadditive.sum_comp, ← MonoidalCategory.whiskerLeft_comp,
biproduct.ι_π, whiskerLeft_dite, comp_dite]
@[reassoc (attr := simp)]
theorem biproduct_ι_comp_leftDistributor_inv {J : Type} [Fintype J] (X : C) (f : J → C) (j : J) :
biproduct.ι _ j ≫ (leftDistributor X f).inv = X ◁ biproduct.ι _ j := by
simp [leftDistributor_inv, Preadditive.comp_sum, ← id_tensor_comp, biproduct.ι_π_assoc, dite_comp]
theorem leftDistributor_assoc {J : Type} [Fintype J] (X Y : C) (f : J → C) :
(asIso (𝟙 X) ⊗ leftDistributor Y f) ≪≫ leftDistributor X _ =
(α_ X Y (⨁ f)).symm ≪≫ leftDistributor (X ⊗ Y) f ≪≫ biproduct.mapIso fun j => α_ X Y _ := by
ext
simp only [Category.comp_id, Category.assoc, eqToHom_refl, Iso.trans_hom, Iso.symm_hom,
asIso_hom, comp_zero, comp_dite, Preadditive.sum_comp, Preadditive.comp_sum, tensor_sum,
id_tensor_comp, tensorIso_hom, leftDistributor_hom, biproduct.mapIso_hom, biproduct.ι_map,
biproduct.ι_π, Finset.sum_dite_irrel, Finset.sum_dite_eq', Finset.sum_const_zero]
simp_rw [← id_tensorHom]
simp only [← id_tensor_comp, biproduct.ι_π]
simp only [id_tensor_comp, tensor_dite, comp_dite]
simp
#align category_theory.left_distributor_assoc CategoryTheory.leftDistributor_assoc
/-- The isomorphism showing how tensor product on the right distributes over direct sums. -/
def rightDistributor {J : Type} [Fintype J] (f : J → C) (X : C) : (⨁ f) ⊗ X ≅ ⨁ fun j => f j ⊗ X :=
(tensorRight X).mapBiproduct f
#align category_theory.right_distributor CategoryTheory.rightDistributor
theorem rightDistributor_hom {J : Type} [Fintype J] (f : J → C) (X : C) :
(rightDistributor f X).hom =
∑ j : J, (biproduct.π f j ▷ X) ≫ biproduct.ι (fun j => f j ⊗ X) j := by
ext
dsimp [rightDistributor, Functor.mapBiproduct, Functor.mapBicone]
erw [biproduct.lift_π]
simp only [Preadditive.sum_comp, Category.assoc, biproduct.ι_π, comp_dite, comp_zero,
Finset.sum_dite_eq', Finset.mem_univ, eqToHom_refl, Category.comp_id, ite_true]
#align category_theory.right_distributor_hom CategoryTheory.rightDistributor_hom
theorem rightDistributor_inv {J : Type} [Fintype J] (f : J → C) (X : C) :
(rightDistributor f X).inv = ∑ j : J, biproduct.π _ j ≫ (biproduct.ι f j ▷ X) := by
ext
dsimp [rightDistributor, Functor.mapBiproduct, Functor.mapBicone]
simp only [biproduct.ι_desc, Preadditive.comp_sum, ne_eq, biproduct.ι_π_assoc, dite_comp,
zero_comp, Finset.sum_dite_eq, Finset.mem_univ, eqToHom_refl, Category.id_comp, ite_true]
#align category_theory.right_distributor_inv CategoryTheory.rightDistributor_inv
@[reassoc (attr := simp)]
theorem rightDistributor_hom_comp_biproduct_π {J : Type} [Fintype J] (f : J → C) (X : C) (j : J) :
(rightDistributor f X).hom ≫ biproduct.π _ j = biproduct.π _ j ▷ X := by
simp [rightDistributor_hom, Preadditive.sum_comp, biproduct.ι_π, comp_dite]
@[reassoc (attr := simp)]
theorem biproduct_ι_comp_rightDistributor_hom {J : Type} [Fintype J] (f : J → C) (X : C) (j : J) :
(biproduct.ι _ j ▷ X) ≫ (rightDistributor f X).hom = biproduct.ι (fun j => f j ⊗ X) j := by
simp [rightDistributor_hom, Preadditive.comp_sum, ← comp_whiskerRight_assoc, biproduct.ι_π,
dite_whiskerRight, dite_comp]
@[reassoc (attr := simp)]
theorem rightDistributor_inv_comp_biproduct_π {J : Type} [Fintype J] (f : J → C) (X : C) (j : J) :
(rightDistributor f X).inv ≫ (biproduct.π _ j ▷ X) = biproduct.π _ j := by
simp [rightDistributor_inv, Preadditive.sum_comp, ← MonoidalCategory.comp_whiskerRight,
biproduct.ι_π, dite_whiskerRight, comp_dite]
@[reassoc (attr := simp)]
theorem biproduct_ι_comp_rightDistributor_inv {J : Type} [Fintype J] (f : J → C) (X : C) (j : J) :
biproduct.ι _ j ≫ (rightDistributor f X).inv = biproduct.ι _ j ▷ X := by
simp [rightDistributor_inv, Preadditive.comp_sum, ← id_tensor_comp, biproduct.ι_π_assoc,
dite_comp]
theorem rightDistributor_assoc {J : Type} [Fintype J] (f : J → C) (X Y : C) :
(rightDistributor f X ⊗ asIso (𝟙 Y)) ≪≫ rightDistributor _ Y =
α_ (⨁ f) X Y ≪≫ rightDistributor f (X ⊗ Y) ≪≫ biproduct.mapIso fun j => (α_ _ X Y).symm := by
ext
simp only [Category.comp_id, Category.assoc, eqToHom_refl, Iso.symm_hom, Iso.trans_hom,
asIso_hom, comp_zero, comp_dite, Preadditive.sum_comp, Preadditive.comp_sum, sum_tensor,
comp_tensor_id, tensorIso_hom, rightDistributor_hom, biproduct.mapIso_hom, biproduct.ι_map,
biproduct.ι_π, Finset.sum_dite_irrel, Finset.sum_dite_eq', Finset.sum_const_zero,
Finset.mem_univ, if_true]
simp_rw [← tensorHom_id]
simp only [← comp_tensor_id, biproduct.ι_π, dite_tensor, comp_dite]
simp
#align category_theory.right_distributor_assoc CategoryTheory.rightDistributor_assoc
theorem leftDistributor_rightDistributor_assoc {J : Type _} [Fintype J]
(X : C) (f : J → C) (Y : C) :
(leftDistributor X f ⊗ asIso (𝟙 Y)) ≪≫ rightDistributor _ Y =
α_ X (⨁ f) Y ≪≫
(asIso (𝟙 X) ⊗ rightDistributor _ Y) ≪≫
leftDistributor X _ ≪≫ biproduct.mapIso fun j => (α_ _ _ _).symm := by
ext
simp only [Category.comp_id, Category.assoc, eqToHom_refl, Iso.symm_hom, Iso.trans_hom,
asIso_hom, comp_zero, comp_dite, Preadditive.sum_comp, Preadditive.comp_sum, sum_tensor,
tensor_sum, comp_tensor_id, tensorIso_hom, leftDistributor_hom, rightDistributor_hom,
biproduct.mapIso_hom, biproduct.ι_map, biproduct.ι_π, Finset.sum_dite_irrel,
Finset.sum_dite_eq', Finset.sum_const_zero, Finset.mem_univ, if_true]
simp_rw [← tensorHom_id, ← id_tensorHom]
simp only [← comp_tensor_id, ← id_tensor_comp_assoc, Category.assoc, biproduct.ι_π, comp_dite,
dite_comp, tensor_dite, dite_tensor]
simp
#align category_theory.left_distributor_right_distributor_assoc CategoryTheory.leftDistributor_rightDistributor_assoc
@[ext]
theorem leftDistributor_ext_left {J : Type} [Fintype J] {X Y : C} {f : J → C} {g h : X ⊗ ⨁ f ⟶ Y}
(w : ∀ j, (X ◁ biproduct.ι f j) ≫ g = (X ◁ biproduct.ι f j) ≫ h) : g = h := by
apply (cancel_epi (leftDistributor X f).inv).mp
ext
simp? [leftDistributor_inv, Preadditive.comp_sum_assoc, biproduct.ι_π_assoc, dite_comp] says
simp only [leftDistributor_inv, Preadditive.comp_sum_assoc, biproduct.ι_π_assoc, dite_comp,
zero_comp, Finset.sum_dite_eq, Finset.mem_univ, ↓reduceIte, eqToHom_refl, Category.id_comp]
apply w
@[ext]
| Mathlib/CategoryTheory/Monoidal/Preadditive.lean | 295 | 304 | theorem leftDistributor_ext_right {J : Type} [Fintype J] {X Y : C} {f : J → C} {g h : X ⟶ Y ⊗ ⨁ f}
(w : ∀ j, g ≫ (Y ◁ biproduct.π f j) = h ≫ (Y ◁ biproduct.π f j)) : g = h := by |
apply (cancel_mono (leftDistributor Y f).hom).mp
ext
simp? [leftDistributor_hom, Preadditive.sum_comp, Preadditive.comp_sum_assoc, biproduct.ι_π,
comp_dite] says
simp only [leftDistributor_hom, Category.assoc, Preadditive.sum_comp, biproduct.ι_π, comp_dite,
comp_zero, Finset.sum_dite_eq', Finset.mem_univ, ↓reduceIte, eqToHom_refl, Category.comp_id]
apply w
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.Algebra.Category.GroupCat.Basic
import Mathlib.CategoryTheory.Limits.Shapes.ZeroObjects
#align_import algebra.category.Group.zero from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# The category of (commutative) (additive) groups has a zero object.
`AddCommGroup` also has zero morphisms. For definitional reasons, we infer this from preadditivity
rather than from the existence of a zero object.
-/
open CategoryTheory
open CategoryTheory.Limits
universe u
namespace GroupCat
@[to_additive]
theorem isZero_of_subsingleton (G : GroupCat) [Subsingleton G] : IsZero G := by
refine ⟨fun X => ⟨⟨⟨1⟩, fun f => ?_⟩⟩, fun X => ⟨⟨⟨1⟩, fun f => ?_⟩⟩⟩
· ext x
have : x = 1 := Subsingleton.elim _ _
rw [this, map_one, map_one]
· ext
apply Subsingleton.elim
set_option linter.uppercaseLean3 false in
#align Group.is_zero_of_subsingleton GroupCat.isZero_of_subsingleton
set_option linter.uppercaseLean3 false in
#align AddGroup.is_zero_of_subsingleton AddGroupCat.isZero_of_subsingleton
@[to_additive AddGroupCat.hasZeroObject]
instance : HasZeroObject GroupCat :=
⟨⟨of PUnit, isZero_of_subsingleton _⟩⟩
end GroupCat
namespace CommGroupCat
@[to_additive]
| Mathlib/Algebra/Category/GroupCat/Zero.lean | 49 | 55 | theorem isZero_of_subsingleton (G : CommGroupCat) [Subsingleton G] : IsZero G := by |
refine ⟨fun X => ⟨⟨⟨1⟩, fun f => ?_⟩⟩, fun X => ⟨⟨⟨1⟩, fun f => ?_⟩⟩⟩
· ext x
have : x = 1 := Subsingleton.elim _ _
rw [this, map_one, map_one]
· ext
apply Subsingleton.elim
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Ken Lee, Chris Hughes
-/
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.Ring.Divisibility.Basic
import Mathlib.Algebra.Ring.Hom.Defs
import Mathlib.GroupTheory.GroupAction.Units
import Mathlib.Logic.Basic
import Mathlib.Tactic.Ring
#align_import ring_theory.coprime.basic from "leanprover-community/mathlib"@"a95b16cbade0f938fc24abd05412bde1e84bab9b"
/-!
# Coprime elements of a ring or monoid
## Main definition
* `IsCoprime x y`: that `x` and `y` are coprime, defined to be the existence of `a` and `b` such
that `a * x + b * y = 1`. Note that elements with no common divisors (`IsRelPrime`) are not
necessarily coprime, e.g., the multivariate polynomials `x₁` and `x₂` are not coprime.
The two notions are equivalent in Bézout rings, see `isRelPrime_iff_isCoprime`.
This file also contains lemmas about `IsRelPrime` parallel to `IsCoprime`.
See also `RingTheory.Coprime.Lemmas` for further development of coprime elements.
-/
universe u v
section CommSemiring
variable {R : Type u} [CommSemiring R] (x y z : R)
/-- The proposition that `x` and `y` are coprime, defined to be the existence of `a` and `b` such
that `a * x + b * y = 1`. Note that elements with no common divisors are not necessarily coprime,
e.g., the multivariate polynomials `x₁` and `x₂` are not coprime. -/
def IsCoprime : Prop :=
∃ a b, a * x + b * y = 1
#align is_coprime IsCoprime
variable {x y z}
@[symm]
theorem IsCoprime.symm (H : IsCoprime x y) : IsCoprime y x :=
let ⟨a, b, H⟩ := H
⟨b, a, by rw [add_comm, H]⟩
#align is_coprime.symm IsCoprime.symm
theorem isCoprime_comm : IsCoprime x y ↔ IsCoprime y x :=
⟨IsCoprime.symm, IsCoprime.symm⟩
#align is_coprime_comm isCoprime_comm
theorem isCoprime_self : IsCoprime x x ↔ IsUnit x :=
⟨fun ⟨a, b, h⟩ => isUnit_of_mul_eq_one x (a + b) <| by rwa [mul_comm, add_mul], fun h =>
let ⟨b, hb⟩ := isUnit_iff_exists_inv'.1 h
⟨b, 0, by rwa [zero_mul, add_zero]⟩⟩
#align is_coprime_self isCoprime_self
theorem isCoprime_zero_left : IsCoprime 0 x ↔ IsUnit x :=
⟨fun ⟨a, b, H⟩ => isUnit_of_mul_eq_one x b <| by rwa [mul_zero, zero_add, mul_comm] at H, fun H =>
let ⟨b, hb⟩ := isUnit_iff_exists_inv'.1 H
⟨1, b, by rwa [one_mul, zero_add]⟩⟩
#align is_coprime_zero_left isCoprime_zero_left
theorem isCoprime_zero_right : IsCoprime x 0 ↔ IsUnit x :=
isCoprime_comm.trans isCoprime_zero_left
#align is_coprime_zero_right isCoprime_zero_right
theorem not_isCoprime_zero_zero [Nontrivial R] : ¬IsCoprime (0 : R) 0 :=
mt isCoprime_zero_right.mp not_isUnit_zero
#align not_coprime_zero_zero not_isCoprime_zero_zero
lemma IsCoprime.intCast {R : Type*} [CommRing R] {a b : ℤ} (h : IsCoprime a b) :
IsCoprime (a : R) (b : R) := by
rcases h with ⟨u, v, H⟩
use u, v
rw_mod_cast [H]
exact Int.cast_one
/-- If a 2-vector `p` satisfies `IsCoprime (p 0) (p 1)`, then `p ≠ 0`. -/
theorem IsCoprime.ne_zero [Nontrivial R] {p : Fin 2 → R} (h : IsCoprime (p 0) (p 1)) : p ≠ 0 := by
rintro rfl
exact not_isCoprime_zero_zero h
#align is_coprime.ne_zero IsCoprime.ne_zero
theorem IsCoprime.ne_zero_or_ne_zero [Nontrivial R] (h : IsCoprime x y) : x ≠ 0 ∨ y ≠ 0 := by
apply not_or_of_imp
rintro rfl rfl
exact not_isCoprime_zero_zero h
theorem isCoprime_one_left : IsCoprime 1 x :=
⟨1, 0, by rw [one_mul, zero_mul, add_zero]⟩
#align is_coprime_one_left isCoprime_one_left
theorem isCoprime_one_right : IsCoprime x 1 :=
⟨0, 1, by rw [one_mul, zero_mul, zero_add]⟩
#align is_coprime_one_right isCoprime_one_right
theorem IsCoprime.dvd_of_dvd_mul_right (H1 : IsCoprime x z) (H2 : x ∣ y * z) : x ∣ y := by
let ⟨a, b, H⟩ := H1
rw [← mul_one y, ← H, mul_add, ← mul_assoc, mul_left_comm]
exact dvd_add (dvd_mul_left _ _) (H2.mul_left _)
#align is_coprime.dvd_of_dvd_mul_right IsCoprime.dvd_of_dvd_mul_right
theorem IsCoprime.dvd_of_dvd_mul_left (H1 : IsCoprime x y) (H2 : x ∣ y * z) : x ∣ z := by
let ⟨a, b, H⟩ := H1
rw [← one_mul z, ← H, add_mul, mul_right_comm, mul_assoc b]
exact dvd_add (dvd_mul_left _ _) (H2.mul_left _)
#align is_coprime.dvd_of_dvd_mul_left IsCoprime.dvd_of_dvd_mul_left
theorem IsCoprime.mul_left (H1 : IsCoprime x z) (H2 : IsCoprime y z) : IsCoprime (x * y) z :=
let ⟨a, b, h1⟩ := H1
let ⟨c, d, h2⟩ := H2
⟨a * c, a * x * d + b * c * y + b * d * z,
calc a * c * (x * y) + (a * x * d + b * c * y + b * d * z) * z
_ = (a * x + b * z) * (c * y + d * z) := by ring
_ = 1 := by rw [h1, h2, mul_one]
⟩
#align is_coprime.mul_left IsCoprime.mul_left
theorem IsCoprime.mul_right (H1 : IsCoprime x y) (H2 : IsCoprime x z) : IsCoprime x (y * z) := by
rw [isCoprime_comm] at H1 H2 ⊢
exact H1.mul_left H2
#align is_coprime.mul_right IsCoprime.mul_right
theorem IsCoprime.mul_dvd (H : IsCoprime x y) (H1 : x ∣ z) (H2 : y ∣ z) : x * y ∣ z := by
obtain ⟨a, b, h⟩ := H
rw [← mul_one z, ← h, mul_add]
apply dvd_add
· rw [mul_comm z, mul_assoc]
exact (mul_dvd_mul_left _ H2).mul_left _
· rw [mul_comm b, ← mul_assoc]
exact (mul_dvd_mul_right H1 _).mul_right _
#align is_coprime.mul_dvd IsCoprime.mul_dvd
theorem IsCoprime.of_mul_left_left (H : IsCoprime (x * y) z) : IsCoprime x z :=
let ⟨a, b, h⟩ := H
⟨a * y, b, by rwa [mul_right_comm, mul_assoc]⟩
#align is_coprime.of_mul_left_left IsCoprime.of_mul_left_left
theorem IsCoprime.of_mul_left_right (H : IsCoprime (x * y) z) : IsCoprime y z := by
rw [mul_comm] at H
exact H.of_mul_left_left
#align is_coprime.of_mul_left_right IsCoprime.of_mul_left_right
theorem IsCoprime.of_mul_right_left (H : IsCoprime x (y * z)) : IsCoprime x y := by
rw [isCoprime_comm] at H ⊢
exact H.of_mul_left_left
#align is_coprime.of_mul_right_left IsCoprime.of_mul_right_left
theorem IsCoprime.of_mul_right_right (H : IsCoprime x (y * z)) : IsCoprime x z := by
rw [mul_comm] at H
exact H.of_mul_right_left
#align is_coprime.of_mul_right_right IsCoprime.of_mul_right_right
theorem IsCoprime.mul_left_iff : IsCoprime (x * y) z ↔ IsCoprime x z ∧ IsCoprime y z :=
⟨fun H => ⟨H.of_mul_left_left, H.of_mul_left_right⟩, fun ⟨H1, H2⟩ => H1.mul_left H2⟩
#align is_coprime.mul_left_iff IsCoprime.mul_left_iff
theorem IsCoprime.mul_right_iff : IsCoprime x (y * z) ↔ IsCoprime x y ∧ IsCoprime x z := by
rw [isCoprime_comm, IsCoprime.mul_left_iff, isCoprime_comm, @isCoprime_comm _ _ z]
#align is_coprime.mul_right_iff IsCoprime.mul_right_iff
theorem IsCoprime.of_isCoprime_of_dvd_left (h : IsCoprime y z) (hdvd : x ∣ y) : IsCoprime x z := by
obtain ⟨d, rfl⟩ := hdvd
exact IsCoprime.of_mul_left_left h
#align is_coprime.of_coprime_of_dvd_left IsCoprime.of_isCoprime_of_dvd_left
theorem IsCoprime.of_isCoprime_of_dvd_right (h : IsCoprime z y) (hdvd : x ∣ y) : IsCoprime z x :=
(h.symm.of_isCoprime_of_dvd_left hdvd).symm
#align is_coprime.of_coprime_of_dvd_right IsCoprime.of_isCoprime_of_dvd_right
theorem IsCoprime.isUnit_of_dvd (H : IsCoprime x y) (d : x ∣ y) : IsUnit x :=
let ⟨k, hk⟩ := d
isCoprime_self.1 <| IsCoprime.of_mul_right_left <| show IsCoprime x (x * k) from hk ▸ H
#align is_coprime.is_unit_of_dvd IsCoprime.isUnit_of_dvd
theorem IsCoprime.isUnit_of_dvd' {a b x : R} (h : IsCoprime a b) (ha : x ∣ a) (hb : x ∣ b) :
IsUnit x :=
(h.of_isCoprime_of_dvd_left ha).isUnit_of_dvd hb
#align is_coprime.is_unit_of_dvd' IsCoprime.isUnit_of_dvd'
theorem IsCoprime.isRelPrime {a b : R} (h : IsCoprime a b) : IsRelPrime a b :=
fun _ ↦ h.isUnit_of_dvd'
theorem IsCoprime.map (H : IsCoprime x y) {S : Type v} [CommSemiring S] (f : R →+* S) :
IsCoprime (f x) (f y) :=
let ⟨a, b, h⟩ := H
⟨f a, f b, by rw [← f.map_mul, ← f.map_mul, ← f.map_add, h, f.map_one]⟩
#align is_coprime.map IsCoprime.map
theorem IsCoprime.of_add_mul_left_left (h : IsCoprime (x + y * z) y) : IsCoprime x y :=
let ⟨a, b, H⟩ := h
⟨a, a * z + b, by
simpa only [add_mul, mul_add, add_assoc, add_comm, add_left_comm, mul_assoc, mul_comm,
mul_left_comm] using H⟩
#align is_coprime.of_add_mul_left_left IsCoprime.of_add_mul_left_left
theorem IsCoprime.of_add_mul_right_left (h : IsCoprime (x + z * y) y) : IsCoprime x y := by
rw [mul_comm] at h
exact h.of_add_mul_left_left
#align is_coprime.of_add_mul_right_left IsCoprime.of_add_mul_right_left
theorem IsCoprime.of_add_mul_left_right (h : IsCoprime x (y + x * z)) : IsCoprime x y := by
rw [isCoprime_comm] at h ⊢
exact h.of_add_mul_left_left
#align is_coprime.of_add_mul_left_right IsCoprime.of_add_mul_left_right
| Mathlib/RingTheory/Coprime/Basic.lean | 212 | 214 | theorem IsCoprime.of_add_mul_right_right (h : IsCoprime x (y + z * x)) : IsCoprime x y := by |
rw [mul_comm] at h
exact h.of_add_mul_left_right
|
/-
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.BaseChange
import Mathlib.Algebra.Lie.Solvable
import Mathlib.Algebra.Lie.Quotient
import Mathlib.Algebra.Lie.Normalizer
import Mathlib.LinearAlgebra.Eigenspace.Basic
import Mathlib.Order.Filter.AtTopBot
import Mathlib.RingTheory.Artinian
import Mathlib.RingTheory.Nilpotent.Lemmas
import Mathlib.Tactic.Monotonicity
#align_import algebra.lie.nilpotent from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1"
/-!
# Nilpotent Lie algebras
Like groups, Lie algebras admit a natural concept of nilpotency. More generally, any Lie module
carries a natural concept of nilpotency. We define these here via the lower central series.
## Main definitions
* `LieModule.lowerCentralSeries`
* `LieModule.IsNilpotent`
## Tags
lie algebra, lower central series, nilpotent
-/
universe u v w w₁ w₂
section NilpotentModules
variable {R : Type u} {L : Type v} {M : Type w}
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
variable (k : ℕ) (N : LieSubmodule R L M)
namespace LieSubmodule
/-- A generalisation of the lower central series. The zeroth term is a specified Lie submodule of
a Lie module. In the case when we specify the top ideal `⊤` of the Lie algebra, regarded as a Lie
module over itself, we get the usual lower central series of a Lie algebra.
It can be more convenient to work with this generalisation when considering the lower central series
of a Lie submodule, regarded as a Lie module in its own right, since it provides a type-theoretic
expression of the fact that the terms of the Lie submodule's lower central series are also Lie
submodules of the enclosing Lie module.
See also `LieSubmodule.lowerCentralSeries_eq_lcs_comap` and
`LieSubmodule.lowerCentralSeries_map_eq_lcs` below, as well as `LieSubmodule.ucs`. -/
def lcs : LieSubmodule R L M → LieSubmodule R L M :=
(fun N => ⁅(⊤ : LieIdeal R L), N⁆)^[k]
#align lie_submodule.lcs LieSubmodule.lcs
@[simp]
theorem lcs_zero (N : LieSubmodule R L M) : N.lcs 0 = N :=
rfl
#align lie_submodule.lcs_zero LieSubmodule.lcs_zero
@[simp]
theorem lcs_succ : N.lcs (k + 1) = ⁅(⊤ : LieIdeal R L), N.lcs k⁆ :=
Function.iterate_succ_apply' (fun N' => ⁅⊤, N'⁆) k N
#align lie_submodule.lcs_succ LieSubmodule.lcs_succ
@[simp]
lemma lcs_sup {N₁ N₂ : LieSubmodule R L M} {k : ℕ} :
(N₁ ⊔ N₂).lcs k = N₁.lcs k ⊔ N₂.lcs k := by
induction' k with k ih
· simp
· simp only [LieSubmodule.lcs_succ, ih, LieSubmodule.lie_sup]
end LieSubmodule
namespace LieModule
variable (R L M)
/-- The lower central series of Lie submodules of a Lie module. -/
def lowerCentralSeries : LieSubmodule R L M :=
(⊤ : LieSubmodule R L M).lcs k
#align lie_module.lower_central_series LieModule.lowerCentralSeries
@[simp]
theorem lowerCentralSeries_zero : lowerCentralSeries R L M 0 = ⊤ :=
rfl
#align lie_module.lower_central_series_zero LieModule.lowerCentralSeries_zero
@[simp]
theorem lowerCentralSeries_succ :
lowerCentralSeries R L M (k + 1) = ⁅(⊤ : LieIdeal R L), lowerCentralSeries R L M k⁆ :=
(⊤ : LieSubmodule R L M).lcs_succ k
#align lie_module.lower_central_series_succ LieModule.lowerCentralSeries_succ
end LieModule
namespace LieSubmodule
open LieModule
theorem lcs_le_self : N.lcs k ≤ N := by
induction' k with k ih
· simp
· simp only [lcs_succ]
exact (LieSubmodule.mono_lie_right _ _ ⊤ ih).trans (N.lie_le_right ⊤)
#align lie_submodule.lcs_le_self LieSubmodule.lcs_le_self
theorem lowerCentralSeries_eq_lcs_comap : lowerCentralSeries R L N k = (N.lcs k).comap N.incl := by
induction' k with k ih
· simp
· simp only [lcs_succ, lowerCentralSeries_succ] at ih ⊢
have : N.lcs k ≤ N.incl.range := by
rw [N.range_incl]
apply lcs_le_self
rw [ih, LieSubmodule.comap_bracket_eq _ _ N.incl N.ker_incl this]
#align lie_submodule.lower_central_series_eq_lcs_comap LieSubmodule.lowerCentralSeries_eq_lcs_comap
theorem lowerCentralSeries_map_eq_lcs : (lowerCentralSeries R L N k).map N.incl = N.lcs k := by
rw [lowerCentralSeries_eq_lcs_comap, LieSubmodule.map_comap_incl, inf_eq_right]
apply lcs_le_self
#align lie_submodule.lower_central_series_map_eq_lcs LieSubmodule.lowerCentralSeries_map_eq_lcs
end LieSubmodule
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
variable (R L M)
theorem antitone_lowerCentralSeries : Antitone <| lowerCentralSeries R L M := by
intro l k
induction' k with k ih generalizing l <;> intro h
· exact (Nat.le_zero.mp h).symm ▸ le_rfl
· rcases Nat.of_le_succ h with (hk | hk)
· rw [lowerCentralSeries_succ]
exact (LieSubmodule.mono_lie_right _ _ ⊤ (ih hk)).trans (LieSubmodule.lie_le_right _ _)
· exact hk.symm ▸ le_rfl
#align lie_module.antitone_lower_central_series LieModule.antitone_lowerCentralSeries
theorem eventually_iInf_lowerCentralSeries_eq [IsArtinian R M] :
∀ᶠ l in Filter.atTop, ⨅ k, lowerCentralSeries R L M k = lowerCentralSeries R L M l := by
have h_wf : WellFounded ((· > ·) : (LieSubmodule R L M)ᵒᵈ → (LieSubmodule R L M)ᵒᵈ → Prop) :=
LieSubmodule.wellFounded_of_isArtinian R L M
obtain ⟨n, hn : ∀ m, n ≤ m → lowerCentralSeries R L M n = lowerCentralSeries R L M m⟩ :=
WellFounded.monotone_chain_condition.mp h_wf ⟨_, antitone_lowerCentralSeries R L M⟩
refine Filter.eventually_atTop.mpr ⟨n, fun l hl ↦ le_antisymm (iInf_le _ _) (le_iInf fun m ↦ ?_)⟩
rcases le_or_lt l m with h | h
· rw [← hn _ hl, ← hn _ (hl.trans h)]
· exact antitone_lowerCentralSeries R L M (le_of_lt h)
theorem trivial_iff_lower_central_eq_bot : IsTrivial L M ↔ lowerCentralSeries R L M 1 = ⊥ := by
constructor <;> intro h
· erw [eq_bot_iff, LieSubmodule.lieSpan_le]; rintro m ⟨x, n, hn⟩; rw [← hn, h.trivial]; simp
· rw [LieSubmodule.eq_bot_iff] at h; apply IsTrivial.mk; intro x m; apply h
apply LieSubmodule.subset_lieSpan
-- Porting note: was `use x, m; rfl`
simp only [LieSubmodule.top_coe, Subtype.exists, LieSubmodule.mem_top, exists_prop, true_and,
Set.mem_setOf]
exact ⟨x, m, rfl⟩
#align lie_module.trivial_iff_lower_central_eq_bot LieModule.trivial_iff_lower_central_eq_bot
theorem iterate_toEnd_mem_lowerCentralSeries (x : L) (m : M) (k : ℕ) :
(toEnd R L M x)^[k] m ∈ lowerCentralSeries R L M k := by
induction' k with k ih
· simp only [Nat.zero_eq, Function.iterate_zero, lowerCentralSeries_zero, LieSubmodule.mem_top]
· simp only [lowerCentralSeries_succ, Function.comp_apply, Function.iterate_succ',
toEnd_apply_apply]
exact LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top x) ih
#align lie_module.iterate_to_endomorphism_mem_lower_central_series LieModule.iterate_toEnd_mem_lowerCentralSeries
theorem iterate_toEnd_mem_lowerCentralSeries₂ (x y : L) (m : M) (k : ℕ) :
(toEnd R L M x ∘ₗ toEnd R L M y)^[k] m ∈
lowerCentralSeries R L M (2 * k) := by
induction' k with k ih
· simp
have hk : 2 * k.succ = (2 * k + 1) + 1 := rfl
simp only [lowerCentralSeries_succ, Function.comp_apply, Function.iterate_succ', hk,
toEnd_apply_apply, LinearMap.coe_comp, toEnd_apply_apply]
refine LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top x) ?_
exact LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top y) ih
variable {R L M}
theorem map_lowerCentralSeries_le (f : M →ₗ⁅R,L⁆ M₂) :
(lowerCentralSeries R L M k).map f ≤ lowerCentralSeries R L M₂ k := by
induction' k with k ih
· simp only [Nat.zero_eq, lowerCentralSeries_zero, le_top]
· simp only [LieModule.lowerCentralSeries_succ, LieSubmodule.map_bracket_eq]
exact LieSubmodule.mono_lie_right _ _ ⊤ ih
#align lie_module.map_lower_central_series_le LieModule.map_lowerCentralSeries_le
lemma map_lowerCentralSeries_eq {f : M →ₗ⁅R,L⁆ M₂} (hf : Function.Surjective f) :
(lowerCentralSeries R L M k).map f = lowerCentralSeries R L M₂ k := by
apply le_antisymm (map_lowerCentralSeries_le k f)
induction' k with k ih
· rwa [lowerCentralSeries_zero, lowerCentralSeries_zero, top_le_iff, f.map_top, f.range_eq_top]
· simp only [lowerCentralSeries_succ, LieSubmodule.map_bracket_eq]
apply LieSubmodule.mono_lie_right
assumption
variable (R L M)
open LieAlgebra
theorem derivedSeries_le_lowerCentralSeries (k : ℕ) :
derivedSeries R L k ≤ lowerCentralSeries R L L k := by
induction' k with k h
· rw [derivedSeries_def, derivedSeriesOfIdeal_zero, lowerCentralSeries_zero]
· have h' : derivedSeries R L k ≤ ⊤ := by simp only [le_top]
rw [derivedSeries_def, derivedSeriesOfIdeal_succ, lowerCentralSeries_succ]
exact LieSubmodule.mono_lie _ _ _ _ h' h
#align lie_module.derived_series_le_lower_central_series LieModule.derivedSeries_le_lowerCentralSeries
/-- A Lie module is nilpotent if its lower central series reaches 0 (in a finite number of
steps). -/
class IsNilpotent : Prop where
nilpotent : ∃ k, lowerCentralSeries R L M k = ⊥
#align lie_module.is_nilpotent LieModule.IsNilpotent
theorem exists_lowerCentralSeries_eq_bot_of_isNilpotent [IsNilpotent R L M] :
∃ k, lowerCentralSeries R L M k = ⊥ :=
IsNilpotent.nilpotent
@[simp] lemma iInf_lowerCentralSeries_eq_bot_of_isNilpotent [IsNilpotent R L M] :
⨅ k, lowerCentralSeries R L M k = ⊥ := by
obtain ⟨k, hk⟩ := exists_lowerCentralSeries_eq_bot_of_isNilpotent R L M
rw [eq_bot_iff, ← hk]
exact iInf_le _ _
/-- See also `LieModule.isNilpotent_iff_exists_ucs_eq_top`. -/
theorem isNilpotent_iff : IsNilpotent R L M ↔ ∃ k, lowerCentralSeries R L M k = ⊥ :=
⟨fun h => h.nilpotent, fun h => ⟨h⟩⟩
#align lie_module.is_nilpotent_iff LieModule.isNilpotent_iff
variable {R L M}
theorem _root_.LieSubmodule.isNilpotent_iff_exists_lcs_eq_bot (N : LieSubmodule R L M) :
LieModule.IsNilpotent R L N ↔ ∃ k, N.lcs k = ⊥ := by
rw [isNilpotent_iff]
refine exists_congr fun k => ?_
rw [N.lowerCentralSeries_eq_lcs_comap k, LieSubmodule.comap_incl_eq_bot,
inf_eq_right.mpr (N.lcs_le_self k)]
#align lie_submodule.is_nilpotent_iff_exists_lcs_eq_bot LieSubmodule.isNilpotent_iff_exists_lcs_eq_bot
variable (R L M)
instance (priority := 100) trivialIsNilpotent [IsTrivial L M] : IsNilpotent R L M :=
⟨by use 1; change ⁅⊤, ⊤⁆ = ⊥; simp⟩
#align lie_module.trivial_is_nilpotent LieModule.trivialIsNilpotent
theorem exists_forall_pow_toEnd_eq_zero [hM : IsNilpotent R L M] :
∃ k : ℕ, ∀ x : L, toEnd R L M x ^ k = 0 := by
obtain ⟨k, hM⟩ := hM
use k
intro x; ext m
rw [LinearMap.pow_apply, LinearMap.zero_apply, ← @LieSubmodule.mem_bot R L M, ← hM]
exact iterate_toEnd_mem_lowerCentralSeries R L M x m k
#align lie_module.nilpotent_endo_of_nilpotent_module LieModule.exists_forall_pow_toEnd_eq_zero
theorem isNilpotent_toEnd_of_isNilpotent [IsNilpotent R L M] (x : L) :
_root_.IsNilpotent (toEnd R L M x) := by
change ∃ k, toEnd R L M x ^ k = 0
have := exists_forall_pow_toEnd_eq_zero R L M
tauto
theorem isNilpotent_toEnd_of_isNilpotent₂ [IsNilpotent R L M] (x y : L) :
_root_.IsNilpotent (toEnd R L M x ∘ₗ toEnd R L M y) := by
obtain ⟨k, hM⟩ := exists_lowerCentralSeries_eq_bot_of_isNilpotent R L M
replace hM : lowerCentralSeries R L M (2 * k) = ⊥ := by
rw [eq_bot_iff, ← hM]; exact antitone_lowerCentralSeries R L M (by omega)
use k
ext m
rw [LinearMap.pow_apply, LinearMap.zero_apply, ← LieSubmodule.mem_bot (R := R) (L := L), ← hM]
exact iterate_toEnd_mem_lowerCentralSeries₂ R L M x y m k
@[simp] lemma maxGenEigenSpace_toEnd_eq_top [IsNilpotent R L M] (x : L) :
((toEnd R L M x).maxGenEigenspace 0) = ⊤ := by
ext m
simp only [Module.End.mem_maxGenEigenspace, zero_smul, sub_zero, Submodule.mem_top,
iff_true]
obtain ⟨k, hk⟩ := exists_forall_pow_toEnd_eq_zero R L M
exact ⟨k, by simp [hk x]⟩
/-- If the quotient of a Lie module `M` by a Lie submodule on which the Lie algebra acts trivially
is nilpotent then `M` is nilpotent.
This is essentially the Lie module equivalent of the fact that a central
extension of nilpotent Lie algebras is nilpotent. See `LieAlgebra.nilpotent_of_nilpotent_quotient`
below for the corresponding result for Lie algebras. -/
theorem nilpotentOfNilpotentQuotient {N : LieSubmodule R L M} (h₁ : N ≤ maxTrivSubmodule R L M)
(h₂ : IsNilpotent R L (M ⧸ N)) : IsNilpotent R L M := by
obtain ⟨k, hk⟩ := h₂
use k + 1
simp only [lowerCentralSeries_succ]
suffices lowerCentralSeries R L M k ≤ N by
replace this := LieSubmodule.mono_lie_right _ _ ⊤ (le_trans this h₁)
rwa [ideal_oper_maxTrivSubmodule_eq_bot, le_bot_iff] at this
rw [← LieSubmodule.Quotient.map_mk'_eq_bot_le, ← le_bot_iff, ← hk]
exact map_lowerCentralSeries_le k (LieSubmodule.Quotient.mk' N)
#align lie_module.nilpotent_of_nilpotent_quotient LieModule.nilpotentOfNilpotentQuotient
theorem isNilpotent_quotient_iff :
IsNilpotent R L (M ⧸ N) ↔ ∃ k, lowerCentralSeries R L M k ≤ N := by
rw [LieModule.isNilpotent_iff]
refine exists_congr fun k ↦ ?_
rw [← LieSubmodule.Quotient.map_mk'_eq_bot_le, map_lowerCentralSeries_eq k
(LieSubmodule.Quotient.surjective_mk' N)]
theorem iInf_lcs_le_of_isNilpotent_quot (h : IsNilpotent R L (M ⧸ N)) :
⨅ k, lowerCentralSeries R L M k ≤ N := by
obtain ⟨k, hk⟩ := (isNilpotent_quotient_iff R L M N).mp h
exact iInf_le_of_le k hk
/-- Given a nilpotent Lie module `M` with lower central series `M = C₀ ≥ C₁ ≥ ⋯ ≥ Cₖ = ⊥`, this is
the natural number `k` (the number of inclusions).
For a non-nilpotent module, we use the junk value 0. -/
noncomputable def nilpotencyLength : ℕ :=
sInf {k | lowerCentralSeries R L M k = ⊥}
#align lie_module.nilpotency_length LieModule.nilpotencyLength
@[simp]
theorem nilpotencyLength_eq_zero_iff [IsNilpotent R L M] :
nilpotencyLength R L M = 0 ↔ Subsingleton M := by
let s := {k | lowerCentralSeries R L M k = ⊥}
have hs : s.Nonempty := by
obtain ⟨k, hk⟩ := (by infer_instance : IsNilpotent R L M)
exact ⟨k, hk⟩
change sInf s = 0 ↔ _
rw [← LieSubmodule.subsingleton_iff R L M, ← subsingleton_iff_bot_eq_top, ←
lowerCentralSeries_zero, @eq_comm (LieSubmodule R L M)]
refine ⟨fun h => h ▸ Nat.sInf_mem hs, fun h => ?_⟩
rw [Nat.sInf_eq_zero]
exact Or.inl h
#align lie_module.nilpotency_length_eq_zero_iff LieModule.nilpotencyLength_eq_zero_iff
theorem nilpotencyLength_eq_succ_iff (k : ℕ) :
nilpotencyLength R L M = k + 1 ↔
lowerCentralSeries R L M (k + 1) = ⊥ ∧ lowerCentralSeries R L M k ≠ ⊥ := by
let s := {k | lowerCentralSeries R L M k = ⊥}
change sInf s = k + 1 ↔ k + 1 ∈ s ∧ k ∉ s
have hs : ∀ k₁ k₂, k₁ ≤ k₂ → k₁ ∈ s → k₂ ∈ s := by
rintro k₁ k₂ h₁₂ (h₁ : lowerCentralSeries R L M k₁ = ⊥)
exact eq_bot_iff.mpr (h₁ ▸ antitone_lowerCentralSeries R L M h₁₂)
exact Nat.sInf_upward_closed_eq_succ_iff hs k
#align lie_module.nilpotency_length_eq_succ_iff LieModule.nilpotencyLength_eq_succ_iff
@[simp]
theorem nilpotencyLength_eq_one_iff [Nontrivial M] :
nilpotencyLength R L M = 1 ↔ IsTrivial L M := by
rw [nilpotencyLength_eq_succ_iff, ← trivial_iff_lower_central_eq_bot]
simp
theorem isTrivial_of_nilpotencyLength_le_one [IsNilpotent R L M] (h : nilpotencyLength R L M ≤ 1) :
IsTrivial L M := by
nontriviality M
cases' Nat.le_one_iff_eq_zero_or_eq_one.mp h with h h
· rw [nilpotencyLength_eq_zero_iff] at h; infer_instance
· rwa [nilpotencyLength_eq_one_iff] at h
/-- Given a non-trivial nilpotent Lie module `M` with lower central series
`M = C₀ ≥ C₁ ≥ ⋯ ≥ Cₖ = ⊥`, this is the `k-1`th term in the lower central series (the last
non-trivial term).
For a trivial or non-nilpotent module, this is the bottom submodule, `⊥`. -/
noncomputable def lowerCentralSeriesLast : LieSubmodule R L M :=
match nilpotencyLength R L M with
| 0 => ⊥
| k + 1 => lowerCentralSeries R L M k
#align lie_module.lower_central_series_last LieModule.lowerCentralSeriesLast
theorem lowerCentralSeriesLast_le_max_triv :
lowerCentralSeriesLast R L M ≤ maxTrivSubmodule R L M := by
rw [lowerCentralSeriesLast]
cases' h : nilpotencyLength R L M with k
· exact bot_le
· rw [le_max_triv_iff_bracket_eq_bot]
rw [nilpotencyLength_eq_succ_iff, lowerCentralSeries_succ] at h
exact h.1
#align lie_module.lower_central_series_last_le_max_triv LieModule.lowerCentralSeriesLast_le_max_triv
theorem nontrivial_lowerCentralSeriesLast [Nontrivial M] [IsNilpotent R L M] :
Nontrivial (lowerCentralSeriesLast R L M) := by
rw [LieSubmodule.nontrivial_iff_ne_bot, lowerCentralSeriesLast]
cases h : nilpotencyLength R L M
· rw [nilpotencyLength_eq_zero_iff, ← not_nontrivial_iff_subsingleton] at h
contradiction
· rw [nilpotencyLength_eq_succ_iff] at h
exact h.2
#align lie_module.nontrivial_lower_central_series_last LieModule.nontrivial_lowerCentralSeriesLast
theorem lowerCentralSeriesLast_le_of_not_isTrivial [IsNilpotent R L M] (h : ¬ IsTrivial L M) :
lowerCentralSeriesLast R L M ≤ lowerCentralSeries R L M 1 := by
rw [lowerCentralSeriesLast]
replace h : 1 < nilpotencyLength R L M := by
by_contra contra
have := isTrivial_of_nilpotencyLength_le_one R L M (not_lt.mp contra)
contradiction
cases' hk : nilpotencyLength R L M with k <;> rw [hk] at h
· contradiction
· exact antitone_lowerCentralSeries _ _ _ (Nat.lt_succ.mp h)
/-- For a nilpotent Lie module `M` of a Lie algebra `L`, the first term in the lower central series
of `M` contains a non-zero element on which `L` acts trivially unless the entire action is trivial.
Taking `M = L`, this provides a useful characterisation of Abelian-ness for nilpotent Lie
algebras. -/
lemma disjoint_lowerCentralSeries_maxTrivSubmodule_iff [IsNilpotent R L M] :
Disjoint (lowerCentralSeries R L M 1) (maxTrivSubmodule R L M) ↔ IsTrivial L M := by
refine ⟨fun h ↦ ?_, fun h ↦ by simp⟩
nontriviality M
by_contra contra
have : lowerCentralSeriesLast R L M ≤ lowerCentralSeries R L M 1 ⊓ maxTrivSubmodule R L M :=
le_inf_iff.mpr ⟨lowerCentralSeriesLast_le_of_not_isTrivial R L M contra,
lowerCentralSeriesLast_le_max_triv R L M⟩
suffices ¬ Nontrivial (lowerCentralSeriesLast R L M) by
exact this (nontrivial_lowerCentralSeriesLast R L M)
rw [h.eq_bot, le_bot_iff] at this
exact this ▸ not_nontrivial _
theorem nontrivial_max_triv_of_isNilpotent [Nontrivial M] [IsNilpotent R L M] :
Nontrivial (maxTrivSubmodule R L M) :=
Set.nontrivial_mono (lowerCentralSeriesLast_le_max_triv R L M)
(nontrivial_lowerCentralSeriesLast R L M)
#align lie_module.nontrivial_max_triv_of_is_nilpotent LieModule.nontrivial_max_triv_of_isNilpotent
@[simp]
theorem coe_lcs_range_toEnd_eq (k : ℕ) :
(lowerCentralSeries R (toEnd R L M).range M k : Submodule R M) =
lowerCentralSeries R L M k := by
induction' k with k ih
· simp
· simp only [lowerCentralSeries_succ, LieSubmodule.lieIdeal_oper_eq_linear_span', ←
(lowerCentralSeries R (toEnd R L M).range M k).mem_coeSubmodule, ih]
congr
ext m
constructor
· rintro ⟨⟨-, ⟨y, rfl⟩⟩, -, n, hn, rfl⟩
exact ⟨y, LieSubmodule.mem_top _, n, hn, rfl⟩
· rintro ⟨x, -, n, hn, rfl⟩
exact
⟨⟨toEnd R L M x, LieHom.mem_range_self _ x⟩, LieSubmodule.mem_top _, n, hn, rfl⟩
#align lie_module.coe_lcs_range_to_endomorphism_eq LieModule.coe_lcs_range_toEnd_eq
@[simp]
theorem isNilpotent_range_toEnd_iff :
IsNilpotent R (toEnd R L M).range M ↔ IsNilpotent R L M := by
constructor <;> rintro ⟨k, hk⟩ <;> use k <;>
rw [← LieSubmodule.coe_toSubmodule_eq_iff] at hk ⊢ <;>
simpa using hk
#align lie_module.is_nilpotent_range_to_endomorphism_iff LieModule.isNilpotent_range_toEnd_iff
end LieModule
namespace LieSubmodule
variable {N₁ N₂ : LieSubmodule R L M}
/-- The upper (aka ascending) central series.
See also `LieSubmodule.lcs`. -/
def ucs (k : ℕ) : LieSubmodule R L M → LieSubmodule R L M :=
normalizer^[k]
#align lie_submodule.ucs LieSubmodule.ucs
@[simp]
theorem ucs_zero : N.ucs 0 = N :=
rfl
#align lie_submodule.ucs_zero LieSubmodule.ucs_zero
@[simp]
theorem ucs_succ (k : ℕ) : N.ucs (k + 1) = (N.ucs k).normalizer :=
Function.iterate_succ_apply' normalizer k N
#align lie_submodule.ucs_succ LieSubmodule.ucs_succ
theorem ucs_add (k l : ℕ) : N.ucs (k + l) = (N.ucs l).ucs k :=
Function.iterate_add_apply normalizer k l N
#align lie_submodule.ucs_add LieSubmodule.ucs_add
@[mono]
theorem ucs_mono (k : ℕ) (h : N₁ ≤ N₂) : N₁.ucs k ≤ N₂.ucs k := by
induction' k with k ih
· simpa
simp only [ucs_succ]
-- Porting note: `mono` makes no progress
apply monotone_normalizer ih
#align lie_submodule.ucs_mono LieSubmodule.ucs_mono
theorem ucs_eq_self_of_normalizer_eq_self (h : N₁.normalizer = N₁) (k : ℕ) : N₁.ucs k = N₁ := by
induction' k with k ih
· simp
· rwa [ucs_succ, ih]
#align lie_submodule.ucs_eq_self_of_normalizer_eq_self LieSubmodule.ucs_eq_self_of_normalizer_eq_self
/-- If a Lie module `M` contains a self-normalizing Lie submodule `N`, then all terms of the upper
central series of `M` are contained in `N`.
An important instance of this situation arises from a Cartan subalgebra `H ⊆ L` with the roles of
`L`, `M`, `N` played by `H`, `L`, `H`, respectively. -/
theorem ucs_le_of_normalizer_eq_self (h : N₁.normalizer = N₁) (k : ℕ) :
(⊥ : LieSubmodule R L M).ucs k ≤ N₁ := by
rw [← ucs_eq_self_of_normalizer_eq_self h k]
mono
simp
#align lie_submodule.ucs_le_of_normalizer_eq_self LieSubmodule.ucs_le_of_normalizer_eq_self
theorem lcs_add_le_iff (l k : ℕ) : N₁.lcs (l + k) ≤ N₂ ↔ N₁.lcs l ≤ N₂.ucs k := by
induction' k with k ih generalizing l
· simp
rw [(by abel : l + (k + 1) = l + 1 + k), ih, ucs_succ, lcs_succ, top_lie_le_iff_le_normalizer]
#align lie_submodule.lcs_add_le_iff LieSubmodule.lcs_add_le_iff
theorem lcs_le_iff (k : ℕ) : N₁.lcs k ≤ N₂ ↔ N₁ ≤ N₂.ucs k := by
-- Porting note: `convert` needed type annotations
convert lcs_add_le_iff (R := R) (L := L) (M := M) 0 k
rw [zero_add]
#align lie_submodule.lcs_le_iff LieSubmodule.lcs_le_iff
theorem gc_lcs_ucs (k : ℕ) :
GaloisConnection (fun N : LieSubmodule R L M => N.lcs k) fun N : LieSubmodule R L M =>
N.ucs k :=
fun _ _ => lcs_le_iff k
#align lie_submodule.gc_lcs_ucs LieSubmodule.gc_lcs_ucs
theorem ucs_eq_top_iff (k : ℕ) : N.ucs k = ⊤ ↔ LieModule.lowerCentralSeries R L M k ≤ N := by
rw [eq_top_iff, ← lcs_le_iff]; rfl
#align lie_submodule.ucs_eq_top_iff LieSubmodule.ucs_eq_top_iff
theorem _root_.LieModule.isNilpotent_iff_exists_ucs_eq_top :
LieModule.IsNilpotent R L M ↔ ∃ k, (⊥ : LieSubmodule R L M).ucs k = ⊤ := by
rw [LieModule.isNilpotent_iff]; exact exists_congr fun k => by simp [ucs_eq_top_iff]
#align lie_module.is_nilpotent_iff_exists_ucs_eq_top LieModule.isNilpotent_iff_exists_ucs_eq_top
theorem ucs_comap_incl (k : ℕ) :
((⊥ : LieSubmodule R L M).ucs k).comap N.incl = (⊥ : LieSubmodule R L N).ucs k := by
induction' k with k ih
· exact N.ker_incl
· simp [← ih]
#align lie_submodule.ucs_comap_incl LieSubmodule.ucs_comap_incl
theorem isNilpotent_iff_exists_self_le_ucs :
LieModule.IsNilpotent R L N ↔ ∃ k, N ≤ (⊥ : LieSubmodule R L M).ucs k := by
simp_rw [LieModule.isNilpotent_iff_exists_ucs_eq_top, ← ucs_comap_incl, comap_incl_eq_top]
#align lie_submodule.is_nilpotent_iff_exists_self_le_ucs LieSubmodule.isNilpotent_iff_exists_self_le_ucs
theorem ucs_bot_one : (⊥ : LieSubmodule R L M).ucs 1 = LieModule.maxTrivSubmodule R L M := by
simp [LieSubmodule.normalizer_bot_eq_maxTrivSubmodule]
end LieSubmodule
section Morphisms
open LieModule Function
variable {L₂ M₂ : Type*} [LieRing L₂] [LieAlgebra R L₂]
variable [AddCommGroup M₂] [Module R M₂] [LieRingModule L₂ M₂] [LieModule R L₂ M₂]
variable {f : L →ₗ⁅R⁆ L₂} {g : M →ₗ[R] M₂}
variable (hf : Surjective f) (hg : Surjective g) (hfg : ∀ x m, ⁅f x, g m⁆ = g ⁅x, m⁆)
theorem Function.Surjective.lieModule_lcs_map_eq (k : ℕ) :
(lowerCentralSeries R L M k : Submodule R M).map g = lowerCentralSeries R L₂ M₂ k := by
induction' k with k ih
· simpa [LinearMap.range_eq_top]
· suffices
g '' {m | ∃ (x : L) (n : _), n ∈ lowerCentralSeries R L M k ∧ ⁅x, n⁆ = m} =
{m | ∃ (x : L₂) (n : _), n ∈ lowerCentralSeries R L M k ∧ ⁅x, g n⁆ = m} by
simp only [← LieSubmodule.mem_coeSubmodule] at this
-- Porting note: was
-- simp [← LieSubmodule.mem_coeSubmodule, ← ih, LieSubmodule.lieIdeal_oper_eq_linear_span',
-- Submodule.map_span, -Submodule.span_image, this,
-- -LieSubmodule.mem_coeSubmodule]
simp_rw [lowerCentralSeries_succ, LieSubmodule.lieIdeal_oper_eq_linear_span',
Submodule.map_span, LieSubmodule.mem_top, true_and, ← LieSubmodule.mem_coeSubmodule, this,
← ih, Submodule.mem_map, exists_exists_and_eq_and]
ext m₂
constructor
· rintro ⟨m, ⟨x, n, hn, rfl⟩, rfl⟩
exact ⟨f x, n, hn, hfg x n⟩
· rintro ⟨x, n, hn, rfl⟩
obtain ⟨y, rfl⟩ := hf x
exact ⟨⁅y, n⁆, ⟨y, n, hn, rfl⟩, (hfg y n).symm⟩
#align function.surjective.lie_module_lcs_map_eq Function.Surjective.lieModule_lcs_map_eq
theorem Function.Surjective.lieModuleIsNilpotent [IsNilpotent R L M] : IsNilpotent R L₂ M₂ := by
obtain ⟨k, hk⟩ := id (by infer_instance : IsNilpotent R L M)
use k
rw [← LieSubmodule.coe_toSubmodule_eq_iff] at hk ⊢
simp [← hf.lieModule_lcs_map_eq hg hfg k, hk]
#align function.surjective.lie_module_is_nilpotent Function.Surjective.lieModuleIsNilpotent
theorem Equiv.lieModule_isNilpotent_iff (f : L ≃ₗ⁅R⁆ L₂) (g : M ≃ₗ[R] M₂)
(hfg : ∀ x m, ⁅f x, g m⁆ = g ⁅x, m⁆) : IsNilpotent R L M ↔ IsNilpotent R L₂ M₂ := by
constructor <;> intro h
· have hg : Surjective (g : M →ₗ[R] M₂) := g.surjective
exact f.surjective.lieModuleIsNilpotent hg hfg
· have hg : Surjective (g.symm : M₂ →ₗ[R] M) := g.symm.surjective
refine f.symm.surjective.lieModuleIsNilpotent hg fun x m => ?_
rw [LinearEquiv.coe_coe, LieEquiv.coe_to_lieHom, ← g.symm_apply_apply ⁅f.symm x, g.symm m⁆, ←
hfg, f.apply_symm_apply, g.apply_symm_apply]
#align equiv.lie_module_is_nilpotent_iff Equiv.lieModule_isNilpotent_iff
@[simp]
theorem LieModule.isNilpotent_of_top_iff :
IsNilpotent R (⊤ : LieSubalgebra R L) M ↔ IsNilpotent R L M :=
Equiv.lieModule_isNilpotent_iff LieSubalgebra.topEquiv (1 : M ≃ₗ[R] M) fun _ _ => rfl
#align lie_module.is_nilpotent_of_top_iff LieModule.isNilpotent_of_top_iff
@[simp] lemma LieModule.isNilpotent_of_top_iff' :
IsNilpotent R L {x // x ∈ (⊤ : LieSubmodule R L M)} ↔ IsNilpotent R L M :=
Equiv.lieModule_isNilpotent_iff 1 (LinearEquiv.ofTop ⊤ rfl) fun _ _ ↦ rfl
end Morphisms
end NilpotentModules
instance (priority := 100) LieAlgebra.isSolvable_of_isNilpotent (R : Type u) (L : Type v)
[CommRing R] [LieRing L] [LieAlgebra R L] [hL : LieModule.IsNilpotent R L L] :
LieAlgebra.IsSolvable R L := by
obtain ⟨k, h⟩ : ∃ k, LieModule.lowerCentralSeries R L L k = ⊥ := hL.nilpotent
use k; rw [← le_bot_iff] at h ⊢
exact le_trans (LieModule.derivedSeries_le_lowerCentralSeries R L k) h
#align lie_algebra.is_solvable_of_is_nilpotent LieAlgebra.isSolvable_of_isNilpotent
section NilpotentAlgebras
variable (R : Type u) (L : Type v) (L' : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [LieRing L'] [LieAlgebra R L']
/-- We say a Lie algebra is nilpotent when it is nilpotent as a Lie module over itself via the
adjoint representation. -/
abbrev LieAlgebra.IsNilpotent (R : Type u) (L : Type v) [CommRing R] [LieRing L] [LieAlgebra R L] :
Prop :=
LieModule.IsNilpotent R L L
#align lie_algebra.is_nilpotent LieAlgebra.IsNilpotent
open LieAlgebra
theorem LieAlgebra.nilpotent_ad_of_nilpotent_algebra [IsNilpotent R L] :
∃ k : ℕ, ∀ x : L, ad R L x ^ k = 0 :=
LieModule.exists_forall_pow_toEnd_eq_zero R L L
#align lie_algebra.nilpotent_ad_of_nilpotent_algebra LieAlgebra.nilpotent_ad_of_nilpotent_algebra
-- TODO Generalise the below to Lie modules if / when we define morphisms, equivs of Lie modules
-- covering a Lie algebra morphism of (possibly different) Lie algebras.
variable {R L L'}
open LieModule (lowerCentralSeries)
/-- Given an ideal `I` of a Lie algebra `L`, the lower central series of `L ⧸ I` is the same
whether we regard `L ⧸ I` as an `L` module or an `L ⧸ I` module.
TODO: This result obviously generalises but the generalisation requires the missing definition of
morphisms between Lie modules over different Lie algebras. -/
-- Porting note: added `LieSubmodule.toSubmodule` in the statement
theorem coe_lowerCentralSeries_ideal_quot_eq {I : LieIdeal R L} (k : ℕ) :
LieSubmodule.toSubmodule (lowerCentralSeries R L (L ⧸ I) k) =
LieSubmodule.toSubmodule (lowerCentralSeries R (L ⧸ I) (L ⧸ I) k) := by
induction' k with k ih
· simp only [Nat.zero_eq, LieModule.lowerCentralSeries_zero, LieSubmodule.top_coeSubmodule,
LieIdeal.top_coe_lieSubalgebra, LieSubalgebra.top_coe_submodule]
· simp only [LieModule.lowerCentralSeries_succ, LieSubmodule.lieIdeal_oper_eq_linear_span]
congr
ext x
constructor
· rintro ⟨⟨y, -⟩, ⟨z, hz⟩, rfl : ⁅y, z⁆ = x⟩
erw [← LieSubmodule.mem_coeSubmodule, ih, LieSubmodule.mem_coeSubmodule] at hz
exact ⟨⟨LieSubmodule.Quotient.mk y, LieSubmodule.mem_top _⟩, ⟨z, hz⟩, rfl⟩
· rintro ⟨⟨⟨y⟩, -⟩, ⟨z, hz⟩, rfl : ⁅y, z⁆ = x⟩
erw [← LieSubmodule.mem_coeSubmodule, ← ih, LieSubmodule.mem_coeSubmodule] at hz
exact ⟨⟨y, LieSubmodule.mem_top _⟩, ⟨z, hz⟩, rfl⟩
#align coe_lower_central_series_ideal_quot_eq coe_lowerCentralSeries_ideal_quot_eq
/-- Note that the below inequality can be strict. For example the ideal of strictly-upper-triangular
2x2 matrices inside the Lie algebra of upper-triangular 2x2 matrices with `k = 1`. -/
-- Porting note: added `LieSubmodule.toSubmodule` in the statement
theorem LieModule.coe_lowerCentralSeries_ideal_le {I : LieIdeal R L} (k : ℕ) :
LieSubmodule.toSubmodule (lowerCentralSeries R I I k) ≤ lowerCentralSeries R L I k := by
induction' k with k ih
· simp
· simp only [LieModule.lowerCentralSeries_succ, LieSubmodule.lieIdeal_oper_eq_linear_span]
apply Submodule.span_mono
rintro x ⟨⟨y, -⟩, ⟨z, hz⟩, rfl : ⁅y, z⁆ = x⟩
exact ⟨⟨y.val, LieSubmodule.mem_top _⟩, ⟨z, ih hz⟩, rfl⟩
#align lie_module.coe_lower_central_series_ideal_le LieModule.coe_lowerCentralSeries_ideal_le
/-- A central extension of nilpotent Lie algebras is nilpotent. -/
theorem LieAlgebra.nilpotent_of_nilpotent_quotient {I : LieIdeal R L} (h₁ : I ≤ center R L)
(h₂ : IsNilpotent R (L ⧸ I)) : IsNilpotent R L := by
suffices LieModule.IsNilpotent R L (L ⧸ I) by
exact LieModule.nilpotentOfNilpotentQuotient R L L h₁ this
obtain ⟨k, hk⟩ := h₂
use k
simp [← LieSubmodule.coe_toSubmodule_eq_iff, coe_lowerCentralSeries_ideal_quot_eq, hk]
#align lie_algebra.nilpotent_of_nilpotent_quotient LieAlgebra.nilpotent_of_nilpotent_quotient
theorem LieAlgebra.non_trivial_center_of_isNilpotent [Nontrivial L] [IsNilpotent R L] :
Nontrivial <| center R L :=
LieModule.nontrivial_max_triv_of_isNilpotent R L L
#align lie_algebra.non_trivial_center_of_is_nilpotent LieAlgebra.non_trivial_center_of_isNilpotent
theorem LieIdeal.map_lowerCentralSeries_le (k : ℕ) {f : L →ₗ⁅R⁆ L'} :
LieIdeal.map f (lowerCentralSeries R L L k) ≤ lowerCentralSeries R L' L' k := by
induction' k with k ih
· simp only [Nat.zero_eq, LieModule.lowerCentralSeries_zero, le_top]
· simp only [LieModule.lowerCentralSeries_succ]
exact le_trans (LieIdeal.map_bracket_le f) (LieSubmodule.mono_lie _ _ _ _ le_top ih)
#align lie_ideal.map_lower_central_series_le LieIdeal.map_lowerCentralSeries_le
theorem LieIdeal.lowerCentralSeries_map_eq (k : ℕ) {f : L →ₗ⁅R⁆ L'} (h : Function.Surjective f) :
LieIdeal.map f (lowerCentralSeries R L L k) = lowerCentralSeries R L' L' k := by
have h' : (⊤ : LieIdeal R L).map f = ⊤ := by
rw [← f.idealRange_eq_map]
exact f.idealRange_eq_top_of_surjective h
induction' k with k ih
· simp only [LieModule.lowerCentralSeries_zero]; exact h'
· simp only [LieModule.lowerCentralSeries_succ, LieIdeal.map_bracket_eq f h, ih, h']
#align lie_ideal.lower_central_series_map_eq LieIdeal.lowerCentralSeries_map_eq
theorem Function.Injective.lieAlgebra_isNilpotent [h₁ : IsNilpotent R L'] {f : L →ₗ⁅R⁆ L'}
(h₂ : Function.Injective f) : IsNilpotent R L :=
{ nilpotent := by
obtain ⟨k, hk⟩ := id h₁
use k
apply LieIdeal.bot_of_map_eq_bot h₂; rw [eq_bot_iff, ← hk]
apply LieIdeal.map_lowerCentralSeries_le }
#align function.injective.lie_algebra_is_nilpotent Function.Injective.lieAlgebra_isNilpotent
| Mathlib/Algebra/Lie/Nilpotent.lean | 732 | 738 | theorem Function.Surjective.lieAlgebra_isNilpotent [h₁ : IsNilpotent R L] {f : L →ₗ⁅R⁆ L'}
(h₂ : Function.Surjective f) : IsNilpotent R L' :=
{ nilpotent := by |
obtain ⟨k, hk⟩ := id h₁
use k
rw [← LieIdeal.lowerCentralSeries_map_eq k h₂, hk]
simp only [LieIdeal.map_eq_bot_iff, bot_le] }
|
/-
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
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
#align has_mfderiv_within_at_inter' hasMFDerivWithinAt_inter'
theorem hasMFDerivWithinAt_inter (h : t ∈ 𝓝 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_nhds I h
#align has_mfderiv_within_at_inter hasMFDerivWithinAt_inter
theorem HasMFDerivWithinAt.union (hs : HasMFDerivWithinAt I I' f s x f')
(ht : HasMFDerivWithinAt I I' f t x f') : HasMFDerivWithinAt I I' f (s ∪ t) x f' := by
constructor
· exact ContinuousWithinAt.union hs.1 ht.1
· convert HasFDerivWithinAt.union hs.2 ht.2 using 1
simp only [union_inter_distrib_right, preimage_union]
#align has_mfderiv_within_at.union HasMFDerivWithinAt.union
theorem HasMFDerivWithinAt.mono_of_mem (h : HasMFDerivWithinAt I I' f s x f') (ht : s ∈ 𝓝[t] x) :
HasMFDerivWithinAt I I' f t x f' :=
(hasMFDerivWithinAt_inter' ht).1 (h.mono inter_subset_right)
#align has_mfderiv_within_at.nhds_within HasMFDerivWithinAt.mono_of_mem
theorem HasMFDerivWithinAt.hasMFDerivAt (h : HasMFDerivWithinAt I I' f s x f') (hs : s ∈ 𝓝 x) :
HasMFDerivAt I I' f x f' := by
rwa [← univ_inter s, hasMFDerivWithinAt_inter hs, hasMFDerivWithinAt_univ] at h
#align has_mfderiv_within_at.has_mfderiv_at HasMFDerivWithinAt.hasMFDerivAt
theorem MDifferentiableWithinAt.hasMFDerivWithinAt (h : MDifferentiableWithinAt I I' f s x) :
HasMFDerivWithinAt I I' f s x (mfderivWithin I I' f s x) := by
refine ⟨h.1, ?_⟩
simp only [mfderivWithin, h, if_pos, mfld_simps]
exact DifferentiableWithinAt.hasFDerivWithinAt h.2
#align mdifferentiable_within_at.has_mfderiv_within_at MDifferentiableWithinAt.hasMFDerivWithinAt
protected theorem MDifferentiableWithinAt.mfderivWithin (h : MDifferentiableWithinAt I I' f s x) :
mfderivWithin I I' f s x =
fderivWithin 𝕜 (writtenInExtChartAt I I' x f : _) ((extChartAt I x).symm ⁻¹' s ∩ range I)
((extChartAt I x) x) := by
simp only [mfderivWithin, h, if_pos]
#align mdifferentiable_within_at.mfderiv_within MDifferentiableWithinAt.mfderivWithin
theorem MDifferentiableAt.hasMFDerivAt (h : MDifferentiableAt I I' f x) :
HasMFDerivAt I I' f x (mfderiv I I' f x) := by
refine ⟨h.continuousAt, ?_⟩
simp only [mfderiv, h, if_pos, mfld_simps]
exact DifferentiableWithinAt.hasFDerivWithinAt h.differentiableWithinAt_writtenInExtChartAt
#align mdifferentiable_at.has_mfderiv_at MDifferentiableAt.hasMFDerivAt
protected theorem MDifferentiableAt.mfderiv (h : MDifferentiableAt I I' f x) :
mfderiv I I' f x =
fderivWithin 𝕜 (writtenInExtChartAt I I' x f : _) (range I) ((extChartAt I x) x) := by
simp only [mfderiv, h, if_pos]
#align mdifferentiable_at.mfderiv MDifferentiableAt.mfderiv
protected theorem HasMFDerivAt.mfderiv (h : HasMFDerivAt I I' f x f') : mfderiv I I' f x = f' :=
(hasMFDerivAt_unique h h.mdifferentiableAt.hasMFDerivAt).symm
#align has_mfderiv_at.mfderiv HasMFDerivAt.mfderiv
theorem HasMFDerivWithinAt.mfderivWithin (h : HasMFDerivWithinAt I I' f s x f')
(hxs : UniqueMDiffWithinAt I s x) : mfderivWithin I I' f s x = f' := by
ext
rw [hxs.eq h h.mdifferentiableWithinAt.hasMFDerivWithinAt]
#align has_mfderiv_within_at.mfderiv_within HasMFDerivWithinAt.mfderivWithin
theorem MDifferentiable.mfderivWithin (h : MDifferentiableAt I I' f x)
(hxs : UniqueMDiffWithinAt I s x) : mfderivWithin I I' f s x = mfderiv I I' f x := by
apply HasMFDerivWithinAt.mfderivWithin _ hxs
exact h.hasMFDerivAt.hasMFDerivWithinAt
#align mdifferentiable.mfderiv_within MDifferentiable.mfderivWithin
theorem mfderivWithin_subset (st : s ⊆ t) (hs : UniqueMDiffWithinAt I s x)
(h : MDifferentiableWithinAt I I' f t x) :
mfderivWithin I I' f s x = mfderivWithin I I' f t x :=
((MDifferentiableWithinAt.hasMFDerivWithinAt h).mono st).mfderivWithin hs
#align mfderiv_within_subset mfderivWithin_subset
theorem MDifferentiableWithinAt.mono (hst : s ⊆ t) (h : MDifferentiableWithinAt I I' f t x) :
MDifferentiableWithinAt I I' f s x :=
⟨ContinuousWithinAt.mono h.1 hst, DifferentiableWithinAt.mono
h.differentiableWithinAt_writtenInExtChartAt
(inter_subset_inter_left _ (preimage_mono hst))⟩
#align mdifferentiable_within_at.mono MDifferentiableWithinAt.mono
theorem mdifferentiableWithinAt_univ :
MDifferentiableWithinAt I I' f univ x ↔ MDifferentiableAt I I' f x := by
simp_rw [MDifferentiableWithinAt, MDifferentiableAt, ChartedSpace.LiftPropAt]
#align mdifferentiable_within_at_univ mdifferentiableWithinAt_univ
theorem mdifferentiableWithinAt_inter (ht : t ∈ 𝓝 x) :
MDifferentiableWithinAt I I' f (s ∩ t) x ↔ MDifferentiableWithinAt I I' f s x := by
rw [MDifferentiableWithinAt, MDifferentiableWithinAt,
(differentiable_within_at_localInvariantProp I I').liftPropWithinAt_inter ht]
#align mdifferentiable_within_at_inter mdifferentiableWithinAt_inter
theorem mdifferentiableWithinAt_inter' (ht : t ∈ 𝓝[s] x) :
MDifferentiableWithinAt I I' f (s ∩ t) x ↔ MDifferentiableWithinAt I I' f s x := by
rw [MDifferentiableWithinAt, MDifferentiableWithinAt,
(differentiable_within_at_localInvariantProp I I').liftPropWithinAt_inter' ht]
#align mdifferentiable_within_at_inter' mdifferentiableWithinAt_inter'
theorem MDifferentiableAt.mdifferentiableWithinAt (h : MDifferentiableAt I I' f x) :
MDifferentiableWithinAt I I' f s x :=
MDifferentiableWithinAt.mono (subset_univ _) (mdifferentiableWithinAt_univ.2 h)
#align mdifferentiable_at.mdifferentiable_within_at MDifferentiableAt.mdifferentiableWithinAt
theorem MDifferentiableWithinAt.mdifferentiableAt (h : MDifferentiableWithinAt I I' f s x)
(hs : s ∈ 𝓝 x) : MDifferentiableAt I I' f x := by
have : s = univ ∩ s := by rw [univ_inter]
rwa [this, mdifferentiableWithinAt_inter hs, mdifferentiableWithinAt_univ] at h
#align mdifferentiable_within_at.mdifferentiable_at MDifferentiableWithinAt.mdifferentiableAt
theorem MDifferentiableOn.mdifferentiableAt (h : MDifferentiableOn I I' f s) (hx : s ∈ 𝓝 x) :
MDifferentiableAt I I' f x :=
(h x (mem_of_mem_nhds hx)).mdifferentiableAt hx
theorem MDifferentiableOn.mono (h : MDifferentiableOn I I' f t) (st : s ⊆ t) :
MDifferentiableOn I I' f s := fun x hx => (h x (st hx)).mono st
#align mdifferentiable_on.mono MDifferentiableOn.mono
theorem mdifferentiableOn_univ : MDifferentiableOn I I' f univ ↔ MDifferentiable I I' f := by
simp only [MDifferentiableOn, mdifferentiableWithinAt_univ, mfld_simps]; rfl
#align mdifferentiable_on_univ mdifferentiableOn_univ
theorem MDifferentiable.mdifferentiableOn (h : MDifferentiable I I' f) :
MDifferentiableOn I I' f s :=
(mdifferentiableOn_univ.2 h).mono (subset_univ _)
#align mdifferentiable.mdifferentiable_on MDifferentiable.mdifferentiableOn
theorem mdifferentiableOn_of_locally_mdifferentiableOn
(h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ MDifferentiableOn I I' f (s ∩ u)) :
MDifferentiableOn I I' f s := by
intro x xs
rcases h x xs with ⟨t, t_open, xt, ht⟩
exact (mdifferentiableWithinAt_inter (t_open.mem_nhds xt)).1 (ht x ⟨xs, xt⟩)
#align mdifferentiable_on_of_locally_mdifferentiable_on mdifferentiableOn_of_locally_mdifferentiableOn
@[simp, mfld_simps]
theorem mfderivWithin_univ : mfderivWithin I I' f univ = mfderiv I I' f := by
ext x : 1
simp only [mfderivWithin, mfderiv, mfld_simps]
rw [mdifferentiableWithinAt_univ]
#align mfderiv_within_univ mfderivWithin_univ
theorem mfderivWithin_inter (ht : t ∈ 𝓝 x) :
mfderivWithin I I' f (s ∩ t) x = mfderivWithin I I' f s x := by
rw [mfderivWithin, mfderivWithin, extChartAt_preimage_inter_eq, mdifferentiableWithinAt_inter ht,
fderivWithin_inter (extChartAt_preimage_mem_nhds I ht)]
#align mfderiv_within_inter mfderivWithin_inter
theorem mfderivWithin_of_mem_nhds (h : s ∈ 𝓝 x) : mfderivWithin I I' f s x = mfderiv I I' f x := by
rw [← mfderivWithin_univ, ← univ_inter s, mfderivWithin_inter h]
lemma mfderivWithin_of_isOpen (hs : IsOpen s) (hx : x ∈ s) :
mfderivWithin I I' f s x = mfderiv I I' f x :=
mfderivWithin_of_mem_nhds (hs.mem_nhds hx)
theorem mfderivWithin_eq_mfderiv (hs : UniqueMDiffWithinAt I s x) (h : MDifferentiableAt I I' f x) :
mfderivWithin I I' f s x = mfderiv I I' f x := by
rw [← mfderivWithin_univ]
exact mfderivWithin_subset (subset_univ _) hs h.mdifferentiableWithinAt
theorem mdifferentiableAt_iff_of_mem_source {x' : M} {y : M'}
(hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) :
MDifferentiableAt I I' f x' ↔
ContinuousAt f x' ∧
DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) (Set.range I)
((extChartAt I x) x') :=
mdifferentiableWithinAt_univ.symm.trans <|
(mdifferentiableWithinAt_iff_of_mem_source hx hy).trans <| by
rw [continuousWithinAt_univ, Set.preimage_univ, Set.univ_inter]
#align mdifferentiable_at_iff_of_mem_source mdifferentiableAt_iff_of_mem_source
/-! ### Deducing differentiability from smoothness -/
-- Porting note: moved from `ContMDiffMFDeriv`
variable {n : ℕ∞}
theorem ContMDiffWithinAt.mdifferentiableWithinAt (hf : ContMDiffWithinAt I I' n f s x)
(hn : 1 ≤ n) : MDifferentiableWithinAt I I' f s x := by
suffices h : MDifferentiableWithinAt I I' f (s ∩ f ⁻¹' (extChartAt I' (f x)).source) x by
rwa [mdifferentiableWithinAt_inter'] at h
apply hf.1.preimage_mem_nhdsWithin
exact extChartAt_source_mem_nhds I' (f x)
rw [mdifferentiableWithinAt_iff]
exact ⟨hf.1.mono inter_subset_left, (hf.2.differentiableWithinAt hn).mono (by mfld_set_tac)⟩
#align cont_mdiff_within_at.mdifferentiable_within_at ContMDiffWithinAt.mdifferentiableWithinAt
theorem ContMDiffAt.mdifferentiableAt (hf : ContMDiffAt I I' n f x) (hn : 1 ≤ n) :
MDifferentiableAt I I' f x :=
mdifferentiableWithinAt_univ.1 <| ContMDiffWithinAt.mdifferentiableWithinAt hf hn
#align cont_mdiff_at.mdifferentiable_at ContMDiffAt.mdifferentiableAt
theorem ContMDiffOn.mdifferentiableOn (hf : ContMDiffOn I I' n f s) (hn : 1 ≤ n) :
MDifferentiableOn I I' f s := fun x hx => (hf x hx).mdifferentiableWithinAt hn
#align cont_mdiff_on.mdifferentiable_on ContMDiffOn.mdifferentiableOn
theorem ContMDiff.mdifferentiable (hf : ContMDiff I I' n f) (hn : 1 ≤ n) : MDifferentiable I I' f :=
fun x => (hf x).mdifferentiableAt hn
#align cont_mdiff.mdifferentiable ContMDiff.mdifferentiable
nonrec theorem SmoothWithinAt.mdifferentiableWithinAt (hf : SmoothWithinAt I I' f s x) :
MDifferentiableWithinAt I I' f s x :=
hf.mdifferentiableWithinAt le_top
#align smooth_within_at.mdifferentiable_within_at SmoothWithinAt.mdifferentiableWithinAt
nonrec theorem SmoothAt.mdifferentiableAt (hf : SmoothAt I I' f x) : MDifferentiableAt I I' f x :=
hf.mdifferentiableAt le_top
#align smooth_at.mdifferentiable_at SmoothAt.mdifferentiableAt
nonrec theorem SmoothOn.mdifferentiableOn (hf : SmoothOn I I' f s) : MDifferentiableOn I I' f s :=
hf.mdifferentiableOn le_top
#align smooth_on.mdifferentiable_on SmoothOn.mdifferentiableOn
theorem Smooth.mdifferentiable (hf : Smooth I I' f) : MDifferentiable I I' f :=
ContMDiff.mdifferentiable hf le_top
#align smooth.mdifferentiable Smooth.mdifferentiable
theorem Smooth.mdifferentiableAt (hf : Smooth I I' f) : MDifferentiableAt I I' f x :=
hf.mdifferentiable x
#align smooth.mdifferentiable_at Smooth.mdifferentiableAt
theorem Smooth.mdifferentiableWithinAt (hf : Smooth I I' f) : MDifferentiableWithinAt I I' f s x :=
hf.mdifferentiableAt.mdifferentiableWithinAt
#align smooth.mdifferentiable_within_at Smooth.mdifferentiableWithinAt
/-! ### Deriving continuity from differentiability on manifolds -/
theorem HasMFDerivWithinAt.continuousWithinAt (h : HasMFDerivWithinAt I I' f s x f') :
ContinuousWithinAt f s x :=
h.1
#align has_mfderiv_within_at.continuous_within_at HasMFDerivWithinAt.continuousWithinAt
theorem HasMFDerivAt.continuousAt (h : HasMFDerivAt I I' f x f') : ContinuousAt f x :=
h.1
#align has_mfderiv_at.continuous_at HasMFDerivAt.continuousAt
theorem MDifferentiableOn.continuousOn (h : MDifferentiableOn I I' f s) : ContinuousOn f s :=
fun x hx => (h x hx).continuousWithinAt
#align mdifferentiable_on.continuous_on MDifferentiableOn.continuousOn
theorem MDifferentiable.continuous (h : MDifferentiable I I' f) : Continuous f :=
continuous_iff_continuousAt.2 fun x => (h x).continuousAt
#align mdifferentiable.continuous MDifferentiable.continuous
theorem tangentMapWithin_subset {p : TangentBundle I M} (st : s ⊆ t)
(hs : UniqueMDiffWithinAt I s p.1) (h : MDifferentiableWithinAt I I' f t p.1) :
tangentMapWithin I I' f s p = tangentMapWithin I I' f t p := by
simp only [tangentMapWithin, mfld_simps]
rw [mfderivWithin_subset st hs h]
#align tangent_map_within_subset tangentMapWithin_subset
theorem tangentMapWithin_univ : tangentMapWithin I I' f univ = tangentMap I I' f := by
ext p : 1
simp only [tangentMapWithin, tangentMap, mfld_simps]
#align tangent_map_within_univ tangentMapWithin_univ
theorem tangentMapWithin_eq_tangentMap {p : TangentBundle I M} (hs : UniqueMDiffWithinAt I s p.1)
(h : MDifferentiableAt I I' f p.1) : tangentMapWithin I I' f s p = tangentMap I I' f p := by
rw [← mdifferentiableWithinAt_univ] at h
rw [← tangentMapWithin_univ]
exact tangentMapWithin_subset (subset_univ _) hs h
#align tangent_map_within_eq_tangent_map tangentMapWithin_eq_tangentMap
@[simp, mfld_simps]
theorem tangentMapWithin_proj {p : TangentBundle I M} :
(tangentMapWithin I I' f s p).proj = f p.proj :=
rfl
#align tangent_map_within_proj tangentMapWithin_proj
@[simp, mfld_simps]
theorem tangentMap_proj {p : TangentBundle I M} : (tangentMap I I' f p).proj = f p.proj :=
rfl
#align tangent_map_proj tangentMap_proj
theorem MDifferentiableWithinAt.prod_mk {f : M → M'} {g : M → M''}
(hf : MDifferentiableWithinAt I I' f s x) (hg : MDifferentiableWithinAt I I'' g s x) :
MDifferentiableWithinAt I (I'.prod I'') (fun x => (f x, g x)) s x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_within_at.prod_mk MDifferentiableWithinAt.prod_mk
theorem MDifferentiableAt.prod_mk {f : M → M'} {g : M → M''} (hf : MDifferentiableAt I I' f x)
(hg : MDifferentiableAt I I'' g x) :
MDifferentiableAt I (I'.prod I'') (fun x => (f x, g x)) x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_at.prod_mk MDifferentiableAt.prod_mk
theorem MDifferentiableOn.prod_mk {f : M → M'} {g : M → M''} (hf : MDifferentiableOn I I' f s)
(hg : MDifferentiableOn I I'' g s) :
MDifferentiableOn I (I'.prod I'') (fun x => (f x, g x)) s := fun x hx =>
(hf x hx).prod_mk (hg x hx)
#align mdifferentiable_on.prod_mk MDifferentiableOn.prod_mk
theorem MDifferentiable.prod_mk {f : M → M'} {g : M → M''} (hf : MDifferentiable I I' f)
(hg : MDifferentiable I I'' g) : MDifferentiable I (I'.prod I'') fun x => (f x, g x) := fun x =>
(hf x).prod_mk (hg x)
#align mdifferentiable.prod_mk MDifferentiable.prod_mk
theorem MDifferentiableWithinAt.prod_mk_space {f : M → E'} {g : M → E''}
(hf : MDifferentiableWithinAt I 𝓘(𝕜, E') f s x)
(hg : MDifferentiableWithinAt I 𝓘(𝕜, E'') g s x) :
MDifferentiableWithinAt I 𝓘(𝕜, E' × E'') (fun x => (f x, g x)) s x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_within_at.prod_mk_space MDifferentiableWithinAt.prod_mk_space
theorem MDifferentiableAt.prod_mk_space {f : M → E'} {g : M → E''}
(hf : MDifferentiableAt I 𝓘(𝕜, E') f x) (hg : MDifferentiableAt I 𝓘(𝕜, E'') g x) :
MDifferentiableAt I 𝓘(𝕜, E' × E'') (fun x => (f x, g x)) x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_at.prod_mk_space MDifferentiableAt.prod_mk_space
theorem MDifferentiableOn.prod_mk_space {f : M → E'} {g : M → E''}
(hf : MDifferentiableOn I 𝓘(𝕜, E') f s) (hg : MDifferentiableOn I 𝓘(𝕜, E'') g s) :
MDifferentiableOn I 𝓘(𝕜, E' × E'') (fun x => (f x, g x)) s := fun x hx =>
(hf x hx).prod_mk_space (hg x hx)
#align mdifferentiable_on.prod_mk_space MDifferentiableOn.prod_mk_space
theorem MDifferentiable.prod_mk_space {f : M → E'} {g : M → E''} (hf : MDifferentiable I 𝓘(𝕜, E') f)
(hg : MDifferentiable I 𝓘(𝕜, E'') g) : MDifferentiable I 𝓘(𝕜, E' × E'') fun x => (f x, g x) :=
fun x => (hf x).prod_mk_space (hg x)
#align mdifferentiable.prod_mk_space MDifferentiable.prod_mk_space
/-! ### Congruence lemmas for derivatives on manifolds -/
theorem HasMFDerivAt.congr_mfderiv (h : HasMFDerivAt I I' f x f') (h' : f' = f₁') :
HasMFDerivAt I I' f x f₁' :=
h' ▸ h
theorem HasMFDerivWithinAt.congr_mfderiv (h : HasMFDerivWithinAt I I' f s x f') (h' : f' = f₁') :
HasMFDerivWithinAt I I' f s x f₁' :=
h' ▸ h
theorem HasMFDerivWithinAt.congr_of_eventuallyEq (h : HasMFDerivWithinAt I I' f s x f')
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : HasMFDerivWithinAt I I' f₁ s x f' := by
refine ⟨ContinuousWithinAt.congr_of_eventuallyEq h.1 h₁ hx, ?_⟩
apply HasFDerivWithinAt.congr_of_eventuallyEq h.2
· have :
(extChartAt I x).symm ⁻¹' {y | f₁ y = f y} ∈
𝓝[(extChartAt I x).symm ⁻¹' s ∩ range I] (extChartAt I x) x :=
extChartAt_preimage_mem_nhdsWithin I h₁
apply Filter.mem_of_superset this fun y => _
simp (config := { contextual := true }) only [hx, mfld_simps]
· simp only [hx, mfld_simps]
#align has_mfderiv_within_at.congr_of_eventually_eq HasMFDerivWithinAt.congr_of_eventuallyEq
theorem HasMFDerivWithinAt.congr_mono (h : HasMFDerivWithinAt I I' f s x f')
(ht : ∀ x ∈ t, f₁ x = f x) (hx : f₁ x = f x) (h₁ : t ⊆ s) : HasMFDerivWithinAt I I' f₁ t x f' :=
(h.mono h₁).congr_of_eventuallyEq (Filter.mem_inf_of_right ht) hx
#align has_mfderiv_within_at.congr_mono HasMFDerivWithinAt.congr_mono
| Mathlib/Geometry/Manifold/MFDeriv/Basic.lean | 558 | 562 | theorem HasMFDerivAt.congr_of_eventuallyEq (h : HasMFDerivAt I I' f x f') (h₁ : f₁ =ᶠ[𝓝 x] f) :
HasMFDerivAt I I' f₁ x f' := by |
rw [← hasMFDerivWithinAt_univ] at h ⊢
apply h.congr_of_eventuallyEq _ (mem_of_mem_nhds h₁ : _)
rwa [nhdsWithin_univ]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Defs.Induced
import Mathlib.Topology.Basic
#align_import topology.order from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Ordering on topologies and (co)induced topologies
Topologies on a fixed type `α` are ordered, by reverse inclusion. That is, for topologies `t₁` and
`t₂` on `α`, we write `t₁ ≤ t₂` if every set open in `t₂` is also open in `t₁`. (One also calls
`t₁` *finer* than `t₂`, and `t₂` *coarser* than `t₁`.)
Any function `f : α → β` induces
* `TopologicalSpace.induced f : TopologicalSpace β → TopologicalSpace α`;
* `TopologicalSpace.coinduced f : TopologicalSpace α → TopologicalSpace β`.
Continuity, the ordering on topologies and (co)induced topologies are related as follows:
* The identity map `(α, t₁) → (α, t₂)` is continuous iff `t₁ ≤ t₂`.
* A map `f : (α, t) → (β, u)` is continuous
* iff `t ≤ TopologicalSpace.induced f u` (`continuous_iff_le_induced`)
* iff `TopologicalSpace.coinduced f t ≤ u` (`continuous_iff_coinduced_le`).
Topologies on `α` form a complete lattice, with `⊥` the discrete topology and `⊤` the indiscrete
topology.
For a function `f : α → β`, `(TopologicalSpace.coinduced f, TopologicalSpace.induced f)` is a Galois
connection between topologies on `α` and topologies on `β`.
## Implementation notes
There is a Galois insertion between topologies on `α` (with the inclusion ordering) and all
collections of sets in `α`. The complete lattice structure on topologies on `α` is defined as the
reverse of the one obtained via this Galois insertion. More precisely, we use the corresponding
Galois coinsertion between topologies on `α` (with the reversed inclusion ordering) and collections
of sets in `α` (with the reversed inclusion ordering).
## Tags
finer, coarser, induced topology, coinduced topology
-/
open Function Set Filter Topology
universe u v w
namespace TopologicalSpace
variable {α : Type u}
/-- The open sets of the least topology containing a collection of basic sets. -/
inductive GenerateOpen (g : Set (Set α)) : Set α → Prop
| basic : ∀ s ∈ g, GenerateOpen g s
| univ : GenerateOpen g univ
| inter : ∀ s t, GenerateOpen g s → GenerateOpen g t → GenerateOpen g (s ∩ t)
| sUnion : ∀ S : Set (Set α), (∀ s ∈ S, GenerateOpen g s) → GenerateOpen g (⋃₀ S)
#align topological_space.generate_open TopologicalSpace.GenerateOpen
/-- The smallest topological space containing the collection `g` of basic sets -/
def generateFrom (g : Set (Set α)) : TopologicalSpace α where
IsOpen := GenerateOpen g
isOpen_univ := GenerateOpen.univ
isOpen_inter := GenerateOpen.inter
isOpen_sUnion := GenerateOpen.sUnion
#align topological_space.generate_from TopologicalSpace.generateFrom
theorem isOpen_generateFrom_of_mem {g : Set (Set α)} {s : Set α} (hs : s ∈ g) :
IsOpen[generateFrom g] s :=
GenerateOpen.basic s hs
#align topological_space.is_open_generate_from_of_mem TopologicalSpace.isOpen_generateFrom_of_mem
theorem nhds_generateFrom {g : Set (Set α)} {a : α} :
@nhds α (generateFrom g) a = ⨅ s ∈ { s | a ∈ s ∧ s ∈ g }, 𝓟 s := by
letI := generateFrom g
rw [nhds_def]
refine le_antisymm (biInf_mono fun s ⟨as, sg⟩ => ⟨as, .basic _ sg⟩) <| le_iInf₂ ?_
rintro s ⟨ha, hs⟩
induction hs with
| basic _ hs => exact iInf₂_le _ ⟨ha, hs⟩
| univ => exact le_top.trans_eq principal_univ.symm
| inter _ _ _ _ hs ht => exact (le_inf (hs ha.1) (ht ha.2)).trans_eq inf_principal
| sUnion _ _ hS =>
let ⟨t, htS, hat⟩ := ha
exact (hS t htS hat).trans (principal_mono.2 <| subset_sUnion_of_mem htS)
#align topological_space.nhds_generate_from TopologicalSpace.nhds_generateFrom
lemma tendsto_nhds_generateFrom_iff {β : Type*} {m : α → β} {f : Filter α} {g : Set (Set β)}
{b : β} : Tendsto m f (@nhds β (generateFrom g) b) ↔ ∀ s ∈ g, b ∈ s → m ⁻¹' s ∈ f := by
simp only [nhds_generateFrom, @forall_swap (b ∈ _), tendsto_iInf, mem_setOf_eq, and_imp,
tendsto_principal]; rfl
@[deprecated] alias ⟨_, tendsto_nhds_generateFrom⟩ := tendsto_nhds_generateFrom_iff
#align topological_space.tendsto_nhds_generate_from TopologicalSpace.tendsto_nhds_generateFrom
/-- Construct a topology on α given the filter of neighborhoods of each point of α. -/
protected def mkOfNhds (n : α → Filter α) : TopologicalSpace α where
IsOpen s := ∀ a ∈ s, s ∈ n a
isOpen_univ _ _ := univ_mem
isOpen_inter := fun _s _t hs ht x ⟨hxs, hxt⟩ => inter_mem (hs x hxs) (ht x hxt)
isOpen_sUnion := fun _s hs _a ⟨x, hx, hxa⟩ =>
mem_of_superset (hs x hx _ hxa) (subset_sUnion_of_mem hx)
#align topological_space.mk_of_nhds TopologicalSpace.mkOfNhds
theorem nhds_mkOfNhds_of_hasBasis {n : α → Filter α} {ι : α → Sort*} {p : ∀ a, ι a → Prop}
{s : ∀ a, ι a → Set α} (hb : ∀ a, (n a).HasBasis (p a) (s a))
(hpure : ∀ a i, p a i → a ∈ s a i) (hopen : ∀ a i, p a i → ∀ᶠ x in n a, s a i ∈ n x) (a : α) :
@nhds α (.mkOfNhds n) a = n a := by
let t : TopologicalSpace α := .mkOfNhds n
apply le_antisymm
· intro U hU
replace hpure : pure ≤ n := fun x ↦ (hb x).ge_iff.2 (hpure x)
refine mem_nhds_iff.2 ⟨{x | U ∈ n x}, fun x hx ↦ hpure x hx, fun x hx ↦ ?_, hU⟩
rcases (hb x).mem_iff.1 hx with ⟨i, hpi, hi⟩
exact (hopen x i hpi).mono fun y hy ↦ mem_of_superset hy hi
· exact (nhds_basis_opens a).ge_iff.2 fun U ⟨haU, hUo⟩ ↦ hUo a haU
theorem nhds_mkOfNhds (n : α → Filter α) (a : α) (h₀ : pure ≤ n)
(h₁ : ∀ a, ∀ s ∈ n a, ∀ᶠ y in n a, s ∈ n y) :
@nhds α (TopologicalSpace.mkOfNhds n) a = n a :=
nhds_mkOfNhds_of_hasBasis (fun a ↦ (n a).basis_sets) h₀ h₁ _
#align topological_space.nhds_mk_of_nhds TopologicalSpace.nhds_mkOfNhds
theorem nhds_mkOfNhds_single [DecidableEq α] {a₀ : α} {l : Filter α} (h : pure a₀ ≤ l) (b : α) :
@nhds α (TopologicalSpace.mkOfNhds (update pure a₀ l)) b =
(update pure a₀ l : α → Filter α) b := by
refine nhds_mkOfNhds _ _ (le_update_iff.mpr ⟨h, fun _ _ => le_rfl⟩) fun a s hs => ?_
rcases eq_or_ne a a₀ with (rfl | ha)
· filter_upwards [hs] with b hb
rcases eq_or_ne b a with (rfl | hb)
· exact hs
· rwa [update_noteq hb]
· simpa only [update_noteq ha, mem_pure, eventually_pure] using hs
#align topological_space.nhds_mk_of_nhds_single TopologicalSpace.nhds_mkOfNhds_single
theorem nhds_mkOfNhds_filterBasis (B : α → FilterBasis α) (a : α) (h₀ : ∀ x, ∀ n ∈ B x, x ∈ n)
(h₁ : ∀ x, ∀ n ∈ B x, ∃ n₁ ∈ B x, ∀ x' ∈ n₁, ∃ n₂ ∈ B x', n₂ ⊆ n) :
@nhds α (TopologicalSpace.mkOfNhds fun x => (B x).filter) a = (B a).filter :=
nhds_mkOfNhds_of_hasBasis (fun a ↦ (B a).hasBasis) h₀ h₁ a
#align topological_space.nhds_mk_of_nhds_filter_basis TopologicalSpace.nhds_mkOfNhds_filterBasis
section Lattice
variable {α : Type u} {β : Type v}
/-- The ordering on topologies on the type `α`. `t ≤ s` if every set open in `s` is also open in `t`
(`t` is finer than `s`). -/
instance : PartialOrder (TopologicalSpace α) :=
{ PartialOrder.lift (fun t => OrderDual.toDual IsOpen[t]) (fun _ _ => TopologicalSpace.ext) with
le := fun s t => ∀ U, IsOpen[t] U → IsOpen[s] U }
protected theorem le_def {α} {t s : TopologicalSpace α} : t ≤ s ↔ IsOpen[s] ≤ IsOpen[t] :=
Iff.rfl
#align topological_space.le_def TopologicalSpace.le_def
theorem le_generateFrom_iff_subset_isOpen {g : Set (Set α)} {t : TopologicalSpace α} :
t ≤ generateFrom g ↔ g ⊆ { s | IsOpen[t] s } :=
⟨fun ht s hs => ht _ <| .basic s hs, fun hg _s hs =>
hs.recOn (fun _ h => hg h) isOpen_univ (fun _ _ _ _ => IsOpen.inter) fun _ _ => isOpen_sUnion⟩
#align topological_space.le_generate_from_iff_subset_is_open TopologicalSpace.le_generateFrom_iff_subset_isOpen
/-- If `s` equals the collection of open sets in the topology it generates, then `s` defines a
topology. -/
protected def mkOfClosure (s : Set (Set α)) (hs : { u | GenerateOpen s u } = s) :
TopologicalSpace α where
IsOpen u := u ∈ s
isOpen_univ := hs ▸ TopologicalSpace.GenerateOpen.univ
isOpen_inter := hs ▸ TopologicalSpace.GenerateOpen.inter
isOpen_sUnion := hs ▸ TopologicalSpace.GenerateOpen.sUnion
#align topological_space.mk_of_closure TopologicalSpace.mkOfClosure
theorem mkOfClosure_sets {s : Set (Set α)} {hs : { u | GenerateOpen s u } = s} :
TopologicalSpace.mkOfClosure s hs = generateFrom s :=
TopologicalSpace.ext hs.symm
#align topological_space.mk_of_closure_sets TopologicalSpace.mkOfClosure_sets
theorem gc_generateFrom (α) :
GaloisConnection (fun t : TopologicalSpace α => OrderDual.toDual { s | IsOpen[t] s })
(generateFrom ∘ OrderDual.ofDual) := fun _ _ =>
le_generateFrom_iff_subset_isOpen.symm
/-- The Galois coinsertion between `TopologicalSpace α` and `(Set (Set α))ᵒᵈ` whose lower part sends
a topology to its collection of open subsets, and whose upper part sends a collection of subsets
of `α` to the topology they generate. -/
def gciGenerateFrom (α : Type*) :
GaloisCoinsertion (fun t : TopologicalSpace α => OrderDual.toDual { s | IsOpen[t] s })
(generateFrom ∘ OrderDual.ofDual) where
gc := gc_generateFrom α
u_l_le _ s hs := TopologicalSpace.GenerateOpen.basic s hs
choice g hg := TopologicalSpace.mkOfClosure g
(Subset.antisymm hg <| le_generateFrom_iff_subset_isOpen.1 <| le_rfl)
choice_eq _ _ := mkOfClosure_sets
#align gi_generate_from TopologicalSpace.gciGenerateFrom
/-- Topologies on `α` form a complete lattice, with `⊥` the discrete topology
and `⊤` the indiscrete topology. The infimum of a collection of topologies
is the topology generated by all their open sets, while the supremum is the
topology whose open sets are those sets open in every member of the collection. -/
instance : CompleteLattice (TopologicalSpace α) := (gciGenerateFrom α).liftCompleteLattice
@[mono]
theorem generateFrom_anti {α} {g₁ g₂ : Set (Set α)} (h : g₁ ⊆ g₂) :
generateFrom g₂ ≤ generateFrom g₁ :=
(gc_generateFrom _).monotone_u h
#align topological_space.generate_from_anti TopologicalSpace.generateFrom_anti
theorem generateFrom_setOf_isOpen (t : TopologicalSpace α) :
generateFrom { s | IsOpen[t] s } = t :=
(gciGenerateFrom α).u_l_eq t
#align topological_space.generate_from_set_of_is_open TopologicalSpace.generateFrom_setOf_isOpen
theorem leftInverse_generateFrom :
LeftInverse generateFrom fun t : TopologicalSpace α => { s | IsOpen[t] s } :=
(gciGenerateFrom α).u_l_leftInverse
#align topological_space.left_inverse_generate_from TopologicalSpace.leftInverse_generateFrom
theorem generateFrom_surjective : Surjective (generateFrom : Set (Set α) → TopologicalSpace α) :=
(gciGenerateFrom α).u_surjective
#align topological_space.generate_from_surjective TopologicalSpace.generateFrom_surjective
theorem setOf_isOpen_injective : Injective fun t : TopologicalSpace α => { s | IsOpen[t] s } :=
(gciGenerateFrom α).l_injective
#align topological_space.set_of_is_open_injective TopologicalSpace.setOf_isOpen_injective
end Lattice
end TopologicalSpace
section Lattice
variable {α : Type*} {t t₁ t₂ : TopologicalSpace α} {s : Set α}
theorem IsOpen.mono (hs : IsOpen[t₂] s) (h : t₁ ≤ t₂) : IsOpen[t₁] s := h s hs
#align is_open.mono IsOpen.mono
theorem IsClosed.mono (hs : IsClosed[t₂] s) (h : t₁ ≤ t₂) : IsClosed[t₁] s :=
(@isOpen_compl_iff α s t₁).mp <| hs.isOpen_compl.mono h
#align is_closed.mono IsClosed.mono
theorem closure.mono (h : t₁ ≤ t₂) : closure[t₁] s ⊆ closure[t₂] s :=
@closure_minimal _ s (@closure _ t₂ s) t₁ subset_closure (IsClosed.mono isClosed_closure h)
theorem isOpen_implies_isOpen_iff : (∀ s, IsOpen[t₁] s → IsOpen[t₂] s) ↔ t₂ ≤ t₁ :=
Iff.rfl
#align is_open_implies_is_open_iff isOpen_implies_isOpen_iff
/-- The only open sets in the indiscrete topology are the empty set and the whole space. -/
theorem TopologicalSpace.isOpen_top_iff {α} (U : Set α) : IsOpen[⊤] U ↔ U = ∅ ∨ U = univ :=
⟨fun h => by
induction h with
| basic _ h => exact False.elim h
| univ => exact .inr rfl
| inter _ _ _ _ h₁ h₂ =>
rcases h₁ with (rfl | rfl) <;> rcases h₂ with (rfl | rfl) <;> simp
| sUnion _ _ ih => exact sUnion_mem_empty_univ ih, by
rintro (rfl | rfl)
exacts [@isOpen_empty _ ⊤, @isOpen_univ _ ⊤]⟩
#align topological_space.is_open_top_iff TopologicalSpace.isOpen_top_iff
/-- A topological space is discrete if every set is open, that is,
its topology equals the discrete topology `⊥`. -/
class DiscreteTopology (α : Type*) [t : TopologicalSpace α] : Prop where
/-- The `TopologicalSpace` structure on a type with discrete topology is equal to `⊥`. -/
eq_bot : t = ⊥
#align discrete_topology DiscreteTopology
theorem discreteTopology_bot (α : Type*) : @DiscreteTopology α ⊥ :=
@DiscreteTopology.mk α ⊥ rfl
#align discrete_topology_bot discreteTopology_bot
section DiscreteTopology
variable [TopologicalSpace α] [DiscreteTopology α] {β : Type*}
@[simp]
theorem isOpen_discrete (s : Set α) : IsOpen s := (@DiscreteTopology.eq_bot α _).symm ▸ trivial
#align is_open_discrete isOpen_discrete
@[simp] theorem isClosed_discrete (s : Set α) : IsClosed s := ⟨isOpen_discrete _⟩
#align is_closed_discrete isClosed_discrete
@[simp] theorem closure_discrete (s : Set α) : closure s = s := (isClosed_discrete _).closure_eq
@[simp] theorem dense_discrete {s : Set α} : Dense s ↔ s = univ := by simp [dense_iff_closure_eq]
@[simp]
theorem denseRange_discrete {ι : Type*} {f : ι → α} : DenseRange f ↔ Surjective f := by
rw [DenseRange, dense_discrete, range_iff_surjective]
@[nontriviality, continuity]
theorem continuous_of_discreteTopology [TopologicalSpace β] {f : α → β} : Continuous f :=
continuous_def.2 fun _ _ => isOpen_discrete _
#align continuous_of_discrete_topology continuous_of_discreteTopology
/-- A function to a discrete topological space is continuous if and only if the preimage of every
singleton is open. -/
theorem continuous_discrete_rng [TopologicalSpace β] [DiscreteTopology β]
{f : α → β} : Continuous f ↔ ∀ b : β, IsOpen (f ⁻¹' {b}) :=
⟨fun h b => (isOpen_discrete _).preimage h, fun h => ⟨fun s _ => by
rw [← biUnion_of_singleton s, preimage_iUnion₂]
exact isOpen_biUnion fun _ _ => h _⟩⟩
@[simp]
theorem nhds_discrete (α : Type*) [TopologicalSpace α] [DiscreteTopology α] : @nhds α _ = pure :=
le_antisymm (fun _ s hs => (isOpen_discrete s).mem_nhds hs) pure_le_nhds
#align nhds_discrete nhds_discrete
theorem mem_nhds_discrete {x : α} {s : Set α} :
s ∈ 𝓝 x ↔ x ∈ s := by rw [nhds_discrete, mem_pure]
#align mem_nhds_discrete mem_nhds_discrete
end DiscreteTopology
theorem le_of_nhds_le_nhds (h : ∀ x, @nhds α t₁ x ≤ @nhds α t₂ x) : t₁ ≤ t₂ := fun s => by
rw [@isOpen_iff_mem_nhds _ _ t₁, @isOpen_iff_mem_nhds α _ t₂]
exact fun hs a ha => h _ (hs _ ha)
#align le_of_nhds_le_nhds le_of_nhds_le_nhds
@[deprecated (since := "2024-03-01")]
alias eq_of_nhds_eq_nhds := TopologicalSpace.ext_nhds
#align eq_of_nhds_eq_nhds TopologicalSpace.ext_nhds
theorem eq_bot_of_singletons_open {t : TopologicalSpace α} (h : ∀ x, IsOpen[t] {x}) : t = ⊥ :=
bot_unique fun s _ => biUnion_of_singleton s ▸ isOpen_biUnion fun x _ => h x
#align eq_bot_of_singletons_open eq_bot_of_singletons_open
theorem forall_open_iff_discrete {X : Type*} [TopologicalSpace X] :
(∀ s : Set X, IsOpen s) ↔ DiscreteTopology X :=
⟨fun h => ⟨eq_bot_of_singletons_open fun _ => h _⟩, @isOpen_discrete _ _⟩
#align forall_open_iff_discrete forall_open_iff_discrete
theorem discreteTopology_iff_forall_isClosed [TopologicalSpace α] :
DiscreteTopology α ↔ ∀ s : Set α, IsClosed s :=
forall_open_iff_discrete.symm.trans <| compl_surjective.forall.trans <| forall_congr' fun _ ↦
isOpen_compl_iff
theorem singletons_open_iff_discrete {X : Type*} [TopologicalSpace X] :
(∀ a : X, IsOpen ({a} : Set X)) ↔ DiscreteTopology X :=
⟨fun h => ⟨eq_bot_of_singletons_open h⟩, fun a _ => @isOpen_discrete _ _ a _⟩
#align singletons_open_iff_discrete singletons_open_iff_discrete
theorem discreteTopology_iff_singleton_mem_nhds [TopologicalSpace α] :
DiscreteTopology α ↔ ∀ x : α, {x} ∈ 𝓝 x := by
simp only [← singletons_open_iff_discrete, isOpen_iff_mem_nhds, mem_singleton_iff, forall_eq]
#align discrete_topology_iff_singleton_mem_nhds discreteTopology_iff_singleton_mem_nhds
/-- This lemma characterizes discrete topological spaces as those whose singletons are
neighbourhoods. -/
| Mathlib/Topology/Order.lean | 354 | 356 | theorem discreteTopology_iff_nhds [TopologicalSpace α] :
DiscreteTopology α ↔ ∀ x : α, 𝓝 x = pure x := by |
simp only [discreteTopology_iff_singleton_mem_nhds, ← nhds_neBot.le_pure_iff, le_pure_iff]
|
/-
Copyright (c) 2021 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.RingTheory.IntegralClosure
import Mathlib.RingTheory.Localization.Integral
#align_import ring_theory.integrally_closed from "leanprover-community/mathlib"@"d35b4ff446f1421bd551fafa4b8efd98ac3ac408"
/-!
# Integrally closed rings
An integrally closed ring `R` contains all the elements of `Frac(R)` that are
integral over `R`. A special case of integrally closed rings are the Dedekind domains.
## Main definitions
* `IsIntegrallyClosedIn R A` states `R` contains all integral elements of `A`
* `IsIntegrallyClosed R` states `R` contains all integral elements of `Frac(R)`
## Main results
* `isIntegrallyClosed_iff K`, where `K` is a fraction field of `R`, states `R`
is integrally closed iff it is the integral closure of `R` in `K`
## TODO: Related notions
The following definitions are closely related, especially in their applications in Mathlib.
A *normal domain* is a domain that is integrally closed in its field of fractions.
[Stacks: normal domain](https://stacks.math.columbia.edu/tag/037B#0309)
Normal domains are the major use case of `IsIntegrallyClosed` at the time of writing, and we have
quite a few results that can be moved wholesale to a new `NormalDomain` definition.
In fact, before PR #6126 `IsIntegrallyClosed` was exactly defined to be a normal domain.
(So you might want to copy some of its API when you define normal domains.)
A normal ring means that localizations at all prime ideals are normal domains.
[Stacks: normal ring](https://stacks.math.columbia.edu/tag/037B#00GV)
This implies `IsIntegrallyClosed`,
[Stacks: Tag 034M](https://stacks.math.columbia.edu/tag/037B#034M)
but is equivalent to it only under some conditions (reduced + finitely many minimal primes),
[Stacks: Tag 030C](https://stacks.math.columbia.edu/tag/037B#030C)
in which case it's also equivalent to being a finite product of normal domains.
We'd need to add these conditions if we want exactly the products of Dedekind domains.
In fact noetherianity is sufficient to guarantee finitely many minimal primes, so `IsDedekindRing`
could be defined as `IsReduced`, `IsNoetherian`, `Ring.DimensionLEOne`, and either
`IsIntegrallyClosed` or `NormalDomain`. If we use `NormalDomain` then `IsReduced` is automatic,
but we could also consider a version of `NormalDomain` that only requires the localizations are
`IsIntegrallyClosed` but may not be domains, and that may not equivalent to the ring itself being
`IsIntegallyClosed` (even for noetherian rings?).
-/
open scoped nonZeroDivisors Polynomial
open Polynomial
/-- `R` is integrally closed in `A` if all integral elements of `A` are also elements of `R`.
-/
abbrev IsIntegrallyClosedIn (R A : Type*) [CommRing R] [CommRing A] [Algebra R A] :=
IsIntegralClosure R R A
/-- `R` is integrally closed if all integral elements of `Frac(R)` are also elements of `R`.
This definition uses `FractionRing R` to denote `Frac(R)`. See `isIntegrallyClosed_iff`
if you want to choose another field of fractions for `R`.
-/
abbrev IsIntegrallyClosed (R : Type*) [CommRing R] := IsIntegrallyClosedIn R (FractionRing R)
#align is_integrally_closed IsIntegrallyClosed
section Iff
variable {R : Type*} [CommRing R]
variable {A B : Type*} [CommRing A] [CommRing B] [Algebra R A] [Algebra R B]
/-- Being integrally closed is preserved under injective algebra homomorphisms. -/
| Mathlib/RingTheory/IntegrallyClosed.lean | 80 | 90 | theorem AlgHom.isIntegrallyClosedIn (f : A →ₐ[R] B) (hf : Function.Injective f) :
IsIntegrallyClosedIn R B → IsIntegrallyClosedIn R A := by |
rintro ⟨inj, cl⟩
refine ⟨Function.Injective.of_comp (f := f) ?_, fun hx => ?_, ?_⟩
· convert inj
aesop
· obtain ⟨y, fx_eq⟩ := cl.mp ((isIntegral_algHom_iff f hf).mpr hx)
aesop
· rintro ⟨y, rfl⟩
apply (isIntegral_algHom_iff f hf).mp
aesop
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nathaniel Thomas, Jeremy Avigad, Johannes Hölzl, Mario Carneiro, Anne Baanen,
Frédéric Dupuis, Heather Macbeth
-/
import Mathlib.Algebra.Module.Basic
import Mathlib.Algebra.Module.Pi
import Mathlib.Algebra.Ring.CompTypeclasses
import Mathlib.Algebra.Star.Basic
import Mathlib.GroupTheory.GroupAction.DomAct.Basic
import Mathlib.GroupTheory.GroupAction.Hom
#align_import algebra.module.linear_map from "leanprover-community/mathlib"@"cc8e88c7c8c7bc80f91f84d11adb584bf9bd658f"
/-!
# (Semi)linear maps
In this file we define
* `LinearMap σ M M₂`, `M →ₛₗ[σ] M₂` : a semilinear map between two `Module`s. Here,
`σ` is a `RingHom` from `R` to `R₂` and an `f : M →ₛₗ[σ] M₂` satisfies
`f (c • x) = (σ c) • (f x)`. We recover plain linear maps by choosing `σ` to be `RingHom.id R`.
This is denoted by `M →ₗ[R] M₂`. We also add the notation `M →ₗ⋆[R] M₂` for star-linear maps.
* `IsLinearMap R f` : predicate saying that `f : M → M₂` is a linear map. (Note that this
was not generalized to semilinear maps.)
We then provide `LinearMap` with the following instances:
* `LinearMap.addCommMonoid` and `LinearMap.addCommGroup`: the elementwise addition structures
corresponding to addition in the codomain
* `LinearMap.distribMulAction` and `LinearMap.module`: the elementwise scalar action structures
corresponding to applying the action in the codomain.
## Implementation notes
To ensure that composition works smoothly for semilinear maps, we use the typeclasses
`RingHomCompTriple`, `RingHomInvPair` and `RingHomSurjective` from
`Mathlib.Algebra.Ring.CompTypeclasses`.
## Notation
* Throughout the file, we denote regular linear maps by `fₗ`, `gₗ`, etc, and semilinear maps
by `f`, `g`, etc.
## TODO
* Parts of this file have not yet been generalized to semilinear maps (i.e. `CompatibleSMul`)
## Tags
linear map
-/
assert_not_exists Submonoid
assert_not_exists Finset
open Function
universe u u' v w x y z
variable {R R₁ R₂ R₃ k S S₃ T M M₁ M₂ M₃ N₁ N₂ N₃ ι : Type*}
/-- A map `f` between modules over a semiring is linear if it satisfies the two properties
`f (x + y) = f x + f y` and `f (c • x) = c • f x`. The predicate `IsLinearMap R f` asserts this
property. A bundled version is available with `LinearMap`, and should be favored over
`IsLinearMap` most of the time. -/
structure IsLinearMap (R : Type u) {M : Type v} {M₂ : Type w} [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂] (f : M → M₂) : Prop where
/-- A linear map preserves addition. -/
map_add : ∀ x y, f (x + y) = f x + f y
/-- A linear map preserves scalar multiplication. -/
map_smul : ∀ (c : R) (x), f (c • x) = c • f x
#align is_linear_map IsLinearMap
section
/-- A map `f` between an `R`-module and an `S`-module over a ring homomorphism `σ : R →+* S`
is semilinear if it satisfies the two properties `f (x + y) = f x + f y` and
`f (c • x) = (σ c) • f x`. Elements of `LinearMap σ M M₂` (available under the notation
`M →ₛₗ[σ] M₂`) are bundled versions of such maps. For plain linear maps (i.e. for which
`σ = RingHom.id R`), the notation `M →ₗ[R] M₂` is available. An unbundled version of plain linear
maps is available with the predicate `IsLinearMap`, but it should be avoided most of the time. -/
structure LinearMap {R S : Type*} [Semiring R] [Semiring S] (σ : R →+* S) (M : Type*)
(M₂ : Type*) [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂] extends
AddHom M M₂, MulActionHom σ M M₂
#align linear_map LinearMap
/-- The `MulActionHom` underlying a `LinearMap`. -/
add_decl_doc LinearMap.toMulActionHom
/-- The `AddHom` underlying a `LinearMap`. -/
add_decl_doc LinearMap.toAddHom
#align linear_map.to_add_hom LinearMap.toAddHom
/-- `M →ₛₗ[σ] N` is the type of `σ`-semilinear maps from `M` to `N`. -/
notation:25 M " →ₛₗ[" σ:25 "] " M₂:0 => LinearMap σ M M₂
/-- `M →ₗ[R] N` is the type of `R`-linear maps from `M` to `N`. -/
notation:25 M " →ₗ[" R:25 "] " M₂:0 => LinearMap (RingHom.id R) M M₂
/-- `M →ₗ⋆[R] N` is the type of `R`-conjugate-linear maps from `M` to `N`. -/
notation:25 M " →ₗ⋆[" R:25 "] " M₂:0 => LinearMap (starRingEnd R) M M₂
/-- `SemilinearMapClass F σ M M₂` asserts `F` is a type of bundled `σ`-semilinear maps `M → M₂`.
See also `LinearMapClass F R M M₂` for the case where `σ` is the identity map on `R`.
A map `f` between an `R`-module and an `S`-module over a ring homomorphism `σ : R →+* S`
is semilinear if it satisfies the two properties `f (x + y) = f x + f y` and
`f (c • x) = (σ c) • f x`. -/
class SemilinearMapClass (F : Type*) {R S : outParam Type*} [Semiring R] [Semiring S]
(σ : outParam (R →+* S)) (M M₂ : outParam Type*) [AddCommMonoid M] [AddCommMonoid M₂]
[Module R M] [Module S M₂] [FunLike F M M₂]
extends AddHomClass F M M₂, MulActionSemiHomClass F σ M M₂ : Prop
#align semilinear_map_class SemilinearMapClass
end
-- Porting note: `dangerousInstance` linter has become smarter about `outParam`s
-- `σ` becomes a metavariable but that's fine because it's an `outParam`
-- attribute [nolint dangerousInstance] SemilinearMapClass.toAddHomClass
-- `map_smulₛₗ` should be `@[simp]` but doesn't fire due to `lean4#3701`.
-- attribute [simp] map_smulₛₗ
/-- `LinearMapClass F R M M₂` asserts `F` is a type of bundled `R`-linear maps `M → M₂`.
This is an abbreviation for `SemilinearMapClass F (RingHom.id R) M M₂`.
-/
abbrev LinearMapClass (F : Type*) (R : outParam Type*) (M M₂ : Type*)
[Semiring R] [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module R M₂]
[FunLike F M M₂] :=
SemilinearMapClass F (RingHom.id R) M M₂
#align linear_map_class LinearMapClass
@[simp high]
protected lemma LinearMapClass.map_smul {R M M₂ : outParam Type*} [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂]
{F : Type*} [FunLike F M M₂] [LinearMapClass F R M M₂] (f : F) (r : R) (x : M) :
f (r • x) = r • f x := by rw [_root_.map_smul]
namespace SemilinearMapClass
variable (F : Type*)
variable [Semiring R] [Semiring S]
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable [Module R M] [Module R M₂] [Module S M₃]
variable {σ : R →+* S}
-- Porting note: the `dangerousInstance` linter has become smarter about `outParam`s
instance (priority := 100) instAddMonoidHomClass [FunLike F M M₃] [SemilinearMapClass F σ M M₃] :
AddMonoidHomClass F M M₃ :=
{ SemilinearMapClass.toAddHomClass with
map_zero := fun f ↦
show f 0 = 0 by
rw [← zero_smul R (0 : M), map_smulₛₗ]
simp }
instance (priority := 100) distribMulActionSemiHomClass
[FunLike F M M₃] [SemilinearMapClass F σ M M₃] :
DistribMulActionSemiHomClass F σ M M₃ :=
{ SemilinearMapClass.toAddHomClass with
map_smulₛₗ := fun f c x ↦ by rw [map_smulₛₗ] }
variable {F} (f : F) [FunLike F M M₃] [SemilinearMapClass F σ M M₃]
theorem map_smul_inv {σ' : S →+* R} [RingHomInvPair σ σ'] (c : S) (x : M) :
c • f x = f (σ' c • x) := by simp [map_smulₛₗ _]
#align semilinear_map_class.map_smul_inv SemilinearMapClass.map_smul_inv
/-- Reinterpret an element of a type of semilinear maps as a semilinear map. -/
@[coe]
def semilinearMap : M →ₛₗ[σ] M₃ where
toFun := f
map_add' := map_add f
map_smul' := map_smulₛₗ f
/-- Reinterpret an element of a type of semilinear maps as a semilinear map. -/
instance instCoeToSemilinearMap : CoeHead F (M →ₛₗ[σ] M₃) where
coe f := semilinearMap f
end SemilinearMapClass
namespace LinearMapClass
variable {F : Type*} [Semiring R] [AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁] [Module R M₂]
(f : F) [FunLike F M₁ M₂] [LinearMapClass F R M₁ M₂]
/-- Reinterpret an element of a type of linear maps as a linear map. -/
abbrev linearMap : M₁ →ₗ[R] M₂ := SemilinearMapClass.semilinearMap f
/-- Reinterpret an element of a type of linear maps as a linear map. -/
instance instCoeToLinearMap : CoeHead F (M₁ →ₗ[R] M₂) where
coe f := SemilinearMapClass.semilinearMap f
end LinearMapClass
namespace LinearMap
section AddCommMonoid
variable [Semiring R] [Semiring S]
section
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable [AddCommMonoid N₁] [AddCommMonoid N₂] [AddCommMonoid N₃]
variable [Module R M] [Module R M₂] [Module S M₃]
variable {σ : R →+* S}
instance instFunLike : FunLike (M →ₛₗ[σ] M₃) M M₃ where
coe f := f.toFun
coe_injective' f g h := by
cases f
cases g
congr
apply DFunLike.coe_injective'
exact h
instance semilinearMapClass : SemilinearMapClass (M →ₛₗ[σ] M₃) σ M M₃ where
map_add f := f.map_add'
map_smulₛₗ := LinearMap.map_smul'
#align linear_map.semilinear_map_class LinearMap.semilinearMapClass
-- Porting note: we don't port specialized `CoeFun` instances if there is `DFunLike` instead
#noalign LinearMap.has_coe_to_fun
/-- The `DistribMulActionHom` underlying a `LinearMap`. -/
def toDistribMulActionHom (f : M →ₛₗ[σ] M₃) : DistribMulActionHom σ.toMonoidHom M M₃ :=
{ f with map_zero' := show f 0 = 0 from map_zero f }
#align linear_map.to_distrib_mul_action_hom LinearMap.toDistribMulActionHom
@[simp]
theorem coe_toAddHom (f : M →ₛₗ[σ] M₃) : ⇑f.toAddHom = f := rfl
-- Porting note: no longer a `simp`
theorem toFun_eq_coe {f : M →ₛₗ[σ] M₃} : f.toFun = (f : M → M₃) := rfl
#align linear_map.to_fun_eq_coe LinearMap.toFun_eq_coe
@[ext]
theorem ext {f g : M →ₛₗ[σ] M₃} (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
#align linear_map.ext LinearMap.ext
/-- Copy of a `LinearMap` with a new `toFun` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (f : M →ₛₗ[σ] M₃) (f' : M → M₃) (h : f' = ⇑f) : M →ₛₗ[σ] M₃ where
toFun := f'
map_add' := h.symm ▸ f.map_add'
map_smul' := h.symm ▸ f.map_smul'
#align linear_map.copy LinearMap.copy
@[simp]
theorem coe_copy (f : M →ₛₗ[σ] M₃) (f' : M → M₃) (h : f' = ⇑f) : ⇑(f.copy f' h) = f' :=
rfl
#align linear_map.coe_copy LinearMap.coe_copy
theorem copy_eq (f : M →ₛₗ[σ] M₃) (f' : M → M₃) (h : f' = ⇑f) : f.copy f' h = f :=
DFunLike.ext' h
#align linear_map.copy_eq LinearMap.copy_eq
initialize_simps_projections LinearMap (toFun → apply)
@[simp]
theorem coe_mk {σ : R →+* S} (f : AddHom M M₃) (h) :
((LinearMap.mk f h : M →ₛₗ[σ] M₃) : M → M₃) = f :=
rfl
#align linear_map.coe_mk LinearMap.coe_mk
-- Porting note: This theorem is new.
@[simp]
theorem coe_addHom_mk {σ : R →+* S} (f : AddHom M M₃) (h) :
((LinearMap.mk f h : M →ₛₗ[σ] M₃) : AddHom M M₃) = f :=
rfl
theorem coe_semilinearMap {F : Type*} [FunLike F M M₃] [SemilinearMapClass F σ M M₃] (f : F) :
((f : M →ₛₗ[σ] M₃) : M → M₃) = f :=
rfl
theorem toLinearMap_injective {F : Type*} [FunLike F M M₃] [SemilinearMapClass F σ M M₃]
{f g : F} (h : (f : M →ₛₗ[σ] M₃) = (g : M →ₛₗ[σ] M₃)) :
f = g := by
apply DFunLike.ext
intro m
exact DFunLike.congr_fun h m
/-- Identity map as a `LinearMap` -/
def id : M →ₗ[R] M :=
{ DistribMulActionHom.id R with toFun := _root_.id }
#align linear_map.id LinearMap.id
theorem id_apply (x : M) : @id R M _ _ _ x = x :=
rfl
#align linear_map.id_apply LinearMap.id_apply
@[simp, norm_cast]
theorem id_coe : ((LinearMap.id : M →ₗ[R] M) : M → M) = _root_.id :=
rfl
#align linear_map.id_coe LinearMap.id_coe
/-- A generalisation of `LinearMap.id` that constructs the identity function
as a `σ`-semilinear map for any ring homomorphism `σ` which we know is the identity. -/
@[simps]
def id' {σ : R →+* R} [RingHomId σ] : M →ₛₗ[σ] M where
toFun x := x
map_add' x y := rfl
map_smul' r x := by
have := (RingHomId.eq_id : σ = _)
subst this
rfl
@[simp, norm_cast]
theorem id'_coe {σ : R →+* R} [RingHomId σ] : ((id' : M →ₛₗ[σ] M) : M → M) = _root_.id :=
rfl
end
section
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable [AddCommMonoid N₁] [AddCommMonoid N₂] [AddCommMonoid N₃]
variable [Module R M] [Module R M₂] [Module S M₃]
variable (σ : R →+* S)
variable (fₗ gₗ : M →ₗ[R] M₂) (f g : M →ₛₗ[σ] M₃)
theorem isLinear : IsLinearMap R fₗ :=
⟨fₗ.map_add', fₗ.map_smul'⟩
#align linear_map.is_linear LinearMap.isLinear
variable {fₗ gₗ f g σ}
theorem coe_injective : Injective (DFunLike.coe : (M →ₛₗ[σ] M₃) → _) :=
DFunLike.coe_injective
#align linear_map.coe_injective LinearMap.coe_injective
protected theorem congr_arg {x x' : M} : x = x' → f x = f x' :=
DFunLike.congr_arg f
#align linear_map.congr_arg LinearMap.congr_arg
/-- If two linear maps are equal, they are equal at each point. -/
protected theorem congr_fun (h : f = g) (x : M) : f x = g x :=
DFunLike.congr_fun h x
#align linear_map.congr_fun LinearMap.congr_fun
theorem ext_iff : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align linear_map.ext_iff LinearMap.ext_iff
@[simp]
theorem mk_coe (f : M →ₛₗ[σ] M₃) (h) : (LinearMap.mk f h : M →ₛₗ[σ] M₃) = f :=
ext fun _ ↦ rfl
#align linear_map.mk_coe LinearMap.mk_coe
variable (fₗ gₗ f g)
protected theorem map_add (x y : M) : f (x + y) = f x + f y :=
map_add f x y
#align linear_map.map_add LinearMap.map_add
protected theorem map_zero : f 0 = 0 :=
map_zero f
#align linear_map.map_zero LinearMap.map_zero
-- Porting note: `simp` wasn't picking up `map_smulₛₗ` for `LinearMap`s without specifying
-- `map_smulₛₗ f`, so we marked this as `@[simp]` in Mathlib3.
-- For Mathlib4, let's try without the `@[simp]` attribute and hope it won't need to be re-enabled.
-- This has to be re-tagged as `@[simp]` in #8386 (see also leanprover/lean4#3107).
@[simp]
protected theorem map_smulₛₗ (c : R) (x : M) : f (c • x) = σ c • f x :=
map_smulₛₗ f c x
#align linear_map.map_smulₛₗ LinearMap.map_smulₛₗ
protected theorem map_smul (c : R) (x : M) : fₗ (c • x) = c • fₗ x :=
map_smul fₗ c x
#align linear_map.map_smul LinearMap.map_smul
protected theorem map_smul_inv {σ' : S →+* R} [RingHomInvPair σ σ'] (c : S) (x : M) :
c • f x = f (σ' c • x) := by simp
#align linear_map.map_smul_inv LinearMap.map_smul_inv
@[simp]
theorem map_eq_zero_iff (h : Function.Injective f) {x : M} : f x = 0 ↔ x = 0 :=
_root_.map_eq_zero_iff f h
#align linear_map.map_eq_zero_iff LinearMap.map_eq_zero_iff
variable (M M₂)
/-- A typeclass for `SMul` structures which can be moved through a `LinearMap`.
This typeclass is generated automatically from an `IsScalarTower` instance, but exists so that
we can also add an instance for `AddCommGroup.intModule`, allowing `z •` to be moved even if
`S` does not support negation.
-/
class CompatibleSMul (R S : Type*) [Semiring S] [SMul R M] [Module S M] [SMul R M₂]
[Module S M₂] : Prop where
/-- Scalar multiplication by `R` of `M` can be moved through linear maps. -/
map_smul : ∀ (fₗ : M →ₗ[S] M₂) (c : R) (x : M), fₗ (c • x) = c • fₗ x
#align linear_map.compatible_smul LinearMap.CompatibleSMul
variable {M M₂}
section
variable {R S : Type*} [Semiring S] [SMul R M] [Module S M] [SMul R M₂] [Module S M₂]
instance (priority := 100) IsScalarTower.compatibleSMul [SMul R S]
[IsScalarTower R S M] [IsScalarTower R S M₂] :
CompatibleSMul M M₂ R S :=
⟨fun fₗ c x ↦ by rw [← smul_one_smul S c x, ← smul_one_smul S c (fₗ x), map_smul]⟩
#align linear_map.is_scalar_tower.compatible_smul LinearMap.IsScalarTower.compatibleSMul
instance IsScalarTower.compatibleSMul' [SMul R S] [IsScalarTower R S M] :
CompatibleSMul S M R S where
map_smul := (IsScalarTower.smulHomClass R S M (S →ₗ[S] M)).map_smulₛₗ
@[simp]
theorem map_smul_of_tower [CompatibleSMul M M₂ R S] (fₗ : M →ₗ[S] M₂) (c : R) (x : M) :
fₗ (c • x) = c • fₗ x :=
CompatibleSMul.map_smul fₗ c x
#align linear_map.map_smul_of_tower LinearMap.map_smul_of_tower
variable (R R) in
theorem isScalarTower_of_injective [SMul R S] [CompatibleSMul M M₂ R S] [IsScalarTower R S M₂]
(f : M →ₗ[S] M₂) (hf : Function.Injective f) : IsScalarTower R S M where
smul_assoc r s _ := hf <| by rw [f.map_smul_of_tower r, map_smul, map_smul, smul_assoc]
end
variable (R) in
theorem isLinearMap_of_compatibleSMul [Module S M] [Module S M₂] [CompatibleSMul M M₂ R S]
(f : M →ₗ[S] M₂) : IsLinearMap R f where
map_add := map_add f
map_smul := map_smul_of_tower f
/-- convert a linear map to an additive map -/
def toAddMonoidHom : M →+ M₃ where
toFun := f
map_zero' := f.map_zero
map_add' := f.map_add
#align linear_map.to_add_monoid_hom LinearMap.toAddMonoidHom
@[simp]
theorem toAddMonoidHom_coe : ⇑f.toAddMonoidHom = f :=
rfl
#align linear_map.to_add_monoid_hom_coe LinearMap.toAddMonoidHom_coe
section RestrictScalars
variable (R)
variable [Module S M] [Module S M₂] [CompatibleSMul M M₂ R S]
/-- If `M` and `M₂` are both `R`-modules and `S`-modules and `R`-module structures
are defined by an action of `R` on `S` (formally, we have two scalar towers), then any `S`-linear
map from `M` to `M₂` is `R`-linear.
See also `LinearMap.map_smul_of_tower`. -/
@[coe] def restrictScalars (fₗ : M →ₗ[S] M₂) : M →ₗ[R] M₂ where
toFun := fₗ
map_add' := fₗ.map_add
map_smul' := fₗ.map_smul_of_tower
#align linear_map.restrict_scalars LinearMap.restrictScalars
-- Porting note: generalized from `Algebra` to `CompatibleSMul`
instance coeIsScalarTower : CoeHTCT (M →ₗ[S] M₂) (M →ₗ[R] M₂) :=
⟨restrictScalars R⟩
#align linear_map.coe_is_scalar_tower LinearMap.coeIsScalarTower
@[simp, norm_cast]
theorem coe_restrictScalars (f : M →ₗ[S] M₂) : ((f : M →ₗ[R] M₂) : M → M₂) = f :=
rfl
#align linear_map.coe_restrict_scalars LinearMap.coe_restrictScalars
theorem restrictScalars_apply (fₗ : M →ₗ[S] M₂) (x) : restrictScalars R fₗ x = fₗ x :=
rfl
#align linear_map.restrict_scalars_apply LinearMap.restrictScalars_apply
theorem restrictScalars_injective :
Function.Injective (restrictScalars R : (M →ₗ[S] M₂) → M →ₗ[R] M₂) := fun _ _ h ↦
ext (LinearMap.congr_fun h : _)
#align linear_map.restrict_scalars_injective LinearMap.restrictScalars_injective
@[simp]
theorem restrictScalars_inj (fₗ gₗ : M →ₗ[S] M₂) :
fₗ.restrictScalars R = gₗ.restrictScalars R ↔ fₗ = gₗ :=
(restrictScalars_injective R).eq_iff
#align linear_map.restrict_scalars_inj LinearMap.restrictScalars_inj
end RestrictScalars
theorem toAddMonoidHom_injective :
Function.Injective (toAddMonoidHom : (M →ₛₗ[σ] M₃) → M →+ M₃) := fun fₗ gₗ h ↦
ext <| (DFunLike.congr_fun h : ∀ x, fₗ.toAddMonoidHom x = gₗ.toAddMonoidHom x)
#align linear_map.to_add_monoid_hom_injective LinearMap.toAddMonoidHom_injective
/-- If two `σ`-linear maps from `R` are equal on `1`, then they are equal. -/
@[ext high]
theorem ext_ring {f g : R →ₛₗ[σ] M₃} (h : f 1 = g 1) : f = g :=
ext fun x ↦ by rw [← mul_one x, ← smul_eq_mul, f.map_smulₛₗ, g.map_smulₛₗ, h]
#align linear_map.ext_ring LinearMap.ext_ring
theorem ext_ring_iff {σ : R →+* R} {f g : R →ₛₗ[σ] M} : f = g ↔ f 1 = g 1 :=
⟨fun h ↦ h ▸ rfl, ext_ring⟩
#align linear_map.ext_ring_iff LinearMap.ext_ring_iff
@[ext high]
theorem ext_ring_op {σ : Rᵐᵒᵖ →+* S} {f g : R →ₛₗ[σ] M₃} (h : f (1 : R) = g (1 : R)) :
f = g :=
ext fun x ↦ by
-- Porting note: replaced the oneliner `rw` proof with a partially term-mode proof
-- because `rw` was giving "motive is type incorrect" errors
rw [← one_mul x, ← op_smul_eq_mul]
refine (f.map_smulₛₗ (MulOpposite.op x) 1).trans ?_
rw [h]
exact (g.map_smulₛₗ (MulOpposite.op x) 1).symm
#align linear_map.ext_ring_op LinearMap.ext_ring_op
end
/-- Interpret a `RingHom` `f` as an `f`-semilinear map. -/
@[simps]
def _root_.RingHom.toSemilinearMap (f : R →+* S) : R →ₛₗ[f] S :=
{ f with
map_smul' := f.map_mul }
#align ring_hom.to_semilinear_map RingHom.toSemilinearMap
#align ring_hom.to_semilinear_map_apply RingHom.toSemilinearMap_apply
section
variable [Semiring R₁] [Semiring R₂] [Semiring R₃]
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable {module_M₁ : Module R₁ M₁} {module_M₂ : Module R₂ M₂} {module_M₃ : Module R₃ M₃}
variable {σ₁₂ : R₁ →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R₁ →+* R₃}
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
variable (f : M₂ →ₛₗ[σ₂₃] M₃) (g : M₁ →ₛₗ[σ₁₂] M₂)
/-- Composition of two linear maps is a linear map -/
def comp : M₁ →ₛₗ[σ₁₃] M₃ where
toFun := f ∘ g
map_add' := by simp only [map_add, forall_const, Function.comp_apply]
-- Note that #8386 changed `map_smulₛₗ` to `map_smulₛₗ _`
map_smul' r x := by simp only [Function.comp_apply, map_smulₛₗ _, RingHomCompTriple.comp_apply]
#align linear_map.comp LinearMap.comp
/-- `∘ₗ` is notation for composition of two linear (not semilinear!) maps into a linear map.
This is useful when Lean is struggling to infer the `RingHomCompTriple` instance. -/
notation3:80 (name := compNotation) f:81 " ∘ₗ " g:80 =>
@LinearMap.comp _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ (RingHom.id _) (RingHom.id _) (RingHom.id _)
RingHomCompTriple.ids f g
theorem comp_apply (x : M₁) : f.comp g x = f (g x) :=
rfl
#align linear_map.comp_apply LinearMap.comp_apply
@[simp, norm_cast]
theorem coe_comp : (f.comp g : M₁ → M₃) = f ∘ g :=
rfl
#align linear_map.coe_comp LinearMap.coe_comp
@[simp]
theorem comp_id : f.comp id = f :=
LinearMap.ext fun _ ↦ rfl
#align linear_map.comp_id LinearMap.comp_id
@[simp]
theorem id_comp : id.comp f = f :=
LinearMap.ext fun _ ↦ rfl
#align linear_map.id_comp LinearMap.id_comp
theorem comp_assoc
{R₄ M₄ : Type*} [Semiring R₄] [AddCommMonoid M₄] [Module R₄ M₄]
{σ₃₄ : R₃ →+* R₄} {σ₂₄ : R₂ →+* R₄} {σ₁₄ : R₁ →+* R₄}
[RingHomCompTriple σ₂₃ σ₃₄ σ₂₄] [RingHomCompTriple σ₁₃ σ₃₄ σ₁₄] [RingHomCompTriple σ₁₂ σ₂₄ σ₁₄]
(f : M₁ →ₛₗ[σ₁₂] M₂) (g : M₂ →ₛₗ[σ₂₃] M₃) (h : M₃ →ₛₗ[σ₃₄] M₄) :
((h.comp g : M₂ →ₛₗ[σ₂₄] M₄).comp f : M₁ →ₛₗ[σ₁₄] M₄) = h.comp (g.comp f : M₁ →ₛₗ[σ₁₃] M₃) :=
rfl
#align linear_map.comp_assoc LinearMap.comp_assoc
variable {f g} {f' : M₂ →ₛₗ[σ₂₃] M₃} {g' : M₁ →ₛₗ[σ₁₂] M₂}
/-- The linear map version of `Function.Surjective.injective_comp_right` -/
lemma _root_.Function.Surjective.injective_linearMapComp_right (hg : Surjective g) :
Injective fun f : M₂ →ₛₗ[σ₂₃] M₃ ↦ f.comp g :=
fun _ _ h ↦ ext <| hg.forall.2 (ext_iff.1 h)
@[simp]
theorem cancel_right (hg : Surjective g) : f.comp g = f'.comp g ↔ f = f' :=
hg.injective_linearMapComp_right.eq_iff
#align linear_map.cancel_right LinearMap.cancel_right
/-- The linear map version of `Function.Injective.comp_left` -/
lemma _root_.Function.Injective.injective_linearMapComp_left (hf : Injective f) :
Injective fun g : M₁ →ₛₗ[σ₁₂] M₂ ↦ f.comp g :=
fun g₁ g₂ (h : f.comp g₁ = f.comp g₂) ↦ ext fun x ↦ hf <| by rw [← comp_apply, h, comp_apply]
@[simp]
theorem cancel_left (hf : Injective f) : f.comp g = f.comp g' ↔ g = g' :=
hf.injective_linearMapComp_left.eq_iff
#align linear_map.cancel_left LinearMap.cancel_left
end
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
/-- If a function `g` is a left and right inverse of a linear map `f`, then `g` is linear itself. -/
def inverse [Module R M] [Module S M₂] {σ : R →+* S} {σ' : S →+* R} [RingHomInvPair σ σ']
(f : M →ₛₗ[σ] M₂) (g : M₂ → M) (h₁ : LeftInverse g f) (h₂ : RightInverse g f) :
M₂ →ₛₗ[σ'] M := by
dsimp [LeftInverse, Function.RightInverse] at h₁ h₂
exact
{ toFun := g
map_add' := fun x y ↦ by rw [← h₁ (g (x + y)), ← h₁ (g x + g y)]; simp [h₂]
map_smul' := fun a b ↦ by
dsimp only
rw [← h₁ (g (a • b)), ← h₁ (σ' a • g b)]
simp [h₂] }
#align linear_map.inverse LinearMap.inverse
end AddCommMonoid
section AddCommGroup
variable [Semiring R] [Semiring S] [AddCommGroup M] [AddCommGroup M₂]
variable {module_M : Module R M} {module_M₂ : Module S M₂} {σ : R →+* S}
variable (f : M →ₛₗ[σ] M₂)
protected theorem map_neg (x : M) : f (-x) = -f x :=
map_neg f x
#align linear_map.map_neg LinearMap.map_neg
protected theorem map_sub (x y : M) : f (x - y) = f x - f y :=
map_sub f x y
#align linear_map.map_sub LinearMap.map_sub
instance CompatibleSMul.intModule {S : Type*} [Semiring S] [Module S M] [Module S M₂] :
CompatibleSMul M M₂ ℤ S :=
⟨fun fₗ c x ↦ by
induction c using Int.induction_on with
| hz => simp
| hp n ih => simp [add_smul, ih]
| hn n ih => simp [sub_smul, ih]⟩
#align linear_map.compatible_smul.int_module LinearMap.CompatibleSMul.intModule
instance CompatibleSMul.units {R S : Type*} [Monoid R] [MulAction R M] [MulAction R M₂]
[Semiring S] [Module S M] [Module S M₂] [CompatibleSMul M M₂ R S] : CompatibleSMul M M₂ Rˣ S :=
⟨fun fₗ c x ↦ (CompatibleSMul.map_smul fₗ (c : R) x : _)⟩
#align linear_map.compatible_smul.units LinearMap.CompatibleSMul.units
end AddCommGroup
end LinearMap
namespace Module
/-- `g : R →+* S` is `R`-linear when the module structure on `S` is `Module.compHom S g` . -/
@[simps]
def compHom.toLinearMap {R S : Type*} [Semiring R] [Semiring S] (g : R →+* S) :
letI := compHom S g; R →ₗ[R] S :=
letI := compHom S g
{ toFun := (g : R → S)
map_add' := g.map_add
map_smul' := g.map_mul }
#align module.comp_hom.to_linear_map Module.compHom.toLinearMap
#align module.comp_hom.to_linear_map_apply Module.compHom.toLinearMap_apply
end Module
namespace DistribMulActionHom
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable [Semiring R] [Module R M] [Semiring S] [Module S M₂] [Module R M₃]
variable {σ : R →+* S}
/-- A `DistribMulActionHom` between two modules is a linear map. -/
@[coe]
def toSemilinearMap (fₗ : M →ₑ+[σ.toMonoidHom] M₂) : M →ₛₗ[σ] M₂ :=
{ fₗ with }
instance : SemilinearMapClass (M →ₑ+[σ.toMonoidHom] M₂) σ M M₂ where
instance instCoeTCSemilinearMap : CoeTC (M →ₑ+[σ.toMonoidHom] M₂) (M →ₛₗ[σ] M₂) :=
⟨toSemilinearMap⟩
/-- A `DistribMulActionHom` between two modules is a linear map. -/
def toLinearMap (fₗ : M →+[R] M₃) : M →ₗ[R] M₃ :=
{ fₗ with }
#align distrib_mul_action_hom.to_linear_map DistribMulActionHom.toLinearMap
instance instCoeTCLinearMap : CoeTC (M →+[R] M₃) (M →ₗ[R] M₃) :=
⟨toLinearMap⟩
/-- A `DistribMulActionHom` between two modules is a linear map. -/
instance : LinearMapClass (M →+[R] M₃) R M M₃ where
-- Porting note: because coercions get unfolded, there is no need for this rewrite
#noalign distrib_mul_action_hom.to_linear_map_eq_coe
-- Porting note: removed @[norm_cast] attribute due to error:
-- norm_cast: badly shaped lemma, rhs can't start with coe
@[simp]
theorem coe_toLinearMap (f : M →ₑ+[σ.toMonoidHom] M₂) : ((f : M →ₛₗ[σ] M₂) : M → M₂) = f :=
rfl
#align distrib_mul_action_hom.coe_to_linear_map DistribMulActionHom.coe_toLinearMap
theorem toLinearMap_injective {f g : M →ₑ+[σ.toMonoidHom] M₂}
(h : (f : M →ₛₗ[σ] M₂) = (g : M →ₛₗ[σ] M₂)) :
f = g := by
ext m
exact LinearMap.congr_fun h m
#align distrib_mul_action_hom.to_linear_map_injective DistribMulActionHom.toLinearMap_injective
end DistribMulActionHom
namespace IsLinearMap
section AddCommMonoid
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid M₂]
variable [Module R M] [Module R M₂]
/-- Convert an `IsLinearMap` predicate to a `LinearMap` -/
def mk' (f : M → M₂) (H : IsLinearMap R f) : M →ₗ[R] M₂ where
toFun := f
map_add' := H.1
map_smul' := H.2
#align is_linear_map.mk' IsLinearMap.mk'
@[simp]
theorem mk'_apply {f : M → M₂} (H : IsLinearMap R f) (x : M) : mk' f H x = f x :=
rfl
#align is_linear_map.mk'_apply IsLinearMap.mk'_apply
theorem isLinearMap_smul {R M : Type*} [CommSemiring R] [AddCommMonoid M] [Module R M] (c : R) :
IsLinearMap R fun z : M ↦ c • z := by
refine IsLinearMap.mk (smul_add c) ?_
intro _ _
simp only [smul_smul, mul_comm]
#align is_linear_map.is_linear_map_smul IsLinearMap.isLinearMap_smul
theorem isLinearMap_smul' {R M : Type*} [Semiring R] [AddCommMonoid M] [Module R M] (a : M) :
IsLinearMap R fun c : R ↦ c • a :=
IsLinearMap.mk (fun x y ↦ add_smul x y a) fun x y ↦ mul_smul x y a
#align is_linear_map.is_linear_map_smul' IsLinearMap.isLinearMap_smul'
variable {f : M → M₂} (lin : IsLinearMap R f)
theorem map_zero : f (0 : M) = (0 : M₂) :=
(lin.mk' f).map_zero
#align is_linear_map.map_zero IsLinearMap.map_zero
end AddCommMonoid
section AddCommGroup
variable [Semiring R] [AddCommGroup M] [AddCommGroup M₂]
variable [Module R M] [Module R M₂]
theorem isLinearMap_neg : IsLinearMap R fun z : M ↦ -z :=
IsLinearMap.mk neg_add fun x y ↦ (smul_neg x y).symm
#align is_linear_map.is_linear_map_neg IsLinearMap.isLinearMap_neg
variable {f : M → M₂} (lin : IsLinearMap R f)
theorem map_neg (x : M) : f (-x) = -f x :=
(lin.mk' f).map_neg x
#align is_linear_map.map_neg IsLinearMap.map_neg
theorem map_sub (x y) : f (x - y) = f x - f y :=
(lin.mk' f).map_sub x y
#align is_linear_map.map_sub IsLinearMap.map_sub
end AddCommGroup
end IsLinearMap
/-- Reinterpret an additive homomorphism as an `ℕ`-linear map. -/
def AddMonoidHom.toNatLinearMap [AddCommMonoid M] [AddCommMonoid M₂] (f : M →+ M₂) :
M →ₗ[ℕ] M₂ where
toFun := f
map_add' := f.map_add
map_smul' := map_nsmul f
#align add_monoid_hom.to_nat_linear_map AddMonoidHom.toNatLinearMap
| Mathlib/Algebra/Module/LinearMap/Basic.lean | 784 | 788 | theorem AddMonoidHom.toNatLinearMap_injective [AddCommMonoid M] [AddCommMonoid M₂] :
Function.Injective (@AddMonoidHom.toNatLinearMap M M₂ _ _) := by |
intro f g h
ext x
exact LinearMap.congr_fun h x
|
/-
Copyright (c) 2020 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot
-/
import Mathlib.Topology.Order.ProjIcc
import Mathlib.Topology.CompactOpen
import Mathlib.Topology.UnitInterval
#align_import topology.path_connected from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Path connectedness
## Main definitions
In the file the unit interval `[0, 1]` in `ℝ` is denoted by `I`, and `X` is a topological space.
* `Path (x y : X)` is the type of paths from `x` to `y`, i.e., continuous maps from `I` to `X`
mapping `0` to `x` and `1` to `y`.
* `Path.map` is the image of a path under a continuous map.
* `Joined (x y : X)` means there is a path between `x` and `y`.
* `Joined.somePath (h : Joined x y)` selects some path between two points `x` and `y`.
* `pathComponent (x : X)` is the set of points joined to `x`.
* `PathConnectedSpace X` is a predicate class asserting that `X` is non-empty and every two
points of `X` are joined.
Then there are corresponding relative notions for `F : Set X`.
* `JoinedIn F (x y : X)` means there is a path `γ` joining `x` to `y` with values in `F`.
* `JoinedIn.somePath (h : JoinedIn F x y)` selects a path from `x` to `y` inside `F`.
* `pathComponentIn F (x : X)` is the set of points joined to `x` in `F`.
* `IsPathConnected F` asserts that `F` is non-empty and every two
points of `F` are joined in `F`.
* `LocPathConnectedSpace X` is a predicate class asserting that `X` is locally path-connected:
each point has a basis of path-connected neighborhoods (we do *not* ask these to be open).
## Main theorems
* `Joined` and `JoinedIn F` are transitive relations.
One can link the absolute and relative version in two directions, using `(univ : Set X)` or the
subtype `↥F`.
* `pathConnectedSpace_iff_univ : PathConnectedSpace X ↔ IsPathConnected (univ : Set X)`
* `isPathConnected_iff_pathConnectedSpace : IsPathConnected F ↔ PathConnectedSpace ↥F`
For locally path connected spaces, we have
* `pathConnectedSpace_iff_connectedSpace : PathConnectedSpace X ↔ ConnectedSpace X`
* `IsOpen.isConnected_iff_isPathConnected (U_op : IsOpen U) : IsPathConnected U ↔ IsConnected U`
## Implementation notes
By default, all paths have `I` as their source and `X` as their target, but there is an
operation `Set.IccExtend` that will extend any continuous map `γ : I → X` into a continuous map
`IccExtend zero_le_one γ : ℝ → X` that is constant before `0` and after `1`.
This is used to define `Path.extend` that turns `γ : Path x y` into a continuous map
`γ.extend : ℝ → X` whose restriction to `I` is the original `γ`, and is equal to `x`
on `(-∞, 0]` and to `y` on `[1, +∞)`.
-/
noncomputable section
open scoped Classical
open Topology Filter unitInterval Set Function
variable {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {x y z : X} {ι : Type*}
/-! ### Paths -/
/-- Continuous path connecting two points `x` and `y` in a topological space -/
-- porting note (#5171): removed @[nolint has_nonempty_instance]
structure Path (x y : X) extends C(I, X) where
/-- The start point of a `Path`. -/
source' : toFun 0 = x
/-- The end point of a `Path`. -/
target' : toFun 1 = y
#align path Path
instance Path.funLike : FunLike (Path x y) I X where
coe := fun γ ↦ ⇑γ.toContinuousMap
coe_injective' := fun γ₁ γ₂ h => by
simp only [DFunLike.coe_fn_eq] at h
cases γ₁; cases γ₂; congr
-- Porting note (#10754): added this instance so that we can use `FunLike.coe` for `CoeFun`
-- this also fixed very strange `simp` timeout issues
instance Path.continuousMapClass : ContinuousMapClass (Path x y) I X where
map_continuous := fun γ => show Continuous γ.toContinuousMap by continuity
-- Porting note: not necessary in light of the instance above
/-
instance : CoeFun (Path x y) fun _ => I → X :=
⟨fun p => p.toFun⟩
-/
@[ext]
protected theorem Path.ext : ∀ {γ₁ γ₂ : Path x y}, (γ₁ : I → X) = γ₂ → γ₁ = γ₂ := by
rintro ⟨⟨x, h11⟩, h12, h13⟩ ⟨⟨x, h21⟩, h22, h23⟩ rfl
rfl
#align path.ext Path.ext
namespace Path
@[simp]
theorem coe_mk_mk (f : I → X) (h₁) (h₂ : f 0 = x) (h₃ : f 1 = y) :
⇑(mk ⟨f, h₁⟩ h₂ h₃ : Path x y) = f :=
rfl
#align path.coe_mk Path.coe_mk_mk
-- Porting note: the name `Path.coe_mk` better refers to a new lemma below
variable (γ : Path x y)
@[continuity]
protected theorem continuous : Continuous γ :=
γ.continuous_toFun
#align path.continuous Path.continuous
@[simp]
protected theorem source : γ 0 = x :=
γ.source'
#align path.source Path.source
@[simp]
protected theorem target : γ 1 = y :=
γ.target'
#align path.target Path.target
/-- See Note [custom simps projection]. We need to specify this projection explicitly in this case,
because it is a composition of multiple projections. -/
def simps.apply : I → X :=
γ
#align path.simps.apply Path.simps.apply
initialize_simps_projections Path (toFun → simps.apply, -toContinuousMap)
@[simp]
theorem coe_toContinuousMap : ⇑γ.toContinuousMap = γ :=
rfl
#align path.coe_to_continuous_map Path.coe_toContinuousMap
-- Porting note: this is needed because of the `Path.continuousMapClass` instance
@[simp]
theorem coe_mk : ⇑(γ : C(I, X)) = γ :=
rfl
/-- Any function `φ : Π (a : α), Path (x a) (y a)` can be seen as a function `α × I → X`. -/
instance hasUncurryPath {X α : Type*} [TopologicalSpace X] {x y : α → X} :
HasUncurry (∀ a : α, Path (x a) (y a)) (α × I) X :=
⟨fun φ p => φ p.1 p.2⟩
#align path.has_uncurry_path Path.hasUncurryPath
/-- The constant path from a point to itself -/
@[refl, simps]
def refl (x : X) : Path x x where
toFun _t := x
continuous_toFun := continuous_const
source' := rfl
target' := rfl
#align path.refl Path.refl
@[simp]
theorem refl_range {a : X} : range (Path.refl a) = {a} := by simp [Path.refl, CoeFun.coe]
#align path.refl_range Path.refl_range
/-- The reverse of a path from `x` to `y`, as a path from `y` to `x` -/
@[symm, simps]
def symm (γ : Path x y) : Path y x where
toFun := γ ∘ σ
continuous_toFun := by continuity
source' := by simpa [-Path.target] using γ.target
target' := by simpa [-Path.source] using γ.source
#align path.symm Path.symm
@[simp]
theorem symm_symm (γ : Path x y) : γ.symm.symm = γ := by
ext t
show γ (σ (σ t)) = γ t
rw [unitInterval.symm_symm]
#align path.symm_symm Path.symm_symm
theorem symm_bijective : Function.Bijective (Path.symm : Path x y → Path y x) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
@[simp]
theorem refl_symm {a : X} : (Path.refl a).symm = Path.refl a := by
ext
rfl
#align path.refl_symm Path.refl_symm
@[simp]
theorem symm_range {a b : X} (γ : Path a b) : range γ.symm = range γ := by
ext x
simp only [mem_range, Path.symm, DFunLike.coe, unitInterval.symm, SetCoe.exists, comp_apply,
Subtype.coe_mk]
constructor <;> rintro ⟨y, hy, hxy⟩ <;> refine ⟨1 - y, mem_iff_one_sub_mem.mp hy, ?_⟩ <;>
convert hxy
simp
#align path.symm_range Path.symm_range
/-! #### Space of paths -/
open ContinuousMap
/- porting note: because of the `DFunLike` instance, we already have a coercion to `C(I, X)`
so we avoid adding another.
--instance : Coe (Path x y) C(I, X) :=
--⟨fun γ => γ.1⟩
-/
/-- The following instance defines the topology on the path space to be induced from the
compact-open topology on the space `C(I,X)` of continuous maps from `I` to `X`.
-/
instance topologicalSpace : TopologicalSpace (Path x y) :=
TopologicalSpace.induced ((↑) : _ → C(I, X)) ContinuousMap.compactOpen
theorem continuous_eval : Continuous fun p : Path x y × I => p.1 p.2 :=
continuous_eval.comp <| (continuous_induced_dom (α := Path x y)).prod_map continuous_id
#align path.continuous_eval Path.continuous_eval
@[continuity]
theorem _root_.Continuous.path_eval {Y} [TopologicalSpace Y] {f : Y → Path x y} {g : Y → I}
(hf : Continuous f) (hg : Continuous g) : Continuous fun y => f y (g y) :=
Continuous.comp continuous_eval (hf.prod_mk hg)
#align continuous.path_eval Continuous.path_eval
theorem continuous_uncurry_iff {Y} [TopologicalSpace Y] {g : Y → Path x y} :
Continuous ↿g ↔ Continuous g :=
Iff.symm <| continuous_induced_rng.trans
⟨fun h => continuous_uncurry_of_continuous ⟨_, h⟩,
continuous_of_continuous_uncurry (fun (y : Y) ↦ ContinuousMap.mk (g y))⟩
#align path.continuous_uncurry_iff Path.continuous_uncurry_iff
/-- A continuous map extending a path to `ℝ`, constant before `0` and after `1`. -/
def extend : ℝ → X :=
IccExtend zero_le_one γ
#align path.extend Path.extend
/-- See Note [continuity lemma statement]. -/
theorem _root_.Continuous.path_extend {γ : Y → Path x y} {f : Y → ℝ} (hγ : Continuous ↿γ)
(hf : Continuous f) : Continuous fun t => (γ t).extend (f t) :=
Continuous.IccExtend hγ hf
#align continuous.path_extend Continuous.path_extend
/-- A useful special case of `Continuous.path_extend`. -/
@[continuity]
theorem continuous_extend : Continuous γ.extend :=
γ.continuous.Icc_extend'
#align path.continuous_extend Path.continuous_extend
theorem _root_.Filter.Tendsto.path_extend
{l r : Y → X} {y : Y} {l₁ : Filter ℝ} {l₂ : Filter X} {γ : ∀ y, Path (l y) (r y)}
(hγ : Tendsto (↿γ) (𝓝 y ×ˢ l₁.map (projIcc 0 1 zero_le_one)) l₂) :
Tendsto (↿fun x => (γ x).extend) (𝓝 y ×ˢ l₁) l₂ :=
Filter.Tendsto.IccExtend _ hγ
#align filter.tendsto.path_extend Filter.Tendsto.path_extend
theorem _root_.ContinuousAt.path_extend {g : Y → ℝ} {l r : Y → X} (γ : ∀ y, Path (l y) (r y))
{y : Y} (hγ : ContinuousAt (↿γ) (y, projIcc 0 1 zero_le_one (g y))) (hg : ContinuousAt g y) :
ContinuousAt (fun i => (γ i).extend (g i)) y :=
hγ.IccExtend (fun x => γ x) hg
#align continuous_at.path_extend ContinuousAt.path_extend
@[simp]
theorem extend_extends {a b : X} (γ : Path a b) {t : ℝ}
(ht : t ∈ (Icc 0 1 : Set ℝ)) : γ.extend t = γ ⟨t, ht⟩ :=
IccExtend_of_mem _ γ ht
#align path.extend_extends Path.extend_extends
theorem extend_zero : γ.extend 0 = x := by simp
#align path.extend_zero Path.extend_zero
theorem extend_one : γ.extend 1 = y := by simp
#align path.extend_one Path.extend_one
@[simp]
theorem extend_extends' {a b : X} (γ : Path a b) (t : (Icc 0 1 : Set ℝ)) : γ.extend t = γ t :=
IccExtend_val _ γ t
#align path.extend_extends' Path.extend_extends'
@[simp]
theorem extend_range {a b : X} (γ : Path a b) :
range γ.extend = range γ :=
IccExtend_range _ γ
#align path.extend_range Path.extend_range
theorem extend_of_le_zero {a b : X} (γ : Path a b) {t : ℝ}
(ht : t ≤ 0) : γ.extend t = a :=
(IccExtend_of_le_left _ _ ht).trans γ.source
#align path.extend_of_le_zero Path.extend_of_le_zero
theorem extend_of_one_le {a b : X} (γ : Path a b) {t : ℝ}
(ht : 1 ≤ t) : γ.extend t = b :=
(IccExtend_of_right_le _ _ ht).trans γ.target
#align path.extend_of_one_le Path.extend_of_one_le
@[simp]
theorem refl_extend {a : X} : (Path.refl a).extend = fun _ => a :=
rfl
#align path.refl_extend Path.refl_extend
/-- The path obtained from a map defined on `ℝ` by restriction to the unit interval. -/
def ofLine {f : ℝ → X} (hf : ContinuousOn f I) (h₀ : f 0 = x) (h₁ : f 1 = y) : Path x y where
toFun := f ∘ ((↑) : unitInterval → ℝ)
continuous_toFun := hf.comp_continuous continuous_subtype_val Subtype.prop
source' := h₀
target' := h₁
#align path.of_line Path.ofLine
theorem ofLine_mem {f : ℝ → X} (hf : ContinuousOn f I) (h₀ : f 0 = x) (h₁ : f 1 = y) :
∀ t, ofLine hf h₀ h₁ t ∈ f '' I := fun ⟨t, t_in⟩ => ⟨t, t_in, rfl⟩
#align path.of_line_mem Path.ofLine_mem
attribute [local simp] Iic_def
set_option tactic.skipAssignedInstances false in
/-- Concatenation of two paths from `x` to `y` and from `y` to `z`, putting the first
path on `[0, 1/2]` and the second one on `[1/2, 1]`. -/
@[trans]
def trans (γ : Path x y) (γ' : Path y z) : Path x z where
toFun := (fun t : ℝ => if t ≤ 1 / 2 then γ.extend (2 * t) else γ'.extend (2 * t - 1)) ∘ (↑)
continuous_toFun := by
refine
(Continuous.if_le ?_ ?_ continuous_id continuous_const (by norm_num)).comp
continuous_subtype_val <;>
continuity
source' := by norm_num
target' := by norm_num
#align path.trans Path.trans
theorem trans_apply (γ : Path x y) (γ' : Path y z) (t : I) :
(γ.trans γ') t =
if h : (t : ℝ) ≤ 1 / 2 then γ ⟨2 * t, (mul_pos_mem_iff zero_lt_two).2 ⟨t.2.1, h⟩⟩
else γ' ⟨2 * t - 1, two_mul_sub_one_mem_iff.2 ⟨(not_le.1 h).le, t.2.2⟩⟩ :=
show ite _ _ _ = _ by split_ifs <;> rw [extend_extends]
#align path.trans_apply Path.trans_apply
@[simp]
theorem trans_symm (γ : Path x y) (γ' : Path y z) : (γ.trans γ').symm = γ'.symm.trans γ.symm := by
ext t
simp only [trans_apply, ← one_div, symm_apply, not_le, Function.comp_apply]
split_ifs with h h₁ h₂ <;> rw [coe_symm_eq] at h
· have ht : (t : ℝ) = 1 / 2 := by linarith
norm_num [ht]
· refine congr_arg _ (Subtype.ext ?_)
norm_num [sub_sub_eq_add_sub, mul_sub]
· refine congr_arg _ (Subtype.ext ?_)
norm_num [mul_sub, h]
ring -- TODO norm_num should really do this
· exfalso
linarith
#align path.trans_symm Path.trans_symm
@[simp]
theorem refl_trans_refl {a : X} :
(Path.refl a).trans (Path.refl a) = Path.refl a := by
ext
simp only [Path.trans, ite_self, one_div, Path.refl_extend]
rfl
#align path.refl_trans_refl Path.refl_trans_refl
theorem trans_range {a b c : X} (γ₁ : Path a b) (γ₂ : Path b c) :
range (γ₁.trans γ₂) = range γ₁ ∪ range γ₂ := by
rw [Path.trans]
apply eq_of_subset_of_subset
· rintro x ⟨⟨t, ht0, ht1⟩, hxt⟩
by_cases h : t ≤ 1 / 2
· left
use ⟨2 * t, ⟨by linarith, by linarith⟩⟩
rw [← γ₁.extend_extends]
rwa [coe_mk_mk, Function.comp_apply, if_pos h] at hxt
· right
use ⟨2 * t - 1, ⟨by linarith, by linarith⟩⟩
rw [← γ₂.extend_extends]
rwa [coe_mk_mk, Function.comp_apply, if_neg h] at hxt
· rintro x (⟨⟨t, ht0, ht1⟩, hxt⟩ | ⟨⟨t, ht0, ht1⟩, hxt⟩)
· use ⟨t / 2, ⟨by linarith, by linarith⟩⟩
have : t / 2 ≤ 1 / 2 := (div_le_div_right (zero_lt_two : (0 : ℝ) < 2)).mpr ht1
rw [coe_mk_mk, Function.comp_apply, if_pos this, Subtype.coe_mk]
ring_nf
rwa [γ₁.extend_extends]
· by_cases h : t = 0
· use ⟨1 / 2, ⟨by linarith, by linarith⟩⟩
rw [coe_mk_mk, Function.comp_apply, if_pos le_rfl, Subtype.coe_mk,
mul_one_div_cancel (two_ne_zero' ℝ)]
rw [γ₁.extend_one]
rwa [← γ₂.extend_extends, h, γ₂.extend_zero] at hxt
· use ⟨(t + 1) / 2, ⟨by linarith, by linarith⟩⟩
replace h : t ≠ 0 := h
have ht0 := lt_of_le_of_ne ht0 h.symm
have : ¬(t + 1) / 2 ≤ 1 / 2 := by
rw [not_le]
linarith
rw [coe_mk_mk, Function.comp_apply, Subtype.coe_mk, if_neg this]
ring_nf
rwa [γ₂.extend_extends]
#align path.trans_range Path.trans_range
/-- Image of a path from `x` to `y` by a map which is continuous on the path. -/
def map' (γ : Path x y) {f : X → Y} (h : ContinuousOn f (range γ)) : Path (f x) (f y) where
toFun := f ∘ γ
continuous_toFun := h.comp_continuous γ.continuous (fun x ↦ mem_range_self x)
source' := by simp
target' := by simp
/-- Image of a path from `x` to `y` by a continuous map -/
def map (γ : Path x y) {f : X → Y} (h : Continuous f) :
Path (f x) (f y) := γ.map' h.continuousOn
#align path.map Path.map
@[simp]
theorem map_coe (γ : Path x y) {f : X → Y} (h : Continuous f) :
(γ.map h : I → Y) = f ∘ γ := by
ext t
rfl
#align path.map_coe Path.map_coe
@[simp]
theorem map_symm (γ : Path x y) {f : X → Y} (h : Continuous f) :
(γ.map h).symm = γ.symm.map h :=
rfl
#align path.map_symm Path.map_symm
@[simp]
theorem map_trans (γ : Path x y) (γ' : Path y z) {f : X → Y}
(h : Continuous f) : (γ.trans γ').map h = (γ.map h).trans (γ'.map h) := by
ext t
rw [trans_apply, map_coe, Function.comp_apply, trans_apply]
split_ifs <;> rfl
#align path.map_trans Path.map_trans
@[simp]
theorem map_id (γ : Path x y) : γ.map continuous_id = γ := by
ext
rfl
#align path.map_id Path.map_id
@[simp]
theorem map_map (γ : Path x y) {Z : Type*} [TopologicalSpace Z]
{f : X → Y} (hf : Continuous f) {g : Y → Z} (hg : Continuous g) :
(γ.map hf).map hg = γ.map (hg.comp hf) := by
ext
rfl
#align path.map_map Path.map_map
/-- Casting a path from `x` to `y` to a path from `x'` to `y'` when `x' = x` and `y' = y` -/
def cast (γ : Path x y) {x' y'} (hx : x' = x) (hy : y' = y) : Path x' y' where
toFun := γ
continuous_toFun := γ.continuous
source' := by simp [hx]
target' := by simp [hy]
#align path.cast Path.cast
@[simp]
theorem symm_cast {a₁ a₂ b₁ b₂ : X} (γ : Path a₂ b₂) (ha : a₁ = a₂) (hb : b₁ = b₂) :
(γ.cast ha hb).symm = γ.symm.cast hb ha :=
rfl
#align path.symm_cast Path.symm_cast
@[simp]
theorem trans_cast {a₁ a₂ b₁ b₂ c₁ c₂ : X} (γ : Path a₂ b₂)
(γ' : Path b₂ c₂) (ha : a₁ = a₂) (hb : b₁ = b₂) (hc : c₁ = c₂) :
(γ.cast ha hb).trans (γ'.cast hb hc) = (γ.trans γ').cast ha hc :=
rfl
#align path.trans_cast Path.trans_cast
@[simp]
theorem cast_coe (γ : Path x y) {x' y'} (hx : x' = x) (hy : y' = y) : (γ.cast hx hy : I → X) = γ :=
rfl
#align path.cast_coe Path.cast_coe
@[continuity]
theorem symm_continuous_family {ι : Type*} [TopologicalSpace ι]
{a b : ι → X} (γ : ∀ t : ι, Path (a t) (b t)) (h : Continuous ↿γ) :
Continuous ↿fun t => (γ t).symm :=
h.comp (continuous_id.prod_map continuous_symm)
#align path.symm_continuous_family Path.symm_continuous_family
@[continuity]
theorem continuous_symm : Continuous (symm : Path x y → Path y x) :=
continuous_uncurry_iff.mp <| symm_continuous_family _ (continuous_fst.path_eval continuous_snd)
#align path.continuous_symm Path.continuous_symm
@[continuity]
theorem continuous_uncurry_extend_of_continuous_family {ι : Type*} [TopologicalSpace ι]
{a b : ι → X} (γ : ∀ t : ι, Path (a t) (b t)) (h : Continuous ↿γ) :
Continuous ↿fun t => (γ t).extend := by
apply h.comp (continuous_id.prod_map continuous_projIcc)
exact zero_le_one
#align path.continuous_uncurry_extend_of_continuous_family Path.continuous_uncurry_extend_of_continuous_family
@[continuity]
theorem trans_continuous_family {ι : Type*} [TopologicalSpace ι]
{a b c : ι → X} (γ₁ : ∀ t : ι, Path (a t) (b t)) (h₁ : Continuous ↿γ₁)
(γ₂ : ∀ t : ι, Path (b t) (c t)) (h₂ : Continuous ↿γ₂) :
Continuous ↿fun t => (γ₁ t).trans (γ₂ t) := by
have h₁' := Path.continuous_uncurry_extend_of_continuous_family γ₁ h₁
have h₂' := Path.continuous_uncurry_extend_of_continuous_family γ₂ h₂
simp only [HasUncurry.uncurry, CoeFun.coe, Path.trans, (· ∘ ·)]
refine Continuous.if_le ?_ ?_ (continuous_subtype_val.comp continuous_snd) continuous_const ?_
· change
Continuous ((fun p : ι × ℝ => (γ₁ p.1).extend p.2) ∘ Prod.map id (fun x => 2 * x : I → ℝ))
exact h₁'.comp (continuous_id.prod_map <| continuous_const.mul continuous_subtype_val)
· change
Continuous ((fun p : ι × ℝ => (γ₂ p.1).extend p.2) ∘ Prod.map id (fun x => 2 * x - 1 : I → ℝ))
exact
h₂'.comp
(continuous_id.prod_map <|
(continuous_const.mul continuous_subtype_val).sub continuous_const)
· rintro st hst
simp [hst, mul_inv_cancel (two_ne_zero' ℝ)]
#align path.trans_continuous_family Path.trans_continuous_family
@[continuity]
theorem _root_.Continuous.path_trans {f : Y → Path x y} {g : Y → Path y z} :
Continuous f → Continuous g → Continuous fun t => (f t).trans (g t) := by
intro hf hg
apply continuous_uncurry_iff.mp
exact trans_continuous_family _ (continuous_uncurry_iff.mpr hf) _ (continuous_uncurry_iff.mpr hg)
#align continuous.path_trans Continuous.path_trans
@[continuity]
theorem continuous_trans {x y z : X} : Continuous fun ρ : Path x y × Path y z => ρ.1.trans ρ.2 :=
continuous_fst.path_trans continuous_snd
#align path.continuous_trans Path.continuous_trans
/-! #### Product of paths -/
section Prod
variable {a₁ a₂ a₃ : X} {b₁ b₂ b₃ : Y}
/-- Given a path in `X` and a path in `Y`, we can take their pointwise product to get a path in
`X × Y`. -/
protected def prod (γ₁ : Path a₁ a₂) (γ₂ : Path b₁ b₂) : Path (a₁, b₁) (a₂, b₂) where
toContinuousMap := ContinuousMap.prodMk γ₁.toContinuousMap γ₂.toContinuousMap
source' := by simp
target' := by simp
#align path.prod Path.prod
@[simp]
theorem prod_coe (γ₁ : Path a₁ a₂) (γ₂ : Path b₁ b₂) :
⇑(γ₁.prod γ₂) = fun t => (γ₁ t, γ₂ t) :=
rfl
#align path.prod_coe_fn Path.prod_coe
/-- Path composition commutes with products -/
theorem trans_prod_eq_prod_trans (γ₁ : Path a₁ a₂) (δ₁ : Path a₂ a₃) (γ₂ : Path b₁ b₂)
(δ₂ : Path b₂ b₃) : (γ₁.prod γ₂).trans (δ₁.prod δ₂) = (γ₁.trans δ₁).prod (γ₂.trans δ₂) := by
ext t <;>
unfold Path.trans <;>
simp only [Path.coe_mk_mk, Path.prod_coe, Function.comp_apply] <;>
split_ifs <;>
rfl
#align path.trans_prod_eq_prod_trans Path.trans_prod_eq_prod_trans
end Prod
section Pi
variable {χ : ι → Type*} [∀ i, TopologicalSpace (χ i)] {as bs cs : ∀ i, χ i}
/-- Given a family of paths, one in each Xᵢ, we take their pointwise product to get a path in
Π i, Xᵢ. -/
protected def pi (γ : ∀ i, Path (as i) (bs i)) : Path as bs where
toContinuousMap := ContinuousMap.pi fun i => (γ i).toContinuousMap
source' := by simp
target' := by simp
#align path.pi Path.pi
@[simp]
theorem pi_coe (γ : ∀ i, Path (as i) (bs i)) : ⇑(Path.pi γ) = fun t i => γ i t :=
rfl
#align path.pi_coe_fn Path.pi_coe
/-- Path composition commutes with products -/
theorem trans_pi_eq_pi_trans (γ₀ : ∀ i, Path (as i) (bs i)) (γ₁ : ∀ i, Path (bs i) (cs i)) :
(Path.pi γ₀).trans (Path.pi γ₁) = Path.pi fun i => (γ₀ i).trans (γ₁ i) := by
ext t i
unfold Path.trans
simp only [Path.coe_mk_mk, Function.comp_apply, pi_coe]
split_ifs <;> rfl
#align path.trans_pi_eq_pi_trans Path.trans_pi_eq_pi_trans
end Pi
/-! #### Pointwise multiplication/addition of two paths in a topological (additive) group -/
/-- Pointwise multiplication of paths in a topological group. The additive version is probably more
useful. -/
@[to_additive "Pointwise addition of paths in a topological additive group."]
protected def mul [Mul X] [ContinuousMul X] {a₁ b₁ a₂ b₂ : X} (γ₁ : Path a₁ b₁) (γ₂ : Path a₂ b₂) :
Path (a₁ * a₂) (b₁ * b₂) :=
(γ₁.prod γ₂).map continuous_mul
#align path.mul Path.mul
#align path.add Path.add
@[to_additive]
protected theorem mul_apply [Mul X] [ContinuousMul X] {a₁ b₁ a₂ b₂ : X} (γ₁ : Path a₁ b₁)
(γ₂ : Path a₂ b₂) (t : unitInterval) : (γ₁.mul γ₂) t = γ₁ t * γ₂ t :=
rfl
#align path.mul_apply Path.mul_apply
#align path.add_apply Path.add_apply
/-! #### Truncating a path -/
/-- `γ.truncate t₀ t₁` is the path which follows the path `γ` on the
time interval `[t₀, t₁]` and stays still otherwise. -/
def truncate {X : Type*} [TopologicalSpace X] {a b : X} (γ : Path a b) (t₀ t₁ : ℝ) :
Path (γ.extend <| min t₀ t₁) (γ.extend t₁) where
toFun s := γ.extend (min (max s t₀) t₁)
continuous_toFun :=
γ.continuous_extend.comp ((continuous_subtype_val.max continuous_const).min continuous_const)
source' := by
simp only [min_def, max_def']
norm_cast
split_ifs with h₁ h₂ h₃ h₄
· simp [γ.extend_of_le_zero h₁]
· congr
linarith
· have h₄ : t₁ ≤ 0 := le_of_lt (by simpa using h₂)
simp [γ.extend_of_le_zero h₄, γ.extend_of_le_zero h₁]
all_goals rfl
target' := by
simp only [min_def, max_def']
norm_cast
split_ifs with h₁ h₂ h₃
· simp [γ.extend_of_one_le h₂]
· rfl
· have h₄ : 1 ≤ t₀ := le_of_lt (by simpa using h₁)
simp [γ.extend_of_one_le h₄, γ.extend_of_one_le (h₄.trans h₃)]
· rfl
#align path.truncate Path.truncate
/-- `γ.truncateOfLE t₀ t₁ h`, where `h : t₀ ≤ t₁` is `γ.truncate t₀ t₁`
casted as a path from `γ.extend t₀` to `γ.extend t₁`. -/
def truncateOfLE {X : Type*} [TopologicalSpace X] {a b : X} (γ : Path a b) {t₀ t₁ : ℝ}
(h : t₀ ≤ t₁) : Path (γ.extend t₀) (γ.extend t₁) :=
(γ.truncate t₀ t₁).cast (by rw [min_eq_left h]) rfl
#align path.truncate_of_le Path.truncateOfLE
theorem truncate_range {a b : X} (γ : Path a b) {t₀ t₁ : ℝ} :
range (γ.truncate t₀ t₁) ⊆ range γ := by
rw [← γ.extend_range]
simp only [range_subset_iff, SetCoe.exists, SetCoe.forall]
intro x _hx
simp only [DFunLike.coe, Path.truncate, mem_range_self]
#align path.truncate_range Path.truncate_range
/-- For a path `γ`, `γ.truncate` gives a "continuous family of paths", by which we
mean the uncurried function which maps `(t₀, t₁, s)` to `γ.truncate t₀ t₁ s` is continuous. -/
@[continuity]
theorem truncate_continuous_family {a b : X} (γ : Path a b) :
Continuous (fun x => γ.truncate x.1 x.2.1 x.2.2 : ℝ × ℝ × I → X) :=
γ.continuous_extend.comp
(((continuous_subtype_val.comp (continuous_snd.comp continuous_snd)).max continuous_fst).min
(continuous_fst.comp continuous_snd))
#align path.truncate_continuous_family Path.truncate_continuous_family
@[continuity]
theorem truncate_const_continuous_family {a b : X} (γ : Path a b)
(t : ℝ) : Continuous ↿(γ.truncate t) := by
have key : Continuous (fun x => (t, x) : ℝ × I → ℝ × ℝ × I) := by continuity
exact γ.truncate_continuous_family.comp key
#align path.truncate_const_continuous_family Path.truncate_const_continuous_family
@[simp]
theorem truncate_self {a b : X} (γ : Path a b) (t : ℝ) :
γ.truncate t t = (Path.refl <| γ.extend t).cast (by rw [min_self]) rfl := by
ext x
rw [cast_coe]
simp only [truncate, DFunLike.coe, refl, min_def, max_def]
split_ifs with h₁ h₂ <;> congr
#align path.truncate_self Path.truncate_self
@[simp 1001] -- Porting note: increase `simp` priority so left-hand side doesn't simplify
theorem truncate_zero_zero {a b : X} (γ : Path a b) :
γ.truncate 0 0 = (Path.refl a).cast (by rw [min_self, γ.extend_zero]) γ.extend_zero := by
convert γ.truncate_self 0
#align path.truncate_zero_zero Path.truncate_zero_zero
@[simp 1001] -- Porting note: increase `simp` priority so left-hand side doesn't simplify
theorem truncate_one_one {a b : X} (γ : Path a b) :
γ.truncate 1 1 = (Path.refl b).cast (by rw [min_self, γ.extend_one]) γ.extend_one := by
convert γ.truncate_self 1
#align path.truncate_one_one Path.truncate_one_one
@[simp]
| Mathlib/Topology/Connected/PathConnected.lean | 695 | 700 | theorem truncate_zero_one {a b : X} (γ : Path a b) :
γ.truncate 0 1 = γ.cast (by simp [zero_le_one, extend_zero]) (by simp) := by |
ext x
rw [cast_coe]
have : ↑x ∈ (Icc 0 1 : Set ℝ) := x.2
rw [truncate, coe_mk_mk, max_eq_left this.1, min_eq_left this.2, extend_extends']
|
/-
Copyright (c) 2018 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Simon Hudon
-/
import Mathlib.Data.PFunctor.Multivariate.W
import Mathlib.Data.QPF.Multivariate.Basic
#align_import data.qpf.multivariate.constructions.fix from "leanprover-community/mathlib"@"28aa996fc6fb4317f0083c4e6daf79878d81be33"
/-!
# The initial algebra of a multivariate qpf is again a qpf.
For an `(n+1)`-ary QPF `F (α₀,..,αₙ)`, we take the least fixed point of `F` with
regards to its last argument `αₙ`. The result is an `n`-ary functor: `Fix F (α₀,..,αₙ₋₁)`.
Making `Fix F` into a functor allows us to take the fixed point, compose with other functors
and take a fixed point again.
## Main definitions
* `Fix.mk` - constructor
* `Fix.dest` - destructor
* `Fix.rec` - recursor: basis for defining functions by structural recursion on `Fix F α`
* `Fix.drec` - dependent recursor: generalization of `Fix.rec` where
the result type of the function is allowed to depend on the `Fix F α` value
* `Fix.rec_eq` - defining equation for `recursor`
* `Fix.ind` - induction principle for `Fix F α`
## Implementation notes
For `F` a `QPF`, we define `Fix F α` in terms of the W-type of the polynomial functor `P` of `F`.
We define the relation `WEquiv` and take its quotient as the definition of `Fix F α`.
See [avigad-carneiro-hudon2019] for more details.
## Reference
* Jeremy Avigad, Mario M. Carneiro and Simon Hudon.
[*Data Types as Quotients of Polynomial Functors*][avigad-carneiro-hudon2019]
-/
universe u v
namespace MvQPF
open TypeVec
open MvFunctor (LiftP LiftR)
open MvFunctor
variable {n : ℕ} {F : TypeVec.{u} (n + 1) → Type u} [MvFunctor F] [q : MvQPF F]
/-- `recF` is used as a basis for defining the recursor on `Fix F α`. `recF`
traverses recursively the W-type generated by `q.P` using a function on `F`
as a recursive step -/
def recF {α : TypeVec n} {β : Type u} (g : F (α.append1 β) → β) : q.P.W α → β :=
q.P.wRec fun a f' _f rec => g (abs ⟨a, splitFun f' rec⟩)
set_option linter.uppercaseLean3 false in
#align mvqpf.recF MvQPF.recF
theorem recF_eq {α : TypeVec n} {β : Type u} (g : F (α.append1 β) → β) (a : q.P.A)
(f' : q.P.drop.B a ⟹ α) (f : q.P.last.B a → q.P.W α) :
recF g (q.P.wMk a f' f) = g (abs ⟨a, splitFun f' (recF g ∘ f)⟩) := by
rw [recF, MvPFunctor.wRec_eq]; rfl
set_option linter.uppercaseLean3 false in
#align mvqpf.recF_eq MvQPF.recF_eq
theorem recF_eq' {α : TypeVec n} {β : Type u} (g : F (α.append1 β) → β) (x : q.P.W α) :
recF g x = g (abs (appendFun id (recF g) <$$> q.P.wDest' x)) := by
apply q.P.w_cases _ x
intro a f' f
rw [recF_eq, q.P.wDest'_wMk, MvPFunctor.map_eq, appendFun_comp_splitFun, TypeVec.id_comp]
set_option linter.uppercaseLean3 false in
#align mvqpf.recF_eq' MvQPF.recF_eq'
/-- Equivalence relation on W-types that represent the same `Fix F`
value -/
inductive WEquiv {α : TypeVec n} : q.P.W α → q.P.W α → Prop
| ind (a : q.P.A) (f' : q.P.drop.B a ⟹ α) (f₀ f₁ : q.P.last.B a → q.P.W α) :
(∀ x, WEquiv (f₀ x) (f₁ x)) → WEquiv (q.P.wMk a f' f₀) (q.P.wMk a f' f₁)
| abs (a₀ : q.P.A) (f'₀ : q.P.drop.B a₀ ⟹ α) (f₀ : q.P.last.B a₀ → q.P.W α) (a₁ : q.P.A)
(f'₁ : q.P.drop.B a₁ ⟹ α) (f₁ : q.P.last.B a₁ → q.P.W α) :
abs ⟨a₀, q.P.appendContents f'₀ f₀⟩ = abs ⟨a₁, q.P.appendContents f'₁ f₁⟩ →
WEquiv (q.P.wMk a₀ f'₀ f₀) (q.P.wMk a₁ f'₁ f₁)
| trans (u v w : q.P.W α) : WEquiv u v → WEquiv v w → WEquiv u w
set_option linter.uppercaseLean3 false in
#align mvqpf.Wequiv MvQPF.WEquiv
theorem recF_eq_of_wEquiv (α : TypeVec n) {β : Type u} (u : F (α.append1 β) → β) (x y : q.P.W α) :
WEquiv x y → recF u x = recF u y := by
apply q.P.w_cases _ x
intro a₀ f'₀ f₀
apply q.P.w_cases _ y
intro a₁ f'₁ f₁
intro h
-- Porting note: induction on h doesn't work.
refine @WEquiv.recOn _ _ _ _ _ (fun a a' _ ↦ recF u a = recF u a') _ _ h ?_ ?_ ?_
· intros a f' f₀ f₁ _h ih; simp only [recF_eq, Function.comp]
congr; funext; congr; funext; apply ih
· intros a₀ f'₀ f₀ a₁ f'₁ f₁ h; simp only [recF_eq', abs_map, MvPFunctor.wDest'_wMk, h]
· intros x y z _e₁ _e₂ ih₁ ih₂; exact Eq.trans ih₁ ih₂
set_option linter.uppercaseLean3 false in
#align mvqpf.recF_eq_of_Wequiv MvQPF.recF_eq_of_wEquiv
theorem wEquiv.abs' {α : TypeVec n} (x y : q.P.W α)
(h : MvQPF.abs (q.P.wDest' x) = MvQPF.abs (q.P.wDest' y)) :
WEquiv x y := by
revert h
apply q.P.w_cases _ x
intro a₀ f'₀ f₀
apply q.P.w_cases _ y
intro a₁ f'₁ f₁
apply WEquiv.abs
set_option linter.uppercaseLean3 false in
#align mvqpf.Wequiv.abs' MvQPF.wEquiv.abs'
theorem wEquiv.refl {α : TypeVec n} (x : q.P.W α) : WEquiv x x := by
apply q.P.w_cases _ x; intro a f' f; exact WEquiv.abs a f' f a f' f rfl
set_option linter.uppercaseLean3 false in
#align mvqpf.Wequiv.refl MvQPF.wEquiv.refl
| Mathlib/Data/QPF/Multivariate/Constructions/Fix.lean | 125 | 129 | theorem wEquiv.symm {α : TypeVec n} (x y : q.P.W α) : WEquiv x y → WEquiv y x := by |
intro h; induction h with
| ind a f' f₀ f₁ _h ih => exact WEquiv.ind _ _ _ _ ih
| abs a₀ f'₀ f₀ a₁ f'₁ f₁ h => exact WEquiv.abs _ _ _ _ _ _ h.symm
| trans x y z _e₁ _e₂ ih₁ ih₂ => exact MvQPF.WEquiv.trans _ _ _ ih₂ ih₁
|
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Integral.IntegrableOn
#align_import measure_theory.function.locally_integrable from "leanprover-community/mathlib"@"08a4542bec7242a5c60f179e4e49de8c0d677b1b"
/-!
# Locally integrable functions
A function is called *locally integrable* (`MeasureTheory.LocallyIntegrable`) if it is integrable
on a neighborhood of every point. More generally, it is *locally integrable on `s`* if it is
locally integrable on a neighbourhood within `s` of any point of `s`.
This file contains properties of locally integrable functions, and integrability results
on compact sets.
## Main statements
* `Continuous.locallyIntegrable`: A continuous function is locally integrable.
* `ContinuousOn.locallyIntegrableOn`: A function which is continuous on `s` is locally
integrable on `s`.
-/
open MeasureTheory MeasureTheory.Measure Set Function TopologicalSpace Bornology
open scoped Topology Interval ENNReal
variable {X Y E F R : Type*} [MeasurableSpace X] [TopologicalSpace X]
variable [MeasurableSpace Y] [TopologicalSpace Y]
variable [NormedAddCommGroup E] [NormedAddCommGroup F] {f g : X → E} {μ : Measure X} {s : Set X}
namespace MeasureTheory
section LocallyIntegrableOn
/-- A function `f : X → E` is *locally integrable on s*, for `s ⊆ X`, if for every `x ∈ s` there is
a neighbourhood of `x` within `s` on which `f` is integrable. (Note this is, in general, strictly
weaker than local integrability with respect to `μ.restrict s`.) -/
def LocallyIntegrableOn (f : X → E) (s : Set X) (μ : Measure X := by volume_tac) : Prop :=
∀ x : X, x ∈ s → IntegrableAtFilter f (𝓝[s] x) μ
#align measure_theory.locally_integrable_on MeasureTheory.LocallyIntegrableOn
theorem LocallyIntegrableOn.mono_set (hf : LocallyIntegrableOn f s μ) {t : Set X}
(hst : t ⊆ s) : LocallyIntegrableOn f t μ := fun x hx =>
(hf x <| hst hx).filter_mono (nhdsWithin_mono x hst)
#align measure_theory.locally_integrable_on.mono MeasureTheory.LocallyIntegrableOn.mono_set
theorem LocallyIntegrableOn.norm (hf : LocallyIntegrableOn f s μ) :
LocallyIntegrableOn (fun x => ‖f x‖) s μ := fun t ht =>
let ⟨U, hU_nhd, hU_int⟩ := hf t ht
⟨U, hU_nhd, hU_int.norm⟩
#align measure_theory.locally_integrable_on.norm MeasureTheory.LocallyIntegrableOn.norm
theorem LocallyIntegrableOn.mono (hf : LocallyIntegrableOn f s μ) {g : X → F}
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) :
LocallyIntegrableOn g s μ := by
intro x hx
rcases hf x hx with ⟨t, t_mem, ht⟩
exact ⟨t, t_mem, Integrable.mono ht hg.restrict (ae_restrict_of_ae h)⟩
theorem IntegrableOn.locallyIntegrableOn (hf : IntegrableOn f s μ) : LocallyIntegrableOn f s μ :=
fun _ _ => ⟨s, self_mem_nhdsWithin, hf⟩
#align measure_theory.integrable_on.locally_integrable_on MeasureTheory.IntegrableOn.locallyIntegrableOn
/-- If a function is locally integrable on a compact set, then it is integrable on that set. -/
theorem LocallyIntegrableOn.integrableOn_isCompact (hf : LocallyIntegrableOn f s μ)
(hs : IsCompact s) : IntegrableOn f s μ :=
IsCompact.induction_on hs integrableOn_empty (fun _u _v huv hv => hv.mono_set huv)
(fun _u _v hu hv => integrableOn_union.mpr ⟨hu, hv⟩) hf
#align measure_theory.locally_integrable_on.integrable_on_is_compact MeasureTheory.LocallyIntegrableOn.integrableOn_isCompact
theorem LocallyIntegrableOn.integrableOn_compact_subset (hf : LocallyIntegrableOn f s μ) {t : Set X}
(hst : t ⊆ s) (ht : IsCompact t) : IntegrableOn f t μ :=
(hf.mono_set hst).integrableOn_isCompact ht
#align measure_theory.locally_integrable_on.integrable_on_compact_subset MeasureTheory.LocallyIntegrableOn.integrableOn_compact_subset
/-- If a function `f` is locally integrable on a set `s` in a second countable topological space,
then there exist countably many open sets `u` covering `s` such that `f` is integrable on each
set `u ∩ s`. -/
theorem LocallyIntegrableOn.exists_countable_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : ∃ T : Set (Set X), T.Countable ∧
(∀ u ∈ T, IsOpen u) ∧ (s ⊆ ⋃ u ∈ T, u) ∧ (∀ u ∈ T, IntegrableOn f (u ∩ s) μ) := by
have : ∀ x : s, ∃ u, IsOpen u ∧ x.1 ∈ u ∧ IntegrableOn f (u ∩ s) μ := by
rintro ⟨x, hx⟩
rcases hf x hx with ⟨t, ht, h't⟩
rcases mem_nhdsWithin.1 ht with ⟨u, u_open, x_mem, u_sub⟩
exact ⟨u, u_open, x_mem, h't.mono_set u_sub⟩
choose u u_open xu hu using this
obtain ⟨T, T_count, hT⟩ : ∃ T : Set s, T.Countable ∧ s ⊆ ⋃ i ∈ T, u i := by
have : s ⊆ ⋃ x : s, u x := fun y hy => mem_iUnion_of_mem ⟨y, hy⟩ (xu ⟨y, hy⟩)
obtain ⟨T, hT_count, hT_un⟩ := isOpen_iUnion_countable u u_open
exact ⟨T, hT_count, by rwa [hT_un]⟩
refine ⟨u '' T, T_count.image _, ?_, by rwa [biUnion_image], ?_⟩
· rintro v ⟨w, -, rfl⟩
exact u_open _
· rintro v ⟨w, -, rfl⟩
exact hu _
/-- If a function `f` is locally integrable on a set `s` in a second countable topological space,
then there exists a sequence of open sets `u n` covering `s` such that `f` is integrable on each
set `u n ∩ s`. -/
theorem LocallyIntegrableOn.exists_nat_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : ∃ u : ℕ → Set X,
(∀ n, IsOpen (u n)) ∧ (s ⊆ ⋃ n, u n) ∧ (∀ n, IntegrableOn f (u n ∩ s) μ) := by
rcases hf.exists_countable_integrableOn with ⟨T, T_count, T_open, sT, hT⟩
let T' : Set (Set X) := insert ∅ T
have T'_count : T'.Countable := Countable.insert ∅ T_count
have T'_ne : T'.Nonempty := by simp only [T', insert_nonempty]
rcases T'_count.exists_eq_range T'_ne with ⟨u, hu⟩
refine ⟨u, ?_, ?_, ?_⟩
· intro n
have : u n ∈ T' := by rw [hu]; exact mem_range_self n
rcases mem_insert_iff.1 this with h|h
· rw [h]
exact isOpen_empty
· exact T_open _ h
· intro x hx
obtain ⟨v, hv, h'v⟩ : ∃ v, v ∈ T ∧ x ∈ v := by simpa only [mem_iUnion, exists_prop] using sT hx
have : v ∈ range u := by rw [← hu]; exact subset_insert ∅ T hv
obtain ⟨n, rfl⟩ : ∃ n, u n = v := by simpa only [mem_range] using this
exact mem_iUnion_of_mem _ h'v
· intro n
have : u n ∈ T' := by rw [hu]; exact mem_range_self n
rcases mem_insert_iff.1 this with h|h
· simp only [h, empty_inter, integrableOn_empty]
· exact hT _ h
theorem LocallyIntegrableOn.aestronglyMeasurable [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : AEStronglyMeasurable f (μ.restrict s) := by
rcases hf.exists_nat_integrableOn with ⟨u, -, su, hu⟩
have : s = ⋃ n, u n ∩ s := by rw [← iUnion_inter]; exact (inter_eq_right.mpr su).symm
rw [this, aestronglyMeasurable_iUnion_iff]
exact fun i : ℕ => (hu i).aestronglyMeasurable
#align measure_theory.locally_integrable_on.ae_strongly_measurable MeasureTheory.LocallyIntegrableOn.aestronglyMeasurable
/-- If `s` is either open, or closed, then `f` is locally integrable on `s` iff it is integrable on
every compact subset contained in `s`. -/
theorem locallyIntegrableOn_iff [LocallyCompactSpace X] [T2Space X] (hs : IsClosed s ∨ IsOpen s) :
LocallyIntegrableOn f s μ ↔ ∀ (k : Set X), k ⊆ s → (IsCompact k → IntegrableOn f k μ) := by
-- The correct condition is that `s` be *locally closed*, i.e. for every `x ∈ s` there is some
-- `U ∈ 𝓝 x` such that `U ∩ s` is closed. But mathlib doesn't have locally closed sets yet.
refine ⟨fun hf k hk => hf.integrableOn_compact_subset hk, fun hf x hx => ?_⟩
cases hs with
| inl hs =>
exact
let ⟨K, hK, h2K⟩ := exists_compact_mem_nhds x
⟨_, inter_mem_nhdsWithin s h2K,
hf _ inter_subset_left
(hK.of_isClosed_subset (hs.inter hK.isClosed) inter_subset_right)⟩
| inr hs =>
obtain ⟨K, hK, h2K, h3K⟩ := exists_compact_subset hs hx
refine ⟨K, ?_, hf K h3K hK⟩
simpa only [IsOpen.nhdsWithin_eq hs hx, interior_eq_nhds'] using h2K
#align measure_theory.locally_integrable_on_iff MeasureTheory.locallyIntegrableOn_iff
protected theorem LocallyIntegrableOn.add
(hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) :
LocallyIntegrableOn (f + g) s μ := fun x hx ↦ (hf x hx).add (hg x hx)
protected theorem LocallyIntegrableOn.sub
(hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) :
LocallyIntegrableOn (f - g) s μ := fun x hx ↦ (hf x hx).sub (hg x hx)
protected theorem LocallyIntegrableOn.neg (hf : LocallyIntegrableOn f s μ) :
LocallyIntegrableOn (-f) s μ := fun x hx ↦ (hf x hx).neg
end LocallyIntegrableOn
/-- A function `f : X → E` is *locally integrable* if it is integrable on a neighborhood of every
point. In particular, it is integrable on all compact sets,
see `LocallyIntegrable.integrableOn_isCompact`. -/
def LocallyIntegrable (f : X → E) (μ : Measure X := by volume_tac) : Prop :=
∀ x : X, IntegrableAtFilter f (𝓝 x) μ
#align measure_theory.locally_integrable MeasureTheory.LocallyIntegrable
theorem locallyIntegrable_comap (hs : MeasurableSet s) :
LocallyIntegrable (fun x : s ↦ f x) (μ.comap Subtype.val) ↔ LocallyIntegrableOn f s μ := by
simp_rw [LocallyIntegrableOn, Subtype.forall', ← map_nhds_subtype_val]
exact forall_congr' fun _ ↦ (MeasurableEmbedding.subtype_coe hs).integrableAtFilter_iff_comap.symm
theorem locallyIntegrableOn_univ : LocallyIntegrableOn f univ μ ↔ LocallyIntegrable f μ := by
simp only [LocallyIntegrableOn, nhdsWithin_univ, mem_univ, true_imp_iff]; rfl
#align measure_theory.locally_integrable_on_univ MeasureTheory.locallyIntegrableOn_univ
theorem LocallyIntegrable.locallyIntegrableOn (hf : LocallyIntegrable f μ) (s : Set X) :
LocallyIntegrableOn f s μ := fun x _ => (hf x).filter_mono nhdsWithin_le_nhds
#align measure_theory.locally_integrable.locally_integrable_on MeasureTheory.LocallyIntegrable.locallyIntegrableOn
theorem Integrable.locallyIntegrable (hf : Integrable f μ) : LocallyIntegrable f μ := fun _ =>
hf.integrableAtFilter _
#align measure_theory.integrable.locally_integrable MeasureTheory.Integrable.locallyIntegrable
theorem LocallyIntegrable.mono (hf : LocallyIntegrable f μ) {g : X → F}
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) :
LocallyIntegrable g μ := by
rw [← locallyIntegrableOn_univ] at hf ⊢
exact hf.mono hg h
/-- If `f` is locally integrable with respect to `μ.restrict s`, it is locally integrable on `s`.
(See `locallyIntegrableOn_iff_locallyIntegrable_restrict` for an iff statement when `s` is
closed.) -/
theorem locallyIntegrableOn_of_locallyIntegrable_restrict [OpensMeasurableSpace X]
(hf : LocallyIntegrable f (μ.restrict s)) : LocallyIntegrableOn f s μ := by
intro x _
obtain ⟨t, ht_mem, ht_int⟩ := hf x
obtain ⟨u, hu_sub, hu_o, hu_mem⟩ := mem_nhds_iff.mp ht_mem
refine ⟨_, inter_mem_nhdsWithin s (hu_o.mem_nhds hu_mem), ?_⟩
simpa only [IntegrableOn, Measure.restrict_restrict hu_o.measurableSet, inter_comm] using
ht_int.mono_set hu_sub
#align measure_theory.locally_integrable_on_of_locally_integrable_restrict MeasureTheory.locallyIntegrableOn_of_locallyIntegrable_restrict
/-- If `s` is closed, being locally integrable on `s` wrt `μ` is equivalent to being locally
integrable with respect to `μ.restrict s`. For the one-way implication without assuming `s` closed,
see `locallyIntegrableOn_of_locallyIntegrable_restrict`. -/
theorem locallyIntegrableOn_iff_locallyIntegrable_restrict [OpensMeasurableSpace X]
(hs : IsClosed s) : LocallyIntegrableOn f s μ ↔ LocallyIntegrable f (μ.restrict s) := by
refine ⟨fun hf x => ?_, locallyIntegrableOn_of_locallyIntegrable_restrict⟩
by_cases h : x ∈ s
· obtain ⟨t, ht_nhds, ht_int⟩ := hf x h
obtain ⟨u, hu_o, hu_x, hu_sub⟩ := mem_nhdsWithin.mp ht_nhds
refine ⟨u, hu_o.mem_nhds hu_x, ?_⟩
rw [IntegrableOn, restrict_restrict hu_o.measurableSet]
exact ht_int.mono_set hu_sub
· rw [← isOpen_compl_iff] at hs
refine ⟨sᶜ, hs.mem_nhds h, ?_⟩
rw [IntegrableOn, restrict_restrict, inter_comm, inter_compl_self, ← IntegrableOn]
exacts [integrableOn_empty, hs.measurableSet]
#align measure_theory.locally_integrable_on_iff_locally_integrable_restrict MeasureTheory.locallyIntegrableOn_iff_locallyIntegrable_restrict
/-- If a function is locally integrable, then it is integrable on any compact set. -/
theorem LocallyIntegrable.integrableOn_isCompact {k : Set X} (hf : LocallyIntegrable f μ)
(hk : IsCompact k) : IntegrableOn f k μ :=
(hf.locallyIntegrableOn k).integrableOn_isCompact hk
#align measure_theory.locally_integrable.integrable_on_is_compact MeasureTheory.LocallyIntegrable.integrableOn_isCompact
/-- If a function is locally integrable, then it is integrable on an open neighborhood of any
compact set. -/
| Mathlib/MeasureTheory/Function/LocallyIntegrable.lean | 241 | 252 | theorem LocallyIntegrable.integrableOn_nhds_isCompact (hf : LocallyIntegrable f μ) {k : Set X}
(hk : IsCompact k) : ∃ u, IsOpen u ∧ k ⊆ u ∧ IntegrableOn f u μ := by |
refine IsCompact.induction_on hk ?_ ?_ ?_ ?_
· refine ⟨∅, isOpen_empty, Subset.rfl, integrableOn_empty⟩
· rintro s t hst ⟨u, u_open, tu, hu⟩
exact ⟨u, u_open, hst.trans tu, hu⟩
· rintro s t ⟨u, u_open, su, hu⟩ ⟨v, v_open, tv, hv⟩
exact ⟨u ∪ v, u_open.union v_open, union_subset_union su tv, hu.union hv⟩
· intro x _
rcases hf x with ⟨u, ux, hu⟩
rcases mem_nhds_iff.1 ux with ⟨v, vu, v_open, xv⟩
exact ⟨v, nhdsWithin_le_nhds (v_open.mem_nhds xv), v, v_open, Subset.rfl, hu.mono_set vu⟩
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Analytic.Basic
import Mathlib.Analysis.Analytic.Composition
import Mathlib.Analysis.Analytic.Linear
import Mathlib.Analysis.Calculus.FDeriv.Analytic
import Mathlib.Geometry.Manifold.ChartedSpace
import Mathlib.Analysis.NormedSpace.FiniteDimension
import Mathlib.Analysis.Calculus.ContDiff.Basic
#align_import geometry.manifold.smooth_manifold_with_corners from "leanprover-community/mathlib"@"ddec54a71a0dd025c05445d467f1a2b7d586a3ba"
/-!
# Smooth manifolds (possibly with boundary or corners)
A smooth manifold is a manifold modelled on a normed vector space, or a subset like a
half-space (to get manifolds with boundaries) for which the changes of coordinates are smooth maps.
We define a model with corners as a map `I : H → E` embedding nicely the topological space `H` in
the vector space `E` (or more precisely as a structure containing all the relevant properties).
Given such a model with corners `I` on `(E, H)`, we define the groupoid of local
homeomorphisms of `H` which are smooth when read in `E` (for any regularity `n : ℕ∞`).
With this groupoid at hand and the general machinery of charted spaces, we thus get the notion
of `C^n` manifold with respect to any model with corners `I` on `(E, H)`. We also introduce a
specific type class for `C^∞` manifolds as these are the most commonly used.
Some texts assume manifolds to be Hausdorff and secound countable. We (in mathlib) assume neither,
but add these assumptions later as needed. (Quite a few results still do not require them.)
## Main definitions
* `ModelWithCorners 𝕜 E H` :
a structure containing informations on the way a space `H` embeds in a
model vector space E over the field `𝕜`. This is all that is needed to
define a smooth manifold with model space `H`, and model vector space `E`.
* `modelWithCornersSelf 𝕜 E` :
trivial model with corners structure on the space `E` embedded in itself by the identity.
* `contDiffGroupoid n I` :
when `I` is a model with corners on `(𝕜, E, H)`, this is the groupoid of partial homeos of `H`
which are of class `C^n` over the normed field `𝕜`, when read in `E`.
* `SmoothManifoldWithCorners I M` :
a type class saying that the charted space `M`, modelled on the space `H`, has `C^∞` changes of
coordinates with respect to the model with corners `I` on `(𝕜, E, H)`. This type class is just
a shortcut for `HasGroupoid M (contDiffGroupoid ∞ I)`.
* `extChartAt I x`:
in a smooth manifold with corners with the model `I` on `(E, H)`, the charts take values in `H`,
but often we may want to use their `E`-valued version, obtained by composing the charts with `I`.
Since the target is in general not open, we can not register them as partial homeomorphisms, but
we register them as `PartialEquiv`s.
`extChartAt I x` is the canonical such partial equiv around `x`.
As specific examples of models with corners, we define (in `Geometry.Manifold.Instances.Real`)
* `modelWithCornersSelf ℝ (EuclideanSpace (Fin n))` for the model space used to define
`n`-dimensional real manifolds without boundary (with notation `𝓡 n` in the locale `Manifold`)
* `ModelWithCorners ℝ (EuclideanSpace (Fin n)) (EuclideanHalfSpace n)` for the model space
used to define `n`-dimensional real manifolds with boundary (with notation `𝓡∂ n` in the locale
`Manifold`)
* `ModelWithCorners ℝ (EuclideanSpace (Fin n)) (EuclideanQuadrant n)` for the model space used
to define `n`-dimensional real manifolds with corners
With these definitions at hand, to invoke an `n`-dimensional real manifold without boundary,
one could use
`variable {n : ℕ} {M : Type*} [TopologicalSpace M] [ChartedSpace (EuclideanSpace (Fin n)) M]
[SmoothManifoldWithCorners (𝓡 n) M]`.
However, this is not the recommended way: a theorem proved using this assumption would not apply
for instance to the tangent space of such a manifold, which is modelled on
`(EuclideanSpace (Fin n)) × (EuclideanSpace (Fin n))` and not on `EuclideanSpace (Fin (2 * n))`!
In the same way, it would not apply to product manifolds, modelled on
`(EuclideanSpace (Fin n)) × (EuclideanSpace (Fin m))`.
The right invocation does not focus on one specific construction, but on all constructions sharing
the right properties, like
`variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [FiniteDimensional ℝ E]
{I : ModelWithCorners ℝ E E} [I.Boundaryless]
{M : Type*} [TopologicalSpace M] [ChartedSpace E M] [SmoothManifoldWithCorners I M]`
Here, `I.Boundaryless` is a typeclass property ensuring that there is no boundary (this is for
instance the case for `modelWithCornersSelf`, or products of these). Note that one could consider
as a natural assumption to only use the trivial model with corners `modelWithCornersSelf ℝ E`,
but again in product manifolds the natural model with corners will not be this one but the product
one (and they are not defeq as `(fun p : E × F ↦ (p.1, p.2))` is not defeq to the identity).
So, it is important to use the above incantation to maximize the applicability of theorems.
## Implementation notes
We want to talk about manifolds modelled on a vector space, but also on manifolds with
boundary, modelled on a half space (or even manifolds with corners). For the latter examples,
we still want to define smooth functions, tangent bundles, and so on. As smooth functions are
well defined on vector spaces or subsets of these, one could take for model space a subtype of a
vector space. With the drawback that the whole vector space itself (which is the most basic
example) is not directly a subtype of itself: the inclusion of `univ : Set E` in `Set E` would
show up in the definition, instead of `id`.
A good abstraction covering both cases it to have a vector
space `E` (with basic example the Euclidean space), a model space `H` (with basic example the upper
half space), and an embedding of `H` into `E` (which can be the identity for `H = E`, or
`Subtype.val` for manifolds with corners). We say that the pair `(E, H)` with their embedding is a
model with corners, and we encompass all the relevant properties (in particular the fact that the
image of `H` in `E` should have unique differentials) in the definition of `ModelWithCorners`.
We concentrate on `C^∞` manifolds: all the definitions work equally well for `C^n` manifolds, but
later on it is a pain to carry all over the smoothness parameter, especially when one wants to deal
with `C^k` functions as there would be additional conditions `k ≤ n` everywhere. Since one deals
almost all the time with `C^∞` (or analytic) manifolds, this seems to be a reasonable choice that
one could revisit later if needed. `C^k` manifolds are still available, but they should be called
using `HasGroupoid M (contDiffGroupoid k I)` where `I` is the model with corners.
I have considered using the model with corners `I` as a typeclass argument, possibly `outParam`, to
get lighter notations later on, but it did not turn out right, as on `E × F` there are two natural
model with corners, the trivial (identity) one, and the product one, and they are not defeq and one
needs to indicate to Lean which one we want to use.
This means that when talking on objects on manifolds one will most often need to specify the model
with corners one is using. For instance, the tangent bundle will be `TangentBundle I M` and the
derivative will be `mfderiv I I' f`, instead of the more natural notations `TangentBundle 𝕜 M` and
`mfderiv 𝕜 f` (the field has to be explicit anyway, as some manifolds could be considered both as
real and complex manifolds).
-/
noncomputable section
universe u v w u' v' w'
open Set Filter Function
open scoped Manifold Filter Topology
/-- The extended natural number `∞` -/
scoped[Manifold] notation "∞" => (⊤ : ℕ∞)
/-! ### Models with corners. -/
/-- A structure containing informations on the way a space `H` embeds in a
model vector space `E` over the field `𝕜`. This is all what is needed to
define a smooth manifold with model space `H`, and model vector space `E`.
-/
@[ext] -- Porting note(#5171): was nolint has_nonempty_instance
structure ModelWithCorners (𝕜 : Type*) [NontriviallyNormedField 𝕜] (E : Type*)
[NormedAddCommGroup E] [NormedSpace 𝕜 E] (H : Type*) [TopologicalSpace H] extends
PartialEquiv H E where
source_eq : source = univ
unique_diff' : UniqueDiffOn 𝕜 toPartialEquiv.target
continuous_toFun : Continuous toFun := by continuity
continuous_invFun : Continuous invFun := by continuity
#align model_with_corners ModelWithCorners
attribute [simp, mfld_simps] ModelWithCorners.source_eq
/-- A vector space is a model with corners. -/
def modelWithCornersSelf (𝕜 : Type*) [NontriviallyNormedField 𝕜] (E : Type*)
[NormedAddCommGroup E] [NormedSpace 𝕜 E] : ModelWithCorners 𝕜 E E where
toPartialEquiv := PartialEquiv.refl E
source_eq := rfl
unique_diff' := uniqueDiffOn_univ
continuous_toFun := continuous_id
continuous_invFun := continuous_id
#align model_with_corners_self modelWithCornersSelf
@[inherit_doc] scoped[Manifold] notation "𝓘(" 𝕜 ", " E ")" => modelWithCornersSelf 𝕜 E
/-- A normed field is a model with corners. -/
scoped[Manifold] notation "𝓘(" 𝕜 ")" => modelWithCornersSelf 𝕜 𝕜
section
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H)
namespace ModelWithCorners
/-- Coercion of a model with corners to a function. We don't use `e.toFun` because it is actually
`e.toPartialEquiv.toFun`, so `simp` will apply lemmas about `toPartialEquiv`. While we may want to
switch to this behavior later, doing it mid-port will break a lot of proofs. -/
@[coe] def toFun' (e : ModelWithCorners 𝕜 E H) : H → E := e.toFun
instance : CoeFun (ModelWithCorners 𝕜 E H) fun _ => H → E := ⟨toFun'⟩
/-- The inverse to a model with corners, only registered as a `PartialEquiv`. -/
protected def symm : PartialEquiv E H :=
I.toPartialEquiv.symm
#align model_with_corners.symm ModelWithCorners.symm
/-- See Note [custom simps projection]. We need to specify this projection explicitly in this case,
because it is a composition of multiple projections. -/
def Simps.apply (𝕜 : Type*) [NontriviallyNormedField 𝕜] (E : Type*) [NormedAddCommGroup E]
[NormedSpace 𝕜 E] (H : Type*) [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H) : H → E :=
I
#align model_with_corners.simps.apply ModelWithCorners.Simps.apply
/-- See Note [custom simps projection] -/
def Simps.symm_apply (𝕜 : Type*) [NontriviallyNormedField 𝕜] (E : Type*) [NormedAddCommGroup E]
[NormedSpace 𝕜 E] (H : Type*) [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H) : E → H :=
I.symm
#align model_with_corners.simps.symm_apply ModelWithCorners.Simps.symm_apply
initialize_simps_projections ModelWithCorners (toFun → apply, invFun → symm_apply)
-- Register a few lemmas to make sure that `simp` puts expressions in normal form
@[simp, mfld_simps]
theorem toPartialEquiv_coe : (I.toPartialEquiv : H → E) = I :=
rfl
#align model_with_corners.to_local_equiv_coe ModelWithCorners.toPartialEquiv_coe
@[simp, mfld_simps]
theorem mk_coe (e : PartialEquiv H E) (a b c d) :
((ModelWithCorners.mk e a b c d : ModelWithCorners 𝕜 E H) : H → E) = (e : H → E) :=
rfl
#align model_with_corners.mk_coe ModelWithCorners.mk_coe
@[simp, mfld_simps]
theorem toPartialEquiv_coe_symm : (I.toPartialEquiv.symm : E → H) = I.symm :=
rfl
#align model_with_corners.to_local_equiv_coe_symm ModelWithCorners.toPartialEquiv_coe_symm
@[simp, mfld_simps]
theorem mk_symm (e : PartialEquiv H E) (a b c d) :
(ModelWithCorners.mk e a b c d : ModelWithCorners 𝕜 E H).symm = e.symm :=
rfl
#align model_with_corners.mk_symm ModelWithCorners.mk_symm
@[continuity]
protected theorem continuous : Continuous I :=
I.continuous_toFun
#align model_with_corners.continuous ModelWithCorners.continuous
protected theorem continuousAt {x} : ContinuousAt I x :=
I.continuous.continuousAt
#align model_with_corners.continuous_at ModelWithCorners.continuousAt
protected theorem continuousWithinAt {s x} : ContinuousWithinAt I s x :=
I.continuousAt.continuousWithinAt
#align model_with_corners.continuous_within_at ModelWithCorners.continuousWithinAt
@[continuity]
theorem continuous_symm : Continuous I.symm :=
I.continuous_invFun
#align model_with_corners.continuous_symm ModelWithCorners.continuous_symm
theorem continuousAt_symm {x} : ContinuousAt I.symm x :=
I.continuous_symm.continuousAt
#align model_with_corners.continuous_at_symm ModelWithCorners.continuousAt_symm
theorem continuousWithinAt_symm {s x} : ContinuousWithinAt I.symm s x :=
I.continuous_symm.continuousWithinAt
#align model_with_corners.continuous_within_at_symm ModelWithCorners.continuousWithinAt_symm
theorem continuousOn_symm {s} : ContinuousOn I.symm s :=
I.continuous_symm.continuousOn
#align model_with_corners.continuous_on_symm ModelWithCorners.continuousOn_symm
@[simp, mfld_simps]
theorem target_eq : I.target = range (I : H → E) := by
rw [← image_univ, ← I.source_eq]
exact I.image_source_eq_target.symm
#align model_with_corners.target_eq ModelWithCorners.target_eq
protected theorem unique_diff : UniqueDiffOn 𝕜 (range I) :=
I.target_eq ▸ I.unique_diff'
#align model_with_corners.unique_diff ModelWithCorners.unique_diff
@[simp, mfld_simps]
protected theorem left_inv (x : H) : I.symm (I x) = x := by refine I.left_inv' ?_; simp
#align model_with_corners.left_inv ModelWithCorners.left_inv
protected theorem leftInverse : LeftInverse I.symm I :=
I.left_inv
#align model_with_corners.left_inverse ModelWithCorners.leftInverse
theorem injective : Injective I :=
I.leftInverse.injective
#align model_with_corners.injective ModelWithCorners.injective
@[simp, mfld_simps]
theorem symm_comp_self : I.symm ∘ I = id :=
I.leftInverse.comp_eq_id
#align model_with_corners.symm_comp_self ModelWithCorners.symm_comp_self
protected theorem rightInvOn : RightInvOn I.symm I (range I) :=
I.leftInverse.rightInvOn_range
#align model_with_corners.right_inv_on ModelWithCorners.rightInvOn
@[simp, mfld_simps]
protected theorem right_inv {x : E} (hx : x ∈ range I) : I (I.symm x) = x :=
I.rightInvOn hx
#align model_with_corners.right_inv ModelWithCorners.right_inv
theorem preimage_image (s : Set H) : I ⁻¹' (I '' s) = s :=
I.injective.preimage_image s
#align model_with_corners.preimage_image ModelWithCorners.preimage_image
protected theorem image_eq (s : Set H) : I '' s = I.symm ⁻¹' s ∩ range I := by
refine (I.toPartialEquiv.image_eq_target_inter_inv_preimage ?_).trans ?_
· rw [I.source_eq]; exact subset_univ _
· rw [inter_comm, I.target_eq, I.toPartialEquiv_coe_symm]
#align model_with_corners.image_eq ModelWithCorners.image_eq
protected theorem closedEmbedding : ClosedEmbedding I :=
I.leftInverse.closedEmbedding I.continuous_symm I.continuous
#align model_with_corners.closed_embedding ModelWithCorners.closedEmbedding
theorem isClosed_range : IsClosed (range I) :=
I.closedEmbedding.isClosed_range
#align model_with_corners.closed_range ModelWithCorners.isClosed_range
@[deprecated (since := "2024-03-17")] alias closed_range := isClosed_range
theorem map_nhds_eq (x : H) : map I (𝓝 x) = 𝓝[range I] I x :=
I.closedEmbedding.toEmbedding.map_nhds_eq x
#align model_with_corners.map_nhds_eq ModelWithCorners.map_nhds_eq
theorem map_nhdsWithin_eq (s : Set H) (x : H) : map I (𝓝[s] x) = 𝓝[I '' s] I x :=
I.closedEmbedding.toEmbedding.map_nhdsWithin_eq s x
#align model_with_corners.map_nhds_within_eq ModelWithCorners.map_nhdsWithin_eq
theorem image_mem_nhdsWithin {x : H} {s : Set H} (hs : s ∈ 𝓝 x) : I '' s ∈ 𝓝[range I] I x :=
I.map_nhds_eq x ▸ image_mem_map hs
#align model_with_corners.image_mem_nhds_within ModelWithCorners.image_mem_nhdsWithin
theorem symm_map_nhdsWithin_image {x : H} {s : Set H} : map I.symm (𝓝[I '' s] I x) = 𝓝[s] x := by
rw [← I.map_nhdsWithin_eq, map_map, I.symm_comp_self, map_id]
#align model_with_corners.symm_map_nhds_within_image ModelWithCorners.symm_map_nhdsWithin_image
theorem symm_map_nhdsWithin_range (x : H) : map I.symm (𝓝[range I] I x) = 𝓝 x := by
rw [← I.map_nhds_eq, map_map, I.symm_comp_self, map_id]
#align model_with_corners.symm_map_nhds_within_range ModelWithCorners.symm_map_nhdsWithin_range
theorem unique_diff_preimage {s : Set H} (hs : IsOpen s) :
UniqueDiffOn 𝕜 (I.symm ⁻¹' s ∩ range I) := by
rw [inter_comm]
exact I.unique_diff.inter (hs.preimage I.continuous_invFun)
#align model_with_corners.unique_diff_preimage ModelWithCorners.unique_diff_preimage
theorem unique_diff_preimage_source {β : Type*} [TopologicalSpace β] {e : PartialHomeomorph H β} :
UniqueDiffOn 𝕜 (I.symm ⁻¹' e.source ∩ range I) :=
I.unique_diff_preimage e.open_source
#align model_with_corners.unique_diff_preimage_source ModelWithCorners.unique_diff_preimage_source
theorem unique_diff_at_image {x : H} : UniqueDiffWithinAt 𝕜 (range I) (I x) :=
I.unique_diff _ (mem_range_self _)
#align model_with_corners.unique_diff_at_image ModelWithCorners.unique_diff_at_image
theorem symm_continuousWithinAt_comp_right_iff {X} [TopologicalSpace X] {f : H → X} {s : Set H}
{x : H} :
ContinuousWithinAt (f ∘ I.symm) (I.symm ⁻¹' s ∩ range I) (I x) ↔ ContinuousWithinAt f s x := by
refine ⟨fun h => ?_, fun h => ?_⟩
· have := h.comp I.continuousWithinAt (mapsTo_preimage _ _)
simp_rw [preimage_inter, preimage_preimage, I.left_inv, preimage_id', preimage_range,
inter_univ] at this
rwa [Function.comp.assoc, I.symm_comp_self] at this
· rw [← I.left_inv x] at h; exact h.comp I.continuousWithinAt_symm inter_subset_left
#align model_with_corners.symm_continuous_within_at_comp_right_iff ModelWithCorners.symm_continuousWithinAt_comp_right_iff
protected theorem locallyCompactSpace [LocallyCompactSpace E] (I : ModelWithCorners 𝕜 E H) :
LocallyCompactSpace H := by
have : ∀ x : H, (𝓝 x).HasBasis (fun s => s ∈ 𝓝 (I x) ∧ IsCompact s)
fun s => I.symm '' (s ∩ range I) := fun x ↦ by
rw [← I.symm_map_nhdsWithin_range]
exact ((compact_basis_nhds (I x)).inf_principal _).map _
refine .of_hasBasis this ?_
rintro x s ⟨-, hsc⟩
exact (hsc.inter_right I.isClosed_range).image I.continuous_symm
#align model_with_corners.locally_compact ModelWithCorners.locallyCompactSpace
open TopologicalSpace
protected theorem secondCountableTopology [SecondCountableTopology E] (I : ModelWithCorners 𝕜 E H) :
SecondCountableTopology H :=
I.closedEmbedding.toEmbedding.secondCountableTopology
#align model_with_corners.second_countable_topology ModelWithCorners.secondCountableTopology
end ModelWithCorners
section
variable (𝕜 E)
/-- In the trivial model with corners, the associated `PartialEquiv` is the identity. -/
@[simp, mfld_simps]
theorem modelWithCornersSelf_partialEquiv : 𝓘(𝕜, E).toPartialEquiv = PartialEquiv.refl E :=
rfl
#align model_with_corners_self_local_equiv modelWithCornersSelf_partialEquiv
@[simp, mfld_simps]
theorem modelWithCornersSelf_coe : (𝓘(𝕜, E) : E → E) = id :=
rfl
#align model_with_corners_self_coe modelWithCornersSelf_coe
@[simp, mfld_simps]
theorem modelWithCornersSelf_coe_symm : (𝓘(𝕜, E).symm : E → E) = id :=
rfl
#align model_with_corners_self_coe_symm modelWithCornersSelf_coe_symm
end
end
section ModelWithCornersProd
/-- Given two model_with_corners `I` on `(E, H)` and `I'` on `(E', H')`, we define the model with
corners `I.prod I'` on `(E × E', ModelProd H H')`. This appears in particular for the manifold
structure on the tangent bundle to a manifold modelled on `(E, H)`: it will be modelled on
`(E × E, H × E)`. See note [Manifold type tags] for explanation about `ModelProd H H'`
vs `H × H'`. -/
@[simps (config := .lemmasOnly)]
def ModelWithCorners.prod {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type v}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type w} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) {E' : Type v'} [NormedAddCommGroup E'] [NormedSpace 𝕜 E']
{H' : Type w'} [TopologicalSpace H'] (I' : ModelWithCorners 𝕜 E' H') :
ModelWithCorners 𝕜 (E × E') (ModelProd H H') :=
{ I.toPartialEquiv.prod I'.toPartialEquiv with
toFun := fun x => (I x.1, I' x.2)
invFun := fun x => (I.symm x.1, I'.symm x.2)
source := { x | x.1 ∈ I.source ∧ x.2 ∈ I'.source }
source_eq := by simp only [setOf_true, mfld_simps]
unique_diff' := I.unique_diff'.prod I'.unique_diff'
continuous_toFun := I.continuous_toFun.prod_map I'.continuous_toFun
continuous_invFun := I.continuous_invFun.prod_map I'.continuous_invFun }
#align model_with_corners.prod ModelWithCorners.prod
/-- Given a finite family of `ModelWithCorners` `I i` on `(E i, H i)`, we define the model with
corners `pi I` on `(Π i, E i, ModelPi H)`. See note [Manifold type tags] for explanation about
`ModelPi H`. -/
def ModelWithCorners.pi {𝕜 : Type u} [NontriviallyNormedField 𝕜] {ι : Type v} [Fintype ι]
{E : ι → Type w} [∀ i, NormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)] {H : ι → Type u'}
[∀ i, TopologicalSpace (H i)] (I : ∀ i, ModelWithCorners 𝕜 (E i) (H i)) :
ModelWithCorners 𝕜 (∀ i, E i) (ModelPi H) where
toPartialEquiv := PartialEquiv.pi fun i => (I i).toPartialEquiv
source_eq := by simp only [pi_univ, mfld_simps]
unique_diff' := UniqueDiffOn.pi ι E _ _ fun i _ => (I i).unique_diff'
continuous_toFun := continuous_pi fun i => (I i).continuous.comp (continuous_apply i)
continuous_invFun := continuous_pi fun i => (I i).continuous_symm.comp (continuous_apply i)
#align model_with_corners.pi ModelWithCorners.pi
/-- Special case of product model with corners, which is trivial on the second factor. This shows up
as the model to tangent bundles. -/
abbrev ModelWithCorners.tangent {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type v}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type w} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) : ModelWithCorners 𝕜 (E × E) (ModelProd H E) :=
I.prod 𝓘(𝕜, E)
#align model_with_corners.tangent ModelWithCorners.tangent
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {F : Type*}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {F' : Type*} [NormedAddCommGroup F'] [NormedSpace 𝕜 F']
{H : Type*} [TopologicalSpace H] {H' : Type*} [TopologicalSpace H'] {G : Type*}
[TopologicalSpace G] {G' : Type*} [TopologicalSpace G'] {I : ModelWithCorners 𝕜 E H}
{J : ModelWithCorners 𝕜 F G}
@[simp, mfld_simps]
theorem modelWithCorners_prod_toPartialEquiv :
(I.prod J).toPartialEquiv = I.toPartialEquiv.prod J.toPartialEquiv :=
rfl
#align model_with_corners_prod_to_local_equiv modelWithCorners_prod_toPartialEquiv
@[simp, mfld_simps]
theorem modelWithCorners_prod_coe (I : ModelWithCorners 𝕜 E H) (I' : ModelWithCorners 𝕜 E' H') :
(I.prod I' : _ × _ → _ × _) = Prod.map I I' :=
rfl
#align model_with_corners_prod_coe modelWithCorners_prod_coe
@[simp, mfld_simps]
theorem modelWithCorners_prod_coe_symm (I : ModelWithCorners 𝕜 E H)
(I' : ModelWithCorners 𝕜 E' H') :
((I.prod I').symm : _ × _ → _ × _) = Prod.map I.symm I'.symm :=
rfl
#align model_with_corners_prod_coe_symm modelWithCorners_prod_coe_symm
theorem modelWithCornersSelf_prod : 𝓘(𝕜, E × F) = 𝓘(𝕜, E).prod 𝓘(𝕜, F) := by ext1 <;> simp
#align model_with_corners_self_prod modelWithCornersSelf_prod
theorem ModelWithCorners.range_prod : range (I.prod J) = range I ×ˢ range J := by
simp_rw [← ModelWithCorners.target_eq]; rfl
#align model_with_corners.range_prod ModelWithCorners.range_prod
end ModelWithCornersProd
section Boundaryless
/-- Property ensuring that the model with corners `I` defines manifolds without boundary. This
differs from the more general `BoundarylessManifold`, which requires every point on the manifold
to be an interior point. -/
class ModelWithCorners.Boundaryless {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) : Prop where
range_eq_univ : range I = univ
#align model_with_corners.boundaryless ModelWithCorners.Boundaryless
theorem ModelWithCorners.range_eq_univ {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) [I.Boundaryless] :
range I = univ := ModelWithCorners.Boundaryless.range_eq_univ
/-- If `I` is a `ModelWithCorners.Boundaryless` model, then it is a homeomorphism. -/
@[simps (config := {simpRhs := true})]
def ModelWithCorners.toHomeomorph {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) [I.Boundaryless] : H ≃ₜ E where
__ := I
left_inv := I.left_inv
right_inv _ := I.right_inv <| I.range_eq_univ.symm ▸ mem_univ _
/-- The trivial model with corners has no boundary -/
instance modelWithCornersSelf_boundaryless (𝕜 : Type*) [NontriviallyNormedField 𝕜] (E : Type*)
[NormedAddCommGroup E] [NormedSpace 𝕜 E] : (modelWithCornersSelf 𝕜 E).Boundaryless :=
⟨by simp⟩
#align model_with_corners_self_boundaryless modelWithCornersSelf_boundaryless
/-- If two model with corners are boundaryless, their product also is -/
instance ModelWithCorners.range_eq_univ_prod {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type v}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type w} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) [I.Boundaryless] {E' : Type v'} [NormedAddCommGroup E']
[NormedSpace 𝕜 E'] {H' : Type w'} [TopologicalSpace H'] (I' : ModelWithCorners 𝕜 E' H')
[I'.Boundaryless] : (I.prod I').Boundaryless := by
constructor
dsimp [ModelWithCorners.prod, ModelProd]
rw [← prod_range_range_eq, ModelWithCorners.Boundaryless.range_eq_univ,
ModelWithCorners.Boundaryless.range_eq_univ, univ_prod_univ]
#align model_with_corners.range_eq_univ_prod ModelWithCorners.range_eq_univ_prod
end Boundaryless
section contDiffGroupoid
/-! ### Smooth functions on models with corners -/
variable {m n : ℕ∞} {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H) {M : Type*}
[TopologicalSpace M]
variable (n)
/-- Given a model with corners `(E, H)`, we define the pregroupoid of `C^n` transformations of `H`
as the maps that are `C^n` when read in `E` through `I`. -/
def contDiffPregroupoid : Pregroupoid H where
property f s := ContDiffOn 𝕜 n (I ∘ f ∘ I.symm) (I.symm ⁻¹' s ∩ range I)
comp {f g u v} hf hg _ _ _ := by
have : I ∘ (g ∘ f) ∘ I.symm = (I ∘ g ∘ I.symm) ∘ I ∘ f ∘ I.symm := by ext x; simp
simp only [this]
refine hg.comp (hf.mono fun x ⟨hx1, hx2⟩ ↦ ⟨hx1.1, hx2⟩) ?_
rintro x ⟨hx1, _⟩
simp only [mfld_simps] at hx1 ⊢
exact hx1.2
id_mem := by
apply ContDiffOn.congr contDiff_id.contDiffOn
rintro x ⟨_, hx2⟩
rcases mem_range.1 hx2 with ⟨y, hy⟩
rw [← hy]
simp only [mfld_simps]
locality {f u} _ H := by
apply contDiffOn_of_locally_contDiffOn
rintro y ⟨hy1, hy2⟩
rcases mem_range.1 hy2 with ⟨x, hx⟩
rw [← hx] at hy1 ⊢
simp only [mfld_simps] at hy1 ⊢
rcases H x hy1 with ⟨v, v_open, xv, hv⟩
have : I.symm ⁻¹' (u ∩ v) ∩ range I = I.symm ⁻¹' u ∩ range I ∩ I.symm ⁻¹' v := by
rw [preimage_inter, inter_assoc, inter_assoc]
congr 1
rw [inter_comm]
rw [this] at hv
exact ⟨I.symm ⁻¹' v, v_open.preimage I.continuous_symm, by simpa, hv⟩
congr {f g u} _ fg hf := by
apply hf.congr
rintro y ⟨hy1, hy2⟩
rcases mem_range.1 hy2 with ⟨x, hx⟩
rw [← hx] at hy1 ⊢
simp only [mfld_simps] at hy1 ⊢
rw [fg _ hy1]
/-- Given a model with corners `(E, H)`, we define the groupoid of invertible `C^n` transformations
of `H` as the invertible maps that are `C^n` when read in `E` through `I`. -/
def contDiffGroupoid : StructureGroupoid H :=
Pregroupoid.groupoid (contDiffPregroupoid n I)
#align cont_diff_groupoid contDiffGroupoid
variable {n}
/-- Inclusion of the groupoid of `C^n` local diffeos in the groupoid of `C^m` local diffeos when
`m ≤ n` -/
theorem contDiffGroupoid_le (h : m ≤ n) : contDiffGroupoid n I ≤ contDiffGroupoid m I := by
rw [contDiffGroupoid, contDiffGroupoid]
apply groupoid_of_pregroupoid_le
intro f s hfs
exact ContDiffOn.of_le hfs h
#align cont_diff_groupoid_le contDiffGroupoid_le
/-- The groupoid of `0`-times continuously differentiable maps is just the groupoid of all
partial homeomorphisms -/
theorem contDiffGroupoid_zero_eq : contDiffGroupoid 0 I = continuousGroupoid H := by
apply le_antisymm le_top
intro u _
-- we have to check that every partial homeomorphism belongs to `contDiffGroupoid 0 I`,
-- by unfolding its definition
change u ∈ contDiffGroupoid 0 I
rw [contDiffGroupoid, mem_groupoid_of_pregroupoid, contDiffPregroupoid]
simp only [contDiffOn_zero]
constructor
· refine I.continuous.comp_continuousOn (u.continuousOn.comp I.continuousOn_symm ?_)
exact (mapsTo_preimage _ _).mono_left inter_subset_left
· refine I.continuous.comp_continuousOn (u.symm.continuousOn.comp I.continuousOn_symm ?_)
exact (mapsTo_preimage _ _).mono_left inter_subset_left
#align cont_diff_groupoid_zero_eq contDiffGroupoid_zero_eq
variable (n)
/-- An identity partial homeomorphism belongs to the `C^n` groupoid. -/
theorem ofSet_mem_contDiffGroupoid {s : Set H} (hs : IsOpen s) :
PartialHomeomorph.ofSet s hs ∈ contDiffGroupoid n I := by
rw [contDiffGroupoid, mem_groupoid_of_pregroupoid]
suffices h : ContDiffOn 𝕜 n (I ∘ I.symm) (I.symm ⁻¹' s ∩ range I) by
simp [h, contDiffPregroupoid]
have : ContDiffOn 𝕜 n id (univ : Set E) := contDiff_id.contDiffOn
exact this.congr_mono (fun x hx => I.right_inv hx.2) (subset_univ _)
#align of_set_mem_cont_diff_groupoid ofSet_mem_contDiffGroupoid
/-- The composition of a partial homeomorphism from `H` to `M` and its inverse belongs to
the `C^n` groupoid. -/
theorem symm_trans_mem_contDiffGroupoid (e : PartialHomeomorph M H) :
e.symm.trans e ∈ contDiffGroupoid n I :=
haveI : e.symm.trans e ≈ PartialHomeomorph.ofSet e.target e.open_target :=
PartialHomeomorph.symm_trans_self _
StructureGroupoid.mem_of_eqOnSource _ (ofSet_mem_contDiffGroupoid n I e.open_target) this
#align symm_trans_mem_cont_diff_groupoid symm_trans_mem_contDiffGroupoid
variable {E' H' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] [TopologicalSpace H']
/-- The product of two smooth partial homeomorphisms is smooth. -/
theorem contDiffGroupoid_prod {I : ModelWithCorners 𝕜 E H} {I' : ModelWithCorners 𝕜 E' H'}
{e : PartialHomeomorph H H} {e' : PartialHomeomorph H' H'} (he : e ∈ contDiffGroupoid ⊤ I)
(he' : e' ∈ contDiffGroupoid ⊤ I') : e.prod e' ∈ contDiffGroupoid ⊤ (I.prod I') := by
cases' he with he he_symm
cases' he' with he' he'_symm
simp only at he he_symm he' he'_symm
constructor <;> simp only [PartialEquiv.prod_source, PartialHomeomorph.prod_toPartialEquiv,
contDiffPregroupoid]
· have h3 := ContDiffOn.prod_map he he'
rw [← I.image_eq, ← I'.image_eq, prod_image_image_eq] at h3
rw [← (I.prod I').image_eq]
exact h3
· have h3 := ContDiffOn.prod_map he_symm he'_symm
rw [← I.image_eq, ← I'.image_eq, prod_image_image_eq] at h3
rw [← (I.prod I').image_eq]
exact h3
#align cont_diff_groupoid_prod contDiffGroupoid_prod
/-- The `C^n` groupoid is closed under restriction. -/
instance : ClosedUnderRestriction (contDiffGroupoid n I) :=
(closedUnderRestriction_iff_id_le _).mpr
(by
rw [StructureGroupoid.le_iff]
rintro e ⟨s, hs, hes⟩
apply (contDiffGroupoid n I).mem_of_eqOnSource' _ _ _ hes
exact ofSet_mem_contDiffGroupoid n I hs)
end contDiffGroupoid
section analyticGroupoid
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]
/-- Given a model with corners `(E, H)`, we define the groupoid of analytic transformations of `H`
as the maps that are analytic and map interior to interior when read in `E` through `I`. We also
explicitly define that they are `C^∞` on the whole domain, since we are only requiring
analyticity on the interior of the domain. -/
def analyticGroupoid : StructureGroupoid H :=
(contDiffGroupoid ∞ I) ⊓ Pregroupoid.groupoid
{ property := fun f s => AnalyticOn 𝕜 (I ∘ f ∘ I.symm) (I.symm ⁻¹' s ∩ interior (range I)) ∧
(I.symm ⁻¹' s ∩ interior (range I)).image (I ∘ f ∘ I.symm) ⊆ interior (range I)
comp := fun {f g u v} hf hg _ _ _ => by
simp only [] at hf hg ⊢
have comp : I ∘ (g ∘ f) ∘ I.symm = (I ∘ g ∘ I.symm) ∘ I ∘ f ∘ I.symm := by ext x; simp
apply And.intro
· simp only [comp, preimage_inter]
refine hg.left.comp (hf.left.mono ?_) ?_
· simp only [subset_inter_iff, inter_subset_right]
rw [inter_assoc]
simp
· intro x hx
apply And.intro
· rw [mem_preimage, comp_apply, I.left_inv]
exact hx.left.right
· apply hf.right
rw [mem_image]
exact ⟨x, ⟨⟨hx.left.left, hx.right⟩, rfl⟩⟩
· simp only [comp]
rw [image_comp]
intro x hx
rw [mem_image] at hx
rcases hx with ⟨x', hx'⟩
refine hg.right ⟨x', And.intro ?_ hx'.right⟩
apply And.intro
· have hx'1 : x' ∈ ((v.preimage f).preimage (I.symm)).image (I ∘ f ∘ I.symm) := by
refine image_subset (I ∘ f ∘ I.symm) ?_ hx'.left
rw [preimage_inter]
refine Subset.trans ?_ (u.preimage I.symm).inter_subset_right
apply inter_subset_left
rcases hx'1 with ⟨x'', hx''⟩
rw [hx''.right.symm]
simp only [comp_apply, mem_preimage, I.left_inv]
exact hx''.left
· rw [mem_image] at hx'
rcases hx'.left with ⟨x'', hx''⟩
exact hf.right ⟨x'', ⟨⟨hx''.left.left.left, hx''.left.right⟩, hx''.right⟩⟩
id_mem := by
apply And.intro
· simp only [preimage_univ, univ_inter]
exact AnalyticOn.congr isOpen_interior
(f := (1 : E →L[𝕜] E)) (fun x _ => (1 : E →L[𝕜] E).analyticAt x)
(fun z hz => (I.right_inv (interior_subset hz)).symm)
· intro x hx
simp only [id_comp, comp_apply, preimage_univ, univ_inter, mem_image] at hx
rcases hx with ⟨y, hy⟩
rw [← hy.right, I.right_inv (interior_subset hy.left)]
exact hy.left
locality := fun {f u} _ h => by
simp only [] at h
simp only [AnalyticOn]
apply And.intro
· intro x hx
rcases h (I.symm x) (mem_preimage.mp hx.left) with ⟨v, hv⟩
exact hv.right.right.left x ⟨mem_preimage.mpr ⟨hx.left, hv.right.left⟩, hx.right⟩
· apply mapsTo'.mp
simp only [MapsTo]
intro x hx
rcases h (I.symm x) hx.left with ⟨v, hv⟩
apply hv.right.right.right
rw [mem_image]
have hx' := And.intro hx (mem_preimage.mpr hv.right.left)
rw [← mem_inter_iff, inter_comm, ← inter_assoc, ← preimage_inter, inter_comm v u] at hx'
exact ⟨x, ⟨hx', rfl⟩⟩
congr := fun {f g u} hu fg hf => by
simp only [] at hf ⊢
apply And.intro
· refine AnalyticOn.congr (IsOpen.inter (hu.preimage I.continuous_symm) isOpen_interior)
hf.left ?_
intro z hz
simp only [comp_apply]
rw [fg (I.symm z) hz.left]
· intro x hx
apply hf.right
rw [mem_image] at hx ⊢
rcases hx with ⟨y, hy⟩
refine ⟨y, ⟨hy.left, ?_⟩⟩
rw [comp_apply, comp_apply, fg (I.symm y) hy.left.left] at hy
exact hy.right }
/-- An identity partial homeomorphism belongs to the analytic groupoid. -/
theorem ofSet_mem_analyticGroupoid {s : Set H} (hs : IsOpen s) :
PartialHomeomorph.ofSet s hs ∈ analyticGroupoid I := by
rw [analyticGroupoid]
refine And.intro (ofSet_mem_contDiffGroupoid ∞ I hs) ?_
apply mem_groupoid_of_pregroupoid.mpr
suffices h : AnalyticOn 𝕜 (I ∘ I.symm) (I.symm ⁻¹' s ∩ interior (range I)) ∧
(I.symm ⁻¹' s ∩ interior (range I)).image (I ∘ I.symm) ⊆ interior (range I) by
simp only [PartialHomeomorph.ofSet_apply, id_comp, PartialHomeomorph.ofSet_toPartialEquiv,
PartialEquiv.ofSet_source, h, comp_apply, mem_range, image_subset_iff, true_and,
PartialHomeomorph.ofSet_symm, PartialEquiv.ofSet_target, and_self]
intro x hx
refine mem_preimage.mpr ?_
rw [← I.right_inv (interior_subset hx.right)] at hx
exact hx.right
apply And.intro
· have : AnalyticOn 𝕜 (1 : E →L[𝕜] E) (univ : Set E) := (fun x _ => (1 : E →L[𝕜] E).analyticAt x)
exact (this.mono (subset_univ (s.preimage (I.symm) ∩ interior (range I)))).congr
((hs.preimage I.continuous_symm).inter isOpen_interior)
fun z hz => (I.right_inv (interior_subset hz.right)).symm
· intro x hx
simp only [comp_apply, mem_image] at hx
rcases hx with ⟨y, hy⟩
rw [← hy.right, I.right_inv (interior_subset hy.left.right)]
exact hy.left.right
/-- The composition of a partial homeomorphism from `H` to `M` and its inverse belongs to
the analytic groupoid. -/
theorem symm_trans_mem_analyticGroupoid (e : PartialHomeomorph M H) :
e.symm.trans e ∈ analyticGroupoid I :=
haveI : e.symm.trans e ≈ PartialHomeomorph.ofSet e.target e.open_target :=
PartialHomeomorph.symm_trans_self _
StructureGroupoid.mem_of_eqOnSource _ (ofSet_mem_analyticGroupoid I e.open_target) this
/-- The analytic groupoid is closed under restriction. -/
instance : ClosedUnderRestriction (analyticGroupoid I) :=
(closedUnderRestriction_iff_id_le _).mpr
(by
rw [StructureGroupoid.le_iff]
rintro e ⟨s, hs, hes⟩
apply (analyticGroupoid I).mem_of_eqOnSource' _ _ _ hes
exact ofSet_mem_analyticGroupoid I hs)
/-- The analytic groupoid on a boundaryless charted space modeled on a complete vector space
consists of the partial homeomorphisms which are analytic and have analytic inverse. -/
theorem mem_analyticGroupoid_of_boundaryless [CompleteSpace E] [I.Boundaryless]
(e : PartialHomeomorph H H) :
e ∈ analyticGroupoid I ↔ AnalyticOn 𝕜 (I ∘ e ∘ I.symm) (I '' e.source) ∧
AnalyticOn 𝕜 (I ∘ e.symm ∘ I.symm) (I '' e.target) := by
apply Iff.intro
· intro he
have := mem_groupoid_of_pregroupoid.mp he.right
simp only [I.image_eq, I.range_eq_univ, interior_univ, subset_univ, and_true] at this ⊢
exact this
· intro he
apply And.intro
all_goals apply mem_groupoid_of_pregroupoid.mpr; simp only [I.image_eq, I.range_eq_univ,
interior_univ, subset_univ, and_true, contDiffPregroupoid] at he ⊢
· exact ⟨he.left.contDiffOn, he.right.contDiffOn⟩
· exact he
end analyticGroupoid
section SmoothManifoldWithCorners
/-! ### Smooth manifolds with corners -/
/-- Typeclass defining smooth manifolds with corners with respect to a model with corners, over a
field `𝕜` and with infinite smoothness to simplify typeclass search and statements later on. -/
class SmoothManifoldWithCorners {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] extends
HasGroupoid M (contDiffGroupoid ∞ I) : Prop
#align smooth_manifold_with_corners SmoothManifoldWithCorners
theorem SmoothManifoldWithCorners.mk' {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]
[gr : HasGroupoid M (contDiffGroupoid ∞ I)] : SmoothManifoldWithCorners I M :=
{ gr with }
#align smooth_manifold_with_corners.mk' SmoothManifoldWithCorners.mk'
theorem smoothManifoldWithCorners_of_contDiffOn {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]
(h : ∀ e e' : PartialHomeomorph M H, e ∈ atlas H M → e' ∈ atlas H M →
ContDiffOn 𝕜 ⊤ (I ∘ e.symm ≫ₕ e' ∘ I.symm) (I.symm ⁻¹' (e.symm ≫ₕ e').source ∩ range I)) :
SmoothManifoldWithCorners I M where
compatible := by
haveI : HasGroupoid M (contDiffGroupoid ∞ I) := hasGroupoid_of_pregroupoid _ (h _ _)
apply StructureGroupoid.compatible
#align smooth_manifold_with_corners_of_cont_diff_on smoothManifoldWithCorners_of_contDiffOn
/-- For any model with corners, the model space is a smooth manifold -/
instance model_space_smooth {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
{I : ModelWithCorners 𝕜 E H} : SmoothManifoldWithCorners I H :=
{ hasGroupoid_model_space _ _ with }
#align model_space_smooth model_space_smooth
end SmoothManifoldWithCorners
namespace SmoothManifoldWithCorners
/- We restate in the namespace `SmoothManifoldWithCorners` some lemmas that hold for general
charted space with a structure groupoid, avoiding the need to specify the groupoid
`contDiffGroupoid ∞ I` explicitly. -/
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]
/-- The maximal atlas of `M` for the smooth manifold with corners structure corresponding to the
model with corners `I`. -/
def maximalAtlas :=
(contDiffGroupoid ∞ I).maximalAtlas M
#align smooth_manifold_with_corners.maximal_atlas SmoothManifoldWithCorners.maximalAtlas
variable {M}
theorem subset_maximalAtlas [SmoothManifoldWithCorners I M] : atlas H M ⊆ maximalAtlas I M :=
StructureGroupoid.subset_maximalAtlas _
#align smooth_manifold_with_corners.subset_maximal_atlas SmoothManifoldWithCorners.subset_maximalAtlas
theorem chart_mem_maximalAtlas [SmoothManifoldWithCorners I M] (x : M) :
chartAt H x ∈ maximalAtlas I M :=
StructureGroupoid.chart_mem_maximalAtlas _ x
#align smooth_manifold_with_corners.chart_mem_maximal_atlas SmoothManifoldWithCorners.chart_mem_maximalAtlas
variable {I}
theorem compatible_of_mem_maximalAtlas {e e' : PartialHomeomorph M H} (he : e ∈ maximalAtlas I M)
(he' : e' ∈ maximalAtlas I M) : e.symm.trans e' ∈ contDiffGroupoid ∞ I :=
StructureGroupoid.compatible_of_mem_maximalAtlas he he'
#align smooth_manifold_with_corners.compatible_of_mem_maximal_atlas SmoothManifoldWithCorners.compatible_of_mem_maximalAtlas
/-- The product of two smooth manifolds with corners is naturally a smooth manifold with corners. -/
instance prod {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H : Type*}
[TopologicalSpace H] {I : ModelWithCorners 𝕜 E H} {H' : Type*} [TopologicalSpace H']
{I' : ModelWithCorners 𝕜 E' H'} (M : Type*) [TopologicalSpace M] [ChartedSpace H M]
[SmoothManifoldWithCorners I M] (M' : Type*) [TopologicalSpace M'] [ChartedSpace H' M']
[SmoothManifoldWithCorners I' M'] : SmoothManifoldWithCorners (I.prod I') (M × M') where
compatible := by
rintro f g ⟨f1, hf1, f2, hf2, rfl⟩ ⟨g1, hg1, g2, hg2, rfl⟩
rw [PartialHomeomorph.prod_symm, PartialHomeomorph.prod_trans]
have h1 := (contDiffGroupoid ⊤ I).compatible hf1 hg1
have h2 := (contDiffGroupoid ⊤ I').compatible hf2 hg2
exact contDiffGroupoid_prod h1 h2
#align smooth_manifold_with_corners.prod SmoothManifoldWithCorners.prod
end SmoothManifoldWithCorners
theorem PartialHomeomorph.singleton_smoothManifoldWithCorners
{𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
{H : Type*} [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H)
{M : Type*} [TopologicalSpace M] (e : PartialHomeomorph M H) (h : e.source = Set.univ) :
@SmoothManifoldWithCorners 𝕜 _ E _ _ H _ I M _ (e.singletonChartedSpace h) :=
@SmoothManifoldWithCorners.mk' _ _ _ _ _ _ _ _ _ _ (id _) <|
e.singleton_hasGroupoid h (contDiffGroupoid ∞ I)
#align local_homeomorph.singleton_smooth_manifold_with_corners PartialHomeomorph.singleton_smoothManifoldWithCorners
theorem OpenEmbedding.singleton_smoothManifoldWithCorners {𝕜 : Type*} [NontriviallyNormedField 𝕜]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) {M : Type*} [TopologicalSpace M] [Nonempty M] {f : M → H}
(h : OpenEmbedding f) :
@SmoothManifoldWithCorners 𝕜 _ E _ _ H _ I M _ h.singletonChartedSpace :=
(h.toPartialHomeomorph f).singleton_smoothManifoldWithCorners I (by simp)
#align open_embedding.singleton_smooth_manifold_with_corners OpenEmbedding.singleton_smoothManifoldWithCorners
namespace TopologicalSpace.Opens
open TopologicalSpace
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] [SmoothManifoldWithCorners I M] (s : Opens M)
instance : SmoothManifoldWithCorners I s :=
{ s.instHasGroupoid (contDiffGroupoid ∞ I) with }
end TopologicalSpace.Opens
section ExtendedCharts
open scoped Topology
variable {𝕜 E M H E' M' H' : Type*} [NontriviallyNormedField 𝕜] [NormedAddCommGroup E]
[NormedSpace 𝕜 E] [TopologicalSpace H] [TopologicalSpace M] (f f' : PartialHomeomorph M H)
(I : ModelWithCorners 𝕜 E H) [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] [TopologicalSpace H']
[TopologicalSpace M'] (I' : ModelWithCorners 𝕜 E' H') {s t : Set M}
/-!
### Extended charts
In a smooth manifold with corners, the model space is the space `H`. However, we will also
need to use extended charts taking values in the model vector space `E`. These extended charts are
not `PartialHomeomorph` as the target is not open in `E` in general, but we can still register them
as `PartialEquiv`.
-/
namespace PartialHomeomorph
/-- Given a chart `f` on a manifold with corners, `f.extend I` is the extended chart to the model
vector space. -/
@[simp, mfld_simps]
def extend : PartialEquiv M E :=
f.toPartialEquiv ≫ I.toPartialEquiv
#align local_homeomorph.extend PartialHomeomorph.extend
theorem extend_coe : ⇑(f.extend I) = I ∘ f :=
rfl
#align local_homeomorph.extend_coe PartialHomeomorph.extend_coe
theorem extend_coe_symm : ⇑(f.extend I).symm = f.symm ∘ I.symm :=
rfl
#align local_homeomorph.extend_coe_symm PartialHomeomorph.extend_coe_symm
theorem extend_source : (f.extend I).source = f.source := by
rw [extend, PartialEquiv.trans_source, I.source_eq, preimage_univ, inter_univ]
#align local_homeomorph.extend_source PartialHomeomorph.extend_source
theorem isOpen_extend_source : IsOpen (f.extend I).source := by
rw [extend_source]
exact f.open_source
#align local_homeomorph.is_open_extend_source PartialHomeomorph.isOpen_extend_source
theorem extend_target : (f.extend I).target = I.symm ⁻¹' f.target ∩ range I := by
simp_rw [extend, PartialEquiv.trans_target, I.target_eq, I.toPartialEquiv_coe_symm, inter_comm]
#align local_homeomorph.extend_target PartialHomeomorph.extend_target
theorem extend_target' : (f.extend I).target = I '' f.target := by
rw [extend, PartialEquiv.trans_target'', I.source_eq, univ_inter, I.toPartialEquiv_coe]
lemma isOpen_extend_target [I.Boundaryless] : IsOpen (f.extend I).target := by
rw [extend_target, I.range_eq_univ, inter_univ]
exact I.continuous_symm.isOpen_preimage _ f.open_target
theorem mapsTo_extend (hs : s ⊆ f.source) :
MapsTo (f.extend I) s ((f.extend I).symm ⁻¹' s ∩ range I) := by
rw [mapsTo', extend_coe, extend_coe_symm, preimage_comp, ← I.image_eq, image_comp,
f.image_eq_target_inter_inv_preimage hs]
exact image_subset _ inter_subset_right
#align local_homeomorph.maps_to_extend PartialHomeomorph.mapsTo_extend
theorem extend_left_inv {x : M} (hxf : x ∈ f.source) : (f.extend I).symm (f.extend I x) = x :=
(f.extend I).left_inv <| by rwa [f.extend_source]
#align local_homeomorph.extend_left_inv PartialHomeomorph.extend_left_inv
/-- Variant of `f.extend_left_inv I`, stated in terms of images. -/
lemma extend_left_inv' (ht: t ⊆ f.source) : ((f.extend I).symm ∘ (f.extend I)) '' t = t :=
EqOn.image_eq_self (fun _ hx ↦ f.extend_left_inv I (ht hx))
theorem extend_source_mem_nhds {x : M} (h : x ∈ f.source) : (f.extend I).source ∈ 𝓝 x :=
(isOpen_extend_source f I).mem_nhds <| by rwa [f.extend_source I]
#align local_homeomorph.extend_source_mem_nhds PartialHomeomorph.extend_source_mem_nhds
theorem extend_source_mem_nhdsWithin {x : M} (h : x ∈ f.source) : (f.extend I).source ∈ 𝓝[s] x :=
mem_nhdsWithin_of_mem_nhds <| extend_source_mem_nhds f I h
#align local_homeomorph.extend_source_mem_nhds_within PartialHomeomorph.extend_source_mem_nhdsWithin
theorem continuousOn_extend : ContinuousOn (f.extend I) (f.extend I).source := by
refine I.continuous.comp_continuousOn ?_
rw [extend_source]
exact f.continuousOn
#align local_homeomorph.continuous_on_extend PartialHomeomorph.continuousOn_extend
theorem continuousAt_extend {x : M} (h : x ∈ f.source) : ContinuousAt (f.extend I) x :=
(continuousOn_extend f I).continuousAt <| extend_source_mem_nhds f I h
#align local_homeomorph.continuous_at_extend PartialHomeomorph.continuousAt_extend
theorem map_extend_nhds {x : M} (hy : x ∈ f.source) :
map (f.extend I) (𝓝 x) = 𝓝[range I] f.extend I x := by
rwa [extend_coe, comp_apply, ← I.map_nhds_eq, ← f.map_nhds_eq, map_map]
#align local_homeomorph.map_extend_nhds PartialHomeomorph.map_extend_nhds
theorem map_extend_nhds_of_boundaryless [I.Boundaryless] {x : M} (hx : x ∈ f.source) :
map (f.extend I) (𝓝 x) = 𝓝 (f.extend I x) := by
rw [f.map_extend_nhds _ hx, I.range_eq_univ, nhdsWithin_univ]
theorem extend_target_mem_nhdsWithin {y : M} (hy : y ∈ f.source) :
(f.extend I).target ∈ 𝓝[range I] f.extend I y := by
rw [← PartialEquiv.image_source_eq_target, ← map_extend_nhds f I hy]
exact image_mem_map (extend_source_mem_nhds _ _ hy)
#align local_homeomorph.extend_target_mem_nhds_within PartialHomeomorph.extend_target_mem_nhdsWithin
theorem extend_image_nhd_mem_nhds_of_boundaryless [I.Boundaryless] {x} (hx : x ∈ f.source)
{s : Set M} (h : s ∈ 𝓝 x) : (f.extend I) '' s ∈ 𝓝 ((f.extend I) x) := by
rw [← f.map_extend_nhds_of_boundaryless _ hx, Filter.mem_map]
filter_upwards [h] using subset_preimage_image (f.extend I) s
theorem extend_target_subset_range : (f.extend I).target ⊆ range I := by simp only [mfld_simps]
#align local_homeomorph.extend_target_subset_range PartialHomeomorph.extend_target_subset_range
lemma interior_extend_target_subset_interior_range :
interior (f.extend I).target ⊆ interior (range I) := by
rw [f.extend_target, interior_inter, (f.open_target.preimage I.continuous_symm).interior_eq]
exact inter_subset_right
/-- If `y ∈ f.target` and `I y ∈ interior (range I)`,
then `I y` is an interior point of `(I ∘ f).target`. -/
lemma mem_interior_extend_target {y : H} (hy : y ∈ f.target)
(hy' : I y ∈ interior (range I)) : I y ∈ interior (f.extend I).target := by
rw [f.extend_target, interior_inter, (f.open_target.preimage I.continuous_symm).interior_eq,
mem_inter_iff, mem_preimage]
exact ⟨mem_of_eq_of_mem (I.left_inv (y)) hy, hy'⟩
theorem nhdsWithin_extend_target_eq {y : M} (hy : y ∈ f.source) :
𝓝[(f.extend I).target] f.extend I y = 𝓝[range I] f.extend I y :=
(nhdsWithin_mono _ (extend_target_subset_range _ _)).antisymm <|
nhdsWithin_le_of_mem (extend_target_mem_nhdsWithin _ _ hy)
#align local_homeomorph.nhds_within_extend_target_eq PartialHomeomorph.nhdsWithin_extend_target_eq
theorem continuousAt_extend_symm' {x : E} (h : x ∈ (f.extend I).target) :
ContinuousAt (f.extend I).symm x :=
(f.continuousAt_symm h.2).comp I.continuous_symm.continuousAt
#align local_homeomorph.continuous_at_extend_symm' PartialHomeomorph.continuousAt_extend_symm'
theorem continuousAt_extend_symm {x : M} (h : x ∈ f.source) :
ContinuousAt (f.extend I).symm (f.extend I x) :=
continuousAt_extend_symm' f I <| (f.extend I).map_source <| by rwa [f.extend_source]
#align local_homeomorph.continuous_at_extend_symm PartialHomeomorph.continuousAt_extend_symm
theorem continuousOn_extend_symm : ContinuousOn (f.extend I).symm (f.extend I).target := fun _ h =>
(continuousAt_extend_symm' _ _ h).continuousWithinAt
#align local_homeomorph.continuous_on_extend_symm PartialHomeomorph.continuousOn_extend_symm
theorem extend_symm_continuousWithinAt_comp_right_iff {X} [TopologicalSpace X] {g : M → X}
{s : Set M} {x : M} :
ContinuousWithinAt (g ∘ (f.extend I).symm) ((f.extend I).symm ⁻¹' s ∩ range I) (f.extend I x) ↔
ContinuousWithinAt (g ∘ f.symm) (f.symm ⁻¹' s) (f x) := by
rw [← I.symm_continuousWithinAt_comp_right_iff]; rfl
#align local_homeomorph.extend_symm_continuous_within_at_comp_right_iff PartialHomeomorph.extend_symm_continuousWithinAt_comp_right_iff
theorem isOpen_extend_preimage' {s : Set E} (hs : IsOpen s) :
IsOpen ((f.extend I).source ∩ f.extend I ⁻¹' s) :=
(continuousOn_extend f I).isOpen_inter_preimage (isOpen_extend_source _ _) hs
#align local_homeomorph.is_open_extend_preimage' PartialHomeomorph.isOpen_extend_preimage'
theorem isOpen_extend_preimage {s : Set E} (hs : IsOpen s) :
IsOpen (f.source ∩ f.extend I ⁻¹' s) := by
rw [← extend_source f I]; exact isOpen_extend_preimage' f I hs
#align local_homeomorph.is_open_extend_preimage PartialHomeomorph.isOpen_extend_preimage
theorem map_extend_nhdsWithin_eq_image {y : M} (hy : y ∈ f.source) :
map (f.extend I) (𝓝[s] y) = 𝓝[f.extend I '' ((f.extend I).source ∩ s)] f.extend I y := by
set e := f.extend I
calc
map e (𝓝[s] y) = map e (𝓝[e.source ∩ s] y) :=
congr_arg (map e) (nhdsWithin_inter_of_mem (extend_source_mem_nhdsWithin f I hy)).symm
_ = 𝓝[e '' (e.source ∩ s)] e y :=
((f.extend I).leftInvOn.mono inter_subset_left).map_nhdsWithin_eq
((f.extend I).left_inv <| by rwa [f.extend_source])
(continuousAt_extend_symm f I hy).continuousWithinAt
(continuousAt_extend f I hy).continuousWithinAt
#align local_homeomorph.map_extend_nhds_within_eq_image PartialHomeomorph.map_extend_nhdsWithin_eq_image
theorem map_extend_nhdsWithin_eq_image_of_subset {y : M} (hy : y ∈ f.source) (hs : s ⊆ f.source) :
map (f.extend I) (𝓝[s] y) = 𝓝[f.extend I '' s] f.extend I y := by
rw [map_extend_nhdsWithin_eq_image _ _ hy, inter_eq_self_of_subset_right]
rwa [extend_source]
theorem map_extend_nhdsWithin {y : M} (hy : y ∈ f.source) :
map (f.extend I) (𝓝[s] y) = 𝓝[(f.extend I).symm ⁻¹' s ∩ range I] f.extend I y := by
rw [map_extend_nhdsWithin_eq_image f I hy, nhdsWithin_inter, ←
nhdsWithin_extend_target_eq _ _ hy, ← nhdsWithin_inter, (f.extend I).image_source_inter_eq',
inter_comm]
#align local_homeomorph.map_extend_nhds_within PartialHomeomorph.map_extend_nhdsWithin
theorem map_extend_symm_nhdsWithin {y : M} (hy : y ∈ f.source) :
map (f.extend I).symm (𝓝[(f.extend I).symm ⁻¹' s ∩ range I] f.extend I y) = 𝓝[s] y := by
rw [← map_extend_nhdsWithin f I hy, map_map, Filter.map_congr, map_id]
exact (f.extend I).leftInvOn.eqOn.eventuallyEq_of_mem (extend_source_mem_nhdsWithin _ _ hy)
#align local_homeomorph.map_extend_symm_nhds_within PartialHomeomorph.map_extend_symm_nhdsWithin
theorem map_extend_symm_nhdsWithin_range {y : M} (hy : y ∈ f.source) :
map (f.extend I).symm (𝓝[range I] f.extend I y) = 𝓝 y := by
rw [← nhdsWithin_univ, ← map_extend_symm_nhdsWithin f I hy, preimage_univ, univ_inter]
#align local_homeomorph.map_extend_symm_nhds_within_range PartialHomeomorph.map_extend_symm_nhdsWithin_range
theorem tendsto_extend_comp_iff {α : Type*} {l : Filter α} {g : α → M}
(hg : ∀ᶠ z in l, g z ∈ f.source) {y : M} (hy : y ∈ f.source) :
Tendsto (f.extend I ∘ g) l (𝓝 (f.extend I y)) ↔ Tendsto g l (𝓝 y) := by
refine ⟨fun h u hu ↦ mem_map.2 ?_, (continuousAt_extend _ _ hy).tendsto.comp⟩
have := (f.continuousAt_extend_symm I hy).tendsto.comp h
rw [extend_left_inv _ _ hy] at this
filter_upwards [hg, mem_map.1 (this hu)] with z hz hzu
simpa only [(· ∘ ·), extend_left_inv _ _ hz, mem_preimage] using hzu
-- there is no definition `writtenInExtend` but we already use some made-up names in this file
theorem continuousWithinAt_writtenInExtend_iff {f' : PartialHomeomorph M' H'} {g : M → M'} {y : M}
(hy : y ∈ f.source) (hgy : g y ∈ f'.source) (hmaps : MapsTo g s f'.source) :
ContinuousWithinAt (f'.extend I' ∘ g ∘ (f.extend I).symm)
((f.extend I).symm ⁻¹' s ∩ range I) (f.extend I y) ↔ ContinuousWithinAt g s y := by
unfold ContinuousWithinAt
simp only [comp_apply]
rw [extend_left_inv _ _ hy, f'.tendsto_extend_comp_iff _ _ hgy,
← f.map_extend_symm_nhdsWithin I hy, tendsto_map'_iff]
rw [← f.map_extend_nhdsWithin I hy, eventually_map]
filter_upwards [inter_mem_nhdsWithin _ (f.open_source.mem_nhds hy)] with z hz
rw [comp_apply, extend_left_inv _ _ hz.2]
exact hmaps hz.1
-- there is no definition `writtenInExtend` but we already use some made-up names in this file
/-- If `s ⊆ f.source` and `g x ∈ f'.source` whenever `x ∈ s`, then `g` is continuous on `s` if and
only if `g` written in charts `f.extend I` and `f'.extend I'` is continuous on `f.extend I '' s`. -/
theorem continuousOn_writtenInExtend_iff {f' : PartialHomeomorph M' H'} {g : M → M'}
(hs : s ⊆ f.source) (hmaps : MapsTo g s f'.source) :
ContinuousOn (f'.extend I' ∘ g ∘ (f.extend I).symm) (f.extend I '' s) ↔ ContinuousOn g s := by
refine forall_mem_image.trans <| forall₂_congr fun x hx ↦ ?_
refine (continuousWithinAt_congr_nhds ?_).trans
(continuousWithinAt_writtenInExtend_iff _ _ _ (hs hx) (hmaps hx) hmaps)
rw [← map_extend_nhdsWithin_eq_image_of_subset, ← map_extend_nhdsWithin]
exacts [hs hx, hs hx, hs]
/-- Technical lemma ensuring that the preimage under an extended chart of a neighborhood of a point
in the source is a neighborhood of the preimage, within a set. -/
theorem extend_preimage_mem_nhdsWithin {x : M} (h : x ∈ f.source) (ht : t ∈ 𝓝[s] x) :
(f.extend I).symm ⁻¹' t ∈ 𝓝[(f.extend I).symm ⁻¹' s ∩ range I] f.extend I x := by
rwa [← map_extend_symm_nhdsWithin f I h, mem_map] at ht
#align local_homeomorph.extend_preimage_mem_nhds_within PartialHomeomorph.extend_preimage_mem_nhdsWithin
theorem extend_preimage_mem_nhds {x : M} (h : x ∈ f.source) (ht : t ∈ 𝓝 x) :
(f.extend I).symm ⁻¹' t ∈ 𝓝 (f.extend I x) := by
apply (continuousAt_extend_symm f I h).preimage_mem_nhds
rwa [(f.extend I).left_inv]
rwa [f.extend_source]
#align local_homeomorph.extend_preimage_mem_nhds PartialHomeomorph.extend_preimage_mem_nhds
/-- Technical lemma to rewrite suitably the preimage of an intersection under an extended chart, to
bring it into a convenient form to apply derivative lemmas. -/
theorem extend_preimage_inter_eq :
(f.extend I).symm ⁻¹' (s ∩ t) ∩ range I =
(f.extend I).symm ⁻¹' s ∩ range I ∩ (f.extend I).symm ⁻¹' t := by
mfld_set_tac
#align local_homeomorph.extend_preimage_inter_eq PartialHomeomorph.extend_preimage_inter_eq
-- Porting note: an `aux` lemma that is no longer needed. Delete?
theorem extend_symm_preimage_inter_range_eventuallyEq_aux {s : Set M} {x : M} (hx : x ∈ f.source) :
((f.extend I).symm ⁻¹' s ∩ range I : Set _) =ᶠ[𝓝 (f.extend I x)]
((f.extend I).target ∩ (f.extend I).symm ⁻¹' s : Set _) := by
rw [f.extend_target, inter_assoc, inter_comm (range I)]
conv =>
congr
· skip
rw [← univ_inter (_ ∩ range I)]
refine (eventuallyEq_univ.mpr ?_).symm.inter EventuallyEq.rfl
refine I.continuousAt_symm.preimage_mem_nhds (f.open_target.mem_nhds ?_)
simp_rw [f.extend_coe, Function.comp_apply, I.left_inv, f.mapsTo hx]
#align local_homeomorph.extend_symm_preimage_inter_range_eventually_eq_aux PartialHomeomorph.extend_symm_preimage_inter_range_eventuallyEq_aux
theorem extend_symm_preimage_inter_range_eventuallyEq {s : Set M} {x : M} (hs : s ⊆ f.source)
(hx : x ∈ f.source) :
((f.extend I).symm ⁻¹' s ∩ range I : Set _) =ᶠ[𝓝 (f.extend I x)] f.extend I '' s := by
rw [← nhdsWithin_eq_iff_eventuallyEq, ← map_extend_nhdsWithin _ _ hx,
map_extend_nhdsWithin_eq_image_of_subset _ _ hx hs]
#align local_homeomorph.extend_symm_preimage_inter_range_eventually_eq PartialHomeomorph.extend_symm_preimage_inter_range_eventuallyEq
/-! We use the name `extend_coord_change` for `(f'.extend I).symm ≫ f.extend I`. -/
theorem extend_coord_change_source :
((f.extend I).symm ≫ f'.extend I).source = I '' (f.symm ≫ₕ f').source := by
simp_rw [PartialEquiv.trans_source, I.image_eq, extend_source, PartialEquiv.symm_source,
extend_target, inter_right_comm _ (range I)]
rfl
#align local_homeomorph.extend_coord_change_source PartialHomeomorph.extend_coord_change_source
theorem extend_image_source_inter :
f.extend I '' (f.source ∩ f'.source) = ((f.extend I).symm ≫ f'.extend I).source := by
simp_rw [f.extend_coord_change_source, f.extend_coe, image_comp I f, trans_source'', symm_symm,
symm_target]
#align local_homeomorph.extend_image_source_inter PartialHomeomorph.extend_image_source_inter
theorem extend_coord_change_source_mem_nhdsWithin {x : E}
(hx : x ∈ ((f.extend I).symm ≫ f'.extend I).source) :
((f.extend I).symm ≫ f'.extend I).source ∈ 𝓝[range I] x := by
rw [f.extend_coord_change_source] at hx ⊢
obtain ⟨x, hx, rfl⟩ := hx
refine I.image_mem_nhdsWithin ?_
exact (PartialHomeomorph.open_source _).mem_nhds hx
#align local_homeomorph.extend_coord_change_source_mem_nhds_within PartialHomeomorph.extend_coord_change_source_mem_nhdsWithin
theorem extend_coord_change_source_mem_nhdsWithin' {x : M} (hxf : x ∈ f.source)
(hxf' : x ∈ f'.source) :
((f.extend I).symm ≫ f'.extend I).source ∈ 𝓝[range I] f.extend I x := by
apply extend_coord_change_source_mem_nhdsWithin
rw [← extend_image_source_inter]
exact mem_image_of_mem _ ⟨hxf, hxf'⟩
#align local_homeomorph.extend_coord_change_source_mem_nhds_within' PartialHomeomorph.extend_coord_change_source_mem_nhdsWithin'
variable {f f'}
open SmoothManifoldWithCorners
| Mathlib/Geometry/Manifold/SmoothManifoldWithCorners.lean | 1,250 | 1,254 | theorem contDiffOn_extend_coord_change [ChartedSpace H M] (hf : f ∈ maximalAtlas I M)
(hf' : f' ∈ maximalAtlas I M) :
ContDiffOn 𝕜 ⊤ (f.extend I ∘ (f'.extend I).symm) ((f'.extend I).symm ≫ f.extend I).source := by |
rw [extend_coord_change_source, I.image_eq]
exact (StructureGroupoid.compatible_of_mem_maximalAtlas hf' hf).1
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Order.BigOperators.Ring.Finset
import Mathlib.Data.Nat.Totient
import Mathlib.GroupTheory.OrderOfElement
import Mathlib.GroupTheory.Subgroup.Simple
import Mathlib.Tactic.Group
import Mathlib.GroupTheory.Exponent
#align_import group_theory.specific_groups.cyclic from "leanprover-community/mathlib"@"0f6670b8af2dff699de1c0b4b49039b31bc13c46"
/-!
# Cyclic groups
A group `G` is called cyclic if there exists an element `g : G` such that every element of `G` is of
the form `g ^ n` for some `n : ℕ`. This file only deals with the predicate on a group to be cyclic.
For the concrete cyclic group of order `n`, see `Data.ZMod.Basic`.
## Main definitions
* `IsCyclic` is a predicate on a group stating that the group is cyclic.
## Main statements
* `isCyclic_of_prime_card` proves that a finite group of prime order is cyclic.
* `isSimpleGroup_of_prime_card`, `IsSimpleGroup.isCyclic`,
and `IsSimpleGroup.prime_card` classify finite simple abelian groups.
* `IsCyclic.exponent_eq_card`: For a finite cyclic group `G`, the exponent is equal to
the group's cardinality.
* `IsCyclic.exponent_eq_zero_of_infinite`: Infinite cyclic groups have exponent zero.
* `IsCyclic.iff_exponent_eq_card`: A finite commutative group is cyclic iff its exponent
is equal to its cardinality.
## Tags
cyclic group
-/
universe u
variable {α : Type u} {a : α}
section Cyclic
attribute [local instance] setFintype
open Subgroup
/-- A group is called *cyclic* if it is generated by a single element. -/
class IsAddCyclic (α : Type u) [AddGroup α] : Prop where
exists_generator : ∃ g : α, ∀ x, x ∈ AddSubgroup.zmultiples g
#align is_add_cyclic IsAddCyclic
/-- A group is called *cyclic* if it is generated by a single element. -/
@[to_additive]
class IsCyclic (α : Type u) [Group α] : Prop where
exists_generator : ∃ g : α, ∀ x, x ∈ zpowers g
#align is_cyclic IsCyclic
@[to_additive]
instance (priority := 100) isCyclic_of_subsingleton [Group α] [Subsingleton α] : IsCyclic α :=
⟨⟨1, fun x => by
rw [Subsingleton.elim x 1]
exact mem_zpowers 1⟩⟩
#align is_cyclic_of_subsingleton isCyclic_of_subsingleton
#align is_add_cyclic_of_subsingleton isAddCyclic_of_subsingleton
@[simp]
theorem isCyclic_multiplicative_iff [AddGroup α] : IsCyclic (Multiplicative α) ↔ IsAddCyclic α :=
⟨fun H ↦ ⟨H.1⟩, fun H ↦ ⟨H.1⟩⟩
instance isCyclic_multiplicative [AddGroup α] [IsAddCyclic α] : IsCyclic (Multiplicative α) :=
isCyclic_multiplicative_iff.mpr inferInstance
@[simp]
theorem isAddCyclic_additive_iff [Group α] : IsAddCyclic (Additive α) ↔ IsCyclic α :=
⟨fun H ↦ ⟨H.1⟩, fun H ↦ ⟨H.1⟩⟩
instance isAddCyclic_additive [Group α] [IsCyclic α] : IsAddCyclic (Additive α) :=
isAddCyclic_additive_iff.mpr inferInstance
/-- A cyclic group is always commutative. This is not an `instance` because often we have a better
proof of `CommGroup`. -/
@[to_additive
"A cyclic group is always commutative. This is not an `instance` because often we have
a better proof of `AddCommGroup`."]
def IsCyclic.commGroup [hg : Group α] [IsCyclic α] : CommGroup α :=
{ hg with
mul_comm := fun x y =>
let ⟨_, hg⟩ := IsCyclic.exists_generator (α := α)
let ⟨_, hn⟩ := hg x
let ⟨_, hm⟩ := hg y
hm ▸ hn ▸ zpow_mul_comm _ _ _ }
#align is_cyclic.comm_group IsCyclic.commGroup
#align is_add_cyclic.add_comm_group IsAddCyclic.addCommGroup
variable [Group α]
/-- A non-cyclic multiplicative group is non-trivial. -/
@[to_additive "A non-cyclic additive group is non-trivial."]
theorem Nontrivial.of_not_isCyclic (nc : ¬IsCyclic α) : Nontrivial α := by
contrapose! nc
exact @isCyclic_of_subsingleton _ _ (not_nontrivial_iff_subsingleton.mp nc)
@[to_additive]
theorem MonoidHom.map_cyclic {G : Type*} [Group G] [h : IsCyclic G] (σ : G →* G) :
∃ m : ℤ, ∀ g : G, σ g = g ^ m := by
obtain ⟨h, hG⟩ := IsCyclic.exists_generator (α := G)
obtain ⟨m, hm⟩ := hG (σ h)
refine ⟨m, fun g => ?_⟩
obtain ⟨n, rfl⟩ := hG g
rw [MonoidHom.map_zpow, ← hm, ← zpow_mul, ← zpow_mul']
#align monoid_hom.map_cyclic MonoidHom.map_cyclic
#align monoid_add_hom.map_add_cyclic AddMonoidHom.map_addCyclic
@[deprecated (since := "2024-02-21")] alias
MonoidAddHom.map_add_cyclic := AddMonoidHom.map_addCyclic
@[to_additive]
theorem isCyclic_of_orderOf_eq_card [Fintype α] (x : α) (hx : orderOf x = Fintype.card α) :
IsCyclic α := by
classical
use x
simp_rw [← SetLike.mem_coe, ← Set.eq_univ_iff_forall]
rw [← Fintype.card_congr (Equiv.Set.univ α), ← Fintype.card_zpowers] at hx
exact Set.eq_of_subset_of_card_le (Set.subset_univ _) (ge_of_eq hx)
#align is_cyclic_of_order_of_eq_card isCyclic_of_orderOf_eq_card
#align is_add_cyclic_of_order_of_eq_card isAddCyclic_of_addOrderOf_eq_card
@[deprecated (since := "2024-02-21")]
alias isAddCyclic_of_orderOf_eq_card := isAddCyclic_of_addOrderOf_eq_card
@[to_additive]
theorem Subgroup.eq_bot_or_eq_top_of_prime_card {G : Type*} [Group G] {_ : Fintype G}
(H : Subgroup G) [hp : Fact (Fintype.card G).Prime] : H = ⊥ ∨ H = ⊤ := by
classical
have := card_subgroup_dvd_card H
rwa [Nat.card_eq_fintype_card (α := G), Nat.dvd_prime hp.1, ← Nat.card_eq_fintype_card,
← eq_bot_iff_card, card_eq_iff_eq_top] at this
/-- Any non-identity element of a finite group of prime order generates the group. -/
@[to_additive "Any non-identity element of a finite group of prime order generates the group."]
theorem zpowers_eq_top_of_prime_card {G : Type*} [Group G] {_ : Fintype G} {p : ℕ}
[hp : Fact p.Prime] (h : Fintype.card G = p) {g : G} (hg : g ≠ 1) : zpowers g = ⊤ := by
subst h
have := (zpowers g).eq_bot_or_eq_top_of_prime_card
rwa [zpowers_eq_bot, or_iff_right hg] at this
@[to_additive]
theorem mem_zpowers_of_prime_card {G : Type*} [Group G] {_ : Fintype G} {p : ℕ} [hp : Fact p.Prime]
(h : Fintype.card G = p) {g g' : G} (hg : g ≠ 1) : g' ∈ zpowers g := by
simp_rw [zpowers_eq_top_of_prime_card h hg, Subgroup.mem_top]
@[to_additive]
theorem mem_powers_of_prime_card {G : Type*} [Group G] {_ : Fintype G} {p : ℕ} [hp : Fact p.Prime]
(h : Fintype.card G = p) {g g' : G} (hg : g ≠ 1) : g' ∈ Submonoid.powers g := by
rw [mem_powers_iff_mem_zpowers]
exact mem_zpowers_of_prime_card h hg
@[to_additive]
theorem powers_eq_top_of_prime_card {G : Type*} [Group G] {_ : Fintype G} {p : ℕ}
[hp : Fact p.Prime] (h : Fintype.card G = p) {g : G} (hg : g ≠ 1) : Submonoid.powers g = ⊤ := by
ext x
simp [mem_powers_of_prime_card h hg]
/-- A finite group of prime order is cyclic. -/
@[to_additive "A finite group of prime order is cyclic."]
theorem isCyclic_of_prime_card {α : Type u} [Group α] [Fintype α] {p : ℕ} [hp : Fact p.Prime]
(h : Fintype.card α = p) : IsCyclic α := by
obtain ⟨g, hg⟩ : ∃ g, g ≠ 1 := Fintype.exists_ne_of_one_lt_card (h.symm ▸ hp.1.one_lt) 1
exact ⟨g, fun g' ↦ mem_zpowers_of_prime_card h hg⟩
#align is_cyclic_of_prime_card isCyclic_of_prime_card
#align is_add_cyclic_of_prime_card isAddCyclic_of_prime_card
@[to_additive]
theorem isCyclic_of_surjective {H G F : Type*} [Group H] [Group G] [hH : IsCyclic H]
[FunLike F H G] [MonoidHomClass F H G] (f : F) (hf : Function.Surjective f) :
IsCyclic G := by
obtain ⟨x, hx⟩ := hH
refine ⟨f x, fun a ↦ ?_⟩
obtain ⟨a, rfl⟩ := hf a
obtain ⟨n, rfl⟩ := hx a
exact ⟨n, (map_zpow _ _ _).symm⟩
@[to_additive]
theorem orderOf_eq_card_of_forall_mem_zpowers [Fintype α] {g : α} (hx : ∀ x, x ∈ zpowers g) :
orderOf g = Fintype.card α := by
classical
rw [← Fintype.card_zpowers]
apply Fintype.card_of_finset'
simpa using hx
#align order_of_eq_card_of_forall_mem_zpowers orderOf_eq_card_of_forall_mem_zpowers
#align add_order_of_eq_card_of_forall_mem_zmultiples addOrderOf_eq_card_of_forall_mem_zmultiples
@[to_additive]
lemma orderOf_generator_eq_natCard (h : ∀ x, x ∈ Subgroup.zpowers a) : orderOf a = Nat.card α :=
Nat.card_zpowers a ▸ (Nat.card_congr <| Equiv.subtypeUnivEquiv h)
@[to_additive]
| Mathlib/GroupTheory/SpecificGroups/Cyclic.lean | 202 | 209 | theorem exists_pow_ne_one_of_isCyclic {G : Type*} [Group G] [Fintype G] [G_cyclic : IsCyclic G]
{k : ℕ} (k_pos : k ≠ 0) (k_lt_card_G : k < Fintype.card G) : ∃ a : G, a ^ k ≠ 1 := by |
rcases G_cyclic with ⟨a, ha⟩
use a
contrapose! k_lt_card_G
convert orderOf_le_of_pow_eq_one k_pos.bot_lt k_lt_card_G
rw [← Nat.card_eq_fintype_card, ← Nat.card_zpowers, eq_comm, card_eq_iff_eq_top, eq_top_iff]
exact fun x _ ↦ ha x
|
/-
Copyright (c) 2023 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll, Sébastien Gouëzel, Jireh Loreaux
-/
import Mathlib.Analysis.MeanInequalities
import Mathlib.Analysis.NormedSpace.WithLp
/-!
# `L^p` distance on products of two metric spaces
Given two metric spaces, one can put the max distance on their product, but there is also
a whole family of natural distances, indexed by a parameter `p : ℝ≥0∞`, that also induce
the product topology. We define them in this file. For `0 < p < ∞`, the distance on `α × β`
is given by
$$
d(x, y) = \left(d(x_1, y_1)^p + d(x_2, y_2)^p\right)^{1/p}.
$$
For `p = ∞` the distance is the supremum of the distances and `p = 0` the distance is the
cardinality of the elements that are not equal.
We give instances of this construction for emetric spaces, metric spaces, normed groups and normed
spaces.
To avoid conflicting instances, all these are defined on a copy of the original Prod-type, named
`WithLp p (α × β)`. The assumption `[Fact (1 ≤ p)]` is required for the metric and normed space
instances.
We ensure that the topology, bornology and uniform structure on `WithLp p (α × β)` are (defeq to)
the product topology, product bornology and product uniformity, to be able to use freely continuity
statements for the coordinate functions, for instance.
# Implementation notes
This files is a straight-forward adaption of `Mathlib.Analysis.NormedSpace.PiLp`.
-/
open Real Set Filter RCLike Bornology Uniformity Topology NNReal ENNReal
noncomputable section
variable (p : ℝ≥0∞) (𝕜 α β : Type*)
namespace WithLp
section algebra
/- Register simplification lemmas for the applications of `WithLp p (α × β)` elements, as the usual
lemmas for `Prod` will not trigger. -/
variable {p 𝕜 α β}
variable [Semiring 𝕜] [AddCommGroup α] [AddCommGroup β]
variable (x y : WithLp p (α × β)) (c : 𝕜)
@[simp]
theorem zero_fst : (0 : WithLp p (α × β)).fst = 0 :=
rfl
@[simp]
theorem zero_snd : (0 : WithLp p (α × β)).snd = 0 :=
rfl
@[simp]
theorem add_fst : (x + y).fst = x.fst + y.fst :=
rfl
@[simp]
theorem add_snd : (x + y).snd = x.snd + y.snd :=
rfl
@[simp]
theorem sub_fst : (x - y).fst = x.fst - y.fst :=
rfl
@[simp]
theorem sub_snd : (x - y).snd = x.snd - y.snd :=
rfl
@[simp]
theorem neg_fst : (-x).fst = -x.fst :=
rfl
@[simp]
theorem neg_snd : (-x).snd = -x.snd :=
rfl
variable [Module 𝕜 α] [Module 𝕜 β]
@[simp]
theorem smul_fst : (c • x).fst = c • x.fst :=
rfl
@[simp]
theorem smul_snd : (c • x).snd = c • x.snd :=
rfl
end algebra
/-! Note that the unapplied versions of these lemmas are deliberately omitted, as they break
the use of the type synonym. -/
section equiv
variable {p α β}
@[simp]
theorem equiv_fst (x : WithLp p (α × β)) : (WithLp.equiv p (α × β) x).fst = x.fst :=
rfl
@[simp]
theorem equiv_snd (x : WithLp p (α × β)) : (WithLp.equiv p (α × β) x).snd = x.snd :=
rfl
@[simp]
theorem equiv_symm_fst (x : α × β) : ((WithLp.equiv p (α × β)).symm x).fst = x.fst :=
rfl
@[simp]
theorem equiv_symm_snd (x : α × β) : ((WithLp.equiv p (α × β)).symm x).snd = x.snd :=
rfl
end equiv
section DistNorm
/-!
### Definition of `edist`, `dist` and `norm` on `WithLp p (α × β)`
In this section we define the `edist`, `dist` and `norm` functions on `WithLp p (α × β)` without
assuming `[Fact (1 ≤ p)]` or metric properties of the spaces `α` and `β`. This allows us to provide
the rewrite lemmas for each of three cases `p = 0`, `p = ∞` and `0 < p.toReal`.
-/
section EDist
variable [EDist α] [EDist β]
open scoped Classical in
/-- Endowing the space `WithLp p (α × β)` with the `L^p` edistance. We register this instance
separate from `WithLp.instProdPseudoEMetric` since the latter requires the type class hypothesis
`[Fact (1 ≤ p)]` in order to prove the triangle inequality.
Registering this separately allows for a future emetric-like structure on `WithLp p (α × β)` for
`p < 1` satisfying a relaxed triangle inequality. The terminology for this varies throughout the
literature, but it is sometimes called a *quasi-metric* or *semi-metric*. -/
instance instProdEDist : EDist (WithLp p (α × β)) where
edist f g :=
if _hp : p = 0 then
(if edist f.fst g.fst = 0 then 0 else 1) + (if edist f.snd g.snd = 0 then 0 else 1)
else if p = ∞ then
edist f.fst g.fst ⊔ edist f.snd g.snd
else
(edist f.fst g.fst ^ p.toReal + edist f.snd g.snd ^ p.toReal) ^ (1 / p.toReal)
variable {p α β}
variable (x y : WithLp p (α × β)) (x' : α × β)
@[simp]
theorem prod_edist_eq_card (f g : WithLp 0 (α × β)) :
edist f g =
(if edist f.fst g.fst = 0 then 0 else 1) + (if edist f.snd g.snd = 0 then 0 else 1) := by
convert if_pos rfl
theorem prod_edist_eq_add (hp : 0 < p.toReal) (f g : WithLp p (α × β)) :
edist f g = (edist f.fst g.fst ^ p.toReal + edist f.snd g.snd ^ p.toReal) ^ (1 / p.toReal) :=
let hp' := ENNReal.toReal_pos_iff.mp hp
(if_neg hp'.1.ne').trans (if_neg hp'.2.ne)
theorem prod_edist_eq_sup (f g : WithLp ∞ (α × β)) :
edist f g = edist f.fst g.fst ⊔ edist f.snd g.snd := by
dsimp [edist]
exact if_neg ENNReal.top_ne_zero
end EDist
section EDistProp
variable {α β}
variable [PseudoEMetricSpace α] [PseudoEMetricSpace β]
/-- The distance from one point to itself is always zero.
This holds independent of `p` and does not require `[Fact (1 ≤ p)]`. We keep it separate
from `WithLp.instProdPseudoEMetricSpace` so it can be used also for `p < 1`. -/
theorem prod_edist_self (f : WithLp p (α × β)) : edist f f = 0 := by
rcases p.trichotomy with (rfl | rfl | h)
· classical
simp
· simp [prod_edist_eq_sup]
· simp [prod_edist_eq_add h, ENNReal.zero_rpow_of_pos h,
ENNReal.zero_rpow_of_pos (inv_pos.2 <| h)]
/-- The distance is symmetric.
This holds independent of `p` and does not require `[Fact (1 ≤ p)]`. We keep it separate
from `WithLp.instProdPseudoEMetricSpace` so it can be used also for `p < 1`. -/
theorem prod_edist_comm (f g : WithLp p (α × β)) : edist f g = edist g f := by
classical
rcases p.trichotomy with (rfl | rfl | h)
· simp only [prod_edist_eq_card, edist_comm]
· simp only [prod_edist_eq_sup, edist_comm]
· simp only [prod_edist_eq_add h, edist_comm]
end EDistProp
section Dist
variable [Dist α] [Dist β]
open scoped Classical in
/-- Endowing the space `WithLp p (α × β)` with the `L^p` distance. We register this instance
separate from `WithLp.instProdPseudoMetricSpace` since the latter requires the type class hypothesis
`[Fact (1 ≤ p)]` in order to prove the triangle inequality.
Registering this separately allows for a future metric-like structure on `WithLp p (α × β)` for
`p < 1` satisfying a relaxed triangle inequality. The terminology for this varies throughout the
literature, but it is sometimes called a *quasi-metric* or *semi-metric*. -/
instance instProdDist : Dist (WithLp p (α × β)) where
dist f g :=
if _hp : p = 0 then
(if dist f.fst g.fst = 0 then 0 else 1) + (if dist f.snd g.snd = 0 then 0 else 1)
else if p = ∞ then
dist f.fst g.fst ⊔ dist f.snd g.snd
else
(dist f.fst g.fst ^ p.toReal + dist f.snd g.snd ^ p.toReal) ^ (1 / p.toReal)
variable {p α β}
theorem prod_dist_eq_card (f g : WithLp 0 (α × β)) : dist f g =
(if dist f.fst g.fst = 0 then 0 else 1) + (if dist f.snd g.snd = 0 then 0 else 1) := by
convert if_pos rfl
theorem prod_dist_eq_add (hp : 0 < p.toReal) (f g : WithLp p (α × β)) :
dist f g = (dist f.fst g.fst ^ p.toReal + dist f.snd g.snd ^ p.toReal) ^ (1 / p.toReal) :=
let hp' := ENNReal.toReal_pos_iff.mp hp
(if_neg hp'.1.ne').trans (if_neg hp'.2.ne)
theorem prod_dist_eq_sup (f g : WithLp ∞ (α × β)) :
dist f g = dist f.fst g.fst ⊔ dist f.snd g.snd := by
dsimp [dist]
exact if_neg ENNReal.top_ne_zero
end Dist
section Norm
variable [Norm α] [Norm β]
open scoped Classical in
/-- Endowing the space `WithLp p (α × β)` with the `L^p` norm. We register this instance
separate from `WithLp.instProdSeminormedAddCommGroup` since the latter requires the type class
hypothesis `[Fact (1 ≤ p)]` in order to prove the triangle inequality.
Registering this separately allows for a future norm-like structure on `WithLp p (α × β)` for
`p < 1` satisfying a relaxed triangle inequality. These are called *quasi-norms*. -/
instance instProdNorm : Norm (WithLp p (α × β)) where
norm f :=
if _hp : p = 0 then
(if ‖f.fst‖ = 0 then 0 else 1) + (if ‖f.snd‖ = 0 then 0 else 1)
else if p = ∞ then
‖f.fst‖ ⊔ ‖f.snd‖
else
(‖f.fst‖ ^ p.toReal + ‖f.snd‖ ^ p.toReal) ^ (1 / p.toReal)
variable {p α β}
@[simp]
theorem prod_norm_eq_card (f : WithLp 0 (α × β)) :
‖f‖ = (if ‖f.fst‖ = 0 then 0 else 1) + (if ‖f.snd‖ = 0 then 0 else 1) := by
convert if_pos rfl
theorem prod_norm_eq_sup (f : WithLp ∞ (α × β)) : ‖f‖ = ‖f.fst‖ ⊔ ‖f.snd‖ := by
dsimp [Norm.norm]
exact if_neg ENNReal.top_ne_zero
theorem prod_norm_eq_add (hp : 0 < p.toReal) (f : WithLp p (α × β)) :
‖f‖ = (‖f.fst‖ ^ p.toReal + ‖f.snd‖ ^ p.toReal) ^ (1 / p.toReal) :=
let hp' := ENNReal.toReal_pos_iff.mp hp
(if_neg hp'.1.ne').trans (if_neg hp'.2.ne)
end Norm
end DistNorm
section Aux
/-!
### The uniformity on finite `L^p` products is the product uniformity
In this section, we put the `L^p` edistance on `WithLp p (α × β)`, and we check that the uniformity
coming from this edistance coincides with the product uniformity, by showing that the canonical
map to the Prod type (with the `L^∞` distance) is a uniform embedding, as it is both Lipschitz and
antiLipschitz.
We only register this emetric space structure as a temporary instance, as the true instance (to be
registered later) will have as uniformity exactly the product uniformity, instead of the one coming
from the edistance (which is equal to it, but not defeq). See Note [forgetful inheritance]
explaining why having definitionally the right uniformity is often important.
-/
variable [hp : Fact (1 ≤ p)]
/-- Endowing the space `WithLp p (α × β)` with the `L^p` pseudoemetric structure. This definition is
not satisfactory, as it does not register the fact that the topology and the uniform structure
coincide with the product one. Therefore, we do not register it as an instance. Using this as a
temporary pseudoemetric space instance, we will show that the uniform structure is equal (but not
defeq) to the product one, and then register an instance in which we replace the uniform structure
by the product one using this pseudoemetric space and `PseudoEMetricSpace.replaceUniformity`. -/
def prodPseudoEMetricAux [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
PseudoEMetricSpace (WithLp p (α × β)) where
edist_self := prod_edist_self p
edist_comm := prod_edist_comm p
edist_triangle f g h := by
rcases p.dichotomy with (rfl | hp)
· simp only [prod_edist_eq_sup]
exact sup_le ((edist_triangle _ g.fst _).trans <| add_le_add le_sup_left le_sup_left)
((edist_triangle _ g.snd _).trans <| add_le_add le_sup_right le_sup_right)
· simp only [prod_edist_eq_add (zero_lt_one.trans_le hp)]
calc
(edist f.fst h.fst ^ p.toReal + edist f.snd h.snd ^ p.toReal) ^ (1 / p.toReal) ≤
((edist f.fst g.fst + edist g.fst h.fst) ^ p.toReal +
(edist f.snd g.snd + edist g.snd h.snd) ^ p.toReal) ^ (1 / p.toReal) := by
gcongr <;> apply edist_triangle
_ ≤
(edist f.fst g.fst ^ p.toReal + edist f.snd g.snd ^ p.toReal) ^ (1 / p.toReal) +
(edist g.fst h.fst ^ p.toReal + edist g.snd h.snd ^ p.toReal) ^ (1 / p.toReal) := by
have := ENNReal.Lp_add_le {0, 1}
(if · = 0 then edist f.fst g.fst else edist f.snd g.snd)
(if · = 0 then edist g.fst h.fst else edist g.snd h.snd) hp
simp only [Finset.mem_singleton, not_false_eq_true, Finset.sum_insert,
Finset.sum_singleton] at this
exact this
attribute [local instance] WithLp.prodPseudoEMetricAux
variable {α β}
/-- An auxiliary lemma used twice in the proof of `WithLp.prodPseudoMetricAux` below. Not intended
for use outside this file. -/
theorem prod_sup_edist_ne_top_aux [PseudoMetricSpace α] [PseudoMetricSpace β]
(f g : WithLp ∞ (α × β)) :
edist f.fst g.fst ⊔ edist f.snd g.snd ≠ ⊤ :=
ne_of_lt <| by simp [edist, PseudoMetricSpace.edist_dist]
variable (α β)
/-- Endowing the space `WithLp p (α × β)` with the `L^p` pseudometric structure. This definition is
not satisfactory, as it does not register the fact that the topology, the uniform structure, and the
bornology coincide with the product ones. Therefore, we do not register it as an instance. Using
this as a temporary pseudoemetric space instance, we will show that the uniform structure is equal
(but not defeq) to the product one, and then register an instance in which we replace the uniform
structure and the bornology by the product ones using this pseudometric space,
`PseudoMetricSpace.replaceUniformity`, and `PseudoMetricSpace.replaceBornology`.
See note [reducible non-instances] -/
abbrev prodPseudoMetricAux [PseudoMetricSpace α] [PseudoMetricSpace β] :
PseudoMetricSpace (WithLp p (α × β)) :=
PseudoEMetricSpace.toPseudoMetricSpaceOfDist dist
(fun f g => by
rcases p.dichotomy with (rfl | h)
· exact prod_sup_edist_ne_top_aux f g
· rw [prod_edist_eq_add (zero_lt_one.trans_le h)]
refine ENNReal.rpow_ne_top_of_nonneg (by positivity) (ne_of_lt ?_)
simp [ENNReal.add_lt_top, ENNReal.rpow_lt_top_of_nonneg, edist_ne_top] )
fun f g => by
rcases p.dichotomy with (rfl | h)
· rw [prod_edist_eq_sup, prod_dist_eq_sup]
refine le_antisymm (sup_le ?_ ?_) ?_
· rw [← ENNReal.ofReal_le_iff_le_toReal (prod_sup_edist_ne_top_aux f g),
← PseudoMetricSpace.edist_dist]
exact le_sup_left
· rw [← ENNReal.ofReal_le_iff_le_toReal (prod_sup_edist_ne_top_aux f g),
← PseudoMetricSpace.edist_dist]
exact le_sup_right
· refine ENNReal.toReal_le_of_le_ofReal ?_ ?_
· simp only [ge_iff_le, le_sup_iff, dist_nonneg, or_self]
· simp [edist, PseudoMetricSpace.edist_dist, ENNReal.ofReal_le_ofReal]
· have h1 : edist f.fst g.fst ^ p.toReal ≠ ⊤ :=
ENNReal.rpow_ne_top_of_nonneg (zero_le_one.trans h) (edist_ne_top _ _)
have h2 : edist f.snd g.snd ^ p.toReal ≠ ⊤ :=
ENNReal.rpow_ne_top_of_nonneg (zero_le_one.trans h) (edist_ne_top _ _)
simp only [prod_edist_eq_add (zero_lt_one.trans_le h), dist_edist, ENNReal.toReal_rpow,
prod_dist_eq_add (zero_lt_one.trans_le h), ← ENNReal.toReal_add h1 h2]
attribute [local instance] WithLp.prodPseudoMetricAux
theorem prod_lipschitzWith_equiv_aux [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
LipschitzWith 1 (WithLp.equiv p (α × β)) := by
intro x y
rcases p.dichotomy with (rfl | h)
· simp [edist]
· have cancel : p.toReal * (1 / p.toReal) = 1 := mul_div_cancel₀ 1 (zero_lt_one.trans_le h).ne'
rw [prod_edist_eq_add (zero_lt_one.trans_le h)]
simp only [edist, forall_prop_of_true, one_mul, ENNReal.coe_one, ge_iff_le, sup_le_iff]
constructor
· calc
edist x.fst y.fst ≤ (edist x.fst y.fst ^ p.toReal) ^ (1 / p.toReal) := by
simp only [← ENNReal.rpow_mul, cancel, ENNReal.rpow_one, le_refl]
_ ≤ (edist x.fst y.fst ^ p.toReal + edist x.snd y.snd ^ p.toReal) ^ (1 / p.toReal) := by
gcongr
simp only [self_le_add_right]
· calc
edist x.snd y.snd ≤ (edist x.snd y.snd ^ p.toReal) ^ (1 / p.toReal) := by
simp only [← ENNReal.rpow_mul, cancel, ENNReal.rpow_one, le_refl]
_ ≤ (edist x.fst y.fst ^ p.toReal + edist x.snd y.snd ^ p.toReal) ^ (1 / p.toReal) := by
gcongr
simp only [self_le_add_left]
theorem prod_antilipschitzWith_equiv_aux [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
AntilipschitzWith ((2 : ℝ≥0) ^ (1 / p).toReal) (WithLp.equiv p (α × β)) := by
intro x y
rcases p.dichotomy with (rfl | h)
· simp [edist]
· have pos : 0 < p.toReal := by positivity
have nonneg : 0 ≤ 1 / p.toReal := by positivity
have cancel : p.toReal * (1 / p.toReal) = 1 := mul_div_cancel₀ 1 (ne_of_gt pos)
rw [prod_edist_eq_add pos, ENNReal.toReal_div 1 p]
simp only [edist, ← one_div, ENNReal.one_toReal]
calc
(edist x.fst y.fst ^ p.toReal + edist x.snd y.snd ^ p.toReal) ^ (1 / p.toReal) ≤
(edist (WithLp.equiv p _ x) (WithLp.equiv p _ y) ^ p.toReal +
edist (WithLp.equiv p _ x) (WithLp.equiv p _ y) ^ p.toReal) ^ (1 / p.toReal) := by
gcongr <;> simp [edist]
_ = (2 ^ (1 / p.toReal) : ℝ≥0) * edist (WithLp.equiv p _ x) (WithLp.equiv p _ y) := by
simp only [← two_mul, ENNReal.mul_rpow_of_nonneg _ _ nonneg, ← ENNReal.rpow_mul, cancel,
ENNReal.rpow_one, ← ENNReal.coe_rpow_of_nonneg _ nonneg, coe_ofNat]
theorem prod_aux_uniformity_eq [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
𝓤 (WithLp p (α × β)) = 𝓤[instUniformSpaceProd] := by
have A : UniformInducing (WithLp.equiv p (α × β)) :=
(prod_antilipschitzWith_equiv_aux p α β).uniformInducing
(prod_lipschitzWith_equiv_aux p α β).uniformContinuous
have : (fun x : WithLp p (α × β) × WithLp p (α × β) =>
((WithLp.equiv p (α × β)) x.fst, (WithLp.equiv p (α × β)) x.snd)) = id := by
ext i <;> rfl
rw [← A.comap_uniformity, this, comap_id]
theorem prod_aux_cobounded_eq [PseudoMetricSpace α] [PseudoMetricSpace β] :
cobounded (WithLp p (α × β)) = @cobounded _ Prod.instBornology :=
calc
cobounded (WithLp p (α × β)) = comap (WithLp.equiv p (α × β)) (cobounded _) :=
le_antisymm (prod_antilipschitzWith_equiv_aux p α β).tendsto_cobounded.le_comap
(prod_lipschitzWith_equiv_aux p α β).comap_cobounded_le
_ = _ := comap_id
end Aux
/-! ### Instances on `L^p` products -/
section TopologicalSpace
variable [TopologicalSpace α] [TopologicalSpace β]
instance instProdTopologicalSpace : TopologicalSpace (WithLp p (α × β)) :=
instTopologicalSpaceProd
@[continuity]
theorem prod_continuous_equiv : Continuous (WithLp.equiv p (α × β)) :=
continuous_id
@[continuity]
theorem prod_continuous_equiv_symm : Continuous (WithLp.equiv p (α × β)).symm :=
continuous_id
variable [T0Space α] [T0Space β]
instance instProdT0Space : T0Space (WithLp p (α × β)) :=
Prod.instT0Space
end TopologicalSpace
section UniformSpace
variable [UniformSpace α] [UniformSpace β]
instance instProdUniformSpace : UniformSpace (WithLp p (α × β)) :=
instUniformSpaceProd
theorem prod_uniformContinuous_equiv : UniformContinuous (WithLp.equiv p (α × β)) :=
uniformContinuous_id
theorem prod_uniformContinuous_equiv_symm : UniformContinuous (WithLp.equiv p (α × β)).symm :=
uniformContinuous_id
variable [CompleteSpace α] [CompleteSpace β]
instance instProdCompleteSpace : CompleteSpace (WithLp p (α × β)) :=
CompleteSpace.prod
end UniformSpace
instance instProdBornology [Bornology α] [Bornology β] : Bornology (WithLp p (α × β)) :=
Prod.instBornology
section ContinuousLinearEquiv
variable [TopologicalSpace α] [TopologicalSpace β]
variable [Semiring 𝕜] [AddCommGroup α] [AddCommGroup β]
variable [Module 𝕜 α] [Module 𝕜 β]
/-- `WithLp.equiv` as a continuous linear equivalence. -/
@[simps! (config := .asFn) apply symm_apply]
protected def prodContinuousLinearEquiv : WithLp p (α × β) ≃L[𝕜] α × β where
toLinearEquiv := WithLp.linearEquiv _ _ _
continuous_toFun := prod_continuous_equiv _ _ _
continuous_invFun := prod_continuous_equiv_symm _ _ _
end ContinuousLinearEquiv
/-! Throughout the rest of the file, we assume `1 ≤ p` -/
variable [hp : Fact (1 ≤ p)]
/-- `PseudoEMetricSpace` instance on the product of two pseudoemetric spaces, using the
`L^p` pseudoedistance, and having as uniformity the product uniformity. -/
instance instProdPseudoEMetricSpace [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
PseudoEMetricSpace (WithLp p (α × β)) :=
(prodPseudoEMetricAux p α β).replaceUniformity (prod_aux_uniformity_eq p α β).symm
/-- `EMetricSpace` instance on the product of two emetric spaces, using the `L^p`
edistance, and having as uniformity the product uniformity. -/
instance instProdEMetricSpace [EMetricSpace α] [EMetricSpace β] : EMetricSpace (WithLp p (α × β)) :=
EMetricSpace.ofT0PseudoEMetricSpace (WithLp p (α × β))
/-- `PseudoMetricSpace` instance on the product of two pseudometric spaces, using the
`L^p` distance, and having as uniformity the product uniformity. -/
instance instProdPseudoMetricSpace [PseudoMetricSpace α] [PseudoMetricSpace β] :
PseudoMetricSpace (WithLp p (α × β)) :=
((prodPseudoMetricAux p α β).replaceUniformity
(prod_aux_uniformity_eq p α β).symm).replaceBornology
fun s => Filter.ext_iff.1 (prod_aux_cobounded_eq p α β).symm sᶜ
/-- `MetricSpace` instance on the product of two metric spaces, using the `L^p` distance,
and having as uniformity the product uniformity. -/
instance instProdMetricSpace [MetricSpace α] [MetricSpace β] : MetricSpace (WithLp p (α × β)) :=
MetricSpace.ofT0PseudoMetricSpace _
variable {p α β}
theorem prod_nndist_eq_add [PseudoMetricSpace α] [PseudoMetricSpace β]
(hp : p ≠ ∞) (x y : WithLp p (α × β)) :
nndist x y = (nndist x.fst y.fst ^ p.toReal + nndist x.snd y.snd ^ p.toReal) ^ (1 / p.toReal) :=
NNReal.eq <| by
push_cast
exact prod_dist_eq_add (p.toReal_pos_iff_ne_top.mpr hp) _ _
theorem prod_nndist_eq_sup [PseudoMetricSpace α] [PseudoMetricSpace β] (x y : WithLp ∞ (α × β)) :
nndist x y = nndist x.fst y.fst ⊔ nndist x.snd y.snd :=
NNReal.eq <| by
push_cast
exact prod_dist_eq_sup _ _
variable (p α β)
theorem prod_lipschitzWith_equiv [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
LipschitzWith 1 (WithLp.equiv p (α × β)) :=
prod_lipschitzWith_equiv_aux p α β
theorem prod_antilipschitzWith_equiv [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
AntilipschitzWith ((2 : ℝ≥0) ^ (1 / p).toReal) (WithLp.equiv p (α × β)) :=
prod_antilipschitzWith_equiv_aux p α β
theorem prod_infty_equiv_isometry [PseudoEMetricSpace α] [PseudoEMetricSpace β] :
Isometry (WithLp.equiv ∞ (α × β)) :=
fun x y =>
le_antisymm (by simpa only [ENNReal.coe_one, one_mul] using prod_lipschitzWith_equiv ∞ α β x y)
(by
simpa only [ENNReal.div_top, ENNReal.zero_toReal, NNReal.rpow_zero, ENNReal.coe_one,
one_mul] using prod_antilipschitzWith_equiv ∞ α β x y)
/-- Seminormed group instance on the product of two normed groups, using the `L^p`
norm. -/
instance instProdSeminormedAddCommGroup [SeminormedAddCommGroup α] [SeminormedAddCommGroup β] :
SeminormedAddCommGroup (WithLp p (α × β)) where
dist_eq x y := by
rcases p.dichotomy with (rfl | h)
· simp only [prod_dist_eq_sup, prod_norm_eq_sup, dist_eq_norm]
rfl
· simp only [prod_dist_eq_add (zero_lt_one.trans_le h),
prod_norm_eq_add (zero_lt_one.trans_le h), dist_eq_norm]
rfl
/-- normed group instance on the product of two normed groups, using the `L^p` norm. -/
instance instProdNormedAddCommGroup [NormedAddCommGroup α] [NormedAddCommGroup β] :
NormedAddCommGroup (WithLp p (α × β)) :=
{ instProdSeminormedAddCommGroup p α β with
eq_of_dist_eq_zero := eq_of_dist_eq_zero }
example [NormedAddCommGroup α] [NormedAddCommGroup β] :
(instProdNormedAddCommGroup p α β).toMetricSpace.toUniformSpace.toTopologicalSpace =
instProdTopologicalSpace p α β :=
rfl
example [NormedAddCommGroup α] [NormedAddCommGroup β] :
(instProdNormedAddCommGroup p α β).toMetricSpace.toUniformSpace = instProdUniformSpace p α β :=
rfl
example [NormedAddCommGroup α] [NormedAddCommGroup β] :
(instProdNormedAddCommGroup p α β).toMetricSpace.toBornology = instProdBornology p α β :=
rfl
section norm_of
variable {p α β}
theorem prod_norm_eq_of_nat [Norm α] [Norm β] (n : ℕ) (h : p = n) (f : WithLp p (α × β)) :
‖f‖ = (‖f.fst‖ ^ n + ‖f.snd‖ ^ n) ^ (1 / (n : ℝ)) := by
have := p.toReal_pos_iff_ne_top.mpr (ne_of_eq_of_ne h <| ENNReal.natCast_ne_top n)
simp only [one_div, h, Real.rpow_natCast, ENNReal.toReal_nat, eq_self_iff_true, Finset.sum_congr,
prod_norm_eq_add this]
variable [SeminormedAddCommGroup α] [SeminormedAddCommGroup β]
theorem prod_nnnorm_eq_add (hp : p ≠ ∞) (f : WithLp p (α × β)) :
‖f‖₊ = (‖f.fst‖₊ ^ p.toReal + ‖f.snd‖₊ ^ p.toReal) ^ (1 / p.toReal) := by
ext
simp [prod_norm_eq_add (p.toReal_pos_iff_ne_top.mpr hp)]
theorem prod_nnnorm_eq_sup (f : WithLp ∞ (α × β)) : ‖f‖₊ = ‖f.fst‖₊ ⊔ ‖f.snd‖₊ := by
ext
norm_cast
@[simp] theorem prod_nnnorm_equiv (f : WithLp ∞ (α × β)) : ‖WithLp.equiv ⊤ _ f‖₊ = ‖f‖₊ := by
rw [prod_nnnorm_eq_sup, Prod.nnnorm_def', _root_.sup_eq_max, equiv_fst, equiv_snd]
@[simp] theorem prod_nnnorm_equiv_symm (f : α × β) : ‖(WithLp.equiv ⊤ _).symm f‖₊ = ‖f‖₊ :=
(prod_nnnorm_equiv _).symm
@[simp] theorem prod_norm_equiv (f : WithLp ∞ (α × β)) : ‖WithLp.equiv ⊤ _ f‖ = ‖f‖ :=
congr_arg NNReal.toReal <| prod_nnnorm_equiv f
@[simp] theorem prod_norm_equiv_symm (f : α × β) : ‖(WithLp.equiv ⊤ _).symm f‖ = ‖f‖ :=
(prod_norm_equiv _).symm
theorem prod_norm_eq_of_L2 (x : WithLp 2 (α × β)) :
‖x‖ = √(‖x.fst‖ ^ 2 + ‖x.snd‖ ^ 2) := by
rw [prod_norm_eq_of_nat 2 (by norm_cast) _, Real.sqrt_eq_rpow]
norm_cast
theorem prod_nnnorm_eq_of_L2 (x : WithLp 2 (α × β)) :
‖x‖₊ = NNReal.sqrt (‖x.fst‖₊ ^ 2 + ‖x.snd‖₊ ^ 2) :=
NNReal.eq <| by
push_cast
exact prod_norm_eq_of_L2 x
theorem prod_norm_sq_eq_of_L2 (x : WithLp 2 (α × β)) : ‖x‖ ^ 2 = ‖x.fst‖ ^ 2 + ‖x.snd‖ ^ 2 := by
suffices ‖x‖₊ ^ 2 = ‖x.fst‖₊ ^ 2 + ‖x.snd‖₊ ^ 2 by
simpa only [NNReal.coe_sum] using congr_arg ((↑) : ℝ≥0 → ℝ) this
rw [prod_nnnorm_eq_of_L2, NNReal.sq_sqrt]
theorem prod_dist_eq_of_L2 (x y : WithLp 2 (α × β)) :
dist x y = √(dist x.fst y.fst ^ 2 + dist x.snd y.snd ^ 2) := by
simp_rw [dist_eq_norm, prod_norm_eq_of_L2]
rfl
theorem prod_nndist_eq_of_L2 (x y : WithLp 2 (α × β)) :
nndist x y = NNReal.sqrt (nndist x.fst y.fst ^ 2 + nndist x.snd y.snd ^ 2) :=
NNReal.eq <| by
push_cast
exact prod_dist_eq_of_L2 _ _
theorem prod_edist_eq_of_L2 (x y : WithLp 2 (α × β)) :
edist x y = (edist x.fst y.fst ^ 2 + edist x.snd y.snd ^ 2) ^ (1 / 2 : ℝ) := by
simp [prod_edist_eq_add]
end norm_of
variable [SeminormedAddCommGroup α] [SeminormedAddCommGroup β]
section Single
@[simp]
theorem nnnorm_equiv_symm_fst (x : α) :
‖(WithLp.equiv p (α × β)).symm (x, 0)‖₊ = ‖x‖₊ := by
induction p generalizing hp with
| top =>
simp [prod_nnnorm_eq_sup]
| coe p =>
have hp0 : (p : ℝ) ≠ 0 := mod_cast (zero_lt_one.trans_le <| Fact.out (p := 1 ≤ (p : ℝ≥0∞))).ne'
simp [prod_nnnorm_eq_add, NNReal.zero_rpow hp0, ← NNReal.rpow_mul, mul_inv_cancel hp0]
@[simp]
theorem nnnorm_equiv_symm_snd (y : β) :
‖(WithLp.equiv p (α × β)).symm (0, y)‖₊ = ‖y‖₊ := by
induction p generalizing hp with
| top =>
simp [prod_nnnorm_eq_sup]
| coe p =>
have hp0 : (p : ℝ) ≠ 0 := mod_cast (zero_lt_one.trans_le <| Fact.out (p := 1 ≤ (p : ℝ≥0∞))).ne'
simp [prod_nnnorm_eq_add, NNReal.zero_rpow hp0, ← NNReal.rpow_mul, mul_inv_cancel hp0]
@[simp]
theorem norm_equiv_symm_fst (x : α) : ‖(WithLp.equiv p (α × β)).symm (x, 0)‖ = ‖x‖ :=
congr_arg ((↑) : ℝ≥0 → ℝ) <| nnnorm_equiv_symm_fst p α β x
@[simp]
theorem norm_equiv_symm_snd (y : β) : ‖(WithLp.equiv p (α × β)).symm (0, y)‖ = ‖y‖ :=
congr_arg ((↑) : ℝ≥0 → ℝ) <| nnnorm_equiv_symm_snd p α β y
@[simp]
theorem nndist_equiv_symm_fst (x₁ x₂ : α) :
nndist ((WithLp.equiv p (α × β)).symm (x₁, 0)) ((WithLp.equiv p (α × β)).symm (x₂, 0)) =
nndist x₁ x₂ := by
rw [nndist_eq_nnnorm, nndist_eq_nnnorm, ← WithLp.equiv_symm_sub, Prod.mk_sub_mk, sub_zero,
nnnorm_equiv_symm_fst]
@[simp]
theorem nndist_equiv_symm_snd (y₁ y₂ : β) :
nndist ((WithLp.equiv p (α × β)).symm (0, y₁)) ((WithLp.equiv p (α × β)).symm (0, y₂)) =
nndist y₁ y₂ := by
rw [nndist_eq_nnnorm, nndist_eq_nnnorm, ← WithLp.equiv_symm_sub, Prod.mk_sub_mk, sub_zero,
nnnorm_equiv_symm_snd]
@[simp]
theorem dist_equiv_symm_fst (x₁ x₂ : α) :
dist ((WithLp.equiv p (α × β)).symm (x₁, 0)) ((WithLp.equiv p (α × β)).symm (x₂, 0)) =
dist x₁ x₂ :=
congr_arg ((↑) : ℝ≥0 → ℝ) <| nndist_equiv_symm_fst p α β x₁ x₂
@[simp]
theorem dist_equiv_symm_snd (y₁ y₂ : β) :
dist ((WithLp.equiv p (α × β)).symm (0, y₁)) ((WithLp.equiv p (α × β)).symm (0, y₂)) =
dist y₁ y₂ :=
congr_arg ((↑) : ℝ≥0 → ℝ) <| nndist_equiv_symm_snd p α β y₁ y₂
@[simp]
theorem edist_equiv_symm_fst (x₁ x₂ : α) :
edist ((WithLp.equiv p (α × β)).symm (x₁, 0)) ((WithLp.equiv p (α × β)).symm (x₂, 0)) =
edist x₁ x₂ := by
simp only [edist_nndist, nndist_equiv_symm_fst p α β x₁ x₂]
@[simp]
| Mathlib/Analysis/NormedSpace/ProdLp.lean | 735 | 738 | theorem edist_equiv_symm_snd (y₁ y₂ : β) :
edist ((WithLp.equiv p (α × β)).symm (0, y₁)) ((WithLp.equiv p (α × β)).symm (0, y₂)) =
edist y₁ y₂ := by |
simp only [edist_nndist, nndist_equiv_symm_snd p α β y₁ y₂]
|
/-
Copyright (c) 2021 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Scott Morrison
-/
import Mathlib.Algebra.Field.Subfield
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Topology.Algebra.GroupWithZero
import Mathlib.Topology.Algebra.Ring.Basic
import Mathlib.Topology.Order.LocalExtr
#align_import topology.algebra.field from "leanprover-community/mathlib"@"c10e724be91096453ee3db13862b9fb9a992fef2"
/-!
# Topological fields
A topological division ring is a topological ring whose inversion function is continuous at every
non-zero element.
-/
variable {K : Type*} [DivisionRing K] [TopologicalSpace K]
/-- Left-multiplication by a nonzero element of a topological division ring is proper, i.e.,
inverse images of compact sets are compact. -/
theorem Filter.tendsto_cocompact_mul_left₀ [ContinuousMul K] {a : K} (ha : a ≠ 0) :
Filter.Tendsto (fun x : K => a * x) (Filter.cocompact K) (Filter.cocompact K) :=
Filter.tendsto_cocompact_mul_left (inv_mul_cancel ha)
#align filter.tendsto_cocompact_mul_left₀ Filter.tendsto_cocompact_mul_left₀
/-- Right-multiplication by a nonzero element of a topological division ring is proper, i.e.,
inverse images of compact sets are compact. -/
theorem Filter.tendsto_cocompact_mul_right₀ [ContinuousMul K] {a : K} (ha : a ≠ 0) :
Filter.Tendsto (fun x : K => x * a) (Filter.cocompact K) (Filter.cocompact K) :=
Filter.tendsto_cocompact_mul_right (mul_inv_cancel ha)
#align filter.tendsto_cocompact_mul_right₀ Filter.tendsto_cocompact_mul_right₀
variable (K)
/-- A topological division ring is a division ring with a topology where all operations are
continuous, including inversion. -/
class TopologicalDivisionRing extends TopologicalRing K, HasContinuousInv₀ K : Prop
#align topological_division_ring TopologicalDivisionRing
section Subfield
variable {α : Type*} [Field α] [TopologicalSpace α] [TopologicalDivisionRing α]
/-- The (topological-space) closure of a subfield of a topological field is
itself a subfield. -/
def Subfield.topologicalClosure (K : Subfield α) : Subfield α :=
{ K.toSubring.topologicalClosure with
carrier := _root_.closure (K : Set α)
inv_mem' := fun x hx => by
dsimp only at hx ⊢
rcases eq_or_ne x 0 with (rfl | h)
· rwa [inv_zero]
· -- Porting note (#11215): TODO: Lean fails to find InvMemClass instance
rw [← @inv_coe_set α (Subfield α) _ _ SubfieldClass.toInvMemClass K, ← Set.image_inv]
exact mem_closure_image (continuousAt_inv₀ h) hx }
#align subfield.topological_closure Subfield.topologicalClosure
theorem Subfield.le_topologicalClosure (s : Subfield α) : s ≤ s.topologicalClosure :=
_root_.subset_closure
#align subfield.le_topological_closure Subfield.le_topologicalClosure
theorem Subfield.isClosed_topologicalClosure (s : Subfield α) :
IsClosed (s.topologicalClosure : Set α) :=
isClosed_closure
#align subfield.is_closed_topological_closure Subfield.isClosed_topologicalClosure
theorem Subfield.topologicalClosure_minimal (s : Subfield α) {t : Subfield α} (h : s ≤ t)
(ht : IsClosed (t : Set α)) : s.topologicalClosure ≤ t :=
closure_minimal h ht
#align subfield.topological_closure_minimal Subfield.topologicalClosure_minimal
end Subfield
section affineHomeomorph
/-!
This section is about affine homeomorphisms from a topological field `𝕜` to itself.
Technically it does not require `𝕜` to be a topological field, a topological ring that
happens to be a field is enough.
-/
variable {𝕜 : Type*} [Field 𝕜] [TopologicalSpace 𝕜] [TopologicalRing 𝕜]
/--
The map `fun x => a * x + b`, as a homeomorphism from `𝕜` (a topological field) to itself,
when `a ≠ 0`.
-/
@[simps]
def affineHomeomorph (a b : 𝕜) (h : a ≠ 0) : 𝕜 ≃ₜ 𝕜 where
toFun x := a * x + b
invFun y := (y - b) / a
left_inv x := by
simp only [add_sub_cancel_right]
exact mul_div_cancel_left₀ x h
right_inv y := by simp [mul_div_cancel₀ _ h]
#align affine_homeomorph affineHomeomorph
end affineHomeomorph
section LocalExtr
variable {α β : Type*} [TopologicalSpace α] [LinearOrderedSemifield β] {a : α}
open Topology
theorem IsLocalMin.inv {f : α → β} {a : α} (h1 : IsLocalMin f a) (h2 : ∀ᶠ z in 𝓝 a, 0 < f z) :
IsLocalMax f⁻¹ a := by
filter_upwards [h1, h2] with z h3 h4 using(inv_le_inv h4 h2.self_of_nhds).mpr h3
#align is_local_min.inv IsLocalMin.inv
end LocalExtr
section Preconnected
/-! Some results about functions on preconnected sets valued in a ring or field with a topology. -/
open Set
variable {α 𝕜 : Type*} {f g : α → 𝕜} {S : Set α} [TopologicalSpace α] [TopologicalSpace 𝕜]
[T1Space 𝕜]
/-- If `f` is a function `α → 𝕜` which is continuous on a preconnected set `S`, and
`f ^ 2 = 1` on `S`, then either `f = 1` on `S`, or `f = -1` on `S`. -/
| Mathlib/Topology/Algebra/Field.lean | 130 | 136 | theorem IsPreconnected.eq_one_or_eq_neg_one_of_sq_eq [Ring 𝕜] [NoZeroDivisors 𝕜]
(hS : IsPreconnected S) (hf : ContinuousOn f S) (hsq : EqOn (f ^ 2) 1 S) :
EqOn f 1 S ∨ EqOn f (-1) S := by |
have : DiscreteTopology ({1, -1} : Set 𝕜) := discrete_of_t1_of_finite
have hmaps : MapsTo f S {1, -1} := by
simpa only [EqOn, Pi.one_apply, Pi.pow_apply, sq_eq_one_iff] using hsq
simpa using hS.eqOn_const_of_mapsTo hf hmaps
|
/-
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.Data.Finset.Finsupp
import Mathlib.Data.Finsupp.Order
import Mathlib.Order.Interval.Finset.Basic
#align_import data.finsupp.interval from "leanprover-community/mathlib"@"1d29de43a5ba4662dd33b5cfeecfc2a27a5a8a29"
/-!
# Finite intervals of finitely supported functions
This file provides the `LocallyFiniteOrder` instance for `ι →₀ α` when `α` itself is locally
finite and calculates the cardinality of its finite intervals.
## Main declarations
* `Finsupp.rangeSingleton`: Postcomposition with `Singleton.singleton` on `Finset` as a
`Finsupp`.
* `Finsupp.rangeIcc`: Postcomposition with `Finset.Icc` as a `Finsupp`.
Both these definitions use the fact that `0 = {0}` to ensure that the resulting function is finitely
supported.
-/
noncomputable section
open Finset Finsupp Function
open scoped Classical
open Pointwise
variable {ι α : Type*}
namespace Finsupp
section RangeSingleton
variable [Zero α] {f : ι →₀ α} {i : ι} {a : α}
/-- Pointwise `Singleton.singleton` bundled as a `Finsupp`. -/
@[simps]
def rangeSingleton (f : ι →₀ α) : ι →₀ Finset α where
toFun i := {f i}
support := f.support
mem_support_toFun i := by
rw [← not_iff_not, not_mem_support_iff, not_ne_iff]
exact singleton_injective.eq_iff.symm
#align finsupp.range_singleton Finsupp.rangeSingleton
theorem mem_rangeSingleton_apply_iff : a ∈ f.rangeSingleton i ↔ a = f i :=
mem_singleton
#align finsupp.mem_range_singleton_apply_iff Finsupp.mem_rangeSingleton_apply_iff
end RangeSingleton
section RangeIcc
variable [Zero α] [PartialOrder α] [LocallyFiniteOrder α] {f g : ι →₀ α} {i : ι} {a : α}
/-- Pointwise `Finset.Icc` bundled as a `Finsupp`. -/
@[simps toFun]
def rangeIcc (f g : ι →₀ α) : ι →₀ Finset α where
toFun i := Icc (f i) (g i)
support :=
-- Porting note: Not needed (due to open scoped Classical), in mathlib3 too
-- haveI := Classical.decEq ι
f.support ∪ g.support
mem_support_toFun i := by
rw [mem_union, ← not_iff_not, not_or, not_mem_support_iff, not_mem_support_iff, not_ne_iff]
exact Icc_eq_singleton_iff.symm
#align finsupp.range_Icc Finsupp.rangeIcc
-- Porting note: Added as alternative to rangeIcc_toFun to be used in proof of card_Icc
lemma coe_rangeIcc (f g : ι →₀ α) : rangeIcc f g i = Icc (f i) (g i) := rfl
@[simp]
theorem rangeIcc_support (f g : ι →₀ α) :
(rangeIcc f g).support = f.support ∪ g.support := rfl
#align finsupp.range_Icc_support Finsupp.rangeIcc_support
theorem mem_rangeIcc_apply_iff : a ∈ f.rangeIcc g i ↔ f i ≤ a ∧ a ≤ g i := mem_Icc
#align finsupp.mem_range_Icc_apply_iff Finsupp.mem_rangeIcc_apply_iff
end RangeIcc
section PartialOrder
variable [PartialOrder α] [Zero α] [LocallyFiniteOrder α] (f g : ι →₀ α)
instance instLocallyFiniteOrder : LocallyFiniteOrder (ι →₀ α) :=
-- Porting note: Not needed (due to open scoped Classical), in mathlib3 too
-- haveI := Classical.decEq ι
-- haveI := Classical.decEq α
LocallyFiniteOrder.ofIcc (ι →₀ α) (fun f g => (f.support ∪ g.support).finsupp <| f.rangeIcc g)
fun f g x => by
refine
(mem_finsupp_iff_of_support_subset <| Finset.subset_of_eq <| rangeIcc_support _ _).trans ?_
simp_rw [mem_rangeIcc_apply_iff]
exact forall_and
theorem Icc_eq : Icc f g = (f.support ∪ g.support).finsupp (f.rangeIcc g) := rfl
#align finsupp.Icc_eq Finsupp.Icc_eq
-- Porting note: removed [DecidableEq ι]
theorem card_Icc : (Icc f g).card = ∏ i ∈ f.support ∪ g.support, (Icc (f i) (g i)).card := by
simp_rw [Icc_eq, card_finsupp, coe_rangeIcc]
#align finsupp.card_Icc Finsupp.card_Icc
-- Porting note: removed [DecidableEq ι]
theorem card_Ico : (Ico f g).card = (∏ i ∈ f.support ∪ g.support, (Icc (f i) (g i)).card) - 1 := by
rw [card_Ico_eq_card_Icc_sub_one, card_Icc]
#align finsupp.card_Ico Finsupp.card_Ico
-- Porting note: removed [DecidableEq ι]
theorem card_Ioc : (Ioc f g).card = (∏ i ∈ f.support ∪ g.support, (Icc (f i) (g i)).card) - 1 := by
rw [card_Ioc_eq_card_Icc_sub_one, card_Icc]
#align finsupp.card_Ioc Finsupp.card_Ioc
-- Porting note: removed [DecidableEq ι]
| Mathlib/Data/Finsupp/Interval.lean | 123 | 124 | theorem card_Ioo : (Ioo f g).card = (∏ i ∈ f.support ∪ g.support, (Icc (f i) (g i)).card) - 2 := by |
rw [card_Ioo_eq_card_Icc_sub_two, card_Icc]
|
/-
Copyright (c) 2020 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Computability.Halting
import Mathlib.Computability.TuringMachine
import Mathlib.Data.Num.Lemmas
import Mathlib.Tactic.DeriveFintype
#align_import computability.tm_to_partrec from "leanprover-community/mathlib"@"6155d4351090a6fad236e3d2e4e0e4e7342668e8"
/-!
# Modelling partial recursive functions using Turing machines
This file defines a simplified basis for partial recursive functions, and a `Turing.TM2` model
Turing machine for evaluating these functions. This amounts to a constructive proof that every
`Partrec` function can be evaluated by a Turing machine.
## Main definitions
* `ToPartrec.Code`: a simplified basis for partial recursive functions, valued in
`List ℕ →. List ℕ`.
* `ToPartrec.Code.eval`: semantics for a `ToPartrec.Code` program
* `PartrecToTM2.tr`: A TM2 turing machine which can evaluate `code` programs
-/
open Function (update)
open Relation
namespace Turing
/-!
## A simplified basis for partrec
This section constructs the type `Code`, which is a data type of programs with `List ℕ` input and
output, with enough expressivity to write any partial recursive function. The primitives are:
* `zero'` appends a `0` to the input. That is, `zero' v = 0 :: v`.
* `succ` returns the successor of the head of the input, defaulting to zero if there is no head:
* `succ [] = [1]`
* `succ (n :: v) = [n + 1]`
* `tail` returns the tail of the input
* `tail [] = []`
* `tail (n :: v) = v`
* `cons f fs` calls `f` and `fs` on the input and conses the results:
* `cons f fs v = (f v).head :: fs v`
* `comp f g` calls `f` on the output of `g`:
* `comp f g v = f (g v)`
* `case f g` cases on the head of the input, calling `f` or `g` depending on whether it is zero or
a successor (similar to `Nat.casesOn`).
* `case f g [] = f []`
* `case f g (0 :: v) = f v`
* `case f g (n+1 :: v) = g (n :: v)`
* `fix f` calls `f` repeatedly, using the head of the result of `f` to decide whether to call `f`
again or finish:
* `fix f v = []` if `f v = []`
* `fix f v = w` if `f v = 0 :: w`
* `fix f v = fix f w` if `f v = n+1 :: w` (the exact value of `n` is discarded)
This basis is convenient because it is closer to the Turing machine model - the key operations are
splitting and merging of lists of unknown length, while the messy `n`-ary composition operation
from the traditional basis for partial recursive functions is absent - but it retains a
compositional semantics. The first step in transitioning to Turing machines is to make a sequential
evaluator for this basis, which we take up in the next section.
-/
namespace ToPartrec
/-- The type of codes for primitive recursive functions. Unlike `Nat.Partrec.Code`, this uses a set
of operations on `List ℕ`. See `Code.eval` for a description of the behavior of the primitives. -/
inductive Code
| zero'
| succ
| tail
| cons : Code → Code → Code
| comp : Code → Code → Code
| case : Code → Code → Code
| fix : Code → Code
deriving DecidableEq, Inhabited
#align turing.to_partrec.code Turing.ToPartrec.Code
#align turing.to_partrec.code.zero' Turing.ToPartrec.Code.zero'
#align turing.to_partrec.code.succ Turing.ToPartrec.Code.succ
#align turing.to_partrec.code.tail Turing.ToPartrec.Code.tail
#align turing.to_partrec.code.cons Turing.ToPartrec.Code.cons
#align turing.to_partrec.code.comp Turing.ToPartrec.Code.comp
#align turing.to_partrec.code.case Turing.ToPartrec.Code.case
#align turing.to_partrec.code.fix Turing.ToPartrec.Code.fix
/-- The semantics of the `Code` primitives, as partial functions `List ℕ →. List ℕ`. By convention
we functions that return a single result return a singleton `[n]`, or in some cases `n :: v` where
`v` will be ignored by a subsequent function.
* `zero'` appends a `0` to the input. That is, `zero' v = 0 :: v`.
* `succ` returns the successor of the head of the input, defaulting to zero if there is no head:
* `succ [] = [1]`
* `succ (n :: v) = [n + 1]`
* `tail` returns the tail of the input
* `tail [] = []`
* `tail (n :: v) = v`
* `cons f fs` calls `f` and `fs` on the input and conses the results:
* `cons f fs v = (f v).head :: fs v`
* `comp f g` calls `f` on the output of `g`:
* `comp f g v = f (g v)`
* `case f g` cases on the head of the input, calling `f` or `g` depending on whether it is zero or
a successor (similar to `Nat.casesOn`).
* `case f g [] = f []`
* `case f g (0 :: v) = f v`
* `case f g (n+1 :: v) = g (n :: v)`
* `fix f` calls `f` repeatedly, using the head of the result of `f` to decide whether to call `f`
again or finish:
* `fix f v = []` if `f v = []`
* `fix f v = w` if `f v = 0 :: w`
* `fix f v = fix f w` if `f v = n+1 :: w` (the exact value of `n` is discarded)
-/
def Code.eval : Code → List ℕ →. List ℕ
| Code.zero' => fun v => pure (0 :: v)
| Code.succ => fun v => pure [v.headI.succ]
| Code.tail => fun v => pure v.tail
| Code.cons f fs => fun v => do
let n ← Code.eval f v
let ns ← Code.eval fs v
pure (n.headI :: ns)
| Code.comp f g => fun v => g.eval v >>= f.eval
| Code.case f g => fun v => v.headI.rec (f.eval v.tail) fun y _ => g.eval (y::v.tail)
| Code.fix f =>
PFun.fix fun v => (f.eval v).map fun v => if v.headI = 0 then Sum.inl v.tail else Sum.inr v.tail
#align turing.to_partrec.code.eval Turing.ToPartrec.Code.eval
namespace Code
/- Porting note: The equation lemma of `eval` is too strong; it simplifies terms like the LHS of
`pred_eval`. Even `eqns` can't fix this. We removed `simp` attr from `eval` and prepare new simp
lemmas for `eval`. -/
@[simp]
theorem zero'_eval : zero'.eval = fun v => pure (0 :: v) := by simp [eval]
@[simp]
theorem succ_eval : succ.eval = fun v => pure [v.headI.succ] := by simp [eval]
@[simp]
theorem tail_eval : tail.eval = fun v => pure v.tail := by simp [eval]
@[simp]
theorem cons_eval (f fs) : (cons f fs).eval = fun v => do {
let n ← Code.eval f v
let ns ← Code.eval fs v
pure (n.headI :: ns) } := by simp [eval]
@[simp]
theorem comp_eval (f g) : (comp f g).eval = fun v => g.eval v >>= f.eval := by simp [eval]
@[simp]
theorem case_eval (f g) :
(case f g).eval = fun v => v.headI.rec (f.eval v.tail) fun y _ => g.eval (y::v.tail) := by
simp [eval]
@[simp]
theorem fix_eval (f) : (fix f).eval =
PFun.fix fun v => (f.eval v).map fun v =>
if v.headI = 0 then Sum.inl v.tail else Sum.inr v.tail := by
simp [eval]
/-- `nil` is the constant nil function: `nil v = []`. -/
def nil : Code :=
tail.comp succ
#align turing.to_partrec.code.nil Turing.ToPartrec.Code.nil
@[simp]
theorem nil_eval (v) : nil.eval v = pure [] := by simp [nil]
#align turing.to_partrec.code.nil_eval Turing.ToPartrec.Code.nil_eval
/-- `id` is the identity function: `id v = v`. -/
def id : Code :=
tail.comp zero'
#align turing.to_partrec.code.id Turing.ToPartrec.Code.id
@[simp]
theorem id_eval (v) : id.eval v = pure v := by simp [id]
#align turing.to_partrec.code.id_eval Turing.ToPartrec.Code.id_eval
/-- `head` gets the head of the input list: `head [] = [0]`, `head (n :: v) = [n]`. -/
def head : Code :=
cons id nil
#align turing.to_partrec.code.head Turing.ToPartrec.Code.head
@[simp]
theorem head_eval (v) : head.eval v = pure [v.headI] := by simp [head]
#align turing.to_partrec.code.head_eval Turing.ToPartrec.Code.head_eval
/-- `zero` is the constant zero function: `zero v = [0]`. -/
def zero : Code :=
cons zero' nil
#align turing.to_partrec.code.zero Turing.ToPartrec.Code.zero
@[simp]
theorem zero_eval (v) : zero.eval v = pure [0] := by simp [zero]
#align turing.to_partrec.code.zero_eval Turing.ToPartrec.Code.zero_eval
/-- `pred` returns the predecessor of the head of the input:
`pred [] = [0]`, `pred (0 :: v) = [0]`, `pred (n+1 :: v) = [n]`. -/
def pred : Code :=
case zero head
#align turing.to_partrec.code.pred Turing.ToPartrec.Code.pred
@[simp]
theorem pred_eval (v) : pred.eval v = pure [v.headI.pred] := by
simp [pred]; cases v.headI <;> simp
#align turing.to_partrec.code.pred_eval Turing.ToPartrec.Code.pred_eval
/-- `rfind f` performs the function of the `rfind` primitive of partial recursive functions.
`rfind f v` returns the smallest `n` such that `(f (n :: v)).head = 0`.
It is implemented as:
rfind f v = pred (fix (fun (n::v) => f (n::v) :: n+1 :: v) (0 :: v))
The idea is that the initial state is `0 :: v`, and the `fix` keeps `n :: v` as its internal state;
it calls `f (n :: v)` as the exit test and `n+1 :: v` as the next state. At the end we get
`n+1 :: v` where `n` is the desired output, and `pred (n+1 :: v) = [n]` returns the result.
-/
def rfind (f : Code) : Code :=
comp pred <| comp (fix <| cons f <| cons succ tail) zero'
#align turing.to_partrec.code.rfind Turing.ToPartrec.Code.rfind
/-- `prec f g` implements the `prec` (primitive recursion) operation of partial recursive
functions. `prec f g` evaluates as:
* `prec f g [] = [f []]`
* `prec f g (0 :: v) = [f v]`
* `prec f g (n+1 :: v) = [g (n :: prec f g (n :: v) :: v)]`
It is implemented as:
G (a :: b :: IH :: v) = (b :: a+1 :: b-1 :: g (a :: IH :: v) :: v)
F (0 :: f_v :: v) = (f_v :: v)
F (n+1 :: f_v :: v) = (fix G (0 :: n :: f_v :: v)).tail.tail
prec f g (a :: v) = [(F (a :: f v :: v)).head]
Because `fix` always evaluates its body at least once, we must special case the `0` case to avoid
calling `g` more times than necessary (which could be bad if `g` diverges). If the input is
`0 :: v`, then `F (0 :: f v :: v) = (f v :: v)` so we return `[f v]`. If the input is `n+1 :: v`,
we evaluate the function from the bottom up, with initial state `0 :: n :: f v :: v`. The first
number counts up, providing arguments for the applications to `g`, while the second number counts
down, providing the exit condition (this is the initial `b` in the return value of `G`, which is
stripped by `fix`). After the `fix` is complete, the final state is `n :: 0 :: res :: v` where
`res` is the desired result, and the rest reduces this to `[res]`. -/
def prec (f g : Code) : Code :=
let G :=
cons tail <|
cons succ <|
cons (comp pred tail) <|
cons (comp g <| cons id <| comp tail tail) <| comp tail <| comp tail tail
let F := case id <| comp (comp (comp tail tail) (fix G)) zero'
cons (comp F (cons head <| cons (comp f tail) tail)) nil
#align turing.to_partrec.code.prec Turing.ToPartrec.Code.prec
attribute [-simp] Part.bind_eq_bind Part.map_eq_map Part.pure_eq_some
theorem exists_code.comp {m n} {f : Vector ℕ n →. ℕ} {g : Fin n → Vector ℕ m →. ℕ}
(hf : ∃ c : Code, ∀ v : Vector ℕ n, c.eval v.1 = pure <$> f v)
(hg : ∀ i, ∃ c : Code, ∀ v : Vector ℕ m, c.eval v.1 = pure <$> g i v) :
∃ c : Code, ∀ v : Vector ℕ m, c.eval v.1 = pure <$> ((Vector.mOfFn fun i => g i v) >>= f) := by
rsuffices ⟨cg, hg⟩ :
∃ c : Code, ∀ v : Vector ℕ m, c.eval v.1 = Subtype.val <$> Vector.mOfFn fun i => g i v
· obtain ⟨cf, hf⟩ := hf
exact
⟨cf.comp cg, fun v => by
simp [hg, hf, map_bind, seq_bind_eq, Function.comp]
rfl⟩
clear hf f; induction' n with n IH
· exact ⟨nil, fun v => by simp [Vector.mOfFn, Bind.bind]; rfl⟩
· obtain ⟨cg, hg₁⟩ := hg 0
obtain ⟨cl, hl⟩ := IH fun i => hg i.succ
exact
⟨cons cg cl, fun v => by
simp [Vector.mOfFn, hg₁, map_bind, seq_bind_eq, bind_assoc, (· ∘ ·), hl]
rfl⟩
#align turing.to_partrec.code.exists_code.comp Turing.ToPartrec.Code.exists_code.comp
theorem exists_code {n} {f : Vector ℕ n →. ℕ} (hf : Nat.Partrec' f) :
∃ c : Code, ∀ v : Vector ℕ n, c.eval v.1 = pure <$> f v := by
induction hf with
| prim hf =>
induction hf with
| zero => exact ⟨zero', fun ⟨[], _⟩ => rfl⟩
| succ => exact ⟨succ, fun ⟨[v], _⟩ => rfl⟩
| get i =>
refine Fin.succRec (fun n => ?_) (fun n i IH => ?_) i
· exact ⟨head, fun ⟨List.cons a as, _⟩ => by simp [Bind.bind]; rfl⟩
· obtain ⟨c, h⟩ := IH
exact ⟨c.comp tail, fun v => by simpa [← Vector.get_tail, Bind.bind] using h v.tail⟩
| comp g hf hg IHf IHg =>
simpa [Part.bind_eq_bind] using exists_code.comp IHf IHg
| @prec n f g _ _ IHf IHg =>
obtain ⟨cf, hf⟩ := IHf
obtain ⟨cg, hg⟩ := IHg
simp only [Part.map_eq_map, Part.map_some, PFun.coe_val] at hf hg
refine ⟨prec cf cg, fun v => ?_⟩
rw [← v.cons_head_tail]
specialize hf v.tail
replace hg := fun a b => hg (a ::ᵥ b ::ᵥ v.tail)
simp only [Vector.cons_val, Vector.tail_val] at hf hg
simp only [Part.map_eq_map, Part.map_some, Vector.cons_val, Vector.tail_cons,
Vector.head_cons, PFun.coe_val, Vector.tail_val]
simp only [← Part.pure_eq_some] at hf hg ⊢
induction' v.head with n _ <;>
simp [prec, hf, Part.bind_assoc, ← Part.bind_some_eq_map, Part.bind_some,
show ∀ x, pure x = [x] from fun _ => rfl, Bind.bind, Functor.map]
suffices ∀ a b, a + b = n →
(n.succ :: 0 ::
g (n ::ᵥ Nat.rec (f v.tail) (fun y IH => g (y ::ᵥ IH ::ᵥ v.tail)) n ::ᵥ v.tail) ::
v.val.tail : List ℕ) ∈
PFun.fix
(fun v : List ℕ => Part.bind (cg.eval (v.headI :: v.tail.tail))
(fun x => Part.some (if v.tail.headI = 0
then Sum.inl
(v.headI.succ :: v.tail.headI.pred :: x.headI :: v.tail.tail.tail : List ℕ)
else Sum.inr
(v.headI.succ :: v.tail.headI.pred :: x.headI :: v.tail.tail.tail))))
(a :: b :: Nat.rec (f v.tail) (fun y IH => g (y ::ᵥ IH ::ᵥ v.tail)) a :: v.val.tail) by
erw [Part.eq_some_iff.2 (this 0 n (zero_add n))]
simp only [List.headI, Part.bind_some, List.tail_cons]
intro a b e
induction' b with b IH generalizing a
· refine PFun.mem_fix_iff.2 (Or.inl <| Part.eq_some_iff.1 ?_)
simp only [hg, ← e, Part.bind_some, List.tail_cons, pure]
rfl
· refine PFun.mem_fix_iff.2 (Or.inr ⟨_, ?_, IH (a + 1) (by rwa [add_right_comm])⟩)
simp only [hg, eval, Part.bind_some, Nat.rec_add_one, List.tail_nil, List.tail_cons, pure]
exact Part.mem_some_iff.2 rfl
| comp g _ _ IHf IHg => exact exists_code.comp IHf IHg
| @rfind n f _ IHf =>
obtain ⟨cf, hf⟩ := IHf; refine ⟨rfind cf, fun v => ?_⟩
replace hf := fun a => hf (a ::ᵥ v)
simp only [Part.map_eq_map, Part.map_some, Vector.cons_val, PFun.coe_val,
show ∀ x, pure x = [x] from fun _ => rfl] at hf ⊢
refine Part.ext fun x => ?_
simp only [rfind, Part.bind_eq_bind, Part.pure_eq_some, Part.map_eq_map, Part.bind_some,
exists_prop, cons_eval, comp_eval, fix_eval, tail_eval, succ_eval, zero'_eval,
List.headI_nil, List.headI_cons, pred_eval, Part.map_some, false_eq_decide_iff,
Part.mem_bind_iff, List.length, Part.mem_map_iff, Nat.mem_rfind, List.tail_nil,
List.tail_cons, true_eq_decide_iff, Part.mem_some_iff, Part.map_bind]
constructor
· rintro ⟨v', h1, rfl⟩
suffices ∀ v₁ : List ℕ, v' ∈ PFun.fix
(fun v => (cf.eval v).bind fun y => Part.some <|
if y.headI = 0 then Sum.inl (v.headI.succ :: v.tail)
else Sum.inr (v.headI.succ :: v.tail)) v₁ →
∀ n, (v₁ = n :: v.val) → (∀ m < n, ¬f (m ::ᵥ v) = 0) →
∃ a : ℕ,
(f (a ::ᵥ v) = 0 ∧ ∀ {m : ℕ}, m < a → ¬f (m ::ᵥ v) = 0) ∧ [a] = [v'.headI.pred]
by exact this _ h1 0 rfl (by rintro _ ⟨⟩)
clear h1
intro v₀ h1
refine PFun.fixInduction h1 fun v₁ h2 IH => ?_
clear h1
rintro n rfl hm
have := PFun.mem_fix_iff.1 h2
simp only [hf, Part.bind_some] at this
split_ifs at this with h
· simp only [List.headI_nil, List.headI_cons, exists_false, or_false_iff, Part.mem_some_iff,
List.tail_cons, false_and_iff, Sum.inl.injEq] at this
subst this
exact ⟨_, ⟨h, @(hm)⟩, rfl⟩
· refine IH (n.succ::v.val) (by simp_all) _ rfl fun m h' => ?_
obtain h | rfl := Nat.lt_succ_iff_lt_or_eq.1 h'
exacts [hm _ h, h]
· rintro ⟨n, ⟨hn, hm⟩, rfl⟩
refine ⟨n.succ::v.1, ?_, rfl⟩
have : (n.succ::v.1 : List ℕ) ∈
PFun.fix (fun v =>
(cf.eval v).bind fun y =>
Part.some <|
if y.headI = 0 then Sum.inl (v.headI.succ :: v.tail)
else Sum.inr (v.headI.succ :: v.tail))
(n::v.val) :=
PFun.mem_fix_iff.2 (Or.inl (by simp [hf, hn]))
generalize (n.succ :: v.1 : List ℕ) = w at this ⊢
clear hn
induction' n with n IH
· exact this
refine IH (fun {m} h' => hm (Nat.lt_succ_of_lt h'))
(PFun.mem_fix_iff.2 (Or.inr ⟨_, ?_, this⟩))
simp only [hf, hm n.lt_succ_self, Part.bind_some, List.headI, eq_self_iff_true, if_false,
Part.mem_some_iff, and_self_iff, List.tail_cons]
#align turing.to_partrec.code.exists_code Turing.ToPartrec.Code.exists_code
end Code
/-!
## From compositional semantics to sequential semantics
Our initial sequential model is designed to be as similar as possible to the compositional
semantics in terms of its primitives, but it is a sequential semantics, meaning that rather than
defining an `eval c : List ℕ →. List ℕ` function for each program, defined by recursion on
programs, we have a type `Cfg` with a step function `step : Cfg → Option cfg` that provides a
deterministic evaluation order. In order to do this, we introduce the notion of a *continuation*,
which can be viewed as a `Code` with a hole in it where evaluation is currently taking place.
Continuations can be assigned a `List ℕ →. List ℕ` semantics as well, with the interpretation
being that given a `List ℕ` result returned from the code in the hole, the remainder of the
program will evaluate to a `List ℕ` final value.
The continuations are:
* `halt`: the empty continuation: the hole is the whole program, whatever is returned is the
final result. In our notation this is just `_`.
* `cons₁ fs v k`: evaluating the first part of a `cons`, that is `k (_ :: fs v)`, where `k` is the
outer continuation.
* `cons₂ ns k`: evaluating the second part of a `cons`: `k (ns.headI :: _)`. (Technically we don't
need to hold on to all of `ns` here since we are already committed to taking the head, but this
is more regular.)
* `comp f k`: evaluating the first part of a composition: `k (f _)`.
* `fix f k`: waiting for the result of `f` in a `fix f` expression:
`k (if _.headI = 0 then _.tail else fix f (_.tail))`
The type `Cfg` of evaluation states is:
* `ret k v`: we have received a result, and are now evaluating the continuation `k` with result
`v`; that is, `k v` where `k` is ready to evaluate.
* `halt v`: we are done and the result is `v`.
The main theorem of this section is that for each code `c`, the state `stepNormal c halt v` steps
to `v'` in finitely many steps if and only if `Code.eval c v = some v'`.
-/
/-- The type of continuations, built up during evaluation of a `Code` expression. -/
inductive Cont
| halt
| cons₁ : Code → List ℕ → Cont → Cont
| cons₂ : List ℕ → Cont → Cont
| comp : Code → Cont → Cont
| fix : Code → Cont → Cont
deriving Inhabited
#align turing.to_partrec.cont Turing.ToPartrec.Cont
#align turing.to_partrec.cont.halt Turing.ToPartrec.Cont.halt
#align turing.to_partrec.cont.cons₁ Turing.ToPartrec.Cont.cons₁
#align turing.to_partrec.cont.cons₂ Turing.ToPartrec.Cont.cons₂
#align turing.to_partrec.cont.comp Turing.ToPartrec.Cont.comp
#align turing.to_partrec.cont.fix Turing.ToPartrec.Cont.fix
/-- The semantics of a continuation. -/
def Cont.eval : Cont → List ℕ →. List ℕ
| Cont.halt => pure
| Cont.cons₁ fs as k => fun v => do
let ns ← Code.eval fs as
Cont.eval k (v.headI :: ns)
| Cont.cons₂ ns k => fun v => Cont.eval k (ns.headI :: v)
| Cont.comp f k => fun v => Code.eval f v >>= Cont.eval k
| Cont.fix f k => fun v => if v.headI = 0 then k.eval v.tail else f.fix.eval v.tail >>= k.eval
#align turing.to_partrec.cont.eval Turing.ToPartrec.Cont.eval
/-- The set of configurations of the machine:
* `halt v`: The machine is about to stop and `v : List ℕ` is the result.
* `ret k v`: The machine is about to pass `v : List ℕ` to continuation `k : cont`.
We don't have a state corresponding to normal evaluation because these are evaluated immediately
to a `ret` "in zero steps" using the `stepNormal` function. -/
inductive Cfg
| halt : List ℕ → Cfg
| ret : Cont → List ℕ → Cfg
deriving Inhabited
#align turing.to_partrec.cfg Turing.ToPartrec.Cfg
#align turing.to_partrec.cfg.halt Turing.ToPartrec.Cfg.halt
#align turing.to_partrec.cfg.ret Turing.ToPartrec.Cfg.ret
/-- Evaluating `c : Code` in a continuation `k : Cont` and input `v : List ℕ`. This goes by
recursion on `c`, building an augmented continuation and a value to pass to it.
* `zero' v = 0 :: v` evaluates immediately, so we return it to the parent continuation
* `succ v = [v.headI.succ]` evaluates immediately, so we return it to the parent continuation
* `tail v = v.tail` evaluates immediately, so we return it to the parent continuation
* `cons f fs v = (f v).headI :: fs v` requires two sub-evaluations, so we evaluate
`f v` in the continuation `k (_.headI :: fs v)` (called `Cont.cons₁ fs v k`)
* `comp f g v = f (g v)` requires two sub-evaluations, so we evaluate
`g v` in the continuation `k (f _)` (called `Cont.comp f k`)
* `case f g v = v.head.casesOn (f v.tail) (fun n => g (n :: v.tail))` has the information needed
to evaluate the case statement, so we do that and transition to either
`f v` or `g (n :: v.tail)`.
* `fix f v = let v' := f v; if v'.headI = 0 then k v'.tail else fix f v'.tail`
needs to first evaluate `f v`, so we do that and leave the rest for the continuation (called
`Cont.fix f k`)
-/
def stepNormal : Code → Cont → List ℕ → Cfg
| Code.zero' => fun k v => Cfg.ret k (0::v)
| Code.succ => fun k v => Cfg.ret k [v.headI.succ]
| Code.tail => fun k v => Cfg.ret k v.tail
| Code.cons f fs => fun k v => stepNormal f (Cont.cons₁ fs v k) v
| Code.comp f g => fun k v => stepNormal g (Cont.comp f k) v
| Code.case f g => fun k v =>
v.headI.rec (stepNormal f k v.tail) fun y _ => stepNormal g k (y::v.tail)
| Code.fix f => fun k v => stepNormal f (Cont.fix f k) v
#align turing.to_partrec.step_normal Turing.ToPartrec.stepNormal
/-- Evaluating a continuation `k : Cont` on input `v : List ℕ`. This is the second part of
evaluation, when we receive results from continuations built by `stepNormal`.
* `Cont.halt v = v`, so we are done and transition to the `Cfg.halt v` state
* `Cont.cons₁ fs as k v = k (v.headI :: fs as)`, so we evaluate `fs as` now with the continuation
`k (v.headI :: _)` (called `cons₂ v k`).
* `Cont.cons₂ ns k v = k (ns.headI :: v)`, where we now have everything we need to evaluate
`ns.headI :: v`, so we return it to `k`.
* `Cont.comp f k v = k (f v)`, so we call `f v` with `k` as the continuation.
* `Cont.fix f k v = k (if v.headI = 0 then k v.tail else fix f v.tail)`, where `v` is a value,
so we evaluate the if statement and either call `k` with `v.tail`, or call `fix f v` with `k` as
the continuation (which immediately calls `f` with `Cont.fix f k` as the continuation).
-/
def stepRet : Cont → List ℕ → Cfg
| Cont.halt, v => Cfg.halt v
| Cont.cons₁ fs as k, v => stepNormal fs (Cont.cons₂ v k) as
| Cont.cons₂ ns k, v => stepRet k (ns.headI :: v)
| Cont.comp f k, v => stepNormal f k v
| Cont.fix f k, v => if v.headI = 0 then stepRet k v.tail else stepNormal f (Cont.fix f k) v.tail
#align turing.to_partrec.step_ret Turing.ToPartrec.stepRet
/-- If we are not done (in `Cfg.halt` state), then we must be still stuck on a continuation, so
this main loop calls `stepRet` with the new continuation. The overall `step` function transitions
from one `Cfg` to another, only halting at the `Cfg.halt` state. -/
def step : Cfg → Option Cfg
| Cfg.halt _ => none
| Cfg.ret k v => some (stepRet k v)
#align turing.to_partrec.step Turing.ToPartrec.step
/-- In order to extract a compositional semantics from the sequential execution behavior of
configurations, we observe that continuations have a monoid structure, with `Cont.halt` as the unit
and `Cont.then` as the multiplication. `Cont.then k₁ k₂` runs `k₁` until it halts, and then takes
the result of `k₁` and passes it to `k₂`.
We will not prove it is associative (although it is), but we are instead interested in the
associativity law `k₂ (eval c k₁) = eval c (k₁.then k₂)`. This holds at both the sequential and
compositional levels, and allows us to express running a machine without the ambient continuation
and relate it to the original machine's evaluation steps. In the literature this is usually
where one uses Turing machines embedded inside other Turing machines, but this approach allows us
to avoid changing the ambient type `Cfg` in the middle of the recursion.
-/
def Cont.then : Cont → Cont → Cont
| Cont.halt => fun k' => k'
| Cont.cons₁ fs as k => fun k' => Cont.cons₁ fs as (k.then k')
| Cont.cons₂ ns k => fun k' => Cont.cons₂ ns (k.then k')
| Cont.comp f k => fun k' => Cont.comp f (k.then k')
| Cont.fix f k => fun k' => Cont.fix f (k.then k')
#align turing.to_partrec.cont.then Turing.ToPartrec.Cont.then
theorem Cont.then_eval {k k' : Cont} {v} : (k.then k').eval v = k.eval v >>= k'.eval := by
induction' k with _ _ _ _ _ _ _ _ _ k_ih _ _ k_ih generalizing v <;>
simp only [Cont.eval, Cont.then, bind_assoc, pure_bind, *]
· simp only [← k_ih]
· split_ifs <;> [rfl; simp only [← k_ih, bind_assoc]]
#align turing.to_partrec.cont.then_eval Turing.ToPartrec.Cont.then_eval
/-- The `then k` function is a "configuration homomorphism". Its operation on states is to append
`k` to the continuation of a `Cfg.ret` state, and to run `k` on `v` if we are in the `Cfg.halt v`
state. -/
def Cfg.then : Cfg → Cont → Cfg
| Cfg.halt v => fun k' => stepRet k' v
| Cfg.ret k v => fun k' => Cfg.ret (k.then k') v
#align turing.to_partrec.cfg.then Turing.ToPartrec.Cfg.then
/-- The `stepNormal` function respects the `then k'` homomorphism. Note that this is an exact
equality, not a simulation; the original and embedded machines move in lock-step until the
embedded machine reaches the halt state. -/
theorem stepNormal_then (c) (k k' : Cont) (v) :
stepNormal c (k.then k') v = (stepNormal c k v).then k' := by
induction c generalizing k v with simp only [Cont.then, stepNormal, *]
| cons c c' ih _ => rw [← ih, Cont.then]
| comp c c' _ ih' => rw [← ih', Cont.then]
| case => cases v.headI <;> simp only [Nat.rec_zero]
| fix c ih => rw [← ih, Cont.then]
| _ => simp only [Cfg.then]
#align turing.to_partrec.step_normal_then Turing.ToPartrec.stepNormal_then
/-- The `stepRet` function respects the `then k'` homomorphism. Note that this is an exact
equality, not a simulation; the original and embedded machines move in lock-step until the
embedded machine reaches the halt state. -/
theorem stepRet_then {k k' : Cont} {v} : stepRet (k.then k') v = (stepRet k v).then k' := by
induction k generalizing v with simp only [Cont.then, stepRet, *]
| cons₁ =>
rw [← stepNormal_then]
rfl
| comp =>
rw [← stepNormal_then]
| fix _ _ k_ih =>
split_ifs
· rw [← k_ih]
· rw [← stepNormal_then]
rfl
| _ => simp only [Cfg.then]
#align turing.to_partrec.step_ret_then Turing.ToPartrec.stepRet_then
/-- This is a temporary definition, because we will prove in `code_is_ok` that it always holds.
It asserts that `c` is semantically correct; that is, for any `k` and `v`,
`eval (stepNormal c k v) = eval (Cfg.ret k (Code.eval c v))`, as an equality of partial values
(so one diverges iff the other does).
In particular, we can let `k = Cont.halt`, and then this asserts that `stepNormal c Cont.halt v`
evaluates to `Cfg.halt (Code.eval c v)`. -/
def Code.Ok (c : Code) :=
∀ k v, Turing.eval step (stepNormal c k v) =
Code.eval c v >>= fun v => Turing.eval step (Cfg.ret k v)
#align turing.to_partrec.code.ok Turing.ToPartrec.Code.Ok
theorem Code.Ok.zero {c} (h : Code.Ok c) {v} :
Turing.eval step (stepNormal c Cont.halt v) = Cfg.halt <$> Code.eval c v := by
rw [h, ← bind_pure_comp]; congr; funext v
exact Part.eq_some_iff.2 (mem_eval.2 ⟨ReflTransGen.single rfl, rfl⟩)
#align turing.to_partrec.code.ok.zero Turing.ToPartrec.Code.Ok.zero
theorem stepNormal.is_ret (c k v) : ∃ k' v', stepNormal c k v = Cfg.ret k' v' := by
induction c generalizing k v with
| cons _f fs IHf _IHfs => apply IHf
| comp f _g _IHf IHg => apply IHg
| case f g IHf IHg =>
rw [stepNormal]
simp only []
cases v.headI <;> [apply IHf; apply IHg]
| fix f IHf => apply IHf
| _ => exact ⟨_, _, rfl⟩
#align turing.to_partrec.step_normal.is_ret Turing.ToPartrec.stepNormal.is_ret
theorem cont_eval_fix {f k v} (fok : Code.Ok f) :
Turing.eval step (stepNormal f (Cont.fix f k) v) =
f.fix.eval v >>= fun v => Turing.eval step (Cfg.ret k v) := by
refine Part.ext fun x => ?_
simp only [Part.bind_eq_bind, Part.mem_bind_iff]
constructor
· suffices ∀ c, x ∈ eval step c → ∀ v c', c = Cfg.then c' (Cont.fix f k) →
Reaches step (stepNormal f Cont.halt v) c' →
∃ v₁ ∈ f.eval v, ∃ v₂ ∈ if List.headI v₁ = 0 then pure v₁.tail else f.fix.eval v₁.tail,
x ∈ eval step (Cfg.ret k v₂) by
intro h
obtain ⟨v₁, hv₁, v₂, hv₂, h₃⟩ :=
this _ h _ _ (stepNormal_then _ Cont.halt _ _) ReflTransGen.refl
refine ⟨v₂, PFun.mem_fix_iff.2 ?_, h₃⟩
simp only [Part.eq_some_iff.2 hv₁, Part.map_some]
split_ifs at hv₂ ⊢
· rw [Part.mem_some_iff.1 hv₂]
exact Or.inl (Part.mem_some _)
· exact Or.inr ⟨_, Part.mem_some _, hv₂⟩
refine fun c he => evalInduction he fun y h IH => ?_
rintro v (⟨v'⟩ | ⟨k', v'⟩) rfl hr <;> rw [Cfg.then] at h IH <;> simp only [] at h IH
· have := mem_eval.2 ⟨hr, rfl⟩
rw [fok, Part.bind_eq_bind, Part.mem_bind_iff] at this
obtain ⟨v'', h₁, h₂⟩ := this
rw [reaches_eval] at h₂
swap
· exact ReflTransGen.single rfl
cases Part.mem_unique h₂ (mem_eval.2 ⟨ReflTransGen.refl, rfl⟩)
refine ⟨v', h₁, ?_⟩
rw [stepRet] at h
revert h
by_cases he : v'.headI = 0 <;> simp only [exists_prop, if_pos, if_false, he] <;> intro h
· refine ⟨_, Part.mem_some _, ?_⟩
rw [reaches_eval]
· exact h
exact ReflTransGen.single rfl
· obtain ⟨k₀, v₀, e₀⟩ := stepNormal.is_ret f Cont.halt v'.tail
have e₁ := stepNormal_then f Cont.halt (Cont.fix f k) v'.tail
rw [e₀, Cont.then, Cfg.then] at e₁
simp only [] at e₁
obtain ⟨v₁, hv₁, v₂, hv₂, h₃⟩ :=
IH (stepRet (k₀.then (Cont.fix f k)) v₀) (by rw [stepRet, if_neg he, e₁]; rfl)
v'.tail _ stepRet_then (by apply ReflTransGen.single; rw [e₀]; rfl)
refine ⟨_, PFun.mem_fix_iff.2 ?_, h₃⟩
simp only [Part.eq_some_iff.2 hv₁, Part.map_some, Part.mem_some_iff]
split_ifs at hv₂ ⊢ <;> [exact Or.inl (congr_arg Sum.inl (Part.mem_some_iff.1 hv₂));
exact Or.inr ⟨_, rfl, hv₂⟩]
· exact IH _ rfl _ _ stepRet_then (ReflTransGen.tail hr rfl)
· rintro ⟨v', he, hr⟩
rw [reaches_eval] at hr
swap
· exact ReflTransGen.single rfl
refine PFun.fixInduction he fun v (he : v' ∈ f.fix.eval v) IH => ?_
rw [fok, Part.bind_eq_bind, Part.mem_bind_iff]
obtain he | ⟨v'', he₁', _⟩ := PFun.mem_fix_iff.1 he
· obtain ⟨v', he₁, he₂⟩ := (Part.mem_map_iff _).1 he
split_ifs at he₂ with h; cases he₂
refine ⟨_, he₁, ?_⟩
rw [reaches_eval]
swap
· exact ReflTransGen.single rfl
rwa [stepRet, if_pos h]
· obtain ⟨v₁, he₁, he₂⟩ := (Part.mem_map_iff _).1 he₁'
split_ifs at he₂ with h; cases he₂
clear he₁'
refine ⟨_, he₁, ?_⟩
rw [reaches_eval]
swap
· exact ReflTransGen.single rfl
rw [stepRet, if_neg h]
exact IH v₁.tail ((Part.mem_map_iff _).2 ⟨_, he₁, if_neg h⟩)
#align turing.to_partrec.cont_eval_fix Turing.ToPartrec.cont_eval_fix
| Mathlib/Computability/TMToPartrec.lean | 699 | 719 | theorem code_is_ok (c) : Code.Ok c := by |
induction c with (intro k v; rw [stepNormal])
| cons f fs IHf IHfs =>
rw [Code.eval, IHf]
simp only [bind_assoc, Cont.eval, pure_bind]; congr; funext v
rw [reaches_eval]; swap
· exact ReflTransGen.single rfl
rw [stepRet, IHfs]; congr; funext v'
refine Eq.trans (b := eval step (stepRet (Cont.cons₂ v k) v')) ?_ (Eq.symm ?_) <;>
exact reaches_eval (ReflTransGen.single rfl)
| comp f g IHf IHg =>
rw [Code.eval, IHg]
simp only [bind_assoc, Cont.eval, pure_bind]; congr; funext v
rw [reaches_eval]; swap
· exact ReflTransGen.single rfl
rw [stepRet, IHf]
| case f g IHf IHg =>
simp only [Code.eval]
cases v.headI <;> simp only [Nat.rec_zero, Part.bind_eq_bind] <;> [apply IHf; apply IHg]
| fix f IHf => rw [cont_eval_fix IHf]
| _ => simp only [Code.eval, pure_bind]
|
/-
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
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 1,485 | 1,488 | 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]
|
/-
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
| .lake/packages/batteries/Batteries/Data/Rat/Lemmas.lean | 52 | 56 | 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)]
|
/-
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, Eric Wieser
-/
import Mathlib.Algebra.Algebra.Prod
import Mathlib.LinearAlgebra.Basic
import Mathlib.LinearAlgebra.Span
import Mathlib.Order.PartialSups
#align_import linear_algebra.prod from "leanprover-community/mathlib"@"cd391184c85986113f8c00844cfe6dda1d34be3d"
/-! ### Products of modules
This file defines constructors for linear maps whose domains or codomains are products.
It contains theorems relating these to each other, as well as to `Submodule.prod`, `Submodule.map`,
`Submodule.comap`, `LinearMap.range`, and `LinearMap.ker`.
## Main definitions
- products in the domain:
- `LinearMap.fst`
- `LinearMap.snd`
- `LinearMap.coprod`
- `LinearMap.prod_ext`
- products in the codomain:
- `LinearMap.inl`
- `LinearMap.inr`
- `LinearMap.prod`
- products in both domain and codomain:
- `LinearMap.prodMap`
- `LinearEquiv.prodMap`
- `LinearEquiv.skewProd`
-/
universe u v w x y z u' v' w' y'
variable {R : Type u} {K : Type u'} {M : Type v} {V : Type v'} {M₂ : Type w} {V₂ : Type w'}
variable {M₃ : Type y} {V₃ : Type y'} {M₄ : Type z} {ι : Type x}
variable {M₅ M₆ : Type*}
section Prod
namespace LinearMap
variable (S : Type*) [Semiring R] [Semiring S]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃] [AddCommMonoid M₄]
variable [AddCommMonoid M₅] [AddCommMonoid M₆]
variable [Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
variable [Module R M₅] [Module R M₆]
variable (f : M →ₗ[R] M₂)
section
variable (R M M₂)
/-- The first projection of a product is a linear map. -/
def fst : M × M₂ →ₗ[R] M where
toFun := Prod.fst
map_add' _x _y := rfl
map_smul' _x _y := rfl
#align linear_map.fst LinearMap.fst
/-- The second projection of a product is a linear map. -/
def snd : M × M₂ →ₗ[R] M₂ where
toFun := Prod.snd
map_add' _x _y := rfl
map_smul' _x _y := rfl
#align linear_map.snd LinearMap.snd
end
@[simp]
theorem fst_apply (x : M × M₂) : fst R M M₂ x = x.1 :=
rfl
#align linear_map.fst_apply LinearMap.fst_apply
@[simp]
theorem snd_apply (x : M × M₂) : snd R M M₂ x = x.2 :=
rfl
#align linear_map.snd_apply LinearMap.snd_apply
theorem fst_surjective : Function.Surjective (fst R M M₂) := fun x => ⟨(x, 0), rfl⟩
#align linear_map.fst_surjective LinearMap.fst_surjective
theorem snd_surjective : Function.Surjective (snd R M M₂) := fun x => ⟨(0, x), rfl⟩
#align linear_map.snd_surjective LinearMap.snd_surjective
/-- The prod of two linear maps is a linear map. -/
@[simps]
def prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : M →ₗ[R] M₂ × M₃ where
toFun := Pi.prod f g
map_add' x y := by simp only [Pi.prod, Prod.mk_add_mk, map_add]
map_smul' c x := by simp only [Pi.prod, Prod.smul_mk, map_smul, RingHom.id_apply]
#align linear_map.prod LinearMap.prod
theorem coe_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : ⇑(f.prod g) = Pi.prod f g :=
rfl
#align linear_map.coe_prod LinearMap.coe_prod
@[simp]
theorem fst_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : (fst R M₂ M₃).comp (prod f g) = f := rfl
#align linear_map.fst_prod LinearMap.fst_prod
@[simp]
theorem snd_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : (snd R M₂ M₃).comp (prod f g) = g := rfl
#align linear_map.snd_prod LinearMap.snd_prod
@[simp]
theorem pair_fst_snd : prod (fst R M M₂) (snd R M M₂) = LinearMap.id := rfl
#align linear_map.pair_fst_snd LinearMap.pair_fst_snd
theorem prod_comp (f : M₂ →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄)
(h : M →ₗ[R] M₂) : (f.prod g).comp h = (f.comp h).prod (g.comp h) :=
rfl
/-- Taking the product of two maps with the same domain is equivalent to taking the product of
their codomains.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used. -/
@[simps]
def prodEquiv [Module S M₂] [Module S M₃] [SMulCommClass R S M₂] [SMulCommClass R S M₃] :
((M →ₗ[R] M₂) × (M →ₗ[R] M₃)) ≃ₗ[S] M →ₗ[R] M₂ × M₃ where
toFun f := f.1.prod f.2
invFun f := ((fst _ _ _).comp f, (snd _ _ _).comp f)
left_inv f := by ext <;> rfl
right_inv f := by ext <;> rfl
map_add' a b := rfl
map_smul' r a := rfl
#align linear_map.prod_equiv LinearMap.prodEquiv
section
variable (R M M₂)
/-- The left injection into a product is a linear map. -/
def inl : M →ₗ[R] M × M₂ :=
prod LinearMap.id 0
#align linear_map.inl LinearMap.inl
/-- The right injection into a product is a linear map. -/
def inr : M₂ →ₗ[R] M × M₂ :=
prod 0 LinearMap.id
#align linear_map.inr LinearMap.inr
theorem range_inl : range (inl R M M₂) = ker (snd R M M₂) := by
ext x
simp only [mem_ker, mem_range]
constructor
· rintro ⟨y, rfl⟩
rfl
· intro h
exact ⟨x.fst, Prod.ext rfl h.symm⟩
#align linear_map.range_inl LinearMap.range_inl
theorem ker_snd : ker (snd R M M₂) = range (inl R M M₂) :=
Eq.symm <| range_inl R M M₂
#align linear_map.ker_snd LinearMap.ker_snd
theorem range_inr : range (inr R M M₂) = ker (fst R M M₂) := by
ext x
simp only [mem_ker, mem_range]
constructor
· rintro ⟨y, rfl⟩
rfl
· intro h
exact ⟨x.snd, Prod.ext h.symm rfl⟩
#align linear_map.range_inr LinearMap.range_inr
theorem ker_fst : ker (fst R M M₂) = range (inr R M M₂) :=
Eq.symm <| range_inr R M M₂
#align linear_map.ker_fst LinearMap.ker_fst
@[simp] theorem fst_comp_inl : fst R M M₂ ∘ₗ inl R M M₂ = id := rfl
@[simp] theorem snd_comp_inl : snd R M M₂ ∘ₗ inl R M M₂ = 0 := rfl
@[simp] theorem fst_comp_inr : fst R M M₂ ∘ₗ inr R M M₂ = 0 := rfl
@[simp] theorem snd_comp_inr : snd R M M₂ ∘ₗ inr R M M₂ = id := rfl
end
@[simp]
theorem coe_inl : (inl R M M₂ : M → M × M₂) = fun x => (x, 0) :=
rfl
#align linear_map.coe_inl LinearMap.coe_inl
theorem inl_apply (x : M) : inl R M M₂ x = (x, 0) :=
rfl
#align linear_map.inl_apply LinearMap.inl_apply
@[simp]
theorem coe_inr : (inr R M M₂ : M₂ → M × M₂) = Prod.mk 0 :=
rfl
#align linear_map.coe_inr LinearMap.coe_inr
theorem inr_apply (x : M₂) : inr R M M₂ x = (0, x) :=
rfl
#align linear_map.inr_apply LinearMap.inr_apply
theorem inl_eq_prod : inl R M M₂ = prod LinearMap.id 0 :=
rfl
#align linear_map.inl_eq_prod LinearMap.inl_eq_prod
theorem inr_eq_prod : inr R M M₂ = prod 0 LinearMap.id :=
rfl
#align linear_map.inr_eq_prod LinearMap.inr_eq_prod
theorem inl_injective : Function.Injective (inl R M M₂) := fun _ => by simp
#align linear_map.inl_injective LinearMap.inl_injective
theorem inr_injective : Function.Injective (inr R M M₂) := fun _ => by simp
#align linear_map.inr_injective LinearMap.inr_injective
/-- The coprod function `x : M × M₂ ↦ f x.1 + g x.2` is a linear map. -/
def coprod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : M × M₂ →ₗ[R] M₃ :=
f.comp (fst _ _ _) + g.comp (snd _ _ _)
#align linear_map.coprod LinearMap.coprod
@[simp]
theorem coprod_apply (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (x : M × M₂) :
coprod f g x = f x.1 + g x.2 :=
rfl
#align linear_map.coprod_apply LinearMap.coprod_apply
@[simp]
theorem coprod_inl (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : (coprod f g).comp (inl R M M₂) = f := by
ext; simp only [map_zero, add_zero, coprod_apply, inl_apply, comp_apply]
#align linear_map.coprod_inl LinearMap.coprod_inl
@[simp]
theorem coprod_inr (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : (coprod f g).comp (inr R M M₂) = g := by
ext; simp only [map_zero, coprod_apply, inr_apply, zero_add, comp_apply]
#align linear_map.coprod_inr LinearMap.coprod_inr
@[simp]
theorem coprod_inl_inr : coprod (inl R M M₂) (inr R M M₂) = LinearMap.id := by
ext <;>
simp only [Prod.mk_add_mk, add_zero, id_apply, coprod_apply, inl_apply, inr_apply, zero_add]
#align linear_map.coprod_inl_inr LinearMap.coprod_inl_inr
theorem coprod_zero_left (g : M₂ →ₗ[R] M₃) : (0 : M →ₗ[R] M₃).coprod g = g.comp (snd R M M₂) :=
zero_add _
theorem coprod_zero_right (f : M →ₗ[R] M₃) : f.coprod (0 : M₂ →ₗ[R] M₃) = f.comp (fst R M M₂) :=
add_zero _
theorem comp_coprod (f : M₃ →ₗ[R] M₄) (g₁ : M →ₗ[R] M₃) (g₂ : M₂ →ₗ[R] M₃) :
f.comp (g₁.coprod g₂) = (f.comp g₁).coprod (f.comp g₂) :=
ext fun x => f.map_add (g₁ x.1) (g₂ x.2)
#align linear_map.comp_coprod LinearMap.comp_coprod
theorem fst_eq_coprod : fst R M M₂ = coprod LinearMap.id 0 := by ext; simp
#align linear_map.fst_eq_coprod LinearMap.fst_eq_coprod
theorem snd_eq_coprod : snd R M M₂ = coprod 0 LinearMap.id := by ext; simp
#align linear_map.snd_eq_coprod LinearMap.snd_eq_coprod
@[simp]
theorem coprod_comp_prod (f : M₂ →ₗ[R] M₄) (g : M₃ →ₗ[R] M₄) (f' : M →ₗ[R] M₂) (g' : M →ₗ[R] M₃) :
(f.coprod g).comp (f'.prod g') = f.comp f' + g.comp g' :=
rfl
#align linear_map.coprod_comp_prod LinearMap.coprod_comp_prod
@[simp]
theorem coprod_map_prod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (S : Submodule R M)
(S' : Submodule R M₂) : (Submodule.prod S S').map (LinearMap.coprod f g) = S.map f ⊔ S'.map g :=
SetLike.coe_injective <| by
simp only [LinearMap.coprod_apply, Submodule.coe_sup, Submodule.map_coe]
rw [← Set.image2_add, Set.image2_image_left, Set.image2_image_right]
exact Set.image_prod fun m m₂ => f m + g m₂
#align linear_map.coprod_map_prod LinearMap.coprod_map_prod
/-- Taking the product of two maps with the same codomain is equivalent to taking the product of
their domains.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used. -/
@[simps]
def coprodEquiv [Module S M₃] [SMulCommClass R S M₃] :
((M →ₗ[R] M₃) × (M₂ →ₗ[R] M₃)) ≃ₗ[S] M × M₂ →ₗ[R] M₃ where
toFun f := f.1.coprod f.2
invFun f := (f.comp (inl _ _ _), f.comp (inr _ _ _))
left_inv f := by simp only [coprod_inl, coprod_inr]
right_inv f := by simp only [← comp_coprod, comp_id, coprod_inl_inr]
map_add' a b := by
ext
simp only [Prod.snd_add, add_apply, coprod_apply, Prod.fst_add, add_add_add_comm]
map_smul' r a := by
dsimp
ext
simp only [smul_add, smul_apply, Prod.smul_snd, Prod.smul_fst, coprod_apply]
#align linear_map.coprod_equiv LinearMap.coprodEquiv
theorem prod_ext_iff {f g : M × M₂ →ₗ[R] M₃} :
f = g ↔ f.comp (inl _ _ _) = g.comp (inl _ _ _) ∧ f.comp (inr _ _ _) = g.comp (inr _ _ _) :=
(coprodEquiv ℕ).symm.injective.eq_iff.symm.trans Prod.ext_iff
#align linear_map.prod_ext_iff LinearMap.prod_ext_iff
/--
Split equality of linear maps from a product into linear maps over each component, to allow `ext`
to apply lemmas specific to `M →ₗ M₃` and `M₂ →ₗ M₃`.
See note [partially-applied ext lemmas]. -/
@[ext 1100]
theorem prod_ext {f g : M × M₂ →ₗ[R] M₃} (hl : f.comp (inl _ _ _) = g.comp (inl _ _ _))
(hr : f.comp (inr _ _ _) = g.comp (inr _ _ _)) : f = g :=
prod_ext_iff.2 ⟨hl, hr⟩
#align linear_map.prod_ext LinearMap.prod_ext
/-- `prod.map` of two linear maps. -/
def prodMap (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) : M × M₂ →ₗ[R] M₃ × M₄ :=
(f.comp (fst R M M₂)).prod (g.comp (snd R M M₂))
#align linear_map.prod_map LinearMap.prodMap
theorem coe_prodMap (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) : ⇑(f.prodMap g) = Prod.map f g :=
rfl
#align linear_map.coe_prod_map LinearMap.coe_prodMap
@[simp]
theorem prodMap_apply (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) (x) : f.prodMap g x = (f x.1, g x.2) :=
rfl
#align linear_map.prod_map_apply LinearMap.prodMap_apply
theorem prodMap_comap_prod (f : M →ₗ[R] M₂) (g : M₃ →ₗ[R] M₄) (S : Submodule R M₂)
(S' : Submodule R M₄) :
(Submodule.prod S S').comap (LinearMap.prodMap f g) = (S.comap f).prod (S'.comap g) :=
SetLike.coe_injective <| Set.preimage_prod_map_prod f g _ _
#align linear_map.prod_map_comap_prod LinearMap.prodMap_comap_prod
theorem ker_prodMap (f : M →ₗ[R] M₂) (g : M₃ →ₗ[R] M₄) :
ker (LinearMap.prodMap f g) = Submodule.prod (ker f) (ker g) := by
dsimp only [ker]
rw [← prodMap_comap_prod, Submodule.prod_bot]
#align linear_map.ker_prod_map LinearMap.ker_prodMap
@[simp]
theorem prodMap_id : (id : M →ₗ[R] M).prodMap (id : M₂ →ₗ[R] M₂) = id :=
rfl
#align linear_map.prod_map_id LinearMap.prodMap_id
@[simp]
theorem prodMap_one : (1 : M →ₗ[R] M).prodMap (1 : M₂ →ₗ[R] M₂) = 1 :=
rfl
#align linear_map.prod_map_one LinearMap.prodMap_one
theorem prodMap_comp (f₁₂ : M →ₗ[R] M₂) (f₂₃ : M₂ →ₗ[R] M₃) (g₁₂ : M₄ →ₗ[R] M₅)
(g₂₃ : M₅ →ₗ[R] M₆) :
f₂₃.prodMap g₂₃ ∘ₗ f₁₂.prodMap g₁₂ = (f₂₃ ∘ₗ f₁₂).prodMap (g₂₃ ∘ₗ g₁₂) :=
rfl
#align linear_map.prod_map_comp LinearMap.prodMap_comp
theorem prodMap_mul (f₁₂ : M →ₗ[R] M) (f₂₃ : M →ₗ[R] M) (g₁₂ : M₂ →ₗ[R] M₂) (g₂₃ : M₂ →ₗ[R] M₂) :
f₂₃.prodMap g₂₃ * f₁₂.prodMap g₁₂ = (f₂₃ * f₁₂).prodMap (g₂₃ * g₁₂) :=
rfl
#align linear_map.prod_map_mul LinearMap.prodMap_mul
theorem prodMap_add (f₁ : M →ₗ[R] M₃) (f₂ : M →ₗ[R] M₃) (g₁ : M₂ →ₗ[R] M₄) (g₂ : M₂ →ₗ[R] M₄) :
(f₁ + f₂).prodMap (g₁ + g₂) = f₁.prodMap g₁ + f₂.prodMap g₂ :=
rfl
#align linear_map.prod_map_add LinearMap.prodMap_add
@[simp]
theorem prodMap_zero : (0 : M →ₗ[R] M₂).prodMap (0 : M₃ →ₗ[R] M₄) = 0 :=
rfl
#align linear_map.prod_map_zero LinearMap.prodMap_zero
@[simp]
theorem prodMap_smul [Module S M₃] [Module S M₄] [SMulCommClass R S M₃] [SMulCommClass R S M₄]
(s : S) (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) : prodMap (s • f) (s • g) = s • prodMap f g :=
rfl
#align linear_map.prod_map_smul LinearMap.prodMap_smul
variable (R M M₂ M₃ M₄)
/-- `LinearMap.prodMap` as a `LinearMap` -/
@[simps]
def prodMapLinear [Module S M₃] [Module S M₄] [SMulCommClass R S M₃] [SMulCommClass R S M₄] :
(M →ₗ[R] M₃) × (M₂ →ₗ[R] M₄) →ₗ[S] M × M₂ →ₗ[R] M₃ × M₄ where
toFun f := prodMap f.1 f.2
map_add' _ _ := rfl
map_smul' _ _ := rfl
#align linear_map.prod_map_linear LinearMap.prodMapLinear
/-- `LinearMap.prodMap` as a `RingHom` -/
@[simps]
def prodMapRingHom : (M →ₗ[R] M) × (M₂ →ₗ[R] M₂) →+* M × M₂ →ₗ[R] M × M₂ where
toFun f := prodMap f.1 f.2
map_one' := prodMap_one
map_zero' := rfl
map_add' _ _ := rfl
map_mul' _ _ := rfl
#align linear_map.prod_map_ring_hom LinearMap.prodMapRingHom
variable {R M M₂ M₃ M₄}
section map_mul
variable {A : Type*} [NonUnitalNonAssocSemiring A] [Module R A]
variable {B : Type*} [NonUnitalNonAssocSemiring B] [Module R B]
theorem inl_map_mul (a₁ a₂ : A) :
LinearMap.inl R A B (a₁ * a₂) = LinearMap.inl R A B a₁ * LinearMap.inl R A B a₂ :=
Prod.ext rfl (by simp)
#align linear_map.inl_map_mul LinearMap.inl_map_mul
theorem inr_map_mul (b₁ b₂ : B) :
LinearMap.inr R A B (b₁ * b₂) = LinearMap.inr R A B b₁ * LinearMap.inr R A B b₂ :=
Prod.ext (by simp) rfl
#align linear_map.inr_map_mul LinearMap.inr_map_mul
end map_mul
end LinearMap
end Prod
namespace LinearMap
variable (R M M₂)
variable [CommSemiring R]
variable [AddCommMonoid M] [AddCommMonoid M₂]
variable [Module R M] [Module R M₂]
/-- `LinearMap.prodMap` as an `AlgHom` -/
@[simps!]
def prodMapAlgHom : Module.End R M × Module.End R M₂ →ₐ[R] Module.End R (M × M₂) :=
{ prodMapRingHom R M M₂ with commutes' := fun _ => rfl }
#align linear_map.prod_map_alg_hom LinearMap.prodMapAlgHom
end LinearMap
namespace LinearMap
open Submodule
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃] [AddCommMonoid M₄]
[Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
theorem range_coprod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : range (f.coprod g) = range f ⊔ range g :=
Submodule.ext fun x => by simp [mem_sup]
#align linear_map.range_coprod LinearMap.range_coprod
theorem isCompl_range_inl_inr : IsCompl (range <| inl R M M₂) (range <| inr R M M₂) := by
constructor
· rw [disjoint_def]
rintro ⟨_, _⟩ ⟨x, hx⟩ ⟨y, hy⟩
simp only [Prod.ext_iff, inl_apply, inr_apply, mem_bot] at hx hy ⊢
exact ⟨hy.1.symm, hx.2.symm⟩
· rw [codisjoint_iff_le_sup]
rintro ⟨x, y⟩ -
simp only [mem_sup, mem_range, exists_prop]
refine ⟨(x, 0), ⟨x, rfl⟩, (0, y), ⟨y, rfl⟩, ?_⟩
simp
#align linear_map.is_compl_range_inl_inr LinearMap.isCompl_range_inl_inr
theorem sup_range_inl_inr : (range <| inl R M M₂) ⊔ (range <| inr R M M₂) = ⊤ :=
IsCompl.sup_eq_top isCompl_range_inl_inr
#align linear_map.sup_range_inl_inr LinearMap.sup_range_inl_inr
theorem disjoint_inl_inr : Disjoint (range <| inl R M M₂) (range <| inr R M M₂) := by
simp (config := { contextual := true }) [disjoint_def, @eq_comm M 0, @eq_comm M₂ 0]
#align linear_map.disjoint_inl_inr LinearMap.disjoint_inl_inr
theorem map_coprod_prod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (p : Submodule R M)
(q : Submodule R M₂) : map (coprod f g) (p.prod q) = map f p ⊔ map g q := by
refine le_antisymm ?_ (sup_le (map_le_iff_le_comap.2 ?_) (map_le_iff_le_comap.2 ?_))
· rw [SetLike.le_def]
rintro _ ⟨x, ⟨h₁, h₂⟩, rfl⟩
exact mem_sup.2 ⟨_, ⟨_, h₁, rfl⟩, _, ⟨_, h₂, rfl⟩, rfl⟩
· exact fun x hx => ⟨(x, 0), by simp [hx]⟩
· exact fun x hx => ⟨(0, x), by simp [hx]⟩
#align linear_map.map_coprod_prod LinearMap.map_coprod_prod
theorem comap_prod_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) (p : Submodule R M₂)
(q : Submodule R M₃) : comap (prod f g) (p.prod q) = comap f p ⊓ comap g q :=
Submodule.ext fun _x => Iff.rfl
#align linear_map.comap_prod_prod LinearMap.comap_prod_prod
theorem prod_eq_inf_comap (p : Submodule R M) (q : Submodule R M₂) :
p.prod q = p.comap (LinearMap.fst R M M₂) ⊓ q.comap (LinearMap.snd R M M₂) :=
Submodule.ext fun _x => Iff.rfl
#align linear_map.prod_eq_inf_comap LinearMap.prod_eq_inf_comap
theorem prod_eq_sup_map (p : Submodule R M) (q : Submodule R M₂) :
p.prod q = p.map (LinearMap.inl R M M₂) ⊔ q.map (LinearMap.inr R M M₂) := by
rw [← map_coprod_prod, coprod_inl_inr, map_id]
#align linear_map.prod_eq_sup_map LinearMap.prod_eq_sup_map
theorem span_inl_union_inr {s : Set M} {t : Set M₂} :
span R (inl R M M₂ '' s ∪ inr R M M₂ '' t) = (span R s).prod (span R t) := by
rw [span_union, prod_eq_sup_map, ← span_image, ← span_image]
#align linear_map.span_inl_union_inr LinearMap.span_inl_union_inr
@[simp]
theorem ker_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : ker (prod f g) = ker f ⊓ ker g := by
rw [ker, ← prod_bot, comap_prod_prod]; rfl
#align linear_map.ker_prod LinearMap.ker_prod
theorem range_prod_le (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) :
range (prod f g) ≤ (range f).prod (range g) := by
simp only [SetLike.le_def, prod_apply, mem_range, SetLike.mem_coe, mem_prod, exists_imp]
rintro _ x rfl
exact ⟨⟨x, rfl⟩, ⟨x, rfl⟩⟩
#align linear_map.range_prod_le LinearMap.range_prod_le
theorem ker_prod_ker_le_ker_coprod {M₂ : Type*} [AddCommGroup M₂] [Module R M₂] {M₃ : Type*}
[AddCommGroup M₃] [Module R M₃] (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) :
(ker f).prod (ker g) ≤ ker (f.coprod g) := by
rintro ⟨y, z⟩
simp (config := { contextual := true })
#align linear_map.ker_prod_ker_le_ker_coprod LinearMap.ker_prod_ker_le_ker_coprod
theorem ker_coprod_of_disjoint_range {M₂ : Type*} [AddCommGroup M₂] [Module R M₂] {M₃ : Type*}
[AddCommGroup M₃] [Module R M₃] (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃)
(hd : Disjoint (range f) (range g)) : ker (f.coprod g) = (ker f).prod (ker g) := by
apply le_antisymm _ (ker_prod_ker_le_ker_coprod f g)
rintro ⟨y, z⟩ h
simp only [mem_ker, mem_prod, coprod_apply] at h ⊢
have : f y ∈ (range f) ⊓ (range g) := by
simp only [true_and_iff, mem_range, mem_inf, exists_apply_eq_apply]
use -z
rwa [eq_comm, map_neg, ← sub_eq_zero, sub_neg_eq_add]
rw [hd.eq_bot, mem_bot] at this
rw [this] at h
simpa [this] using h
#align linear_map.ker_coprod_of_disjoint_range LinearMap.ker_coprod_of_disjoint_range
end LinearMap
namespace Submodule
open LinearMap
variable [Semiring R]
variable [AddCommMonoid M] [AddCommMonoid M₂]
variable [Module R M] [Module R M₂]
theorem sup_eq_range (p q : Submodule R M) : p ⊔ q = range (p.subtype.coprod q.subtype) :=
Submodule.ext fun x => by simp [Submodule.mem_sup, SetLike.exists]
#align submodule.sup_eq_range Submodule.sup_eq_range
variable (p : Submodule R M) (q : Submodule R M₂)
@[simp]
theorem map_inl : p.map (inl R M M₂) = prod p ⊥ := by
ext ⟨x, y⟩
simp only [and_left_comm, eq_comm, mem_map, Prod.mk.inj_iff, inl_apply, mem_bot, exists_eq_left',
mem_prod]
#align submodule.map_inl Submodule.map_inl
@[simp]
| Mathlib/LinearAlgebra/Prod.lean | 555 | 556 | theorem map_inr : q.map (inr R M M₂) = prod ⊥ q := by |
ext ⟨x, y⟩; simp [and_left_comm, eq_comm, and_comm]
|
/-
Copyright (c) 2022 Vincent Beffara. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Vincent Beffara
-/
import Mathlib.Analysis.Complex.RemovableSingularity
import Mathlib.Analysis.Calculus.UniformLimitsDeriv
import Mathlib.Analysis.NormedSpace.FunctionSeries
#align_import analysis.complex.locally_uniform_limit from "leanprover-community/mathlib"@"fe44cd36149e675eb5dec87acc7e8f1d6568e081"
/-!
# Locally uniform limits of holomorphic functions
This file gathers some results about locally uniform limits of holomorphic functions on an open
subset of the complex plane.
## Main results
* `TendstoLocallyUniformlyOn.differentiableOn`: A locally uniform limit of holomorphic functions
is holomorphic.
* `TendstoLocallyUniformlyOn.deriv`: Locally uniform convergence implies locally uniform
convergence of the derivatives to the derivative of the limit.
-/
open Set Metric MeasureTheory Filter Complex intervalIntegral
open scoped Real Topology
variable {E ι : Type*} [NormedAddCommGroup E] [NormedSpace ℂ E] [CompleteSpace E] {U K : Set ℂ}
{z : ℂ} {M r δ : ℝ} {φ : Filter ι} {F : ι → ℂ → E} {f g : ℂ → E}
namespace Complex
section Cderiv
/-- A circle integral which coincides with `deriv f z` whenever one can apply the Cauchy formula for
the derivative. It is useful in the proof that locally uniform limits of holomorphic functions are
holomorphic, because it depends continuously on `f` for the uniform topology. -/
noncomputable def cderiv (r : ℝ) (f : ℂ → E) (z : ℂ) : E :=
(2 * π * I : ℂ)⁻¹ • ∮ w in C(z, r), ((w - z) ^ 2)⁻¹ • f w
#align complex.cderiv Complex.cderiv
theorem cderiv_eq_deriv (hU : IsOpen U) (hf : DifferentiableOn ℂ f U) (hr : 0 < r)
(hzr : closedBall z r ⊆ U) : cderiv r f z = deriv f z :=
two_pi_I_inv_smul_circleIntegral_sub_sq_inv_smul_of_differentiable hU hzr hf (mem_ball_self hr)
#align complex.cderiv_eq_deriv Complex.cderiv_eq_deriv
theorem norm_cderiv_le (hr : 0 < r) (hf : ∀ w ∈ sphere z r, ‖f w‖ ≤ M) :
‖cderiv r f z‖ ≤ M / r := by
have hM : 0 ≤ M := by
obtain ⟨w, hw⟩ : (sphere z r).Nonempty := NormedSpace.sphere_nonempty.mpr hr.le
exact (norm_nonneg _).trans (hf w hw)
have h1 : ∀ w ∈ sphere z r, ‖((w - z) ^ 2)⁻¹ • f w‖ ≤ M / r ^ 2 := by
intro w hw
simp only [mem_sphere_iff_norm, norm_eq_abs] at hw
simp only [norm_smul, inv_mul_eq_div, hw, norm_eq_abs, map_inv₀, Complex.abs_pow]
exact div_le_div hM (hf w hw) (sq_pos_of_pos hr) le_rfl
have h2 := circleIntegral.norm_integral_le_of_norm_le_const hr.le h1
simp only [cderiv, norm_smul]
refine (mul_le_mul le_rfl h2 (norm_nonneg _) (norm_nonneg _)).trans (le_of_eq ?_)
field_simp [_root_.abs_of_nonneg Real.pi_pos.le]
ring
#align complex.norm_cderiv_le Complex.norm_cderiv_le
theorem cderiv_sub (hr : 0 < r) (hf : ContinuousOn f (sphere z r))
(hg : ContinuousOn g (sphere z r)) : cderiv r (f - g) z = cderiv r f z - cderiv r g z := by
have h1 : ContinuousOn (fun w : ℂ => ((w - z) ^ 2)⁻¹) (sphere z r) := by
refine ((continuous_id'.sub continuous_const).pow 2).continuousOn.inv₀ fun w hw h => hr.ne ?_
rwa [mem_sphere_iff_norm, sq_eq_zero_iff.mp h, norm_zero] at hw
simp_rw [cderiv, ← smul_sub]
congr 1
simpa only [Pi.sub_apply, smul_sub] using
circleIntegral.integral_sub ((h1.smul hf).circleIntegrable hr.le)
((h1.smul hg).circleIntegrable hr.le)
#align complex.cderiv_sub Complex.cderiv_sub
theorem norm_cderiv_lt (hr : 0 < r) (hfM : ∀ w ∈ sphere z r, ‖f w‖ < M)
(hf : ContinuousOn f (sphere z r)) : ‖cderiv r f z‖ < M / r := by
obtain ⟨L, hL1, hL2⟩ : ∃ L < M, ∀ w ∈ sphere z r, ‖f w‖ ≤ L := by
have e1 : (sphere z r).Nonempty := NormedSpace.sphere_nonempty.mpr hr.le
have e2 : ContinuousOn (fun w => ‖f w‖) (sphere z r) := continuous_norm.comp_continuousOn hf
obtain ⟨x, hx, hx'⟩ := (isCompact_sphere z r).exists_isMaxOn e1 e2
exact ⟨‖f x‖, hfM x hx, hx'⟩
exact (norm_cderiv_le hr hL2).trans_lt ((div_lt_div_right hr).mpr hL1)
#align complex.norm_cderiv_lt Complex.norm_cderiv_lt
theorem norm_cderiv_sub_lt (hr : 0 < r) (hfg : ∀ w ∈ sphere z r, ‖f w - g w‖ < M)
(hf : ContinuousOn f (sphere z r)) (hg : ContinuousOn g (sphere z r)) :
‖cderiv r f z - cderiv r g z‖ < M / r :=
cderiv_sub hr hf hg ▸ norm_cderiv_lt hr hfg (hf.sub hg)
#align complex.norm_cderiv_sub_lt Complex.norm_cderiv_sub_lt
theorem _root_.TendstoUniformlyOn.cderiv (hF : TendstoUniformlyOn F f φ (cthickening δ K))
(hδ : 0 < δ) (hFn : ∀ᶠ n in φ, ContinuousOn (F n) (cthickening δ K)) :
TendstoUniformlyOn (cderiv δ ∘ F) (cderiv δ f) φ K := by
rcases φ.eq_or_neBot with rfl | hne
· simp only [TendstoUniformlyOn, eventually_bot, imp_true_iff]
have e1 : ContinuousOn f (cthickening δ K) := TendstoUniformlyOn.continuousOn hF hFn
rw [tendstoUniformlyOn_iff] at hF ⊢
rintro ε hε
filter_upwards [hF (ε * δ) (mul_pos hε hδ), hFn] with n h h' z hz
simp_rw [dist_eq_norm] at h ⊢
have e2 : ∀ w ∈ sphere z δ, ‖f w - F n w‖ < ε * δ := fun w hw1 =>
h w (closedBall_subset_cthickening hz δ (sphere_subset_closedBall hw1))
have e3 := sphere_subset_closedBall.trans (closedBall_subset_cthickening hz δ)
have hf : ContinuousOn f (sphere z δ) :=
e1.mono (sphere_subset_closedBall.trans (closedBall_subset_cthickening hz δ))
simpa only [mul_div_cancel_right₀ _ hδ.ne.symm] using norm_cderiv_sub_lt hδ e2 hf (h'.mono e3)
#align tendsto_uniformly_on.cderiv TendstoUniformlyOn.cderiv
end Cderiv
section Weierstrass
theorem tendstoUniformlyOn_deriv_of_cthickening_subset (hf : TendstoLocallyUniformlyOn F f φ U)
(hF : ∀ᶠ n in φ, DifferentiableOn ℂ (F n) U) {δ : ℝ} (hδ : 0 < δ) (hK : IsCompact K)
(hU : IsOpen U) (hKU : cthickening δ K ⊆ U) :
TendstoUniformlyOn (deriv ∘ F) (cderiv δ f) φ K := by
have h1 : ∀ᶠ n in φ, ContinuousOn (F n) (cthickening δ K) := by
filter_upwards [hF] with n h using h.continuousOn.mono hKU
have h2 : IsCompact (cthickening δ K) := hK.cthickening
have h3 : TendstoUniformlyOn F f φ (cthickening δ K) :=
(tendstoLocallyUniformlyOn_iff_forall_isCompact hU).mp hf (cthickening δ K) hKU h2
apply (h3.cderiv hδ h1).congr
filter_upwards [hF] with n h z hz
exact cderiv_eq_deriv hU h hδ ((closedBall_subset_cthickening hz δ).trans hKU)
#align complex.tendsto_uniformly_on_deriv_of_cthickening_subset Complex.tendstoUniformlyOn_deriv_of_cthickening_subset
theorem exists_cthickening_tendstoUniformlyOn (hf : TendstoLocallyUniformlyOn F f φ U)
(hF : ∀ᶠ n in φ, DifferentiableOn ℂ (F n) U) (hK : IsCompact K) (hU : IsOpen U) (hKU : K ⊆ U) :
∃ δ > 0, cthickening δ K ⊆ U ∧ TendstoUniformlyOn (deriv ∘ F) (cderiv δ f) φ K := by
obtain ⟨δ, hδ, hKδ⟩ := hK.exists_cthickening_subset_open hU hKU
exact ⟨δ, hδ, hKδ, tendstoUniformlyOn_deriv_of_cthickening_subset hf hF hδ hK hU hKδ⟩
#align complex.exists_cthickening_tendsto_uniformly_on Complex.exists_cthickening_tendstoUniformlyOn
/-- A locally uniform limit of holomorphic functions on an open domain of the complex plane is
holomorphic (the derivatives converge locally uniformly to that of the limit, which is proved
as `TendstoLocallyUniformlyOn.deriv`). -/
theorem _root_.TendstoLocallyUniformlyOn.differentiableOn [φ.NeBot]
(hf : TendstoLocallyUniformlyOn F f φ U) (hF : ∀ᶠ n in φ, DifferentiableOn ℂ (F n) U)
(hU : IsOpen U) : DifferentiableOn ℂ f U := by
rintro x hx
obtain ⟨K, ⟨hKx, hK⟩, hKU⟩ := (compact_basis_nhds x).mem_iff.mp (hU.mem_nhds hx)
obtain ⟨δ, _, _, h1⟩ := exists_cthickening_tendstoUniformlyOn hf hF hK hU hKU
have h2 : interior K ⊆ U := interior_subset.trans hKU
have h3 : ∀ᶠ n in φ, DifferentiableOn ℂ (F n) (interior K) := by
filter_upwards [hF] with n h using h.mono h2
have h4 : TendstoLocallyUniformlyOn F f φ (interior K) := hf.mono h2
have h5 : TendstoLocallyUniformlyOn (deriv ∘ F) (cderiv δ f) φ (interior K) :=
h1.tendstoLocallyUniformlyOn.mono interior_subset
have h6 : ∀ x ∈ interior K, HasDerivAt f (cderiv δ f x) x := fun x h =>
hasDerivAt_of_tendsto_locally_uniformly_on' isOpen_interior h5 h3 (fun _ => h4.tendsto_at) h
have h7 : DifferentiableOn ℂ f (interior K) := fun x hx =>
(h6 x hx).differentiableAt.differentiableWithinAt
exact (h7.differentiableAt (interior_mem_nhds.mpr hKx)).differentiableWithinAt
#align tendsto_locally_uniformly_on.differentiable_on TendstoLocallyUniformlyOn.differentiableOn
theorem _root_.TendstoLocallyUniformlyOn.deriv (hf : TendstoLocallyUniformlyOn F f φ U)
(hF : ∀ᶠ n in φ, DifferentiableOn ℂ (F n) U) (hU : IsOpen U) :
TendstoLocallyUniformlyOn (deriv ∘ F) (deriv f) φ U := by
rw [tendstoLocallyUniformlyOn_iff_forall_isCompact hU]
rcases φ.eq_or_neBot with rfl | hne
· simp only [TendstoUniformlyOn, eventually_bot, imp_true_iff]
rintro K hKU hK
obtain ⟨δ, hδ, hK4, h⟩ := exists_cthickening_tendstoUniformlyOn hf hF hK hU hKU
refine h.congr_right fun z hz => cderiv_eq_deriv hU (hf.differentiableOn hF hU) hδ ?_
exact (closedBall_subset_cthickening hz δ).trans hK4
#align tendsto_locally_uniformly_on.deriv TendstoLocallyUniformlyOn.deriv
end Weierstrass
section Tsums
/-- If the terms in the sum `∑' (i : ι), F i` are uniformly bounded on `U` by a
summable function, and each term in the sum is differentiable on `U`, then so is the sum. -/
| Mathlib/Analysis/Complex/LocallyUniformLimit.lean | 178 | 185 | theorem differentiableOn_tsum_of_summable_norm {u : ι → ℝ} (hu : Summable u)
(hf : ∀ i : ι, DifferentiableOn ℂ (F i) U) (hU : IsOpen U)
(hF_le : ∀ (i : ι) (w : ℂ), w ∈ U → ‖F i w‖ ≤ u i) :
DifferentiableOn ℂ (fun w : ℂ => ∑' i : ι, F i w) U := by |
classical
have hc := (tendstoUniformlyOn_tsum hu hF_le).tendstoLocallyUniformlyOn
refine hc.differentiableOn (eventually_of_forall fun s => ?_) hU
exact DifferentiableOn.sum fun i _ => hf i
|
/-
Copyright (c) 2023 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.MeasureTheory.Constructions.Pi
import Mathlib.Probability.Kernel.Basic
/-!
# Independence with respect to a kernel and a measure
A family of sets of sets `π : ι → Set (Set Ω)` is independent with respect to a kernel
`κ : kernel α Ω` and a measure `μ` on `α` if for any finite set of indices `s = {i_1, ..., i_n}`,
for any sets `f i_1 ∈ π i_1, ..., f i_n ∈ π i_n`, then for `μ`-almost every `a : α`,
`κ a (⋂ i in s, f i) = ∏ i ∈ s, κ a (f i)`.
This notion of independence is a generalization of both independence and conditional independence.
For conditional independence, `κ` is the conditional kernel `ProbabilityTheory.condexpKernel` and
`μ` is the ambiant measure. For (non-conditional) independence, `κ = kernel.const Unit μ` and the
measure is the Dirac measure on `Unit`.
The main purpose of this file is to prove only once the properties that hold for both conditional
and non-conditional independence.
## Main definitions
* `ProbabilityTheory.kernel.iIndepSets`: independence of a family of sets of sets.
Variant for two sets of sets: `ProbabilityTheory.kernel.IndepSets`.
* `ProbabilityTheory.kernel.iIndep`: independence of a family of σ-algebras. Variant for two
σ-algebras: `Indep`.
* `ProbabilityTheory.kernel.iIndepSet`: independence of a family of sets. Variant for two sets:
`ProbabilityTheory.kernel.IndepSet`.
* `ProbabilityTheory.kernel.iIndepFun`: independence of a family of functions (random variables).
Variant for two functions: `ProbabilityTheory.kernel.IndepFun`.
See the file `Mathlib/Probability/Kernel/Basic.lean` for a more detailed discussion of these
definitions in the particular case of the usual independence notion.
## Main statements
* `ProbabilityTheory.kernel.iIndepSets.iIndep`: if π-systems are independent as sets of sets,
then the measurable space structures they generate are independent.
* `ProbabilityTheory.kernel.IndepSets.Indep`: variant with two π-systems.
-/
open MeasureTheory MeasurableSpace
open scoped MeasureTheory ENNReal
namespace ProbabilityTheory.kernel
variable {α Ω ι : Type*}
section Definitions
variable {_mα : MeasurableSpace α}
/-- A family of sets of sets `π : ι → Set (Set Ω)` is independent with respect to a kernel `κ` and
a measure `μ` if for any finite set of indices `s = {i_1, ..., i_n}`, for any sets
`f i_1 ∈ π i_1, ..., f i_n ∈ π i_n`, then `∀ᵐ a ∂μ, κ a (⋂ i in s, f i) = ∏ i ∈ s, κ a (f i)`.
It will be used for families of pi_systems. -/
def iIndepSets {_mΩ : MeasurableSpace Ω}
(π : ι → Set (Set Ω)) (κ : kernel α Ω) (μ : Measure α := by volume_tac) : Prop :=
∀ (s : Finset ι) {f : ι → Set Ω} (_H : ∀ i, i ∈ s → f i ∈ π i),
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i)
/-- Two sets of sets `s₁, s₂` are independent with respect to a kernel `κ` and a measure `μ` if for
any sets `t₁ ∈ s₁, t₂ ∈ s₂`, then `∀ᵐ a ∂μ, κ a (t₁ ∩ t₂) = κ a (t₁) * κ a (t₂)` -/
def IndepSets {_mΩ : MeasurableSpace Ω}
(s1 s2 : Set (Set Ω)) (κ : kernel α Ω) (μ : Measure α := by volume_tac) : Prop :=
∀ t1 t2 : Set Ω, t1 ∈ s1 → t2 ∈ s2 → (∀ᵐ a ∂μ, κ a (t1 ∩ t2) = κ a t1 * κ a t2)
/-- A family of measurable space structures (i.e. of σ-algebras) is independent with respect to a
kernel `κ` and a measure `μ` if the family of sets of measurable sets they define is independent. -/
def iIndep (m : ι → MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω} (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndepSets (fun x ↦ {s | MeasurableSet[m x] s}) κ μ
/-- Two measurable space structures (or σ-algebras) `m₁, m₂` are independent with respect to a
kernel `κ` and a measure `μ` if for any sets `t₁ ∈ m₁, t₂ ∈ m₂`,
`∀ᵐ a ∂μ, κ a (t₁ ∩ t₂) = κ a (t₁) * κ a (t₂)` -/
def Indep (m₁ m₂ : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω} (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
IndepSets {s | MeasurableSet[m₁] s} {s | MeasurableSet[m₂] s} κ μ
/-- A family of sets is independent if the family of measurable space structures they generate is
independent. For a set `s`, the generated measurable space has measurable sets `∅, s, sᶜ, univ`. -/
def iIndepSet {_mΩ : MeasurableSpace Ω} (s : ι → Set Ω) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndep (fun i ↦ generateFrom {s i}) κ μ
/-- Two sets are independent if the two measurable space structures they generate are independent.
For a set `s`, the generated measurable space structure has measurable sets `∅, s, sᶜ, univ`. -/
def IndepSet {_mΩ : MeasurableSpace Ω} (s t : Set Ω) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
Indep (generateFrom {s}) (generateFrom {t}) κ μ
/-- A family of functions defined on the same space `Ω` and taking values in possibly different
spaces, each with a measurable space structure, is independent if the family of measurable space
structures they generate on `Ω` is independent. For a function `g` with codomain having measurable
space structure `m`, the generated measurable space structure is `MeasurableSpace.comap g m`. -/
def iIndepFun {_mΩ : MeasurableSpace Ω} {β : ι → Type*} (m : ∀ x : ι, MeasurableSpace (β x))
(f : ∀ x : ι, Ω → β x) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndep (fun x ↦ MeasurableSpace.comap (f x) (m x)) κ μ
/-- Two functions are independent if the two measurable space structures they generate are
independent. For a function `f` with codomain having measurable space structure `m`, the generated
measurable space structure is `MeasurableSpace.comap f m`. -/
def IndepFun {β γ} {_mΩ : MeasurableSpace Ω} [mβ : MeasurableSpace β] [mγ : MeasurableSpace γ]
(f : Ω → β) (g : Ω → γ) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
Indep (MeasurableSpace.comap f mβ) (MeasurableSpace.comap g mγ) κ μ
end Definitions
section ByDefinition
variable {β : ι → Type*} {mβ : ∀ i, MeasurableSpace (β i)}
{_mα : MeasurableSpace α} {m : ι → MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
{π : ι → Set (Set Ω)} {s : ι → Set Ω} {S : Finset ι} {f : ∀ x : ι, Ω → β x}
lemma iIndepSets.meas_biInter (h : iIndepSets π κ μ) (s : Finset ι)
{f : ι → Set Ω} (hf : ∀ i, i ∈ s → f i ∈ π i) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i) := h s hf
lemma iIndepSets.meas_iInter [Fintype ι] (h : iIndepSets π κ μ) (hs : ∀ i, s i ∈ π i) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := by
filter_upwards [h.meas_biInter Finset.univ (fun _i _ ↦ hs _)] with a ha using by simp [← ha]
lemma iIndep.iIndepSets' (hμ : iIndep m κ μ) :
iIndepSets (fun x ↦ {s | MeasurableSet[m x] s}) κ μ := hμ
lemma iIndep.meas_biInter (hμ : iIndep m κ μ) (hs : ∀ i, i ∈ S → MeasurableSet[m i] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := hμ _ hs
lemma iIndep.meas_iInter [Fintype ι] (h : iIndep m κ μ) (hs : ∀ i, MeasurableSet[m i] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := by
filter_upwards [h.meas_biInter (fun i (_ : i ∈ Finset.univ) ↦ hs _)] with a ha
simp [← ha]
protected lemma iIndepFun.iIndep (hf : iIndepFun mβ f κ μ) :
iIndep (fun x ↦ (mβ x).comap (f x)) κ μ := hf
lemma iIndepFun.meas_biInter (hf : iIndepFun mβ f κ μ)
(hs : ∀ i, i ∈ S → MeasurableSet[(mβ i).comap (f i)] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := hf.iIndep.meas_biInter hs
lemma iIndepFun.meas_iInter [Fintype ι] (hf : iIndepFun mβ f κ μ)
(hs : ∀ i, MeasurableSet[(mβ i).comap (f i)] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := hf.iIndep.meas_iInter hs
lemma IndepFun.meas_inter {β γ : Type*} [mβ : MeasurableSpace β] [mγ : MeasurableSpace γ]
{f : Ω → β} {g : Ω → γ} (hfg : IndepFun f g κ μ)
{s t : Set Ω} (hs : MeasurableSet[mβ.comap f] s) (ht : MeasurableSet[mγ.comap g] t) :
∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t := hfg _ _ hs ht
end ByDefinition
section Indep
variable {_mα : MeasurableSpace α}
@[symm]
theorem IndepSets.symm {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
{s₁ s₂ : Set (Set Ω)} (h : IndepSets s₁ s₂ κ μ) :
IndepSets s₂ s₁ κ μ := by
intros t1 t2 ht1 ht2
filter_upwards [h t2 t1 ht2 ht1] with a ha
rwa [Set.inter_comm, mul_comm]
@[symm]
theorem Indep.symm {m₁ m₂ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α} (h : Indep m₁ m₂ κ μ) :
Indep m₂ m₁ κ μ :=
IndepSets.symm h
theorem indep_bot_right (m' : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] :
Indep m' ⊥ κ μ := by
intros s t _ ht
rw [Set.mem_setOf_eq, MeasurableSpace.measurableSet_bot_iff] at ht
refine Filter.eventually_of_forall (fun a ↦ ?_)
cases' ht with ht ht
· rw [ht, Set.inter_empty, measure_empty, mul_zero]
· rw [ht, Set.inter_univ, measure_univ, mul_one]
theorem indep_bot_left (m' : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] :
Indep ⊥ m' κ μ := (indep_bot_right m').symm
theorem indepSet_empty_right {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] (s : Set Ω) :
IndepSet s ∅ κ μ := by
simp only [IndepSet, generateFrom_singleton_empty];
exact indep_bot_right _
theorem indepSet_empty_left {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α} [IsMarkovKernel κ] (s : Set Ω) :
IndepSet ∅ s κ μ :=
(indepSet_empty_right s).symm
theorem indepSets_of_indepSets_of_le_left {s₁ s₂ s₃ : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : IndepSets s₁ s₂ κ μ) (h31 : s₃ ⊆ s₁) :
IndepSets s₃ s₂ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 (Set.mem_of_subset_of_mem h31 ht1) ht2
theorem indepSets_of_indepSets_of_le_right {s₁ s₂ s₃ : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : IndepSets s₁ s₂ κ μ) (h32 : s₃ ⊆ s₂) :
IndepSets s₁ s₃ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 ht1 (Set.mem_of_subset_of_mem h32 ht2)
theorem indep_of_indep_of_le_left {m₁ m₂ m₃ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : Indep m₁ m₂ κ μ) (h31 : m₃ ≤ m₁) :
Indep m₃ m₂ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 (h31 _ ht1) ht2
theorem indep_of_indep_of_le_right {m₁ m₂ m₃ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : Indep m₁ m₂ κ μ) (h32 : m₃ ≤ m₂) :
Indep m₁ m₃ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 ht1 (h32 _ ht2)
theorem IndepSets.union {s₁ s₂ s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
(h₁ : IndepSets s₁ s' κ μ) (h₂ : IndepSets s₂ s' κ μ) :
IndepSets (s₁ ∪ s₂) s' κ μ := by
intro t1 t2 ht1 ht2
cases' (Set.mem_union _ _ _).mp ht1 with ht1₁ ht1₂
· exact h₁ t1 t2 ht1₁ ht2
· exact h₂ t1 t2 ht1₂ ht2
@[simp]
theorem IndepSets.union_iff {s₁ s₂ s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
IndepSets (s₁ ∪ s₂) s' κ μ ↔ IndepSets s₁ s' κ μ ∧ IndepSets s₂ s' κ μ :=
⟨fun h =>
⟨indepSets_of_indepSets_of_le_left h Set.subset_union_left,
indepSets_of_indepSets_of_le_left h Set.subset_union_right⟩,
fun h => IndepSets.union h.left h.right⟩
theorem IndepSets.iUnion {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (hyp : ∀ n, IndepSets (s n) s' κ μ) :
IndepSets (⋃ n, s n) s' κ μ := by
intro t1 t2 ht1 ht2
rw [Set.mem_iUnion] at ht1
cases' ht1 with n ht1
exact hyp n t1 t2 ht1 ht2
theorem IndepSets.bUnion {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {u : Set ι} (hyp : ∀ n ∈ u, IndepSets (s n) s' κ μ) :
IndepSets (⋃ n ∈ u, s n) s' κ μ := by
intro t1 t2 ht1 ht2
simp_rw [Set.mem_iUnion] at ht1
rcases ht1 with ⟨n, hpn, ht1⟩
exact hyp n hpn t1 t2 ht1 ht2
theorem IndepSets.inter {s₁ s' : Set (Set Ω)} (s₂ : Set (Set Ω)) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h₁ : IndepSets s₁ s' κ μ) :
IndepSets (s₁ ∩ s₂) s' κ μ :=
fun t1 t2 ht1 ht2 => h₁ t1 t2 ((Set.mem_inter_iff _ _ _).mp ht1).left ht2
theorem IndepSets.iInter {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h : ∃ n, IndepSets (s n) s' κ μ) :
IndepSets (⋂ n, s n) s' κ μ := by
intro t1 t2 ht1 ht2; cases' h with n h; exact h t1 t2 (Set.mem_iInter.mp ht1 n) ht2
theorem IndepSets.bInter {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {u : Set ι} (h : ∃ n ∈ u, IndepSets (s n) s' κ μ) :
IndepSets (⋂ n ∈ u, s n) s' κ μ := by
intro t1 t2 ht1 ht2
rcases h with ⟨n, hn, h⟩
exact h t1 t2 (Set.biInter_subset_of_mem hn ht1) ht2
theorem iIndep_comap_mem_iff {f : ι → Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
iIndep (fun i => MeasurableSpace.comap (· ∈ f i) ⊤) κ μ ↔ iIndepSet f κ μ := by
simp_rw [← generateFrom_singleton, iIndepSet]
theorem iIndepSets_singleton_iff {s : ι → Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
iIndepSets (fun i ↦ {s i}) κ μ ↔
∀ S : Finset ι, ∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := by
refine ⟨fun h S ↦ h S (fun i _ ↦ rfl), fun h S f hf ↦ ?_⟩
filter_upwards [h S] with a ha
have : ∀ i ∈ S, κ a (f i) = κ a (s i) := fun i hi ↦ by rw [hf i hi]
rwa [Finset.prod_congr rfl this, Set.iInter₂_congr hf]
theorem indepSets_singleton_iff {s t : Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
IndepSets {s} {t} κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t :=
⟨fun h ↦ h s t rfl rfl,
fun h s1 t1 hs1 ht1 ↦ by rwa [Set.mem_singleton_iff.mp hs1, Set.mem_singleton_iff.mp ht1]⟩
end Indep
/-! ### Deducing `Indep` from `iIndep` -/
section FromiIndepToIndep
variable {_mα : MeasurableSpace α}
theorem iIndepSets.indepSets {s : ι → Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : iIndepSets s κ μ) {i j : ι} (hij : i ≠ j) :
IndepSets (s i) (s j) κ μ := by
classical
intro t₁ t₂ ht₁ ht₂
have hf_m : ∀ x : ι, x ∈ ({i, j} : Finset ι) → ite (x = i) t₁ t₂ ∈ s x := by
intro x hx
cases' Finset.mem_insert.mp hx with hx hx
· simp [hx, ht₁]
· simp [Finset.mem_singleton.mp hx, hij.symm, ht₂]
have h1 : t₁ = ite (i = i) t₁ t₂ := by simp only [if_true, eq_self_iff_true]
have h2 : t₂ = ite (j = i) t₁ t₂ := by simp only [hij.symm, if_false]
have h_inter : ⋂ (t : ι) (_ : t ∈ ({i, j} : Finset ι)), ite (t = i) t₁ t₂ =
ite (i = i) t₁ t₂ ∩ ite (j = i) t₁ t₂ := by
simp only [Finset.set_biInter_singleton, Finset.set_biInter_insert]
filter_upwards [h_indep {i, j} hf_m] with a h_indep'
have h_prod : (∏ t ∈ ({i, j} : Finset ι), κ a (ite (t = i) t₁ t₂))
= κ a (ite (i = i) t₁ t₂) * κ a (ite (j = i) t₁ t₂) := by
simp only [hij, Finset.prod_singleton, Finset.prod_insert, not_false_iff,
Finset.mem_singleton]
rw [h1]
nth_rw 2 [h2]
nth_rw 4 [h2]
rw [← h_inter, ← h_prod, h_indep']
theorem iIndep.indep {m : ι → MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
(h_indep : iIndep m κ μ) {i j : ι} (hij : i ≠ j) : Indep (m i) (m j) κ μ :=
iIndepSets.indepSets h_indep hij
theorem iIndepFun.indepFun {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {β : ι → Type*}
{m : ∀ x, MeasurableSpace (β x)} {f : ∀ i, Ω → β i} (hf_Indep : iIndepFun m f κ μ) {i j : ι}
(hij : i ≠ j) : IndepFun (f i) (f j) κ μ :=
hf_Indep.indep hij
end FromiIndepToIndep
/-!
## π-system lemma
Independence of measurable spaces is equivalent to independence of generating π-systems.
-/
section FromMeasurableSpacesToSetsOfSets
/-! ### Independence of measurable space structures implies independence of generating π-systems -/
variable {_mα : MeasurableSpace α}
theorem iIndep.iIndepSets {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {m : ι → MeasurableSpace Ω}
{s : ι → Set (Set Ω)} (hms : ∀ n, m n = generateFrom (s n)) (h_indep : iIndep m κ μ) :
iIndepSets s κ μ :=
fun S f hfs =>
h_indep S fun x hxS =>
((hms x).symm ▸ measurableSet_generateFrom (hfs x hxS) : MeasurableSet[m x] (f x))
theorem Indep.indepSets {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {s1 s2 : Set (Set Ω)}
(h_indep : Indep (generateFrom s1) (generateFrom s2) κ μ) :
IndepSets s1 s2 κ μ :=
fun t1 t2 ht1 ht2 =>
h_indep t1 t2 (measurableSet_generateFrom ht1) (measurableSet_generateFrom ht2)
end FromMeasurableSpacesToSetsOfSets
section FromPiSystemsToMeasurableSpaces
/-! ### Independence of generating π-systems implies independence of measurable space structures -/
variable {_mα : MeasurableSpace α}
theorem IndepSets.indep_aux {m₂ m : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] {p1 p2 : Set (Set Ω)} (h2 : m₂ ≤ m)
(hp2 : IsPiSystem p2) (hpm2 : m₂ = generateFrom p2) (hyp : IndepSets p1 p2 κ μ) {t1 t2 : Set Ω}
(ht1 : t1 ∈ p1) (ht1m : MeasurableSet[m] t1) (ht2m : MeasurableSet[m₂] t2) :
∀ᵐ a ∂μ, κ a (t1 ∩ t2) = κ a t1 * κ a t2 := by
refine @induction_on_inter _ (fun t ↦ ∀ᵐ a ∂μ, κ a (t1 ∩ t) = κ a t1 * κ a t) _
m₂ hpm2 hp2 ?_ ?_ ?_ ?_ t2 ht2m
· simp only [Set.inter_empty, measure_empty, mul_zero, eq_self_iff_true,
Filter.eventually_true]
· exact fun t ht_mem_p2 ↦ hyp t1 t ht1 ht_mem_p2
· intros t ht h
filter_upwards [h] with a ha
have : t1 ∩ tᶜ = t1 \ (t1 ∩ t) := by
rw [Set.diff_self_inter, Set.diff_eq_compl_inter, Set.inter_comm]
rw [this,
measure_diff Set.inter_subset_left (ht1m.inter (h2 _ ht)) (measure_ne_top (κ a) _),
measure_compl (h2 _ ht) (measure_ne_top (κ a) t), measure_univ,
ENNReal.mul_sub (fun _ _ ↦ measure_ne_top (κ a) _), mul_one, ha]
· intros f hf_disj hf_meas h
rw [← ae_all_iff] at h
filter_upwards [h] with a ha
rw [Set.inter_iUnion, measure_iUnion]
· rw [measure_iUnion hf_disj (fun i ↦ h2 _ (hf_meas i))]
rw [← ENNReal.tsum_mul_left]
congr with i
rw [ha i]
· intros i j hij
rw [Function.onFun, Set.inter_comm t1, Set.inter_comm t1]
exact Disjoint.inter_left _ (Disjoint.inter_right _ (hf_disj hij))
· exact fun i ↦ ht1m.inter (h2 _ (hf_meas i))
/-- The measurable space structures generated by independent pi-systems are independent. -/
theorem IndepSets.indep {m1 m2 m : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
[IsMarkovKernel κ] {p1 p2 : Set (Set Ω)} (h1 : m1 ≤ m) (h2 : m2 ≤ m) (hp1 : IsPiSystem p1)
(hp2 : IsPiSystem p2) (hpm1 : m1 = generateFrom p1) (hpm2 : m2 = generateFrom p2)
(hyp : IndepSets p1 p2 κ μ) :
Indep m1 m2 κ μ := by
intros t1 t2 ht1 ht2
refine @induction_on_inter _ (fun t ↦ ∀ᵐ (a : α) ∂μ, κ a (t ∩ t2) = κ a t * κ a t2) _ m1 hpm1 hp1
?_ ?_ ?_ ?_ _ ht1
· simp only [Set.empty_inter, measure_empty, zero_mul, eq_self_iff_true,
Filter.eventually_true]
· intros t ht_mem_p1
have ht1 : MeasurableSet[m] t := by
refine h1 _ ?_
rw [hpm1]
exact measurableSet_generateFrom ht_mem_p1
exact IndepSets.indep_aux h2 hp2 hpm2 hyp ht_mem_p1 ht1 ht2
· intros t ht h
filter_upwards [h] with a ha
have : tᶜ ∩ t2 = t2 \ (t ∩ t2) := by
rw [Set.inter_comm t, Set.diff_self_inter, Set.diff_eq_compl_inter]
rw [this, Set.inter_comm t t2,
measure_diff Set.inter_subset_left ((h2 _ ht2).inter (h1 _ ht))
(measure_ne_top (κ a) _),
Set.inter_comm, ha, measure_compl (h1 _ ht) (measure_ne_top (κ a) t), measure_univ,
mul_comm (1 - κ a t), ENNReal.mul_sub (fun _ _ ↦ measure_ne_top (κ a) _), mul_one, mul_comm]
· intros f hf_disj hf_meas h
rw [← ae_all_iff] at h
filter_upwards [h] with a ha
rw [Set.inter_comm, Set.inter_iUnion, measure_iUnion]
· rw [measure_iUnion hf_disj (fun i ↦ h1 _ (hf_meas i))]
rw [← ENNReal.tsum_mul_right]
congr 1 with i
rw [Set.inter_comm t2, ha i]
· intros i j hij
rw [Function.onFun, Set.inter_comm t2, Set.inter_comm t2]
exact Disjoint.inter_left _ (Disjoint.inter_right _ (hf_disj hij))
· exact fun i ↦ (h2 _ ht2).inter (h1 _ (hf_meas i))
theorem IndepSets.indep' {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
{p1 p2 : Set (Set Ω)} (hp1m : ∀ s ∈ p1, MeasurableSet s) (hp2m : ∀ s ∈ p2, MeasurableSet s)
(hp1 : IsPiSystem p1) (hp2 : IsPiSystem p2) (hyp : IndepSets p1 p2 κ μ) :
Indep (generateFrom p1) (generateFrom p2) κ μ :=
hyp.indep (generateFrom_le hp1m) (generateFrom_le hp2m) hp1 hp2 rfl rfl
variable {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
theorem indepSets_piiUnionInter_of_disjoint [IsMarkovKernel κ] {s : ι → Set (Set Ω)}
{S T : Set ι} (h_indep : iIndepSets s κ μ) (hST : Disjoint S T) :
IndepSets (piiUnionInter s S) (piiUnionInter s T) κ μ := by
rintro t1 t2 ⟨p1, hp1, f1, ht1_m, ht1_eq⟩ ⟨p2, hp2, f2, ht2_m, ht2_eq⟩
classical
let g i := ite (i ∈ p1) (f1 i) Set.univ ∩ ite (i ∈ p2) (f2 i) Set.univ
have h_P_inter : ∀ᵐ a ∂μ, κ a (t1 ∩ t2) = ∏ n ∈ p1 ∪ p2, κ a (g n) := by
have hgm : ∀ i ∈ p1 ∪ p2, g i ∈ s i := by
intro i hi_mem_union
rw [Finset.mem_union] at hi_mem_union
cases' hi_mem_union with hi1 hi2
· have hi2 : i ∉ p2 := fun hip2 => Set.disjoint_left.mp hST (hp1 hi1) (hp2 hip2)
simp_rw [g, if_pos hi1, if_neg hi2, Set.inter_univ]
exact ht1_m i hi1
· have hi1 : i ∉ p1 := fun hip1 => Set.disjoint_right.mp hST (hp2 hi2) (hp1 hip1)
simp_rw [g, if_neg hi1, if_pos hi2, Set.univ_inter]
exact ht2_m i hi2
have h_p1_inter_p2 :
((⋂ x ∈ p1, f1 x) ∩ ⋂ x ∈ p2, f2 x) =
⋂ i ∈ p1 ∪ p2, ite (i ∈ p1) (f1 i) Set.univ ∩ ite (i ∈ p2) (f2 i) Set.univ := by
ext1 x
simp only [Set.mem_ite_univ_right, Set.mem_inter_iff, Set.mem_iInter, Finset.mem_union]
exact
⟨fun h i _ => ⟨h.1 i, h.2 i⟩, fun h =>
⟨fun i hi => (h i (Or.inl hi)).1 hi, fun i hi => (h i (Or.inr hi)).2 hi⟩⟩
filter_upwards [h_indep _ hgm] with a ha
rw [ht1_eq, ht2_eq, h_p1_inter_p2, ← ha]
filter_upwards [h_P_inter, h_indep p1 ht1_m, h_indep p2 ht2_m] with a h_P_inter ha1 ha2
have h_μg : ∀ n, κ a (g n) = (ite (n ∈ p1) (κ a (f1 n)) 1) * (ite (n ∈ p2) (κ a (f2 n)) 1) := by
intro n
dsimp only [g]
split_ifs with h1 h2
· exact absurd rfl (Set.disjoint_iff_forall_ne.mp hST (hp1 h1) (hp2 h2))
all_goals simp only [measure_univ, one_mul, mul_one, Set.inter_univ, Set.univ_inter]
simp_rw [h_P_inter, h_μg, Finset.prod_mul_distrib,
Finset.prod_ite_mem (p1 ∪ p2) p1 (fun x ↦ κ a (f1 x)), Finset.union_inter_cancel_left,
Finset.prod_ite_mem (p1 ∪ p2) p2 (fun x => κ a (f2 x)), Finset.union_inter_cancel_right, ht1_eq,
← ha1, ht2_eq, ← ha2]
theorem iIndepSet.indep_generateFrom_of_disjoint [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (S T : Set ι) (hST : Disjoint S T) :
Indep (generateFrom { t | ∃ n ∈ S, s n = t }) (generateFrom { t | ∃ k ∈ T, s k = t }) κ μ := by
rw [← generateFrom_piiUnionInter_singleton_left, ← generateFrom_piiUnionInter_singleton_left]
refine
IndepSets.indep'
(fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht))
(fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht)) ?_ ?_ ?_
· exact fun k => generateFrom_le fun t ht => (Set.mem_singleton_iff.1 ht).symm ▸ hsm k
· exact fun k => generateFrom_le fun t ht => (Set.mem_singleton_iff.1 ht).symm ▸ hsm k
· exact isPiSystem_piiUnionInter _ (fun k => IsPiSystem.singleton _) _
· exact isPiSystem_piiUnionInter _ (fun k => IsPiSystem.singleton _) _
· classical exact indepSets_piiUnionInter_of_disjoint (iIndep.iIndepSets (fun n => rfl) hs) hST
theorem indep_iSup_of_disjoint [IsMarkovKernel κ] {m : ι → MeasurableSpace Ω}
(h_le : ∀ i, m i ≤ _mΩ) (h_indep : iIndep m κ μ) {S T : Set ι} (hST : Disjoint S T) :
Indep (⨆ i ∈ S, m i) (⨆ i ∈ T, m i) κ μ := by
refine
IndepSets.indep (iSup₂_le fun i _ => h_le i) (iSup₂_le fun i _ => h_le i) ?_ ?_
(generateFrom_piiUnionInter_measurableSet m S).symm
(generateFrom_piiUnionInter_measurableSet m T).symm ?_
· exact isPiSystem_piiUnionInter _ (fun n => @isPiSystem_measurableSet Ω (m n)) _
· exact isPiSystem_piiUnionInter _ (fun n => @isPiSystem_measurableSet Ω (m n)) _
· classical exact indepSets_piiUnionInter_of_disjoint h_indep hST
theorem indep_iSup_of_directed_le {Ω} {m : ι → MeasurableSpace Ω} {m' m0 : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] (h_indep : ∀ i, Indep (m i) m' κ μ)
(h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0) (hm : Directed (· ≤ ·) m) :
Indep (⨆ i, m i) m' κ μ := by
let p : ι → Set (Set Ω) := fun n => { t | MeasurableSet[m n] t }
have hp : ∀ n, IsPiSystem (p n) := fun n => @isPiSystem_measurableSet Ω (m n)
have h_gen_n : ∀ n, m n = generateFrom (p n) := fun n =>
(@generateFrom_measurableSet Ω (m n)).symm
have hp_supr_pi : IsPiSystem (⋃ n, p n) := isPiSystem_iUnion_of_directed_le p hp hm
let p' := { t : Set Ω | MeasurableSet[m'] t }
have hp'_pi : IsPiSystem p' := @isPiSystem_measurableSet Ω m'
have h_gen' : m' = generateFrom p' := (@generateFrom_measurableSet Ω m').symm
-- the π-systems defined are independent
have h_pi_system_indep : IndepSets (⋃ n, p n) p' κ μ := by
refine IndepSets.iUnion ?_
conv at h_indep =>
intro i
rw [h_gen_n i, h_gen']
exact fun n => (h_indep n).indepSets
-- now go from π-systems to σ-algebras
refine IndepSets.indep (iSup_le h_le) h_le' hp_supr_pi hp'_pi ?_ h_gen' h_pi_system_indep
exact (generateFrom_iUnion_measurableSet _).symm
theorem iIndepSet.indep_generateFrom_lt [Preorder ι] [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (i : ι) :
Indep (generateFrom {s i}) (generateFrom { t | ∃ j < i, s j = t }) κ μ := by
convert iIndepSet.indep_generateFrom_of_disjoint hsm hs {i} { j | j < i }
(Set.disjoint_singleton_left.mpr (lt_irrefl _))
simp only [Set.mem_singleton_iff, exists_prop, exists_eq_left, Set.setOf_eq_eq_singleton']
theorem iIndepSet.indep_generateFrom_le [LinearOrder ι] [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (i : ι) {k : ι} (hk : i < k) :
Indep (generateFrom {s k}) (generateFrom { t | ∃ j ≤ i, s j = t }) κ μ := by
convert iIndepSet.indep_generateFrom_of_disjoint hsm hs {k} { j | j ≤ i }
(Set.disjoint_singleton_left.mpr hk.not_le)
simp only [Set.mem_singleton_iff, exists_prop, exists_eq_left, Set.setOf_eq_eq_singleton']
theorem iIndepSet.indep_generateFrom_le_nat [IsMarkovKernel κ] {s : ℕ → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (n : ℕ) :
Indep (generateFrom {s (n + 1)}) (generateFrom { t | ∃ k ≤ n, s k = t }) κ μ :=
iIndepSet.indep_generateFrom_le hsm hs _ n.lt_succ_self
theorem indep_iSup_of_monotone [SemilatticeSup ι] {Ω} {m : ι → MeasurableSpace Ω}
{m' m0 : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
(h_indep : ∀ i, Indep (m i) m' κ μ) (h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0)
(hm : Monotone m) :
Indep (⨆ i, m i) m' κ μ :=
indep_iSup_of_directed_le h_indep h_le h_le' (Monotone.directed_le hm)
theorem indep_iSup_of_antitone [SemilatticeInf ι] {Ω} {m : ι → MeasurableSpace Ω}
{m' m0 : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
(h_indep : ∀ i, Indep (m i) m' κ μ) (h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0)
(hm : Antitone m) :
Indep (⨆ i, m i) m' κ μ :=
indep_iSup_of_directed_le h_indep h_le h_le' hm.directed_le
| Mathlib/Probability/Independence/Kernel.lean | 577 | 612 | theorem iIndepSets.piiUnionInter_of_not_mem {π : ι → Set (Set Ω)} {a : ι} {S : Finset ι}
(hp_ind : iIndepSets π κ μ) (haS : a ∉ S) :
IndepSets (piiUnionInter π S) (π a) κ μ := by |
rintro t1 t2 ⟨s, hs_mem, ft1, hft1_mem, ht1_eq⟩ ht2_mem_pia
rw [Finset.coe_subset] at hs_mem
classical
let f := fun n => ite (n = a) t2 (ite (n ∈ s) (ft1 n) Set.univ)
have h_f_mem : ∀ n ∈ insert a s, f n ∈ π n := by
intro n hn_mem_insert
dsimp only [f]
cases' Finset.mem_insert.mp hn_mem_insert with hn_mem hn_mem
· simp [hn_mem, ht2_mem_pia]
· have hn_ne_a : n ≠ a := by rintro rfl; exact haS (hs_mem hn_mem)
simp [hn_ne_a, hn_mem, hft1_mem n hn_mem]
have h_f_mem_pi : ∀ n ∈ s, f n ∈ π n := fun x hxS => h_f_mem x (by simp [hxS])
have h_t1 : t1 = ⋂ n ∈ s, f n := by
suffices h_forall : ∀ n ∈ s, f n = ft1 n by
rw [ht1_eq]
ext x
simp_rw [Set.mem_iInter]
conv => lhs; intro i hns; rw [← h_forall i hns]
intro n hnS
have hn_ne_a : n ≠ a := by rintro rfl; exact haS (hs_mem hnS)
simp_rw [f, if_pos hnS, if_neg hn_ne_a]
have h_μ_t1 : ∀ᵐ a' ∂μ, κ a' t1 = ∏ n ∈ s, κ a' (f n) := by
filter_upwards [hp_ind s h_f_mem_pi] with a' ha'
rw [h_t1, ← ha']
have h_t2 : t2 = f a := by simp [f]
have h_μ_inter : ∀ᵐ a' ∂μ, κ a' (t1 ∩ t2) = ∏ n ∈ insert a s, κ a' (f n) := by
have h_t1_inter_t2 : t1 ∩ t2 = ⋂ n ∈ insert a s, f n := by
rw [h_t1, h_t2, Finset.set_biInter_insert, Set.inter_comm]
filter_upwards [hp_ind (insert a s) h_f_mem] with a' ha'
rw [h_t1_inter_t2, ← ha']
have has : a ∉ s := fun has_mem => haS (hs_mem has_mem)
filter_upwards [h_μ_t1, h_μ_inter] with a' ha1 ha2
rw [ha2, Finset.prod_insert has, h_t2, mul_comm, ha1]
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Johan Commelin, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Equivalence
#align_import category_theory.adjunction.basic from "leanprover-community/mathlib"@"d101e93197bb5f6ea89bd7ba386b7f7dff1f3903"
/-!
# Adjunctions between functors
`F ⊣ G` represents the data of an adjunction between two functors
`F : C ⥤ D` and `G : D ⥤ C`. `F` is the left adjoint and `G` is the right adjoint.
We provide various useful constructors:
* `mkOfHomEquiv`
* `mkOfUnitCounit`
* `leftAdjointOfEquiv` / `rightAdjointOfEquiv`
construct a left/right adjoint of a given functor given the action on objects and
the relevant equivalence of morphism spaces.
* `adjunctionOfEquivLeft` / `adjunctionOfEquivRight` witness that these constructions
give adjunctions.
There are also typeclasses `IsLeftAdjoint` / `IsRightAdjoint`, which asserts the
existence of a adjoint functor. Given `[F.IsLeftAdjoint]`, a chosen right
adjoint can be obtained as `F.rightAdjoint`.
`Adjunction.comp` composes adjunctions.
`toEquivalence` upgrades an adjunction to an equivalence,
given witnesses that the unit and counit are pointwise isomorphisms.
Conversely `Equivalence.toAdjunction` recovers the underlying adjunction from an equivalence.
-/
namespace CategoryTheory
open Category
-- declare the `v`'s first; see `CategoryTheory.Category` for an explanation
universe v₁ v₂ v₃ u₁ u₂ u₃
-- Porting Note: `elab_without_expected_type` cannot be a local attribute
-- attribute [local elab_without_expected_type] whiskerLeft whiskerRight
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D]
/-- `F ⊣ G` represents the data of an adjunction between two functors
`F : C ⥤ D` and `G : D ⥤ C`. `F` is the left adjoint and `G` is the right adjoint.
To construct an `adjunction` between two functors, it's often easier to instead use the
constructors `mkOfHomEquiv` or `mkOfUnitCounit`. To construct a left adjoint,
there are also constructors `leftAdjointOfEquiv` and `adjunctionOfEquivLeft` (as
well as their duals) which can be simpler in practice.
Uniqueness of adjoints is shown in `CategoryTheory.Adjunction.Opposites`.
See <https://stacks.math.columbia.edu/tag/0037>.
-/
structure Adjunction (F : C ⥤ D) (G : D ⥤ C) where
/-- The equivalence between `Hom (F X) Y` and `Hom X (G Y)` coming from an adjunction -/
homEquiv : ∀ X Y, (F.obj X ⟶ Y) ≃ (X ⟶ G.obj Y)
/-- The unit of an adjunction -/
unit : 𝟭 C ⟶ F.comp G
/-- The counit of an adjunction -/
counit : G.comp F ⟶ 𝟭 D
-- Porting note: It's strange that this `Prop` is being flagged by the `docBlame` linter
/-- Naturality of the unit of an adjunction -/
homEquiv_unit : ∀ {X Y f}, (homEquiv X Y) f = (unit : _ ⟶ _).app X ≫ G.map f := by aesop_cat
-- Porting note: It's strange that this `Prop` is being flagged by the `docBlame` linter
/-- Naturality of the counit of an adjunction -/
homEquiv_counit : ∀ {X Y g}, (homEquiv X Y).symm g = F.map g ≫ counit.app Y := by aesop_cat
#align category_theory.adjunction CategoryTheory.Adjunction
#align category_theory.adjunction.hom_equiv CategoryTheory.Adjunction.homEquiv
#align category_theory.adjunction.hom_equiv_unit CategoryTheory.Adjunction.homEquiv_unit
#align category_theory.adjunction.hom_equiv_unit' CategoryTheory.Adjunction.homEquiv_unit
#align category_theory.adjunction.hom_equiv_counit CategoryTheory.Adjunction.homEquiv_counit
#align category_theory.adjunction.hom_equiv_counit' CategoryTheory.Adjunction.homEquiv_counit
/-- The notation `F ⊣ G` stands for `Adjunction F G` representing that `F` is left adjoint to `G` -/
infixl:15 " ⊣ " => Adjunction
namespace Functor
/-- A class asserting the existence of a right adjoint. -/
class IsLeftAdjoint (left : C ⥤ D) : Prop where
exists_rightAdjoint : ∃ (right : D ⥤ C), Nonempty (left ⊣ right)
#align category_theory.is_left_adjoint CategoryTheory.Functor.IsLeftAdjoint
/-- A class asserting the existence of a left adjoint. -/
class IsRightAdjoint (right : D ⥤ C) : Prop where
exists_leftAdjoint : ∃ (left : C ⥤ D), Nonempty (left ⊣ right)
#align category_theory.is_right_adjoint CategoryTheory.Functor.IsRightAdjoint
/-- A chosen left adjoint to a functor that is a right adjoint. -/
noncomputable def leftAdjoint (R : D ⥤ C) [IsRightAdjoint R] : C ⥤ D :=
(IsRightAdjoint.exists_leftAdjoint (right := R)).choose
#align category_theory.left_adjoint CategoryTheory.Functor.leftAdjoint
/-- A chosen right adjoint to a functor that is a left adjoint. -/
noncomputable def rightAdjoint (L : C ⥤ D) [IsLeftAdjoint L] : D ⥤ C :=
(IsLeftAdjoint.exists_rightAdjoint (left := L)).choose
#align category_theory.right_adjoint CategoryTheory.Functor.rightAdjoint
end Functor
/-- The adjunction associated to a functor known to be a left adjoint. -/
noncomputable def Adjunction.ofIsLeftAdjoint (left : C ⥤ D) [left.IsLeftAdjoint] :
left ⊣ left.rightAdjoint :=
Functor.IsLeftAdjoint.exists_rightAdjoint.choose_spec.some
#align category_theory.adjunction.of_left_adjoint CategoryTheory.Adjunction.ofIsLeftAdjoint
/-- The adjunction associated to a functor known to be a right adjoint. -/
noncomputable def Adjunction.ofIsRightAdjoint (right : C ⥤ D) [right.IsRightAdjoint] :
right.leftAdjoint ⊣ right :=
Functor.IsRightAdjoint.exists_leftAdjoint.choose_spec.some
#align category_theory.adjunction.of_right_adjoint CategoryTheory.Adjunction.ofIsRightAdjoint
namespace Adjunction
-- Porting note: Workaround not needed in Lean 4
-- restate_axiom homEquiv_unit'
-- restate_axiom homEquiv_counit'
attribute [simp] homEquiv_unit homEquiv_counit
section
variable {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G)
lemma isLeftAdjoint : F.IsLeftAdjoint := ⟨_, ⟨adj⟩⟩
lemma isRightAdjoint : G.IsRightAdjoint := ⟨_, ⟨adj⟩⟩
instance (R : D ⥤ C) [R.IsRightAdjoint] : R.leftAdjoint.IsLeftAdjoint :=
(ofIsRightAdjoint R).isLeftAdjoint
instance (L : C ⥤ D) [L.IsLeftAdjoint] : L.rightAdjoint.IsRightAdjoint :=
(ofIsLeftAdjoint L).isRightAdjoint
variable {X' X : C} {Y Y' : D}
theorem homEquiv_id (X : C) : adj.homEquiv X _ (𝟙 _) = adj.unit.app X := by simp
#align category_theory.adjunction.hom_equiv_id CategoryTheory.Adjunction.homEquiv_id
theorem homEquiv_symm_id (X : D) : (adj.homEquiv _ X).symm (𝟙 _) = adj.counit.app X := by simp
#align category_theory.adjunction.hom_equiv_symm_id CategoryTheory.Adjunction.homEquiv_symm_id
/-
Porting note: `nolint simpNF` as the linter was complaining that this was provable using `simp`
but it is in fact not. Also the `docBlame` linter expects a docstring even though this is `Prop`
valued
-/
@[simp, nolint simpNF]
theorem homEquiv_naturality_left_symm (f : X' ⟶ X) (g : X ⟶ G.obj Y) :
(adj.homEquiv X' Y).symm (f ≫ g) = F.map f ≫ (adj.homEquiv X Y).symm g := by
rw [homEquiv_counit, F.map_comp, assoc, adj.homEquiv_counit.symm]
#align category_theory.adjunction.hom_equiv_naturality_left_symm CategoryTheory.Adjunction.homEquiv_naturality_left_symm
-- Porting note: Same as above
@[simp, nolint simpNF]
theorem homEquiv_naturality_left (f : X' ⟶ X) (g : F.obj X ⟶ Y) :
(adj.homEquiv X' Y) (F.map f ≫ g) = f ≫ (adj.homEquiv X Y) g := by
rw [← Equiv.eq_symm_apply]
simp only [Equiv.symm_apply_apply,eq_self_iff_true,homEquiv_naturality_left_symm]
#align category_theory.adjunction.hom_equiv_naturality_left CategoryTheory.Adjunction.homEquiv_naturality_left
-- Porting note: Same as above
@[simp, nolint simpNF]
| Mathlib/CategoryTheory/Adjunction/Basic.lean | 172 | 174 | theorem homEquiv_naturality_right (f : F.obj X ⟶ Y) (g : Y ⟶ Y') :
(adj.homEquiv X Y') (f ≫ g) = (adj.homEquiv X Y) f ≫ G.map g := by |
rw [homEquiv_unit, G.map_comp, ← assoc, ← homEquiv_unit]
|
/-
Copyright (c) 2018 Guy Leroy. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sangwoo Jo (aka Jason), Guy Leroy, Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Algebra.Group.Commute.Units
import Mathlib.Algebra.Group.Int
import Mathlib.Algebra.GroupWithZero.Semiconj
import Mathlib.Data.Nat.GCD.Basic
import Mathlib.Order.Bounds.Basic
#align_import data.int.gcd from "leanprover-community/mathlib"@"47a1a73351de8dd6c8d3d32b569c8e434b03ca47"
/-!
# Extended GCD and divisibility over ℤ
## Main definitions
* Given `x y : ℕ`, `xgcd x y` computes the pair of integers `(a, b)` such that
`gcd x y = x * a + y * b`. `gcdA x y` and `gcdB x y` are defined to be `a` and `b`,
respectively.
## Main statements
* `gcd_eq_gcd_ab`: Bézout's lemma, given `x y : ℕ`, `gcd x y = x * gcdA x y + y * gcdB x y`.
## Tags
Bézout's lemma, Bezout's lemma
-/
/-! ### Extended Euclidean algorithm -/
namespace Nat
/-- Helper function for the extended GCD algorithm (`Nat.xgcd`). -/
def xgcdAux : ℕ → ℤ → ℤ → ℕ → ℤ → ℤ → ℕ × ℤ × ℤ
| 0, _, _, r', s', t' => (r', s', t')
| succ k, s, t, r', s', t' =>
let q := r' / succ k
xgcdAux (r' % succ k) (s' - q * s) (t' - q * t) (succ k) s t
termination_by k => k
decreasing_by exact mod_lt _ <| (succ_pos _).gt
#align nat.xgcd_aux Nat.xgcdAux
@[simp]
theorem xgcd_zero_left {s t r' s' t'} : xgcdAux 0 s t r' s' t' = (r', s', t') := by simp [xgcdAux]
#align nat.xgcd_zero_left Nat.xgcd_zero_left
theorem xgcdAux_rec {r s t r' s' t'} (h : 0 < r) :
xgcdAux r s t r' s' t' = xgcdAux (r' % r) (s' - r' / r * s) (t' - r' / r * t) r s t := by
obtain ⟨r, rfl⟩ := Nat.exists_eq_succ_of_ne_zero h.ne'
simp [xgcdAux]
#align nat.xgcd_aux_rec Nat.xgcdAux_rec
/-- Use the extended GCD algorithm to generate the `a` and `b` values
satisfying `gcd x y = x * a + y * b`. -/
def xgcd (x y : ℕ) : ℤ × ℤ :=
(xgcdAux x 1 0 y 0 1).2
#align nat.xgcd Nat.xgcd
/-- The extended GCD `a` value in the equation `gcd x y = x * a + y * b`. -/
def gcdA (x y : ℕ) : ℤ :=
(xgcd x y).1
#align nat.gcd_a Nat.gcdA
/-- The extended GCD `b` value in the equation `gcd x y = x * a + y * b`. -/
def gcdB (x y : ℕ) : ℤ :=
(xgcd x y).2
#align nat.gcd_b Nat.gcdB
@[simp]
theorem gcdA_zero_left {s : ℕ} : gcdA 0 s = 0 := by
unfold gcdA
rw [xgcd, xgcd_zero_left]
#align nat.gcd_a_zero_left Nat.gcdA_zero_left
@[simp]
theorem gcdB_zero_left {s : ℕ} : gcdB 0 s = 1 := by
unfold gcdB
rw [xgcd, xgcd_zero_left]
#align nat.gcd_b_zero_left Nat.gcdB_zero_left
@[simp]
theorem gcdA_zero_right {s : ℕ} (h : s ≠ 0) : gcdA s 0 = 1 := by
unfold gcdA xgcd
obtain ⟨s, rfl⟩ := Nat.exists_eq_succ_of_ne_zero h
rw [xgcdAux]
simp
#align nat.gcd_a_zero_right Nat.gcdA_zero_right
@[simp]
theorem gcdB_zero_right {s : ℕ} (h : s ≠ 0) : gcdB s 0 = 0 := by
unfold gcdB xgcd
obtain ⟨s, rfl⟩ := Nat.exists_eq_succ_of_ne_zero h
rw [xgcdAux]
simp
#align nat.gcd_b_zero_right Nat.gcdB_zero_right
@[simp]
theorem xgcdAux_fst (x y) : ∀ s t s' t', (xgcdAux x s t y s' t').1 = gcd x y :=
gcd.induction x y (by simp) fun x y h IH s t s' t' => by
simp only [h, xgcdAux_rec, IH]
rw [← gcd_rec]
#align nat.xgcd_aux_fst Nat.xgcdAux_fst
theorem xgcdAux_val (x y) : xgcdAux x 1 0 y 0 1 = (gcd x y, xgcd x y) := by
rw [xgcd, ← xgcdAux_fst x y 1 0 0 1]
#align nat.xgcd_aux_val Nat.xgcdAux_val
theorem xgcd_val (x y) : xgcd x y = (gcdA x y, gcdB x y) := by
unfold gcdA gcdB; cases xgcd x y; rfl
#align nat.xgcd_val Nat.xgcd_val
section
variable (x y : ℕ)
private def P : ℕ × ℤ × ℤ → Prop
| (r, s, t) => (r : ℤ) = x * s + y * t
theorem xgcdAux_P {r r'} :
∀ {s t s' t'}, P x y (r, s, t) → P x y (r', s', t') → P x y (xgcdAux r s t r' s' t') := by
induction r, r' using gcd.induction with
| H0 => simp
| H1 a b h IH =>
intro s t s' t' p p'
rw [xgcdAux_rec h]; refine IH ?_ p; dsimp [P] at *
rw [Int.emod_def]; generalize (b / a : ℤ) = k
rw [p, p', Int.mul_sub, sub_add_eq_add_sub, Int.mul_sub, Int.add_mul, mul_comm k t,
mul_comm k s, ← mul_assoc, ← mul_assoc, add_comm (x * s * k), ← add_sub_assoc, sub_sub]
set_option linter.uppercaseLean3 false in
#align nat.xgcd_aux_P Nat.xgcdAux_P
/-- **Bézout's lemma**: given `x y : ℕ`, `gcd x y = x * a + y * b`, where `a = gcd_a x y` and
`b = gcd_b x y` are computed by the extended Euclidean algorithm.
-/
theorem gcd_eq_gcd_ab : (gcd x y : ℤ) = x * gcdA x y + y * gcdB x y := by
have := @xgcdAux_P x y x y 1 0 0 1 (by simp [P]) (by simp [P])
rwa [xgcdAux_val, xgcd_val] at this
#align nat.gcd_eq_gcd_ab Nat.gcd_eq_gcd_ab
end
theorem exists_mul_emod_eq_gcd {k n : ℕ} (hk : gcd n k < k) : ∃ m, n * m % k = gcd n k := by
have hk' := Int.ofNat_ne_zero.2 (ne_of_gt (lt_of_le_of_lt (zero_le (gcd n k)) hk))
have key := congr_arg (fun (m : ℤ) => (m % k).toNat) (gcd_eq_gcd_ab n k)
simp only at key
rw [Int.add_mul_emod_self_left, ← Int.natCast_mod, Int.toNat_natCast, mod_eq_of_lt hk] at key
refine ⟨(n.gcdA k % k).toNat, Eq.trans (Int.ofNat.inj ?_) key.symm⟩
rw [Int.ofNat_eq_coe, Int.natCast_mod, Int.ofNat_mul, Int.toNat_of_nonneg (Int.emod_nonneg _ hk'),
Int.ofNat_eq_coe, Int.toNat_of_nonneg (Int.emod_nonneg _ hk'), Int.mul_emod, Int.emod_emod,
← Int.mul_emod]
#align nat.exists_mul_mod_eq_gcd Nat.exists_mul_emod_eq_gcd
theorem exists_mul_emod_eq_one_of_coprime {k n : ℕ} (hkn : Coprime n k) (hk : 1 < k) :
∃ m, n * m % k = 1 :=
Exists.recOn (exists_mul_emod_eq_gcd (lt_of_le_of_lt (le_of_eq hkn) hk)) fun m hm ↦
⟨m, hm.trans hkn⟩
#align nat.exists_mul_mod_eq_one_of_coprime Nat.exists_mul_emod_eq_one_of_coprime
end Nat
/-! ### Divisibility over ℤ -/
namespace Int
theorem gcd_def (i j : ℤ) : gcd i j = Nat.gcd i.natAbs j.natAbs := rfl
@[simp, norm_cast] protected lemma gcd_natCast_natCast (m n : ℕ) : gcd ↑m ↑n = m.gcd n := rfl
#align int.coe_nat_gcd Int.gcd_natCast_natCast
@[deprecated (since := "2024-05-25")] alias coe_nat_gcd := Int.gcd_natCast_natCast
/-- The extended GCD `a` value in the equation `gcd x y = x * a + y * b`. -/
def gcdA : ℤ → ℤ → ℤ
| ofNat m, n => m.gcdA n.natAbs
| -[m+1], n => -m.succ.gcdA n.natAbs
#align int.gcd_a Int.gcdA
/-- The extended GCD `b` value in the equation `gcd x y = x * a + y * b`. -/
def gcdB : ℤ → ℤ → ℤ
| m, ofNat n => m.natAbs.gcdB n
| m, -[n+1] => -m.natAbs.gcdB n.succ
#align int.gcd_b Int.gcdB
/-- **Bézout's lemma** -/
theorem gcd_eq_gcd_ab : ∀ x y : ℤ, (gcd x y : ℤ) = x * gcdA x y + y * gcdB x y
| (m : ℕ), (n : ℕ) => Nat.gcd_eq_gcd_ab _ _
| (m : ℕ), -[n+1] =>
show (_ : ℤ) = _ + -(n + 1) * -_ by rw [Int.neg_mul_neg]; apply Nat.gcd_eq_gcd_ab
| -[m+1], (n : ℕ) =>
show (_ : ℤ) = -(m + 1) * -_ + _ by rw [Int.neg_mul_neg]; apply Nat.gcd_eq_gcd_ab
| -[m+1], -[n+1] =>
show (_ : ℤ) = -(m + 1) * -_ + -(n + 1) * -_ by
rw [Int.neg_mul_neg, Int.neg_mul_neg]
apply Nat.gcd_eq_gcd_ab
#align int.gcd_eq_gcd_ab Int.gcd_eq_gcd_ab
#align int.lcm Int.lcm
theorem lcm_def (i j : ℤ) : lcm i j = Nat.lcm (natAbs i) (natAbs j) :=
rfl
#align int.lcm_def Int.lcm_def
protected theorem coe_nat_lcm (m n : ℕ) : Int.lcm ↑m ↑n = Nat.lcm m n :=
rfl
#align int.coe_nat_lcm Int.coe_nat_lcm
#align int.gcd_dvd_left Int.gcd_dvd_left
#align int.gcd_dvd_right Int.gcd_dvd_right
theorem dvd_gcd {i j k : ℤ} (h1 : k ∣ i) (h2 : k ∣ j) : k ∣ gcd i j :=
natAbs_dvd.1 <|
natCast_dvd_natCast.2 <| Nat.dvd_gcd (natAbs_dvd_natAbs.2 h1) (natAbs_dvd_natAbs.2 h2)
#align int.dvd_gcd Int.dvd_gcd
theorem gcd_mul_lcm (i j : ℤ) : gcd i j * lcm i j = natAbs (i * j) := by
rw [Int.gcd, Int.lcm, Nat.gcd_mul_lcm, natAbs_mul]
#align int.gcd_mul_lcm Int.gcd_mul_lcm
theorem gcd_comm (i j : ℤ) : gcd i j = gcd j i :=
Nat.gcd_comm _ _
#align int.gcd_comm Int.gcd_comm
theorem gcd_assoc (i j k : ℤ) : gcd (gcd i j) k = gcd i (gcd j k) :=
Nat.gcd_assoc _ _ _
#align int.gcd_assoc Int.gcd_assoc
@[simp]
theorem gcd_self (i : ℤ) : gcd i i = natAbs i := by simp [gcd]
#align int.gcd_self Int.gcd_self
@[simp]
theorem gcd_zero_left (i : ℤ) : gcd 0 i = natAbs i := by simp [gcd]
#align int.gcd_zero_left Int.gcd_zero_left
@[simp]
theorem gcd_zero_right (i : ℤ) : gcd i 0 = natAbs i := by simp [gcd]
#align int.gcd_zero_right Int.gcd_zero_right
#align int.gcd_one_left Int.one_gcd
#align int.gcd_one_right Int.gcd_one
#align int.gcd_neg_right Int.gcd_neg
#align int.gcd_neg_left Int.neg_gcd
theorem gcd_mul_left (i j k : ℤ) : gcd (i * j) (i * k) = natAbs i * gcd j k := by
rw [Int.gcd, Int.gcd, natAbs_mul, natAbs_mul]
apply Nat.gcd_mul_left
#align int.gcd_mul_left Int.gcd_mul_left
theorem gcd_mul_right (i j k : ℤ) : gcd (i * j) (k * j) = gcd i k * natAbs j := by
rw [Int.gcd, Int.gcd, natAbs_mul, natAbs_mul]
apply Nat.gcd_mul_right
#align int.gcd_mul_right Int.gcd_mul_right
theorem gcd_pos_of_ne_zero_left {i : ℤ} (j : ℤ) (hi : i ≠ 0) : 0 < gcd i j :=
Nat.gcd_pos_of_pos_left _ <| natAbs_pos.2 hi
#align int.gcd_pos_of_ne_zero_left Int.gcd_pos_of_ne_zero_left
theorem gcd_pos_of_ne_zero_right (i : ℤ) {j : ℤ} (hj : j ≠ 0) : 0 < gcd i j :=
Nat.gcd_pos_of_pos_right _ <| natAbs_pos.2 hj
#align int.gcd_pos_of_ne_zero_right Int.gcd_pos_of_ne_zero_right
theorem gcd_eq_zero_iff {i j : ℤ} : gcd i j = 0 ↔ i = 0 ∧ j = 0 := by
rw [gcd, Nat.gcd_eq_zero_iff, natAbs_eq_zero, natAbs_eq_zero]
#align int.gcd_eq_zero_iff Int.gcd_eq_zero_iff
theorem gcd_pos_iff {i j : ℤ} : 0 < gcd i j ↔ i ≠ 0 ∨ j ≠ 0 :=
pos_iff_ne_zero.trans <| gcd_eq_zero_iff.not.trans not_and_or
#align int.gcd_pos_iff Int.gcd_pos_iff
theorem gcd_div {i j k : ℤ} (H1 : k ∣ i) (H2 : k ∣ j) :
gcd (i / k) (j / k) = gcd i j / natAbs k := by
rw [gcd, natAbs_ediv i k H1, natAbs_ediv j k H2]
exact Nat.gcd_div (natAbs_dvd_natAbs.mpr H1) (natAbs_dvd_natAbs.mpr H2)
#align int.gcd_div Int.gcd_div
theorem gcd_div_gcd_div_gcd {i j : ℤ} (H : 0 < gcd i j) : gcd (i / gcd i j) (j / gcd i j) = 1 := by
rw [gcd_div gcd_dvd_left gcd_dvd_right, natAbs_ofNat, Nat.div_self H]
#align int.gcd_div_gcd_div_gcd Int.gcd_div_gcd_div_gcd
theorem gcd_dvd_gcd_of_dvd_left {i k : ℤ} (j : ℤ) (H : i ∣ k) : gcd i j ∣ gcd k j :=
Int.natCast_dvd_natCast.1 <| dvd_gcd (gcd_dvd_left.trans H) gcd_dvd_right
#align int.gcd_dvd_gcd_of_dvd_left Int.gcd_dvd_gcd_of_dvd_left
theorem gcd_dvd_gcd_of_dvd_right {i k : ℤ} (j : ℤ) (H : i ∣ k) : gcd j i ∣ gcd j k :=
Int.natCast_dvd_natCast.1 <| dvd_gcd gcd_dvd_left (gcd_dvd_right.trans H)
#align int.gcd_dvd_gcd_of_dvd_right Int.gcd_dvd_gcd_of_dvd_right
theorem gcd_dvd_gcd_mul_left (i j k : ℤ) : gcd i j ∣ gcd (k * i) j :=
gcd_dvd_gcd_of_dvd_left _ (dvd_mul_left _ _)
#align int.gcd_dvd_gcd_mul_left Int.gcd_dvd_gcd_mul_left
theorem gcd_dvd_gcd_mul_right (i j k : ℤ) : gcd i j ∣ gcd (i * k) j :=
gcd_dvd_gcd_of_dvd_left _ (dvd_mul_right _ _)
#align int.gcd_dvd_gcd_mul_right Int.gcd_dvd_gcd_mul_right
theorem gcd_dvd_gcd_mul_left_right (i j k : ℤ) : gcd i j ∣ gcd i (k * j) :=
gcd_dvd_gcd_of_dvd_right _ (dvd_mul_left _ _)
#align int.gcd_dvd_gcd_mul_left_right Int.gcd_dvd_gcd_mul_left_right
theorem gcd_dvd_gcd_mul_right_right (i j k : ℤ) : gcd i j ∣ gcd i (j * k) :=
gcd_dvd_gcd_of_dvd_right _ (dvd_mul_right _ _)
#align int.gcd_dvd_gcd_mul_right_right Int.gcd_dvd_gcd_mul_right_right
/-- If `gcd a (m * n) = 1`, then `gcd a m = 1`. -/
theorem gcd_eq_one_of_gcd_mul_right_eq_one_left {a : ℤ} {m n : ℕ} (h : a.gcd (m * n) = 1) :
a.gcd m = 1 :=
Nat.dvd_one.mp <| h ▸ gcd_dvd_gcd_mul_right_right a m n
#align int.gcd_eq_one_of_gcd_mul_right_eq_one_left Int.gcd_eq_one_of_gcd_mul_right_eq_one_left
/-- If `gcd a (m * n) = 1`, then `gcd a n = 1`. -/
theorem gcd_eq_one_of_gcd_mul_right_eq_one_right {a : ℤ} {m n : ℕ} (h : a.gcd (m * n) = 1) :
a.gcd n = 1 :=
Nat.dvd_one.mp <| h ▸ gcd_dvd_gcd_mul_left_right a n m
theorem gcd_eq_left {i j : ℤ} (H : i ∣ j) : gcd i j = natAbs i :=
Nat.dvd_antisymm (Nat.gcd_dvd_left _ _) (Nat.dvd_gcd dvd_rfl (natAbs_dvd_natAbs.mpr H))
#align int.gcd_eq_left Int.gcd_eq_left
theorem gcd_eq_right {i j : ℤ} (H : j ∣ i) : gcd i j = natAbs j := by rw [gcd_comm, gcd_eq_left H]
#align int.gcd_eq_right Int.gcd_eq_right
theorem ne_zero_of_gcd {x y : ℤ} (hc : gcd x y ≠ 0) : x ≠ 0 ∨ y ≠ 0 := by
contrapose! hc
rw [hc.left, hc.right, gcd_zero_right, natAbs_zero]
#align int.ne_zero_of_gcd Int.ne_zero_of_gcd
theorem exists_gcd_one {m n : ℤ} (H : 0 < gcd m n) :
∃ m' n' : ℤ, gcd m' n' = 1 ∧ m = m' * gcd m n ∧ n = n' * gcd m n :=
⟨_, _, gcd_div_gcd_div_gcd H, (Int.ediv_mul_cancel gcd_dvd_left).symm,
(Int.ediv_mul_cancel gcd_dvd_right).symm⟩
#align int.exists_gcd_one Int.exists_gcd_one
theorem exists_gcd_one' {m n : ℤ} (H : 0 < gcd m n) :
∃ (g : ℕ) (m' n' : ℤ), 0 < g ∧ gcd m' n' = 1 ∧ m = m' * g ∧ n = n' * g :=
let ⟨m', n', h⟩ := exists_gcd_one H
⟨_, m', n', H, h⟩
#align int.exists_gcd_one' Int.exists_gcd_one'
theorem pow_dvd_pow_iff {m n : ℤ} {k : ℕ} (k0 : k ≠ 0) : m ^ k ∣ n ^ k ↔ m ∣ n := by
refine ⟨fun h => ?_, fun h => pow_dvd_pow_of_dvd h _⟩
rwa [← natAbs_dvd_natAbs, ← Nat.pow_dvd_pow_iff k0, ← Int.natAbs_pow, ← Int.natAbs_pow,
natAbs_dvd_natAbs]
#align int.pow_dvd_pow_iff Int.pow_dvd_pow_iff
theorem gcd_dvd_iff {a b : ℤ} {n : ℕ} : gcd a b ∣ n ↔ ∃ x y : ℤ, ↑n = a * x + b * y := by
constructor
· intro h
rw [← Nat.mul_div_cancel' h, Int.ofNat_mul, gcd_eq_gcd_ab, Int.add_mul, mul_assoc, mul_assoc]
exact ⟨_, _, rfl⟩
· rintro ⟨x, y, h⟩
rw [← Int.natCast_dvd_natCast, h]
exact Int.dvd_add (dvd_mul_of_dvd_left gcd_dvd_left _) (dvd_mul_of_dvd_left gcd_dvd_right y)
#align int.gcd_dvd_iff Int.gcd_dvd_iff
theorem gcd_greatest {a b d : ℤ} (hd_pos : 0 ≤ d) (hda : d ∣ a) (hdb : d ∣ b)
(hd : ∀ e : ℤ, e ∣ a → e ∣ b → e ∣ d) : d = gcd a b :=
dvd_antisymm hd_pos (ofNat_zero_le (gcd a b)) (dvd_gcd hda hdb)
(hd _ gcd_dvd_left gcd_dvd_right)
#align int.gcd_greatest Int.gcd_greatest
/-- Euclid's lemma: if `a ∣ b * c` and `gcd a c = 1` then `a ∣ b`.
Compare with `IsCoprime.dvd_of_dvd_mul_left` and
`UniqueFactorizationMonoid.dvd_of_dvd_mul_left_of_no_prime_factors` -/
theorem dvd_of_dvd_mul_left_of_gcd_one {a b c : ℤ} (habc : a ∣ b * c) (hab : gcd a c = 1) :
a ∣ b := by
have := gcd_eq_gcd_ab a c
simp only [hab, Int.ofNat_zero, Int.ofNat_succ, zero_add] at this
have : b * a * gcdA a c + b * c * gcdB a c = b := by simp [mul_assoc, ← Int.mul_add, ← this]
rw [← this]
exact Int.dvd_add (dvd_mul_of_dvd_left (dvd_mul_left a b) _) (dvd_mul_of_dvd_left habc _)
#align int.dvd_of_dvd_mul_left_of_gcd_one Int.dvd_of_dvd_mul_left_of_gcd_one
/-- Euclid's lemma: if `a ∣ b * c` and `gcd a b = 1` then `a ∣ c`.
Compare with `IsCoprime.dvd_of_dvd_mul_right` and
`UniqueFactorizationMonoid.dvd_of_dvd_mul_right_of_no_prime_factors` -/
theorem dvd_of_dvd_mul_right_of_gcd_one {a b c : ℤ} (habc : a ∣ b * c) (hab : gcd a b = 1) :
a ∣ c := by
rw [mul_comm] at habc
exact dvd_of_dvd_mul_left_of_gcd_one habc hab
#align int.dvd_of_dvd_mul_right_of_gcd_one Int.dvd_of_dvd_mul_right_of_gcd_one
/-- For nonzero integers `a` and `b`, `gcd a b` is the smallest positive natural number that can be
written in the form `a * x + b * y` for some pair of integers `x` and `y` -/
| Mathlib/Data/Int/GCD.lean | 389 | 395 | theorem gcd_least_linear {a b : ℤ} (ha : a ≠ 0) :
IsLeast { n : ℕ | 0 < n ∧ ∃ x y : ℤ, ↑n = a * x + b * y } (a.gcd b) := by |
simp_rw [← gcd_dvd_iff]
constructor
· simpa [and_true_iff, dvd_refl, Set.mem_setOf_eq] using gcd_pos_of_ne_zero_left b ha
· simp only [lowerBounds, and_imp, Set.mem_setOf_eq]
exact fun n hn_pos hn => Nat.le_of_dvd hn_pos hn
|
/-
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
| Mathlib/LinearAlgebra/Span.lean | 578 | 580 | 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]
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Robert Y. Lewis
-/
import Mathlib.RingTheory.WittVector.Truncated
import Mathlib.RingTheory.WittVector.Identities
import Mathlib.NumberTheory.Padics.RingHoms
#align_import ring_theory.witt_vector.compare from "leanprover-community/mathlib"@"168ad7fc5d8173ad38be9767a22d50b8ecf1cd00"
/-!
# Comparison isomorphism between `WittVector p (ZMod p)` and `ℤ_[p]`
We construct a ring isomorphism between `WittVector p (ZMod p)` and `ℤ_[p]`.
This isomorphism follows from the fact that both satisfy the universal property
of the inverse limit of `ZMod (p^n)`.
## Main declarations
* `WittVector.toZModPow`: a family of compatible ring homs `𝕎 (ZMod p) → ZMod (p^k)`
* `WittVector.equiv`: the isomorphism
## References
* [Hazewinkel, *Witt Vectors*][Haze09]
* [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21]
-/
noncomputable section
variable {p : ℕ} [hp : Fact p.Prime]
local notation "𝕎" => WittVector p
namespace TruncatedWittVector
variable (p) (n : ℕ) (R : Type*) [CommRing R]
theorem eq_of_le_of_cast_pow_eq_zero [CharP R p] (i : ℕ) (hin : i ≤ n)
(hpi : (p : TruncatedWittVector p n R) ^ i = 0) : i = n := by
contrapose! hpi
replace hin := lt_of_le_of_ne hin hpi; clear hpi
have : (p : TruncatedWittVector p n R) ^ i = WittVector.truncate n ((p : 𝕎 R) ^ i) := by
rw [RingHom.map_pow, map_natCast]
rw [this, ne_eq, ext_iff, not_forall]; clear this
use ⟨i, hin⟩
rw [WittVector.coeff_truncate, coeff_zero, Fin.val_mk, WittVector.coeff_p_pow]
haveI : Nontrivial R := CharP.nontrivial_of_char_ne_one hp.1.ne_one
exact one_ne_zero
#align truncated_witt_vector.eq_of_le_of_cast_pow_eq_zero TruncatedWittVector.eq_of_le_of_cast_pow_eq_zero
section Iso
variable {R}
theorem card_zmod : Fintype.card (TruncatedWittVector p n (ZMod p)) = p ^ n := by
rw [card, ZMod.card]
#align truncated_witt_vector.card_zmod TruncatedWittVector.card_zmod
theorem charP_zmod : CharP (TruncatedWittVector p n (ZMod p)) (p ^ n) :=
charP_of_prime_pow_injective _ _ _ (card_zmod _ _) (eq_of_le_of_cast_pow_eq_zero p n (ZMod p))
#align truncated_witt_vector.char_p_zmod TruncatedWittVector.charP_zmod
attribute [local instance] charP_zmod
/-- The unique isomorphism between `ZMod p^n` and `TruncatedWittVector p n (ZMod p)`.
This isomorphism exists, because `TruncatedWittVector p n (ZMod p)` is a finite ring
with characteristic and cardinality `p^n`.
-/
def zmodEquivTrunc : ZMod (p ^ n) ≃+* TruncatedWittVector p n (ZMod p) :=
ZMod.ringEquiv (TruncatedWittVector p n (ZMod p)) (card_zmod _ _)
#align truncated_witt_vector.zmod_equiv_trunc TruncatedWittVector.zmodEquivTrunc
theorem zmodEquivTrunc_apply {x : ZMod (p ^ n)} :
zmodEquivTrunc p n x = ZMod.castHom (by rfl) (TruncatedWittVector p n (ZMod p)) x :=
rfl
#align truncated_witt_vector.zmod_equiv_trunc_apply TruncatedWittVector.zmodEquivTrunc_apply
/-- The following diagram commutes:
```text
zmod (p^n) ----------------------------> zmod (p^m)
| |
| |
v v
TruncatedWittVector p n (zmod p) ----> TruncatedWittVector p m (zmod p)
```
Here the vertical arrows are `TruncatedWittVector.zmodEquivTrunc`,
the horizontal arrow at the top is `ZMod.castHom`,
and the horizontal arrow at the bottom is `TruncatedWittVector.truncate`.
-/
theorem commutes {m : ℕ} (hm : n ≤ m) :
(truncate hm).comp (zmodEquivTrunc p m).toRingHom =
(zmodEquivTrunc p n).toRingHom.comp (ZMod.castHom (pow_dvd_pow p hm) _) :=
RingHom.ext_zmod _ _
#align truncated_witt_vector.commutes TruncatedWittVector.commutes
theorem commutes' {m : ℕ} (hm : n ≤ m) (x : ZMod (p ^ m)) :
truncate hm (zmodEquivTrunc p m x) = zmodEquivTrunc p n (ZMod.castHom (pow_dvd_pow p hm) _ x) :=
show (truncate hm).comp (zmodEquivTrunc p m).toRingHom x = _ by rw [commutes _ _ hm]; rfl
#align truncated_witt_vector.commutes' TruncatedWittVector.commutes'
theorem commutes_symm' {m : ℕ} (hm : n ≤ m) (x : TruncatedWittVector p m (ZMod p)) :
(zmodEquivTrunc p n).symm (truncate hm x) =
ZMod.castHom (pow_dvd_pow p hm) _ ((zmodEquivTrunc p m).symm x) := by
apply (zmodEquivTrunc p n).injective
rw [← commutes' _ _ hm]
simp
#align truncated_witt_vector.commutes_symm' TruncatedWittVector.commutes_symm'
/-- The following diagram commutes:
```text
TruncatedWittVector p n (zmod p) ----> TruncatedWittVector p m (zmod p)
| |
| |
v v
zmod (p^n) ----------------------------> zmod (p^m)
```
Here the vertical arrows are `(TruncatedWittVector.zmodEquivTrunc p _).symm`,
the horizontal arrow at the top is `ZMod.castHom`,
and the horizontal arrow at the bottom is `TruncatedWittVector.truncate`.
-/
theorem commutes_symm {m : ℕ} (hm : n ≤ m) :
(zmodEquivTrunc p n).symm.toRingHom.comp (truncate hm) =
(ZMod.castHom (pow_dvd_pow p hm) _).comp (zmodEquivTrunc p m).symm.toRingHom := by
ext; apply commutes_symm'
#align truncated_witt_vector.commutes_symm TruncatedWittVector.commutes_symm
end Iso
end TruncatedWittVector
namespace WittVector
open TruncatedWittVector
variable (p)
/-- `toZModPow` is a family of compatible ring homs. We get this family by composing
`TruncatedWittVector.zmodEquivTrunc` (in right-to-left direction) with `WittVector.truncate`. -/
def toZModPow (k : ℕ) : 𝕎 (ZMod p) →+* ZMod (p ^ k) :=
(zmodEquivTrunc p k).symm.toRingHom.comp (truncate k)
#align witt_vector.to_zmod_pow WittVector.toZModPow
theorem toZModPow_compat (m n : ℕ) (h : m ≤ n) :
(ZMod.castHom (pow_dvd_pow p h) (ZMod (p ^ m))).comp (toZModPow p n) = toZModPow p m :=
calc
(ZMod.castHom _ (ZMod (p ^ m))).comp ((zmodEquivTrunc p n).symm.toRingHom.comp (truncate n))
_ = ((zmodEquivTrunc p m).symm.toRingHom.comp (TruncatedWittVector.truncate h)).comp
(truncate n) := by
rw [commutes_symm, RingHom.comp_assoc]
_ = (zmodEquivTrunc p m).symm.toRingHom.comp (truncate m) := by
rw [RingHom.comp_assoc, truncate_comp_wittVector_truncate]
#align witt_vector.to_zmod_pow_compat WittVector.toZModPow_compat
/-- `toPadicInt` lifts `toZModPow : 𝕎 (ZMod p) →+* ZMod (p ^ k)` to a ring hom to `ℤ_[p]`
using `PadicInt.lift`, the universal property of `ℤ_[p]`.
-/
def toPadicInt : 𝕎 (ZMod p) →+* ℤ_[p] :=
PadicInt.lift <| toZModPow_compat p
#align witt_vector.to_padic_int WittVector.toPadicInt
theorem zmodEquivTrunc_compat (k₁ k₂ : ℕ) (hk : k₁ ≤ k₂) :
(TruncatedWittVector.truncate hk).comp
((zmodEquivTrunc p k₂).toRingHom.comp (PadicInt.toZModPow k₂)) =
(zmodEquivTrunc p k₁).toRingHom.comp (PadicInt.toZModPow k₁) := by
rw [← RingHom.comp_assoc, commutes, RingHom.comp_assoc,
PadicInt.zmod_cast_comp_toZModPow _ _ hk]
#align witt_vector.zmod_equiv_trunc_compat WittVector.zmodEquivTrunc_compat
/-- `fromPadicInt` uses `WittVector.lift` to lift `TruncatedWittVector.zmodEquivTrunc`
composed with `PadicInt.toZModPow` to a ring hom `ℤ_[p] →+* 𝕎 (ZMod p)`.
-/
def fromPadicInt : ℤ_[p] →+* 𝕎 (ZMod p) :=
(WittVector.lift fun k => (zmodEquivTrunc p k).toRingHom.comp (PadicInt.toZModPow k)) <|
zmodEquivTrunc_compat _
#align witt_vector.from_padic_int WittVector.fromPadicInt
theorem toPadicInt_comp_fromPadicInt : (toPadicInt p).comp (fromPadicInt p) = RingHom.id ℤ_[p] := by
rw [← PadicInt.toZModPow_eq_iff_ext]
intro n
rw [← RingHom.comp_assoc, toPadicInt, PadicInt.lift_spec]
simp only [fromPadicInt, toZModPow, RingHom.comp_id]
rw [RingHom.comp_assoc, truncate_comp_lift, ← RingHom.comp_assoc]
simp only [RingEquiv.symm_toRingHom_comp_toRingHom, RingHom.id_comp]
#align witt_vector.to_padic_int_comp_from_padic_int WittVector.toPadicInt_comp_fromPadicInt
theorem toPadicInt_comp_fromPadicInt_ext (x) :
(toPadicInt p).comp (fromPadicInt p) x = RingHom.id ℤ_[p] x := by
rw [toPadicInt_comp_fromPadicInt]
#align witt_vector.to_padic_int_comp_from_padic_int_ext WittVector.toPadicInt_comp_fromPadicInt_ext
theorem fromPadicInt_comp_toPadicInt :
(fromPadicInt p).comp (toPadicInt p) = RingHom.id (𝕎 (ZMod p)) := by
apply WittVector.hom_ext
intro n
rw [fromPadicInt, ← RingHom.comp_assoc, truncate_comp_lift, RingHom.comp_assoc]
simp only [toPadicInt, toZModPow, RingHom.comp_id, PadicInt.lift_spec, RingHom.id_comp, ←
RingHom.comp_assoc, RingEquiv.toRingHom_comp_symm_toRingHom]
#align witt_vector.from_padic_int_comp_to_padic_int WittVector.fromPadicInt_comp_toPadicInt
| Mathlib/RingTheory/WittVector/Compare.lean | 206 | 208 | theorem fromPadicInt_comp_toPadicInt_ext (x) :
(fromPadicInt p).comp (toPadicInt p) x = RingHom.id (𝕎 (ZMod p)) x := by |
rw [fromPadicInt_comp_toPadicInt]
|
/-
Copyright (c) 2024 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Order.Sublattice
import Mathlib.Order.Hom.CompleteLattice
/-!
# Complete Sublattices
This file defines complete sublattices. These are subsets of complete lattices which are closed
under arbitrary suprema and infima. As a standard example one could take the complete sublattice of
invariant submodules of some module with respect to a linear map.
## Main definitions:
* `CompleteSublattice`: the definition of a complete sublattice
* `CompleteSublattice.mk'`: an alternate constructor for a complete sublattice, demanding fewer
hypotheses
* `CompleteSublattice.instCompleteLattice`: a complete sublattice is a complete lattice
* `CompleteSublattice.map`: complete sublattices push forward under complete lattice morphisms.
* `CompleteSublattice.comap`: complete sublattices pull back under complete lattice morphisms.
-/
open Function Set
variable (α β : Type*) [CompleteLattice α] [CompleteLattice β] (f : CompleteLatticeHom α β)
/-- A complete sublattice is a subset of a complete lattice that is closed under arbitrary suprema
and infima. -/
structure CompleteSublattice extends Sublattice α where
sSupClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sSup s ∈ carrier
sInfClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sInf s ∈ carrier
variable {α β}
namespace CompleteSublattice
/-- To check that a subset is a complete sublattice, one does not need to check that it is closed
under binary `Sup` since this follows from the stronger `sSup` condition. Likewise for infima. -/
@[simps] def mk' (carrier : Set α)
(sSupClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sSup s ∈ carrier)
(sInfClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sInf s ∈ carrier) :
CompleteSublattice α where
carrier := carrier
sSupClosed' := sSupClosed'
sInfClosed' := sInfClosed'
supClosed' := fun x hx y hy ↦ by
suffices x ⊔ y = sSup {x, y} by exact this ▸ sSupClosed' (fun z hz ↦ by aesop)
simp [sSup_singleton]
infClosed' := fun x hx y hy ↦ by
suffices x ⊓ y = sInf {x, y} by exact this ▸ sInfClosed' (fun z hz ↦ by aesop)
simp [sInf_singleton]
variable {L : CompleteSublattice α}
instance instSetLike : SetLike (CompleteSublattice α) α where
coe L := L.carrier
coe_injective' L M h := by cases L; cases M; congr; exact SetLike.coe_injective' h
instance instBot : Bot L where
bot := ⟨⊥, by simpa using L.sSupClosed' <| empty_subset _⟩
instance instTop : Top L where
top := ⟨⊤, by simpa using L.sInfClosed' <| empty_subset _⟩
instance instSupSet : SupSet L where
sSup s := ⟨sSup s, L.sSupClosed' image_val_subset⟩
instance instInfSet : InfSet L where
sInf s := ⟨sInf s, L.sInfClosed' image_val_subset⟩
theorem sSupClosed {s : Set α} (h : s ⊆ L) : sSup s ∈ L := L.sSupClosed' h
theorem sInfClosed {s : Set α} (h : s ⊆ L) : sInf s ∈ L := L.sInfClosed' h
@[simp] theorem coe_bot : (↑(⊥ : L) : α) = ⊥ := rfl
@[simp] theorem coe_top : (↑(⊤ : L) : α) = ⊤ := rfl
@[simp] theorem coe_sSup (S : Set L) : (↑(sSup S) : α) = sSup {(s : α) | s ∈ S} := rfl
theorem coe_sSup' (S : Set L) : (↑(sSup S) : α) = ⨆ N ∈ S, (N : α) := by
rw [coe_sSup, ← Set.image, sSup_image]
@[simp] theorem coe_sInf (S : Set L) : (↑(sInf S) : α) = sInf {(s : α) | s ∈ S} := rfl
| Mathlib/Order/CompleteSublattice.lean | 89 | 90 | theorem coe_sInf' (S : Set L) : (↑(sInf S) : α) = ⨅ N ∈ S, (N : α) := by |
rw [coe_sInf, ← Set.image, sInf_image]
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Finset.Image
import Mathlib.Data.List.FinRange
#align_import data.fintype.basic from "leanprover-community/mathlib"@"d78597269638367c3863d40d45108f52207e03cf"
/-!
# Finite types
This file defines a typeclass to state that a type is finite.
## Main declarations
* `Fintype α`: Typeclass saying that a type is finite. It takes as fields a `Finset` and a proof
that all terms of type `α` are in it.
* `Finset.univ`: The finset of all elements of a fintype.
See `Data.Fintype.Card` for the cardinality of a fintype,
the equivalence with `Fin (Fintype.card α)`, and pigeonhole principles.
## Instances
Instances for `Fintype` for
* `{x // p x}` are in this file as `Fintype.subtype`
* `Option α` are in `Data.Fintype.Option`
* `α × β` are in `Data.Fintype.Prod`
* `α ⊕ β` are in `Data.Fintype.Sum`
* `Σ (a : α), β a` are in `Data.Fintype.Sigma`
These files also contain appropriate `Infinite` instances for these types.
`Infinite` instances for `ℕ`, `ℤ`, `Multiset α`, and `List α` are in `Data.Fintype.Lattice`.
Types which have a surjection from/an injection to a `Fintype` are themselves fintypes.
See `Fintype.ofInjective` and `Fintype.ofSurjective`.
-/
assert_not_exists MonoidWithZero
assert_not_exists MulAction
open Function
open Nat
universe u v
variable {α β γ : Type*}
/-- `Fintype α` means that `α` is finite, i.e. there are only
finitely many distinct elements of type `α`. The evidence of this
is a finset `elems` (a list up to permutation without duplicates),
together with a proof that everything of type `α` is in the list. -/
class Fintype (α : Type*) where
/-- The `Finset` containing all elements of a `Fintype` -/
elems : Finset α
/-- A proof that `elems` contains every element of the type -/
complete : ∀ x : α, x ∈ elems
#align fintype Fintype
namespace Finset
variable [Fintype α] {s t : Finset α}
/-- `univ` is the universal finite set of type `Finset α` implied from
the assumption `Fintype α`. -/
def univ : Finset α :=
@Fintype.elems α _
#align finset.univ Finset.univ
@[simp]
theorem mem_univ (x : α) : x ∈ (univ : Finset α) :=
Fintype.complete x
#align finset.mem_univ Finset.mem_univ
-- Porting note: removing @[simp], simp can prove it
theorem mem_univ_val : ∀ x, x ∈ (univ : Finset α).1 :=
mem_univ
#align finset.mem_univ_val Finset.mem_univ_val
theorem eq_univ_iff_forall : s = univ ↔ ∀ x, x ∈ s := by simp [ext_iff]
#align finset.eq_univ_iff_forall Finset.eq_univ_iff_forall
theorem eq_univ_of_forall : (∀ x, x ∈ s) → s = univ :=
eq_univ_iff_forall.2
#align finset.eq_univ_of_forall Finset.eq_univ_of_forall
@[simp, norm_cast]
theorem coe_univ : ↑(univ : Finset α) = (Set.univ : Set α) := by ext; simp
#align finset.coe_univ Finset.coe_univ
@[simp, norm_cast]
theorem coe_eq_univ : (s : Set α) = Set.univ ↔ s = univ := by rw [← coe_univ, coe_inj]
#align finset.coe_eq_univ Finset.coe_eq_univ
theorem Nonempty.eq_univ [Subsingleton α] : s.Nonempty → s = univ := by
rintro ⟨x, hx⟩
exact eq_univ_of_forall fun y => by rwa [Subsingleton.elim y x]
#align finset.nonempty.eq_univ Finset.Nonempty.eq_univ
theorem univ_nonempty_iff : (univ : Finset α).Nonempty ↔ Nonempty α := by
rw [← coe_nonempty, coe_univ, Set.nonempty_iff_univ_nonempty]
#align finset.univ_nonempty_iff Finset.univ_nonempty_iff
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem univ_nonempty [Nonempty α] : (univ : Finset α).Nonempty :=
univ_nonempty_iff.2 ‹_›
#align finset.univ_nonempty Finset.univ_nonempty
theorem univ_eq_empty_iff : (univ : Finset α) = ∅ ↔ IsEmpty α := by
rw [← not_nonempty_iff, ← univ_nonempty_iff, not_nonempty_iff_eq_empty]
#align finset.univ_eq_empty_iff Finset.univ_eq_empty_iff
@[simp]
theorem univ_eq_empty [IsEmpty α] : (univ : Finset α) = ∅ :=
univ_eq_empty_iff.2 ‹_›
#align finset.univ_eq_empty Finset.univ_eq_empty
@[simp]
theorem univ_unique [Unique α] : (univ : Finset α) = {default} :=
Finset.ext fun x => iff_of_true (mem_univ _) <| mem_singleton.2 <| Subsingleton.elim x default
#align finset.univ_unique Finset.univ_unique
@[simp]
theorem subset_univ (s : Finset α) : s ⊆ univ := fun a _ => mem_univ a
#align finset.subset_univ Finset.subset_univ
instance boundedOrder : BoundedOrder (Finset α) :=
{ inferInstanceAs (OrderBot (Finset α)) with
top := univ
le_top := subset_univ }
#align finset.bounded_order Finset.boundedOrder
@[simp]
theorem top_eq_univ : (⊤ : Finset α) = univ :=
rfl
#align finset.top_eq_univ Finset.top_eq_univ
theorem ssubset_univ_iff {s : Finset α} : s ⊂ univ ↔ s ≠ univ :=
@lt_top_iff_ne_top _ _ _ s
#align finset.ssubset_univ_iff Finset.ssubset_univ_iff
@[simp]
theorem univ_subset_iff {s : Finset α} : univ ⊆ s ↔ s = univ :=
@top_le_iff _ _ _ s
theorem codisjoint_left : Codisjoint s t ↔ ∀ ⦃a⦄, a ∉ s → a ∈ t := by
classical simp [codisjoint_iff, eq_univ_iff_forall, or_iff_not_imp_left]
#align finset.codisjoint_left Finset.codisjoint_left
theorem codisjoint_right : Codisjoint s t ↔ ∀ ⦃a⦄, a ∉ t → a ∈ s :=
Codisjoint_comm.trans codisjoint_left
#align finset.codisjoint_right Finset.codisjoint_right
section BooleanAlgebra
variable [DecidableEq α] {a : α}
instance booleanAlgebra : BooleanAlgebra (Finset α) :=
GeneralizedBooleanAlgebra.toBooleanAlgebra
#align finset.boolean_algebra Finset.booleanAlgebra
theorem sdiff_eq_inter_compl (s t : Finset α) : s \ t = s ∩ tᶜ :=
sdiff_eq
#align finset.sdiff_eq_inter_compl Finset.sdiff_eq_inter_compl
theorem compl_eq_univ_sdiff (s : Finset α) : sᶜ = univ \ s :=
rfl
#align finset.compl_eq_univ_sdiff Finset.compl_eq_univ_sdiff
@[simp]
theorem mem_compl : a ∈ sᶜ ↔ a ∉ s := by simp [compl_eq_univ_sdiff]
#align finset.mem_compl Finset.mem_compl
theorem not_mem_compl : a ∉ sᶜ ↔ a ∈ s := by rw [mem_compl, not_not]
#align finset.not_mem_compl Finset.not_mem_compl
@[simp, norm_cast]
theorem coe_compl (s : Finset α) : ↑sᶜ = (↑s : Set α)ᶜ :=
Set.ext fun _ => mem_compl
#align finset.coe_compl Finset.coe_compl
@[simp] lemma compl_subset_compl : sᶜ ⊆ tᶜ ↔ t ⊆ s := @compl_le_compl_iff_le (Finset α) _ _ _
@[simp] lemma compl_ssubset_compl : sᶜ ⊂ tᶜ ↔ t ⊂ s := @compl_lt_compl_iff_lt (Finset α) _ _ _
lemma subset_compl_comm : s ⊆ tᶜ ↔ t ⊆ sᶜ := le_compl_iff_le_compl (α := Finset α)
@[simp] lemma subset_compl_singleton : s ⊆ {a}ᶜ ↔ a ∉ s := by
rw [subset_compl_comm, singleton_subset_iff, mem_compl]
@[simp]
theorem compl_empty : (∅ : Finset α)ᶜ = univ :=
compl_bot
#align finset.compl_empty Finset.compl_empty
@[simp]
theorem compl_univ : (univ : Finset α)ᶜ = ∅ :=
compl_top
#align finset.compl_univ Finset.compl_univ
@[simp]
theorem compl_eq_empty_iff (s : Finset α) : sᶜ = ∅ ↔ s = univ :=
compl_eq_bot
#align finset.compl_eq_empty_iff Finset.compl_eq_empty_iff
@[simp]
theorem compl_eq_univ_iff (s : Finset α) : sᶜ = univ ↔ s = ∅ :=
compl_eq_top
#align finset.compl_eq_univ_iff Finset.compl_eq_univ_iff
@[simp]
theorem union_compl (s : Finset α) : s ∪ sᶜ = univ :=
sup_compl_eq_top
#align finset.union_compl Finset.union_compl
@[simp]
theorem inter_compl (s : Finset α) : s ∩ sᶜ = ∅ :=
inf_compl_eq_bot
#align finset.inter_compl Finset.inter_compl
@[simp]
theorem compl_union (s t : Finset α) : (s ∪ t)ᶜ = sᶜ ∩ tᶜ :=
compl_sup
#align finset.compl_union Finset.compl_union
@[simp]
theorem compl_inter (s t : Finset α) : (s ∩ t)ᶜ = sᶜ ∪ tᶜ :=
compl_inf
#align finset.compl_inter Finset.compl_inter
@[simp]
theorem compl_erase : (s.erase a)ᶜ = insert a sᶜ := by
ext
simp only [or_iff_not_imp_left, mem_insert, not_and, mem_compl, mem_erase]
#align finset.compl_erase Finset.compl_erase
@[simp]
theorem compl_insert : (insert a s)ᶜ = sᶜ.erase a := by
ext
simp only [not_or, mem_insert, iff_self_iff, mem_compl, mem_erase]
#align finset.compl_insert Finset.compl_insert
theorem insert_compl_insert (ha : a ∉ s) : insert a (insert a s)ᶜ = sᶜ := by
simp_rw [compl_insert, insert_erase (mem_compl.2 ha)]
@[simp]
theorem insert_compl_self (x : α) : insert x ({x}ᶜ : Finset α) = univ := by
rw [← compl_erase, erase_singleton, compl_empty]
#align finset.insert_compl_self Finset.insert_compl_self
@[simp]
theorem compl_filter (p : α → Prop) [DecidablePred p] [∀ x, Decidable ¬p x] :
(univ.filter p)ᶜ = univ.filter fun x => ¬p x :=
ext <| by simp
#align finset.compl_filter Finset.compl_filter
theorem compl_ne_univ_iff_nonempty (s : Finset α) : sᶜ ≠ univ ↔ s.Nonempty := by
simp [eq_univ_iff_forall, Finset.Nonempty]
#align finset.compl_ne_univ_iff_nonempty Finset.compl_ne_univ_iff_nonempty
theorem compl_singleton (a : α) : ({a} : Finset α)ᶜ = univ.erase a := by
rw [compl_eq_univ_sdiff, sdiff_singleton_eq_erase]
#align finset.compl_singleton Finset.compl_singleton
theorem insert_inj_on' (s : Finset α) : Set.InjOn (fun a => insert a s) (sᶜ : Finset α) := by
rw [coe_compl]
exact s.insert_inj_on
#align finset.insert_inj_on' Finset.insert_inj_on'
theorem image_univ_of_surjective [Fintype β] {f : β → α} (hf : Surjective f) :
univ.image f = univ :=
eq_univ_of_forall <| hf.forall.2 fun _ => mem_image_of_mem _ <| mem_univ _
#align finset.image_univ_of_surjective Finset.image_univ_of_surjective
@[simp]
theorem image_univ_equiv [Fintype β] (f : β ≃ α) : univ.image f = univ :=
Finset.image_univ_of_surjective f.surjective
@[simp] lemma univ_inter (s : Finset α) : univ ∩ s = s := by ext a; simp
#align finset.univ_inter Finset.univ_inter
@[simp] lemma inter_univ (s : Finset α) : s ∩ univ = s := by rw [inter_comm, univ_inter]
#align finset.inter_univ Finset.inter_univ
@[simp] lemma inter_eq_univ : s ∩ t = univ ↔ s = univ ∧ t = univ := inf_eq_top_iff
end BooleanAlgebra
-- @[simp] --Note this would loop with `Finset.univ_unique`
lemma singleton_eq_univ [Subsingleton α] (a : α) : ({a} : Finset α) = univ := by
ext b; simp [Subsingleton.elim a b]
theorem map_univ_of_surjective [Fintype β] {f : β ↪ α} (hf : Surjective f) : univ.map f = univ :=
eq_univ_of_forall <| hf.forall.2 fun _ => mem_map_of_mem _ <| mem_univ _
#align finset.map_univ_of_surjective Finset.map_univ_of_surjective
@[simp]
theorem map_univ_equiv [Fintype β] (f : β ≃ α) : univ.map f.toEmbedding = univ :=
map_univ_of_surjective f.surjective
#align finset.map_univ_equiv Finset.map_univ_equiv
theorem univ_map_equiv_to_embedding {α β : Type*} [Fintype α] [Fintype β] (e : α ≃ β) :
univ.map e.toEmbedding = univ :=
eq_univ_iff_forall.mpr fun b => mem_map.mpr ⟨e.symm b, mem_univ _, by simp⟩
#align finset.univ_map_equiv_to_embedding Finset.univ_map_equiv_to_embedding
@[simp]
theorem univ_filter_exists (f : α → β) [Fintype β] [DecidablePred fun y => ∃ x, f x = y]
[DecidableEq β] : (Finset.univ.filter fun y => ∃ x, f x = y) = Finset.univ.image f := by
ext
simp
#align finset.univ_filter_exists Finset.univ_filter_exists
/-- Note this is a special case of `(Finset.image_preimage f univ _).symm`. -/
theorem univ_filter_mem_range (f : α → β) [Fintype β] [DecidablePred fun y => y ∈ Set.range f]
[DecidableEq β] : (Finset.univ.filter fun y => y ∈ Set.range f) = Finset.univ.image f := by
letI : DecidablePred (fun y => ∃ x, f x = y) := by simpa using ‹_›
exact univ_filter_exists f
#align finset.univ_filter_mem_range Finset.univ_filter_mem_range
theorem coe_filter_univ (p : α → Prop) [DecidablePred p] :
(univ.filter p : Set α) = { x | p x } := by simp
#align finset.coe_filter_univ Finset.coe_filter_univ
@[simp] lemma subtype_eq_univ {p : α → Prop} [DecidablePred p] [Fintype {a // p a}] :
s.subtype p = univ ↔ ∀ ⦃a⦄, p a → a ∈ s := by simp [ext_iff]
@[simp] lemma subtype_univ [Fintype α] (p : α → Prop) [DecidablePred p] [Fintype {a // p a}] :
univ.subtype p = univ := by simp
end Finset
open Finset Function
namespace Fintype
instance decidablePiFintype {α} {β : α → Type*} [∀ a, DecidableEq (β a)] [Fintype α] :
DecidableEq (∀ a, β a) := fun f g =>
decidable_of_iff (∀ a ∈ @Fintype.elems α _, f a = g a)
(by simp [Function.funext_iff, Fintype.complete])
#align fintype.decidable_pi_fintype Fintype.decidablePiFintype
instance decidableForallFintype {p : α → Prop} [DecidablePred p] [Fintype α] :
Decidable (∀ a, p a) :=
decidable_of_iff (∀ a ∈ @univ α _, p a) (by simp)
#align fintype.decidable_forall_fintype Fintype.decidableForallFintype
instance decidableExistsFintype {p : α → Prop} [DecidablePred p] [Fintype α] :
Decidable (∃ a, p a) :=
decidable_of_iff (∃ a ∈ @univ α _, p a) (by simp)
#align fintype.decidable_exists_fintype Fintype.decidableExistsFintype
instance decidableMemRangeFintype [Fintype α] [DecidableEq β] (f : α → β) :
DecidablePred (· ∈ Set.range f) := fun _ => Fintype.decidableExistsFintype
#align fintype.decidable_mem_range_fintype Fintype.decidableMemRangeFintype
instance decidableSubsingleton [Fintype α] [DecidableEq α] {s : Set α} [DecidablePred (· ∈ s)] :
Decidable s.Subsingleton := decidable_of_iff (∀ a ∈ s, ∀ b ∈ s, a = b) Iff.rfl
section BundledHoms
instance decidableEqEquivFintype [DecidableEq β] [Fintype α] : DecidableEq (α ≃ β) := fun a b =>
decidable_of_iff (a.1 = b.1) Equiv.coe_fn_injective.eq_iff
#align fintype.decidable_eq_equiv_fintype Fintype.decidableEqEquivFintype
instance decidableEqEmbeddingFintype [DecidableEq β] [Fintype α] : DecidableEq (α ↪ β) := fun a b =>
decidable_of_iff ((a : α → β) = b) Function.Embedding.coe_injective.eq_iff
#align fintype.decidable_eq_embedding_fintype Fintype.decidableEqEmbeddingFintype
end BundledHoms
instance decidableInjectiveFintype [DecidableEq α] [DecidableEq β] [Fintype α] :
DecidablePred (Injective : (α → β) → Prop) := fun x => by unfold Injective; infer_instance
#align fintype.decidable_injective_fintype Fintype.decidableInjectiveFintype
instance decidableSurjectiveFintype [DecidableEq β] [Fintype α] [Fintype β] :
DecidablePred (Surjective : (α → β) → Prop) := fun x => by unfold Surjective; infer_instance
#align fintype.decidable_surjective_fintype Fintype.decidableSurjectiveFintype
instance decidableBijectiveFintype [DecidableEq α] [DecidableEq β] [Fintype α] [Fintype β] :
DecidablePred (Bijective : (α → β) → Prop) := fun x => by unfold Bijective; infer_instance
#align fintype.decidable_bijective_fintype Fintype.decidableBijectiveFintype
instance decidableRightInverseFintype [DecidableEq α] [Fintype α] (f : α → β) (g : β → α) :
Decidable (Function.RightInverse f g) :=
show Decidable (∀ x, g (f x) = x) by infer_instance
#align fintype.decidable_right_inverse_fintype Fintype.decidableRightInverseFintype
instance decidableLeftInverseFintype [DecidableEq β] [Fintype β] (f : α → β) (g : β → α) :
Decidable (Function.LeftInverse f g) :=
show Decidable (∀ x, f (g x) = x) by infer_instance
#align fintype.decidable_left_inverse_fintype Fintype.decidableLeftInverseFintype
/-- Construct a proof of `Fintype α` from a universal multiset -/
def ofMultiset [DecidableEq α] (s : Multiset α) (H : ∀ x : α, x ∈ s) : Fintype α :=
⟨s.toFinset, by simpa using H⟩
#align fintype.of_multiset Fintype.ofMultiset
/-- Construct a proof of `Fintype α` from a universal list -/
def ofList [DecidableEq α] (l : List α) (H : ∀ x : α, x ∈ l) : Fintype α :=
⟨l.toFinset, by simpa using H⟩
#align fintype.of_list Fintype.ofList
instance subsingleton (α : Type*) : Subsingleton (Fintype α) :=
⟨fun ⟨s₁, h₁⟩ ⟨s₂, h₂⟩ => by congr; simp [Finset.ext_iff, h₁, h₂]⟩
#align fintype.subsingleton Fintype.subsingleton
instance (α : Type*) : Lean.Meta.FastSubsingleton (Fintype α) := {}
/-- Given a predicate that can be represented by a finset, the subtype
associated to the predicate is a fintype. -/
protected def subtype {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x) :
Fintype { x // p x } :=
⟨⟨s.1.pmap Subtype.mk fun x => (H x).1, s.nodup.pmap fun _ _ _ _ => congr_arg Subtype.val⟩,
fun ⟨x, px⟩ => Multiset.mem_pmap.2 ⟨x, (H x).2 px, rfl⟩⟩
#align fintype.subtype Fintype.subtype
/-- Construct a fintype from a finset with the same elements. -/
def ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) : Fintype p :=
Fintype.subtype s H
#align fintype.of_finset Fintype.ofFinset
/-- If `f : α → β` is a bijection and `α` is a fintype, then `β` is also a fintype. -/
def ofBijective [Fintype α] (f : α → β) (H : Function.Bijective f) : Fintype β :=
⟨univ.map ⟨f, H.1⟩, fun b =>
let ⟨_, e⟩ := H.2 b
e ▸ mem_map_of_mem _ (mem_univ _)⟩
#align fintype.of_bijective Fintype.ofBijective
/-- If `f : α → β` is a surjection and `α` is a fintype, then `β` is also a fintype. -/
def ofSurjective [DecidableEq β] [Fintype α] (f : α → β) (H : Function.Surjective f) : Fintype β :=
⟨univ.image f, fun b =>
let ⟨_, e⟩ := H b
e ▸ mem_image_of_mem _ (mem_univ _)⟩
#align fintype.of_surjective Fintype.ofSurjective
end Fintype
namespace Finset
variable [Fintype α] [DecidableEq α] {s t : Finset α}
@[simp]
lemma filter_univ_mem (s : Finset α) : univ.filter (· ∈ s) = s := by simp [filter_mem_eq_inter]
instance decidableCodisjoint : Decidable (Codisjoint s t) :=
decidable_of_iff _ codisjoint_left.symm
#align finset.decidable_codisjoint Finset.decidableCodisjoint
instance decidableIsCompl : Decidable (IsCompl s t) :=
decidable_of_iff' _ isCompl_iff
#align finset.decidable_is_compl Finset.decidableIsCompl
end Finset
section Inv
namespace Function
variable [Fintype α] [DecidableEq β]
namespace Injective
variable {f : α → β} (hf : Function.Injective f)
/-- The inverse of an `hf : injective` function `f : α → β`, of the type `↥(Set.range f) → α`.
This is the computable version of `Function.invFun` that requires `Fintype α` and `DecidableEq β`,
or the function version of applying `(Equiv.ofInjective f hf).symm`.
This function should not usually be used for actual computation because for most cases,
an explicit inverse can be stated that has better computational properties.
This function computes by checking all terms `a : α` to find the `f a = b`, so it is O(N) where
`N = Fintype.card α`.
-/
def invOfMemRange : Set.range f → α := fun b =>
Finset.choose (fun a => f a = b) Finset.univ
((exists_unique_congr (by simp)).mp (hf.exists_unique_of_mem_range b.property))
#align function.injective.inv_of_mem_range Function.Injective.invOfMemRange
theorem left_inv_of_invOfMemRange (b : Set.range f) : f (hf.invOfMemRange b) = b :=
(Finset.choose_spec (fun a => f a = b) _ _).right
#align function.injective.left_inv_of_inv_of_mem_range Function.Injective.left_inv_of_invOfMemRange
@[simp]
theorem right_inv_of_invOfMemRange (a : α) : hf.invOfMemRange ⟨f a, Set.mem_range_self a⟩ = a :=
hf (Finset.choose_spec (fun a' => f a' = f a) _ _).right
#align function.injective.right_inv_of_inv_of_mem_range Function.Injective.right_inv_of_invOfMemRange
theorem invFun_restrict [Nonempty α] : (Set.range f).restrict (invFun f) = hf.invOfMemRange := by
ext ⟨b, h⟩
apply hf
simp [hf.left_inv_of_invOfMemRange, @invFun_eq _ _ _ f b (Set.mem_range.mp h)]
#align function.injective.inv_fun_restrict Function.Injective.invFun_restrict
theorem invOfMemRange_surjective : Function.Surjective hf.invOfMemRange := fun a =>
⟨⟨f a, Set.mem_range_self a⟩, by simp⟩
#align function.injective.inv_of_mem_range_surjective Function.Injective.invOfMemRange_surjective
end Injective
namespace Embedding
variable (f : α ↪ β) (b : Set.range f)
/-- The inverse of an embedding `f : α ↪ β`, of the type `↥(Set.range f) → α`.
This is the computable version of `Function.invFun` that requires `Fintype α` and `DecidableEq β`,
or the function version of applying `(Equiv.ofInjective f f.injective).symm`.
This function should not usually be used for actual computation because for most cases,
an explicit inverse can be stated that has better computational properties.
This function computes by checking all terms `a : α` to find the `f a = b`, so it is O(N) where
`N = Fintype.card α`.
-/
def invOfMemRange : α :=
f.injective.invOfMemRange b
#align function.embedding.inv_of_mem_range Function.Embedding.invOfMemRange
@[simp]
theorem left_inv_of_invOfMemRange : f (f.invOfMemRange b) = b :=
f.injective.left_inv_of_invOfMemRange b
#align function.embedding.left_inv_of_inv_of_mem_range Function.Embedding.left_inv_of_invOfMemRange
@[simp]
theorem right_inv_of_invOfMemRange (a : α) : f.invOfMemRange ⟨f a, Set.mem_range_self a⟩ = a :=
f.injective.right_inv_of_invOfMemRange a
#align function.embedding.right_inv_of_inv_of_mem_range Function.Embedding.right_inv_of_invOfMemRange
theorem invFun_restrict [Nonempty α] : (Set.range f).restrict (invFun f) = f.invOfMemRange := by
ext ⟨b, h⟩
apply f.injective
simp [f.left_inv_of_invOfMemRange, @invFun_eq _ _ _ f b (Set.mem_range.mp h)]
#align function.embedding.inv_fun_restrict Function.Embedding.invFun_restrict
theorem invOfMemRange_surjective : Function.Surjective f.invOfMemRange := fun a =>
⟨⟨f a, Set.mem_range_self a⟩, by simp⟩
#align function.embedding.inv_of_mem_range_surjective Function.Embedding.invOfMemRange_surjective
end Embedding
end Function
end Inv
namespace Fintype
/-- Given an injective function to a fintype, the domain is also a
fintype. This is noncomputable because injectivity alone cannot be
used to construct preimages. -/
noncomputable def ofInjective [Fintype β] (f : α → β) (H : Function.Injective f) : Fintype α :=
letI := Classical.dec
if hα : Nonempty α then
letI := Classical.inhabited_of_nonempty hα
ofSurjective (invFun f) (invFun_surjective H)
else ⟨∅, fun x => (hα ⟨x⟩).elim⟩
#align fintype.of_injective Fintype.ofInjective
/-- If `f : α ≃ β` and `α` is a fintype, then `β` is also a fintype. -/
def ofEquiv (α : Type*) [Fintype α] (f : α ≃ β) : Fintype β :=
ofBijective _ f.bijective
#align fintype.of_equiv Fintype.ofEquiv
/-- Any subsingleton type with a witness is a fintype (with one term). -/
def ofSubsingleton (a : α) [Subsingleton α] : Fintype α :=
⟨{a}, fun _ => Finset.mem_singleton.2 (Subsingleton.elim _ _)⟩
#align fintype.of_subsingleton Fintype.ofSubsingleton
@[simp]
theorem univ_ofSubsingleton (a : α) [Subsingleton α] : @univ _ (ofSubsingleton a) = {a} :=
rfl
#align fintype.univ_of_subsingleton Fintype.univ_ofSubsingleton
/-- An empty type is a fintype. Not registered as an instance, to make sure that there aren't two
conflicting `Fintype ι` instances around when casing over whether a fintype `ι` is empty or not. -/
def ofIsEmpty [IsEmpty α] : Fintype α :=
⟨∅, isEmptyElim⟩
#align fintype.of_is_empty Fintype.ofIsEmpty
/-- Note: this lemma is specifically about `Fintype.ofIsEmpty`. For a statement about
arbitrary `Fintype` instances, use `Finset.univ_eq_empty`. -/
theorem univ_ofIsEmpty [IsEmpty α] : @univ α Fintype.ofIsEmpty = ∅ :=
rfl
#align fintype.univ_of_is_empty Fintype.univ_ofIsEmpty
instance : Fintype Empty := Fintype.ofIsEmpty
instance : Fintype PEmpty := Fintype.ofIsEmpty
end Fintype
namespace Set
variable {s t : Set α}
/-- Construct a finset enumerating a set `s`, given a `Fintype` instance. -/
def toFinset (s : Set α) [Fintype s] : Finset α :=
(@Finset.univ s _).map <| Function.Embedding.subtype _
#align set.to_finset Set.toFinset
@[congr]
theorem toFinset_congr {s t : Set α} [Fintype s] [Fintype t] (h : s = t) :
toFinset s = toFinset t := by subst h; congr; exact Subsingleton.elim _ _
#align set.to_finset_congr Set.toFinset_congr
@[simp]
theorem mem_toFinset {s : Set α} [Fintype s] {a : α} : a ∈ s.toFinset ↔ a ∈ s := by
simp [toFinset]
#align set.mem_to_finset Set.mem_toFinset
/-- Many `Fintype` instances for sets are defined using an extensionally equal `Finset`.
Rewriting `s.toFinset` with `Set.toFinset_ofFinset` replaces the term with such a `Finset`. -/
theorem toFinset_ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) :
@Set.toFinset _ p (Fintype.ofFinset s H) = s :=
Finset.ext fun x => by rw [@mem_toFinset _ _ (id _), H]
#align set.to_finset_of_finset Set.toFinset_ofFinset
/-- Membership of a set with a `Fintype` instance is decidable.
Using this as an instance leads to potential loops with `Subtype.fintype` under certain decidability
assumptions, so it should only be declared a local instance. -/
def decidableMemOfFintype [DecidableEq α] (s : Set α) [Fintype s] (a) : Decidable (a ∈ s) :=
decidable_of_iff _ mem_toFinset
#align set.decidable_mem_of_fintype Set.decidableMemOfFintype
@[simp]
theorem coe_toFinset (s : Set α) [Fintype s] : (↑s.toFinset : Set α) = s :=
Set.ext fun _ => mem_toFinset
#align set.coe_to_finset Set.coe_toFinset
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem toFinset_nonempty {s : Set α} [Fintype s] : s.toFinset.Nonempty ↔ s.Nonempty := by
rw [← Finset.coe_nonempty, coe_toFinset]
#align set.to_finset_nonempty Set.toFinset_nonempty
@[simp]
theorem toFinset_inj {s t : Set α} [Fintype s] [Fintype t] : s.toFinset = t.toFinset ↔ s = t :=
⟨fun h => by rw [← s.coe_toFinset, h, t.coe_toFinset], fun h => by simp [h]⟩
#align set.to_finset_inj Set.toFinset_inj
@[mono]
theorem toFinset_subset_toFinset [Fintype s] [Fintype t] : s.toFinset ⊆ t.toFinset ↔ s ⊆ t := by
simp [Finset.subset_iff, Set.subset_def]
#align set.to_finset_subset_to_finset Set.toFinset_subset_toFinset
@[simp]
theorem toFinset_ssubset [Fintype s] {t : Finset α} : s.toFinset ⊂ t ↔ s ⊂ t := by
rw [← Finset.coe_ssubset, coe_toFinset]
#align set.to_finset_ssubset Set.toFinset_ssubset
@[simp]
theorem subset_toFinset {s : Finset α} [Fintype t] : s ⊆ t.toFinset ↔ ↑s ⊆ t := by
rw [← Finset.coe_subset, coe_toFinset]
#align set.subset_to_finset Set.subset_toFinset
@[simp]
theorem ssubset_toFinset {s : Finset α} [Fintype t] : s ⊂ t.toFinset ↔ ↑s ⊂ t := by
rw [← Finset.coe_ssubset, coe_toFinset]
#align set.ssubset_to_finset Set.ssubset_toFinset
@[mono]
theorem toFinset_ssubset_toFinset [Fintype s] [Fintype t] : s.toFinset ⊂ t.toFinset ↔ s ⊂ t := by
simp only [Finset.ssubset_def, toFinset_subset_toFinset, ssubset_def]
#align set.to_finset_ssubset_to_finset Set.toFinset_ssubset_toFinset
@[simp]
theorem toFinset_subset [Fintype s] {t : Finset α} : s.toFinset ⊆ t ↔ s ⊆ t := by
rw [← Finset.coe_subset, coe_toFinset]
#align set.to_finset_subset Set.toFinset_subset
alias ⟨_, toFinset_mono⟩ := toFinset_subset_toFinset
#align set.to_finset_mono Set.toFinset_mono
alias ⟨_, toFinset_strict_mono⟩ := toFinset_ssubset_toFinset
#align set.to_finset_strict_mono Set.toFinset_strict_mono
@[simp]
theorem disjoint_toFinset [Fintype s] [Fintype t] :
Disjoint s.toFinset t.toFinset ↔ Disjoint s t := by simp only [← disjoint_coe, coe_toFinset]
#align set.disjoint_to_finset Set.disjoint_toFinset
section DecidableEq
variable [DecidableEq α] (s t) [Fintype s] [Fintype t]
@[simp]
theorem toFinset_inter [Fintype (s ∩ t : Set _)] : (s ∩ t).toFinset = s.toFinset ∩ t.toFinset := by
ext
simp
#align set.to_finset_inter Set.toFinset_inter
@[simp]
theorem toFinset_union [Fintype (s ∪ t : Set _)] : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by
ext
simp
#align set.to_finset_union Set.toFinset_union
@[simp]
theorem toFinset_diff [Fintype (s \ t : Set _)] : (s \ t).toFinset = s.toFinset \ t.toFinset := by
ext
simp
#align set.to_finset_diff Set.toFinset_diff
open scoped symmDiff in
@[simp]
theorem toFinset_symmDiff [Fintype (s ∆ t : Set _)] :
(s ∆ t).toFinset = s.toFinset ∆ t.toFinset := by
ext
simp [mem_symmDiff, Finset.mem_symmDiff]
#align set.to_finset_symm_diff Set.toFinset_symmDiff
@[simp]
theorem toFinset_compl [Fintype α] [Fintype (sᶜ : Set _)] : sᶜ.toFinset = s.toFinsetᶜ := by
ext
simp
#align set.to_finset_compl Set.toFinset_compl
end DecidableEq
-- TODO The `↥` circumvents an elaboration bug. See comment on `Set.toFinset_univ`.
@[simp]
theorem toFinset_empty [Fintype (∅ : Set α)] : (∅ : Set α).toFinset = ∅ := by
ext
simp
#align set.to_finset_empty Set.toFinset_empty
/- TODO Without the coercion arrow (`↥`) there is an elaboration bug in the following two;
it essentially infers `Fintype.{v} (Set.univ.{u} : Set α)` with `v` and `u` distinct.
Reported in leanprover-community/lean#672 -/
@[simp]
theorem toFinset_univ [Fintype α] [Fintype (Set.univ : Set α)] :
(Set.univ : Set α).toFinset = Finset.univ := by
ext
simp
#align set.to_finset_univ Set.toFinset_univ
@[simp]
| Mathlib/Data/Fintype/Basic.lean | 737 | 739 | theorem toFinset_eq_empty [Fintype s] : s.toFinset = ∅ ↔ s = ∅ := by |
let A : Fintype (∅ : Set α) := Fintype.ofIsEmpty
rw [← toFinset_empty, toFinset_inj]
|
/-
Copyright (c) 2016 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura
-/
import Mathlib.Mathport.Rename
import Mathlib.Init.Algebra.Classes
import Mathlib.Init.Data.Ordering.Basic
import Mathlib.Tactic.SplitIfs
import Mathlib.Tactic.TypeStar
import Batteries.Classes.Order
#align_import init.algebra.order from "leanprover-community/lean"@"c2bcdbcbe741ed37c361a30d38e179182b989f76"
/-!
# Orders
Defines classes for preorders, partial orders, and linear orders
and proves some basic lemmas about them.
-/
universe u
variable {α : Type u}
section Preorder
/-!
### Definition of `Preorder` and lemmas about types with a `Preorder`
-/
/-- A preorder is a reflexive, transitive relation `≤` with `a < b` defined in the obvious way. -/
class Preorder (α : Type u) extends LE α, LT α where
le_refl : ∀ a : α, a ≤ a
le_trans : ∀ a b c : α, a ≤ b → b ≤ c → a ≤ c
lt := fun a b => a ≤ b ∧ ¬b ≤ a
lt_iff_le_not_le : ∀ a b : α, a < b ↔ a ≤ b ∧ ¬b ≤ a := by intros; rfl
#align preorder Preorder
#align preorder.to_has_le Preorder.toLE
#align preorder.to_has_lt Preorder.toLT
variable [Preorder α]
/-- The relation `≤` on a preorder is reflexive. -/
@[refl]
theorem le_refl : ∀ a : α, a ≤ a :=
Preorder.le_refl
#align le_refl le_refl
/-- A version of `le_refl` where the argument is implicit -/
theorem le_rfl {a : α} : a ≤ a :=
le_refl a
#align le_rfl le_rfl
/-- The relation `≤` on a preorder is transitive. -/
@[trans]
theorem le_trans : ∀ {a b c : α}, a ≤ b → b ≤ c → a ≤ c :=
Preorder.le_trans _ _ _
#align le_trans le_trans
theorem lt_iff_le_not_le : ∀ {a b : α}, a < b ↔ a ≤ b ∧ ¬b ≤ a :=
Preorder.lt_iff_le_not_le _ _
#align lt_iff_le_not_le lt_iff_le_not_le
theorem lt_of_le_not_le : ∀ {a b : α}, a ≤ b → ¬b ≤ a → a < b
| _a, _b, hab, hba => lt_iff_le_not_le.mpr ⟨hab, hba⟩
#align lt_of_le_not_le lt_of_le_not_le
theorem le_not_le_of_lt : ∀ {a b : α}, a < b → a ≤ b ∧ ¬b ≤ a
| _a, _b, hab => lt_iff_le_not_le.mp hab
#align le_not_le_of_lt le_not_le_of_lt
theorem le_of_eq {a b : α} : a = b → a ≤ b := fun h => h ▸ le_refl a
#align le_of_eq le_of_eq
@[trans]
theorem ge_trans : ∀ {a b c : α}, a ≥ b → b ≥ c → a ≥ c := fun h₁ h₂ => le_trans h₂ h₁
#align ge_trans ge_trans
theorem lt_irrefl : ∀ a : α, ¬a < a
| _a, haa =>
match le_not_le_of_lt haa with
| ⟨h1, h2⟩ => h2 h1
#align lt_irrefl lt_irrefl
theorem gt_irrefl : ∀ a : α, ¬a > a :=
lt_irrefl
#align gt_irrefl gt_irrefl
@[trans]
theorem lt_trans : ∀ {a b c : α}, a < b → b < c → a < c
| _a, _b, _c, hab, hbc =>
match le_not_le_of_lt hab, le_not_le_of_lt hbc with
| ⟨hab, _hba⟩, ⟨hbc, hcb⟩ =>
lt_of_le_not_le (le_trans hab hbc) fun hca => hcb (le_trans hca hab)
#align lt_trans lt_trans
@[trans]
theorem gt_trans : ∀ {a b c : α}, a > b → b > c → a > c := fun h₁ h₂ => lt_trans h₂ h₁
#align gt_trans gt_trans
theorem ne_of_lt {a b : α} (h : a < b) : a ≠ b := fun he => absurd h (he ▸ lt_irrefl a)
#align ne_of_lt ne_of_lt
theorem ne_of_gt {a b : α} (h : b < a) : a ≠ b := fun he => absurd h (he ▸ lt_irrefl a)
#align ne_of_gt ne_of_gt
theorem lt_asymm {a b : α} (h : a < b) : ¬b < a := fun h1 : b < a => lt_irrefl a (lt_trans h h1)
#align lt_asymm lt_asymm
theorem le_of_lt : ∀ {a b : α}, a < b → a ≤ b
| _a, _b, hab => (le_not_le_of_lt hab).left
#align le_of_lt le_of_lt
@[trans]
theorem lt_of_lt_of_le : ∀ {a b c : α}, a < b → b ≤ c → a < c
| _a, _b, _c, hab, hbc =>
let ⟨hab, hba⟩ := le_not_le_of_lt hab
lt_of_le_not_le (le_trans hab hbc) fun hca => hba (le_trans hbc hca)
#align lt_of_lt_of_le lt_of_lt_of_le
@[trans]
theorem lt_of_le_of_lt : ∀ {a b c : α}, a ≤ b → b < c → a < c
| _a, _b, _c, hab, hbc =>
let ⟨hbc, hcb⟩ := le_not_le_of_lt hbc
lt_of_le_not_le (le_trans hab hbc) fun hca => hcb (le_trans hca hab)
#align lt_of_le_of_lt lt_of_le_of_lt
@[trans]
theorem gt_of_gt_of_ge {a b c : α} (h₁ : a > b) (h₂ : b ≥ c) : a > c :=
lt_of_le_of_lt h₂ h₁
#align gt_of_gt_of_ge gt_of_gt_of_ge
@[trans]
theorem gt_of_ge_of_gt {a b c : α} (h₁ : a ≥ b) (h₂ : b > c) : a > c :=
lt_of_lt_of_le h₂ h₁
#align gt_of_ge_of_gt gt_of_ge_of_gt
-- Porting note (#10754): new instance
instance (priority := 900) : @Trans α α α LE.le LE.le LE.le := ⟨le_trans⟩
instance (priority := 900) : @Trans α α α LT.lt LT.lt LT.lt := ⟨lt_trans⟩
instance (priority := 900) : @Trans α α α LT.lt LE.le LT.lt := ⟨lt_of_lt_of_le⟩
instance (priority := 900) : @Trans α α α LE.le LT.lt LT.lt := ⟨lt_of_le_of_lt⟩
instance (priority := 900) : @Trans α α α GE.ge GE.ge GE.ge := ⟨ge_trans⟩
instance (priority := 900) : @Trans α α α GT.gt GT.gt GT.gt := ⟨gt_trans⟩
instance (priority := 900) : @Trans α α α GT.gt GE.ge GT.gt := ⟨gt_of_gt_of_ge⟩
instance (priority := 900) : @Trans α α α GE.ge GT.gt GT.gt := ⟨gt_of_ge_of_gt⟩
theorem not_le_of_gt {a b : α} (h : a > b) : ¬a ≤ b :=
(le_not_le_of_lt h).right
#align not_le_of_gt not_le_of_gt
theorem not_lt_of_ge {a b : α} (h : a ≥ b) : ¬a < b := fun hab => not_le_of_gt hab h
#align not_lt_of_ge not_lt_of_ge
theorem le_of_lt_or_eq : ∀ {a b : α}, a < b ∨ a = b → a ≤ b
| _a, _b, Or.inl hab => le_of_lt hab
| _a, _b, Or.inr hab => hab ▸ le_refl _
#align le_of_lt_or_eq le_of_lt_or_eq
theorem le_of_eq_or_lt {a b : α} (h : a = b ∨ a < b) : a ≤ b :=
Or.elim h le_of_eq le_of_lt
#align le_of_eq_or_lt le_of_eq_or_lt
/-- `<` is decidable if `≤` is. -/
def decidableLTOfDecidableLE [@DecidableRel α (· ≤ ·)] : @DecidableRel α (· < ·)
| a, b =>
if hab : a ≤ b then
if hba : b ≤ a then isFalse fun hab' => not_le_of_gt hab' hba
else isTrue <| lt_of_le_not_le hab hba
else isFalse fun hab' => hab (le_of_lt hab')
#align decidable_lt_of_decidable_le decidableLTOfDecidableLE
end Preorder
section PartialOrder
/-!
### Definition of `PartialOrder` and lemmas about types with a partial order
-/
/-- A partial order is a reflexive, transitive, antisymmetric relation `≤`. -/
class PartialOrder (α : Type u) extends Preorder α where
le_antisymm : ∀ a b : α, a ≤ b → b ≤ a → a = b
#align partial_order PartialOrder
variable [PartialOrder α]
theorem le_antisymm : ∀ {a b : α}, a ≤ b → b ≤ a → a = b :=
PartialOrder.le_antisymm _ _
#align le_antisymm le_antisymm
alias eq_of_le_of_le := le_antisymm
theorem le_antisymm_iff {a b : α} : a = b ↔ a ≤ b ∧ b ≤ a :=
⟨fun e => ⟨le_of_eq e, le_of_eq e.symm⟩, fun ⟨h1, h2⟩ => le_antisymm h1 h2⟩
#align le_antisymm_iff le_antisymm_iff
theorem lt_of_le_of_ne {a b : α} : a ≤ b → a ≠ b → a < b := fun h₁ h₂ =>
lt_of_le_not_le h₁ <| mt (le_antisymm h₁) h₂
#align lt_of_le_of_ne lt_of_le_of_ne
/-- Equality is decidable if `≤` is. -/
def decidableEqOfDecidableLE [@DecidableRel α (· ≤ ·)] : DecidableEq α
| a, b =>
if hab : a ≤ b then
if hba : b ≤ a then isTrue (le_antisymm hab hba) else isFalse fun heq => hba (heq ▸ le_refl _)
else isFalse fun heq => hab (heq ▸ le_refl _)
#align decidable_eq_of_decidable_le decidableEqOfDecidableLE
namespace Decidable
variable [@DecidableRel α (· ≤ ·)]
theorem lt_or_eq_of_le {a b : α} (hab : a ≤ b) : a < b ∨ a = b :=
if hba : b ≤ a then Or.inr (le_antisymm hab hba) else Or.inl (lt_of_le_not_le hab hba)
#align decidable.lt_or_eq_of_le Decidable.lt_or_eq_of_le
theorem eq_or_lt_of_le {a b : α} (hab : a ≤ b) : a = b ∨ a < b :=
(lt_or_eq_of_le hab).symm
#align decidable.eq_or_lt_of_le Decidable.eq_or_lt_of_le
theorem le_iff_lt_or_eq {a b : α} : a ≤ b ↔ a < b ∨ a = b :=
⟨lt_or_eq_of_le, le_of_lt_or_eq⟩
#align decidable.le_iff_lt_or_eq Decidable.le_iff_lt_or_eq
end Decidable
attribute [local instance] Classical.propDecidable
theorem lt_or_eq_of_le {a b : α} : a ≤ b → a < b ∨ a = b :=
Decidable.lt_or_eq_of_le
#align lt_or_eq_of_le lt_or_eq_of_le
theorem le_iff_lt_or_eq {a b : α} : a ≤ b ↔ a < b ∨ a = b :=
Decidable.le_iff_lt_or_eq
#align le_iff_lt_or_eq le_iff_lt_or_eq
end PartialOrder
section LinearOrder
/-!
### Definition of `LinearOrder` and lemmas about types with a linear order
-/
/-- Default definition of `max`. -/
def maxDefault {α : Type u} [LE α] [DecidableRel ((· ≤ ·) : α → α → Prop)] (a b : α) :=
if a ≤ b then b else a
#align max_default maxDefault
/-- Default definition of `min`. -/
def minDefault {α : Type u} [LE α] [DecidableRel ((· ≤ ·) : α → α → Prop)] (a b : α) :=
if a ≤ b then a else b
/-- This attempts to prove that a given instance of `compare` is equal to `compareOfLessAndEq` by
introducing the arguments and trying the following approaches in order:
1. seeing if `rfl` works
2. seeing if the `compare` at hand is nonetheless essentially `compareOfLessAndEq`, but, because of
implicit arguments, requires us to unfold the defs and split the `if`s in the definition of
`compareOfLessAndEq`
3. seeing if we can split by cases on the arguments, then see if the defs work themselves out
(useful when `compare` is defined via a `match` statement, as it is for `Bool`) -/
macro "compareOfLessAndEq_rfl" : tactic =>
`(tactic| (intros a b; first | rfl |
(simp only [compare, compareOfLessAndEq]; split_ifs <;> rfl) |
(induction a <;> induction b <;> simp (config := {decide := true}) only [])))
/-- A linear order is reflexive, transitive, antisymmetric and total relation `≤`.
We assume that every linear ordered type has decidable `(≤)`, `(<)`, and `(=)`. -/
class LinearOrder (α : Type u) extends PartialOrder α, Min α, Max α, Ord α :=
/-- 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
min := fun a b => if a ≤ b then a else b
max := fun a b => if a ≤ b then b else a
/-- The minimum function is equivalent to the one you get from `minOfLe`. -/
min_def : ∀ a b, min a b = if a ≤ b then a else b := by intros; rfl
/-- The minimum function is equivalent to the one you get from `maxOfLe`. -/
max_def : ∀ a b, max a b = if a ≤ b then b else a := by intros; rfl
compare a b := compareOfLessAndEq a b
/-- Comparison via `compare` is equal to the canonical comparison given decidable `<` and `=`. -/
compare_eq_compareOfLessAndEq : ∀ a b, compare a b = compareOfLessAndEq a b := by
compareOfLessAndEq_rfl
#align linear_order LinearOrder
variable [LinearOrder α]
attribute [local instance] LinearOrder.decidableLE
theorem le_total : ∀ a b : α, a ≤ b ∨ b ≤ a :=
LinearOrder.le_total
#align le_total le_total
theorem le_of_not_ge {a b : α} : ¬a ≥ b → a ≤ b :=
Or.resolve_left (le_total b a)
#align le_of_not_ge le_of_not_ge
theorem le_of_not_le {a b : α} : ¬a ≤ b → b ≤ a :=
Or.resolve_left (le_total a b)
#align le_of_not_le le_of_not_le
theorem not_lt_of_gt {a b : α} (h : a > b) : ¬a < b :=
lt_asymm h
#align not_lt_of_gt not_lt_of_gt
theorem lt_trichotomy (a b : α) : a < b ∨ a = b ∨ b < a :=
Or.elim (le_total a b)
(fun h : a ≤ b =>
Or.elim (Decidable.lt_or_eq_of_le h) (fun h : a < b => Or.inl h) fun h : a = b =>
Or.inr (Or.inl h))
fun h : b ≤ a =>
Or.elim (Decidable.lt_or_eq_of_le h) (fun h : b < a => Or.inr (Or.inr h)) fun h : b = a =>
Or.inr (Or.inl h.symm)
#align lt_trichotomy lt_trichotomy
theorem le_of_not_lt {a b : α} (h : ¬b < a) : a ≤ b :=
match lt_trichotomy a b with
| Or.inl hlt => le_of_lt hlt
| Or.inr (Or.inl HEq) => HEq ▸ le_refl a
| Or.inr (Or.inr hgt) => absurd hgt h
#align le_of_not_lt le_of_not_lt
theorem le_of_not_gt {a b : α} : ¬a > b → a ≤ b :=
le_of_not_lt
#align le_of_not_gt le_of_not_gt
theorem lt_of_not_ge {a b : α} (h : ¬a ≥ b) : a < b :=
lt_of_le_not_le ((le_total _ _).resolve_right h) h
#align lt_of_not_ge lt_of_not_ge
theorem lt_or_le (a b : α) : a < b ∨ b ≤ a :=
if hba : b ≤ a then Or.inr hba else Or.inl <| lt_of_not_ge hba
#align lt_or_le lt_or_le
theorem le_or_lt (a b : α) : a ≤ b ∨ b < a :=
(lt_or_le b a).symm
#align le_or_lt le_or_lt
theorem lt_or_ge : ∀ a b : α, a < b ∨ a ≥ b :=
lt_or_le
#align lt_or_ge lt_or_ge
theorem le_or_gt : ∀ a b : α, a ≤ b ∨ a > b :=
le_or_lt
#align le_or_gt le_or_gt
theorem lt_or_gt_of_ne {a b : α} (h : a ≠ b) : a < b ∨ a > b :=
match lt_trichotomy a b with
| Or.inl hlt => Or.inl hlt
| Or.inr (Or.inl HEq) => absurd HEq h
| Or.inr (Or.inr hgt) => Or.inr hgt
#align lt_or_gt_of_ne lt_or_gt_of_ne
theorem ne_iff_lt_or_gt {a b : α} : a ≠ b ↔ a < b ∨ a > b :=
⟨lt_or_gt_of_ne, fun o => Or.elim o ne_of_lt ne_of_gt⟩
#align ne_iff_lt_or_gt ne_iff_lt_or_gt
theorem lt_iff_not_ge (x y : α) : x < y ↔ ¬x ≥ y :=
⟨not_le_of_gt, lt_of_not_ge⟩
#align lt_iff_not_ge lt_iff_not_ge
@[simp]
theorem not_lt {a b : α} : ¬a < b ↔ b ≤ a :=
⟨le_of_not_gt, not_lt_of_ge⟩
#align not_lt not_lt
@[simp]
theorem not_le {a b : α} : ¬a ≤ b ↔ b < a :=
(lt_iff_not_ge _ _).symm
#align not_le not_le
instance (priority := 900) (a b : α) : Decidable (a < b) :=
LinearOrder.decidableLT a b
instance (priority := 900) (a b : α) : Decidable (a ≤ b) :=
LinearOrder.decidableLE a b
instance (priority := 900) (a b : α) : Decidable (a = b) :=
LinearOrder.decidableEq a b
theorem eq_or_lt_of_not_lt {a b : α} (h : ¬a < b) : a = b ∨ b < a :=
if h₁ : a = b then Or.inl h₁ else Or.inr (lt_of_not_ge fun hge => h (lt_of_le_of_ne hge h₁))
#align eq_or_lt_of_not_lt eq_or_lt_of_not_lt
instance : IsTotalPreorder α (· ≤ ·) where
trans := @le_trans _ _
total := le_total
-- TODO(Leo): decide whether we should keep this instance or not
instance isStrictWeakOrder_of_linearOrder : IsStrictWeakOrder α (· < ·) :=
have : IsTotalPreorder α (· ≤ ·) := by infer_instance -- Porting note: added
isStrictWeakOrder_of_isTotalPreorder lt_iff_not_ge
#align is_strict_weak_order_of_linear_order isStrictWeakOrder_of_linearOrder
-- TODO(Leo): decide whether we should keep this instance or not
instance isStrictTotalOrder_of_linearOrder : IsStrictTotalOrder α (· < ·) where
trichotomous := lt_trichotomy
#align is_strict_total_order_of_linear_order isStrictTotalOrder_of_linearOrder
/-- Perform a case-split on the ordering of `x` and `y` in a decidable linear order. -/
def ltByCases (x y : α) {P : Sort*} (h₁ : x < y → P) (h₂ : x = y → P) (h₃ : y < x → P) : P :=
if h : x < y then h₁ h
else if h' : y < x then h₃ h' else h₂ (le_antisymm (le_of_not_gt h') (le_of_not_gt h))
#align lt_by_cases ltByCases
theorem le_imp_le_of_lt_imp_lt {β} [Preorder α] [LinearOrder β] {a b : α} {c d : β}
(H : d < c → b < a) (h : a ≤ b) : c ≤ d :=
le_of_not_lt fun h' => not_le_of_gt (H h') h
#align le_imp_le_of_lt_imp_lt le_imp_le_of_lt_imp_lt
-- Porting note: new
section Ord
theorem compare_lt_iff_lt {a b : α} : (compare a b = .lt) ↔ a < b := by
rw [LinearOrder.compare_eq_compareOfLessAndEq, compareOfLessAndEq]
split_ifs <;> simp only [*, lt_irrefl]
theorem compare_gt_iff_gt {a b : α} : (compare a b = .gt) ↔ a > b := by
rw [LinearOrder.compare_eq_compareOfLessAndEq, compareOfLessAndEq]
split_ifs <;> simp only [*, lt_irrefl, not_lt_of_gt]
case _ h₁ h₂ =>
have h : b < a := lt_trichotomy a b |>.resolve_left h₁ |>.resolve_left h₂
exact true_iff_iff.2 h
theorem compare_eq_iff_eq {a b : α} : (compare a b = .eq) ↔ a = b := by
rw [LinearOrder.compare_eq_compareOfLessAndEq, compareOfLessAndEq]
split_ifs <;> try simp only
case _ h => exact false_iff_iff.2 <| ne_iff_lt_or_gt.2 <| .inl h
case _ _ h => exact true_iff_iff.2 h
case _ _ h => exact false_iff_iff.2 h
theorem compare_le_iff_le {a b : α} : (compare a b ≠ .gt) ↔ a ≤ b := by
cases h : compare a b <;> simp
· exact le_of_lt <| compare_lt_iff_lt.1 h
· exact le_of_eq <| compare_eq_iff_eq.1 h
· exact compare_gt_iff_gt.1 h
theorem compare_ge_iff_ge {a b : α} : (compare a b ≠ .lt) ↔ a ≥ b := by
cases h : compare a b <;> simp
· exact compare_lt_iff_lt.1 h
· exact le_of_eq <| (·.symm) <| compare_eq_iff_eq.1 h
· exact le_of_lt <| compare_gt_iff_gt.1 h
| Mathlib/Init/Order/Defs.lean | 451 | 455 | theorem compare_iff (a b : α) {o : Ordering} : compare a b = o ↔ o.toRel a b := by |
cases o <;> simp only [Ordering.toRel]
· exact compare_lt_iff_lt
· exact compare_eq_iff_eq
· exact compare_gt_iff_gt
|
/-
Copyright (c) 2021 Chris Hughes, Junyan Xu. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Junyan Xu
-/
import Mathlib.Algebra.MvPolynomial.Equiv
import Mathlib.Data.Finsupp.Fintype
import Mathlib.SetTheory.Cardinal.Ordinal
#align_import data.mv_polynomial.cardinal from "leanprover-community/mathlib"@"3cd7b577c6acf365f59a6376c5867533124eff6b"
/-!
# Cardinality of Multivariate Polynomial Ring
The main result in this file is `MvPolynomial.cardinal_mk_le_max`, which says that
the cardinality of `MvPolynomial σ R` is bounded above by the maximum of `#R`, `#σ`
and `ℵ₀`.
-/
universe u v
open Cardinal
open Cardinal
namespace MvPolynomial
section TwoUniverses
variable {σ : Type u} {R : Type v} [CommSemiring R]
@[simp]
theorem cardinal_mk_eq_max_lift [Nonempty σ] [Nontrivial R] :
#(MvPolynomial σ R) = max (max (Cardinal.lift.{u} #R) <| Cardinal.lift.{v} #σ) ℵ₀ :=
(mk_finsupp_lift_of_infinite _ R).trans <| by
rw [mk_finsupp_nat, max_assoc, lift_max, lift_aleph0, max_comm]
#align mv_polynomial.cardinal_mk_eq_max_lift MvPolynomial.cardinal_mk_eq_max_lift
@[simp]
theorem cardinal_mk_eq_lift [IsEmpty σ] : #(MvPolynomial σ R) = Cardinal.lift.{u} #R :=
((isEmptyRingEquiv R σ).toEquiv.trans Equiv.ulift.{u}.symm).cardinal_eq
#align mv_polynomial.cardinal_mk_eq_lift MvPolynomial.cardinal_mk_eq_lift
theorem cardinal_lift_mk_le_max {σ : Type u} {R : Type v} [CommSemiring R] : #(MvPolynomial σ R) ≤
max (max (Cardinal.lift.{u} #R) <| Cardinal.lift.{v} #σ) ℵ₀ := by
cases subsingleton_or_nontrivial R
· exact (mk_eq_one _).trans_le (le_max_of_le_right one_le_aleph0)
cases isEmpty_or_nonempty σ
· exact cardinal_mk_eq_lift.trans_le (le_max_of_le_left <| le_max_left _ _)
· exact cardinal_mk_eq_max_lift.le
#align mv_polynomial.cardinal_lift_mk_le_max MvPolynomial.cardinal_lift_mk_le_max
end TwoUniverses
variable {σ R : Type u} [CommSemiring R]
| Mathlib/Algebra/MvPolynomial/Cardinal.lean | 58 | 59 | theorem cardinal_mk_eq_max [Nonempty σ] [Nontrivial R] :
#(MvPolynomial σ R) = max (max #R #σ) ℵ₀ := by | simp
|
/-
Copyright (c) 2021 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Analysis.Normed.Group.Basic
#align_import analysis.normed.group.hom from "leanprover-community/mathlib"@"3c4225288b55380a90df078ebae0991080b12393"
/-!
# Normed groups homomorphisms
This file gathers definitions and elementary constructions about bounded group homomorphisms
between normed (abelian) groups (abbreviated to "normed group homs").
The main lemmas relate the boundedness condition to continuity and Lipschitzness.
The main construction is to endow the type of normed group homs between two given normed groups
with a group structure and a norm, giving rise to a normed group structure. We provide several
simple constructions for normed group homs, like kernel, range and equalizer.
Some easy other constructions are related to subgroups of normed groups.
Since a lot of elementary properties don't require `‖x‖ = 0 → x = 0` we start setting up the
theory of `SeminormedAddGroupHom` and we specialize to `NormedAddGroupHom` when needed.
-/
noncomputable section
open NNReal
-- TODO: migrate to the new morphism / morphism_class style
/-- A morphism of seminormed abelian groups is a bounded group homomorphism. -/
structure NormedAddGroupHom (V W : Type*) [SeminormedAddCommGroup V]
[SeminormedAddCommGroup W] where
/-- The function underlying a `NormedAddGroupHom` -/
toFun : V → W
/-- A `NormedAddGroupHom` is additive. -/
map_add' : ∀ v₁ v₂, toFun (v₁ + v₂) = toFun v₁ + toFun v₂
/-- A `NormedAddGroupHom` is bounded. -/
bound' : ∃ C, ∀ v, ‖toFun v‖ ≤ C * ‖v‖
#align normed_add_group_hom NormedAddGroupHom
namespace AddMonoidHom
variable {V W : Type*} [SeminormedAddCommGroup V] [SeminormedAddCommGroup W]
{f g : NormedAddGroupHom V W}
/-- Associate to a group homomorphism a bounded group homomorphism under a norm control condition.
See `AddMonoidHom.mkNormedAddGroupHom'` for a version that uses `ℝ≥0` for the bound. -/
def mkNormedAddGroupHom (f : V →+ W) (C : ℝ) (h : ∀ v, ‖f v‖ ≤ C * ‖v‖) : NormedAddGroupHom V W :=
{ f with bound' := ⟨C, h⟩ }
#align add_monoid_hom.mk_normed_add_group_hom AddMonoidHom.mkNormedAddGroupHom
/-- Associate to a group homomorphism a bounded group homomorphism under a norm control condition.
See `AddMonoidHom.mkNormedAddGroupHom` for a version that uses `ℝ` for the bound. -/
def mkNormedAddGroupHom' (f : V →+ W) (C : ℝ≥0) (hC : ∀ x, ‖f x‖₊ ≤ C * ‖x‖₊) :
NormedAddGroupHom V W :=
{ f with bound' := ⟨C, hC⟩ }
#align add_monoid_hom.mk_normed_add_group_hom' AddMonoidHom.mkNormedAddGroupHom'
end AddMonoidHom
| Mathlib/Analysis/Normed/Group/Hom.lean | 67 | 74 | theorem exists_pos_bound_of_bound {V W : Type*} [SeminormedAddCommGroup V]
[SeminormedAddCommGroup W] {f : V → W} (M : ℝ) (h : ∀ x, ‖f x‖ ≤ M * ‖x‖) :
∃ N, 0 < N ∧ ∀ x, ‖f x‖ ≤ N * ‖x‖ :=
⟨max M 1, lt_of_lt_of_le zero_lt_one (le_max_right _ _), fun x =>
calc
‖f x‖ ≤ M * ‖x‖ := h x
_ ≤ max M 1 * ‖x‖ := by | gcongr; apply le_max_left
⟩
|
/-
Copyright (c) 2020 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Alex Meiburg
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.Polynomial.Degree.Lemmas
#align_import data.polynomial.erase_lead from "leanprover-community/mathlib"@"fa256f00ce018e7b40e1dc756e403c86680bf448"
/-!
# Erase the leading term of a univariate polynomial
## Definition
* `eraseLead f`: the polynomial `f - leading term of f`
`eraseLead` serves as reduction step in an induction, shaving off one monomial from a polynomial.
The definition is set up so that it does not mention subtraction in the definition,
and thus works for polynomials over semirings as well as rings.
-/
noncomputable section
open Polynomial
open Polynomial Finset
namespace Polynomial
variable {R : Type*} [Semiring R] {f : R[X]}
/-- `eraseLead f` for a polynomial `f` is the polynomial obtained by
subtracting from `f` the leading term of `f`. -/
def eraseLead (f : R[X]) : R[X] :=
Polynomial.erase f.natDegree f
#align polynomial.erase_lead Polynomial.eraseLead
section EraseLead
theorem eraseLead_support (f : R[X]) : f.eraseLead.support = f.support.erase f.natDegree := by
simp only [eraseLead, support_erase]
#align polynomial.erase_lead_support Polynomial.eraseLead_support
theorem eraseLead_coeff (i : ℕ) :
f.eraseLead.coeff i = if i = f.natDegree then 0 else f.coeff i := by
simp only [eraseLead, coeff_erase]
#align polynomial.erase_lead_coeff Polynomial.eraseLead_coeff
@[simp]
theorem eraseLead_coeff_natDegree : f.eraseLead.coeff f.natDegree = 0 := by simp [eraseLead_coeff]
#align polynomial.erase_lead_coeff_nat_degree Polynomial.eraseLead_coeff_natDegree
theorem eraseLead_coeff_of_ne (i : ℕ) (hi : i ≠ f.natDegree) : f.eraseLead.coeff i = f.coeff i := by
simp [eraseLead_coeff, hi]
#align polynomial.erase_lead_coeff_of_ne Polynomial.eraseLead_coeff_of_ne
@[simp]
theorem eraseLead_zero : eraseLead (0 : R[X]) = 0 := by simp only [eraseLead, erase_zero]
#align polynomial.erase_lead_zero Polynomial.eraseLead_zero
@[simp]
theorem eraseLead_add_monomial_natDegree_leadingCoeff (f : R[X]) :
f.eraseLead + monomial f.natDegree f.leadingCoeff = f :=
(add_comm _ _).trans (f.monomial_add_erase _)
#align polynomial.erase_lead_add_monomial_nat_degree_leading_coeff Polynomial.eraseLead_add_monomial_natDegree_leadingCoeff
@[simp]
theorem eraseLead_add_C_mul_X_pow (f : R[X]) :
f.eraseLead + C f.leadingCoeff * X ^ f.natDegree = f := by
rw [C_mul_X_pow_eq_monomial, eraseLead_add_monomial_natDegree_leadingCoeff]
set_option linter.uppercaseLean3 false in
#align polynomial.erase_lead_add_C_mul_X_pow Polynomial.eraseLead_add_C_mul_X_pow
@[simp]
theorem self_sub_monomial_natDegree_leadingCoeff {R : Type*} [Ring R] (f : R[X]) :
f - monomial f.natDegree f.leadingCoeff = f.eraseLead :=
(eq_sub_iff_add_eq.mpr (eraseLead_add_monomial_natDegree_leadingCoeff f)).symm
#align polynomial.self_sub_monomial_nat_degree_leading_coeff Polynomial.self_sub_monomial_natDegree_leadingCoeff
@[simp]
theorem self_sub_C_mul_X_pow {R : Type*} [Ring R] (f : R[X]) :
f - C f.leadingCoeff * X ^ f.natDegree = f.eraseLead := by
rw [C_mul_X_pow_eq_monomial, self_sub_monomial_natDegree_leadingCoeff]
set_option linter.uppercaseLean3 false in
#align polynomial.self_sub_C_mul_X_pow Polynomial.self_sub_C_mul_X_pow
theorem eraseLead_ne_zero (f0 : 2 ≤ f.support.card) : eraseLead f ≠ 0 := by
rw [Ne, ← card_support_eq_zero, eraseLead_support]
exact
(zero_lt_one.trans_le <| (tsub_le_tsub_right f0 1).trans Finset.pred_card_le_card_erase).ne.symm
#align polynomial.erase_lead_ne_zero Polynomial.eraseLead_ne_zero
theorem lt_natDegree_of_mem_eraseLead_support {a : ℕ} (h : a ∈ (eraseLead f).support) :
a < f.natDegree := by
rw [eraseLead_support, mem_erase] at h
exact (le_natDegree_of_mem_supp a h.2).lt_of_ne h.1
#align polynomial.lt_nat_degree_of_mem_erase_lead_support Polynomial.lt_natDegree_of_mem_eraseLead_support
theorem ne_natDegree_of_mem_eraseLead_support {a : ℕ} (h : a ∈ (eraseLead f).support) :
a ≠ f.natDegree :=
(lt_natDegree_of_mem_eraseLead_support h).ne
#align polynomial.ne_nat_degree_of_mem_erase_lead_support Polynomial.ne_natDegree_of_mem_eraseLead_support
theorem natDegree_not_mem_eraseLead_support : f.natDegree ∉ (eraseLead f).support := fun h =>
ne_natDegree_of_mem_eraseLead_support h rfl
#align polynomial.nat_degree_not_mem_erase_lead_support Polynomial.natDegree_not_mem_eraseLead_support
theorem eraseLead_support_card_lt (h : f ≠ 0) : (eraseLead f).support.card < f.support.card := by
rw [eraseLead_support]
exact card_lt_card (erase_ssubset <| natDegree_mem_support_of_nonzero h)
#align polynomial.erase_lead_support_card_lt Polynomial.eraseLead_support_card_lt
theorem card_support_eraseLead_add_one (h : f ≠ 0) :
f.eraseLead.support.card + 1 = f.support.card := by
set c := f.support.card with hc
cases h₁ : c
case zero =>
by_contra
exact h (card_support_eq_zero.mp h₁)
case succ =>
rw [eraseLead_support, card_erase_of_mem (natDegree_mem_support_of_nonzero h), ← hc, h₁]
rfl
@[simp]
theorem card_support_eraseLead : f.eraseLead.support.card = f.support.card - 1 := by
by_cases hf : f = 0
· rw [hf, eraseLead_zero, support_zero, card_empty]
· rw [← card_support_eraseLead_add_one hf, add_tsub_cancel_right]
theorem card_support_eraseLead' {c : ℕ} (fc : f.support.card = c + 1) :
f.eraseLead.support.card = c := by
rw [card_support_eraseLead, fc, add_tsub_cancel_right]
#align polynomial.erase_lead_card_support' Polynomial.card_support_eraseLead'
theorem card_support_eq_one_of_eraseLead_eq_zero (h₀ : f ≠ 0) (h₁ : f.eraseLead = 0) :
f.support.card = 1 :=
(card_support_eq_zero.mpr h₁ ▸ card_support_eraseLead_add_one h₀).symm
| Mathlib/Algebra/Polynomial/EraseLead.lean | 141 | 144 | theorem card_support_le_one_of_eraseLead_eq_zero (h : f.eraseLead = 0) : f.support.card ≤ 1 := by |
by_cases hpz : f = 0
case pos => simp [hpz]
case neg => exact le_of_eq (card_support_eq_one_of_eraseLead_eq_zero hpz h)
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Monoid.Unbundled.Pow
import Mathlib.Data.Finset.Fold
import Mathlib.Data.Finset.Option
import Mathlib.Data.Finset.Pi
import Mathlib.Data.Finset.Prod
import Mathlib.Data.Multiset.Lattice
import Mathlib.Data.Set.Lattice
import Mathlib.Order.Hom.Lattice
import Mathlib.Order.Nat
#align_import data.finset.lattice from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Lattice operations on finsets
-/
-- TODO:
-- assert_not_exists OrderedCommMonoid
assert_not_exists MonoidWithZero
open Function Multiset OrderDual
variable {F α β γ ι κ : Type*}
namespace Finset
/-! ### sup -/
section Sup
-- TODO: define with just `[Bot α]` where some lemmas hold without requiring `[OrderBot α]`
variable [SemilatticeSup α] [OrderBot α]
/-- Supremum of a finite set: `sup {a, b, c} f = f a ⊔ f b ⊔ f c` -/
def sup (s : Finset β) (f : β → α) : α :=
s.fold (· ⊔ ·) ⊥ f
#align finset.sup Finset.sup
variable {s s₁ s₂ : Finset β} {f g : β → α} {a : α}
theorem sup_def : s.sup f = (s.1.map f).sup :=
rfl
#align finset.sup_def Finset.sup_def
@[simp]
theorem sup_empty : (∅ : Finset β).sup f = ⊥ :=
fold_empty
#align finset.sup_empty Finset.sup_empty
@[simp]
theorem sup_cons {b : β} (h : b ∉ s) : (cons b s h).sup f = f b ⊔ s.sup f :=
fold_cons h
#align finset.sup_cons Finset.sup_cons
@[simp]
theorem sup_insert [DecidableEq β] {b : β} : (insert b s : Finset β).sup f = f b ⊔ s.sup f :=
fold_insert_idem
#align finset.sup_insert Finset.sup_insert
@[simp]
theorem sup_image [DecidableEq β] (s : Finset γ) (f : γ → β) (g : β → α) :
(s.image f).sup g = s.sup (g ∘ f) :=
fold_image_idem
#align finset.sup_image Finset.sup_image
@[simp]
theorem sup_map (s : Finset γ) (f : γ ↪ β) (g : β → α) : (s.map f).sup g = s.sup (g ∘ f) :=
fold_map
#align finset.sup_map Finset.sup_map
@[simp]
theorem sup_singleton {b : β} : ({b} : Finset β).sup f = f b :=
Multiset.sup_singleton
#align finset.sup_singleton Finset.sup_singleton
theorem sup_sup : s.sup (f ⊔ g) = s.sup f ⊔ s.sup g := by
induction s using Finset.cons_induction with
| empty => rw [sup_empty, sup_empty, sup_empty, bot_sup_eq]
| cons _ _ _ ih =>
rw [sup_cons, sup_cons, sup_cons, ih]
exact sup_sup_sup_comm _ _ _ _
#align finset.sup_sup Finset.sup_sup
theorem sup_congr {f g : β → α} (hs : s₁ = s₂) (hfg : ∀ a ∈ s₂, f a = g a) :
s₁.sup f = s₂.sup g := by
subst hs
exact Finset.fold_congr hfg
#align finset.sup_congr Finset.sup_congr
@[simp]
theorem _root_.map_finset_sup [SemilatticeSup β] [OrderBot β]
[FunLike F α β] [SupBotHomClass F α β]
(f : F) (s : Finset ι) (g : ι → α) : f (s.sup g) = s.sup (f ∘ g) :=
Finset.cons_induction_on s (map_bot f) fun i s _ h => by
rw [sup_cons, sup_cons, map_sup, h, Function.comp_apply]
#align map_finset_sup map_finset_sup
@[simp]
protected theorem sup_le_iff {a : α} : s.sup f ≤ a ↔ ∀ b ∈ s, f b ≤ a := by
apply Iff.trans Multiset.sup_le
simp only [Multiset.mem_map, and_imp, exists_imp]
exact ⟨fun k b hb => k _ _ hb rfl, fun k a' b hb h => h ▸ k _ hb⟩
#align finset.sup_le_iff Finset.sup_le_iff
protected alias ⟨_, sup_le⟩ := Finset.sup_le_iff
#align finset.sup_le Finset.sup_le
theorem sup_const_le : (s.sup fun _ => a) ≤ a :=
Finset.sup_le fun _ _ => le_rfl
#align finset.sup_const_le Finset.sup_const_le
theorem le_sup {b : β} (hb : b ∈ s) : f b ≤ s.sup f :=
Finset.sup_le_iff.1 le_rfl _ hb
#align finset.le_sup Finset.le_sup
theorem le_sup_of_le {b : β} (hb : b ∈ s) (h : a ≤ f b) : a ≤ s.sup f := h.trans <| le_sup hb
#align finset.le_sup_of_le Finset.le_sup_of_le
theorem sup_union [DecidableEq β] : (s₁ ∪ s₂).sup f = s₁.sup f ⊔ s₂.sup f :=
eq_of_forall_ge_iff fun c => by simp [or_imp, forall_and]
#align finset.sup_union Finset.sup_union
@[simp]
theorem sup_biUnion [DecidableEq β] (s : Finset γ) (t : γ → Finset β) :
(s.biUnion t).sup f = s.sup fun x => (t x).sup f :=
eq_of_forall_ge_iff fun c => by simp [@forall_swap _ β]
#align finset.sup_bUnion Finset.sup_biUnion
theorem sup_const {s : Finset β} (h : s.Nonempty) (c : α) : (s.sup fun _ => c) = c :=
eq_of_forall_ge_iff (fun _ => Finset.sup_le_iff.trans h.forall_const)
#align finset.sup_const Finset.sup_const
@[simp]
theorem sup_bot (s : Finset β) : (s.sup fun _ => ⊥) = (⊥ : α) := by
obtain rfl | hs := s.eq_empty_or_nonempty
· exact sup_empty
· exact sup_const hs _
#align finset.sup_bot Finset.sup_bot
theorem sup_ite (p : β → Prop) [DecidablePred p] :
(s.sup fun i => ite (p i) (f i) (g i)) = (s.filter p).sup f ⊔ (s.filter fun i => ¬p i).sup g :=
fold_ite _
#align finset.sup_ite Finset.sup_ite
theorem sup_mono_fun {g : β → α} (h : ∀ b ∈ s, f b ≤ g b) : s.sup f ≤ s.sup g :=
Finset.sup_le fun b hb => le_trans (h b hb) (le_sup hb)
#align finset.sup_mono_fun Finset.sup_mono_fun
@[gcongr]
theorem sup_mono (h : s₁ ⊆ s₂) : s₁.sup f ≤ s₂.sup f :=
Finset.sup_le (fun _ hb => le_sup (h hb))
#align finset.sup_mono Finset.sup_mono
protected theorem sup_comm (s : Finset β) (t : Finset γ) (f : β → γ → α) :
(s.sup fun b => t.sup (f b)) = t.sup fun c => s.sup fun b => f b c :=
eq_of_forall_ge_iff fun a => by simpa using forall₂_swap
#align finset.sup_comm Finset.sup_comm
@[simp, nolint simpNF] -- Porting note: linter claims that LHS does not simplify
theorem sup_attach (s : Finset β) (f : β → α) : (s.attach.sup fun x => f x) = s.sup f :=
(s.attach.sup_map (Function.Embedding.subtype _) f).symm.trans <| congr_arg _ attach_map_val
#align finset.sup_attach Finset.sup_attach
/-- See also `Finset.product_biUnion`. -/
theorem sup_product_left (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).sup f = s.sup fun i => t.sup fun i' => f ⟨i, i'⟩ :=
eq_of_forall_ge_iff fun a => by simp [@forall_swap _ γ]
#align finset.sup_product_left Finset.sup_product_left
theorem sup_product_right (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).sup f = t.sup fun i' => s.sup fun i => f ⟨i, i'⟩ := by
rw [sup_product_left, Finset.sup_comm]
#align finset.sup_product_right Finset.sup_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeSup α] [SemilatticeSup β] [OrderBot α] [OrderBot β]
{s : Finset ι} {t : Finset κ}
@[simp] lemma sup_prodMap (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
sup (s ×ˢ t) (Prod.map f g) = (sup s f, sup t g) :=
eq_of_forall_ge_iff fun i ↦ by
obtain ⟨a, ha⟩ := hs
obtain ⟨b, hb⟩ := ht
simp only [Prod.map, Finset.sup_le_iff, mem_product, and_imp, Prod.forall, Prod.le_def]
exact ⟨fun h ↦ ⟨fun i hi ↦ (h _ _ hi hb).1, fun j hj ↦ (h _ _ ha hj).2⟩, by aesop⟩
end Prod
@[simp]
theorem sup_erase_bot [DecidableEq α] (s : Finset α) : (s.erase ⊥).sup id = s.sup id := by
refine (sup_mono (s.erase_subset _)).antisymm (Finset.sup_le_iff.2 fun a ha => ?_)
obtain rfl | ha' := eq_or_ne a ⊥
· exact bot_le
· exact le_sup (mem_erase.2 ⟨ha', ha⟩)
#align finset.sup_erase_bot Finset.sup_erase_bot
theorem sup_sdiff_right {α β : Type*} [GeneralizedBooleanAlgebra α] (s : Finset β) (f : β → α)
(a : α) : (s.sup fun b => f b \ a) = s.sup f \ a := by
induction s using Finset.cons_induction with
| empty => rw [sup_empty, sup_empty, bot_sdiff]
| cons _ _ _ h => rw [sup_cons, sup_cons, h, sup_sdiff]
#align finset.sup_sdiff_right Finset.sup_sdiff_right
theorem comp_sup_eq_sup_comp [SemilatticeSup γ] [OrderBot γ] {s : Finset β} {f : β → α} (g : α → γ)
(g_sup : ∀ x y, g (x ⊔ y) = g x ⊔ g y) (bot : g ⊥ = ⊥) : g (s.sup f) = s.sup (g ∘ f) :=
Finset.cons_induction_on s bot fun c t hc ih => by
rw [sup_cons, sup_cons, g_sup, ih, Function.comp_apply]
#align finset.comp_sup_eq_sup_comp Finset.comp_sup_eq_sup_comp
/-- Computing `sup` in a subtype (closed under `sup`) is the same as computing it in `α`. -/
theorem sup_coe {P : α → Prop} {Pbot : P ⊥} {Psup : ∀ ⦃x y⦄, P x → P y → P (x ⊔ y)} (t : Finset β)
(f : β → { x : α // P x }) :
(@sup { x // P x } _ (Subtype.semilatticeSup Psup) (Subtype.orderBot Pbot) t f : α) =
t.sup fun x => ↑(f x) := by
letI := Subtype.semilatticeSup Psup
letI := Subtype.orderBot Pbot
apply comp_sup_eq_sup_comp Subtype.val <;> intros <;> rfl
#align finset.sup_coe Finset.sup_coe
@[simp]
theorem sup_toFinset {α β} [DecidableEq β] (s : Finset α) (f : α → Multiset β) :
(s.sup f).toFinset = s.sup fun x => (f x).toFinset :=
comp_sup_eq_sup_comp Multiset.toFinset toFinset_union rfl
#align finset.sup_to_finset Finset.sup_toFinset
theorem _root_.List.foldr_sup_eq_sup_toFinset [DecidableEq α] (l : List α) :
l.foldr (· ⊔ ·) ⊥ = l.toFinset.sup id := by
rw [← coe_fold_r, ← Multiset.fold_dedup_idem, sup_def, ← List.toFinset_coe, toFinset_val,
Multiset.map_id]
rfl
#align list.foldr_sup_eq_sup_to_finset List.foldr_sup_eq_sup_toFinset
theorem subset_range_sup_succ (s : Finset ℕ) : s ⊆ range (s.sup id).succ := fun _ hn =>
mem_range.2 <| Nat.lt_succ_of_le <| @le_sup _ _ _ _ _ id _ hn
#align finset.subset_range_sup_succ Finset.subset_range_sup_succ
theorem exists_nat_subset_range (s : Finset ℕ) : ∃ n : ℕ, s ⊆ range n :=
⟨_, s.subset_range_sup_succ⟩
#align finset.exists_nat_subset_range Finset.exists_nat_subset_range
theorem sup_induction {p : α → Prop} (hb : p ⊥) (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊔ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.sup f) := by
induction s using Finset.cons_induction with
| empty => exact hb
| cons _ _ _ ih =>
simp only [sup_cons, forall_mem_cons] at hs ⊢
exact hp _ hs.1 _ (ih hs.2)
#align finset.sup_induction Finset.sup_induction
theorem sup_le_of_le_directed {α : Type*} [SemilatticeSup α] [OrderBot α] (s : Set α)
(hs : s.Nonempty) (hdir : DirectedOn (· ≤ ·) s) (t : Finset α) :
(∀ x ∈ t, ∃ y ∈ s, x ≤ y) → ∃ x ∈ s, t.sup id ≤ x := by
classical
induction' t using Finset.induction_on with a r _ ih h
· simpa only [forall_prop_of_true, and_true_iff, forall_prop_of_false, bot_le, not_false_iff,
sup_empty, forall_true_iff, not_mem_empty]
· intro h
have incs : (r : Set α) ⊆ ↑(insert a r) := by
rw [Finset.coe_subset]
apply Finset.subset_insert
-- x ∈ s is above the sup of r
obtain ⟨x, ⟨hxs, hsx_sup⟩⟩ := ih fun x hx => h x <| incs hx
-- y ∈ s is above a
obtain ⟨y, hys, hay⟩ := h a (Finset.mem_insert_self a r)
-- z ∈ s is above x and y
obtain ⟨z, hzs, ⟨hxz, hyz⟩⟩ := hdir x hxs y hys
use z, hzs
rw [sup_insert, id, sup_le_iff]
exact ⟨le_trans hay hyz, le_trans hsx_sup hxz⟩
#align finset.sup_le_of_le_directed Finset.sup_le_of_le_directed
-- If we acquire sublattices
-- the hypotheses should be reformulated as `s : SubsemilatticeSupBot`
theorem sup_mem (s : Set α) (w₁ : ⊥ ∈ s) (w₂ : ∀ᵉ (x ∈ s) (y ∈ s), x ⊔ y ∈ s)
{ι : Type*} (t : Finset ι) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.sup p ∈ s :=
@sup_induction _ _ _ _ _ _ (· ∈ s) w₁ w₂ h
#align finset.sup_mem Finset.sup_mem
@[simp]
protected theorem sup_eq_bot_iff (f : β → α) (S : Finset β) : S.sup f = ⊥ ↔ ∀ s ∈ S, f s = ⊥ := by
classical induction' S using Finset.induction with a S _ hi <;> simp [*]
#align finset.sup_eq_bot_iff Finset.sup_eq_bot_iff
end Sup
theorem sup_eq_iSup [CompleteLattice β] (s : Finset α) (f : α → β) : s.sup f = ⨆ a ∈ s, f a :=
le_antisymm
(Finset.sup_le (fun a ha => le_iSup_of_le a <| le_iSup (fun _ => f a) ha))
(iSup_le fun _ => iSup_le fun ha => le_sup ha)
#align finset.sup_eq_supr Finset.sup_eq_iSup
theorem sup_id_eq_sSup [CompleteLattice α] (s : Finset α) : s.sup id = sSup s := by
simp [sSup_eq_iSup, sup_eq_iSup]
#align finset.sup_id_eq_Sup Finset.sup_id_eq_sSup
theorem sup_id_set_eq_sUnion (s : Finset (Set α)) : s.sup id = ⋃₀ ↑s :=
sup_id_eq_sSup _
#align finset.sup_id_set_eq_sUnion Finset.sup_id_set_eq_sUnion
@[simp]
theorem sup_set_eq_biUnion (s : Finset α) (f : α → Set β) : s.sup f = ⋃ x ∈ s, f x :=
sup_eq_iSup _ _
#align finset.sup_set_eq_bUnion Finset.sup_set_eq_biUnion
theorem sup_eq_sSup_image [CompleteLattice β] (s : Finset α) (f : α → β) :
s.sup f = sSup (f '' s) := by
classical rw [← Finset.coe_image, ← sup_id_eq_sSup, sup_image, Function.id_comp]
#align finset.sup_eq_Sup_image Finset.sup_eq_sSup_image
/-! ### inf -/
section Inf
-- TODO: define with just `[Top α]` where some lemmas hold without requiring `[OrderTop α]`
variable [SemilatticeInf α] [OrderTop α]
/-- Infimum of a finite set: `inf {a, b, c} f = f a ⊓ f b ⊓ f c` -/
def inf (s : Finset β) (f : β → α) : α :=
s.fold (· ⊓ ·) ⊤ f
#align finset.inf Finset.inf
variable {s s₁ s₂ : Finset β} {f g : β → α} {a : α}
theorem inf_def : s.inf f = (s.1.map f).inf :=
rfl
#align finset.inf_def Finset.inf_def
@[simp]
theorem inf_empty : (∅ : Finset β).inf f = ⊤ :=
fold_empty
#align finset.inf_empty Finset.inf_empty
@[simp]
theorem inf_cons {b : β} (h : b ∉ s) : (cons b s h).inf f = f b ⊓ s.inf f :=
@sup_cons αᵒᵈ _ _ _ _ _ _ h
#align finset.inf_cons Finset.inf_cons
@[simp]
theorem inf_insert [DecidableEq β] {b : β} : (insert b s : Finset β).inf f = f b ⊓ s.inf f :=
fold_insert_idem
#align finset.inf_insert Finset.inf_insert
@[simp]
theorem inf_image [DecidableEq β] (s : Finset γ) (f : γ → β) (g : β → α) :
(s.image f).inf g = s.inf (g ∘ f) :=
fold_image_idem
#align finset.inf_image Finset.inf_image
@[simp]
theorem inf_map (s : Finset γ) (f : γ ↪ β) (g : β → α) : (s.map f).inf g = s.inf (g ∘ f) :=
fold_map
#align finset.inf_map Finset.inf_map
@[simp]
theorem inf_singleton {b : β} : ({b} : Finset β).inf f = f b :=
Multiset.inf_singleton
#align finset.inf_singleton Finset.inf_singleton
theorem inf_inf : s.inf (f ⊓ g) = s.inf f ⊓ s.inf g :=
@sup_sup αᵒᵈ _ _ _ _ _ _
#align finset.inf_inf Finset.inf_inf
theorem inf_congr {f g : β → α} (hs : s₁ = s₂) (hfg : ∀ a ∈ s₂, f a = g a) :
s₁.inf f = s₂.inf g := by
subst hs
exact Finset.fold_congr hfg
#align finset.inf_congr Finset.inf_congr
@[simp]
theorem _root_.map_finset_inf [SemilatticeInf β] [OrderTop β]
[FunLike F α β] [InfTopHomClass F α β]
(f : F) (s : Finset ι) (g : ι → α) : f (s.inf g) = s.inf (f ∘ g) :=
Finset.cons_induction_on s (map_top f) fun i s _ h => by
rw [inf_cons, inf_cons, map_inf, h, Function.comp_apply]
#align map_finset_inf map_finset_inf
@[simp] protected theorem le_inf_iff {a : α} : a ≤ s.inf f ↔ ∀ b ∈ s, a ≤ f b :=
@Finset.sup_le_iff αᵒᵈ _ _ _ _ _ _
#align finset.le_inf_iff Finset.le_inf_iff
protected alias ⟨_, le_inf⟩ := Finset.le_inf_iff
#align finset.le_inf Finset.le_inf
theorem le_inf_const_le : a ≤ s.inf fun _ => a :=
Finset.le_inf fun _ _ => le_rfl
#align finset.le_inf_const_le Finset.le_inf_const_le
theorem inf_le {b : β} (hb : b ∈ s) : s.inf f ≤ f b :=
Finset.le_inf_iff.1 le_rfl _ hb
#align finset.inf_le Finset.inf_le
theorem inf_le_of_le {b : β} (hb : b ∈ s) (h : f b ≤ a) : s.inf f ≤ a := (inf_le hb).trans h
#align finset.inf_le_of_le Finset.inf_le_of_le
theorem inf_union [DecidableEq β] : (s₁ ∪ s₂).inf f = s₁.inf f ⊓ s₂.inf f :=
eq_of_forall_le_iff fun c ↦ by simp [or_imp, forall_and]
#align finset.inf_union Finset.inf_union
@[simp] theorem inf_biUnion [DecidableEq β] (s : Finset γ) (t : γ → Finset β) :
(s.biUnion t).inf f = s.inf fun x => (t x).inf f :=
@sup_biUnion αᵒᵈ _ _ _ _ _ _ _ _
#align finset.inf_bUnion Finset.inf_biUnion
theorem inf_const (h : s.Nonempty) (c : α) : (s.inf fun _ => c) = c := @sup_const αᵒᵈ _ _ _ _ h _
#align finset.inf_const Finset.inf_const
@[simp] theorem inf_top (s : Finset β) : (s.inf fun _ => ⊤) = (⊤ : α) := @sup_bot αᵒᵈ _ _ _ _
#align finset.inf_top Finset.inf_top
theorem inf_ite (p : β → Prop) [DecidablePred p] :
(s.inf fun i ↦ ite (p i) (f i) (g i)) = (s.filter p).inf f ⊓ (s.filter fun i ↦ ¬ p i).inf g :=
fold_ite _
theorem inf_mono_fun {g : β → α} (h : ∀ b ∈ s, f b ≤ g b) : s.inf f ≤ s.inf g :=
Finset.le_inf fun b hb => le_trans (inf_le hb) (h b hb)
#align finset.inf_mono_fun Finset.inf_mono_fun
@[gcongr]
theorem inf_mono (h : s₁ ⊆ s₂) : s₂.inf f ≤ s₁.inf f :=
Finset.le_inf (fun _ hb => inf_le (h hb))
#align finset.inf_mono Finset.inf_mono
protected theorem inf_comm (s : Finset β) (t : Finset γ) (f : β → γ → α) :
(s.inf fun b => t.inf (f b)) = t.inf fun c => s.inf fun b => f b c :=
@Finset.sup_comm αᵒᵈ _ _ _ _ _ _ _
#align finset.inf_comm Finset.inf_comm
theorem inf_attach (s : Finset β) (f : β → α) : (s.attach.inf fun x => f x) = s.inf f :=
@sup_attach αᵒᵈ _ _ _ _ _
#align finset.inf_attach Finset.inf_attach
theorem inf_product_left (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).inf f = s.inf fun i => t.inf fun i' => f ⟨i, i'⟩ :=
@sup_product_left αᵒᵈ _ _ _ _ _ _ _
#align finset.inf_product_left Finset.inf_product_left
theorem inf_product_right (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).inf f = t.inf fun i' => s.inf fun i => f ⟨i, i'⟩ :=
@sup_product_right αᵒᵈ _ _ _ _ _ _ _
#align finset.inf_product_right Finset.inf_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeInf α] [SemilatticeInf β] [OrderTop α] [OrderTop β]
{s : Finset ι} {t : Finset κ}
@[simp] lemma inf_prodMap (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
inf (s ×ˢ t) (Prod.map f g) = (inf s f, inf t g) :=
sup_prodMap (α := αᵒᵈ) (β := βᵒᵈ) hs ht _ _
end Prod
@[simp]
theorem inf_erase_top [DecidableEq α] (s : Finset α) : (s.erase ⊤).inf id = s.inf id :=
@sup_erase_bot αᵒᵈ _ _ _ _
#align finset.inf_erase_top Finset.inf_erase_top
theorem comp_inf_eq_inf_comp [SemilatticeInf γ] [OrderTop γ] {s : Finset β} {f : β → α} (g : α → γ)
(g_inf : ∀ x y, g (x ⊓ y) = g x ⊓ g y) (top : g ⊤ = ⊤) : g (s.inf f) = s.inf (g ∘ f) :=
@comp_sup_eq_sup_comp αᵒᵈ _ γᵒᵈ _ _ _ _ _ _ _ g_inf top
#align finset.comp_inf_eq_inf_comp Finset.comp_inf_eq_inf_comp
/-- Computing `inf` in a subtype (closed under `inf`) is the same as computing it in `α`. -/
theorem inf_coe {P : α → Prop} {Ptop : P ⊤} {Pinf : ∀ ⦃x y⦄, P x → P y → P (x ⊓ y)} (t : Finset β)
(f : β → { x : α // P x }) :
(@inf { x // P x } _ (Subtype.semilatticeInf Pinf) (Subtype.orderTop Ptop) t f : α) =
t.inf fun x => ↑(f x) :=
@sup_coe αᵒᵈ _ _ _ _ Ptop Pinf t f
#align finset.inf_coe Finset.inf_coe
theorem _root_.List.foldr_inf_eq_inf_toFinset [DecidableEq α] (l : List α) :
l.foldr (· ⊓ ·) ⊤ = l.toFinset.inf id := by
rw [← coe_fold_r, ← Multiset.fold_dedup_idem, inf_def, ← List.toFinset_coe, toFinset_val,
Multiset.map_id]
rfl
#align list.foldr_inf_eq_inf_to_finset List.foldr_inf_eq_inf_toFinset
theorem inf_induction {p : α → Prop} (ht : p ⊤) (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊓ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.inf f) :=
@sup_induction αᵒᵈ _ _ _ _ _ _ ht hp hs
#align finset.inf_induction Finset.inf_induction
theorem inf_mem (s : Set α) (w₁ : ⊤ ∈ s) (w₂ : ∀ᵉ (x ∈ s) (y ∈ s), x ⊓ y ∈ s)
{ι : Type*} (t : Finset ι) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.inf p ∈ s :=
@inf_induction _ _ _ _ _ _ (· ∈ s) w₁ w₂ h
#align finset.inf_mem Finset.inf_mem
@[simp]
protected theorem inf_eq_top_iff (f : β → α) (S : Finset β) : S.inf f = ⊤ ↔ ∀ s ∈ S, f s = ⊤ :=
@Finset.sup_eq_bot_iff αᵒᵈ _ _ _ _ _
#align finset.inf_eq_top_iff Finset.inf_eq_top_iff
end Inf
@[simp]
theorem toDual_sup [SemilatticeSup α] [OrderBot α] (s : Finset β) (f : β → α) :
toDual (s.sup f) = s.inf (toDual ∘ f) :=
rfl
#align finset.to_dual_sup Finset.toDual_sup
@[simp]
theorem toDual_inf [SemilatticeInf α] [OrderTop α] (s : Finset β) (f : β → α) :
toDual (s.inf f) = s.sup (toDual ∘ f) :=
rfl
#align finset.to_dual_inf Finset.toDual_inf
@[simp]
theorem ofDual_sup [SemilatticeInf α] [OrderTop α] (s : Finset β) (f : β → αᵒᵈ) :
ofDual (s.sup f) = s.inf (ofDual ∘ f) :=
rfl
#align finset.of_dual_sup Finset.ofDual_sup
@[simp]
theorem ofDual_inf [SemilatticeSup α] [OrderBot α] (s : Finset β) (f : β → αᵒᵈ) :
ofDual (s.inf f) = s.sup (ofDual ∘ f) :=
rfl
#align finset.of_dual_inf Finset.ofDual_inf
section DistribLattice
variable [DistribLattice α]
section OrderBot
variable [OrderBot α] {s : Finset ι} {t : Finset κ} {f : ι → α} {g : κ → α} {a : α}
theorem sup_inf_distrib_left (s : Finset ι) (f : ι → α) (a : α) :
a ⊓ s.sup f = s.sup fun i => a ⊓ f i := by
induction s using Finset.cons_induction with
| empty => simp_rw [Finset.sup_empty, inf_bot_eq]
| cons _ _ _ h => rw [sup_cons, sup_cons, inf_sup_left, h]
#align finset.sup_inf_distrib_left Finset.sup_inf_distrib_left
theorem sup_inf_distrib_right (s : Finset ι) (f : ι → α) (a : α) :
s.sup f ⊓ a = s.sup fun i => f i ⊓ a := by
rw [_root_.inf_comm, s.sup_inf_distrib_left]
simp_rw [_root_.inf_comm]
#align finset.sup_inf_distrib_right Finset.sup_inf_distrib_right
protected theorem disjoint_sup_right : Disjoint a (s.sup f) ↔ ∀ ⦃i⦄, i ∈ s → Disjoint a (f i) := by
simp only [disjoint_iff, sup_inf_distrib_left, Finset.sup_eq_bot_iff]
#align finset.disjoint_sup_right Finset.disjoint_sup_right
protected theorem disjoint_sup_left : Disjoint (s.sup f) a ↔ ∀ ⦃i⦄, i ∈ s → Disjoint (f i) a := by
simp only [disjoint_iff, sup_inf_distrib_right, Finset.sup_eq_bot_iff]
#align finset.disjoint_sup_left Finset.disjoint_sup_left
theorem sup_inf_sup (s : Finset ι) (t : Finset κ) (f : ι → α) (g : κ → α) :
s.sup f ⊓ t.sup g = (s ×ˢ t).sup fun i => f i.1 ⊓ g i.2 := by
simp_rw [Finset.sup_inf_distrib_right, Finset.sup_inf_distrib_left, sup_product_left]
#align finset.sup_inf_sup Finset.sup_inf_sup
end OrderBot
section OrderTop
variable [OrderTop α] {f : ι → α} {g : κ → α} {s : Finset ι} {t : Finset κ} {a : α}
theorem inf_sup_distrib_left (s : Finset ι) (f : ι → α) (a : α) :
a ⊔ s.inf f = s.inf fun i => a ⊔ f i :=
@sup_inf_distrib_left αᵒᵈ _ _ _ _ _ _
#align finset.inf_sup_distrib_left Finset.inf_sup_distrib_left
theorem inf_sup_distrib_right (s : Finset ι) (f : ι → α) (a : α) :
s.inf f ⊔ a = s.inf fun i => f i ⊔ a :=
@sup_inf_distrib_right αᵒᵈ _ _ _ _ _ _
#align finset.inf_sup_distrib_right Finset.inf_sup_distrib_right
protected theorem codisjoint_inf_right :
Codisjoint a (s.inf f) ↔ ∀ ⦃i⦄, i ∈ s → Codisjoint a (f i) :=
@Finset.disjoint_sup_right αᵒᵈ _ _ _ _ _ _
#align finset.codisjoint_inf_right Finset.codisjoint_inf_right
protected theorem codisjoint_inf_left :
Codisjoint (s.inf f) a ↔ ∀ ⦃i⦄, i ∈ s → Codisjoint (f i) a :=
@Finset.disjoint_sup_left αᵒᵈ _ _ _ _ _ _
#align finset.codisjoint_inf_left Finset.codisjoint_inf_left
theorem inf_sup_inf (s : Finset ι) (t : Finset κ) (f : ι → α) (g : κ → α) :
s.inf f ⊔ t.inf g = (s ×ˢ t).inf fun i => f i.1 ⊔ g i.2 :=
@sup_inf_sup αᵒᵈ _ _ _ _ _ _ _ _
#align finset.inf_sup_inf Finset.inf_sup_inf
end OrderTop
section BoundedOrder
variable [BoundedOrder α] [DecidableEq ι]
--TODO: Extract out the obvious isomorphism `(insert i s).pi t ≃ t i ×ˢ s.pi t` from this proof
theorem inf_sup {κ : ι → Type*} (s : Finset ι) (t : ∀ i, Finset (κ i)) (f : ∀ i, κ i → α) :
(s.inf fun i => (t i).sup (f i)) =
(s.pi t).sup fun g => s.attach.inf fun i => f _ <| g _ i.2 := by
induction' s using Finset.induction with i s hi ih
· simp
rw [inf_insert, ih, attach_insert, sup_inf_sup]
refine eq_of_forall_ge_iff fun c => ?_
simp only [Finset.sup_le_iff, mem_product, mem_pi, and_imp, Prod.forall,
inf_insert, inf_image]
refine
⟨fun h g hg =>
h (g i <| mem_insert_self _ _) (fun j hj => g j <| mem_insert_of_mem hj)
(hg _ <| mem_insert_self _ _) fun j hj => hg _ <| mem_insert_of_mem hj,
fun h a g ha hg => ?_⟩
-- TODO: This `have` must be named to prevent it being shadowed by the internal `this` in `simpa`
have aux : ∀ j : { x // x ∈ s }, ↑j ≠ i := fun j : s => ne_of_mem_of_not_mem j.2 hi
-- Porting note: `simpa` doesn't support placeholders in proof terms
have := h (fun j hj => if hji : j = i then cast (congr_arg κ hji.symm) a
else g _ <| mem_of_mem_insert_of_ne hj hji) (fun j hj => ?_)
· simpa only [cast_eq, dif_pos, Function.comp, Subtype.coe_mk, dif_neg, aux] using this
rw [mem_insert] at hj
obtain (rfl | hj) := hj
· simpa
· simpa [ne_of_mem_of_not_mem hj hi] using hg _ _
#align finset.inf_sup Finset.inf_sup
theorem sup_inf {κ : ι → Type*} (s : Finset ι) (t : ∀ i, Finset (κ i)) (f : ∀ i, κ i → α) :
(s.sup fun i => (t i).inf (f i)) = (s.pi t).inf fun g => s.attach.sup fun i => f _ <| g _ i.2 :=
@inf_sup αᵒᵈ _ _ _ _ _ _ _ _
#align finset.sup_inf Finset.sup_inf
end BoundedOrder
end DistribLattice
section BooleanAlgebra
variable [BooleanAlgebra α] {s : Finset ι}
theorem sup_sdiff_left (s : Finset ι) (f : ι → α) (a : α) :
(s.sup fun b => a \ f b) = a \ s.inf f := by
induction s using Finset.cons_induction with
| empty => rw [sup_empty, inf_empty, sdiff_top]
| cons _ _ _ h => rw [sup_cons, inf_cons, h, sdiff_inf]
#align finset.sup_sdiff_left Finset.sup_sdiff_left
theorem inf_sdiff_left (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.inf fun b => a \ f b) = a \ s.sup f := by
induction hs using Finset.Nonempty.cons_induction with
| singleton => rw [sup_singleton, inf_singleton]
| cons _ _ _ _ ih => rw [sup_cons, inf_cons, ih, sdiff_sup]
#align finset.inf_sdiff_left Finset.inf_sdiff_left
theorem inf_sdiff_right (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.inf fun b => f b \ a) = s.inf f \ a := by
induction hs using Finset.Nonempty.cons_induction with
| singleton => rw [inf_singleton, inf_singleton]
| cons _ _ _ _ ih => rw [inf_cons, inf_cons, ih, inf_sdiff]
#align finset.inf_sdiff_right Finset.inf_sdiff_right
theorem inf_himp_right (s : Finset ι) (f : ι → α) (a : α) :
(s.inf fun b => f b ⇨ a) = s.sup f ⇨ a :=
@sup_sdiff_left αᵒᵈ _ _ _ _ _
#align finset.inf_himp_right Finset.inf_himp_right
theorem sup_himp_right (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.sup fun b => f b ⇨ a) = s.inf f ⇨ a :=
@inf_sdiff_left αᵒᵈ _ _ _ hs _ _
#align finset.sup_himp_right Finset.sup_himp_right
theorem sup_himp_left (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.sup fun b => a ⇨ f b) = a ⇨ s.sup f :=
@inf_sdiff_right αᵒᵈ _ _ _ hs _ _
#align finset.sup_himp_left Finset.sup_himp_left
@[simp]
protected theorem compl_sup (s : Finset ι) (f : ι → α) : (s.sup f)ᶜ = s.inf fun i => (f i)ᶜ :=
map_finset_sup (OrderIso.compl α) _ _
#align finset.compl_sup Finset.compl_sup
@[simp]
protected theorem compl_inf (s : Finset ι) (f : ι → α) : (s.inf f)ᶜ = s.sup fun i => (f i)ᶜ :=
map_finset_inf (OrderIso.compl α) _ _
#align finset.compl_inf Finset.compl_inf
end BooleanAlgebra
section LinearOrder
variable [LinearOrder α]
section OrderBot
variable [OrderBot α] {s : Finset ι} {f : ι → α} {a : α}
theorem comp_sup_eq_sup_comp_of_is_total [SemilatticeSup β] [OrderBot β] (g : α → β)
(mono_g : Monotone g) (bot : g ⊥ = ⊥) : g (s.sup f) = s.sup (g ∘ f) :=
comp_sup_eq_sup_comp g mono_g.map_sup bot
#align finset.comp_sup_eq_sup_comp_of_is_total Finset.comp_sup_eq_sup_comp_of_is_total
@[simp]
protected theorem le_sup_iff (ha : ⊥ < a) : a ≤ s.sup f ↔ ∃ b ∈ s, a ≤ f b := by
apply Iff.intro
· induction s using cons_induction with
| empty => exact (absurd · (not_le_of_lt ha))
| cons c t hc ih =>
rw [sup_cons, le_sup_iff]
exact fun
| Or.inl h => ⟨c, mem_cons.2 (Or.inl rfl), h⟩
| Or.inr h => let ⟨b, hb, hle⟩ := ih h; ⟨b, mem_cons.2 (Or.inr hb), hle⟩
· exact fun ⟨b, hb, hle⟩ => le_trans hle (le_sup hb)
#align finset.le_sup_iff Finset.le_sup_iff
@[simp]
protected theorem lt_sup_iff : a < s.sup f ↔ ∃ b ∈ s, a < f b := by
apply Iff.intro
· induction s using cons_induction with
| empty => exact (absurd · not_lt_bot)
| cons c t hc ih =>
rw [sup_cons, lt_sup_iff]
exact fun
| Or.inl h => ⟨c, mem_cons.2 (Or.inl rfl), h⟩
| Or.inr h => let ⟨b, hb, hlt⟩ := ih h; ⟨b, mem_cons.2 (Or.inr hb), hlt⟩
· exact fun ⟨b, hb, hlt⟩ => lt_of_lt_of_le hlt (le_sup hb)
#align finset.lt_sup_iff Finset.lt_sup_iff
@[simp]
protected theorem sup_lt_iff (ha : ⊥ < a) : s.sup f < a ↔ ∀ b ∈ s, f b < a :=
⟨fun hs b hb => lt_of_le_of_lt (le_sup hb) hs,
Finset.cons_induction_on s (fun _ => ha) fun c t hc => by
simpa only [sup_cons, sup_lt_iff, mem_cons, forall_eq_or_imp] using And.imp_right⟩
#align finset.sup_lt_iff Finset.sup_lt_iff
end OrderBot
section OrderTop
variable [OrderTop α] {s : Finset ι} {f : ι → α} {a : α}
theorem comp_inf_eq_inf_comp_of_is_total [SemilatticeInf β] [OrderTop β] (g : α → β)
(mono_g : Monotone g) (top : g ⊤ = ⊤) : g (s.inf f) = s.inf (g ∘ f) :=
comp_inf_eq_inf_comp g mono_g.map_inf top
#align finset.comp_inf_eq_inf_comp_of_is_total Finset.comp_inf_eq_inf_comp_of_is_total
@[simp]
protected theorem inf_le_iff (ha : a < ⊤) : s.inf f ≤ a ↔ ∃ b ∈ s, f b ≤ a :=
@Finset.le_sup_iff αᵒᵈ _ _ _ _ _ _ ha
#align finset.inf_le_iff Finset.inf_le_iff
@[simp]
protected theorem inf_lt_iff : s.inf f < a ↔ ∃ b ∈ s, f b < a :=
@Finset.lt_sup_iff αᵒᵈ _ _ _ _ _ _
#align finset.inf_lt_iff Finset.inf_lt_iff
@[simp]
protected theorem lt_inf_iff (ha : a < ⊤) : a < s.inf f ↔ ∀ b ∈ s, a < f b :=
@Finset.sup_lt_iff αᵒᵈ _ _ _ _ _ _ ha
#align finset.lt_inf_iff Finset.lt_inf_iff
end OrderTop
end LinearOrder
theorem inf_eq_iInf [CompleteLattice β] (s : Finset α) (f : α → β) : s.inf f = ⨅ a ∈ s, f a :=
@sup_eq_iSup _ βᵒᵈ _ _ _
#align finset.inf_eq_infi Finset.inf_eq_iInf
theorem inf_id_eq_sInf [CompleteLattice α] (s : Finset α) : s.inf id = sInf s :=
@sup_id_eq_sSup αᵒᵈ _ _
#align finset.inf_id_eq_Inf Finset.inf_id_eq_sInf
theorem inf_id_set_eq_sInter (s : Finset (Set α)) : s.inf id = ⋂₀ ↑s :=
inf_id_eq_sInf _
#align finset.inf_id_set_eq_sInter Finset.inf_id_set_eq_sInter
@[simp]
theorem inf_set_eq_iInter (s : Finset α) (f : α → Set β) : s.inf f = ⋂ x ∈ s, f x :=
inf_eq_iInf _ _
#align finset.inf_set_eq_bInter Finset.inf_set_eq_iInter
theorem inf_eq_sInf_image [CompleteLattice β] (s : Finset α) (f : α → β) :
s.inf f = sInf (f '' s) :=
@sup_eq_sSup_image _ βᵒᵈ _ _ _
#align finset.inf_eq_Inf_image Finset.inf_eq_sInf_image
section Sup'
variable [SemilatticeSup α]
theorem sup_of_mem {s : Finset β} (f : β → α) {b : β} (h : b ∈ s) :
∃ a : α, s.sup ((↑) ∘ f : β → WithBot α) = ↑a :=
Exists.imp (fun _ => And.left) (@le_sup (WithBot α) _ _ _ _ _ _ h (f b) rfl)
#align finset.sup_of_mem Finset.sup_of_mem
/-- Given nonempty finset `s` then `s.sup' H f` is the supremum of its image under `f` in (possibly
unbounded) join-semilattice `α`, where `H` is a proof of nonemptiness. If `α` has a bottom element
you may instead use `Finset.sup` which does not require `s` nonempty. -/
def sup' (s : Finset β) (H : s.Nonempty) (f : β → α) : α :=
WithBot.unbot (s.sup ((↑) ∘ f)) (by simpa using H)
#align finset.sup' Finset.sup'
variable {s : Finset β} (H : s.Nonempty) (f : β → α)
@[simp]
theorem coe_sup' : ((s.sup' H f : α) : WithBot α) = s.sup ((↑) ∘ f) := by
rw [sup', WithBot.coe_unbot]
#align finset.coe_sup' Finset.coe_sup'
@[simp]
theorem sup'_cons {b : β} {hb : b ∉ s} :
(cons b s hb).sup' (nonempty_cons hb) f = f b ⊔ s.sup' H f := by
rw [← WithBot.coe_eq_coe]
simp [WithBot.coe_sup]
#align finset.sup'_cons Finset.sup'_cons
@[simp]
theorem sup'_insert [DecidableEq β] {b : β} :
(insert b s).sup' (insert_nonempty _ _) f = f b ⊔ s.sup' H f := by
rw [← WithBot.coe_eq_coe]
simp [WithBot.coe_sup]
#align finset.sup'_insert Finset.sup'_insert
@[simp]
theorem sup'_singleton {b : β} : ({b} : Finset β).sup' (singleton_nonempty _) f = f b :=
rfl
#align finset.sup'_singleton Finset.sup'_singleton
@[simp]
theorem sup'_le_iff {a : α} : s.sup' H f ≤ a ↔ ∀ b ∈ s, f b ≤ a := by
simp_rw [← @WithBot.coe_le_coe α, coe_sup', Finset.sup_le_iff]; rfl
#align finset.sup'_le_iff Finset.sup'_le_iff
alias ⟨_, sup'_le⟩ := sup'_le_iff
#align finset.sup'_le Finset.sup'_le
theorem le_sup' {b : β} (h : b ∈ s) : f b ≤ s.sup' ⟨b, h⟩ f :=
(sup'_le_iff ⟨b, h⟩ f).1 le_rfl b h
#align finset.le_sup' Finset.le_sup'
theorem le_sup'_of_le {a : α} {b : β} (hb : b ∈ s) (h : a ≤ f b) : a ≤ s.sup' ⟨b, hb⟩ f :=
h.trans <| le_sup' _ hb
#align finset.le_sup'_of_le Finset.le_sup'_of_le
@[simp]
theorem sup'_const (a : α) : s.sup' H (fun _ => a) = a := by
apply le_antisymm
· apply sup'_le
intros
exact le_rfl
· apply le_sup' (fun _ => a) H.choose_spec
#align finset.sup'_const Finset.sup'_const
theorem sup'_union [DecidableEq β] {s₁ s₂ : Finset β} (h₁ : s₁.Nonempty) (h₂ : s₂.Nonempty)
(f : β → α) :
(s₁ ∪ s₂).sup' (h₁.mono subset_union_left) f = s₁.sup' h₁ f ⊔ s₂.sup' h₂ f :=
eq_of_forall_ge_iff fun a => by simp [or_imp, forall_and]
#align finset.sup'_union Finset.sup'_union
theorem sup'_biUnion [DecidableEq β] {s : Finset γ} (Hs : s.Nonempty) {t : γ → Finset β}
(Ht : ∀ b, (t b).Nonempty) :
(s.biUnion t).sup' (Hs.biUnion fun b _ => Ht b) f = s.sup' Hs (fun b => (t b).sup' (Ht b) f) :=
eq_of_forall_ge_iff fun c => by simp [@forall_swap _ β]
#align finset.sup'_bUnion Finset.sup'_biUnion
protected theorem sup'_comm {t : Finset γ} (hs : s.Nonempty) (ht : t.Nonempty) (f : β → γ → α) :
(s.sup' hs fun b => t.sup' ht (f b)) = t.sup' ht fun c => s.sup' hs fun b => f b c :=
eq_of_forall_ge_iff fun a => by simpa using forall₂_swap
#align finset.sup'_comm Finset.sup'_comm
theorem sup'_product_left {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).sup' h f = s.sup' h.fst fun i => t.sup' h.snd fun i' => f ⟨i, i'⟩ :=
eq_of_forall_ge_iff fun a => by simp [@forall_swap _ γ]
#align finset.sup'_product_left Finset.sup'_product_left
theorem sup'_product_right {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).sup' h f = t.sup' h.snd fun i' => s.sup' h.fst fun i => f ⟨i, i'⟩ := by
rw [sup'_product_left, Finset.sup'_comm]
#align finset.sup'_product_right Finset.sup'_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeSup α] [SemilatticeSup β] {s : Finset ι} {t : Finset κ}
/-- See also `Finset.sup'_prodMap`. -/
lemma prodMk_sup'_sup' (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
(sup' s hs f, sup' t ht g) = sup' (s ×ˢ t) (hs.product ht) (Prod.map f g) :=
eq_of_forall_ge_iff fun i ↦ by
obtain ⟨a, ha⟩ := hs
obtain ⟨b, hb⟩ := ht
simp only [Prod.map, sup'_le_iff, mem_product, and_imp, Prod.forall, Prod.le_def]
exact ⟨by aesop, fun h ↦ ⟨fun i hi ↦ (h _ _ hi hb).1, fun j hj ↦ (h _ _ ha hj).2⟩⟩
/-- See also `Finset.prodMk_sup'_sup'`. -/
-- @[simp] -- TODO: Why does `Prod.map_apply` simplify the LHS?
lemma sup'_prodMap (hst : (s ×ˢ t).Nonempty) (f : ι → α) (g : κ → β) :
sup' (s ×ˢ t) hst (Prod.map f g) = (sup' s hst.fst f, sup' t hst.snd g) :=
(prodMk_sup'_sup' _ _ _ _).symm
end Prod
theorem sup'_induction {p : α → Prop} (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊔ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.sup' H f) := by
show @WithBot.recBotCoe α (fun _ => Prop) True p ↑(s.sup' H f)
rw [coe_sup']
refine sup_induction trivial (fun a₁ h₁ a₂ h₂ ↦ ?_) hs
match a₁, a₂ with
| ⊥, _ => rwa [bot_sup_eq]
| (a₁ : α), ⊥ => rwa [sup_bot_eq]
| (a₁ : α), (a₂ : α) => exact hp a₁ h₁ a₂ h₂
#align finset.sup'_induction Finset.sup'_induction
theorem sup'_mem (s : Set α) (w : ∀ᵉ (x ∈ s) (y ∈ s), x ⊔ y ∈ s) {ι : Type*}
(t : Finset ι) (H : t.Nonempty) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.sup' H p ∈ s :=
sup'_induction H p w h
#align finset.sup'_mem Finset.sup'_mem
@[congr]
theorem sup'_congr {t : Finset β} {f g : β → α} (h₁ : s = t) (h₂ : ∀ x ∈ s, f x = g x) :
s.sup' H f = t.sup' (h₁ ▸ H) g := by
subst s
refine eq_of_forall_ge_iff fun c => ?_
simp (config := { contextual := true }) only [sup'_le_iff, h₂]
#align finset.sup'_congr Finset.sup'_congr
theorem comp_sup'_eq_sup'_comp [SemilatticeSup γ] {s : Finset β} (H : s.Nonempty) {f : β → α}
(g : α → γ) (g_sup : ∀ x y, g (x ⊔ y) = g x ⊔ g y) : g (s.sup' H f) = s.sup' H (g ∘ f) := by
refine H.cons_induction ?_ ?_ <;> intros <;> simp [*]
#align finset.comp_sup'_eq_sup'_comp Finset.comp_sup'_eq_sup'_comp
@[simp]
theorem _root_.map_finset_sup' [SemilatticeSup β] [FunLike F α β] [SupHomClass F α β]
(f : F) {s : Finset ι} (hs) (g : ι → α) :
f (s.sup' hs g) = s.sup' hs (f ∘ g) := by
refine hs.cons_induction ?_ ?_ <;> intros <;> simp [*]
#align map_finset_sup' map_finset_sup'
lemma nsmul_sup' [LinearOrderedAddCommMonoid β] {s : Finset α}
(hs : s.Nonempty) (f : α → β) (n : ℕ) :
s.sup' hs (fun a => n • f a) = n • s.sup' hs f :=
let ns : SupHom β β := { toFun := (n • ·), map_sup' := fun _ _ => (nsmul_right_mono n).map_max }
(map_finset_sup' ns hs _).symm
/-- To rewrite from right to left, use `Finset.sup'_comp_eq_image`. -/
@[simp]
theorem sup'_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : (s.image f).Nonempty)
(g : β → α) :
(s.image f).sup' hs g = s.sup' hs.of_image (g ∘ f) := by
rw [← WithBot.coe_eq_coe]; simp only [coe_sup', sup_image, WithBot.coe_sup]; rfl
#align finset.sup'_image Finset.sup'_image
/-- A version of `Finset.sup'_image` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma sup'_comp_eq_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : s.Nonempty) (g : β → α) :
s.sup' hs (g ∘ f) = (s.image f).sup' (hs.image f) g :=
.symm <| sup'_image _ _
/-- To rewrite from right to left, use `Finset.sup'_comp_eq_map`. -/
@[simp]
theorem sup'_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : (s.map f).Nonempty) :
(s.map f).sup' hs g = s.sup' (map_nonempty.1 hs) (g ∘ f) := by
rw [← WithBot.coe_eq_coe, coe_sup', sup_map, coe_sup']
rfl
#align finset.sup'_map Finset.sup'_map
/-- A version of `Finset.sup'_map` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma sup'_comp_eq_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : s.Nonempty) :
s.sup' hs (g ∘ f) = (s.map f).sup' (map_nonempty.2 hs) g :=
.symm <| sup'_map _ _
theorem sup'_mono {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂) (h₁ : s₁.Nonempty):
s₁.sup' h₁ f ≤ s₂.sup' (h₁.mono h) f :=
Finset.sup'_le h₁ _ (fun _ hb => le_sup' _ (h hb))
/-- A version of `Finset.sup'_mono` acceptable for `@[gcongr]`.
Instead of deducing `s₂.Nonempty` from `s₁.Nonempty` and `s₁ ⊆ s₂`,
this version takes it as an argument. -/
@[gcongr]
lemma _root_.GCongr.finset_sup'_le {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂)
{h₁ : s₁.Nonempty} {h₂ : s₂.Nonempty} : s₁.sup' h₁ f ≤ s₂.sup' h₂ f :=
sup'_mono f h h₁
end Sup'
section Inf'
variable [SemilatticeInf α]
theorem inf_of_mem {s : Finset β} (f : β → α) {b : β} (h : b ∈ s) :
∃ a : α, s.inf ((↑) ∘ f : β → WithTop α) = ↑a :=
@sup_of_mem αᵒᵈ _ _ _ f _ h
#align finset.inf_of_mem Finset.inf_of_mem
/-- Given nonempty finset `s` then `s.inf' H f` is the infimum of its image under `f` in (possibly
unbounded) meet-semilattice `α`, where `H` is a proof of nonemptiness. If `α` has a top element you
may instead use `Finset.inf` which does not require `s` nonempty. -/
def inf' (s : Finset β) (H : s.Nonempty) (f : β → α) : α :=
WithTop.untop (s.inf ((↑) ∘ f)) (by simpa using H)
#align finset.inf' Finset.inf'
variable {s : Finset β} (H : s.Nonempty) (f : β → α)
@[simp]
theorem coe_inf' : ((s.inf' H f : α) : WithTop α) = s.inf ((↑) ∘ f) :=
@coe_sup' αᵒᵈ _ _ _ H f
#align finset.coe_inf' Finset.coe_inf'
@[simp]
theorem inf'_cons {b : β} {hb : b ∉ s} :
(cons b s hb).inf' (nonempty_cons hb) f = f b ⊓ s.inf' H f :=
@sup'_cons αᵒᵈ _ _ _ H f _ _
#align finset.inf'_cons Finset.inf'_cons
@[simp]
theorem inf'_insert [DecidableEq β] {b : β} :
(insert b s).inf' (insert_nonempty _ _) f = f b ⊓ s.inf' H f :=
@sup'_insert αᵒᵈ _ _ _ H f _ _
#align finset.inf'_insert Finset.inf'_insert
@[simp]
theorem inf'_singleton {b : β} : ({b} : Finset β).inf' (singleton_nonempty _) f = f b :=
rfl
#align finset.inf'_singleton Finset.inf'_singleton
@[simp]
theorem le_inf'_iff {a : α} : a ≤ s.inf' H f ↔ ∀ b ∈ s, a ≤ f b :=
sup'_le_iff (α := αᵒᵈ) H f
#align finset.le_inf'_iff Finset.le_inf'_iff
theorem le_inf' {a : α} (hs : ∀ b ∈ s, a ≤ f b) : a ≤ s.inf' H f :=
sup'_le (α := αᵒᵈ) H f hs
#align finset.le_inf' Finset.le_inf'
theorem inf'_le {b : β} (h : b ∈ s) : s.inf' ⟨b, h⟩ f ≤ f b :=
le_sup' (α := αᵒᵈ) f h
#align finset.inf'_le Finset.inf'_le
theorem inf'_le_of_le {a : α} {b : β} (hb : b ∈ s) (h : f b ≤ a) :
s.inf' ⟨b, hb⟩ f ≤ a := (inf'_le _ hb).trans h
#align finset.inf'_le_of_le Finset.inf'_le_of_le
@[simp]
theorem inf'_const (a : α) : (s.inf' H fun _ => a) = a :=
sup'_const (α := αᵒᵈ) H a
#align finset.inf'_const Finset.inf'_const
theorem inf'_union [DecidableEq β] {s₁ s₂ : Finset β} (h₁ : s₁.Nonempty) (h₂ : s₂.Nonempty)
(f : β → α) :
(s₁ ∪ s₂).inf' (h₁.mono subset_union_left) f = s₁.inf' h₁ f ⊓ s₂.inf' h₂ f :=
@sup'_union αᵒᵈ _ _ _ _ _ h₁ h₂ _
#align finset.inf'_union Finset.inf'_union
theorem inf'_biUnion [DecidableEq β] {s : Finset γ} (Hs : s.Nonempty) {t : γ → Finset β}
(Ht : ∀ b, (t b).Nonempty) :
(s.biUnion t).inf' (Hs.biUnion fun b _ => Ht b) f = s.inf' Hs (fun b => (t b).inf' (Ht b) f) :=
sup'_biUnion (α := αᵒᵈ) _ Hs Ht
#align finset.inf'_bUnion Finset.inf'_biUnion
protected theorem inf'_comm {t : Finset γ} (hs : s.Nonempty) (ht : t.Nonempty) (f : β → γ → α) :
(s.inf' hs fun b => t.inf' ht (f b)) = t.inf' ht fun c => s.inf' hs fun b => f b c :=
@Finset.sup'_comm αᵒᵈ _ _ _ _ _ hs ht _
#align finset.inf'_comm Finset.inf'_comm
theorem inf'_product_left {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).inf' h f = s.inf' h.fst fun i => t.inf' h.snd fun i' => f ⟨i, i'⟩ :=
sup'_product_left (α := αᵒᵈ) h f
#align finset.inf'_product_left Finset.inf'_product_left
theorem inf'_product_right {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).inf' h f = t.inf' h.snd fun i' => s.inf' h.fst fun i => f ⟨i, i'⟩ :=
sup'_product_right (α := αᵒᵈ) h f
#align finset.inf'_product_right Finset.inf'_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeInf α] [SemilatticeInf β] {s : Finset ι} {t : Finset κ}
/-- See also `Finset.inf'_prodMap`. -/
lemma prodMk_inf'_inf' (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
(inf' s hs f, inf' t ht g) = inf' (s ×ˢ t) (hs.product ht) (Prod.map f g) :=
prodMk_sup'_sup' (α := αᵒᵈ) (β := βᵒᵈ) hs ht _ _
/-- See also `Finset.prodMk_inf'_inf'`. -/
-- @[simp] -- TODO: Why does `Prod.map_apply` simplify the LHS?
lemma inf'_prodMap (hst : (s ×ˢ t).Nonempty) (f : ι → α) (g : κ → β) :
inf' (s ×ˢ t) hst (Prod.map f g) = (inf' s hst.fst f, inf' t hst.snd g) :=
(prodMk_inf'_inf' _ _ _ _).symm
end Prod
theorem comp_inf'_eq_inf'_comp [SemilatticeInf γ] {s : Finset β} (H : s.Nonempty) {f : β → α}
(g : α → γ) (g_inf : ∀ x y, g (x ⊓ y) = g x ⊓ g y) : g (s.inf' H f) = s.inf' H (g ∘ f) :=
comp_sup'_eq_sup'_comp (α := αᵒᵈ) (γ := γᵒᵈ) H g g_inf
#align finset.comp_inf'_eq_inf'_comp Finset.comp_inf'_eq_inf'_comp
theorem inf'_induction {p : α → Prop} (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊓ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.inf' H f) :=
sup'_induction (α := αᵒᵈ) H f hp hs
#align finset.inf'_induction Finset.inf'_induction
theorem inf'_mem (s : Set α) (w : ∀ᵉ (x ∈ s) (y ∈ s), x ⊓ y ∈ s) {ι : Type*}
(t : Finset ι) (H : t.Nonempty) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.inf' H p ∈ s :=
inf'_induction H p w h
#align finset.inf'_mem Finset.inf'_mem
@[congr]
theorem inf'_congr {t : Finset β} {f g : β → α} (h₁ : s = t) (h₂ : ∀ x ∈ s, f x = g x) :
s.inf' H f = t.inf' (h₁ ▸ H) g :=
sup'_congr (α := αᵒᵈ) H h₁ h₂
#align finset.inf'_congr Finset.inf'_congr
@[simp]
theorem _root_.map_finset_inf' [SemilatticeInf β] [FunLike F α β] [InfHomClass F α β]
(f : F) {s : Finset ι} (hs) (g : ι → α) :
f (s.inf' hs g) = s.inf' hs (f ∘ g) := by
refine hs.cons_induction ?_ ?_ <;> intros <;> simp [*]
#align map_finset_inf' map_finset_inf'
lemma nsmul_inf' [LinearOrderedAddCommMonoid β] {s : Finset α}
(hs : s.Nonempty) (f : α → β) (n : ℕ) :
s.inf' hs (fun a => n • f a) = n • s.inf' hs f :=
let ns : InfHom β β := { toFun := (n • ·), map_inf' := fun _ _ => (nsmul_right_mono n).map_min }
(map_finset_inf' ns hs _).symm
/-- To rewrite from right to left, use `Finset.inf'_comp_eq_image`. -/
@[simp]
theorem inf'_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : (s.image f).Nonempty)
(g : β → α) :
(s.image f).inf' hs g = s.inf' hs.of_image (g ∘ f) :=
@sup'_image αᵒᵈ _ _ _ _ _ _ hs _
#align finset.inf'_image Finset.inf'_image
/-- A version of `Finset.inf'_image` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma inf'_comp_eq_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : s.Nonempty) (g : β → α) :
s.inf' hs (g ∘ f) = (s.image f).inf' (hs.image f) g :=
sup'_comp_eq_image (α := αᵒᵈ) hs g
/-- To rewrite from right to left, use `Finset.inf'_comp_eq_map`. -/
@[simp]
theorem inf'_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : (s.map f).Nonempty) :
(s.map f).inf' hs g = s.inf' (map_nonempty.1 hs) (g ∘ f) :=
sup'_map (α := αᵒᵈ) _ hs
#align finset.inf'_map Finset.inf'_map
/-- A version of `Finset.inf'_map` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma inf'_comp_eq_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : s.Nonempty) :
s.inf' hs (g ∘ f) = (s.map f).inf' (map_nonempty.2 hs) g :=
sup'_comp_eq_map (α := αᵒᵈ) g hs
theorem inf'_mono {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂) (h₁ : s₁.Nonempty) :
s₂.inf' (h₁.mono h) f ≤ s₁.inf' h₁ f :=
Finset.le_inf' h₁ _ (fun _ hb => inf'_le _ (h hb))
/-- A version of `Finset.inf'_mono` acceptable for `@[gcongr]`.
Instead of deducing `s₂.Nonempty` from `s₁.Nonempty` and `s₁ ⊆ s₂`,
this version takes it as an argument. -/
@[gcongr]
lemma _root_.GCongr.finset_inf'_mono {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂)
{h₁ : s₁.Nonempty} {h₂ : s₂.Nonempty} : s₂.inf' h₂ f ≤ s₁.inf' h₁ f :=
inf'_mono f h h₁
end Inf'
section Sup
variable [SemilatticeSup α] [OrderBot α]
theorem sup'_eq_sup {s : Finset β} (H : s.Nonempty) (f : β → α) : s.sup' H f = s.sup f :=
le_antisymm (sup'_le H f fun _ => le_sup) (Finset.sup_le fun _ => le_sup' f)
#align finset.sup'_eq_sup Finset.sup'_eq_sup
theorem coe_sup_of_nonempty {s : Finset β} (h : s.Nonempty) (f : β → α) :
(↑(s.sup f) : WithBot α) = s.sup ((↑) ∘ f) := by simp only [← sup'_eq_sup h, coe_sup' h]
#align finset.coe_sup_of_nonempty Finset.coe_sup_of_nonempty
end Sup
section Inf
variable [SemilatticeInf α] [OrderTop α]
theorem inf'_eq_inf {s : Finset β} (H : s.Nonempty) (f : β → α) : s.inf' H f = s.inf f :=
sup'_eq_sup (α := αᵒᵈ) H f
#align finset.inf'_eq_inf Finset.inf'_eq_inf
theorem coe_inf_of_nonempty {s : Finset β} (h : s.Nonempty) (f : β → α) :
(↑(s.inf f) : WithTop α) = s.inf ((↑) ∘ f) :=
coe_sup_of_nonempty (α := αᵒᵈ) h f
#align finset.coe_inf_of_nonempty Finset.coe_inf_of_nonempty
end Inf
@[simp]
protected theorem sup_apply {C : β → Type*} [∀ b : β, SemilatticeSup (C b)]
[∀ b : β, OrderBot (C b)] (s : Finset α) (f : α → ∀ b : β, C b) (b : β) :
s.sup f b = s.sup fun a => f a b :=
comp_sup_eq_sup_comp (fun x : ∀ b : β, C b => x b) (fun _ _ => rfl) rfl
#align finset.sup_apply Finset.sup_apply
@[simp]
protected theorem inf_apply {C : β → Type*} [∀ b : β, SemilatticeInf (C b)]
[∀ b : β, OrderTop (C b)] (s : Finset α) (f : α → ∀ b : β, C b) (b : β) :
s.inf f b = s.inf fun a => f a b :=
Finset.sup_apply (C := fun b => (C b)ᵒᵈ) s f b
#align finset.inf_apply Finset.inf_apply
@[simp]
protected theorem sup'_apply {C : β → Type*} [∀ b : β, SemilatticeSup (C b)]
{s : Finset α} (H : s.Nonempty) (f : α → ∀ b : β, C b) (b : β) :
s.sup' H f b = s.sup' H fun a => f a b :=
comp_sup'_eq_sup'_comp H (fun x : ∀ b : β, C b => x b) fun _ _ => rfl
#align finset.sup'_apply Finset.sup'_apply
@[simp]
protected theorem inf'_apply {C : β → Type*} [∀ b : β, SemilatticeInf (C b)]
{s : Finset α} (H : s.Nonempty) (f : α → ∀ b : β, C b) (b : β) :
s.inf' H f b = s.inf' H fun a => f a b :=
Finset.sup'_apply (C := fun b => (C b)ᵒᵈ) H f b
#align finset.inf'_apply Finset.inf'_apply
@[simp]
theorem toDual_sup' [SemilatticeSup α] {s : Finset ι} (hs : s.Nonempty) (f : ι → α) :
toDual (s.sup' hs f) = s.inf' hs (toDual ∘ f) :=
rfl
#align finset.to_dual_sup' Finset.toDual_sup'
@[simp]
theorem toDual_inf' [SemilatticeInf α] {s : Finset ι} (hs : s.Nonempty) (f : ι → α) :
toDual (s.inf' hs f) = s.sup' hs (toDual ∘ f) :=
rfl
#align finset.to_dual_inf' Finset.toDual_inf'
@[simp]
theorem ofDual_sup' [SemilatticeInf α] {s : Finset ι} (hs : s.Nonempty) (f : ι → αᵒᵈ) :
ofDual (s.sup' hs f) = s.inf' hs (ofDual ∘ f) :=
rfl
#align finset.of_dual_sup' Finset.ofDual_sup'
@[simp]
theorem ofDual_inf' [SemilatticeSup α] {s : Finset ι} (hs : s.Nonempty) (f : ι → αᵒᵈ) :
ofDual (s.inf' hs f) = s.sup' hs (ofDual ∘ f) :=
rfl
#align finset.of_dual_inf' Finset.ofDual_inf'
section DistribLattice
variable [DistribLattice α] {s : Finset ι} {t : Finset κ} (hs : s.Nonempty) (ht : t.Nonempty)
{f : ι → α} {g : κ → α} {a : α}
theorem sup'_inf_distrib_left (f : ι → α) (a : α) :
a ⊓ s.sup' hs f = s.sup' hs fun i ↦ a ⊓ f i := by
induction hs using Finset.Nonempty.cons_induction with
| singleton => simp
| cons _ _ _ hs ih => simp_rw [sup'_cons hs, inf_sup_left, ih]
#align finset.sup'_inf_distrib_left Finset.sup'_inf_distrib_left
theorem sup'_inf_distrib_right (f : ι → α) (a : α) :
s.sup' hs f ⊓ a = s.sup' hs fun i => f i ⊓ a := by
rw [inf_comm, sup'_inf_distrib_left]; simp_rw [inf_comm]
#align finset.sup'_inf_distrib_right Finset.sup'_inf_distrib_right
theorem sup'_inf_sup' (f : ι → α) (g : κ → α) :
s.sup' hs f ⊓ t.sup' ht g = (s ×ˢ t).sup' (hs.product ht) fun i => f i.1 ⊓ g i.2 := by
simp_rw [Finset.sup'_inf_distrib_right, Finset.sup'_inf_distrib_left, sup'_product_left]
#align finset.sup'_inf_sup' Finset.sup'_inf_sup'
theorem inf'_sup_distrib_left (f : ι → α) (a : α) : a ⊔ s.inf' hs f = s.inf' hs fun i => a ⊔ f i :=
@sup'_inf_distrib_left αᵒᵈ _ _ _ hs _ _
#align finset.inf'_sup_distrib_left Finset.inf'_sup_distrib_left
theorem inf'_sup_distrib_right (f : ι → α) (a : α) : s.inf' hs f ⊔ a = s.inf' hs fun i => f i ⊔ a :=
@sup'_inf_distrib_right αᵒᵈ _ _ _ hs _ _
#align finset.inf'_sup_distrib_right Finset.inf'_sup_distrib_right
theorem inf'_sup_inf' (f : ι → α) (g : κ → α) :
s.inf' hs f ⊔ t.inf' ht g = (s ×ˢ t).inf' (hs.product ht) fun i => f i.1 ⊔ g i.2 :=
@sup'_inf_sup' αᵒᵈ _ _ _ _ _ hs ht _ _
#align finset.inf'_sup_inf' Finset.inf'_sup_inf'
end DistribLattice
section LinearOrder
variable [LinearOrder α] {s : Finset ι} (H : s.Nonempty) {f : ι → α} {a : α}
@[simp]
theorem le_sup'_iff : a ≤ s.sup' H f ↔ ∃ b ∈ s, a ≤ f b := by
rw [← WithBot.coe_le_coe, coe_sup', Finset.le_sup_iff (WithBot.bot_lt_coe a)]
exact exists_congr (fun _ => and_congr_right' WithBot.coe_le_coe)
#align finset.le_sup'_iff Finset.le_sup'_iff
@[simp]
theorem lt_sup'_iff : a < s.sup' H f ↔ ∃ b ∈ s, a < f b := by
rw [← WithBot.coe_lt_coe, coe_sup', Finset.lt_sup_iff]
exact exists_congr (fun _ => and_congr_right' WithBot.coe_lt_coe)
#align finset.lt_sup'_iff Finset.lt_sup'_iff
@[simp]
theorem sup'_lt_iff : s.sup' H f < a ↔ ∀ i ∈ s, f i < a := by
rw [← WithBot.coe_lt_coe, coe_sup', Finset.sup_lt_iff (WithBot.bot_lt_coe a)]
exact forall₂_congr (fun _ _ => WithBot.coe_lt_coe)
#align finset.sup'_lt_iff Finset.sup'_lt_iff
@[simp]
theorem inf'_le_iff : s.inf' H f ≤ a ↔ ∃ i ∈ s, f i ≤ a :=
le_sup'_iff (α := αᵒᵈ) H
#align finset.inf'_le_iff Finset.inf'_le_iff
@[simp]
theorem inf'_lt_iff : s.inf' H f < a ↔ ∃ i ∈ s, f i < a :=
lt_sup'_iff (α := αᵒᵈ) H
#align finset.inf'_lt_iff Finset.inf'_lt_iff
@[simp]
theorem lt_inf'_iff : a < s.inf' H f ↔ ∀ i ∈ s, a < f i :=
sup'_lt_iff (α := αᵒᵈ) H
#align finset.lt_inf'_iff Finset.lt_inf'_iff
theorem exists_mem_eq_sup' (f : ι → α) : ∃ i, i ∈ s ∧ s.sup' H f = f i := by
induction H using Finset.Nonempty.cons_induction with
| singleton c => exact ⟨c, mem_singleton_self c, rfl⟩
| cons c s hcs hs ih =>
rcases ih with ⟨b, hb, h'⟩
rw [sup'_cons hs, h']
cases le_total (f b) (f c) with
| inl h => exact ⟨c, mem_cons.2 (Or.inl rfl), sup_eq_left.2 h⟩
| inr h => exact ⟨b, mem_cons.2 (Or.inr hb), sup_eq_right.2 h⟩
#align finset.exists_mem_eq_sup' Finset.exists_mem_eq_sup'
theorem exists_mem_eq_inf' (f : ι → α) : ∃ i, i ∈ s ∧ s.inf' H f = f i :=
exists_mem_eq_sup' (α := αᵒᵈ) H f
#align finset.exists_mem_eq_inf' Finset.exists_mem_eq_inf'
theorem exists_mem_eq_sup [OrderBot α] (s : Finset ι) (h : s.Nonempty) (f : ι → α) :
∃ i, i ∈ s ∧ s.sup f = f i :=
sup'_eq_sup h f ▸ exists_mem_eq_sup' h f
#align finset.exists_mem_eq_sup Finset.exists_mem_eq_sup
theorem exists_mem_eq_inf [OrderTop α] (s : Finset ι) (h : s.Nonempty) (f : ι → α) :
∃ i, i ∈ s ∧ s.inf f = f i :=
exists_mem_eq_sup (α := αᵒᵈ) s h f
#align finset.exists_mem_eq_inf Finset.exists_mem_eq_inf
end LinearOrder
/-! ### max and min of finite sets -/
section MaxMin
variable [LinearOrder α]
/-- Let `s` be a finset in a linear order. Then `s.max` is the maximum of `s` if `s` is not empty,
and `⊥` otherwise. It belongs to `WithBot α`. If you want to get an element of `α`, see
`s.max'`. -/
protected def max (s : Finset α) : WithBot α :=
sup s (↑)
#align finset.max Finset.max
theorem max_eq_sup_coe {s : Finset α} : s.max = s.sup (↑) :=
rfl
#align finset.max_eq_sup_coe Finset.max_eq_sup_coe
theorem max_eq_sup_withBot (s : Finset α) : s.max = sup s (↑) :=
rfl
#align finset.max_eq_sup_with_bot Finset.max_eq_sup_withBot
@[simp]
theorem max_empty : (∅ : Finset α).max = ⊥ :=
rfl
#align finset.max_empty Finset.max_empty
@[simp]
theorem max_insert {a : α} {s : Finset α} : (insert a s).max = max ↑a s.max :=
fold_insert_idem
#align finset.max_insert Finset.max_insert
@[simp]
theorem max_singleton {a : α} : Finset.max {a} = (a : WithBot α) := by
rw [← insert_emptyc_eq]
exact max_insert
#align finset.max_singleton Finset.max_singleton
theorem max_of_mem {s : Finset α} {a : α} (h : a ∈ s) : ∃ b : α, s.max = b := by
obtain ⟨b, h, _⟩ := le_sup (α := WithBot α) h _ rfl
exact ⟨b, h⟩
#align finset.max_of_mem Finset.max_of_mem
theorem max_of_nonempty {s : Finset α} (h : s.Nonempty) : ∃ a : α, s.max = a :=
let ⟨_, h⟩ := h
max_of_mem h
#align finset.max_of_nonempty Finset.max_of_nonempty
theorem max_eq_bot {s : Finset α} : s.max = ⊥ ↔ s = ∅ :=
⟨fun h ↦ s.eq_empty_or_nonempty.elim id fun H ↦ by
obtain ⟨a, ha⟩ := max_of_nonempty H
rw [h] at ha; cases ha; , -- the `;` is needed since the `cases` syntax allows `cases a, b`
fun h ↦ h.symm ▸ max_empty⟩
#align finset.max_eq_bot Finset.max_eq_bot
theorem mem_of_max {s : Finset α} : ∀ {a : α}, s.max = a → a ∈ s := by
induction' s using Finset.induction_on with b s _ ih
· intro _ H; cases H
· intro a h
by_cases p : b = a
· induction p
exact mem_insert_self b s
· cases' max_choice (↑b) s.max with q q <;> rw [max_insert, q] at h
· cases h
cases p rfl
· exact mem_insert_of_mem (ih h)
#align finset.mem_of_max Finset.mem_of_max
theorem le_max {a : α} {s : Finset α} (as : a ∈ s) : ↑a ≤ s.max :=
le_sup as
#align finset.le_max Finset.le_max
theorem not_mem_of_max_lt_coe {a : α} {s : Finset α} (h : s.max < a) : a ∉ s :=
mt le_max h.not_le
#align finset.not_mem_of_max_lt_coe Finset.not_mem_of_max_lt_coe
theorem le_max_of_eq {s : Finset α} {a b : α} (h₁ : a ∈ s) (h₂ : s.max = b) : a ≤ b :=
WithBot.coe_le_coe.mp <| (le_max h₁).trans h₂.le
#align finset.le_max_of_eq Finset.le_max_of_eq
theorem not_mem_of_max_lt {s : Finset α} {a b : α} (h₁ : b < a) (h₂ : s.max = ↑b) : a ∉ s :=
Finset.not_mem_of_max_lt_coe <| h₂.trans_lt <| WithBot.coe_lt_coe.mpr h₁
#align finset.not_mem_of_max_lt Finset.not_mem_of_max_lt
@[gcongr]
theorem max_mono {s t : Finset α} (st : s ⊆ t) : s.max ≤ t.max :=
sup_mono st
#align finset.max_mono Finset.max_mono
protected theorem max_le {M : WithBot α} {s : Finset α} (st : ∀ a ∈ s, (a : WithBot α) ≤ M) :
s.max ≤ M :=
Finset.sup_le st
#align finset.max_le Finset.max_le
/-- Let `s` be a finset in a linear order. Then `s.min` is the minimum of `s` if `s` is not empty,
and `⊤` otherwise. It belongs to `WithTop α`. If you want to get an element of `α`, see
`s.min'`. -/
protected def min (s : Finset α) : WithTop α :=
inf s (↑)
#align finset.min Finset.min
theorem min_eq_inf_withTop (s : Finset α) : s.min = inf s (↑) :=
rfl
#align finset.min_eq_inf_with_top Finset.min_eq_inf_withTop
@[simp]
theorem min_empty : (∅ : Finset α).min = ⊤ :=
rfl
#align finset.min_empty Finset.min_empty
@[simp]
theorem min_insert {a : α} {s : Finset α} : (insert a s).min = min (↑a) s.min :=
fold_insert_idem
#align finset.min_insert Finset.min_insert
@[simp]
| Mathlib/Data/Finset/Lattice.lean | 1,457 | 1,459 | theorem min_singleton {a : α} : Finset.min {a} = (a : WithTop α) := by |
rw [← insert_emptyc_eq]
exact min_insert
|
/-
Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn
-/
import Mathlib.Data.Finset.Basic
import Mathlib.ModelTheory.Syntax
import Mathlib.Data.List.ProdSigma
#align_import model_theory.semantics from "leanprover-community/mathlib"@"d565b3df44619c1498326936be16f1a935df0728"
/-!
# Basics on First-Order Semantics
This file defines the interpretations of first-order terms, formulas, sentences, and theories
in a style inspired by the [Flypitch project](https://flypitch.github.io/).
## Main Definitions
* `FirstOrder.Language.Term.realize` is defined so that `t.realize v` is the term `t` evaluated at
variables `v`.
* `FirstOrder.Language.BoundedFormula.Realize` is defined so that `φ.Realize v xs` is the bounded
formula `φ` evaluated at tuples of variables `v` and `xs`.
* `FirstOrder.Language.Formula.Realize` is defined so that `φ.Realize v` is the formula `φ`
evaluated at variables `v`.
* `FirstOrder.Language.Sentence.Realize` is defined so that `φ.Realize M` is the sentence `φ`
evaluated in the structure `M`. Also denoted `M ⊨ φ`.
* `FirstOrder.Language.Theory.Model` is defined so that `T.Model M` is true if and only if every
sentence of `T` is realized in `M`. Also denoted `T ⊨ φ`.
## Main Results
* `FirstOrder.Language.BoundedFormula.realize_toPrenex` shows that the prenex normal form of a
formula has the same realization as the original formula.
* Several results in this file show that syntactic constructions such as `relabel`, `castLE`,
`liftAt`, `subst`, and the actions of language maps commute with realization of terms, formulas,
sentences, and theories.
## Implementation Notes
* Formulas use a modified version of de Bruijn variables. Specifically, a `L.BoundedFormula α n`
is a formula with some variables indexed by a type `α`, which cannot be quantified over, and some
indexed by `Fin n`, which can. For any `φ : L.BoundedFormula α (n + 1)`, we define the formula
`∀' φ : L.BoundedFormula α n` by universally quantifying over the variable indexed by
`n : Fin (n + 1)`.
## References
For the Flypitch project:
- [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*]
[flypitch_cpp]
- [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of
the continuum hypothesis*][flypitch_itp]
-/
universe u v w u' v'
namespace FirstOrder
namespace Language
variable {L : Language.{u, v}} {L' : Language}
variable {M : Type w} {N P : Type*} [L.Structure M] [L.Structure N] [L.Structure P]
variable {α : Type u'} {β : Type v'} {γ : Type*}
open FirstOrder Cardinal
open Structure Cardinal Fin
namespace Term
-- Porting note: universes in different order
/-- A term `t` with variables indexed by `α` can be evaluated by giving a value to each variable. -/
def realize (v : α → M) : ∀ _t : L.Term α, M
| var k => v k
| func f ts => funMap f fun i => (ts i).realize v
#align first_order.language.term.realize FirstOrder.Language.Term.realize
/- Porting note: The equation lemma of `realize` is too strong; it simplifies terms like the LHS of
`realize_functions_apply₁`. Even `eqns` can't fix this. We removed `simp` attr from `realize` and
prepare new simp lemmas for `realize`. -/
@[simp]
theorem realize_var (v : α → M) (k) : realize v (var k : L.Term α) = v k := rfl
@[simp]
theorem realize_func (v : α → M) {n} (f : L.Functions n) (ts) :
realize v (func f ts : L.Term α) = funMap f fun i => (ts i).realize v := rfl
@[simp]
theorem realize_relabel {t : L.Term α} {g : α → β} {v : β → M} :
(t.relabel g).realize v = t.realize (v ∘ g) := by
induction' t with _ n f ts ih
· rfl
· simp [ih]
#align first_order.language.term.realize_relabel FirstOrder.Language.Term.realize_relabel
@[simp]
theorem realize_liftAt {n n' m : ℕ} {t : L.Term (Sum α (Fin n))} {v : Sum α (Fin (n + n')) → M} :
(t.liftAt n' m).realize v =
t.realize (v ∘ Sum.map id fun i : Fin _ =>
if ↑i < m then Fin.castAdd n' i else Fin.addNat i n') :=
realize_relabel
#align first_order.language.term.realize_lift_at FirstOrder.Language.Term.realize_liftAt
@[simp]
theorem realize_constants {c : L.Constants} {v : α → M} : c.term.realize v = c :=
funMap_eq_coe_constants
#align first_order.language.term.realize_constants FirstOrder.Language.Term.realize_constants
@[simp]
theorem realize_functions_apply₁ {f : L.Functions 1} {t : L.Term α} {v : α → M} :
(f.apply₁ t).realize v = funMap f ![t.realize v] := by
rw [Functions.apply₁, Term.realize]
refine congr rfl (funext fun i => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.term.realize_functions_apply₁ FirstOrder.Language.Term.realize_functions_apply₁
@[simp]
theorem realize_functions_apply₂ {f : L.Functions 2} {t₁ t₂ : L.Term α} {v : α → M} :
(f.apply₂ t₁ t₂).realize v = funMap f ![t₁.realize v, t₂.realize v] := by
rw [Functions.apply₂, Term.realize]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.term.realize_functions_apply₂ FirstOrder.Language.Term.realize_functions_apply₂
theorem realize_con {A : Set M} {a : A} {v : α → M} : (L.con a).term.realize v = a :=
rfl
#align first_order.language.term.realize_con FirstOrder.Language.Term.realize_con
@[simp]
theorem realize_subst {t : L.Term α} {tf : α → L.Term β} {v : β → M} :
(t.subst tf).realize v = t.realize fun a => (tf a).realize v := by
induction' t with _ _ _ _ ih
· rfl
· simp [ih]
#align first_order.language.term.realize_subst FirstOrder.Language.Term.realize_subst
@[simp]
theorem realize_restrictVar [DecidableEq α] {t : L.Term α} {s : Set α} (h : ↑t.varFinset ⊆ s)
{v : α → M} : (t.restrictVar (Set.inclusion h)).realize (v ∘ (↑)) = t.realize v := by
induction' t with _ _ _ _ ih
· rfl
· simp_rw [varFinset, Finset.coe_biUnion, Set.iUnion_subset_iff] at h
exact congr rfl (funext fun i => ih i (h i (Finset.mem_univ i)))
#align first_order.language.term.realize_restrict_var FirstOrder.Language.Term.realize_restrictVar
@[simp]
theorem realize_restrictVarLeft [DecidableEq α] {γ : Type*} {t : L.Term (Sum α γ)} {s : Set α}
(h : ↑t.varFinsetLeft ⊆ s) {v : α → M} {xs : γ → M} :
(t.restrictVarLeft (Set.inclusion h)).realize (Sum.elim (v ∘ (↑)) xs) =
t.realize (Sum.elim v xs) := by
induction' t with a _ _ _ ih
· cases a <;> rfl
· simp_rw [varFinsetLeft, Finset.coe_biUnion, Set.iUnion_subset_iff] at h
exact congr rfl (funext fun i => ih i (h i (Finset.mem_univ i)))
#align first_order.language.term.realize_restrict_var_left FirstOrder.Language.Term.realize_restrictVarLeft
@[simp]
theorem realize_constantsToVars [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{t : L[[α]].Term β} {v : β → M} :
t.constantsToVars.realize (Sum.elim (fun a => ↑(L.con a)) v) = t.realize v := by
induction' t with _ n f ts ih
· simp
· cases n
· cases f
· simp only [realize, ih, Nat.zero_eq, constantsOn, mk₂_Functions]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
· simp only [realize, constantsToVars, Sum.elim_inl, funMap_eq_coe_constants]
rfl
· cases' f with _ f
· simp only [realize, ih, constantsOn, mk₂_Functions]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
· exact isEmptyElim f
#align first_order.language.term.realize_constants_to_vars FirstOrder.Language.Term.realize_constantsToVars
@[simp]
theorem realize_varsToConstants [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{t : L.Term (Sum α β)} {v : β → M} :
t.varsToConstants.realize v = t.realize (Sum.elim (fun a => ↑(L.con a)) v) := by
induction' t with ab n f ts ih
· cases' ab with a b
-- Porting note: both cases were `simp [Language.con]`
· simp [Language.con, realize, funMap_eq_coe_constants]
· simp [realize, constantMap]
· simp only [realize, constantsOn, mk₂_Functions, ih]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
#align first_order.language.term.realize_vars_to_constants FirstOrder.Language.Term.realize_varsToConstants
theorem realize_constantsVarsEquivLeft [L[[α]].Structure M]
[(lhomWithConstants L α).IsExpansionOn M] {n} {t : L[[α]].Term (Sum β (Fin n))} {v : β → M}
{xs : Fin n → M} :
(constantsVarsEquivLeft t).realize (Sum.elim (Sum.elim (fun a => ↑(L.con a)) v) xs) =
t.realize (Sum.elim v xs) := by
simp only [constantsVarsEquivLeft, realize_relabel, Equiv.coe_trans, Function.comp_apply,
constantsVarsEquiv_apply, relabelEquiv_symm_apply]
refine _root_.trans ?_ realize_constantsToVars
rcongr x
rcases x with (a | (b | i)) <;> simp
#align first_order.language.term.realize_constants_vars_equiv_left FirstOrder.Language.Term.realize_constantsVarsEquivLeft
end Term
namespace LHom
@[simp]
theorem realize_onTerm [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] (t : L.Term α)
(v : α → M) : (φ.onTerm t).realize v = t.realize v := by
induction' t with _ n f ts ih
· rfl
· simp only [Term.realize, LHom.onTerm, LHom.map_onFunction, ih]
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_term FirstOrder.Language.LHom.realize_onTerm
end LHom
@[simp]
theorem Hom.realize_term (g : M →[L] N) {t : L.Term α} {v : α → M} :
t.realize (g ∘ v) = g (t.realize v) := by
induction t
· rfl
· rw [Term.realize, Term.realize, g.map_fun]
refine congr rfl ?_
ext x
simp [*]
#align first_order.language.hom.realize_term FirstOrder.Language.Hom.realize_term
@[simp]
theorem Embedding.realize_term {v : α → M} (t : L.Term α) (g : M ↪[L] N) :
t.realize (g ∘ v) = g (t.realize v) :=
g.toHom.realize_term
#align first_order.language.embedding.realize_term FirstOrder.Language.Embedding.realize_term
@[simp]
theorem Equiv.realize_term {v : α → M} (t : L.Term α) (g : M ≃[L] N) :
t.realize (g ∘ v) = g (t.realize v) :=
g.toHom.realize_term
#align first_order.language.equiv.realize_term FirstOrder.Language.Equiv.realize_term
variable {n : ℕ}
namespace BoundedFormula
open Term
-- Porting note: universes in different order
/-- A bounded formula can be evaluated as true or false by giving values to each free variable. -/
def Realize : ∀ {l} (_f : L.BoundedFormula α l) (_v : α → M) (_xs : Fin l → M), Prop
| _, falsum, _v, _xs => False
| _, equal t₁ t₂, v, xs => t₁.realize (Sum.elim v xs) = t₂.realize (Sum.elim v xs)
| _, rel R ts, v, xs => RelMap R fun i => (ts i).realize (Sum.elim v xs)
| _, imp f₁ f₂, v, xs => Realize f₁ v xs → Realize f₂ v xs
| _, all f, v, xs => ∀ x : M, Realize f v (snoc xs x)
#align first_order.language.bounded_formula.realize FirstOrder.Language.BoundedFormula.Realize
variable {l : ℕ} {φ ψ : L.BoundedFormula α l} {θ : L.BoundedFormula α l.succ}
variable {v : α → M} {xs : Fin l → M}
@[simp]
theorem realize_bot : (⊥ : L.BoundedFormula α l).Realize v xs ↔ False :=
Iff.rfl
#align first_order.language.bounded_formula.realize_bot FirstOrder.Language.BoundedFormula.realize_bot
@[simp]
theorem realize_not : φ.not.Realize v xs ↔ ¬φ.Realize v xs :=
Iff.rfl
#align first_order.language.bounded_formula.realize_not FirstOrder.Language.BoundedFormula.realize_not
@[simp]
theorem realize_bdEqual (t₁ t₂ : L.Term (Sum α (Fin l))) :
(t₁.bdEqual t₂).Realize v xs ↔ t₁.realize (Sum.elim v xs) = t₂.realize (Sum.elim v xs) :=
Iff.rfl
#align first_order.language.bounded_formula.realize_bd_equal FirstOrder.Language.BoundedFormula.realize_bdEqual
@[simp]
theorem realize_top : (⊤ : L.BoundedFormula α l).Realize v xs ↔ True := by simp [Top.top]
#align first_order.language.bounded_formula.realize_top FirstOrder.Language.BoundedFormula.realize_top
@[simp]
theorem realize_inf : (φ ⊓ ψ).Realize v xs ↔ φ.Realize v xs ∧ ψ.Realize v xs := by
simp [Inf.inf, Realize]
#align first_order.language.bounded_formula.realize_inf FirstOrder.Language.BoundedFormula.realize_inf
@[simp]
theorem realize_foldr_inf (l : List (L.BoundedFormula α n)) (v : α → M) (xs : Fin n → M) :
(l.foldr (· ⊓ ·) ⊤).Realize v xs ↔ ∀ φ ∈ l, BoundedFormula.Realize φ v xs := by
induction' l with φ l ih
· simp
· simp [ih]
#align first_order.language.bounded_formula.realize_foldr_inf FirstOrder.Language.BoundedFormula.realize_foldr_inf
@[simp]
theorem realize_imp : (φ.imp ψ).Realize v xs ↔ φ.Realize v xs → ψ.Realize v xs := by
simp only [Realize]
#align first_order.language.bounded_formula.realize_imp FirstOrder.Language.BoundedFormula.realize_imp
@[simp]
theorem realize_rel {k : ℕ} {R : L.Relations k} {ts : Fin k → L.Term _} :
(R.boundedFormula ts).Realize v xs ↔ RelMap R fun i => (ts i).realize (Sum.elim v xs) :=
Iff.rfl
#align first_order.language.bounded_formula.realize_rel FirstOrder.Language.BoundedFormula.realize_rel
@[simp]
theorem realize_rel₁ {R : L.Relations 1} {t : L.Term _} :
(R.boundedFormula₁ t).Realize v xs ↔ RelMap R ![t.realize (Sum.elim v xs)] := by
rw [Relations.boundedFormula₁, realize_rel, iff_eq_eq]
refine congr rfl (funext fun _ => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.bounded_formula.realize_rel₁ FirstOrder.Language.BoundedFormula.realize_rel₁
@[simp]
theorem realize_rel₂ {R : L.Relations 2} {t₁ t₂ : L.Term _} :
(R.boundedFormula₂ t₁ t₂).Realize v xs ↔
RelMap R ![t₁.realize (Sum.elim v xs), t₂.realize (Sum.elim v xs)] := by
rw [Relations.boundedFormula₂, realize_rel, iff_eq_eq]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.bounded_formula.realize_rel₂ FirstOrder.Language.BoundedFormula.realize_rel₂
@[simp]
theorem realize_sup : (φ ⊔ ψ).Realize v xs ↔ φ.Realize v xs ∨ ψ.Realize v xs := by
simp only [realize, Sup.sup, realize_not, eq_iff_iff]
tauto
#align first_order.language.bounded_formula.realize_sup FirstOrder.Language.BoundedFormula.realize_sup
@[simp]
theorem realize_foldr_sup (l : List (L.BoundedFormula α n)) (v : α → M) (xs : Fin n → M) :
(l.foldr (· ⊔ ·) ⊥).Realize v xs ↔ ∃ φ ∈ l, BoundedFormula.Realize φ v xs := by
induction' l with φ l ih
· simp
· simp_rw [List.foldr_cons, realize_sup, ih, List.mem_cons, or_and_right, exists_or,
exists_eq_left]
#align first_order.language.bounded_formula.realize_foldr_sup FirstOrder.Language.BoundedFormula.realize_foldr_sup
@[simp]
theorem realize_all : (all θ).Realize v xs ↔ ∀ a : M, θ.Realize v (Fin.snoc xs a) :=
Iff.rfl
#align first_order.language.bounded_formula.realize_all FirstOrder.Language.BoundedFormula.realize_all
@[simp]
theorem realize_ex : θ.ex.Realize v xs ↔ ∃ a : M, θ.Realize v (Fin.snoc xs a) := by
rw [BoundedFormula.ex, realize_not, realize_all, not_forall]
simp_rw [realize_not, Classical.not_not]
#align first_order.language.bounded_formula.realize_ex FirstOrder.Language.BoundedFormula.realize_ex
@[simp]
theorem realize_iff : (φ.iff ψ).Realize v xs ↔ (φ.Realize v xs ↔ ψ.Realize v xs) := by
simp only [BoundedFormula.iff, realize_inf, realize_imp, and_imp, ← iff_def]
#align first_order.language.bounded_formula.realize_iff FirstOrder.Language.BoundedFormula.realize_iff
theorem realize_castLE_of_eq {m n : ℕ} (h : m = n) {h' : m ≤ n} {φ : L.BoundedFormula α m}
{v : α → M} {xs : Fin n → M} : (φ.castLE h').Realize v xs ↔ φ.Realize v (xs ∘ cast h) := by
subst h
simp only [castLE_rfl, cast_refl, OrderIso.coe_refl, Function.comp_id]
#align first_order.language.bounded_formula.realize_cast_le_of_eq FirstOrder.Language.BoundedFormula.realize_castLE_of_eq
theorem realize_mapTermRel_id [L'.Structure M]
{ft : ∀ n, L.Term (Sum α (Fin n)) → L'.Term (Sum β (Fin n))}
{fr : ∀ n, L.Relations n → L'.Relations n} {n} {φ : L.BoundedFormula α n} {v : α → M}
{v' : β → M} {xs : Fin n → M}
(h1 :
∀ (n) (t : L.Term (Sum α (Fin n))) (xs : Fin n → M),
(ft n t).realize (Sum.elim v' xs) = t.realize (Sum.elim v xs))
(h2 : ∀ (n) (R : L.Relations n) (x : Fin n → M), RelMap (fr n R) x = RelMap R x) :
(φ.mapTermRel ft fr fun _ => id).Realize v' xs ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih
· rfl
· simp [mapTermRel, Realize, h1]
· simp [mapTermRel, Realize, h1, h2]
· simp [mapTermRel, Realize, ih1, ih2]
· simp only [mapTermRel, Realize, ih, id]
#align first_order.language.bounded_formula.realize_map_term_rel_id FirstOrder.Language.BoundedFormula.realize_mapTermRel_id
theorem realize_mapTermRel_add_castLe [L'.Structure M] {k : ℕ}
{ft : ∀ n, L.Term (Sum α (Fin n)) → L'.Term (Sum β (Fin (k + n)))}
{fr : ∀ n, L.Relations n → L'.Relations n} {n} {φ : L.BoundedFormula α n}
(v : ∀ {n}, (Fin (k + n) → M) → α → M) {v' : β → M} (xs : Fin (k + n) → M)
(h1 :
∀ (n) (t : L.Term (Sum α (Fin n))) (xs' : Fin (k + n) → M),
(ft n t).realize (Sum.elim v' xs') = t.realize (Sum.elim (v xs') (xs' ∘ Fin.natAdd _)))
(h2 : ∀ (n) (R : L.Relations n) (x : Fin n → M), RelMap (fr n R) x = RelMap R x)
(hv : ∀ (n) (xs : Fin (k + n) → M) (x : M), @v (n + 1) (snoc xs x : Fin _ → M) = v xs) :
(φ.mapTermRel ft fr fun n => castLE (add_assoc _ _ _).symm.le).Realize v' xs ↔
φ.Realize (v xs) (xs ∘ Fin.natAdd _) := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih
· rfl
· simp [mapTermRel, Realize, h1]
· simp [mapTermRel, Realize, h1, h2]
· simp [mapTermRel, Realize, ih1, ih2]
· simp [mapTermRel, Realize, ih, hv]
#align first_order.language.bounded_formula.realize_map_term_rel_add_cast_le FirstOrder.Language.BoundedFormula.realize_mapTermRel_add_castLe
@[simp]
theorem realize_relabel {m n : ℕ} {φ : L.BoundedFormula α n} {g : α → Sum β (Fin m)} {v : β → M}
{xs : Fin (m + n) → M} :
(φ.relabel g).Realize v xs ↔
φ.Realize (Sum.elim v (xs ∘ Fin.castAdd n) ∘ g) (xs ∘ Fin.natAdd m) := by
rw [relabel, realize_mapTermRel_add_castLe] <;> intros <;> simp
#align first_order.language.bounded_formula.realize_relabel FirstOrder.Language.BoundedFormula.realize_relabel
theorem realize_liftAt {n n' m : ℕ} {φ : L.BoundedFormula α n} {v : α → M} {xs : Fin (n + n') → M}
(hmn : m + n' ≤ n + 1) :
(φ.liftAt n' m).Realize v xs ↔
φ.Realize v (xs ∘ fun i => if ↑i < m then Fin.castAdd n' i else Fin.addNat i n') := by
rw [liftAt]
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 k _ ih3
· simp [mapTermRel, Realize]
· simp [mapTermRel, Realize, realize_rel, realize_liftAt, Sum.elim_comp_map]
· simp [mapTermRel, Realize, realize_rel, realize_liftAt, Sum.elim_comp_map]
· simp only [mapTermRel, Realize, ih1 hmn, ih2 hmn]
· have h : k + 1 + n' = k + n' + 1 := by rw [add_assoc, add_comm 1 n', ← add_assoc]
simp only [mapTermRel, Realize, realize_castLE_of_eq h, ih3 (hmn.trans k.succ.le_succ)]
refine forall_congr' fun x => iff_eq_eq.mpr (congr rfl (funext (Fin.lastCases ?_ fun i => ?_)))
· simp only [Function.comp_apply, val_last, snoc_last]
by_cases h : k < m
· rw [if_pos h]
refine (congr rfl (ext ?_)).trans (snoc_last _ _)
simp only [coe_cast, coe_castAdd, val_last, self_eq_add_right]
refine le_antisymm
(le_of_add_le_add_left ((hmn.trans (Nat.succ_le_of_lt h)).trans ?_)) n'.zero_le
rw [add_zero]
· rw [if_neg h]
refine (congr rfl (ext ?_)).trans (snoc_last _ _)
simp
· simp only [Function.comp_apply, Fin.snoc_castSucc]
refine (congr rfl (ext ?_)).trans (snoc_castSucc _ _ _)
simp only [coe_castSucc, coe_cast]
split_ifs <;> simp
#align first_order.language.bounded_formula.realize_lift_at FirstOrder.Language.BoundedFormula.realize_liftAt
theorem realize_liftAt_one {n m : ℕ} {φ : L.BoundedFormula α n} {v : α → M} {xs : Fin (n + 1) → M}
(hmn : m ≤ n) :
(φ.liftAt 1 m).Realize v xs ↔
φ.Realize v (xs ∘ fun i => if ↑i < m then castSucc i else i.succ) := by
simp [realize_liftAt (add_le_add_right hmn 1), castSucc]
#align first_order.language.bounded_formula.realize_lift_at_one FirstOrder.Language.BoundedFormula.realize_liftAt_one
@[simp]
theorem realize_liftAt_one_self {n : ℕ} {φ : L.BoundedFormula α n} {v : α → M}
{xs : Fin (n + 1) → M} : (φ.liftAt 1 n).Realize v xs ↔ φ.Realize v (xs ∘ castSucc) := by
rw [realize_liftAt_one (refl n), iff_eq_eq]
refine congr rfl (congr rfl (funext fun i => ?_))
rw [if_pos i.is_lt]
#align first_order.language.bounded_formula.realize_lift_at_one_self FirstOrder.Language.BoundedFormula.realize_liftAt_one_self
@[simp]
theorem realize_subst {φ : L.BoundedFormula α n} {tf : α → L.Term β} {v : β → M} {xs : Fin n → M} :
(φ.subst tf).Realize v xs ↔ φ.Realize (fun a => (tf a).realize v) xs :=
realize_mapTermRel_id
(fun n t x => by
rw [Term.realize_subst]
rcongr a
cases a
· simp only [Sum.elim_inl, Function.comp_apply, Term.realize_relabel, Sum.elim_comp_inl]
· rfl)
(by simp)
#align first_order.language.bounded_formula.realize_subst FirstOrder.Language.BoundedFormula.realize_subst
@[simp]
theorem realize_restrictFreeVar [DecidableEq α] {n : ℕ} {φ : L.BoundedFormula α n} {s : Set α}
(h : ↑φ.freeVarFinset ⊆ s) {v : α → M} {xs : Fin n → M} :
(φ.restrictFreeVar (Set.inclusion h)).Realize (v ∘ (↑)) xs ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih3
· rfl
· simp [restrictFreeVar, Realize]
· simp [restrictFreeVar, Realize]
· simp [restrictFreeVar, Realize, ih1, ih2]
· simp [restrictFreeVar, Realize, ih3]
#align first_order.language.bounded_formula.realize_restrict_free_var FirstOrder.Language.BoundedFormula.realize_restrictFreeVar
theorem realize_constantsVarsEquiv [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{n} {φ : L[[α]].BoundedFormula β n} {v : β → M} {xs : Fin n → M} :
(constantsVarsEquiv φ).Realize (Sum.elim (fun a => ↑(L.con a)) v) xs ↔ φ.Realize v xs := by
refine realize_mapTermRel_id (fun n t xs => realize_constantsVarsEquivLeft) fun n R xs => ?_
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [← (lhomWithConstants L α).map_onRelation
(Equiv.sumEmpty (L.Relations n) ((constantsOn α).Relations n) R) xs]
rcongr
cases' R with R R
· simp
· exact isEmptyElim R
#align first_order.language.bounded_formula.realize_constants_vars_equiv FirstOrder.Language.BoundedFormula.realize_constantsVarsEquiv
@[simp]
theorem realize_relabelEquiv {g : α ≃ β} {k} {φ : L.BoundedFormula α k} {v : β → M}
{xs : Fin k → M} : (relabelEquiv g φ).Realize v xs ↔ φ.Realize (v ∘ g) xs := by
simp only [relabelEquiv, mapTermRelEquiv_apply, Equiv.coe_refl]
refine realize_mapTermRel_id (fun n t xs => ?_) fun _ _ _ => rfl
simp only [relabelEquiv_apply, Term.realize_relabel]
refine congr (congr rfl ?_) rfl
ext (i | i) <;> rfl
#align first_order.language.bounded_formula.realize_relabel_equiv FirstOrder.Language.BoundedFormula.realize_relabelEquiv
variable [Nonempty M]
theorem realize_all_liftAt_one_self {n : ℕ} {φ : L.BoundedFormula α n} {v : α → M}
{xs : Fin n → M} : (φ.liftAt 1 n).all.Realize v xs ↔ φ.Realize v xs := by
inhabit M
simp only [realize_all, realize_liftAt_one_self]
refine ⟨fun h => ?_, fun h a => ?_⟩
· refine (congr rfl (funext fun i => ?_)).mp (h default)
simp
· refine (congr rfl (funext fun i => ?_)).mp h
simp
#align first_order.language.bounded_formula.realize_all_lift_at_one_self FirstOrder.Language.BoundedFormula.realize_all_liftAt_one_self
theorem realize_toPrenexImpRight {φ ψ : L.BoundedFormula α n} (hφ : IsQF φ) (hψ : IsPrenex ψ)
{v : α → M} {xs : Fin n → M} :
(φ.toPrenexImpRight ψ).Realize v xs ↔ (φ.imp ψ).Realize v xs := by
induction' hψ with _ _ hψ _ _ _hψ ih _ _ _hψ ih
· rw [hψ.toPrenexImpRight]
· refine _root_.trans (forall_congr' fun _ => ih hφ.liftAt) ?_
simp only [realize_imp, realize_liftAt_one_self, snoc_comp_castSucc, realize_all]
exact ⟨fun h1 a h2 => h1 h2 a, fun h1 h2 a => h1 a h2⟩
· unfold toPrenexImpRight
rw [realize_ex]
refine _root_.trans (exists_congr fun _ => ih hφ.liftAt) ?_
simp only [realize_imp, realize_liftAt_one_self, snoc_comp_castSucc, realize_ex]
refine ⟨?_, fun h' => ?_⟩
· rintro ⟨a, ha⟩ h
exact ⟨a, ha h⟩
· by_cases h : φ.Realize v xs
· obtain ⟨a, ha⟩ := h' h
exact ⟨a, fun _ => ha⟩
· inhabit M
exact ⟨default, fun h'' => (h h'').elim⟩
#align first_order.language.bounded_formula.realize_to_prenex_imp_right FirstOrder.Language.BoundedFormula.realize_toPrenexImpRight
theorem realize_toPrenexImp {φ ψ : L.BoundedFormula α n} (hφ : IsPrenex φ) (hψ : IsPrenex ψ)
{v : α → M} {xs : Fin n → M} : (φ.toPrenexImp ψ).Realize v xs ↔ (φ.imp ψ).Realize v xs := by
revert ψ
induction' hφ with _ _ hφ _ _ _hφ ih _ _ _hφ ih <;> intro ψ hψ
· rw [hφ.toPrenexImp]
exact realize_toPrenexImpRight hφ hψ
· unfold toPrenexImp
rw [realize_ex]
refine _root_.trans (exists_congr fun _ => ih hψ.liftAt) ?_
simp only [realize_imp, realize_liftAt_one_self, snoc_comp_castSucc, realize_all]
refine ⟨?_, fun h' => ?_⟩
· rintro ⟨a, ha⟩ h
exact ha (h a)
· by_cases h : ψ.Realize v xs
· inhabit M
exact ⟨default, fun _h'' => h⟩
· obtain ⟨a, ha⟩ := not_forall.1 (h ∘ h')
exact ⟨a, fun h => (ha h).elim⟩
· refine _root_.trans (forall_congr' fun _ => ih hψ.liftAt) ?_
simp
#align first_order.language.bounded_formula.realize_to_prenex_imp FirstOrder.Language.BoundedFormula.realize_toPrenexImp
@[simp]
theorem realize_toPrenex (φ : L.BoundedFormula α n) {v : α → M} :
∀ {xs : Fin n → M}, φ.toPrenex.Realize v xs ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ f1 f2 h1 h2 _ _ h
· exact Iff.rfl
· exact Iff.rfl
· exact Iff.rfl
· intros
rw [toPrenex, realize_toPrenexImp f1.toPrenex_isPrenex f2.toPrenex_isPrenex, realize_imp,
realize_imp, h1, h2]
· intros
rw [realize_all, toPrenex, realize_all]
exact forall_congr' fun a => h
#align first_order.language.bounded_formula.realize_to_prenex FirstOrder.Language.BoundedFormula.realize_toPrenex
end BoundedFormula
-- Porting note: no `protected` attribute in Lean4
-- attribute [protected] bounded_formula.falsum bounded_formula.equal bounded_formula.rel
-- attribute [protected] bounded_formula.imp bounded_formula.all
namespace LHom
open BoundedFormula
@[simp]
theorem realize_onBoundedFormula [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] {n : ℕ}
(ψ : L.BoundedFormula α n) {v : α → M} {xs : Fin n → M} :
(φ.onBoundedFormula ψ).Realize v xs ↔ ψ.Realize v xs := by
induction' ψ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih3
· rfl
· simp only [onBoundedFormula, realize_bdEqual, realize_onTerm]
rfl
· simp only [onBoundedFormula, realize_rel, LHom.map_onRelation,
Function.comp_apply, realize_onTerm]
rfl
· simp only [onBoundedFormula, ih1, ih2, realize_imp]
· simp only [onBoundedFormula, ih3, realize_all]
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_bounded_formula FirstOrder.Language.LHom.realize_onBoundedFormula
end LHom
-- Porting note: no `protected` attribute in Lean4
-- attribute [protected] bounded_formula.falsum bounded_formula.equal bounded_formula.rel
-- attribute [protected] bounded_formula.imp bounded_formula.all
namespace Formula
/-- A formula can be evaluated as true or false by giving values to each free variable. -/
nonrec def Realize (φ : L.Formula α) (v : α → M) : Prop :=
φ.Realize v default
#align first_order.language.formula.realize FirstOrder.Language.Formula.Realize
variable {φ ψ : L.Formula α} {v : α → M}
@[simp]
theorem realize_not : φ.not.Realize v ↔ ¬φ.Realize v :=
Iff.rfl
#align first_order.language.formula.realize_not FirstOrder.Language.Formula.realize_not
@[simp]
theorem realize_bot : (⊥ : L.Formula α).Realize v ↔ False :=
Iff.rfl
#align first_order.language.formula.realize_bot FirstOrder.Language.Formula.realize_bot
@[simp]
theorem realize_top : (⊤ : L.Formula α).Realize v ↔ True :=
BoundedFormula.realize_top
#align first_order.language.formula.realize_top FirstOrder.Language.Formula.realize_top
@[simp]
theorem realize_inf : (φ ⊓ ψ).Realize v ↔ φ.Realize v ∧ ψ.Realize v :=
BoundedFormula.realize_inf
#align first_order.language.formula.realize_inf FirstOrder.Language.Formula.realize_inf
@[simp]
theorem realize_imp : (φ.imp ψ).Realize v ↔ φ.Realize v → ψ.Realize v :=
BoundedFormula.realize_imp
#align first_order.language.formula.realize_imp FirstOrder.Language.Formula.realize_imp
@[simp]
theorem realize_rel {k : ℕ} {R : L.Relations k} {ts : Fin k → L.Term α} :
(R.formula ts).Realize v ↔ RelMap R fun i => (ts i).realize v :=
BoundedFormula.realize_rel.trans (by simp)
#align first_order.language.formula.realize_rel FirstOrder.Language.Formula.realize_rel
@[simp]
theorem realize_rel₁ {R : L.Relations 1} {t : L.Term _} :
(R.formula₁ t).Realize v ↔ RelMap R ![t.realize v] := by
rw [Relations.formula₁, realize_rel, iff_eq_eq]
refine congr rfl (funext fun _ => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.formula.realize_rel₁ FirstOrder.Language.Formula.realize_rel₁
@[simp]
theorem realize_rel₂ {R : L.Relations 2} {t₁ t₂ : L.Term _} :
(R.formula₂ t₁ t₂).Realize v ↔ RelMap R ![t₁.realize v, t₂.realize v] := by
rw [Relations.formula₂, realize_rel, iff_eq_eq]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.formula.realize_rel₂ FirstOrder.Language.Formula.realize_rel₂
@[simp]
theorem realize_sup : (φ ⊔ ψ).Realize v ↔ φ.Realize v ∨ ψ.Realize v :=
BoundedFormula.realize_sup
#align first_order.language.formula.realize_sup FirstOrder.Language.Formula.realize_sup
@[simp]
theorem realize_iff : (φ.iff ψ).Realize v ↔ (φ.Realize v ↔ ψ.Realize v) :=
BoundedFormula.realize_iff
#align first_order.language.formula.realize_iff FirstOrder.Language.Formula.realize_iff
@[simp]
theorem realize_relabel {φ : L.Formula α} {g : α → β} {v : β → M} :
(φ.relabel g).Realize v ↔ φ.Realize (v ∘ g) := by
rw [Realize, Realize, relabel, BoundedFormula.realize_relabel, iff_eq_eq, Fin.castAdd_zero]
exact congr rfl (funext finZeroElim)
#align first_order.language.formula.realize_relabel FirstOrder.Language.Formula.realize_relabel
theorem realize_relabel_sum_inr (φ : L.Formula (Fin n)) {v : Empty → M} {x : Fin n → M} :
(BoundedFormula.relabel Sum.inr φ).Realize v x ↔ φ.Realize x := by
rw [BoundedFormula.realize_relabel, Formula.Realize, Sum.elim_comp_inr, Fin.castAdd_zero,
cast_refl, Function.comp_id,
Subsingleton.elim (x ∘ (natAdd n : Fin 0 → Fin n)) default]
#align first_order.language.formula.realize_relabel_sum_inr FirstOrder.Language.Formula.realize_relabel_sum_inr
@[simp]
theorem realize_equal {t₁ t₂ : L.Term α} {x : α → M} :
(t₁.equal t₂).Realize x ↔ t₁.realize x = t₂.realize x := by simp [Term.equal, Realize]
#align first_order.language.formula.realize_equal FirstOrder.Language.Formula.realize_equal
@[simp]
theorem realize_graph {f : L.Functions n} {x : Fin n → M} {y : M} :
(Formula.graph f).Realize (Fin.cons y x : _ → M) ↔ funMap f x = y := by
simp only [Formula.graph, Term.realize, realize_equal, Fin.cons_zero, Fin.cons_succ]
rw [eq_comm]
#align first_order.language.formula.realize_graph FirstOrder.Language.Formula.realize_graph
end Formula
@[simp]
theorem LHom.realize_onFormula [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] (ψ : L.Formula α)
{v : α → M} : (φ.onFormula ψ).Realize v ↔ ψ.Realize v :=
φ.realize_onBoundedFormula ψ
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_formula FirstOrder.Language.LHom.realize_onFormula
@[simp]
theorem LHom.setOf_realize_onFormula [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M]
(ψ : L.Formula α) : (setOf (φ.onFormula ψ).Realize : Set (α → M)) = setOf ψ.Realize := by
ext
simp
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.set_of_realize_on_formula FirstOrder.Language.LHom.setOf_realize_onFormula
variable (M)
/-- A sentence can be evaluated as true or false in a structure. -/
nonrec def Sentence.Realize (φ : L.Sentence) : Prop :=
φ.Realize (default : _ → M)
#align first_order.language.sentence.realize FirstOrder.Language.Sentence.Realize
-- input using \|= or \vDash, but not using \models
@[inherit_doc Sentence.Realize]
infixl:51 " ⊨ " => Sentence.Realize
@[simp]
theorem Sentence.realize_not {φ : L.Sentence} : M ⊨ φ.not ↔ ¬M ⊨ φ :=
Iff.rfl
#align first_order.language.sentence.realize_not FirstOrder.Language.Sentence.realize_not
namespace Formula
@[simp]
theorem realize_equivSentence_symm_con [L[[α]].Structure M]
[(L.lhomWithConstants α).IsExpansionOn M] (φ : L[[α]].Sentence) :
((equivSentence.symm φ).Realize fun a => (L.con a : M)) ↔ φ.Realize M := by
simp only [equivSentence, _root_.Equiv.symm_symm, Equiv.coe_trans, Realize,
BoundedFormula.realize_relabelEquiv, Function.comp]
refine _root_.trans ?_ BoundedFormula.realize_constantsVarsEquiv
rw [iff_iff_eq]
congr with (_ | a)
· simp
· cases a
#align first_order.language.formula.realize_equiv_sentence_symm_con FirstOrder.Language.Formula.realize_equivSentence_symm_con
@[simp]
theorem realize_equivSentence [L[[α]].Structure M] [(L.lhomWithConstants α).IsExpansionOn M]
(φ : L.Formula α) : (equivSentence φ).Realize M ↔ φ.Realize fun a => (L.con a : M) := by
rw [← realize_equivSentence_symm_con M (equivSentence φ), _root_.Equiv.symm_apply_apply]
#align first_order.language.formula.realize_equiv_sentence FirstOrder.Language.Formula.realize_equivSentence
theorem realize_equivSentence_symm (φ : L[[α]].Sentence) (v : α → M) :
(equivSentence.symm φ).Realize v ↔
@Sentence.Realize _ M (@Language.withConstantsStructure L M _ α (constantsOn.structure v))
φ :=
letI := constantsOn.structure v
realize_equivSentence_symm_con M φ
#align first_order.language.formula.realize_equiv_sentence_symm FirstOrder.Language.Formula.realize_equivSentence_symm
end Formula
@[simp]
theorem LHom.realize_onSentence [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M]
(ψ : L.Sentence) : M ⊨ φ.onSentence ψ ↔ M ⊨ ψ :=
φ.realize_onFormula ψ
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_sentence FirstOrder.Language.LHom.realize_onSentence
variable (L)
/-- The complete theory of a structure `M` is the set of all sentences `M` satisfies. -/
def completeTheory : L.Theory :=
{ φ | M ⊨ φ }
#align first_order.language.complete_theory FirstOrder.Language.completeTheory
variable (N)
/-- Two structures are elementarily equivalent when they satisfy the same sentences. -/
def ElementarilyEquivalent : Prop :=
L.completeTheory M = L.completeTheory N
#align first_order.language.elementarily_equivalent FirstOrder.Language.ElementarilyEquivalent
@[inherit_doc FirstOrder.Language.ElementarilyEquivalent]
scoped[FirstOrder]
notation:25 A " ≅[" L "] " B:50 => FirstOrder.Language.ElementarilyEquivalent L A B
variable {L} {M} {N}
@[simp]
theorem mem_completeTheory {φ : Sentence L} : φ ∈ L.completeTheory M ↔ M ⊨ φ :=
Iff.rfl
#align first_order.language.mem_complete_theory FirstOrder.Language.mem_completeTheory
theorem elementarilyEquivalent_iff : M ≅[L] N ↔ ∀ φ : L.Sentence, M ⊨ φ ↔ N ⊨ φ := by
simp only [ElementarilyEquivalent, Set.ext_iff, completeTheory, Set.mem_setOf_eq]
#align first_order.language.elementarily_equivalent_iff FirstOrder.Language.elementarilyEquivalent_iff
variable (M)
/-- A model of a theory is a structure in which every sentence is realized as true. -/
class Theory.Model (T : L.Theory) : Prop where
realize_of_mem : ∀ φ ∈ T, M ⊨ φ
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model FirstOrder.Language.Theory.Model
-- input using \|= or \vDash, but not using \models
@[inherit_doc Theory.Model]
infixl:51 " ⊨ " => Theory.Model
variable {M} (T : L.Theory)
@[simp default-10]
theorem Theory.model_iff : M ⊨ T ↔ ∀ φ ∈ T, M ⊨ φ :=
⟨fun h => h.realize_of_mem, fun h => ⟨h⟩⟩
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model_iff FirstOrder.Language.Theory.model_iff
theorem Theory.realize_sentence_of_mem [M ⊨ T] {φ : L.Sentence} (h : φ ∈ T) : M ⊨ φ :=
Theory.Model.realize_of_mem φ h
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.realize_sentence_of_mem FirstOrder.Language.Theory.realize_sentence_of_mem
@[simp]
| Mathlib/ModelTheory/Semantics.lean | 822 | 823 | theorem LHom.onTheory_model [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] (T : L.Theory) :
M ⊨ φ.onTheory T ↔ M ⊨ T := by | simp [Theory.model_iff, LHom.onTheory]
|
/-
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
| Mathlib/Topology/UniformSpace/Basic.lean | 1,309 | 1,312 | 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
|
/-
Copyright (c) 2021 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Thomas Murrills
-/
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.Tactic.NormNum.Basic
/-!
## `norm_num` plugin for `^`.
-/
set_option autoImplicit true
namespace Mathlib
open Lean hiding Rat mkRat
open Meta
namespace Meta.NormNum
open Qq
theorem natPow_zero : Nat.pow a (nat_lit 0) = nat_lit 1 := rfl
theorem natPow_one : Nat.pow a (nat_lit 1) = a := Nat.pow_one _
theorem zero_natPow : Nat.pow (nat_lit 0) (Nat.succ b) = nat_lit 0 := rfl
theorem one_natPow : Nat.pow (nat_lit 1) b = nat_lit 1 := Nat.one_pow _
/-- This is an opaque wrapper around `Nat.pow` to prevent lean from unfolding the definition of
`Nat.pow` on numerals. The arbitrary precondition `p` is actually a formula of the form
`Nat.pow a' b' = c'` but we usually don't care to unfold this proposition so we just carry a
reference to it. -/
structure IsNatPowT (p : Prop) (a b c : Nat) : Prop where
/-- Unfolds the assertion. -/
run' : p → Nat.pow a b = c
theorem IsNatPowT.run
(p : IsNatPowT (Nat.pow a (nat_lit 1) = a) a b c) : Nat.pow a b = c := p.run' (Nat.pow_one _)
/-- This is the key to making the proof proceed as a balanced tree of applications instead of
a linear sequence. It is just modus ponens after unwrapping the definitions. -/
theorem IsNatPowT.trans (h1 : IsNatPowT p a b c) (h2 : IsNatPowT (Nat.pow a b = c) a b' c') :
IsNatPowT p a b' c' := ⟨h2.run' ∘ h1.run'⟩
theorem IsNatPowT.bit0 : IsNatPowT (Nat.pow a b = c) a (nat_lit 2 * b) (Nat.mul c c) :=
⟨fun h1 => by simp [two_mul, pow_add, ← h1]⟩
theorem IsNatPowT.bit1 :
IsNatPowT (Nat.pow a b = c) a (nat_lit 2 * b + nat_lit 1) (Nat.mul c (Nat.mul c a)) :=
⟨fun h1 => by simp [two_mul, pow_add, mul_assoc, ← h1]⟩
/--
Proves `Nat.pow a b = c` where `a` and `b` are raw nat literals. This could be done by just
`rfl` but the kernel does not have a special case implementation for `Nat.pow` so this would
proceed by unary recursion on `b`, which is too slow and also leads to deep recursion.
We instead do the proof by binary recursion, but this can still lead to deep recursion,
so we use an additional trick to do binary subdivision on `log2 b`. As a result this produces
a proof of depth `log (log b)` which will essentially never overflow before the numbers involved
themselves exceed memory limits.
-/
partial def evalNatPow (a b : Q(ℕ)) : (c : Q(ℕ)) × Q(Nat.pow $a $b = $c) :=
if b.natLit! = 0 then
haveI : $b =Q 0 := ⟨⟩
⟨q(nat_lit 1), q(natPow_zero)⟩
else if a.natLit! = 0 then
haveI : $a =Q 0 := ⟨⟩
have b' : Q(ℕ) := mkRawNatLit (b.natLit! - 1)
haveI : $b =Q Nat.succ $b' := ⟨⟩
⟨q(nat_lit 0), q(zero_natPow)⟩
else if a.natLit! = 1 then
haveI : $a =Q 1 := ⟨⟩
⟨q(nat_lit 1), q(one_natPow)⟩
else if b.natLit! = 1 then
haveI : $b =Q 1 := ⟨⟩
⟨a, q(natPow_one)⟩
else
let ⟨c, p⟩ := go b.natLit!.log2 a (mkRawNatLit 1) a b _ .rfl
⟨c, q(($p).run)⟩
where
/-- Invariants: `a ^ b₀ = c₀`, `depth > 0`, `b >>> depth = b₀`, `p := Nat.pow $a $b₀ = $c₀` -/
go (depth : Nat) (a b₀ c₀ b : Q(ℕ)) (p : Q(Prop)) (hp : $p =Q (Nat.pow $a $b₀ = $c₀)) :
(c : Q(ℕ)) × Q(IsNatPowT $p $a $b $c) :=
let b' := b.natLit!
if depth ≤ 1 then
let a' := a.natLit!
let c₀' := c₀.natLit!
if b' &&& 1 == 0 then
have c : Q(ℕ) := mkRawNatLit (c₀' * c₀')
haveI : $c =Q Nat.mul $c₀ $c₀ := ⟨⟩
haveI : $b =Q 2 * $b₀ := ⟨⟩
⟨c, q(IsNatPowT.bit0)⟩
else
have c : Q(ℕ) := mkRawNatLit (c₀' * (c₀' * a'))
haveI : $c =Q Nat.mul $c₀ (Nat.mul $c₀ $a) := ⟨⟩
haveI : $b =Q 2 * $b₀ + 1 := ⟨⟩
⟨c, q(IsNatPowT.bit1)⟩
else
let d := depth >>> 1
have hi : Q(ℕ) := mkRawNatLit (b' >>> d)
let ⟨c1, p1⟩ := go (depth - d) a b₀ c₀ hi p (by exact hp)
let ⟨c2, p2⟩ := go d a hi c1 b q(Nat.pow $a $hi = $c1) ⟨⟩
⟨c2, q(($p1).trans $p2)⟩
theorem intPow_ofNat (h1 : Nat.pow a b = c) :
Int.pow (Int.ofNat a) b = Int.ofNat c := by simp [← h1]
theorem intPow_negOfNat_bit0 (h1 : Nat.pow a b' = c')
(hb : nat_lit 2 * b' = b) (hc : c' * c' = c) :
Int.pow (Int.negOfNat a) b = Int.ofNat c := by
rw [← hb, Int.negOfNat_eq, Int.pow_eq, pow_mul, neg_pow_two, ← pow_mul, two_mul, pow_add, ← hc,
← h1]
simp
theorem intPow_negOfNat_bit1 (h1 : Nat.pow a b' = c')
(hb : nat_lit 2 * b' + nat_lit 1 = b) (hc : c' * (c' * a) = c) :
Int.pow (Int.negOfNat a) b = Int.negOfNat c := by
rw [← hb, Int.negOfNat_eq, Int.negOfNat_eq, Int.pow_eq, pow_succ, pow_mul, neg_pow_two, ← pow_mul,
two_mul, pow_add, ← hc, ← h1]
simp [mul_assoc, mul_comm, mul_left_comm]
/-- Evaluates `Int.pow a b = c` where `a` and `b` are raw integer literals. -/
partial def evalIntPow (za : ℤ) (a : Q(ℤ)) (b : Q(ℕ)) : ℤ × (c : Q(ℤ)) × Q(Int.pow $a $b = $c) :=
have a' : Q(ℕ) := a.appArg!
if 0 ≤ za then
haveI : $a =Q .ofNat $a' := ⟨⟩
let ⟨c, p⟩ := evalNatPow a' b
⟨c.natLit!, q(.ofNat $c), q(intPow_ofNat $p)⟩
else
haveI : $a =Q .negOfNat $a' := ⟨⟩
let b' := b.natLit!
have b₀ : Q(ℕ) := mkRawNatLit (b' >>> 1)
let ⟨c₀, p⟩ := evalNatPow a' b₀
let c' := c₀.natLit!
if b' &&& 1 == 0 then
have c : Q(ℕ) := mkRawNatLit (c' * c')
have pc : Q($c₀ * $c₀ = $c) := (q(Eq.refl $c) : Expr)
have pb : Q(2 * $b₀ = $b) := (q(Eq.refl $b) : Expr)
⟨c.natLit!, q(.ofNat $c), q(intPow_negOfNat_bit0 $p $pb $pc)⟩
else
have c : Q(ℕ) := mkRawNatLit (c' * (c' * a'.natLit!))
have pc : Q($c₀ * ($c₀ * $a') = $c) := (q(Eq.refl $c) : Expr)
have pb : Q(2 * $b₀ + 1 = $b) := (q(Eq.refl $b) : Expr)
⟨-c.natLit!, q(.negOfNat $c), q(intPow_negOfNat_bit1 $p $pb $pc)⟩
-- see note [norm_num lemma function equality]
theorem isNat_pow {α} [Semiring α] : ∀ {f : α → ℕ → α} {a : α} {b a' b' c : ℕ},
f = HPow.hPow → IsNat a a' → IsNat b b' → Nat.pow a' b' = c → IsNat (f a b) c
| _, _, _, _, _, _, rfl, ⟨rfl⟩, ⟨rfl⟩, rfl => ⟨by simp⟩
-- see note [norm_num lemma function equality]
theorem isInt_pow {α} [Ring α] : ∀ {f : α → ℕ → α} {a : α} {b : ℕ} {a' : ℤ} {b' : ℕ} {c : ℤ},
f = HPow.hPow → IsInt a a' → IsNat b b' → Int.pow a' b' = c → IsInt (f a b) c
| _, _, _, _, _, _, rfl, ⟨rfl⟩, ⟨rfl⟩, rfl => ⟨by simp⟩
-- see note [norm_num lemma function equality]
theorem isRat_pow {α} [Ring α] {f : α → ℕ → α} {a : α} {an cn : ℤ} {ad b b' cd : ℕ} :
f = HPow.hPow → IsRat a an ad → IsNat b b' →
Int.pow an b' = cn → Nat.pow ad b' = cd →
IsRat (f a b) cn cd := by
rintro rfl ⟨_, rfl⟩ ⟨rfl⟩ (rfl : an ^ b = _) (rfl : ad ^ b = _)
have := invertiblePow (ad:α) b
rw [← Nat.cast_pow] at this
use this; simp [invOf_pow, Commute.mul_pow]
/-- The `norm_num` extension which identifies expressions of the form `a ^ b`,
such that `norm_num` successfully recognises both `a` and `b`, with `b : ℕ`. -/
@[norm_num (_ : α) ^ (_ : ℕ)]
def evalPow : NormNumExt where eval {u α} e := do
let .app (.app (f : Q($α → ℕ → $α)) (a : Q($α))) (b : Q(ℕ)) ← whnfR e | failure
let ⟨nb, pb⟩ ← deriveNat b q(instAddMonoidWithOneNat)
let sα ← inferSemiring α
let ra ← derive a
guard <|← withDefault <| withNewMCtxDepth <| isDefEq f q(HPow.hPow (α := $α))
haveI' : $e =Q $a ^ $b := ⟨⟩
haveI' : $f =Q HPow.hPow := ⟨⟩
let rec
/-- Main part of `evalPow`. -/
core : Option (Result e) := do
match ra with
| .isBool .. => failure
| .isNat sα na pa =>
assumeInstancesCommute
have ⟨c, r⟩ := evalNatPow na nb
return .isNat sα c q(isNat_pow (f := $f) (.refl $f) $pa $pb $r)
| .isNegNat rα .. =>
assumeInstancesCommute
let ⟨za, na, pa⟩ ← ra.toInt rα
have ⟨zc, c, r⟩ := evalIntPow za na nb
return .isInt rα c zc q(isInt_pow (f := $f) (.refl $f) $pa $pb $r)
| .isRat dα qa na da pa =>
assumeInstancesCommute
have ⟨zc, nc, r1⟩ := evalIntPow qa.num na nb
have ⟨dc, r2⟩ := evalNatPow da nb
let qc := mkRat zc dc.natLit!
return .isRat' dα qc nc dc q(isRat_pow (f := $f) (.refl $f) $pa $pb $r1 $r2)
core
theorem isNat_zpow_pos {α : Type*} [DivisionSemiring α] {a : α} {b : ℤ} {nb ne : ℕ}
(pb : IsNat b nb) (pe' : IsNat (a ^ nb) ne) :
IsNat (a ^ b) ne := by
rwa [pb.out, zpow_natCast]
theorem isNat_zpow_neg {α : Type*} [DivisionSemiring α] {a : α} {b : ℤ} {nb ne : ℕ}
(pb : IsInt b (Int.negOfNat nb)) (pe' : IsNat (a ^ nb)⁻¹ ne) :
IsNat (a ^ b) ne := by
rwa [pb.out, Int.cast_negOfNat, zpow_neg, zpow_natCast]
theorem isInt_zpow_pos {α : Type*} [DivisionRing α] {a : α} {b : ℤ} {nb ne : ℕ}
(pb : IsNat b nb) (pe' : IsInt (a ^ nb) (Int.negOfNat ne)) :
IsInt (a ^ b) (Int.negOfNat ne) := by
rwa [pb.out, zpow_natCast]
theorem isInt_zpow_neg {α : Type*} [DivisionRing α] {a : α} {b : ℤ} {nb ne : ℕ}
(pb : IsInt b (Int.negOfNat nb)) (pe' : IsInt (a ^ nb)⁻¹ (Int.negOfNat ne)) :
IsInt (a ^ b) (Int.negOfNat ne) := by
rwa [pb.out, Int.cast_negOfNat, zpow_neg, zpow_natCast]
theorem isRat_zpow_pos {α : Type*} [DivisionRing α] {a : α} {b : ℤ} {nb : ℕ}
{num : ℤ} {den : ℕ}
(pb : IsNat b nb) (pe' : IsRat (a^nb) num den) :
IsRat (a^b) num den := by
rwa [pb.out, zpow_natCast]
| Mathlib/Tactic/NormNum/Pow.lean | 222 | 226 | theorem isRat_zpow_neg {α : Type*} [DivisionRing α] {a : α} {b : ℤ} {nb : ℕ}
{num : ℤ} {den : ℕ}
(pb : IsInt b (Int.negOfNat nb)) (pe' : IsRat ((a^nb)⁻¹) num den) :
IsRat (a^b) num den := by |
rwa [pb.out, Int.cast_negOfNat, zpow_neg, zpow_natCast]
|
/-
Copyright (c) 2020 Kevin Kappelmann. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Kappelmann
-/
import Mathlib.Algebra.ContinuedFractions.Computation.Basic
import Mathlib.Algebra.ContinuedFractions.Translations
#align_import algebra.continued_fractions.computation.translations from "leanprover-community/mathlib"@"a7e36e48519ab281320c4d192da6a7b348ce40ad"
/-!
# Basic Translation Lemmas Between Structures Defined for Computing Continued Fractions
## Summary
This is a collection of simple lemmas between the different structures used for the computation
of continued fractions defined in `Algebra.ContinuedFractions.Computation.Basic`. The file consists
of three sections:
1. Recurrences and inversion lemmas for `IntFractPair.stream`: these lemmas give us inversion
rules and recurrences for the computation of the stream of integer and fractional parts of
a value.
2. Translation lemmas for the head term: these lemmas show us that the head term of the computed
continued fraction of a value `v` is `⌊v⌋` and how this head term is moved along the structures
used in the computation process.
3. Translation lemmas for the sequence: these lemmas show how the sequences of the involved
structures (`IntFractPair.stream`, `IntFractPair.seq1`, and
`GeneralizedContinuedFraction.of`) are connected, i.e. how the values are moved along the
structures and the termination of one sequence implies the termination of another sequence.
## Main Theorems
- `succ_nth_stream_eq_some_iff` gives as a recurrence to compute the `n + 1`th value of the sequence
of integer and fractional parts of a value in case of non-termination.
- `succ_nth_stream_eq_none_iff` gives as a recurrence to compute the `n + 1`th value of the sequence
of integer and fractional parts of a value in case of termination.
- `get?_of_eq_some_of_succ_get?_intFractPair_stream` and
`get?_of_eq_some_of_get?_intFractPair_stream_fr_ne_zero` show how the entries of the sequence
of the computed continued fraction can be obtained from the stream of integer and fractional
parts.
-/
namespace GeneralizedContinuedFraction
open GeneralizedContinuedFraction (of)
-- Fix a discrete linear ordered floor field and a value `v`.
variable {K : Type*} [LinearOrderedField K] [FloorRing K] {v : K}
namespace IntFractPair
/-!
### Recurrences and Inversion Lemmas for `IntFractPair.stream`
Here we state some lemmas that give us inversion rules and recurrences for the computation of the
stream of integer and fractional parts of a value.
-/
theorem stream_zero (v : K) : IntFractPair.stream v 0 = some (IntFractPair.of v) :=
rfl
#align generalized_continued_fraction.int_fract_pair.stream_zero GeneralizedContinuedFraction.IntFractPair.stream_zero
variable {n : ℕ}
theorem stream_eq_none_of_fr_eq_zero {ifp_n : IntFractPair K}
(stream_nth_eq : IntFractPair.stream v n = some ifp_n) (nth_fr_eq_zero : ifp_n.fr = 0) :
IntFractPair.stream v (n + 1) = none := by
cases' ifp_n with _ fr
change fr = 0 at nth_fr_eq_zero
simp [IntFractPair.stream, stream_nth_eq, nth_fr_eq_zero]
#align generalized_continued_fraction.int_fract_pair.stream_eq_none_of_fr_eq_zero GeneralizedContinuedFraction.IntFractPair.stream_eq_none_of_fr_eq_zero
/-- Gives a recurrence to compute the `n + 1`th value of the sequence of integer and fractional
parts of a value in case of termination.
-/
theorem succ_nth_stream_eq_none_iff :
IntFractPair.stream v (n + 1) = none ↔
IntFractPair.stream v n = none ∨ ∃ ifp, IntFractPair.stream v n = some ifp ∧ ifp.fr = 0 := by
rw [IntFractPair.stream]
cases IntFractPair.stream v n <;> simp [imp_false]
#align generalized_continued_fraction.int_fract_pair.succ_nth_stream_eq_none_iff GeneralizedContinuedFraction.IntFractPair.succ_nth_stream_eq_none_iff
/-- Gives a recurrence to compute the `n + 1`th value of the sequence of integer and fractional
parts of a value in case of non-termination.
-/
theorem succ_nth_stream_eq_some_iff {ifp_succ_n : IntFractPair K} :
IntFractPair.stream v (n + 1) = some ifp_succ_n ↔
∃ ifp_n : IntFractPair K,
IntFractPair.stream v n = some ifp_n ∧
ifp_n.fr ≠ 0 ∧ IntFractPair.of ifp_n.fr⁻¹ = ifp_succ_n := by
simp [IntFractPair.stream, ite_eq_iff, Option.bind_eq_some]
#align generalized_continued_fraction.int_fract_pair.succ_nth_stream_eq_some_iff GeneralizedContinuedFraction.IntFractPair.succ_nth_stream_eq_some_iff
/-- An easier to use version of one direction of
`GeneralizedContinuedFraction.IntFractPair.succ_nth_stream_eq_some_iff`.
-/
theorem stream_succ_of_some {p : IntFractPair K} (h : IntFractPair.stream v n = some p)
(h' : p.fr ≠ 0) : IntFractPair.stream v (n + 1) = some (IntFractPair.of p.fr⁻¹) :=
succ_nth_stream_eq_some_iff.mpr ⟨p, h, h', rfl⟩
#align generalized_continued_fraction.int_fract_pair.stream_succ_of_some GeneralizedContinuedFraction.IntFractPair.stream_succ_of_some
/-- The stream of `IntFractPair`s of an integer stops after the first term.
-/
theorem stream_succ_of_int (a : ℤ) (n : ℕ) : IntFractPair.stream (a : K) (n + 1) = none := by
induction' n with n ih
· refine IntFractPair.stream_eq_none_of_fr_eq_zero (IntFractPair.stream_zero (a : K)) ?_
simp only [IntFractPair.of, Int.fract_intCast]
· exact IntFractPair.succ_nth_stream_eq_none_iff.mpr (Or.inl ih)
#align generalized_continued_fraction.int_fract_pair.stream_succ_of_int GeneralizedContinuedFraction.IntFractPair.stream_succ_of_int
theorem exists_succ_nth_stream_of_fr_zero {ifp_succ_n : IntFractPair K}
(stream_succ_nth_eq : IntFractPair.stream v (n + 1) = some ifp_succ_n)
(succ_nth_fr_eq_zero : ifp_succ_n.fr = 0) :
∃ ifp_n : IntFractPair K, IntFractPair.stream v n = some ifp_n ∧ ifp_n.fr⁻¹ = ⌊ifp_n.fr⁻¹⌋ := by
-- get the witness from `succ_nth_stream_eq_some_iff` and prove that it has the additional
-- properties
rcases succ_nth_stream_eq_some_iff.mp stream_succ_nth_eq with
⟨ifp_n, seq_nth_eq, _, rfl⟩
refine ⟨ifp_n, seq_nth_eq, ?_⟩
simpa only [IntFractPair.of, Int.fract, sub_eq_zero] using succ_nth_fr_eq_zero
#align generalized_continued_fraction.int_fract_pair.exists_succ_nth_stream_of_fr_zero GeneralizedContinuedFraction.IntFractPair.exists_succ_nth_stream_of_fr_zero
/-- A recurrence relation that expresses the `(n+1)`th term of the stream of `IntFractPair`s
of `v` for non-integer `v` in terms of the `n`th term of the stream associated to
the inverse of the fractional part of `v`.
-/
theorem stream_succ (h : Int.fract v ≠ 0) (n : ℕ) :
IntFractPair.stream v (n + 1) = IntFractPair.stream (Int.fract v)⁻¹ n := by
induction' n with n ih
· have H : (IntFractPair.of v).fr = Int.fract v := rfl
rw [stream_zero, stream_succ_of_some (stream_zero v) (ne_of_eq_of_ne H h), H]
· rcases eq_or_ne (IntFractPair.stream (Int.fract v)⁻¹ n) none with hnone | hsome
· rw [hnone] at ih
rw [succ_nth_stream_eq_none_iff.mpr (Or.inl hnone),
succ_nth_stream_eq_none_iff.mpr (Or.inl ih)]
· obtain ⟨p, hp⟩ := Option.ne_none_iff_exists'.mp hsome
rw [hp] at ih
rcases eq_or_ne p.fr 0 with hz | hnz
· rw [stream_eq_none_of_fr_eq_zero hp hz, stream_eq_none_of_fr_eq_zero ih hz]
· rw [stream_succ_of_some hp hnz, stream_succ_of_some ih hnz]
#align generalized_continued_fraction.int_fract_pair.stream_succ GeneralizedContinuedFraction.IntFractPair.stream_succ
end IntFractPair
section Head
/-!
### Translation of the Head Term
Here we state some lemmas that show us that the head term of the computed continued fraction of a
value `v` is `⌊v⌋` and how this head term is moved along the structures used in the computation
process.
-/
/-- The head term of the sequence with head of `v` is just the integer part of `v`. -/
@[simp]
theorem IntFractPair.seq1_fst_eq_of : (IntFractPair.seq1 v).fst = IntFractPair.of v :=
rfl
#align generalized_continued_fraction.int_fract_pair.seq1_fst_eq_of GeneralizedContinuedFraction.IntFractPair.seq1_fst_eq_of
theorem of_h_eq_intFractPair_seq1_fst_b : (of v).h = (IntFractPair.seq1 v).fst.b := by
cases aux_seq_eq : IntFractPair.seq1 v
simp [of, aux_seq_eq]
#align generalized_continued_fraction.of_h_eq_int_fract_pair_seq1_fst_b GeneralizedContinuedFraction.of_h_eq_intFractPair_seq1_fst_b
/-- The head term of the gcf of `v` is `⌊v⌋`. -/
@[simp]
theorem of_h_eq_floor : (of v).h = ⌊v⌋ := by
simp [of_h_eq_intFractPair_seq1_fst_b, IntFractPair.of]
#align generalized_continued_fraction.of_h_eq_floor GeneralizedContinuedFraction.of_h_eq_floor
end Head
section sequence
/-!
### Translation of the Sequences
Here we state some lemmas that show how the sequences of the involved structures
(`IntFractPair.stream`, `IntFractPair.seq1`, and `GeneralizedContinuedFraction.of`) are
connected, i.e. how the values are moved along the structures and how the termination of one
sequence implies the termination of another sequence.
-/
variable {n : ℕ}
theorem IntFractPair.get?_seq1_eq_succ_get?_stream :
(IntFractPair.seq1 v).snd.get? n = (IntFractPair.stream v) (n + 1) :=
rfl
#align generalized_continued_fraction.int_fract_pair.nth_seq1_eq_succ_nth_stream GeneralizedContinuedFraction.IntFractPair.get?_seq1_eq_succ_get?_stream
section Termination
/-!
#### Translation of the Termination of the Sequences
Let's first show how the termination of one sequence implies the termination of another sequence.
-/
theorem of_terminatedAt_iff_intFractPair_seq1_terminatedAt :
(of v).TerminatedAt n ↔ (IntFractPair.seq1 v).snd.TerminatedAt n :=
Option.map_eq_none
#align generalized_continued_fraction.of_terminated_at_iff_int_fract_pair_seq1_terminated_at GeneralizedContinuedFraction.of_terminatedAt_iff_intFractPair_seq1_terminatedAt
theorem of_terminatedAt_n_iff_succ_nth_intFractPair_stream_eq_none :
(of v).TerminatedAt n ↔ IntFractPair.stream v (n + 1) = none := by
rw [of_terminatedAt_iff_intFractPair_seq1_terminatedAt, Stream'.Seq.TerminatedAt,
IntFractPair.get?_seq1_eq_succ_get?_stream]
#align generalized_continued_fraction.of_terminated_at_n_iff_succ_nth_int_fract_pair_stream_eq_none GeneralizedContinuedFraction.of_terminatedAt_n_iff_succ_nth_intFractPair_stream_eq_none
end Termination
section Values
/-!
#### Translation of the Values of the Sequence
Now let's show how the values of the sequences correspond to one another.
-/
theorem IntFractPair.exists_succ_get?_stream_of_gcf_of_get?_eq_some {gp_n : Pair K}
(s_nth_eq : (of v).s.get? n = some gp_n) :
∃ ifp : IntFractPair K, IntFractPair.stream v (n + 1) = some ifp ∧ (ifp.b : K) = gp_n.b := by
obtain ⟨ifp, stream_succ_nth_eq, gp_n_eq⟩ :
∃ ifp, IntFractPair.stream v (n + 1) = some ifp ∧ Pair.mk 1 (ifp.b : K) = gp_n := by
unfold of IntFractPair.seq1 at s_nth_eq
simpa [Stream'.Seq.get?_tail, Stream'.Seq.map_get?] using s_nth_eq
cases gp_n_eq
simp_all only [Option.some.injEq, exists_eq_left']
#align generalized_continued_fraction.int_fract_pair.exists_succ_nth_stream_of_gcf_of_nth_eq_some GeneralizedContinuedFraction.IntFractPair.exists_succ_get?_stream_of_gcf_of_get?_eq_some
/-- Shows how the entries of the sequence of the computed continued fraction can be obtained by the
integer parts of the stream of integer and fractional parts.
-/
theorem get?_of_eq_some_of_succ_get?_intFractPair_stream {ifp_succ_n : IntFractPair K}
(stream_succ_nth_eq : IntFractPair.stream v (n + 1) = some ifp_succ_n) :
(of v).s.get? n = some ⟨1, ifp_succ_n.b⟩ := by
unfold of IntFractPair.seq1
simp [Stream'.Seq.map_tail, Stream'.Seq.get?_tail, Stream'.Seq.map_get?, stream_succ_nth_eq]
#align generalized_continued_fraction.nth_of_eq_some_of_succ_nth_int_fract_pair_stream GeneralizedContinuedFraction.get?_of_eq_some_of_succ_get?_intFractPair_stream
/-- Shows how the entries of the sequence of the computed continued fraction can be obtained by the
fractional parts of the stream of integer and fractional parts.
-/
theorem get?_of_eq_some_of_get?_intFractPair_stream_fr_ne_zero {ifp_n : IntFractPair K}
(stream_nth_eq : IntFractPair.stream v n = some ifp_n) (nth_fr_ne_zero : ifp_n.fr ≠ 0) :
(of v).s.get? n = some ⟨1, (IntFractPair.of ifp_n.fr⁻¹).b⟩ :=
have : IntFractPair.stream v (n + 1) = some (IntFractPair.of ifp_n.fr⁻¹) := by
cases ifp_n
simp only [IntFractPair.stream, Nat.add_eq, add_zero, stream_nth_eq, Option.some_bind,
ite_eq_right_iff]
intro; contradiction
get?_of_eq_some_of_succ_get?_intFractPair_stream this
#align generalized_continued_fraction.nth_of_eq_some_of_nth_int_fract_pair_stream_fr_ne_zero GeneralizedContinuedFraction.get?_of_eq_some_of_get?_intFractPair_stream_fr_ne_zero
open Int IntFractPair
theorem of_s_head_aux (v : K) : (of v).s.get? 0 = (IntFractPair.stream v 1).bind (some ∘ fun p =>
{ a := 1
b := p.b }) := by
rw [of, IntFractPair.seq1]
simp only [of, Stream'.Seq.map_tail, Stream'.Seq.map, Stream'.Seq.tail, Stream'.Seq.head,
Stream'.Seq.get?, Stream'.map]
rw [← Stream'.get_succ, Stream'.get, Option.map]
split <;> simp_all only [Option.some_bind, Option.none_bind, Function.comp_apply]
#align generalized_continued_fraction.of_s_head_aux GeneralizedContinuedFraction.of_s_head_aux
/-- This gives the first pair of coefficients of the continued fraction of a non-integer `v`.
-/
theorem of_s_head (h : fract v ≠ 0) : (of v).s.head = some ⟨1, ⌊(fract v)⁻¹⌋⟩ := by
change (of v).s.get? 0 = _
rw [of_s_head_aux, stream_succ_of_some (stream_zero v) h, Option.bind]
rfl
#align generalized_continued_fraction.of_s_head GeneralizedContinuedFraction.of_s_head
variable (K)
/-- If `a` is an integer, then the coefficient sequence of its continued fraction is empty.
-/
theorem of_s_of_int (a : ℤ) : (of (a : K)).s = Stream'.Seq.nil :=
haveI h : ∀ n, (of (a : K)).s.get? n = none := by
intro n
induction' n with n ih
· rw [of_s_head_aux, stream_succ_of_int, Option.bind]
· exact (of (a : K)).s.prop ih
Stream'.Seq.ext fun n => (h n).trans (Stream'.Seq.get?_nil n).symm
#align generalized_continued_fraction.of_s_of_int GeneralizedContinuedFraction.of_s_of_int
variable {K} (v)
/-- Recurrence for the `GeneralizedContinuedFraction.of` an element `v` of `K` in terms of
that of the inverse of the fractional part of `v`.
-/
theorem of_s_succ (n : ℕ) : (of v).s.get? (n + 1) = (of (fract v)⁻¹).s.get? n := by
rcases eq_or_ne (fract v) 0 with h | h
· obtain ⟨a, rfl⟩ : ∃ a : ℤ, v = a := ⟨⌊v⌋, eq_of_sub_eq_zero h⟩
rw [fract_intCast, inv_zero, of_s_of_int, ← cast_zero, of_s_of_int,
Stream'.Seq.get?_nil, Stream'.Seq.get?_nil]
rcases eq_or_ne ((of (fract v)⁻¹).s.get? n) none with h₁ | h₁
· rwa [h₁, ← terminatedAt_iff_s_none,
of_terminatedAt_n_iff_succ_nth_intFractPair_stream_eq_none, stream_succ h, ←
of_terminatedAt_n_iff_succ_nth_intFractPair_stream_eq_none, terminatedAt_iff_s_none]
· obtain ⟨p, hp⟩ := Option.ne_none_iff_exists'.mp h₁
obtain ⟨p', hp'₁, _⟩ := exists_succ_get?_stream_of_gcf_of_get?_eq_some hp
have Hp := get?_of_eq_some_of_succ_get?_intFractPair_stream hp'₁
rw [← stream_succ h] at hp'₁
rw [Hp, get?_of_eq_some_of_succ_get?_intFractPair_stream hp'₁]
#align generalized_continued_fraction.of_s_succ GeneralizedContinuedFraction.of_s_succ
/-- This expresses the tail of the coefficient sequence of the `GeneralizedContinuedFraction.of`
an element `v` of `K` as the coefficient sequence of that of the inverse of the
fractional part of `v`.
-/
theorem of_s_tail : (of v).s.tail = (of (fract v)⁻¹).s :=
Stream'.Seq.ext fun n => Stream'.Seq.get?_tail (of v).s n ▸ of_s_succ v n
#align generalized_continued_fraction.of_s_tail GeneralizedContinuedFraction.of_s_tail
variable (K) (n)
/-- If `a` is an integer, then the `convergents'` of its continued fraction expansion
are all equal to `a`.
-/
theorem convergents'_of_int (a : ℤ) : (of (a : K)).convergents' n = a := by
induction' n with n
· simp only [zeroth_convergent'_eq_h, of_h_eq_floor, floor_intCast, Nat.zero_eq]
· rw [convergents', of_h_eq_floor, floor_intCast, add_right_eq_self]
exact convergents'Aux_succ_none ((of_s_of_int K a).symm ▸ Stream'.Seq.get?_nil 0) _
#align generalized_continued_fraction.convergents'_of_int GeneralizedContinuedFraction.convergents'_of_int
variable {K}
/-- The recurrence relation for the `convergents'` of the continued fraction expansion
of an element `v` of `K` in terms of the convergents of the inverse of its fractional part.
-/
| Mathlib/Algebra/ContinuedFractions/Computation/Translations.lean | 340 | 347 | theorem convergents'_succ :
(of v).convergents' (n + 1) = ⌊v⌋ + 1 / (of (fract v)⁻¹).convergents' n := by |
rcases eq_or_ne (fract v) 0 with h | h
· obtain ⟨a, rfl⟩ : ∃ a : ℤ, v = a := ⟨⌊v⌋, eq_of_sub_eq_zero h⟩
rw [convergents'_of_int, fract_intCast, inv_zero, ← cast_zero, convergents'_of_int, cast_zero,
div_zero, add_zero, floor_intCast]
· rw [convergents', of_h_eq_floor, add_right_inj, convergents'Aux_succ_some (of_s_head h)]
exact congr_arg (1 / ·) (by rw [convergents', of_h_eq_floor, add_right_inj, of_s_tail])
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Johannes Hölzl, Mario Carneiro, Patrick Massot
-/
import Mathlib.Data.Prod.PProd
import Mathlib.Data.Set.Countable
import Mathlib.Order.Filter.Prod
import Mathlib.Order.Filter.Ker
#align_import order.filter.bases from "leanprover-community/mathlib"@"996b0ff959da753a555053a480f36e5f264d4207"
/-!
# Filter bases
A filter basis `B : FilterBasis α` on a type `α` is a nonempty collection of sets of `α`
such that the intersection of two elements of this collection contains some element of
the collection. Compared to filters, filter bases do not require that any set containing
an element of `B` belongs to `B`.
A filter basis `B` can be used to construct `B.filter : Filter α` such that a set belongs
to `B.filter` if and only if it contains an element of `B`.
Given an indexing type `ι`, a predicate `p : ι → Prop`, and a map `s : ι → Set α`,
the proposition `h : Filter.IsBasis p s` makes sure the range of `s` bounded by `p`
(ie. `s '' setOf p`) defines a filter basis `h.filterBasis`.
If one already has a filter `l` on `α`, `Filter.HasBasis l p s` (where `p : ι → Prop`
and `s : ι → Set α` as above) means that a set belongs to `l` if and
only if it contains some `s i` with `p i`. It implies `h : Filter.IsBasis p s`, and
`l = h.filterBasis.filter`. The point of this definition is that checking statements
involving elements of `l` often reduces to checking them on the basis elements.
We define a function `HasBasis.index (h : Filter.HasBasis l p s) (t) (ht : t ∈ l)` that returns
some index `i` such that `p i` and `s i ⊆ t`. This function can be useful to avoid manual
destruction of `h.mem_iff.mpr ht` using `cases` or `let`.
This file also introduces more restricted classes of bases, involving monotonicity or
countability. In particular, for `l : Filter α`, `l.IsCountablyGenerated` means
there is a countable set of sets which generates `s`. This is reformulated in term of bases,
and consequences are derived.
## Main statements
* `Filter.HasBasis.mem_iff`, `HasBasis.mem_of_superset`, `HasBasis.mem_of_mem` : restate `t ∈ f` in
terms of a basis;
* `Filter.basis_sets` : all sets of a filter form a basis;
* `Filter.HasBasis.inf`, `Filter.HasBasis.inf_principal`, `Filter.HasBasis.prod`,
`Filter.HasBasis.prod_self`, `Filter.HasBasis.map`, `Filter.HasBasis.comap` : combinators to
construct filters of `l ⊓ l'`, `l ⊓ 𝓟 t`, `l ×ˢ l'`, `l ×ˢ l`, `l.map f`, `l.comap f`
respectively;
* `Filter.HasBasis.le_iff`, `Filter.HasBasis.ge_iff`, `Filter.HasBasis.le_basis_iff` : restate
`l ≤ l'` in terms of bases.
* `Filter.HasBasis.tendsto_right_iff`, `Filter.HasBasis.tendsto_left_iff`,
`Filter.HasBasis.tendsto_iff` : restate `Tendsto f l l'` in terms of bases.
* `isCountablyGenerated_iff_exists_antitone_basis` : proves a filter is countably generated if and
only if it admits a basis parametrized by a decreasing sequence of sets indexed by `ℕ`.
* `tendsto_iff_seq_tendsto` : an abstract version of "sequentially continuous implies continuous".
## Implementation notes
As with `Set.iUnion`/`biUnion`/`Set.sUnion`, there are three different approaches to filter bases:
* `Filter.HasBasis l s`, `s : Set (Set α)`;
* `Filter.HasBasis l s`, `s : ι → Set α`;
* `Filter.HasBasis l p s`, `p : ι → Prop`, `s : ι → Set α`.
We use the latter one because, e.g., `𝓝 x` in an `EMetricSpace` or in a `MetricSpace` has a basis
of this form. The other two can be emulated using `s = id` or `p = fun _ ↦ True`.
With this approach sometimes one needs to `simp` the statement provided by the `Filter.HasBasis`
machinery, e.g., `simp only [true_and]` or `simp only [forall_const]` can help with the case
`p = fun _ ↦ True`.
-/
set_option autoImplicit true
open Set Filter
open scoped Classical
open Filter
section sort
variable {α β γ : Type*} {ι ι' : Sort*}
/-- A filter basis `B` on a type `α` is a nonempty collection of sets of `α`
such that the intersection of two elements of this collection contains some element
of the collection. -/
structure FilterBasis (α : Type*) where
/-- Sets of a filter basis. -/
sets : Set (Set α)
/-- The set of filter basis sets is nonempty. -/
nonempty : sets.Nonempty
/-- The set of filter basis sets is directed downwards. -/
inter_sets {x y} : x ∈ sets → y ∈ sets → ∃ z ∈ sets, z ⊆ x ∩ y
#align filter_basis FilterBasis
instance FilterBasis.nonempty_sets (B : FilterBasis α) : Nonempty B.sets :=
B.nonempty.to_subtype
#align filter_basis.nonempty_sets FilterBasis.nonempty_sets
-- Porting note: this instance was reducible but it doesn't work the same way in Lean 4
/-- If `B` is a filter basis on `α`, and `U` a subset of `α` then we can write `U ∈ B` as
on paper. -/
instance {α : Type*} : Membership (Set α) (FilterBasis α) :=
⟨fun U B => U ∈ B.sets⟩
@[simp] theorem FilterBasis.mem_sets {s : Set α} {B : FilterBasis α} : s ∈ B.sets ↔ s ∈ B := Iff.rfl
-- For illustration purposes, the filter basis defining `(atTop : Filter ℕ)`
instance : Inhabited (FilterBasis ℕ) :=
⟨{ sets := range Ici
nonempty := ⟨Ici 0, mem_range_self 0⟩
inter_sets := by
rintro _ _ ⟨n, rfl⟩ ⟨m, rfl⟩
exact ⟨Ici (max n m), mem_range_self _, Ici_inter_Ici.symm.subset⟩ }⟩
/-- View a filter as a filter basis. -/
def Filter.asBasis (f : Filter α) : FilterBasis α :=
⟨f.sets, ⟨univ, univ_mem⟩, fun {x y} hx hy => ⟨x ∩ y, inter_mem hx hy, subset_rfl⟩⟩
#align filter.as_basis Filter.asBasis
-- Porting note: was `protected` in Lean 3 but `protected` didn't work; removed
/-- `is_basis p s` means the image of `s` bounded by `p` is a filter basis. -/
structure Filter.IsBasis (p : ι → Prop) (s : ι → Set α) : Prop where
/-- There exists at least one `i` that satisfies `p`. -/
nonempty : ∃ i, p i
/-- `s` is directed downwards on `i` such that `p i`. -/
inter : ∀ {i j}, p i → p j → ∃ k, p k ∧ s k ⊆ s i ∩ s j
#align filter.is_basis Filter.IsBasis
namespace Filter
namespace IsBasis
/-- Constructs a filter basis from an indexed family of sets satisfying `IsBasis`. -/
protected def filterBasis {p : ι → Prop} {s : ι → Set α} (h : IsBasis p s) : FilterBasis α where
sets := { t | ∃ i, p i ∧ s i = t }
nonempty :=
let ⟨i, hi⟩ := h.nonempty
⟨s i, ⟨i, hi, rfl⟩⟩
inter_sets := by
rintro _ _ ⟨i, hi, rfl⟩ ⟨j, hj, rfl⟩
rcases h.inter hi hj with ⟨k, hk, hk'⟩
exact ⟨_, ⟨k, hk, rfl⟩, hk'⟩
#align filter.is_basis.filter_basis Filter.IsBasis.filterBasis
variable {p : ι → Prop} {s : ι → Set α} (h : IsBasis p s)
theorem mem_filterBasis_iff {U : Set α} : U ∈ h.filterBasis ↔ ∃ i, p i ∧ s i = U :=
Iff.rfl
#align filter.is_basis.mem_filter_basis_iff Filter.IsBasis.mem_filterBasis_iff
end IsBasis
end Filter
namespace FilterBasis
/-- The filter associated to a filter basis. -/
protected def filter (B : FilterBasis α) : Filter α where
sets := { s | ∃ t ∈ B, t ⊆ s }
univ_sets := B.nonempty.imp fun s s_in => ⟨s_in, s.subset_univ⟩
sets_of_superset := fun ⟨s, s_in, h⟩ hxy => ⟨s, s_in, Set.Subset.trans h hxy⟩
inter_sets := fun ⟨_s, s_in, hs⟩ ⟨_t, t_in, ht⟩ =>
let ⟨u, u_in, u_sub⟩ := B.inter_sets s_in t_in
⟨u, u_in, u_sub.trans (inter_subset_inter hs ht)⟩
#align filter_basis.filter FilterBasis.filter
theorem mem_filter_iff (B : FilterBasis α) {U : Set α} : U ∈ B.filter ↔ ∃ s ∈ B, s ⊆ U :=
Iff.rfl
#align filter_basis.mem_filter_iff FilterBasis.mem_filter_iff
theorem mem_filter_of_mem (B : FilterBasis α) {U : Set α} : U ∈ B → U ∈ B.filter := fun U_in =>
⟨U, U_in, Subset.refl _⟩
#align filter_basis.mem_filter_of_mem FilterBasis.mem_filter_of_mem
theorem eq_iInf_principal (B : FilterBasis α) : B.filter = ⨅ s : B.sets, 𝓟 s := by
have : Directed (· ≥ ·) fun s : B.sets => 𝓟 (s : Set α) := by
rintro ⟨U, U_in⟩ ⟨V, V_in⟩
rcases B.inter_sets U_in V_in with ⟨W, W_in, W_sub⟩
use ⟨W, W_in⟩
simp only [ge_iff_le, le_principal_iff, mem_principal, Subtype.coe_mk]
exact subset_inter_iff.mp W_sub
ext U
simp [mem_filter_iff, mem_iInf_of_directed this]
#align filter_basis.eq_infi_principal FilterBasis.eq_iInf_principal
protected theorem generate (B : FilterBasis α) : generate B.sets = B.filter := by
apply le_antisymm
· intro U U_in
rcases B.mem_filter_iff.mp U_in with ⟨V, V_in, h⟩
exact GenerateSets.superset (GenerateSets.basic V_in) h
· rw [le_generate_iff]
apply mem_filter_of_mem
#align filter_basis.generate FilterBasis.generate
end FilterBasis
namespace Filter
namespace IsBasis
variable {p : ι → Prop} {s : ι → Set α}
/-- Constructs a filter from an indexed family of sets satisfying `IsBasis`. -/
protected def filter (h : IsBasis p s) : Filter α :=
h.filterBasis.filter
#align filter.is_basis.filter Filter.IsBasis.filter
protected theorem mem_filter_iff (h : IsBasis p s) {U : Set α} :
U ∈ h.filter ↔ ∃ i, p i ∧ s i ⊆ U := by
simp only [IsBasis.filter, FilterBasis.mem_filter_iff, mem_filterBasis_iff,
exists_exists_and_eq_and]
#align filter.is_basis.mem_filter_iff Filter.IsBasis.mem_filter_iff
theorem filter_eq_generate (h : IsBasis p s) : h.filter = generate { U | ∃ i, p i ∧ s i = U } := by
erw [h.filterBasis.generate]; rfl
#align filter.is_basis.filter_eq_generate Filter.IsBasis.filter_eq_generate
end IsBasis
-- Porting note: was `protected` in Lean 3 but `protected` didn't work; removed
/-- We say that a filter `l` has a basis `s : ι → Set α` bounded by `p : ι → Prop`,
if `t ∈ l` if and only if `t` includes `s i` for some `i` such that `p i`. -/
structure HasBasis (l : Filter α) (p : ι → Prop) (s : ι → Set α) : Prop where
/-- A set `t` belongs to a filter `l` iff it includes an element of the basis. -/
mem_iff' : ∀ t : Set α, t ∈ l ↔ ∃ i, p i ∧ s i ⊆ t
#align filter.has_basis Filter.HasBasis
section SameType
variable {l l' : Filter α} {p : ι → Prop} {s : ι → Set α} {t : Set α} {i : ι} {p' : ι' → Prop}
{s' : ι' → Set α} {i' : ι'}
theorem hasBasis_generate (s : Set (Set α)) :
(generate s).HasBasis (fun t => Set.Finite t ∧ t ⊆ s) fun t => ⋂₀ t :=
⟨fun U => by simp only [mem_generate_iff, exists_prop, and_assoc, and_left_comm]⟩
#align filter.has_basis_generate Filter.hasBasis_generate
/-- The smallest filter basis containing a given collection of sets. -/
def FilterBasis.ofSets (s : Set (Set α)) : FilterBasis α where
sets := sInter '' { t | Set.Finite t ∧ t ⊆ s }
nonempty := ⟨univ, ∅, ⟨⟨finite_empty, empty_subset s⟩, sInter_empty⟩⟩
inter_sets := by
rintro _ _ ⟨a, ⟨fina, suba⟩, rfl⟩ ⟨b, ⟨finb, subb⟩, rfl⟩
exact ⟨⋂₀ (a ∪ b), mem_image_of_mem _ ⟨fina.union finb, union_subset suba subb⟩,
(sInter_union _ _).subset⟩
#align filter.filter_basis.of_sets Filter.FilterBasis.ofSets
lemma FilterBasis.ofSets_sets (s : Set (Set α)) :
(FilterBasis.ofSets s).sets = sInter '' { t | Set.Finite t ∧ t ⊆ s } :=
rfl
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
/-- Definition of `HasBasis` unfolded with implicit set argument. -/
theorem HasBasis.mem_iff (hl : l.HasBasis p s) : t ∈ l ↔ ∃ i, p i ∧ s i ⊆ t :=
hl.mem_iff' t
#align filter.has_basis.mem_iff Filter.HasBasis.mem_iffₓ
theorem HasBasis.eq_of_same_basis (hl : l.HasBasis p s) (hl' : l'.HasBasis p s) : l = l' := by
ext t
rw [hl.mem_iff, hl'.mem_iff]
#align filter.has_basis.eq_of_same_basis Filter.HasBasis.eq_of_same_basis
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem hasBasis_iff : l.HasBasis p s ↔ ∀ t, t ∈ l ↔ ∃ i, p i ∧ s i ⊆ t :=
⟨fun ⟨h⟩ => h, fun h => ⟨h⟩⟩
#align filter.has_basis_iff Filter.hasBasis_iffₓ
theorem HasBasis.ex_mem (h : l.HasBasis p s) : ∃ i, p i :=
(h.mem_iff.mp univ_mem).imp fun _ => And.left
#align filter.has_basis.ex_mem Filter.HasBasis.ex_mem
protected theorem HasBasis.nonempty (h : l.HasBasis p s) : Nonempty ι :=
nonempty_of_exists h.ex_mem
#align filter.has_basis.nonempty Filter.HasBasis.nonempty
protected theorem IsBasis.hasBasis (h : IsBasis p s) : HasBasis h.filter p s :=
⟨fun t => by simp only [h.mem_filter_iff, exists_prop]⟩
#align filter.is_basis.has_basis Filter.IsBasis.hasBasis
protected theorem HasBasis.mem_of_superset (hl : l.HasBasis p s) (hi : p i) (ht : s i ⊆ t) :
t ∈ l :=
hl.mem_iff.2 ⟨i, hi, ht⟩
#align filter.has_basis.mem_of_superset Filter.HasBasis.mem_of_superset
theorem HasBasis.mem_of_mem (hl : l.HasBasis p s) (hi : p i) : s i ∈ l :=
hl.mem_of_superset hi Subset.rfl
#align filter.has_basis.mem_of_mem Filter.HasBasis.mem_of_mem
/-- Index of a basis set such that `s i ⊆ t` as an element of `Subtype p`. -/
noncomputable def HasBasis.index (h : l.HasBasis p s) (t : Set α) (ht : t ∈ l) : { i : ι // p i } :=
⟨(h.mem_iff.1 ht).choose, (h.mem_iff.1 ht).choose_spec.1⟩
#align filter.has_basis.index Filter.HasBasis.index
theorem HasBasis.property_index (h : l.HasBasis p s) (ht : t ∈ l) : p (h.index t ht) :=
(h.index t ht).2
#align filter.has_basis.property_index Filter.HasBasis.property_index
theorem HasBasis.set_index_mem (h : l.HasBasis p s) (ht : t ∈ l) : s (h.index t ht) ∈ l :=
h.mem_of_mem <| h.property_index _
#align filter.has_basis.set_index_mem Filter.HasBasis.set_index_mem
theorem HasBasis.set_index_subset (h : l.HasBasis p s) (ht : t ∈ l) : s (h.index t ht) ⊆ t :=
(h.mem_iff.1 ht).choose_spec.2
#align filter.has_basis.set_index_subset Filter.HasBasis.set_index_subset
theorem HasBasis.isBasis (h : l.HasBasis p s) : IsBasis p s where
nonempty := h.ex_mem
inter hi hj := by
simpa only [h.mem_iff] using inter_mem (h.mem_of_mem hi) (h.mem_of_mem hj)
#align filter.has_basis.is_basis Filter.HasBasis.isBasis
theorem HasBasis.filter_eq (h : l.HasBasis p s) : h.isBasis.filter = l := by
ext U
simp [h.mem_iff, IsBasis.mem_filter_iff]
#align filter.has_basis.filter_eq Filter.HasBasis.filter_eq
theorem HasBasis.eq_generate (h : l.HasBasis p s) : l = generate { U | ∃ i, p i ∧ s i = U } := by
rw [← h.isBasis.filter_eq_generate, h.filter_eq]
#align filter.has_basis.eq_generate Filter.HasBasis.eq_generate
theorem generate_eq_generate_inter (s : Set (Set α)) :
generate s = generate (sInter '' { t | Set.Finite t ∧ t ⊆ s }) := by
rw [← FilterBasis.ofSets_sets, FilterBasis.generate, ← (hasBasis_generate s).filter_eq]; rfl
#align filter.generate_eq_generate_inter Filter.generate_eq_generate_inter
theorem ofSets_filter_eq_generate (s : Set (Set α)) :
(FilterBasis.ofSets s).filter = generate s := by
rw [← (FilterBasis.ofSets s).generate, FilterBasis.ofSets_sets, ← generate_eq_generate_inter]
#align filter.of_sets_filter_eq_generate Filter.ofSets_filter_eq_generate
protected theorem _root_.FilterBasis.hasBasis (B : FilterBasis α) :
HasBasis B.filter (fun s : Set α => s ∈ B) id :=
⟨fun _ => B.mem_filter_iff⟩
#align filter_basis.has_basis FilterBasis.hasBasis
theorem HasBasis.to_hasBasis' (hl : l.HasBasis p s) (h : ∀ i, p i → ∃ i', p' i' ∧ s' i' ⊆ s i)
(h' : ∀ i', p' i' → s' i' ∈ l) : l.HasBasis p' s' := by
refine ⟨fun t => ⟨fun ht => ?_, fun ⟨i', hi', ht⟩ => mem_of_superset (h' i' hi') ht⟩⟩
rcases hl.mem_iff.1 ht with ⟨i, hi, ht⟩
rcases h i hi with ⟨i', hi', hs's⟩
exact ⟨i', hi', hs's.trans ht⟩
#align filter.has_basis.to_has_basis' Filter.HasBasis.to_hasBasis'
theorem HasBasis.to_hasBasis (hl : l.HasBasis p s) (h : ∀ i, p i → ∃ i', p' i' ∧ s' i' ⊆ s i)
(h' : ∀ i', p' i' → ∃ i, p i ∧ s i ⊆ s' i') : l.HasBasis p' s' :=
hl.to_hasBasis' h fun i' hi' =>
let ⟨i, hi, hss'⟩ := h' i' hi'
hl.mem_iff.2 ⟨i, hi, hss'⟩
#align filter.has_basis.to_has_basis Filter.HasBasis.to_hasBasis
protected lemma HasBasis.congr (hl : l.HasBasis p s) {p' s'} (hp : ∀ i, p i ↔ p' i)
(hs : ∀ i, p i → s i = s' i) : l.HasBasis p' s' :=
⟨fun t ↦ by simp only [hl.mem_iff, ← hp]; exact exists_congr fun i ↦
and_congr_right fun hi ↦ hs i hi ▸ Iff.rfl⟩
theorem HasBasis.to_subset (hl : l.HasBasis p s) {t : ι → Set α} (h : ∀ i, p i → t i ⊆ s i)
(ht : ∀ i, p i → t i ∈ l) : l.HasBasis p t :=
hl.to_hasBasis' (fun i hi => ⟨i, hi, h i hi⟩) ht
#align filter.has_basis.to_subset Filter.HasBasis.to_subset
theorem HasBasis.eventually_iff (hl : l.HasBasis p s) {q : α → Prop} :
(∀ᶠ x in l, q x) ↔ ∃ i, p i ∧ ∀ ⦃x⦄, x ∈ s i → q x := by simpa using hl.mem_iff
#align filter.has_basis.eventually_iff Filter.HasBasis.eventually_iff
theorem HasBasis.frequently_iff (hl : l.HasBasis p s) {q : α → Prop} :
(∃ᶠ x in l, q x) ↔ ∀ i, p i → ∃ x ∈ s i, q x := by
simp only [Filter.Frequently, hl.eventually_iff]; push_neg; rfl
#align filter.has_basis.frequently_iff Filter.HasBasis.frequently_iff
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.exists_iff (hl : l.HasBasis p s) {P : Set α → Prop}
(mono : ∀ ⦃s t⦄, s ⊆ t → P t → P s) : (∃ s ∈ l, P s) ↔ ∃ i, p i ∧ P (s i) :=
⟨fun ⟨_s, hs, hP⟩ =>
let ⟨i, hi, his⟩ := hl.mem_iff.1 hs
⟨i, hi, mono his hP⟩,
fun ⟨i, hi, hP⟩ => ⟨s i, hl.mem_of_mem hi, hP⟩⟩
#align filter.has_basis.exists_iff Filter.HasBasis.exists_iffₓ
theorem HasBasis.forall_iff (hl : l.HasBasis p s) {P : Set α → Prop}
(mono : ∀ ⦃s t⦄, s ⊆ t → P s → P t) : (∀ s ∈ l, P s) ↔ ∀ i, p i → P (s i) :=
⟨fun H i hi => H (s i) <| hl.mem_of_mem hi, fun H _s hs =>
let ⟨i, hi, his⟩ := hl.mem_iff.1 hs
mono his (H i hi)⟩
#align filter.has_basis.forall_iff Filter.HasBasis.forall_iff
protected theorem HasBasis.neBot_iff (hl : l.HasBasis p s) :
NeBot l ↔ ∀ {i}, p i → (s i).Nonempty :=
forall_mem_nonempty_iff_neBot.symm.trans <| hl.forall_iff fun _ _ => Nonempty.mono
#align filter.has_basis.ne_bot_iff Filter.HasBasis.neBot_iff
theorem HasBasis.eq_bot_iff (hl : l.HasBasis p s) : l = ⊥ ↔ ∃ i, p i ∧ s i = ∅ :=
not_iff_not.1 <| neBot_iff.symm.trans <|
hl.neBot_iff.trans <| by simp only [not_exists, not_and, nonempty_iff_ne_empty]
#align filter.has_basis.eq_bot_iff Filter.HasBasis.eq_bot_iff
theorem generate_neBot_iff {s : Set (Set α)} :
NeBot (generate s) ↔ ∀ t, t ⊆ s → t.Finite → (⋂₀ t).Nonempty :=
(hasBasis_generate s).neBot_iff.trans <| by simp only [← and_imp, and_comm]
#align filter.generate_ne_bot_iff Filter.generate_neBot_iff
theorem basis_sets (l : Filter α) : l.HasBasis (fun s : Set α => s ∈ l) id :=
⟨fun _ => exists_mem_subset_iff.symm⟩
#align filter.basis_sets Filter.basis_sets
theorem asBasis_filter (f : Filter α) : f.asBasis.filter = f :=
Filter.ext fun _ => exists_mem_subset_iff
#align filter.as_basis_filter Filter.asBasis_filter
theorem hasBasis_self {l : Filter α} {P : Set α → Prop} :
HasBasis l (fun s => s ∈ l ∧ P s) id ↔ ∀ t ∈ l, ∃ r ∈ l, P r ∧ r ⊆ t := by
simp only [hasBasis_iff, id, and_assoc]
exact forall_congr' fun s =>
⟨fun h => h.1, fun h => ⟨h, fun ⟨t, hl, _, hts⟩ => mem_of_superset hl hts⟩⟩
#align filter.has_basis_self Filter.hasBasis_self
theorem HasBasis.comp_surjective (h : l.HasBasis p s) {g : ι' → ι} (hg : Function.Surjective g) :
l.HasBasis (p ∘ g) (s ∘ g) :=
⟨fun _ => h.mem_iff.trans hg.exists⟩
#align filter.has_basis.comp_surjective Filter.HasBasis.comp_surjective
theorem HasBasis.comp_equiv (h : l.HasBasis p s) (e : ι' ≃ ι) : l.HasBasis (p ∘ e) (s ∘ e) :=
h.comp_surjective e.surjective
#align filter.has_basis.comp_equiv Filter.HasBasis.comp_equiv
theorem HasBasis.to_image_id' (h : l.HasBasis p s) : l.HasBasis (fun t ↦ ∃ i, p i ∧ s i = t) id :=
⟨fun _ ↦ by simp [h.mem_iff]⟩
theorem HasBasis.to_image_id {ι : Type*} {p : ι → Prop} {s : ι → Set α} (h : l.HasBasis p s) :
l.HasBasis (· ∈ s '' {i | p i}) id :=
h.to_image_id'
/-- If `{s i | p i}` is a basis of a filter `l` and each `s i` includes `s j` such that
`p j ∧ q j`, then `{s j | p j ∧ q j}` is a basis of `l`. -/
theorem HasBasis.restrict (h : l.HasBasis p s) {q : ι → Prop}
(hq : ∀ i, p i → ∃ j, p j ∧ q j ∧ s j ⊆ s i) : l.HasBasis (fun i => p i ∧ q i) s := by
refine ⟨fun t => ⟨fun ht => ?_, fun ⟨i, hpi, hti⟩ => h.mem_iff.2 ⟨i, hpi.1, hti⟩⟩⟩
rcases h.mem_iff.1 ht with ⟨i, hpi, hti⟩
rcases hq i hpi with ⟨j, hpj, hqj, hji⟩
exact ⟨j, ⟨hpj, hqj⟩, hji.trans hti⟩
#align filter.has_basis.restrict Filter.HasBasis.restrict
/-- If `{s i | p i}` is a basis of a filter `l` and `V ∈ l`, then `{s i | p i ∧ s i ⊆ V}`
is a basis of `l`. -/
theorem HasBasis.restrict_subset (h : l.HasBasis p s) {V : Set α} (hV : V ∈ l) :
l.HasBasis (fun i => p i ∧ s i ⊆ V) s :=
h.restrict fun _i hi => (h.mem_iff.1 (inter_mem hV (h.mem_of_mem hi))).imp fun _j hj =>
⟨hj.1, subset_inter_iff.1 hj.2⟩
#align filter.has_basis.restrict_subset Filter.HasBasis.restrict_subset
theorem HasBasis.hasBasis_self_subset {p : Set α → Prop} (h : l.HasBasis (fun s => s ∈ l ∧ p s) id)
{V : Set α} (hV : V ∈ l) : l.HasBasis (fun s => s ∈ l ∧ p s ∧ s ⊆ V) id := by
simpa only [and_assoc] using h.restrict_subset hV
#align filter.has_basis.has_basis_self_subset Filter.HasBasis.hasBasis_self_subset
theorem HasBasis.ge_iff (hl' : l'.HasBasis p' s') : l ≤ l' ↔ ∀ i', p' i' → s' i' ∈ l :=
⟨fun h _i' hi' => h <| hl'.mem_of_mem hi', fun h _s hs =>
let ⟨_i', hi', hs⟩ := hl'.mem_iff.1 hs
mem_of_superset (h _ hi') hs⟩
#align filter.has_basis.ge_iff Filter.HasBasis.ge_iff
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.le_iff (hl : l.HasBasis p s) : l ≤ l' ↔ ∀ t ∈ l', ∃ i, p i ∧ s i ⊆ t := by
simp only [le_def, hl.mem_iff]
#align filter.has_basis.le_iff Filter.HasBasis.le_iffₓ
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.le_basis_iff (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
l ≤ l' ↔ ∀ i', p' i' → ∃ i, p i ∧ s i ⊆ s' i' := by
simp only [hl'.ge_iff, hl.mem_iff]
#align filter.has_basis.le_basis_iff Filter.HasBasis.le_basis_iffₓ
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.ext (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s')
(h : ∀ i, p i → ∃ i', p' i' ∧ s' i' ⊆ s i) (h' : ∀ i', p' i' → ∃ i, p i ∧ s i ⊆ s' i') :
l = l' := by
apply le_antisymm
· rw [hl.le_basis_iff hl']
simpa using h'
· rw [hl'.le_basis_iff hl]
simpa using h
#align filter.has_basis.ext Filter.HasBasis.extₓ
theorem HasBasis.inf' (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
(l ⊓ l').HasBasis (fun i : PProd ι ι' => p i.1 ∧ p' i.2) fun i => s i.1 ∩ s' i.2 :=
⟨by
intro t
constructor
· simp only [mem_inf_iff, hl.mem_iff, hl'.mem_iff]
rintro ⟨t, ⟨i, hi, ht⟩, t', ⟨i', hi', ht'⟩, rfl⟩
exact ⟨⟨i, i'⟩, ⟨hi, hi'⟩, inter_subset_inter ht ht'⟩
· rintro ⟨⟨i, i'⟩, ⟨hi, hi'⟩, H⟩
exact mem_inf_of_inter (hl.mem_of_mem hi) (hl'.mem_of_mem hi') H⟩
#align filter.has_basis.inf' Filter.HasBasis.inf'
theorem HasBasis.inf {ι ι' : Type*} {p : ι → Prop} {s : ι → Set α} {p' : ι' → Prop}
{s' : ι' → Set α} (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
(l ⊓ l').HasBasis (fun i : ι × ι' => p i.1 ∧ p' i.2) fun i => s i.1 ∩ s' i.2 :=
(hl.inf' hl').comp_equiv Equiv.pprodEquivProd.symm
#align filter.has_basis.inf Filter.HasBasis.inf
theorem hasBasis_iInf' {ι : Type*} {ι' : ι → Type*} {l : ι → Filter α} {p : ∀ i, ι' i → Prop}
{s : ∀ i, ι' i → Set α} (hl : ∀ i, (l i).HasBasis (p i) (s i)) :
(⨅ i, l i).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 => ⋂ i ∈ If.1, s i (If.2 i) :=
⟨by
intro t
constructor
· simp only [mem_iInf', (hl _).mem_iff]
rintro ⟨I, hI, V, hV, -, rfl, -⟩
choose u hu using hV
exact ⟨⟨I, u⟩, ⟨hI, fun i _ => (hu i).1⟩, iInter₂_mono fun i _ => (hu i).2⟩
· rintro ⟨⟨I, f⟩, ⟨hI₁, hI₂⟩, hsub⟩
refine mem_of_superset ?_ hsub
exact (biInter_mem hI₁).mpr fun i hi => mem_iInf_of_mem i <| (hl i).mem_of_mem <| hI₂ _ hi⟩
#align filter.has_basis_infi' Filter.hasBasis_iInf'
theorem hasBasis_iInf {ι : Type*} {ι' : ι → Type*} {l : ι → Filter α} {p : ∀ i, ι' i → Prop}
{s : ∀ i, ι' i → Set α} (hl : ∀ i, (l i).HasBasis (p i) (s i)) :
(⨅ i, l i).HasBasis
(fun If : Σ I : Set ι, ∀ i : I, ι' i => If.1.Finite ∧ ∀ i : If.1, p i (If.2 i)) fun If =>
⋂ i : If.1, s i (If.2 i) := by
refine ⟨fun t => ⟨fun ht => ?_, ?_⟩⟩
· rcases (hasBasis_iInf' hl).mem_iff.mp ht with ⟨⟨I, f⟩, ⟨hI, hf⟩, hsub⟩
exact ⟨⟨I, fun i => f i⟩, ⟨hI, Subtype.forall.mpr hf⟩, trans (iInter_subtype _ _) hsub⟩
· rintro ⟨⟨I, f⟩, ⟨hI, hf⟩, hsub⟩
refine mem_of_superset ?_ hsub
cases hI.nonempty_fintype
exact iInter_mem.2 fun i => mem_iInf_of_mem ↑i <| (hl i).mem_of_mem <| hf _
#align filter.has_basis_infi Filter.hasBasis_iInf
theorem hasBasis_iInf_of_directed' {ι : Type*} {ι' : ι → Sort _} [Nonempty ι] {l : ι → Filter α}
(s : ∀ i, ι' i → Set α) (p : ∀ i, ι' i → Prop) (hl : ∀ i, (l i).HasBasis (p i) (s i))
(h : Directed (· ≥ ·) l) :
(⨅ i, l i).HasBasis (fun ii' : Σi, ι' i => p ii'.1 ii'.2) fun ii' => s ii'.1 ii'.2 := by
refine ⟨fun t => ?_⟩
rw [mem_iInf_of_directed h, Sigma.exists]
exact exists_congr fun i => (hl i).mem_iff
#align filter.has_basis_infi_of_directed' Filter.hasBasis_iInf_of_directed'
theorem hasBasis_iInf_of_directed {ι : Type*} {ι' : Sort _} [Nonempty ι] {l : ι → Filter α}
(s : ι → ι' → Set α) (p : ι → ι' → Prop) (hl : ∀ i, (l i).HasBasis (p i) (s i))
(h : Directed (· ≥ ·) l) :
(⨅ i, l i).HasBasis (fun ii' : ι × ι' => p ii'.1 ii'.2) fun ii' => s ii'.1 ii'.2 := by
refine ⟨fun t => ?_⟩
rw [mem_iInf_of_directed h, Prod.exists]
exact exists_congr fun i => (hl i).mem_iff
#align filter.has_basis_infi_of_directed Filter.hasBasis_iInf_of_directed
theorem hasBasis_biInf_of_directed' {ι : Type*} {ι' : ι → Sort _} {dom : Set ι}
(hdom : dom.Nonempty) {l : ι → Filter α} (s : ∀ i, ι' i → Set α) (p : ∀ i, ι' i → Prop)
(hl : ∀ i ∈ dom, (l i).HasBasis (p i) (s i)) (h : DirectedOn (l ⁻¹'o GE.ge) dom) :
(⨅ i ∈ dom, l i).HasBasis (fun ii' : Σi, ι' i => ii'.1 ∈ dom ∧ p ii'.1 ii'.2) fun ii' =>
s ii'.1 ii'.2 := by
refine ⟨fun t => ?_⟩
rw [mem_biInf_of_directed h hdom, Sigma.exists]
refine exists_congr fun i => ⟨?_, ?_⟩
· rintro ⟨hi, hti⟩
rcases (hl i hi).mem_iff.mp hti with ⟨b, hb, hbt⟩
exact ⟨b, ⟨hi, hb⟩, hbt⟩
· rintro ⟨b, ⟨hi, hb⟩, hibt⟩
exact ⟨hi, (hl i hi).mem_iff.mpr ⟨b, hb, hibt⟩⟩
#align filter.has_basis_binfi_of_directed' Filter.hasBasis_biInf_of_directed'
theorem hasBasis_biInf_of_directed {ι : Type*} {ι' : Sort _} {dom : Set ι} (hdom : dom.Nonempty)
{l : ι → Filter α} (s : ι → ι' → Set α) (p : ι → ι' → Prop)
(hl : ∀ i ∈ dom, (l i).HasBasis (p i) (s i)) (h : DirectedOn (l ⁻¹'o GE.ge) dom) :
(⨅ i ∈ dom, l i).HasBasis (fun ii' : ι × ι' => ii'.1 ∈ dom ∧ p ii'.1 ii'.2) fun ii' =>
s ii'.1 ii'.2 := by
refine ⟨fun t => ?_⟩
rw [mem_biInf_of_directed h hdom, Prod.exists]
refine exists_congr fun i => ⟨?_, ?_⟩
· rintro ⟨hi, hti⟩
rcases (hl i hi).mem_iff.mp hti with ⟨b, hb, hbt⟩
exact ⟨b, ⟨hi, hb⟩, hbt⟩
· rintro ⟨b, ⟨hi, hb⟩, hibt⟩
exact ⟨hi, (hl i hi).mem_iff.mpr ⟨b, hb, hibt⟩⟩
#align filter.has_basis_binfi_of_directed Filter.hasBasis_biInf_of_directed
theorem hasBasis_principal (t : Set α) : (𝓟 t).HasBasis (fun _ : Unit => True) fun _ => t :=
⟨fun U => by simp⟩
#align filter.has_basis_principal Filter.hasBasis_principal
theorem hasBasis_pure (x : α) :
(pure x : Filter α).HasBasis (fun _ : Unit => True) fun _ => {x} := by
simp only [← principal_singleton, hasBasis_principal]
#align filter.has_basis_pure Filter.hasBasis_pure
theorem HasBasis.sup' (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
(l ⊔ l').HasBasis (fun i : PProd ι ι' => p i.1 ∧ p' i.2) fun i => s i.1 ∪ s' i.2 :=
⟨by
intro t
simp_rw [mem_sup, hl.mem_iff, hl'.mem_iff, PProd.exists, union_subset_iff,
← exists_and_right, ← exists_and_left]
simp only [and_assoc, and_left_comm]⟩
#align filter.has_basis.sup' Filter.HasBasis.sup'
theorem HasBasis.sup {ι ι' : Type*} {p : ι → Prop} {s : ι → Set α} {p' : ι' → Prop}
{s' : ι' → Set α} (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
(l ⊔ l').HasBasis (fun i : ι × ι' => p i.1 ∧ p' i.2) fun i => s i.1 ∪ s' i.2 :=
(hl.sup' hl').comp_equiv Equiv.pprodEquivProd.symm
#align filter.has_basis.sup Filter.HasBasis.sup
theorem hasBasis_iSup {ι : Sort*} {ι' : ι → Type*} {l : ι → Filter α} {p : ∀ i, ι' i → Prop}
{s : ∀ i, ι' i → Set α} (hl : ∀ i, (l i).HasBasis (p i) (s i)) :
(⨆ i, l i).HasBasis (fun f : ∀ i, ι' i => ∀ i, p i (f i)) fun f : ∀ i, ι' i => ⋃ i, s i (f i) :=
hasBasis_iff.mpr fun t => by
simp only [hasBasis_iff, (hl _).mem_iff, Classical.skolem, forall_and, iUnion_subset_iff,
mem_iSup]
#align filter.has_basis_supr Filter.hasBasis_iSup
theorem HasBasis.sup_principal (hl : l.HasBasis p s) (t : Set α) :
(l ⊔ 𝓟 t).HasBasis p fun i => s i ∪ t :=
⟨fun u => by
simp only [(hl.sup' (hasBasis_principal t)).mem_iff, PProd.exists, exists_prop, and_true_iff,
Unique.exists_iff]⟩
#align filter.has_basis.sup_principal Filter.HasBasis.sup_principal
theorem HasBasis.sup_pure (hl : l.HasBasis p s) (x : α) :
(l ⊔ pure x).HasBasis p fun i => s i ∪ {x} := by
simp only [← principal_singleton, hl.sup_principal]
#align filter.has_basis.sup_pure Filter.HasBasis.sup_pure
theorem HasBasis.inf_principal (hl : l.HasBasis p s) (s' : Set α) :
(l ⊓ 𝓟 s').HasBasis p fun i => s i ∩ s' :=
⟨fun t => by
simp only [mem_inf_principal, hl.mem_iff, subset_def, mem_setOf_eq, mem_inter_iff, and_imp]⟩
#align filter.has_basis.inf_principal Filter.HasBasis.inf_principal
theorem HasBasis.principal_inf (hl : l.HasBasis p s) (s' : Set α) :
(𝓟 s' ⊓ l).HasBasis p fun i => s' ∩ s i := by
simpa only [inf_comm, inter_comm] using hl.inf_principal s'
#align filter.has_basis.principal_inf Filter.HasBasis.principal_inf
theorem HasBasis.inf_basis_neBot_iff (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
NeBot (l ⊓ l') ↔ ∀ ⦃i⦄, p i → ∀ ⦃i'⦄, p' i' → (s i ∩ s' i').Nonempty :=
(hl.inf' hl').neBot_iff.trans <| by simp [@forall_swap _ ι']
#align filter.has_basis.inf_basis_ne_bot_iff Filter.HasBasis.inf_basis_neBot_iff
theorem HasBasis.inf_neBot_iff (hl : l.HasBasis p s) :
NeBot (l ⊓ l') ↔ ∀ ⦃i⦄, p i → ∀ ⦃s'⦄, s' ∈ l' → (s i ∩ s').Nonempty :=
hl.inf_basis_neBot_iff l'.basis_sets
#align filter.has_basis.inf_ne_bot_iff Filter.HasBasis.inf_neBot_iff
theorem HasBasis.inf_principal_neBot_iff (hl : l.HasBasis p s) {t : Set α} :
NeBot (l ⊓ 𝓟 t) ↔ ∀ ⦃i⦄, p i → (s i ∩ t).Nonempty :=
(hl.inf_principal t).neBot_iff
#align filter.has_basis.inf_principal_ne_bot_iff Filter.HasBasis.inf_principal_neBot_iff
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.disjoint_iff (hl : l.HasBasis p s) (hl' : l'.HasBasis p' s') :
Disjoint l l' ↔ ∃ i, p i ∧ ∃ i', p' i' ∧ Disjoint (s i) (s' i') :=
not_iff_not.mp <| by simp only [_root_.disjoint_iff, ← Ne.eq_def, ← neBot_iff, inf_eq_inter,
hl.inf_basis_neBot_iff hl', not_exists, not_and, bot_eq_empty, ← nonempty_iff_ne_empty]
#align filter.has_basis.disjoint_iff Filter.HasBasis.disjoint_iffₓ
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem _root_.Disjoint.exists_mem_filter_basis (h : Disjoint l l') (hl : l.HasBasis p s)
(hl' : l'.HasBasis p' s') : ∃ i, p i ∧ ∃ i', p' i' ∧ Disjoint (s i) (s' i') :=
(hl.disjoint_iff hl').1 h
#align disjoint.exists_mem_filter_basis Disjoint.exists_mem_filter_basisₓ
theorem _root_.Pairwise.exists_mem_filter_basis_of_disjoint {I} [Finite I] {l : I → Filter α}
{ι : I → Sort*} {p : ∀ i, ι i → Prop} {s : ∀ i, ι i → Set α} (hd : Pairwise (Disjoint on l))
(h : ∀ i, (l i).HasBasis (p i) (s i)) :
∃ ind : ∀ i, ι i, (∀ i, p i (ind i)) ∧ Pairwise (Disjoint on fun i => s i (ind i)) := by
rcases hd.exists_mem_filter_of_disjoint with ⟨t, htl, hd⟩
choose ind hp ht using fun i => (h i).mem_iff.1 (htl i)
exact ⟨ind, hp, hd.mono fun i j hij => hij.mono (ht _) (ht _)⟩
#align pairwise.exists_mem_filter_basis_of_disjoint Pairwise.exists_mem_filter_basis_of_disjoint
theorem _root_.Set.PairwiseDisjoint.exists_mem_filter_basis {I : Type*} {l : I → Filter α}
{ι : I → Sort*} {p : ∀ i, ι i → Prop} {s : ∀ i, ι i → Set α} {S : Set I}
(hd : S.PairwiseDisjoint l) (hS : S.Finite) (h : ∀ i, (l i).HasBasis (p i) (s i)) :
∃ ind : ∀ i, ι i, (∀ i, p i (ind i)) ∧ S.PairwiseDisjoint fun i => s i (ind i) := by
rcases hd.exists_mem_filter hS with ⟨t, htl, hd⟩
choose ind hp ht using fun i => (h i).mem_iff.1 (htl i)
exact ⟨ind, hp, hd.mono ht⟩
#align set.pairwise_disjoint.exists_mem_filter_basis Set.PairwiseDisjoint.exists_mem_filter_basis
theorem inf_neBot_iff :
NeBot (l ⊓ l') ↔ ∀ ⦃s : Set α⦄, s ∈ l → ∀ ⦃s'⦄, s' ∈ l' → (s ∩ s').Nonempty :=
l.basis_sets.inf_neBot_iff
#align filter.inf_ne_bot_iff Filter.inf_neBot_iff
theorem inf_principal_neBot_iff {s : Set α} : NeBot (l ⊓ 𝓟 s) ↔ ∀ U ∈ l, (U ∩ s).Nonempty :=
l.basis_sets.inf_principal_neBot_iff
#align filter.inf_principal_ne_bot_iff Filter.inf_principal_neBot_iff
theorem mem_iff_inf_principal_compl {f : Filter α} {s : Set α} : s ∈ f ↔ f ⊓ 𝓟 sᶜ = ⊥ := by
refine not_iff_not.1 ((inf_principal_neBot_iff.trans ?_).symm.trans neBot_iff)
exact
⟨fun h hs => by simpa [Set.not_nonempty_empty] using h s hs, fun hs t ht =>
inter_compl_nonempty_iff.2 fun hts => hs <| mem_of_superset ht hts⟩
#align filter.mem_iff_inf_principal_compl Filter.mem_iff_inf_principal_compl
theorem not_mem_iff_inf_principal_compl {f : Filter α} {s : Set α} : s ∉ f ↔ NeBot (f ⊓ 𝓟 sᶜ) :=
(not_congr mem_iff_inf_principal_compl).trans neBot_iff.symm
#align filter.not_mem_iff_inf_principal_compl Filter.not_mem_iff_inf_principal_compl
@[simp]
theorem disjoint_principal_right {f : Filter α} {s : Set α} : Disjoint f (𝓟 s) ↔ sᶜ ∈ f := by
rw [mem_iff_inf_principal_compl, compl_compl, disjoint_iff]
#align filter.disjoint_principal_right Filter.disjoint_principal_right
@[simp]
theorem disjoint_principal_left {f : Filter α} {s : Set α} : Disjoint (𝓟 s) f ↔ sᶜ ∈ f := by
rw [disjoint_comm, disjoint_principal_right]
#align filter.disjoint_principal_left Filter.disjoint_principal_left
@[simp 1100] -- Porting note: higher priority for linter
theorem disjoint_principal_principal {s t : Set α} : Disjoint (𝓟 s) (𝓟 t) ↔ Disjoint s t := by
rw [← subset_compl_iff_disjoint_left, disjoint_principal_left, mem_principal]
#align filter.disjoint_principal_principal Filter.disjoint_principal_principal
alias ⟨_, _root_.Disjoint.filter_principal⟩ := disjoint_principal_principal
#align disjoint.filter_principal Disjoint.filter_principal
@[simp]
theorem disjoint_pure_pure {x y : α} : Disjoint (pure x : Filter α) (pure y) ↔ x ≠ y := by
simp only [← principal_singleton, disjoint_principal_principal, disjoint_singleton]
#align filter.disjoint_pure_pure Filter.disjoint_pure_pure
@[simp]
theorem compl_diagonal_mem_prod {l₁ l₂ : Filter α} : (diagonal α)ᶜ ∈ l₁ ×ˢ l₂ ↔ Disjoint l₁ l₂ := by
simp only [mem_prod_iff, Filter.disjoint_iff, prod_subset_compl_diagonal_iff_disjoint]
#align filter.compl_diagonal_mem_prod Filter.compl_diagonal_mem_prod
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.disjoint_iff_left (h : l.HasBasis p s) :
Disjoint l l' ↔ ∃ i, p i ∧ (s i)ᶜ ∈ l' := by
simp only [h.disjoint_iff l'.basis_sets, id, ← disjoint_principal_left,
(hasBasis_principal _).disjoint_iff l'.basis_sets, true_and, Unique.exists_iff]
#align filter.has_basis.disjoint_iff_left Filter.HasBasis.disjoint_iff_leftₓ
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.disjoint_iff_right (h : l.HasBasis p s) :
Disjoint l' l ↔ ∃ i, p i ∧ (s i)ᶜ ∈ l' :=
disjoint_comm.trans h.disjoint_iff_left
#align filter.has_basis.disjoint_iff_right Filter.HasBasis.disjoint_iff_rightₓ
theorem le_iff_forall_inf_principal_compl {f g : Filter α} : f ≤ g ↔ ∀ V ∈ g, f ⊓ 𝓟 Vᶜ = ⊥ :=
forall₂_congr fun _ _ => mem_iff_inf_principal_compl
#align filter.le_iff_forall_inf_principal_compl Filter.le_iff_forall_inf_principal_compl
theorem inf_neBot_iff_frequently_left {f g : Filter α} :
NeBot (f ⊓ g) ↔ ∀ {p : α → Prop}, (∀ᶠ x in f, p x) → ∃ᶠ x in g, p x := by
simp only [inf_neBot_iff, frequently_iff, and_comm]; rfl
#align filter.inf_ne_bot_iff_frequently_left Filter.inf_neBot_iff_frequently_left
theorem inf_neBot_iff_frequently_right {f g : Filter α} :
NeBot (f ⊓ g) ↔ ∀ {p : α → Prop}, (∀ᶠ x in g, p x) → ∃ᶠ x in f, p x := by
rw [inf_comm]
exact inf_neBot_iff_frequently_left
#align filter.inf_ne_bot_iff_frequently_right Filter.inf_neBot_iff_frequently_right
theorem HasBasis.eq_biInf (h : l.HasBasis p s) : l = ⨅ (i) (_ : p i), 𝓟 (s i) :=
eq_biInf_of_mem_iff_exists_mem fun {_} => by simp only [h.mem_iff, mem_principal, exists_prop]
#align filter.has_basis.eq_binfi Filter.HasBasis.eq_biInf
theorem HasBasis.eq_iInf (h : l.HasBasis (fun _ => True) s) : l = ⨅ i, 𝓟 (s i) := by
simpa only [iInf_true] using h.eq_biInf
#align filter.has_basis.eq_infi Filter.HasBasis.eq_iInf
theorem hasBasis_iInf_principal {s : ι → Set α} (h : Directed (· ≥ ·) s) [Nonempty ι] :
(⨅ i, 𝓟 (s i)).HasBasis (fun _ => True) s :=
⟨fun t => by
simpa only [true_and] using mem_iInf_of_directed (h.mono_comp monotone_principal.dual) t⟩
#align filter.has_basis_infi_principal Filter.hasBasis_iInf_principal
/-- If `s : ι → Set α` is an indexed family of sets, then finite intersections of `s i` form a basis
of `⨅ i, 𝓟 (s i)`. -/
theorem hasBasis_iInf_principal_finite {ι : Type*} (s : ι → Set α) :
(⨅ i, 𝓟 (s i)).HasBasis (fun t : Set ι => t.Finite) fun t => ⋂ i ∈ t, s i := by
refine ⟨fun U => (mem_iInf_finite _).trans ?_⟩
simp only [iInf_principal_finset, mem_iUnion, mem_principal, exists_prop,
exists_finite_iff_finset, Finset.set_biInter_coe]
#align filter.has_basis_infi_principal_finite Filter.hasBasis_iInf_principal_finite
theorem hasBasis_biInf_principal {s : β → Set α} {S : Set β} (h : DirectedOn (s ⁻¹'o (· ≥ ·)) S)
(ne : S.Nonempty) : (⨅ i ∈ S, 𝓟 (s i)).HasBasis (fun i => i ∈ S) s :=
⟨fun t => by
refine mem_biInf_of_directed ?_ ne
rw [directedOn_iff_directed, ← directed_comp] at h ⊢
refine h.mono_comp ?_
exact fun _ _ => principal_mono.2⟩
#align filter.has_basis_binfi_principal Filter.hasBasis_biInf_principal
theorem hasBasis_biInf_principal' {ι : Type*} {p : ι → Prop} {s : ι → Set α}
(h : ∀ i, p i → ∀ j, p j → ∃ k, p k ∧ s k ⊆ s i ∧ s k ⊆ s j) (ne : ∃ i, p i) :
(⨅ (i) (_ : p i), 𝓟 (s i)).HasBasis p s :=
Filter.hasBasis_biInf_principal h ne
#align filter.has_basis_binfi_principal' Filter.hasBasis_biInf_principal'
theorem HasBasis.map (f : α → β) (hl : l.HasBasis p s) : (l.map f).HasBasis p fun i => f '' s i :=
⟨fun t => by simp only [mem_map, image_subset_iff, hl.mem_iff, preimage]⟩
#align filter.has_basis.map Filter.HasBasis.map
theorem HasBasis.comap (f : β → α) (hl : l.HasBasis p s) :
(l.comap f).HasBasis p fun i => f ⁻¹' s i :=
⟨fun t => by
simp only [mem_comap', hl.mem_iff]
refine exists_congr (fun i => Iff.rfl.and ?_)
exact ⟨fun h x hx => h hx rfl, fun h y hy x hx => h <| by rwa [mem_preimage, hx]⟩⟩
#align filter.has_basis.comap Filter.HasBasis.comap
theorem comap_hasBasis (f : α → β) (l : Filter β) :
HasBasis (comap f l) (fun s : Set β => s ∈ l) fun s => f ⁻¹' s :=
⟨fun _ => mem_comap⟩
#align filter.comap_has_basis Filter.comap_hasBasis
theorem HasBasis.forall_mem_mem (h : HasBasis l p s) {x : α} :
(∀ t ∈ l, x ∈ t) ↔ ∀ i, p i → x ∈ s i := by
simp only [h.mem_iff, exists_imp, and_imp]
exact ⟨fun h i hi => h (s i) i hi Subset.rfl, fun h t i hi ht => ht (h i hi)⟩
#align filter.has_basis.forall_mem_mem Filter.HasBasis.forall_mem_mem
protected theorem HasBasis.biInf_mem [CompleteLattice β] {f : Set α → β} (h : HasBasis l p s)
(hf : Monotone f) : ⨅ t ∈ l, f t = ⨅ (i) (_ : p i), f (s i) :=
le_antisymm (le_iInf₂ fun i hi => iInf₂_le (s i) (h.mem_of_mem hi)) <|
le_iInf₂ fun _t ht =>
let ⟨i, hpi, hi⟩ := h.mem_iff.1 ht
iInf₂_le_of_le i hpi (hf hi)
#align filter.has_basis.binfi_mem Filter.HasBasis.biInf_mem
protected theorem HasBasis.biInter_mem {f : Set α → Set β} (h : HasBasis l p s) (hf : Monotone f) :
⋂ t ∈ l, f t = ⋂ (i) (_ : p i), f (s i) :=
h.biInf_mem hf
#align filter.has_basis.bInter_mem Filter.HasBasis.biInter_mem
protected theorem HasBasis.ker (h : HasBasis l p s) : l.ker = ⋂ (i) (_ : p i), s i :=
l.ker_def.trans <| h.biInter_mem monotone_id
#align filter.has_basis.sInter_sets Filter.HasBasis.ker
variable {ι'' : Type*} [Preorder ι''] (l) (s'' : ι'' → Set α)
/-- `IsAntitoneBasis s` means the image of `s` is a filter basis such that `s` is decreasing. -/
structure IsAntitoneBasis extends IsBasis (fun _ => True) s'' : Prop where
/-- The sequence of sets is antitone. -/
protected antitone : Antitone s''
#align filter.is_antitone_basis Filter.IsAntitoneBasis
/-- We say that a filter `l` has an antitone basis `s : ι → Set α`, if `t ∈ l` if and only if `t`
includes `s i` for some `i`, and `s` is decreasing. -/
structure HasAntitoneBasis (l : Filter α) (s : ι'' → Set α)
extends HasBasis l (fun _ => True) s : Prop where
/-- The sequence of sets is antitone. -/
protected antitone : Antitone s
#align filter.has_antitone_basis Filter.HasAntitoneBasis
protected theorem HasAntitoneBasis.map {l : Filter α} {s : ι'' → Set α}
(hf : HasAntitoneBasis l s) (m : α → β) : HasAntitoneBasis (map m l) (m '' s ·) :=
⟨HasBasis.map _ hf.toHasBasis, fun _ _ h => image_subset _ <| hf.2 h⟩
#align filter.has_antitone_basis.map Filter.HasAntitoneBasis.map
protected theorem HasAntitoneBasis.comap {l : Filter α} {s : ι'' → Set α}
(hf : HasAntitoneBasis l s) (m : β → α) : HasAntitoneBasis (comap m l) (m ⁻¹' s ·) :=
⟨hf.1.comap _, fun _ _ h ↦ preimage_mono (hf.2 h)⟩
lemma HasAntitoneBasis.iInf_principal {ι : Type*} [Preorder ι] [Nonempty ι] [IsDirected ι (· ≤ ·)]
{s : ι → Set α} (hs : Antitone s) : (⨅ i, 𝓟 (s i)).HasAntitoneBasis s :=
⟨hasBasis_iInf_principal hs.directed_ge, hs⟩
end SameType
section TwoTypes
variable {la : Filter α} {pa : ι → Prop} {sa : ι → Set α} {lb : Filter β} {pb : ι' → Prop}
{sb : ι' → Set β} {f : α → β}
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.tendsto_left_iff (hla : la.HasBasis pa sa) :
Tendsto f la lb ↔ ∀ t ∈ lb, ∃ i, pa i ∧ MapsTo f (sa i) t := by
simp only [Tendsto, (hla.map f).le_iff, image_subset_iff]
rfl
#align filter.has_basis.tendsto_left_iff Filter.HasBasis.tendsto_left_iffₓ
theorem HasBasis.tendsto_right_iff (hlb : lb.HasBasis pb sb) :
Tendsto f la lb ↔ ∀ i, pb i → ∀ᶠ x in la, f x ∈ sb i := by
simp only [Tendsto, hlb.ge_iff, mem_map', Filter.Eventually]
#align filter.has_basis.tendsto_right_iff Filter.HasBasis.tendsto_right_iff
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem HasBasis.tendsto_iff (hla : la.HasBasis pa sa) (hlb : lb.HasBasis pb sb) :
Tendsto f la lb ↔ ∀ ib, pb ib → ∃ ia, pa ia ∧ ∀ x ∈ sa ia, f x ∈ sb ib := by
simp [hlb.tendsto_right_iff, hla.eventually_iff]
#align filter.has_basis.tendsto_iff Filter.HasBasis.tendsto_iffₓ
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem Tendsto.basis_left (H : Tendsto f la lb) (hla : la.HasBasis pa sa) :
∀ t ∈ lb, ∃ i, pa i ∧ MapsTo f (sa i) t :=
hla.tendsto_left_iff.1 H
#align filter.tendsto.basis_left Filter.Tendsto.basis_leftₓ
theorem Tendsto.basis_right (H : Tendsto f la lb) (hlb : lb.HasBasis pb sb) :
∀ i, pb i → ∀ᶠ x in la, f x ∈ sb i :=
hlb.tendsto_right_iff.1 H
#align filter.tendsto.basis_right Filter.Tendsto.basis_right
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`.
theorem Tendsto.basis_both (H : Tendsto f la lb) (hla : la.HasBasis pa sa)
(hlb : lb.HasBasis pb sb) :
∀ ib, pb ib → ∃ ia, pa ia ∧ MapsTo f (sa ia) (sb ib) :=
(hla.tendsto_iff hlb).1 H
#align filter.tendsto.basis_both Filter.Tendsto.basis_bothₓ
theorem HasBasis.prod_pprod (hla : la.HasBasis pa sa) (hlb : lb.HasBasis pb sb) :
(la ×ˢ lb).HasBasis (fun i : PProd ι ι' => pa i.1 ∧ pb i.2) fun i => sa i.1 ×ˢ sb i.2 :=
(hla.comap Prod.fst).inf' (hlb.comap Prod.snd)
#align filter.has_basis.prod_pprod Filter.HasBasis.prod_pprod
theorem HasBasis.prod {ι ι' : Type*} {pa : ι → Prop} {sa : ι → Set α} {pb : ι' → Prop}
{sb : ι' → Set β} (hla : la.HasBasis pa sa) (hlb : lb.HasBasis pb sb) :
(la ×ˢ lb).HasBasis (fun i : ι × ι' => pa i.1 ∧ pb i.2) fun i => sa i.1 ×ˢ sb i.2 :=
(hla.comap Prod.fst).inf (hlb.comap Prod.snd)
#align filter.has_basis.prod Filter.HasBasis.prod
theorem HasBasis.prod_same_index {p : ι → Prop} {sb : ι → Set β} (hla : la.HasBasis p sa)
(hlb : lb.HasBasis p sb) (h_dir : ∀ {i j}, p i → p j → ∃ k, p k ∧ sa k ⊆ sa i ∧ sb k ⊆ sb j) :
(la ×ˢ lb).HasBasis p fun i => sa i ×ˢ sb i := by
simp only [hasBasis_iff, (hla.prod_pprod hlb).mem_iff]
refine fun t => ⟨?_, ?_⟩
· rintro ⟨⟨i, j⟩, ⟨hi, hj⟩, hsub : sa i ×ˢ sb j ⊆ t⟩
rcases h_dir hi hj with ⟨k, hk, ki, kj⟩
exact ⟨k, hk, (Set.prod_mono ki kj).trans hsub⟩
· rintro ⟨i, hi, h⟩
exact ⟨⟨i, i⟩, ⟨hi, hi⟩, h⟩
#align filter.has_basis.prod_same_index Filter.HasBasis.prod_same_index
theorem HasBasis.prod_same_index_mono {ι : Type*} [LinearOrder ι] {p : ι → Prop} {sa : ι → Set α}
{sb : ι → Set β} (hla : la.HasBasis p sa) (hlb : lb.HasBasis p sb)
(hsa : MonotoneOn sa { i | p i }) (hsb : MonotoneOn sb { i | p i }) :
(la ×ˢ lb).HasBasis p fun i => sa i ×ˢ sb i :=
hla.prod_same_index hlb fun {i j} hi hj =>
have : p (min i j) := min_rec' _ hi hj
⟨min i j, this, hsa this hi <| min_le_left _ _, hsb this hj <| min_le_right _ _⟩
#align filter.has_basis.prod_same_index_mono Filter.HasBasis.prod_same_index_mono
theorem HasBasis.prod_same_index_anti {ι : Type*} [LinearOrder ι] {p : ι → Prop} {sa : ι → Set α}
{sb : ι → Set β} (hla : la.HasBasis p sa) (hlb : lb.HasBasis p sb)
(hsa : AntitoneOn sa { i | p i }) (hsb : AntitoneOn sb { i | p i }) :
(la ×ˢ lb).HasBasis p fun i => sa i ×ˢ sb i :=
@HasBasis.prod_same_index_mono _ _ _ _ ιᵒᵈ _ _ _ _ hla hlb hsa.dual_left hsb.dual_left
#align filter.has_basis.prod_same_index_anti Filter.HasBasis.prod_same_index_anti
theorem HasBasis.prod_self (hl : la.HasBasis pa sa) :
(la ×ˢ la).HasBasis pa fun i => sa i ×ˢ sa i :=
hl.prod_same_index hl fun {i j} hi hj => by
simpa only [exists_prop, subset_inter_iff] using
hl.mem_iff.1 (inter_mem (hl.mem_of_mem hi) (hl.mem_of_mem hj))
#align filter.has_basis.prod_self Filter.HasBasis.prod_self
theorem mem_prod_self_iff {s} : s ∈ la ×ˢ la ↔ ∃ t ∈ la, t ×ˢ t ⊆ s :=
la.basis_sets.prod_self.mem_iff
#align filter.mem_prod_self_iff Filter.mem_prod_self_iff
lemma eventually_prod_self_iff {r : α → α → Prop} :
(∀ᶠ x in la ×ˢ la, r x.1 x.2) ↔ ∃ t ∈ la, ∀ x ∈ t, ∀ y ∈ t, r x y :=
mem_prod_self_iff.trans <| by simp only [prod_subset_iff, mem_setOf_eq]
theorem HasAntitoneBasis.prod {ι : Type*} [LinearOrder ι] {f : Filter α} {g : Filter β}
{s : ι → Set α} {t : ι → Set β} (hf : HasAntitoneBasis f s) (hg : HasAntitoneBasis g t) :
HasAntitoneBasis (f ×ˢ g) fun n => s n ×ˢ t n :=
⟨hf.1.prod_same_index_anti hg.1 (hf.2.antitoneOn _) (hg.2.antitoneOn _), hf.2.set_prod hg.2⟩
#align filter.has_antitone_basis.prod Filter.HasAntitoneBasis.prod
theorem HasBasis.coprod {ι ι' : Type*} {pa : ι → Prop} {sa : ι → Set α} {pb : ι' → Prop}
{sb : ι' → Set β} (hla : la.HasBasis pa sa) (hlb : lb.HasBasis pb sb) :
(la.coprod lb).HasBasis (fun i : ι × ι' => pa i.1 ∧ pb i.2) fun i =>
Prod.fst ⁻¹' sa i.1 ∪ Prod.snd ⁻¹' sb i.2 :=
(hla.comap Prod.fst).sup (hlb.comap Prod.snd)
#align filter.has_basis.coprod Filter.HasBasis.coprod
end TwoTypes
theorem map_sigma_mk_comap {π : α → Type*} {π' : β → Type*} {f : α → β}
(hf : Function.Injective f) (g : ∀ a, π a → π' (f a)) (a : α) (l : Filter (π' (f a))) :
map (Sigma.mk a) (comap (g a) l) = comap (Sigma.map f g) (map (Sigma.mk (f a)) l) := by
refine (((basis_sets _).comap _).map _).eq_of_same_basis ?_
convert ((basis_sets l).map (Sigma.mk (f a))).comap (Sigma.map f g)
apply image_sigmaMk_preimage_sigmaMap hf
#align filter.map_sigma_mk_comap Filter.map_sigma_mk_comap
end Filter
end sort
namespace Filter
variable {α β γ ι : Type*} {ι' : Sort*}
/-- `IsCountablyGenerated f` means `f = generate s` for some countable `s`. -/
class IsCountablyGenerated (f : Filter α) : Prop where
/-- There exists a countable set that generates the filter. -/
out : ∃ s : Set (Set α), s.Countable ∧ f = generate s
#align filter.is_countably_generated Filter.IsCountablyGenerated
/-- `IsCountableBasis p s` means the image of `s` bounded by `p` is a countable filter basis. -/
structure IsCountableBasis (p : ι → Prop) (s : ι → Set α) extends IsBasis p s : Prop where
/-- The set of `i` that satisfy the predicate `p` is countable. -/
countable : (setOf p).Countable
#align filter.is_countable_basis Filter.IsCountableBasis
/-- We say that a filter `l` has a countable basis `s : ι → Set α` bounded by `p : ι → Prop`,
if `t ∈ l` if and only if `t` includes `s i` for some `i` such that `p i`, and the set
defined by `p` is countable. -/
structure HasCountableBasis (l : Filter α) (p : ι → Prop) (s : ι → Set α)
extends HasBasis l p s : Prop where
/-- The set of `i` that satisfy the predicate `p` is countable. -/
countable : (setOf p).Countable
#align filter.has_countable_basis Filter.HasCountableBasis
/-- A countable filter basis `B` on a type `α` is a nonempty countable collection of sets of `α`
such that the intersection of two elements of this collection contains some element
of the collection. -/
structure CountableFilterBasis (α : Type*) extends FilterBasis α where
/-- The set of sets of the filter basis is countable. -/
countable : sets.Countable
#align filter.countable_filter_basis Filter.CountableFilterBasis
-- For illustration purposes, the countable filter basis defining `(atTop : Filter ℕ)`
instance Nat.inhabitedCountableFilterBasis : Inhabited (CountableFilterBasis ℕ) :=
⟨⟨default, countable_range fun n => Ici n⟩⟩
#align filter.nat.inhabited_countable_filter_basis Filter.Nat.inhabitedCountableFilterBasis
theorem HasCountableBasis.isCountablyGenerated {f : Filter α} {p : ι → Prop} {s : ι → Set α}
(h : f.HasCountableBasis p s) : f.IsCountablyGenerated :=
⟨⟨{ t | ∃ i, p i ∧ s i = t }, h.countable.image s, h.toHasBasis.eq_generate⟩⟩
#align filter.has_countable_basis.is_countably_generated Filter.HasCountableBasis.isCountablyGenerated
theorem HasBasis.isCountablyGenerated [Countable ι] {f : Filter α} {p : ι → Prop} {s : ι → Set α}
(h : f.HasBasis p s) : f.IsCountablyGenerated :=
HasCountableBasis.isCountablyGenerated ⟨h, to_countable _⟩
theorem antitone_seq_of_seq (s : ℕ → Set α) :
∃ t : ℕ → Set α, Antitone t ∧ ⨅ i, 𝓟 (s i) = ⨅ i, 𝓟 (t i) := by
use fun n => ⋂ m ≤ n, s m; constructor
· exact fun i j hij => biInter_mono (Iic_subset_Iic.2 hij) fun n _ => Subset.rfl
apply le_antisymm <;> rw [le_iInf_iff] <;> intro i
· rw [le_principal_iff]
refine (biInter_mem (finite_le_nat _)).2 fun j _ => ?_
exact mem_iInf_of_mem j (mem_principal_self _)
· refine iInf_le_of_le i (principal_mono.2 <| iInter₂_subset i ?_)
rfl
#align filter.antitone_seq_of_seq Filter.antitone_seq_of_seq
theorem countable_biInf_eq_iInf_seq [CompleteLattice α] {B : Set ι} (Bcbl : B.Countable)
(Bne : B.Nonempty) (f : ι → α) : ∃ x : ℕ → ι, ⨅ t ∈ B, f t = ⨅ i, f (x i) :=
let ⟨g, hg⟩ := Bcbl.exists_eq_range Bne
⟨g, hg.symm ▸ iInf_range⟩
#align filter.countable_binfi_eq_infi_seq Filter.countable_biInf_eq_iInf_seq
| Mathlib/Order/Filter/Bases.lean | 1,062 | 1,068 | theorem countable_biInf_eq_iInf_seq' [CompleteLattice α] {B : Set ι} (Bcbl : B.Countable)
(f : ι → α) {i₀ : ι} (h : f i₀ = ⊤) : ∃ x : ℕ → ι, ⨅ t ∈ B, f t = ⨅ i, f (x i) := by |
rcases B.eq_empty_or_nonempty with hB | Bnonempty
· rw [hB, iInf_emptyset]
use fun _ => i₀
simp [h]
· exact countable_biInf_eq_iInf_seq Bcbl Bnonempty f
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Manuel Candales
-/
import Mathlib.Analysis.Convex.Between
import Mathlib.Analysis.Normed.Group.AddTorsor
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic
import Mathlib.Analysis.NormedSpace.AffineIsometry
#align_import geometry.euclidean.angle.unoriented.affine from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Angles between points
This file defines unoriented angles in Euclidean affine spaces.
## Main definitions
* `EuclideanGeometry.angle`, with notation `∠`, is the undirected angle determined by three
points.
## TODO
Prove the triangle inequality for the angle.
-/
noncomputable section
open Real RealInnerProductSpace
namespace EuclideanGeometry
open InnerProductGeometry
variable {V P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P]
[NormedAddTorsor V P] {p p₀ p₁ p₂ : P}
/-- The undirected angle at `p2` between the line segments to `p1` and
`p3`. If either of those points equals `p2`, this is π/2. Use
`open scoped EuclideanGeometry` to access the `∠ p1 p2 p3`
notation. -/
nonrec def angle (p1 p2 p3 : P) : ℝ :=
angle (p1 -ᵥ p2 : V) (p3 -ᵥ p2)
#align euclidean_geometry.angle EuclideanGeometry.angle
@[inherit_doc] scoped notation "∠" => EuclideanGeometry.angle
theorem continuousAt_angle {x : P × P × P} (hx12 : x.1 ≠ x.2.1) (hx32 : x.2.2 ≠ x.2.1) :
ContinuousAt (fun y : P × P × P => ∠ y.1 y.2.1 y.2.2) x := by
let f : P × P × P → V × V := fun y => (y.1 -ᵥ y.2.1, y.2.2 -ᵥ y.2.1)
have hf1 : (f x).1 ≠ 0 := by simp [hx12]
have hf2 : (f x).2 ≠ 0 := by simp [hx32]
exact (InnerProductGeometry.continuousAt_angle hf1 hf2).comp
((continuous_fst.vsub continuous_snd.fst).prod_mk
(continuous_snd.snd.vsub continuous_snd.fst)).continuousAt
#align euclidean_geometry.continuous_at_angle EuclideanGeometry.continuousAt_angle
@[simp]
theorem _root_.AffineIsometry.angle_map {V₂ P₂ : Type*} [NormedAddCommGroup V₂]
[InnerProductSpace ℝ V₂] [MetricSpace P₂] [NormedAddTorsor V₂ P₂]
(f : P →ᵃⁱ[ℝ] P₂) (p₁ p₂ p₃ : P) : ∠ (f p₁) (f p₂) (f p₃) = ∠ p₁ p₂ p₃ := by
simp_rw [angle, ← AffineIsometry.map_vsub, LinearIsometry.angle_map]
#align affine_isometry.angle_map AffineIsometry.angle_map
@[simp, norm_cast]
theorem _root_.AffineSubspace.angle_coe {s : AffineSubspace ℝ P} (p₁ p₂ p₃ : s) :
haveI : Nonempty s := ⟨p₁⟩
∠ (p₁ : P) (p₂ : P) (p₃ : P) = ∠ p₁ p₂ p₃ :=
haveI : Nonempty s := ⟨p₁⟩
s.subtypeₐᵢ.angle_map p₁ p₂ p₃
#align affine_subspace.angle_coe AffineSubspace.angle_coe
/-- Angles are translation invariant -/
@[simp]
theorem angle_const_vadd (v : V) (p₁ p₂ p₃ : P) : ∠ (v +ᵥ p₁) (v +ᵥ p₂) (v +ᵥ p₃) = ∠ p₁ p₂ p₃ :=
(AffineIsometryEquiv.constVAdd ℝ P v).toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_const_vadd EuclideanGeometry.angle_const_vadd
/-- Angles are translation invariant -/
@[simp]
theorem angle_vadd_const (v₁ v₂ v₃ : V) (p : P) : ∠ (v₁ +ᵥ p) (v₂ +ᵥ p) (v₃ +ᵥ p) = ∠ v₁ v₂ v₃ :=
(AffineIsometryEquiv.vaddConst ℝ p).toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_vadd_const EuclideanGeometry.angle_vadd_const
/-- Angles are translation invariant -/
@[simp]
theorem angle_const_vsub (p p₁ p₂ p₃ : P) : ∠ (p -ᵥ p₁) (p -ᵥ p₂) (p -ᵥ p₃) = ∠ p₁ p₂ p₃ :=
(AffineIsometryEquiv.constVSub ℝ p).toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_const_vsub EuclideanGeometry.angle_const_vsub
/-- Angles are translation invariant -/
@[simp]
theorem angle_vsub_const (p₁ p₂ p₃ p : P) : ∠ (p₁ -ᵥ p) (p₂ -ᵥ p) (p₃ -ᵥ p) = ∠ p₁ p₂ p₃ :=
(AffineIsometryEquiv.vaddConst ℝ p).symm.toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_vsub_const EuclideanGeometry.angle_vsub_const
/-- Angles in a vector space are translation invariant -/
@[simp]
theorem angle_add_const (v₁ v₂ v₃ : V) (v : V) : ∠ (v₁ + v) (v₂ + v) (v₃ + v) = ∠ v₁ v₂ v₃ :=
angle_vadd_const _ _ _ _
#align euclidean_geometry.angle_add_const EuclideanGeometry.angle_add_const
/-- Angles in a vector space are translation invariant -/
@[simp]
theorem angle_const_add (v : V) (v₁ v₂ v₃ : V) : ∠ (v + v₁) (v + v₂) (v + v₃) = ∠ v₁ v₂ v₃ :=
angle_const_vadd _ _ _ _
#align euclidean_geometry.angle_const_add EuclideanGeometry.angle_const_add
/-- Angles in a vector space are translation invariant -/
@[simp]
theorem angle_sub_const (v₁ v₂ v₃ : V) (v : V) : ∠ (v₁ - v) (v₂ - v) (v₃ - v) = ∠ v₁ v₂ v₃ := by
simpa only [vsub_eq_sub] using angle_vsub_const v₁ v₂ v₃ v
#align euclidean_geometry.angle_sub_const EuclideanGeometry.angle_sub_const
/-- Angles in a vector space are invariant to inversion -/
@[simp]
theorem angle_const_sub (v : V) (v₁ v₂ v₃ : V) : ∠ (v - v₁) (v - v₂) (v - v₃) = ∠ v₁ v₂ v₃ := by
simpa only [vsub_eq_sub] using angle_const_vsub v v₁ v₂ v₃
#align euclidean_geometry.angle_const_sub EuclideanGeometry.angle_const_sub
/-- Angles in a vector space are invariant to inversion -/
@[simp]
theorem angle_neg (v₁ v₂ v₃ : V) : ∠ (-v₁) (-v₂) (-v₃) = ∠ v₁ v₂ v₃ := by
simpa only [zero_sub] using angle_const_sub 0 v₁ v₂ v₃
#align euclidean_geometry.angle_neg EuclideanGeometry.angle_neg
/-- The angle at a point does not depend on the order of the other two
points. -/
nonrec theorem angle_comm (p1 p2 p3 : P) : ∠ p1 p2 p3 = ∠ p3 p2 p1 :=
angle_comm _ _
#align euclidean_geometry.angle_comm EuclideanGeometry.angle_comm
/-- The angle at a point is nonnegative. -/
nonrec theorem angle_nonneg (p1 p2 p3 : P) : 0 ≤ ∠ p1 p2 p3 :=
angle_nonneg _ _
#align euclidean_geometry.angle_nonneg EuclideanGeometry.angle_nonneg
/-- The angle at a point is at most π. -/
nonrec theorem angle_le_pi (p1 p2 p3 : P) : ∠ p1 p2 p3 ≤ π :=
angle_le_pi _ _
#align euclidean_geometry.angle_le_pi EuclideanGeometry.angle_le_pi
/-- The angle ∠AAB at a point is always `π / 2`. -/
@[simp] lemma angle_self_left (p₀ p : P) : ∠ p₀ p₀ p = π / 2 := by
unfold angle
rw [vsub_self]
exact angle_zero_left _
#align euclidean_geometry.angle_eq_left EuclideanGeometry.angle_self_left
/-- The angle ∠ABB at a point is always `π / 2`. -/
@[simp] lemma angle_self_right (p₀ p : P) : ∠ p p₀ p₀ = π / 2 := by rw [angle_comm, angle_self_left]
#align euclidean_geometry.angle_eq_right EuclideanGeometry.angle_self_right
/-- The angle ∠ABA at a point is `0`, unless `A = B`. -/
theorem angle_self_of_ne (h : p ≠ p₀) : ∠ p p₀ p = 0 := angle_self $ vsub_ne_zero.2 h
#align euclidean_geometry.angle_eq_of_ne EuclideanGeometry.angle_self_of_ne
@[deprecated (since := "2024-02-14")] alias angle_eq_left := angle_self_left
@[deprecated (since := "2024-02-14")] alias angle_eq_right := angle_self_right
@[deprecated (since := "2024-02-14")] alias angle_eq_of_ne := angle_self_of_ne
/-- If the angle ∠ABC at a point is π, the angle ∠BAC is 0. -/
theorem angle_eq_zero_of_angle_eq_pi_left {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) : ∠ p2 p1 p3 = 0 := by
unfold angle at h
rw [angle_eq_pi_iff] at h
rcases h with ⟨hp1p2, ⟨r, ⟨hr, hpr⟩⟩⟩
unfold angle
rw [angle_eq_zero_iff]
rw [← neg_vsub_eq_vsub_rev, neg_ne_zero] at hp1p2
use hp1p2, -r + 1, add_pos (neg_pos_of_neg hr) zero_lt_one
rw [add_smul, ← neg_vsub_eq_vsub_rev p1 p2, smul_neg]
simp [← hpr]
#align euclidean_geometry.angle_eq_zero_of_angle_eq_pi_left EuclideanGeometry.angle_eq_zero_of_angle_eq_pi_left
/-- If the angle ∠ABC at a point is π, the angle ∠BCA is 0. -/
theorem angle_eq_zero_of_angle_eq_pi_right {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) :
∠ p2 p3 p1 = 0 := by
rw [angle_comm] at h
exact angle_eq_zero_of_angle_eq_pi_left h
#align euclidean_geometry.angle_eq_zero_of_angle_eq_pi_right EuclideanGeometry.angle_eq_zero_of_angle_eq_pi_right
/-- If ∠BCD = π, then ∠ABC = ∠ABD. -/
theorem angle_eq_angle_of_angle_eq_pi (p1 : P) {p2 p3 p4 : P} (h : ∠ p2 p3 p4 = π) :
∠ p1 p2 p3 = ∠ p1 p2 p4 := by
unfold angle at *
rcases angle_eq_pi_iff.1 h with ⟨_, ⟨r, ⟨hr, hpr⟩⟩⟩
rw [eq_comm]
convert angle_smul_right_of_pos (p1 -ᵥ p2) (p3 -ᵥ p2) (add_pos (neg_pos_of_neg hr) zero_lt_one)
rw [add_smul, ← neg_vsub_eq_vsub_rev p2 p3, smul_neg, neg_smul, ← hpr]
simp
#align euclidean_geometry.angle_eq_angle_of_angle_eq_pi EuclideanGeometry.angle_eq_angle_of_angle_eq_pi
/-- If ∠BCD = π, then ∠ACB + ∠ACD = π. -/
nonrec theorem angle_add_angle_eq_pi_of_angle_eq_pi (p1 : P) {p2 p3 p4 : P} (h : ∠ p2 p3 p4 = π) :
∠ p1 p3 p2 + ∠ p1 p3 p4 = π := by
unfold angle at h
rw [angle_comm p1 p3 p2, angle_comm p1 p3 p4]
unfold angle
exact angle_add_angle_eq_pi_of_angle_eq_pi _ h
#align euclidean_geometry.angle_add_angle_eq_pi_of_angle_eq_pi EuclideanGeometry.angle_add_angle_eq_pi_of_angle_eq_pi
/-- **Vertical Angles Theorem**: angles opposite each other, formed by two intersecting straight
lines, are equal. -/
theorem angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi {p1 p2 p3 p4 p5 : P} (hapc : ∠ p1 p5 p3 = π)
(hbpd : ∠ p2 p5 p4 = π) : ∠ p1 p5 p2 = ∠ p3 p5 p4 := by
linarith [angle_add_angle_eq_pi_of_angle_eq_pi p1 hbpd, angle_comm p4 p5 p1,
angle_add_angle_eq_pi_of_angle_eq_pi p4 hapc, angle_comm p4 p5 p3]
#align euclidean_geometry.angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi EuclideanGeometry.angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi
/-- If ∠ABC = π then dist A B ≠ 0. -/
theorem left_dist_ne_zero_of_angle_eq_pi {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) : dist p1 p2 ≠ 0 := by
by_contra heq
rw [dist_eq_zero] at heq
rw [heq, angle_self_left] at h
exact Real.pi_ne_zero (by linarith)
#align euclidean_geometry.left_dist_ne_zero_of_angle_eq_pi EuclideanGeometry.left_dist_ne_zero_of_angle_eq_pi
/-- If ∠ABC = π then dist C B ≠ 0. -/
theorem right_dist_ne_zero_of_angle_eq_pi {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) : dist p3 p2 ≠ 0 :=
left_dist_ne_zero_of_angle_eq_pi <| (angle_comm _ _ _).trans h
#align euclidean_geometry.right_dist_ne_zero_of_angle_eq_pi EuclideanGeometry.right_dist_ne_zero_of_angle_eq_pi
/-- If ∠ABC = π, then (dist A C) = (dist A B) + (dist B C). -/
theorem dist_eq_add_dist_of_angle_eq_pi {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) :
dist p1 p3 = dist p1 p2 + dist p3 p2 := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact norm_sub_eq_add_norm_of_angle_eq_pi h
#align euclidean_geometry.dist_eq_add_dist_of_angle_eq_pi EuclideanGeometry.dist_eq_add_dist_of_angle_eq_pi
/-- If A ≠ B and C ≠ B then ∠ABC = π if and only if (dist A C) = (dist A B) + (dist B C). -/
theorem dist_eq_add_dist_iff_angle_eq_pi {p1 p2 p3 : P} (hp1p2 : p1 ≠ p2) (hp3p2 : p3 ≠ p2) :
dist p1 p3 = dist p1 p2 + dist p3 p2 ↔ ∠ p1 p2 p3 = π := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact
norm_sub_eq_add_norm_iff_angle_eq_pi (fun he => hp1p2 (vsub_eq_zero_iff_eq.1 he)) fun he =>
hp3p2 (vsub_eq_zero_iff_eq.1 he)
#align euclidean_geometry.dist_eq_add_dist_iff_angle_eq_pi EuclideanGeometry.dist_eq_add_dist_iff_angle_eq_pi
/-- If ∠ABC = 0, then (dist A C) = abs ((dist A B) - (dist B C)). -/
theorem dist_eq_abs_sub_dist_of_angle_eq_zero {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = 0) :
dist p1 p3 = |dist p1 p2 - dist p3 p2| := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact norm_sub_eq_abs_sub_norm_of_angle_eq_zero h
#align euclidean_geometry.dist_eq_abs_sub_dist_of_angle_eq_zero EuclideanGeometry.dist_eq_abs_sub_dist_of_angle_eq_zero
/-- If A ≠ B and C ≠ B then ∠ABC = 0 if and only if (dist A C) = abs ((dist A B) - (dist B C)). -/
| Mathlib/Geometry/Euclidean/Angle/Unoriented/Affine.lean | 249 | 254 | theorem dist_eq_abs_sub_dist_iff_angle_eq_zero {p1 p2 p3 : P} (hp1p2 : p1 ≠ p2) (hp3p2 : p3 ≠ p2) :
dist p1 p3 = |dist p1 p2 - dist p3 p2| ↔ ∠ p1 p2 p3 = 0 := by |
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact
norm_sub_eq_abs_sub_norm_iff_angle_eq_zero (fun he => hp1p2 (vsub_eq_zero_iff_eq.1 he))
fun he => hp3p2 (vsub_eq_zero_iff_eq.1 he)
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen
-/
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.LinearAlgebra.StdBasis
import Mathlib.RingTheory.AlgebraTower
import Mathlib.Algebra.Algebra.Subalgebra.Tower
#align_import linear_algebra.matrix.to_lin from "leanprover-community/mathlib"@"0e2aab2b0d521f060f62a14d2cf2e2c54e8491d6"
/-!
# Linear maps and matrices
This file defines the maps to send matrices to a linear map,
and to send linear maps between modules with a finite bases
to matrices. This defines a linear equivalence between linear maps
between finite-dimensional vector spaces and matrices indexed by
the respective bases.
## Main definitions
In the list below, and in all this file, `R` is a commutative ring (semiring
is sometimes enough), `M` and its variations are `R`-modules, `ι`, `κ`, `n` and `m` are finite
types used for indexing.
* `LinearMap.toMatrix`: given bases `v₁ : ι → M₁` and `v₂ : κ → M₂`,
the `R`-linear equivalence from `M₁ →ₗ[R] M₂` to `Matrix κ ι R`
* `Matrix.toLin`: the inverse of `LinearMap.toMatrix`
* `LinearMap.toMatrix'`: the `R`-linear equivalence from `(m → R) →ₗ[R] (n → R)`
to `Matrix m n R` (with the standard basis on `m → R` and `n → R`)
* `Matrix.toLin'`: the inverse of `LinearMap.toMatrix'`
* `algEquivMatrix`: given a basis indexed by `n`, the `R`-algebra equivalence between
`R`-endomorphisms of `M` and `Matrix n n R`
## Issues
This file was originally written without attention to non-commutative rings,
and so mostly only works in the commutative setting. This should be fixed.
In particular, `Matrix.mulVec` gives us a linear equivalence
`Matrix m n R ≃ₗ[R] (n → R) →ₗ[Rᵐᵒᵖ] (m → R)`
while `Matrix.vecMul` gives us a linear equivalence
`Matrix m n R ≃ₗ[Rᵐᵒᵖ] (m → R) →ₗ[R] (n → R)`.
At present, the first equivalence is developed in detail but only for commutative rings
(and we omit the distinction between `Rᵐᵒᵖ` and `R`),
while the second equivalence is developed only in brief, but for not-necessarily-commutative rings.
Naming is slightly inconsistent between the two developments.
In the original (commutative) development `linear` is abbreviated to `lin`,
although this is not consistent with the rest of mathlib.
In the new (non-commutative) development `linear` is not abbreviated, and declarations use `_right`
to indicate they use the right action of matrices on vectors (via `Matrix.vecMul`).
When the two developments are made uniform, the names should be made uniform, too,
by choosing between `linear` and `lin` consistently,
and (presumably) adding `_left` where necessary.
## Tags
linear_map, matrix, linear_equiv, diagonal, det, trace
-/
noncomputable section
open LinearMap Matrix Set Submodule
section ToMatrixRight
variable {R : Type*} [Semiring R]
variable {l m n : Type*}
/-- `Matrix.vecMul M` is a linear map. -/
def Matrix.vecMulLinear [Fintype m] (M : Matrix m n R) : (m → R) →ₗ[R] n → R where
toFun x := x ᵥ* M
map_add' _ _ := funext fun _ ↦ add_dotProduct _ _ _
map_smul' _ _ := funext fun _ ↦ smul_dotProduct _ _ _
#align matrix.vec_mul_linear Matrix.vecMulLinear
@[simp] theorem Matrix.vecMulLinear_apply [Fintype m] (M : Matrix m n R) (x : m → R) :
M.vecMulLinear x = x ᵥ* M := rfl
theorem Matrix.coe_vecMulLinear [Fintype m] (M : Matrix m n R) :
(M.vecMulLinear : _ → _) = M.vecMul := rfl
variable [Fintype m] [DecidableEq m]
@[simp]
theorem Matrix.vecMul_stdBasis (M : Matrix m n R) (i j) :
(LinearMap.stdBasis R (fun _ ↦ R) i 1 ᵥ* M) j = M i j := by
have : (∑ i', (if i = i' then 1 else 0) * M i' j) = M i j := by
simp_rw [boole_mul, Finset.sum_ite_eq, Finset.mem_univ, if_true]
simp only [vecMul, dotProduct]
convert this
split_ifs with h <;> simp only [stdBasis_apply]
· rw [h, Function.update_same]
· rw [Function.update_noteq (Ne.symm h), Pi.zero_apply]
#align matrix.vec_mul_std_basis Matrix.vecMul_stdBasis
theorem range_vecMulLinear (M : Matrix m n R) :
LinearMap.range M.vecMulLinear = span R (range M) := by
letI := Classical.decEq m
simp_rw [range_eq_map, ← iSup_range_stdBasis, Submodule.map_iSup, range_eq_map, ←
Ideal.span_singleton_one, Ideal.span, Submodule.map_span, image_image, image_singleton,
Matrix.vecMulLinear_apply, iSup_span, range_eq_iUnion, iUnion_singleton_eq_range,
LinearMap.stdBasis, coe_single]
unfold vecMul
simp_rw [single_dotProduct, one_mul]
theorem Matrix.vecMul_injective_iff {R : Type*} [CommRing R] {M : Matrix m n R} :
Function.Injective M.vecMul ↔ LinearIndependent R (fun i ↦ M i) := by
rw [← coe_vecMulLinear]
simp only [← LinearMap.ker_eq_bot, Fintype.linearIndependent_iff, Submodule.eq_bot_iff,
LinearMap.mem_ker, vecMulLinear_apply]
refine ⟨fun h c h0 ↦ congr_fun <| h c ?_, fun h c h0 ↦ funext <| h c ?_⟩
· rw [← h0]
ext i
simp [vecMul, dotProduct]
· rw [← h0]
ext j
simp [vecMul, dotProduct]
/-- Linear maps `(m → R) →ₗ[R] (n → R)` are linearly equivalent over `Rᵐᵒᵖ` to `Matrix m n R`,
by having matrices act by right multiplication.
-/
def LinearMap.toMatrixRight' : ((m → R) →ₗ[R] n → R) ≃ₗ[Rᵐᵒᵖ] Matrix m n R where
toFun f i j := f (stdBasis R (fun _ ↦ R) i 1) j
invFun := Matrix.vecMulLinear
right_inv M := by
ext i j
simp only [Matrix.vecMul_stdBasis, Matrix.vecMulLinear_apply]
left_inv f := by
apply (Pi.basisFun R m).ext
intro j; ext i
simp only [Pi.basisFun_apply, Matrix.vecMul_stdBasis, Matrix.vecMulLinear_apply]
map_add' f g := by
ext i j
simp only [Pi.add_apply, LinearMap.add_apply, Matrix.add_apply]
map_smul' c f := by
ext i j
simp only [Pi.smul_apply, LinearMap.smul_apply, RingHom.id_apply, Matrix.smul_apply]
#align linear_map.to_matrix_right' LinearMap.toMatrixRight'
/-- A `Matrix m n R` is linearly equivalent over `Rᵐᵒᵖ` to a linear map `(m → R) →ₗ[R] (n → R)`,
by having matrices act by right multiplication. -/
abbrev Matrix.toLinearMapRight' : Matrix m n R ≃ₗ[Rᵐᵒᵖ] (m → R) →ₗ[R] n → R :=
LinearEquiv.symm LinearMap.toMatrixRight'
#align matrix.to_linear_map_right' Matrix.toLinearMapRight'
@[simp]
theorem Matrix.toLinearMapRight'_apply (M : Matrix m n R) (v : m → R) :
(Matrix.toLinearMapRight') M v = v ᵥ* M := rfl
#align matrix.to_linear_map_right'_apply Matrix.toLinearMapRight'_apply
@[simp]
theorem Matrix.toLinearMapRight'_mul [Fintype l] [DecidableEq l] (M : Matrix l m R)
(N : Matrix m n R) :
Matrix.toLinearMapRight' (M * N) =
(Matrix.toLinearMapRight' N).comp (Matrix.toLinearMapRight' M) :=
LinearMap.ext fun _x ↦ (vecMul_vecMul _ M N).symm
#align matrix.to_linear_map_right'_mul Matrix.toLinearMapRight'_mul
theorem Matrix.toLinearMapRight'_mul_apply [Fintype l] [DecidableEq l] (M : Matrix l m R)
(N : Matrix m n R) (x) :
Matrix.toLinearMapRight' (M * N) x =
Matrix.toLinearMapRight' N (Matrix.toLinearMapRight' M x) :=
(vecMul_vecMul _ M N).symm
#align matrix.to_linear_map_right'_mul_apply Matrix.toLinearMapRight'_mul_apply
@[simp]
theorem Matrix.toLinearMapRight'_one :
Matrix.toLinearMapRight' (1 : Matrix m m R) = LinearMap.id := by
ext
simp [LinearMap.one_apply, stdBasis_apply]
#align matrix.to_linear_map_right'_one Matrix.toLinearMapRight'_one
/-- If `M` and `M'` are each other's inverse matrices, they provide an equivalence between `n → A`
and `m → A` corresponding to `M.vecMul` and `M'.vecMul`. -/
@[simps]
def Matrix.toLinearEquivRight'OfInv [Fintype n] [DecidableEq n] {M : Matrix m n R}
{M' : Matrix n m R} (hMM' : M * M' = 1) (hM'M : M' * M = 1) : (n → R) ≃ₗ[R] m → R :=
{ LinearMap.toMatrixRight'.symm M' with
toFun := Matrix.toLinearMapRight' M'
invFun := Matrix.toLinearMapRight' M
left_inv := fun x ↦ by
rw [← Matrix.toLinearMapRight'_mul_apply, hM'M, Matrix.toLinearMapRight'_one, id_apply]
right_inv := fun x ↦ by
dsimp only -- Porting note: needed due to non-flat structures
rw [← Matrix.toLinearMapRight'_mul_apply, hMM', Matrix.toLinearMapRight'_one, id_apply] }
#align matrix.to_linear_equiv_right'_of_inv Matrix.toLinearEquivRight'OfInv
end ToMatrixRight
/-!
From this point on, we only work with commutative rings,
and fail to distinguish between `Rᵐᵒᵖ` and `R`.
This should eventually be remedied.
-/
section mulVec
variable {R : Type*} [CommSemiring R]
variable {k l m n : Type*}
/-- `Matrix.mulVec M` is a linear map. -/
def Matrix.mulVecLin [Fintype n] (M : Matrix m n R) : (n → R) →ₗ[R] m → R where
toFun := M.mulVec
map_add' _ _ := funext fun _ ↦ dotProduct_add _ _ _
map_smul' _ _ := funext fun _ ↦ dotProduct_smul _ _ _
#align matrix.mul_vec_lin Matrix.mulVecLin
theorem Matrix.coe_mulVecLin [Fintype n] (M : Matrix m n R) :
(M.mulVecLin : _ → _) = M.mulVec := rfl
@[simp]
theorem Matrix.mulVecLin_apply [Fintype n] (M : Matrix m n R) (v : n → R) :
M.mulVecLin v = M *ᵥ v :=
rfl
#align matrix.mul_vec_lin_apply Matrix.mulVecLin_apply
@[simp]
theorem Matrix.mulVecLin_zero [Fintype n] : Matrix.mulVecLin (0 : Matrix m n R) = 0 :=
LinearMap.ext zero_mulVec
#align matrix.mul_vec_lin_zero Matrix.mulVecLin_zero
@[simp]
theorem Matrix.mulVecLin_add [Fintype n] (M N : Matrix m n R) :
(M + N).mulVecLin = M.mulVecLin + N.mulVecLin :=
LinearMap.ext fun _ ↦ add_mulVec _ _ _
#align matrix.mul_vec_lin_add Matrix.mulVecLin_add
@[simp] theorem Matrix.mulVecLin_transpose [Fintype m] (M : Matrix m n R) :
Mᵀ.mulVecLin = M.vecMulLinear := by
ext; simp [mulVec_transpose]
@[simp] theorem Matrix.vecMulLinear_transpose [Fintype n] (M : Matrix m n R) :
Mᵀ.vecMulLinear = M.mulVecLin := by
ext; simp [vecMul_transpose]
theorem Matrix.mulVecLin_submatrix [Fintype n] [Fintype l] (f₁ : m → k) (e₂ : n ≃ l)
(M : Matrix k l R) :
(M.submatrix f₁ e₂).mulVecLin = funLeft R R f₁ ∘ₗ M.mulVecLin ∘ₗ funLeft _ _ e₂.symm :=
LinearMap.ext fun _ ↦ submatrix_mulVec_equiv _ _ _ _
#align matrix.mul_vec_lin_submatrix Matrix.mulVecLin_submatrix
/-- A variant of `Matrix.mulVecLin_submatrix` that keeps around `LinearEquiv`s. -/
theorem Matrix.mulVecLin_reindex [Fintype n] [Fintype l] (e₁ : k ≃ m) (e₂ : l ≃ n)
(M : Matrix k l R) :
(reindex e₁ e₂ M).mulVecLin =
↑(LinearEquiv.funCongrLeft R R e₁.symm) ∘ₗ
M.mulVecLin ∘ₗ ↑(LinearEquiv.funCongrLeft R R e₂) :=
Matrix.mulVecLin_submatrix _ _ _
#align matrix.mul_vec_lin_reindex Matrix.mulVecLin_reindex
variable [Fintype n]
@[simp]
theorem Matrix.mulVecLin_one [DecidableEq n] :
Matrix.mulVecLin (1 : Matrix n n R) = LinearMap.id := by
ext; simp [Matrix.one_apply, Pi.single_apply]
#align matrix.mul_vec_lin_one Matrix.mulVecLin_one
@[simp]
theorem Matrix.mulVecLin_mul [Fintype m] (M : Matrix l m R) (N : Matrix m n R) :
Matrix.mulVecLin (M * N) = (Matrix.mulVecLin M).comp (Matrix.mulVecLin N) :=
LinearMap.ext fun _ ↦ (mulVec_mulVec _ _ _).symm
#align matrix.mul_vec_lin_mul Matrix.mulVecLin_mul
theorem Matrix.ker_mulVecLin_eq_bot_iff {M : Matrix m n R} :
(LinearMap.ker M.mulVecLin) = ⊥ ↔ ∀ v, M *ᵥ v = 0 → v = 0 := by
simp only [Submodule.eq_bot_iff, LinearMap.mem_ker, Matrix.mulVecLin_apply]
#align matrix.ker_mul_vec_lin_eq_bot_iff Matrix.ker_mulVecLin_eq_bot_iff
theorem Matrix.mulVec_stdBasis [DecidableEq n] (M : Matrix m n R) (i j) :
(M *ᵥ LinearMap.stdBasis R (fun _ ↦ R) j 1) i = M i j :=
(congr_fun (Matrix.mulVec_single _ _ (1 : R)) i).trans <| mul_one _
#align matrix.mul_vec_std_basis Matrix.mulVec_stdBasis
@[simp]
theorem Matrix.mulVec_stdBasis_apply [DecidableEq n] (M : Matrix m n R) (j) :
M *ᵥ LinearMap.stdBasis R (fun _ ↦ R) j 1 = Mᵀ j :=
funext fun i ↦ Matrix.mulVec_stdBasis M i j
#align matrix.mul_vec_std_basis_apply Matrix.mulVec_stdBasis_apply
theorem Matrix.range_mulVecLin (M : Matrix m n R) :
LinearMap.range M.mulVecLin = span R (range Mᵀ) := by
rw [← vecMulLinear_transpose, range_vecMulLinear]
#align matrix.range_mul_vec_lin Matrix.range_mulVecLin
theorem Matrix.mulVec_injective_iff {R : Type*} [CommRing R] {M : Matrix m n R} :
Function.Injective M.mulVec ↔ LinearIndependent R (fun i ↦ Mᵀ i) := by
change Function.Injective (fun x ↦ _) ↔ _
simp_rw [← M.vecMul_transpose, vecMul_injective_iff]
end mulVec
section ToMatrix'
variable {R : Type*} [CommSemiring R]
variable {k l m n : Type*} [DecidableEq n] [Fintype n]
/-- Linear maps `(n → R) →ₗ[R] (m → R)` are linearly equivalent to `Matrix m n R`. -/
def LinearMap.toMatrix' : ((n → R) →ₗ[R] m → R) ≃ₗ[R] Matrix m n R where
toFun f := of fun i j ↦ f (stdBasis R (fun _ ↦ R) j 1) i
invFun := Matrix.mulVecLin
right_inv M := by
ext i j
simp only [Matrix.mulVec_stdBasis, Matrix.mulVecLin_apply, of_apply]
left_inv f := by
apply (Pi.basisFun R n).ext
intro j; ext i
simp only [Pi.basisFun_apply, Matrix.mulVec_stdBasis, Matrix.mulVecLin_apply, of_apply]
map_add' f g := by
ext i j
simp only [Pi.add_apply, LinearMap.add_apply, of_apply, Matrix.add_apply]
map_smul' c f := by
ext i j
simp only [Pi.smul_apply, LinearMap.smul_apply, RingHom.id_apply, of_apply, Matrix.smul_apply]
#align linear_map.to_matrix' LinearMap.toMatrix'
/-- A `Matrix m n R` is linearly equivalent to a linear map `(n → R) →ₗ[R] (m → R)`.
Note that the forward-direction does not require `DecidableEq` and is `Matrix.vecMulLin`. -/
def Matrix.toLin' : Matrix m n R ≃ₗ[R] (n → R) →ₗ[R] m → R :=
LinearMap.toMatrix'.symm
#align matrix.to_lin' Matrix.toLin'
theorem Matrix.toLin'_apply' (M : Matrix m n R) : Matrix.toLin' M = M.mulVecLin :=
rfl
#align matrix.to_lin'_apply' Matrix.toLin'_apply'
@[simp]
theorem LinearMap.toMatrix'_symm :
(LinearMap.toMatrix'.symm : Matrix m n R ≃ₗ[R] _) = Matrix.toLin' :=
rfl
#align linear_map.to_matrix'_symm LinearMap.toMatrix'_symm
@[simp]
theorem Matrix.toLin'_symm :
(Matrix.toLin'.symm : ((n → R) →ₗ[R] m → R) ≃ₗ[R] _) = LinearMap.toMatrix' :=
rfl
#align matrix.to_lin'_symm Matrix.toLin'_symm
@[simp]
theorem LinearMap.toMatrix'_toLin' (M : Matrix m n R) : LinearMap.toMatrix' (Matrix.toLin' M) = M :=
LinearMap.toMatrix'.apply_symm_apply M
#align linear_map.to_matrix'_to_lin' LinearMap.toMatrix'_toLin'
@[simp]
theorem Matrix.toLin'_toMatrix' (f : (n → R) →ₗ[R] m → R) :
Matrix.toLin' (LinearMap.toMatrix' f) = f :=
Matrix.toLin'.apply_symm_apply f
#align matrix.to_lin'_to_matrix' Matrix.toLin'_toMatrix'
@[simp]
theorem LinearMap.toMatrix'_apply (f : (n → R) →ₗ[R] m → R) (i j) :
LinearMap.toMatrix' f i j = f (fun j' ↦ if j' = j then 1 else 0) i := by
simp only [LinearMap.toMatrix', LinearEquiv.coe_mk, of_apply]
refine congr_fun ?_ _ -- Porting note: `congr` didn't do this
congr
ext j'
split_ifs with h
· rw [h, stdBasis_same]
apply stdBasis_ne _ _ _ _ h
#align linear_map.to_matrix'_apply LinearMap.toMatrix'_apply
@[simp]
theorem Matrix.toLin'_apply (M : Matrix m n R) (v : n → R) : Matrix.toLin' M v = M *ᵥ v :=
rfl
#align matrix.to_lin'_apply Matrix.toLin'_apply
@[simp]
theorem Matrix.toLin'_one : Matrix.toLin' (1 : Matrix n n R) = LinearMap.id :=
Matrix.mulVecLin_one
#align matrix.to_lin'_one Matrix.toLin'_one
@[simp]
theorem LinearMap.toMatrix'_id : LinearMap.toMatrix' (LinearMap.id : (n → R) →ₗ[R] n → R) = 1 := by
ext
rw [Matrix.one_apply, LinearMap.toMatrix'_apply, id_apply]
#align linear_map.to_matrix'_id LinearMap.toMatrix'_id
@[simp]
theorem LinearMap.toMatrix'_one : LinearMap.toMatrix' (1 : (n → R) →ₗ[R] n → R) = 1 :=
LinearMap.toMatrix'_id
@[simp]
theorem Matrix.toLin'_mul [Fintype m] [DecidableEq m] (M : Matrix l m R) (N : Matrix m n R) :
Matrix.toLin' (M * N) = (Matrix.toLin' M).comp (Matrix.toLin' N) :=
Matrix.mulVecLin_mul _ _
#align matrix.to_lin'_mul Matrix.toLin'_mul
@[simp]
theorem Matrix.toLin'_submatrix [Fintype l] [DecidableEq l] (f₁ : m → k) (e₂ : n ≃ l)
(M : Matrix k l R) :
Matrix.toLin' (M.submatrix f₁ e₂) =
funLeft R R f₁ ∘ₗ (Matrix.toLin' M) ∘ₗ funLeft _ _ e₂.symm :=
Matrix.mulVecLin_submatrix _ _ _
#align matrix.to_lin'_submatrix Matrix.toLin'_submatrix
/-- A variant of `Matrix.toLin'_submatrix` that keeps around `LinearEquiv`s. -/
theorem Matrix.toLin'_reindex [Fintype l] [DecidableEq l] (e₁ : k ≃ m) (e₂ : l ≃ n)
(M : Matrix k l R) :
Matrix.toLin' (reindex e₁ e₂ M) =
↑(LinearEquiv.funCongrLeft R R e₁.symm) ∘ₗ (Matrix.toLin' M) ∘ₗ
↑(LinearEquiv.funCongrLeft R R e₂) :=
Matrix.mulVecLin_reindex _ _ _
#align matrix.to_lin'_reindex Matrix.toLin'_reindex
/-- Shortcut lemma for `Matrix.toLin'_mul` and `LinearMap.comp_apply` -/
theorem Matrix.toLin'_mul_apply [Fintype m] [DecidableEq m] (M : Matrix l m R) (N : Matrix m n R)
(x) : Matrix.toLin' (M * N) x = Matrix.toLin' M (Matrix.toLin' N x) := by
rw [Matrix.toLin'_mul, LinearMap.comp_apply]
#align matrix.to_lin'_mul_apply Matrix.toLin'_mul_apply
theorem LinearMap.toMatrix'_comp [Fintype l] [DecidableEq l] (f : (n → R) →ₗ[R] m → R)
(g : (l → R) →ₗ[R] n → R) :
LinearMap.toMatrix' (f.comp g) = LinearMap.toMatrix' f * LinearMap.toMatrix' g := by
suffices f.comp g = Matrix.toLin' (LinearMap.toMatrix' f * LinearMap.toMatrix' g) by
rw [this, LinearMap.toMatrix'_toLin']
rw [Matrix.toLin'_mul, Matrix.toLin'_toMatrix', Matrix.toLin'_toMatrix']
#align linear_map.to_matrix'_comp LinearMap.toMatrix'_comp
theorem LinearMap.toMatrix'_mul [Fintype m] [DecidableEq m] (f g : (m → R) →ₗ[R] m → R) :
LinearMap.toMatrix' (f * g) = LinearMap.toMatrix' f * LinearMap.toMatrix' g :=
LinearMap.toMatrix'_comp f g
#align linear_map.to_matrix'_mul LinearMap.toMatrix'_mul
@[simp]
theorem LinearMap.toMatrix'_algebraMap (x : R) :
LinearMap.toMatrix' (algebraMap R (Module.End R (n → R)) x) = scalar n x := by
simp [Module.algebraMap_end_eq_smul_id, smul_eq_diagonal_mul]
#align linear_map.to_matrix'_algebra_map LinearMap.toMatrix'_algebraMap
theorem Matrix.ker_toLin'_eq_bot_iff {M : Matrix n n R} :
LinearMap.ker (Matrix.toLin' M) = ⊥ ↔ ∀ v, M *ᵥ v = 0 → v = 0 :=
Matrix.ker_mulVecLin_eq_bot_iff
#align matrix.ker_to_lin'_eq_bot_iff Matrix.ker_toLin'_eq_bot_iff
theorem Matrix.range_toLin' (M : Matrix m n R) :
LinearMap.range (Matrix.toLin' M) = span R (range Mᵀ) :=
Matrix.range_mulVecLin _
#align matrix.range_to_lin' Matrix.range_toLin'
/-- If `M` and `M'` are each other's inverse matrices, they provide an equivalence between `m → A`
and `n → A` corresponding to `M.mulVec` and `M'.mulVec`. -/
@[simps]
def Matrix.toLin'OfInv [Fintype m] [DecidableEq m] {M : Matrix m n R} {M' : Matrix n m R}
(hMM' : M * M' = 1) (hM'M : M' * M = 1) : (m → R) ≃ₗ[R] n → R :=
{ Matrix.toLin' M' with
toFun := Matrix.toLin' M'
invFun := Matrix.toLin' M
left_inv := fun x ↦ by rw [← Matrix.toLin'_mul_apply, hMM', Matrix.toLin'_one, id_apply]
right_inv := fun x ↦ by
simp only
rw [← Matrix.toLin'_mul_apply, hM'M, Matrix.toLin'_one, id_apply] }
#align matrix.to_lin'_of_inv Matrix.toLin'OfInv
/-- Linear maps `(n → R) →ₗ[R] (n → R)` are algebra equivalent to `Matrix n n R`. -/
def LinearMap.toMatrixAlgEquiv' : ((n → R) →ₗ[R] n → R) ≃ₐ[R] Matrix n n R :=
AlgEquiv.ofLinearEquiv LinearMap.toMatrix' LinearMap.toMatrix'_one LinearMap.toMatrix'_mul
#align linear_map.to_matrix_alg_equiv' LinearMap.toMatrixAlgEquiv'
/-- A `Matrix n n R` is algebra equivalent to a linear map `(n → R) →ₗ[R] (n → R)`. -/
def Matrix.toLinAlgEquiv' : Matrix n n R ≃ₐ[R] (n → R) →ₗ[R] n → R :=
LinearMap.toMatrixAlgEquiv'.symm
#align matrix.to_lin_alg_equiv' Matrix.toLinAlgEquiv'
@[simp]
theorem LinearMap.toMatrixAlgEquiv'_symm :
(LinearMap.toMatrixAlgEquiv'.symm : Matrix n n R ≃ₐ[R] _) = Matrix.toLinAlgEquiv' :=
rfl
#align linear_map.to_matrix_alg_equiv'_symm LinearMap.toMatrixAlgEquiv'_symm
@[simp]
theorem Matrix.toLinAlgEquiv'_symm :
(Matrix.toLinAlgEquiv'.symm : ((n → R) →ₗ[R] n → R) ≃ₐ[R] _) = LinearMap.toMatrixAlgEquiv' :=
rfl
#align matrix.to_lin_alg_equiv'_symm Matrix.toLinAlgEquiv'_symm
@[simp]
theorem LinearMap.toMatrixAlgEquiv'_toLinAlgEquiv' (M : Matrix n n R) :
LinearMap.toMatrixAlgEquiv' (Matrix.toLinAlgEquiv' M) = M :=
LinearMap.toMatrixAlgEquiv'.apply_symm_apply M
#align linear_map.to_matrix_alg_equiv'_to_lin_alg_equiv' LinearMap.toMatrixAlgEquiv'_toLinAlgEquiv'
@[simp]
theorem Matrix.toLinAlgEquiv'_toMatrixAlgEquiv' (f : (n → R) →ₗ[R] n → R) :
Matrix.toLinAlgEquiv' (LinearMap.toMatrixAlgEquiv' f) = f :=
Matrix.toLinAlgEquiv'.apply_symm_apply f
#align matrix.to_lin_alg_equiv'_to_matrix_alg_equiv' Matrix.toLinAlgEquiv'_toMatrixAlgEquiv'
@[simp]
theorem LinearMap.toMatrixAlgEquiv'_apply (f : (n → R) →ₗ[R] n → R) (i j) :
LinearMap.toMatrixAlgEquiv' f i j = f (fun j' ↦ if j' = j then 1 else 0) i := by
simp [LinearMap.toMatrixAlgEquiv']
#align linear_map.to_matrix_alg_equiv'_apply LinearMap.toMatrixAlgEquiv'_apply
@[simp]
theorem Matrix.toLinAlgEquiv'_apply (M : Matrix n n R) (v : n → R) :
Matrix.toLinAlgEquiv' M v = M *ᵥ v :=
rfl
#align matrix.to_lin_alg_equiv'_apply Matrix.toLinAlgEquiv'_apply
-- Porting note: the simpNF linter rejects this, as `simp` already simplifies the lhs
-- to `(1 : (n → R) →ₗ[R] n → R)`.
-- @[simp]
theorem Matrix.toLinAlgEquiv'_one : Matrix.toLinAlgEquiv' (1 : Matrix n n R) = LinearMap.id :=
Matrix.toLin'_one
#align matrix.to_lin_alg_equiv'_one Matrix.toLinAlgEquiv'_one
@[simp]
theorem LinearMap.toMatrixAlgEquiv'_id :
LinearMap.toMatrixAlgEquiv' (LinearMap.id : (n → R) →ₗ[R] n → R) = 1 :=
LinearMap.toMatrix'_id
#align linear_map.to_matrix_alg_equiv'_id LinearMap.toMatrixAlgEquiv'_id
#align matrix.to_lin_alg_equiv'_mul map_mulₓ
theorem LinearMap.toMatrixAlgEquiv'_comp (f g : (n → R) →ₗ[R] n → R) :
LinearMap.toMatrixAlgEquiv' (f.comp g) =
LinearMap.toMatrixAlgEquiv' f * LinearMap.toMatrixAlgEquiv' g :=
LinearMap.toMatrix'_comp _ _
#align linear_map.to_matrix_alg_equiv'_comp LinearMap.toMatrixAlgEquiv'_comp
theorem LinearMap.toMatrixAlgEquiv'_mul (f g : (n → R) →ₗ[R] n → R) :
LinearMap.toMatrixAlgEquiv' (f * g) =
LinearMap.toMatrixAlgEquiv' f * LinearMap.toMatrixAlgEquiv' g :=
LinearMap.toMatrixAlgEquiv'_comp f g
#align linear_map.to_matrix_alg_equiv'_mul LinearMap.toMatrixAlgEquiv'_mul
end ToMatrix'
section ToMatrix
section Finite
variable {R : Type*} [CommSemiring R]
variable {l m n : Type*} [Fintype n] [Finite m] [DecidableEq n]
variable {M₁ M₂ : Type*} [AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁] [Module R M₂]
variable (v₁ : Basis n R M₁) (v₂ : Basis m R M₂)
/-- Given bases of two modules `M₁` and `M₂` over a commutative ring `R`, we get a linear
equivalence between linear maps `M₁ →ₗ M₂` and matrices over `R` indexed by the bases. -/
def LinearMap.toMatrix : (M₁ →ₗ[R] M₂) ≃ₗ[R] Matrix m n R :=
LinearEquiv.trans (LinearEquiv.arrowCongr v₁.equivFun v₂.equivFun) LinearMap.toMatrix'
#align linear_map.to_matrix LinearMap.toMatrix
/-- `LinearMap.toMatrix'` is a particular case of `LinearMap.toMatrix`, for the standard basis
`Pi.basisFun R n`. -/
theorem LinearMap.toMatrix_eq_toMatrix' :
LinearMap.toMatrix (Pi.basisFun R n) (Pi.basisFun R n) = LinearMap.toMatrix' :=
rfl
#align linear_map.to_matrix_eq_to_matrix' LinearMap.toMatrix_eq_toMatrix'
/-- Given bases of two modules `M₁` and `M₂` over a commutative ring `R`, we get a linear
equivalence between matrices over `R` indexed by the bases and linear maps `M₁ →ₗ M₂`. -/
def Matrix.toLin : Matrix m n R ≃ₗ[R] M₁ →ₗ[R] M₂ :=
(LinearMap.toMatrix v₁ v₂).symm
#align matrix.to_lin Matrix.toLin
/-- `Matrix.toLin'` is a particular case of `Matrix.toLin`, for the standard basis
`Pi.basisFun R n`. -/
theorem Matrix.toLin_eq_toLin' : Matrix.toLin (Pi.basisFun R n) (Pi.basisFun R m) = Matrix.toLin' :=
rfl
#align matrix.to_lin_eq_to_lin' Matrix.toLin_eq_toLin'
@[simp]
theorem LinearMap.toMatrix_symm : (LinearMap.toMatrix v₁ v₂).symm = Matrix.toLin v₁ v₂ :=
rfl
#align linear_map.to_matrix_symm LinearMap.toMatrix_symm
@[simp]
theorem Matrix.toLin_symm : (Matrix.toLin v₁ v₂).symm = LinearMap.toMatrix v₁ v₂ :=
rfl
#align matrix.to_lin_symm Matrix.toLin_symm
@[simp]
| Mathlib/LinearAlgebra/Matrix/ToLin.lean | 582 | 584 | theorem Matrix.toLin_toMatrix (f : M₁ →ₗ[R] M₂) :
Matrix.toLin v₁ v₂ (LinearMap.toMatrix v₁ v₂ f) = f := by |
rw [← Matrix.toLin_symm, LinearEquiv.apply_symm_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.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]
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 922 | 928 | 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⟩
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Jeremy Avigad, Simon Hudon
-/
import Mathlib.Data.Set.Subsingleton
import Mathlib.Logic.Equiv.Defs
import Mathlib.Algebra.Group.Defs
#align_import data.part from "leanprover-community/mathlib"@"80c43012d26f63026d362c3aba28f3c3bafb07e6"
/-!
# Partial values of a type
This file defines `Part α`, the partial values of a type.
`o : Part α` carries a proposition `o.Dom`, its domain, along with a function `get : o.Dom → α`, its
value. The rule is then that every partial value has a value but, to access it, you need to provide
a proof of the domain.
`Part α` behaves the same as `Option α` except that `o : Option α` is decidably `none` or `some a`
for some `a : α`, while the domain of `o : Part α` doesn't have to be decidable. That means you can
translate back and forth between a partial value with a decidable domain and an option, and
`Option α` and `Part α` are classically equivalent. In general, `Part α` is bigger than `Option α`.
In current mathlib, `Part ℕ`, aka `PartENat`, is used to move decidability of the order to
decidability of `PartENat.find` (which is the smallest natural satisfying a predicate, or `∞` if
there's none).
## Main declarations
`Option`-like declarations:
* `Part.none`: The partial value whose domain is `False`.
* `Part.some a`: The partial value whose domain is `True` and whose value is `a`.
* `Part.ofOption`: Converts an `Option α` to a `Part α` by sending `none` to `none` and `some a` to
`some a`.
* `Part.toOption`: Converts a `Part α` with a decidable domain to an `Option α`.
* `Part.equivOption`: Classical equivalence between `Part α` and `Option α`.
Monadic structure:
* `Part.bind`: `o.bind f` has value `(f (o.get _)).get _` (`f o` morally) and is defined when `o`
and `f (o.get _)` are defined.
* `Part.map`: Maps the value and keeps the same domain.
Other:
* `Part.restrict`: `Part.restrict p o` replaces the domain of `o : Part α` by `p : Prop` so long as
`p → o.Dom`.
* `Part.assert`: `assert p f` appends `p` to the domains of the values of a partial function.
* `Part.unwrap`: Gets the value of a partial value regardless of its domain. Unsound.
## Notation
For `a : α`, `o : Part α`, `a ∈ o` means that `o` is defined and equal to `a`. Formally, it means
`o.Dom` and `o.get _ = a`.
-/
open Function
/-- `Part α` is the type of "partial values" of type `α`. It
is similar to `Option α` except the domain condition can be an
arbitrary proposition, not necessarily decidable. -/
structure Part.{u} (α : Type u) : Type u where
/-- The domain of a partial value -/
Dom : Prop
/-- Extract a value from a partial value given a proof of `Dom` -/
get : Dom → α
#align part Part
namespace Part
variable {α : Type*} {β : Type*} {γ : Type*}
/-- Convert a `Part α` with a decidable domain to an option -/
def toOption (o : Part α) [Decidable o.Dom] : Option α :=
if h : Dom o then some (o.get h) else none
#align part.to_option Part.toOption
@[simp] lemma toOption_isSome (o : Part α) [Decidable o.Dom] : o.toOption.isSome ↔ o.Dom := by
by_cases h : o.Dom <;> simp [h, toOption]
#align part.to_option_is_some Part.toOption_isSome
@[simp] lemma toOption_isNone (o : Part α) [Decidable o.Dom] : o.toOption.isNone ↔ ¬o.Dom := by
by_cases h : o.Dom <;> simp [h, toOption]
#align part.to_option_is_none Part.toOption_isNone
/-- `Part` extensionality -/
theorem ext' : ∀ {o p : Part α}, (o.Dom ↔ p.Dom) → (∀ h₁ h₂, o.get h₁ = p.get h₂) → o = p
| ⟨od, o⟩, ⟨pd, p⟩, H1, H2 => by
have t : od = pd := propext H1
cases t; rw [show o = p from funext fun p => H2 p p]
#align part.ext' Part.ext'
/-- `Part` eta expansion -/
@[simp]
theorem eta : ∀ o : Part α, (⟨o.Dom, fun h => o.get h⟩ : Part α) = o
| ⟨_, _⟩ => rfl
#align part.eta Part.eta
/-- `a ∈ o` means that `o` is defined and equal to `a` -/
protected def Mem (a : α) (o : Part α) : Prop :=
∃ h, o.get h = a
#align part.mem Part.Mem
instance : Membership α (Part α) :=
⟨Part.Mem⟩
theorem mem_eq (a : α) (o : Part α) : (a ∈ o) = ∃ h, o.get h = a :=
rfl
#align part.mem_eq Part.mem_eq
theorem dom_iff_mem : ∀ {o : Part α}, o.Dom ↔ ∃ y, y ∈ o
| ⟨_, f⟩ => ⟨fun h => ⟨f h, h, rfl⟩, fun ⟨_, h, rfl⟩ => h⟩
#align part.dom_iff_mem Part.dom_iff_mem
theorem get_mem {o : Part α} (h) : get o h ∈ o :=
⟨_, rfl⟩
#align part.get_mem Part.get_mem
@[simp]
theorem mem_mk_iff {p : Prop} {o : p → α} {a : α} : a ∈ Part.mk p o ↔ ∃ h, o h = a :=
Iff.rfl
#align part.mem_mk_iff Part.mem_mk_iff
/-- `Part` extensionality -/
@[ext]
theorem ext {o p : Part α} (H : ∀ a, a ∈ o ↔ a ∈ p) : o = p :=
(ext' ⟨fun h => ((H _).1 ⟨h, rfl⟩).fst, fun h => ((H _).2 ⟨h, rfl⟩).fst⟩) fun _ _ =>
((H _).2 ⟨_, rfl⟩).snd
#align part.ext Part.ext
/-- The `none` value in `Part` has a `False` domain and an empty function. -/
def none : Part α :=
⟨False, False.rec⟩
#align part.none Part.none
instance : Inhabited (Part α) :=
⟨none⟩
@[simp]
theorem not_mem_none (a : α) : a ∉ @none α := fun h => h.fst
#align part.not_mem_none Part.not_mem_none
/-- The `some a` value in `Part` has a `True` domain and the
function returns `a`. -/
def some (a : α) : Part α :=
⟨True, fun _ => a⟩
#align part.some Part.some
@[simp]
theorem some_dom (a : α) : (some a).Dom :=
trivial
#align part.some_dom Part.some_dom
theorem mem_unique : ∀ {a b : α} {o : Part α}, a ∈ o → b ∈ o → a = b
| _, _, ⟨_, _⟩, ⟨_, rfl⟩, ⟨_, rfl⟩ => rfl
#align part.mem_unique Part.mem_unique
theorem Mem.left_unique : Relator.LeftUnique ((· ∈ ·) : α → Part α → Prop) := fun _ _ _ =>
mem_unique
#align part.mem.left_unique Part.Mem.left_unique
theorem get_eq_of_mem {o : Part α} {a} (h : a ∈ o) (h') : get o h' = a :=
mem_unique ⟨_, rfl⟩ h
#align part.get_eq_of_mem Part.get_eq_of_mem
protected theorem subsingleton (o : Part α) : Set.Subsingleton { a | a ∈ o } := fun _ ha _ hb =>
mem_unique ha hb
#align part.subsingleton Part.subsingleton
@[simp]
theorem get_some {a : α} (ha : (some a).Dom) : get (some a) ha = a :=
rfl
#align part.get_some Part.get_some
theorem mem_some (a : α) : a ∈ some a :=
⟨trivial, rfl⟩
#align part.mem_some Part.mem_some
@[simp]
theorem mem_some_iff {a b} : b ∈ (some a : Part α) ↔ b = a :=
⟨fun ⟨_, e⟩ => e.symm, fun e => ⟨trivial, e.symm⟩⟩
#align part.mem_some_iff Part.mem_some_iff
theorem eq_some_iff {a : α} {o : Part α} : o = some a ↔ a ∈ o :=
⟨fun e => e.symm ▸ mem_some _, fun ⟨h, e⟩ => e ▸ ext' (iff_true_intro h) fun _ _ => rfl⟩
#align part.eq_some_iff Part.eq_some_iff
theorem eq_none_iff {o : Part α} : o = none ↔ ∀ a, a ∉ o :=
⟨fun e => e.symm ▸ not_mem_none, fun h => ext (by simpa)⟩
#align part.eq_none_iff Part.eq_none_iff
theorem eq_none_iff' {o : Part α} : o = none ↔ ¬o.Dom :=
⟨fun e => e.symm ▸ id, fun h => eq_none_iff.2 fun _ h' => h h'.fst⟩
#align part.eq_none_iff' Part.eq_none_iff'
@[simp]
theorem not_none_dom : ¬(none : Part α).Dom :=
id
#align part.not_none_dom Part.not_none_dom
@[simp]
theorem some_ne_none (x : α) : some x ≠ none := by
intro h
exact true_ne_false (congr_arg Dom h)
#align part.some_ne_none Part.some_ne_none
@[simp]
theorem none_ne_some (x : α) : none ≠ some x :=
(some_ne_none x).symm
#align part.none_ne_some Part.none_ne_some
theorem ne_none_iff {o : Part α} : o ≠ none ↔ ∃ x, o = some x := by
constructor
· rw [Ne, eq_none_iff', not_not]
exact fun h => ⟨o.get h, eq_some_iff.2 (get_mem h)⟩
· rintro ⟨x, rfl⟩
apply some_ne_none
#align part.ne_none_iff Part.ne_none_iff
theorem eq_none_or_eq_some (o : Part α) : o = none ∨ ∃ x, o = some x :=
or_iff_not_imp_left.2 ne_none_iff.1
#align part.eq_none_or_eq_some Part.eq_none_or_eq_some
theorem some_injective : Injective (@Part.some α) := fun _ _ h =>
congr_fun (eq_of_heq (Part.mk.inj h).2) trivial
#align part.some_injective Part.some_injective
@[simp]
theorem some_inj {a b : α} : Part.some a = some b ↔ a = b :=
some_injective.eq_iff
#align part.some_inj Part.some_inj
@[simp]
theorem some_get {a : Part α} (ha : a.Dom) : Part.some (Part.get a ha) = a :=
Eq.symm (eq_some_iff.2 ⟨ha, rfl⟩)
#align part.some_get Part.some_get
theorem get_eq_iff_eq_some {a : Part α} {ha : a.Dom} {b : α} : a.get ha = b ↔ a = some b :=
⟨fun h => by simp [h.symm], fun h => by simp [h]⟩
#align part.get_eq_iff_eq_some Part.get_eq_iff_eq_some
theorem get_eq_get_of_eq (a : Part α) (ha : a.Dom) {b : Part α} (h : a = b) :
a.get ha = b.get (h ▸ ha) := by
congr
#align part.get_eq_get_of_eq Part.get_eq_get_of_eq
theorem get_eq_iff_mem {o : Part α} {a : α} (h : o.Dom) : o.get h = a ↔ a ∈ o :=
⟨fun H => ⟨h, H⟩, fun ⟨_, H⟩ => H⟩
#align part.get_eq_iff_mem Part.get_eq_iff_mem
theorem eq_get_iff_mem {o : Part α} {a : α} (h : o.Dom) : a = o.get h ↔ a ∈ o :=
eq_comm.trans (get_eq_iff_mem h)
#align part.eq_get_iff_mem Part.eq_get_iff_mem
@[simp]
theorem none_toOption [Decidable (@none α).Dom] : (none : Part α).toOption = Option.none :=
dif_neg id
#align part.none_to_option Part.none_toOption
@[simp]
theorem some_toOption (a : α) [Decidable (some a).Dom] : (some a).toOption = Option.some a :=
dif_pos trivial
#align part.some_to_option Part.some_toOption
instance noneDecidable : Decidable (@none α).Dom :=
instDecidableFalse
#align part.none_decidable Part.noneDecidable
instance someDecidable (a : α) : Decidable (some a).Dom :=
instDecidableTrue
#align part.some_decidable Part.someDecidable
/-- Retrieves the value of `a : Part α` if it exists, and return the provided default value
otherwise. -/
def getOrElse (a : Part α) [Decidable a.Dom] (d : α) :=
if ha : a.Dom then a.get ha else d
#align part.get_or_else Part.getOrElse
theorem getOrElse_of_dom (a : Part α) (h : a.Dom) [Decidable a.Dom] (d : α) :
getOrElse a d = a.get h :=
dif_pos h
#align part.get_or_else_of_dom Part.getOrElse_of_dom
theorem getOrElse_of_not_dom (a : Part α) (h : ¬a.Dom) [Decidable a.Dom] (d : α) :
getOrElse a d = d :=
dif_neg h
#align part.get_or_else_of_not_dom Part.getOrElse_of_not_dom
@[simp]
theorem getOrElse_none (d : α) [Decidable (none : Part α).Dom] : getOrElse none d = d :=
none.getOrElse_of_not_dom not_none_dom d
#align part.get_or_else_none Part.getOrElse_none
@[simp]
theorem getOrElse_some (a : α) (d : α) [Decidable (some a).Dom] : getOrElse (some a) d = a :=
(some a).getOrElse_of_dom (some_dom a) d
#align part.get_or_else_some Part.getOrElse_some
-- Porting note: removed `simp`
theorem mem_toOption {o : Part α} [Decidable o.Dom] {a : α} : a ∈ toOption o ↔ a ∈ o := by
unfold toOption
by_cases h : o.Dom <;> simp [h]
· exact ⟨fun h => ⟨_, h⟩, fun ⟨_, h⟩ => h⟩
· exact mt Exists.fst h
#align part.mem_to_option Part.mem_toOption
-- Porting note (#10756): new theorem, like `mem_toOption` but with LHS in `simp` normal form
@[simp]
| Mathlib/Data/Part.lean | 299 | 301 | theorem toOption_eq_some_iff {o : Part α} [Decidable o.Dom] {a : α} :
toOption o = Option.some a ↔ a ∈ o := by |
rw [← Option.mem_def, mem_toOption]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.Group.Equiv.Basic
import Mathlib.Data.ENat.Lattice
import Mathlib.Data.Part
import Mathlib.Tactic.NormNum
#align_import data.nat.part_enat from "leanprover-community/mathlib"@"3ff3f2d6a3118b8711063de7111a0d77a53219a8"
/-!
# Natural numbers with infinity
The natural numbers and an extra `top` element `⊤`. This implementation uses `Part ℕ` as an
implementation. Use `ℕ∞` instead unless you care about computability.
## Main definitions
The following instances are defined:
* `OrderedAddCommMonoid PartENat`
* `CanonicallyOrderedAddCommMonoid PartENat`
* `CompleteLinearOrder PartENat`
There is no additive analogue of `MonoidWithZero`; if there were then `PartENat` could
be an `AddMonoidWithTop`.
* `toWithTop` : the map from `PartENat` to `ℕ∞`, with theorems that it plays well
with `+` and `≤`.
* `withTopAddEquiv : PartENat ≃+ ℕ∞`
* `withTopOrderIso : PartENat ≃o ℕ∞`
## Implementation details
`PartENat` is defined to be `Part ℕ`.
`+` and `≤` are defined on `PartENat`, but there is an issue with `*` because it's not
clear what `0 * ⊤` should be. `mul` is hence left undefined. Similarly `⊤ - ⊤` is ambiguous
so there is no `-` defined on `PartENat`.
Before the `open scoped Classical` line, various proofs are made with decidability assumptions.
This can cause issues -- see for example the non-simp lemma `toWithTopZero` proved by `rfl`,
followed by `@[simp] lemma toWithTopZero'` whose proof uses `convert`.
## Tags
PartENat, ℕ∞
-/
open Part hiding some
/-- Type of natural numbers with infinity (`⊤`) -/
def PartENat : Type :=
Part ℕ
#align part_enat PartENat
namespace PartENat
/-- The computable embedding `ℕ → PartENat`.
This coincides with the coercion `coe : ℕ → PartENat`, see `PartENat.some_eq_natCast`. -/
@[coe]
def some : ℕ → PartENat :=
Part.some
#align part_enat.some PartENat.some
instance : Zero PartENat :=
⟨some 0⟩
instance : Inhabited PartENat :=
⟨0⟩
instance : One PartENat :=
⟨some 1⟩
instance : Add PartENat :=
⟨fun x y => ⟨x.Dom ∧ y.Dom, fun h => get x h.1 + get y h.2⟩⟩
instance (n : ℕ) : Decidable (some n).Dom :=
isTrue trivial
@[simp]
theorem dom_some (x : ℕ) : (some x).Dom :=
trivial
#align part_enat.dom_some PartENat.dom_some
instance addCommMonoid : AddCommMonoid PartENat where
add := (· + ·)
zero := 0
add_comm x y := Part.ext' and_comm fun _ _ => add_comm _ _
zero_add x := Part.ext' (true_and_iff _) fun _ _ => zero_add _
add_zero x := Part.ext' (and_true_iff _) fun _ _ => add_zero _
add_assoc x y z := Part.ext' and_assoc fun _ _ => add_assoc _ _ _
nsmul := nsmulRec
instance : AddCommMonoidWithOne PartENat :=
{ PartENat.addCommMonoid with
one := 1
natCast := some
natCast_zero := rfl
natCast_succ := fun _ => Part.ext' (true_and_iff _).symm fun _ _ => rfl }
theorem some_eq_natCast (n : ℕ) : some n = n :=
rfl
#align part_enat.some_eq_coe PartENat.some_eq_natCast
instance : CharZero PartENat where
cast_injective := Part.some_injective
/-- Alias of `Nat.cast_inj` specialized to `PartENat` --/
theorem natCast_inj {x y : ℕ} : (x : PartENat) = y ↔ x = y :=
Nat.cast_inj
#align part_enat.coe_inj PartENat.natCast_inj
@[simp]
theorem dom_natCast (x : ℕ) : (x : PartENat).Dom :=
trivial
#align part_enat.dom_coe PartENat.dom_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem dom_ofNat (x : ℕ) [x.AtLeastTwo] : (no_index (OfNat.ofNat x : PartENat)).Dom :=
trivial
@[simp]
theorem dom_zero : (0 : PartENat).Dom :=
trivial
@[simp]
theorem dom_one : (1 : PartENat).Dom :=
trivial
instance : CanLift PartENat ℕ (↑) Dom :=
⟨fun n hn => ⟨n.get hn, Part.some_get _⟩⟩
instance : LE PartENat :=
⟨fun x y => ∃ h : y.Dom → x.Dom, ∀ hy : y.Dom, x.get (h hy) ≤ y.get hy⟩
instance : Top PartENat :=
⟨none⟩
instance : Bot PartENat :=
⟨0⟩
instance : Sup PartENat :=
⟨fun x y => ⟨x.Dom ∧ y.Dom, fun h => x.get h.1 ⊔ y.get h.2⟩⟩
theorem le_def (x y : PartENat) :
x ≤ y ↔ ∃ h : y.Dom → x.Dom, ∀ hy : y.Dom, x.get (h hy) ≤ y.get hy :=
Iff.rfl
#align part_enat.le_def PartENat.le_def
@[elab_as_elim]
protected theorem casesOn' {P : PartENat → Prop} :
∀ a : PartENat, P ⊤ → (∀ n : ℕ, P (some n)) → P a :=
Part.induction_on
#align part_enat.cases_on' PartENat.casesOn'
@[elab_as_elim]
protected theorem casesOn {P : PartENat → Prop} : ∀ a : PartENat, P ⊤ → (∀ n : ℕ, P n) → P a := by
exact PartENat.casesOn'
#align part_enat.cases_on PartENat.casesOn
-- not a simp lemma as we will provide a `LinearOrderedAddCommMonoidWithTop` instance later
theorem top_add (x : PartENat) : ⊤ + x = ⊤ :=
Part.ext' (false_and_iff _) fun h => h.left.elim
#align part_enat.top_add PartENat.top_add
-- not a simp lemma as we will provide a `LinearOrderedAddCommMonoidWithTop` instance later
theorem add_top (x : PartENat) : x + ⊤ = ⊤ := by rw [add_comm, top_add]
#align part_enat.add_top PartENat.add_top
@[simp]
theorem natCast_get {x : PartENat} (h : x.Dom) : (x.get h : PartENat) = x := by
exact Part.ext' (iff_of_true trivial h) fun _ _ => rfl
#align part_enat.coe_get PartENat.natCast_get
@[simp, norm_cast]
theorem get_natCast' (x : ℕ) (h : (x : PartENat).Dom) : get (x : PartENat) h = x := by
rw [← natCast_inj, natCast_get]
#align part_enat.get_coe' PartENat.get_natCast'
theorem get_natCast {x : ℕ} : get (x : PartENat) (dom_natCast x) = x :=
get_natCast' _ _
#align part_enat.get_coe PartENat.get_natCast
theorem coe_add_get {x : ℕ} {y : PartENat} (h : ((x : PartENat) + y).Dom) :
get ((x : PartENat) + y) h = x + get y h.2 := by
rfl
#align part_enat.coe_add_get PartENat.coe_add_get
@[simp]
theorem get_add {x y : PartENat} (h : (x + y).Dom) : get (x + y) h = x.get h.1 + y.get h.2 :=
rfl
#align part_enat.get_add PartENat.get_add
@[simp]
theorem get_zero (h : (0 : PartENat).Dom) : (0 : PartENat).get h = 0 :=
rfl
#align part_enat.get_zero PartENat.get_zero
@[simp]
theorem get_one (h : (1 : PartENat).Dom) : (1 : PartENat).get h = 1 :=
rfl
#align part_enat.get_one PartENat.get_one
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem get_ofNat' (x : ℕ) [x.AtLeastTwo] (h : (no_index (OfNat.ofNat x : PartENat)).Dom) :
Part.get (no_index (OfNat.ofNat x : PartENat)) h = (no_index (OfNat.ofNat x)) :=
get_natCast' x h
nonrec theorem get_eq_iff_eq_some {a : PartENat} {ha : a.Dom} {b : ℕ} : a.get ha = b ↔ a = some b :=
get_eq_iff_eq_some
#align part_enat.get_eq_iff_eq_some PartENat.get_eq_iff_eq_some
theorem get_eq_iff_eq_coe {a : PartENat} {ha : a.Dom} {b : ℕ} : a.get ha = b ↔ a = b := by
rw [get_eq_iff_eq_some]
rfl
#align part_enat.get_eq_iff_eq_coe PartENat.get_eq_iff_eq_coe
theorem dom_of_le_of_dom {x y : PartENat} : x ≤ y → y.Dom → x.Dom := fun ⟨h, _⟩ => h
#align part_enat.dom_of_le_of_dom PartENat.dom_of_le_of_dom
theorem dom_of_le_some {x : PartENat} {y : ℕ} (h : x ≤ some y) : x.Dom :=
dom_of_le_of_dom h trivial
#align part_enat.dom_of_le_some PartENat.dom_of_le_some
theorem dom_of_le_natCast {x : PartENat} {y : ℕ} (h : x ≤ y) : x.Dom := by
exact dom_of_le_some h
#align part_enat.dom_of_le_coe PartENat.dom_of_le_natCast
instance decidableLe (x y : PartENat) [Decidable x.Dom] [Decidable y.Dom] : Decidable (x ≤ y) :=
if hx : x.Dom then
decidable_of_decidable_of_iff (by rw [le_def])
else
if hy : y.Dom then isFalse fun h => hx <| dom_of_le_of_dom h hy
else isTrue ⟨fun h => (hy h).elim, fun h => (hy h).elim⟩
#align part_enat.decidable_le PartENat.decidableLe
-- Porting note: Removed. Use `Nat.castAddMonoidHom` instead.
#noalign part_enat.coe_hom
#noalign part_enat.coe_coe_hom
instance partialOrder : PartialOrder PartENat where
le := (· ≤ ·)
le_refl _ := ⟨id, fun _ => le_rfl⟩
le_trans := fun _ _ _ ⟨hxy₁, hxy₂⟩ ⟨hyz₁, hyz₂⟩ =>
⟨hxy₁ ∘ hyz₁, fun _ => le_trans (hxy₂ _) (hyz₂ _)⟩
lt_iff_le_not_le _ _ := Iff.rfl
le_antisymm := fun _ _ ⟨hxy₁, hxy₂⟩ ⟨hyx₁, hyx₂⟩ =>
Part.ext' ⟨hyx₁, hxy₁⟩ fun _ _ => le_antisymm (hxy₂ _) (hyx₂ _)
theorem lt_def (x y : PartENat) : x < y ↔ ∃ hx : x.Dom, ∀ hy : y.Dom, x.get hx < y.get hy := by
rw [lt_iff_le_not_le, le_def, le_def, not_exists]
constructor
· rintro ⟨⟨hyx, H⟩, h⟩
by_cases hx : x.Dom
· use hx
intro hy
specialize H hy
specialize h fun _ => hy
rw [not_forall] at h
cases' h with hx' h
rw [not_le] at h
exact h
· specialize h fun hx' => (hx hx').elim
rw [not_forall] at h
cases' h with hx' h
exact (hx hx').elim
· rintro ⟨hx, H⟩
exact ⟨⟨fun _ => hx, fun hy => (H hy).le⟩, fun hxy h => not_lt_of_le (h _) (H _)⟩
#align part_enat.lt_def PartENat.lt_def
noncomputable instance orderedAddCommMonoid : OrderedAddCommMonoid PartENat :=
{ PartENat.partialOrder, PartENat.addCommMonoid with
add_le_add_left := fun a b ⟨h₁, h₂⟩ c =>
PartENat.casesOn c (by simp [top_add]) fun c =>
⟨fun h => And.intro (dom_natCast _) (h₁ h.2), fun h => by
simpa only [coe_add_get] using add_le_add_left (h₂ _) c⟩ }
instance semilatticeSup : SemilatticeSup PartENat :=
{ PartENat.partialOrder with
sup := (· ⊔ ·)
le_sup_left := fun _ _ => ⟨And.left, fun _ => le_sup_left⟩
le_sup_right := fun _ _ => ⟨And.right, fun _ => le_sup_right⟩
sup_le := fun _ _ _ ⟨hx₁, hx₂⟩ ⟨hy₁, hy₂⟩ =>
⟨fun hz => ⟨hx₁ hz, hy₁ hz⟩, fun _ => sup_le (hx₂ _) (hy₂ _)⟩ }
#align part_enat.semilattice_sup PartENat.semilatticeSup
instance orderBot : OrderBot PartENat where
bot := ⊥
bot_le _ := ⟨fun _ => trivial, fun _ => Nat.zero_le _⟩
#align part_enat.order_bot PartENat.orderBot
instance orderTop : OrderTop PartENat where
top := ⊤
le_top _ := ⟨fun h => False.elim h, fun hy => False.elim hy⟩
#align part_enat.order_top PartENat.orderTop
instance : ZeroLEOneClass PartENat where
zero_le_one := bot_le
/-- Alias of `Nat.cast_le` specialized to `PartENat` --/
theorem coe_le_coe {x y : ℕ} : (x : PartENat) ≤ y ↔ x ≤ y := Nat.cast_le
#align part_enat.coe_le_coe PartENat.coe_le_coe
/-- Alias of `Nat.cast_lt` specialized to `PartENat` --/
theorem coe_lt_coe {x y : ℕ} : (x : PartENat) < y ↔ x < y := Nat.cast_lt
#align part_enat.coe_lt_coe PartENat.coe_lt_coe
@[simp]
theorem get_le_get {x y : PartENat} {hx : x.Dom} {hy : y.Dom} : x.get hx ≤ y.get hy ↔ x ≤ y := by
conv =>
lhs
rw [← coe_le_coe, natCast_get, natCast_get]
#align part_enat.get_le_get PartENat.get_le_get
theorem le_coe_iff (x : PartENat) (n : ℕ) : x ≤ n ↔ ∃ h : x.Dom, x.get h ≤ n := by
show (∃ h : True → x.Dom, _) ↔ ∃ h : x.Dom, x.get h ≤ n
simp only [forall_prop_of_true, dom_natCast, get_natCast']
#align part_enat.le_coe_iff PartENat.le_coe_iff
theorem lt_coe_iff (x : PartENat) (n : ℕ) : x < n ↔ ∃ h : x.Dom, x.get h < n := by
simp only [lt_def, forall_prop_of_true, get_natCast', dom_natCast]
#align part_enat.lt_coe_iff PartENat.lt_coe_iff
theorem coe_le_iff (n : ℕ) (x : PartENat) : (n : PartENat) ≤ x ↔ ∀ h : x.Dom, n ≤ x.get h := by
rw [← some_eq_natCast]
simp only [le_def, exists_prop_of_true, dom_some, forall_true_iff]
rfl
#align part_enat.coe_le_iff PartENat.coe_le_iff
theorem coe_lt_iff (n : ℕ) (x : PartENat) : (n : PartENat) < x ↔ ∀ h : x.Dom, n < x.get h := by
rw [← some_eq_natCast]
simp only [lt_def, exists_prop_of_true, dom_some, forall_true_iff]
rfl
#align part_enat.coe_lt_iff PartENat.coe_lt_iff
nonrec theorem eq_zero_iff {x : PartENat} : x = 0 ↔ x ≤ 0 :=
eq_bot_iff
#align part_enat.eq_zero_iff PartENat.eq_zero_iff
theorem ne_zero_iff {x : PartENat} : x ≠ 0 ↔ ⊥ < x :=
bot_lt_iff_ne_bot.symm
#align part_enat.ne_zero_iff PartENat.ne_zero_iff
theorem dom_of_lt {x y : PartENat} : x < y → x.Dom :=
PartENat.casesOn x not_top_lt fun _ _ => dom_natCast _
#align part_enat.dom_of_lt PartENat.dom_of_lt
theorem top_eq_none : (⊤ : PartENat) = Part.none :=
rfl
#align part_enat.top_eq_none PartENat.top_eq_none
@[simp]
theorem natCast_lt_top (x : ℕ) : (x : PartENat) < ⊤ :=
Ne.lt_top fun h => absurd (congr_arg Dom h) <| by simp only [dom_natCast]; exact true_ne_false
#align part_enat.coe_lt_top PartENat.natCast_lt_top
@[simp]
theorem zero_lt_top : (0 : PartENat) < ⊤ :=
natCast_lt_top 0
@[simp]
theorem one_lt_top : (1 : PartENat) < ⊤ :=
natCast_lt_top 1
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem ofNat_lt_top (x : ℕ) [x.AtLeastTwo] : (no_index (OfNat.ofNat x : PartENat)) < ⊤ :=
natCast_lt_top x
@[simp]
theorem natCast_ne_top (x : ℕ) : (x : PartENat) ≠ ⊤ :=
ne_of_lt (natCast_lt_top x)
#align part_enat.coe_ne_top PartENat.natCast_ne_top
@[simp]
theorem zero_ne_top : (0 : PartENat) ≠ ⊤ :=
natCast_ne_top 0
@[simp]
theorem one_ne_top : (1 : PartENat) ≠ ⊤ :=
natCast_ne_top 1
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem ofNat_ne_top (x : ℕ) [x.AtLeastTwo] : (no_index (OfNat.ofNat x : PartENat)) ≠ ⊤ :=
natCast_ne_top x
theorem not_isMax_natCast (x : ℕ) : ¬IsMax (x : PartENat) :=
not_isMax_of_lt (natCast_lt_top x)
#align part_enat.not_is_max_coe PartENat.not_isMax_natCast
theorem ne_top_iff {x : PartENat} : x ≠ ⊤ ↔ ∃ n : ℕ, x = n := by
simpa only [← some_eq_natCast] using Part.ne_none_iff
#align part_enat.ne_top_iff PartENat.ne_top_iff
theorem ne_top_iff_dom {x : PartENat} : x ≠ ⊤ ↔ x.Dom := by
classical exact not_iff_comm.1 Part.eq_none_iff'.symm
#align part_enat.ne_top_iff_dom PartENat.ne_top_iff_dom
theorem not_dom_iff_eq_top {x : PartENat} : ¬x.Dom ↔ x = ⊤ :=
Iff.not_left ne_top_iff_dom.symm
#align part_enat.not_dom_iff_eq_top PartENat.not_dom_iff_eq_top
theorem ne_top_of_lt {x y : PartENat} (h : x < y) : x ≠ ⊤ :=
ne_of_lt <| lt_of_lt_of_le h le_top
#align part_enat.ne_top_of_lt PartENat.ne_top_of_lt
theorem eq_top_iff_forall_lt (x : PartENat) : x = ⊤ ↔ ∀ n : ℕ, (n : PartENat) < x := by
constructor
· rintro rfl n
exact natCast_lt_top _
· contrapose!
rw [ne_top_iff]
rintro ⟨n, rfl⟩
exact ⟨n, irrefl _⟩
#align part_enat.eq_top_iff_forall_lt PartENat.eq_top_iff_forall_lt
theorem eq_top_iff_forall_le (x : PartENat) : x = ⊤ ↔ ∀ n : ℕ, (n : PartENat) ≤ x :=
(eq_top_iff_forall_lt x).trans
⟨fun h n => (h n).le, fun h n => lt_of_lt_of_le (coe_lt_coe.mpr n.lt_succ_self) (h (n + 1))⟩
#align part_enat.eq_top_iff_forall_le PartENat.eq_top_iff_forall_le
theorem pos_iff_one_le {x : PartENat} : 0 < x ↔ 1 ≤ x :=
PartENat.casesOn x
(by simp only [iff_true_iff, le_top, natCast_lt_top, ← @Nat.cast_zero PartENat])
fun n => by
rw [← Nat.cast_zero, ← Nat.cast_one, PartENat.coe_lt_coe, PartENat.coe_le_coe]
rfl
#align part_enat.pos_iff_one_le PartENat.pos_iff_one_le
instance isTotal : IsTotal PartENat (· ≤ ·) where
total x y :=
PartENat.casesOn (P := fun z => z ≤ y ∨ y ≤ z) x (Or.inr le_top)
(PartENat.casesOn y (fun _ => Or.inl le_top) fun x y =>
(le_total x y).elim (Or.inr ∘ coe_le_coe.2) (Or.inl ∘ coe_le_coe.2))
noncomputable instance linearOrder : LinearOrder PartENat :=
{ PartENat.partialOrder with
le_total := IsTotal.total
decidableLE := Classical.decRel _
max := (· ⊔ ·)
-- Porting note: was `max_def := @sup_eq_maxDefault _ _ (id _) _ }`
max_def := fun a b => by
change (fun a b => a ⊔ b) a b = _
rw [@sup_eq_maxDefault PartENat _ (id _) _]
rfl }
instance boundedOrder : BoundedOrder PartENat :=
{ PartENat.orderTop, PartENat.orderBot with }
noncomputable instance lattice : Lattice PartENat :=
{ PartENat.semilatticeSup with
inf := min
inf_le_left := min_le_left
inf_le_right := min_le_right
le_inf := fun _ _ _ => le_min }
noncomputable instance : CanonicallyOrderedAddCommMonoid PartENat :=
{ PartENat.semilatticeSup, PartENat.orderBot,
PartENat.orderedAddCommMonoid with
le_self_add := fun a b =>
PartENat.casesOn b (le_top.trans_eq (add_top _).symm) fun b =>
PartENat.casesOn a (top_add _).ge fun a =>
(coe_le_coe.2 le_self_add).trans_eq (Nat.cast_add _ _)
exists_add_of_le := fun {a b} =>
PartENat.casesOn b (fun _ => ⟨⊤, (add_top _).symm⟩) fun b =>
PartENat.casesOn a (fun h => ((natCast_lt_top _).not_le h).elim) fun a h =>
⟨(b - a : ℕ), by
rw [← Nat.cast_add, natCast_inj, add_comm, tsub_add_cancel_of_le (coe_le_coe.1 h)]⟩ }
theorem eq_natCast_sub_of_add_eq_natCast {x y : PartENat} {n : ℕ} (h : x + y = n) :
x = ↑(n - y.get (dom_of_le_natCast ((le_add_left le_rfl).trans_eq h))) := by
lift x to ℕ using dom_of_le_natCast ((le_add_right le_rfl).trans_eq h)
lift y to ℕ using dom_of_le_natCast ((le_add_left le_rfl).trans_eq h)
rw [← Nat.cast_add, natCast_inj] at h
rw [get_natCast, natCast_inj, eq_tsub_of_add_eq h]
#align part_enat.eq_coe_sub_of_add_eq_coe PartENat.eq_natCast_sub_of_add_eq_natCast
protected theorem add_lt_add_right {x y z : PartENat} (h : x < y) (hz : z ≠ ⊤) : x + z < y + z := by
rcases ne_top_iff.mp (ne_top_of_lt h) with ⟨m, rfl⟩
rcases ne_top_iff.mp hz with ⟨k, rfl⟩
induction' y using PartENat.casesOn with n
· rw [top_add]
-- Porting note: was apply_mod_cast natCast_lt_top
norm_cast; apply natCast_lt_top
norm_cast at h
-- Porting note: was `apply_mod_cast add_lt_add_right h`
norm_cast; apply add_lt_add_right h
#align part_enat.add_lt_add_right PartENat.add_lt_add_right
protected theorem add_lt_add_iff_right {x y z : PartENat} (hz : z ≠ ⊤) : x + z < y + z ↔ x < y :=
⟨lt_of_add_lt_add_right, fun h => PartENat.add_lt_add_right h hz⟩
#align part_enat.add_lt_add_iff_right PartENat.add_lt_add_iff_right
protected theorem add_lt_add_iff_left {x y z : PartENat} (hz : z ≠ ⊤) : z + x < z + y ↔ x < y := by
rw [add_comm z, add_comm z, PartENat.add_lt_add_iff_right hz]
#align part_enat.add_lt_add_iff_left PartENat.add_lt_add_iff_left
protected theorem lt_add_iff_pos_right {x y : PartENat} (hx : x ≠ ⊤) : x < x + y ↔ 0 < y := by
conv_rhs => rw [← PartENat.add_lt_add_iff_left hx]
rw [add_zero]
#align part_enat.lt_add_iff_pos_right PartENat.lt_add_iff_pos_right
theorem lt_add_one {x : PartENat} (hx : x ≠ ⊤) : x < x + 1 := by
rw [PartENat.lt_add_iff_pos_right hx]
norm_cast
#align part_enat.lt_add_one PartENat.lt_add_one
theorem le_of_lt_add_one {x y : PartENat} (h : x < y + 1) : x ≤ y := by
induction' y using PartENat.casesOn with n
· apply le_top
rcases ne_top_iff.mp (ne_top_of_lt h) with ⟨m, rfl⟩
-- Porting note: was `apply_mod_cast Nat.le_of_lt_succ; apply_mod_cast h`
norm_cast; apply Nat.le_of_lt_succ; norm_cast at h
#align part_enat.le_of_lt_add_one PartENat.le_of_lt_add_one
theorem add_one_le_of_lt {x y : PartENat} (h : x < y) : x + 1 ≤ y := by
induction' y using PartENat.casesOn with n
· apply le_top
rcases ne_top_iff.mp (ne_top_of_lt h) with ⟨m, rfl⟩
-- Porting note: was `apply_mod_cast Nat.succ_le_of_lt; apply_mod_cast h`
norm_cast; apply Nat.succ_le_of_lt; norm_cast at h
#align part_enat.add_one_le_of_lt PartENat.add_one_le_of_lt
theorem add_one_le_iff_lt {x y : PartENat} (hx : x ≠ ⊤) : x + 1 ≤ y ↔ x < y := by
refine ⟨fun h => ?_, add_one_le_of_lt⟩
rcases ne_top_iff.mp hx with ⟨m, rfl⟩
induction' y using PartENat.casesOn with n
· apply natCast_lt_top
-- Porting note: was `apply_mod_cast Nat.lt_of_succ_le; apply_mod_cast h`
norm_cast; apply Nat.lt_of_succ_le; norm_cast at h
#align part_enat.add_one_le_iff_lt PartENat.add_one_le_iff_lt
theorem coe_succ_le_iff {n : ℕ} {e : PartENat} : ↑n.succ ≤ e ↔ ↑n < e := by
rw [Nat.succ_eq_add_one n, Nat.cast_add, Nat.cast_one, add_one_le_iff_lt (natCast_ne_top n)]
#align part_enat.coe_succ_le_succ_iff PartENat.coe_succ_le_iff
theorem lt_add_one_iff_lt {x y : PartENat} (hx : x ≠ ⊤) : x < y + 1 ↔ x ≤ y := by
refine ⟨le_of_lt_add_one, fun h => ?_⟩
rcases ne_top_iff.mp hx with ⟨m, rfl⟩
induction' y using PartENat.casesOn with n
· rw [top_add]
apply natCast_lt_top
-- Porting note: was `apply_mod_cast Nat.lt_succ_of_le; apply_mod_cast h`
norm_cast; apply Nat.lt_succ_of_le; norm_cast at h
#align part_enat.lt_add_one_iff_lt PartENat.lt_add_one_iff_lt
lemma lt_coe_succ_iff_le {x : PartENat} {n : ℕ} (hx : x ≠ ⊤) : x < n.succ ↔ x ≤ n := by
rw [Nat.succ_eq_add_one n, Nat.cast_add, Nat.cast_one, lt_add_one_iff_lt hx]
#align part_enat.lt_coe_succ_iff_le PartENat.lt_coe_succ_iff_le
theorem add_eq_top_iff {a b : PartENat} : a + b = ⊤ ↔ a = ⊤ ∨ b = ⊤ := by
refine PartENat.casesOn a ?_ ?_
<;> refine PartENat.casesOn b ?_ ?_
<;> simp [top_add, add_top]
simp only [← Nat.cast_add, PartENat.natCast_ne_top, forall_const, not_false_eq_true]
#align part_enat.add_eq_top_iff PartENat.add_eq_top_iff
protected theorem add_right_cancel_iff {a b c : PartENat} (hc : c ≠ ⊤) : a + c = b + c ↔ a = b := by
rcases ne_top_iff.1 hc with ⟨c, rfl⟩
refine PartENat.casesOn a ?_ ?_
<;> refine PartENat.casesOn b ?_ ?_
<;> simp [add_eq_top_iff, natCast_ne_top, @eq_comm _ (⊤ : PartENat), top_add]
simp only [← Nat.cast_add, add_left_cancel_iff, PartENat.natCast_inj, add_comm, forall_const]
#align part_enat.add_right_cancel_iff PartENat.add_right_cancel_iff
protected theorem add_left_cancel_iff {a b c : PartENat} (ha : a ≠ ⊤) : a + b = a + c ↔ b = c := by
rw [add_comm a, add_comm a, PartENat.add_right_cancel_iff ha]
#align part_enat.add_left_cancel_iff PartENat.add_left_cancel_iff
section WithTop
/-- Computably converts a `PartENat` to a `ℕ∞`. -/
def toWithTop (x : PartENat) [Decidable x.Dom] : ℕ∞ :=
x.toOption
#align part_enat.to_with_top PartENat.toWithTop
theorem toWithTop_top :
have : Decidable (⊤ : PartENat).Dom := Part.noneDecidable
toWithTop ⊤ = ⊤ :=
rfl
#align part_enat.to_with_top_top PartENat.toWithTop_top
@[simp]
theorem toWithTop_top' {h : Decidable (⊤ : PartENat).Dom} : toWithTop ⊤ = ⊤ := by
convert toWithTop_top
#align part_enat.to_with_top_top' PartENat.toWithTop_top'
theorem toWithTop_zero :
have : Decidable (0 : PartENat).Dom := someDecidable 0
toWithTop 0 = 0 :=
rfl
#align part_enat.to_with_top_zero PartENat.toWithTop_zero
@[simp]
theorem toWithTop_zero' {h : Decidable (0 : PartENat).Dom} : toWithTop 0 = 0 := by
convert toWithTop_zero
#align part_enat.to_with_top_zero' PartENat.toWithTop_zero'
theorem toWithTop_one :
have : Decidable (1 : PartENat).Dom := someDecidable 1
toWithTop 1 = 1 :=
rfl
@[simp]
theorem toWithTop_one' {h : Decidable (1 : PartENat).Dom} : toWithTop 1 = 1 := by
convert toWithTop_one
theorem toWithTop_some (n : ℕ) : toWithTop (some n) = n :=
rfl
#align part_enat.to_with_top_some PartENat.toWithTop_some
theorem toWithTop_natCast (n : ℕ) {_ : Decidable (n : PartENat).Dom} : toWithTop n = n := by
simp only [← toWithTop_some]
congr
#align part_enat.to_with_top_coe PartENat.toWithTop_natCast
@[simp]
theorem toWithTop_natCast' (n : ℕ) {_ : Decidable (n : PartENat).Dom} :
toWithTop (n : PartENat) = n := by
rw [toWithTop_natCast n]
#align part_enat.to_with_top_coe' PartENat.toWithTop_natCast'
@[simp]
theorem toWithTop_ofNat (n : ℕ) [n.AtLeastTwo] {_ : Decidable (OfNat.ofNat n : PartENat).Dom} :
toWithTop (no_index (OfNat.ofNat n : PartENat)) = OfNat.ofNat n := toWithTop_natCast' n
-- Porting note: statement changed. Mathlib 3 statement was
-- ```
-- @[simp] lemma to_with_top_le {x y : part_enat} :
-- Π [decidable x.dom] [decidable y.dom], by exactI to_with_top x ≤ to_with_top y ↔ x ≤ y :=
-- ```
-- This used to be really slow to typecheck when the definition of `ENat`
-- was still `deriving AddCommMonoidWithOne`. Now that I removed that it is fine.
-- (The problem was that the last `simp` got stuck at `CharZero ℕ∞ ≟ CharZero ℕ∞` where
-- one side used `instENatAddCommMonoidWithOne` and the other used
-- `NonAssocSemiring.toAddCommMonoidWithOne`. Now the former doesn't exist anymore.)
@[simp]
theorem toWithTop_le {x y : PartENat} [hx : Decidable x.Dom] [hy : Decidable y.Dom] :
toWithTop x ≤ toWithTop y ↔ x ≤ y := by
induction y using PartENat.casesOn generalizing hy
· simp
induction x using PartENat.casesOn generalizing hx
· simp
· simp -- Porting note: this takes too long.
#align part_enat.to_with_top_le PartENat.toWithTop_le
/-
Porting note: As part of the investigation above, I noticed that Lean4 does not
find the following two instances which it could find in Lean3 automatically:
```
#synth Decidable (⊤ : PartENat).Dom
variable {n : ℕ}
#synth Decidable (n : PartENat).Dom
```
-/
@[simp]
theorem toWithTop_lt {x y : PartENat} [Decidable x.Dom] [Decidable y.Dom] :
toWithTop x < toWithTop y ↔ x < y :=
lt_iff_lt_of_le_iff_le toWithTop_le
#align part_enat.to_with_top_lt PartENat.toWithTop_lt
end WithTop
-- Porting note: new, extracted from `withTopEquiv`.
/-- Coercion from `ℕ∞` to `PartENat`. -/
@[coe]
def ofENat : ℕ∞ → PartENat :=
fun x => match x with
| Option.none => none
| Option.some n => some n
-- Porting note (#10754): new instance
instance : Coe ℕ∞ PartENat := ⟨ofENat⟩
-- Porting note: new. This could probably be moved to tests or removed.
example (n : ℕ) : ((n : ℕ∞) : PartENat) = ↑n := rfl
-- Porting note (#10756): new lemma
@[simp, norm_cast]
lemma ofENat_top : ofENat ⊤ = ⊤ := rfl
-- Porting note (#10756): new lemma
@[simp, norm_cast]
lemma ofENat_coe (n : ℕ) : ofENat n = n := rfl
@[simp, norm_cast]
theorem ofENat_zero : ofENat 0 = 0 := rfl
@[simp, norm_cast]
theorem ofENat_one : ofENat 1 = 1 := rfl
@[simp, norm_cast]
theorem ofENat_ofNat (n : Nat) [n.AtLeastTwo] : ofENat (no_index (OfNat.ofNat n)) = OfNat.ofNat n :=
rfl
-- Porting note (#10756): new theorem
@[simp, norm_cast]
theorem toWithTop_ofENat (n : ℕ∞) {_ : Decidable (n : PartENat).Dom} : toWithTop (↑n) = n := by
cases n with
| top => simp
| coe n => simp
@[simp, norm_cast]
theorem ofENat_toWithTop (x : PartENat) {_ : Decidable (x : PartENat).Dom} : toWithTop x = x := by
induction x using PartENat.casesOn <;> simp
@[simp, norm_cast]
| Mathlib/Data/Nat/PartENat.lean | 719 | 721 | theorem ofENat_le {x y : ℕ∞} : ofENat x ≤ ofENat y ↔ x ≤ y := by |
classical
rw [← toWithTop_le, toWithTop_ofENat, toWithTop_ofENat]
|
/-
Copyright (c) 2020 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Monic
#align_import data.polynomial.lifts from "leanprover-community/mathlib"@"63417e01fbc711beaf25fa73b6edb395c0cfddd0"
/-!
# Polynomials that lift
Given semirings `R` and `S` with a morphism `f : R →+* S`, we define a subsemiring `lifts` of
`S[X]` by the image of `RingHom.of (map f)`.
Then, we prove that a polynomial that lifts can always be lifted to a polynomial of the same degree
and that a monic polynomial that lifts can be lifted to a monic polynomial (of the same degree).
## Main definition
* `lifts (f : R →+* S)` : the subsemiring of polynomials that lift.
## Main results
* `lifts_and_degree_eq` : A polynomial lifts if and only if it can be lifted to a polynomial
of the same degree.
* `lifts_and_degree_eq_and_monic` : A monic polynomial lifts if and only if it can be lifted to a
monic polynomial of the same degree.
* `lifts_iff_alg` : if `R` is commutative, a polynomial lifts if and only if it is in the image of
`mapAlg`, where `mapAlg : R[X] →ₐ[R] S[X]` is the only `R`-algebra map
that sends `X` to `X`.
## Implementation details
In general `R` and `S` are semiring, so `lifts` is a semiring. In the case of rings, see
`lifts_iff_lifts_ring`.
Since we do not assume `R` to be commutative, we cannot say in general that the set of polynomials
that lift is a subalgebra. (By `lift_iff` this is true if `R` is commutative.)
-/
open Polynomial
noncomputable section
namespace Polynomial
universe u v w
section Semiring
variable {R : Type u} [Semiring R] {S : Type v} [Semiring S] {f : R →+* S}
/-- We define the subsemiring of polynomials that lifts as the image of `RingHom.of (map f)`. -/
def lifts (f : R →+* S) : Subsemiring S[X] :=
RingHom.rangeS (mapRingHom f)
#align polynomial.lifts Polynomial.lifts
theorem mem_lifts (p : S[X]) : p ∈ lifts f ↔ ∃ q : R[X], map f q = p := by
simp only [coe_mapRingHom, lifts, RingHom.mem_rangeS]
#align polynomial.mem_lifts Polynomial.mem_lifts
theorem lifts_iff_set_range (p : S[X]) : p ∈ lifts f ↔ p ∈ Set.range (map f) := by
simp only [coe_mapRingHom, lifts, Set.mem_range, RingHom.mem_rangeS]
#align polynomial.lifts_iff_set_range Polynomial.lifts_iff_set_range
theorem lifts_iff_ringHom_rangeS (p : S[X]) : p ∈ lifts f ↔ p ∈ (mapRingHom f).rangeS := by
simp only [coe_mapRingHom, lifts, Set.mem_range, RingHom.mem_rangeS]
#align polynomial.lifts_iff_ring_hom_srange Polynomial.lifts_iff_ringHom_rangeS
theorem lifts_iff_coeff_lifts (p : S[X]) : p ∈ lifts f ↔ ∀ n : ℕ, p.coeff n ∈ Set.range f := by
rw [lifts_iff_ringHom_rangeS, mem_map_rangeS f]
rfl
#align polynomial.lifts_iff_coeff_lifts Polynomial.lifts_iff_coeff_lifts
/-- If `(r : R)`, then `C (f r)` lifts. -/
theorem C_mem_lifts (f : R →+* S) (r : R) : C (f r) ∈ lifts f :=
⟨C r, by
simp only [coe_mapRingHom, map_C, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true,
and_self_iff]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.C_mem_lifts Polynomial.C_mem_lifts
/-- If `(s : S)` is in the image of `f`, then `C s` lifts. -/
theorem C'_mem_lifts {f : R →+* S} {s : S} (h : s ∈ Set.range f) : C s ∈ lifts f := by
obtain ⟨r, rfl⟩ := Set.mem_range.1 h
use C r
simp only [coe_mapRingHom, map_C, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true,
and_self_iff]
set_option linter.uppercaseLean3 false in
#align polynomial.C'_mem_lifts Polynomial.C'_mem_lifts
/-- The polynomial `X` lifts. -/
theorem X_mem_lifts (f : R →+* S) : (X : S[X]) ∈ lifts f :=
⟨X, by
simp only [coe_mapRingHom, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true, map_X,
and_self_iff]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.X_mem_lifts Polynomial.X_mem_lifts
/-- The polynomial `X ^ n` lifts. -/
theorem X_pow_mem_lifts (f : R →+* S) (n : ℕ) : (X ^ n : S[X]) ∈ lifts f :=
⟨X ^ n, by
simp only [coe_mapRingHom, map_pow, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true,
map_X, and_self_iff]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.X_pow_mem_lifts Polynomial.X_pow_mem_lifts
/-- If `p` lifts and `(r : R)` then `r * p` lifts. -/
theorem base_mul_mem_lifts {p : S[X]} (r : R) (hp : p ∈ lifts f) : C (f r) * p ∈ lifts f := by
simp only [lifts, RingHom.mem_rangeS] at hp ⊢
obtain ⟨p₁, rfl⟩ := hp
use C r * p₁
simp only [coe_mapRingHom, map_C, map_mul]
#align polynomial.base_mul_mem_lifts Polynomial.base_mul_mem_lifts
/-- If `(s : S)` is in the image of `f`, then `monomial n s` lifts. -/
theorem monomial_mem_lifts {s : S} (n : ℕ) (h : s ∈ Set.range f) : monomial n s ∈ lifts f := by
obtain ⟨r, rfl⟩ := Set.mem_range.1 h
use monomial n r
simp only [coe_mapRingHom, Set.mem_univ, map_monomial, Subsemiring.coe_top, eq_self_iff_true,
and_self_iff]
#align polynomial.monomial_mem_lifts Polynomial.monomial_mem_lifts
/-- If `p` lifts then `p.erase n` lifts. -/
theorem erase_mem_lifts {p : S[X]} (n : ℕ) (h : p ∈ lifts f) : p.erase n ∈ lifts f := by
rw [lifts_iff_ringHom_rangeS, mem_map_rangeS] at h ⊢
intro k
by_cases hk : k = n
· use 0
simp only [hk, RingHom.map_zero, erase_same]
obtain ⟨i, hi⟩ := h k
use i
simp only [hi, hk, erase_ne, Ne, not_false_iff]
#align polynomial.erase_mem_lifts Polynomial.erase_mem_lifts
section LiftDeg
| Mathlib/Algebra/Polynomial/Lifts.lean | 141 | 162 | theorem monomial_mem_lifts_and_degree_eq {s : S} {n : ℕ} (hl : monomial n s ∈ lifts f) :
∃ q : R[X], map f q = monomial n s ∧ q.degree = (monomial n s).degree := by |
by_cases hzero : s = 0
· use 0
simp only [hzero, degree_zero, eq_self_iff_true, and_self_iff, monomial_zero_right,
Polynomial.map_zero]
rw [lifts_iff_set_range] at hl
obtain ⟨q, hq⟩ := hl
replace hq := (ext_iff.1 hq) n
have hcoeff : f (q.coeff n) = s := by
simp? [coeff_monomial] at hq says simp only [coeff_map, coeff_monomial, ↓reduceIte] at hq
exact hq
use monomial n (q.coeff n)
constructor
· simp only [hcoeff, map_monomial]
have hqzero : q.coeff n ≠ 0 := by
intro habs
simp only [habs, RingHom.map_zero] at hcoeff
exact hzero hcoeff.symm
rw [← C_mul_X_pow_eq_monomial]
rw [← C_mul_X_pow_eq_monomial]
simp only [hzero, hqzero, Ne, not_false_iff, degree_C_mul_X_pow]
|
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Mario Carneiro, Johannes Hölzl
-/
import Mathlib.Order.BoundedOrder
import Mathlib.Order.MinMax
import Mathlib.Algebra.NeZero
import Mathlib.Algebra.Order.Monoid.Defs
#align_import algebra.order.monoid.canonical.defs from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3"
/-!
# Canonically ordered monoids
-/
universe u
variable {α : Type u}
/-- An `OrderedCommMonoid` with one-sided 'division' in the sense that
if `a ≤ b`, there is some `c` for which `a * c = b`. This is a weaker version
of the condition on canonical orderings defined by `CanonicallyOrderedCommMonoid`. -/
class ExistsMulOfLE (α : Type u) [Mul α] [LE α] : Prop where
/-- For `a ≤ b`, `a` left divides `b` -/
exists_mul_of_le : ∀ {a b : α}, a ≤ b → ∃ c : α, b = a * c
#align has_exists_mul_of_le ExistsMulOfLE
/-- An `OrderedAddCommMonoid` with one-sided 'subtraction' in the sense that
if `a ≤ b`, then there is some `c` for which `a + c = b`. This is a weaker version
of the condition on canonical orderings defined by `CanonicallyOrderedAddCommMonoid`. -/
class ExistsAddOfLE (α : Type u) [Add α] [LE α] : Prop where
/-- For `a ≤ b`, there is a `c` so `b = a + c`. -/
exists_add_of_le : ∀ {a b : α}, a ≤ b → ∃ c : α, b = a + c
#align has_exists_add_of_le ExistsAddOfLE
attribute [to_additive] ExistsMulOfLE
export ExistsMulOfLE (exists_mul_of_le)
export ExistsAddOfLE (exists_add_of_le)
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) Group.existsMulOfLE (α : Type u) [Group α] [LE α] : ExistsMulOfLE α :=
⟨fun {a b} _ => ⟨a⁻¹ * b, (mul_inv_cancel_left _ _).symm⟩⟩
#align group.has_exists_mul_of_le Group.existsMulOfLE
#align add_group.has_exists_add_of_le AddGroup.existsAddOfLE
section MulOneClass
variable [MulOneClass α] [Preorder α] [ContravariantClass α α (· * ·) (· < ·)] [ExistsMulOfLE α]
{a b : α}
@[to_additive]
| Mathlib/Algebra/Order/Monoid/Canonical/Defs.lean | 56 | 58 | theorem exists_one_lt_mul_of_lt' (h : a < b) : ∃ c, 1 < c ∧ a * c = b := by |
obtain ⟨c, rfl⟩ := exists_mul_of_le h.le
exact ⟨c, one_lt_of_lt_mul_right h, 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. -/
| Mathlib/MeasureTheory/Integral/Bochner.lean | 380 | 393 | 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]
|
/-
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.Algebra.Algebra.Operations
import Mathlib.Data.Fintype.Lattice
import Mathlib.RingTheory.Coprime.Lemmas
#align_import ring_theory.ideal.operations from "leanprover-community/mathlib"@"e7f0ddbf65bd7181a85edb74b64bdc35ba4bdc74"
/-!
# More operations on modules and ideals
-/
assert_not_exists Basis -- See `RingTheory.Ideal.Basis`
assert_not_exists Submodule.hasQuotient -- See `RingTheory.Ideal.QuotientOperations`
universe u v w x
open Pointwise
namespace Submodule
variable {R : Type u} {M : Type v} {M' F G : Type*}
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M'] [Module R M']
open Pointwise
instance hasSMul' : SMul (Ideal R) (Submodule R M) :=
⟨Submodule.map₂ (LinearMap.lsmul R M)⟩
#align submodule.has_smul' Submodule.hasSMul'
/-- This duplicates the global `smul_eq_mul`, but doesn't have to unfold anywhere near as much to
apply. -/
protected theorem _root_.Ideal.smul_eq_mul (I J : Ideal R) : I • J = I * J :=
rfl
#align ideal.smul_eq_mul Ideal.smul_eq_mul
variable (R M) in
/-- `Module.annihilator R M` is the ideal of all elements `r : R` such that `r • M = 0`. -/
def _root_.Module.annihilator : Ideal R := LinearMap.ker (LinearMap.lsmul R M)
theorem _root_.Module.mem_annihilator {r} : r ∈ Module.annihilator R M ↔ ∀ m : M, r • m = 0 :=
⟨fun h ↦ (congr($h ·)), (LinearMap.ext ·)⟩
theorem _root_.LinearMap.annihilator_le_of_injective (f : M →ₗ[R] M') (hf : Function.Injective f) :
Module.annihilator R M' ≤ Module.annihilator R M := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢; exact fun m ↦ hf (by rw [map_smul, h, f.map_zero])
theorem _root_.LinearMap.annihilator_le_of_surjective (f : M →ₗ[R] M')
(hf : Function.Surjective f) : Module.annihilator R M ≤ Module.annihilator R M' := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢
intro m; obtain ⟨m, rfl⟩ := hf m
rw [← map_smul, h, f.map_zero]
theorem _root_.LinearEquiv.annihilator_eq (e : M ≃ₗ[R] M') :
Module.annihilator R M = Module.annihilator R M' :=
(e.annihilator_le_of_surjective e.surjective).antisymm (e.annihilator_le_of_injective e.injective)
/-- `N.annihilator` is the ideal of all elements `r : R` such that `r • N = 0`. -/
abbrev annihilator (N : Submodule R M) : Ideal R :=
Module.annihilator R N
#align submodule.annihilator Submodule.annihilator
theorem annihilator_top : (⊤ : Submodule R M).annihilator = Module.annihilator R M :=
topEquiv.annihilator_eq
variable {I J : Ideal R} {N P : Submodule R M}
theorem mem_annihilator {r} : r ∈ N.annihilator ↔ ∀ n ∈ N, r • n = (0 : M) := by
simp_rw [annihilator, Module.mem_annihilator, Subtype.forall, Subtype.ext_iff]; rfl
#align submodule.mem_annihilator Submodule.mem_annihilator
theorem mem_annihilator' {r} : r ∈ N.annihilator ↔ N ≤ comap (r • (LinearMap.id : M →ₗ[R] M)) ⊥ :=
mem_annihilator.trans ⟨fun H n hn => (mem_bot R).2 <| H n hn, fun H _ hn => (mem_bot R).1 <| H hn⟩
#align submodule.mem_annihilator' Submodule.mem_annihilator'
theorem mem_annihilator_span (s : Set M) (r : R) :
r ∈ (Submodule.span R s).annihilator ↔ ∀ n : s, r • (n : M) = 0 := by
rw [Submodule.mem_annihilator]
constructor
· intro h n
exact h _ (Submodule.subset_span n.prop)
· intro h n hn
refine Submodule.span_induction hn ?_ ?_ ?_ ?_
· intro x hx
exact h ⟨x, hx⟩
· exact smul_zero _
· intro x y hx hy
rw [smul_add, hx, hy, zero_add]
· intro a x hx
rw [smul_comm, hx, smul_zero]
#align submodule.mem_annihilator_span Submodule.mem_annihilator_span
theorem mem_annihilator_span_singleton (g : M) (r : R) :
r ∈ (Submodule.span R ({g} : Set M)).annihilator ↔ r • g = 0 := by simp [mem_annihilator_span]
#align submodule.mem_annihilator_span_singleton Submodule.mem_annihilator_span_singleton
theorem annihilator_bot : (⊥ : Submodule R M).annihilator = ⊤ :=
(Ideal.eq_top_iff_one _).2 <| mem_annihilator'.2 bot_le
#align submodule.annihilator_bot Submodule.annihilator_bot
theorem annihilator_eq_top_iff : N.annihilator = ⊤ ↔ N = ⊥ :=
⟨fun H =>
eq_bot_iff.2 fun (n : M) hn =>
(mem_bot R).2 <| one_smul R n ▸ mem_annihilator.1 ((Ideal.eq_top_iff_one _).1 H) n hn,
fun H => H.symm ▸ annihilator_bot⟩
#align submodule.annihilator_eq_top_iff Submodule.annihilator_eq_top_iff
theorem annihilator_mono (h : N ≤ P) : P.annihilator ≤ N.annihilator := fun _ hrp =>
mem_annihilator.2 fun n hn => mem_annihilator.1 hrp n <| h hn
#align submodule.annihilator_mono Submodule.annihilator_mono
theorem annihilator_iSup (ι : Sort w) (f : ι → Submodule R M) :
annihilator (⨆ i, f i) = ⨅ i, annihilator (f i) :=
le_antisymm (le_iInf fun _ => annihilator_mono <| le_iSup _ _) fun _ H =>
mem_annihilator'.2 <|
iSup_le fun i =>
have := (mem_iInf _).1 H i
mem_annihilator'.1 this
#align submodule.annihilator_supr Submodule.annihilator_iSup
theorem smul_mem_smul {r} {n} (hr : r ∈ I) (hn : n ∈ N) : r • n ∈ I • N :=
apply_mem_map₂ _ hr hn
#align submodule.smul_mem_smul Submodule.smul_mem_smul
theorem smul_le {P : Submodule R M} : I • N ≤ P ↔ ∀ r ∈ I, ∀ n ∈ N, r • n ∈ P :=
map₂_le
#align submodule.smul_le Submodule.smul_le
@[simp, norm_cast]
lemma coe_set_smul : (I : Set R) • N = I • N :=
Submodule.set_smul_eq_of_le _ _ _
(fun _ _ hr hx => smul_mem_smul hr hx)
(smul_le.mpr fun _ hr _ hx => mem_set_smul_of_mem_mem hr hx)
@[elab_as_elim]
theorem smul_induction_on {p : M → Prop} {x} (H : x ∈ I • N) (smul : ∀ r ∈ I, ∀ n ∈ N, p (r • n))
(add : ∀ x y, p x → p y → p (x + y)) : p x := by
have H0 : p 0 := by simpa only [zero_smul] using smul 0 I.zero_mem 0 N.zero_mem
refine Submodule.iSup_induction (x := x) _ H ?_ H0 add
rintro ⟨i, hi⟩ m ⟨j, hj, hj'⟩
rw [← hj']
exact smul _ hi _ hj
#align submodule.smul_induction_on Submodule.smul_induction_on
/-- Dependent version of `Submodule.smul_induction_on`. -/
@[elab_as_elim]
theorem smul_induction_on' {x : M} (hx : x ∈ I • N) {p : ∀ x, x ∈ I • N → Prop}
(smul : ∀ (r : R) (hr : r ∈ I) (n : M) (hn : n ∈ N), p (r • n) (smul_mem_smul hr hn))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›)) : p x hx := by
refine Exists.elim ?_ fun (h : x ∈ I • N) (H : p x h) => H
exact
smul_induction_on hx (fun a ha x hx => ⟨_, smul _ ha _ hx⟩) fun x y ⟨_, hx⟩ ⟨_, hy⟩ =>
⟨_, add _ _ _ _ hx hy⟩
#align submodule.smul_induction_on' Submodule.smul_induction_on'
theorem mem_smul_span_singleton {I : Ideal R} {m : M} {x : M} :
x ∈ I • span R ({m} : Set M) ↔ ∃ y ∈ I, y • m = x :=
⟨fun hx =>
smul_induction_on hx
(fun r hri n hnm =>
let ⟨s, hs⟩ := mem_span_singleton.1 hnm
⟨r * s, I.mul_mem_right _ hri, hs ▸ mul_smul r s m⟩)
fun m1 m2 ⟨y1, hyi1, hy1⟩ ⟨y2, hyi2, hy2⟩ =>
⟨y1 + y2, I.add_mem hyi1 hyi2, by rw [add_smul, hy1, hy2]⟩,
fun ⟨y, hyi, hy⟩ => hy ▸ smul_mem_smul hyi (subset_span <| Set.mem_singleton m)⟩
#align submodule.mem_smul_span_singleton Submodule.mem_smul_span_singleton
theorem smul_le_right : I • N ≤ N :=
smul_le.2 fun r _ _ => N.smul_mem r
#align submodule.smul_le_right Submodule.smul_le_right
theorem smul_mono (hij : I ≤ J) (hnp : N ≤ P) : I • N ≤ J • P :=
map₂_le_map₂ hij hnp
#align submodule.smul_mono Submodule.smul_mono
theorem smul_mono_left (h : I ≤ J) : I • N ≤ J • N :=
map₂_le_map₂_left h
#align submodule.smul_mono_left Submodule.smul_mono_left
instance : CovariantClass (Ideal R) (Submodule R M) HSMul.hSMul LE.le :=
⟨fun _ _ => map₂_le_map₂_right⟩
@[deprecated smul_mono_right (since := "2024-03-31")]
protected theorem smul_mono_right (h : N ≤ P) : I • N ≤ I • P :=
_root_.smul_mono_right I h
#align submodule.smul_mono_right Submodule.smul_mono_right
theorem map_le_smul_top (I : Ideal R) (f : R →ₗ[R] M) :
Submodule.map f I ≤ I • (⊤ : Submodule R M) := by
rintro _ ⟨y, hy, rfl⟩
rw [← mul_one y, ← smul_eq_mul, f.map_smul]
exact smul_mem_smul hy mem_top
#align submodule.map_le_smul_top Submodule.map_le_smul_top
@[simp]
theorem annihilator_smul (N : Submodule R M) : annihilator N • N = ⊥ :=
eq_bot_iff.2 (smul_le.2 fun _ => mem_annihilator.1)
#align submodule.annihilator_smul Submodule.annihilator_smul
@[simp]
theorem annihilator_mul (I : Ideal R) : annihilator I * I = ⊥ :=
annihilator_smul I
#align submodule.annihilator_mul Submodule.annihilator_mul
@[simp]
theorem mul_annihilator (I : Ideal R) : I * annihilator I = ⊥ := by rw [mul_comm, annihilator_mul]
#align submodule.mul_annihilator Submodule.mul_annihilator
variable (I J N P)
@[simp]
theorem smul_bot : I • (⊥ : Submodule R M) = ⊥ :=
map₂_bot_right _ _
#align submodule.smul_bot Submodule.smul_bot
@[simp]
theorem bot_smul : (⊥ : Ideal R) • N = ⊥ :=
map₂_bot_left _ _
#align submodule.bot_smul Submodule.bot_smul
@[simp]
theorem top_smul : (⊤ : Ideal R) • N = N :=
le_antisymm smul_le_right fun r hri => one_smul R r ▸ smul_mem_smul mem_top hri
#align submodule.top_smul Submodule.top_smul
theorem smul_sup : I • (N ⊔ P) = I • N ⊔ I • P :=
map₂_sup_right _ _ _ _
#align submodule.smul_sup Submodule.smul_sup
theorem sup_smul : (I ⊔ J) • N = I • N ⊔ J • N :=
map₂_sup_left _ _ _ _
#align submodule.sup_smul Submodule.sup_smul
protected theorem smul_assoc : (I • J) • N = I • J • N :=
le_antisymm
(smul_le.2 fun _ hrsij t htn =>
smul_induction_on hrsij
(fun r hr s hs =>
(@smul_eq_mul R _ r s).symm ▸ smul_smul r s t ▸ smul_mem_smul hr (smul_mem_smul hs htn))
fun x y => (add_smul x y t).symm ▸ Submodule.add_mem _)
(smul_le.2 fun r hr _ hsn =>
suffices J • N ≤ Submodule.comap (r • (LinearMap.id : M →ₗ[R] M)) ((I • J) • N) from this hsn
smul_le.2 fun s hs n hn =>
show r • s • n ∈ (I • J) • N from mul_smul r s n ▸ smul_mem_smul (smul_mem_smul hr hs) hn)
#align submodule.smul_assoc Submodule.smul_assoc
@[deprecated smul_inf_le (since := "2024-03-31")]
protected theorem smul_inf_le (M₁ M₂ : Submodule R M) :
I • (M₁ ⊓ M₂) ≤ I • M₁ ⊓ I • M₂ := smul_inf_le _ _ _
#align submodule.smul_inf_le Submodule.smul_inf_le
theorem smul_iSup {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} : I • iSup t = ⨆ i, I • t i :=
map₂_iSup_right _ _ _
#align submodule.smul_supr Submodule.smul_iSup
@[deprecated smul_iInf_le (since := "2024-03-31")]
protected theorem smul_iInf_le {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} :
I • iInf t ≤ ⨅ i, I • t i :=
smul_iInf_le
#align submodule.smul_infi_le Submodule.smul_iInf_le
variable (S : Set R) (T : Set M)
theorem span_smul_span : Ideal.span S • span R T = span R (⋃ (s ∈ S) (t ∈ T), {s • t}) :=
(map₂_span_span _ _ _ _).trans <| congr_arg _ <| Set.image2_eq_iUnion _ _ _
#align submodule.span_smul_span Submodule.span_smul_span
theorem ideal_span_singleton_smul (r : R) (N : Submodule R M) :
(Ideal.span {r} : Ideal R) • N = r • N := by
have : span R (⋃ (t : M) (_ : t ∈ N), {r • t}) = r • N := by
convert span_eq (r • N)
exact (Set.image_eq_iUnion _ (N : Set M)).symm
conv_lhs => rw [← span_eq N, span_smul_span]
simpa
#align submodule.ideal_span_singleton_smul Submodule.ideal_span_singleton_smul
theorem mem_of_span_top_of_smul_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤) (x : M)
(H : ∀ r : s, (r : R) • x ∈ M') : x ∈ M' := by
suffices (⊤ : Ideal R) • span R ({x} : Set M) ≤ M' by
rw [top_smul] at this
exact this (subset_span (Set.mem_singleton x))
rw [← hs, span_smul_span, span_le]
simpa using H
#align submodule.mem_of_span_top_of_smul_mem Submodule.mem_of_span_top_of_smul_mem
/-- Given `s`, a generating set of `R`, to check that an `x : M` falls in a
submodule `M'` of `x`, we only need to show that `r ^ n • x ∈ M'` for some `n` for each `r : s`. -/
theorem mem_of_span_eq_top_of_smul_pow_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤)
(x : M) (H : ∀ r : s, ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M') : x ∈ M' := by
obtain ⟨s', hs₁, hs₂⟩ := (Ideal.span_eq_top_iff_finite _).mp hs
replace H : ∀ r : s', ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M' := fun r => H ⟨_, hs₁ r.2⟩
choose n₁ n₂ using H
let N := s'.attach.sup n₁
have hs' := Ideal.span_pow_eq_top (s' : Set R) hs₂ N
apply M'.mem_of_span_top_of_smul_mem _ hs'
rintro ⟨_, r, hr, rfl⟩
convert M'.smul_mem (r ^ (N - n₁ ⟨r, hr⟩)) (n₂ ⟨r, hr⟩) using 1
simp only [Subtype.coe_mk, smul_smul, ← pow_add]
rw [tsub_add_cancel_of_le (Finset.le_sup (s'.mem_attach _) : n₁ ⟨r, hr⟩ ≤ N)]
#align submodule.mem_of_span_eq_top_of_smul_pow_mem Submodule.mem_of_span_eq_top_of_smul_pow_mem
variable {M' : Type w} [AddCommMonoid M'] [Module R M']
@[simp]
theorem map_smul'' (f : M →ₗ[R] M') : (I • N).map f = I • N.map f :=
le_antisymm
(map_le_iff_le_comap.2 <|
smul_le.2 fun r hr n hn =>
show f (r • n) ∈ I • N.map f from
(f.map_smul r n).symm ▸ smul_mem_smul hr (mem_map_of_mem hn)) <|
smul_le.2 fun r hr _ hn =>
let ⟨p, hp, hfp⟩ := mem_map.1 hn
hfp ▸ f.map_smul r p ▸ mem_map_of_mem (smul_mem_smul hr hp)
#align submodule.map_smul'' Submodule.map_smul''
open Pointwise in
@[simp]
theorem map_pointwise_smul (r : R) (N : Submodule R M) (f : M →ₗ[R] M') :
(r • N).map f = r • N.map f := by
simp_rw [← ideal_span_singleton_smul, map_smul'']
variable {I}
theorem mem_smul_span {s : Set M} {x : M} :
x ∈ I • Submodule.span R s ↔ x ∈ Submodule.span R (⋃ (a ∈ I) (b ∈ s), ({a • b} : Set M)) := by
rw [← I.span_eq, Submodule.span_smul_span, I.span_eq]
rfl
#align submodule.mem_smul_span Submodule.mem_smul_span
variable (I)
/-- If `x` is an `I`-multiple of the submodule spanned by `f '' s`,
then we can write `x` as an `I`-linear combination of the elements of `f '' s`. -/
theorem mem_ideal_smul_span_iff_exists_sum {ι : Type*} (f : ι → M) (x : M) :
x ∈ I • span R (Set.range f) ↔
∃ (a : ι →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
constructor; swap
· rintro ⟨a, ha, rfl⟩
exact Submodule.sum_mem _ fun c _ => smul_mem_smul (ha c) <| subset_span <| Set.mem_range_self _
refine fun hx => span_induction (mem_smul_span.mp hx) ?_ ?_ ?_ ?_
· simp only [Set.mem_iUnion, Set.mem_range, Set.mem_singleton_iff]
rintro x ⟨y, hy, x, ⟨i, rfl⟩, rfl⟩
refine ⟨Finsupp.single i y, fun j => ?_, ?_⟩
· letI := Classical.decEq ι
rw [Finsupp.single_apply]
split_ifs
· assumption
· exact I.zero_mem
refine @Finsupp.sum_single_index ι R M _ _ i _ (fun i y => y • f i) ?_
simp
· exact ⟨0, fun _ => I.zero_mem, Finsupp.sum_zero_index⟩
· rintro x y ⟨ax, hax, rfl⟩ ⟨ay, hay, rfl⟩
refine ⟨ax + ay, fun i => I.add_mem (hax i) (hay i), Finsupp.sum_add_index' ?_ ?_⟩ <;>
intros <;> simp only [zero_smul, add_smul]
· rintro c x ⟨a, ha, rfl⟩
refine ⟨c • a, fun i => I.mul_mem_left c (ha i), ?_⟩
rw [Finsupp.sum_smul_index, Finsupp.smul_sum] <;> intros <;> simp only [zero_smul, mul_smul]
#align submodule.mem_ideal_smul_span_iff_exists_sum Submodule.mem_ideal_smul_span_iff_exists_sum
theorem mem_ideal_smul_span_iff_exists_sum' {ι : Type*} (s : Set ι) (f : ι → M) (x : M) :
x ∈ I • span R (f '' s) ↔
∃ (a : s →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
rw [← Submodule.mem_ideal_smul_span_iff_exists_sum, ← Set.image_eq_range]
#align submodule.mem_ideal_smul_span_iff_exists_sum' Submodule.mem_ideal_smul_span_iff_exists_sum'
theorem mem_smul_top_iff (N : Submodule R M) (x : N) :
x ∈ I • (⊤ : Submodule R N) ↔ (x : M) ∈ I • N := by
change _ ↔ N.subtype x ∈ I • N
have : Submodule.map N.subtype (I • ⊤) = I • N := by
rw [Submodule.map_smul'', Submodule.map_top, Submodule.range_subtype]
rw [← this]
exact (Function.Injective.mem_set_image N.injective_subtype).symm
#align submodule.mem_smul_top_iff Submodule.mem_smul_top_iff
@[simp]
theorem smul_comap_le_comap_smul (f : M →ₗ[R] M') (S : Submodule R M') (I : Ideal R) :
I • S.comap f ≤ (I • S).comap f := by
refine Submodule.smul_le.mpr fun r hr x hx => ?_
rw [Submodule.mem_comap] at hx ⊢
rw [f.map_smul]
exact Submodule.smul_mem_smul hr hx
#align submodule.smul_comap_le_comap_smul Submodule.smul_comap_le_comap_smul
end CommSemiring
end Submodule
namespace Ideal
section Add
variable {R : Type u} [Semiring R]
@[simp]
theorem add_eq_sup {I J : Ideal R} : I + J = I ⊔ J :=
rfl
#align ideal.add_eq_sup Ideal.add_eq_sup
@[simp]
theorem zero_eq_bot : (0 : Ideal R) = ⊥ :=
rfl
#align ideal.zero_eq_bot Ideal.zero_eq_bot
@[simp]
theorem sum_eq_sup {ι : Type*} (s : Finset ι) (f : ι → Ideal R) : s.sum f = s.sup f :=
rfl
#align ideal.sum_eq_sup Ideal.sum_eq_sup
end Add
section MulAndRadical
variable {R : Type u} {ι : Type*} [CommSemiring R]
variable {I J K L : Ideal R}
instance : Mul (Ideal R) :=
⟨(· • ·)⟩
@[simp]
theorem one_eq_top : (1 : Ideal R) = ⊤ := by erw [Submodule.one_eq_range, LinearMap.range_id]
#align ideal.one_eq_top Ideal.one_eq_top
theorem add_eq_one_iff : I + J = 1 ↔ ∃ i ∈ I, ∃ j ∈ J, i + j = 1 := by
rw [one_eq_top, eq_top_iff_one, add_eq_sup, Submodule.mem_sup]
theorem mul_mem_mul {r s} (hr : r ∈ I) (hs : s ∈ J) : r * s ∈ I * J :=
Submodule.smul_mem_smul hr hs
#align ideal.mul_mem_mul Ideal.mul_mem_mul
theorem mul_mem_mul_rev {r s} (hr : r ∈ I) (hs : s ∈ J) : s * r ∈ I * J :=
mul_comm r s ▸ mul_mem_mul hr hs
#align ideal.mul_mem_mul_rev Ideal.mul_mem_mul_rev
theorem pow_mem_pow {x : R} (hx : x ∈ I) (n : ℕ) : x ^ n ∈ I ^ n :=
Submodule.pow_mem_pow _ hx _
#align ideal.pow_mem_pow Ideal.pow_mem_pow
theorem prod_mem_prod {ι : Type*} {s : Finset ι} {I : ι → Ideal R} {x : ι → R} :
(∀ i ∈ s, x i ∈ I i) → (∏ i ∈ s, x i) ∈ ∏ i ∈ s, I i := by
classical
refine Finset.induction_on s ?_ ?_
· intro
rw [Finset.prod_empty, Finset.prod_empty, one_eq_top]
exact Submodule.mem_top
· intro a s ha IH h
rw [Finset.prod_insert ha, Finset.prod_insert ha]
exact
mul_mem_mul (h a <| Finset.mem_insert_self a s)
(IH fun i hi => h i <| Finset.mem_insert_of_mem hi)
#align ideal.prod_mem_prod Ideal.prod_mem_prod
theorem mul_le : I * J ≤ K ↔ ∀ r ∈ I, ∀ s ∈ J, r * s ∈ K :=
Submodule.smul_le
#align ideal.mul_le Ideal.mul_le
theorem mul_le_left : I * J ≤ J :=
Ideal.mul_le.2 fun _ _ _ => J.mul_mem_left _
#align ideal.mul_le_left Ideal.mul_le_left
theorem mul_le_right : I * J ≤ I :=
Ideal.mul_le.2 fun _ hr _ _ => I.mul_mem_right _ hr
#align ideal.mul_le_right Ideal.mul_le_right
@[simp]
theorem sup_mul_right_self : I ⊔ I * J = I :=
sup_eq_left.2 Ideal.mul_le_right
#align ideal.sup_mul_right_self Ideal.sup_mul_right_self
@[simp]
theorem sup_mul_left_self : I ⊔ J * I = I :=
sup_eq_left.2 Ideal.mul_le_left
#align ideal.sup_mul_left_self Ideal.sup_mul_left_self
@[simp]
theorem mul_right_self_sup : I * J ⊔ I = I :=
sup_eq_right.2 Ideal.mul_le_right
#align ideal.mul_right_self_sup Ideal.mul_right_self_sup
@[simp]
theorem mul_left_self_sup : J * I ⊔ I = I :=
sup_eq_right.2 Ideal.mul_le_left
#align ideal.mul_left_self_sup Ideal.mul_left_self_sup
variable (I J K)
protected theorem mul_comm : I * J = J * I :=
le_antisymm (mul_le.2 fun _ hrI _ hsJ => mul_mem_mul_rev hsJ hrI)
(mul_le.2 fun _ hrJ _ hsI => mul_mem_mul_rev hsI hrJ)
#align ideal.mul_comm Ideal.mul_comm
protected theorem mul_assoc : I * J * K = I * (J * K) :=
Submodule.smul_assoc I J K
#align ideal.mul_assoc Ideal.mul_assoc
theorem span_mul_span (S T : Set R) : span S * span T = span (⋃ (s ∈ S) (t ∈ T), {s * t}) :=
Submodule.span_smul_span S T
#align ideal.span_mul_span Ideal.span_mul_span
variable {I J K}
theorem span_mul_span' (S T : Set R) : span S * span T = span (S * T) := by
unfold span
rw [Submodule.span_mul_span]
#align ideal.span_mul_span' Ideal.span_mul_span'
theorem span_singleton_mul_span_singleton (r s : R) :
span {r} * span {s} = (span {r * s} : Ideal R) := by
unfold span
rw [Submodule.span_mul_span, Set.singleton_mul_singleton]
#align ideal.span_singleton_mul_span_singleton Ideal.span_singleton_mul_span_singleton
theorem span_singleton_pow (s : R) (n : ℕ) : span {s} ^ n = (span {s ^ n} : Ideal R) := by
induction' n with n ih; · simp [Set.singleton_one]
simp only [pow_succ, ih, span_singleton_mul_span_singleton]
#align ideal.span_singleton_pow Ideal.span_singleton_pow
theorem mem_mul_span_singleton {x y : R} {I : Ideal R} : x ∈ I * span {y} ↔ ∃ z ∈ I, z * y = x :=
Submodule.mem_smul_span_singleton
#align ideal.mem_mul_span_singleton Ideal.mem_mul_span_singleton
theorem mem_span_singleton_mul {x y : R} {I : Ideal R} : x ∈ span {y} * I ↔ ∃ z ∈ I, y * z = x := by
simp only [mul_comm, mem_mul_span_singleton]
#align ideal.mem_span_singleton_mul Ideal.mem_span_singleton_mul
theorem le_span_singleton_mul_iff {x : R} {I J : Ideal R} :
I ≤ span {x} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI :=
show (∀ {zI} (_ : zI ∈ I), zI ∈ span {x} * J) ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI by
simp only [mem_span_singleton_mul]
#align ideal.le_span_singleton_mul_iff Ideal.le_span_singleton_mul_iff
theorem span_singleton_mul_le_iff {x : R} {I J : Ideal R} :
span {x} * I ≤ J ↔ ∀ z ∈ I, x * z ∈ J := by
simp only [mul_le, mem_span_singleton_mul, mem_span_singleton]
constructor
· intro h zI hzI
exact h x (dvd_refl x) zI hzI
· rintro h _ ⟨z, rfl⟩ zI hzI
rw [mul_comm x z, mul_assoc]
exact J.mul_mem_left _ (h zI hzI)
#align ideal.span_singleton_mul_le_iff Ideal.span_singleton_mul_le_iff
theorem span_singleton_mul_le_span_singleton_mul {x y : R} {I J : Ideal R} :
span {x} * I ≤ span {y} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ := by
simp only [span_singleton_mul_le_iff, mem_span_singleton_mul, eq_comm]
#align ideal.span_singleton_mul_le_span_singleton_mul Ideal.span_singleton_mul_le_span_singleton_mul
theorem span_singleton_mul_right_mono [IsDomain R] {x : R} (hx : x ≠ 0) :
span {x} * I ≤ span {x} * J ↔ I ≤ J := by
simp_rw [span_singleton_mul_le_span_singleton_mul, mul_right_inj' hx,
exists_eq_right', SetLike.le_def]
#align ideal.span_singleton_mul_right_mono Ideal.span_singleton_mul_right_mono
theorem span_singleton_mul_left_mono [IsDomain R] {x : R} (hx : x ≠ 0) :
I * span {x} ≤ J * span {x} ↔ I ≤ J := by
simpa only [mul_comm I, mul_comm J] using span_singleton_mul_right_mono hx
#align ideal.span_singleton_mul_left_mono Ideal.span_singleton_mul_left_mono
theorem span_singleton_mul_right_inj [IsDomain R] {x : R} (hx : x ≠ 0) :
span {x} * I = span {x} * J ↔ I = J := by
simp only [le_antisymm_iff, span_singleton_mul_right_mono hx]
#align ideal.span_singleton_mul_right_inj Ideal.span_singleton_mul_right_inj
theorem span_singleton_mul_left_inj [IsDomain R] {x : R} (hx : x ≠ 0) :
I * span {x} = J * span {x} ↔ I = J := by
simp only [le_antisymm_iff, span_singleton_mul_left_mono hx]
#align ideal.span_singleton_mul_left_inj Ideal.span_singleton_mul_left_inj
theorem span_singleton_mul_right_injective [IsDomain R] {x : R} (hx : x ≠ 0) :
Function.Injective ((span {x} : Ideal R) * ·) := fun _ _ =>
(span_singleton_mul_right_inj hx).mp
#align ideal.span_singleton_mul_right_injective Ideal.span_singleton_mul_right_injective
theorem span_singleton_mul_left_injective [IsDomain R] {x : R} (hx : x ≠ 0) :
Function.Injective fun I : Ideal R => I * span {x} := fun _ _ =>
(span_singleton_mul_left_inj hx).mp
#align ideal.span_singleton_mul_left_injective Ideal.span_singleton_mul_left_injective
theorem eq_span_singleton_mul {x : R} (I J : Ideal R) :
I = span {x} * J ↔ (∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI) ∧ ∀ z ∈ J, x * z ∈ I := by
simp only [le_antisymm_iff, le_span_singleton_mul_iff, span_singleton_mul_le_iff]
#align ideal.eq_span_singleton_mul Ideal.eq_span_singleton_mul
theorem span_singleton_mul_eq_span_singleton_mul {x y : R} (I J : Ideal R) :
span {x} * I = span {y} * J ↔
(∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ) ∧ ∀ zJ ∈ J, ∃ zI ∈ I, x * zI = y * zJ := by
simp only [le_antisymm_iff, span_singleton_mul_le_span_singleton_mul, eq_comm]
#align ideal.span_singleton_mul_eq_span_singleton_mul Ideal.span_singleton_mul_eq_span_singleton_mul
theorem prod_span {ι : Type*} (s : Finset ι) (I : ι → Set R) :
(∏ i ∈ s, Ideal.span (I i)) = Ideal.span (∏ i ∈ s, I i) :=
Submodule.prod_span s I
#align ideal.prod_span Ideal.prod_span
theorem prod_span_singleton {ι : Type*} (s : Finset ι) (I : ι → R) :
(∏ i ∈ s, Ideal.span ({I i} : Set R)) = Ideal.span {∏ i ∈ s, I i} :=
Submodule.prod_span_singleton s I
#align ideal.prod_span_singleton Ideal.prod_span_singleton
@[simp]
theorem multiset_prod_span_singleton (m : Multiset R) :
(m.map fun x => Ideal.span {x}).prod = Ideal.span ({Multiset.prod m} : Set R) :=
Multiset.induction_on m (by simp) fun a m ih => by
simp only [Multiset.map_cons, Multiset.prod_cons, ih, ← Ideal.span_singleton_mul_span_singleton]
#align ideal.multiset_prod_span_singleton Ideal.multiset_prod_span_singleton
theorem finset_inf_span_singleton {ι : Type*} (s : Finset ι) (I : ι → R)
(hI : Set.Pairwise (↑s) (IsCoprime on I)) :
(s.inf fun i => Ideal.span ({I i} : Set R)) = Ideal.span {∏ i ∈ s, I i} := by
ext x
simp only [Submodule.mem_finset_inf, Ideal.mem_span_singleton]
exact ⟨Finset.prod_dvd_of_coprime hI, fun h i hi => (Finset.dvd_prod_of_mem _ hi).trans h⟩
#align ideal.finset_inf_span_singleton Ideal.finset_inf_span_singleton
theorem iInf_span_singleton {ι : Type*} [Fintype ι] {I : ι → R}
(hI : ∀ (i j) (_ : i ≠ j), IsCoprime (I i) (I j)) :
⨅ i, span ({I i} : Set R) = span {∏ i, I i} := by
rw [← Finset.inf_univ_eq_iInf, finset_inf_span_singleton]
rwa [Finset.coe_univ, Set.pairwise_univ]
#align ideal.infi_span_singleton Ideal.iInf_span_singleton
theorem iInf_span_singleton_natCast {R : Type*} [CommRing R] {ι : Type*} [Fintype ι]
{I : ι → ℕ} (hI : Pairwise fun i j => (I i).Coprime (I j)) :
⨅ (i : ι), span {(I i : R)} = span {((∏ i : ι, I i : ℕ) : R)} := by
rw [iInf_span_singleton, Nat.cast_prod]
exact fun i j h ↦ (hI h).cast
theorem sup_eq_top_iff_isCoprime {R : Type*} [CommSemiring R] (x y : R) :
span ({x} : Set R) ⊔ span {y} = ⊤ ↔ IsCoprime x y := by
rw [eq_top_iff_one, Submodule.mem_sup]
constructor
· rintro ⟨u, hu, v, hv, h1⟩
rw [mem_span_singleton'] at hu hv
rw [← hu.choose_spec, ← hv.choose_spec] at h1
exact ⟨_, _, h1⟩
· exact fun ⟨u, v, h1⟩ =>
⟨_, mem_span_singleton'.mpr ⟨_, rfl⟩, _, mem_span_singleton'.mpr ⟨_, rfl⟩, h1⟩
#align ideal.sup_eq_top_iff_is_coprime Ideal.sup_eq_top_iff_isCoprime
theorem mul_le_inf : I * J ≤ I ⊓ J :=
mul_le.2 fun r hri s hsj => ⟨I.mul_mem_right s hri, J.mul_mem_left r hsj⟩
#align ideal.mul_le_inf Ideal.mul_le_inf
theorem multiset_prod_le_inf {s : Multiset (Ideal R)} : s.prod ≤ s.inf := by
classical
refine s.induction_on ?_ ?_
· rw [Multiset.inf_zero]
exact le_top
intro a s ih
rw [Multiset.prod_cons, Multiset.inf_cons]
exact le_trans mul_le_inf (inf_le_inf le_rfl ih)
#align ideal.multiset_prod_le_inf Ideal.multiset_prod_le_inf
theorem prod_le_inf {s : Finset ι} {f : ι → Ideal R} : s.prod f ≤ s.inf f :=
multiset_prod_le_inf
#align ideal.prod_le_inf Ideal.prod_le_inf
theorem mul_eq_inf_of_coprime (h : I ⊔ J = ⊤) : I * J = I ⊓ J :=
le_antisymm mul_le_inf fun r ⟨hri, hrj⟩ =>
let ⟨s, hsi, t, htj, hst⟩ := Submodule.mem_sup.1 ((eq_top_iff_one _).1 h)
mul_one r ▸
hst ▸
(mul_add r s t).symm ▸ Ideal.add_mem (I * J) (mul_mem_mul_rev hsi hrj) (mul_mem_mul hri htj)
#align ideal.mul_eq_inf_of_coprime Ideal.mul_eq_inf_of_coprime
theorem sup_mul_eq_of_coprime_left (h : I ⊔ J = ⊤) : I ⊔ J * K = I ⊔ K :=
le_antisymm (sup_le_sup_left mul_le_left _) fun i hi => by
rw [eq_top_iff_one] at h; rw [Submodule.mem_sup] at h hi ⊢
obtain ⟨i1, hi1, j, hj, h⟩ := h; obtain ⟨i', hi', k, hk, hi⟩ := hi
refine ⟨_, add_mem hi' (mul_mem_right k _ hi1), _, mul_mem_mul hj hk, ?_⟩
rw [add_assoc, ← add_mul, h, one_mul, hi]
#align ideal.sup_mul_eq_of_coprime_left Ideal.sup_mul_eq_of_coprime_left
theorem sup_mul_eq_of_coprime_right (h : I ⊔ K = ⊤) : I ⊔ J * K = I ⊔ J := by
rw [mul_comm]
exact sup_mul_eq_of_coprime_left h
#align ideal.sup_mul_eq_of_coprime_right Ideal.sup_mul_eq_of_coprime_right
theorem mul_sup_eq_of_coprime_left (h : I ⊔ J = ⊤) : I * K ⊔ J = K ⊔ J := by
rw [sup_comm] at h
rw [sup_comm, sup_mul_eq_of_coprime_left h, sup_comm]
#align ideal.mul_sup_eq_of_coprime_left Ideal.mul_sup_eq_of_coprime_left
theorem mul_sup_eq_of_coprime_right (h : K ⊔ J = ⊤) : I * K ⊔ J = I ⊔ J := by
rw [sup_comm] at h
rw [sup_comm, sup_mul_eq_of_coprime_right h, sup_comm]
#align ideal.mul_sup_eq_of_coprime_right Ideal.mul_sup_eq_of_coprime_right
theorem sup_prod_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → I ⊔ J i = ⊤) :
(I ⊔ ∏ i ∈ s, J i) = ⊤ :=
Finset.prod_induction _ (fun J => I ⊔ J = ⊤)
(fun J K hJ hK => (sup_mul_eq_of_coprime_left hJ).trans hK)
(by simp_rw [one_eq_top, sup_top_eq]) h
#align ideal.sup_prod_eq_top Ideal.sup_prod_eq_top
theorem sup_iInf_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → I ⊔ J i = ⊤) :
(I ⊔ ⨅ i ∈ s, J i) = ⊤ :=
eq_top_iff.mpr <|
le_of_eq_of_le (sup_prod_eq_top h).symm <|
sup_le_sup_left (le_of_le_of_eq prod_le_inf <| Finset.inf_eq_iInf _ _) _
#align ideal.sup_infi_eq_top Ideal.sup_iInf_eq_top
theorem prod_sup_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → J i ⊔ I = ⊤) :
(∏ i ∈ s, J i) ⊔ I = ⊤ := by rw [sup_comm, sup_prod_eq_top]; intro i hi; rw [sup_comm, h i hi]
#align ideal.prod_sup_eq_top Ideal.prod_sup_eq_top
theorem iInf_sup_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → J i ⊔ I = ⊤) :
(⨅ i ∈ s, J i) ⊔ I = ⊤ := by rw [sup_comm, sup_iInf_eq_top]; intro i hi; rw [sup_comm, h i hi]
#align ideal.infi_sup_eq_top Ideal.iInf_sup_eq_top
theorem sup_pow_eq_top {n : ℕ} (h : I ⊔ J = ⊤) : I ⊔ J ^ n = ⊤ := by
rw [← Finset.card_range n, ← Finset.prod_const]
exact sup_prod_eq_top fun _ _ => h
#align ideal.sup_pow_eq_top Ideal.sup_pow_eq_top
theorem pow_sup_eq_top {n : ℕ} (h : I ⊔ J = ⊤) : I ^ n ⊔ J = ⊤ := by
rw [← Finset.card_range n, ← Finset.prod_const]
exact prod_sup_eq_top fun _ _ => h
#align ideal.pow_sup_eq_top Ideal.pow_sup_eq_top
theorem pow_sup_pow_eq_top {m n : ℕ} (h : I ⊔ J = ⊤) : I ^ m ⊔ J ^ n = ⊤ :=
sup_pow_eq_top (pow_sup_eq_top h)
#align ideal.pow_sup_pow_eq_top Ideal.pow_sup_pow_eq_top
variable (I)
-- @[simp] -- Porting note (#10618): simp can prove this
theorem mul_bot : I * ⊥ = ⊥ := by simp
#align ideal.mul_bot Ideal.mul_bot
-- @[simp] -- Porting note (#10618): simp can prove thisrove this
theorem bot_mul : ⊥ * I = ⊥ := by simp
#align ideal.bot_mul Ideal.bot_mul
@[simp]
theorem mul_top : I * ⊤ = I :=
Ideal.mul_comm ⊤ I ▸ Submodule.top_smul I
#align ideal.mul_top Ideal.mul_top
@[simp]
theorem top_mul : ⊤ * I = I :=
Submodule.top_smul I
#align ideal.top_mul Ideal.top_mul
variable {I}
theorem mul_mono (hik : I ≤ K) (hjl : J ≤ L) : I * J ≤ K * L :=
Submodule.smul_mono hik hjl
#align ideal.mul_mono Ideal.mul_mono
theorem mul_mono_left (h : I ≤ J) : I * K ≤ J * K :=
Submodule.smul_mono_left h
#align ideal.mul_mono_left Ideal.mul_mono_left
theorem mul_mono_right (h : J ≤ K) : I * J ≤ I * K :=
smul_mono_right _ h
#align ideal.mul_mono_right Ideal.mul_mono_right
variable (I J K)
theorem mul_sup : I * (J ⊔ K) = I * J ⊔ I * K :=
Submodule.smul_sup I J K
#align ideal.mul_sup Ideal.mul_sup
theorem sup_mul : (I ⊔ J) * K = I * K ⊔ J * K :=
Submodule.sup_smul I J K
#align ideal.sup_mul Ideal.sup_mul
variable {I J K}
theorem pow_le_pow_right {m n : ℕ} (h : m ≤ n) : I ^ n ≤ I ^ m := by
cases' Nat.exists_eq_add_of_le h with k hk
rw [hk, pow_add]
exact le_trans mul_le_inf inf_le_left
#align ideal.pow_le_pow_right Ideal.pow_le_pow_right
theorem pow_le_self {n : ℕ} (hn : n ≠ 0) : I ^ n ≤ I :=
calc
I ^ n ≤ I ^ 1 := pow_le_pow_right (Nat.pos_of_ne_zero hn)
_ = I := pow_one _
#align ideal.pow_le_self Ideal.pow_le_self
theorem pow_right_mono {I J : Ideal R} (e : I ≤ J) (n : ℕ) : I ^ n ≤ J ^ n := by
induction' n with _ hn
· rw [pow_zero, pow_zero]
· rw [pow_succ, pow_succ]
exact Ideal.mul_mono hn e
#align ideal.pow_right_mono Ideal.pow_right_mono
@[simp]
theorem mul_eq_bot {R : Type*} [CommSemiring R] [NoZeroDivisors R] {I J : Ideal R} :
I * J = ⊥ ↔ I = ⊥ ∨ J = ⊥ :=
⟨fun hij =>
or_iff_not_imp_left.mpr fun I_ne_bot =>
J.eq_bot_iff.mpr fun j hj =>
let ⟨i, hi, ne0⟩ := I.ne_bot_iff.mp I_ne_bot
Or.resolve_left (mul_eq_zero.mp ((I * J).eq_bot_iff.mp hij _ (mul_mem_mul hi hj))) ne0,
fun h => by cases' h with h h <;> rw [← Ideal.mul_bot, h, Ideal.mul_comm]⟩
#align ideal.mul_eq_bot Ideal.mul_eq_bot
instance {R : Type*} [CommSemiring R] [NoZeroDivisors R] : NoZeroDivisors (Ideal R) where
eq_zero_or_eq_zero_of_mul_eq_zero := mul_eq_bot.1
instance {R : Type*} [CommSemiring R] {S : Type*} [CommRing S] [Algebra R S]
[NoZeroSMulDivisors R S] {I : Ideal S} : NoZeroSMulDivisors R I :=
Submodule.noZeroSMulDivisors (Submodule.restrictScalars R I)
/-- A product of ideals in an integral domain is zero if and only if one of the terms is zero. -/
@[simp]
lemma multiset_prod_eq_bot {R : Type*} [CommRing R] [IsDomain R] {s : Multiset (Ideal R)} :
s.prod = ⊥ ↔ ⊥ ∈ s :=
Multiset.prod_eq_zero_iff
/-- A product of ideals in an integral domain is zero if and only if one of the terms is zero. -/
@[deprecated multiset_prod_eq_bot (since := "2023-12-26")]
theorem prod_eq_bot {R : Type*} [CommRing R] [IsDomain R] {s : Multiset (Ideal R)} :
s.prod = ⊥ ↔ ∃ I ∈ s, I = ⊥ := by
simp
#align ideal.prod_eq_bot Ideal.prod_eq_bot
theorem span_pair_mul_span_pair (w x y z : R) :
(span {w, x} : Ideal R) * span {y, z} = span {w * y, w * z, x * y, x * z} := by
simp_rw [span_insert, sup_mul, mul_sup, span_singleton_mul_span_singleton, sup_assoc]
#align ideal.span_pair_mul_span_pair Ideal.span_pair_mul_span_pair
theorem isCoprime_iff_codisjoint : IsCoprime I J ↔ Codisjoint I J := by
rw [IsCoprime, codisjoint_iff]
constructor
· rintro ⟨x, y, hxy⟩
rw [eq_top_iff_one]
apply (show x * I + y * J ≤ I ⊔ J from
sup_le (mul_le_left.trans le_sup_left) (mul_le_left.trans le_sup_right))
rw [hxy]
simp only [one_eq_top, Submodule.mem_top]
· intro h
refine ⟨1, 1, ?_⟩
simpa only [one_eq_top, top_mul, Submodule.add_eq_sup]
theorem isCoprime_iff_add : IsCoprime I J ↔ I + J = 1 := by
rw [isCoprime_iff_codisjoint, codisjoint_iff, add_eq_sup, one_eq_top]
theorem isCoprime_iff_exists : IsCoprime I J ↔ ∃ i ∈ I, ∃ j ∈ J, i + j = 1 := by
rw [← add_eq_one_iff, isCoprime_iff_add]
theorem isCoprime_iff_sup_eq : IsCoprime I J ↔ I ⊔ J = ⊤ := by
rw [isCoprime_iff_codisjoint, codisjoint_iff]
open List in
theorem isCoprime_tfae : TFAE [IsCoprime I J, Codisjoint I J, I + J = 1,
∃ i ∈ I, ∃ j ∈ J, i + j = 1, I ⊔ J = ⊤] := by
rw [← isCoprime_iff_codisjoint, ← isCoprime_iff_add, ← isCoprime_iff_exists,
← isCoprime_iff_sup_eq]
simp
theorem _root_.IsCoprime.codisjoint (h : IsCoprime I J) : Codisjoint I J :=
isCoprime_iff_codisjoint.mp h
theorem _root_.IsCoprime.add_eq (h : IsCoprime I J) : I + J = 1 := isCoprime_iff_add.mp h
theorem _root_.IsCoprime.exists (h : IsCoprime I J) : ∃ i ∈ I, ∃ j ∈ J, i + j = 1 :=
isCoprime_iff_exists.mp h
theorem _root_.IsCoprime.sup_eq (h : IsCoprime I J) : I ⊔ J = ⊤ := isCoprime_iff_sup_eq.mp h
theorem inf_eq_mul_of_isCoprime (coprime : IsCoprime I J) : I ⊓ J = I * J :=
(Ideal.mul_eq_inf_of_coprime coprime.sup_eq).symm
#align ideal.inf_eq_mul_of_coprime Ideal.inf_eq_mul_of_isCoprime
@[deprecated (since := "2024-05-28")]
alias inf_eq_mul_of_coprime := inf_eq_mul_of_isCoprime
theorem isCoprime_span_singleton_iff (x y : R) :
IsCoprime (span <| singleton x) (span <| singleton y) ↔ IsCoprime x y := by
simp_rw [isCoprime_iff_codisjoint, codisjoint_iff, eq_top_iff_one, mem_span_singleton_sup,
mem_span_singleton]
constructor
· rintro ⟨a, _, ⟨b, rfl⟩, e⟩; exact ⟨a, b, mul_comm b y ▸ e⟩
· rintro ⟨a, b, e⟩; exact ⟨a, _, ⟨b, rfl⟩, mul_comm y b ▸ e⟩
theorem isCoprime_biInf {J : ι → Ideal R} {s : Finset ι}
(hf : ∀ j ∈ s, IsCoprime I (J j)) : IsCoprime I (⨅ j ∈ s, J j) := by
classical
simp_rw [isCoprime_iff_add] at *
induction s using Finset.induction with
| empty =>
simp
| @insert i s _ hs =>
rw [Finset.iInf_insert, inf_comm, one_eq_top, eq_top_iff, ← one_eq_top]
set K := ⨅ j ∈ s, J j
calc
1 = I + K := (hs fun j hj ↦ hf j (Finset.mem_insert_of_mem hj)).symm
_ = I + K*(I + J i) := by rw [hf i (Finset.mem_insert_self i s), mul_one]
_ = (1+K)*I + K*J i := by ring
_ ≤ I + K ⊓ J i := add_le_add mul_le_left mul_le_inf
/-- The radical of an ideal `I` consists of the elements `r` such that `r ^ n ∈ I` for some `n`. -/
def radical (I : Ideal R) : Ideal R where
carrier := { r | ∃ n : ℕ, r ^ n ∈ I }
zero_mem' := ⟨1, (pow_one (0 : R)).symm ▸ I.zero_mem⟩
add_mem' := fun {_ _} ⟨m, hxmi⟩ ⟨n, hyni⟩ =>
⟨m + n - 1, add_pow_add_pred_mem_of_pow_mem I hxmi hyni⟩
smul_mem' {r s} := fun ⟨n, h⟩ ↦ ⟨n, (mul_pow r s n).symm ▸ I.mul_mem_left (r ^ n) h⟩
#align ideal.radical Ideal.radical
theorem mem_radical_iff {r : R} : r ∈ I.radical ↔ ∃ n : ℕ, r ^ n ∈ I := Iff.rfl
/-- An ideal is radical if it contains its radical. -/
def IsRadical (I : Ideal R) : Prop :=
I.radical ≤ I
#align ideal.is_radical Ideal.IsRadical
theorem le_radical : I ≤ radical I := fun r hri => ⟨1, (pow_one r).symm ▸ hri⟩
#align ideal.le_radical Ideal.le_radical
/-- An ideal is radical iff it is equal to its radical. -/
theorem radical_eq_iff : I.radical = I ↔ I.IsRadical := by
rw [le_antisymm_iff, and_iff_left le_radical, IsRadical]
#align ideal.radical_eq_iff Ideal.radical_eq_iff
alias ⟨_, IsRadical.radical⟩ := radical_eq_iff
#align ideal.is_radical.radical Ideal.IsRadical.radical
theorem isRadical_iff_pow_one_lt (k : ℕ) (hk : 1 < k) : I.IsRadical ↔ ∀ r, r ^ k ∈ I → r ∈ I :=
⟨fun h _r hr ↦ h ⟨k, hr⟩, fun h x ⟨n, hx⟩ ↦
k.pow_imp_self_of_one_lt hk _ (fun _ _ ↦ .inr ∘ I.smul_mem _) h n x hx⟩
variable (R)
theorem radical_top : (radical ⊤ : Ideal R) = ⊤ :=
(eq_top_iff_one _).2 ⟨0, Submodule.mem_top⟩
#align ideal.radical_top Ideal.radical_top
variable {R}
theorem radical_mono (H : I ≤ J) : radical I ≤ radical J := fun _ ⟨n, hrni⟩ => ⟨n, H hrni⟩
#align ideal.radical_mono Ideal.radical_mono
variable (I)
theorem radical_isRadical : (radical I).IsRadical := fun r ⟨n, k, hrnki⟩ =>
⟨n * k, (pow_mul r n k).symm ▸ hrnki⟩
#align ideal.radical_is_radical Ideal.radical_isRadical
@[simp]
theorem radical_idem : radical (radical I) = radical I :=
(radical_isRadical I).radical
#align ideal.radical_idem Ideal.radical_idem
variable {I}
theorem IsRadical.radical_le_iff (hJ : J.IsRadical) : I.radical ≤ J ↔ I ≤ J :=
⟨le_trans le_radical, fun h => hJ.radical ▸ radical_mono h⟩
#align ideal.is_radical.radical_le_iff Ideal.IsRadical.radical_le_iff
theorem radical_le_radical_iff : radical I ≤ radical J ↔ I ≤ radical J :=
(radical_isRadical J).radical_le_iff
#align ideal.radical_le_radical_iff Ideal.radical_le_radical_iff
theorem radical_eq_top : radical I = ⊤ ↔ I = ⊤ :=
⟨fun h =>
(eq_top_iff_one _).2 <|
let ⟨n, hn⟩ := (eq_top_iff_one _).1 h
@one_pow R _ n ▸ hn,
fun h => h.symm ▸ radical_top R⟩
#align ideal.radical_eq_top Ideal.radical_eq_top
theorem IsPrime.isRadical (H : IsPrime I) : I.IsRadical := fun _ ⟨n, hrni⟩ =>
H.mem_of_pow_mem n hrni
#align ideal.is_prime.is_radical Ideal.IsPrime.isRadical
theorem IsPrime.radical (H : IsPrime I) : radical I = I :=
IsRadical.radical H.isRadical
#align ideal.is_prime.radical Ideal.IsPrime.radical
theorem mem_radical_of_pow_mem {I : Ideal R} {x : R} {m : ℕ} (hx : x ^ m ∈ radical I) :
x ∈ radical I :=
radical_idem I ▸ ⟨m, hx⟩
#align ideal.mem_radical_of_pow_mem Ideal.mem_radical_of_pow_mem
theorem disjoint_powers_iff_not_mem (y : R) (hI : I.IsRadical) :
Disjoint (Submonoid.powers y : Set R) ↑I ↔ y ∉ I.1 := by
refine ⟨fun h => Set.disjoint_left.1 h (Submonoid.mem_powers _),
fun h => disjoint_iff.mpr (eq_bot_iff.mpr ?_)⟩
rintro x ⟨⟨n, rfl⟩, hx'⟩
exact h (hI <| mem_radical_of_pow_mem <| le_radical hx')
#align ideal.disjoint_powers_iff_not_mem Ideal.disjoint_powers_iff_not_mem
variable (I J)
theorem radical_sup : radical (I ⊔ J) = radical (radical I ⊔ radical J) :=
le_antisymm (radical_mono <| sup_le_sup le_radical le_radical) <|
radical_le_radical_iff.2 <| sup_le (radical_mono le_sup_left) (radical_mono le_sup_right)
#align ideal.radical_sup Ideal.radical_sup
theorem radical_inf : radical (I ⊓ J) = radical I ⊓ radical J :=
le_antisymm (le_inf (radical_mono inf_le_left) (radical_mono inf_le_right))
fun r ⟨⟨m, hrm⟩, ⟨n, hrn⟩⟩ =>
⟨m + n, (pow_add r m n).symm ▸ I.mul_mem_right _ hrm,
(pow_add r m n).symm ▸ J.mul_mem_left _ hrn⟩
#align ideal.radical_inf Ideal.radical_inf
variable {I J} in
theorem IsRadical.inf (hI : IsRadical I) (hJ : IsRadical J) : IsRadical (I ⊓ J) := by
rw [IsRadical, radical_inf]; exact inf_le_inf hI hJ
/-- The reverse inclusion does not hold for e.g. `I := fun n : ℕ ↦ Ideal.span {(2 ^ n : ℤ)}`. -/
theorem radical_iInf_le {ι} (I : ι → Ideal R) : radical (⨅ i, I i) ≤ ⨅ i, radical (I i) :=
le_iInf fun _ ↦ radical_mono (iInf_le _ _)
theorem isRadical_iInf {ι} (I : ι → Ideal R) (hI : ∀ i, IsRadical (I i)) : IsRadical (⨅ i, I i) :=
(radical_iInf_le I).trans (iInf_mono hI)
theorem radical_mul : radical (I * J) = radical I ⊓ radical J := by
refine le_antisymm ?_ fun r ⟨⟨m, hrm⟩, ⟨n, hrn⟩⟩ =>
⟨m + n, (pow_add r m n).symm ▸ mul_mem_mul hrm hrn⟩
have := radical_mono <| @mul_le_inf _ _ I J
simp_rw [radical_inf I J] at this
assumption
#align ideal.radical_mul Ideal.radical_mul
variable {I J}
theorem IsPrime.radical_le_iff (hJ : IsPrime J) : I.radical ≤ J ↔ I ≤ J :=
IsRadical.radical_le_iff hJ.isRadical
#align ideal.is_prime.radical_le_iff Ideal.IsPrime.radical_le_iff
theorem radical_eq_sInf (I : Ideal R) : radical I = sInf { J : Ideal R | I ≤ J ∧ IsPrime J } :=
le_antisymm (le_sInf fun J hJ ↦ hJ.2.radical_le_iff.2 hJ.1) fun r hr ↦
by_contradiction fun hri ↦
let ⟨m, (hrm : r ∉ radical m), him, hm⟩ :=
zorn_nonempty_partialOrder₀ { K : Ideal R | r ∉ radical K }
(fun c hc hcc y hyc =>
⟨sSup c, fun ⟨n, hrnc⟩ =>
let ⟨y, hyc, hrny⟩ := (Submodule.mem_sSup_of_directed ⟨y, hyc⟩ hcc.directedOn).1 hrnc
hc hyc ⟨n, hrny⟩,
fun z => le_sSup⟩)
I hri
have : ∀ x ∉ m, r ∈ radical (m ⊔ span {x}) := fun x hxm =>
by_contradiction fun hrmx =>
hxm <|
hm (m ⊔ span {x}) hrmx le_sup_left ▸
(le_sup_right : _ ≤ m ⊔ span {x}) (subset_span <| Set.mem_singleton _)
have : IsPrime m :=
⟨by rintro rfl; rw [radical_top] at hrm; exact hrm trivial, fun {x y} hxym =>
or_iff_not_imp_left.2 fun hxm =>
by_contradiction fun hym =>
let ⟨n, hrn⟩ := this _ hxm
let ⟨p, hpm, q, hq, hpqrn⟩ := Submodule.mem_sup.1 hrn
let ⟨c, hcxq⟩ := mem_span_singleton'.1 hq
let ⟨k, hrk⟩ := this _ hym
let ⟨f, hfm, g, hg, hfgrk⟩ := Submodule.mem_sup.1 hrk
let ⟨d, hdyg⟩ := mem_span_singleton'.1 hg
hrm
⟨n + k, by
rw [pow_add, ← hpqrn, ← hcxq, ← hfgrk, ← hdyg, add_mul, mul_add (c * x),
mul_assoc c x (d * y), mul_left_comm x, ← mul_assoc];
refine
m.add_mem (m.mul_mem_right _ hpm)
(m.add_mem (m.mul_mem_left _ hfm) (m.mul_mem_left _ hxym))⟩⟩
hrm <|
this.radical.symm ▸ (sInf_le ⟨him, this⟩ : sInf { J : Ideal R | I ≤ J ∧ IsPrime J } ≤ m) hr
#align ideal.radical_eq_Inf Ideal.radical_eq_sInf
theorem isRadical_bot_of_noZeroDivisors {R} [CommSemiring R] [NoZeroDivisors R] :
(⊥ : Ideal R).IsRadical := fun _ hx => hx.recOn fun _ hn => pow_eq_zero hn
#align ideal.is_radical_bot_of_no_zero_divisors Ideal.isRadical_bot_of_noZeroDivisors
@[simp]
theorem radical_bot_of_noZeroDivisors {R : Type u} [CommSemiring R] [NoZeroDivisors R] :
radical (⊥ : Ideal R) = ⊥ :=
eq_bot_iff.2 isRadical_bot_of_noZeroDivisors
#align ideal.radical_bot_of_no_zero_divisors Ideal.radical_bot_of_noZeroDivisors
instance : IdemCommSemiring (Ideal R) :=
inferInstance
variable (R)
theorem top_pow (n : ℕ) : (⊤ ^ n : Ideal R) = ⊤ :=
Nat.recOn n one_eq_top fun n ih => by rw [pow_succ, ih, top_mul]
#align ideal.top_pow Ideal.top_pow
variable {R}
variable (I)
lemma radical_pow : ∀ {n}, n ≠ 0 → radical (I ^ n) = radical I
| 1, _ => by simp
| n + 2, _ => by rw [pow_succ, radical_mul, radical_pow n.succ_ne_zero, inf_idem]
#align ideal.radical_pow Ideal.radical_pow
theorem IsPrime.mul_le {I J P : Ideal R} (hp : IsPrime P) : I * J ≤ P ↔ I ≤ P ∨ J ≤ P := by
rw [or_comm, Ideal.mul_le]
simp_rw [hp.mul_mem_iff_mem_or_mem, SetLike.le_def, ← forall_or_left, or_comm, forall_or_left]
#align ideal.is_prime.mul_le Ideal.IsPrime.mul_le
theorem IsPrime.inf_le {I J P : Ideal R} (hp : IsPrime P) : I ⊓ J ≤ P ↔ I ≤ P ∨ J ≤ P :=
⟨fun h ↦ hp.mul_le.1 <| mul_le_inf.trans h, fun h ↦ h.elim inf_le_left.trans inf_le_right.trans⟩
#align ideal.is_prime.inf_le Ideal.IsPrime.inf_le
theorem IsPrime.multiset_prod_le {s : Multiset (Ideal R)} {P : Ideal R} (hp : IsPrime P) :
s.prod ≤ P ↔ ∃ I ∈ s, I ≤ P :=
s.induction_on (by simp [hp.ne_top]) fun I s ih ↦ by simp [hp.mul_le, ih]
#align ideal.is_prime.multiset_prod_le Ideal.IsPrime.multiset_prod_le
theorem IsPrime.multiset_prod_map_le {s : Multiset ι} (f : ι → Ideal R) {P : Ideal R}
(hp : IsPrime P) : (s.map f).prod ≤ P ↔ ∃ i ∈ s, f i ≤ P := by
simp_rw [hp.multiset_prod_le, Multiset.mem_map, exists_exists_and_eq_and]
#align ideal.is_prime.multiset_prod_map_le Ideal.IsPrime.multiset_prod_map_le
theorem IsPrime.multiset_prod_mem_iff_exists_mem {I : Ideal R} (hI : I.IsPrime) (s : Multiset R) :
s.prod ∈ I ↔ ∃ p ∈ s, p ∈ I := by
simpa [span_singleton_le_iff_mem] using (hI.multiset_prod_map_le (span {·}))
theorem IsPrime.prod_le {s : Finset ι} {f : ι → Ideal R} {P : Ideal R} (hp : IsPrime P) :
s.prod f ≤ P ↔ ∃ i ∈ s, f i ≤ P :=
hp.multiset_prod_map_le f
#align ideal.is_prime.prod_le Ideal.IsPrime.prod_le
theorem IsPrime.prod_mem_iff_exists_mem {I : Ideal R} (hI : I.IsPrime) (s : Finset R) :
s.prod (fun x ↦ x) ∈ I ↔ ∃ p ∈ s, p ∈ I := by
rw [Finset.prod_eq_multiset_prod, Multiset.map_id']
exact hI.multiset_prod_mem_iff_exists_mem s.val
theorem IsPrime.inf_le' {s : Finset ι} {f : ι → Ideal R} {P : Ideal R} (hp : IsPrime P) :
s.inf f ≤ P ↔ ∃ i ∈ s, f i ≤ P :=
⟨fun h ↦ hp.prod_le.1 <| prod_le_inf.trans h, fun ⟨_, his, hip⟩ ↦ (Finset.inf_le his).trans hip⟩
#align ideal.is_prime.inf_le' Ideal.IsPrime.inf_le'
-- Porting note: needed to add explicit coercions (· : Set R).
theorem subset_union {R : Type u} [Ring R] {I J K : Ideal R} :
(I : Set R) ⊆ J ∪ K ↔ I ≤ J ∨ I ≤ K :=
AddSubgroupClass.subset_union
#align ideal.subset_union Ideal.subset_union
theorem subset_union_prime' {R : Type u} [CommRing R] {s : Finset ι} {f : ι → Ideal R} {a b : ι}
(hp : ∀ i ∈ s, IsPrime (f i)) {I : Ideal R} :
((I : Set R) ⊆ f a ∪ f b ∪ ⋃ i ∈ (↑s : Set ι), f i) ↔ I ≤ f a ∨ I ≤ f b ∨ ∃ i ∈ s, I ≤ f i := by
suffices
((I : Set R) ⊆ f a ∪ f b ∪ ⋃ i ∈ (↑s : Set ι), f i) → I ≤ f a ∨ I ≤ f b ∨ ∃ i ∈ s, I ≤ f i from
⟨this, fun h =>
Or.casesOn h
(fun h =>
Set.Subset.trans h <|
Set.Subset.trans Set.subset_union_left Set.subset_union_left)
fun h =>
Or.casesOn h
(fun h =>
Set.Subset.trans h <|
Set.Subset.trans Set.subset_union_right Set.subset_union_left)
fun ⟨i, his, hi⟩ => by
refine Set.Subset.trans hi <| Set.Subset.trans ?_ Set.subset_union_right;
exact Set.subset_biUnion_of_mem (u := fun x ↦ (f x : Set R)) (Finset.mem_coe.2 his)⟩
generalize hn : s.card = n; intro h
induction' n with n ih generalizing a b s
· clear hp
rw [Finset.card_eq_zero] at hn
subst hn
rw [Finset.coe_empty, Set.biUnion_empty, Set.union_empty, subset_union] at h
simpa only [exists_prop, Finset.not_mem_empty, false_and_iff, exists_false, or_false_iff]
classical
replace hn : ∃ (i : ι) (t : Finset ι), i ∉ t ∧ insert i t = s ∧ t.card = n :=
Finset.card_eq_succ.1 hn
rcases hn with ⟨i, t, hit, rfl, hn⟩
replace hp : IsPrime (f i) ∧ ∀ x ∈ t, IsPrime (f x) := (t.forall_mem_insert _ _).1 hp
by_cases Ht : ∃ j ∈ t, f j ≤ f i
· obtain ⟨j, hjt, hfji⟩ : ∃ j ∈ t, f j ≤ f i := Ht
obtain ⟨u, hju, rfl⟩ : ∃ u, j ∉ u ∧ insert j u = t :=
⟨t.erase j, t.not_mem_erase j, Finset.insert_erase hjt⟩
have hp' : ∀ k ∈ insert i u, IsPrime (f k) := by
rw [Finset.forall_mem_insert] at hp ⊢
exact ⟨hp.1, hp.2.2⟩
have hiu : i ∉ u := mt Finset.mem_insert_of_mem hit
have hn' : (insert i u).card = n := by
rwa [Finset.card_insert_of_not_mem] at hn ⊢
exacts [hiu, hju]
have h' : (I : Set R) ⊆ f a ∪ f b ∪ ⋃ k ∈ (↑(insert i u) : Set ι), f k := by
rw [Finset.coe_insert] at h ⊢
rw [Finset.coe_insert] at h
simp only [Set.biUnion_insert] at h ⊢
rw [← Set.union_assoc (f i : Set R)] at h
erw [Set.union_eq_self_of_subset_right hfji] at h
exact h
specialize ih hp' hn' h'
refine ih.imp id (Or.imp id (Exists.imp fun k => ?_))
exact And.imp (fun hk => Finset.insert_subset_insert i (Finset.subset_insert j u) hk) id
by_cases Ha : f a ≤ f i
· have h' : (I : Set R) ⊆ f i ∪ f b ∪ ⋃ j ∈ (↑t : Set ι), f j := by
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_assoc,
Set.union_right_comm (f a : Set R)] at h
erw [Set.union_eq_self_of_subset_left Ha] at h
exact h
specialize ih hp.2 hn h'
right
rcases ih with (ih | ih | ⟨k, hkt, ih⟩)
· exact Or.inr ⟨i, Finset.mem_insert_self i t, ih⟩
· exact Or.inl ih
· exact Or.inr ⟨k, Finset.mem_insert_of_mem hkt, ih⟩
by_cases Hb : f b ≤ f i
· have h' : (I : Set R) ⊆ f a ∪ f i ∪ ⋃ j ∈ (↑t : Set ι), f j := by
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_assoc,
Set.union_assoc (f a : Set R)] at h
erw [Set.union_eq_self_of_subset_left Hb] at h
exact h
specialize ih hp.2 hn h'
rcases ih with (ih | ih | ⟨k, hkt, ih⟩)
· exact Or.inl ih
· exact Or.inr (Or.inr ⟨i, Finset.mem_insert_self i t, ih⟩)
· exact Or.inr (Or.inr ⟨k, Finset.mem_insert_of_mem hkt, ih⟩)
by_cases Hi : I ≤ f i
· exact Or.inr (Or.inr ⟨i, Finset.mem_insert_self i t, Hi⟩)
have : ¬I ⊓ f a ⊓ f b ⊓ t.inf f ≤ f i := by
simp only [hp.1.inf_le, hp.1.inf_le', not_or]
exact ⟨⟨⟨Hi, Ha⟩, Hb⟩, Ht⟩
rcases Set.not_subset.1 this with ⟨r, ⟨⟨⟨hrI, hra⟩, hrb⟩, hr⟩, hri⟩
by_cases HI : (I : Set R) ⊆ f a ∪ f b ∪ ⋃ j ∈ (↑t : Set ι), f j
· specialize ih hp.2 hn HI
rcases ih with (ih | ih | ⟨k, hkt, ih⟩)
· left
exact ih
· right
left
exact ih
· right
right
exact ⟨k, Finset.mem_insert_of_mem hkt, ih⟩
exfalso
rcases Set.not_subset.1 HI with ⟨s, hsI, hs⟩
rw [Finset.coe_insert, Set.biUnion_insert] at h
have hsi : s ∈ f i := ((h hsI).resolve_left (mt Or.inl hs)).resolve_right (mt Or.inr hs)
rcases h (I.add_mem hrI hsI) with (⟨ha | hb⟩ | hi | ht)
· exact hs (Or.inl <| Or.inl <| add_sub_cancel_left r s ▸ (f a).sub_mem ha hra)
· exact hs (Or.inl <| Or.inr <| add_sub_cancel_left r s ▸ (f b).sub_mem hb hrb)
· exact hri (add_sub_cancel_right r s ▸ (f i).sub_mem hi hsi)
· rw [Set.mem_iUnion₂] at ht
rcases ht with ⟨j, hjt, hj⟩
simp only [Finset.inf_eq_iInf, SetLike.mem_coe, Submodule.mem_iInf] at hr
exact hs $ Or.inr $ Set.mem_biUnion hjt <|
add_sub_cancel_left r s ▸ (f j).sub_mem hj <| hr j hjt
#align ideal.subset_union_prime' Ideal.subset_union_prime'
/-- Prime avoidance. Atiyah-Macdonald 1.11, Eisenbud 3.3, Stacks 00DS, Matsumura Ex.1.6. -/
| Mathlib/RingTheory/Ideal/Operations.lean | 1,247 | 1,302 | theorem subset_union_prime {R : Type u} [CommRing R] {s : Finset ι} {f : ι → Ideal R} (a b : ι)
(hp : ∀ i ∈ s, i ≠ a → i ≠ b → IsPrime (f i)) {I : Ideal R} :
((I : Set R) ⊆ ⋃ i ∈ (↑s : Set ι), f i) ↔ ∃ i ∈ s, I ≤ f i :=
suffices ((I : Set R) ⊆ ⋃ i ∈ (↑s : Set ι), f i) → ∃ i, i ∈ s ∧ I ≤ f i by
have aux := fun h => (bex_def.2 <| this h)
simp_rw [exists_prop] at aux
refine ⟨aux, fun ⟨i, his, hi⟩ ↦ Set.Subset.trans hi ?_⟩
apply Set.subset_biUnion_of_mem (show i ∈ (↑s : Set ι) from his)
fun h : (I : Set R) ⊆ ⋃ i ∈ (↑s : Set ι), f i => by
classical
by_cases has : a ∈ s
· obtain ⟨t, hat, rfl⟩ : ∃ t, a ∉ t ∧ insert a t = s :=
⟨s.erase a, Finset.not_mem_erase a s, Finset.insert_erase has⟩
by_cases hbt : b ∈ t
· obtain ⟨u, hbu, rfl⟩ : ∃ u, b ∉ u ∧ insert b u = t :=
⟨t.erase b, Finset.not_mem_erase b t, Finset.insert_erase hbt⟩
have hp' : ∀ i ∈ u, IsPrime (f i) := by |
intro i hiu
refine hp i (Finset.mem_insert_of_mem (Finset.mem_insert_of_mem hiu)) ?_ ?_ <;>
rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Finset.coe_insert, Set.biUnion_insert, Set.biUnion_insert, ←
Set.union_assoc, subset_union_prime' hp'] at h
rwa [Finset.exists_mem_insert, Finset.exists_mem_insert]
· have hp' : ∀ j ∈ t, IsPrime (f j) := by
intro j hj
refine hp j (Finset.mem_insert_of_mem hj) ?_ ?_ <;> rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_self (f a : Set R),
subset_union_prime' hp', ← or_assoc, or_self_iff] at h
rwa [Finset.exists_mem_insert]
· by_cases hbs : b ∈ s
· obtain ⟨t, hbt, rfl⟩ : ∃ t, b ∉ t ∧ insert b t = s :=
⟨s.erase b, Finset.not_mem_erase b s, Finset.insert_erase hbs⟩
have hp' : ∀ j ∈ t, IsPrime (f j) := by
intro j hj
refine hp j (Finset.mem_insert_of_mem hj) ?_ ?_ <;> rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_self (f b : Set R),
subset_union_prime' hp', ← or_assoc, or_self_iff] at h
rwa [Finset.exists_mem_insert]
rcases s.eq_empty_or_nonempty with hse | hsne
· subst hse
rw [Finset.coe_empty, Set.biUnion_empty, Set.subset_empty_iff] at h
have : (I : Set R) ≠ ∅ := Set.Nonempty.ne_empty (Set.nonempty_of_mem I.zero_mem)
exact absurd h this
· cases' hsne with i his
obtain ⟨t, _, rfl⟩ : ∃ t, i ∉ t ∧ insert i t = s :=
⟨s.erase i, Finset.not_mem_erase i s, Finset.insert_erase his⟩
have hp' : ∀ j ∈ t, IsPrime (f j) := by
intro j hj
refine hp j (Finset.mem_insert_of_mem hj) ?_ ?_ <;> rintro rfl <;>
solve_by_elim only [Finset.mem_insert_of_mem, *]
rw [Finset.coe_insert, Set.biUnion_insert, ← Set.union_self (f i : Set R),
subset_union_prime' hp', ← or_assoc, or_self_iff] at h
rwa [Finset.exists_mem_insert]
|
/-
Copyright (c) 2018 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Simon Hudon
-/
import Mathlib.Data.PFunctor.Multivariate.Basic
#align_import data.pfunctor.multivariate.W from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988"
/-!
# The W construction as a multivariate polynomial functor.
W types are well-founded tree-like structures. They are defined
as the least fixpoint of a polynomial functor.
## Main definitions
* `W_mk` - constructor
* `W_dest - destructor
* `W_rec` - recursor: basis for defining functions by structural recursion on `P.W α`
* `W_rec_eq` - defining equation for `W_rec`
* `W_ind` - induction principle for `P.W α`
## Implementation notes
Three views of M-types:
* `wp`: polynomial functor
* `W`: data type inductively defined by a triple:
shape of the root, data in the root and children of the root
* `W`: least fixed point of a polynomial functor
Specifically, we define the polynomial functor `wp` as:
* A := a tree-like structure without information in the nodes
* B := given the tree-like structure `t`, `B t` is a valid path
(specified inductively by `W_path`) from the root of `t` to any given node.
As a result `wp α` is made of a dataless tree and a function from
its valid paths to values of `α`
## Reference
* Jeremy Avigad, Mario M. Carneiro and Simon Hudon.
[*Data Types as Quotients of Polynomial Functors*][avigad-carneiro-hudon2019]
-/
universe u v
namespace MvPFunctor
open TypeVec
open MvFunctor
variable {n : ℕ} (P : MvPFunctor.{u} (n + 1))
/-- A path from the root of a tree to one of its node -/
inductive WPath : P.last.W → Fin2 n → Type u
| root (a : P.A) (f : P.last.B a → P.last.W) (i : Fin2 n) (c : P.drop.B a i) : WPath ⟨a, f⟩ i
| child (a : P.A) (f : P.last.B a → P.last.W) (i : Fin2 n) (j : P.last.B a)
(c : WPath (f j) i) : WPath ⟨a, f⟩ i
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path MvPFunctor.WPath
instance WPath.inhabited (x : P.last.W) {i} [I : Inhabited (P.drop.B x.head i)] :
Inhabited (WPath P x i) :=
⟨match x, I with
| ⟨a, f⟩, I => WPath.root a f i (@default _ I)⟩
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path.inhabited MvPFunctor.WPath.inhabited
/-- Specialized destructor on `WPath` -/
def wPathCasesOn {α : TypeVec n} {a : P.A} {f : P.last.B a → P.last.W} (g' : P.drop.B a ⟹ α)
(g : ∀ j : P.last.B a, P.WPath (f j) ⟹ α) : P.WPath ⟨a, f⟩ ⟹ α := by
intro i x;
match x with
| WPath.root _ _ i c => exact g' i c
| WPath.child _ _ i j c => exact g j i c
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path_cases_on MvPFunctor.wPathCasesOn
/-- Specialized destructor on `WPath` -/
def wPathDestLeft {α : TypeVec n} {a : P.A} {f : P.last.B a → P.last.W}
(h : P.WPath ⟨a, f⟩ ⟹ α) : P.drop.B a ⟹ α := fun i c => h i (WPath.root a f i c)
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path_dest_left MvPFunctor.wPathDestLeft
/-- Specialized destructor on `WPath` -/
def wPathDestRight {α : TypeVec n} {a : P.A} {f : P.last.B a → P.last.W}
(h : P.WPath ⟨a, f⟩ ⟹ α) : ∀ j : P.last.B a, P.WPath (f j) ⟹ α := fun j i c =>
h i (WPath.child a f i j c)
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path_dest_right MvPFunctor.wPathDestRight
theorem wPathDestLeft_wPathCasesOn {α : TypeVec n} {a : P.A} {f : P.last.B a → P.last.W}
(g' : P.drop.B a ⟹ α) (g : ∀ j : P.last.B a, P.WPath (f j) ⟹ α) :
P.wPathDestLeft (P.wPathCasesOn g' g) = g' := rfl
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path_dest_left_W_path_cases_on MvPFunctor.wPathDestLeft_wPathCasesOn
theorem wPathDestRight_wPathCasesOn {α : TypeVec n} {a : P.A} {f : P.last.B a → P.last.W}
(g' : P.drop.B a ⟹ α) (g : ∀ j : P.last.B a, P.WPath (f j) ⟹ α) :
P.wPathDestRight (P.wPathCasesOn g' g) = g := rfl
set_option linter.uppercaseLean3 false in
#align mvpfunctor.W_path_dest_right_W_path_cases_on MvPFunctor.wPathDestRight_wPathCasesOn
| Mathlib/Data/PFunctor/Multivariate/W.lean | 109 | 111 | theorem wPathCasesOn_eta {α : TypeVec n} {a : P.A} {f : P.last.B a → P.last.W}
(h : P.WPath ⟨a, f⟩ ⟹ α) : P.wPathCasesOn (P.wPathDestLeft h) (P.wPathDestRight h) = h := by |
ext i x; cases x <;> rfl
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Complex
import Qq
#align_import analysis.special_functions.pow.real from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-! # Power function on `ℝ`
We construct the power functions `x ^ y`, where `x` and `y` are real numbers.
-/
noncomputable section
open scoped Classical
open Real ComplexConjugate
open Finset Set
/-
## Definitions
-/
namespace Real
variable {x y z : ℝ}
/-- The real power function `x ^ y`, defined as the real part of the complex power function.
For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`, one sets `0 ^ 0=1` and `0 ^ y=0` for
`y ≠ 0`. For `x < 0`, the definition is somewhat arbitrary as it depends on the choice of a complex
determination of the logarithm. With our conventions, it is equal to `exp (y log x) cos (π y)`. -/
noncomputable def rpow (x y : ℝ) :=
((x : ℂ) ^ (y : ℂ)).re
#align real.rpow Real.rpow
noncomputable instance : Pow ℝ ℝ := ⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x y : ℝ) : rpow x y = x ^ y := rfl
#align real.rpow_eq_pow Real.rpow_eq_pow
theorem rpow_def (x y : ℝ) : x ^ y = ((x : ℂ) ^ (y : ℂ)).re := rfl
#align real.rpow_def Real.rpow_def
theorem rpow_def_of_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) := by
simp only [rpow_def, Complex.cpow_def]; split_ifs <;>
simp_all [(Complex.ofReal_log hx).symm, -Complex.ofReal_mul, -RCLike.ofReal_mul,
(Complex.ofReal_mul _ _).symm, Complex.exp_ofReal_re, Complex.ofReal_eq_zero]
#align real.rpow_def_of_nonneg Real.rpow_def_of_nonneg
theorem rpow_def_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : x ^ y = exp (log x * y) := by
rw [rpow_def_of_nonneg (le_of_lt hx), if_neg (ne_of_gt hx)]
#align real.rpow_def_of_pos Real.rpow_def_of_pos
theorem exp_mul (x y : ℝ) : exp (x * y) = exp x ^ y := by rw [rpow_def_of_pos (exp_pos _), log_exp]
#align real.exp_mul Real.exp_mul
@[simp, norm_cast]
theorem rpow_intCast (x : ℝ) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by
simp only [rpow_def, ← Complex.ofReal_zpow, Complex.cpow_intCast, Complex.ofReal_intCast,
Complex.ofReal_re]
#align real.rpow_int_cast Real.rpow_intCast
@[deprecated (since := "2024-04-17")]
alias rpow_int_cast := rpow_intCast
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by simpa using rpow_intCast x n
#align real.rpow_nat_cast Real.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
theorem exp_one_rpow (x : ℝ) : exp 1 ^ x = exp x := by rw [← exp_mul, one_mul]
#align real.exp_one_rpow Real.exp_one_rpow
@[simp] lemma exp_one_pow (n : ℕ) : exp 1 ^ n = exp n := by rw [← rpow_natCast, exp_one_rpow]
theorem rpow_eq_zero_iff_of_nonneg (hx : 0 ≤ x) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [rpow_def_of_nonneg hx]
split_ifs <;> simp [*, exp_ne_zero]
#align real.rpow_eq_zero_iff_of_nonneg Real.rpow_eq_zero_iff_of_nonneg
@[simp]
lemma rpow_eq_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y = 0 ↔ x = 0 := by
simp [rpow_eq_zero_iff_of_nonneg, *]
@[simp]
lemma rpow_ne_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y ≠ 0 ↔ x ≠ 0 :=
Real.rpow_eq_zero hx hy |>.not
open Real
theorem rpow_def_of_neg {x : ℝ} (hx : x < 0) (y : ℝ) : x ^ y = exp (log x * y) * cos (y * π) := by
rw [rpow_def, Complex.cpow_def, if_neg]
· have : Complex.log x * y = ↑(log (-x) * y) + ↑(y * π) * Complex.I := by
simp only [Complex.log, abs_of_neg hx, Complex.arg_ofReal_of_neg hx, Complex.abs_ofReal,
Complex.ofReal_mul]
ring
rw [this, Complex.exp_add_mul_I, ← Complex.ofReal_exp, ← Complex.ofReal_cos, ←
Complex.ofReal_sin, mul_add, ← Complex.ofReal_mul, ← mul_assoc, ← Complex.ofReal_mul,
Complex.add_re, Complex.ofReal_re, Complex.mul_re, Complex.I_re, Complex.ofReal_im,
Real.log_neg_eq_log]
ring
· rw [Complex.ofReal_eq_zero]
exact ne_of_lt hx
#align real.rpow_def_of_neg Real.rpow_def_of_neg
theorem rpow_def_of_nonpos {x : ℝ} (hx : x ≤ 0) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) * cos (y * π) := by
split_ifs with h <;> simp [rpow_def, *]; exact rpow_def_of_neg (lt_of_le_of_ne hx h) _
#align real.rpow_def_of_nonpos Real.rpow_def_of_nonpos
theorem rpow_pos_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : 0 < x ^ y := by
rw [rpow_def_of_pos hx]; apply exp_pos
#align real.rpow_pos_of_pos Real.rpow_pos_of_pos
@[simp]
theorem rpow_zero (x : ℝ) : x ^ (0 : ℝ) = 1 := by simp [rpow_def]
#align real.rpow_zero Real.rpow_zero
theorem rpow_zero_pos (x : ℝ) : 0 < x ^ (0 : ℝ) := by simp
@[simp]
theorem zero_rpow {x : ℝ} (h : x ≠ 0) : (0 : ℝ) ^ x = 0 := by simp [rpow_def, *]
#align real.zero_rpow Real.zero_rpow
theorem zero_rpow_eq_iff {x : ℝ} {a : ℝ} : 0 ^ x = a ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
constructor
· intro hyp
simp only [rpow_def, Complex.ofReal_zero] at hyp
by_cases h : x = 0
· subst h
simp only [Complex.one_re, Complex.ofReal_zero, Complex.cpow_zero] at hyp
exact Or.inr ⟨rfl, hyp.symm⟩
· rw [Complex.zero_cpow (Complex.ofReal_ne_zero.mpr h)] at hyp
exact Or.inl ⟨h, hyp.symm⟩
· rintro (⟨h, rfl⟩ | ⟨rfl, rfl⟩)
· exact zero_rpow h
· exact rpow_zero _
#align real.zero_rpow_eq_iff Real.zero_rpow_eq_iff
theorem eq_zero_rpow_iff {x : ℝ} {a : ℝ} : a = 0 ^ x ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
rw [← zero_rpow_eq_iff, eq_comm]
#align real.eq_zero_rpow_iff Real.eq_zero_rpow_iff
@[simp]
theorem rpow_one (x : ℝ) : x ^ (1 : ℝ) = x := by simp [rpow_def]
#align real.rpow_one Real.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ) ^ x = 1 := by simp [rpow_def]
#align real.one_rpow Real.one_rpow
theorem zero_rpow_le_one (x : ℝ) : (0 : ℝ) ^ x ≤ 1 := by
by_cases h : x = 0 <;> simp [h, zero_le_one]
#align real.zero_rpow_le_one Real.zero_rpow_le_one
theorem zero_rpow_nonneg (x : ℝ) : 0 ≤ (0 : ℝ) ^ x := by
by_cases h : x = 0 <;> simp [h, zero_le_one]
#align real.zero_rpow_nonneg Real.zero_rpow_nonneg
theorem rpow_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : 0 ≤ x ^ y := by
rw [rpow_def_of_nonneg hx]; split_ifs <;>
simp only [zero_le_one, le_refl, le_of_lt (exp_pos _)]
#align real.rpow_nonneg_of_nonneg Real.rpow_nonneg
theorem abs_rpow_of_nonneg {x y : ℝ} (hx_nonneg : 0 ≤ x) : |x ^ y| = |x| ^ y := by
have h_rpow_nonneg : 0 ≤ x ^ y := Real.rpow_nonneg hx_nonneg _
rw [abs_eq_self.mpr hx_nonneg, abs_eq_self.mpr h_rpow_nonneg]
#align real.abs_rpow_of_nonneg Real.abs_rpow_of_nonneg
theorem abs_rpow_le_abs_rpow (x y : ℝ) : |x ^ y| ≤ |x| ^ y := by
rcases le_or_lt 0 x with hx | hx
· rw [abs_rpow_of_nonneg hx]
· rw [abs_of_neg hx, rpow_def_of_neg hx, rpow_def_of_pos (neg_pos.2 hx), log_neg_eq_log, abs_mul,
abs_of_pos (exp_pos _)]
exact mul_le_of_le_one_right (exp_pos _).le (abs_cos_le_one _)
#align real.abs_rpow_le_abs_rpow Real.abs_rpow_le_abs_rpow
theorem abs_rpow_le_exp_log_mul (x y : ℝ) : |x ^ y| ≤ exp (log x * y) := by
refine (abs_rpow_le_abs_rpow x y).trans ?_
by_cases hx : x = 0
· by_cases hy : y = 0 <;> simp [hx, hy, zero_le_one]
· rw [rpow_def_of_pos (abs_pos.2 hx), log_abs]
#align real.abs_rpow_le_exp_log_mul Real.abs_rpow_le_exp_log_mul
theorem norm_rpow_of_nonneg {x y : ℝ} (hx_nonneg : 0 ≤ x) : ‖x ^ y‖ = ‖x‖ ^ y := by
simp_rw [Real.norm_eq_abs]
exact abs_rpow_of_nonneg hx_nonneg
#align real.norm_rpow_of_nonneg Real.norm_rpow_of_nonneg
variable {w x y z : ℝ}
theorem rpow_add (hx : 0 < x) (y z : ℝ) : x ^ (y + z) = x ^ y * x ^ z := by
simp only [rpow_def_of_pos hx, mul_add, exp_add]
#align real.rpow_add Real.rpow_add
theorem rpow_add' (hx : 0 ≤ x) (h : y + z ≠ 0) : x ^ (y + z) = x ^ y * x ^ z := by
rcases hx.eq_or_lt with (rfl | pos)
· rw [zero_rpow h, zero_eq_mul]
have : y ≠ 0 ∨ z ≠ 0 := not_and_or.1 fun ⟨hy, hz⟩ => h <| hy.symm ▸ hz.symm ▸ zero_add 0
exact this.imp zero_rpow zero_rpow
· exact rpow_add pos _ _
#align real.rpow_add' Real.rpow_add'
/-- Variant of `Real.rpow_add'` that avoids having to prove `y + z = w` twice. -/
lemma rpow_of_add_eq (hx : 0 ≤ x) (hw : w ≠ 0) (h : y + z = w) : x ^ w = x ^ y * x ^ z := by
rw [← h, rpow_add' hx]; rwa [h]
theorem rpow_add_of_nonneg (hx : 0 ≤ x) (hy : 0 ≤ y) (hz : 0 ≤ z) :
x ^ (y + z) = x ^ y * x ^ z := by
rcases hy.eq_or_lt with (rfl | hy)
· rw [zero_add, rpow_zero, one_mul]
exact rpow_add' hx (ne_of_gt <| add_pos_of_pos_of_nonneg hy hz)
#align real.rpow_add_of_nonneg Real.rpow_add_of_nonneg
/-- For `0 ≤ x`, the only problematic case in the equality `x ^ y * x ^ z = x ^ (y + z)` is for
`x = 0` and `y + z = 0`, where the right hand side is `1` while the left hand side can vanish.
The inequality is always true, though, and given in this lemma. -/
theorem le_rpow_add {x : ℝ} (hx : 0 ≤ x) (y z : ℝ) : x ^ y * x ^ z ≤ x ^ (y + z) := by
rcases le_iff_eq_or_lt.1 hx with (H | pos)
· by_cases h : y + z = 0
· simp only [H.symm, h, rpow_zero]
calc
(0 : ℝ) ^ y * 0 ^ z ≤ 1 * 1 :=
mul_le_mul (zero_rpow_le_one y) (zero_rpow_le_one z) (zero_rpow_nonneg z) zero_le_one
_ = 1 := by simp
· simp [rpow_add', ← H, h]
· simp [rpow_add pos]
#align real.le_rpow_add Real.le_rpow_add
theorem rpow_sum_of_pos {ι : Type*} {a : ℝ} (ha : 0 < a) (f : ι → ℝ) (s : Finset ι) :
(a ^ ∑ x ∈ s, f x) = ∏ x ∈ s, a ^ f x :=
map_sum (⟨⟨fun (x : ℝ) => (a ^ x : ℝ), rpow_zero a⟩, rpow_add ha⟩ : ℝ →+ (Additive ℝ)) f s
#align real.rpow_sum_of_pos Real.rpow_sum_of_pos
theorem rpow_sum_of_nonneg {ι : Type*} {a : ℝ} (ha : 0 ≤ a) {s : Finset ι} {f : ι → ℝ}
(h : ∀ x ∈ s, 0 ≤ f x) : (a ^ ∑ x ∈ s, f x) = ∏ x ∈ s, a ^ f x := by
induction' s using Finset.cons_induction with i s hi ihs
· rw [sum_empty, Finset.prod_empty, rpow_zero]
· rw [forall_mem_cons] at h
rw [sum_cons, prod_cons, ← ihs h.2, rpow_add_of_nonneg ha h.1 (sum_nonneg h.2)]
#align real.rpow_sum_of_nonneg Real.rpow_sum_of_nonneg
theorem rpow_neg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ := by
simp only [rpow_def_of_nonneg hx]; split_ifs <;> simp_all [exp_neg]
#align real.rpow_neg Real.rpow_neg
theorem rpow_sub {x : ℝ} (hx : 0 < x) (y z : ℝ) : x ^ (y - z) = x ^ y / x ^ z := by
simp only [sub_eq_add_neg, rpow_add hx, rpow_neg (le_of_lt hx), div_eq_mul_inv]
#align real.rpow_sub Real.rpow_sub
theorem rpow_sub' {x : ℝ} (hx : 0 ≤ x) {y z : ℝ} (h : y - z ≠ 0) : x ^ (y - z) = x ^ y / x ^ z := by
simp only [sub_eq_add_neg] at h ⊢
simp only [rpow_add' hx h, rpow_neg hx, div_eq_mul_inv]
#align real.rpow_sub' Real.rpow_sub'
end Real
/-!
## Comparing real and complex powers
-/
namespace Complex
theorem ofReal_cpow {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : ((x ^ y : ℝ) : ℂ) = (x : ℂ) ^ (y : ℂ) := by
simp only [Real.rpow_def_of_nonneg hx, Complex.cpow_def, ofReal_eq_zero]; split_ifs <;>
simp [Complex.ofReal_log hx]
#align complex.of_real_cpow Complex.ofReal_cpow
theorem ofReal_cpow_of_nonpos {x : ℝ} (hx : x ≤ 0) (y : ℂ) :
(x : ℂ) ^ y = (-x : ℂ) ^ y * exp (π * I * y) := by
rcases hx.eq_or_lt with (rfl | hlt)
· rcases eq_or_ne y 0 with (rfl | hy) <;> simp [*]
have hne : (x : ℂ) ≠ 0 := ofReal_ne_zero.mpr hlt.ne
rw [cpow_def_of_ne_zero hne, cpow_def_of_ne_zero (neg_ne_zero.2 hne), ← exp_add, ← add_mul, log,
log, abs.map_neg, arg_ofReal_of_neg hlt, ← ofReal_neg,
arg_ofReal_of_nonneg (neg_nonneg.2 hx), ofReal_zero, zero_mul, add_zero]
#align complex.of_real_cpow_of_nonpos Complex.ofReal_cpow_of_nonpos
lemma cpow_ofReal (x : ℂ) (y : ℝ) :
x ^ (y : ℂ) = ↑(abs x ^ y) * (Real.cos (arg x * y) + Real.sin (arg x * y) * I) := by
rcases eq_or_ne x 0 with rfl | hx
· simp [ofReal_cpow le_rfl]
· rw [cpow_def_of_ne_zero hx, exp_eq_exp_re_mul_sin_add_cos, mul_comm (log x)]
norm_cast
rw [re_ofReal_mul, im_ofReal_mul, log_re, log_im, mul_comm y, mul_comm y, Real.exp_mul,
Real.exp_log]
rwa [abs.pos_iff]
lemma cpow_ofReal_re (x : ℂ) (y : ℝ) : (x ^ (y : ℂ)).re = (abs x) ^ y * Real.cos (arg x * y) := by
rw [cpow_ofReal]; generalize arg x * y = z; simp [Real.cos]
lemma cpow_ofReal_im (x : ℂ) (y : ℝ) : (x ^ (y : ℂ)).im = (abs x) ^ y * Real.sin (arg x * y) := by
rw [cpow_ofReal]; generalize arg x * y = z; simp [Real.sin]
theorem abs_cpow_of_ne_zero {z : ℂ} (hz : z ≠ 0) (w : ℂ) :
abs (z ^ w) = abs z ^ w.re / Real.exp (arg z * im w) := by
rw [cpow_def_of_ne_zero hz, abs_exp, mul_re, log_re, log_im, Real.exp_sub,
Real.rpow_def_of_pos (abs.pos hz)]
#align complex.abs_cpow_of_ne_zero Complex.abs_cpow_of_ne_zero
theorem abs_cpow_of_imp {z w : ℂ} (h : z = 0 → w.re = 0 → w = 0) :
abs (z ^ w) = abs z ^ w.re / Real.exp (arg z * im w) := by
rcases ne_or_eq z 0 with (hz | rfl) <;> [exact abs_cpow_of_ne_zero hz w; rw [map_zero]]
rcases eq_or_ne w.re 0 with hw | hw
· simp [hw, h rfl hw]
· rw [Real.zero_rpow hw, zero_div, zero_cpow, map_zero]
exact ne_of_apply_ne re hw
#align complex.abs_cpow_of_imp Complex.abs_cpow_of_imp
theorem abs_cpow_le (z w : ℂ) : abs (z ^ w) ≤ abs z ^ w.re / Real.exp (arg z * im w) := by
by_cases h : z = 0 → w.re = 0 → w = 0
· exact (abs_cpow_of_imp h).le
· push_neg at h
simp [h]
#align complex.abs_cpow_le Complex.abs_cpow_le
@[simp]
theorem abs_cpow_real (x : ℂ) (y : ℝ) : abs (x ^ (y : ℂ)) = Complex.abs x ^ y := by
rw [abs_cpow_of_imp] <;> simp
#align complex.abs_cpow_real Complex.abs_cpow_real
@[simp]
theorem abs_cpow_inv_nat (x : ℂ) (n : ℕ) : abs (x ^ (n⁻¹ : ℂ)) = Complex.abs x ^ (n⁻¹ : ℝ) := by
rw [← abs_cpow_real]; simp [-abs_cpow_real]
#align complex.abs_cpow_inv_nat Complex.abs_cpow_inv_nat
theorem abs_cpow_eq_rpow_re_of_pos {x : ℝ} (hx : 0 < x) (y : ℂ) : abs (x ^ y) = x ^ y.re := by
rw [abs_cpow_of_ne_zero (ofReal_ne_zero.mpr hx.ne'), arg_ofReal_of_nonneg hx.le,
zero_mul, Real.exp_zero, div_one, abs_of_nonneg hx.le]
#align complex.abs_cpow_eq_rpow_re_of_pos Complex.abs_cpow_eq_rpow_re_of_pos
theorem abs_cpow_eq_rpow_re_of_nonneg {x : ℝ} (hx : 0 ≤ x) {y : ℂ} (hy : re y ≠ 0) :
abs (x ^ y) = x ^ re y := by
rw [abs_cpow_of_imp] <;> simp [*, arg_ofReal_of_nonneg, _root_.abs_of_nonneg]
#align complex.abs_cpow_eq_rpow_re_of_nonneg Complex.abs_cpow_eq_rpow_re_of_nonneg
lemma norm_natCast_cpow_of_re_ne_zero (n : ℕ) {s : ℂ} (hs : s.re ≠ 0) :
‖(n : ℂ) ^ s‖ = (n : ℝ) ^ (s.re) := by
rw [norm_eq_abs, ← ofReal_natCast, abs_cpow_eq_rpow_re_of_nonneg n.cast_nonneg hs]
lemma norm_natCast_cpow_of_pos {n : ℕ} (hn : 0 < n) (s : ℂ) :
‖(n : ℂ) ^ s‖ = (n : ℝ) ^ (s.re) := by
rw [norm_eq_abs, ← ofReal_natCast, abs_cpow_eq_rpow_re_of_pos (Nat.cast_pos.mpr hn) _]
lemma norm_natCast_cpow_pos_of_pos {n : ℕ} (hn : 0 < n) (s : ℂ) : 0 < ‖(n : ℂ) ^ s‖ :=
(norm_natCast_cpow_of_pos hn _).symm ▸ Real.rpow_pos_of_pos (Nat.cast_pos.mpr hn) _
theorem cpow_mul_ofReal_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) (z : ℂ) :
(x : ℂ) ^ (↑y * z) = (↑(x ^ y) : ℂ) ^ z := by
rw [cpow_mul, ofReal_cpow hx]
· rw [← ofReal_log hx, ← ofReal_mul, ofReal_im, neg_lt_zero]; exact Real.pi_pos
· rw [← ofReal_log hx, ← ofReal_mul, ofReal_im]; exact Real.pi_pos.le
#align complex.cpow_mul_of_real_nonneg Complex.cpow_mul_ofReal_nonneg
end Complex
/-! ### Positivity extension -/
namespace Mathlib.Meta.Positivity
open Lean Meta Qq
/-- Extension for the `positivity` tactic: exponentiation by a real number is positive (namely 1)
when the exponent is zero. The other cases are done in `evalRpow`. -/
@[positivity (_ : ℝ) ^ (0 : ℝ)]
def evalRpowZero : PositivityExt where eval {u α} _ _ e := do
match u, α, e with
| 0, ~q(ℝ), ~q($a ^ (0 : ℝ)) =>
assertInstancesCommute
pure (.positive q(Real.rpow_zero_pos $a))
| _, _, _ => throwError "not Real.rpow"
/-- Extension for the `positivity` tactic: exponentiation by a real number is nonnegative when
the base is nonnegative and positive when the base is positive. -/
@[positivity (_ : ℝ) ^ (_ : ℝ)]
def evalRpow : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q($a ^ ($b : ℝ)) =>
let ra ← core q(inferInstance) q(inferInstance) a
assertInstancesCommute
match ra with
| .positive pa =>
pure (.positive q(Real.rpow_pos_of_pos $pa $b))
| .nonnegative pa =>
pure (.nonnegative q(Real.rpow_nonneg $pa $b))
| _ => pure .none
| _, _, _ => throwError "not Real.rpow"
end Mathlib.Meta.Positivity
/-!
## Further algebraic properties of `rpow`
-/
namespace Real
variable {x y z : ℝ} {n : ℕ}
theorem rpow_mul {x : ℝ} (hx : 0 ≤ x) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z := by
rw [← Complex.ofReal_inj, Complex.ofReal_cpow (rpow_nonneg hx _),
Complex.ofReal_cpow hx, Complex.ofReal_mul, Complex.cpow_mul, Complex.ofReal_cpow hx] <;>
simp only [(Complex.ofReal_mul _ _).symm, (Complex.ofReal_log hx).symm, Complex.ofReal_im,
neg_lt_zero, pi_pos, le_of_lt pi_pos]
#align real.rpow_mul Real.rpow_mul
theorem rpow_add_int {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℤ) : x ^ (y + n) = x ^ y * x ^ n := by
rw [rpow_def, rpow_def, Complex.ofReal_add,
Complex.cpow_add _ _ (Complex.ofReal_ne_zero.mpr hx), Complex.ofReal_intCast,
Complex.cpow_intCast, ← Complex.ofReal_zpow, mul_comm, Complex.re_ofReal_mul, mul_comm]
#align real.rpow_add_int Real.rpow_add_int
theorem rpow_add_nat {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℕ) : x ^ (y + n) = x ^ y * x ^ n := by
simpa using rpow_add_int hx y n
#align real.rpow_add_nat Real.rpow_add_nat
theorem rpow_sub_int {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℕ) : x ^ (y - n) = x ^ y / x ^ n := by
simpa using rpow_add_int hx y (-n)
#align real.rpow_sub_int Real.rpow_sub_int
theorem rpow_sub_nat {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℕ) : x ^ (y - n) = x ^ y / x ^ n := by
simpa using rpow_sub_int hx y n
#align real.rpow_sub_nat Real.rpow_sub_nat
lemma rpow_add_int' (hx : 0 ≤ x) {n : ℤ} (h : y + n ≠ 0) : x ^ (y + n) = x ^ y * x ^ n := by
rw [rpow_add' hx h, rpow_intCast]
lemma rpow_add_nat' (hx : 0 ≤ x) (h : y + n ≠ 0) : x ^ (y + n) = x ^ y * x ^ n := by
rw [rpow_add' hx h, rpow_natCast]
lemma rpow_sub_int' (hx : 0 ≤ x) {n : ℤ} (h : y - n ≠ 0) : x ^ (y - n) = x ^ y / x ^ n := by
rw [rpow_sub' hx h, rpow_intCast]
lemma rpow_sub_nat' (hx : 0 ≤ x) (h : y - n ≠ 0) : x ^ (y - n) = x ^ y / x ^ n := by
rw [rpow_sub' hx h, rpow_natCast]
theorem rpow_add_one {x : ℝ} (hx : x ≠ 0) (y : ℝ) : x ^ (y + 1) = x ^ y * x := by
simpa using rpow_add_nat hx y 1
#align real.rpow_add_one Real.rpow_add_one
theorem rpow_sub_one {x : ℝ} (hx : x ≠ 0) (y : ℝ) : x ^ (y - 1) = x ^ y / x := by
simpa using rpow_sub_nat hx y 1
#align real.rpow_sub_one Real.rpow_sub_one
lemma rpow_add_one' (hx : 0 ≤ x) (h : y + 1 ≠ 0) : x ^ (y + 1) = x ^ y * x := by
rw [rpow_add' hx h, rpow_one]
lemma rpow_one_add' (hx : 0 ≤ x) (h : 1 + y ≠ 0) : x ^ (1 + y) = x * x ^ y := by
rw [rpow_add' hx h, rpow_one]
lemma rpow_sub_one' (hx : 0 ≤ x) (h : y - 1 ≠ 0) : x ^ (y - 1) = x ^ y / x := by
rw [rpow_sub' hx h, rpow_one]
lemma rpow_one_sub' (hx : 0 ≤ x) (h : 1 - y ≠ 0) : x ^ (1 - y) = x / x ^ y := by
rw [rpow_sub' hx h, rpow_one]
@[simp]
theorem rpow_two (x : ℝ) : x ^ (2 : ℝ) = x ^ 2 := by
rw [← rpow_natCast]
simp only [Nat.cast_ofNat]
#align real.rpow_two Real.rpow_two
theorem rpow_neg_one (x : ℝ) : x ^ (-1 : ℝ) = x⁻¹ := by
suffices H : x ^ ((-1 : ℤ) : ℝ) = x⁻¹ by rwa [Int.cast_neg, Int.cast_one] at H
simp only [rpow_intCast, zpow_one, zpow_neg]
#align real.rpow_neg_one Real.rpow_neg_one
| Mathlib/Analysis/SpecialFunctions/Pow/Real.lean | 478 | 481 | theorem mul_rpow (hx : 0 ≤ x) (hy : 0 ≤ y) : (x * y) ^ z = x ^ z * y ^ z := by |
iterate 2 rw [Real.rpow_def_of_nonneg]; split_ifs with h_ifs <;> simp_all
· rw [log_mul ‹_› ‹_›, add_mul, exp_add, rpow_def_of_pos (hy.lt_of_ne' ‹_›)]
all_goals positivity
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Continuity
import Mathlib.Analysis.SpecialFunctions.Complex.LogDeriv
import Mathlib.Analysis.Calculus.FDeriv.Extend
import Mathlib.Analysis.Calculus.Deriv.Prod
import Mathlib.Analysis.SpecialFunctions.Log.Deriv
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Deriv
#align_import analysis.special_functions.pow.deriv from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Derivatives of power function on `ℂ`, `ℝ`, `ℝ≥0`, and `ℝ≥0∞`
We also prove differentiability and provide derivatives for the power functions `x ^ y`.
-/
noncomputable section
open scoped Classical Real Topology NNReal ENNReal Filter
open Filter
namespace Complex
theorem hasStrictFDerivAt_cpow {p : ℂ × ℂ} (hp : p.1 ∈ slitPlane) :
HasStrictFDerivAt (fun x : ℂ × ℂ => x.1 ^ x.2)
((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℂ ℂ ℂ +
(p.1 ^ p.2 * log p.1) • ContinuousLinearMap.snd ℂ ℂ ℂ) p := by
have A : p.1 ≠ 0 := slitPlane_ne_zero hp
have : (fun x : ℂ × ℂ => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) :=
((isOpen_ne.preimage continuous_fst).eventually_mem A).mono fun p hp =>
cpow_def_of_ne_zero hp _
rw [cpow_sub _ _ A, cpow_one, mul_div_left_comm, mul_smul, mul_smul]
refine HasStrictFDerivAt.congr_of_eventuallyEq ?_ this.symm
simpa only [cpow_def_of_ne_zero A, div_eq_mul_inv, mul_smul, add_comm, smul_add] using
((hasStrictFDerivAt_fst.clog hp).mul hasStrictFDerivAt_snd).cexp
#align complex.has_strict_fderiv_at_cpow Complex.hasStrictFDerivAt_cpow
theorem hasStrictFDerivAt_cpow' {x y : ℂ} (hp : x ∈ slitPlane) :
HasStrictFDerivAt (fun x : ℂ × ℂ => x.1 ^ x.2)
((y * x ^ (y - 1)) • ContinuousLinearMap.fst ℂ ℂ ℂ +
(x ^ y * log x) • ContinuousLinearMap.snd ℂ ℂ ℂ) (x, y) :=
@hasStrictFDerivAt_cpow (x, y) hp
#align complex.has_strict_fderiv_at_cpow' Complex.hasStrictFDerivAt_cpow'
theorem hasStrictDerivAt_const_cpow {x y : ℂ} (h : x ≠ 0 ∨ y ≠ 0) :
HasStrictDerivAt (fun y => x ^ y) (x ^ y * log x) y := by
rcases em (x = 0) with (rfl | hx)
· replace h := h.neg_resolve_left rfl
rw [log_zero, mul_zero]
refine (hasStrictDerivAt_const _ 0).congr_of_eventuallyEq ?_
exact (isOpen_ne.eventually_mem h).mono fun y hy => (zero_cpow hy).symm
· simpa only [cpow_def_of_ne_zero hx, mul_one] using
((hasStrictDerivAt_id y).const_mul (log x)).cexp
#align complex.has_strict_deriv_at_const_cpow Complex.hasStrictDerivAt_const_cpow
theorem hasFDerivAt_cpow {p : ℂ × ℂ} (hp : p.1 ∈ slitPlane) :
HasFDerivAt (fun x : ℂ × ℂ => x.1 ^ x.2)
((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℂ ℂ ℂ +
(p.1 ^ p.2 * log p.1) • ContinuousLinearMap.snd ℂ ℂ ℂ) p :=
(hasStrictFDerivAt_cpow hp).hasFDerivAt
#align complex.has_fderiv_at_cpow Complex.hasFDerivAt_cpow
end Complex
section fderiv
open Complex
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℂ E] {f g : E → ℂ} {f' g' : E →L[ℂ] ℂ}
{x : E} {s : Set E} {c : ℂ}
theorem HasStrictFDerivAt.cpow (hf : HasStrictFDerivAt f f' x) (hg : HasStrictFDerivAt g g' x)
(h0 : f x ∈ slitPlane) : HasStrictFDerivAt (fun x => f x ^ g x)
((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Complex.log (f x)) • g') x := by
convert (@hasStrictFDerivAt_cpow ((fun x => (f x, g x)) x) h0).comp x (hf.prod hg)
#align has_strict_fderiv_at.cpow HasStrictFDerivAt.cpow
theorem HasStrictFDerivAt.const_cpow (hf : HasStrictFDerivAt f f' x) (h0 : c ≠ 0 ∨ f x ≠ 0) :
HasStrictFDerivAt (fun x => c ^ f x) ((c ^ f x * Complex.log c) • f') x :=
(hasStrictDerivAt_const_cpow h0).comp_hasStrictFDerivAt x hf
#align has_strict_fderiv_at.const_cpow HasStrictFDerivAt.const_cpow
theorem HasFDerivAt.cpow (hf : HasFDerivAt f f' x) (hg : HasFDerivAt g g' x)
(h0 : f x ∈ slitPlane) : HasFDerivAt (fun x => f x ^ g x)
((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Complex.log (f x)) • g') x := by
convert (@Complex.hasFDerivAt_cpow ((fun x => (f x, g x)) x) h0).comp x (hf.prod hg)
#align has_fderiv_at.cpow HasFDerivAt.cpow
theorem HasFDerivAt.const_cpow (hf : HasFDerivAt f f' x) (h0 : c ≠ 0 ∨ f x ≠ 0) :
HasFDerivAt (fun x => c ^ f x) ((c ^ f x * Complex.log c) • f') x :=
(hasStrictDerivAt_const_cpow h0).hasDerivAt.comp_hasFDerivAt x hf
#align has_fderiv_at.const_cpow HasFDerivAt.const_cpow
theorem HasFDerivWithinAt.cpow (hf : HasFDerivWithinAt f f' s x) (hg : HasFDerivWithinAt g g' s x)
(h0 : f x ∈ slitPlane) : HasFDerivWithinAt (fun x => f x ^ g x)
((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Complex.log (f x)) • g') s x := by
convert
(@Complex.hasFDerivAt_cpow ((fun x => (f x, g x)) x) h0).comp_hasFDerivWithinAt x (hf.prod hg)
#align has_fderiv_within_at.cpow HasFDerivWithinAt.cpow
theorem HasFDerivWithinAt.const_cpow (hf : HasFDerivWithinAt f f' s x) (h0 : c ≠ 0 ∨ f x ≠ 0) :
HasFDerivWithinAt (fun x => c ^ f x) ((c ^ f x * Complex.log c) • f') s x :=
(hasStrictDerivAt_const_cpow h0).hasDerivAt.comp_hasFDerivWithinAt x hf
#align has_fderiv_within_at.const_cpow HasFDerivWithinAt.const_cpow
theorem DifferentiableAt.cpow (hf : DifferentiableAt ℂ f x) (hg : DifferentiableAt ℂ g x)
(h0 : f x ∈ slitPlane) : DifferentiableAt ℂ (fun x => f x ^ g x) x :=
(hf.hasFDerivAt.cpow hg.hasFDerivAt h0).differentiableAt
#align differentiable_at.cpow DifferentiableAt.cpow
theorem DifferentiableAt.const_cpow (hf : DifferentiableAt ℂ f x) (h0 : c ≠ 0 ∨ f x ≠ 0) :
DifferentiableAt ℂ (fun x => c ^ f x) x :=
(hf.hasFDerivAt.const_cpow h0).differentiableAt
#align differentiable_at.const_cpow DifferentiableAt.const_cpow
theorem DifferentiableWithinAt.cpow (hf : DifferentiableWithinAt ℂ f s x)
(hg : DifferentiableWithinAt ℂ g s x) (h0 : f x ∈ slitPlane) :
DifferentiableWithinAt ℂ (fun x => f x ^ g x) s x :=
(hf.hasFDerivWithinAt.cpow hg.hasFDerivWithinAt h0).differentiableWithinAt
#align differentiable_within_at.cpow DifferentiableWithinAt.cpow
theorem DifferentiableWithinAt.const_cpow (hf : DifferentiableWithinAt ℂ f s x)
(h0 : c ≠ 0 ∨ f x ≠ 0) : DifferentiableWithinAt ℂ (fun x => c ^ f x) s x :=
(hf.hasFDerivWithinAt.const_cpow h0).differentiableWithinAt
#align differentiable_within_at.const_cpow DifferentiableWithinAt.const_cpow
theorem DifferentiableOn.cpow (hf : DifferentiableOn ℂ f s) (hg : DifferentiableOn ℂ g s)
(h0 : Set.MapsTo f s slitPlane) : DifferentiableOn ℂ (fun x ↦ f x ^ g x) s :=
fun x hx ↦ (hf x hx).cpow (hg x hx) (h0 hx)
theorem DifferentiableOn.const_cpow (hf : DifferentiableOn ℂ f s)
(h0 : c ≠ 0 ∨ ∀ x ∈ s, f x ≠ 0) : DifferentiableOn ℂ (fun x ↦ c ^ f x) s :=
fun x hx ↦ (hf x hx).const_cpow (h0.imp_right fun h ↦ h x hx)
theorem Differentiable.cpow (hf : Differentiable ℂ f) (hg : Differentiable ℂ g)
(h0 : ∀ x, f x ∈ slitPlane) : Differentiable ℂ (fun x ↦ f x ^ g x) :=
fun x ↦ (hf x).cpow (hg x) (h0 x)
theorem Differentiable.const_cpow (hf : Differentiable ℂ f)
(h0 : c ≠ 0 ∨ ∀ x, f x ≠ 0) : Differentiable ℂ (fun x ↦ c ^ f x) :=
fun x ↦ (hf x).const_cpow (h0.imp_right fun h ↦ h x)
end fderiv
section deriv
open Complex
variable {f g : ℂ → ℂ} {s : Set ℂ} {f' g' x c : ℂ}
/-- A private lemma that rewrites the output of lemmas like `HasFDerivAt.cpow` to the form
expected by lemmas like `HasDerivAt.cpow`. -/
private theorem aux : ((g x * f x ^ (g x - 1)) • (1 : ℂ →L[ℂ] ℂ).smulRight f' +
(f x ^ g x * log (f x)) • (1 : ℂ →L[ℂ] ℂ).smulRight g') 1 =
g x * f x ^ (g x - 1) * f' + f x ^ g x * log (f x) * g' := by
simp only [Algebra.id.smul_eq_mul, one_mul, ContinuousLinearMap.one_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.add_apply, Pi.smul_apply,
ContinuousLinearMap.coe_smul']
nonrec theorem HasStrictDerivAt.cpow (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x)
(h0 : f x ∈ slitPlane) : HasStrictDerivAt (fun x => f x ^ g x)
(g x * f x ^ (g x - 1) * f' + f x ^ g x * Complex.log (f x) * g') x := by
simpa using (hf.cpow hg h0).hasStrictDerivAt
#align has_strict_deriv_at.cpow HasStrictDerivAt.cpow
theorem HasStrictDerivAt.const_cpow (hf : HasStrictDerivAt f f' x) (h : c ≠ 0 ∨ f x ≠ 0) :
HasStrictDerivAt (fun x => c ^ f x) (c ^ f x * Complex.log c * f') x :=
(hasStrictDerivAt_const_cpow h).comp x hf
#align has_strict_deriv_at.const_cpow HasStrictDerivAt.const_cpow
theorem Complex.hasStrictDerivAt_cpow_const (h : x ∈ slitPlane) :
HasStrictDerivAt (fun z : ℂ => z ^ c) (c * x ^ (c - 1)) x := by
simpa only [mul_zero, add_zero, mul_one] using
(hasStrictDerivAt_id x).cpow (hasStrictDerivAt_const x c) h
#align complex.has_strict_deriv_at_cpow_const Complex.hasStrictDerivAt_cpow_const
theorem HasStrictDerivAt.cpow_const (hf : HasStrictDerivAt f f' x)
(h0 : f x ∈ slitPlane) :
HasStrictDerivAt (fun x => f x ^ c) (c * f x ^ (c - 1) * f') x :=
(Complex.hasStrictDerivAt_cpow_const h0).comp x hf
#align has_strict_deriv_at.cpow_const HasStrictDerivAt.cpow_const
theorem HasDerivAt.cpow (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x)
(h0 : f x ∈ slitPlane) : HasDerivAt (fun x => f x ^ g x)
(g x * f x ^ (g x - 1) * f' + f x ^ g x * Complex.log (f x) * g') x := by
simpa only [aux] using (hf.hasFDerivAt.cpow hg h0).hasDerivAt
#align has_deriv_at.cpow HasDerivAt.cpow
theorem HasDerivAt.const_cpow (hf : HasDerivAt f f' x) (h0 : c ≠ 0 ∨ f x ≠ 0) :
HasDerivAt (fun x => c ^ f x) (c ^ f x * Complex.log c * f') x :=
(hasStrictDerivAt_const_cpow h0).hasDerivAt.comp x hf
#align has_deriv_at.const_cpow HasDerivAt.const_cpow
theorem HasDerivAt.cpow_const (hf : HasDerivAt f f' x) (h0 : f x ∈ slitPlane) :
HasDerivAt (fun x => f x ^ c) (c * f x ^ (c - 1) * f') x :=
(Complex.hasStrictDerivAt_cpow_const h0).hasDerivAt.comp x hf
#align has_deriv_at.cpow_const HasDerivAt.cpow_const
theorem HasDerivWithinAt.cpow (hf : HasDerivWithinAt f f' s x) (hg : HasDerivWithinAt g g' s x)
(h0 : f x ∈ slitPlane) : HasDerivWithinAt (fun x => f x ^ g x)
(g x * f x ^ (g x - 1) * f' + f x ^ g x * Complex.log (f x) * g') s x := by
simpa only [aux] using (hf.hasFDerivWithinAt.cpow hg h0).hasDerivWithinAt
#align has_deriv_within_at.cpow HasDerivWithinAt.cpow
theorem HasDerivWithinAt.const_cpow (hf : HasDerivWithinAt f f' s x) (h0 : c ≠ 0 ∨ f x ≠ 0) :
HasDerivWithinAt (fun x => c ^ f x) (c ^ f x * Complex.log c * f') s x :=
(hasStrictDerivAt_const_cpow h0).hasDerivAt.comp_hasDerivWithinAt x hf
#align has_deriv_within_at.const_cpow HasDerivWithinAt.const_cpow
theorem HasDerivWithinAt.cpow_const (hf : HasDerivWithinAt f f' s x)
(h0 : f x ∈ slitPlane) :
HasDerivWithinAt (fun x => f x ^ c) (c * f x ^ (c - 1) * f') s x :=
(Complex.hasStrictDerivAt_cpow_const h0).hasDerivAt.comp_hasDerivWithinAt x hf
#align has_deriv_within_at.cpow_const HasDerivWithinAt.cpow_const
/-- Although `fun x => x ^ r` for fixed `r` is *not* complex-differentiable along the negative real
line, it is still real-differentiable, and the derivative is what one would formally expect. -/
theorem hasDerivAt_ofReal_cpow {x : ℝ} (hx : x ≠ 0) {r : ℂ} (hr : r ≠ -1) :
HasDerivAt (fun y : ℝ => (y : ℂ) ^ (r + 1) / (r + 1)) (x ^ r) x := by
rw [Ne, ← add_eq_zero_iff_eq_neg, ← Ne] at hr
rcases lt_or_gt_of_ne hx.symm with (hx | hx)
· -- easy case : `0 < x`
-- Porting note: proof used to be
-- convert (((hasDerivAt_id (x : ℂ)).cpow_const _).div_const (r + 1)).comp_ofReal using 1
-- · rw [add_sub_cancel, id.def, mul_one, mul_comm, mul_div_cancel _ hr]
-- · rw [id.def, ofReal_re]; exact Or.inl hx
apply HasDerivAt.comp_ofReal (e := fun y => (y : ℂ) ^ (r + 1) / (r + 1))
convert HasDerivAt.div_const (𝕜 := ℂ) ?_ (r + 1) using 1
· exact (mul_div_cancel_right₀ _ hr).symm
· convert HasDerivAt.cpow_const ?_ ?_ using 1
· rw [add_sub_cancel_right, mul_comm]; exact (mul_one _).symm
· exact hasDerivAt_id (x : ℂ)
· simp [hx]
· -- harder case : `x < 0`
have : ∀ᶠ y : ℝ in 𝓝 x,
(y : ℂ) ^ (r + 1) / (r + 1) = (-y : ℂ) ^ (r + 1) * exp (π * I * (r + 1)) / (r + 1) := by
refine Filter.eventually_of_mem (Iio_mem_nhds hx) fun y hy => ?_
rw [ofReal_cpow_of_nonpos (le_of_lt hy)]
refine HasDerivAt.congr_of_eventuallyEq ?_ this
rw [ofReal_cpow_of_nonpos (le_of_lt hx)]
suffices HasDerivAt (fun y : ℝ => (-↑y) ^ (r + 1) * exp (↑π * I * (r + 1)))
((r + 1) * (-↑x) ^ r * exp (↑π * I * r)) x by
convert this.div_const (r + 1) using 1
conv_rhs => rw [mul_assoc, mul_comm, mul_div_cancel_right₀ _ hr]
rw [mul_add ((π : ℂ) * _), mul_one, exp_add, exp_pi_mul_I, mul_comm (_ : ℂ) (-1 : ℂ),
neg_one_mul]
simp_rw [mul_neg, ← neg_mul, ← ofReal_neg]
suffices HasDerivAt (fun y : ℝ => (↑(-y) : ℂ) ^ (r + 1)) (-(r + 1) * ↑(-x) ^ r) x by
convert this.neg.mul_const _ using 1; ring
suffices HasDerivAt (fun y : ℝ => (y : ℂ) ^ (r + 1)) ((r + 1) * ↑(-x) ^ r) (-x) by
convert @HasDerivAt.scomp ℝ _ ℂ _ _ x ℝ _ _ _ _ _ _ _ _ this (hasDerivAt_neg x) using 1
rw [real_smul, ofReal_neg 1, ofReal_one]; ring
suffices HasDerivAt (fun y : ℂ => y ^ (r + 1)) ((r + 1) * ↑(-x) ^ r) ↑(-x) by
exact this.comp_ofReal
conv in ↑_ ^ _ => rw [(by ring : r = r + 1 - 1)]
convert HasDerivAt.cpow_const ?_ ?_ using 1
· rw [add_sub_cancel_right, add_sub_cancel_right]; exact (mul_one _).symm
· exact hasDerivAt_id ((-x : ℝ) : ℂ)
· simp [hx]
#align has_deriv_at_of_real_cpow hasDerivAt_ofReal_cpow
end deriv
namespace Real
variable {x y z : ℝ}
/-- `(x, y) ↦ x ^ y` is strictly differentiable at `p : ℝ × ℝ` such that `0 < p.fst`. -/
theorem hasStrictFDerivAt_rpow_of_pos (p : ℝ × ℝ) (hp : 0 < p.1) :
HasStrictFDerivAt (fun x : ℝ × ℝ => x.1 ^ x.2)
((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℝ ℝ ℝ +
(p.1 ^ p.2 * log p.1) • ContinuousLinearMap.snd ℝ ℝ ℝ) p := by
have : (fun x : ℝ × ℝ => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) :=
(continuousAt_fst.eventually (lt_mem_nhds hp)).mono fun p hp => rpow_def_of_pos hp _
refine HasStrictFDerivAt.congr_of_eventuallyEq ?_ this.symm
convert ((hasStrictFDerivAt_fst.log hp.ne').mul hasStrictFDerivAt_snd).exp using 1
rw [rpow_sub_one hp.ne', ← rpow_def_of_pos hp, smul_add, smul_smul, mul_div_left_comm,
div_eq_mul_inv, smul_smul, smul_smul, mul_assoc, add_comm]
#align real.has_strict_fderiv_at_rpow_of_pos Real.hasStrictFDerivAt_rpow_of_pos
/-- `(x, y) ↦ x ^ y` is strictly differentiable at `p : ℝ × ℝ` such that `p.fst < 0`. -/
theorem hasStrictFDerivAt_rpow_of_neg (p : ℝ × ℝ) (hp : p.1 < 0) :
HasStrictFDerivAt (fun x : ℝ × ℝ => x.1 ^ x.2)
((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℝ ℝ ℝ +
(p.1 ^ p.2 * log p.1 - exp (log p.1 * p.2) * sin (p.2 * π) * π) •
ContinuousLinearMap.snd ℝ ℝ ℝ) p := by
have : (fun x : ℝ × ℝ => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) * cos (x.2 * π) :=
(continuousAt_fst.eventually (gt_mem_nhds hp)).mono fun p hp => rpow_def_of_neg hp _
refine HasStrictFDerivAt.congr_of_eventuallyEq ?_ this.symm
convert ((hasStrictFDerivAt_fst.log hp.ne).mul hasStrictFDerivAt_snd).exp.mul
(hasStrictFDerivAt_snd.mul_const π).cos using 1
simp_rw [rpow_sub_one hp.ne, smul_add, ← add_assoc, smul_smul, ← add_smul, ← mul_assoc,
mul_comm (cos _), ← rpow_def_of_neg hp]
rw [div_eq_mul_inv, add_comm]; congr 2 <;> ring
#align real.has_strict_fderiv_at_rpow_of_neg Real.hasStrictFDerivAt_rpow_of_neg
/-- The function `fun (x, y) => x ^ y` is infinitely smooth at `(x, y)` unless `x = 0`. -/
theorem contDiffAt_rpow_of_ne (p : ℝ × ℝ) (hp : p.1 ≠ 0) {n : ℕ∞} :
ContDiffAt ℝ n (fun p : ℝ × ℝ => p.1 ^ p.2) p := by
cases' hp.lt_or_lt with hneg hpos
exacts
[(((contDiffAt_fst.log hneg.ne).mul contDiffAt_snd).exp.mul
(contDiffAt_snd.mul contDiffAt_const).cos).congr_of_eventuallyEq
((continuousAt_fst.eventually (gt_mem_nhds hneg)).mono fun p hp => rpow_def_of_neg hp _),
((contDiffAt_fst.log hpos.ne').mul contDiffAt_snd).exp.congr_of_eventuallyEq
((continuousAt_fst.eventually (lt_mem_nhds hpos)).mono fun p hp => rpow_def_of_pos hp _)]
#align real.cont_diff_at_rpow_of_ne Real.contDiffAt_rpow_of_ne
theorem differentiableAt_rpow_of_ne (p : ℝ × ℝ) (hp : p.1 ≠ 0) :
DifferentiableAt ℝ (fun p : ℝ × ℝ => p.1 ^ p.2) p :=
(contDiffAt_rpow_of_ne p hp).differentiableAt le_rfl
#align real.differentiable_at_rpow_of_ne Real.differentiableAt_rpow_of_ne
theorem _root_.HasStrictDerivAt.rpow {f g : ℝ → ℝ} {f' g' : ℝ} (hf : HasStrictDerivAt f f' x)
(hg : HasStrictDerivAt g g' x) (h : 0 < f x) : HasStrictDerivAt (fun x => f x ^ g x)
(f' * g x * f x ^ (g x - 1) + g' * f x ^ g x * Real.log (f x)) x := by
convert (hasStrictFDerivAt_rpow_of_pos ((fun x => (f x, g x)) x) h).comp_hasStrictDerivAt x
(hf.prod hg) using 1
simp [mul_assoc, mul_comm, mul_left_comm]
#align has_strict_deriv_at.rpow HasStrictDerivAt.rpow
theorem hasStrictDerivAt_rpow_const_of_ne {x : ℝ} (hx : x ≠ 0) (p : ℝ) :
HasStrictDerivAt (fun x => x ^ p) (p * x ^ (p - 1)) x := by
cases' hx.lt_or_lt with hx hx
· have := (hasStrictFDerivAt_rpow_of_neg (x, p) hx).comp_hasStrictDerivAt x
((hasStrictDerivAt_id x).prod (hasStrictDerivAt_const _ _))
convert this using 1; simp
· simpa using (hasStrictDerivAt_id x).rpow (hasStrictDerivAt_const x p) hx
#align real.has_strict_deriv_at_rpow_const_of_ne Real.hasStrictDerivAt_rpow_const_of_ne
theorem hasStrictDerivAt_const_rpow {a : ℝ} (ha : 0 < a) (x : ℝ) :
HasStrictDerivAt (fun x => a ^ x) (a ^ x * log a) x := by
simpa using (hasStrictDerivAt_const _ _).rpow (hasStrictDerivAt_id x) ha
#align real.has_strict_deriv_at_const_rpow Real.hasStrictDerivAt_const_rpow
lemma differentiableAt_rpow_const_of_ne (p : ℝ) {x : ℝ} (hx : x ≠ 0) :
DifferentiableAt ℝ (fun x => x ^ p) x :=
(hasStrictDerivAt_rpow_const_of_ne hx p).differentiableAt
lemma differentiableOn_rpow_const (p : ℝ) :
DifferentiableOn ℝ (fun x => (x : ℝ) ^ p) {0}ᶜ :=
fun _ hx => (Real.differentiableAt_rpow_const_of_ne p hx).differentiableWithinAt
/-- This lemma says that `fun x => a ^ x` is strictly differentiable for `a < 0`. Note that these
values of `a` are outside of the "official" domain of `a ^ x`, and we may redefine `a ^ x`
for negative `a` if some other definition will be more convenient. -/
theorem hasStrictDerivAt_const_rpow_of_neg {a x : ℝ} (ha : a < 0) :
HasStrictDerivAt (fun x => a ^ x) (a ^ x * log a - exp (log a * x) * sin (x * π) * π) x := by
simpa using (hasStrictFDerivAt_rpow_of_neg (a, x) ha).comp_hasStrictDerivAt x
((hasStrictDerivAt_const _ _).prod (hasStrictDerivAt_id _))
#align real.has_strict_deriv_at_const_rpow_of_neg Real.hasStrictDerivAt_const_rpow_of_neg
end Real
namespace Real
variable {z x y : ℝ}
theorem hasDerivAt_rpow_const {x p : ℝ} (h : x ≠ 0 ∨ 1 ≤ p) :
HasDerivAt (fun x => x ^ p) (p * x ^ (p - 1)) x := by
rcases ne_or_eq x 0 with (hx | rfl)
· exact (hasStrictDerivAt_rpow_const_of_ne hx _).hasDerivAt
replace h : 1 ≤ p := h.neg_resolve_left rfl
apply hasDerivAt_of_hasDerivAt_of_ne fun x hx =>
(hasStrictDerivAt_rpow_const_of_ne hx p).hasDerivAt
exacts [continuousAt_id.rpow_const (Or.inr (zero_le_one.trans h)),
continuousAt_const.mul (continuousAt_id.rpow_const (Or.inr (sub_nonneg.2 h)))]
#align real.has_deriv_at_rpow_const Real.hasDerivAt_rpow_const
theorem differentiable_rpow_const {p : ℝ} (hp : 1 ≤ p) : Differentiable ℝ fun x : ℝ => x ^ p :=
fun _ => (hasDerivAt_rpow_const (Or.inr hp)).differentiableAt
#align real.differentiable_rpow_const Real.differentiable_rpow_const
theorem deriv_rpow_const {x p : ℝ} (h : x ≠ 0 ∨ 1 ≤ p) :
deriv (fun x : ℝ => x ^ p) x = p * x ^ (p - 1) :=
(hasDerivAt_rpow_const h).deriv
#align real.deriv_rpow_const Real.deriv_rpow_const
theorem deriv_rpow_const' {p : ℝ} (h : 1 ≤ p) :
(deriv fun x : ℝ => x ^ p) = fun x => p * x ^ (p - 1) :=
funext fun _ => deriv_rpow_const (Or.inr h)
#align real.deriv_rpow_const' Real.deriv_rpow_const'
theorem contDiffAt_rpow_const_of_ne {x p : ℝ} {n : ℕ∞} (h : x ≠ 0) :
ContDiffAt ℝ n (fun x => x ^ p) x :=
(contDiffAt_rpow_of_ne (x, p) h).comp x (contDiffAt_id.prod contDiffAt_const)
#align real.cont_diff_at_rpow_const_of_ne Real.contDiffAt_rpow_const_of_ne
theorem contDiff_rpow_const_of_le {p : ℝ} {n : ℕ} (h : ↑n ≤ p) :
ContDiff ℝ n fun x : ℝ => x ^ p := by
induction' n with n ihn generalizing p
· exact contDiff_zero.2 (continuous_id.rpow_const fun x => Or.inr <| by simpa using h)
· have h1 : 1 ≤ p := le_trans (by simp) h
rw [Nat.cast_succ, ← le_sub_iff_add_le] at h
rw [contDiff_succ_iff_deriv, deriv_rpow_const' h1]
exact ⟨differentiable_rpow_const h1, contDiff_const.mul (ihn h)⟩
#align real.cont_diff_rpow_const_of_le Real.contDiff_rpow_const_of_le
theorem contDiffAt_rpow_const_of_le {x p : ℝ} {n : ℕ} (h : ↑n ≤ p) :
ContDiffAt ℝ n (fun x : ℝ => x ^ p) x :=
(contDiff_rpow_const_of_le h).contDiffAt
#align real.cont_diff_at_rpow_const_of_le Real.contDiffAt_rpow_const_of_le
theorem contDiffAt_rpow_const {x p : ℝ} {n : ℕ} (h : x ≠ 0 ∨ ↑n ≤ p) :
ContDiffAt ℝ n (fun x : ℝ => x ^ p) x :=
h.elim contDiffAt_rpow_const_of_ne contDiffAt_rpow_const_of_le
#align real.cont_diff_at_rpow_const Real.contDiffAt_rpow_const
theorem hasStrictDerivAt_rpow_const {x p : ℝ} (hx : x ≠ 0 ∨ 1 ≤ p) :
HasStrictDerivAt (fun x => x ^ p) (p * x ^ (p - 1)) x :=
ContDiffAt.hasStrictDerivAt' (contDiffAt_rpow_const (by rwa [← Nat.cast_one] at hx))
(hasDerivAt_rpow_const hx) le_rfl
#align real.has_strict_deriv_at_rpow_const Real.hasStrictDerivAt_rpow_const
end Real
section Differentiability
open Real
section fderiv
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] {f g : E → ℝ} {f' g' : E →L[ℝ] ℝ}
{x : E} {s : Set E} {c p : ℝ} {n : ℕ∞}
theorem HasFDerivWithinAt.rpow (hf : HasFDerivWithinAt f f' s x) (hg : HasFDerivWithinAt g g' s x)
(h : 0 < f x) : HasFDerivWithinAt (fun x => f x ^ g x)
((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Real.log (f x)) • g') s x :=
(hasStrictFDerivAt_rpow_of_pos (f x, g x) h).hasFDerivAt.comp_hasFDerivWithinAt x (hf.prod hg)
#align has_fderiv_within_at.rpow HasFDerivWithinAt.rpow
theorem HasFDerivAt.rpow (hf : HasFDerivAt f f' x) (hg : HasFDerivAt g g' x) (h : 0 < f x) :
HasFDerivAt (fun x => f x ^ g x)
((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Real.log (f x)) • g') x :=
(hasStrictFDerivAt_rpow_of_pos (f x, g x) h).hasFDerivAt.comp x (hf.prod hg)
#align has_fderiv_at.rpow HasFDerivAt.rpow
theorem HasStrictFDerivAt.rpow (hf : HasStrictFDerivAt f f' x) (hg : HasStrictFDerivAt g g' x)
(h : 0 < f x) : HasStrictFDerivAt (fun x => f x ^ g x)
((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Real.log (f x)) • g') x :=
(hasStrictFDerivAt_rpow_of_pos (f x, g x) h).comp x (hf.prod hg)
#align has_strict_fderiv_at.rpow HasStrictFDerivAt.rpow
theorem DifferentiableWithinAt.rpow (hf : DifferentiableWithinAt ℝ f s x)
(hg : DifferentiableWithinAt ℝ g s x) (h : f x ≠ 0) :
DifferentiableWithinAt ℝ (fun x => f x ^ g x) s x :=
(differentiableAt_rpow_of_ne (f x, g x) h).comp_differentiableWithinAt x (hf.prod hg)
#align differentiable_within_at.rpow DifferentiableWithinAt.rpow
theorem DifferentiableAt.rpow (hf : DifferentiableAt ℝ f x) (hg : DifferentiableAt ℝ g x)
(h : f x ≠ 0) : DifferentiableAt ℝ (fun x => f x ^ g x) x :=
(differentiableAt_rpow_of_ne (f x, g x) h).comp x (hf.prod hg)
#align differentiable_at.rpow DifferentiableAt.rpow
theorem DifferentiableOn.rpow (hf : DifferentiableOn ℝ f s) (hg : DifferentiableOn ℝ g s)
(h : ∀ x ∈ s, f x ≠ 0) : DifferentiableOn ℝ (fun x => f x ^ g x) s := fun x hx =>
(hf x hx).rpow (hg x hx) (h x hx)
#align differentiable_on.rpow DifferentiableOn.rpow
theorem Differentiable.rpow (hf : Differentiable ℝ f) (hg : Differentiable ℝ g) (h : ∀ x, f x ≠ 0) :
Differentiable ℝ fun x => f x ^ g x := fun x => (hf x).rpow (hg x) (h x)
#align differentiable.rpow Differentiable.rpow
theorem HasFDerivWithinAt.rpow_const (hf : HasFDerivWithinAt f f' s x) (h : f x ≠ 0 ∨ 1 ≤ p) :
HasFDerivWithinAt (fun x => f x ^ p) ((p * f x ^ (p - 1)) • f') s x :=
(hasDerivAt_rpow_const h).comp_hasFDerivWithinAt x hf
#align has_fderiv_within_at.rpow_const HasFDerivWithinAt.rpow_const
theorem HasFDerivAt.rpow_const (hf : HasFDerivAt f f' x) (h : f x ≠ 0 ∨ 1 ≤ p) :
HasFDerivAt (fun x => f x ^ p) ((p * f x ^ (p - 1)) • f') x :=
(hasDerivAt_rpow_const h).comp_hasFDerivAt x hf
#align has_fderiv_at.rpow_const HasFDerivAt.rpow_const
theorem HasStrictFDerivAt.rpow_const (hf : HasStrictFDerivAt f f' x) (h : f x ≠ 0 ∨ 1 ≤ p) :
HasStrictFDerivAt (fun x => f x ^ p) ((p * f x ^ (p - 1)) • f') x :=
(hasStrictDerivAt_rpow_const h).comp_hasStrictFDerivAt x hf
#align has_strict_fderiv_at.rpow_const HasStrictFDerivAt.rpow_const
theorem DifferentiableWithinAt.rpow_const (hf : DifferentiableWithinAt ℝ f s x)
(h : f x ≠ 0 ∨ 1 ≤ p) : DifferentiableWithinAt ℝ (fun x => f x ^ p) s x :=
(hf.hasFDerivWithinAt.rpow_const h).differentiableWithinAt
#align differentiable_within_at.rpow_const DifferentiableWithinAt.rpow_const
@[simp]
theorem DifferentiableAt.rpow_const (hf : DifferentiableAt ℝ f x) (h : f x ≠ 0 ∨ 1 ≤ p) :
DifferentiableAt ℝ (fun x => f x ^ p) x :=
(hf.hasFDerivAt.rpow_const h).differentiableAt
#align differentiable_at.rpow_const DifferentiableAt.rpow_const
theorem DifferentiableOn.rpow_const (hf : DifferentiableOn ℝ f s) (h : ∀ x ∈ s, f x ≠ 0 ∨ 1 ≤ p) :
DifferentiableOn ℝ (fun x => f x ^ p) s := fun x hx => (hf x hx).rpow_const (h x hx)
#align differentiable_on.rpow_const DifferentiableOn.rpow_const
theorem Differentiable.rpow_const (hf : Differentiable ℝ f) (h : ∀ x, f x ≠ 0 ∨ 1 ≤ p) :
Differentiable ℝ fun x => f x ^ p := fun x => (hf x).rpow_const (h x)
#align differentiable.rpow_const Differentiable.rpow_const
theorem HasFDerivWithinAt.const_rpow (hf : HasFDerivWithinAt f f' s x) (hc : 0 < c) :
HasFDerivWithinAt (fun x => c ^ f x) ((c ^ f x * Real.log c) • f') s x :=
(hasStrictDerivAt_const_rpow hc (f x)).hasDerivAt.comp_hasFDerivWithinAt x hf
#align has_fderiv_within_at.const_rpow HasFDerivWithinAt.const_rpow
theorem HasFDerivAt.const_rpow (hf : HasFDerivAt f f' x) (hc : 0 < c) :
HasFDerivAt (fun x => c ^ f x) ((c ^ f x * Real.log c) • f') x :=
(hasStrictDerivAt_const_rpow hc (f x)).hasDerivAt.comp_hasFDerivAt x hf
#align has_fderiv_at.const_rpow HasFDerivAt.const_rpow
theorem HasStrictFDerivAt.const_rpow (hf : HasStrictFDerivAt f f' x) (hc : 0 < c) :
HasStrictFDerivAt (fun x => c ^ f x) ((c ^ f x * Real.log c) • f') x :=
(hasStrictDerivAt_const_rpow hc (f x)).comp_hasStrictFDerivAt x hf
#align has_strict_fderiv_at.const_rpow HasStrictFDerivAt.const_rpow
theorem ContDiffWithinAt.rpow (hf : ContDiffWithinAt ℝ n f s x) (hg : ContDiffWithinAt ℝ n g s x)
(h : f x ≠ 0) : ContDiffWithinAt ℝ n (fun x => f x ^ g x) s x :=
(contDiffAt_rpow_of_ne (f x, g x) h).comp_contDiffWithinAt x (hf.prod hg)
#align cont_diff_within_at.rpow ContDiffWithinAt.rpow
theorem ContDiffAt.rpow (hf : ContDiffAt ℝ n f x) (hg : ContDiffAt ℝ n g x) (h : f x ≠ 0) :
ContDiffAt ℝ n (fun x => f x ^ g x) x :=
(contDiffAt_rpow_of_ne (f x, g x) h).comp x (hf.prod hg)
#align cont_diff_at.rpow ContDiffAt.rpow
theorem ContDiffOn.rpow (hf : ContDiffOn ℝ n f s) (hg : ContDiffOn ℝ n g s) (h : ∀ x ∈ s, f x ≠ 0) :
ContDiffOn ℝ n (fun x => f x ^ g x) s := fun x hx => (hf x hx).rpow (hg x hx) (h x hx)
#align cont_diff_on.rpow ContDiffOn.rpow
theorem ContDiff.rpow (hf : ContDiff ℝ n f) (hg : ContDiff ℝ n g) (h : ∀ x, f x ≠ 0) :
ContDiff ℝ n fun x => f x ^ g x :=
contDiff_iff_contDiffAt.mpr fun x => hf.contDiffAt.rpow hg.contDiffAt (h x)
#align cont_diff.rpow ContDiff.rpow
theorem ContDiffWithinAt.rpow_const_of_ne (hf : ContDiffWithinAt ℝ n f s x) (h : f x ≠ 0) :
ContDiffWithinAt ℝ n (fun x => f x ^ p) s x :=
hf.rpow contDiffWithinAt_const h
#align cont_diff_within_at.rpow_const_of_ne ContDiffWithinAt.rpow_const_of_ne
theorem ContDiffAt.rpow_const_of_ne (hf : ContDiffAt ℝ n f x) (h : f x ≠ 0) :
ContDiffAt ℝ n (fun x => f x ^ p) x :=
hf.rpow contDiffAt_const h
#align cont_diff_at.rpow_const_of_ne ContDiffAt.rpow_const_of_ne
theorem ContDiffOn.rpow_const_of_ne (hf : ContDiffOn ℝ n f s) (h : ∀ x ∈ s, f x ≠ 0) :
ContDiffOn ℝ n (fun x => f x ^ p) s := fun x hx => (hf x hx).rpow_const_of_ne (h x hx)
#align cont_diff_on.rpow_const_of_ne ContDiffOn.rpow_const_of_ne
theorem ContDiff.rpow_const_of_ne (hf : ContDiff ℝ n f) (h : ∀ x, f x ≠ 0) :
ContDiff ℝ n fun x => f x ^ p :=
hf.rpow contDiff_const h
#align cont_diff.rpow_const_of_ne ContDiff.rpow_const_of_ne
variable {m : ℕ}
theorem ContDiffWithinAt.rpow_const_of_le (hf : ContDiffWithinAt ℝ m f s x) (h : ↑m ≤ p) :
ContDiffWithinAt ℝ m (fun x => f x ^ p) s x :=
(contDiffAt_rpow_const_of_le h).comp_contDiffWithinAt x hf
#align cont_diff_within_at.rpow_const_of_le ContDiffWithinAt.rpow_const_of_le
theorem ContDiffAt.rpow_const_of_le (hf : ContDiffAt ℝ m f x) (h : ↑m ≤ p) :
ContDiffAt ℝ m (fun x => f x ^ p) x := by
rw [← contDiffWithinAt_univ] at *; exact hf.rpow_const_of_le h
#align cont_diff_at.rpow_const_of_le ContDiffAt.rpow_const_of_le
theorem ContDiffOn.rpow_const_of_le (hf : ContDiffOn ℝ m f s) (h : ↑m ≤ p) :
ContDiffOn ℝ m (fun x => f x ^ p) s := fun x hx => (hf x hx).rpow_const_of_le h
#align cont_diff_on.rpow_const_of_le ContDiffOn.rpow_const_of_le
theorem ContDiff.rpow_const_of_le (hf : ContDiff ℝ m f) (h : ↑m ≤ p) :
ContDiff ℝ m fun x => f x ^ p :=
contDiff_iff_contDiffAt.mpr fun _ => hf.contDiffAt.rpow_const_of_le h
#align cont_diff.rpow_const_of_le ContDiff.rpow_const_of_le
end fderiv
section deriv
variable {f g : ℝ → ℝ} {f' g' x y p : ℝ} {s : Set ℝ}
theorem HasDerivWithinAt.rpow (hf : HasDerivWithinAt f f' s x) (hg : HasDerivWithinAt g g' s x)
(h : 0 < f x) : HasDerivWithinAt (fun x => f x ^ g x)
(f' * g x * f x ^ (g x - 1) + g' * f x ^ g x * Real.log (f x)) s x := by
convert (hf.hasFDerivWithinAt.rpow hg.hasFDerivWithinAt h).hasDerivWithinAt using 1
dsimp; ring
#align has_deriv_within_at.rpow HasDerivWithinAt.rpow
| Mathlib/Analysis/SpecialFunctions/Pow/Deriv.lean | 592 | 596 | theorem HasDerivAt.rpow (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) (h : 0 < f x) :
HasDerivAt (fun x => f x ^ g x)
(f' * g x * f x ^ (g x - 1) + g' * f x ^ g x * Real.log (f x)) x := by |
rw [← hasDerivWithinAt_univ] at *
exact hf.rpow hg h
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.TwoDim
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic
#align_import geometry.euclidean.angle.oriented.basic from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Oriented angles.
This file defines oriented angles in real inner product spaces.
## Main definitions
* `Orientation.oangle` is the oriented angle between two vectors with respect to an orientation.
## Implementation notes
The definitions here use the `Real.angle` type, angles modulo `2 * π`. For some purposes,
angles modulo `π` are more convenient, because results are true for such angles with less
configuration dependence. Results that are only equalities modulo `π` can be represented
modulo `2 * π` as equalities of `(2 : ℤ) • θ`.
## References
* Evan Chen, Euclidean Geometry in Mathematical Olympiads.
-/
noncomputable section
open FiniteDimensional Complex
open scoped Real RealInnerProductSpace ComplexConjugate
namespace Orientation
attribute [local instance] Complex.finrank_real_complex_fact
variable {V V' : Type*}
variable [NormedAddCommGroup V] [NormedAddCommGroup V']
variable [InnerProductSpace ℝ V] [InnerProductSpace ℝ V']
variable [Fact (finrank ℝ V = 2)] [Fact (finrank ℝ V' = 2)] (o : Orientation ℝ V (Fin 2))
local notation "ω" => o.areaForm
/-- The oriented angle from `x` to `y`, modulo `2 * π`. If either vector is 0, this is 0.
See `InnerProductGeometry.angle` for the corresponding unoriented angle definition. -/
def oangle (x y : V) : Real.Angle :=
Complex.arg (o.kahler x y)
#align orientation.oangle Orientation.oangle
/-- Oriented angles are continuous when the vectors involved are nonzero. -/
theorem continuousAt_oangle {x : V × V} (hx1 : x.1 ≠ 0) (hx2 : x.2 ≠ 0) :
ContinuousAt (fun y : V × V => o.oangle y.1 y.2) x := by
refine (Complex.continuousAt_arg_coe_angle ?_).comp ?_
· exact o.kahler_ne_zero hx1 hx2
exact ((continuous_ofReal.comp continuous_inner).add
((continuous_ofReal.comp o.areaForm'.continuous₂).mul continuous_const)).continuousAt
#align orientation.continuous_at_oangle Orientation.continuousAt_oangle
/-- If the first vector passed to `oangle` is 0, the result is 0. -/
@[simp]
theorem oangle_zero_left (x : V) : o.oangle 0 x = 0 := by simp [oangle]
#align orientation.oangle_zero_left Orientation.oangle_zero_left
/-- If the second vector passed to `oangle` is 0, the result is 0. -/
@[simp]
| Mathlib/Geometry/Euclidean/Angle/Oriented/Basic.lean | 73 | 73 | theorem oangle_zero_right (x : V) : o.oangle x 0 = 0 := by | simp [oangle]
|
/-
Copyright (c) 2020 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Monic
#align_import data.polynomial.lifts from "leanprover-community/mathlib"@"63417e01fbc711beaf25fa73b6edb395c0cfddd0"
/-!
# Polynomials that lift
Given semirings `R` and `S` with a morphism `f : R →+* S`, we define a subsemiring `lifts` of
`S[X]` by the image of `RingHom.of (map f)`.
Then, we prove that a polynomial that lifts can always be lifted to a polynomial of the same degree
and that a monic polynomial that lifts can be lifted to a monic polynomial (of the same degree).
## Main definition
* `lifts (f : R →+* S)` : the subsemiring of polynomials that lift.
## Main results
* `lifts_and_degree_eq` : A polynomial lifts if and only if it can be lifted to a polynomial
of the same degree.
* `lifts_and_degree_eq_and_monic` : A monic polynomial lifts if and only if it can be lifted to a
monic polynomial of the same degree.
* `lifts_iff_alg` : if `R` is commutative, a polynomial lifts if and only if it is in the image of
`mapAlg`, where `mapAlg : R[X] →ₐ[R] S[X]` is the only `R`-algebra map
that sends `X` to `X`.
## Implementation details
In general `R` and `S` are semiring, so `lifts` is a semiring. In the case of rings, see
`lifts_iff_lifts_ring`.
Since we do not assume `R` to be commutative, we cannot say in general that the set of polynomials
that lift is a subalgebra. (By `lift_iff` this is true if `R` is commutative.)
-/
open Polynomial
noncomputable section
namespace Polynomial
universe u v w
section Semiring
variable {R : Type u} [Semiring R] {S : Type v} [Semiring S] {f : R →+* S}
/-- We define the subsemiring of polynomials that lifts as the image of `RingHom.of (map f)`. -/
def lifts (f : R →+* S) : Subsemiring S[X] :=
RingHom.rangeS (mapRingHom f)
#align polynomial.lifts Polynomial.lifts
theorem mem_lifts (p : S[X]) : p ∈ lifts f ↔ ∃ q : R[X], map f q = p := by
simp only [coe_mapRingHom, lifts, RingHom.mem_rangeS]
#align polynomial.mem_lifts Polynomial.mem_lifts
theorem lifts_iff_set_range (p : S[X]) : p ∈ lifts f ↔ p ∈ Set.range (map f) := by
simp only [coe_mapRingHom, lifts, Set.mem_range, RingHom.mem_rangeS]
#align polynomial.lifts_iff_set_range Polynomial.lifts_iff_set_range
theorem lifts_iff_ringHom_rangeS (p : S[X]) : p ∈ lifts f ↔ p ∈ (mapRingHom f).rangeS := by
simp only [coe_mapRingHom, lifts, Set.mem_range, RingHom.mem_rangeS]
#align polynomial.lifts_iff_ring_hom_srange Polynomial.lifts_iff_ringHom_rangeS
theorem lifts_iff_coeff_lifts (p : S[X]) : p ∈ lifts f ↔ ∀ n : ℕ, p.coeff n ∈ Set.range f := by
rw [lifts_iff_ringHom_rangeS, mem_map_rangeS f]
rfl
#align polynomial.lifts_iff_coeff_lifts Polynomial.lifts_iff_coeff_lifts
/-- If `(r : R)`, then `C (f r)` lifts. -/
theorem C_mem_lifts (f : R →+* S) (r : R) : C (f r) ∈ lifts f :=
⟨C r, by
simp only [coe_mapRingHom, map_C, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true,
and_self_iff]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.C_mem_lifts Polynomial.C_mem_lifts
/-- If `(s : S)` is in the image of `f`, then `C s` lifts. -/
theorem C'_mem_lifts {f : R →+* S} {s : S} (h : s ∈ Set.range f) : C s ∈ lifts f := by
obtain ⟨r, rfl⟩ := Set.mem_range.1 h
use C r
simp only [coe_mapRingHom, map_C, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true,
and_self_iff]
set_option linter.uppercaseLean3 false in
#align polynomial.C'_mem_lifts Polynomial.C'_mem_lifts
/-- The polynomial `X` lifts. -/
theorem X_mem_lifts (f : R →+* S) : (X : S[X]) ∈ lifts f :=
⟨X, by
simp only [coe_mapRingHom, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true, map_X,
and_self_iff]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.X_mem_lifts Polynomial.X_mem_lifts
/-- The polynomial `X ^ n` lifts. -/
theorem X_pow_mem_lifts (f : R →+* S) (n : ℕ) : (X ^ n : S[X]) ∈ lifts f :=
⟨X ^ n, by
simp only [coe_mapRingHom, map_pow, Set.mem_univ, Subsemiring.coe_top, eq_self_iff_true,
map_X, and_self_iff]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.X_pow_mem_lifts Polynomial.X_pow_mem_lifts
/-- If `p` lifts and `(r : R)` then `r * p` lifts. -/
theorem base_mul_mem_lifts {p : S[X]} (r : R) (hp : p ∈ lifts f) : C (f r) * p ∈ lifts f := by
simp only [lifts, RingHom.mem_rangeS] at hp ⊢
obtain ⟨p₁, rfl⟩ := hp
use C r * p₁
simp only [coe_mapRingHom, map_C, map_mul]
#align polynomial.base_mul_mem_lifts Polynomial.base_mul_mem_lifts
/-- If `(s : S)` is in the image of `f`, then `monomial n s` lifts. -/
theorem monomial_mem_lifts {s : S} (n : ℕ) (h : s ∈ Set.range f) : monomial n s ∈ lifts f := by
obtain ⟨r, rfl⟩ := Set.mem_range.1 h
use monomial n r
simp only [coe_mapRingHom, Set.mem_univ, map_monomial, Subsemiring.coe_top, eq_self_iff_true,
and_self_iff]
#align polynomial.monomial_mem_lifts Polynomial.monomial_mem_lifts
/-- If `p` lifts then `p.erase n` lifts. -/
theorem erase_mem_lifts {p : S[X]} (n : ℕ) (h : p ∈ lifts f) : p.erase n ∈ lifts f := by
rw [lifts_iff_ringHom_rangeS, mem_map_rangeS] at h ⊢
intro k
by_cases hk : k = n
· use 0
simp only [hk, RingHom.map_zero, erase_same]
obtain ⟨i, hi⟩ := h k
use i
simp only [hi, hk, erase_ne, Ne, not_false_iff]
#align polynomial.erase_mem_lifts Polynomial.erase_mem_lifts
section LiftDeg
theorem monomial_mem_lifts_and_degree_eq {s : S} {n : ℕ} (hl : monomial n s ∈ lifts f) :
∃ q : R[X], map f q = monomial n s ∧ q.degree = (monomial n s).degree := by
by_cases hzero : s = 0
· use 0
simp only [hzero, degree_zero, eq_self_iff_true, and_self_iff, monomial_zero_right,
Polynomial.map_zero]
rw [lifts_iff_set_range] at hl
obtain ⟨q, hq⟩ := hl
replace hq := (ext_iff.1 hq) n
have hcoeff : f (q.coeff n) = s := by
simp? [coeff_monomial] at hq says simp only [coeff_map, coeff_monomial, ↓reduceIte] at hq
exact hq
use monomial n (q.coeff n)
constructor
· simp only [hcoeff, map_monomial]
have hqzero : q.coeff n ≠ 0 := by
intro habs
simp only [habs, RingHom.map_zero] at hcoeff
exact hzero hcoeff.symm
rw [← C_mul_X_pow_eq_monomial]
rw [← C_mul_X_pow_eq_monomial]
simp only [hzero, hqzero, Ne, not_false_iff, degree_C_mul_X_pow]
#align polynomial.monomial_mem_lifts_and_degree_eq Polynomial.monomial_mem_lifts_and_degree_eq
/-- A polynomial lifts if and only if it can be lifted to a polynomial of the same degree. -/
theorem mem_lifts_and_degree_eq {p : S[X]} (hlifts : p ∈ lifts f) :
∃ q : R[X], map f q = p ∧ q.degree = p.degree := by
generalize hd : p.natDegree = d
revert hd p
induction' d using Nat.strong_induction_on with n hn
intros p hlifts hdeg
by_cases erase_zero : p.eraseLead = 0
· rw [← eraseLead_add_monomial_natDegree_leadingCoeff p, erase_zero, zero_add, leadingCoeff]
exact
monomial_mem_lifts_and_degree_eq
(monomial_mem_lifts p.natDegree ((lifts_iff_coeff_lifts p).1 hlifts p.natDegree))
have deg_erase := Or.resolve_right (eraseLead_natDegree_lt_or_eraseLead_eq_zero p) erase_zero
have pzero : p ≠ 0 := by
intro habs
exfalso
rw [habs, eraseLead_zero, eq_self_iff_true, not_true] at erase_zero
exact erase_zero
have lead_zero : p.coeff p.natDegree ≠ 0 := by
rw [← leadingCoeff, Ne, leadingCoeff_eq_zero]; exact pzero
obtain ⟨lead, hlead⟩ :=
monomial_mem_lifts_and_degree_eq
(monomial_mem_lifts p.natDegree ((lifts_iff_coeff_lifts p).1 hlifts p.natDegree))
have deg_lead : lead.degree = p.natDegree := by
rw [hlead.2, ← C_mul_X_pow_eq_monomial, degree_C_mul_X_pow p.natDegree lead_zero]
rw [hdeg] at deg_erase
obtain ⟨erase, herase⟩ :=
hn p.eraseLead.natDegree deg_erase (erase_mem_lifts p.natDegree hlifts)
(refl p.eraseLead.natDegree)
use erase + lead
constructor
· simp only [hlead, herase, Polynomial.map_add]
rw [← eraseLead, ← leadingCoeff]
rw [eraseLead_add_monomial_natDegree_leadingCoeff p]
rw [degree_eq_natDegree pzero, ← deg_lead]
apply degree_add_eq_right_of_degree_lt
rw [herase.2, deg_lead, ← degree_eq_natDegree pzero]
exact degree_erase_lt pzero
#align polynomial.mem_lifts_and_degree_eq Polynomial.mem_lifts_and_degree_eq
end LiftDeg
section Monic
/-- A monic polynomial lifts if and only if it can be lifted to a monic polynomial
of the same degree. -/
theorem lifts_and_degree_eq_and_monic [Nontrivial S] {p : S[X]} (hlifts : p ∈ lifts f)
(hp : p.Monic) : ∃ q : R[X], map f q = p ∧ q.degree = p.degree ∧ q.Monic := by
cases' subsingleton_or_nontrivial R with hR hR
· obtain ⟨q, hq⟩ := mem_lifts_and_degree_eq hlifts
exact ⟨q, hq.1, hq.2, monic_of_subsingleton _⟩
have H : erase p.natDegree p + X ^ p.natDegree = p := by
simpa only [hp.leadingCoeff, C_1, one_mul, eraseLead] using eraseLead_add_C_mul_X_pow p
by_cases h0 : erase p.natDegree p = 0
· rw [← H, h0, zero_add]
refine ⟨X ^ p.natDegree, ?_, ?_, monic_X_pow p.natDegree⟩
· rw [Polynomial.map_pow, map_X]
· rw [degree_X_pow, degree_X_pow]
obtain ⟨q, hq⟩ := mem_lifts_and_degree_eq (erase_mem_lifts p.natDegree hlifts)
have p_neq_0 : p ≠ 0 := by intro hp; apply h0; rw [hp]; simp only [natDegree_zero, erase_zero]
have hdeg : q.degree < ((X : R[X]) ^ p.natDegree).degree := by
rw [@degree_X_pow R, hq.2, ← degree_eq_natDegree p_neq_0]
exact degree_erase_lt p_neq_0
refine ⟨q + X ^ p.natDegree, ?_, ?_, (monic_X_pow _).add_of_right hdeg⟩
· rw [Polynomial.map_add, hq.1, Polynomial.map_pow, map_X, H]
· rw [degree_add_eq_right_of_degree_lt hdeg, degree_X_pow, degree_eq_natDegree hp.ne_zero]
#align polynomial.lifts_and_degree_eq_and_monic Polynomial.lifts_and_degree_eq_and_monic
theorem lifts_and_natDegree_eq_and_monic {p : S[X]} (hlifts : p ∈ lifts f) (hp : p.Monic) :
∃ q : R[X], map f q = p ∧ q.natDegree = p.natDegree ∧ q.Monic := by
cases' subsingleton_or_nontrivial S with hR hR
· obtain rfl : p = 1 := Subsingleton.elim _ _
exact ⟨1, Subsingleton.elim _ _, by simp, by simp⟩
obtain ⟨p', h₁, h₂, h₃⟩ := lifts_and_degree_eq_and_monic hlifts hp
exact ⟨p', h₁, natDegree_eq_of_degree_eq h₂, h₃⟩
#align polynomial.lifts_and_nat_degree_eq_and_monic Polynomial.lifts_and_natDegree_eq_and_monic
end Monic
end Semiring
section Ring
variable {R : Type u} [Ring R] {S : Type v} [Ring S] (f : R →+* S)
/-- The subring of polynomials that lift. -/
def liftsRing (f : R →+* S) : Subring S[X] :=
RingHom.range (mapRingHom f)
#align polynomial.lifts_ring Polynomial.liftsRing
/-- If `R` and `S` are rings, `p` is in the subring of polynomials that lift if and only if it is in
the subsemiring of polynomials that lift. -/
theorem lifts_iff_liftsRing (p : S[X]) : p ∈ lifts f ↔ p ∈ liftsRing f := by
simp only [lifts, liftsRing, RingHom.mem_range, RingHom.mem_rangeS]
#align polynomial.lifts_iff_lifts_ring Polynomial.lifts_iff_liftsRing
end Ring
section Algebra
variable {R : Type u} [CommSemiring R] {S : Type v} [Semiring S] [Algebra R S]
/-- The map `R[X] → S[X]` as an algebra homomorphism. -/
def mapAlg (R : Type u) [CommSemiring R] (S : Type v) [Semiring S] [Algebra R S] :
R[X] →ₐ[R] S[X] :=
@aeval _ S[X] _ _ _ (X : S[X])
#align polynomial.map_alg Polynomial.mapAlg
/-- `mapAlg` is the morphism induced by `R → S`. -/
theorem mapAlg_eq_map (p : R[X]) : mapAlg R S p = map (algebraMap R S) p := by
simp only [mapAlg, aeval_def, eval₂_eq_sum, map, algebraMap_apply, RingHom.coe_comp]
ext; congr
#align polynomial.map_alg_eq_map Polynomial.mapAlg_eq_map
/-- A polynomial `p` lifts if and only if it is in the image of `mapAlg`. -/
theorem mem_lifts_iff_mem_alg (R : Type u) [CommSemiring R] {S : Type v} [Semiring S] [Algebra R S]
(p : S[X]) : p ∈ lifts (algebraMap R S) ↔ p ∈ AlgHom.range (@mapAlg R _ S _ _) := by
simp only [coe_mapRingHom, lifts, mapAlg_eq_map, AlgHom.mem_range, RingHom.mem_rangeS]
#align polynomial.mem_lifts_iff_mem_alg Polynomial.mem_lifts_iff_mem_alg
/-- If `p` lifts and `(r : R)` then `r • p` lifts. -/
| Mathlib/Algebra/Polynomial/Lifts.lean | 286 | 289 | theorem smul_mem_lifts {p : S[X]} (r : R) (hp : p ∈ lifts (algebraMap R S)) :
r • p ∈ lifts (algebraMap R S) := by |
rw [mem_lifts_iff_mem_alg] at hp ⊢
exact Subalgebra.smul_mem (mapAlg R S).range hp r
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl, Patrick Massot
-/
import Mathlib.Data.Set.Image
import Mathlib.Data.SProd
#align_import data.set.prod from "leanprover-community/mathlib"@"48fb5b5280e7c81672afc9524185ae994553ebf4"
/-!
# Sets in product and pi types
This file defines the product of sets in `α × β` and in `Π i, α i` along with the diagonal of a
type.
## Main declarations
* `Set.prod`: Binary product of sets. For `s : Set α`, `t : Set β`, we have
`s.prod t : Set (α × β)`.
* `Set.diagonal`: Diagonal of a type. `Set.diagonal α = {(x, x) | x : α}`.
* `Set.offDiag`: Off-diagonal. `s ×ˢ s` without the diagonal.
* `Set.pi`: Arbitrary product of sets.
-/
open Function
namespace Set
/-! ### Cartesian binary product of sets -/
section Prod
variable {α β γ δ : Type*} {s s₁ s₂ : Set α} {t t₁ t₂ : Set β} {a : α} {b : β}
theorem Subsingleton.prod (hs : s.Subsingleton) (ht : t.Subsingleton) :
(s ×ˢ t).Subsingleton := fun _x hx _y hy ↦
Prod.ext (hs hx.1 hy.1) (ht hx.2 hy.2)
noncomputable instance decidableMemProd [DecidablePred (· ∈ s)] [DecidablePred (· ∈ t)] :
DecidablePred (· ∈ s ×ˢ t) := fun _ => And.decidable
#align set.decidable_mem_prod Set.decidableMemProd
@[gcongr]
theorem prod_mono (hs : s₁ ⊆ s₂) (ht : t₁ ⊆ t₂) : s₁ ×ˢ t₁ ⊆ s₂ ×ˢ t₂ :=
fun _ ⟨h₁, h₂⟩ => ⟨hs h₁, ht h₂⟩
#align set.prod_mono Set.prod_mono
@[gcongr]
theorem prod_mono_left (hs : s₁ ⊆ s₂) : s₁ ×ˢ t ⊆ s₂ ×ˢ t :=
prod_mono hs Subset.rfl
#align set.prod_mono_left Set.prod_mono_left
@[gcongr]
theorem prod_mono_right (ht : t₁ ⊆ t₂) : s ×ˢ t₁ ⊆ s ×ˢ t₂ :=
prod_mono Subset.rfl ht
#align set.prod_mono_right Set.prod_mono_right
@[simp]
theorem prod_self_subset_prod_self : s₁ ×ˢ s₁ ⊆ s₂ ×ˢ s₂ ↔ s₁ ⊆ s₂ :=
⟨fun h _ hx => (h (mk_mem_prod hx hx)).1, fun h _ hx => ⟨h hx.1, h hx.2⟩⟩
#align set.prod_self_subset_prod_self Set.prod_self_subset_prod_self
@[simp]
theorem prod_self_ssubset_prod_self : s₁ ×ˢ s₁ ⊂ s₂ ×ˢ s₂ ↔ s₁ ⊂ s₂ :=
and_congr prod_self_subset_prod_self <| not_congr prod_self_subset_prod_self
#align set.prod_self_ssubset_prod_self Set.prod_self_ssubset_prod_self
theorem prod_subset_iff {P : Set (α × β)} : s ×ˢ t ⊆ P ↔ ∀ x ∈ s, ∀ y ∈ t, (x, y) ∈ P :=
⟨fun h _ hx _ hy => h (mk_mem_prod hx hy), fun h ⟨_, _⟩ hp => h _ hp.1 _ hp.2⟩
#align set.prod_subset_iff Set.prod_subset_iff
theorem forall_prod_set {p : α × β → Prop} : (∀ x ∈ s ×ˢ t, p x) ↔ ∀ x ∈ s, ∀ y ∈ t, p (x, y) :=
prod_subset_iff
#align set.forall_prod_set Set.forall_prod_set
theorem exists_prod_set {p : α × β → Prop} : (∃ x ∈ s ×ˢ t, p x) ↔ ∃ x ∈ s, ∃ y ∈ t, p (x, y) := by
simp [and_assoc]
#align set.exists_prod_set Set.exists_prod_set
@[simp]
theorem prod_empty : s ×ˢ (∅ : Set β) = ∅ := by
ext
exact and_false_iff _
#align set.prod_empty Set.prod_empty
@[simp]
theorem empty_prod : (∅ : Set α) ×ˢ t = ∅ := by
ext
exact false_and_iff _
#align set.empty_prod Set.empty_prod
@[simp, mfld_simps]
theorem univ_prod_univ : @univ α ×ˢ @univ β = univ := by
ext
exact true_and_iff _
#align set.univ_prod_univ Set.univ_prod_univ
theorem univ_prod {t : Set β} : (univ : Set α) ×ˢ t = Prod.snd ⁻¹' t := by simp [prod_eq]
#align set.univ_prod Set.univ_prod
theorem prod_univ {s : Set α} : s ×ˢ (univ : Set β) = Prod.fst ⁻¹' s := by simp [prod_eq]
#align set.prod_univ Set.prod_univ
@[simp] lemma prod_eq_univ [Nonempty α] [Nonempty β] : s ×ˢ t = univ ↔ s = univ ∧ t = univ := by
simp [eq_univ_iff_forall, forall_and]
@[simp]
theorem singleton_prod : ({a} : Set α) ×ˢ t = Prod.mk a '' t := by
ext ⟨x, y⟩
simp [and_left_comm, eq_comm]
#align set.singleton_prod Set.singleton_prod
@[simp]
theorem prod_singleton : s ×ˢ ({b} : Set β) = (fun a => (a, b)) '' s := by
ext ⟨x, y⟩
simp [and_left_comm, eq_comm]
#align set.prod_singleton Set.prod_singleton
theorem singleton_prod_singleton : ({a} : Set α) ×ˢ ({b} : Set β) = {(a, b)} := by simp
#align set.singleton_prod_singleton Set.singleton_prod_singleton
@[simp]
theorem union_prod : (s₁ ∪ s₂) ×ˢ t = s₁ ×ˢ t ∪ s₂ ×ˢ t := by
ext ⟨x, y⟩
simp [or_and_right]
#align set.union_prod Set.union_prod
@[simp]
theorem prod_union : s ×ˢ (t₁ ∪ t₂) = s ×ˢ t₁ ∪ s ×ˢ t₂ := by
ext ⟨x, y⟩
simp [and_or_left]
#align set.prod_union Set.prod_union
theorem inter_prod : (s₁ ∩ s₂) ×ˢ t = s₁ ×ˢ t ∩ s₂ ×ˢ t := by
ext ⟨x, y⟩
simp only [← and_and_right, mem_inter_iff, mem_prod]
#align set.inter_prod Set.inter_prod
theorem prod_inter : s ×ˢ (t₁ ∩ t₂) = s ×ˢ t₁ ∩ s ×ˢ t₂ := by
ext ⟨x, y⟩
simp only [← and_and_left, mem_inter_iff, mem_prod]
#align set.prod_inter Set.prod_inter
@[mfld_simps]
theorem prod_inter_prod : s₁ ×ˢ t₁ ∩ s₂ ×ˢ t₂ = (s₁ ∩ s₂) ×ˢ (t₁ ∩ t₂) := by
ext ⟨x, y⟩
simp [and_assoc, and_left_comm]
#align set.prod_inter_prod Set.prod_inter_prod
lemma compl_prod_eq_union {α β : Type*} (s : Set α) (t : Set β) :
(s ×ˢ t)ᶜ = (sᶜ ×ˢ univ) ∪ (univ ×ˢ tᶜ) := by
ext p
simp only [mem_compl_iff, mem_prod, not_and, mem_union, mem_univ, and_true, true_and]
constructor <;> intro h
· by_cases fst_in_s : p.fst ∈ s
· exact Or.inr (h fst_in_s)
· exact Or.inl fst_in_s
· intro fst_in_s
simpa only [fst_in_s, not_true, false_or] using h
@[simp]
theorem disjoint_prod : Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) ↔ Disjoint s₁ s₂ ∨ Disjoint t₁ t₂ := by
simp_rw [disjoint_left, mem_prod, not_and_or, Prod.forall, and_imp, ← @forall_or_right α, ←
@forall_or_left β, ← @forall_or_right (_ ∈ s₁), ← @forall_or_left (_ ∈ t₁)]
#align set.disjoint_prod Set.disjoint_prod
theorem Disjoint.set_prod_left (hs : Disjoint s₁ s₂) (t₁ t₂ : Set β) :
Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) :=
disjoint_left.2 fun ⟨_a, _b⟩ ⟨ha₁, _⟩ ⟨ha₂, _⟩ => disjoint_left.1 hs ha₁ ha₂
#align set.disjoint.set_prod_left Set.Disjoint.set_prod_left
theorem Disjoint.set_prod_right (ht : Disjoint t₁ t₂) (s₁ s₂ : Set α) :
Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) :=
disjoint_left.2 fun ⟨_a, _b⟩ ⟨_, hb₁⟩ ⟨_, hb₂⟩ => disjoint_left.1 ht hb₁ hb₂
#align set.disjoint.set_prod_right Set.Disjoint.set_prod_right
theorem insert_prod : insert a s ×ˢ t = Prod.mk a '' t ∪ s ×ˢ t := by
ext ⟨x, y⟩
simp (config := { contextual := true }) [image, iff_def, or_imp]
#align set.insert_prod Set.insert_prod
theorem prod_insert : s ×ˢ insert b t = (fun a => (a, b)) '' s ∪ s ×ˢ t := by
ext ⟨x, y⟩
-- porting note (#10745):
-- was `simp (config := { contextual := true }) [image, iff_def, or_imp, Imp.swap]`
simp only [mem_prod, mem_insert_iff, image, mem_union, mem_setOf_eq, Prod.mk.injEq]
refine ⟨fun h => ?_, fun h => ?_⟩
· obtain ⟨hx, rfl|hy⟩ := h
· exact Or.inl ⟨x, hx, rfl, rfl⟩
· exact Or.inr ⟨hx, hy⟩
· obtain ⟨x, hx, rfl, rfl⟩|⟨hx, hy⟩ := h
· exact ⟨hx, Or.inl rfl⟩
· exact ⟨hx, Or.inr hy⟩
#align set.prod_insert Set.prod_insert
theorem prod_preimage_eq {f : γ → α} {g : δ → β} :
(f ⁻¹' s) ×ˢ (g ⁻¹' t) = (fun p : γ × δ => (f p.1, g p.2)) ⁻¹' s ×ˢ t :=
rfl
#align set.prod_preimage_eq Set.prod_preimage_eq
theorem prod_preimage_left {f : γ → α} :
(f ⁻¹' s) ×ˢ t = (fun p : γ × β => (f p.1, p.2)) ⁻¹' s ×ˢ t :=
rfl
#align set.prod_preimage_left Set.prod_preimage_left
theorem prod_preimage_right {g : δ → β} :
s ×ˢ (g ⁻¹' t) = (fun p : α × δ => (p.1, g p.2)) ⁻¹' s ×ˢ t :=
rfl
#align set.prod_preimage_right Set.prod_preimage_right
theorem preimage_prod_map_prod (f : α → β) (g : γ → δ) (s : Set β) (t : Set δ) :
Prod.map f g ⁻¹' s ×ˢ t = (f ⁻¹' s) ×ˢ (g ⁻¹' t) :=
rfl
#align set.preimage_prod_map_prod Set.preimage_prod_map_prod
theorem mk_preimage_prod (f : γ → α) (g : γ → β) :
(fun x => (f x, g x)) ⁻¹' s ×ˢ t = f ⁻¹' s ∩ g ⁻¹' t :=
rfl
#align set.mk_preimage_prod Set.mk_preimage_prod
@[simp]
theorem mk_preimage_prod_left (hb : b ∈ t) : (fun a => (a, b)) ⁻¹' s ×ˢ t = s := by
ext a
simp [hb]
#align set.mk_preimage_prod_left Set.mk_preimage_prod_left
@[simp]
theorem mk_preimage_prod_right (ha : a ∈ s) : Prod.mk a ⁻¹' s ×ˢ t = t := by
ext b
simp [ha]
#align set.mk_preimage_prod_right Set.mk_preimage_prod_right
@[simp]
theorem mk_preimage_prod_left_eq_empty (hb : b ∉ t) : (fun a => (a, b)) ⁻¹' s ×ˢ t = ∅ := by
ext a
simp [hb]
#align set.mk_preimage_prod_left_eq_empty Set.mk_preimage_prod_left_eq_empty
@[simp]
theorem mk_preimage_prod_right_eq_empty (ha : a ∉ s) : Prod.mk a ⁻¹' s ×ˢ t = ∅ := by
ext b
simp [ha]
#align set.mk_preimage_prod_right_eq_empty Set.mk_preimage_prod_right_eq_empty
theorem mk_preimage_prod_left_eq_if [DecidablePred (· ∈ t)] :
(fun a => (a, b)) ⁻¹' s ×ˢ t = if b ∈ t then s else ∅ := by split_ifs with h <;> simp [h]
#align set.mk_preimage_prod_left_eq_if Set.mk_preimage_prod_left_eq_if
theorem mk_preimage_prod_right_eq_if [DecidablePred (· ∈ s)] :
Prod.mk a ⁻¹' s ×ˢ t = if a ∈ s then t else ∅ := by split_ifs with h <;> simp [h]
#align set.mk_preimage_prod_right_eq_if Set.mk_preimage_prod_right_eq_if
theorem mk_preimage_prod_left_fn_eq_if [DecidablePred (· ∈ t)] (f : γ → α) :
(fun a => (f a, b)) ⁻¹' s ×ˢ t = if b ∈ t then f ⁻¹' s else ∅ := by
rw [← mk_preimage_prod_left_eq_if, prod_preimage_left, preimage_preimage]
#align set.mk_preimage_prod_left_fn_eq_if Set.mk_preimage_prod_left_fn_eq_if
theorem mk_preimage_prod_right_fn_eq_if [DecidablePred (· ∈ s)] (g : δ → β) :
(fun b => (a, g b)) ⁻¹' s ×ˢ t = if a ∈ s then g ⁻¹' t else ∅ := by
rw [← mk_preimage_prod_right_eq_if, prod_preimage_right, preimage_preimage]
#align set.mk_preimage_prod_right_fn_eq_if Set.mk_preimage_prod_right_fn_eq_if
@[simp]
theorem preimage_swap_prod (s : Set α) (t : Set β) : Prod.swap ⁻¹' s ×ˢ t = t ×ˢ s := by
ext ⟨x, y⟩
simp [and_comm]
#align set.preimage_swap_prod Set.preimage_swap_prod
@[simp]
theorem image_swap_prod (s : Set α) (t : Set β) : Prod.swap '' s ×ˢ t = t ×ˢ s := by
rw [image_swap_eq_preimage_swap, preimage_swap_prod]
#align set.image_swap_prod Set.image_swap_prod
theorem prod_image_image_eq {m₁ : α → γ} {m₂ : β → δ} :
(m₁ '' s) ×ˢ (m₂ '' t) = (fun p : α × β => (m₁ p.1, m₂ p.2)) '' s ×ˢ t :=
ext <| by
simp [-exists_and_right, exists_and_right.symm, and_left_comm, and_assoc, and_comm]
#align set.prod_image_image_eq Set.prod_image_image_eq
theorem prod_range_range_eq {m₁ : α → γ} {m₂ : β → δ} :
range m₁ ×ˢ range m₂ = range fun p : α × β => (m₁ p.1, m₂ p.2) :=
ext <| by simp [range]
#align set.prod_range_range_eq Set.prod_range_range_eq
@[simp, mfld_simps]
theorem range_prod_map {m₁ : α → γ} {m₂ : β → δ} : range (Prod.map m₁ m₂) = range m₁ ×ˢ range m₂ :=
prod_range_range_eq.symm
#align set.range_prod_map Set.range_prod_map
theorem prod_range_univ_eq {m₁ : α → γ} :
range m₁ ×ˢ (univ : Set β) = range fun p : α × β => (m₁ p.1, p.2) :=
ext <| by simp [range]
#align set.prod_range_univ_eq Set.prod_range_univ_eq
theorem prod_univ_range_eq {m₂ : β → δ} :
(univ : Set α) ×ˢ range m₂ = range fun p : α × β => (p.1, m₂ p.2) :=
ext <| by simp [range]
#align set.prod_univ_range_eq Set.prod_univ_range_eq
theorem range_pair_subset (f : α → β) (g : α → γ) :
(range fun x => (f x, g x)) ⊆ range f ×ˢ range g := by
have : (fun x => (f x, g x)) = Prod.map f g ∘ fun x => (x, x) := funext fun x => rfl
rw [this, ← range_prod_map]
apply range_comp_subset_range
#align set.range_pair_subset Set.range_pair_subset
theorem Nonempty.prod : s.Nonempty → t.Nonempty → (s ×ˢ t).Nonempty := fun ⟨x, hx⟩ ⟨y, hy⟩ =>
⟨(x, y), ⟨hx, hy⟩⟩
#align set.nonempty.prod Set.Nonempty.prod
theorem Nonempty.fst : (s ×ˢ t).Nonempty → s.Nonempty := fun ⟨x, hx⟩ => ⟨x.1, hx.1⟩
#align set.nonempty.fst Set.Nonempty.fst
theorem Nonempty.snd : (s ×ˢ t).Nonempty → t.Nonempty := fun ⟨x, hx⟩ => ⟨x.2, hx.2⟩
#align set.nonempty.snd Set.Nonempty.snd
@[simp]
theorem prod_nonempty_iff : (s ×ˢ t).Nonempty ↔ s.Nonempty ∧ t.Nonempty :=
⟨fun h => ⟨h.fst, h.snd⟩, fun h => h.1.prod h.2⟩
#align set.prod_nonempty_iff Set.prod_nonempty_iff
@[simp]
theorem prod_eq_empty_iff : s ×ˢ t = ∅ ↔ s = ∅ ∨ t = ∅ := by
simp only [not_nonempty_iff_eq_empty.symm, prod_nonempty_iff, not_and_or]
#align set.prod_eq_empty_iff Set.prod_eq_empty_iff
theorem prod_sub_preimage_iff {W : Set γ} {f : α × β → γ} :
s ×ˢ t ⊆ f ⁻¹' W ↔ ∀ a b, a ∈ s → b ∈ t → f (a, b) ∈ W := by simp [subset_def]
#align set.prod_sub_preimage_iff Set.prod_sub_preimage_iff
theorem image_prod_mk_subset_prod {f : α → β} {g : α → γ} {s : Set α} :
(fun x => (f x, g x)) '' s ⊆ (f '' s) ×ˢ (g '' s) := by
rintro _ ⟨x, hx, rfl⟩
exact mk_mem_prod (mem_image_of_mem f hx) (mem_image_of_mem g hx)
#align set.image_prod_mk_subset_prod Set.image_prod_mk_subset_prod
theorem image_prod_mk_subset_prod_left (hb : b ∈ t) : (fun a => (a, b)) '' s ⊆ s ×ˢ t := by
rintro _ ⟨a, ha, rfl⟩
exact ⟨ha, hb⟩
#align set.image_prod_mk_subset_prod_left Set.image_prod_mk_subset_prod_left
theorem image_prod_mk_subset_prod_right (ha : a ∈ s) : Prod.mk a '' t ⊆ s ×ˢ t := by
rintro _ ⟨b, hb, rfl⟩
exact ⟨ha, hb⟩
#align set.image_prod_mk_subset_prod_right Set.image_prod_mk_subset_prod_right
theorem prod_subset_preimage_fst (s : Set α) (t : Set β) : s ×ˢ t ⊆ Prod.fst ⁻¹' s :=
inter_subset_left
#align set.prod_subset_preimage_fst Set.prod_subset_preimage_fst
theorem fst_image_prod_subset (s : Set α) (t : Set β) : Prod.fst '' s ×ˢ t ⊆ s :=
image_subset_iff.2 <| prod_subset_preimage_fst s t
#align set.fst_image_prod_subset Set.fst_image_prod_subset
theorem fst_image_prod (s : Set β) {t : Set α} (ht : t.Nonempty) : Prod.fst '' s ×ˢ t = s :=
(fst_image_prod_subset _ _).antisymm fun y hy =>
let ⟨x, hx⟩ := ht
⟨(y, x), ⟨hy, hx⟩, rfl⟩
#align set.fst_image_prod Set.fst_image_prod
theorem prod_subset_preimage_snd (s : Set α) (t : Set β) : s ×ˢ t ⊆ Prod.snd ⁻¹' t :=
inter_subset_right
#align set.prod_subset_preimage_snd Set.prod_subset_preimage_snd
theorem snd_image_prod_subset (s : Set α) (t : Set β) : Prod.snd '' s ×ˢ t ⊆ t :=
image_subset_iff.2 <| prod_subset_preimage_snd s t
#align set.snd_image_prod_subset Set.snd_image_prod_subset
theorem snd_image_prod {s : Set α} (hs : s.Nonempty) (t : Set β) : Prod.snd '' s ×ˢ t = t :=
(snd_image_prod_subset _ _).antisymm fun y y_in =>
let ⟨x, x_in⟩ := hs
⟨(x, y), ⟨x_in, y_in⟩, rfl⟩
#align set.snd_image_prod Set.snd_image_prod
theorem prod_diff_prod : s ×ˢ t \ s₁ ×ˢ t₁ = s ×ˢ (t \ t₁) ∪ (s \ s₁) ×ˢ t := by
ext x
by_cases h₁ : x.1 ∈ s₁ <;> by_cases h₂ : x.2 ∈ t₁ <;> simp [*]
#align set.prod_diff_prod Set.prod_diff_prod
/-- A product set is included in a product set if and only factors are included, or a factor of the
first set is empty. -/
theorem prod_subset_prod_iff : s ×ˢ t ⊆ s₁ ×ˢ t₁ ↔ s ⊆ s₁ ∧ t ⊆ t₁ ∨ s = ∅ ∨ t = ∅ := by
rcases (s ×ˢ t).eq_empty_or_nonempty with h | h
· simp [h, prod_eq_empty_iff.1 h]
have st : s.Nonempty ∧ t.Nonempty := by rwa [prod_nonempty_iff] at h
refine ⟨fun H => Or.inl ⟨?_, ?_⟩, ?_⟩
· have := image_subset (Prod.fst : α × β → α) H
rwa [fst_image_prod _ st.2, fst_image_prod _ (h.mono H).snd] at this
· have := image_subset (Prod.snd : α × β → β) H
rwa [snd_image_prod st.1, snd_image_prod (h.mono H).fst] at this
· intro H
simp only [st.1.ne_empty, st.2.ne_empty, or_false_iff] at H
exact prod_mono H.1 H.2
#align set.prod_subset_prod_iff Set.prod_subset_prod_iff
theorem prod_eq_prod_iff_of_nonempty (h : (s ×ˢ t).Nonempty) :
s ×ˢ t = s₁ ×ˢ t₁ ↔ s = s₁ ∧ t = t₁ := by
constructor
· intro heq
have h₁ : (s₁ ×ˢ t₁ : Set _).Nonempty := by rwa [← heq]
rw [prod_nonempty_iff] at h h₁
rw [← fst_image_prod s h.2, ← fst_image_prod s₁ h₁.2, heq, eq_self_iff_true, true_and_iff, ←
snd_image_prod h.1 t, ← snd_image_prod h₁.1 t₁, heq]
· rintro ⟨rfl, rfl⟩
rfl
#align set.prod_eq_prod_iff_of_nonempty Set.prod_eq_prod_iff_of_nonempty
theorem prod_eq_prod_iff :
s ×ˢ t = s₁ ×ˢ t₁ ↔ s = s₁ ∧ t = t₁ ∨ (s = ∅ ∨ t = ∅) ∧ (s₁ = ∅ ∨ t₁ = ∅) := by
symm
rcases eq_empty_or_nonempty (s ×ˢ t) with h | h
· simp_rw [h, @eq_comm _ ∅, prod_eq_empty_iff, prod_eq_empty_iff.mp h, true_and_iff,
or_iff_right_iff_imp]
rintro ⟨rfl, rfl⟩
exact prod_eq_empty_iff.mp h
rw [prod_eq_prod_iff_of_nonempty h]
rw [nonempty_iff_ne_empty, Ne, prod_eq_empty_iff] at h
simp_rw [h, false_and_iff, or_false_iff]
#align set.prod_eq_prod_iff Set.prod_eq_prod_iff
@[simp]
theorem prod_eq_iff_eq (ht : t.Nonempty) : s ×ˢ t = s₁ ×ˢ t ↔ s = s₁ := by
simp_rw [prod_eq_prod_iff, ht.ne_empty, and_true_iff, or_iff_left_iff_imp,
or_false_iff]
rintro ⟨rfl, rfl⟩
rfl
#align set.prod_eq_iff_eq Set.prod_eq_iff_eq
section Mono
variable [Preorder α] {f : α → Set β} {g : α → Set γ}
theorem _root_.Monotone.set_prod (hf : Monotone f) (hg : Monotone g) :
Monotone fun x => f x ×ˢ g x :=
fun _ _ h => prod_mono (hf h) (hg h)
#align monotone.set_prod Monotone.set_prod
theorem _root_.Antitone.set_prod (hf : Antitone f) (hg : Antitone g) :
Antitone fun x => f x ×ˢ g x :=
fun _ _ h => prod_mono (hf h) (hg h)
#align antitone.set_prod Antitone.set_prod
theorem _root_.MonotoneOn.set_prod (hf : MonotoneOn f s) (hg : MonotoneOn g s) :
MonotoneOn (fun x => f x ×ˢ g x) s := fun _ ha _ hb h => prod_mono (hf ha hb h) (hg ha hb h)
#align monotone_on.set_prod MonotoneOn.set_prod
theorem _root_.AntitoneOn.set_prod (hf : AntitoneOn f s) (hg : AntitoneOn g s) :
AntitoneOn (fun x => f x ×ˢ g x) s := fun _ ha _ hb h => prod_mono (hf ha hb h) (hg ha hb h)
#align antitone_on.set_prod AntitoneOn.set_prod
end Mono
end Prod
/-! ### Diagonal
In this section we prove some lemmas about the diagonal set `{p | p.1 = p.2}` and the diagonal map
`fun x ↦ (x, x)`.
-/
section Diagonal
variable {α : Type*} {s t : Set α}
lemma diagonal_nonempty [Nonempty α] : (diagonal α).Nonempty :=
Nonempty.elim ‹_› fun x => ⟨_, mem_diagonal x⟩
#align set.diagonal_nonempty Set.diagonal_nonempty
instance decidableMemDiagonal [h : DecidableEq α] (x : α × α) : Decidable (x ∈ diagonal α) :=
h x.1 x.2
#align set.decidable_mem_diagonal Set.decidableMemDiagonal
theorem preimage_coe_coe_diagonal (s : Set α) :
Prod.map (fun x : s => (x : α)) (fun x : s => (x : α)) ⁻¹' diagonal α = diagonal s := by
ext ⟨⟨x, hx⟩, ⟨y, hy⟩⟩
simp [Set.diagonal]
#align set.preimage_coe_coe_diagonal Set.preimage_coe_coe_diagonal
@[simp]
theorem range_diag : (range fun x => (x, x)) = diagonal α := by
ext ⟨x, y⟩
simp [diagonal, eq_comm]
#align set.range_diag Set.range_diag
theorem diagonal_subset_iff {s} : diagonal α ⊆ s ↔ ∀ x, (x, x) ∈ s := by
rw [← range_diag, range_subset_iff]
#align set.diagonal_subset_iff Set.diagonal_subset_iff
@[simp]
theorem prod_subset_compl_diagonal_iff_disjoint : s ×ˢ t ⊆ (diagonal α)ᶜ ↔ Disjoint s t :=
prod_subset_iff.trans disjoint_iff_forall_ne.symm
#align set.prod_subset_compl_diagonal_iff_disjoint Set.prod_subset_compl_diagonal_iff_disjoint
@[simp]
theorem diag_preimage_prod (s t : Set α) : (fun x => (x, x)) ⁻¹' s ×ˢ t = s ∩ t :=
rfl
#align set.diag_preimage_prod Set.diag_preimage_prod
theorem diag_preimage_prod_self (s : Set α) : (fun x => (x, x)) ⁻¹' s ×ˢ s = s :=
inter_self s
#align set.diag_preimage_prod_self Set.diag_preimage_prod_self
theorem diag_image (s : Set α) : (fun x => (x, x)) '' s = diagonal α ∩ s ×ˢ s := by
rw [← range_diag, ← image_preimage_eq_range_inter, diag_preimage_prod_self]
#align set.diag_image Set.diag_image
theorem diagonal_eq_univ_iff : diagonal α = univ ↔ Subsingleton α := by
simp only [subsingleton_iff, eq_univ_iff_forall, Prod.forall, mem_diagonal_iff]
theorem diagonal_eq_univ [Subsingleton α] : diagonal α = univ := diagonal_eq_univ_iff.2 ‹_›
end Diagonal
/-- A function is `Function.const α a` for some `a` if and only if `∀ x y, f x = f y`. -/
theorem range_const_eq_diagonal {α β : Type*} [hβ : Nonempty β] :
range (const α) = {f : α → β | ∀ x y, f x = f y} := by
refine (range_eq_iff _ _).mpr ⟨fun _ _ _ ↦ rfl, fun f hf ↦ ?_⟩
rcases isEmpty_or_nonempty α with h|⟨⟨a⟩⟩
· exact hβ.elim fun b ↦ ⟨b, Subsingleton.elim _ _⟩
· exact ⟨f a, funext fun x ↦ hf _ _⟩
end Set
section Pullback
open Set
variable {X Y Z}
/-- The fiber product $X \times_Y Z$. -/
abbrev Function.Pullback (f : X → Y) (g : Z → Y) := {p : X × Z // f p.1 = g p.2}
/-- The fiber product $X \times_Y X$. -/
abbrev Function.PullbackSelf (f : X → Y) := f.Pullback f
/-- The projection from the fiber product to the first factor. -/
def Function.Pullback.fst {f : X → Y} {g : Z → Y} (p : f.Pullback g) : X := p.val.1
/-- The projection from the fiber product to the second factor. -/
def Function.Pullback.snd {f : X → Y} {g : Z → Y} (p : f.Pullback g) : Z := p.val.2
open Function.Pullback in
lemma Function.pullback_comm_sq (f : X → Y) (g : Z → Y) :
f ∘ @fst X Y Z f g = g ∘ @snd X Y Z f g := funext fun p ↦ p.2
/-- The diagonal map $\Delta: X \to X \times_Y X$. -/
def toPullbackDiag (f : X → Y) (x : X) : f.Pullback f := ⟨(x, x), rfl⟩
/-- The diagonal $\Delta(X) \subseteq X \times_Y X$. -/
def Function.pullbackDiagonal (f : X → Y) : Set (f.Pullback f) := {p | p.fst = p.snd}
/-- Three functions between the three pairs of spaces $X_i, Y_i, Z_i$ that are compatible
induce a function $X_1 \times_{Y_1} Z_1 \to X_2 \times_{Y_2} Z_2$. -/
def Function.mapPullback {X₁ X₂ Y₁ Y₂ Z₁ Z₂}
{f₁ : X₁ → Y₁} {g₁ : Z₁ → Y₁} {f₂ : X₂ → Y₂} {g₂ : Z₂ → Y₂}
(mapX : X₁ → X₂) (mapY : Y₁ → Y₂) (mapZ : Z₁ → Z₂)
(commX : f₂ ∘ mapX = mapY ∘ f₁) (commZ : g₂ ∘ mapZ = mapY ∘ g₁)
(p : f₁.Pullback g₁) : f₂.Pullback g₂ :=
⟨(mapX p.fst, mapZ p.snd),
(congr_fun commX _).trans <| (congr_arg mapY p.2).trans <| congr_fun commZ.symm _⟩
open Function.Pullback in
/-- The projection $(X \times_Y Z) \times_Z (X \times_Y Z) \to X \times_Y X$. -/
def Function.PullbackSelf.map_fst {f : X → Y} {g : Z → Y} :
(@snd X Y Z f g).PullbackSelf → f.PullbackSelf :=
mapPullback fst g fst (pullback_comm_sq f g) (pullback_comm_sq f g)
open Function.Pullback in
/-- The projection $(X \times_Y Z) \times_X (X \times_Y Z) \to Z \times_Y Z$. -/
def Function.PullbackSelf.map_snd {f : X → Y} {g : Z → Y} :
(@fst X Y Z f g).PullbackSelf → g.PullbackSelf :=
mapPullback snd f snd (pullback_comm_sq f g).symm (pullback_comm_sq f g).symm
open Function.PullbackSelf Function.Pullback
theorem preimage_map_fst_pullbackDiagonal {f : X → Y} {g : Z → Y} :
@map_fst X Y Z f g ⁻¹' pullbackDiagonal f = pullbackDiagonal (@snd X Y Z f g) := by
ext ⟨⟨p₁, p₂⟩, he⟩
simp_rw [pullbackDiagonal, mem_setOf, Subtype.ext_iff, Prod.ext_iff]
exact (and_iff_left he).symm
theorem Function.Injective.preimage_pullbackDiagonal {f : X → Y} {g : Z → X} (inj : g.Injective) :
mapPullback g id g (by rfl) (by rfl) ⁻¹' pullbackDiagonal f = pullbackDiagonal (f ∘ g) :=
ext fun _ ↦ inj.eq_iff
theorem image_toPullbackDiag (f : X → Y) (s : Set X) :
toPullbackDiag f '' s = pullbackDiagonal f ∩ Subtype.val ⁻¹' s ×ˢ s := by
ext x
constructor
· rintro ⟨x, hx, rfl⟩
exact ⟨rfl, hx, hx⟩
· obtain ⟨⟨x, y⟩, h⟩ := x
rintro ⟨rfl : x = y, h2x⟩
exact mem_image_of_mem _ h2x.1
theorem range_toPullbackDiag (f : X → Y) : range (toPullbackDiag f) = pullbackDiagonal f := by
rw [← image_univ, image_toPullbackDiag, univ_prod_univ, preimage_univ, inter_univ]
theorem injective_toPullbackDiag (f : X → Y) : (toPullbackDiag f).Injective :=
fun _ _ h ↦ congr_arg Prod.fst (congr_arg Subtype.val h)
end Pullback
namespace Set
section OffDiag
variable {α : Type*} {s t : Set α} {x : α × α} {a : α}
theorem offDiag_mono : Monotone (offDiag : Set α → Set (α × α)) := fun _ _ h _ =>
And.imp (@h _) <| And.imp_left <| @h _
#align set.off_diag_mono Set.offDiag_mono
@[simp]
theorem offDiag_nonempty : s.offDiag.Nonempty ↔ s.Nontrivial := by
simp [offDiag, Set.Nonempty, Set.Nontrivial]
#align set.off_diag_nonempty Set.offDiag_nonempty
@[simp]
theorem offDiag_eq_empty : s.offDiag = ∅ ↔ s.Subsingleton := by
rw [← not_nonempty_iff_eq_empty, ← not_nontrivial_iff, offDiag_nonempty.not]
#align set.off_diag_eq_empty Set.offDiag_eq_empty
alias ⟨_, Nontrivial.offDiag_nonempty⟩ := offDiag_nonempty
#align set.nontrivial.off_diag_nonempty Set.Nontrivial.offDiag_nonempty
alias ⟨_, Subsingleton.offDiag_eq_empty⟩ := offDiag_nonempty
#align set.subsingleton.off_diag_eq_empty Set.Subsingleton.offDiag_eq_empty
variable (s t)
theorem offDiag_subset_prod : s.offDiag ⊆ s ×ˢ s := fun _ hx => ⟨hx.1, hx.2.1⟩
#align set.off_diag_subset_prod Set.offDiag_subset_prod
theorem offDiag_eq_sep_prod : s.offDiag = { x ∈ s ×ˢ s | x.1 ≠ x.2 } :=
ext fun _ => and_assoc.symm
#align set.off_diag_eq_sep_prod Set.offDiag_eq_sep_prod
@[simp]
theorem offDiag_empty : (∅ : Set α).offDiag = ∅ := by simp
#align set.off_diag_empty Set.offDiag_empty
@[simp]
theorem offDiag_singleton (a : α) : ({a} : Set α).offDiag = ∅ := by simp
#align set.off_diag_singleton Set.offDiag_singleton
@[simp]
theorem offDiag_univ : (univ : Set α).offDiag = (diagonal α)ᶜ :=
ext <| by simp
#align set.off_diag_univ Set.offDiag_univ
@[simp]
theorem prod_sdiff_diagonal : s ×ˢ s \ diagonal α = s.offDiag :=
ext fun _ => and_assoc
#align set.prod_sdiff_diagonal Set.prod_sdiff_diagonal
@[simp]
theorem disjoint_diagonal_offDiag : Disjoint (diagonal α) s.offDiag :=
disjoint_left.mpr fun _ hd ho => ho.2.2 hd
#align set.disjoint_diagonal_off_diag Set.disjoint_diagonal_offDiag
theorem offDiag_inter : (s ∩ t).offDiag = s.offDiag ∩ t.offDiag :=
ext fun x => by
simp only [mem_offDiag, mem_inter_iff]
tauto
#align set.off_diag_inter Set.offDiag_inter
variable {s t}
theorem offDiag_union (h : Disjoint s t) :
(s ∪ t).offDiag = s.offDiag ∪ t.offDiag ∪ s ×ˢ t ∪ t ×ˢ s := by
ext x
simp only [mem_offDiag, mem_union, ne_eq, mem_prod]
constructor
· rintro ⟨h0|h0, h1|h1, h2⟩ <;> simp [h0, h1, h2]
· rintro (((⟨h0, h1, h2⟩|⟨h0, h1, h2⟩)|⟨h0, h1⟩)|⟨h0, h1⟩) <;> simp [*]
· rintro h3
rw [h3] at h0
exact Set.disjoint_left.mp h h0 h1
· rintro h3
rw [h3] at h0
exact (Set.disjoint_right.mp h h0 h1).elim
#align set.off_diag_union Set.offDiag_union
theorem offDiag_insert (ha : a ∉ s) : (insert a s).offDiag = s.offDiag ∪ {a} ×ˢ s ∪ s ×ˢ {a} := by
rw [insert_eq, union_comm, offDiag_union, offDiag_singleton, union_empty, union_right_comm]
rw [disjoint_left]
rintro b hb (rfl : b = a)
exact ha hb
#align set.off_diag_insert Set.offDiag_insert
end OffDiag
/-! ### Cartesian set-indexed product of sets -/
section Pi
variable {ι : Type*} {α β : ι → Type*} {s s₁ s₂ : Set ι} {t t₁ t₂ : ∀ i, Set (α i)} {i : ι}
@[simp]
theorem empty_pi (s : ∀ i, Set (α i)) : pi ∅ s = univ := by
ext
simp [pi]
#align set.empty_pi Set.empty_pi
theorem subsingleton_univ_pi (ht : ∀ i, (t i).Subsingleton) :
(univ.pi t).Subsingleton := fun _f hf _g hg ↦ funext fun i ↦
(ht i) (hf _ <| mem_univ _) (hg _ <| mem_univ _)
@[simp]
theorem pi_univ (s : Set ι) : (pi s fun i => (univ : Set (α i))) = univ :=
eq_univ_of_forall fun _ _ _ => mem_univ _
#align set.pi_univ Set.pi_univ
@[simp]
theorem pi_univ_ite (s : Set ι) [DecidablePred (· ∈ s)] (t : ∀ i, Set (α i)) :
(pi univ fun i => if i ∈ s then t i else univ) = s.pi t := by
ext; simp_rw [Set.mem_pi]; apply forall_congr'; intro i; split_ifs with h <;> simp [h]
theorem pi_mono (h : ∀ i ∈ s, t₁ i ⊆ t₂ i) : pi s t₁ ⊆ pi s t₂ := fun _ hx i hi => h i hi <| hx i hi
#align set.pi_mono Set.pi_mono
theorem pi_inter_distrib : (s.pi fun i => t i ∩ t₁ i) = s.pi t ∩ s.pi t₁ :=
ext fun x => by simp only [forall_and, mem_pi, mem_inter_iff]
#align set.pi_inter_distrib Set.pi_inter_distrib
theorem pi_congr (h : s₁ = s₂) (h' : ∀ i ∈ s₁, t₁ i = t₂ i) : s₁.pi t₁ = s₂.pi t₂ :=
h ▸ ext fun _ => forall₂_congr fun i hi => h' i hi ▸ Iff.rfl
#align set.pi_congr Set.pi_congr
theorem pi_eq_empty (hs : i ∈ s) (ht : t i = ∅) : s.pi t = ∅ := by
ext f
simp only [mem_empty_iff_false, not_forall, iff_false_iff, mem_pi, Classical.not_imp]
exact ⟨i, hs, by simp [ht]⟩
#align set.pi_eq_empty Set.pi_eq_empty
theorem univ_pi_eq_empty (ht : t i = ∅) : pi univ t = ∅ :=
pi_eq_empty (mem_univ i) ht
#align set.univ_pi_eq_empty Set.univ_pi_eq_empty
theorem pi_nonempty_iff : (s.pi t).Nonempty ↔ ∀ i, ∃ x, i ∈ s → x ∈ t i := by
simp [Classical.skolem, Set.Nonempty]
#align set.pi_nonempty_iff Set.pi_nonempty_iff
theorem univ_pi_nonempty_iff : (pi univ t).Nonempty ↔ ∀ i, (t i).Nonempty := by
simp [Classical.skolem, Set.Nonempty]
#align set.univ_pi_nonempty_iff Set.univ_pi_nonempty_iff
theorem pi_eq_empty_iff : s.pi t = ∅ ↔ ∃ i, IsEmpty (α i) ∨ i ∈ s ∧ t i = ∅ := by
rw [← not_nonempty_iff_eq_empty, pi_nonempty_iff]
push_neg
refine exists_congr fun i => ?_
cases isEmpty_or_nonempty (α i) <;> simp [*, forall_and, eq_empty_iff_forall_not_mem]
#align set.pi_eq_empty_iff Set.pi_eq_empty_iff
@[simp]
theorem univ_pi_eq_empty_iff : pi univ t = ∅ ↔ ∃ i, t i = ∅ := by
simp [← not_nonempty_iff_eq_empty, univ_pi_nonempty_iff]
#align set.univ_pi_eq_empty_iff Set.univ_pi_eq_empty_iff
@[simp]
theorem univ_pi_empty [h : Nonempty ι] : pi univ (fun _ => ∅ : ∀ i, Set (α i)) = ∅ :=
univ_pi_eq_empty_iff.2 <| h.elim fun x => ⟨x, rfl⟩
#align set.univ_pi_empty Set.univ_pi_empty
@[simp]
theorem disjoint_univ_pi : Disjoint (pi univ t₁) (pi univ t₂) ↔ ∃ i, Disjoint (t₁ i) (t₂ i) := by
simp only [disjoint_iff_inter_eq_empty, ← pi_inter_distrib, univ_pi_eq_empty_iff]
#align set.disjoint_univ_pi Set.disjoint_univ_pi
theorem Disjoint.set_pi (hi : i ∈ s) (ht : Disjoint (t₁ i) (t₂ i)) : Disjoint (s.pi t₁) (s.pi t₂) :=
disjoint_left.2 fun _ h₁ h₂ => disjoint_left.1 ht (h₁ _ hi) (h₂ _ hi)
#align set.disjoint.set_pi Set.Disjoint.set_pi
theorem uniqueElim_preimage [Unique ι] (t : ∀ i, Set (α i)) :
uniqueElim ⁻¹' pi univ t = t (default : ι) := by ext; simp [Unique.forall_iff]
section Nonempty
variable [∀ i, Nonempty (α i)]
| Mathlib/Data/Set/Prod.lean | 786 | 786 | theorem pi_eq_empty_iff' : s.pi t = ∅ ↔ ∃ i ∈ s, t i = ∅ := by | simp [pi_eq_empty_iff]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Yury Kudryashov
-/
import Mathlib.Data.Rat.Sqrt
import Mathlib.Data.Real.Sqrt
import Mathlib.RingTheory.Algebraic
import Mathlib.RingTheory.Int.Basic
import Mathlib.Tactic.IntervalCases
#align_import data.real.irrational from "leanprover-community/mathlib"@"7e7aaccf9b0182576cabdde36cf1b5ad3585b70d"
/-!
# Irrational real numbers
In this file we define a predicate `Irrational` on `ℝ`, prove that the `n`-th root of an integer
number is irrational if it is not integer, and that `sqrt q` is irrational if and only if
`Rat.sqrt q * Rat.sqrt q ≠ q ∧ 0 ≤ q`.
We also provide dot-style constructors like `Irrational.add_rat`, `Irrational.rat_sub` etc.
-/
open Rat Real multiplicity
/-- A real number is irrational if it is not equal to any rational number. -/
def Irrational (x : ℝ) :=
x ∉ Set.range ((↑) : ℚ → ℝ)
#align irrational Irrational
theorem irrational_iff_ne_rational (x : ℝ) : Irrational x ↔ ∀ a b : ℤ, x ≠ a / b := by
simp only [Irrational, Rat.forall, cast_mk, not_exists, Set.mem_range, cast_intCast, cast_div,
eq_comm]
#align irrational_iff_ne_rational irrational_iff_ne_rational
/-- A transcendental real number is irrational. -/
theorem Transcendental.irrational {r : ℝ} (tr : Transcendental ℚ r) : Irrational r := by
rintro ⟨a, rfl⟩
exact tr (isAlgebraic_algebraMap a)
#align transcendental.irrational Transcendental.irrational
/-!
### Irrationality of roots of integer and rational numbers
-/
/-- If `x^n`, `n > 0`, is integer and is not the `n`-th power of an integer, then
`x` is irrational. -/
theorem irrational_nrt_of_notint_nrt {x : ℝ} (n : ℕ) (m : ℤ) (hxr : x ^ n = m)
(hv : ¬∃ y : ℤ, x = y) (hnpos : 0 < n) : Irrational x := by
rintro ⟨⟨N, D, P, C⟩, rfl⟩
rw [← cast_pow] at hxr
have c1 : ((D : ℤ) : ℝ) ≠ 0 := by
rw [Int.cast_ne_zero, Int.natCast_ne_zero]
exact P
have c2 : ((D : ℤ) : ℝ) ^ n ≠ 0 := pow_ne_zero _ c1
rw [mk'_eq_divInt, cast_pow, cast_mk, div_pow, div_eq_iff_mul_eq c2, ← Int.cast_pow,
← Int.cast_pow, ← Int.cast_mul, Int.cast_inj] at hxr
have hdivn : (D : ℤ) ^ n ∣ N ^ n := Dvd.intro_left m hxr
rw [← Int.dvd_natAbs, ← Int.natCast_pow, Int.natCast_dvd_natCast, Int.natAbs_pow,
Nat.pow_dvd_pow_iff hnpos.ne'] at hdivn
obtain rfl : D = 1 := by rw [← Nat.gcd_eq_right hdivn, C.gcd_eq_one]
refine hv ⟨N, ?_⟩
rw [mk'_eq_divInt, Int.ofNat_one, divInt_one, cast_intCast]
#align irrational_nrt_of_notint_nrt irrational_nrt_of_notint_nrt
/-- If `x^n = m` is an integer and `n` does not divide the `multiplicity p m`, then `x`
is irrational. -/
theorem irrational_nrt_of_n_not_dvd_multiplicity {x : ℝ} (n : ℕ) {m : ℤ} (hm : m ≠ 0) (p : ℕ)
[hp : Fact p.Prime] (hxr : x ^ n = m)
(hv : (multiplicity (p : ℤ) m).get (finite_int_iff.2 ⟨hp.1.ne_one, hm⟩) % n ≠ 0) :
Irrational x := by
rcases Nat.eq_zero_or_pos n with (rfl | hnpos)
· rw [eq_comm, pow_zero, ← Int.cast_one, Int.cast_inj] at hxr
simp [hxr, multiplicity.one_right (mt isUnit_iff_dvd_one.1
(mt Int.natCast_dvd_natCast.1 hp.1.not_dvd_one)), Nat.zero_mod] at hv
refine irrational_nrt_of_notint_nrt _ _ hxr ?_ hnpos
rintro ⟨y, rfl⟩
rw [← Int.cast_pow, Int.cast_inj] at hxr
subst m
have : y ≠ 0 := by rintro rfl; rw [zero_pow hnpos.ne'] at hm; exact hm rfl
erw [multiplicity.pow' (Nat.prime_iff_prime_int.1 hp.1) (finite_int_iff.2 ⟨hp.1.ne_one, this⟩),
Nat.mul_mod_right] at hv
exact hv rfl
#align irrational_nrt_of_n_not_dvd_multiplicity irrational_nrt_of_n_not_dvd_multiplicity
theorem irrational_sqrt_of_multiplicity_odd (m : ℤ) (hm : 0 < m) (p : ℕ) [hp : Fact p.Prime]
(Hpv :
(multiplicity (p : ℤ) m).get (finite_int_iff.2 ⟨hp.1.ne_one, (ne_of_lt hm).symm⟩) % 2 = 1) :
Irrational (√m) :=
@irrational_nrt_of_n_not_dvd_multiplicity _ 2 _ (Ne.symm (ne_of_lt hm)) p hp
(sq_sqrt (Int.cast_nonneg.2 <| le_of_lt hm)) (by rw [Hpv]; exact one_ne_zero)
#align irrational_sqrt_of_multiplicity_odd irrational_sqrt_of_multiplicity_odd
theorem Nat.Prime.irrational_sqrt {p : ℕ} (hp : Nat.Prime p) : Irrational (√p) :=
@irrational_sqrt_of_multiplicity_odd p (Int.natCast_pos.2 hp.pos) p ⟨hp⟩ <| by
simp [multiplicity.multiplicity_self
(mt isUnit_iff_dvd_one.1 (mt Int.natCast_dvd_natCast.1 hp.not_dvd_one))]
#align nat.prime.irrational_sqrt Nat.Prime.irrational_sqrt
/-- **Irrationality of the Square Root of 2** -/
theorem irrational_sqrt_two : Irrational (√2) := by
simpa using Nat.prime_two.irrational_sqrt
#align irrational_sqrt_two irrational_sqrt_two
theorem irrational_sqrt_rat_iff (q : ℚ) :
Irrational (√q) ↔ Rat.sqrt q * Rat.sqrt q ≠ q ∧ 0 ≤ q :=
if H1 : Rat.sqrt q * Rat.sqrt q = q then
iff_of_false
(not_not_intro
⟨Rat.sqrt q, by
rw [← H1, cast_mul, sqrt_mul_self (cast_nonneg.2 <| Rat.sqrt_nonneg q), sqrt_eq,
abs_of_nonneg (Rat.sqrt_nonneg q)]⟩)
fun h => h.1 H1
else
if H2 : 0 ≤ q then
iff_of_true
(fun ⟨r, hr⟩ =>
H1 <|
(exists_mul_self _).1
⟨r, by
rwa [eq_comm, sqrt_eq_iff_mul_self_eq (cast_nonneg.2 H2), ← cast_mul,
Rat.cast_inj] at hr
rw [← hr]
exact Real.sqrt_nonneg _⟩)
⟨H1, H2⟩
else
iff_of_false
(not_not_intro
⟨0, by
rw [cast_zero]
exact (sqrt_eq_zero_of_nonpos (Rat.cast_nonpos.2 <| le_of_not_le H2)).symm⟩)
fun h => H2 h.2
#align irrational_sqrt_rat_iff irrational_sqrt_rat_iff
instance (q : ℚ) : Decidable (Irrational (√q)) :=
decidable_of_iff' _ (irrational_sqrt_rat_iff q)
/-!
### Dot-style operations on `Irrational`
#### Coercion of a rational/integer/natural number is not irrational
-/
namespace Irrational
variable {x : ℝ}
/-!
#### Irrational number is not equal to a rational/integer/natural number
-/
theorem ne_rat (h : Irrational x) (q : ℚ) : x ≠ q := fun hq => h ⟨q, hq.symm⟩
#align irrational.ne_rat Irrational.ne_rat
theorem ne_int (h : Irrational x) (m : ℤ) : x ≠ m := by
rw [← Rat.cast_intCast]
exact h.ne_rat _
#align irrational.ne_int Irrational.ne_int
theorem ne_nat (h : Irrational x) (m : ℕ) : x ≠ m :=
h.ne_int m
#align irrational.ne_nat Irrational.ne_nat
theorem ne_zero (h : Irrational x) : x ≠ 0 := mod_cast h.ne_nat 0
#align irrational.ne_zero Irrational.ne_zero
theorem ne_one (h : Irrational x) : x ≠ 1 := by simpa only [Nat.cast_one] using h.ne_nat 1
#align irrational.ne_one Irrational.ne_one
end Irrational
@[simp]
theorem Rat.not_irrational (q : ℚ) : ¬Irrational q := fun h => h ⟨q, rfl⟩
#align rat.not_irrational Rat.not_irrational
@[simp]
theorem Int.not_irrational (m : ℤ) : ¬Irrational m := fun h => h.ne_int m rfl
#align int.not_irrational Int.not_irrational
@[simp]
theorem Nat.not_irrational (m : ℕ) : ¬Irrational m := fun h => h.ne_nat m rfl
#align nat.not_irrational Nat.not_irrational
namespace Irrational
variable (q : ℚ) {x y : ℝ}
/-!
#### Addition of rational/integer/natural numbers
-/
/-- If `x + y` is irrational, then at least one of `x` and `y` is irrational. -/
theorem add_cases : Irrational (x + y) → Irrational x ∨ Irrational y := by
delta Irrational
contrapose!
rintro ⟨⟨rx, rfl⟩, ⟨ry, rfl⟩⟩
exact ⟨rx + ry, cast_add rx ry⟩
#align irrational.add_cases Irrational.add_cases
theorem of_rat_add (h : Irrational (q + x)) : Irrational x :=
h.add_cases.resolve_left q.not_irrational
#align irrational.of_rat_add Irrational.of_rat_add
theorem rat_add (h : Irrational x) : Irrational (q + x) :=
of_rat_add (-q) <| by rwa [cast_neg, neg_add_cancel_left]
#align irrational.rat_add Irrational.rat_add
theorem of_add_rat : Irrational (x + q) → Irrational x :=
add_comm (↑q) x ▸ of_rat_add q
#align irrational.of_add_rat Irrational.of_add_rat
theorem add_rat (h : Irrational x) : Irrational (x + q) :=
add_comm (↑q) x ▸ h.rat_add q
#align irrational.add_rat Irrational.add_rat
theorem of_int_add (m : ℤ) (h : Irrational (m + x)) : Irrational x := by
rw [← cast_intCast] at h
exact h.of_rat_add m
#align irrational.of_int_add Irrational.of_int_add
theorem of_add_int (m : ℤ) (h : Irrational (x + m)) : Irrational x :=
of_int_add m <| add_comm x m ▸ h
#align irrational.of_add_int Irrational.of_add_int
theorem int_add (h : Irrational x) (m : ℤ) : Irrational (m + x) := by
rw [← cast_intCast]
exact h.rat_add m
#align irrational.int_add Irrational.int_add
theorem add_int (h : Irrational x) (m : ℤ) : Irrational (x + m) :=
add_comm (↑m) x ▸ h.int_add m
#align irrational.add_int Irrational.add_int
theorem of_nat_add (m : ℕ) (h : Irrational (m + x)) : Irrational x :=
h.of_int_add m
#align irrational.of_nat_add Irrational.of_nat_add
theorem of_add_nat (m : ℕ) (h : Irrational (x + m)) : Irrational x :=
h.of_add_int m
#align irrational.of_add_nat Irrational.of_add_nat
theorem nat_add (h : Irrational x) (m : ℕ) : Irrational (m + x) :=
h.int_add m
#align irrational.nat_add Irrational.nat_add
theorem add_nat (h : Irrational x) (m : ℕ) : Irrational (x + m) :=
h.add_int m
#align irrational.add_nat Irrational.add_nat
/-!
#### Negation
-/
theorem of_neg (h : Irrational (-x)) : Irrational x := fun ⟨q, hx⟩ => h ⟨-q, by rw [cast_neg, hx]⟩
#align irrational.of_neg Irrational.of_neg
protected theorem neg (h : Irrational x) : Irrational (-x) :=
of_neg <| by rwa [neg_neg]
#align irrational.neg Irrational.neg
/-!
#### Subtraction of rational/integer/natural numbers
-/
theorem sub_rat (h : Irrational x) : Irrational (x - q) := by
simpa only [sub_eq_add_neg, cast_neg] using h.add_rat (-q)
#align irrational.sub_rat Irrational.sub_rat
theorem rat_sub (h : Irrational x) : Irrational (q - x) := by
simpa only [sub_eq_add_neg] using h.neg.rat_add q
#align irrational.rat_sub Irrational.rat_sub
theorem of_sub_rat (h : Irrational (x - q)) : Irrational x :=
of_add_rat (-q) <| by simpa only [cast_neg, sub_eq_add_neg] using h
#align irrational.of_sub_rat Irrational.of_sub_rat
theorem of_rat_sub (h : Irrational (q - x)) : Irrational x :=
of_neg (of_rat_add q (by simpa only [sub_eq_add_neg] using h))
#align irrational.of_rat_sub Irrational.of_rat_sub
theorem sub_int (h : Irrational x) (m : ℤ) : Irrational (x - m) := by
simpa only [Rat.cast_intCast] using h.sub_rat m
#align irrational.sub_int Irrational.sub_int
theorem int_sub (h : Irrational x) (m : ℤ) : Irrational (m - x) := by
simpa only [Rat.cast_intCast] using h.rat_sub m
#align irrational.int_sub Irrational.int_sub
theorem of_sub_int (m : ℤ) (h : Irrational (x - m)) : Irrational x :=
of_sub_rat m <| by rwa [Rat.cast_intCast]
#align irrational.of_sub_int Irrational.of_sub_int
theorem of_int_sub (m : ℤ) (h : Irrational (m - x)) : Irrational x :=
of_rat_sub m <| by rwa [Rat.cast_intCast]
#align irrational.of_int_sub Irrational.of_int_sub
theorem sub_nat (h : Irrational x) (m : ℕ) : Irrational (x - m) :=
h.sub_int m
#align irrational.sub_nat Irrational.sub_nat
theorem nat_sub (h : Irrational x) (m : ℕ) : Irrational (m - x) :=
h.int_sub m
#align irrational.nat_sub Irrational.nat_sub
theorem of_sub_nat (m : ℕ) (h : Irrational (x - m)) : Irrational x :=
h.of_sub_int m
#align irrational.of_sub_nat Irrational.of_sub_nat
theorem of_nat_sub (m : ℕ) (h : Irrational (m - x)) : Irrational x :=
h.of_int_sub m
#align irrational.of_nat_sub Irrational.of_nat_sub
/-!
#### Multiplication by rational numbers
-/
theorem mul_cases : Irrational (x * y) → Irrational x ∨ Irrational y := by
delta Irrational
contrapose!
rintro ⟨⟨rx, rfl⟩, ⟨ry, rfl⟩⟩
exact ⟨rx * ry, cast_mul rx ry⟩
#align irrational.mul_cases Irrational.mul_cases
theorem of_mul_rat (h : Irrational (x * q)) : Irrational x :=
h.mul_cases.resolve_right q.not_irrational
#align irrational.of_mul_rat Irrational.of_mul_rat
theorem mul_rat (h : Irrational x) {q : ℚ} (hq : q ≠ 0) : Irrational (x * q) :=
of_mul_rat q⁻¹ <| by rwa [mul_assoc, ← cast_mul, mul_inv_cancel hq, cast_one, mul_one]
#align irrational.mul_rat Irrational.mul_rat
theorem of_rat_mul : Irrational (q * x) → Irrational x :=
mul_comm x q ▸ of_mul_rat q
#align irrational.of_rat_mul Irrational.of_rat_mul
theorem rat_mul (h : Irrational x) {q : ℚ} (hq : q ≠ 0) : Irrational (q * x) :=
mul_comm x q ▸ h.mul_rat hq
#align irrational.rat_mul Irrational.rat_mul
theorem of_mul_int (m : ℤ) (h : Irrational (x * m)) : Irrational x :=
of_mul_rat m <| by rwa [cast_intCast]
#align irrational.of_mul_int Irrational.of_mul_int
theorem of_int_mul (m : ℤ) (h : Irrational (m * x)) : Irrational x :=
of_rat_mul m <| by rwa [cast_intCast]
#align irrational.of_int_mul Irrational.of_int_mul
theorem mul_int (h : Irrational x) {m : ℤ} (hm : m ≠ 0) : Irrational (x * m) := by
rw [← cast_intCast]
refine h.mul_rat ?_
rwa [Int.cast_ne_zero]
#align irrational.mul_int Irrational.mul_int
theorem int_mul (h : Irrational x) {m : ℤ} (hm : m ≠ 0) : Irrational (m * x) :=
mul_comm x m ▸ h.mul_int hm
#align irrational.int_mul Irrational.int_mul
theorem of_mul_nat (m : ℕ) (h : Irrational (x * m)) : Irrational x :=
h.of_mul_int m
#align irrational.of_mul_nat Irrational.of_mul_nat
theorem of_nat_mul (m : ℕ) (h : Irrational (m * x)) : Irrational x :=
h.of_int_mul m
#align irrational.of_nat_mul Irrational.of_nat_mul
theorem mul_nat (h : Irrational x) {m : ℕ} (hm : m ≠ 0) : Irrational (x * m) :=
h.mul_int <| Int.natCast_ne_zero.2 hm
#align irrational.mul_nat Irrational.mul_nat
theorem nat_mul (h : Irrational x) {m : ℕ} (hm : m ≠ 0) : Irrational (m * x) :=
h.int_mul <| Int.natCast_ne_zero.2 hm
#align irrational.nat_mul Irrational.nat_mul
/-!
#### Inverse
-/
theorem of_inv (h : Irrational x⁻¹) : Irrational x := fun ⟨q, hq⟩ => h <| hq ▸ ⟨q⁻¹, q.cast_inv⟩
#align irrational.of_inv Irrational.of_inv
protected theorem inv (h : Irrational x) : Irrational x⁻¹ :=
of_inv <| by rwa [inv_inv]
#align irrational.inv Irrational.inv
/-!
#### Division
-/
theorem div_cases (h : Irrational (x / y)) : Irrational x ∨ Irrational y :=
h.mul_cases.imp id of_inv
#align irrational.div_cases Irrational.div_cases
theorem of_rat_div (h : Irrational (q / x)) : Irrational x :=
(h.of_rat_mul q).of_inv
#align irrational.of_rat_div Irrational.of_rat_div
theorem of_div_rat (h : Irrational (x / q)) : Irrational x :=
h.div_cases.resolve_right q.not_irrational
#align irrational.of_div_rat Irrational.of_div_rat
theorem rat_div (h : Irrational x) {q : ℚ} (hq : q ≠ 0) : Irrational (q / x) :=
h.inv.rat_mul hq
#align irrational.rat_div Irrational.rat_div
theorem div_rat (h : Irrational x) {q : ℚ} (hq : q ≠ 0) : Irrational (x / q) := by
rw [div_eq_mul_inv, ← cast_inv]
exact h.mul_rat (inv_ne_zero hq)
#align irrational.div_rat Irrational.div_rat
theorem of_int_div (m : ℤ) (h : Irrational (m / x)) : Irrational x :=
h.div_cases.resolve_left m.not_irrational
#align irrational.of_int_div Irrational.of_int_div
theorem of_div_int (m : ℤ) (h : Irrational (x / m)) : Irrational x :=
h.div_cases.resolve_right m.not_irrational
#align irrational.of_div_int Irrational.of_div_int
theorem int_div (h : Irrational x) {m : ℤ} (hm : m ≠ 0) : Irrational (m / x) :=
h.inv.int_mul hm
#align irrational.int_div Irrational.int_div
theorem div_int (h : Irrational x) {m : ℤ} (hm : m ≠ 0) : Irrational (x / m) := by
rw [← cast_intCast]
refine h.div_rat ?_
rwa [Int.cast_ne_zero]
#align irrational.div_int Irrational.div_int
theorem of_nat_div (m : ℕ) (h : Irrational (m / x)) : Irrational x :=
h.of_int_div m
#align irrational.of_nat_div Irrational.of_nat_div
theorem of_div_nat (m : ℕ) (h : Irrational (x / m)) : Irrational x :=
h.of_div_int m
#align irrational.of_div_nat Irrational.of_div_nat
theorem nat_div (h : Irrational x) {m : ℕ} (hm : m ≠ 0) : Irrational (m / x) :=
h.inv.nat_mul hm
#align irrational.nat_div Irrational.nat_div
theorem div_nat (h : Irrational x) {m : ℕ} (hm : m ≠ 0) : Irrational (x / m) :=
h.div_int <| by rwa [Int.natCast_ne_zero]
#align irrational.div_nat Irrational.div_nat
theorem of_one_div (h : Irrational (1 / x)) : Irrational x :=
of_rat_div 1 <| by rwa [cast_one]
#align irrational.of_one_div Irrational.of_one_div
/-!
#### Natural and integer power
-/
theorem of_mul_self (h : Irrational (x * x)) : Irrational x :=
h.mul_cases.elim id id
#align irrational.of_mul_self Irrational.of_mul_self
theorem of_pow : ∀ n : ℕ, Irrational (x ^ n) → Irrational x
| 0 => fun h => by
rw [pow_zero] at h
exact (h ⟨1, cast_one⟩).elim
| n + 1 => fun h => by
rw [pow_succ] at h
exact h.mul_cases.elim (of_pow n) id
#align irrational.of_pow Irrational.of_pow
open Int in
theorem of_zpow : ∀ m : ℤ, Irrational (x ^ m) → Irrational x
| (n : ℕ) => fun h => by
rw [zpow_natCast] at h
exact h.of_pow _
| -[n+1] => fun h => by
rw [zpow_negSucc] at h
exact h.of_inv.of_pow _
#align irrational.of_zpow Irrational.of_zpow
end Irrational
section Polynomial
open Polynomial
open Polynomial
variable (x : ℝ) (p : ℤ[X])
theorem one_lt_natDegree_of_irrational_root (hx : Irrational x) (p_nonzero : p ≠ 0)
(x_is_root : aeval x p = 0) : 1 < p.natDegree := by
by_contra rid
rcases exists_eq_X_add_C_of_natDegree_le_one (not_lt.1 rid) with ⟨a, b, rfl⟩
clear rid
have : (a : ℝ) * x = -b := by simpa [eq_neg_iff_add_eq_zero] using x_is_root
rcases em (a = 0) with (rfl | ha)
· obtain rfl : b = 0 := by simpa
simp at p_nonzero
· rw [mul_comm, ← eq_div_iff_mul_eq, eq_comm] at this
· refine hx ⟨-b / a, ?_⟩
assumption_mod_cast
· assumption_mod_cast
#align one_lt_nat_degree_of_irrational_root one_lt_natDegree_of_irrational_root
end Polynomial
section
variable {q : ℚ} {m : ℤ} {n : ℕ} {x : ℝ}
open Irrational
/-!
### Simplification lemmas about operations
-/
@[simp]
theorem irrational_rat_add_iff : Irrational (q + x) ↔ Irrational x :=
⟨of_rat_add q, rat_add q⟩
#align irrational_rat_add_iff irrational_rat_add_iff
@[simp]
theorem irrational_int_add_iff : Irrational (m + x) ↔ Irrational x :=
⟨of_int_add m, fun h => h.int_add m⟩
#align irrational_int_add_iff irrational_int_add_iff
@[simp]
theorem irrational_nat_add_iff : Irrational (n + x) ↔ Irrational x :=
⟨of_nat_add n, fun h => h.nat_add n⟩
#align irrational_nat_add_iff irrational_nat_add_iff
@[simp]
theorem irrational_add_rat_iff : Irrational (x + q) ↔ Irrational x :=
⟨of_add_rat q, add_rat q⟩
#align irrational_add_rat_iff irrational_add_rat_iff
@[simp]
theorem irrational_add_int_iff : Irrational (x + m) ↔ Irrational x :=
⟨of_add_int m, fun h => h.add_int m⟩
#align irrational_add_int_iff irrational_add_int_iff
@[simp]
theorem irrational_add_nat_iff : Irrational (x + n) ↔ Irrational x :=
⟨of_add_nat n, fun h => h.add_nat n⟩
#align irrational_add_nat_iff irrational_add_nat_iff
@[simp]
theorem irrational_rat_sub_iff : Irrational (q - x) ↔ Irrational x :=
⟨of_rat_sub q, rat_sub q⟩
#align irrational_rat_sub_iff irrational_rat_sub_iff
@[simp]
theorem irrational_int_sub_iff : Irrational (m - x) ↔ Irrational x :=
⟨of_int_sub m, fun h => h.int_sub m⟩
#align irrational_int_sub_iff irrational_int_sub_iff
@[simp]
theorem irrational_nat_sub_iff : Irrational (n - x) ↔ Irrational x :=
⟨of_nat_sub n, fun h => h.nat_sub n⟩
#align irrational_nat_sub_iff irrational_nat_sub_iff
@[simp]
theorem irrational_sub_rat_iff : Irrational (x - q) ↔ Irrational x :=
⟨of_sub_rat q, sub_rat q⟩
#align irrational_sub_rat_iff irrational_sub_rat_iff
@[simp]
theorem irrational_sub_int_iff : Irrational (x - m) ↔ Irrational x :=
⟨of_sub_int m, fun h => h.sub_int m⟩
#align irrational_sub_int_iff irrational_sub_int_iff
@[simp]
theorem irrational_sub_nat_iff : Irrational (x - n) ↔ Irrational x :=
⟨of_sub_nat n, fun h => h.sub_nat n⟩
#align irrational_sub_nat_iff irrational_sub_nat_iff
@[simp]
theorem irrational_neg_iff : Irrational (-x) ↔ Irrational x :=
⟨of_neg, Irrational.neg⟩
#align irrational_neg_iff irrational_neg_iff
@[simp]
theorem irrational_inv_iff : Irrational x⁻¹ ↔ Irrational x :=
⟨of_inv, Irrational.inv⟩
#align irrational_inv_iff irrational_inv_iff
@[simp]
theorem irrational_rat_mul_iff : Irrational (q * x) ↔ q ≠ 0 ∧ Irrational x :=
⟨fun h => ⟨Rat.cast_ne_zero.1 <| left_ne_zero_of_mul h.ne_zero, h.of_rat_mul q⟩, fun h =>
h.2.rat_mul h.1⟩
#align irrational_rat_mul_iff irrational_rat_mul_iff
@[simp]
theorem irrational_mul_rat_iff : Irrational (x * q) ↔ q ≠ 0 ∧ Irrational x := by
rw [mul_comm, irrational_rat_mul_iff]
#align irrational_mul_rat_iff irrational_mul_rat_iff
@[simp]
theorem irrational_int_mul_iff : Irrational (m * x) ↔ m ≠ 0 ∧ Irrational x := by
rw [← cast_intCast, irrational_rat_mul_iff, Int.cast_ne_zero]
#align irrational_int_mul_iff irrational_int_mul_iff
@[simp]
theorem irrational_mul_int_iff : Irrational (x * m) ↔ m ≠ 0 ∧ Irrational x := by
rw [← cast_intCast, irrational_mul_rat_iff, Int.cast_ne_zero]
#align irrational_mul_int_iff irrational_mul_int_iff
@[simp]
theorem irrational_nat_mul_iff : Irrational (n * x) ↔ n ≠ 0 ∧ Irrational x := by
rw [← cast_natCast, irrational_rat_mul_iff, Nat.cast_ne_zero]
#align irrational_nat_mul_iff irrational_nat_mul_iff
@[simp]
theorem irrational_mul_nat_iff : Irrational (x * n) ↔ n ≠ 0 ∧ Irrational x := by
rw [← cast_natCast, irrational_mul_rat_iff, Nat.cast_ne_zero]
#align irrational_mul_nat_iff irrational_mul_nat_iff
@[simp]
theorem irrational_rat_div_iff : Irrational (q / x) ↔ q ≠ 0 ∧ Irrational x := by
simp [div_eq_mul_inv]
#align irrational_rat_div_iff irrational_rat_div_iff
@[simp]
theorem irrational_div_rat_iff : Irrational (x / q) ↔ q ≠ 0 ∧ Irrational x := by
rw [div_eq_mul_inv, ← cast_inv, irrational_mul_rat_iff, Ne, inv_eq_zero]
#align irrational_div_rat_iff irrational_div_rat_iff
@[simp]
theorem irrational_int_div_iff : Irrational (m / x) ↔ m ≠ 0 ∧ Irrational x := by
simp [div_eq_mul_inv]
#align irrational_int_div_iff irrational_int_div_iff
@[simp]
| Mathlib/Data/Real/Irrational.lean | 641 | 642 | theorem irrational_div_int_iff : Irrational (x / m) ↔ m ≠ 0 ∧ Irrational x := by |
rw [← cast_intCast, irrational_div_rat_iff, Int.cast_ne_zero]
|
/-
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
| Mathlib/MeasureTheory/Function/SimpleFunc.lean | 1,076 | 1,078 | 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]
|
/-
Copyright (c) 2020 Thomas Browning, Patrick Lutz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning, Patrick Lutz
-/
import Mathlib.Algebra.Algebra.Subalgebra.Directed
import Mathlib.FieldTheory.IntermediateField
import Mathlib.FieldTheory.Separable
import Mathlib.FieldTheory.SplittingField.IsSplittingField
import Mathlib.RingTheory.TensorProduct.Basic
#align_import field_theory.adjoin from "leanprover-community/mathlib"@"df76f43357840485b9d04ed5dee5ab115d420e87"
/-!
# Adjoining Elements to Fields
In this file we introduce the notion of adjoining elements to fields.
This isn't quite the same as adjoining elements to rings.
For example, `Algebra.adjoin K {x}` might not include `x⁻¹`.
## Main results
- `adjoin_adjoin_left`: adjoining S and then T is the same as adjoining `S ∪ T`.
- `bot_eq_top_of_rank_adjoin_eq_one`: if `F⟮x⟯` has dimension `1` over `F` for every `x`
in `E` then `F = E`
## Notation
- `F⟮α⟯`: adjoin a single element `α` to `F` (in scope `IntermediateField`).
-/
set_option autoImplicit true
open FiniteDimensional Polynomial
open scoped Classical Polynomial
namespace IntermediateField
section AdjoinDef
variable (F : Type*) [Field F] {E : Type*} [Field E] [Algebra F E] (S : Set E)
-- Porting note: not adding `neg_mem'` causes an error.
/-- `adjoin F S` extends a field `F` by adjoining a set `S ⊆ E`. -/
def adjoin : IntermediateField F E :=
{ Subfield.closure (Set.range (algebraMap F E) ∪ S) with
algebraMap_mem' := fun x => Subfield.subset_closure (Or.inl (Set.mem_range_self x)) }
#align intermediate_field.adjoin IntermediateField.adjoin
variable {S}
theorem mem_adjoin_iff (x : E) :
x ∈ adjoin F S ↔ ∃ r s : MvPolynomial S F,
x = MvPolynomial.aeval Subtype.val r / MvPolynomial.aeval Subtype.val s := by
simp only [adjoin, mem_mk, Subring.mem_toSubsemiring, Subfield.mem_toSubring,
Subfield.mem_closure_iff, ← Algebra.adjoin_eq_ring_closure, Subalgebra.mem_toSubring,
Algebra.adjoin_eq_range, AlgHom.mem_range, exists_exists_eq_and]
tauto
theorem mem_adjoin_simple_iff {α : E} (x : E) :
x ∈ adjoin F {α} ↔ ∃ r s : F[X], x = aeval α r / aeval α s := by
simp only [adjoin, mem_mk, Subring.mem_toSubsemiring, Subfield.mem_toSubring,
Subfield.mem_closure_iff, ← Algebra.adjoin_eq_ring_closure, Subalgebra.mem_toSubring,
Algebra.adjoin_singleton_eq_range_aeval, AlgHom.mem_range, exists_exists_eq_and]
tauto
end AdjoinDef
section Lattice
variable {F : Type*} [Field F] {E : Type*} [Field E] [Algebra F E]
@[simp]
theorem adjoin_le_iff {S : Set E} {T : IntermediateField F E} : adjoin F S ≤ T ↔ S ≤ T :=
⟨fun H => le_trans (le_trans Set.subset_union_right Subfield.subset_closure) H, fun H =>
(@Subfield.closure_le E _ (Set.range (algebraMap F E) ∪ S) T.toSubfield).mpr
(Set.union_subset (IntermediateField.set_range_subset T) H)⟩
#align intermediate_field.adjoin_le_iff IntermediateField.adjoin_le_iff
theorem gc : GaloisConnection (adjoin F : Set E → IntermediateField F E)
(fun (x : IntermediateField F E) => (x : Set E)) := fun _ _ =>
adjoin_le_iff
#align intermediate_field.gc IntermediateField.gc
/-- Galois insertion between `adjoin` and `coe`. -/
def gi : GaloisInsertion (adjoin F : Set E → IntermediateField F E)
(fun (x : IntermediateField F E) => (x : Set E)) where
choice s hs := (adjoin F s).copy s <| le_antisymm (gc.le_u_l s) hs
gc := IntermediateField.gc
le_l_u S := (IntermediateField.gc (S : Set E) (adjoin F S)).1 <| le_rfl
choice_eq _ _ := copy_eq _ _ _
#align intermediate_field.gi IntermediateField.gi
instance : CompleteLattice (IntermediateField F E) where
__ := GaloisInsertion.liftCompleteLattice IntermediateField.gi
bot :=
{ toSubalgebra := ⊥
inv_mem' := by rintro x ⟨r, rfl⟩; exact ⟨r⁻¹, map_inv₀ _ _⟩ }
bot_le x := (bot_le : ⊥ ≤ x.toSubalgebra)
instance : Inhabited (IntermediateField F E) :=
⟨⊤⟩
instance : Unique (IntermediateField F F) :=
{ inferInstanceAs (Inhabited (IntermediateField F F)) with
uniq := fun _ ↦ toSubalgebra_injective <| Subsingleton.elim _ _ }
theorem coe_bot : ↑(⊥ : IntermediateField F E) = Set.range (algebraMap F E) := rfl
#align intermediate_field.coe_bot IntermediateField.coe_bot
theorem mem_bot {x : E} : x ∈ (⊥ : IntermediateField F E) ↔ x ∈ Set.range (algebraMap F E) :=
Iff.rfl
#align intermediate_field.mem_bot IntermediateField.mem_bot
@[simp]
theorem bot_toSubalgebra : (⊥ : IntermediateField F E).toSubalgebra = ⊥ := rfl
#align intermediate_field.bot_to_subalgebra IntermediateField.bot_toSubalgebra
@[simp]
theorem coe_top : ↑(⊤ : IntermediateField F E) = (Set.univ : Set E) :=
rfl
#align intermediate_field.coe_top IntermediateField.coe_top
@[simp]
theorem mem_top {x : E} : x ∈ (⊤ : IntermediateField F E) :=
trivial
#align intermediate_field.mem_top IntermediateField.mem_top
@[simp]
theorem top_toSubalgebra : (⊤ : IntermediateField F E).toSubalgebra = ⊤ :=
rfl
#align intermediate_field.top_to_subalgebra IntermediateField.top_toSubalgebra
@[simp]
theorem top_toSubfield : (⊤ : IntermediateField F E).toSubfield = ⊤ :=
rfl
#align intermediate_field.top_to_subfield IntermediateField.top_toSubfield
@[simp, norm_cast]
theorem coe_inf (S T : IntermediateField F E) : (↑(S ⊓ T) : Set E) = (S : Set E) ∩ T :=
rfl
#align intermediate_field.coe_inf IntermediateField.coe_inf
@[simp]
theorem mem_inf {S T : IntermediateField F E} {x : E} : x ∈ S ⊓ T ↔ x ∈ S ∧ x ∈ T :=
Iff.rfl
#align intermediate_field.mem_inf IntermediateField.mem_inf
@[simp]
theorem inf_toSubalgebra (S T : IntermediateField F E) :
(S ⊓ T).toSubalgebra = S.toSubalgebra ⊓ T.toSubalgebra :=
rfl
#align intermediate_field.inf_to_subalgebra IntermediateField.inf_toSubalgebra
@[simp]
theorem inf_toSubfield (S T : IntermediateField F E) :
(S ⊓ T).toSubfield = S.toSubfield ⊓ T.toSubfield :=
rfl
#align intermediate_field.inf_to_subfield IntermediateField.inf_toSubfield
@[simp, norm_cast]
theorem coe_sInf (S : Set (IntermediateField F E)) : (↑(sInf S) : Set E) =
sInf ((fun (x : IntermediateField F E) => (x : Set E)) '' S) :=
rfl
#align intermediate_field.coe_Inf IntermediateField.coe_sInf
@[simp]
theorem sInf_toSubalgebra (S : Set (IntermediateField F E)) :
(sInf S).toSubalgebra = sInf (toSubalgebra '' S) :=
SetLike.coe_injective <| by simp [Set.sUnion_image]
#align intermediate_field.Inf_to_subalgebra IntermediateField.sInf_toSubalgebra
@[simp]
theorem sInf_toSubfield (S : Set (IntermediateField F E)) :
(sInf S).toSubfield = sInf (toSubfield '' S) :=
SetLike.coe_injective <| by simp [Set.sUnion_image]
#align intermediate_field.Inf_to_subfield IntermediateField.sInf_toSubfield
@[simp, norm_cast]
theorem coe_iInf {ι : Sort*} (S : ι → IntermediateField F E) : (↑(iInf S) : Set E) = ⋂ i, S i := by
simp [iInf]
#align intermediate_field.coe_infi IntermediateField.coe_iInf
@[simp]
theorem iInf_toSubalgebra {ι : Sort*} (S : ι → IntermediateField F E) :
(iInf S).toSubalgebra = ⨅ i, (S i).toSubalgebra :=
SetLike.coe_injective <| by simp [iInf]
#align intermediate_field.infi_to_subalgebra IntermediateField.iInf_toSubalgebra
@[simp]
theorem iInf_toSubfield {ι : Sort*} (S : ι → IntermediateField F E) :
(iInf S).toSubfield = ⨅ i, (S i).toSubfield :=
SetLike.coe_injective <| by simp [iInf]
#align intermediate_field.infi_to_subfield IntermediateField.iInf_toSubfield
/-- Construct an algebra isomorphism from an equality of intermediate fields -/
@[simps! apply]
def equivOfEq {S T : IntermediateField F E} (h : S = T) : S ≃ₐ[F] T :=
Subalgebra.equivOfEq _ _ (congr_arg toSubalgebra h)
#align intermediate_field.equiv_of_eq IntermediateField.equivOfEq
@[simp]
theorem equivOfEq_symm {S T : IntermediateField F E} (h : S = T) :
(equivOfEq h).symm = equivOfEq h.symm :=
rfl
#align intermediate_field.equiv_of_eq_symm IntermediateField.equivOfEq_symm
@[simp]
theorem equivOfEq_rfl (S : IntermediateField F E) : equivOfEq (rfl : S = S) = AlgEquiv.refl := by
ext; rfl
#align intermediate_field.equiv_of_eq_rfl IntermediateField.equivOfEq_rfl
@[simp]
theorem equivOfEq_trans {S T U : IntermediateField F E} (hST : S = T) (hTU : T = U) :
(equivOfEq hST).trans (equivOfEq hTU) = equivOfEq (hST.trans hTU) :=
rfl
#align intermediate_field.equiv_of_eq_trans IntermediateField.equivOfEq_trans
variable (F E)
/-- The bottom intermediate_field is isomorphic to the field. -/
noncomputable def botEquiv : (⊥ : IntermediateField F E) ≃ₐ[F] F :=
(Subalgebra.equivOfEq _ _ bot_toSubalgebra).trans (Algebra.botEquiv F E)
#align intermediate_field.bot_equiv IntermediateField.botEquiv
variable {F E}
-- Porting note: this was tagged `simp`.
theorem botEquiv_def (x : F) : botEquiv F E (algebraMap F (⊥ : IntermediateField F E) x) = x := by
simp
#align intermediate_field.bot_equiv_def IntermediateField.botEquiv_def
@[simp]
theorem botEquiv_symm (x : F) : (botEquiv F E).symm x = algebraMap F _ x :=
rfl
#align intermediate_field.bot_equiv_symm IntermediateField.botEquiv_symm
noncomputable instance algebraOverBot : Algebra (⊥ : IntermediateField F E) F :=
(IntermediateField.botEquiv F E).toAlgHom.toRingHom.toAlgebra
#align intermediate_field.algebra_over_bot IntermediateField.algebraOverBot
theorem coe_algebraMap_over_bot :
(algebraMap (⊥ : IntermediateField F E) F : (⊥ : IntermediateField F E) → F) =
IntermediateField.botEquiv F E :=
rfl
#align intermediate_field.coe_algebra_map_over_bot IntermediateField.coe_algebraMap_over_bot
instance isScalarTower_over_bot : IsScalarTower (⊥ : IntermediateField F E) F E :=
IsScalarTower.of_algebraMap_eq
(by
intro x
obtain ⟨y, rfl⟩ := (botEquiv F E).symm.surjective x
rw [coe_algebraMap_over_bot, (botEquiv F E).apply_symm_apply, botEquiv_symm,
IsScalarTower.algebraMap_apply F (⊥ : IntermediateField F E) E])
#align intermediate_field.is_scalar_tower_over_bot IntermediateField.isScalarTower_over_bot
/-- The top `IntermediateField` is isomorphic to the field.
This is the intermediate field version of `Subalgebra.topEquiv`. -/
@[simps!]
def topEquiv : (⊤ : IntermediateField F E) ≃ₐ[F] E :=
(Subalgebra.equivOfEq _ _ top_toSubalgebra).trans Subalgebra.topEquiv
#align intermediate_field.top_equiv IntermediateField.topEquiv
-- Porting note: this theorem is now generated by the `@[simps!]` above.
#align intermediate_field.top_equiv_symm_apply_coe IntermediateField.topEquiv_symm_apply_coe
@[simp]
theorem restrictScalars_bot_eq_self (K : IntermediateField F E) :
(⊥ : IntermediateField K E).restrictScalars _ = K :=
SetLike.coe_injective Subtype.range_coe
#align intermediate_field.restrict_scalars_bot_eq_self IntermediateField.restrictScalars_bot_eq_self
@[simp]
theorem restrictScalars_top {K : Type*} [Field K] [Algebra K E] [Algebra K F]
[IsScalarTower K F E] : (⊤ : IntermediateField F E).restrictScalars K = ⊤ :=
rfl
#align intermediate_field.restrict_scalars_top IntermediateField.restrictScalars_top
variable {K : Type*} [Field K] [Algebra F K]
@[simp]
theorem map_bot (f : E →ₐ[F] K) :
IntermediateField.map f ⊥ = ⊥ :=
toSubalgebra_injective <| Algebra.map_bot _
theorem map_sup (s t : IntermediateField F E) (f : E →ₐ[F] K) : (s ⊔ t).map f = s.map f ⊔ t.map f :=
(gc_map_comap f).l_sup
theorem map_iSup {ι : Sort*} (f : E →ₐ[F] K) (s : ι → IntermediateField F E) :
(iSup s).map f = ⨆ i, (s i).map f :=
(gc_map_comap f).l_iSup
theorem _root_.AlgHom.fieldRange_eq_map (f : E →ₐ[F] K) :
f.fieldRange = IntermediateField.map f ⊤ :=
SetLike.ext' Set.image_univ.symm
#align alg_hom.field_range_eq_map AlgHom.fieldRange_eq_map
theorem _root_.AlgHom.map_fieldRange {L : Type*} [Field L] [Algebra F L]
(f : E →ₐ[F] K) (g : K →ₐ[F] L) : f.fieldRange.map g = (g.comp f).fieldRange :=
SetLike.ext' (Set.range_comp g f).symm
#align alg_hom.map_field_range AlgHom.map_fieldRange
theorem _root_.AlgHom.fieldRange_eq_top {f : E →ₐ[F] K} :
f.fieldRange = ⊤ ↔ Function.Surjective f :=
SetLike.ext'_iff.trans Set.range_iff_surjective
#align alg_hom.field_range_eq_top AlgHom.fieldRange_eq_top
@[simp]
theorem _root_.AlgEquiv.fieldRange_eq_top (f : E ≃ₐ[F] K) :
(f : E →ₐ[F] K).fieldRange = ⊤ :=
AlgHom.fieldRange_eq_top.mpr f.surjective
#align alg_equiv.field_range_eq_top AlgEquiv.fieldRange_eq_top
end Lattice
section equivMap
variable {F : Type*} [Field F] {E : Type*} [Field E] [Algebra F E]
{K : Type*} [Field K] [Algebra F K] (L : IntermediateField F E) (f : E →ₐ[F] K)
theorem fieldRange_comp_val : (f.comp L.val).fieldRange = L.map f := toSubalgebra_injective <| by
rw [toSubalgebra_map, AlgHom.fieldRange_toSubalgebra, AlgHom.range_comp, range_val]
/-- An intermediate field is isomorphic to its image under an `AlgHom`
(which is automatically injective) -/
noncomputable def equivMap : L ≃ₐ[F] L.map f :=
(AlgEquiv.ofInjective _ (f.comp L.val).injective).trans (equivOfEq (fieldRange_comp_val L f))
@[simp]
theorem coe_equivMap_apply (x : L) : ↑(equivMap L f x) = f x := rfl
end equivMap
section AdjoinDef
variable (F : Type*) [Field F] {E : Type*} [Field E] [Algebra F E] (S : Set E)
theorem adjoin_eq_range_algebraMap_adjoin :
(adjoin F S : Set E) = Set.range (algebraMap (adjoin F S) E) :=
Subtype.range_coe.symm
#align intermediate_field.adjoin_eq_range_algebra_map_adjoin IntermediateField.adjoin_eq_range_algebraMap_adjoin
theorem adjoin.algebraMap_mem (x : F) : algebraMap F E x ∈ adjoin F S :=
IntermediateField.algebraMap_mem (adjoin F S) x
#align intermediate_field.adjoin.algebra_map_mem IntermediateField.adjoin.algebraMap_mem
theorem adjoin.range_algebraMap_subset : Set.range (algebraMap F E) ⊆ adjoin F S := by
intro x hx
cases' hx with f hf
rw [← hf]
exact adjoin.algebraMap_mem F S f
#align intermediate_field.adjoin.range_algebra_map_subset IntermediateField.adjoin.range_algebraMap_subset
instance adjoin.fieldCoe : CoeTC F (adjoin F S) where
coe x := ⟨algebraMap F E x, adjoin.algebraMap_mem F S x⟩
#align intermediate_field.adjoin.field_coe IntermediateField.adjoin.fieldCoe
theorem subset_adjoin : S ⊆ adjoin F S := fun _ hx => Subfield.subset_closure (Or.inr hx)
#align intermediate_field.subset_adjoin IntermediateField.subset_adjoin
instance adjoin.setCoe : CoeTC S (adjoin F S) where coe x := ⟨x, subset_adjoin F S (Subtype.mem x)⟩
#align intermediate_field.adjoin.set_coe IntermediateField.adjoin.setCoe
@[mono]
theorem adjoin.mono (T : Set E) (h : S ⊆ T) : adjoin F S ≤ adjoin F T :=
GaloisConnection.monotone_l gc h
#align intermediate_field.adjoin.mono IntermediateField.adjoin.mono
theorem adjoin_contains_field_as_subfield (F : Subfield E) : (F : Set E) ⊆ adjoin F S := fun x hx =>
adjoin.algebraMap_mem F S ⟨x, hx⟩
#align intermediate_field.adjoin_contains_field_as_subfield IntermediateField.adjoin_contains_field_as_subfield
theorem subset_adjoin_of_subset_left {F : Subfield E} {T : Set E} (HT : T ⊆ F) : T ⊆ adjoin F S :=
fun x hx => (adjoin F S).algebraMap_mem ⟨x, HT hx⟩
#align intermediate_field.subset_adjoin_of_subset_left IntermediateField.subset_adjoin_of_subset_left
theorem subset_adjoin_of_subset_right {T : Set E} (H : T ⊆ S) : T ⊆ adjoin F S := fun _ hx =>
subset_adjoin F S (H hx)
#align intermediate_field.subset_adjoin_of_subset_right IntermediateField.subset_adjoin_of_subset_right
@[simp]
theorem adjoin_empty (F E : Type*) [Field F] [Field E] [Algebra F E] : adjoin F (∅ : Set E) = ⊥ :=
eq_bot_iff.mpr (adjoin_le_iff.mpr (Set.empty_subset _))
#align intermediate_field.adjoin_empty IntermediateField.adjoin_empty
@[simp]
theorem adjoin_univ (F E : Type*) [Field F] [Field E] [Algebra F E] :
adjoin F (Set.univ : Set E) = ⊤ :=
eq_top_iff.mpr <| subset_adjoin _ _
#align intermediate_field.adjoin_univ IntermediateField.adjoin_univ
/-- If `K` is a field with `F ⊆ K` and `S ⊆ K` then `adjoin F S ≤ K`. -/
theorem adjoin_le_subfield {K : Subfield E} (HF : Set.range (algebraMap F E) ⊆ K) (HS : S ⊆ K) :
(adjoin F S).toSubfield ≤ K := by
apply Subfield.closure_le.mpr
rw [Set.union_subset_iff]
exact ⟨HF, HS⟩
#align intermediate_field.adjoin_le_subfield IntermediateField.adjoin_le_subfield
theorem adjoin_subset_adjoin_iff {F' : Type*} [Field F'] [Algebra F' E] {S S' : Set E} :
(adjoin F S : Set E) ⊆ adjoin F' S' ↔
Set.range (algebraMap F E) ⊆ adjoin F' S' ∧ S ⊆ adjoin F' S' :=
⟨fun h => ⟨(adjoin.range_algebraMap_subset _ _).trans h,
(subset_adjoin _ _).trans h⟩, fun ⟨hF, hS⟩ =>
(Subfield.closure_le (t := (adjoin F' S').toSubfield)).mpr (Set.union_subset hF hS)⟩
#align intermediate_field.adjoin_subset_adjoin_iff IntermediateField.adjoin_subset_adjoin_iff
/-- `F[S][T] = F[S ∪ T]` -/
theorem adjoin_adjoin_left (T : Set E) :
(adjoin (adjoin F S) T).restrictScalars _ = adjoin F (S ∪ T) := by
rw [SetLike.ext'_iff]
change (↑(adjoin (adjoin F S) T) : Set E) = _
apply Set.eq_of_subset_of_subset <;> rw [adjoin_subset_adjoin_iff] <;> constructor
· rintro _ ⟨⟨x, hx⟩, rfl⟩; exact adjoin.mono _ _ _ Set.subset_union_left hx
· exact subset_adjoin_of_subset_right _ _ Set.subset_union_right
-- Porting note: orginal proof times out
· rintro x ⟨f, rfl⟩
refine Subfield.subset_closure ?_
left
exact ⟨f, rfl⟩
-- Porting note: orginal proof times out
· refine Set.union_subset (fun x hx => Subfield.subset_closure ?_)
(fun x hx => Subfield.subset_closure ?_)
· left
refine ⟨⟨x, Subfield.subset_closure ?_⟩, rfl⟩
right
exact hx
· right
exact hx
#align intermediate_field.adjoin_adjoin_left IntermediateField.adjoin_adjoin_left
@[simp]
theorem adjoin_insert_adjoin (x : E) :
adjoin F (insert x (adjoin F S : Set E)) = adjoin F (insert x S) :=
le_antisymm
(adjoin_le_iff.mpr
(Set.insert_subset_iff.mpr
⟨subset_adjoin _ _ (Set.mem_insert _ _),
adjoin_le_iff.mpr (subset_adjoin_of_subset_right _ _ (Set.subset_insert _ _))⟩))
(adjoin.mono _ _ _ (Set.insert_subset_insert (subset_adjoin _ _)))
#align intermediate_field.adjoin_insert_adjoin IntermediateField.adjoin_insert_adjoin
/-- `F[S][T] = F[T][S]` -/
theorem adjoin_adjoin_comm (T : Set E) :
(adjoin (adjoin F S) T).restrictScalars F = (adjoin (adjoin F T) S).restrictScalars F := by
rw [adjoin_adjoin_left, adjoin_adjoin_left, Set.union_comm]
#align intermediate_field.adjoin_adjoin_comm IntermediateField.adjoin_adjoin_comm
theorem adjoin_map {E' : Type*} [Field E'] [Algebra F E'] (f : E →ₐ[F] E') :
(adjoin F S).map f = adjoin F (f '' S) := by
ext x
show
x ∈ (Subfield.closure (Set.range (algebraMap F E) ∪ S)).map (f : E →+* E') ↔
x ∈ Subfield.closure (Set.range (algebraMap F E') ∪ f '' S)
rw [RingHom.map_field_closure, Set.image_union, ← Set.range_comp, ← RingHom.coe_comp,
f.comp_algebraMap]
rfl
#align intermediate_field.adjoin_map IntermediateField.adjoin_map
@[simp]
theorem lift_adjoin (K : IntermediateField F E) (S : Set K) :
lift (adjoin F S) = adjoin F (Subtype.val '' S) :=
adjoin_map _ _ _
theorem lift_adjoin_simple (K : IntermediateField F E) (α : K) :
lift (adjoin F {α}) = adjoin F {α.1} := by
simp only [lift_adjoin, Set.image_singleton]
@[simp]
theorem lift_bot (K : IntermediateField F E) :
lift (F := K) ⊥ = ⊥ := map_bot _
@[simp]
theorem lift_top (K : IntermediateField F E) :
lift (F := K) ⊤ = K := by rw [lift, ← AlgHom.fieldRange_eq_map, fieldRange_val]
@[simp]
theorem adjoin_self (K : IntermediateField F E) :
adjoin F K = K := le_antisymm (adjoin_le_iff.2 fun _ ↦ id) (subset_adjoin F _)
theorem restrictScalars_adjoin (K : IntermediateField F E) (S : Set E) :
restrictScalars F (adjoin K S) = adjoin F (K ∪ S) := by
rw [← adjoin_self _ K, adjoin_adjoin_left, adjoin_self _ K]
variable {F} in
theorem extendScalars_adjoin {K : IntermediateField F E} {S : Set E} (h : K ≤ adjoin F S) :
extendScalars h = adjoin K S := restrictScalars_injective F <| by
rw [extendScalars_restrictScalars, restrictScalars_adjoin]
exact le_antisymm (adjoin.mono F S _ Set.subset_union_right) <| adjoin_le_iff.2 <|
Set.union_subset h (subset_adjoin F S)
variable {F} in
/-- If `E / L / F` and `E / L' / F` are two field extension towers, `L ≃ₐ[F] L'` is an isomorphism
compatible with `E / L` and `E / L'`, then for any subset `S` of `E`, `L(S)` and `L'(S)` are
equal as intermediate fields of `E / F`. -/
theorem restrictScalars_adjoin_of_algEquiv
{L L' : Type*} [Field L] [Field L']
[Algebra F L] [Algebra L E] [Algebra F L'] [Algebra L' E]
[IsScalarTower F L E] [IsScalarTower F L' E] (i : L ≃ₐ[F] L')
(hi : algebraMap L E = (algebraMap L' E) ∘ i) (S : Set E) :
(adjoin L S).restrictScalars F = (adjoin L' S).restrictScalars F := by
apply_fun toSubfield using (fun K K' h ↦ by
ext x; change x ∈ K.toSubfield ↔ x ∈ K'.toSubfield; rw [h])
change Subfield.closure _ = Subfield.closure _
congr
ext x
exact ⟨fun ⟨y, h⟩ ↦ ⟨i y, by rw [← h, hi]; rfl⟩,
fun ⟨y, h⟩ ↦ ⟨i.symm y, by rw [← h, hi, Function.comp_apply, AlgEquiv.apply_symm_apply]⟩⟩
theorem algebra_adjoin_le_adjoin : Algebra.adjoin F S ≤ (adjoin F S).toSubalgebra :=
Algebra.adjoin_le (subset_adjoin _ _)
#align intermediate_field.algebra_adjoin_le_adjoin IntermediateField.algebra_adjoin_le_adjoin
theorem adjoin_eq_algebra_adjoin (inv_mem : ∀ x ∈ Algebra.adjoin F S, x⁻¹ ∈ Algebra.adjoin F S) :
(adjoin F S).toSubalgebra = Algebra.adjoin F S :=
le_antisymm
(show adjoin F S ≤
{ Algebra.adjoin F S with
inv_mem' := inv_mem }
from adjoin_le_iff.mpr Algebra.subset_adjoin)
(algebra_adjoin_le_adjoin _ _)
#align intermediate_field.adjoin_eq_algebra_adjoin IntermediateField.adjoin_eq_algebra_adjoin
theorem eq_adjoin_of_eq_algebra_adjoin (K : IntermediateField F E)
(h : K.toSubalgebra = Algebra.adjoin F S) : K = adjoin F S := by
apply toSubalgebra_injective
rw [h]
refine (adjoin_eq_algebra_adjoin F _ ?_).symm
intro x
convert K.inv_mem (x := x) <;> rw [← h] <;> rfl
#align intermediate_field.eq_adjoin_of_eq_algebra_adjoin IntermediateField.eq_adjoin_of_eq_algebra_adjoin
theorem adjoin_eq_top_of_algebra (hS : Algebra.adjoin F S = ⊤) : adjoin F S = ⊤ :=
top_le_iff.mp (hS.symm.trans_le <| algebra_adjoin_le_adjoin F S)
@[elab_as_elim]
theorem adjoin_induction {s : Set E} {p : E → Prop} {x} (h : x ∈ adjoin F s) (mem : ∀ x ∈ s, p x)
(algebraMap : ∀ x, p (algebraMap F E x)) (add : ∀ x y, p x → p y → p (x + y))
(neg : ∀ x, p x → p (-x)) (inv : ∀ x, p x → p x⁻¹) (mul : ∀ x y, p x → p y → p (x * y)) :
p x :=
Subfield.closure_induction h
(fun x hx => Or.casesOn hx (fun ⟨x, hx⟩ => hx ▸ algebraMap x) (mem x))
((_root_.algebraMap F E).map_one ▸ algebraMap 1) add neg inv mul
#align intermediate_field.adjoin_induction IntermediateField.adjoin_induction
/- Porting note (kmill): this notation is replacing the typeclass-based one I had previously
written, and it gives true `{x₁, x₂, ..., xₙ}` sets in the `adjoin` term. -/
open Lean in
/-- Supporting function for the `F⟮x₁,x₂,...,xₙ⟯` adjunction notation. -/
private partial def mkInsertTerm [Monad m] [MonadQuotation m] (xs : TSyntaxArray `term) : m Term :=
run 0
where
run (i : Nat) : m Term := do
if i + 1 == xs.size then
``(singleton $(xs[i]!))
else if i < xs.size then
``(insert $(xs[i]!) $(← run (i + 1)))
else
``(EmptyCollection.emptyCollection)
/-- If `x₁ x₂ ... xₙ : E` then `F⟮x₁,x₂,...,xₙ⟯` is the `IntermediateField F E`
generated by these elements. -/
scoped macro:max K:term "⟮" xs:term,* "⟯" : term => do ``(adjoin $K $(← mkInsertTerm xs.getElems))
open Lean PrettyPrinter.Delaborator SubExpr in
@[delab app.IntermediateField.adjoin]
partial def delabAdjoinNotation : Delab := whenPPOption getPPNotation do
let e ← getExpr
guard <| e.isAppOfArity ``adjoin 6
let F ← withNaryArg 0 delab
let xs ← withNaryArg 5 delabInsertArray
`($F⟮$(xs.toArray),*⟯)
where
delabInsertArray : DelabM (List Term) := do
let e ← getExpr
if e.isAppOfArity ``EmptyCollection.emptyCollection 2 then
return []
else if e.isAppOfArity ``singleton 4 then
let x ← withNaryArg 3 delab
return [x]
else if e.isAppOfArity ``insert 5 then
let x ← withNaryArg 3 delab
let xs ← withNaryArg 4 delabInsertArray
return x :: xs
else failure
section AdjoinSimple
variable (α : E)
-- Porting note: in all the theorems below, mathport translated `F⟮α⟯` into `F⟮⟯`.
theorem mem_adjoin_simple_self : α ∈ F⟮α⟯ :=
subset_adjoin F {α} (Set.mem_singleton α)
#align intermediate_field.mem_adjoin_simple_self IntermediateField.mem_adjoin_simple_self
/-- generator of `F⟮α⟯` -/
def AdjoinSimple.gen : F⟮α⟯ :=
⟨α, mem_adjoin_simple_self F α⟩
#align intermediate_field.adjoin_simple.gen IntermediateField.AdjoinSimple.gen
@[simp]
theorem AdjoinSimple.coe_gen : (AdjoinSimple.gen F α : E) = α :=
rfl
theorem AdjoinSimple.algebraMap_gen : algebraMap F⟮α⟯ E (AdjoinSimple.gen F α) = α :=
rfl
#align intermediate_field.adjoin_simple.algebra_map_gen IntermediateField.AdjoinSimple.algebraMap_gen
@[simp]
theorem AdjoinSimple.isIntegral_gen : IsIntegral F (AdjoinSimple.gen F α) ↔ IsIntegral F α := by
conv_rhs => rw [← AdjoinSimple.algebraMap_gen F α]
rw [isIntegral_algebraMap_iff (algebraMap F⟮α⟯ E).injective]
#align intermediate_field.adjoin_simple.is_integral_gen IntermediateField.AdjoinSimple.isIntegral_gen
theorem adjoin_simple_adjoin_simple (β : E) : F⟮α⟯⟮β⟯.restrictScalars F = F⟮α, β⟯ :=
adjoin_adjoin_left _ _ _
#align intermediate_field.adjoin_simple_adjoin_simple IntermediateField.adjoin_simple_adjoin_simple
theorem adjoin_simple_comm (β : E) : F⟮α⟯⟮β⟯.restrictScalars F = F⟮β⟯⟮α⟯.restrictScalars F :=
adjoin_adjoin_comm _ _ _
#align intermediate_field.adjoin_simple_comm IntermediateField.adjoin_simple_comm
variable {F} {α}
| Mathlib/FieldTheory/Adjoin.lean | 629 | 635 | theorem adjoin_algebraic_toSubalgebra {S : Set E} (hS : ∀ x ∈ S, IsAlgebraic F x) :
(IntermediateField.adjoin F S).toSubalgebra = Algebra.adjoin F S := by |
simp only [isAlgebraic_iff_isIntegral] at hS
have : Algebra.IsIntegral F (Algebra.adjoin F S) := by
rwa [← le_integralClosure_iff_isIntegral, Algebra.adjoin_le_iff]
have : IsField (Algebra.adjoin F S) := isField_of_isIntegral_of_isField' (Field.toIsField F)
rw [← ((Algebra.adjoin F S).toIntermediateField' this).eq_adjoin_of_eq_algebra_adjoin F S] <;> rfl
|
/-
Copyright (c) 2021 Benjamin Davidson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Benjamin Davidson
-/
import Mathlib.MeasureTheory.Integral.FundThmCalculus
import Mathlib.Analysis.SpecialFunctions.Trigonometric.ArctanDeriv
import Mathlib.Analysis.SpecialFunctions.NonIntegrable
import Mathlib.Analysis.SpecialFunctions.Pow.Deriv
#align_import analysis.special_functions.integrals from "leanprover-community/mathlib"@"011cafb4a5bc695875d186e245d6b3df03bf6c40"
/-!
# Integration of specific interval integrals
This file contains proofs of the integrals of various specific functions. This includes:
* Integrals of simple functions, such as `id`, `pow`, `inv`, `exp`, `log`
* Integrals of some trigonometric functions, such as `sin`, `cos`, `1 / (1 + x^2)`
* The integral of `cos x ^ 2 - sin x ^ 2`
* Reduction formulae for the integrals of `sin x ^ n` and `cos x ^ n` for `n ≥ 2`
* The computation of `∫ x in 0..π, sin x ^ n` as a product for even and odd `n` (used in proving the
Wallis product for pi)
* Integrals of the form `sin x ^ m * cos x ^ n`
With these lemmas, many simple integrals can be computed by `simp` or `norm_num`.
See `test/integration.lean` for specific examples.
This file also contains some facts about the interval integrability of specific functions.
This file is still being developed.
## Tags
integrate, integration, integrable, integrability
-/
open Real Nat Set Finset
open scoped Real Interval
variable {a b : ℝ} (n : ℕ)
namespace intervalIntegral
open MeasureTheory
variable {f : ℝ → ℝ} {μ ν : Measure ℝ} [IsLocallyFiniteMeasure μ] (c d : ℝ)
/-! ### Interval integrability -/
@[simp]
theorem intervalIntegrable_pow : IntervalIntegrable (fun x => x ^ n) μ a b :=
(continuous_pow n).intervalIntegrable a b
#align interval_integral.interval_integrable_pow intervalIntegral.intervalIntegrable_pow
theorem intervalIntegrable_zpow {n : ℤ} (h : 0 ≤ n ∨ (0 : ℝ) ∉ [[a, b]]) :
IntervalIntegrable (fun x => x ^ n) μ a b :=
(continuousOn_id.zpow₀ n fun _ hx => h.symm.imp (ne_of_mem_of_not_mem hx) id).intervalIntegrable
#align interval_integral.interval_integrable_zpow intervalIntegral.intervalIntegrable_zpow
/-- See `intervalIntegrable_rpow'` for a version with a weaker hypothesis on `r`, but assuming the
measure is volume. -/
theorem intervalIntegrable_rpow {r : ℝ} (h : 0 ≤ r ∨ (0 : ℝ) ∉ [[a, b]]) :
IntervalIntegrable (fun x => x ^ r) μ a b :=
(continuousOn_id.rpow_const fun _ hx =>
h.symm.imp (ne_of_mem_of_not_mem hx) id).intervalIntegrable
#align interval_integral.interval_integrable_rpow intervalIntegral.intervalIntegrable_rpow
/-- See `intervalIntegrable_rpow` for a version applying to any locally finite measure, but with a
stronger hypothesis on `r`. -/
theorem intervalIntegrable_rpow' {r : ℝ} (h : -1 < r) :
IntervalIntegrable (fun x => x ^ r) volume a b := by
suffices ∀ c : ℝ, IntervalIntegrable (fun x => x ^ r) volume 0 c by
exact IntervalIntegrable.trans (this a).symm (this b)
have : ∀ c : ℝ, 0 ≤ c → IntervalIntegrable (fun x => x ^ r) volume 0 c := by
intro c hc
rw [intervalIntegrable_iff, uIoc_of_le hc]
have hderiv : ∀ x ∈ Ioo 0 c, HasDerivAt (fun x : ℝ => x ^ (r + 1) / (r + 1)) (x ^ r) x := by
intro x hx
convert (Real.hasDerivAt_rpow_const (p := r + 1) (Or.inl hx.1.ne')).div_const (r + 1) using 1
field_simp [(by linarith : r + 1 ≠ 0)]
apply integrableOn_deriv_of_nonneg _ hderiv
· intro x hx; apply rpow_nonneg hx.1.le
· refine (continuousOn_id.rpow_const ?_).div_const _; intro x _; right; linarith
intro c; rcases le_total 0 c with (hc | hc)
· exact this c hc
· rw [IntervalIntegrable.iff_comp_neg, neg_zero]
have m := (this (-c) (by linarith)).smul (cos (r * π))
rw [intervalIntegrable_iff] at m ⊢
refine m.congr_fun ?_ measurableSet_Ioc; intro x hx
rw [uIoc_of_le (by linarith : 0 ≤ -c)] at hx
simp only [Pi.smul_apply, Algebra.id.smul_eq_mul, log_neg_eq_log, mul_comm,
rpow_def_of_pos hx.1, rpow_def_of_neg (by linarith [hx.1] : -x < 0)]
#align interval_integral.interval_integrable_rpow' intervalIntegral.intervalIntegrable_rpow'
/-- The power function `x ↦ x^s` is integrable on `(0, t)` iff `-1 < s`. -/
lemma integrableOn_Ioo_rpow_iff {s t : ℝ} (ht : 0 < t) :
IntegrableOn (fun x ↦ x ^ s) (Ioo (0 : ℝ) t) ↔ -1 < s := by
refine ⟨fun h ↦ ?_, fun h ↦ by simpa [intervalIntegrable_iff_integrableOn_Ioo_of_le ht.le]
using intervalIntegrable_rpow' h (a := 0) (b := t)⟩
contrapose! h
intro H
have I : 0 < min 1 t := lt_min zero_lt_one ht
have H' : IntegrableOn (fun x ↦ x ^ s) (Ioo 0 (min 1 t)) :=
H.mono (Set.Ioo_subset_Ioo le_rfl (min_le_right _ _)) le_rfl
have : IntegrableOn (fun x ↦ x⁻¹) (Ioo 0 (min 1 t)) := by
apply H'.mono' measurable_inv.aestronglyMeasurable
filter_upwards [ae_restrict_mem measurableSet_Ioo] with x hx
simp only [norm_inv, Real.norm_eq_abs, abs_of_nonneg (le_of_lt hx.1)]
rwa [← Real.rpow_neg_one x, Real.rpow_le_rpow_left_iff_of_base_lt_one hx.1]
exact lt_of_lt_of_le hx.2 (min_le_left _ _)
have : IntervalIntegrable (fun x ↦ x⁻¹) volume 0 (min 1 t) := by
rwa [intervalIntegrable_iff_integrableOn_Ioo_of_le I.le]
simp [intervalIntegrable_inv_iff, I.ne] at this
/-- See `intervalIntegrable_cpow'` for a version with a weaker hypothesis on `r`, but assuming the
measure is volume. -/
theorem intervalIntegrable_cpow {r : ℂ} (h : 0 ≤ r.re ∨ (0 : ℝ) ∉ [[a, b]]) :
IntervalIntegrable (fun x : ℝ => (x : ℂ) ^ r) μ a b := by
by_cases h2 : (0 : ℝ) ∉ [[a, b]]
· -- Easy case #1: 0 ∉ [a, b] -- use continuity.
refine (ContinuousAt.continuousOn fun x hx => ?_).intervalIntegrable
exact Complex.continuousAt_ofReal_cpow_const _ _ (Or.inr <| ne_of_mem_of_not_mem hx h2)
rw [eq_false h2, or_false_iff] at h
rcases lt_or_eq_of_le h with (h' | h')
· -- Easy case #2: 0 < re r -- again use continuity
exact (Complex.continuous_ofReal_cpow_const h').intervalIntegrable _ _
-- Now the hard case: re r = 0 and 0 is in the interval.
refine (IntervalIntegrable.intervalIntegrable_norm_iff ?_).mp ?_
· refine (measurable_of_continuousOn_compl_singleton (0 : ℝ) ?_).aestronglyMeasurable
exact ContinuousAt.continuousOn fun x hx =>
Complex.continuousAt_ofReal_cpow_const x r (Or.inr hx)
-- reduce to case of integral over `[0, c]`
suffices ∀ c : ℝ, IntervalIntegrable (fun x : ℝ => ‖(x:ℂ) ^ r‖) μ 0 c from
(this a).symm.trans (this b)
intro c
rcases le_or_lt 0 c with (hc | hc)
· -- case `0 ≤ c`: integrand is identically 1
have : IntervalIntegrable (fun _ => 1 : ℝ → ℝ) μ 0 c := intervalIntegrable_const
rw [intervalIntegrable_iff_integrableOn_Ioc_of_le hc] at this ⊢
refine IntegrableOn.congr_fun this (fun x hx => ?_) measurableSet_Ioc
dsimp only
rw [Complex.norm_eq_abs, Complex.abs_cpow_eq_rpow_re_of_pos hx.1, ← h', rpow_zero]
· -- case `c < 0`: integrand is identically constant, *except* at `x = 0` if `r ≠ 0`.
apply IntervalIntegrable.symm
rw [intervalIntegrable_iff_integrableOn_Ioc_of_le hc.le]
have : Ioc c 0 = Ioo c 0 ∪ {(0 : ℝ)} := by
rw [← Ioo_union_Icc_eq_Ioc hc (le_refl 0), ← Icc_def]
simp_rw [← le_antisymm_iff, setOf_eq_eq_singleton']
rw [this, integrableOn_union, and_comm]; constructor
· refine integrableOn_singleton_iff.mpr (Or.inr ?_)
exact isFiniteMeasureOnCompacts_of_isLocallyFiniteMeasure.lt_top_of_isCompact
isCompact_singleton
· have : ∀ x : ℝ, x ∈ Ioo c 0 → ‖Complex.exp (↑π * Complex.I * r)‖ = ‖(x : ℂ) ^ r‖ := by
intro x hx
rw [Complex.ofReal_cpow_of_nonpos hx.2.le, norm_mul, ← Complex.ofReal_neg,
Complex.norm_eq_abs (_ ^ _), Complex.abs_cpow_eq_rpow_re_of_pos (neg_pos.mpr hx.2), ← h',
rpow_zero, one_mul]
refine IntegrableOn.congr_fun ?_ this measurableSet_Ioo
rw [integrableOn_const]
refine Or.inr ((measure_mono Set.Ioo_subset_Icc_self).trans_lt ?_)
exact isFiniteMeasureOnCompacts_of_isLocallyFiniteMeasure.lt_top_of_isCompact isCompact_Icc
#align interval_integral.interval_integrable_cpow intervalIntegral.intervalIntegrable_cpow
/-- See `intervalIntegrable_cpow` for a version applying to any locally finite measure, but with a
stronger hypothesis on `r`. -/
theorem intervalIntegrable_cpow' {r : ℂ} (h : -1 < r.re) :
IntervalIntegrable (fun x : ℝ => (x : ℂ) ^ r) volume a b := by
suffices ∀ c : ℝ, IntervalIntegrable (fun x => (x : ℂ) ^ r) volume 0 c by
exact IntervalIntegrable.trans (this a).symm (this b)
have : ∀ c : ℝ, 0 ≤ c → IntervalIntegrable (fun x => (x : ℂ) ^ r) volume 0 c := by
intro c hc
rw [← IntervalIntegrable.intervalIntegrable_norm_iff]
· rw [intervalIntegrable_iff]
apply IntegrableOn.congr_fun
· rw [← intervalIntegrable_iff]; exact intervalIntegral.intervalIntegrable_rpow' h
· intro x hx
rw [uIoc_of_le hc] at hx
dsimp only
rw [Complex.norm_eq_abs, Complex.abs_cpow_eq_rpow_re_of_pos hx.1]
· exact measurableSet_uIoc
· refine ContinuousOn.aestronglyMeasurable ?_ measurableSet_uIoc
refine ContinuousAt.continuousOn fun x hx => ?_
rw [uIoc_of_le hc] at hx
refine (continuousAt_cpow_const (Or.inl ?_)).comp Complex.continuous_ofReal.continuousAt
rw [Complex.ofReal_re]
exact hx.1
intro c; rcases le_total 0 c with (hc | hc)
· exact this c hc
· rw [IntervalIntegrable.iff_comp_neg, neg_zero]
have m := (this (-c) (by linarith)).const_mul (Complex.exp (π * Complex.I * r))
rw [intervalIntegrable_iff, uIoc_of_le (by linarith : 0 ≤ -c)] at m ⊢
refine m.congr_fun (fun x hx => ?_) measurableSet_Ioc
dsimp only
have : -x ≤ 0 := by linarith [hx.1]
rw [Complex.ofReal_cpow_of_nonpos this, mul_comm]
simp
#align interval_integral.interval_integrable_cpow' intervalIntegral.intervalIntegrable_cpow'
/-- The complex power function `x ↦ x^s` is integrable on `(0, t)` iff `-1 < s.re`. -/
theorem integrableOn_Ioo_cpow_iff {s : ℂ} {t : ℝ} (ht : 0 < t) :
IntegrableOn (fun x : ℝ ↦ (x : ℂ) ^ s) (Ioo (0 : ℝ) t) ↔ -1 < s.re := by
refine ⟨fun h ↦ ?_, fun h ↦ by simpa [intervalIntegrable_iff_integrableOn_Ioo_of_le ht.le]
using intervalIntegrable_cpow' h (a := 0) (b := t)⟩
have B : IntegrableOn (fun a ↦ a ^ s.re) (Ioo 0 t) := by
apply (integrableOn_congr_fun _ measurableSet_Ioo).1 h.norm
intro a ha
simp [Complex.abs_cpow_eq_rpow_re_of_pos ha.1]
rwa [integrableOn_Ioo_rpow_iff ht] at B
@[simp]
theorem intervalIntegrable_id : IntervalIntegrable (fun x => x) μ a b :=
continuous_id.intervalIntegrable a b
#align interval_integral.interval_integrable_id intervalIntegral.intervalIntegrable_id
-- @[simp] -- Porting note (#10618): simp can prove this
theorem intervalIntegrable_const : IntervalIntegrable (fun _ => c) μ a b :=
continuous_const.intervalIntegrable a b
#align interval_integral.interval_integrable_const intervalIntegral.intervalIntegrable_const
theorem intervalIntegrable_one_div (h : ∀ x : ℝ, x ∈ [[a, b]] → f x ≠ 0)
(hf : ContinuousOn f [[a, b]]) : IntervalIntegrable (fun x => 1 / f x) μ a b :=
(continuousOn_const.div hf h).intervalIntegrable
#align interval_integral.interval_integrable_one_div intervalIntegral.intervalIntegrable_one_div
@[simp]
theorem intervalIntegrable_inv (h : ∀ x : ℝ, x ∈ [[a, b]] → f x ≠ 0)
(hf : ContinuousOn f [[a, b]]) : IntervalIntegrable (fun x => (f x)⁻¹) μ a b := by
simpa only [one_div] using intervalIntegrable_one_div h hf
#align interval_integral.interval_integrable_inv intervalIntegral.intervalIntegrable_inv
@[simp]
theorem intervalIntegrable_exp : IntervalIntegrable exp μ a b :=
continuous_exp.intervalIntegrable a b
#align interval_integral.interval_integrable_exp intervalIntegral.intervalIntegrable_exp
@[simp]
theorem _root_.IntervalIntegrable.log (hf : ContinuousOn f [[a, b]])
(h : ∀ x : ℝ, x ∈ [[a, b]] → f x ≠ 0) :
IntervalIntegrable (fun x => log (f x)) μ a b :=
(ContinuousOn.log hf h).intervalIntegrable
#align interval_integrable.log IntervalIntegrable.log
@[simp]
theorem intervalIntegrable_log (h : (0 : ℝ) ∉ [[a, b]]) : IntervalIntegrable log μ a b :=
IntervalIntegrable.log continuousOn_id fun _ hx => ne_of_mem_of_not_mem hx h
#align interval_integral.interval_integrable_log intervalIntegral.intervalIntegrable_log
@[simp]
theorem intervalIntegrable_sin : IntervalIntegrable sin μ a b :=
continuous_sin.intervalIntegrable a b
#align interval_integral.interval_integrable_sin intervalIntegral.intervalIntegrable_sin
@[simp]
theorem intervalIntegrable_cos : IntervalIntegrable cos μ a b :=
continuous_cos.intervalIntegrable a b
#align interval_integral.interval_integrable_cos intervalIntegral.intervalIntegrable_cos
theorem intervalIntegrable_one_div_one_add_sq :
IntervalIntegrable (fun x : ℝ => 1 / (↑1 + x ^ 2)) μ a b := by
refine (continuous_const.div ?_ fun x => ?_).intervalIntegrable a b
· continuity
· nlinarith
#align interval_integral.interval_integrable_one_div_one_add_sq intervalIntegral.intervalIntegrable_one_div_one_add_sq
@[simp]
theorem intervalIntegrable_inv_one_add_sq :
IntervalIntegrable (fun x : ℝ => (↑1 + x ^ 2)⁻¹) μ a b := by
field_simp; exact mod_cast intervalIntegrable_one_div_one_add_sq
#align interval_integral.interval_integrable_inv_one_add_sq intervalIntegral.intervalIntegrable_inv_one_add_sq
/-! ### Integrals of the form `c * ∫ x in a..b, f (c * x + d)` -/
-- Porting note (#10618): was @[simp];
-- simpNF says LHS does not simplify when applying lemma on itself
theorem mul_integral_comp_mul_right : (c * ∫ x in a..b, f (x * c)) = ∫ x in a * c..b * c, f x :=
smul_integral_comp_mul_right f c
#align interval_integral.mul_integral_comp_mul_right intervalIntegral.mul_integral_comp_mul_right
-- Porting note (#10618): was @[simp]
theorem mul_integral_comp_mul_left : (c * ∫ x in a..b, f (c * x)) = ∫ x in c * a..c * b, f x :=
smul_integral_comp_mul_left f c
#align interval_integral.mul_integral_comp_mul_left intervalIntegral.mul_integral_comp_mul_left
-- Porting note (#10618): was @[simp]
theorem inv_mul_integral_comp_div : (c⁻¹ * ∫ x in a..b, f (x / c)) = ∫ x in a / c..b / c, f x :=
inv_smul_integral_comp_div f c
#align interval_integral.inv_mul_integral_comp_div intervalIntegral.inv_mul_integral_comp_div
-- Porting note (#10618): was @[simp]
theorem mul_integral_comp_mul_add :
(c * ∫ x in a..b, f (c * x + d)) = ∫ x in c * a + d..c * b + d, f x :=
smul_integral_comp_mul_add f c d
#align interval_integral.mul_integral_comp_mul_add intervalIntegral.mul_integral_comp_mul_add
-- Porting note (#10618): was @[simp]
theorem mul_integral_comp_add_mul :
(c * ∫ x in a..b, f (d + c * x)) = ∫ x in d + c * a..d + c * b, f x :=
smul_integral_comp_add_mul f c d
#align interval_integral.mul_integral_comp_add_mul intervalIntegral.mul_integral_comp_add_mul
-- Porting note (#10618): was @[simp]
theorem inv_mul_integral_comp_div_add :
(c⁻¹ * ∫ x in a..b, f (x / c + d)) = ∫ x in a / c + d..b / c + d, f x :=
inv_smul_integral_comp_div_add f c d
#align interval_integral.inv_mul_integral_comp_div_add intervalIntegral.inv_mul_integral_comp_div_add
-- Porting note (#10618): was @[simp]
theorem inv_mul_integral_comp_add_div :
(c⁻¹ * ∫ x in a..b, f (d + x / c)) = ∫ x in d + a / c..d + b / c, f x :=
inv_smul_integral_comp_add_div f c d
#align interval_integral.inv_mul_integral_comp_add_div intervalIntegral.inv_mul_integral_comp_add_div
-- Porting note (#10618): was @[simp]
theorem mul_integral_comp_mul_sub :
(c * ∫ x in a..b, f (c * x - d)) = ∫ x in c * a - d..c * b - d, f x :=
smul_integral_comp_mul_sub f c d
#align interval_integral.mul_integral_comp_mul_sub intervalIntegral.mul_integral_comp_mul_sub
-- Porting note (#10618): was @[simp]
theorem mul_integral_comp_sub_mul :
(c * ∫ x in a..b, f (d - c * x)) = ∫ x in d - c * b..d - c * a, f x :=
smul_integral_comp_sub_mul f c d
#align interval_integral.mul_integral_comp_sub_mul intervalIntegral.mul_integral_comp_sub_mul
-- Porting note (#10618): was @[simp]
theorem inv_mul_integral_comp_div_sub :
(c⁻¹ * ∫ x in a..b, f (x / c - d)) = ∫ x in a / c - d..b / c - d, f x :=
inv_smul_integral_comp_div_sub f c d
#align interval_integral.inv_mul_integral_comp_div_sub intervalIntegral.inv_mul_integral_comp_div_sub
-- Porting note (#10618): was @[simp]
theorem inv_mul_integral_comp_sub_div :
(c⁻¹ * ∫ x in a..b, f (d - x / c)) = ∫ x in d - b / c..d - a / c, f x :=
inv_smul_integral_comp_sub_div f c d
#align interval_integral.inv_mul_integral_comp_sub_div intervalIntegral.inv_mul_integral_comp_sub_div
end intervalIntegral
open intervalIntegral
/-! ### Integrals of simple functions -/
theorem integral_cpow {r : ℂ} (h : -1 < r.re ∨ r ≠ -1 ∧ (0 : ℝ) ∉ [[a, b]]) :
(∫ x : ℝ in a..b, (x : ℂ) ^ r) = ((b:ℂ) ^ (r + 1) - (a:ℂ) ^ (r + 1)) / (r + 1) := by
rw [sub_div]
have hr : r + 1 ≠ 0 := by
cases' h with h h
· apply_fun Complex.re
rw [Complex.add_re, Complex.one_re, Complex.zero_re, Ne, add_eq_zero_iff_eq_neg]
exact h.ne'
· rw [Ne, ← add_eq_zero_iff_eq_neg] at h; exact h.1
by_cases hab : (0 : ℝ) ∉ [[a, b]]
· apply integral_eq_sub_of_hasDerivAt (fun x hx => ?_)
(intervalIntegrable_cpow (r := r) <| Or.inr hab)
refine hasDerivAt_ofReal_cpow (ne_of_mem_of_not_mem hx hab) ?_
contrapose! hr; rwa [add_eq_zero_iff_eq_neg]
replace h : -1 < r.re := by tauto
suffices ∀ c : ℝ, (∫ x : ℝ in (0)..c, (x : ℂ) ^ r) =
(c:ℂ) ^ (r + 1) / (r + 1) - (0:ℂ) ^ (r + 1) / (r + 1) by
rw [← integral_add_adjacent_intervals (@intervalIntegrable_cpow' a 0 r h)
(@intervalIntegrable_cpow' 0 b r h), integral_symm, this a, this b, Complex.zero_cpow hr]
ring
intro c
apply integral_eq_sub_of_hasDeriv_right
· refine ((Complex.continuous_ofReal_cpow_const ?_).div_const _).continuousOn
rwa [Complex.add_re, Complex.one_re, ← neg_lt_iff_pos_add]
· refine fun x hx => (hasDerivAt_ofReal_cpow ?_ ?_).hasDerivWithinAt
· rcases le_total c 0 with (hc | hc)
· rw [max_eq_left hc] at hx; exact hx.2.ne
· rw [min_eq_left hc] at hx; exact hx.1.ne'
· contrapose! hr; rw [hr]; ring
· exact intervalIntegrable_cpow' h
#align integral_cpow integral_cpow
theorem integral_rpow {r : ℝ} (h : -1 < r ∨ r ≠ -1 ∧ (0 : ℝ) ∉ [[a, b]]) :
∫ x in a..b, x ^ r = (b ^ (r + 1) - a ^ (r + 1)) / (r + 1) := by
have h' : -1 < (r : ℂ).re ∨ (r : ℂ) ≠ -1 ∧ (0 : ℝ) ∉ [[a, b]] := by
cases h
· left; rwa [Complex.ofReal_re]
· right; rwa [← Complex.ofReal_one, ← Complex.ofReal_neg, Ne, Complex.ofReal_inj]
have :
(∫ x in a..b, (x : ℂ) ^ (r : ℂ)) = ((b : ℂ) ^ (r + 1 : ℂ) - (a : ℂ) ^ (r + 1 : ℂ)) / (r + 1) :=
integral_cpow h'
apply_fun Complex.re at this; convert this
· simp_rw [intervalIntegral_eq_integral_uIoc, Complex.real_smul, Complex.re_ofReal_mul]
-- Porting note: was `change ... with ...`
have : Complex.re = RCLike.re := rfl
rw [this, ← integral_re]
· rfl
refine intervalIntegrable_iff.mp ?_
cases' h' with h' h'
· exact intervalIntegrable_cpow' h'
· exact intervalIntegrable_cpow (Or.inr h'.2)
· rw [(by push_cast; rfl : (r : ℂ) + 1 = ((r + 1 : ℝ) : ℂ))]
simp_rw [div_eq_inv_mul, ← Complex.ofReal_inv, Complex.re_ofReal_mul, Complex.sub_re]
rfl
#align integral_rpow integral_rpow
theorem integral_zpow {n : ℤ} (h : 0 ≤ n ∨ n ≠ -1 ∧ (0 : ℝ) ∉ [[a, b]]) :
∫ x in a..b, x ^ n = (b ^ (n + 1) - a ^ (n + 1)) / (n + 1) := by
replace h : -1 < (n : ℝ) ∨ (n : ℝ) ≠ -1 ∧ (0 : ℝ) ∉ [[a, b]] := mod_cast h
exact mod_cast integral_rpow h
#align integral_zpow integral_zpow
@[simp]
theorem integral_pow : ∫ x in a..b, x ^ n = (b ^ (n + 1) - a ^ (n + 1)) / (n + 1) := by
simpa only [← Int.ofNat_succ, zpow_natCast] using integral_zpow (Or.inl n.cast_nonneg)
#align integral_pow integral_pow
/-- Integral of `|x - a| ^ n` over `Ι a b`. This integral appears in the proof of the
Picard-Lindelöf/Cauchy-Lipschitz theorem. -/
theorem integral_pow_abs_sub_uIoc : ∫ x in Ι a b, |x - a| ^ n = |b - a| ^ (n + 1) / (n + 1) := by
rcases le_or_lt a b with hab | hab
· calc
∫ x in Ι a b, |x - a| ^ n = ∫ x in a..b, |x - a| ^ n := by
rw [uIoc_of_le hab, ← integral_of_le hab]
_ = ∫ x in (0)..(b - a), x ^ n := by
simp only [integral_comp_sub_right fun x => |x| ^ n, sub_self]
refine integral_congr fun x hx => congr_arg₂ Pow.pow (abs_of_nonneg <| ?_) rfl
rw [uIcc_of_le (sub_nonneg.2 hab)] at hx
exact hx.1
_ = |b - a| ^ (n + 1) / (n + 1) := by simp [abs_of_nonneg (sub_nonneg.2 hab)]
· calc
∫ x in Ι a b, |x - a| ^ n = ∫ x in b..a, |x - a| ^ n := by
rw [uIoc_of_lt hab, ← integral_of_le hab.le]
_ = ∫ x in b - a..0, (-x) ^ n := by
simp only [integral_comp_sub_right fun x => |x| ^ n, sub_self]
refine integral_congr fun x hx => congr_arg₂ Pow.pow (abs_of_nonpos <| ?_) rfl
rw [uIcc_of_le (sub_nonpos.2 hab.le)] at hx
exact hx.2
_ = |b - a| ^ (n + 1) / (n + 1) := by
simp [integral_comp_neg fun x => x ^ n, abs_of_neg (sub_neg.2 hab)]
#align integral_pow_abs_sub_uIoc integral_pow_abs_sub_uIoc
@[simp]
theorem integral_id : ∫ x in a..b, x = (b ^ 2 - a ^ 2) / 2 := by
have := @integral_pow a b 1
norm_num at this
exact this
#align integral_id integral_id
-- @[simp] -- Porting note (#10618): simp can prove this
theorem integral_one : (∫ _ in a..b, (1 : ℝ)) = b - a := by
simp only [mul_one, smul_eq_mul, integral_const]
#align integral_one integral_one
theorem integral_const_on_unit_interval : ∫ _ in a..a + 1, b = b := by simp
#align integral_const_on_unit_interval integral_const_on_unit_interval
@[simp]
theorem integral_inv (h : (0 : ℝ) ∉ [[a, b]]) : ∫ x in a..b, x⁻¹ = log (b / a) := by
have h' := fun x (hx : x ∈ [[a, b]]) => ne_of_mem_of_not_mem hx h
rw [integral_deriv_eq_sub' _ deriv_log' (fun x hx => differentiableAt_log (h' x hx))
(continuousOn_inv₀.mono <| subset_compl_singleton_iff.mpr h),
log_div (h' b right_mem_uIcc) (h' a left_mem_uIcc)]
#align integral_inv integral_inv
@[simp]
theorem integral_inv_of_pos (ha : 0 < a) (hb : 0 < b) : ∫ x in a..b, x⁻¹ = log (b / a) :=
integral_inv <| not_mem_uIcc_of_lt ha hb
#align integral_inv_of_pos integral_inv_of_pos
@[simp]
theorem integral_inv_of_neg (ha : a < 0) (hb : b < 0) : ∫ x in a..b, x⁻¹ = log (b / a) :=
integral_inv <| not_mem_uIcc_of_gt ha hb
#align integral_inv_of_neg integral_inv_of_neg
theorem integral_one_div (h : (0 : ℝ) ∉ [[a, b]]) : ∫ x : ℝ in a..b, 1 / x = log (b / a) := by
simp only [one_div, integral_inv h]
#align integral_one_div integral_one_div
theorem integral_one_div_of_pos (ha : 0 < a) (hb : 0 < b) :
∫ x : ℝ in a..b, 1 / x = log (b / a) := by simp only [one_div, integral_inv_of_pos ha hb]
#align integral_one_div_of_pos integral_one_div_of_pos
theorem integral_one_div_of_neg (ha : a < 0) (hb : b < 0) :
∫ x : ℝ in a..b, 1 / x = log (b / a) := by simp only [one_div, integral_inv_of_neg ha hb]
#align integral_one_div_of_neg integral_one_div_of_neg
@[simp]
theorem integral_exp : ∫ x in a..b, exp x = exp b - exp a := by
rw [integral_deriv_eq_sub']
· simp
· exact fun _ _ => differentiableAt_exp
· exact continuousOn_exp
#align integral_exp integral_exp
theorem integral_exp_mul_complex {c : ℂ} (hc : c ≠ 0) :
(∫ x in a..b, Complex.exp (c * x)) = (Complex.exp (c * b) - Complex.exp (c * a)) / c := by
have D : ∀ x : ℝ, HasDerivAt (fun y : ℝ => Complex.exp (c * y) / c) (Complex.exp (c * x)) x := by
intro x
conv => congr
rw [← mul_div_cancel_right₀ (Complex.exp (c * x)) hc]
apply ((Complex.hasDerivAt_exp _).comp x _).div_const c
simpa only [mul_one] using ((hasDerivAt_id (x : ℂ)).const_mul _).comp_ofReal
rw [integral_deriv_eq_sub' _ (funext fun x => (D x).deriv) fun x _ => (D x).differentiableAt]
· ring
· apply Continuous.continuousOn; continuity
#align integral_exp_mul_complex integral_exp_mul_complex
@[simp]
theorem integral_log (h : (0 : ℝ) ∉ [[a, b]]) :
∫ x in a..b, log x = b * log b - a * log a - b + a := by
have h' := fun x (hx : x ∈ [[a, b]]) => ne_of_mem_of_not_mem hx h
have heq := fun x hx => mul_inv_cancel (h' x hx)
convert integral_mul_deriv_eq_deriv_mul (fun x hx => hasDerivAt_log (h' x hx))
(fun x _ => hasDerivAt_id x) (continuousOn_inv₀.mono <|
subset_compl_singleton_iff.mpr h).intervalIntegrable
continuousOn_const.intervalIntegrable using 1 <;>
simp [integral_congr heq, mul_comm, ← sub_add]
#align integral_log integral_log
@[simp]
theorem integral_log_of_pos (ha : 0 < a) (hb : 0 < b) :
∫ x in a..b, log x = b * log b - a * log a - b + a :=
integral_log <| not_mem_uIcc_of_lt ha hb
#align integral_log_of_pos integral_log_of_pos
@[simp]
theorem integral_log_of_neg (ha : a < 0) (hb : b < 0) :
∫ x in a..b, log x = b * log b - a * log a - b + a :=
integral_log <| not_mem_uIcc_of_gt ha hb
#align integral_log_of_neg integral_log_of_neg
@[simp]
theorem integral_sin : ∫ x in a..b, sin x = cos a - cos b := by
rw [integral_deriv_eq_sub' fun x => -cos x]
· ring
· norm_num
· simp only [differentiableAt_neg_iff, differentiableAt_cos, implies_true]
· exact continuousOn_sin
#align integral_sin integral_sin
@[simp]
theorem integral_cos : ∫ x in a..b, cos x = sin b - sin a := by
rw [integral_deriv_eq_sub']
· norm_num
· simp only [differentiableAt_sin, implies_true]
· exact continuousOn_cos
#align integral_cos integral_cos
theorem integral_cos_mul_complex {z : ℂ} (hz : z ≠ 0) (a b : ℝ) :
(∫ x in a..b, Complex.cos (z * x)) = Complex.sin (z * b) / z - Complex.sin (z * a) / z := by
apply integral_eq_sub_of_hasDerivAt
swap
· apply Continuous.intervalIntegrable
exact Complex.continuous_cos.comp (continuous_const.mul Complex.continuous_ofReal)
intro x _
have a := Complex.hasDerivAt_sin (↑x * z)
have b : HasDerivAt (fun y => y * z : ℂ → ℂ) z ↑x := hasDerivAt_mul_const _
have c : HasDerivAt (fun y : ℂ => Complex.sin (y * z)) _ ↑x := HasDerivAt.comp (𝕜 := ℂ) x a b
have d := HasDerivAt.comp_ofReal (c.div_const z)
simp only [mul_comm] at d
convert d using 1
conv_rhs => arg 1; rw [mul_comm]
rw [mul_div_cancel_right₀ _ hz]
#align integral_cos_mul_complex integral_cos_mul_complex
theorem integral_cos_sq_sub_sin_sq :
∫ x in a..b, cos x ^ 2 - sin x ^ 2 = sin b * cos b - sin a * cos a := by
simpa only [sq, sub_eq_add_neg, neg_mul_eq_mul_neg] using
integral_deriv_mul_eq_sub (fun x _ => hasDerivAt_sin x) (fun x _ => hasDerivAt_cos x)
continuousOn_cos.intervalIntegrable continuousOn_sin.neg.intervalIntegrable
#align integral_cos_sq_sub_sin_sq integral_cos_sq_sub_sin_sq
theorem integral_one_div_one_add_sq :
(∫ x : ℝ in a..b, ↑1 / (↑1 + x ^ 2)) = arctan b - arctan a := by
refine integral_deriv_eq_sub' _ Real.deriv_arctan (fun _ _ => differentiableAt_arctan _)
(continuous_const.div ?_ fun x => ?_).continuousOn
· continuity
· nlinarith
#align integral_one_div_one_add_sq integral_one_div_one_add_sq
@[simp]
theorem integral_inv_one_add_sq : (∫ x : ℝ in a..b, (↑1 + x ^ 2)⁻¹) = arctan b - arctan a := by
simp only [← one_div, integral_one_div_one_add_sq]
#align integral_inv_one_add_sq integral_inv_one_add_sq
section RpowCpow
open Complex
theorem integral_mul_cpow_one_add_sq {t : ℂ} (ht : t ≠ -1) :
(∫ x : ℝ in a..b, (x : ℂ) * ((1:ℂ) + ↑x ^ 2) ^ t) =
((1:ℂ) + (b:ℂ) ^ 2) ^ (t + 1) / (2 * (t + ↑1)) -
((1:ℂ) + (a:ℂ) ^ 2) ^ (t + 1) / (2 * (t + ↑1)) := by
have : t + 1 ≠ 0 := by contrapose! ht; rwa [add_eq_zero_iff_eq_neg] at ht
apply integral_eq_sub_of_hasDerivAt
· intro x _
have f : HasDerivAt (fun y : ℂ => 1 + y ^ 2) (2 * x : ℂ) x := by
convert (hasDerivAt_pow 2 (x : ℂ)).const_add 1
simp
have g :
∀ {z : ℂ}, 0 < z.re → HasDerivAt (fun z => z ^ (t + 1) / (2 * (t + 1))) (z ^ t / 2) z := by
intro z hz
convert (HasDerivAt.cpow_const (c := t + 1) (hasDerivAt_id _)
(Or.inl hz)).div_const (2 * (t + 1)) using 1
field_simp
ring
convert (HasDerivAt.comp (↑x) (g _) f).comp_ofReal using 1
· field_simp; ring
· exact mod_cast add_pos_of_pos_of_nonneg zero_lt_one (sq_nonneg x)
· apply Continuous.intervalIntegrable
refine continuous_ofReal.mul ?_
apply Continuous.cpow
· exact continuous_const.add (continuous_ofReal.pow 2)
· exact continuous_const
· intro a
norm_cast
exact ofReal_mem_slitPlane.2 <| add_pos_of_pos_of_nonneg one_pos <| sq_nonneg a
#align integral_mul_cpow_one_add_sq integral_mul_cpow_one_add_sq
| Mathlib/Analysis/SpecialFunctions/Integrals.lean | 618 | 634 | theorem integral_mul_rpow_one_add_sq {t : ℝ} (ht : t ≠ -1) :
(∫ x : ℝ in a..b, x * (↑1 + x ^ 2) ^ t) =
(↑1 + b ^ 2) ^ (t + 1) / (↑2 * (t + ↑1)) - (↑1 + a ^ 2) ^ (t + 1) / (↑2 * (t + ↑1)) := by |
have : ∀ x s : ℝ, (((↑1 + x ^ 2) ^ s : ℝ) : ℂ) = (1 + (x : ℂ) ^ 2) ^ (s:ℂ) := by
intro x s
norm_cast
rw [ofReal_cpow, ofReal_add, ofReal_pow, ofReal_one]
exact add_nonneg zero_le_one (sq_nonneg x)
rw [← ofReal_inj]
convert integral_mul_cpow_one_add_sq (_ : (t : ℂ) ≠ -1)
· rw [← intervalIntegral.integral_ofReal]
congr with x : 1
rw [ofReal_mul, this x t]
· simp_rw [ofReal_sub, ofReal_div, this a (t + 1), this b (t + 1)]
push_cast; rfl
· rw [← ofReal_one, ← ofReal_neg, Ne, ofReal_inj]
exact ht
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Alexander Bentkamp, Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.Prod
import Mathlib.SetTheory.Cardinal.Basic
import Mathlib.Tactic.FinCases
import Mathlib.Tactic.LinearCombination
import Mathlib.Lean.Expr.ExtraRecognizers
import Mathlib.Data.Set.Subsingleton
#align_import linear_algebra.linear_independent from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Linear independence
This file defines linear independence in a module or vector space.
It is inspired by Isabelle/HOL's linear algebra, and hence indirectly by HOL Light.
We define `LinearIndependent R v` as `ker (Finsupp.total ι M R v) = ⊥`. Here `Finsupp.total` is the
linear map sending a function `f : ι →₀ R` with finite support to the linear combination of vectors
from `v` with these coefficients. Then we prove that several other statements are equivalent to this
one, including injectivity of `Finsupp.total ι M R v` and some versions with explicitly written
linear combinations.
## 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.
* `LinearIndependent R v` states that the elements of the family `v` are linearly independent.
* `LinearIndependent.repr hv x` returns the linear combination representing `x : span R (range v)`
on the linearly independent vectors `v`, given `hv : LinearIndependent R v`
(using classical choice). `LinearIndependent.repr hv` is provided as a linear map.
## Main statements
We prove several specialized tests for linear independence of families of vectors and of sets of
vectors.
* `Fintype.linearIndependent_iff`: if `ι` is a finite type, then any function `f : ι → R` has
finite support, so we can reformulate the statement using `∑ i : ι, f i • v i` instead of a sum
over an auxiliary `s : Finset ι`;
* `linearIndependent_empty_type`: a family indexed by an empty type is linearly independent;
* `linearIndependent_unique_iff`: if `ι` is a singleton, then `LinearIndependent K v` is
equivalent to `v default ≠ 0`;
* `linearIndependent_option`, `linearIndependent_sum`, `linearIndependent_fin_cons`,
`linearIndependent_fin_succ`: type-specific tests for linear independence of families of vector
fields;
* `linearIndependent_insert`, `linearIndependent_union`, `linearIndependent_pair`,
`linearIndependent_singleton`: linear independence tests for set operations.
In many cases we additionally provide dot-style operations (e.g., `LinearIndependent.union`) to
make the linear independence tests usable as `hv.insert ha` etc.
We also prove that, when working over a division ring,
any family of vectors includes a linear independent subfamily spanning the same subspace.
## Implementation notes
We use families instead of sets because it allows us to say that two identical vectors are linearly
dependent.
If you want to use sets, use the family `(fun x ↦ x : s → M)` given a set `s : Set M`. The lemmas
`LinearIndependent.to_subtype_range` and `LinearIndependent.of_subtype_range` connect those two
worlds.
## Tags
linearly dependent, linear dependence, linearly independent, linear independence
-/
noncomputable section
open Function Set Submodule
open Cardinal
universe u' u
variable {ι : Type u'} {ι' : Type*} {R : Type*} {K : Type*}
variable {M : Type*} {M' M'' : Type*} {V : Type u} {V' : Type*}
section Module
variable {v : ι → M}
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid M'] [AddCommMonoid M'']
variable [Module R M] [Module R M'] [Module R M'']
variable {a b : R} {x y : M}
variable (R) (v)
/-- `LinearIndependent R v` states the family of vectors `v` is linearly independent over `R`. -/
def LinearIndependent : Prop :=
LinearMap.ker (Finsupp.total ι M R v) = ⊥
#align linear_independent LinearIndependent
open Lean PrettyPrinter.Delaborator SubExpr in
/-- Delaborator for `LinearIndependent` that suggests pretty printing with type hints
in case the family of vectors is over a `Set`.
Type hints look like `LinearIndependent fun (v : ↑s) => ↑v` or `LinearIndependent (ι := ↑s) f`,
depending on whether the family is a lambda expression or not. -/
@[delab app.LinearIndependent]
def delabLinearIndependent : Delab :=
whenPPOption getPPNotation <|
whenNotPPOption getPPAnalysisSkip <|
withOptionAtCurrPos `pp.analysis.skip true do
let e ← getExpr
guard <| e.isAppOfArity ``LinearIndependent 7
let some _ := (e.getArg! 0).coeTypeSet? | failure
let optionsPerPos ← if (e.getArg! 3).isLambda then
withNaryArg 3 do return (← read).optionsPerPos.setBool (← getPos) pp.funBinderTypes.name true
else
withNaryArg 0 do return (← read).optionsPerPos.setBool (← getPos) `pp.analysis.namedArg true
withTheReader Context ({· with optionsPerPos}) delab
variable {R} {v}
theorem linearIndependent_iff :
LinearIndependent R v ↔ ∀ l, Finsupp.total ι M R v l = 0 → l = 0 := by
simp [LinearIndependent, LinearMap.ker_eq_bot']
#align linear_independent_iff linearIndependent_iff
theorem linearIndependent_iff' :
LinearIndependent R v ↔
∀ s : Finset ι, ∀ g : ι → R, ∑ i ∈ s, g i • v i = 0 → ∀ i ∈ s, g i = 0 :=
linearIndependent_iff.trans
⟨fun hf s g hg i his =>
have h :=
hf (∑ i ∈ s, Finsupp.single i (g i)) <| by
simpa only [map_sum, Finsupp.total_single] using hg
calc
g i = (Finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (Finsupp.single i (g i)) := by
{ rw [Finsupp.lapply_apply, Finsupp.single_eq_same] }
_ = ∑ j ∈ s, (Finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (Finsupp.single j (g j)) :=
Eq.symm <|
Finset.sum_eq_single i
(fun j _hjs hji => by rw [Finsupp.lapply_apply, Finsupp.single_eq_of_ne hji])
fun hnis => hnis.elim his
_ = (∑ j ∈ s, Finsupp.single j (g j)) i := (map_sum ..).symm
_ = 0 := DFunLike.ext_iff.1 h i,
fun hf l hl =>
Finsupp.ext fun i =>
_root_.by_contradiction fun hni => hni <| hf _ _ hl _ <| Finsupp.mem_support_iff.2 hni⟩
#align linear_independent_iff' linearIndependent_iff'
theorem linearIndependent_iff'' :
LinearIndependent R v ↔
∀ (s : Finset ι) (g : ι → R), (∀ i ∉ s, g i = 0) →
∑ i ∈ s, g i • v i = 0 → ∀ i, g i = 0 := by
classical
exact linearIndependent_iff'.trans
⟨fun H s g hg hv i => if his : i ∈ s then H s g hv i his else hg i his, fun H s g hg i hi => by
convert
H s (fun j => if j ∈ s then g j else 0) (fun j hj => if_neg hj)
(by simp_rw [ite_smul, zero_smul, Finset.sum_extend_by_zero, hg]) i
exact (if_pos hi).symm⟩
#align linear_independent_iff'' linearIndependent_iff''
theorem not_linearIndependent_iff :
¬LinearIndependent R v ↔
∃ s : Finset ι, ∃ g : ι → R, ∑ i ∈ s, g i • v i = 0 ∧ ∃ i ∈ s, g i ≠ 0 := by
rw [linearIndependent_iff']
simp only [exists_prop, not_forall]
#align not_linear_independent_iff not_linearIndependent_iff
theorem Fintype.linearIndependent_iff [Fintype ι] :
LinearIndependent R v ↔ ∀ g : ι → R, ∑ i, g i • v i = 0 → ∀ i, g i = 0 := by
refine
⟨fun H g => by simpa using linearIndependent_iff'.1 H Finset.univ g, fun H =>
linearIndependent_iff''.2 fun s g hg hs i => H _ ?_ _⟩
rw [← hs]
refine (Finset.sum_subset (Finset.subset_univ _) fun i _ hi => ?_).symm
rw [hg i hi, zero_smul]
#align fintype.linear_independent_iff Fintype.linearIndependent_iff
/-- A finite family of vectors `v i` is linear independent iff the linear map that sends
`c : ι → R` to `∑ i, c i • v i` has the trivial kernel. -/
theorem Fintype.linearIndependent_iff' [Fintype ι] [DecidableEq ι] :
LinearIndependent R v ↔
LinearMap.ker (LinearMap.lsum R (fun _ ↦ R) ℕ fun i ↦ LinearMap.id.smulRight (v i)) = ⊥ := by
simp [Fintype.linearIndependent_iff, LinearMap.ker_eq_bot', funext_iff]
#align fintype.linear_independent_iff' Fintype.linearIndependent_iff'
theorem Fintype.not_linearIndependent_iff [Fintype ι] :
¬LinearIndependent R v ↔ ∃ g : ι → R, ∑ i, g i • v i = 0 ∧ ∃ i, g i ≠ 0 := by
simpa using not_iff_not.2 Fintype.linearIndependent_iff
#align fintype.not_linear_independent_iff Fintype.not_linearIndependent_iff
theorem linearIndependent_empty_type [IsEmpty ι] : LinearIndependent R v :=
linearIndependent_iff.mpr fun v _hv => Subsingleton.elim v 0
#align linear_independent_empty_type linearIndependent_empty_type
theorem LinearIndependent.ne_zero [Nontrivial R] (i : ι) (hv : LinearIndependent R v) : v i ≠ 0 :=
fun h =>
zero_ne_one' R <|
Eq.symm
(by
suffices (Finsupp.single i 1 : ι →₀ R) i = 0 by simpa
rw [linearIndependent_iff.1 hv (Finsupp.single i 1)]
· simp
· simp [h])
#align linear_independent.ne_zero LinearIndependent.ne_zero
lemma LinearIndependent.eq_zero_of_pair {x y : M} (h : LinearIndependent R ![x, y])
{s t : R} (h' : s • x + t • y = 0) : s = 0 ∧ t = 0 := by
have := linearIndependent_iff'.1 h Finset.univ ![s, t]
simp only [Fin.sum_univ_two, Matrix.cons_val_zero, Matrix.cons_val_one, Matrix.head_cons, h',
Finset.mem_univ, forall_true_left] at this
exact ⟨this 0, this 1⟩
/-- Also see `LinearIndependent.pair_iff'` for a simpler version over fields. -/
lemma LinearIndependent.pair_iff {x y : M} :
LinearIndependent R ![x, y] ↔ ∀ (s t : R), s • x + t • y = 0 → s = 0 ∧ t = 0 := by
refine ⟨fun h s t hst ↦ h.eq_zero_of_pair hst, fun h ↦ ?_⟩
apply Fintype.linearIndependent_iff.2
intro g hg
simp only [Fin.sum_univ_two, Matrix.cons_val_zero, Matrix.cons_val_one, Matrix.head_cons] at hg
intro i
fin_cases i
exacts [(h _ _ hg).1, (h _ _ hg).2]
/-- A subfamily of a linearly independent family (i.e., a composition with an injective map) is a
linearly independent family. -/
theorem LinearIndependent.comp (h : LinearIndependent R v) (f : ι' → ι) (hf : Injective f) :
LinearIndependent R (v ∘ f) := by
rw [linearIndependent_iff, Finsupp.total_comp]
intro l hl
have h_map_domain : ∀ x, (Finsupp.mapDomain f l) (f x) = 0 := by
rw [linearIndependent_iff.1 h (Finsupp.mapDomain f l) hl]; simp
ext x
convert h_map_domain x
rw [Finsupp.mapDomain_apply hf]
#align linear_independent.comp LinearIndependent.comp
/-- A family is linearly independent if and only if all of its finite subfamily is
linearly independent. -/
theorem linearIndependent_iff_finset_linearIndependent :
LinearIndependent R v ↔ ∀ (s : Finset ι), LinearIndependent R (v ∘ (Subtype.val : s → ι)) :=
⟨fun H _ ↦ H.comp _ Subtype.val_injective, fun H ↦ linearIndependent_iff'.2 fun s g hg i hi ↦
Fintype.linearIndependent_iff.1 (H s) (g ∘ Subtype.val)
(hg ▸ Finset.sum_attach s fun j ↦ g j • v j) ⟨i, hi⟩⟩
theorem LinearIndependent.coe_range (i : LinearIndependent R v) :
LinearIndependent R ((↑) : range v → M) := by simpa using i.comp _ (rangeSplitting_injective v)
#align linear_independent.coe_range LinearIndependent.coe_range
/-- If `v` is a linearly independent family of vectors and the kernel of a linear map `f` is
disjoint with the submodule spanned by the vectors of `v`, then `f ∘ v` is a linearly independent
family of vectors. See also `LinearIndependent.map'` for a special case assuming `ker f = ⊥`. -/
theorem LinearIndependent.map (hv : LinearIndependent R v) {f : M →ₗ[R] M'}
(hf_inj : Disjoint (span R (range v)) (LinearMap.ker f)) : LinearIndependent R (f ∘ v) := by
rw [disjoint_iff_inf_le, ← Set.image_univ, Finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap, map_le_iff_le_comap, comap_bot, Finsupp.supported_univ, top_inf_eq]
at hf_inj
unfold LinearIndependent at hv ⊢
rw [hv, le_bot_iff] at hf_inj
haveI : Inhabited M := ⟨0⟩
rw [Finsupp.total_comp, Finsupp.lmapDomain_total _ _ f, LinearMap.ker_comp,
hf_inj]
exact fun _ => rfl
#align linear_independent.map LinearIndependent.map
/-- If `v` is an injective family of vectors such that `f ∘ v` is linearly independent, then `v`
spans a submodule disjoint from the kernel of `f` -/
theorem Submodule.range_ker_disjoint {f : M →ₗ[R] M'}
(hv : LinearIndependent R (f ∘ v)) :
Disjoint (span R (range v)) (LinearMap.ker f) := by
rw [LinearIndependent, Finsupp.total_comp, Finsupp.lmapDomain_total R _ f (fun _ ↦ rfl),
LinearMap.ker_comp] at hv
rw [disjoint_iff_inf_le, ← Set.image_univ, Finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap, hv, inf_bot_eq, map_bot]
/-- An injective linear map sends linearly independent families of vectors to linearly independent
families of vectors. See also `LinearIndependent.map` for a more general statement. -/
theorem LinearIndependent.map' (hv : LinearIndependent R v) (f : M →ₗ[R] M')
(hf_inj : LinearMap.ker f = ⊥) : LinearIndependent R (f ∘ v) :=
hv.map <| by simp [hf_inj]
#align linear_independent.map' LinearIndependent.map'
/-- If `M / R` and `M' / R'` are modules, `i : R' → R` is a map, `j : M →+ M'` is a monoid map,
such that they send non-zero elements to non-zero elements, and compatible with the scalar
multiplications on `M` and `M'`, then `j` sends linearly independent families of vectors to
linearly independent families of vectors. As a special case, taking `R = R'`
it is `LinearIndependent.map'`. -/
theorem LinearIndependent.map_of_injective_injective {R' : Type*} {M' : Type*}
[Semiring R'] [AddCommMonoid M'] [Module R' M'] (hv : LinearIndependent R v)
(i : R' → R) (j : M →+ M') (hi : ∀ r, i r = 0 → r = 0) (hj : ∀ m, j m = 0 → m = 0)
(hc : ∀ (r : R') (m : M), j (i r • m) = r • j m) : LinearIndependent R' (j ∘ v) := by
rw [linearIndependent_iff'] at hv ⊢
intro S r' H s hs
simp_rw [comp_apply, ← hc, ← map_sum] at H
exact hi _ <| hv _ _ (hj _ H) s hs
/-- If `M / R` and `M' / R'` are modules, `i : R → R'` is a surjective map which maps zero to zero,
`j : M →+ M'` is a monoid map which sends non-zero elements to non-zero elements, such that the
scalar multiplications on `M` and `M'` are compatible, then `j` sends linearly independent families
of vectors to linearly independent families of vectors. As a special case, taking `R = R'`
it is `LinearIndependent.map'`. -/
theorem LinearIndependent.map_of_surjective_injective {R' : Type*} {M' : Type*}
[Semiring R'] [AddCommMonoid M'] [Module R' M'] (hv : LinearIndependent R v)
(i : ZeroHom R R') (j : M →+ M') (hi : Surjective i) (hj : ∀ m, j m = 0 → m = 0)
(hc : ∀ (r : R) (m : M), j (r • m) = i r • j m) : LinearIndependent R' (j ∘ v) := by
obtain ⟨i', hi'⟩ := hi.hasRightInverse
refine hv.map_of_injective_injective i' j (fun _ h ↦ ?_) hj fun r m ↦ ?_
· apply_fun i at h
rwa [hi', i.map_zero] at h
rw [hc (i' r) m, hi']
/-- If the image of a family of vectors under a linear map is linearly independent, then so is
the original family. -/
theorem LinearIndependent.of_comp (f : M →ₗ[R] M') (hfv : LinearIndependent R (f ∘ v)) :
LinearIndependent R v :=
linearIndependent_iff'.2 fun s g hg i his =>
have : (∑ i ∈ s, g i • f (v i)) = 0 := by
simp_rw [← map_smul, ← map_sum, hg, f.map_zero]
linearIndependent_iff'.1 hfv s g this i his
#align linear_independent.of_comp LinearIndependent.of_comp
/-- If `f` is an injective linear map, then the family `f ∘ v` is linearly independent
if and only if the family `v` is linearly independent. -/
protected theorem LinearMap.linearIndependent_iff (f : M →ₗ[R] M') (hf_inj : LinearMap.ker f = ⊥) :
LinearIndependent R (f ∘ v) ↔ LinearIndependent R v :=
⟨fun h => h.of_comp f, fun h => h.map <| by simp only [hf_inj, disjoint_bot_right]⟩
#align linear_map.linear_independent_iff LinearMap.linearIndependent_iff
@[nontriviality]
theorem linearIndependent_of_subsingleton [Subsingleton R] : LinearIndependent R v :=
linearIndependent_iff.2 fun _l _hl => Subsingleton.elim _ _
#align linear_independent_of_subsingleton linearIndependent_of_subsingleton
theorem linearIndependent_equiv (e : ι ≃ ι') {f : ι' → M} :
LinearIndependent R (f ∘ e) ↔ LinearIndependent R f :=
⟨fun h => Function.comp_id f ▸ e.self_comp_symm ▸ h.comp _ e.symm.injective, fun h =>
h.comp _ e.injective⟩
#align linear_independent_equiv linearIndependent_equiv
theorem linearIndependent_equiv' (e : ι ≃ ι') {f : ι' → M} {g : ι → M} (h : f ∘ e = g) :
LinearIndependent R g ↔ LinearIndependent R f :=
h ▸ linearIndependent_equiv e
#align linear_independent_equiv' linearIndependent_equiv'
theorem linearIndependent_subtype_range {ι} {f : ι → M} (hf : Injective f) :
LinearIndependent R ((↑) : range f → M) ↔ LinearIndependent R f :=
Iff.symm <| linearIndependent_equiv' (Equiv.ofInjective f hf) rfl
#align linear_independent_subtype_range linearIndependent_subtype_range
alias ⟨LinearIndependent.of_subtype_range, _⟩ := linearIndependent_subtype_range
#align linear_independent.of_subtype_range LinearIndependent.of_subtype_range
theorem linearIndependent_image {ι} {s : Set ι} {f : ι → M} (hf : Set.InjOn f s) :
(LinearIndependent R fun x : s => f x) ↔ LinearIndependent R fun x : f '' s => (x : M) :=
linearIndependent_equiv' (Equiv.Set.imageOfInjOn _ _ hf) rfl
#align linear_independent_image linearIndependent_image
theorem linearIndependent_span (hs : LinearIndependent R v) :
LinearIndependent R (M := span R (range v))
(fun i : ι => ⟨v i, subset_span (mem_range_self i)⟩) :=
LinearIndependent.of_comp (span R (range v)).subtype hs
#align linear_independent_span linearIndependent_span
/-- See `LinearIndependent.fin_cons` for a family of elements in a vector space. -/
theorem LinearIndependent.fin_cons' {m : ℕ} (x : M) (v : Fin m → M) (hli : LinearIndependent R v)
(x_ortho : ∀ (c : R) (y : Submodule.span R (Set.range v)), c • x + y = (0 : M) → c = 0) :
LinearIndependent R (Fin.cons x v : Fin m.succ → M) := by
rw [Fintype.linearIndependent_iff] at hli ⊢
rintro g total_eq j
simp_rw [Fin.sum_univ_succ, Fin.cons_zero, Fin.cons_succ] at total_eq
have : g 0 = 0 := by
refine x_ortho (g 0) ⟨∑ i : Fin m, g i.succ • v i, ?_⟩ total_eq
exact sum_mem fun i _ => smul_mem _ _ (subset_span ⟨i, rfl⟩)
rw [this, zero_smul, zero_add] at total_eq
exact Fin.cases this (hli _ total_eq) j
#align linear_independent.fin_cons' LinearIndependent.fin_cons'
/-- A set of linearly independent vectors in a module `M` over a semiring `K` is also linearly
independent over a subring `R` of `K`.
The implementation uses minimal assumptions about the relationship between `R`, `K` and `M`.
The version where `K` is an `R`-algebra is `LinearIndependent.restrict_scalars_algebras`.
-/
theorem LinearIndependent.restrict_scalars [Semiring K] [SMulWithZero R K] [Module K M]
[IsScalarTower R K M] (hinj : Function.Injective fun r : R => r • (1 : K))
(li : LinearIndependent K v) : LinearIndependent R v := by
refine linearIndependent_iff'.mpr fun s g hg i hi => hinj ?_
dsimp only; rw [zero_smul]
refine (linearIndependent_iff'.mp li : _) _ (g · • (1:K)) ?_ i hi
simp_rw [smul_assoc, one_smul]
exact hg
#align linear_independent.restrict_scalars LinearIndependent.restrict_scalars
/-- Every finite subset of a linearly independent set is linearly independent. -/
theorem linearIndependent_finset_map_embedding_subtype (s : Set M)
(li : LinearIndependent R ((↑) : s → M)) (t : Finset s) :
LinearIndependent R ((↑) : Finset.map (Embedding.subtype s) t → M) := by
let f : t.map (Embedding.subtype s) → s := fun x =>
⟨x.1, by
obtain ⟨x, h⟩ := x
rw [Finset.mem_map] at h
obtain ⟨a, _ha, rfl⟩ := h
simp only [Subtype.coe_prop, Embedding.coe_subtype]⟩
convert LinearIndependent.comp li f ?_
rintro ⟨x, hx⟩ ⟨y, hy⟩
rw [Finset.mem_map] at hx hy
obtain ⟨a, _ha, rfl⟩ := hx
obtain ⟨b, _hb, rfl⟩ := hy
simp only [f, imp_self, Subtype.mk_eq_mk]
#align linear_independent_finset_map_embedding_subtype linearIndependent_finset_map_embedding_subtype
/-- If every finite set of linearly independent vectors has cardinality at most `n`,
then the same is true for arbitrary sets of linearly independent vectors.
-/
theorem linearIndependent_bounded_of_finset_linearIndependent_bounded {n : ℕ}
(H : ∀ s : Finset M, (LinearIndependent R fun i : s => (i : M)) → s.card ≤ n) :
∀ s : Set M, LinearIndependent R ((↑) : s → M) → #s ≤ n := by
intro s li
apply Cardinal.card_le_of
intro t
rw [← Finset.card_map (Embedding.subtype s)]
apply H
apply linearIndependent_finset_map_embedding_subtype _ li
#align linear_independent_bounded_of_finset_linear_independent_bounded linearIndependent_bounded_of_finset_linearIndependent_bounded
section Subtype
/-! The following lemmas use the subtype defined by a set in `M` as the index set `ι`. -/
theorem linearIndependent_comp_subtype {s : Set ι} :
LinearIndependent R (v ∘ (↑) : s → M) ↔
∀ l ∈ Finsupp.supported R R s, (Finsupp.total ι M R v) l = 0 → l = 0 := by
simp only [linearIndependent_iff, (· ∘ ·), Finsupp.mem_supported, Finsupp.total_apply,
Set.subset_def, Finset.mem_coe]
constructor
· intro h l hl₁ hl₂
have := h (l.subtypeDomain s) ((Finsupp.sum_subtypeDomain_index hl₁).trans hl₂)
exact (Finsupp.subtypeDomain_eq_zero_iff hl₁).1 this
· intro h l hl
refine Finsupp.embDomain_eq_zero.1 (h (l.embDomain <| Function.Embedding.subtype s) ?_ ?_)
· suffices ∀ i hi, ¬l ⟨i, hi⟩ = 0 → i ∈ s by simpa
intros
assumption
· rwa [Finsupp.embDomain_eq_mapDomain, Finsupp.sum_mapDomain_index]
exacts [fun _ => zero_smul _ _, fun _ _ _ => add_smul _ _ _]
#align linear_independent_comp_subtype linearIndependent_comp_subtype
theorem linearDependent_comp_subtype' {s : Set ι} :
¬LinearIndependent R (v ∘ (↑) : s → M) ↔
∃ f : ι →₀ R, f ∈ Finsupp.supported R R s ∧ Finsupp.total ι M R v f = 0 ∧ f ≠ 0 := by
simp [linearIndependent_comp_subtype, and_left_comm]
#align linear_dependent_comp_subtype' linearDependent_comp_subtype'
/-- A version of `linearDependent_comp_subtype'` with `Finsupp.total` unfolded. -/
theorem linearDependent_comp_subtype {s : Set ι} :
¬LinearIndependent R (v ∘ (↑) : s → M) ↔
∃ f : ι →₀ R, f ∈ Finsupp.supported R R s ∧ ∑ i ∈ f.support, f i • v i = 0 ∧ f ≠ 0 :=
linearDependent_comp_subtype'
#align linear_dependent_comp_subtype linearDependent_comp_subtype
theorem linearIndependent_subtype {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
∀ l ∈ Finsupp.supported R R s, (Finsupp.total M M R id) l = 0 → l = 0 := by
apply linearIndependent_comp_subtype (v := id)
#align linear_independent_subtype linearIndependent_subtype
theorem linearIndependent_comp_subtype_disjoint {s : Set ι} :
LinearIndependent R (v ∘ (↑) : s → M) ↔
Disjoint (Finsupp.supported R R s) (LinearMap.ker <| Finsupp.total ι M R v) := by
rw [linearIndependent_comp_subtype, LinearMap.disjoint_ker]
#align linear_independent_comp_subtype_disjoint linearIndependent_comp_subtype_disjoint
theorem linearIndependent_subtype_disjoint {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
Disjoint (Finsupp.supported R R s) (LinearMap.ker <| Finsupp.total M M R id) := by
apply linearIndependent_comp_subtype_disjoint (v := id)
#align linear_independent_subtype_disjoint linearIndependent_subtype_disjoint
theorem linearIndependent_iff_totalOn {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
(LinearMap.ker <| Finsupp.totalOn M M R id s) = ⊥ := by
rw [Finsupp.totalOn, LinearMap.ker, LinearMap.comap_codRestrict, Submodule.map_bot, comap_bot,
LinearMap.ker_comp, linearIndependent_subtype_disjoint, disjoint_iff_inf_le, ←
map_comap_subtype, map_le_iff_le_comap, comap_bot, ker_subtype, le_bot_iff]
#align linear_independent_iff_total_on linearIndependent_iff_totalOn
theorem LinearIndependent.restrict_of_comp_subtype {s : Set ι}
(hs : LinearIndependent R (v ∘ (↑) : s → M)) : LinearIndependent R (s.restrict v) :=
hs
#align linear_independent.restrict_of_comp_subtype LinearIndependent.restrict_of_comp_subtype
variable (R M)
theorem linearIndependent_empty : LinearIndependent R (fun x => x : (∅ : Set M) → M) := by
simp [linearIndependent_subtype_disjoint]
#align linear_independent_empty linearIndependent_empty
variable {R M}
theorem LinearIndependent.mono {t s : Set M} (h : t ⊆ s) :
LinearIndependent R (fun x => x : s → M) → LinearIndependent R (fun x => x : t → M) := by
simp only [linearIndependent_subtype_disjoint]
exact Disjoint.mono_left (Finsupp.supported_mono h)
#align linear_independent.mono LinearIndependent.mono
theorem linearIndependent_of_finite (s : Set M)
(H : ∀ t ⊆ s, Set.Finite t → LinearIndependent R (fun x => x : t → M)) :
LinearIndependent R (fun x => x : s → M) :=
linearIndependent_subtype.2 fun l hl =>
linearIndependent_subtype.1 (H _ hl (Finset.finite_toSet _)) l (Subset.refl _)
#align linear_independent_of_finite linearIndependent_of_finite
theorem linearIndependent_iUnion_of_directed {η : Type*} {s : η → Set M} (hs : Directed (· ⊆ ·) s)
(h : ∀ i, LinearIndependent R (fun x => x : s i → M)) :
LinearIndependent R (fun x => x : (⋃ i, s i) → M) := by
by_cases hη : Nonempty η
· refine linearIndependent_of_finite (⋃ i, s i) fun t ht ft => ?_
rcases finite_subset_iUnion ft ht with ⟨I, fi, hI⟩
rcases hs.finset_le fi.toFinset with ⟨i, hi⟩
exact (h i).mono (Subset.trans hI <| iUnion₂_subset fun j hj => hi j (fi.mem_toFinset.2 hj))
· refine (linearIndependent_empty R M).mono (t := iUnion (s ·)) ?_
rintro _ ⟨_, ⟨i, _⟩, _⟩
exact hη ⟨i⟩
#align linear_independent_Union_of_directed linearIndependent_iUnion_of_directed
theorem linearIndependent_sUnion_of_directed {s : Set (Set M)} (hs : DirectedOn (· ⊆ ·) s)
(h : ∀ a ∈ s, LinearIndependent R ((↑) : ((a : Set M) : Type _) → M)) :
LinearIndependent R (fun x => x : ⋃₀ s → M) := by
rw [sUnion_eq_iUnion];
exact linearIndependent_iUnion_of_directed hs.directed_val (by simpa using h)
#align linear_independent_sUnion_of_directed linearIndependent_sUnion_of_directed
theorem linearIndependent_biUnion_of_directed {η} {s : Set η} {t : η → Set M}
(hs : DirectedOn (t ⁻¹'o (· ⊆ ·)) s) (h : ∀ a ∈ s, LinearIndependent R (fun x => x : t a → M)) :
LinearIndependent R (fun x => x : (⋃ a ∈ s, t a) → M) := by
rw [biUnion_eq_iUnion]
exact
linearIndependent_iUnion_of_directed (directed_comp.2 <| hs.directed_val) (by simpa using h)
#align linear_independent_bUnion_of_directed linearIndependent_biUnion_of_directed
end Subtype
end Module
/-! ### Properties which require `Ring R` -/
section Module
variable {v : ι → M}
variable [Ring R] [AddCommGroup M] [AddCommGroup M'] [AddCommGroup M'']
variable [Module R M] [Module R M'] [Module R M'']
variable {a b : R} {x y : M}
theorem linearIndependent_iff_injective_total :
LinearIndependent R v ↔ Function.Injective (Finsupp.total ι M R v) :=
linearIndependent_iff.trans
(injective_iff_map_eq_zero (Finsupp.total ι M R v).toAddMonoidHom).symm
#align linear_independent_iff_injective_total linearIndependent_iff_injective_total
alias ⟨LinearIndependent.injective_total, _⟩ := linearIndependent_iff_injective_total
#align linear_independent.injective_total LinearIndependent.injective_total
theorem LinearIndependent.injective [Nontrivial R] (hv : LinearIndependent R v) : Injective v := by
intro i j hij
let l : ι →₀ R := Finsupp.single i (1 : R) - Finsupp.single j 1
have h_total : Finsupp.total ι M R v l = 0 := by
simp_rw [l, LinearMap.map_sub, Finsupp.total_apply]
simp [hij]
have h_single_eq : Finsupp.single i (1 : R) = Finsupp.single j 1 := by
rw [linearIndependent_iff] at hv
simp [eq_add_of_sub_eq' (hv l h_total)]
simpa [Finsupp.single_eq_single_iff] using h_single_eq
#align linear_independent.injective LinearIndependent.injective
theorem LinearIndependent.to_subtype_range {ι} {f : ι → M} (hf : LinearIndependent R f) :
LinearIndependent R ((↑) : range f → M) := by
nontriviality R
exact (linearIndependent_subtype_range hf.injective).2 hf
#align linear_independent.to_subtype_range LinearIndependent.to_subtype_range
theorem LinearIndependent.to_subtype_range' {ι} {f : ι → M} (hf : LinearIndependent R f) {t}
(ht : range f = t) : LinearIndependent R ((↑) : t → M) :=
ht ▸ hf.to_subtype_range
#align linear_independent.to_subtype_range' LinearIndependent.to_subtype_range'
theorem LinearIndependent.image_of_comp {ι ι'} (s : Set ι) (f : ι → ι') (g : ι' → M)
(hs : LinearIndependent R fun x : s => g (f x)) :
LinearIndependent R fun x : f '' s => g x := by
nontriviality R
have : InjOn f s := injOn_iff_injective.2 hs.injective.of_comp
exact (linearIndependent_equiv' (Equiv.Set.imageOfInjOn f s this) rfl).1 hs
#align linear_independent.image_of_comp LinearIndependent.image_of_comp
theorem LinearIndependent.image {ι} {s : Set ι} {f : ι → M}
(hs : LinearIndependent R fun x : s => f x) :
LinearIndependent R fun x : f '' s => (x : M) := by
convert LinearIndependent.image_of_comp s f id hs
#align linear_independent.image LinearIndependent.image
theorem LinearIndependent.group_smul {G : Type*} [hG : Group G] [DistribMulAction G R]
[DistribMulAction G M] [IsScalarTower G R M] [SMulCommClass G R M] {v : ι → M}
(hv : LinearIndependent R v) (w : ι → G) : LinearIndependent R (w • v) := by
rw [linearIndependent_iff''] at hv ⊢
intro s g hgs hsum i
refine (smul_eq_zero_iff_eq (w i)).1 ?_
refine hv s (fun i => w i • g i) (fun i hi => ?_) ?_ i
· dsimp only
exact (hgs i hi).symm ▸ smul_zero _
· rw [← hsum, Finset.sum_congr rfl _]
intros
dsimp
rw [smul_assoc, smul_comm]
#align linear_independent.group_smul LinearIndependent.group_smul
-- This lemma cannot be proved with `LinearIndependent.group_smul` since the action of
-- `Rˣ` on `R` is not commutative.
theorem LinearIndependent.units_smul {v : ι → M} (hv : LinearIndependent R v) (w : ι → Rˣ) :
LinearIndependent R (w • v) := by
rw [linearIndependent_iff''] at hv ⊢
intro s g hgs hsum i
rw [← (w i).mul_left_eq_zero]
refine hv s (fun i => g i • (w i : R)) (fun i hi => ?_) ?_ i
· dsimp only
exact (hgs i hi).symm ▸ zero_smul _ _
· rw [← hsum, Finset.sum_congr rfl _]
intros
erw [Pi.smul_apply, smul_assoc]
rfl
#align linear_independent.units_smul LinearIndependent.units_smul
lemma LinearIndependent.eq_of_pair {x y : M} (h : LinearIndependent R ![x, y])
{s t s' t' : R} (h' : s • x + t • y = s' • x + t' • y) : s = s' ∧ t = t' := by
have : (s - s') • x + (t - t') • y = 0 := by
rw [← sub_eq_zero_of_eq h', ← sub_eq_zero]
simp only [sub_smul]
abel
simpa [sub_eq_zero] using h.eq_zero_of_pair this
lemma LinearIndependent.eq_zero_of_pair' {x y : M} (h : LinearIndependent R ![x, y])
{s t : R} (h' : s • x = t • y) : s = 0 ∧ t = 0 := by
suffices H : s = 0 ∧ 0 = t from ⟨H.1, H.2.symm⟩
exact h.eq_of_pair (by simpa using h')
/-- If two vectors `x` and `y` are linearly independent, so are their linear combinations
`a x + b y` and `c x + d y` provided the determinant `a * d - b * c` is nonzero. -/
lemma LinearIndependent.linear_combination_pair_of_det_ne_zero {R M : Type*} [CommRing R]
[NoZeroDivisors R] [AddCommGroup M] [Module R M]
{x y : M} (h : LinearIndependent R ![x, y])
{a b c d : R} (h' : a * d - b * c ≠ 0) :
LinearIndependent R ![a • x + b • y, c • x + d • y] := by
apply LinearIndependent.pair_iff.2 (fun s t hst ↦ ?_)
have H : (s * a + t * c) • x + (s * b + t * d) • y = 0 := by
convert hst using 1
simp only [_root_.add_smul, smul_add, smul_smul]
abel
have I1 : s * a + t * c = 0 := (h.eq_zero_of_pair H).1
have I2 : s * b + t * d = 0 := (h.eq_zero_of_pair H).2
have J1 : (a * d - b * c) * s = 0 := by linear_combination d * I1 - c * I2
have J2 : (a * d - b * c) * t = 0 := by linear_combination -b * I1 + a * I2
exact ⟨by simpa [h'] using mul_eq_zero.1 J1, by simpa [h'] using mul_eq_zero.1 J2⟩
section Maximal
universe v w
/--
A linearly independent family is maximal if there is no strictly larger linearly independent family.
-/
@[nolint unusedArguments]
def LinearIndependent.Maximal {ι : Type w} {R : Type u} [Semiring R] {M : Type v} [AddCommMonoid M]
[Module R M] {v : ι → M} (_i : LinearIndependent R v) : Prop :=
∀ (s : Set M) (_i' : LinearIndependent R ((↑) : s → M)) (_h : range v ≤ s), range v = s
#align linear_independent.maximal LinearIndependent.Maximal
/-- An alternative characterization of a maximal linearly independent family,
quantifying over types (in the same universe as `M`) into which the indexing family injects.
-/
theorem LinearIndependent.maximal_iff {ι : Type w} {R : Type u} [Ring R] [Nontrivial R] {M : Type v}
[AddCommGroup M] [Module R M] {v : ι → M} (i : LinearIndependent R v) :
i.Maximal ↔
∀ (κ : Type v) (w : κ → M) (_i' : LinearIndependent R w) (j : ι → κ) (_h : w ∘ j = v),
Surjective j := by
constructor
· rintro p κ w i' j rfl
specialize p (range w) i'.coe_range (range_comp_subset_range _ _)
rw [range_comp, ← image_univ (f := w)] at p
exact range_iff_surjective.mp (image_injective.mpr i'.injective p)
· intro p w i' h
specialize
p w ((↑) : w → M) i' (fun i => ⟨v i, range_subset_iff.mp h i⟩)
(by
ext
simp)
have q := congr_arg (fun s => ((↑) : w → M) '' s) p.range_eq
dsimp at q
rw [← image_univ, image_image] at q
simpa using q
#align linear_independent.maximal_iff LinearIndependent.maximal_iff
end Maximal
/-- Linear independent families are injective, even if you multiply either side. -/
theorem LinearIndependent.eq_of_smul_apply_eq_smul_apply {M : Type*} [AddCommGroup M] [Module R M]
{v : ι → M} (li : LinearIndependent R v) (c d : R) (i j : ι) (hc : c ≠ 0)
(h : c • v i = d • v j) : i = j := by
let l : ι →₀ R := Finsupp.single i c - Finsupp.single j d
have h_total : Finsupp.total ι M R v l = 0 := by
simp_rw [l, LinearMap.map_sub, Finsupp.total_apply]
simp [h]
have h_single_eq : Finsupp.single i c = Finsupp.single j d := by
rw [linearIndependent_iff] at li
simp [eq_add_of_sub_eq' (li l h_total)]
rcases (Finsupp.single_eq_single_iff ..).mp h_single_eq with (⟨H, _⟩ | ⟨hc, _⟩)
· exact H
· contradiction
#align linear_independent.eq_of_smul_apply_eq_smul_apply LinearIndependent.eq_of_smul_apply_eq_smul_apply
section Subtype
/-! The following lemmas use the subtype defined by a set in `M` as the index set `ι`. -/
theorem LinearIndependent.disjoint_span_image (hv : LinearIndependent R v) {s t : Set ι}
(hs : Disjoint s t) : Disjoint (Submodule.span R <| v '' s) (Submodule.span R <| v '' t) := by
simp only [disjoint_def, Finsupp.mem_span_image_iff_total]
rintro _ ⟨l₁, hl₁, rfl⟩ ⟨l₂, hl₂, H⟩
rw [hv.injective_total.eq_iff] at H; subst l₂
have : l₁ = 0 := Submodule.disjoint_def.mp (Finsupp.disjoint_supported_supported hs) _ hl₁ hl₂
simp [this]
#align linear_independent.disjoint_span_image LinearIndependent.disjoint_span_image
theorem LinearIndependent.not_mem_span_image [Nontrivial R] (hv : LinearIndependent R v) {s : Set ι}
{x : ι} (h : x ∉ s) : v x ∉ Submodule.span R (v '' s) := by
have h' : v x ∈ Submodule.span R (v '' {x}) := by
rw [Set.image_singleton]
exact mem_span_singleton_self (v x)
intro w
apply LinearIndependent.ne_zero x hv
refine disjoint_def.1 (hv.disjoint_span_image ?_) (v x) h' w
simpa using h
#align linear_independent.not_mem_span_image LinearIndependent.not_mem_span_image
theorem LinearIndependent.total_ne_of_not_mem_support [Nontrivial R] (hv : LinearIndependent R v)
{x : ι} (f : ι →₀ R) (h : x ∉ f.support) : Finsupp.total ι M R v f ≠ v x := by
replace h : x ∉ (f.support : Set ι) := h
have p := hv.not_mem_span_image h
intro w
rw [← w] at p
rw [Finsupp.span_image_eq_map_total] at p
simp only [not_exists, not_and, mem_map] at p -- Porting note: `mem_map` isn't currently triggered
exact p f (f.mem_supported_support R) rfl
#align linear_independent.total_ne_of_not_mem_support LinearIndependent.total_ne_of_not_mem_support
theorem linearIndependent_sum {v : Sum ι ι' → M} :
LinearIndependent R v ↔
LinearIndependent R (v ∘ Sum.inl) ∧
LinearIndependent R (v ∘ Sum.inr) ∧
Disjoint (Submodule.span R (range (v ∘ Sum.inl)))
(Submodule.span R (range (v ∘ Sum.inr))) := by
classical
rw [range_comp v, range_comp v]
refine ⟨?_, ?_⟩
· intro h
refine ⟨h.comp _ Sum.inl_injective, h.comp _ Sum.inr_injective, ?_⟩
refine h.disjoint_span_image ?_
-- Porting note: `isCompl_range_inl_range_inr.1` timeouts.
exact IsCompl.disjoint isCompl_range_inl_range_inr
rintro ⟨hl, hr, hlr⟩
rw [linearIndependent_iff'] at *
intro s g hg i hi
have :
((∑ i ∈ s.preimage Sum.inl Sum.inl_injective.injOn, (fun x => g x • v x) (Sum.inl i)) +
∑ i ∈ s.preimage Sum.inr Sum.inr_injective.injOn, (fun x => g x • v x) (Sum.inr i)) =
0 := by
-- Porting note: `g` must be specified.
rw [Finset.sum_preimage' (g := fun x => g x • v x),
Finset.sum_preimage' (g := fun x => g x • v x), ← Finset.sum_union, ← Finset.filter_or]
· simpa only [← mem_union, range_inl_union_range_inr, mem_univ, Finset.filter_True]
· -- Porting note: Here was one `exact`, but timeouted.
refine Finset.disjoint_filter.2 fun x _ hx =>
disjoint_left.1 ?_ hx
exact IsCompl.disjoint isCompl_range_inl_range_inr
rw [← eq_neg_iff_add_eq_zero] at this
rw [disjoint_def'] at hlr
have A := by
refine hlr _ (sum_mem fun i _ => ?_) _ (neg_mem <| sum_mem fun i _ => ?_) this
· exact smul_mem _ _ (subset_span ⟨Sum.inl i, mem_range_self _, rfl⟩)
· exact smul_mem _ _ (subset_span ⟨Sum.inr i, mem_range_self _, rfl⟩)
cases' i with i i
· exact hl _ _ A i (Finset.mem_preimage.2 hi)
· rw [this, neg_eq_zero] at A
exact hr _ _ A i (Finset.mem_preimage.2 hi)
#align linear_independent_sum linearIndependent_sum
theorem LinearIndependent.sum_type {v' : ι' → M} (hv : LinearIndependent R v)
(hv' : LinearIndependent R v')
(h : Disjoint (Submodule.span R (range v)) (Submodule.span R (range v'))) :
LinearIndependent R (Sum.elim v v') :=
linearIndependent_sum.2 ⟨hv, hv', h⟩
#align linear_independent.sum_type LinearIndependent.sum_type
theorem LinearIndependent.union {s t : Set M} (hs : LinearIndependent R (fun x => x : s → M))
(ht : LinearIndependent R (fun x => x : t → M)) (hst : Disjoint (span R s) (span R t)) :
LinearIndependent R (fun x => x : ↥(s ∪ t) → M) :=
(hs.sum_type ht <| by simpa).to_subtype_range' <| by simp
#align linear_independent.union LinearIndependent.union
theorem linearIndependent_iUnion_finite_subtype {ι : Type*} {f : ι → Set M}
(hl : ∀ i, LinearIndependent R (fun x => x : f i → M))
(hd : ∀ i, ∀ t : Set ι, t.Finite → i ∉ t → Disjoint (span R (f i)) (⨆ i ∈ t, span R (f i))) :
LinearIndependent R (fun x => x : (⋃ i, f i) → M) := by
classical
rw [iUnion_eq_iUnion_finset f]
apply linearIndependent_iUnion_of_directed
· apply directed_of_isDirected_le
exact fun t₁ t₂ ht => iUnion_mono fun i => iUnion_subset_iUnion_const fun h => ht h
intro t
induction' t using Finset.induction_on with i s his ih
· refine (linearIndependent_empty R M).mono ?_
simp
· rw [Finset.set_biUnion_insert]
refine (hl _).union ih ?_
rw [span_iUnion₂]
exact hd i s s.finite_toSet his
#align linear_independent_Union_finite_subtype linearIndependent_iUnion_finite_subtype
theorem linearIndependent_iUnion_finite {η : Type*} {ιs : η → Type*} {f : ∀ j : η, ιs j → M}
(hindep : ∀ j, LinearIndependent R (f j))
(hd : ∀ i, ∀ t : Set η,
t.Finite → i ∉ t → Disjoint (span R (range (f i))) (⨆ i ∈ t, span R (range (f i)))) :
LinearIndependent R fun ji : Σ j, ιs j => f ji.1 ji.2 := by
nontriviality R
apply LinearIndependent.of_subtype_range
· rintro ⟨x₁, x₂⟩ ⟨y₁, y₂⟩ hxy
by_cases h_cases : x₁ = y₁
· subst h_cases
refine Sigma.eq rfl ?_
rw [LinearIndependent.injective (hindep _) hxy]
· have h0 : f x₁ x₂ = 0 := by
apply
disjoint_def.1 (hd x₁ {y₁} (finite_singleton y₁) fun h => h_cases (eq_of_mem_singleton h))
(f x₁ x₂) (subset_span (mem_range_self _))
rw [iSup_singleton]
simp only at hxy
rw [hxy]
exact subset_span (mem_range_self y₂)
exact False.elim ((hindep x₁).ne_zero _ h0)
rw [range_sigma_eq_iUnion_range]
apply linearIndependent_iUnion_finite_subtype (fun j => (hindep j).to_subtype_range) hd
#align linear_independent_Union_finite linearIndependent_iUnion_finite
end Subtype
section repr
variable (hv : LinearIndependent R v)
/-- Canonical isomorphism between linear combinations and the span of linearly independent vectors.
-/
@[simps (config := { rhsMd := default }) symm_apply]
def LinearIndependent.totalEquiv (hv : LinearIndependent R v) :
(ι →₀ R) ≃ₗ[R] span R (range v) := by
apply LinearEquiv.ofBijective (LinearMap.codRestrict (span R (range v)) (Finsupp.total ι M R v) _)
constructor
· rw [← LinearMap.ker_eq_bot, LinearMap.ker_codRestrict]
· apply hv
· intro l
rw [← Finsupp.range_total]
rw [LinearMap.mem_range]
apply mem_range_self l
· rw [← LinearMap.range_eq_top, LinearMap.range_eq_map, LinearMap.map_codRestrict, ←
LinearMap.range_le_iff_comap, range_subtype, Submodule.map_top]
rw [Finsupp.range_total]
#align linear_independent.total_equiv LinearIndependent.totalEquiv
#align linear_independent.total_equiv_symm_apply LinearIndependent.totalEquiv_symm_apply
-- Porting note: The original theorem generated by `simps` was
-- different from the theorem on Lean 3, and not simp-normal form.
@[simp]
theorem LinearIndependent.totalEquiv_apply_coe (hv : LinearIndependent R v) (l : ι →₀ R) :
hv.totalEquiv l = Finsupp.total ι M R v l := rfl
#align linear_independent.total_equiv_apply_coe LinearIndependent.totalEquiv_apply_coe
/-- Linear combination representing a vector in the span of linearly independent vectors.
Given a family of linearly independent vectors, we can represent any vector in their span as
a linear combination of these vectors. These are provided by this linear map.
It is simply one direction of `LinearIndependent.total_equiv`. -/
def LinearIndependent.repr (hv : LinearIndependent R v) : span R (range v) →ₗ[R] ι →₀ R :=
hv.totalEquiv.symm
#align linear_independent.repr LinearIndependent.repr
@[simp]
theorem LinearIndependent.total_repr (x) : Finsupp.total ι M R v (hv.repr x) = x :=
Subtype.ext_iff.1 (LinearEquiv.apply_symm_apply hv.totalEquiv x)
#align linear_independent.total_repr LinearIndependent.total_repr
theorem LinearIndependent.total_comp_repr :
(Finsupp.total ι M R v).comp hv.repr = Submodule.subtype _ :=
LinearMap.ext <| hv.total_repr
#align linear_independent.total_comp_repr LinearIndependent.total_comp_repr
theorem LinearIndependent.repr_ker : LinearMap.ker hv.repr = ⊥ := by
rw [LinearIndependent.repr, LinearEquiv.ker]
#align linear_independent.repr_ker LinearIndependent.repr_ker
theorem LinearIndependent.repr_range : LinearMap.range hv.repr = ⊤ := by
rw [LinearIndependent.repr, LinearEquiv.range]
#align linear_independent.repr_range LinearIndependent.repr_range
theorem LinearIndependent.repr_eq {l : ι →₀ R} {x : span R (range v)}
(eq : Finsupp.total ι M R v l = ↑x) : hv.repr x = l := by
have :
↑((LinearIndependent.totalEquiv hv : (ι →₀ R) →ₗ[R] span R (range v)) l) =
Finsupp.total ι M R v l :=
rfl
have : (LinearIndependent.totalEquiv hv : (ι →₀ R) →ₗ[R] span R (range v)) l = x := by
rw [eq] at this
exact Subtype.ext_iff.2 this
rw [← LinearEquiv.symm_apply_apply hv.totalEquiv l]
rw [← this]
rfl
#align linear_independent.repr_eq LinearIndependent.repr_eq
theorem LinearIndependent.repr_eq_single (i) (x : span R (range v)) (hx : ↑x = v i) :
hv.repr x = Finsupp.single i 1 := by
apply hv.repr_eq
simp [Finsupp.total_single, hx]
#align linear_independent.repr_eq_single LinearIndependent.repr_eq_single
theorem LinearIndependent.span_repr_eq [Nontrivial R] (x) :
Span.repr R (Set.range v) x =
(hv.repr x).equivMapDomain (Equiv.ofInjective _ hv.injective) := by
have p :
(Span.repr R (Set.range v) x).equivMapDomain (Equiv.ofInjective _ hv.injective).symm =
hv.repr x := by
apply (LinearIndependent.totalEquiv hv).injective
ext
simp only [LinearIndependent.totalEquiv_apply_coe, Equiv.self_comp_ofInjective_symm,
LinearIndependent.total_repr, Finsupp.total_equivMapDomain, Span.finsupp_total_repr]
ext ⟨_, ⟨i, rfl⟩⟩
simp [← p]
#align linear_independent.span_repr_eq LinearIndependent.span_repr_eq
theorem linearIndependent_iff_not_smul_mem_span :
LinearIndependent R v ↔ ∀ (i : ι) (a : R), a • v i ∈ span R (v '' (univ \ {i})) → a = 0 :=
⟨fun hv i a ha => by
rw [Finsupp.span_image_eq_map_total, mem_map] at ha
rcases ha with ⟨l, hl, e⟩
rw [sub_eq_zero.1 (linearIndependent_iff.1 hv (l - Finsupp.single i a) (by simp [e]))] at hl
by_contra hn
exact (not_mem_of_mem_diff (hl <| by simp [hn])) (mem_singleton _), fun H =>
linearIndependent_iff.2 fun l hl => by
ext i; simp only [Finsupp.zero_apply]
by_contra hn
refine hn (H i _ ?_)
refine (Finsupp.mem_span_image_iff_total R).2 ⟨Finsupp.single i (l i) - l, ?_, ?_⟩
· rw [Finsupp.mem_supported']
intro j hj
have hij : j = i :=
Classical.not_not.1 fun hij : j ≠ i =>
hj ((mem_diff _).2 ⟨mem_univ _, fun h => hij (eq_of_mem_singleton h)⟩)
simp [hij]
· simp [hl]⟩
#align linear_independent_iff_not_smul_mem_span linearIndependent_iff_not_smul_mem_span
/-- See also `CompleteLattice.independent_iff_linearIndependent_of_ne_zero`. -/
theorem LinearIndependent.independent_span_singleton (hv : LinearIndependent R v) :
CompleteLattice.Independent fun i => R ∙ v i := by
refine CompleteLattice.independent_def.mp fun i => ?_
rw [disjoint_iff_inf_le]
intro m hm
simp only [mem_inf, mem_span_singleton, iSup_subtype'] at hm
rw [← span_range_eq_iSup] at hm
obtain ⟨⟨r, rfl⟩, hm⟩ := hm
suffices r = 0 by simp [this]
apply linearIndependent_iff_not_smul_mem_span.mp hv i
-- Porting note: The original proof was using `convert hm`.
suffices v '' (univ \ {i}) = range fun j : { j // j ≠ i } => v j by
rwa [this]
ext
simp
#align linear_independent.independent_span_singleton LinearIndependent.independent_span_singleton
variable (R)
theorem exists_maximal_independent' (s : ι → M) :
∃ I : Set ι,
(LinearIndependent R fun x : I => s x) ∧
∀ J : Set ι, I ⊆ J → (LinearIndependent R fun x : J => s x) → I = J := by
let indep : Set ι → Prop := fun I => LinearIndependent R (s ∘ (↑) : I → M)
let X := { I : Set ι // indep I }
let r : X → X → Prop := fun I J => I.1 ⊆ J.1
have key : ∀ c : Set X, IsChain r c → indep (⋃ (I : X) (_ : I ∈ c), I) := by
intro c hc
dsimp [indep]
rw [linearIndependent_comp_subtype]
intro f hsupport hsum
rcases eq_empty_or_nonempty c with (rfl | hn)
· simpa using hsupport
haveI : IsRefl X r := ⟨fun _ => Set.Subset.refl _⟩
obtain ⟨I, _I_mem, hI⟩ : ∃ I ∈ c, (f.support : Set ι) ⊆ I :=
hc.directedOn.exists_mem_subset_of_finset_subset_biUnion hn hsupport
exact linearIndependent_comp_subtype.mp I.2 f hI hsum
have trans : Transitive r := fun I J K => Set.Subset.trans
obtain ⟨⟨I, hli : indep I⟩, hmax : ∀ a, r ⟨I, hli⟩ a → r a ⟨I, hli⟩⟩ :=
exists_maximal_of_chains_bounded
(fun c hc => ⟨⟨⋃ I ∈ c, (I : Set ι), key c hc⟩, fun I => Set.subset_biUnion_of_mem⟩) @trans
exact ⟨I, hli, fun J hsub hli => Set.Subset.antisymm hsub (hmax ⟨J, hli⟩ hsub)⟩
#align exists_maximal_independent' exists_maximal_independent'
theorem exists_maximal_independent (s : ι → M) :
∃ I : Set ι,
(LinearIndependent R fun x : I => s x) ∧
∀ i ∉ I, ∃ a : R, a ≠ 0 ∧ a • s i ∈ span R (s '' I) := by
classical
rcases exists_maximal_independent' R s with ⟨I, hIlinind, hImaximal⟩
use I, hIlinind
intro i hi
specialize hImaximal (I ∪ {i}) (by simp)
set J := I ∪ {i} with hJ
have memJ : ∀ {x}, x ∈ J ↔ x = i ∨ x ∈ I := by simp [hJ]
have hiJ : i ∈ J := by simp [J]
have h := by
refine mt hImaximal ?_
· intro h2
rw [h2] at hi
exact absurd hiJ hi
obtain ⟨f, supp_f, sum_f, f_ne⟩ := linearDependent_comp_subtype.mp h
have hfi : f i ≠ 0 := by
contrapose hIlinind
refine linearDependent_comp_subtype.mpr ⟨f, ?_, sum_f, f_ne⟩
simp only [Finsupp.mem_supported, hJ] at supp_f ⊢
rintro x hx
refine (memJ.mp (supp_f hx)).resolve_left ?_
rintro rfl
exact hIlinind (Finsupp.mem_support_iff.mp hx)
use f i, hfi
have hfi' : i ∈ f.support := Finsupp.mem_support_iff.mpr hfi
rw [← Finset.insert_erase hfi', Finset.sum_insert (Finset.not_mem_erase _ _),
add_eq_zero_iff_eq_neg] at sum_f
rw [sum_f]
refine neg_mem (sum_mem fun c hc => smul_mem _ _ (subset_span ⟨c, ?_, rfl⟩))
exact (memJ.mp (supp_f (Finset.erase_subset _ _ hc))).resolve_left (Finset.ne_of_mem_erase hc)
#align exists_maximal_independent exists_maximal_independent
end repr
theorem surjective_of_linearIndependent_of_span [Nontrivial R] (hv : LinearIndependent R v)
(f : ι' ↪ ι) (hss : range v ⊆ span R (range (v ∘ f))) : Surjective f := by
intro i
let repr : (span R (range (v ∘ f)) : Type _) → ι' →₀ R := (hv.comp f f.injective).repr
let l := (repr ⟨v i, hss (mem_range_self i)⟩).mapDomain f
have h_total_l : Finsupp.total ι M R v l = v i := by
dsimp only [l]
rw [Finsupp.total_mapDomain]
rw [(hv.comp f f.injective).total_repr]
-- Porting note: `rfl` isn't necessary.
have h_total_eq : (Finsupp.total ι M R v) l = (Finsupp.total ι M R v) (Finsupp.single i 1) := by
rw [h_total_l, Finsupp.total_single, one_smul]
have l_eq : l = _ := LinearMap.ker_eq_bot.1 hv h_total_eq
dsimp only [l] at l_eq
rw [← Finsupp.embDomain_eq_mapDomain] at l_eq
rcases Finsupp.single_of_embDomain_single (repr ⟨v i, _⟩) f i (1 : R) zero_ne_one.symm l_eq with
⟨i', hi'⟩
use i'
exact hi'.2
#align surjective_of_linear_independent_of_span surjective_of_linearIndependent_of_span
theorem eq_of_linearIndependent_of_span_subtype [Nontrivial R] {s t : Set M}
(hs : LinearIndependent R (fun x => x : s → M)) (h : t ⊆ s) (hst : s ⊆ span R t) : s = t := by
let f : t ↪ s :=
⟨fun x => ⟨x.1, h x.2⟩, fun a b hab => Subtype.coe_injective (Subtype.mk.inj hab)⟩
have h_surj : Surjective f := by
apply surjective_of_linearIndependent_of_span hs f _
convert hst <;> simp [f, comp]
show s = t
apply Subset.antisymm _ h
intro x hx
rcases h_surj ⟨x, hx⟩ with ⟨y, hy⟩
convert y.mem
rw [← Subtype.mk.inj hy]
#align eq_of_linear_independent_of_span_subtype eq_of_linearIndependent_of_span_subtype
open LinearMap
theorem LinearIndependent.image_subtype {s : Set M} {f : M →ₗ[R] M'}
(hs : LinearIndependent R (fun x => x : s → M))
(hf_inj : Disjoint (span R s) (LinearMap.ker f)) :
LinearIndependent R (fun x => x : f '' s → M') := by
rw [← Subtype.range_coe (s := s)] at hf_inj
refine (hs.map hf_inj).to_subtype_range' ?_
simp [Set.range_comp f]
#align linear_independent.image_subtype LinearIndependent.image_subtype
theorem LinearIndependent.inl_union_inr {s : Set M} {t : Set M'}
(hs : LinearIndependent R (fun x => x : s → M))
(ht : LinearIndependent R (fun x => x : t → M')) :
LinearIndependent R (fun x => x : ↥(inl R M M' '' s ∪ inr R M M' '' t) → M × M') := by
refine (hs.image_subtype ?_).union (ht.image_subtype ?_) ?_ <;> [simp; simp; skip]
-- Note: #8386 had to change `span_image` into `span_image _`
simp only [span_image _]
simp [disjoint_iff, prod_inf_prod]
#align linear_independent.inl_union_inr LinearIndependent.inl_union_inr
theorem linearIndependent_inl_union_inr' {v : ι → M} {v' : ι' → M'} (hv : LinearIndependent R v)
(hv' : LinearIndependent R v') :
LinearIndependent R (Sum.elim (inl R M M' ∘ v) (inr R M M' ∘ v')) :=
(hv.map' (inl R M M') ker_inl).sum_type (hv'.map' (inr R M M') ker_inr) <| by
refine isCompl_range_inl_inr.disjoint.mono ?_ ?_ <;>
simp only [span_le, range_coe, range_comp_subset_range]
#align linear_independent_inl_union_inr' linearIndependent_inl_union_inr'
-- See, for example, Keith Conrad's note
-- <https://kconrad.math.uconn.edu/blurbs/galoistheory/linearchar.pdf>
/-- Dedekind's linear independence of characters -/
theorem linearIndependent_monoidHom (G : Type*) [Monoid G] (L : Type*) [CommRing L]
[NoZeroDivisors L] : LinearIndependent L (M := G → L) (fun f => f : (G →* L) → G → L) := by
-- Porting note: Some casts are required.
letI := Classical.decEq (G →* L);
letI : MulAction L L := DistribMulAction.toMulAction;
-- We prove linear independence by showing that only the trivial linear combination vanishes.
exact linearIndependent_iff'.2
-- To do this, we use `Finset` induction,
-- Porting note: `False.elim` → `fun h => False.elim <| Finset.not_mem_empty _ h`
fun s =>
Finset.induction_on s
(fun g _hg i h => False.elim <| Finset.not_mem_empty _ h) fun a s has ih g hg =>
-- Here
-- * `a` is a new character we will insert into the `Finset` of characters `s`,
-- * `ih` is the fact that only the trivial linear combination of characters in `s` is zero
-- * `hg` is the fact that `g` are the coefficients of a linear combination summing to zero
-- and it remains to prove that `g` vanishes on `insert a s`.
-- We now make the key calculation:
-- For any character `i` in the original `Finset`, we have `g i • i = g i • a` as functions
-- on the monoid `G`.
have h1 : ∀ i ∈ s, (g i • (i : G → L)) = g i • (a : G → L) := fun i his =>
funext fun x : G =>
-- We prove these expressions are equal by showing
-- the differences of their values on each monoid element `x` is zero
eq_of_sub_eq_zero <|
ih (fun j => g j * j x - g j * a x)
(funext fun y : G => calc
-- After that, it's just a chase scene.
(∑ i ∈ s, ((g i * i x - g i * a x) • (i : G → L))) y =
∑ i ∈ s, (g i * i x - g i * a x) * i y :=
Finset.sum_apply ..
_ = ∑ i ∈ s, (g i * i x * i y - g i * a x * i y) :=
Finset.sum_congr rfl fun _ _ => sub_mul ..
_ = (∑ i ∈ s, g i * i x * i y) - ∑ i ∈ s, g i * a x * i y :=
Finset.sum_sub_distrib
_ =
(g a * a x * a y + ∑ i ∈ s, g i * i x * i y) -
(g a * a x * a y + ∑ i ∈ s, g i * a x * i y) := by
rw [add_sub_add_left_eq_sub]
_ =
(∑ i ∈ insert a s, g i * i x * i y) -
∑ i ∈ insert a s, g i * a x * i y := by
rw [Finset.sum_insert has, Finset.sum_insert has]
_ =
(∑ i ∈ insert a s, g i * i (x * y)) -
∑ i ∈ insert a s, a x * (g i * i y) :=
congr
(congr_arg Sub.sub
(Finset.sum_congr rfl fun i _ => by rw [i.map_mul, mul_assoc]))
(Finset.sum_congr rfl fun _ _ => by rw [mul_assoc, mul_left_comm])
_ =
(∑ i ∈ insert a s, (g i • (i : G → L))) (x * y) -
a x * (∑ i ∈ insert a s, (g i • (i : G → L))) y := by
rw [Finset.sum_apply, Finset.sum_apply, Finset.mul_sum]; rfl
_ = 0 - a x * 0 := by rw [hg]; rfl
_ = 0 := by rw [mul_zero, sub_zero]
)
i his
-- On the other hand, since `a` is not already in `s`, for any character `i ∈ s`
-- there is some element of the monoid on which it differs from `a`.
have h2 : ∀ i : G →* L, i ∈ s → ∃ y, i y ≠ a y := fun i his =>
Classical.by_contradiction fun h =>
have hia : i = a := MonoidHom.ext fun y =>
Classical.by_contradiction fun hy => h ⟨y, hy⟩
has <| hia ▸ his
-- From these two facts we deduce that `g` actually vanishes on `s`,
have h3 : ∀ i ∈ s, g i = 0 := fun i his =>
let ⟨y, hy⟩ := h2 i his
have h : g i • i y = g i • a y := congr_fun (h1 i his) y
Or.resolve_right (mul_eq_zero.1 <| by rw [mul_sub, sub_eq_zero]; exact h)
(sub_ne_zero_of_ne hy)
-- And so, using the fact that the linear combination over `s` and over `insert a s` both
-- vanish, we deduce that `g a = 0`.
have h4 : g a = 0 :=
calc
g a = g a * 1 := (mul_one _).symm
_ = (g a • (a : G → L)) 1 := by rw [← a.map_one]; rfl
_ = (∑ i ∈ insert a s, (g i • (i : G → L))) 1 := by
rw [Finset.sum_eq_single a]
· intro i his hia
rw [Finset.mem_insert] at his
rw [h3 i (his.resolve_left hia), zero_smul]
· intro haas
exfalso
apply haas
exact Finset.mem_insert_self a s
_ = 0 := by rw [hg]; rfl
-- Now we're done; the last two facts together imply that `g` vanishes on every element
-- of `insert a s`.
(Finset.forall_mem_insert ..).2 ⟨h4, h3⟩
#align linear_independent_monoid_hom linearIndependent_monoidHom
lemma linearIndependent_algHom_toLinearMap
(K M L) [CommSemiring K] [Semiring M] [Algebra K M] [CommRing L] [IsDomain L] [Algebra K L] :
LinearIndependent L (AlgHom.toLinearMap : (M →ₐ[K] L) → M →ₗ[K] L) := by
apply LinearIndependent.of_comp (LinearMap.ltoFun K M L)
exact (linearIndependent_monoidHom M L).comp
(RingHom.toMonoidHom ∘ AlgHom.toRingHom)
(fun _ _ e ↦ AlgHom.ext (DFunLike.congr_fun e : _))
lemma linearIndependent_algHom_toLinearMap' (K M L) [CommRing K]
[Semiring M] [Algebra K M] [CommRing L] [IsDomain L] [Algebra K L] [NoZeroSMulDivisors K L] :
LinearIndependent K (AlgHom.toLinearMap : (M →ₐ[K] L) → M →ₗ[K] L) := by
apply (linearIndependent_algHom_toLinearMap K M L).restrict_scalars
simp_rw [Algebra.smul_def, mul_one]
exact NoZeroSMulDivisors.algebraMap_injective K L
| Mathlib/LinearAlgebra/LinearIndependent.lean | 1,229 | 1,234 | theorem le_of_span_le_span [Nontrivial R] {s t u : Set M} (hl : LinearIndependent R ((↑) : u → M))
(hsu : s ⊆ u) (htu : t ⊆ u) (hst : span R s ≤ span R t) : s ⊆ t := by |
have :=
eq_of_linearIndependent_of_span_subtype (hl.mono (Set.union_subset hsu htu))
Set.subset_union_right (Set.union_subset (Set.Subset.trans subset_span hst) subset_span)
rw [← this]; apply Set.subset_union_left
|
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Complex.Basic
import Mathlib.Topology.FiberBundle.IsHomeomorphicTrivialBundle
#align_import analysis.complex.re_im_topology from "leanprover-community/mathlib"@"468b141b14016d54b479eb7a0fff1e360b7e3cf6"
/-!
# Closure, interior, and frontier of preimages under `re` and `im`
In this fact we use the fact that `ℂ` is naturally homeomorphic to `ℝ × ℝ` to deduce some
topological properties of `Complex.re` and `Complex.im`.
## Main statements
Each statement about `Complex.re` listed below has a counterpart about `Complex.im`.
* `Complex.isHomeomorphicTrivialFiberBundle_re`: `Complex.re` turns `ℂ` into a trivial
topological fiber bundle over `ℝ`;
* `Complex.isOpenMap_re`, `Complex.quotientMap_re`: in particular, `Complex.re` is an open map
and is a quotient map;
* `Complex.interior_preimage_re`, `Complex.closure_preimage_re`, `Complex.frontier_preimage_re`:
formulas for `interior (Complex.re ⁻¹' s)` etc;
* `Complex.interior_setOf_re_le` etc: particular cases of the above formulas in the cases when `s`
is one of the infinite intervals `Set.Ioi a`, `Set.Ici a`, `Set.Iio a`, and `Set.Iic a`,
formulated as `interior {z : ℂ | z.re ≤ a} = {z | z.re < a}` etc.
## Tags
complex, real part, imaginary part, closure, interior, frontier
-/
open Set
noncomputable section
namespace Complex
/-- `Complex.re` turns `ℂ` into a trivial topological fiber bundle over `ℝ`. -/
theorem isHomeomorphicTrivialFiberBundle_re : IsHomeomorphicTrivialFiberBundle ℝ re :=
⟨equivRealProdCLM.toHomeomorph, fun _ => rfl⟩
#align complex.is_homeomorphic_trivial_fiber_bundle_re Complex.isHomeomorphicTrivialFiberBundle_re
/-- `Complex.im` turns `ℂ` into a trivial topological fiber bundle over `ℝ`. -/
theorem isHomeomorphicTrivialFiberBundle_im : IsHomeomorphicTrivialFiberBundle ℝ im :=
⟨equivRealProdCLM.toHomeomorph.trans (Homeomorph.prodComm ℝ ℝ), fun _ => rfl⟩
#align complex.is_homeomorphic_trivial_fiber_bundle_im Complex.isHomeomorphicTrivialFiberBundle_im
theorem isOpenMap_re : IsOpenMap re :=
isHomeomorphicTrivialFiberBundle_re.isOpenMap_proj
#align complex.is_open_map_re Complex.isOpenMap_re
theorem isOpenMap_im : IsOpenMap im :=
isHomeomorphicTrivialFiberBundle_im.isOpenMap_proj
#align complex.is_open_map_im Complex.isOpenMap_im
theorem quotientMap_re : QuotientMap re :=
isHomeomorphicTrivialFiberBundle_re.quotientMap_proj
#align complex.quotient_map_re Complex.quotientMap_re
theorem quotientMap_im : QuotientMap im :=
isHomeomorphicTrivialFiberBundle_im.quotientMap_proj
#align complex.quotient_map_im Complex.quotientMap_im
theorem interior_preimage_re (s : Set ℝ) : interior (re ⁻¹' s) = re ⁻¹' interior s :=
(isOpenMap_re.preimage_interior_eq_interior_preimage continuous_re _).symm
#align complex.interior_preimage_re Complex.interior_preimage_re
theorem interior_preimage_im (s : Set ℝ) : interior (im ⁻¹' s) = im ⁻¹' interior s :=
(isOpenMap_im.preimage_interior_eq_interior_preimage continuous_im _).symm
#align complex.interior_preimage_im Complex.interior_preimage_im
theorem closure_preimage_re (s : Set ℝ) : closure (re ⁻¹' s) = re ⁻¹' closure s :=
(isOpenMap_re.preimage_closure_eq_closure_preimage continuous_re _).symm
#align complex.closure_preimage_re Complex.closure_preimage_re
theorem closure_preimage_im (s : Set ℝ) : closure (im ⁻¹' s) = im ⁻¹' closure s :=
(isOpenMap_im.preimage_closure_eq_closure_preimage continuous_im _).symm
#align complex.closure_preimage_im Complex.closure_preimage_im
theorem frontier_preimage_re (s : Set ℝ) : frontier (re ⁻¹' s) = re ⁻¹' frontier s :=
(isOpenMap_re.preimage_frontier_eq_frontier_preimage continuous_re _).symm
#align complex.frontier_preimage_re Complex.frontier_preimage_re
theorem frontier_preimage_im (s : Set ℝ) : frontier (im ⁻¹' s) = im ⁻¹' frontier s :=
(isOpenMap_im.preimage_frontier_eq_frontier_preimage continuous_im _).symm
#align complex.frontier_preimage_im Complex.frontier_preimage_im
@[simp]
theorem interior_setOf_re_le (a : ℝ) : interior { z : ℂ | z.re ≤ a } = { z | z.re < a } := by
simpa only [interior_Iic] using interior_preimage_re (Iic a)
#align complex.interior_set_of_re_le Complex.interior_setOf_re_le
@[simp]
theorem interior_setOf_im_le (a : ℝ) : interior { z : ℂ | z.im ≤ a } = { z | z.im < a } := by
simpa only [interior_Iic] using interior_preimage_im (Iic a)
#align complex.interior_set_of_im_le Complex.interior_setOf_im_le
@[simp]
theorem interior_setOf_le_re (a : ℝ) : interior { z : ℂ | a ≤ z.re } = { z | a < z.re } := by
simpa only [interior_Ici] using interior_preimage_re (Ici a)
#align complex.interior_set_of_le_re Complex.interior_setOf_le_re
@[simp]
theorem interior_setOf_le_im (a : ℝ) : interior { z : ℂ | a ≤ z.im } = { z | a < z.im } := by
simpa only [interior_Ici] using interior_preimage_im (Ici a)
#align complex.interior_set_of_le_im Complex.interior_setOf_le_im
@[simp]
theorem closure_setOf_re_lt (a : ℝ) : closure { z : ℂ | z.re < a } = { z | z.re ≤ a } := by
simpa only [closure_Iio] using closure_preimage_re (Iio a)
#align complex.closure_set_of_re_lt Complex.closure_setOf_re_lt
@[simp]
theorem closure_setOf_im_lt (a : ℝ) : closure { z : ℂ | z.im < a } = { z | z.im ≤ a } := by
simpa only [closure_Iio] using closure_preimage_im (Iio a)
#align complex.closure_set_of_im_lt Complex.closure_setOf_im_lt
@[simp]
theorem closure_setOf_lt_re (a : ℝ) : closure { z : ℂ | a < z.re } = { z | a ≤ z.re } := by
simpa only [closure_Ioi] using closure_preimage_re (Ioi a)
#align complex.closure_set_of_lt_re Complex.closure_setOf_lt_re
@[simp]
| Mathlib/Analysis/Complex/ReImTopology.lean | 129 | 130 | theorem closure_setOf_lt_im (a : ℝ) : closure { z : ℂ | a < z.im } = { z | a ≤ z.im } := by |
simpa only [closure_Ioi] using closure_preimage_im (Ioi a)
|
/-
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, Eric Wieser
-/
import Mathlib.Algebra.Algebra.Prod
import Mathlib.LinearAlgebra.Basic
import Mathlib.LinearAlgebra.Span
import Mathlib.Order.PartialSups
#align_import linear_algebra.prod from "leanprover-community/mathlib"@"cd391184c85986113f8c00844cfe6dda1d34be3d"
/-! ### Products of modules
This file defines constructors for linear maps whose domains or codomains are products.
It contains theorems relating these to each other, as well as to `Submodule.prod`, `Submodule.map`,
`Submodule.comap`, `LinearMap.range`, and `LinearMap.ker`.
## Main definitions
- products in the domain:
- `LinearMap.fst`
- `LinearMap.snd`
- `LinearMap.coprod`
- `LinearMap.prod_ext`
- products in the codomain:
- `LinearMap.inl`
- `LinearMap.inr`
- `LinearMap.prod`
- products in both domain and codomain:
- `LinearMap.prodMap`
- `LinearEquiv.prodMap`
- `LinearEquiv.skewProd`
-/
universe u v w x y z u' v' w' y'
variable {R : Type u} {K : Type u'} {M : Type v} {V : Type v'} {M₂ : Type w} {V₂ : Type w'}
variable {M₃ : Type y} {V₃ : Type y'} {M₄ : Type z} {ι : Type x}
variable {M₅ M₆ : Type*}
section Prod
namespace LinearMap
variable (S : Type*) [Semiring R] [Semiring S]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃] [AddCommMonoid M₄]
variable [AddCommMonoid M₅] [AddCommMonoid M₆]
variable [Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
variable [Module R M₅] [Module R M₆]
variable (f : M →ₗ[R] M₂)
section
variable (R M M₂)
/-- The first projection of a product is a linear map. -/
def fst : M × M₂ →ₗ[R] M where
toFun := Prod.fst
map_add' _x _y := rfl
map_smul' _x _y := rfl
#align linear_map.fst LinearMap.fst
/-- The second projection of a product is a linear map. -/
def snd : M × M₂ →ₗ[R] M₂ where
toFun := Prod.snd
map_add' _x _y := rfl
map_smul' _x _y := rfl
#align linear_map.snd LinearMap.snd
end
@[simp]
theorem fst_apply (x : M × M₂) : fst R M M₂ x = x.1 :=
rfl
#align linear_map.fst_apply LinearMap.fst_apply
@[simp]
theorem snd_apply (x : M × M₂) : snd R M M₂ x = x.2 :=
rfl
#align linear_map.snd_apply LinearMap.snd_apply
theorem fst_surjective : Function.Surjective (fst R M M₂) := fun x => ⟨(x, 0), rfl⟩
#align linear_map.fst_surjective LinearMap.fst_surjective
theorem snd_surjective : Function.Surjective (snd R M M₂) := fun x => ⟨(0, x), rfl⟩
#align linear_map.snd_surjective LinearMap.snd_surjective
/-- The prod of two linear maps is a linear map. -/
@[simps]
def prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : M →ₗ[R] M₂ × M₃ where
toFun := Pi.prod f g
map_add' x y := by simp only [Pi.prod, Prod.mk_add_mk, map_add]
map_smul' c x := by simp only [Pi.prod, Prod.smul_mk, map_smul, RingHom.id_apply]
#align linear_map.prod LinearMap.prod
theorem coe_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : ⇑(f.prod g) = Pi.prod f g :=
rfl
#align linear_map.coe_prod LinearMap.coe_prod
@[simp]
theorem fst_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : (fst R M₂ M₃).comp (prod f g) = f := rfl
#align linear_map.fst_prod LinearMap.fst_prod
@[simp]
theorem snd_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : (snd R M₂ M₃).comp (prod f g) = g := rfl
#align linear_map.snd_prod LinearMap.snd_prod
@[simp]
theorem pair_fst_snd : prod (fst R M M₂) (snd R M M₂) = LinearMap.id := rfl
#align linear_map.pair_fst_snd LinearMap.pair_fst_snd
theorem prod_comp (f : M₂ →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄)
(h : M →ₗ[R] M₂) : (f.prod g).comp h = (f.comp h).prod (g.comp h) :=
rfl
/-- Taking the product of two maps with the same domain is equivalent to taking the product of
their codomains.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used. -/
@[simps]
def prodEquiv [Module S M₂] [Module S M₃] [SMulCommClass R S M₂] [SMulCommClass R S M₃] :
((M →ₗ[R] M₂) × (M →ₗ[R] M₃)) ≃ₗ[S] M →ₗ[R] M₂ × M₃ where
toFun f := f.1.prod f.2
invFun f := ((fst _ _ _).comp f, (snd _ _ _).comp f)
left_inv f := by ext <;> rfl
right_inv f := by ext <;> rfl
map_add' a b := rfl
map_smul' r a := rfl
#align linear_map.prod_equiv LinearMap.prodEquiv
section
variable (R M M₂)
/-- The left injection into a product is a linear map. -/
def inl : M →ₗ[R] M × M₂ :=
prod LinearMap.id 0
#align linear_map.inl LinearMap.inl
/-- The right injection into a product is a linear map. -/
def inr : M₂ →ₗ[R] M × M₂ :=
prod 0 LinearMap.id
#align linear_map.inr LinearMap.inr
theorem range_inl : range (inl R M M₂) = ker (snd R M M₂) := by
ext x
simp only [mem_ker, mem_range]
constructor
· rintro ⟨y, rfl⟩
rfl
· intro h
exact ⟨x.fst, Prod.ext rfl h.symm⟩
#align linear_map.range_inl LinearMap.range_inl
theorem ker_snd : ker (snd R M M₂) = range (inl R M M₂) :=
Eq.symm <| range_inl R M M₂
#align linear_map.ker_snd LinearMap.ker_snd
theorem range_inr : range (inr R M M₂) = ker (fst R M M₂) := by
ext x
simp only [mem_ker, mem_range]
constructor
· rintro ⟨y, rfl⟩
rfl
· intro h
exact ⟨x.snd, Prod.ext h.symm rfl⟩
#align linear_map.range_inr LinearMap.range_inr
theorem ker_fst : ker (fst R M M₂) = range (inr R M M₂) :=
Eq.symm <| range_inr R M M₂
#align linear_map.ker_fst LinearMap.ker_fst
@[simp] theorem fst_comp_inl : fst R M M₂ ∘ₗ inl R M M₂ = id := rfl
@[simp] theorem snd_comp_inl : snd R M M₂ ∘ₗ inl R M M₂ = 0 := rfl
@[simp] theorem fst_comp_inr : fst R M M₂ ∘ₗ inr R M M₂ = 0 := rfl
@[simp] theorem snd_comp_inr : snd R M M₂ ∘ₗ inr R M M₂ = id := rfl
end
@[simp]
theorem coe_inl : (inl R M M₂ : M → M × M₂) = fun x => (x, 0) :=
rfl
#align linear_map.coe_inl LinearMap.coe_inl
theorem inl_apply (x : M) : inl R M M₂ x = (x, 0) :=
rfl
#align linear_map.inl_apply LinearMap.inl_apply
@[simp]
theorem coe_inr : (inr R M M₂ : M₂ → M × M₂) = Prod.mk 0 :=
rfl
#align linear_map.coe_inr LinearMap.coe_inr
theorem inr_apply (x : M₂) : inr R M M₂ x = (0, x) :=
rfl
#align linear_map.inr_apply LinearMap.inr_apply
theorem inl_eq_prod : inl R M M₂ = prod LinearMap.id 0 :=
rfl
#align linear_map.inl_eq_prod LinearMap.inl_eq_prod
theorem inr_eq_prod : inr R M M₂ = prod 0 LinearMap.id :=
rfl
#align linear_map.inr_eq_prod LinearMap.inr_eq_prod
theorem inl_injective : Function.Injective (inl R M M₂) := fun _ => by simp
#align linear_map.inl_injective LinearMap.inl_injective
theorem inr_injective : Function.Injective (inr R M M₂) := fun _ => by simp
#align linear_map.inr_injective LinearMap.inr_injective
/-- The coprod function `x : M × M₂ ↦ f x.1 + g x.2` is a linear map. -/
def coprod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : M × M₂ →ₗ[R] M₃ :=
f.comp (fst _ _ _) + g.comp (snd _ _ _)
#align linear_map.coprod LinearMap.coprod
@[simp]
theorem coprod_apply (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (x : M × M₂) :
coprod f g x = f x.1 + g x.2 :=
rfl
#align linear_map.coprod_apply LinearMap.coprod_apply
@[simp]
theorem coprod_inl (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : (coprod f g).comp (inl R M M₂) = f := by
ext; simp only [map_zero, add_zero, coprod_apply, inl_apply, comp_apply]
#align linear_map.coprod_inl LinearMap.coprod_inl
@[simp]
theorem coprod_inr (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : (coprod f g).comp (inr R M M₂) = g := by
ext; simp only [map_zero, coprod_apply, inr_apply, zero_add, comp_apply]
#align linear_map.coprod_inr LinearMap.coprod_inr
@[simp]
| Mathlib/LinearAlgebra/Prod.lean | 240 | 242 | theorem coprod_inl_inr : coprod (inl R M M₂) (inr R M M₂) = LinearMap.id := by |
ext <;>
simp only [Prod.mk_add_mk, add_zero, id_apply, coprod_apply, inl_apply, inr_apply, zero_add]
|
/-
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
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]
#align equiv.perm.form_perm_to_list Equiv.Perm.formPerm_toList
/-- Given a cyclic `f : Perm α`, generate the `Cycle α` in the order
of application of `f`. Implemented by finding an element `x : α`
in the support of `f` in `Finset.univ`, and iterating on using
`Equiv.Perm.toList f x`.
-/
def toCycle (f : Perm α) (hf : IsCycle f) : Cycle α :=
Multiset.recOn (Finset.univ : Finset α).val (Quot.mk _ [])
(fun x _ l => if f x = x then l else toList f x)
(by
intro x y _ s
refine heq_of_eq ?_
split_ifs with hx hy hy <;> try rfl
have hc : SameCycle f x y := IsCycle.sameCycle hf hx hy
exact Quotient.sound' hc.toList_isRotated)
#align equiv.perm.to_cycle Equiv.Perm.toCycle
| Mathlib/GroupTheory/Perm/Cycle/Concrete.lean | 416 | 420 | theorem toCycle_eq_toList (f : Perm α) (hf : IsCycle f) (x : α) (hx : f x ≠ x) :
toCycle f hf = toList f x := by |
have key : (Finset.univ : Finset α).val = x ::ₘ Finset.univ.val.erase x := by simp
rw [toCycle, key]
simp [hx]
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Markus Himmel
-/
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Zero
#align_import category_theory.limits.shapes.kernels from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
# Kernels and cokernels
In a category with zero morphisms, the kernel of a morphism `f : X ⟶ Y` is
the equalizer of `f` and `0 : X ⟶ Y`. (Similarly the cokernel is the coequalizer.)
The basic definitions are
* `kernel : (X ⟶ Y) → C`
* `kernel.ι : kernel f ⟶ X`
* `kernel.condition : kernel.ι f ≫ f = 0` and
* `kernel.lift (k : W ⟶ X) (h : k ≫ f = 0) : W ⟶ kernel f` (as well as the dual versions)
## Main statements
Besides the definition and lifts, we prove
* `kernel.ιZeroIsIso`: a kernel map of a zero morphism is an isomorphism
* `kernel.eq_zero_of_epi_kernel`: if `kernel.ι f` is an epimorphism, then `f = 0`
* `kernel.ofMono`: the kernel of a monomorphism is the zero object
* `kernel.liftMono`: the lift of a monomorphism `k : W ⟶ X` such that `k ≫ f = 0`
is still a monomorphism
* `kernel.isLimitConeZeroCone`: if our category has a zero object, then the map from the zero
object is a kernel map of any monomorphism
* `kernel.ιOfZero`: `kernel.ι (0 : X ⟶ Y)` is an isomorphism
and the corresponding dual statements.
## Future work
* TODO: connect this with existing work in the group theory and ring theory libraries.
## Implementation notes
As with the other special shapes in the limits library, all the definitions here are given as
`abbreviation`s of the general statements for limits, so all the `simp` lemmas and theorems about
general limits can be used.
## References
* [F. Borceux, *Handbook of Categorical Algebra 2*][borceux-vol2]
-/
noncomputable section
universe v v₂ u u' u₂
open CategoryTheory
open CategoryTheory.Limits.WalkingParallelPair
namespace CategoryTheory.Limits
variable {C : Type u} [Category.{v} C]
variable [HasZeroMorphisms C]
/-- A morphism `f` has a kernel if the functor `ParallelPair f 0` has a limit. -/
abbrev HasKernel {X Y : C} (f : X ⟶ Y) : Prop :=
HasLimit (parallelPair f 0)
#align category_theory.limits.has_kernel CategoryTheory.Limits.HasKernel
/-- A morphism `f` has a cokernel if the functor `ParallelPair f 0` has a colimit. -/
abbrev HasCokernel {X Y : C} (f : X ⟶ Y) : Prop :=
HasColimit (parallelPair f 0)
#align category_theory.limits.has_cokernel CategoryTheory.Limits.HasCokernel
variable {X Y : C} (f : X ⟶ Y)
section
/-- A kernel fork is just a fork where the second morphism is a zero morphism. -/
abbrev KernelFork :=
Fork f 0
#align category_theory.limits.kernel_fork CategoryTheory.Limits.KernelFork
variable {f}
@[reassoc (attr := simp)]
theorem KernelFork.condition (s : KernelFork f) : Fork.ι s ≫ f = 0 := by
erw [Fork.condition, HasZeroMorphisms.comp_zero]
#align category_theory.limits.kernel_fork.condition CategoryTheory.Limits.KernelFork.condition
-- Porting note (#10618): simp can prove this, removed simp tag
theorem KernelFork.app_one (s : KernelFork f) : s.π.app one = 0 := by
simp [Fork.app_one_eq_ι_comp_right]
#align category_theory.limits.kernel_fork.app_one CategoryTheory.Limits.KernelFork.app_one
/-- A morphism `ι` satisfying `ι ≫ f = 0` determines a kernel fork over `f`. -/
abbrev KernelFork.ofι {Z : C} (ι : Z ⟶ X) (w : ι ≫ f = 0) : KernelFork f :=
Fork.ofι ι <| by rw [w, HasZeroMorphisms.comp_zero]
#align category_theory.limits.kernel_fork.of_ι CategoryTheory.Limits.KernelFork.ofι
@[simp]
theorem KernelFork.ι_ofι {X Y P : C} (f : X ⟶ Y) (ι : P ⟶ X) (w : ι ≫ f = 0) :
Fork.ι (KernelFork.ofι ι w) = ι := rfl
#align category_theory.limits.kernel_fork.ι_of_ι CategoryTheory.Limits.KernelFork.ι_ofι
section
-- attribute [local tidy] tactic.case_bash Porting note: no tidy nor case_bash
/-- Every kernel fork `s` is isomorphic (actually, equal) to `fork.ofι (fork.ι s) _`. -/
def isoOfι (s : Fork f 0) : s ≅ Fork.ofι (Fork.ι s) (Fork.condition s) :=
Cones.ext (Iso.refl _) <| by rintro ⟨j⟩ <;> simp
#align category_theory.limits.iso_of_ι CategoryTheory.Limits.isoOfι
/-- If `ι = ι'`, then `fork.ofι ι _` and `fork.ofι ι' _` are isomorphic. -/
def ofιCongr {P : C} {ι ι' : P ⟶ X} {w : ι ≫ f = 0} (h : ι = ι') :
KernelFork.ofι ι w ≅ KernelFork.ofι ι' (by rw [← h, w]) :=
Cones.ext (Iso.refl _)
#align category_theory.limits.of_ι_congr CategoryTheory.Limits.ofιCongr
/-- If `F` is an equivalence, then applying `F` to a diagram indexing a (co)kernel of `f` yields
the diagram indexing the (co)kernel of `F.map f`. -/
def compNatIso {D : Type u'} [Category.{v} D] [HasZeroMorphisms D] (F : C ⥤ D) [F.IsEquivalence] :
parallelPair f 0 ⋙ F ≅ parallelPair (F.map f) 0 :=
let app (j :WalkingParallelPair) :
(parallelPair f 0 ⋙ F).obj j ≅ (parallelPair (F.map f) 0).obj j :=
match j with
| zero => Iso.refl _
| one => Iso.refl _
NatIso.ofComponents app <| by rintro ⟨i⟩ ⟨j⟩ <;> intro g <;> cases g <;> simp [app]
#align category_theory.limits.comp_nat_iso CategoryTheory.Limits.compNatIso
end
/-- If `s` is a limit kernel fork and `k : W ⟶ X` satisfies `k ≫ f = 0`, then there is some
`l : W ⟶ s.X` such that `l ≫ fork.ι s = k`. -/
def KernelFork.IsLimit.lift' {s : KernelFork f} (hs : IsLimit s) {W : C} (k : W ⟶ X)
(h : k ≫ f = 0) : { l : W ⟶ s.pt // l ≫ Fork.ι s = k } :=
⟨hs.lift <| KernelFork.ofι _ h, hs.fac _ _⟩
#align category_theory.limits.kernel_fork.is_limit.lift' CategoryTheory.Limits.KernelFork.IsLimit.lift'
/-- This is a slightly more convenient method to verify that a kernel fork is a limit cone. It
only asks for a proof of facts that carry any mathematical content -/
def isLimitAux (t : KernelFork f) (lift : ∀ s : KernelFork f, s.pt ⟶ t.pt)
(fac : ∀ s : KernelFork f, lift s ≫ t.ι = s.ι)
(uniq : ∀ (s : KernelFork f) (m : s.pt ⟶ t.pt) (_ : m ≫ t.ι = s.ι), m = lift s) : IsLimit t :=
{ lift
fac := fun s j => by
cases j
· exact fac s
· simp
uniq := fun s m w => uniq s m (w Limits.WalkingParallelPair.zero) }
#align category_theory.limits.is_limit_aux CategoryTheory.Limits.isLimitAux
/-- This is a more convenient formulation to show that a `KernelFork` constructed using
`KernelFork.ofι` is a limit cone.
-/
def KernelFork.IsLimit.ofι {W : C} (g : W ⟶ X) (eq : g ≫ f = 0)
(lift : ∀ {W' : C} (g' : W' ⟶ X) (_ : g' ≫ f = 0), W' ⟶ W)
(fac : ∀ {W' : C} (g' : W' ⟶ X) (eq' : g' ≫ f = 0), lift g' eq' ≫ g = g')
(uniq :
∀ {W' : C} (g' : W' ⟶ X) (eq' : g' ≫ f = 0) (m : W' ⟶ W) (_ : m ≫ g = g'), m = lift g' eq') :
IsLimit (KernelFork.ofι g eq) :=
isLimitAux _ (fun s => lift s.ι s.condition) (fun s => fac s.ι s.condition) fun s =>
uniq s.ι s.condition
#align category_theory.limits.kernel_fork.is_limit.of_ι CategoryTheory.Limits.KernelFork.IsLimit.ofι
/-- This is a more convenient formulation to show that a `KernelFork` of the form
`KernelFork.ofι i _` is a limit cone when we know that `i` is a monomorphism. -/
def KernelFork.IsLimit.ofι' {X Y K : C} {f : X ⟶ Y} (i : K ⟶ X) (w : i ≫ f = 0)
(h : ∀ {A : C} (k : A ⟶ X) (_ : k ≫ f = 0), { l : A ⟶ K // l ≫ i = k}) [hi : Mono i] :
IsLimit (KernelFork.ofι i w) :=
ofι _ _ (fun {A} k hk => (h k hk).1) (fun {A} k hk => (h k hk).2) (fun {A} k hk m hm => by
rw [← cancel_mono i, (h k hk).2, hm])
/-- Every kernel of `f` induces a kernel of `f ≫ g` if `g` is mono. -/
def isKernelCompMono {c : KernelFork f} (i : IsLimit c) {Z} (g : Y ⟶ Z) [hg : Mono g] {h : X ⟶ Z}
(hh : h = f ≫ g) : IsLimit (KernelFork.ofι c.ι (by simp [hh]) : KernelFork h) :=
Fork.IsLimit.mk' _ fun s =>
let s' : KernelFork f := Fork.ofι s.ι (by rw [← cancel_mono g]; simp [← hh, s.condition])
let l := KernelFork.IsLimit.lift' i s'.ι s'.condition
⟨l.1, l.2, fun hm => by
apply Fork.IsLimit.hom_ext i; rw [Fork.ι_ofι] at hm; rw [hm]; exact l.2.symm⟩
#align category_theory.limits.is_kernel_comp_mono CategoryTheory.Limits.isKernelCompMono
theorem isKernelCompMono_lift {c : KernelFork f} (i : IsLimit c) {Z} (g : Y ⟶ Z) [hg : Mono g]
{h : X ⟶ Z} (hh : h = f ≫ g) (s : KernelFork h) :
(isKernelCompMono i g hh).lift s = i.lift (Fork.ofι s.ι (by
rw [← cancel_mono g, Category.assoc, ← hh]
simp)) := rfl
#align category_theory.limits.is_kernel_comp_mono_lift CategoryTheory.Limits.isKernelCompMono_lift
/-- Every kernel of `f ≫ g` is also a kernel of `f`, as long as `c.ι ≫ f` vanishes. -/
def isKernelOfComp {W : C} (g : Y ⟶ W) (h : X ⟶ W) {c : KernelFork h} (i : IsLimit c)
(hf : c.ι ≫ f = 0) (hfg : f ≫ g = h) : IsLimit (KernelFork.ofι c.ι hf) :=
Fork.IsLimit.mk _ (fun s => i.lift (KernelFork.ofι s.ι (by simp [← hfg])))
(fun s => by simp only [KernelFork.ι_ofι, Fork.IsLimit.lift_ι]) fun s m h => by
apply Fork.IsLimit.hom_ext i; simpa using h
#align category_theory.limits.is_kernel_of_comp CategoryTheory.Limits.isKernelOfComp
/-- `X` identifies to the kernel of a zero map `X ⟶ Y`. -/
def KernelFork.IsLimit.ofId {X Y : C} (f : X ⟶ Y) (hf : f = 0) :
IsLimit (KernelFork.ofι (𝟙 X) (show 𝟙 X ≫ f = 0 by rw [hf, comp_zero])) :=
KernelFork.IsLimit.ofι _ _ (fun x _ => x) (fun _ _ => Category.comp_id _)
(fun _ _ _ hb => by simp only [← hb, Category.comp_id])
/-- Any zero object identifies to the kernel of a given monomorphisms. -/
def KernelFork.IsLimit.ofMonoOfIsZero {X Y : C} {f : X ⟶ Y} (c : KernelFork f)
(hf : Mono f) (h : IsZero c.pt) : IsLimit c :=
isLimitAux _ (fun s => 0) (fun s => by rw [zero_comp, ← cancel_mono f, zero_comp, s.condition])
(fun _ _ _ => h.eq_of_tgt _ _)
lemma KernelFork.IsLimit.isIso_ι {X Y : C} {f : X ⟶ Y} (c : KernelFork f)
(hc : IsLimit c) (hf : f = 0) : IsIso c.ι := by
let e : c.pt ≅ X := IsLimit.conePointUniqueUpToIso hc
(KernelFork.IsLimit.ofId (f : X ⟶ Y) hf)
have eq : e.inv ≫ c.ι = 𝟙 X := Fork.IsLimit.lift_ι hc
haveI : IsIso (e.inv ≫ c.ι) := by
rw [eq]
infer_instance
exact IsIso.of_isIso_comp_left e.inv c.ι
end
namespace KernelFork
variable {f} {X' Y' : C} {f' : X' ⟶ Y'}
/-- The morphism between points of kernel forks induced by a morphism
in the category of arrows. -/
def mapOfIsLimit (kf : KernelFork f) {kf' : KernelFork f'} (hf' : IsLimit kf')
(φ : Arrow.mk f ⟶ Arrow.mk f') : kf.pt ⟶ kf'.pt :=
hf'.lift (KernelFork.ofι (kf.ι ≫ φ.left) (by simp))
@[reassoc (attr := simp)]
lemma mapOfIsLimit_ι (kf : KernelFork f) {kf' : KernelFork f'} (hf' : IsLimit kf')
(φ : Arrow.mk f ⟶ Arrow.mk f') :
kf.mapOfIsLimit hf' φ ≫ kf'.ι = kf.ι ≫ φ.left :=
hf'.fac _ _
/-- The isomorphism between points of limit kernel forks induced by an isomorphism
in the category of arrows. -/
@[simps]
def mapIsoOfIsLimit {kf : KernelFork f} {kf' : KernelFork f'}
(hf : IsLimit kf) (hf' : IsLimit kf')
(φ : Arrow.mk f ≅ Arrow.mk f') : kf.pt ≅ kf'.pt where
hom := kf.mapOfIsLimit hf' φ.hom
inv := kf'.mapOfIsLimit hf φ.inv
hom_inv_id := Fork.IsLimit.hom_ext hf (by simp)
inv_hom_id := Fork.IsLimit.hom_ext hf' (by simp)
end KernelFork
section
variable [HasKernel f]
/-- The kernel of a morphism, expressed as the equalizer with the 0 morphism. -/
abbrev kernel (f : X ⟶ Y) [HasKernel f] : C :=
equalizer f 0
#align category_theory.limits.kernel CategoryTheory.Limits.kernel
/-- The map from `kernel f` into the source of `f`. -/
abbrev kernel.ι : kernel f ⟶ X :=
equalizer.ι f 0
#align category_theory.limits.kernel.ι CategoryTheory.Limits.kernel.ι
@[simp]
theorem equalizer_as_kernel : equalizer.ι f 0 = kernel.ι f := rfl
#align category_theory.limits.equalizer_as_kernel CategoryTheory.Limits.equalizer_as_kernel
@[reassoc (attr := simp)]
theorem kernel.condition : kernel.ι f ≫ f = 0 :=
KernelFork.condition _
#align category_theory.limits.kernel.condition CategoryTheory.Limits.kernel.condition
/-- The kernel built from `kernel.ι f` is limiting. -/
def kernelIsKernel : IsLimit (Fork.ofι (kernel.ι f) ((kernel.condition f).trans comp_zero.symm)) :=
IsLimit.ofIsoLimit (limit.isLimit _) (Fork.ext (Iso.refl _) (by aesop_cat))
#align category_theory.limits.kernel_is_kernel CategoryTheory.Limits.kernelIsKernel
/-- Given any morphism `k : W ⟶ X` satisfying `k ≫ f = 0`, `k` factors through `kernel.ι f`
via `kernel.lift : W ⟶ kernel f`. -/
abbrev kernel.lift {W : C} (k : W ⟶ X) (h : k ≫ f = 0) : W ⟶ kernel f :=
(kernelIsKernel f).lift (KernelFork.ofι k h)
#align category_theory.limits.kernel.lift CategoryTheory.Limits.kernel.lift
@[reassoc (attr := simp)]
theorem kernel.lift_ι {W : C} (k : W ⟶ X) (h : k ≫ f = 0) : kernel.lift f k h ≫ kernel.ι f = k :=
(kernelIsKernel f).fac (KernelFork.ofι k h) WalkingParallelPair.zero
#align category_theory.limits.kernel.lift_ι CategoryTheory.Limits.kernel.lift_ι
@[simp]
theorem kernel.lift_zero {W : C} {h} : kernel.lift f (0 : W ⟶ X) h = 0 := by
ext; simp
#align category_theory.limits.kernel.lift_zero CategoryTheory.Limits.kernel.lift_zero
instance kernel.lift_mono {W : C} (k : W ⟶ X) (h : k ≫ f = 0) [Mono k] : Mono (kernel.lift f k h) :=
⟨fun {Z} g g' w => by
replace w := w =≫ kernel.ι f
simp only [Category.assoc, kernel.lift_ι] at w
exact (cancel_mono k).1 w⟩
#align category_theory.limits.kernel.lift_mono CategoryTheory.Limits.kernel.lift_mono
/-- Any morphism `k : W ⟶ X` satisfying `k ≫ f = 0` induces a morphism `l : W ⟶ kernel f` such that
`l ≫ kernel.ι f = k`. -/
def kernel.lift' {W : C} (k : W ⟶ X) (h : k ≫ f = 0) : { l : W ⟶ kernel f // l ≫ kernel.ι f = k } :=
⟨kernel.lift f k h, kernel.lift_ι _ _ _⟩
#align category_theory.limits.kernel.lift' CategoryTheory.Limits.kernel.lift'
/-- A commuting square induces a morphism of kernels. -/
abbrev kernel.map {X' Y' : C} (f' : X' ⟶ Y') [HasKernel f'] (p : X ⟶ X') (q : Y ⟶ Y')
(w : f ≫ q = p ≫ f') : kernel f ⟶ kernel f' :=
kernel.lift f' (kernel.ι f ≫ p) (by simp [← w])
#align category_theory.limits.kernel.map CategoryTheory.Limits.kernel.map
/-- Given a commutative diagram
X --f--> Y --g--> Z
| | |
| | |
v v v
X' -f'-> Y' -g'-> Z'
with horizontal arrows composing to zero,
then we obtain a commutative square
X ---> kernel g
| |
| | kernel.map
| |
v v
X' --> kernel g'
-/
theorem kernel.lift_map {X Y Z X' Y' Z' : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasKernel g] (w : f ≫ g = 0)
(f' : X' ⟶ Y') (g' : Y' ⟶ Z') [HasKernel g'] (w' : f' ≫ g' = 0) (p : X ⟶ X') (q : Y ⟶ Y')
(r : Z ⟶ Z') (h₁ : f ≫ q = p ≫ f') (h₂ : g ≫ r = q ≫ g') :
kernel.lift g f w ≫ kernel.map g g' q r h₂ = p ≫ kernel.lift g' f' w' := by
ext; simp [h₁]
#align category_theory.limits.kernel.lift_map CategoryTheory.Limits.kernel.lift_map
/-- A commuting square of isomorphisms induces an isomorphism of kernels. -/
@[simps]
def kernel.mapIso {X' Y' : C} (f' : X' ⟶ Y') [HasKernel f'] (p : X ≅ X') (q : Y ≅ Y')
(w : f ≫ q.hom = p.hom ≫ f') : kernel f ≅ kernel f' where
hom := kernel.map f f' p.hom q.hom w
inv :=
kernel.map f' f p.inv q.inv
(by
refine (cancel_mono q.hom).1 ?_
simp [w])
#align category_theory.limits.kernel.map_iso CategoryTheory.Limits.kernel.mapIso
/-- Every kernel of the zero morphism is an isomorphism -/
instance kernel.ι_zero_isIso : IsIso (kernel.ι (0 : X ⟶ Y)) :=
equalizer.ι_of_self _
#align category_theory.limits.kernel.ι_zero_is_iso CategoryTheory.Limits.kernel.ι_zero_isIso
theorem eq_zero_of_epi_kernel [Epi (kernel.ι f)] : f = 0 :=
(cancel_epi (kernel.ι f)).1 (by simp)
#align category_theory.limits.eq_zero_of_epi_kernel CategoryTheory.Limits.eq_zero_of_epi_kernel
/-- The kernel of a zero morphism is isomorphic to the source. -/
def kernelZeroIsoSource : kernel (0 : X ⟶ Y) ≅ X :=
equalizer.isoSourceOfSelf 0
#align category_theory.limits.kernel_zero_iso_source CategoryTheory.Limits.kernelZeroIsoSource
@[simp]
theorem kernelZeroIsoSource_hom : kernelZeroIsoSource.hom = kernel.ι (0 : X ⟶ Y) := rfl
#align category_theory.limits.kernel_zero_iso_source_hom CategoryTheory.Limits.kernelZeroIsoSource_hom
@[simp]
theorem kernelZeroIsoSource_inv :
kernelZeroIsoSource.inv = kernel.lift (0 : X ⟶ Y) (𝟙 X) (by simp) := by
ext
simp [kernelZeroIsoSource]
#align category_theory.limits.kernel_zero_iso_source_inv CategoryTheory.Limits.kernelZeroIsoSource_inv
/-- If two morphisms are known to be equal, then their kernels are isomorphic. -/
def kernelIsoOfEq {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g) : kernel f ≅ kernel g :=
HasLimit.isoOfNatIso (by rw [h])
#align category_theory.limits.kernel_iso_of_eq CategoryTheory.Limits.kernelIsoOfEq
@[simp]
theorem kernelIsoOfEq_refl {h : f = f} : kernelIsoOfEq h = Iso.refl (kernel f) := by
ext
simp [kernelIsoOfEq]
#align category_theory.limits.kernel_iso_of_eq_refl CategoryTheory.Limits.kernelIsoOfEq_refl
/- Porting note: induction on Eq is trying instantiate another g... -/
@[reassoc (attr := simp)]
theorem kernelIsoOfEq_hom_comp_ι {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g) :
(kernelIsoOfEq h).hom ≫ kernel.ι g = kernel.ι f := by
cases h; simp
#align category_theory.limits.kernel_iso_of_eq_hom_comp_ι CategoryTheory.Limits.kernelIsoOfEq_hom_comp_ι
@[reassoc (attr := simp)]
theorem kernelIsoOfEq_inv_comp_ι {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g) :
(kernelIsoOfEq h).inv ≫ kernel.ι _ = kernel.ι _ := by
cases h; simp
#align category_theory.limits.kernel_iso_of_eq_inv_comp_ι CategoryTheory.Limits.kernelIsoOfEq_inv_comp_ι
@[reassoc (attr := simp)]
theorem lift_comp_kernelIsoOfEq_hom {Z} {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g)
(e : Z ⟶ X) (he) :
kernel.lift _ e he ≫ (kernelIsoOfEq h).hom = kernel.lift _ e (by simp [← h, he]) := by
cases h; simp
#align category_theory.limits.lift_comp_kernel_iso_of_eq_hom CategoryTheory.Limits.lift_comp_kernelIsoOfEq_hom
@[reassoc (attr := simp)]
theorem lift_comp_kernelIsoOfEq_inv {Z} {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g)
(e : Z ⟶ X) (he) :
kernel.lift _ e he ≫ (kernelIsoOfEq h).inv = kernel.lift _ e (by simp [h, he]) := by
cases h; simp
#align category_theory.limits.lift_comp_kernel_iso_of_eq_inv CategoryTheory.Limits.lift_comp_kernelIsoOfEq_inv
@[simp]
theorem kernelIsoOfEq_trans {f g h : X ⟶ Y} [HasKernel f] [HasKernel g] [HasKernel h] (w₁ : f = g)
(w₂ : g = h) : kernelIsoOfEq w₁ ≪≫ kernelIsoOfEq w₂ = kernelIsoOfEq (w₁.trans w₂) := by
cases w₁; cases w₂; ext; simp [kernelIsoOfEq]
#align category_theory.limits.kernel_iso_of_eq_trans CategoryTheory.Limits.kernelIsoOfEq_trans
variable {f}
theorem kernel_not_epi_of_nonzero (w : f ≠ 0) : ¬Epi (kernel.ι f) := fun _ =>
w (eq_zero_of_epi_kernel f)
#align category_theory.limits.kernel_not_epi_of_nonzero CategoryTheory.Limits.kernel_not_epi_of_nonzero
theorem kernel_not_iso_of_nonzero (w : f ≠ 0) : IsIso (kernel.ι f) → False := fun _ =>
kernel_not_epi_of_nonzero w inferInstance
#align category_theory.limits.kernel_not_iso_of_nonzero CategoryTheory.Limits.kernel_not_iso_of_nonzero
instance hasKernel_comp_mono {X Y Z : C} (f : X ⟶ Y) [HasKernel f] (g : Y ⟶ Z) [Mono g] :
HasKernel (f ≫ g) :=
⟨⟨{ cone := _
isLimit := isKernelCompMono (limit.isLimit _) g rfl }⟩⟩
#align category_theory.limits.has_kernel_comp_mono CategoryTheory.Limits.hasKernel_comp_mono
/-- When `g` is a monomorphism, the kernel of `f ≫ g` is isomorphic to the kernel of `f`.
-/
@[simps]
def kernelCompMono {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasKernel f] [Mono g] :
kernel (f ≫ g) ≅ kernel f where
hom :=
kernel.lift _ (kernel.ι _)
(by
rw [← cancel_mono g]
simp)
inv := kernel.lift _ (kernel.ι _) (by simp)
#align category_theory.limits.kernel_comp_mono CategoryTheory.Limits.kernelCompMono
#adaptation_note /-- nightly-2024-04-01 The `symm` wasn't previously necessary. -/
instance hasKernel_iso_comp {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [HasKernel g] :
HasKernel (f ≫ g) where
exists_limit :=
⟨{ cone := KernelFork.ofι (kernel.ι g ≫ inv f) (by simp)
isLimit := isLimitAux _ (fun s => kernel.lift _ (s.ι ≫ f) (by aesop_cat))
(by aesop_cat) fun s m w => by
simp_rw [← w]
symm
apply equalizer.hom_ext
simp }⟩
#align category_theory.limits.has_kernel_iso_comp CategoryTheory.Limits.hasKernel_iso_comp
/-- When `f` is an isomorphism, the kernel of `f ≫ g` is isomorphic to the kernel of `g`.
-/
@[simps]
def kernelIsIsoComp {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [HasKernel g] :
kernel (f ≫ g) ≅ kernel g where
hom := kernel.lift _ (kernel.ι _ ≫ f) (by simp)
inv := kernel.lift _ (kernel.ι _ ≫ inv f) (by simp)
#align category_theory.limits.kernel_is_iso_comp CategoryTheory.Limits.kernelIsIsoComp
end
section HasZeroObject
variable [HasZeroObject C]
open ZeroObject
/-- The morphism from the zero object determines a cone on a kernel diagram -/
def kernel.zeroKernelFork : KernelFork f where
pt := 0
π := { app := fun j => 0 }
#align category_theory.limits.kernel.zero_kernel_fork CategoryTheory.Limits.kernel.zeroKernelFork
/-- The map from the zero object is a kernel of a monomorphism -/
def kernel.isLimitConeZeroCone [Mono f] : IsLimit (kernel.zeroKernelFork f) :=
Fork.IsLimit.mk _ (fun s => 0)
(fun s => by
erw [zero_comp]
refine (zero_of_comp_mono f ?_).symm
exact KernelFork.condition _)
fun _ _ _ => zero_of_to_zero _
#align category_theory.limits.kernel.is_limit_cone_zero_cone CategoryTheory.Limits.kernel.isLimitConeZeroCone
/-- The kernel of a monomorphism is isomorphic to the zero object -/
def kernel.ofMono [HasKernel f] [Mono f] : kernel f ≅ 0 :=
Functor.mapIso (Cones.forget _) <|
IsLimit.uniqueUpToIso (limit.isLimit (parallelPair f 0)) (kernel.isLimitConeZeroCone f)
#align category_theory.limits.kernel.of_mono CategoryTheory.Limits.kernel.ofMono
/-- The kernel morphism of a monomorphism is a zero morphism -/
theorem kernel.ι_of_mono [HasKernel f] [Mono f] : kernel.ι f = 0 :=
zero_of_source_iso_zero _ (kernel.ofMono f)
#align category_theory.limits.kernel.ι_of_mono CategoryTheory.Limits.kernel.ι_of_mono
/-- If `g ≫ f = 0` implies `g = 0` for all `g`, then `0 : 0 ⟶ X` is a kernel of `f`. -/
def zeroKernelOfCancelZero {X Y : C} (f : X ⟶ Y)
(hf : ∀ (Z : C) (g : Z ⟶ X) (_ : g ≫ f = 0), g = 0) :
IsLimit (KernelFork.ofι (0 : 0 ⟶ X) (show 0 ≫ f = 0 by simp)) :=
Fork.IsLimit.mk _ (fun s => 0) (fun s => by rw [hf _ _ (KernelFork.condition s), zero_comp])
fun s m _ => by dsimp; apply HasZeroObject.to_zero_ext
#align category_theory.limits.zero_kernel_of_cancel_zero CategoryTheory.Limits.zeroKernelOfCancelZero
end HasZeroObject
section Transport
/-- If `i` is an isomorphism such that `l ≫ i.hom = f`, any kernel of `f` is a kernel of `l`. -/
def IsKernel.ofCompIso {Z : C} (l : X ⟶ Z) (i : Z ≅ Y) (h : l ≫ i.hom = f) {s : KernelFork f}
(hs : IsLimit s) :
IsLimit
(KernelFork.ofι (Fork.ι s) <| show Fork.ι s ≫ l = 0 by simp [← i.comp_inv_eq.2 h.symm]) :=
Fork.IsLimit.mk _ (fun s => hs.lift <| KernelFork.ofι (Fork.ι s) <| by simp [← h])
(fun s => by simp) fun s m h => by
apply Fork.IsLimit.hom_ext hs
simpa using h
#align category_theory.limits.is_kernel.of_comp_iso CategoryTheory.Limits.IsKernel.ofCompIso
/-- If `i` is an isomorphism such that `l ≫ i.hom = f`, the kernel of `f` is a kernel of `l`. -/
def kernel.ofCompIso [HasKernel f] {Z : C} (l : X ⟶ Z) (i : Z ≅ Y) (h : l ≫ i.hom = f) :
IsLimit
(KernelFork.ofι (kernel.ι f) <| show kernel.ι f ≫ l = 0 by simp [← i.comp_inv_eq.2 h.symm]) :=
IsKernel.ofCompIso f l i h <| limit.isLimit _
#align category_theory.limits.kernel.of_comp_iso CategoryTheory.Limits.kernel.ofCompIso
/-- If `s` is any limit kernel cone over `f` and if `i` is an isomorphism such that
`i.hom ≫ s.ι = l`, then `l` is a kernel of `f`. -/
def IsKernel.isoKernel {Z : C} (l : Z ⟶ X) {s : KernelFork f} (hs : IsLimit s) (i : Z ≅ s.pt)
(h : i.hom ≫ Fork.ι s = l) : IsLimit (KernelFork.ofι l <| show l ≫ f = 0 by simp [← h]) :=
IsLimit.ofIsoLimit hs <|
Cones.ext i.symm fun j => by
cases j
· exact (Iso.eq_inv_comp i).2 h
· dsimp; rw [← h]; simp
#align category_theory.limits.is_kernel.iso_kernel CategoryTheory.Limits.IsKernel.isoKernel
/-- If `i` is an isomorphism such that `i.hom ≫ kernel.ι f = l`, then `l` is a kernel of `f`. -/
def kernel.isoKernel [HasKernel f] {Z : C} (l : Z ⟶ X) (i : Z ≅ kernel f)
(h : i.hom ≫ kernel.ι f = l) :
IsLimit (@KernelFork.ofι _ _ _ _ _ f _ l <| by simp [← h]) :=
IsKernel.isoKernel f l (limit.isLimit _) i h
#align category_theory.limits.kernel.iso_kernel CategoryTheory.Limits.kernel.isoKernel
end Transport
section
variable (X Y)
/-- The kernel morphism of a zero morphism is an isomorphism -/
theorem kernel.ι_of_zero : IsIso (kernel.ι (0 : X ⟶ Y)) :=
equalizer.ι_of_self _
#align category_theory.limits.kernel.ι_of_zero CategoryTheory.Limits.kernel.ι_of_zero
end
section
/-- A cokernel cofork is just a cofork where the second morphism is a zero morphism. -/
abbrev CokernelCofork :=
Cofork f 0
#align category_theory.limits.cokernel_cofork CategoryTheory.Limits.CokernelCofork
variable {f}
@[reassoc (attr := simp)]
theorem CokernelCofork.condition (s : CokernelCofork f) : f ≫ s.π = 0 := by
rw [Cofork.condition, zero_comp]
#align category_theory.limits.cokernel_cofork.condition CategoryTheory.Limits.CokernelCofork.condition
-- Porting note (#10618): simp can prove this, removed simp tag
| Mathlib/CategoryTheory/Limits/Shapes/Kernels.lean | 581 | 582 | theorem CokernelCofork.π_eq_zero (s : CokernelCofork f) : s.ι.app zero = 0 := by |
simp [Cofork.app_zero_eq_comp_π_right]
|
/-
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, Jakob von Raumer
-/
import Mathlib.CategoryTheory.Functor.Trifunctor
import Mathlib.CategoryTheory.Products.Basic
#align_import category_theory.monoidal.category from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Monoidal categories
A monoidal category is a category equipped with a tensor product, unitors, and an associator.
In the definition, we provide the tensor product as a pair of functions
* `tensorObj : C → C → C`
* `tensorHom : (X₁ ⟶ Y₁) → (X₂ ⟶ Y₂) → ((X₁ ⊗ X₂) ⟶ (Y₁ ⊗ Y₂))`
and allow use of the overloaded notation `⊗` for both.
The unitors and associator are provided componentwise.
The tensor product can be expressed as a functor via `tensor : C × C ⥤ C`.
The unitors and associator are gathered together as natural
isomorphisms in `leftUnitor_nat_iso`, `rightUnitor_nat_iso` and `associator_nat_iso`.
Some consequences of the definition are proved in other files after proving the coherence theorem,
e.g. `(λ_ (𝟙_ C)).hom = (ρ_ (𝟙_ C)).hom` in `CategoryTheory.Monoidal.CoherenceLemmas`.
## Implementation notes
In the definition of monoidal categories, we also provide the whiskering operators:
* `whiskerLeft (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂) : X ⊗ Y₁ ⟶ X ⊗ Y₂`, denoted by `X ◁ f`,
* `whiskerRight {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C) : X₁ ⊗ Y ⟶ X₂ ⊗ Y`, denoted by `f ▷ Y`.
These are products of an object and a morphism (the terminology "whiskering"
is borrowed from 2-category theory). The tensor product of morphisms `tensorHom` can be defined
in terms of the whiskerings. There are two possible such definitions, which are related by
the exchange property of the whiskerings. These two definitions are accessed by `tensorHom_def`
and `tensorHom_def'`. By default, `tensorHom` is defined so that `tensorHom_def` holds
definitionally.
If you want to provide `tensorHom` and define `whiskerLeft` and `whiskerRight` in terms of it,
you can use the alternative constructor `CategoryTheory.MonoidalCategory.ofTensorHom`.
The whiskerings are useful when considering simp-normal forms of morphisms in monoidal categories.
### Simp-normal form for morphisms
Rewriting involving associators and unitors could be very complicated. We try to ease this
complexity by putting carefully chosen simp lemmas that rewrite any morphisms into the simp-normal
form defined below. Rewriting into simp-normal form is especially useful in preprocessing
performed by the `coherence` tactic.
The simp-normal form of morphisms is defined to be an expression that has the minimal number of
parentheses. More precisely,
1. it is a composition of morphisms like `f₁ ≫ f₂ ≫ f₃ ≫ f₄ ≫ f₅` such that each `fᵢ` is
either a structural morphisms (morphisms made up only of identities, associators, unitors)
or non-structural morphisms, and
2. each non-structural morphism in the composition is of the form `X₁ ◁ X₂ ◁ X₃ ◁ f ▷ X₄ ▷ X₅`,
where each `Xᵢ` is a object that is not the identity or a tensor and `f` is a non-structural
morphisms that is not the identity or a composite.
Note that `X₁ ◁ X₂ ◁ X₃ ◁ f ▷ X₄ ▷ X₅` is actually `X₁ ◁ (X₂ ◁ (X₃ ◁ ((f ▷ X₄) ▷ X₅)))`.
Currently, the simp lemmas don't rewrite `𝟙 X ⊗ f` and `f ⊗ 𝟙 Y` into `X ◁ f` and `f ▷ Y`,
respectively, since it requires a huge refactoring. We hope to add these simp lemmas soon.
## References
* Tensor categories, Etingof, Gelaki, Nikshych, Ostrik,
http://www-math.mit.edu/~etingof/egnobookfinal.pdf
* <https://stacks.math.columbia.edu/tag/0FFK>.
-/
universe v u
open CategoryTheory.Category
open CategoryTheory.Iso
namespace CategoryTheory
/-- Auxiliary structure to carry only the data fields of (and provide notation for)
`MonoidalCategory`. -/
class MonoidalCategoryStruct (C : Type u) [𝒞 : Category.{v} C] where
/-- curried tensor product of objects -/
tensorObj : C → C → C
/-- left whiskering for morphisms -/
whiskerLeft (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂) : tensorObj X Y₁ ⟶ tensorObj X Y₂
/-- right whiskering for morphisms -/
whiskerRight {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C) : tensorObj X₁ Y ⟶ tensorObj X₂ Y
/-- Tensor product of identity maps is the identity: `(𝟙 X₁ ⊗ 𝟙 X₂) = 𝟙 (X₁ ⊗ X₂)` -/
-- By default, it is defined in terms of whiskerings.
tensorHom {X₁ Y₁ X₂ Y₂ : C} (f : X₁ ⟶ Y₁) (g: X₂ ⟶ Y₂) : (tensorObj X₁ X₂ ⟶ tensorObj Y₁ Y₂) :=
whiskerRight f X₂ ≫ whiskerLeft Y₁ g
/-- The tensor unity in the monoidal structure `𝟙_ C` -/
tensorUnit : C
/-- The associator isomorphism `(X ⊗ Y) ⊗ Z ≃ X ⊗ (Y ⊗ Z)` -/
associator : ∀ X Y Z : C, tensorObj (tensorObj X Y) Z ≅ tensorObj X (tensorObj Y Z)
/-- The left unitor: `𝟙_ C ⊗ X ≃ X` -/
leftUnitor : ∀ X : C, tensorObj tensorUnit X ≅ X
/-- The right unitor: `X ⊗ 𝟙_ C ≃ X` -/
rightUnitor : ∀ X : C, tensorObj X tensorUnit ≅ X
namespace MonoidalCategory
export MonoidalCategoryStruct
(tensorObj whiskerLeft whiskerRight tensorHom tensorUnit associator leftUnitor rightUnitor)
end MonoidalCategory
namespace MonoidalCategory
/-- Notation for `tensorObj`, the tensor product of objects in a monoidal category -/
scoped infixr:70 " ⊗ " => MonoidalCategoryStruct.tensorObj
/-- Notation for the `whiskerLeft` operator of monoidal categories -/
scoped infixr:81 " ◁ " => MonoidalCategoryStruct.whiskerLeft
/-- Notation for the `whiskerRight` operator of monoidal categories -/
scoped infixl:81 " ▷ " => MonoidalCategoryStruct.whiskerRight
/-- Notation for `tensorHom`, the tensor product of morphisms in a monoidal category -/
scoped infixr:70 " ⊗ " => MonoidalCategoryStruct.tensorHom
/-- Notation for `tensorUnit`, the two-sided identity of `⊗` -/
scoped notation "𝟙_ " C:max => (MonoidalCategoryStruct.tensorUnit : C)
open Lean PrettyPrinter.Delaborator SubExpr in
/-- Used to ensure that `𝟙_` notation is used, as the ascription makes this not automatic. -/
@[delab app.CategoryTheory.MonoidalCategoryStruct.tensorUnit]
def delabTensorUnit : Delab := whenPPOption getPPNotation <| withOverApp 3 do
let e ← getExpr
guard <| e.isAppOfArity ``MonoidalCategoryStruct.tensorUnit 3
let C ← withNaryArg 0 delab
`(𝟙_ $C)
/-- Notation for the monoidal `associator`: `(X ⊗ Y) ⊗ Z ≃ X ⊗ (Y ⊗ Z)` -/
scoped notation "α_" => MonoidalCategoryStruct.associator
/-- Notation for the `leftUnitor`: `𝟙_C ⊗ X ≃ X` -/
scoped notation "λ_" => MonoidalCategoryStruct.leftUnitor
/-- Notation for the `rightUnitor`: `X ⊗ 𝟙_C ≃ X` -/
scoped notation "ρ_" => MonoidalCategoryStruct.rightUnitor
end MonoidalCategory
open MonoidalCategory
/--
In a monoidal category, we can take the tensor product of objects, `X ⊗ Y` and of morphisms `f ⊗ g`.
Tensor product does not need to be strictly associative on objects, but there is a
specified associator, `α_ X Y Z : (X ⊗ Y) ⊗ Z ≅ X ⊗ (Y ⊗ Z)`. There is a tensor unit `𝟙_ C`,
with specified left and right unitor isomorphisms `λ_ X : 𝟙_ C ⊗ X ≅ X` and `ρ_ X : X ⊗ 𝟙_ C ≅ X`.
These associators and unitors satisfy the pentagon and triangle equations.
See <https://stacks.math.columbia.edu/tag/0FFK>.
-/
-- Porting note: The Mathport did not translate the temporary notation
class MonoidalCategory (C : Type u) [𝒞 : Category.{v} C] extends MonoidalCategoryStruct C where
tensorHom_def {X₁ Y₁ X₂ Y₂ : C} (f : X₁ ⟶ Y₁) (g: X₂ ⟶ Y₂) :
f ⊗ g = (f ▷ X₂) ≫ (Y₁ ◁ g) := by
aesop_cat
/-- Tensor product of identity maps is the identity: `(𝟙 X₁ ⊗ 𝟙 X₂) = 𝟙 (X₁ ⊗ X₂)` -/
tensor_id : ∀ X₁ X₂ : C, 𝟙 X₁ ⊗ 𝟙 X₂ = 𝟙 (X₁ ⊗ X₂) := by aesop_cat
/--
Composition of tensor products is tensor product of compositions:
`(f₁ ⊗ g₁) ∘ (f₂ ⊗ g₂) = (f₁ ∘ f₂) ⊗ (g₁ ⊗ g₂)`
-/
tensor_comp :
∀ {X₁ Y₁ Z₁ X₂ Y₂ Z₂ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (g₁ : Y₁ ⟶ Z₁) (g₂ : Y₂ ⟶ Z₂),
(f₁ ≫ g₁) ⊗ (f₂ ≫ g₂) = (f₁ ⊗ f₂) ≫ (g₁ ⊗ g₂) := by
aesop_cat
whiskerLeft_id : ∀ (X Y : C), X ◁ 𝟙 Y = 𝟙 (X ⊗ Y) := by
aesop_cat
id_whiskerRight : ∀ (X Y : C), 𝟙 X ▷ Y = 𝟙 (X ⊗ Y) := by
aesop_cat
/-- Naturality of the associator isomorphism: `(f₁ ⊗ f₂) ⊗ f₃ ≃ f₁ ⊗ (f₂ ⊗ f₃)` -/
associator_naturality :
∀ {X₁ X₂ X₃ Y₁ Y₂ Y₃ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (f₃ : X₃ ⟶ Y₃),
((f₁ ⊗ f₂) ⊗ f₃) ≫ (α_ Y₁ Y₂ Y₃).hom = (α_ X₁ X₂ X₃).hom ≫ (f₁ ⊗ (f₂ ⊗ f₃)) := by
aesop_cat
/--
Naturality of the left unitor, commutativity of `𝟙_ C ⊗ X ⟶ 𝟙_ C ⊗ Y ⟶ Y` and `𝟙_ C ⊗ X ⟶ X ⟶ Y`
-/
leftUnitor_naturality :
∀ {X Y : C} (f : X ⟶ Y), 𝟙_ _ ◁ f ≫ (λ_ Y).hom = (λ_ X).hom ≫ f := by
aesop_cat
/--
Naturality of the right unitor: commutativity of `X ⊗ 𝟙_ C ⟶ Y ⊗ 𝟙_ C ⟶ Y` and `X ⊗ 𝟙_ C ⟶ X ⟶ Y`
-/
rightUnitor_naturality :
∀ {X Y : C} (f : X ⟶ Y), f ▷ 𝟙_ _ ≫ (ρ_ Y).hom = (ρ_ X).hom ≫ f := by
aesop_cat
/--
The pentagon identity relating the isomorphism between `X ⊗ (Y ⊗ (Z ⊗ W))` and `((X ⊗ Y) ⊗ Z) ⊗ W`
-/
pentagon :
∀ W X Y Z : C,
(α_ W X Y).hom ▷ Z ≫ (α_ W (X ⊗ Y) Z).hom ≫ W ◁ (α_ X Y Z).hom =
(α_ (W ⊗ X) Y Z).hom ≫ (α_ W X (Y ⊗ Z)).hom := by
aesop_cat
/--
The identity relating the isomorphisms between `X ⊗ (𝟙_ C ⊗ Y)`, `(X ⊗ 𝟙_ C) ⊗ Y` and `X ⊗ Y`
-/
triangle :
∀ X Y : C, (α_ X (𝟙_ _) Y).hom ≫ X ◁ (λ_ Y).hom = (ρ_ X).hom ▷ Y := by
aesop_cat
#align category_theory.monoidal_category CategoryTheory.MonoidalCategory
attribute [reassoc] MonoidalCategory.tensorHom_def
attribute [reassoc, simp] MonoidalCategory.whiskerLeft_id
attribute [reassoc, simp] MonoidalCategory.id_whiskerRight
attribute [reassoc] MonoidalCategory.tensor_comp
attribute [simp] MonoidalCategory.tensor_comp
attribute [reassoc] MonoidalCategory.associator_naturality
attribute [reassoc] MonoidalCategory.leftUnitor_naturality
attribute [reassoc] MonoidalCategory.rightUnitor_naturality
attribute [reassoc (attr := simp)] MonoidalCategory.pentagon
attribute [reassoc (attr := simp)] MonoidalCategory.triangle
namespace MonoidalCategory
variable {C : Type u} [𝒞 : Category.{v} C] [MonoidalCategory C]
@[simp]
theorem id_tensorHom (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂) :
𝟙 X ⊗ f = X ◁ f := by
simp [tensorHom_def]
@[simp]
theorem tensorHom_id {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C) :
f ⊗ 𝟙 Y = f ▷ Y := by
simp [tensorHom_def]
@[reassoc, simp]
theorem whiskerLeft_comp (W : C) {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) :
W ◁ (f ≫ g) = W ◁ f ≫ W ◁ g := by
simp only [← id_tensorHom, ← tensor_comp, comp_id]
@[reassoc, simp]
theorem id_whiskerLeft {X Y : C} (f : X ⟶ Y) :
𝟙_ C ◁ f = (λ_ X).hom ≫ f ≫ (λ_ Y).inv := by
rw [← assoc, ← leftUnitor_naturality]; simp [id_tensorHom]
#align category_theory.monoidal_category.left_unitor_conjugation CategoryTheory.MonoidalCategory.id_whiskerLeft
@[reassoc, simp]
theorem tensor_whiskerLeft (X Y : C) {Z Z' : C} (f : Z ⟶ Z') :
(X ⊗ Y) ◁ f = (α_ X Y Z).hom ≫ X ◁ Y ◁ f ≫ (α_ X Y Z').inv := by
simp only [← id_tensorHom, ← tensorHom_id]
rw [← assoc, ← associator_naturality]
simp
@[reassoc, simp]
theorem comp_whiskerRight {W X Y : C} (f : W ⟶ X) (g : X ⟶ Y) (Z : C) :
(f ≫ g) ▷ Z = f ▷ Z ≫ g ▷ Z := by
simp only [← tensorHom_id, ← tensor_comp, id_comp]
@[reassoc, simp]
theorem whiskerRight_id {X Y : C} (f : X ⟶ Y) :
f ▷ 𝟙_ C = (ρ_ X).hom ≫ f ≫ (ρ_ Y).inv := by
rw [← assoc, ← rightUnitor_naturality]; simp [tensorHom_id]
#align category_theory.monoidal_category.right_unitor_conjugation CategoryTheory.MonoidalCategory.whiskerRight_id
@[reassoc, simp]
theorem whiskerRight_tensor {X X' : C} (f : X ⟶ X') (Y Z : C) :
f ▷ (Y ⊗ Z) = (α_ X Y Z).inv ≫ f ▷ Y ▷ Z ≫ (α_ X' Y Z).hom := by
simp only [← id_tensorHom, ← tensorHom_id]
rw [associator_naturality]
simp [tensor_id]
@[reassoc, simp]
theorem whisker_assoc (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) :
(X ◁ f) ▷ Z = (α_ X Y Z).hom ≫ X ◁ f ▷ Z ≫ (α_ X Y' Z).inv := by
simp only [← id_tensorHom, ← tensorHom_id]
rw [← assoc, ← associator_naturality]
simp
@[reassoc]
theorem whisker_exchange {W X Y Z : C} (f : W ⟶ X) (g : Y ⟶ Z) :
W ◁ g ≫ f ▷ Z = f ▷ Y ≫ X ◁ g := by
simp only [← id_tensorHom, ← tensorHom_id, ← tensor_comp, id_comp, comp_id]
@[reassoc]
theorem tensorHom_def' {X₁ Y₁ X₂ Y₂ : C} (f : X₁ ⟶ Y₁) (g : X₂ ⟶ Y₂) :
f ⊗ g = X₁ ◁ g ≫ f ▷ Y₂ :=
whisker_exchange f g ▸ tensorHom_def f g
end MonoidalCategory
open scoped MonoidalCategory
open MonoidalCategory
variable {C : Type u} [𝒞 : Category.{v} C] [MonoidalCategory C]
namespace MonoidalCategory
@[reassoc (attr := simp)]
theorem whiskerLeft_hom_inv (X : C) {Y Z : C} (f : Y ≅ Z) :
X ◁ f.hom ≫ X ◁ f.inv = 𝟙 (X ⊗ Y) := by
rw [← whiskerLeft_comp, hom_inv_id, whiskerLeft_id]
@[reassoc (attr := simp)]
theorem hom_inv_whiskerRight {X Y : C} (f : X ≅ Y) (Z : C) :
f.hom ▷ Z ≫ f.inv ▷ Z = 𝟙 (X ⊗ Z) := by
rw [← comp_whiskerRight, hom_inv_id, id_whiskerRight]
@[reassoc (attr := simp)]
theorem whiskerLeft_inv_hom (X : C) {Y Z : C} (f : Y ≅ Z) :
X ◁ f.inv ≫ X ◁ f.hom = 𝟙 (X ⊗ Z) := by
rw [← whiskerLeft_comp, inv_hom_id, whiskerLeft_id]
@[reassoc (attr := simp)]
theorem inv_hom_whiskerRight {X Y : C} (f : X ≅ Y) (Z : C) :
f.inv ▷ Z ≫ f.hom ▷ Z = 𝟙 (Y ⊗ Z) := by
rw [← comp_whiskerRight, inv_hom_id, id_whiskerRight]
@[reassoc (attr := simp)]
theorem whiskerLeft_hom_inv' (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] :
X ◁ f ≫ X ◁ inv f = 𝟙 (X ⊗ Y) := by
rw [← whiskerLeft_comp, IsIso.hom_inv_id, whiskerLeft_id]
@[reassoc (attr := simp)]
theorem hom_inv_whiskerRight' {X Y : C} (f : X ⟶ Y) [IsIso f] (Z : C) :
f ▷ Z ≫ inv f ▷ Z = 𝟙 (X ⊗ Z) := by
rw [← comp_whiskerRight, IsIso.hom_inv_id, id_whiskerRight]
@[reassoc (attr := simp)]
theorem whiskerLeft_inv_hom' (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] :
X ◁ inv f ≫ X ◁ f = 𝟙 (X ⊗ Z) := by
rw [← whiskerLeft_comp, IsIso.inv_hom_id, whiskerLeft_id]
@[reassoc (attr := simp)]
theorem inv_hom_whiskerRight' {X Y : C} (f : X ⟶ Y) [IsIso f] (Z : C) :
inv f ▷ Z ≫ f ▷ Z = 𝟙 (Y ⊗ Z) := by
rw [← comp_whiskerRight, IsIso.inv_hom_id, id_whiskerRight]
/-- The left whiskering of an isomorphism is an isomorphism. -/
@[simps]
def whiskerLeftIso (X : C) {Y Z : C} (f : Y ≅ Z) : X ⊗ Y ≅ X ⊗ Z where
hom := X ◁ f.hom
inv := X ◁ f.inv
instance whiskerLeft_isIso (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] : IsIso (X ◁ f) :=
(whiskerLeftIso X (asIso f)).isIso_hom
@[simp]
theorem inv_whiskerLeft (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] :
inv (X ◁ f) = X ◁ inv f := by
aesop_cat
@[simp]
lemma whiskerLeftIso_refl (W X : C) :
whiskerLeftIso W (Iso.refl X) = Iso.refl (W ⊗ X) :=
Iso.ext (whiskerLeft_id W X)
@[simp]
lemma whiskerLeftIso_trans (W : C) {X Y Z : C} (f : X ≅ Y) (g : Y ≅ Z) :
whiskerLeftIso W (f ≪≫ g) = whiskerLeftIso W f ≪≫ whiskerLeftIso W g :=
Iso.ext (whiskerLeft_comp W f.hom g.hom)
@[simp]
lemma whiskerLeftIso_symm (W : C) {X Y : C} (f : X ≅ Y) :
(whiskerLeftIso W f).symm = whiskerLeftIso W f.symm := rfl
/-- The right whiskering of an isomorphism is an isomorphism. -/
@[simps!]
def whiskerRightIso {X Y : C} (f : X ≅ Y) (Z : C) : X ⊗ Z ≅ Y ⊗ Z where
hom := f.hom ▷ Z
inv := f.inv ▷ Z
instance whiskerRight_isIso {X Y : C} (f : X ⟶ Y) (Z : C) [IsIso f] : IsIso (f ▷ Z) :=
(whiskerRightIso (asIso f) Z).isIso_hom
@[simp]
theorem inv_whiskerRight {X Y : C} (f : X ⟶ Y) (Z : C) [IsIso f] :
inv (f ▷ Z) = inv f ▷ Z := by
aesop_cat
@[simp]
lemma whiskerRightIso_refl (X W : C) :
whiskerRightIso (Iso.refl X) W = Iso.refl (X ⊗ W) :=
Iso.ext (id_whiskerRight X W)
@[simp]
lemma whiskerRightIso_trans {X Y Z : C} (f : X ≅ Y) (g : Y ≅ Z) (W : C) :
whiskerRightIso (f ≪≫ g) W = whiskerRightIso f W ≪≫ whiskerRightIso g W :=
Iso.ext (comp_whiskerRight f.hom g.hom W)
@[simp]
lemma whiskerRightIso_symm {X Y : C} (f : X ≅ Y) (W : C) :
(whiskerRightIso f W).symm = whiskerRightIso f.symm W := rfl
end MonoidalCategory
/-- The tensor product of two isomorphisms is an isomorphism. -/
@[simps]
def tensorIso {C : Type u} {X Y X' Y' : C} [Category.{v} C] [MonoidalCategory.{v} C] (f : X ≅ Y)
(g : X' ≅ Y') : X ⊗ X' ≅ Y ⊗ Y' where
hom := f.hom ⊗ g.hom
inv := f.inv ⊗ g.inv
hom_inv_id := by rw [← tensor_comp, Iso.hom_inv_id, Iso.hom_inv_id, ← tensor_id]
inv_hom_id := by rw [← tensor_comp, Iso.inv_hom_id, Iso.inv_hom_id, ← tensor_id]
#align category_theory.tensor_iso CategoryTheory.tensorIso
/-- Notation for `tensorIso`, the tensor product of isomorphisms -/
infixr:70 " ⊗ " => tensorIso
namespace MonoidalCategory
section
variable {C : Type u} [Category.{v} C] [MonoidalCategory.{v} C]
instance tensor_isIso {W X Y Z : C} (f : W ⟶ X) [IsIso f] (g : Y ⟶ Z) [IsIso g] : IsIso (f ⊗ g) :=
(asIso f ⊗ asIso g).isIso_hom
#align category_theory.monoidal_category.tensor_is_iso CategoryTheory.MonoidalCategory.tensor_isIso
@[simp]
theorem inv_tensor {W X Y Z : C} (f : W ⟶ X) [IsIso f] (g : Y ⟶ Z) [IsIso g] :
inv (f ⊗ g) = inv f ⊗ inv g := by
simp [tensorHom_def ,whisker_exchange]
#align category_theory.monoidal_category.inv_tensor CategoryTheory.MonoidalCategory.inv_tensor
variable {U V W X Y Z : C}
theorem whiskerLeft_dite {P : Prop} [Decidable P]
(X : C) {Y Z : C} (f : P → (Y ⟶ Z)) (f' : ¬P → (Y ⟶ Z)) :
X ◁ (if h : P then f h else f' h) = if h : P then X ◁ f h else X ◁ f' h := by
split_ifs <;> rfl
theorem dite_whiskerRight {P : Prop} [Decidable P]
{X Y : C} (f : P → (X ⟶ Y)) (f' : ¬P → (X ⟶ Y)) (Z : C):
(if h : P then f h else f' h) ▷ Z = if h : P then f h ▷ Z else f' h ▷ Z := by
split_ifs <;> rfl
theorem tensor_dite {P : Prop} [Decidable P] {W X Y Z : C} (f : W ⟶ X) (g : P → (Y ⟶ Z))
(g' : ¬P → (Y ⟶ Z)) : (f ⊗ if h : P then g h else g' h) =
if h : P then f ⊗ g h else f ⊗ g' h := by split_ifs <;> rfl
#align category_theory.monoidal_category.tensor_dite CategoryTheory.MonoidalCategory.tensor_dite
theorem dite_tensor {P : Prop} [Decidable P] {W X Y Z : C} (f : W ⟶ X) (g : P → (Y ⟶ Z))
(g' : ¬P → (Y ⟶ Z)) : (if h : P then g h else g' h) ⊗ f =
if h : P then g h ⊗ f else g' h ⊗ f := by split_ifs <;> rfl
#align category_theory.monoidal_category.dite_tensor CategoryTheory.MonoidalCategory.dite_tensor
@[simp]
theorem whiskerLeft_eqToHom (X : C) {Y Z : C} (f : Y = Z) :
X ◁ eqToHom f = eqToHom (congr_arg₂ tensorObj rfl f) := by
cases f
simp only [whiskerLeft_id, eqToHom_refl]
@[simp]
theorem eqToHom_whiskerRight {X Y : C} (f : X = Y) (Z : C) :
eqToHom f ▷ Z = eqToHom (congr_arg₂ tensorObj f rfl) := by
cases f
simp only [id_whiskerRight, eqToHom_refl]
@[reassoc]
theorem associator_naturality_left {X X' : C} (f : X ⟶ X') (Y Z : C) :
f ▷ Y ▷ Z ≫ (α_ X' Y Z).hom = (α_ X Y Z).hom ≫ f ▷ (Y ⊗ Z) := by simp
@[reassoc]
theorem associator_inv_naturality_left {X X' : C} (f : X ⟶ X') (Y Z : C) :
f ▷ (Y ⊗ Z) ≫ (α_ X' Y Z).inv = (α_ X Y Z).inv ≫ f ▷ Y ▷ Z := by simp
@[reassoc]
theorem whiskerRight_tensor_symm {X X' : C} (f : X ⟶ X') (Y Z : C) :
f ▷ Y ▷ Z = (α_ X Y Z).hom ≫ f ▷ (Y ⊗ Z) ≫ (α_ X' Y Z).inv := by simp
@[reassoc]
theorem associator_naturality_middle (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) :
(X ◁ f) ▷ Z ≫ (α_ X Y' Z).hom = (α_ X Y Z).hom ≫ X ◁ f ▷ Z := by simp
@[reassoc]
theorem associator_inv_naturality_middle (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) :
X ◁ f ▷ Z ≫ (α_ X Y' Z).inv = (α_ X Y Z).inv ≫ (X ◁ f) ▷ Z := by simp
@[reassoc]
theorem whisker_assoc_symm (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) :
X ◁ f ▷ Z = (α_ X Y Z).inv ≫ (X ◁ f) ▷ Z ≫ (α_ X Y' Z).hom := by simp
@[reassoc]
theorem associator_naturality_right (X Y : C) {Z Z' : C} (f : Z ⟶ Z') :
(X ⊗ Y) ◁ f ≫ (α_ X Y Z').hom = (α_ X Y Z).hom ≫ X ◁ Y ◁ f := by simp
@[reassoc]
theorem associator_inv_naturality_right (X Y : C) {Z Z' : C} (f : Z ⟶ Z') :
X ◁ Y ◁ f ≫ (α_ X Y Z').inv = (α_ X Y Z).inv ≫ (X ⊗ Y) ◁ f := by simp
@[reassoc]
theorem tensor_whiskerLeft_symm (X Y : C) {Z Z' : C} (f : Z ⟶ Z') :
X ◁ Y ◁ f = (α_ X Y Z).inv ≫ (X ⊗ Y) ◁ f ≫ (α_ X Y Z').hom := by simp
@[reassoc]
theorem leftUnitor_inv_naturality {X Y : C} (f : X ⟶ Y) :
f ≫ (λ_ Y).inv = (λ_ X).inv ≫ _ ◁ f := by simp
#align category_theory.monoidal_category.left_unitor_inv_naturality CategoryTheory.MonoidalCategory.leftUnitor_inv_naturality
@[reassoc]
theorem id_whiskerLeft_symm {X X' : C} (f : X ⟶ X') :
f = (λ_ X).inv ≫ 𝟙_ C ◁ f ≫ (λ_ X').hom := by
simp only [id_whiskerLeft, assoc, inv_hom_id, comp_id, inv_hom_id_assoc]
@[reassoc]
theorem rightUnitor_inv_naturality {X X' : C} (f : X ⟶ X') :
f ≫ (ρ_ X').inv = (ρ_ X).inv ≫ f ▷ _ := by simp
#align category_theory.monoidal_category.right_unitor_inv_naturality CategoryTheory.MonoidalCategory.rightUnitor_inv_naturality
@[reassoc]
theorem whiskerRight_id_symm {X Y : C} (f : X ⟶ Y) :
f = (ρ_ X).inv ≫ f ▷ 𝟙_ C ≫ (ρ_ Y).hom := by
simp
theorem whiskerLeft_iff {X Y : C} (f g : X ⟶ Y) : 𝟙_ C ◁ f = 𝟙_ C ◁ g ↔ f = g := by simp
theorem whiskerRight_iff {X Y : C} (f g : X ⟶ Y) : f ▷ 𝟙_ C = g ▷ 𝟙_ C ↔ f = g := by simp
/-! The lemmas in the next section are true by coherence,
but we prove them directly as they are used in proving the coherence theorem. -/
section
@[reassoc (attr := simp)]
theorem pentagon_inv :
W ◁ (α_ X Y Z).inv ≫ (α_ W (X ⊗ Y) Z).inv ≫ (α_ W X Y).inv ▷ Z =
(α_ W X (Y ⊗ Z)).inv ≫ (α_ (W ⊗ X) Y Z).inv :=
eq_of_inv_eq_inv (by simp)
#align category_theory.monoidal_category.pentagon_inv CategoryTheory.MonoidalCategory.pentagon_inv
@[reassoc (attr := simp)]
theorem pentagon_inv_inv_hom_hom_inv :
(α_ W (X ⊗ Y) Z).inv ≫ (α_ W X Y).inv ▷ Z ≫ (α_ (W ⊗ X) Y Z).hom =
W ◁ (α_ X Y Z).hom ≫ (α_ W X (Y ⊗ Z)).inv := by
rw [← cancel_epi (W ◁ (α_ X Y Z).inv), ← cancel_mono (α_ (W ⊗ X) Y Z).inv]
simp
@[reassoc (attr := simp)]
theorem pentagon_inv_hom_hom_hom_inv :
(α_ (W ⊗ X) Y Z).inv ≫ (α_ W X Y).hom ▷ Z ≫ (α_ W (X ⊗ Y) Z).hom =
(α_ W X (Y ⊗ Z)).hom ≫ W ◁ (α_ X Y Z).inv :=
eq_of_inv_eq_inv (by simp)
@[reassoc (attr := simp)]
theorem pentagon_hom_inv_inv_inv_inv :
W ◁ (α_ X Y Z).hom ≫ (α_ W X (Y ⊗ Z)).inv ≫ (α_ (W ⊗ X) Y Z).inv =
(α_ W (X ⊗ Y) Z).inv ≫ (α_ W X Y).inv ▷ Z := by
simp [← cancel_epi (W ◁ (α_ X Y Z).inv)]
@[reassoc (attr := simp)]
theorem pentagon_hom_hom_inv_hom_hom :
(α_ (W ⊗ X) Y Z).hom ≫ (α_ W X (Y ⊗ Z)).hom ≫ W ◁ (α_ X Y Z).inv =
(α_ W X Y).hom ▷ Z ≫ (α_ W (X ⊗ Y) Z).hom :=
eq_of_inv_eq_inv (by simp)
@[reassoc (attr := simp)]
theorem pentagon_hom_inv_inv_inv_hom :
(α_ W X (Y ⊗ Z)).hom ≫ W ◁ (α_ X Y Z).inv ≫ (α_ W (X ⊗ Y) Z).inv =
(α_ (W ⊗ X) Y Z).inv ≫ (α_ W X Y).hom ▷ Z := by
rw [← cancel_epi (α_ W X (Y ⊗ Z)).inv, ← cancel_mono ((α_ W X Y).inv ▷ Z)]
simp
@[reassoc (attr := simp)]
theorem pentagon_hom_hom_inv_inv_hom :
(α_ W (X ⊗ Y) Z).hom ≫ W ◁ (α_ X Y Z).hom ≫ (α_ W X (Y ⊗ Z)).inv =
(α_ W X Y).inv ▷ Z ≫ (α_ (W ⊗ X) Y Z).hom :=
eq_of_inv_eq_inv (by simp)
@[reassoc (attr := simp)]
theorem pentagon_inv_hom_hom_hom_hom :
(α_ W X Y).inv ▷ Z ≫ (α_ (W ⊗ X) Y Z).hom ≫ (α_ W X (Y ⊗ Z)).hom =
(α_ W (X ⊗ Y) Z).hom ≫ W ◁ (α_ X Y Z).hom := by
simp [← cancel_epi ((α_ W X Y).hom ▷ Z)]
@[reassoc (attr := simp)]
theorem pentagon_inv_inv_hom_inv_inv :
(α_ W X (Y ⊗ Z)).inv ≫ (α_ (W ⊗ X) Y Z).inv ≫ (α_ W X Y).hom ▷ Z =
W ◁ (α_ X Y Z).inv ≫ (α_ W (X ⊗ Y) Z).inv :=
eq_of_inv_eq_inv (by simp)
@[reassoc (attr := simp)]
theorem triangle_assoc_comp_right (X Y : C) :
(α_ X (𝟙_ C) Y).inv ≫ ((ρ_ X).hom ▷ Y) = X ◁ (λ_ Y).hom := by
rw [← triangle, Iso.inv_hom_id_assoc]
#align category_theory.monoidal_category.triangle_assoc_comp_right CategoryTheory.MonoidalCategory.triangle_assoc_comp_right
@[reassoc (attr := simp)]
theorem triangle_assoc_comp_right_inv (X Y : C) :
(ρ_ X).inv ▷ Y ≫ (α_ X (𝟙_ C) Y).hom = X ◁ (λ_ Y).inv := by
simp [← cancel_mono (X ◁ (λ_ Y).hom)]
#align category_theory.monoidal_category.triangle_assoc_comp_right_inv CategoryTheory.MonoidalCategory.triangle_assoc_comp_right_inv
@[reassoc (attr := simp)]
theorem triangle_assoc_comp_left_inv (X Y : C) :
(X ◁ (λ_ Y).inv) ≫ (α_ X (𝟙_ C) Y).inv = (ρ_ X).inv ▷ Y := by
simp [← cancel_mono ((ρ_ X).hom ▷ Y)]
#align category_theory.monoidal_category.triangle_assoc_comp_left_inv CategoryTheory.MonoidalCategory.triangle_assoc_comp_left_inv
/-- We state it as a simp lemma, which is regarded as an involved version of
`id_whiskerRight X Y : 𝟙 X ▷ Y = 𝟙 (X ⊗ Y)`.
-/
@[reassoc, simp]
theorem leftUnitor_whiskerRight (X Y : C) :
(λ_ X).hom ▷ Y = (α_ (𝟙_ C) X Y).hom ≫ (λ_ (X ⊗ Y)).hom := by
rw [← whiskerLeft_iff, whiskerLeft_comp, ← cancel_epi (α_ _ _ _).hom, ←
cancel_epi ((α_ _ _ _).hom ▷ _), pentagon_assoc, triangle, ← associator_naturality_middle, ←
comp_whiskerRight_assoc, triangle, associator_naturality_left]
@[reassoc, simp]
theorem leftUnitor_inv_whiskerRight (X Y : C) :
(λ_ X).inv ▷ Y = (λ_ (X ⊗ Y)).inv ≫ (α_ (𝟙_ C) X Y).inv :=
eq_of_inv_eq_inv (by simp)
@[reassoc, simp]
theorem whiskerLeft_rightUnitor (X Y : C) :
X ◁ (ρ_ Y).hom = (α_ X Y (𝟙_ C)).inv ≫ (ρ_ (X ⊗ Y)).hom := by
rw [← whiskerRight_iff, comp_whiskerRight, ← cancel_epi (α_ _ _ _).inv, ←
cancel_epi (X ◁ (α_ _ _ _).inv), pentagon_inv_assoc, triangle_assoc_comp_right, ←
associator_inv_naturality_middle, ← whiskerLeft_comp_assoc, triangle_assoc_comp_right,
associator_inv_naturality_right]
@[reassoc, simp]
theorem whiskerLeft_rightUnitor_inv (X Y : C) :
X ◁ (ρ_ Y).inv = (ρ_ (X ⊗ Y)).inv ≫ (α_ X Y (𝟙_ C)).hom :=
eq_of_inv_eq_inv (by simp)
@[reassoc]
theorem leftUnitor_tensor (X Y : C) :
(λ_ (X ⊗ Y)).hom = (α_ (𝟙_ C) X Y).inv ≫ (λ_ X).hom ▷ Y := by simp
@[reassoc]
theorem leftUnitor_tensor_inv (X Y : C) :
(λ_ (X ⊗ Y)).inv = (λ_ X).inv ▷ Y ≫ (α_ (𝟙_ C) X Y).hom := by simp
@[reassoc]
theorem rightUnitor_tensor (X Y : C) :
(ρ_ (X ⊗ Y)).hom = (α_ X Y (𝟙_ C)).hom ≫ X ◁ (ρ_ Y).hom := by simp
#align category_theory.monoidal_category.right_unitor_tensor CategoryTheory.MonoidalCategory.rightUnitor_tensor
@[reassoc]
theorem rightUnitor_tensor_inv (X Y : C) :
(ρ_ (X ⊗ Y)).inv = X ◁ (ρ_ Y).inv ≫ (α_ X Y (𝟙_ C)).inv := by simp
#align category_theory.monoidal_category.right_unitor_tensor_inv CategoryTheory.MonoidalCategory.rightUnitor_tensor_inv
end
@[reassoc]
theorem associator_inv_naturality {X Y Z X' Y' Z' : C} (f : X ⟶ X') (g : Y ⟶ Y') (h : Z ⟶ Z') :
(f ⊗ g ⊗ h) ≫ (α_ X' Y' Z').inv = (α_ X Y Z).inv ≫ ((f ⊗ g) ⊗ h) := by
simp [tensorHom_def]
#align category_theory.monoidal_category.associator_inv_naturality CategoryTheory.MonoidalCategory.associator_inv_naturality
@[reassoc, simp]
theorem associator_conjugation {X X' Y Y' Z Z' : C} (f : X ⟶ X') (g : Y ⟶ Y') (h : Z ⟶ Z') :
(f ⊗ g) ⊗ h = (α_ X Y Z).hom ≫ (f ⊗ g ⊗ h) ≫ (α_ X' Y' Z').inv := by
rw [associator_inv_naturality, hom_inv_id_assoc]
#align category_theory.monoidal_category.associator_conjugation CategoryTheory.MonoidalCategory.associator_conjugation
@[reassoc]
theorem associator_inv_conjugation {X X' Y Y' Z Z' : C} (f : X ⟶ X') (g : Y ⟶ Y') (h : Z ⟶ Z') :
f ⊗ g ⊗ h = (α_ X Y Z).inv ≫ ((f ⊗ g) ⊗ h) ≫ (α_ X' Y' Z').hom := by
rw [associator_naturality, inv_hom_id_assoc]
#align category_theory.monoidal_category.associator_inv_conjugation CategoryTheory.MonoidalCategory.associator_inv_conjugation
-- TODO these next two lemmas aren't so fundamental, and perhaps could be removed
-- (replacing their usages by their proofs).
@[reassoc]
theorem id_tensor_associator_naturality {X Y Z Z' : C} (h : Z ⟶ Z') :
(𝟙 (X ⊗ Y) ⊗ h) ≫ (α_ X Y Z').hom = (α_ X Y Z).hom ≫ (𝟙 X ⊗ 𝟙 Y ⊗ h) := by
rw [← tensor_id, associator_naturality]
#align category_theory.monoidal_category.id_tensor_associator_naturality CategoryTheory.MonoidalCategory.id_tensor_associator_naturality
@[reassoc]
theorem id_tensor_associator_inv_naturality {X Y Z X' : C} (f : X ⟶ X') :
(f ⊗ 𝟙 (Y ⊗ Z)) ≫ (α_ X' Y Z).inv = (α_ X Y Z).inv ≫ ((f ⊗ 𝟙 Y) ⊗ 𝟙 Z) := by
rw [← tensor_id, associator_inv_naturality]
#align category_theory.monoidal_category.id_tensor_associator_inv_naturality CategoryTheory.MonoidalCategory.id_tensor_associator_inv_naturality
@[reassoc (attr := simp)]
theorem hom_inv_id_tensor {V W X Y Z : C} (f : V ≅ W) (g : X ⟶ Y) (h : Y ⟶ Z) :
(f.hom ⊗ g) ≫ (f.inv ⊗ h) = (𝟙 V ⊗ g) ≫ (𝟙 V ⊗ h) := by
rw [← tensor_comp, f.hom_inv_id]; simp [id_tensorHom]
#align category_theory.monoidal_category.hom_inv_id_tensor CategoryTheory.MonoidalCategory.hom_inv_id_tensor
@[reassoc (attr := simp)]
theorem inv_hom_id_tensor {V W X Y Z : C} (f : V ≅ W) (g : X ⟶ Y) (h : Y ⟶ Z) :
(f.inv ⊗ g) ≫ (f.hom ⊗ h) = (𝟙 W ⊗ g) ≫ (𝟙 W ⊗ h) := by
rw [← tensor_comp, f.inv_hom_id]; simp [id_tensorHom]
#align category_theory.monoidal_category.inv_hom_id_tensor CategoryTheory.MonoidalCategory.inv_hom_id_tensor
@[reassoc (attr := simp)]
theorem tensor_hom_inv_id {V W X Y Z : C} (f : V ≅ W) (g : X ⟶ Y) (h : Y ⟶ Z) :
(g ⊗ f.hom) ≫ (h ⊗ f.inv) = (g ⊗ 𝟙 V) ≫ (h ⊗ 𝟙 V) := by
rw [← tensor_comp, f.hom_inv_id]; simp [tensorHom_id]
#align category_theory.monoidal_category.tensor_hom_inv_id CategoryTheory.MonoidalCategory.tensor_hom_inv_id
@[reassoc (attr := simp)]
theorem tensor_inv_hom_id {V W X Y Z : C} (f : V ≅ W) (g : X ⟶ Y) (h : Y ⟶ Z) :
(g ⊗ f.inv) ≫ (h ⊗ f.hom) = (g ⊗ 𝟙 W) ≫ (h ⊗ 𝟙 W) := by
rw [← tensor_comp, f.inv_hom_id]; simp [tensorHom_id]
#align category_theory.monoidal_category.tensor_inv_hom_id CategoryTheory.MonoidalCategory.tensor_inv_hom_id
@[reassoc (attr := simp)]
theorem hom_inv_id_tensor' {V W X Y Z : C} (f : V ⟶ W) [IsIso f] (g : X ⟶ Y) (h : Y ⟶ Z) :
(f ⊗ g) ≫ (inv f ⊗ h) = (𝟙 V ⊗ g) ≫ (𝟙 V ⊗ h) := by
rw [← tensor_comp, IsIso.hom_inv_id]; simp [id_tensorHom]
#align category_theory.monoidal_category.hom_inv_id_tensor' CategoryTheory.MonoidalCategory.hom_inv_id_tensor'
@[reassoc (attr := simp)]
theorem inv_hom_id_tensor' {V W X Y Z : C} (f : V ⟶ W) [IsIso f] (g : X ⟶ Y) (h : Y ⟶ Z) :
(inv f ⊗ g) ≫ (f ⊗ h) = (𝟙 W ⊗ g) ≫ (𝟙 W ⊗ h) := by
rw [← tensor_comp, IsIso.inv_hom_id]; simp [id_tensorHom]
#align category_theory.monoidal_category.inv_hom_id_tensor' CategoryTheory.MonoidalCategory.inv_hom_id_tensor'
@[reassoc (attr := simp)]
theorem tensor_hom_inv_id' {V W X Y Z : C} (f : V ⟶ W) [IsIso f] (g : X ⟶ Y) (h : Y ⟶ Z) :
(g ⊗ f) ≫ (h ⊗ inv f) = (g ⊗ 𝟙 V) ≫ (h ⊗ 𝟙 V) := by
rw [← tensor_comp, IsIso.hom_inv_id]; simp [tensorHom_id]
#align category_theory.monoidal_category.tensor_hom_inv_id' CategoryTheory.MonoidalCategory.tensor_hom_inv_id'
@[reassoc (attr := simp)]
theorem tensor_inv_hom_id' {V W X Y Z : C} (f : V ⟶ W) [IsIso f] (g : X ⟶ Y) (h : Y ⟶ Z) :
(g ⊗ inv f) ≫ (h ⊗ f) = (g ⊗ 𝟙 W) ≫ (h ⊗ 𝟙 W) := by
rw [← tensor_comp, IsIso.inv_hom_id]; simp [tensorHom_id]
#align category_theory.monoidal_category.tensor_inv_hom_id' CategoryTheory.MonoidalCategory.tensor_inv_hom_id'
/--
A constructor for monoidal categories that requires `tensorHom` instead of `whiskerLeft` and
`whiskerRight`.
-/
abbrev ofTensorHom [MonoidalCategoryStruct C]
(tensor_id : ∀ X₁ X₂ : C, tensorHom (𝟙 X₁) (𝟙 X₂) = 𝟙 (tensorObj X₁ X₂) := by
aesop_cat)
(id_tensorHom : ∀ (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂), tensorHom (𝟙 X) f = whiskerLeft X f := by
aesop_cat)
(tensorHom_id : ∀ {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C), tensorHom f (𝟙 Y) = whiskerRight f Y := by
aesop_cat)
(tensor_comp :
∀ {X₁ Y₁ Z₁ X₂ Y₂ Z₂ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (g₁ : Y₁ ⟶ Z₁) (g₂ : Y₂ ⟶ Z₂),
tensorHom (f₁ ≫ g₁) (f₂ ≫ g₂) = tensorHom f₁ f₂ ≫ tensorHom g₁ g₂ := by
aesop_cat)
(associator_naturality :
∀ {X₁ X₂ X₃ Y₁ Y₂ Y₃ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (f₃ : X₃ ⟶ Y₃),
tensorHom (tensorHom f₁ f₂) f₃ ≫ (associator Y₁ Y₂ Y₃).hom =
(associator X₁ X₂ X₃).hom ≫ tensorHom f₁ (tensorHom f₂ f₃) := by
aesop_cat)
(leftUnitor_naturality :
∀ {X Y : C} (f : X ⟶ Y),
tensorHom (𝟙 tensorUnit) f ≫ (leftUnitor Y).hom = (leftUnitor X).hom ≫ f := by
aesop_cat)
(rightUnitor_naturality :
∀ {X Y : C} (f : X ⟶ Y),
tensorHom f (𝟙 tensorUnit) ≫ (rightUnitor Y).hom = (rightUnitor X).hom ≫ f := by
aesop_cat)
(pentagon :
∀ W X Y Z : C,
tensorHom (associator W X Y).hom (𝟙 Z) ≫
(associator W (tensorObj X Y) Z).hom ≫ tensorHom (𝟙 W) (associator X Y Z).hom =
(associator (tensorObj W X) Y Z).hom ≫ (associator W X (tensorObj Y Z)).hom := by
aesop_cat)
(triangle :
∀ X Y : C,
(associator X tensorUnit Y).hom ≫ tensorHom (𝟙 X) (leftUnitor Y).hom =
tensorHom (rightUnitor X).hom (𝟙 Y) := by
aesop_cat) :
MonoidalCategory C where
tensorHom_def := by intros; simp [← id_tensorHom, ← tensorHom_id, ← tensor_comp]
whiskerLeft_id := by intros; simp [← id_tensorHom, ← tensor_id]
id_whiskerRight := by intros; simp [← tensorHom_id, tensor_id]
pentagon := by intros; simp [← id_tensorHom, ← tensorHom_id, pentagon]
triangle := by intros; simp [← id_tensorHom, ← tensorHom_id, triangle]
@[reassoc]
theorem comp_tensor_id (f : W ⟶ X) (g : X ⟶ Y) : f ≫ g ⊗ 𝟙 Z = (f ⊗ 𝟙 Z) ≫ (g ⊗ 𝟙 Z) := by
simp
#align category_theory.monoidal_category.comp_tensor_id CategoryTheory.MonoidalCategory.comp_tensor_id
@[reassoc]
theorem id_tensor_comp (f : W ⟶ X) (g : X ⟶ Y) : 𝟙 Z ⊗ f ≫ g = (𝟙 Z ⊗ f) ≫ (𝟙 Z ⊗ g) := by
simp
#align category_theory.monoidal_category.id_tensor_comp CategoryTheory.MonoidalCategory.id_tensor_comp
@[reassoc]
| Mathlib/CategoryTheory/Monoidal/Category.lean | 782 | 784 | theorem id_tensor_comp_tensor_id (f : W ⟶ X) (g : Y ⟶ Z) : (𝟙 Y ⊗ f) ≫ (g ⊗ 𝟙 X) = g ⊗ f := by |
rw [← tensor_comp]
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. -/
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 853 | 859 | 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
|
/-
Copyright (c) 2020 Fox Thomson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Fox Thomson, Martin Dvorak
-/
import Mathlib.Algebra.Order.Kleene
import Mathlib.Algebra.Ring.Hom.Defs
import Mathlib.Data.List.Join
import Mathlib.Data.Set.Lattice
import Mathlib.Tactic.DeriveFintype
#align_import computability.language from "leanprover-community/mathlib"@"a239cd3e7ac2c7cde36c913808f9d40c411344f6"
/-!
# Languages
This file contains the definition and operations on formal languages over an alphabet.
Note that "strings" are implemented as lists over the alphabet.
Union and concatenation define a [Kleene algebra](https://en.wikipedia.org/wiki/Kleene_algebra)
over the languages.
In addition to that, we define a reversal of a language and prove that it behaves well
with respect to other language operations.
-/
open List Set Computability
universe v
variable {α β γ : Type*}
/-- A language is a set of strings over an alphabet. -/
def Language (α) :=
Set (List α)
#align language Language
instance : Membership (List α) (Language α) := ⟨Set.Mem⟩
instance : Singleton (List α) (Language α) := ⟨Set.singleton⟩
instance : Insert (List α) (Language α) := ⟨Set.insert⟩
instance : CompleteAtomicBooleanAlgebra (Language α) := Set.completeAtomicBooleanAlgebra
namespace Language
variable {l m : Language α} {a b x : List α}
-- Porting note: `reducible` attribute cannot be local.
-- attribute [local reducible] Language
/-- Zero language has no elements. -/
instance : Zero (Language α) :=
⟨(∅ : Set _)⟩
/-- `1 : Language α` contains only one element `[]`. -/
instance : One (Language α) :=
⟨{[]}⟩
instance : Inhabited (Language α) := ⟨(∅ : Set _)⟩
/-- The sum of two languages is their union. -/
instance : Add (Language α) :=
⟨((· ∪ ·) : Set (List α) → Set (List α) → Set (List α))⟩
/-- The product of two languages `l` and `m` is the language made of the strings `x ++ y` where
`x ∈ l` and `y ∈ m`. -/
instance : Mul (Language α) :=
⟨image2 (· ++ ·)⟩
theorem zero_def : (0 : Language α) = (∅ : Set _) :=
rfl
#align language.zero_def Language.zero_def
theorem one_def : (1 : Language α) = ({[]} : Set (List α)) :=
rfl
#align language.one_def Language.one_def
theorem add_def (l m : Language α) : l + m = (l ∪ m : Set (List α)) :=
rfl
#align language.add_def Language.add_def
theorem mul_def (l m : Language α) : l * m = image2 (· ++ ·) l m :=
rfl
#align language.mul_def Language.mul_def
/-- The Kleene star of a language `L` is the set of all strings which can be written by
concatenating strings from `L`. -/
instance : KStar (Language α) := ⟨fun l ↦ {x | ∃ L : List (List α), x = L.join ∧ ∀ y ∈ L, y ∈ l}⟩
lemma kstar_def (l : Language α) : l∗ = {x | ∃ L : List (List α), x = L.join ∧ ∀ y ∈ L, y ∈ l} :=
rfl
#align language.kstar_def Language.kstar_def
-- Porting note: `reducible` attribute cannot be local,
-- so this new theorem is required in place of `Set.ext`.
@[ext]
theorem ext {l m : Language α} (h : ∀ (x : List α), x ∈ l ↔ x ∈ m) : l = m :=
Set.ext h
@[simp]
theorem not_mem_zero (x : List α) : x ∉ (0 : Language α) :=
id
#align language.not_mem_zero Language.not_mem_zero
@[simp]
theorem mem_one (x : List α) : x ∈ (1 : Language α) ↔ x = [] := by rfl
#align language.mem_one Language.mem_one
theorem nil_mem_one : [] ∈ (1 : Language α) :=
Set.mem_singleton _
#align language.nil_mem_one Language.nil_mem_one
theorem mem_add (l m : Language α) (x : List α) : x ∈ l + m ↔ x ∈ l ∨ x ∈ m :=
Iff.rfl
#align language.mem_add Language.mem_add
theorem mem_mul : x ∈ l * m ↔ ∃ a ∈ l, ∃ b ∈ m, a ++ b = x :=
mem_image2
#align language.mem_mul Language.mem_mul
theorem append_mem_mul : a ∈ l → b ∈ m → a ++ b ∈ l * m :=
mem_image2_of_mem
#align language.append_mem_mul Language.append_mem_mul
theorem mem_kstar : x ∈ l∗ ↔ ∃ L : List (List α), x = L.join ∧ ∀ y ∈ L, y ∈ l :=
Iff.rfl
#align language.mem_kstar Language.mem_kstar
theorem join_mem_kstar {L : List (List α)} (h : ∀ y ∈ L, y ∈ l) : L.join ∈ l∗ :=
⟨L, rfl, h⟩
#align language.join_mem_kstar Language.join_mem_kstar
theorem nil_mem_kstar (l : Language α) : [] ∈ l∗ :=
⟨[], rfl, fun _ h ↦ by contradiction⟩
#align language.nil_mem_kstar Language.nil_mem_kstar
instance instSemiring : Semiring (Language α) where
add := (· + ·)
add_assoc := union_assoc
zero := 0
zero_add := empty_union
add_zero := union_empty
add_comm := union_comm
mul := (· * ·)
mul_assoc _ _ _ := image2_assoc append_assoc
zero_mul _ := image2_empty_left
mul_zero _ := image2_empty_right
one := 1
one_mul l := by simp [mul_def, one_def]
mul_one l := by simp [mul_def, one_def]
natCast n := if n = 0 then 0 else 1
natCast_zero := rfl
natCast_succ n := by cases n <;> simp [Nat.cast, add_def, zero_def]
left_distrib _ _ _ := image2_union_right
right_distrib _ _ _ := image2_union_left
nsmul := nsmulRec
@[simp]
theorem add_self (l : Language α) : l + l = l :=
sup_idem _
#align language.add_self Language.add_self
/-- Maps the alphabet of a language. -/
def map (f : α → β) : Language α →+* Language β where
toFun := image (List.map f)
map_zero' := image_empty _
map_one' := image_singleton
map_add' := image_union _
map_mul' _ _ := image_image2_distrib <| map_append _
#align language.map Language.map
@[simp]
theorem map_id (l : Language α) : map id l = l := by simp [map]
#align language.map_id Language.map_id
@[simp]
theorem map_map (g : β → γ) (f : α → β) (l : Language α) : map g (map f l) = map (g ∘ f) l := by
simp [map, image_image]
#align language.map_map Language.map_map
lemma mem_kstar_iff_exists_nonempty {x : List α} :
x ∈ l∗ ↔ ∃ S : List (List α), x = S.join ∧ ∀ y ∈ S, y ∈ l ∧ y ≠ [] := by
constructor
· rintro ⟨S, rfl, h⟩
refine ⟨S.filter fun l ↦ !List.isEmpty l, by simp, fun y hy ↦ ?_⟩
-- Porting note: The previous code was:
-- rw [mem_filter, empty_iff_eq_nil] at hy
rw [mem_filter, Bool.not_eq_true', ← Bool.bool_iff_false, isEmpty_iff_eq_nil] at hy
exact ⟨h y hy.1, hy.2⟩
· rintro ⟨S, hx, h⟩
exact ⟨S, hx, fun y hy ↦ (h y hy).1⟩
theorem kstar_def_nonempty (l : Language α) :
l∗ = { x | ∃ S : List (List α), x = S.join ∧ ∀ y ∈ S, y ∈ l ∧ y ≠ [] } := by
ext x; apply mem_kstar_iff_exists_nonempty
#align language.kstar_def_nonempty Language.kstar_def_nonempty
theorem le_iff (l m : Language α) : l ≤ m ↔ l + m = m :=
sup_eq_right.symm
#align language.le_iff Language.le_iff
theorem le_mul_congr {l₁ l₂ m₁ m₂ : Language α} : l₁ ≤ m₁ → l₂ ≤ m₂ → l₁ * l₂ ≤ m₁ * m₂ := by
intro h₁ h₂ x hx
simp only [mul_def, exists_and_left, mem_image2, image_prod] at hx ⊢
tauto
#align language.le_mul_congr Language.le_mul_congr
theorem le_add_congr {l₁ l₂ m₁ m₂ : Language α} : l₁ ≤ m₁ → l₂ ≤ m₂ → l₁ + l₂ ≤ m₁ + m₂ :=
sup_le_sup
#align language.le_add_congr Language.le_add_congr
theorem mem_iSup {ι : Sort v} {l : ι → Language α} {x : List α} : (x ∈ ⨆ i, l i) ↔ ∃ i, x ∈ l i :=
mem_iUnion
#align language.mem_supr Language.mem_iSup
theorem iSup_mul {ι : Sort v} (l : ι → Language α) (m : Language α) :
(⨆ i, l i) * m = ⨆ i, l i * m :=
image2_iUnion_left _ _ _
#align language.supr_mul Language.iSup_mul
theorem mul_iSup {ι : Sort v} (l : ι → Language α) (m : Language α) :
(m * ⨆ i, l i) = ⨆ i, m * l i :=
image2_iUnion_right _ _ _
#align language.mul_supr Language.mul_iSup
theorem iSup_add {ι : Sort v} [Nonempty ι] (l : ι → Language α) (m : Language α) :
(⨆ i, l i) + m = ⨆ i, l i + m :=
iSup_sup
#align language.supr_add Language.iSup_add
theorem add_iSup {ι : Sort v} [Nonempty ι] (l : ι → Language α) (m : Language α) :
(m + ⨆ i, l i) = ⨆ i, m + l i :=
sup_iSup
#align language.add_supr Language.add_iSup
theorem mem_pow {l : Language α} {x : List α} {n : ℕ} :
x ∈ l ^ n ↔ ∃ S : List (List α), x = S.join ∧ S.length = n ∧ ∀ y ∈ S, y ∈ l := by
induction' n with n ihn generalizing x
· simp only [mem_one, pow_zero, length_eq_zero]
constructor
· rintro rfl
exact ⟨[], rfl, rfl, fun _ h ↦ by contradiction⟩
· rintro ⟨_, rfl, rfl, _⟩
rfl
· simp only [pow_succ', mem_mul, ihn]
constructor
· rintro ⟨a, ha, b, ⟨S, rfl, rfl, hS⟩, rfl⟩
exact ⟨a :: S, rfl, rfl, forall_mem_cons.2 ⟨ha, hS⟩⟩
· rintro ⟨_ | ⟨a, S⟩, rfl, hn, hS⟩ <;> cases hn
rw [forall_mem_cons] at hS
exact ⟨a, hS.1, _, ⟨S, rfl, rfl, hS.2⟩, rfl⟩
#align language.mem_pow Language.mem_pow
| Mathlib/Computability/Language.lean | 252 | 259 | theorem kstar_eq_iSup_pow (l : Language α) : l∗ = ⨆ i : ℕ, l ^ i := by |
ext x
simp only [mem_kstar, mem_iSup, mem_pow]
constructor
· rintro ⟨S, rfl, hS⟩
exact ⟨_, S, rfl, rfl, hS⟩
· rintro ⟨_, S, rfl, rfl, hS⟩
exact ⟨S, rfl, hS⟩
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Yaël Dillies
-/
import Mathlib.Algebra.Module.BigOperators
import Mathlib.Data.Fintype.Perm
import Mathlib.GroupTheory.Perm.Finite
import Mathlib.GroupTheory.Perm.List
#align_import group_theory.perm.cycle.basic from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3"
/-!
# Cycles of a permutation
This file starts the theory of cycles in permutations.
## Main definitions
In the following, `f : Equiv.Perm β`.
* `Equiv.Perm.SameCycle`: `f.SameCycle x y` when `x` and `y` are in the same cycle of `f`.
* `Equiv.Perm.IsCycle`: `f` is a cycle if any two nonfixed points of `f` are related by repeated
applications of `f`, and `f` is not the identity.
* `Equiv.Perm.IsCycleOn`: `f` is a cycle on a set `s` when any two points of `s` are related by
repeated applications of `f`.
## Notes
`Equiv.Perm.IsCycle` and `Equiv.Perm.IsCycleOn` are different in three ways:
* `IsCycle` is about the entire type while `IsCycleOn` is restricted to a set.
* `IsCycle` forbids the identity while `IsCycleOn` allows it (if `s` is a subsingleton).
* `IsCycleOn` forbids fixed points on `s` (if `s` is nontrivial), while `IsCycle` allows them.
-/
open Equiv Function Finset
variable {ι α β : Type*}
namespace Equiv.Perm
/-! ### `SameCycle` -/
section SameCycle
variable {f g : Perm α} {p : α → Prop} {x y z : α}
/-- The equivalence relation indicating that two points are in the same cycle of a permutation. -/
def SameCycle (f : Perm α) (x y : α) : Prop :=
∃ i : ℤ, (f ^ i) x = y
#align equiv.perm.same_cycle Equiv.Perm.SameCycle
@[refl]
theorem SameCycle.refl (f : Perm α) (x : α) : SameCycle f x x :=
⟨0, rfl⟩
#align equiv.perm.same_cycle.refl Equiv.Perm.SameCycle.refl
theorem SameCycle.rfl : SameCycle f x x :=
SameCycle.refl _ _
#align equiv.perm.same_cycle.rfl Equiv.Perm.SameCycle.rfl
protected theorem _root_.Eq.sameCycle (h : x = y) (f : Perm α) : f.SameCycle x y := by rw [h]
#align eq.same_cycle Eq.sameCycle
@[symm]
theorem SameCycle.symm : SameCycle f x y → SameCycle f y x := fun ⟨i, hi⟩ =>
⟨-i, by rw [zpow_neg, ← hi, inv_apply_self]⟩
#align equiv.perm.same_cycle.symm Equiv.Perm.SameCycle.symm
theorem sameCycle_comm : SameCycle f x y ↔ SameCycle f y x :=
⟨SameCycle.symm, SameCycle.symm⟩
#align equiv.perm.same_cycle_comm Equiv.Perm.sameCycle_comm
@[trans]
theorem SameCycle.trans : SameCycle f x y → SameCycle f y z → SameCycle f x z :=
fun ⟨i, hi⟩ ⟨j, hj⟩ => ⟨j + i, by rw [zpow_add, mul_apply, hi, hj]⟩
#align equiv.perm.same_cycle.trans Equiv.Perm.SameCycle.trans
variable (f) in
theorem SameCycle.equivalence : Equivalence (SameCycle f) :=
⟨SameCycle.refl f, SameCycle.symm, SameCycle.trans⟩
/-- The setoid defined by the `SameCycle` relation. -/
def SameCycle.setoid (f : Perm α) : Setoid α where
iseqv := SameCycle.equivalence f
@[simp]
theorem sameCycle_one : SameCycle 1 x y ↔ x = y := by simp [SameCycle]
#align equiv.perm.same_cycle_one Equiv.Perm.sameCycle_one
@[simp]
theorem sameCycle_inv : SameCycle f⁻¹ x y ↔ SameCycle f x y :=
(Equiv.neg _).exists_congr_left.trans <| by simp [SameCycle]
#align equiv.perm.same_cycle_inv Equiv.Perm.sameCycle_inv
alias ⟨SameCycle.of_inv, SameCycle.inv⟩ := sameCycle_inv
#align equiv.perm.same_cycle.of_inv Equiv.Perm.SameCycle.of_inv
#align equiv.perm.same_cycle.inv Equiv.Perm.SameCycle.inv
@[simp]
theorem sameCycle_conj : SameCycle (g * f * g⁻¹) x y ↔ SameCycle f (g⁻¹ x) (g⁻¹ y) :=
exists_congr fun i => by simp [conj_zpow, eq_inv_iff_eq]
#align equiv.perm.same_cycle_conj Equiv.Perm.sameCycle_conj
theorem SameCycle.conj : SameCycle f x y → SameCycle (g * f * g⁻¹) (g x) (g y) := by
simp [sameCycle_conj]
#align equiv.perm.same_cycle.conj Equiv.Perm.SameCycle.conj
theorem SameCycle.apply_eq_self_iff : SameCycle f x y → (f x = x ↔ f y = y) := fun ⟨i, hi⟩ => by
rw [← hi, ← mul_apply, ← zpow_one_add, add_comm, zpow_add_one, mul_apply,
(f ^ i).injective.eq_iff]
#align equiv.perm.same_cycle.apply_eq_self_iff Equiv.Perm.SameCycle.apply_eq_self_iff
theorem SameCycle.eq_of_left (h : SameCycle f x y) (hx : IsFixedPt f x) : x = y :=
let ⟨_, hn⟩ := h
(hx.perm_zpow _).eq.symm.trans hn
#align equiv.perm.same_cycle.eq_of_left Equiv.Perm.SameCycle.eq_of_left
theorem SameCycle.eq_of_right (h : SameCycle f x y) (hy : IsFixedPt f y) : x = y :=
h.eq_of_left <| h.apply_eq_self_iff.2 hy
#align equiv.perm.same_cycle.eq_of_right Equiv.Perm.SameCycle.eq_of_right
@[simp]
theorem sameCycle_apply_left : SameCycle f (f x) y ↔ SameCycle f x y :=
(Equiv.addRight 1).exists_congr_left.trans <| by
simp [zpow_sub, SameCycle, Int.add_neg_one, Function.comp]
#align equiv.perm.same_cycle_apply_left Equiv.Perm.sameCycle_apply_left
@[simp]
theorem sameCycle_apply_right : SameCycle f x (f y) ↔ SameCycle f x y := by
rw [sameCycle_comm, sameCycle_apply_left, sameCycle_comm]
#align equiv.perm.same_cycle_apply_right Equiv.Perm.sameCycle_apply_right
@[simp]
theorem sameCycle_inv_apply_left : SameCycle f (f⁻¹ x) y ↔ SameCycle f x y := by
rw [← sameCycle_apply_left, apply_inv_self]
#align equiv.perm.same_cycle_inv_apply_left Equiv.Perm.sameCycle_inv_apply_left
@[simp]
theorem sameCycle_inv_apply_right : SameCycle f x (f⁻¹ y) ↔ SameCycle f x y := by
rw [← sameCycle_apply_right, apply_inv_self]
#align equiv.perm.same_cycle_inv_apply_right Equiv.Perm.sameCycle_inv_apply_right
@[simp]
theorem sameCycle_zpow_left {n : ℤ} : SameCycle f ((f ^ n) x) y ↔ SameCycle f x y :=
(Equiv.addRight (n : ℤ)).exists_congr_left.trans <| by simp [SameCycle, zpow_add]
#align equiv.perm.same_cycle_zpow_left Equiv.Perm.sameCycle_zpow_left
@[simp]
theorem sameCycle_zpow_right {n : ℤ} : SameCycle f x ((f ^ n) y) ↔ SameCycle f x y := by
rw [sameCycle_comm, sameCycle_zpow_left, sameCycle_comm]
#align equiv.perm.same_cycle_zpow_right Equiv.Perm.sameCycle_zpow_right
@[simp]
theorem sameCycle_pow_left {n : ℕ} : SameCycle f ((f ^ n) x) y ↔ SameCycle f x y := by
rw [← zpow_natCast, sameCycle_zpow_left]
#align equiv.perm.same_cycle_pow_left Equiv.Perm.sameCycle_pow_left
@[simp]
theorem sameCycle_pow_right {n : ℕ} : SameCycle f x ((f ^ n) y) ↔ SameCycle f x y := by
rw [← zpow_natCast, sameCycle_zpow_right]
#align equiv.perm.same_cycle_pow_right Equiv.Perm.sameCycle_pow_right
alias ⟨SameCycle.of_apply_left, SameCycle.apply_left⟩ := sameCycle_apply_left
#align equiv.perm.same_cycle.of_apply_left Equiv.Perm.SameCycle.of_apply_left
#align equiv.perm.same_cycle.apply_left Equiv.Perm.SameCycle.apply_left
alias ⟨SameCycle.of_apply_right, SameCycle.apply_right⟩ := sameCycle_apply_right
#align equiv.perm.same_cycle.of_apply_right Equiv.Perm.SameCycle.of_apply_right
#align equiv.perm.same_cycle.apply_right Equiv.Perm.SameCycle.apply_right
alias ⟨SameCycle.of_inv_apply_left, SameCycle.inv_apply_left⟩ := sameCycle_inv_apply_left
#align equiv.perm.same_cycle.of_inv_apply_left Equiv.Perm.SameCycle.of_inv_apply_left
#align equiv.perm.same_cycle.inv_apply_left Equiv.Perm.SameCycle.inv_apply_left
alias ⟨SameCycle.of_inv_apply_right, SameCycle.inv_apply_right⟩ := sameCycle_inv_apply_right
#align equiv.perm.same_cycle.of_inv_apply_right Equiv.Perm.SameCycle.of_inv_apply_right
#align equiv.perm.same_cycle.inv_apply_right Equiv.Perm.SameCycle.inv_apply_right
alias ⟨SameCycle.of_pow_left, SameCycle.pow_left⟩ := sameCycle_pow_left
#align equiv.perm.same_cycle.of_pow_left Equiv.Perm.SameCycle.of_pow_left
#align equiv.perm.same_cycle.pow_left Equiv.Perm.SameCycle.pow_left
alias ⟨SameCycle.of_pow_right, SameCycle.pow_right⟩ := sameCycle_pow_right
#align equiv.perm.same_cycle.of_pow_right Equiv.Perm.SameCycle.of_pow_right
#align equiv.perm.same_cycle.pow_right Equiv.Perm.SameCycle.pow_right
alias ⟨SameCycle.of_zpow_left, SameCycle.zpow_left⟩ := sameCycle_zpow_left
#align equiv.perm.same_cycle.of_zpow_left Equiv.Perm.SameCycle.of_zpow_left
#align equiv.perm.same_cycle.zpow_left Equiv.Perm.SameCycle.zpow_left
alias ⟨SameCycle.of_zpow_right, SameCycle.zpow_right⟩ := sameCycle_zpow_right
#align equiv.perm.same_cycle.of_zpow_right Equiv.Perm.SameCycle.of_zpow_right
#align equiv.perm.same_cycle.zpow_right Equiv.Perm.SameCycle.zpow_right
theorem SameCycle.of_pow {n : ℕ} : SameCycle (f ^ n) x y → SameCycle f x y := fun ⟨m, h⟩ =>
⟨n * m, by simp [zpow_mul, h]⟩
#align equiv.perm.same_cycle.of_pow Equiv.Perm.SameCycle.of_pow
theorem SameCycle.of_zpow {n : ℤ} : SameCycle (f ^ n) x y → SameCycle f x y := fun ⟨m, h⟩ =>
⟨n * m, by simp [zpow_mul, h]⟩
#align equiv.perm.same_cycle.of_zpow Equiv.Perm.SameCycle.of_zpow
@[simp]
theorem sameCycle_subtypePerm {h} {x y : { x // p x }} :
(f.subtypePerm h).SameCycle x y ↔ f.SameCycle x y :=
exists_congr fun n => by simp [Subtype.ext_iff]
#align equiv.perm.same_cycle_subtype_perm Equiv.Perm.sameCycle_subtypePerm
alias ⟨_, SameCycle.subtypePerm⟩ := sameCycle_subtypePerm
#align equiv.perm.same_cycle.subtype_perm Equiv.Perm.SameCycle.subtypePerm
@[simp]
theorem sameCycle_extendDomain {p : β → Prop} [DecidablePred p] {f : α ≃ Subtype p} :
SameCycle (g.extendDomain f) (f x) (f y) ↔ g.SameCycle x y :=
exists_congr fun n => by
rw [← extendDomain_zpow, extendDomain_apply_image, Subtype.coe_inj, f.injective.eq_iff]
#align equiv.perm.same_cycle_extend_domain Equiv.Perm.sameCycle_extendDomain
alias ⟨_, SameCycle.extendDomain⟩ := sameCycle_extendDomain
#align equiv.perm.same_cycle.extend_domain Equiv.Perm.SameCycle.extendDomain
theorem SameCycle.exists_pow_eq' [Finite α] : SameCycle f x y → ∃ i < orderOf f, (f ^ i) x = y := by
classical
rintro ⟨k, rfl⟩
use (k % orderOf f).natAbs
have h₀ := Int.natCast_pos.mpr (orderOf_pos f)
have h₁ := Int.emod_nonneg k h₀.ne'
rw [← zpow_natCast, Int.natAbs_of_nonneg h₁, zpow_mod_orderOf]
refine ⟨?_, by rfl⟩
rw [← Int.ofNat_lt, Int.natAbs_of_nonneg h₁]
exact Int.emod_lt_of_pos _ h₀
#align equiv.perm.same_cycle.exists_pow_eq' Equiv.Perm.SameCycle.exists_pow_eq'
theorem SameCycle.exists_pow_eq'' [Finite α] (h : SameCycle f x y) :
∃ i : ℕ, 0 < i ∧ i ≤ orderOf f ∧ (f ^ i) x = y := by
classical
obtain ⟨_ | i, hi, rfl⟩ := h.exists_pow_eq'
· refine ⟨orderOf f, orderOf_pos f, le_rfl, ?_⟩
rw [pow_orderOf_eq_one, pow_zero]
· exact ⟨i.succ, i.zero_lt_succ, hi.le, by rfl⟩
#align equiv.perm.same_cycle.exists_pow_eq'' Equiv.Perm.SameCycle.exists_pow_eq''
instance [Fintype α] [DecidableEq α] (f : Perm α) : DecidableRel (SameCycle f) := fun x y =>
decidable_of_iff (∃ n ∈ List.range (Fintype.card (Perm α)), (f ^ n) x = y)
⟨fun ⟨n, _, hn⟩ => ⟨n, hn⟩, fun ⟨i, hi⟩ => ⟨(i % orderOf f).natAbs,
List.mem_range.2 (Int.ofNat_lt.1 <| by
rw [Int.natAbs_of_nonneg (Int.emod_nonneg _ <| Int.natCast_ne_zero.2 (orderOf_pos _).ne')]
refine (Int.emod_lt _ <| Int.natCast_ne_zero_iff_pos.2 <| orderOf_pos _).trans_le ?_
simp [orderOf_le_card_univ]),
by
rw [← zpow_natCast, Int.natAbs_of_nonneg (Int.emod_nonneg _ <|
Int.natCast_ne_zero_iff_pos.2 <| orderOf_pos _), zpow_mod_orderOf, hi]⟩⟩
end SameCycle
/-!
### `IsCycle`
-/
section IsCycle
variable {f g : Perm α} {x y : α}
/-- A cycle is a non identity permutation where any two nonfixed points of the permutation are
related by repeated application of the permutation. -/
def IsCycle (f : Perm α) : Prop :=
∃ x, f x ≠ x ∧ ∀ ⦃y⦄, f y ≠ y → SameCycle f x y
#align equiv.perm.is_cycle Equiv.Perm.IsCycle
theorem IsCycle.ne_one (h : IsCycle f) : f ≠ 1 := fun hf => by simp [hf, IsCycle] at h
#align equiv.perm.is_cycle.ne_one Equiv.Perm.IsCycle.ne_one
@[simp]
theorem not_isCycle_one : ¬(1 : Perm α).IsCycle := fun H => H.ne_one rfl
#align equiv.perm.not_is_cycle_one Equiv.Perm.not_isCycle_one
protected theorem IsCycle.sameCycle (hf : IsCycle f) (hx : f x ≠ x) (hy : f y ≠ y) :
SameCycle f x y :=
let ⟨g, hg⟩ := hf
let ⟨a, ha⟩ := hg.2 hx
let ⟨b, hb⟩ := hg.2 hy
⟨b - a, by rw [← ha, ← mul_apply, ← zpow_add, sub_add_cancel, hb]⟩
#align equiv.perm.is_cycle.same_cycle Equiv.Perm.IsCycle.sameCycle
theorem IsCycle.exists_zpow_eq : IsCycle f → f x ≠ x → f y ≠ y → ∃ i : ℤ, (f ^ i) x = y :=
IsCycle.sameCycle
#align equiv.perm.is_cycle.exists_zpow_eq Equiv.Perm.IsCycle.exists_zpow_eq
theorem IsCycle.inv (hf : IsCycle f) : IsCycle f⁻¹ :=
hf.imp fun _ ⟨hx, h⟩ =>
⟨inv_eq_iff_eq.not.2 hx.symm, fun _ hy => (h <| inv_eq_iff_eq.not.2 hy.symm).inv⟩
#align equiv.perm.is_cycle.inv Equiv.Perm.IsCycle.inv
@[simp]
theorem isCycle_inv : IsCycle f⁻¹ ↔ IsCycle f :=
⟨fun h => h.inv, IsCycle.inv⟩
#align equiv.perm.is_cycle_inv Equiv.Perm.isCycle_inv
theorem IsCycle.conj : IsCycle f → IsCycle (g * f * g⁻¹) := by
rintro ⟨x, hx, h⟩
refine ⟨g x, by simp [coe_mul, inv_apply_self, hx], fun y hy => ?_⟩
rw [← apply_inv_self g y]
exact (h <| eq_inv_iff_eq.not.2 hy).conj
#align equiv.perm.is_cycle.conj Equiv.Perm.IsCycle.conj
protected theorem IsCycle.extendDomain {p : β → Prop} [DecidablePred p] (f : α ≃ Subtype p) :
IsCycle g → IsCycle (g.extendDomain f) := by
rintro ⟨a, ha, ha'⟩
refine ⟨f a, ?_, fun b hb => ?_⟩
· rw [extendDomain_apply_image]
exact Subtype.coe_injective.ne (f.injective.ne ha)
have h : b = f (f.symm ⟨b, of_not_not <| hb ∘ extendDomain_apply_not_subtype _ _⟩) := by
rw [apply_symm_apply, Subtype.coe_mk]
rw [h] at hb ⊢
simp only [extendDomain_apply_image, Subtype.coe_injective.ne_iff, f.injective.ne_iff] at hb
exact (ha' hb).extendDomain
#align equiv.perm.is_cycle.extend_domain Equiv.Perm.IsCycle.extendDomain
theorem isCycle_iff_sameCycle (hx : f x ≠ x) : IsCycle f ↔ ∀ {y}, SameCycle f x y ↔ f y ≠ y :=
⟨fun hf y =>
⟨fun ⟨i, hi⟩ hy =>
hx <| by
rw [← zpow_apply_eq_self_of_apply_eq_self hy i, (f ^ i).injective.eq_iff] at hi
rw [hi, hy],
hf.exists_zpow_eq hx⟩,
fun h => ⟨x, hx, fun y hy => h.2 hy⟩⟩
#align equiv.perm.is_cycle_iff_same_cycle Equiv.Perm.isCycle_iff_sameCycle
section Finite
variable [Finite α]
theorem IsCycle.exists_pow_eq (hf : IsCycle f) (hx : f x ≠ x) (hy : f y ≠ y) :
∃ i : ℕ, (f ^ i) x = y := by
let ⟨n, hn⟩ := hf.exists_zpow_eq hx hy
classical exact
⟨(n % orderOf f).toNat, by
{have := n.emod_nonneg (Int.natCast_ne_zero.mpr (ne_of_gt (orderOf_pos f)))
rwa [← zpow_natCast, Int.toNat_of_nonneg this, zpow_mod_orderOf]}⟩
#align equiv.perm.is_cycle.exists_pow_eq Equiv.Perm.IsCycle.exists_pow_eq
end Finite
variable [DecidableEq α]
theorem isCycle_swap (hxy : x ≠ y) : IsCycle (swap x y) :=
⟨y, by rwa [swap_apply_right], fun a (ha : ite (a = x) y (ite (a = y) x a) ≠ a) =>
if hya : y = a then ⟨0, hya⟩
else
⟨1, by
rw [zpow_one, swap_apply_def]
split_ifs at * <;> tauto⟩⟩
#align equiv.perm.is_cycle_swap Equiv.Perm.isCycle_swap
protected theorem IsSwap.isCycle : IsSwap f → IsCycle f := by
rintro ⟨x, y, hxy, rfl⟩
exact isCycle_swap hxy
#align equiv.perm.is_swap.is_cycle Equiv.Perm.IsSwap.isCycle
variable [Fintype α]
theorem IsCycle.two_le_card_support (h : IsCycle f) : 2 ≤ f.support.card :=
two_le_card_support_of_ne_one h.ne_one
#align equiv.perm.is_cycle.two_le_card_support Equiv.Perm.IsCycle.two_le_card_support
#noalign equiv.perm.is_cycle.exists_pow_eq_one
/-- The subgroup generated by a cycle is in bijection with its support -/
noncomputable def IsCycle.zpowersEquivSupport {σ : Perm α} (hσ : IsCycle σ) :
(Subgroup.zpowers σ) ≃ σ.support :=
Equiv.ofBijective
(fun (τ : ↥ ((Subgroup.zpowers σ) : Set (Perm α))) =>
⟨(τ : Perm α) (Classical.choose hσ), by
obtain ⟨τ, n, rfl⟩ := τ
erw [Finset.mem_coe, Subtype.coe_mk, zpow_apply_mem_support, mem_support]
exact (Classical.choose_spec hσ).1⟩)
(by
constructor
· rintro ⟨a, m, rfl⟩ ⟨b, n, rfl⟩ h
ext y
by_cases hy : σ y = y
· simp_rw [zpow_apply_eq_self_of_apply_eq_self hy]
· obtain ⟨i, rfl⟩ := (Classical.choose_spec hσ).2 hy
rw [Subtype.coe_mk, Subtype.coe_mk, zpow_apply_comm σ m i, zpow_apply_comm σ n i]
exact congr_arg _ (Subtype.ext_iff.mp h)
· rintro ⟨y, hy⟩
erw [Finset.mem_coe, mem_support] at hy
obtain ⟨n, rfl⟩ := (Classical.choose_spec hσ).2 hy
exact ⟨⟨σ ^ n, n, rfl⟩, rfl⟩)
#align equiv.perm.is_cycle.zpowers_equiv_support Equiv.Perm.IsCycle.zpowersEquivSupport
@[simp]
theorem IsCycle.zpowersEquivSupport_apply {σ : Perm α} (hσ : IsCycle σ) {n : ℕ} :
hσ.zpowersEquivSupport ⟨σ ^ n, n, rfl⟩ =
⟨(σ ^ n) (Classical.choose hσ),
pow_apply_mem_support.2 (mem_support.2 (Classical.choose_spec hσ).1)⟩ :=
rfl
#align equiv.perm.is_cycle.zpowers_equiv_support_apply Equiv.Perm.IsCycle.zpowersEquivSupport_apply
@[simp]
theorem IsCycle.zpowersEquivSupport_symm_apply {σ : Perm α} (hσ : IsCycle σ) (n : ℕ) :
hσ.zpowersEquivSupport.symm
⟨(σ ^ n) (Classical.choose hσ),
pow_apply_mem_support.2 (mem_support.2 (Classical.choose_spec hσ).1)⟩ =
⟨σ ^ n, n, rfl⟩ :=
(Equiv.symm_apply_eq _).2 hσ.zpowersEquivSupport_apply
#align equiv.perm.is_cycle.zpowers_equiv_support_symm_apply Equiv.Perm.IsCycle.zpowersEquivSupport_symm_apply
protected theorem IsCycle.orderOf (hf : IsCycle f) : orderOf f = f.support.card := by
rw [← Fintype.card_zpowers, ← Fintype.card_coe]
convert Fintype.card_congr (IsCycle.zpowersEquivSupport hf)
#align equiv.perm.is_cycle.order_of Equiv.Perm.IsCycle.orderOf
theorem isCycle_swap_mul_aux₁ {α : Type*} [DecidableEq α] :
∀ (n : ℕ) {b x : α} {f : Perm α} (_ : (swap x (f x) * f) b ≠ b) (_ : (f ^ n) (f x) = b),
∃ i : ℤ, ((swap x (f x) * f) ^ i) (f x) = b := by
intro n
induction' n with n hn
· exact fun _ h => ⟨0, h⟩
· intro b x f hb h
exact if hfbx : f x = b then ⟨0, hfbx⟩
else
have : f b ≠ b ∧ b ≠ x := ne_and_ne_of_swap_mul_apply_ne_self hb
have hb' : (swap x (f x) * f) (f⁻¹ b) ≠ f⁻¹ b := by
rw [mul_apply, apply_inv_self, swap_apply_of_ne_of_ne this.2 (Ne.symm hfbx), Ne, ←
f.injective.eq_iff, apply_inv_self]
exact this.1
let ⟨i, hi⟩ := hn hb' (f.injective <| by
rw [apply_inv_self]; rwa [pow_succ', mul_apply] at h)
⟨i + 1, by
rw [add_comm, zpow_add, mul_apply, hi, zpow_one, mul_apply, apply_inv_self,
swap_apply_of_ne_of_ne (ne_and_ne_of_swap_mul_apply_ne_self hb).2 (Ne.symm hfbx)]⟩
#align equiv.perm.is_cycle_swap_mul_aux₁ Equiv.Perm.isCycle_swap_mul_aux₁
theorem isCycle_swap_mul_aux₂ {α : Type*} [DecidableEq α] :
∀ (n : ℤ) {b x : α} {f : Perm α} (_ : (swap x (f x) * f) b ≠ b) (_ : (f ^ n) (f x) = b),
∃ i : ℤ, ((swap x (f x) * f) ^ i) (f x) = b := by
intro n
induction' n with n n
· exact isCycle_swap_mul_aux₁ n
· intro b x f hb h
exact if hfbx' : f x = b then ⟨0, hfbx'⟩
else
have : f b ≠ b ∧ b ≠ x := ne_and_ne_of_swap_mul_apply_ne_self hb
have hb : (swap x (f⁻¹ x) * f⁻¹) (f⁻¹ b) ≠ f⁻¹ b := by
rw [mul_apply, swap_apply_def]
split_ifs <;>
simp only [inv_eq_iff_eq, Perm.mul_apply, zpow_negSucc, Ne, Perm.apply_inv_self] at *
<;> tauto
let ⟨i, hi⟩ :=
isCycle_swap_mul_aux₁ n hb
(show (f⁻¹ ^ n) (f⁻¹ x) = f⁻¹ b by
rw [← zpow_natCast, ← h, ← mul_apply, ← mul_apply, ← mul_apply, zpow_negSucc,
← inv_pow, pow_succ, mul_assoc, mul_assoc, inv_mul_self, mul_one, zpow_natCast,
← pow_succ', ← pow_succ])
have h : (swap x (f⁻¹ x) * f⁻¹) (f x) = f⁻¹ x := by
rw [mul_apply, inv_apply_self, swap_apply_left]
⟨-i, by
rw [← add_sub_cancel_right i 1, neg_sub, sub_eq_add_neg, zpow_add, zpow_one, zpow_neg,
← inv_zpow, mul_inv_rev, swap_inv, mul_swap_eq_swap_mul, inv_apply_self, swap_comm _ x,
zpow_add, zpow_one, mul_apply, mul_apply (_ ^ i), h, hi, mul_apply, apply_inv_self,
swap_apply_of_ne_of_ne this.2 (Ne.symm hfbx')]⟩
#align equiv.perm.is_cycle_swap_mul_aux₂ Equiv.Perm.isCycle_swap_mul_aux₂
theorem IsCycle.eq_swap_of_apply_apply_eq_self {α : Type*} [DecidableEq α] {f : Perm α}
(hf : IsCycle f) {x : α} (hfx : f x ≠ x) (hffx : f (f x) = x) : f = swap x (f x) :=
Equiv.ext fun y =>
let ⟨z, hz⟩ := hf
let ⟨i, hi⟩ := hz.2 hfx
if hyx : y = x then by simp [hyx]
else
if hfyx : y = f x then by simp [hfyx, hffx]
else by
rw [swap_apply_of_ne_of_ne hyx hfyx]
refine by_contradiction fun hy => ?_
cases' hz.2 hy with j hj
rw [← sub_add_cancel j i, zpow_add, mul_apply, hi] at hj
cases' zpow_apply_eq_of_apply_apply_eq_self hffx (j - i) with hji hji
· rw [← hj, hji] at hyx
tauto
· rw [← hj, hji] at hfyx
tauto
#align equiv.perm.is_cycle.eq_swap_of_apply_apply_eq_self Equiv.Perm.IsCycle.eq_swap_of_apply_apply_eq_self
theorem IsCycle.swap_mul {α : Type*} [DecidableEq α] {f : Perm α} (hf : IsCycle f) {x : α}
(hx : f x ≠ x) (hffx : f (f x) ≠ x) : IsCycle (swap x (f x) * f) :=
⟨f x, by simp [swap_apply_def, mul_apply, if_neg hffx, f.injective.eq_iff, if_neg hx, hx],
fun y hy =>
let ⟨i, hi⟩ := hf.exists_zpow_eq hx (ne_and_ne_of_swap_mul_apply_ne_self hy).1
-- Porting note: Needed to add Perm α typehint, otherwise does not know how to coerce to fun
have hi : (f ^ (i - 1) : Perm α) (f x) = y :=
calc
(f ^ (i - 1) : Perm α) (f x) = (f ^ (i - 1) * f ^ (1 : ℤ) : Perm α) x := by simp
_ = y := by rwa [← zpow_add, sub_add_cancel]
isCycle_swap_mul_aux₂ (i - 1) hy hi⟩
#align equiv.perm.is_cycle.swap_mul Equiv.Perm.IsCycle.swap_mul
theorem IsCycle.sign {f : Perm α} (hf : IsCycle f) : sign f = -(-1) ^ f.support.card :=
let ⟨x, hx⟩ := hf
calc
Perm.sign f = Perm.sign (swap x (f x) * (swap x (f x) * f)) := by
{rw [← mul_assoc, mul_def, mul_def, swap_swap, trans_refl]}
_ = -(-1) ^ f.support.card :=
if h1 : f (f x) = x then by
have h : swap x (f x) * f = 1 := by
simp only [mul_def, one_def]
rw [hf.eq_swap_of_apply_apply_eq_self hx.1 h1, swap_apply_left, swap_swap]
rw [sign_mul, sign_swap hx.1.symm, h, sign_one,
hf.eq_swap_of_apply_apply_eq_self hx.1 h1, card_support_swap hx.1.symm]
rfl
else by
have h : card (support (swap x (f x) * f)) + 1 = card (support f) := by
rw [← insert_erase (mem_support.2 hx.1), support_swap_mul_eq _ _ h1,
card_insert_of_not_mem (not_mem_erase _ _), sdiff_singleton_eq_erase]
have : card (support (swap x (f x) * f)) < card (support f) :=
card_support_swap_mul hx.1
rw [sign_mul, sign_swap hx.1.symm, (hf.swap_mul hx.1 h1).sign, ← h]
simp only [mul_neg, neg_mul, one_mul, neg_neg, pow_add, pow_one, mul_one]
termination_by f.support.card
#align equiv.perm.is_cycle.sign Equiv.Perm.IsCycle.sign
theorem IsCycle.of_pow {n : ℕ} (h1 : IsCycle (f ^ n)) (h2 : f.support ⊆ (f ^ n).support) :
IsCycle f := by
have key : ∀ x : α, (f ^ n) x ≠ x ↔ f x ≠ x := by
simp_rw [← mem_support, ← Finset.ext_iff]
exact (support_pow_le _ n).antisymm h2
obtain ⟨x, hx1, hx2⟩ := h1
refine ⟨x, (key x).mp hx1, fun y hy => ?_⟩
cases' hx2 ((key y).mpr hy) with i _
exact ⟨n * i, by rwa [zpow_mul]⟩
#align equiv.perm.is_cycle.of_pow Equiv.Perm.IsCycle.of_pow
-- The lemma `support_zpow_le` is relevant. It means that `h2` is equivalent to
-- `σ.support = (σ ^ n).support`, as well as to `σ.support.card ≤ (σ ^ n).support.card`.
| Mathlib/GroupTheory/Perm/Cycle/Basic.lean | 539 | 544 | theorem IsCycle.of_zpow {n : ℤ} (h1 : IsCycle (f ^ n)) (h2 : f.support ⊆ (f ^ n).support) :
IsCycle f := by |
cases n
· exact h1.of_pow h2
· simp only [le_eq_subset, zpow_negSucc, Perm.support_inv] at h1 h2
exact (inv_inv (f ^ _) ▸ h1.inv).of_pow h2
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Kevin Buzzard
-/
import Mathlib.Algebra.BigOperators.NatAntidiagonal
import Mathlib.Algebra.GeomSum
import Mathlib.Data.Fintype.BigOperators
import Mathlib.RingTheory.PowerSeries.Inverse
import Mathlib.RingTheory.PowerSeries.WellKnown
import Mathlib.Tactic.FieldSimp
#align_import number_theory.bernoulli from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Bernoulli numbers
The Bernoulli numbers are a sequence of rational numbers that frequently show up in
number theory.
## Mathematical overview
The Bernoulli numbers $(B_0, B_1, B_2, \ldots)=(1, -1/2, 1/6, 0, -1/30, \ldots)$ are
a sequence of rational numbers. They show up in the formula for the sums of $k$th
powers. They are related to the Taylor series expansions of $x/\tan(x)$ and
of $\coth(x)$, and also show up in the values that the Riemann Zeta function
takes both at both negative and positive integers (and hence in the
theory of modular forms). For example, if $1 \leq n$ is even then
$$\zeta(2n)=\sum_{t\geq1}t^{-2n}=(-1)^{n+1}\frac{(2\pi)^{2n}B_{2n}}{2(2n)!}.$$
Note however that this result is not yet formalised in Lean.
The Bernoulli numbers can be formally defined using the power series
$$\sum B_n\frac{t^n}{n!}=\frac{t}{1-e^{-t}}$$
although that happens to not be the definition in mathlib (this is an *implementation
detail* and need not concern the mathematician).
Note that $B_1=-1/2$, meaning that we are using the $B_n^-$ of
[from Wikipedia](https://en.wikipedia.org/wiki/Bernoulli_number).
## Implementation detail
The Bernoulli numbers are defined using well-founded induction, by the formula
$$B_n=1-\sum_{k\lt n}\frac{\binom{n}{k}}{n-k+1}B_k.$$
This formula is true for all $n$ and in particular $B_0=1$. Note that this is the definition
for positive Bernoulli numbers, which we call `bernoulli'`. The negative Bernoulli numbers are
then defined as `bernoulli := (-1)^n * bernoulli'`.
## Main theorems
`sum_bernoulli : ∑ k ∈ Finset.range n, (n.choose k : ℚ) * bernoulli k = if n = 1 then 1 else 0`
-/
open Nat Finset Finset.Nat PowerSeries
variable (A : Type*) [CommRing A] [Algebra ℚ A]
/-! ### Definitions -/
/-- The Bernoulli numbers:
the $n$-th Bernoulli number $B_n$ is defined recursively via
$$B_n = 1 - \sum_{k < n} \binom{n}{k}\frac{B_k}{n+1-k}$$ -/
def bernoulli' : ℕ → ℚ :=
WellFounded.fix Nat.lt_wfRel.wf fun n bernoulli' =>
1 - ∑ k : Fin n, n.choose k / (n - k + 1) * bernoulli' k k.2
#align bernoulli' bernoulli'
theorem bernoulli'_def' (n : ℕ) :
bernoulli' n = 1 - ∑ k : Fin n, n.choose k / (n - k + 1) * bernoulli' k :=
WellFounded.fix_eq _ _ _
#align bernoulli'_def' bernoulli'_def'
theorem bernoulli'_def (n : ℕ) :
bernoulli' n = 1 - ∑ k ∈ range n, n.choose k / (n - k + 1) * bernoulli' k := by
rw [bernoulli'_def', ← Fin.sum_univ_eq_sum_range]
#align bernoulli'_def bernoulli'_def
theorem bernoulli'_spec (n : ℕ) :
(∑ k ∈ range n.succ, (n.choose (n - k) : ℚ) / (n - k + 1) * bernoulli' k) = 1 := by
rw [sum_range_succ_comm, bernoulli'_def n, tsub_self, choose_zero_right, sub_self, zero_add,
div_one, cast_one, one_mul, sub_add, ← sum_sub_distrib, ← sub_eq_zero, sub_sub_cancel_left,
neg_eq_zero]
exact Finset.sum_eq_zero (fun x hx => by rw [choose_symm (le_of_lt (mem_range.1 hx)), sub_self])
#align bernoulli'_spec bernoulli'_spec
theorem bernoulli'_spec' (n : ℕ) :
(∑ k ∈ antidiagonal n, ((k.1 + k.2).choose k.2 : ℚ) / (k.2 + 1) * bernoulli' k.1) = 1 := by
refine ((sum_antidiagonal_eq_sum_range_succ_mk _ n).trans ?_).trans (bernoulli'_spec n)
refine sum_congr rfl fun x hx => ?_
simp only [add_tsub_cancel_of_le, mem_range_succ_iff.mp hx, cast_sub]
#align bernoulli'_spec' bernoulli'_spec'
/-! ### Examples -/
section Examples
@[simp]
theorem bernoulli'_zero : bernoulli' 0 = 1 := by
rw [bernoulli'_def]
norm_num
#align bernoulli'_zero bernoulli'_zero
@[simp]
theorem bernoulli'_one : bernoulli' 1 = 1 / 2 := by
rw [bernoulli'_def]
norm_num
#align bernoulli'_one bernoulli'_one
@[simp]
theorem bernoulli'_two : bernoulli' 2 = 1 / 6 := by
rw [bernoulli'_def]
norm_num [sum_range_succ, sum_range_succ, sum_range_zero]
#align bernoulli'_two bernoulli'_two
@[simp]
theorem bernoulli'_three : bernoulli' 3 = 0 := by
rw [bernoulli'_def]
norm_num [sum_range_succ, sum_range_succ, sum_range_zero]
#align bernoulli'_three bernoulli'_three
@[simp]
| Mathlib/NumberTheory/Bernoulli.lean | 128 | 131 | theorem bernoulli'_four : bernoulli' 4 = -1 / 30 := by |
have : Nat.choose 4 2 = 6 := by decide -- shrug
rw [bernoulli'_def]
norm_num [sum_range_succ, sum_range_succ, sum_range_zero, this]
|
/-
Copyright (c) 2020 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker, Devon Tuma
-/
import Mathlib.Algebra.Polynomial.Roots
import Mathlib.Analysis.Asymptotics.AsymptoticEquivalent
import Mathlib.Analysis.Asymptotics.SpecificAsymptotics
#align_import analysis.special_functions.polynomials from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Limits related to polynomial and rational functions
This file proves basic facts about limits of polynomial and rationals functions.
The main result is `eval_is_equivalent_at_top_eval_lead`, which states that for
any polynomial `P` of degree `n` with leading coefficient `a`, the corresponding
polynomial function is equivalent to `a * x^n` as `x` goes to +∞.
We can then use this result to prove various limits for polynomial and rational
functions, depending on the degrees and leading coefficients of the considered
polynomials.
-/
open Filter Finset Asymptotics
open Asymptotics Polynomial Topology
namespace Polynomial
variable {𝕜 : Type*} [NormedLinearOrderedField 𝕜] (P Q : 𝕜[X])
theorem eventually_no_roots (hP : P ≠ 0) : ∀ᶠ x in atTop, ¬P.IsRoot x :=
atTop_le_cofinite <| (finite_setOf_isRoot hP).compl_mem_cofinite
#align polynomial.eventually_no_roots Polynomial.eventually_no_roots
variable [OrderTopology 𝕜]
section PolynomialAtTop
theorem isEquivalent_atTop_lead :
(fun x => eval x P) ~[atTop] fun x => P.leadingCoeff * x ^ P.natDegree := by
by_cases h : P = 0
· simp [h, IsEquivalent.refl]
· simp only [Polynomial.eval_eq_sum_range, sum_range_succ]
exact
IsLittleO.add_isEquivalent
(IsLittleO.sum fun i hi =>
IsLittleO.const_mul_left
((IsLittleO.const_mul_right fun hz => h <| leadingCoeff_eq_zero.mp hz) <|
isLittleO_pow_pow_atTop_of_lt (mem_range.mp hi))
_)
IsEquivalent.refl
#align polynomial.is_equivalent_at_top_lead Polynomial.isEquivalent_atTop_lead
theorem tendsto_atTop_of_leadingCoeff_nonneg (hdeg : 0 < P.degree) (hnng : 0 ≤ P.leadingCoeff) :
Tendsto (fun x => eval x P) atTop atTop :=
P.isEquivalent_atTop_lead.symm.tendsto_atTop <|
tendsto_const_mul_pow_atTop (natDegree_pos_iff_degree_pos.2 hdeg).ne' <|
hnng.lt_of_ne' <| leadingCoeff_ne_zero.mpr <| ne_zero_of_degree_gt hdeg
#align polynomial.tendsto_at_top_of_leading_coeff_nonneg Polynomial.tendsto_atTop_of_leadingCoeff_nonneg
theorem tendsto_atTop_iff_leadingCoeff_nonneg :
Tendsto (fun x => eval x P) atTop atTop ↔ 0 < P.degree ∧ 0 ≤ P.leadingCoeff := by
refine ⟨fun h => ?_, fun h => tendsto_atTop_of_leadingCoeff_nonneg P h.1 h.2⟩
have : Tendsto (fun x => P.leadingCoeff * x ^ P.natDegree) atTop atTop :=
(isEquivalent_atTop_lead P).tendsto_atTop h
rw [tendsto_const_mul_pow_atTop_iff, ← pos_iff_ne_zero, natDegree_pos_iff_degree_pos] at this
exact ⟨this.1, this.2.le⟩
#align polynomial.tendsto_at_top_iff_leading_coeff_nonneg Polynomial.tendsto_atTop_iff_leadingCoeff_nonneg
theorem tendsto_atBot_iff_leadingCoeff_nonpos :
Tendsto (fun x => eval x P) atTop atBot ↔ 0 < P.degree ∧ P.leadingCoeff ≤ 0 := by
simp only [← tendsto_neg_atTop_iff, ← eval_neg, tendsto_atTop_iff_leadingCoeff_nonneg,
degree_neg, leadingCoeff_neg, neg_nonneg]
#align polynomial.tendsto_at_bot_iff_leading_coeff_nonpos Polynomial.tendsto_atBot_iff_leadingCoeff_nonpos
theorem tendsto_atBot_of_leadingCoeff_nonpos (hdeg : 0 < P.degree) (hnps : P.leadingCoeff ≤ 0) :
Tendsto (fun x => eval x P) atTop atBot :=
P.tendsto_atBot_iff_leadingCoeff_nonpos.2 ⟨hdeg, hnps⟩
#align polynomial.tendsto_at_bot_of_leading_coeff_nonpos Polynomial.tendsto_atBot_of_leadingCoeff_nonpos
theorem abs_tendsto_atTop (hdeg : 0 < P.degree) :
Tendsto (fun x => abs <| eval x P) atTop atTop := by
rcases le_total 0 P.leadingCoeff with hP | hP
· exact tendsto_abs_atTop_atTop.comp (P.tendsto_atTop_of_leadingCoeff_nonneg hdeg hP)
· exact tendsto_abs_atBot_atTop.comp (P.tendsto_atBot_of_leadingCoeff_nonpos hdeg hP)
#align polynomial.abs_tendsto_at_top Polynomial.abs_tendsto_atTop
theorem abs_isBoundedUnder_iff :
(IsBoundedUnder (· ≤ ·) atTop fun x => |eval x P|) ↔ P.degree ≤ 0 := by
refine ⟨fun h => ?_, fun h => ⟨|P.coeff 0|, eventually_map.mpr (eventually_of_forall
(forall_imp (fun _ => le_of_eq) fun x => congr_arg abs <| _root_.trans (congr_arg (eval x)
(eq_C_of_degree_le_zero h)) eval_C))⟩⟩
contrapose! h
exact not_isBoundedUnder_of_tendsto_atTop (abs_tendsto_atTop P h)
#align polynomial.abs_is_bounded_under_iff Polynomial.abs_isBoundedUnder_iff
theorem abs_tendsto_atTop_iff : Tendsto (fun x => abs <| eval x P) atTop atTop ↔ 0 < P.degree :=
⟨fun h => not_le.mp (mt (abs_isBoundedUnder_iff P).mpr (not_isBoundedUnder_of_tendsto_atTop h)),
abs_tendsto_atTop P⟩
#align polynomial.abs_tendsto_at_top_iff Polynomial.abs_tendsto_atTop_iff
theorem tendsto_nhds_iff {c : 𝕜} :
Tendsto (fun x => eval x P) atTop (𝓝 c) ↔ P.leadingCoeff = c ∧ P.degree ≤ 0 := by
refine ⟨fun h => ?_, fun h => ?_⟩
· have := P.isEquivalent_atTop_lead.tendsto_nhds h
by_cases hP : P.leadingCoeff = 0
· simp only [hP, zero_mul, tendsto_const_nhds_iff] at this
exact ⟨_root_.trans hP this, by simp [leadingCoeff_eq_zero.1 hP]⟩
· rw [tendsto_const_mul_pow_nhds_iff hP, natDegree_eq_zero_iff_degree_le_zero] at this
exact this.symm
· refine P.isEquivalent_atTop_lead.symm.tendsto_nhds ?_
have : P.natDegree = 0 := natDegree_eq_zero_iff_degree_le_zero.2 h.2
simp only [h.1, this, pow_zero, mul_one]
exact tendsto_const_nhds
#align polynomial.tendsto_nhds_iff Polynomial.tendsto_nhds_iff
end PolynomialAtTop
section PolynomialDivAtTop
theorem isEquivalent_atTop_div :
(fun x => eval x P / eval x Q) ~[atTop] fun x =>
P.leadingCoeff / Q.leadingCoeff * x ^ (P.natDegree - Q.natDegree : ℤ) := by
by_cases hP : P = 0
· simp [hP, IsEquivalent.refl]
by_cases hQ : Q = 0
· simp [hQ, IsEquivalent.refl]
refine
(P.isEquivalent_atTop_lead.symm.div Q.isEquivalent_atTop_lead.symm).symm.trans
(EventuallyEq.isEquivalent ((eventually_gt_atTop 0).mono fun x hx => ?_))
simp [← div_mul_div_comm, hP, hQ, zpow_sub₀ hx.ne.symm]
#align polynomial.is_equivalent_at_top_div Polynomial.isEquivalent_atTop_div
theorem div_tendsto_zero_of_degree_lt (hdeg : P.degree < Q.degree) :
Tendsto (fun x => eval x P / eval x Q) atTop (𝓝 0) := by
by_cases hP : P = 0
· simp [hP, tendsto_const_nhds]
rw [← natDegree_lt_natDegree_iff hP] at hdeg
refine (isEquivalent_atTop_div P Q).symm.tendsto_nhds ?_
rw [← mul_zero]
refine (tendsto_zpow_atTop_zero ?_).const_mul _
omega
#align polynomial.div_tendsto_zero_of_degree_lt Polynomial.div_tendsto_zero_of_degree_lt
theorem div_tendsto_zero_iff_degree_lt (hQ : Q ≠ 0) :
Tendsto (fun x => eval x P / eval x Q) atTop (𝓝 0) ↔ P.degree < Q.degree := by
refine ⟨fun h => ?_, div_tendsto_zero_of_degree_lt P Q⟩
by_cases hPQ : P.leadingCoeff / Q.leadingCoeff = 0
· simp only [div_eq_mul_inv, inv_eq_zero, mul_eq_zero] at hPQ
cases' hPQ with hP0 hQ0
· rw [leadingCoeff_eq_zero.1 hP0, degree_zero]
exact bot_lt_iff_ne_bot.2 fun hQ' => hQ (degree_eq_bot.1 hQ')
· exact absurd (leadingCoeff_eq_zero.1 hQ0) hQ
· have := (isEquivalent_atTop_div P Q).tendsto_nhds h
rw [tendsto_const_mul_zpow_atTop_nhds_iff hPQ] at this
cases' this with h h
· exact absurd h.2 hPQ
· rw [sub_lt_iff_lt_add, zero_add, Int.ofNat_lt] at h
exact degree_lt_degree h.1
#align polynomial.div_tendsto_zero_iff_degree_lt Polynomial.div_tendsto_zero_iff_degree_lt
theorem div_tendsto_leadingCoeff_div_of_degree_eq (hdeg : P.degree = Q.degree) :
Tendsto (fun x => eval x P / eval x Q) atTop (𝓝 <| P.leadingCoeff / Q.leadingCoeff) := by
refine (isEquivalent_atTop_div P Q).symm.tendsto_nhds ?_
rw [show (P.natDegree : ℤ) = Q.natDegree by simp [hdeg, natDegree]]
simp [tendsto_const_nhds]
#align polynomial.div_tendsto_leading_coeff_div_of_degree_eq Polynomial.div_tendsto_leadingCoeff_div_of_degree_eq
theorem div_tendsto_atTop_of_degree_gt' (hdeg : Q.degree < P.degree)
(hpos : 0 < P.leadingCoeff / Q.leadingCoeff) :
Tendsto (fun x => eval x P / eval x Q) atTop atTop := by
have hQ : Q ≠ 0 := fun h => by
simp only [h, div_zero, leadingCoeff_zero] at hpos
exact hpos.false
rw [← natDegree_lt_natDegree_iff hQ] at hdeg
refine (isEquivalent_atTop_div P Q).symm.tendsto_atTop ?_
apply Tendsto.const_mul_atTop hpos
apply tendsto_zpow_atTop_atTop
omega
#align polynomial.div_tendsto_at_top_of_degree_gt' Polynomial.div_tendsto_atTop_of_degree_gt'
theorem div_tendsto_atTop_of_degree_gt (hdeg : Q.degree < P.degree) (hQ : Q ≠ 0)
(hnng : 0 ≤ P.leadingCoeff / Q.leadingCoeff) :
Tendsto (fun x => eval x P / eval x Q) atTop atTop :=
have ratio_pos : 0 < P.leadingCoeff / Q.leadingCoeff :=
lt_of_le_of_ne hnng
(div_ne_zero (fun h => ne_zero_of_degree_gt hdeg <| leadingCoeff_eq_zero.mp h) fun h =>
hQ <| leadingCoeff_eq_zero.mp h).symm
div_tendsto_atTop_of_degree_gt' P Q hdeg ratio_pos
#align polynomial.div_tendsto_at_top_of_degree_gt Polynomial.div_tendsto_atTop_of_degree_gt
| Mathlib/Analysis/SpecialFunctions/Polynomials.lean | 195 | 205 | theorem div_tendsto_atBot_of_degree_gt' (hdeg : Q.degree < P.degree)
(hneg : P.leadingCoeff / Q.leadingCoeff < 0) :
Tendsto (fun x => eval x P / eval x Q) atTop atBot := by |
have hQ : Q ≠ 0 := fun h => by
simp only [h, div_zero, leadingCoeff_zero] at hneg
exact hneg.false
rw [← natDegree_lt_natDegree_iff hQ] at hdeg
refine (isEquivalent_atTop_div P Q).symm.tendsto_atBot ?_
apply Tendsto.const_mul_atTop_of_neg hneg
apply tendsto_zpow_atTop_atTop
omega
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Topology.Constructions
#align_import topology.continuous_on from "leanprover-community/mathlib"@"d4f691b9e5f94cfc64639973f3544c95f8d5d494"
/-!
# Neighborhoods and continuity relative to a subset
This file defines relative versions
* `nhdsWithin` of `nhds`
* `ContinuousOn` of `Continuous`
* `ContinuousWithinAt` of `ContinuousAt`
and proves their basic properties, including the relationships between
these restricted notions and the corresponding notions for the subtype
equipped with the subspace topology.
## Notation
* `𝓝 x`: the filter of neighborhoods of a point `x`;
* `𝓟 s`: the principal filter of a set `s`;
* `𝓝[s] x`: the filter `nhdsWithin x s` of neighborhoods of a point `x` within a set `s`.
-/
open Set Filter Function Topology Filter
variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*}
variable [TopologicalSpace α]
@[simp]
theorem nhds_bind_nhdsWithin {a : α} {s : Set α} : ((𝓝 a).bind fun x => 𝓝[s] x) = 𝓝[s] a :=
bind_inf_principal.trans <| congr_arg₂ _ nhds_bind_nhds rfl
#align nhds_bind_nhds_within nhds_bind_nhdsWithin
@[simp]
theorem eventually_nhds_nhdsWithin {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ y in 𝓝 a, ∀ᶠ x in 𝓝[s] y, p x) ↔ ∀ᶠ x in 𝓝[s] a, p x :=
Filter.ext_iff.1 nhds_bind_nhdsWithin { x | p x }
#align eventually_nhds_nhds_within eventually_nhds_nhdsWithin
theorem eventually_nhdsWithin_iff {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ x in 𝓝[s] a, p x) ↔ ∀ᶠ x in 𝓝 a, x ∈ s → p x :=
eventually_inf_principal
#align eventually_nhds_within_iff eventually_nhdsWithin_iff
theorem frequently_nhdsWithin_iff {z : α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in 𝓝[s] z, p x) ↔ ∃ᶠ x in 𝓝 z, p x ∧ x ∈ s :=
frequently_inf_principal.trans <| by simp only [and_comm]
#align frequently_nhds_within_iff frequently_nhdsWithin_iff
theorem mem_closure_ne_iff_frequently_within {z : α} {s : Set α} :
z ∈ closure (s \ {z}) ↔ ∃ᶠ x in 𝓝[≠] z, x ∈ s := by
simp [mem_closure_iff_frequently, frequently_nhdsWithin_iff]
#align mem_closure_ne_iff_frequently_within mem_closure_ne_iff_frequently_within
@[simp]
theorem eventually_nhdsWithin_nhdsWithin {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ y in 𝓝[s] a, ∀ᶠ x in 𝓝[s] y, p x) ↔ ∀ᶠ x in 𝓝[s] a, p x := by
refine ⟨fun h => ?_, fun h => (eventually_nhds_nhdsWithin.2 h).filter_mono inf_le_left⟩
simp only [eventually_nhdsWithin_iff] at h ⊢
exact h.mono fun x hx hxs => (hx hxs).self_of_nhds hxs
#align eventually_nhds_within_nhds_within eventually_nhdsWithin_nhdsWithin
theorem nhdsWithin_eq (a : α) (s : Set α) :
𝓝[s] a = ⨅ t ∈ { t : Set α | a ∈ t ∧ IsOpen t }, 𝓟 (t ∩ s) :=
((nhds_basis_opens a).inf_principal s).eq_biInf
#align nhds_within_eq nhdsWithin_eq
theorem nhdsWithin_univ (a : α) : 𝓝[Set.univ] a = 𝓝 a := by
rw [nhdsWithin, principal_univ, inf_top_eq]
#align nhds_within_univ nhdsWithin_univ
theorem nhdsWithin_hasBasis {p : β → Prop} {s : β → Set α} {a : α} (h : (𝓝 a).HasBasis p s)
(t : Set α) : (𝓝[t] a).HasBasis p fun i => s i ∩ t :=
h.inf_principal t
#align nhds_within_has_basis nhdsWithin_hasBasis
theorem nhdsWithin_basis_open (a : α) (t : Set α) :
(𝓝[t] a).HasBasis (fun u => a ∈ u ∧ IsOpen u) fun u => u ∩ t :=
nhdsWithin_hasBasis (nhds_basis_opens a) t
#align nhds_within_basis_open nhdsWithin_basis_open
theorem mem_nhdsWithin {t : Set α} {a : α} {s : Set α} :
t ∈ 𝓝[s] a ↔ ∃ u, IsOpen u ∧ a ∈ u ∧ u ∩ s ⊆ t := by
simpa only [and_assoc, and_left_comm] using (nhdsWithin_basis_open a s).mem_iff
#align mem_nhds_within mem_nhdsWithin
theorem mem_nhdsWithin_iff_exists_mem_nhds_inter {t : Set α} {a : α} {s : Set α} :
t ∈ 𝓝[s] a ↔ ∃ u ∈ 𝓝 a, u ∩ s ⊆ t :=
(nhdsWithin_hasBasis (𝓝 a).basis_sets s).mem_iff
#align mem_nhds_within_iff_exists_mem_nhds_inter mem_nhdsWithin_iff_exists_mem_nhds_inter
theorem diff_mem_nhdsWithin_compl {x : α} {s : Set α} (hs : s ∈ 𝓝 x) (t : Set α) :
s \ t ∈ 𝓝[tᶜ] x :=
diff_mem_inf_principal_compl hs t
#align diff_mem_nhds_within_compl diff_mem_nhdsWithin_compl
theorem diff_mem_nhdsWithin_diff {x : α} {s t : Set α} (hs : s ∈ 𝓝[t] x) (t' : Set α) :
s \ t' ∈ 𝓝[t \ t'] x := by
rw [nhdsWithin, diff_eq, diff_eq, ← inf_principal, ← inf_assoc]
exact inter_mem_inf hs (mem_principal_self _)
#align diff_mem_nhds_within_diff diff_mem_nhdsWithin_diff
theorem nhds_of_nhdsWithin_of_nhds {s t : Set α} {a : α} (h1 : s ∈ 𝓝 a) (h2 : t ∈ 𝓝[s] a) :
t ∈ 𝓝 a := by
rcases mem_nhdsWithin_iff_exists_mem_nhds_inter.mp h2 with ⟨_, Hw, hw⟩
exact (𝓝 a).sets_of_superset ((𝓝 a).inter_sets Hw h1) hw
#align nhds_of_nhds_within_of_nhds nhds_of_nhdsWithin_of_nhds
theorem mem_nhdsWithin_iff_eventually {s t : Set α} {x : α} :
t ∈ 𝓝[s] x ↔ ∀ᶠ y in 𝓝 x, y ∈ s → y ∈ t :=
eventually_inf_principal
#align mem_nhds_within_iff_eventually mem_nhdsWithin_iff_eventually
theorem mem_nhdsWithin_iff_eventuallyEq {s t : Set α} {x : α} :
t ∈ 𝓝[s] x ↔ s =ᶠ[𝓝 x] (s ∩ t : Set α) := by
simp_rw [mem_nhdsWithin_iff_eventually, eventuallyEq_set, mem_inter_iff, iff_self_and]
#align mem_nhds_within_iff_eventually_eq mem_nhdsWithin_iff_eventuallyEq
theorem nhdsWithin_eq_iff_eventuallyEq {s t : Set α} {x : α} : 𝓝[s] x = 𝓝[t] x ↔ s =ᶠ[𝓝 x] t :=
set_eventuallyEq_iff_inf_principal.symm
#align nhds_within_eq_iff_eventually_eq nhdsWithin_eq_iff_eventuallyEq
theorem nhdsWithin_le_iff {s t : Set α} {x : α} : 𝓝[s] x ≤ 𝓝[t] x ↔ t ∈ 𝓝[s] x :=
set_eventuallyLE_iff_inf_principal_le.symm.trans set_eventuallyLE_iff_mem_inf_principal
#align nhds_within_le_iff nhdsWithin_le_iff
-- Porting note: golfed, dropped an unneeded assumption
theorem preimage_nhdsWithin_coinduced' {π : α → β} {s : Set β} {t : Set α} {a : α} (h : a ∈ t)
(hs : s ∈ @nhds β (.coinduced (fun x : t => π x) inferInstance) (π a)) :
π ⁻¹' s ∈ 𝓝[t] a := by
lift a to t using h
replace hs : (fun x : t => π x) ⁻¹' s ∈ 𝓝 a := preimage_nhds_coinduced hs
rwa [← map_nhds_subtype_val, mem_map]
#align preimage_nhds_within_coinduced' preimage_nhdsWithin_coinduced'ₓ
theorem mem_nhdsWithin_of_mem_nhds {s t : Set α} {a : α} (h : s ∈ 𝓝 a) : s ∈ 𝓝[t] a :=
mem_inf_of_left h
#align mem_nhds_within_of_mem_nhds mem_nhdsWithin_of_mem_nhds
theorem self_mem_nhdsWithin {a : α} {s : Set α} : s ∈ 𝓝[s] a :=
mem_inf_of_right (mem_principal_self s)
#align self_mem_nhds_within self_mem_nhdsWithin
theorem eventually_mem_nhdsWithin {a : α} {s : Set α} : ∀ᶠ x in 𝓝[s] a, x ∈ s :=
self_mem_nhdsWithin
#align eventually_mem_nhds_within eventually_mem_nhdsWithin
theorem inter_mem_nhdsWithin (s : Set α) {t : Set α} {a : α} (h : t ∈ 𝓝 a) : s ∩ t ∈ 𝓝[s] a :=
inter_mem self_mem_nhdsWithin (mem_inf_of_left h)
#align inter_mem_nhds_within inter_mem_nhdsWithin
theorem nhdsWithin_mono (a : α) {s t : Set α} (h : s ⊆ t) : 𝓝[s] a ≤ 𝓝[t] a :=
inf_le_inf_left _ (principal_mono.mpr h)
#align nhds_within_mono nhdsWithin_mono
theorem pure_le_nhdsWithin {a : α} {s : Set α} (ha : a ∈ s) : pure a ≤ 𝓝[s] a :=
le_inf (pure_le_nhds a) (le_principal_iff.2 ha)
#align pure_le_nhds_within pure_le_nhdsWithin
theorem mem_of_mem_nhdsWithin {a : α} {s t : Set α} (ha : a ∈ s) (ht : t ∈ 𝓝[s] a) : a ∈ t :=
pure_le_nhdsWithin ha ht
#align mem_of_mem_nhds_within mem_of_mem_nhdsWithin
theorem Filter.Eventually.self_of_nhdsWithin {p : α → Prop} {s : Set α} {x : α}
(h : ∀ᶠ y in 𝓝[s] x, p y) (hx : x ∈ s) : p x :=
mem_of_mem_nhdsWithin hx h
#align filter.eventually.self_of_nhds_within Filter.Eventually.self_of_nhdsWithin
theorem tendsto_const_nhdsWithin {l : Filter β} {s : Set α} {a : α} (ha : a ∈ s) :
Tendsto (fun _ : β => a) l (𝓝[s] a) :=
tendsto_const_pure.mono_right <| pure_le_nhdsWithin ha
#align tendsto_const_nhds_within tendsto_const_nhdsWithin
theorem nhdsWithin_restrict'' {a : α} (s : Set α) {t : Set α} (h : t ∈ 𝓝[s] a) :
𝓝[s] a = 𝓝[s ∩ t] a :=
le_antisymm (le_inf inf_le_left (le_principal_iff.mpr (inter_mem self_mem_nhdsWithin h)))
(inf_le_inf_left _ (principal_mono.mpr Set.inter_subset_left))
#align nhds_within_restrict'' nhdsWithin_restrict''
theorem nhdsWithin_restrict' {a : α} (s : Set α) {t : Set α} (h : t ∈ 𝓝 a) : 𝓝[s] a = 𝓝[s ∩ t] a :=
nhdsWithin_restrict'' s <| mem_inf_of_left h
#align nhds_within_restrict' nhdsWithin_restrict'
theorem nhdsWithin_restrict {a : α} (s : Set α) {t : Set α} (h₀ : a ∈ t) (h₁ : IsOpen t) :
𝓝[s] a = 𝓝[s ∩ t] a :=
nhdsWithin_restrict' s (IsOpen.mem_nhds h₁ h₀)
#align nhds_within_restrict nhdsWithin_restrict
theorem nhdsWithin_le_of_mem {a : α} {s t : Set α} (h : s ∈ 𝓝[t] a) : 𝓝[t] a ≤ 𝓝[s] a :=
nhdsWithin_le_iff.mpr h
#align nhds_within_le_of_mem nhdsWithin_le_of_mem
theorem nhdsWithin_le_nhds {a : α} {s : Set α} : 𝓝[s] a ≤ 𝓝 a := by
rw [← nhdsWithin_univ]
apply nhdsWithin_le_of_mem
exact univ_mem
#align nhds_within_le_nhds nhdsWithin_le_nhds
theorem nhdsWithin_eq_nhdsWithin' {a : α} {s t u : Set α} (hs : s ∈ 𝓝 a) (h₂ : t ∩ s = u ∩ s) :
𝓝[t] a = 𝓝[u] a := by rw [nhdsWithin_restrict' t hs, nhdsWithin_restrict' u hs, h₂]
#align nhds_within_eq_nhds_within' nhdsWithin_eq_nhdsWithin'
theorem nhdsWithin_eq_nhdsWithin {a : α} {s t u : Set α} (h₀ : a ∈ s) (h₁ : IsOpen s)
(h₂ : t ∩ s = u ∩ s) : 𝓝[t] a = 𝓝[u] a := by
rw [nhdsWithin_restrict t h₀ h₁, nhdsWithin_restrict u h₀ h₁, h₂]
#align nhds_within_eq_nhds_within nhdsWithin_eq_nhdsWithin
@[simp] theorem nhdsWithin_eq_nhds {a : α} {s : Set α} : 𝓝[s] a = 𝓝 a ↔ s ∈ 𝓝 a :=
inf_eq_left.trans le_principal_iff
#align nhds_within_eq_nhds nhdsWithin_eq_nhds
theorem IsOpen.nhdsWithin_eq {a : α} {s : Set α} (h : IsOpen s) (ha : a ∈ s) : 𝓝[s] a = 𝓝 a :=
nhdsWithin_eq_nhds.2 <| h.mem_nhds ha
#align is_open.nhds_within_eq IsOpen.nhdsWithin_eq
| Mathlib/Topology/ContinuousOn.lean | 223 | 228 | theorem preimage_nhds_within_coinduced {π : α → β} {s : Set β} {t : Set α} {a : α} (h : a ∈ t)
(ht : IsOpen t)
(hs : s ∈ @nhds β (.coinduced (fun x : t => π x) inferInstance) (π a)) :
π ⁻¹' s ∈ 𝓝 a := by |
rw [← ht.nhdsWithin_eq h]
exact preimage_nhdsWithin_coinduced' h hs
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Algebra.Order.BigOperators.Ring.Finset
import Mathlib.Data.NNRat.Defs
/-! # Casting lemmas for non-negative rational numbers involving sums and products
-/
variable {ι α : Type*}
namespace NNRat
@[norm_cast]
theorem coe_list_sum (l : List ℚ≥0) : (l.sum : ℚ) = (l.map (↑)).sum :=
map_list_sum coeHom _
#align nnrat.coe_list_sum NNRat.coe_list_sum
@[norm_cast]
theorem coe_list_prod (l : List ℚ≥0) : (l.prod : ℚ) = (l.map (↑)).prod :=
map_list_prod coeHom _
#align nnrat.coe_list_prod NNRat.coe_list_prod
@[norm_cast]
theorem coe_multiset_sum (s : Multiset ℚ≥0) : (s.sum : ℚ) = (s.map (↑)).sum :=
map_multiset_sum coeHom _
#align nnrat.coe_multiset_sum NNRat.coe_multiset_sum
@[norm_cast]
theorem coe_multiset_prod (s : Multiset ℚ≥0) : (s.prod : ℚ) = (s.map (↑)).prod :=
map_multiset_prod coeHom _
#align nnrat.coe_multiset_prod NNRat.coe_multiset_prod
@[norm_cast]
theorem coe_sum {s : Finset α} {f : α → ℚ≥0} : ↑(∑ a ∈ s, f a) = ∑ a ∈ s, (f a : ℚ) :=
map_sum coeHom _ _
#align nnrat.coe_sum NNRat.coe_sum
| Mathlib/Data/NNRat/BigOperators.lean | 41 | 44 | theorem toNNRat_sum_of_nonneg {s : Finset α} {f : α → ℚ} (hf : ∀ a, a ∈ s → 0 ≤ f a) :
(∑ a ∈ s, f a).toNNRat = ∑ a ∈ s, (f a).toNNRat := by |
rw [← coe_inj, coe_sum, Rat.coe_toNNRat _ (Finset.sum_nonneg hf)]
exact Finset.sum_congr rfl fun x hxs ↦ by rw [Rat.coe_toNNRat _ (hf x hxs)]
|
/-
Copyright (c) 2018 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis
-/
import Mathlib.RingTheory.Valuation.Basic
import Mathlib.NumberTheory.Padics.PadicNorm
import Mathlib.Analysis.Normed.Field.Basic
#align_import number_theory.padics.padic_numbers from "leanprover-community/mathlib"@"b9b2114f7711fec1c1e055d507f082f8ceb2c3b7"
/-!
# p-adic numbers
This file defines the `p`-adic numbers (rationals) `ℚ_[p]` as
the completion of `ℚ` with respect to the `p`-adic norm.
We show that the `p`-adic norm on `ℚ` extends to `ℚ_[p]`, that `ℚ` is embedded in `ℚ_[p]`,
and that `ℚ_[p]` is Cauchy complete.
## Important definitions
* `Padic` : the type of `p`-adic numbers
* `padicNormE` : the rational valued `p`-adic norm on `ℚ_[p]`
* `Padic.addValuation` : the additive `p`-adic valuation on `ℚ_[p]`, with values in `WithTop ℤ`
## Notation
We introduce the notation `ℚ_[p]` for the `p`-adic numbers.
## Implementation notes
Much, but not all, of this file assumes that `p` is prime. This assumption is inferred automatically
by taking `[Fact p.Prime]` as a type class argument.
We use the same concrete Cauchy sequence construction that is used to construct `ℝ`.
`ℚ_[p]` inherits a field structure from this construction.
The extension of the norm on `ℚ` to `ℚ_[p]` is *not* analogous to extending the absolute value to
`ℝ` and hence the proof that `ℚ_[p]` is complete is different from the proof that ℝ is complete.
A small special-purpose simplification tactic, `padic_index_simp`, is used to manipulate sequence
indices in the proof that the norm extends.
`padicNormE` is the rational-valued `p`-adic norm on `ℚ_[p]`.
To instantiate `ℚ_[p]` as a normed field, we must cast this into an `ℝ`-valued norm.
The `ℝ`-valued norm, using notation `‖ ‖` from normed spaces,
is the canonical representation of this norm.
`simp` prefers `padicNorm` to `padicNormE` when possible.
Since `padicNormE` and `‖ ‖` have different types, `simp` does not rewrite one to the other.
Coercions from `ℚ` to `ℚ_[p]` are set up to work with the `norm_cast` tactic.
## References
* [F. Q. Gouvêa, *p-adic numbers*][gouvea1997]
* [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019]
* <https://en.wikipedia.org/wiki/P-adic_number>
## Tags
p-adic, p adic, padic, norm, valuation, cauchy, completion, p-adic completion
-/
noncomputable section
open scoped Classical
open Nat multiplicity padicNorm CauSeq CauSeq.Completion Metric
/-- The type of Cauchy sequences of rationals with respect to the `p`-adic norm. -/
abbrev PadicSeq (p : ℕ) :=
CauSeq _ (padicNorm p)
#align padic_seq PadicSeq
namespace PadicSeq
section
variable {p : ℕ} [Fact p.Prime]
/-- The `p`-adic norm of the entries of a nonzero Cauchy sequence of rationals is eventually
constant. -/
theorem stationary {f : CauSeq ℚ (padicNorm p)} (hf : ¬f ≈ 0) :
∃ N, ∀ m n, N ≤ m → N ≤ n → padicNorm p (f n) = padicNorm p (f m) :=
have : ∃ ε > 0, ∃ N1, ∀ j ≥ N1, ε ≤ padicNorm p (f j) :=
CauSeq.abv_pos_of_not_limZero <| not_limZero_of_not_congr_zero hf
let ⟨ε, hε, N1, hN1⟩ := this
let ⟨N2, hN2⟩ := CauSeq.cauchy₂ f hε
⟨max N1 N2, fun n m hn hm ↦ by
have : padicNorm p (f n - f m) < ε := hN2 _ (max_le_iff.1 hn).2 _ (max_le_iff.1 hm).2
have : padicNorm p (f n - f m) < padicNorm p (f n) :=
lt_of_lt_of_le this <| hN1 _ (max_le_iff.1 hn).1
have : padicNorm p (f n - f m) < max (padicNorm p (f n)) (padicNorm p (f m)) :=
lt_max_iff.2 (Or.inl this)
by_contra hne
rw [← padicNorm.neg (f m)] at hne
have hnam := add_eq_max_of_ne hne
rw [padicNorm.neg, max_comm] at hnam
rw [← hnam, sub_eq_add_neg, add_comm] at this
apply _root_.lt_irrefl _ this⟩
#align padic_seq.stationary PadicSeq.stationary
/-- For all `n ≥ stationaryPoint f hf`, the `p`-adic norm of `f n` is the same. -/
def stationaryPoint {f : PadicSeq p} (hf : ¬f ≈ 0) : ℕ :=
Classical.choose <| stationary hf
#align padic_seq.stationary_point PadicSeq.stationaryPoint
theorem stationaryPoint_spec {f : PadicSeq p} (hf : ¬f ≈ 0) :
∀ {m n},
stationaryPoint hf ≤ m → stationaryPoint hf ≤ n → padicNorm p (f n) = padicNorm p (f m) :=
@(Classical.choose_spec <| stationary hf)
#align padic_seq.stationary_point_spec PadicSeq.stationaryPoint_spec
/-- Since the norm of the entries of a Cauchy sequence is eventually stationary,
we can lift the norm to sequences. -/
def norm (f : PadicSeq p) : ℚ :=
if hf : f ≈ 0 then 0 else padicNorm p (f (stationaryPoint hf))
#align padic_seq.norm PadicSeq.norm
theorem norm_zero_iff (f : PadicSeq p) : f.norm = 0 ↔ f ≈ 0 := by
constructor
· intro h
by_contra hf
unfold norm at h
split_ifs at h
· contradiction
apply hf
intro ε hε
exists stationaryPoint hf
intro j hj
have heq := stationaryPoint_spec hf le_rfl hj
simpa [h, heq]
· intro h
simp [norm, h]
#align padic_seq.norm_zero_iff PadicSeq.norm_zero_iff
end
section Embedding
open CauSeq
variable {p : ℕ} [Fact p.Prime]
theorem equiv_zero_of_val_eq_of_equiv_zero {f g : PadicSeq p}
(h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) (hf : f ≈ 0) : g ≈ 0 := fun ε hε ↦
let ⟨i, hi⟩ := hf _ hε
⟨i, fun j hj ↦ by simpa [h] using hi _ hj⟩
#align padic_seq.equiv_zero_of_val_eq_of_equiv_zero PadicSeq.equiv_zero_of_val_eq_of_equiv_zero
theorem norm_nonzero_of_not_equiv_zero {f : PadicSeq p} (hf : ¬f ≈ 0) : f.norm ≠ 0 :=
hf ∘ f.norm_zero_iff.1
#align padic_seq.norm_nonzero_of_not_equiv_zero PadicSeq.norm_nonzero_of_not_equiv_zero
theorem norm_eq_norm_app_of_nonzero {f : PadicSeq p} (hf : ¬f ≈ 0) :
∃ k, f.norm = padicNorm p k ∧ k ≠ 0 :=
have heq : f.norm = padicNorm p (f <| stationaryPoint hf) := by simp [norm, hf]
⟨f <| stationaryPoint hf, heq, fun h ↦
norm_nonzero_of_not_equiv_zero hf (by simpa [h] using heq)⟩
#align padic_seq.norm_eq_norm_app_of_nonzero PadicSeq.norm_eq_norm_app_of_nonzero
theorem not_limZero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬LimZero (const (padicNorm p) q) :=
fun h' ↦ hq <| const_limZero.1 h'
#align padic_seq.not_lim_zero_const_of_nonzero PadicSeq.not_limZero_const_of_nonzero
theorem not_equiv_zero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬const (padicNorm p) q ≈ 0 :=
fun h : LimZero (const (padicNorm p) q - 0) ↦ not_limZero_const_of_nonzero hq <| by simpa using h
#align padic_seq.not_equiv_zero_const_of_nonzero PadicSeq.not_equiv_zero_const_of_nonzero
theorem norm_nonneg (f : PadicSeq p) : 0 ≤ f.norm :=
if hf : f ≈ 0 then by simp [hf, norm] else by simp [norm, hf, padicNorm.nonneg]
#align padic_seq.norm_nonneg PadicSeq.norm_nonneg
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_left_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v2 v3 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max (stationaryPoint hf) (max v2 v3))) := by
apply stationaryPoint_spec hf
· apply le_max_left
· exact le_rfl
#align padic_seq.lift_index_left_left PadicSeq.lift_index_left_left
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v3 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max v1 (max (stationaryPoint hf) v3))) := by
apply stationaryPoint_spec hf
· apply le_trans
· apply le_max_left _ v3
· apply le_max_right
· exact le_rfl
#align padic_seq.lift_index_left PadicSeq.lift_index_left
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_right {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v2 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max v1 (max v2 (stationaryPoint hf)))) := by
apply stationaryPoint_spec hf
· apply le_trans
· apply le_max_right v2
· apply le_max_right
· exact le_rfl
#align padic_seq.lift_index_right PadicSeq.lift_index_right
end Embedding
section Valuation
open CauSeq
variable {p : ℕ} [Fact p.Prime]
/-! ### Valuation on `PadicSeq` -/
/-- The `p`-adic valuation on `ℚ` lifts to `PadicSeq p`.
`Valuation f` is defined to be the valuation of the (`ℚ`-valued) stationary point of `f`. -/
def valuation (f : PadicSeq p) : ℤ :=
if hf : f ≈ 0 then 0 else padicValRat p (f (stationaryPoint hf))
#align padic_seq.valuation PadicSeq.valuation
theorem norm_eq_pow_val {f : PadicSeq p} (hf : ¬f ≈ 0) : f.norm = (p : ℚ) ^ (-f.valuation : ℤ) := by
rw [norm, valuation, dif_neg hf, dif_neg hf, padicNorm, if_neg]
intro H
apply CauSeq.not_limZero_of_not_congr_zero hf
intro ε hε
use stationaryPoint hf
intro n hn
rw [stationaryPoint_spec hf le_rfl hn]
simpa [H] using hε
#align padic_seq.norm_eq_pow_val PadicSeq.norm_eq_pow_val
theorem val_eq_iff_norm_eq {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) :
f.valuation = g.valuation ↔ f.norm = g.norm := by
rw [norm_eq_pow_val hf, norm_eq_pow_val hg, ← neg_inj, zpow_inj]
· exact mod_cast (Fact.out : p.Prime).pos
· exact mod_cast (Fact.out : p.Prime).ne_one
#align padic_seq.val_eq_iff_norm_eq PadicSeq.val_eq_iff_norm_eq
end Valuation
end PadicSeq
section
open PadicSeq
-- Porting note: Commented out `padic_index_simp` tactic
/-
private unsafe def index_simp_core (hh hf hg : expr)
(at_ : Interactive.Loc := Interactive.Loc.ns [none]) : tactic Unit := do
let [v1, v2, v3] ← [hh, hf, hg].mapM fun n => tactic.mk_app `` stationary_point [n] <|> return n
let e1 ← tactic.mk_app `` lift_index_left_left [hh, v2, v3] <|> return q(True)
let e2 ← tactic.mk_app `` lift_index_left [hf, v1, v3] <|> return q(True)
let e3 ← tactic.mk_app `` lift_index_right [hg, v1, v2] <|> return q(True)
let sl ← [e1, e2, e3].foldlM (fun s e => simp_lemmas.add s e) simp_lemmas.mk
when at_ (tactic.simp_target sl >> tactic.skip)
let hs ← at_.get_locals
hs (tactic.simp_hyp sl [])
#align index_simp_core index_simp_core
/-- This is a special-purpose tactic that lifts `padicNorm (f (stationary_point f))` to
`padicNorm (f (max _ _ _))`. -/
unsafe def tactic.interactive.padic_index_simp (l : interactive.parse interactive.types.pexpr_list)
(at_ : interactive.parse interactive.types.location) : tactic Unit := do
let [h, f, g] ← l.mapM tactic.i_to_expr
index_simp_core h f g at_
#align tactic.interactive.padic_index_simp tactic.interactive.padic_index_simp
-/
end
namespace PadicSeq
section Embedding
open CauSeq
variable {p : ℕ} [hp : Fact p.Prime]
theorem norm_mul (f g : PadicSeq p) : (f * g).norm = f.norm * g.norm :=
if hf : f ≈ 0 then by
have hg : f * g ≈ 0 := mul_equiv_zero' _ hf
simp only [hf, hg, norm, dif_pos, zero_mul]
else
if hg : g ≈ 0 then by
have hf : f * g ≈ 0 := mul_equiv_zero _ hg
simp only [hf, hg, norm, dif_pos, mul_zero]
else by
unfold norm
split_ifs with hfg
· exact (mul_not_equiv_zero hf hg hfg).elim
-- Porting note: originally `padic_index_simp [hfg, hf, hg]`
rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
apply padicNorm.mul
#align padic_seq.norm_mul PadicSeq.norm_mul
theorem eq_zero_iff_equiv_zero (f : PadicSeq p) : mk f = 0 ↔ f ≈ 0 :=
mk_eq
#align padic_seq.eq_zero_iff_equiv_zero PadicSeq.eq_zero_iff_equiv_zero
theorem ne_zero_iff_nequiv_zero (f : PadicSeq p) : mk f ≠ 0 ↔ ¬f ≈ 0 :=
not_iff_not.2 (eq_zero_iff_equiv_zero _)
#align padic_seq.ne_zero_iff_nequiv_zero PadicSeq.ne_zero_iff_nequiv_zero
theorem norm_const (q : ℚ) : norm (const (padicNorm p) q) = padicNorm p q :=
if hq : q = 0 then by
have : const (padicNorm p) q ≈ 0 := by simp [hq]; apply Setoid.refl (const (padicNorm p) 0)
subst hq; simp [norm, this]
else by
have : ¬const (padicNorm p) q ≈ 0 := not_equiv_zero_const_of_nonzero hq
simp [norm, this]
#align padic_seq.norm_const PadicSeq.norm_const
theorem norm_values_discrete (a : PadicSeq p) (ha : ¬a ≈ 0) : ∃ z : ℤ, a.norm = (p : ℚ) ^ (-z) := by
let ⟨k, hk, hk'⟩ := norm_eq_norm_app_of_nonzero ha
simpa [hk] using padicNorm.values_discrete hk'
#align padic_seq.norm_values_discrete PadicSeq.norm_values_discrete
theorem norm_one : norm (1 : PadicSeq p) = 1 := by
have h1 : ¬(1 : PadicSeq p) ≈ 0 := one_not_equiv_zero _
simp [h1, norm, hp.1.one_lt]
#align padic_seq.norm_one PadicSeq.norm_one
private theorem norm_eq_of_equiv_aux {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g)
(h : padicNorm p (f (stationaryPoint hf)) ≠ padicNorm p (g (stationaryPoint hg)))
(hlt : padicNorm p (g (stationaryPoint hg)) < padicNorm p (f (stationaryPoint hf))) :
False := by
have hpn : 0 < padicNorm p (f (stationaryPoint hf)) - padicNorm p (g (stationaryPoint hg)) :=
sub_pos_of_lt hlt
cases' hfg _ hpn with N hN
let i := max N (max (stationaryPoint hf) (stationaryPoint hg))
have hi : N ≤ i := le_max_left _ _
have hN' := hN _ hi
-- Porting note: originally `padic_index_simp [N, hf, hg] at hN' h hlt`
rw [lift_index_left hf N (stationaryPoint hg), lift_index_right hg N (stationaryPoint hf)]
at hN' h hlt
have hpne : padicNorm p (f i) ≠ padicNorm p (-g i) := by rwa [← padicNorm.neg (g i)] at h
rw [CauSeq.sub_apply, sub_eq_add_neg, add_eq_max_of_ne hpne, padicNorm.neg, max_eq_left_of_lt hlt]
at hN'
have : padicNorm p (f i) < padicNorm p (f i) := by
apply lt_of_lt_of_le hN'
apply sub_le_self
apply padicNorm.nonneg
exact lt_irrefl _ this
private theorem norm_eq_of_equiv {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g) :
padicNorm p (f (stationaryPoint hf)) = padicNorm p (g (stationaryPoint hg)) := by
by_contra h
cases'
Decidable.em
(padicNorm p (g (stationaryPoint hg)) < padicNorm p (f (stationaryPoint hf))) with
hlt hnlt
· exact norm_eq_of_equiv_aux hf hg hfg h hlt
· apply norm_eq_of_equiv_aux hg hf (Setoid.symm hfg) (Ne.symm h)
apply lt_of_le_of_ne
· apply le_of_not_gt hnlt
· apply h
theorem norm_equiv {f g : PadicSeq p} (hfg : f ≈ g) : f.norm = g.norm :=
if hf : f ≈ 0 then by
have hg : g ≈ 0 := Setoid.trans (Setoid.symm hfg) hf
simp [norm, hf, hg]
else by
have hg : ¬g ≈ 0 := hf ∘ Setoid.trans hfg
unfold norm; split_ifs; exact norm_eq_of_equiv hf hg hfg
#align padic_seq.norm_equiv PadicSeq.norm_equiv
private theorem norm_nonarchimedean_aux {f g : PadicSeq p} (hfg : ¬f + g ≈ 0) (hf : ¬f ≈ 0)
(hg : ¬g ≈ 0) : (f + g).norm ≤ max f.norm g.norm := by
unfold norm; split_ifs
-- Porting note: originally `padic_index_simp [hfg, hf, hg]`
rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
apply padicNorm.nonarchimedean
theorem norm_nonarchimedean (f g : PadicSeq p) : (f + g).norm ≤ max f.norm g.norm :=
if hfg : f + g ≈ 0 then by
have : 0 ≤ max f.norm g.norm := le_max_of_le_left (norm_nonneg _)
simpa only [hfg, norm]
else
if hf : f ≈ 0 then by
have hfg' : f + g ≈ g := by
change LimZero (f - 0) at hf
show LimZero (f + g - g); · simpa only [sub_zero, add_sub_cancel_right] using hf
have hcfg : (f + g).norm = g.norm := norm_equiv hfg'
have hcl : f.norm = 0 := (norm_zero_iff f).2 hf
have : max f.norm g.norm = g.norm := by rw [hcl]; exact max_eq_right (norm_nonneg _)
rw [this, hcfg]
else
if hg : g ≈ 0 then by
have hfg' : f + g ≈ f := by
change LimZero (g - 0) at hg
show LimZero (f + g - f); · simpa only [add_sub_cancel_left, sub_zero] using hg
have hcfg : (f + g).norm = f.norm := norm_equiv hfg'
have hcl : g.norm = 0 := (norm_zero_iff g).2 hg
have : max f.norm g.norm = f.norm := by rw [hcl]; exact max_eq_left (norm_nonneg _)
rw [this, hcfg]
else norm_nonarchimedean_aux hfg hf hg
#align padic_seq.norm_nonarchimedean PadicSeq.norm_nonarchimedean
theorem norm_eq {f g : PadicSeq p} (h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) :
f.norm = g.norm :=
if hf : f ≈ 0 then by
have hg : g ≈ 0 := equiv_zero_of_val_eq_of_equiv_zero h hf
simp only [hf, hg, norm, dif_pos]
else by
have hg : ¬g ≈ 0 := fun hg ↦
hf <| equiv_zero_of_val_eq_of_equiv_zero (by simp only [h, forall_const, eq_self_iff_true]) hg
simp only [hg, hf, norm, dif_neg, not_false_iff]
let i := max (stationaryPoint hf) (stationaryPoint hg)
have hpf : padicNorm p (f (stationaryPoint hf)) = padicNorm p (f i) := by
apply stationaryPoint_spec
· apply le_max_left
· exact le_rfl
have hpg : padicNorm p (g (stationaryPoint hg)) = padicNorm p (g i) := by
apply stationaryPoint_spec
· apply le_max_right
· exact le_rfl
rw [hpf, hpg, h]
#align padic_seq.norm_eq PadicSeq.norm_eq
theorem norm_neg (a : PadicSeq p) : (-a).norm = a.norm :=
norm_eq <| by simp
#align padic_seq.norm_neg PadicSeq.norm_neg
theorem norm_eq_of_add_equiv_zero {f g : PadicSeq p} (h : f + g ≈ 0) : f.norm = g.norm := by
have : LimZero (f + g - 0) := h
have : f ≈ -g := show LimZero (f - -g) by simpa only [sub_zero, sub_neg_eq_add]
have : f.norm = (-g).norm := norm_equiv this
simpa only [norm_neg] using this
#align padic_seq.norm_eq_of_add_equiv_zero PadicSeq.norm_eq_of_add_equiv_zero
theorem add_eq_max_of_ne {f g : PadicSeq p} (hfgne : f.norm ≠ g.norm) :
(f + g).norm = max f.norm g.norm :=
have hfg : ¬f + g ≈ 0 := mt norm_eq_of_add_equiv_zero hfgne
if hf : f ≈ 0 then by
have : LimZero (f - 0) := hf
have : f + g ≈ g := show LimZero (f + g - g) by simpa only [sub_zero, add_sub_cancel_right]
have h1 : (f + g).norm = g.norm := norm_equiv this
have h2 : f.norm = 0 := (norm_zero_iff _).2 hf
rw [h1, h2, max_eq_right (norm_nonneg _)]
else
if hg : g ≈ 0 then by
have : LimZero (g - 0) := hg
have : f + g ≈ f := show LimZero (f + g - f) by simpa only [add_sub_cancel_left, sub_zero]
have h1 : (f + g).norm = f.norm := norm_equiv this
have h2 : g.norm = 0 := (norm_zero_iff _).2 hg
rw [h1, h2, max_eq_left (norm_nonneg _)]
else by
unfold norm at hfgne ⊢; split_ifs at hfgne ⊢
-- Porting note: originally `padic_index_simp [hfg, hf, hg] at hfgne ⊢`
rw [lift_index_left hf, lift_index_right hg] at hfgne
· rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
exact padicNorm.add_eq_max_of_ne hfgne
#align padic_seq.add_eq_max_of_ne PadicSeq.add_eq_max_of_ne
end Embedding
end PadicSeq
/-- The `p`-adic numbers `ℚ_[p]` are the Cauchy completion of `ℚ` with respect to the `p`-adic norm.
-/
def Padic (p : ℕ) [Fact p.Prime] :=
CauSeq.Completion.Cauchy (padicNorm p)
#align padic Padic
/-- notation for p-padic rationals -/
notation "ℚ_[" p "]" => Padic p
namespace Padic
section Completion
variable {p : ℕ} [Fact p.Prime]
instance field : Field ℚ_[p] :=
Cauchy.field
instance : Inhabited ℚ_[p] :=
⟨0⟩
-- short circuits
instance : CommRing ℚ_[p] :=
Cauchy.commRing
instance : Ring ℚ_[p] :=
Cauchy.ring
instance : Zero ℚ_[p] := by infer_instance
instance : One ℚ_[p] := by infer_instance
instance : Add ℚ_[p] := by infer_instance
instance : Mul ℚ_[p] := by infer_instance
instance : Sub ℚ_[p] := by infer_instance
instance : Neg ℚ_[p] := by infer_instance
instance : Div ℚ_[p] := by infer_instance
instance : AddCommGroup ℚ_[p] := by infer_instance
/-- Builds the equivalence class of a Cauchy sequence of rationals. -/
def mk : PadicSeq p → ℚ_[p] :=
Quotient.mk'
#align padic.mk Padic.mk
variable (p)
theorem zero_def : (0 : ℚ_[p]) = ⟦0⟧ := rfl
#align padic.zero_def Padic.zero_def
theorem mk_eq {f g : PadicSeq p} : mk f = mk g ↔ f ≈ g :=
Quotient.eq'
#align padic.mk_eq Padic.mk_eq
theorem const_equiv {q r : ℚ} : const (padicNorm p) q ≈ const (padicNorm p) r ↔ q = r :=
⟨fun heq ↦ eq_of_sub_eq_zero <| const_limZero.1 heq, fun heq ↦ by
rw [heq]⟩
#align padic.const_equiv Padic.const_equiv
@[norm_cast]
theorem coe_inj {q r : ℚ} : (↑q : ℚ_[p]) = ↑r ↔ q = r :=
⟨(const_equiv p).1 ∘ Quotient.eq'.1, fun h ↦ by rw [h]⟩
#align padic.coe_inj Padic.coe_inj
instance : CharZero ℚ_[p] :=
⟨fun m n ↦ by
rw [← Rat.cast_natCast]
norm_cast
exact id⟩
@[norm_cast]
theorem coe_add : ∀ {x y : ℚ}, (↑(x + y) : ℚ_[p]) = ↑x + ↑y :=
Rat.cast_add _ _
#align padic.coe_add Padic.coe_add
@[norm_cast]
theorem coe_neg : ∀ {x : ℚ}, (↑(-x) : ℚ_[p]) = -↑x :=
Rat.cast_neg _
#align padic.coe_neg Padic.coe_neg
@[norm_cast]
theorem coe_mul : ∀ {x y : ℚ}, (↑(x * y) : ℚ_[p]) = ↑x * ↑y :=
Rat.cast_mul _ _
#align padic.coe_mul Padic.coe_mul
@[norm_cast]
theorem coe_sub : ∀ {x y : ℚ}, (↑(x - y) : ℚ_[p]) = ↑x - ↑y :=
Rat.cast_sub _ _
#align padic.coe_sub Padic.coe_sub
@[norm_cast]
theorem coe_div : ∀ {x y : ℚ}, (↑(x / y) : ℚ_[p]) = ↑x / ↑y :=
Rat.cast_div _ _
#align padic.coe_div Padic.coe_div
@[norm_cast]
theorem coe_one : (↑(1 : ℚ) : ℚ_[p]) = 1 := rfl
#align padic.coe_one Padic.coe_one
@[norm_cast]
theorem coe_zero : (↑(0 : ℚ) : ℚ_[p]) = 0 := rfl
#align padic.coe_zero Padic.coe_zero
end Completion
end Padic
/-- The rational-valued `p`-adic norm on `ℚ_[p]` is lifted from the norm on Cauchy sequences. The
canonical form of this function is the normed space instance, with notation `‖ ‖`. -/
def padicNormE {p : ℕ} [hp : Fact p.Prime] : AbsoluteValue ℚ_[p] ℚ where
toFun := Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _
map_mul' q r := Quotient.inductionOn₂ q r <| PadicSeq.norm_mul
nonneg' q := Quotient.inductionOn q <| PadicSeq.norm_nonneg
eq_zero' q := Quotient.inductionOn q fun r ↦ by
rw [Padic.zero_def, Quotient.eq]
exact PadicSeq.norm_zero_iff r
add_le' q r := by
trans
max ((Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _) q)
((Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _) r)
· exact Quotient.inductionOn₂ q r <| PadicSeq.norm_nonarchimedean
refine max_le_add_of_nonneg (Quotient.inductionOn q <| PadicSeq.norm_nonneg) ?_
exact Quotient.inductionOn r <| PadicSeq.norm_nonneg
#align padic_norm_e padicNormE
namespace padicNormE
section Embedding
open PadicSeq
variable {p : ℕ} [Fact p.Prime]
-- Porting note: Expanded `⟦f⟧` to `Padic.mk f`
theorem defn (f : PadicSeq p) {ε : ℚ} (hε : 0 < ε) :
∃ N, ∀ i ≥ N, padicNormE (Padic.mk f - f i : ℚ_[p]) < ε := by
dsimp [padicNormE]
change ∃ N, ∀ i ≥ N, (f - const _ (f i)).norm < ε
by_contra! h
cases' cauchy₂ f hε with N hN
rcases h N with ⟨i, hi, hge⟩
have hne : ¬f - const (padicNorm p) (f i) ≈ 0 := fun h ↦ by
rw [PadicSeq.norm, dif_pos h] at hge
exact not_lt_of_ge hge hε
unfold PadicSeq.norm at hge; split_ifs at hge
· exact not_le_of_gt hε hge
apply not_le_of_gt _ hge
cases' _root_.em (N ≤ stationaryPoint hne) with hgen hngen
· apply hN _ hgen _ hi
· have := stationaryPoint_spec hne le_rfl (le_of_not_le hngen)
rw [← this]
exact hN _ le_rfl _ hi
#align padic_norm_e.defn padicNormE.defn
/-- Theorems about `padicNormE` are named with a `'` so the names do not conflict with the
equivalent theorems about `norm` (`‖ ‖`). -/
theorem nonarchimedean' (q r : ℚ_[p]) :
padicNormE (q + r : ℚ_[p]) ≤ max (padicNormE q) (padicNormE r) :=
Quotient.inductionOn₂ q r <| norm_nonarchimedean
#align padic_norm_e.nonarchimedean' padicNormE.nonarchimedean'
/-- Theorems about `padicNormE` are named with a `'` so the names do not conflict with the
equivalent theorems about `norm` (`‖ ‖`). -/
theorem add_eq_max_of_ne' {q r : ℚ_[p]} :
padicNormE q ≠ padicNormE r → padicNormE (q + r : ℚ_[p]) = max (padicNormE q) (padicNormE r) :=
Quotient.inductionOn₂ q r fun _ _ ↦ PadicSeq.add_eq_max_of_ne
#align padic_norm_e.add_eq_max_of_ne' padicNormE.add_eq_max_of_ne'
@[simp]
theorem eq_padic_norm' (q : ℚ) : padicNormE (q : ℚ_[p]) = padicNorm p q :=
norm_const _
#align padic_norm_e.eq_padic_norm' padicNormE.eq_padic_norm'
protected theorem image' {q : ℚ_[p]} : q ≠ 0 → ∃ n : ℤ, padicNormE q = (p : ℚ) ^ (-n) :=
Quotient.inductionOn q fun f hf ↦
have : ¬f ≈ 0 := (ne_zero_iff_nequiv_zero f).1 hf
norm_values_discrete f this
#align padic_norm_e.image' padicNormE.image'
end Embedding
end padicNormE
namespace Padic
section Complete
open PadicSeq Padic
variable {p : ℕ} [Fact p.Prime] (f : CauSeq _ (@padicNormE p _))
theorem rat_dense' (q : ℚ_[p]) {ε : ℚ} (hε : 0 < ε) : ∃ r : ℚ, padicNormE (q - r : ℚ_[p]) < ε :=
Quotient.inductionOn q fun q' ↦
have : ∃ N, ∀ m ≥ N, ∀ n ≥ N, padicNorm p (q' m - q' n) < ε := cauchy₂ _ hε
let ⟨N, hN⟩ := this
⟨q' N, by
dsimp [padicNormE]
-- Porting note: `change` → `convert_to` (`change` times out!)
-- and add `PadicSeq p` type annotation
convert_to PadicSeq.norm (q' - const _ (q' N) : PadicSeq p) < ε
cases' Decidable.em (q' - const (padicNorm p) (q' N) ≈ 0) with heq hne'
· simpa only [heq, PadicSeq.norm, dif_pos]
· simp only [PadicSeq.norm, dif_neg hne']
change padicNorm p (q' _ - q' _) < ε
cases' Decidable.em (stationaryPoint hne' ≤ N) with hle hle
· -- Porting note: inlined `stationaryPoint_spec` invocation.
have := (stationaryPoint_spec hne' le_rfl hle).symm
simp only [const_apply, sub_apply, padicNorm.zero, sub_self] at this
simpa only [this]
· exact hN _ (lt_of_not_ge hle).le _ le_rfl⟩
#align padic.rat_dense' Padic.rat_dense'
open scoped Classical
private theorem div_nat_pos (n : ℕ) : 0 < 1 / (n + 1 : ℚ) :=
div_pos zero_lt_one (mod_cast succ_pos _)
/-- `limSeq f`, for `f` a Cauchy sequence of `p`-adic numbers, is a sequence of rationals with the
same limit point as `f`. -/
def limSeq : ℕ → ℚ :=
fun n ↦ Classical.choose (rat_dense' (f n) (div_nat_pos n))
#align padic.lim_seq Padic.limSeq
theorem exi_rat_seq_conv {ε : ℚ} (hε : 0 < ε) :
∃ N, ∀ i ≥ N, padicNormE (f i - (limSeq f i : ℚ_[p]) : ℚ_[p]) < ε := by
refine (exists_nat_gt (1 / ε)).imp fun N hN i hi ↦ ?_
have h := Classical.choose_spec (rat_dense' (f i) (div_nat_pos i))
refine lt_of_lt_of_le h ((div_le_iff' <| mod_cast succ_pos _).mpr ?_)
rw [right_distrib]
apply le_add_of_le_of_nonneg
· exact (div_le_iff hε).mp (le_trans (le_of_lt hN) (mod_cast hi))
· apply le_of_lt
simpa
#align padic.exi_rat_seq_conv Padic.exi_rat_seq_conv
theorem exi_rat_seq_conv_cauchy : IsCauSeq (padicNorm p) (limSeq f) := fun ε hε ↦ by
have hε3 : 0 < ε / 3 := div_pos hε (by norm_num)
let ⟨N, hN⟩ := exi_rat_seq_conv f hε3
let ⟨N2, hN2⟩ := f.cauchy₂ hε3
exists max N N2
intro j hj
suffices
padicNormE (limSeq f j - f (max N N2) + (f (max N N2) - limSeq f (max N N2)) : ℚ_[p]) < ε by
ring_nf at this ⊢
rw [← padicNormE.eq_padic_norm']
exact mod_cast this
apply lt_of_le_of_lt
· apply padicNormE.add_le
· rw [← add_thirds ε]
apply _root_.add_lt_add
· suffices padicNormE (limSeq f j - f j + (f j - f (max N N2)) : ℚ_[p]) < ε / 3 + ε / 3 by
simpa only [sub_add_sub_cancel]
apply lt_of_le_of_lt
· apply padicNormE.add_le
· apply _root_.add_lt_add
· rw [padicNormE.map_sub]
apply mod_cast hN j
exact le_of_max_le_left hj
· exact hN2 _ (le_of_max_le_right hj) _ (le_max_right _ _)
· apply mod_cast hN (max N N2)
apply le_max_left
#align padic.exi_rat_seq_conv_cauchy Padic.exi_rat_seq_conv_cauchy
private def lim' : PadicSeq p :=
⟨_, exi_rat_seq_conv_cauchy f⟩
private def lim : ℚ_[p] :=
⟦lim' f⟧
theorem complete' : ∃ q : ℚ_[p], ∀ ε > 0, ∃ N, ∀ i ≥ N, padicNormE (q - f i : ℚ_[p]) < ε :=
⟨lim f, fun ε hε ↦ by
obtain ⟨N, hN⟩ := exi_rat_seq_conv f (half_pos hε)
obtain ⟨N2, hN2⟩ := padicNormE.defn (lim' f) (half_pos hε)
refine ⟨max N N2, fun i hi ↦ ?_⟩
rw [← sub_add_sub_cancel _ (lim' f i : ℚ_[p]) _]
refine (padicNormE.add_le _ _).trans_lt ?_
rw [← add_halves ε]
apply _root_.add_lt_add
· apply hN2 _ (le_of_max_le_right hi)
· rw [padicNormE.map_sub]
exact hN _ (le_of_max_le_left hi)⟩
#align padic.complete' Padic.complete'
theorem complete'' : ∃ q : ℚ_[p], ∀ ε > 0, ∃ N, ∀ i ≥ N, padicNormE (f i - q : ℚ_[p]) < ε := by
obtain ⟨x, hx⟩ := complete' f
refine ⟨x, fun ε hε => ?_⟩
obtain ⟨N, hN⟩ := hx ε hε
refine ⟨N, fun i hi => ?_⟩
rw [padicNormE.map_sub]
exact hN i hi
end Complete
section NormedSpace
variable (p : ℕ) [Fact p.Prime]
instance : Dist ℚ_[p] :=
⟨fun x y ↦ padicNormE (x - y : ℚ_[p])⟩
instance metricSpace : MetricSpace ℚ_[p] where
dist_self := by simp [dist]
dist := dist
dist_comm x y := by simp [dist, ← padicNormE.map_neg (x - y : ℚ_[p])]
dist_triangle x y z := by
dsimp [dist]
exact mod_cast padicNormE.sub_le x y z
eq_of_dist_eq_zero := by
dsimp [dist]; intro _ _ h
apply eq_of_sub_eq_zero
apply padicNormE.eq_zero.1
exact mod_cast h
-- Porting note: added because autoparam was not ported
edist_dist := by intros; exact (ENNReal.ofReal_eq_coe_nnreal _).symm
instance : Norm ℚ_[p] :=
⟨fun x ↦ padicNormE x⟩
instance normedField : NormedField ℚ_[p] :=
{ Padic.field,
Padic.metricSpace p with
dist_eq := fun _ _ ↦ rfl
norm_mul' := by simp [Norm.norm, map_mul]
norm := norm }
instance isAbsoluteValue : IsAbsoluteValue fun a : ℚ_[p] ↦ ‖a‖ where
abv_nonneg' := norm_nonneg
abv_eq_zero' := norm_eq_zero
abv_add' := norm_add_le
abv_mul' := by simp [Norm.norm, map_mul]
#align padic.is_absolute_value Padic.isAbsoluteValue
theorem rat_dense (q : ℚ_[p]) {ε : ℝ} (hε : 0 < ε) : ∃ r : ℚ, ‖q - r‖ < ε :=
let ⟨ε', hε'l, hε'r⟩ := exists_rat_btwn hε
let ⟨r, hr⟩ := rat_dense' q (ε := ε') (by simpa using hε'l)
⟨r, lt_trans (by simpa [Norm.norm] using hr) hε'r⟩
#align padic.rat_dense Padic.rat_dense
end NormedSpace
end Padic
namespace padicNormE
section NormedSpace
variable {p : ℕ} [hp : Fact p.Prime]
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
protected theorem mul (q r : ℚ_[p]) : ‖q * r‖ = ‖q‖ * ‖r‖ := by simp [Norm.norm, map_mul]
#align padic_norm_e.mul padicNormE.mul
protected theorem is_norm (q : ℚ_[p]) : ↑(padicNormE q) = ‖q‖ := rfl
#align padic_norm_e.is_norm padicNormE.is_norm
theorem nonarchimedean (q r : ℚ_[p]) : ‖q + r‖ ≤ max ‖q‖ ‖r‖ := by
dsimp [norm]
exact mod_cast nonarchimedean' _ _
#align padic_norm_e.nonarchimedean padicNormE.nonarchimedean
theorem add_eq_max_of_ne {q r : ℚ_[p]} (h : ‖q‖ ≠ ‖r‖) : ‖q + r‖ = max ‖q‖ ‖r‖ := by
dsimp [norm] at h ⊢
have : padicNormE q ≠ padicNormE r := mod_cast h
exact mod_cast add_eq_max_of_ne' this
#align padic_norm_e.add_eq_max_of_ne padicNormE.add_eq_max_of_ne
@[simp]
theorem eq_padicNorm (q : ℚ) : ‖(q : ℚ_[p])‖ = padicNorm p q := by
dsimp [norm]
rw [← padicNormE.eq_padic_norm']
#align padic_norm_e.eq_padic_norm padicNormE.eq_padicNorm
@[simp]
theorem norm_p : ‖(p : ℚ_[p])‖ = (p : ℝ)⁻¹ := by
rw [← @Rat.cast_natCast ℝ _ p]
rw [← @Rat.cast_natCast ℚ_[p] _ p]
simp [hp.1.ne_zero, hp.1.ne_one, norm, padicNorm, padicValRat, padicValInt, zpow_neg,
-Rat.cast_natCast]
#align padic_norm_e.norm_p padicNormE.norm_p
theorem norm_p_lt_one : ‖(p : ℚ_[p])‖ < 1 := by
rw [norm_p]
apply inv_lt_one
exact mod_cast hp.1.one_lt
#align padic_norm_e.norm_p_lt_one padicNormE.norm_p_lt_one
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
theorem norm_p_zpow (n : ℤ) : ‖(p : ℚ_[p]) ^ n‖ = (p : ℝ) ^ (-n) := by
rw [norm_zpow, norm_p, zpow_neg, inv_zpow]
#align padic_norm_e.norm_p_zpow padicNormE.norm_p_zpow
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
theorem norm_p_pow (n : ℕ) : ‖(p : ℚ_[p]) ^ n‖ = (p : ℝ) ^ (-n : ℤ) := by
rw [← norm_p_zpow, zpow_natCast]
#align padic_norm_e.norm_p_pow padicNormE.norm_p_pow
instance : NontriviallyNormedField ℚ_[p] :=
{ Padic.normedField p with
non_trivial :=
⟨p⁻¹, by
rw [norm_inv, norm_p, inv_inv]
exact mod_cast hp.1.one_lt⟩ }
protected theorem image {q : ℚ_[p]} : q ≠ 0 → ∃ n : ℤ, ‖q‖ = ↑((p : ℚ) ^ (-n)) :=
Quotient.inductionOn q fun f hf ↦
have : ¬f ≈ 0 := (PadicSeq.ne_zero_iff_nequiv_zero f).1 hf
let ⟨n, hn⟩ := PadicSeq.norm_values_discrete f this
⟨n, by rw [← hn]; rfl⟩
#align padic_norm_e.image padicNormE.image
protected theorem is_rat (q : ℚ_[p]) : ∃ q' : ℚ, ‖q‖ = q' :=
if h : q = 0 then ⟨0, by simp [h]⟩
else
let ⟨n, hn⟩ := padicNormE.image h
⟨_, hn⟩
#align padic_norm_e.is_rat padicNormE.is_rat
/-- `ratNorm q`, for a `p`-adic number `q` is the `p`-adic norm of `q`, as rational number.
The lemma `padicNormE.eq_ratNorm` asserts `‖q‖ = ratNorm q`. -/
def ratNorm (q : ℚ_[p]) : ℚ :=
Classical.choose (padicNormE.is_rat q)
#align padic_norm_e.rat_norm padicNormE.ratNorm
theorem eq_ratNorm (q : ℚ_[p]) : ‖q‖ = ratNorm q :=
Classical.choose_spec (padicNormE.is_rat q)
#align padic_norm_e.eq_rat_norm padicNormE.eq_ratNorm
theorem norm_rat_le_one : ∀ {q : ℚ} (_ : ¬p ∣ q.den), ‖(q : ℚ_[p])‖ ≤ 1
| ⟨n, d, hn, hd⟩ => fun hq : ¬p ∣ d ↦
if hnz : n = 0 then by
have : (⟨n, d, hn, hd⟩ : ℚ) = 0 := Rat.zero_iff_num_zero.mpr hnz
set_option tactic.skipAssignedInstances false in norm_num [this]
else by
have hnz' : (⟨n, d, hn, hd⟩ : ℚ) ≠ 0 := mt Rat.zero_iff_num_zero.1 hnz
rw [padicNormE.eq_padicNorm]
norm_cast
-- Porting note: `Nat.cast_zero` instead of another `norm_cast` call
rw [padicNorm.eq_zpow_of_nonzero hnz', padicValRat, neg_sub,
padicValNat.eq_zero_of_not_dvd hq, Nat.cast_zero, zero_sub, zpow_neg, zpow_natCast]
apply inv_le_one
norm_cast
apply one_le_pow
exact hp.1.pos
#align padic_norm_e.norm_rat_le_one padicNormE.norm_rat_le_one
theorem norm_int_le_one (z : ℤ) : ‖(z : ℚ_[p])‖ ≤ 1 :=
suffices ‖((z : ℚ) : ℚ_[p])‖ ≤ 1 by simpa
norm_rat_le_one <| by simp [hp.1.ne_one]
#align padic_norm_e.norm_int_le_one padicNormE.norm_int_le_one
theorem norm_int_lt_one_iff_dvd (k : ℤ) : ‖(k : ℚ_[p])‖ < 1 ↔ ↑p ∣ k := by
constructor
· intro h
contrapose! h
apply le_of_eq
rw [eq_comm]
calc
‖(k : ℚ_[p])‖ = ‖((k : ℚ) : ℚ_[p])‖ := by norm_cast
_ = padicNorm p k := padicNormE.eq_padicNorm _
_ = 1 := mod_cast (int_eq_one_iff k).mpr h
· rintro ⟨x, rfl⟩
push_cast
rw [padicNormE.mul]
calc
_ ≤ ‖(p : ℚ_[p])‖ * 1 :=
mul_le_mul le_rfl (by simpa using norm_int_le_one _) (norm_nonneg _) (norm_nonneg _)
_ < 1 := by
rw [mul_one, padicNormE.norm_p]
apply inv_lt_one
exact mod_cast hp.1.one_lt
#align padic_norm_e.norm_int_lt_one_iff_dvd padicNormE.norm_int_lt_one_iff_dvd
theorem norm_int_le_pow_iff_dvd (k : ℤ) (n : ℕ) :
‖(k : ℚ_[p])‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ (p ^ n : ℤ) ∣ k := by
have : (p : ℝ) ^ (-n : ℤ) = (p : ℚ) ^ (-n : ℤ) := by simp
rw [show (k : ℚ_[p]) = ((k : ℚ) : ℚ_[p]) by norm_cast, eq_padicNorm, this]
norm_cast
rw [← padicNorm.dvd_iff_norm_le]
#align padic_norm_e.norm_int_le_pow_iff_dvd padicNormE.norm_int_le_pow_iff_dvd
theorem eq_of_norm_add_lt_right {z1 z2 : ℚ_[p]} (h : ‖z1 + z2‖ < ‖z2‖) : ‖z1‖ = ‖z2‖ :=
_root_.by_contradiction fun hne ↦
not_lt_of_ge (by rw [padicNormE.add_eq_max_of_ne hne]; apply le_max_right) h
#align padic_norm_e.eq_of_norm_add_lt_right padicNormE.eq_of_norm_add_lt_right
theorem eq_of_norm_add_lt_left {z1 z2 : ℚ_[p]} (h : ‖z1 + z2‖ < ‖z1‖) : ‖z1‖ = ‖z2‖ :=
_root_.by_contradiction fun hne ↦
not_lt_of_ge (by rw [padicNormE.add_eq_max_of_ne hne]; apply le_max_left) h
#align padic_norm_e.eq_of_norm_add_lt_left padicNormE.eq_of_norm_add_lt_left
end NormedSpace
end padicNormE
namespace Padic
variable {p : ℕ} [hp : Fact p.Prime]
-- Porting note: remove `set_option eqn_compiler.zeta true`
instance complete : CauSeq.IsComplete ℚ_[p] norm where
isComplete f := by
have cau_seq_norm_e : IsCauSeq padicNormE f := fun ε hε => by
have h := isCauSeq f ε (mod_cast hε)
dsimp [norm] at h
exact mod_cast h
-- Porting note: Padic.complete' works with `f i - q`, but the goal needs `q - f i`,
-- using `rewrite [padicNormE.map_sub]` causes time out, so a separate lemma is created
cases' Padic.complete'' ⟨f, cau_seq_norm_e⟩ with q hq
exists q
intro ε hε
cases' exists_rat_btwn hε with ε' hε'
norm_cast at hε'
cases' hq ε' hε'.1 with N hN
exists N
intro i hi
have h := hN i hi
change norm (f i - q) < ε
refine lt_trans ?_ hε'.2
dsimp [norm]
exact mod_cast h
#align padic.complete Padic.complete
theorem padicNormE_lim_le {f : CauSeq ℚ_[p] norm} {a : ℝ} (ha : 0 < a) (hf : ∀ i, ‖f i‖ ≤ a) :
‖f.lim‖ ≤ a := by
-- Porting note: `Setoid.symm` cannot work out which `Setoid` to use, so instead swap the order
-- now, I use a rewrite to swap it later
obtain ⟨N, hN⟩ := (CauSeq.equiv_lim f) _ ha
rw [← sub_add_cancel f.lim (f N)]
refine le_trans (padicNormE.nonarchimedean _ _) ?_
rw [norm_sub_rev]
exact max_le (le_of_lt (hN _ le_rfl)) (hf _)
-- Porting note: the following nice `calc` block does not work
-- exact calc
-- ‖f.lim‖ = ‖f.lim - f N + f N‖ := sorry
-- ‖f.lim - f N + f N‖ ≤ max ‖f.lim - f N‖ ‖f N‖ := sorry -- (padicNormE.nonarchimedean _ _)
-- max ‖f.lim - f N‖ ‖f N‖ = max ‖f N - f.lim‖ ‖f N‖ := sorry -- by congr; rw [norm_sub_rev]
-- max ‖f N - f.lim‖ ‖f N‖ ≤ a := sorry -- max_le (le_of_lt (hN _ le_rfl)) (hf _)
#align padic.padic_norm_e_lim_le Padic.padicNormE_lim_le
open Filter Set
instance : CompleteSpace ℚ_[p] := by
apply complete_of_cauchySeq_tendsto
intro u hu
let c : CauSeq ℚ_[p] norm := ⟨u, Metric.cauchySeq_iff'.mp hu⟩
refine ⟨c.lim, fun s h ↦ ?_⟩
rcases Metric.mem_nhds_iff.1 h with ⟨ε, ε0, hε⟩
have := c.equiv_lim ε ε0
simp only [mem_map, mem_atTop_sets, mem_setOf_eq]
exact this.imp fun N hN n hn ↦ hε (hN n hn)
/-! ### Valuation on `ℚ_[p]` -/
/-- `Padic.valuation` lifts the `p`-adic valuation on rationals to `ℚ_[p]`. -/
def valuation : ℚ_[p] → ℤ :=
Quotient.lift (@PadicSeq.valuation p _) fun f g h ↦ by
by_cases hf : f ≈ 0
· have hg : g ≈ 0 := Setoid.trans (Setoid.symm h) hf
simp [hf, hg, PadicSeq.valuation]
· have hg : ¬g ≈ 0 := fun hg ↦ hf (Setoid.trans h hg)
rw [PadicSeq.val_eq_iff_norm_eq hf hg]
exact PadicSeq.norm_equiv h
#align padic.valuation Padic.valuation
@[simp]
theorem valuation_zero : valuation (0 : ℚ_[p]) = 0 :=
dif_pos ((const_equiv p).2 rfl)
#align padic.valuation_zero Padic.valuation_zero
@[simp]
theorem valuation_one : valuation (1 : ℚ_[p]) = 0 := by
change dite (CauSeq.const (padicNorm p) 1 ≈ _) _ _ = _
have h : ¬CauSeq.const (padicNorm p) 1 ≈ 0 := by
intro H
erw [const_equiv p] at H
exact one_ne_zero H
rw [dif_neg h]
simp
#align padic.valuation_one Padic.valuation_one
theorem norm_eq_pow_val {x : ℚ_[p]} : x ≠ 0 → ‖x‖ = (p : ℝ) ^ (-x.valuation) := by
refine Quotient.inductionOn' x fun f hf => ?_
change (PadicSeq.norm _ : ℝ) = (p : ℝ) ^ (-PadicSeq.valuation _)
rw [PadicSeq.norm_eq_pow_val]
· change ↑((p : ℚ) ^ (-PadicSeq.valuation f)) = (p : ℝ) ^ (-PadicSeq.valuation f)
rw [Rat.cast_zpow, Rat.cast_natCast]
· apply CauSeq.not_limZero_of_not_congr_zero
-- Porting note: was `contrapose! hf`
intro hf'
apply hf
apply Quotient.sound
simpa using hf'
#align padic.norm_eq_pow_val Padic.norm_eq_pow_val
@[simp]
theorem valuation_p : valuation (p : ℚ_[p]) = 1 := by
have h : (1 : ℝ) < p := mod_cast (Fact.out : p.Prime).one_lt
refine neg_injective ((zpow_strictMono h).injective <| (norm_eq_pow_val ?_).symm.trans ?_)
· exact mod_cast (Fact.out : p.Prime).ne_zero
· simp
#align padic.valuation_p Padic.valuation_p
theorem valuation_map_add {x y : ℚ_[p]} (hxy : x + y ≠ 0) :
min (valuation x) (valuation y) ≤ valuation (x + y : ℚ_[p]) := by
by_cases hx : x = 0
· rw [hx, zero_add]
exact min_le_right _ _
· by_cases hy : y = 0
· rw [hy, add_zero]
exact min_le_left _ _
· have h_norm : ‖x + y‖ ≤ max ‖x‖ ‖y‖ := padicNormE.nonarchimedean x y
have hp_one : (1 : ℝ) < p := by
rw [← Nat.cast_one, Nat.cast_lt]
exact Nat.Prime.one_lt hp.elim
rwa [norm_eq_pow_val hx, norm_eq_pow_val hy, norm_eq_pow_val hxy,
zpow_le_max_iff_min_le hp_one] at h_norm
#align padic.valuation_map_add Padic.valuation_map_add
@[simp]
theorem valuation_map_mul {x y : ℚ_[p]} (hx : x ≠ 0) (hy : y ≠ 0) :
valuation (x * y : ℚ_[p]) = valuation x + valuation y := by
have h_norm : ‖x * y‖ = ‖x‖ * ‖y‖ := norm_mul x y
have hp_ne_one : (p : ℝ) ≠ 1 := by
rw [← Nat.cast_one, Ne, Nat.cast_inj]
exact Nat.Prime.ne_one hp.elim
have hp_pos : (0 : ℝ) < p := by
rw [← Nat.cast_zero, Nat.cast_lt]
exact Nat.Prime.pos hp.elim
rw [norm_eq_pow_val hx, norm_eq_pow_val hy, norm_eq_pow_val (mul_ne_zero hx hy), ←
zpow_add₀ (ne_of_gt hp_pos), zpow_inj hp_pos hp_ne_one, ← neg_add, neg_inj] at h_norm
exact h_norm
#align padic.valuation_map_mul Padic.valuation_map_mul
/-- The additive `p`-adic valuation on `ℚ_[p]`, with values in `WithTop ℤ`. -/
def addValuationDef : ℚ_[p] → WithTop ℤ :=
fun x ↦ if x = 0 then ⊤ else x.valuation
#align padic.add_valuation_def Padic.addValuationDef
@[simp]
| Mathlib/NumberTheory/Padics/PadicNumbers.lean | 1,109 | 1,110 | theorem AddValuation.map_zero : addValuationDef (0 : ℚ_[p]) = ⊤ := by |
rw [addValuationDef, if_pos (Eq.refl _)]
|
/-
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 Batteries.Tactic.Alias
import Batteries.Data.List.Init.Attach
import Batteries.Data.List.Pairwise
-- Adaptation note: nightly-2024-03-18. We should be able to remove this after nightly-2024-03-19.
import Lean.Elab.Tactic.Rfl
/-!
# List Permutations
This file introduces the `List.Perm` relation, which is true if two lists are permutations of one
another.
## Notation
The notation `~` is used for permutation equivalence.
-/
open Nat
namespace List
open Perm (swap)
@[simp, refl] protected theorem Perm.refl : ∀ l : List α, l ~ l
| [] => .nil
| x :: xs => (Perm.refl xs).cons x
protected theorem Perm.rfl {l : List α} : l ~ l := .refl _
theorem Perm.of_eq (h : l₁ = l₂) : l₁ ~ l₂ := h ▸ .rfl
protected theorem Perm.symm {l₁ l₂ : List α} (h : l₁ ~ l₂) : l₂ ~ l₁ := by
induction h with
| nil => exact nil
| cons _ _ ih => exact cons _ ih
| swap => exact swap ..
| trans _ _ ih₁ ih₂ => exact trans ih₂ ih₁
theorem perm_comm {l₁ l₂ : List α} : l₁ ~ l₂ ↔ l₂ ~ l₁ := ⟨Perm.symm, Perm.symm⟩
theorem Perm.swap' (x y : α) {l₁ l₂ : List α} (p : l₁ ~ l₂) : y :: x :: l₁ ~ x :: y :: l₂ :=
(swap ..).trans <| p.cons _ |>.cons _
/--
Similar to `Perm.recOn`, but the `swap` case is generalized to `Perm.swap'`,
where the tail of the lists are not necessarily the same.
-/
@[elab_as_elim] theorem Perm.recOnSwap'
{motive : (l₁ : List α) → (l₂ : List α) → l₁ ~ l₂ → Prop} {l₁ l₂ : List α} (p : l₁ ~ l₂)
(nil : motive [] [] .nil)
(cons : ∀ x {l₁ l₂}, (h : l₁ ~ l₂) → motive l₁ l₂ h → motive (x :: l₁) (x :: l₂) (.cons x h))
(swap' : ∀ x y {l₁ l₂}, (h : l₁ ~ l₂) → motive l₁ l₂ h →
motive (y :: x :: l₁) (x :: y :: l₂) (.swap' _ _ h))
(trans : ∀ {l₁ l₂ l₃}, (h₁ : l₁ ~ l₂) → (h₂ : l₂ ~ l₃) → motive l₁ l₂ h₁ → motive l₂ l₃ h₂ →
motive l₁ l₃ (.trans h₁ h₂)) : motive l₁ l₂ p :=
have motive_refl l : motive l l (.refl l) :=
List.recOn l nil fun x xs ih => cons x (.refl xs) ih
Perm.recOn p nil cons (fun x y l => swap' x y (.refl l) (motive_refl l)) trans
theorem Perm.eqv (α) : Equivalence (@Perm α) := ⟨.refl, .symm, .trans⟩
instance isSetoid (α) : Setoid (List α) := .mk Perm (Perm.eqv α)
theorem Perm.mem_iff {a : α} {l₁ l₂ : List α} (p : l₁ ~ l₂) : a ∈ l₁ ↔ a ∈ l₂ := by
induction p with
| nil => rfl
| cons _ _ ih => simp only [mem_cons, ih]
| swap => simp only [mem_cons, or_left_comm]
| trans _ _ ih₁ ih₂ => simp only [ih₁, ih₂]
theorem Perm.subset {l₁ l₂ : List α} (p : l₁ ~ l₂) : l₁ ⊆ l₂ := fun _ => p.mem_iff.mp
theorem Perm.append_right {l₁ l₂ : List α} (t₁ : List α) (p : l₁ ~ l₂) : l₁ ++ t₁ ~ l₂ ++ t₁ := by
induction p with
| nil => rfl
| cons _ _ ih => exact cons _ ih
| swap => exact swap ..
| trans _ _ ih₁ ih₂ => exact trans ih₁ ih₂
theorem Perm.append_left {t₁ t₂ : List α} : ∀ l : List α, t₁ ~ t₂ → l ++ t₁ ~ l ++ t₂
| [], p => p
| x :: xs, p => (p.append_left xs).cons x
theorem Perm.append {l₁ l₂ t₁ t₂ : List α} (p₁ : l₁ ~ l₂) (p₂ : t₁ ~ t₂) : l₁ ++ t₁ ~ l₂ ++ t₂ :=
(p₁.append_right t₁).trans (p₂.append_left l₂)
theorem Perm.append_cons (a : α) {h₁ h₂ t₁ t₂ : List α} (p₁ : h₁ ~ h₂) (p₂ : t₁ ~ t₂) :
h₁ ++ a :: t₁ ~ h₂ ++ a :: t₂ := p₁.append (p₂.cons a)
@[simp] theorem perm_middle {a : α} : ∀ {l₁ l₂ : List α}, l₁ ++ a :: l₂ ~ a :: (l₁ ++ l₂)
| [], _ => .refl _
| b :: _, _ => (Perm.cons _ perm_middle).trans (swap a b _)
@[simp] theorem perm_append_singleton (a : α) (l : List α) : l ++ [a] ~ a :: l :=
perm_middle.trans <| by rw [append_nil]
theorem perm_append_comm : ∀ {l₁ l₂ : List α}, l₁ ++ l₂ ~ l₂ ++ l₁
| [], l₂ => by simp
| a :: t, l₂ => (perm_append_comm.cons _).trans perm_middle.symm
theorem concat_perm (l : List α) (a : α) : concat l a ~ a :: l := by simp
theorem Perm.length_eq {l₁ l₂ : List α} (p : l₁ ~ l₂) : length l₁ = length l₂ := by
induction p with
| nil => rfl
| cons _ _ ih => simp only [length_cons, ih]
| swap => rfl
| trans _ _ ih₁ ih₂ => simp only [ih₁, ih₂]
theorem Perm.eq_nil {l : List α} (p : l ~ []) : l = [] := eq_nil_of_length_eq_zero p.length_eq
theorem Perm.nil_eq {l : List α} (p : [] ~ l) : [] = l := p.symm.eq_nil.symm
@[simp] theorem perm_nil {l₁ : List α} : l₁ ~ [] ↔ l₁ = [] :=
⟨fun p => p.eq_nil, fun e => e ▸ .rfl⟩
@[simp] theorem nil_perm {l₁ : List α} : [] ~ l₁ ↔ l₁ = [] := perm_comm.trans perm_nil
theorem not_perm_nil_cons (x : α) (l : List α) : ¬[] ~ x :: l := (nomatch ·.symm.eq_nil)
@[simp] theorem reverse_perm : ∀ l : List α, reverse l ~ l
| [] => .nil
| a :: l => reverse_cons .. ▸ (perm_append_singleton _ _).trans ((reverse_perm l).cons a)
theorem perm_cons_append_cons {l l₁ l₂ : List α} (a : α) (p : l ~ l₁ ++ l₂) :
a :: l ~ l₁ ++ a :: l₂ := (p.cons a).trans perm_middle.symm
@[simp] theorem perm_replicate {n : Nat} {a : α} {l : List α} :
l ~ replicate n a ↔ l = replicate n a := by
refine ⟨fun p => eq_replicate.2 ?_, fun h => h ▸ .rfl⟩
exact ⟨p.length_eq.trans <| length_replicate .., fun _b m => eq_of_mem_replicate <| p.subset m⟩
@[simp] theorem replicate_perm {n : Nat} {a : α} {l : List α} :
replicate n a ~ l ↔ replicate n a = l := (perm_comm.trans perm_replicate).trans eq_comm
@[simp] theorem perm_singleton {a : α} {l : List α} : l ~ [a] ↔ l = [a] := perm_replicate (n := 1)
@[simp] theorem singleton_perm {a : α} {l : List α} : [a] ~ l ↔ [a] = l := replicate_perm (n := 1)
alias ⟨Perm.eq_singleton,_⟩ := perm_singleton
alias ⟨Perm.singleton_eq,_⟩ := singleton_perm
theorem singleton_perm_singleton {a b : α} : [a] ~ [b] ↔ a = b := by simp
theorem perm_cons_erase [DecidableEq α] {a : α} {l : List α} (h : a ∈ l) : l ~ a :: l.erase a :=
let ⟨_l₁, _l₂, _, e₁, e₂⟩ := exists_erase_eq h
e₂ ▸ e₁ ▸ perm_middle
theorem Perm.filterMap (f : α → Option β) {l₁ l₂ : List α} (p : l₁ ~ l₂) :
filterMap f l₁ ~ filterMap f l₂ := by
induction p with
| nil => simp
| cons x _p IH => cases h : f x <;> simp [h, filterMap, IH, Perm.cons]
| swap x y l₂ => cases hx : f x <;> cases hy : f y <;> simp [hx, hy, filterMap, swap]
| trans _p₁ _p₂ IH₁ IH₂ => exact IH₁.trans IH₂
theorem Perm.map (f : α → β) {l₁ l₂ : List α} (p : l₁ ~ l₂) : map f l₁ ~ map f l₂ :=
filterMap_eq_map f ▸ p.filterMap _
theorem Perm.pmap {p : α → Prop} (f : ∀ a, p a → β) {l₁ l₂ : List α} (p : l₁ ~ l₂) {H₁ H₂} :
pmap f l₁ H₁ ~ pmap f l₂ H₂ := by
induction p with
| nil => simp
| cons x _p IH => simp [IH, Perm.cons]
| swap x y => simp [swap]
| trans _p₁ p₂ IH₁ IH₂ => exact IH₁.trans (IH₂ (H₁ := fun a m => H₂ a (p₂.subset m)))
theorem Perm.filter (p : α → Bool) {l₁ l₂ : List α} (s : l₁ ~ l₂) :
filter p l₁ ~ filter p l₂ := by rw [← filterMap_eq_filter]; apply s.filterMap
theorem filter_append_perm (p : α → Bool) (l : List α) :
filter p l ++ filter (fun x => !p x) l ~ l := by
induction l with
| nil => rfl
| cons x l ih =>
by_cases h : p x <;> simp [h]
· exact ih.cons x
· exact Perm.trans (perm_append_comm.trans (perm_append_comm.cons _)) (ih.cons x)
theorem exists_perm_sublist {l₁ l₂ l₂' : List α} (s : l₁ <+ l₂) (p : l₂ ~ l₂') :
∃ l₁', l₁' ~ l₁ ∧ l₁' <+ l₂' := by
induction p generalizing l₁ with
| nil => exact ⟨[], sublist_nil.mp s ▸ .rfl, nil_sublist _⟩
| cons x _ IH =>
match s with
| .cons _ s => let ⟨l₁', p', s'⟩ := IH s; exact ⟨l₁', p', s'.cons _⟩
| .cons₂ _ s => let ⟨l₁', p', s'⟩ := IH s; exact ⟨x :: l₁', p'.cons x, s'.cons₂ _⟩
| swap x y l' =>
match s with
| .cons _ (.cons _ s) => exact ⟨_, .rfl, (s.cons _).cons _⟩
| .cons _ (.cons₂ _ s) => exact ⟨x :: _, .rfl, (s.cons _).cons₂ _⟩
| .cons₂ _ (.cons _ s) => exact ⟨y :: _, .rfl, (s.cons₂ _).cons _⟩
| .cons₂ _ (.cons₂ _ s) => exact ⟨x :: y :: _, .swap .., (s.cons₂ _).cons₂ _⟩
| trans _ _ IH₁ IH₂ =>
let ⟨m₁, pm, sm⟩ := IH₁ s
let ⟨r₁, pr, sr⟩ := IH₂ sm
exact ⟨r₁, pr.trans pm, sr⟩
theorem Perm.sizeOf_eq_sizeOf [SizeOf α] {l₁ l₂ : List α} (h : l₁ ~ l₂) :
sizeOf l₁ = sizeOf l₂ := by
induction h with
| nil => rfl
| cons _ _ h_sz₁₂ => simp [h_sz₁₂]
| swap => simp [Nat.add_left_comm]
| trans _ _ h_sz₁₂ h_sz₂₃ => simp [h_sz₁₂, h_sz₂₃]
section Subperm
theorem nil_subperm {l : List α} : [] <+~ l := ⟨[], Perm.nil, by simp⟩
theorem Perm.subperm_left {l l₁ l₂ : List α} (p : l₁ ~ l₂) : l <+~ l₁ ↔ l <+~ l₂ :=
suffices ∀ {l₁ l₂ : List α}, l₁ ~ l₂ → l <+~ l₁ → l <+~ l₂ from ⟨this p, this p.symm⟩
fun p ⟨_u, pu, su⟩ =>
let ⟨v, pv, sv⟩ := exists_perm_sublist su p
⟨v, pv.trans pu, sv⟩
theorem Perm.subperm_right {l₁ l₂ l : List α} (p : l₁ ~ l₂) : l₁ <+~ l ↔ l₂ <+~ l :=
⟨fun ⟨u, pu, su⟩ => ⟨u, pu.trans p, su⟩, fun ⟨u, pu, su⟩ => ⟨u, pu.trans p.symm, su⟩⟩
theorem Sublist.subperm {l₁ l₂ : List α} (s : l₁ <+ l₂) : l₁ <+~ l₂ := ⟨l₁, .rfl, s⟩
theorem Perm.subperm {l₁ l₂ : List α} (p : l₁ ~ l₂) : l₁ <+~ l₂ := ⟨l₂, p.symm, Sublist.refl _⟩
@[refl] theorem Subperm.refl (l : List α) : l <+~ l := Perm.rfl.subperm
theorem Subperm.trans {l₁ l₂ l₃ : List α} (s₁₂ : l₁ <+~ l₂) (s₂₃ : l₂ <+~ l₃) : l₁ <+~ l₃ :=
let ⟨_l₂', p₂, s₂⟩ := s₂₃
let ⟨l₁', p₁, s₁⟩ := p₂.subperm_left.2 s₁₂
⟨l₁', p₁, s₁.trans s₂⟩
theorem Subperm.cons_right {α : Type _} {l l' : List α} (x : α) (h : l <+~ l') : l <+~ x :: l' :=
h.trans (sublist_cons x l').subperm
theorem Subperm.length_le {l₁ l₂ : List α} : l₁ <+~ l₂ → length l₁ ≤ length l₂
| ⟨_l, p, s⟩ => p.length_eq ▸ s.length_le
theorem Subperm.perm_of_length_le {l₁ l₂ : List α} : l₁ <+~ l₂ → length l₂ ≤ length l₁ → l₁ ~ l₂
| ⟨_l, p, s⟩, h => (s.eq_of_length_le <| p.symm.length_eq ▸ h) ▸ p.symm
theorem Subperm.antisymm {l₁ l₂ : List α} (h₁ : l₁ <+~ l₂) (h₂ : l₂ <+~ l₁) : l₁ ~ l₂ :=
h₁.perm_of_length_le h₂.length_le
theorem Subperm.subset {l₁ l₂ : List α} : l₁ <+~ l₂ → l₁ ⊆ l₂
| ⟨_l, p, s⟩ => Subset.trans p.symm.subset s.subset
theorem Subperm.filter (p : α → Bool) ⦃l l' : List α⦄ (h : l <+~ l') :
filter p l <+~ filter p l' := by
let ⟨xs, hp, h⟩ := h
exact ⟨_, hp.filter p, h.filter p⟩
@[simp] theorem singleton_subperm_iff {α} {l : List α} {a : α} : [a] <+~ l ↔ a ∈ l := by
refine ⟨fun ⟨s, hla, h⟩ => ?_, fun h => ⟨[a], .rfl, singleton_sublist.mpr h⟩⟩
rwa [perm_singleton.mp hla, singleton_sublist] at h
end Subperm
theorem Sublist.exists_perm_append {l₁ l₂ : List α} : l₁ <+ l₂ → ∃ l, l₂ ~ l₁ ++ l
| Sublist.slnil => ⟨nil, .rfl⟩
| Sublist.cons a s =>
let ⟨l, p⟩ := Sublist.exists_perm_append s
⟨a :: l, (p.cons a).trans perm_middle.symm⟩
| Sublist.cons₂ a s =>
let ⟨l, p⟩ := Sublist.exists_perm_append s
⟨l, p.cons a⟩
theorem Perm.countP_eq (p : α → Bool) {l₁ l₂ : List α} (s : l₁ ~ l₂) :
countP p l₁ = countP p l₂ := by
simp only [countP_eq_length_filter]
exact (s.filter _).length_eq
theorem Subperm.countP_le (p : α → Bool) {l₁ l₂ : List α} : l₁ <+~ l₂ → countP p l₁ ≤ countP p l₂
| ⟨_l, p', s⟩ => p'.countP_eq p ▸ s.countP_le p
theorem Perm.countP_congr {l₁ l₂ : List α} (s : l₁ ~ l₂) {p p' : α → Bool}
(hp : ∀ x ∈ l₁, p x = p' x) : l₁.countP p = l₂.countP p' := by
rw [← s.countP_eq p']
clear s
induction l₁ with
| nil => rfl
| cons y s hs =>
simp only [mem_cons, forall_eq_or_imp] at hp
simp only [countP_cons, hs hp.2, hp.1]
theorem countP_eq_countP_filter_add (l : List α) (p q : α → Bool) :
l.countP p = (l.filter q).countP p + (l.filter fun a => !q a).countP p :=
countP_append .. ▸ Perm.countP_eq _ (filter_append_perm _ _).symm
theorem Perm.count_eq [DecidableEq α] {l₁ l₂ : List α} (p : l₁ ~ l₂) (a) :
count a l₁ = count a l₂ := p.countP_eq _
theorem Subperm.count_le [DecidableEq α] {l₁ l₂ : List α} (s : l₁ <+~ l₂) (a) :
count a l₁ ≤ count a l₂ := s.countP_le _
theorem Perm.foldl_eq' {f : β → α → β} {l₁ l₂ : List α} (p : l₁ ~ l₂)
(comm : ∀ x ∈ l₁, ∀ y ∈ l₁, ∀ (z), f (f z x) y = f (f z y) x)
(init) : foldl f init l₁ = foldl f init l₂ := by
induction p using recOnSwap' generalizing init with
| nil => simp
| cons x _p IH =>
simp only [foldl]
apply IH; intros; apply comm <;> exact .tail _ ‹_›
| swap' x y _p IH =>
simp only [foldl]
rw [comm x (.tail _ <| .head _) y (.head _)]
apply IH; intros; apply comm <;> exact .tail _ (.tail _ ‹_›)
| trans p₁ _p₂ IH₁ IH₂ =>
refine (IH₁ comm init).trans (IH₂ ?_ _)
intros; apply comm <;> apply p₁.symm.subset <;> assumption
theorem Perm.rec_heq {β : List α → Sort _} {f : ∀ a l, β l → β (a :: l)} {b : β []} {l l' : List α}
(hl : l ~ l') (f_congr : ∀ {a l l' b b'}, l ~ l' → HEq b b' → HEq (f a l b) (f a l' b'))
(f_swap : ∀ {a a' l b}, HEq (f a (a' :: l) (f a' l b)) (f a' (a :: l) (f a l b))) :
HEq (@List.rec α β b f l) (@List.rec α β b f l') := by
induction hl with
| nil => rfl
| cons a h ih => exact f_congr h ih
| swap a a' l => exact f_swap
| trans _h₁ _h₂ ih₁ ih₂ => exact ih₁.trans ih₂
/-- Lemma used to destruct perms element by element. -/
theorem perm_inv_core {a : α} {l₁ l₂ r₁ r₂ : List α} :
l₁ ++ a :: r₁ ~ l₂ ++ a :: r₂ → l₁ ++ r₁ ~ l₂ ++ r₂ := by
-- Necessary generalization for `induction`
suffices ∀ s₁ s₂ (_ : s₁ ~ s₂) {l₁ l₂ r₁ r₂},
l₁ ++ a :: r₁ = s₁ → l₂ ++ a :: r₂ = s₂ → l₁ ++ r₁ ~ l₂ ++ r₂ from (this _ _ · rfl rfl)
intro s₁ s₂ p
induction p using Perm.recOnSwap' with intro l₁ l₂ r₁ r₂ e₁ e₂
| nil =>
simp at e₁
| cons x p IH =>
cases l₁ <;> cases l₂ <;>
dsimp at e₁ e₂ <;> injections <;> subst_vars
· exact p
· exact p.trans perm_middle
· exact perm_middle.symm.trans p
· exact (IH rfl rfl).cons _
| swap' x y p IH =>
obtain _ | ⟨y, _ | ⟨z, l₁⟩⟩ := l₁
<;> obtain _ | ⟨u, _ | ⟨v, l₂⟩⟩ := l₂
<;> dsimp at e₁ e₂ <;> injections <;> subst_vars
<;> try exact p.cons _
· exact (p.trans perm_middle).cons u
· exact ((p.trans perm_middle).cons _).trans (swap _ _ _)
· exact (perm_middle.symm.trans p).cons y
· exact (swap _ _ _).trans ((perm_middle.symm.trans p).cons u)
· exact (IH rfl rfl).swap' _ _
| trans p₁ p₂ IH₁ IH₂ =>
subst e₁ e₂
obtain ⟨l₂, r₂, rfl⟩ := append_of_mem (a := a) (p₁.subset (by simp))
exact (IH₁ rfl rfl).trans (IH₂ rfl rfl)
theorem Perm.cons_inv {a : α} {l₁ l₂ : List α} : a :: l₁ ~ a :: l₂ → l₁ ~ l₂ :=
perm_inv_core (l₁ := []) (l₂ := [])
@[simp] theorem perm_cons (a : α) {l₁ l₂ : List α} : a :: l₁ ~ a :: l₂ ↔ l₁ ~ l₂ :=
⟨.cons_inv, .cons a⟩
theorem perm_append_left_iff {l₁ l₂ : List α} : ∀ l, l ++ l₁ ~ l ++ l₂ ↔ l₁ ~ l₂
| [] => .rfl
| a :: l => (perm_cons a).trans (perm_append_left_iff l)
theorem perm_append_right_iff {l₁ l₂ : List α} (l) : l₁ ++ l ~ l₂ ++ l ↔ l₁ ~ l₂ := by
refine ⟨fun p => ?_, .append_right _⟩
exact (perm_append_left_iff _).1 <| perm_append_comm.trans <| p.trans perm_append_comm
theorem subperm_cons (a : α) {l₁ l₂ : List α} : a :: l₁ <+~ a :: l₂ ↔ l₁ <+~ l₂ := by
refine ⟨fun ⟨l, p, s⟩ => ?_, fun ⟨l, p, s⟩ => ⟨a :: l, p.cons a, s.cons₂ _⟩⟩
match s with
| .cons _ s' => exact (p.subperm_left.2 <| (sublist_cons _ _).subperm).trans s'.subperm
| .cons₂ _ s' => exact ⟨_, p.cons_inv, s'⟩
/-- Weaker version of `Subperm.cons_left` -/
theorem cons_subperm_of_not_mem_of_mem {a : α} {l₁ l₂ : List α} (h₁ : a ∉ l₁) (h₂ : a ∈ l₂)
(s : l₁ <+~ l₂) : a :: l₁ <+~ l₂ := by
obtain ⟨l, p, s⟩ := s
induction s generalizing l₁ with
| slnil => cases h₂
| @cons r₁ _ b s' ih =>
simp at h₂
match h₂ with
| .inl e => subst_vars; exact ⟨_ :: r₁, p.cons _, s'.cons₂ _⟩
| .inr m => let ⟨t, p', s'⟩ := ih h₁ m p; exact ⟨t, p', s'.cons _⟩
| @cons₂ _ r₂ b _ ih =>
have bm : b ∈ l₁ := p.subset <| mem_cons_self _ _
have am : a ∈ r₂ := by
simp only [find?, mem_cons] at h₂
exact h₂.resolve_left fun e => h₁ <| e.symm ▸ bm
obtain ⟨t₁, t₂, rfl⟩ := append_of_mem bm
have st : t₁ ++ t₂ <+ t₁ ++ b :: t₂ := by simp
obtain ⟨t, p', s'⟩ := ih (mt (st.subset ·) h₁) am (.cons_inv <| p.trans perm_middle)
exact ⟨b :: t, (p'.cons b).trans <| (swap ..).trans (perm_middle.symm.cons a), s'.cons₂ _⟩
theorem subperm_append_left {l₁ l₂ : List α} : ∀ l, l ++ l₁ <+~ l ++ l₂ ↔ l₁ <+~ l₂
| [] => .rfl
| a :: l => (subperm_cons a).trans (subperm_append_left l)
theorem subperm_append_right {l₁ l₂ : List α} (l) : l₁ ++ l <+~ l₂ ++ l ↔ l₁ <+~ l₂ :=
(perm_append_comm.subperm_left.trans perm_append_comm.subperm_right).trans (subperm_append_left l)
theorem Subperm.exists_of_length_lt {l₁ l₂ : List α} (s : l₁ <+~ l₂) (h : length l₁ < length l₂) :
∃ a, a :: l₁ <+~ l₂ := by
obtain ⟨l, p, s⟩ := s
suffices length l < length l₂ → ∃ a : α, a :: l <+~ l₂ from
(this <| p.symm.length_eq ▸ h).imp fun a => (p.cons a).subperm_right.1
clear h p l₁
induction s with intro h
| slnil => cases h
| cons a s IH =>
match Nat.lt_or_eq_of_le (Nat.le_of_lt_succ h) with
| .inl h => exact (IH h).imp fun a s => s.trans (sublist_cons _ _).subperm
| .inr h => exact ⟨a, s.eq_of_length h ▸ .refl _⟩
| cons₂ b _ IH =>
exact (IH <| Nat.lt_of_succ_lt_succ h).imp fun a s =>
(swap ..).subperm_right.1 <| (subperm_cons _).2 s
theorem subperm_of_subset (d : Nodup l₁) (H : l₁ ⊆ l₂) : l₁ <+~ l₂ := by
induction d with
| nil => exact ⟨nil, .nil, nil_sublist _⟩
| cons h _ IH =>
have ⟨H₁, H₂⟩ := forall_mem_cons.1 H
exact cons_subperm_of_not_mem_of_mem (h _ · rfl) H₁ (IH H₂)
theorem perm_ext_iff_of_nodup {l₁ l₂ : List α} (d₁ : Nodup l₁) (d₂ : Nodup l₂) :
l₁ ~ l₂ ↔ ∀ a, a ∈ l₁ ↔ a ∈ l₂ := by
refine ⟨fun p _ => p.mem_iff, fun H => ?_⟩
exact (subperm_of_subset d₁ fun a => (H a).1).antisymm <| subperm_of_subset d₂ fun a => (H a).2
theorem Nodup.perm_iff_eq_of_sublist {l₁ l₂ l : List α} (d : Nodup l)
(s₁ : l₁ <+ l) (s₂ : l₂ <+ l) : l₁ ~ l₂ ↔ l₁ = l₂ := by
refine ⟨fun h => ?_, fun h => by rw [h]⟩
induction s₂ generalizing l₁ with simp [Nodup] at d
| slnil => exact h.eq_nil
| cons a s₂ IH =>
match s₁ with
| .cons _ s₁ => exact IH d.2 s₁ h
| .cons₂ _ s₁ =>
have := Subperm.subset ⟨_, h.symm, s₂⟩ (.head _)
exact (d.1 _ this rfl).elim
| cons₂ a _ IH =>
match s₁ with
| .cons _ s₁ =>
have := Subperm.subset ⟨_, h, s₁⟩ (.head _)
exact (d.1 _ this rfl).elim
| .cons₂ _ s₁ => rw [IH d.2 s₁ h.cons_inv]
section DecidableEq
variable [DecidableEq α]
theorem Perm.erase (a : α) {l₁ l₂ : List α} (p : l₁ ~ l₂) : l₁.erase a ~ l₂.erase a :=
if h₁ : a ∈ l₁ then
have h₂ : a ∈ l₂ := p.subset h₁
.cons_inv <| (perm_cons_erase h₁).symm.trans <| p.trans (perm_cons_erase h₂)
else by
have h₂ : a ∉ l₂ := mt p.mem_iff.2 h₁
rw [erase_of_not_mem h₁, erase_of_not_mem h₂]; exact p
theorem subperm_cons_erase (a : α) (l : List α) : l <+~ a :: l.erase a :=
if h : a ∈ l then
(perm_cons_erase h).subperm
else
(erase_of_not_mem h).symm ▸ (sublist_cons _ _).subperm
theorem erase_subperm (a : α) (l : List α) : l.erase a <+~ l := (erase_sublist _ _).subperm
theorem Subperm.erase {l₁ l₂ : List α} (a : α) (h : l₁ <+~ l₂) : l₁.erase a <+~ l₂.erase a :=
let ⟨l, hp, hs⟩ := h
⟨l.erase a, hp.erase _, hs.erase _⟩
theorem Perm.diff_right {l₁ l₂ : List α} (t : List α) (h : l₁ ~ l₂) : l₁.diff t ~ l₂.diff t := by
induction t generalizing l₁ l₂ h with simp only [List.diff]
| nil => exact h
| cons x t ih =>
simp only [elem_eq_mem, decide_eq_true_eq, Perm.mem_iff h]
split
· exact ih (h.erase _)
· exact ih h
theorem Perm.diff_left (l : List α) {t₁ t₂ : List α} (h : t₁ ~ t₂) : l.diff t₁ = l.diff t₂ := by
induction h generalizing l with try simp [List.diff]
| cons x _ ih => apply ite_congr rfl <;> (intro; apply ih)
| swap x y =>
if h : x = y then
simp [h]
else
simp [mem_erase_of_ne h, mem_erase_of_ne (Ne.symm h), erase_comm x y]
split <;> simp [h]
| trans => simp only [*]
theorem Perm.diff {l₁ l₂ t₁ t₂ : List α} (hl : l₁ ~ l₂) (ht : t₁ ~ t₂) : l₁.diff t₁ ~ l₂.diff t₂ :=
ht.diff_left l₂ ▸ hl.diff_right _
theorem Subperm.diff_right {l₁ l₂ : List α} (h : l₁ <+~ l₂) (t : List α) :
l₁.diff t <+~ l₂.diff t := by
induction t generalizing l₁ l₂ h with simp [List.diff, elem_eq_mem, *]
| cons x t ih =>
split <;> rename_i hx1
· simp [h.subset hx1]
exact ih (h.erase _)
· split
· rw [← erase_of_not_mem hx1]
exact ih (h.erase _)
· exact ih h
theorem erase_cons_subperm_cons_erase (a b : α) (l : List α) :
(a :: l).erase b <+~ a :: l.erase b := by
if h : a = b then
rw [h, erase_cons_head]; apply subperm_cons_erase
else
have : ¬(a == b) = true := by simp only [beq_false_of_ne h, not_false_eq_true]
rw [erase_cons_tail _ this]
theorem subperm_cons_diff {a : α} {l₁ l₂ : List α} : (a :: l₁).diff l₂ <+~ a :: l₁.diff l₂ := by
induction l₂ with
| nil => exact ⟨a :: l₁, by simp [List.diff]⟩
| cons b l₂ ih =>
rw [diff_cons, diff_cons, ← diff_erase, ← diff_erase]
exact Subperm.trans (.erase _ ih) (erase_cons_subperm_cons_erase ..)
theorem subset_cons_diff {a : α} {l₁ l₂ : List α} : (a :: l₁).diff l₂ ⊆ a :: l₁.diff l₂ :=
subperm_cons_diff.subset
theorem cons_perm_iff_perm_erase {a : α} {l₁ l₂ : List α} :
a :: l₁ ~ l₂ ↔ a ∈ l₂ ∧ l₁ ~ l₂.erase a := by
refine ⟨fun h => ?_, fun ⟨m, h⟩ => (h.cons a).trans (perm_cons_erase m).symm⟩
have : a ∈ l₂ := h.subset (mem_cons_self a l₁)
exact ⟨this, (h.trans <| perm_cons_erase this).cons_inv⟩
theorem perm_iff_count {l₁ l₂ : List α} : l₁ ~ l₂ ↔ ∀ a, count a l₁ = count a l₂ := by
refine ⟨Perm.count_eq, fun H => ?_⟩
induction l₁ generalizing l₂ with
| nil =>
match l₂ with
| nil => rfl
| cons b l₂ =>
specialize H b
simp at H
| cons a l₁ IH =>
have : a ∈ l₂ := count_pos_iff_mem.mp (by rw [← H]; simp)
refine ((IH fun b => ?_).cons a).trans (perm_cons_erase this).symm
specialize H b
rw [(perm_cons_erase this).count_eq] at H
by_cases h : b = a <;> simpa [h] using H
/-- The list version of `add_tsub_cancel_of_le` for multisets. -/
| .lake/packages/batteries/Batteries/Data/List/Perm.lean | 551 | 566 | theorem subperm_append_diff_self_of_count_le {l₁ l₂ : List α}
(h : ∀ x ∈ l₁, count x l₁ ≤ count x l₂) : l₁ ++ l₂.diff l₁ ~ l₂ := by |
induction l₁ generalizing l₂ with
| nil => simp
| cons hd tl IH =>
have : hd ∈ l₂ := by
rw [← count_pos_iff_mem]
exact Nat.lt_of_lt_of_le (count_pos_iff_mem.mpr (.head _)) (h hd (.head _))
have := perm_cons_erase this
refine Perm.trans ?_ this.symm
rw [cons_append, diff_cons, perm_cons]
refine IH fun x hx => ?_
specialize h x (.tail _ hx)
rw [perm_iff_count.mp this] at h
if hx : x = hd then subst hd; simpa [Nat.succ_le_succ_iff] using h
else simpa [hx] using h
|
/-
Copyright (c) 2020 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot
-/
import Mathlib.Topology.Order.ProjIcc
import Mathlib.Topology.CompactOpen
import Mathlib.Topology.UnitInterval
#align_import topology.path_connected from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Path connectedness
## Main definitions
In the file the unit interval `[0, 1]` in `ℝ` is denoted by `I`, and `X` is a topological space.
* `Path (x y : X)` is the type of paths from `x` to `y`, i.e., continuous maps from `I` to `X`
mapping `0` to `x` and `1` to `y`.
* `Path.map` is the image of a path under a continuous map.
* `Joined (x y : X)` means there is a path between `x` and `y`.
* `Joined.somePath (h : Joined x y)` selects some path between two points `x` and `y`.
* `pathComponent (x : X)` is the set of points joined to `x`.
* `PathConnectedSpace X` is a predicate class asserting that `X` is non-empty and every two
points of `X` are joined.
Then there are corresponding relative notions for `F : Set X`.
* `JoinedIn F (x y : X)` means there is a path `γ` joining `x` to `y` with values in `F`.
* `JoinedIn.somePath (h : JoinedIn F x y)` selects a path from `x` to `y` inside `F`.
* `pathComponentIn F (x : X)` is the set of points joined to `x` in `F`.
* `IsPathConnected F` asserts that `F` is non-empty and every two
points of `F` are joined in `F`.
* `LocPathConnectedSpace X` is a predicate class asserting that `X` is locally path-connected:
each point has a basis of path-connected neighborhoods (we do *not* ask these to be open).
## Main theorems
* `Joined` and `JoinedIn F` are transitive relations.
One can link the absolute and relative version in two directions, using `(univ : Set X)` or the
subtype `↥F`.
* `pathConnectedSpace_iff_univ : PathConnectedSpace X ↔ IsPathConnected (univ : Set X)`
* `isPathConnected_iff_pathConnectedSpace : IsPathConnected F ↔ PathConnectedSpace ↥F`
For locally path connected spaces, we have
* `pathConnectedSpace_iff_connectedSpace : PathConnectedSpace X ↔ ConnectedSpace X`
* `IsOpen.isConnected_iff_isPathConnected (U_op : IsOpen U) : IsPathConnected U ↔ IsConnected U`
## Implementation notes
By default, all paths have `I` as their source and `X` as their target, but there is an
operation `Set.IccExtend` that will extend any continuous map `γ : I → X` into a continuous map
`IccExtend zero_le_one γ : ℝ → X` that is constant before `0` and after `1`.
This is used to define `Path.extend` that turns `γ : Path x y` into a continuous map
`γ.extend : ℝ → X` whose restriction to `I` is the original `γ`, and is equal to `x`
on `(-∞, 0]` and to `y` on `[1, +∞)`.
-/
noncomputable section
open scoped Classical
open Topology Filter unitInterval Set Function
variable {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {x y z : X} {ι : Type*}
/-! ### Paths -/
/-- Continuous path connecting two points `x` and `y` in a topological space -/
-- porting note (#5171): removed @[nolint has_nonempty_instance]
structure Path (x y : X) extends C(I, X) where
/-- The start point of a `Path`. -/
source' : toFun 0 = x
/-- The end point of a `Path`. -/
target' : toFun 1 = y
#align path Path
instance Path.funLike : FunLike (Path x y) I X where
coe := fun γ ↦ ⇑γ.toContinuousMap
coe_injective' := fun γ₁ γ₂ h => by
simp only [DFunLike.coe_fn_eq] at h
cases γ₁; cases γ₂; congr
-- Porting note (#10754): added this instance so that we can use `FunLike.coe` for `CoeFun`
-- this also fixed very strange `simp` timeout issues
instance Path.continuousMapClass : ContinuousMapClass (Path x y) I X where
map_continuous := fun γ => show Continuous γ.toContinuousMap by continuity
-- Porting note: not necessary in light of the instance above
/-
instance : CoeFun (Path x y) fun _ => I → X :=
⟨fun p => p.toFun⟩
-/
@[ext]
protected theorem Path.ext : ∀ {γ₁ γ₂ : Path x y}, (γ₁ : I → X) = γ₂ → γ₁ = γ₂ := by
rintro ⟨⟨x, h11⟩, h12, h13⟩ ⟨⟨x, h21⟩, h22, h23⟩ rfl
rfl
#align path.ext Path.ext
namespace Path
@[simp]
theorem coe_mk_mk (f : I → X) (h₁) (h₂ : f 0 = x) (h₃ : f 1 = y) :
⇑(mk ⟨f, h₁⟩ h₂ h₃ : Path x y) = f :=
rfl
#align path.coe_mk Path.coe_mk_mk
-- Porting note: the name `Path.coe_mk` better refers to a new lemma below
variable (γ : Path x y)
@[continuity]
protected theorem continuous : Continuous γ :=
γ.continuous_toFun
#align path.continuous Path.continuous
@[simp]
protected theorem source : γ 0 = x :=
γ.source'
#align path.source Path.source
@[simp]
protected theorem target : γ 1 = y :=
γ.target'
#align path.target Path.target
/-- See Note [custom simps projection]. We need to specify this projection explicitly in this case,
because it is a composition of multiple projections. -/
def simps.apply : I → X :=
γ
#align path.simps.apply Path.simps.apply
initialize_simps_projections Path (toFun → simps.apply, -toContinuousMap)
@[simp]
theorem coe_toContinuousMap : ⇑γ.toContinuousMap = γ :=
rfl
#align path.coe_to_continuous_map Path.coe_toContinuousMap
-- Porting note: this is needed because of the `Path.continuousMapClass` instance
@[simp]
theorem coe_mk : ⇑(γ : C(I, X)) = γ :=
rfl
/-- Any function `φ : Π (a : α), Path (x a) (y a)` can be seen as a function `α × I → X`. -/
instance hasUncurryPath {X α : Type*} [TopologicalSpace X] {x y : α → X} :
HasUncurry (∀ a : α, Path (x a) (y a)) (α × I) X :=
⟨fun φ p => φ p.1 p.2⟩
#align path.has_uncurry_path Path.hasUncurryPath
/-- The constant path from a point to itself -/
@[refl, simps]
def refl (x : X) : Path x x where
toFun _t := x
continuous_toFun := continuous_const
source' := rfl
target' := rfl
#align path.refl Path.refl
@[simp]
theorem refl_range {a : X} : range (Path.refl a) = {a} := by simp [Path.refl, CoeFun.coe]
#align path.refl_range Path.refl_range
/-- The reverse of a path from `x` to `y`, as a path from `y` to `x` -/
@[symm, simps]
def symm (γ : Path x y) : Path y x where
toFun := γ ∘ σ
continuous_toFun := by continuity
source' := by simpa [-Path.target] using γ.target
target' := by simpa [-Path.source] using γ.source
#align path.symm Path.symm
@[simp]
theorem symm_symm (γ : Path x y) : γ.symm.symm = γ := by
ext t
show γ (σ (σ t)) = γ t
rw [unitInterval.symm_symm]
#align path.symm_symm Path.symm_symm
theorem symm_bijective : Function.Bijective (Path.symm : Path x y → Path y x) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
@[simp]
theorem refl_symm {a : X} : (Path.refl a).symm = Path.refl a := by
ext
rfl
#align path.refl_symm Path.refl_symm
@[simp]
theorem symm_range {a b : X} (γ : Path a b) : range γ.symm = range γ := by
ext x
simp only [mem_range, Path.symm, DFunLike.coe, unitInterval.symm, SetCoe.exists, comp_apply,
Subtype.coe_mk]
constructor <;> rintro ⟨y, hy, hxy⟩ <;> refine ⟨1 - y, mem_iff_one_sub_mem.mp hy, ?_⟩ <;>
convert hxy
simp
#align path.symm_range Path.symm_range
/-! #### Space of paths -/
open ContinuousMap
/- porting note: because of the `DFunLike` instance, we already have a coercion to `C(I, X)`
so we avoid adding another.
--instance : Coe (Path x y) C(I, X) :=
--⟨fun γ => γ.1⟩
-/
/-- The following instance defines the topology on the path space to be induced from the
compact-open topology on the space `C(I,X)` of continuous maps from `I` to `X`.
-/
instance topologicalSpace : TopologicalSpace (Path x y) :=
TopologicalSpace.induced ((↑) : _ → C(I, X)) ContinuousMap.compactOpen
theorem continuous_eval : Continuous fun p : Path x y × I => p.1 p.2 :=
continuous_eval.comp <| (continuous_induced_dom (α := Path x y)).prod_map continuous_id
#align path.continuous_eval Path.continuous_eval
@[continuity]
theorem _root_.Continuous.path_eval {Y} [TopologicalSpace Y] {f : Y → Path x y} {g : Y → I}
(hf : Continuous f) (hg : Continuous g) : Continuous fun y => f y (g y) :=
Continuous.comp continuous_eval (hf.prod_mk hg)
#align continuous.path_eval Continuous.path_eval
theorem continuous_uncurry_iff {Y} [TopologicalSpace Y] {g : Y → Path x y} :
Continuous ↿g ↔ Continuous g :=
Iff.symm <| continuous_induced_rng.trans
⟨fun h => continuous_uncurry_of_continuous ⟨_, h⟩,
continuous_of_continuous_uncurry (fun (y : Y) ↦ ContinuousMap.mk (g y))⟩
#align path.continuous_uncurry_iff Path.continuous_uncurry_iff
/-- A continuous map extending a path to `ℝ`, constant before `0` and after `1`. -/
def extend : ℝ → X :=
IccExtend zero_le_one γ
#align path.extend Path.extend
/-- See Note [continuity lemma statement]. -/
theorem _root_.Continuous.path_extend {γ : Y → Path x y} {f : Y → ℝ} (hγ : Continuous ↿γ)
(hf : Continuous f) : Continuous fun t => (γ t).extend (f t) :=
Continuous.IccExtend hγ hf
#align continuous.path_extend Continuous.path_extend
/-- A useful special case of `Continuous.path_extend`. -/
@[continuity]
theorem continuous_extend : Continuous γ.extend :=
γ.continuous.Icc_extend'
#align path.continuous_extend Path.continuous_extend
theorem _root_.Filter.Tendsto.path_extend
{l r : Y → X} {y : Y} {l₁ : Filter ℝ} {l₂ : Filter X} {γ : ∀ y, Path (l y) (r y)}
(hγ : Tendsto (↿γ) (𝓝 y ×ˢ l₁.map (projIcc 0 1 zero_le_one)) l₂) :
Tendsto (↿fun x => (γ x).extend) (𝓝 y ×ˢ l₁) l₂ :=
Filter.Tendsto.IccExtend _ hγ
#align filter.tendsto.path_extend Filter.Tendsto.path_extend
theorem _root_.ContinuousAt.path_extend {g : Y → ℝ} {l r : Y → X} (γ : ∀ y, Path (l y) (r y))
{y : Y} (hγ : ContinuousAt (↿γ) (y, projIcc 0 1 zero_le_one (g y))) (hg : ContinuousAt g y) :
ContinuousAt (fun i => (γ i).extend (g i)) y :=
hγ.IccExtend (fun x => γ x) hg
#align continuous_at.path_extend ContinuousAt.path_extend
@[simp]
theorem extend_extends {a b : X} (γ : Path a b) {t : ℝ}
(ht : t ∈ (Icc 0 1 : Set ℝ)) : γ.extend t = γ ⟨t, ht⟩ :=
IccExtend_of_mem _ γ ht
#align path.extend_extends Path.extend_extends
theorem extend_zero : γ.extend 0 = x := by simp
#align path.extend_zero Path.extend_zero
theorem extend_one : γ.extend 1 = y := by simp
#align path.extend_one Path.extend_one
@[simp]
theorem extend_extends' {a b : X} (γ : Path a b) (t : (Icc 0 1 : Set ℝ)) : γ.extend t = γ t :=
IccExtend_val _ γ t
#align path.extend_extends' Path.extend_extends'
@[simp]
theorem extend_range {a b : X} (γ : Path a b) :
range γ.extend = range γ :=
IccExtend_range _ γ
#align path.extend_range Path.extend_range
theorem extend_of_le_zero {a b : X} (γ : Path a b) {t : ℝ}
(ht : t ≤ 0) : γ.extend t = a :=
(IccExtend_of_le_left _ _ ht).trans γ.source
#align path.extend_of_le_zero Path.extend_of_le_zero
theorem extend_of_one_le {a b : X} (γ : Path a b) {t : ℝ}
(ht : 1 ≤ t) : γ.extend t = b :=
(IccExtend_of_right_le _ _ ht).trans γ.target
#align path.extend_of_one_le Path.extend_of_one_le
@[simp]
theorem refl_extend {a : X} : (Path.refl a).extend = fun _ => a :=
rfl
#align path.refl_extend Path.refl_extend
/-- The path obtained from a map defined on `ℝ` by restriction to the unit interval. -/
def ofLine {f : ℝ → X} (hf : ContinuousOn f I) (h₀ : f 0 = x) (h₁ : f 1 = y) : Path x y where
toFun := f ∘ ((↑) : unitInterval → ℝ)
continuous_toFun := hf.comp_continuous continuous_subtype_val Subtype.prop
source' := h₀
target' := h₁
#align path.of_line Path.ofLine
theorem ofLine_mem {f : ℝ → X} (hf : ContinuousOn f I) (h₀ : f 0 = x) (h₁ : f 1 = y) :
∀ t, ofLine hf h₀ h₁ t ∈ f '' I := fun ⟨t, t_in⟩ => ⟨t, t_in, rfl⟩
#align path.of_line_mem Path.ofLine_mem
attribute [local simp] Iic_def
set_option tactic.skipAssignedInstances false in
/-- Concatenation of two paths from `x` to `y` and from `y` to `z`, putting the first
path on `[0, 1/2]` and the second one on `[1/2, 1]`. -/
@[trans]
def trans (γ : Path x y) (γ' : Path y z) : Path x z where
toFun := (fun t : ℝ => if t ≤ 1 / 2 then γ.extend (2 * t) else γ'.extend (2 * t - 1)) ∘ (↑)
continuous_toFun := by
refine
(Continuous.if_le ?_ ?_ continuous_id continuous_const (by norm_num)).comp
continuous_subtype_val <;>
continuity
source' := by norm_num
target' := by norm_num
#align path.trans Path.trans
theorem trans_apply (γ : Path x y) (γ' : Path y z) (t : I) :
(γ.trans γ') t =
if h : (t : ℝ) ≤ 1 / 2 then γ ⟨2 * t, (mul_pos_mem_iff zero_lt_two).2 ⟨t.2.1, h⟩⟩
else γ' ⟨2 * t - 1, two_mul_sub_one_mem_iff.2 ⟨(not_le.1 h).le, t.2.2⟩⟩ :=
show ite _ _ _ = _ by split_ifs <;> rw [extend_extends]
#align path.trans_apply Path.trans_apply
@[simp]
theorem trans_symm (γ : Path x y) (γ' : Path y z) : (γ.trans γ').symm = γ'.symm.trans γ.symm := by
ext t
simp only [trans_apply, ← one_div, symm_apply, not_le, Function.comp_apply]
split_ifs with h h₁ h₂ <;> rw [coe_symm_eq] at h
· have ht : (t : ℝ) = 1 / 2 := by linarith
norm_num [ht]
· refine congr_arg _ (Subtype.ext ?_)
norm_num [sub_sub_eq_add_sub, mul_sub]
· refine congr_arg _ (Subtype.ext ?_)
norm_num [mul_sub, h]
ring -- TODO norm_num should really do this
· exfalso
linarith
#align path.trans_symm Path.trans_symm
@[simp]
| Mathlib/Topology/Connected/PathConnected.lean | 358 | 362 | theorem refl_trans_refl {a : X} :
(Path.refl a).trans (Path.refl a) = Path.refl a := by |
ext
simp only [Path.trans, ite_self, one_div, Path.refl_extend]
rfl
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro
-/
import Mathlib.Data.Finset.Attr
import Mathlib.Data.Multiset.FinsetOps
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Basic
#align_import data.finset.basic from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Finite sets
Terms of type `Finset α` are one way of talking about finite subsets of `α` in mathlib.
Below, `Finset α` is defined as a structure with 2 fields:
1. `val` is a `Multiset α` of elements;
2. `nodup` is a proof that `val` has no duplicates.
Finsets in Lean are constructive in that they have an underlying `List` that enumerates their
elements. In particular, any function that uses the data of the underlying list cannot depend on its
ordering. This is handled on the `Multiset` level by multiset API, so in most cases one needn't
worry about it explicitly.
Finsets give a basic foundation for defining finite sums and products over types:
1. `∑ i ∈ (s : Finset α), f i`;
2. `∏ i ∈ (s : Finset α), f i`.
Lean refers to these operations as big operators.
More information can be found in `Mathlib.Algebra.BigOperators.Group.Finset`.
Finsets are directly used to define fintypes in Lean.
A `Fintype α` instance for a type `α` consists of a universal `Finset α` containing every term of
`α`, called `univ`. See `Mathlib.Data.Fintype.Basic`.
There is also `univ'`, the noncomputable partner to `univ`,
which is defined to be `α` as a finset if `α` is finite,
and the empty finset otherwise. See `Mathlib.Data.Fintype.Basic`.
`Finset.card`, the size of a finset is defined in `Mathlib.Data.Finset.Card`.
This is then used to define `Fintype.card`, the size of a type.
## Main declarations
### Main definitions
* `Finset`: Defines a type for the finite subsets of `α`.
Constructing a `Finset` requires two pieces of data: `val`, a `Multiset α` of elements,
and `nodup`, a proof that `val` has no duplicates.
* `Finset.instMembershipFinset`: Defines membership `a ∈ (s : Finset α)`.
* `Finset.instCoeTCFinsetSet`: Provides a coercion `s : Finset α` to `s : Set α`.
* `Finset.instCoeSortFinsetType`: Coerce `s : Finset α` to the type of all `x ∈ s`.
* `Finset.induction_on`: Induction on finsets. To prove a proposition about an arbitrary `Finset α`,
it suffices to prove it for the empty finset, and to show that if it holds for some `Finset α`,
then it holds for the finset obtained by inserting a new element.
* `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element
satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate.
### Finset constructions
* `Finset.instSingletonFinset`: Denoted by `{a}`; the finset consisting of one element.
* `Finset.empty`: Denoted by `∅`. The finset associated to any type consisting of no elements.
* `Finset.range`: For any `n : ℕ`, `range n` is equal to `{0, 1, ... , n - 1} ⊆ ℕ`.
This convention is consistent with other languages and normalizes `card (range n) = n`.
Beware, `n` is not in `range n`.
* `Finset.attach`: Given `s : Finset α`, `attach s` forms a finset of elements of the subtype
`{a // a ∈ s}`; in other words, it attaches elements to a proof of membership in the set.
### Finsets from functions
* `Finset.filter`: Given a decidable predicate `p : α → Prop`, `s.filter p` is
the finset consisting of those elements in `s` satisfying the predicate `p`.
### The lattice structure on subsets of finsets
There is a natural lattice structure on the subsets of a set.
In Lean, we use lattice notation to talk about things involving unions and intersections. See
`Mathlib.Order.Lattice`. For the lattice structure on finsets, `⊥` is called `bot` with `⊥ = ∅` and
`⊤` is called `top` with `⊤ = univ`.
* `Finset.instHasSubsetFinset`: Lots of API about lattices, otherwise behaves as one would expect.
* `Finset.instUnionFinset`: Defines `s ∪ t` (or `s ⊔ t`) as the union of `s` and `t`.
See `Finset.sup`/`Finset.biUnion` for finite unions.
* `Finset.instInterFinset`: Defines `s ∩ t` (or `s ⊓ t`) as the intersection of `s` and `t`.
See `Finset.inf` for finite intersections.
### Operations on two or more finsets
* `insert` and `Finset.cons`: For any `a : α`, `insert s a` returns `s ∪ {a}`. `cons s a h`
returns the same except that it requires a hypothesis stating that `a` is not already in `s`.
This does not require decidable equality on the type `α`.
* `Finset.instUnionFinset`: see "The lattice structure on subsets of finsets"
* `Finset.instInterFinset`: see "The lattice structure on subsets of finsets"
* `Finset.erase`: For any `a : α`, `erase s a` returns `s` with the element `a` removed.
* `Finset.instSDiffFinset`: Defines the set difference `s \ t` for finsets `s` and `t`.
* `Finset.product`: Given finsets of `α` and `β`, defines finsets of `α × β`.
For arbitrary dependent products, see `Mathlib.Data.Finset.Pi`.
### Predicates on finsets
* `Disjoint`: defined via the lattice structure on finsets; two sets are disjoint if their
intersection is empty.
* `Finset.Nonempty`: A finset is nonempty if it has elements. This is equivalent to saying `s ≠ ∅`.
### Equivalences between finsets
* The `Mathlib.Data.Equiv` files describe a general type of equivalence, so look in there for any
lemmas. There is some API for rewriting sums and products from `s` to `t` given that `s ≃ t`.
TODO: examples
## Tags
finite sets, finset
-/
-- Assert that we define `Finset` without the material on `List.sublists`.
-- Note that we cannot use `List.sublists` itself as that is defined very early.
assert_not_exists List.sublistsLen
assert_not_exists Multiset.Powerset
assert_not_exists CompleteLattice
open Multiset Subtype Nat Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
/-- `Finset α` is the type of finite sets of elements of `α`. It is implemented
as a multiset (a list up to permutation) which has no duplicate elements. -/
structure Finset (α : Type*) where
/-- The underlying multiset -/
val : Multiset α
/-- `val` contains no duplicates -/
nodup : Nodup val
#align finset Finset
instance Multiset.canLiftFinset {α} : CanLift (Multiset α) (Finset α) Finset.val Multiset.Nodup :=
⟨fun m hm => ⟨⟨m, hm⟩, rfl⟩⟩
#align multiset.can_lift_finset Multiset.canLiftFinset
namespace Finset
theorem eq_of_veq : ∀ {s t : Finset α}, s.1 = t.1 → s = t
| ⟨s, _⟩, ⟨t, _⟩, h => by cases h; rfl
#align finset.eq_of_veq Finset.eq_of_veq
theorem val_injective : Injective (val : Finset α → Multiset α) := fun _ _ => eq_of_veq
#align finset.val_injective Finset.val_injective
@[simp]
theorem val_inj {s t : Finset α} : s.1 = t.1 ↔ s = t :=
val_injective.eq_iff
#align finset.val_inj Finset.val_inj
@[simp]
theorem dedup_eq_self [DecidableEq α] (s : Finset α) : dedup s.1 = s.1 :=
s.2.dedup
#align finset.dedup_eq_self Finset.dedup_eq_self
instance decidableEq [DecidableEq α] : DecidableEq (Finset α)
| _, _ => decidable_of_iff _ val_inj
#align finset.has_decidable_eq Finset.decidableEq
/-! ### membership -/
instance : Membership α (Finset α) :=
⟨fun a s => a ∈ s.1⟩
theorem mem_def {a : α} {s : Finset α} : a ∈ s ↔ a ∈ s.1 :=
Iff.rfl
#align finset.mem_def Finset.mem_def
@[simp]
theorem mem_val {a : α} {s : Finset α} : a ∈ s.1 ↔ a ∈ s :=
Iff.rfl
#align finset.mem_val Finset.mem_val
@[simp]
theorem mem_mk {a : α} {s nd} : a ∈ @Finset.mk α s nd ↔ a ∈ s :=
Iff.rfl
#align finset.mem_mk Finset.mem_mk
instance decidableMem [_h : DecidableEq α] (a : α) (s : Finset α) : Decidable (a ∈ s) :=
Multiset.decidableMem _ _
#align finset.decidable_mem Finset.decidableMem
@[simp] lemma forall_mem_not_eq {s : Finset α} {a : α} : (∀ b ∈ s, ¬ a = b) ↔ a ∉ s := by aesop
@[simp] lemma forall_mem_not_eq' {s : Finset α} {a : α} : (∀ b ∈ s, ¬ b = a) ↔ a ∉ s := by aesop
/-! ### set coercion -/
-- Porting note (#11445): new definition
/-- Convert a finset to a set in the natural way. -/
@[coe] def toSet (s : Finset α) : Set α :=
{ a | a ∈ s }
/-- Convert a finset to a set in the natural way. -/
instance : CoeTC (Finset α) (Set α) :=
⟨toSet⟩
@[simp, norm_cast]
theorem mem_coe {a : α} {s : Finset α} : a ∈ (s : Set α) ↔ a ∈ (s : Finset α) :=
Iff.rfl
#align finset.mem_coe Finset.mem_coe
@[simp]
theorem setOf_mem {α} {s : Finset α} : { a | a ∈ s } = s :=
rfl
#align finset.set_of_mem Finset.setOf_mem
@[simp]
theorem coe_mem {s : Finset α} (x : (s : Set α)) : ↑x ∈ s :=
x.2
#align finset.coe_mem Finset.coe_mem
-- Porting note (#10618): @[simp] can prove this
theorem mk_coe {s : Finset α} (x : (s : Set α)) {h} : (⟨x, h⟩ : (s : Set α)) = x :=
Subtype.coe_eta _ _
#align finset.mk_coe Finset.mk_coe
instance decidableMem' [DecidableEq α] (a : α) (s : Finset α) : Decidable (a ∈ (s : Set α)) :=
s.decidableMem _
#align finset.decidable_mem' Finset.decidableMem'
/-! ### extensionality -/
theorem ext_iff {s₁ s₂ : Finset α} : s₁ = s₂ ↔ ∀ a, a ∈ s₁ ↔ a ∈ s₂ :=
val_inj.symm.trans <| s₁.nodup.ext s₂.nodup
#align finset.ext_iff Finset.ext_iff
@[ext]
theorem ext {s₁ s₂ : Finset α} : (∀ a, a ∈ s₁ ↔ a ∈ s₂) → s₁ = s₂ :=
ext_iff.2
#align finset.ext Finset.ext
@[simp, norm_cast]
theorem coe_inj {s₁ s₂ : Finset α} : (s₁ : Set α) = s₂ ↔ s₁ = s₂ :=
Set.ext_iff.trans ext_iff.symm
#align finset.coe_inj Finset.coe_inj
theorem coe_injective {α} : Injective ((↑) : Finset α → Set α) := fun _s _t => coe_inj.1
#align finset.coe_injective Finset.coe_injective
/-! ### type coercion -/
/-- Coercion from a finset to the corresponding subtype. -/
instance {α : Type u} : CoeSort (Finset α) (Type u) :=
⟨fun s => { x // x ∈ s }⟩
-- Porting note (#10618): @[simp] can prove this
protected theorem forall_coe {α : Type*} (s : Finset α) (p : s → Prop) :
(∀ x : s, p x) ↔ ∀ (x : α) (h : x ∈ s), p ⟨x, h⟩ :=
Subtype.forall
#align finset.forall_coe Finset.forall_coe
-- Porting note (#10618): @[simp] can prove this
protected theorem exists_coe {α : Type*} (s : Finset α) (p : s → Prop) :
(∃ x : s, p x) ↔ ∃ (x : α) (h : x ∈ s), p ⟨x, h⟩ :=
Subtype.exists
#align finset.exists_coe Finset.exists_coe
instance PiFinsetCoe.canLift (ι : Type*) (α : ι → Type*) [_ne : ∀ i, Nonempty (α i)]
(s : Finset ι) : CanLift (∀ i : s, α i) (∀ i, α i) (fun f i => f i) fun _ => True :=
PiSubtype.canLift ι α (· ∈ s)
#align finset.pi_finset_coe.can_lift Finset.PiFinsetCoe.canLift
instance PiFinsetCoe.canLift' (ι α : Type*) [_ne : Nonempty α] (s : Finset ι) :
CanLift (s → α) (ι → α) (fun f i => f i) fun _ => True :=
PiFinsetCoe.canLift ι (fun _ => α) s
#align finset.pi_finset_coe.can_lift' Finset.PiFinsetCoe.canLift'
instance FinsetCoe.canLift (s : Finset α) : CanLift α s (↑) fun a => a ∈ s where
prf a ha := ⟨⟨a, ha⟩, rfl⟩
#align finset.finset_coe.can_lift Finset.FinsetCoe.canLift
@[simp, norm_cast]
theorem coe_sort_coe (s : Finset α) : ((s : Set α) : Sort _) = s :=
rfl
#align finset.coe_sort_coe Finset.coe_sort_coe
/-! ### Subset and strict subset relations -/
section Subset
variable {s t : Finset α}
instance : HasSubset (Finset α) :=
⟨fun s t => ∀ ⦃a⦄, a ∈ s → a ∈ t⟩
instance : HasSSubset (Finset α) :=
⟨fun s t => s ⊆ t ∧ ¬t ⊆ s⟩
instance partialOrder : PartialOrder (Finset α) where
le := (· ⊆ ·)
lt := (· ⊂ ·)
le_refl s a := id
le_trans s t u hst htu a ha := htu <| hst ha
le_antisymm s t hst hts := ext fun a => ⟨@hst _, @hts _⟩
instance : IsRefl (Finset α) (· ⊆ ·) :=
show IsRefl (Finset α) (· ≤ ·) by infer_instance
instance : IsTrans (Finset α) (· ⊆ ·) :=
show IsTrans (Finset α) (· ≤ ·) by infer_instance
instance : IsAntisymm (Finset α) (· ⊆ ·) :=
show IsAntisymm (Finset α) (· ≤ ·) by infer_instance
instance : IsIrrefl (Finset α) (· ⊂ ·) :=
show IsIrrefl (Finset α) (· < ·) by infer_instance
instance : IsTrans (Finset α) (· ⊂ ·) :=
show IsTrans (Finset α) (· < ·) by infer_instance
instance : IsAsymm (Finset α) (· ⊂ ·) :=
show IsAsymm (Finset α) (· < ·) by infer_instance
instance : IsNonstrictStrictOrder (Finset α) (· ⊆ ·) (· ⊂ ·) :=
⟨fun _ _ => Iff.rfl⟩
theorem subset_def : s ⊆ t ↔ s.1 ⊆ t.1 :=
Iff.rfl
#align finset.subset_def Finset.subset_def
theorem ssubset_def : s ⊂ t ↔ s ⊆ t ∧ ¬t ⊆ s :=
Iff.rfl
#align finset.ssubset_def Finset.ssubset_def
@[simp]
theorem Subset.refl (s : Finset α) : s ⊆ s :=
Multiset.Subset.refl _
#align finset.subset.refl Finset.Subset.refl
protected theorem Subset.rfl {s : Finset α} : s ⊆ s :=
Subset.refl _
#align finset.subset.rfl Finset.Subset.rfl
protected theorem subset_of_eq {s t : Finset α} (h : s = t) : s ⊆ t :=
h ▸ Subset.refl _
#align finset.subset_of_eq Finset.subset_of_eq
theorem Subset.trans {s₁ s₂ s₃ : Finset α} : s₁ ⊆ s₂ → s₂ ⊆ s₃ → s₁ ⊆ s₃ :=
Multiset.Subset.trans
#align finset.subset.trans Finset.Subset.trans
theorem Superset.trans {s₁ s₂ s₃ : Finset α} : s₁ ⊇ s₂ → s₂ ⊇ s₃ → s₁ ⊇ s₃ := fun h' h =>
Subset.trans h h'
#align finset.superset.trans Finset.Superset.trans
theorem mem_of_subset {s₁ s₂ : Finset α} {a : α} : s₁ ⊆ s₂ → a ∈ s₁ → a ∈ s₂ :=
Multiset.mem_of_subset
#align finset.mem_of_subset Finset.mem_of_subset
theorem not_mem_mono {s t : Finset α} (h : s ⊆ t) {a : α} : a ∉ t → a ∉ s :=
mt <| @h _
#align finset.not_mem_mono Finset.not_mem_mono
theorem Subset.antisymm {s₁ s₂ : Finset α} (H₁ : s₁ ⊆ s₂) (H₂ : s₂ ⊆ s₁) : s₁ = s₂ :=
ext fun a => ⟨@H₁ a, @H₂ a⟩
#align finset.subset.antisymm Finset.Subset.antisymm
theorem subset_iff {s₁ s₂ : Finset α} : s₁ ⊆ s₂ ↔ ∀ ⦃x⦄, x ∈ s₁ → x ∈ s₂ :=
Iff.rfl
#align finset.subset_iff Finset.subset_iff
@[simp, norm_cast]
theorem coe_subset {s₁ s₂ : Finset α} : (s₁ : Set α) ⊆ s₂ ↔ s₁ ⊆ s₂ :=
Iff.rfl
#align finset.coe_subset Finset.coe_subset
@[simp]
theorem val_le_iff {s₁ s₂ : Finset α} : s₁.1 ≤ s₂.1 ↔ s₁ ⊆ s₂ :=
le_iff_subset s₁.2
#align finset.val_le_iff Finset.val_le_iff
theorem Subset.antisymm_iff {s₁ s₂ : Finset α} : s₁ = s₂ ↔ s₁ ⊆ s₂ ∧ s₂ ⊆ s₁ :=
le_antisymm_iff
#align finset.subset.antisymm_iff Finset.Subset.antisymm_iff
theorem not_subset : ¬s ⊆ t ↔ ∃ x ∈ s, x ∉ t := by simp only [← coe_subset, Set.not_subset, mem_coe]
#align finset.not_subset Finset.not_subset
@[simp]
theorem le_eq_subset : ((· ≤ ·) : Finset α → Finset α → Prop) = (· ⊆ ·) :=
rfl
#align finset.le_eq_subset Finset.le_eq_subset
@[simp]
theorem lt_eq_subset : ((· < ·) : Finset α → Finset α → Prop) = (· ⊂ ·) :=
rfl
#align finset.lt_eq_subset Finset.lt_eq_subset
theorem le_iff_subset {s₁ s₂ : Finset α} : s₁ ≤ s₂ ↔ s₁ ⊆ s₂ :=
Iff.rfl
#align finset.le_iff_subset Finset.le_iff_subset
theorem lt_iff_ssubset {s₁ s₂ : Finset α} : s₁ < s₂ ↔ s₁ ⊂ s₂ :=
Iff.rfl
#align finset.lt_iff_ssubset Finset.lt_iff_ssubset
@[simp, norm_cast]
theorem coe_ssubset {s₁ s₂ : Finset α} : (s₁ : Set α) ⊂ s₂ ↔ s₁ ⊂ s₂ :=
show (s₁ : Set α) ⊂ s₂ ↔ s₁ ⊆ s₂ ∧ ¬s₂ ⊆ s₁ by simp only [Set.ssubset_def, Finset.coe_subset]
#align finset.coe_ssubset Finset.coe_ssubset
@[simp]
theorem val_lt_iff {s₁ s₂ : Finset α} : s₁.1 < s₂.1 ↔ s₁ ⊂ s₂ :=
and_congr val_le_iff <| not_congr val_le_iff
#align finset.val_lt_iff Finset.val_lt_iff
lemma val_strictMono : StrictMono (val : Finset α → Multiset α) := fun _ _ ↦ val_lt_iff.2
theorem ssubset_iff_subset_ne {s t : Finset α} : s ⊂ t ↔ s ⊆ t ∧ s ≠ t :=
@lt_iff_le_and_ne _ _ s t
#align finset.ssubset_iff_subset_ne Finset.ssubset_iff_subset_ne
theorem ssubset_iff_of_subset {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₁ ⊂ s₂ ↔ ∃ x ∈ s₂, x ∉ s₁ :=
Set.ssubset_iff_of_subset h
#align finset.ssubset_iff_of_subset Finset.ssubset_iff_of_subset
theorem ssubset_of_ssubset_of_subset {s₁ s₂ s₃ : Finset α} (hs₁s₂ : s₁ ⊂ s₂) (hs₂s₃ : s₂ ⊆ s₃) :
s₁ ⊂ s₃ :=
Set.ssubset_of_ssubset_of_subset hs₁s₂ hs₂s₃
#align finset.ssubset_of_ssubset_of_subset Finset.ssubset_of_ssubset_of_subset
theorem ssubset_of_subset_of_ssubset {s₁ s₂ s₃ : Finset α} (hs₁s₂ : s₁ ⊆ s₂) (hs₂s₃ : s₂ ⊂ s₃) :
s₁ ⊂ s₃ :=
Set.ssubset_of_subset_of_ssubset hs₁s₂ hs₂s₃
#align finset.ssubset_of_subset_of_ssubset Finset.ssubset_of_subset_of_ssubset
theorem exists_of_ssubset {s₁ s₂ : Finset α} (h : s₁ ⊂ s₂) : ∃ x ∈ s₂, x ∉ s₁ :=
Set.exists_of_ssubset h
#align finset.exists_of_ssubset Finset.exists_of_ssubset
instance isWellFounded_ssubset : IsWellFounded (Finset α) (· ⊂ ·) :=
Subrelation.isWellFounded (InvImage _ _) val_lt_iff.2
#align finset.is_well_founded_ssubset Finset.isWellFounded_ssubset
instance wellFoundedLT : WellFoundedLT (Finset α) :=
Finset.isWellFounded_ssubset
#align finset.is_well_founded_lt Finset.wellFoundedLT
end Subset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
/-! ### Order embedding from `Finset α` to `Set α` -/
/-- Coercion to `Set α` as an `OrderEmbedding`. -/
def coeEmb : Finset α ↪o Set α :=
⟨⟨(↑), coe_injective⟩, coe_subset⟩
#align finset.coe_emb Finset.coeEmb
@[simp]
theorem coe_coeEmb : ⇑(coeEmb : Finset α ↪o Set α) = ((↑) : Finset α → Set α) :=
rfl
#align finset.coe_coe_emb Finset.coe_coeEmb
/-! ### Nonempty -/
/-- The property `s.Nonempty` expresses the fact that the finset `s` is not empty. It should be used
in theorem assumptions instead of `∃ x, x ∈ s` or `s ≠ ∅` as it gives access to a nice API thanks
to the dot notation. -/
protected def Nonempty (s : Finset α) : Prop := ∃ x : α, x ∈ s
#align finset.nonempty Finset.Nonempty
-- Porting note: Much longer than in Lean3
instance decidableNonempty {s : Finset α} : Decidable s.Nonempty :=
Quotient.recOnSubsingleton (motive := fun s : Multiset α => Decidable (∃ a, a ∈ s)) s.1
(fun l : List α =>
match l with
| [] => isFalse <| by simp
| a::l => isTrue ⟨a, by simp⟩)
#align finset.decidable_nonempty Finset.decidableNonempty
@[simp, norm_cast]
theorem coe_nonempty {s : Finset α} : (s : Set α).Nonempty ↔ s.Nonempty :=
Iff.rfl
#align finset.coe_nonempty Finset.coe_nonempty
-- Porting note: Left-hand side simplifies @[simp]
theorem nonempty_coe_sort {s : Finset α} : Nonempty (s : Type _) ↔ s.Nonempty :=
nonempty_subtype
#align finset.nonempty_coe_sort Finset.nonempty_coe_sort
alias ⟨_, Nonempty.to_set⟩ := coe_nonempty
#align finset.nonempty.to_set Finset.Nonempty.to_set
alias ⟨_, Nonempty.coe_sort⟩ := nonempty_coe_sort
#align finset.nonempty.coe_sort Finset.Nonempty.coe_sort
theorem Nonempty.exists_mem {s : Finset α} (h : s.Nonempty) : ∃ x : α, x ∈ s :=
h
#align finset.nonempty.bex Finset.Nonempty.exists_mem
@[deprecated (since := "2024-03-23")] alias Nonempty.bex := Nonempty.exists_mem
theorem Nonempty.mono {s t : Finset α} (hst : s ⊆ t) (hs : s.Nonempty) : t.Nonempty :=
Set.Nonempty.mono hst hs
#align finset.nonempty.mono Finset.Nonempty.mono
theorem Nonempty.forall_const {s : Finset α} (h : s.Nonempty) {p : Prop} : (∀ x ∈ s, p) ↔ p :=
let ⟨x, hx⟩ := h
⟨fun h => h x hx, fun h _ _ => h⟩
#align finset.nonempty.forall_const Finset.Nonempty.forall_const
theorem Nonempty.to_subtype {s : Finset α} : s.Nonempty → Nonempty s :=
nonempty_coe_sort.2
#align finset.nonempty.to_subtype Finset.Nonempty.to_subtype
theorem Nonempty.to_type {s : Finset α} : s.Nonempty → Nonempty α := fun ⟨x, _hx⟩ => ⟨x⟩
#align finset.nonempty.to_type Finset.Nonempty.to_type
/-! ### empty -/
section Empty
variable {s : Finset α}
/-- The empty finset -/
protected def empty : Finset α :=
⟨0, nodup_zero⟩
#align finset.empty Finset.empty
instance : EmptyCollection (Finset α) :=
⟨Finset.empty⟩
instance inhabitedFinset : Inhabited (Finset α) :=
⟨∅⟩
#align finset.inhabited_finset Finset.inhabitedFinset
@[simp]
theorem empty_val : (∅ : Finset α).1 = 0 :=
rfl
#align finset.empty_val Finset.empty_val
@[simp]
theorem not_mem_empty (a : α) : a ∉ (∅ : Finset α) := by
-- Porting note: was `id`. `a ∈ List.nil` is no longer definitionally equal to `False`
simp only [mem_def, empty_val, not_mem_zero, not_false_iff]
#align finset.not_mem_empty Finset.not_mem_empty
@[simp]
theorem not_nonempty_empty : ¬(∅ : Finset α).Nonempty := fun ⟨x, hx⟩ => not_mem_empty x hx
#align finset.not_nonempty_empty Finset.not_nonempty_empty
@[simp]
theorem mk_zero : (⟨0, nodup_zero⟩ : Finset α) = ∅ :=
rfl
#align finset.mk_zero Finset.mk_zero
theorem ne_empty_of_mem {a : α} {s : Finset α} (h : a ∈ s) : s ≠ ∅ := fun e =>
not_mem_empty a <| e ▸ h
#align finset.ne_empty_of_mem Finset.ne_empty_of_mem
theorem Nonempty.ne_empty {s : Finset α} (h : s.Nonempty) : s ≠ ∅ :=
(Exists.elim h) fun _a => ne_empty_of_mem
#align finset.nonempty.ne_empty Finset.Nonempty.ne_empty
@[simp]
theorem empty_subset (s : Finset α) : ∅ ⊆ s :=
zero_subset _
#align finset.empty_subset Finset.empty_subset
theorem eq_empty_of_forall_not_mem {s : Finset α} (H : ∀ x, x ∉ s) : s = ∅ :=
eq_of_veq (eq_zero_of_forall_not_mem H)
#align finset.eq_empty_of_forall_not_mem Finset.eq_empty_of_forall_not_mem
theorem eq_empty_iff_forall_not_mem {s : Finset α} : s = ∅ ↔ ∀ x, x ∉ s :=
-- Porting note: used `id`
⟨by rintro rfl x; apply not_mem_empty, fun h => eq_empty_of_forall_not_mem h⟩
#align finset.eq_empty_iff_forall_not_mem Finset.eq_empty_iff_forall_not_mem
@[simp]
theorem val_eq_zero {s : Finset α} : s.1 = 0 ↔ s = ∅ :=
@val_inj _ s ∅
#align finset.val_eq_zero Finset.val_eq_zero
theorem subset_empty {s : Finset α} : s ⊆ ∅ ↔ s = ∅ :=
subset_zero.trans val_eq_zero
#align finset.subset_empty Finset.subset_empty
@[simp]
theorem not_ssubset_empty (s : Finset α) : ¬s ⊂ ∅ := fun h =>
let ⟨_, he, _⟩ := exists_of_ssubset h
-- Porting note: was `he`
not_mem_empty _ he
#align finset.not_ssubset_empty Finset.not_ssubset_empty
theorem nonempty_of_ne_empty {s : Finset α} (h : s ≠ ∅) : s.Nonempty :=
exists_mem_of_ne_zero (mt val_eq_zero.1 h)
#align finset.nonempty_of_ne_empty Finset.nonempty_of_ne_empty
theorem nonempty_iff_ne_empty {s : Finset α} : s.Nonempty ↔ s ≠ ∅ :=
⟨Nonempty.ne_empty, nonempty_of_ne_empty⟩
#align finset.nonempty_iff_ne_empty Finset.nonempty_iff_ne_empty
@[simp]
theorem not_nonempty_iff_eq_empty {s : Finset α} : ¬s.Nonempty ↔ s = ∅ :=
nonempty_iff_ne_empty.not.trans not_not
#align finset.not_nonempty_iff_eq_empty Finset.not_nonempty_iff_eq_empty
theorem eq_empty_or_nonempty (s : Finset α) : s = ∅ ∨ s.Nonempty :=
by_cases Or.inl fun h => Or.inr (nonempty_of_ne_empty h)
#align finset.eq_empty_or_nonempty Finset.eq_empty_or_nonempty
@[simp, norm_cast]
theorem coe_empty : ((∅ : Finset α) : Set α) = ∅ :=
Set.ext <| by simp
#align finset.coe_empty Finset.coe_empty
@[simp, norm_cast]
theorem coe_eq_empty {s : Finset α} : (s : Set α) = ∅ ↔ s = ∅ := by rw [← coe_empty, coe_inj]
#align finset.coe_eq_empty Finset.coe_eq_empty
-- Porting note: Left-hand side simplifies @[simp]
theorem isEmpty_coe_sort {s : Finset α} : IsEmpty (s : Type _) ↔ s = ∅ := by
simpa using @Set.isEmpty_coe_sort α s
#align finset.is_empty_coe_sort Finset.isEmpty_coe_sort
instance instIsEmpty : IsEmpty (∅ : Finset α) :=
isEmpty_coe_sort.2 rfl
/-- A `Finset` for an empty type is empty. -/
theorem eq_empty_of_isEmpty [IsEmpty α] (s : Finset α) : s = ∅ :=
Finset.eq_empty_of_forall_not_mem isEmptyElim
#align finset.eq_empty_of_is_empty Finset.eq_empty_of_isEmpty
instance : OrderBot (Finset α) where
bot := ∅
bot_le := empty_subset
@[simp]
theorem bot_eq_empty : (⊥ : Finset α) = ∅ :=
rfl
#align finset.bot_eq_empty Finset.bot_eq_empty
@[simp]
theorem empty_ssubset : ∅ ⊂ s ↔ s.Nonempty :=
(@bot_lt_iff_ne_bot (Finset α) _ _ _).trans nonempty_iff_ne_empty.symm
#align finset.empty_ssubset Finset.empty_ssubset
alias ⟨_, Nonempty.empty_ssubset⟩ := empty_ssubset
#align finset.nonempty.empty_ssubset Finset.Nonempty.empty_ssubset
end Empty
/-! ### singleton -/
section Singleton
variable {s : Finset α} {a b : α}
/-- `{a} : Finset a` is the set `{a}` containing `a` and nothing else.
This differs from `insert a ∅` in that it does not require a `DecidableEq` instance for `α`.
-/
instance : Singleton α (Finset α) :=
⟨fun a => ⟨{a}, nodup_singleton a⟩⟩
@[simp]
theorem singleton_val (a : α) : ({a} : Finset α).1 = {a} :=
rfl
#align finset.singleton_val Finset.singleton_val
@[simp]
theorem mem_singleton {a b : α} : b ∈ ({a} : Finset α) ↔ b = a :=
Multiset.mem_singleton
#align finset.mem_singleton Finset.mem_singleton
theorem eq_of_mem_singleton {x y : α} (h : x ∈ ({y} : Finset α)) : x = y :=
mem_singleton.1 h
#align finset.eq_of_mem_singleton Finset.eq_of_mem_singleton
theorem not_mem_singleton {a b : α} : a ∉ ({b} : Finset α) ↔ a ≠ b :=
not_congr mem_singleton
#align finset.not_mem_singleton Finset.not_mem_singleton
theorem mem_singleton_self (a : α) : a ∈ ({a} : Finset α) :=
-- Porting note: was `Or.inl rfl`
mem_singleton.mpr rfl
#align finset.mem_singleton_self Finset.mem_singleton_self
@[simp]
theorem val_eq_singleton_iff {a : α} {s : Finset α} : s.val = {a} ↔ s = {a} := by
rw [← val_inj]
rfl
#align finset.val_eq_singleton_iff Finset.val_eq_singleton_iff
theorem singleton_injective : Injective (singleton : α → Finset α) := fun _a _b h =>
mem_singleton.1 (h ▸ mem_singleton_self _)
#align finset.singleton_injective Finset.singleton_injective
@[simp]
theorem singleton_inj : ({a} : Finset α) = {b} ↔ a = b :=
singleton_injective.eq_iff
#align finset.singleton_inj Finset.singleton_inj
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem singleton_nonempty (a : α) : ({a} : Finset α).Nonempty :=
⟨a, mem_singleton_self a⟩
#align finset.singleton_nonempty Finset.singleton_nonempty
@[simp]
theorem singleton_ne_empty (a : α) : ({a} : Finset α) ≠ ∅ :=
(singleton_nonempty a).ne_empty
#align finset.singleton_ne_empty Finset.singleton_ne_empty
theorem empty_ssubset_singleton : (∅ : Finset α) ⊂ {a} :=
(singleton_nonempty _).empty_ssubset
#align finset.empty_ssubset_singleton Finset.empty_ssubset_singleton
@[simp, norm_cast]
theorem coe_singleton (a : α) : (({a} : Finset α) : Set α) = {a} := by
ext
simp
#align finset.coe_singleton Finset.coe_singleton
@[simp, norm_cast]
theorem coe_eq_singleton {s : Finset α} {a : α} : (s : Set α) = {a} ↔ s = {a} := by
rw [← coe_singleton, coe_inj]
#align finset.coe_eq_singleton Finset.coe_eq_singleton
@[norm_cast]
lemma coe_subset_singleton : (s : Set α) ⊆ {a} ↔ s ⊆ {a} := by rw [← coe_subset, coe_singleton]
@[norm_cast]
lemma singleton_subset_coe : {a} ⊆ (s : Set α) ↔ {a} ⊆ s := by rw [← coe_subset, coe_singleton]
theorem eq_singleton_iff_unique_mem {s : Finset α} {a : α} : s = {a} ↔ a ∈ s ∧ ∀ x ∈ s, x = a := by
constructor <;> intro t
· rw [t]
exact ⟨Finset.mem_singleton_self _, fun _ => Finset.mem_singleton.1⟩
· ext
rw [Finset.mem_singleton]
exact ⟨t.right _, fun r => r.symm ▸ t.left⟩
#align finset.eq_singleton_iff_unique_mem Finset.eq_singleton_iff_unique_mem
theorem eq_singleton_iff_nonempty_unique_mem {s : Finset α} {a : α} :
s = {a} ↔ s.Nonempty ∧ ∀ x ∈ s, x = a := by
constructor
· rintro rfl
simp
· rintro ⟨hne, h_uniq⟩
rw [eq_singleton_iff_unique_mem]
refine ⟨?_, h_uniq⟩
rw [← h_uniq hne.choose hne.choose_spec]
exact hne.choose_spec
#align finset.eq_singleton_iff_nonempty_unique_mem Finset.eq_singleton_iff_nonempty_unique_mem
theorem nonempty_iff_eq_singleton_default [Unique α] {s : Finset α} :
s.Nonempty ↔ s = {default} := by
simp [eq_singleton_iff_nonempty_unique_mem, eq_iff_true_of_subsingleton]
#align finset.nonempty_iff_eq_singleton_default Finset.nonempty_iff_eq_singleton_default
alias ⟨Nonempty.eq_singleton_default, _⟩ := nonempty_iff_eq_singleton_default
#align finset.nonempty.eq_singleton_default Finset.Nonempty.eq_singleton_default
theorem singleton_iff_unique_mem (s : Finset α) : (∃ a, s = {a}) ↔ ∃! a, a ∈ s := by
simp only [eq_singleton_iff_unique_mem, ExistsUnique]
#align finset.singleton_iff_unique_mem Finset.singleton_iff_unique_mem
theorem singleton_subset_set_iff {s : Set α} {a : α} : ↑({a} : Finset α) ⊆ s ↔ a ∈ s := by
rw [coe_singleton, Set.singleton_subset_iff]
#align finset.singleton_subset_set_iff Finset.singleton_subset_set_iff
@[simp]
theorem singleton_subset_iff {s : Finset α} {a : α} : {a} ⊆ s ↔ a ∈ s :=
singleton_subset_set_iff
#align finset.singleton_subset_iff Finset.singleton_subset_iff
@[simp]
theorem subset_singleton_iff {s : Finset α} {a : α} : s ⊆ {a} ↔ s = ∅ ∨ s = {a} := by
rw [← coe_subset, coe_singleton, Set.subset_singleton_iff_eq, coe_eq_empty, coe_eq_singleton]
#align finset.subset_singleton_iff Finset.subset_singleton_iff
theorem singleton_subset_singleton : ({a} : Finset α) ⊆ {b} ↔ a = b := by simp
#align finset.singleton_subset_singleton Finset.singleton_subset_singleton
protected theorem Nonempty.subset_singleton_iff {s : Finset α} {a : α} (h : s.Nonempty) :
s ⊆ {a} ↔ s = {a} :=
subset_singleton_iff.trans <| or_iff_right h.ne_empty
#align finset.nonempty.subset_singleton_iff Finset.Nonempty.subset_singleton_iff
theorem subset_singleton_iff' {s : Finset α} {a : α} : s ⊆ {a} ↔ ∀ b ∈ s, b = a :=
forall₂_congr fun _ _ => mem_singleton
#align finset.subset_singleton_iff' Finset.subset_singleton_iff'
@[simp]
theorem ssubset_singleton_iff {s : Finset α} {a : α} : s ⊂ {a} ↔ s = ∅ := by
rw [← coe_ssubset, coe_singleton, Set.ssubset_singleton_iff, coe_eq_empty]
#align finset.ssubset_singleton_iff Finset.ssubset_singleton_iff
theorem eq_empty_of_ssubset_singleton {s : Finset α} {x : α} (hs : s ⊂ {x}) : s = ∅ :=
ssubset_singleton_iff.1 hs
#align finset.eq_empty_of_ssubset_singleton Finset.eq_empty_of_ssubset_singleton
/-- A finset is nontrivial if it has at least two elements. -/
protected abbrev Nontrivial (s : Finset α) : Prop := (s : Set α).Nontrivial
#align finset.nontrivial Finset.Nontrivial
@[simp]
theorem not_nontrivial_empty : ¬ (∅ : Finset α).Nontrivial := by simp [Finset.Nontrivial]
#align finset.not_nontrivial_empty Finset.not_nontrivial_empty
@[simp]
theorem not_nontrivial_singleton : ¬ ({a} : Finset α).Nontrivial := by simp [Finset.Nontrivial]
#align finset.not_nontrivial_singleton Finset.not_nontrivial_singleton
theorem Nontrivial.ne_singleton (hs : s.Nontrivial) : s ≠ {a} := by
rintro rfl; exact not_nontrivial_singleton hs
#align finset.nontrivial.ne_singleton Finset.Nontrivial.ne_singleton
nonrec lemma Nontrivial.exists_ne (hs : s.Nontrivial) (a : α) : ∃ b ∈ s, b ≠ a := hs.exists_ne _
theorem eq_singleton_or_nontrivial (ha : a ∈ s) : s = {a} ∨ s.Nontrivial := by
rw [← coe_eq_singleton]; exact Set.eq_singleton_or_nontrivial ha
#align finset.eq_singleton_or_nontrivial Finset.eq_singleton_or_nontrivial
theorem nontrivial_iff_ne_singleton (ha : a ∈ s) : s.Nontrivial ↔ s ≠ {a} :=
⟨Nontrivial.ne_singleton, (eq_singleton_or_nontrivial ha).resolve_left⟩
#align finset.nontrivial_iff_ne_singleton Finset.nontrivial_iff_ne_singleton
theorem Nonempty.exists_eq_singleton_or_nontrivial : s.Nonempty → (∃ a, s = {a}) ∨ s.Nontrivial :=
fun ⟨a, ha⟩ => (eq_singleton_or_nontrivial ha).imp_left <| Exists.intro a
#align finset.nonempty.exists_eq_singleton_or_nontrivial Finset.Nonempty.exists_eq_singleton_or_nontrivial
instance instNontrivial [Nonempty α] : Nontrivial (Finset α) :=
‹Nonempty α›.elim fun a => ⟨⟨{a}, ∅, singleton_ne_empty _⟩⟩
#align finset.nontrivial' Finset.instNontrivial
instance [IsEmpty α] : Unique (Finset α) where
default := ∅
uniq _ := eq_empty_of_forall_not_mem isEmptyElim
instance (i : α) : Unique ({i} : Finset α) where
default := ⟨i, mem_singleton_self i⟩
uniq j := Subtype.ext <| mem_singleton.mp j.2
@[simp]
lemma default_singleton (i : α) : ((default : ({i} : Finset α)) : α) = i := rfl
end Singleton
/-! ### cons -/
section Cons
variable {s t : Finset α} {a b : α}
/-- `cons a s h` is the set `{a} ∪ s` containing `a` and the elements of `s`. It is the same as
`insert a s` when it is defined, but unlike `insert a s` it does not require `DecidableEq α`,
and the union is guaranteed to be disjoint. -/
def cons (a : α) (s : Finset α) (h : a ∉ s) : Finset α :=
⟨a ::ₘ s.1, nodup_cons.2 ⟨h, s.2⟩⟩
#align finset.cons Finset.cons
@[simp]
theorem mem_cons {h} : b ∈ s.cons a h ↔ b = a ∨ b ∈ s :=
Multiset.mem_cons
#align finset.mem_cons Finset.mem_cons
theorem mem_cons_of_mem {a b : α} {s : Finset α} {hb : b ∉ s} (ha : a ∈ s) : a ∈ cons b s hb :=
Multiset.mem_cons_of_mem ha
-- Porting note (#10618): @[simp] can prove this
theorem mem_cons_self (a : α) (s : Finset α) {h} : a ∈ cons a s h :=
Multiset.mem_cons_self _ _
#align finset.mem_cons_self Finset.mem_cons_self
@[simp]
theorem cons_val (h : a ∉ s) : (cons a s h).1 = a ::ₘ s.1 :=
rfl
#align finset.cons_val Finset.cons_val
theorem forall_mem_cons (h : a ∉ s) (p : α → Prop) :
(∀ x, x ∈ cons a s h → p x) ↔ p a ∧ ∀ x, x ∈ s → p x := by
simp only [mem_cons, or_imp, forall_and, forall_eq]
#align finset.forall_mem_cons Finset.forall_mem_cons
/-- Useful in proofs by induction. -/
theorem forall_of_forall_cons {p : α → Prop} {h : a ∉ s} (H : ∀ x, x ∈ cons a s h → p x) (x)
(h : x ∈ s) : p x :=
H _ <| mem_cons.2 <| Or.inr h
#align finset.forall_of_forall_cons Finset.forall_of_forall_cons
@[simp]
theorem mk_cons {s : Multiset α} (h : (a ::ₘ s).Nodup) :
(⟨a ::ₘ s, h⟩ : Finset α) = cons a ⟨s, (nodup_cons.1 h).2⟩ (nodup_cons.1 h).1 :=
rfl
#align finset.mk_cons Finset.mk_cons
@[simp]
theorem cons_empty (a : α) : cons a ∅ (not_mem_empty _) = {a} := rfl
#align finset.cons_empty Finset.cons_empty
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem nonempty_cons (h : a ∉ s) : (cons a s h).Nonempty :=
⟨a, mem_cons.2 <| Or.inl rfl⟩
#align finset.nonempty_cons Finset.nonempty_cons
@[simp]
theorem nonempty_mk {m : Multiset α} {hm} : (⟨m, hm⟩ : Finset α).Nonempty ↔ m ≠ 0 := by
induction m using Multiset.induction_on <;> simp
#align finset.nonempty_mk Finset.nonempty_mk
@[simp]
theorem coe_cons {a s h} : (@cons α a s h : Set α) = insert a (s : Set α) := by
ext
simp
#align finset.coe_cons Finset.coe_cons
theorem subset_cons (h : a ∉ s) : s ⊆ s.cons a h :=
Multiset.subset_cons _ _
#align finset.subset_cons Finset.subset_cons
theorem ssubset_cons (h : a ∉ s) : s ⊂ s.cons a h :=
Multiset.ssubset_cons h
#align finset.ssubset_cons Finset.ssubset_cons
theorem cons_subset {h : a ∉ s} : s.cons a h ⊆ t ↔ a ∈ t ∧ s ⊆ t :=
Multiset.cons_subset
#align finset.cons_subset Finset.cons_subset
@[simp]
theorem cons_subset_cons {hs ht} : s.cons a hs ⊆ t.cons a ht ↔ s ⊆ t := by
rwa [← coe_subset, coe_cons, coe_cons, Set.insert_subset_insert_iff, coe_subset]
#align finset.cons_subset_cons Finset.cons_subset_cons
theorem ssubset_iff_exists_cons_subset : s ⊂ t ↔ ∃ (a : _) (h : a ∉ s), s.cons a h ⊆ t := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_ssubset_of_subset (ssubset_cons _) h⟩
obtain ⟨a, hs, ht⟩ := not_subset.1 h.2
exact ⟨a, ht, cons_subset.2 ⟨hs, h.subset⟩⟩
#align finset.ssubset_iff_exists_cons_subset Finset.ssubset_iff_exists_cons_subset
end Cons
/-! ### disjoint -/
section Disjoint
variable {f : α → β} {s t u : Finset α} {a b : α}
theorem disjoint_left : Disjoint s t ↔ ∀ ⦃a⦄, a ∈ s → a ∉ t :=
⟨fun h a hs ht => not_mem_empty a <|
singleton_subset_iff.mp (h (singleton_subset_iff.mpr hs) (singleton_subset_iff.mpr ht)),
fun h _ hs ht _ ha => (h (hs ha) (ht ha)).elim⟩
#align finset.disjoint_left Finset.disjoint_left
theorem disjoint_right : Disjoint s t ↔ ∀ ⦃a⦄, a ∈ t → a ∉ s := by
rw [_root_.disjoint_comm, disjoint_left]
#align finset.disjoint_right Finset.disjoint_right
theorem disjoint_iff_ne : Disjoint s t ↔ ∀ a ∈ s, ∀ b ∈ t, a ≠ b := by
simp only [disjoint_left, imp_not_comm, forall_eq']
#align finset.disjoint_iff_ne Finset.disjoint_iff_ne
@[simp]
theorem disjoint_val : s.1.Disjoint t.1 ↔ Disjoint s t :=
disjoint_left.symm
#align finset.disjoint_val Finset.disjoint_val
theorem _root_.Disjoint.forall_ne_finset (h : Disjoint s t) (ha : a ∈ s) (hb : b ∈ t) : a ≠ b :=
disjoint_iff_ne.1 h _ ha _ hb
#align disjoint.forall_ne_finset Disjoint.forall_ne_finset
theorem not_disjoint_iff : ¬Disjoint s t ↔ ∃ a, a ∈ s ∧ a ∈ t :=
disjoint_left.not.trans <| not_forall.trans <| exists_congr fun _ => by
rw [Classical.not_imp, not_not]
#align finset.not_disjoint_iff Finset.not_disjoint_iff
theorem disjoint_of_subset_left (h : s ⊆ u) (d : Disjoint u t) : Disjoint s t :=
disjoint_left.2 fun _x m₁ => (disjoint_left.1 d) (h m₁)
#align finset.disjoint_of_subset_left Finset.disjoint_of_subset_left
theorem disjoint_of_subset_right (h : t ⊆ u) (d : Disjoint s u) : Disjoint s t :=
disjoint_right.2 fun _x m₁ => (disjoint_right.1 d) (h m₁)
#align finset.disjoint_of_subset_right Finset.disjoint_of_subset_right
@[simp]
theorem disjoint_empty_left (s : Finset α) : Disjoint ∅ s :=
disjoint_bot_left
#align finset.disjoint_empty_left Finset.disjoint_empty_left
@[simp]
theorem disjoint_empty_right (s : Finset α) : Disjoint s ∅ :=
disjoint_bot_right
#align finset.disjoint_empty_right Finset.disjoint_empty_right
@[simp]
theorem disjoint_singleton_left : Disjoint (singleton a) s ↔ a ∉ s := by
simp only [disjoint_left, mem_singleton, forall_eq]
#align finset.disjoint_singleton_left Finset.disjoint_singleton_left
@[simp]
theorem disjoint_singleton_right : Disjoint s (singleton a) ↔ a ∉ s :=
disjoint_comm.trans disjoint_singleton_left
#align finset.disjoint_singleton_right Finset.disjoint_singleton_right
-- Porting note: Left-hand side simplifies @[simp]
theorem disjoint_singleton : Disjoint ({a} : Finset α) {b} ↔ a ≠ b := by
rw [disjoint_singleton_left, mem_singleton]
#align finset.disjoint_singleton Finset.disjoint_singleton
theorem disjoint_self_iff_empty (s : Finset α) : Disjoint s s ↔ s = ∅ :=
disjoint_self
#align finset.disjoint_self_iff_empty Finset.disjoint_self_iff_empty
@[simp, norm_cast]
theorem disjoint_coe : Disjoint (s : Set α) t ↔ Disjoint s t := by
simp only [Finset.disjoint_left, Set.disjoint_left, mem_coe]
#align finset.disjoint_coe Finset.disjoint_coe
@[simp, norm_cast]
theorem pairwiseDisjoint_coe {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint (fun i => f i : ι → Set α) ↔ s.PairwiseDisjoint f :=
forall₅_congr fun _ _ _ _ _ => disjoint_coe
#align finset.pairwise_disjoint_coe Finset.pairwiseDisjoint_coe
end Disjoint
/-! ### disjoint union -/
/-- `disjUnion s t h` is the set such that `a ∈ disjUnion s t h` iff `a ∈ s` or `a ∈ t`.
It is the same as `s ∪ t`, but it does not require decidable equality on the type. The hypothesis
ensures that the sets are disjoint. -/
def disjUnion (s t : Finset α) (h : Disjoint s t) : Finset α :=
⟨s.1 + t.1, Multiset.nodup_add.2 ⟨s.2, t.2, disjoint_val.2 h⟩⟩
#align finset.disj_union Finset.disjUnion
@[simp]
theorem mem_disjUnion {α s t h a} : a ∈ @disjUnion α s t h ↔ a ∈ s ∨ a ∈ t := by
rcases s with ⟨⟨s⟩⟩; rcases t with ⟨⟨t⟩⟩; apply List.mem_append
#align finset.mem_disj_union Finset.mem_disjUnion
@[simp, norm_cast]
theorem coe_disjUnion {s t : Finset α} (h : Disjoint s t) :
(disjUnion s t h : Set α) = (s : Set α) ∪ t :=
Set.ext <| by simp
theorem disjUnion_comm (s t : Finset α) (h : Disjoint s t) :
disjUnion s t h = disjUnion t s h.symm :=
eq_of_veq <| add_comm _ _
#align finset.disj_union_comm Finset.disjUnion_comm
@[simp]
theorem empty_disjUnion (t : Finset α) (h : Disjoint ∅ t := disjoint_bot_left) :
disjUnion ∅ t h = t :=
eq_of_veq <| zero_add _
#align finset.empty_disj_union Finset.empty_disjUnion
@[simp]
theorem disjUnion_empty (s : Finset α) (h : Disjoint s ∅ := disjoint_bot_right) :
disjUnion s ∅ h = s :=
eq_of_veq <| add_zero _
#align finset.disj_union_empty Finset.disjUnion_empty
theorem singleton_disjUnion (a : α) (t : Finset α) (h : Disjoint {a} t) :
disjUnion {a} t h = cons a t (disjoint_singleton_left.mp h) :=
eq_of_veq <| Multiset.singleton_add _ _
#align finset.singleton_disj_union Finset.singleton_disjUnion
theorem disjUnion_singleton (s : Finset α) (a : α) (h : Disjoint s {a}) :
disjUnion s {a} h = cons a s (disjoint_singleton_right.mp h) := by
rw [disjUnion_comm, singleton_disjUnion]
#align finset.disj_union_singleton Finset.disjUnion_singleton
/-! ### insert -/
section Insert
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `insert a s` is the set `{a} ∪ s` containing `a` and the elements of `s`. -/
instance : Insert α (Finset α) :=
⟨fun a s => ⟨_, s.2.ndinsert a⟩⟩
theorem insert_def (a : α) (s : Finset α) : insert a s = ⟨_, s.2.ndinsert a⟩ :=
rfl
#align finset.insert_def Finset.insert_def
@[simp]
theorem insert_val (a : α) (s : Finset α) : (insert a s).1 = ndinsert a s.1 :=
rfl
#align finset.insert_val Finset.insert_val
theorem insert_val' (a : α) (s : Finset α) : (insert a s).1 = dedup (a ::ₘ s.1) := by
rw [dedup_cons, dedup_eq_self]; rfl
#align finset.insert_val' Finset.insert_val'
theorem insert_val_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : (insert a s).1 = a ::ₘ s.1 := by
rw [insert_val, ndinsert_of_not_mem h]
#align finset.insert_val_of_not_mem Finset.insert_val_of_not_mem
@[simp]
theorem mem_insert : a ∈ insert b s ↔ a = b ∨ a ∈ s :=
mem_ndinsert
#align finset.mem_insert Finset.mem_insert
theorem mem_insert_self (a : α) (s : Finset α) : a ∈ insert a s :=
mem_ndinsert_self a s.1
#align finset.mem_insert_self Finset.mem_insert_self
theorem mem_insert_of_mem (h : a ∈ s) : a ∈ insert b s :=
mem_ndinsert_of_mem h
#align finset.mem_insert_of_mem Finset.mem_insert_of_mem
theorem mem_of_mem_insert_of_ne (h : b ∈ insert a s) : b ≠ a → b ∈ s :=
(mem_insert.1 h).resolve_left
#align finset.mem_of_mem_insert_of_ne Finset.mem_of_mem_insert_of_ne
theorem eq_of_not_mem_of_mem_insert (ha : b ∈ insert a s) (hb : b ∉ s) : b = a :=
(mem_insert.1 ha).resolve_right hb
#align finset.eq_of_not_mem_of_mem_insert Finset.eq_of_not_mem_of_mem_insert
/-- A version of `LawfulSingleton.insert_emptyc_eq` that works with `dsimp`. -/
@[simp, nolint simpNF] lemma insert_empty : insert a (∅ : Finset α) = {a} := rfl
@[simp]
theorem cons_eq_insert (a s h) : @cons α a s h = insert a s :=
ext fun a => by simp
#align finset.cons_eq_insert Finset.cons_eq_insert
@[simp, norm_cast]
theorem coe_insert (a : α) (s : Finset α) : ↑(insert a s) = (insert a s : Set α) :=
Set.ext fun x => by simp only [mem_coe, mem_insert, Set.mem_insert_iff]
#align finset.coe_insert Finset.coe_insert
theorem mem_insert_coe {s : Finset α} {x y : α} : x ∈ insert y s ↔ x ∈ insert y (s : Set α) := by
simp
#align finset.mem_insert_coe Finset.mem_insert_coe
instance : LawfulSingleton α (Finset α) :=
⟨fun a => by ext; simp⟩
@[simp]
theorem insert_eq_of_mem (h : a ∈ s) : insert a s = s :=
eq_of_veq <| ndinsert_of_mem h
#align finset.insert_eq_of_mem Finset.insert_eq_of_mem
@[simp]
theorem insert_eq_self : insert a s = s ↔ a ∈ s :=
⟨fun h => h ▸ mem_insert_self _ _, insert_eq_of_mem⟩
#align finset.insert_eq_self Finset.insert_eq_self
theorem insert_ne_self : insert a s ≠ s ↔ a ∉ s :=
insert_eq_self.not
#align finset.insert_ne_self Finset.insert_ne_self
-- Porting note (#10618): @[simp] can prove this
theorem pair_eq_singleton (a : α) : ({a, a} : Finset α) = {a} :=
insert_eq_of_mem <| mem_singleton_self _
#align finset.pair_eq_singleton Finset.pair_eq_singleton
theorem Insert.comm (a b : α) (s : Finset α) : insert a (insert b s) = insert b (insert a s) :=
ext fun x => by simp only [mem_insert, or_left_comm]
#align finset.insert.comm Finset.Insert.comm
-- Porting note (#10618): @[simp] can prove this
@[norm_cast]
theorem coe_pair {a b : α} : (({a, b} : Finset α) : Set α) = {a, b} := by
ext
simp
#align finset.coe_pair Finset.coe_pair
@[simp, norm_cast]
theorem coe_eq_pair {s : Finset α} {a b : α} : (s : Set α) = {a, b} ↔ s = {a, b} := by
rw [← coe_pair, coe_inj]
#align finset.coe_eq_pair Finset.coe_eq_pair
theorem pair_comm (a b : α) : ({a, b} : Finset α) = {b, a} :=
Insert.comm a b ∅
#align finset.pair_comm Finset.pair_comm
-- Porting note (#10618): @[simp] can prove this
theorem insert_idem (a : α) (s : Finset α) : insert a (insert a s) = insert a s :=
ext fun x => by simp only [mem_insert, ← or_assoc, or_self_iff]
#align finset.insert_idem Finset.insert_idem
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem insert_nonempty (a : α) (s : Finset α) : (insert a s).Nonempty :=
⟨a, mem_insert_self a s⟩
#align finset.insert_nonempty Finset.insert_nonempty
@[simp]
theorem insert_ne_empty (a : α) (s : Finset α) : insert a s ≠ ∅ :=
(insert_nonempty a s).ne_empty
#align finset.insert_ne_empty Finset.insert_ne_empty
-- Porting note: explicit universe annotation is no longer required.
instance (i : α) (s : Finset α) : Nonempty ((insert i s : Finset α) : Set α) :=
(Finset.coe_nonempty.mpr (s.insert_nonempty i)).to_subtype
theorem ne_insert_of_not_mem (s t : Finset α) {a : α} (h : a ∉ s) : s ≠ insert a t := by
contrapose! h
simp [h]
#align finset.ne_insert_of_not_mem Finset.ne_insert_of_not_mem
theorem insert_subset_iff : insert a s ⊆ t ↔ a ∈ t ∧ s ⊆ t := by
simp only [subset_iff, mem_insert, forall_eq, or_imp, forall_and]
#align finset.insert_subset Finset.insert_subset_iff
theorem insert_subset (ha : a ∈ t) (hs : s ⊆ t) : insert a s ⊆ t :=
insert_subset_iff.mpr ⟨ha,hs⟩
@[simp] theorem subset_insert (a : α) (s : Finset α) : s ⊆ insert a s := fun _b => mem_insert_of_mem
#align finset.subset_insert Finset.subset_insert
@[gcongr]
theorem insert_subset_insert (a : α) {s t : Finset α} (h : s ⊆ t) : insert a s ⊆ insert a t :=
insert_subset_iff.2 ⟨mem_insert_self _ _, Subset.trans h (subset_insert _ _)⟩
#align finset.insert_subset_insert Finset.insert_subset_insert
@[simp] lemma insert_subset_insert_iff (ha : a ∉ s) : insert a s ⊆ insert a t ↔ s ⊆ t := by
simp_rw [← coe_subset]; simp [-coe_subset, ha]
theorem insert_inj (ha : a ∉ s) : insert a s = insert b s ↔ a = b :=
⟨fun h => eq_of_not_mem_of_mem_insert (h.subst <| mem_insert_self _ _) ha, congr_arg (insert · s)⟩
#align finset.insert_inj Finset.insert_inj
theorem insert_inj_on (s : Finset α) : Set.InjOn (fun a => insert a s) sᶜ := fun _ h _ _ =>
(insert_inj h).1
#align finset.insert_inj_on Finset.insert_inj_on
theorem ssubset_iff : s ⊂ t ↔ ∃ a ∉ s, insert a s ⊆ t := mod_cast @Set.ssubset_iff_insert α s t
#align finset.ssubset_iff Finset.ssubset_iff
theorem ssubset_insert (h : a ∉ s) : s ⊂ insert a s :=
ssubset_iff.mpr ⟨a, h, Subset.rfl⟩
#align finset.ssubset_insert Finset.ssubset_insert
@[elab_as_elim]
theorem cons_induction {α : Type*} {p : Finset α → Prop} (empty : p ∅)
(cons : ∀ (a : α) (s : Finset α) (h : a ∉ s), p s → p (cons a s h)) : ∀ s, p s
| ⟨s, nd⟩ => by
induction s using Multiset.induction with
| empty => exact empty
| cons a s IH =>
rw [mk_cons nd]
exact cons a _ _ (IH _)
#align finset.cons_induction Finset.cons_induction
@[elab_as_elim]
theorem cons_induction_on {α : Type*} {p : Finset α → Prop} (s : Finset α) (h₁ : p ∅)
(h₂ : ∀ ⦃a : α⦄ {s : Finset α} (h : a ∉ s), p s → p (cons a s h)) : p s :=
cons_induction h₁ h₂ s
#align finset.cons_induction_on Finset.cons_induction_on
@[elab_as_elim]
protected theorem induction {α : Type*} {p : Finset α → Prop} [DecidableEq α] (empty : p ∅)
(insert : ∀ ⦃a : α⦄ {s : Finset α}, a ∉ s → p s → p (insert a s)) : ∀ s, p s :=
cons_induction empty fun a s ha => (s.cons_eq_insert a ha).symm ▸ insert ha
#align finset.induction Finset.induction
/-- To prove a proposition about an arbitrary `Finset α`,
it suffices to prove it for the empty `Finset`,
and to show that if it holds for some `Finset α`,
then it holds for the `Finset` obtained by inserting a new element.
-/
@[elab_as_elim]
protected theorem induction_on {α : Type*} {p : Finset α → Prop} [DecidableEq α] (s : Finset α)
(empty : p ∅) (insert : ∀ ⦃a : α⦄ {s : Finset α}, a ∉ s → p s → p (insert a s)) : p s :=
Finset.induction empty insert s
#align finset.induction_on Finset.induction_on
/-- To prove a proposition about `S : Finset α`,
it suffices to prove it for the empty `Finset`,
and to show that if it holds for some `Finset α ⊆ S`,
then it holds for the `Finset` obtained by inserting a new element of `S`.
-/
@[elab_as_elim]
theorem induction_on' {α : Type*} {p : Finset α → Prop} [DecidableEq α] (S : Finset α) (h₁ : p ∅)
(h₂ : ∀ {a s}, a ∈ S → s ⊆ S → a ∉ s → p s → p (insert a s)) : p S :=
@Finset.induction_on α (fun T => T ⊆ S → p T) _ S (fun _ => h₁)
(fun _ _ has hqs hs =>
let ⟨hS, sS⟩ := Finset.insert_subset_iff.1 hs
h₂ hS sS has (hqs sS))
(Finset.Subset.refl S)
#align finset.induction_on' Finset.induction_on'
/-- To prove a proposition about a nonempty `s : Finset α`, it suffices to show it holds for all
singletons and that if it holds for nonempty `t : Finset α`, then it also holds for the `Finset`
obtained by inserting an element in `t`. -/
@[elab_as_elim]
theorem Nonempty.cons_induction {α : Type*} {p : ∀ s : Finset α, s.Nonempty → Prop}
(singleton : ∀ a, p {a} (singleton_nonempty _))
(cons : ∀ a s (h : a ∉ s) (hs), p s hs → p (Finset.cons a s h) (nonempty_cons h))
{s : Finset α} (hs : s.Nonempty) : p s hs := by
induction s using Finset.cons_induction with
| empty => exact (not_nonempty_empty hs).elim
| cons a t ha h =>
obtain rfl | ht := t.eq_empty_or_nonempty
· exact singleton a
· exact cons a t ha ht (h ht)
#align finset.nonempty.cons_induction Finset.Nonempty.cons_induction
lemma Nonempty.exists_cons_eq (hs : s.Nonempty) : ∃ t a ha, cons a t ha = s :=
hs.cons_induction (fun a ↦ ⟨∅, a, _, cons_empty _⟩) fun _ _ _ _ _ ↦ ⟨_, _, _, rfl⟩
/-- Inserting an element to a finite set is equivalent to the option type. -/
def subtypeInsertEquivOption {t : Finset α} {x : α} (h : x ∉ t) :
{ i // i ∈ insert x t } ≃ Option { i // i ∈ t } where
toFun y := if h : ↑y = x then none else some ⟨y, (mem_insert.mp y.2).resolve_left h⟩
invFun y := (y.elim ⟨x, mem_insert_self _ _⟩) fun z => ⟨z, mem_insert_of_mem z.2⟩
left_inv y := by
by_cases h : ↑y = x
· simp only [Subtype.ext_iff, h, Option.elim, dif_pos, Subtype.coe_mk]
· simp only [h, Option.elim, dif_neg, not_false_iff, Subtype.coe_eta, Subtype.coe_mk]
right_inv := by
rintro (_ | y)
· simp only [Option.elim, dif_pos]
· have : ↑y ≠ x := by
rintro ⟨⟩
exact h y.2
simp only [this, Option.elim, Subtype.eta, dif_neg, not_false_iff, Subtype.coe_mk]
#align finset.subtype_insert_equiv_option Finset.subtypeInsertEquivOption
@[simp]
theorem disjoint_insert_left : Disjoint (insert a s) t ↔ a ∉ t ∧ Disjoint s t := by
simp only [disjoint_left, mem_insert, or_imp, forall_and, forall_eq]
#align finset.disjoint_insert_left Finset.disjoint_insert_left
@[simp]
theorem disjoint_insert_right : Disjoint s (insert a t) ↔ a ∉ s ∧ Disjoint s t :=
disjoint_comm.trans <| by rw [disjoint_insert_left, _root_.disjoint_comm]
#align finset.disjoint_insert_right Finset.disjoint_insert_right
end Insert
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-- `s ∪ t` is the set such that `a ∈ s ∪ t` iff `a ∈ s` or `a ∈ t`. -/
instance : Union (Finset α) :=
⟨fun s t => ⟨_, t.2.ndunion s.1⟩⟩
/-- `s ∩ t` is the set such that `a ∈ s ∩ t` iff `a ∈ s` and `a ∈ t`. -/
instance : Inter (Finset α) :=
⟨fun s t => ⟨_, s.2.ndinter t.1⟩⟩
instance : Lattice (Finset α) :=
{ Finset.partialOrder with
sup := (· ∪ ·)
sup_le := fun _ _ _ hs ht _ ha => (mem_ndunion.1 ha).elim (fun h => hs h) fun h => ht h
le_sup_left := fun _ _ _ h => mem_ndunion.2 <| Or.inl h
le_sup_right := fun _ _ _ h => mem_ndunion.2 <| Or.inr h
inf := (· ∩ ·)
le_inf := fun _ _ _ ht hu _ h => mem_ndinter.2 ⟨ht h, hu h⟩
inf_le_left := fun _ _ _ h => (mem_ndinter.1 h).1
inf_le_right := fun _ _ _ h => (mem_ndinter.1 h).2 }
@[simp]
theorem sup_eq_union : (Sup.sup : Finset α → Finset α → Finset α) = Union.union :=
rfl
#align finset.sup_eq_union Finset.sup_eq_union
@[simp]
theorem inf_eq_inter : (Inf.inf : Finset α → Finset α → Finset α) = Inter.inter :=
rfl
#align finset.inf_eq_inter Finset.inf_eq_inter
theorem disjoint_iff_inter_eq_empty : Disjoint s t ↔ s ∩ t = ∅ :=
disjoint_iff
#align finset.disjoint_iff_inter_eq_empty Finset.disjoint_iff_inter_eq_empty
instance decidableDisjoint (U V : Finset α) : Decidable (Disjoint U V) :=
decidable_of_iff _ disjoint_left.symm
#align finset.decidable_disjoint Finset.decidableDisjoint
/-! #### union -/
theorem union_val_nd (s t : Finset α) : (s ∪ t).1 = ndunion s.1 t.1 :=
rfl
#align finset.union_val_nd Finset.union_val_nd
@[simp]
theorem union_val (s t : Finset α) : (s ∪ t).1 = s.1 ∪ t.1 :=
ndunion_eq_union s.2
#align finset.union_val Finset.union_val
@[simp]
theorem mem_union : a ∈ s ∪ t ↔ a ∈ s ∨ a ∈ t :=
mem_ndunion
#align finset.mem_union Finset.mem_union
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
#align finset.disj_union_eq_union Finset.disjUnion_eq_union
theorem mem_union_left (t : Finset α) (h : a ∈ s) : a ∈ s ∪ t :=
mem_union.2 <| Or.inl h
#align finset.mem_union_left Finset.mem_union_left
theorem mem_union_right (s : Finset α) (h : a ∈ t) : a ∈ s ∪ t :=
mem_union.2 <| Or.inr h
#align finset.mem_union_right Finset.mem_union_right
theorem forall_mem_union {p : α → Prop} : (∀ a ∈ s ∪ t, p a) ↔ (∀ a ∈ s, p a) ∧ ∀ a ∈ t, p a :=
⟨fun h => ⟨fun a => h a ∘ mem_union_left _, fun b => h b ∘ mem_union_right _⟩,
fun h _ab hab => (mem_union.mp hab).elim (h.1 _) (h.2 _)⟩
#align finset.forall_mem_union Finset.forall_mem_union
theorem not_mem_union : a ∉ s ∪ t ↔ a ∉ s ∧ a ∉ t := by rw [mem_union, not_or]
#align finset.not_mem_union Finset.not_mem_union
@[simp, norm_cast]
theorem coe_union (s₁ s₂ : Finset α) : ↑(s₁ ∪ s₂) = (s₁ ∪ s₂ : Set α) :=
Set.ext fun _ => mem_union
#align finset.coe_union Finset.coe_union
theorem union_subset (hs : s ⊆ u) : t ⊆ u → s ∪ t ⊆ u :=
sup_le <| le_iff_subset.2 hs
#align finset.union_subset Finset.union_subset
theorem subset_union_left {s₁ s₂ : Finset α} : s₁ ⊆ s₁ ∪ s₂ := fun _x => mem_union_left _
#align finset.subset_union_left Finset.subset_union_left
theorem subset_union_right {s₁ s₂ : Finset α} : s₂ ⊆ s₁ ∪ s₂ := fun _x => mem_union_right _
#align finset.subset_union_right Finset.subset_union_right
@[gcongr]
theorem union_subset_union (hsu : s ⊆ u) (htv : t ⊆ v) : s ∪ t ⊆ u ∪ v :=
sup_le_sup (le_iff_subset.2 hsu) htv
#align finset.union_subset_union Finset.union_subset_union
@[gcongr]
theorem union_subset_union_left (h : s₁ ⊆ s₂) : s₁ ∪ t ⊆ s₂ ∪ t :=
union_subset_union h Subset.rfl
#align finset.union_subset_union_left Finset.union_subset_union_left
@[gcongr]
theorem union_subset_union_right (h : t₁ ⊆ t₂) : s ∪ t₁ ⊆ s ∪ t₂ :=
union_subset_union Subset.rfl h
#align finset.union_subset_union_right Finset.union_subset_union_right
theorem union_comm (s₁ s₂ : Finset α) : s₁ ∪ s₂ = s₂ ∪ s₁ := sup_comm _ _
#align finset.union_comm Finset.union_comm
instance : Std.Commutative (α := Finset α) (· ∪ ·) :=
⟨union_comm⟩
@[simp]
theorem union_assoc (s₁ s₂ s₃ : Finset α) : s₁ ∪ s₂ ∪ s₃ = s₁ ∪ (s₂ ∪ s₃) := sup_assoc _ _ _
#align finset.union_assoc Finset.union_assoc
instance : Std.Associative (α := Finset α) (· ∪ ·) :=
⟨union_assoc⟩
@[simp]
theorem union_idempotent (s : Finset α) : s ∪ s = s := sup_idem _
#align finset.union_idempotent Finset.union_idempotent
instance : Std.IdempotentOp (α := Finset α) (· ∪ ·) :=
⟨union_idempotent⟩
theorem union_subset_left (h : s ∪ t ⊆ u) : s ⊆ u :=
subset_union_left.trans h
#align finset.union_subset_left Finset.union_subset_left
theorem union_subset_right {s t u : Finset α} (h : s ∪ t ⊆ u) : t ⊆ u :=
Subset.trans subset_union_right h
#align finset.union_subset_right Finset.union_subset_right
theorem union_left_comm (s t u : Finset α) : s ∪ (t ∪ u) = t ∪ (s ∪ u) :=
ext fun _ => by simp only [mem_union, or_left_comm]
#align finset.union_left_comm Finset.union_left_comm
theorem union_right_comm (s t u : Finset α) : s ∪ t ∪ u = s ∪ u ∪ t :=
ext fun x => by simp only [mem_union, or_assoc, @or_comm (x ∈ t)]
#align finset.union_right_comm Finset.union_right_comm
theorem union_self (s : Finset α) : s ∪ s = s :=
union_idempotent s
#align finset.union_self Finset.union_self
@[simp]
theorem union_empty (s : Finset α) : s ∪ ∅ = s :=
ext fun x => mem_union.trans <| by simp
#align finset.union_empty Finset.union_empty
@[simp]
theorem empty_union (s : Finset α) : ∅ ∪ s = s :=
ext fun x => mem_union.trans <| by simp
#align finset.empty_union Finset.empty_union
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem Nonempty.inl {s t : Finset α} (h : s.Nonempty) : (s ∪ t).Nonempty :=
h.mono subset_union_left
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem Nonempty.inr {s t : Finset α} (h : t.Nonempty) : (s ∪ t).Nonempty :=
h.mono subset_union_right
theorem insert_eq (a : α) (s : Finset α) : insert a s = {a} ∪ s :=
rfl
#align finset.insert_eq Finset.insert_eq
@[simp]
theorem insert_union (a : α) (s t : Finset α) : insert a s ∪ t = insert a (s ∪ t) := by
simp only [insert_eq, union_assoc]
#align finset.insert_union Finset.insert_union
@[simp]
theorem union_insert (a : α) (s t : Finset α) : s ∪ insert a t = insert a (s ∪ t) := by
simp only [insert_eq, union_left_comm]
#align finset.union_insert Finset.union_insert
theorem insert_union_distrib (a : α) (s t : Finset α) :
insert a (s ∪ t) = insert a s ∪ insert a t := by
simp only [insert_union, union_insert, insert_idem]
#align finset.insert_union_distrib Finset.insert_union_distrib
@[simp] lemma union_eq_left : s ∪ t = s ↔ t ⊆ s := sup_eq_left
#align finset.union_eq_left_iff_subset Finset.union_eq_left
@[simp] lemma left_eq_union : s = s ∪ t ↔ t ⊆ s := by rw [eq_comm, union_eq_left]
#align finset.left_eq_union_iff_subset Finset.left_eq_union
@[simp] lemma union_eq_right : s ∪ t = t ↔ s ⊆ t := sup_eq_right
#align finset.union_eq_right_iff_subset Finset.union_eq_right
@[simp] lemma right_eq_union : s = t ∪ s ↔ t ⊆ s := by rw [eq_comm, union_eq_right]
#align finset.right_eq_union_iff_subset Finset.right_eq_union
-- Porting note: replaced `⊔` in RHS
theorem union_congr_left (ht : t ⊆ s ∪ u) (hu : u ⊆ s ∪ t) : s ∪ t = s ∪ u :=
sup_congr_left ht hu
#align finset.union_congr_left Finset.union_congr_left
theorem union_congr_right (hs : s ⊆ t ∪ u) (ht : t ⊆ s ∪ u) : s ∪ u = t ∪ u :=
sup_congr_right hs ht
#align finset.union_congr_right Finset.union_congr_right
theorem union_eq_union_iff_left : s ∪ t = s ∪ u ↔ t ⊆ s ∪ u ∧ u ⊆ s ∪ t :=
sup_eq_sup_iff_left
#align finset.union_eq_union_iff_left Finset.union_eq_union_iff_left
theorem union_eq_union_iff_right : s ∪ u = t ∪ u ↔ s ⊆ t ∪ u ∧ t ⊆ s ∪ u :=
sup_eq_sup_iff_right
#align finset.union_eq_union_iff_right Finset.union_eq_union_iff_right
@[simp]
theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by
simp only [disjoint_left, mem_union, or_imp, forall_and]
#align finset.disjoint_union_left Finset.disjoint_union_left
@[simp]
theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by
simp only [disjoint_right, mem_union, or_imp, forall_and]
#align finset.disjoint_union_right Finset.disjoint_union_right
/-- To prove a relation on pairs of `Finset X`, it suffices to show that it is
* symmetric,
* it holds when one of the `Finset`s is empty,
* it holds for pairs of singletons,
* if it holds for `[a, c]` and for `[b, c]`, then it holds for `[a ∪ b, c]`.
-/
theorem induction_on_union (P : Finset α → Finset α → Prop) (symm : ∀ {a b}, P a b → P b a)
(empty_right : ∀ {a}, P a ∅) (singletons : ∀ {a b}, P {a} {b})
(union_of : ∀ {a b c}, P a c → P b c → P (a ∪ b) c) : ∀ a b, P a b := by
intro a b
refine Finset.induction_on b empty_right fun x s _xs hi => symm ?_
rw [Finset.insert_eq]
apply union_of _ (symm hi)
refine Finset.induction_on a empty_right fun a t _ta hi => symm ?_
rw [Finset.insert_eq]
exact union_of singletons (symm hi)
#align finset.induction_on_union Finset.induction_on_union
/-! #### inter -/
theorem inter_val_nd (s₁ s₂ : Finset α) : (s₁ ∩ s₂).1 = ndinter s₁.1 s₂.1 :=
rfl
#align finset.inter_val_nd Finset.inter_val_nd
@[simp]
theorem inter_val (s₁ s₂ : Finset α) : (s₁ ∩ s₂).1 = s₁.1 ∩ s₂.1 :=
ndinter_eq_inter s₁.2
#align finset.inter_val Finset.inter_val
@[simp]
theorem mem_inter {a : α} {s₁ s₂ : Finset α} : a ∈ s₁ ∩ s₂ ↔ a ∈ s₁ ∧ a ∈ s₂ :=
mem_ndinter
#align finset.mem_inter Finset.mem_inter
theorem mem_of_mem_inter_left {a : α} {s₁ s₂ : Finset α} (h : a ∈ s₁ ∩ s₂) : a ∈ s₁ :=
(mem_inter.1 h).1
#align finset.mem_of_mem_inter_left Finset.mem_of_mem_inter_left
theorem mem_of_mem_inter_right {a : α} {s₁ s₂ : Finset α} (h : a ∈ s₁ ∩ s₂) : a ∈ s₂ :=
(mem_inter.1 h).2
#align finset.mem_of_mem_inter_right Finset.mem_of_mem_inter_right
theorem mem_inter_of_mem {a : α} {s₁ s₂ : Finset α} : a ∈ s₁ → a ∈ s₂ → a ∈ s₁ ∩ s₂ :=
and_imp.1 mem_inter.2
#align finset.mem_inter_of_mem Finset.mem_inter_of_mem
theorem inter_subset_left {s₁ s₂ : Finset α} : s₁ ∩ s₂ ⊆ s₁ := fun _a => mem_of_mem_inter_left
#align finset.inter_subset_left Finset.inter_subset_left
theorem inter_subset_right {s₁ s₂ : Finset α} : s₁ ∩ s₂ ⊆ s₂ := fun _a => mem_of_mem_inter_right
#align finset.inter_subset_right Finset.inter_subset_right
theorem subset_inter {s₁ s₂ u : Finset α} : s₁ ⊆ s₂ → s₁ ⊆ u → s₁ ⊆ s₂ ∩ u := by
simp (config := { contextual := true }) [subset_iff, mem_inter]
#align finset.subset_inter Finset.subset_inter
@[simp, norm_cast]
theorem coe_inter (s₁ s₂ : Finset α) : ↑(s₁ ∩ s₂) = (s₁ ∩ s₂ : Set α) :=
Set.ext fun _ => mem_inter
#align finset.coe_inter Finset.coe_inter
@[simp]
theorem union_inter_cancel_left {s t : Finset α} : (s ∪ t) ∩ s = s := by
rw [← coe_inj, coe_inter, coe_union, Set.union_inter_cancel_left]
#align finset.union_inter_cancel_left Finset.union_inter_cancel_left
@[simp]
theorem union_inter_cancel_right {s t : Finset α} : (s ∪ t) ∩ t = t := by
rw [← coe_inj, coe_inter, coe_union, Set.union_inter_cancel_right]
#align finset.union_inter_cancel_right Finset.union_inter_cancel_right
theorem inter_comm (s₁ s₂ : Finset α) : s₁ ∩ s₂ = s₂ ∩ s₁ :=
ext fun _ => by simp only [mem_inter, and_comm]
#align finset.inter_comm Finset.inter_comm
@[simp]
theorem inter_assoc (s₁ s₂ s₃ : Finset α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ (s₂ ∩ s₃) :=
ext fun _ => by simp only [mem_inter, and_assoc]
#align finset.inter_assoc Finset.inter_assoc
theorem inter_left_comm (s₁ s₂ s₃ : Finset α) : s₁ ∩ (s₂ ∩ s₃) = s₂ ∩ (s₁ ∩ s₃) :=
ext fun _ => by simp only [mem_inter, and_left_comm]
#align finset.inter_left_comm Finset.inter_left_comm
theorem inter_right_comm (s₁ s₂ s₃ : Finset α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ s₃ ∩ s₂ :=
ext fun _ => by simp only [mem_inter, and_right_comm]
#align finset.inter_right_comm Finset.inter_right_comm
@[simp]
theorem inter_self (s : Finset α) : s ∩ s = s :=
ext fun _ => mem_inter.trans <| and_self_iff
#align finset.inter_self Finset.inter_self
@[simp]
theorem inter_empty (s : Finset α) : s ∩ ∅ = ∅ :=
ext fun _ => mem_inter.trans <| by simp
#align finset.inter_empty Finset.inter_empty
@[simp]
theorem empty_inter (s : Finset α) : ∅ ∩ s = ∅ :=
ext fun _ => mem_inter.trans <| by simp
#align finset.empty_inter Finset.empty_inter
@[simp]
theorem inter_union_self (s t : Finset α) : s ∩ (t ∪ s) = s := by
rw [inter_comm, union_inter_cancel_right]
#align finset.inter_union_self Finset.inter_union_self
@[simp]
theorem insert_inter_of_mem {s₁ s₂ : Finset α} {a : α} (h : a ∈ s₂) :
insert a s₁ ∩ s₂ = insert a (s₁ ∩ s₂) :=
ext fun x => by
have : x = a ∨ x ∈ s₂ ↔ x ∈ s₂ := or_iff_right_of_imp <| by rintro rfl; exact h
simp only [mem_inter, mem_insert, or_and_left, this]
#align finset.insert_inter_of_mem Finset.insert_inter_of_mem
@[simp]
theorem inter_insert_of_mem {s₁ s₂ : Finset α} {a : α} (h : a ∈ s₁) :
s₁ ∩ insert a s₂ = insert a (s₁ ∩ s₂) := by rw [inter_comm, insert_inter_of_mem h, inter_comm]
#align finset.inter_insert_of_mem Finset.inter_insert_of_mem
@[simp]
theorem insert_inter_of_not_mem {s₁ s₂ : Finset α} {a : α} (h : a ∉ s₂) :
insert a s₁ ∩ s₂ = s₁ ∩ s₂ :=
ext fun x => by
have : ¬(x = a ∧ x ∈ s₂) := by rintro ⟨rfl, H⟩; exact h H
simp only [mem_inter, mem_insert, or_and_right, this, false_or_iff]
#align finset.insert_inter_of_not_mem Finset.insert_inter_of_not_mem
@[simp]
theorem inter_insert_of_not_mem {s₁ s₂ : Finset α} {a : α} (h : a ∉ s₁) :
s₁ ∩ insert a s₂ = s₁ ∩ s₂ := by rw [inter_comm, insert_inter_of_not_mem h, inter_comm]
#align finset.inter_insert_of_not_mem Finset.inter_insert_of_not_mem
@[simp]
theorem singleton_inter_of_mem {a : α} {s : Finset α} (H : a ∈ s) : {a} ∩ s = {a} :=
show insert a ∅ ∩ s = insert a ∅ by rw [insert_inter_of_mem H, empty_inter]
#align finset.singleton_inter_of_mem Finset.singleton_inter_of_mem
@[simp]
theorem singleton_inter_of_not_mem {a : α} {s : Finset α} (H : a ∉ s) : {a} ∩ s = ∅ :=
eq_empty_of_forall_not_mem <| by
simp only [mem_inter, mem_singleton]; rintro x ⟨rfl, h⟩; exact H h
#align finset.singleton_inter_of_not_mem Finset.singleton_inter_of_not_mem
@[simp]
theorem inter_singleton_of_mem {a : α} {s : Finset α} (h : a ∈ s) : s ∩ {a} = {a} := by
rw [inter_comm, singleton_inter_of_mem h]
#align finset.inter_singleton_of_mem Finset.inter_singleton_of_mem
@[simp]
theorem inter_singleton_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : s ∩ {a} = ∅ := by
rw [inter_comm, singleton_inter_of_not_mem h]
#align finset.inter_singleton_of_not_mem Finset.inter_singleton_of_not_mem
@[mono, gcongr]
theorem inter_subset_inter {x y s t : Finset α} (h : x ⊆ y) (h' : s ⊆ t) : x ∩ s ⊆ y ∩ t := by
intro a a_in
rw [Finset.mem_inter] at a_in ⊢
exact ⟨h a_in.1, h' a_in.2⟩
#align finset.inter_subset_inter Finset.inter_subset_inter
@[gcongr]
theorem inter_subset_inter_left (h : t ⊆ u) : s ∩ t ⊆ s ∩ u :=
inter_subset_inter Subset.rfl h
#align finset.inter_subset_inter_left Finset.inter_subset_inter_left
@[gcongr]
theorem inter_subset_inter_right (h : s ⊆ t) : s ∩ u ⊆ t ∩ u :=
inter_subset_inter h Subset.rfl
#align finset.inter_subset_inter_right Finset.inter_subset_inter_right
theorem inter_subset_union : s ∩ t ⊆ s ∪ t :=
le_iff_subset.1 inf_le_sup
#align finset.inter_subset_union Finset.inter_subset_union
instance : DistribLattice (Finset α) :=
{ le_sup_inf := fun a b c => by
simp (config := { contextual := true }) only
[sup_eq_union, inf_eq_inter, le_eq_subset, subset_iff, mem_inter, mem_union, and_imp,
or_imp, true_or_iff, imp_true_iff, true_and_iff, or_true_iff] }
@[simp]
theorem union_left_idem (s t : Finset α) : s ∪ (s ∪ t) = s ∪ t := sup_left_idem _ _
#align finset.union_left_idem Finset.union_left_idem
-- Porting note (#10618): @[simp] can prove this
theorem union_right_idem (s t : Finset α) : s ∪ t ∪ t = s ∪ t := sup_right_idem _ _
#align finset.union_right_idem Finset.union_right_idem
@[simp]
theorem inter_left_idem (s t : Finset α) : s ∩ (s ∩ t) = s ∩ t := inf_left_idem _ _
#align finset.inter_left_idem Finset.inter_left_idem
-- Porting note (#10618): @[simp] can prove this
theorem inter_right_idem (s t : Finset α) : s ∩ t ∩ t = s ∩ t := inf_right_idem _ _
#align finset.inter_right_idem Finset.inter_right_idem
theorem inter_union_distrib_left (s t u : Finset α) : s ∩ (t ∪ u) = s ∩ t ∪ s ∩ u :=
inf_sup_left _ _ _
#align finset.inter_distrib_left Finset.inter_union_distrib_left
theorem union_inter_distrib_right (s t u : Finset α) : (s ∪ t) ∩ u = s ∩ u ∪ t ∩ u :=
inf_sup_right _ _ _
#align finset.inter_distrib_right Finset.union_inter_distrib_right
theorem union_inter_distrib_left (s t u : Finset α) : s ∪ t ∩ u = (s ∪ t) ∩ (s ∪ u) :=
sup_inf_left _ _ _
#align finset.union_distrib_left Finset.union_inter_distrib_left
theorem inter_union_distrib_right (s t u : Finset α) : s ∩ t ∪ u = (s ∪ u) ∩ (t ∪ u) :=
sup_inf_right _ _ _
#align finset.union_distrib_right Finset.inter_union_distrib_right
-- 2024-03-22
@[deprecated] alias inter_distrib_left := inter_union_distrib_left
@[deprecated] alias inter_distrib_right := union_inter_distrib_right
@[deprecated] alias union_distrib_left := union_inter_distrib_left
@[deprecated] alias union_distrib_right := inter_union_distrib_right
theorem union_union_distrib_left (s t u : Finset α) : s ∪ (t ∪ u) = s ∪ t ∪ (s ∪ u) :=
sup_sup_distrib_left _ _ _
#align finset.union_union_distrib_left Finset.union_union_distrib_left
theorem union_union_distrib_right (s t u : Finset α) : s ∪ t ∪ u = s ∪ u ∪ (t ∪ u) :=
sup_sup_distrib_right _ _ _
#align finset.union_union_distrib_right Finset.union_union_distrib_right
theorem inter_inter_distrib_left (s t u : Finset α) : s ∩ (t ∩ u) = s ∩ t ∩ (s ∩ u) :=
inf_inf_distrib_left _ _ _
#align finset.inter_inter_distrib_left Finset.inter_inter_distrib_left
theorem inter_inter_distrib_right (s t u : Finset α) : s ∩ t ∩ u = s ∩ u ∩ (t ∩ u) :=
inf_inf_distrib_right _ _ _
#align finset.inter_inter_distrib_right Finset.inter_inter_distrib_right
theorem union_union_union_comm (s t u v : Finset α) : s ∪ t ∪ (u ∪ v) = s ∪ u ∪ (t ∪ v) :=
sup_sup_sup_comm _ _ _ _
#align finset.union_union_union_comm Finset.union_union_union_comm
theorem inter_inter_inter_comm (s t u v : Finset α) : s ∩ t ∩ (u ∩ v) = s ∩ u ∩ (t ∩ v) :=
inf_inf_inf_comm _ _ _ _
#align finset.inter_inter_inter_comm Finset.inter_inter_inter_comm
lemma union_eq_empty : s ∪ t = ∅ ↔ s = ∅ ∧ t = ∅ := sup_eq_bot_iff
#align finset.union_eq_empty_iff Finset.union_eq_empty
theorem union_subset_iff : s ∪ t ⊆ u ↔ s ⊆ u ∧ t ⊆ u :=
(sup_le_iff : s ⊔ t ≤ u ↔ s ≤ u ∧ t ≤ u)
#align finset.union_subset_iff Finset.union_subset_iff
theorem subset_inter_iff : s ⊆ t ∩ u ↔ s ⊆ t ∧ s ⊆ u :=
(le_inf_iff : s ≤ t ⊓ u ↔ s ≤ t ∧ s ≤ u)
#align finset.subset_inter_iff Finset.subset_inter_iff
@[simp] lemma inter_eq_left : s ∩ t = s ↔ s ⊆ t := inf_eq_left
#align finset.inter_eq_left_iff_subset_iff_subset Finset.inter_eq_left
@[simp] lemma inter_eq_right : t ∩ s = s ↔ s ⊆ t := inf_eq_right
#align finset.inter_eq_right_iff_subset Finset.inter_eq_right
theorem inter_congr_left (ht : s ∩ u ⊆ t) (hu : s ∩ t ⊆ u) : s ∩ t = s ∩ u :=
inf_congr_left ht hu
#align finset.inter_congr_left Finset.inter_congr_left
theorem inter_congr_right (hs : t ∩ u ⊆ s) (ht : s ∩ u ⊆ t) : s ∩ u = t ∩ u :=
inf_congr_right hs ht
#align finset.inter_congr_right Finset.inter_congr_right
theorem inter_eq_inter_iff_left : s ∩ t = s ∩ u ↔ s ∩ u ⊆ t ∧ s ∩ t ⊆ u :=
inf_eq_inf_iff_left
#align finset.inter_eq_inter_iff_left Finset.inter_eq_inter_iff_left
theorem inter_eq_inter_iff_right : s ∩ u = t ∩ u ↔ t ∩ u ⊆ s ∧ s ∩ u ⊆ t :=
inf_eq_inf_iff_right
#align finset.inter_eq_inter_iff_right Finset.inter_eq_inter_iff_right
theorem ite_subset_union (s s' : Finset α) (P : Prop) [Decidable P] : ite P s s' ⊆ s ∪ s' :=
ite_le_sup s s' P
#align finset.ite_subset_union Finset.ite_subset_union
theorem inter_subset_ite (s s' : Finset α) (P : Prop) [Decidable P] : s ∩ s' ⊆ ite P s s' :=
inf_le_ite s s' P
#align finset.inter_subset_ite Finset.inter_subset_ite
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
#align finset.not_disjoint_iff_nonempty_inter Finset.not_disjoint_iff_nonempty_inter
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
#align finset.nonempty.not_disjoint Finset.Nonempty.not_disjoint
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
#align finset.disjoint_or_nonempty_inter Finset.disjoint_or_nonempty_inter
end Lattice
instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance
instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le
/-! ### erase -/
section Erase
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `erase s a` is the set `s - {a}`, that is, the elements of `s` which are
not equal to `a`. -/
def erase (s : Finset α) (a : α) : Finset α :=
⟨_, s.2.erase a⟩
#align finset.erase Finset.erase
@[simp]
theorem erase_val (s : Finset α) (a : α) : (erase s a).1 = s.1.erase a :=
rfl
#align finset.erase_val Finset.erase_val
@[simp]
theorem mem_erase {a b : α} {s : Finset α} : a ∈ erase s b ↔ a ≠ b ∧ a ∈ s :=
s.2.mem_erase_iff
#align finset.mem_erase Finset.mem_erase
theorem not_mem_erase (a : α) (s : Finset α) : a ∉ erase s a :=
s.2.not_mem_erase
#align finset.not_mem_erase Finset.not_mem_erase
-- While this can be solved by `simp`, this lemma is eligible for `dsimp`
@[nolint simpNF, simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
#align finset.erase_empty Finset.erase_empty
protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty :=
(hs.exists_ne a).imp $ by aesop
@[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by
simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)]
refine ⟨?_, fun hs ↦ hs.exists_ne a⟩
rintro ⟨b, hb, hba⟩
exact ⟨_, hb, _, ha, hba⟩
@[simp]
theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by
ext x
simp
#align finset.erase_singleton Finset.erase_singleton
theorem ne_of_mem_erase : b ∈ erase s a → b ≠ a := fun h => (mem_erase.1 h).1
#align finset.ne_of_mem_erase Finset.ne_of_mem_erase
theorem mem_of_mem_erase : b ∈ erase s a → b ∈ s :=
Multiset.mem_of_mem_erase
#align finset.mem_of_mem_erase Finset.mem_of_mem_erase
theorem mem_erase_of_ne_of_mem : a ≠ b → a ∈ s → a ∈ erase s b := by
simp only [mem_erase]; exact And.intro
#align finset.mem_erase_of_ne_of_mem Finset.mem_erase_of_ne_of_mem
/-- An element of `s` that is not an element of `erase s a` must be`a`. -/
theorem eq_of_mem_of_not_mem_erase (hs : b ∈ s) (hsa : b ∉ s.erase a) : b = a := by
rw [mem_erase, not_and] at hsa
exact not_imp_not.mp hsa hs
#align finset.eq_of_mem_of_not_mem_erase Finset.eq_of_mem_of_not_mem_erase
@[simp]
theorem erase_eq_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : erase s a = s :=
eq_of_veq <| erase_of_not_mem h
#align finset.erase_eq_of_not_mem Finset.erase_eq_of_not_mem
@[simp]
theorem erase_eq_self : s.erase a = s ↔ a ∉ s :=
⟨fun h => h ▸ not_mem_erase _ _, erase_eq_of_not_mem⟩
#align finset.erase_eq_self Finset.erase_eq_self
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp (config := { contextual := true }) only [mem_erase, mem_insert, and_congr_right_iff,
false_or_iff, iff_self_iff, imp_true_iff]
#align finset.erase_insert_eq_erase Finset.erase_insert_eq_erase
theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by
rw [erase_insert_eq_erase, erase_eq_of_not_mem h]
#align finset.erase_insert Finset.erase_insert
theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) :
erase (insert a s) b = insert a (erase s b) :=
ext fun x => by
have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h
simp only [mem_erase, mem_insert, and_or_left, this]
#align finset.erase_insert_of_ne Finset.erase_insert_of_ne
theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) :
erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by
simp only [cons_eq_insert, erase_insert_of_ne hb]
#align finset.erase_cons_of_ne Finset.erase_cons_of_ne
@[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s :=
ext fun x => by
simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and_iff]
apply or_iff_right_of_imp
rintro rfl
exact h
#align finset.insert_erase Finset.insert_erase
lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by
aesop
lemma insert_erase_invOn :
Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} :=
⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩
theorem erase_subset_erase (a : α) {s t : Finset α} (h : s ⊆ t) : erase s a ⊆ erase t a :=
val_le_iff.1 <| erase_le_erase _ <| val_le_iff.2 h
#align finset.erase_subset_erase Finset.erase_subset_erase
theorem erase_subset (a : α) (s : Finset α) : erase s a ⊆ s :=
Multiset.erase_subset _ _
#align finset.erase_subset Finset.erase_subset
theorem subset_erase {a : α} {s t : Finset α} : s ⊆ t.erase a ↔ s ⊆ t ∧ a ∉ s :=
⟨fun h => ⟨h.trans (erase_subset _ _), fun ha => not_mem_erase _ _ (h ha)⟩,
fun h _b hb => mem_erase.2 ⟨ne_of_mem_of_not_mem hb h.2, h.1 hb⟩⟩
#align finset.subset_erase Finset.subset_erase
@[simp, norm_cast]
theorem coe_erase (a : α) (s : Finset α) : ↑(erase s a) = (s \ {a} : Set α) :=
Set.ext fun _ => mem_erase.trans <| by rw [and_comm, Set.mem_diff, Set.mem_singleton_iff, mem_coe]
#align finset.coe_erase Finset.coe_erase
theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s :=
calc
s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _
_ = _ := insert_erase h
#align finset.erase_ssubset Finset.erase_ssubset
theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩
obtain ⟨a, ht, hs⟩ := not_subset.1 h.2
exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩
#align finset.ssubset_iff_exists_subset_erase Finset.ssubset_iff_exists_subset_erase
theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s :=
ssubset_iff_exists_subset_erase.2
⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩
#align finset.erase_ssubset_insert Finset.erase_ssubset_insert
theorem erase_ne_self : s.erase a ≠ s ↔ a ∈ s :=
erase_eq_self.not_left
#align finset.erase_ne_self Finset.erase_ne_self
theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by
rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h]
#align finset.erase_cons Finset.erase_cons
theorem erase_idem {a : α} {s : Finset α} : erase (erase s a) a = erase s a := by simp
#align finset.erase_idem Finset.erase_idem
| Mathlib/Data/Finset/Basic.lean | 2,036 | 2,039 | theorem erase_right_comm {a b : α} {s : Finset α} : erase (erase s a) b = erase (erase s b) a := by |
ext x
simp only [mem_erase, ← and_assoc]
rw [@and_comm (x ≠ a)]
|
/-
Copyright (c) 2021 Frédéric Dupuis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Frédéric Dupuis
-/
import Mathlib.Analysis.Normed.Group.Hom
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Analysis.NormedSpace.LinearIsometry
import Mathlib.Algebra.Star.SelfAdjoint
import Mathlib.Algebra.Star.Subalgebra
import Mathlib.Algebra.Star.Unitary
import Mathlib.Topology.Algebra.Module.Star
#align_import analysis.normed_space.star.basic from "leanprover-community/mathlib"@"aa6669832974f87406a3d9d70fc5707a60546207"
/-!
# Normed star rings and algebras
A normed star group is a normed group with a compatible `star` which is isometric.
A C⋆-ring is a normed star group that is also a ring and that verifies the stronger
condition `‖x⋆ * x‖ = ‖x‖^2` for all `x`. If a C⋆-ring is also a star algebra, then it is a
C⋆-algebra.
To get a C⋆-algebra `E` over field `𝕜`, use
`[NormedField 𝕜] [StarRing 𝕜] [NormedRing E] [StarRing E] [CstarRing E]
[NormedAlgebra 𝕜 E] [StarModule 𝕜 E]`.
## TODO
- Show that `‖x⋆ * x‖ = ‖x‖^2` is equivalent to `‖x⋆ * x‖ = ‖x⋆‖ * ‖x‖`, which is used as the
definition of C*-algebras in some sources (e.g. Wikipedia).
-/
open Topology
local postfix:max "⋆" => star
/-- A normed star group is a normed group with a compatible `star` which is isometric. -/
class NormedStarGroup (E : Type*) [SeminormedAddCommGroup E] [StarAddMonoid E] : Prop where
norm_star : ∀ x : E, ‖x⋆‖ = ‖x‖
#align normed_star_group NormedStarGroup
export NormedStarGroup (norm_star)
attribute [simp] norm_star
variable {𝕜 E α : Type*}
section NormedStarGroup
variable [SeminormedAddCommGroup E] [StarAddMonoid E] [NormedStarGroup E]
@[simp]
theorem nnnorm_star (x : E) : ‖star x‖₊ = ‖x‖₊ :=
Subtype.ext <| norm_star _
#align nnnorm_star nnnorm_star
/-- The `star` map in a normed star group is a normed group homomorphism. -/
def starNormedAddGroupHom : NormedAddGroupHom E E :=
{ starAddEquiv with bound' := ⟨1, fun _ => le_trans (norm_star _).le (one_mul _).symm.le⟩ }
#align star_normed_add_group_hom starNormedAddGroupHom
/-- The `star` map in a normed star group is an isometry -/
theorem star_isometry : Isometry (star : E → E) :=
show Isometry starAddEquiv from
AddMonoidHomClass.isometry_of_norm starAddEquiv (show ∀ x, ‖x⋆‖ = ‖x‖ from norm_star)
#align star_isometry star_isometry
instance (priority := 100) NormedStarGroup.to_continuousStar : ContinuousStar E :=
⟨star_isometry.continuous⟩
#align normed_star_group.to_has_continuous_star NormedStarGroup.to_continuousStar
end NormedStarGroup
instance RingHomIsometric.starRingEnd [NormedCommRing E] [StarRing E] [NormedStarGroup E] :
RingHomIsometric (starRingEnd E) :=
⟨@norm_star _ _ _ _⟩
#align ring_hom_isometric.star_ring_end RingHomIsometric.starRingEnd
/-- A C*-ring is a normed star ring that satisfies the stronger condition `‖x⋆ * x‖ = ‖x‖^2`
for every `x`. -/
class CstarRing (E : Type*) [NonUnitalNormedRing E] [StarRing E] : Prop where
norm_star_mul_self : ∀ {x : E}, ‖x⋆ * x‖ = ‖x‖ * ‖x‖
#align cstar_ring CstarRing
instance : CstarRing ℝ where norm_star_mul_self {x} := by simp only [star, id, norm_mul]
namespace CstarRing
section NonUnital
variable [NonUnitalNormedRing E] [StarRing E] [CstarRing E]
-- see Note [lower instance priority]
/-- In a C*-ring, star preserves the norm. -/
instance (priority := 100) to_normedStarGroup : NormedStarGroup E :=
⟨by
intro x
by_cases htriv : x = 0
· simp only [htriv, star_zero]
· have hnt : 0 < ‖x‖ := norm_pos_iff.mpr htriv
have hnt_star : 0 < ‖x⋆‖ :=
norm_pos_iff.mpr ((AddEquiv.map_ne_zero_iff starAddEquiv (M := E)).mpr htriv)
have h₁ :=
calc
‖x‖ * ‖x‖ = ‖x⋆ * x‖ := norm_star_mul_self.symm
_ ≤ ‖x⋆‖ * ‖x‖ := norm_mul_le _ _
have h₂ :=
calc
‖x⋆‖ * ‖x⋆‖ = ‖x * x⋆‖ := by rw [← norm_star_mul_self, star_star]
_ ≤ ‖x‖ * ‖x⋆‖ := norm_mul_le _ _
exact le_antisymm (le_of_mul_le_mul_right h₂ hnt_star) (le_of_mul_le_mul_right h₁ hnt)⟩
#align cstar_ring.to_normed_star_group CstarRing.to_normedStarGroup
theorem norm_self_mul_star {x : E} : ‖x * x⋆‖ = ‖x‖ * ‖x‖ := by
nth_rw 1 [← star_star x]
simp only [norm_star_mul_self, norm_star]
#align cstar_ring.norm_self_mul_star CstarRing.norm_self_mul_star
theorem norm_star_mul_self' {x : E} : ‖x⋆ * x‖ = ‖x⋆‖ * ‖x‖ := by rw [norm_star_mul_self, norm_star]
#align cstar_ring.norm_star_mul_self' CstarRing.norm_star_mul_self'
theorem nnnorm_self_mul_star {x : E} : ‖x * x⋆‖₊ = ‖x‖₊ * ‖x‖₊ :=
Subtype.ext norm_self_mul_star
#align cstar_ring.nnnorm_self_mul_star CstarRing.nnnorm_self_mul_star
theorem nnnorm_star_mul_self {x : E} : ‖x⋆ * x‖₊ = ‖x‖₊ * ‖x‖₊ :=
Subtype.ext norm_star_mul_self
#align cstar_ring.nnnorm_star_mul_self CstarRing.nnnorm_star_mul_self
@[simp]
theorem star_mul_self_eq_zero_iff (x : E) : x⋆ * x = 0 ↔ x = 0 := by
rw [← norm_eq_zero, norm_star_mul_self]
exact mul_self_eq_zero.trans norm_eq_zero
#align cstar_ring.star_mul_self_eq_zero_iff CstarRing.star_mul_self_eq_zero_iff
theorem star_mul_self_ne_zero_iff (x : E) : x⋆ * x ≠ 0 ↔ x ≠ 0 := by
simp only [Ne, star_mul_self_eq_zero_iff]
#align cstar_ring.star_mul_self_ne_zero_iff CstarRing.star_mul_self_ne_zero_iff
@[simp]
theorem mul_star_self_eq_zero_iff (x : E) : x * x⋆ = 0 ↔ x = 0 := by
simpa only [star_eq_zero, star_star] using @star_mul_self_eq_zero_iff _ _ _ _ (star x)
#align cstar_ring.mul_star_self_eq_zero_iff CstarRing.mul_star_self_eq_zero_iff
theorem mul_star_self_ne_zero_iff (x : E) : x * x⋆ ≠ 0 ↔ x ≠ 0 := by
simp only [Ne, mul_star_self_eq_zero_iff]
#align cstar_ring.mul_star_self_ne_zero_iff CstarRing.mul_star_self_ne_zero_iff
end NonUnital
section ProdPi
variable {ι R₁ R₂ : Type*} {R : ι → Type*}
variable [NonUnitalNormedRing R₁] [StarRing R₁] [CstarRing R₁]
variable [NonUnitalNormedRing R₂] [StarRing R₂] [CstarRing R₂]
variable [∀ i, NonUnitalNormedRing (R i)] [∀ i, StarRing (R i)]
/-- This instance exists to short circuit type class resolution because of problems with
inference involving Π-types. -/
instance _root_.Pi.starRing' : StarRing (∀ i, R i) :=
inferInstance
#align pi.star_ring' Pi.starRing'
variable [Fintype ι] [∀ i, CstarRing (R i)]
instance _root_.Prod.cstarRing : CstarRing (R₁ × R₂) where
norm_star_mul_self {x} := by
dsimp only [norm]
simp only [Prod.fst_mul, Prod.fst_star, Prod.snd_mul, Prod.snd_star, norm_star_mul_self, ← sq]
refine le_antisymm ?_ ?_
· refine max_le ?_ ?_ <;> rw [sq_le_sq, abs_of_nonneg (norm_nonneg _)]
· exact (le_max_left _ _).trans (le_abs_self _)
· exact (le_max_right _ _).trans (le_abs_self _)
· rw [le_sup_iff]
rcases le_total ‖x.fst‖ ‖x.snd‖ with (h | h) <;> simp [h]
#align prod.cstar_ring Prod.cstarRing
instance _root_.Pi.cstarRing : CstarRing (∀ i, R i) where
norm_star_mul_self {x} := by
simp only [norm, Pi.mul_apply, Pi.star_apply, nnnorm_star_mul_self, ← sq]
norm_cast
exact
(Finset.comp_sup_eq_sup_comp_of_is_total (fun x : NNReal => x ^ 2)
(fun x y h => by simpa only [sq] using mul_le_mul' h h) (by simp)).symm
#align pi.cstar_ring Pi.cstarRing
instance _root_.Pi.cstarRing' : CstarRing (ι → R₁) :=
Pi.cstarRing
#align pi.cstar_ring' Pi.cstarRing'
end ProdPi
section Unital
variable [NormedRing E] [StarRing E] [CstarRing E]
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem norm_one [Nontrivial E] : ‖(1 : E)‖ = 1 := by
have : 0 < ‖(1 : E)‖ := norm_pos_iff.mpr one_ne_zero
rw [← mul_left_inj' this.ne', ← norm_star_mul_self, mul_one, star_one, one_mul]
#align cstar_ring.norm_one CstarRing.norm_one
-- see Note [lower instance priority]
instance (priority := 100) [Nontrivial E] : NormOneClass E :=
⟨norm_one⟩
theorem norm_coe_unitary [Nontrivial E] (U : unitary E) : ‖(U : E)‖ = 1 := by
rw [← sq_eq_sq (norm_nonneg _) zero_le_one, one_pow 2, sq, ← CstarRing.norm_star_mul_self,
unitary.coe_star_mul_self, CstarRing.norm_one]
#align cstar_ring.norm_coe_unitary CstarRing.norm_coe_unitary
@[simp]
theorem norm_of_mem_unitary [Nontrivial E] {U : E} (hU : U ∈ unitary E) : ‖U‖ = 1 :=
norm_coe_unitary ⟨U, hU⟩
#align cstar_ring.norm_of_mem_unitary CstarRing.norm_of_mem_unitary
@[simp]
theorem norm_coe_unitary_mul (U : unitary E) (A : E) : ‖(U : E) * A‖ = ‖A‖ := by
nontriviality E
refine le_antisymm ?_ ?_
· calc
_ ≤ ‖(U : E)‖ * ‖A‖ := norm_mul_le _ _
_ = ‖A‖ := by rw [norm_coe_unitary, one_mul]
· calc
_ = ‖(U : E)⋆ * U * A‖ := by rw [unitary.coe_star_mul_self U, one_mul]
_ ≤ ‖(U : E)⋆‖ * ‖(U : E) * A‖ := by
rw [mul_assoc]
exact norm_mul_le _ _
_ = ‖(U : E) * A‖ := by rw [norm_star, norm_coe_unitary, one_mul]
#align cstar_ring.norm_coe_unitary_mul CstarRing.norm_coe_unitary_mul
@[simp]
theorem norm_unitary_smul (U : unitary E) (A : E) : ‖U • A‖ = ‖A‖ :=
norm_coe_unitary_mul U A
#align cstar_ring.norm_unitary_smul CstarRing.norm_unitary_smul
theorem norm_mem_unitary_mul {U : E} (A : E) (hU : U ∈ unitary E) : ‖U * A‖ = ‖A‖ :=
norm_coe_unitary_mul ⟨U, hU⟩ A
#align cstar_ring.norm_mem_unitary_mul CstarRing.norm_mem_unitary_mul
@[simp]
| Mathlib/Analysis/NormedSpace/Star/Basic.lean | 247 | 252 | theorem norm_mul_coe_unitary (A : E) (U : unitary E) : ‖A * U‖ = ‖A‖ :=
calc
_ = ‖((U : E)⋆ * A⋆)⋆‖ := by | simp only [star_star, star_mul]
_ = ‖(U : E)⋆ * A⋆‖ := by rw [norm_star]
_ = ‖A⋆‖ := norm_mem_unitary_mul (star A) (unitary.star_mem U.prop)
_ = ‖A‖ := norm_star _
|
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