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/-
Copyright (c) 2024 Jz Pan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jz Pan
-/
import Mathlib.FieldTheory.SeparableClosure
import Mathlib.Algebra.CharP.IntermediateField
/-!
# Purely inseparable extension and relative perfect closure
This file contains basics about purely inseparable extensions and the relative perfect closure
of fields.
## Main definitions
- `IsPurelyInseparable`: typeclass for purely inseparable field extensions: an algebraic extension
`E / F` is purely inseparable if and only if the minimal polynomial of every element of `E ∖ F`
is not separable.
- `perfectClosure`: the relative perfect closure of `F` in `E`, it consists of the elements
`x` of `E` such that there exists a natural number `n` such that `x ^ (ringExpChar F) ^ n`
is contained in `F`, where `ringExpChar F` is the exponential characteristic of `F`.
It is also the maximal purely inseparable subextension of `E / F` (`le_perfectClosure_iff`).
## Main results
- `IsPurelyInseparable.surjective_algebraMap_of_isSeparable`,
`IsPurelyInseparable.bijective_algebraMap_of_isSeparable`,
`IntermediateField.eq_bot_of_isPurelyInseparable_of_isSeparable`:
if `E / F` is both purely inseparable and separable, then `algebraMap F E` is surjective
(hence bijective). In particular, if an intermediate field of `E / F` is both purely inseparable
and separable, then it is equal to `F`.
- `isPurelyInseparable_iff_pow_mem`: a field extension `E / F` of exponential characteristic `q` is
purely inseparable if and only if for every element `x` of `E`, there exists a natural number `n`
such that `x ^ (q ^ n)` is contained in `F`.
- `IsPurelyInseparable.trans`: if `E / F` and `K / E` are both purely inseparable extensions, then
`K / F` is also purely inseparable.
- `isPurelyInseparable_iff_natSepDegree_eq_one`: `E / F` is purely inseparable if and only if for
every element `x` of `E`, its minimal polynomial has separable degree one.
- `isPurelyInseparable_iff_minpoly_eq_X_pow_sub_C`: a field extension `E / F` of exponential
characteristic `q` is purely inseparable if and only if for every element `x` of `E`, the minimal
polynomial of `x` over `F` is of form `X ^ (q ^ n) - y` for some natural number `n` and some
element `y` of `F`.
- `isPurelyInseparable_iff_minpoly_eq_X_sub_C_pow`: a field extension `E / F` of exponential
characteristic `q` is purely inseparable if and only if for every element `x` of `E`, the minimal
polynomial of `x` over `F` is of form `(X - x) ^ (q ^ n)` for some natural number `n`.
- `isPurelyInseparable_iff_finSepDegree_eq_one`: an algebraic extension is purely inseparable
if and only if it has finite separable degree (`Field.finSepDegree`) one.
**TODO:** remove the algebraic assumption.
- `IsPurelyInseparable.normal`: a purely inseparable extension is normal.
- `separableClosure.isPurelyInseparable`: if `E / F` is algebraic, then `E` is purely inseparable
over the separable closure of `F` in `E`.
- `separableClosure_le_iff`: if `E / F` is algebraic, then an intermediate field of `E / F` contains
the separable closure of `F` in `E` if and only if `E` is purely inseparable over it.
- `eq_separableClosure_iff`: if `E / F` is algebraic, then an intermediate field of `E / F` is equal
to the separable closure of `F` in `E` if and only if it is separable over `F`, and `E`
is purely inseparable over it.
- `le_perfectClosure_iff`: an intermediate field of `E / F` is contained in the relative perfect
closure of `F` in `E` if and only if it is purely inseparable over `F`.
- `perfectClosure.perfectRing`, `perfectClosure.perfectField`: if `E` is a perfect field, then the
(relative) perfect closure `perfectClosure F E` is perfect.
- `IsPurelyInseparable.injective_comp_algebraMap`: if `E / F` is purely inseparable, then for any
reduced ring `L`, the map `(E →+* L) → (F →+* L)` induced by `algebraMap F E` is injective.
In particular, a purely inseparable field extension is an epimorphism in the category of fields.
- `IntermediateField.isPurelyInseparable_adjoin_iff_pow_mem`: if `F` is of exponential
characteristic `q`, then `F(S) / F` is a purely inseparable extension if and only if for any
`x ∈ S`, `x ^ (q ^ n)` is contained in `F` for some `n : ℕ`.
- `Field.finSepDegree_eq`: if `E / F` is algebraic, then the `Field.finSepDegree F E` is equal to
`Field.sepDegree F E` as a natural number. This means that the cardinality of `Field.Emb F E`
and the degree of `(separableClosure F E) / F` are both finite or infinite, and when they are
finite, they coincide.
- `Field.finSepDegree_mul_finInsepDegree`: the finite separable degree multiply by the finite
inseparable degree is equal to the (finite) field extension degree.
- `Field.lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic`: the separable degrees satisfy the
tower law: $[E:F]_s [K:E]_s = [K:F]_s$.
- `IntermediateField.sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable`,
`IntermediateField.sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable'`:
if `K / E / F` is a field extension tower, such that `E / F` is purely inseparable, then
for any subset `S` of `K` such that `F(S) / F` is algebraic, the `E(S) / E` and `F(S) / F` have
the same separable degree. In particular, if `S` is an intermediate field of `K / F` such that
`S / F` is algebraic, the `E(S) / E` and `S / F` have the same separable degree.
- `minpoly.map_eq_of_separable_of_isPurelyInseparable`: if `K / E / F` is a field extension tower,
such that `E / F` is purely inseparable, then for any element `x` of `K` separable over `F`,
it has the same minimal polynomials over `F` and over `E`.
- `Polynomial.Separable.map_irreducible_of_isPurelyInseparable`: if `E / F` is purely inseparable,
`f` is a separable irreducible polynomial over `F`, then it is also irreducible over `E`.
## Tags
separable degree, degree, separable closure, purely inseparable
## TODO
- `IsPurelyInseparable.of_injective_comp_algebraMap`: if `L` is an algebraically closed field
containing `E`, such that the map `(E →+* L) → (F →+* L)` induced by `algebraMap F E` is
injective, then `E / F` is purely inseparable. As a corollary, epimorphisms in the category of
fields must be purely inseparable extensions. Need to use the fact that `Emb F E` is infinite
(or just not a singleton) when `E / F` is (purely) transcendental.
- Restate some intermediate result in terms of linearly disjointness.
- Prove that the inseparable degrees satisfy the tower law: $[E:F]_i [K:E]_i = [K:F]_i$.
Probably an argument using linearly disjointness is needed.
-/
open FiniteDimensional Polynomial IntermediateField Field
noncomputable section
universe u v w
variable (F : Type u) (E : Type v) [Field F] [Field E] [Algebra F E]
variable (K : Type w) [Field K] [Algebra F K]
section IsPurelyInseparable
/-- Typeclass for purely inseparable field extensions: an algebraic extension `E / F` is purely
inseparable if and only if the minimal polynomial of every element of `E ∖ F` is not separable. -/
class IsPurelyInseparable : Prop where
isIntegral : Algebra.IsIntegral F E
inseparable' (x : E) : (minpoly F x).Separable → x ∈ (algebraMap F E).range
attribute [instance] IsPurelyInseparable.isIntegral
variable {E} in
theorem IsPurelyInseparable.isIntegral' [IsPurelyInseparable F E] (x : E) : IsIntegral F x :=
Algebra.IsIntegral.isIntegral _
theorem IsPurelyInseparable.isAlgebraic [IsPurelyInseparable F E] :
Algebra.IsAlgebraic F E := inferInstance
variable {E}
theorem IsPurelyInseparable.inseparable [IsPurelyInseparable F E] :
∀ x : E, (minpoly F x).Separable → x ∈ (algebraMap F E).range :=
IsPurelyInseparable.inseparable'
variable {F K}
theorem isPurelyInseparable_iff : IsPurelyInseparable F E ↔ ∀ x : E,
IsIntegral F x ∧ ((minpoly F x).Separable → x ∈ (algebraMap F E).range) :=
⟨fun h x ↦ ⟨h.isIntegral' x, h.inseparable' x⟩, fun h ↦ ⟨⟨fun x ↦ (h x).1⟩, fun x ↦ (h x).2⟩⟩
/-- Transfer `IsPurelyInseparable` across an `AlgEquiv`. -/
theorem AlgEquiv.isPurelyInseparable (e : K ≃ₐ[F] E) [IsPurelyInseparable F K] :
IsPurelyInseparable F E := by
refine ⟨⟨fun _ ↦ by rw [← isIntegral_algEquiv e.symm]; exact IsPurelyInseparable.isIntegral' F _⟩,
fun x h ↦ ?_⟩
rw [← minpoly.algEquiv_eq e.symm] at h
simpa only [RingHom.mem_range, algebraMap_eq_apply] using IsPurelyInseparable.inseparable F _ h
theorem AlgEquiv.isPurelyInseparable_iff (e : K ≃ₐ[F] E) :
IsPurelyInseparable F K ↔ IsPurelyInseparable F E :=
⟨fun _ ↦ e.isPurelyInseparable, fun _ ↦ e.symm.isPurelyInseparable⟩
/-- If `E / F` is an algebraic extension, `F` is separably closed,
then `E / F` is purely inseparable. -/
theorem Algebra.IsAlgebraic.isPurelyInseparable_of_isSepClosed [Algebra.IsAlgebraic F E]
[IsSepClosed F] : IsPurelyInseparable F E :=
⟨inferInstance, fun x h ↦ minpoly.mem_range_of_degree_eq_one F x <|
IsSepClosed.degree_eq_one_of_irreducible F (minpoly.irreducible
(Algebra.IsIntegral.isIntegral _)) h⟩
variable (F E K)
/-- If `E / F` is both purely inseparable and separable, then `algebraMap F E` is surjective. -/
theorem IsPurelyInseparable.surjective_algebraMap_of_isSeparable
[IsPurelyInseparable F E] [IsSeparable F E] : Function.Surjective (algebraMap F E) :=
fun x ↦ IsPurelyInseparable.inseparable F x (IsSeparable.separable F x)
/-- If `E / F` is both purely inseparable and separable, then `algebraMap F E` is bijective. -/
theorem IsPurelyInseparable.bijective_algebraMap_of_isSeparable
[IsPurelyInseparable F E] [IsSeparable F E] : Function.Bijective (algebraMap F E) :=
⟨(algebraMap F E).injective, surjective_algebraMap_of_isSeparable F E⟩
variable {F E} in
/-- If an intermediate field of `E / F` is both purely inseparable and separable, then it is equal
to `F`. -/
theorem IntermediateField.eq_bot_of_isPurelyInseparable_of_isSeparable (L : IntermediateField F E)
[IsPurelyInseparable F L] [IsSeparable F L] : L = ⊥ := bot_unique fun x hx ↦ by
obtain ⟨y, hy⟩ := IsPurelyInseparable.surjective_algebraMap_of_isSeparable F L ⟨x, hx⟩
exact ⟨y, congr_arg (algebraMap L E) hy⟩
/-- If `E / F` is purely inseparable, then the separable closure of `F` in `E` is
equal to `F`. -/
theorem separableClosure.eq_bot_of_isPurelyInseparable [IsPurelyInseparable F E] :
separableClosure F E = ⊥ :=
bot_unique fun x h ↦ IsPurelyInseparable.inseparable F x (mem_separableClosure_iff.1 h)
variable {F E} in
/-- If `E / F` is an algebraic extension, then the separable closure of `F` in `E` is
equal to `F` if and only if `E / F` is purely inseparable. -/
theorem separableClosure.eq_bot_iff [Algebra.IsAlgebraic F E] :
separableClosure F E = ⊥ ↔ IsPurelyInseparable F E :=
⟨fun h ↦ isPurelyInseparable_iff.2 fun x ↦ ⟨Algebra.IsIntegral.isIntegral x, fun hs ↦ by
simpa only [h] using mem_separableClosure_iff.2 hs⟩, fun _ ↦ eq_bot_of_isPurelyInseparable F E⟩
instance isPurelyInseparable_self : IsPurelyInseparable F F :=
⟨inferInstance, fun x _ ↦ ⟨x, rfl⟩⟩
variable {E}
/-- A field extension `E / F` of exponential characteristic `q` is purely inseparable
if and only if for every element `x` of `E`, there exists a natural number `n` such that
`x ^ (q ^ n)` is contained in `F`. -/
theorem isPurelyInseparable_iff_pow_mem (q : ℕ) [ExpChar F q] :
IsPurelyInseparable F E ↔ ∀ x : E, ∃ n : ℕ, x ^ q ^ n ∈ (algebraMap F E).range := by
rw [isPurelyInseparable_iff]
refine ⟨fun h x ↦ ?_, fun h x ↦ ?_⟩
· obtain ⟨g, h1, n, h2⟩ := (minpoly.irreducible (h x).1).hasSeparableContraction q
exact ⟨n, (h _).2 <| h1.of_dvd <| minpoly.dvd F _ <| by
simpa only [expand_aeval, minpoly.aeval] using congr_arg (aeval x) h2⟩
have hdeg := (minpoly.natSepDegree_eq_one_iff_pow_mem q).2 (h x)
have halg : IsIntegral F x := by_contra fun h' ↦ by
simp only [minpoly.eq_zero h', natSepDegree_zero, zero_ne_one] at hdeg
refine ⟨halg, fun hsep ↦ ?_⟩
rw [hsep.natSepDegree_eq_natDegree, ← adjoin.finrank halg,
IntermediateField.finrank_eq_one_iff] at hdeg
simpa only [hdeg] using mem_adjoin_simple_self F x
theorem IsPurelyInseparable.pow_mem (q : ℕ) [ExpChar F q] [IsPurelyInseparable F E] (x : E) :
∃ n : ℕ, x ^ q ^ n ∈ (algebraMap F E).range :=
(isPurelyInseparable_iff_pow_mem F q).1 ‹_› x
end IsPurelyInseparable
section perfectClosure
/-- The relative perfect closure of `F` in `E`, consists of the elements `x` of `E` such that there
exists a natural number `n` such that `x ^ (ringExpChar F) ^ n` is contained in `F`, where
`ringExpChar F` is the exponential characteristic of `F`. It is also the maximal purely inseparable
subextension of `E / F` (`le_perfectClosure_iff`). -/
def perfectClosure : IntermediateField F E where
carrier := {x : E | ∃ n : ℕ, x ^ (ringExpChar F) ^ n ∈ (algebraMap F E).range}
add_mem' := by
rintro x y ⟨n, hx⟩ ⟨m, hy⟩
use n + m
have := expChar_of_injective_algebraMap (algebraMap F E).injective (ringExpChar F)
rw [add_pow_expChar_pow, pow_add, pow_mul, mul_comm (_ ^ n), pow_mul]
exact add_mem (pow_mem hx _) (pow_mem hy _)
mul_mem' := by
rintro x y ⟨n, hx⟩ ⟨m, hy⟩
use n + m
rw [mul_pow, pow_add, pow_mul, mul_comm (_ ^ n), pow_mul]
exact mul_mem (pow_mem hx _) (pow_mem hy _)
inv_mem' := by
rintro x ⟨n, hx⟩
use n; rw [inv_pow]
apply inv_mem (id hx : _ ∈ (⊥ : IntermediateField F E))
algebraMap_mem' := fun x ↦ ⟨0, by rw [pow_zero, pow_one]; exact ⟨x, rfl⟩⟩
variable {F E}
theorem mem_perfectClosure_iff {x : E} :
x ∈ perfectClosure F E ↔ ∃ n : ℕ, x ^ (ringExpChar F) ^ n ∈ (algebraMap F E).range := Iff.rfl
theorem mem_perfectClosure_iff_pow_mem (q : ℕ) [ExpChar F q] {x : E} :
x ∈ perfectClosure F E ↔ ∃ n : ℕ, x ^ q ^ n ∈ (algebraMap F E).range := by
rw [mem_perfectClosure_iff, ringExpChar.eq F q]
/-- An element is contained in the relative perfect closure if and only if its mininal polynomial
has separable degree one. -/
theorem mem_perfectClosure_iff_natSepDegree_eq_one {x : E} :
x ∈ perfectClosure F E ↔ (minpoly F x).natSepDegree = 1 := by
rw [mem_perfectClosure_iff, minpoly.natSepDegree_eq_one_iff_pow_mem (ringExpChar F)]
/-- A field extension `E / F` is purely inseparable if and only if the relative perfect closure of
`F` in `E` is equal to `E`. -/
theorem isPurelyInseparable_iff_perfectClosure_eq_top :
IsPurelyInseparable F E ↔ perfectClosure F E = ⊤ := by
rw [isPurelyInseparable_iff_pow_mem F (ringExpChar F)]
exact ⟨fun H ↦ top_unique fun x _ ↦ H x, fun H _ ↦ H.ge trivial⟩
variable (F E)
/-- The relative perfect closure of `F` in `E` is purely inseparable over `F`. -/
instance perfectClosure.isPurelyInseparable : IsPurelyInseparable F (perfectClosure F E) := by
rw [isPurelyInseparable_iff_pow_mem F (ringExpChar F)]
exact fun ⟨_, n, y, h⟩ ↦ ⟨n, y, (algebraMap _ E).injective h⟩
/-- The relative perfect closure of `F` in `E` is algebraic over `F`. -/
instance perfectClosure.isAlgebraic : Algebra.IsAlgebraic F (perfectClosure F E) :=
IsPurelyInseparable.isAlgebraic F _
/-- If `E / F` is separable, then the perfect closure of `F` in `E` is equal to `F`. Note that
the converse is not necessarily true (see https://math.stackexchange.com/a/3009197)
even when `E / F` is algebraic. -/
theorem perfectClosure.eq_bot_of_isSeparable [IsSeparable F E] : perfectClosure F E = ⊥ :=
haveI := isSeparable_tower_bot_of_isSeparable F (perfectClosure F E) E
eq_bot_of_isPurelyInseparable_of_isSeparable _
/-- An intermediate field of `E / F` is contained in the relative perfect closure of `F` in `E`
if it is purely inseparable over `F`. -/
theorem le_perfectClosure (L : IntermediateField F E) [h : IsPurelyInseparable F L] :
L ≤ perfectClosure F E := by
rw [isPurelyInseparable_iff_pow_mem F (ringExpChar F)] at h
intro x hx
obtain ⟨n, y, hy⟩ := h ⟨x, hx⟩
exact ⟨n, y, congr_arg (algebraMap L E) hy⟩
/-- An intermediate field of `E / F` is contained in the relative perfect closure of `F` in `E`
if and only if it is purely inseparable over `F`. -/
theorem le_perfectClosure_iff (L : IntermediateField F E) :
L ≤ perfectClosure F E ↔ IsPurelyInseparable F L := by
refine ⟨fun h ↦ (isPurelyInseparable_iff_pow_mem F (ringExpChar F)).2 fun x ↦ ?_,
fun _ ↦ le_perfectClosure F E L⟩
obtain ⟨n, y, hy⟩ := h x.2
exact ⟨n, y, (algebraMap L E).injective hy⟩
theorem separableClosure_inf_perfectClosure : separableClosure F E ⊓ perfectClosure F E = ⊥ :=
haveI := (le_separableClosure_iff F E _).mp (inf_le_left (b := perfectClosure F E))
haveI := (le_perfectClosure_iff F E _).mp (inf_le_right (a := separableClosure F E))
eq_bot_of_isPurelyInseparable_of_isSeparable _
section map
variable {F E K}
/-- If `i` is an `F`-algebra homomorphism from `E` to `K`, then `i x` is contained in
`perfectClosure F K` if and only if `x` is contained in `perfectClosure F E`. -/
theorem map_mem_perfectClosure_iff (i : E →ₐ[F] K) {x : E} :
i x ∈ perfectClosure F K ↔ x ∈ perfectClosure F E := by
simp_rw [mem_perfectClosure_iff]
refine ⟨fun ⟨n, y, h⟩ ↦ ⟨n, y, ?_⟩, fun ⟨n, y, h⟩ ↦ ⟨n, y, ?_⟩⟩
· apply_fun i using i.injective
rwa [AlgHom.commutes, map_pow]
simpa only [AlgHom.commutes, map_pow] using congr_arg i h
/-- If `i` is an `F`-algebra homomorphism from `E` to `K`, then the preimage of `perfectClosure F K`
under the map `i` is equal to `perfectClosure F E`. -/
theorem perfectClosure.comap_eq_of_algHom (i : E →ₐ[F] K) :
(perfectClosure F K).comap i = perfectClosure F E := by
ext x
exact map_mem_perfectClosure_iff i
/-- If `i` is an `F`-algebra homomorphism from `E` to `K`, then the image of `perfectClosure F E`
under the map `i` is contained in `perfectClosure F K`. -/
theorem perfectClosure.map_le_of_algHom (i : E →ₐ[F] K) :
(perfectClosure F E).map i ≤ perfectClosure F K :=
map_le_iff_le_comap.mpr (perfectClosure.comap_eq_of_algHom i).ge
/-- If `i` is an `F`-algebra isomorphism of `E` and `K`, then the image of `perfectClosure F E`
under the map `i` is equal to in `perfectClosure F K`. -/
theorem perfectClosure.map_eq_of_algEquiv (i : E ≃ₐ[F] K) :
(perfectClosure F E).map i.toAlgHom = perfectClosure F K :=
(map_le_of_algHom i.toAlgHom).antisymm (fun x hx ↦ ⟨i.symm x,
(map_mem_perfectClosure_iff i.symm.toAlgHom).2 hx, i.right_inv x⟩)
/-- If `E` and `K` are isomorphic as `F`-algebras, then `perfectClosure F E` and
`perfectClosure F K` are also isomorphic as `F`-algebras. -/
def perfectClosure.algEquivOfAlgEquiv (i : E ≃ₐ[F] K) :
perfectClosure F E ≃ₐ[F] perfectClosure F K :=
(intermediateFieldMap i _).trans (equivOfEq (map_eq_of_algEquiv i))
alias AlgEquiv.perfectClosure := perfectClosure.algEquivOfAlgEquiv
end map
/-- If `E` is a perfect field of exponential characteristic `p`, then the (relative) perfect closure
`perfectClosure F E` is perfect. -/
instance perfectClosure.perfectRing (p : ℕ) [ExpChar E p]
[PerfectRing E p] : PerfectRing (perfectClosure F E) p := .ofSurjective _ p fun x ↦ by
haveI := RingHom.expChar _ (algebraMap F E).injective p
obtain ⟨x', hx⟩ := surjective_frobenius E p x.1
obtain ⟨n, y, hy⟩ := (mem_perfectClosure_iff_pow_mem p).1 x.2
rw [frobenius_def] at hx
rw [← hx, ← pow_mul, ← pow_succ'] at hy
exact ⟨⟨x', (mem_perfectClosure_iff_pow_mem p).2 ⟨n + 1, y, hy⟩⟩, by
simp_rw [frobenius_def, SubmonoidClass.mk_pow, hx]⟩
/-- If `E` is a perfect field, then the (relative) perfect closure
`perfectClosure F E` is perfect. -/
instance perfectClosure.perfectField [PerfectField E] : PerfectField (perfectClosure F E) :=
PerfectRing.toPerfectField _ (ringExpChar E)
end perfectClosure
section IsPurelyInseparable
/-- If `K / E / F` is a field extension tower such that `K / F` is purely inseparable,
then `E / F` is also purely inseparable. -/
theorem IsPurelyInseparable.tower_bot [Algebra E K] [IsScalarTower F E K]
[IsPurelyInseparable F K] : IsPurelyInseparable F E := by
refine ⟨⟨fun x ↦ (isIntegral' F (algebraMap E K x)).tower_bot_of_field⟩, fun x h ↦ ?_⟩
rw [← minpoly.algebraMap_eq (algebraMap E K).injective] at h
obtain ⟨y, h⟩ := inseparable F _ h
exact ⟨y, (algebraMap E K).injective (h.symm ▸ (IsScalarTower.algebraMap_apply F E K y).symm)⟩
/-- If `K / E / F` is a field extension tower such that `K / F` is purely inseparable,
then `K / E` is also purely inseparable. -/
theorem IsPurelyInseparable.tower_top [Algebra E K] [IsScalarTower F E K]
[h : IsPurelyInseparable F K] : IsPurelyInseparable E K := by
obtain ⟨q, _⟩ := ExpChar.exists F
haveI := expChar_of_injective_algebraMap (algebraMap F E).injective q
rw [isPurelyInseparable_iff_pow_mem _ q] at h ⊢
intro x
obtain ⟨n, y, h⟩ := h x
exact ⟨n, (algebraMap F E) y, h.symm ▸ (IsScalarTower.algebraMap_apply F E K y).symm⟩
/-- If `E / F` and `K / E` are both purely inseparable extensions, then `K / F` is also
purely inseparable. -/
theorem IsPurelyInseparable.trans [Algebra E K] [IsScalarTower F E K]
[h1 : IsPurelyInseparable F E] [h2 : IsPurelyInseparable E K] : IsPurelyInseparable F K := by
obtain ⟨q, _⟩ := ExpChar.exists F
haveI := expChar_of_injective_algebraMap (algebraMap F E).injective q
rw [isPurelyInseparable_iff_pow_mem _ q] at h1 h2 ⊢
intro x
obtain ⟨n, y, h2⟩ := h2 x
obtain ⟨m, z, h1⟩ := h1 y
refine ⟨n + m, z, ?_⟩
rw [IsScalarTower.algebraMap_apply F E K, h1, map_pow, h2, ← pow_mul, ← pow_add]
variable {E}
/-- A field extension `E / F` is purely inseparable if and only if for every element `x` of `E`,
its minimal polynomial has separable degree one. -/
theorem isPurelyInseparable_iff_natSepDegree_eq_one :
IsPurelyInseparable F E ↔ ∀ x : E, (minpoly F x).natSepDegree = 1 := by
obtain ⟨q, _⟩ := ExpChar.exists F
simp_rw [isPurelyInseparable_iff_pow_mem F q, minpoly.natSepDegree_eq_one_iff_pow_mem q]
theorem IsPurelyInseparable.natSepDegree_eq_one [IsPurelyInseparable F E] (x : E) :
(minpoly F x).natSepDegree = 1 :=
(isPurelyInseparable_iff_natSepDegree_eq_one F).1 ‹_› x
/-- A field extension `E / F` of exponential characteristic `q` is purely inseparable
if and only if for every element `x` of `E`, the minimal polynomial of `x` over `F` is of form
`X ^ (q ^ n) - y` for some natural number `n` and some element `y` of `F`. -/
theorem isPurelyInseparable_iff_minpoly_eq_X_pow_sub_C (q : ℕ) [hF : ExpChar F q] :
IsPurelyInseparable F E ↔ ∀ x : E, ∃ (n : ℕ) (y : F), minpoly F x = X ^ q ^ n - C y := by
simp_rw [isPurelyInseparable_iff_natSepDegree_eq_one,
minpoly.natSepDegree_eq_one_iff_eq_X_pow_sub_C q]
theorem IsPurelyInseparable.minpoly_eq_X_pow_sub_C (q : ℕ) [ExpChar F q] [IsPurelyInseparable F E]
(x : E) : ∃ (n : ℕ) (y : F), minpoly F x = X ^ q ^ n - C y :=
(isPurelyInseparable_iff_minpoly_eq_X_pow_sub_C F q).1 ‹_› x
/-- A field extension `E / F` of exponential characteristic `q` is purely inseparable
if and only if for every element `x` of `E`, the minimal polynomial of `x` over `F` is of form
`(X - x) ^ (q ^ n)` for some natural number `n`. -/
theorem isPurelyInseparable_iff_minpoly_eq_X_sub_C_pow (q : ℕ) [hF : ExpChar F q] :
IsPurelyInseparable F E ↔
∀ x : E, ∃ n : ℕ, (minpoly F x).map (algebraMap F E) = (X - C x) ^ q ^ n := by
simp_rw [isPurelyInseparable_iff_natSepDegree_eq_one,
minpoly.natSepDegree_eq_one_iff_eq_X_sub_C_pow q]
theorem IsPurelyInseparable.minpoly_eq_X_sub_C_pow (q : ℕ) [ExpChar F q] [IsPurelyInseparable F E]
(x : E) : ∃ n : ℕ, (minpoly F x).map (algebraMap F E) = (X - C x) ^ q ^ n :=
(isPurelyInseparable_iff_minpoly_eq_X_sub_C_pow F q).1 ‹_› x
variable (E)
-- TODO: remove `halg` assumption
variable {F E} in
/-- If an algebraic extension has finite separable degree one, then it is purely inseparable. -/
theorem isPurelyInseparable_of_finSepDegree_eq_one [Algebra.IsAlgebraic F E]
(hdeg : finSepDegree F E = 1) : IsPurelyInseparable F E := by
rw [isPurelyInseparable_iff]
refine fun x ↦ ⟨Algebra.IsIntegral.isIntegral x, fun hsep ↦ ?_⟩
have : Algebra.IsAlgebraic F⟮x⟯ E := Algebra.IsAlgebraic.tower_top (K := F) F⟮x⟯
have := finSepDegree_mul_finSepDegree_of_isAlgebraic F F⟮x⟯ E
rw [hdeg, mul_eq_one, (finSepDegree_adjoin_simple_eq_finrank_iff F E x
(Algebra.IsAlgebraic.isAlgebraic x)).2 hsep,
IntermediateField.finrank_eq_one_iff] at this
simpa only [this.1] using mem_adjoin_simple_self F x
/-- If `E / F` is purely inseparable, then for any reduced ring `L`, the map `(E →+* L) → (F →+* L)`
induced by `algebraMap F E` is injective. In particular, a purely inseparable field extension
is an epimorphism in the category of fields. -/
theorem IsPurelyInseparable.injective_comp_algebraMap [IsPurelyInseparable F E]
(L : Type w) [CommRing L] [IsReduced L] :
Function.Injective fun f : E →+* L ↦ f.comp (algebraMap F E) := fun f g heq ↦ by
ext x
let q := ringExpChar F
obtain ⟨n, y, h⟩ := IsPurelyInseparable.pow_mem F q x
replace heq := congr($heq y)
simp_rw [RingHom.comp_apply, h, map_pow] at heq
nontriviality L
haveI := expChar_of_injective_ringHom (f.comp (algebraMap F E)).injective q
exact iterateFrobenius_inj L q n heq
/-- If `E / F` is purely inseparable, then for any reduced `F`-algebra `L`, there exists at most one
`F`-algebra homomorphism from `E` to `L`. -/
instance instSubsingletonAlgHomOfIsPurelyInseparable [IsPurelyInseparable F E] (L : Type w)
[CommRing L] [IsReduced L] [Algebra F L] : Subsingleton (E →ₐ[F] L) where
allEq f g := AlgHom.coe_ringHom_injective <|
IsPurelyInseparable.injective_comp_algebraMap F E L (by simp_rw [AlgHom.comp_algebraMap])
instance instUniqueAlgHomOfIsPurelyInseparable [IsPurelyInseparable F E] (L : Type w)
[CommRing L] [IsReduced L] [Algebra F L] [Algebra E L] [IsScalarTower F E L] :
Unique (E →ₐ[F] L) := uniqueOfSubsingleton (IsScalarTower.toAlgHom F E L)
/-- If `E / F` is purely inseparable, then `Field.Emb F E` has exactly one element. -/
instance instUniqueEmbOfIsPurelyInseparable [IsPurelyInseparable F E] :
Unique (Emb F E) := instUniqueAlgHomOfIsPurelyInseparable F E _
/-- A purely inseparable extension has finite separable degree one. -/
theorem IsPurelyInseparable.finSepDegree_eq_one [IsPurelyInseparable F E] :
finSepDegree F E = 1 := Nat.card_unique
/-- A purely inseparable extension has separable degree one. -/
theorem IsPurelyInseparable.sepDegree_eq_one [IsPurelyInseparable F E] :
sepDegree F E = 1 := by
rw [sepDegree, separableClosure.eq_bot_of_isPurelyInseparable, IntermediateField.rank_bot]
/-- A purely inseparable extension has inseparable degree equal to degree. -/
theorem IsPurelyInseparable.insepDegree_eq [IsPurelyInseparable F E] :
insepDegree F E = Module.rank F E := by
rw [insepDegree, separableClosure.eq_bot_of_isPurelyInseparable, rank_bot']
/-- A purely inseparable extension has finite inseparable degree equal to degree. -/
theorem IsPurelyInseparable.finInsepDegree_eq [IsPurelyInseparable F E] :
finInsepDegree F E = finrank F E := congr(Cardinal.toNat $(insepDegree_eq F E))
-- TODO: remove `halg` assumption
/-- An algebraic extension is purely inseparable if and only if it has finite separable
degree one. -/
theorem isPurelyInseparable_iff_finSepDegree_eq_one [Algebra.IsAlgebraic F E] :
IsPurelyInseparable F E ↔ finSepDegree F E = 1 :=
⟨fun _ ↦ IsPurelyInseparable.finSepDegree_eq_one F E,
fun h ↦ isPurelyInseparable_of_finSepDegree_eq_one h⟩
variable {F E} in
/-- An algebraic extension is purely inseparable if and only if all of its finite dimensional
subextensions are purely inseparable. -/
theorem isPurelyInseparable_iff_fd_isPurelyInseparable [Algebra.IsAlgebraic F E] :
IsPurelyInseparable F E ↔
∀ L : IntermediateField F E, FiniteDimensional F L → IsPurelyInseparable F L := by
refine ⟨fun _ _ _ ↦ IsPurelyInseparable.tower_bot F _ E,
fun h ↦ isPurelyInseparable_iff.2 fun x ↦ ?_⟩
have hx : IsIntegral F x := Algebra.IsIntegral.isIntegral x
refine ⟨hx, fun _ ↦ ?_⟩
obtain ⟨y, h⟩ := (h _ (adjoin.finiteDimensional hx)).inseparable' _ <|
show Separable (minpoly F (AdjoinSimple.gen F x)) by rwa [minpoly_eq]
exact ⟨y, congr_arg (algebraMap _ E) h⟩
/-- A purely inseparable extension is normal. -/
instance IsPurelyInseparable.normal [IsPurelyInseparable F E] : Normal F E where
toIsAlgebraic := isAlgebraic F E
splits' x := by
obtain ⟨n, h⟩ := IsPurelyInseparable.minpoly_eq_X_sub_C_pow F (ringExpChar F) x
rw [← splits_id_iff_splits, h]
exact splits_pow _ (splits_X_sub_C _) _
/-- If `E / F` is algebraic, then `E` is purely inseparable over the
separable closure of `F` in `E`. -/
theorem separableClosure.isPurelyInseparable [Algebra.IsAlgebraic F E] :
IsPurelyInseparable (separableClosure F E) E := isPurelyInseparable_iff.2 fun x ↦ by
set L := separableClosure F E
refine ⟨(IsAlgebraic.tower_top L (Algebra.IsAlgebraic.isAlgebraic (R := F) x)).isIntegral,
fun h ↦ ?_⟩
haveI := (isSeparable_adjoin_simple_iff_separable L E).2 h
haveI : IsSeparable F (restrictScalars F L⟮x⟯) := IsSeparable.trans F L L⟮x⟯
have hx : x ∈ restrictScalars F L⟮x⟯ := mem_adjoin_simple_self _ x
exact ⟨⟨x, mem_separableClosure_iff.2 <| separable_of_mem_isSeparable F E hx⟩, rfl⟩
/-- An intermediate field of `E / F` contains the separable closure of `F` in `E`
if `E` is purely inseparable over it. -/
theorem separableClosure_le (L : IntermediateField F E)
[h : IsPurelyInseparable L E] : separableClosure F E ≤ L := fun x hx ↦ by
obtain ⟨y, rfl⟩ := h.inseparable' _ <| (mem_separableClosure_iff.1 hx).map_minpoly L
exact y.2
/-- If `E / F` is algebraic, then an intermediate field of `E / F` contains the
separable closure of `F` in `E` if and only if `E` is purely inseparable over it. -/
theorem separableClosure_le_iff [Algebra.IsAlgebraic F E] (L : IntermediateField F E) :
separableClosure F E ≤ L ↔ IsPurelyInseparable L E := by
refine ⟨fun h ↦ ?_, fun _ ↦ separableClosure_le F E L⟩
have := separableClosure.isPurelyInseparable F E
letI := (inclusion h).toAlgebra
letI : SMul (separableClosure F E) L := Algebra.toSMul
haveI : IsScalarTower (separableClosure F E) L E := IsScalarTower.of_algebraMap_eq (congrFun rfl)
exact IsPurelyInseparable.tower_top (separableClosure F E) L E
/-- If an intermediate field of `E / F` is separable over `F`, and `E` is purely inseparable
over it, then it is equal to the separable closure of `F` in `E`. -/
theorem eq_separableClosure (L : IntermediateField F E)
[IsSeparable F L] [IsPurelyInseparable L E] : L = separableClosure F E :=
le_antisymm (le_separableClosure F E L) (separableClosure_le F E L)
open separableClosure in
/-- If `E / F` is algebraic, then an intermediate field of `E / F` is equal to the separable closure
of `F` in `E` if and only if it is separable over `F`, and `E` is purely inseparable
over it. -/
theorem eq_separableClosure_iff [Algebra.IsAlgebraic F E] (L : IntermediateField F E) :
L = separableClosure F E ↔ IsSeparable F L ∧ IsPurelyInseparable L E :=
⟨by rintro rfl; exact ⟨isSeparable F E, isPurelyInseparable F E⟩,
fun ⟨_, _⟩ ↦ eq_separableClosure F E L⟩
-- TODO: prove it
set_option linter.unusedVariables false in
/-- If `L` is an algebraically closed field containing `E`, such that the map
`(E →+* L) → (F →+* L)` induced by `algebraMap F E` is injective, then `E / F` is
purely inseparable. As a corollary, epimorphisms in the category of fields must be
purely inseparable extensions. -/
proof_wanted IsPurelyInseparable.of_injective_comp_algebraMap (L : Type w) [Field L] [IsAlgClosed L]
(hn : Nonempty (E →+* L)) (h : Function.Injective fun f : E →+* L ↦ f.comp (algebraMap F E)) :
IsPurelyInseparable F E
end IsPurelyInseparable
namespace IntermediateField
instance isPurelyInseparable_bot : IsPurelyInseparable F (⊥ : IntermediateField F E) :=
(botEquiv F E).symm.isPurelyInseparable
/-- `F⟮x⟯ / F` is a purely inseparable extension if and only if the mininal polynomial of `x`
has separable degree one. -/
theorem isPurelyInseparable_adjoin_simple_iff_natSepDegree_eq_one {x : E} :
IsPurelyInseparable F F⟮x⟯ ↔ (minpoly F x).natSepDegree = 1 := by
rw [← le_perfectClosure_iff, adjoin_simple_le_iff, mem_perfectClosure_iff_natSepDegree_eq_one]
/-- If `F` is of exponential characteristic `q`, then `F⟮x⟯ / F` is a purely inseparable extension
if and only if `x ^ (q ^ n)` is contained in `F` for some `n : ℕ`. -/
theorem isPurelyInseparable_adjoin_simple_iff_pow_mem (q : ℕ) [hF : ExpChar F q] {x : E} :
IsPurelyInseparable F F⟮x⟯ ↔ ∃ n : ℕ, x ^ q ^ n ∈ (algebraMap F E).range := by
rw [← le_perfectClosure_iff, adjoin_simple_le_iff, mem_perfectClosure_iff_pow_mem q]
/-- If `F` is of exponential characteristic `q`, then `F(S) / F` is a purely inseparable extension
if and only if for any `x ∈ S`, `x ^ (q ^ n)` is contained in `F` for some `n : ℕ`. -/
| Mathlib/FieldTheory/PurelyInseparable.lean | 645 | 648 | theorem isPurelyInseparable_adjoin_iff_pow_mem (q : ℕ) [hF : ExpChar F q] {S : Set E} :
IsPurelyInseparable F (adjoin F S) ↔ ∀ x ∈ S, ∃ n : ℕ, x ^ q ^ n ∈ (algebraMap F E).range := by |
simp_rw [← le_perfectClosure_iff, adjoin_le_iff, ← mem_perfectClosure_iff_pow_mem q,
Set.le_iff_subset, Set.subset_def, SetLike.mem_coe]
|
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad
-/
import Mathlib.Algebra.Ring.Int
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.Size
#align_import data.int.bitwise from "leanprover-community/mathlib"@"0743cc5d9d86bcd1bba10f480e948a257d65056f"
#align_import init.data.int.bitwise from "leanprover-community/lean"@"855e5b74e3a52a40552e8f067169d747d48743fd"
/-!
# Bitwise operations on integers
Possibly only of archaeological significance.
## Recursors
* `Int.bitCasesOn`: Parity disjunction. Something is true/defined on `ℤ` if it's true/defined for
even and for odd values.
-/
namespace Int
/-- `div2 n = n/2`-/
def div2 : ℤ → ℤ
| (n : ℕ) => n.div2
| -[n +1] => negSucc n.div2
#align int.div2 Int.div2
/-- `bodd n` returns `true` if `n` is odd-/
def bodd : ℤ → Bool
| (n : ℕ) => n.bodd
| -[n +1] => not (n.bodd)
#align int.bodd Int.bodd
-- Porting note: `bit0, bit1` deprecated, do we need to adapt `bit`?
set_option linter.deprecated false in
/-- `bit b` appends the digit `b` to the binary representation of
its integer input. -/
def bit (b : Bool) : ℤ → ℤ :=
cond b bit1 bit0
#align int.bit Int.bit
/-- `testBit m n` returns whether the `(n+1)ˢᵗ` least significant bit is `1` or `0`-/
def testBit : ℤ → ℕ → Bool
| (m : ℕ), n => Nat.testBit m n
| -[m +1], n => !(Nat.testBit m n)
#align int.test_bit Int.testBit
/-- `Int.natBitwise` is an auxiliary definition for `Int.bitwise`. -/
def natBitwise (f : Bool → Bool → Bool) (m n : ℕ) : ℤ :=
cond (f false false) -[ Nat.bitwise (fun x y => not (f x y)) m n +1] (Nat.bitwise f m n)
#align int.nat_bitwise Int.natBitwise
/-- `Int.bitwise` applies the function `f` to pairs of bits in the same position in
the binary representations of its inputs. -/
def bitwise (f : Bool → Bool → Bool) : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => natBitwise f m n
| (m : ℕ), -[n +1] => natBitwise (fun x y => f x (not y)) m n
| -[m +1], (n : ℕ) => natBitwise (fun x y => f (not x) y) m n
| -[m +1], -[n +1] => natBitwise (fun x y => f (not x) (not y)) m n
#align int.bitwise Int.bitwise
/-- `lnot` flips all the bits in the binary representation of its input -/
def lnot : ℤ → ℤ
| (m : ℕ) => -[m +1]
| -[m +1] => m
#align int.lnot Int.lnot
/-- `lor` takes two integers and returns their bitwise `or`-/
def lor : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => m ||| n
| (m : ℕ), -[n +1] => -[Nat.ldiff n m +1]
| -[m +1], (n : ℕ) => -[Nat.ldiff m n +1]
| -[m +1], -[n +1] => -[m &&& n +1]
#align int.lor Int.lor
/-- `land` takes two integers and returns their bitwise `and`-/
def land : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => m &&& n
| (m : ℕ), -[n +1] => Nat.ldiff m n
| -[m +1], (n : ℕ) => Nat.ldiff n m
| -[m +1], -[n +1] => -[m ||| n +1]
#align int.land Int.land
-- Porting note: I don't know why `Nat.ldiff` got the prime, but I'm matching this change here
/-- `ldiff a b` performs bitwise set difference. For each corresponding
pair of bits taken as booleans, say `aᵢ` and `bᵢ`, it applies the
boolean operation `aᵢ ∧ bᵢ` to obtain the `iᵗʰ` bit of the result. -/
def ldiff : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => Nat.ldiff m n
| (m : ℕ), -[n +1] => m &&& n
| -[m +1], (n : ℕ) => -[m ||| n +1]
| -[m +1], -[n +1] => Nat.ldiff n m
#align int.ldiff Int.ldiff
-- Porting note: I don't know why `Nat.xor'` got the prime, but I'm matching this change here
/-- `xor` computes the bitwise `xor` of two natural numbers-/
protected def xor : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => (m ^^^ n)
| (m : ℕ), -[n +1] => -[(m ^^^ n) +1]
| -[m +1], (n : ℕ) => -[(m ^^^ n) +1]
| -[m +1], -[n +1] => (m ^^^ n)
#align int.lxor Int.xor
/-- `m <<< n` produces an integer whose binary representation
is obtained by left-shifting the binary representation of `m` by `n` places -/
instance : ShiftLeft ℤ where
shiftLeft
| (m : ℕ), (n : ℕ) => Nat.shiftLeft' false m n
| (m : ℕ), -[n +1] => m >>> (Nat.succ n)
| -[m +1], (n : ℕ) => -[Nat.shiftLeft' true m n +1]
| -[m +1], -[n +1] => -[m >>> (Nat.succ n) +1]
#align int.shiftl ShiftLeft.shiftLeft
/-- `m >>> n` produces an integer whose binary representation
is obtained by right-shifting the binary representation of `m` by `n` places -/
instance : ShiftRight ℤ where
shiftRight m n := m <<< (-n)
#align int.shiftr ShiftRight.shiftRight
/-! ### bitwise ops -/
@[simp]
theorem bodd_zero : bodd 0 = false :=
rfl
#align int.bodd_zero Int.bodd_zero
@[simp]
theorem bodd_one : bodd 1 = true :=
rfl
#align int.bodd_one Int.bodd_one
theorem bodd_two : bodd 2 = false :=
rfl
#align int.bodd_two Int.bodd_two
@[simp, norm_cast]
theorem bodd_coe (n : ℕ) : Int.bodd n = Nat.bodd n :=
rfl
#align int.bodd_coe Int.bodd_coe
@[simp]
theorem bodd_subNatNat (m n : ℕ) : bodd (subNatNat m n) = xor m.bodd n.bodd := by
apply subNatNat_elim m n fun m n i => bodd i = xor m.bodd n.bodd <;>
intros i j <;>
simp only [Int.bodd, Int.bodd_coe, Nat.bodd_add] <;>
cases Nat.bodd i <;> simp
#align int.bodd_sub_nat_nat Int.bodd_subNatNat
@[simp]
theorem bodd_negOfNat (n : ℕ) : bodd (negOfNat n) = n.bodd := by
cases n <;> simp (config := {decide := true})
rfl
#align int.bodd_neg_of_nat Int.bodd_negOfNat
@[simp]
theorem bodd_neg (n : ℤ) : bodd (-n) = bodd n := by
cases n with
| ofNat =>
rw [← negOfNat_eq, bodd_negOfNat]
simp
| negSucc n =>
rw [neg_negSucc, bodd_coe, Nat.bodd_succ]
change (!Nat.bodd n) = !(bodd n)
rw [bodd_coe]
-- Porting note: Heavily refactored proof, used to work all with `simp`:
-- `cases n <;> simp [Neg.neg, Int.natCast_eq_ofNat, Int.neg, bodd, -of_nat_eq_coe]`
#align int.bodd_neg Int.bodd_neg
@[simp]
theorem bodd_add (m n : ℤ) : bodd (m + n) = xor (bodd m) (bodd n) := by
cases' m with m m <;>
cases' n with n n <;>
simp only [ofNat_eq_coe, ofNat_add_negSucc, negSucc_add_ofNat,
negSucc_add_negSucc, bodd_subNatNat] <;>
simp only [negSucc_coe, bodd_neg, bodd_coe, ← Nat.bodd_add, Bool.xor_comm, ← Nat.cast_add]
rw [← Nat.succ_add, add_assoc]
-- Porting note: Heavily refactored proof, used to work all with `simp`:
-- `by cases m with m m; cases n with n n; unfold has_add.add;`
-- `simp [int.add, -of_nat_eq_coe, bool.xor_comm]`
#align int.bodd_add Int.bodd_add
@[simp]
theorem bodd_mul (m n : ℤ) : bodd (m * n) = (bodd m && bodd n) := by
cases' m with m m <;> cases' n with n n <;>
simp only [ofNat_eq_coe, ofNat_mul_negSucc, negSucc_mul_ofNat, ofNat_mul_ofNat,
negSucc_mul_negSucc] <;>
simp only [negSucc_coe, bodd_neg, bodd_coe, ← Nat.bodd_mul]
-- Porting note: Heavily refactored proof, used to be:
-- `by cases m with m m; cases n with n n;`
-- `simp [← int.mul_def, int.mul, -of_nat_eq_coe, bool.xor_comm]`
#align int.bodd_mul Int.bodd_mul
theorem bodd_add_div2 : ∀ n, cond (bodd n) 1 0 + 2 * div2 n = n
| (n : ℕ) => by
rw [show (cond (bodd n) 1 0 : ℤ) = (cond (bodd n) 1 0 : ℕ) by cases bodd n <;> rfl]
exact congr_arg ofNat n.bodd_add_div2
| -[n+1] => by
refine Eq.trans ?_ (congr_arg negSucc n.bodd_add_div2)
dsimp [bodd]; cases Nat.bodd n <;> dsimp [cond, not, div2, Int.mul]
· change -[2 * Nat.div2 n+1] = _
rw [zero_add]
· rw [zero_add, add_comm]
rfl
#align int.bodd_add_div2 Int.bodd_add_div2
theorem div2_val : ∀ n, div2 n = n / 2
| (n : ℕ) => congr_arg ofNat n.div2_val
| -[n+1] => congr_arg negSucc n.div2_val
#align int.div2_val Int.div2_val
section deprecated
set_option linter.deprecated false
@[deprecated]
theorem bit0_val (n : ℤ) : bit0 n = 2 * n :=
(two_mul _).symm
#align int.bit0_val Int.bit0_val
@[deprecated]
theorem bit1_val (n : ℤ) : bit1 n = 2 * n + 1 :=
congr_arg (· + (1 : ℤ)) (bit0_val _)
#align int.bit1_val Int.bit1_val
theorem bit_val (b n) : bit b n = 2 * n + cond b 1 0 := by
cases b
· apply (bit0_val n).trans (add_zero _).symm
· apply bit1_val
#align int.bit_val Int.bit_val
theorem bit_decomp (n : ℤ) : bit (bodd n) (div2 n) = n :=
(bit_val _ _).trans <| (add_comm _ _).trans <| bodd_add_div2 _
#align int.bit_decomp Int.bit_decomp
/-- Defines a function from `ℤ` conditionally, if it is defined for odd and even integers separately
using `bit`. -/
def bitCasesOn.{u} {C : ℤ → Sort u} (n) (h : ∀ b n, C (bit b n)) : C n := by
rw [← bit_decomp n]
apply h
#align int.bit_cases_on Int.bitCasesOn
@[simp]
theorem bit_zero : bit false 0 = 0 :=
rfl
#align int.bit_zero Int.bit_zero
@[simp]
| Mathlib/Data/Int/Bitwise.lean | 251 | 253 | theorem bit_coe_nat (b) (n : ℕ) : bit b n = Nat.bit b n := by |
rw [bit_val, Nat.bit_val]
cases b <;> rfl
|
/-
Copyright (c) 2022 Bolton Bailey. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bolton Bailey, Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Mathlib.Data.Int.Log
#align_import analysis.special_functions.log.base from "leanprover-community/mathlib"@"f23a09ce6d3f367220dc3cecad6b7eb69eb01690"
/-!
# Real logarithm base `b`
In this file we define `Real.logb` to be the logarithm of a real number in a given base `b`. We
define this as the division of the natural logarithms of the argument and the base, so that we have
a globally defined function with `logb b 0 = 0`, `logb b (-x) = logb b x` `logb 0 x = 0` and
`logb (-b) x = logb b x`.
We prove some basic properties of this function and its relation to `rpow`.
## Tags
logarithm, continuity
-/
open Set Filter Function
open Topology
noncomputable section
namespace Real
variable {b x y : ℝ}
/-- The real logarithm in a given base. As with the natural logarithm, we define `logb b x` to
be `logb b |x|` for `x < 0`, and `0` for `x = 0`. -/
-- @[pp_nodot] -- Porting note: removed
noncomputable def logb (b x : ℝ) : ℝ :=
log x / log b
#align real.logb Real.logb
theorem log_div_log : log x / log b = logb b x :=
rfl
#align real.log_div_log Real.log_div_log
@[simp]
| Mathlib/Analysis/SpecialFunctions/Log/Base.lean | 49 | 49 | theorem logb_zero : logb b 0 = 0 := by | simp [logb]
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Scott Morrison, Adam Topaz
-/
import Mathlib.Tactic.Linarith
import Mathlib.CategoryTheory.Skeletal
import Mathlib.Data.Fintype.Sort
import Mathlib.Order.Category.NonemptyFinLinOrd
import Mathlib.CategoryTheory.Functor.ReflectsIso
#align_import algebraic_topology.simplex_category from "leanprover-community/mathlib"@"e8ac6315bcfcbaf2d19a046719c3b553206dac75"
/-! # The simplex category
We construct a skeletal model of the simplex category, with objects `ℕ` and the
morphism `n ⟶ m` being the monotone maps from `Fin (n+1)` to `Fin (m+1)`.
We show that this category is equivalent to `NonemptyFinLinOrd`.
## Remarks
The definitions `SimplexCategory` and `SimplexCategory.Hom` are marked as irreducible.
We provide the following functions to work with these objects:
1. `SimplexCategory.mk` creates an object of `SimplexCategory` out of a natural number.
Use the notation `[n]` in the `Simplicial` locale.
2. `SimplexCategory.len` gives the "length" of an object of `SimplexCategory`, as a natural.
3. `SimplexCategory.Hom.mk` makes a morphism out of a monotone map between `Fin`'s.
4. `SimplexCategory.Hom.toOrderHom` gives the underlying monotone map associated to a
term of `SimplexCategory.Hom`.
-/
universe v
open CategoryTheory CategoryTheory.Limits
/-- The simplex category:
* objects are natural numbers `n : ℕ`
* morphisms from `n` to `m` are monotone functions `Fin (n+1) → Fin (m+1)`
-/
def SimplexCategory :=
ℕ
#align simplex_category SimplexCategory
namespace SimplexCategory
section
-- Porting note: the definition of `SimplexCategory` is made irreducible below
/-- Interpret a natural number as an object of the simplex category. -/
def mk (n : ℕ) : SimplexCategory :=
n
#align simplex_category.mk SimplexCategory.mk
/-- the `n`-dimensional simplex can be denoted `[n]` -/
scoped[Simplicial] notation "[" n "]" => SimplexCategory.mk n
-- TODO: Make `len` irreducible.
/-- The length of an object of `SimplexCategory`. -/
def len (n : SimplexCategory) : ℕ :=
n
#align simplex_category.len SimplexCategory.len
@[ext]
theorem ext (a b : SimplexCategory) : a.len = b.len → a = b :=
id
#align simplex_category.ext SimplexCategory.ext
attribute [irreducible] SimplexCategory
open Simplicial
@[simp]
theorem len_mk (n : ℕ) : [n].len = n :=
rfl
#align simplex_category.len_mk SimplexCategory.len_mk
@[simp]
theorem mk_len (n : SimplexCategory) : ([n.len] : SimplexCategory) = n :=
rfl
#align simplex_category.mk_len SimplexCategory.mk_len
/-- A recursor for `SimplexCategory`. Use it as `induction Δ using SimplexCategory.rec`. -/
protected def rec {F : SimplexCategory → Sort*} (h : ∀ n : ℕ, F [n]) : ∀ X, F X := fun n =>
h n.len
#align simplex_category.rec SimplexCategory.rec
-- porting note (#5171): removed @[nolint has_nonempty_instance]
/-- Morphisms in the `SimplexCategory`. -/
protected def Hom (a b : SimplexCategory) :=
Fin (a.len + 1) →o Fin (b.len + 1)
#align simplex_category.hom SimplexCategory.Hom
namespace Hom
/-- Make a morphism in `SimplexCategory` from a monotone map of `Fin`'s. -/
def mk {a b : SimplexCategory} (f : Fin (a.len + 1) →o Fin (b.len + 1)) : SimplexCategory.Hom a b :=
f
#align simplex_category.hom.mk SimplexCategory.Hom.mk
/-- Recover the monotone map from a morphism in the simplex category. -/
def toOrderHom {a b : SimplexCategory} (f : SimplexCategory.Hom a b) :
Fin (a.len + 1) →o Fin (b.len + 1) :=
f
#align simplex_category.hom.to_order_hom SimplexCategory.Hom.toOrderHom
theorem ext' {a b : SimplexCategory} (f g : SimplexCategory.Hom a b) :
f.toOrderHom = g.toOrderHom → f = g :=
id
#align simplex_category.hom.ext SimplexCategory.Hom.ext'
attribute [irreducible] SimplexCategory.Hom
@[simp]
theorem mk_toOrderHom {a b : SimplexCategory} (f : SimplexCategory.Hom a b) : mk f.toOrderHom = f :=
rfl
#align simplex_category.hom.mk_to_order_hom SimplexCategory.Hom.mk_toOrderHom
@[simp]
theorem toOrderHom_mk {a b : SimplexCategory} (f : Fin (a.len + 1) →o Fin (b.len + 1)) :
(mk f).toOrderHom = f :=
rfl
#align simplex_category.hom.to_order_hom_mk SimplexCategory.Hom.toOrderHom_mk
theorem mk_toOrderHom_apply {a b : SimplexCategory} (f : Fin (a.len + 1) →o Fin (b.len + 1))
(i : Fin (a.len + 1)) : (mk f).toOrderHom i = f i :=
rfl
#align simplex_category.hom.mk_to_order_hom_apply SimplexCategory.Hom.mk_toOrderHom_apply
/-- Identity morphisms of `SimplexCategory`. -/
@[simp]
def id (a : SimplexCategory) : SimplexCategory.Hom a a :=
mk OrderHom.id
#align simplex_category.hom.id SimplexCategory.Hom.id
/-- Composition of morphisms of `SimplexCategory`. -/
@[simp]
def comp {a b c : SimplexCategory} (f : SimplexCategory.Hom b c) (g : SimplexCategory.Hom a b) :
SimplexCategory.Hom a c :=
mk <| f.toOrderHom.comp g.toOrderHom
#align simplex_category.hom.comp SimplexCategory.Hom.comp
end Hom
instance smallCategory : SmallCategory.{0} SimplexCategory where
Hom n m := SimplexCategory.Hom n m
id m := SimplexCategory.Hom.id _
comp f g := SimplexCategory.Hom.comp g f
#align simplex_category.small_category SimplexCategory.smallCategory
@[simp]
lemma id_toOrderHom (a : SimplexCategory) :
Hom.toOrderHom (𝟙 a) = OrderHom.id := rfl
@[simp]
lemma comp_toOrderHom {a b c: SimplexCategory} (f : a ⟶ b) (g : b ⟶ c) :
(f ≫ g).toOrderHom = g.toOrderHom.comp f.toOrderHom := rfl
-- Porting note: added because `Hom.ext'` is not triggered automatically
@[ext]
theorem Hom.ext {a b : SimplexCategory} (f g : a ⟶ b) :
f.toOrderHom = g.toOrderHom → f = g :=
Hom.ext' _ _
/-- The constant morphism from [0]. -/
def const (x y : SimplexCategory) (i : Fin (y.len + 1)) : x ⟶ y :=
Hom.mk <| ⟨fun _ => i, by tauto⟩
#align simplex_category.const SimplexCategory.const
@[simp]
lemma const_eq_id : const [0] [0] 0 = 𝟙 _ := by aesop
@[simp]
lemma const_apply (x y : SimplexCategory) (i : Fin (y.len + 1)) (a : Fin (x.len + 1)) :
(const x y i).toOrderHom a = i := rfl
@[simp]
theorem const_comp (x : SimplexCategory) {y z : SimplexCategory}
(f : y ⟶ z) (i : Fin (y.len + 1)) :
const x y i ≫ f = const x z (f.toOrderHom i) :=
rfl
#align simplex_category.const_comp SimplexCategory.const_comp
/-- Make a morphism `[n] ⟶ [m]` from a monotone map between fin's.
This is useful for constructing morphisms between `[n]` directly
without identifying `n` with `[n].len`.
-/
@[simp]
def mkHom {n m : ℕ} (f : Fin (n + 1) →o Fin (m + 1)) : ([n] : SimplexCategory) ⟶ [m] :=
SimplexCategory.Hom.mk f
#align simplex_category.mk_hom SimplexCategory.mkHom
theorem hom_zero_zero (f : ([0] : SimplexCategory) ⟶ [0]) : f = 𝟙 _ := by
ext : 3
apply @Subsingleton.elim (Fin 1)
#align simplex_category.hom_zero_zero SimplexCategory.hom_zero_zero
end
open Simplicial
section Generators
/-!
## Generating maps for the simplex category
TODO: prove that the simplex category is equivalent to
one given by the following generators and relations.
-/
/-- The `i`-th face map from `[n]` to `[n+1]` -/
def δ {n} (i : Fin (n + 2)) : ([n] : SimplexCategory) ⟶ [n + 1] :=
mkHom (Fin.succAboveOrderEmb i).toOrderHom
#align simplex_category.δ SimplexCategory.δ
/-- The `i`-th degeneracy map from `[n+1]` to `[n]` -/
def σ {n} (i : Fin (n + 1)) : ([n + 1] : SimplexCategory) ⟶ [n] :=
mkHom
{ toFun := Fin.predAbove i
monotone' := Fin.predAbove_right_monotone i }
#align simplex_category.σ SimplexCategory.σ
/-- The generic case of the first simplicial identity -/
theorem δ_comp_δ {n} {i j : Fin (n + 2)} (H : i ≤ j) :
δ i ≫ δ j.succ = δ j ≫ δ (Fin.castSucc i) := by
ext k
dsimp [δ, Fin.succAbove]
rcases i with ⟨i, _⟩
rcases j with ⟨j, _⟩
rcases k with ⟨k, _⟩
split_ifs <;> · simp at * <;> omega
#align simplex_category.δ_comp_δ SimplexCategory.δ_comp_δ
theorem δ_comp_δ' {n} {i : Fin (n + 2)} {j : Fin (n + 3)} (H : Fin.castSucc i < j) :
δ i ≫ δ j =
δ (j.pred fun (hj : j = 0) => by simp [hj, Fin.not_lt_zero] at H) ≫
δ (Fin.castSucc i) := by
rw [← δ_comp_δ]
· rw [Fin.succ_pred]
· simpa only [Fin.le_iff_val_le_val, ← Nat.lt_succ_iff, Nat.succ_eq_add_one, ← Fin.val_succ,
j.succ_pred, Fin.lt_iff_val_lt_val] using H
#align simplex_category.δ_comp_δ' SimplexCategory.δ_comp_δ'
theorem δ_comp_δ'' {n} {i : Fin (n + 3)} {j : Fin (n + 2)} (H : i ≤ Fin.castSucc j) :
δ (i.castLT (Nat.lt_of_le_of_lt (Fin.le_iff_val_le_val.mp H) j.is_lt)) ≫ δ j.succ =
δ j ≫ δ i := by
rw [δ_comp_δ]
· rfl
· exact H
#align simplex_category.δ_comp_δ'' SimplexCategory.δ_comp_δ''
/-- The special case of the first simplicial identity -/
@[reassoc]
theorem δ_comp_δ_self {n} {i : Fin (n + 2)} : δ i ≫ δ (Fin.castSucc i) = δ i ≫ δ i.succ :=
(δ_comp_δ (le_refl i)).symm
#align simplex_category.δ_comp_δ_self SimplexCategory.δ_comp_δ_self
@[reassoc]
theorem δ_comp_δ_self' {n} {i : Fin (n + 2)} {j : Fin (n + 3)} (H : j = Fin.castSucc i) :
δ i ≫ δ j = δ i ≫ δ i.succ := by
subst H
rw [δ_comp_δ_self]
#align simplex_category.δ_comp_δ_self' SimplexCategory.δ_comp_δ_self'
/-- The second simplicial identity -/
@[reassoc]
| Mathlib/AlgebraicTopology/SimplexCategory.lean | 272 | 289 | theorem δ_comp_σ_of_le {n} {i : Fin (n + 2)} {j : Fin (n + 1)} (H : i ≤ Fin.castSucc j) :
δ (Fin.castSucc i) ≫ σ j.succ = σ j ≫ δ i := by |
ext k : 3
dsimp [σ, δ]
rcases le_or_lt i k with (hik | hik)
· rw [Fin.succAbove_of_le_castSucc _ _ (Fin.castSucc_le_castSucc_iff.mpr hik),
Fin.succ_predAbove_succ, Fin.succAbove_of_le_castSucc]
rcases le_or_lt k (j.castSucc) with (hjk | hjk)
· rwa [Fin.predAbove_of_le_castSucc _ _ hjk, Fin.castSucc_castPred]
· rw [Fin.le_castSucc_iff, Fin.predAbove_of_castSucc_lt _ _ hjk, Fin.succ_pred]
exact H.trans_lt hjk
· rw [Fin.succAbove_of_castSucc_lt _ _ (Fin.castSucc_lt_castSucc_iff.mpr hik)]
have hjk := H.trans_lt' hik
rw [Fin.predAbove_of_le_castSucc _ _ (Fin.castSucc_le_castSucc_iff.mpr
(hjk.trans (Fin.castSucc_lt_succ _)).le),
Fin.predAbove_of_le_castSucc _ _ hjk.le, Fin.castPred_castSucc, Fin.succAbove_of_castSucc_lt,
Fin.castSucc_castPred]
rwa [Fin.castSucc_castPred]
|
/-
Copyright (c) 2023 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Data.Finset.Pointwise
#align_import combinatorics.additive.e_transform from "leanprover-community/mathlib"@"207c92594599a06e7c134f8d00a030a83e6c7259"
/-!
# e-transforms
e-transforms are a family of transformations of pairs of finite sets that aim to reduce the size
of the sumset while keeping some invariant the same. This file defines a few of them, to be used
as internals of other proofs.
## Main declarations
* `Finset.mulDysonETransform`: The Dyson e-transform. Replaces `(s, t)` by
`(s ∪ e • t, t ∩ e⁻¹ • s)`. The additive version preserves `|s ∩ [1, m]| + |t ∩ [1, m - e]|`.
* `Finset.mulETransformLeft`/`Finset.mulETransformRight`: Replace `(s, t)` by
`(s ∩ s • e, t ∪ e⁻¹ • t)` and `(s ∪ s • e, t ∩ e⁻¹ • t)`. Preserve (together) the sum of
the cardinalities (see `Finset.MulETransform.card`). In particular, one of the two transforms
increases the sum of the cardinalities and the other one decreases it. See
`le_or_lt_of_add_le_add` and around.
## TODO
Prove the invariance property of the Dyson e-transform.
-/
open MulOpposite
open Pointwise
variable {α : Type*} [DecidableEq α]
namespace Finset
/-! ### Dyson e-transform -/
section CommGroup
variable [CommGroup α] (e : α) (x : Finset α × Finset α)
/-- The **Dyson e-transform**. Turns `(s, t)` into `(s ∪ e • t, t ∩ e⁻¹ • s)`. This reduces the
product of the two sets. -/
@[to_additive (attr := simps) "The **Dyson e-transform**.
Turns `(s, t)` into `(s ∪ e +ᵥ t, t ∩ -e +ᵥ s)`. This reduces the sum of the two sets."]
def mulDysonETransform : Finset α × Finset α :=
(x.1 ∪ e • x.2, x.2 ∩ e⁻¹ • x.1)
#align finset.mul_dyson_e_transform Finset.mulDysonETransform
#align finset.add_dyson_e_transform Finset.addDysonETransform
@[to_additive]
theorem mulDysonETransform.subset :
(mulDysonETransform e x).1 * (mulDysonETransform e x).2 ⊆ x.1 * x.2 := by
refine union_mul_inter_subset_union.trans (union_subset Subset.rfl ?_)
rw [mul_smul_comm, smul_mul_assoc, inv_smul_smul, mul_comm]
#align finset.mul_dyson_e_transform.subset Finset.mulDysonETransform.subset
#align finset.add_dyson_e_transform.subset Finset.addDysonETransform.subset
@[to_additive]
theorem mulDysonETransform.card :
(mulDysonETransform e x).1.card + (mulDysonETransform e x).2.card = x.1.card + x.2.card := by
dsimp
rw [← card_smul_finset e (_ ∩ _), smul_finset_inter, smul_inv_smul, inter_comm,
card_union_add_card_inter, card_smul_finset]
#align finset.mul_dyson_e_transform.card Finset.mulDysonETransform.card
#align finset.add_dyson_e_transform.card Finset.addDysonETransform.card
@[to_additive (attr := simp)]
| Mathlib/Combinatorics/Additive/ETransform.lean | 75 | 81 | theorem mulDysonETransform_idem :
mulDysonETransform e (mulDysonETransform e x) = mulDysonETransform e x := by |
ext : 1 <;> dsimp
· rw [smul_finset_inter, smul_inv_smul, inter_comm, union_eq_left]
exact inter_subset_union
· rw [smul_finset_union, inv_smul_smul, union_comm, inter_eq_left]
exact inter_subset_union
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.MvPolynomial.Degrees
#align_import data.mv_polynomial.variables from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Variables of polynomials
This file establishes many results about the variable sets of a multivariate polynomial.
The *variable set* of a polynomial $P \in R[X]$ is a `Finset` containing each $x \in X$
that appears in a monomial in $P$.
## Main declarations
* `MvPolynomial.vars p` : the finset of variables occurring in `p`.
For example if `p = x⁴y+yz` then `vars p = {x, y, z}`
## Notation
As in other polynomial files, we typically use the notation:
+ `σ τ : Type*` (indexing the variables)
+ `R : Type*` `[CommSemiring R]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `r : R`
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ R`
-/
noncomputable section
open Set Function Finsupp AddMonoidAlgebra
universe u v w
variable {R : Type u} {S : Type v}
namespace MvPolynomial
variable {σ τ : Type*} {r : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ}
section CommSemiring
variable [CommSemiring R] {p q : MvPolynomial σ R}
section Vars
/-! ### `vars` -/
/-- `vars p` is the set of variables appearing in the polynomial `p` -/
def vars (p : MvPolynomial σ R) : Finset σ :=
letI := Classical.decEq σ
p.degrees.toFinset
#align mv_polynomial.vars MvPolynomial.vars
theorem vars_def [DecidableEq σ] (p : MvPolynomial σ R) : p.vars = p.degrees.toFinset := by
rw [vars]
convert rfl
#align mv_polynomial.vars_def MvPolynomial.vars_def
@[simp]
theorem vars_0 : (0 : MvPolynomial σ R).vars = ∅ := by
classical rw [vars_def, degrees_zero, Multiset.toFinset_zero]
#align mv_polynomial.vars_0 MvPolynomial.vars_0
@[simp]
theorem vars_monomial (h : r ≠ 0) : (monomial s r).vars = s.support := by
classical rw [vars_def, degrees_monomial_eq _ _ h, Finsupp.toFinset_toMultiset]
#align mv_polynomial.vars_monomial MvPolynomial.vars_monomial
@[simp]
theorem vars_C : (C r : MvPolynomial σ R).vars = ∅ := by
classical rw [vars_def, degrees_C, Multiset.toFinset_zero]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.vars_C MvPolynomial.vars_C
@[simp]
theorem vars_X [Nontrivial R] : (X n : MvPolynomial σ R).vars = {n} := by
rw [X, vars_monomial (one_ne_zero' R), Finsupp.support_single_ne_zero _ (one_ne_zero' ℕ)]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.vars_X MvPolynomial.vars_X
theorem mem_vars (i : σ) : i ∈ p.vars ↔ ∃ d ∈ p.support, i ∈ d.support := by
classical simp only [vars_def, Multiset.mem_toFinset, mem_degrees, mem_support_iff, exists_prop]
#align mv_polynomial.mem_vars MvPolynomial.mem_vars
theorem mem_support_not_mem_vars_zero {f : MvPolynomial σ R} {x : σ →₀ ℕ} (H : x ∈ f.support)
{v : σ} (h : v ∉ vars f) : x v = 0 := by
contrapose! h
exact (mem_vars v).mpr ⟨x, H, Finsupp.mem_support_iff.mpr h⟩
#align mv_polynomial.mem_support_not_mem_vars_zero MvPolynomial.mem_support_not_mem_vars_zero
theorem vars_add_subset [DecidableEq σ] (p q : MvPolynomial σ R) :
(p + q).vars ⊆ p.vars ∪ q.vars := by
intro x hx
simp only [vars_def, Finset.mem_union, Multiset.mem_toFinset] at hx ⊢
simpa using Multiset.mem_of_le (degrees_add _ _) hx
#align mv_polynomial.vars_add_subset MvPolynomial.vars_add_subset
theorem vars_add_of_disjoint [DecidableEq σ] (h : Disjoint p.vars q.vars) :
(p + q).vars = p.vars ∪ q.vars := by
refine (vars_add_subset p q).antisymm fun x hx => ?_
simp only [vars_def, Multiset.disjoint_toFinset] at h hx ⊢
rwa [degrees_add_of_disjoint h, Multiset.toFinset_union]
#align mv_polynomial.vars_add_of_disjoint MvPolynomial.vars_add_of_disjoint
section Mul
theorem vars_mul [DecidableEq σ] (φ ψ : MvPolynomial σ R) : (φ * ψ).vars ⊆ φ.vars ∪ ψ.vars := by
simp_rw [vars_def, ← Multiset.toFinset_add, Multiset.toFinset_subset]
exact Multiset.subset_of_le (degrees_mul φ ψ)
#align mv_polynomial.vars_mul MvPolynomial.vars_mul
@[simp]
theorem vars_one : (1 : MvPolynomial σ R).vars = ∅ :=
vars_C
#align mv_polynomial.vars_one MvPolynomial.vars_one
theorem vars_pow (φ : MvPolynomial σ R) (n : ℕ) : (φ ^ n).vars ⊆ φ.vars := by
classical
induction' n with n ih
· simp
· rw [pow_succ']
apply Finset.Subset.trans (vars_mul _ _)
exact Finset.union_subset (Finset.Subset.refl _) ih
#align mv_polynomial.vars_pow MvPolynomial.vars_pow
/-- The variables of the product of a family of polynomials
are a subset of the union of the sets of variables of each polynomial.
-/
theorem vars_prod {ι : Type*} [DecidableEq σ] {s : Finset ι} (f : ι → MvPolynomial σ R) :
(∏ i ∈ s, f i).vars ⊆ s.biUnion fun i => (f i).vars := by
classical
induction s using Finset.induction_on with
| empty => simp
| insert hs hsub =>
simp only [hs, Finset.biUnion_insert, Finset.prod_insert, not_false_iff]
apply Finset.Subset.trans (vars_mul _ _)
exact Finset.union_subset_union (Finset.Subset.refl _) hsub
#align mv_polynomial.vars_prod MvPolynomial.vars_prod
section IsDomain
variable {A : Type*} [CommRing A] [IsDomain A]
theorem vars_C_mul (a : A) (ha : a ≠ 0) (φ : MvPolynomial σ A) :
(C a * φ : MvPolynomial σ A).vars = φ.vars := by
ext1 i
simp only [mem_vars, exists_prop, mem_support_iff]
apply exists_congr
intro d
apply and_congr _ Iff.rfl
rw [coeff_C_mul, mul_ne_zero_iff, eq_true ha, true_and_iff]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.vars_C_mul MvPolynomial.vars_C_mul
end IsDomain
end Mul
section Sum
variable {ι : Type*} (t : Finset ι) (φ : ι → MvPolynomial σ R)
theorem vars_sum_subset [DecidableEq σ] :
(∑ i ∈ t, φ i).vars ⊆ Finset.biUnion t fun i => (φ i).vars := by
classical
induction t using Finset.induction_on with
| empty => simp
| insert has hsum =>
rw [Finset.biUnion_insert, Finset.sum_insert has]
refine Finset.Subset.trans
(vars_add_subset _ _) (Finset.union_subset_union (Finset.Subset.refl _) ?_)
assumption
#align mv_polynomial.vars_sum_subset MvPolynomial.vars_sum_subset
| Mathlib/Algebra/MvPolynomial/Variables.lean | 192 | 207 | theorem vars_sum_of_disjoint [DecidableEq σ] (h : Pairwise <| (Disjoint on fun i => (φ i).vars)) :
(∑ i ∈ t, φ i).vars = Finset.biUnion t fun i => (φ i).vars := by |
classical
induction t using Finset.induction_on with
| empty => simp
| insert has hsum =>
rw [Finset.biUnion_insert, Finset.sum_insert has, vars_add_of_disjoint, hsum]
unfold Pairwise onFun at h
rw [hsum]
simp only [Finset.disjoint_iff_ne] at h ⊢
intro v hv v2 hv2
rw [Finset.mem_biUnion] at hv2
rcases hv2 with ⟨i, his, hi⟩
refine h ?_ _ hv _ hi
rintro rfl
contradiction
|
/-
Copyright (c) 2023 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.MeasureTheory.Integral.IntegralEqImproper
#align_import measure_theory.integral.peak_function from "leanprover-community/mathlib"@"13b0d72fd8533ba459ac66e9a885e35ffabb32b2"
/-!
# Integrals against peak functions
A sequence of peak functions is a sequence of functions with average one concentrating around
a point `x₀`. Given such a sequence `φₙ`, then `∫ φₙ g` tends to `g x₀` in many situations, with
a whole zoo of possible assumptions on `φₙ` and `g`. This file is devoted to such results. Such
functions are also called approximations of unity, or approximations of identity.
## Main results
* `tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto`: If a sequence of peak
functions `φᵢ` converges uniformly to zero away from a point `x₀`, and
`g` is integrable and continuous at `x₀`, then `∫ φᵢ • g` converges to `g x₀`.
* `tendsto_setIntegral_pow_smul_of_unique_maximum_of_isCompact_of_continuousOn`:
If a continuous function `c` realizes its maximum at a unique point `x₀` in a compact set `s`,
then the sequence of functions `(c x) ^ n / ∫ (c x) ^ n` is a sequence of peak functions
concentrating around `x₀`. Therefore, `∫ (c x) ^ n * g / ∫ (c x) ^ n` converges to `g x₀`
if `g` is continuous on `s`.
* `tendsto_integral_comp_smul_smul_of_integrable`:
If a nonnegative function `φ` has integral one and decays quickly enough at infinity,
then its renormalizations `x ↦ c ^ d * φ (c • x)` form a sequence of peak functions as `c → ∞`.
Therefore, `∫ (c ^ d * φ (c • x)) • g x` converges to `g 0` as `c → ∞` if `g` is continuous
at `0` and integrable.
Note that there are related results about convolution with respect to peak functions in the file
`Analysis.Convolution`, such as `convolution_tendsto_right` there.
-/
open Set Filter MeasureTheory MeasureTheory.Measure TopologicalSpace Metric
open scoped Topology ENNReal
/-!
### General convergent result for integrals against a sequence of peak functions
-/
open Set
variable {α E ι : Type*} {hm : MeasurableSpace α} {μ : Measure α} [TopologicalSpace α]
[BorelSpace α] [NormedAddCommGroup E] [NormedSpace ℝ E] {g : α → E} {l : Filter ι} {x₀ : α}
{s t : Set α} {φ : ι → α → ℝ} {a : E}
/-- If a sequence of peak functions `φᵢ` converges uniformly to zero away from a point `x₀`, and
`g` is integrable and has a limit at `x₀`, then `φᵢ • g` is eventually integrable. -/
theorem integrableOn_peak_smul_of_integrableOn_of_tendsto
(hs : MeasurableSet s) (h'st : t ∈ 𝓝[s] x₀)
(hlφ : ∀ u : Set α, IsOpen u → x₀ ∈ u → TendstoUniformlyOn φ 0 l (s \ u))
(hiφ : Tendsto (fun i ↦ ∫ x in t, φ i x ∂μ) l (𝓝 1))
(h'iφ : ∀ᶠ i in l, AEStronglyMeasurable (φ i) (μ.restrict s))
(hmg : IntegrableOn g s μ) (hcg : Tendsto g (𝓝[s] x₀) (𝓝 a)) :
∀ᶠ i in l, IntegrableOn (fun x => φ i x • g x) s μ := by
obtain ⟨u, u_open, x₀u, ut, hu⟩ :
∃ u, IsOpen u ∧ x₀ ∈ u ∧ s ∩ u ⊆ t ∧ ∀ x ∈ u ∩ s, g x ∈ ball a 1 := by
rcases mem_nhdsWithin.1 (Filter.inter_mem h'st (hcg (ball_mem_nhds _ zero_lt_one)))
with ⟨u, u_open, x₀u, hu⟩
refine ⟨u, u_open, x₀u, ?_, hu.trans inter_subset_right⟩
rw [inter_comm]
exact hu.trans inter_subset_left
rw [tendsto_iff_norm_sub_tendsto_zero] at hiφ
filter_upwards [tendstoUniformlyOn_iff.1 (hlφ u u_open x₀u) 1 zero_lt_one,
(tendsto_order.1 hiφ).2 1 zero_lt_one, h'iφ] with i hi h'i h''i
have I : IntegrableOn (φ i) t μ := .of_integral_ne_zero (fun h ↦ by simp [h] at h'i)
have A : IntegrableOn (fun x => φ i x • g x) (s \ u) μ := by
refine Integrable.smul_of_top_right (hmg.mono diff_subset le_rfl) ?_
apply memℒp_top_of_bound (h''i.mono_set diff_subset) 1
filter_upwards [self_mem_ae_restrict (hs.diff u_open.measurableSet)] with x hx
simpa only [Pi.zero_apply, dist_zero_left] using (hi x hx).le
have B : IntegrableOn (fun x => φ i x • g x) (s ∩ u) μ := by
apply Integrable.smul_of_top_left
· exact IntegrableOn.mono_set I ut
· apply
memℒp_top_of_bound (hmg.mono_set inter_subset_left).aestronglyMeasurable (‖a‖ + 1)
filter_upwards [self_mem_ae_restrict (hs.inter u_open.measurableSet)] with x hx
rw [inter_comm] at hx
exact (norm_lt_of_mem_ball (hu x hx)).le
convert A.union B
simp only [diff_union_inter]
#align integrable_on_peak_smul_of_integrable_on_of_continuous_within_at integrableOn_peak_smul_of_integrableOn_of_tendsto
@[deprecated (since := "2024-02-20")]
alias integrableOn_peak_smul_of_integrableOn_of_continuousWithinAt :=
integrableOn_peak_smul_of_integrableOn_of_tendsto
variable [CompleteSpace E]
/-- If a sequence of peak functions `φᵢ` converges uniformly to zero away from a point `x₀` and its
integral on some finite-measure neighborhood of `x₀` converges to `1`, and `g` is integrable and
has a limit `a` at `x₀`, then `∫ φᵢ • g` converges to `a`.
Auxiliary lemma where one assumes additionally `a = 0`. -/
theorem tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto_aux
(hs : MeasurableSet s) (ht : MeasurableSet t) (hts : t ⊆ s) (h'ts : t ∈ 𝓝[s] x₀)
(hnφ : ∀ᶠ i in l, ∀ x ∈ s, 0 ≤ φ i x)
(hlφ : ∀ u : Set α, IsOpen u → x₀ ∈ u → TendstoUniformlyOn φ 0 l (s \ u))
(hiφ : Tendsto (fun i ↦ ∫ x in t, φ i x ∂μ) l (𝓝 1))
(h'iφ : ∀ᶠ i in l, AEStronglyMeasurable (φ i) (μ.restrict s))
(hmg : IntegrableOn g s μ) (hcg : Tendsto g (𝓝[s] x₀) (𝓝 0)) :
Tendsto (fun i : ι => ∫ x in s, φ i x • g x ∂μ) l (𝓝 0) := by
refine Metric.tendsto_nhds.2 fun ε εpos => ?_
obtain ⟨δ, hδ, δpos, δone⟩ : ∃ δ, (δ * ∫ x in s, ‖g x‖ ∂μ) + 2 * δ < ε ∧ 0 < δ ∧ δ < 1:= by
have A :
Tendsto (fun δ => (δ * ∫ x in s, ‖g x‖ ∂μ) + 2 * δ) (𝓝[>] 0)
(𝓝 ((0 * ∫ x in s, ‖g x‖ ∂μ) + 2 * 0)) := by
apply Tendsto.mono_left _ nhdsWithin_le_nhds
exact (tendsto_id.mul tendsto_const_nhds).add (tendsto_id.const_mul _)
rw [zero_mul, zero_add, mul_zero] at A
have : Ioo (0 : ℝ) 1 ∈ 𝓝[>] 0 := Ioo_mem_nhdsWithin_Ioi ⟨le_rfl, zero_lt_one⟩
rcases (((tendsto_order.1 A).2 ε εpos).and this).exists with ⟨δ, hδ, h'δ⟩
exact ⟨δ, hδ, h'δ.1, h'δ.2⟩
suffices ∀ᶠ i in l, ‖∫ x in s, φ i x • g x ∂μ‖ ≤ (δ * ∫ x in s, ‖g x‖ ∂μ) + 2 * δ by
filter_upwards [this] with i hi
simp only [dist_zero_right]
exact hi.trans_lt hδ
obtain ⟨u, u_open, x₀u, ut, hu⟩ :
∃ u, IsOpen u ∧ x₀ ∈ u ∧ s ∩ u ⊆ t ∧ ∀ x ∈ u ∩ s, g x ∈ ball 0 δ := by
rcases mem_nhdsWithin.1 (Filter.inter_mem h'ts (hcg (ball_mem_nhds _ δpos)))
with ⟨u, u_open, x₀u, hu⟩
refine ⟨u, u_open, x₀u, ?_, hu.trans inter_subset_right⟩
rw [inter_comm]
exact hu.trans inter_subset_left
filter_upwards [tendstoUniformlyOn_iff.1 (hlφ u u_open x₀u) δ δpos,
(tendsto_order.1 (tendsto_iff_norm_sub_tendsto_zero.1 hiφ)).2 δ δpos, hnφ,
integrableOn_peak_smul_of_integrableOn_of_tendsto hs h'ts hlφ hiφ h'iφ hmg hcg]
with i hi h'i hφpos h''i
have I : IntegrableOn (φ i) t μ := by
apply Integrable.of_integral_ne_zero (fun h ↦ ?_)
simp [h] at h'i
linarith
have B : ‖∫ x in s ∩ u, φ i x • g x ∂μ‖ ≤ 2 * δ :=
calc
‖∫ x in s ∩ u, φ i x • g x ∂μ‖ ≤ ∫ x in s ∩ u, ‖φ i x • g x‖ ∂μ :=
norm_integral_le_integral_norm _
_ ≤ ∫ x in s ∩ u, ‖φ i x‖ * δ ∂μ := by
refine setIntegral_mono_on ?_ ?_ (hs.inter u_open.measurableSet) fun x hx => ?_
· exact IntegrableOn.mono_set h''i.norm inter_subset_left
· exact IntegrableOn.mono_set (I.norm.mul_const _) ut
rw [norm_smul]
apply mul_le_mul_of_nonneg_left _ (norm_nonneg _)
rw [inter_comm] at hu
exact (mem_ball_zero_iff.1 (hu x hx)).le
_ ≤ ∫ x in t, ‖φ i x‖ * δ ∂μ := by
apply setIntegral_mono_set
· exact I.norm.mul_const _
· exact eventually_of_forall fun x => mul_nonneg (norm_nonneg _) δpos.le
· exact eventually_of_forall ut
_ = ∫ x in t, φ i x * δ ∂μ := by
apply setIntegral_congr ht fun x hx => ?_
rw [Real.norm_of_nonneg (hφpos _ (hts hx))]
_ = (∫ x in t, φ i x ∂μ) * δ := by rw [integral_mul_right]
_ ≤ 2 * δ := by gcongr; linarith [(le_abs_self _).trans h'i.le]
have C : ‖∫ x in s \ u, φ i x • g x ∂μ‖ ≤ δ * ∫ x in s, ‖g x‖ ∂μ :=
calc
‖∫ x in s \ u, φ i x • g x ∂μ‖ ≤ ∫ x in s \ u, ‖φ i x • g x‖ ∂μ :=
norm_integral_le_integral_norm _
_ ≤ ∫ x in s \ u, δ * ‖g x‖ ∂μ := by
refine setIntegral_mono_on ?_ ?_ (hs.diff u_open.measurableSet) fun x hx => ?_
· exact IntegrableOn.mono_set h''i.norm diff_subset
· exact IntegrableOn.mono_set (hmg.norm.const_mul _) diff_subset
rw [norm_smul]
apply mul_le_mul_of_nonneg_right _ (norm_nonneg _)
simpa only [Pi.zero_apply, dist_zero_left] using (hi x hx).le
_ ≤ δ * ∫ x in s, ‖g x‖ ∂μ := by
rw [integral_mul_left]
apply mul_le_mul_of_nonneg_left (setIntegral_mono_set hmg.norm _ _) δpos.le
· filter_upwards with x using norm_nonneg _
· filter_upwards using diff_subset (s := s) (t := u)
calc
‖∫ x in s, φ i x • g x ∂μ‖ =
‖(∫ x in s \ u, φ i x • g x ∂μ) + ∫ x in s ∩ u, φ i x • g x ∂μ‖ := by
conv_lhs => rw [← diff_union_inter s u]
rw [integral_union disjoint_sdiff_inter (hs.inter u_open.measurableSet)
(h''i.mono_set diff_subset) (h''i.mono_set inter_subset_left)]
_ ≤ ‖∫ x in s \ u, φ i x • g x ∂μ‖ + ‖∫ x in s ∩ u, φ i x • g x ∂μ‖ := norm_add_le _ _
_ ≤ (δ * ∫ x in s, ‖g x‖ ∂μ) + 2 * δ := add_le_add C B
#align tendsto_set_integral_peak_smul_of_integrable_on_of_continuous_within_at_aux tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto_aux
@[deprecated (since := "2024-02-20")]
alias tendsto_setIntegral_peak_smul_of_integrableOn_of_continuousWithinAt_aux :=
tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto_aux
/-- If a sequence of peak functions `φᵢ` converges uniformly to zero away from a point `x₀` and its
integral on some finite-measure neighborhood of `x₀` converges to `1`, and `g` is integrable and
has a limit `a` at `x₀`, then `∫ φᵢ • g` converges to `a`. Version localized to a subset. -/
theorem tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto
(hs : MeasurableSet s) {t : Set α} (ht : MeasurableSet t) (hts : t ⊆ s) (h'ts : t ∈ 𝓝[s] x₀)
(h't : μ t ≠ ∞) (hnφ : ∀ᶠ i in l, ∀ x ∈ s, 0 ≤ φ i x)
(hlφ : ∀ u : Set α, IsOpen u → x₀ ∈ u → TendstoUniformlyOn φ 0 l (s \ u))
(hiφ : Tendsto (fun i ↦ ∫ x in t, φ i x ∂μ) l (𝓝 1))
(h'iφ : ∀ᶠ i in l, AEStronglyMeasurable (φ i) (μ.restrict s))
(hmg : IntegrableOn g s μ) (hcg : Tendsto g (𝓝[s] x₀) (𝓝 a)) :
Tendsto (fun i : ι ↦ ∫ x in s, φ i x • g x ∂μ) l (𝓝 a) := by
let h := g - t.indicator (fun _ ↦ a)
have A : Tendsto (fun i : ι => (∫ x in s, φ i x • h x ∂μ) + (∫ x in t, φ i x ∂μ) • a) l
(𝓝 (0 + (1 : ℝ) • a)) := by
refine Tendsto.add ?_ (Tendsto.smul hiφ tendsto_const_nhds)
apply tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto_aux hs ht hts h'ts
hnφ hlφ hiφ h'iφ
· apply hmg.sub
simp only [integrable_indicator_iff ht, integrableOn_const, ht, Measure.restrict_apply]
right
exact lt_of_le_of_lt (measure_mono inter_subset_left) (h't.lt_top)
· rw [← sub_self a]
apply Tendsto.sub hcg
apply tendsto_const_nhds.congr'
filter_upwards [h'ts] with x hx using by simp [hx]
simp only [one_smul, zero_add] at A
refine Tendsto.congr' ?_ A
filter_upwards [integrableOn_peak_smul_of_integrableOn_of_tendsto hs h'ts
hlφ hiφ h'iφ hmg hcg,
(tendsto_order.1 (tendsto_iff_norm_sub_tendsto_zero.1 hiφ)).2 1 zero_lt_one] with i hi h'i
simp only [h, Pi.sub_apply, smul_sub, ← indicator_smul_apply]
rw [integral_sub hi, setIntegral_indicator ht, inter_eq_right.mpr hts,
integral_smul_const, sub_add_cancel]
rw [integrable_indicator_iff ht]
apply Integrable.smul_const
rw [restrict_restrict ht, inter_eq_left.mpr hts]
exact .of_integral_ne_zero (fun h ↦ by simp [h] at h'i)
#align tendsto_set_integral_peak_smul_of_integrable_on_of_continuous_within_at tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto
@[deprecated (since := "2024-02-20")]
alias tendsto_setIntegral_peak_smul_of_integrableOn_of_continuousWithinAt :=
tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto
/-- If a sequence of peak functions `φᵢ` converges uniformly to zero away from a point `x₀` and its
integral on some finite-measure neighborhood of `x₀` converges to `1`, and `g` is integrable and
has a limit `a` at `x₀`, then `∫ φᵢ • g` converges to `a`. -/
| Mathlib/MeasureTheory/Integral/PeakFunction.lean | 235 | 247 | theorem tendsto_integral_peak_smul_of_integrable_of_tendsto
{t : Set α} (ht : MeasurableSet t) (h'ts : t ∈ 𝓝 x₀)
(h't : μ t ≠ ∞) (hnφ : ∀ᶠ i in l, ∀ x, 0 ≤ φ i x)
(hlφ : ∀ u : Set α, IsOpen u → x₀ ∈ u → TendstoUniformlyOn φ 0 l uᶜ)
(hiφ : Tendsto (fun i ↦ ∫ x in t, φ i x ∂μ) l (𝓝 1))
(h'iφ : ∀ᶠ i in l, AEStronglyMeasurable (φ i) μ)
(hmg : Integrable g μ) (hcg : Tendsto g (𝓝 x₀) (𝓝 a)) :
Tendsto (fun i : ι ↦ ∫ x, φ i x • g x ∂μ) l (𝓝 a) := by |
suffices Tendsto (fun i : ι ↦ ∫ x in univ, φ i x • g x ∂μ) l (𝓝 a) by simpa
exact tendsto_setIntegral_peak_smul_of_integrableOn_of_tendsto MeasurableSet.univ ht (x₀ := x₀)
(subset_univ _) (by simpa [nhdsWithin_univ]) h't (by simpa)
(by simpa [← compl_eq_univ_diff] using hlφ) hiφ
(by simpa) (by simpa) (by simpa [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, Mitchell Lee
-/
import Mathlib.Topology.Algebra.InfiniteSum.Defs
import Mathlib.Data.Fintype.BigOperators
import Mathlib.Topology.Algebra.Monoid
/-!
# Lemmas on infinite sums and products in topological monoids
This file contains many simple lemmas on `tsum`, `HasSum` etc, which are placed here in order to
keep the basic file of definitions as short as possible.
Results requiring a group (rather than monoid) structure on the target should go in `Group.lean`.
-/
noncomputable section
open Filter Finset Function
open scoped Topology
variable {α β γ δ : Type*}
section HasProd
variable [CommMonoid α] [TopologicalSpace α]
variable {f g : β → α} {a b : α} {s : Finset β}
/-- Constant one function has product `1` -/
@[to_additive "Constant zero function has sum `0`"]
theorem hasProd_one : HasProd (fun _ ↦ 1 : β → α) 1 := by simp [HasProd, tendsto_const_nhds]
#align has_sum_zero hasSum_zero
@[to_additive]
theorem hasProd_empty [IsEmpty β] : HasProd f 1 := by
convert @hasProd_one α β _ _
#align has_sum_empty hasSum_empty
@[to_additive]
theorem multipliable_one : Multipliable (fun _ ↦ 1 : β → α) :=
hasProd_one.multipliable
#align summable_zero summable_zero
@[to_additive]
theorem multipliable_empty [IsEmpty β] : Multipliable f :=
hasProd_empty.multipliable
#align summable_empty summable_empty
@[to_additive]
theorem multipliable_congr (hfg : ∀ b, f b = g b) : Multipliable f ↔ Multipliable g :=
iff_of_eq (congr_arg Multipliable <| funext hfg)
#align summable_congr summable_congr
@[to_additive]
theorem Multipliable.congr (hf : Multipliable f) (hfg : ∀ b, f b = g b) : Multipliable g :=
(multipliable_congr hfg).mp hf
#align summable.congr Summable.congr
@[to_additive]
lemma HasProd.congr_fun (hf : HasProd f a) (h : ∀ x : β, g x = f x) : HasProd g a :=
(funext h : g = f) ▸ hf
@[to_additive]
theorem HasProd.hasProd_of_prod_eq {g : γ → α}
(h_eq : ∀ u : Finset γ, ∃ v : Finset β, ∀ v', v ⊆ v' →
∃ u', u ⊆ u' ∧ ∏ x ∈ u', g x = ∏ b ∈ v', f b)
(hf : HasProd g a) : HasProd f a :=
le_trans (map_atTop_finset_prod_le_of_prod_eq h_eq) hf
#align has_sum.has_sum_of_sum_eq HasSum.hasSum_of_sum_eq
@[to_additive]
theorem hasProd_iff_hasProd {g : γ → α}
(h₁ : ∀ u : Finset γ, ∃ v : Finset β, ∀ v', v ⊆ v' →
∃ u', u ⊆ u' ∧ ∏ x ∈ u', g x = ∏ b ∈ v', f b)
(h₂ : ∀ v : Finset β, ∃ u : Finset γ, ∀ u', u ⊆ u' →
∃ v', v ⊆ v' ∧ ∏ b ∈ v', f b = ∏ x ∈ u', g x) :
HasProd f a ↔ HasProd g a :=
⟨HasProd.hasProd_of_prod_eq h₂, HasProd.hasProd_of_prod_eq h₁⟩
#align has_sum_iff_has_sum hasSum_iff_hasSum
@[to_additive]
theorem Function.Injective.multipliable_iff {g : γ → β} (hg : Injective g)
(hf : ∀ x ∉ Set.range g, f x = 1) : Multipliable (f ∘ g) ↔ Multipliable f :=
exists_congr fun _ ↦ hg.hasProd_iff hf
#align function.injective.summable_iff Function.Injective.summable_iff
@[to_additive (attr := simp)] theorem hasProd_extend_one {g : β → γ} (hg : Injective g) :
HasProd (extend g f 1) a ↔ HasProd f a := by
rw [← hg.hasProd_iff, extend_comp hg]
exact extend_apply' _ _
@[to_additive (attr := simp)] theorem multipliable_extend_one {g : β → γ} (hg : Injective g) :
Multipliable (extend g f 1) ↔ Multipliable f :=
exists_congr fun _ ↦ hasProd_extend_one hg
@[to_additive]
theorem hasProd_subtype_iff_mulIndicator {s : Set β} :
HasProd (f ∘ (↑) : s → α) a ↔ HasProd (s.mulIndicator f) a := by
rw [← Set.mulIndicator_range_comp, Subtype.range_coe,
hasProd_subtype_iff_of_mulSupport_subset Set.mulSupport_mulIndicator_subset]
#align has_sum_subtype_iff_indicator hasSum_subtype_iff_indicator
@[to_additive]
theorem multipliable_subtype_iff_mulIndicator {s : Set β} :
Multipliable (f ∘ (↑) : s → α) ↔ Multipliable (s.mulIndicator f) :=
exists_congr fun _ ↦ hasProd_subtype_iff_mulIndicator
#align summable_subtype_iff_indicator summable_subtype_iff_indicator
@[to_additive (attr := simp)]
theorem hasProd_subtype_mulSupport : HasProd (f ∘ (↑) : mulSupport f → α) a ↔ HasProd f a :=
hasProd_subtype_iff_of_mulSupport_subset <| Set.Subset.refl _
#align has_sum_subtype_support hasSum_subtype_support
@[to_additive]
protected theorem Finset.multipliable (s : Finset β) (f : β → α) :
Multipliable (f ∘ (↑) : (↑s : Set β) → α) :=
(s.hasProd f).multipliable
#align finset.summable Finset.summable
@[to_additive]
protected theorem Set.Finite.multipliable {s : Set β} (hs : s.Finite) (f : β → α) :
Multipliable (f ∘ (↑) : s → α) := by
have := hs.toFinset.multipliable f
rwa [hs.coe_toFinset] at this
#align set.finite.summable Set.Finite.summable
@[to_additive]
theorem multipliable_of_finite_mulSupport (h : (mulSupport f).Finite) : Multipliable f := by
apply multipliable_of_ne_finset_one (s := h.toFinset); simp
@[to_additive]
theorem hasProd_single {f : β → α} (b : β) (hf : ∀ (b') (_ : b' ≠ b), f b' = 1) : HasProd f (f b) :=
suffices HasProd f (∏ b' ∈ {b}, f b') by simpa using this
hasProd_prod_of_ne_finset_one <| by simpa [hf]
#align has_sum_single hasSum_single
@[to_additive (attr := simp)] lemma hasProd_unique [Unique β] (f : β → α) : HasProd f (f default) :=
hasProd_single default (fun _ hb ↦ False.elim <| hb <| Unique.uniq ..)
@[to_additive (attr := simp)]
lemma hasProd_singleton (m : β) (f : β → α) : HasProd (({m} : Set β).restrict f) (f m) :=
hasProd_unique (Set.restrict {m} f)
@[to_additive]
theorem hasProd_ite_eq (b : β) [DecidablePred (· = b)] (a : α) :
HasProd (fun b' ↦ if b' = b then a else 1) a := by
convert @hasProd_single _ _ _ _ (fun b' ↦ if b' = b then a else 1) b (fun b' hb' ↦ if_neg hb')
exact (if_pos rfl).symm
#align has_sum_ite_eq hasSum_ite_eq
@[to_additive]
theorem Equiv.hasProd_iff (e : γ ≃ β) : HasProd (f ∘ e) a ↔ HasProd f a :=
e.injective.hasProd_iff <| by simp
#align equiv.has_sum_iff Equiv.hasSum_iff
@[to_additive]
theorem Function.Injective.hasProd_range_iff {g : γ → β} (hg : Injective g) :
HasProd (fun x : Set.range g ↦ f x) a ↔ HasProd (f ∘ g) a :=
(Equiv.ofInjective g hg).hasProd_iff.symm
#align function.injective.has_sum_range_iff Function.Injective.hasSum_range_iff
@[to_additive]
theorem Equiv.multipliable_iff (e : γ ≃ β) : Multipliable (f ∘ e) ↔ Multipliable f :=
exists_congr fun _ ↦ e.hasProd_iff
#align equiv.summable_iff Equiv.summable_iff
@[to_additive]
theorem Equiv.hasProd_iff_of_mulSupport {g : γ → α} (e : mulSupport f ≃ mulSupport g)
(he : ∀ x : mulSupport f, g (e x) = f x) : HasProd f a ↔ HasProd g a := by
have : (g ∘ (↑)) ∘ e = f ∘ (↑) := funext he
rw [← hasProd_subtype_mulSupport, ← this, e.hasProd_iff, hasProd_subtype_mulSupport]
#align equiv.has_sum_iff_of_support Equiv.hasSum_iff_of_support
@[to_additive]
theorem hasProd_iff_hasProd_of_ne_one_bij {g : γ → α} (i : mulSupport g → β)
(hi : Injective i) (hf : mulSupport f ⊆ Set.range i)
(hfg : ∀ x, f (i x) = g x) : HasProd f a ↔ HasProd g a :=
Iff.symm <|
Equiv.hasProd_iff_of_mulSupport
(Equiv.ofBijective (fun x ↦ ⟨i x, fun hx ↦ x.coe_prop <| hfg x ▸ hx⟩)
⟨fun _ _ h ↦ hi <| Subtype.ext_iff.1 h, fun y ↦
(hf y.coe_prop).imp fun _ hx ↦ Subtype.ext hx⟩)
hfg
#align has_sum_iff_has_sum_of_ne_zero_bij hasSum_iff_hasSum_of_ne_zero_bij
@[to_additive]
theorem Equiv.multipliable_iff_of_mulSupport {g : γ → α} (e : mulSupport f ≃ mulSupport g)
(he : ∀ x : mulSupport f, g (e x) = f x) : Multipliable f ↔ Multipliable g :=
exists_congr fun _ ↦ e.hasProd_iff_of_mulSupport he
#align equiv.summable_iff_of_support Equiv.summable_iff_of_support
@[to_additive]
protected theorem HasProd.map [CommMonoid γ] [TopologicalSpace γ] (hf : HasProd f a) {G}
[FunLike G α γ] [MonoidHomClass G α γ] (g : G) (hg : Continuous g) :
HasProd (g ∘ f) (g a) := by
have : (g ∘ fun s : Finset β ↦ ∏ b ∈ s, f b) = fun s : Finset β ↦ ∏ b ∈ s, (g ∘ f) b :=
funext <| map_prod g _
unfold HasProd
rw [← this]
exact (hg.tendsto a).comp hf
#align has_sum.map HasSum.map
@[to_additive]
protected theorem Inducing.hasProd_iff [CommMonoid γ] [TopologicalSpace γ] {G}
[FunLike G α γ] [MonoidHomClass G α γ] {g : G} (hg : Inducing g) (f : β → α) (a : α) :
HasProd (g ∘ f) (g a) ↔ HasProd f a := by
simp_rw [HasProd, comp_apply, ← map_prod]
exact hg.tendsto_nhds_iff.symm
@[to_additive]
protected theorem Multipliable.map [CommMonoid γ] [TopologicalSpace γ] (hf : Multipliable f) {G}
[FunLike G α γ] [MonoidHomClass G α γ] (g : G) (hg : Continuous g) : Multipliable (g ∘ f) :=
(hf.hasProd.map g hg).multipliable
#align summable.map Summable.map
@[to_additive]
protected theorem Multipliable.map_iff_of_leftInverse [CommMonoid γ] [TopologicalSpace γ] {G G'}
[FunLike G α γ] [MonoidHomClass G α γ] [FunLike G' γ α] [MonoidHomClass G' γ α]
(g : G) (g' : G') (hg : Continuous g) (hg' : Continuous g') (hinv : Function.LeftInverse g' g) :
Multipliable (g ∘ f) ↔ Multipliable f :=
⟨fun h ↦ by
have := h.map _ hg'
rwa [← Function.comp.assoc, hinv.id] at this, fun h ↦ h.map _ hg⟩
#align summable.map_iff_of_left_inverse Summable.map_iff_of_leftInverse
@[to_additive]
theorem Multipliable.map_tprod [CommMonoid γ] [TopologicalSpace γ] [T2Space γ] (hf : Multipliable f)
{G} [FunLike G α γ] [MonoidHomClass G α γ] (g : G) (hg : Continuous g) :
g (∏' i, f i) = ∏' i, g (f i) := (HasProd.tprod_eq (HasProd.map hf.hasProd g hg)).symm
@[to_additive]
theorem Inducing.multipliable_iff_tprod_comp_mem_range [CommMonoid γ] [TopologicalSpace γ]
[T2Space γ] {G} [FunLike G α γ] [MonoidHomClass G α γ] {g : G} (hg : Inducing g) (f : β → α) :
Multipliable f ↔ Multipliable (g ∘ f) ∧ ∏' i, g (f i) ∈ Set.range g := by
constructor
· intro hf
constructor
· exact hf.map g hg.continuous
· use ∏' i, f i
exact hf.map_tprod g hg.continuous
· rintro ⟨hgf, a, ha⟩
use a
have := hgf.hasProd
simp_rw [comp_apply, ← ha] at this
exact (hg.hasProd_iff f a).mp this
/-- "A special case of `Multipliable.map_iff_of_leftInverse` for convenience" -/
@[to_additive "A special case of `Summable.map_iff_of_leftInverse` for convenience"]
protected theorem Multipliable.map_iff_of_equiv [CommMonoid γ] [TopologicalSpace γ] {G}
[EquivLike G α γ] [MulEquivClass G α γ] (g : G) (hg : Continuous g)
(hg' : Continuous (EquivLike.inv g : γ → α)) : Multipliable (g ∘ f) ↔ Multipliable f :=
Multipliable.map_iff_of_leftInverse g (g : α ≃* γ).symm hg hg' (EquivLike.left_inv g)
#align summable.map_iff_of_equiv Summable.map_iff_of_equiv
@[to_additive]
theorem Function.Surjective.multipliable_iff_of_hasProd_iff {α' : Type*} [CommMonoid α']
[TopologicalSpace α'] {e : α' → α} (hes : Function.Surjective e) {f : β → α} {g : γ → α'}
(he : ∀ {a}, HasProd f (e a) ↔ HasProd g a) : Multipliable f ↔ Multipliable g :=
hes.exists.trans <| exists_congr <| @he
#align function.surjective.summable_iff_of_has_sum_iff Function.Surjective.summable_iff_of_hasSum_iff
variable [ContinuousMul α]
@[to_additive]
theorem HasProd.mul (hf : HasProd f a) (hg : HasProd g b) :
HasProd (fun b ↦ f b * g b) (a * b) := by
dsimp only [HasProd] at hf hg ⊢
simp_rw [prod_mul_distrib]
exact hf.mul hg
#align has_sum.add HasSum.add
@[to_additive]
theorem Multipliable.mul (hf : Multipliable f) (hg : Multipliable g) :
Multipliable fun b ↦ f b * g b :=
(hf.hasProd.mul hg.hasProd).multipliable
#align summable.add Summable.add
@[to_additive]
theorem hasProd_prod {f : γ → β → α} {a : γ → α} {s : Finset γ} :
(∀ i ∈ s, HasProd (f i) (a i)) → HasProd (fun b ↦ ∏ i ∈ s, f i b) (∏ i ∈ s, a i) := by
classical
exact Finset.induction_on s (by simp only [hasProd_one, prod_empty, forall_true_iff]) <| by
-- Porting note: with some help, `simp` used to be able to close the goal
simp (config := { contextual := true }) only [mem_insert, forall_eq_or_imp, not_false_iff,
prod_insert, and_imp]
exact fun x s _ IH hx h ↦ hx.mul (IH h)
#align has_sum_sum hasSum_sum
@[to_additive]
theorem multipliable_prod {f : γ → β → α} {s : Finset γ} (hf : ∀ i ∈ s, Multipliable (f i)) :
Multipliable fun b ↦ ∏ i ∈ s, f i b :=
(hasProd_prod fun i hi ↦ (hf i hi).hasProd).multipliable
#align summable_sum summable_sum
@[to_additive]
theorem HasProd.mul_disjoint {s t : Set β} (hs : Disjoint s t) (ha : HasProd (f ∘ (↑) : s → α) a)
(hb : HasProd (f ∘ (↑) : t → α) b) : HasProd (f ∘ (↑) : (s ∪ t : Set β) → α) (a * b) := by
rw [hasProd_subtype_iff_mulIndicator] at *
rw [Set.mulIndicator_union_of_disjoint hs]
exact ha.mul hb
#align has_sum.add_disjoint HasSum.add_disjoint
@[to_additive]
theorem hasProd_prod_disjoint {ι} (s : Finset ι) {t : ι → Set β} {a : ι → α}
(hs : (s : Set ι).Pairwise (Disjoint on t)) (hf : ∀ i ∈ s, HasProd (f ∘ (↑) : t i → α) (a i)) :
HasProd (f ∘ (↑) : (⋃ i ∈ s, t i) → α) (∏ i ∈ s, a i) := by
simp_rw [hasProd_subtype_iff_mulIndicator] at *
rw [Finset.mulIndicator_biUnion _ _ hs]
exact hasProd_prod hf
#align has_sum_sum_disjoint hasSum_sum_disjoint
@[to_additive]
theorem HasProd.mul_isCompl {s t : Set β} (hs : IsCompl s t) (ha : HasProd (f ∘ (↑) : s → α) a)
(hb : HasProd (f ∘ (↑) : t → α) b) : HasProd f (a * b) := by
simpa [← hs.compl_eq] using
(hasProd_subtype_iff_mulIndicator.1 ha).mul (hasProd_subtype_iff_mulIndicator.1 hb)
#align has_sum.add_is_compl HasSum.add_isCompl
@[to_additive]
theorem HasProd.mul_compl {s : Set β} (ha : HasProd (f ∘ (↑) : s → α) a)
(hb : HasProd (f ∘ (↑) : (sᶜ : Set β) → α) b) : HasProd f (a * b) :=
ha.mul_isCompl isCompl_compl hb
#align has_sum.add_compl HasSum.add_compl
@[to_additive]
theorem Multipliable.mul_compl {s : Set β} (hs : Multipliable (f ∘ (↑) : s → α))
(hsc : Multipliable (f ∘ (↑) : (sᶜ : Set β) → α)) : Multipliable f :=
(hs.hasProd.mul_compl hsc.hasProd).multipliable
#align summable.add_compl Summable.add_compl
@[to_additive]
theorem HasProd.compl_mul {s : Set β} (ha : HasProd (f ∘ (↑) : (sᶜ : Set β) → α) a)
(hb : HasProd (f ∘ (↑) : s → α) b) : HasProd f (a * b) :=
ha.mul_isCompl isCompl_compl.symm hb
#align has_sum.compl_add HasSum.compl_add
@[to_additive]
theorem Multipliable.compl_add {s : Set β} (hs : Multipliable (f ∘ (↑) : (sᶜ : Set β) → α))
(hsc : Multipliable (f ∘ (↑) : s → α)) : Multipliable f :=
(hs.hasProd.compl_mul hsc.hasProd).multipliable
#align summable.compl_add Summable.compl_add
/-- Version of `HasProd.update` for `CommMonoid` rather than `CommGroup`.
Rather than showing that `f.update` has a specific product in terms of `HasProd`,
it gives a relationship between the products of `f` and `f.update` given that both exist. -/
@[to_additive "Version of `HasSum.update` for `AddCommMonoid` rather than `AddCommGroup`.
Rather than showing that `f.update` has a specific sum in terms of `HasSum`,
it gives a relationship between the sums of `f` and `f.update` given that both exist."]
theorem HasProd.update' {α β : Type*} [TopologicalSpace α] [CommMonoid α] [T2Space α]
[ContinuousMul α] [DecidableEq β] {f : β → α} {a a' : α} (hf : HasProd f a) (b : β) (x : α)
(hf' : HasProd (update f b x) a') : a * x = a' * f b := by
have : ∀ b', f b' * ite (b' = b) x 1 = update f b x b' * ite (b' = b) (f b) 1 := by
intro b'
split_ifs with hb'
· simpa only [Function.update_apply, hb', eq_self_iff_true] using mul_comm (f b) x
· simp only [Function.update_apply, hb', if_false]
have h := hf.mul (hasProd_ite_eq b x)
simp_rw [this] at h
exact HasProd.unique h (hf'.mul (hasProd_ite_eq b (f b)))
#align has_sum.update' HasSum.update'
/-- Version of `hasProd_ite_div_hasProd` for `CommMonoid` rather than `CommGroup`.
Rather than showing that the `ite` expression has a specific product in terms of `HasProd`, it gives
a relationship between the products of `f` and `ite (n = b) 0 (f n)` given that both exist. -/
@[to_additive "Version of `hasSum_ite_sub_hasSum` for `AddCommMonoid` rather than `AddCommGroup`.
Rather than showing that the `ite` expression has a specific sum in terms of `HasSum`,
it gives a relationship between the sums of `f` and `ite (n = b) 0 (f n)` given that both exist."]
theorem eq_mul_of_hasProd_ite {α β : Type*} [TopologicalSpace α] [CommMonoid α] [T2Space α]
[ContinuousMul α] [DecidableEq β] {f : β → α} {a : α} (hf : HasProd f a) (b : β) (a' : α)
(hf' : HasProd (fun n ↦ ite (n = b) 1 (f n)) a') : a = a' * f b := by
refine (mul_one a).symm.trans (hf.update' b 1 ?_)
convert hf'
apply update_apply
#align eq_add_of_has_sum_ite eq_add_of_hasSum_ite
end HasProd
section tprod
variable [CommMonoid α] [TopologicalSpace α] {f g : β → α} {a a₁ a₂ : α}
@[to_additive]
theorem tprod_congr_set_coe (f : β → α) {s t : Set β} (h : s = t) :
∏' x : s, f x = ∏' x : t, f x := by rw [h]
#align tsum_congr_subtype tsum_congr_set_coe
@[to_additive]
theorem tprod_congr_subtype (f : β → α) {P Q : β → Prop} (h : ∀ x, P x ↔ Q x) :
∏' x : {x // P x}, f x = ∏' x : {x // Q x}, f x :=
tprod_congr_set_coe f <| Set.ext h
@[to_additive]
theorem tprod_eq_finprod (hf : (mulSupport f).Finite) :
∏' b, f b = ∏ᶠ b, f b := by simp [tprod_def, multipliable_of_finite_mulSupport hf, hf]
@[to_additive]
theorem tprod_eq_prod' {s : Finset β} (hf : mulSupport f ⊆ s) :
∏' b, f b = ∏ b ∈ s, f b := by
rw [tprod_eq_finprod (s.finite_toSet.subset hf), finprod_eq_prod_of_mulSupport_subset _ hf]
@[to_additive]
theorem tprod_eq_prod {s : Finset β} (hf : ∀ b ∉ s, f b = 1) :
∏' b, f b = ∏ b ∈ s, f b :=
tprod_eq_prod' <| mulSupport_subset_iff'.2 hf
#align tsum_eq_sum tsum_eq_sum
@[to_additive (attr := simp)]
theorem tprod_one : ∏' _ : β, (1 : α) = 1 := by rw [tprod_eq_finprod] <;> simp
#align tsum_zero tsum_zero
#align tsum_zero' tsum_zero
@[to_additive (attr := simp)]
theorem tprod_empty [IsEmpty β] : ∏' b, f b = 1 := by
rw [tprod_eq_prod (s := (∅ : Finset β))] <;> simp
#align tsum_empty tsum_empty
@[to_additive]
theorem tprod_congr {f g : β → α}
(hfg : ∀ b, f b = g b) : ∏' b, f b = ∏' b, g b :=
congr_arg tprod (funext hfg)
#align tsum_congr tsum_congr
@[to_additive]
theorem tprod_fintype [Fintype β] (f : β → α) : ∏' b, f b = ∏ b, f b := by
apply tprod_eq_prod; simp
#align tsum_fintype tsum_fintype
@[to_additive]
theorem prod_eq_tprod_mulIndicator (f : β → α) (s : Finset β) :
∏ x ∈ s, f x = ∏' x, Set.mulIndicator (↑s) f x := by
rw [tprod_eq_prod' (Set.mulSupport_mulIndicator_subset),
Finset.prod_mulIndicator_subset _ Finset.Subset.rfl]
#align sum_eq_tsum_indicator sum_eq_tsum_indicator
@[to_additive]
theorem tprod_bool (f : Bool → α) : ∏' i : Bool, f i = f false * f true := by
rw [tprod_fintype, Fintype.prod_bool, mul_comm]
#align tsum_bool tsum_bool
@[to_additive]
theorem tprod_eq_mulSingle {f : β → α} (b : β) (hf : ∀ b' ≠ b, f b' = 1) :
∏' b, f b = f b := by
rw [tprod_eq_prod (s := {b}), prod_singleton]
exact fun b' hb' ↦ hf b' (by simpa using hb')
#align tsum_eq_single tsum_eq_single
@[to_additive]
theorem tprod_tprod_eq_mulSingle (f : β → γ → α) (b : β) (c : γ) (hfb : ∀ b' ≠ b, f b' c = 1)
(hfc : ∀ b', ∀ c' ≠ c, f b' c' = 1) : ∏' (b') (c'), f b' c' = f b c :=
calc
∏' (b') (c'), f b' c' = ∏' b', f b' c := tprod_congr fun b' ↦ tprod_eq_mulSingle _ (hfc b')
_ = f b c := tprod_eq_mulSingle _ hfb
#align tsum_tsum_eq_single tsum_tsum_eq_single
@[to_additive (attr := simp)]
theorem tprod_ite_eq (b : β) [DecidablePred (· = b)] (a : α) :
∏' b', (if b' = b then a else 1) = a := by
rw [tprod_eq_mulSingle b]
· simp
· intro b' hb'; simp [hb']
#align tsum_ite_eq tsum_ite_eq
-- Porting note: Added nolint simpNF, simpNF falsely claims that lhs does not simplify under simp
@[to_additive (attr := simp, nolint simpNF)]
theorem Finset.tprod_subtype (s : Finset β) (f : β → α) :
∏' x : { x // x ∈ s }, f x = ∏ x ∈ s, f x := by
rw [← prod_attach]; exact tprod_fintype _
#align finset.tsum_subtype Finset.tsum_subtype
@[to_additive]
| Mathlib/Topology/Algebra/InfiniteSum/Basic.lean | 475 | 476 | theorem Finset.tprod_subtype' (s : Finset β) (f : β → α) :
∏' x : (s : Set β), f x = ∏ x ∈ s, f x := by | simp
|
/-
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.SpecialFunctions.Complex.Circle
import Mathlib.Geometry.Euclidean.Angle.Oriented.Basic
#align_import geometry.euclidean.angle.oriented.rotation from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Rotations by oriented angles.
This file defines rotations by oriented angles in real inner product spaces.
## Main definitions
* `Orientation.rotation` is the rotation by an oriented angle with respect to an orientation.
-/
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 "J" => o.rightAngleRotation
/-- Auxiliary construction to build a rotation by the oriented angle `θ`. -/
def rotationAux (θ : Real.Angle) : V →ₗᵢ[ℝ] V :=
LinearMap.isometryOfInner
(Real.Angle.cos θ • LinearMap.id +
Real.Angle.sin θ • (LinearIsometryEquiv.toLinearEquiv J).toLinearMap)
(by
intro x y
simp only [RCLike.conj_to_real, id, LinearMap.smul_apply, LinearMap.add_apply,
LinearMap.id_coe, LinearEquiv.coe_coe, LinearIsometryEquiv.coe_toLinearEquiv,
Orientation.areaForm_rightAngleRotation_left, Orientation.inner_rightAngleRotation_left,
Orientation.inner_rightAngleRotation_right, inner_add_left, inner_smul_left,
inner_add_right, inner_smul_right]
linear_combination inner (𝕜 := ℝ) x y * θ.cos_sq_add_sin_sq)
#align orientation.rotation_aux Orientation.rotationAux
@[simp]
theorem rotationAux_apply (θ : Real.Angle) (x : V) :
o.rotationAux θ x = Real.Angle.cos θ • x + Real.Angle.sin θ • J x :=
rfl
#align orientation.rotation_aux_apply Orientation.rotationAux_apply
/-- A rotation by the oriented angle `θ`. -/
def rotation (θ : Real.Angle) : V ≃ₗᵢ[ℝ] V :=
LinearIsometryEquiv.ofLinearIsometry (o.rotationAux θ)
(Real.Angle.cos θ • LinearMap.id -
Real.Angle.sin θ • (LinearIsometryEquiv.toLinearEquiv J).toLinearMap)
(by
ext x
convert congr_arg (fun t : ℝ => t • x) θ.cos_sq_add_sin_sq using 1
· simp only [o.rightAngleRotation_rightAngleRotation, o.rotationAux_apply,
Function.comp_apply, id, LinearEquiv.coe_coe, LinearIsometry.coe_toLinearMap,
LinearIsometryEquiv.coe_toLinearEquiv, map_smul, map_sub, LinearMap.coe_comp,
LinearMap.id_coe, LinearMap.smul_apply, LinearMap.sub_apply, ← mul_smul, add_smul,
smul_add, smul_neg, smul_sub, mul_comm, sq]
abel
· simp)
(by
ext x
convert congr_arg (fun t : ℝ => t • x) θ.cos_sq_add_sin_sq using 1
· simp only [o.rightAngleRotation_rightAngleRotation, o.rotationAux_apply,
Function.comp_apply, id, LinearEquiv.coe_coe, LinearIsometry.coe_toLinearMap,
LinearIsometryEquiv.coe_toLinearEquiv, map_add, map_smul, LinearMap.coe_comp,
LinearMap.id_coe, LinearMap.smul_apply, LinearMap.sub_apply,
add_smul, smul_neg, smul_sub, smul_smul]
ring_nf
abel
· simp)
#align orientation.rotation Orientation.rotation
theorem rotation_apply (θ : Real.Angle) (x : V) :
o.rotation θ x = Real.Angle.cos θ • x + Real.Angle.sin θ • J x :=
rfl
#align orientation.rotation_apply Orientation.rotation_apply
theorem rotation_symm_apply (θ : Real.Angle) (x : V) :
(o.rotation θ).symm x = Real.Angle.cos θ • x - Real.Angle.sin θ • J x :=
rfl
#align orientation.rotation_symm_apply Orientation.rotation_symm_apply
theorem rotation_eq_matrix_toLin (θ : Real.Angle) {x : V} (hx : x ≠ 0) :
(o.rotation θ).toLinearMap =
Matrix.toLin (o.basisRightAngleRotation x hx) (o.basisRightAngleRotation x hx)
!![θ.cos, -θ.sin; θ.sin, θ.cos] := by
apply (o.basisRightAngleRotation x hx).ext
intro i
fin_cases i
· rw [Matrix.toLin_self]
simp [rotation_apply, Fin.sum_univ_succ]
· rw [Matrix.toLin_self]
simp [rotation_apply, Fin.sum_univ_succ, add_comm]
#align orientation.rotation_eq_matrix_to_lin Orientation.rotation_eq_matrix_toLin
/-- The determinant of `rotation` (as a linear map) is equal to `1`. -/
@[simp]
theorem det_rotation (θ : Real.Angle) : LinearMap.det (o.rotation θ).toLinearMap = 1 := by
haveI : Nontrivial V :=
FiniteDimensional.nontrivial_of_finrank_eq_succ (@Fact.out (finrank ℝ V = 2) _)
obtain ⟨x, hx⟩ : ∃ x, x ≠ (0 : V) := exists_ne (0 : V)
rw [o.rotation_eq_matrix_toLin θ hx]
simpa [sq] using θ.cos_sq_add_sin_sq
#align orientation.det_rotation Orientation.det_rotation
/-- The determinant of `rotation` (as a linear equiv) is equal to `1`. -/
@[simp]
theorem linearEquiv_det_rotation (θ : Real.Angle) :
LinearEquiv.det (o.rotation θ).toLinearEquiv = 1 :=
Units.ext <| by
-- Porting note: Lean can't see through `LinearEquiv.coe_det` and needed the rewrite
-- in mathlib3 this was just `units.ext <| o.det_rotation θ`
simpa only [LinearEquiv.coe_det, Units.val_one] using o.det_rotation θ
#align orientation.linear_equiv_det_rotation Orientation.linearEquiv_det_rotation
/-- The inverse of `rotation` is rotation by the negation of the angle. -/
@[simp]
theorem rotation_symm (θ : Real.Angle) : (o.rotation θ).symm = o.rotation (-θ) := by
ext; simp [o.rotation_apply, o.rotation_symm_apply, sub_eq_add_neg]
#align orientation.rotation_symm Orientation.rotation_symm
/-- Rotation by 0 is the identity. -/
@[simp]
theorem rotation_zero : o.rotation 0 = LinearIsometryEquiv.refl ℝ V := by ext; simp [rotation]
#align orientation.rotation_zero Orientation.rotation_zero
/-- Rotation by π is negation. -/
@[simp]
theorem rotation_pi : o.rotation π = LinearIsometryEquiv.neg ℝ := by
ext x
simp [rotation]
#align orientation.rotation_pi Orientation.rotation_pi
/-- Rotation by π is negation. -/
theorem rotation_pi_apply (x : V) : o.rotation π x = -x := by simp
#align orientation.rotation_pi_apply Orientation.rotation_pi_apply
/-- Rotation by π / 2 is the "right-angle-rotation" map `J`. -/
theorem rotation_pi_div_two : o.rotation (π / 2 : ℝ) = J := by
ext x
simp [rotation]
#align orientation.rotation_pi_div_two Orientation.rotation_pi_div_two
/-- Rotating twice is equivalent to rotating by the sum of the angles. -/
@[simp]
theorem rotation_rotation (θ₁ θ₂ : Real.Angle) (x : V) :
o.rotation θ₁ (o.rotation θ₂ x) = o.rotation (θ₁ + θ₂) x := by
simp only [o.rotation_apply, ← mul_smul, Real.Angle.cos_add, Real.Angle.sin_add, add_smul,
sub_smul, LinearIsometryEquiv.trans_apply, smul_add, LinearIsometryEquiv.map_add,
LinearIsometryEquiv.map_smul, rightAngleRotation_rightAngleRotation, smul_neg]
ring_nf
abel
#align orientation.rotation_rotation Orientation.rotation_rotation
/-- Rotating twice is equivalent to rotating by the sum of the angles. -/
@[simp]
theorem rotation_trans (θ₁ θ₂ : Real.Angle) :
(o.rotation θ₁).trans (o.rotation θ₂) = o.rotation (θ₂ + θ₁) :=
LinearIsometryEquiv.ext fun _ => by rw [← rotation_rotation, LinearIsometryEquiv.trans_apply]
#align orientation.rotation_trans Orientation.rotation_trans
/-- Rotating the first of two vectors by `θ` scales their Kahler form by `cos θ - sin θ * I`. -/
@[simp]
theorem kahler_rotation_left (x y : V) (θ : Real.Angle) :
o.kahler (o.rotation θ x) y = conj (θ.expMapCircle : ℂ) * o.kahler x y := by
-- Porting note: this needed the `Complex.conj_ofReal` instead of `RCLike.conj_ofReal`;
-- I believe this is because the respective coercions are no longer defeq, and
-- `Real.Angle.coe_expMapCircle` uses the `Complex` version.
simp only [o.rotation_apply, map_add, map_mul, LinearMap.map_smulₛₗ, RingHom.id_apply,
LinearMap.add_apply, LinearMap.smul_apply, real_smul, kahler_rightAngleRotation_left,
Real.Angle.coe_expMapCircle, Complex.conj_ofReal, conj_I]
ring
#align orientation.kahler_rotation_left Orientation.kahler_rotation_left
/-- Negating a rotation is equivalent to rotation by π plus the angle. -/
theorem neg_rotation (θ : Real.Angle) (x : V) : -o.rotation θ x = o.rotation (π + θ) x := by
rw [← o.rotation_pi_apply, rotation_rotation]
#align orientation.neg_rotation Orientation.neg_rotation
/-- Negating a rotation by -π / 2 is equivalent to rotation by π / 2. -/
@[simp]
theorem neg_rotation_neg_pi_div_two (x : V) :
-o.rotation (-π / 2 : ℝ) x = o.rotation (π / 2 : ℝ) x := by
rw [neg_rotation, ← Real.Angle.coe_add, neg_div, ← sub_eq_add_neg, sub_half]
#align orientation.neg_rotation_neg_pi_div_two Orientation.neg_rotation_neg_pi_div_two
/-- Negating a rotation by π / 2 is equivalent to rotation by -π / 2. -/
theorem neg_rotation_pi_div_two (x : V) : -o.rotation (π / 2 : ℝ) x = o.rotation (-π / 2 : ℝ) x :=
(neg_eq_iff_eq_neg.mp <| o.neg_rotation_neg_pi_div_two _).symm
#align orientation.neg_rotation_pi_div_two Orientation.neg_rotation_pi_div_two
/-- Rotating the first of two vectors by `θ` scales their Kahler form by `cos (-θ) + sin (-θ) * I`.
-/
| Mathlib/Geometry/Euclidean/Angle/Oriented/Rotation.lean | 210 | 212 | theorem kahler_rotation_left' (x y : V) (θ : Real.Angle) :
o.kahler (o.rotation θ x) y = (-θ).expMapCircle * o.kahler x y := by |
simp only [Real.Angle.expMapCircle_neg, coe_inv_circle_eq_conj, kahler_rotation_left]
|
/-
Copyright (c) 2022 Michael Stoll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Stoll
-/
import Mathlib.Algebra.CharP.Basic
import Mathlib.Data.Fintype.Units
import Mathlib.GroupTheory.OrderOfElement
#align_import number_theory.legendre_symbol.mul_character from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Multiplicative characters of finite rings and fields
Let `R` and `R'` be a commutative rings.
A *multiplicative character* of `R` with values in `R'` is a morphism of
monoids from the multiplicative monoid of `R` into that of `R'`
that sends non-units to zero.
We use the namespace `MulChar` for the definitions and results.
## Main results
We show that the multiplicative characters form a group (if `R'` is commutative);
see `MulChar.commGroup`. We also provide an equivalence with the
homomorphisms `Rˣ →* R'ˣ`; see `MulChar.equivToUnitHom`.
We define a multiplicative character to be *quadratic* if its values
are among `0`, `1` and `-1`, and we prove some properties of quadratic characters.
Finally, we show that the sum of all values of a nontrivial multiplicative
character vanishes; see `MulChar.IsNontrivial.sum_eq_zero`.
## Tags
multiplicative character
-/
/-!
### Definitions related to multiplicative characters
Even though the intended use is when domain and target of the characters
are commutative rings, we define them in the more general setting when
the domain is a commutative monoid and the target is a commutative monoid
with zero. (We need a zero in the target, since non-units are supposed
to map to zero.)
In this setting, there is an equivalence between multiplicative characters
`R → R'` and group homomorphisms `Rˣ → R'ˣ`, and the multiplicative characters
have a natural structure as a commutative group.
-/
section Defi
-- The domain of our multiplicative characters
variable (R : Type*) [CommMonoid R]
-- The target
variable (R' : Type*) [CommMonoidWithZero R']
/-- Define a structure for multiplicative characters.
A multiplicative character from a commutative monoid `R` to a commutative monoid with zero `R'`
is a homomorphism of (multiplicative) monoids that sends non-units to zero. -/
structure MulChar extends MonoidHom R R' where
map_nonunit' : ∀ a : R, ¬IsUnit a → toFun a = 0
#align mul_char MulChar
instance MulChar.instFunLike : FunLike (MulChar R R') R R' :=
⟨fun χ => χ.toFun,
fun χ₀ χ₁ h => by cases χ₀; cases χ₁; congr; apply MonoidHom.ext (fun _ => congr_fun h _)⟩
/-- This is the corresponding extension of `MonoidHomClass`. -/
class MulCharClass (F : Type*) (R R' : outParam Type*) [CommMonoid R]
[CommMonoidWithZero R'] [FunLike F R R'] extends MonoidHomClass F R R' : Prop where
map_nonunit : ∀ (χ : F) {a : R} (_ : ¬IsUnit a), χ a = 0
#align mul_char_class MulCharClass
initialize_simps_projections MulChar (toFun → apply, -toMonoidHom)
attribute [simp] MulCharClass.map_nonunit
end Defi
namespace MulChar
section Group
-- The domain of our multiplicative characters
variable {R : Type*} [CommMonoid R]
-- The target
variable {R' : Type*} [CommMonoidWithZero R']
variable (R R') in
/-- The trivial multiplicative character. It takes the value `0` on non-units and
the value `1` on units. -/
@[simps]
noncomputable def trivial : MulChar R R' where
toFun := by classical exact fun x => if IsUnit x then 1 else 0
map_nonunit' := by
intro a ha
simp only [ha, if_false]
map_one' := by simp only [isUnit_one, if_true]
map_mul' := by
intro x y
classical
simp only [IsUnit.mul_iff, boole_mul]
split_ifs <;> tauto
#align mul_char.trivial MulChar.trivial
@[simp]
theorem coe_mk (f : R →* R') (hf) : (MulChar.mk f hf : R → R') = f :=
rfl
#align mul_char.coe_mk MulChar.coe_mk
/-- Extensionality. See `ext` below for the version that will actually be used. -/
theorem ext' {χ χ' : MulChar R R'} (h : ∀ a, χ a = χ' a) : χ = χ' := by
cases χ
cases χ'
congr
exact MonoidHom.ext h
#align mul_char.ext' MulChar.ext'
instance : MulCharClass (MulChar R R') R R' where
map_mul χ := χ.map_mul'
map_one χ := χ.map_one'
map_nonunit χ := χ.map_nonunit' _
theorem map_nonunit (χ : MulChar R R') {a : R} (ha : ¬IsUnit a) : χ a = 0 :=
χ.map_nonunit' a ha
#align mul_char.map_nonunit MulChar.map_nonunit
/-- Extensionality. Since `MulChar`s always take the value zero on non-units, it is sufficient
to compare the values on units. -/
@[ext]
theorem ext {χ χ' : MulChar R R'} (h : ∀ a : Rˣ, χ a = χ' a) : χ = χ' := by
apply ext'
intro a
by_cases ha : IsUnit a
· exact h ha.unit
· rw [map_nonunit χ ha, map_nonunit χ' ha]
#align mul_char.ext MulChar.ext
theorem ext_iff {χ χ' : MulChar R R'} : χ = χ' ↔ ∀ a : Rˣ, χ a = χ' a :=
⟨by
rintro rfl a
rfl, ext⟩
#align mul_char.ext_iff MulChar.ext_iff
/-!
### Equivalence of multiplicative characters with homomorphisms on units
We show that restriction / extension by zero gives an equivalence
between `MulChar R R'` and `Rˣ →* R'ˣ`.
-/
/-- Turn a `MulChar` into a homomorphism between the unit groups. -/
def toUnitHom (χ : MulChar R R') : Rˣ →* R'ˣ :=
Units.map χ
#align mul_char.to_unit_hom MulChar.toUnitHom
theorem coe_toUnitHom (χ : MulChar R R') (a : Rˣ) : ↑(χ.toUnitHom a) = χ a :=
rfl
#align mul_char.coe_to_unit_hom MulChar.coe_toUnitHom
/-- Turn a homomorphism between unit groups into a `MulChar`. -/
noncomputable def ofUnitHom (f : Rˣ →* R'ˣ) : MulChar R R' where
toFun := by classical exact fun x => if hx : IsUnit x then f hx.unit else 0
map_one' := by
have h1 : (isUnit_one.unit : Rˣ) = 1 := Units.eq_iff.mp rfl
simp only [h1, dif_pos, Units.val_eq_one, map_one, isUnit_one]
map_mul' := by
classical
intro x y
by_cases hx : IsUnit x
· simp only [hx, IsUnit.mul_iff, true_and_iff, dif_pos]
by_cases hy : IsUnit y
· simp only [hy, dif_pos]
have hm : (IsUnit.mul_iff.mpr ⟨hx, hy⟩).unit = hx.unit * hy.unit := Units.eq_iff.mp rfl
rw [hm, map_mul]
norm_cast
· simp only [hy, not_false_iff, dif_neg, mul_zero]
· simp only [hx, IsUnit.mul_iff, false_and_iff, not_false_iff, dif_neg, zero_mul]
map_nonunit' := by
intro a ha
simp only [ha, not_false_iff, dif_neg]
#align mul_char.of_unit_hom MulChar.ofUnitHom
theorem ofUnitHom_coe (f : Rˣ →* R'ˣ) (a : Rˣ) : ofUnitHom f ↑a = f a := by simp [ofUnitHom]
#align mul_char.of_unit_hom_coe MulChar.ofUnitHom_coe
/-- The equivalence between multiplicative characters and homomorphisms of unit groups. -/
noncomputable def equivToUnitHom : MulChar R R' ≃ (Rˣ →* R'ˣ) where
toFun := toUnitHom
invFun := ofUnitHom
left_inv := by
intro χ
ext x
rw [ofUnitHom_coe, coe_toUnitHom]
right_inv := by
intro f
ext x
simp only [coe_toUnitHom, ofUnitHom_coe]
#align mul_char.equiv_to_unit_hom MulChar.equivToUnitHom
@[simp]
theorem toUnitHom_eq (χ : MulChar R R') : toUnitHom χ = equivToUnitHom χ :=
rfl
#align mul_char.to_unit_hom_eq MulChar.toUnitHom_eq
@[simp]
theorem ofUnitHom_eq (χ : Rˣ →* R'ˣ) : ofUnitHom χ = equivToUnitHom.symm χ :=
rfl
#align mul_char.of_unit_hom_eq MulChar.ofUnitHom_eq
@[simp]
theorem coe_equivToUnitHom (χ : MulChar R R') (a : Rˣ) : ↑(equivToUnitHom χ a) = χ a :=
coe_toUnitHom χ a
#align mul_char.coe_equiv_to_unit_hom MulChar.coe_equivToUnitHom
@[simp]
theorem equivToUnitHom_symm_coe (f : Rˣ →* R'ˣ) (a : Rˣ) : equivToUnitHom.symm f ↑a = f a :=
ofUnitHom_coe f a
#align mul_char.equiv_unit_hom_symm_coe MulChar.equivToUnitHom_symm_coe
@[simp]
lemma coe_toMonoidHom [CommMonoid R] (χ : MulChar R R')
(x : R) : χ.toMonoidHom x = χ x := rfl
/-!
### Commutative group structure on multiplicative characters
The multiplicative characters `R → R'` form a commutative group.
-/
protected theorem map_one (χ : MulChar R R') : χ (1 : R) = 1 :=
χ.map_one'
#align mul_char.map_one MulChar.map_one
/-- If the domain has a zero (and is nontrivial), then `χ 0 = 0`. -/
protected theorem map_zero {R : Type*} [CommMonoidWithZero R] [Nontrivial R] (χ : MulChar R R') :
χ (0 : R) = 0 := by rw [map_nonunit χ not_isUnit_zero]
#align mul_char.map_zero MulChar.map_zero
/-- We can convert a multiplicative character into a homomorphism of monoids with zero when
the source has a zero and another element. -/
@[coe, simps]
def toMonoidWithZeroHom {R : Type*} [CommMonoidWithZero R] [Nontrivial R] (χ : MulChar R R') :
R →*₀ R' where
toFun := χ.toFun
map_zero' := χ.map_zero
map_one' := χ.map_one'
map_mul' := χ.map_mul'
/-- If the domain is a ring `R`, then `χ (ringChar R) = 0`. -/
theorem map_ringChar {R : Type*} [CommRing R] [Nontrivial R] (χ : MulChar R R') :
χ (ringChar R) = 0 := by rw [ringChar.Nat.cast_ringChar, χ.map_zero]
#align mul_char.map_ring_char MulChar.map_ringChar
noncomputable instance hasOne : One (MulChar R R') :=
⟨trivial R R'⟩
#align mul_char.has_one MulChar.hasOne
noncomputable instance inhabited : Inhabited (MulChar R R') :=
⟨1⟩
#align mul_char.inhabited MulChar.inhabited
/-- Evaluation of the trivial character -/
@[simp]
theorem one_apply_coe (a : Rˣ) : (1 : MulChar R R') a = 1 := by classical exact dif_pos a.isUnit
#align mul_char.one_apply_coe MulChar.one_apply_coe
/-- Evaluation of the trivial character -/
lemma one_apply {x : R} (hx : IsUnit x) : (1 : MulChar R R') x = 1 := one_apply_coe hx.unit
/-- Multiplication of multiplicative characters. (This needs the target to be commutative.) -/
def mul (χ χ' : MulChar R R') : MulChar R R' :=
{ χ.toMonoidHom * χ'.toMonoidHom with
toFun := χ * χ'
map_nonunit' := fun a ha => by simp only [map_nonunit χ ha, zero_mul, Pi.mul_apply] }
#align mul_char.mul MulChar.mul
instance hasMul : Mul (MulChar R R') :=
⟨mul⟩
#align mul_char.has_mul MulChar.hasMul
theorem mul_apply (χ χ' : MulChar R R') (a : R) : (χ * χ') a = χ a * χ' a :=
rfl
#align mul_char.mul_apply MulChar.mul_apply
@[simp]
theorem coeToFun_mul (χ χ' : MulChar R R') : ⇑(χ * χ') = χ * χ' :=
rfl
#align mul_char.coe_to_fun_mul MulChar.coeToFun_mul
protected theorem one_mul (χ : MulChar R R') : (1 : MulChar R R') * χ = χ := by
ext
simp only [one_mul, Pi.mul_apply, MulChar.coeToFun_mul, MulChar.one_apply_coe]
#align mul_char.one_mul MulChar.one_mul
protected theorem mul_one (χ : MulChar R R') : χ * 1 = χ := by
ext
simp only [mul_one, Pi.mul_apply, MulChar.coeToFun_mul, MulChar.one_apply_coe]
#align mul_char.mul_one MulChar.mul_one
/-- The inverse of a multiplicative character. We define it as `inverse ∘ χ`. -/
noncomputable def inv (χ : MulChar R R') : MulChar R R' :=
{ MonoidWithZero.inverse.toMonoidHom.comp χ.toMonoidHom with
toFun := fun a => MonoidWithZero.inverse (χ a)
map_nonunit' := fun a ha => by simp [map_nonunit _ ha] }
#align mul_char.inv MulChar.inv
noncomputable instance hasInv : Inv (MulChar R R') :=
⟨inv⟩
#align mul_char.has_inv MulChar.hasInv
/-- The inverse of a multiplicative character `χ`, applied to `a`, is the inverse of `χ a`. -/
theorem inv_apply_eq_inv (χ : MulChar R R') (a : R) : χ⁻¹ a = Ring.inverse (χ a) :=
Eq.refl <| inv χ a
#align mul_char.inv_apply_eq_inv MulChar.inv_apply_eq_inv
/-- The inverse of a multiplicative character `χ`, applied to `a`, is the inverse of `χ a`.
Variant when the target is a field -/
theorem inv_apply_eq_inv' {R' : Type*} [Field R'] (χ : MulChar R R') (a : R) : χ⁻¹ a = (χ a)⁻¹ :=
(inv_apply_eq_inv χ a).trans <| Ring.inverse_eq_inv (χ a)
#align mul_char.inv_apply_eq_inv' MulChar.inv_apply_eq_inv'
/-- When the domain has a zero, then the inverse of a multiplicative character `χ`,
applied to `a`, is `χ` applied to the inverse of `a`. -/
theorem inv_apply {R : Type*} [CommMonoidWithZero R] (χ : MulChar R R') (a : R) :
χ⁻¹ a = χ (Ring.inverse a) := by
by_cases ha : IsUnit a
· rw [inv_apply_eq_inv]
have h := IsUnit.map χ ha
apply_fun (χ a * ·) using IsUnit.mul_right_injective h
dsimp only
rw [Ring.mul_inverse_cancel _ h, ← map_mul, Ring.mul_inverse_cancel _ ha, map_one]
· revert ha
nontriviality R
intro ha
-- `nontriviality R` by itself doesn't do it
rw [map_nonunit _ ha, Ring.inverse_non_unit a ha, MulChar.map_zero χ]
#align mul_char.inv_apply MulChar.inv_apply
/-- When the domain has a zero, then the inverse of a multiplicative character `χ`,
applied to `a`, is `χ` applied to the inverse of `a`. -/
theorem inv_apply' {R : Type*} [Field R] (χ : MulChar R R') (a : R) : χ⁻¹ a = χ a⁻¹ :=
(inv_apply χ a).trans <| congr_arg _ (Ring.inverse_eq_inv a)
#align mul_char.inv_apply' MulChar.inv_apply'
/-- The product of a character with its inverse is the trivial character. -/
-- Porting note (#10618): @[simp] can prove this (later)
theorem inv_mul (χ : MulChar R R') : χ⁻¹ * χ = 1 := by
ext x
rw [coeToFun_mul, Pi.mul_apply, inv_apply_eq_inv]
simp only [Ring.inverse_mul_cancel _ (IsUnit.map χ x.isUnit)]
rw [one_apply_coe]
#align mul_char.inv_mul MulChar.inv_mul
/-- The commutative group structure on `MulChar R R'`. -/
noncomputable instance commGroup : CommGroup (MulChar R R') :=
{ one := 1
mul := (· * ·)
inv := Inv.inv
mul_left_inv := inv_mul
mul_assoc := by
intro χ₁ χ₂ χ₃
ext a
simp only [mul_assoc, Pi.mul_apply, MulChar.coeToFun_mul]
mul_comm := by
intro χ₁ χ₂
ext a
simp only [mul_comm, Pi.mul_apply, MulChar.coeToFun_mul]
one_mul := MulChar.one_mul
mul_one := MulChar.mul_one }
#align mul_char.comm_group MulChar.commGroup
/-- If `a` is a unit and `n : ℕ`, then `(χ ^ n) a = (χ a) ^ n`. -/
| Mathlib/NumberTheory/MulChar/Basic.lean | 383 | 386 | theorem pow_apply_coe (χ : MulChar R R') (n : ℕ) (a : Rˣ) : (χ ^ n) a = χ a ^ n := by |
induction' n with n ih
· rw [pow_zero, pow_zero, one_apply_coe]
· rw [pow_succ, pow_succ, mul_apply, ih]
|
/-
Copyright (c) 2020 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Patrick Massot, Sébastien Gouëzel
-/
import Mathlib.Order.Interval.Set.Disjoint
import Mathlib.MeasureTheory.Integral.SetIntegral
import Mathlib.MeasureTheory.Measure.Lebesgue.Basic
#align_import measure_theory.integral.interval_integral from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Integral over an interval
In this file we define `∫ x in a..b, f x ∂μ` to be `∫ x in Ioc a b, f x ∂μ` if `a ≤ b` and
`-∫ x in Ioc b a, f x ∂μ` if `b ≤ a`.
## Implementation notes
### Avoiding `if`, `min`, and `max`
In order to avoid `if`s in the definition, we define `IntervalIntegrable f μ a b` as
`integrable_on f (Ioc a b) μ ∧ integrable_on f (Ioc b a) μ`. For any `a`, `b` one of these
intervals is empty and the other coincides with `Set.uIoc a b = Set.Ioc (min a b) (max a b)`.
Similarly, we define `∫ x in a..b, f x ∂μ` to be `∫ x in Ioc a b, f x ∂μ - ∫ x in Ioc b a, f x ∂μ`.
Again, for any `a`, `b` one of these integrals is zero, and the other gives the expected result.
This way some properties can be translated from integrals over sets without dealing with
the cases `a ≤ b` and `b ≤ a` separately.
### Choice of the interval
We use integral over `Set.uIoc a b = Set.Ioc (min a b) (max a b)` instead of one of the other
three possible intervals with the same endpoints for two reasons:
* this way `∫ x in a..b, f x ∂μ + ∫ x in b..c, f x ∂μ = ∫ x in a..c, f x ∂μ` holds whenever
`f` is integrable on each interval; in particular, it works even if the measure `μ` has an atom
at `b`; this rules out `Set.Ioo` and `Set.Icc` intervals;
* with this definition for a probability measure `μ`, the integral `∫ x in a..b, 1 ∂μ` equals
the difference $F_μ(b)-F_μ(a)$, where $F_μ(a)=μ(-∞, a]$ is the
[cumulative distribution function](https://en.wikipedia.org/wiki/Cumulative_distribution_function)
of `μ`.
## Tags
integral
-/
noncomputable section
open scoped Classical
open MeasureTheory Set Filter Function
open scoped Classical Topology Filter ENNReal Interval NNReal
variable {ι 𝕜 E F A : Type*} [NormedAddCommGroup E]
/-!
### Integrability on an interval
-/
/-- A function `f` is called *interval integrable* with respect to a measure `μ` on an unordered
interval `a..b` if it is integrable on both intervals `(a, b]` and `(b, a]`. One of these
intervals is always empty, so this property is equivalent to `f` being integrable on
`(min a b, max a b]`. -/
def IntervalIntegrable (f : ℝ → E) (μ : Measure ℝ) (a b : ℝ) : Prop :=
IntegrableOn f (Ioc a b) μ ∧ IntegrableOn f (Ioc b a) μ
#align interval_integrable IntervalIntegrable
/-!
## Basic iff's for `IntervalIntegrable`
-/
section
variable {f : ℝ → E} {a b : ℝ} {μ : Measure ℝ}
/-- A function is interval integrable with respect to a given measure `μ` on `a..b` if and
only if it is integrable on `uIoc a b` with respect to `μ`. This is an equivalent
definition of `IntervalIntegrable`. -/
theorem intervalIntegrable_iff : IntervalIntegrable f μ a b ↔ IntegrableOn f (Ι a b) μ := by
rw [uIoc_eq_union, integrableOn_union, IntervalIntegrable]
#align interval_integrable_iff intervalIntegrable_iff
/-- If a function is interval integrable with respect to a given measure `μ` on `a..b` then
it is integrable on `uIoc a b` with respect to `μ`. -/
theorem IntervalIntegrable.def' (h : IntervalIntegrable f μ a b) : IntegrableOn f (Ι a b) μ :=
intervalIntegrable_iff.mp h
#align interval_integrable.def IntervalIntegrable.def'
theorem intervalIntegrable_iff_integrableOn_Ioc_of_le (hab : a ≤ b) :
IntervalIntegrable f μ a b ↔ IntegrableOn f (Ioc a b) μ := by
rw [intervalIntegrable_iff, uIoc_of_le hab]
#align interval_integrable_iff_integrable_Ioc_of_le intervalIntegrable_iff_integrableOn_Ioc_of_le
theorem intervalIntegrable_iff' [NoAtoms μ] :
IntervalIntegrable f μ a b ↔ IntegrableOn f (uIcc a b) μ := by
rw [intervalIntegrable_iff, ← Icc_min_max, uIoc, integrableOn_Icc_iff_integrableOn_Ioc]
#align interval_integrable_iff' intervalIntegrable_iff'
theorem intervalIntegrable_iff_integrableOn_Icc_of_le {f : ℝ → E} {a b : ℝ} (hab : a ≤ b)
{μ : Measure ℝ} [NoAtoms μ] : IntervalIntegrable f μ a b ↔ IntegrableOn f (Icc a b) μ := by
rw [intervalIntegrable_iff_integrableOn_Ioc_of_le hab, integrableOn_Icc_iff_integrableOn_Ioc]
#align interval_integrable_iff_integrable_Icc_of_le intervalIntegrable_iff_integrableOn_Icc_of_le
theorem intervalIntegrable_iff_integrableOn_Ico_of_le [NoAtoms μ] (hab : a ≤ b) :
IntervalIntegrable f μ a b ↔ IntegrableOn f (Ico a b) μ := by
rw [intervalIntegrable_iff_integrableOn_Icc_of_le hab, integrableOn_Icc_iff_integrableOn_Ico]
theorem intervalIntegrable_iff_integrableOn_Ioo_of_le [NoAtoms μ] (hab : a ≤ b) :
IntervalIntegrable f μ a b ↔ IntegrableOn f (Ioo a b) μ := by
rw [intervalIntegrable_iff_integrableOn_Icc_of_le hab, integrableOn_Icc_iff_integrableOn_Ioo]
/-- If a function is integrable with respect to a given measure `μ` then it is interval integrable
with respect to `μ` on `uIcc a b`. -/
theorem MeasureTheory.Integrable.intervalIntegrable (hf : Integrable f μ) :
IntervalIntegrable f μ a b :=
⟨hf.integrableOn, hf.integrableOn⟩
#align measure_theory.integrable.interval_integrable MeasureTheory.Integrable.intervalIntegrable
theorem MeasureTheory.IntegrableOn.intervalIntegrable (hf : IntegrableOn f [[a, b]] μ) :
IntervalIntegrable f μ a b :=
⟨MeasureTheory.IntegrableOn.mono_set hf (Ioc_subset_Icc_self.trans Icc_subset_uIcc),
MeasureTheory.IntegrableOn.mono_set hf (Ioc_subset_Icc_self.trans Icc_subset_uIcc')⟩
#align measure_theory.integrable_on.interval_integrable MeasureTheory.IntegrableOn.intervalIntegrable
theorem intervalIntegrable_const_iff {c : E} :
IntervalIntegrable (fun _ => c) μ a b ↔ c = 0 ∨ μ (Ι a b) < ∞ := by
simp only [intervalIntegrable_iff, integrableOn_const]
#align interval_integrable_const_iff intervalIntegrable_const_iff
@[simp]
theorem intervalIntegrable_const [IsLocallyFiniteMeasure μ] {c : E} :
IntervalIntegrable (fun _ => c) μ a b :=
intervalIntegrable_const_iff.2 <| Or.inr measure_Ioc_lt_top
#align interval_integrable_const intervalIntegrable_const
end
/-!
## Basic properties of interval integrability
- interval integrability is symmetric, reflexive, transitive
- monotonicity and strong measurability of the interval integral
- if `f` is interval integrable, so are its absolute value and norm
- arithmetic properties
-/
namespace IntervalIntegrable
section
variable {f : ℝ → E} {a b c d : ℝ} {μ ν : Measure ℝ}
@[symm]
nonrec theorem symm (h : IntervalIntegrable f μ a b) : IntervalIntegrable f μ b a :=
h.symm
#align interval_integrable.symm IntervalIntegrable.symm
@[refl, simp] -- Porting note: added `simp`
| Mathlib/MeasureTheory/Integral/IntervalIntegral.lean | 161 | 161 | theorem refl : IntervalIntegrable f μ a a := by | constructor <;> simp
|
/-
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.Algebra.Ring.Int
import Mathlib.Data.ZMod.Basic
import Mathlib.FieldTheory.Finite.Basic
import Mathlib.Data.Fintype.BigOperators
#align_import number_theory.sum_four_squares from "leanprover-community/mathlib"@"bd9851ca476957ea4549eb19b40e7b5ade9428cc"
/-!
# Lagrange's four square theorem
The main result in this file is `sum_four_squares`,
a proof that every natural number is the sum of four square numbers.
## Implementation Notes
The proof used is close to Lagrange's original proof.
-/
open Finset Polynomial FiniteField Equiv
/-- **Euler's four-square identity**. -/
theorem euler_four_squares {R : Type*} [CommRing R] (a b c d x y z w : R) :
(a * x - b * y - c * z - d * w) ^ 2 + (a * y + b * x + c * w - d * z) ^ 2 +
(a * z - b * w + c * x + d * y) ^ 2 + (a * w + b * z - c * y + d * x) ^ 2 =
(a ^ 2 + b ^ 2 + c ^ 2 + d ^ 2) * (x ^ 2 + y ^ 2 + z ^ 2 + w ^ 2) := by ring
/-- **Euler's four-square identity**, a version for natural numbers. -/
theorem Nat.euler_four_squares (a b c d x y z w : ℕ) :
((a : ℤ) * x - b * y - c * z - d * w).natAbs ^ 2 +
((a : ℤ) * y + b * x + c * w - d * z).natAbs ^ 2 +
((a : ℤ) * z - b * w + c * x + d * y).natAbs ^ 2 +
((a : ℤ) * w + b * z - c * y + d * x).natAbs ^ 2 =
(a ^ 2 + b ^ 2 + c ^ 2 + d ^ 2) * (x ^ 2 + y ^ 2 + z ^ 2 + w ^ 2) := by
rw [← Int.natCast_inj]
push_cast
simp only [sq_abs, _root_.euler_four_squares]
namespace Int
| Mathlib/NumberTheory/SumFourSquares.lean | 46 | 59 | theorem sq_add_sq_of_two_mul_sq_add_sq {m x y : ℤ} (h : 2 * m = x ^ 2 + y ^ 2) :
m = ((x - y) / 2) ^ 2 + ((x + y) / 2) ^ 2 :=
have : Even (x ^ 2 + y ^ 2) := by | simp [← h, even_mul]
have hxaddy : Even (x + y) := by simpa [sq, parity_simps]
have hxsuby : Even (x - y) := by simpa [sq, parity_simps]
mul_right_injective₀ (show (2 * 2 : ℤ) ≠ 0 by decide) <|
calc
2 * 2 * m = (x - y) ^ 2 + (x + y) ^ 2 := by rw [mul_assoc, h]; ring
_ = (2 * ((x - y) / 2)) ^ 2 + (2 * ((x + y) / 2)) ^ 2 := by
rw [even_iff_two_dvd] at hxsuby hxaddy
rw [Int.mul_ediv_cancel' hxsuby, Int.mul_ediv_cancel' hxaddy]
_ = 2 * 2 * (((x - y) / 2) ^ 2 + ((x + y) / 2) ^ 2) := by
set_option simprocs false in
simp [mul_add, pow_succ, mul_comm, mul_assoc, mul_left_comm]
|
/-
Copyright (c) 2020 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Algebra.Group.Conj
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Subsemigroup.Operations
import Mathlib.Algebra.Group.Submonoid.Operations
import Mathlib.Algebra.Order.Group.Abs
import Mathlib.Data.Set.Image
import Mathlib.Order.Atoms
import Mathlib.Tactic.ApplyFun
#align_import group_theory.subgroup.basic from "leanprover-community/mathlib"@"4be589053caf347b899a494da75410deb55fb3ef"
/-!
# Subgroups
This file defines multiplicative and additive subgroups as an extension of submonoids, in a bundled
form (unbundled subgroups are in `Deprecated/Subgroups.lean`).
We prove subgroups of a group form a complete lattice, and results about images and preimages of
subgroups under group homomorphisms. The bundled subgroups use bundled monoid homomorphisms.
There are also theorems about the subgroups generated by an element or a subset of a group,
defined both inductively and as the infimum of the set of subgroups containing a given
element/subset.
Special thanks goes to Amelia Livingston and Yury Kudryashov for their help and inspiration.
## Main definitions
Notation used here:
- `G N` are `Group`s
- `A` is an `AddGroup`
- `H K` are `Subgroup`s of `G` or `AddSubgroup`s of `A`
- `x` is an element of type `G` or type `A`
- `f g : N →* G` are group homomorphisms
- `s k` are sets of elements of type `G`
Definitions in the file:
* `Subgroup G` : the type of subgroups of a group `G`
* `AddSubgroup A` : the type of subgroups of an additive group `A`
* `CompleteLattice (Subgroup G)` : the subgroups of `G` form a complete lattice
* `Subgroup.closure k` : the minimal subgroup that includes the set `k`
* `Subgroup.subtype` : the natural group homomorphism from a subgroup of group `G` to `G`
* `Subgroup.gi` : `closure` forms a Galois insertion with the coercion to set
* `Subgroup.comap H f` : the preimage of a subgroup `H` along the group homomorphism `f` is also a
subgroup
* `Subgroup.map f H` : the image of a subgroup `H` along the group homomorphism `f` is also a
subgroup
* `Subgroup.prod H K` : the product of subgroups `H`, `K` of groups `G`, `N` respectively, `H × K`
is a subgroup of `G × N`
* `MonoidHom.range f` : the range of the group homomorphism `f` is a subgroup
* `MonoidHom.ker f` : the kernel of a group homomorphism `f` is the subgroup of elements `x : G`
such that `f x = 1`
* `MonoidHom.eq_locus f g` : given group homomorphisms `f`, `g`, the elements of `G` such that
`f x = g x` form a subgroup of `G`
## Implementation notes
Subgroup inclusion is denoted `≤` rather than `⊆`, although `∈` is defined as
membership of a subgroup's underlying set.
## Tags
subgroup, subgroups
-/
open Function
open Int
variable {G G' G'' : Type*} [Group G] [Group G'] [Group G'']
variable {A : Type*} [AddGroup A]
section SubgroupClass
/-- `InvMemClass S G` states `S` is a type of subsets `s ⊆ G` closed under inverses. -/
class InvMemClass (S G : Type*) [Inv G] [SetLike S G] : Prop where
/-- `s` is closed under inverses -/
inv_mem : ∀ {s : S} {x}, x ∈ s → x⁻¹ ∈ s
#align inv_mem_class InvMemClass
export InvMemClass (inv_mem)
/-- `NegMemClass S G` states `S` is a type of subsets `s ⊆ G` closed under negation. -/
class NegMemClass (S G : Type*) [Neg G] [SetLike S G] : Prop where
/-- `s` is closed under negation -/
neg_mem : ∀ {s : S} {x}, x ∈ s → -x ∈ s
#align neg_mem_class NegMemClass
export NegMemClass (neg_mem)
/-- `SubgroupClass S G` states `S` is a type of subsets `s ⊆ G` that are subgroups of `G`. -/
class SubgroupClass (S G : Type*) [DivInvMonoid G] [SetLike S G] extends SubmonoidClass S G,
InvMemClass S G : Prop
#align subgroup_class SubgroupClass
/-- `AddSubgroupClass S G` states `S` is a type of subsets `s ⊆ G` that are
additive subgroups of `G`. -/
class AddSubgroupClass (S G : Type*) [SubNegMonoid G] [SetLike S G] extends AddSubmonoidClass S G,
NegMemClass S G : Prop
#align add_subgroup_class AddSubgroupClass
attribute [to_additive] InvMemClass SubgroupClass
attribute [aesop safe apply (rule_sets := [SetLike])] inv_mem neg_mem
@[to_additive (attr := simp)]
theorem inv_mem_iff {S G} [InvolutiveInv G] {_ : SetLike S G} [InvMemClass S G] {H : S}
{x : G} : x⁻¹ ∈ H ↔ x ∈ H :=
⟨fun h => inv_inv x ▸ inv_mem h, inv_mem⟩
#align inv_mem_iff inv_mem_iff
#align neg_mem_iff neg_mem_iff
@[simp] theorem abs_mem_iff {S G} [AddGroup G] [LinearOrder G] {_ : SetLike S G}
[NegMemClass S G] {H : S} {x : G} : |x| ∈ H ↔ x ∈ H := by
cases abs_choice x <;> simp [*]
variable {M S : Type*} [DivInvMonoid M] [SetLike S M] [hSM : SubgroupClass S M] {H K : S}
/-- A subgroup is closed under division. -/
@[to_additive (attr := aesop safe apply (rule_sets := [SetLike]))
"An additive subgroup is closed under subtraction."]
theorem div_mem {x y : M} (hx : x ∈ H) (hy : y ∈ H) : x / y ∈ H := by
rw [div_eq_mul_inv]; exact mul_mem hx (inv_mem hy)
#align div_mem div_mem
#align sub_mem sub_mem
@[to_additive (attr := aesop safe apply (rule_sets := [SetLike]))]
theorem zpow_mem {x : M} (hx : x ∈ K) : ∀ n : ℤ, x ^ n ∈ K
| (n : ℕ) => by
rw [zpow_natCast]
exact pow_mem hx n
| -[n+1] => by
rw [zpow_negSucc]
exact inv_mem (pow_mem hx n.succ)
#align zpow_mem zpow_mem
#align zsmul_mem zsmul_mem
variable [SetLike S G] [SubgroupClass S G]
@[to_additive]
theorem div_mem_comm_iff {a b : G} : a / b ∈ H ↔ b / a ∈ H :=
inv_div b a ▸ inv_mem_iff
#align div_mem_comm_iff div_mem_comm_iff
#align sub_mem_comm_iff sub_mem_comm_iff
@[to_additive /-(attr := simp)-/] -- Porting note: `simp` cannot simplify LHS
theorem exists_inv_mem_iff_exists_mem {P : G → Prop} :
(∃ x : G, x ∈ H ∧ P x⁻¹) ↔ ∃ x ∈ H, P x := by
constructor <;>
· rintro ⟨x, x_in, hx⟩
exact ⟨x⁻¹, inv_mem x_in, by simp [hx]⟩
#align exists_inv_mem_iff_exists_mem exists_inv_mem_iff_exists_mem
#align exists_neg_mem_iff_exists_mem exists_neg_mem_iff_exists_mem
@[to_additive]
theorem mul_mem_cancel_right {x y : G} (h : x ∈ H) : y * x ∈ H ↔ y ∈ H :=
⟨fun hba => by simpa using mul_mem hba (inv_mem h), fun hb => mul_mem hb h⟩
#align mul_mem_cancel_right mul_mem_cancel_right
#align add_mem_cancel_right add_mem_cancel_right
@[to_additive]
theorem mul_mem_cancel_left {x y : G} (h : x ∈ H) : x * y ∈ H ↔ y ∈ H :=
⟨fun hab => by simpa using mul_mem (inv_mem h) hab, mul_mem h⟩
#align mul_mem_cancel_left mul_mem_cancel_left
#align add_mem_cancel_left add_mem_cancel_left
namespace InvMemClass
/-- A subgroup of a group inherits an inverse. -/
@[to_additive "An additive subgroup of an `AddGroup` inherits an inverse."]
instance inv {G : Type u_1} {S : Type u_2} [Inv G] [SetLike S G]
[InvMemClass S G] {H : S} : Inv H :=
⟨fun a => ⟨a⁻¹, inv_mem a.2⟩⟩
#align subgroup_class.has_inv InvMemClass.inv
#align add_subgroup_class.has_neg NegMemClass.neg
@[to_additive (attr := simp, norm_cast)]
theorem coe_inv (x : H) : (x⁻¹).1 = x.1⁻¹ :=
rfl
#align subgroup_class.coe_inv InvMemClass.coe_inv
#align add_subgroup_class.coe_neg NegMemClass.coe_neg
end InvMemClass
namespace SubgroupClass
@[to_additive (attr := deprecated (since := "2024-01-15"))] alias coe_inv := InvMemClass.coe_inv
-- Here we assume H, K, and L are subgroups, but in fact any one of them
-- could be allowed to be a subsemigroup.
-- Counterexample where K and L are submonoids: H = ℤ, K = ℕ, L = -ℕ
-- Counterexample where H and K are submonoids: H = {n | n = 0 ∨ 3 ≤ n}, K = 3ℕ + 4ℕ, L = 5ℤ
@[to_additive]
theorem subset_union {H K L : S} : (H : Set G) ⊆ K ∪ L ↔ H ≤ K ∨ H ≤ L := by
refine ⟨fun h ↦ ?_, fun h x xH ↦ h.imp (· xH) (· xH)⟩
rw [or_iff_not_imp_left, SetLike.not_le_iff_exists]
exact fun ⟨x, xH, xK⟩ y yH ↦ (h <| mul_mem xH yH).elim
((h yH).resolve_left fun yK ↦ xK <| (mul_mem_cancel_right yK).mp ·)
(mul_mem_cancel_left <| (h xH).resolve_left xK).mp
/-- A subgroup of a group inherits a division -/
@[to_additive "An additive subgroup of an `AddGroup` inherits a subtraction."]
instance div {G : Type u_1} {S : Type u_2} [DivInvMonoid G] [SetLike S G]
[SubgroupClass S G] {H : S} : Div H :=
⟨fun a b => ⟨a / b, div_mem a.2 b.2⟩⟩
#align subgroup_class.has_div SubgroupClass.div
#align add_subgroup_class.has_sub AddSubgroupClass.sub
/-- An additive subgroup of an `AddGroup` inherits an integer scaling. -/
instance _root_.AddSubgroupClass.zsmul {M S} [SubNegMonoid M] [SetLike S M]
[AddSubgroupClass S M] {H : S} : SMul ℤ H :=
⟨fun n a => ⟨n • a.1, zsmul_mem a.2 n⟩⟩
#align add_subgroup_class.has_zsmul AddSubgroupClass.zsmul
/-- A subgroup of a group inherits an integer power. -/
@[to_additive existing]
instance zpow {M S} [DivInvMonoid M] [SetLike S M] [SubgroupClass S M] {H : S} : Pow H ℤ :=
⟨fun a n => ⟨a.1 ^ n, zpow_mem a.2 n⟩⟩
#align subgroup_class.has_zpow SubgroupClass.zpow
-- Porting note: additive align statement is given above
@[to_additive (attr := simp, norm_cast)]
theorem coe_div (x y : H) : (x / y).1 = x.1 / y.1 :=
rfl
#align subgroup_class.coe_div SubgroupClass.coe_div
#align add_subgroup_class.coe_sub AddSubgroupClass.coe_sub
variable (H)
-- Prefer subclasses of `Group` over subclasses of `SubgroupClass`.
/-- A subgroup of a group inherits a group structure. -/
@[to_additive "An additive subgroup of an `AddGroup` inherits an `AddGroup` structure."]
instance (priority := 75) toGroup : Group H :=
Subtype.coe_injective.group _ rfl (fun _ _ => rfl) (fun _ => rfl) (fun _ _ => rfl)
(fun _ _ => rfl) fun _ _ => rfl
#align subgroup_class.to_group SubgroupClass.toGroup
#align add_subgroup_class.to_add_group AddSubgroupClass.toAddGroup
-- Prefer subclasses of `CommGroup` over subclasses of `SubgroupClass`.
/-- A subgroup of a `CommGroup` is a `CommGroup`. -/
@[to_additive "An additive subgroup of an `AddCommGroup` is an `AddCommGroup`."]
instance (priority := 75) toCommGroup {G : Type*} [CommGroup G] [SetLike S G] [SubgroupClass S G] :
CommGroup H :=
Subtype.coe_injective.commGroup _ rfl (fun _ _ => rfl) (fun _ => rfl) (fun _ _ => rfl)
(fun _ _ => rfl) fun _ _ => rfl
#align subgroup_class.to_comm_group SubgroupClass.toCommGroup
#align add_subgroup_class.to_add_comm_group AddSubgroupClass.toAddCommGroup
/-- The natural group hom from a subgroup of group `G` to `G`. -/
@[to_additive (attr := coe)
"The natural group hom from an additive subgroup of `AddGroup` `G` to `G`."]
protected def subtype : H →* G where
toFun := ((↑) : H → G); map_one' := rfl; map_mul' := fun _ _ => rfl
#align subgroup_class.subtype SubgroupClass.subtype
#align add_subgroup_class.subtype AddSubgroupClass.subtype
@[to_additive (attr := simp)]
| Mathlib/Algebra/Group/Subgroup/Basic.lean | 280 | 281 | theorem coeSubtype : (SubgroupClass.subtype H : H → G) = ((↑) : H → G) := by |
rfl
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jens Wagemaker, Anne Baanen
-/
import Mathlib.Algebra.Associated
import Mathlib.Algebra.BigOperators.Finsupp
#align_import algebra.big_operators.associated from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c"
/-!
# Products of associated, prime, and irreducible elements.
This file contains some theorems relating definitions in `Algebra.Associated`
and products of multisets, finsets, and finsupps.
-/
variable {α β γ δ : Type*}
-- the same local notation used in `Algebra.Associated`
local infixl:50 " ~ᵤ " => Associated
namespace Prime
variable [CommMonoidWithZero α] {p : α} (hp : Prime p)
theorem exists_mem_multiset_dvd {s : Multiset α} : p ∣ s.prod → ∃ a ∈ s, p ∣ a :=
Multiset.induction_on s (fun h => (hp.not_dvd_one h).elim) fun a s ih h =>
have : p ∣ a * s.prod := by simpa using h
match hp.dvd_or_dvd this with
| Or.inl h => ⟨a, Multiset.mem_cons_self a s, h⟩
| Or.inr h =>
let ⟨a, has, h⟩ := ih h
⟨a, Multiset.mem_cons_of_mem has, h⟩
#align prime.exists_mem_multiset_dvd Prime.exists_mem_multiset_dvd
theorem exists_mem_multiset_map_dvd {s : Multiset β} {f : β → α} :
p ∣ (s.map f).prod → ∃ a ∈ s, p ∣ f a := fun h => by
simpa only [exists_prop, Multiset.mem_map, exists_exists_and_eq_and] using
hp.exists_mem_multiset_dvd h
#align prime.exists_mem_multiset_map_dvd Prime.exists_mem_multiset_map_dvd
theorem exists_mem_finset_dvd {s : Finset β} {f : β → α} : p ∣ s.prod f → ∃ i ∈ s, p ∣ f i :=
hp.exists_mem_multiset_map_dvd
#align prime.exists_mem_finset_dvd Prime.exists_mem_finset_dvd
end Prime
theorem Prod.associated_iff {M N : Type*} [Monoid M] [Monoid N] {x z : M × N} :
x ~ᵤ z ↔ x.1 ~ᵤ z.1 ∧ x.2 ~ᵤ z.2 :=
⟨fun ⟨u, hu⟩ => ⟨⟨(MulEquiv.prodUnits.toFun u).1, (Prod.eq_iff_fst_eq_snd_eq.1 hu).1⟩,
⟨(MulEquiv.prodUnits.toFun u).2, (Prod.eq_iff_fst_eq_snd_eq.1 hu).2⟩⟩,
fun ⟨⟨u₁, h₁⟩, ⟨u₂, h₂⟩⟩ =>
⟨MulEquiv.prodUnits.invFun (u₁, u₂), Prod.eq_iff_fst_eq_snd_eq.2 ⟨h₁, h₂⟩⟩⟩
theorem Associated.prod {M : Type*} [CommMonoid M] {ι : Type*} (s : Finset ι) (f : ι → M)
(g : ι → M) (h : ∀ i, i ∈ s → (f i) ~ᵤ (g i)) : (∏ i ∈ s, f i) ~ᵤ (∏ i ∈ s, g i) := by
induction s using Finset.induction with
| empty =>
simp only [Finset.prod_empty]
rfl
| @insert j s hjs IH =>
classical
convert_to (∏ i ∈ insert j s, f i) ~ᵤ (∏ i ∈ insert j s, g i)
rw [Finset.prod_insert hjs, Finset.prod_insert hjs]
exact Associated.mul_mul (h j (Finset.mem_insert_self j s))
(IH (fun i hi ↦ h i (Finset.mem_insert_of_mem hi)))
theorem exists_associated_mem_of_dvd_prod [CancelCommMonoidWithZero α] {p : α} (hp : Prime p)
{s : Multiset α} : (∀ r ∈ s, Prime r) → p ∣ s.prod → ∃ q ∈ s, p ~ᵤ q :=
Multiset.induction_on s (by simp [mt isUnit_iff_dvd_one.2 hp.not_unit]) fun a s ih hs hps => by
rw [Multiset.prod_cons] at hps
cases' hp.dvd_or_dvd hps with h h
· have hap := hs a (Multiset.mem_cons.2 (Or.inl rfl))
exact ⟨a, Multiset.mem_cons_self a _, hp.associated_of_dvd hap h⟩
· rcases ih (fun r hr => hs _ (Multiset.mem_cons.2 (Or.inr hr))) h with ⟨q, hq₁, hq₂⟩
exact ⟨q, Multiset.mem_cons.2 (Or.inr hq₁), hq₂⟩
#align exists_associated_mem_of_dvd_prod exists_associated_mem_of_dvd_prod
theorem Multiset.prod_primes_dvd [CancelCommMonoidWithZero α]
[∀ a : α, DecidablePred (Associated a)] {s : Multiset α} (n : α) (h : ∀ a ∈ s, Prime a)
(div : ∀ a ∈ s, a ∣ n) (uniq : ∀ a, s.countP (Associated a) ≤ 1) : s.prod ∣ n := by
induction' s using Multiset.induction_on with a s induct n primes divs generalizing n
· simp only [Multiset.prod_zero, one_dvd]
· rw [Multiset.prod_cons]
obtain ⟨k, rfl⟩ : a ∣ n := div a (Multiset.mem_cons_self a s)
apply mul_dvd_mul_left a
refine induct _ (fun a ha => h a (Multiset.mem_cons_of_mem ha)) (fun b b_in_s => ?_)
fun a => (Multiset.countP_le_of_le _ (Multiset.le_cons_self _ _)).trans (uniq a)
have b_div_n := div b (Multiset.mem_cons_of_mem b_in_s)
have a_prime := h a (Multiset.mem_cons_self a s)
have b_prime := h b (Multiset.mem_cons_of_mem b_in_s)
refine (b_prime.dvd_or_dvd b_div_n).resolve_left fun b_div_a => ?_
have assoc := b_prime.associated_of_dvd a_prime b_div_a
have := uniq a
rw [Multiset.countP_cons_of_pos _ (Associated.refl _), Nat.succ_le_succ_iff, ← not_lt,
Multiset.countP_pos] at this
exact this ⟨b, b_in_s, assoc.symm⟩
#align multiset.prod_primes_dvd Multiset.prod_primes_dvd
theorem Finset.prod_primes_dvd [CancelCommMonoidWithZero α] [Unique αˣ] {s : Finset α} (n : α)
(h : ∀ a ∈ s, Prime a) (div : ∀ a ∈ s, a ∣ n) : (∏ p ∈ s, p) ∣ n := by
classical
exact
Multiset.prod_primes_dvd n (by simpa only [Multiset.map_id', Finset.mem_def] using h)
(by simpa only [Multiset.map_id', Finset.mem_def] using div)
(by
simp only [Multiset.map_id', associated_eq_eq, Multiset.countP_eq_card_filter,
← s.val.count_eq_card_filter_eq, ← Multiset.nodup_iff_count_le_one, s.nodup])
#align finset.prod_primes_dvd Finset.prod_primes_dvd
namespace Associates
section CommMonoid
variable [CommMonoid α]
theorem prod_mk {p : Multiset α} : (p.map Associates.mk).prod = Associates.mk p.prod :=
Multiset.induction_on p (by simp) fun a s ih => by simp [ih, Associates.mk_mul_mk]
#align associates.prod_mk Associates.prod_mk
| Mathlib/Algebra/BigOperators/Associated.lean | 124 | 130 | theorem finset_prod_mk {p : Finset β} {f : β → α} :
(∏ i ∈ p, Associates.mk (f i)) = Associates.mk (∏ i ∈ p, f i) := by |
-- Porting note: added
have : (fun i => Associates.mk (f i)) = Associates.mk ∘ f :=
funext fun x => Function.comp_apply
rw [Finset.prod_eq_multiset_prod, this, ← Multiset.map_map, prod_mk,
← Finset.prod_eq_multiset_prod]
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Yaël Dillies
-/
import Mathlib.Order.Cover
import Mathlib.Order.Interval.Finset.Defs
#align_import data.finset.locally_finite from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Intervals as finsets
This file provides basic results about all the `Finset.Ixx`, which are defined in
`Order.Interval.Finset.Defs`.
In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of,
respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly
functions whose domain is a locally finite order. In particular, this file proves:
* `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿`
* `lt_iff_transGen_covBy`: `≤` is the transitive closure of `⩿`
* `monotone_iff_forall_wcovBy`: Characterization of monotone functions
* `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions
## TODO
This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to
generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general,
what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure.
Complete the API. See
https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235
for some ideas.
-/
assert_not_exists MonoidWithZero
assert_not_exists Finset.sum
open Function OrderDual
open FinsetInterval
variable {ι α : Type*}
namespace Finset
section Preorder
variable [Preorder α]
section LocallyFiniteOrder
variable [LocallyFiniteOrder α] {a a₁ a₂ b b₁ b₂ c x : α}
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by
rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc]
#align finset.nonempty_Icc Finset.nonempty_Icc
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico]
#align finset.nonempty_Ico Finset.nonempty_Ico
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc]
#align finset.nonempty_Ioc Finset.nonempty_Ioc
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo]
#align finset.nonempty_Ioo Finset.nonempty_Ioo
@[simp]
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff]
#align finset.Icc_eq_empty_iff Finset.Icc_eq_empty_iff
@[simp]
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff]
#align finset.Ico_eq_empty_iff Finset.Ico_eq_empty_iff
@[simp]
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff]
#align finset.Ioc_eq_empty_iff Finset.Ioc_eq_empty_iff
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff]
#align finset.Ioo_eq_empty_iff Finset.Ioo_eq_empty_iff
alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff
#align finset.Icc_eq_empty Finset.Icc_eq_empty
alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff
#align finset.Ico_eq_empty Finset.Ico_eq_empty
alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff
#align finset.Ioc_eq_empty Finset.Ioc_eq_empty
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2)
#align finset.Ioo_eq_empty Finset.Ioo_eq_empty
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
#align finset.Icc_eq_empty_of_lt Finset.Icc_eq_empty_of_lt
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
#align finset.Ico_eq_empty_of_le Finset.Ico_eq_empty_of_le
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
#align finset.Ioc_eq_empty_of_le Finset.Ioc_eq_empty_of_le
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
#align finset.Ioo_eq_empty_of_le Finset.Ioo_eq_empty_of_le
-- porting note (#10618): simp can prove this
-- @[simp]
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and_iff, le_rfl]
#align finset.left_mem_Icc Finset.left_mem_Icc
-- porting note (#10618): simp can prove this
-- @[simp]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and_iff, le_refl]
#align finset.left_mem_Ico Finset.left_mem_Ico
-- porting note (#10618): simp can prove this
-- @[simp]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true_iff, le_rfl]
#align finset.right_mem_Icc Finset.right_mem_Icc
-- porting note (#10618): simp can prove this
-- @[simp]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true_iff, le_rfl]
#align finset.right_mem_Ioc Finset.right_mem_Ioc
-- porting note (#10618): simp can prove this
-- @[simp]
theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1
#align finset.left_not_mem_Ioc Finset.left_not_mem_Ioc
-- porting note (#10618): simp can prove this
-- @[simp]
theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1
#align finset.left_not_mem_Ioo Finset.left_not_mem_Ioo
-- porting note (#10618): simp can prove this
-- @[simp]
theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2
#align finset.right_not_mem_Ico Finset.right_not_mem_Ico
-- porting note (#10618): simp can prove this
-- @[simp]
theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2
#align finset.right_not_mem_Ioo Finset.right_not_mem_Ioo
theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by
simpa [← coe_subset] using Set.Icc_subset_Icc ha hb
#align finset.Icc_subset_Icc Finset.Icc_subset_Icc
theorem Ico_subset_Ico (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := by
simpa [← coe_subset] using Set.Ico_subset_Ico ha hb
#align finset.Ico_subset_Ico Finset.Ico_subset_Ico
theorem Ioc_subset_Ioc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := by
simpa [← coe_subset] using Set.Ioc_subset_Ioc ha hb
#align finset.Ioc_subset_Ioc Finset.Ioc_subset_Ioc
theorem Ioo_subset_Ioo (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := by
simpa [← coe_subset] using Set.Ioo_subset_Ioo ha hb
#align finset.Ioo_subset_Ioo Finset.Ioo_subset_Ioo
theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b :=
Icc_subset_Icc h le_rfl
#align finset.Icc_subset_Icc_left Finset.Icc_subset_Icc_left
theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b :=
Ico_subset_Ico h le_rfl
#align finset.Ico_subset_Ico_left Finset.Ico_subset_Ico_left
theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b :=
Ioc_subset_Ioc h le_rfl
#align finset.Ioc_subset_Ioc_left Finset.Ioc_subset_Ioc_left
theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b :=
Ioo_subset_Ioo h le_rfl
#align finset.Ioo_subset_Ioo_left Finset.Ioo_subset_Ioo_left
theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ :=
Icc_subset_Icc le_rfl h
#align finset.Icc_subset_Icc_right Finset.Icc_subset_Icc_right
theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ :=
Ico_subset_Ico le_rfl h
#align finset.Ico_subset_Ico_right Finset.Ico_subset_Ico_right
theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ :=
Ioc_subset_Ioc le_rfl h
#align finset.Ioc_subset_Ioc_right Finset.Ioc_subset_Ioc_right
theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ :=
Ioo_subset_Ioo le_rfl h
#align finset.Ioo_subset_Ioo_right Finset.Ioo_subset_Ioo_right
theorem Ico_subset_Ioo_left (h : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := by
rw [← coe_subset, coe_Ico, coe_Ioo]
exact Set.Ico_subset_Ioo_left h
#align finset.Ico_subset_Ioo_left Finset.Ico_subset_Ioo_left
theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := by
rw [← coe_subset, coe_Ioc, coe_Ioo]
exact Set.Ioc_subset_Ioo_right h
#align finset.Ioc_subset_Ioo_right Finset.Ioc_subset_Ioo_right
theorem Icc_subset_Ico_right (h : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico]
exact Set.Icc_subset_Ico_right h
#align finset.Icc_subset_Ico_right Finset.Icc_subset_Ico_right
theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := by
rw [← coe_subset, coe_Ioo, coe_Ico]
exact Set.Ioo_subset_Ico_self
#align finset.Ioo_subset_Ico_self Finset.Ioo_subset_Ico_self
theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := by
rw [← coe_subset, coe_Ioo, coe_Ioc]
exact Set.Ioo_subset_Ioc_self
#align finset.Ioo_subset_Ioc_self Finset.Ioo_subset_Ioc_self
theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ico, coe_Icc]
exact Set.Ico_subset_Icc_self
#align finset.Ico_subset_Icc_self Finset.Ico_subset_Icc_self
theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ioc, coe_Icc]
exact Set.Ioc_subset_Icc_self
#align finset.Ioc_subset_Icc_self Finset.Ioc_subset_Icc_self
theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b :=
Ioo_subset_Ico_self.trans Ico_subset_Icc_self
#align finset.Ioo_subset_Icc_self Finset.Ioo_subset_Icc_self
theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by
rw [← coe_subset, coe_Icc, coe_Icc, Set.Icc_subset_Icc_iff h₁]
#align finset.Icc_subset_Icc_iff Finset.Icc_subset_Icc_iff
theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ioo, Set.Icc_subset_Ioo_iff h₁]
#align finset.Icc_subset_Ioo_iff Finset.Icc_subset_Ioo_iff
theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico, Set.Icc_subset_Ico_iff h₁]
#align finset.Icc_subset_Ico_iff Finset.Icc_subset_Ico_iff
theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ :=
(Icc_subset_Ico_iff h₁.dual).trans and_comm
#align finset.Icc_subset_Ioc_iff Finset.Icc_subset_Ioc_iff
--TODO: `Ico_subset_Ioo_iff`, `Ioc_subset_Ioo_iff`
theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_left hI ha hb
#align finset.Icc_ssubset_Icc_left Finset.Icc_ssubset_Icc_left
theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_right hI ha hb
#align finset.Icc_ssubset_Icc_right Finset.Icc_ssubset_Icc_right
variable (a)
-- porting note (#10618): simp can prove this
-- @[simp]
theorem Ico_self : Ico a a = ∅ :=
Ico_eq_empty <| lt_irrefl _
#align finset.Ico_self Finset.Ico_self
-- porting note (#10618): simp can prove this
-- @[simp]
theorem Ioc_self : Ioc a a = ∅ :=
Ioc_eq_empty <| lt_irrefl _
#align finset.Ioc_self Finset.Ioc_self
-- porting note (#10618): simp can prove this
-- @[simp]
theorem Ioo_self : Ioo a a = ∅ :=
Ioo_eq_empty <| lt_irrefl _
#align finset.Ioo_self Finset.Ioo_self
variable {a}
/-- A set with upper and lower bounds in a locally finite order is a fintype -/
def _root_.Set.fintypeOfMemBounds {s : Set α} [DecidablePred (· ∈ s)] (ha : a ∈ lowerBounds s)
(hb : b ∈ upperBounds s) : Fintype s :=
Set.fintypeSubset (Set.Icc a b) fun _ hx => ⟨ha hx, hb hx⟩
#align set.fintype_of_mem_bounds Set.fintypeOfMemBounds
section Filter
theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) :
(Ico a b).filter (· < c) = ∅ :=
filter_false_of_mem fun _ hx => (hca.trans (mem_Ico.1 hx).1).not_lt
#align finset.Ico_filter_lt_of_le_left Finset.Ico_filter_lt_of_le_left
theorem Ico_filter_lt_of_right_le [DecidablePred (· < c)] (hbc : b ≤ c) :
(Ico a b).filter (· < c) = Ico a b :=
filter_true_of_mem fun _ hx => (mem_Ico.1 hx).2.trans_le hbc
#align finset.Ico_filter_lt_of_right_le Finset.Ico_filter_lt_of_right_le
theorem Ico_filter_lt_of_le_right [DecidablePred (· < c)] (hcb : c ≤ b) :
(Ico a b).filter (· < c) = Ico a c := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_right_comm]
exact and_iff_left_of_imp fun h => h.2.trans_le hcb
#align finset.Ico_filter_lt_of_le_right Finset.Ico_filter_lt_of_le_right
theorem Ico_filter_le_of_le_left {a b c : α} [DecidablePred (c ≤ ·)] (hca : c ≤ a) :
(Ico a b).filter (c ≤ ·) = Ico a b :=
filter_true_of_mem fun _ hx => hca.trans (mem_Ico.1 hx).1
#align finset.Ico_filter_le_of_le_left Finset.Ico_filter_le_of_le_left
theorem Ico_filter_le_of_right_le {a b : α} [DecidablePred (b ≤ ·)] :
(Ico a b).filter (b ≤ ·) = ∅ :=
filter_false_of_mem fun _ hx => (mem_Ico.1 hx).2.not_le
#align finset.Ico_filter_le_of_right_le Finset.Ico_filter_le_of_right_le
theorem Ico_filter_le_of_left_le {a b c : α} [DecidablePred (c ≤ ·)] (hac : a ≤ c) :
(Ico a b).filter (c ≤ ·) = Ico c b := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_comm, and_left_comm]
exact and_iff_right_of_imp fun h => hac.trans h.1
#align finset.Ico_filter_le_of_left_le Finset.Ico_filter_le_of_left_le
theorem Icc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
(Icc a b).filter (· < c) = Icc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Icc.1 hx).2 h
#align finset.Icc_filter_lt_of_lt_right Finset.Icc_filter_lt_of_lt_right
theorem Ioc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
(Ioc a b).filter (· < c) = Ioc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Ioc.1 hx).2 h
#align finset.Ioc_filter_lt_of_lt_right Finset.Ioc_filter_lt_of_lt_right
theorem Iic_filter_lt_of_lt_right {α} [Preorder α] [LocallyFiniteOrderBot α] {a c : α}
[DecidablePred (· < c)] (h : a < c) : (Iic a).filter (· < c) = Iic a :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Iic.1 hx) h
#align finset.Iic_filter_lt_of_lt_right Finset.Iic_filter_lt_of_lt_right
variable (a b) [Fintype α]
theorem filter_lt_lt_eq_Ioo [DecidablePred fun j => a < j ∧ j < b] :
(univ.filter fun j => a < j ∧ j < b) = Ioo a b := by
ext
simp
#align finset.filter_lt_lt_eq_Ioo Finset.filter_lt_lt_eq_Ioo
theorem filter_lt_le_eq_Ioc [DecidablePred fun j => a < j ∧ j ≤ b] :
(univ.filter fun j => a < j ∧ j ≤ b) = Ioc a b := by
ext
simp
#align finset.filter_lt_le_eq_Ioc Finset.filter_lt_le_eq_Ioc
theorem filter_le_lt_eq_Ico [DecidablePred fun j => a ≤ j ∧ j < b] :
(univ.filter fun j => a ≤ j ∧ j < b) = Ico a b := by
ext
simp
#align finset.filter_le_lt_eq_Ico Finset.filter_le_lt_eq_Ico
theorem filter_le_le_eq_Icc [DecidablePred fun j => a ≤ j ∧ j ≤ b] :
(univ.filter fun j => a ≤ j ∧ j ≤ b) = Icc a b := by
ext
simp
#align finset.filter_le_le_eq_Icc Finset.filter_le_le_eq_Icc
end Filter
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Ici : (Ici a).Nonempty := ⟨a, mem_Ici.2 le_rfl⟩
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Ioi : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [Finset.Nonempty]
theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Icc_subset_Ici_self
#align finset.Icc_subset_Ici_self Finset.Icc_subset_Ici_self
theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Ico_subset_Ici_self
#align finset.Ico_subset_Ici_self Finset.Ico_subset_Ici_self
theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioc_subset_Ioi_self
#align finset.Ioc_subset_Ioi_self Finset.Ioc_subset_Ioi_self
theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioo_subset_Ioi_self
#align finset.Ioo_subset_Ioi_self Finset.Ioo_subset_Ioi_self
theorem Ioc_subset_Ici_self : Ioc a b ⊆ Ici a :=
Ioc_subset_Icc_self.trans Icc_subset_Ici_self
#align finset.Ioc_subset_Ici_self Finset.Ioc_subset_Ici_self
theorem Ioo_subset_Ici_self : Ioo a b ⊆ Ici a :=
Ioo_subset_Ico_self.trans Ico_subset_Ici_self
#align finset.Ioo_subset_Ici_self Finset.Ioo_subset_Ici_self
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α]
@[simp] lemma nonempty_Iic : (Iic a).Nonempty := ⟨a, mem_Iic.2 le_rfl⟩
@[simp] lemma nonempty_Iio : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [Finset.Nonempty]
theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Icc_subset_Iic_self
#align finset.Icc_subset_Iic_self Finset.Icc_subset_Iic_self
theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Ioc_subset_Iic_self
#align finset.Ioc_subset_Iic_self Finset.Ioc_subset_Iic_self
theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ico_subset_Iio_self
#align finset.Ico_subset_Iio_self Finset.Ico_subset_Iio_self
theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ioo_subset_Iio_self
#align finset.Ioo_subset_Iio_self Finset.Ioo_subset_Iio_self
theorem Ico_subset_Iic_self : Ico a b ⊆ Iic b :=
Ico_subset_Icc_self.trans Icc_subset_Iic_self
#align finset.Ico_subset_Iic_self Finset.Ico_subset_Iic_self
theorem Ioo_subset_Iic_self : Ioo a b ⊆ Iic b :=
Ioo_subset_Ioc_self.trans Ioc_subset_Iic_self
#align finset.Ioo_subset_Iic_self Finset.Ioo_subset_Iic_self
end LocallyFiniteOrderBot
end LocallyFiniteOrder
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α] {a : α}
theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := by
simpa [← coe_subset] using Set.Ioi_subset_Ici_self
#align finset.Ioi_subset_Ici_self Finset.Ioi_subset_Ici_self
theorem _root_.BddBelow.finite {s : Set α} (hs : BddBelow s) : s.Finite :=
let ⟨a, ha⟩ := hs
(Ici a).finite_toSet.subset fun _ hx => mem_Ici.2 <| ha hx
#align bdd_below.finite BddBelow.finite
theorem _root_.Set.Infinite.not_bddBelow {s : Set α} : s.Infinite → ¬BddBelow s :=
mt BddBelow.finite
#align set.infinite.not_bdd_below Set.Infinite.not_bddBelow
variable [Fintype α]
theorem filter_lt_eq_Ioi [DecidablePred (a < ·)] : univ.filter (a < ·) = Ioi a := by
ext
simp
#align finset.filter_lt_eq_Ioi Finset.filter_lt_eq_Ioi
theorem filter_le_eq_Ici [DecidablePred (a ≤ ·)] : univ.filter (a ≤ ·) = Ici a := by
ext
simp
#align finset.filter_le_eq_Ici Finset.filter_le_eq_Ici
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α] {a : α}
theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := by
simpa [← coe_subset] using Set.Iio_subset_Iic_self
#align finset.Iio_subset_Iic_self Finset.Iio_subset_Iic_self
theorem _root_.BddAbove.finite {s : Set α} (hs : BddAbove s) : s.Finite :=
hs.dual.finite
#align bdd_above.finite BddAbove.finite
theorem _root_.Set.Infinite.not_bddAbove {s : Set α} : s.Infinite → ¬BddAbove s :=
mt BddAbove.finite
#align set.infinite.not_bdd_above Set.Infinite.not_bddAbove
variable [Fintype α]
theorem filter_gt_eq_Iio [DecidablePred (· < a)] : univ.filter (· < a) = Iio a := by
ext
simp
#align finset.filter_gt_eq_Iio Finset.filter_gt_eq_Iio
theorem filter_ge_eq_Iic [DecidablePred (· ≤ a)] : univ.filter (· ≤ a) = Iic a := by
ext
simp
#align finset.filter_ge_eq_Iic Finset.filter_ge_eq_Iic
end LocallyFiniteOrderBot
variable [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α]
theorem disjoint_Ioi_Iio (a : α) : Disjoint (Ioi a) (Iio a) :=
disjoint_left.2 fun _ hab hba => (mem_Ioi.1 hab).not_lt <| mem_Iio.1 hba
#align finset.disjoint_Ioi_Iio Finset.disjoint_Ioi_Iio
end Preorder
section PartialOrder
variable [PartialOrder α] [LocallyFiniteOrder α] {a b c : α}
@[simp]
theorem Icc_self (a : α) : Icc a a = {a} := by rw [← coe_eq_singleton, coe_Icc, Set.Icc_self]
#align finset.Icc_self Finset.Icc_self
@[simp]
theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by
rw [← coe_eq_singleton, coe_Icc, Set.Icc_eq_singleton_iff]
#align finset.Icc_eq_singleton_iff Finset.Icc_eq_singleton_iff
theorem Ico_disjoint_Ico_consecutive (a b c : α) : Disjoint (Ico a b) (Ico b c) :=
disjoint_left.2 fun _ hab hbc => (mem_Ico.mp hab).2.not_le (mem_Ico.mp hbc).1
#align finset.Ico_disjoint_Ico_consecutive Finset.Ico_disjoint_Ico_consecutive
section DecidableEq
variable [DecidableEq α]
@[simp]
theorem Icc_erase_left (a b : α) : (Icc a b).erase a = Ioc a b := by simp [← coe_inj]
#align finset.Icc_erase_left Finset.Icc_erase_left
@[simp]
theorem Icc_erase_right (a b : α) : (Icc a b).erase b = Ico a b := by simp [← coe_inj]
#align finset.Icc_erase_right Finset.Icc_erase_right
@[simp]
theorem Ico_erase_left (a b : α) : (Ico a b).erase a = Ioo a b := by simp [← coe_inj]
#align finset.Ico_erase_left Finset.Ico_erase_left
@[simp]
theorem Ioc_erase_right (a b : α) : (Ioc a b).erase b = Ioo a b := by simp [← coe_inj]
#align finset.Ioc_erase_right Finset.Ioc_erase_right
@[simp]
theorem Icc_diff_both (a b : α) : Icc a b \ {a, b} = Ioo a b := by simp [← coe_inj]
#align finset.Icc_diff_both Finset.Icc_diff_both
@[simp]
theorem Ico_insert_right (h : a ≤ b) : insert b (Ico a b) = Icc a b := by
rw [← coe_inj, coe_insert, coe_Icc, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ico_union_right h]
#align finset.Ico_insert_right Finset.Ico_insert_right
@[simp]
theorem Ioc_insert_left (h : a ≤ b) : insert a (Ioc a b) = Icc a b := by
rw [← coe_inj, coe_insert, coe_Ioc, coe_Icc, Set.insert_eq, Set.union_comm, Set.Ioc_union_left h]
#align finset.Ioc_insert_left Finset.Ioc_insert_left
@[simp]
theorem Ioo_insert_left (h : a < b) : insert a (Ioo a b) = Ico a b := by
rw [← coe_inj, coe_insert, coe_Ioo, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ioo_union_left h]
#align finset.Ioo_insert_left Finset.Ioo_insert_left
@[simp]
theorem Ioo_insert_right (h : a < b) : insert b (Ioo a b) = Ioc a b := by
rw [← coe_inj, coe_insert, coe_Ioo, coe_Ioc, Set.insert_eq, Set.union_comm, Set.Ioo_union_right h]
#align finset.Ioo_insert_right Finset.Ioo_insert_right
@[simp]
theorem Icc_diff_Ico_self (h : a ≤ b) : Icc a b \ Ico a b = {b} := by simp [← coe_inj, h]
#align finset.Icc_diff_Ico_self Finset.Icc_diff_Ico_self
@[simp]
theorem Icc_diff_Ioc_self (h : a ≤ b) : Icc a b \ Ioc a b = {a} := by simp [← coe_inj, h]
#align finset.Icc_diff_Ioc_self Finset.Icc_diff_Ioc_self
@[simp]
theorem Icc_diff_Ioo_self (h : a ≤ b) : Icc a b \ Ioo a b = {a, b} := by simp [← coe_inj, h]
#align finset.Icc_diff_Ioo_self Finset.Icc_diff_Ioo_self
@[simp]
theorem Ico_diff_Ioo_self (h : a < b) : Ico a b \ Ioo a b = {a} := by simp [← coe_inj, h]
#align finset.Ico_diff_Ioo_self Finset.Ico_diff_Ioo_self
@[simp]
theorem Ioc_diff_Ioo_self (h : a < b) : Ioc a b \ Ioo a b = {b} := by simp [← coe_inj, h]
#align finset.Ioc_diff_Ioo_self Finset.Ioc_diff_Ioo_self
@[simp]
theorem Ico_inter_Ico_consecutive (a b c : α) : Ico a b ∩ Ico b c = ∅ :=
(Ico_disjoint_Ico_consecutive a b c).eq_bot
#align finset.Ico_inter_Ico_consecutive Finset.Ico_inter_Ico_consecutive
end DecidableEq
-- Those lemmas are purposefully the other way around
/-- `Finset.cons` version of `Finset.Ico_insert_right`. -/
theorem Icc_eq_cons_Ico (h : a ≤ b) : Icc a b = (Ico a b).cons b right_not_mem_Ico := by
classical rw [cons_eq_insert, Ico_insert_right h]
#align finset.Icc_eq_cons_Ico Finset.Icc_eq_cons_Ico
/-- `Finset.cons` version of `Finset.Ioc_insert_left`. -/
| Mathlib/Order/Interval/Finset/Basic.lean | 630 | 631 | theorem Icc_eq_cons_Ioc (h : a ≤ b) : Icc a b = (Ioc a b).cons a left_not_mem_Ioc := by |
classical rw [cons_eq_insert, Ioc_insert_left h]
|
/-
Copyright (c) 2021 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Eric Wieser
-/
import Mathlib.RingTheory.Ideal.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.RingTheory.GradedAlgebra.Basic
#align_import ring_theory.graded_algebra.homogeneous_ideal from "leanprover-community/mathlib"@"4e861f25ba5ceef42ba0712d8ffeb32f38ad6441"
/-!
# Homogeneous ideals of a graded algebra
This file defines homogeneous ideals of `GradedRing 𝒜` where `𝒜 : ι → Submodule R A` and
operations on them.
## Main definitions
For any `I : Ideal A`:
* `Ideal.IsHomogeneous 𝒜 I`: The property that an ideal is closed under `GradedRing.proj`.
* `HomogeneousIdeal 𝒜`: The structure extending ideals which satisfy `Ideal.IsHomogeneous`.
* `Ideal.homogeneousCore I 𝒜`: The largest homogeneous ideal smaller than `I`.
* `Ideal.homogeneousHull I 𝒜`: The smallest homogeneous ideal larger than `I`.
## Main statements
* `HomogeneousIdeal.completeLattice`: `Ideal.IsHomogeneous` is preserved by `⊥`, `⊤`, `⊔`, `⊓`,
`⨆`, `⨅`, and so the subtype of homogeneous ideals inherits a complete lattice structure.
* `Ideal.homogeneousCore.gi`: `Ideal.homogeneousCore` forms a galois insertion with coercion.
* `Ideal.homogeneousHull.gi`: `Ideal.homogeneousHull` forms a galois insertion with coercion.
## Implementation notes
We introduce `Ideal.homogeneousCore'` earlier than might be expected so that we can get access
to `Ideal.IsHomogeneous.iff_exists` as quickly as possible.
## Tags
graded algebra, homogeneous
-/
open SetLike DirectSum Set
open Pointwise DirectSum
variable {ι σ R A : Type*}
section HomogeneousDef
variable [Semiring A]
variable [SetLike σ A] [AddSubmonoidClass σ A] (𝒜 : ι → σ)
variable [DecidableEq ι] [AddMonoid ι] [GradedRing 𝒜]
variable (I : Ideal A)
/-- An `I : Ideal A` is homogeneous if for every `r ∈ I`, all homogeneous components
of `r` are in `I`. -/
def Ideal.IsHomogeneous : Prop :=
∀ (i : ι) ⦃r : A⦄, r ∈ I → (DirectSum.decompose 𝒜 r i : A) ∈ I
#align ideal.is_homogeneous Ideal.IsHomogeneous
theorem Ideal.IsHomogeneous.mem_iff {I} (hI : Ideal.IsHomogeneous 𝒜 I) {x} :
x ∈ I ↔ ∀ i, (decompose 𝒜 x i : A) ∈ I := by
classical
refine ⟨fun hx i ↦ hI i hx, fun hx ↦ ?_⟩
rw [← DirectSum.sum_support_decompose 𝒜 x]
exact Ideal.sum_mem _ (fun i _ ↦ hx i)
/-- For any `Semiring A`, we collect the homogeneous ideals of `A` into a type. -/
structure HomogeneousIdeal extends Submodule A A where
is_homogeneous' : Ideal.IsHomogeneous 𝒜 toSubmodule
#align homogeneous_ideal HomogeneousIdeal
variable {𝒜}
/-- Converting a homogeneous ideal to an ideal. -/
def HomogeneousIdeal.toIdeal (I : HomogeneousIdeal 𝒜) : Ideal A :=
I.toSubmodule
#align homogeneous_ideal.to_ideal HomogeneousIdeal.toIdeal
theorem HomogeneousIdeal.isHomogeneous (I : HomogeneousIdeal 𝒜) : I.toIdeal.IsHomogeneous 𝒜 :=
I.is_homogeneous'
#align homogeneous_ideal.is_homogeneous HomogeneousIdeal.isHomogeneous
theorem HomogeneousIdeal.toIdeal_injective :
Function.Injective (HomogeneousIdeal.toIdeal : HomogeneousIdeal 𝒜 → Ideal A) :=
fun ⟨x, hx⟩ ⟨y, hy⟩ => fun (h : x = y) => by simp [h]
#align homogeneous_ideal.to_ideal_injective HomogeneousIdeal.toIdeal_injective
instance HomogeneousIdeal.setLike : SetLike (HomogeneousIdeal 𝒜) A where
coe I := I.toIdeal
coe_injective' _ _ h := HomogeneousIdeal.toIdeal_injective <| SetLike.coe_injective h
#align homogeneous_ideal.set_like HomogeneousIdeal.setLike
@[ext]
theorem HomogeneousIdeal.ext {I J : HomogeneousIdeal 𝒜} (h : I.toIdeal = J.toIdeal) : I = J :=
HomogeneousIdeal.toIdeal_injective h
#align homogeneous_ideal.ext HomogeneousIdeal.ext
theorem HomogeneousIdeal.ext' {I J : HomogeneousIdeal 𝒜} (h : ∀ i, ∀ x ∈ 𝒜 i, x ∈ I ↔ x ∈ J) :
I = J := by
ext
rw [I.isHomogeneous.mem_iff, J.isHomogeneous.mem_iff]
apply forall_congr'
exact fun i ↦ h i _ (decompose 𝒜 _ i).2
@[simp]
theorem HomogeneousIdeal.mem_iff {I : HomogeneousIdeal 𝒜} {x : A} : x ∈ I.toIdeal ↔ x ∈ I :=
Iff.rfl
#align homogeneous_ideal.mem_iff HomogeneousIdeal.mem_iff
end HomogeneousDef
section HomogeneousCore
variable [Semiring A]
variable [SetLike σ A] (𝒜 : ι → σ)
variable (I : Ideal A)
/-- For any `I : Ideal A`, not necessarily homogeneous, `I.homogeneousCore' 𝒜`
is the largest homogeneous ideal of `A` contained in `I`, as an ideal. -/
def Ideal.homogeneousCore' (I : Ideal A) : Ideal A :=
Ideal.span ((↑) '' (((↑) : Subtype (Homogeneous 𝒜) → A) ⁻¹' I))
#align ideal.homogeneous_core' Ideal.homogeneousCore'
theorem Ideal.homogeneousCore'_mono : Monotone (Ideal.homogeneousCore' 𝒜) :=
fun _ _ I_le_J => Ideal.span_mono <| Set.image_subset _ fun _ => @I_le_J _
#align ideal.homogeneous_core'_mono Ideal.homogeneousCore'_mono
theorem Ideal.homogeneousCore'_le : I.homogeneousCore' 𝒜 ≤ I :=
Ideal.span_le.2 <| image_preimage_subset _ _
#align ideal.homogeneous_core'_le Ideal.homogeneousCore'_le
end HomogeneousCore
section IsHomogeneousIdealDefs
variable [Semiring A]
variable [SetLike σ A] [AddSubmonoidClass σ A] (𝒜 : ι → σ)
variable [DecidableEq ι] [AddMonoid ι] [GradedRing 𝒜]
variable (I : Ideal A)
theorem Ideal.isHomogeneous_iff_forall_subset :
I.IsHomogeneous 𝒜 ↔ ∀ i, (I : Set A) ⊆ GradedRing.proj 𝒜 i ⁻¹' I :=
Iff.rfl
#align ideal.is_homogeneous_iff_forall_subset Ideal.isHomogeneous_iff_forall_subset
theorem Ideal.isHomogeneous_iff_subset_iInter :
I.IsHomogeneous 𝒜 ↔ (I : Set A) ⊆ ⋂ i, GradedRing.proj 𝒜 i ⁻¹' ↑I :=
subset_iInter_iff.symm
#align ideal.is_homogeneous_iff_subset_Inter Ideal.isHomogeneous_iff_subset_iInter
theorem Ideal.mul_homogeneous_element_mem_of_mem {I : Ideal A} (r x : A) (hx₁ : Homogeneous 𝒜 x)
(hx₂ : x ∈ I) (j : ι) : GradedRing.proj 𝒜 j (r * x) ∈ I := by
classical
rw [← DirectSum.sum_support_decompose 𝒜 r, Finset.sum_mul, map_sum]
apply Ideal.sum_mem
intro k _
obtain ⟨i, hi⟩ := hx₁
have mem₁ : (DirectSum.decompose 𝒜 r k : A) * x ∈ 𝒜 (k + i) :=
GradedMul.mul_mem (SetLike.coe_mem _) hi
erw [GradedRing.proj_apply, DirectSum.decompose_of_mem 𝒜 mem₁, coe_of_apply]
split_ifs
· exact I.mul_mem_left _ hx₂
· exact I.zero_mem
#align ideal.mul_homogeneous_element_mem_of_mem Ideal.mul_homogeneous_element_mem_of_mem
theorem Ideal.homogeneous_span (s : Set A) (h : ∀ x ∈ s, Homogeneous 𝒜 x) :
(Ideal.span s).IsHomogeneous 𝒜 := by
rintro i r hr
rw [Ideal.span, Finsupp.span_eq_range_total] at hr
rw [LinearMap.mem_range] at hr
obtain ⟨s, rfl⟩ := hr
rw [Finsupp.total_apply, Finsupp.sum, decompose_sum, DFinsupp.finset_sum_apply,
AddSubmonoidClass.coe_finset_sum]
refine Ideal.sum_mem _ ?_
rintro z hz1
rw [smul_eq_mul]
refine Ideal.mul_homogeneous_element_mem_of_mem 𝒜 (s z) z ?_ ?_ i
· rcases z with ⟨z, hz2⟩
apply h _ hz2
· exact Ideal.subset_span z.2
#align ideal.is_homogeneous_span Ideal.homogeneous_span
/-- For any `I : Ideal A`, not necessarily homogeneous, `I.homogeneousCore' 𝒜`
is the largest homogeneous ideal of `A` contained in `I`. -/
def Ideal.homogeneousCore : HomogeneousIdeal 𝒜 :=
⟨Ideal.homogeneousCore' 𝒜 I,
Ideal.homogeneous_span _ _ fun _ h => by
have := Subtype.image_preimage_coe (setOf (Homogeneous 𝒜)) (I : Set A)
exact (cast congr(_ ∈ $this) h).1⟩
#align ideal.homogeneous_core Ideal.homogeneousCore
theorem Ideal.homogeneousCore_mono : Monotone (Ideal.homogeneousCore 𝒜) :=
Ideal.homogeneousCore'_mono 𝒜
#align ideal.homogeneous_core_mono Ideal.homogeneousCore_mono
theorem Ideal.toIdeal_homogeneousCore_le : (I.homogeneousCore 𝒜).toIdeal ≤ I :=
Ideal.homogeneousCore'_le 𝒜 I
#align ideal.to_ideal_homogeneous_core_le Ideal.toIdeal_homogeneousCore_le
variable {𝒜 I}
theorem Ideal.mem_homogeneousCore_of_homogeneous_of_mem {x : A} (h : SetLike.Homogeneous 𝒜 x)
(hmem : x ∈ I) : x ∈ I.homogeneousCore 𝒜 :=
Ideal.subset_span ⟨⟨x, h⟩, hmem, rfl⟩
#align ideal.mem_homogeneous_core_of_is_homogeneous_of_mem Ideal.mem_homogeneousCore_of_homogeneous_of_mem
theorem Ideal.IsHomogeneous.toIdeal_homogeneousCore_eq_self (h : I.IsHomogeneous 𝒜) :
(I.homogeneousCore 𝒜).toIdeal = I := by
apply le_antisymm (I.homogeneousCore'_le 𝒜) _
intro x hx
classical
rw [← DirectSum.sum_support_decompose 𝒜 x]
exact Ideal.sum_mem _ fun j _ => Ideal.subset_span ⟨⟨_, homogeneous_coe _⟩, h _ hx, rfl⟩
#align ideal.is_homogeneous.to_ideal_homogeneous_core_eq_self Ideal.IsHomogeneous.toIdeal_homogeneousCore_eq_self
@[simp]
theorem HomogeneousIdeal.toIdeal_homogeneousCore_eq_self (I : HomogeneousIdeal 𝒜) :
I.toIdeal.homogeneousCore 𝒜 = I := by
ext1
convert Ideal.IsHomogeneous.toIdeal_homogeneousCore_eq_self I.isHomogeneous
#align homogeneous_ideal.to_ideal_homogeneous_core_eq_self HomogeneousIdeal.toIdeal_homogeneousCore_eq_self
variable (𝒜 I)
theorem Ideal.IsHomogeneous.iff_eq : I.IsHomogeneous 𝒜 ↔ (I.homogeneousCore 𝒜).toIdeal = I :=
⟨fun hI => hI.toIdeal_homogeneousCore_eq_self, fun hI => hI ▸ (Ideal.homogeneousCore 𝒜 I).2⟩
#align ideal.is_homogeneous.iff_eq Ideal.IsHomogeneous.iff_eq
theorem Ideal.IsHomogeneous.iff_exists :
I.IsHomogeneous 𝒜 ↔ ∃ S : Set (homogeneousSubmonoid 𝒜), I = Ideal.span ((↑) '' S) := by
rw [Ideal.IsHomogeneous.iff_eq, eq_comm]
exact ((Set.image_preimage.compose (Submodule.gi _ _).gc).exists_eq_l _).symm
#align ideal.is_homogeneous.iff_exists Ideal.IsHomogeneous.iff_exists
end IsHomogeneousIdealDefs
/-! ### Operations
In this section, we show that `Ideal.IsHomogeneous` is preserved by various notations, then use
these results to provide these notation typeclasses for `HomogeneousIdeal`. -/
section Operations
section Semiring
variable [Semiring A] [DecidableEq ι] [AddMonoid ι]
variable [SetLike σ A] [AddSubmonoidClass σ A] (𝒜 : ι → σ) [GradedRing 𝒜]
namespace Ideal.IsHomogeneous
theorem bot : Ideal.IsHomogeneous 𝒜 ⊥ := fun i r hr => by
simp only [Ideal.mem_bot] at hr
rw [hr, decompose_zero, zero_apply]
apply Ideal.zero_mem
#align ideal.is_homogeneous.bot Ideal.IsHomogeneous.bot
theorem top : Ideal.IsHomogeneous 𝒜 ⊤ := fun i r _ => by simp only [Submodule.mem_top]
#align ideal.is_homogeneous.top Ideal.IsHomogeneous.top
variable {𝒜}
theorem inf {I J : Ideal A} (HI : I.IsHomogeneous 𝒜) (HJ : J.IsHomogeneous 𝒜) :
(I ⊓ J).IsHomogeneous 𝒜 :=
fun _ _ hr => ⟨HI _ hr.1, HJ _ hr.2⟩
#align ideal.is_homogeneous.inf Ideal.IsHomogeneous.inf
theorem sup {I J : Ideal A} (HI : I.IsHomogeneous 𝒜) (HJ : J.IsHomogeneous 𝒜) :
(I ⊔ J).IsHomogeneous 𝒜 := by
rw [iff_exists] at HI HJ ⊢
obtain ⟨⟨s₁, rfl⟩, ⟨s₂, rfl⟩⟩ := HI, HJ
refine ⟨s₁ ∪ s₂, ?_⟩
rw [Set.image_union]
exact (Submodule.span_union _ _).symm
#align ideal.is_homogeneous.sup Ideal.IsHomogeneous.sup
protected theorem iSup {κ : Sort*} {f : κ → Ideal A} (h : ∀ i, (f i).IsHomogeneous 𝒜) :
(⨆ i, f i).IsHomogeneous 𝒜 := by
simp_rw [iff_exists] at h ⊢
choose s hs using h
refine ⟨⋃ i, s i, ?_⟩
simp_rw [Set.image_iUnion, Ideal.span_iUnion]
congr
exact funext hs
#align ideal.is_homogeneous.supr Ideal.IsHomogeneous.iSup
protected theorem iInf {κ : Sort*} {f : κ → Ideal A} (h : ∀ i, (f i).IsHomogeneous 𝒜) :
(⨅ i, f i).IsHomogeneous 𝒜 := by
intro i x hx
simp only [Ideal.mem_iInf] at hx ⊢
exact fun j => h _ _ (hx j)
#align ideal.is_homogeneous.infi Ideal.IsHomogeneous.iInf
theorem iSup₂ {κ : Sort*} {κ' : κ → Sort*} {f : ∀ i, κ' i → Ideal A}
(h : ∀ i j, (f i j).IsHomogeneous 𝒜) : (⨆ (i) (j), f i j).IsHomogeneous 𝒜 :=
IsHomogeneous.iSup fun i => IsHomogeneous.iSup <| h i
#align ideal.is_homogeneous.supr₂ Ideal.IsHomogeneous.iSup₂
theorem iInf₂ {κ : Sort*} {κ' : κ → Sort*} {f : ∀ i, κ' i → Ideal A}
(h : ∀ i j, (f i j).IsHomogeneous 𝒜) : (⨅ (i) (j), f i j).IsHomogeneous 𝒜 :=
IsHomogeneous.iInf fun i => IsHomogeneous.iInf <| h i
#align ideal.is_homogeneous.infi₂ Ideal.IsHomogeneous.iInf₂
theorem sSup {ℐ : Set (Ideal A)} (h : ∀ I ∈ ℐ, Ideal.IsHomogeneous 𝒜 I) :
(sSup ℐ).IsHomogeneous 𝒜 := by
rw [sSup_eq_iSup]
exact iSup₂ h
#align ideal.is_homogeneous.Sup Ideal.IsHomogeneous.sSup
theorem sInf {ℐ : Set (Ideal A)} (h : ∀ I ∈ ℐ, Ideal.IsHomogeneous 𝒜 I) :
(sInf ℐ).IsHomogeneous 𝒜 := by
rw [sInf_eq_iInf]
exact iInf₂ h
#align ideal.is_homogeneous.Inf Ideal.IsHomogeneous.sInf
end Ideal.IsHomogeneous
variable {𝒜}
namespace HomogeneousIdeal
instance : PartialOrder (HomogeneousIdeal 𝒜) :=
SetLike.instPartialOrder
instance : Top (HomogeneousIdeal 𝒜) :=
⟨⟨⊤, Ideal.IsHomogeneous.top 𝒜⟩⟩
instance : Bot (HomogeneousIdeal 𝒜) :=
⟨⟨⊥, Ideal.IsHomogeneous.bot 𝒜⟩⟩
instance : Sup (HomogeneousIdeal 𝒜) :=
⟨fun I J => ⟨_, I.isHomogeneous.sup J.isHomogeneous⟩⟩
instance : Inf (HomogeneousIdeal 𝒜) :=
⟨fun I J => ⟨_, I.isHomogeneous.inf J.isHomogeneous⟩⟩
instance : SupSet (HomogeneousIdeal 𝒜) :=
⟨fun S => ⟨⨆ s ∈ S, toIdeal s, Ideal.IsHomogeneous.iSup₂ fun s _ => s.isHomogeneous⟩⟩
instance : InfSet (HomogeneousIdeal 𝒜) :=
⟨fun S => ⟨⨅ s ∈ S, toIdeal s, Ideal.IsHomogeneous.iInf₂ fun s _ => s.isHomogeneous⟩⟩
@[simp]
theorem coe_top : ((⊤ : HomogeneousIdeal 𝒜) : Set A) = univ :=
rfl
#align homogeneous_ideal.coe_top HomogeneousIdeal.coe_top
@[simp]
theorem coe_bot : ((⊥ : HomogeneousIdeal 𝒜) : Set A) = 0 :=
rfl
#align homogeneous_ideal.coe_bot HomogeneousIdeal.coe_bot
@[simp]
theorem coe_sup (I J : HomogeneousIdeal 𝒜) : ↑(I ⊔ J) = (I + J : Set A) :=
Submodule.coe_sup _ _
#align homogeneous_ideal.coe_sup HomogeneousIdeal.coe_sup
@[simp]
theorem coe_inf (I J : HomogeneousIdeal 𝒜) : (↑(I ⊓ J) : Set A) = ↑I ∩ ↑J :=
rfl
#align homogeneous_ideal.coe_inf HomogeneousIdeal.coe_inf
@[simp]
theorem toIdeal_top : (⊤ : HomogeneousIdeal 𝒜).toIdeal = (⊤ : Ideal A) :=
rfl
#align homogeneous_ideal.to_ideal_top HomogeneousIdeal.toIdeal_top
@[simp]
theorem toIdeal_bot : (⊥ : HomogeneousIdeal 𝒜).toIdeal = (⊥ : Ideal A) :=
rfl
#align homogeneous_ideal.to_ideal_bot HomogeneousIdeal.toIdeal_bot
@[simp]
theorem toIdeal_sup (I J : HomogeneousIdeal 𝒜) : (I ⊔ J).toIdeal = I.toIdeal ⊔ J.toIdeal :=
rfl
#align homogeneous_ideal.to_ideal_sup HomogeneousIdeal.toIdeal_sup
@[simp]
theorem toIdeal_inf (I J : HomogeneousIdeal 𝒜) : (I ⊓ J).toIdeal = I.toIdeal ⊓ J.toIdeal :=
rfl
#align homogeneous_ideal.to_ideal_inf HomogeneousIdeal.toIdeal_inf
@[simp]
theorem toIdeal_sSup (ℐ : Set (HomogeneousIdeal 𝒜)) : (sSup ℐ).toIdeal = ⨆ s ∈ ℐ, toIdeal s :=
rfl
#align homogeneous_ideal.to_ideal_Sup HomogeneousIdeal.toIdeal_sSup
@[simp]
theorem toIdeal_sInf (ℐ : Set (HomogeneousIdeal 𝒜)) : (sInf ℐ).toIdeal = ⨅ s ∈ ℐ, toIdeal s :=
rfl
#align homogeneous_ideal.to_ideal_Inf HomogeneousIdeal.toIdeal_sInf
@[simp]
theorem toIdeal_iSup {κ : Sort*} (s : κ → HomogeneousIdeal 𝒜) :
(⨆ i, s i).toIdeal = ⨆ i, (s i).toIdeal := by
rw [iSup, toIdeal_sSup, iSup_range]
#align homogeneous_ideal.to_ideal_supr HomogeneousIdeal.toIdeal_iSup
@[simp]
theorem toIdeal_iInf {κ : Sort*} (s : κ → HomogeneousIdeal 𝒜) :
(⨅ i, s i).toIdeal = ⨅ i, (s i).toIdeal := by
rw [iInf, toIdeal_sInf, iInf_range]
#align homogeneous_ideal.to_ideal_infi HomogeneousIdeal.toIdeal_iInf
-- @[simp] -- Porting note (#10618): simp can prove this
theorem toIdeal_iSup₂ {κ : Sort*} {κ' : κ → Sort*} (s : ∀ i, κ' i → HomogeneousIdeal 𝒜) :
(⨆ (i) (j), s i j).toIdeal = ⨆ (i) (j), (s i j).toIdeal := by
simp_rw [toIdeal_iSup]
#align homogeneous_ideal.to_ideal_supr₂ HomogeneousIdeal.toIdeal_iSup₂
-- @[simp] -- Porting note (#10618): simp can prove this
| Mathlib/RingTheory/GradedAlgebra/HomogeneousIdeal.lean | 416 | 418 | theorem toIdeal_iInf₂ {κ : Sort*} {κ' : κ → Sort*} (s : ∀ i, κ' i → HomogeneousIdeal 𝒜) :
(⨅ (i) (j), s i j).toIdeal = ⨅ (i) (j), (s i j).toIdeal := by |
simp_rw [toIdeal_iInf]
|
/-
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]
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]
#align category_theory.adjunction.hom_equiv_naturality_right CategoryTheory.Adjunction.homEquiv_naturality_right
-- Porting note: Same as above
@[simp, nolint simpNF]
theorem homEquiv_naturality_right_symm (f : X ⟶ G.obj Y) (g : Y ⟶ Y') :
(adj.homEquiv X Y').symm (f ≫ G.map g) = (adj.homEquiv X Y).symm f ≫ g := by
rw [Equiv.symm_apply_eq]
simp only [homEquiv_naturality_right,eq_self_iff_true,Equiv.apply_symm_apply]
#align category_theory.adjunction.hom_equiv_naturality_right_symm CategoryTheory.Adjunction.homEquiv_naturality_right_symm
@[reassoc]
theorem homEquiv_naturality_left_square (f : X' ⟶ X) (g : F.obj X ⟶ Y')
(h : F.obj X' ⟶ Y) (k : Y ⟶ Y') (w : F.map f ≫ g = h ≫ k) :
f ≫ (adj.homEquiv X Y') g = (adj.homEquiv X' Y) h ≫ G.map k := by
rw [← homEquiv_naturality_left, ← homEquiv_naturality_right, w]
@[reassoc]
theorem homEquiv_naturality_right_square (f : X' ⟶ X) (g : X ⟶ G.obj Y')
(h : X' ⟶ G.obj Y) (k : Y ⟶ Y') (w : f ≫ g = h ≫ G.map k) :
F.map f ≫ (adj.homEquiv X Y').symm g = (adj.homEquiv X' Y).symm h ≫ k := by
rw [← homEquiv_naturality_left_symm, ← homEquiv_naturality_right_symm, w]
theorem homEquiv_naturality_left_square_iff (f : X' ⟶ X) (g : F.obj X ⟶ Y')
(h : F.obj X' ⟶ Y) (k : Y ⟶ Y') :
(f ≫ (adj.homEquiv X Y') g = (adj.homEquiv X' Y) h ≫ G.map k) ↔
(F.map f ≫ g = h ≫ k) :=
⟨fun w ↦ by simpa only [Equiv.symm_apply_apply]
using homEquiv_naturality_right_square adj _ _ _ _ w,
homEquiv_naturality_left_square adj f g h k⟩
theorem homEquiv_naturality_right_square_iff (f : X' ⟶ X) (g : X ⟶ G.obj Y')
(h : X' ⟶ G.obj Y) (k : Y ⟶ Y') :
(F.map f ≫ (adj.homEquiv X Y').symm g = (adj.homEquiv X' Y).symm h ≫ k) ↔
(f ≫ g = h ≫ G.map k) :=
⟨fun w ↦ by simpa only [Equiv.apply_symm_apply]
using homEquiv_naturality_left_square adj _ _ _ _ w,
homEquiv_naturality_right_square adj f g h k⟩
@[simp]
theorem left_triangle : whiskerRight adj.unit F ≫ whiskerLeft F adj.counit = 𝟙 _ := by
ext; dsimp
erw [← adj.homEquiv_counit, Equiv.symm_apply_eq, adj.homEquiv_unit]
simp
#align category_theory.adjunction.left_triangle CategoryTheory.Adjunction.left_triangle
@[simp]
theorem right_triangle : whiskerLeft G adj.unit ≫ whiskerRight adj.counit G = 𝟙 _ := by
ext; dsimp
erw [← adj.homEquiv_unit, ← Equiv.eq_symm_apply, adj.homEquiv_counit]
simp
#align category_theory.adjunction.right_triangle CategoryTheory.Adjunction.right_triangle
variable (X Y)
@[reassoc (attr := simp)]
theorem left_triangle_components :
F.map (adj.unit.app X) ≫ adj.counit.app (F.obj X) = 𝟙 (F.obj X) :=
congr_arg (fun t : NatTrans _ (𝟭 C ⋙ F) => t.app X) adj.left_triangle
#align category_theory.adjunction.left_triangle_components CategoryTheory.Adjunction.left_triangle_components
@[reassoc (attr := simp)]
theorem right_triangle_components :
adj.unit.app (G.obj Y) ≫ G.map (adj.counit.app Y) = 𝟙 (G.obj Y) :=
congr_arg (fun t : NatTrans _ (G ⋙ 𝟭 C) => t.app Y) adj.right_triangle
#align category_theory.adjunction.right_triangle_components CategoryTheory.Adjunction.right_triangle_components
variable {X Y}
@[reassoc (attr := simp)]
theorem counit_naturality {X Y : D} (f : X ⟶ Y) :
F.map (G.map f) ≫ adj.counit.app Y = adj.counit.app X ≫ f :=
adj.counit.naturality f
#align category_theory.adjunction.counit_naturality CategoryTheory.Adjunction.counit_naturality
@[reassoc (attr := simp)]
theorem unit_naturality {X Y : C} (f : X ⟶ Y) :
adj.unit.app X ≫ G.map (F.map f) = f ≫ adj.unit.app Y :=
(adj.unit.naturality f).symm
#align category_theory.adjunction.unit_naturality CategoryTheory.Adjunction.unit_naturality
theorem homEquiv_apply_eq {A : C} {B : D} (f : F.obj A ⟶ B) (g : A ⟶ G.obj B) :
adj.homEquiv A B f = g ↔ f = (adj.homEquiv A B).symm g :=
⟨fun h => by
cases h
simp, fun h => by
cases h
simp⟩
#align category_theory.adjunction.hom_equiv_apply_eq CategoryTheory.Adjunction.homEquiv_apply_eq
theorem eq_homEquiv_apply {A : C} {B : D} (f : F.obj A ⟶ B) (g : A ⟶ G.obj B) :
g = adj.homEquiv A B f ↔ (adj.homEquiv A B).symm g = f :=
⟨fun h => by
cases h
simp, fun h => by
cases h
simp⟩
#align category_theory.adjunction.eq_hom_equiv_apply CategoryTheory.Adjunction.eq_homEquiv_apply
end
end Adjunction
namespace Adjunction
/-- This is an auxiliary data structure useful for constructing adjunctions.
See `Adjunction.mkOfHomEquiv`.
This structure won't typically be used anywhere else.
-/
-- Porting note(#5171): `has_nonempty_instance` linter not ported yet
-- @[nolint has_nonempty_instance]
structure CoreHomEquiv (F : C ⥤ D) (G : D ⥤ C) where
/-- The equivalence between `Hom (F X) Y` and `Hom X (G Y)` -/
homEquiv : ∀ X Y, (F.obj X ⟶ Y) ≃ (X ⟶ G.obj Y)
/-- The property that describes how `homEquiv.symm` transforms compositions `X' ⟶ X ⟶ G Y` -/
homEquiv_naturality_left_symm :
∀ {X' X Y} (f : X' ⟶ X) (g : X ⟶ G.obj Y),
(homEquiv X' Y).symm (f ≫ g) = F.map f ≫ (homEquiv X Y).symm g := by
aesop_cat
/-- The property that describes how `homEquiv` transforms compositions `F X ⟶ Y ⟶ Y'` -/
homEquiv_naturality_right :
∀ {X Y Y'} (f : F.obj X ⟶ Y) (g : Y ⟶ Y'),
(homEquiv X Y') (f ≫ g) = (homEquiv X Y) f ≫ G.map g := by
aesop_cat
#align category_theory.adjunction.core_hom_equiv CategoryTheory.Adjunction.CoreHomEquiv
#align category_theory.adjunction.core_hom_equiv.hom_equiv CategoryTheory.Adjunction.CoreHomEquiv.homEquiv
#align category_theory.adjunction.core_hom_equiv.hom_equiv' CategoryTheory.Adjunction.CoreHomEquiv.homEquiv
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_right CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_right
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_right' CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_right
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_left_symm CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_left_symm
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_left_symm' CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_left_symm
namespace CoreHomEquiv
-- Porting note: Workaround not needed in Lean 4.
-- restate_axiom homEquiv_naturality_left_symm'
-- restate_axiom homEquiv_naturality_right'
attribute [simp] homEquiv_naturality_left_symm homEquiv_naturality_right
variable {F : C ⥤ D} {G : D ⥤ C} (adj : CoreHomEquiv F G) {X' X : C} {Y Y' : D}
@[simp]
| Mathlib/CategoryTheory/Adjunction/Basic.lean | 318 | 320 | theorem homEquiv_naturality_left_aux (f : X' ⟶ X) (g : F.obj X ⟶ Y) :
(adj.homEquiv X' (F.obj X)) (F.map f) ≫ G.map g = f ≫ (adj.homEquiv X Y) g := by |
rw [← homEquiv_naturality_right, ← Equiv.eq_symm_apply]; simp
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir
-/
import Mathlib.Algebra.Order.CauSeq.BigOperators
import Mathlib.Data.Complex.Abs
import Mathlib.Data.Complex.BigOperators
import Mathlib.Data.Nat.Choose.Sum
#align_import data.complex.exponential from "leanprover-community/mathlib"@"a8b2226cfb0a79f5986492053fc49b1a0c6aeffb"
/-!
# Exponential, trigonometric and hyperbolic trigonometric functions
This file contains the definitions of the real and complex exponential, sine, cosine, tangent,
hyperbolic sine, hyperbolic cosine, and hyperbolic tangent functions.
-/
open CauSeq Finset IsAbsoluteValue
open scoped Classical ComplexConjugate
namespace Complex
theorem isCauSeq_abs_exp (z : ℂ) :
IsCauSeq _root_.abs fun n => ∑ m ∈ range n, abs (z ^ m / m.factorial) :=
let ⟨n, hn⟩ := exists_nat_gt (abs z)
have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (abs.nonneg _) hn
IsCauSeq.series_ratio_test n (abs z / n) (div_nonneg (abs.nonneg _) (le_of_lt hn0))
(by rwa [div_lt_iff hn0, one_mul]) fun m hm => by
rw [abs_abs, abs_abs, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div,
mul_div_assoc, mul_div_right_comm, map_mul, map_div₀, abs_natCast]
gcongr
exact le_trans hm (Nat.le_succ _)
#align complex.is_cau_abs_exp Complex.isCauSeq_abs_exp
noncomputable section
theorem isCauSeq_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, z ^ m / m.factorial :=
(isCauSeq_abs_exp z).of_abv
#align complex.is_cau_exp Complex.isCauSeq_exp
/-- The Cauchy sequence consisting of partial sums of the Taylor series of
the complex exponential function -/
-- Porting note (#11180): removed `@[pp_nodot]`
def exp' (z : ℂ) : CauSeq ℂ Complex.abs :=
⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩
#align complex.exp' Complex.exp'
/-- The complex exponential function, defined via its Taylor series -/
-- Porting note (#11180): removed `@[pp_nodot]`
-- Porting note: removed `irreducible` attribute, so I can prove things
def exp (z : ℂ) : ℂ :=
CauSeq.lim (exp' z)
#align complex.exp Complex.exp
/-- The complex sine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def sin (z : ℂ) : ℂ :=
(exp (-z * I) - exp (z * I)) * I / 2
#align complex.sin Complex.sin
/-- The complex cosine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def cos (z : ℂ) : ℂ :=
(exp (z * I) + exp (-z * I)) / 2
#align complex.cos Complex.cos
/-- The complex tangent function, defined as `sin z / cos z` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def tan (z : ℂ) : ℂ :=
sin z / cos z
#align complex.tan Complex.tan
/-- The complex cotangent function, defined as `cos z / sin z` -/
def cot (z : ℂ) : ℂ :=
cos z / sin z
/-- The complex hyperbolic sine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def sinh (z : ℂ) : ℂ :=
(exp z - exp (-z)) / 2
#align complex.sinh Complex.sinh
/-- The complex hyperbolic cosine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def cosh (z : ℂ) : ℂ :=
(exp z + exp (-z)) / 2
#align complex.cosh Complex.cosh
/-- The complex hyperbolic tangent function, defined as `sinh z / cosh z` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def tanh (z : ℂ) : ℂ :=
sinh z / cosh z
#align complex.tanh Complex.tanh
/-- scoped notation for the complex exponential function -/
scoped notation "cexp" => Complex.exp
end
end Complex
namespace Real
open Complex
noncomputable section
/-- The real exponential function, defined as the real part of the complex exponential -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def exp (x : ℝ) : ℝ :=
(exp x).re
#align real.exp Real.exp
/-- The real sine function, defined as the real part of the complex sine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def sin (x : ℝ) : ℝ :=
(sin x).re
#align real.sin Real.sin
/-- The real cosine function, defined as the real part of the complex cosine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def cos (x : ℝ) : ℝ :=
(cos x).re
#align real.cos Real.cos
/-- The real tangent function, defined as the real part of the complex tangent -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def tan (x : ℝ) : ℝ :=
(tan x).re
#align real.tan Real.tan
/-- The real cotangent function, defined as the real part of the complex cotangent -/
nonrec def cot (x : ℝ) : ℝ :=
(cot x).re
/-- The real hypebolic sine function, defined as the real part of the complex hyperbolic sine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def sinh (x : ℝ) : ℝ :=
(sinh x).re
#align real.sinh Real.sinh
/-- The real hypebolic cosine function, defined as the real part of the complex hyperbolic cosine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def cosh (x : ℝ) : ℝ :=
(cosh x).re
#align real.cosh Real.cosh
/-- The real hypebolic tangent function, defined as the real part of
the complex hyperbolic tangent -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def tanh (x : ℝ) : ℝ :=
(tanh x).re
#align real.tanh Real.tanh
/-- scoped notation for the real exponential function -/
scoped notation "rexp" => Real.exp
end
end Real
namespace Complex
variable (x y : ℂ)
@[simp]
theorem exp_zero : exp 0 = 1 := by
rw [exp]
refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩
convert (config := .unfoldSameFun) ε0 -- Porting note: ε0 : ε > 0 but goal is _ < ε
cases' j with j j
· exact absurd hj (not_le_of_gt zero_lt_one)
· dsimp [exp']
induction' j with j ih
· dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl]
· rw [← ih (by simp [Nat.succ_le_succ])]
simp only [sum_range_succ, pow_succ]
simp
#align complex.exp_zero Complex.exp_zero
theorem exp_add : exp (x + y) = exp x * exp y := by
have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) =
∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial *
(y ^ (i - k) / (i - k).factorial) := by
intro j
refine Finset.sum_congr rfl fun m _ => ?_
rw [add_pow, div_eq_mul_inv, sum_mul]
refine Finset.sum_congr rfl fun I hi => ?_
have h₁ : (m.choose I : ℂ) ≠ 0 :=
Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi))))
have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi)
rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv]
simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹,
mul_comm (m.choose I : ℂ)]
rw [inv_mul_cancel h₁]
simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm]
simp_rw [exp, exp', lim_mul_lim]
apply (lim_eq_lim_of_equiv _).symm
simp only [hj]
exact cauchy_product (isCauSeq_abs_exp x) (isCauSeq_exp y)
#align complex.exp_add Complex.exp_add
-- Porting note (#11445): new definition
/-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/
noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ :=
{ toFun := fun z => exp (Multiplicative.toAdd z),
map_one' := by simp,
map_mul' := by simp [exp_add] }
theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod :=
map_list_prod (M := Multiplicative ℂ) expMonoidHom l
#align complex.exp_list_sum Complex.exp_list_sum
theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod :=
@MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s
#align complex.exp_multiset_sum Complex.exp_multiset_sum
theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) :
exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) :=
map_prod (β := Multiplicative ℂ) expMonoidHom f s
#align complex.exp_sum Complex.exp_sum
lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n :=
@MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _
theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n
| 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero]
| Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul]
#align complex.exp_nat_mul Complex.exp_nat_mul
theorem exp_ne_zero : exp x ≠ 0 := fun h =>
zero_ne_one <| by rw [← exp_zero, ← add_neg_self x, exp_add, h]; simp
#align complex.exp_ne_zero Complex.exp_ne_zero
theorem exp_neg : exp (-x) = (exp x)⁻¹ := by
rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel (exp_ne_zero x)]
#align complex.exp_neg Complex.exp_neg
theorem exp_sub : exp (x - y) = exp x / exp y := by
simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv]
#align complex.exp_sub Complex.exp_sub
theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by
cases n
· simp [exp_nat_mul]
· simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul]
#align complex.exp_int_mul Complex.exp_int_mul
@[simp]
theorem exp_conj : exp (conj x) = conj (exp x) := by
dsimp [exp]
rw [← lim_conj]
refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_)
dsimp [exp', Function.comp_def, cauSeqConj]
rw [map_sum (starRingEnd _)]
refine sum_congr rfl fun n _ => ?_
rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal]
#align complex.exp_conj Complex.exp_conj
@[simp]
theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x :=
conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal]
#align complex.of_real_exp_of_real_re Complex.ofReal_exp_ofReal_re
@[simp, norm_cast]
theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x :=
ofReal_exp_ofReal_re _
#align complex.of_real_exp Complex.ofReal_exp
@[simp]
theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im]
#align complex.exp_of_real_im Complex.exp_ofReal_im
theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x :=
rfl
#align complex.exp_of_real_re Complex.exp_ofReal_re
theorem two_sinh : 2 * sinh x = exp x - exp (-x) :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_sinh Complex.two_sinh
theorem two_cosh : 2 * cosh x = exp x + exp (-x) :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_cosh Complex.two_cosh
@[simp]
theorem sinh_zero : sinh 0 = 0 := by simp [sinh]
#align complex.sinh_zero Complex.sinh_zero
@[simp]
theorem sinh_neg : sinh (-x) = -sinh x := by simp [sinh, exp_neg, (neg_div _ _).symm, add_mul]
#align complex.sinh_neg Complex.sinh_neg
private theorem sinh_add_aux {a b c d : ℂ} :
(a - b) * (c + d) + (a + b) * (c - d) = 2 * (a * c - b * d) := by ring
theorem sinh_add : sinh (x + y) = sinh x * cosh y + cosh x * sinh y := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_sinh, exp_add, neg_add, exp_add, eq_comm, mul_add, ←
mul_assoc, two_sinh, mul_left_comm, two_sinh, ← mul_right_inj' (two_ne_zero' ℂ), mul_add,
mul_left_comm, two_cosh, ← mul_assoc, two_cosh]
exact sinh_add_aux
#align complex.sinh_add Complex.sinh_add
@[simp]
theorem cosh_zero : cosh 0 = 1 := by simp [cosh]
#align complex.cosh_zero Complex.cosh_zero
@[simp]
theorem cosh_neg : cosh (-x) = cosh x := by simp [add_comm, cosh, exp_neg]
#align complex.cosh_neg Complex.cosh_neg
private theorem cosh_add_aux {a b c d : ℂ} :
(a + b) * (c + d) + (a - b) * (c - d) = 2 * (a * c + b * d) := by ring
theorem cosh_add : cosh (x + y) = cosh x * cosh y + sinh x * sinh y := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_cosh, exp_add, neg_add, exp_add, eq_comm, mul_add, ←
mul_assoc, two_cosh, ← mul_assoc, two_sinh, ← mul_right_inj' (two_ne_zero' ℂ), mul_add,
mul_left_comm, two_cosh, mul_left_comm, two_sinh]
exact cosh_add_aux
#align complex.cosh_add Complex.cosh_add
theorem sinh_sub : sinh (x - y) = sinh x * cosh y - cosh x * sinh y := by
simp [sub_eq_add_neg, sinh_add, sinh_neg, cosh_neg]
#align complex.sinh_sub Complex.sinh_sub
theorem cosh_sub : cosh (x - y) = cosh x * cosh y - sinh x * sinh y := by
simp [sub_eq_add_neg, cosh_add, sinh_neg, cosh_neg]
#align complex.cosh_sub Complex.cosh_sub
theorem sinh_conj : sinh (conj x) = conj (sinh x) := by
rw [sinh, ← RingHom.map_neg, exp_conj, exp_conj, ← RingHom.map_sub, sinh, map_div₀]
-- Porting note: not nice
simp [← one_add_one_eq_two]
#align complex.sinh_conj Complex.sinh_conj
@[simp]
theorem ofReal_sinh_ofReal_re (x : ℝ) : ((sinh x).re : ℂ) = sinh x :=
conj_eq_iff_re.1 <| by rw [← sinh_conj, conj_ofReal]
#align complex.of_real_sinh_of_real_re Complex.ofReal_sinh_ofReal_re
@[simp, norm_cast]
theorem ofReal_sinh (x : ℝ) : (Real.sinh x : ℂ) = sinh x :=
ofReal_sinh_ofReal_re _
#align complex.of_real_sinh Complex.ofReal_sinh
@[simp]
theorem sinh_ofReal_im (x : ℝ) : (sinh x).im = 0 := by rw [← ofReal_sinh_ofReal_re, ofReal_im]
#align complex.sinh_of_real_im Complex.sinh_ofReal_im
theorem sinh_ofReal_re (x : ℝ) : (sinh x).re = Real.sinh x :=
rfl
#align complex.sinh_of_real_re Complex.sinh_ofReal_re
theorem cosh_conj : cosh (conj x) = conj (cosh x) := by
rw [cosh, ← RingHom.map_neg, exp_conj, exp_conj, ← RingHom.map_add, cosh, map_div₀]
-- Porting note: not nice
simp [← one_add_one_eq_two]
#align complex.cosh_conj Complex.cosh_conj
theorem ofReal_cosh_ofReal_re (x : ℝ) : ((cosh x).re : ℂ) = cosh x :=
conj_eq_iff_re.1 <| by rw [← cosh_conj, conj_ofReal]
#align complex.of_real_cosh_of_real_re Complex.ofReal_cosh_ofReal_re
@[simp, norm_cast]
theorem ofReal_cosh (x : ℝ) : (Real.cosh x : ℂ) = cosh x :=
ofReal_cosh_ofReal_re _
#align complex.of_real_cosh Complex.ofReal_cosh
@[simp]
theorem cosh_ofReal_im (x : ℝ) : (cosh x).im = 0 := by rw [← ofReal_cosh_ofReal_re, ofReal_im]
#align complex.cosh_of_real_im Complex.cosh_ofReal_im
@[simp]
theorem cosh_ofReal_re (x : ℝ) : (cosh x).re = Real.cosh x :=
rfl
#align complex.cosh_of_real_re Complex.cosh_ofReal_re
theorem tanh_eq_sinh_div_cosh : tanh x = sinh x / cosh x :=
rfl
#align complex.tanh_eq_sinh_div_cosh Complex.tanh_eq_sinh_div_cosh
@[simp]
theorem tanh_zero : tanh 0 = 0 := by simp [tanh]
#align complex.tanh_zero Complex.tanh_zero
@[simp]
theorem tanh_neg : tanh (-x) = -tanh x := by simp [tanh, neg_div]
#align complex.tanh_neg Complex.tanh_neg
theorem tanh_conj : tanh (conj x) = conj (tanh x) := by
rw [tanh, sinh_conj, cosh_conj, ← map_div₀, tanh]
#align complex.tanh_conj Complex.tanh_conj
@[simp]
theorem ofReal_tanh_ofReal_re (x : ℝ) : ((tanh x).re : ℂ) = tanh x :=
conj_eq_iff_re.1 <| by rw [← tanh_conj, conj_ofReal]
#align complex.of_real_tanh_of_real_re Complex.ofReal_tanh_ofReal_re
@[simp, norm_cast]
theorem ofReal_tanh (x : ℝ) : (Real.tanh x : ℂ) = tanh x :=
ofReal_tanh_ofReal_re _
#align complex.of_real_tanh Complex.ofReal_tanh
@[simp]
theorem tanh_ofReal_im (x : ℝ) : (tanh x).im = 0 := by rw [← ofReal_tanh_ofReal_re, ofReal_im]
#align complex.tanh_of_real_im Complex.tanh_ofReal_im
theorem tanh_ofReal_re (x : ℝ) : (tanh x).re = Real.tanh x :=
rfl
#align complex.tanh_of_real_re Complex.tanh_ofReal_re
@[simp]
theorem cosh_add_sinh : cosh x + sinh x = exp x := by
rw [← mul_right_inj' (two_ne_zero' ℂ), mul_add, two_cosh, two_sinh, add_add_sub_cancel, two_mul]
#align complex.cosh_add_sinh Complex.cosh_add_sinh
@[simp]
theorem sinh_add_cosh : sinh x + cosh x = exp x := by rw [add_comm, cosh_add_sinh]
#align complex.sinh_add_cosh Complex.sinh_add_cosh
@[simp]
theorem exp_sub_cosh : exp x - cosh x = sinh x :=
sub_eq_iff_eq_add.2 (sinh_add_cosh x).symm
#align complex.exp_sub_cosh Complex.exp_sub_cosh
@[simp]
theorem exp_sub_sinh : exp x - sinh x = cosh x :=
sub_eq_iff_eq_add.2 (cosh_add_sinh x).symm
#align complex.exp_sub_sinh Complex.exp_sub_sinh
@[simp]
theorem cosh_sub_sinh : cosh x - sinh x = exp (-x) := by
rw [← mul_right_inj' (two_ne_zero' ℂ), mul_sub, two_cosh, two_sinh, add_sub_sub_cancel, two_mul]
#align complex.cosh_sub_sinh Complex.cosh_sub_sinh
@[simp]
theorem sinh_sub_cosh : sinh x - cosh x = -exp (-x) := by rw [← neg_sub, cosh_sub_sinh]
#align complex.sinh_sub_cosh Complex.sinh_sub_cosh
@[simp]
theorem cosh_sq_sub_sinh_sq : cosh x ^ 2 - sinh x ^ 2 = 1 := by
rw [sq_sub_sq, cosh_add_sinh, cosh_sub_sinh, ← exp_add, add_neg_self, exp_zero]
#align complex.cosh_sq_sub_sinh_sq Complex.cosh_sq_sub_sinh_sq
theorem cosh_sq : cosh x ^ 2 = sinh x ^ 2 + 1 := by
rw [← cosh_sq_sub_sinh_sq x]
ring
#align complex.cosh_sq Complex.cosh_sq
theorem sinh_sq : sinh x ^ 2 = cosh x ^ 2 - 1 := by
rw [← cosh_sq_sub_sinh_sq x]
ring
#align complex.sinh_sq Complex.sinh_sq
theorem cosh_two_mul : cosh (2 * x) = cosh x ^ 2 + sinh x ^ 2 := by rw [two_mul, cosh_add, sq, sq]
#align complex.cosh_two_mul Complex.cosh_two_mul
theorem sinh_two_mul : sinh (2 * x) = 2 * sinh x * cosh x := by
rw [two_mul, sinh_add]
ring
#align complex.sinh_two_mul Complex.sinh_two_mul
theorem cosh_three_mul : cosh (3 * x) = 4 * cosh x ^ 3 - 3 * cosh x := by
have h1 : x + 2 * x = 3 * x := by ring
rw [← h1, cosh_add x (2 * x)]
simp only [cosh_two_mul, sinh_two_mul]
have h2 : sinh x * (2 * sinh x * cosh x) = 2 * cosh x * sinh x ^ 2 := by ring
rw [h2, sinh_sq]
ring
#align complex.cosh_three_mul Complex.cosh_three_mul
theorem sinh_three_mul : sinh (3 * x) = 4 * sinh x ^ 3 + 3 * sinh x := by
have h1 : x + 2 * x = 3 * x := by ring
rw [← h1, sinh_add x (2 * x)]
simp only [cosh_two_mul, sinh_two_mul]
have h2 : cosh x * (2 * sinh x * cosh x) = 2 * sinh x * cosh x ^ 2 := by ring
rw [h2, cosh_sq]
ring
#align complex.sinh_three_mul Complex.sinh_three_mul
@[simp]
theorem sin_zero : sin 0 = 0 := by simp [sin]
#align complex.sin_zero Complex.sin_zero
@[simp]
theorem sin_neg : sin (-x) = -sin x := by
simp [sin, sub_eq_add_neg, exp_neg, (neg_div _ _).symm, add_mul]
#align complex.sin_neg Complex.sin_neg
theorem two_sin : 2 * sin x = (exp (-x * I) - exp (x * I)) * I :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_sin Complex.two_sin
theorem two_cos : 2 * cos x = exp (x * I) + exp (-x * I) :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_cos Complex.two_cos
theorem sinh_mul_I : sinh (x * I) = sin x * I := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_sinh, ← mul_assoc, two_sin, mul_assoc, I_mul_I,
mul_neg_one, neg_sub, neg_mul_eq_neg_mul]
set_option linter.uppercaseLean3 false in
#align complex.sinh_mul_I Complex.sinh_mul_I
theorem cosh_mul_I : cosh (x * I) = cos x := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_cosh, two_cos, neg_mul_eq_neg_mul]
set_option linter.uppercaseLean3 false in
#align complex.cosh_mul_I Complex.cosh_mul_I
theorem tanh_mul_I : tanh (x * I) = tan x * I := by
rw [tanh_eq_sinh_div_cosh, cosh_mul_I, sinh_mul_I, mul_div_right_comm, tan]
set_option linter.uppercaseLean3 false in
#align complex.tanh_mul_I Complex.tanh_mul_I
theorem cos_mul_I : cos (x * I) = cosh x := by rw [← cosh_mul_I]; ring_nf; simp
set_option linter.uppercaseLean3 false in
#align complex.cos_mul_I Complex.cos_mul_I
theorem sin_mul_I : sin (x * I) = sinh x * I := by
have h : I * sin (x * I) = -sinh x := by
rw [mul_comm, ← sinh_mul_I]
ring_nf
simp
rw [← neg_neg (sinh x), ← h]
apply Complex.ext <;> simp
set_option linter.uppercaseLean3 false in
#align complex.sin_mul_I Complex.sin_mul_I
theorem tan_mul_I : tan (x * I) = tanh x * I := by
rw [tan, sin_mul_I, cos_mul_I, mul_div_right_comm, tanh_eq_sinh_div_cosh]
set_option linter.uppercaseLean3 false in
#align complex.tan_mul_I Complex.tan_mul_I
theorem sin_add : sin (x + y) = sin x * cos y + cos x * sin y := by
rw [← mul_left_inj' I_ne_zero, ← sinh_mul_I, add_mul, add_mul, mul_right_comm, ← sinh_mul_I,
mul_assoc, ← sinh_mul_I, ← cosh_mul_I, ← cosh_mul_I, sinh_add]
#align complex.sin_add Complex.sin_add
@[simp]
theorem cos_zero : cos 0 = 1 := by simp [cos]
#align complex.cos_zero Complex.cos_zero
@[simp]
theorem cos_neg : cos (-x) = cos x := by simp [cos, sub_eq_add_neg, exp_neg, add_comm]
#align complex.cos_neg Complex.cos_neg
private theorem cos_add_aux {a b c d : ℂ} :
(a + b) * (c + d) - (b - a) * (d - c) * -1 = 2 * (a * c + b * d) := by ring
theorem cos_add : cos (x + y) = cos x * cos y - sin x * sin y := by
rw [← cosh_mul_I, add_mul, cosh_add, cosh_mul_I, cosh_mul_I, sinh_mul_I, sinh_mul_I,
mul_mul_mul_comm, I_mul_I, mul_neg_one, sub_eq_add_neg]
#align complex.cos_add Complex.cos_add
theorem sin_sub : sin (x - y) = sin x * cos y - cos x * sin y := by
simp [sub_eq_add_neg, sin_add, sin_neg, cos_neg]
#align complex.sin_sub Complex.sin_sub
theorem cos_sub : cos (x - y) = cos x * cos y + sin x * sin y := by
simp [sub_eq_add_neg, cos_add, sin_neg, cos_neg]
#align complex.cos_sub Complex.cos_sub
theorem sin_add_mul_I (x y : ℂ) : sin (x + y * I) = sin x * cosh y + cos x * sinh y * I := by
rw [sin_add, cos_mul_I, sin_mul_I, mul_assoc]
set_option linter.uppercaseLean3 false in
#align complex.sin_add_mul_I Complex.sin_add_mul_I
theorem sin_eq (z : ℂ) : sin z = sin z.re * cosh z.im + cos z.re * sinh z.im * I := by
convert sin_add_mul_I z.re z.im; exact (re_add_im z).symm
#align complex.sin_eq Complex.sin_eq
theorem cos_add_mul_I (x y : ℂ) : cos (x + y * I) = cos x * cosh y - sin x * sinh y * I := by
rw [cos_add, cos_mul_I, sin_mul_I, mul_assoc]
set_option linter.uppercaseLean3 false in
#align complex.cos_add_mul_I Complex.cos_add_mul_I
theorem cos_eq (z : ℂ) : cos z = cos z.re * cosh z.im - sin z.re * sinh z.im * I := by
convert cos_add_mul_I z.re z.im; exact (re_add_im z).symm
#align complex.cos_eq Complex.cos_eq
theorem sin_sub_sin : sin x - sin y = 2 * sin ((x - y) / 2) * cos ((x + y) / 2) := by
have s1 := sin_add ((x + y) / 2) ((x - y) / 2)
have s2 := sin_sub ((x + y) / 2) ((x - y) / 2)
rw [div_add_div_same, add_sub, add_right_comm, add_sub_cancel_right, half_add_self] at s1
rw [div_sub_div_same, ← sub_add, add_sub_cancel_left, half_add_self] at s2
rw [s1, s2]
ring
#align complex.sin_sub_sin Complex.sin_sub_sin
theorem cos_sub_cos : cos x - cos y = -2 * sin ((x + y) / 2) * sin ((x - y) / 2) := by
have s1 := cos_add ((x + y) / 2) ((x - y) / 2)
have s2 := cos_sub ((x + y) / 2) ((x - y) / 2)
rw [div_add_div_same, add_sub, add_right_comm, add_sub_cancel_right, half_add_self] at s1
rw [div_sub_div_same, ← sub_add, add_sub_cancel_left, half_add_self] at s2
rw [s1, s2]
ring
#align complex.cos_sub_cos Complex.cos_sub_cos
theorem sin_add_sin : sin x + sin y = 2 * sin ((x + y) / 2) * cos ((x - y) / 2) := by
simpa using sin_sub_sin x (-y)
theorem cos_add_cos : cos x + cos y = 2 * cos ((x + y) / 2) * cos ((x - y) / 2) := by
calc
cos x + cos y = cos ((x + y) / 2 + (x - y) / 2) + cos ((x + y) / 2 - (x - y) / 2) := ?_
_ =
cos ((x + y) / 2) * cos ((x - y) / 2) - sin ((x + y) / 2) * sin ((x - y) / 2) +
(cos ((x + y) / 2) * cos ((x - y) / 2) + sin ((x + y) / 2) * sin ((x - y) / 2)) :=
?_
_ = 2 * cos ((x + y) / 2) * cos ((x - y) / 2) := ?_
· congr <;> field_simp
· rw [cos_add, cos_sub]
ring
#align complex.cos_add_cos Complex.cos_add_cos
theorem sin_conj : sin (conj x) = conj (sin x) := by
rw [← mul_left_inj' I_ne_zero, ← sinh_mul_I, ← conj_neg_I, ← RingHom.map_mul, ← RingHom.map_mul,
sinh_conj, mul_neg, sinh_neg, sinh_mul_I, mul_neg]
#align complex.sin_conj Complex.sin_conj
@[simp]
theorem ofReal_sin_ofReal_re (x : ℝ) : ((sin x).re : ℂ) = sin x :=
conj_eq_iff_re.1 <| by rw [← sin_conj, conj_ofReal]
#align complex.of_real_sin_of_real_re Complex.ofReal_sin_ofReal_re
@[simp, norm_cast]
theorem ofReal_sin (x : ℝ) : (Real.sin x : ℂ) = sin x :=
ofReal_sin_ofReal_re _
#align complex.of_real_sin Complex.ofReal_sin
@[simp]
theorem sin_ofReal_im (x : ℝ) : (sin x).im = 0 := by rw [← ofReal_sin_ofReal_re, ofReal_im]
#align complex.sin_of_real_im Complex.sin_ofReal_im
theorem sin_ofReal_re (x : ℝ) : (sin x).re = Real.sin x :=
rfl
#align complex.sin_of_real_re Complex.sin_ofReal_re
theorem cos_conj : cos (conj x) = conj (cos x) := by
rw [← cosh_mul_I, ← conj_neg_I, ← RingHom.map_mul, ← cosh_mul_I, cosh_conj, mul_neg, cosh_neg]
#align complex.cos_conj Complex.cos_conj
@[simp]
theorem ofReal_cos_ofReal_re (x : ℝ) : ((cos x).re : ℂ) = cos x :=
conj_eq_iff_re.1 <| by rw [← cos_conj, conj_ofReal]
#align complex.of_real_cos_of_real_re Complex.ofReal_cos_ofReal_re
@[simp, norm_cast]
theorem ofReal_cos (x : ℝ) : (Real.cos x : ℂ) = cos x :=
ofReal_cos_ofReal_re _
#align complex.of_real_cos Complex.ofReal_cos
@[simp]
theorem cos_ofReal_im (x : ℝ) : (cos x).im = 0 := by rw [← ofReal_cos_ofReal_re, ofReal_im]
#align complex.cos_of_real_im Complex.cos_ofReal_im
theorem cos_ofReal_re (x : ℝ) : (cos x).re = Real.cos x :=
rfl
#align complex.cos_of_real_re Complex.cos_ofReal_re
@[simp]
theorem tan_zero : tan 0 = 0 := by simp [tan]
#align complex.tan_zero Complex.tan_zero
theorem tan_eq_sin_div_cos : tan x = sin x / cos x :=
rfl
#align complex.tan_eq_sin_div_cos Complex.tan_eq_sin_div_cos
theorem tan_mul_cos {x : ℂ} (hx : cos x ≠ 0) : tan x * cos x = sin x := by
rw [tan_eq_sin_div_cos, div_mul_cancel₀ _ hx]
#align complex.tan_mul_cos Complex.tan_mul_cos
@[simp]
theorem tan_neg : tan (-x) = -tan x := by simp [tan, neg_div]
#align complex.tan_neg Complex.tan_neg
theorem tan_conj : tan (conj x) = conj (tan x) := by rw [tan, sin_conj, cos_conj, ← map_div₀, tan]
#align complex.tan_conj Complex.tan_conj
@[simp]
theorem ofReal_tan_ofReal_re (x : ℝ) : ((tan x).re : ℂ) = tan x :=
conj_eq_iff_re.1 <| by rw [← tan_conj, conj_ofReal]
#align complex.of_real_tan_of_real_re Complex.ofReal_tan_ofReal_re
@[simp, norm_cast]
theorem ofReal_tan (x : ℝ) : (Real.tan x : ℂ) = tan x :=
ofReal_tan_ofReal_re _
#align complex.of_real_tan Complex.ofReal_tan
@[simp]
| Mathlib/Data/Complex/Exponential.lean | 693 | 693 | theorem tan_ofReal_im (x : ℝ) : (tan x).im = 0 := by | rw [← ofReal_tan_ofReal_re, ofReal_im]
|
/-
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.Analysis.NormedSpace.AffineIsometry
import Mathlib.Topology.Algebra.ContinuousAffineMap
import Mathlib.Analysis.NormedSpace.OperatorNorm.NormedSpace
#align_import analysis.normed_space.continuous_affine_map from "leanprover-community/mathlib"@"17ef379e997badd73e5eabb4d38f11919ab3c4b3"
/-!
# Continuous affine maps between normed spaces.
This file develops the theory of continuous affine maps between affine spaces modelled on normed
spaces.
In the particular case that the affine spaces are just normed vector spaces `V`, `W`, we define a
norm on the space of continuous affine maps by defining the norm of `f : V →ᴬ[𝕜] W` to be
`‖f‖ = max ‖f 0‖ ‖f.cont_linear‖`. This is chosen so that we have a linear isometry:
`(V →ᴬ[𝕜] W) ≃ₗᵢ[𝕜] W × (V →L[𝕜] W)`.
The abstract picture is that for an affine space `P` modelled on a vector space `V`, together with
a vector space `W`, there is an exact sequence of `𝕜`-modules: `0 → C → A → L → 0` where `C`, `A`
are the spaces of constant and affine maps `P → W` and `L` is the space of linear maps `V → W`.
Any choice of a base point in `P` corresponds to a splitting of this sequence so in particular if we
take `P = V`, using `0 : V` as the base point provides a splitting, and we prove this is an
isometric decomposition.
On the other hand, choosing a base point breaks the affine invariance so the norm fails to be
submultiplicative: for a composition of maps, we have only `‖f.comp g‖ ≤ ‖f‖ * ‖g‖ + ‖f 0‖`.
## Main definitions:
* `ContinuousAffineMap.contLinear`
* `ContinuousAffineMap.hasNorm`
* `ContinuousAffineMap.norm_comp_le`
* `ContinuousAffineMap.toConstProdContinuousLinearMap`
-/
namespace ContinuousAffineMap
variable {𝕜 R V W W₂ P Q Q₂ : Type*}
variable [NormedAddCommGroup V] [MetricSpace P] [NormedAddTorsor V P]
variable [NormedAddCommGroup W] [MetricSpace Q] [NormedAddTorsor W Q]
variable [NormedAddCommGroup W₂] [MetricSpace Q₂] [NormedAddTorsor W₂ Q₂]
variable [NormedField R] [NormedSpace R V] [NormedSpace R W] [NormedSpace R W₂]
variable [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 V] [NormedSpace 𝕜 W] [NormedSpace 𝕜 W₂]
/-- The linear map underlying a continuous affine map is continuous. -/
def contLinear (f : P →ᴬ[R] Q) : V →L[R] W :=
{ f.linear with
toFun := f.linear
cont := by rw [AffineMap.continuous_linear_iff]; exact f.cont }
#align continuous_affine_map.cont_linear ContinuousAffineMap.contLinear
@[simp]
theorem coe_contLinear (f : P →ᴬ[R] Q) : (f.contLinear : V → W) = f.linear :=
rfl
#align continuous_affine_map.coe_cont_linear ContinuousAffineMap.coe_contLinear
@[simp]
theorem coe_contLinear_eq_linear (f : P →ᴬ[R] Q) :
(f.contLinear : V →ₗ[R] W) = (f : P →ᵃ[R] Q).linear := by ext; rfl
#align continuous_affine_map.coe_cont_linear_eq_linear ContinuousAffineMap.coe_contLinear_eq_linear
@[simp]
theorem coe_mk_const_linear_eq_linear (f : P →ᵃ[R] Q) (h) :
((⟨f, h⟩ : P →ᴬ[R] Q).contLinear : V → W) = f.linear :=
rfl
#align continuous_affine_map.coe_mk_const_linear_eq_linear ContinuousAffineMap.coe_mk_const_linear_eq_linear
theorem coe_linear_eq_coe_contLinear (f : P →ᴬ[R] Q) :
((f : P →ᵃ[R] Q).linear : V → W) = (⇑f.contLinear : V → W) :=
rfl
#align continuous_affine_map.coe_linear_eq_coe_cont_linear ContinuousAffineMap.coe_linear_eq_coe_contLinear
@[simp]
theorem comp_contLinear (f : P →ᴬ[R] Q) (g : Q →ᴬ[R] Q₂) :
(g.comp f).contLinear = g.contLinear.comp f.contLinear :=
rfl
#align continuous_affine_map.comp_cont_linear ContinuousAffineMap.comp_contLinear
@[simp]
theorem map_vadd (f : P →ᴬ[R] Q) (p : P) (v : V) : f (v +ᵥ p) = f.contLinear v +ᵥ f p :=
f.map_vadd' p v
#align continuous_affine_map.map_vadd ContinuousAffineMap.map_vadd
@[simp]
theorem contLinear_map_vsub (f : P →ᴬ[R] Q) (p₁ p₂ : P) : f.contLinear (p₁ -ᵥ p₂) = f p₁ -ᵥ f p₂ :=
f.toAffineMap.linearMap_vsub p₁ p₂
#align continuous_affine_map.cont_linear_map_vsub ContinuousAffineMap.contLinear_map_vsub
@[simp]
theorem const_contLinear (q : Q) : (const R P q).contLinear = 0 :=
rfl
#align continuous_affine_map.const_cont_linear ContinuousAffineMap.const_contLinear
theorem contLinear_eq_zero_iff_exists_const (f : P →ᴬ[R] Q) :
f.contLinear = 0 ↔ ∃ q, f = const R P q := by
have h₁ : f.contLinear = 0 ↔ (f : P →ᵃ[R] Q).linear = 0 := by
refine ⟨fun h => ?_, fun h => ?_⟩ <;> ext
· rw [← coe_contLinear_eq_linear, h]; rfl
· rw [← coe_linear_eq_coe_contLinear, h]; rfl
have h₂ : ∀ q : Q, f = const R P q ↔ (f : P →ᵃ[R] Q) = AffineMap.const R P q := by
intro q
refine ⟨fun h => ?_, fun h => ?_⟩ <;> ext
· rw [h]; rfl
· rw [← coe_to_affineMap, h]; rfl
simp_rw [h₁, h₂]
exact (f : P →ᵃ[R] Q).linear_eq_zero_iff_exists_const
#align continuous_affine_map.cont_linear_eq_zero_iff_exists_const ContinuousAffineMap.contLinear_eq_zero_iff_exists_const
@[simp]
theorem to_affine_map_contLinear (f : V →L[R] W) : f.toContinuousAffineMap.contLinear = f := by
ext
rfl
#align continuous_affine_map.to_affine_map_cont_linear ContinuousAffineMap.to_affine_map_contLinear
@[simp]
theorem zero_contLinear : (0 : P →ᴬ[R] W).contLinear = 0 :=
rfl
#align continuous_affine_map.zero_cont_linear ContinuousAffineMap.zero_contLinear
@[simp]
theorem add_contLinear (f g : P →ᴬ[R] W) : (f + g).contLinear = f.contLinear + g.contLinear :=
rfl
#align continuous_affine_map.add_cont_linear ContinuousAffineMap.add_contLinear
@[simp]
theorem sub_contLinear (f g : P →ᴬ[R] W) : (f - g).contLinear = f.contLinear - g.contLinear :=
rfl
#align continuous_affine_map.sub_cont_linear ContinuousAffineMap.sub_contLinear
@[simp]
theorem neg_contLinear (f : P →ᴬ[R] W) : (-f).contLinear = -f.contLinear :=
rfl
#align continuous_affine_map.neg_cont_linear ContinuousAffineMap.neg_contLinear
@[simp]
theorem smul_contLinear (t : R) (f : P →ᴬ[R] W) : (t • f).contLinear = t • f.contLinear :=
rfl
#align continuous_affine_map.smul_cont_linear ContinuousAffineMap.smul_contLinear
theorem decomp (f : V →ᴬ[R] W) : (f : V → W) = f.contLinear + Function.const V (f 0) := by
rcases f with ⟨f, h⟩
rw [coe_mk_const_linear_eq_linear, coe_mk, f.decomp, Pi.add_apply, LinearMap.map_zero, zero_add,
← Function.const_def]
#align continuous_affine_map.decomp ContinuousAffineMap.decomp
section NormedSpaceStructure
variable (f : V →ᴬ[𝕜] W)
/-- Note that unlike the operator norm for linear maps, this norm is _not_ submultiplicative:
we do _not_ necessarily have `‖f.comp g‖ ≤ ‖f‖ * ‖g‖`. See `norm_comp_le` for what we can say. -/
noncomputable instance hasNorm : Norm (V →ᴬ[𝕜] W) :=
⟨fun f => max ‖f 0‖ ‖f.contLinear‖⟩
#align continuous_affine_map.has_norm ContinuousAffineMap.hasNorm
theorem norm_def : ‖f‖ = max ‖f 0‖ ‖f.contLinear‖ :=
rfl
#align continuous_affine_map.norm_def ContinuousAffineMap.norm_def
theorem norm_contLinear_le : ‖f.contLinear‖ ≤ ‖f‖ :=
le_max_right _ _
#align continuous_affine_map.norm_cont_linear_le ContinuousAffineMap.norm_contLinear_le
theorem norm_image_zero_le : ‖f 0‖ ≤ ‖f‖ :=
le_max_left _ _
#align continuous_affine_map.norm_image_zero_le ContinuousAffineMap.norm_image_zero_le
@[simp]
theorem norm_eq (h : f 0 = 0) : ‖f‖ = ‖f.contLinear‖ :=
calc
‖f‖ = max ‖f 0‖ ‖f.contLinear‖ := by rw [norm_def]
_ = max 0 ‖f.contLinear‖ := by rw [h, norm_zero]
_ = ‖f.contLinear‖ := max_eq_right (norm_nonneg _)
#align continuous_affine_map.norm_eq ContinuousAffineMap.norm_eq
noncomputable instance : NormedAddCommGroup (V →ᴬ[𝕜] W) :=
AddGroupNorm.toNormedAddCommGroup
{ toFun := fun f => max ‖f 0‖ ‖f.contLinear‖
map_zero' := by simp [(ContinuousAffineMap.zero_apply)]
neg' := fun f => by
simp [(ContinuousAffineMap.neg_apply)]
add_le' := fun f g => by
simp only [coe_add, max_le_iff, Pi.add_apply, add_contLinear]
exact
⟨(norm_add_le _ _).trans (add_le_add (le_max_left _ _) (le_max_left _ _)),
(norm_add_le _ _).trans (add_le_add (le_max_right _ _) (le_max_right _ _))⟩
eq_zero_of_map_eq_zero' := fun f h₀ => by
rcases max_eq_iff.mp h₀ with (⟨h₁, h₂⟩ | ⟨h₁, h₂⟩) <;> rw [h₁] at h₂
· rw [norm_le_zero_iff, contLinear_eq_zero_iff_exists_const] at h₂
obtain ⟨q, rfl⟩ := h₂
simp only [norm_eq_zero, coe_const, Function.const_apply] at h₁
rw [h₁]
rfl
· rw [norm_eq_zero', contLinear_eq_zero_iff_exists_const] at h₁
obtain ⟨q, rfl⟩ := h₁
simp only [norm_le_zero_iff, coe_const, Function.const_apply] at h₂
rw [h₂]
rfl }
instance : NormedSpace 𝕜 (V →ᴬ[𝕜] W) where
norm_smul_le t f := by
simp only [SMul.smul, norm_def, smul_contLinear, norm_smul]
-- Porting note: previously all these rewrites were in the `simp only`,
-- but now they don't fire.
-- (in fact, `norm_smul` fires, but only once rather than twice!)
have : NormedAddCommGroup (V →ᴬ[𝕜] W) := inferInstance -- this is necessary for `norm_smul`
rw [coe_smul, Pi.smul_apply, norm_smul, norm_smul _ (f.contLinear),
← mul_max_of_nonneg _ _ (norm_nonneg t)]
| Mathlib/Analysis/NormedSpace/ContinuousAffineMap.lean | 220 | 236 | theorem norm_comp_le (g : W₂ →ᴬ[𝕜] V) : ‖f.comp g‖ ≤ ‖f‖ * ‖g‖ + ‖f 0‖ := by |
rw [norm_def, max_le_iff]
constructor
· calc
‖f.comp g 0‖ = ‖f (g 0)‖ := by simp
_ = ‖f.contLinear (g 0) + f 0‖ := by rw [f.decomp]; simp
_ ≤ ‖f.contLinear‖ * ‖g 0‖ + ‖f 0‖ :=
((norm_add_le _ _).trans (add_le_add_right (f.contLinear.le_opNorm _) _))
_ ≤ ‖f‖ * ‖g‖ + ‖f 0‖ :=
add_le_add_right
(mul_le_mul f.norm_contLinear_le g.norm_image_zero_le (norm_nonneg _) (norm_nonneg _)) _
· calc
‖(f.comp g).contLinear‖ ≤ ‖f.contLinear‖ * ‖g.contLinear‖ :=
(g.comp_contLinear f).symm ▸ f.contLinear.opNorm_comp_le _
_ ≤ ‖f‖ * ‖g‖ :=
(mul_le_mul f.norm_contLinear_le g.norm_contLinear_le (norm_nonneg _) (norm_nonneg _))
_ ≤ ‖f‖ * ‖g‖ + ‖f 0‖ := by rw [le_add_iff_nonneg_right]; apply norm_nonneg
|
/-
Copyright (c) 2020 Jalex Stark. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jalex Stark, Scott Morrison, Eric Wieser, Oliver Nash, Wen Yang
-/
import Mathlib.Data.Matrix.Basic
import Mathlib.LinearAlgebra.Matrix.Trace
#align_import data.matrix.basis from "leanprover-community/mathlib"@"320df450e9abeb5fc6417971e75acb6ae8bc3794"
/-!
# Matrices with a single non-zero element.
This file provides `Matrix.stdBasisMatrix`. The matrix `Matrix.stdBasisMatrix i j c` has `c`
at position `(i, j)`, and zeroes elsewhere.
-/
variable {l m n : Type*}
variable {R α : Type*}
namespace Matrix
open Matrix
variable [DecidableEq l] [DecidableEq m] [DecidableEq n]
variable [Semiring α]
/-- `stdBasisMatrix i j a` is the matrix with `a` in the `i`-th row, `j`-th column,
and zeroes elsewhere.
-/
def stdBasisMatrix (i : m) (j : n) (a : α) : Matrix m n α := fun i' j' =>
if i = i' ∧ j = j' then a else 0
#align matrix.std_basis_matrix Matrix.stdBasisMatrix
@[simp]
theorem smul_stdBasisMatrix [SMulZeroClass R α] (r : R) (i : m) (j : n) (a : α) :
r • stdBasisMatrix i j a = stdBasisMatrix i j (r • a) := by
unfold stdBasisMatrix
ext
simp [smul_ite]
#align matrix.smul_std_basis_matrix Matrix.smul_stdBasisMatrix
@[simp]
theorem stdBasisMatrix_zero (i : m) (j : n) : stdBasisMatrix i j (0 : α) = 0 := by
unfold stdBasisMatrix
ext
simp
#align matrix.std_basis_matrix_zero Matrix.stdBasisMatrix_zero
theorem stdBasisMatrix_add (i : m) (j : n) (a b : α) :
stdBasisMatrix i j (a + b) = stdBasisMatrix i j a + stdBasisMatrix i j b := by
unfold stdBasisMatrix; ext
split_ifs with h <;> simp [h]
#align matrix.std_basis_matrix_add Matrix.stdBasisMatrix_add
theorem mulVec_stdBasisMatrix [Fintype m] (i : n) (j : m) (c : α) (x : m → α) :
mulVec (stdBasisMatrix i j c) x = Function.update (0 : n → α) i (c * x j) := by
ext i'
simp [stdBasisMatrix, mulVec, dotProduct]
rcases eq_or_ne i i' with rfl|h
· simp
simp [h, h.symm]
theorem matrix_eq_sum_std_basis [Fintype m] [Fintype n] (x : Matrix m n α) :
x = ∑ i : m, ∑ j : n, stdBasisMatrix i j (x i j) := by
ext i j; symm
iterate 2 rw [Finset.sum_apply]
-- Porting note: was `convert`
refine (Fintype.sum_eq_single i ?_).trans ?_; swap
· -- Porting note: `simp` seems unwilling to apply `Fintype.sum_apply`
simp (config := { unfoldPartialApp := true }) only [stdBasisMatrix]
rw [Fintype.sum_apply, Fintype.sum_apply]
simp
· intro j' hj'
-- Porting note: `simp` seems unwilling to apply `Fintype.sum_apply`
simp (config := { unfoldPartialApp := true }) only [stdBasisMatrix]
rw [Fintype.sum_apply, Fintype.sum_apply]
simp [hj']
#align matrix.matrix_eq_sum_std_basis Matrix.matrix_eq_sum_std_basis
-- TODO: tie this up with the `Basis` machinery of linear algebra
-- this is not completely trivial because we are indexing by two types, instead of one
-- TODO: add `std_basis_vec`
theorem std_basis_eq_basis_mul_basis (i : m) (j : n) :
stdBasisMatrix i j (1 : α) =
vecMulVec (fun i' => ite (i = i') 1 0) fun j' => ite (j = j') 1 0 := by
ext i' j'
-- Porting note: was `norm_num [std_basis_matrix, vec_mul_vec]` though there are no numerals
-- involved.
simp only [stdBasisMatrix, vecMulVec, mul_ite, mul_one, mul_zero, of_apply]
-- Porting note: added next line
simp_rw [@and_comm (i = i')]
exact ite_and _ _ _ _
#align matrix.std_basis_eq_basis_mul_basis Matrix.std_basis_eq_basis_mul_basis
-- todo: the old proof used fintypes, I don't know `Finsupp` but this feels generalizable
@[elab_as_elim]
protected theorem induction_on' [Finite m] [Finite n] {P : Matrix m n α → Prop} (M : Matrix m n α)
(h_zero : P 0) (h_add : ∀ p q, P p → P q → P (p + q))
(h_std_basis : ∀ (i : m) (j : n) (x : α), P (stdBasisMatrix i j x)) : P M := by
cases nonempty_fintype m; cases nonempty_fintype n
rw [matrix_eq_sum_std_basis M, ← Finset.sum_product']
apply Finset.sum_induction _ _ h_add h_zero
· intros
apply h_std_basis
#align matrix.induction_on' Matrix.induction_on'
@[elab_as_elim]
protected theorem induction_on [Finite m] [Finite n] [Nonempty m] [Nonempty n]
{P : Matrix m n α → Prop} (M : Matrix m n α) (h_add : ∀ p q, P p → P q → P (p + q))
(h_std_basis : ∀ i j x, P (stdBasisMatrix i j x)) : P M :=
Matrix.induction_on' M
(by
inhabit m
inhabit n
simpa using h_std_basis default default 0)
h_add h_std_basis
#align matrix.induction_on Matrix.induction_on
namespace StdBasisMatrix
section
variable (i : m) (j : n) (c : α) (i' : m) (j' : n)
@[simp]
theorem apply_same : stdBasisMatrix i j c i j = c :=
if_pos (And.intro rfl rfl)
#align matrix.std_basis_matrix.apply_same Matrix.StdBasisMatrix.apply_same
@[simp]
theorem apply_of_ne (h : ¬(i = i' ∧ j = j')) : stdBasisMatrix i j c i' j' = 0 := by
simp only [stdBasisMatrix, and_imp, ite_eq_right_iff]
tauto
#align matrix.std_basis_matrix.apply_of_ne Matrix.StdBasisMatrix.apply_of_ne
@[simp]
theorem apply_of_row_ne {i i' : m} (hi : i ≠ i') (j j' : n) (a : α) :
stdBasisMatrix i j a i' j' = 0 := by simp [hi]
#align matrix.std_basis_matrix.apply_of_row_ne Matrix.StdBasisMatrix.apply_of_row_ne
@[simp]
theorem apply_of_col_ne (i i' : m) {j j' : n} (hj : j ≠ j') (a : α) :
stdBasisMatrix i j a i' j' = 0 := by simp [hj]
#align matrix.std_basis_matrix.apply_of_col_ne Matrix.StdBasisMatrix.apply_of_col_ne
end
section
variable (i j : n) (c : α) (i' j' : n)
@[simp]
theorem diag_zero (h : j ≠ i) : diag (stdBasisMatrix i j c) = 0 :=
funext fun _ => if_neg fun ⟨e₁, e₂⟩ => h (e₂.trans e₁.symm)
#align matrix.std_basis_matrix.diag_zero Matrix.StdBasisMatrix.diag_zero
@[simp]
theorem diag_same : diag (stdBasisMatrix i i c) = Pi.single i c := by
ext j
by_cases hij : i = j <;> (try rw [hij]) <;> simp [hij]
#align matrix.std_basis_matrix.diag_same Matrix.StdBasisMatrix.diag_same
variable [Fintype n]
@[simp]
theorem trace_zero (h : j ≠ i) : trace (stdBasisMatrix i j c) = 0 := by
-- Porting note: added `-diag_apply`
simp [trace, -diag_apply, h]
#align matrix.std_basis_matrix.trace_zero Matrix.StdBasisMatrix.trace_zero
@[simp]
theorem trace_eq : trace (stdBasisMatrix i i c) = c := by
-- Porting note: added `-diag_apply`
simp [trace, -diag_apply]
#align matrix.std_basis_matrix.trace_eq Matrix.StdBasisMatrix.trace_eq
@[simp]
theorem mul_left_apply_same (b : n) (M : Matrix n n α) :
(stdBasisMatrix i j c * M) i b = c * M j b := by simp [mul_apply, stdBasisMatrix]
#align matrix.std_basis_matrix.mul_left_apply_same Matrix.StdBasisMatrix.mul_left_apply_same
@[simp]
theorem mul_right_apply_same (a : n) (M : Matrix n n α) :
(M * stdBasisMatrix i j c) a j = M a i * c := by simp [mul_apply, stdBasisMatrix, mul_comm]
#align matrix.std_basis_matrix.mul_right_apply_same Matrix.StdBasisMatrix.mul_right_apply_same
@[simp]
theorem mul_left_apply_of_ne (a b : n) (h : a ≠ i) (M : Matrix n n α) :
(stdBasisMatrix i j c * M) a b = 0 := by simp [mul_apply, h.symm]
#align matrix.std_basis_matrix.mul_left_apply_of_ne Matrix.StdBasisMatrix.mul_left_apply_of_ne
@[simp]
| Mathlib/Data/Matrix/Basis.lean | 195 | 196 | theorem mul_right_apply_of_ne (a b : n) (hbj : b ≠ j) (M : Matrix n n α) :
(M * stdBasisMatrix i j c) a b = 0 := by | simp [mul_apply, hbj.symm]
|
/-
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.Measure.GiryMonad
import Mathlib.Dynamics.Ergodic.MeasurePreserving
import Mathlib.MeasureTheory.Integral.Lebesgue
import Mathlib.MeasureTheory.Measure.OpenPos
#align_import measure_theory.constructions.prod.basic from "leanprover-community/mathlib"@"00abe0695d8767201e6d008afa22393978bb324d"
/-!
# The product measure
In this file we define and prove properties about the binary product measure. If `α` and `β` have
s-finite measures `μ` resp. `ν` then `α × β` can be equipped with a s-finite measure `μ.prod ν` that
satisfies `(μ.prod ν) s = ∫⁻ x, ν {y | (x, y) ∈ s} ∂μ`.
We also have `(μ.prod ν) (s ×ˢ t) = μ s * ν t`, i.e. the measure of a rectangle is the product of
the measures of the sides.
We also prove Tonelli's theorem.
## Main definition
* `MeasureTheory.Measure.prod`: The product of two measures.
## Main results
* `MeasureTheory.Measure.prod_apply` states `μ.prod ν s = ∫⁻ x, ν {y | (x, y) ∈ s} ∂μ`
for measurable `s`. `MeasureTheory.Measure.prod_apply_symm` is the reversed version.
* `MeasureTheory.Measure.prod_prod` states `μ.prod ν (s ×ˢ t) = μ s * ν t` for measurable sets
`s` and `t`.
* `MeasureTheory.lintegral_prod`: Tonelli's theorem. It states that for a measurable function
`α × β → ℝ≥0∞` we have `∫⁻ z, f z ∂(μ.prod ν) = ∫⁻ x, ∫⁻ y, f (x, y) ∂ν ∂μ`. The version
for functions `α → β → ℝ≥0∞` is reversed, and called `lintegral_lintegral`. Both versions have
a variant with `_symm` appended, where the order of integration is reversed.
The lemma `Measurable.lintegral_prod_right'` states that the inner integral of the right-hand side
is measurable.
## Implementation Notes
Many results are proven twice, once for functions in curried form (`α → β → γ`) and one for
functions in uncurried form (`α × β → γ`). The former often has an assumption
`Measurable (uncurry f)`, which could be inconvenient to discharge, but for the latter it is more
common that the function has to be given explicitly, since Lean cannot synthesize the function by
itself. We name the lemmas about the uncurried form with a prime.
Tonelli's theorem has a different naming scheme, since the version for the uncurried version is
reversed.
## Tags
product measure, Tonelli's theorem, Fubini-Tonelli theorem
-/
noncomputable section
open scoped Classical
open Topology ENNReal MeasureTheory
open Set Function Real ENNReal
open MeasureTheory MeasurableSpace MeasureTheory.Measure
open TopologicalSpace hiding generateFrom
open Filter hiding prod_eq map
variable {α α' β β' γ E : Type*}
/-- Rectangles formed by π-systems form a π-system. -/
theorem IsPiSystem.prod {C : Set (Set α)} {D : Set (Set β)} (hC : IsPiSystem C)
(hD : IsPiSystem D) : IsPiSystem (image2 (· ×ˢ ·) C D) := by
rintro _ ⟨s₁, hs₁, t₁, ht₁, rfl⟩ _ ⟨s₂, hs₂, t₂, ht₂, rfl⟩ hst
rw [prod_inter_prod] at hst ⊢; rw [prod_nonempty_iff] at hst
exact mem_image2_of_mem (hC _ hs₁ _ hs₂ hst.1) (hD _ ht₁ _ ht₂ hst.2)
#align is_pi_system.prod IsPiSystem.prod
/-- Rectangles of countably spanning sets are countably spanning. -/
theorem IsCountablySpanning.prod {C : Set (Set α)} {D : Set (Set β)} (hC : IsCountablySpanning C)
(hD : IsCountablySpanning D) : IsCountablySpanning (image2 (· ×ˢ ·) C D) := by
rcases hC, hD with ⟨⟨s, h1s, h2s⟩, t, h1t, h2t⟩
refine ⟨fun n => s n.unpair.1 ×ˢ t n.unpair.2, fun n => mem_image2_of_mem (h1s _) (h1t _), ?_⟩
rw [iUnion_unpair_prod, h2s, h2t, univ_prod_univ]
#align is_countably_spanning.prod IsCountablySpanning.prod
variable [MeasurableSpace α] [MeasurableSpace α'] [MeasurableSpace β] [MeasurableSpace β']
variable [MeasurableSpace γ]
variable {μ μ' : Measure α} {ν ν' : Measure β} {τ : Measure γ}
variable [NormedAddCommGroup E]
/-! ### Measurability
Before we define the product measure, we can talk about the measurability of operations on binary
functions. We show that if `f` is a binary measurable function, then the function that integrates
along one of the variables (using either the Lebesgue or Bochner integral) is measurable.
-/
/-- The product of generated σ-algebras is the one generated by rectangles, if both generating sets
are countably spanning. -/
theorem generateFrom_prod_eq {α β} {C : Set (Set α)} {D : Set (Set β)} (hC : IsCountablySpanning C)
(hD : IsCountablySpanning D) :
@Prod.instMeasurableSpace _ _ (generateFrom C) (generateFrom D) =
generateFrom (image2 (· ×ˢ ·) C D) := by
apply le_antisymm
· refine sup_le ?_ ?_ <;> rw [comap_generateFrom] <;> apply generateFrom_le <;>
rintro _ ⟨s, hs, rfl⟩
· rcases hD with ⟨t, h1t, h2t⟩
rw [← prod_univ, ← h2t, prod_iUnion]
apply MeasurableSet.iUnion
intro n
apply measurableSet_generateFrom
exact ⟨s, hs, t n, h1t n, rfl⟩
· rcases hC with ⟨t, h1t, h2t⟩
rw [← univ_prod, ← h2t, iUnion_prod_const]
apply MeasurableSet.iUnion
rintro n
apply measurableSet_generateFrom
exact mem_image2_of_mem (h1t n) hs
· apply generateFrom_le
rintro _ ⟨s, hs, t, ht, rfl⟩
dsimp only
rw [prod_eq]
apply (measurable_fst _).inter (measurable_snd _)
· exact measurableSet_generateFrom hs
· exact measurableSet_generateFrom ht
#align generate_from_prod_eq generateFrom_prod_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_prod {C : Set (Set α)} {D : Set (Set β)} (hC : generateFrom C = ‹_›)
(hD : generateFrom D = ‹_›) (h2C : IsCountablySpanning C) (h2D : IsCountablySpanning D) :
generateFrom (image2 (· ×ˢ ·) C D) = Prod.instMeasurableSpace := by
rw [← hC, ← hD, generateFrom_prod_eq h2C h2D]
#align generate_from_eq_prod generateFrom_eq_prod
/-- The product σ-algebra is generated from boxes, i.e. `s ×ˢ t` for sets `s : Set α` and
`t : Set β`. -/
theorem generateFrom_prod :
generateFrom (image2 (· ×ˢ ·) { s : Set α | MeasurableSet s } { t : Set β | MeasurableSet t }) =
Prod.instMeasurableSpace :=
generateFrom_eq_prod generateFrom_measurableSet generateFrom_measurableSet
isCountablySpanning_measurableSet isCountablySpanning_measurableSet
#align generate_from_prod generateFrom_prod
/-- Rectangles form a π-system. -/
theorem isPiSystem_prod :
IsPiSystem (image2 (· ×ˢ ·) { s : Set α | MeasurableSet s } { t : Set β | MeasurableSet t }) :=
isPiSystem_measurableSet.prod isPiSystem_measurableSet
#align is_pi_system_prod isPiSystem_prod
/-- If `ν` is a finite measure, and `s ⊆ α × β` is measurable, then `x ↦ ν { y | (x, y) ∈ s }` is
a measurable function. `measurable_measure_prod_mk_left` is strictly more general. -/
theorem measurable_measure_prod_mk_left_finite [IsFiniteMeasure ν] {s : Set (α × β)}
(hs : MeasurableSet s) : Measurable fun x => ν (Prod.mk x ⁻¹' s) := by
refine induction_on_inter (C := fun s => Measurable fun x => ν (Prod.mk x ⁻¹' s))
generateFrom_prod.symm isPiSystem_prod ?_ ?_ ?_ ?_ hs
· simp
· rintro _ ⟨s, hs, t, _, rfl⟩
simp only [mk_preimage_prod_right_eq_if, measure_if]
exact measurable_const.indicator hs
· intro t ht h2t
simp_rw [preimage_compl, measure_compl (measurable_prod_mk_left ht) (measure_ne_top ν _)]
exact h2t.const_sub _
· intro f h1f h2f h3f
simp_rw [preimage_iUnion]
have : ∀ b, ν (⋃ i, Prod.mk b ⁻¹' f i) = ∑' i, ν (Prod.mk b ⁻¹' f i) := fun b =>
measure_iUnion (fun i j hij => Disjoint.preimage _ (h1f hij)) fun i =>
measurable_prod_mk_left (h2f i)
simp_rw [this]
apply Measurable.ennreal_tsum h3f
#align measurable_measure_prod_mk_left_finite measurable_measure_prod_mk_left_finite
/-- If `ν` is an s-finite measure, and `s ⊆ α × β` is measurable, then `x ↦ ν { y | (x, y) ∈ s }`
is a measurable function. -/
theorem measurable_measure_prod_mk_left [SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) :
Measurable fun x => ν (Prod.mk x ⁻¹' s) := by
rw [← sum_sFiniteSeq ν]
simp_rw [Measure.sum_apply_of_countable]
exact Measurable.ennreal_tsum (fun i ↦ measurable_measure_prod_mk_left_finite hs)
#align measurable_measure_prod_mk_left measurable_measure_prod_mk_left
/-- If `μ` is a σ-finite measure, and `s ⊆ α × β` is measurable, then `y ↦ μ { x | (x, y) ∈ s }` is
a measurable function. -/
theorem measurable_measure_prod_mk_right {μ : Measure α} [SFinite μ] {s : Set (α × β)}
(hs : MeasurableSet s) : Measurable fun y => μ ((fun x => (x, y)) ⁻¹' s) :=
measurable_measure_prod_mk_left (measurableSet_swap_iff.mpr hs)
#align measurable_measure_prod_mk_right measurable_measure_prod_mk_right
theorem Measurable.map_prod_mk_left [SFinite ν] :
Measurable fun x : α => map (Prod.mk x) ν := by
apply measurable_of_measurable_coe; intro s hs
simp_rw [map_apply measurable_prod_mk_left hs]
exact measurable_measure_prod_mk_left hs
#align measurable.map_prod_mk_left Measurable.map_prod_mk_left
theorem Measurable.map_prod_mk_right {μ : Measure α} [SFinite μ] :
Measurable fun y : β => map (fun x : α => (x, y)) μ := by
apply measurable_of_measurable_coe; intro s hs
simp_rw [map_apply measurable_prod_mk_right hs]
exact measurable_measure_prod_mk_right hs
#align measurable.map_prod_mk_right Measurable.map_prod_mk_right
theorem MeasurableEmbedding.prod_mk {α β γ δ : Type*} {mα : MeasurableSpace α}
{mβ : MeasurableSpace β} {mγ : MeasurableSpace γ} {mδ : MeasurableSpace δ} {f : α → β}
{g : γ → δ} (hg : MeasurableEmbedding g) (hf : MeasurableEmbedding f) :
MeasurableEmbedding fun x : γ × α => (g x.1, f x.2) := by
have h_inj : Function.Injective fun x : γ × α => (g x.fst, f x.snd) := by
intro x y hxy
rw [← @Prod.mk.eta _ _ x, ← @Prod.mk.eta _ _ y]
simp only [Prod.mk.inj_iff] at hxy ⊢
exact ⟨hg.injective hxy.1, hf.injective hxy.2⟩
refine ⟨h_inj, ?_, ?_⟩
· exact (hg.measurable.comp measurable_fst).prod_mk (hf.measurable.comp measurable_snd)
· -- Induction using the π-system of rectangles
refine fun s hs =>
@MeasurableSpace.induction_on_inter _
(fun s => MeasurableSet ((fun x : γ × α => (g x.fst, f x.snd)) '' s)) _ _
generateFrom_prod.symm isPiSystem_prod ?_ ?_ ?_ ?_ _ hs
· simp only [Set.image_empty, MeasurableSet.empty]
· rintro t ⟨t₁, ht₁, t₂, ht₂, rfl⟩
rw [← Set.prod_image_image_eq]
exact (hg.measurableSet_image.mpr ht₁).prod (hf.measurableSet_image.mpr ht₂)
· intro t _ ht_m
rw [← Set.range_diff_image h_inj, ← Set.prod_range_range_eq]
exact
MeasurableSet.diff (MeasurableSet.prod hg.measurableSet_range hf.measurableSet_range) ht_m
· intro g _ _ hg
simp_rw [Set.image_iUnion]
exact MeasurableSet.iUnion hg
#align measurable_embedding.prod_mk MeasurableEmbedding.prod_mk
lemma MeasurableEmbedding.prod_mk_left {β γ : Type*} [MeasurableSingletonClass α]
{mβ : MeasurableSpace β} {mγ : MeasurableSpace γ}
(x : α) {f : γ → β} (hf : MeasurableEmbedding f) :
MeasurableEmbedding (fun y ↦ (x, f y)) where
injective := by
intro y y'
simp only [Prod.mk.injEq, true_and]
exact fun h ↦ hf.injective h
measurable := Measurable.prod_mk measurable_const hf.measurable
measurableSet_image' := by
intro s hs
convert (MeasurableSet.singleton x).prod (hf.measurableSet_image.mpr hs)
ext x
simp
lemma measurableEmbedding_prod_mk_left [MeasurableSingletonClass α] (x : α) :
MeasurableEmbedding (Prod.mk x : β → α × β) :=
MeasurableEmbedding.prod_mk_left x MeasurableEmbedding.id
lemma MeasurableEmbedding.prod_mk_right {β γ : Type*} [MeasurableSingletonClass α]
{mβ : MeasurableSpace β} {mγ : MeasurableSpace γ}
{f : γ → β} (hf : MeasurableEmbedding f) (x : α) :
MeasurableEmbedding (fun y ↦ (f y, x)) where
injective := by
intro y y'
simp only [Prod.mk.injEq, and_true]
exact fun h ↦ hf.injective h
measurable := Measurable.prod_mk hf.measurable measurable_const
measurableSet_image' := by
intro s hs
convert (hf.measurableSet_image.mpr hs).prod (MeasurableSet.singleton x)
ext x
simp
lemma measurableEmbedding_prod_mk_right [MeasurableSingletonClass α] (x : α) :
MeasurableEmbedding (fun y ↦ (y, x) : β → β × α) :=
MeasurableEmbedding.prod_mk_right MeasurableEmbedding.id x
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
Tonelli's theorem is measurable. -/
theorem Measurable.lintegral_prod_right' [SFinite ν] :
∀ {f : α × β → ℝ≥0∞}, Measurable f → Measurable fun x => ∫⁻ y, f (x, y) ∂ν := by
have m := @measurable_prod_mk_left
refine Measurable.ennreal_induction (P := fun f => Measurable fun (x : α) => ∫⁻ y, f (x, y) ∂ν)
?_ ?_ ?_
· intro c s hs
simp only [← indicator_comp_right]
suffices Measurable fun x => c * ν (Prod.mk x ⁻¹' s) by simpa [lintegral_indicator _ (m hs)]
exact (measurable_measure_prod_mk_left hs).const_mul _
· rintro f g - hf - h2f h2g
simp only [Pi.add_apply]
conv => enter [1, x]; erw [lintegral_add_left (hf.comp m)]
exact h2f.add h2g
· intro f hf h2f h3f
have := measurable_iSup h3f
have : ∀ x, Monotone fun n y => f n (x, y) := fun x i j hij y => h2f hij (x, y)
conv => enter [1, x]; erw [lintegral_iSup (fun n => (hf n).comp m) (this x)]
assumption
#align measurable.lintegral_prod_right' Measurable.lintegral_prod_right'
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
Tonelli's theorem is measurable.
This version has the argument `f` in curried form. -/
theorem Measurable.lintegral_prod_right [SFinite ν] {f : α → β → ℝ≥0∞}
(hf : Measurable (uncurry f)) : Measurable fun x => ∫⁻ y, f x y ∂ν :=
hf.lintegral_prod_right'
#align measurable.lintegral_prod_right Measurable.lintegral_prod_right
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Tonelli's theorem is measurable. -/
theorem Measurable.lintegral_prod_left' [SFinite μ] {f : α × β → ℝ≥0∞} (hf : Measurable f) :
Measurable fun y => ∫⁻ x, f (x, y) ∂μ :=
(measurable_swap_iff.mpr hf).lintegral_prod_right'
#align measurable.lintegral_prod_left' Measurable.lintegral_prod_left'
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Tonelli's theorem is measurable.
This version has the argument `f` in curried form. -/
theorem Measurable.lintegral_prod_left [SFinite μ] {f : α → β → ℝ≥0∞}
(hf : Measurable (uncurry f)) : Measurable fun y => ∫⁻ x, f x y ∂μ :=
hf.lintegral_prod_left'
#align measurable.lintegral_prod_left Measurable.lintegral_prod_left
/-! ### The product measure -/
namespace MeasureTheory
namespace Measure
/-- The binary product of measures. They are defined for arbitrary measures, but we basically
prove all properties under the assumption that at least one of them is s-finite. -/
protected irreducible_def prod (μ : Measure α) (ν : Measure β) : Measure (α × β) :=
bind μ fun x : α => map (Prod.mk x) ν
#align measure_theory.measure.prod MeasureTheory.Measure.prod
instance prod.measureSpace {α β} [MeasureSpace α] [MeasureSpace β] : MeasureSpace (α × β) where
volume := volume.prod volume
#align measure_theory.measure.prod.measure_space MeasureTheory.Measure.prod.measureSpace
theorem volume_eq_prod (α β) [MeasureSpace α] [MeasureSpace β] :
(volume : Measure (α × β)) = (volume : Measure α).prod (volume : Measure β) :=
rfl
#align measure_theory.measure.volume_eq_prod MeasureTheory.Measure.volume_eq_prod
variable [SFinite ν]
theorem prod_apply {s : Set (α × β)} (hs : MeasurableSet s) :
μ.prod ν s = ∫⁻ x, ν (Prod.mk x ⁻¹' s) ∂μ := by
simp_rw [Measure.prod, bind_apply hs (Measurable.map_prod_mk_left (ν := ν)),
map_apply measurable_prod_mk_left hs]
#align measure_theory.measure.prod_apply MeasureTheory.Measure.prod_apply
/-- The product measure of the product of two sets is the product of their measures. Note that we
do not need the sets to be measurable. -/
@[simp]
theorem prod_prod (s : Set α) (t : Set β) : μ.prod ν (s ×ˢ t) = μ s * ν t := by
apply le_antisymm
· set S := toMeasurable μ s
set T := toMeasurable ν t
have hSTm : MeasurableSet (S ×ˢ T) :=
(measurableSet_toMeasurable _ _).prod (measurableSet_toMeasurable _ _)
calc
μ.prod ν (s ×ˢ t) ≤ μ.prod ν (S ×ˢ T) := by gcongr <;> apply subset_toMeasurable
_ = μ S * ν T := by
rw [prod_apply hSTm]
simp_rw [mk_preimage_prod_right_eq_if, measure_if,
lintegral_indicator _ (measurableSet_toMeasurable _ _), lintegral_const,
restrict_apply_univ, mul_comm]
_ = μ s * ν t := by rw [measure_toMeasurable, measure_toMeasurable]
· -- Formalization is based on https://mathoverflow.net/a/254134/136589
set ST := toMeasurable (μ.prod ν) (s ×ˢ t)
have hSTm : MeasurableSet ST := measurableSet_toMeasurable _ _
have hST : s ×ˢ t ⊆ ST := subset_toMeasurable _ _
set f : α → ℝ≥0∞ := fun x => ν (Prod.mk x ⁻¹' ST)
have hfm : Measurable f := measurable_measure_prod_mk_left hSTm
set s' : Set α := { x | ν t ≤ f x }
have hss' : s ⊆ s' := fun x hx => measure_mono fun y hy => hST <| mk_mem_prod hx hy
calc
μ s * ν t ≤ μ s' * ν t := by gcongr
_ = ∫⁻ _ in s', ν t ∂μ := by rw [set_lintegral_const, mul_comm]
_ ≤ ∫⁻ x in s', f x ∂μ := set_lintegral_mono measurable_const hfm fun x => id
_ ≤ ∫⁻ x, f x ∂μ := lintegral_mono' restrict_le_self le_rfl
_ = μ.prod ν ST := (prod_apply hSTm).symm
_ = μ.prod ν (s ×ˢ t) := measure_toMeasurable _
#align measure_theory.measure.prod_prod MeasureTheory.Measure.prod_prod
@[simp] lemma map_fst_prod : Measure.map Prod.fst (μ.prod ν) = (ν univ) • μ := by
ext s hs
simp [Measure.map_apply measurable_fst hs, ← prod_univ, mul_comm]
@[simp] lemma map_snd_prod : Measure.map Prod.snd (μ.prod ν) = (μ univ) • ν := by
ext s hs
simp [Measure.map_apply measurable_snd hs, ← univ_prod]
instance prod.instIsOpenPosMeasure {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y]
{m : MeasurableSpace X} {μ : Measure X} [IsOpenPosMeasure μ] {m' : MeasurableSpace Y}
{ν : Measure Y} [IsOpenPosMeasure ν] [SFinite ν] : IsOpenPosMeasure (μ.prod ν) := by
constructor
rintro U U_open ⟨⟨x, y⟩, hxy⟩
rcases isOpen_prod_iff.1 U_open x y hxy with ⟨u, v, u_open, v_open, xu, yv, huv⟩
refine ne_of_gt (lt_of_lt_of_le ?_ (measure_mono huv))
simp only [prod_prod, CanonicallyOrderedCommSemiring.mul_pos]
constructor
· exact u_open.measure_pos μ ⟨x, xu⟩
· exact v_open.measure_pos ν ⟨y, yv⟩
#align measure_theory.measure.prod.is_open_pos_measure MeasureTheory.Measure.prod.instIsOpenPosMeasure
instance {X Y : Type*}
[TopologicalSpace X] [MeasureSpace X] [IsOpenPosMeasure (volume : Measure X)]
[TopologicalSpace Y] [MeasureSpace Y] [IsOpenPosMeasure (volume : Measure Y)]
[SFinite (volume : Measure Y)] : IsOpenPosMeasure (volume : Measure (X × Y)) :=
prod.instIsOpenPosMeasure
instance prod.instIsFiniteMeasure {α β : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β}
(μ : Measure α) (ν : Measure β) [IsFiniteMeasure μ] [IsFiniteMeasure ν] :
IsFiniteMeasure (μ.prod ν) := by
constructor
rw [← univ_prod_univ, prod_prod]
exact mul_lt_top (measure_lt_top _ _).ne (measure_lt_top _ _).ne
#align measure_theory.measure.prod.measure_theory.is_finite_measure MeasureTheory.Measure.prod.instIsFiniteMeasure
instance {α β : Type*} [MeasureSpace α] [MeasureSpace β] [IsFiniteMeasure (volume : Measure α)]
[IsFiniteMeasure (volume : Measure β)] : IsFiniteMeasure (volume : Measure (α × β)) :=
prod.instIsFiniteMeasure _ _
instance prod.instIsProbabilityMeasure {α β : Type*} {mα : MeasurableSpace α}
{mβ : MeasurableSpace β} (μ : Measure α) (ν : Measure β) [IsProbabilityMeasure μ]
[IsProbabilityMeasure ν] : IsProbabilityMeasure (μ.prod ν) :=
⟨by rw [← univ_prod_univ, prod_prod, measure_univ, measure_univ, mul_one]⟩
#align measure_theory.measure.prod.measure_theory.is_probability_measure MeasureTheory.Measure.prod.instIsProbabilityMeasure
instance {α β : Type*} [MeasureSpace α] [MeasureSpace β]
[IsProbabilityMeasure (volume : Measure α)] [IsProbabilityMeasure (volume : Measure β)] :
IsProbabilityMeasure (volume : Measure (α × β)) :=
prod.instIsProbabilityMeasure _ _
instance prod.instIsFiniteMeasureOnCompacts {α β : Type*} [TopologicalSpace α] [TopologicalSpace β]
{mα : MeasurableSpace α} {mβ : MeasurableSpace β} (μ : Measure α) (ν : Measure β)
[IsFiniteMeasureOnCompacts μ] [IsFiniteMeasureOnCompacts ν] [SFinite ν] :
IsFiniteMeasureOnCompacts (μ.prod ν) := by
refine ⟨fun K hK => ?_⟩
set L := (Prod.fst '' K) ×ˢ (Prod.snd '' K) with hL
have : K ⊆ L := by
rintro ⟨x, y⟩ hxy
simp only [L, prod_mk_mem_set_prod_eq, mem_image, Prod.exists, exists_and_right,
exists_eq_right]
exact ⟨⟨y, hxy⟩, ⟨x, hxy⟩⟩
apply lt_of_le_of_lt (measure_mono this)
rw [hL, prod_prod]
exact
mul_lt_top (IsCompact.measure_lt_top (hK.image continuous_fst)).ne
(IsCompact.measure_lt_top (hK.image continuous_snd)).ne
#align measure_theory.measure.prod.measure_theory.is_finite_measure_on_compacts MeasureTheory.Measure.prod.instIsFiniteMeasureOnCompacts
instance {X Y : Type*}
[TopologicalSpace X] [MeasureSpace X] [IsFiniteMeasureOnCompacts (volume : Measure X)]
[TopologicalSpace Y] [MeasureSpace Y] [IsFiniteMeasureOnCompacts (volume : Measure Y)]
[SFinite (volume : Measure Y)] : IsFiniteMeasureOnCompacts (volume : Measure (X × Y)) :=
prod.instIsFiniteMeasureOnCompacts _ _
instance prod.instNoAtoms_fst [NoAtoms μ] :
NoAtoms (Measure.prod μ ν) := by
refine NoAtoms.mk (fun x => ?_)
rw [← Set.singleton_prod_singleton, Measure.prod_prod, measure_singleton, zero_mul]
instance prod.instNoAtoms_snd [NoAtoms ν] :
NoAtoms (Measure.prod μ ν) := by
refine NoAtoms.mk (fun x => ?_)
rw [← Set.singleton_prod_singleton, Measure.prod_prod, measure_singleton (μ := ν), mul_zero]
theorem ae_measure_lt_top {s : Set (α × β)} (hs : MeasurableSet s) (h2s : (μ.prod ν) s ≠ ∞) :
∀ᵐ x ∂μ, ν (Prod.mk x ⁻¹' s) < ∞ := by
rw [prod_apply hs] at h2s
exact ae_lt_top (measurable_measure_prod_mk_left hs) h2s
#align measure_theory.measure.ae_measure_lt_top MeasureTheory.Measure.ae_measure_lt_top
/-- Note: the assumption `hs` cannot be dropped. For a counterexample, see
Walter Rudin *Real and Complex Analysis*, example (c) in section 8.9. -/
theorem measure_prod_null {s : Set (α × β)} (hs : MeasurableSet s) :
μ.prod ν s = 0 ↔ (fun x => ν (Prod.mk x ⁻¹' s)) =ᵐ[μ] 0 := by
rw [prod_apply hs, lintegral_eq_zero_iff (measurable_measure_prod_mk_left hs)]
#align measure_theory.measure.measure_prod_null MeasureTheory.Measure.measure_prod_null
/-- Note: the converse is not true without assuming that `s` is measurable. For a counterexample,
see Walter Rudin *Real and Complex Analysis*, example (c) in section 8.9. -/
theorem measure_ae_null_of_prod_null {s : Set (α × β)} (h : μ.prod ν s = 0) :
(fun x => ν (Prod.mk x ⁻¹' s)) =ᵐ[μ] 0 := by
obtain ⟨t, hst, mt, ht⟩ := exists_measurable_superset_of_null h
rw [measure_prod_null mt] at ht
rw [eventuallyLE_antisymm_iff]
exact
⟨EventuallyLE.trans_eq (eventually_of_forall fun x => (measure_mono (preimage_mono hst) : _))
ht,
eventually_of_forall fun x => zero_le _⟩
#align measure_theory.measure.measure_ae_null_of_prod_null MeasureTheory.Measure.measure_ae_null_of_prod_null
theorem AbsolutelyContinuous.prod [SFinite ν'] (h1 : μ ≪ μ') (h2 : ν ≪ ν') :
μ.prod ν ≪ μ'.prod ν' := by
refine AbsolutelyContinuous.mk fun s hs h2s => ?_
rw [measure_prod_null hs] at h2s ⊢
exact (h2s.filter_mono h1.ae_le).mono fun _ h => h2 h
#align measure_theory.measure.absolutely_continuous.prod MeasureTheory.Measure.AbsolutelyContinuous.prod
/-- Note: the converse is not true. For a counterexample, see
Walter Rudin *Real and Complex Analysis*, example (c) in section 8.9. It is true if the set is
measurable, see `ae_prod_mem_iff_ae_ae_mem`. -/
theorem ae_ae_of_ae_prod {p : α × β → Prop} (h : ∀ᵐ z ∂μ.prod ν, p z) :
∀ᵐ x ∂μ, ∀ᵐ y ∂ν, p (x, y) :=
measure_ae_null_of_prod_null h
#align measure_theory.measure.ae_ae_of_ae_prod MeasureTheory.Measure.ae_ae_of_ae_prod
theorem ae_ae_eq_curry_of_prod {f g : α × β → γ} (h : f =ᵐ[μ.prod ν] g) :
∀ᵐ x ∂μ, curry f x =ᵐ[ν] curry g x :=
ae_ae_of_ae_prod h
theorem ae_ae_eq_of_ae_eq_uncurry {f g : α → β → γ} (h : uncurry f =ᵐ[μ.prod ν] uncurry g) :
∀ᵐ x ∂μ, f x =ᵐ[ν] g x :=
ae_ae_eq_curry_of_prod h
theorem ae_prod_mem_iff_ae_ae_mem {s : Set (α × β)} (hs : MeasurableSet s) :
(∀ᵐ z ∂μ.prod ν, z ∈ s) ↔ ∀ᵐ x ∂μ, ∀ᵐ y ∂ν, (x, y) ∈ s :=
measure_prod_null hs.compl
theorem quasiMeasurePreserving_fst : QuasiMeasurePreserving Prod.fst (μ.prod ν) μ := by
refine ⟨measurable_fst, AbsolutelyContinuous.mk fun s hs h2s => ?_⟩
rw [map_apply measurable_fst hs, ← prod_univ, prod_prod, h2s, zero_mul]
#align measure_theory.measure.quasi_measure_preserving_fst MeasureTheory.Measure.quasiMeasurePreserving_fst
theorem quasiMeasurePreserving_snd : QuasiMeasurePreserving Prod.snd (μ.prod ν) ν := by
refine ⟨measurable_snd, AbsolutelyContinuous.mk fun s hs h2s => ?_⟩
rw [map_apply measurable_snd hs, ← univ_prod, prod_prod, h2s, mul_zero]
#align measure_theory.measure.quasi_measure_preserving_snd MeasureTheory.Measure.quasiMeasurePreserving_snd
lemma set_prod_ae_eq {s s' : Set α} {t t' : Set β} (hs : s =ᵐ[μ] s') (ht : t =ᵐ[ν] t') :
(s ×ˢ t : Set (α × β)) =ᵐ[μ.prod ν] (s' ×ˢ t' : Set (α × β)) :=
(quasiMeasurePreserving_fst.preimage_ae_eq hs).inter
(quasiMeasurePreserving_snd.preimage_ae_eq ht)
lemma measure_prod_compl_eq_zero {s : Set α} {t : Set β}
(s_ae_univ : μ sᶜ = 0) (t_ae_univ : ν tᶜ = 0) :
μ.prod ν (s ×ˢ t)ᶜ = 0 := by
rw [Set.compl_prod_eq_union, measure_union_null_iff]
simp [s_ae_univ, t_ae_univ]
lemma _root_.MeasureTheory.NullMeasurableSet.prod {s : Set α} {t : Set β}
(s_mble : NullMeasurableSet s μ) (t_mble : NullMeasurableSet t ν) :
NullMeasurableSet (s ×ˢ t) (μ.prod ν) :=
let ⟨s₀, mble_s₀, s_aeeq_s₀⟩ := s_mble
let ⟨t₀, mble_t₀, t_aeeq_t₀⟩ := t_mble
⟨s₀ ×ˢ t₀, ⟨mble_s₀.prod mble_t₀, set_prod_ae_eq s_aeeq_s₀ t_aeeq_t₀⟩⟩
/-- If `s ×ˢ t` is a null measurable set and `μ s ≠ 0`, then `t` is a null measurable set. -/
lemma _root_.MeasureTheory.NullMeasurableSet.right_of_prod {s : Set α} {t : Set β}
(h : NullMeasurableSet (s ×ˢ t) (μ.prod ν)) (hs : μ s ≠ 0) : NullMeasurableSet t ν := by
rcases h with ⟨u, hum, hu⟩
obtain ⟨x, hxs, hx⟩ : ∃ x ∈ s, (Prod.mk x ⁻¹' (s ×ˢ t)) =ᵐ[ν] (Prod.mk x ⁻¹' u) :=
((frequently_ae_iff.2 hs).and_eventually (ae_ae_eq_curry_of_prod hu)).exists
refine ⟨Prod.mk x ⁻¹' u, measurable_prod_mk_left hum, ?_⟩
rwa [mk_preimage_prod_right hxs] at hx
/-- If `Prod.snd ⁻¹' t` is a null measurable set and `μ ≠ 0`, then `t` is a null measurable set. -/
lemma _root_.MeasureTheory.NullMeasurableSet.of_preimage_snd [NeZero μ] {t : Set β}
(h : NullMeasurableSet (Prod.snd ⁻¹' t) (μ.prod ν)) : NullMeasurableSet t ν :=
.right_of_prod (by rwa [univ_prod]) (NeZero.ne _)
/-- `Prod.snd ⁻¹' t` is null measurable w.r.t. `μ.prod ν` iff `t` is null measurable w.r.t. `ν`
provided that `μ ≠ 0`. -/
lemma nullMeasurableSet_preimage_snd [NeZero μ] {t : Set β} :
NullMeasurableSet (Prod.snd ⁻¹' t) (μ.prod ν) ↔ NullMeasurableSet t ν :=
⟨.of_preimage_snd, (.preimage · quasiMeasurePreserving_snd)⟩
lemma nullMeasurable_comp_snd [NeZero μ] {f : β → γ} :
NullMeasurable (f ∘ Prod.snd) (μ.prod ν) ↔ NullMeasurable f ν :=
forall₂_congr fun s _ ↦ nullMeasurableSet_preimage_snd (t := f ⁻¹' s)
/-- `μ.prod ν` has finite spanning sets in rectangles of finite spanning sets. -/
noncomputable def FiniteSpanningSetsIn.prod {ν : Measure β} {C : Set (Set α)} {D : Set (Set β)}
(hμ : μ.FiniteSpanningSetsIn C) (hν : ν.FiniteSpanningSetsIn D) :
(μ.prod ν).FiniteSpanningSetsIn (image2 (· ×ˢ ·) C D) := by
haveI := hν.sigmaFinite
refine
⟨fun n => hμ.set n.unpair.1 ×ˢ hν.set n.unpair.2, fun n =>
mem_image2_of_mem (hμ.set_mem _) (hν.set_mem _), fun n => ?_, ?_⟩
· rw [prod_prod]
exact mul_lt_top (hμ.finite _).ne (hν.finite _).ne
· simp_rw [iUnion_unpair_prod, hμ.spanning, hν.spanning, univ_prod_univ]
#align measure_theory.measure.finite_spanning_sets_in.prod MeasureTheory.Measure.FiniteSpanningSetsIn.prod
lemma prod_sum_left {ι : Type*} (m : ι → Measure α) (μ : Measure β) [SFinite μ] :
(Measure.sum m).prod μ = Measure.sum (fun i ↦ (m i).prod μ) := by
ext s hs
simp only [prod_apply hs, lintegral_sum_measure, hs, sum_apply, ENNReal.tsum_prod']
#align measure_theory.measure.sum_prod MeasureTheory.Measure.prod_sum_left
lemma prod_sum_right {ι' : Type*} [Countable ι'] (m : Measure α) (m' : ι' → Measure β)
[∀ n, SFinite (m' n)] :
m.prod (Measure.sum m') = Measure.sum (fun p ↦ m.prod (m' p)) := by
ext s hs
simp only [prod_apply hs, lintegral_sum_measure, hs, sum_apply, ENNReal.tsum_prod']
have M : ∀ x, MeasurableSet (Prod.mk x ⁻¹' s) := fun x => measurable_prod_mk_left hs
simp_rw [Measure.sum_apply _ (M _)]
rw [lintegral_tsum (fun i ↦ (measurable_measure_prod_mk_left hs).aemeasurable)]
#align measure_theory.measure.prod_sum MeasureTheory.Measure.prod_sum_right
lemma prod_sum {ι ι' : Type*} [Countable ι'] (m : ι → Measure α) (m' : ι' → Measure β)
[∀ n, SFinite (m' n)] :
(Measure.sum m).prod (Measure.sum m') =
Measure.sum (fun (p : ι × ι') ↦ (m p.1).prod (m' p.2)) := by
simp_rw [prod_sum_left, prod_sum_right, sum_sum]
instance prod.instSigmaFinite {α β : Type*} {_ : MeasurableSpace α} {μ : Measure α}
[SigmaFinite μ] {_ : MeasurableSpace β} {ν : Measure β} [SigmaFinite ν] :
SigmaFinite (μ.prod ν) :=
(μ.toFiniteSpanningSetsIn.prod ν.toFiniteSpanningSetsIn).sigmaFinite
#align measure_theory.measure.prod.sigma_finite MeasureTheory.Measure.prod.instSigmaFinite
instance prod.instSFinite {α β : Type*} {_ : MeasurableSpace α} {μ : Measure α}
[SFinite μ] {_ : MeasurableSpace β} {ν : Measure β} [SFinite ν] :
SFinite (μ.prod ν) := by
have : μ.prod ν =
Measure.sum (fun (p : ℕ × ℕ) ↦ (sFiniteSeq μ p.1).prod (sFiniteSeq ν p.2)) := by
conv_lhs => rw [← sum_sFiniteSeq μ, ← sum_sFiniteSeq ν]
apply prod_sum
rw [this]
infer_instance
instance {α β} [MeasureSpace α] [SigmaFinite (volume : Measure α)]
[MeasureSpace β] [SigmaFinite (volume : Measure β)] : SigmaFinite (volume : Measure (α × β)) :=
prod.instSigmaFinite
instance {α β} [MeasureSpace α] [SFinite (volume : Measure α)]
[MeasureSpace β] [SFinite (volume : Measure β)] : SFinite (volume : Measure (α × β)) :=
prod.instSFinite
/-- A measure on a product space equals the product measure if they are equal on rectangles
with as sides sets that generate the corresponding σ-algebras. -/
theorem prod_eq_generateFrom {μ : Measure α} {ν : Measure β} {C : Set (Set α)} {D : Set (Set β)}
(hC : generateFrom C = ‹_›) (hD : generateFrom D = ‹_›) (h2C : IsPiSystem C)
(h2D : IsPiSystem D) (h3C : μ.FiniteSpanningSetsIn C) (h3D : ν.FiniteSpanningSetsIn D)
{μν : Measure (α × β)} (h₁ : ∀ s ∈ C, ∀ t ∈ D, μν (s ×ˢ t) = μ s * ν t) : μ.prod ν = μν := by
refine
(h3C.prod h3D).ext
(generateFrom_eq_prod hC hD h3C.isCountablySpanning h3D.isCountablySpanning).symm
(h2C.prod h2D) ?_
rintro _ ⟨s, hs, t, ht, rfl⟩
haveI := h3D.sigmaFinite
rw [h₁ s hs t ht, prod_prod]
#align measure_theory.measure.prod_eq_generate_from MeasureTheory.Measure.prod_eq_generateFrom
/- Note that the next theorem is not true for s-finite measures: let `μ = ν = ∞ • Leb` on `[0,1]`
(they are s-finite as countable sums of the finite Lebesgue measure), and let `μν = μ.prod ν + λ`
where `λ` is Lebesgue measure on the diagonal. Then both measures give infinite mass to rectangles
`s × t` whose sides have positive Lebesgue measure, and `0` measure when one of the sides has zero
Lebesgue measure. And yet they do not coincide, as the first one gives zero mass to the diagonal,
and the second one gives mass one.
-/
/-- A measure on a product space equals the product measure of sigma-finite measures if they are
equal on rectangles. -/
theorem prod_eq {μ : Measure α} [SigmaFinite μ] {ν : Measure β} [SigmaFinite ν]
{μν : Measure (α × β)}
(h : ∀ s t, MeasurableSet s → MeasurableSet t → μν (s ×ˢ t) = μ s * ν t) : μ.prod ν = μν :=
prod_eq_generateFrom generateFrom_measurableSet generateFrom_measurableSet
isPiSystem_measurableSet isPiSystem_measurableSet μ.toFiniteSpanningSetsIn
ν.toFiniteSpanningSetsIn fun s hs t ht => h s t hs ht
#align measure_theory.measure.prod_eq MeasureTheory.Measure.prod_eq
variable [SFinite μ]
theorem prod_swap : map Prod.swap (μ.prod ν) = ν.prod μ := by
have : sum (fun (i : ℕ × ℕ) ↦ map Prod.swap ((sFiniteSeq μ i.1).prod (sFiniteSeq ν i.2)))
= sum (fun (i : ℕ × ℕ) ↦ map Prod.swap ((sFiniteSeq μ i.2).prod (sFiniteSeq ν i.1))) := by
ext s hs
rw [sum_apply _ hs, sum_apply _ hs]
exact ((Equiv.prodComm ℕ ℕ).tsum_eq _).symm
rw [← sum_sFiniteSeq μ, ← sum_sFiniteSeq ν, prod_sum, prod_sum,
map_sum measurable_swap.aemeasurable, this]
congr 1
ext1 i
refine (prod_eq ?_).symm
intro s t hs ht
simp_rw [map_apply measurable_swap (hs.prod ht), preimage_swap_prod, prod_prod, mul_comm]
#align measure_theory.measure.prod_swap MeasureTheory.Measure.prod_swap
theorem measurePreserving_swap : MeasurePreserving Prod.swap (μ.prod ν) (ν.prod μ) :=
⟨measurable_swap, prod_swap⟩
#align measure_theory.measure.measure_preserving_swap MeasureTheory.Measure.measurePreserving_swap
theorem prod_apply_symm {s : Set (α × β)} (hs : MeasurableSet s) :
μ.prod ν s = ∫⁻ y, μ ((fun x => (x, y)) ⁻¹' s) ∂ν := by
rw [← prod_swap, map_apply measurable_swap hs, prod_apply (measurable_swap hs)]
rfl
#align measure_theory.measure.prod_apply_symm MeasureTheory.Measure.prod_apply_symm
/-- If `s ×ˢ t` is a null measurable set and `ν t ≠ 0`, then `s` is a null measurable set. -/
lemma _root_.MeasureTheory.NullMeasurableSet.left_of_prod {s : Set α} {t : Set β}
(h : NullMeasurableSet (s ×ˢ t) (μ.prod ν)) (ht : ν t ≠ 0) : NullMeasurableSet s μ := by
refine .right_of_prod ?_ ht
rw [← preimage_swap_prod]
exact h.preimage measurePreserving_swap.quasiMeasurePreserving
/-- If `Prod.fst ⁻¹' s` is a null measurable set and `ν ≠ 0`, then `s` is a null measurable set. -/
lemma _root_.MeasureTheory.NullMeasurableSet.of_preimage_fst [NeZero ν] {s : Set α}
(h : NullMeasurableSet (Prod.fst ⁻¹' s) (μ.prod ν)) : NullMeasurableSet s μ :=
.left_of_prod (by rwa [prod_univ]) (NeZero.ne _)
/-- `Prod.fst ⁻¹' s` is null measurable w.r.t. `μ.prod ν` iff `s` is null measurable w.r.t. `μ`
provided that `ν ≠ 0`. -/
lemma nullMeasurableSet_preimage_fst [NeZero ν] {s : Set α} :
NullMeasurableSet (Prod.fst ⁻¹' s) (μ.prod ν) ↔ NullMeasurableSet s μ :=
⟨.of_preimage_fst, (.preimage · quasiMeasurePreserving_fst)⟩
lemma nullMeasurable_comp_fst [NeZero ν] {f : α → γ} :
NullMeasurable (f ∘ Prod.fst) (μ.prod ν) ↔ NullMeasurable f μ :=
forall₂_congr fun s _ ↦ nullMeasurableSet_preimage_fst (s := f ⁻¹' s)
/-- The product of two non-null sets is null measurable
if and only if both of them are null measurable. -/
lemma nullMeasurableSet_prod_of_ne_zero {s : Set α} {t : Set β} (hs : μ s ≠ 0) (ht : ν t ≠ 0) :
NullMeasurableSet (s ×ˢ t) (μ.prod ν) ↔ NullMeasurableSet s μ ∧ NullMeasurableSet t ν :=
⟨fun h ↦ ⟨h.left_of_prod ht, h.right_of_prod hs⟩, fun ⟨hs, ht⟩ ↦ hs.prod ht⟩
/-- The product of two sets is null measurable
if and only if both of them are null measurable or one of them has measure zero. -/
lemma nullMeasurableSet_prod {s : Set α} {t : Set β} :
NullMeasurableSet (s ×ˢ t) (μ.prod ν) ↔
NullMeasurableSet s μ ∧ NullMeasurableSet t ν ∨ μ s = 0 ∨ ν t = 0 := by
rcases eq_or_ne (μ s) 0 with hs | hs; · simp [NullMeasurableSet.of_null, *]
rcases eq_or_ne (ν t) 0 with ht | ht; · simp [NullMeasurableSet.of_null, *]
simp [*, nullMeasurableSet_prod_of_ne_zero]
theorem prodAssoc_prod [SFinite τ] :
map MeasurableEquiv.prodAssoc ((μ.prod ν).prod τ) = μ.prod (ν.prod τ) := by
have : sum (fun (p : ℕ × ℕ × ℕ) ↦
(sFiniteSeq μ p.1).prod ((sFiniteSeq ν p.2.1).prod (sFiniteSeq τ p.2.2)))
= sum (fun (p : (ℕ × ℕ) × ℕ) ↦
(sFiniteSeq μ p.1.1).prod ((sFiniteSeq ν p.1.2).prod (sFiniteSeq τ p.2))) := by
ext s hs
rw [sum_apply _ hs, sum_apply _ hs, ← (Equiv.prodAssoc _ _ _).tsum_eq]
simp only [Equiv.prodAssoc_apply]
rw [← sum_sFiniteSeq μ, ← sum_sFiniteSeq ν, ← sum_sFiniteSeq τ, prod_sum, prod_sum,
map_sum MeasurableEquiv.prodAssoc.measurable.aemeasurable, prod_sum, prod_sum, this]
congr
ext1 i
refine (prod_eq_generateFrom generateFrom_measurableSet generateFrom_prod
isPiSystem_measurableSet isPiSystem_prod ((sFiniteSeq μ i.1.1)).toFiniteSpanningSetsIn
((sFiniteSeq ν i.1.2).toFiniteSpanningSetsIn.prod (sFiniteSeq τ i.2).toFiniteSpanningSetsIn)
?_).symm
rintro s hs _ ⟨t, ht, u, hu, rfl⟩; rw [mem_setOf_eq] at hs ht hu
simp_rw [map_apply (MeasurableEquiv.measurable _) (hs.prod (ht.prod hu)),
MeasurableEquiv.prodAssoc, MeasurableEquiv.coe_mk, Equiv.prod_assoc_preimage, prod_prod,
mul_assoc]
#align measure_theory.measure.prod_assoc_prod MeasureTheory.Measure.prodAssoc_prod
/-! ### The product of specific measures -/
theorem prod_restrict (s : Set α) (t : Set β) :
(μ.restrict s).prod (ν.restrict t) = (μ.prod ν).restrict (s ×ˢ t) := by
rw [← sum_sFiniteSeq μ, ← sum_sFiniteSeq ν, restrict_sum_of_countable, restrict_sum_of_countable,
prod_sum, prod_sum, restrict_sum_of_countable]
congr 1
ext1 i
refine prod_eq fun s' t' hs' ht' => ?_
rw [restrict_apply (hs'.prod ht'), prod_inter_prod, prod_prod, restrict_apply hs',
restrict_apply ht']
#align measure_theory.measure.prod_restrict MeasureTheory.Measure.prod_restrict
theorem restrict_prod_eq_prod_univ (s : Set α) :
(μ.restrict s).prod ν = (μ.prod ν).restrict (s ×ˢ univ) := by
have : ν = ν.restrict Set.univ := Measure.restrict_univ.symm
rw [this, Measure.prod_restrict, ← this]
#align measure_theory.measure.restrict_prod_eq_prod_univ MeasureTheory.Measure.restrict_prod_eq_prod_univ
theorem prod_dirac (y : β) : μ.prod (dirac y) = map (fun x => (x, y)) μ := by
rw [← sum_sFiniteSeq μ, prod_sum_left, map_sum measurable_prod_mk_right.aemeasurable]
congr
ext1 i
refine prod_eq fun s t hs ht => ?_
simp_rw [map_apply measurable_prod_mk_right (hs.prod ht), mk_preimage_prod_left_eq_if, measure_if,
dirac_apply' _ ht, ← indicator_mul_right _ fun _ => sFiniteSeq μ i s, Pi.one_apply, mul_one]
#align measure_theory.measure.prod_dirac MeasureTheory.Measure.prod_dirac
| Mathlib/MeasureTheory/Constructions/Prod/Basic.lean | 776 | 782 | theorem dirac_prod (x : α) : (dirac x).prod ν = map (Prod.mk x) ν := by |
rw [← sum_sFiniteSeq ν, prod_sum_right, map_sum measurable_prod_mk_left.aemeasurable]
congr
ext1 i
refine prod_eq fun s t hs ht => ?_
simp_rw [map_apply measurable_prod_mk_left (hs.prod ht), mk_preimage_prod_right_eq_if, measure_if,
dirac_apply' _ hs, ← indicator_mul_left _ _ fun _ => sFiniteSeq ν i t, Pi.one_apply, one_mul]
|
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Sébastien Gouëzel
-/
import Mathlib.Analysis.Normed.Group.Hom
import Mathlib.Analysis.SpecialFunctions.Pow.Continuity
import Mathlib.Data.Set.Image
import Mathlib.MeasureTheory.Function.LpSeminorm.ChebyshevMarkov
import Mathlib.MeasureTheory.Function.LpSeminorm.CompareExp
import Mathlib.MeasureTheory.Function.LpSeminorm.TriangleInequality
import Mathlib.MeasureTheory.Measure.OpenPos
import Mathlib.Topology.ContinuousFunction.Compact
import Mathlib.Order.Filter.IndicatorFunction
#align_import measure_theory.function.lp_space from "leanprover-community/mathlib"@"c4015acc0a223449d44061e27ddac1835a3852b9"
/-!
# Lp space
This file provides the space `Lp E p μ` as the subtype of elements of `α →ₘ[μ] E` (see ae_eq_fun)
such that `snorm f p μ` is finite. For `1 ≤ p`, `snorm` defines a norm and `Lp` is a complete metric
space.
## Main definitions
* `Lp E p μ` : elements of `α →ₘ[μ] E` (see ae_eq_fun) such that `snorm f p μ` is finite. Defined
as an `AddSubgroup` of `α →ₘ[μ] E`.
Lipschitz functions vanishing at zero act by composition on `Lp`. We define this action, and prove
that it is continuous. In particular,
* `ContinuousLinearMap.compLp` defines the action on `Lp` of a continuous linear map.
* `Lp.posPart` is the positive part of an `Lp` function.
* `Lp.negPart` is the negative part of an `Lp` function.
When `α` is a topological space equipped with a finite Borel measure, there is a bounded linear map
from the normed space of bounded continuous functions (`α →ᵇ E`) to `Lp E p μ`. We construct this
as `BoundedContinuousFunction.toLp`.
## Notations
* `α →₁[μ] E` : the type `Lp E 1 μ`.
* `α →₂[μ] E` : the type `Lp E 2 μ`.
## Implementation
Since `Lp` is defined as an `AddSubgroup`, dot notation does not work. Use `Lp.Measurable f` to
say that the coercion of `f` to a genuine function is measurable, instead of the non-working
`f.Measurable`.
To prove that two `Lp` elements are equal, it suffices to show that their coercions to functions
coincide almost everywhere (this is registered as an `ext` rule). This can often be done using
`filter_upwards`. For instance, a proof from first principles that `f + (g + h) = (f + g) + h`
could read (in the `Lp` namespace)
```
example (f g h : Lp E p μ) : (f + g) + h = f + (g + h) := by
ext1
filter_upwards [coeFn_add (f + g) h, coeFn_add f g, coeFn_add f (g + h), coeFn_add g h]
with _ ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, add_assoc]
```
The lemma `coeFn_add` states that the coercion of `f + g` coincides almost everywhere with the sum
of the coercions of `f` and `g`. All such lemmas use `coeFn` in their name, to distinguish the
function coercion from the coercion to almost everywhere defined functions.
-/
noncomputable section
set_option linter.uppercaseLean3 false
open TopologicalSpace MeasureTheory Filter
open scoped NNReal ENNReal Topology MeasureTheory Uniformity
variable {α E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G]
namespace MeasureTheory
/-!
### Lp space
The space of equivalence classes of measurable functions for which `snorm f p μ < ∞`.
-/
@[simp]
theorem snorm_aeeqFun {α E : Type*} [MeasurableSpace α] {μ : Measure α} [NormedAddCommGroup E]
{p : ℝ≥0∞} {f : α → E} (hf : AEStronglyMeasurable f μ) :
snorm (AEEqFun.mk f hf) p μ = snorm f p μ :=
snorm_congr_ae (AEEqFun.coeFn_mk _ _)
#align measure_theory.snorm_ae_eq_fun MeasureTheory.snorm_aeeqFun
theorem Memℒp.snorm_mk_lt_top {α E : Type*} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] {p : ℝ≥0∞} {f : α → E} (hfp : Memℒp f p μ) :
snorm (AEEqFun.mk f hfp.1) p μ < ∞ := by simp [hfp.2]
#align measure_theory.mem_ℒp.snorm_mk_lt_top MeasureTheory.Memℒp.snorm_mk_lt_top
/-- Lp space -/
def Lp {α} (E : Type*) {m : MeasurableSpace α} [NormedAddCommGroup E] (p : ℝ≥0∞)
(μ : Measure α := by volume_tac) : AddSubgroup (α →ₘ[μ] E) where
carrier := { f | snorm f p μ < ∞ }
zero_mem' := by simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
add_mem' {f g} hf hg := by
simp [snorm_congr_ae (AEEqFun.coeFn_add f g),
snorm_add_lt_top ⟨f.aestronglyMeasurable, hf⟩ ⟨g.aestronglyMeasurable, hg⟩]
neg_mem' {f} hf := by rwa [Set.mem_setOf_eq, snorm_congr_ae (AEEqFun.coeFn_neg f), snorm_neg]
#align measure_theory.Lp MeasureTheory.Lp
-- Porting note: calling the first argument `α` breaks the `(α := ·)` notation
scoped notation:25 α' " →₁[" μ "] " E => MeasureTheory.Lp (α := α') E 1 μ
scoped notation:25 α' " →₂[" μ "] " E => MeasureTheory.Lp (α := α') E 2 μ
namespace Memℒp
/-- make an element of Lp from a function verifying `Memℒp` -/
def toLp (f : α → E) (h_mem_ℒp : Memℒp f p μ) : Lp E p μ :=
⟨AEEqFun.mk f h_mem_ℒp.1, h_mem_ℒp.snorm_mk_lt_top⟩
#align measure_theory.mem_ℒp.to_Lp MeasureTheory.Memℒp.toLp
theorem coeFn_toLp {f : α → E} (hf : Memℒp f p μ) : hf.toLp f =ᵐ[μ] f :=
AEEqFun.coeFn_mk _ _
#align measure_theory.mem_ℒp.coe_fn_to_Lp MeasureTheory.Memℒp.coeFn_toLp
theorem toLp_congr {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) (hfg : f =ᵐ[μ] g) :
hf.toLp f = hg.toLp g := by simp [toLp, hfg]
#align measure_theory.mem_ℒp.to_Lp_congr MeasureTheory.Memℒp.toLp_congr
@[simp]
theorem toLp_eq_toLp_iff {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
hf.toLp f = hg.toLp g ↔ f =ᵐ[μ] g := by simp [toLp]
#align measure_theory.mem_ℒp.to_Lp_eq_to_Lp_iff MeasureTheory.Memℒp.toLp_eq_toLp_iff
@[simp]
theorem toLp_zero (h : Memℒp (0 : α → E) p μ) : h.toLp 0 = 0 :=
rfl
#align measure_theory.mem_ℒp.to_Lp_zero MeasureTheory.Memℒp.toLp_zero
theorem toLp_add {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.add hg).toLp (f + g) = hf.toLp f + hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_add MeasureTheory.Memℒp.toLp_add
theorem toLp_neg {f : α → E} (hf : Memℒp f p μ) : hf.neg.toLp (-f) = -hf.toLp f :=
rfl
#align measure_theory.mem_ℒp.to_Lp_neg MeasureTheory.Memℒp.toLp_neg
theorem toLp_sub {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.sub hg).toLp (f - g) = hf.toLp f - hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_sub MeasureTheory.Memℒp.toLp_sub
end Memℒp
namespace Lp
instance instCoeFun : CoeFun (Lp E p μ) (fun _ => α → E) :=
⟨fun f => ((f : α →ₘ[μ] E) : α → E)⟩
#align measure_theory.Lp.has_coe_to_fun MeasureTheory.Lp.instCoeFun
@[ext high]
theorem ext {f g : Lp E p μ} (h : f =ᵐ[μ] g) : f = g := by
cases f
cases g
simp only [Subtype.mk_eq_mk]
exact AEEqFun.ext h
#align measure_theory.Lp.ext MeasureTheory.Lp.ext
theorem ext_iff {f g : Lp E p μ} : f = g ↔ f =ᵐ[μ] g :=
⟨fun h => by rw [h], fun h => ext h⟩
#align measure_theory.Lp.ext_iff MeasureTheory.Lp.ext_iff
theorem mem_Lp_iff_snorm_lt_top {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ snorm f p μ < ∞ := Iff.rfl
#align measure_theory.Lp.mem_Lp_iff_snorm_lt_top MeasureTheory.Lp.mem_Lp_iff_snorm_lt_top
theorem mem_Lp_iff_memℒp {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ Memℒp f p μ := by
simp [mem_Lp_iff_snorm_lt_top, Memℒp, f.stronglyMeasurable.aestronglyMeasurable]
#align measure_theory.Lp.mem_Lp_iff_mem_ℒp MeasureTheory.Lp.mem_Lp_iff_memℒp
protected theorem antitone [IsFiniteMeasure μ] {p q : ℝ≥0∞} (hpq : p ≤ q) : Lp E q μ ≤ Lp E p μ :=
fun f hf => (Memℒp.memℒp_of_exponent_le ⟨f.aestronglyMeasurable, hf⟩ hpq).2
#align measure_theory.Lp.antitone MeasureTheory.Lp.antitone
@[simp]
theorem coeFn_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α → E) = f :=
rfl
#align measure_theory.Lp.coe_fn_mk MeasureTheory.Lp.coeFn_mk
-- @[simp] -- Porting note (#10685): dsimp can prove this
theorem coe_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α →ₘ[μ] E) = f :=
rfl
#align measure_theory.Lp.coe_mk MeasureTheory.Lp.coe_mk
@[simp]
theorem toLp_coeFn (f : Lp E p μ) (hf : Memℒp f p μ) : hf.toLp f = f := by
cases f
simp [Memℒp.toLp]
#align measure_theory.Lp.to_Lp_coe_fn MeasureTheory.Lp.toLp_coeFn
theorem snorm_lt_top (f : Lp E p μ) : snorm f p μ < ∞ :=
f.prop
#align measure_theory.Lp.snorm_lt_top MeasureTheory.Lp.snorm_lt_top
theorem snorm_ne_top (f : Lp E p μ) : snorm f p μ ≠ ∞ :=
(snorm_lt_top f).ne
#align measure_theory.Lp.snorm_ne_top MeasureTheory.Lp.snorm_ne_top
@[measurability]
protected theorem stronglyMeasurable (f : Lp E p μ) : StronglyMeasurable f :=
f.val.stronglyMeasurable
#align measure_theory.Lp.strongly_measurable MeasureTheory.Lp.stronglyMeasurable
@[measurability]
protected theorem aestronglyMeasurable (f : Lp E p μ) : AEStronglyMeasurable f μ :=
f.val.aestronglyMeasurable
#align measure_theory.Lp.ae_strongly_measurable MeasureTheory.Lp.aestronglyMeasurable
protected theorem memℒp (f : Lp E p μ) : Memℒp f p μ :=
⟨Lp.aestronglyMeasurable f, f.prop⟩
#align measure_theory.Lp.mem_ℒp MeasureTheory.Lp.memℒp
variable (E p μ)
theorem coeFn_zero : ⇑(0 : Lp E p μ) =ᵐ[μ] 0 :=
AEEqFun.coeFn_zero
#align measure_theory.Lp.coe_fn_zero MeasureTheory.Lp.coeFn_zero
variable {E p μ}
theorem coeFn_neg (f : Lp E p μ) : ⇑(-f) =ᵐ[μ] -f :=
AEEqFun.coeFn_neg _
#align measure_theory.Lp.coe_fn_neg MeasureTheory.Lp.coeFn_neg
theorem coeFn_add (f g : Lp E p μ) : ⇑(f + g) =ᵐ[μ] f + g :=
AEEqFun.coeFn_add _ _
#align measure_theory.Lp.coe_fn_add MeasureTheory.Lp.coeFn_add
theorem coeFn_sub (f g : Lp E p μ) : ⇑(f - g) =ᵐ[μ] f - g :=
AEEqFun.coeFn_sub _ _
#align measure_theory.Lp.coe_fn_sub MeasureTheory.Lp.coeFn_sub
theorem const_mem_Lp (α) {_ : MeasurableSpace α} (μ : Measure α) (c : E) [IsFiniteMeasure μ] :
@AEEqFun.const α _ _ μ _ c ∈ Lp E p μ :=
(memℒp_const c).snorm_mk_lt_top
#align measure_theory.Lp.mem_Lp_const MeasureTheory.Lp.const_mem_Lp
instance instNorm : Norm (Lp E p μ) where norm f := ENNReal.toReal (snorm f p μ)
#align measure_theory.Lp.has_norm MeasureTheory.Lp.instNorm
-- note: we need this to be defeq to the instance from `SeminormedAddGroup.toNNNorm`, so
-- can't use `ENNReal.toNNReal (snorm f p μ)`
instance instNNNorm : NNNorm (Lp E p μ) where nnnorm f := ⟨‖f‖, ENNReal.toReal_nonneg⟩
#align measure_theory.Lp.has_nnnorm MeasureTheory.Lp.instNNNorm
instance instDist : Dist (Lp E p μ) where dist f g := ‖f - g‖
#align measure_theory.Lp.has_dist MeasureTheory.Lp.instDist
instance instEDist : EDist (Lp E p μ) where edist f g := snorm (⇑f - ⇑g) p μ
#align measure_theory.Lp.has_edist MeasureTheory.Lp.instEDist
theorem norm_def (f : Lp E p μ) : ‖f‖ = ENNReal.toReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.norm_def MeasureTheory.Lp.norm_def
theorem nnnorm_def (f : Lp E p μ) : ‖f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.nnnorm_def MeasureTheory.Lp.nnnorm_def
@[simp, norm_cast]
protected theorem coe_nnnorm (f : Lp E p μ) : (‖f‖₊ : ℝ) = ‖f‖ :=
rfl
#align measure_theory.Lp.coe_nnnorm MeasureTheory.Lp.coe_nnnorm
@[simp, norm_cast]
theorem nnnorm_coe_ennreal (f : Lp E p μ) : (‖f‖₊ : ℝ≥0∞) = snorm f p μ :=
ENNReal.coe_toNNReal <| Lp.snorm_ne_top f
@[simp]
theorem norm_toLp (f : α → E) (hf : Memℒp f p μ) : ‖hf.toLp f‖ = ENNReal.toReal (snorm f p μ) := by
erw [norm_def, snorm_congr_ae (Memℒp.coeFn_toLp hf)]
#align measure_theory.Lp.norm_to_Lp MeasureTheory.Lp.norm_toLp
@[simp]
theorem nnnorm_toLp (f : α → E) (hf : Memℒp f p μ) :
‖hf.toLp f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
NNReal.eq <| norm_toLp f hf
#align measure_theory.Lp.nnnorm_to_Lp MeasureTheory.Lp.nnnorm_toLp
theorem coe_nnnorm_toLp {f : α → E} (hf : Memℒp f p μ) : (‖hf.toLp f‖₊ : ℝ≥0∞) = snorm f p μ := by
rw [nnnorm_toLp f hf, ENNReal.coe_toNNReal hf.2.ne]
theorem dist_def (f g : Lp E p μ) : dist f g = (snorm (⇑f - ⇑g) p μ).toReal := by
simp_rw [dist, norm_def]
refine congr_arg _ ?_
apply snorm_congr_ae (coeFn_sub _ _)
#align measure_theory.Lp.dist_def MeasureTheory.Lp.dist_def
theorem edist_def (f g : Lp E p μ) : edist f g = snorm (⇑f - ⇑g) p μ :=
rfl
#align measure_theory.Lp.edist_def MeasureTheory.Lp.edist_def
protected theorem edist_dist (f g : Lp E p μ) : edist f g = .ofReal (dist f g) := by
rw [edist_def, dist_def, ← snorm_congr_ae (coeFn_sub _ _),
ENNReal.ofReal_toReal (snorm_ne_top (f - g))]
protected theorem dist_edist (f g : Lp E p μ) : dist f g = (edist f g).toReal :=
MeasureTheory.Lp.dist_def ..
theorem dist_eq_norm (f g : Lp E p μ) : dist f g = ‖f - g‖ := rfl
@[simp]
theorem edist_toLp_toLp (f g : α → E) (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
edist (hf.toLp f) (hg.toLp g) = snorm (f - g) p μ := by
rw [edist_def]
exact snorm_congr_ae (hf.coeFn_toLp.sub hg.coeFn_toLp)
#align measure_theory.Lp.edist_to_Lp_to_Lp MeasureTheory.Lp.edist_toLp_toLp
@[simp]
theorem edist_toLp_zero (f : α → E) (hf : Memℒp f p μ) : edist (hf.toLp f) 0 = snorm f p μ := by
convert edist_toLp_toLp f 0 hf zero_memℒp
simp
#align measure_theory.Lp.edist_to_Lp_zero MeasureTheory.Lp.edist_toLp_zero
@[simp]
| Mathlib/MeasureTheory/Function/LpSpace.lean | 326 | 329 | theorem nnnorm_zero : ‖(0 : Lp E p μ)‖₊ = 0 := by |
rw [nnnorm_def]
change (snorm (⇑(0 : α →ₘ[μ] E)) p μ).toNNReal = 0
simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
|
/-
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.Group.Subgroup.Basic
import Mathlib.Data.Fintype.Basic
import Mathlib.Data.List.Sublists
import Mathlib.Data.List.InsertNth
#align_import group_theory.free_group from "leanprover-community/mathlib"@"f93c11933efbc3c2f0299e47b8ff83e9b539cbf6"
/-!
# Free groups
This file defines free groups over a type. Furthermore, it is shown that the free group construction
is an instance of a monad. For the result that `FreeGroup` is the left adjoint to the forgetful
functor from groups to types, see `Algebra/Category/Group/Adjunctions`.
## Main definitions
* `FreeGroup`/`FreeAddGroup`: the free group (resp. free additive group) associated to a type
`α` defined as the words over `a : α × Bool` modulo the relation `a * x * x⁻¹ * b = a * b`.
* `FreeGroup.mk`/`FreeAddGroup.mk`: the canonical quotient map `List (α × Bool) → FreeGroup α`.
* `FreeGroup.of`/`FreeAddGroup.of`: the canonical injection `α → FreeGroup α`.
* `FreeGroup.lift f`/`FreeAddGroup.lift`: the canonical group homomorphism `FreeGroup α →* G`
given a group `G` and a function `f : α → G`.
## Main statements
* `FreeGroup.Red.church_rosser`/`FreeAddGroup.Red.church_rosser`: The Church-Rosser theorem for word
reduction (also known as Newman's diamond lemma).
* `FreeGroup.freeGroupUnitEquivInt`: The free group over the one-point type
is isomorphic to the integers.
* The free group construction is an instance of a monad.
## Implementation details
First we introduce the one step reduction relation `FreeGroup.Red.Step`:
`w * x * x⁻¹ * v ~> w * v`, its reflexive transitive closure `FreeGroup.Red.trans`
and prove that its join is an equivalence relation. Then we introduce `FreeGroup α` as a quotient
over `FreeGroup.Red.Step`.
For the additive version we introduce the same relation under a different name so that we can
distinguish the quotient types more easily.
## Tags
free group, Newman's diamond lemma, Church-Rosser theorem
-/
open Relation
universe u v w
variable {α : Type u}
attribute [local simp] List.append_eq_has_append
-- Porting note: to_additive.map_namespace is not supported yet
-- worked around it by putting a few extra manual mappings (but not too many all in all)
-- run_cmd to_additive.map_namespace `FreeGroup `FreeAddGroup
/-- Reduction step for the additive free group relation: `w + x + (-x) + v ~> w + v` -/
inductive FreeAddGroup.Red.Step : List (α × Bool) → List (α × Bool) → Prop
| not {L₁ L₂ x b} : FreeAddGroup.Red.Step (L₁ ++ (x, b) :: (x, not b) :: L₂) (L₁ ++ L₂)
#align free_add_group.red.step FreeAddGroup.Red.Step
attribute [simp] FreeAddGroup.Red.Step.not
/-- Reduction step for the multiplicative free group relation: `w * x * x⁻¹ * v ~> w * v` -/
@[to_additive FreeAddGroup.Red.Step]
inductive FreeGroup.Red.Step : List (α × Bool) → List (α × Bool) → Prop
| not {L₁ L₂ x b} : FreeGroup.Red.Step (L₁ ++ (x, b) :: (x, not b) :: L₂) (L₁ ++ L₂)
#align free_group.red.step FreeGroup.Red.Step
attribute [simp] FreeGroup.Red.Step.not
namespace FreeGroup
variable {L L₁ L₂ L₃ L₄ : List (α × Bool)}
/-- Reflexive-transitive closure of `Red.Step` -/
@[to_additive FreeAddGroup.Red "Reflexive-transitive closure of `Red.Step`"]
def Red : List (α × Bool) → List (α × Bool) → Prop :=
ReflTransGen Red.Step
#align free_group.red FreeGroup.Red
#align free_add_group.red FreeAddGroup.Red
@[to_additive (attr := refl)]
theorem Red.refl : Red L L :=
ReflTransGen.refl
#align free_group.red.refl FreeGroup.Red.refl
#align free_add_group.red.refl FreeAddGroup.Red.refl
@[to_additive (attr := trans)]
theorem Red.trans : Red L₁ L₂ → Red L₂ L₃ → Red L₁ L₃ :=
ReflTransGen.trans
#align free_group.red.trans FreeGroup.Red.trans
#align free_add_group.red.trans FreeAddGroup.Red.trans
namespace Red
/-- Predicate asserting that the word `w₁` can be reduced to `w₂` in one step, i.e. there are words
`w₃ w₄` and letter `x` such that `w₁ = w₃xx⁻¹w₄` and `w₂ = w₃w₄` -/
@[to_additive "Predicate asserting that the word `w₁` can be reduced to `w₂` in one step, i.e. there
are words `w₃ w₄` and letter `x` such that `w₁ = w₃ + x + (-x) + w₄` and `w₂ = w₃w₄`"]
theorem Step.length : ∀ {L₁ L₂ : List (α × Bool)}, Step L₁ L₂ → L₂.length + 2 = L₁.length
| _, _, @Red.Step.not _ L1 L2 x b => by rw [List.length_append, List.length_append]; rfl
#align free_group.red.step.length FreeGroup.Red.Step.length
#align free_add_group.red.step.length FreeAddGroup.Red.Step.length
@[to_additive (attr := simp)]
theorem Step.not_rev {x b} : Step (L₁ ++ (x, !b) :: (x, b) :: L₂) (L₁ ++ L₂) := by
cases b <;> exact Step.not
#align free_group.red.step.bnot_rev FreeGroup.Red.Step.not_rev
#align free_add_group.red.step.bnot_rev FreeAddGroup.Red.Step.not_rev
@[to_additive (attr := simp)]
theorem Step.cons_not {x b} : Red.Step ((x, b) :: (x, !b) :: L) L :=
@Step.not _ [] _ _ _
#align free_group.red.step.cons_bnot FreeGroup.Red.Step.cons_not
#align free_add_group.red.step.cons_bnot FreeAddGroup.Red.Step.cons_not
@[to_additive (attr := simp)]
theorem Step.cons_not_rev {x b} : Red.Step ((x, !b) :: (x, b) :: L) L :=
@Red.Step.not_rev _ [] _ _ _
#align free_group.red.step.cons_bnot_rev FreeGroup.Red.Step.cons_not_rev
#align free_add_group.red.step.cons_bnot_rev FreeAddGroup.Red.Step.cons_not_rev
@[to_additive]
theorem Step.append_left : ∀ {L₁ L₂ L₃ : List (α × Bool)}, Step L₂ L₃ → Step (L₁ ++ L₂) (L₁ ++ L₃)
| _, _, _, Red.Step.not => by rw [← List.append_assoc, ← List.append_assoc]; constructor
#align free_group.red.step.append_left FreeGroup.Red.Step.append_left
#align free_add_group.red.step.append_left FreeAddGroup.Red.Step.append_left
@[to_additive]
theorem Step.cons {x} (H : Red.Step L₁ L₂) : Red.Step (x :: L₁) (x :: L₂) :=
@Step.append_left _ [x] _ _ H
#align free_group.red.step.cons FreeGroup.Red.Step.cons
#align free_add_group.red.step.cons FreeAddGroup.Red.Step.cons
@[to_additive]
theorem Step.append_right : ∀ {L₁ L₂ L₃ : List (α × Bool)}, Step L₁ L₂ → Step (L₁ ++ L₃) (L₂ ++ L₃)
| _, _, _, Red.Step.not => by simp
#align free_group.red.step.append_right FreeGroup.Red.Step.append_right
#align free_add_group.red.step.append_right FreeAddGroup.Red.Step.append_right
@[to_additive]
theorem not_step_nil : ¬Step [] L := by
generalize h' : [] = L'
intro h
cases' h with L₁ L₂
simp [List.nil_eq_append] at h'
#align free_group.red.not_step_nil FreeGroup.Red.not_step_nil
#align free_add_group.red.not_step_nil FreeAddGroup.Red.not_step_nil
@[to_additive]
theorem Step.cons_left_iff {a : α} {b : Bool} :
Step ((a, b) :: L₁) L₂ ↔ (∃ L, Step L₁ L ∧ L₂ = (a, b) :: L) ∨ L₁ = (a, ! b) :: L₂ := by
constructor
· generalize hL : ((a, b) :: L₁ : List _) = L
rintro @⟨_ | ⟨p, s'⟩, e, a', b'⟩
· simp at hL
simp [*]
· simp at hL
rcases hL with ⟨rfl, rfl⟩
refine Or.inl ⟨s' ++ e, Step.not, ?_⟩
simp
· rintro (⟨L, h, rfl⟩ | rfl)
· exact Step.cons h
· exact Step.cons_not
#align free_group.red.step.cons_left_iff FreeGroup.Red.Step.cons_left_iff
#align free_add_group.red.step.cons_left_iff FreeAddGroup.Red.Step.cons_left_iff
@[to_additive]
theorem not_step_singleton : ∀ {p : α × Bool}, ¬Step [p] L
| (a, b) => by simp [Step.cons_left_iff, not_step_nil]
#align free_group.red.not_step_singleton FreeGroup.Red.not_step_singleton
#align free_add_group.red.not_step_singleton FreeAddGroup.Red.not_step_singleton
@[to_additive]
theorem Step.cons_cons_iff : ∀ {p : α × Bool}, Step (p :: L₁) (p :: L₂) ↔ Step L₁ L₂ := by
simp (config := { contextual := true }) [Step.cons_left_iff, iff_def, or_imp]
#align free_group.red.step.cons_cons_iff FreeGroup.Red.Step.cons_cons_iff
#align free_add_group.red.step.cons_cons_iff FreeAddGroup.Red.Step.cons_cons_iff
@[to_additive]
theorem Step.append_left_iff : ∀ L, Step (L ++ L₁) (L ++ L₂) ↔ Step L₁ L₂
| [] => by simp
| p :: l => by simp [Step.append_left_iff l, Step.cons_cons_iff]
#align free_group.red.step.append_left_iff FreeGroup.Red.Step.append_left_iff
#align free_add_group.red.step.append_left_iff FreeAddGroup.Red.Step.append_left_iff
@[to_additive]
theorem Step.diamond_aux :
∀ {L₁ L₂ L₃ L₄ : List (α × Bool)} {x1 b1 x2 b2},
L₁ ++ (x1, b1) :: (x1, !b1) :: L₂ = L₃ ++ (x2, b2) :: (x2, !b2) :: L₄ →
L₁ ++ L₂ = L₃ ++ L₄ ∨ ∃ L₅, Red.Step (L₁ ++ L₂) L₅ ∧ Red.Step (L₃ ++ L₄) L₅
| [], _, [], _, _, _, _, _, H => by injections; subst_vars; simp
| [], _, [(x3, b3)], _, _, _, _, _, H => by injections; subst_vars; simp
| [(x3, b3)], _, [], _, _, _, _, _, H => by injections; subst_vars; simp
| [], _, (x3, b3) :: (x4, b4) :: tl, _, _, _, _, _, H => by
injections; subst_vars; simp; right; exact ⟨_, Red.Step.not, Red.Step.cons_not⟩
| (x3, b3) :: (x4, b4) :: tl, _, [], _, _, _, _, _, H => by
injections; subst_vars; simp; right; exact ⟨_, Red.Step.cons_not, Red.Step.not⟩
| (x3, b3) :: tl, _, (x4, b4) :: tl2, _, _, _, _, _, H =>
let ⟨H1, H2⟩ := List.cons.inj H
match Step.diamond_aux H2 with
| Or.inl H3 => Or.inl <| by simp [H1, H3]
| Or.inr ⟨L₅, H3, H4⟩ => Or.inr ⟨_, Step.cons H3, by simpa [H1] using Step.cons H4⟩
#align free_group.red.step.diamond_aux FreeGroup.Red.Step.diamond_aux
#align free_add_group.red.step.diamond_aux FreeAddGroup.Red.Step.diamond_aux
@[to_additive]
theorem Step.diamond :
∀ {L₁ L₂ L₃ L₄ : List (α × Bool)},
Red.Step L₁ L₃ → Red.Step L₂ L₄ → L₁ = L₂ → L₃ = L₄ ∨ ∃ L₅, Red.Step L₃ L₅ ∧ Red.Step L₄ L₅
| _, _, _, _, Red.Step.not, Red.Step.not, H => Step.diamond_aux H
#align free_group.red.step.diamond FreeGroup.Red.Step.diamond
#align free_add_group.red.step.diamond FreeAddGroup.Red.Step.diamond
@[to_additive]
theorem Step.to_red : Step L₁ L₂ → Red L₁ L₂ :=
ReflTransGen.single
#align free_group.red.step.to_red FreeGroup.Red.Step.to_red
#align free_add_group.red.step.to_red FreeAddGroup.Red.Step.to_red
/-- **Church-Rosser theorem** for word reduction: If `w1 w2 w3` are words such that `w1` reduces
to `w2` and `w3` respectively, then there is a word `w4` such that `w2` and `w3` reduce to `w4`
respectively. This is also known as Newman's diamond lemma. -/
@[to_additive
"**Church-Rosser theorem** for word reduction: If `w1 w2 w3` are words such that `w1` reduces
to `w2` and `w3` respectively, then there is a word `w4` such that `w2` and `w3` reduce to `w4`
respectively. This is also known as Newman's diamond lemma."]
theorem church_rosser : Red L₁ L₂ → Red L₁ L₃ → Join Red L₂ L₃ :=
Relation.church_rosser fun a b c hab hac =>
match b, c, Red.Step.diamond hab hac rfl with
| b, _, Or.inl rfl => ⟨b, by rfl, by rfl⟩
| b, c, Or.inr ⟨d, hbd, hcd⟩ => ⟨d, ReflGen.single hbd, hcd.to_red⟩
#align free_group.red.church_rosser FreeGroup.Red.church_rosser
#align free_add_group.red.church_rosser FreeAddGroup.Red.church_rosser
@[to_additive]
theorem cons_cons {p} : Red L₁ L₂ → Red (p :: L₁) (p :: L₂) :=
ReflTransGen.lift (List.cons p) fun _ _ => Step.cons
#align free_group.red.cons_cons FreeGroup.Red.cons_cons
#align free_add_group.red.cons_cons FreeAddGroup.Red.cons_cons
@[to_additive]
theorem cons_cons_iff (p) : Red (p :: L₁) (p :: L₂) ↔ Red L₁ L₂ :=
Iff.intro
(by
generalize eq₁ : (p :: L₁ : List _) = LL₁
generalize eq₂ : (p :: L₂ : List _) = LL₂
intro h
induction' h using Relation.ReflTransGen.head_induction_on
with L₁ L₂ h₁₂ h ih
generalizing L₁ L₂
· subst_vars
cases eq₂
constructor
· subst_vars
cases' p with a b
rw [Step.cons_left_iff] at h₁₂
rcases h₁₂ with (⟨L, h₁₂, rfl⟩ | rfl)
· exact (ih rfl rfl).head h₁₂
· exact (cons_cons h).tail Step.cons_not_rev)
cons_cons
#align free_group.red.cons_cons_iff FreeGroup.Red.cons_cons_iff
#align free_add_group.red.cons_cons_iff FreeAddGroup.Red.cons_cons_iff
@[to_additive]
theorem append_append_left_iff : ∀ L, Red (L ++ L₁) (L ++ L₂) ↔ Red L₁ L₂
| [] => Iff.rfl
| p :: L => by simp [append_append_left_iff L, cons_cons_iff]
#align free_group.red.append_append_left_iff FreeGroup.Red.append_append_left_iff
#align free_add_group.red.append_append_left_iff FreeAddGroup.Red.append_append_left_iff
@[to_additive]
theorem append_append (h₁ : Red L₁ L₃) (h₂ : Red L₂ L₄) : Red (L₁ ++ L₂) (L₃ ++ L₄) :=
(h₁.lift (fun L => L ++ L₂) fun _ _ => Step.append_right).trans ((append_append_left_iff _).2 h₂)
#align free_group.red.append_append FreeGroup.Red.append_append
#align free_add_group.red.append_append FreeAddGroup.Red.append_append
@[to_additive]
theorem to_append_iff : Red L (L₁ ++ L₂) ↔ ∃ L₃ L₄, L = L₃ ++ L₄ ∧ Red L₃ L₁ ∧ Red L₄ L₂ :=
Iff.intro
(by
generalize eq : L₁ ++ L₂ = L₁₂
intro h
induction' h with L' L₁₂ hLL' h ih generalizing L₁ L₂
· exact ⟨_, _, eq.symm, by rfl, by rfl⟩
· cases' h with s e a b
rcases List.append_eq_append_iff.1 eq with (⟨s', rfl, rfl⟩ | ⟨e', rfl, rfl⟩)
· have : L₁ ++ (s' ++ (a, b) :: (a, not b) :: e) = L₁ ++ s' ++ (a, b) :: (a, not b) :: e :=
by simp
rcases ih this with ⟨w₁, w₂, rfl, h₁, h₂⟩
exact ⟨w₁, w₂, rfl, h₁, h₂.tail Step.not⟩
· have : s ++ (a, b) :: (a, not b) :: e' ++ L₂ = s ++ (a, b) :: (a, not b) :: (e' ++ L₂) :=
by simp
rcases ih this with ⟨w₁, w₂, rfl, h₁, h₂⟩
exact ⟨w₁, w₂, rfl, h₁.tail Step.not, h₂⟩)
fun ⟨L₃, L₄, Eq, h₃, h₄⟩ => Eq.symm ▸ append_append h₃ h₄
#align free_group.red.to_append_iff FreeGroup.Red.to_append_iff
#align free_add_group.red.to_append_iff FreeAddGroup.Red.to_append_iff
/-- The empty word `[]` only reduces to itself. -/
@[to_additive "The empty word `[]` only reduces to itself."]
theorem nil_iff : Red [] L ↔ L = [] :=
reflTransGen_iff_eq fun _ => Red.not_step_nil
#align free_group.red.nil_iff FreeGroup.Red.nil_iff
#align free_add_group.red.nil_iff FreeAddGroup.Red.nil_iff
/-- A letter only reduces to itself. -/
@[to_additive "A letter only reduces to itself."]
theorem singleton_iff {x} : Red [x] L₁ ↔ L₁ = [x] :=
reflTransGen_iff_eq fun _ => not_step_singleton
#align free_group.red.singleton_iff FreeGroup.Red.singleton_iff
#align free_add_group.red.singleton_iff FreeAddGroup.Red.singleton_iff
/-- If `x` is a letter and `w` is a word such that `xw` reduces to the empty word, then `w` reduces
to `x⁻¹` -/
@[to_additive
"If `x` is a letter and `w` is a word such that `x + w` reduces to the empty word, then `w`
reduces to `-x`."]
theorem cons_nil_iff_singleton {x b} : Red ((x, b) :: L) [] ↔ Red L [(x, not b)] :=
Iff.intro
(fun h => by
have h₁ : Red ((x, not b) :: (x, b) :: L) [(x, not b)] := cons_cons h
have h₂ : Red ((x, not b) :: (x, b) :: L) L := ReflTransGen.single Step.cons_not_rev
let ⟨L', h₁, h₂⟩ := church_rosser h₁ h₂
rw [singleton_iff] at h₁
subst L'
assumption)
fun h => (cons_cons h).tail Step.cons_not
#align free_group.red.cons_nil_iff_singleton FreeGroup.Red.cons_nil_iff_singleton
#align free_add_group.red.cons_nil_iff_singleton FreeAddGroup.Red.cons_nil_iff_singleton
@[to_additive]
theorem red_iff_irreducible {x1 b1 x2 b2} (h : (x1, b1) ≠ (x2, b2)) :
Red [(x1, !b1), (x2, b2)] L ↔ L = [(x1, !b1), (x2, b2)] := by
apply reflTransGen_iff_eq
generalize eq : [(x1, not b1), (x2, b2)] = L'
intro L h'
cases h'
simp [List.cons_eq_append, List.nil_eq_append] at eq
rcases eq with ⟨rfl, ⟨rfl, rfl⟩, ⟨rfl, rfl⟩, rfl⟩
simp at h
#align free_group.red.red_iff_irreducible FreeGroup.Red.red_iff_irreducible
#align free_add_group.red.red_iff_irreducible FreeAddGroup.Red.red_iff_irreducible
/-- If `x` and `y` are distinct letters and `w₁ w₂` are words such that `xw₁` reduces to `yw₂`, then
`w₁` reduces to `x⁻¹yw₂`. -/
@[to_additive "If `x` and `y` are distinct letters and `w₁ w₂` are words such that `x + w₁` reduces
to `y + w₂`, then `w₁` reduces to `-x + y + w₂`."]
theorem inv_of_red_of_ne {x1 b1 x2 b2} (H1 : (x1, b1) ≠ (x2, b2))
(H2 : Red ((x1, b1) :: L₁) ((x2, b2) :: L₂)) : Red L₁ ((x1, not b1) :: (x2, b2) :: L₂) := by
have : Red ((x1, b1) :: L₁) ([(x2, b2)] ++ L₂) := H2
rcases to_append_iff.1 this with ⟨_ | ⟨p, L₃⟩, L₄, eq, h₁, h₂⟩
· simp [nil_iff] at h₁
· cases eq
show Red (L₃ ++ L₄) ([(x1, not b1), (x2, b2)] ++ L₂)
apply append_append _ h₂
have h₁ : Red ((x1, not b1) :: (x1, b1) :: L₃) [(x1, not b1), (x2, b2)] := cons_cons h₁
have h₂ : Red ((x1, not b1) :: (x1, b1) :: L₃) L₃ := Step.cons_not_rev.to_red
rcases church_rosser h₁ h₂ with ⟨L', h₁, h₂⟩
rw [red_iff_irreducible H1] at h₁
rwa [h₁] at h₂
#align free_group.red.inv_of_red_of_ne FreeGroup.Red.inv_of_red_of_ne
#align free_add_group.red.neg_of_red_of_ne FreeAddGroup.Red.neg_of_red_of_ne
open List -- for <+ notation
@[to_additive]
theorem Step.sublist (H : Red.Step L₁ L₂) : Sublist L₂ L₁ := by
cases H; simp; constructor; constructor; rfl
#align free_group.red.step.sublist FreeGroup.Red.Step.sublist
#align free_add_group.red.step.sublist FreeAddGroup.Red.Step.sublist
/-- If `w₁ w₂` are words such that `w₁` reduces to `w₂`, then `w₂` is a sublist of `w₁`. -/
@[to_additive "If `w₁ w₂` are words such that `w₁` reduces to `w₂`, then `w₂` is a sublist of
`w₁`."]
protected theorem sublist : Red L₁ L₂ → L₂ <+ L₁ :=
@reflTransGen_of_transitive_reflexive
_ (fun a b => b <+ a) _ _ _
(fun l => List.Sublist.refl l)
(fun _a _b _c hab hbc => List.Sublist.trans hbc hab)
(fun _ _ => Red.Step.sublist)
#align free_group.red.sublist FreeGroup.Red.sublist
#align free_add_group.red.sublist FreeAddGroup.Red.sublist
@[to_additive]
theorem length_le (h : Red L₁ L₂) : L₂.length ≤ L₁.length :=
h.sublist.length_le
#align free_group.red.length_le FreeGroup.Red.length_le
#align free_add_group.red.length_le FreeAddGroup.Red.length_le
@[to_additive]
theorem sizeof_of_step : ∀ {L₁ L₂ : List (α × Bool)},
Step L₁ L₂ → sizeOf L₂ < sizeOf L₁
| _, _, @Step.not _ L1 L2 x b => by
induction L1 with
| nil =>
-- dsimp [sizeOf]
dsimp
simp only [Bool.sizeOf_eq_one]
have H :
1 + (1 + 1) + (1 + (1 + 1) + sizeOf L2) =
sizeOf L2 + (1 + ((1 + 1) + (1 + 1) + 1)) := by
ac_rfl
rw [H]
apply Nat.lt_add_of_pos_right
apply Nat.lt_add_right
apply Nat.zero_lt_one
| cons hd tl ih =>
dsimp
exact Nat.add_lt_add_left ih _
#align free_group.red.sizeof_of_step FreeGroup.Red.sizeof_of_step
#align free_add_group.red.sizeof_of_step FreeAddGroup.Red.sizeof_of_step
@[to_additive]
theorem length (h : Red L₁ L₂) : ∃ n, L₁.length = L₂.length + 2 * n := by
induction' h with L₂ L₃ _h₁₂ h₂₃ ih
· exact ⟨0, rfl⟩
· rcases ih with ⟨n, eq⟩
exists 1 + n
simp [Nat.mul_add, eq, (Step.length h₂₃).symm, add_assoc]
#align free_group.red.length FreeGroup.Red.length
#align free_add_group.red.length FreeAddGroup.Red.length
@[to_additive]
theorem antisymm (h₁₂ : Red L₁ L₂) (h₂₁ : Red L₂ L₁) : L₁ = L₂ :=
h₂₁.sublist.antisymm h₁₂.sublist
#align free_group.red.antisymm FreeGroup.Red.antisymm
#align free_add_group.red.antisymm FreeAddGroup.Red.antisymm
end Red
@[to_additive FreeAddGroup.equivalence_join_red]
theorem equivalence_join_red : Equivalence (Join (@Red α)) :=
equivalence_join_reflTransGen fun a b c hab hac =>
match b, c, Red.Step.diamond hab hac rfl with
| b, _, Or.inl rfl => ⟨b, by rfl, by rfl⟩
| b, c, Or.inr ⟨d, hbd, hcd⟩ => ⟨d, ReflGen.single hbd, ReflTransGen.single hcd⟩
#align free_group.equivalence_join_red FreeGroup.equivalence_join_red
#align free_add_group.equivalence_join_red FreeAddGroup.equivalence_join_red
@[to_additive FreeAddGroup.join_red_of_step]
theorem join_red_of_step (h : Red.Step L₁ L₂) : Join Red L₁ L₂ :=
join_of_single reflexive_reflTransGen h.to_red
#align free_group.join_red_of_step FreeGroup.join_red_of_step
#align free_add_group.join_red_of_step FreeAddGroup.join_red_of_step
@[to_additive FreeAddGroup.eqvGen_step_iff_join_red]
theorem eqvGen_step_iff_join_red : EqvGen Red.Step L₁ L₂ ↔ Join Red L₁ L₂ :=
Iff.intro
(fun h =>
have : EqvGen (Join Red) L₁ L₂ := h.mono fun _ _ => join_red_of_step
equivalence_join_red.eqvGen_iff.1 this)
(join_of_equivalence (EqvGen.is_equivalence _) fun _ _ =>
reflTransGen_of_equivalence (EqvGen.is_equivalence _) EqvGen.rel)
#align free_group.eqv_gen_step_iff_join_red FreeGroup.eqvGen_step_iff_join_red
#align free_add_group.eqv_gen_step_iff_join_red FreeAddGroup.eqvGen_step_iff_join_red
end FreeGroup
/-- The free group over a type, i.e. the words formed by the elements of the type and their formal
inverses, quotient by one step reduction. -/
@[to_additive "The free additive group over a type, i.e. the words formed by the elements of the
type and their formal inverses, quotient by one step reduction."]
def FreeGroup (α : Type u) : Type u :=
Quot <| @FreeGroup.Red.Step α
#align free_group FreeGroup
#align free_add_group FreeAddGroup
namespace FreeGroup
variable {L L₁ L₂ L₃ L₄ : List (α × Bool)}
/-- The canonical map from `List (α × Bool)` to the free group on `α`. -/
@[to_additive "The canonical map from `list (α × bool)` to the free additive group on `α`."]
def mk (L : List (α × Bool)) : FreeGroup α :=
Quot.mk Red.Step L
#align free_group.mk FreeGroup.mk
#align free_add_group.mk FreeAddGroup.mk
@[to_additive (attr := simp)]
theorem quot_mk_eq_mk : Quot.mk Red.Step L = mk L :=
rfl
#align free_group.quot_mk_eq_mk FreeGroup.quot_mk_eq_mk
#align free_add_group.quot_mk_eq_mk FreeAddGroup.quot_mk_eq_mk
@[to_additive (attr := simp)]
theorem quot_lift_mk (β : Type v) (f : List (α × Bool) → β)
(H : ∀ L₁ L₂, Red.Step L₁ L₂ → f L₁ = f L₂) : Quot.lift f H (mk L) = f L :=
rfl
#align free_group.quot_lift_mk FreeGroup.quot_lift_mk
#align free_add_group.quot_lift_mk FreeAddGroup.quot_lift_mk
@[to_additive (attr := simp)]
theorem quot_liftOn_mk (β : Type v) (f : List (α × Bool) → β)
(H : ∀ L₁ L₂, Red.Step L₁ L₂ → f L₁ = f L₂) : Quot.liftOn (mk L) f H = f L :=
rfl
#align free_group.quot_lift_on_mk FreeGroup.quot_liftOn_mk
#align free_add_group.quot_lift_on_mk FreeAddGroup.quot_liftOn_mk
@[to_additive (attr := simp)]
theorem quot_map_mk (β : Type v) (f : List (α × Bool) → List (β × Bool))
(H : (Red.Step ⇒ Red.Step) f f) : Quot.map f H (mk L) = mk (f L) :=
rfl
#align free_group.quot_map_mk FreeGroup.quot_map_mk
#align free_add_group.quot_map_mk FreeAddGroup.quot_map_mk
@[to_additive]
instance : One (FreeGroup α) :=
⟨mk []⟩
@[to_additive]
theorem one_eq_mk : (1 : FreeGroup α) = mk [] :=
rfl
#align free_group.one_eq_mk FreeGroup.one_eq_mk
#align free_add_group.zero_eq_mk FreeAddGroup.zero_eq_mk
@[to_additive]
instance : Inhabited (FreeGroup α) :=
⟨1⟩
@[to_additive]
instance [IsEmpty α] : Unique (FreeGroup α) := by unfold FreeGroup; infer_instance
@[to_additive]
instance : Mul (FreeGroup α) :=
⟨fun x y =>
Quot.liftOn x
(fun L₁ =>
Quot.liftOn y (fun L₂ => mk <| L₁ ++ L₂) fun _L₂ _L₃ H =>
Quot.sound <| Red.Step.append_left H)
fun _L₁ _L₂ H => Quot.inductionOn y fun _L₃ => Quot.sound <| Red.Step.append_right H⟩
@[to_additive (attr := simp)]
theorem mul_mk : mk L₁ * mk L₂ = mk (L₁ ++ L₂) :=
rfl
#align free_group.mul_mk FreeGroup.mul_mk
#align free_add_group.add_mk FreeAddGroup.add_mk
/-- Transform a word representing a free group element into a word representing its inverse. -/
@[to_additive "Transform a word representing a free group element into a word representing its
negative."]
def invRev (w : List (α × Bool)) : List (α × Bool) :=
(List.map (fun g : α × Bool => (g.1, not g.2)) w).reverse
#align free_group.inv_rev FreeGroup.invRev
#align free_add_group.neg_rev FreeAddGroup.negRev
@[to_additive (attr := simp)]
theorem invRev_length : (invRev L₁).length = L₁.length := by simp [invRev]
#align free_group.inv_rev_length FreeGroup.invRev_length
#align free_add_group.neg_rev_length FreeAddGroup.negRev_length
@[to_additive (attr := simp)]
theorem invRev_invRev : invRev (invRev L₁) = L₁ := by
simp [invRev, List.map_reverse, (· ∘ ·)]
#align free_group.inv_rev_inv_rev FreeGroup.invRev_invRev
#align free_add_group.neg_rev_neg_rev FreeAddGroup.negRev_negRev
@[to_additive (attr := simp)]
theorem invRev_empty : invRev ([] : List (α × Bool)) = [] :=
rfl
#align free_group.inv_rev_empty FreeGroup.invRev_empty
#align free_add_group.neg_rev_empty FreeAddGroup.negRev_empty
@[to_additive]
theorem invRev_involutive : Function.Involutive (@invRev α) := fun _ => invRev_invRev
#align free_group.inv_rev_involutive FreeGroup.invRev_involutive
#align free_add_group.neg_rev_involutive FreeAddGroup.negRev_involutive
@[to_additive]
theorem invRev_injective : Function.Injective (@invRev α) :=
invRev_involutive.injective
#align free_group.inv_rev_injective FreeGroup.invRev_injective
#align free_add_group.neg_rev_injective FreeAddGroup.negRev_injective
@[to_additive]
theorem invRev_surjective : Function.Surjective (@invRev α) :=
invRev_involutive.surjective
#align free_group.inv_rev_surjective FreeGroup.invRev_surjective
#align free_add_group.neg_rev_surjective FreeAddGroup.negRev_surjective
@[to_additive]
theorem invRev_bijective : Function.Bijective (@invRev α) :=
invRev_involutive.bijective
#align free_group.inv_rev_bijective FreeGroup.invRev_bijective
#align free_add_group.neg_rev_bijective FreeAddGroup.negRev_bijective
@[to_additive]
instance : Inv (FreeGroup α) :=
⟨Quot.map invRev
(by
intro a b h
cases h
simp [invRev])⟩
@[to_additive (attr := simp)]
theorem inv_mk : (mk L)⁻¹ = mk (invRev L) :=
rfl
#align free_group.inv_mk FreeGroup.inv_mk
#align free_add_group.neg_mk FreeAddGroup.neg_mk
@[to_additive]
theorem Red.Step.invRev {L₁ L₂ : List (α × Bool)} (h : Red.Step L₁ L₂) :
Red.Step (FreeGroup.invRev L₁) (FreeGroup.invRev L₂) := by
cases' h with a b x y
simp [FreeGroup.invRev]
#align free_group.red.step.inv_rev FreeGroup.Red.Step.invRev
#align free_add_group.red.step.neg_rev FreeAddGroup.Red.Step.negRev
@[to_additive]
theorem Red.invRev {L₁ L₂ : List (α × Bool)} (h : Red L₁ L₂) : Red (invRev L₁) (invRev L₂) :=
Relation.ReflTransGen.lift _ (fun _a _b => Red.Step.invRev) h
#align free_group.red.inv_rev FreeGroup.Red.invRev
#align free_add_group.red.neg_rev FreeAddGroup.Red.negRev
@[to_additive (attr := simp)]
theorem Red.step_invRev_iff :
Red.Step (FreeGroup.invRev L₁) (FreeGroup.invRev L₂) ↔ Red.Step L₁ L₂ :=
⟨fun h => by simpa only [invRev_invRev] using h.invRev, fun h => h.invRev⟩
#align free_group.red.step_inv_rev_iff FreeGroup.Red.step_invRev_iff
#align free_add_group.red.step_neg_rev_iff FreeAddGroup.Red.step_negRev_iff
@[to_additive (attr := simp)]
theorem red_invRev_iff : Red (invRev L₁) (invRev L₂) ↔ Red L₁ L₂ :=
⟨fun h => by simpa only [invRev_invRev] using h.invRev, fun h => h.invRev⟩
#align free_group.red_inv_rev_iff FreeGroup.red_invRev_iff
#align free_add_group.red_neg_rev_iff FreeAddGroup.red_negRev_iff
@[to_additive]
instance : Group (FreeGroup α) where
mul := (· * ·)
one := 1
inv := Inv.inv
mul_assoc := by rintro ⟨L₁⟩ ⟨L₂⟩ ⟨L₃⟩; simp
one_mul := by rintro ⟨L⟩; rfl
mul_one := by rintro ⟨L⟩; simp [one_eq_mk]
mul_left_inv := by
rintro ⟨L⟩
exact
List.recOn L rfl fun ⟨x, b⟩ tl ih =>
Eq.trans (Quot.sound <| by simp [invRev, one_eq_mk]) ih
/-- `of` is the canonical injection from the type to the free group over that type by sending each
element to the equivalence class of the letter that is the element. -/
@[to_additive "`of` is the canonical injection from the type to the free group over that type
by sending each element to the equivalence class of the letter that is the element."]
def of (x : α) : FreeGroup α :=
mk [(x, true)]
#align free_group.of FreeGroup.of
#align free_add_group.of FreeAddGroup.of
@[to_additive]
theorem Red.exact : mk L₁ = mk L₂ ↔ Join Red L₁ L₂ :=
calc
mk L₁ = mk L₂ ↔ EqvGen Red.Step L₁ L₂ := Iff.intro (Quot.exact _) Quot.EqvGen_sound
_ ↔ Join Red L₁ L₂ := eqvGen_step_iff_join_red
#align free_group.red.exact FreeGroup.Red.exact
#align free_add_group.red.exact FreeAddGroup.Red.exact
/-- The canonical map from the type to the free group is an injection. -/
@[to_additive "The canonical map from the type to the additive free group is an injection."]
theorem of_injective : Function.Injective (@of α) := fun _ _ H => by
let ⟨L₁, hx, hy⟩ := Red.exact.1 H
simp [Red.singleton_iff] at hx hy; aesop
#align free_group.of_injective FreeGroup.of_injective
#align free_add_group.of_injective FreeAddGroup.of_injective
section lift
variable {β : Type v} [Group β] (f : α → β) {x y : FreeGroup α}
/-- Given `f : α → β` with `β` a group, the canonical map `List (α × Bool) → β` -/
@[to_additive "Given `f : α → β` with `β` an additive group, the canonical map
`list (α × bool) → β`"]
def Lift.aux : List (α × Bool) → β := fun L =>
List.prod <| L.map fun x => cond x.2 (f x.1) (f x.1)⁻¹
#align free_group.lift.aux FreeGroup.Lift.aux
#align free_add_group.lift.aux FreeAddGroup.Lift.aux
@[to_additive]
theorem Red.Step.lift {f : α → β} (H : Red.Step L₁ L₂) : Lift.aux f L₁ = Lift.aux f L₂ := by
cases' H with _ _ _ b; cases b <;> simp [Lift.aux]
#align free_group.red.step.lift FreeGroup.Red.Step.lift
#align free_add_group.red.step.lift FreeAddGroup.Red.Step.lift
/-- If `β` is a group, then any function from `α` to `β` extends uniquely to a group homomorphism
from the free group over `α` to `β` -/
@[to_additive (attr := simps symm_apply)
"If `β` is an additive group, then any function from `α` to `β` extends uniquely to an
additive group homomorphism from the free additive group over `α` to `β`"]
def lift : (α → β) ≃ (FreeGroup α →* β) where
toFun f :=
MonoidHom.mk' (Quot.lift (Lift.aux f) fun L₁ L₂ => Red.Step.lift) <| by
rintro ⟨L₁⟩ ⟨L₂⟩; simp [Lift.aux]
invFun g := g ∘ of
left_inv f := one_mul _
right_inv g :=
MonoidHom.ext <| by
rintro ⟨L⟩
exact List.recOn L
(g.map_one.symm)
(by
rintro ⟨x, _ | _⟩ t (ih : _ = g (mk t))
· show _ = g ((of x)⁻¹ * mk t)
simpa [Lift.aux] using ih
· show _ = g (of x * mk t)
simpa [Lift.aux] using ih)
#align free_group.lift FreeGroup.lift
#align free_add_group.lift FreeAddGroup.lift
#align free_group.lift_symm_apply FreeGroup.lift_symm_apply
#align free_add_group.lift_symm_apply FreeAddGroup.lift_symm_apply
variable {f}
@[to_additive (attr := simp)]
theorem lift.mk : lift f (mk L) = List.prod (L.map fun x => cond x.2 (f x.1) (f x.1)⁻¹) :=
rfl
#align free_group.lift.mk FreeGroup.lift.mk
#align free_add_group.lift.mk FreeAddGroup.lift.mk
@[to_additive (attr := simp)]
theorem lift.of {x} : lift f (of x) = f x :=
one_mul _
#align free_group.lift.of FreeGroup.lift.of
#align free_add_group.lift.of FreeAddGroup.lift.of
@[to_additive]
theorem lift.unique (g : FreeGroup α →* β) (hg : ∀ x, g (FreeGroup.of x) = f x) {x} :
g x = FreeGroup.lift f x :=
DFunLike.congr_fun (lift.symm_apply_eq.mp (funext hg : g ∘ FreeGroup.of = f)) x
#align free_group.lift.unique FreeGroup.lift.unique
#align free_add_group.lift.unique FreeAddGroup.lift.unique
/-- Two homomorphisms out of a free group are equal if they are equal on generators.
See note [partially-applied ext lemmas]. -/
@[to_additive (attr := ext) "Two homomorphisms out of a free additive group are equal if they are
equal on generators. See note [partially-applied ext lemmas]."]
theorem ext_hom {G : Type*} [Group G] (f g : FreeGroup α →* G) (h : ∀ a, f (of a) = g (of a)) :
f = g :=
lift.symm.injective <| funext h
#align free_group.ext_hom FreeGroup.ext_hom
#align free_add_group.ext_hom FreeAddGroup.ext_hom
@[to_additive]
theorem lift_of_eq_id (α) : lift of = MonoidHom.id (FreeGroup α) :=
lift.apply_symm_apply (MonoidHom.id _)
@[to_additive]
theorem lift.of_eq (x : FreeGroup α) : lift FreeGroup.of x = x :=
DFunLike.congr_fun (lift_of_eq_id α) x
#align free_group.lift.of_eq FreeGroup.lift.of_eq
#align free_add_group.lift.of_eq FreeAddGroup.lift.of_eq
@[to_additive]
theorem lift.range_le {s : Subgroup β} (H : Set.range f ⊆ s) : (lift f).range ≤ s := by
rintro _ ⟨⟨L⟩, rfl⟩;
exact
List.recOn L s.one_mem fun ⟨x, b⟩ tl ih =>
Bool.recOn b (by simp at ih ⊢; exact s.mul_mem (s.inv_mem <| H ⟨x, rfl⟩) ih)
(by simp at ih ⊢; exact s.mul_mem (H ⟨x, rfl⟩) ih)
#align free_group.lift.range_le FreeGroup.lift.range_le
#align free_add_group.lift.range_le FreeAddGroup.lift.range_le
@[to_additive]
theorem lift.range_eq_closure : (lift f).range = Subgroup.closure (Set.range f) := by
apply le_antisymm (lift.range_le Subgroup.subset_closure)
rw [Subgroup.closure_le]
rintro _ ⟨a, rfl⟩
exact ⟨FreeGroup.of a, by simp only [lift.of]⟩
#align free_group.lift.range_eq_closure FreeGroup.lift.range_eq_closure
#align free_add_group.lift.range_eq_closure FreeAddGroup.lift.range_eq_closure
/-- The generators of `FreeGroup α` generate `FreeGroup α`. That is, the subgroup closure of the
set of generators equals `⊤`. -/
@[to_additive (attr := simp)]
theorem closure_range_of (α) :
Subgroup.closure (Set.range (FreeGroup.of : α → FreeGroup α)) = ⊤ := by
rw [← lift.range_eq_closure, lift_of_eq_id]
exact MonoidHom.range_top_of_surjective _ Function.surjective_id
end lift
section Map
variable {β : Type v} (f : α → β) {x y : FreeGroup α}
/-- Any function from `α` to `β` extends uniquely to a group homomorphism from the free group over
`α` to the free group over `β`. -/
@[to_additive "Any function from `α` to `β` extends uniquely to an additive group homomorphism from
the additive free group over `α` to the additive free group over `β`."]
def map : FreeGroup α →* FreeGroup β :=
MonoidHom.mk'
(Quot.map (List.map fun x => (f x.1, x.2)) fun L₁ L₂ H => by cases H; simp)
(by rintro ⟨L₁⟩ ⟨L₂⟩; simp)
#align free_group.map FreeGroup.map
#align free_add_group.map FreeAddGroup.map
variable {f}
@[to_additive (attr := simp)]
theorem map.mk : map f (mk L) = mk (L.map fun x => (f x.1, x.2)) :=
rfl
#align free_group.map.mk FreeGroup.map.mk
#align free_add_group.map.mk FreeAddGroup.map.mk
@[to_additive (attr := simp)]
theorem map.id (x : FreeGroup α) : map id x = x := by rcases x with ⟨L⟩; simp [List.map_id']
#align free_group.map.id FreeGroup.map.id
#align free_add_group.map.id FreeAddGroup.map.id
@[to_additive (attr := simp)]
theorem map.id' (x : FreeGroup α) : map (fun z => z) x = x :=
map.id x
#align free_group.map.id' FreeGroup.map.id'
#align free_add_group.map.id' FreeAddGroup.map.id'
@[to_additive]
theorem map.comp {γ : Type w} (f : α → β) (g : β → γ) (x) :
map g (map f x) = map (g ∘ f) x := by
rcases x with ⟨L⟩; simp [(· ∘ ·)]
#align free_group.map.comp FreeGroup.map.comp
#align free_add_group.map.comp FreeAddGroup.map.comp
@[to_additive (attr := simp)]
theorem map.of {x} : map f (of x) = of (f x) :=
rfl
#align free_group.map.of FreeGroup.map.of
#align free_add_group.map.of FreeAddGroup.map.of
@[to_additive]
theorem map.unique (g : FreeGroup α →* FreeGroup β)
(hg : ∀ x, g (FreeGroup.of x) = FreeGroup.of (f x)) :
∀ {x}, g x = map f x := by
rintro ⟨L⟩
exact List.recOn L g.map_one fun ⟨x, b⟩ t (ih : g (FreeGroup.mk t) = map f (FreeGroup.mk t)) =>
Bool.recOn b
(show g ((FreeGroup.of x)⁻¹ * FreeGroup.mk t) =
FreeGroup.map f ((FreeGroup.of x)⁻¹ * FreeGroup.mk t) by
simp [g.map_mul, g.map_inv, hg, ih])
(show g (FreeGroup.of x * FreeGroup.mk t) =
FreeGroup.map f (FreeGroup.of x * FreeGroup.mk t) by simp [g.map_mul, hg, ih])
#align free_group.map.unique FreeGroup.map.unique
#align free_add_group.map.unique FreeAddGroup.map.unique
@[to_additive]
theorem map_eq_lift : map f x = lift (of ∘ f) x :=
Eq.symm <| map.unique _ fun x => by simp
#align free_group.map_eq_lift FreeGroup.map_eq_lift
#align free_add_group.map_eq_lift FreeAddGroup.map_eq_lift
/-- Equivalent types give rise to multiplicatively equivalent free groups.
The converse can be found in `GroupTheory.FreeAbelianGroupFinsupp`,
as `Equiv.of_freeGroupEquiv`
-/
@[to_additive (attr := simps apply)
"Equivalent types give rise to additively equivalent additive free groups."]
def freeGroupCongr {α β} (e : α ≃ β) : FreeGroup α ≃* FreeGroup β where
toFun := map e
invFun := map e.symm
left_inv x := by simp [Function.comp, map.comp]
right_inv x := by simp [Function.comp, map.comp]
map_mul' := MonoidHom.map_mul _
#align free_group.free_group_congr FreeGroup.freeGroupCongr
#align free_add_group.free_add_group_congr FreeAddGroup.freeAddGroupCongr
#align free_group.free_group_congr_apply FreeGroup.freeGroupCongr_apply
#align free_add_group.free_add_group_congr_apply FreeAddGroup.freeAddGroupCongr_apply
@[to_additive (attr := simp)]
theorem freeGroupCongr_refl : freeGroupCongr (Equiv.refl α) = MulEquiv.refl _ :=
MulEquiv.ext map.id
#align free_group.free_group_congr_refl FreeGroup.freeGroupCongr_refl
#align free_add_group.free_add_group_congr_refl FreeAddGroup.freeAddGroupCongr_refl
@[to_additive (attr := simp)]
theorem freeGroupCongr_symm {α β} (e : α ≃ β) : (freeGroupCongr e).symm = freeGroupCongr e.symm :=
rfl
#align free_group.free_group_congr_symm FreeGroup.freeGroupCongr_symm
#align free_add_group.free_add_group_congr_symm FreeAddGroup.freeAddGroupCongr_symm
@[to_additive]
theorem freeGroupCongr_trans {α β γ} (e : α ≃ β) (f : β ≃ γ) :
(freeGroupCongr e).trans (freeGroupCongr f) = freeGroupCongr (e.trans f) :=
MulEquiv.ext <| map.comp _ _
#align free_group.free_group_congr_trans FreeGroup.freeGroupCongr_trans
#align free_add_group.free_add_group_congr_trans FreeAddGroup.freeAddGroupCongr_trans
end Map
section Prod
variable [Group α] (x y : FreeGroup α)
/-- If `α` is a group, then any function from `α` to `α` extends uniquely to a homomorphism from the
free group over `α` to `α`. This is the multiplicative version of `FreeGroup.sum`. -/
@[to_additive "If `α` is an additive group, then any function from `α` to `α` extends uniquely to an
additive homomorphism from the additive free group over `α` to `α`."]
def prod : FreeGroup α →* α :=
lift id
#align free_group.prod FreeGroup.prod
#align free_add_group.sum FreeAddGroup.sum
variable {x y}
@[to_additive (attr := simp)]
theorem prod_mk : prod (mk L) = List.prod (L.map fun x => cond x.2 x.1 x.1⁻¹) :=
rfl
#align free_group.prod_mk FreeGroup.prod_mk
#align free_add_group.sum_mk FreeAddGroup.sum_mk
@[to_additive (attr := simp)]
theorem prod.of {x : α} : prod (of x) = x :=
lift.of
#align free_group.prod.of FreeGroup.prod.of
#align free_add_group.sum.of FreeAddGroup.sum.of
@[to_additive]
theorem prod.unique (g : FreeGroup α →* α) (hg : ∀ x, g (FreeGroup.of x) = x) {x} : g x = prod x :=
lift.unique g hg
#align free_group.prod.unique FreeGroup.prod.unique
#align free_add_group.sum.unique FreeAddGroup.sum.unique
end Prod
@[to_additive]
theorem lift_eq_prod_map {β : Type v} [Group β] {f : α → β} {x} : lift f x = prod (map f x) := by
rw [← lift.unique (prod.comp (map f))]
· rfl
· simp
#align free_group.lift_eq_prod_map FreeGroup.lift_eq_prod_map
#align free_add_group.lift_eq_sum_map FreeAddGroup.lift_eq_sum_map
section Sum
variable [AddGroup α] (x y : FreeGroup α)
/-- If `α` is a group, then any function from `α` to `α` extends uniquely to a homomorphism from the
free group over `α` to `α`. This is the additive version of `Prod`. -/
def sum : α :=
@prod (Multiplicative _) _ x
#align free_group.sum FreeGroup.sum
variable {x y}
@[simp]
theorem sum_mk : sum (mk L) = List.sum (L.map fun x => cond x.2 x.1 (-x.1)) :=
rfl
#align free_group.sum_mk FreeGroup.sum_mk
@[simp]
theorem sum.of {x : α} : sum (of x) = x :=
@prod.of _ (_) _
#align free_group.sum.of FreeGroup.sum.of
-- note: there are no bundled homs with different notation in the domain and codomain, so we copy
-- these manually
@[simp]
theorem sum.map_mul : sum (x * y) = sum x + sum y :=
(@prod (Multiplicative _) _).map_mul _ _
#align free_group.sum.map_mul FreeGroup.sum.map_mul
@[simp]
theorem sum.map_one : sum (1 : FreeGroup α) = 0 :=
(@prod (Multiplicative _) _).map_one
#align free_group.sum.map_one FreeGroup.sum.map_one
@[simp]
theorem sum.map_inv : sum x⁻¹ = -sum x :=
(prod : FreeGroup (Multiplicative α) →* Multiplicative α).map_inv _
#align free_group.sum.map_inv FreeGroup.sum.map_inv
end Sum
/-- The bijection between the free group on the empty type, and a type with one element. -/
@[to_additive "The bijection between the additive free group on the empty type, and a type with one
element."]
def freeGroupEmptyEquivUnit : FreeGroup Empty ≃ Unit where
toFun _ := ()
invFun _ := 1
left_inv := by rintro ⟨_ | ⟨⟨⟨⟩, _⟩, _⟩⟩; rfl
right_inv := fun ⟨⟩ => rfl
#align free_group.free_group_empty_equiv_unit FreeGroup.freeGroupEmptyEquivUnit
#align free_add_group.free_add_group_empty_equiv_add_unit FreeAddGroup.freeAddGroupEmptyEquivAddUnit
/-- The bijection between the free group on a singleton, and the integers. -/
def freeGroupUnitEquivInt : FreeGroup Unit ≃ ℤ where
toFun x := sum (by
revert x
change (FreeGroup Unit →* FreeGroup ℤ)
apply map fun _ => (1 : ℤ))
invFun x := of () ^ x
left_inv := by
rintro ⟨L⟩
simp only [quot_mk_eq_mk, map.mk, sum_mk, List.map_map]
exact List.recOn L
(by rfl)
(fun ⟨⟨⟩, b⟩ tl ih => by
cases b <;> simp [zpow_add] at ih ⊢ <;> rw [ih] <;> rfl)
right_inv x :=
Int.induction_on x (by simp)
(fun i ih => by
simp only [zpow_natCast, map_pow, map.of] at ih
simp [zpow_add, ih])
(fun i ih => by
simp only [zpow_neg, zpow_natCast, map_inv, map_pow, map.of, sum.map_inv, neg_inj] at ih
simp [zpow_add, ih, sub_eq_add_neg])
#align free_group.free_group_unit_equiv_int FreeGroup.freeGroupUnitEquivInt
section Category
variable {β : Type u}
@[to_additive]
instance : Monad FreeGroup.{u} where
pure {_α} := of
map {_α} {_β} {f} := map f
bind {_α} {_β} {x} {f} := lift f x
@[to_additive (attr := elab_as_elim)]
protected theorem induction_on {C : FreeGroup α → Prop} (z : FreeGroup α) (C1 : C 1)
(Cp : ∀ x, C <| pure x) (Ci : ∀ x, C (pure x) → C (pure x)⁻¹)
(Cm : ∀ x y, C x → C y → C (x * y)) : C z :=
Quot.inductionOn z fun L =>
List.recOn L C1 fun ⟨x, b⟩ _tl ih => Bool.recOn b (Cm _ _ (Ci _ <| Cp x) ih) (Cm _ _ (Cp x) ih)
#align free_group.induction_on FreeGroup.induction_on
#align free_add_group.induction_on FreeAddGroup.induction_on
-- porting note (#10618): simp can prove this: by simp only [@map_pure]
@[to_additive]
theorem map_pure (f : α → β) (x : α) : f <$> (pure x : FreeGroup α) = pure (f x) :=
map.of
#align free_group.map_pure FreeGroup.map_pure
#align free_add_group.map_pure FreeAddGroup.map_pure
@[to_additive (attr := simp)]
theorem map_one (f : α → β) : f <$> (1 : FreeGroup α) = 1 :=
(map f).map_one
#align free_group.map_one FreeGroup.map_one
#align free_add_group.map_zero FreeAddGroup.map_zero
@[to_additive (attr := simp)]
theorem map_mul (f : α → β) (x y : FreeGroup α) : f <$> (x * y) = f <$> x * f <$> y :=
(map f).map_mul x y
#align free_group.map_mul FreeGroup.map_mul
#align free_add_group.map_add FreeAddGroup.map_add
@[to_additive (attr := simp)]
theorem map_inv (f : α → β) (x : FreeGroup α) : f <$> x⁻¹ = (f <$> x)⁻¹ :=
(map f).map_inv x
#align free_group.map_inv FreeGroup.map_inv
#align free_add_group.map_neg FreeAddGroup.map_neg
-- porting note (#10618): simp can prove this: by simp only [@pure_bind]
@[to_additive]
theorem pure_bind (f : α → FreeGroup β) (x) : pure x >>= f = f x :=
lift.of
#align free_group.pure_bind FreeGroup.pure_bind
#align free_add_group.pure_bind FreeAddGroup.pure_bind
@[to_additive (attr := simp)]
theorem one_bind (f : α → FreeGroup β) : 1 >>= f = 1 :=
(lift f).map_one
#align free_group.one_bind FreeGroup.one_bind
#align free_add_group.zero_bind FreeAddGroup.zero_bind
@[to_additive (attr := simp)]
theorem mul_bind (f : α → FreeGroup β) (x y : FreeGroup α) : x * y >>= f = (x >>= f) * (y >>= f) :=
(lift f).map_mul _ _
#align free_group.mul_bind FreeGroup.mul_bind
#align free_add_group.add_bind FreeAddGroup.add_bind
@[to_additive (attr := simp)]
theorem inv_bind (f : α → FreeGroup β) (x : FreeGroup α) : x⁻¹ >>= f = (x >>= f)⁻¹ :=
(lift f).map_inv _
#align free_group.inv_bind FreeGroup.inv_bind
#align free_add_group.neg_bind FreeAddGroup.neg_bind
@[to_additive]
instance : LawfulMonad FreeGroup.{u} := LawfulMonad.mk'
(id_map := fun x =>
FreeGroup.induction_on x (map_one id) (fun x => map_pure id x) (fun x ih => by rw [map_inv, ih])
fun x y ihx ihy => by rw [map_mul, ihx, ihy])
(pure_bind := fun x f => pure_bind f x)
(bind_assoc := fun x =>
FreeGroup.induction_on x
(by intros; iterate 3 rw [one_bind])
(fun x => by intros; iterate 2 rw [pure_bind])
(fun x ih => by intros; (iterate 3 rw [inv_bind]); rw [ih])
(fun x y ihx ihy => by intros; (iterate 3 rw [mul_bind]); rw [ihx, ihy]))
(bind_pure_comp := fun f x =>
FreeGroup.induction_on x (by rw [one_bind, map_one]) (fun x => by rw [pure_bind, map_pure])
(fun x ih => by rw [inv_bind, map_inv, ih]) fun x y ihx ihy => by
rw [mul_bind, map_mul, ihx, ihy])
end Category
section Reduce
variable [DecidableEq α]
/-- The maximal reduction of a word. It is computable
iff `α` has decidable equality. -/
@[to_additive "The maximal reduction of a word. It is computable iff `α` has decidable equality."]
def reduce : (L : List (α × Bool)) -> List (α × Bool) :=
List.rec [] fun hd1 _tl1 ih =>
List.casesOn ih [hd1] fun hd2 tl2 =>
if hd1.1 = hd2.1 ∧ hd1.2 = not hd2.2 then tl2 else hd1 :: hd2 :: tl2
#align free_group.reduce FreeGroup.reduce
#align free_add_group.reduce FreeAddGroup.reduce
@[to_additive (attr := simp)]
theorem reduce.cons (x) :
reduce (x :: L) =
List.casesOn (reduce L) [x] fun hd tl =>
if x.1 = hd.1 ∧ x.2 = not hd.2 then tl else x :: hd :: tl :=
rfl
#align free_group.reduce.cons FreeGroup.reduce.cons
#align free_add_group.reduce.cons FreeAddGroup.reduce.cons
/-- The first theorem that characterises the function `reduce`: a word reduces to its maximal
reduction. -/
@[to_additive "The first theorem that characterises the function `reduce`: a word reduces to its
maximal reduction."]
theorem reduce.red : Red L (reduce L) := by
induction L with
| nil => constructor
| cons hd1 tl1 ih =>
dsimp
revert ih
generalize htl : reduce tl1 = TL
intro ih
cases TL with
| nil => exact Red.cons_cons ih
| cons hd2 tl2 =>
dsimp only
split_ifs with h
· cases hd1
cases hd2
cases h
dsimp at *
subst_vars
apply Red.trans (Red.cons_cons ih)
exact Red.Step.cons_not_rev.to_red
· exact Red.cons_cons ih
#align free_group.reduce.red FreeGroup.reduce.red
#align free_add_group.reduce.red FreeAddGroup.reduce.red
@[to_additive]
theorem reduce.not {p : Prop} :
∀ {L₁ L₂ L₃ : List (α × Bool)} {x b}, reduce L₁ = L₂ ++ (x, b) :: (x, !b) :: L₃ → p
| [], L2, L3, _, _ => fun h => by cases L2 <;> injections
| (x, b) :: L1, L2, L3, x', b' => by
dsimp
cases r : reduce L1 with
| nil =>
dsimp; intro h
exfalso
have := congr_arg List.length h
simp? [List.length] at this says
simp only [List.length, zero_add, List.length_append] at this
rw [add_comm, add_assoc, add_assoc, add_comm, <-add_assoc] at this
omega
| cons hd tail =>
cases' hd with y c
dsimp only
split_ifs with h <;> intro H
· rw [H] at r
exact @reduce.not _ L1 ((y, c) :: L2) L3 x' b' r
rcases L2 with (_ | ⟨a, L2⟩)
· injections; subst_vars
simp at h
· refine @reduce.not _ L1 L2 L3 x' b' ?_
injection H with _ H
rw [r, H]; rfl
#align free_group.reduce.not FreeGroup.reduce.not
#align free_add_group.reduce.not FreeAddGroup.reduce.not
/-- The second theorem that characterises the function `reduce`: the maximal reduction of a word
only reduces to itself. -/
@[to_additive "The second theorem that characterises the function `reduce`: the maximal reduction of
a word only reduces to itself."]
theorem reduce.min (H : Red (reduce L₁) L₂) : reduce L₁ = L₂ := by
induction' H with L1 L' L2 H1 H2 ih
· rfl
· cases' H1 with L4 L5 x b
exact reduce.not H2
#align free_group.reduce.min FreeGroup.reduce.min
#align free_add_group.reduce.min FreeAddGroup.reduce.min
/-- `reduce` is idempotent, i.e. the maximal reduction of the maximal reduction of a word is the
maximal reduction of the word. -/
@[to_additive (attr := simp) "`reduce` is idempotent, i.e. the maximal reduction of the maximal
reduction of a word is the maximal reduction of the word."]
theorem reduce.idem : reduce (reduce L) = reduce L :=
Eq.symm <| reduce.min reduce.red
#align free_group.reduce.idem FreeGroup.reduce.idem
#align free_add_group.reduce.idem FreeAddGroup.reduce.idem
@[to_additive]
theorem reduce.Step.eq (H : Red.Step L₁ L₂) : reduce L₁ = reduce L₂ :=
let ⟨_L₃, HR13, HR23⟩ := Red.church_rosser reduce.red (reduce.red.head H)
(reduce.min HR13).trans (reduce.min HR23).symm
#align free_group.reduce.step.eq FreeGroup.reduce.Step.eq
#align free_add_group.reduce.step.eq FreeAddGroup.reduce.Step.eq
/-- If a word reduces to another word, then they have a common maximal reduction. -/
@[to_additive "If a word reduces to another word, then they have a common maximal reduction."]
theorem reduce.eq_of_red (H : Red L₁ L₂) : reduce L₁ = reduce L₂ :=
let ⟨_L₃, HR13, HR23⟩ := Red.church_rosser reduce.red (Red.trans H reduce.red)
(reduce.min HR13).trans (reduce.min HR23).symm
#align free_group.reduce.eq_of_red FreeGroup.reduce.eq_of_red
#align free_add_group.reduce.eq_of_red FreeAddGroup.reduce.eq_of_red
alias red.reduce_eq := reduce.eq_of_red
#align free_group.red.reduce_eq FreeGroup.red.reduce_eq
alias freeAddGroup.red.reduce_eq := FreeAddGroup.reduce.eq_of_red
#align free_group.free_add_group.red.reduce_eq FreeGroup.freeAddGroup.red.reduce_eq
@[to_additive]
theorem Red.reduce_right (h : Red L₁ L₂) : Red L₁ (reduce L₂) :=
reduce.eq_of_red h ▸ reduce.red
#align free_group.red.reduce_right FreeGroup.Red.reduce_right
#align free_add_group.red.reduce_right FreeAddGroup.Red.reduce_right
@[to_additive]
theorem Red.reduce_left (h : Red L₁ L₂) : Red L₂ (reduce L₁) :=
(reduce.eq_of_red h).symm ▸ reduce.red
#align free_group.red.reduce_left FreeGroup.Red.reduce_left
#align free_add_group.red.reduce_left FreeAddGroup.Red.reduce_left
/-- If two words correspond to the same element in the free group, then they
have a common maximal reduction. This is the proof that the function that sends
an element of the free group to its maximal reduction is well-defined. -/
@[to_additive "If two words correspond to the same element in the additive free group, then they
have a common maximal reduction. This is the proof that the function that sends an element of the
free group to its maximal reduction is well-defined."]
theorem reduce.sound (H : mk L₁ = mk L₂) : reduce L₁ = reduce L₂ :=
let ⟨_L₃, H13, H23⟩ := Red.exact.1 H
(reduce.eq_of_red H13).trans (reduce.eq_of_red H23).symm
#align free_group.reduce.sound FreeGroup.reduce.sound
#align free_add_group.reduce.sound FreeAddGroup.reduce.sound
/-- If two words have a common maximal reduction, then they correspond to the same element in the
free group. -/
@[to_additive "If two words have a common maximal reduction, then they correspond to the same
element in the additive free group."]
theorem reduce.exact (H : reduce L₁ = reduce L₂) : mk L₁ = mk L₂ :=
Red.exact.2 ⟨reduce L₂, H ▸ reduce.red, reduce.red⟩
#align free_group.reduce.exact FreeGroup.reduce.exact
#align free_add_group.reduce.exact FreeAddGroup.reduce.exact
/-- A word and its maximal reduction correspond to the same element of the free group. -/
@[to_additive "A word and its maximal reduction correspond to the same element of the additive free
group."]
theorem reduce.self : mk (reduce L) = mk L :=
reduce.exact reduce.idem
#align free_group.reduce.self FreeGroup.reduce.self
#align free_add_group.reduce.self FreeAddGroup.reduce.self
/-- If words `w₁ w₂` are such that `w₁` reduces to `w₂`, then `w₂` reduces to the maximal reduction
of `w₁`. -/
@[to_additive "If words `w₁ w₂` are such that `w₁` reduces to `w₂`, then `w₂` reduces to the maximal
reduction of `w₁`."]
theorem reduce.rev (H : Red L₁ L₂) : Red L₂ (reduce L₁) :=
(reduce.eq_of_red H).symm ▸ reduce.red
#align free_group.reduce.rev FreeGroup.reduce.rev
#align free_add_group.reduce.rev FreeAddGroup.reduce.rev
/-- The function that sends an element of the free group to its maximal reduction. -/
@[to_additive "The function that sends an element of the additive free group to its maximal
reduction."]
def toWord : FreeGroup α → List (α × Bool) :=
Quot.lift reduce fun _L₁ _L₂ H => reduce.Step.eq H
#align free_group.to_word FreeGroup.toWord
#align free_add_group.to_word FreeAddGroup.toWord
@[to_additive]
theorem mk_toWord : ∀ {x : FreeGroup α}, mk (toWord x) = x := by rintro ⟨L⟩; exact reduce.self
#align free_group.mk_to_word FreeGroup.mk_toWord
#align free_add_group.mk_to_word FreeAddGroup.mk_toWord
@[to_additive]
| Mathlib/GroupTheory/FreeGroup/Basic.lean | 1,295 | 1,296 | theorem toWord_injective : Function.Injective (toWord : FreeGroup α → List (α × Bool)) := by |
rintro ⟨L₁⟩ ⟨L₂⟩; exact reduce.exact
|
/-
Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel
-/
import Mathlib.Topology.EMetricSpace.Basic
import Mathlib.Topology.Bornology.Constructions
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.Topology.Order.DenselyOrdered
/-!
## Pseudo-metric spaces
This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the
condition `dist x y = 0 → x = y`.
Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform
spaces and topological spaces. For example: open and closed sets, compactness, completeness,
continuity and uniform continuity.
## Main definitions
* `Dist α`: Endows a space `α` with a function `dist a b`.
* `PseudoMetricSpace α`: A space endowed with a distance function, which can
be zero even if the two elements are non-equal.
* `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`.
* `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded.
* `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`.
Additional useful definitions:
* `nndist a b`: `dist` as a function to the non-negative reals.
* `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`.
* `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`.
TODO (anyone): Add "Main results" section.
## Tags
pseudo_metric, dist
-/
open Set Filter TopologicalSpace Bornology
open scoped ENNReal NNReal Uniformity Topology
universe u v w
variable {α : Type u} {β : Type v} {X ι : Type*}
theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε :=
⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩
/-- Construct a uniform structure from a distance function and metric space axioms -/
def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0)
(dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α :=
.ofFun dist dist_self dist_comm dist_triangle ofDist_aux
#align uniform_space_of_dist UniformSpace.ofDist
-- Porting note: dropped the `dist_self` argument
/-- Construct a bornology from a distance function and metric space axioms. -/
abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x)
(dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α :=
Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C }
⟨0, fun x hx y => hx.elim⟩ (fun s ⟨c, hc⟩ t h => ⟨c, fun x hx y hy => hc (h hx) (h hy)⟩)
(fun s hs t ht => by
rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩
· rwa [empty_union]
rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩
· rwa [union_empty]
rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C
· refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩
simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb)
rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩
refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim
(fun hz => (hs hx hz).trans (le_max_left _ _))
(fun hz => (dist_triangle x y z).trans <|
(add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩)
fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩
#align bornology.of_dist Bornology.ofDistₓ
/-- The distance function (given an ambient metric space on `α`), which returns
a nonnegative real number `dist x y` given `x y : α`. -/
@[ext]
class Dist (α : Type*) where
dist : α → α → ℝ
#align has_dist Dist
export Dist (dist)
-- the uniform structure and the emetric space structure are embedded in the metric space structure
-- to avoid instance diamond issues. See Note [forgetful inheritance].
/-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/
private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y :=
have : 0 ≤ 2 * dist x y :=
calc 0 = dist x x := (dist_self _).symm
_ ≤ dist x y + dist y x := dist_triangle _ _ _
_ = 2 * dist x y := by rw [two_mul, dist_comm]
nonneg_of_mul_nonneg_right this two_pos
#noalign pseudo_metric_space.edist_dist_tac -- Porting note (#11215): TODO: restore
/-- Pseudo metric and Metric spaces
A pseudo metric space is endowed with a distance for which the requirement `d(x,y)=0 → x = y` might
not hold. A metric space is a pseudo metric space such that `d(x,y)=0 → x = y`.
Each pseudo metric space induces a canonical `UniformSpace` and hence a canonical
`TopologicalSpace` This is enforced in the type class definition, by extending the `UniformSpace`
structure. When instantiating a `PseudoMetricSpace` structure, the uniformity fields are not
necessary, they will be filled in by default. In the same way, each (pseudo) metric space induces a
(pseudo) emetric space structure. It is included in the structure, but filled in by default.
-/
class PseudoMetricSpace (α : Type u) extends Dist α : Type u where
dist_self : ∀ x : α, dist x x = 0
dist_comm : ∀ x y : α, dist x y = dist y x
dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z
edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩
edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y)
-- Porting note (#11215): TODO: add := by _
toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle
uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl
toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets : (Bornology.cobounded α).sets =
{ s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl
#align pseudo_metric_space PseudoMetricSpace
/-- Two pseudo metric space structures with the same distance function coincide. -/
@[ext]
theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α}
(h : m.toDist = m'.toDist) : m = m' := by
cases' m with d _ _ _ ed hed U hU B hB
cases' m' with d' _ _ _ ed' hed' U' hU' B' hB'
obtain rfl : d = d' := h
congr
· ext x y : 2
rw [hed, hed']
· exact UniformSpace.ext (hU.trans hU'.symm)
· ext : 2
rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB']
#align pseudo_metric_space.ext PseudoMetricSpace.ext
variable [PseudoMetricSpace α]
attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology
-- see Note [lower instance priority]
instance (priority := 200) PseudoMetricSpace.toEDist : EDist α :=
⟨PseudoMetricSpace.edist⟩
#align pseudo_metric_space.to_has_edist PseudoMetricSpace.toEDist
/-- Construct a pseudo-metric space structure whose underlying topological space structure
(definitionally) agrees which a pre-existing topology which is compatible with a given distance
function. -/
def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z)
(H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) :
PseudoMetricSpace α :=
{ dist := dist
dist_self := dist_self
dist_comm := dist_comm
dist_triangle := dist_triangle
edist_dist := fun x y => by exact ENNReal.coe_nnreal_eq _
toUniformSpace :=
(UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <|
TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦
((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle
UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm
uniformity_dist := rfl
toBornology := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets := rfl }
#align pseudo_metric_space.of_dist_topology PseudoMetricSpace.ofDistTopology
@[simp]
theorem dist_self (x : α) : dist x x = 0 :=
PseudoMetricSpace.dist_self x
#align dist_self dist_self
theorem dist_comm (x y : α) : dist x y = dist y x :=
PseudoMetricSpace.dist_comm x y
#align dist_comm dist_comm
theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) :=
PseudoMetricSpace.edist_dist x y
#align edist_dist edist_dist
theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z :=
PseudoMetricSpace.dist_triangle x y z
#align dist_triangle dist_triangle
theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by
rw [dist_comm z]; apply dist_triangle
#align dist_triangle_left dist_triangle_left
theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by
rw [dist_comm y]; apply dist_triangle
#align dist_triangle_right dist_triangle_right
theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w :=
calc
dist x w ≤ dist x z + dist z w := dist_triangle x z w
_ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _
#align dist_triangle4 dist_triangle4
theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) :
dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by
rw [add_left_comm, dist_comm x₁, ← add_assoc]
apply dist_triangle4
#align dist_triangle4_left dist_triangle4_left
theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) :
dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by
rw [add_right_comm, dist_comm y₁]
apply dist_triangle4
#align dist_triangle4_right dist_triangle4_right
/-- The triangle (polygon) inequality for sequences of points; `Finset.Ico` version. -/
theorem dist_le_Ico_sum_dist (f : ℕ → α) {m n} (h : m ≤ n) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, dist (f i) (f (i + 1)) := by
induction n, h using Nat.le_induction with
| base => rw [Finset.Ico_self, Finset.sum_empty, dist_self]
| succ n hle ihn =>
calc
dist (f m) (f (n + 1)) ≤ dist (f m) (f n) + dist (f n) (f (n + 1)) := dist_triangle _ _ _
_ ≤ (∑ i ∈ Finset.Ico m n, _) + _ := add_le_add ihn le_rfl
_ = ∑ i ∈ Finset.Ico m (n + 1), _ := by
{ rw [Nat.Ico_succ_right_eq_insert_Ico hle, Finset.sum_insert, add_comm]; simp }
#align dist_le_Ico_sum_dist dist_le_Ico_sum_dist
/-- The triangle (polygon) inequality for sequences of points; `Finset.range` version. -/
theorem dist_le_range_sum_dist (f : ℕ → α) (n : ℕ) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, dist (f i) (f (i + 1)) :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_dist f (Nat.zero_le n)
#align dist_le_range_sum_dist dist_le_range_sum_dist
/-- A version of `dist_le_Ico_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_Ico_sum_of_dist_le {f : ℕ → α} {m n} (hmn : m ≤ n) {d : ℕ → ℝ}
(hd : ∀ {k}, m ≤ k → k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, d i :=
le_trans (dist_le_Ico_sum_dist f hmn) <|
Finset.sum_le_sum fun _k hk => hd (Finset.mem_Ico.1 hk).1 (Finset.mem_Ico.1 hk).2
#align dist_le_Ico_sum_of_dist_le dist_le_Ico_sum_of_dist_le
/-- A version of `dist_le_range_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_range_sum_of_dist_le {f : ℕ → α} (n : ℕ) {d : ℕ → ℝ}
(hd : ∀ {k}, k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, d i :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_of_dist_le (zero_le n) fun _ => hd
#align dist_le_range_sum_of_dist_le dist_le_range_sum_of_dist_le
theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _
#align swap_dist swap_dist
theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y :=
abs_sub_le_iff.2
⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩
#align abs_dist_sub_le abs_dist_sub_le
theorem dist_nonneg {x y : α} : 0 ≤ dist x y :=
dist_nonneg' dist dist_self dist_comm dist_triangle
#align dist_nonneg dist_nonneg
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
/-- Extension for the `positivity` tactic: distances are nonnegative. -/
@[positivity Dist.dist _ _]
def evalDist : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) =>
let _inst ← synthInstanceQ q(PseudoMetricSpace $β)
assertInstancesCommute
pure (.nonnegative q(dist_nonneg))
| _, _, _ => throwError "not dist"
end Mathlib.Meta.Positivity
example {x y : α} : 0 ≤ dist x y := by positivity
@[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg
#align abs_dist abs_dist
/-- A version of `Dist` that takes value in `ℝ≥0`. -/
class NNDist (α : Type*) where
nndist : α → α → ℝ≥0
#align has_nndist NNDist
export NNDist (nndist)
-- see Note [lower instance priority]
/-- Distance as a nonnegative real number. -/
instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α :=
⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩
#align pseudo_metric_space.to_has_nndist PseudoMetricSpace.toNNDist
/-- Express `dist` in terms of `nndist`-/
theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl
#align dist_nndist dist_nndist
@[simp, norm_cast]
theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl
#align coe_nndist coe_nndist
/-- Express `edist` in terms of `nndist`-/
theorem edist_nndist (x y : α) : edist x y = nndist x y := by
rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal]
#align edist_nndist edist_nndist
/-- Express `nndist` in terms of `edist`-/
theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by
simp [edist_nndist]
#align nndist_edist nndist_edist
@[simp, norm_cast]
theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y :=
(edist_nndist x y).symm
#align coe_nnreal_ennreal_nndist coe_nnreal_ennreal_nndist
@[simp, norm_cast]
theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by
rw [edist_nndist, ENNReal.coe_lt_coe]
#align edist_lt_coe edist_lt_coe
@[simp, norm_cast]
theorem edist_le_coe {x y : α} {c : ℝ≥0} : edist x y ≤ c ↔ nndist x y ≤ c := by
rw [edist_nndist, ENNReal.coe_le_coe]
#align edist_le_coe edist_le_coe
/-- In a pseudometric space, the extended distance is always finite-/
theorem edist_lt_top {α : Type*} [PseudoMetricSpace α] (x y : α) : edist x y < ⊤ :=
(edist_dist x y).symm ▸ ENNReal.ofReal_lt_top
#align edist_lt_top edist_lt_top
/-- In a pseudometric space, the extended distance is always finite-/
theorem edist_ne_top (x y : α) : edist x y ≠ ⊤ :=
(edist_lt_top x y).ne
#align edist_ne_top edist_ne_top
/-- `nndist x x` vanishes-/
@[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a)
#align nndist_self nndist_self
-- Porting note: `dist_nndist` and `coe_nndist` moved up
@[simp, norm_cast]
theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c :=
Iff.rfl
#align dist_lt_coe dist_lt_coe
@[simp, norm_cast]
theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c :=
Iff.rfl
#align dist_le_coe dist_le_coe
@[simp]
theorem edist_lt_ofReal {x y : α} {r : ℝ} : edist x y < ENNReal.ofReal r ↔ dist x y < r := by
rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg]
#align edist_lt_of_real edist_lt_ofReal
@[simp]
theorem edist_le_ofReal {x y : α} {r : ℝ} (hr : 0 ≤ r) :
edist x y ≤ ENNReal.ofReal r ↔ dist x y ≤ r := by
rw [edist_dist, ENNReal.ofReal_le_ofReal_iff hr]
#align edist_le_of_real edist_le_ofReal
/-- Express `nndist` in terms of `dist`-/
theorem nndist_dist (x y : α) : nndist x y = Real.toNNReal (dist x y) := by
rw [dist_nndist, Real.toNNReal_coe]
#align nndist_dist nndist_dist
theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y
#align nndist_comm nndist_comm
/-- Triangle inequality for the nonnegative distance-/
theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z :=
dist_triangle _ _ _
#align nndist_triangle nndist_triangle
theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y :=
dist_triangle_left _ _ _
#align nndist_triangle_left nndist_triangle_left
theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z :=
dist_triangle_right _ _ _
#align nndist_triangle_right nndist_triangle_right
/-- Express `dist` in terms of `edist`-/
theorem dist_edist (x y : α) : dist x y = (edist x y).toReal := by
rw [edist_dist, ENNReal.toReal_ofReal dist_nonneg]
#align dist_edist dist_edist
namespace Metric
-- instantiate pseudometric space as a topology
variable {x y z : α} {δ ε ε₁ ε₂ : ℝ} {s : Set α}
/-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/
def ball (x : α) (ε : ℝ) : Set α :=
{ y | dist y x < ε }
#align metric.ball Metric.ball
@[simp]
theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε :=
Iff.rfl
#align metric.mem_ball Metric.mem_ball
theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball]
#align metric.mem_ball' Metric.mem_ball'
theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε :=
dist_nonneg.trans_lt hy
#align metric.pos_of_mem_ball Metric.pos_of_mem_ball
theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by
rwa [mem_ball, dist_self]
#align metric.mem_ball_self Metric.mem_ball_self
@[simp]
theorem nonempty_ball : (ball x ε).Nonempty ↔ 0 < ε :=
⟨fun ⟨_x, hx⟩ => pos_of_mem_ball hx, fun h => ⟨x, mem_ball_self h⟩⟩
#align metric.nonempty_ball Metric.nonempty_ball
@[simp]
theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt]
#align metric.ball_eq_empty Metric.ball_eq_empty
@[simp]
theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty]
#align metric.ball_zero Metric.ball_zero
/-- If a point belongs to an open ball, then there is a strictly smaller radius whose ball also
contains it.
See also `exists_lt_subset_ball`. -/
theorem exists_lt_mem_ball_of_mem_ball (h : x ∈ ball y ε) : ∃ ε' < ε, x ∈ ball y ε' := by
simp only [mem_ball] at h ⊢
exact ⟨(dist x y + ε) / 2, by linarith, by linarith⟩
#align metric.exists_lt_mem_ball_of_mem_ball Metric.exists_lt_mem_ball_of_mem_ball
theorem ball_eq_ball (ε : ℝ) (x : α) :
UniformSpace.ball x { p | dist p.2 p.1 < ε } = Metric.ball x ε :=
rfl
#align metric.ball_eq_ball Metric.ball_eq_ball
theorem ball_eq_ball' (ε : ℝ) (x : α) :
UniformSpace.ball x { p | dist p.1 p.2 < ε } = Metric.ball x ε := by
ext
simp [dist_comm, UniformSpace.ball]
#align metric.ball_eq_ball' Metric.ball_eq_ball'
@[simp]
theorem iUnion_ball_nat (x : α) : ⋃ n : ℕ, ball x n = univ :=
iUnion_eq_univ_iff.2 fun y => exists_nat_gt (dist y x)
#align metric.Union_ball_nat Metric.iUnion_ball_nat
@[simp]
theorem iUnion_ball_nat_succ (x : α) : ⋃ n : ℕ, ball x (n + 1) = univ :=
iUnion_eq_univ_iff.2 fun y => (exists_nat_gt (dist y x)).imp fun _ h => h.trans (lt_add_one _)
#align metric.Union_ball_nat_succ Metric.iUnion_ball_nat_succ
/-- `closedBall x ε` is the set of all points `y` with `dist y x ≤ ε` -/
def closedBall (x : α) (ε : ℝ) :=
{ y | dist y x ≤ ε }
#align metric.closed_ball Metric.closedBall
@[simp] theorem mem_closedBall : y ∈ closedBall x ε ↔ dist y x ≤ ε := Iff.rfl
#align metric.mem_closed_ball Metric.mem_closedBall
theorem mem_closedBall' : y ∈ closedBall x ε ↔ dist x y ≤ ε := by rw [dist_comm, mem_closedBall]
#align metric.mem_closed_ball' Metric.mem_closedBall'
/-- `sphere x ε` is the set of all points `y` with `dist y x = ε` -/
def sphere (x : α) (ε : ℝ) := { y | dist y x = ε }
#align metric.sphere Metric.sphere
@[simp] theorem mem_sphere : y ∈ sphere x ε ↔ dist y x = ε := Iff.rfl
#align metric.mem_sphere Metric.mem_sphere
theorem mem_sphere' : y ∈ sphere x ε ↔ dist x y = ε := by rw [dist_comm, mem_sphere]
#align metric.mem_sphere' Metric.mem_sphere'
theorem ne_of_mem_sphere (h : y ∈ sphere x ε) (hε : ε ≠ 0) : y ≠ x :=
ne_of_mem_of_not_mem h <| by simpa using hε.symm
#align metric.ne_of_mem_sphere Metric.ne_of_mem_sphere
theorem nonneg_of_mem_sphere (hy : y ∈ sphere x ε) : 0 ≤ ε :=
dist_nonneg.trans_eq hy
#align metric.nonneg_of_mem_sphere Metric.nonneg_of_mem_sphere
@[simp]
theorem sphere_eq_empty_of_neg (hε : ε < 0) : sphere x ε = ∅ :=
Set.eq_empty_iff_forall_not_mem.mpr fun _y hy => (nonneg_of_mem_sphere hy).not_lt hε
#align metric.sphere_eq_empty_of_neg Metric.sphere_eq_empty_of_neg
theorem sphere_eq_empty_of_subsingleton [Subsingleton α] (hε : ε ≠ 0) : sphere x ε = ∅ :=
Set.eq_empty_iff_forall_not_mem.mpr fun _ h => ne_of_mem_sphere h hε (Subsingleton.elim _ _)
#align metric.sphere_eq_empty_of_subsingleton Metric.sphere_eq_empty_of_subsingleton
instance sphere_isEmpty_of_subsingleton [Subsingleton α] [NeZero ε] : IsEmpty (sphere x ε) := by
rw [sphere_eq_empty_of_subsingleton (NeZero.ne ε)]; infer_instance
#align metric.sphere_is_empty_of_subsingleton Metric.sphere_isEmpty_of_subsingleton
theorem mem_closedBall_self (h : 0 ≤ ε) : x ∈ closedBall x ε := by
rwa [mem_closedBall, dist_self]
#align metric.mem_closed_ball_self Metric.mem_closedBall_self
@[simp]
theorem nonempty_closedBall : (closedBall x ε).Nonempty ↔ 0 ≤ ε :=
⟨fun ⟨_x, hx⟩ => dist_nonneg.trans hx, fun h => ⟨x, mem_closedBall_self h⟩⟩
#align metric.nonempty_closed_ball Metric.nonempty_closedBall
@[simp]
theorem closedBall_eq_empty : closedBall x ε = ∅ ↔ ε < 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_closedBall, not_le]
#align metric.closed_ball_eq_empty Metric.closedBall_eq_empty
/-- Closed balls and spheres coincide when the radius is non-positive -/
theorem closedBall_eq_sphere_of_nonpos (hε : ε ≤ 0) : closedBall x ε = sphere x ε :=
Set.ext fun _ => (hε.trans dist_nonneg).le_iff_eq
#align metric.closed_ball_eq_sphere_of_nonpos Metric.closedBall_eq_sphere_of_nonpos
theorem ball_subset_closedBall : ball x ε ⊆ closedBall x ε := fun _y hy =>
mem_closedBall.2 (le_of_lt hy)
#align metric.ball_subset_closed_ball Metric.ball_subset_closedBall
theorem sphere_subset_closedBall : sphere x ε ⊆ closedBall x ε := fun _ => le_of_eq
#align metric.sphere_subset_closed_ball Metric.sphere_subset_closedBall
lemma sphere_subset_ball {r R : ℝ} (h : r < R) : sphere x r ⊆ ball x R := fun _x hx ↦
(mem_sphere.1 hx).trans_lt h
theorem closedBall_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (closedBall x δ) (ball y ε) :=
Set.disjoint_left.mpr fun _a ha1 ha2 =>
(h.trans <| dist_triangle_left _ _ _).not_lt <| add_lt_add_of_le_of_lt ha1 ha2
#align metric.closed_ball_disjoint_ball Metric.closedBall_disjoint_ball
theorem ball_disjoint_closedBall (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (closedBall y ε) :=
(closedBall_disjoint_ball <| by rwa [add_comm, dist_comm]).symm
#align metric.ball_disjoint_closed_ball Metric.ball_disjoint_closedBall
theorem ball_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (ball y ε) :=
(closedBall_disjoint_ball h).mono_left ball_subset_closedBall
#align metric.ball_disjoint_ball Metric.ball_disjoint_ball
theorem closedBall_disjoint_closedBall (h : δ + ε < dist x y) :
Disjoint (closedBall x δ) (closedBall y ε) :=
Set.disjoint_left.mpr fun _a ha1 ha2 =>
h.not_le <| (dist_triangle_left _ _ _).trans <| add_le_add ha1 ha2
#align metric.closed_ball_disjoint_closed_ball Metric.closedBall_disjoint_closedBall
theorem sphere_disjoint_ball : Disjoint (sphere x ε) (ball x ε) :=
Set.disjoint_left.mpr fun _y hy₁ hy₂ => absurd hy₁ <| ne_of_lt hy₂
#align metric.sphere_disjoint_ball Metric.sphere_disjoint_ball
@[simp]
theorem ball_union_sphere : ball x ε ∪ sphere x ε = closedBall x ε :=
Set.ext fun _y => (@le_iff_lt_or_eq ℝ _ _ _).symm
#align metric.ball_union_sphere Metric.ball_union_sphere
@[simp]
theorem sphere_union_ball : sphere x ε ∪ ball x ε = closedBall x ε := by
rw [union_comm, ball_union_sphere]
#align metric.sphere_union_ball Metric.sphere_union_ball
@[simp]
theorem closedBall_diff_sphere : closedBall x ε \ sphere x ε = ball x ε := by
rw [← ball_union_sphere, Set.union_diff_cancel_right sphere_disjoint_ball.symm.le_bot]
#align metric.closed_ball_diff_sphere Metric.closedBall_diff_sphere
@[simp]
theorem closedBall_diff_ball : closedBall x ε \ ball x ε = sphere x ε := by
rw [← ball_union_sphere, Set.union_diff_cancel_left sphere_disjoint_ball.symm.le_bot]
#align metric.closed_ball_diff_ball Metric.closedBall_diff_ball
theorem mem_ball_comm : x ∈ ball y ε ↔ y ∈ ball x ε := by rw [mem_ball', mem_ball]
#align metric.mem_ball_comm Metric.mem_ball_comm
theorem mem_closedBall_comm : x ∈ closedBall y ε ↔ y ∈ closedBall x ε := by
rw [mem_closedBall', mem_closedBall]
#align metric.mem_closed_ball_comm Metric.mem_closedBall_comm
theorem mem_sphere_comm : x ∈ sphere y ε ↔ y ∈ sphere x ε := by rw [mem_sphere', mem_sphere]
#align metric.mem_sphere_comm Metric.mem_sphere_comm
@[gcongr]
theorem ball_subset_ball (h : ε₁ ≤ ε₂) : ball x ε₁ ⊆ ball x ε₂ := fun _y yx =>
lt_of_lt_of_le (mem_ball.1 yx) h
#align metric.ball_subset_ball Metric.ball_subset_ball
theorem closedBall_eq_bInter_ball : closedBall x ε = ⋂ δ > ε, ball x δ := by
ext y; rw [mem_closedBall, ← forall_lt_iff_le', mem_iInter₂]; rfl
#align metric.closed_ball_eq_bInter_ball Metric.closedBall_eq_bInter_ball
theorem ball_subset_ball' (h : ε₁ + dist x y ≤ ε₂) : ball x ε₁ ⊆ ball y ε₂ := fun z hz =>
calc
dist z y ≤ dist z x + dist x y := dist_triangle _ _ _
_ < ε₁ + dist x y := add_lt_add_right (mem_ball.1 hz) _
_ ≤ ε₂ := h
#align metric.ball_subset_ball' Metric.ball_subset_ball'
@[gcongr]
theorem closedBall_subset_closedBall (h : ε₁ ≤ ε₂) : closedBall x ε₁ ⊆ closedBall x ε₂ :=
fun _y (yx : _ ≤ ε₁) => le_trans yx h
#align metric.closed_ball_subset_closed_ball Metric.closedBall_subset_closedBall
theorem closedBall_subset_closedBall' (h : ε₁ + dist x y ≤ ε₂) :
closedBall x ε₁ ⊆ closedBall y ε₂ := fun z hz =>
calc
dist z y ≤ dist z x + dist x y := dist_triangle _ _ _
_ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _
_ ≤ ε₂ := h
#align metric.closed_ball_subset_closed_ball' Metric.closedBall_subset_closedBall'
theorem closedBall_subset_ball (h : ε₁ < ε₂) : closedBall x ε₁ ⊆ ball x ε₂ :=
fun y (yh : dist y x ≤ ε₁) => lt_of_le_of_lt yh h
#align metric.closed_ball_subset_ball Metric.closedBall_subset_ball
theorem closedBall_subset_ball' (h : ε₁ + dist x y < ε₂) :
closedBall x ε₁ ⊆ ball y ε₂ := fun z hz =>
calc
dist z y ≤ dist z x + dist x y := dist_triangle _ _ _
_ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _
_ < ε₂ := h
#align metric.closed_ball_subset_ball' Metric.closedBall_subset_ball'
theorem dist_le_add_of_nonempty_closedBall_inter_closedBall
(h : (closedBall x ε₁ ∩ closedBall y ε₂).Nonempty) : dist x y ≤ ε₁ + ε₂ :=
let ⟨z, hz⟩ := h
calc
dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _
_ ≤ ε₁ + ε₂ := add_le_add hz.1 hz.2
#align metric.dist_le_add_of_nonempty_closed_ball_inter_closed_ball Metric.dist_le_add_of_nonempty_closedBall_inter_closedBall
theorem dist_lt_add_of_nonempty_closedBall_inter_ball (h : (closedBall x ε₁ ∩ ball y ε₂).Nonempty) :
dist x y < ε₁ + ε₂ :=
let ⟨z, hz⟩ := h
calc
dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _
_ < ε₁ + ε₂ := add_lt_add_of_le_of_lt hz.1 hz.2
#align metric.dist_lt_add_of_nonempty_closed_ball_inter_ball Metric.dist_lt_add_of_nonempty_closedBall_inter_ball
theorem dist_lt_add_of_nonempty_ball_inter_closedBall (h : (ball x ε₁ ∩ closedBall y ε₂).Nonempty) :
dist x y < ε₁ + ε₂ := by
rw [inter_comm] at h
rw [add_comm, dist_comm]
exact dist_lt_add_of_nonempty_closedBall_inter_ball h
#align metric.dist_lt_add_of_nonempty_ball_inter_closed_ball Metric.dist_lt_add_of_nonempty_ball_inter_closedBall
theorem dist_lt_add_of_nonempty_ball_inter_ball (h : (ball x ε₁ ∩ ball y ε₂).Nonempty) :
dist x y < ε₁ + ε₂ :=
dist_lt_add_of_nonempty_closedBall_inter_ball <|
h.mono (inter_subset_inter ball_subset_closedBall Subset.rfl)
#align metric.dist_lt_add_of_nonempty_ball_inter_ball Metric.dist_lt_add_of_nonempty_ball_inter_ball
@[simp]
theorem iUnion_closedBall_nat (x : α) : ⋃ n : ℕ, closedBall x n = univ :=
iUnion_eq_univ_iff.2 fun y => exists_nat_ge (dist y x)
#align metric.Union_closed_ball_nat Metric.iUnion_closedBall_nat
theorem iUnion_inter_closedBall_nat (s : Set α) (x : α) : ⋃ n : ℕ, s ∩ closedBall x n = s := by
rw [← inter_iUnion, iUnion_closedBall_nat, inter_univ]
#align metric.Union_inter_closed_ball_nat Metric.iUnion_inter_closedBall_nat
theorem ball_subset (h : dist x y ≤ ε₂ - ε₁) : ball x ε₁ ⊆ ball y ε₂ := fun z zx => by
rw [← add_sub_cancel ε₁ ε₂]
exact lt_of_le_of_lt (dist_triangle z x y) (add_lt_add_of_lt_of_le zx h)
#align metric.ball_subset Metric.ball_subset
theorem ball_half_subset (y) (h : y ∈ ball x (ε / 2)) : ball y (ε / 2) ⊆ ball x ε :=
ball_subset <| by rw [sub_self_div_two]; exact le_of_lt h
#align metric.ball_half_subset Metric.ball_half_subset
theorem exists_ball_subset_ball (h : y ∈ ball x ε) : ∃ ε' > 0, ball y ε' ⊆ ball x ε :=
⟨_, sub_pos.2 h, ball_subset <| by rw [sub_sub_self]⟩
#align metric.exists_ball_subset_ball Metric.exists_ball_subset_ball
/-- If a property holds for all points in closed balls of arbitrarily large radii, then it holds for
all points. -/
theorem forall_of_forall_mem_closedBall (p : α → Prop) (x : α)
(H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ closedBall x R, p y) (y : α) : p y := by
obtain ⟨R, hR, h⟩ : ∃ R ≥ dist y x, ∀ z : α, z ∈ closedBall x R → p z :=
frequently_iff.1 H (Ici_mem_atTop (dist y x))
exact h _ hR
#align metric.forall_of_forall_mem_closed_ball Metric.forall_of_forall_mem_closedBall
/-- If a property holds for all points in balls of arbitrarily large radii, then it holds for all
points. -/
theorem forall_of_forall_mem_ball (p : α → Prop) (x : α)
(H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ ball x R, p y) (y : α) : p y := by
obtain ⟨R, hR, h⟩ : ∃ R > dist y x, ∀ z : α, z ∈ ball x R → p z :=
frequently_iff.1 H (Ioi_mem_atTop (dist y x))
exact h _ hR
#align metric.forall_of_forall_mem_ball Metric.forall_of_forall_mem_ball
theorem isBounded_iff {s : Set α} :
IsBounded s ↔ ∃ C : ℝ, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := by
rw [isBounded_def, ← Filter.mem_sets, @PseudoMetricSpace.cobounded_sets α, mem_setOf_eq,
compl_compl]
#align metric.is_bounded_iff Metric.isBounded_iff
theorem isBounded_iff_eventually {s : Set α} :
IsBounded s ↔ ∀ᶠ C in atTop, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C :=
isBounded_iff.trans
⟨fun ⟨C, h⟩ => eventually_atTop.2 ⟨C, fun _C' hC' _x hx _y hy => (h hx hy).trans hC'⟩,
Eventually.exists⟩
#align metric.is_bounded_iff_eventually Metric.isBounded_iff_eventually
theorem isBounded_iff_exists_ge {s : Set α} (c : ℝ) :
IsBounded s ↔ ∃ C, c ≤ C ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C :=
⟨fun h => ((eventually_ge_atTop c).and (isBounded_iff_eventually.1 h)).exists, fun h =>
isBounded_iff.2 <| h.imp fun _ => And.right⟩
#align metric.is_bounded_iff_exists_ge Metric.isBounded_iff_exists_ge
theorem isBounded_iff_nndist {s : Set α} :
IsBounded s ↔ ∃ C : ℝ≥0, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → nndist x y ≤ C := by
simp only [isBounded_iff_exists_ge 0, NNReal.exists, ← NNReal.coe_le_coe, ← dist_nndist,
NNReal.coe_mk, exists_prop]
#align metric.is_bounded_iff_nndist Metric.isBounded_iff_nndist
theorem toUniformSpace_eq :
‹PseudoMetricSpace α›.toUniformSpace = .ofDist dist dist_self dist_comm dist_triangle :=
UniformSpace.ext PseudoMetricSpace.uniformity_dist
#align metric.to_uniform_space_eq Metric.toUniformSpace_eq
theorem uniformity_basis_dist :
(𝓤 α).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { p : α × α | dist p.1 p.2 < ε } := by
rw [toUniformSpace_eq]
exact UniformSpace.hasBasis_ofFun (exists_gt _) _ _ _ _ _
#align metric.uniformity_basis_dist Metric.uniformity_basis_dist
/-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers
accumulating to zero, then `f i`-neighborhoods of the diagonal form a basis of `𝓤 α`.
For specific bases see `uniformity_basis_dist`, `uniformity_basis_dist_inv_nat_succ`,
and `uniformity_basis_dist_inv_nat_pos`. -/
protected theorem mk_uniformity_basis {β : Type*} {p : β → Prop} {f : β → ℝ}
(hf₀ : ∀ i, p i → 0 < f i) (hf : ∀ ⦃ε⦄, 0 < ε → ∃ i, p i ∧ f i ≤ ε) :
(𝓤 α).HasBasis p fun i => { p : α × α | dist p.1 p.2 < f i } := by
refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩
constructor
· rintro ⟨ε, ε₀, hε⟩
rcases hf ε₀ with ⟨i, hi, H⟩
exact ⟨i, hi, fun x (hx : _ < _) => hε <| lt_of_lt_of_le hx H⟩
· exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, H⟩
#align metric.mk_uniformity_basis Metric.mk_uniformity_basis
theorem uniformity_basis_dist_rat :
(𝓤 α).HasBasis (fun r : ℚ => 0 < r) fun r => { p : α × α | dist p.1 p.2 < r } :=
Metric.mk_uniformity_basis (fun _ => Rat.cast_pos.2) fun _ε hε =>
let ⟨r, hr0, hrε⟩ := exists_rat_btwn hε
⟨r, Rat.cast_pos.1 hr0, hrε.le⟩
#align metric.uniformity_basis_dist_rat Metric.uniformity_basis_dist_rat
theorem uniformity_basis_dist_inv_nat_succ :
(𝓤 α).HasBasis (fun _ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / (↑n + 1) } :=
Metric.mk_uniformity_basis (fun n _ => div_pos zero_lt_one <| Nat.cast_add_one_pos n) fun _ε ε0 =>
(exists_nat_one_div_lt ε0).imp fun _n hn => ⟨trivial, le_of_lt hn⟩
#align metric.uniformity_basis_dist_inv_nat_succ Metric.uniformity_basis_dist_inv_nat_succ
theorem uniformity_basis_dist_inv_nat_pos :
(𝓤 α).HasBasis (fun n : ℕ => 0 < n) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / ↑n } :=
Metric.mk_uniformity_basis (fun _ hn => div_pos zero_lt_one <| Nat.cast_pos.2 hn) fun _ ε0 =>
let ⟨n, hn⟩ := exists_nat_one_div_lt ε0
⟨n + 1, Nat.succ_pos n, mod_cast hn.le⟩
#align metric.uniformity_basis_dist_inv_nat_pos Metric.uniformity_basis_dist_inv_nat_pos
theorem uniformity_basis_dist_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < r ^ n } :=
Metric.mk_uniformity_basis (fun _ _ => pow_pos h0 _) fun _ε ε0 =>
let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1
⟨n, trivial, hn.le⟩
#align metric.uniformity_basis_dist_pow Metric.uniformity_basis_dist_pow
theorem uniformity_basis_dist_lt {R : ℝ} (hR : 0 < R) :
(𝓤 α).HasBasis (fun r : ℝ => 0 < r ∧ r < R) fun r => { p : α × α | dist p.1 p.2 < r } :=
Metric.mk_uniformity_basis (fun _ => And.left) fun r hr =>
⟨min r (R / 2), ⟨lt_min hr (half_pos hR), min_lt_iff.2 <| Or.inr (half_lt_self hR)⟩,
min_le_left _ _⟩
#align metric.uniformity_basis_dist_lt Metric.uniformity_basis_dist_lt
/-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers
accumulating to zero, then closed neighborhoods of the diagonal of sizes `{f i | p i}`
form a basis of `𝓤 α`.
Currently we have only one specific basis `uniformity_basis_dist_le` based on this constructor.
More can be easily added if needed in the future. -/
protected theorem mk_uniformity_basis_le {β : Type*} {p : β → Prop} {f : β → ℝ}
(hf₀ : ∀ x, p x → 0 < f x) (hf : ∀ ε, 0 < ε → ∃ x, p x ∧ f x ≤ ε) :
(𝓤 α).HasBasis p fun x => { p : α × α | dist p.1 p.2 ≤ f x } := by
refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩
constructor
· rintro ⟨ε, ε₀, hε⟩
rcases exists_between ε₀ with ⟨ε', hε'⟩
rcases hf ε' hε'.1 with ⟨i, hi, H⟩
exact ⟨i, hi, fun x (hx : _ ≤ _) => hε <| lt_of_le_of_lt (le_trans hx H) hε'.2⟩
· exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, fun x (hx : _ < _) => H (mem_setOf.2 hx.le)⟩
#align metric.mk_uniformity_basis_le Metric.mk_uniformity_basis_le
/-- Constant size closed neighborhoods of the diagonal form a basis
of the uniformity filter. -/
theorem uniformity_basis_dist_le :
(𝓤 α).HasBasis ((0 : ℝ) < ·) fun ε => { p : α × α | dist p.1 p.2 ≤ ε } :=
Metric.mk_uniformity_basis_le (fun _ => id) fun ε ε₀ => ⟨ε, ε₀, le_refl ε⟩
#align metric.uniformity_basis_dist_le Metric.uniformity_basis_dist_le
theorem uniformity_basis_dist_le_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 ≤ r ^ n } :=
Metric.mk_uniformity_basis_le (fun _ _ => pow_pos h0 _) fun _ε ε0 =>
let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1
⟨n, trivial, hn.le⟩
#align metric.uniformity_basis_dist_le_pow Metric.uniformity_basis_dist_le_pow
theorem mem_uniformity_dist {s : Set (α × α)} :
s ∈ 𝓤 α ↔ ∃ ε > 0, ∀ {a b : α}, dist a b < ε → (a, b) ∈ s :=
uniformity_basis_dist.mem_uniformity_iff
#align metric.mem_uniformity_dist Metric.mem_uniformity_dist
/-- A constant size neighborhood of the diagonal is an entourage. -/
theorem dist_mem_uniformity {ε : ℝ} (ε0 : 0 < ε) : { p : α × α | dist p.1 p.2 < ε } ∈ 𝓤 α :=
mem_uniformity_dist.2 ⟨ε, ε0, id⟩
#align metric.dist_mem_uniformity Metric.dist_mem_uniformity
theorem uniformContinuous_iff [PseudoMetricSpace β] {f : α → β} :
UniformContinuous f ↔ ∀ ε > 0, ∃ δ > 0, ∀ {a b : α}, dist a b < δ → dist (f a) (f b) < ε :=
uniformity_basis_dist.uniformContinuous_iff uniformity_basis_dist
#align metric.uniform_continuous_iff Metric.uniformContinuous_iff
theorem uniformContinuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} :
UniformContinuousOn f s ↔
∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y < δ → dist (f x) (f y) < ε :=
Metric.uniformity_basis_dist.uniformContinuousOn_iff Metric.uniformity_basis_dist
#align metric.uniform_continuous_on_iff Metric.uniformContinuousOn_iff
theorem uniformContinuousOn_iff_le [PseudoMetricSpace β] {f : α → β} {s : Set α} :
UniformContinuousOn f s ↔
∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y ≤ δ → dist (f x) (f y) ≤ ε :=
Metric.uniformity_basis_dist_le.uniformContinuousOn_iff Metric.uniformity_basis_dist_le
#align metric.uniform_continuous_on_iff_le Metric.uniformContinuousOn_iff_le
nonrec theorem uniformInducing_iff [PseudoMetricSpace β] {f : α → β} :
UniformInducing f ↔ UniformContinuous f ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ :=
uniformInducing_iff'.trans <| Iff.rfl.and <|
((uniformity_basis_dist.comap _).le_basis_iff uniformity_basis_dist).trans <| by
simp only [subset_def, Prod.forall, gt_iff_lt, preimage_setOf_eq, Prod.map_apply, mem_setOf]
nonrec theorem uniformEmbedding_iff [PseudoMetricSpace β] {f : α → β} :
UniformEmbedding f ↔ Function.Injective f ∧ UniformContinuous f ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ := by
rw [uniformEmbedding_iff, and_comm, uniformInducing_iff]
#align metric.uniform_embedding_iff Metric.uniformEmbedding_iff
/-- If a map between pseudometric spaces is a uniform embedding then the distance between `f x`
and `f y` is controlled in terms of the distance between `x` and `y`. -/
theorem controlled_of_uniformEmbedding [PseudoMetricSpace β] {f : α → β} (h : UniformEmbedding f) :
(∀ ε > 0, ∃ δ > 0, ∀ {a b : α}, dist a b < δ → dist (f a) (f b) < ε) ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ :=
⟨uniformContinuous_iff.1 h.uniformContinuous, (uniformEmbedding_iff.1 h).2.2⟩
#align metric.controlled_of_uniform_embedding Metric.controlled_of_uniformEmbedding
theorem totallyBounded_iff {s : Set α} :
TotallyBounded s ↔ ∀ ε > 0, ∃ t : Set α, t.Finite ∧ s ⊆ ⋃ y ∈ t, ball y ε :=
uniformity_basis_dist.totallyBounded_iff
#align metric.totally_bounded_iff Metric.totallyBounded_iff
/-- A pseudometric space is totally bounded if one can reconstruct up to any ε>0 any element of the
space from finitely many data. -/
theorem totallyBounded_of_finite_discretization {s : Set α}
(H : ∀ ε > (0 : ℝ),
∃ (β : Type u) (_ : Fintype β) (F : s → β), ∀ x y, F x = F y → dist (x : α) y < ε) :
TotallyBounded s := by
rcases s.eq_empty_or_nonempty with hs | hs
· rw [hs]
exact totallyBounded_empty
rcases hs with ⟨x0, hx0⟩
haveI : Inhabited s := ⟨⟨x0, hx0⟩⟩
refine totallyBounded_iff.2 fun ε ε0 => ?_
rcases H ε ε0 with ⟨β, fβ, F, hF⟩
let Finv := Function.invFun F
refine ⟨range (Subtype.val ∘ Finv), finite_range _, fun x xs => ?_⟩
let x' := Finv (F ⟨x, xs⟩)
have : F x' = F ⟨x, xs⟩ := Function.invFun_eq ⟨⟨x, xs⟩, rfl⟩
simp only [Set.mem_iUnion, Set.mem_range]
exact ⟨_, ⟨F ⟨x, xs⟩, rfl⟩, hF _ _ this.symm⟩
#align metric.totally_bounded_of_finite_discretization Metric.totallyBounded_of_finite_discretization
theorem finite_approx_of_totallyBounded {s : Set α} (hs : TotallyBounded s) :
∀ ε > 0, ∃ t, t ⊆ s ∧ Set.Finite t ∧ s ⊆ ⋃ y ∈ t, ball y ε := by
intro ε ε_pos
rw [totallyBounded_iff_subset] at hs
exact hs _ (dist_mem_uniformity ε_pos)
#align metric.finite_approx_of_totally_bounded Metric.finite_approx_of_totallyBounded
/-- Expressing uniform convergence using `dist` -/
theorem tendstoUniformlyOnFilter_iff {F : ι → β → α} {f : β → α} {p : Filter ι} {p' : Filter β} :
TendstoUniformlyOnFilter F f p p' ↔
∀ ε > 0, ∀ᶠ n : ι × β in p ×ˢ p', dist (f n.snd) (F n.fst n.snd) < ε := by
refine ⟨fun H ε hε => H _ (dist_mem_uniformity hε), fun H u hu => ?_⟩
rcases mem_uniformity_dist.1 hu with ⟨ε, εpos, hε⟩
exact (H ε εpos).mono fun n hn => hε hn
#align metric.tendsto_uniformly_on_filter_iff Metric.tendstoUniformlyOnFilter_iff
/-- Expressing locally uniform convergence on a set using `dist`. -/
theorem tendstoLocallyUniformlyOn_iff [TopologicalSpace β] {F : ι → β → α} {f : β → α}
{p : Filter ι} {s : Set β} :
TendstoLocallyUniformlyOn F f p s ↔
∀ ε > 0, ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, ∀ᶠ n in p, ∀ y ∈ t, dist (f y) (F n y) < ε := by
refine ⟨fun H ε hε => H _ (dist_mem_uniformity hε), fun H u hu x hx => ?_⟩
rcases mem_uniformity_dist.1 hu with ⟨ε, εpos, hε⟩
rcases H ε εpos x hx with ⟨t, ht, Ht⟩
exact ⟨t, ht, Ht.mono fun n hs x hx => hε (hs x hx)⟩
#align metric.tendsto_locally_uniformly_on_iff Metric.tendstoLocallyUniformlyOn_iff
/-- Expressing uniform convergence on a set using `dist`. -/
theorem tendstoUniformlyOn_iff {F : ι → β → α} {f : β → α} {p : Filter ι} {s : Set β} :
TendstoUniformlyOn F f p s ↔ ∀ ε > 0, ∀ᶠ n in p, ∀ x ∈ s, dist (f x) (F n x) < ε := by
refine ⟨fun H ε hε => H _ (dist_mem_uniformity hε), fun H u hu => ?_⟩
rcases mem_uniformity_dist.1 hu with ⟨ε, εpos, hε⟩
exact (H ε εpos).mono fun n hs x hx => hε (hs x hx)
#align metric.tendsto_uniformly_on_iff Metric.tendstoUniformlyOn_iff
/-- Expressing locally uniform convergence using `dist`. -/
theorem tendstoLocallyUniformly_iff [TopologicalSpace β] {F : ι → β → α} {f : β → α}
{p : Filter ι} :
TendstoLocallyUniformly F f p ↔
∀ ε > 0, ∀ x : β, ∃ t ∈ 𝓝 x, ∀ᶠ n in p, ∀ y ∈ t, dist (f y) (F n y) < ε := by
simp only [← tendstoLocallyUniformlyOn_univ, tendstoLocallyUniformlyOn_iff, nhdsWithin_univ,
mem_univ, forall_const, exists_prop]
#align metric.tendsto_locally_uniformly_iff Metric.tendstoLocallyUniformly_iff
/-- Expressing uniform convergence using `dist`. -/
theorem tendstoUniformly_iff {F : ι → β → α} {f : β → α} {p : Filter ι} :
TendstoUniformly F f p ↔ ∀ ε > 0, ∀ᶠ n in p, ∀ x, dist (f x) (F n x) < ε := by
rw [← tendstoUniformlyOn_univ, tendstoUniformlyOn_iff]
simp
#align metric.tendsto_uniformly_iff Metric.tendstoUniformly_iff
protected theorem cauchy_iff {f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ ε > 0, ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, dist x y < ε :=
uniformity_basis_dist.cauchy_iff
#align metric.cauchy_iff Metric.cauchy_iff
theorem nhds_basis_ball : (𝓝 x).HasBasis (0 < ·) (ball x) :=
nhds_basis_uniformity uniformity_basis_dist
#align metric.nhds_basis_ball Metric.nhds_basis_ball
theorem mem_nhds_iff : s ∈ 𝓝 x ↔ ∃ ε > 0, ball x ε ⊆ s :=
nhds_basis_ball.mem_iff
#align metric.mem_nhds_iff Metric.mem_nhds_iff
theorem eventually_nhds_iff {p : α → Prop} :
(∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ ⦃y⦄, dist y x < ε → p y :=
mem_nhds_iff
#align metric.eventually_nhds_iff Metric.eventually_nhds_iff
theorem eventually_nhds_iff_ball {p : α → Prop} :
(∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ y ∈ ball x ε, p y :=
mem_nhds_iff
#align metric.eventually_nhds_iff_ball Metric.eventually_nhds_iff_ball
/-- A version of `Filter.eventually_prod_iff` where the first filter consists of neighborhoods
in a pseudo-metric space. -/
theorem eventually_nhds_prod_iff {f : Filter ι} {x₀ : α} {p : α × ι → Prop} :
(∀ᶠ x in 𝓝 x₀ ×ˢ f, p x) ↔ ∃ ε > (0 : ℝ), ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧
∀ {x}, dist x x₀ < ε → ∀ {i}, pa i → p (x, i) := by
refine (nhds_basis_ball.prod f.basis_sets).eventually_iff.trans ?_
simp only [Prod.exists, forall_prod_set, id, mem_ball, and_assoc, exists_and_left, and_imp]
rfl
#align metric.eventually_nhds_prod_iff Metric.eventually_nhds_prod_iff
/-- A version of `Filter.eventually_prod_iff` where the second filter consists of neighborhoods
in a pseudo-metric space. -/
theorem eventually_prod_nhds_iff {f : Filter ι} {x₀ : α} {p : ι × α → Prop} :
(∀ᶠ x in f ×ˢ 𝓝 x₀, p x) ↔ ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧
∃ ε > 0, ∀ {i}, pa i → ∀ {x}, dist x x₀ < ε → p (i, x) := by
rw [eventually_swap_iff, Metric.eventually_nhds_prod_iff]
constructor <;>
· rintro ⟨a1, a2, a3, a4, a5⟩
exact ⟨a3, a4, a1, a2, fun b1 b2 b3 => a5 b3 b1⟩
#align metric.eventually_prod_nhds_iff Metric.eventually_prod_nhds_iff
theorem nhds_basis_closedBall : (𝓝 x).HasBasis (fun ε : ℝ => 0 < ε) (closedBall x) :=
nhds_basis_uniformity uniformity_basis_dist_le
#align metric.nhds_basis_closed_ball Metric.nhds_basis_closedBall
theorem nhds_basis_ball_inv_nat_succ :
(𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (1 / (↑n + 1)) :=
nhds_basis_uniformity uniformity_basis_dist_inv_nat_succ
#align metric.nhds_basis_ball_inv_nat_succ Metric.nhds_basis_ball_inv_nat_succ
theorem nhds_basis_ball_inv_nat_pos :
(𝓝 x).HasBasis (fun n => 0 < n) fun n : ℕ => ball x (1 / ↑n) :=
nhds_basis_uniformity uniformity_basis_dist_inv_nat_pos
#align metric.nhds_basis_ball_inv_nat_pos Metric.nhds_basis_ball_inv_nat_pos
theorem nhds_basis_ball_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (r ^ n) :=
nhds_basis_uniformity (uniformity_basis_dist_pow h0 h1)
#align metric.nhds_basis_ball_pow Metric.nhds_basis_ball_pow
theorem nhds_basis_closedBall_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓝 x).HasBasis (fun _ => True) fun n : ℕ => closedBall x (r ^ n) :=
nhds_basis_uniformity (uniformity_basis_dist_le_pow h0 h1)
#align metric.nhds_basis_closed_ball_pow Metric.nhds_basis_closedBall_pow
theorem isOpen_iff : IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ball x ε ⊆ s := by
simp only [isOpen_iff_mem_nhds, mem_nhds_iff]
#align metric.is_open_iff Metric.isOpen_iff
theorem isOpen_ball : IsOpen (ball x ε) :=
isOpen_iff.2 fun _ => exists_ball_subset_ball
#align metric.is_open_ball Metric.isOpen_ball
theorem ball_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : ball x ε ∈ 𝓝 x :=
isOpen_ball.mem_nhds (mem_ball_self ε0)
#align metric.ball_mem_nhds Metric.ball_mem_nhds
theorem closedBall_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : closedBall x ε ∈ 𝓝 x :=
mem_of_superset (ball_mem_nhds x ε0) ball_subset_closedBall
#align metric.closed_ball_mem_nhds Metric.closedBall_mem_nhds
theorem closedBall_mem_nhds_of_mem {x c : α} {ε : ℝ} (h : x ∈ ball c ε) : closedBall c ε ∈ 𝓝 x :=
mem_of_superset (isOpen_ball.mem_nhds h) ball_subset_closedBall
#align metric.closed_ball_mem_nhds_of_mem Metric.closedBall_mem_nhds_of_mem
theorem nhdsWithin_basis_ball {s : Set α} :
(𝓝[s] x).HasBasis (fun ε : ℝ => 0 < ε) fun ε => ball x ε ∩ s :=
nhdsWithin_hasBasis nhds_basis_ball s
#align metric.nhds_within_basis_ball Metric.nhdsWithin_basis_ball
theorem mem_nhdsWithin_iff {t : Set α} : s ∈ 𝓝[t] x ↔ ∃ ε > 0, ball x ε ∩ t ⊆ s :=
nhdsWithin_basis_ball.mem_iff
#align metric.mem_nhds_within_iff Metric.mem_nhdsWithin_iff
theorem tendsto_nhdsWithin_nhdsWithin [PseudoMetricSpace β] {t : Set β} {f : α → β} {a b} :
Tendsto f (𝓝[s] a) (𝓝[t] b) ↔
∀ ε > 0, ∃ δ > 0, ∀ {x : α}, x ∈ s → dist x a < δ → f x ∈ t ∧ dist (f x) b < ε :=
(nhdsWithin_basis_ball.tendsto_iff nhdsWithin_basis_ball).trans <| by
simp only [inter_comm _ s, inter_comm _ t, mem_inter_iff, and_imp, gt_iff_lt, mem_ball]
#align metric.tendsto_nhds_within_nhds_within Metric.tendsto_nhdsWithin_nhdsWithin
theorem tendsto_nhdsWithin_nhds [PseudoMetricSpace β] {f : α → β} {a b} :
Tendsto f (𝓝[s] a) (𝓝 b) ↔
∀ ε > 0, ∃ δ > 0, ∀ {x : α}, x ∈ s → dist x a < δ → dist (f x) b < ε := by
rw [← nhdsWithin_univ b, tendsto_nhdsWithin_nhdsWithin]
simp only [mem_univ, true_and_iff]
#align metric.tendsto_nhds_within_nhds Metric.tendsto_nhdsWithin_nhds
theorem tendsto_nhds_nhds [PseudoMetricSpace β] {f : α → β} {a b} :
Tendsto f (𝓝 a) (𝓝 b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ {x : α}, dist x a < δ → dist (f x) b < ε :=
nhds_basis_ball.tendsto_iff nhds_basis_ball
#align metric.tendsto_nhds_nhds Metric.tendsto_nhds_nhds
theorem continuousAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} :
ContinuousAt f a ↔ ∀ ε > 0, ∃ δ > 0, ∀ {x : α}, dist x a < δ → dist (f x) (f a) < ε := by
rw [ContinuousAt, tendsto_nhds_nhds]
#align metric.continuous_at_iff Metric.continuousAt_iff
theorem continuousWithinAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} {s : Set α} :
ContinuousWithinAt f s a ↔
∀ ε > 0, ∃ δ > 0, ∀ {x : α}, x ∈ s → dist x a < δ → dist (f x) (f a) < ε := by
rw [ContinuousWithinAt, tendsto_nhdsWithin_nhds]
#align metric.continuous_within_at_iff Metric.continuousWithinAt_iff
theorem continuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} :
ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∃ δ > 0, ∀ a ∈ s, dist a b < δ → dist (f a) (f b) < ε := by
simp [ContinuousOn, continuousWithinAt_iff]
#align metric.continuous_on_iff Metric.continuousOn_iff
theorem continuous_iff [PseudoMetricSpace β] {f : α → β} :
Continuous f ↔ ∀ b, ∀ ε > 0, ∃ δ > 0, ∀ a, dist a b < δ → dist (f a) (f b) < ε :=
continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds_nhds
#align metric.continuous_iff Metric.continuous_iff
theorem tendsto_nhds {f : Filter β} {u : β → α} {a : α} :
Tendsto u f (𝓝 a) ↔ ∀ ε > 0, ∀ᶠ x in f, dist (u x) a < ε :=
nhds_basis_ball.tendsto_right_iff
#align metric.tendsto_nhds Metric.tendsto_nhds
theorem continuousAt_iff' [TopologicalSpace β] {f : β → α} {b : β} :
ContinuousAt f b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝 b, dist (f x) (f b) < ε := by
rw [ContinuousAt, tendsto_nhds]
#align metric.continuous_at_iff' Metric.continuousAt_iff'
theorem continuousWithinAt_iff' [TopologicalSpace β] {f : β → α} {b : β} {s : Set β} :
ContinuousWithinAt f s b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by
rw [ContinuousWithinAt, tendsto_nhds]
#align metric.continuous_within_at_iff' Metric.continuousWithinAt_iff'
theorem continuousOn_iff' [TopologicalSpace β] {f : β → α} {s : Set β} :
ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by
simp [ContinuousOn, continuousWithinAt_iff']
#align metric.continuous_on_iff' Metric.continuousOn_iff'
theorem continuous_iff' [TopologicalSpace β] {f : β → α} :
Continuous f ↔ ∀ (a), ∀ ε > 0, ∀ᶠ x in 𝓝 a, dist (f x) (f a) < ε :=
continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds
#align metric.continuous_iff' Metric.continuous_iff'
theorem tendsto_atTop [Nonempty β] [SemilatticeSup β] {u : β → α} {a : α} :
Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n ≥ N, dist (u n) a < ε :=
(atTop_basis.tendsto_iff nhds_basis_ball).trans <| by
simp only [true_and, mem_ball, mem_Ici]
#align metric.tendsto_at_top Metric.tendsto_atTop
/-- A variant of `tendsto_atTop` that
uses `∃ N, ∀ n > N, ...` rather than `∃ N, ∀ n ≥ N, ...`
-/
theorem tendsto_atTop' [Nonempty β] [SemilatticeSup β] [NoMaxOrder β] {u : β → α} {a : α} :
Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n > N, dist (u n) a < ε :=
(atTop_basis_Ioi.tendsto_iff nhds_basis_ball).trans <| by
simp only [true_and, gt_iff_lt, mem_Ioi, mem_ball]
#align metric.tendsto_at_top' Metric.tendsto_atTop'
theorem isOpen_singleton_iff {α : Type*} [PseudoMetricSpace α] {x : α} :
IsOpen ({x} : Set α) ↔ ∃ ε > 0, ∀ y, dist y x < ε → y = x := by
simp [isOpen_iff, subset_singleton_iff, mem_ball]
#align metric.is_open_singleton_iff Metric.isOpen_singleton_iff
/-- Given a point `x` in a discrete subset `s` of a pseudometric space, there is an open ball
centered at `x` and intersecting `s` only at `x`. -/
theorem exists_ball_inter_eq_singleton_of_mem_discrete [DiscreteTopology s] {x : α} (hx : x ∈ s) :
∃ ε > 0, Metric.ball x ε ∩ s = {x} :=
nhds_basis_ball.exists_inter_eq_singleton_of_mem_discrete hx
#align metric.exists_ball_inter_eq_singleton_of_mem_discrete Metric.exists_ball_inter_eq_singleton_of_mem_discrete
/-- Given a point `x` in a discrete subset `s` of a pseudometric space, there is a closed ball
of positive radius centered at `x` and intersecting `s` only at `x`. -/
theorem exists_closedBall_inter_eq_singleton_of_discrete [DiscreteTopology s] {x : α} (hx : x ∈ s) :
∃ ε > 0, Metric.closedBall x ε ∩ s = {x} :=
nhds_basis_closedBall.exists_inter_eq_singleton_of_mem_discrete hx
#align metric.exists_closed_ball_inter_eq_singleton_of_discrete Metric.exists_closedBall_inter_eq_singleton_of_discrete
theorem _root_.Dense.exists_dist_lt {s : Set α} (hs : Dense s) (x : α) {ε : ℝ} (hε : 0 < ε) :
∃ y ∈ s, dist x y < ε := by
have : (ball x ε).Nonempty := by simp [hε]
simpa only [mem_ball'] using hs.exists_mem_open isOpen_ball this
#align dense.exists_dist_lt Dense.exists_dist_lt
nonrec theorem _root_.DenseRange.exists_dist_lt {β : Type*} {f : β → α} (hf : DenseRange f) (x : α)
{ε : ℝ} (hε : 0 < ε) : ∃ y, dist x (f y) < ε :=
exists_range_iff.1 (hf.exists_dist_lt x hε)
#align dense_range.exists_dist_lt DenseRange.exists_dist_lt
end Metric
open Metric
/- Instantiate a pseudometric space as a pseudoemetric space. Before we can state the instance,
we need to show that the uniform structure coming from the edistance and the
distance coincide. -/
-- Porting note (#10756): new theorem
theorem Metric.uniformity_edist_aux {α} (d : α → α → ℝ≥0) :
⨅ ε > (0 : ℝ), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } =
⨅ ε > (0 : ℝ≥0∞), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } := by
simp only [le_antisymm_iff, le_iInf_iff, le_principal_iff]
refine ⟨fun ε hε => ?_, fun ε hε => ?_⟩
· rcases ENNReal.lt_iff_exists_nnreal_btwn.1 hε with ⟨ε', ε'0, ε'ε⟩
refine mem_iInf_of_mem (ε' : ℝ) (mem_iInf_of_mem (ENNReal.coe_pos.1 ε'0) ?_)
exact fun x hx => lt_trans (ENNReal.coe_lt_coe.2 hx) ε'ε
· lift ε to ℝ≥0 using le_of_lt hε
refine mem_iInf_of_mem (ε : ℝ≥0∞) (mem_iInf_of_mem (ENNReal.coe_pos.2 hε) ?_)
exact fun _ => ENNReal.coe_lt_coe.1
theorem Metric.uniformity_edist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | edist p.1 p.2 < ε } := by
simp only [PseudoMetricSpace.uniformity_dist, dist_nndist, edist_nndist,
Metric.uniformity_edist_aux]
#align metric.uniformity_edist Metric.uniformity_edist
-- see Note [lower instance priority]
/-- A pseudometric space induces a pseudoemetric space -/
instance (priority := 100) PseudoMetricSpace.toPseudoEMetricSpace : PseudoEMetricSpace α :=
{ ‹PseudoMetricSpace α› with
edist_self := by simp [edist_dist]
edist_comm := fun _ _ => by simp only [edist_dist, dist_comm]
edist_triangle := fun x y z => by
simp only [edist_dist, ← ENNReal.ofReal_add, dist_nonneg]
rw [ENNReal.ofReal_le_ofReal_iff _]
· exact dist_triangle _ _ _
· simpa using add_le_add (dist_nonneg : 0 ≤ dist x y) dist_nonneg
uniformity_edist := Metric.uniformity_edist }
#align pseudo_metric_space.to_pseudo_emetric_space PseudoMetricSpace.toPseudoEMetricSpace
/-- Expressing the uniformity in terms of `edist` -/
@[deprecated _root_.uniformity_basis_edist]
protected theorem Metric.uniformity_basis_edist :
(𝓤 α).HasBasis (fun ε : ℝ≥0∞ => 0 < ε) fun ε => { p | edist p.1 p.2 < ε } :=
uniformity_basis_edist
#align pseudo_metric.uniformity_basis_edist Metric.uniformity_basis_edist
/-- In a pseudometric space, an open ball of infinite radius is the whole space -/
theorem Metric.eball_top_eq_univ (x : α) : EMetric.ball x ∞ = Set.univ :=
Set.eq_univ_iff_forall.mpr fun y => edist_lt_top y x
#align metric.eball_top_eq_univ Metric.eball_top_eq_univ
/-- Balls defined using the distance or the edistance coincide -/
@[simp]
theorem Metric.emetric_ball {x : α} {ε : ℝ} : EMetric.ball x (ENNReal.ofReal ε) = ball x ε := by
ext y
simp only [EMetric.mem_ball, mem_ball, edist_dist]
exact ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg
#align metric.emetric_ball Metric.emetric_ball
/-- Balls defined using the distance or the edistance coincide -/
@[simp]
theorem Metric.emetric_ball_nnreal {x : α} {ε : ℝ≥0} : EMetric.ball x ε = ball x ε := by
rw [← Metric.emetric_ball]
simp
#align metric.emetric_ball_nnreal Metric.emetric_ball_nnreal
/-- Closed balls defined using the distance or the edistance coincide -/
theorem Metric.emetric_closedBall {x : α} {ε : ℝ} (h : 0 ≤ ε) :
EMetric.closedBall x (ENNReal.ofReal ε) = closedBall x ε := by
ext y; simp [edist_le_ofReal h]
#align metric.emetric_closed_ball Metric.emetric_closedBall
/-- Closed balls defined using the distance or the edistance coincide -/
@[simp]
theorem Metric.emetric_closedBall_nnreal {x : α} {ε : ℝ≥0} :
EMetric.closedBall x ε = closedBall x ε := by
rw [← Metric.emetric_closedBall ε.coe_nonneg, ENNReal.ofReal_coe_nnreal]
#align metric.emetric_closed_ball_nnreal Metric.emetric_closedBall_nnreal
@[simp]
theorem Metric.emetric_ball_top (x : α) : EMetric.ball x ⊤ = univ :=
eq_univ_of_forall fun _ => edist_lt_top _ _
#align metric.emetric_ball_top Metric.emetric_ball_top
theorem Metric.inseparable_iff {x y : α} : Inseparable x y ↔ dist x y = 0 := by
rw [EMetric.inseparable_iff, edist_nndist, dist_nndist, ENNReal.coe_eq_zero, NNReal.coe_eq_zero]
#align metric.inseparable_iff Metric.inseparable_iff
/-- Build a new pseudometric space from an old one where the bundled uniform structure is provably
(but typically non-definitionaly) equal to some given uniform structure.
See Note [forgetful inheritance].
-/
abbrev PseudoMetricSpace.replaceUniformity {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : PseudoMetricSpace α :=
{ m with
toUniformSpace := U
uniformity_dist := H.trans PseudoMetricSpace.uniformity_dist }
#align pseudo_metric_space.replace_uniformity PseudoMetricSpace.replaceUniformity
theorem PseudoMetricSpace.replaceUniformity_eq {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : m.replaceUniformity H = m := by
ext
rfl
#align pseudo_metric_space.replace_uniformity_eq PseudoMetricSpace.replaceUniformity_eq
-- ensure that the bornology is unchanged when replacing the uniformity.
example {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) :
(PseudoMetricSpace.replaceUniformity m H).toBornology = m.toBornology := rfl
/-- Build a new pseudo metric space from an old one where the bundled topological structure is
provably (but typically non-definitionaly) equal to some given topological structure.
See Note [forgetful inheritance].
-/
abbrev PseudoMetricSpace.replaceTopology {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ)
(H : U = m.toUniformSpace.toTopologicalSpace) : PseudoMetricSpace γ :=
@PseudoMetricSpace.replaceUniformity γ (m.toUniformSpace.replaceTopology H) m rfl
#align pseudo_metric_space.replace_topology PseudoMetricSpace.replaceTopology
theorem PseudoMetricSpace.replaceTopology_eq {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ)
(H : U = m.toUniformSpace.toTopologicalSpace) : m.replaceTopology H = m := by
ext
rfl
#align pseudo_metric_space.replace_topology_eq PseudoMetricSpace.replaceTopology_eq
/-- One gets a pseudometric space from an emetric space if the edistance
is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the
uniformity are defeq in the pseudometric space and the pseudoemetric space. In this definition, the
distance is given separately, to be able to prescribe some expression which is not defeq to the
push-forward of the edistance to reals. See note [reducible non-instances]. -/
abbrev PseudoEMetricSpace.toPseudoMetricSpaceOfDist {α : Type u} [e : PseudoEMetricSpace α]
(dist : α → α → ℝ) (edist_ne_top : ∀ x y : α, edist x y ≠ ⊤)
(h : ∀ x y, dist x y = ENNReal.toReal (edist x y)) : PseudoMetricSpace α where
dist := dist
dist_self x := by simp [h]
dist_comm x y := by simp [h, edist_comm]
dist_triangle x y z := by
simp only [h]
exact ENNReal.toReal_le_add (edist_triangle _ _ _) (edist_ne_top _ _) (edist_ne_top _ _)
edist := edist
edist_dist _ _ := by simp only [h, ENNReal.ofReal_toReal (edist_ne_top _ _)]
toUniformSpace := e.toUniformSpace
uniformity_dist := e.uniformity_edist.trans <| by
simpa only [ENNReal.coe_toNNReal (edist_ne_top _ _), h]
using (Metric.uniformity_edist_aux fun x y : α => (edist x y).toNNReal).symm
#align pseudo_emetric_space.to_pseudo_metric_space_of_dist PseudoEMetricSpace.toPseudoMetricSpaceOfDist
/-- One gets a pseudometric space from an emetric space if the edistance
is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the
uniformity are defeq in the pseudometric space and the emetric space. -/
abbrev PseudoEMetricSpace.toPseudoMetricSpace {α : Type u} [PseudoEMetricSpace α]
(h : ∀ x y : α, edist x y ≠ ⊤) : PseudoMetricSpace α :=
PseudoEMetricSpace.toPseudoMetricSpaceOfDist (fun x y => ENNReal.toReal (edist x y)) h fun _ _ =>
rfl
#align pseudo_emetric_space.to_pseudo_metric_space PseudoEMetricSpace.toPseudoMetricSpace
/-- Build a new pseudometric space from an old one where the bundled bornology structure is provably
(but typically non-definitionaly) equal to some given bornology structure.
See Note [forgetful inheritance].
-/
abbrev PseudoMetricSpace.replaceBornology {α} [B : Bornology α] (m : PseudoMetricSpace α)
(H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) :
PseudoMetricSpace α :=
{ m with
toBornology := B
cobounded_sets := Set.ext <| compl_surjective.forall.2 fun s =>
(H s).trans <| by rw [isBounded_iff, mem_setOf_eq, compl_compl] }
#align pseudo_metric_space.replace_bornology PseudoMetricSpace.replaceBornology
theorem PseudoMetricSpace.replaceBornology_eq {α} [m : PseudoMetricSpace α] [B : Bornology α]
(H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) :
PseudoMetricSpace.replaceBornology _ H = m := by
ext
rfl
#align pseudo_metric_space.replace_bornology_eq PseudoMetricSpace.replaceBornology_eq
-- ensure that the uniformity is unchanged when replacing the bornology.
example {α} [B : Bornology α] (m : PseudoMetricSpace α)
(H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) :
(PseudoMetricSpace.replaceBornology m H).toUniformSpace = m.toUniformSpace := rfl
section Real
/-- Instantiate the reals as a pseudometric space. -/
instance Real.pseudoMetricSpace : PseudoMetricSpace ℝ where
dist x y := |x - y|
dist_self := by simp [abs_zero]
dist_comm x y := abs_sub_comm _ _
dist_triangle x y z := abs_sub_le _ _ _
edist_dist := fun x y => by exact ENNReal.coe_nnreal_eq _
#align real.pseudo_metric_space Real.pseudoMetricSpace
theorem Real.dist_eq (x y : ℝ) : dist x y = |x - y| := rfl
#align real.dist_eq Real.dist_eq
theorem Real.nndist_eq (x y : ℝ) : nndist x y = Real.nnabs (x - y) := rfl
#align real.nndist_eq Real.nndist_eq
theorem Real.nndist_eq' (x y : ℝ) : nndist x y = Real.nnabs (y - x) :=
nndist_comm _ _
#align real.nndist_eq' Real.nndist_eq'
theorem Real.dist_0_eq_abs (x : ℝ) : dist x 0 = |x| := by simp [Real.dist_eq]
#align real.dist_0_eq_abs Real.dist_0_eq_abs
theorem Real.sub_le_dist (x y : ℝ) : x - y ≤ dist x y := by
rw [Real.dist_eq, le_abs]
exact Or.inl (le_refl _)
| Mathlib/Topology/MetricSpace/PseudoMetric.lean | 1,360 | 1,361 | theorem Real.dist_left_le_of_mem_uIcc {x y z : ℝ} (h : y ∈ uIcc x z) : dist x y ≤ dist x z := by |
simpa only [dist_comm x] using abs_sub_left_of_mem_uIcc h
|
/-
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.Subalgebra
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.Artinian
#align_import algebra.lie.submodule from "leanprover-community/mathlib"@"9822b65bfc4ac74537d77ae318d27df1df662471"
/-!
# Lie submodules of a Lie algebra
In this file we define Lie submodules and Lie ideals, we construct the lattice structure on Lie
submodules and we use it to define various important operations, notably the Lie span of a subset
of a Lie module.
## Main definitions
* `LieSubmodule`
* `LieSubmodule.wellFounded_of_noetherian`
* `LieSubmodule.lieSpan`
* `LieSubmodule.map`
* `LieSubmodule.comap`
* `LieIdeal`
* `LieIdeal.map`
* `LieIdeal.comap`
## Tags
lie algebra, lie submodule, lie ideal, lattice structure
-/
universe u v w w₁ w₂
section LieSubmodule
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie submodule of a Lie module is a submodule that is closed under the Lie bracket.
This is a sufficient condition for the subset itself to form a Lie module. -/
structure LieSubmodule extends Submodule R M where
lie_mem : ∀ {x : L} {m : M}, m ∈ carrier → ⁅x, m⁆ ∈ carrier
#align lie_submodule LieSubmodule
attribute [nolint docBlame] LieSubmodule.toSubmodule
attribute [coe] LieSubmodule.toSubmodule
namespace LieSubmodule
variable {R L M}
variable (N N' : LieSubmodule R L M)
instance : SetLike (LieSubmodule R L M) M where
coe s := s.carrier
coe_injective' N O h := by cases N; cases O; congr; exact SetLike.coe_injective' h
instance : AddSubgroupClass (LieSubmodule R L M) M where
add_mem {N} _ _ := N.add_mem'
zero_mem N := N.zero_mem'
neg_mem {N} x hx := show -x ∈ N.toSubmodule from neg_mem hx
instance instSMulMemClass : SMulMemClass (LieSubmodule R L M) R M where
smul_mem {s} c _ h := s.smul_mem' c h
/-- The zero module is a Lie submodule of any Lie module. -/
instance : Zero (LieSubmodule R L M) :=
⟨{ (0 : Submodule R M) with
lie_mem := fun {x m} h ↦ by rw [(Submodule.mem_bot R).1 h]; apply lie_zero }⟩
instance : Inhabited (LieSubmodule R L M) :=
⟨0⟩
instance coeSubmodule : CoeOut (LieSubmodule R L M) (Submodule R M) :=
⟨toSubmodule⟩
#align lie_submodule.coe_submodule LieSubmodule.coeSubmodule
-- Syntactic tautology
#noalign lie_submodule.to_submodule_eq_coe
@[norm_cast]
theorem coe_toSubmodule : ((N : Submodule R M) : Set M) = N :=
rfl
#align lie_submodule.coe_to_submodule LieSubmodule.coe_toSubmodule
-- Porting note (#10618): `simp` can prove this after `mem_coeSubmodule` is added to the simp set,
-- but `dsimp` can't.
@[simp, nolint simpNF]
theorem mem_carrier {x : M} : x ∈ N.carrier ↔ x ∈ (N : Set M) :=
Iff.rfl
#align lie_submodule.mem_carrier LieSubmodule.mem_carrier
theorem mem_mk_iff (S : Set M) (h₁ h₂ h₃ h₄) {x : M} :
x ∈ (⟨⟨⟨⟨S, h₁⟩, h₂⟩, h₃⟩, h₄⟩ : LieSubmodule R L M) ↔ x ∈ S :=
Iff.rfl
#align lie_submodule.mem_mk_iff LieSubmodule.mem_mk_iff
@[simp]
theorem mem_mk_iff' (p : Submodule R M) (h) {x : M} :
x ∈ (⟨p, h⟩ : LieSubmodule R L M) ↔ x ∈ p :=
Iff.rfl
@[simp]
theorem mem_coeSubmodule {x : M} : x ∈ (N : Submodule R M) ↔ x ∈ N :=
Iff.rfl
#align lie_submodule.mem_coe_submodule LieSubmodule.mem_coeSubmodule
theorem mem_coe {x : M} : x ∈ (N : Set M) ↔ x ∈ N :=
Iff.rfl
#align lie_submodule.mem_coe LieSubmodule.mem_coe
@[simp]
protected theorem zero_mem : (0 : M) ∈ N :=
zero_mem N
#align lie_submodule.zero_mem LieSubmodule.zero_mem
-- Porting note (#10618): @[simp] can prove this
theorem mk_eq_zero {x} (h : x ∈ N) : (⟨x, h⟩ : N) = 0 ↔ x = 0 :=
Subtype.ext_iff_val
#align lie_submodule.mk_eq_zero LieSubmodule.mk_eq_zero
@[simp]
theorem coe_toSet_mk (S : Set M) (h₁ h₂ h₃ h₄) :
((⟨⟨⟨⟨S, h₁⟩, h₂⟩, h₃⟩, h₄⟩ : LieSubmodule R L M) : Set M) = S :=
rfl
#align lie_submodule.coe_to_set_mk LieSubmodule.coe_toSet_mk
theorem coe_toSubmodule_mk (p : Submodule R M) (h) :
(({ p with lie_mem := h } : LieSubmodule R L M) : Submodule R M) = p := by cases p; rfl
#align lie_submodule.coe_to_submodule_mk LieSubmodule.coe_toSubmodule_mk
theorem coeSubmodule_injective :
Function.Injective (toSubmodule : LieSubmodule R L M → Submodule R M) := fun x y h ↦ by
cases x; cases y; congr
#align lie_submodule.coe_submodule_injective LieSubmodule.coeSubmodule_injective
@[ext]
theorem ext (h : ∀ m, m ∈ N ↔ m ∈ N') : N = N' :=
SetLike.ext h
#align lie_submodule.ext LieSubmodule.ext
@[simp]
theorem coe_toSubmodule_eq_iff : (N : Submodule R M) = (N' : Submodule R M) ↔ N = N' :=
coeSubmodule_injective.eq_iff
#align lie_submodule.coe_to_submodule_eq_iff LieSubmodule.coe_toSubmodule_eq_iff
/-- Copy of a `LieSubmodule` with a new `carrier` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (s : Set M) (hs : s = ↑N) : LieSubmodule R L M where
carrier := s
-- Porting note: all the proofs below were in term mode
zero_mem' := by exact hs.symm ▸ N.zero_mem'
add_mem' x y := by rw [hs] at x y ⊢; exact N.add_mem' x y
smul_mem' := by exact hs.symm ▸ N.smul_mem'
lie_mem := by exact hs.symm ▸ N.lie_mem
#align lie_submodule.copy LieSubmodule.copy
@[simp]
theorem coe_copy (S : LieSubmodule R L M) (s : Set M) (hs : s = ↑S) : (S.copy s hs : Set M) = s :=
rfl
#align lie_submodule.coe_copy LieSubmodule.coe_copy
theorem copy_eq (S : LieSubmodule R L M) (s : Set M) (hs : s = ↑S) : S.copy s hs = S :=
SetLike.coe_injective hs
#align lie_submodule.copy_eq LieSubmodule.copy_eq
instance : LieRingModule L N where
bracket (x : L) (m : N) := ⟨⁅x, m.val⁆, N.lie_mem m.property⟩
add_lie := by intro x y m; apply SetCoe.ext; apply add_lie
lie_add := by intro x m n; apply SetCoe.ext; apply lie_add
leibniz_lie := by intro x y m; apply SetCoe.ext; apply leibniz_lie
instance module' {S : Type*} [Semiring S] [SMul S R] [Module S M] [IsScalarTower S R M] :
Module S N :=
N.toSubmodule.module'
#align lie_submodule.module' LieSubmodule.module'
instance : Module R N :=
N.toSubmodule.module
instance {S : Type*} [Semiring S] [SMul S R] [SMul Sᵐᵒᵖ R] [Module S M] [Module Sᵐᵒᵖ M]
[IsScalarTower S R M] [IsScalarTower Sᵐᵒᵖ R M] [IsCentralScalar S M] : IsCentralScalar S N :=
N.toSubmodule.isCentralScalar
instance instLieModule : LieModule R L N where
lie_smul := by intro t x y; apply SetCoe.ext; apply lie_smul
smul_lie := by intro t x y; apply SetCoe.ext; apply smul_lie
@[simp, norm_cast]
theorem coe_zero : ((0 : N) : M) = (0 : M) :=
rfl
#align lie_submodule.coe_zero LieSubmodule.coe_zero
@[simp, norm_cast]
theorem coe_add (m m' : N) : (↑(m + m') : M) = (m : M) + (m' : M) :=
rfl
#align lie_submodule.coe_add LieSubmodule.coe_add
@[simp, norm_cast]
theorem coe_neg (m : N) : (↑(-m) : M) = -(m : M) :=
rfl
#align lie_submodule.coe_neg LieSubmodule.coe_neg
@[simp, norm_cast]
theorem coe_sub (m m' : N) : (↑(m - m') : M) = (m : M) - (m' : M) :=
rfl
#align lie_submodule.coe_sub LieSubmodule.coe_sub
@[simp, norm_cast]
theorem coe_smul (t : R) (m : N) : (↑(t • m) : M) = t • (m : M) :=
rfl
#align lie_submodule.coe_smul LieSubmodule.coe_smul
@[simp, norm_cast]
theorem coe_bracket (x : L) (m : N) : (↑⁅x, m⁆ : M) = ⁅x, ↑m⁆ :=
rfl
#align lie_submodule.coe_bracket LieSubmodule.coe_bracket
instance [Subsingleton M] : Unique (LieSubmodule R L M) :=
⟨⟨0⟩, fun _ ↦ (coe_toSubmodule_eq_iff _ _).mp (Subsingleton.elim _ _)⟩
end LieSubmodule
section LieIdeal
/-- An ideal of a Lie algebra is a Lie submodule of the Lie algebra as a Lie module over itself. -/
abbrev LieIdeal :=
LieSubmodule R L L
#align lie_ideal LieIdeal
theorem lie_mem_right (I : LieIdeal R L) (x y : L) (h : y ∈ I) : ⁅x, y⁆ ∈ I :=
I.lie_mem h
#align lie_mem_right lie_mem_right
theorem lie_mem_left (I : LieIdeal R L) (x y : L) (h : x ∈ I) : ⁅x, y⁆ ∈ I := by
rw [← lie_skew, ← neg_lie]; apply lie_mem_right; assumption
#align lie_mem_left lie_mem_left
/-- An ideal of a Lie algebra is a Lie subalgebra. -/
def lieIdealSubalgebra (I : LieIdeal R L) : LieSubalgebra R L :=
{ I.toSubmodule with lie_mem' := by intro x y _ hy; apply lie_mem_right; exact hy }
#align lie_ideal_subalgebra lieIdealSubalgebra
instance : Coe (LieIdeal R L) (LieSubalgebra R L) :=
⟨lieIdealSubalgebra R L⟩
@[simp]
theorem LieIdeal.coe_toSubalgebra (I : LieIdeal R L) : ((I : LieSubalgebra R L) : Set L) = I :=
rfl
#align lie_ideal.coe_to_subalgebra LieIdeal.coe_toSubalgebra
@[simp]
theorem LieIdeal.coe_to_lieSubalgebra_to_submodule (I : LieIdeal R L) :
((I : LieSubalgebra R L) : Submodule R L) = LieSubmodule.toSubmodule I :=
rfl
#align lie_ideal.coe_to_lie_subalgebra_to_submodule LieIdeal.coe_to_lieSubalgebra_to_submodule
/-- An ideal of `L` is a Lie subalgebra of `L`, so it is a Lie ring. -/
instance LieIdeal.lieRing (I : LieIdeal R L) : LieRing I :=
LieSubalgebra.lieRing R L ↑I
#align lie_ideal.lie_ring LieIdeal.lieRing
/-- Transfer the `LieAlgebra` instance from the coercion `LieIdeal → LieSubalgebra`. -/
instance LieIdeal.lieAlgebra (I : LieIdeal R L) : LieAlgebra R I :=
LieSubalgebra.lieAlgebra R L ↑I
#align lie_ideal.lie_algebra LieIdeal.lieAlgebra
/-- Transfer the `LieRingModule` instance from the coercion `LieIdeal → LieSubalgebra`. -/
instance LieIdeal.lieRingModule {R L : Type*} [CommRing R] [LieRing L] [LieAlgebra R L]
(I : LieIdeal R L) [LieRingModule L M] : LieRingModule I M :=
LieSubalgebra.lieRingModule (I : LieSubalgebra R L)
#align lie_ideal.lie_ring_module LieIdeal.lieRingModule
@[simp]
theorem LieIdeal.coe_bracket_of_module {R L : Type*} [CommRing R] [LieRing L] [LieAlgebra R L]
(I : LieIdeal R L) [LieRingModule L M] (x : I) (m : M) : ⁅x, m⁆ = ⁅(↑x : L), m⁆ :=
LieSubalgebra.coe_bracket_of_module (I : LieSubalgebra R L) x m
#align lie_ideal.coe_bracket_of_module LieIdeal.coe_bracket_of_module
/-- Transfer the `LieModule` instance from the coercion `LieIdeal → LieSubalgebra`. -/
instance LieIdeal.lieModule (I : LieIdeal R L) : LieModule R I M :=
LieSubalgebra.lieModule (I : LieSubalgebra R L)
#align lie_ideal.lie_module LieIdeal.lieModule
end LieIdeal
variable {R M}
theorem Submodule.exists_lieSubmodule_coe_eq_iff (p : Submodule R M) :
(∃ N : LieSubmodule R L M, ↑N = p) ↔ ∀ (x : L) (m : M), m ∈ p → ⁅x, m⁆ ∈ p := by
constructor
· rintro ⟨N, rfl⟩ _ _; exact N.lie_mem
· intro h; use { p with lie_mem := @h }
#align submodule.exists_lie_submodule_coe_eq_iff Submodule.exists_lieSubmodule_coe_eq_iff
namespace LieSubalgebra
variable {L}
variable (K : LieSubalgebra R L)
/-- Given a Lie subalgebra `K ⊆ L`, if we view `L` as a `K`-module by restriction, it contains
a distinguished Lie submodule for the action of `K`, namely `K` itself. -/
def toLieSubmodule : LieSubmodule R K L :=
{ (K : Submodule R L) with lie_mem := fun {x _} hy ↦ K.lie_mem x.property hy }
#align lie_subalgebra.to_lie_submodule LieSubalgebra.toLieSubmodule
@[simp]
theorem coe_toLieSubmodule : (K.toLieSubmodule : Submodule R L) = K := rfl
#align lie_subalgebra.coe_to_lie_submodule LieSubalgebra.coe_toLieSubmodule
variable {K}
@[simp]
theorem mem_toLieSubmodule (x : L) : x ∈ K.toLieSubmodule ↔ x ∈ K :=
Iff.rfl
#align lie_subalgebra.mem_to_lie_submodule LieSubalgebra.mem_toLieSubmodule
theorem exists_lieIdeal_coe_eq_iff :
(∃ I : LieIdeal R L, ↑I = K) ↔ ∀ x y : L, y ∈ K → ⁅x, y⁆ ∈ K := by
simp only [← coe_to_submodule_eq_iff, LieIdeal.coe_to_lieSubalgebra_to_submodule,
Submodule.exists_lieSubmodule_coe_eq_iff L]
exact Iff.rfl
#align lie_subalgebra.exists_lie_ideal_coe_eq_iff LieSubalgebra.exists_lieIdeal_coe_eq_iff
theorem exists_nested_lieIdeal_coe_eq_iff {K' : LieSubalgebra R L} (h : K ≤ K') :
(∃ I : LieIdeal R K', ↑I = ofLe h) ↔ ∀ x y : L, x ∈ K' → y ∈ K → ⁅x, y⁆ ∈ K := by
simp only [exists_lieIdeal_coe_eq_iff, coe_bracket, mem_ofLe]
constructor
· intro h' x y hx hy; exact h' ⟨x, hx⟩ ⟨y, h hy⟩ hy
· rintro h' ⟨x, hx⟩ ⟨y, hy⟩ hy'; exact h' x y hx hy'
#align lie_subalgebra.exists_nested_lie_ideal_coe_eq_iff LieSubalgebra.exists_nested_lieIdeal_coe_eq_iff
end LieSubalgebra
end LieSubmodule
namespace LieSubmodule
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 (N N' : LieSubmodule R L M) (I J : LieIdeal R L)
section LatticeStructure
open Set
theorem coe_injective : Function.Injective ((↑) : LieSubmodule R L M → Set M) :=
SetLike.coe_injective
#align lie_submodule.coe_injective LieSubmodule.coe_injective
@[simp, norm_cast]
theorem coeSubmodule_le_coeSubmodule : (N : Submodule R M) ≤ N' ↔ N ≤ N' :=
Iff.rfl
#align lie_submodule.coe_submodule_le_coe_submodule LieSubmodule.coeSubmodule_le_coeSubmodule
instance : Bot (LieSubmodule R L M) :=
⟨0⟩
@[simp]
theorem bot_coe : ((⊥ : LieSubmodule R L M) : Set M) = {0} :=
rfl
#align lie_submodule.bot_coe LieSubmodule.bot_coe
@[simp]
theorem bot_coeSubmodule : ((⊥ : LieSubmodule R L M) : Submodule R M) = ⊥ :=
rfl
#align lie_submodule.bot_coe_submodule LieSubmodule.bot_coeSubmodule
@[simp]
theorem coeSubmodule_eq_bot_iff : (N : Submodule R M) = ⊥ ↔ N = ⊥ := by
rw [← coe_toSubmodule_eq_iff, bot_coeSubmodule]
@[simp] theorem mk_eq_bot_iff {N : Submodule R M} {h} :
(⟨N, h⟩ : LieSubmodule R L M) = ⊥ ↔ N = ⊥ := by
rw [← coe_toSubmodule_eq_iff, bot_coeSubmodule]
@[simp]
theorem mem_bot (x : M) : x ∈ (⊥ : LieSubmodule R L M) ↔ x = 0 :=
mem_singleton_iff
#align lie_submodule.mem_bot LieSubmodule.mem_bot
instance : Top (LieSubmodule R L M) :=
⟨{ (⊤ : Submodule R M) with lie_mem := fun {x m} _ ↦ mem_univ ⁅x, m⁆ }⟩
@[simp]
theorem top_coe : ((⊤ : LieSubmodule R L M) : Set M) = univ :=
rfl
#align lie_submodule.top_coe LieSubmodule.top_coe
@[simp]
theorem top_coeSubmodule : ((⊤ : LieSubmodule R L M) : Submodule R M) = ⊤ :=
rfl
#align lie_submodule.top_coe_submodule LieSubmodule.top_coeSubmodule
@[simp]
theorem coeSubmodule_eq_top_iff : (N : Submodule R M) = ⊤ ↔ N = ⊤ := by
rw [← coe_toSubmodule_eq_iff, top_coeSubmodule]
@[simp] theorem mk_eq_top_iff {N : Submodule R M} {h} :
(⟨N, h⟩ : LieSubmodule R L M) = ⊤ ↔ N = ⊤ := by
rw [← coe_toSubmodule_eq_iff, top_coeSubmodule]
@[simp]
theorem mem_top (x : M) : x ∈ (⊤ : LieSubmodule R L M) :=
mem_univ x
#align lie_submodule.mem_top LieSubmodule.mem_top
instance : Inf (LieSubmodule R L M) :=
⟨fun N N' ↦
{ (N ⊓ N' : Submodule R M) with
lie_mem := fun h ↦ mem_inter (N.lie_mem h.1) (N'.lie_mem h.2) }⟩
instance : InfSet (LieSubmodule R L M) :=
⟨fun S ↦
{ toSubmodule := sInf {(s : Submodule R M) | s ∈ S}
lie_mem := fun {x m} h ↦ by
simp only [Submodule.mem_carrier, mem_iInter, Submodule.sInf_coe, mem_setOf_eq,
forall_apply_eq_imp_iff₂, forall_exists_index, and_imp] at h ⊢
intro N hN; apply N.lie_mem (h N hN) }⟩
@[simp]
theorem inf_coe : (↑(N ⊓ N') : Set M) = ↑N ∩ ↑N' :=
rfl
#align lie_submodule.inf_coe LieSubmodule.inf_coe
@[norm_cast, simp]
theorem inf_coe_toSubmodule :
(↑(N ⊓ N') : Submodule R M) = (N : Submodule R M) ⊓ (N' : Submodule R M) :=
rfl
#align lie_submodule.inf_coe_to_submodule LieSubmodule.inf_coe_toSubmodule
@[simp]
theorem sInf_coe_toSubmodule (S : Set (LieSubmodule R L M)) :
(↑(sInf S) : Submodule R M) = sInf {(s : Submodule R M) | s ∈ S} :=
rfl
#align lie_submodule.Inf_coe_to_submodule LieSubmodule.sInf_coe_toSubmodule
theorem sInf_coe_toSubmodule' (S : Set (LieSubmodule R L M)) :
(↑(sInf S) : Submodule R M) = ⨅ N ∈ S, (N : Submodule R M) := by
rw [sInf_coe_toSubmodule, ← Set.image, sInf_image]
@[simp]
theorem iInf_coe_toSubmodule {ι} (p : ι → LieSubmodule R L M) :
(↑(⨅ i, p i) : Submodule R M) = ⨅ i, (p i : Submodule R M) := by
rw [iInf, sInf_coe_toSubmodule]; ext; simp
@[simp]
theorem sInf_coe (S : Set (LieSubmodule R L M)) : (↑(sInf S) : Set M) = ⋂ s ∈ S, (s : Set M) := by
rw [← LieSubmodule.coe_toSubmodule, sInf_coe_toSubmodule, Submodule.sInf_coe]
ext m
simp only [mem_iInter, mem_setOf_eq, forall_apply_eq_imp_iff₂, exists_imp,
and_imp, SetLike.mem_coe, mem_coeSubmodule]
#align lie_submodule.Inf_coe LieSubmodule.sInf_coe
@[simp]
theorem iInf_coe {ι} (p : ι → LieSubmodule R L M) : (↑(⨅ i, p i) : Set M) = ⋂ i, ↑(p i) := by
rw [iInf, sInf_coe]; simp only [Set.mem_range, Set.iInter_exists, Set.iInter_iInter_eq']
@[simp]
theorem mem_iInf {ι} (p : ι → LieSubmodule R L M) {x} : (x ∈ ⨅ i, p i) ↔ ∀ i, x ∈ p i := by
rw [← SetLike.mem_coe, iInf_coe, Set.mem_iInter]; rfl
instance : Sup (LieSubmodule R L M) where
sup N N' :=
{ toSubmodule := (N : Submodule R M) ⊔ (N' : Submodule R M)
lie_mem := by
rintro x m (hm : m ∈ (N : Submodule R M) ⊔ (N' : Submodule R M))
change ⁅x, m⁆ ∈ (N : Submodule R M) ⊔ (N' : Submodule R M)
rw [Submodule.mem_sup] at hm ⊢
obtain ⟨y, hy, z, hz, rfl⟩ := hm
exact ⟨⁅x, y⁆, N.lie_mem hy, ⁅x, z⁆, N'.lie_mem hz, (lie_add _ _ _).symm⟩ }
instance : SupSet (LieSubmodule R L M) where
sSup S :=
{ toSubmodule := sSup {(p : Submodule R M) | p ∈ S}
lie_mem := by
intro x m (hm : m ∈ sSup {(p : Submodule R M) | p ∈ S})
change ⁅x, m⁆ ∈ sSup {(p : Submodule R M) | p ∈ S}
obtain ⟨s, hs, hsm⟩ := Submodule.mem_sSup_iff_exists_finset.mp hm
clear hm
classical
induction' s using Finset.induction_on with q t hqt ih generalizing m
· replace hsm : m = 0 := by simpa using hsm
simp [hsm]
· rw [Finset.iSup_insert] at hsm
obtain ⟨m', hm', u, hu, rfl⟩ := Submodule.mem_sup.mp hsm
rw [lie_add]
refine add_mem ?_ (ih (Subset.trans (by simp) hs) hu)
obtain ⟨p, hp, rfl⟩ : ∃ p ∈ S, ↑p = q := hs (Finset.mem_insert_self q t)
suffices p ≤ sSup {(p : Submodule R M) | p ∈ S} by exact this (p.lie_mem hm')
exact le_sSup ⟨p, hp, rfl⟩ }
@[norm_cast, simp]
theorem sup_coe_toSubmodule :
(↑(N ⊔ N') : Submodule R M) = (N : Submodule R M) ⊔ (N' : Submodule R M) := by
rfl
#align lie_submodule.sup_coe_to_submodule LieSubmodule.sup_coe_toSubmodule
@[simp]
theorem sSup_coe_toSubmodule (S : Set (LieSubmodule R L M)) :
(↑(sSup S) : Submodule R M) = sSup {(s : Submodule R M) | s ∈ S} :=
rfl
theorem sSup_coe_toSubmodule' (S : Set (LieSubmodule R L M)) :
(↑(sSup S) : Submodule R M) = ⨆ N ∈ S, (N : Submodule R M) := by
rw [sSup_coe_toSubmodule, ← Set.image, sSup_image]
@[simp]
theorem iSup_coe_toSubmodule {ι} (p : ι → LieSubmodule R L M) :
(↑(⨆ i, p i) : Submodule R M) = ⨆ i, (p i : Submodule R M) := by
rw [iSup, sSup_coe_toSubmodule]; ext; simp [Submodule.mem_sSup, Submodule.mem_iSup]
/-- The set of Lie submodules of a Lie module form a complete lattice. -/
instance : CompleteLattice (LieSubmodule R L M) :=
{ coeSubmodule_injective.completeLattice toSubmodule sup_coe_toSubmodule inf_coe_toSubmodule
sSup_coe_toSubmodule' sInf_coe_toSubmodule' rfl rfl with
toPartialOrder := SetLike.instPartialOrder }
theorem mem_iSup_of_mem {ι} {b : M} {N : ι → LieSubmodule R L M} (i : ι) (h : b ∈ N i) :
b ∈ ⨆ i, N i :=
(le_iSup N i) h
lemma iSup_induction {ι} (N : ι → LieSubmodule R L M) {C : M → Prop} {x : M}
(hx : x ∈ ⨆ i, N i) (hN : ∀ i, ∀ y ∈ N i, C y) (h0 : C 0)
(hadd : ∀ y z, C y → C z → C (y + z)) : C x := by
rw [← LieSubmodule.mem_coeSubmodule, LieSubmodule.iSup_coe_toSubmodule] at hx
exact Submodule.iSup_induction (C := C) (fun i ↦ (N i : Submodule R M)) hx hN h0 hadd
@[elab_as_elim]
theorem iSup_induction' {ι} (N : ι → LieSubmodule R L M) {C : (x : M) → (x ∈ ⨆ i, N i) → Prop}
(hN : ∀ (i) (x) (hx : x ∈ N i), C x (mem_iSup_of_mem i hx)) (h0 : C 0 (zero_mem _))
(hadd : ∀ x y hx hy, C x hx → C y hy → C (x + y) (add_mem ‹_› ‹_›)) {x : M}
(hx : x ∈ ⨆ i, N i) : C x hx := by
refine Exists.elim ?_ fun (hx : x ∈ ⨆ i, N i) (hc : C x hx) => hc
refine iSup_induction N (C := fun x : M ↦ ∃ (hx : x ∈ ⨆ i, N i), C x hx) hx
(fun i x hx => ?_) ?_ fun x y => ?_
· exact ⟨_, hN _ _ hx⟩
· exact ⟨_, h0⟩
· rintro ⟨_, Cx⟩ ⟨_, Cy⟩
exact ⟨_, hadd _ _ _ _ Cx Cy⟩
theorem disjoint_iff_coe_toSubmodule :
Disjoint N N' ↔ Disjoint (N : Submodule R M) (N' : Submodule R M) := by
rw [disjoint_iff, disjoint_iff, ← coe_toSubmodule_eq_iff, inf_coe_toSubmodule, bot_coeSubmodule,
← disjoint_iff]
theorem codisjoint_iff_coe_toSubmodule :
Codisjoint N N' ↔ Codisjoint (N : Submodule R M) (N' : Submodule R M) := by
rw [codisjoint_iff, codisjoint_iff, ← coe_toSubmodule_eq_iff, sup_coe_toSubmodule,
top_coeSubmodule, ← codisjoint_iff]
theorem isCompl_iff_coe_toSubmodule :
IsCompl N N' ↔ IsCompl (N : Submodule R M) (N' : Submodule R M) := by
simp only [isCompl_iff, disjoint_iff_coe_toSubmodule, codisjoint_iff_coe_toSubmodule]
theorem independent_iff_coe_toSubmodule {ι : Type*} {N : ι → LieSubmodule R L M} :
CompleteLattice.Independent N ↔ CompleteLattice.Independent fun i ↦ (N i : Submodule R M) := by
simp [CompleteLattice.independent_def, disjoint_iff_coe_toSubmodule]
theorem iSup_eq_top_iff_coe_toSubmodule {ι : Sort*} {N : ι → LieSubmodule R L M} :
⨆ i, N i = ⊤ ↔ ⨆ i, (N i : Submodule R M) = ⊤ := by
rw [← iSup_coe_toSubmodule, ← top_coeSubmodule (L := L), coe_toSubmodule_eq_iff]
instance : Add (LieSubmodule R L M) where add := Sup.sup
instance : Zero (LieSubmodule R L M) where zero := ⊥
instance : AddCommMonoid (LieSubmodule R L M) where
add_assoc := sup_assoc
zero_add := bot_sup_eq
add_zero := sup_bot_eq
add_comm := sup_comm
nsmul := nsmulRec
@[simp]
theorem add_eq_sup : N + N' = N ⊔ N' :=
rfl
#align lie_submodule.add_eq_sup LieSubmodule.add_eq_sup
@[simp]
theorem mem_inf (x : M) : x ∈ N ⊓ N' ↔ x ∈ N ∧ x ∈ N' := by
rw [← mem_coeSubmodule, ← mem_coeSubmodule, ← mem_coeSubmodule, inf_coe_toSubmodule,
Submodule.mem_inf]
#align lie_submodule.mem_inf LieSubmodule.mem_inf
theorem mem_sup (x : M) : x ∈ N ⊔ N' ↔ ∃ y ∈ N, ∃ z ∈ N', y + z = x := by
rw [← mem_coeSubmodule, sup_coe_toSubmodule, Submodule.mem_sup]; exact Iff.rfl
#align lie_submodule.mem_sup LieSubmodule.mem_sup
nonrec theorem eq_bot_iff : N = ⊥ ↔ ∀ m : M, m ∈ N → m = 0 := by rw [eq_bot_iff]; exact Iff.rfl
#align lie_submodule.eq_bot_iff LieSubmodule.eq_bot_iff
instance subsingleton_of_bot : Subsingleton (LieSubmodule R L ↑(⊥ : LieSubmodule R L M)) := by
apply subsingleton_of_bot_eq_top
ext ⟨x, hx⟩; change x ∈ ⊥ at hx; rw [Submodule.mem_bot] at hx; subst hx
simp only [true_iff_iff, eq_self_iff_true, Submodule.mk_eq_zero, LieSubmodule.mem_bot, mem_top]
#align lie_submodule.subsingleton_of_bot LieSubmodule.subsingleton_of_bot
instance : IsModularLattice (LieSubmodule R L M) where
sup_inf_le_assoc_of_le _ _ := by
simp only [← coeSubmodule_le_coeSubmodule, sup_coe_toSubmodule, inf_coe_toSubmodule]
exact IsModularLattice.sup_inf_le_assoc_of_le _
variable (R L M)
/-- The natural functor that forgets the action of `L` as an order embedding. -/
@[simps] def toSubmodule_orderEmbedding : LieSubmodule R L M ↪o Submodule R M :=
{ toFun := (↑)
inj' := coeSubmodule_injective
map_rel_iff' := Iff.rfl }
theorem wellFounded_of_noetherian [IsNoetherian R M] :
WellFounded ((· > ·) : LieSubmodule R L M → LieSubmodule R L M → Prop) :=
RelHomClass.wellFounded (toSubmodule_orderEmbedding R L M).dual.ltEmbedding <|
isNoetherian_iff_wellFounded.mp inferInstance
#align lie_submodule.well_founded_of_noetherian LieSubmodule.wellFounded_of_noetherian
theorem wellFounded_of_isArtinian [IsArtinian R M] :
WellFounded ((· < ·) : LieSubmodule R L M → LieSubmodule R L M → Prop) :=
RelHomClass.wellFounded (toSubmodule_orderEmbedding R L M).ltEmbedding <|
IsArtinian.wellFounded_submodule_lt R M
instance [IsArtinian R M] : IsAtomic (LieSubmodule R L M) :=
isAtomic_of_orderBot_wellFounded_lt <| wellFounded_of_isArtinian R L M
@[simp]
| Mathlib/Algebra/Lie/Submodule.lean | 632 | 636 | theorem subsingleton_iff : Subsingleton (LieSubmodule R L M) ↔ Subsingleton M :=
have h : Subsingleton (LieSubmodule R L M) ↔ Subsingleton (Submodule R M) := by |
rw [← subsingleton_iff_bot_eq_top, ← subsingleton_iff_bot_eq_top, ← coe_toSubmodule_eq_iff,
top_coeSubmodule, bot_coeSubmodule]
h.trans <| Submodule.subsingleton_iff R
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Mario Carneiro
-/
import Mathlib.Data.Bool.Basic
import Mathlib.Data.Option.Defs
import Mathlib.Data.Prod.Basic
import Mathlib.Data.Sigma.Basic
import Mathlib.Data.Subtype
import Mathlib.Data.Sum.Basic
import Mathlib.Init.Data.Sigma.Basic
import Mathlib.Logic.Equiv.Defs
import Mathlib.Logic.Function.Conjugate
import Mathlib.Tactic.Lift
import Mathlib.Tactic.Convert
import Mathlib.Tactic.Contrapose
import Mathlib.Tactic.GeneralizeProofs
import Mathlib.Tactic.SimpRw
#align_import logic.equiv.basic from "leanprover-community/mathlib"@"cd391184c85986113f8c00844cfe6dda1d34be3d"
/-!
# Equivalence between types
In this file we continue the work on equivalences begun in `Logic/Equiv/Defs.lean`, defining
* canonical isomorphisms between various types: e.g.,
- `Equiv.sumEquivSigmaBool` is the canonical equivalence between the sum of two types `α ⊕ β`
and the sigma-type `Σ b : Bool, b.casesOn α β`;
- `Equiv.prodSumDistrib : α × (β ⊕ γ) ≃ (α × β) ⊕ (α × γ)` shows that type product and type sum
satisfy the distributive law up to a canonical equivalence;
* operations on equivalences: e.g.,
- `Equiv.prodCongr ea eb : α₁ × β₁ ≃ α₂ × β₂`: combine two equivalences `ea : α₁ ≃ α₂` and
`eb : β₁ ≃ β₂` using `Prod.map`.
More definitions of this kind can be found in other files.
E.g., `Data/Equiv/TransferInstance.lean` does it for many algebraic type classes like
`Group`, `Module`, etc.
## Tags
equivalence, congruence, bijective map
-/
set_option autoImplicit true
universe u
open Function
namespace Equiv
/-- `PProd α β` is equivalent to `α × β` -/
@[simps apply symm_apply]
def pprodEquivProd : PProd α β ≃ α × β where
toFun x := (x.1, x.2)
invFun x := ⟨x.1, x.2⟩
left_inv := fun _ => rfl
right_inv := fun _ => rfl
#align equiv.pprod_equiv_prod Equiv.pprodEquivProd
#align equiv.pprod_equiv_prod_apply Equiv.pprodEquivProd_apply
#align equiv.pprod_equiv_prod_symm_apply Equiv.pprodEquivProd_symm_apply
/-- Product of two equivalences, in terms of `PProd`. If `α ≃ β` and `γ ≃ δ`, then
`PProd α γ ≃ PProd β δ`. -/
-- Porting note: in Lean 3 this had `@[congr]`
@[simps apply]
def pprodCongr (e₁ : α ≃ β) (e₂ : γ ≃ δ) : PProd α γ ≃ PProd β δ where
toFun x := ⟨e₁ x.1, e₂ x.2⟩
invFun x := ⟨e₁.symm x.1, e₂.symm x.2⟩
left_inv := fun ⟨x, y⟩ => by simp
right_inv := fun ⟨x, y⟩ => by simp
#align equiv.pprod_congr Equiv.pprodCongr
#align equiv.pprod_congr_apply Equiv.pprodCongr_apply
/-- Combine two equivalences using `PProd` in the domain and `Prod` in the codomain. -/
@[simps! apply symm_apply]
def pprodProd (ea : α₁ ≃ α₂) (eb : β₁ ≃ β₂) :
PProd α₁ β₁ ≃ α₂ × β₂ :=
(ea.pprodCongr eb).trans pprodEquivProd
#align equiv.pprod_prod Equiv.pprodProd
#align equiv.pprod_prod_apply Equiv.pprodProd_apply
#align equiv.pprod_prod_symm_apply Equiv.pprodProd_symm_apply
/-- Combine two equivalences using `PProd` in the codomain and `Prod` in the domain. -/
@[simps! apply symm_apply]
def prodPProd (ea : α₁ ≃ α₂) (eb : β₁ ≃ β₂) :
α₁ × β₁ ≃ PProd α₂ β₂ :=
(ea.symm.pprodProd eb.symm).symm
#align equiv.prod_pprod Equiv.prodPProd
#align equiv.prod_pprod_symm_apply Equiv.prodPProd_symm_apply
#align equiv.prod_pprod_apply Equiv.prodPProd_apply
/-- `PProd α β` is equivalent to `PLift α × PLift β` -/
@[simps! apply symm_apply]
def pprodEquivProdPLift : PProd α β ≃ PLift α × PLift β :=
Equiv.plift.symm.pprodProd Equiv.plift.symm
#align equiv.pprod_equiv_prod_plift Equiv.pprodEquivProdPLift
#align equiv.pprod_equiv_prod_plift_symm_apply Equiv.pprodEquivProdPLift_symm_apply
#align equiv.pprod_equiv_prod_plift_apply Equiv.pprodEquivProdPLift_apply
/-- Product of two equivalences. If `α₁ ≃ α₂` and `β₁ ≃ β₂`, then `α₁ × β₁ ≃ α₂ × β₂`. This is
`Prod.map` as an equivalence. -/
-- Porting note: in Lean 3 there was also a @[congr] tag
@[simps (config := .asFn) apply]
def prodCongr (e₁ : α₁ ≃ α₂) (e₂ : β₁ ≃ β₂) : α₁ × β₁ ≃ α₂ × β₂ :=
⟨Prod.map e₁ e₂, Prod.map e₁.symm e₂.symm, fun ⟨a, b⟩ => by simp, fun ⟨a, b⟩ => by simp⟩
#align equiv.prod_congr Equiv.prodCongr
#align equiv.prod_congr_apply Equiv.prodCongr_apply
@[simp]
theorem prodCongr_symm (e₁ : α₁ ≃ α₂) (e₂ : β₁ ≃ β₂) :
(prodCongr e₁ e₂).symm = prodCongr e₁.symm e₂.symm :=
rfl
#align equiv.prod_congr_symm Equiv.prodCongr_symm
/-- Type product is commutative up to an equivalence: `α × β ≃ β × α`. This is `Prod.swap` as an
equivalence. -/
def prodComm (α β) : α × β ≃ β × α :=
⟨Prod.swap, Prod.swap, Prod.swap_swap, Prod.swap_swap⟩
#align equiv.prod_comm Equiv.prodComm
@[simp]
theorem coe_prodComm (α β) : (⇑(prodComm α β) : α × β → β × α) = Prod.swap :=
rfl
#align equiv.coe_prod_comm Equiv.coe_prodComm
@[simp]
theorem prodComm_apply (x : α × β) : prodComm α β x = x.swap :=
rfl
#align equiv.prod_comm_apply Equiv.prodComm_apply
@[simp]
theorem prodComm_symm (α β) : (prodComm α β).symm = prodComm β α :=
rfl
#align equiv.prod_comm_symm Equiv.prodComm_symm
/-- Type product is associative up to an equivalence. -/
@[simps]
def prodAssoc (α β γ) : (α × β) × γ ≃ α × β × γ :=
⟨fun p => (p.1.1, p.1.2, p.2), fun p => ((p.1, p.2.1), p.2.2), fun ⟨⟨_, _⟩, _⟩ => rfl,
fun ⟨_, ⟨_, _⟩⟩ => rfl⟩
#align equiv.prod_assoc Equiv.prodAssoc
#align equiv.prod_assoc_symm_apply Equiv.prodAssoc_symm_apply
#align equiv.prod_assoc_apply Equiv.prodAssoc_apply
/-- Four-way commutativity of `prod`. The name matches `mul_mul_mul_comm`. -/
@[simps apply]
def prodProdProdComm (α β γ δ : Type*) : (α × β) × γ × δ ≃ (α × γ) × β × δ where
toFun abcd := ((abcd.1.1, abcd.2.1), (abcd.1.2, abcd.2.2))
invFun acbd := ((acbd.1.1, acbd.2.1), (acbd.1.2, acbd.2.2))
left_inv := fun ⟨⟨_a, _b⟩, ⟨_c, _d⟩⟩ => rfl
right_inv := fun ⟨⟨_a, _c⟩, ⟨_b, _d⟩⟩ => rfl
#align equiv.prod_prod_prod_comm Equiv.prodProdProdComm
@[simp]
theorem prodProdProdComm_symm (α β γ δ : Type*) :
(prodProdProdComm α β γ δ).symm = prodProdProdComm α γ β δ :=
rfl
#align equiv.prod_prod_prod_comm_symm Equiv.prodProdProdComm_symm
/-- `γ`-valued functions on `α × β` are equivalent to functions `α → β → γ`. -/
@[simps (config := .asFn)]
def curry (α β γ) : (α × β → γ) ≃ (α → β → γ) where
toFun := Function.curry
invFun := uncurry
left_inv := uncurry_curry
right_inv := curry_uncurry
#align equiv.curry Equiv.curry
#align equiv.curry_symm_apply Equiv.curry_symm_apply
#align equiv.curry_apply Equiv.curry_apply
section
/-- `PUnit` is a right identity for type product up to an equivalence. -/
@[simps]
def prodPUnit (α) : α × PUnit ≃ α :=
⟨fun p => p.1, fun a => (a, PUnit.unit), fun ⟨_, PUnit.unit⟩ => rfl, fun _ => rfl⟩
#align equiv.prod_punit Equiv.prodPUnit
#align equiv.prod_punit_apply Equiv.prodPUnit_apply
#align equiv.prod_punit_symm_apply Equiv.prodPUnit_symm_apply
/-- `PUnit` is a left identity for type product up to an equivalence. -/
@[simps!]
def punitProd (α) : PUnit × α ≃ α :=
calc
PUnit × α ≃ α × PUnit := prodComm _ _
_ ≃ α := prodPUnit _
#align equiv.punit_prod Equiv.punitProd
#align equiv.punit_prod_symm_apply Equiv.punitProd_symm_apply
#align equiv.punit_prod_apply Equiv.punitProd_apply
/-- `PUnit` is a right identity for dependent type product up to an equivalence. -/
@[simps]
def sigmaPUnit (α) : (_ : α) × PUnit ≃ α :=
⟨fun p => p.1, fun a => ⟨a, PUnit.unit⟩, fun ⟨_, PUnit.unit⟩ => rfl, fun _ => rfl⟩
/-- Any `Unique` type is a right identity for type product up to equivalence. -/
def prodUnique (α β) [Unique β] : α × β ≃ α :=
((Equiv.refl α).prodCongr <| equivPUnit.{_,1} β).trans <| prodPUnit α
#align equiv.prod_unique Equiv.prodUnique
@[simp]
theorem coe_prodUnique [Unique β] : (⇑(prodUnique α β) : α × β → α) = Prod.fst :=
rfl
#align equiv.coe_prod_unique Equiv.coe_prodUnique
theorem prodUnique_apply [Unique β] (x : α × β) : prodUnique α β x = x.1 :=
rfl
#align equiv.prod_unique_apply Equiv.prodUnique_apply
@[simp]
theorem prodUnique_symm_apply [Unique β] (x : α) :
(prodUnique α β).symm x = (x, default) :=
rfl
#align equiv.prod_unique_symm_apply Equiv.prodUnique_symm_apply
/-- Any `Unique` type is a left identity for type product up to equivalence. -/
def uniqueProd (α β) [Unique β] : β × α ≃ α :=
((equivPUnit.{_,1} β).prodCongr <| Equiv.refl α).trans <| punitProd α
#align equiv.unique_prod Equiv.uniqueProd
@[simp]
theorem coe_uniqueProd [Unique β] : (⇑(uniqueProd α β) : β × α → α) = Prod.snd :=
rfl
#align equiv.coe_unique_prod Equiv.coe_uniqueProd
theorem uniqueProd_apply [Unique β] (x : β × α) : uniqueProd α β x = x.2 :=
rfl
#align equiv.unique_prod_apply Equiv.uniqueProd_apply
@[simp]
theorem uniqueProd_symm_apply [Unique β] (x : α) :
(uniqueProd α β).symm x = (default, x) :=
rfl
#align equiv.unique_prod_symm_apply Equiv.uniqueProd_symm_apply
/-- Any family of `Unique` types is a right identity for dependent type product up to
equivalence. -/
def sigmaUnique (α) (β : α → Type*) [∀ a, Unique (β a)] : (a : α) × (β a) ≃ α :=
(Equiv.sigmaCongrRight fun a ↦ equivPUnit.{_,1} (β a)).trans <| sigmaPUnit α
@[simp]
theorem coe_sigmaUnique {β : α → Type*} [∀ a, Unique (β a)] :
(⇑(sigmaUnique α β) : (a : α) × (β a) → α) = Sigma.fst :=
rfl
theorem sigmaUnique_apply {β : α → Type*} [∀ a, Unique (β a)] (x : (a : α) × β a) :
sigmaUnique α β x = x.1 :=
rfl
@[simp]
theorem sigmaUnique_symm_apply {β : α → Type*} [∀ a, Unique (β a)] (x : α) :
(sigmaUnique α β).symm x = ⟨x, default⟩ :=
rfl
/-- `Empty` type is a right absorbing element for type product up to an equivalence. -/
def prodEmpty (α) : α × Empty ≃ Empty :=
equivEmpty _
#align equiv.prod_empty Equiv.prodEmpty
/-- `Empty` type is a left absorbing element for type product up to an equivalence. -/
def emptyProd (α) : Empty × α ≃ Empty :=
equivEmpty _
#align equiv.empty_prod Equiv.emptyProd
/-- `PEmpty` type is a right absorbing element for type product up to an equivalence. -/
def prodPEmpty (α) : α × PEmpty ≃ PEmpty :=
equivPEmpty _
#align equiv.prod_pempty Equiv.prodPEmpty
/-- `PEmpty` type is a left absorbing element for type product up to an equivalence. -/
def pemptyProd (α) : PEmpty × α ≃ PEmpty :=
equivPEmpty _
#align equiv.pempty_prod Equiv.pemptyProd
end
section
open Sum
/-- `PSum` is equivalent to `Sum`. -/
def psumEquivSum (α β) : PSum α β ≃ Sum α β where
toFun s := PSum.casesOn s inl inr
invFun := Sum.elim PSum.inl PSum.inr
left_inv s := by cases s <;> rfl
right_inv s := by cases s <;> rfl
#align equiv.psum_equiv_sum Equiv.psumEquivSum
/-- If `α ≃ α'` and `β ≃ β'`, then `α ⊕ β ≃ α' ⊕ β'`. This is `Sum.map` as an equivalence. -/
@[simps apply]
def sumCongr (ea : α₁ ≃ α₂) (eb : β₁ ≃ β₂) : Sum α₁ β₁ ≃ Sum α₂ β₂ :=
⟨Sum.map ea eb, Sum.map ea.symm eb.symm, fun x => by simp, fun x => by simp⟩
#align equiv.sum_congr Equiv.sumCongr
#align equiv.sum_congr_apply Equiv.sumCongr_apply
/-- If `α ≃ α'` and `β ≃ β'`, then `PSum α β ≃ PSum α' β'`. -/
def psumCongr (e₁ : α ≃ β) (e₂ : γ ≃ δ) : PSum α γ ≃ PSum β δ where
toFun x := PSum.casesOn x (PSum.inl ∘ e₁) (PSum.inr ∘ e₂)
invFun x := PSum.casesOn x (PSum.inl ∘ e₁.symm) (PSum.inr ∘ e₂.symm)
left_inv := by rintro (x | x) <;> simp
right_inv := by rintro (x | x) <;> simp
#align equiv.psum_congr Equiv.psumCongr
/-- Combine two `Equiv`s using `PSum` in the domain and `Sum` in the codomain. -/
def psumSum (ea : α₁ ≃ α₂) (eb : β₁ ≃ β₂) :
PSum α₁ β₁ ≃ Sum α₂ β₂ :=
(ea.psumCongr eb).trans (psumEquivSum _ _)
#align equiv.psum_sum Equiv.psumSum
/-- Combine two `Equiv`s using `Sum` in the domain and `PSum` in the codomain. -/
def sumPSum (ea : α₁ ≃ α₂) (eb : β₁ ≃ β₂) :
Sum α₁ β₁ ≃ PSum α₂ β₂ :=
(ea.symm.psumSum eb.symm).symm
#align equiv.sum_psum Equiv.sumPSum
@[simp]
theorem sumCongr_trans (e : α₁ ≃ β₁) (f : α₂ ≃ β₂) (g : β₁ ≃ γ₁) (h : β₂ ≃ γ₂) :
(Equiv.sumCongr e f).trans (Equiv.sumCongr g h) = Equiv.sumCongr (e.trans g) (f.trans h) := by
ext i
cases i <;> rfl
#align equiv.sum_congr_trans Equiv.sumCongr_trans
@[simp]
theorem sumCongr_symm (e : α ≃ β) (f : γ ≃ δ) :
(Equiv.sumCongr e f).symm = Equiv.sumCongr e.symm f.symm :=
rfl
#align equiv.sum_congr_symm Equiv.sumCongr_symm
@[simp]
theorem sumCongr_refl : Equiv.sumCongr (Equiv.refl α) (Equiv.refl β) = Equiv.refl (Sum α β) := by
ext i
cases i <;> rfl
#align equiv.sum_congr_refl Equiv.sumCongr_refl
/-- A subtype of a sum is equivalent to a sum of subtypes. -/
def subtypeSum {p : α ⊕ β → Prop} : {c // p c} ≃ {a // p (Sum.inl a)} ⊕ {b // p (Sum.inr b)} where
toFun c := match h : c.1 with
| Sum.inl a => Sum.inl ⟨a, h ▸ c.2⟩
| Sum.inr b => Sum.inr ⟨b, h ▸ c.2⟩
invFun c := match c with
| Sum.inl a => ⟨Sum.inl a, a.2⟩
| Sum.inr b => ⟨Sum.inr b, b.2⟩
left_inv := by rintro ⟨a | b, h⟩ <;> rfl
right_inv := by rintro (a | b) <;> rfl
namespace Perm
/-- Combine a permutation of `α` and of `β` into a permutation of `α ⊕ β`. -/
abbrev sumCongr (ea : Equiv.Perm α) (eb : Equiv.Perm β) : Equiv.Perm (Sum α β) :=
Equiv.sumCongr ea eb
#align equiv.perm.sum_congr Equiv.Perm.sumCongr
@[simp]
theorem sumCongr_apply (ea : Equiv.Perm α) (eb : Equiv.Perm β) (x : Sum α β) :
sumCongr ea eb x = Sum.map (⇑ea) (⇑eb) x :=
Equiv.sumCongr_apply ea eb x
#align equiv.perm.sum_congr_apply Equiv.Perm.sumCongr_apply
-- Porting note: it seems the general theorem about `Equiv` is now applied, so there's no need
-- to have this version also have `@[simp]`. Similarly for below.
theorem sumCongr_trans (e : Equiv.Perm α) (f : Equiv.Perm β) (g : Equiv.Perm α)
(h : Equiv.Perm β) : (sumCongr e f).trans (sumCongr g h) = sumCongr (e.trans g) (f.trans h) :=
Equiv.sumCongr_trans e f g h
#align equiv.perm.sum_congr_trans Equiv.Perm.sumCongr_trans
theorem sumCongr_symm (e : Equiv.Perm α) (f : Equiv.Perm β) :
(sumCongr e f).symm = sumCongr e.symm f.symm :=
Equiv.sumCongr_symm e f
#align equiv.perm.sum_congr_symm Equiv.Perm.sumCongr_symm
theorem sumCongr_refl : sumCongr (Equiv.refl α) (Equiv.refl β) = Equiv.refl (Sum α β) :=
Equiv.sumCongr_refl
#align equiv.perm.sum_congr_refl Equiv.Perm.sumCongr_refl
end Perm
/-- `Bool` is equivalent the sum of two `PUnit`s. -/
def boolEquivPUnitSumPUnit : Bool ≃ Sum PUnit.{u + 1} PUnit.{v + 1} :=
⟨fun b => b.casesOn (inl PUnit.unit) (inr PUnit.unit) , Sum.elim (fun _ => false) fun _ => true,
fun b => by cases b <;> rfl, fun s => by rcases s with (⟨⟨⟩⟩ | ⟨⟨⟩⟩) <;> rfl⟩
#align equiv.bool_equiv_punit_sum_punit Equiv.boolEquivPUnitSumPUnit
/-- Sum of types is commutative up to an equivalence. This is `Sum.swap` as an equivalence. -/
@[simps (config := .asFn) apply]
def sumComm (α β) : Sum α β ≃ Sum β α :=
⟨Sum.swap, Sum.swap, Sum.swap_swap, Sum.swap_swap⟩
#align equiv.sum_comm Equiv.sumComm
#align equiv.sum_comm_apply Equiv.sumComm_apply
@[simp]
theorem sumComm_symm (α β) : (sumComm α β).symm = sumComm β α :=
rfl
#align equiv.sum_comm_symm Equiv.sumComm_symm
/-- Sum of types is associative up to an equivalence. -/
def sumAssoc (α β γ) : Sum (Sum α β) γ ≃ Sum α (Sum β γ) :=
⟨Sum.elim (Sum.elim Sum.inl (Sum.inr ∘ Sum.inl)) (Sum.inr ∘ Sum.inr),
Sum.elim (Sum.inl ∘ Sum.inl) <| Sum.elim (Sum.inl ∘ Sum.inr) Sum.inr,
by rintro (⟨_ | _⟩ | _) <;> rfl, by
rintro (_ | ⟨_ | _⟩) <;> rfl⟩
#align equiv.sum_assoc Equiv.sumAssoc
@[simp]
theorem sumAssoc_apply_inl_inl (a) : sumAssoc α β γ (inl (inl a)) = inl a :=
rfl
#align equiv.sum_assoc_apply_inl_inl Equiv.sumAssoc_apply_inl_inl
@[simp]
theorem sumAssoc_apply_inl_inr (b) : sumAssoc α β γ (inl (inr b)) = inr (inl b) :=
rfl
#align equiv.sum_assoc_apply_inl_inr Equiv.sumAssoc_apply_inl_inr
@[simp]
theorem sumAssoc_apply_inr (c) : sumAssoc α β γ (inr c) = inr (inr c) :=
rfl
#align equiv.sum_assoc_apply_inr Equiv.sumAssoc_apply_inr
@[simp]
theorem sumAssoc_symm_apply_inl {α β γ} (a) : (sumAssoc α β γ).symm (inl a) = inl (inl a) :=
rfl
#align equiv.sum_assoc_symm_apply_inl Equiv.sumAssoc_symm_apply_inl
@[simp]
theorem sumAssoc_symm_apply_inr_inl {α β γ} (b) :
(sumAssoc α β γ).symm (inr (inl b)) = inl (inr b) :=
rfl
#align equiv.sum_assoc_symm_apply_inr_inl Equiv.sumAssoc_symm_apply_inr_inl
@[simp]
theorem sumAssoc_symm_apply_inr_inr {α β γ} (c) : (sumAssoc α β γ).symm (inr (inr c)) = inr c :=
rfl
#align equiv.sum_assoc_symm_apply_inr_inr Equiv.sumAssoc_symm_apply_inr_inr
/-- Sum with `IsEmpty` is equivalent to the original type. -/
@[simps symm_apply]
def sumEmpty (α β) [IsEmpty β] : Sum α β ≃ α where
toFun := Sum.elim id isEmptyElim
invFun := inl
left_inv s := by
rcases s with (_ | x)
· rfl
· exact isEmptyElim x
right_inv _ := rfl
#align equiv.sum_empty Equiv.sumEmpty
#align equiv.sum_empty_symm_apply Equiv.sumEmpty_symm_apply
@[simp]
theorem sumEmpty_apply_inl [IsEmpty β] (a : α) : sumEmpty α β (Sum.inl a) = a :=
rfl
#align equiv.sum_empty_apply_inl Equiv.sumEmpty_apply_inl
/-- The sum of `IsEmpty` with any type is equivalent to that type. -/
@[simps! symm_apply]
def emptySum (α β) [IsEmpty α] : Sum α β ≃ β :=
(sumComm _ _).trans <| sumEmpty _ _
#align equiv.empty_sum Equiv.emptySum
#align equiv.empty_sum_symm_apply Equiv.emptySum_symm_apply
@[simp]
theorem emptySum_apply_inr [IsEmpty α] (b : β) : emptySum α β (Sum.inr b) = b :=
rfl
#align equiv.empty_sum_apply_inr Equiv.emptySum_apply_inr
/-- `Option α` is equivalent to `α ⊕ PUnit` -/
def optionEquivSumPUnit (α) : Option α ≃ Sum α PUnit :=
⟨fun o => o.elim (inr PUnit.unit) inl, fun s => s.elim some fun _ => none,
fun o => by cases o <;> rfl,
fun s => by rcases s with (_ | ⟨⟨⟩⟩) <;> rfl⟩
#align equiv.option_equiv_sum_punit Equiv.optionEquivSumPUnit
@[simp]
theorem optionEquivSumPUnit_none : optionEquivSumPUnit α none = Sum.inr PUnit.unit :=
rfl
#align equiv.option_equiv_sum_punit_none Equiv.optionEquivSumPUnit_none
@[simp]
theorem optionEquivSumPUnit_some (a) : optionEquivSumPUnit α (some a) = Sum.inl a :=
rfl
#align equiv.option_equiv_sum_punit_some Equiv.optionEquivSumPUnit_some
@[simp]
theorem optionEquivSumPUnit_coe (a : α) : optionEquivSumPUnit α a = Sum.inl a :=
rfl
#align equiv.option_equiv_sum_punit_coe Equiv.optionEquivSumPUnit_coe
@[simp]
theorem optionEquivSumPUnit_symm_inl (a) : (optionEquivSumPUnit α).symm (Sum.inl a) = a :=
rfl
#align equiv.option_equiv_sum_punit_symm_inl Equiv.optionEquivSumPUnit_symm_inl
@[simp]
theorem optionEquivSumPUnit_symm_inr (a) : (optionEquivSumPUnit α).symm (Sum.inr a) = none :=
rfl
#align equiv.option_equiv_sum_punit_symm_inr Equiv.optionEquivSumPUnit_symm_inr
/-- The set of `x : Option α` such that `isSome x` is equivalent to `α`. -/
@[simps]
def optionIsSomeEquiv (α) : { x : Option α // x.isSome } ≃ α where
toFun o := Option.get _ o.2
invFun x := ⟨some x, rfl⟩
left_inv _ := Subtype.eq <| Option.some_get _
right_inv _ := Option.get_some _ _
#align equiv.option_is_some_equiv Equiv.optionIsSomeEquiv
#align equiv.option_is_some_equiv_apply Equiv.optionIsSomeEquiv_apply
#align equiv.option_is_some_equiv_symm_apply_coe Equiv.optionIsSomeEquiv_symm_apply_coe
/-- The product over `Option α` of `β a` is the binary product of the
product over `α` of `β (some α)` and `β none` -/
@[simps]
def piOptionEquivProd {β : Option α → Type*} :
(∀ a : Option α, β a) ≃ β none × ∀ a : α, β (some a) where
toFun f := (f none, fun a => f (some a))
invFun x a := Option.casesOn a x.fst x.snd
left_inv f := funext fun a => by cases a <;> rfl
right_inv x := by simp
#align equiv.pi_option_equiv_prod Equiv.piOptionEquivProd
#align equiv.pi_option_equiv_prod_symm_apply Equiv.piOptionEquivProd_symm_apply
#align equiv.pi_option_equiv_prod_apply Equiv.piOptionEquivProd_apply
/-- `α ⊕ β` is equivalent to a `Sigma`-type over `Bool`. Note that this definition assumes `α` and
`β` to be types from the same universe, so it cannot be used directly to transfer theorems about
sigma types to theorems about sum types. In many cases one can use `ULift` to work around this
difficulty. -/
def sumEquivSigmaBool (α β : Type u) : Sum α β ≃ Σ b : Bool, b.casesOn α β :=
⟨fun s => s.elim (fun x => ⟨false, x⟩) fun x => ⟨true, x⟩, fun s =>
match s with
| ⟨false, a⟩ => inl a
| ⟨true, b⟩ => inr b,
fun s => by cases s <;> rfl, fun s => by rcases s with ⟨_ | _, _⟩ <;> rfl⟩
#align equiv.sum_equiv_sigma_bool Equiv.sumEquivSigmaBool
-- See also `Equiv.sigmaPreimageEquiv`.
/-- `sigmaFiberEquiv f` for `f : α → β` is the natural equivalence between
the type of all fibres of `f` and the total space `α`. -/
@[simps]
def sigmaFiberEquiv {α β : Type*} (f : α → β) : (Σ y : β, { x // f x = y }) ≃ α :=
⟨fun x => ↑x.2, fun x => ⟨f x, x, rfl⟩, fun ⟨_, _, rfl⟩ => rfl, fun _ => rfl⟩
#align equiv.sigma_fiber_equiv Equiv.sigmaFiberEquiv
#align equiv.sigma_fiber_equiv_apply Equiv.sigmaFiberEquiv_apply
#align equiv.sigma_fiber_equiv_symm_apply_fst Equiv.sigmaFiberEquiv_symm_apply_fst
#align equiv.sigma_fiber_equiv_symm_apply_snd_coe Equiv.sigmaFiberEquiv_symm_apply_snd_coe
/-- Inhabited types are equivalent to `Option β` for some `β` by identifying `default` with `none`.
-/
def sigmaEquivOptionOfInhabited (α : Type u) [Inhabited α] [DecidableEq α] :
Σ β : Type u, α ≃ Option β where
fst := {a // a ≠ default}
snd.toFun a := if h : a = default then none else some ⟨a, h⟩
snd.invFun := Option.elim' default (↑)
snd.left_inv a := by dsimp only; split_ifs <;> simp [*]
snd.right_inv
| none => by simp
| some ⟨a, ha⟩ => dif_neg ha
#align equiv.sigma_equiv_option_of_inhabited Equiv.sigmaEquivOptionOfInhabited
end
section sumCompl
/-- For any predicate `p` on `α`,
the sum of the two subtypes `{a // p a}` and its complement `{a // ¬ p a}`
is naturally equivalent to `α`.
See `subtypeOrEquiv` for sum types over subtypes `{x // p x}` and `{x // q x}`
that are not necessarily `IsCompl p q`. -/
def sumCompl {α : Type*} (p : α → Prop) [DecidablePred p] :
Sum { a // p a } { a // ¬p a } ≃ α where
toFun := Sum.elim Subtype.val Subtype.val
invFun a := if h : p a then Sum.inl ⟨a, h⟩ else Sum.inr ⟨a, h⟩
left_inv := by
rintro (⟨x, hx⟩ | ⟨x, hx⟩) <;> dsimp
· rw [dif_pos]
· rw [dif_neg]
right_inv a := by
dsimp
split_ifs <;> rfl
#align equiv.sum_compl Equiv.sumCompl
@[simp]
theorem sumCompl_apply_inl (p : α → Prop) [DecidablePred p] (x : { a // p a }) :
sumCompl p (Sum.inl x) = x :=
rfl
#align equiv.sum_compl_apply_inl Equiv.sumCompl_apply_inl
@[simp]
theorem sumCompl_apply_inr (p : α → Prop) [DecidablePred p] (x : { a // ¬p a }) :
sumCompl p (Sum.inr x) = x :=
rfl
#align equiv.sum_compl_apply_inr Equiv.sumCompl_apply_inr
@[simp]
theorem sumCompl_apply_symm_of_pos (p : α → Prop) [DecidablePred p] (a : α) (h : p a) :
(sumCompl p).symm a = Sum.inl ⟨a, h⟩ :=
dif_pos h
#align equiv.sum_compl_apply_symm_of_pos Equiv.sumCompl_apply_symm_of_pos
@[simp]
theorem sumCompl_apply_symm_of_neg (p : α → Prop) [DecidablePred p] (a : α) (h : ¬p a) :
(sumCompl p).symm a = Sum.inr ⟨a, h⟩ :=
dif_neg h
#align equiv.sum_compl_apply_symm_of_neg Equiv.sumCompl_apply_symm_of_neg
/-- Combines an `Equiv` between two subtypes with an `Equiv` between their complements to form a
permutation. -/
def subtypeCongr {p q : α → Prop} [DecidablePred p] [DecidablePred q]
(e : { x // p x } ≃ { x // q x }) (f : { x // ¬p x } ≃ { x // ¬q x }) : Perm α :=
(sumCompl p).symm.trans ((sumCongr e f).trans (sumCompl q))
#align equiv.subtype_congr Equiv.subtypeCongr
variable {p : ε → Prop} [DecidablePred p]
variable (ep ep' : Perm { a // p a }) (en en' : Perm { a // ¬p a })
/-- Combining permutations on `ε` that permute only inside or outside the subtype
split induced by `p : ε → Prop` constructs a permutation on `ε`. -/
def Perm.subtypeCongr : Equiv.Perm ε :=
permCongr (sumCompl p) (sumCongr ep en)
#align equiv.perm.subtype_congr Equiv.Perm.subtypeCongr
theorem Perm.subtypeCongr.apply (a : ε) : ep.subtypeCongr en a =
if h : p a then (ep ⟨a, h⟩ : ε) else en ⟨a, h⟩ := by
by_cases h : p a <;> simp [Perm.subtypeCongr, h]
#align equiv.perm.subtype_congr.apply Equiv.Perm.subtypeCongr.apply
@[simp]
theorem Perm.subtypeCongr.left_apply {a : ε} (h : p a) : ep.subtypeCongr en a = ep ⟨a, h⟩ := by
simp [Perm.subtypeCongr.apply, h]
#align equiv.perm.subtype_congr.left_apply Equiv.Perm.subtypeCongr.left_apply
@[simp]
theorem Perm.subtypeCongr.left_apply_subtype (a : { a // p a }) : ep.subtypeCongr en a = ep a :=
Perm.subtypeCongr.left_apply ep en a.property
#align equiv.perm.subtype_congr.left_apply_subtype Equiv.Perm.subtypeCongr.left_apply_subtype
@[simp]
theorem Perm.subtypeCongr.right_apply {a : ε} (h : ¬p a) : ep.subtypeCongr en a = en ⟨a, h⟩ := by
simp [Perm.subtypeCongr.apply, h]
#align equiv.perm.subtype_congr.right_apply Equiv.Perm.subtypeCongr.right_apply
@[simp]
theorem Perm.subtypeCongr.right_apply_subtype (a : { a // ¬p a }) : ep.subtypeCongr en a = en a :=
Perm.subtypeCongr.right_apply ep en a.property
#align equiv.perm.subtype_congr.right_apply_subtype Equiv.Perm.subtypeCongr.right_apply_subtype
@[simp]
theorem Perm.subtypeCongr.refl :
Perm.subtypeCongr (Equiv.refl { a // p a }) (Equiv.refl { a // ¬p a }) = Equiv.refl ε := by
ext x
by_cases h:p x <;> simp [h]
#align equiv.perm.subtype_congr.refl Equiv.Perm.subtypeCongr.refl
@[simp]
theorem Perm.subtypeCongr.symm : (ep.subtypeCongr en).symm = Perm.subtypeCongr ep.symm en.symm := by
ext x
by_cases h:p x
· have : p (ep.symm ⟨x, h⟩) := Subtype.property _
simp [Perm.subtypeCongr.apply, h, symm_apply_eq, this]
· have : ¬p (en.symm ⟨x, h⟩) := Subtype.property (en.symm _)
simp [Perm.subtypeCongr.apply, h, symm_apply_eq, this]
#align equiv.perm.subtype_congr.symm Equiv.Perm.subtypeCongr.symm
@[simp]
theorem Perm.subtypeCongr.trans :
(ep.subtypeCongr en).trans (ep'.subtypeCongr en')
= Perm.subtypeCongr (ep.trans ep') (en.trans en') := by
ext x
by_cases h:p x
· have : p (ep ⟨x, h⟩) := Subtype.property _
simp [Perm.subtypeCongr.apply, h, this]
· have : ¬p (en ⟨x, h⟩) := Subtype.property (en _)
simp [Perm.subtypeCongr.apply, h, symm_apply_eq, this]
#align equiv.perm.subtype_congr.trans Equiv.Perm.subtypeCongr.trans
end sumCompl
section subtypePreimage
variable (p : α → Prop) [DecidablePred p] (x₀ : { a // p a } → β)
/-- For a fixed function `x₀ : {a // p a} → β` defined on a subtype of `α`,
the subtype of functions `x : α → β` that agree with `x₀` on the subtype `{a // p a}`
is naturally equivalent to the type of functions `{a // ¬ p a} → β`. -/
@[simps]
def subtypePreimage : { x : α → β // x ∘ Subtype.val = x₀ } ≃ ({ a // ¬p a } → β) where
toFun (x : { x : α → β // x ∘ Subtype.val = x₀ }) a := (x : α → β) a
invFun x := ⟨fun a => if h : p a then x₀ ⟨a, h⟩ else x ⟨a, h⟩, funext fun ⟨a, h⟩ => dif_pos h⟩
left_inv := fun ⟨x, hx⟩ =>
Subtype.val_injective <|
funext fun a => by
dsimp only
split_ifs
· rw [← hx]; rfl
· rfl
right_inv x :=
funext fun ⟨a, h⟩ =>
show dite (p a) _ _ = _ by
dsimp only
rw [dif_neg h]
#align equiv.subtype_preimage Equiv.subtypePreimage
#align equiv.subtype_preimage_symm_apply_coe Equiv.subtypePreimage_symm_apply_coe
#align equiv.subtype_preimage_apply Equiv.subtypePreimage_apply
theorem subtypePreimage_symm_apply_coe_pos (x : { a // ¬p a } → β) (a : α) (h : p a) :
((subtypePreimage p x₀).symm x : α → β) a = x₀ ⟨a, h⟩ :=
dif_pos h
#align equiv.subtype_preimage_symm_apply_coe_pos Equiv.subtypePreimage_symm_apply_coe_pos
theorem subtypePreimage_symm_apply_coe_neg (x : { a // ¬p a } → β) (a : α) (h : ¬p a) :
((subtypePreimage p x₀).symm x : α → β) a = x ⟨a, h⟩ :=
dif_neg h
#align equiv.subtype_preimage_symm_apply_coe_neg Equiv.subtypePreimage_symm_apply_coe_neg
end subtypePreimage
section
/-- A family of equivalences `∀ a, β₁ a ≃ β₂ a` generates an equivalence between `∀ a, β₁ a` and
`∀ a, β₂ a`. -/
def piCongrRight {β₁ β₂ : α → Sort*} (F : ∀ a, β₁ a ≃ β₂ a) : (∀ a, β₁ a) ≃ (∀ a, β₂ a) :=
⟨fun H a => F a (H a), fun H a => (F a).symm (H a), fun H => funext <| by simp,
fun H => funext <| by simp⟩
#align equiv.Pi_congr_right Equiv.piCongrRight
/-- Given `φ : α → β → Sort*`, we have an equivalence between `∀ a b, φ a b` and `∀ b a, φ a b`.
This is `Function.swap` as an `Equiv`. -/
@[simps apply]
def piComm (φ : α → β → Sort*) : (∀ a b, φ a b) ≃ ∀ b a, φ a b :=
⟨swap, swap, fun _ => rfl, fun _ => rfl⟩
#align equiv.Pi_comm Equiv.piComm
#align equiv.Pi_comm_apply Equiv.piComm_apply
@[simp]
theorem piComm_symm {φ : α → β → Sort*} : (piComm φ).symm = (piComm <| swap φ) :=
rfl
#align equiv.Pi_comm_symm Equiv.piComm_symm
/-- Dependent `curry` equivalence: the type of dependent functions on `Σ i, β i` is equivalent
to the type of dependent functions of two arguments (i.e., functions to the space of functions).
This is `Sigma.curry` and `Sigma.uncurry` together as an equiv. -/
def piCurry {β : α → Type*} (γ : ∀ a, β a → Type*) :
(∀ x : Σ i, β i, γ x.1 x.2) ≃ ∀ a b, γ a b where
toFun := Sigma.curry
invFun := Sigma.uncurry
left_inv := Sigma.uncurry_curry
right_inv := Sigma.curry_uncurry
#align equiv.Pi_curry Equiv.piCurry
-- `simps` overapplies these but `simps (config := .asFn)` under-applies them
@[simp] theorem piCurry_apply {β : α → Type*} (γ : ∀ a, β a → Type*)
(f : ∀ x : Σ i, β i, γ x.1 x.2) :
piCurry γ f = Sigma.curry f :=
rfl
@[simp] theorem piCurry_symm_apply {β : α → Type*} (γ : ∀ a, β a → Type*) (f : ∀ a b, γ a b) :
(piCurry γ).symm f = Sigma.uncurry f :=
rfl
end
section prodCongr
variable (e : α₁ → β₁ ≃ β₂)
/-- A family of equivalences `∀ (a : α₁), β₁ ≃ β₂` generates an equivalence
between `β₁ × α₁` and `β₂ × α₁`. -/
def prodCongrLeft : β₁ × α₁ ≃ β₂ × α₁ where
toFun ab := ⟨e ab.2 ab.1, ab.2⟩
invFun ab := ⟨(e ab.2).symm ab.1, ab.2⟩
left_inv := by
rintro ⟨a, b⟩
simp
right_inv := by
rintro ⟨a, b⟩
simp
#align equiv.prod_congr_left Equiv.prodCongrLeft
@[simp]
theorem prodCongrLeft_apply (b : β₁) (a : α₁) : prodCongrLeft e (b, a) = (e a b, a) :=
rfl
#align equiv.prod_congr_left_apply Equiv.prodCongrLeft_apply
theorem prodCongr_refl_right (e : β₁ ≃ β₂) :
prodCongr e (Equiv.refl α₁) = prodCongrLeft fun _ => e := by
ext ⟨a, b⟩ : 1
simp
#align equiv.prod_congr_refl_right Equiv.prodCongr_refl_right
/-- A family of equivalences `∀ (a : α₁), β₁ ≃ β₂` generates an equivalence
between `α₁ × β₁` and `α₁ × β₂`. -/
def prodCongrRight : α₁ × β₁ ≃ α₁ × β₂ where
toFun ab := ⟨ab.1, e ab.1 ab.2⟩
invFun ab := ⟨ab.1, (e ab.1).symm ab.2⟩
left_inv := by
rintro ⟨a, b⟩
simp
right_inv := by
rintro ⟨a, b⟩
simp
#align equiv.prod_congr_right Equiv.prodCongrRight
@[simp]
theorem prodCongrRight_apply (a : α₁) (b : β₁) : prodCongrRight e (a, b) = (a, e a b) :=
rfl
#align equiv.prod_congr_right_apply Equiv.prodCongrRight_apply
theorem prodCongr_refl_left (e : β₁ ≃ β₂) :
prodCongr (Equiv.refl α₁) e = prodCongrRight fun _ => e := by
ext ⟨a, b⟩ : 1
simp
#align equiv.prod_congr_refl_left Equiv.prodCongr_refl_left
@[simp]
theorem prodCongrLeft_trans_prodComm :
(prodCongrLeft e).trans (prodComm _ _) = (prodComm _ _).trans (prodCongrRight e) := by
ext ⟨a, b⟩ : 1
simp
#align equiv.prod_congr_left_trans_prod_comm Equiv.prodCongrLeft_trans_prodComm
@[simp]
theorem prodCongrRight_trans_prodComm :
(prodCongrRight e).trans (prodComm _ _) = (prodComm _ _).trans (prodCongrLeft e) := by
ext ⟨a, b⟩ : 1
simp
#align equiv.prod_congr_right_trans_prod_comm Equiv.prodCongrRight_trans_prodComm
theorem sigmaCongrRight_sigmaEquivProd :
(sigmaCongrRight e).trans (sigmaEquivProd α₁ β₂)
= (sigmaEquivProd α₁ β₁).trans (prodCongrRight e) := by
ext ⟨a, b⟩ : 1
simp
#align equiv.sigma_congr_right_sigma_equiv_prod Equiv.sigmaCongrRight_sigmaEquivProd
theorem sigmaEquivProd_sigmaCongrRight :
(sigmaEquivProd α₁ β₁).symm.trans (sigmaCongrRight e)
= (prodCongrRight e).trans (sigmaEquivProd α₁ β₂).symm := by
ext ⟨a, b⟩ : 1
simp only [trans_apply, sigmaCongrRight_apply, prodCongrRight_apply]
rfl
#align equiv.sigma_equiv_prod_sigma_congr_right Equiv.sigmaEquivProd_sigmaCongrRight
-- See also `Equiv.ofPreimageEquiv`.
/-- A family of equivalences between fibers gives an equivalence between domains. -/
@[simps!]
def ofFiberEquiv {f : α → γ} {g : β → γ} (e : ∀ c, { a // f a = c } ≃ { b // g b = c }) : α ≃ β :=
(sigmaFiberEquiv f).symm.trans <| (Equiv.sigmaCongrRight e).trans (sigmaFiberEquiv g)
#align equiv.of_fiber_equiv Equiv.ofFiberEquiv
#align equiv.of_fiber_equiv_apply Equiv.ofFiberEquiv_apply
#align equiv.of_fiber_equiv_symm_apply Equiv.ofFiberEquiv_symm_apply
theorem ofFiberEquiv_map {α β γ} {f : α → γ} {g : β → γ}
(e : ∀ c, { a // f a = c } ≃ { b // g b = c }) (a : α) : g (ofFiberEquiv e a) = f a :=
(_ : { b // g b = _ }).property
#align equiv.of_fiber_equiv_map Equiv.ofFiberEquiv_map
/-- A variation on `Equiv.prodCongr` where the equivalence in the second component can depend
on the first component. A typical example is a shear mapping, explaining the name of this
declaration. -/
@[simps (config := .asFn)]
def prodShear (e₁ : α₁ ≃ α₂) (e₂ : α₁ → β₁ ≃ β₂) : α₁ × β₁ ≃ α₂ × β₂ where
toFun := fun x : α₁ × β₁ => (e₁ x.1, e₂ x.1 x.2)
invFun := fun y : α₂ × β₂ => (e₁.symm y.1, (e₂ <| e₁.symm y.1).symm y.2)
left_inv := by
rintro ⟨x₁, y₁⟩
simp only [symm_apply_apply]
right_inv := by
rintro ⟨x₁, y₁⟩
simp only [apply_symm_apply]
#align equiv.prod_shear Equiv.prodShear
#align equiv.prod_shear_apply Equiv.prodShear_apply
#align equiv.prod_shear_symm_apply Equiv.prodShear_symm_apply
end prodCongr
namespace Perm
variable [DecidableEq α₁] (a : α₁) (e : Perm β₁)
/-- `prodExtendRight a e` extends `e : Perm β` to `Perm (α × β)` by sending `(a, b)` to
`(a, e b)` and keeping the other `(a', b)` fixed. -/
def prodExtendRight : Perm (α₁ × β₁) where
toFun ab := if ab.fst = a then (a, e ab.snd) else ab
invFun ab := if ab.fst = a then (a, e.symm ab.snd) else ab
left_inv := by
rintro ⟨k', x⟩
dsimp only
split_ifs with h₁ h₂
· simp [h₁]
· simp at h₂
· simp
right_inv := by
rintro ⟨k', x⟩
dsimp only
split_ifs with h₁ h₂
· simp [h₁]
· simp at h₂
· simp
#align equiv.perm.prod_extend_right Equiv.Perm.prodExtendRight
@[simp]
theorem prodExtendRight_apply_eq (b : β₁) : prodExtendRight a e (a, b) = (a, e b) :=
if_pos rfl
#align equiv.perm.prod_extend_right_apply_eq Equiv.Perm.prodExtendRight_apply_eq
theorem prodExtendRight_apply_ne {a a' : α₁} (h : a' ≠ a) (b : β₁) :
prodExtendRight a e (a', b) = (a', b) :=
if_neg h
#align equiv.perm.prod_extend_right_apply_ne Equiv.Perm.prodExtendRight_apply_ne
theorem eq_of_prodExtendRight_ne {e : Perm β₁} {a a' : α₁} {b : β₁}
(h : prodExtendRight a e (a', b) ≠ (a', b)) : a' = a := by
contrapose! h
exact prodExtendRight_apply_ne _ h _
#align equiv.perm.eq_of_prod_extend_right_ne Equiv.Perm.eq_of_prodExtendRight_ne
@[simp]
theorem fst_prodExtendRight (ab : α₁ × β₁) : (prodExtendRight a e ab).fst = ab.fst := by
rw [prodExtendRight]
dsimp
split_ifs with h
· rw [h]
· rfl
#align equiv.perm.fst_prod_extend_right Equiv.Perm.fst_prodExtendRight
end Perm
section
/-- The type of functions to a product `α × β` is equivalent to the type of pairs of functions
`γ → α` and `γ → β`. -/
def arrowProdEquivProdArrow (α β γ : Type*) : (γ → α × β) ≃ (γ → α) × (γ → β) where
toFun := fun f => (fun c => (f c).1, fun c => (f c).2)
invFun := fun p c => (p.1 c, p.2 c)
left_inv := fun f => rfl
right_inv := fun p => by cases p; rfl
#align equiv.arrow_prod_equiv_prod_arrow Equiv.arrowProdEquivProdArrow
open Sum
/-- The type of dependent functions on a sum type `ι ⊕ ι'` is equivalent to the type of pairs of
functions on `ι` and on `ι'`. This is a dependent version of `Equiv.sumArrowEquivProdArrow`. -/
@[simps]
def sumPiEquivProdPi (π : ι ⊕ ι' → Type*) : (∀ i, π i) ≃ (∀ i, π (inl i)) × ∀ i', π (inr i') where
toFun f := ⟨fun i => f (inl i), fun i' => f (inr i')⟩
invFun g := Sum.rec g.1 g.2
left_inv f := by ext (i | i) <;> rfl
right_inv g := Prod.ext rfl rfl
/-- The equivalence between a product of two dependent functions types and a single dependent
function type. Basically a symmetric version of `Equiv.sumPiEquivProdPi`. -/
@[simps!]
def prodPiEquivSumPi (π : ι → Type u) (π' : ι' → Type u) :
((∀ i, π i) × ∀ i', π' i') ≃ ∀ i, Sum.elim π π' i :=
sumPiEquivProdPi (Sum.elim π π') |>.symm
/-- The type of functions on a sum type `α ⊕ β` is equivalent to the type of pairs of functions
on `α` and on `β`. -/
def sumArrowEquivProdArrow (α β γ : Type*) : (Sum α β → γ) ≃ (α → γ) × (β → γ) :=
⟨fun f => (f ∘ inl, f ∘ inr), fun p => Sum.elim p.1 p.2, fun f => by ext ⟨⟩ <;> rfl, fun p => by
cases p
rfl⟩
#align equiv.sum_arrow_equiv_prod_arrow Equiv.sumArrowEquivProdArrow
@[simp]
theorem sumArrowEquivProdArrow_apply_fst (f : Sum α β → γ) (a : α) :
(sumArrowEquivProdArrow α β γ f).1 a = f (inl a) :=
rfl
#align equiv.sum_arrow_equiv_prod_arrow_apply_fst Equiv.sumArrowEquivProdArrow_apply_fst
@[simp]
theorem sumArrowEquivProdArrow_apply_snd (f : Sum α β → γ) (b : β) :
(sumArrowEquivProdArrow α β γ f).2 b = f (inr b) :=
rfl
#align equiv.sum_arrow_equiv_prod_arrow_apply_snd Equiv.sumArrowEquivProdArrow_apply_snd
@[simp]
theorem sumArrowEquivProdArrow_symm_apply_inl (f : α → γ) (g : β → γ) (a : α) :
((sumArrowEquivProdArrow α β γ).symm (f, g)) (inl a) = f a :=
rfl
#align equiv.sum_arrow_equiv_prod_arrow_symm_apply_inl Equiv.sumArrowEquivProdArrow_symm_apply_inl
@[simp]
theorem sumArrowEquivProdArrow_symm_apply_inr (f : α → γ) (g : β → γ) (b : β) :
((sumArrowEquivProdArrow α β γ).symm (f, g)) (inr b) = g b :=
rfl
#align equiv.sum_arrow_equiv_prod_arrow_symm_apply_inr Equiv.sumArrowEquivProdArrow_symm_apply_inr
/-- Type product is right distributive with respect to type sum up to an equivalence. -/
def sumProdDistrib (α β γ) : Sum α β × γ ≃ Sum (α × γ) (β × γ) :=
⟨fun p => p.1.map (fun x => (x, p.2)) fun x => (x, p.2),
fun s => s.elim (Prod.map inl id) (Prod.map inr id), by
rintro ⟨_ | _, _⟩ <;> rfl, by rintro (⟨_, _⟩ | ⟨_, _⟩) <;> rfl⟩
#align equiv.sum_prod_distrib Equiv.sumProdDistrib
@[simp]
theorem sumProdDistrib_apply_left (a : α) (c : γ) :
sumProdDistrib α β γ (Sum.inl a, c) = Sum.inl (a, c) :=
rfl
#align equiv.sum_prod_distrib_apply_left Equiv.sumProdDistrib_apply_left
@[simp]
theorem sumProdDistrib_apply_right (b : β) (c : γ) :
sumProdDistrib α β γ (Sum.inr b, c) = Sum.inr (b, c) :=
rfl
#align equiv.sum_prod_distrib_apply_right Equiv.sumProdDistrib_apply_right
@[simp]
theorem sumProdDistrib_symm_apply_left (a : α × γ) :
(sumProdDistrib α β γ).symm (inl a) = (inl a.1, a.2) :=
rfl
#align equiv.sum_prod_distrib_symm_apply_left Equiv.sumProdDistrib_symm_apply_left
@[simp]
theorem sumProdDistrib_symm_apply_right (b : β × γ) :
(sumProdDistrib α β γ).symm (inr b) = (inr b.1, b.2) :=
rfl
#align equiv.sum_prod_distrib_symm_apply_right Equiv.sumProdDistrib_symm_apply_right
/-- Type product is left distributive with respect to type sum up to an equivalence. -/
def prodSumDistrib (α β γ) : α × Sum β γ ≃ Sum (α × β) (α × γ) :=
calc
α × Sum β γ ≃ Sum β γ × α := prodComm _ _
_ ≃ Sum (β × α) (γ × α) := sumProdDistrib _ _ _
_ ≃ Sum (α × β) (α × γ) := sumCongr (prodComm _ _) (prodComm _ _)
#align equiv.prod_sum_distrib Equiv.prodSumDistrib
@[simp]
theorem prodSumDistrib_apply_left (a : α) (b : β) :
prodSumDistrib α β γ (a, Sum.inl b) = Sum.inl (a, b) :=
rfl
#align equiv.prod_sum_distrib_apply_left Equiv.prodSumDistrib_apply_left
@[simp]
theorem prodSumDistrib_apply_right (a : α) (c : γ) :
prodSumDistrib α β γ (a, Sum.inr c) = Sum.inr (a, c) :=
rfl
#align equiv.prod_sum_distrib_apply_right Equiv.prodSumDistrib_apply_right
@[simp]
theorem prodSumDistrib_symm_apply_left (a : α × β) :
(prodSumDistrib α β γ).symm (inl a) = (a.1, inl a.2) :=
rfl
#align equiv.prod_sum_distrib_symm_apply_left Equiv.prodSumDistrib_symm_apply_left
@[simp]
theorem prodSumDistrib_symm_apply_right (a : α × γ) :
(prodSumDistrib α β γ).symm (inr a) = (a.1, inr a.2) :=
rfl
#align equiv.prod_sum_distrib_symm_apply_right Equiv.prodSumDistrib_symm_apply_right
/-- An indexed sum of disjoint sums of types is equivalent to the sum of the indexed sums. -/
@[simps]
def sigmaSumDistrib (α β : ι → Type*) :
(Σ i, Sum (α i) (β i)) ≃ Sum (Σ i, α i) (Σ i, β i) :=
⟨fun p => p.2.map (Sigma.mk p.1) (Sigma.mk p.1),
Sum.elim (Sigma.map id fun _ => Sum.inl) (Sigma.map id fun _ => Sum.inr), fun p => by
rcases p with ⟨i, a | b⟩ <;> rfl, fun p => by rcases p with (⟨i, a⟩ | ⟨i, b⟩) <;> rfl⟩
#align equiv.sigma_sum_distrib Equiv.sigmaSumDistrib
#align equiv.sigma_sum_distrib_apply Equiv.sigmaSumDistrib_apply
#align equiv.sigma_sum_distrib_symm_apply Equiv.sigmaSumDistrib_symm_apply
/-- The product of an indexed sum of types (formally, a `Sigma`-type `Σ i, α i`) by a type `β` is
equivalent to the sum of products `Σ i, (α i × β)`. -/
def sigmaProdDistrib (α : ι → Type*) (β : Type*) : (Σ i, α i) × β ≃ Σ i, α i × β :=
⟨fun p => ⟨p.1.1, (p.1.2, p.2)⟩, fun p => (⟨p.1, p.2.1⟩, p.2.2), fun p => by
rcases p with ⟨⟨_, _⟩, _⟩
rfl, fun p => by
rcases p with ⟨_, ⟨_, _⟩⟩
rfl⟩
#align equiv.sigma_prod_distrib Equiv.sigmaProdDistrib
/-- An equivalence that separates out the 0th fiber of `(Σ (n : ℕ), f n)`. -/
def sigmaNatSucc (f : ℕ → Type u) : (Σ n, f n) ≃ Sum (f 0) (Σ n, f (n + 1)) :=
⟨fun x =>
@Sigma.casesOn ℕ f (fun _ => Sum (f 0) (Σn, f (n + 1))) x fun n =>
@Nat.casesOn (fun i => f i → Sum (f 0) (Σn : ℕ, f (n + 1))) n (fun x : f 0 => Sum.inl x)
fun (n : ℕ) (x : f n.succ) => Sum.inr ⟨n, x⟩,
Sum.elim (Sigma.mk 0) (Sigma.map Nat.succ fun _ => id), by rintro ⟨n | n, x⟩ <;> rfl, by
rintro (x | ⟨n, x⟩) <;> rfl⟩
#align equiv.sigma_nat_succ Equiv.sigmaNatSucc
/-- The product `Bool × α` is equivalent to `α ⊕ α`. -/
@[simps]
def boolProdEquivSum (α) : Bool × α ≃ Sum α α where
toFun p := p.1.casesOn (inl p.2) (inr p.2)
invFun := Sum.elim (Prod.mk false) (Prod.mk true)
left_inv := by rintro ⟨_ | _, _⟩ <;> rfl
right_inv := by rintro (_ | _) <;> rfl
#align equiv.bool_prod_equiv_sum Equiv.boolProdEquivSum
#align equiv.bool_prod_equiv_sum_apply Equiv.boolProdEquivSum_apply
#align equiv.bool_prod_equiv_sum_symm_apply Equiv.boolProdEquivSum_symm_apply
/-- The function type `Bool → α` is equivalent to `α × α`. -/
@[simps]
def boolArrowEquivProd (α) : (Bool → α) ≃ α × α where
toFun f := (f false, f true)
invFun p b := b.casesOn p.1 p.2
left_inv _ := funext <| Bool.forall_bool.2 ⟨rfl, rfl⟩
right_inv := fun _ => rfl
#align equiv.bool_arrow_equiv_prod Equiv.boolArrowEquivProd
#align equiv.bool_arrow_equiv_prod_apply Equiv.boolArrowEquivProd_apply
#align equiv.bool_arrow_equiv_prod_symm_apply Equiv.boolArrowEquivProd_symm_apply
end
section
open Sum Nat
/-- The set of natural numbers is equivalent to `ℕ ⊕ PUnit`. -/
def natEquivNatSumPUnit : ℕ ≃ Sum ℕ PUnit where
toFun n := Nat.casesOn n (inr PUnit.unit) inl
invFun := Sum.elim Nat.succ fun _ => 0
left_inv n := by cases n <;> rfl
right_inv := by rintro (_ | _) <;> rfl
#align equiv.nat_equiv_nat_sum_punit Equiv.natEquivNatSumPUnit
/-- `ℕ ⊕ PUnit` is equivalent to `ℕ`. -/
def natSumPUnitEquivNat : Sum ℕ PUnit ≃ ℕ :=
natEquivNatSumPUnit.symm
#align equiv.nat_sum_punit_equiv_nat Equiv.natSumPUnitEquivNat
/-- The type of integer numbers is equivalent to `ℕ ⊕ ℕ`. -/
def intEquivNatSumNat : ℤ ≃ Sum ℕ ℕ where
toFun z := Int.casesOn z inl inr
invFun := Sum.elim Int.ofNat Int.negSucc
left_inv := by rintro (m | n) <;> rfl
right_inv := by rintro (m | n) <;> rfl
#align equiv.int_equiv_nat_sum_nat Equiv.intEquivNatSumNat
end
/-- An equivalence between `α` and `β` generates an equivalence between `List α` and `List β`. -/
def listEquivOfEquiv (e : α ≃ β) : List α ≃ List β where
toFun := List.map e
invFun := List.map e.symm
left_inv l := by rw [List.map_map, e.symm_comp_self, List.map_id]
right_inv l := by rw [List.map_map, e.self_comp_symm, List.map_id]
#align equiv.list_equiv_of_equiv Equiv.listEquivOfEquiv
/-- If `α` is equivalent to `β`, then `Unique α` is equivalent to `Unique β`. -/
def uniqueCongr (e : α ≃ β) : Unique α ≃ Unique β where
toFun h := @Equiv.unique _ _ h e.symm
invFun h := @Equiv.unique _ _ h e
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
#align equiv.unique_congr Equiv.uniqueCongr
/-- If `α` is equivalent to `β`, then `IsEmpty α` is equivalent to `IsEmpty β`. -/
theorem isEmpty_congr (e : α ≃ β) : IsEmpty α ↔ IsEmpty β :=
⟨fun h => @Function.isEmpty _ _ h e.symm, fun h => @Function.isEmpty _ _ h e⟩
#align equiv.is_empty_congr Equiv.isEmpty_congr
protected theorem isEmpty (e : α ≃ β) [IsEmpty β] : IsEmpty α :=
e.isEmpty_congr.mpr ‹_›
#align equiv.is_empty Equiv.isEmpty
section
open Subtype
/-- If `α` is equivalent to `β` and the predicates `p : α → Prop` and `q : β → Prop` are equivalent
at corresponding points, then `{a // p a}` is equivalent to `{b // q b}`.
For the statement where `α = β`, that is, `e : perm α`, see `Perm.subtypePerm`. -/
def subtypeEquiv {p : α → Prop} {q : β → Prop} (e : α ≃ β) (h : ∀ a, p a ↔ q (e a)) :
{ a : α // p a } ≃ { b : β // q b } where
toFun a := ⟨e a, (h _).mp a.property⟩
invFun b := ⟨e.symm b, (h _).mpr ((e.apply_symm_apply b).symm ▸ b.property)⟩
left_inv a := Subtype.ext <| by simp
right_inv b := Subtype.ext <| by simp
#align equiv.subtype_equiv Equiv.subtypeEquiv
lemma coe_subtypeEquiv_eq_map {X Y : Type*} {p : X → Prop} {q : Y → Prop} (e : X ≃ Y)
(h : ∀ x, p x ↔ q (e x)) : ⇑(e.subtypeEquiv h) = Subtype.map e (h · |>.mp) :=
rfl
@[simp]
theorem subtypeEquiv_refl {p : α → Prop} (h : ∀ a, p a ↔ p (Equiv.refl _ a) := fun a => Iff.rfl) :
(Equiv.refl α).subtypeEquiv h = Equiv.refl { a : α // p a } := by
ext
rfl
#align equiv.subtype_equiv_refl Equiv.subtypeEquiv_refl
@[simp]
theorem subtypeEquiv_symm {p : α → Prop} {q : β → Prop} (e : α ≃ β) (h : ∀ a : α, p a ↔ q (e a)) :
(e.subtypeEquiv h).symm =
e.symm.subtypeEquiv fun a => by
convert (h <| e.symm a).symm
exact (e.apply_symm_apply a).symm :=
rfl
#align equiv.subtype_equiv_symm Equiv.subtypeEquiv_symm
@[simp]
theorem subtypeEquiv_trans {p : α → Prop} {q : β → Prop} {r : γ → Prop} (e : α ≃ β) (f : β ≃ γ)
(h : ∀ a : α, p a ↔ q (e a)) (h' : ∀ b : β, q b ↔ r (f b)) :
(e.subtypeEquiv h).trans (f.subtypeEquiv h')
= (e.trans f).subtypeEquiv fun a => (h a).trans (h' <| e a) :=
rfl
#align equiv.subtype_equiv_trans Equiv.subtypeEquiv_trans
@[simp]
theorem subtypeEquiv_apply {p : α → Prop} {q : β → Prop}
(e : α ≃ β) (h : ∀ a : α, p a ↔ q (e a)) (x : { x // p x }) :
e.subtypeEquiv h x = ⟨e x, (h _).1 x.2⟩ :=
rfl
#align equiv.subtype_equiv_apply Equiv.subtypeEquiv_apply
/-- If two predicates `p` and `q` are pointwise equivalent, then `{x // p x}` is equivalent to
`{x // q x}`. -/
@[simps!]
def subtypeEquivRight {p q : α → Prop} (e : ∀ x, p x ↔ q x) : { x // p x } ≃ { x // q x } :=
subtypeEquiv (Equiv.refl _) e
#align equiv.subtype_equiv_right Equiv.subtypeEquivRight
#align equiv.subtype_equiv_right_apply_coe Equiv.subtypeEquivRight_apply_coe
#align equiv.subtype_equiv_right_symm_apply_coe Equiv.subtypeEquivRight_symm_apply_coe
lemma subtypeEquivRight_apply {p q : α → Prop} (e : ∀ x, p x ↔ q x)
(z : { x // p x }) : subtypeEquivRight e z = ⟨z, (e z.1).mp z.2⟩ := rfl
lemma subtypeEquivRight_symm_apply {p q : α → Prop} (e : ∀ x, p x ↔ q x)
(z : { x // q x }) : (subtypeEquivRight e).symm z = ⟨z, (e z.1).mpr z.2⟩ := rfl
/-- If `α ≃ β`, then for any predicate `p : β → Prop` the subtype `{a // p (e a)}` is equivalent
to the subtype `{b // p b}`. -/
def subtypeEquivOfSubtype {p : β → Prop} (e : α ≃ β) : { a : α // p (e a) } ≃ { b : β // p b } :=
subtypeEquiv e <| by simp
#align equiv.subtype_equiv_of_subtype Equiv.subtypeEquivOfSubtype
/-- If `α ≃ β`, then for any predicate `p : α → Prop` the subtype `{a // p a}` is equivalent
to the subtype `{b // p (e.symm b)}`. This version is used by `equiv_rw`. -/
def subtypeEquivOfSubtype' {p : α → Prop} (e : α ≃ β) :
{ a : α // p a } ≃ { b : β // p (e.symm b) } :=
e.symm.subtypeEquivOfSubtype.symm
#align equiv.subtype_equiv_of_subtype' Equiv.subtypeEquivOfSubtype'
/-- If two predicates are equal, then the corresponding subtypes are equivalent. -/
def subtypeEquivProp {p q : α → Prop} (h : p = q) : Subtype p ≃ Subtype q :=
subtypeEquiv (Equiv.refl α) fun _ => h ▸ Iff.rfl
#align equiv.subtype_equiv_prop Equiv.subtypeEquivProp
/-- A subtype of a subtype is equivalent to the subtype of elements satisfying both predicates. This
version allows the “inner” predicate to depend on `h : p a`. -/
@[simps]
def subtypeSubtypeEquivSubtypeExists (p : α → Prop) (q : Subtype p → Prop) :
Subtype q ≃ { a : α // ∃ h : p a, q ⟨a, h⟩ } :=
⟨fun a =>
⟨a.1, a.1.2, by
rcases a with ⟨⟨a, hap⟩, haq⟩
exact haq⟩,
fun a => ⟨⟨a, a.2.fst⟩, a.2.snd⟩, fun ⟨⟨a, ha⟩, h⟩ => rfl, fun ⟨a, h₁, h₂⟩ => rfl⟩
#align equiv.subtype_subtype_equiv_subtype_exists Equiv.subtypeSubtypeEquivSubtypeExists
#align equiv.subtype_subtype_equiv_subtype_exists_symm_apply_coe_coe Equiv.subtypeSubtypeEquivSubtypeExists_symm_apply_coe_coe
#align equiv.subtype_subtype_equiv_subtype_exists_apply_coe Equiv.subtypeSubtypeEquivSubtypeExists_apply_coe
/-- A subtype of a subtype is equivalent to the subtype of elements satisfying both predicates. -/
@[simps!]
def subtypeSubtypeEquivSubtypeInter {α : Type u} (p q : α → Prop) :
{ x : Subtype p // q x.1 } ≃ Subtype fun x => p x ∧ q x :=
(subtypeSubtypeEquivSubtypeExists p _).trans <|
subtypeEquivRight fun x => @exists_prop (q x) (p x)
#align equiv.subtype_subtype_equiv_subtype_inter Equiv.subtypeSubtypeEquivSubtypeInter
#align equiv.subtype_subtype_equiv_subtype_inter_apply_coe Equiv.subtypeSubtypeEquivSubtypeInter_apply_coe
#align equiv.subtype_subtype_equiv_subtype_inter_symm_apply_coe_coe Equiv.subtypeSubtypeEquivSubtypeInter_symm_apply_coe_coe
/-- If the outer subtype has more restrictive predicate than the inner one,
then we can drop the latter. -/
@[simps!]
def subtypeSubtypeEquivSubtype {p q : α → Prop} (h : ∀ {x}, q x → p x) :
{ x : Subtype p // q x.1 } ≃ Subtype q :=
(subtypeSubtypeEquivSubtypeInter p _).trans <| subtypeEquivRight fun _ => and_iff_right_of_imp h
#align equiv.subtype_subtype_equiv_subtype Equiv.subtypeSubtypeEquivSubtype
#align equiv.subtype_subtype_equiv_subtype_apply_coe Equiv.subtypeSubtypeEquivSubtype_apply_coe
#align equiv.subtype_subtype_equiv_subtype_symm_apply_coe_coe Equiv.subtypeSubtypeEquivSubtype_symm_apply_coe_coe
/-- If a proposition holds for all elements, then the subtype is
equivalent to the original type. -/
@[simps apply symm_apply]
def subtypeUnivEquiv {p : α → Prop} (h : ∀ x, p x) : Subtype p ≃ α :=
⟨fun x => x, fun x => ⟨x, h x⟩, fun _ => Subtype.eq rfl, fun _ => rfl⟩
#align equiv.subtype_univ_equiv Equiv.subtypeUnivEquiv
#align equiv.subtype_univ_equiv_apply Equiv.subtypeUnivEquiv_apply
#align equiv.subtype_univ_equiv_symm_apply Equiv.subtypeUnivEquiv_symm_apply
/-- A subtype of a sigma-type is a sigma-type over a subtype. -/
def subtypeSigmaEquiv (p : α → Type v) (q : α → Prop) : { y : Sigma p // q y.1 } ≃ Σ x :
Subtype q, p x.1 :=
⟨fun x => ⟨⟨x.1.1, x.2⟩, x.1.2⟩, fun x => ⟨⟨x.1.1, x.2⟩, x.1.2⟩, fun _ => rfl,
fun _ => rfl⟩
#align equiv.subtype_sigma_equiv Equiv.subtypeSigmaEquiv
/-- A sigma type over a subtype is equivalent to the sigma set over the original type,
if the fiber is empty outside of the subset -/
def sigmaSubtypeEquivOfSubset (p : α → Type v) (q : α → Prop) (h : ∀ x, p x → q x) :
(Σ x : Subtype q, p x) ≃ Σ x : α, p x :=
(subtypeSigmaEquiv p q).symm.trans <| subtypeUnivEquiv fun x => h x.1 x.2
#align equiv.sigma_subtype_equiv_of_subset Equiv.sigmaSubtypeEquivOfSubset
/-- If a predicate `p : β → Prop` is true on the range of a map `f : α → β`, then
`Σ y : {y // p y}, {x // f x = y}` is equivalent to `α`. -/
def sigmaSubtypeFiberEquiv {α β : Type*} (f : α → β) (p : β → Prop) (h : ∀ x, p (f x)) :
(Σ y : Subtype p, { x : α // f x = y }) ≃ α :=
calc
_ ≃ Σy : β, { x : α // f x = y } := sigmaSubtypeEquivOfSubset _ p fun _ ⟨x, h'⟩ => h' ▸ h x
_ ≃ α := sigmaFiberEquiv f
#align equiv.sigma_subtype_fiber_equiv Equiv.sigmaSubtypeFiberEquiv
/-- If for each `x` we have `p x ↔ q (f x)`, then `Σ y : {y // q y}, f ⁻¹' {y}` is equivalent
to `{x // p x}`. -/
def sigmaSubtypeFiberEquivSubtype {α β : Type*} (f : α → β) {p : α → Prop} {q : β → Prop}
(h : ∀ x, p x ↔ q (f x)) : (Σ y : Subtype q, { x : α // f x = y }) ≃ Subtype p :=
calc
(Σy : Subtype q, { x : α // f x = y }) ≃ Σy :
Subtype q, { x : Subtype p // Subtype.mk (f x) ((h x).1 x.2) = y } := by {
apply sigmaCongrRight
intro y
apply Equiv.symm
refine (subtypeSubtypeEquivSubtypeExists _ _).trans (subtypeEquivRight ?_)
intro x
exact ⟨fun ⟨hp, h'⟩ => congr_arg Subtype.val h', fun h' => ⟨(h x).2 (h'.symm ▸ y.2),
Subtype.eq h'⟩⟩ }
_ ≃ Subtype p := sigmaFiberEquiv fun x : Subtype p => (⟨f x, (h x).1 x.property⟩ : Subtype q)
#align equiv.sigma_subtype_fiber_equiv_subtype Equiv.sigmaSubtypeFiberEquivSubtype
/-- A sigma type over an `Option` is equivalent to the sigma set over the original type,
if the fiber is empty at none. -/
def sigmaOptionEquivOfSome (p : Option α → Type v) (h : p none → False) :
(Σ x : Option α, p x) ≃ Σ x : α, p (some x) :=
haveI h' : ∀ x, p x → x.isSome := by
intro x
cases x
· intro n
exfalso
exact h n
· intro _
exact rfl
(sigmaSubtypeEquivOfSubset _ _ h').symm.trans (sigmaCongrLeft' (optionIsSomeEquiv α))
#align equiv.sigma_option_equiv_of_some Equiv.sigmaOptionEquivOfSome
/-- The `Pi`-type `∀ i, π i` is equivalent to the type of sections `f : ι → Σ i, π i` of the
`Sigma` type such that for all `i` we have `(f i).fst = i`. -/
def piEquivSubtypeSigma (ι) (π : ι → Type*) :
(∀ i, π i) ≃ { f : ι → Σ i, π i // ∀ i, (f i).1 = i } where
toFun := fun f => ⟨fun i => ⟨i, f i⟩, fun i => rfl⟩
invFun := fun f i => by rw [← f.2 i]; exact (f.1 i).2
left_inv := fun f => funext fun i => rfl
right_inv := fun ⟨f, hf⟩ =>
Subtype.eq <| funext fun i =>
Sigma.eq (hf i).symm <| eq_of_heq <| rec_heq_of_heq _ <| by simp
#align equiv.pi_equiv_subtype_sigma Equiv.piEquivSubtypeSigma
/-- The type of functions `f : ∀ a, β a` such that for all `a` we have `p a (f a)` is equivalent
to the type of functions `∀ a, {b : β a // p a b}`. -/
def subtypePiEquivPi {β : α → Sort v} {p : ∀ a, β a → Prop} :
{ f : ∀ a, β a // ∀ a, p a (f a) } ≃ ∀ a, { b : β a // p a b } where
toFun := fun f a => ⟨f.1 a, f.2 a⟩
invFun := fun f => ⟨fun a => (f a).1, fun a => (f a).2⟩
left_inv := by
rintro ⟨f, h⟩
rfl
right_inv := by
rintro f
funext a
exact Subtype.ext_val rfl
#align equiv.subtype_pi_equiv_pi Equiv.subtypePiEquivPi
/-- A subtype of a product defined by componentwise conditions
is equivalent to a product of subtypes. -/
def subtypeProdEquivProd {p : α → Prop} {q : β → Prop} :
{ c : α × β // p c.1 ∧ q c.2 } ≃ { a // p a } × { b // q b } where
toFun := fun x => ⟨⟨x.1.1, x.2.1⟩, ⟨x.1.2, x.2.2⟩⟩
invFun := fun x => ⟨⟨x.1.1, x.2.1⟩, ⟨x.1.2, x.2.2⟩⟩
left_inv := fun ⟨⟨_, _⟩, ⟨_, _⟩⟩ => rfl
right_inv := fun ⟨⟨_, _⟩, ⟨_, _⟩⟩ => rfl
#align equiv.subtype_prod_equiv_prod Equiv.subtypeProdEquivProd
/-- A subtype of a `Prod` that depends only on the first component is equivalent to the
corresponding subtype of the first type times the second type. -/
def prodSubtypeFstEquivSubtypeProd {p : α → Prop} : {s : α × β // p s.1} ≃ {a // p a} × β where
toFun x := ⟨⟨x.1.1, x.2⟩, x.1.2⟩
invFun x := ⟨⟨x.1.1, x.2⟩, x.1.2⟩
left_inv _ := rfl
right_inv _ := rfl
/-- A subtype of a `Prod` is equivalent to a sigma type whose fibers are subtypes. -/
def subtypeProdEquivSigmaSubtype (p : α → β → Prop) :
{ x : α × β // p x.1 x.2 } ≃ Σa, { b : β // p a b } where
toFun x := ⟨x.1.1, x.1.2, x.property⟩
invFun x := ⟨⟨x.1, x.2⟩, x.2.property⟩
left_inv x := by ext <;> rfl
right_inv := fun ⟨a, b, pab⟩ => rfl
#align equiv.subtype_prod_equiv_sigma_subtype Equiv.subtypeProdEquivSigmaSubtype
/-- The type `∀ (i : α), β i` can be split as a product by separating the indices in `α`
depending on whether they satisfy a predicate `p` or not. -/
@[simps]
def piEquivPiSubtypeProd {α : Type*} (p : α → Prop) (β : α → Type*) [DecidablePred p] :
(∀ i : α, β i) ≃ (∀ i : { x // p x }, β i) × ∀ i : { x // ¬p x }, β i where
toFun f := (fun x => f x, fun x => f x)
invFun f x := if h : p x then f.1 ⟨x, h⟩ else f.2 ⟨x, h⟩
right_inv := by
rintro ⟨f, g⟩
ext1 <;>
· ext y
rcases y with ⟨val, property⟩
simp only [property, dif_pos, dif_neg, not_false_iff, Subtype.coe_mk]
left_inv f := by
ext x
by_cases h:p x <;>
· simp only [h, dif_neg, dif_pos, not_false_iff]
#align equiv.pi_equiv_pi_subtype_prod Equiv.piEquivPiSubtypeProd
#align equiv.pi_equiv_pi_subtype_prod_symm_apply Equiv.piEquivPiSubtypeProd_symm_apply
#align equiv.pi_equiv_pi_subtype_prod_apply Equiv.piEquivPiSubtypeProd_apply
/-- A product of types can be split as the binary product of one of the types and the product
of all the remaining types. -/
@[simps]
def piSplitAt {α : Type*} [DecidableEq α] (i : α) (β : α → Type*) :
(∀ j, β j) ≃ β i × ∀ j : { j // j ≠ i }, β j where
toFun f := ⟨f i, fun j => f j⟩
invFun f j := if h : j = i then h.symm.rec f.1 else f.2 ⟨j, h⟩
right_inv f := by
ext x
exacts [dif_pos rfl, (dif_neg x.2).trans (by cases x; rfl)]
left_inv f := by
ext x
dsimp only
split_ifs with h
· subst h; rfl
· rfl
#align equiv.pi_split_at Equiv.piSplitAt
#align equiv.pi_split_at_apply Equiv.piSplitAt_apply
#align equiv.pi_split_at_symm_apply Equiv.piSplitAt_symm_apply
/-- A product of copies of a type can be split as the binary product of one copy and the product
of all the remaining copies. -/
@[simps!]
def funSplitAt {α : Type*} [DecidableEq α] (i : α) (β : Type*) :
(α → β) ≃ β × ({ j // j ≠ i } → β) :=
piSplitAt i _
#align equiv.fun_split_at Equiv.funSplitAt
#align equiv.fun_split_at_symm_apply Equiv.funSplitAt_symm_apply
#align equiv.fun_split_at_apply Equiv.funSplitAt_apply
end
section subtypeEquivCodomain
variable [DecidableEq X] {x : X}
/-- The type of all functions `X → Y` with prescribed values for all `x' ≠ x`
is equivalent to the codomain `Y`. -/
def subtypeEquivCodomain (f : { x' // x' ≠ x } → Y) :
{ g : X → Y // g ∘ (↑) = f } ≃ Y :=
(subtypePreimage _ f).trans <|
@funUnique { x' // ¬x' ≠ x } _ <|
show Unique { x' // ¬x' ≠ x } from
@Equiv.unique _ _
(show Unique { x' // x' = x } from {
default := ⟨x, rfl⟩, uniq := fun ⟨_, h⟩ => Subtype.val_injective h })
(subtypeEquivRight fun _ => not_not)
#align equiv.subtype_equiv_codomain Equiv.subtypeEquivCodomain
@[simp]
theorem coe_subtypeEquivCodomain (f : { x' // x' ≠ x } → Y) :
(subtypeEquivCodomain f : _ → Y) =
fun g : { g : X → Y // g ∘ (↑) = f } => (g : X → Y) x :=
rfl
#align equiv.coe_subtype_equiv_codomain Equiv.coe_subtypeEquivCodomain
@[simp]
theorem subtypeEquivCodomain_apply (f : { x' // x' ≠ x } → Y) (g) :
subtypeEquivCodomain f g = (g : X → Y) x :=
rfl
#align equiv.subtype_equiv_codomain_apply Equiv.subtypeEquivCodomain_apply
theorem coe_subtypeEquivCodomain_symm (f : { x' // x' ≠ x } → Y) :
((subtypeEquivCodomain f).symm : Y → _) = fun y =>
⟨fun x' => if h : x' ≠ x then f ⟨x', h⟩ else y, by
funext x'
simp only [ne_eq, dite_not, comp_apply, Subtype.coe_eta, dite_eq_ite, ite_eq_right_iff]
intro w
exfalso
exact x'.property w⟩ :=
rfl
#align equiv.coe_subtype_equiv_codomain_symm Equiv.coe_subtypeEquivCodomain_symm
@[simp]
theorem subtypeEquivCodomain_symm_apply (f : { x' // x' ≠ x } → Y) (y : Y) (x' : X) :
((subtypeEquivCodomain f).symm y : X → Y) x' = if h : x' ≠ x then f ⟨x', h⟩ else y :=
rfl
#align equiv.subtype_equiv_codomain_symm_apply Equiv.subtypeEquivCodomain_symm_apply
theorem subtypeEquivCodomain_symm_apply_eq (f : { x' // x' ≠ x } → Y) (y : Y) :
((subtypeEquivCodomain f).symm y : X → Y) x = y :=
dif_neg (not_not.mpr rfl)
#align equiv.subtype_equiv_codomain_symm_apply_eq Equiv.subtypeEquivCodomain_symm_apply_eq
theorem subtypeEquivCodomain_symm_apply_ne
(f : { x' // x' ≠ x } → Y) (y : Y) (x' : X) (h : x' ≠ x) :
((subtypeEquivCodomain f).symm y : X → Y) x' = f ⟨x', h⟩ :=
dif_pos h
#align equiv.subtype_equiv_codomain_symm_apply_ne Equiv.subtypeEquivCodomain_symm_apply_ne
end subtypeEquivCodomain
instance : CanLift (α → β) (α ≃ β) (↑) Bijective where prf f hf := ⟨ofBijective f hf, rfl⟩
section
variable {α' β' : Type*} (e : Perm α') {p : β' → Prop} [DecidablePred p] (f : α' ≃ Subtype p)
/-- Extend the domain of `e : Equiv.Perm α` to one that is over `β` via `f : α → Subtype p`,
where `p : β → Prop`, permuting only the `b : β` that satisfy `p b`.
This can be used to extend the domain across a function `f : α → β`,
keeping everything outside of `Set.range f` fixed. For this use-case `Equiv` given by `f` can
be constructed by `Equiv.of_leftInverse'` or `Equiv.of_leftInverse` when there is a known
inverse, or `Equiv.ofInjective` in the general case.
-/
def Perm.extendDomain : Perm β' :=
(permCongr f e).subtypeCongr (Equiv.refl _)
#align equiv.perm.extend_domain Equiv.Perm.extendDomain
@[simp]
theorem Perm.extendDomain_apply_image (a : α') : e.extendDomain f (f a) = f (e a) := by
simp [Perm.extendDomain]
#align equiv.perm.extend_domain_apply_image Equiv.Perm.extendDomain_apply_image
theorem Perm.extendDomain_apply_subtype {b : β'} (h : p b) :
e.extendDomain f b = f (e (f.symm ⟨b, h⟩)) := by
simp [Perm.extendDomain, h]
#align equiv.perm.extend_domain_apply_subtype Equiv.Perm.extendDomain_apply_subtype
theorem Perm.extendDomain_apply_not_subtype {b : β'} (h : ¬p b) : e.extendDomain f b = b := by
simp [Perm.extendDomain, h]
#align equiv.perm.extend_domain_apply_not_subtype Equiv.Perm.extendDomain_apply_not_subtype
@[simp]
theorem Perm.extendDomain_refl : Perm.extendDomain (Equiv.refl _) f = Equiv.refl _ := by
simp [Perm.extendDomain]
#align equiv.perm.extend_domain_refl Equiv.Perm.extendDomain_refl
@[simp]
theorem Perm.extendDomain_symm : (e.extendDomain f).symm = Perm.extendDomain e.symm f :=
rfl
#align equiv.perm.extend_domain_symm Equiv.Perm.extendDomain_symm
theorem Perm.extendDomain_trans (e e' : Perm α') :
(e.extendDomain f).trans (e'.extendDomain f) = Perm.extendDomain (e.trans e') f := by
simp [Perm.extendDomain, permCongr_trans]
#align equiv.perm.extend_domain_trans Equiv.Perm.extendDomain_trans
end
/-- Subtype of the quotient is equivalent to the quotient of the subtype. Let `α` be a setoid with
equivalence relation `~`. Let `p₂` be a predicate on the quotient type `α/~`, and `p₁` be the lift
of this predicate to `α`: `p₁ a ↔ p₂ ⟦a⟧`. Let `~₂` be the restriction of `~` to `{x // p₁ x}`.
Then `{x // p₂ x}` is equivalent to the quotient of `{x // p₁ x}` by `~₂`. -/
def subtypeQuotientEquivQuotientSubtype (p₁ : α → Prop) {s₁ : Setoid α} {s₂ : Setoid (Subtype p₁)}
(p₂ : Quotient s₁ → Prop) (hp₂ : ∀ a, p₁ a ↔ p₂ ⟦a⟧)
(h : ∀ x y : Subtype p₁, s₂.r x y ↔ s₁.r x y) : {x // p₂ x} ≃ Quotient s₂ where
toFun a :=
Quotient.hrecOn a.1 (fun a h => ⟦⟨a, (hp₂ _).2 h⟩⟧)
(fun a b hab => hfunext (by rw [Quotient.sound hab]) fun h₁ h₂ _ =>
heq_of_eq (Quotient.sound ((h _ _).2 hab)))
a.2
invFun a :=
Quotient.liftOn a (fun a => (⟨⟦a.1⟧, (hp₂ _).1 a.2⟩ : { x // p₂ x })) fun a b hab =>
Subtype.ext_val (Quotient.sound ((h _ _).1 hab))
left_inv := by exact fun ⟨a, ha⟩ => Quotient.inductionOn a (fun b hb => rfl) ha
right_inv a := Quotient.inductionOn a fun ⟨a, ha⟩ => rfl
#align equiv.subtype_quotient_equiv_quotient_subtype Equiv.subtypeQuotientEquivQuotientSubtype
@[simp]
theorem subtypeQuotientEquivQuotientSubtype_mk (p₁ : α → Prop)
[s₁ : Setoid α] [s₂ : Setoid (Subtype p₁)] (p₂ : Quotient s₁ → Prop) (hp₂ : ∀ a, p₁ a ↔ p₂ ⟦a⟧)
(h : ∀ x y : Subtype p₁, @Setoid.r _ s₂ x y ↔ (x : α) ≈ y)
(x hx) : subtypeQuotientEquivQuotientSubtype p₁ p₂ hp₂ h ⟨⟦x⟧, hx⟩ = ⟦⟨x, (hp₂ _).2 hx⟩⟧ :=
rfl
#align equiv.subtype_quotient_equiv_quotient_subtype_mk Equiv.subtypeQuotientEquivQuotientSubtype_mk
@[simp]
theorem subtypeQuotientEquivQuotientSubtype_symm_mk (p₁ : α → Prop)
[s₁ : Setoid α] [s₂ : Setoid (Subtype p₁)] (p₂ : Quotient s₁ → Prop) (hp₂ : ∀ a, p₁ a ↔ p₂ ⟦a⟧)
(h : ∀ x y : Subtype p₁, @Setoid.r _ s₂ x y ↔ (x : α) ≈ y) (x) :
(subtypeQuotientEquivQuotientSubtype p₁ p₂ hp₂ h).symm ⟦x⟧ = ⟨⟦x⟧, (hp₂ _).1 x.property⟩ :=
rfl
#align equiv.subtype_quotient_equiv_quotient_subtype_symm_mk Equiv.subtypeQuotientEquivQuotientSubtype_symm_mk
section Swap
variable [DecidableEq α]
/-- A helper function for `Equiv.swap`. -/
def swapCore (a b r : α) : α :=
if r = a then b else if r = b then a else r
#align equiv.swap_core Equiv.swapCore
theorem swapCore_self (r a : α) : swapCore a a r = r := by
unfold swapCore
split_ifs <;> simp [*]
#align equiv.swap_core_self Equiv.swapCore_self
theorem swapCore_swapCore (r a b : α) : swapCore a b (swapCore a b r) = r := by
unfold swapCore
-- Porting note: cc missing.
-- `casesm` would work here, with `casesm _ = _, ¬ _ = _`,
-- if it would just continue past failures on hypotheses matching the pattern
split_ifs with h₁ h₂ h₃ h₄ h₅
· subst h₁; exact h₂
· subst h₁; rfl
· cases h₃ rfl
· exact h₄.symm
· cases h₅ rfl
· cases h₅ rfl
· rfl
#align equiv.swap_core_swap_core Equiv.swapCore_swapCore
theorem swapCore_comm (r a b : α) : swapCore a b r = swapCore b a r := by
unfold swapCore
-- Porting note: whatever solution works for `swapCore_swapCore` will work here too.
split_ifs with h₁ h₂ h₃ <;> try simp
· cases h₁; cases h₂; rfl
#align equiv.swap_core_comm Equiv.swapCore_comm
/-- `swap a b` is the permutation that swaps `a` and `b` and
leaves other values as is. -/
def swap (a b : α) : Perm α :=
⟨swapCore a b, swapCore a b, fun r => swapCore_swapCore r a b,
fun r => swapCore_swapCore r a b⟩
#align equiv.swap Equiv.swap
@[simp]
theorem swap_self (a : α) : swap a a = Equiv.refl _ :=
ext fun r => swapCore_self r a
#align equiv.swap_self Equiv.swap_self
theorem swap_comm (a b : α) : swap a b = swap b a :=
ext fun r => swapCore_comm r _ _
#align equiv.swap_comm Equiv.swap_comm
theorem swap_apply_def (a b x : α) : swap a b x = if x = a then b else if x = b then a else x :=
rfl
#align equiv.swap_apply_def Equiv.swap_apply_def
@[simp]
theorem swap_apply_left (a b : α) : swap a b a = b :=
if_pos rfl
#align equiv.swap_apply_left Equiv.swap_apply_left
@[simp]
theorem swap_apply_right (a b : α) : swap a b b = a := by
by_cases h:b = a <;> simp [swap_apply_def, h]
#align equiv.swap_apply_right Equiv.swap_apply_right
theorem swap_apply_of_ne_of_ne {a b x : α} : x ≠ a → x ≠ b → swap a b x = x := by
simp (config := { contextual := true }) [swap_apply_def]
#align equiv.swap_apply_of_ne_of_ne Equiv.swap_apply_of_ne_of_ne
| Mathlib/Logic/Equiv/Basic.lean | 1,665 | 1,667 | theorem eq_or_eq_of_swap_apply_ne_self {a b x : α} (h : swap a b x ≠ x) : x = a ∨ x = b := by |
contrapose! h
exact swap_apply_of_ne_of_ne h.1 h.2
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Group.Indicator
import Mathlib.Data.Finset.Piecewise
import Mathlib.Data.Finset.Preimage
#align_import algebra.big_operators.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Big operators
In this file we define products and sums indexed by finite sets (specifically, `Finset`).
## Notation
We introduce the following notation.
Let `s` be a `Finset α`, and `f : α → β` a function.
* `∏ x ∈ s, f x` is notation for `Finset.prod s f` (assuming `β` is a `CommMonoid`)
* `∑ x ∈ s, f x` is notation for `Finset.sum s f` (assuming `β` is an `AddCommMonoid`)
* `∏ x, f x` is notation for `Finset.prod Finset.univ f`
(assuming `α` is a `Fintype` and `β` is a `CommMonoid`)
* `∑ x, f x` is notation for `Finset.sum Finset.univ f`
(assuming `α` is a `Fintype` and `β` is an `AddCommMonoid`)
## Implementation Notes
The first arguments in all definitions and lemmas is the codomain of the function of the big
operator. This is necessary for the heuristic in `@[to_additive]`.
See the documentation of `to_additive.attr` for more information.
-/
-- TODO
-- assert_not_exists AddCommMonoidWithOne
assert_not_exists MonoidWithZero
assert_not_exists MulAction
variable {ι κ α β γ : Type*}
open Fin Function
namespace Finset
/-- `∏ x ∈ s, f x` is the product of `f x`
as `x` ranges over the elements of the finite set `s`.
-/
@[to_additive "`∑ x ∈ s, f x` is the sum of `f x` as `x` ranges over the elements
of the finite set `s`."]
protected def prod [CommMonoid β] (s : Finset α) (f : α → β) : β :=
(s.1.map f).prod
#align finset.prod Finset.prod
#align finset.sum Finset.sum
@[to_additive (attr := simp)]
theorem prod_mk [CommMonoid β] (s : Multiset α) (hs : s.Nodup) (f : α → β) :
(⟨s, hs⟩ : Finset α).prod f = (s.map f).prod :=
rfl
#align finset.prod_mk Finset.prod_mk
#align finset.sum_mk Finset.sum_mk
@[to_additive (attr := simp)]
theorem prod_val [CommMonoid α] (s : Finset α) : s.1.prod = s.prod id := by
rw [Finset.prod, Multiset.map_id]
#align finset.prod_val Finset.prod_val
#align finset.sum_val Finset.sum_val
end Finset
library_note "operator precedence of big operators"/--
There is no established mathematical convention
for the operator precedence of big operators like `∏` and `∑`.
We will have to make a choice.
Online discussions, such as https://math.stackexchange.com/q/185538/30839
seem to suggest that `∏` and `∑` should have the same precedence,
and that this should be somewhere between `*` and `+`.
The latter have precedence levels `70` and `65` respectively,
and we therefore choose the level `67`.
In practice, this means that parentheses should be placed as follows:
```lean
∑ k ∈ K, (a k + b k) = ∑ k ∈ K, a k + ∑ k ∈ K, b k →
∏ k ∈ K, a k * b k = (∏ k ∈ K, a k) * (∏ k ∈ K, b k)
```
(Example taken from page 490 of Knuth's *Concrete Mathematics*.)
-/
namespace BigOperators
open Batteries.ExtendedBinder Lean Meta
-- TODO: contribute this modification back to `extBinder`
/-- A `bigOpBinder` is like an `extBinder` and has the form `x`, `x : ty`, or `x pred`
where `pred` is a `binderPred` like `< 2`.
Unlike `extBinder`, `x` is a term. -/
syntax bigOpBinder := term:max ((" : " term) <|> binderPred)?
/-- A BigOperator binder in parentheses -/
syntax bigOpBinderParenthesized := " (" bigOpBinder ")"
/-- A list of parenthesized binders -/
syntax bigOpBinderCollection := bigOpBinderParenthesized+
/-- A single (unparenthesized) binder, or a list of parenthesized binders -/
syntax bigOpBinders := bigOpBinderCollection <|> (ppSpace bigOpBinder)
/-- Collects additional binder/Finset pairs for the given `bigOpBinder`.
Note: this is not extensible at the moment, unlike the usual `bigOpBinder` expansions. -/
def processBigOpBinder (processed : (Array (Term × Term)))
(binder : TSyntax ``bigOpBinder) : MacroM (Array (Term × Term)) :=
set_option hygiene false in
withRef binder do
match binder with
| `(bigOpBinder| $x:term) =>
match x with
| `(($a + $b = $n)) => -- Maybe this is too cute.
return processed |>.push (← `(⟨$a, $b⟩), ← `(Finset.Nat.antidiagonal $n))
| _ => return processed |>.push (x, ← ``(Finset.univ))
| `(bigOpBinder| $x : $t) => return processed |>.push (x, ← ``((Finset.univ : Finset $t)))
| `(bigOpBinder| $x ∈ $s) => return processed |>.push (x, ← `(finset% $s))
| `(bigOpBinder| $x < $n) => return processed |>.push (x, ← `(Finset.Iio $n))
| `(bigOpBinder| $x ≤ $n) => return processed |>.push (x, ← `(Finset.Iic $n))
| `(bigOpBinder| $x > $n) => return processed |>.push (x, ← `(Finset.Ioi $n))
| `(bigOpBinder| $x ≥ $n) => return processed |>.push (x, ← `(Finset.Ici $n))
| _ => Macro.throwUnsupported
/-- Collects the binder/Finset pairs for the given `bigOpBinders`. -/
def processBigOpBinders (binders : TSyntax ``bigOpBinders) :
MacroM (Array (Term × Term)) :=
match binders with
| `(bigOpBinders| $b:bigOpBinder) => processBigOpBinder #[] b
| `(bigOpBinders| $[($bs:bigOpBinder)]*) => bs.foldlM processBigOpBinder #[]
| _ => Macro.throwUnsupported
/-- Collect the binderIdents into a `⟨...⟩` expression. -/
def bigOpBindersPattern (processed : (Array (Term × Term))) :
MacroM Term := do
let ts := processed.map Prod.fst
if ts.size == 1 then
return ts[0]!
else
`(⟨$ts,*⟩)
/-- Collect the terms into a product of sets. -/
def bigOpBindersProd (processed : (Array (Term × Term))) :
MacroM Term := do
if processed.isEmpty then
`((Finset.univ : Finset Unit))
else if processed.size == 1 then
return processed[0]!.2
else
processed.foldrM (fun s p => `(SProd.sprod $(s.2) $p)) processed.back.2
(start := processed.size - 1)
/--
- `∑ x, f x` is notation for `Finset.sum Finset.univ f`. It is the sum of `f x`,
where `x` ranges over the finite domain of `f`.
- `∑ x ∈ s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∑ x ∈ s with p x, f x` is notation for `Finset.sum (Finset.filter p s) f`.
- `∑ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.sum (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∑ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∑" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigsum) "∑ " bigOpBinders ("with " term)? ", " term:67 : term
/--
- `∏ x, f x` is notation for `Finset.prod Finset.univ f`. It is the product of `f x`,
where `x` ranges over the finite domain of `f`.
- `∏ x ∈ s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∏ x ∈ s with p x, f x` is notation for `Finset.prod (Finset.filter p s) f`.
- `∏ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.prod (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∏ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∏" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigprod) "∏ " bigOpBinders ("with " term)? ", " term:67 : term
macro_rules (kind := bigsum)
| `(∑ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.sum (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.sum $s (fun $x ↦ $v))
macro_rules (kind := bigprod)
| `(∏ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.prod (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.prod $s (fun $x ↦ $v))
/-- (Deprecated, use `∑ x ∈ s, f x`)
`∑ x in s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigsumin) "∑ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigsumin)
| `(∑ $x:ident in $s, $r) => `(∑ $x:ident ∈ $s, $r)
| `(∑ $x:ident : $t in $s, $r) => `(∑ $x:ident ∈ ($s : Finset $t), $r)
/-- (Deprecated, use `∏ x ∈ s, f x`)
`∏ x in s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigprodin) "∏ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigprodin)
| `(∏ $x:ident in $s, $r) => `(∏ $x:ident ∈ $s, $r)
| `(∏ $x:ident : $t in $s, $r) => `(∏ $x:ident ∈ ($s : Finset $t), $r)
open Lean Meta Parser.Term PrettyPrinter.Delaborator SubExpr
open Batteries.ExtendedBinder
/-- Delaborator for `Finset.prod`. The `pp.piBinderTypes` option controls whether
to show the domain type when the product is over `Finset.univ`. -/
@[delab app.Finset.prod] def delabFinsetProd : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∏ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∏ $(.mk i):ident ∈ $ss, $body)
/-- Delaborator for `Finset.sum`. The `pp.piBinderTypes` option controls whether
to show the domain type when the sum is over `Finset.univ`. -/
@[delab app.Finset.sum] def delabFinsetSum : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∑ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∑ $(.mk i):ident ∈ $ss, $body)
end BigOperators
namespace Finset
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
@[to_additive]
theorem prod_eq_multiset_prod [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = (s.1.map f).prod :=
rfl
#align finset.prod_eq_multiset_prod Finset.prod_eq_multiset_prod
#align finset.sum_eq_multiset_sum Finset.sum_eq_multiset_sum
@[to_additive (attr := simp)]
lemma prod_map_val [CommMonoid β] (s : Finset α) (f : α → β) : (s.1.map f).prod = ∏ a ∈ s, f a :=
rfl
#align finset.prod_map_val Finset.prod_map_val
#align finset.sum_map_val Finset.sum_map_val
@[to_additive]
theorem prod_eq_fold [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = s.fold ((· * ·) : β → β → β) 1 f :=
rfl
#align finset.prod_eq_fold Finset.prod_eq_fold
#align finset.sum_eq_fold Finset.sum_eq_fold
@[simp]
theorem sum_multiset_singleton (s : Finset α) : (s.sum fun x => {x}) = s.val := by
simp only [sum_eq_multiset_sum, Multiset.sum_map_singleton]
#align finset.sum_multiset_singleton Finset.sum_multiset_singleton
end Finset
@[to_additive (attr := simp)]
theorem map_prod [CommMonoid β] [CommMonoid γ] {G : Type*} [FunLike G β γ] [MonoidHomClass G β γ]
(g : G) (f : α → β) (s : Finset α) : g (∏ x ∈ s, f x) = ∏ x ∈ s, g (f x) := by
simp only [Finset.prod_eq_multiset_prod, map_multiset_prod, Multiset.map_map]; rfl
#align map_prod map_prod
#align map_sum map_sum
@[to_additive]
theorem MonoidHom.coe_finset_prod [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α) :
⇑(∏ x ∈ s, f x) = ∏ x ∈ s, ⇑(f x) :=
map_prod (MonoidHom.coeFn β γ) _ _
#align monoid_hom.coe_finset_prod MonoidHom.coe_finset_prod
#align add_monoid_hom.coe_finset_sum AddMonoidHom.coe_finset_sum
/-- See also `Finset.prod_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ` -/
@[to_additive (attr := simp)
"See also `Finset.sum_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ`"]
theorem MonoidHom.finset_prod_apply [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α)
(b : β) : (∏ x ∈ s, f x) b = ∏ x ∈ s, f x b :=
map_prod (MonoidHom.eval b) _ _
#align monoid_hom.finset_prod_apply MonoidHom.finset_prod_apply
#align add_monoid_hom.finset_sum_apply AddMonoidHom.finset_sum_apply
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
namespace Finset
section CommMonoid
variable [CommMonoid β]
@[to_additive (attr := simp)]
theorem prod_empty : ∏ x ∈ ∅, f x = 1 :=
rfl
#align finset.prod_empty Finset.prod_empty
#align finset.sum_empty Finset.sum_empty
@[to_additive]
theorem prod_of_empty [IsEmpty α] (s : Finset α) : ∏ i ∈ s, f i = 1 := by
rw [eq_empty_of_isEmpty s, prod_empty]
#align finset.prod_of_empty Finset.prod_of_empty
#align finset.sum_of_empty Finset.sum_of_empty
@[to_additive (attr := simp)]
theorem prod_cons (h : a ∉ s) : ∏ x ∈ cons a s h, f x = f a * ∏ x ∈ s, f x :=
fold_cons h
#align finset.prod_cons Finset.prod_cons
#align finset.sum_cons Finset.sum_cons
@[to_additive (attr := simp)]
theorem prod_insert [DecidableEq α] : a ∉ s → ∏ x ∈ insert a s, f x = f a * ∏ x ∈ s, f x :=
fold_insert
#align finset.prod_insert Finset.prod_insert
#align finset.sum_insert Finset.sum_insert
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `a` is in `s` or `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `a` is in `s` or `f a = 0`."]
theorem prod_insert_of_eq_one_if_not_mem [DecidableEq α] (h : a ∉ s → f a = 1) :
∏ x ∈ insert a s, f x = ∏ x ∈ s, f x := by
by_cases hm : a ∈ s
· simp_rw [insert_eq_of_mem hm]
· rw [prod_insert hm, h hm, one_mul]
#align finset.prod_insert_of_eq_one_if_not_mem Finset.prod_insert_of_eq_one_if_not_mem
#align finset.sum_insert_of_eq_zero_if_not_mem Finset.sum_insert_of_eq_zero_if_not_mem
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `f a = 0`."]
theorem prod_insert_one [DecidableEq α] (h : f a = 1) : ∏ x ∈ insert a s, f x = ∏ x ∈ s, f x :=
prod_insert_of_eq_one_if_not_mem fun _ => h
#align finset.prod_insert_one Finset.prod_insert_one
#align finset.sum_insert_zero Finset.sum_insert_zero
@[to_additive]
theorem prod_insert_div {M : Type*} [CommGroup M] [DecidableEq α] (ha : a ∉ s) {f : α → M} :
(∏ x ∈ insert a s, f x) / f a = ∏ x ∈ s, f x := by simp [ha]
@[to_additive (attr := simp)]
theorem prod_singleton (f : α → β) (a : α) : ∏ x ∈ singleton a, f x = f a :=
Eq.trans fold_singleton <| mul_one _
#align finset.prod_singleton Finset.prod_singleton
#align finset.sum_singleton Finset.sum_singleton
@[to_additive]
theorem prod_pair [DecidableEq α] {a b : α} (h : a ≠ b) :
(∏ x ∈ ({a, b} : Finset α), f x) = f a * f b := by
rw [prod_insert (not_mem_singleton.2 h), prod_singleton]
#align finset.prod_pair Finset.prod_pair
#align finset.sum_pair Finset.sum_pair
@[to_additive (attr := simp)]
theorem prod_const_one : (∏ _x ∈ s, (1 : β)) = 1 := by
simp only [Finset.prod, Multiset.map_const', Multiset.prod_replicate, one_pow]
#align finset.prod_const_one Finset.prod_const_one
#align finset.sum_const_zero Finset.sum_const_zero
@[to_additive (attr := simp)]
theorem prod_image [DecidableEq α] {s : Finset γ} {g : γ → α} :
(∀ x ∈ s, ∀ y ∈ s, g x = g y → x = y) → ∏ x ∈ s.image g, f x = ∏ x ∈ s, f (g x) :=
fold_image
#align finset.prod_image Finset.prod_image
#align finset.sum_image Finset.sum_image
@[to_additive (attr := simp)]
theorem prod_map (s : Finset α) (e : α ↪ γ) (f : γ → β) :
∏ x ∈ s.map e, f x = ∏ x ∈ s, f (e x) := by
rw [Finset.prod, Finset.map_val, Multiset.map_map]; rfl
#align finset.prod_map Finset.prod_map
#align finset.sum_map Finset.sum_map
@[to_additive]
lemma prod_attach (s : Finset α) (f : α → β) : ∏ x ∈ s.attach, f x = ∏ x ∈ s, f x := by
classical rw [← prod_image Subtype.coe_injective.injOn, attach_image_val]
#align finset.prod_attach Finset.prod_attach
#align finset.sum_attach Finset.sum_attach
@[to_additive (attr := congr)]
theorem prod_congr (h : s₁ = s₂) : (∀ x ∈ s₂, f x = g x) → s₁.prod f = s₂.prod g := by
rw [h]; exact fold_congr
#align finset.prod_congr Finset.prod_congr
#align finset.sum_congr Finset.sum_congr
@[to_additive]
theorem prod_eq_one {f : α → β} {s : Finset α} (h : ∀ x ∈ s, f x = 1) : ∏ x ∈ s, f x = 1 :=
calc
∏ x ∈ s, f x = ∏ _x ∈ s, 1 := Finset.prod_congr rfl h
_ = 1 := Finset.prod_const_one
#align finset.prod_eq_one Finset.prod_eq_one
#align finset.sum_eq_zero Finset.sum_eq_zero
@[to_additive]
theorem prod_disjUnion (h) :
∏ x ∈ s₁.disjUnion s₂ h, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
refine Eq.trans ?_ (fold_disjUnion h)
rw [one_mul]
rfl
#align finset.prod_disj_union Finset.prod_disjUnion
#align finset.sum_disj_union Finset.sum_disjUnion
@[to_additive]
theorem prod_disjiUnion (s : Finset ι) (t : ι → Finset α) (h) :
∏ x ∈ s.disjiUnion t h, f x = ∏ i ∈ s, ∏ x ∈ t i, f x := by
refine Eq.trans ?_ (fold_disjiUnion h)
dsimp [Finset.prod, Multiset.prod, Multiset.fold, Finset.disjUnion, Finset.fold]
congr
exact prod_const_one.symm
#align finset.prod_disj_Union Finset.prod_disjiUnion
#align finset.sum_disj_Union Finset.sum_disjiUnion
@[to_additive]
theorem prod_union_inter [DecidableEq α] :
(∏ x ∈ s₁ ∪ s₂, f x) * ∏ x ∈ s₁ ∩ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x :=
fold_union_inter
#align finset.prod_union_inter Finset.prod_union_inter
#align finset.sum_union_inter Finset.sum_union_inter
@[to_additive]
theorem prod_union [DecidableEq α] (h : Disjoint s₁ s₂) :
∏ x ∈ s₁ ∪ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
rw [← prod_union_inter, disjoint_iff_inter_eq_empty.mp h]; exact (mul_one _).symm
#align finset.prod_union Finset.prod_union
#align finset.sum_union Finset.sum_union
@[to_additive]
theorem prod_filter_mul_prod_filter_not
(s : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] (f : α → β) :
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, f x = ∏ x ∈ s, f x := by
have := Classical.decEq α
rw [← prod_union (disjoint_filter_filter_neg s s p), filter_union_filter_neg_eq]
#align finset.prod_filter_mul_prod_filter_not Finset.prod_filter_mul_prod_filter_not
#align finset.sum_filter_add_sum_filter_not Finset.sum_filter_add_sum_filter_not
section ToList
@[to_additive (attr := simp)]
theorem prod_to_list (s : Finset α) (f : α → β) : (s.toList.map f).prod = s.prod f := by
rw [Finset.prod, ← Multiset.prod_coe, ← Multiset.map_coe, Finset.coe_toList]
#align finset.prod_to_list Finset.prod_to_list
#align finset.sum_to_list Finset.sum_to_list
end ToList
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp (σ : Equiv.Perm α) (s : Finset α) (f : α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x)) = ∏ x ∈ s, f x := by
convert (prod_map s σ.toEmbedding f).symm
exact (map_perm hs).symm
#align equiv.perm.prod_comp Equiv.Perm.prod_comp
#align equiv.perm.sum_comp Equiv.Perm.sum_comp
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp' (σ : Equiv.Perm α) (s : Finset α) (f : α → α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x) x) = ∏ x ∈ s, f x (σ.symm x) := by
convert σ.prod_comp s (fun x => f x (σ.symm x)) hs
rw [Equiv.symm_apply_apply]
#align equiv.perm.prod_comp' Equiv.Perm.prod_comp'
#align equiv.perm.sum_comp' Equiv.Perm.sum_comp'
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_insert [DecidableEq α] (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (insert a s).powerset, f t =
(∏ t ∈ s.powerset, f t) * ∏ t ∈ s.powerset, f (insert a t) := by
rw [powerset_insert, prod_union, prod_image]
· exact insert_erase_invOn.2.injOn.mono fun t ht ↦ not_mem_mono (mem_powerset.1 ht) ha
· aesop (add simp [disjoint_left, insert_subset_iff])
#align finset.prod_powerset_insert Finset.prod_powerset_insert
#align finset.sum_powerset_insert Finset.sum_powerset_insert
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_cons (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (s.cons a ha).powerset, f t = (∏ t ∈ s.powerset, f t) *
∏ t ∈ s.powerset.attach, f (cons a t $ not_mem_mono (mem_powerset.1 t.2) ha) := by
classical
simp_rw [cons_eq_insert]
rw [prod_powerset_insert ha, prod_attach _ fun t ↦ f (insert a t)]
/-- A product over `powerset s` is equal to the double product over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`. -/
@[to_additive "A sum over `powerset s` is equal to the double sum over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`"]
lemma prod_powerset (s : Finset α) (f : Finset α → β) :
∏ t ∈ powerset s, f t = ∏ j ∈ range (card s + 1), ∏ t ∈ powersetCard j s, f t := by
rw [powerset_card_disjiUnion, prod_disjiUnion]
#align finset.prod_powerset Finset.prod_powerset
#align finset.sum_powerset Finset.sum_powerset
end CommMonoid
end Finset
section
open Finset
variable [Fintype α] [CommMonoid β]
@[to_additive]
theorem IsCompl.prod_mul_prod {s t : Finset α} (h : IsCompl s t) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ t, f i = ∏ i, f i :=
(Finset.prod_disjUnion h.disjoint).symm.trans <| by
classical rw [Finset.disjUnion_eq_union, ← Finset.sup_eq_union, h.sup_eq_top]; rfl
#align is_compl.prod_mul_prod IsCompl.prod_mul_prod
#align is_compl.sum_add_sum IsCompl.sum_add_sum
end
namespace Finset
section CommMonoid
variable [CommMonoid β]
/-- Multiplying the products of a function over `s` and over `sᶜ` gives the whole product.
For a version expressed with subtypes, see `Fintype.prod_subtype_mul_prod_subtype`. -/
@[to_additive "Adding the sums of a function over `s` and over `sᶜ` gives the whole sum.
For a version expressed with subtypes, see `Fintype.sum_subtype_add_sum_subtype`. "]
theorem prod_mul_prod_compl [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ sᶜ, f i = ∏ i, f i :=
IsCompl.prod_mul_prod isCompl_compl f
#align finset.prod_mul_prod_compl Finset.prod_mul_prod_compl
#align finset.sum_add_sum_compl Finset.sum_add_sum_compl
@[to_additive]
theorem prod_compl_mul_prod [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ sᶜ, f i) * ∏ i ∈ s, f i = ∏ i, f i :=
(@isCompl_compl _ s _).symm.prod_mul_prod f
#align finset.prod_compl_mul_prod Finset.prod_compl_mul_prod
#align finset.sum_compl_add_sum Finset.sum_compl_add_sum
@[to_additive]
theorem prod_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) :
(∏ x ∈ s₂ \ s₁, f x) * ∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x := by
rw [← prod_union sdiff_disjoint, sdiff_union_of_subset h]
#align finset.prod_sdiff Finset.prod_sdiff
#align finset.sum_sdiff Finset.sum_sdiff
@[to_additive]
theorem prod_subset_one_on_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) (hg : ∀ x ∈ s₂ \ s₁, g x = 1)
(hfg : ∀ x ∈ s₁, f x = g x) : ∏ i ∈ s₁, f i = ∏ i ∈ s₂, g i := by
rw [← prod_sdiff h, prod_eq_one hg, one_mul]
exact prod_congr rfl hfg
#align finset.prod_subset_one_on_sdiff Finset.prod_subset_one_on_sdiff
#align finset.sum_subset_zero_on_sdiff Finset.sum_subset_zero_on_sdiff
@[to_additive]
theorem prod_subset (h : s₁ ⊆ s₂) (hf : ∀ x ∈ s₂, x ∉ s₁ → f x = 1) :
∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x :=
haveI := Classical.decEq α
prod_subset_one_on_sdiff h (by simpa) fun _ _ => rfl
#align finset.prod_subset Finset.prod_subset
#align finset.sum_subset Finset.sum_subset
@[to_additive (attr := simp)]
theorem prod_disj_sum (s : Finset α) (t : Finset γ) (f : Sum α γ → β) :
∏ x ∈ s.disjSum t, f x = (∏ x ∈ s, f (Sum.inl x)) * ∏ x ∈ t, f (Sum.inr x) := by
rw [← map_inl_disjUnion_map_inr, prod_disjUnion, prod_map, prod_map]
rfl
#align finset.prod_disj_sum Finset.prod_disj_sum
#align finset.sum_disj_sum Finset.sum_disj_sum
@[to_additive]
theorem prod_sum_elim (s : Finset α) (t : Finset γ) (f : α → β) (g : γ → β) :
∏ x ∈ s.disjSum t, Sum.elim f g x = (∏ x ∈ s, f x) * ∏ x ∈ t, g x := by simp
#align finset.prod_sum_elim Finset.prod_sum_elim
#align finset.sum_sum_elim Finset.sum_sum_elim
@[to_additive]
theorem prod_biUnion [DecidableEq α] {s : Finset γ} {t : γ → Finset α}
(hs : Set.PairwiseDisjoint (↑s) t) : ∏ x ∈ s.biUnion t, f x = ∏ x ∈ s, ∏ i ∈ t x, f i := by
rw [← disjiUnion_eq_biUnion _ _ hs, prod_disjiUnion]
#align finset.prod_bUnion Finset.prod_biUnion
#align finset.sum_bUnion Finset.sum_biUnion
/-- Product over a sigma type equals the product of fiberwise products. For rewriting
in the reverse direction, use `Finset.prod_sigma'`. -/
@[to_additive "Sum over a sigma type equals the sum of fiberwise sums. For rewriting
in the reverse direction, use `Finset.sum_sigma'`"]
theorem prod_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : Sigma σ → β) :
∏ x ∈ s.sigma t, f x = ∏ a ∈ s, ∏ s ∈ t a, f ⟨a, s⟩ := by
simp_rw [← disjiUnion_map_sigma_mk, prod_disjiUnion, prod_map, Function.Embedding.sigmaMk_apply]
#align finset.prod_sigma Finset.prod_sigma
#align finset.sum_sigma Finset.sum_sigma
@[to_additive]
theorem prod_sigma' {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : ∀ a, σ a → β) :
(∏ a ∈ s, ∏ s ∈ t a, f a s) = ∏ x ∈ s.sigma t, f x.1 x.2 :=
Eq.symm <| prod_sigma s t fun x => f x.1 x.2
#align finset.prod_sigma' Finset.prod_sigma'
#align finset.sum_sigma' Finset.sum_sigma'
section bij
variable {ι κ α : Type*} [CommMonoid α] {s : Finset ι} {t : Finset κ} {f : ι → α} {g : κ → α}
/-- Reorder a product.
The difference with `Finset.prod_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.prod_nbij` is that the bijection is allowed to use membership of the
domain of the product, rather than being a non-dependent function. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_nbij` is that the bijection is allowed to use membership of the
domain of the sum, rather than being a non-dependent function."]
theorem prod_bij (i : ∀ a ∈ s, κ) (hi : ∀ a ha, i a ha ∈ t)
(i_inj : ∀ a₁ ha₁ a₂ ha₂, i a₁ ha₁ = i a₂ ha₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, ∃ a ha, i a ha = b) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
congr_arg Multiset.prod (Multiset.map_eq_map_of_bij_of_nodup f g s.2 t.2 i hi i_inj i_surj h)
#align finset.prod_bij Finset.prod_bij
#align finset.sum_bij Finset.sum_bij
/-- Reorder a product.
The difference with `Finset.prod_bij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the products, rather than being non-dependent functions. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij` is that the bijection is specified with an inverse, rather than
as a surjective injection.
The difference with `Finset.sum_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the sums, rather than being non-dependent functions."]
theorem prod_bij' (i : ∀ a ∈ s, κ) (j : ∀ a ∈ t, ι) (hi : ∀ a ha, i a ha ∈ t)
(hj : ∀ a ha, j a ha ∈ s) (left_inv : ∀ a ha, j (i a ha) (hi a ha) = a)
(right_inv : ∀ a ha, i (j a ha) (hj a ha) = a) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
refine prod_bij i hi (fun a1 h1 a2 h2 eq ↦ ?_) (fun b hb ↦ ⟨_, hj b hb, right_inv b hb⟩) h
rw [← left_inv a1 h1, ← left_inv a2 h2]
simp only [eq]
#align finset.prod_bij' Finset.prod_bij'
#align finset.sum_bij' Finset.sum_bij'
/-- Reorder a product.
The difference with `Finset.prod_nbij'` is that the bijection is specified as a surjective
injection, rather than by an inverse function.
The difference with `Finset.prod_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the product. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the sum."]
lemma prod_nbij (i : ι → κ) (hi : ∀ a ∈ s, i a ∈ t) (i_inj : (s : Set ι).InjOn i)
(i_surj : (s : Set ι).SurjOn i t) (h : ∀ a ∈ s, f a = g (i a)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij (fun a _ ↦ i a) hi i_inj (by simpa using i_surj) h
/-- Reorder a product.
The difference with `Finset.prod_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the products.
The difference with `Finset.prod_equiv` is that bijectivity is only required to hold on the domains
of the products, rather than on the entire types.
-/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.sum_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the sums.
The difference with `Finset.sum_equiv` is that bijectivity is only required to hold on the domains
of the sums, rather than on the entire types."]
lemma prod_nbij' (i : ι → κ) (j : κ → ι) (hi : ∀ a ∈ s, i a ∈ t) (hj : ∀ a ∈ t, j a ∈ s)
(left_inv : ∀ a ∈ s, j (i a) = a) (right_inv : ∀ a ∈ t, i (j a) = a)
(h : ∀ a ∈ s, f a = g (i a)) : ∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij' (fun a _ ↦ i a) (fun b _ ↦ j b) hi hj left_inv right_inv h
/-- Specialization of `Finset.prod_nbij'` that automatically fills in most arguments.
See `Fintype.prod_equiv` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_nbij'` that automatically fills in most arguments.
See `Fintype.sum_equiv` for the version where `s` and `t` are `univ`."]
lemma prod_equiv (e : ι ≃ κ) (hst : ∀ i, i ∈ s ↔ e i ∈ t) (hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := by refine prod_nbij' e e.symm ?_ ?_ ?_ ?_ hfg <;> simp [hst]
#align finset.equiv.prod_comp_finset Finset.prod_equiv
#align finset.equiv.sum_comp_finset Finset.sum_equiv
/-- Specialization of `Finset.prod_bij` that automatically fills in most arguments.
See `Fintype.prod_bijective` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_bij` that automatically fills in most arguments.
See `Fintype.sum_bijective` for the version where `s` and `t` are `univ`."]
lemma prod_bijective (e : ι → κ) (he : e.Bijective) (hst : ∀ i, i ∈ s ↔ e i ∈ t)
(hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := prod_equiv (.ofBijective e he) hst hfg
@[to_additive]
lemma prod_of_injOn (e : ι → κ) (he : Set.InjOn e s) (hest : Set.MapsTo e s t)
(h' : ∀ i ∈ t, i ∉ e '' s → g i = 1) (h : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ j ∈ t, g j := by
classical
exact (prod_nbij e (fun a ↦ mem_image_of_mem e) he (by simp [Set.surjOn_image]) h).trans <|
prod_subset (image_subset_iff.2 hest) <| by simpa using h'
variable [DecidableEq κ]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter' (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f (g i) := by
calc
_ = ∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f (g i) :=
prod_congr rfl fun j _ ↦ prod_congr rfl fun i hi ↦ by rw [(mem_filter.1 hi).2]
_ = _ := prod_fiberwise_eq_prod_filter _ _ _ _
@[to_additive]
lemma prod_fiberwise_of_maps_to {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq_of_maps_to h]
#align finset.prod_fiberwise_of_maps_to Finset.prod_fiberwise_of_maps_to
#align finset.sum_fiberwise_of_maps_to Finset.sum_fiberwise_of_maps_to
@[to_additive]
lemma prod_fiberwise_of_maps_to' {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) := by
calc
_ = ∏ y ∈ t, ∏ x ∈ s.filter fun x ↦ g x = y, f (g x) :=
prod_congr rfl fun y _ ↦ prod_congr rfl fun x hx ↦ by rw [(mem_filter.1 hx).2]
_ = _ := prod_fiberwise_of_maps_to h _
variable [Fintype κ]
@[to_additive]
lemma prod_fiberwise (s : Finset ι) (g : ι → κ) (f : ι → α) :
∏ j, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i :=
prod_fiberwise_of_maps_to (fun _ _ ↦ mem_univ _) _
#align finset.prod_fiberwise Finset.prod_fiberwise
#align finset.sum_fiberwise Finset.sum_fiberwise
@[to_additive]
lemma prod_fiberwise' (s : Finset ι) (g : ι → κ) (f : κ → α) :
∏ j, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) :=
prod_fiberwise_of_maps_to' (fun _ _ ↦ mem_univ _) _
end bij
/-- Taking a product over `univ.pi t` is the same as taking the product over `Fintype.piFinset t`.
`univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`, but differ
in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`. -/
@[to_additive "Taking a sum over `univ.pi t` is the same as taking the sum over
`Fintype.piFinset t`. `univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`,
but differ in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`."]
lemma prod_univ_pi [DecidableEq ι] [Fintype ι] {κ : ι → Type*} (t : ∀ i, Finset (κ i))
(f : (∀ i ∈ (univ : Finset ι), κ i) → β) :
∏ x ∈ univ.pi t, f x = ∏ x ∈ Fintype.piFinset t, f fun a _ ↦ x a := by
apply prod_nbij' (fun x i ↦ x i $ mem_univ _) (fun x i _ ↦ x i) <;> simp
#align finset.prod_univ_pi Finset.prod_univ_pi
#align finset.sum_univ_pi Finset.sum_univ_pi
@[to_additive (attr := simp)]
lemma prod_diag [DecidableEq α] (s : Finset α) (f : α × α → β) :
∏ i ∈ s.diag, f i = ∏ i ∈ s, f (i, i) := by
apply prod_nbij' Prod.fst (fun i ↦ (i, i)) <;> simp
@[to_additive]
theorem prod_finset_product (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ × α → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (c, a) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.1, p.2))
apply prod_equiv (Equiv.sigmaEquivProd _ _).symm <;> simp [h]
#align finset.prod_finset_product Finset.prod_finset_product
#align finset.sum_finset_product Finset.sum_finset_product
@[to_additive]
theorem prod_finset_product' (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ → α → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f c a :=
prod_finset_product r s t h
#align finset.prod_finset_product' Finset.prod_finset_product'
#align finset.sum_finset_product' Finset.sum_finset_product'
@[to_additive]
theorem prod_finset_product_right (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α × γ → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (a, c) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.2, p.1))
apply prod_equiv ((Equiv.prodComm _ _).trans (Equiv.sigmaEquivProd _ _).symm) <;> simp [h]
#align finset.prod_finset_product_right Finset.prod_finset_product_right
#align finset.sum_finset_product_right Finset.sum_finset_product_right
@[to_additive]
theorem prod_finset_product_right' (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α → γ → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f a c :=
prod_finset_product_right r s t h
#align finset.prod_finset_product_right' Finset.prod_finset_product_right'
#align finset.sum_finset_product_right' Finset.sum_finset_product_right'
@[to_additive]
theorem prod_image' [DecidableEq α] {s : Finset γ} {g : γ → α} (h : γ → β)
(eq : ∀ c ∈ s, f (g c) = ∏ x ∈ s.filter fun c' => g c' = g c, h x) :
∏ x ∈ s.image g, f x = ∏ x ∈ s, h x :=
calc
∏ x ∈ s.image g, f x = ∏ x ∈ s.image g, ∏ x ∈ s.filter fun c' => g c' = x, h x :=
(prod_congr rfl) fun _x hx =>
let ⟨c, hcs, hc⟩ := mem_image.1 hx
hc ▸ eq c hcs
_ = ∏ x ∈ s, h x := prod_fiberwise_of_maps_to (fun _x => mem_image_of_mem g) _
#align finset.prod_image' Finset.prod_image'
#align finset.sum_image' Finset.sum_image'
@[to_additive]
theorem prod_mul_distrib : ∏ x ∈ s, f x * g x = (∏ x ∈ s, f x) * ∏ x ∈ s, g x :=
Eq.trans (by rw [one_mul]; rfl) fold_op_distrib
#align finset.prod_mul_distrib Finset.prod_mul_distrib
#align finset.sum_add_distrib Finset.sum_add_distrib
@[to_additive]
lemma prod_mul_prod_comm (f g h i : α → β) :
(∏ a ∈ s, f a * g a) * ∏ a ∈ s, h a * i a = (∏ a ∈ s, f a * h a) * ∏ a ∈ s, g a * i a := by
simp_rw [prod_mul_distrib, mul_mul_mul_comm]
@[to_additive]
theorem prod_product {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ x ∈ s, ∏ y ∈ t, f (x, y) :=
prod_finset_product (s ×ˢ t) s (fun _a => t) fun _p => mem_product
#align finset.prod_product Finset.prod_product
#align finset.sum_product Finset.sum_product
/-- An uncurried version of `Finset.prod_product`. -/
@[to_additive "An uncurried version of `Finset.sum_product`"]
theorem prod_product' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ x ∈ s, ∏ y ∈ t, f x y :=
prod_product
#align finset.prod_product' Finset.prod_product'
#align finset.sum_product' Finset.sum_product'
@[to_additive]
theorem prod_product_right {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ y ∈ t, ∏ x ∈ s, f (x, y) :=
prod_finset_product_right (s ×ˢ t) t (fun _a => s) fun _p => mem_product.trans and_comm
#align finset.prod_product_right Finset.prod_product_right
#align finset.sum_product_right Finset.sum_product_right
/-- An uncurried version of `Finset.prod_product_right`. -/
@[to_additive "An uncurried version of `Finset.sum_product_right`"]
theorem prod_product_right' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_product_right
#align finset.prod_product_right' Finset.prod_product_right'
#align finset.sum_product_right' Finset.sum_product_right'
/-- Generalization of `Finset.prod_comm` to the case when the inner `Finset`s depend on the outer
variable. -/
@[to_additive "Generalization of `Finset.sum_comm` to the case when the inner `Finset`s depend on
the outer variable."]
theorem prod_comm' {s : Finset γ} {t : γ → Finset α} {t' : Finset α} {s' : α → Finset γ}
(h : ∀ x y, x ∈ s ∧ y ∈ t x ↔ x ∈ s' y ∧ y ∈ t') {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t x, f x y) = ∏ y ∈ t', ∏ x ∈ s' y, f x y := by
classical
have : ∀ z : γ × α, (z ∈ s.biUnion fun x => (t x).map <| Function.Embedding.sectr x _) ↔
z.1 ∈ s ∧ z.2 ∈ t z.1 := by
rintro ⟨x, y⟩
simp only [mem_biUnion, mem_map, Function.Embedding.sectr_apply, Prod.mk.injEq,
exists_eq_right, ← and_assoc]
exact
(prod_finset_product' _ _ _ this).symm.trans
((prod_finset_product_right' _ _ _) fun ⟨x, y⟩ => (this _).trans ((h x y).trans and_comm))
#align finset.prod_comm' Finset.prod_comm'
#align finset.sum_comm' Finset.sum_comm'
@[to_additive]
theorem prod_comm {s : Finset γ} {t : Finset α} {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t, f x y) = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_comm' fun _ _ => Iff.rfl
#align finset.prod_comm Finset.prod_comm
#align finset.sum_comm Finset.sum_comm
@[to_additive]
theorem prod_hom_rel [CommMonoid γ] {r : β → γ → Prop} {f : α → β} {g : α → γ} {s : Finset α}
(h₁ : r 1 1) (h₂ : ∀ a b c, r b c → r (f a * b) (g a * c)) :
r (∏ x ∈ s, f x) (∏ x ∈ s, g x) := by
delta Finset.prod
apply Multiset.prod_hom_rel <;> assumption
#align finset.prod_hom_rel Finset.prod_hom_rel
#align finset.sum_hom_rel Finset.sum_hom_rel
@[to_additive]
theorem prod_filter_of_ne {p : α → Prop} [DecidablePred p] (hp : ∀ x ∈ s, f x ≠ 1 → p x) :
∏ x ∈ s.filter p, f x = ∏ x ∈ s, f x :=
(prod_subset (filter_subset _ _)) fun x => by
classical
rw [not_imp_comm, mem_filter]
exact fun h₁ h₂ => ⟨h₁, by simpa using hp _ h₁ h₂⟩
#align finset.prod_filter_of_ne Finset.prod_filter_of_ne
#align finset.sum_filter_of_ne Finset.sum_filter_of_ne
-- If we use `[DecidableEq β]` here, some rewrites fail because they find a wrong `Decidable`
-- instance first; `{∀ x, Decidable (f x ≠ 1)}` doesn't work with `rw ← prod_filter_ne_one`
@[to_additive]
theorem prod_filter_ne_one (s : Finset α) [∀ x, Decidable (f x ≠ 1)] :
∏ x ∈ s.filter fun x => f x ≠ 1, f x = ∏ x ∈ s, f x :=
prod_filter_of_ne fun _ _ => id
#align finset.prod_filter_ne_one Finset.prod_filter_ne_one
#align finset.sum_filter_ne_zero Finset.sum_filter_ne_zero
@[to_additive]
theorem prod_filter (p : α → Prop) [DecidablePred p] (f : α → β) :
∏ a ∈ s.filter p, f a = ∏ a ∈ s, if p a then f a else 1 :=
calc
∏ a ∈ s.filter p, f a = ∏ a ∈ s.filter p, if p a then f a else 1 :=
prod_congr rfl fun a h => by rw [if_pos]; simpa using (mem_filter.1 h).2
_ = ∏ a ∈ s, if p a then f a else 1 := by
{ refine prod_subset (filter_subset _ s) fun x hs h => ?_
rw [mem_filter, not_and] at h
exact if_neg (by simpa using h hs) }
#align finset.prod_filter Finset.prod_filter
#align finset.sum_filter Finset.sum_filter
@[to_additive]
theorem prod_eq_single_of_mem {s : Finset α} {f : α → β} (a : α) (h : a ∈ s)
(h₀ : ∀ b ∈ s, b ≠ a → f b = 1) : ∏ x ∈ s, f x = f a := by
haveI := Classical.decEq α
calc
∏ x ∈ s, f x = ∏ x ∈ {a}, f x := by
{ refine (prod_subset ?_ ?_).symm
· intro _ H
rwa [mem_singleton.1 H]
· simpa only [mem_singleton] }
_ = f a := prod_singleton _ _
#align finset.prod_eq_single_of_mem Finset.prod_eq_single_of_mem
#align finset.sum_eq_single_of_mem Finset.sum_eq_single_of_mem
@[to_additive]
theorem prod_eq_single {s : Finset α} {f : α → β} (a : α) (h₀ : ∀ b ∈ s, b ≠ a → f b = 1)
(h₁ : a ∉ s → f a = 1) : ∏ x ∈ s, f x = f a :=
haveI := Classical.decEq α
by_cases (prod_eq_single_of_mem a · h₀) fun this =>
(prod_congr rfl fun b hb => h₀ b hb <| by rintro rfl; exact this hb).trans <|
prod_const_one.trans (h₁ this).symm
#align finset.prod_eq_single Finset.prod_eq_single
#align finset.sum_eq_single Finset.sum_eq_single
@[to_additive]
lemma prod_union_eq_left [DecidableEq α] (hs : ∀ a ∈ s₂, a ∉ s₁ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₁, f a :=
Eq.symm <|
prod_subset subset_union_left fun _a ha ha' ↦ hs _ ((mem_union.1 ha).resolve_left ha') ha'
@[to_additive]
lemma prod_union_eq_right [DecidableEq α] (hs : ∀ a ∈ s₁, a ∉ s₂ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₂, f a := by rw [union_comm, prod_union_eq_left hs]
@[to_additive]
theorem prod_eq_mul_of_mem {s : Finset α} {f : α → β} (a b : α) (ha : a ∈ s) (hb : b ∈ s)
(hn : a ≠ b) (h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) : ∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; let s' := ({a, b} : Finset α)
have hu : s' ⊆ s := by
refine insert_subset_iff.mpr ?_
apply And.intro ha
apply singleton_subset_iff.mpr hb
have hf : ∀ c ∈ s, c ∉ s' → f c = 1 := by
intro c hc hcs
apply h₀ c hc
apply not_or.mp
intro hab
apply hcs
rw [mem_insert, mem_singleton]
exact hab
rw [← prod_subset hu hf]
exact Finset.prod_pair hn
#align finset.prod_eq_mul_of_mem Finset.prod_eq_mul_of_mem
#align finset.sum_eq_add_of_mem Finset.sum_eq_add_of_mem
@[to_additive]
theorem prod_eq_mul {s : Finset α} {f : α → β} (a b : α) (hn : a ≠ b)
(h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) (ha : a ∉ s → f a = 1) (hb : b ∉ s → f b = 1) :
∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; by_cases h₁ : a ∈ s <;> by_cases h₂ : b ∈ s
· exact prod_eq_mul_of_mem a b h₁ h₂ hn h₀
· rw [hb h₂, mul_one]
apply prod_eq_single_of_mem a h₁
exact fun c hc hca => h₀ c hc ⟨hca, ne_of_mem_of_not_mem hc h₂⟩
· rw [ha h₁, one_mul]
apply prod_eq_single_of_mem b h₂
exact fun c hc hcb => h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, hcb⟩
· rw [ha h₁, hb h₂, mul_one]
exact
_root_.trans
(prod_congr rfl fun c hc =>
h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, ne_of_mem_of_not_mem hc h₂⟩)
prod_const_one
#align finset.prod_eq_mul Finset.prod_eq_mul
#align finset.sum_eq_add Finset.sum_eq_add
-- Porting note: simpNF linter complains that LHS doesn't simplify, but it does
/-- A product over `s.subtype p` equals one over `s.filter p`. -/
@[to_additive (attr := simp, nolint simpNF)
"A sum over `s.subtype p` equals one over `s.filter p`."]
theorem prod_subtype_eq_prod_filter (f : α → β) {p : α → Prop} [DecidablePred p] :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s.filter p, f x := by
conv_lhs => erw [← prod_map (s.subtype p) (Function.Embedding.subtype _) f]
exact prod_congr (subtype_map _) fun x _hx => rfl
#align finset.prod_subtype_eq_prod_filter Finset.prod_subtype_eq_prod_filter
#align finset.sum_subtype_eq_sum_filter Finset.sum_subtype_eq_sum_filter
/-- If all elements of a `Finset` satisfy the predicate `p`, a product
over `s.subtype p` equals that product over `s`. -/
@[to_additive "If all elements of a `Finset` satisfy the predicate `p`, a sum
over `s.subtype p` equals that sum over `s`."]
theorem prod_subtype_of_mem (f : α → β) {p : α → Prop} [DecidablePred p] (h : ∀ x ∈ s, p x) :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s, f x := by
rw [prod_subtype_eq_prod_filter, filter_true_of_mem]
simpa using h
#align finset.prod_subtype_of_mem Finset.prod_subtype_of_mem
#align finset.sum_subtype_of_mem Finset.sum_subtype_of_mem
/-- A product of a function over a `Finset` in a subtype equals a
product in the main type of a function that agrees with the first
function on that `Finset`. -/
@[to_additive "A sum of a function over a `Finset` in a subtype equals a
sum in the main type of a function that agrees with the first
function on that `Finset`."]
theorem prod_subtype_map_embedding {p : α → Prop} {s : Finset { x // p x }} {f : { x // p x } → β}
{g : α → β} (h : ∀ x : { x // p x }, x ∈ s → g x = f x) :
(∏ x ∈ s.map (Function.Embedding.subtype _), g x) = ∏ x ∈ s, f x := by
rw [Finset.prod_map]
exact Finset.prod_congr rfl h
#align finset.prod_subtype_map_embedding Finset.prod_subtype_map_embedding
#align finset.sum_subtype_map_embedding Finset.sum_subtype_map_embedding
variable (f s)
@[to_additive]
theorem prod_coe_sort_eq_attach (f : s → β) : ∏ i : s, f i = ∏ i ∈ s.attach, f i :=
rfl
#align finset.prod_coe_sort_eq_attach Finset.prod_coe_sort_eq_attach
#align finset.sum_coe_sort_eq_attach Finset.sum_coe_sort_eq_attach
@[to_additive]
theorem prod_coe_sort : ∏ i : s, f i = ∏ i ∈ s, f i := prod_attach _ _
#align finset.prod_coe_sort Finset.prod_coe_sort
#align finset.sum_coe_sort Finset.sum_coe_sort
@[to_additive]
theorem prod_finset_coe (f : α → β) (s : Finset α) : (∏ i : (s : Set α), f i) = ∏ i ∈ s, f i :=
prod_coe_sort s f
#align finset.prod_finset_coe Finset.prod_finset_coe
#align finset.sum_finset_coe Finset.sum_finset_coe
variable {f s}
@[to_additive]
theorem prod_subtype {p : α → Prop} {F : Fintype (Subtype p)} (s : Finset α) (h : ∀ x, x ∈ s ↔ p x)
(f : α → β) : ∏ a ∈ s, f a = ∏ a : Subtype p, f a := by
have : (· ∈ s) = p := Set.ext h
subst p
rw [← prod_coe_sort]
congr!
#align finset.prod_subtype Finset.prod_subtype
#align finset.sum_subtype Finset.sum_subtype
@[to_additive]
lemma prod_preimage' (f : ι → κ) [DecidablePred (· ∈ Set.range f)] (s : Finset κ) (hf) (g : κ → β) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s.filter (· ∈ Set.range f), g x := by
classical
calc
∏ x ∈ preimage s f hf, g (f x) = ∏ x ∈ image f (preimage s f hf), g x :=
Eq.symm <| prod_image <| by simpa only [mem_preimage, Set.InjOn] using hf
_ = ∏ x ∈ s.filter fun x => x ∈ Set.range f, g x := by rw [image_preimage]
#align finset.prod_preimage' Finset.prod_preimage'
#align finset.sum_preimage' Finset.sum_preimage'
@[to_additive]
lemma prod_preimage (f : ι → κ) (s : Finset κ) (hf) (g : κ → β)
(hg : ∀ x ∈ s, x ∉ Set.range f → g x = 1) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s, g x := by
classical rw [prod_preimage', prod_filter_of_ne]; exact fun x hx ↦ Not.imp_symm (hg x hx)
#align finset.prod_preimage Finset.prod_preimage
#align finset.sum_preimage Finset.sum_preimage
@[to_additive]
lemma prod_preimage_of_bij (f : ι → κ) (s : Finset κ) (hf : Set.BijOn f (f ⁻¹' ↑s) ↑s) (g : κ → β) :
∏ x ∈ s.preimage f hf.injOn, g (f x) = ∏ x ∈ s, g x :=
prod_preimage _ _ hf.injOn g fun _ hs h_f ↦ (h_f <| hf.subset_range hs).elim
#align finset.prod_preimage_of_bij Finset.prod_preimage_of_bij
#align finset.sum_preimage_of_bij Finset.sum_preimage_of_bij
@[to_additive]
theorem prod_set_coe (s : Set α) [Fintype s] : (∏ i : s, f i) = ∏ i ∈ s.toFinset, f i :=
(Finset.prod_subtype s.toFinset (fun _ ↦ Set.mem_toFinset) f).symm
/-- The product of a function `g` defined only on a set `s` is equal to
the product of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 1` off `s`. -/
@[to_additive "The sum of a function `g` defined only on a set `s` is equal to
the sum of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 0` off `s`."]
theorem prod_congr_set {α : Type*} [CommMonoid α] {β : Type*} [Fintype β] (s : Set β)
[DecidablePred (· ∈ s)] (f : β → α) (g : s → α) (w : ∀ (x : β) (h : x ∈ s), f x = g ⟨x, h⟩)
(w' : ∀ x : β, x ∉ s → f x = 1) : Finset.univ.prod f = Finset.univ.prod g := by
rw [← @Finset.prod_subset _ _ s.toFinset Finset.univ f _ (by simp)]
· rw [Finset.prod_subtype]
· apply Finset.prod_congr rfl
exact fun ⟨x, h⟩ _ => w x h
· simp
· rintro x _ h
exact w' x (by simpa using h)
#align finset.prod_congr_set Finset.prod_congr_set
#align finset.sum_congr_set Finset.sum_congr_set
@[to_additive]
theorem prod_apply_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p}
[DecidablePred fun x => ¬p x] (f : ∀ x : α, p x → γ) (g : ∀ x : α, ¬p x → γ) (h : γ → β) :
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
calc
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ s.filter p, h (if hx : p x then f x hx else g x hx)) *
∏ x ∈ s.filter (¬p ·), h (if hx : p x then f x hx else g x hx) :=
(prod_filter_mul_prod_filter_not s p _).symm
_ = (∏ x ∈ (s.filter p).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx) :=
congr_arg₂ _ (prod_attach _ _).symm (prod_attach _ _).symm
_ = (∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
congr_arg₂ _ (prod_congr rfl fun x _hx ↦
congr_arg h (dif_pos <| by simpa using (mem_filter.mp x.2).2))
(prod_congr rfl fun x _hx => congr_arg h (dif_neg <| by simpa using (mem_filter.mp x.2).2))
#align finset.prod_apply_dite Finset.prod_apply_dite
#align finset.sum_apply_dite Finset.sum_apply_dite
@[to_additive]
theorem prod_apply_ite {s : Finset α} {p : α → Prop} {_hp : DecidablePred p} (f g : α → γ)
(h : γ → β) :
(∏ x ∈ s, h (if p x then f x else g x)) =
(∏ x ∈ s.filter p, h (f x)) * ∏ x ∈ s.filter fun x => ¬p x, h (g x) :=
(prod_apply_dite _ _ _).trans <| congr_arg₂ _ (prod_attach _ (h ∘ f)) (prod_attach _ (h ∘ g))
#align finset.prod_apply_ite Finset.prod_apply_ite
#align finset.sum_apply_ite Finset.sum_apply_ite
@[to_additive]
theorem prod_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f : ∀ x : α, p x → β)
(g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) =
(∏ x ∈ (s.filter p).attach, f x.1 (by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, g x.1 (by simpa using (mem_filter.mp x.2).2) := by
simp [prod_apply_dite _ _ fun x => x]
#align finset.prod_dite Finset.prod_dite
#align finset.sum_dite Finset.sum_dite
@[to_additive]
theorem prod_ite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f g : α → β) :
∏ x ∈ s, (if p x then f x else g x) =
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, g x := by
simp [prod_apply_ite _ _ fun x => x]
#align finset.prod_ite Finset.prod_ite
#align finset.sum_ite Finset.sum_ite
@[to_additive]
theorem prod_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, ¬p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, g x := by
rw [prod_ite, filter_false_of_mem, filter_true_of_mem]
· simp only [prod_empty, one_mul]
all_goals intros; apply h; assumption
#align finset.prod_ite_of_false Finset.prod_ite_of_false
#align finset.sum_ite_of_false Finset.sum_ite_of_false
@[to_additive]
theorem prod_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, f x := by
simp_rw [← ite_not (p _)]
apply prod_ite_of_false
simpa
#align finset.prod_ite_of_true Finset.prod_ite_of_true
#align finset.sum_ite_of_true Finset.sum_ite_of_true
@[to_additive]
theorem prod_apply_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, ¬p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (g x) := by
simp_rw [apply_ite k]
exact prod_ite_of_false _ _ h
#align finset.prod_apply_ite_of_false Finset.prod_apply_ite_of_false
#align finset.sum_apply_ite_of_false Finset.sum_apply_ite_of_false
@[to_additive]
theorem prod_apply_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (f x) := by
simp_rw [apply_ite k]
exact prod_ite_of_true _ _ h
#align finset.prod_apply_ite_of_true Finset.prod_apply_ite_of_true
#align finset.sum_apply_ite_of_true Finset.sum_apply_ite_of_true
@[to_additive]
theorem prod_extend_by_one [DecidableEq α] (s : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ s then f i else 1) = ∏ i ∈ s, f i :=
(prod_congr rfl) fun _i hi => if_pos hi
#align finset.prod_extend_by_one Finset.prod_extend_by_one
#align finset.sum_extend_by_zero Finset.sum_extend_by_zero
@[to_additive (attr := simp)]
theorem prod_ite_mem [DecidableEq α] (s t : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ t then f i else 1) = ∏ i ∈ s ∩ t, f i := by
rw [← Finset.prod_filter, Finset.filter_mem_eq_inter]
#align finset.prod_ite_mem Finset.prod_ite_mem
#align finset.sum_ite_mem Finset.sum_ite_mem
@[to_additive (attr := simp)]
theorem prod_dite_eq [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, a = x → β) :
∏ x ∈ s, (if h : a = x then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h.symm
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq Finset.prod_dite_eq
#align finset.sum_dite_eq Finset.sum_dite_eq
@[to_additive (attr := simp)]
theorem prod_dite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, x = a → β) :
∏ x ∈ s, (if h : x = a then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq' Finset.prod_dite_eq'
#align finset.sum_dite_eq' Finset.sum_dite_eq'
@[to_additive (attr := simp)]
theorem prod_ite_eq [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (a = x) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq s a fun x _ => b x
#align finset.prod_ite_eq Finset.prod_ite_eq
#align finset.sum_ite_eq Finset.sum_ite_eq
/-- A product taken over a conditional whose condition is an equality test on the index and whose
alternative is `1` has value either the term at that index or `1`.
The difference with `Finset.prod_ite_eq` is that the arguments to `Eq` are swapped. -/
@[to_additive (attr := simp) "A sum taken over a conditional whose condition is an equality
test on the index and whose alternative is `0` has value either the term at that index or `0`.
The difference with `Finset.sum_ite_eq` is that the arguments to `Eq` are swapped."]
theorem prod_ite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (x = a) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq' s a fun x _ => b x
#align finset.prod_ite_eq' Finset.prod_ite_eq'
#align finset.sum_ite_eq' Finset.sum_ite_eq'
@[to_additive]
theorem prod_ite_index (p : Prop) [Decidable p] (s t : Finset α) (f : α → β) :
∏ x ∈ if p then s else t, f x = if p then ∏ x ∈ s, f x else ∏ x ∈ t, f x :=
apply_ite (fun s => ∏ x ∈ s, f x) _ _ _
#align finset.prod_ite_index Finset.prod_ite_index
#align finset.sum_ite_index Finset.sum_ite_index
@[to_additive (attr := simp)]
theorem prod_ite_irrel (p : Prop) [Decidable p] (s : Finset α) (f g : α → β) :
∏ x ∈ s, (if p then f x else g x) = if p then ∏ x ∈ s, f x else ∏ x ∈ s, g x := by
split_ifs with h <;> rfl
#align finset.prod_ite_irrel Finset.prod_ite_irrel
#align finset.sum_ite_irrel Finset.sum_ite_irrel
@[to_additive (attr := simp)]
theorem prod_dite_irrel (p : Prop) [Decidable p] (s : Finset α) (f : p → α → β) (g : ¬p → α → β) :
∏ x ∈ s, (if h : p then f h x else g h x) =
if h : p then ∏ x ∈ s, f h x else ∏ x ∈ s, g h x := by
split_ifs with h <;> rfl
#align finset.prod_dite_irrel Finset.prod_dite_irrel
#align finset.sum_dite_irrel Finset.sum_dite_irrel
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle' [DecidableEq α] (a : α) (x : β) (s : Finset α) :
∏ a' ∈ s, Pi.mulSingle a x a' = if a ∈ s then x else 1 :=
prod_dite_eq' _ _ _
#align finset.prod_pi_mul_single' Finset.prod_pi_mulSingle'
#align finset.sum_pi_single' Finset.sum_pi_single'
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle {β : α → Type*} [DecidableEq α] [∀ a, CommMonoid (β a)] (a : α)
(f : ∀ a, β a) (s : Finset α) :
(∏ a' ∈ s, Pi.mulSingle a' (f a') a) = if a ∈ s then f a else 1 :=
prod_dite_eq _ _ _
#align finset.prod_pi_mul_single Finset.prod_pi_mulSingle
@[to_additive]
lemma mulSupport_prod (s : Finset ι) (f : ι → α → β) :
mulSupport (fun x ↦ ∏ i ∈ s, f i x) ⊆ ⋃ i ∈ s, mulSupport (f i) := by
simp only [mulSupport_subset_iff', Set.mem_iUnion, not_exists, nmem_mulSupport]
exact fun x ↦ prod_eq_one
#align function.mul_support_prod Finset.mulSupport_prod
#align function.support_sum Finset.support_sum
section indicator
open Set
variable {κ : Type*}
/-- Consider a product of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (· ^ n)`, which maps a second argument of `1` to `1`. Then if `f` is replaced by the
corresponding multiplicative indicator function, the finset may be replaced by a possibly larger
finset without changing the value of the product. -/
@[to_additive "Consider a sum of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (n • ·)`, which maps a second argument of `0` to `0` (or a weighted sum of `f i * h i` or
`f i • h i`, where `f` gives the weights that are multiplied by some other function `h`). Then if
`f` is replaced by the corresponding indicator function, the finset may be replaced by a possibly
larger finset without changing the value of the sum."]
lemma prod_mulIndicator_subset_of_eq_one [One α] (f : ι → α) (g : ι → α → β) {s t : Finset ι}
(h : s ⊆ t) (hg : ∀ a, g a 1 = 1) :
∏ i ∈ t, g i (mulIndicator ↑s f i) = ∏ i ∈ s, g i (f i) := by
calc
_ = ∏ i ∈ s, g i (mulIndicator ↑s f i) := by rw [prod_subset h fun i _ hn ↦ by simp [hn, hg]]
-- Porting note: This did not use to need the implicit argument
_ = _ := prod_congr rfl fun i hi ↦ congr_arg _ <| mulIndicator_of_mem (α := ι) hi f
#align set.prod_mul_indicator_subset_of_eq_one Finset.prod_mulIndicator_subset_of_eq_one
#align set.sum_indicator_subset_of_eq_zero Finset.sum_indicator_subset_of_eq_zero
/-- Taking the product of an indicator function over a possibly larger finset is the same as
taking the original function over the original finset. -/
@[to_additive "Summing an indicator function over a possibly larger `Finset` is the same as summing
the original function over the original finset."]
lemma prod_mulIndicator_subset (f : ι → β) {s t : Finset ι} (h : s ⊆ t) :
∏ i ∈ t, mulIndicator (↑s) f i = ∏ i ∈ s, f i :=
prod_mulIndicator_subset_of_eq_one _ (fun _ ↦ id) h fun _ ↦ rfl
#align set.prod_mul_indicator_subset Finset.prod_mulIndicator_subset
#align set.sum_indicator_subset Finset.sum_indicator_subset
@[to_additive]
lemma prod_mulIndicator_eq_prod_filter (s : Finset ι) (f : ι → κ → β) (t : ι → Set κ) (g : ι → κ)
[DecidablePred fun i ↦ g i ∈ t i] :
∏ i ∈ s, mulIndicator (t i) (f i) (g i) = ∏ i ∈ s.filter fun i ↦ g i ∈ t i, f i (g i) := by
refine (prod_filter_mul_prod_filter_not s (fun i ↦ g i ∈ t i) _).symm.trans <|
Eq.trans (congr_arg₂ (· * ·) ?_ ?_) (mul_one _)
· exact prod_congr rfl fun x hx ↦ mulIndicator_of_mem (mem_filter.1 hx).2 _
· exact prod_eq_one fun x hx ↦ mulIndicator_of_not_mem (mem_filter.1 hx).2 _
#align finset.prod_mul_indicator_eq_prod_filter Finset.prod_mulIndicator_eq_prod_filter
#align finset.sum_indicator_eq_sum_filter Finset.sum_indicator_eq_sum_filter
@[to_additive]
lemma prod_mulIndicator_eq_prod_inter [DecidableEq ι] (s t : Finset ι) (f : ι → β) :
∏ i ∈ s, (t : Set ι).mulIndicator f i = ∏ i ∈ s ∩ t, f i := by
rw [← filter_mem_eq_inter, prod_mulIndicator_eq_prod_filter]; rfl
@[to_additive]
lemma mulIndicator_prod (s : Finset ι) (t : Set κ) (f : ι → κ → β) :
mulIndicator t (∏ i ∈ s, f i) = ∏ i ∈ s, mulIndicator t (f i) :=
map_prod (mulIndicatorHom _ _) _ _
#align set.mul_indicator_finset_prod Finset.mulIndicator_prod
#align set.indicator_finset_sum Finset.indicator_sum
variable {κ : Type*}
@[to_additive]
lemma mulIndicator_biUnion (s : Finset ι) (t : ι → Set κ) {f : κ → β} :
((s : Set ι).PairwiseDisjoint t) →
mulIndicator (⋃ i ∈ s, t i) f = fun a ↦ ∏ i ∈ s, mulIndicator (t i) f a := by
classical
refine Finset.induction_on s (by simp) fun i s hi ih hs ↦ funext fun j ↦ ?_
rw [prod_insert hi, set_biUnion_insert, mulIndicator_union_of_not_mem_inter,
ih (hs.subset <| subset_insert _ _)]
simp only [not_exists, exists_prop, mem_iUnion, mem_inter_iff, not_and]
exact fun hji i' hi' hji' ↦ (ne_of_mem_of_not_mem hi' hi).symm <|
hs.elim_set (mem_insert_self _ _) (mem_insert_of_mem hi') _ hji hji'
#align set.mul_indicator_finset_bUnion Finset.mulIndicator_biUnion
#align set.indicator_finset_bUnion Finset.indicator_biUnion
@[to_additive]
lemma mulIndicator_biUnion_apply (s : Finset ι) (t : ι → Set κ) {f : κ → β}
(h : (s : Set ι).PairwiseDisjoint t) (x : κ) :
mulIndicator (⋃ i ∈ s, t i) f x = ∏ i ∈ s, mulIndicator (t i) f x := by
rw [mulIndicator_biUnion s t h]
#align set.mul_indicator_finset_bUnion_apply Finset.mulIndicator_biUnion_apply
#align set.indicator_finset_bUnion_apply Finset.indicator_biUnion_apply
end indicator
@[to_additive]
theorem prod_bij_ne_one {s : Finset α} {t : Finset γ} {f : α → β} {g : γ → β}
(i : ∀ a ∈ s, f a ≠ 1 → γ) (hi : ∀ a h₁ h₂, i a h₁ h₂ ∈ t)
(i_inj : ∀ a₁ h₁₁ h₁₂ a₂ h₂₁ h₂₂, i a₁ h₁₁ h₁₂ = i a₂ h₂₁ h₂₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, g b ≠ 1 → ∃ a h₁ h₂, i a h₁ h₂ = b) (h : ∀ a h₁ h₂, f a = g (i a h₁ h₂)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
classical
calc
∏ x ∈ s, f x = ∏ x ∈ s.filter fun x => f x ≠ 1, f x := by rw [prod_filter_ne_one]
_ = ∏ x ∈ t.filter fun x => g x ≠ 1, g x :=
prod_bij (fun a ha => i a (mem_filter.mp ha).1 <| by simpa using (mem_filter.mp ha).2)
?_ ?_ ?_ ?_
_ = ∏ x ∈ t, g x := prod_filter_ne_one _
· intros a ha
refine (mem_filter.mp ha).elim ?_
intros h₁ h₂
refine (mem_filter.mpr ⟨hi a h₁ _, ?_⟩)
specialize h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
rwa [← h]
· intros a₁ ha₁ a₂ ha₂
refine (mem_filter.mp ha₁).elim fun _ha₁₁ _ha₁₂ ↦ ?_
refine (mem_filter.mp ha₂).elim fun _ha₂₁ _ha₂₂ ↦ ?_
apply i_inj
· intros b hb
refine (mem_filter.mp hb).elim fun h₁ h₂ ↦ ?_
obtain ⟨a, ha₁, ha₂, eq⟩ := i_surj b h₁ fun H ↦ by rw [H] at h₂; simp at h₂
exact ⟨a, mem_filter.mpr ⟨ha₁, ha₂⟩, eq⟩
· refine (fun a ha => (mem_filter.mp ha).elim fun h₁ h₂ ↦ ?_)
exact h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
#align finset.prod_bij_ne_one Finset.prod_bij_ne_one
#align finset.sum_bij_ne_zero Finset.sum_bij_ne_zero
@[to_additive]
theorem prod_dite_of_false {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, ¬p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, g x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_false Finset.prod_dite_of_false
#align finset.sum_dite_of_false Finset.sum_dite_of_false
@[to_additive]
theorem prod_dite_of_true {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, f x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_true Finset.prod_dite_of_true
#align finset.sum_dite_of_true Finset.sum_dite_of_true
@[to_additive]
theorem nonempty_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun H => False.elim <| h <| H.symm ▸ prod_empty) id
#align finset.nonempty_of_prod_ne_one Finset.nonempty_of_prod_ne_one
#align finset.nonempty_of_sum_ne_zero Finset.nonempty_of_sum_ne_zero
@[to_additive]
theorem exists_ne_one_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : ∃ a ∈ s, f a ≠ 1 := by
classical
rw [← prod_filter_ne_one] at h
rcases nonempty_of_prod_ne_one h with ⟨x, hx⟩
exact ⟨x, (mem_filter.1 hx).1, by simpa using (mem_filter.1 hx).2⟩
#align finset.exists_ne_one_of_prod_ne_one Finset.exists_ne_one_of_prod_ne_one
#align finset.exists_ne_zero_of_sum_ne_zero Finset.exists_ne_zero_of_sum_ne_zero
@[to_additive]
theorem prod_range_succ_comm (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = f n * ∏ x ∈ range n, f x := by
rw [range_succ, prod_insert not_mem_range_self]
#align finset.prod_range_succ_comm Finset.prod_range_succ_comm
#align finset.sum_range_succ_comm Finset.sum_range_succ_comm
@[to_additive]
theorem prod_range_succ (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = (∏ x ∈ range n, f x) * f n := by
simp only [mul_comm, prod_range_succ_comm]
#align finset.prod_range_succ Finset.prod_range_succ
#align finset.sum_range_succ Finset.sum_range_succ
@[to_additive]
theorem prod_range_succ' (f : ℕ → β) :
∀ n : ℕ, (∏ k ∈ range (n + 1), f k) = (∏ k ∈ range n, f (k + 1)) * f 0
| 0 => prod_range_succ _ _
| n + 1 => by rw [prod_range_succ _ n, mul_right_comm, ← prod_range_succ' _ n, prod_range_succ]
#align finset.prod_range_succ' Finset.prod_range_succ'
#align finset.sum_range_succ' Finset.sum_range_succ'
@[to_additive]
theorem eventually_constant_prod {u : ℕ → β} {N : ℕ} (hu : ∀ n ≥ N, u n = 1) {n : ℕ} (hn : N ≤ n) :
(∏ k ∈ range n, u k) = ∏ k ∈ range N, u k := by
obtain ⟨m, rfl : n = N + m⟩ := Nat.exists_eq_add_of_le hn
clear hn
induction' m with m hm
· simp
· simp [← add_assoc, prod_range_succ, hm, hu]
#align finset.eventually_constant_prod Finset.eventually_constant_prod
#align finset.eventually_constant_sum Finset.eventually_constant_sum
@[to_additive]
theorem prod_range_add (f : ℕ → β) (n m : ℕ) :
(∏ x ∈ range (n + m), f x) = (∏ x ∈ range n, f x) * ∏ x ∈ range m, f (n + x) := by
induction' m with m hm
· simp
· erw [Nat.add_succ, prod_range_succ, prod_range_succ, hm, mul_assoc]
#align finset.prod_range_add Finset.prod_range_add
#align finset.sum_range_add Finset.sum_range_add
@[to_additive]
theorem prod_range_add_div_prod_range {α : Type*} [CommGroup α] (f : ℕ → α) (n m : ℕ) :
(∏ k ∈ range (n + m), f k) / ∏ k ∈ range n, f k = ∏ k ∈ Finset.range m, f (n + k) :=
div_eq_of_eq_mul' (prod_range_add f n m)
#align finset.prod_range_add_div_prod_range Finset.prod_range_add_div_prod_range
#align finset.sum_range_add_sub_sum_range Finset.sum_range_add_sub_sum_range
@[to_additive]
theorem prod_range_zero (f : ℕ → β) : ∏ k ∈ range 0, f k = 1 := by rw [range_zero, prod_empty]
#align finset.prod_range_zero Finset.prod_range_zero
#align finset.sum_range_zero Finset.sum_range_zero
@[to_additive sum_range_one]
theorem prod_range_one (f : ℕ → β) : ∏ k ∈ range 1, f k = f 0 := by
rw [range_one, prod_singleton]
#align finset.prod_range_one Finset.prod_range_one
#align finset.sum_range_one Finset.sum_range_one
open List
@[to_additive]
theorem prod_list_map_count [DecidableEq α] (l : List α) {M : Type*} [CommMonoid M] (f : α → M) :
(l.map f).prod = ∏ m ∈ l.toFinset, f m ^ l.count m := by
induction' l with a s IH; · simp only [map_nil, prod_nil, count_nil, pow_zero, prod_const_one]
simp only [List.map, List.prod_cons, toFinset_cons, IH]
by_cases has : a ∈ s.toFinset
· rw [insert_eq_of_mem has, ← insert_erase has, prod_insert (not_mem_erase _ _),
prod_insert (not_mem_erase _ _), ← mul_assoc, count_cons_self, pow_succ']
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne (ne_of_mem_erase hx)]
rw [prod_insert has, count_cons_self, count_eq_zero_of_not_mem (mt mem_toFinset.2 has), pow_one]
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne]
rintro rfl
exact has hx
#align finset.prod_list_map_count Finset.prod_list_map_count
#align finset.sum_list_map_count Finset.sum_list_map_count
@[to_additive]
theorem prod_list_count [DecidableEq α] [CommMonoid α] (s : List α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by simpa using prod_list_map_count s id
#align finset.prod_list_count Finset.prod_list_count
#align finset.sum_list_count Finset.sum_list_count
@[to_additive]
theorem prod_list_count_of_subset [DecidableEq α] [CommMonoid α] (m : List α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
rw [prod_list_count]
refine prod_subset hs fun x _ hx => ?_
rw [mem_toFinset] at hx
rw [count_eq_zero_of_not_mem hx, pow_zero]
#align finset.prod_list_count_of_subset Finset.prod_list_count_of_subset
#align finset.sum_list_count_of_subset Finset.sum_list_count_of_subset
theorem sum_filter_count_eq_countP [DecidableEq α] (p : α → Prop) [DecidablePred p] (l : List α) :
∑ x ∈ l.toFinset.filter p, l.count x = l.countP p := by
simp [Finset.sum, sum_map_count_dedup_filter_eq_countP p l]
#align finset.sum_filter_count_eq_countp Finset.sum_filter_count_eq_countP
open Multiset
@[to_additive]
theorem prod_multiset_map_count [DecidableEq α] (s : Multiset α) {M : Type*} [CommMonoid M]
(f : α → M) : (s.map f).prod = ∏ m ∈ s.toFinset, f m ^ s.count m := by
refine Quot.induction_on s fun l => ?_
simp [prod_list_map_count l f]
#align finset.prod_multiset_map_count Finset.prod_multiset_map_count
#align finset.sum_multiset_map_count Finset.sum_multiset_map_count
@[to_additive]
theorem prod_multiset_count [DecidableEq α] [CommMonoid α] (s : Multiset α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by
convert prod_multiset_map_count s id
rw [Multiset.map_id]
#align finset.prod_multiset_count Finset.prod_multiset_count
#align finset.sum_multiset_count Finset.sum_multiset_count
@[to_additive]
theorem prod_multiset_count_of_subset [DecidableEq α] [CommMonoid α] (m : Multiset α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
revert hs
refine Quot.induction_on m fun l => ?_
simp only [quot_mk_to_coe'', prod_coe, coe_count]
apply prod_list_count_of_subset l s
#align finset.prod_multiset_count_of_subset Finset.prod_multiset_count_of_subset
#align finset.sum_multiset_count_of_subset Finset.sum_multiset_count_of_subset
@[to_additive]
theorem prod_mem_multiset [DecidableEq α] (m : Multiset α) (f : { x // x ∈ m } → β) (g : α → β)
(hfg : ∀ x, f x = g x) : ∏ x : { x // x ∈ m }, f x = ∏ x ∈ m.toFinset, g x := by
refine prod_bij' (fun x _ ↦ x) (fun x hx ↦ ⟨x, Multiset.mem_toFinset.1 hx⟩) ?_ ?_ ?_ ?_ ?_ <;>
simp [hfg]
#align finset.prod_mem_multiset Finset.prod_mem_multiset
#align finset.sum_mem_multiset Finset.sum_mem_multiset
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction _ _ hom unit (Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction Finset.prod_induction
#align finset.sum_induction Finset.sum_induction
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction_nonempty {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (nonempty : s.Nonempty) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction_nonempty p hom (by simp [nonempty_iff_ne_empty.mp nonempty])
(Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction_nonempty Finset.prod_induction_nonempty
#align finset.sum_induction_nonempty Finset.sum_induction_nonempty
/-- For any product along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can verify
that it's equal to a different function just by checking ratios of adjacent terms.
This is a multiplicative discrete analogue of the fundamental theorem of calculus. -/
@[to_additive "For any sum along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can
verify that it's equal to a different function just by checking differences of adjacent terms.
This is a discrete analogue of the fundamental theorem of calculus."]
theorem prod_range_induction (f s : ℕ → β) (base : s 0 = 1)
(step : ∀ n, s (n + 1) = s n * f n) (n : ℕ) :
∏ k ∈ Finset.range n, f k = s n := by
induction' n with k hk
· rw [Finset.prod_range_zero, base]
· simp only [hk, Finset.prod_range_succ, step, mul_comm]
#align finset.prod_range_induction Finset.prod_range_induction
#align finset.sum_range_induction Finset.sum_range_induction
/-- A telescoping product along `{0, ..., n - 1}` of a commutative group valued function reduces to
the ratio of the last and first factors. -/
@[to_additive "A telescoping sum along `{0, ..., n - 1}` of an additive commutative group valued
function reduces to the difference of the last and first terms."]
theorem prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f (i + 1) / f i) = f n / f 0 := by apply prod_range_induction <;> simp
#align finset.prod_range_div Finset.prod_range_div
#align finset.sum_range_sub Finset.sum_range_sub
@[to_additive]
theorem prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f i / f (i + 1)) = f 0 / f n := by apply prod_range_induction <;> simp
#align finset.prod_range_div' Finset.prod_range_div'
#align finset.sum_range_sub' Finset.sum_range_sub'
@[to_additive]
theorem eq_prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = f 0 * ∏ i ∈ range n, f (i + 1) / f i := by rw [prod_range_div, mul_div_cancel]
#align finset.eq_prod_range_div Finset.eq_prod_range_div
#align finset.eq_sum_range_sub Finset.eq_sum_range_sub
@[to_additive]
theorem eq_prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = ∏ i ∈ range (n + 1), if i = 0 then f 0 else f i / f (i - 1) := by
conv_lhs => rw [Finset.eq_prod_range_div f]
simp [Finset.prod_range_succ', mul_comm]
#align finset.eq_prod_range_div' Finset.eq_prod_range_div'
#align finset.eq_sum_range_sub' Finset.eq_sum_range_sub'
/-- A telescoping sum along `{0, ..., n-1}` of an `ℕ`-valued function
reduces to the difference of the last and first terms
when the function we are summing is monotone.
-/
theorem sum_range_tsub [CanonicallyOrderedAddCommMonoid α] [Sub α] [OrderedSub α]
[ContravariantClass α α (· + ·) (· ≤ ·)] {f : ℕ → α} (h : Monotone f) (n : ℕ) :
∑ i ∈ range n, (f (i + 1) - f i) = f n - f 0 := by
apply sum_range_induction
case base => apply tsub_self
case step =>
intro n
have h₁ : f n ≤ f (n + 1) := h (Nat.le_succ _)
have h₂ : f 0 ≤ f n := h (Nat.zero_le _)
rw [tsub_add_eq_add_tsub h₂, add_tsub_cancel_of_le h₁]
#align finset.sum_range_tsub Finset.sum_range_tsub
@[to_additive (attr := simp)]
theorem prod_const (b : β) : ∏ _x ∈ s, b = b ^ s.card :=
(congr_arg _ <| s.val.map_const b).trans <| Multiset.prod_replicate s.card b
#align finset.prod_const Finset.prod_const
#align finset.sum_const Finset.sum_const
@[to_additive sum_eq_card_nsmul]
theorem prod_eq_pow_card {b : β} (hf : ∀ a ∈ s, f a = b) : ∏ a ∈ s, f a = b ^ s.card :=
(prod_congr rfl hf).trans <| prod_const _
#align finset.prod_eq_pow_card Finset.prod_eq_pow_card
#align finset.sum_eq_card_nsmul Finset.sum_eq_card_nsmul
@[to_additive card_nsmul_add_sum]
theorem pow_card_mul_prod {b : β} : b ^ s.card * ∏ a ∈ s, f a = ∏ a ∈ s, b * f a :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive sum_add_card_nsmul]
theorem prod_mul_pow_card {b : β} : (∏ a ∈ s, f a) * b ^ s.card = ∏ a ∈ s, f a * b :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive]
theorem pow_eq_prod_const (b : β) : ∀ n, b ^ n = ∏ _k ∈ range n, b := by simp
#align finset.pow_eq_prod_const Finset.pow_eq_prod_const
#align finset.nsmul_eq_sum_const Finset.nsmul_eq_sum_const
@[to_additive]
theorem prod_pow (s : Finset α) (n : ℕ) (f : α → β) : ∏ x ∈ s, f x ^ n = (∏ x ∈ s, f x) ^ n :=
Multiset.prod_map_pow
#align finset.prod_pow Finset.prod_pow
#align finset.sum_nsmul Finset.sum_nsmul
@[to_additive sum_nsmul_assoc]
lemma prod_pow_eq_pow_sum (s : Finset ι) (f : ι → ℕ) (a : β) :
∏ i ∈ s, a ^ f i = a ^ ∑ i ∈ s, f i :=
cons_induction (by simp) (fun _ _ _ _ ↦ by simp [prod_cons, sum_cons, pow_add, *]) s
#align finset.prod_pow_eq_pow_sum Finset.prod_pow_eq_pow_sum
/-- A product over `Finset.powersetCard` which only depends on the size of the sets is constant. -/
@[to_additive
"A sum over `Finset.powersetCard` which only depends on the size of the sets is constant."]
lemma prod_powersetCard (n : ℕ) (s : Finset α) (f : ℕ → β) :
∏ t ∈ powersetCard n s, f t.card = f n ^ s.card.choose n := by
rw [prod_eq_pow_card, card_powersetCard]; rintro a ha; rw [(mem_powersetCard.1 ha).2]
@[to_additive]
theorem prod_flip {n : ℕ} (f : ℕ → β) :
(∏ r ∈ range (n + 1), f (n - r)) = ∏ k ∈ range (n + 1), f k := by
induction' n with n ih
· rw [prod_range_one, prod_range_one]
· rw [prod_range_succ', prod_range_succ _ (Nat.succ n)]
simp [← ih]
#align finset.prod_flip Finset.prod_flip
#align finset.sum_flip Finset.sum_flip
@[to_additive]
theorem prod_involution {s : Finset α} {f : α → β} :
∀ (g : ∀ a ∈ s, α) (_ : ∀ a ha, f a * f (g a ha) = 1) (_ : ∀ a ha, f a ≠ 1 → g a ha ≠ a)
(g_mem : ∀ a ha, g a ha ∈ s) (_ : ∀ a ha, g (g a ha) (g_mem a ha) = a),
∏ x ∈ s, f x = 1 := by
haveI := Classical.decEq α; haveI := Classical.decEq β
exact
Finset.strongInductionOn s fun s ih g h g_ne g_mem g_inv =>
s.eq_empty_or_nonempty.elim (fun hs => hs.symm ▸ rfl) fun ⟨x, hx⟩ =>
have hmem : ∀ y ∈ (s.erase x).erase (g x hx), y ∈ s := fun y hy =>
mem_of_mem_erase (mem_of_mem_erase hy)
have g_inj : ∀ {x hx y hy}, g x hx = g y hy → x = y := fun {x hx y hy} h => by
rw [← g_inv x hx, ← g_inv y hy]; simp [h]
have ih' : (∏ y ∈ erase (erase s x) (g x hx), f y) = (1 : β) :=
ih ((s.erase x).erase (g x hx))
⟨Subset.trans (erase_subset _ _) (erase_subset _ _), fun h =>
not_mem_erase (g x hx) (s.erase x) (h (g_mem x hx))⟩
(fun y hy => g y (hmem y hy)) (fun y hy => h y (hmem y hy))
(fun y hy => g_ne y (hmem y hy))
(fun y hy =>
mem_erase.2
⟨fun h : g y _ = g x hx => by simp [g_inj h] at hy,
mem_erase.2
⟨fun h : g y _ = x => by
have : y = g x hx := g_inv y (hmem y hy) ▸ by simp [h]
simp [this] at hy, g_mem y (hmem y hy)⟩⟩)
fun y hy => g_inv y (hmem y hy)
if hx1 : f x = 1 then
ih' ▸
Eq.symm
(prod_subset hmem fun y hy hy₁ =>
have : y = x ∨ y = g x hx := by
simpa [hy, -not_and, mem_erase, not_and_or, or_comm] using hy₁
this.elim (fun hy => hy.symm ▸ hx1) fun hy =>
h x hx ▸ hy ▸ hx1.symm ▸ (one_mul _).symm)
else by
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase.2 ⟨g_ne x hx hx1, g_mem x hx⟩),
prod_insert (not_mem_erase _ _), ih', mul_one, h x hx]
#align finset.prod_involution Finset.prod_involution
#align finset.sum_involution Finset.sum_involution
/-- The product of the composition of functions `f` and `g`, is the product over `b ∈ s.image g` of
`f b` to the power of the cardinality of the fibre of `b`. See also `Finset.prod_image`. -/
@[to_additive "The sum of the composition of functions `f` and `g`, is the sum over `b ∈ s.image g`
of `f b` times of the cardinality of the fibre of `b`. See also `Finset.sum_image`."]
theorem prod_comp [DecidableEq γ] (f : γ → β) (g : α → γ) :
∏ a ∈ s, f (g a) = ∏ b ∈ s.image g, f b ^ (s.filter fun a => g a = b).card := by
simp_rw [← prod_const, prod_fiberwise_of_maps_to' fun _ ↦ mem_image_of_mem _]
#align finset.prod_comp Finset.prod_comp
#align finset.sum_comp Finset.sum_comp
@[to_additive]
theorem prod_piecewise [DecidableEq α] (s t : Finset α) (f g : α → β) :
(∏ x ∈ s, (t.piecewise f g) x) = (∏ x ∈ s ∩ t, f x) * ∏ x ∈ s \ t, g x := by
erw [prod_ite, filter_mem_eq_inter, ← sdiff_eq_filter]
#align finset.prod_piecewise Finset.prod_piecewise
#align finset.sum_piecewise Finset.sum_piecewise
@[to_additive]
theorem prod_inter_mul_prod_diff [DecidableEq α] (s t : Finset α) (f : α → β) :
(∏ x ∈ s ∩ t, f x) * ∏ x ∈ s \ t, f x = ∏ x ∈ s, f x := by
convert (s.prod_piecewise t f f).symm
simp (config := { unfoldPartialApp := true }) [Finset.piecewise]
#align finset.prod_inter_mul_prod_diff Finset.prod_inter_mul_prod_diff
#align finset.sum_inter_add_sum_diff Finset.sum_inter_add_sum_diff
@[to_additive]
theorem prod_eq_mul_prod_diff_singleton [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s)
(f : α → β) : ∏ x ∈ s, f x = f i * ∏ x ∈ s \ {i}, f x := by
convert (s.prod_inter_mul_prod_diff {i} f).symm
simp [h]
#align finset.prod_eq_mul_prod_diff_singleton Finset.prod_eq_mul_prod_diff_singleton
#align finset.sum_eq_add_sum_diff_singleton Finset.sum_eq_add_sum_diff_singleton
@[to_additive]
theorem prod_eq_prod_diff_singleton_mul [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s)
(f : α → β) : ∏ x ∈ s, f x = (∏ x ∈ s \ {i}, f x) * f i := by
rw [prod_eq_mul_prod_diff_singleton h, mul_comm]
#align finset.prod_eq_prod_diff_singleton_mul Finset.prod_eq_prod_diff_singleton_mul
#align finset.sum_eq_sum_diff_singleton_add Finset.sum_eq_sum_diff_singleton_add
@[to_additive]
theorem _root_.Fintype.prod_eq_mul_prod_compl [DecidableEq α] [Fintype α] (a : α) (f : α → β) :
∏ i, f i = f a * ∏ i ∈ {a}ᶜ, f i :=
prod_eq_mul_prod_diff_singleton (mem_univ a) f
#align fintype.prod_eq_mul_prod_compl Fintype.prod_eq_mul_prod_compl
#align fintype.sum_eq_add_sum_compl Fintype.sum_eq_add_sum_compl
@[to_additive]
theorem _root_.Fintype.prod_eq_prod_compl_mul [DecidableEq α] [Fintype α] (a : α) (f : α → β) :
∏ i, f i = (∏ i ∈ {a}ᶜ, f i) * f a :=
prod_eq_prod_diff_singleton_mul (mem_univ a) f
#align fintype.prod_eq_prod_compl_mul Fintype.prod_eq_prod_compl_mul
#align fintype.sum_eq_sum_compl_add Fintype.sum_eq_sum_compl_add
theorem dvd_prod_of_mem (f : α → β) {a : α} {s : Finset α} (ha : a ∈ s) : f a ∣ ∏ i ∈ s, f i := by
classical
rw [Finset.prod_eq_mul_prod_diff_singleton ha]
exact dvd_mul_right _ _
#align finset.dvd_prod_of_mem Finset.dvd_prod_of_mem
/-- A product can be partitioned into a product of products, each equivalent under a setoid. -/
@[to_additive "A sum can be partitioned into a sum of sums, each equivalent under a setoid."]
theorem prod_partition (R : Setoid α) [DecidableRel R.r] :
∏ x ∈ s, f x = ∏ xbar ∈ s.image Quotient.mk'', ∏ y ∈ s.filter (⟦·⟧ = xbar), f y := by
refine (Finset.prod_image' f fun x _hx => ?_).symm
rfl
#align finset.prod_partition Finset.prod_partition
#align finset.sum_partition Finset.sum_partition
/-- If we can partition a product into subsets that cancel out, then the whole product cancels. -/
@[to_additive "If we can partition a sum into subsets that cancel out, then the whole sum cancels."]
theorem prod_cancels_of_partition_cancels (R : Setoid α) [DecidableRel R.r]
(h : ∀ x ∈ s, ∏ a ∈ s.filter fun y => y ≈ x, f a = 1) : ∏ x ∈ s, f x = 1 := by
rw [prod_partition R, ← Finset.prod_eq_one]
intro xbar xbar_in_s
obtain ⟨x, x_in_s, rfl⟩ := mem_image.mp xbar_in_s
simp only [← Quotient.eq] at h
exact h x x_in_s
#align finset.prod_cancels_of_partition_cancels Finset.prod_cancels_of_partition_cancels
#align finset.sum_cancels_of_partition_cancels Finset.sum_cancels_of_partition_cancels
@[to_additive]
theorem prod_update_of_not_mem [DecidableEq α] {s : Finset α} {i : α} (h : i ∉ s) (f : α → β)
(b : β) : ∏ x ∈ s, Function.update f i b x = ∏ x ∈ s, f x := by
apply prod_congr rfl
intros j hj
have : j ≠ i := by
rintro rfl
exact h hj
simp [this]
#align finset.prod_update_of_not_mem Finset.prod_update_of_not_mem
#align finset.sum_update_of_not_mem Finset.sum_update_of_not_mem
@[to_additive]
theorem prod_update_of_mem [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s) (f : α → β) (b : β) :
∏ x ∈ s, Function.update f i b x = b * ∏ x ∈ s \ singleton i, f x := by
rw [update_eq_piecewise, prod_piecewise]
simp [h]
#align finset.prod_update_of_mem Finset.prod_update_of_mem
#align finset.sum_update_of_mem Finset.sum_update_of_mem
/-- If a product of a `Finset` of size at most 1 has a given value, so
do the terms in that product. -/
@[to_additive eq_of_card_le_one_of_sum_eq "If a sum of a `Finset` of size at most 1 has a given
value, so do the terms in that sum."]
theorem eq_of_card_le_one_of_prod_eq {s : Finset α} (hc : s.card ≤ 1) {f : α → β} {b : β}
(h : ∏ x ∈ s, f x = b) : ∀ x ∈ s, f x = b := by
intro x hx
by_cases hc0 : s.card = 0
· exact False.elim (card_ne_zero_of_mem hx hc0)
· have h1 : s.card = 1 := le_antisymm hc (Nat.one_le_of_lt (Nat.pos_of_ne_zero hc0))
rw [card_eq_one] at h1
cases' h1 with x2 hx2
rw [hx2, mem_singleton] at hx
simp_rw [hx2] at h
rw [hx]
rw [prod_singleton] at h
exact h
#align finset.eq_of_card_le_one_of_prod_eq Finset.eq_of_card_le_one_of_prod_eq
#align finset.eq_of_card_le_one_of_sum_eq Finset.eq_of_card_le_one_of_sum_eq
/-- Taking a product over `s : Finset α` is the same as multiplying the value on a single element
`f a` by the product of `s.erase a`.
See `Multiset.prod_map_erase` for the `Multiset` version. -/
@[to_additive "Taking a sum over `s : Finset α` is the same as adding the value on a single element
`f a` to the sum over `s.erase a`.
See `Multiset.sum_map_erase` for the `Multiset` version."]
theorem mul_prod_erase [DecidableEq α] (s : Finset α) (f : α → β) {a : α} (h : a ∈ s) :
(f a * ∏ x ∈ s.erase a, f x) = ∏ x ∈ s, f x := by
rw [← prod_insert (not_mem_erase a s), insert_erase h]
#align finset.mul_prod_erase Finset.mul_prod_erase
#align finset.add_sum_erase Finset.add_sum_erase
/-- A variant of `Finset.mul_prod_erase` with the multiplication swapped. -/
@[to_additive "A variant of `Finset.add_sum_erase` with the addition swapped."]
theorem prod_erase_mul [DecidableEq α] (s : Finset α) (f : α → β) {a : α} (h : a ∈ s) :
(∏ x ∈ s.erase a, f x) * f a = ∏ x ∈ s, f x := by rw [mul_comm, mul_prod_erase s f h]
#align finset.prod_erase_mul Finset.prod_erase_mul
#align finset.sum_erase_add Finset.sum_erase_add
/-- If a function applied at a point is 1, a product is unchanged by
removing that point, if present, from a `Finset`. -/
@[to_additive "If a function applied at a point is 0, a sum is unchanged by
removing that point, if present, from a `Finset`."]
theorem prod_erase [DecidableEq α] (s : Finset α) {f : α → β} {a : α} (h : f a = 1) :
∏ x ∈ s.erase a, f x = ∏ x ∈ s, f x := by
rw [← sdiff_singleton_eq_erase]
refine prod_subset sdiff_subset fun x hx hnx => ?_
rw [sdiff_singleton_eq_erase] at hnx
rwa [eq_of_mem_of_not_mem_erase hx hnx]
#align finset.prod_erase Finset.prod_erase
#align finset.sum_erase Finset.sum_erase
/-- See also `Finset.prod_boole`. -/
@[to_additive "See also `Finset.sum_boole`."]
theorem prod_ite_one (s : Finset α) (p : α → Prop) [DecidablePred p]
(h : ∀ i ∈ s, ∀ j ∈ s, p i → p j → i = j) (a : β) :
∏ i ∈ s, ite (p i) a 1 = ite (∃ i ∈ s, p i) a 1 := by
split_ifs with h
· obtain ⟨i, hi, hpi⟩ := h
rw [prod_eq_single_of_mem _ hi, if_pos hpi]
exact fun j hj hji ↦ if_neg fun hpj ↦ hji <| h _ hj _ hi hpj hpi
· push_neg at h
rw [prod_eq_one]
exact fun i hi => if_neg (h i hi)
#align finset.prod_ite_one Finset.prod_ite_one
#align finset.sum_ite_zero Finset.sum_ite_zero
@[to_additive]
theorem prod_erase_lt_of_one_lt {γ : Type*} [DecidableEq α] [OrderedCommMonoid γ]
[CovariantClass γ γ (· * ·) (· < ·)] {s : Finset α} {d : α} (hd : d ∈ s) {f : α → γ}
(hdf : 1 < f d) : ∏ m ∈ s.erase d, f m < ∏ m ∈ s, f m := by
conv in ∏ m ∈ s, f m => rw [← Finset.insert_erase hd]
rw [Finset.prod_insert (Finset.not_mem_erase d s)]
exact lt_mul_of_one_lt_left' _ hdf
#align finset.prod_erase_lt_of_one_lt Finset.prod_erase_lt_of_one_lt
#align finset.sum_erase_lt_of_pos Finset.sum_erase_lt_of_pos
/-- If a product is 1 and the function is 1 except possibly at one
point, it is 1 everywhere on the `Finset`. -/
@[to_additive "If a sum is 0 and the function is 0 except possibly at one
point, it is 0 everywhere on the `Finset`."]
theorem eq_one_of_prod_eq_one {s : Finset α} {f : α → β} {a : α} (hp : ∏ x ∈ s, f x = 1)
(h1 : ∀ x ∈ s, x ≠ a → f x = 1) : ∀ x ∈ s, f x = 1 := by
intro x hx
classical
by_cases h : x = a
· rw [h]
rw [h] at hx
rw [← prod_subset (singleton_subset_iff.2 hx) fun t ht ha => h1 t ht (not_mem_singleton.1 ha),
prod_singleton] at hp
exact hp
· exact h1 x hx h
#align finset.eq_one_of_prod_eq_one Finset.eq_one_of_prod_eq_one
#align finset.eq_zero_of_sum_eq_zero Finset.eq_zero_of_sum_eq_zero
@[to_additive sum_boole_nsmul]
theorem prod_pow_boole [DecidableEq α] (s : Finset α) (f : α → β) (a : α) :
(∏ x ∈ s, f x ^ ite (a = x) 1 0) = ite (a ∈ s) (f a) 1 := by simp
#align finset.prod_pow_boole Finset.prod_pow_boole
theorem prod_dvd_prod_of_dvd {S : Finset α} (g1 g2 : α → β) (h : ∀ a ∈ S, g1 a ∣ g2 a) :
S.prod g1 ∣ S.prod g2 := by
classical
induction' S using Finset.induction_on' with a T _haS _hTS haT IH
· simp
· rw [Finset.prod_insert haT, prod_insert haT]
exact mul_dvd_mul (h a <| T.mem_insert_self a) <| IH fun b hb ↦ h b <| mem_insert_of_mem hb
#align finset.prod_dvd_prod_of_dvd Finset.prod_dvd_prod_of_dvd
theorem prod_dvd_prod_of_subset {ι M : Type*} [CommMonoid M] (s t : Finset ι) (f : ι → M)
(h : s ⊆ t) : (∏ i ∈ s, f i) ∣ ∏ i ∈ t, f i :=
Multiset.prod_dvd_prod_of_le <| Multiset.map_le_map <| by simpa
#align finset.prod_dvd_prod_of_subset Finset.prod_dvd_prod_of_subset
end CommMonoid
section CancelCommMonoid
variable [DecidableEq ι] [CancelCommMonoid α] {s t : Finset ι} {f : ι → α}
@[to_additive]
lemma prod_sdiff_eq_prod_sdiff_iff :
∏ i ∈ s \ t, f i = ∏ i ∈ t \ s, f i ↔ ∏ i ∈ s, f i = ∏ i ∈ t, f i :=
eq_comm.trans $ eq_iff_eq_of_mul_eq_mul $ by
rw [← prod_union disjoint_sdiff_self_left, ← prod_union disjoint_sdiff_self_left,
sdiff_union_self_eq_union, sdiff_union_self_eq_union, union_comm]
@[to_additive]
lemma prod_sdiff_ne_prod_sdiff_iff :
∏ i ∈ s \ t, f i ≠ ∏ i ∈ t \ s, f i ↔ ∏ i ∈ s, f i ≠ ∏ i ∈ t, f i :=
prod_sdiff_eq_prod_sdiff_iff.not
end CancelCommMonoid
theorem card_eq_sum_ones (s : Finset α) : s.card = ∑ x ∈ s, 1 := by simp
#align finset.card_eq_sum_ones Finset.card_eq_sum_ones
theorem sum_const_nat {m : ℕ} {f : α → ℕ} (h₁ : ∀ x ∈ s, f x = m) :
∑ x ∈ s, f x = card s * m := by
rw [← Nat.nsmul_eq_mul, ← sum_const]
apply sum_congr rfl h₁
#align finset.sum_const_nat Finset.sum_const_nat
lemma sum_card_fiberwise_eq_card_filter {κ : Type*} [DecidableEq κ] (s : Finset ι) (t : Finset κ)
(g : ι → κ) : ∑ j ∈ t, (s.filter fun i ↦ g i = j).card = (s.filter fun i ↦ g i ∈ t).card := by
simpa only [card_eq_sum_ones] using sum_fiberwise_eq_sum_filter _ _ _ _
lemma card_filter (p) [DecidablePred p] (s : Finset α) :
(filter p s).card = ∑ a ∈ s, ite (p a) 1 0 := by simp [sum_ite]
#align finset.card_filter Finset.card_filter
section Opposite
open MulOpposite
/-- Moving to the opposite additive commutative monoid commutes with summing. -/
@[simp]
theorem op_sum [AddCommMonoid β] {s : Finset α} (f : α → β) :
op (∑ x ∈ s, f x) = ∑ x ∈ s, op (f x) :=
map_sum (opAddEquiv : β ≃+ βᵐᵒᵖ) _ _
#align finset.op_sum Finset.op_sum
@[simp]
theorem unop_sum [AddCommMonoid β] {s : Finset α} (f : α → βᵐᵒᵖ) :
unop (∑ x ∈ s, f x) = ∑ x ∈ s, unop (f x) :=
map_sum (opAddEquiv : β ≃+ βᵐᵒᵖ).symm _ _
#align finset.unop_sum Finset.unop_sum
end Opposite
section DivisionCommMonoid
variable [DivisionCommMonoid β]
@[to_additive (attr := simp)]
theorem prod_inv_distrib : (∏ x ∈ s, (f x)⁻¹) = (∏ x ∈ s, f x)⁻¹ :=
Multiset.prod_map_inv
#align finset.prod_inv_distrib Finset.prod_inv_distrib
#align finset.sum_neg_distrib Finset.sum_neg_distrib
@[to_additive (attr := simp)]
theorem prod_div_distrib : ∏ x ∈ s, f x / g x = (∏ x ∈ s, f x) / ∏ x ∈ s, g x :=
Multiset.prod_map_div
#align finset.prod_div_distrib Finset.prod_div_distrib
#align finset.sum_sub_distrib Finset.sum_sub_distrib
@[to_additive]
theorem prod_zpow (f : α → β) (s : Finset α) (n : ℤ) : ∏ a ∈ s, f a ^ n = (∏ a ∈ s, f a) ^ n :=
Multiset.prod_map_zpow
#align finset.prod_zpow Finset.prod_zpow
#align finset.sum_zsmul Finset.sum_zsmul
end DivisionCommMonoid
section CommGroup
variable [CommGroup β] [DecidableEq α]
@[to_additive (attr := simp)]
theorem prod_sdiff_eq_div (h : s₁ ⊆ s₂) :
∏ x ∈ s₂ \ s₁, f x = (∏ x ∈ s₂, f x) / ∏ x ∈ s₁, f x := by
rw [eq_div_iff_mul_eq', prod_sdiff h]
#align finset.prod_sdiff_eq_div Finset.prod_sdiff_eq_div
#align finset.sum_sdiff_eq_sub Finset.sum_sdiff_eq_sub
@[to_additive]
theorem prod_sdiff_div_prod_sdiff :
(∏ x ∈ s₂ \ s₁, f x) / ∏ x ∈ s₁ \ s₂, f x = (∏ x ∈ s₂, f x) / ∏ x ∈ s₁, f x := by
simp [← Finset.prod_sdiff (@inf_le_left _ _ s₁ s₂), ← Finset.prod_sdiff (@inf_le_right _ _ s₁ s₂)]
#align finset.prod_sdiff_div_prod_sdiff Finset.prod_sdiff_div_prod_sdiff
#align finset.sum_sdiff_sub_sum_sdiff Finset.sum_sdiff_sub_sum_sdiff
@[to_additive (attr := simp)]
theorem prod_erase_eq_div {a : α} (h : a ∈ s) :
∏ x ∈ s.erase a, f x = (∏ x ∈ s, f x) / f a := by
rw [eq_div_iff_mul_eq', prod_erase_mul _ _ h]
#align finset.prod_erase_eq_div Finset.prod_erase_eq_div
#align finset.sum_erase_eq_sub Finset.sum_erase_eq_sub
end CommGroup
@[simp]
theorem card_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) :
card (s.sigma t) = ∑ a ∈ s, card (t a) :=
Multiset.card_sigma _ _
#align finset.card_sigma Finset.card_sigma
@[simp]
theorem card_disjiUnion (s : Finset α) (t : α → Finset β) (h) :
(s.disjiUnion t h).card = s.sum fun i => (t i).card :=
Multiset.card_bind _ _
#align finset.card_disj_Union Finset.card_disjiUnion
theorem card_biUnion [DecidableEq β] {s : Finset α} {t : α → Finset β}
(h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → Disjoint (t x) (t y)) :
(s.biUnion t).card = ∑ u ∈ s, card (t u) :=
calc
(s.biUnion t).card = ∑ i ∈ s.biUnion t, 1 := card_eq_sum_ones _
_ = ∑ a ∈ s, ∑ _i ∈ t a, 1 := Finset.sum_biUnion h
_ = ∑ u ∈ s, card (t u) := by simp_rw [card_eq_sum_ones]
#align finset.card_bUnion Finset.card_biUnion
theorem card_biUnion_le [DecidableEq β] {s : Finset α} {t : α → Finset β} :
(s.biUnion t).card ≤ ∑ a ∈ s, (t a).card :=
haveI := Classical.decEq α
Finset.induction_on s (by simp) fun a s has ih =>
calc
((insert a s).biUnion t).card ≤ (t a).card + (s.biUnion t).card := by
{ rw [biUnion_insert]; exact Finset.card_union_le _ _ }
_ ≤ ∑ a ∈ insert a s, card (t a) := by rw [sum_insert has]; exact Nat.add_le_add_left ih _
#align finset.card_bUnion_le Finset.card_biUnion_le
theorem card_eq_sum_card_fiberwise [DecidableEq β] {f : α → β} {s : Finset α} {t : Finset β}
(H : ∀ x ∈ s, f x ∈ t) : s.card = ∑ a ∈ t, (s.filter fun x => f x = a).card := by
simp only [card_eq_sum_ones, sum_fiberwise_of_maps_to H]
#align finset.card_eq_sum_card_fiberwise Finset.card_eq_sum_card_fiberwise
theorem card_eq_sum_card_image [DecidableEq β] (f : α → β) (s : Finset α) :
s.card = ∑ a ∈ s.image f, (s.filter fun x => f x = a).card :=
card_eq_sum_card_fiberwise fun _ => mem_image_of_mem _
#align finset.card_eq_sum_card_image Finset.card_eq_sum_card_image
theorem mem_sum {f : α → Multiset β} (s : Finset α) (b : β) :
(b ∈ ∑ x ∈ s, f x) ↔ ∃ a ∈ s, b ∈ f a := by
classical
refine s.induction_on (by simp) ?_
intro a t hi ih
simp [sum_insert hi, ih, or_and_right, exists_or]
#align finset.mem_sum Finset.mem_sum
@[to_additive]
theorem prod_unique_nonempty {α β : Type*} [CommMonoid β] [Unique α] (s : Finset α) (f : α → β)
(h : s.Nonempty) : ∏ x ∈ s, f x = f default := by
rw [h.eq_singleton_default, Finset.prod_singleton]
#align finset.prod_unique_nonempty Finset.prod_unique_nonempty
#align finset.sum_unique_nonempty Finset.sum_unique_nonempty
theorem sum_nat_mod (s : Finset α) (n : ℕ) (f : α → ℕ) :
(∑ i ∈ s, f i) % n = (∑ i ∈ s, f i % n) % n :=
(Multiset.sum_nat_mod _ _).trans <| by rw [Finset.sum, Multiset.map_map]; rfl
#align finset.sum_nat_mod Finset.sum_nat_mod
theorem prod_nat_mod (s : Finset α) (n : ℕ) (f : α → ℕ) :
(∏ i ∈ s, f i) % n = (∏ i ∈ s, f i % n) % n :=
(Multiset.prod_nat_mod _ _).trans <| by rw [Finset.prod, Multiset.map_map]; rfl
#align finset.prod_nat_mod Finset.prod_nat_mod
theorem sum_int_mod (s : Finset α) (n : ℤ) (f : α → ℤ) :
(∑ i ∈ s, f i) % n = (∑ i ∈ s, f i % n) % n :=
(Multiset.sum_int_mod _ _).trans <| by rw [Finset.sum, Multiset.map_map]; rfl
#align finset.sum_int_mod Finset.sum_int_mod
theorem prod_int_mod (s : Finset α) (n : ℤ) (f : α → ℤ) :
(∏ i ∈ s, f i) % n = (∏ i ∈ s, f i % n) % n :=
(Multiset.prod_int_mod _ _).trans <| by rw [Finset.prod, Multiset.map_map]; rfl
#align finset.prod_int_mod Finset.prod_int_mod
end Finset
namespace Fintype
variable {ι κ α : Type*} [Fintype ι] [Fintype κ]
open Finset
section CommMonoid
variable [CommMonoid α]
/-- `Fintype.prod_bijective` is a variant of `Finset.prod_bij` that accepts `Function.Bijective`.
See `Function.Bijective.prod_comp` for a version without `h`. -/
@[to_additive "`Fintype.sum_bijective` is a variant of `Finset.sum_bij` that accepts
`Function.Bijective`.
See `Function.Bijective.sum_comp` for a version without `h`. "]
lemma prod_bijective (e : ι → κ) (he : e.Bijective) (f : ι → α) (g : κ → α)
(h : ∀ x, f x = g (e x)) : ∏ x, f x = ∏ x, g x :=
prod_equiv (.ofBijective e he) (by simp) (by simp [h])
#align fintype.prod_bijective Fintype.prod_bijective
#align fintype.sum_bijective Fintype.sum_bijective
@[to_additive] alias _root_.Function.Bijective.finset_prod := prod_bijective
/-- `Fintype.prod_equiv` is a specialization of `Finset.prod_bij` that
automatically fills in most arguments.
See `Equiv.prod_comp` for a version without `h`.
-/
@[to_additive "`Fintype.sum_equiv` is a specialization of `Finset.sum_bij` that
automatically fills in most arguments.
See `Equiv.sum_comp` for a version without `h`."]
lemma prod_equiv (e : ι ≃ κ) (f : ι → α) (g : κ → α) (h : ∀ x, f x = g (e x)) :
∏ x, f x = ∏ x, g x := prod_bijective _ e.bijective _ _ h
#align fintype.prod_equiv Fintype.prod_equiv
#align fintype.sum_equiv Fintype.sum_equiv
@[to_additive]
lemma _root_.Function.Bijective.prod_comp {e : ι → κ} (he : e.Bijective) (g : κ → α) :
∏ i, g (e i) = ∏ i, g i := prod_bijective _ he _ _ fun _ ↦ rfl
#align function.bijective.prod_comp Function.Bijective.prod_comp
#align function.bijective.sum_comp Function.Bijective.sum_comp
@[to_additive]
lemma _root_.Equiv.prod_comp (e : ι ≃ κ) (g : κ → α) : ∏ i, g (e i) = ∏ i, g i :=
prod_equiv e _ _ fun _ ↦ rfl
#align equiv.prod_comp Equiv.prod_comp
#align equiv.sum_comp Equiv.sum_comp
@[to_additive]
lemma prod_of_injective (e : ι → κ) (he : Injective e) (f : ι → α) (g : κ → α)
(h' : ∀ i ∉ Set.range e, g i = 1) (h : ∀ i, f i = g (e i)) : ∏ i, f i = ∏ j, g j :=
prod_of_injOn e he.injOn (by simp) (by simpa using h') (fun i _ ↦ h i)
@[to_additive]
lemma prod_fiberwise [DecidableEq κ] (g : ι → κ) (f : ι → α) :
∏ j, ∏ i : {i // g i = j}, f i = ∏ i, f i := by
rw [← Finset.prod_fiberwise _ g f]
congr with j
exact (prod_subtype _ (by simp) _).symm
#align fintype.prod_fiberwise Fintype.prod_fiberwise
#align fintype.sum_fiberwise Fintype.sum_fiberwise
@[to_additive]
lemma prod_fiberwise' [DecidableEq κ] (g : ι → κ) (f : κ → α) :
∏ j, ∏ _i : {i // g i = j}, f j = ∏ i, f (g i) := by
rw [← Finset.prod_fiberwise' _ g f]
congr with j
exact (prod_subtype _ (by simp) fun _ ↦ _).symm
@[to_additive]
theorem prod_unique {α β : Type*} [CommMonoid β] [Unique α] [Fintype α] (f : α → β) :
∏ x : α, f x = f default := by rw [univ_unique, prod_singleton]
#align fintype.prod_unique Fintype.prod_unique
#align fintype.sum_unique Fintype.sum_unique
@[to_additive]
theorem prod_empty {α β : Type*} [CommMonoid β] [IsEmpty α] [Fintype α] (f : α → β) :
∏ x : α, f x = 1 :=
Finset.prod_of_empty _
#align fintype.prod_empty Fintype.prod_empty
#align fintype.sum_empty Fintype.sum_empty
@[to_additive]
theorem prod_subsingleton {α β : Type*} [CommMonoid β] [Subsingleton α] [Fintype α] (f : α → β)
(a : α) : ∏ x : α, f x = f a := by
haveI : Unique α := uniqueOfSubsingleton a
rw [prod_unique f, Subsingleton.elim default a]
#align fintype.prod_subsingleton Fintype.prod_subsingleton
#align fintype.sum_subsingleton Fintype.sum_subsingleton
@[to_additive]
theorem prod_subtype_mul_prod_subtype {α β : Type*} [Fintype α] [CommMonoid β] (p : α → Prop)
(f : α → β) [DecidablePred p] :
(∏ i : { x // p x }, f i) * ∏ i : { x // ¬p x }, f i = ∏ i, f i := by
classical
let s := { x | p x }.toFinset
rw [← Finset.prod_subtype s, ← Finset.prod_subtype sᶜ]
· exact Finset.prod_mul_prod_compl _ _
· simp [s]
· simp [s]
#align fintype.prod_subtype_mul_prod_subtype Fintype.prod_subtype_mul_prod_subtype
#align fintype.sum_subtype_add_sum_subtype Fintype.sum_subtype_add_sum_subtype
@[to_additive] lemma prod_subset {s : Finset ι} {f : ι → α} (h : ∀ i, f i ≠ 1 → i ∈ s) :
∏ i ∈ s, f i = ∏ i, f i :=
Finset.prod_subset s.subset_univ $ by simpa [not_imp_comm (a := _ ∈ s)]
@[to_additive]
lemma prod_ite_eq_ite_exists (p : ι → Prop) [DecidablePred p] (h : ∀ i j, p i → p j → i = j)
(a : α) : ∏ i, ite (p i) a 1 = ite (∃ i, p i) a 1 := by
simp [prod_ite_one univ p (by simpa using h)]
variable [DecidableEq ι]
/-- See also `Finset.prod_dite_eq`. -/
@[to_additive "See also `Finset.sum_dite_eq`."] lemma prod_dite_eq (i : ι) (f : ∀ j, i = j → α) :
∏ j, (if h : i = j then f j h else 1) = f i rfl := by
rw [Finset.prod_dite_eq, if_pos (mem_univ _)]
/-- See also `Finset.prod_dite_eq'`. -/
@[to_additive "See also `Finset.sum_dite_eq'`."] lemma prod_dite_eq' (i : ι) (f : ∀ j, j = i → α) :
∏ j, (if h : j = i then f j h else 1) = f i rfl := by
rw [Finset.prod_dite_eq', if_pos (mem_univ _)]
/-- See also `Finset.prod_ite_eq`. -/
@[to_additive "See also `Finset.sum_ite_eq`."]
lemma prod_ite_eq (i : ι) (f : ι → α) : ∏ j, (if i = j then f j else 1) = f i := by
rw [Finset.prod_ite_eq, if_pos (mem_univ _)]
/-- See also `Finset.prod_ite_eq'`. -/
@[to_additive "See also `Finset.sum_ite_eq'`."]
lemma prod_ite_eq' (i : ι) (f : ι → α) : ∏ j, (if j = i then f j else 1) = f i := by
rw [Finset.prod_ite_eq', if_pos (mem_univ _)]
/-- See also `Finset.prod_pi_mulSingle`. -/
@[to_additive "See also `Finset.sum_pi_single`."]
lemma prod_pi_mulSingle {α : ι → Type*} [∀ i, CommMonoid (α i)] (i : ι) (f : ∀ i, α i) :
∏ j, Pi.mulSingle j (f j) i = f i := prod_dite_eq _ _
/-- See also `Finset.prod_pi_mulSingle'`. -/
@[to_additive "See also `Finset.sum_pi_single'`."]
lemma prod_pi_mulSingle' (i : ι) (a : α) : ∏ j, Pi.mulSingle i a j = a := prod_dite_eq' _ _
end CommMonoid
end Fintype
namespace Finset
variable [CommMonoid α]
@[to_additive (attr := simp)]
lemma prod_attach_univ [Fintype ι] (f : {i // i ∈ @univ ι _} → α) :
∏ i ∈ univ.attach, f i = ∏ i, f ⟨i, mem_univ _⟩ :=
Fintype.prod_equiv (Equiv.subtypeUnivEquiv mem_univ) _ _ $ by simp
#align finset.prod_attach_univ Finset.prod_attach_univ
#align finset.sum_attach_univ Finset.sum_attach_univ
@[to_additive]
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 2,391 | 2,394 | theorem prod_erase_attach [DecidableEq ι] {s : Finset ι} (f : ι → α) (i : ↑s) :
∏ j ∈ s.attach.erase i, f ↑j = ∏ j ∈ s.erase ↑i, f j := by |
rw [← Function.Embedding.coe_subtype, ← prod_map]
simp [attach_map_val]
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Cardinal.Ordinal
import Mathlib.SetTheory.Ordinal.FixedPoint
#align_import set_theory.cardinal.cofinality from "leanprover-community/mathlib"@"7c2ce0c2da15516b4e65d0c9e254bb6dc93abd1f"
/-!
# Cofinality
This file contains the definition of cofinality of an ordinal number and regular cardinals
## Main Definitions
* `Ordinal.cof o` is the cofinality of the ordinal `o`.
If `o` is the order type of the relation `<` on `α`, then `o.cof` is the smallest cardinality of a
subset `s` of α that is *cofinal* in `α`, i.e. `∀ x : α, ∃ y ∈ s, ¬ y < x`.
* `Cardinal.IsStrongLimit c` means that `c` is a strong limit cardinal:
`c ≠ 0 ∧ ∀ x < c, 2 ^ x < c`.
* `Cardinal.IsRegular c` means that `c` is a regular cardinal: `ℵ₀ ≤ c ∧ c.ord.cof = c`.
* `Cardinal.IsInaccessible c` means that `c` is strongly inaccessible:
`ℵ₀ < c ∧ IsRegular c ∧ IsStrongLimit c`.
## Main Statements
* `Ordinal.infinite_pigeonhole_card`: the infinite pigeonhole principle
* `Cardinal.lt_power_cof`: A consequence of König's theorem stating that `c < c ^ c.ord.cof` for
`c ≥ ℵ₀`
* `Cardinal.univ_inaccessible`: The type of ordinals in `Type u` form an inaccessible cardinal
(in `Type v` with `v > u`). This shows (externally) that in `Type u` there are at least `u`
inaccessible cardinals.
## Implementation Notes
* The cofinality is defined for ordinals.
If `c` is a cardinal number, its cofinality is `c.ord.cof`.
## Tags
cofinality, regular cardinals, limits cardinals, inaccessible cardinals,
infinite pigeonhole principle
-/
noncomputable section
open Function Cardinal Set Order
open scoped Classical
open Cardinal Ordinal
universe u v w
variable {α : Type*} {r : α → α → Prop}
/-! ### Cofinality of orders -/
namespace Order
/-- Cofinality of a reflexive order `≼`. This is the smallest cardinality
of a subset `S : Set α` such that `∀ a, ∃ b ∈ S, a ≼ b`. -/
def cof (r : α → α → Prop) : Cardinal :=
sInf { c | ∃ S : Set α, (∀ a, ∃ b ∈ S, r a b) ∧ #S = c }
#align order.cof Order.cof
/-- The set in the definition of `Order.cof` is nonempty. -/
theorem cof_nonempty (r : α → α → Prop) [IsRefl α r] :
{ c | ∃ S : Set α, (∀ a, ∃ b ∈ S, r a b) ∧ #S = c }.Nonempty :=
⟨_, Set.univ, fun a => ⟨a, ⟨⟩, refl _⟩, rfl⟩
#align order.cof_nonempty Order.cof_nonempty
theorem cof_le (r : α → α → Prop) {S : Set α} (h : ∀ a, ∃ b ∈ S, r a b) : cof r ≤ #S :=
csInf_le' ⟨S, h, rfl⟩
#align order.cof_le Order.cof_le
theorem le_cof {r : α → α → Prop} [IsRefl α r] (c : Cardinal) :
c ≤ cof r ↔ ∀ {S : Set α}, (∀ a, ∃ b ∈ S, r a b) → c ≤ #S := by
rw [cof, le_csInf_iff'' (cof_nonempty r)]
use fun H S h => H _ ⟨S, h, rfl⟩
rintro H d ⟨S, h, rfl⟩
exact H h
#align order.le_cof Order.le_cof
end Order
theorem RelIso.cof_le_lift {α : Type u} {β : Type v} {r : α → α → Prop} {s} [IsRefl β s]
(f : r ≃r s) : Cardinal.lift.{max u v} (Order.cof r) ≤
Cardinal.lift.{max u v} (Order.cof s) := by
rw [Order.cof, Order.cof, lift_sInf, lift_sInf,
le_csInf_iff'' ((Order.cof_nonempty s).image _)]
rintro - ⟨-, ⟨u, H, rfl⟩, rfl⟩
apply csInf_le'
refine
⟨_, ⟨f.symm '' u, fun a => ?_, rfl⟩,
lift_mk_eq.{u, v, max u v}.2 ⟨(f.symm.toEquiv.image u).symm⟩⟩
rcases H (f a) with ⟨b, hb, hb'⟩
refine ⟨f.symm b, mem_image_of_mem _ hb, f.map_rel_iff.1 ?_⟩
rwa [RelIso.apply_symm_apply]
#align rel_iso.cof_le_lift RelIso.cof_le_lift
theorem RelIso.cof_eq_lift {α : Type u} {β : Type v} {r s} [IsRefl α r] [IsRefl β s] (f : r ≃r s) :
Cardinal.lift.{max u v} (Order.cof r) = Cardinal.lift.{max u v} (Order.cof s) :=
(RelIso.cof_le_lift f).antisymm (RelIso.cof_le_lift f.symm)
#align rel_iso.cof_eq_lift RelIso.cof_eq_lift
theorem RelIso.cof_le {α β : Type u} {r : α → α → Prop} {s} [IsRefl β s] (f : r ≃r s) :
Order.cof r ≤ Order.cof s :=
lift_le.1 (RelIso.cof_le_lift f)
#align rel_iso.cof_le RelIso.cof_le
theorem RelIso.cof_eq {α β : Type u} {r s} [IsRefl α r] [IsRefl β s] (f : r ≃r s) :
Order.cof r = Order.cof s :=
lift_inj.1 (RelIso.cof_eq_lift f)
#align rel_iso.cof_eq RelIso.cof_eq
/-- Cofinality of a strict order `≺`. This is the smallest cardinality of a set `S : Set α` such
that `∀ a, ∃ b ∈ S, ¬ b ≺ a`. -/
def StrictOrder.cof (r : α → α → Prop) : Cardinal :=
Order.cof (swap rᶜ)
#align strict_order.cof StrictOrder.cof
/-- The set in the definition of `Order.StrictOrder.cof` is nonempty. -/
theorem StrictOrder.cof_nonempty (r : α → α → Prop) [IsIrrefl α r] :
{ c | ∃ S : Set α, Unbounded r S ∧ #S = c }.Nonempty :=
@Order.cof_nonempty α _ (IsRefl.swap rᶜ)
#align strict_order.cof_nonempty StrictOrder.cof_nonempty
/-! ### Cofinality of ordinals -/
namespace Ordinal
/-- Cofinality of an ordinal. This is the smallest cardinal of a
subset `S` of the ordinal which is unbounded, in the sense
`∀ a, ∃ b ∈ S, a ≤ b`. It is defined for all ordinals, but
`cof 0 = 0` and `cof (succ o) = 1`, so it is only really
interesting on limit ordinals (when it is an infinite cardinal). -/
def cof (o : Ordinal.{u}) : Cardinal.{u} :=
o.liftOn (fun a => StrictOrder.cof a.r)
(by
rintro ⟨α, r, wo₁⟩ ⟨β, s, wo₂⟩ ⟨⟨f, hf⟩⟩
haveI := wo₁; haveI := wo₂
dsimp only
apply @RelIso.cof_eq _ _ _ _ ?_ ?_
· constructor
exact @fun a b => not_iff_not.2 hf
· dsimp only [swap]
exact ⟨fun _ => irrefl _⟩
· dsimp only [swap]
exact ⟨fun _ => irrefl _⟩)
#align ordinal.cof Ordinal.cof
theorem cof_type (r : α → α → Prop) [IsWellOrder α r] : (type r).cof = StrictOrder.cof r :=
rfl
#align ordinal.cof_type Ordinal.cof_type
theorem le_cof_type [IsWellOrder α r] {c} : c ≤ cof (type r) ↔ ∀ S, Unbounded r S → c ≤ #S :=
(le_csInf_iff'' (StrictOrder.cof_nonempty r)).trans
⟨fun H S h => H _ ⟨S, h, rfl⟩, by
rintro H d ⟨S, h, rfl⟩
exact H _ h⟩
#align ordinal.le_cof_type Ordinal.le_cof_type
theorem cof_type_le [IsWellOrder α r] {S : Set α} (h : Unbounded r S) : cof (type r) ≤ #S :=
le_cof_type.1 le_rfl S h
#align ordinal.cof_type_le Ordinal.cof_type_le
theorem lt_cof_type [IsWellOrder α r] {S : Set α} : #S < cof (type r) → Bounded r S := by
simpa using not_imp_not.2 cof_type_le
#align ordinal.lt_cof_type Ordinal.lt_cof_type
theorem cof_eq (r : α → α → Prop) [IsWellOrder α r] : ∃ S, Unbounded r S ∧ #S = cof (type r) :=
csInf_mem (StrictOrder.cof_nonempty r)
#align ordinal.cof_eq Ordinal.cof_eq
theorem ord_cof_eq (r : α → α → Prop) [IsWellOrder α r] :
∃ S, Unbounded r S ∧ type (Subrel r S) = (cof (type r)).ord := by
let ⟨S, hS, e⟩ := cof_eq r
let ⟨s, _, e'⟩ := Cardinal.ord_eq S
let T : Set α := { a | ∃ aS : a ∈ S, ∀ b : S, s b ⟨_, aS⟩ → r b a }
suffices Unbounded r T by
refine ⟨T, this, le_antisymm ?_ (Cardinal.ord_le.2 <| cof_type_le this)⟩
rw [← e, e']
refine
(RelEmbedding.ofMonotone
(fun a : T =>
(⟨a,
let ⟨aS, _⟩ := a.2
aS⟩ :
S))
fun a b h => ?_).ordinal_type_le
rcases a with ⟨a, aS, ha⟩
rcases b with ⟨b, bS, hb⟩
change s ⟨a, _⟩ ⟨b, _⟩
refine ((trichotomous_of s _ _).resolve_left fun hn => ?_).resolve_left ?_
· exact asymm h (ha _ hn)
· intro e
injection e with e
subst b
exact irrefl _ h
intro a
have : { b : S | ¬r b a }.Nonempty :=
let ⟨b, bS, ba⟩ := hS a
⟨⟨b, bS⟩, ba⟩
let b := (IsWellFounded.wf : WellFounded s).min _ this
have ba : ¬r b a := IsWellFounded.wf.min_mem _ this
refine ⟨b, ⟨b.2, fun c => not_imp_not.1 fun h => ?_⟩, ba⟩
rw [show ∀ b : S, (⟨b, b.2⟩ : S) = b by intro b; cases b; rfl]
exact IsWellFounded.wf.not_lt_min _ this (IsOrderConnected.neg_trans h ba)
#align ordinal.ord_cof_eq Ordinal.ord_cof_eq
/-! ### Cofinality of suprema and least strict upper bounds -/
private theorem card_mem_cof {o} : ∃ (ι : _) (f : ι → Ordinal), lsub.{u, u} f = o ∧ #ι = o.card :=
⟨_, _, lsub_typein o, mk_ordinal_out o⟩
/-- The set in the `lsub` characterization of `cof` is nonempty. -/
theorem cof_lsub_def_nonempty (o) :
{ a : Cardinal | ∃ (ι : _) (f : ι → Ordinal), lsub.{u, u} f = o ∧ #ι = a }.Nonempty :=
⟨_, card_mem_cof⟩
#align ordinal.cof_lsub_def_nonempty Ordinal.cof_lsub_def_nonempty
theorem cof_eq_sInf_lsub (o : Ordinal.{u}) : cof o =
sInf { a : Cardinal | ∃ (ι : Type u) (f : ι → Ordinal), lsub.{u, u} f = o ∧ #ι = a } := by
refine le_antisymm (le_csInf (cof_lsub_def_nonempty o) ?_) (csInf_le' ?_)
· rintro a ⟨ι, f, hf, rfl⟩
rw [← type_lt o]
refine
(cof_type_le fun a => ?_).trans
(@mk_le_of_injective _ _
(fun s : typein ((· < ·) : o.out.α → o.out.α → Prop) ⁻¹' Set.range f =>
Classical.choose s.prop)
fun s t hst => by
let H := congr_arg f hst
rwa [Classical.choose_spec s.prop, Classical.choose_spec t.prop, typein_inj,
Subtype.coe_inj] at H)
have := typein_lt_self a
simp_rw [← hf, lt_lsub_iff] at this
cases' this with i hi
refine ⟨enum (· < ·) (f i) ?_, ?_, ?_⟩
· rw [type_lt, ← hf]
apply lt_lsub
· rw [mem_preimage, typein_enum]
exact mem_range_self i
· rwa [← typein_le_typein, typein_enum]
· rcases cof_eq (· < · : (Quotient.out o).α → (Quotient.out o).α → Prop) with ⟨S, hS, hS'⟩
let f : S → Ordinal := fun s => typein LT.lt s.val
refine ⟨S, f, le_antisymm (lsub_le fun i => typein_lt_self (o := o) i)
(le_of_forall_lt fun a ha => ?_), by rwa [type_lt o] at hS'⟩
rw [← type_lt o] at ha
rcases hS (enum (· < ·) a ha) with ⟨b, hb, hb'⟩
rw [← typein_le_typein, typein_enum] at hb'
exact hb'.trans_lt (lt_lsub.{u, u} f ⟨b, hb⟩)
#align ordinal.cof_eq_Inf_lsub Ordinal.cof_eq_sInf_lsub
@[simp]
theorem lift_cof (o) : Cardinal.lift.{u, v} (cof o) = cof (Ordinal.lift.{u, v} o) := by
refine inductionOn o ?_
intro α r _
apply le_antisymm
· refine le_cof_type.2 fun S H => ?_
have : Cardinal.lift.{u, v} #(ULift.up ⁻¹' S) ≤ #(S : Type (max u v)) := by
rw [← Cardinal.lift_umax.{v, u}, ← Cardinal.lift_id'.{v, u} #S]
exact mk_preimage_of_injective_lift.{v, max u v} ULift.up S (ULift.up_injective.{u, v})
refine (Cardinal.lift_le.2 <| cof_type_le ?_).trans this
exact fun a =>
let ⟨⟨b⟩, bs, br⟩ := H ⟨a⟩
⟨b, bs, br⟩
· rcases cof_eq r with ⟨S, H, e'⟩
have : #(ULift.down.{u, v} ⁻¹' S) ≤ Cardinal.lift.{u, v} #S :=
⟨⟨fun ⟨⟨x⟩, h⟩ => ⟨⟨x, h⟩⟩, fun ⟨⟨x⟩, h₁⟩ ⟨⟨y⟩, h₂⟩ e => by
simp at e; congr⟩⟩
rw [e'] at this
refine (cof_type_le ?_).trans this
exact fun ⟨a⟩ =>
let ⟨b, bs, br⟩ := H a
⟨⟨b⟩, bs, br⟩
#align ordinal.lift_cof Ordinal.lift_cof
theorem cof_le_card (o) : cof o ≤ card o := by
rw [cof_eq_sInf_lsub]
exact csInf_le' card_mem_cof
#align ordinal.cof_le_card Ordinal.cof_le_card
theorem cof_ord_le (c : Cardinal) : c.ord.cof ≤ c := by simpa using cof_le_card c.ord
#align ordinal.cof_ord_le Ordinal.cof_ord_le
theorem ord_cof_le (o : Ordinal.{u}) : o.cof.ord ≤ o :=
(ord_le_ord.2 (cof_le_card o)).trans (ord_card_le o)
#align ordinal.ord_cof_le Ordinal.ord_cof_le
theorem exists_lsub_cof (o : Ordinal) :
∃ (ι : _) (f : ι → Ordinal), lsub.{u, u} f = o ∧ #ι = cof o := by
rw [cof_eq_sInf_lsub]
exact csInf_mem (cof_lsub_def_nonempty o)
#align ordinal.exists_lsub_cof Ordinal.exists_lsub_cof
theorem cof_lsub_le {ι} (f : ι → Ordinal) : cof (lsub.{u, u} f) ≤ #ι := by
rw [cof_eq_sInf_lsub]
exact csInf_le' ⟨ι, f, rfl, rfl⟩
#align ordinal.cof_lsub_le Ordinal.cof_lsub_le
theorem cof_lsub_le_lift {ι} (f : ι → Ordinal) :
cof (lsub.{u, v} f) ≤ Cardinal.lift.{v, u} #ι := by
rw [← mk_uLift.{u, v}]
convert cof_lsub_le.{max u v} fun i : ULift.{v, u} ι => f i.down
exact
lsub_eq_of_range_eq.{u, max u v, max u v}
(Set.ext fun x => ⟨fun ⟨i, hi⟩ => ⟨ULift.up.{v, u} i, hi⟩, fun ⟨i, hi⟩ => ⟨_, hi⟩⟩)
#align ordinal.cof_lsub_le_lift Ordinal.cof_lsub_le_lift
theorem le_cof_iff_lsub {o : Ordinal} {a : Cardinal} :
a ≤ cof o ↔ ∀ {ι} (f : ι → Ordinal), lsub.{u, u} f = o → a ≤ #ι := by
rw [cof_eq_sInf_lsub]
exact
(le_csInf_iff'' (cof_lsub_def_nonempty o)).trans
⟨fun H ι f hf => H _ ⟨ι, f, hf, rfl⟩, fun H b ⟨ι, f, hf, hb⟩ => by
rw [← hb]
exact H _ hf⟩
#align ordinal.le_cof_iff_lsub Ordinal.le_cof_iff_lsub
theorem lsub_lt_ord_lift {ι} {f : ι → Ordinal} {c : Ordinal}
(hι : Cardinal.lift.{v, u} #ι < c.cof)
(hf : ∀ i, f i < c) : lsub.{u, v} f < c :=
lt_of_le_of_ne (lsub_le.{v, u} hf) fun h => by
subst h
exact (cof_lsub_le_lift.{u, v} f).not_lt hι
#align ordinal.lsub_lt_ord_lift Ordinal.lsub_lt_ord_lift
theorem lsub_lt_ord {ι} {f : ι → Ordinal} {c : Ordinal} (hι : #ι < c.cof) :
(∀ i, f i < c) → lsub.{u, u} f < c :=
lsub_lt_ord_lift (by rwa [(#ι).lift_id])
#align ordinal.lsub_lt_ord Ordinal.lsub_lt_ord
theorem cof_sup_le_lift {ι} {f : ι → Ordinal} (H : ∀ i, f i < sup.{u, v} f) :
cof (sup.{u, v} f) ≤ Cardinal.lift.{v, u} #ι := by
rw [← sup_eq_lsub_iff_lt_sup.{u, v}] at H
rw [H]
exact cof_lsub_le_lift f
#align ordinal.cof_sup_le_lift Ordinal.cof_sup_le_lift
theorem cof_sup_le {ι} {f : ι → Ordinal} (H : ∀ i, f i < sup.{u, u} f) :
cof (sup.{u, u} f) ≤ #ι := by
rw [← (#ι).lift_id]
exact cof_sup_le_lift H
#align ordinal.cof_sup_le Ordinal.cof_sup_le
theorem sup_lt_ord_lift {ι} {f : ι → Ordinal} {c : Ordinal} (hι : Cardinal.lift.{v, u} #ι < c.cof)
(hf : ∀ i, f i < c) : sup.{u, v} f < c :=
(sup_le_lsub.{u, v} f).trans_lt (lsub_lt_ord_lift hι hf)
#align ordinal.sup_lt_ord_lift Ordinal.sup_lt_ord_lift
theorem sup_lt_ord {ι} {f : ι → Ordinal} {c : Ordinal} (hι : #ι < c.cof) :
(∀ i, f i < c) → sup.{u, u} f < c :=
sup_lt_ord_lift (by rwa [(#ι).lift_id])
#align ordinal.sup_lt_ord Ordinal.sup_lt_ord
theorem iSup_lt_lift {ι} {f : ι → Cardinal} {c : Cardinal}
(hι : Cardinal.lift.{v, u} #ι < c.ord.cof)
(hf : ∀ i, f i < c) : iSup.{max u v + 1, u + 1} f < c := by
rw [← ord_lt_ord, iSup_ord (Cardinal.bddAbove_range.{u, v} _)]
refine sup_lt_ord_lift hι fun i => ?_
rw [ord_lt_ord]
apply hf
#align ordinal.supr_lt_lift Ordinal.iSup_lt_lift
theorem iSup_lt {ι} {f : ι → Cardinal} {c : Cardinal} (hι : #ι < c.ord.cof) :
(∀ i, f i < c) → iSup f < c :=
iSup_lt_lift (by rwa [(#ι).lift_id])
#align ordinal.supr_lt Ordinal.iSup_lt
| Mathlib/SetTheory/Cardinal/Cofinality.lean | 377 | 386 | theorem nfpFamily_lt_ord_lift {ι} {f : ι → Ordinal → Ordinal} {c} (hc : ℵ₀ < cof c)
(hc' : Cardinal.lift.{v, u} #ι < cof c) (hf : ∀ (i), ∀ b < c, f i b < c) {a} (ha : a < c) :
nfpFamily.{u, v} f a < c := by |
refine sup_lt_ord_lift ((Cardinal.lift_le.2 (mk_list_le_max ι)).trans_lt ?_) fun l => ?_
· rw [lift_max]
apply max_lt _ hc'
rwa [Cardinal.lift_aleph0]
· induction' l with i l H
· exact ha
· exact hf _ _ H
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Algebra.ModEq
import Mathlib.Algebra.Module.Defs
import Mathlib.Algebra.Order.Archimedean
import Mathlib.Algebra.Periodic
import Mathlib.Data.Int.SuccPred
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.Order.Circular
import Mathlib.Data.List.TFAE
import Mathlib.Data.Set.Lattice
#align_import algebra.order.to_interval_mod from "leanprover-community/mathlib"@"213b0cff7bc5ab6696ee07cceec80829ce42efec"
/-!
# Reducing to an interval modulo its length
This file defines operations that reduce a number (in an `Archimedean`
`LinearOrderedAddCommGroup`) to a number in a given interval, modulo the length of that
interval.
## Main definitions
* `toIcoDiv hp a b` (where `hp : 0 < p`): The unique integer such that this multiple of `p`,
subtracted from `b`, is in `Ico a (a + p)`.
* `toIcoMod hp a b` (where `hp : 0 < p`): Reduce `b` to the interval `Ico a (a + p)`.
* `toIocDiv hp a b` (where `hp : 0 < p`): The unique integer such that this multiple of `p`,
subtracted from `b`, is in `Ioc a (a + p)`.
* `toIocMod hp a b` (where `hp : 0 < p`): Reduce `b` to the interval `Ioc a (a + p)`.
-/
noncomputable section
section LinearOrderedAddCommGroup
variable {α : Type*} [LinearOrderedAddCommGroup α] [hα : Archimedean α] {p : α} (hp : 0 < p)
{a b c : α} {n : ℤ}
/--
The unique integer such that this multiple of `p`, subtracted from `b`, is in `Ico a (a + p)`. -/
def toIcoDiv (a b : α) : ℤ :=
(existsUnique_sub_zsmul_mem_Ico hp b a).choose
#align to_Ico_div toIcoDiv
theorem sub_toIcoDiv_zsmul_mem_Ico (a b : α) : b - toIcoDiv hp a b • p ∈ Set.Ico a (a + p) :=
(existsUnique_sub_zsmul_mem_Ico hp b a).choose_spec.1
#align sub_to_Ico_div_zsmul_mem_Ico sub_toIcoDiv_zsmul_mem_Ico
theorem toIcoDiv_eq_of_sub_zsmul_mem_Ico (h : b - n • p ∈ Set.Ico a (a + p)) :
toIcoDiv hp a b = n :=
((existsUnique_sub_zsmul_mem_Ico hp b a).choose_spec.2 _ h).symm
#align to_Ico_div_eq_of_sub_zsmul_mem_Ico toIcoDiv_eq_of_sub_zsmul_mem_Ico
/--
The unique integer such that this multiple of `p`, subtracted from `b`, is in `Ioc a (a + p)`. -/
def toIocDiv (a b : α) : ℤ :=
(existsUnique_sub_zsmul_mem_Ioc hp b a).choose
#align to_Ioc_div toIocDiv
theorem sub_toIocDiv_zsmul_mem_Ioc (a b : α) : b - toIocDiv hp a b • p ∈ Set.Ioc a (a + p) :=
(existsUnique_sub_zsmul_mem_Ioc hp b a).choose_spec.1
#align sub_to_Ioc_div_zsmul_mem_Ioc sub_toIocDiv_zsmul_mem_Ioc
theorem toIocDiv_eq_of_sub_zsmul_mem_Ioc (h : b - n • p ∈ Set.Ioc a (a + p)) :
toIocDiv hp a b = n :=
((existsUnique_sub_zsmul_mem_Ioc hp b a).choose_spec.2 _ h).symm
#align to_Ioc_div_eq_of_sub_zsmul_mem_Ioc toIocDiv_eq_of_sub_zsmul_mem_Ioc
/-- Reduce `b` to the interval `Ico a (a + p)`. -/
def toIcoMod (a b : α) : α :=
b - toIcoDiv hp a b • p
#align to_Ico_mod toIcoMod
/-- Reduce `b` to the interval `Ioc a (a + p)`. -/
def toIocMod (a b : α) : α :=
b - toIocDiv hp a b • p
#align to_Ioc_mod toIocMod
theorem toIcoMod_mem_Ico (a b : α) : toIcoMod hp a b ∈ Set.Ico a (a + p) :=
sub_toIcoDiv_zsmul_mem_Ico hp a b
#align to_Ico_mod_mem_Ico toIcoMod_mem_Ico
theorem toIcoMod_mem_Ico' (b : α) : toIcoMod hp 0 b ∈ Set.Ico 0 p := by
convert toIcoMod_mem_Ico hp 0 b
exact (zero_add p).symm
#align to_Ico_mod_mem_Ico' toIcoMod_mem_Ico'
theorem toIocMod_mem_Ioc (a b : α) : toIocMod hp a b ∈ Set.Ioc a (a + p) :=
sub_toIocDiv_zsmul_mem_Ioc hp a b
#align to_Ioc_mod_mem_Ioc toIocMod_mem_Ioc
theorem left_le_toIcoMod (a b : α) : a ≤ toIcoMod hp a b :=
(Set.mem_Ico.1 (toIcoMod_mem_Ico hp a b)).1
#align left_le_to_Ico_mod left_le_toIcoMod
theorem left_lt_toIocMod (a b : α) : a < toIocMod hp a b :=
(Set.mem_Ioc.1 (toIocMod_mem_Ioc hp a b)).1
#align left_lt_to_Ioc_mod left_lt_toIocMod
theorem toIcoMod_lt_right (a b : α) : toIcoMod hp a b < a + p :=
(Set.mem_Ico.1 (toIcoMod_mem_Ico hp a b)).2
#align to_Ico_mod_lt_right toIcoMod_lt_right
theorem toIocMod_le_right (a b : α) : toIocMod hp a b ≤ a + p :=
(Set.mem_Ioc.1 (toIocMod_mem_Ioc hp a b)).2
#align to_Ioc_mod_le_right toIocMod_le_right
@[simp]
theorem self_sub_toIcoDiv_zsmul (a b : α) : b - toIcoDiv hp a b • p = toIcoMod hp a b :=
rfl
#align self_sub_to_Ico_div_zsmul self_sub_toIcoDiv_zsmul
@[simp]
theorem self_sub_toIocDiv_zsmul (a b : α) : b - toIocDiv hp a b • p = toIocMod hp a b :=
rfl
#align self_sub_to_Ioc_div_zsmul self_sub_toIocDiv_zsmul
@[simp]
theorem toIcoDiv_zsmul_sub_self (a b : α) : toIcoDiv hp a b • p - b = -toIcoMod hp a b := by
rw [toIcoMod, neg_sub]
#align to_Ico_div_zsmul_sub_self toIcoDiv_zsmul_sub_self
@[simp]
theorem toIocDiv_zsmul_sub_self (a b : α) : toIocDiv hp a b • p - b = -toIocMod hp a b := by
rw [toIocMod, neg_sub]
#align to_Ioc_div_zsmul_sub_self toIocDiv_zsmul_sub_self
@[simp]
theorem toIcoMod_sub_self (a b : α) : toIcoMod hp a b - b = -toIcoDiv hp a b • p := by
rw [toIcoMod, sub_sub_cancel_left, neg_smul]
#align to_Ico_mod_sub_self toIcoMod_sub_self
@[simp]
theorem toIocMod_sub_self (a b : α) : toIocMod hp a b - b = -toIocDiv hp a b • p := by
rw [toIocMod, sub_sub_cancel_left, neg_smul]
#align to_Ioc_mod_sub_self toIocMod_sub_self
@[simp]
theorem self_sub_toIcoMod (a b : α) : b - toIcoMod hp a b = toIcoDiv hp a b • p := by
rw [toIcoMod, sub_sub_cancel]
#align self_sub_to_Ico_mod self_sub_toIcoMod
@[simp]
theorem self_sub_toIocMod (a b : α) : b - toIocMod hp a b = toIocDiv hp a b • p := by
rw [toIocMod, sub_sub_cancel]
#align self_sub_to_Ioc_mod self_sub_toIocMod
@[simp]
theorem toIcoMod_add_toIcoDiv_zsmul (a b : α) : toIcoMod hp a b + toIcoDiv hp a b • p = b := by
rw [toIcoMod, sub_add_cancel]
#align to_Ico_mod_add_to_Ico_div_zsmul toIcoMod_add_toIcoDiv_zsmul
@[simp]
theorem toIocMod_add_toIocDiv_zsmul (a b : α) : toIocMod hp a b + toIocDiv hp a b • p = b := by
rw [toIocMod, sub_add_cancel]
#align to_Ioc_mod_add_to_Ioc_div_zsmul toIocMod_add_toIocDiv_zsmul
@[simp]
theorem toIcoDiv_zsmul_sub_toIcoMod (a b : α) : toIcoDiv hp a b • p + toIcoMod hp a b = b := by
rw [add_comm, toIcoMod_add_toIcoDiv_zsmul]
#align to_Ico_div_zsmul_sub_to_Ico_mod toIcoDiv_zsmul_sub_toIcoMod
@[simp]
theorem toIocDiv_zsmul_sub_toIocMod (a b : α) : toIocDiv hp a b • p + toIocMod hp a b = b := by
rw [add_comm, toIocMod_add_toIocDiv_zsmul]
#align to_Ioc_div_zsmul_sub_to_Ioc_mod toIocDiv_zsmul_sub_toIocMod
theorem toIcoMod_eq_iff : toIcoMod hp a b = c ↔ c ∈ Set.Ico a (a + p) ∧ ∃ z : ℤ, b = c + z • p := by
refine
⟨fun h =>
⟨h ▸ toIcoMod_mem_Ico hp a b, toIcoDiv hp a b, h ▸ (toIcoMod_add_toIcoDiv_zsmul _ _ _).symm⟩,
?_⟩
simp_rw [← @sub_eq_iff_eq_add]
rintro ⟨hc, n, rfl⟩
rw [← toIcoDiv_eq_of_sub_zsmul_mem_Ico hp hc, toIcoMod]
#align to_Ico_mod_eq_iff toIcoMod_eq_iff
theorem toIocMod_eq_iff : toIocMod hp a b = c ↔ c ∈ Set.Ioc a (a + p) ∧ ∃ z : ℤ, b = c + z • p := by
refine
⟨fun h =>
⟨h ▸ toIocMod_mem_Ioc hp a b, toIocDiv hp a b, h ▸ (toIocMod_add_toIocDiv_zsmul hp _ _).symm⟩,
?_⟩
simp_rw [← @sub_eq_iff_eq_add]
rintro ⟨hc, n, rfl⟩
rw [← toIocDiv_eq_of_sub_zsmul_mem_Ioc hp hc, toIocMod]
#align to_Ioc_mod_eq_iff toIocMod_eq_iff
@[simp]
theorem toIcoDiv_apply_left (a : α) : toIcoDiv hp a a = 0 :=
toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by simp [hp]
#align to_Ico_div_apply_left toIcoDiv_apply_left
@[simp]
theorem toIocDiv_apply_left (a : α) : toIocDiv hp a a = -1 :=
toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by simp [hp]
#align to_Ioc_div_apply_left toIocDiv_apply_left
@[simp]
theorem toIcoMod_apply_left (a : α) : toIcoMod hp a a = a := by
rw [toIcoMod_eq_iff hp, Set.left_mem_Ico]
exact ⟨lt_add_of_pos_right _ hp, 0, by simp⟩
#align to_Ico_mod_apply_left toIcoMod_apply_left
@[simp]
theorem toIocMod_apply_left (a : α) : toIocMod hp a a = a + p := by
rw [toIocMod_eq_iff hp, Set.right_mem_Ioc]
exact ⟨lt_add_of_pos_right _ hp, -1, by simp⟩
#align to_Ioc_mod_apply_left toIocMod_apply_left
theorem toIcoDiv_apply_right (a : α) : toIcoDiv hp a (a + p) = 1 :=
toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by simp [hp]
#align to_Ico_div_apply_right toIcoDiv_apply_right
theorem toIocDiv_apply_right (a : α) : toIocDiv hp a (a + p) = 0 :=
toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by simp [hp]
#align to_Ioc_div_apply_right toIocDiv_apply_right
theorem toIcoMod_apply_right (a : α) : toIcoMod hp a (a + p) = a := by
rw [toIcoMod_eq_iff hp, Set.left_mem_Ico]
exact ⟨lt_add_of_pos_right _ hp, 1, by simp⟩
#align to_Ico_mod_apply_right toIcoMod_apply_right
theorem toIocMod_apply_right (a : α) : toIocMod hp a (a + p) = a + p := by
rw [toIocMod_eq_iff hp, Set.right_mem_Ioc]
exact ⟨lt_add_of_pos_right _ hp, 0, by simp⟩
#align to_Ioc_mod_apply_right toIocMod_apply_right
@[simp]
theorem toIcoDiv_add_zsmul (a b : α) (m : ℤ) : toIcoDiv hp a (b + m • p) = toIcoDiv hp a b + m :=
toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by
simpa only [add_smul, add_sub_add_right_eq_sub] using sub_toIcoDiv_zsmul_mem_Ico hp a b
#align to_Ico_div_add_zsmul toIcoDiv_add_zsmul
@[simp]
theorem toIcoDiv_add_zsmul' (a b : α) (m : ℤ) :
toIcoDiv hp (a + m • p) b = toIcoDiv hp a b - m := by
refine toIcoDiv_eq_of_sub_zsmul_mem_Ico _ ?_
rw [sub_smul, ← sub_add, add_right_comm]
simpa using sub_toIcoDiv_zsmul_mem_Ico hp a b
#align to_Ico_div_add_zsmul' toIcoDiv_add_zsmul'
@[simp]
theorem toIocDiv_add_zsmul (a b : α) (m : ℤ) : toIocDiv hp a (b + m • p) = toIocDiv hp a b + m :=
toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by
simpa only [add_smul, add_sub_add_right_eq_sub] using sub_toIocDiv_zsmul_mem_Ioc hp a b
#align to_Ioc_div_add_zsmul toIocDiv_add_zsmul
@[simp]
| Mathlib/Algebra/Order/ToIntervalMod.lean | 253 | 257 | theorem toIocDiv_add_zsmul' (a b : α) (m : ℤ) :
toIocDiv hp (a + m • p) b = toIocDiv hp a b - m := by |
refine toIocDiv_eq_of_sub_zsmul_mem_Ioc _ ?_
rw [sub_smul, ← sub_add, add_right_comm]
simpa using sub_toIocDiv_zsmul_mem_Ioc hp a b
|
/-
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.FDeriv
/-!
# Differentiability of specific functions
In this file, we establish differentiability results for
- continuous linear maps and continuous linear equivalences
- the identity
- constant functions
- products
- arithmetic operations (such as addition and scalar multiplication).
-/
noncomputable section
open scoped Manifold
open Bundle Set Topology
section SpecificFunctions
/-! ### Differentiability of specific functions -/
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] {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'] {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'']
namespace ContinuousLinearMap
variable (f : E →L[𝕜] E') {s : Set E} {x : E}
protected theorem hasMFDerivWithinAt : HasMFDerivWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x f :=
f.hasFDerivWithinAt.hasMFDerivWithinAt
#align continuous_linear_map.has_mfderiv_within_at ContinuousLinearMap.hasMFDerivWithinAt
protected theorem hasMFDerivAt : HasMFDerivAt 𝓘(𝕜, E) 𝓘(𝕜, E') f x f :=
f.hasFDerivAt.hasMFDerivAt
#align continuous_linear_map.has_mfderiv_at ContinuousLinearMap.hasMFDerivAt
protected theorem mdifferentiableWithinAt : MDifferentiableWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x :=
f.differentiableWithinAt.mdifferentiableWithinAt
#align continuous_linear_map.mdifferentiable_within_at ContinuousLinearMap.mdifferentiableWithinAt
protected theorem mdifferentiableOn : MDifferentiableOn 𝓘(𝕜, E) 𝓘(𝕜, E') f s :=
f.differentiableOn.mdifferentiableOn
#align continuous_linear_map.mdifferentiable_on ContinuousLinearMap.mdifferentiableOn
protected theorem mdifferentiableAt : MDifferentiableAt 𝓘(𝕜, E) 𝓘(𝕜, E') f x :=
f.differentiableAt.mdifferentiableAt
#align continuous_linear_map.mdifferentiable_at ContinuousLinearMap.mdifferentiableAt
protected theorem mdifferentiable : MDifferentiable 𝓘(𝕜, E) 𝓘(𝕜, E') f :=
f.differentiable.mdifferentiable
#align continuous_linear_map.mdifferentiable ContinuousLinearMap.mdifferentiable
theorem mfderiv_eq : mfderiv 𝓘(𝕜, E) 𝓘(𝕜, E') f x = f :=
f.hasMFDerivAt.mfderiv
#align continuous_linear_map.mfderiv_eq ContinuousLinearMap.mfderiv_eq
theorem mfderivWithin_eq (hs : UniqueMDiffWithinAt 𝓘(𝕜, E) s x) :
mfderivWithin 𝓘(𝕜, E) 𝓘(𝕜, E') f s x = f :=
f.hasMFDerivWithinAt.mfderivWithin hs
#align continuous_linear_map.mfderiv_within_eq ContinuousLinearMap.mfderivWithin_eq
end ContinuousLinearMap
namespace ContinuousLinearEquiv
variable (f : E ≃L[𝕜] E') {s : Set E} {x : E}
protected theorem hasMFDerivWithinAt : HasMFDerivWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x (f : E →L[𝕜] E') :=
f.hasFDerivWithinAt.hasMFDerivWithinAt
#align continuous_linear_equiv.has_mfderiv_within_at ContinuousLinearEquiv.hasMFDerivWithinAt
protected theorem hasMFDerivAt : HasMFDerivAt 𝓘(𝕜, E) 𝓘(𝕜, E') f x (f : E →L[𝕜] E') :=
f.hasFDerivAt.hasMFDerivAt
#align continuous_linear_equiv.has_mfderiv_at ContinuousLinearEquiv.hasMFDerivAt
protected theorem mdifferentiableWithinAt : MDifferentiableWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x :=
f.differentiableWithinAt.mdifferentiableWithinAt
#align continuous_linear_equiv.mdifferentiable_within_at ContinuousLinearEquiv.mdifferentiableWithinAt
protected theorem mdifferentiableOn : MDifferentiableOn 𝓘(𝕜, E) 𝓘(𝕜, E') f s :=
f.differentiableOn.mdifferentiableOn
#align continuous_linear_equiv.mdifferentiable_on ContinuousLinearEquiv.mdifferentiableOn
protected theorem mdifferentiableAt : MDifferentiableAt 𝓘(𝕜, E) 𝓘(𝕜, E') f x :=
f.differentiableAt.mdifferentiableAt
#align continuous_linear_equiv.mdifferentiable_at ContinuousLinearEquiv.mdifferentiableAt
protected theorem mdifferentiable : MDifferentiable 𝓘(𝕜, E) 𝓘(𝕜, E') f :=
f.differentiable.mdifferentiable
#align continuous_linear_equiv.mdifferentiable ContinuousLinearEquiv.mdifferentiable
theorem mfderiv_eq : mfderiv 𝓘(𝕜, E) 𝓘(𝕜, E') f x = (f : E →L[𝕜] E') :=
f.hasMFDerivAt.mfderiv
#align continuous_linear_equiv.mfderiv_eq ContinuousLinearEquiv.mfderiv_eq
theorem mfderivWithin_eq (hs : UniqueMDiffWithinAt 𝓘(𝕜, E) s x) :
mfderivWithin 𝓘(𝕜, E) 𝓘(𝕜, E') f s x = (f : E →L[𝕜] E') :=
f.hasMFDerivWithinAt.mfderivWithin hs
#align continuous_linear_equiv.mfderiv_within_eq ContinuousLinearEquiv.mfderivWithin_eq
end ContinuousLinearEquiv
variable {s : Set M} {x : M}
section id
/-! #### Identity -/
theorem hasMFDerivAt_id (x : M) :
HasMFDerivAt I I (@id M) x (ContinuousLinearMap.id 𝕜 (TangentSpace I x)) := by
refine ⟨continuousAt_id, ?_⟩
have : ∀ᶠ y in 𝓝[range I] (extChartAt I x) x, (extChartAt I x ∘ (extChartAt I x).symm) y = y := by
apply Filter.mem_of_superset (extChartAt_target_mem_nhdsWithin I x)
mfld_set_tac
apply HasFDerivWithinAt.congr_of_eventuallyEq (hasFDerivWithinAt_id _ _) this
simp only [mfld_simps]
#align has_mfderiv_at_id hasMFDerivAt_id
theorem hasMFDerivWithinAt_id (s : Set M) (x : M) :
HasMFDerivWithinAt I I (@id M) s x (ContinuousLinearMap.id 𝕜 (TangentSpace I x)) :=
(hasMFDerivAt_id I x).hasMFDerivWithinAt
#align has_mfderiv_within_at_id hasMFDerivWithinAt_id
theorem mdifferentiableAt_id : MDifferentiableAt I I (@id M) x :=
(hasMFDerivAt_id I x).mdifferentiableAt
#align mdifferentiable_at_id mdifferentiableAt_id
theorem mdifferentiableWithinAt_id : MDifferentiableWithinAt I I (@id M) s x :=
(mdifferentiableAt_id I).mdifferentiableWithinAt
#align mdifferentiable_within_at_id mdifferentiableWithinAt_id
theorem mdifferentiable_id : MDifferentiable I I (@id M) := fun _ => mdifferentiableAt_id I
#align mdifferentiable_id mdifferentiable_id
theorem mdifferentiableOn_id : MDifferentiableOn I I (@id M) s :=
(mdifferentiable_id I).mdifferentiableOn
#align mdifferentiable_on_id mdifferentiableOn_id
@[simp, mfld_simps]
theorem mfderiv_id : mfderiv I I (@id M) x = ContinuousLinearMap.id 𝕜 (TangentSpace I x) :=
HasMFDerivAt.mfderiv (hasMFDerivAt_id I x)
#align mfderiv_id mfderiv_id
theorem mfderivWithin_id (hxs : UniqueMDiffWithinAt I s x) :
mfderivWithin I I (@id M) s x = ContinuousLinearMap.id 𝕜 (TangentSpace I x) := by
rw [MDifferentiable.mfderivWithin (mdifferentiableAt_id I) hxs]
exact mfderiv_id I
#align mfderiv_within_id mfderivWithin_id
@[simp, mfld_simps]
theorem tangentMap_id : tangentMap I I (id : M → M) = id := by ext1 ⟨x, v⟩; simp [tangentMap]
#align tangent_map_id tangentMap_id
theorem tangentMapWithin_id {p : TangentBundle I M} (hs : UniqueMDiffWithinAt I s p.proj) :
tangentMapWithin I I (id : M → M) s p = p := by
simp only [tangentMapWithin, id]
rw [mfderivWithin_id]
· rcases p with ⟨⟩; rfl
· exact hs
#align tangent_map_within_id tangentMapWithin_id
end id
section Const
/-! #### Constants -/
variable {c : M'}
theorem hasMFDerivAt_const (c : M') (x : M) :
HasMFDerivAt I I' (fun _ : M => c) x (0 : TangentSpace I x →L[𝕜] TangentSpace I' c) := by
refine ⟨continuous_const.continuousAt, ?_⟩
simp only [writtenInExtChartAt, (· ∘ ·), hasFDerivWithinAt_const]
#align has_mfderiv_at_const hasMFDerivAt_const
theorem hasMFDerivWithinAt_const (c : M') (s : Set M) (x : M) :
HasMFDerivWithinAt I I' (fun _ : M => c) s x (0 : TangentSpace I x →L[𝕜] TangentSpace I' c) :=
(hasMFDerivAt_const I I' c x).hasMFDerivWithinAt
#align has_mfderiv_within_at_const hasMFDerivWithinAt_const
theorem mdifferentiableAt_const : MDifferentiableAt I I' (fun _ : M => c) x :=
(hasMFDerivAt_const I I' c x).mdifferentiableAt
#align mdifferentiable_at_const mdifferentiableAt_const
theorem mdifferentiableWithinAt_const : MDifferentiableWithinAt I I' (fun _ : M => c) s x :=
(mdifferentiableAt_const I I').mdifferentiableWithinAt
#align mdifferentiable_within_at_const mdifferentiableWithinAt_const
theorem mdifferentiable_const : MDifferentiable I I' fun _ : M => c := fun _ =>
mdifferentiableAt_const I I'
#align mdifferentiable_const mdifferentiable_const
theorem mdifferentiableOn_const : MDifferentiableOn I I' (fun _ : M => c) s :=
(mdifferentiable_const I I').mdifferentiableOn
#align mdifferentiable_on_const mdifferentiableOn_const
@[simp, mfld_simps]
theorem mfderiv_const :
mfderiv I I' (fun _ : M => c) x = (0 : TangentSpace I x →L[𝕜] TangentSpace I' c) :=
HasMFDerivAt.mfderiv (hasMFDerivAt_const I I' c x)
#align mfderiv_const mfderiv_const
theorem mfderivWithin_const (hxs : UniqueMDiffWithinAt I s x) :
mfderivWithin I I' (fun _ : M => c) s x = (0 : TangentSpace I x →L[𝕜] TangentSpace I' c) :=
(hasMFDerivWithinAt_const _ _ _ _ _).mfderivWithin hxs
#align mfderiv_within_const mfderivWithin_const
end Const
section Prod
/-! ### Operations on the product of two manifolds -/
theorem hasMFDerivAt_fst (x : M × M') :
HasMFDerivAt (I.prod I') I Prod.fst x
(ContinuousLinearMap.fst 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2)) := by
refine ⟨continuous_fst.continuousAt, ?_⟩
have :
∀ᶠ y in 𝓝[range (I.prod I')] extChartAt (I.prod I') x x,
(extChartAt I x.1 ∘ Prod.fst ∘ (extChartAt (I.prod I') x).symm) y = y.1 := by
/- porting note: was
apply Filter.mem_of_superset (extChartAt_target_mem_nhdsWithin (I.prod I') x)
mfld_set_tac
-/
filter_upwards [extChartAt_target_mem_nhdsWithin (I.prod I') x] with y hy
rw [extChartAt_prod] at hy
exact (extChartAt I x.1).right_inv hy.1
apply HasFDerivWithinAt.congr_of_eventuallyEq hasFDerivWithinAt_fst this
-- Porting note: next line was `simp only [mfld_simps]`
exact (extChartAt I x.1).right_inv <| (extChartAt I x.1).map_source (mem_extChartAt_source _ _)
#align has_mfderiv_at_fst hasMFDerivAt_fst
theorem hasMFDerivWithinAt_fst (s : Set (M × M')) (x : M × M') :
HasMFDerivWithinAt (I.prod I') I Prod.fst s x
(ContinuousLinearMap.fst 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2)) :=
(hasMFDerivAt_fst I I' x).hasMFDerivWithinAt
#align has_mfderiv_within_at_fst hasMFDerivWithinAt_fst
theorem mdifferentiableAt_fst {x : M × M'} : MDifferentiableAt (I.prod I') I Prod.fst x :=
(hasMFDerivAt_fst I I' x).mdifferentiableAt
#align mdifferentiable_at_fst mdifferentiableAt_fst
theorem mdifferentiableWithinAt_fst {s : Set (M × M')} {x : M × M'} :
MDifferentiableWithinAt (I.prod I') I Prod.fst s x :=
(mdifferentiableAt_fst I I').mdifferentiableWithinAt
#align mdifferentiable_within_at_fst mdifferentiableWithinAt_fst
theorem mdifferentiable_fst : MDifferentiable (I.prod I') I (Prod.fst : M × M' → M) := fun _ =>
mdifferentiableAt_fst I I'
#align mdifferentiable_fst mdifferentiable_fst
theorem mdifferentiableOn_fst {s : Set (M × M')} : MDifferentiableOn (I.prod I') I Prod.fst s :=
(mdifferentiable_fst I I').mdifferentiableOn
#align mdifferentiable_on_fst mdifferentiableOn_fst
@[simp, mfld_simps]
theorem mfderiv_fst {x : M × M'} :
mfderiv (I.prod I') I Prod.fst x =
ContinuousLinearMap.fst 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2) :=
(hasMFDerivAt_fst I I' x).mfderiv
#align mfderiv_fst mfderiv_fst
theorem mfderivWithin_fst {s : Set (M × M')} {x : M × M'}
(hxs : UniqueMDiffWithinAt (I.prod I') s x) :
mfderivWithin (I.prod I') I Prod.fst s x =
ContinuousLinearMap.fst 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2) := by
rw [MDifferentiable.mfderivWithin (mdifferentiableAt_fst I I') hxs]; exact mfderiv_fst I I'
#align mfderiv_within_fst mfderivWithin_fst
@[simp, mfld_simps]
theorem tangentMap_prod_fst {p : TangentBundle (I.prod I') (M × M')} :
tangentMap (I.prod I') I Prod.fst p = ⟨p.proj.1, p.2.1⟩ := by
-- Porting note: `rfl` wasn't needed
simp [tangentMap]; rfl
#align tangent_map_prod_fst tangentMap_prod_fst
theorem tangentMapWithin_prod_fst {s : Set (M × M')} {p : TangentBundle (I.prod I') (M × M')}
(hs : UniqueMDiffWithinAt (I.prod I') s p.proj) :
tangentMapWithin (I.prod I') I Prod.fst s p = ⟨p.proj.1, p.2.1⟩ := by
simp only [tangentMapWithin]
rw [mfderivWithin_fst]
· rcases p with ⟨⟩; rfl
· exact hs
#align tangent_map_within_prod_fst tangentMapWithin_prod_fst
theorem hasMFDerivAt_snd (x : M × M') :
HasMFDerivAt (I.prod I') I' Prod.snd x
(ContinuousLinearMap.snd 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2)) := by
refine ⟨continuous_snd.continuousAt, ?_⟩
have :
∀ᶠ y in 𝓝[range (I.prod I')] extChartAt (I.prod I') x x,
(extChartAt I' x.2 ∘ Prod.snd ∘ (extChartAt (I.prod I') x).symm) y = y.2 := by
/- porting note: was
apply Filter.mem_of_superset (extChartAt_target_mem_nhdsWithin (I.prod I') x)
mfld_set_tac
-/
filter_upwards [extChartAt_target_mem_nhdsWithin (I.prod I') x] with y hy
rw [extChartAt_prod] at hy
exact (extChartAt I' x.2).right_inv hy.2
apply HasFDerivWithinAt.congr_of_eventuallyEq hasFDerivWithinAt_snd this
-- Porting note: the next line was `simp only [mfld_simps]`
exact (extChartAt I' x.2).right_inv <| (extChartAt I' x.2).map_source (mem_extChartAt_source _ _)
#align has_mfderiv_at_snd hasMFDerivAt_snd
theorem hasMFDerivWithinAt_snd (s : Set (M × M')) (x : M × M') :
HasMFDerivWithinAt (I.prod I') I' Prod.snd s x
(ContinuousLinearMap.snd 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2)) :=
(hasMFDerivAt_snd I I' x).hasMFDerivWithinAt
#align has_mfderiv_within_at_snd hasMFDerivWithinAt_snd
theorem mdifferentiableAt_snd {x : M × M'} : MDifferentiableAt (I.prod I') I' Prod.snd x :=
(hasMFDerivAt_snd I I' x).mdifferentiableAt
#align mdifferentiable_at_snd mdifferentiableAt_snd
theorem mdifferentiableWithinAt_snd {s : Set (M × M')} {x : M × M'} :
MDifferentiableWithinAt (I.prod I') I' Prod.snd s x :=
(mdifferentiableAt_snd I I').mdifferentiableWithinAt
#align mdifferentiable_within_at_snd mdifferentiableWithinAt_snd
theorem mdifferentiable_snd : MDifferentiable (I.prod I') I' (Prod.snd : M × M' → M') := fun _ =>
mdifferentiableAt_snd I I'
#align mdifferentiable_snd mdifferentiable_snd
theorem mdifferentiableOn_snd {s : Set (M × M')} : MDifferentiableOn (I.prod I') I' Prod.snd s :=
(mdifferentiable_snd I I').mdifferentiableOn
#align mdifferentiable_on_snd mdifferentiableOn_snd
@[simp, mfld_simps]
theorem mfderiv_snd {x : M × M'} :
mfderiv (I.prod I') I' Prod.snd x =
ContinuousLinearMap.snd 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2) :=
(hasMFDerivAt_snd I I' x).mfderiv
#align mfderiv_snd mfderiv_snd
theorem mfderivWithin_snd {s : Set (M × M')} {x : M × M'}
(hxs : UniqueMDiffWithinAt (I.prod I') s x) :
mfderivWithin (I.prod I') I' Prod.snd s x =
ContinuousLinearMap.snd 𝕜 (TangentSpace I x.1) (TangentSpace I' x.2) := by
rw [MDifferentiable.mfderivWithin (mdifferentiableAt_snd I I') hxs]; exact mfderiv_snd I I'
#align mfderiv_within_snd mfderivWithin_snd
@[simp, mfld_simps]
theorem tangentMap_prod_snd {p : TangentBundle (I.prod I') (M × M')} :
tangentMap (I.prod I') I' Prod.snd p = ⟨p.proj.2, p.2.2⟩ := by
-- Porting note: `rfl` wasn't needed
simp [tangentMap]; rfl
#align tangent_map_prod_snd tangentMap_prod_snd
theorem tangentMapWithin_prod_snd {s : Set (M × M')} {p : TangentBundle (I.prod I') (M × M')}
(hs : UniqueMDiffWithinAt (I.prod I') s p.proj) :
tangentMapWithin (I.prod I') I' Prod.snd s p = ⟨p.proj.2, p.2.2⟩ := by
simp only [tangentMapWithin]
rw [mfderivWithin_snd]
· rcases p with ⟨⟩; rfl
· exact hs
#align tangent_map_within_prod_snd tangentMapWithin_prod_snd
variable {I I' I''}
theorem MDifferentiableAt.mfderiv_prod {f : M → M'} {g : M → M''} {x : M}
(hf : MDifferentiableAt I I' f x) (hg : MDifferentiableAt I I'' g x) :
mfderiv I (I'.prod I'') (fun x => (f x, g x)) x =
(mfderiv I I' f x).prod (mfderiv I I'' g x) := by
classical
simp_rw [mfderiv, if_pos (hf.prod_mk hg), if_pos hf, if_pos hg]
exact hf.differentiableWithinAt_writtenInExtChartAt.fderivWithin_prod
hg.differentiableWithinAt_writtenInExtChartAt (I.unique_diff _ (mem_range_self _))
#align mdifferentiable_at.mfderiv_prod MDifferentiableAt.mfderiv_prod
variable (I I' I'')
theorem mfderiv_prod_left {x₀ : M} {y₀ : M'} :
mfderiv I (I.prod I') (fun x => (x, y₀)) x₀ =
ContinuousLinearMap.inl 𝕜 (TangentSpace I x₀) (TangentSpace I' y₀) := by
refine ((mdifferentiableAt_id I).mfderiv_prod (mdifferentiableAt_const I I')).trans ?_
rw [mfderiv_id, mfderiv_const, ContinuousLinearMap.inl]
#align mfderiv_prod_left mfderiv_prod_left
theorem mfderiv_prod_right {x₀ : M} {y₀ : M'} :
mfderiv I' (I.prod I') (fun y => (x₀, y)) y₀ =
ContinuousLinearMap.inr 𝕜 (TangentSpace I x₀) (TangentSpace I' y₀) := by
refine ((mdifferentiableAt_const I' I).mfderiv_prod (mdifferentiableAt_id I')).trans ?_
rw [mfderiv_id, mfderiv_const, ContinuousLinearMap.inr]
#align mfderiv_prod_right mfderiv_prod_right
/-- The total derivative of a function in two variables is the sum of the partial derivatives.
Note that to state this (without casts) we need to be able to see through the definition of
`TangentSpace`. -/
| Mathlib/Geometry/Manifold/MFDeriv/SpecificFunctions.lean | 403 | 419 | theorem mfderiv_prod_eq_add {f : M × M' → M''} {p : M × M'}
(hf : MDifferentiableAt (I.prod I') I'' f p) :
mfderiv (I.prod I') I'' f p =
show E × E' →L[𝕜] E'' from
mfderiv (I.prod I') I'' (fun z : M × M' => f (z.1, p.2)) p +
mfderiv (I.prod I') I'' (fun z : M × M' => f (p.1, z.2)) p := by |
dsimp only
erw [mfderiv_comp_of_eq hf ((mdifferentiableAt_fst I I').prod_mk (mdifferentiableAt_const _ _))
rfl,
mfderiv_comp_of_eq hf ((mdifferentiableAt_const _ _).prod_mk (mdifferentiableAt_snd I I')) rfl,
← ContinuousLinearMap.comp_add,
(mdifferentiableAt_fst I I').mfderiv_prod (mdifferentiableAt_const (I.prod I') I'),
(mdifferentiableAt_const (I.prod I') I).mfderiv_prod (mdifferentiableAt_snd I I'), mfderiv_fst,
mfderiv_snd, mfderiv_const, mfderiv_const]
symm
convert ContinuousLinearMap.comp_id <| mfderiv (.prod I I') I'' f (p.1, p.2)
exact ContinuousLinearMap.coprod_inl_inr
|
/-
Copyright (c) 2022 Wrenna Robson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Wrenna Robson
-/
import Mathlib.Topology.MetricSpace.Basic
#align_import topology.metric_space.infsep from "leanprover-community/mathlib"@"5316314b553dcf8c6716541851517c1a9715e22b"
/-!
# Infimum separation
This file defines the extended infimum separation of a set. This is approximately dual to the
diameter of a set, but where the extended diameter of a set is the supremum of the extended distance
between elements of the set, the extended infimum separation is the infimum of the (extended)
distance between *distinct* elements in the set.
We also define the infimum separation as the cast of the extended infimum separation to the reals.
This is the infimum of the distance between distinct elements of the set when in a pseudometric
space.
All lemmas and definitions are in the `Set` namespace to give access to dot notation.
## Main definitions
* `Set.einfsep`: Extended infimum separation of a set.
* `Set.infsep`: Infimum separation of a set (when in a pseudometric space).
!-/
variable {α β : Type*}
namespace Set
section Einfsep
open ENNReal
open Function
/-- The "extended infimum separation" of a set with an edist function. -/
noncomputable def einfsep [EDist α] (s : Set α) : ℝ≥0∞ :=
⨅ (x ∈ s) (y ∈ s) (_ : x ≠ y), edist x y
#align set.einfsep Set.einfsep
section EDist
variable [EDist α] {x y : α} {s t : Set α}
theorem le_einfsep_iff {d} :
d ≤ s.einfsep ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ edist x y := by
simp_rw [einfsep, le_iInf_iff]
#align set.le_einfsep_iff Set.le_einfsep_iff
theorem einfsep_zero : s.einfsep = 0 ↔ ∀ C > 0, ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < C := by
simp_rw [einfsep, ← _root_.bot_eq_zero, iInf_eq_bot, iInf_lt_iff, exists_prop]
#align set.einfsep_zero Set.einfsep_zero
theorem einfsep_pos : 0 < s.einfsep ↔ ∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y := by
rw [pos_iff_ne_zero, Ne, einfsep_zero]
simp only [not_forall, not_exists, not_lt, exists_prop, not_and]
#align set.einfsep_pos Set.einfsep_pos
theorem einfsep_top :
s.einfsep = ∞ ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → edist x y = ∞ := by
simp_rw [einfsep, iInf_eq_top]
#align set.einfsep_top Set.einfsep_top
theorem einfsep_lt_top :
s.einfsep < ∞ ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < ∞ := by
simp_rw [einfsep, iInf_lt_iff, exists_prop]
#align set.einfsep_lt_top Set.einfsep_lt_top
theorem einfsep_ne_top :
s.einfsep ≠ ∞ ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y ≠ ∞ := by
simp_rw [← lt_top_iff_ne_top, einfsep_lt_top]
#align set.einfsep_ne_top Set.einfsep_ne_top
| Mathlib/Topology/MetricSpace/Infsep.lean | 79 | 81 | theorem einfsep_lt_iff {d} :
s.einfsep < d ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < d := by |
simp_rw [einfsep, iInf_lt_iff, exists_prop]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Scott Morrison
-/
import Mathlib.Algebra.Group.Indicator
import Mathlib.Algebra.Group.Submonoid.Basic
import Mathlib.Data.Set.Finite
#align_import data.finsupp.defs from "leanprover-community/mathlib"@"842328d9df7e96fd90fc424e115679c15fb23a71"
/-!
# Type of functions with finite support
For any type `α` and any type `M` with zero, we define the type `Finsupp α M` (notation: `α →₀ M`)
of finitely supported functions from `α` to `M`, i.e. the functions which are zero everywhere
on `α` except on a finite set.
Functions with finite support are used (at least) in the following parts of the library:
* `MonoidAlgebra R M` and `AddMonoidAlgebra R M` are defined as `M →₀ R`;
* polynomials and multivariate polynomials are defined as `AddMonoidAlgebra`s, hence they use
`Finsupp` under the hood;
* the linear combination of a family of vectors `v i` with coefficients `f i` (as used, e.g., to
define linearly independent family `LinearIndependent`) is defined as a map
`Finsupp.total : (ι → M) → (ι →₀ R) →ₗ[R] M`.
Some other constructions are naturally equivalent to `α →₀ M` with some `α` and `M` but are defined
in a different way in the library:
* `Multiset α ≃+ α →₀ ℕ`;
* `FreeAbelianGroup α ≃+ α →₀ ℤ`.
Most of the theory assumes that the range is a commutative additive monoid. This gives us the big
sum operator as a powerful way to construct `Finsupp` elements, which is defined in
`Algebra/BigOperators/Finsupp`.
-- Porting note: the semireducibility remark no longer applies in Lean 4, afaict.
Many constructions based on `α →₀ M` use `semireducible` type tags to avoid reusing unwanted type
instances. E.g., `MonoidAlgebra`, `AddMonoidAlgebra`, and types based on these two have
non-pointwise multiplication.
## Main declarations
* `Finsupp`: The type of finitely supported functions from `α` to `β`.
* `Finsupp.single`: The `Finsupp` which is nonzero in exactly one point.
* `Finsupp.update`: Changes one value of a `Finsupp`.
* `Finsupp.erase`: Replaces one value of a `Finsupp` by `0`.
* `Finsupp.onFinset`: The restriction of a function to a `Finset` as a `Finsupp`.
* `Finsupp.mapRange`: Composition of a `ZeroHom` with a `Finsupp`.
* `Finsupp.embDomain`: Maps the domain of a `Finsupp` by an embedding.
* `Finsupp.zipWith`: Postcomposition of two `Finsupp`s with a function `f` such that `f 0 0 = 0`.
## Notations
This file adds `α →₀ M` as a global notation for `Finsupp α M`.
We also use the following convention for `Type*` variables in this file
* `α`, `β`, `γ`: types with no additional structure that appear as the first argument to `Finsupp`
somewhere in the statement;
* `ι` : an auxiliary index type;
* `M`, `M'`, `N`, `P`: types with `Zero` or `(Add)(Comm)Monoid` structure; `M` is also used
for a (semi)module over a (semi)ring.
* `G`, `H`: groups (commutative or not, multiplicative or additive);
* `R`, `S`: (semi)rings.
## Implementation notes
This file is a `noncomputable theory` and uses classical logic throughout.
## TODO
* Expand the list of definitions and important lemmas to the module docstring.
-/
noncomputable section
open Finset Function
variable {α β γ ι M M' N P G H R S : Type*}
/-- `Finsupp α M`, denoted `α →₀ M`, is the type of functions `f : α → M` such that
`f x = 0` for all but finitely many `x`. -/
structure Finsupp (α : Type*) (M : Type*) [Zero M] where
/-- The support of a finitely supported function (aka `Finsupp`). -/
support : Finset α
/-- The underlying function of a bundled finitely supported function (aka `Finsupp`). -/
toFun : α → M
/-- The witness that the support of a `Finsupp` is indeed the exact locus where its
underlying function is nonzero. -/
mem_support_toFun : ∀ a, a ∈ support ↔ toFun a ≠ 0
#align finsupp Finsupp
#align finsupp.support Finsupp.support
#align finsupp.to_fun Finsupp.toFun
#align finsupp.mem_support_to_fun Finsupp.mem_support_toFun
@[inherit_doc]
infixr:25 " →₀ " => Finsupp
namespace Finsupp
/-! ### Basic declarations about `Finsupp` -/
section Basic
variable [Zero M]
instance instFunLike : FunLike (α →₀ M) α M :=
⟨toFun, by
rintro ⟨s, f, hf⟩ ⟨t, g, hg⟩ (rfl : f = g)
congr
ext a
exact (hf _).trans (hg _).symm⟩
#align finsupp.fun_like Finsupp.instFunLike
/-- Helper instance for when there are too many metavariables to apply the `DFunLike` instance
directly. -/
instance instCoeFun : CoeFun (α →₀ M) fun _ => α → M :=
inferInstance
#align finsupp.has_coe_to_fun Finsupp.instCoeFun
@[ext]
theorem ext {f g : α →₀ M} (h : ∀ a, f a = g a) : f = g :=
DFunLike.ext _ _ h
#align finsupp.ext Finsupp.ext
#align finsupp.ext_iff DFunLike.ext_iff
lemma ne_iff {f g : α →₀ M} : f ≠ g ↔ ∃ a, f a ≠ g a := DFunLike.ne_iff
#align finsupp.coe_fn_inj DFunLike.coe_fn_eq
#align finsupp.coe_fn_injective DFunLike.coe_injective
#align finsupp.congr_fun DFunLike.congr_fun
@[simp, norm_cast]
theorem coe_mk (f : α → M) (s : Finset α) (h : ∀ a, a ∈ s ↔ f a ≠ 0) : ⇑(⟨s, f, h⟩ : α →₀ M) = f :=
rfl
#align finsupp.coe_mk Finsupp.coe_mk
instance instZero : Zero (α →₀ M) :=
⟨⟨∅, 0, fun _ => ⟨fun h ↦ (not_mem_empty _ h).elim, fun H => (H rfl).elim⟩⟩⟩
#align finsupp.has_zero Finsupp.instZero
@[simp, norm_cast] lemma coe_zero : ⇑(0 : α →₀ M) = 0 := rfl
#align finsupp.coe_zero Finsupp.coe_zero
theorem zero_apply {a : α} : (0 : α →₀ M) a = 0 :=
rfl
#align finsupp.zero_apply Finsupp.zero_apply
@[simp]
theorem support_zero : (0 : α →₀ M).support = ∅ :=
rfl
#align finsupp.support_zero Finsupp.support_zero
instance instInhabited : Inhabited (α →₀ M) :=
⟨0⟩
#align finsupp.inhabited Finsupp.instInhabited
@[simp]
theorem mem_support_iff {f : α →₀ M} : ∀ {a : α}, a ∈ f.support ↔ f a ≠ 0 :=
@(f.mem_support_toFun)
#align finsupp.mem_support_iff Finsupp.mem_support_iff
@[simp, norm_cast]
theorem fun_support_eq (f : α →₀ M) : Function.support f = f.support :=
Set.ext fun _x => mem_support_iff.symm
#align finsupp.fun_support_eq Finsupp.fun_support_eq
theorem not_mem_support_iff {f : α →₀ M} {a} : a ∉ f.support ↔ f a = 0 :=
not_iff_comm.1 mem_support_iff.symm
#align finsupp.not_mem_support_iff Finsupp.not_mem_support_iff
@[simp, norm_cast]
theorem coe_eq_zero {f : α →₀ M} : (f : α → M) = 0 ↔ f = 0 := by rw [← coe_zero, DFunLike.coe_fn_eq]
#align finsupp.coe_eq_zero Finsupp.coe_eq_zero
theorem ext_iff' {f g : α →₀ M} : f = g ↔ f.support = g.support ∧ ∀ x ∈ f.support, f x = g x :=
⟨fun h => h ▸ ⟨rfl, fun _ _ => rfl⟩, fun ⟨h₁, h₂⟩ =>
ext fun a => by
classical
exact if h : a ∈ f.support then h₂ a h else by
have hf : f a = 0 := not_mem_support_iff.1 h
have hg : g a = 0 := by rwa [h₁, not_mem_support_iff] at h
rw [hf, hg]⟩
#align finsupp.ext_iff' Finsupp.ext_iff'
@[simp]
theorem support_eq_empty {f : α →₀ M} : f.support = ∅ ↔ f = 0 :=
mod_cast @Function.support_eq_empty_iff _ _ _ f
#align finsupp.support_eq_empty Finsupp.support_eq_empty
theorem support_nonempty_iff {f : α →₀ M} : f.support.Nonempty ↔ f ≠ 0 := by
simp only [Finsupp.support_eq_empty, Finset.nonempty_iff_ne_empty, Ne]
#align finsupp.support_nonempty_iff Finsupp.support_nonempty_iff
#align finsupp.nonzero_iff_exists Finsupp.ne_iff
theorem card_support_eq_zero {f : α →₀ M} : card f.support = 0 ↔ f = 0 := by simp
#align finsupp.card_support_eq_zero Finsupp.card_support_eq_zero
instance instDecidableEq [DecidableEq α] [DecidableEq M] : DecidableEq (α →₀ M) := fun f g =>
decidable_of_iff (f.support = g.support ∧ ∀ a ∈ f.support, f a = g a) ext_iff'.symm
#align finsupp.decidable_eq Finsupp.instDecidableEq
theorem finite_support (f : α →₀ M) : Set.Finite (Function.support f) :=
f.fun_support_eq.symm ▸ f.support.finite_toSet
#align finsupp.finite_support Finsupp.finite_support
theorem support_subset_iff {s : Set α} {f : α →₀ M} :
↑f.support ⊆ s ↔ ∀ a ∉ s, f a = 0 := by
simp only [Set.subset_def, mem_coe, mem_support_iff]; exact forall_congr' fun a => not_imp_comm
#align finsupp.support_subset_iff Finsupp.support_subset_iff
/-- Given `Finite α`, `equivFunOnFinite` is the `Equiv` between `α →₀ β` and `α → β`.
(All functions on a finite type are finitely supported.) -/
@[simps]
def equivFunOnFinite [Finite α] : (α →₀ M) ≃ (α → M) where
toFun := (⇑)
invFun f := mk (Function.support f).toFinite.toFinset f fun _a => Set.Finite.mem_toFinset _
left_inv _f := ext fun _x => rfl
right_inv _f := rfl
#align finsupp.equiv_fun_on_finite Finsupp.equivFunOnFinite
@[simp]
theorem equivFunOnFinite_symm_coe {α} [Finite α] (f : α →₀ M) : equivFunOnFinite.symm f = f :=
equivFunOnFinite.symm_apply_apply f
#align finsupp.equiv_fun_on_finite_symm_coe Finsupp.equivFunOnFinite_symm_coe
/--
If `α` has a unique term, the type of finitely supported functions `α →₀ β` is equivalent to `β`.
-/
@[simps!]
noncomputable def _root_.Equiv.finsuppUnique {ι : Type*} [Unique ι] : (ι →₀ M) ≃ M :=
Finsupp.equivFunOnFinite.trans (Equiv.funUnique ι M)
#align equiv.finsupp_unique Equiv.finsuppUnique
#align equiv.finsupp_unique_symm_apply_support_val Equiv.finsuppUnique_symm_apply_support_val
#align equiv.finsupp_unique_symm_apply_to_fun Equiv.finsuppUnique_symm_apply_toFun
#align equiv.finsupp_unique_apply Equiv.finsuppUnique_apply
@[ext]
theorem unique_ext [Unique α] {f g : α →₀ M} (h : f default = g default) : f = g :=
ext fun a => by rwa [Unique.eq_default a]
#align finsupp.unique_ext Finsupp.unique_ext
theorem unique_ext_iff [Unique α] {f g : α →₀ M} : f = g ↔ f default = g default :=
⟨fun h => h ▸ rfl, unique_ext⟩
#align finsupp.unique_ext_iff Finsupp.unique_ext_iff
end Basic
/-! ### Declarations about `single` -/
section Single
variable [Zero M] {a a' : α} {b : M}
/-- `single a b` is the finitely supported function with value `b` at `a` and zero otherwise. -/
def single (a : α) (b : M) : α →₀ M where
support :=
haveI := Classical.decEq M
if b = 0 then ∅ else {a}
toFun :=
haveI := Classical.decEq α
Pi.single a b
mem_support_toFun a' := by
classical
obtain rfl | hb := eq_or_ne b 0
· simp [Pi.single, update]
rw [if_neg hb, mem_singleton]
obtain rfl | ha := eq_or_ne a' a
· simp [hb, Pi.single, update]
simp [Pi.single_eq_of_ne' ha.symm, ha]
#align finsupp.single Finsupp.single
theorem single_apply [Decidable (a = a')] : single a b a' = if a = a' then b else 0 := by
classical
simp_rw [@eq_comm _ a a']
convert Pi.single_apply a b a'
#align finsupp.single_apply Finsupp.single_apply
theorem single_apply_left {f : α → β} (hf : Function.Injective f) (x z : α) (y : M) :
single (f x) y (f z) = single x y z := by classical simp only [single_apply, hf.eq_iff]
#align finsupp.single_apply_left Finsupp.single_apply_left
theorem single_eq_set_indicator : ⇑(single a b) = Set.indicator {a} fun _ => b := by
classical
ext
simp [single_apply, Set.indicator, @eq_comm _ a]
#align finsupp.single_eq_set_indicator Finsupp.single_eq_set_indicator
@[simp]
| Mathlib/Data/Finsupp/Defs.lean | 304 | 305 | theorem single_eq_same : (single a b : α →₀ M) a = b := by |
classical exact Pi.single_eq_same (f := fun _ ↦ M) a b
|
/-
Copyright (c) 2021 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Analysis.Convex.Topology
import Mathlib.Analysis.NormedSpace.Pointwise
import Mathlib.Analysis.Seminorm
import Mathlib.Analysis.LocallyConvex.Bounded
import Mathlib.Analysis.RCLike.Basic
#align_import analysis.convex.gauge from "leanprover-community/mathlib"@"373b03b5b9d0486534edbe94747f23cb3712f93d"
/-!
# The Minkowski functional
This file defines the Minkowski functional, aka gauge.
The Minkowski functional of a set `s` is the function which associates each point to how much you
need to scale `s` for `x` to be inside it. When `s` is symmetric, convex and absorbent, its gauge is
a seminorm. Reciprocally, any seminorm arises as the gauge of some set, namely its unit ball. This
induces the equivalence of seminorms and locally convex topological vector spaces.
## Main declarations
For a real vector space,
* `gauge`: Aka Minkowski functional. `gauge s x` is the least (actually, an infimum) `r` such
that `x ∈ r • s`.
* `gaugeSeminorm`: The Minkowski functional as a seminorm, when `s` is symmetric, convex and
absorbent.
## References
* [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966]
## Tags
Minkowski functional, gauge
-/
open NormedField Set
open scoped Pointwise Topology NNReal
noncomputable section
variable {𝕜 E F : Type*}
section AddCommGroup
variable [AddCommGroup E] [Module ℝ E]
/-- The Minkowski functional. Given a set `s` in a real vector space, `gauge s` is the functional
which sends `x : E` to the smallest `r : ℝ` such that `x` is in `s` scaled by `r`. -/
def gauge (s : Set E) (x : E) : ℝ :=
sInf { r : ℝ | 0 < r ∧ x ∈ r • s }
#align gauge gauge
variable {s t : Set E} {x : E} {a : ℝ}
theorem gauge_def : gauge s x = sInf ({ r ∈ Set.Ioi (0 : ℝ) | x ∈ r • s }) :=
rfl
#align gauge_def gauge_def
/-- An alternative definition of the gauge using scalar multiplication on the element rather than on
the set. -/
theorem gauge_def' : gauge s x = sInf {r ∈ Set.Ioi (0 : ℝ) | r⁻¹ • x ∈ s} := by
congrm sInf {r | ?_}
exact and_congr_right fun hr => mem_smul_set_iff_inv_smul_mem₀ hr.ne' _ _
#align gauge_def' gauge_def'
private theorem gauge_set_bddBelow : BddBelow { r : ℝ | 0 < r ∧ x ∈ r • s } :=
⟨0, fun _ hr => hr.1.le⟩
/-- If the given subset is `Absorbent` then the set we take an infimum over in `gauge` is nonempty,
which is useful for proving many properties about the gauge. -/
theorem Absorbent.gauge_set_nonempty (absorbs : Absorbent ℝ s) :
{ r : ℝ | 0 < r ∧ x ∈ r • s }.Nonempty :=
let ⟨r, hr₁, hr₂⟩ := (absorbs x).exists_pos
⟨r, hr₁, hr₂ r (Real.norm_of_nonneg hr₁.le).ge rfl⟩
#align absorbent.gauge_set_nonempty Absorbent.gauge_set_nonempty
theorem gauge_mono (hs : Absorbent ℝ s) (h : s ⊆ t) : gauge t ≤ gauge s := fun _ =>
csInf_le_csInf gauge_set_bddBelow hs.gauge_set_nonempty fun _ hr => ⟨hr.1, smul_set_mono h hr.2⟩
#align gauge_mono gauge_mono
theorem exists_lt_of_gauge_lt (absorbs : Absorbent ℝ s) (h : gauge s x < a) :
∃ b, 0 < b ∧ b < a ∧ x ∈ b • s := by
obtain ⟨b, ⟨hb, hx⟩, hba⟩ := exists_lt_of_csInf_lt absorbs.gauge_set_nonempty h
exact ⟨b, hb, hba, hx⟩
#align exists_lt_of_gauge_lt exists_lt_of_gauge_lt
/-- The gauge evaluated at `0` is always zero (mathematically this requires `0` to be in the set `s`
but, the real infimum of the empty set in Lean being defined as `0`, it holds unconditionally). -/
@[simp]
theorem gauge_zero : gauge s 0 = 0 := by
rw [gauge_def']
by_cases h : (0 : E) ∈ s
· simp only [smul_zero, sep_true, h, csInf_Ioi]
· simp only [smul_zero, sep_false, h, Real.sInf_empty]
#align gauge_zero gauge_zero
@[simp]
theorem gauge_zero' : gauge (0 : Set E) = 0 := by
ext x
rw [gauge_def']
obtain rfl | hx := eq_or_ne x 0
· simp only [csInf_Ioi, mem_zero, Pi.zero_apply, eq_self_iff_true, sep_true, smul_zero]
· simp only [mem_zero, Pi.zero_apply, inv_eq_zero, smul_eq_zero]
convert Real.sInf_empty
exact eq_empty_iff_forall_not_mem.2 fun r hr => hr.2.elim (ne_of_gt hr.1) hx
#align gauge_zero' gauge_zero'
@[simp]
theorem gauge_empty : gauge (∅ : Set E) = 0 := by
ext
simp only [gauge_def', Real.sInf_empty, mem_empty_iff_false, Pi.zero_apply, sep_false]
#align gauge_empty gauge_empty
theorem gauge_of_subset_zero (h : s ⊆ 0) : gauge s = 0 := by
obtain rfl | rfl := subset_singleton_iff_eq.1 h
exacts [gauge_empty, gauge_zero']
#align gauge_of_subset_zero gauge_of_subset_zero
/-- The gauge is always nonnegative. -/
theorem gauge_nonneg (x : E) : 0 ≤ gauge s x :=
Real.sInf_nonneg _ fun _ hx => hx.1.le
#align gauge_nonneg gauge_nonneg
theorem gauge_neg (symmetric : ∀ x ∈ s, -x ∈ s) (x : E) : gauge s (-x) = gauge s x := by
have : ∀ x, -x ∈ s ↔ x ∈ s := fun x => ⟨fun h => by simpa using symmetric _ h, symmetric x⟩
simp_rw [gauge_def', smul_neg, this]
#align gauge_neg gauge_neg
theorem gauge_neg_set_neg (x : E) : gauge (-s) (-x) = gauge s x := by
simp_rw [gauge_def', smul_neg, neg_mem_neg]
#align gauge_neg_set_neg gauge_neg_set_neg
theorem gauge_neg_set_eq_gauge_neg (x : E) : gauge (-s) x = gauge s (-x) := by
rw [← gauge_neg_set_neg, neg_neg]
#align gauge_neg_set_eq_gauge_neg gauge_neg_set_eq_gauge_neg
theorem gauge_le_of_mem (ha : 0 ≤ a) (hx : x ∈ a • s) : gauge s x ≤ a := by
obtain rfl | ha' := ha.eq_or_lt
· rw [mem_singleton_iff.1 (zero_smul_set_subset _ hx), gauge_zero]
· exact csInf_le gauge_set_bddBelow ⟨ha', hx⟩
#align gauge_le_of_mem gauge_le_of_mem
theorem gauge_le_eq (hs₁ : Convex ℝ s) (hs₀ : (0 : E) ∈ s) (hs₂ : Absorbent ℝ s) (ha : 0 ≤ a) :
{ x | gauge s x ≤ a } = ⋂ (r : ℝ) (_ : a < r), r • s := by
ext x
simp_rw [Set.mem_iInter, Set.mem_setOf_eq]
refine ⟨fun h r hr => ?_, fun h => le_of_forall_pos_lt_add fun ε hε => ?_⟩
· have hr' := ha.trans_lt hr
rw [mem_smul_set_iff_inv_smul_mem₀ hr'.ne']
obtain ⟨δ, δ_pos, hδr, hδ⟩ := exists_lt_of_gauge_lt hs₂ (h.trans_lt hr)
suffices (r⁻¹ * δ) • δ⁻¹ • x ∈ s by rwa [smul_smul, mul_inv_cancel_right₀ δ_pos.ne'] at this
rw [mem_smul_set_iff_inv_smul_mem₀ δ_pos.ne'] at hδ
refine hs₁.smul_mem_of_zero_mem hs₀ hδ ⟨by positivity, ?_⟩
rw [inv_mul_le_iff hr', mul_one]
exact hδr.le
· have hε' := (lt_add_iff_pos_right a).2 (half_pos hε)
exact
(gauge_le_of_mem (ha.trans hε'.le) <| h _ hε').trans_lt (add_lt_add_left (half_lt_self hε) _)
#align gauge_le_eq gauge_le_eq
theorem gauge_lt_eq' (absorbs : Absorbent ℝ s) (a : ℝ) :
{ x | gauge s x < a } = ⋃ (r : ℝ) (_ : 0 < r) (_ : r < a), r • s := by
ext
simp_rw [mem_setOf, mem_iUnion, exists_prop]
exact
⟨exists_lt_of_gauge_lt absorbs, fun ⟨r, hr₀, hr₁, hx⟩ =>
(gauge_le_of_mem hr₀.le hx).trans_lt hr₁⟩
#align gauge_lt_eq' gauge_lt_eq'
theorem gauge_lt_eq (absorbs : Absorbent ℝ s) (a : ℝ) :
{ x | gauge s x < a } = ⋃ r ∈ Set.Ioo 0 (a : ℝ), r • s := by
ext
simp_rw [mem_setOf, mem_iUnion, exists_prop, mem_Ioo, and_assoc]
exact
⟨exists_lt_of_gauge_lt absorbs, fun ⟨r, hr₀, hr₁, hx⟩ =>
(gauge_le_of_mem hr₀.le hx).trans_lt hr₁⟩
#align gauge_lt_eq gauge_lt_eq
theorem mem_openSegment_of_gauge_lt_one (absorbs : Absorbent ℝ s) (hgauge : gauge s x < 1) :
∃ y ∈ s, x ∈ openSegment ℝ 0 y := by
rcases exists_lt_of_gauge_lt absorbs hgauge with ⟨r, hr₀, hr₁, y, hy, rfl⟩
refine ⟨y, hy, 1 - r, r, ?_⟩
simp [*]
theorem gauge_lt_one_subset_self (hs : Convex ℝ s) (h₀ : (0 : E) ∈ s) (absorbs : Absorbent ℝ s) :
{ x | gauge s x < 1 } ⊆ s := fun _x hx ↦
let ⟨_y, hys, hx⟩ := mem_openSegment_of_gauge_lt_one absorbs hx
hs.openSegment_subset h₀ hys hx
#align gauge_lt_one_subset_self gauge_lt_one_subset_self
theorem gauge_le_one_of_mem {x : E} (hx : x ∈ s) : gauge s x ≤ 1 :=
gauge_le_of_mem zero_le_one <| by rwa [one_smul]
#align gauge_le_one_of_mem gauge_le_one_of_mem
/-- Gauge is subadditive. -/
theorem gauge_add_le (hs : Convex ℝ s) (absorbs : Absorbent ℝ s) (x y : E) :
gauge s (x + y) ≤ gauge s x + gauge s y := by
refine le_of_forall_pos_lt_add fun ε hε => ?_
obtain ⟨a, ha, ha', x, hx, rfl⟩ :=
exists_lt_of_gauge_lt absorbs (lt_add_of_pos_right (gauge s x) (half_pos hε))
obtain ⟨b, hb, hb', y, hy, rfl⟩ :=
exists_lt_of_gauge_lt absorbs (lt_add_of_pos_right (gauge s y) (half_pos hε))
calc
gauge s (a • x + b • y) ≤ a + b := gauge_le_of_mem (by positivity) <| by
rw [hs.add_smul ha.le hb.le]
exact add_mem_add (smul_mem_smul_set hx) (smul_mem_smul_set hy)
_ < gauge s (a • x) + gauge s (b • y) + ε := by linarith
#align gauge_add_le gauge_add_le
theorem self_subset_gauge_le_one : s ⊆ { x | gauge s x ≤ 1 } := fun _ => gauge_le_one_of_mem
#align self_subset_gauge_le_one self_subset_gauge_le_one
theorem Convex.gauge_le (hs : Convex ℝ s) (h₀ : (0 : E) ∈ s) (absorbs : Absorbent ℝ s) (a : ℝ) :
Convex ℝ { x | gauge s x ≤ a } := by
by_cases ha : 0 ≤ a
· rw [gauge_le_eq hs h₀ absorbs ha]
exact convex_iInter fun i => convex_iInter fun _ => hs.smul _
· -- Porting note: `convert` needed help
convert convex_empty (𝕜 := ℝ) (E := E)
exact eq_empty_iff_forall_not_mem.2 fun x hx => ha <| (gauge_nonneg _).trans hx
#align convex.gauge_le Convex.gauge_le
theorem Balanced.starConvex (hs : Balanced ℝ s) : StarConvex ℝ 0 s :=
starConvex_zero_iff.2 fun x hx a ha₀ ha₁ =>
hs _ (by rwa [Real.norm_of_nonneg ha₀]) (smul_mem_smul_set hx)
#align balanced.star_convex Balanced.starConvex
theorem le_gauge_of_not_mem (hs₀ : StarConvex ℝ 0 s) (hs₂ : Absorbs ℝ s {x}) (hx : x ∉ a • s) :
a ≤ gauge s x := by
rw [starConvex_zero_iff] at hs₀
obtain ⟨r, hr, h⟩ := hs₂.exists_pos
refine le_csInf ⟨r, hr, singleton_subset_iff.1 <| h _ (Real.norm_of_nonneg hr.le).ge⟩ ?_
rintro b ⟨hb, x, hx', rfl⟩
refine not_lt.1 fun hba => hx ?_
have ha := hb.trans hba
refine ⟨(a⁻¹ * b) • x, hs₀ hx' (by positivity) ?_, ?_⟩
· rw [← div_eq_inv_mul]
exact div_le_one_of_le hba.le ha.le
· dsimp only
rw [← mul_smul, mul_inv_cancel_left₀ ha.ne']
#align le_gauge_of_not_mem le_gauge_of_not_mem
theorem one_le_gauge_of_not_mem (hs₁ : StarConvex ℝ 0 s) (hs₂ : Absorbs ℝ s {x}) (hx : x ∉ s) :
1 ≤ gauge s x :=
le_gauge_of_not_mem hs₁ hs₂ <| by rwa [one_smul]
#align one_le_gauge_of_not_mem one_le_gauge_of_not_mem
section LinearOrderedField
variable {α : Type*} [LinearOrderedField α] [MulActionWithZero α ℝ] [OrderedSMul α ℝ]
theorem gauge_smul_of_nonneg [MulActionWithZero α E] [IsScalarTower α ℝ (Set E)] {s : Set E} {a : α}
(ha : 0 ≤ a) (x : E) : gauge s (a • x) = a • gauge s x := by
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_smul, gauge_zero, zero_smul]
rw [gauge_def', gauge_def', ← Real.sInf_smul_of_nonneg ha]
congr 1
ext r
simp_rw [Set.mem_smul_set, Set.mem_sep_iff]
constructor
· rintro ⟨hr, hx⟩
simp_rw [mem_Ioi] at hr ⊢
rw [← mem_smul_set_iff_inv_smul_mem₀ hr.ne'] at hx
have := smul_pos (inv_pos.2 ha') hr
refine ⟨a⁻¹ • r, ⟨this, ?_⟩, smul_inv_smul₀ ha'.ne' _⟩
rwa [← mem_smul_set_iff_inv_smul_mem₀ this.ne', smul_assoc,
mem_smul_set_iff_inv_smul_mem₀ (inv_ne_zero ha'.ne'), inv_inv]
· rintro ⟨r, ⟨hr, hx⟩, rfl⟩
rw [mem_Ioi] at hr ⊢
rw [← mem_smul_set_iff_inv_smul_mem₀ hr.ne'] at hx
have := smul_pos ha' hr
refine ⟨this, ?_⟩
rw [← mem_smul_set_iff_inv_smul_mem₀ this.ne', smul_assoc]
exact smul_mem_smul_set hx
#align gauge_smul_of_nonneg gauge_smul_of_nonneg
theorem gauge_smul_left_of_nonneg [MulActionWithZero α E] [SMulCommClass α ℝ ℝ]
[IsScalarTower α ℝ ℝ] [IsScalarTower α ℝ E] {s : Set E} {a : α} (ha : 0 ≤ a) :
gauge (a • s) = a⁻¹ • gauge s := by
obtain rfl | ha' := ha.eq_or_lt
· rw [inv_zero, zero_smul, gauge_of_subset_zero (zero_smul_set_subset _)]
ext x
rw [gauge_def', Pi.smul_apply, gauge_def', ← Real.sInf_smul_of_nonneg (inv_nonneg.2 ha)]
congr 1
ext r
simp_rw [Set.mem_smul_set, Set.mem_sep_iff]
constructor
· rintro ⟨hr, y, hy, h⟩
simp_rw [mem_Ioi] at hr ⊢
refine ⟨a • r, ⟨smul_pos ha' hr, ?_⟩, inv_smul_smul₀ ha'.ne' _⟩
rwa [smul_inv₀, smul_assoc, ← h, inv_smul_smul₀ ha'.ne']
· rintro ⟨r, ⟨hr, hx⟩, rfl⟩
rw [mem_Ioi] at hr ⊢
refine ⟨smul_pos (inv_pos.2 ha') hr, r⁻¹ • x, hx, ?_⟩
rw [smul_inv₀, smul_assoc, inv_inv]
#align gauge_smul_left_of_nonneg gauge_smul_left_of_nonneg
theorem gauge_smul_left [Module α E] [SMulCommClass α ℝ ℝ] [IsScalarTower α ℝ ℝ]
[IsScalarTower α ℝ E] {s : Set E} (symmetric : ∀ x ∈ s, -x ∈ s) (a : α) :
gauge (a • s) = |a|⁻¹ • gauge s := by
rw [← gauge_smul_left_of_nonneg (abs_nonneg a)]
obtain h | h := abs_choice a
· rw [h]
· rw [h, Set.neg_smul_set, ← Set.smul_set_neg]
-- Porting note: was congr
apply congr_arg
apply congr_arg
ext y
refine ⟨symmetric _, fun hy => ?_⟩
rw [← neg_neg y]
exact symmetric _ hy
#align gauge_smul_left gauge_smul_left
end LinearOrderedField
section RCLike
variable [RCLike 𝕜] [Module 𝕜 E] [IsScalarTower ℝ 𝕜 E]
theorem gauge_norm_smul (hs : Balanced 𝕜 s) (r : 𝕜) (x : E) :
gauge s (‖r‖ • x) = gauge s (r • x) := by
unfold gauge
congr with θ
rw [@RCLike.real_smul_eq_coe_smul 𝕜]
refine and_congr_right fun hθ => (hs.smul _).smul_mem_iff ?_
rw [RCLike.norm_ofReal, abs_norm]
#align gauge_norm_smul gauge_norm_smul
/-- If `s` is balanced, then the Minkowski functional is ℂ-homogeneous. -/
theorem gauge_smul (hs : Balanced 𝕜 s) (r : 𝕜) (x : E) : gauge s (r • x) = ‖r‖ * gauge s x := by
rw [← smul_eq_mul, ← gauge_smul_of_nonneg (norm_nonneg r), gauge_norm_smul hs]
#align gauge_smul gauge_smul
end RCLike
open Filter
section TopologicalSpace
variable [TopologicalSpace E]
theorem comap_gauge_nhds_zero_le (ha : Absorbent ℝ s) (hb : Bornology.IsVonNBounded ℝ s) :
comap (gauge s) (𝓝 0) ≤ 𝓝 0 := fun u hu ↦ by
rcases (hb hu).exists_pos with ⟨r, hr₀, hr⟩
filter_upwards [preimage_mem_comap (gt_mem_nhds (inv_pos.2 hr₀))] with x (hx : gauge s x < r⁻¹)
rcases exists_lt_of_gauge_lt ha hx with ⟨c, hc₀, hcr, y, hy, rfl⟩
have hrc := (lt_inv hr₀ hc₀).2 hcr
rcases hr c⁻¹ (hrc.le.trans (le_abs_self _)) hy with ⟨z, hz, rfl⟩
simpa only [smul_inv_smul₀ hc₀.ne']
variable [T1Space E]
theorem gauge_eq_zero (hs : Absorbent ℝ s) (hb : Bornology.IsVonNBounded ℝ s) :
gauge s x = 0 ↔ x = 0 := by
refine ⟨fun h₀ ↦ by_contra fun (hne : x ≠ 0) ↦ ?_, fun h ↦ h.symm ▸ gauge_zero⟩
have : {x}ᶜ ∈ comap (gauge s) (𝓝 0) :=
comap_gauge_nhds_zero_le hs hb (isOpen_compl_singleton.mem_nhds hne.symm)
rcases ((nhds_basis_zero_abs_sub_lt _).comap _).mem_iff.1 this with ⟨r, hr₀, hr⟩
exact hr (by simpa [h₀]) rfl
theorem gauge_pos (hs : Absorbent ℝ s) (hb : Bornology.IsVonNBounded ℝ s) :
0 < gauge s x ↔ x ≠ 0 := by
simp only [(gauge_nonneg _).gt_iff_ne, Ne, gauge_eq_zero hs hb]
end TopologicalSpace
section ContinuousSMul
variable [TopologicalSpace E] [ContinuousSMul ℝ E]
open Filter in
theorem interior_subset_gauge_lt_one (s : Set E) : interior s ⊆ { x | gauge s x < 1 } := by
intro x hx
have H₁ : Tendsto (fun r : ℝ ↦ r⁻¹ • x) (𝓝[<] 1) (𝓝 ((1 : ℝ)⁻¹ • x)) :=
((tendsto_id.inv₀ one_ne_zero).smul tendsto_const_nhds).mono_left inf_le_left
rw [inv_one, one_smul] at H₁
have H₂ : ∀ᶠ r in 𝓝[<] (1 : ℝ), x ∈ r • s ∧ 0 < r ∧ r < 1 := by
filter_upwards [H₁ (mem_interior_iff_mem_nhds.1 hx), Ioo_mem_nhdsWithin_Iio' one_pos]
intro r h₁ h₂
exact ⟨(mem_smul_set_iff_inv_smul_mem₀ h₂.1.ne' _ _).2 h₁, h₂⟩
rcases H₂.exists with ⟨r, hxr, hr₀, hr₁⟩
exact (gauge_le_of_mem hr₀.le hxr).trans_lt hr₁
#align interior_subset_gauge_lt_one interior_subset_gauge_lt_one
theorem gauge_lt_one_eq_self_of_isOpen (hs₁ : Convex ℝ s) (hs₀ : (0 : E) ∈ s) (hs₂ : IsOpen s) :
{ x | gauge s x < 1 } = s := by
refine (gauge_lt_one_subset_self hs₁ ‹_› <| absorbent_nhds_zero <| hs₂.mem_nhds hs₀).antisymm ?_
convert interior_subset_gauge_lt_one s
exact hs₂.interior_eq.symm
#align gauge_lt_one_eq_self_of_open gauge_lt_one_eq_self_of_isOpen
-- Porting note: droped unneeded assumptions
theorem gauge_lt_one_of_mem_of_isOpen (hs₂ : IsOpen s) {x : E} (hx : x ∈ s) :
gauge s x < 1 :=
interior_subset_gauge_lt_one s <| by rwa [hs₂.interior_eq]
#align gauge_lt_one_of_mem_of_open gauge_lt_one_of_mem_of_isOpenₓ
-- Porting note: droped unneeded assumptions
theorem gauge_lt_of_mem_smul (x : E) (ε : ℝ) (hε : 0 < ε) (hs₂ : IsOpen s) (hx : x ∈ ε • s) :
gauge s x < ε := by
have : ε⁻¹ • x ∈ s := by rwa [← mem_smul_set_iff_inv_smul_mem₀ hε.ne']
have h_gauge_lt := gauge_lt_one_of_mem_of_isOpen hs₂ this
rwa [gauge_smul_of_nonneg (inv_nonneg.2 hε.le), smul_eq_mul, inv_mul_lt_iff hε, mul_one]
at h_gauge_lt
#align gauge_lt_of_mem_smul gauge_lt_of_mem_smulₓ
theorem mem_closure_of_gauge_le_one (hc : Convex ℝ s) (hs₀ : 0 ∈ s) (ha : Absorbent ℝ s)
(h : gauge s x ≤ 1) : x ∈ closure s := by
have : ∀ᶠ r : ℝ in 𝓝[<] 1, r • x ∈ s := by
filter_upwards [Ico_mem_nhdsWithin_Iio' one_pos] with r ⟨hr₀, hr₁⟩
apply gauge_lt_one_subset_self hc hs₀ ha
rw [mem_setOf_eq, gauge_smul_of_nonneg hr₀]
exact mul_lt_one_of_nonneg_of_lt_one_left hr₀ hr₁ h
refine mem_closure_of_tendsto ?_ this
exact Filter.Tendsto.mono_left (Continuous.tendsto' (by continuity) _ _ (one_smul _ _))
inf_le_left
theorem mem_frontier_of_gauge_eq_one (hc : Convex ℝ s) (hs₀ : 0 ∈ s) (ha : Absorbent ℝ s)
(h : gauge s x = 1) : x ∈ frontier s :=
⟨mem_closure_of_gauge_le_one hc hs₀ ha h.le, fun h' ↦
(interior_subset_gauge_lt_one s h').out.ne h⟩
theorem tendsto_gauge_nhds_zero' (hs : s ∈ 𝓝 0) : Tendsto (gauge s) (𝓝 0) (𝓝[≥] 0) := by
refine nhdsWithin_Ici_basis_Icc.tendsto_right_iff.2 fun ε hε ↦ ?_
rw [← set_smul_mem_nhds_zero_iff hε.ne'] at hs
filter_upwards [hs] with x hx
exact ⟨gauge_nonneg _, gauge_le_of_mem hε.le hx⟩
theorem tendsto_gauge_nhds_zero (hs : s ∈ 𝓝 0) : Tendsto (gauge s) (𝓝 0) (𝓝 0) :=
(tendsto_gauge_nhds_zero' hs).mono_right inf_le_left
/-- If `s` is a neighborhood of the origin, then `gauge s` is continuous at the origin.
See also `continuousAt_gauge`. -/
theorem continuousAt_gauge_zero (hs : s ∈ 𝓝 0) : ContinuousAt (gauge s) 0 := by
rw [ContinuousAt, gauge_zero]
exact tendsto_gauge_nhds_zero hs
theorem comap_gauge_nhds_zero (hb : Bornology.IsVonNBounded ℝ s) (h₀ : s ∈ 𝓝 0) :
comap (gauge s) (𝓝 0) = 𝓝 0 :=
(comap_gauge_nhds_zero_le (absorbent_nhds_zero h₀) hb).antisymm
(tendsto_gauge_nhds_zero h₀).le_comap
end ContinuousSMul
section TopologicalVectorSpace
open Filter
variable [TopologicalSpace E] [TopologicalAddGroup E] [ContinuousSMul ℝ E]
/-- If `s` is a convex neighborhood of the origin in a topological real vector space, then `gauge s`
is continuous. If the ambient space is a normed space, then `gauge s` is Lipschitz continuous, see
`Convex.lipschitz_gauge`. -/
theorem continuousAt_gauge (hc : Convex ℝ s) (hs₀ : s ∈ 𝓝 0) : ContinuousAt (gauge s) x := by
have ha : Absorbent ℝ s := absorbent_nhds_zero hs₀
refine (nhds_basis_Icc_pos _).tendsto_right_iff.2 fun ε hε₀ ↦ ?_
rw [← map_add_left_nhds_zero, eventually_map]
have : ε • s ∩ -(ε • s) ∈ 𝓝 0 :=
inter_mem ((set_smul_mem_nhds_zero_iff hε₀.ne').2 hs₀)
(neg_mem_nhds_zero _ ((set_smul_mem_nhds_zero_iff hε₀.ne').2 hs₀))
filter_upwards [this] with y hy
constructor
· rw [sub_le_iff_le_add]
calc
gauge s x = gauge s (x + y + (-y)) := by simp
_ ≤ gauge s (x + y) + gauge s (-y) := gauge_add_le hc ha _ _
_ ≤ gauge s (x + y) + ε := add_le_add_left (gauge_le_of_mem hε₀.le (mem_neg.1 hy.2)) _
· calc
gauge s (x + y) ≤ gauge s x + gauge s y := gauge_add_le hc ha _ _
_ ≤ gauge s x + ε := add_le_add_left (gauge_le_of_mem hε₀.le hy.1) _
/-- If `s` is a convex neighborhood of the origin in a topological real vector space, then `gauge s`
is continuous. If the ambient space is a normed space, then `gauge s` is Lipschitz continuous, see
`Convex.lipschitz_gauge`. -/
@[continuity]
theorem continuous_gauge (hc : Convex ℝ s) (hs₀ : s ∈ 𝓝 0) : Continuous (gauge s) :=
continuous_iff_continuousAt.2 fun _ ↦ continuousAt_gauge hc hs₀
theorem gauge_lt_one_eq_interior (hc : Convex ℝ s) (hs₀ : s ∈ 𝓝 0) :
{ x | gauge s x < 1 } = interior s := by
refine Subset.antisymm (fun x hx ↦ ?_) (interior_subset_gauge_lt_one s)
rcases mem_openSegment_of_gauge_lt_one (absorbent_nhds_zero hs₀) hx with ⟨y, hys, hxy⟩
exact hc.openSegment_interior_self_subset_interior (mem_interior_iff_mem_nhds.2 hs₀) hys hxy
theorem gauge_lt_one_iff_mem_interior (hc : Convex ℝ s) (hs₀ : s ∈ 𝓝 0) :
gauge s x < 1 ↔ x ∈ interior s :=
Set.ext_iff.1 (gauge_lt_one_eq_interior hc hs₀) _
theorem gauge_le_one_iff_mem_closure (hc : Convex ℝ s) (hs₀ : s ∈ 𝓝 0) :
gauge s x ≤ 1 ↔ x ∈ closure s :=
⟨mem_closure_of_gauge_le_one hc (mem_of_mem_nhds hs₀) (absorbent_nhds_zero hs₀), fun h ↦
le_on_closure (fun _ ↦ gauge_le_one_of_mem) (continuous_gauge hc hs₀).continuousOn
continuousOn_const h⟩
theorem gauge_eq_one_iff_mem_frontier (hc : Convex ℝ s) (hs₀ : s ∈ 𝓝 0) :
gauge s x = 1 ↔ x ∈ frontier s := by
rw [eq_iff_le_not_lt, gauge_le_one_iff_mem_closure hc hs₀, gauge_lt_one_iff_mem_interior hc hs₀]
rfl
end TopologicalVectorSpace
section RCLike
variable [RCLike 𝕜] [Module 𝕜 E] [IsScalarTower ℝ 𝕜 E]
/-- `gauge s` as a seminorm when `s` is balanced, convex and absorbent. -/
@[simps!]
def gaugeSeminorm (hs₀ : Balanced 𝕜 s) (hs₁ : Convex ℝ s) (hs₂ : Absorbent ℝ s) : Seminorm 𝕜 E :=
Seminorm.of (gauge s) (gauge_add_le hs₁ hs₂) (gauge_smul hs₀)
#align gauge_seminorm gaugeSeminorm
variable {hs₀ : Balanced 𝕜 s} {hs₁ : Convex ℝ s} {hs₂ : Absorbent ℝ s} [TopologicalSpace E]
[ContinuousSMul ℝ E]
theorem gaugeSeminorm_lt_one_of_isOpen (hs : IsOpen s) {x : E} (hx : x ∈ s) :
gaugeSeminorm hs₀ hs₁ hs₂ x < 1 :=
gauge_lt_one_of_mem_of_isOpen hs hx
#align gauge_seminorm_lt_one_of_open gaugeSeminorm_lt_one_of_isOpen
| Mathlib/Analysis/Convex/Gauge.lean | 525 | 527 | theorem gaugeSeminorm_ball_one (hs : IsOpen s) : (gaugeSeminorm hs₀ hs₁ hs₂).ball 0 1 = s := by |
rw [Seminorm.ball_zero_eq]
exact gauge_lt_one_eq_self_of_isOpen hs₁ hs₂.zero_mem hs
|
/-
Copyright (c) 2022 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.NumberTheory.BernoulliPolynomials
import Mathlib.MeasureTheory.Integral.IntervalIntegral
import Mathlib.Analysis.Calculus.Deriv.Polynomial
import Mathlib.Analysis.Fourier.AddCircle
import Mathlib.Analysis.PSeries
#align_import number_theory.zeta_values from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Critical values of the Riemann zeta function
In this file we prove formulae for the critical values of `ζ(s)`, and more generally of Hurwitz
zeta functions, in terms of Bernoulli polynomials.
## Main results:
* `hasSum_zeta_nat`: the final formula for zeta values,
$$\zeta(2k) = \frac{(-1)^{(k + 1)} 2 ^ {2k - 1} \pi^{2k} B_{2 k}}{(2 k)!}.$$
* `hasSum_zeta_two` and `hasSum_zeta_four`: special cases given explicitly.
* `hasSum_one_div_nat_pow_mul_cos`: a formula for the sum `∑ (n : ℕ), cos (2 π i n x) / n ^ k` as
an explicit multiple of `Bₖ(x)`, for any `x ∈ [0, 1]` and `k ≥ 2` even.
* `hasSum_one_div_nat_pow_mul_sin`: a formula for the sum `∑ (n : ℕ), sin (2 π i n x) / n ^ k` as
an explicit multiple of `Bₖ(x)`, for any `x ∈ [0, 1]` and `k ≥ 3` odd.
-/
noncomputable section
open scoped Nat Real Interval
open Complex MeasureTheory Set intervalIntegral
local notation "𝕌" => UnitAddCircle
section BernoulliFunProps
/-! Simple properties of the Bernoulli polynomial, as a function `ℝ → ℝ`. -/
/-- The function `x ↦ Bₖ(x) : ℝ → ℝ`. -/
def bernoulliFun (k : ℕ) (x : ℝ) : ℝ :=
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli k)).eval x
#align bernoulli_fun bernoulliFun
theorem bernoulliFun_eval_zero (k : ℕ) : bernoulliFun k 0 = bernoulli k := by
rw [bernoulliFun, Polynomial.eval_zero_map, Polynomial.bernoulli_eval_zero, eq_ratCast]
#align bernoulli_fun_eval_zero bernoulliFun_eval_zero
theorem bernoulliFun_endpoints_eq_of_ne_one {k : ℕ} (hk : k ≠ 1) :
bernoulliFun k 1 = bernoulliFun k 0 := by
rw [bernoulliFun_eval_zero, bernoulliFun, Polynomial.eval_one_map, Polynomial.bernoulli_eval_one,
bernoulli_eq_bernoulli'_of_ne_one hk, eq_ratCast]
#align bernoulli_fun_endpoints_eq_of_ne_one bernoulliFun_endpoints_eq_of_ne_one
theorem bernoulliFun_eval_one (k : ℕ) : bernoulliFun k 1 = bernoulliFun k 0 + ite (k = 1) 1 0 := by
rw [bernoulliFun, bernoulliFun_eval_zero, Polynomial.eval_one_map, Polynomial.bernoulli_eval_one]
split_ifs with h
· rw [h, bernoulli_one, bernoulli'_one, eq_ratCast]
push_cast; ring
· rw [bernoulli_eq_bernoulli'_of_ne_one h, add_zero, eq_ratCast]
#align bernoulli_fun_eval_one bernoulliFun_eval_one
theorem hasDerivAt_bernoulliFun (k : ℕ) (x : ℝ) :
HasDerivAt (bernoulliFun k) (k * bernoulliFun (k - 1) x) x := by
convert ((Polynomial.bernoulli k).map <| algebraMap ℚ ℝ).hasDerivAt x using 1
simp only [bernoulliFun, Polynomial.derivative_map, Polynomial.derivative_bernoulli k,
Polynomial.map_mul, Polynomial.map_natCast, Polynomial.eval_mul, Polynomial.eval_natCast]
#align has_deriv_at_bernoulli_fun hasDerivAt_bernoulliFun
theorem antideriv_bernoulliFun (k : ℕ) (x : ℝ) :
HasDerivAt (fun x => bernoulliFun (k + 1) x / (k + 1)) (bernoulliFun k x) x := by
convert (hasDerivAt_bernoulliFun (k + 1) x).div_const _ using 1
field_simp [Nat.cast_add_one_ne_zero k]
#align antideriv_bernoulli_fun antideriv_bernoulliFun
theorem integral_bernoulliFun_eq_zero {k : ℕ} (hk : k ≠ 0) :
∫ x : ℝ in (0)..1, bernoulliFun k x = 0 := by
rw [integral_eq_sub_of_hasDerivAt (fun x _ => antideriv_bernoulliFun k x)
((Polynomial.continuous _).intervalIntegrable _ _)]
rw [bernoulliFun_eval_one]
split_ifs with h
· exfalso; exact hk (Nat.succ_inj'.mp h)
· simp
#align integral_bernoulli_fun_eq_zero integral_bernoulliFun_eq_zero
end BernoulliFunProps
section BernoulliFourierCoeffs
/-! Compute the Fourier coefficients of the Bernoulli functions via integration by parts. -/
/-- The `n`-th Fourier coefficient of the `k`-th Bernoulli function on the interval `[0, 1]`. -/
def bernoulliFourierCoeff (k : ℕ) (n : ℤ) : ℂ :=
fourierCoeffOn zero_lt_one (fun x => bernoulliFun k x) n
#align bernoulli_fourier_coeff bernoulliFourierCoeff
/-- Recurrence relation (in `k`) for the `n`-th Fourier coefficient of `Bₖ`. -/
theorem bernoulliFourierCoeff_recurrence (k : ℕ) {n : ℤ} (hn : n ≠ 0) :
bernoulliFourierCoeff k n =
1 / (-2 * π * I * n) * (ite (k = 1) 1 0 - k * bernoulliFourierCoeff (k - 1) n) := by
unfold bernoulliFourierCoeff
rw [fourierCoeffOn_of_hasDerivAt zero_lt_one hn
(fun x _ => (hasDerivAt_bernoulliFun k x).ofReal_comp)
((continuous_ofReal.comp <|
continuous_const.mul <| Polynomial.continuous _).intervalIntegrable
_ _)]
simp_rw [ofReal_one, ofReal_zero, sub_zero, one_mul]
rw [QuotientAddGroup.mk_zero, fourier_eval_zero, one_mul, ← ofReal_sub, bernoulliFun_eval_one,
add_sub_cancel_left]
congr 2
· split_ifs <;> simp only [ofReal_one, ofReal_zero, one_mul]
· simp_rw [ofReal_mul, ofReal_natCast, fourierCoeffOn.const_mul]
#align bernoulli_fourier_coeff_recurrence bernoulliFourierCoeff_recurrence
/-- The Fourier coefficients of `B₀(x) = 1`. -/
theorem bernoulli_zero_fourier_coeff {n : ℤ} (hn : n ≠ 0) : bernoulliFourierCoeff 0 n = 0 := by
simpa using bernoulliFourierCoeff_recurrence 0 hn
#align bernoulli_zero_fourier_coeff bernoulli_zero_fourier_coeff
/-- The `0`-th Fourier coefficient of `Bₖ(x)`. -/
theorem bernoulliFourierCoeff_zero {k : ℕ} (hk : k ≠ 0) : bernoulliFourierCoeff k 0 = 0 := by
simp_rw [bernoulliFourierCoeff, fourierCoeffOn_eq_integral, neg_zero, fourier_zero, sub_zero,
div_one, one_smul, intervalIntegral.integral_ofReal, integral_bernoulliFun_eq_zero hk,
ofReal_zero]
#align bernoulli_fourier_coeff_zero bernoulliFourierCoeff_zero
theorem bernoulliFourierCoeff_eq {k : ℕ} (hk : k ≠ 0) (n : ℤ) :
bernoulliFourierCoeff k n = -k ! / (2 * π * I * n) ^ k := by
rcases eq_or_ne n 0 with (rfl | hn)
· rw [bernoulliFourierCoeff_zero hk, Int.cast_zero, mul_zero, zero_pow hk,
div_zero]
refine Nat.le_induction ?_ (fun k hk h'k => ?_) k (Nat.one_le_iff_ne_zero.mpr hk)
· rw [bernoulliFourierCoeff_recurrence 1 hn]
simp only [Nat.cast_one, tsub_self, neg_mul, one_mul, eq_self_iff_true, if_true,
Nat.factorial_one, pow_one, inv_I, mul_neg]
rw [bernoulli_zero_fourier_coeff hn, sub_zero, mul_one, div_neg, neg_div]
· rw [bernoulliFourierCoeff_recurrence (k + 1) hn, Nat.add_sub_cancel k 1]
split_ifs with h
· exfalso; exact (ne_of_gt (Nat.lt_succ_iff.mpr hk)) h
· rw [h'k, Nat.factorial_succ, zero_sub, Nat.cast_mul, pow_add, pow_one, neg_div, mul_neg,
mul_neg, mul_neg, neg_neg, neg_mul, neg_mul, neg_mul, div_neg]
field_simp [Int.cast_ne_zero.mpr hn, I_ne_zero]
ring_nf
#align bernoulli_fourier_coeff_eq bernoulliFourierCoeff_eq
end BernoulliFourierCoeffs
section BernoulliPeriodized
/-! In this section we use the above evaluations of the Fourier coefficients of Bernoulli
polynomials, together with the theorem `has_pointwise_sum_fourier_series_of_summable` from Fourier
theory, to obtain an explicit formula for `∑ (n:ℤ), 1 / n ^ k * fourier n x`. -/
/-- The Bernoulli polynomial, extended from `[0, 1)` to the unit circle. -/
def periodizedBernoulli (k : ℕ) : 𝕌 → ℝ :=
AddCircle.liftIco 1 0 (bernoulliFun k)
#align periodized_bernoulli periodizedBernoulli
theorem periodizedBernoulli.continuous {k : ℕ} (hk : k ≠ 1) : Continuous (periodizedBernoulli k) :=
AddCircle.liftIco_zero_continuous
(mod_cast (bernoulliFun_endpoints_eq_of_ne_one hk).symm)
(Polynomial.continuous _).continuousOn
#align periodized_bernoulli.continuous periodizedBernoulli.continuous
theorem fourierCoeff_bernoulli_eq {k : ℕ} (hk : k ≠ 0) (n : ℤ) :
fourierCoeff ((↑) ∘ periodizedBernoulli k : 𝕌 → ℂ) n = -k ! / (2 * π * I * n) ^ k := by
have : ((↑) ∘ periodizedBernoulli k : 𝕌 → ℂ) = AddCircle.liftIco 1 0 ((↑) ∘ bernoulliFun k) := by
ext1 x; rfl
rw [this, fourierCoeff_liftIco_eq]
simpa only [zero_add] using bernoulliFourierCoeff_eq hk n
#align fourier_coeff_bernoulli_eq fourierCoeff_bernoulli_eq
theorem summable_bernoulli_fourier {k : ℕ} (hk : 2 ≤ k) :
Summable (fun n => -k ! / (2 * π * I * n) ^ k : ℤ → ℂ) := by
have :
∀ n : ℤ, -(k ! : ℂ) / (2 * π * I * n) ^ k = -k ! / (2 * π * I) ^ k * (1 / (n : ℂ) ^ k) := by
intro n; rw [mul_one_div, div_div, ← mul_pow]
simp_rw [this]
refine Summable.mul_left _ <| .of_norm ?_
have : (fun x : ℤ => ‖1 / (x : ℂ) ^ k‖) = fun x : ℤ => |1 / (x : ℝ) ^ k| := by
ext1 x
rw [norm_eq_abs, ← Complex.abs_ofReal]
congr 1
norm_cast
simp_rw [this]
rwa [summable_abs_iff, Real.summable_one_div_int_pow]
#align summable_bernoulli_fourier summable_bernoulli_fourier
theorem hasSum_one_div_pow_mul_fourier_mul_bernoulliFun {k : ℕ} (hk : 2 ≤ k) {x : ℝ}
(hx : x ∈ Icc (0 : ℝ) 1) :
HasSum (fun n : ℤ => 1 / (n : ℂ) ^ k * fourier n (x : 𝕌))
(-(2 * π * I) ^ k / k ! * bernoulliFun k x) := by
-- first show it suffices to prove result for `Ico 0 1`
suffices ∀ {y : ℝ}, y ∈ Ico (0 : ℝ) 1 →
HasSum (fun (n : ℤ) ↦ 1 / (n : ℂ) ^ k * fourier n y)
(-(2 * (π : ℂ) * I) ^ k / k ! * bernoulliFun k y) by
rw [← Ico_insert_right (zero_le_one' ℝ), mem_insert_iff, or_comm] at hx
rcases hx with (hx | rfl)
· exact this hx
· convert this (left_mem_Ico.mpr zero_lt_one) using 1
· rw [AddCircle.coe_period, QuotientAddGroup.mk_zero]
· rw [bernoulliFun_endpoints_eq_of_ne_one (by omega : k ≠ 1)]
intro y hy
let B : C(𝕌, ℂ) :=
ContinuousMap.mk ((↑) ∘ periodizedBernoulli k)
(continuous_ofReal.comp (periodizedBernoulli.continuous (by omega)))
have step1 : ∀ n : ℤ, fourierCoeff B n = -k ! / (2 * π * I * n) ^ k := by
rw [ContinuousMap.coe_mk]; exact fourierCoeff_bernoulli_eq (by omega : k ≠ 0)
have step2 :=
has_pointwise_sum_fourier_series_of_summable
((summable_bernoulli_fourier hk).congr fun n => (step1 n).symm) y
simp_rw [step1] at step2
convert step2.mul_left (-(2 * ↑π * I) ^ k / (k ! : ℂ)) using 2 with n
· rw [smul_eq_mul, ← mul_assoc, mul_div, mul_neg, div_mul_cancel₀, neg_neg, mul_pow _ (n : ℂ),
← div_div, div_self]
· rw [Ne, pow_eq_zero_iff', not_and_or]
exact Or.inl two_pi_I_ne_zero
· exact Nat.cast_ne_zero.mpr (Nat.factorial_ne_zero _)
· rw [ContinuousMap.coe_mk, Function.comp_apply, ofReal_inj, periodizedBernoulli,
AddCircle.liftIco_coe_apply (show y ∈ Ico 0 (0 + 1) by rwa [zero_add])]
#align has_sum_one_div_pow_mul_fourier_mul_bernoulli_fun hasSum_one_div_pow_mul_fourier_mul_bernoulliFun
end BernoulliPeriodized
section Cleanup
-- This section is just reformulating the results in a nicer form.
theorem hasSum_one_div_nat_pow_mul_fourier {k : ℕ} (hk : 2 ≤ k) {x : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) :
HasSum
(fun n : ℕ =>
(1 : ℂ) / (n : ℂ) ^ k * (fourier n (x : 𝕌) + (-1 : ℂ) ^ k * fourier (-n) (x : 𝕌)))
(-(2 * π * I) ^ k / k ! * bernoulliFun k x) := by
convert (hasSum_one_div_pow_mul_fourier_mul_bernoulliFun hk hx).nat_add_neg using 1
· ext1 n
rw [Int.cast_neg, mul_add, ← mul_assoc]
conv_rhs => rw [neg_eq_neg_one_mul, mul_pow, ← div_div]
congr 2
rw [div_mul_eq_mul_div₀, one_mul]
congr 1
rw [eq_div_iff, ← mul_pow, ← neg_eq_neg_one_mul, neg_neg, one_pow]
apply pow_ne_zero; rw [neg_ne_zero]; exact one_ne_zero
· rw [Int.cast_zero, zero_pow (by positivity : k ≠ 0), div_zero, zero_mul, add_zero]
#align has_sum_one_div_nat_pow_mul_fourier hasSum_one_div_nat_pow_mul_fourier
theorem hasSum_one_div_nat_pow_mul_cos {k : ℕ} (hk : k ≠ 0) {x : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) :
HasSum (fun n : ℕ => 1 / (n : ℝ) ^ (2 * k) * Real.cos (2 * π * n * x))
((-1 : ℝ) ^ (k + 1) * (2 * π) ^ (2 * k) / 2 / (2 * k)! *
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli (2 * k))).eval x) := by
have :
HasSum (fun n : ℕ => 1 / (n : ℂ) ^ (2 * k) * (fourier n (x : 𝕌) + fourier (-n) (x : 𝕌)))
((-1 : ℂ) ^ (k + 1) * (2 * (π : ℂ)) ^ (2 * k) / (2 * k)! * bernoulliFun (2 * k) x) := by
convert
hasSum_one_div_nat_pow_mul_fourier (by omega : 2 ≤ 2 * k)
hx using 3
· rw [pow_mul (-1 : ℂ), neg_one_sq, one_pow, one_mul]
· rw [pow_add, pow_one]
conv_rhs =>
rw [mul_pow]
congr
congr
· skip
· rw [pow_mul, I_sq]
ring
have ofReal_two : ((2 : ℝ) : ℂ) = 2 := by norm_cast
convert ((hasSum_iff _ _).mp (this.div_const 2)).1 with n
· convert (ofReal_re _).symm
rw [ofReal_mul]; rw [← mul_div]; congr
· rw [ofReal_div, ofReal_one, ofReal_pow]; rfl
· rw [ofReal_cos, ofReal_mul, fourier_coe_apply, fourier_coe_apply, cos, ofReal_one, div_one,
div_one, ofReal_mul, ofReal_mul, ofReal_two, Int.cast_neg, Int.cast_natCast,
ofReal_natCast]
congr 3
· ring
· ring
· convert (ofReal_re _).symm
rw [ofReal_mul, ofReal_div, ofReal_div, ofReal_mul, ofReal_pow, ofReal_pow, ofReal_neg,
ofReal_natCast, ofReal_mul, ofReal_two, ofReal_one]
rw [bernoulliFun]
ring
#align has_sum_one_div_nat_pow_mul_cos hasSum_one_div_nat_pow_mul_cos
theorem hasSum_one_div_nat_pow_mul_sin {k : ℕ} (hk : k ≠ 0) {x : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) :
HasSum (fun n : ℕ => 1 / (n : ℝ) ^ (2 * k + 1) * Real.sin (2 * π * n * x))
((-1 : ℝ) ^ (k + 1) * (2 * π) ^ (2 * k + 1) / 2 / (2 * k + 1)! *
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli (2 * k + 1))).eval x) := by
have :
HasSum (fun n : ℕ => 1 / (n : ℂ) ^ (2 * k + 1) * (fourier n (x : 𝕌) - fourier (-n) (x : 𝕌)))
((-1 : ℂ) ^ (k + 1) * I * (2 * π : ℂ) ^ (2 * k + 1) / (2 * k + 1)! *
bernoulliFun (2 * k + 1) x) := by
convert
hasSum_one_div_nat_pow_mul_fourier
(by omega : 2 ≤ 2 * k + 1) hx using 1
· ext1 n
rw [pow_add (-1 : ℂ), pow_mul (-1 : ℂ), neg_one_sq, one_pow, one_mul, pow_one, ←
neg_eq_neg_one_mul, ← sub_eq_add_neg]
· congr
rw [pow_add, pow_one]
conv_rhs =>
rw [mul_pow]
congr
congr
· skip
· rw [pow_add, pow_one, pow_mul, I_sq]
ring
have ofReal_two : ((2 : ℝ) : ℂ) = 2 := by norm_cast
convert ((hasSum_iff _ _).mp (this.div_const (2 * I))).1
· convert (ofReal_re _).symm
rw [ofReal_mul]; rw [← mul_div]; congr
· rw [ofReal_div, ofReal_one, ofReal_pow]; rfl
· rw [ofReal_sin, ofReal_mul, fourier_coe_apply, fourier_coe_apply, sin, ofReal_one, div_one,
div_one, ofReal_mul, ofReal_mul, ofReal_two, Int.cast_neg, Int.cast_natCast,
ofReal_natCast, ← div_div, div_I, div_mul_eq_mul_div₀, ← neg_div, ← neg_mul, neg_sub]
congr 4
· ring
· ring
· convert (ofReal_re _).symm
rw [ofReal_mul, ofReal_div, ofReal_div, ofReal_mul, ofReal_pow, ofReal_pow, ofReal_neg,
ofReal_natCast, ofReal_mul, ofReal_two, ofReal_one, ← div_div, div_I,
div_mul_eq_mul_div₀]
have : ∀ α β γ δ : ℂ, α * I * β / γ * δ * I = I ^ 2 * α * β / γ * δ := by intros; ring
rw [this, I_sq]
rw [bernoulliFun]
ring
#align has_sum_one_div_nat_pow_mul_sin hasSum_one_div_nat_pow_mul_sin
theorem hasSum_zeta_nat {k : ℕ} (hk : k ≠ 0) :
HasSum (fun n : ℕ => 1 / (n : ℝ) ^ (2 * k))
((-1 : ℝ) ^ (k + 1) * (2 : ℝ) ^ (2 * k - 1) * π ^ (2 * k) *
bernoulli (2 * k) / (2 * k)!) := by
convert hasSum_one_div_nat_pow_mul_cos hk (left_mem_Icc.mpr zero_le_one) using 1
· ext1 n; rw [mul_zero, Real.cos_zero, mul_one]
rw [Polynomial.eval_zero_map, Polynomial.bernoulli_eval_zero, eq_ratCast]
have : (2 : ℝ) ^ (2 * k - 1) = (2 : ℝ) ^ (2 * k) / 2 := by
rw [eq_div_iff (two_ne_zero' ℝ)]
conv_lhs =>
congr
· skip
· rw [← pow_one (2 : ℝ)]
rw [← pow_add, Nat.sub_add_cancel]
omega
rw [this, mul_pow]
ring
#align has_sum_zeta_nat hasSum_zeta_nat
end Cleanup
section Examples
theorem hasSum_zeta_two : HasSum (fun n : ℕ => (1 : ℝ) / (n : ℝ) ^ 2) (π ^ 2 / 6) := by
convert hasSum_zeta_nat one_ne_zero using 1; rw [mul_one]
rw [bernoulli_eq_bernoulli'_of_ne_one (by decide : 2 ≠ 1), bernoulli'_two]
norm_num [Nat.factorial]; field_simp; ring
#align has_sum_zeta_two hasSum_zeta_two
theorem hasSum_zeta_four : HasSum (fun n : ℕ => (1 : ℝ) / (n : ℝ) ^ 4) (π ^ 4 / 90) := by
convert hasSum_zeta_nat two_ne_zero using 1; norm_num
rw [bernoulli_eq_bernoulli'_of_ne_one, bernoulli'_four]
· norm_num [Nat.factorial]; field_simp; ring
· decide
#align has_sum_zeta_four hasSum_zeta_four
| Mathlib/NumberTheory/ZetaValues.lean | 368 | 376 | theorem Polynomial.bernoulli_three_eval_one_quarter :
(Polynomial.bernoulli 3).eval (1 / 4) = 3 / 64 := by |
simp_rw [Polynomial.bernoulli, Finset.sum_range_succ, Polynomial.eval_add,
Polynomial.eval_monomial]
rw [Finset.sum_range_zero, Polynomial.eval_zero, zero_add, bernoulli_one]
rw [bernoulli_eq_bernoulli'_of_ne_one zero_ne_one, bernoulli'_zero,
bernoulli_eq_bernoulli'_of_ne_one (by decide : 2 ≠ 1), bernoulli'_two,
bernoulli_eq_bernoulli'_of_ne_one (by decide : 3 ≠ 1), bernoulli'_three]
norm_num
|
/-
Copyright (c) 2021 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Algebra.Group.Subgroup.Actions
import Mathlib.Algebra.Order.Module.Algebra
import Mathlib.LinearAlgebra.LinearIndependent
import Mathlib.Algebra.Ring.Subring.Units
#align_import linear_algebra.ray from "leanprover-community/mathlib"@"0f6670b8af2dff699de1c0b4b49039b31bc13c46"
/-!
# Rays in modules
This file defines rays in modules.
## Main definitions
* `SameRay`: two vectors belong to the same ray if they are proportional with a nonnegative
coefficient.
* `Module.Ray` is a type for the equivalence class of nonzero vectors in a module with some
common positive multiple.
-/
noncomputable section
section StrictOrderedCommSemiring
variable (R : Type*) [StrictOrderedCommSemiring R]
variable {M : Type*} [AddCommMonoid M] [Module R M]
variable {N : Type*} [AddCommMonoid N] [Module R N]
variable (ι : Type*) [DecidableEq ι]
/-- Two vectors are in the same ray if either one of them is zero or some positive multiples of them
are equal (in the typical case over a field, this means one of them is a nonnegative multiple of
the other). -/
def SameRay (v₁ v₂ : M) : Prop :=
v₁ = 0 ∨ v₂ = 0 ∨ ∃ r₁ r₂ : R, 0 < r₁ ∧ 0 < r₂ ∧ r₁ • v₁ = r₂ • v₂
#align same_ray SameRay
variable {R}
namespace SameRay
variable {x y z : M}
@[simp]
theorem zero_left (y : M) : SameRay R 0 y :=
Or.inl rfl
#align same_ray.zero_left SameRay.zero_left
@[simp]
theorem zero_right (x : M) : SameRay R x 0 :=
Or.inr <| Or.inl rfl
#align same_ray.zero_right SameRay.zero_right
@[nontriviality]
theorem of_subsingleton [Subsingleton M] (x y : M) : SameRay R x y := by
rw [Subsingleton.elim x 0]
exact zero_left _
#align same_ray.of_subsingleton SameRay.of_subsingleton
@[nontriviality]
theorem of_subsingleton' [Subsingleton R] (x y : M) : SameRay R x y :=
haveI := Module.subsingleton R M
of_subsingleton x y
#align same_ray.of_subsingleton' SameRay.of_subsingleton'
/-- `SameRay` is reflexive. -/
@[refl]
theorem refl (x : M) : SameRay R x x := by
nontriviality R
exact Or.inr (Or.inr <| ⟨1, 1, zero_lt_one, zero_lt_one, rfl⟩)
#align same_ray.refl SameRay.refl
protected theorem rfl : SameRay R x x :=
refl _
#align same_ray.rfl SameRay.rfl
/-- `SameRay` is symmetric. -/
@[symm]
theorem symm (h : SameRay R x y) : SameRay R y x :=
(or_left_comm.1 h).imp_right <| Or.imp_right fun ⟨r₁, r₂, h₁, h₂, h⟩ => ⟨r₂, r₁, h₂, h₁, h.symm⟩
#align same_ray.symm SameRay.symm
/-- If `x` and `y` are nonzero vectors on the same ray, then there exist positive numbers `r₁ r₂`
such that `r₁ • x = r₂ • y`. -/
theorem exists_pos (h : SameRay R x y) (hx : x ≠ 0) (hy : y ≠ 0) :
∃ r₁ r₂ : R, 0 < r₁ ∧ 0 < r₂ ∧ r₁ • x = r₂ • y :=
(h.resolve_left hx).resolve_left hy
#align same_ray.exists_pos SameRay.exists_pos
theorem sameRay_comm : SameRay R x y ↔ SameRay R y x :=
⟨SameRay.symm, SameRay.symm⟩
#align same_ray_comm SameRay.sameRay_comm
/-- `SameRay` is transitive unless the vector in the middle is zero and both other vectors are
nonzero. -/
theorem trans (hxy : SameRay R x y) (hyz : SameRay R y z) (hy : y = 0 → x = 0 ∨ z = 0) :
SameRay R x z := by
rcases eq_or_ne x 0 with (rfl | hx); · exact zero_left z
rcases eq_or_ne z 0 with (rfl | hz); · exact zero_right x
rcases eq_or_ne y 0 with (rfl | hy);
· exact (hy rfl).elim (fun h => (hx h).elim) fun h => (hz h).elim
rcases hxy.exists_pos hx hy with ⟨r₁, r₂, hr₁, hr₂, h₁⟩
rcases hyz.exists_pos hy hz with ⟨r₃, r₄, hr₃, hr₄, h₂⟩
refine Or.inr (Or.inr <| ⟨r₃ * r₁, r₂ * r₄, mul_pos hr₃ hr₁, mul_pos hr₂ hr₄, ?_⟩)
rw [mul_smul, mul_smul, h₁, ← h₂, smul_comm]
#align same_ray.trans SameRay.trans
variable {S : Type*} [OrderedCommSemiring S] [Algebra S R] [Module S M] [SMulPosMono S R]
[IsScalarTower S R M] {a : S}
/-- A vector is in the same ray as a nonnegative multiple of itself. -/
lemma sameRay_nonneg_smul_right (v : M) (h : 0 ≤ a) : SameRay R v (a • v) := by
obtain h | h := (algebraMap_nonneg R h).eq_or_gt
· rw [← algebraMap_smul R a v, h, zero_smul]
exact zero_right _
· refine Or.inr $ Or.inr ⟨algebraMap S R a, 1, h, by nontriviality R; exact zero_lt_one, ?_⟩
rw [algebraMap_smul, one_smul]
#align same_ray_nonneg_smul_right SameRay.sameRay_nonneg_smul_right
/-- A nonnegative multiple of a vector is in the same ray as that vector. -/
lemma sameRay_nonneg_smul_left (v : M) (ha : 0 ≤ a) : SameRay R (a • v) v :=
(sameRay_nonneg_smul_right v ha).symm
#align same_ray_nonneg_smul_left SameRay.sameRay_nonneg_smul_left
/-- A vector is in the same ray as a positive multiple of itself. -/
lemma sameRay_pos_smul_right (v : M) (ha : 0 < a) : SameRay R v (a • v) :=
sameRay_nonneg_smul_right v ha.le
#align same_ray_pos_smul_right SameRay.sameRay_pos_smul_right
/-- A positive multiple of a vector is in the same ray as that vector. -/
lemma sameRay_pos_smul_left (v : M) (ha : 0 < a) : SameRay R (a • v) v :=
sameRay_nonneg_smul_left v ha.le
#align same_ray_pos_smul_left SameRay.sameRay_pos_smul_left
/-- A vector is in the same ray as a nonnegative multiple of one it is in the same ray as. -/
lemma nonneg_smul_right (h : SameRay R x y) (ha : 0 ≤ a) : SameRay R x (a • y) :=
h.trans (sameRay_nonneg_smul_right y ha) fun hy => Or.inr <| by rw [hy, smul_zero]
#align same_ray.nonneg_smul_right SameRay.nonneg_smul_right
/-- A nonnegative multiple of a vector is in the same ray as one it is in the same ray as. -/
lemma nonneg_smul_left (h : SameRay R x y) (ha : 0 ≤ a) : SameRay R (a • x) y :=
(h.symm.nonneg_smul_right ha).symm
#align same_ray.nonneg_smul_left SameRay.nonneg_smul_left
/-- A vector is in the same ray as a positive multiple of one it is in the same ray as. -/
theorem pos_smul_right (h : SameRay R x y) (ha : 0 < a) : SameRay R x (a • y) :=
h.nonneg_smul_right ha.le
#align same_ray.pos_smul_right SameRay.pos_smul_right
/-- A positive multiple of a vector is in the same ray as one it is in the same ray as. -/
theorem pos_smul_left (h : SameRay R x y) (hr : 0 < a) : SameRay R (a • x) y :=
h.nonneg_smul_left hr.le
#align same_ray.pos_smul_left SameRay.pos_smul_left
/-- If two vectors are on the same ray then they remain so after applying a linear map. -/
theorem map (f : M →ₗ[R] N) (h : SameRay R x y) : SameRay R (f x) (f y) :=
(h.imp fun hx => by rw [hx, map_zero]) <|
Or.imp (fun hy => by rw [hy, map_zero]) fun ⟨r₁, r₂, hr₁, hr₂, h⟩ =>
⟨r₁, r₂, hr₁, hr₂, by rw [← f.map_smul, ← f.map_smul, h]⟩
#align same_ray.map SameRay.map
/-- The images of two vectors under an injective linear map are on the same ray if and only if the
original vectors are on the same ray. -/
theorem _root_.Function.Injective.sameRay_map_iff
{F : Type*} [FunLike F M N] [LinearMapClass F R M N]
{f : F} (hf : Function.Injective f) :
SameRay R (f x) (f y) ↔ SameRay R x y := by
simp only [SameRay, map_zero, ← hf.eq_iff, map_smul]
#align function.injective.same_ray_map_iff Function.Injective.sameRay_map_iff
/-- The images of two vectors under a linear equivalence are on the same ray if and only if the
original vectors are on the same ray. -/
@[simp]
theorem sameRay_map_iff (e : M ≃ₗ[R] N) : SameRay R (e x) (e y) ↔ SameRay R x y :=
Function.Injective.sameRay_map_iff (EquivLike.injective e)
#align same_ray_map_iff SameRay.sameRay_map_iff
/-- If two vectors are on the same ray then both scaled by the same action are also on the same
ray. -/
theorem smul {S : Type*} [Monoid S] [DistribMulAction S M] [SMulCommClass R S M]
(h : SameRay R x y) (s : S) : SameRay R (s • x) (s • y) :=
h.map (s • (LinearMap.id : M →ₗ[R] M))
#align same_ray.smul SameRay.smul
/-- If `x` and `y` are on the same ray as `z`, then so is `x + y`. -/
theorem add_left (hx : SameRay R x z) (hy : SameRay R y z) : SameRay R (x + y) z := by
rcases eq_or_ne x 0 with (rfl | hx₀); · rwa [zero_add]
rcases eq_or_ne y 0 with (rfl | hy₀); · rwa [add_zero]
rcases eq_or_ne z 0 with (rfl | hz₀); · apply zero_right
rcases hx.exists_pos hx₀ hz₀ with ⟨rx, rz₁, hrx, hrz₁, Hx⟩
rcases hy.exists_pos hy₀ hz₀ with ⟨ry, rz₂, hry, hrz₂, Hy⟩
refine Or.inr (Or.inr ⟨rx * ry, ry * rz₁ + rx * rz₂, mul_pos hrx hry, ?_, ?_⟩)
· apply_rules [add_pos, mul_pos]
· simp only [mul_smul, smul_add, add_smul, ← Hx, ← Hy]
rw [smul_comm]
#align same_ray.add_left SameRay.add_left
/-- If `y` and `z` are on the same ray as `x`, then so is `y + z`. -/
theorem add_right (hy : SameRay R x y) (hz : SameRay R x z) : SameRay R x (y + z) :=
(hy.symm.add_left hz.symm).symm
#align same_ray.add_right SameRay.add_right
end SameRay
-- Porting note(#5171): removed has_nonempty_instance nolint, no such linter
set_option linter.unusedVariables false in
/-- Nonzero vectors, as used to define rays. This type depends on an unused argument `R` so that
`RayVector.Setoid` can be an instance. -/
@[nolint unusedArguments]
def RayVector (R M : Type*) [Zero M] :=
{ v : M // v ≠ 0 }
#align ray_vector RayVector
-- Porting note: Made Coe into CoeOut so it's not dangerous anymore
instance RayVector.coe [Zero M] : CoeOut (RayVector R M) M where
coe := Subtype.val
#align ray_vector.has_coe RayVector.coe
instance {R M : Type*} [Zero M] [Nontrivial M] : Nonempty (RayVector R M) :=
let ⟨x, hx⟩ := exists_ne (0 : M)
⟨⟨x, hx⟩⟩
variable (R M)
/-- The setoid of the `SameRay` relation for the subtype of nonzero vectors. -/
instance RayVector.Setoid : Setoid (RayVector R M) where
r x y := SameRay R (x : M) y
iseqv :=
⟨fun x => SameRay.refl _, fun h => h.symm, by
intros x y z hxy hyz
exact hxy.trans hyz fun hy => (y.2 hy).elim⟩
/-- A ray (equivalence class of nonzero vectors with common positive multiples) in a module. -/
-- Porting note(#5171): removed has_nonempty_instance nolint, no such linter
def Module.Ray :=
Quotient (RayVector.Setoid R M)
#align module.ray Module.Ray
variable {R M}
/-- Equivalence of nonzero vectors, in terms of `SameRay`. -/
theorem equiv_iff_sameRay {v₁ v₂ : RayVector R M} : v₁ ≈ v₂ ↔ SameRay R (v₁ : M) v₂ :=
Iff.rfl
#align equiv_iff_same_ray equiv_iff_sameRay
variable (R)
-- Porting note: Removed `protected` here, not in namespace
/-- The ray given by a nonzero vector. -/
def rayOfNeZero (v : M) (h : v ≠ 0) : Module.Ray R M :=
⟦⟨v, h⟩⟧
#align ray_of_ne_zero rayOfNeZero
/-- An induction principle for `Module.Ray`, used as `induction x using Module.Ray.ind`. -/
theorem Module.Ray.ind {C : Module.Ray R M → Prop} (h : ∀ (v) (hv : v ≠ 0), C (rayOfNeZero R v hv))
(x : Module.Ray R M) : C x :=
Quotient.ind (Subtype.rec <| h) x
#align module.ray.ind Module.Ray.ind
variable {R}
instance [Nontrivial M] : Nonempty (Module.Ray R M) :=
Nonempty.map Quotient.mk' inferInstance
/-- The rays given by two nonzero vectors are equal if and only if those vectors
satisfy `SameRay`. -/
theorem ray_eq_iff {v₁ v₂ : M} (hv₁ : v₁ ≠ 0) (hv₂ : v₂ ≠ 0) :
rayOfNeZero R _ hv₁ = rayOfNeZero R _ hv₂ ↔ SameRay R v₁ v₂ :=
Quotient.eq'
#align ray_eq_iff ray_eq_iff
/-- The ray given by a positive multiple of a nonzero vector. -/
@[simp]
theorem ray_pos_smul {v : M} (h : v ≠ 0) {r : R} (hr : 0 < r) (hrv : r • v ≠ 0) :
rayOfNeZero R (r • v) hrv = rayOfNeZero R v h :=
(ray_eq_iff _ _).2 <| SameRay.sameRay_pos_smul_left v hr
#align ray_pos_smul ray_pos_smul
/-- An equivalence between modules implies an equivalence between ray vectors. -/
def RayVector.mapLinearEquiv (e : M ≃ₗ[R] N) : RayVector R M ≃ RayVector R N :=
Equiv.subtypeEquiv e.toEquiv fun _ => e.map_ne_zero_iff.symm
#align ray_vector.map_linear_equiv RayVector.mapLinearEquiv
/-- An equivalence between modules implies an equivalence between rays. -/
def Module.Ray.map (e : M ≃ₗ[R] N) : Module.Ray R M ≃ Module.Ray R N :=
Quotient.congr (RayVector.mapLinearEquiv e) fun _ _=> (SameRay.sameRay_map_iff _).symm
#align module.ray.map Module.Ray.map
@[simp]
theorem Module.Ray.map_apply (e : M ≃ₗ[R] N) (v : M) (hv : v ≠ 0) :
Module.Ray.map e (rayOfNeZero _ v hv) = rayOfNeZero _ (e v) (e.map_ne_zero_iff.2 hv) :=
rfl
#align module.ray.map_apply Module.Ray.map_apply
@[simp]
theorem Module.Ray.map_refl : (Module.Ray.map <| LinearEquiv.refl R M) = Equiv.refl _ :=
Equiv.ext <| Module.Ray.ind R fun _ _ => rfl
#align module.ray.map_refl Module.Ray.map_refl
@[simp]
theorem Module.Ray.map_symm (e : M ≃ₗ[R] N) : (Module.Ray.map e).symm = Module.Ray.map e.symm :=
rfl
#align module.ray.map_symm Module.Ray.map_symm
section Action
variable {G : Type*} [Group G] [DistribMulAction G M]
/-- Any invertible action preserves the non-zeroness of ray vectors. This is primarily of interest
when `G = Rˣ` -/
instance {R : Type*} : MulAction G (RayVector R M) where
smul r := Subtype.map (r • ·) fun _ => (smul_ne_zero_iff_ne _).2
mul_smul a b _ := Subtype.ext <| mul_smul a b _
one_smul _ := Subtype.ext <| one_smul _ _
variable [SMulCommClass R G M]
/-- Any invertible action preserves the non-zeroness of rays. This is primarily of interest when
`G = Rˣ` -/
instance : MulAction G (Module.Ray R M) where
smul r := Quotient.map (r • ·) fun _ _ h => h.smul _
mul_smul a b := Quotient.ind fun _ => congr_arg Quotient.mk' <| mul_smul a b _
one_smul := Quotient.ind fun _ => congr_arg Quotient.mk' <| one_smul _ _
/-- The action via `LinearEquiv.apply_distribMulAction` corresponds to `Module.Ray.map`. -/
@[simp]
theorem Module.Ray.linearEquiv_smul_eq_map (e : M ≃ₗ[R] M) (v : Module.Ray R M) :
e • v = Module.Ray.map e v :=
rfl
#align module.ray.linear_equiv_smul_eq_map Module.Ray.linearEquiv_smul_eq_map
@[simp]
theorem smul_rayOfNeZero (g : G) (v : M) (hv) :
g • rayOfNeZero R v hv = rayOfNeZero R (g • v) ((smul_ne_zero_iff_ne _).2 hv) :=
rfl
#align smul_ray_of_ne_zero smul_rayOfNeZero
end Action
namespace Module.Ray
-- Porting note: `(u.1 : R)` was `(u : R)`, CoeHead from R to Rˣ does not seem to work.
/-- Scaling by a positive unit is a no-op. -/
theorem units_smul_of_pos (u : Rˣ) (hu : 0 < (u.1 : R)) (v : Module.Ray R M) : u • v = v := by
induction v using Module.Ray.ind
rw [smul_rayOfNeZero, ray_eq_iff]
exact SameRay.sameRay_pos_smul_left _ hu
#align module.ray.units_smul_of_pos Module.Ray.units_smul_of_pos
/-- An arbitrary `RayVector` giving a ray. -/
def someRayVector (x : Module.Ray R M) : RayVector R M :=
Quotient.out x
#align module.ray.some_ray_vector Module.Ray.someRayVector
/-- The ray of `someRayVector`. -/
@[simp]
theorem someRayVector_ray (x : Module.Ray R M) : (⟦x.someRayVector⟧ : Module.Ray R M) = x :=
Quotient.out_eq _
#align module.ray.some_ray_vector_ray Module.Ray.someRayVector_ray
/-- An arbitrary nonzero vector giving a ray. -/
def someVector (x : Module.Ray R M) : M :=
x.someRayVector
#align module.ray.some_vector Module.Ray.someVector
/-- `someVector` is nonzero. -/
@[simp]
theorem someVector_ne_zero (x : Module.Ray R M) : x.someVector ≠ 0 :=
x.someRayVector.property
#align module.ray.some_vector_ne_zero Module.Ray.someVector_ne_zero
/-- The ray of `someVector`. -/
@[simp]
theorem someVector_ray (x : Module.Ray R M) : rayOfNeZero R _ x.someVector_ne_zero = x :=
(congr_arg _ (Subtype.coe_eta _ _) : _).trans x.out_eq
#align module.ray.some_vector_ray Module.Ray.someVector_ray
end Module.Ray
end StrictOrderedCommSemiring
section StrictOrderedCommRing
variable {R : Type*} [StrictOrderedCommRing R]
variable {M N : Type*} [AddCommGroup M] [AddCommGroup N] [Module R M] [Module R N] {x y : M}
/-- `SameRay.neg` as an `iff`. -/
@[simp]
theorem sameRay_neg_iff : SameRay R (-x) (-y) ↔ SameRay R x y := by
simp only [SameRay, neg_eq_zero, smul_neg, neg_inj]
#align same_ray_neg_iff sameRay_neg_iff
alias ⟨SameRay.of_neg, SameRay.neg⟩ := sameRay_neg_iff
#align same_ray.of_neg SameRay.of_neg
#align same_ray.neg SameRay.neg
theorem sameRay_neg_swap : SameRay R (-x) y ↔ SameRay R x (-y) := by rw [← sameRay_neg_iff, neg_neg]
#align same_ray_neg_swap sameRay_neg_swap
theorem eq_zero_of_sameRay_neg_smul_right [NoZeroSMulDivisors R M] {r : R} (hr : r < 0)
(h : SameRay R x (r • x)) : x = 0 := by
rcases h with (rfl | h₀ | ⟨r₁, r₂, hr₁, hr₂, h⟩)
· rfl
· simpa [hr.ne] using h₀
· rw [← sub_eq_zero, smul_smul, ← sub_smul, smul_eq_zero] at h
refine h.resolve_left (ne_of_gt <| sub_pos.2 ?_)
exact (mul_neg_of_pos_of_neg hr₂ hr).trans hr₁
#align eq_zero_of_same_ray_neg_smul_right eq_zero_of_sameRay_neg_smul_right
/-- If a vector is in the same ray as its negation, that vector is zero. -/
theorem eq_zero_of_sameRay_self_neg [NoZeroSMulDivisors R M] (h : SameRay R x (-x)) : x = 0 := by
nontriviality M; haveI : Nontrivial R := Module.nontrivial R M
refine eq_zero_of_sameRay_neg_smul_right (neg_lt_zero.2 (zero_lt_one' R)) ?_
rwa [neg_one_smul]
#align eq_zero_of_same_ray_self_neg eq_zero_of_sameRay_self_neg
namespace RayVector
/-- Negating a nonzero vector. -/
instance {R : Type*} : Neg (RayVector R M) :=
⟨fun v => ⟨-v, neg_ne_zero.2 v.prop⟩⟩
/-- Negating a nonzero vector commutes with coercion to the underlying module. -/
@[simp, norm_cast]
theorem coe_neg {R : Type*} (v : RayVector R M) : ↑(-v) = -(v : M) :=
rfl
#align ray_vector.coe_neg RayVector.coe_neg
/-- Negating a nonzero vector twice produces the original vector. -/
instance {R : Type*} : InvolutiveNeg (RayVector R M) where
neg := Neg.neg
neg_neg v := by rw [Subtype.ext_iff, coe_neg, coe_neg, neg_neg]
/-- If two nonzero vectors are equivalent, so are their negations. -/
@[simp]
theorem equiv_neg_iff {v₁ v₂ : RayVector R M} : -v₁ ≈ -v₂ ↔ v₁ ≈ v₂ :=
sameRay_neg_iff
#align ray_vector.equiv_neg_iff RayVector.equiv_neg_iff
end RayVector
variable (R)
/-- Negating a ray. -/
instance : Neg (Module.Ray R M) :=
⟨Quotient.map (fun v => -v) fun _ _ => RayVector.equiv_neg_iff.2⟩
/-- The ray given by the negation of a nonzero vector. -/
@[simp]
theorem neg_rayOfNeZero (v : M) (h : v ≠ 0) :
-rayOfNeZero R _ h = rayOfNeZero R (-v) (neg_ne_zero.2 h) :=
rfl
#align neg_ray_of_ne_zero neg_rayOfNeZero
namespace Module.Ray
variable {R}
/-- Negating a ray twice produces the original ray. -/
instance : InvolutiveNeg (Module.Ray R M) where
neg := Neg.neg
neg_neg x := by apply ind R (by simp) x
-- Quotient.ind (fun a => congr_arg Quotient.mk' <| neg_neg _) x
/-- A ray does not equal its own negation. -/
theorem ne_neg_self [NoZeroSMulDivisors R M] (x : Module.Ray R M) : x ≠ -x := by
induction' x using Module.Ray.ind with x hx
rw [neg_rayOfNeZero, Ne, ray_eq_iff]
exact mt eq_zero_of_sameRay_self_neg hx
#align module.ray.ne_neg_self Module.Ray.ne_neg_self
theorem neg_units_smul (u : Rˣ) (v : Module.Ray R M) : -u • v = -(u • v) := by
induction v using Module.Ray.ind
simp only [smul_rayOfNeZero, Units.smul_def, Units.val_neg, neg_smul, neg_rayOfNeZero]
#align module.ray.neg_units_smul Module.Ray.neg_units_smul
-- Porting note: `(u.1 : R)` was `(u : R)`, CoeHead from R to Rˣ does not seem to work.
/-- Scaling by a negative unit is negation. -/
theorem units_smul_of_neg (u : Rˣ) (hu : u.1 < 0) (v : Module.Ray R M) : u • v = -v := by
rw [← neg_inj, neg_neg, ← neg_units_smul, units_smul_of_pos]
rwa [Units.val_neg, Right.neg_pos_iff]
#align module.ray.units_smul_of_neg Module.Ray.units_smul_of_neg
@[simp]
protected theorem map_neg (f : M ≃ₗ[R] N) (v : Module.Ray R M) : map f (-v) = -map f v := by
induction' v using Module.Ray.ind with g hg
simp
#align module.ray.map_neg Module.Ray.map_neg
end Module.Ray
end StrictOrderedCommRing
section LinearOrderedCommRing
variable {R : Type*} [LinearOrderedCommRing R]
variable {M : Type*} [AddCommGroup M] [Module R M]
-- Porting note: Needed to add coercion ↥ below
/-- `SameRay` follows from membership of `MulAction.orbit` for the `Units.posSubgroup`. -/
theorem sameRay_of_mem_orbit {v₁ v₂ : M} (h : v₁ ∈ MulAction.orbit ↥(Units.posSubgroup R) v₂) :
SameRay R v₁ v₂ := by
rcases h with ⟨⟨r, hr : 0 < r.1⟩, rfl : r • v₂ = v₁⟩
exact SameRay.sameRay_pos_smul_left _ hr
#align same_ray_of_mem_orbit sameRay_of_mem_orbit
/-- Scaling by an inverse unit is the same as scaling by itself. -/
@[simp]
theorem units_inv_smul (u : Rˣ) (v : Module.Ray R M) : u⁻¹ • v = u • v :=
have := mul_self_pos.2 u.ne_zero
calc
u⁻¹ • v = (u * u) • u⁻¹ • v := Eq.symm <| (u⁻¹ • v).units_smul_of_pos _ (by exact this)
_ = u • v := by rw [mul_smul, smul_inv_smul]
#align units_inv_smul units_inv_smul
section
variable [NoZeroSMulDivisors R M]
@[simp]
theorem sameRay_smul_right_iff {v : M} {r : R} : SameRay R v (r • v) ↔ 0 ≤ r ∨ v = 0 :=
⟨fun hrv => or_iff_not_imp_left.2 fun hr => eq_zero_of_sameRay_neg_smul_right (not_le.1 hr) hrv,
or_imp.2 ⟨SameRay.sameRay_nonneg_smul_right v, fun h => h.symm ▸ SameRay.zero_left _⟩⟩
#align same_ray_smul_right_iff sameRay_smul_right_iff
/-- A nonzero vector is in the same ray as a multiple of itself if and only if that multiple
is positive. -/
theorem sameRay_smul_right_iff_of_ne {v : M} (hv : v ≠ 0) {r : R} (hr : r ≠ 0) :
SameRay R v (r • v) ↔ 0 < r := by
simp only [sameRay_smul_right_iff, hv, or_false_iff, hr.symm.le_iff_lt]
#align same_ray_smul_right_iff_of_ne sameRay_smul_right_iff_of_ne
@[simp]
theorem sameRay_smul_left_iff {v : M} {r : R} : SameRay R (r • v) v ↔ 0 ≤ r ∨ v = 0 :=
SameRay.sameRay_comm.trans sameRay_smul_right_iff
#align same_ray_smul_left_iff sameRay_smul_left_iff
/-- A multiple of a nonzero vector is in the same ray as that vector if and only if that multiple
is positive. -/
theorem sameRay_smul_left_iff_of_ne {v : M} (hv : v ≠ 0) {r : R} (hr : r ≠ 0) :
SameRay R (r • v) v ↔ 0 < r :=
SameRay.sameRay_comm.trans (sameRay_smul_right_iff_of_ne hv hr)
#align same_ray_smul_left_iff_of_ne sameRay_smul_left_iff_of_ne
@[simp]
theorem sameRay_neg_smul_right_iff {v : M} {r : R} : SameRay R (-v) (r • v) ↔ r ≤ 0 ∨ v = 0 := by
rw [← sameRay_neg_iff, neg_neg, ← neg_smul, sameRay_smul_right_iff, neg_nonneg]
#align same_ray_neg_smul_right_iff sameRay_neg_smul_right_iff
theorem sameRay_neg_smul_right_iff_of_ne {v : M} {r : R} (hv : v ≠ 0) (hr : r ≠ 0) :
SameRay R (-v) (r • v) ↔ r < 0 := by
simp only [sameRay_neg_smul_right_iff, hv, or_false_iff, hr.le_iff_lt]
#align same_ray_neg_smul_right_iff_of_ne sameRay_neg_smul_right_iff_of_ne
@[simp]
theorem sameRay_neg_smul_left_iff {v : M} {r : R} : SameRay R (r • v) (-v) ↔ r ≤ 0 ∨ v = 0 :=
SameRay.sameRay_comm.trans sameRay_neg_smul_right_iff
#align same_ray_neg_smul_left_iff sameRay_neg_smul_left_iff
theorem sameRay_neg_smul_left_iff_of_ne {v : M} {r : R} (hv : v ≠ 0) (hr : r ≠ 0) :
SameRay R (r • v) (-v) ↔ r < 0 :=
SameRay.sameRay_comm.trans <| sameRay_neg_smul_right_iff_of_ne hv hr
#align same_ray_neg_smul_left_iff_of_ne sameRay_neg_smul_left_iff_of_ne
-- Porting note: `(u.1 : R)` was `(u : R)`, CoeHead from R to Rˣ does not seem to work.
@[simp]
theorem units_smul_eq_self_iff {u : Rˣ} {v : Module.Ray R M} : u • v = v ↔ 0 < u.1 := by
induction' v using Module.Ray.ind with v hv
simp only [smul_rayOfNeZero, ray_eq_iff, Units.smul_def, sameRay_smul_left_iff_of_ne hv u.ne_zero]
#align units_smul_eq_self_iff units_smul_eq_self_iff
@[simp]
theorem units_smul_eq_neg_iff {u : Rˣ} {v : Module.Ray R M} : u • v = -v ↔ u.1 < 0 := by
rw [← neg_inj, neg_neg, ← Module.Ray.neg_units_smul, units_smul_eq_self_iff, Units.val_neg,
neg_pos]
#align units_smul_eq_neg_iff units_smul_eq_neg_iff
/-- Two vectors are in the same ray, or the first is in the same ray as the negation of the
second, if and only if they are not linearly independent. -/
theorem sameRay_or_sameRay_neg_iff_not_linearIndependent {x y : M} :
SameRay R x y ∨ SameRay R x (-y) ↔ ¬LinearIndependent R ![x, y] := by
by_cases hx : x = 0; · simpa [hx] using fun h : LinearIndependent R ![0, y] => h.ne_zero 0 rfl
by_cases hy : y = 0; · simpa [hy] using fun h : LinearIndependent R ![x, 0] => h.ne_zero 1 rfl
simp_rw [Fintype.not_linearIndependent_iff]
refine ⟨fun h => ?_, fun h => ?_⟩
· rcases h with ((hx0 | hy0 | ⟨r₁, r₂, hr₁, _, h⟩) | (hx0 | hy0 | ⟨r₁, r₂, hr₁, _, h⟩))
· exact False.elim (hx hx0)
· exact False.elim (hy hy0)
· refine ⟨![r₁, -r₂], ?_⟩
rw [Fin.sum_univ_two, Fin.exists_fin_two]
simp [h, hr₁.ne.symm]
· exact False.elim (hx hx0)
· exact False.elim (hy (neg_eq_zero.1 hy0))
· refine ⟨![r₁, r₂], ?_⟩
rw [Fin.sum_univ_two, Fin.exists_fin_two]
simp [h, hr₁.ne.symm]
· rcases h with ⟨m, hm, hmne⟩
rw [Fin.sum_univ_two, add_eq_zero_iff_eq_neg, Matrix.cons_val_zero,
Matrix.cons_val_one, Matrix.head_cons] at hm
rcases lt_trichotomy (m 0) 0 with (hm0 | hm0 | hm0) <;>
rcases lt_trichotomy (m 1) 0 with (hm1 | hm1 | hm1)
· refine
Or.inr (Or.inr (Or.inr ⟨-m 0, -m 1, Left.neg_pos_iff.2 hm0, Left.neg_pos_iff.2 hm1, ?_⟩))
rw [neg_smul_neg, neg_smul, hm, neg_neg]
· exfalso
simp [hm1, hx, hm0.ne] at hm
· refine Or.inl (Or.inr (Or.inr ⟨-m 0, m 1, Left.neg_pos_iff.2 hm0, hm1, ?_⟩))
rw [neg_smul, hm, neg_neg]
· exfalso
simp [hm0, hy, hm1.ne] at hm
· rw [Fin.exists_fin_two] at hmne
exact False.elim (not_and_or.2 hmne ⟨hm0, hm1⟩)
· exfalso
simp [hm0, hy, hm1.ne.symm] at hm
· refine Or.inl (Or.inr (Or.inr ⟨m 0, -m 1, hm0, Left.neg_pos_iff.2 hm1, ?_⟩))
rwa [neg_smul]
· exfalso
simp [hm1, hx, hm0.ne.symm] at hm
· refine Or.inr (Or.inr (Or.inr ⟨m 0, m 1, hm0, hm1, ?_⟩))
rwa [smul_neg]
#align same_ray_or_same_ray_neg_iff_not_linear_independent sameRay_or_sameRay_neg_iff_not_linearIndependent
/-- Two vectors are in the same ray, or they are nonzero and the first is in the same ray as the
negation of the second, if and only if they are not linearly independent. -/
| Mathlib/LinearAlgebra/Ray.lean | 629 | 633 | theorem sameRay_or_ne_zero_and_sameRay_neg_iff_not_linearIndependent {x y : M} :
SameRay R x y ∨ x ≠ 0 ∧ y ≠ 0 ∧ SameRay R x (-y) ↔ ¬LinearIndependent R ![x, y] := by |
rw [← sameRay_or_sameRay_neg_iff_not_linearIndependent]
by_cases hx : x = 0; · simp [hx]
by_cases hy : y = 0 <;> simp [hx, hy]
|
/-
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]
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]
#align bernoulli'_four bernoulli'_four
end Examples
@[simp]
theorem sum_bernoulli' (n : ℕ) : (∑ k ∈ range n, (n.choose k : ℚ) * bernoulli' k) = n := by
cases' n with n
· simp
suffices
((n + 1 : ℚ) * ∑ k ∈ range n, ↑(n.choose k) / (n - k + 1) * bernoulli' k) =
∑ x ∈ range n, ↑(n.succ.choose x) * bernoulli' x by
rw_mod_cast [sum_range_succ, bernoulli'_def, ← this, choose_succ_self_right]
ring
simp_rw [mul_sum, ← mul_assoc]
refine sum_congr rfl fun k hk => ?_
congr
have : ((n - k : ℕ) : ℚ) + 1 ≠ 0 := by norm_cast
field_simp [← cast_sub (mem_range.1 hk).le, mul_comm]
rw_mod_cast [tsub_add_eq_add_tsub (mem_range.1 hk).le, choose_mul_succ_eq]
#align sum_bernoulli' sum_bernoulli'
/-- The exponential generating function for the Bernoulli numbers `bernoulli' n`. -/
def bernoulli'PowerSeries :=
mk fun n => algebraMap ℚ A (bernoulli' n / n !)
#align bernoulli'_power_series bernoulli'PowerSeries
theorem bernoulli'PowerSeries_mul_exp_sub_one :
bernoulli'PowerSeries A * (exp A - 1) = X * exp A := by
ext n
-- constant coefficient is a special case
cases' n with n
· simp
rw [bernoulli'PowerSeries, coeff_mul, mul_comm X, sum_antidiagonal_succ']
suffices (∑ p ∈ antidiagonal n,
bernoulli' p.1 / p.1! * ((p.2 + 1) * p.2! : ℚ)⁻¹) = (n ! : ℚ)⁻¹ by
simpa [map_sum, Nat.factorial] using congr_arg (algebraMap ℚ A) this
apply eq_inv_of_mul_eq_one_left
rw [sum_mul]
convert bernoulli'_spec' n using 1
apply sum_congr rfl
simp_rw [mem_antidiagonal]
rintro ⟨i, j⟩ rfl
have := factorial_mul_factorial_dvd_factorial_add i j
field_simp [mul_comm _ (bernoulli' i), mul_assoc, add_choose]
norm_cast
simp [mul_comm (j + 1)]
#align bernoulli'_power_series_mul_exp_sub_one bernoulli'PowerSeries_mul_exp_sub_one
/-- Odd Bernoulli numbers (greater than 1) are zero. -/
theorem bernoulli'_odd_eq_zero {n : ℕ} (h_odd : Odd n) (hlt : 1 < n) : bernoulli' n = 0 := by
let B := mk fun n => bernoulli' n / (n ! : ℚ)
suffices (B - evalNegHom B) * (exp ℚ - 1) = X * (exp ℚ - 1) by
cases' mul_eq_mul_right_iff.mp this with h h <;>
simp only [PowerSeries.ext_iff, evalNegHom, coeff_X] at h
· apply eq_zero_of_neg_eq
specialize h n
split_ifs at h <;> simp_all [B, h_odd.neg_one_pow, factorial_ne_zero]
· simpa (config := {decide := true}) [Nat.factorial] using h 1
have h : B * (exp ℚ - 1) = X * exp ℚ := by
simpa [bernoulli'PowerSeries] using bernoulli'PowerSeries_mul_exp_sub_one ℚ
rw [sub_mul, h, mul_sub X, sub_right_inj, ← neg_sub, mul_neg, neg_eq_iff_eq_neg]
suffices evalNegHom (B * (exp ℚ - 1)) * exp ℚ = evalNegHom (X * exp ℚ) * exp ℚ by
rw [map_mul, map_mul] at this -- Porting note: Why doesn't simp do this?
simpa [mul_assoc, sub_mul, mul_comm (evalNegHom (exp ℚ)), exp_mul_exp_neg_eq_one]
congr
#align bernoulli'_odd_eq_zero bernoulli'_odd_eq_zero
/-- The Bernoulli numbers are defined to be `bernoulli'` with a parity sign. -/
def bernoulli (n : ℕ) : ℚ :=
(-1) ^ n * bernoulli' n
#align bernoulli bernoulli
theorem bernoulli'_eq_bernoulli (n : ℕ) : bernoulli' n = (-1) ^ n * bernoulli n := by
simp [bernoulli, ← mul_assoc, ← sq, ← pow_mul, mul_comm n 2, pow_mul]
#align bernoulli'_eq_bernoulli bernoulli'_eq_bernoulli
@[simp]
theorem bernoulli_zero : bernoulli 0 = 1 := by simp [bernoulli]
#align bernoulli_zero bernoulli_zero
@[simp]
theorem bernoulli_one : bernoulli 1 = -1 / 2 := by norm_num [bernoulli]
#align bernoulli_one bernoulli_one
| Mathlib/NumberTheory/Bernoulli.lean | 216 | 221 | theorem bernoulli_eq_bernoulli'_of_ne_one {n : ℕ} (hn : n ≠ 1) : bernoulli n = bernoulli' n := by |
by_cases h0 : n = 0; · simp [h0]
rw [bernoulli, neg_one_pow_eq_pow_mod_two]
cases' mod_two_eq_zero_or_one n with h h
· simp [h]
· simp [bernoulli'_odd_eq_zero (odd_iff.mpr h) (one_lt_iff_ne_zero_and_ne_one.mpr ⟨h0, hn⟩)]
|
/-
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 -/
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 1,110 | 1,119 | 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
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Geometry.Euclidean.Angle.Oriented.RightAngle
import Mathlib.Geometry.Euclidean.Circumcenter
#align_import geometry.euclidean.angle.sphere from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Angles in circles and sphere.
This file proves results about angles in circles and spheres.
-/
noncomputable section
open FiniteDimensional Complex
open scoped EuclideanGeometry Real RealInnerProductSpace ComplexConjugate
namespace Orientation
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
variable [Fact (finrank ℝ V = 2)] (o : Orientation ℝ V (Fin 2))
/-- Angle at center of a circle equals twice angle at circumference, oriented vector angle
form. -/
theorem oangle_eq_two_zsmul_oangle_sub_of_norm_eq {x y z : V} (hxyne : x ≠ y) (hxzne : x ≠ z)
(hxy : ‖x‖ = ‖y‖) (hxz : ‖x‖ = ‖z‖) : o.oangle y z = (2 : ℤ) • o.oangle (y - x) (z - x) := by
have hy : y ≠ 0 := by
rintro rfl
rw [norm_zero, norm_eq_zero] at hxy
exact hxyne hxy
have hx : x ≠ 0 := norm_ne_zero_iff.1 (hxy.symm ▸ norm_ne_zero_iff.2 hy)
have hz : z ≠ 0 := norm_ne_zero_iff.1 (hxz ▸ norm_ne_zero_iff.2 hx)
calc
o.oangle y z = o.oangle x z - o.oangle x y := (o.oangle_sub_left hx hy hz).symm
_ = π - (2 : ℤ) • o.oangle (x - z) x - (π - (2 : ℤ) • o.oangle (x - y) x) := by
rw [o.oangle_eq_pi_sub_two_zsmul_oangle_sub_of_norm_eq hxzne.symm hxz.symm,
o.oangle_eq_pi_sub_two_zsmul_oangle_sub_of_norm_eq hxyne.symm hxy.symm]
_ = (2 : ℤ) • (o.oangle (x - y) x - o.oangle (x - z) x) := by abel
_ = (2 : ℤ) • o.oangle (x - y) (x - z) := by
rw [o.oangle_sub_right (sub_ne_zero_of_ne hxyne) (sub_ne_zero_of_ne hxzne) hx]
_ = (2 : ℤ) • o.oangle (y - x) (z - x) := by rw [← oangle_neg_neg, neg_sub, neg_sub]
#align orientation.oangle_eq_two_zsmul_oangle_sub_of_norm_eq Orientation.oangle_eq_two_zsmul_oangle_sub_of_norm_eq
/-- Angle at center of a circle equals twice angle at circumference, oriented vector angle
form with radius specified. -/
theorem oangle_eq_two_zsmul_oangle_sub_of_norm_eq_real {x y z : V} (hxyne : x ≠ y) (hxzne : x ≠ z)
{r : ℝ} (hx : ‖x‖ = r) (hy : ‖y‖ = r) (hz : ‖z‖ = r) :
o.oangle y z = (2 : ℤ) • o.oangle (y - x) (z - x) :=
o.oangle_eq_two_zsmul_oangle_sub_of_norm_eq hxyne hxzne (hy.symm ▸ hx) (hz.symm ▸ hx)
#align orientation.oangle_eq_two_zsmul_oangle_sub_of_norm_eq_real Orientation.oangle_eq_two_zsmul_oangle_sub_of_norm_eq_real
/-- Oriented vector angle version of "angles in same segment are equal" and "opposite angles of
a cyclic quadrilateral add to π", for oriented angles mod π (for which those are the same
result), represented here as equality of twice the angles. -/
theorem two_zsmul_oangle_sub_eq_two_zsmul_oangle_sub_of_norm_eq {x₁ x₂ y z : V} (hx₁yne : x₁ ≠ y)
(hx₁zne : x₁ ≠ z) (hx₂yne : x₂ ≠ y) (hx₂zne : x₂ ≠ z) {r : ℝ} (hx₁ : ‖x₁‖ = r) (hx₂ : ‖x₂‖ = r)
(hy : ‖y‖ = r) (hz : ‖z‖ = r) :
(2 : ℤ) • o.oangle (y - x₁) (z - x₁) = (2 : ℤ) • o.oangle (y - x₂) (z - x₂) :=
o.oangle_eq_two_zsmul_oangle_sub_of_norm_eq_real hx₁yne hx₁zne hx₁ hy hz ▸
o.oangle_eq_two_zsmul_oangle_sub_of_norm_eq_real hx₂yne hx₂zne hx₂ hy hz
#align orientation.two_zsmul_oangle_sub_eq_two_zsmul_oangle_sub_of_norm_eq Orientation.two_zsmul_oangle_sub_eq_two_zsmul_oangle_sub_of_norm_eq
end Orientation
namespace EuclideanGeometry
variable {V : Type*} {P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P]
[NormedAddTorsor V P] [hd2 : Fact (finrank ℝ V = 2)] [Module.Oriented ℝ V (Fin 2)]
local notation "o" => Module.Oriented.positiveOrientation
namespace Sphere
/-- Angle at center of a circle equals twice angle at circumference, oriented angle version. -/
theorem oangle_center_eq_two_zsmul_oangle {s : Sphere P} {p₁ p₂ p₃ : P} (hp₁ : p₁ ∈ s)
(hp₂ : p₂ ∈ s) (hp₃ : p₃ ∈ s) (hp₂p₁ : p₂ ≠ p₁) (hp₂p₃ : p₂ ≠ p₃) :
∡ p₁ s.center p₃ = (2 : ℤ) • ∡ p₁ p₂ p₃ := by
rw [mem_sphere, @dist_eq_norm_vsub V] at hp₁ hp₂ hp₃
rw [oangle, oangle, o.oangle_eq_two_zsmul_oangle_sub_of_norm_eq_real _ _ hp₂ hp₁ hp₃] <;>
simp [hp₂p₁, hp₂p₃]
#align euclidean_geometry.sphere.oangle_center_eq_two_zsmul_oangle EuclideanGeometry.Sphere.oangle_center_eq_two_zsmul_oangle
/-- Oriented angle version of "angles in same segment are equal" and "opposite angles of a
cyclic quadrilateral add to π", for oriented angles mod π (for which those are the same result),
represented here as equality of twice the angles. -/
theorem two_zsmul_oangle_eq {s : Sphere P} {p₁ p₂ p₃ p₄ : P} (hp₁ : p₁ ∈ s) (hp₂ : p₂ ∈ s)
(hp₃ : p₃ ∈ s) (hp₄ : p₄ ∈ s) (hp₂p₁ : p₂ ≠ p₁) (hp₂p₄ : p₂ ≠ p₄) (hp₃p₁ : p₃ ≠ p₁)
(hp₃p₄ : p₃ ≠ p₄) : (2 : ℤ) • ∡ p₁ p₂ p₄ = (2 : ℤ) • ∡ p₁ p₃ p₄ := by
rw [mem_sphere, @dist_eq_norm_vsub V] at hp₁ hp₂ hp₃ hp₄
rw [oangle, oangle, ← vsub_sub_vsub_cancel_right p₁ p₂ s.center, ←
vsub_sub_vsub_cancel_right p₄ p₂ s.center,
o.two_zsmul_oangle_sub_eq_two_zsmul_oangle_sub_of_norm_eq _ _ _ _ hp₂ hp₃ hp₁ hp₄] <;>
simp [hp₂p₁, hp₂p₄, hp₃p₁, hp₃p₄]
#align euclidean_geometry.sphere.two_zsmul_oangle_eq EuclideanGeometry.Sphere.two_zsmul_oangle_eq
end Sphere
/-- Oriented angle version of "angles in same segment are equal" and "opposite angles of a
cyclic quadrilateral add to π", for oriented angles mod π (for which those are the same result),
represented here as equality of twice the angles. -/
theorem Cospherical.two_zsmul_oangle_eq {p₁ p₂ p₃ p₄ : P}
(h : Cospherical ({p₁, p₂, p₃, p₄} : Set P)) (hp₂p₁ : p₂ ≠ p₁) (hp₂p₄ : p₂ ≠ p₄)
(hp₃p₁ : p₃ ≠ p₁) (hp₃p₄ : p₃ ≠ p₄) : (2 : ℤ) • ∡ p₁ p₂ p₄ = (2 : ℤ) • ∡ p₁ p₃ p₄ := by
obtain ⟨s, hs⟩ := cospherical_iff_exists_sphere.1 h
simp_rw [Set.insert_subset_iff, Set.singleton_subset_iff, Sphere.mem_coe] at hs
exact Sphere.two_zsmul_oangle_eq hs.1 hs.2.1 hs.2.2.1 hs.2.2.2 hp₂p₁ hp₂p₄ hp₃p₁ hp₃p₄
#align euclidean_geometry.cospherical.two_zsmul_oangle_eq EuclideanGeometry.Cospherical.two_zsmul_oangle_eq
namespace Sphere
/-- The angle at the apex of an isosceles triangle is `π` minus twice a base angle, oriented
angle-at-point form where the apex is given as the center of a circle. -/
| Mathlib/Geometry/Euclidean/Angle/Sphere.lean | 120 | 123 | theorem oangle_eq_pi_sub_two_zsmul_oangle_center_left {s : Sphere P} {p₁ p₂ : P} (hp₁ : p₁ ∈ s)
(hp₂ : p₂ ∈ s) (h : p₁ ≠ p₂) : ∡ p₁ s.center p₂ = π - (2 : ℤ) • ∡ s.center p₂ p₁ := by |
rw [oangle_eq_pi_sub_two_zsmul_oangle_of_dist_eq h.symm
(dist_center_eq_dist_center_of_mem_sphere' hp₂ hp₁)]
|
/-
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
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
#align preimage_nhds_within_coinduced preimage_nhds_within_coinduced
@[simp]
theorem nhdsWithin_empty (a : α) : 𝓝[∅] a = ⊥ := by rw [nhdsWithin, principal_empty, inf_bot_eq]
#align nhds_within_empty nhdsWithin_empty
theorem nhdsWithin_union (a : α) (s t : Set α) : 𝓝[s ∪ t] a = 𝓝[s] a ⊔ 𝓝[t] a := by
delta nhdsWithin
rw [← inf_sup_left, sup_principal]
#align nhds_within_union nhdsWithin_union
theorem nhdsWithin_biUnion {ι} {I : Set ι} (hI : I.Finite) (s : ι → Set α) (a : α) :
𝓝[⋃ i ∈ I, s i] a = ⨆ i ∈ I, 𝓝[s i] a :=
Set.Finite.induction_on hI (by simp) fun _ _ hT ↦ by
simp only [hT, nhdsWithin_union, iSup_insert, biUnion_insert]
#align nhds_within_bUnion nhdsWithin_biUnion
theorem nhdsWithin_sUnion {S : Set (Set α)} (hS : S.Finite) (a : α) :
𝓝[⋃₀ S] a = ⨆ s ∈ S, 𝓝[s] a := by
rw [sUnion_eq_biUnion, nhdsWithin_biUnion hS]
#align nhds_within_sUnion nhdsWithin_sUnion
theorem nhdsWithin_iUnion {ι} [Finite ι] (s : ι → Set α) (a : α) :
𝓝[⋃ i, s i] a = ⨆ i, 𝓝[s i] a := by
rw [← sUnion_range, nhdsWithin_sUnion (finite_range s), iSup_range]
#align nhds_within_Union nhdsWithin_iUnion
theorem nhdsWithin_inter (a : α) (s t : Set α) : 𝓝[s ∩ t] a = 𝓝[s] a ⊓ 𝓝[t] a := by
delta nhdsWithin
rw [inf_left_comm, inf_assoc, inf_principal, ← inf_assoc, inf_idem]
#align nhds_within_inter nhdsWithin_inter
theorem nhdsWithin_inter' (a : α) (s t : Set α) : 𝓝[s ∩ t] a = 𝓝[s] a ⊓ 𝓟 t := by
delta nhdsWithin
rw [← inf_principal, inf_assoc]
#align nhds_within_inter' nhdsWithin_inter'
theorem nhdsWithin_inter_of_mem {a : α} {s t : Set α} (h : s ∈ 𝓝[t] a) : 𝓝[s ∩ t] a = 𝓝[t] a := by
rw [nhdsWithin_inter, inf_eq_right]
exact nhdsWithin_le_of_mem h
#align nhds_within_inter_of_mem nhdsWithin_inter_of_mem
theorem nhdsWithin_inter_of_mem' {a : α} {s t : Set α} (h : t ∈ 𝓝[s] a) : 𝓝[s ∩ t] a = 𝓝[s] a := by
rw [inter_comm, nhdsWithin_inter_of_mem h]
#align nhds_within_inter_of_mem' nhdsWithin_inter_of_mem'
@[simp]
theorem nhdsWithin_singleton (a : α) : 𝓝[{a}] a = pure a := by
rw [nhdsWithin, principal_singleton, inf_eq_right.2 (pure_le_nhds a)]
#align nhds_within_singleton nhdsWithin_singleton
@[simp]
theorem nhdsWithin_insert (a : α) (s : Set α) : 𝓝[insert a s] a = pure a ⊔ 𝓝[s] a := by
rw [← singleton_union, nhdsWithin_union, nhdsWithin_singleton]
#align nhds_within_insert nhdsWithin_insert
theorem mem_nhdsWithin_insert {a : α} {s t : Set α} : t ∈ 𝓝[insert a s] a ↔ a ∈ t ∧ t ∈ 𝓝[s] a := by
simp
#align mem_nhds_within_insert mem_nhdsWithin_insert
theorem insert_mem_nhdsWithin_insert {a : α} {s t : Set α} (h : t ∈ 𝓝[s] a) :
insert a t ∈ 𝓝[insert a s] a := by simp [mem_of_superset h]
#align insert_mem_nhds_within_insert insert_mem_nhdsWithin_insert
theorem insert_mem_nhds_iff {a : α} {s : Set α} : insert a s ∈ 𝓝 a ↔ s ∈ 𝓝[≠] a := by
simp only [nhdsWithin, mem_inf_principal, mem_compl_iff, mem_singleton_iff, or_iff_not_imp_left,
insert_def]
#align insert_mem_nhds_iff insert_mem_nhds_iff
@[simp]
theorem nhdsWithin_compl_singleton_sup_pure (a : α) : 𝓝[≠] a ⊔ pure a = 𝓝 a := by
rw [← nhdsWithin_singleton, ← nhdsWithin_union, compl_union_self, nhdsWithin_univ]
#align nhds_within_compl_singleton_sup_pure nhdsWithin_compl_singleton_sup_pure
theorem nhdsWithin_prod {α : Type*} [TopologicalSpace α] {β : Type*} [TopologicalSpace β]
{s u : Set α} {t v : Set β} {a : α} {b : β} (hu : u ∈ 𝓝[s] a) (hv : v ∈ 𝓝[t] b) :
u ×ˢ v ∈ 𝓝[s ×ˢ t] (a, b) := by
rw [nhdsWithin_prod_eq]
exact prod_mem_prod hu hv
#align nhds_within_prod nhdsWithin_prod
theorem nhdsWithin_pi_eq' {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
(hI : I.Finite) (s : ∀ i, Set (α i)) (x : ∀ i, α i) :
𝓝[pi I s] x = ⨅ i, comap (fun x => x i) (𝓝 (x i) ⊓ ⨅ (_ : i ∈ I), 𝓟 (s i)) := by
simp only [nhdsWithin, nhds_pi, Filter.pi, comap_inf, comap_iInf, pi_def, comap_principal, ←
iInf_principal_finite hI, ← iInf_inf_eq]
#align nhds_within_pi_eq' nhdsWithin_pi_eq'
theorem nhdsWithin_pi_eq {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
(hI : I.Finite) (s : ∀ i, Set (α i)) (x : ∀ i, α i) :
𝓝[pi I s] x =
(⨅ i ∈ I, comap (fun x => x i) (𝓝[s i] x i)) ⊓
⨅ (i) (_ : i ∉ I), comap (fun x => x i) (𝓝 (x i)) := by
simp only [nhdsWithin, nhds_pi, Filter.pi, pi_def, ← iInf_principal_finite hI, comap_inf,
comap_principal, eval]
rw [iInf_split _ fun i => i ∈ I, inf_right_comm]
simp only [iInf_inf_eq]
#align nhds_within_pi_eq nhdsWithin_pi_eq
theorem nhdsWithin_pi_univ_eq {ι : Type*} {α : ι → Type*} [Finite ι] [∀ i, TopologicalSpace (α i)]
(s : ∀ i, Set (α i)) (x : ∀ i, α i) :
𝓝[pi univ s] x = ⨅ i, comap (fun x => x i) (𝓝[s i] x i) := by
simpa [nhdsWithin] using nhdsWithin_pi_eq finite_univ s x
#align nhds_within_pi_univ_eq nhdsWithin_pi_univ_eq
theorem nhdsWithin_pi_eq_bot {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
{s : ∀ i, Set (α i)} {x : ∀ i, α i} : 𝓝[pi I s] x = ⊥ ↔ ∃ i ∈ I, 𝓝[s i] x i = ⊥ := by
simp only [nhdsWithin, nhds_pi, pi_inf_principal_pi_eq_bot]
#align nhds_within_pi_eq_bot nhdsWithin_pi_eq_bot
theorem nhdsWithin_pi_neBot {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
{s : ∀ i, Set (α i)} {x : ∀ i, α i} : (𝓝[pi I s] x).NeBot ↔ ∀ i ∈ I, (𝓝[s i] x i).NeBot := by
simp [neBot_iff, nhdsWithin_pi_eq_bot]
#align nhds_within_pi_ne_bot nhdsWithin_pi_neBot
theorem Filter.Tendsto.piecewise_nhdsWithin {f g : α → β} {t : Set α} [∀ x, Decidable (x ∈ t)]
{a : α} {s : Set α} {l : Filter β} (h₀ : Tendsto f (𝓝[s ∩ t] a) l)
(h₁ : Tendsto g (𝓝[s ∩ tᶜ] a) l) : Tendsto (piecewise t f g) (𝓝[s] a) l := by
apply Tendsto.piecewise <;> rwa [← nhdsWithin_inter']
#align filter.tendsto.piecewise_nhds_within Filter.Tendsto.piecewise_nhdsWithin
theorem Filter.Tendsto.if_nhdsWithin {f g : α → β} {p : α → Prop} [DecidablePred p] {a : α}
{s : Set α} {l : Filter β} (h₀ : Tendsto f (𝓝[s ∩ { x | p x }] a) l)
(h₁ : Tendsto g (𝓝[s ∩ { x | ¬p x }] a) l) :
Tendsto (fun x => if p x then f x else g x) (𝓝[s] a) l :=
h₀.piecewise_nhdsWithin h₁
#align filter.tendsto.if_nhds_within Filter.Tendsto.if_nhdsWithin
theorem map_nhdsWithin (f : α → β) (a : α) (s : Set α) :
map f (𝓝[s] a) = ⨅ t ∈ { t : Set α | a ∈ t ∧ IsOpen t }, 𝓟 (f '' (t ∩ s)) :=
((nhdsWithin_basis_open a s).map f).eq_biInf
#align map_nhds_within map_nhdsWithin
theorem tendsto_nhdsWithin_mono_left {f : α → β} {a : α} {s t : Set α} {l : Filter β} (hst : s ⊆ t)
(h : Tendsto f (𝓝[t] a) l) : Tendsto f (𝓝[s] a) l :=
h.mono_left <| nhdsWithin_mono a hst
#align tendsto_nhds_within_mono_left tendsto_nhdsWithin_mono_left
theorem tendsto_nhdsWithin_mono_right {f : β → α} {l : Filter β} {a : α} {s t : Set α} (hst : s ⊆ t)
(h : Tendsto f l (𝓝[s] a)) : Tendsto f l (𝓝[t] a) :=
h.mono_right (nhdsWithin_mono a hst)
#align tendsto_nhds_within_mono_right tendsto_nhdsWithin_mono_right
theorem tendsto_nhdsWithin_of_tendsto_nhds {f : α → β} {a : α} {s : Set α} {l : Filter β}
(h : Tendsto f (𝓝 a) l) : Tendsto f (𝓝[s] a) l :=
h.mono_left inf_le_left
#align tendsto_nhds_within_of_tendsto_nhds tendsto_nhdsWithin_of_tendsto_nhds
theorem eventually_mem_of_tendsto_nhdsWithin {f : β → α} {a : α} {s : Set α} {l : Filter β}
(h : Tendsto f l (𝓝[s] a)) : ∀ᶠ i in l, f i ∈ s := by
simp_rw [nhdsWithin_eq, tendsto_iInf, mem_setOf_eq, tendsto_principal, mem_inter_iff,
eventually_and] at h
exact (h univ ⟨mem_univ a, isOpen_univ⟩).2
#align eventually_mem_of_tendsto_nhds_within eventually_mem_of_tendsto_nhdsWithin
theorem tendsto_nhds_of_tendsto_nhdsWithin {f : β → α} {a : α} {s : Set α} {l : Filter β}
(h : Tendsto f l (𝓝[s] a)) : Tendsto f l (𝓝 a) :=
h.mono_right nhdsWithin_le_nhds
#align tendsto_nhds_of_tendsto_nhds_within tendsto_nhds_of_tendsto_nhdsWithin
theorem nhdsWithin_neBot_of_mem {s : Set α} {x : α} (hx : x ∈ s) : NeBot (𝓝[s] x) :=
mem_closure_iff_nhdsWithin_neBot.1 <| subset_closure hx
#align nhds_within_ne_bot_of_mem nhdsWithin_neBot_of_mem
theorem IsClosed.mem_of_nhdsWithin_neBot {s : Set α} (hs : IsClosed s) {x : α}
(hx : NeBot <| 𝓝[s] x) : x ∈ s :=
hs.closure_eq ▸ mem_closure_iff_nhdsWithin_neBot.2 hx
#align is_closed.mem_of_nhds_within_ne_bot IsClosed.mem_of_nhdsWithin_neBot
theorem DenseRange.nhdsWithin_neBot {ι : Type*} {f : ι → α} (h : DenseRange f) (x : α) :
NeBot (𝓝[range f] x) :=
mem_closure_iff_clusterPt.1 (h x)
#align dense_range.nhds_within_ne_bot DenseRange.nhdsWithin_neBot
theorem mem_closure_pi {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
{s : ∀ i, Set (α i)} {x : ∀ i, α i} : x ∈ closure (pi I s) ↔ ∀ i ∈ I, x i ∈ closure (s i) := by
simp only [mem_closure_iff_nhdsWithin_neBot, nhdsWithin_pi_neBot]
#align mem_closure_pi mem_closure_pi
theorem closure_pi_set {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] (I : Set ι)
(s : ∀ i, Set (α i)) : closure (pi I s) = pi I fun i => closure (s i) :=
Set.ext fun _ => mem_closure_pi
#align closure_pi_set closure_pi_set
theorem dense_pi {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {s : ∀ i, Set (α i)}
(I : Set ι) (hs : ∀ i ∈ I, Dense (s i)) : Dense (pi I s) := by
simp only [dense_iff_closure_eq, closure_pi_set, pi_congr rfl fun i hi => (hs i hi).closure_eq,
pi_univ]
#align dense_pi dense_pi
theorem eventuallyEq_nhdsWithin_iff {f g : α → β} {s : Set α} {a : α} :
f =ᶠ[𝓝[s] a] g ↔ ∀ᶠ x in 𝓝 a, x ∈ s → f x = g x :=
mem_inf_principal
#align eventually_eq_nhds_within_iff eventuallyEq_nhdsWithin_iff
theorem eventuallyEq_nhdsWithin_of_eqOn {f g : α → β} {s : Set α} {a : α} (h : EqOn f g s) :
f =ᶠ[𝓝[s] a] g :=
mem_inf_of_right h
#align eventually_eq_nhds_within_of_eq_on eventuallyEq_nhdsWithin_of_eqOn
theorem Set.EqOn.eventuallyEq_nhdsWithin {f g : α → β} {s : Set α} {a : α} (h : EqOn f g s) :
f =ᶠ[𝓝[s] a] g :=
eventuallyEq_nhdsWithin_of_eqOn h
#align set.eq_on.eventually_eq_nhds_within Set.EqOn.eventuallyEq_nhdsWithin
theorem tendsto_nhdsWithin_congr {f g : α → β} {s : Set α} {a : α} {l : Filter β}
(hfg : ∀ x ∈ s, f x = g x) (hf : Tendsto f (𝓝[s] a) l) : Tendsto g (𝓝[s] a) l :=
(tendsto_congr' <| eventuallyEq_nhdsWithin_of_eqOn hfg).1 hf
#align tendsto_nhds_within_congr tendsto_nhdsWithin_congr
theorem eventually_nhdsWithin_of_forall {s : Set α} {a : α} {p : α → Prop} (h : ∀ x ∈ s, p x) :
∀ᶠ x in 𝓝[s] a, p x :=
mem_inf_of_right h
#align eventually_nhds_within_of_forall eventually_nhdsWithin_of_forall
theorem tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within {a : α} {l : Filter β} {s : Set α}
(f : β → α) (h1 : Tendsto f l (𝓝 a)) (h2 : ∀ᶠ x in l, f x ∈ s) : Tendsto f l (𝓝[s] a) :=
tendsto_inf.2 ⟨h1, tendsto_principal.2 h2⟩
#align tendsto_nhds_within_of_tendsto_nhds_of_eventually_within tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within
theorem tendsto_nhdsWithin_iff {a : α} {l : Filter β} {s : Set α} {f : β → α} :
Tendsto f l (𝓝[s] a) ↔ Tendsto f l (𝓝 a) ∧ ∀ᶠ n in l, f n ∈ s :=
⟨fun h => ⟨tendsto_nhds_of_tendsto_nhdsWithin h, eventually_mem_of_tendsto_nhdsWithin h⟩, fun h =>
tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _ h.1 h.2⟩
#align tendsto_nhds_within_iff tendsto_nhdsWithin_iff
@[simp]
theorem tendsto_nhdsWithin_range {a : α} {l : Filter β} {f : β → α} :
Tendsto f l (𝓝[range f] a) ↔ Tendsto f l (𝓝 a) :=
⟨fun h => h.mono_right inf_le_left, fun h =>
tendsto_inf.2 ⟨h, tendsto_principal.2 <| eventually_of_forall mem_range_self⟩⟩
#align tendsto_nhds_within_range tendsto_nhdsWithin_range
theorem Filter.EventuallyEq.eq_of_nhdsWithin {s : Set α} {f g : α → β} {a : α} (h : f =ᶠ[𝓝[s] a] g)
(hmem : a ∈ s) : f a = g a :=
h.self_of_nhdsWithin hmem
#align filter.eventually_eq.eq_of_nhds_within Filter.EventuallyEq.eq_of_nhdsWithin
theorem eventually_nhdsWithin_of_eventually_nhds {α : Type*} [TopologicalSpace α] {s : Set α}
{a : α} {p : α → Prop} (h : ∀ᶠ x in 𝓝 a, p x) : ∀ᶠ x in 𝓝[s] a, p x :=
mem_nhdsWithin_of_mem_nhds h
#align eventually_nhds_within_of_eventually_nhds eventually_nhdsWithin_of_eventually_nhds
/-!
### `nhdsWithin` and subtypes
-/
theorem mem_nhdsWithin_subtype {s : Set α} {a : { x // x ∈ s }} {t u : Set { x // x ∈ s }} :
t ∈ 𝓝[u] a ↔ t ∈ comap ((↑) : s → α) (𝓝[(↑) '' u] a) := by
rw [nhdsWithin, nhds_subtype, principal_subtype, ← comap_inf, ← nhdsWithin]
#align mem_nhds_within_subtype mem_nhdsWithin_subtype
theorem nhdsWithin_subtype (s : Set α) (a : { x // x ∈ s }) (t : Set { x // x ∈ s }) :
𝓝[t] a = comap ((↑) : s → α) (𝓝[(↑) '' t] a) :=
Filter.ext fun _ => mem_nhdsWithin_subtype
#align nhds_within_subtype nhdsWithin_subtype
theorem nhdsWithin_eq_map_subtype_coe {s : Set α} {a : α} (h : a ∈ s) :
𝓝[s] a = map ((↑) : s → α) (𝓝 ⟨a, h⟩) :=
(map_nhds_subtype_val ⟨a, h⟩).symm
#align nhds_within_eq_map_subtype_coe nhdsWithin_eq_map_subtype_coe
theorem mem_nhds_subtype_iff_nhdsWithin {s : Set α} {a : s} {t : Set s} :
t ∈ 𝓝 a ↔ (↑) '' t ∈ 𝓝[s] (a : α) := by
rw [← map_nhds_subtype_val, image_mem_map_iff Subtype.val_injective]
#align mem_nhds_subtype_iff_nhds_within mem_nhds_subtype_iff_nhdsWithin
| Mathlib/Topology/ContinuousOn.lean | 496 | 497 | theorem preimage_coe_mem_nhds_subtype {s t : Set α} {a : s} : (↑) ⁻¹' t ∈ 𝓝 a ↔ t ∈ 𝓝[s] ↑a := by |
rw [← map_nhds_subtype_val, mem_map]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Topology.ExtendFrom
import Mathlib.Topology.Order.DenselyOrdered
#align_import topology.algebra.order.extend_from from "leanprover-community/mathlib"@"0a0ec35061ed9960bf0e7ffb0335f44447b58977"
/-!
# Lemmas about `extendFrom` in an order topology.
-/
set_option autoImplicit true
open Filter Set TopologicalSpace
open scoped Classical
open Topology
theorem continuousOn_Icc_extendFrom_Ioo [TopologicalSpace α] [LinearOrder α] [DenselyOrdered α]
[OrderTopology α] [TopologicalSpace β] [RegularSpace β] {f : α → β} {a b : α} {la lb : β}
(hab : a ≠ b) (hf : ContinuousOn f (Ioo a b)) (ha : Tendsto f (𝓝[>] a) (𝓝 la))
(hb : Tendsto f (𝓝[<] b) (𝓝 lb)) : ContinuousOn (extendFrom (Ioo a b) f) (Icc a b) := by
apply continuousOn_extendFrom
· rw [closure_Ioo hab]
· intro x x_in
rcases eq_endpoints_or_mem_Ioo_of_mem_Icc x_in with (rfl | rfl | h)
· exact ⟨la, ha.mono_left <| nhdsWithin_mono _ Ioo_subset_Ioi_self⟩
· exact ⟨lb, hb.mono_left <| nhdsWithin_mono _ Ioo_subset_Iio_self⟩
· exact ⟨f x, hf x h⟩
#align continuous_on_Icc_extend_from_Ioo continuousOn_Icc_extendFrom_Ioo
theorem eq_lim_at_left_extendFrom_Ioo [TopologicalSpace α] [LinearOrder α] [DenselyOrdered α]
[OrderTopology α] [TopologicalSpace β] [T2Space β] {f : α → β} {a b : α} {la : β} (hab : a < b)
(ha : Tendsto f (𝓝[>] a) (𝓝 la)) : extendFrom (Ioo a b) f a = la := by
apply extendFrom_eq
· rw [closure_Ioo hab.ne]
simp only [le_of_lt hab, left_mem_Icc, right_mem_Icc]
· simpa [hab]
#align eq_lim_at_left_extend_from_Ioo eq_lim_at_left_extendFrom_Ioo
theorem eq_lim_at_right_extendFrom_Ioo [TopologicalSpace α] [LinearOrder α] [DenselyOrdered α]
[OrderTopology α] [TopologicalSpace β] [T2Space β] {f : α → β} {a b : α} {lb : β} (hab : a < b)
(hb : Tendsto f (𝓝[<] b) (𝓝 lb)) : extendFrom (Ioo a b) f b = lb := by
apply extendFrom_eq
· rw [closure_Ioo hab.ne]
simp only [le_of_lt hab, left_mem_Icc, right_mem_Icc]
· simpa [hab]
#align eq_lim_at_right_extend_from_Ioo eq_lim_at_right_extendFrom_Ioo
| Mathlib/Topology/Order/ExtendFrom.lean | 54 | 65 | theorem continuousOn_Ico_extendFrom_Ioo [TopologicalSpace α] [LinearOrder α] [DenselyOrdered α]
[OrderTopology α] [TopologicalSpace β] [RegularSpace β] {f : α → β} {a b : α} {la : β}
(hab : a < b) (hf : ContinuousOn f (Ioo a b)) (ha : Tendsto f (𝓝[>] a) (𝓝 la)) :
ContinuousOn (extendFrom (Ioo a b) f) (Ico a b) := by |
apply continuousOn_extendFrom
· rw [closure_Ioo hab.ne]
exact Ico_subset_Icc_self
· intro x x_in
rcases eq_left_or_mem_Ioo_of_mem_Ico x_in with (rfl | h)
· use la
simpa [hab]
· exact ⟨f x, hf x h⟩
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Thomas Browning
-/
import Mathlib.Data.Nat.Factorization.Basic
import Mathlib.Data.SetLike.Fintype
import Mathlib.GroupTheory.GroupAction.ConjAct
import Mathlib.GroupTheory.PGroup
import Mathlib.GroupTheory.NoncommPiCoprod
import Mathlib.Order.Atoms.Finite
import Mathlib.Data.Set.Lattice
#align_import group_theory.sylow from "leanprover-community/mathlib"@"4be589053caf347b899a494da75410deb55fb3ef"
/-!
# Sylow theorems
The Sylow theorems are the following results for every finite group `G` and every prime number `p`.
* There exists a Sylow `p`-subgroup of `G`.
* All Sylow `p`-subgroups of `G` are conjugate to each other.
* Let `nₚ` be the number of Sylow `p`-subgroups of `G`, then `nₚ` divides the index of the Sylow
`p`-subgroup, `nₚ ≡ 1 [MOD p]`, and `nₚ` is equal to the index of the normalizer of the Sylow
`p`-subgroup in `G`.
## Main definitions
* `Sylow p G` : The type of Sylow `p`-subgroups of `G`.
## Main statements
* `exists_subgroup_card_pow_prime`: A generalization of Sylow's first theorem:
For every prime power `pⁿ` dividing the cardinality of `G`,
there exists a subgroup of `G` of order `pⁿ`.
* `IsPGroup.exists_le_sylow`: A generalization of Sylow's first theorem:
Every `p`-subgroup is contained in a Sylow `p`-subgroup.
* `Sylow.card_eq_multiplicity`: The cardinality of a Sylow subgroup is `p ^ n`
where `n` is the multiplicity of `p` in the group order.
* `sylow_conjugate`: A generalization of Sylow's second theorem:
If the number of Sylow `p`-subgroups is finite, then all Sylow `p`-subgroups are conjugate.
* `card_sylow_modEq_one`: A generalization of Sylow's third theorem:
If the number of Sylow `p`-subgroups is finite, then it is congruent to `1` modulo `p`.
-/
open Fintype MulAction Subgroup
section InfiniteSylow
variable (p : ℕ) (G : Type*) [Group G]
/-- A Sylow `p`-subgroup is a maximal `p`-subgroup. -/
structure Sylow extends Subgroup G where
isPGroup' : IsPGroup p toSubgroup
is_maximal' : ∀ {Q : Subgroup G}, IsPGroup p Q → toSubgroup ≤ Q → Q = toSubgroup
#align sylow Sylow
variable {p} {G}
namespace Sylow
attribute [coe] Sylow.toSubgroup
-- Porting note: Changed to `CoeOut`
instance : CoeOut (Sylow p G) (Subgroup G) :=
⟨Sylow.toSubgroup⟩
-- Porting note: syntactic tautology
-- @[simp]
-- theorem toSubgroup_eq_coe {P : Sylow p G} : P.toSubgroup = ↑P :=
-- rfl
#noalign sylow.to_subgroup_eq_coe
@[ext]
theorem ext {P Q : Sylow p G} (h : (P : Subgroup G) = Q) : P = Q := by cases P; cases Q; congr
#align sylow.ext Sylow.ext
theorem ext_iff {P Q : Sylow p G} : P = Q ↔ (P : Subgroup G) = Q :=
⟨congr_arg _, ext⟩
#align sylow.ext_iff Sylow.ext_iff
instance : SetLike (Sylow p G) G where
coe := (↑)
coe_injective' _ _ h := ext (SetLike.coe_injective h)
instance : SubgroupClass (Sylow p G) G where
mul_mem := Subgroup.mul_mem _
one_mem _ := Subgroup.one_mem _
inv_mem := Subgroup.inv_mem _
variable (P : Sylow p G)
/-- The action by a Sylow subgroup is the action by the underlying group. -/
instance mulActionLeft {α : Type*} [MulAction G α] : MulAction P α :=
inferInstanceAs (MulAction (P : Subgroup G) α)
#align sylow.mul_action_left Sylow.mulActionLeft
variable {K : Type*} [Group K] (ϕ : K →* G) {N : Subgroup G}
/-- The preimage of a Sylow subgroup under a p-group-kernel homomorphism is a Sylow subgroup. -/
def comapOfKerIsPGroup (hϕ : IsPGroup p ϕ.ker) (h : ↑P ≤ ϕ.range) : Sylow p K :=
{ P.1.comap ϕ with
isPGroup' := P.2.comap_of_ker_isPGroup ϕ hϕ
is_maximal' := fun {Q} hQ hle => by
show Q = P.1.comap ϕ
rw [← P.3 (hQ.map ϕ) (le_trans (ge_of_eq (map_comap_eq_self h)) (map_mono hle))]
exact (comap_map_eq_self ((P.1.ker_le_comap ϕ).trans hle)).symm }
#align sylow.comap_of_ker_is_p_group Sylow.comapOfKerIsPGroup
@[simp]
theorem coe_comapOfKerIsPGroup (hϕ : IsPGroup p ϕ.ker) (h : ↑P ≤ ϕ.range) :
(P.comapOfKerIsPGroup ϕ hϕ h : Subgroup K) = Subgroup.comap ϕ ↑P :=
rfl
#align sylow.coe_comap_of_ker_is_p_group Sylow.coe_comapOfKerIsPGroup
/-- The preimage of a Sylow subgroup under an injective homomorphism is a Sylow subgroup. -/
def comapOfInjective (hϕ : Function.Injective ϕ) (h : ↑P ≤ ϕ.range) : Sylow p K :=
P.comapOfKerIsPGroup ϕ (IsPGroup.ker_isPGroup_of_injective hϕ) h
#align sylow.comap_of_injective Sylow.comapOfInjective
@[simp]
theorem coe_comapOfInjective (hϕ : Function.Injective ϕ) (h : ↑P ≤ ϕ.range) :
↑(P.comapOfInjective ϕ hϕ h) = Subgroup.comap ϕ ↑P :=
rfl
#align sylow.coe_comap_of_injective Sylow.coe_comapOfInjective
/-- A sylow subgroup of G is also a sylow subgroup of a subgroup of G. -/
protected def subtype (h : ↑P ≤ N) : Sylow p N :=
P.comapOfInjective N.subtype Subtype.coe_injective (by rwa [subtype_range])
#align sylow.subtype Sylow.subtype
@[simp]
theorem coe_subtype (h : ↑P ≤ N) : ↑(P.subtype h) = subgroupOf (↑P) N :=
rfl
#align sylow.coe_subtype Sylow.coe_subtype
theorem subtype_injective {P Q : Sylow p G} {hP : ↑P ≤ N} {hQ : ↑Q ≤ N}
(h : P.subtype hP = Q.subtype hQ) : P = Q := by
rw [SetLike.ext_iff] at h ⊢
exact fun g => ⟨fun hg => (h ⟨g, hP hg⟩).mp hg, fun hg => (h ⟨g, hQ hg⟩).mpr hg⟩
#align sylow.subtype_injective Sylow.subtype_injective
end Sylow
/-- A generalization of **Sylow's first theorem**.
Every `p`-subgroup is contained in a Sylow `p`-subgroup. -/
theorem IsPGroup.exists_le_sylow {P : Subgroup G} (hP : IsPGroup p P) : ∃ Q : Sylow p G, P ≤ Q :=
Exists.elim
(zorn_nonempty_partialOrder₀ { Q : Subgroup G | IsPGroup p Q }
(fun c hc1 hc2 Q hQ =>
⟨{ carrier := ⋃ R : c, R
one_mem' := ⟨Q, ⟨⟨Q, hQ⟩, rfl⟩, Q.one_mem⟩
inv_mem' := fun {g} ⟨_, ⟨R, rfl⟩, hg⟩ => ⟨R, ⟨R, rfl⟩, R.1.inv_mem hg⟩
mul_mem' := fun {g} h ⟨_, ⟨R, rfl⟩, hg⟩ ⟨_, ⟨S, rfl⟩, hh⟩ =>
(hc2.total R.2 S.2).elim (fun T => ⟨S, ⟨S, rfl⟩, S.1.mul_mem (T hg) hh⟩) fun T =>
⟨R, ⟨R, rfl⟩, R.1.mul_mem hg (T hh)⟩ },
fun ⟨g, _, ⟨S, rfl⟩, hg⟩ => by
refine Exists.imp (fun k hk => ?_) (hc1 S.2 ⟨g, hg⟩)
rwa [Subtype.ext_iff, coe_pow] at hk ⊢, fun M hM g hg => ⟨M, ⟨⟨M, hM⟩, rfl⟩, hg⟩⟩)
P hP)
fun {Q} ⟨hQ1, hQ2, hQ3⟩ => ⟨⟨Q, hQ1, hQ3 _⟩, hQ2⟩
#align is_p_group.exists_le_sylow IsPGroup.exists_le_sylow
instance Sylow.nonempty : Nonempty (Sylow p G) :=
nonempty_of_exists IsPGroup.of_bot.exists_le_sylow
#align sylow.nonempty Sylow.nonempty
noncomputable instance Sylow.inhabited : Inhabited (Sylow p G) :=
Classical.inhabited_of_nonempty Sylow.nonempty
#align sylow.inhabited Sylow.inhabited
theorem Sylow.exists_comap_eq_of_ker_isPGroup {H : Type*} [Group H] (P : Sylow p H) {f : H →* G}
(hf : IsPGroup p f.ker) : ∃ Q : Sylow p G, (Q : Subgroup G).comap f = P :=
Exists.imp (fun Q hQ => P.3 (Q.2.comap_of_ker_isPGroup f hf) (map_le_iff_le_comap.mp hQ))
(P.2.map f).exists_le_sylow
#align sylow.exists_comap_eq_of_ker_is_p_group Sylow.exists_comap_eq_of_ker_isPGroup
theorem Sylow.exists_comap_eq_of_injective {H : Type*} [Group H] (P : Sylow p H) {f : H →* G}
(hf : Function.Injective f) : ∃ Q : Sylow p G, (Q : Subgroup G).comap f = P :=
P.exists_comap_eq_of_ker_isPGroup (IsPGroup.ker_isPGroup_of_injective hf)
#align sylow.exists_comap_eq_of_injective Sylow.exists_comap_eq_of_injective
theorem Sylow.exists_comap_subtype_eq {H : Subgroup G} (P : Sylow p H) :
∃ Q : Sylow p G, (Q : Subgroup G).comap H.subtype = P :=
P.exists_comap_eq_of_injective Subtype.coe_injective
#align sylow.exists_comap_subtype_eq Sylow.exists_comap_subtype_eq
/-- If the kernel of `f : H →* G` is a `p`-group,
then `Fintype (Sylow p G)` implies `Fintype (Sylow p H)`. -/
noncomputable def Sylow.fintypeOfKerIsPGroup {H : Type*} [Group H] {f : H →* G}
(hf : IsPGroup p f.ker) [Fintype (Sylow p G)] : Fintype (Sylow p H) :=
let h_exists := fun P : Sylow p H => P.exists_comap_eq_of_ker_isPGroup hf
let g : Sylow p H → Sylow p G := fun P => Classical.choose (h_exists P)
have hg : ∀ P : Sylow p H, (g P).1.comap f = P := fun P => Classical.choose_spec (h_exists P)
Fintype.ofInjective g fun P Q h => Sylow.ext (by rw [← hg, h]; exact (h_exists Q).choose_spec)
#align sylow.fintype_of_ker_is_p_group Sylow.fintypeOfKerIsPGroup
/-- If `f : H →* G` is injective, then `Fintype (Sylow p G)` implies `Fintype (Sylow p H)`. -/
noncomputable def Sylow.fintypeOfInjective {H : Type*} [Group H] {f : H →* G}
(hf : Function.Injective f) [Fintype (Sylow p G)] : Fintype (Sylow p H) :=
Sylow.fintypeOfKerIsPGroup (IsPGroup.ker_isPGroup_of_injective hf)
#align sylow.fintype_of_injective Sylow.fintypeOfInjective
/-- If `H` is a subgroup of `G`, then `Fintype (Sylow p G)` implies `Fintype (Sylow p H)`. -/
noncomputable instance (H : Subgroup G) [Fintype (Sylow p G)] : Fintype (Sylow p H) :=
Sylow.fintypeOfInjective H.subtype_injective
/-- If `H` is a subgroup of `G`, then `Finite (Sylow p G)` implies `Finite (Sylow p H)`. -/
instance (H : Subgroup G) [Finite (Sylow p G)] : Finite (Sylow p H) := by
cases nonempty_fintype (Sylow p G)
infer_instance
open Pointwise
/-- `Subgroup.pointwiseMulAction` preserves Sylow subgroups. -/
instance Sylow.pointwiseMulAction {α : Type*} [Group α] [MulDistribMulAction α G] :
MulAction α (Sylow p G) where
smul g P :=
⟨(g • P.toSubgroup : Subgroup G), P.2.map _, fun {Q} hQ hS =>
inv_smul_eq_iff.mp
(P.3 (hQ.map _) fun s hs =>
(congr_arg (· ∈ g⁻¹ • Q) (inv_smul_smul g s)).mp
(smul_mem_pointwise_smul (g • s) g⁻¹ Q (hS (smul_mem_pointwise_smul s g P hs))))⟩
one_smul P := Sylow.ext (one_smul α P.toSubgroup)
mul_smul g h P := Sylow.ext (mul_smul g h P.toSubgroup)
#align sylow.pointwise_mul_action Sylow.pointwiseMulAction
theorem Sylow.pointwise_smul_def {α : Type*} [Group α] [MulDistribMulAction α G] {g : α}
{P : Sylow p G} : ↑(g • P) = g • (P : Subgroup G) :=
rfl
#align sylow.pointwise_smul_def Sylow.pointwise_smul_def
instance Sylow.mulAction : MulAction G (Sylow p G) :=
compHom _ MulAut.conj
#align sylow.mul_action Sylow.mulAction
theorem Sylow.smul_def {g : G} {P : Sylow p G} : g • P = MulAut.conj g • P :=
rfl
#align sylow.smul_def Sylow.smul_def
theorem Sylow.coe_subgroup_smul {g : G} {P : Sylow p G} :
↑(g • P) = MulAut.conj g • (P : Subgroup G) :=
rfl
#align sylow.coe_subgroup_smul Sylow.coe_subgroup_smul
theorem Sylow.coe_smul {g : G} {P : Sylow p G} : ↑(g • P) = MulAut.conj g • (P : Set G) :=
rfl
#align sylow.coe_smul Sylow.coe_smul
theorem Sylow.smul_le {P : Sylow p G} {H : Subgroup G} (hP : ↑P ≤ H) (h : H) : ↑(h • P) ≤ H :=
Subgroup.conj_smul_le_of_le hP h
#align sylow.smul_le Sylow.smul_le
theorem Sylow.smul_subtype {P : Sylow p G} {H : Subgroup G} (hP : ↑P ≤ H) (h : H) :
h • P.subtype hP = (h • P).subtype (Sylow.smul_le hP h) :=
Sylow.ext (Subgroup.conj_smul_subgroupOf hP h)
#align sylow.smul_subtype Sylow.smul_subtype
theorem Sylow.smul_eq_iff_mem_normalizer {g : G} {P : Sylow p G} :
g • P = P ↔ g ∈ (P : Subgroup G).normalizer := by
rw [eq_comm, SetLike.ext_iff, ← inv_mem_iff (G := G) (H := normalizer P.toSubgroup),
mem_normalizer_iff, inv_inv]
exact
forall_congr' fun h =>
iff_congr Iff.rfl
⟨fun ⟨a, b, c⟩ => c ▸ by simpa [mul_assoc] using b,
fun hh => ⟨(MulAut.conj g)⁻¹ h, hh, MulAut.apply_inv_self G (MulAut.conj g) h⟩⟩
#align sylow.smul_eq_iff_mem_normalizer Sylow.smul_eq_iff_mem_normalizer
theorem Sylow.smul_eq_of_normal {g : G} {P : Sylow p G} [h : (P : Subgroup G).Normal] :
g • P = P := by simp only [Sylow.smul_eq_iff_mem_normalizer, normalizer_eq_top.mpr h, mem_top]
#align sylow.smul_eq_of_normal Sylow.smul_eq_of_normal
theorem Subgroup.sylow_mem_fixedPoints_iff (H : Subgroup G) {P : Sylow p G} :
P ∈ fixedPoints H (Sylow p G) ↔ H ≤ (P : Subgroup G).normalizer := by
simp_rw [SetLike.le_def, ← Sylow.smul_eq_iff_mem_normalizer]; exact Subtype.forall
#align subgroup.sylow_mem_fixed_points_iff Subgroup.sylow_mem_fixedPoints_iff
theorem IsPGroup.inf_normalizer_sylow {P : Subgroup G} (hP : IsPGroup p P) (Q : Sylow p G) :
P ⊓ (Q : Subgroup G).normalizer = P ⊓ Q :=
le_antisymm
(le_inf inf_le_left
(sup_eq_right.mp
(Q.3 (hP.to_inf_left.to_sup_of_normal_right' Q.2 inf_le_right) le_sup_right)))
(inf_le_inf_left P le_normalizer)
#align is_p_group.inf_normalizer_sylow IsPGroup.inf_normalizer_sylow
theorem IsPGroup.sylow_mem_fixedPoints_iff {P : Subgroup G} (hP : IsPGroup p P) {Q : Sylow p G} :
Q ∈ fixedPoints P (Sylow p G) ↔ P ≤ Q := by
rw [P.sylow_mem_fixedPoints_iff, ← inf_eq_left, hP.inf_normalizer_sylow, inf_eq_left]
#align is_p_group.sylow_mem_fixed_points_iff IsPGroup.sylow_mem_fixedPoints_iff
/-- A generalization of **Sylow's second theorem**.
If the number of Sylow `p`-subgroups is finite, then all Sylow `p`-subgroups are conjugate. -/
instance [hp : Fact p.Prime] [Finite (Sylow p G)] : IsPretransitive G (Sylow p G) :=
⟨fun P Q => by
classical
cases nonempty_fintype (Sylow p G)
have H := fun {R : Sylow p G} {S : orbit G P} =>
calc
S ∈ fixedPoints R (orbit G P) ↔ S.1 ∈ fixedPoints R (Sylow p G) :=
forall_congr' fun a => Subtype.ext_iff
_ ↔ R.1 ≤ S := R.2.sylow_mem_fixedPoints_iff
_ ↔ S.1.1 = R := ⟨fun h => R.3 S.1.2 h, ge_of_eq⟩
suffices Set.Nonempty (fixedPoints Q (orbit G P)) by
exact Exists.elim this fun R hR => by
rw [← Sylow.ext (H.mp hR)]
exact R.2
apply Q.2.nonempty_fixed_point_of_prime_not_dvd_card
refine fun h => hp.out.not_dvd_one (Nat.modEq_zero_iff_dvd.mp ?_)
calc
1 = card (fixedPoints P (orbit G P)) := ?_
_ ≡ card (orbit G P) [MOD p] := (P.2.card_modEq_card_fixedPoints (orbit G P)).symm
_ ≡ 0 [MOD p] := Nat.modEq_zero_iff_dvd.mpr h
rw [← Set.card_singleton (⟨P, mem_orbit_self P⟩ : orbit G P)]
refine card_congr' (congr_arg _ (Eq.symm ?_))
rw [Set.eq_singleton_iff_unique_mem]
exact ⟨H.mpr rfl, fun R h => Subtype.ext (Sylow.ext (H.mp h))⟩⟩
variable (p) (G)
/-- A generalization of **Sylow's third theorem**.
If the number of Sylow `p`-subgroups is finite, then it is congruent to `1` modulo `p`. -/
theorem card_sylow_modEq_one [Fact p.Prime] [Fintype (Sylow p G)] :
card (Sylow p G) ≡ 1 [MOD p] := by
refine Sylow.nonempty.elim fun P : Sylow p G => ?_
have : fixedPoints P.1 (Sylow p G) = {P} :=
Set.ext fun Q : Sylow p G =>
calc
Q ∈ fixedPoints P (Sylow p G) ↔ P.1 ≤ Q := P.2.sylow_mem_fixedPoints_iff
_ ↔ Q.1 = P.1 := ⟨P.3 Q.2, ge_of_eq⟩
_ ↔ Q ∈ {P} := Sylow.ext_iff.symm.trans Set.mem_singleton_iff.symm
have fin : Fintype (fixedPoints P.1 (Sylow p G)) := by
rw [this]
infer_instance
have : card (fixedPoints P.1 (Sylow p G)) = 1 := by simp [this]
exact (P.2.card_modEq_card_fixedPoints (Sylow p G)).trans (by rw [this])
#align card_sylow_modeq_one card_sylow_modEq_one
theorem not_dvd_card_sylow [hp : Fact p.Prime] [Fintype (Sylow p G)] : ¬p ∣ card (Sylow p G) :=
fun h =>
hp.1.ne_one
(Nat.dvd_one.mp
((Nat.modEq_iff_dvd' zero_le_one).mp
((Nat.modEq_zero_iff_dvd.mpr h).symm.trans (card_sylow_modEq_one p G))))
#align not_dvd_card_sylow not_dvd_card_sylow
variable {p} {G}
/-- Sylow subgroups are isomorphic -/
nonrec def Sylow.equivSMul (P : Sylow p G) (g : G) : P ≃* (g • P : Sylow p G) :=
equivSMul (MulAut.conj g) P.toSubgroup
#align sylow.equiv_smul Sylow.equivSMul
/-- Sylow subgroups are isomorphic -/
noncomputable def Sylow.equiv [Fact p.Prime] [Finite (Sylow p G)] (P Q : Sylow p G) : P ≃* Q := by
rw [← Classical.choose_spec (exists_smul_eq G P Q)]
exact P.equivSMul (Classical.choose (exists_smul_eq G P Q))
#align sylow.equiv Sylow.equiv
@[simp]
theorem Sylow.orbit_eq_top [Fact p.Prime] [Finite (Sylow p G)] (P : Sylow p G) : orbit G P = ⊤ :=
top_le_iff.mp fun Q _ => exists_smul_eq G P Q
#align sylow.orbit_eq_top Sylow.orbit_eq_top
theorem Sylow.stabilizer_eq_normalizer (P : Sylow p G) :
stabilizer G P = (P : Subgroup G).normalizer := by
ext; simp [Sylow.smul_eq_iff_mem_normalizer]
#align sylow.stabilizer_eq_normalizer Sylow.stabilizer_eq_normalizer
theorem Sylow.conj_eq_normalizer_conj_of_mem_centralizer [Fact p.Prime] [Finite (Sylow p G)]
(P : Sylow p G) (x g : G) (hx : x ∈ centralizer (P : Set G))
(hy : g⁻¹ * x * g ∈ centralizer (P : Set G)) :
∃ n ∈ (P : Subgroup G).normalizer, g⁻¹ * x * g = n⁻¹ * x * n := by
have h1 : ↑P ≤ centralizer (zpowers x : Set G) := by rwa [le_centralizer_iff, zpowers_le]
have h2 : ↑(g • P) ≤ centralizer (zpowers x : Set G) := by
rw [le_centralizer_iff, zpowers_le]
rintro - ⟨z, hz, rfl⟩
specialize hy z hz
rwa [← mul_assoc, ← eq_mul_inv_iff_mul_eq, mul_assoc, mul_assoc, mul_assoc, ← mul_assoc,
eq_inv_mul_iff_mul_eq, ← mul_assoc, ← mul_assoc] at hy
obtain ⟨h, hh⟩ :=
exists_smul_eq (centralizer (zpowers x : Set G)) ((g • P).subtype h2) (P.subtype h1)
simp_rw [Sylow.smul_subtype, Subgroup.smul_def, smul_smul] at hh
refine ⟨h * g, Sylow.smul_eq_iff_mem_normalizer.mp (Sylow.subtype_injective hh), ?_⟩
rw [← mul_assoc, Commute.right_comm (h.prop x (mem_zpowers x)), mul_inv_rev, inv_mul_cancel_right]
#align sylow.conj_eq_normalizer_conj_of_mem_centralizer Sylow.conj_eq_normalizer_conj_of_mem_centralizer
theorem Sylow.conj_eq_normalizer_conj_of_mem [Fact p.Prime] [Finite (Sylow p G)] (P : Sylow p G)
[_hP : (P : Subgroup G).IsCommutative] (x g : G) (hx : x ∈ P) (hy : g⁻¹ * x * g ∈ P) :
∃ n ∈ (P : Subgroup G).normalizer, g⁻¹ * x * g = n⁻¹ * x * n :=
P.conj_eq_normalizer_conj_of_mem_centralizer x g (le_centralizer P hx) (le_centralizer P hy)
#align sylow.conj_eq_normalizer_conj_of_mem Sylow.conj_eq_normalizer_conj_of_mem
/-- Sylow `p`-subgroups are in bijection with cosets of the normalizer of a Sylow `p`-subgroup -/
noncomputable def Sylow.equivQuotientNormalizer [Fact p.Prime] [Finite (Sylow p G)]
(P : Sylow p G) : Sylow p G ≃ G ⧸ (P : Subgroup G).normalizer :=
calc
Sylow p G ≃ (⊤ : Set (Sylow p G)) := (Equiv.Set.univ (Sylow p G)).symm
_ ≃ orbit G P := Equiv.setCongr P.orbit_eq_top.symm
_ ≃ G ⧸ stabilizer G P := orbitEquivQuotientStabilizer G P
_ ≃ G ⧸ (P : Subgroup G).normalizer := by rw [P.stabilizer_eq_normalizer]
#align sylow.equiv_quotient_normalizer Sylow.equivQuotientNormalizer
noncomputable instance [Fact p.Prime] [Fintype (Sylow p G)] (P : Sylow p G) :
Fintype (G ⧸ (P : Subgroup G).normalizer) :=
ofEquiv (Sylow p G) P.equivQuotientNormalizer
theorem card_sylow_eq_card_quotient_normalizer [Fact p.Prime] [Fintype (Sylow p G)]
(P : Sylow p G) : card (Sylow p G) = card (G ⧸ (P : Subgroup G).normalizer) :=
card_congr P.equivQuotientNormalizer
#align card_sylow_eq_card_quotient_normalizer card_sylow_eq_card_quotient_normalizer
theorem card_sylow_eq_index_normalizer [Fact p.Prime] [Fintype (Sylow p G)] (P : Sylow p G) :
card (Sylow p G) = (P : Subgroup G).normalizer.index :=
(card_sylow_eq_card_quotient_normalizer P).trans (P : Subgroup G).normalizer.index_eq_card.symm
#align card_sylow_eq_index_normalizer card_sylow_eq_index_normalizer
theorem card_sylow_dvd_index [Fact p.Prime] [Fintype (Sylow p G)] (P : Sylow p G) :
card (Sylow p G) ∣ (P : Subgroup G).index :=
((congr_arg _ (card_sylow_eq_index_normalizer P)).mp dvd_rfl).trans
(index_dvd_of_le le_normalizer)
#align card_sylow_dvd_index card_sylow_dvd_index
theorem not_dvd_index_sylow' [hp : Fact p.Prime] (P : Sylow p G) [(P : Subgroup G).Normal]
[fP : FiniteIndex (P : Subgroup G)] : ¬p ∣ (P : Subgroup G).index := by
intro h
letI : Fintype (G ⧸ (P : Subgroup G)) := (P : Subgroup G).fintypeQuotientOfFiniteIndex
rw [index_eq_card (P : Subgroup G)] at h
obtain ⟨x, hx⟩ := exists_prime_orderOf_dvd_card (G := G ⧸ (P : Subgroup G)) p h
have h := IsPGroup.of_card ((Fintype.card_zpowers.trans hx).trans (pow_one p).symm)
let Q := (zpowers x).comap (QuotientGroup.mk' (P : Subgroup G))
have hQ : IsPGroup p Q := by
apply h.comap_of_ker_isPGroup
rw [QuotientGroup.ker_mk']
exact P.2
replace hp := mt orderOf_eq_one_iff.mpr (ne_of_eq_of_ne hx hp.1.ne_one)
rw [← zpowers_eq_bot, ← Ne, ← bot_lt_iff_ne_bot, ←
comap_lt_comap_of_surjective (QuotientGroup.mk'_surjective _), MonoidHom.comap_bot,
QuotientGroup.ker_mk'] at hp
exact hp.ne' (P.3 hQ hp.le)
#align not_dvd_index_sylow' not_dvd_index_sylow'
theorem not_dvd_index_sylow [hp : Fact p.Prime] [Finite (Sylow p G)] (P : Sylow p G)
(hP : relindex ↑P (P : Subgroup G).normalizer ≠ 0) : ¬p ∣ (P : Subgroup G).index := by
cases nonempty_fintype (Sylow p G)
rw [← relindex_mul_index le_normalizer, ← card_sylow_eq_index_normalizer]
haveI : (P.subtype le_normalizer : Subgroup (P : Subgroup G).normalizer).Normal :=
Subgroup.normal_in_normalizer
haveI : FiniteIndex ↑(P.subtype le_normalizer : Subgroup (P : Subgroup G).normalizer) := ⟨hP⟩
replace hP := not_dvd_index_sylow' (P.subtype le_normalizer)
exact hp.1.not_dvd_mul hP (not_dvd_card_sylow p G)
#align not_dvd_index_sylow not_dvd_index_sylow
/-- **Frattini's Argument**: If `N` is a normal subgroup of `G`, and if `P` is a Sylow `p`-subgroup
of `N`, then `N_G(P) ⊔ N = G`. -/
theorem Sylow.normalizer_sup_eq_top {p : ℕ} [Fact p.Prime] {N : Subgroup G} [N.Normal]
[Finite (Sylow p N)] (P : Sylow p N) :
((↑P : Subgroup N).map N.subtype).normalizer ⊔ N = ⊤ := by
refine top_le_iff.mp fun g _ => ?_
obtain ⟨n, hn⟩ := exists_smul_eq N ((MulAut.conjNormal g : MulAut N) • P) P
rw [← inv_mul_cancel_left (↑n) g, sup_comm]
apply mul_mem_sup (N.inv_mem n.2)
rw [Sylow.smul_def, ← mul_smul, ← MulAut.conjNormal_val, ← MulAut.conjNormal.map_mul,
Sylow.ext_iff, Sylow.pointwise_smul_def, Subgroup.pointwise_smul_def] at hn
have : Function.Injective (MulAut.conj (n * g)).toMonoidHom := (MulAut.conj (n * g)).injective
refine fun x ↦ (mem_map_iff_mem this).symm.trans ?_
rw [map_map, ← congr_arg (map N.subtype) hn, map_map]
rfl
#align sylow.normalizer_sup_eq_top Sylow.normalizer_sup_eq_top
/-- **Frattini's Argument**: If `N` is a normal subgroup of `G`, and if `P` is a Sylow `p`-subgroup
of `N`, then `N_G(P) ⊔ N = G`. -/
theorem Sylow.normalizer_sup_eq_top' {p : ℕ} [Fact p.Prime] {N : Subgroup G} [N.Normal]
[Finite (Sylow p N)] (P : Sylow p G) (hP : ↑P ≤ N) : (P : Subgroup G).normalizer ⊔ N = ⊤ := by
rw [← Sylow.normalizer_sup_eq_top (P.subtype hP), P.coe_subtype, subgroupOf_map_subtype,
inf_of_le_left hP]
#align sylow.normalizer_sup_eq_top' Sylow.normalizer_sup_eq_top'
end InfiniteSylow
open Equiv Equiv.Perm Finset Function List QuotientGroup
universe u v w
variable {G : Type u} {α : Type v} {β : Type w} [Group G]
attribute [local instance 10] Subtype.fintype setFintype Classical.propDecidable
theorem QuotientGroup.card_preimage_mk [Fintype G] (s : Subgroup G) (t : Set (G ⧸ s)) :
Fintype.card (QuotientGroup.mk ⁻¹' t) = Fintype.card s * Fintype.card t := by
rw [← Fintype.card_prod, Fintype.card_congr (preimageMkEquivSubgroupProdSet _ _)]
#align quotient_group.card_preimage_mk QuotientGroup.card_preimage_mk
namespace Sylow
theorem mem_fixedPoints_mul_left_cosets_iff_mem_normalizer {H : Subgroup G} [Finite (H : Set G)]
{x : G} : (x : G ⧸ H) ∈ MulAction.fixedPoints H (G ⧸ H) ↔ x ∈ normalizer H :=
⟨fun hx =>
have ha : ∀ {y : G ⧸ H}, y ∈ orbit H (x : G ⧸ H) → y = x := mem_fixedPoints'.1 hx _
(inv_mem_iff (G := G)).1
(mem_normalizer_fintype fun n (hn : n ∈ H) =>
have : (n⁻¹ * x)⁻¹ * x ∈ H := QuotientGroup.eq.1 (ha ⟨⟨n⁻¹, inv_mem hn⟩, rfl⟩)
show _ ∈ H by
rw [mul_inv_rev, inv_inv] at this
convert this
rw [inv_inv]),
fun hx : ∀ n : G, n ∈ H ↔ x * n * x⁻¹ ∈ H =>
mem_fixedPoints'.2 fun y =>
Quotient.inductionOn' y fun y hy =>
QuotientGroup.eq.2
(let ⟨⟨b, hb₁⟩, hb₂⟩ := hy
have hb₂ : (b * x)⁻¹ * y ∈ H := QuotientGroup.eq.1 hb₂
(inv_mem_iff (G := G)).1 <|
(hx _).2 <|
(mul_mem_cancel_left (inv_mem hb₁)).1 <| by
rw [hx] at hb₂; simpa [mul_inv_rev, mul_assoc] using hb₂)⟩
#align sylow.mem_fixed_points_mul_left_cosets_iff_mem_normalizer Sylow.mem_fixedPoints_mul_left_cosets_iff_mem_normalizer
/-- The fixed points of the action of `H` on its cosets correspond to `normalizer H / H`. -/
def fixedPointsMulLeftCosetsEquivQuotient (H : Subgroup G) [Finite (H : Set G)] :
MulAction.fixedPoints H (G ⧸ H) ≃
normalizer H ⧸ Subgroup.comap ((normalizer H).subtype : normalizer H →* G) H :=
@subtypeQuotientEquivQuotientSubtype G (normalizer H : Set G) (_) (_)
(MulAction.fixedPoints H (G ⧸ H))
(fun a => (@mem_fixedPoints_mul_left_cosets_iff_mem_normalizer _ _ _ ‹_› _).symm)
(by
intros
unfold_projs
rw [leftRel_apply (α := normalizer H), leftRel_apply]
rfl)
#align sylow.fixed_points_mul_left_cosets_equiv_quotient Sylow.fixedPointsMulLeftCosetsEquivQuotient
/-- If `H` is a `p`-subgroup of `G`, then the index of `H` inside its normalizer is congruent
mod `p` to the index of `H`. -/
theorem card_quotient_normalizer_modEq_card_quotient [Fintype G] {p : ℕ} {n : ℕ} [hp : Fact p.Prime]
{H : Subgroup G} (hH : Fintype.card H = p ^ n) :
Fintype.card (normalizer H ⧸ Subgroup.comap ((normalizer H).subtype : normalizer H →* G) H) ≡
card (G ⧸ H) [MOD p] := by
rw [← Fintype.card_congr (fixedPointsMulLeftCosetsEquivQuotient H)]
exact ((IsPGroup.of_card hH).card_modEq_card_fixedPoints _).symm
#align sylow.card_quotient_normalizer_modeq_card_quotient Sylow.card_quotient_normalizer_modEq_card_quotient
/-- If `H` is a subgroup of `G` of cardinality `p ^ n`, then the cardinality of the
normalizer of `H` is congruent mod `p ^ (n + 1)` to the cardinality of `G`. -/
theorem card_normalizer_modEq_card [Fintype G] {p : ℕ} {n : ℕ} [hp : Fact p.Prime] {H : Subgroup G}
(hH : Fintype.card H = p ^ n) : card (normalizer H) ≡ card G [MOD p ^ (n + 1)] := by
have : H.subgroupOf (normalizer H) ≃ H := (subgroupOfEquivOfLe le_normalizer).toEquiv
simp only [← Nat.card_eq_fintype_card] at hH ⊢
rw [card_eq_card_quotient_mul_card_subgroup H,
card_eq_card_quotient_mul_card_subgroup (H.subgroupOf (normalizer H)), Nat.card_congr this,
hH, pow_succ']
simp only [Nat.card_eq_fintype_card] at hH ⊢
exact (card_quotient_normalizer_modEq_card_quotient hH).mul_right' _
#align sylow.card_normalizer_modeq_card Sylow.card_normalizer_modEq_card
/-- If `H` is a `p`-subgroup but not a Sylow `p`-subgroup, then `p` divides the
index of `H` inside its normalizer. -/
theorem prime_dvd_card_quotient_normalizer [Fintype G] {p : ℕ} {n : ℕ} [hp : Fact p.Prime]
(hdvd : p ^ (n + 1) ∣ card G) {H : Subgroup G} (hH : Fintype.card H = p ^ n) :
p ∣ card (normalizer H ⧸ Subgroup.comap ((normalizer H).subtype : normalizer H →* G) H) :=
let ⟨s, hs⟩ := exists_eq_mul_left_of_dvd hdvd
have hcard : card (G ⧸ H) = s * p :=
(mul_left_inj' (show card H ≠ 0 from Fintype.card_ne_zero)).1
(by
simp only [← Nat.card_eq_fintype_card] at hs hH ⊢
rw [← card_eq_card_quotient_mul_card_subgroup H, hH, hs, pow_succ', mul_assoc, mul_comm p])
have hm :
s * p % p =
card (normalizer H ⧸ Subgroup.comap ((normalizer H).subtype : normalizer H →* G) H) % p :=
hcard ▸ (card_quotient_normalizer_modEq_card_quotient hH).symm
Nat.dvd_of_mod_eq_zero (by rwa [Nat.mod_eq_zero_of_dvd (dvd_mul_left _ _), eq_comm] at hm)
#align sylow.prime_dvd_card_quotient_normalizer Sylow.prime_dvd_card_quotient_normalizer
/-- If `H` is a `p`-subgroup but not a Sylow `p`-subgroup of cardinality `p ^ n`,
then `p ^ (n + 1)` divides the cardinality of the normalizer of `H`. -/
theorem prime_pow_dvd_card_normalizer [Fintype G] {p : ℕ} {n : ℕ} [_hp : Fact p.Prime]
(hdvd : p ^ (n + 1) ∣ card G) {H : Subgroup G} (hH : Fintype.card H = p ^ n) :
p ^ (n + 1) ∣ card (normalizer H) :=
Nat.modEq_zero_iff_dvd.1 ((card_normalizer_modEq_card hH).trans hdvd.modEq_zero_nat)
#align sylow.prime_pow_dvd_card_normalizer Sylow.prime_pow_dvd_card_normalizer
/-- If `H` is a subgroup of `G` of cardinality `p ^ n`,
then `H` is contained in a subgroup of cardinality `p ^ (n + 1)`
if `p ^ (n + 1)` divides the cardinality of `G` -/
theorem exists_subgroup_card_pow_succ [Fintype G] {p : ℕ} {n : ℕ} [hp : Fact p.Prime]
(hdvd : p ^ (n + 1) ∣ card G) {H : Subgroup G} (hH : Fintype.card H = p ^ n) :
∃ K : Subgroup G, Fintype.card K = p ^ (n + 1) ∧ H ≤ K :=
let ⟨s, hs⟩ := exists_eq_mul_left_of_dvd hdvd
have hcard : card (G ⧸ H) = s * p :=
(mul_left_inj' (show card H ≠ 0 from Fintype.card_ne_zero)).1
(by
simp only [← Nat.card_eq_fintype_card] at hs hH ⊢
rw [← card_eq_card_quotient_mul_card_subgroup H, hH, hs, pow_succ', mul_assoc, mul_comm p])
have hm : s * p % p = card (normalizer H ⧸ H.subgroupOf H.normalizer) % p :=
Fintype.card_congr (fixedPointsMulLeftCosetsEquivQuotient H) ▸
hcard ▸ (IsPGroup.of_card hH).card_modEq_card_fixedPoints _
have hm' : p ∣ card (normalizer H ⧸ H.subgroupOf H.normalizer) :=
Nat.dvd_of_mod_eq_zero (by rwa [Nat.mod_eq_zero_of_dvd (dvd_mul_left _ _), eq_comm] at hm)
let ⟨x, hx⟩ := @exists_prime_orderOf_dvd_card _ (QuotientGroup.Quotient.group _) _ _ hp hm'
have hequiv : H ≃ H.subgroupOf H.normalizer := (subgroupOfEquivOfLe le_normalizer).symm.toEquiv
⟨Subgroup.map (normalizer H).subtype
(Subgroup.comap (mk' (H.subgroupOf H.normalizer)) (zpowers x)), by
show Fintype.card (Subgroup.map H.normalizer.subtype
(comap (mk' (H.subgroupOf H.normalizer)) (Subgroup.zpowers x))) = p ^ (n + 1)
suffices Fintype.card (Subtype.val ''
(Subgroup.comap (mk' (H.subgroupOf H.normalizer)) (zpowers x) : Set H.normalizer)) =
p ^ (n + 1)
by convert this using 2
rw [Set.card_image_of_injective
(Subgroup.comap (mk' (H.subgroupOf H.normalizer)) (zpowers x) : Set H.normalizer)
Subtype.val_injective,
pow_succ, ← hH, Fintype.card_congr hequiv, ← hx, ← Fintype.card_zpowers, ←
Fintype.card_prod]
exact @Fintype.card_congr _ _ (_) (_)
(preimageMkEquivSubgroupProdSet (H.subgroupOf H.normalizer) (zpowers x)), by
intro y hy
simp only [exists_prop, Subgroup.coeSubtype, mk'_apply, Subgroup.mem_map, Subgroup.mem_comap]
refine ⟨⟨y, le_normalizer hy⟩, ⟨0, ?_⟩, rfl⟩
dsimp only
rw [zpow_zero, eq_comm, QuotientGroup.eq_one_iff]
simpa using hy⟩
#align sylow.exists_subgroup_card_pow_succ Sylow.exists_subgroup_card_pow_succ
/-- If `H` is a subgroup of `G` of cardinality `p ^ n`,
then `H` is contained in a subgroup of cardinality `p ^ m`
if `n ≤ m` and `p ^ m` divides the cardinality of `G` -/
theorem exists_subgroup_card_pow_prime_le [Fintype G] (p : ℕ) :
∀ {n m : ℕ} [_hp : Fact p.Prime] (_hdvd : p ^ m ∣ card G) (H : Subgroup G)
(_hH : card H = p ^ n) (_hnm : n ≤ m), ∃ K : Subgroup G, card K = p ^ m ∧ H ≤ K
| n, m => fun {hdvd H hH hnm} =>
(lt_or_eq_of_le hnm).elim
(fun hnm : n < m =>
have h0m : 0 < m := lt_of_le_of_lt n.zero_le hnm
have _wf : m - 1 < m := Nat.sub_lt h0m zero_lt_one
have hnm1 : n ≤ m - 1 := le_tsub_of_add_le_right hnm
let ⟨K, hK⟩ :=
@exists_subgroup_card_pow_prime_le _ _ n (m - 1) _
(Nat.pow_dvd_of_le_of_pow_dvd tsub_le_self hdvd) H hH hnm1
have hdvd' : p ^ (m - 1 + 1) ∣ card G := by rwa [tsub_add_cancel_of_le h0m.nat_succ_le]
let ⟨K', hK'⟩ := @exists_subgroup_card_pow_succ _ _ _ _ _ _ hdvd' K hK.1
⟨K', by rw [hK'.1, tsub_add_cancel_of_le h0m.nat_succ_le], le_trans hK.2 hK'.2⟩)
fun hnm : n = m => ⟨H, by simp [hH, hnm]⟩
#align sylow.exists_subgroup_card_pow_prime_le Sylow.exists_subgroup_card_pow_prime_le
/-- A generalisation of **Sylow's first theorem**. If `p ^ n` divides
the cardinality of `G`, then there is a subgroup of cardinality `p ^ n` -/
theorem exists_subgroup_card_pow_prime [Fintype G] (p : ℕ) {n : ℕ} [Fact p.Prime]
(hdvd : p ^ n ∣ card G) : ∃ K : Subgroup G, Fintype.card K = p ^ n :=
let ⟨K, hK⟩ := exists_subgroup_card_pow_prime_le p hdvd ⊥
-- The @ is due to a Fintype ⊥ mismatch, but this will be fixed once we convert to Nat.card
(by rw [← @Nat.card_eq_fintype_card, card_bot, pow_zero]) n.zero_le
⟨K, hK.1⟩
#align sylow.exists_subgroup_card_pow_prime Sylow.exists_subgroup_card_pow_prime
/-- A special case of **Sylow's first theorem**. If `G` is a `p`-group of size at least `p ^ n`
then there is a subgroup of cardinality `p ^ n`. -/
lemma exists_subgroup_card_pow_prime_of_le_card {n p : ℕ} (hp : p.Prime) (h : IsPGroup p G)
(hn : p ^ n ≤ Nat.card G) : ∃ H : Subgroup G, Nat.card H = p ^ n := by
have : Fact p.Prime := ⟨hp⟩
have : Finite G := Nat.finite_of_card_ne_zero <| by linarith [Nat.one_le_pow n p hp.pos]
cases nonempty_fintype G
obtain ⟨m, hm⟩ := h.exists_card_eq
simp_rw [Nat.card_eq_fintype_card] at hm hn ⊢
refine exists_subgroup_card_pow_prime _ ?_
rw [hm] at hn ⊢
exact pow_dvd_pow _ <| (pow_le_pow_iff_right hp.one_lt).1 hn
/-- A special case of **Sylow's first theorem**. If `G` is a `p`-group and `H` a subgroup of size at
least `p ^ n` then there is a subgroup of `H` of cardinality `p ^ n`. -/
lemma exists_subgroup_le_card_pow_prime_of_le_card {n p : ℕ} (hp : p.Prime) (h : IsPGroup p G)
{H : Subgroup G} (hn : p ^ n ≤ Nat.card H) : ∃ H' ≤ H, Nat.card H' = p ^ n := by
obtain ⟨H', H'card⟩ := exists_subgroup_card_pow_prime_of_le_card hp (h.to_subgroup H) hn
refine ⟨H'.map H.subtype, map_subtype_le _, ?_⟩
rw [← H'card]
let e : H' ≃* H'.map H.subtype := H'.equivMapOfInjective (Subgroup.subtype H) H.subtype_injective
exact Nat.card_congr e.symm.toEquiv
/-- A special case of **Sylow's first theorem**. If `G` is a `p`-group and `H` a subgroup of size at
least `k` then there is a subgroup of `H` of cardinality between `k / p` and `k`. -/
lemma exists_subgroup_le_card_le {k p : ℕ} (hp : p.Prime) (h : IsPGroup p G) {H : Subgroup G}
(hk : k ≤ Nat.card H) (hk₀ : k ≠ 0) : ∃ H' ≤ H, Nat.card H' ≤ k ∧ k < p * Nat.card H' := by
obtain ⟨m, hmk, hkm⟩ : ∃ s, p ^ s ≤ k ∧ k < p ^ (s + 1) :=
exists_nat_pow_near (Nat.one_le_iff_ne_zero.2 hk₀) hp.one_lt
obtain ⟨H', H'H, H'card⟩ := exists_subgroup_le_card_pow_prime_of_le_card hp h (hmk.trans hk)
refine ⟨H', H'H, ?_⟩
simpa only [pow_succ', H'card] using And.intro hmk hkm
theorem pow_dvd_card_of_pow_dvd_card [Fintype G] {p n : ℕ} [hp : Fact p.Prime] (P : Sylow p G)
(hdvd : p ^ n ∣ card G) : p ^ n ∣ card P :=
(hp.1.coprime_pow_of_not_dvd
(not_dvd_index_sylow P index_ne_zero_of_finite)).symm.dvd_of_dvd_mul_left
((index_mul_card P.1).symm ▸ hdvd)
#align sylow.pow_dvd_card_of_pow_dvd_card Sylow.pow_dvd_card_of_pow_dvd_card
| Mathlib/GroupTheory/Sylow.lean | 698 | 702 | theorem dvd_card_of_dvd_card [Fintype G] {p : ℕ} [Fact p.Prime] (P : Sylow p G)
(hdvd : p ∣ card G) : p ∣ card P := by |
rw [← pow_one p] at hdvd
have key := P.pow_dvd_card_of_pow_dvd_card hdvd
rwa [pow_one] at key
|
/-
Copyright (c) 2018 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Johannes Hölzl
-/
import Mathlib.Topology.UniformSpace.UniformConvergence
import Mathlib.Topology.UniformSpace.UniformEmbedding
import Mathlib.Topology.UniformSpace.CompleteSeparated
import Mathlib.Topology.UniformSpace.Compact
import Mathlib.Topology.Algebra.Group.Basic
import Mathlib.Topology.DiscreteSubset
import Mathlib.Tactic.Abel
#align_import topology.algebra.uniform_group from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Uniform structure on topological groups
This file defines uniform groups and its additive counterpart. These typeclasses should be
preferred over using `[TopologicalSpace α] [TopologicalGroup α]` since every topological
group naturally induces a uniform structure.
## Main declarations
* `UniformGroup` and `UniformAddGroup`: Multiplicative and additive uniform groups, that
i.e., groups with uniformly continuous `(*)` and `(⁻¹)` / `(+)` and `(-)`.
## Main results
* `TopologicalAddGroup.toUniformSpace` and `comm_topologicalAddGroup_is_uniform` can be used
to construct a canonical uniformity for a topological add group.
* extension of ℤ-bilinear maps to complete groups (useful for ring completions)
* `QuotientGroup.completeSpace` and `QuotientAddGroup.completeSpace` guarantee that quotients
of first countable topological groups by normal subgroups are themselves complete. In particular,
the quotient of a Banach space by a subspace is complete.
-/
noncomputable section
open scoped Classical
open Uniformity Topology Filter Pointwise
section UniformGroup
open Filter Set
variable {α : Type*} {β : Type*}
/-- A uniform group is a group in which multiplication and inversion are uniformly continuous. -/
class UniformGroup (α : Type*) [UniformSpace α] [Group α] : Prop where
uniformContinuous_div : UniformContinuous fun p : α × α => p.1 / p.2
#align uniform_group UniformGroup
/-- A uniform additive group is an additive group in which addition
and negation are uniformly continuous. -/
class UniformAddGroup (α : Type*) [UniformSpace α] [AddGroup α] : Prop where
uniformContinuous_sub : UniformContinuous fun p : α × α => p.1 - p.2
#align uniform_add_group UniformAddGroup
attribute [to_additive] UniformGroup
@[to_additive]
theorem UniformGroup.mk' {α} [UniformSpace α] [Group α]
(h₁ : UniformContinuous fun p : α × α => p.1 * p.2) (h₂ : UniformContinuous fun p : α => p⁻¹) :
UniformGroup α :=
⟨by simpa only [div_eq_mul_inv] using
h₁.comp (uniformContinuous_fst.prod_mk (h₂.comp uniformContinuous_snd))⟩
#align uniform_group.mk' UniformGroup.mk'
#align uniform_add_group.mk' UniformAddGroup.mk'
variable [UniformSpace α] [Group α] [UniformGroup α]
@[to_additive]
theorem uniformContinuous_div : UniformContinuous fun p : α × α => p.1 / p.2 :=
UniformGroup.uniformContinuous_div
#align uniform_continuous_div uniformContinuous_div
#align uniform_continuous_sub uniformContinuous_sub
@[to_additive]
theorem UniformContinuous.div [UniformSpace β] {f : β → α} {g : β → α} (hf : UniformContinuous f)
(hg : UniformContinuous g) : UniformContinuous fun x => f x / g x :=
uniformContinuous_div.comp (hf.prod_mk hg)
#align uniform_continuous.div UniformContinuous.div
#align uniform_continuous.sub UniformContinuous.sub
@[to_additive]
theorem UniformContinuous.inv [UniformSpace β] {f : β → α} (hf : UniformContinuous f) :
UniformContinuous fun x => (f x)⁻¹ := by
have : UniformContinuous fun x => 1 / f x := uniformContinuous_const.div hf
simp_all
#align uniform_continuous.inv UniformContinuous.inv
#align uniform_continuous.neg UniformContinuous.neg
@[to_additive]
theorem uniformContinuous_inv : UniformContinuous fun x : α => x⁻¹ :=
uniformContinuous_id.inv
#align uniform_continuous_inv uniformContinuous_inv
#align uniform_continuous_neg uniformContinuous_neg
@[to_additive]
theorem UniformContinuous.mul [UniformSpace β] {f : β → α} {g : β → α} (hf : UniformContinuous f)
(hg : UniformContinuous g) : UniformContinuous fun x => f x * g x := by
have : UniformContinuous fun x => f x / (g x)⁻¹ := hf.div hg.inv
simp_all
#align uniform_continuous.mul UniformContinuous.mul
#align uniform_continuous.add UniformContinuous.add
@[to_additive]
theorem uniformContinuous_mul : UniformContinuous fun p : α × α => p.1 * p.2 :=
uniformContinuous_fst.mul uniformContinuous_snd
#align uniform_continuous_mul uniformContinuous_mul
#align uniform_continuous_add uniformContinuous_add
@[to_additive UniformContinuous.const_nsmul]
theorem UniformContinuous.pow_const [UniformSpace β] {f : β → α} (hf : UniformContinuous f) :
∀ n : ℕ, UniformContinuous fun x => f x ^ n
| 0 => by
simp_rw [pow_zero]
exact uniformContinuous_const
| n + 1 => by
simp_rw [pow_succ']
exact hf.mul (hf.pow_const n)
#align uniform_continuous.pow_const UniformContinuous.pow_const
#align uniform_continuous.const_nsmul UniformContinuous.const_nsmul
@[to_additive uniformContinuous_const_nsmul]
theorem uniformContinuous_pow_const (n : ℕ) : UniformContinuous fun x : α => x ^ n :=
uniformContinuous_id.pow_const n
#align uniform_continuous_pow_const uniformContinuous_pow_const
#align uniform_continuous_const_nsmul uniformContinuous_const_nsmul
@[to_additive UniformContinuous.const_zsmul]
theorem UniformContinuous.zpow_const [UniformSpace β] {f : β → α} (hf : UniformContinuous f) :
∀ n : ℤ, UniformContinuous fun x => f x ^ n
| (n : ℕ) => by
simp_rw [zpow_natCast]
exact hf.pow_const _
| Int.negSucc n => by
simp_rw [zpow_negSucc]
exact (hf.pow_const _).inv
#align uniform_continuous.zpow_const UniformContinuous.zpow_const
#align uniform_continuous.const_zsmul UniformContinuous.const_zsmul
@[to_additive uniformContinuous_const_zsmul]
theorem uniformContinuous_zpow_const (n : ℤ) : UniformContinuous fun x : α => x ^ n :=
uniformContinuous_id.zpow_const n
#align uniform_continuous_zpow_const uniformContinuous_zpow_const
#align uniform_continuous_const_zsmul uniformContinuous_const_zsmul
@[to_additive]
instance (priority := 10) UniformGroup.to_topologicalGroup : TopologicalGroup α where
continuous_mul := uniformContinuous_mul.continuous
continuous_inv := uniformContinuous_inv.continuous
#align uniform_group.to_topological_group UniformGroup.to_topologicalGroup
#align uniform_add_group.to_topological_add_group UniformAddGroup.to_topologicalAddGroup
@[to_additive]
instance [UniformSpace β] [Group β] [UniformGroup β] : UniformGroup (α × β) :=
⟨((uniformContinuous_fst.comp uniformContinuous_fst).div
(uniformContinuous_fst.comp uniformContinuous_snd)).prod_mk
((uniformContinuous_snd.comp uniformContinuous_fst).div
(uniformContinuous_snd.comp uniformContinuous_snd))⟩
@[to_additive]
instance Pi.instUniformGroup {ι : Type*} {G : ι → Type*} [∀ i, UniformSpace (G i)]
[∀ i, Group (G i)] [∀ i, UniformGroup (G i)] : UniformGroup (∀ i, G i) where
uniformContinuous_div := uniformContinuous_pi.mpr fun i ↦
(uniformContinuous_proj G i).comp uniformContinuous_fst |>.div <|
(uniformContinuous_proj G i).comp uniformContinuous_snd
@[to_additive]
theorem uniformity_translate_mul (a : α) : ((𝓤 α).map fun x : α × α => (x.1 * a, x.2 * a)) = 𝓤 α :=
le_antisymm (uniformContinuous_id.mul uniformContinuous_const)
(calc
𝓤 α =
((𝓤 α).map fun x : α × α => (x.1 * a⁻¹, x.2 * a⁻¹)).map fun x : α × α =>
(x.1 * a, x.2 * a) := by simp [Filter.map_map, (· ∘ ·)]
_ ≤ (𝓤 α).map fun x : α × α => (x.1 * a, x.2 * a) :=
Filter.map_mono (uniformContinuous_id.mul uniformContinuous_const)
)
#align uniformity_translate_mul uniformity_translate_mul
#align uniformity_translate_add uniformity_translate_add
@[to_additive]
theorem uniformEmbedding_translate_mul (a : α) : UniformEmbedding fun x : α => x * a :=
{ comap_uniformity := by
nth_rw 1 [← uniformity_translate_mul a, comap_map]
rintro ⟨p₁, p₂⟩ ⟨q₁, q₂⟩
simp only [Prod.mk.injEq, mul_left_inj, imp_self]
inj := mul_left_injective a }
#align uniform_embedding_translate_mul uniformEmbedding_translate_mul
#align uniform_embedding_translate_add uniformEmbedding_translate_add
namespace MulOpposite
@[to_additive]
instance : UniformGroup αᵐᵒᵖ :=
⟨uniformContinuous_op.comp
((uniformContinuous_unop.comp uniformContinuous_snd).inv.mul <|
uniformContinuous_unop.comp uniformContinuous_fst)⟩
end MulOpposite
section LatticeOps
variable [Group β]
@[to_additive]
theorem uniformGroup_sInf {us : Set (UniformSpace β)} (h : ∀ u ∈ us, @UniformGroup β u _) :
@UniformGroup β (sInf us) _ :=
-- Porting note: {_} does not find `sInf us` instance, see `continuousSMul_sInf`
@UniformGroup.mk β (_) _ <|
uniformContinuous_sInf_rng.mpr fun u hu =>
uniformContinuous_sInf_dom₂ hu hu (@UniformGroup.uniformContinuous_div β u _ (h u hu))
#align uniform_group_Inf uniformGroup_sInf
#align uniform_add_group_Inf uniformAddGroup_sInf
@[to_additive]
theorem uniformGroup_iInf {ι : Sort*} {us' : ι → UniformSpace β}
(h' : ∀ i, @UniformGroup β (us' i) _) : @UniformGroup β (⨅ i, us' i) _ := by
rw [← sInf_range]
exact uniformGroup_sInf (Set.forall_mem_range.mpr h')
#align uniform_group_infi uniformGroup_iInf
#align uniform_add_group_infi uniformAddGroup_iInf
@[to_additive]
| Mathlib/Topology/Algebra/UniformGroup.lean | 229 | 233 | theorem uniformGroup_inf {u₁ u₂ : UniformSpace β} (h₁ : @UniformGroup β u₁ _)
(h₂ : @UniformGroup β u₂ _) : @UniformGroup β (u₁ ⊓ u₂) _ := by |
rw [inf_eq_iInf]
refine uniformGroup_iInf fun b => ?_
cases b <;> assumption
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jan-David Salchow, Sébastien Gouëzel, Jean Lo, Yury Kudryashov, Frédéric Dupuis,
Heather Macbeth
-/
import Mathlib.Topology.Algebra.Ring.Basic
import Mathlib.Topology.Algebra.MulAction
import Mathlib.Topology.Algebra.UniformGroup
import Mathlib.Topology.ContinuousFunction.Basic
import Mathlib.Topology.UniformSpace.UniformEmbedding
import Mathlib.Algebra.Algebra.Defs
import Mathlib.LinearAlgebra.Projection
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Finsupp
#align_import topology.algebra.module.basic from "leanprover-community/mathlib"@"6285167a053ad0990fc88e56c48ccd9fae6550eb"
/-!
# Theory of topological modules and continuous linear maps.
We use the class `ContinuousSMul` for topological (semi) modules and topological vector spaces.
In this file we define continuous (semi-)linear maps, as semilinear maps between topological
modules which are continuous. The set of continuous semilinear maps between the topological
`R₁`-module `M` and `R₂`-module `M₂` with respect to the `RingHom` `σ` is denoted by `M →SL[σ] M₂`.
Plain linear maps are denoted by `M →L[R] M₂` and star-linear maps by `M →L⋆[R] M₂`.
The corresponding notation for equivalences is `M ≃SL[σ] M₂`, `M ≃L[R] M₂` and `M ≃L⋆[R] M₂`.
-/
open LinearMap (ker range)
open Topology Filter Pointwise
universe u v w u'
section
variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M]
[AddCommGroup M] [Module R M]
theorem ContinuousSMul.of_nhds_zero [TopologicalRing R] [TopologicalAddGroup M]
(hmul : Tendsto (fun p : R × M => p.1 • p.2) (𝓝 0 ×ˢ 𝓝 0) (𝓝 0))
(hmulleft : ∀ m : M, Tendsto (fun a : R => a • m) (𝓝 0) (𝓝 0))
(hmulright : ∀ a : R, Tendsto (fun m : M => a • m) (𝓝 0) (𝓝 0)) : ContinuousSMul R M where
continuous_smul := by
refine continuous_of_continuousAt_zero₂ (AddMonoidHom.smul : R →+ M →+ M) ?_ ?_ ?_ <;>
simpa [ContinuousAt, nhds_prod_eq]
#align has_continuous_smul.of_nhds_zero ContinuousSMul.of_nhds_zero
end
section
variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M]
[AddCommGroup M] [ContinuousAdd M] [Module R M] [ContinuousSMul R M]
/-- If `M` is a topological module over `R` and `0` is a limit of invertible elements of `R`, then
`⊤` is the only submodule of `M` with a nonempty interior.
This is the case, e.g., if `R` is a nontrivially normed field. -/
theorem Submodule.eq_top_of_nonempty_interior' [NeBot (𝓝[{ x : R | IsUnit x }] 0)]
(s : Submodule R M) (hs : (interior (s : Set M)).Nonempty) : s = ⊤ := by
rcases hs with ⟨y, hy⟩
refine Submodule.eq_top_iff'.2 fun x => ?_
rw [mem_interior_iff_mem_nhds] at hy
have : Tendsto (fun c : R => y + c • x) (𝓝[{ x : R | IsUnit x }] 0) (𝓝 (y + (0 : R) • x)) :=
tendsto_const_nhds.add ((tendsto_nhdsWithin_of_tendsto_nhds tendsto_id).smul tendsto_const_nhds)
rw [zero_smul, add_zero] at this
obtain ⟨_, hu : y + _ • _ ∈ s, u, rfl⟩ :=
nonempty_of_mem (inter_mem (Filter.mem_map.1 (this hy)) self_mem_nhdsWithin)
have hy' : y ∈ ↑s := mem_of_mem_nhds hy
rwa [s.add_mem_iff_right hy', ← Units.smul_def, s.smul_mem_iff' u] at hu
#align submodule.eq_top_of_nonempty_interior' Submodule.eq_top_of_nonempty_interior'
variable (R M)
/-- Let `R` be a topological ring such that zero is not an isolated point (e.g., a nontrivially
normed field, see `NormedField.punctured_nhds_neBot`). Let `M` be a nontrivial module over `R`
such that `c • x = 0` implies `c = 0 ∨ x = 0`. Then `M` has no isolated points. We formulate this
using `NeBot (𝓝[≠] x)`.
This lemma is not an instance because Lean would need to find `[ContinuousSMul ?m_1 M]` with
unknown `?m_1`. We register this as an instance for `R = ℝ` in `Real.punctured_nhds_module_neBot`.
One can also use `haveI := Module.punctured_nhds_neBot R M` in a proof.
-/
theorem Module.punctured_nhds_neBot [Nontrivial M] [NeBot (𝓝[≠] (0 : R))] [NoZeroSMulDivisors R M]
(x : M) : NeBot (𝓝[≠] x) := by
rcases exists_ne (0 : M) with ⟨y, hy⟩
suffices Tendsto (fun c : R => x + c • y) (𝓝[≠] 0) (𝓝[≠] x) from this.neBot
refine Tendsto.inf ?_ (tendsto_principal_principal.2 <| ?_)
· convert tendsto_const_nhds.add ((@tendsto_id R _).smul_const y)
rw [zero_smul, add_zero]
· intro c hc
simpa [hy] using hc
#align module.punctured_nhds_ne_bot Module.punctured_nhds_neBot
end
section LatticeOps
variable {ι R M₁ M₂ : Type*} [Semiring R] [AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁]
[Module R M₂] [u : TopologicalSpace R] {t : TopologicalSpace M₂} [ContinuousSMul R M₂]
(f : M₁ →ₗ[R] M₂)
theorem continuousSMul_induced : @ContinuousSMul R M₁ _ u (t.induced f) :=
let _ : TopologicalSpace M₁ := t.induced f
Inducing.continuousSMul ⟨rfl⟩ continuous_id (map_smul f _ _)
#align has_continuous_smul_induced continuousSMul_induced
end LatticeOps
/-- The span of a separable subset with respect to a separable scalar ring is again separable. -/
lemma TopologicalSpace.IsSeparable.span {R M : Type*} [AddCommMonoid M] [Semiring R] [Module R M]
[TopologicalSpace M] [TopologicalSpace R] [SeparableSpace R]
[ContinuousAdd M] [ContinuousSMul R M] {s : Set M} (hs : IsSeparable s) :
IsSeparable (Submodule.span R s : Set M) := by
rw [span_eq_iUnion_nat]
refine .iUnion fun n ↦ .image ?_ ?_
· have : IsSeparable {f : Fin n → R × M | ∀ (i : Fin n), f i ∈ Set.univ ×ˢ s} := by
apply isSeparable_pi (fun i ↦ .prod (.of_separableSpace Set.univ) hs)
rwa [Set.univ_prod] at this
· apply continuous_finset_sum _ (fun i _ ↦ ?_)
exact (continuous_fst.comp (continuous_apply i)).smul (continuous_snd.comp (continuous_apply i))
namespace Submodule
variable {α β : Type*} [TopologicalSpace β]
#align submodule.has_continuous_smul SMulMemClass.continuousSMul
instance topologicalAddGroup [Ring α] [AddCommGroup β] [Module α β] [TopologicalAddGroup β]
(S : Submodule α β) : TopologicalAddGroup S :=
inferInstanceAs (TopologicalAddGroup S.toAddSubgroup)
#align submodule.topological_add_group Submodule.topologicalAddGroup
end Submodule
section closure
variable {R R' : Type u} {M M' : Type v} [Semiring R] [Ring R']
[TopologicalSpace M] [AddCommMonoid M] [TopologicalSpace M'] [AddCommGroup M'] [Module R M]
[ContinuousConstSMul R M] [Module R' M'] [ContinuousConstSMul R' M']
theorem Submodule.mapsTo_smul_closure (s : Submodule R M) (c : R) :
Set.MapsTo (c • ·) (closure s : Set M) (closure s) :=
have : Set.MapsTo (c • ·) (s : Set M) s := fun _ h ↦ s.smul_mem c h
this.closure (continuous_const_smul c)
theorem Submodule.smul_closure_subset (s : Submodule R M) (c : R) :
c • closure (s : Set M) ⊆ closure (s : Set M) :=
(s.mapsTo_smul_closure c).image_subset
variable [ContinuousAdd M]
/-- The (topological-space) closure of a submodule of a topological `R`-module `M` is itself
a submodule. -/
def Submodule.topologicalClosure (s : Submodule R M) : Submodule R M :=
{ s.toAddSubmonoid.topologicalClosure with
smul_mem' := s.mapsTo_smul_closure }
#align submodule.topological_closure Submodule.topologicalClosure
@[simp]
theorem Submodule.topologicalClosure_coe (s : Submodule R M) :
(s.topologicalClosure : Set M) = closure (s : Set M) :=
rfl
#align submodule.topological_closure_coe Submodule.topologicalClosure_coe
theorem Submodule.le_topologicalClosure (s : Submodule R M) : s ≤ s.topologicalClosure :=
subset_closure
#align submodule.le_topological_closure Submodule.le_topologicalClosure
theorem Submodule.closure_subset_topologicalClosure_span (s : Set M) :
closure s ⊆ (span R s).topologicalClosure := by
rw [Submodule.topologicalClosure_coe]
exact closure_mono subset_span
theorem Submodule.isClosed_topologicalClosure (s : Submodule R M) :
IsClosed (s.topologicalClosure : Set M) := isClosed_closure
#align submodule.is_closed_topological_closure Submodule.isClosed_topologicalClosure
theorem Submodule.topologicalClosure_minimal (s : Submodule R M) {t : Submodule R M} (h : s ≤ t)
(ht : IsClosed (t : Set M)) : s.topologicalClosure ≤ t :=
closure_minimal h ht
#align submodule.topological_closure_minimal Submodule.topologicalClosure_minimal
theorem Submodule.topologicalClosure_mono {s : Submodule R M} {t : Submodule R M} (h : s ≤ t) :
s.topologicalClosure ≤ t.topologicalClosure :=
closure_mono h
#align submodule.topological_closure_mono Submodule.topologicalClosure_mono
/-- The topological closure of a closed submodule `s` is equal to `s`. -/
theorem IsClosed.submodule_topologicalClosure_eq {s : Submodule R M} (hs : IsClosed (s : Set M)) :
s.topologicalClosure = s :=
SetLike.ext' hs.closure_eq
#align is_closed.submodule_topological_closure_eq IsClosed.submodule_topologicalClosure_eq
/-- A subspace is dense iff its topological closure is the entire space. -/
theorem Submodule.dense_iff_topologicalClosure_eq_top {s : Submodule R M} :
Dense (s : Set M) ↔ s.topologicalClosure = ⊤ := by
rw [← SetLike.coe_set_eq, dense_iff_closure_eq]
simp
#align submodule.dense_iff_topological_closure_eq_top Submodule.dense_iff_topologicalClosure_eq_top
instance Submodule.topologicalClosure.completeSpace {M' : Type*} [AddCommMonoid M'] [Module R M']
[UniformSpace M'] [ContinuousAdd M'] [ContinuousConstSMul R M'] [CompleteSpace M']
(U : Submodule R M') : CompleteSpace U.topologicalClosure :=
isClosed_closure.completeSpace_coe
#align submodule.topological_closure.complete_space Submodule.topologicalClosure.completeSpace
/-- A maximal proper subspace of a topological module (i.e a `Submodule` satisfying `IsCoatom`)
is either closed or dense. -/
theorem Submodule.isClosed_or_dense_of_isCoatom (s : Submodule R M) (hs : IsCoatom s) :
IsClosed (s : Set M) ∨ Dense (s : Set M) := by
refine (hs.le_iff.mp s.le_topologicalClosure).symm.imp ?_ dense_iff_topologicalClosure_eq_top.mpr
exact fun h ↦ h ▸ isClosed_closure
#align submodule.is_closed_or_dense_of_is_coatom Submodule.isClosed_or_dense_of_isCoatom
end closure
section Pi
theorem LinearMap.continuous_on_pi {ι : Type*} {R : Type*} {M : Type*} [Finite ι] [Semiring R]
[TopologicalSpace R] [AddCommMonoid M] [Module R M] [TopologicalSpace M] [ContinuousAdd M]
[ContinuousSMul R M] (f : (ι → R) →ₗ[R] M) : Continuous f := by
cases nonempty_fintype ι
classical
-- for the proof, write `f` in the standard basis, and use that each coordinate is a continuous
-- function.
have : (f : (ι → R) → M) = fun x => ∑ i : ι, x i • f fun j => if i = j then 1 else 0 := by
ext x
exact f.pi_apply_eq_sum_univ x
rw [this]
refine continuous_finset_sum _ fun i _ => ?_
exact (continuous_apply i).smul continuous_const
#align linear_map.continuous_on_pi LinearMap.continuous_on_pi
end Pi
/-- Continuous linear maps between modules. We only put the type classes that are necessary for the
definition, although in applications `M` and `M₂` will be topological modules over the topological
ring `R`. -/
structure ContinuousLinearMap {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
(M : Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : Type*) [TopologicalSpace M₂]
[AddCommMonoid M₂] [Module R M] [Module S M₂] extends M →ₛₗ[σ] M₂ where
cont : Continuous toFun := by continuity
#align continuous_linear_map ContinuousLinearMap
attribute [inherit_doc ContinuousLinearMap] ContinuousLinearMap.cont
@[inherit_doc]
notation:25 M " →SL[" σ "] " M₂ => ContinuousLinearMap σ M M₂
@[inherit_doc]
notation:25 M " →L[" R "] " M₂ => ContinuousLinearMap (RingHom.id R) M M₂
@[inherit_doc]
notation:25 M " →L⋆[" R "] " M₂ => ContinuousLinearMap (starRingEnd R) M M₂
/-- `ContinuousSemilinearMapClass F σ M M₂` asserts `F` is a type of bundled continuous
`σ`-semilinear maps `M → M₂`. See also `ContinuousLinearMapClass 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 ContinuousSemilinearMapClass (F : Type*) {R S : outParam Type*} [Semiring R] [Semiring S]
(σ : outParam <| R →+* S) (M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M]
(M₂ : outParam Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] [FunLike F M M₂]
extends SemilinearMapClass F σ M M₂, ContinuousMapClass F M M₂ : Prop
#align continuous_semilinear_map_class ContinuousSemilinearMapClass
-- `σ`, `R` and `S` become metavariables, but they are all outparams so it's OK
-- Porting note(#12094): removed nolint; dangerous_instance linter not ported yet
-- attribute [nolint dangerous_instance] ContinuousSemilinearMapClass.toContinuousMapClass
/-- `ContinuousLinearMapClass F R M M₂` asserts `F` is a type of bundled continuous
`R`-linear maps `M → M₂`. This is an abbreviation for
`ContinuousSemilinearMapClass F (RingHom.id R) M M₂`. -/
abbrev ContinuousLinearMapClass (F : Type*) (R : outParam Type*) [Semiring R]
(M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : outParam Type*)
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M] [Module R M₂] [FunLike F M M₂] :=
ContinuousSemilinearMapClass F (RingHom.id R) M M₂
#align continuous_linear_map_class ContinuousLinearMapClass
/-- Continuous linear equivalences between modules. We only put the type classes that are necessary
for the definition, although in applications `M` and `M₂` will be topological modules over the
topological semiring `R`. -/
-- Porting note (#5171): linter not ported yet; was @[nolint has_nonempty_instance]
structure ContinuousLinearEquiv {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : Type*) [TopologicalSpace M]
[AddCommMonoid M] (M₂ : Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] extends M ≃ₛₗ[σ] M₂ where
continuous_toFun : Continuous toFun := by continuity
continuous_invFun : Continuous invFun := by continuity
#align continuous_linear_equiv ContinuousLinearEquiv
attribute [inherit_doc ContinuousLinearEquiv] ContinuousLinearEquiv.continuous_toFun
ContinuousLinearEquiv.continuous_invFun
@[inherit_doc]
notation:50 M " ≃SL[" σ "] " M₂ => ContinuousLinearEquiv σ M M₂
@[inherit_doc]
notation:50 M " ≃L[" R "] " M₂ => ContinuousLinearEquiv (RingHom.id R) M M₂
@[inherit_doc]
notation:50 M " ≃L⋆[" R "] " M₂ => ContinuousLinearEquiv (starRingEnd R) M M₂
/-- `ContinuousSemilinearEquivClass F σ M M₂` asserts `F` is a type of bundled continuous
`σ`-semilinear equivs `M → M₂`. See also `ContinuousLinearEquivClass 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 ContinuousSemilinearEquivClass (F : Type*) {R : outParam Type*} {S : outParam Type*}
[Semiring R] [Semiring S] (σ : outParam <| R →+* S) {σ' : outParam <| S →+* R}
[RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : outParam Type*) [TopologicalSpace M]
[AddCommMonoid M] (M₂ : outParam Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] [EquivLike F M M₂] extends SemilinearEquivClass F σ M M₂ : Prop where
map_continuous : ∀ f : F, Continuous f := by continuity
inv_continuous : ∀ f : F, Continuous (EquivLike.inv f) := by continuity
#align continuous_semilinear_equiv_class ContinuousSemilinearEquivClass
attribute [inherit_doc ContinuousSemilinearEquivClass]
ContinuousSemilinearEquivClass.map_continuous
ContinuousSemilinearEquivClass.inv_continuous
/-- `ContinuousLinearEquivClass F σ M M₂` asserts `F` is a type of bundled continuous
`R`-linear equivs `M → M₂`. This is an abbreviation for
`ContinuousSemilinearEquivClass F (RingHom.id R) M M₂`. -/
abbrev ContinuousLinearEquivClass (F : Type*) (R : outParam Type*) [Semiring R]
(M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : outParam Type*)
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M] [Module R M₂] [EquivLike F M M₂] :=
ContinuousSemilinearEquivClass F (RingHom.id R) M M₂
#align continuous_linear_equiv_class ContinuousLinearEquivClass
namespace ContinuousSemilinearEquivClass
variable (F : Type*) {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
(M : Type*) [TopologicalSpace M] [AddCommMonoid M]
(M₂ : Type*) [TopologicalSpace M₂] [AddCommMonoid M₂]
[Module R M] [Module S M₂]
-- `σ'` becomes a metavariable, but it's OK since it's an outparam
instance (priority := 100) continuousSemilinearMapClass [EquivLike F M M₂]
[s : ContinuousSemilinearEquivClass F σ M M₂] : ContinuousSemilinearMapClass F σ M M₂ :=
{ s with }
#align continuous_semilinear_equiv_class.continuous_semilinear_map_class ContinuousSemilinearEquivClass.continuousSemilinearMapClass
end ContinuousSemilinearEquivClass
section PointwiseLimits
variable {M₁ M₂ α R S : Type*} [TopologicalSpace M₂] [T2Space M₂] [Semiring R] [Semiring S]
[AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁] [Module S M₂] [ContinuousConstSMul S M₂]
variable [ContinuousAdd M₂] {σ : R →+* S} {l : Filter α}
/-- Constructs a bundled linear map from a function and a proof that this function belongs to the
closure of the set of linear maps. -/
@[simps (config := .asFn)]
def linearMapOfMemClosureRangeCoe (f : M₁ → M₂)
(hf : f ∈ closure (Set.range ((↑) : (M₁ →ₛₗ[σ] M₂) → M₁ → M₂))) : M₁ →ₛₗ[σ] M₂ :=
{ addMonoidHomOfMemClosureRangeCoe f hf with
map_smul' := (isClosed_setOf_map_smul M₁ M₂ σ).closure_subset_iff.2
(Set.range_subset_iff.2 LinearMap.map_smulₛₗ) hf }
#align linear_map_of_mem_closure_range_coe linearMapOfMemClosureRangeCoe
#align linear_map_of_mem_closure_range_coe_apply linearMapOfMemClosureRangeCoe_apply
/-- Construct a bundled linear map from a pointwise limit of linear maps -/
@[simps! (config := .asFn)]
def linearMapOfTendsto (f : M₁ → M₂) (g : α → M₁ →ₛₗ[σ] M₂) [l.NeBot]
(h : Tendsto (fun a x => g a x) l (𝓝 f)) : M₁ →ₛₗ[σ] M₂ :=
linearMapOfMemClosureRangeCoe f <|
mem_closure_of_tendsto h <| eventually_of_forall fun _ => Set.mem_range_self _
#align linear_map_of_tendsto linearMapOfTendsto
#align linear_map_of_tendsto_apply linearMapOfTendsto_apply
variable (M₁ M₂ σ)
theorem LinearMap.isClosed_range_coe : IsClosed (Set.range ((↑) : (M₁ →ₛₗ[σ] M₂) → M₁ → M₂)) :=
isClosed_of_closure_subset fun f hf => ⟨linearMapOfMemClosureRangeCoe f hf, rfl⟩
#align linear_map.is_closed_range_coe LinearMap.isClosed_range_coe
end PointwiseLimits
namespace ContinuousLinearMap
section Semiring
/-!
### Properties that hold for non-necessarily commutative semirings.
-/
variable {R₁ : Type*} {R₂ : Type*} {R₃ : Type*} [Semiring R₁] [Semiring R₂] [Semiring R₃]
{σ₁₂ : R₁ →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R₁ →+* R₃} {M₁ : Type*} [TopologicalSpace M₁]
[AddCommMonoid M₁] {M'₁ : Type*} [TopologicalSpace M'₁] [AddCommMonoid M'₁] {M₂ : Type*}
[TopologicalSpace M₂] [AddCommMonoid M₂] {M₃ : Type*} [TopologicalSpace M₃] [AddCommMonoid M₃]
{M₄ : Type*} [TopologicalSpace M₄] [AddCommMonoid M₄] [Module R₁ M₁] [Module R₁ M'₁]
[Module R₂ M₂] [Module R₃ M₃]
attribute [coe] ContinuousLinearMap.toLinearMap
/-- Coerce continuous linear maps to linear maps. -/
instance LinearMap.coe : Coe (M₁ →SL[σ₁₂] M₂) (M₁ →ₛₗ[σ₁₂] M₂) := ⟨toLinearMap⟩
#align continuous_linear_map.linear_map.has_coe ContinuousLinearMap.LinearMap.coe
#noalign continuous_linear_map.to_linear_map_eq_coe
theorem coe_injective : Function.Injective ((↑) : (M₁ →SL[σ₁₂] M₂) → M₁ →ₛₗ[σ₁₂] M₂) := by
intro f g H
cases f
cases g
congr
#align continuous_linear_map.coe_injective ContinuousLinearMap.coe_injective
instance funLike : FunLike (M₁ →SL[σ₁₂] M₂) M₁ M₂ where
coe f := f.toLinearMap
coe_injective' _ _ h := coe_injective (DFunLike.coe_injective h)
instance continuousSemilinearMapClass :
ContinuousSemilinearMapClass (M₁ →SL[σ₁₂] M₂) σ₁₂ M₁ M₂ where
map_add f := map_add f.toLinearMap
map_continuous f := f.2
map_smulₛₗ f := f.toLinearMap.map_smul'
#align continuous_linear_map.continuous_semilinear_map_class ContinuousLinearMap.continuousSemilinearMapClass
-- see Note [function coercion]
/-- Coerce continuous linear maps to functions. -/
--instance toFun' : CoeFun (M₁ →SL[σ₁₂] M₂) fun _ => M₁ → M₂ := ⟨DFunLike.coe⟩
-- porting note (#10618): was `simp`, now `simp only` proves it
theorem coe_mk (f : M₁ →ₛₗ[σ₁₂] M₂) (h) : (mk f h : M₁ →ₛₗ[σ₁₂] M₂) = f :=
rfl
#align continuous_linear_map.coe_mk ContinuousLinearMap.coe_mk
@[simp]
theorem coe_mk' (f : M₁ →ₛₗ[σ₁₂] M₂) (h) : (mk f h : M₁ → M₂) = f :=
rfl
#align continuous_linear_map.coe_mk' ContinuousLinearMap.coe_mk'
@[continuity]
protected theorem continuous (f : M₁ →SL[σ₁₂] M₂) : Continuous f :=
f.2
#align continuous_linear_map.continuous ContinuousLinearMap.continuous
protected theorem uniformContinuous {E₁ E₂ : Type*} [UniformSpace E₁] [UniformSpace E₂]
[AddCommGroup E₁] [AddCommGroup E₂] [Module R₁ E₁] [Module R₂ E₂] [UniformAddGroup E₁]
[UniformAddGroup E₂] (f : E₁ →SL[σ₁₂] E₂) : UniformContinuous f :=
uniformContinuous_addMonoidHom_of_continuous f.continuous
#align continuous_linear_map.uniform_continuous ContinuousLinearMap.uniformContinuous
@[simp, norm_cast]
theorem coe_inj {f g : M₁ →SL[σ₁₂] M₂} : (f : M₁ →ₛₗ[σ₁₂] M₂) = g ↔ f = g :=
coe_injective.eq_iff
#align continuous_linear_map.coe_inj ContinuousLinearMap.coe_inj
theorem coeFn_injective : @Function.Injective (M₁ →SL[σ₁₂] M₂) (M₁ → M₂) (↑) :=
DFunLike.coe_injective
#align continuous_linear_map.coe_fn_injective ContinuousLinearMap.coeFn_injective
/-- 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 (h : M₁ →SL[σ₁₂] M₂) : M₁ → M₂ :=
h
#align continuous_linear_map.simps.apply ContinuousLinearMap.Simps.apply
/-- See Note [custom simps projection]. -/
def Simps.coe (h : M₁ →SL[σ₁₂] M₂) : M₁ →ₛₗ[σ₁₂] M₂ :=
h
#align continuous_linear_map.simps.coe ContinuousLinearMap.Simps.coe
initialize_simps_projections ContinuousLinearMap (toLinearMap_toFun → apply, toLinearMap → coe)
@[ext]
theorem ext {f g : M₁ →SL[σ₁₂] M₂} (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
#align continuous_linear_map.ext ContinuousLinearMap.ext
theorem ext_iff {f g : M₁ →SL[σ₁₂] M₂} : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align continuous_linear_map.ext_iff ContinuousLinearMap.ext_iff
/-- Copy of a `ContinuousLinearMap` with a new `toFun` equal to the old one. Useful to fix
definitional equalities. -/
protected def copy (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : M₁ →SL[σ₁₂] M₂ where
toLinearMap := f.toLinearMap.copy f' h
cont := show Continuous f' from h.symm ▸ f.continuous
#align continuous_linear_map.copy ContinuousLinearMap.copy
@[simp]
theorem coe_copy (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : ⇑(f.copy f' h) = f' :=
rfl
#align continuous_linear_map.coe_copy ContinuousLinearMap.coe_copy
theorem copy_eq (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : f.copy f' h = f :=
DFunLike.ext' h
#align continuous_linear_map.copy_eq ContinuousLinearMap.copy_eq
-- make some straightforward lemmas available to `simp`.
protected theorem map_zero (f : M₁ →SL[σ₁₂] M₂) : f (0 : M₁) = 0 :=
map_zero f
#align continuous_linear_map.map_zero ContinuousLinearMap.map_zero
protected theorem map_add (f : M₁ →SL[σ₁₂] M₂) (x y : M₁) : f (x + y) = f x + f y :=
map_add f x y
#align continuous_linear_map.map_add ContinuousLinearMap.map_add
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smulₛₗ (f : M₁ →SL[σ₁₂] M₂) (c : R₁) (x : M₁) : f (c • x) = σ₁₂ c • f x :=
(toLinearMap _).map_smulₛₗ _ _
#align continuous_linear_map.map_smulₛₗ ContinuousLinearMap.map_smulₛₗ
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smul [Module R₁ M₂] (f : M₁ →L[R₁] M₂) (c : R₁) (x : M₁) :
f (c • x) = c • f x := by simp only [RingHom.id_apply, ContinuousLinearMap.map_smulₛₗ]
#align continuous_linear_map.map_smul ContinuousLinearMap.map_smul
@[simp]
theorem map_smul_of_tower {R S : Type*} [Semiring S] [SMul R M₁] [Module S M₁] [SMul R M₂]
[Module S M₂] [LinearMap.CompatibleSMul M₁ M₂ R S] (f : M₁ →L[S] M₂) (c : R) (x : M₁) :
f (c • x) = c • f x :=
LinearMap.CompatibleSMul.map_smul (f : M₁ →ₗ[S] M₂) c x
#align continuous_linear_map.map_smul_of_tower ContinuousLinearMap.map_smul_of_tower
@[deprecated _root_.map_sum]
protected theorem map_sum {ι : Type*} (f : M₁ →SL[σ₁₂] M₂) (s : Finset ι) (g : ι → M₁) :
f (∑ i ∈ s, g i) = ∑ i ∈ s, f (g i) :=
map_sum ..
#align continuous_linear_map.map_sum ContinuousLinearMap.map_sum
@[simp, norm_cast]
theorem coe_coe (f : M₁ →SL[σ₁₂] M₂) : ⇑(f : M₁ →ₛₗ[σ₁₂] M₂) = f :=
rfl
#align continuous_linear_map.coe_coe ContinuousLinearMap.coe_coe
@[ext]
theorem ext_ring [TopologicalSpace R₁] {f g : R₁ →L[R₁] M₁} (h : f 1 = g 1) : f = g :=
coe_inj.1 <| LinearMap.ext_ring h
#align continuous_linear_map.ext_ring ContinuousLinearMap.ext_ring
theorem ext_ring_iff [TopologicalSpace R₁] {f g : R₁ →L[R₁] M₁} : f = g ↔ f 1 = g 1 :=
⟨fun h => h ▸ rfl, ext_ring⟩
#align continuous_linear_map.ext_ring_iff ContinuousLinearMap.ext_ring_iff
/-- If two continuous linear maps are equal on a set `s`, then they are equal on the closure
of the `Submodule.span` of this set. -/
theorem eqOn_closure_span [T2Space M₂] {s : Set M₁} {f g : M₁ →SL[σ₁₂] M₂} (h : Set.EqOn f g s) :
Set.EqOn f g (closure (Submodule.span R₁ s : Set M₁)) :=
(LinearMap.eqOn_span' h).closure f.continuous g.continuous
#align continuous_linear_map.eq_on_closure_span ContinuousLinearMap.eqOn_closure_span
/-- If the submodule generated by a set `s` is dense in the ambient module, then two continuous
linear maps equal on `s` are equal. -/
theorem ext_on [T2Space M₂] {s : Set M₁} (hs : Dense (Submodule.span R₁ s : Set M₁))
{f g : M₁ →SL[σ₁₂] M₂} (h : Set.EqOn f g s) : f = g :=
ext fun x => eqOn_closure_span h (hs x)
#align continuous_linear_map.ext_on ContinuousLinearMap.ext_on
/-- Under a continuous linear map, the image of the `TopologicalClosure` of a submodule is
contained in the `TopologicalClosure` of its image. -/
theorem _root_.Submodule.topologicalClosure_map [RingHomSurjective σ₁₂] [TopologicalSpace R₁]
[TopologicalSpace R₂] [ContinuousSMul R₁ M₁] [ContinuousAdd M₁] [ContinuousSMul R₂ M₂]
[ContinuousAdd M₂] (f : M₁ →SL[σ₁₂] M₂) (s : Submodule R₁ M₁) :
s.topologicalClosure.map (f : M₁ →ₛₗ[σ₁₂] M₂) ≤
(s.map (f : M₁ →ₛₗ[σ₁₂] M₂)).topologicalClosure :=
image_closure_subset_closure_image f.continuous
#align submodule.topological_closure_map Submodule.topologicalClosure_map
/-- Under a dense continuous linear map, a submodule whose `TopologicalClosure` is `⊤` is sent to
another such submodule. That is, the image of a dense set under a map with dense range is dense.
-/
theorem _root_.DenseRange.topologicalClosure_map_submodule [RingHomSurjective σ₁₂]
[TopologicalSpace R₁] [TopologicalSpace R₂] [ContinuousSMul R₁ M₁] [ContinuousAdd M₁]
[ContinuousSMul R₂ M₂] [ContinuousAdd M₂] {f : M₁ →SL[σ₁₂] M₂} (hf' : DenseRange f)
{s : Submodule R₁ M₁} (hs : s.topologicalClosure = ⊤) :
(s.map (f : M₁ →ₛₗ[σ₁₂] M₂)).topologicalClosure = ⊤ := by
rw [SetLike.ext'_iff] at hs ⊢
simp only [Submodule.topologicalClosure_coe, Submodule.top_coe, ← dense_iff_closure_eq] at hs ⊢
exact hf'.dense_image f.continuous hs
#align dense_range.topological_closure_map_submodule DenseRange.topologicalClosure_map_submodule
section SMulMonoid
variable {S₂ T₂ : Type*} [Monoid S₂] [Monoid T₂]
variable [DistribMulAction S₂ M₂] [SMulCommClass R₂ S₂ M₂] [ContinuousConstSMul S₂ M₂]
variable [DistribMulAction T₂ M₂] [SMulCommClass R₂ T₂ M₂] [ContinuousConstSMul T₂ M₂]
instance instSMul : SMul S₂ (M₁ →SL[σ₁₂] M₂) where
smul c f := ⟨c • (f : M₁ →ₛₗ[σ₁₂] M₂), (f.2.const_smul _ : Continuous fun x => c • f x)⟩
instance mulAction : MulAction S₂ (M₁ →SL[σ₁₂] M₂) where
one_smul _f := ext fun _x => one_smul _ _
mul_smul _a _b _f := ext fun _x => mul_smul _ _ _
#align continuous_linear_map.mul_action ContinuousLinearMap.mulAction
theorem smul_apply (c : S₂) (f : M₁ →SL[σ₁₂] M₂) (x : M₁) : (c • f) x = c • f x :=
rfl
#align continuous_linear_map.smul_apply ContinuousLinearMap.smul_apply
@[simp, norm_cast]
theorem coe_smul (c : S₂) (f : M₁ →SL[σ₁₂] M₂) :
↑(c • f) = c • (f : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align continuous_linear_map.coe_smul ContinuousLinearMap.coe_smul
@[simp, norm_cast]
theorem coe_smul' (c : S₂) (f : M₁ →SL[σ₁₂] M₂) :
↑(c • f) = c • (f : M₁ → M₂) :=
rfl
#align continuous_linear_map.coe_smul' ContinuousLinearMap.coe_smul'
instance isScalarTower [SMul S₂ T₂] [IsScalarTower S₂ T₂ M₂] :
IsScalarTower S₂ T₂ (M₁ →SL[σ₁₂] M₂) :=
⟨fun a b f => ext fun x => smul_assoc a b (f x)⟩
#align continuous_linear_map.is_scalar_tower ContinuousLinearMap.isScalarTower
instance smulCommClass [SMulCommClass S₂ T₂ M₂] : SMulCommClass S₂ T₂ (M₁ →SL[σ₁₂] M₂) :=
⟨fun a b f => ext fun x => smul_comm a b (f x)⟩
#align continuous_linear_map.smul_comm_class ContinuousLinearMap.smulCommClass
end SMulMonoid
/-- The continuous map that is constantly zero. -/
instance zero : Zero (M₁ →SL[σ₁₂] M₂) :=
⟨⟨0, continuous_zero⟩⟩
#align continuous_linear_map.has_zero ContinuousLinearMap.zero
instance inhabited : Inhabited (M₁ →SL[σ₁₂] M₂) :=
⟨0⟩
#align continuous_linear_map.inhabited ContinuousLinearMap.inhabited
@[simp]
theorem default_def : (default : M₁ →SL[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.default_def ContinuousLinearMap.default_def
@[simp]
theorem zero_apply (x : M₁) : (0 : M₁ →SL[σ₁₂] M₂) x = 0 :=
rfl
#align continuous_linear_map.zero_apply ContinuousLinearMap.zero_apply
@[simp, norm_cast]
theorem coe_zero : ((0 : M₁ →SL[σ₁₂] M₂) : M₁ →ₛₗ[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.coe_zero ContinuousLinearMap.coe_zero
/- no simp attribute on the next line as simp does not always simplify `0 x` to `0`
when `0` is the zero function, while it does for the zero continuous linear map,
and this is the most important property we care about. -/
@[norm_cast]
theorem coe_zero' : ⇑(0 : M₁ →SL[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.coe_zero' ContinuousLinearMap.coe_zero'
instance uniqueOfLeft [Subsingleton M₁] : Unique (M₁ →SL[σ₁₂] M₂) :=
coe_injective.unique
#align continuous_linear_map.unique_of_left ContinuousLinearMap.uniqueOfLeft
instance uniqueOfRight [Subsingleton M₂] : Unique (M₁ →SL[σ₁₂] M₂) :=
coe_injective.unique
#align continuous_linear_map.unique_of_right ContinuousLinearMap.uniqueOfRight
theorem exists_ne_zero {f : M₁ →SL[σ₁₂] M₂} (hf : f ≠ 0) : ∃ x, f x ≠ 0 := by
by_contra! h
exact hf (ContinuousLinearMap.ext h)
#align continuous_linear_map.exists_ne_zero ContinuousLinearMap.exists_ne_zero
section
variable (R₁ M₁)
/-- the identity map as a continuous linear map. -/
def id : M₁ →L[R₁] M₁ :=
⟨LinearMap.id, continuous_id⟩
#align continuous_linear_map.id ContinuousLinearMap.id
end
instance one : One (M₁ →L[R₁] M₁) :=
⟨id R₁ M₁⟩
#align continuous_linear_map.has_one ContinuousLinearMap.one
theorem one_def : (1 : M₁ →L[R₁] M₁) = id R₁ M₁ :=
rfl
#align continuous_linear_map.one_def ContinuousLinearMap.one_def
theorem id_apply (x : M₁) : id R₁ M₁ x = x :=
rfl
#align continuous_linear_map.id_apply ContinuousLinearMap.id_apply
@[simp, norm_cast]
theorem coe_id : (id R₁ M₁ : M₁ →ₗ[R₁] M₁) = LinearMap.id :=
rfl
#align continuous_linear_map.coe_id ContinuousLinearMap.coe_id
@[simp, norm_cast]
theorem coe_id' : ⇑(id R₁ M₁) = _root_.id :=
rfl
#align continuous_linear_map.coe_id' ContinuousLinearMap.coe_id'
@[simp, norm_cast]
theorem coe_eq_id {f : M₁ →L[R₁] M₁} : (f : M₁ →ₗ[R₁] M₁) = LinearMap.id ↔ f = id _ _ := by
rw [← coe_id, coe_inj]
#align continuous_linear_map.coe_eq_id ContinuousLinearMap.coe_eq_id
@[simp]
theorem one_apply (x : M₁) : (1 : M₁ →L[R₁] M₁) x = x :=
rfl
#align continuous_linear_map.one_apply ContinuousLinearMap.one_apply
instance [Nontrivial M₁] : Nontrivial (M₁ →L[R₁] M₁) :=
⟨0, 1, fun e ↦
have ⟨x, hx⟩ := exists_ne (0 : M₁); hx (by simpa using DFunLike.congr_fun e.symm x)⟩
section Add
variable [ContinuousAdd M₂]
instance add : Add (M₁ →SL[σ₁₂] M₂) :=
⟨fun f g => ⟨f + g, f.2.add g.2⟩⟩
#align continuous_linear_map.has_add ContinuousLinearMap.add
@[simp]
theorem add_apply (f g : M₁ →SL[σ₁₂] M₂) (x : M₁) : (f + g) x = f x + g x :=
rfl
#align continuous_linear_map.add_apply ContinuousLinearMap.add_apply
@[simp, norm_cast]
theorem coe_add (f g : M₁ →SL[σ₁₂] M₂) : (↑(f + g) : M₁ →ₛₗ[σ₁₂] M₂) = f + g :=
rfl
#align continuous_linear_map.coe_add ContinuousLinearMap.coe_add
@[norm_cast]
theorem coe_add' (f g : M₁ →SL[σ₁₂] M₂) : ⇑(f + g) = f + g :=
rfl
#align continuous_linear_map.coe_add' ContinuousLinearMap.coe_add'
instance addCommMonoid : AddCommMonoid (M₁ →SL[σ₁₂] M₂) where
zero_add := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_zero := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_comm := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_assoc := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
nsmul := (· • ·)
nsmul_zero f := by
ext
simp
nsmul_succ n f := by
ext
simp [add_smul]
#align continuous_linear_map.add_comm_monoid ContinuousLinearMap.addCommMonoid
@[simp, norm_cast]
theorem coe_sum {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) :
↑(∑ d ∈ t, f d) = (∑ d ∈ t, f d : M₁ →ₛₗ[σ₁₂] M₂) :=
map_sum (AddMonoidHom.mk ⟨((↑) : (M₁ →SL[σ₁₂] M₂) → M₁ →ₛₗ[σ₁₂] M₂), rfl⟩ fun _ _ => rfl) _ _
#align continuous_linear_map.coe_sum ContinuousLinearMap.coe_sum
@[simp, norm_cast]
theorem coe_sum' {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) :
⇑(∑ d ∈ t, f d) = ∑ d ∈ t, ⇑(f d) := by simp only [← coe_coe, coe_sum, LinearMap.coeFn_sum]
#align continuous_linear_map.coe_sum' ContinuousLinearMap.coe_sum'
theorem sum_apply {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) (b : M₁) :
(∑ d ∈ t, f d) b = ∑ d ∈ t, f d b := by simp only [coe_sum', Finset.sum_apply]
#align continuous_linear_map.sum_apply ContinuousLinearMap.sum_apply
end Add
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
/-- Composition of bounded linear maps. -/
def comp (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) : M₁ →SL[σ₁₃] M₃ :=
⟨(g : M₂ →ₛₗ[σ₂₃] M₃).comp (f : M₁ →ₛₗ[σ₁₂] M₂), g.2.comp f.2⟩
#align continuous_linear_map.comp ContinuousLinearMap.comp
@[inherit_doc comp]
infixr:80 " ∘L " =>
@ContinuousLinearMap.comp _ _ _ _ _ _ (RingHom.id _) (RingHom.id _) (RingHom.id _) _ _ _ _ _ _ _ _
_ _ _ _ RingHomCompTriple.ids
@[simp, norm_cast]
theorem coe_comp (h : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(h.comp f : M₁ →ₛₗ[σ₁₃] M₃) = (h : M₂ →ₛₗ[σ₂₃] M₃).comp (f : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align continuous_linear_map.coe_comp ContinuousLinearMap.coe_comp
@[simp, norm_cast]
theorem coe_comp' (h : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) : ⇑(h.comp f) = h ∘ f :=
rfl
#align continuous_linear_map.coe_comp' ContinuousLinearMap.coe_comp'
theorem comp_apply (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) (x : M₁) : (g.comp f) x = g (f x) :=
rfl
#align continuous_linear_map.comp_apply ContinuousLinearMap.comp_apply
@[simp]
theorem comp_id (f : M₁ →SL[σ₁₂] M₂) : f.comp (id R₁ M₁) = f :=
ext fun _x => rfl
#align continuous_linear_map.comp_id ContinuousLinearMap.comp_id
@[simp]
theorem id_comp (f : M₁ →SL[σ₁₂] M₂) : (id R₂ M₂).comp f = f :=
ext fun _x => rfl
#align continuous_linear_map.id_comp ContinuousLinearMap.id_comp
@[simp]
theorem comp_zero (g : M₂ →SL[σ₂₃] M₃) : g.comp (0 : M₁ →SL[σ₁₂] M₂) = 0 := by
ext
simp
#align continuous_linear_map.comp_zero ContinuousLinearMap.comp_zero
@[simp]
theorem zero_comp (f : M₁ →SL[σ₁₂] M₂) : (0 : M₂ →SL[σ₂₃] M₃).comp f = 0 := by
ext
simp
#align continuous_linear_map.zero_comp ContinuousLinearMap.zero_comp
@[simp]
theorem comp_add [ContinuousAdd M₂] [ContinuousAdd M₃] (g : M₂ →SL[σ₂₃] M₃)
(f₁ f₂ : M₁ →SL[σ₁₂] M₂) : g.comp (f₁ + f₂) = g.comp f₁ + g.comp f₂ := by
ext
simp
#align continuous_linear_map.comp_add ContinuousLinearMap.comp_add
@[simp]
theorem add_comp [ContinuousAdd M₃] (g₁ g₂ : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(g₁ + g₂).comp f = g₁.comp f + g₂.comp f := by
ext
simp
#align continuous_linear_map.add_comp ContinuousLinearMap.add_comp
theorem comp_assoc {R₄ : Type*} [Semiring R₄] [Module R₄ M₄] {σ₁₄ : R₁ →+* R₄} {σ₂₄ : R₂ →+* R₄}
{σ₃₄ : R₃ →+* R₄} [RingHomCompTriple σ₁₃ σ₃₄ σ₁₄] [RingHomCompTriple σ₂₃ σ₃₄ σ₂₄]
[RingHomCompTriple σ₁₂ σ₂₄ σ₁₄] (h : M₃ →SL[σ₃₄] M₄) (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(h.comp g).comp f = h.comp (g.comp f) :=
rfl
#align continuous_linear_map.comp_assoc ContinuousLinearMap.comp_assoc
instance instMul : Mul (M₁ →L[R₁] M₁) :=
⟨comp⟩
#align continuous_linear_map.has_mul ContinuousLinearMap.instMul
theorem mul_def (f g : M₁ →L[R₁] M₁) : f * g = f.comp g :=
rfl
#align continuous_linear_map.mul_def ContinuousLinearMap.mul_def
@[simp]
theorem coe_mul (f g : M₁ →L[R₁] M₁) : ⇑(f * g) = f ∘ g :=
rfl
#align continuous_linear_map.coe_mul ContinuousLinearMap.coe_mul
theorem mul_apply (f g : M₁ →L[R₁] M₁) (x : M₁) : (f * g) x = f (g x) :=
rfl
#align continuous_linear_map.mul_apply ContinuousLinearMap.mul_apply
instance monoidWithZero : MonoidWithZero (M₁ →L[R₁] M₁) where
mul_zero f := ext fun _ => map_zero f
zero_mul _ := ext fun _ => rfl
mul_one _ := ext fun _ => rfl
one_mul _ := ext fun _ => rfl
mul_assoc _ _ _ := ext fun _ => rfl
#align continuous_linear_map.monoid_with_zero ContinuousLinearMap.monoidWithZero
theorem coe_pow (f : M₁ →L[R₁] M₁) (n : ℕ) : ⇑(f ^ n) = f^[n] :=
hom_coe_pow _ rfl (fun _ _ ↦ rfl) _ _
instance instNatCast [ContinuousAdd M₁] : NatCast (M₁ →L[R₁] M₁) where
natCast n := n • (1 : M₁ →L[R₁] M₁)
instance semiring [ContinuousAdd M₁] : Semiring (M₁ →L[R₁] M₁) where
__ := ContinuousLinearMap.monoidWithZero
__ := ContinuousLinearMap.addCommMonoid
left_distrib f g h := ext fun x => map_add f (g x) (h x)
right_distrib _ _ _ := ext fun _ => LinearMap.add_apply _ _ _
toNatCast := instNatCast
natCast_zero := zero_smul ℕ (1 : M₁ →L[R₁] M₁)
natCast_succ n := AddMonoid.nsmul_succ n (1 : M₁ →L[R₁] M₁)
#align continuous_linear_map.semiring ContinuousLinearMap.semiring
/-- `ContinuousLinearMap.toLinearMap` as a `RingHom`. -/
@[simps]
def toLinearMapRingHom [ContinuousAdd M₁] : (M₁ →L[R₁] M₁) →+* M₁ →ₗ[R₁] M₁ where
toFun := toLinearMap
map_zero' := rfl
map_one' := rfl
map_add' _ _ := rfl
map_mul' _ _ := rfl
#align continuous_linear_map.to_linear_map_ring_hom ContinuousLinearMap.toLinearMapRingHom
#align continuous_linear_map.to_linear_map_ring_hom_apply ContinuousLinearMap.toLinearMapRingHom_apply
@[simp]
theorem natCast_apply [ContinuousAdd M₁] (n : ℕ) (m : M₁) : (↑n : M₁ →L[R₁] M₁) m = n • m :=
rfl
@[simp]
theorem ofNat_apply [ContinuousAdd M₁] (n : ℕ) [n.AtLeastTwo] (m : M₁) :
((no_index (OfNat.ofNat n) : M₁ →L[R₁] M₁)) m = OfNat.ofNat n • m :=
rfl
section ApplyAction
variable [ContinuousAdd M₁]
/-- The tautological action by `M₁ →L[R₁] M₁` on `M`.
This generalizes `Function.End.applyMulAction`. -/
instance applyModule : Module (M₁ →L[R₁] M₁) M₁ :=
Module.compHom _ toLinearMapRingHom
#align continuous_linear_map.apply_module ContinuousLinearMap.applyModule
@[simp]
protected theorem smul_def (f : M₁ →L[R₁] M₁) (a : M₁) : f • a = f a :=
rfl
#align continuous_linear_map.smul_def ContinuousLinearMap.smul_def
/-- `ContinuousLinearMap.applyModule` is faithful. -/
instance applyFaithfulSMul : FaithfulSMul (M₁ →L[R₁] M₁) M₁ :=
⟨fun {_ _} => ContinuousLinearMap.ext⟩
#align continuous_linear_map.apply_has_faithful_smul ContinuousLinearMap.applyFaithfulSMul
instance applySMulCommClass : SMulCommClass R₁ (M₁ →L[R₁] M₁) M₁ where
smul_comm r e m := (e.map_smul r m).symm
#align continuous_linear_map.apply_smul_comm_class ContinuousLinearMap.applySMulCommClass
instance applySMulCommClass' : SMulCommClass (M₁ →L[R₁] M₁) R₁ M₁ where
smul_comm := ContinuousLinearMap.map_smul
#align continuous_linear_map.apply_smul_comm_class' ContinuousLinearMap.applySMulCommClass'
instance continuousConstSMul_apply : ContinuousConstSMul (M₁ →L[R₁] M₁) M₁ :=
⟨ContinuousLinearMap.continuous⟩
#align continuous_linear_map.has_continuous_const_smul ContinuousLinearMap.continuousConstSMul_apply
end ApplyAction
/-- The cartesian product of two bounded linear maps, as a bounded linear map. -/
protected def prod [Module R₁ M₂] [Module R₁ M₃] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₁ →L[R₁] M₃) :
M₁ →L[R₁] M₂ × M₃ :=
⟨(f₁ : M₁ →ₗ[R₁] M₂).prod f₂, f₁.2.prod_mk f₂.2⟩
#align continuous_linear_map.prod ContinuousLinearMap.prod
@[simp, norm_cast]
theorem coe_prod [Module R₁ M₂] [Module R₁ M₃] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₁ →L[R₁] M₃) :
(f₁.prod f₂ : M₁ →ₗ[R₁] M₂ × M₃) = LinearMap.prod f₁ f₂ :=
rfl
#align continuous_linear_map.coe_prod ContinuousLinearMap.coe_prod
@[simp, norm_cast]
theorem prod_apply [Module R₁ M₂] [Module R₁ M₃] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₁ →L[R₁] M₃) (x : M₁) :
f₁.prod f₂ x = (f₁ x, f₂ x) :=
rfl
#align continuous_linear_map.prod_apply ContinuousLinearMap.prod_apply
section
variable (R₁ M₁ M₂)
/-- The left injection into a product is a continuous linear map. -/
def inl [Module R₁ M₂] : M₁ →L[R₁] M₁ × M₂ :=
(id R₁ M₁).prod 0
#align continuous_linear_map.inl ContinuousLinearMap.inl
/-- The right injection into a product is a continuous linear map. -/
def inr [Module R₁ M₂] : M₂ →L[R₁] M₁ × M₂ :=
(0 : M₂ →L[R₁] M₁).prod (id R₁ M₂)
#align continuous_linear_map.inr ContinuousLinearMap.inr
end
variable {F : Type*}
@[simp]
theorem inl_apply [Module R₁ M₂] (x : M₁) : inl R₁ M₁ M₂ x = (x, 0) :=
rfl
#align continuous_linear_map.inl_apply ContinuousLinearMap.inl_apply
@[simp]
theorem inr_apply [Module R₁ M₂] (x : M₂) : inr R₁ M₁ M₂ x = (0, x) :=
rfl
#align continuous_linear_map.inr_apply ContinuousLinearMap.inr_apply
@[simp, norm_cast]
theorem coe_inl [Module R₁ M₂] : (inl R₁ M₁ M₂ : M₁ →ₗ[R₁] M₁ × M₂) = LinearMap.inl R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_inl ContinuousLinearMap.coe_inl
@[simp, norm_cast]
theorem coe_inr [Module R₁ M₂] : (inr R₁ M₁ M₂ : M₂ →ₗ[R₁] M₁ × M₂) = LinearMap.inr R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_inr ContinuousLinearMap.coe_inr
theorem isClosed_ker [T1Space M₂] [FunLike F M₁ M₂] [ContinuousSemilinearMapClass F σ₁₂ M₁ M₂]
(f : F) :
IsClosed (ker f : Set M₁) :=
continuous_iff_isClosed.1 (map_continuous f) _ isClosed_singleton
#align continuous_linear_map.is_closed_ker ContinuousLinearMap.isClosed_ker
theorem isComplete_ker {M' : Type*} [UniformSpace M'] [CompleteSpace M'] [AddCommMonoid M']
[Module R₁ M'] [T1Space M₂] [FunLike F M' M₂] [ContinuousSemilinearMapClass F σ₁₂ M' M₂]
(f : F) :
IsComplete (ker f : Set M') :=
(isClosed_ker f).isComplete
#align continuous_linear_map.is_complete_ker ContinuousLinearMap.isComplete_ker
instance completeSpace_ker {M' : Type*} [UniformSpace M'] [CompleteSpace M']
[AddCommMonoid M'] [Module R₁ M'] [T1Space M₂]
[FunLike F M' M₂] [ContinuousSemilinearMapClass F σ₁₂ M' M₂]
(f : F) : CompleteSpace (ker f) :=
(isComplete_ker f).completeSpace_coe
#align continuous_linear_map.complete_space_ker ContinuousLinearMap.completeSpace_ker
instance completeSpace_eqLocus {M' : Type*} [UniformSpace M'] [CompleteSpace M']
[AddCommMonoid M'] [Module R₁ M'] [T2Space M₂]
[FunLike F M' M₂] [ContinuousSemilinearMapClass F σ₁₂ M' M₂]
(f g : F) : CompleteSpace (LinearMap.eqLocus f g) :=
IsClosed.completeSpace_coe <| isClosed_eq (map_continuous f) (map_continuous g)
@[simp]
theorem ker_prod [Module R₁ M₂] [Module R₁ M₃] (f : M₁ →L[R₁] M₂) (g : M₁ →L[R₁] M₃) :
ker (f.prod g) = ker f ⊓ ker g :=
LinearMap.ker_prod (f : M₁ →ₗ[R₁] M₂) (g : M₁ →ₗ[R₁] M₃)
#align continuous_linear_map.ker_prod ContinuousLinearMap.ker_prod
/-- Restrict codomain of a continuous linear map. -/
def codRestrict (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) :
M₁ →SL[σ₁₂] p where
cont := f.continuous.subtype_mk _
toLinearMap := (f : M₁ →ₛₗ[σ₁₂] M₂).codRestrict p h
#align continuous_linear_map.cod_restrict ContinuousLinearMap.codRestrict
@[norm_cast]
theorem coe_codRestrict (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) :
(f.codRestrict p h : M₁ →ₛₗ[σ₁₂] p) = (f : M₁ →ₛₗ[σ₁₂] M₂).codRestrict p h :=
rfl
#align continuous_linear_map.coe_cod_restrict ContinuousLinearMap.coe_codRestrict
@[simp]
theorem coe_codRestrict_apply (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) (x) :
(f.codRestrict p h x : M₂) = f x :=
rfl
#align continuous_linear_map.coe_cod_restrict_apply ContinuousLinearMap.coe_codRestrict_apply
@[simp]
theorem ker_codRestrict (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) :
ker (f.codRestrict p h) = ker f :=
(f : M₁ →ₛₗ[σ₁₂] M₂).ker_codRestrict p h
#align continuous_linear_map.ker_cod_restrict ContinuousLinearMap.ker_codRestrict
/-- Restrict the codomain of a continuous linear map `f` to `f.range`. -/
abbrev rangeRestrict [RingHomSurjective σ₁₂] (f : M₁ →SL[σ₁₂] M₂) :=
f.codRestrict (LinearMap.range f) (LinearMap.mem_range_self f)
@[simp]
theorem coe_rangeRestrict [RingHomSurjective σ₁₂] (f : M₁ →SL[σ₁₂] M₂) :
(f.rangeRestrict : M₁ →ₛₗ[σ₁₂] LinearMap.range f) = (f : M₁ →ₛₗ[σ₁₂] M₂).rangeRestrict :=
rfl
/-- `Submodule.subtype` as a `ContinuousLinearMap`. -/
def _root_.Submodule.subtypeL (p : Submodule R₁ M₁) : p →L[R₁] M₁ where
cont := continuous_subtype_val
toLinearMap := p.subtype
set_option linter.uppercaseLean3 false in
#align submodule.subtypeL Submodule.subtypeL
@[simp, norm_cast]
theorem _root_.Submodule.coe_subtypeL (p : Submodule R₁ M₁) :
(p.subtypeL : p →ₗ[R₁] M₁) = p.subtype :=
rfl
set_option linter.uppercaseLean3 false in
#align submodule.coe_subtypeL Submodule.coe_subtypeL
@[simp]
theorem _root_.Submodule.coe_subtypeL' (p : Submodule R₁ M₁) : ⇑p.subtypeL = p.subtype :=
rfl
set_option linter.uppercaseLean3 false in
#align submodule.coe_subtypeL' Submodule.coe_subtypeL'
@[simp] -- @[norm_cast] -- Porting note: A theorem with this can't have a rhs starting with `↑`.
theorem _root_.Submodule.subtypeL_apply (p : Submodule R₁ M₁) (x : p) : p.subtypeL x = x :=
rfl
set_option linter.uppercaseLean3 false in
#align submodule.subtypeL_apply Submodule.subtypeL_apply
@[simp]
theorem _root_.Submodule.range_subtypeL (p : Submodule R₁ M₁) : range p.subtypeL = p :=
Submodule.range_subtype _
set_option linter.uppercaseLean3 false in
#align submodule.range_subtypeL Submodule.range_subtypeL
@[simp]
theorem _root_.Submodule.ker_subtypeL (p : Submodule R₁ M₁) : ker p.subtypeL = ⊥ :=
Submodule.ker_subtype _
set_option linter.uppercaseLean3 false in
#align submodule.ker_subtypeL Submodule.ker_subtypeL
variable (R₁ M₁ M₂)
/-- `Prod.fst` as a `ContinuousLinearMap`. -/
def fst [Module R₁ M₂] : M₁ × M₂ →L[R₁] M₁ where
cont := continuous_fst
toLinearMap := LinearMap.fst R₁ M₁ M₂
#align continuous_linear_map.fst ContinuousLinearMap.fst
/-- `Prod.snd` as a `ContinuousLinearMap`. -/
def snd [Module R₁ M₂] : M₁ × M₂ →L[R₁] M₂ where
cont := continuous_snd
toLinearMap := LinearMap.snd R₁ M₁ M₂
#align continuous_linear_map.snd ContinuousLinearMap.snd
variable {R₁ M₁ M₂}
@[simp, norm_cast]
theorem coe_fst [Module R₁ M₂] : ↑(fst R₁ M₁ M₂) = LinearMap.fst R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_fst ContinuousLinearMap.coe_fst
@[simp, norm_cast]
theorem coe_fst' [Module R₁ M₂] : ⇑(fst R₁ M₁ M₂) = Prod.fst :=
rfl
#align continuous_linear_map.coe_fst' ContinuousLinearMap.coe_fst'
@[simp, norm_cast]
theorem coe_snd [Module R₁ M₂] : ↑(snd R₁ M₁ M₂) = LinearMap.snd R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_snd ContinuousLinearMap.coe_snd
@[simp, norm_cast]
theorem coe_snd' [Module R₁ M₂] : ⇑(snd R₁ M₁ M₂) = Prod.snd :=
rfl
#align continuous_linear_map.coe_snd' ContinuousLinearMap.coe_snd'
@[simp]
theorem fst_prod_snd [Module R₁ M₂] : (fst R₁ M₁ M₂).prod (snd R₁ M₁ M₂) = id R₁ (M₁ × M₂) :=
ext fun ⟨_x, _y⟩ => rfl
#align continuous_linear_map.fst_prod_snd ContinuousLinearMap.fst_prod_snd
@[simp]
theorem fst_comp_prod [Module R₁ M₂] [Module R₁ M₃] (f : M₁ →L[R₁] M₂) (g : M₁ →L[R₁] M₃) :
(fst R₁ M₂ M₃).comp (f.prod g) = f :=
ext fun _x => rfl
#align continuous_linear_map.fst_comp_prod ContinuousLinearMap.fst_comp_prod
@[simp]
theorem snd_comp_prod [Module R₁ M₂] [Module R₁ M₃] (f : M₁ →L[R₁] M₂) (g : M₁ →L[R₁] M₃) :
(snd R₁ M₂ M₃).comp (f.prod g) = g :=
ext fun _x => rfl
#align continuous_linear_map.snd_comp_prod ContinuousLinearMap.snd_comp_prod
/-- `Prod.map` of two continuous linear maps. -/
def prodMap [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₃ →L[R₁] M₄) :
M₁ × M₃ →L[R₁] M₂ × M₄ :=
(f₁.comp (fst R₁ M₁ M₃)).prod (f₂.comp (snd R₁ M₁ M₃))
#align continuous_linear_map.prod_map ContinuousLinearMap.prodMap
@[simp, norm_cast]
theorem coe_prodMap [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (f₁ : M₁ →L[R₁] M₂)
(f₂ : M₃ →L[R₁] M₄) : ↑(f₁.prodMap f₂) = (f₁ : M₁ →ₗ[R₁] M₂).prodMap (f₂ : M₃ →ₗ[R₁] M₄) :=
rfl
#align continuous_linear_map.coe_prod_map ContinuousLinearMap.coe_prodMap
@[simp, norm_cast]
theorem coe_prodMap' [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (f₁ : M₁ →L[R₁] M₂)
(f₂ : M₃ →L[R₁] M₄) : ⇑(f₁.prodMap f₂) = Prod.map f₁ f₂ :=
rfl
#align continuous_linear_map.coe_prod_map' ContinuousLinearMap.coe_prodMap'
/-- The continuous linear map given by `(x, y) ↦ f₁ x + f₂ y`. -/
def coprod [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) : M₁ × M₂ →L[R₁] M₃ :=
⟨LinearMap.coprod f₁ f₂, (f₁.cont.comp continuous_fst).add (f₂.cont.comp continuous_snd)⟩
#align continuous_linear_map.coprod ContinuousLinearMap.coprod
@[norm_cast, simp]
theorem coe_coprod [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) : (f₁.coprod f₂ : M₁ × M₂ →ₗ[R₁] M₃) = LinearMap.coprod f₁ f₂ :=
rfl
#align continuous_linear_map.coe_coprod ContinuousLinearMap.coe_coprod
@[simp]
theorem coprod_apply [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) (x) : f₁.coprod f₂ x = f₁ x.1 + f₂ x.2 :=
rfl
#align continuous_linear_map.coprod_apply ContinuousLinearMap.coprod_apply
theorem range_coprod [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) : range (f₁.coprod f₂) = range f₁ ⊔ range f₂ :=
LinearMap.range_coprod _ _
#align continuous_linear_map.range_coprod ContinuousLinearMap.range_coprod
theorem comp_fst_add_comp_snd [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f : M₁ →L[R₁] M₃)
(g : M₂ →L[R₁] M₃) :
f.comp (ContinuousLinearMap.fst R₁ M₁ M₂) + g.comp (ContinuousLinearMap.snd R₁ M₁ M₂) =
f.coprod g :=
rfl
#align continuous_linear_map.comp_fst_add_comp_snd ContinuousLinearMap.comp_fst_add_comp_snd
theorem coprod_inl_inr [ContinuousAdd M₁] [ContinuousAdd M'₁] :
(ContinuousLinearMap.inl R₁ M₁ M'₁).coprod (ContinuousLinearMap.inr R₁ M₁ M'₁) =
ContinuousLinearMap.id R₁ (M₁ × M'₁) := by
apply coe_injective; apply LinearMap.coprod_inl_inr
#align continuous_linear_map.coprod_inl_inr ContinuousLinearMap.coprod_inl_inr
section
variable {R S : Type*} [Semiring R] [Semiring S] [Module R M₁] [Module R M₂] [Module R S]
[Module S M₂] [IsScalarTower R S M₂] [TopologicalSpace S] [ContinuousSMul S M₂]
/-- The linear map `fun x => c x • f`. Associates to a scalar-valued linear map and an element of
`M₂` the `M₂`-valued linear map obtained by multiplying the two (a.k.a. tensoring by `M₂`).
See also `ContinuousLinearMap.smulRightₗ` and `ContinuousLinearMap.smulRightL`. -/
def smulRight (c : M₁ →L[R] S) (f : M₂) : M₁ →L[R] M₂ :=
{ c.toLinearMap.smulRight f with cont := c.2.smul continuous_const }
#align continuous_linear_map.smul_right ContinuousLinearMap.smulRight
@[simp]
theorem smulRight_apply {c : M₁ →L[R] S} {f : M₂} {x : M₁} :
(smulRight c f : M₁ → M₂) x = c x • f :=
rfl
#align continuous_linear_map.smul_right_apply ContinuousLinearMap.smulRight_apply
end
variable [Module R₁ M₂] [TopologicalSpace R₁] [ContinuousSMul R₁ M₂]
@[simp]
theorem smulRight_one_one (c : R₁ →L[R₁] M₂) : smulRight (1 : R₁ →L[R₁] R₁) (c 1) = c := by
ext
simp [← ContinuousLinearMap.map_smul_of_tower]
#align continuous_linear_map.smul_right_one_one ContinuousLinearMap.smulRight_one_one
@[simp]
theorem smulRight_one_eq_iff {f f' : M₂} :
smulRight (1 : R₁ →L[R₁] R₁) f = smulRight (1 : R₁ →L[R₁] R₁) f' ↔ f = f' := by
simp only [ext_ring_iff, smulRight_apply, one_apply, one_smul]
#align continuous_linear_map.smul_right_one_eq_iff ContinuousLinearMap.smulRight_one_eq_iff
theorem smulRight_comp [ContinuousMul R₁] {x : M₂} {c : R₁} :
(smulRight (1 : R₁ →L[R₁] R₁) x).comp (smulRight (1 : R₁ →L[R₁] R₁) c) =
smulRight (1 : R₁ →L[R₁] R₁) (c • x) := by
ext
simp [mul_smul]
#align continuous_linear_map.smul_right_comp ContinuousLinearMap.smulRight_comp
section ToSpanSingleton
variable (R₁)
variable [ContinuousSMul R₁ M₁]
/-- Given an element `x` of a topological space `M` over a semiring `R`, the natural continuous
linear map from `R` to `M` by taking multiples of `x`. -/
def toSpanSingleton (x : M₁) : R₁ →L[R₁] M₁ where
toLinearMap := LinearMap.toSpanSingleton R₁ M₁ x
cont := continuous_id.smul continuous_const
#align continuous_linear_map.to_span_singleton ContinuousLinearMap.toSpanSingleton
theorem toSpanSingleton_apply (x : M₁) (r : R₁) : toSpanSingleton R₁ x r = r • x :=
rfl
#align continuous_linear_map.to_span_singleton_apply ContinuousLinearMap.toSpanSingleton_apply
theorem toSpanSingleton_add [ContinuousAdd M₁] (x y : M₁) :
toSpanSingleton R₁ (x + y) = toSpanSingleton R₁ x + toSpanSingleton R₁ y := by
ext1; simp [toSpanSingleton_apply]
#align continuous_linear_map.to_span_singleton_add ContinuousLinearMap.toSpanSingleton_add
theorem toSpanSingleton_smul' {α} [Monoid α] [DistribMulAction α M₁] [ContinuousConstSMul α M₁]
[SMulCommClass R₁ α M₁] (c : α) (x : M₁) :
toSpanSingleton R₁ (c • x) = c • toSpanSingleton R₁ x := by
ext1; rw [toSpanSingleton_apply, smul_apply, toSpanSingleton_apply, smul_comm]
#align continuous_linear_map.to_span_singleton_smul' ContinuousLinearMap.toSpanSingleton_smul'
/-- A special case of `to_span_singleton_smul'` for when `R` is commutative. -/
theorem toSpanSingleton_smul (R) {M₁} [CommSemiring R] [AddCommMonoid M₁] [Module R M₁]
[TopologicalSpace R] [TopologicalSpace M₁] [ContinuousSMul R M₁] (c : R) (x : M₁) :
toSpanSingleton R (c • x) = c • toSpanSingleton R x :=
toSpanSingleton_smul' R c x
#align continuous_linear_map.to_span_singleton_smul ContinuousLinearMap.toSpanSingleton_smul
end ToSpanSingleton
end Semiring
section Pi
variable {R : Type*} [Semiring R] {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [Module R M]
{M₂ : Type*} [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M₂] {ι : Type*} {φ : ι → Type*}
[∀ i, TopologicalSpace (φ i)] [∀ i, AddCommMonoid (φ i)] [∀ i, Module R (φ i)]
/-- `pi` construction for continuous linear functions. From a family of continuous linear functions
it produces a continuous linear function into a family of topological modules. -/
def pi (f : ∀ i, M →L[R] φ i) : M →L[R] ∀ i, φ i :=
⟨LinearMap.pi fun i => f i, continuous_pi fun i => (f i).continuous⟩
#align continuous_linear_map.pi ContinuousLinearMap.pi
@[simp]
theorem coe_pi' (f : ∀ i, M →L[R] φ i) : ⇑(pi f) = fun c i => f i c :=
rfl
#align continuous_linear_map.coe_pi' ContinuousLinearMap.coe_pi'
@[simp]
theorem coe_pi (f : ∀ i, M →L[R] φ i) : (pi f : M →ₗ[R] ∀ i, φ i) = LinearMap.pi fun i => f i :=
rfl
#align continuous_linear_map.coe_pi ContinuousLinearMap.coe_pi
theorem pi_apply (f : ∀ i, M →L[R] φ i) (c : M) (i : ι) : pi f c i = f i c :=
rfl
#align continuous_linear_map.pi_apply ContinuousLinearMap.pi_apply
theorem pi_eq_zero (f : ∀ i, M →L[R] φ i) : pi f = 0 ↔ ∀ i, f i = 0 := by
simp only [ext_iff, pi_apply, Function.funext_iff]
exact forall_swap
#align continuous_linear_map.pi_eq_zero ContinuousLinearMap.pi_eq_zero
theorem pi_zero : pi (fun _ => 0 : ∀ i, M →L[R] φ i) = 0 :=
ext fun _ => rfl
#align continuous_linear_map.pi_zero ContinuousLinearMap.pi_zero
theorem pi_comp (f : ∀ i, M →L[R] φ i) (g : M₂ →L[R] M) :
(pi f).comp g = pi fun i => (f i).comp g :=
rfl
#align continuous_linear_map.pi_comp ContinuousLinearMap.pi_comp
/-- The projections from a family of topological modules are continuous linear maps. -/
def proj (i : ι) : (∀ i, φ i) →L[R] φ i :=
⟨LinearMap.proj i, continuous_apply _⟩
#align continuous_linear_map.proj ContinuousLinearMap.proj
@[simp]
theorem proj_apply (i : ι) (b : ∀ i, φ i) : (proj i : (∀ i, φ i) →L[R] φ i) b = b i :=
rfl
#align continuous_linear_map.proj_apply ContinuousLinearMap.proj_apply
theorem proj_pi (f : ∀ i, M₂ →L[R] φ i) (i : ι) : (proj i).comp (pi f) = f i :=
ext fun _c => rfl
#align continuous_linear_map.proj_pi ContinuousLinearMap.proj_pi
theorem iInf_ker_proj : (⨅ i, ker (proj i : (∀ i, φ i) →L[R] φ i) : Submodule R (∀ i, φ i)) = ⊥ :=
LinearMap.iInf_ker_proj
#align continuous_linear_map.infi_ker_proj ContinuousLinearMap.iInf_ker_proj
variable (R φ)
/-- Given a function `f : α → ι`, it induces a continuous linear function by right composition on
product types. For `f = Subtype.val`, this corresponds to forgetting some set of variables. -/
def _root_.Pi.compRightL {α : Type*} (f : α → ι) : ((i : ι) → φ i) →L[R] ((i : α) → φ (f i)) where
toFun := fun v i ↦ v (f i)
map_add' := by intros; ext; simp
map_smul' := by intros; ext; simp
cont := by continuity
@[simp] lemma _root_.Pi.compRightL_apply {α : Type*} (f : α → ι) (v : (i : ι) → φ i) (i : α) :
Pi.compRightL R φ f v i = v (f i) := rfl
/-- If `I` and `J` are complementary index sets, the product of the kernels of the `J`th projections
of `φ` is linearly equivalent to the product over `I`. -/
def iInfKerProjEquiv {I J : Set ι} [DecidablePred fun i => i ∈ I] (hd : Disjoint I J)
(hu : Set.univ ⊆ I ∪ J) :
(⨅ i ∈ J, ker (proj i : (∀ i, φ i) →L[R] φ i) :
Submodule R (∀ i, φ i)) ≃L[R] ∀ i : I, φ i where
toLinearEquiv := LinearMap.iInfKerProjEquiv R φ hd hu
continuous_toFun :=
continuous_pi fun i => by
have :=
@continuous_subtype_val _ _ fun x =>
x ∈ (⨅ i ∈ J, ker (proj i : (∀ i, φ i) →L[R] φ i) : Submodule R (∀ i, φ i))
have := Continuous.comp (continuous_apply (π := φ) i) this
exact this
continuous_invFun :=
Continuous.subtype_mk
(continuous_pi fun i => by
-- Porting note: Was `dsimp`.
change
Continuous (⇑(if h : i ∈ I then LinearMap.proj (R := R) (ι := ↥I)
(φ := fun i : ↥I => φ i) ⟨i, h⟩ else
(0 : ((i : I) → φ i) →ₗ[R] φ i)))
split_ifs <;> [apply continuous_apply; exact continuous_zero])
_
#align continuous_linear_map.infi_ker_proj_equiv ContinuousLinearMap.iInfKerProjEquiv
end Pi
section Ring
variable {R : Type*} [Ring R] {R₂ : Type*} [Ring R₂] {R₃ : Type*} [Ring R₃] {M : Type*}
[TopologicalSpace M] [AddCommGroup M] {M₂ : Type*} [TopologicalSpace M₂] [AddCommGroup M₂]
{M₃ : Type*} [TopologicalSpace M₃] [AddCommGroup M₃] {M₄ : Type*} [TopologicalSpace M₄]
[AddCommGroup M₄] [Module R M] [Module R₂ M₂] [Module R₃ M₃] {σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃}
{σ₁₃ : R →+* R₃}
section
protected theorem map_neg (f : M →SL[σ₁₂] M₂) (x : M) : f (-x) = -f x := by
exact map_neg f x
#align continuous_linear_map.map_neg ContinuousLinearMap.map_neg
protected theorem map_sub (f : M →SL[σ₁₂] M₂) (x y : M) : f (x - y) = f x - f y := by
exact map_sub f x y
#align continuous_linear_map.map_sub ContinuousLinearMap.map_sub
@[simp]
theorem sub_apply' (f g : M →SL[σ₁₂] M₂) (x : M) : ((f : M →ₛₗ[σ₁₂] M₂) - g) x = f x - g x :=
rfl
#align continuous_linear_map.sub_apply' ContinuousLinearMap.sub_apply'
end
section
variable [Module R M₂] [Module R M₃] [Module R M₄]
theorem range_prod_eq {f : M →L[R] M₂} {g : M →L[R] M₃} (h : ker f ⊔ ker g = ⊤) :
range (f.prod g) = (range f).prod (range g) :=
LinearMap.range_prod_eq h
#align continuous_linear_map.range_prod_eq ContinuousLinearMap.range_prod_eq
theorem ker_prod_ker_le_ker_coprod [ContinuousAdd M₃] (f : M →L[R] M₃) (g : M₂ →L[R] M₃) :
(LinearMap.ker f).prod (LinearMap.ker g) ≤ LinearMap.ker (f.coprod g) :=
LinearMap.ker_prod_ker_le_ker_coprod f.toLinearMap g.toLinearMap
#align continuous_linear_map.ker_prod_ker_le_ker_coprod ContinuousLinearMap.ker_prod_ker_le_ker_coprod
theorem ker_coprod_of_disjoint_range [ContinuousAdd M₃] (f : M →L[R] M₃) (g : M₂ →L[R] M₃)
(hd : Disjoint (range f) (range g)) :
LinearMap.ker (f.coprod g) = (LinearMap.ker f).prod (LinearMap.ker g) :=
LinearMap.ker_coprod_of_disjoint_range f.toLinearMap g.toLinearMap hd
#align continuous_linear_map.ker_coprod_of_disjoint_range ContinuousLinearMap.ker_coprod_of_disjoint_range
end
section
variable [TopologicalAddGroup M₂]
instance neg : Neg (M →SL[σ₁₂] M₂) :=
⟨fun f => ⟨-f, f.2.neg⟩⟩
#align continuous_linear_map.has_neg ContinuousLinearMap.neg
@[simp]
theorem neg_apply (f : M →SL[σ₁₂] M₂) (x : M) : (-f) x = -f x :=
rfl
#align continuous_linear_map.neg_apply ContinuousLinearMap.neg_apply
@[simp, norm_cast]
theorem coe_neg (f : M →SL[σ₁₂] M₂) : (↑(-f) : M →ₛₗ[σ₁₂] M₂) = -f :=
rfl
#align continuous_linear_map.coe_neg ContinuousLinearMap.coe_neg
@[norm_cast]
theorem coe_neg' (f : M →SL[σ₁₂] M₂) : ⇑(-f) = -f :=
rfl
#align continuous_linear_map.coe_neg' ContinuousLinearMap.coe_neg'
instance sub : Sub (M →SL[σ₁₂] M₂) :=
⟨fun f g => ⟨f - g, f.2.sub g.2⟩⟩
#align continuous_linear_map.has_sub ContinuousLinearMap.sub
instance addCommGroup : AddCommGroup (M →SL[σ₁₂] M₂) where
__ := ContinuousLinearMap.addCommMonoid
neg := (-·)
sub := (· - ·)
sub_eq_add_neg _ _ := by ext; apply sub_eq_add_neg
nsmul := (· • ·)
zsmul := (· • ·)
zsmul_zero' f := by ext; simp
zsmul_succ' n f := by ext; simp [add_smul, add_comm]
zsmul_neg' n f := by ext; simp [Nat.succ_eq_add_one, add_smul]
add_left_neg _ := by ext; apply add_left_neg
#align continuous_linear_map.add_comm_group ContinuousLinearMap.addCommGroup
theorem sub_apply (f g : M →SL[σ₁₂] M₂) (x : M) : (f - g) x = f x - g x :=
rfl
#align continuous_linear_map.sub_apply ContinuousLinearMap.sub_apply
@[simp, norm_cast]
theorem coe_sub (f g : M →SL[σ₁₂] M₂) : (↑(f - g) : M →ₛₗ[σ₁₂] M₂) = f - g :=
rfl
#align continuous_linear_map.coe_sub ContinuousLinearMap.coe_sub
@[simp, norm_cast]
theorem coe_sub' (f g : M →SL[σ₁₂] M₂) : ⇑(f - g) = f - g :=
rfl
#align continuous_linear_map.coe_sub' ContinuousLinearMap.coe_sub'
end
@[simp]
theorem comp_neg [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₂] [TopologicalAddGroup M₃]
(g : M₂ →SL[σ₂₃] M₃) (f : M →SL[σ₁₂] M₂) : g.comp (-f) = -g.comp f := by
ext x
simp
#align continuous_linear_map.comp_neg ContinuousLinearMap.comp_neg
@[simp]
theorem neg_comp [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₃] (g : M₂ →SL[σ₂₃] M₃)
(f : M →SL[σ₁₂] M₂) : (-g).comp f = -g.comp f := by
ext
simp
#align continuous_linear_map.neg_comp ContinuousLinearMap.neg_comp
@[simp]
theorem comp_sub [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₂] [TopologicalAddGroup M₃]
(g : M₂ →SL[σ₂₃] M₃) (f₁ f₂ : M →SL[σ₁₂] M₂) : g.comp (f₁ - f₂) = g.comp f₁ - g.comp f₂ := by
ext
simp
#align continuous_linear_map.comp_sub ContinuousLinearMap.comp_sub
@[simp]
theorem sub_comp [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₃] (g₁ g₂ : M₂ →SL[σ₂₃] M₃)
(f : M →SL[σ₁₂] M₂) : (g₁ - g₂).comp f = g₁.comp f - g₂.comp f := by
ext
simp
#align continuous_linear_map.sub_comp ContinuousLinearMap.sub_comp
instance ring [TopologicalAddGroup M] : Ring (M →L[R] M) where
__ := ContinuousLinearMap.semiring
__ := ContinuousLinearMap.addCommGroup
intCast z := z • (1 : M →L[R] M)
intCast_ofNat := natCast_zsmul _
intCast_negSucc := negSucc_zsmul _
#align continuous_linear_map.ring ContinuousLinearMap.ring
@[simp]
theorem intCast_apply [TopologicalAddGroup M] (z : ℤ) (m : M) : (↑z : M →L[R] M) m = z • m :=
rfl
theorem smulRight_one_pow [TopologicalSpace R] [TopologicalRing R] (c : R) (n : ℕ) :
smulRight (1 : R →L[R] R) c ^ n = smulRight (1 : R →L[R] R) (c ^ n) := by
induction' n with n ihn
· ext
simp
· rw [pow_succ, ihn, mul_def, smulRight_comp, smul_eq_mul, pow_succ']
#align continuous_linear_map.smul_right_one_pow ContinuousLinearMap.smulRight_one_pow
section
variable {σ₂₁ : R₂ →+* R} [RingHomInvPair σ₁₂ σ₂₁]
/-- Given a right inverse `f₂ : M₂ →L[R] M` to `f₁ : M →L[R] M₂`,
`projKerOfRightInverse f₁ f₂ h` is the projection `M →L[R] LinearMap.ker f₁` along
`LinearMap.range f₂`. -/
def projKerOfRightInverse [TopologicalAddGroup M] (f₁ : M →SL[σ₁₂] M₂) (f₂ : M₂ →SL[σ₂₁] M)
(h : Function.RightInverse f₂ f₁) : M →L[R] LinearMap.ker f₁ :=
(id R M - f₂.comp f₁).codRestrict (LinearMap.ker f₁) fun x => by simp [h (f₁ x)]
#align continuous_linear_map.proj_ker_of_right_inverse ContinuousLinearMap.projKerOfRightInverse
@[simp]
theorem coe_projKerOfRightInverse_apply [TopologicalAddGroup M] (f₁ : M →SL[σ₁₂] M₂)
(f₂ : M₂ →SL[σ₂₁] M) (h : Function.RightInverse f₂ f₁) (x : M) :
(f₁.projKerOfRightInverse f₂ h x : M) = x - f₂ (f₁ x) :=
rfl
#align continuous_linear_map.coe_proj_ker_of_right_inverse_apply ContinuousLinearMap.coe_projKerOfRightInverse_apply
@[simp]
theorem projKerOfRightInverse_apply_idem [TopologicalAddGroup M] (f₁ : M →SL[σ₁₂] M₂)
(f₂ : M₂ →SL[σ₂₁] M) (h : Function.RightInverse f₂ f₁) (x : LinearMap.ker f₁) :
f₁.projKerOfRightInverse f₂ h x = x := by
ext1
simp
#align continuous_linear_map.proj_ker_of_right_inverse_apply_idem ContinuousLinearMap.projKerOfRightInverse_apply_idem
@[simp]
theorem projKerOfRightInverse_comp_inv [TopologicalAddGroup M] (f₁ : M →SL[σ₁₂] M₂)
(f₂ : M₂ →SL[σ₂₁] M) (h : Function.RightInverse f₂ f₁) (y : M₂) :
f₁.projKerOfRightInverse f₂ h (f₂ y) = 0 :=
Subtype.ext_iff_val.2 <| by simp [h y]
#align continuous_linear_map.proj_ker_of_right_inverse_comp_inv ContinuousLinearMap.projKerOfRightInverse_comp_inv
end
end Ring
section DivisionMonoid
variable {R M : Type*}
/-- A nonzero continuous linear functional is open. -/
protected theorem isOpenMap_of_ne_zero [TopologicalSpace R] [DivisionRing R] [ContinuousSub R]
[AddCommGroup M] [TopologicalSpace M] [ContinuousAdd M] [Module R M] [ContinuousSMul R M]
(f : M →L[R] R) (hf : f ≠ 0) : IsOpenMap f :=
let ⟨x, hx⟩ := exists_ne_zero hf
IsOpenMap.of_sections fun y =>
⟨fun a => y + (a - f y) • (f x)⁻¹ • x, Continuous.continuousAt <| by continuity, by simp,
fun a => by simp [hx]⟩
#align continuous_linear_map.is_open_map_of_ne_zero ContinuousLinearMap.isOpenMap_of_ne_zero
end DivisionMonoid
section SMulMonoid
-- The M's are used for semilinear maps, and the N's for plain linear maps
variable {R R₂ R₃ S S₃ : Type*} [Semiring R] [Semiring R₂] [Semiring R₃] [Monoid S] [Monoid S₃]
{M : Type*} [TopologicalSpace M] [AddCommMonoid M] [Module R M] {M₂ : Type*}
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R₂ M₂] {M₃ : Type*} [TopologicalSpace M₃]
[AddCommMonoid M₃] [Module R₃ M₃] {N₂ : Type*} [TopologicalSpace N₂] [AddCommMonoid N₂]
[Module R N₂] {N₃ : Type*} [TopologicalSpace N₃] [AddCommMonoid N₃] [Module R N₃]
[DistribMulAction S₃ M₃] [SMulCommClass R₃ S₃ M₃] [ContinuousConstSMul S₃ M₃]
[DistribMulAction S N₃] [SMulCommClass R S N₃] [ContinuousConstSMul S N₃] {σ₁₂ : R →+* R₂}
{σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃} [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
@[simp]
theorem smul_comp (c : S₃) (h : M₂ →SL[σ₂₃] M₃) (f : M →SL[σ₁₂] M₂) :
(c • h).comp f = c • h.comp f :=
rfl
#align continuous_linear_map.smul_comp ContinuousLinearMap.smul_comp
variable [DistribMulAction S₃ M₂] [ContinuousConstSMul S₃ M₂] [SMulCommClass R₂ S₃ M₂]
variable [DistribMulAction S N₂] [ContinuousConstSMul S N₂] [SMulCommClass R S N₂]
@[simp]
theorem comp_smul [LinearMap.CompatibleSMul N₂ N₃ S R] (hₗ : N₂ →L[R] N₃) (c : S)
(fₗ : M →L[R] N₂) : hₗ.comp (c • fₗ) = c • hₗ.comp fₗ := by
ext x
exact hₗ.map_smul_of_tower c (fₗ x)
#align continuous_linear_map.comp_smul ContinuousLinearMap.comp_smul
@[simp]
theorem comp_smulₛₗ [SMulCommClass R₂ R₂ M₂] [SMulCommClass R₃ R₃ M₃] [ContinuousConstSMul R₂ M₂]
[ContinuousConstSMul R₃ M₃] (h : M₂ →SL[σ₂₃] M₃) (c : R₂) (f : M →SL[σ₁₂] M₂) :
h.comp (c • f) = σ₂₃ c • h.comp f := by
ext x
simp only [coe_smul', coe_comp', Function.comp_apply, Pi.smul_apply,
ContinuousLinearMap.map_smulₛₗ]
#align continuous_linear_map.comp_smulₛₗ ContinuousLinearMap.comp_smulₛₗ
instance distribMulAction [ContinuousAdd M₂] : DistribMulAction S₃ (M →SL[σ₁₂] M₂) where
smul_add a f g := ext fun x => smul_add a (f x) (g x)
smul_zero a := ext fun _ => smul_zero a
#align continuous_linear_map.distrib_mul_action ContinuousLinearMap.distribMulAction
end SMulMonoid
section SMul
-- The M's are used for semilinear maps, and the N's for plain linear maps
variable {R R₂ R₃ S S₃ : Type*} [Semiring R] [Semiring R₂] [Semiring R₃] [Semiring S] [Semiring S₃]
{M : Type*} [TopologicalSpace M] [AddCommMonoid M] [Module R M] {M₂ : Type*}
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R₂ M₂] {M₃ : Type*} [TopologicalSpace M₃]
[AddCommMonoid M₃] [Module R₃ M₃] {N₂ : Type*} [TopologicalSpace N₂] [AddCommMonoid N₂]
[Module R N₂] {N₃ : Type*} [TopologicalSpace N₃] [AddCommMonoid N₃] [Module R N₃] [Module S₃ M₃]
[SMulCommClass R₃ S₃ M₃] [ContinuousConstSMul S₃ M₃] [Module S N₂] [ContinuousConstSMul S N₂]
[SMulCommClass R S N₂] [Module S N₃] [SMulCommClass R S N₃] [ContinuousConstSMul S N₃]
{σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃} [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] (c : S)
(h : M₂ →SL[σ₂₃] M₃) (f g : M →SL[σ₁₂] M₂) (x y z : M)
/-- `ContinuousLinearMap.prod` as an `Equiv`. -/
@[simps apply]
def prodEquiv : (M →L[R] N₂) × (M →L[R] N₃) ≃ (M →L[R] N₂ × N₃) 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
#align continuous_linear_map.prod_equiv ContinuousLinearMap.prodEquiv
#align continuous_linear_map.prod_equiv_apply ContinuousLinearMap.prodEquiv_apply
theorem prod_ext_iff {f g : M × N₂ →L[R] N₃} :
f = g ↔ f.comp (inl _ _ _) = g.comp (inl _ _ _) ∧ f.comp (inr _ _ _) = g.comp (inr _ _ _) := by
simp only [← coe_inj, LinearMap.prod_ext_iff]
rfl
#align continuous_linear_map.prod_ext_iff ContinuousLinearMap.prod_ext_iff
@[ext]
theorem prod_ext {f g : M × N₂ →L[R] N₃} (hl : f.comp (inl _ _ _) = g.comp (inl _ _ _))
(hr : f.comp (inr _ _ _) = g.comp (inr _ _ _)) : f = g :=
prod_ext_iff.2 ⟨hl, hr⟩
#align continuous_linear_map.prod_ext ContinuousLinearMap.prod_ext
variable [ContinuousAdd M₂] [ContinuousAdd M₃] [ContinuousAdd N₂]
instance module : Module S₃ (M →SL[σ₁₃] M₃) where
zero_smul _ := ext fun _ => zero_smul S₃ _
add_smul _ _ _ := ext fun _ => add_smul _ _ _
#align continuous_linear_map.module ContinuousLinearMap.module
instance isCentralScalar [Module S₃ᵐᵒᵖ M₃] [IsCentralScalar S₃ M₃] :
IsCentralScalar S₃ (M →SL[σ₁₃] M₃) where
op_smul_eq_smul _ _ := ext fun _ => op_smul_eq_smul _ _
#align continuous_linear_map.is_central_scalar ContinuousLinearMap.isCentralScalar
variable (S) [ContinuousAdd N₃]
/-- `ContinuousLinearMap.prod` as a `LinearEquiv`. -/
@[simps apply]
def prodₗ : ((M →L[R] N₂) × (M →L[R] N₃)) ≃ₗ[S] M →L[R] N₂ × N₃ :=
{ prodEquiv with
map_add' := fun _f _g => rfl
map_smul' := fun _c _f => rfl }
#align continuous_linear_map.prodₗ ContinuousLinearMap.prodₗ
#align continuous_linear_map.prodₗ_apply ContinuousLinearMap.prodₗ_apply
/-- The coercion from `M →L[R] M₂` to `M →ₗ[R] M₂`, as a linear map. -/
@[simps]
def coeLM : (M →L[R] N₃) →ₗ[S] M →ₗ[R] N₃ where
toFun := (↑)
map_add' f g := coe_add f g
map_smul' c f := coe_smul c f
#align continuous_linear_map.coe_lm ContinuousLinearMap.coeLM
#align continuous_linear_map.coe_lm_apply ContinuousLinearMap.coeLM_apply
variable {S} (σ₁₃)
/-- The coercion from `M →SL[σ] M₂` to `M →ₛₗ[σ] M₂`, as a linear map. -/
@[simps]
def coeLMₛₗ : (M →SL[σ₁₃] M₃) →ₗ[S₃] M →ₛₗ[σ₁₃] M₃ where
toFun := (↑)
map_add' f g := coe_add f g
map_smul' c f := coe_smul c f
#align continuous_linear_map.coe_lmₛₗ ContinuousLinearMap.coeLMₛₗ
#align continuous_linear_map.coe_lmₛₗ_apply ContinuousLinearMap.coeLMₛₗ_apply
end SMul
section SMulRightₗ
variable {R S T M M₂ : Type*} [Semiring R] [Semiring S] [Semiring T] [Module R S]
[AddCommMonoid M₂] [Module R M₂] [Module S M₂] [IsScalarTower R S M₂] [TopologicalSpace S]
[TopologicalSpace M₂] [ContinuousSMul S M₂] [TopologicalSpace M] [AddCommMonoid M] [Module R M]
[ContinuousAdd M₂] [Module T M₂] [ContinuousConstSMul T M₂] [SMulCommClass R T M₂]
[SMulCommClass S T M₂]
/-- Given `c : E →L[𝕜] 𝕜`, `c.smulRightₗ` is the linear map from `F` to `E →L[𝕜] F`
sending `f` to `fun e => c e • f`. See also `ContinuousLinearMap.smulRightL`. -/
def smulRightₗ (c : M →L[R] S) : M₂ →ₗ[T] M →L[R] M₂ where
toFun := c.smulRight
map_add' x y := by
ext e
apply smul_add (c e)
map_smul' a x := by
ext e
dsimp
apply smul_comm
#align continuous_linear_map.smul_rightₗ ContinuousLinearMap.smulRightₗ
@[simp]
theorem coe_smulRightₗ (c : M →L[R] S) : ⇑(smulRightₗ c : M₂ →ₗ[T] M →L[R] M₂) = c.smulRight :=
rfl
#align continuous_linear_map.coe_smul_rightₗ ContinuousLinearMap.coe_smulRightₗ
end SMulRightₗ
section CommRing
variable {R : Type*} [CommRing R] {M : Type*} [TopologicalSpace M] [AddCommGroup M] {M₂ : Type*}
[TopologicalSpace M₂] [AddCommGroup M₂] {M₃ : Type*} [TopologicalSpace M₃] [AddCommGroup M₃]
[Module R M] [Module R M₂] [Module R M₃] [ContinuousConstSMul R M₃]
variable [TopologicalAddGroup M₂] [ContinuousConstSMul R M₂]
instance algebra : Algebra R (M₂ →L[R] M₂) :=
Algebra.ofModule smul_comp fun _ _ _ => comp_smul _ _ _
#align continuous_linear_map.algebra ContinuousLinearMap.algebra
@[simp] theorem algebraMap_apply (r : R) (m : M₂) : algebraMap R (M₂ →L[R] M₂) r m = r • m := rfl
end CommRing
section RestrictScalars
variable {A M M₂ : Type*} [Ring A] [AddCommGroup M] [AddCommGroup M₂] [Module A M] [Module A M₂]
[TopologicalSpace M] [TopologicalSpace M₂] (R : Type*) [Ring R] [Module R M] [Module R M₂]
[LinearMap.CompatibleSMul M M₂ R A]
/-- If `A` is an `R`-algebra, then a continuous `A`-linear map can be interpreted as a continuous
`R`-linear map. We assume `LinearMap.CompatibleSMul M M₂ R A` to match assumptions of
`LinearMap.map_smul_of_tower`. -/
def restrictScalars (f : M →L[A] M₂) : M →L[R] M₂ :=
⟨(f : M →ₗ[A] M₂).restrictScalars R, f.continuous⟩
#align continuous_linear_map.restrict_scalars ContinuousLinearMap.restrictScalars
variable {R}
@[simp] -- @[norm_cast] -- Porting note: This theorem can't be a `norm_cast` theorem.
theorem coe_restrictScalars (f : M →L[A] M₂) :
(f.restrictScalars R : M →ₗ[R] M₂) = (f : M →ₗ[A] M₂).restrictScalars R :=
rfl
#align continuous_linear_map.coe_restrict_scalars ContinuousLinearMap.coe_restrictScalars
@[simp]
theorem coe_restrictScalars' (f : M →L[A] M₂) : ⇑(f.restrictScalars R) = f :=
rfl
#align continuous_linear_map.coe_restrict_scalars' ContinuousLinearMap.coe_restrictScalars'
@[simp]
theorem restrictScalars_zero : (0 : M →L[A] M₂).restrictScalars R = 0 :=
rfl
#align continuous_linear_map.restrict_scalars_zero ContinuousLinearMap.restrictScalars_zero
section
variable [TopologicalAddGroup M₂]
@[simp]
theorem restrictScalars_add (f g : M →L[A] M₂) :
(f + g).restrictScalars R = f.restrictScalars R + g.restrictScalars R :=
rfl
#align continuous_linear_map.restrict_scalars_add ContinuousLinearMap.restrictScalars_add
@[simp]
theorem restrictScalars_neg (f : M →L[A] M₂) : (-f).restrictScalars R = -f.restrictScalars R :=
rfl
#align continuous_linear_map.restrict_scalars_neg ContinuousLinearMap.restrictScalars_neg
end
variable {S : Type*}
variable [Ring S] [Module S M₂] [ContinuousConstSMul S M₂] [SMulCommClass A S M₂]
[SMulCommClass R S M₂]
@[simp]
theorem restrictScalars_smul (c : S) (f : M →L[A] M₂) :
(c • f).restrictScalars R = c • f.restrictScalars R :=
rfl
#align continuous_linear_map.restrict_scalars_smul ContinuousLinearMap.restrictScalars_smul
variable (A M M₂ R S)
variable [TopologicalAddGroup M₂]
/-- `ContinuousLinearMap.restrictScalars` as a `LinearMap`. See also
`ContinuousLinearMap.restrictScalarsL`. -/
def restrictScalarsₗ : (M →L[A] M₂) →ₗ[S] M →L[R] M₂ where
toFun := restrictScalars R
map_add' := restrictScalars_add
map_smul' := restrictScalars_smul
#align continuous_linear_map.restrict_scalarsₗ ContinuousLinearMap.restrictScalarsₗ
variable {A M M₂ R S}
@[simp]
theorem coe_restrictScalarsₗ : ⇑(restrictScalarsₗ A M M₂ R S) = restrictScalars R :=
rfl
#align continuous_linear_map.coe_restrict_scalarsₗ ContinuousLinearMap.coe_restrictScalarsₗ
end RestrictScalars
end ContinuousLinearMap
namespace ContinuousLinearEquiv
section AddCommMonoid
variable {R₁ : Type*} {R₂ : Type*} {R₃ : Type*} [Semiring R₁] [Semiring R₂] [Semiring R₃]
{σ₁₂ : R₁ →+* R₂} {σ₂₁ : R₂ →+* R₁} [RingHomInvPair σ₁₂ σ₂₁] [RingHomInvPair σ₂₁ σ₁₂]
{σ₂₃ : R₂ →+* R₃} {σ₃₂ : R₃ →+* R₂} [RingHomInvPair σ₂₃ σ₃₂] [RingHomInvPair σ₃₂ σ₂₃]
{σ₁₃ : R₁ →+* R₃} {σ₃₁ : R₃ →+* R₁} [RingHomInvPair σ₁₃ σ₃₁] [RingHomInvPair σ₃₁ σ₁₃]
[RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [RingHomCompTriple σ₃₂ σ₂₁ σ₃₁] {M₁ : Type*}
[TopologicalSpace M₁] [AddCommMonoid M₁] {M'₁ : Type*} [TopologicalSpace M'₁] [AddCommMonoid M'₁]
{M₂ : Type*} [TopologicalSpace M₂] [AddCommMonoid M₂] {M₃ : Type*} [TopologicalSpace M₃]
[AddCommMonoid M₃] {M₄ : Type*} [TopologicalSpace M₄] [AddCommMonoid M₄] [Module R₁ M₁]
[Module R₁ M'₁] [Module R₂ M₂] [Module R₃ M₃]
/-- A continuous linear equivalence induces a continuous linear map. -/
@[coe]
def toContinuousLinearMap (e : M₁ ≃SL[σ₁₂] M₂) : M₁ →SL[σ₁₂] M₂ :=
{ e.toLinearEquiv.toLinearMap with cont := e.continuous_toFun }
#align continuous_linear_equiv.to_continuous_linear_map ContinuousLinearEquiv.toContinuousLinearMap
/-- Coerce continuous linear equivs to continuous linear maps. -/
instance ContinuousLinearMap.coe : Coe (M₁ ≃SL[σ₁₂] M₂) (M₁ →SL[σ₁₂] M₂) :=
⟨toContinuousLinearMap⟩
#align continuous_linear_equiv.continuous_linear_map.has_coe ContinuousLinearEquiv.ContinuousLinearMap.coe
instance equivLike :
EquivLike (M₁ ≃SL[σ₁₂] M₂) M₁ M₂ where
coe f := f.toFun
inv f := f.invFun
coe_injective' f g h₁ h₂ := by
cases' f with f' _
cases' g with g' _
rcases f' with ⟨⟨⟨_, _⟩, _⟩, _⟩
rcases g' with ⟨⟨⟨_, _⟩, _⟩, _⟩
congr
left_inv f := f.left_inv
right_inv f := f.right_inv
instance continuousSemilinearEquivClass :
ContinuousSemilinearEquivClass (M₁ ≃SL[σ₁₂] M₂) σ₁₂ M₁ M₂ where
map_add f := f.map_add'
map_smulₛₗ f := f.map_smul'
map_continuous := continuous_toFun
inv_continuous := continuous_invFun
#align continuous_linear_equiv.continuous_semilinear_equiv_class ContinuousLinearEquiv.continuousSemilinearEquivClass
-- see Note [function coercion]
-- /-- Coerce continuous linear equivs to maps. -/
-- instance : CoeFun (M₁ ≃SL[σ₁₂] M₂) fun _ => M₁ → M₂ :=
-- ⟨fun f => f⟩
-- Porting note: Syntactic tautology.
#noalign continuous_linear_equiv.coe_def_rev
theorem coe_apply (e : M₁ ≃SL[σ₁₂] M₂) (b : M₁) : (e : M₁ →SL[σ₁₂] M₂) b = e b :=
rfl
#align continuous_linear_equiv.coe_apply ContinuousLinearEquiv.coe_apply
@[simp]
theorem coe_toLinearEquiv (f : M₁ ≃SL[σ₁₂] M₂) : ⇑f.toLinearEquiv = f :=
rfl
#align continuous_linear_equiv.coe_to_linear_equiv ContinuousLinearEquiv.coe_toLinearEquiv
@[simp, norm_cast]
theorem coe_coe (e : M₁ ≃SL[σ₁₂] M₂) : ⇑(e : M₁ →SL[σ₁₂] M₂) = e :=
rfl
#align continuous_linear_equiv.coe_coe ContinuousLinearEquiv.coe_coe
theorem toLinearEquiv_injective :
Function.Injective (toLinearEquiv : (M₁ ≃SL[σ₁₂] M₂) → M₁ ≃ₛₗ[σ₁₂] M₂) := by
rintro ⟨e, _, _⟩ ⟨e', _, _⟩ rfl
rfl
#align continuous_linear_equiv.to_linear_equiv_injective ContinuousLinearEquiv.toLinearEquiv_injective
@[ext]
theorem ext {f g : M₁ ≃SL[σ₁₂] M₂} (h : (f : M₁ → M₂) = g) : f = g :=
toLinearEquiv_injective <| LinearEquiv.ext <| congr_fun h
#align continuous_linear_equiv.ext ContinuousLinearEquiv.ext
theorem coe_injective : Function.Injective ((↑) : (M₁ ≃SL[σ₁₂] M₂) → M₁ →SL[σ₁₂] M₂) :=
fun _e _e' h => ext <| funext <| ContinuousLinearMap.ext_iff.1 h
#align continuous_linear_equiv.coe_injective ContinuousLinearEquiv.coe_injective
@[simp, norm_cast]
theorem coe_inj {e e' : M₁ ≃SL[σ₁₂] M₂} : (e : M₁ →SL[σ₁₂] M₂) = e' ↔ e = e' :=
coe_injective.eq_iff
#align continuous_linear_equiv.coe_inj ContinuousLinearEquiv.coe_inj
/-- A continuous linear equivalence induces a homeomorphism. -/
def toHomeomorph (e : M₁ ≃SL[σ₁₂] M₂) : M₁ ≃ₜ M₂ :=
{ e with toEquiv := e.toLinearEquiv.toEquiv }
#align continuous_linear_equiv.to_homeomorph ContinuousLinearEquiv.toHomeomorph
@[simp]
theorem coe_toHomeomorph (e : M₁ ≃SL[σ₁₂] M₂) : ⇑e.toHomeomorph = e :=
rfl
#align continuous_linear_equiv.coe_to_homeomorph ContinuousLinearEquiv.coe_toHomeomorph
theorem isOpenMap (e : M₁ ≃SL[σ₁₂] M₂) : IsOpenMap e :=
(ContinuousLinearEquiv.toHomeomorph e).isOpenMap
theorem image_closure (e : M₁ ≃SL[σ₁₂] M₂) (s : Set M₁) : e '' closure s = closure (e '' s) :=
e.toHomeomorph.image_closure s
#align continuous_linear_equiv.image_closure ContinuousLinearEquiv.image_closure
theorem preimage_closure (e : M₁ ≃SL[σ₁₂] M₂) (s : Set M₂) : e ⁻¹' closure s = closure (e ⁻¹' s) :=
e.toHomeomorph.preimage_closure s
#align continuous_linear_equiv.preimage_closure ContinuousLinearEquiv.preimage_closure
@[simp]
theorem isClosed_image (e : M₁ ≃SL[σ₁₂] M₂) {s : Set M₁} : IsClosed (e '' s) ↔ IsClosed s :=
e.toHomeomorph.isClosed_image
#align continuous_linear_equiv.is_closed_image ContinuousLinearEquiv.isClosed_image
theorem map_nhds_eq (e : M₁ ≃SL[σ₁₂] M₂) (x : M₁) : map e (𝓝 x) = 𝓝 (e x) :=
e.toHomeomorph.map_nhds_eq x
#align continuous_linear_equiv.map_nhds_eq ContinuousLinearEquiv.map_nhds_eq
-- Make some straightforward lemmas available to `simp`.
-- @[simp] -- Porting note (#10618): simp can prove this
theorem map_zero (e : M₁ ≃SL[σ₁₂] M₂) : e (0 : M₁) = 0 :=
(e : M₁ →SL[σ₁₂] M₂).map_zero
#align continuous_linear_equiv.map_zero ContinuousLinearEquiv.map_zero
-- @[simp] -- Porting note (#10618): simp can prove this
theorem map_add (e : M₁ ≃SL[σ₁₂] M₂) (x y : M₁) : e (x + y) = e x + e y :=
(e : M₁ →SL[σ₁₂] M₂).map_add x y
#align continuous_linear_equiv.map_add ContinuousLinearEquiv.map_add
-- @[simp] -- Porting note (#10618): simp can prove this
theorem map_smulₛₗ (e : M₁ ≃SL[σ₁₂] M₂) (c : R₁) (x : M₁) : e (c • x) = σ₁₂ c • e x :=
(e : M₁ →SL[σ₁₂] M₂).map_smulₛₗ c x
#align continuous_linear_equiv.map_smulₛₗ ContinuousLinearEquiv.map_smulₛₗ
-- @[simp] -- Porting note (#10618): simp can prove this
theorem map_smul [Module R₁ M₂] (e : M₁ ≃L[R₁] M₂) (c : R₁) (x : M₁) : e (c • x) = c • e x :=
(e : M₁ →L[R₁] M₂).map_smul c x
#align continuous_linear_equiv.map_smul ContinuousLinearEquiv.map_smul
-- @[simp] -- Porting note (#10618): simp can prove this
theorem map_eq_zero_iff (e : M₁ ≃SL[σ₁₂] M₂) {x : M₁} : e x = 0 ↔ x = 0 :=
e.toLinearEquiv.map_eq_zero_iff
#align continuous_linear_equiv.map_eq_zero_iff ContinuousLinearEquiv.map_eq_zero_iff
attribute [continuity]
ContinuousLinearEquiv.continuous_toFun ContinuousLinearEquiv.continuous_invFun
@[continuity]
protected theorem continuous (e : M₁ ≃SL[σ₁₂] M₂) : Continuous (e : M₁ → M₂) :=
e.continuous_toFun
#align continuous_linear_equiv.continuous ContinuousLinearEquiv.continuous
protected theorem continuousOn (e : M₁ ≃SL[σ₁₂] M₂) {s : Set M₁} : ContinuousOn (e : M₁ → M₂) s :=
e.continuous.continuousOn
#align continuous_linear_equiv.continuous_on ContinuousLinearEquiv.continuousOn
protected theorem continuousAt (e : M₁ ≃SL[σ₁₂] M₂) {x : M₁} : ContinuousAt (e : M₁ → M₂) x :=
e.continuous.continuousAt
#align continuous_linear_equiv.continuous_at ContinuousLinearEquiv.continuousAt
protected theorem continuousWithinAt (e : M₁ ≃SL[σ₁₂] M₂) {s : Set M₁} {x : M₁} :
ContinuousWithinAt (e : M₁ → M₂) s x :=
e.continuous.continuousWithinAt
#align continuous_linear_equiv.continuous_within_at ContinuousLinearEquiv.continuousWithinAt
theorem comp_continuousOn_iff {α : Type*} [TopologicalSpace α] (e : M₁ ≃SL[σ₁₂] M₂) {f : α → M₁}
{s : Set α} : ContinuousOn (e ∘ f) s ↔ ContinuousOn f s :=
e.toHomeomorph.comp_continuousOn_iff _ _
#align continuous_linear_equiv.comp_continuous_on_iff ContinuousLinearEquiv.comp_continuousOn_iff
theorem comp_continuous_iff {α : Type*} [TopologicalSpace α] (e : M₁ ≃SL[σ₁₂] M₂) {f : α → M₁} :
Continuous (e ∘ f) ↔ Continuous f :=
e.toHomeomorph.comp_continuous_iff
#align continuous_linear_equiv.comp_continuous_iff ContinuousLinearEquiv.comp_continuous_iff
/-- An extensionality lemma for `R ≃L[R] M`. -/
theorem ext₁ [TopologicalSpace R₁] {f g : R₁ ≃L[R₁] M₁} (h : f 1 = g 1) : f = g :=
ext <| funext fun x => mul_one x ▸ by rw [← smul_eq_mul, map_smul, h, map_smul]
#align continuous_linear_equiv.ext₁ ContinuousLinearEquiv.ext₁
section
variable (R₁ M₁)
/-- The identity map as a continuous linear equivalence. -/
@[refl]
protected def refl : M₁ ≃L[R₁] M₁ :=
{ LinearEquiv.refl R₁ M₁ with
continuous_toFun := continuous_id
continuous_invFun := continuous_id }
#align continuous_linear_equiv.refl ContinuousLinearEquiv.refl
end
@[simp, norm_cast]
theorem coe_refl : ↑(ContinuousLinearEquiv.refl R₁ M₁) = ContinuousLinearMap.id R₁ M₁ :=
rfl
#align continuous_linear_equiv.coe_refl ContinuousLinearEquiv.coe_refl
@[simp, norm_cast]
theorem coe_refl' : ⇑(ContinuousLinearEquiv.refl R₁ M₁) = id :=
rfl
#align continuous_linear_equiv.coe_refl' ContinuousLinearEquiv.coe_refl'
/-- The inverse of a continuous linear equivalence as a continuous linear equivalence-/
@[symm]
protected def symm (e : M₁ ≃SL[σ₁₂] M₂) : M₂ ≃SL[σ₂₁] M₁ :=
{ e.toLinearEquiv.symm with
continuous_toFun := e.continuous_invFun
continuous_invFun := e.continuous_toFun }
#align continuous_linear_equiv.symm ContinuousLinearEquiv.symm
@[simp]
theorem symm_toLinearEquiv (e : M₁ ≃SL[σ₁₂] M₂) : e.symm.toLinearEquiv = e.toLinearEquiv.symm := by
ext
rfl
#align continuous_linear_equiv.symm_to_linear_equiv ContinuousLinearEquiv.symm_toLinearEquiv
@[simp]
theorem symm_toHomeomorph (e : M₁ ≃SL[σ₁₂] M₂) : e.toHomeomorph.symm = e.symm.toHomeomorph :=
rfl
#align continuous_linear_equiv.symm_to_homeomorph ContinuousLinearEquiv.symm_toHomeomorph
/-- 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 (h : M₁ ≃SL[σ₁₂] M₂) : M₁ → M₂ :=
h
#align continuous_linear_equiv.simps.apply ContinuousLinearEquiv.Simps.apply
/-- See Note [custom simps projection] -/
def Simps.symm_apply (h : M₁ ≃SL[σ₁₂] M₂) : M₂ → M₁ :=
h.symm
#align continuous_linear_equiv.simps.symm_apply ContinuousLinearEquiv.Simps.symm_apply
initialize_simps_projections ContinuousLinearEquiv (toFun → apply, invFun → symm_apply)
theorem symm_map_nhds_eq (e : M₁ ≃SL[σ₁₂] M₂) (x : M₁) : map e.symm (𝓝 (e x)) = 𝓝 x :=
e.toHomeomorph.symm_map_nhds_eq x
#align continuous_linear_equiv.symm_map_nhds_eq ContinuousLinearEquiv.symm_map_nhds_eq
/-- The composition of two continuous linear equivalences as a continuous linear equivalence. -/
@[trans]
protected def trans (e₁ : M₁ ≃SL[σ₁₂] M₂) (e₂ : M₂ ≃SL[σ₂₃] M₃) : M₁ ≃SL[σ₁₃] M₃ :=
{ e₁.toLinearEquiv.trans e₂.toLinearEquiv with
continuous_toFun := e₂.continuous_toFun.comp e₁.continuous_toFun
continuous_invFun := e₁.continuous_invFun.comp e₂.continuous_invFun }
#align continuous_linear_equiv.trans ContinuousLinearEquiv.trans
@[simp]
theorem trans_toLinearEquiv (e₁ : M₁ ≃SL[σ₁₂] M₂) (e₂ : M₂ ≃SL[σ₂₃] M₃) :
(e₁.trans e₂).toLinearEquiv = e₁.toLinearEquiv.trans e₂.toLinearEquiv := by
ext
rfl
#align continuous_linear_equiv.trans_to_linear_equiv ContinuousLinearEquiv.trans_toLinearEquiv
/-- Product of two continuous linear equivalences. The map comes from `Equiv.prodCongr`. -/
def prod [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (e : M₁ ≃L[R₁] M₂) (e' : M₃ ≃L[R₁] M₄) :
(M₁ × M₃) ≃L[R₁] M₂ × M₄ :=
{ e.toLinearEquiv.prod e'.toLinearEquiv with
continuous_toFun := e.continuous_toFun.prod_map e'.continuous_toFun
continuous_invFun := e.continuous_invFun.prod_map e'.continuous_invFun }
#align continuous_linear_equiv.prod ContinuousLinearEquiv.prod
@[simp, norm_cast]
theorem prod_apply [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (e : M₁ ≃L[R₁] M₂)
(e' : M₃ ≃L[R₁] M₄) (x) : e.prod e' x = (e x.1, e' x.2) :=
rfl
#align continuous_linear_equiv.prod_apply ContinuousLinearEquiv.prod_apply
@[simp, norm_cast]
theorem coe_prod [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (e : M₁ ≃L[R₁] M₂)
(e' : M₃ ≃L[R₁] M₄) :
(e.prod e' : M₁ × M₃ →L[R₁] M₂ × M₄) = (e : M₁ →L[R₁] M₂).prodMap (e' : M₃ →L[R₁] M₄) :=
rfl
#align continuous_linear_equiv.coe_prod ContinuousLinearEquiv.coe_prod
theorem prod_symm [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (e : M₁ ≃L[R₁] M₂)
(e' : M₃ ≃L[R₁] M₄) : (e.prod e').symm = e.symm.prod e'.symm :=
rfl
#align continuous_linear_equiv.prod_symm ContinuousLinearEquiv.prod_symm
variable (R₁ M₁ M₂)
/-- Product of modules is commutative up to continuous linear isomorphism. -/
@[simps! apply toLinearEquiv]
def prodComm [Module R₁ M₂] : (M₁ × M₂) ≃L[R₁] M₂ × M₁ :=
{ LinearEquiv.prodComm R₁ M₁ M₂ with
continuous_toFun := continuous_swap
continuous_invFun := continuous_swap }
@[simp] lemma prodComm_symm [Module R₁ M₂] : (prodComm R₁ M₁ M₂).symm = prodComm R₁ M₂ M₁ := rfl
variable {R₁ M₁ M₂}
protected theorem bijective (e : M₁ ≃SL[σ₁₂] M₂) : Function.Bijective e :=
e.toLinearEquiv.toEquiv.bijective
#align continuous_linear_equiv.bijective ContinuousLinearEquiv.bijective
protected theorem injective (e : M₁ ≃SL[σ₁₂] M₂) : Function.Injective e :=
e.toLinearEquiv.toEquiv.injective
#align continuous_linear_equiv.injective ContinuousLinearEquiv.injective
protected theorem surjective (e : M₁ ≃SL[σ₁₂] M₂) : Function.Surjective e :=
e.toLinearEquiv.toEquiv.surjective
#align continuous_linear_equiv.surjective ContinuousLinearEquiv.surjective
@[simp]
theorem trans_apply (e₁ : M₁ ≃SL[σ₁₂] M₂) (e₂ : M₂ ≃SL[σ₂₃] M₃) (c : M₁) :
(e₁.trans e₂) c = e₂ (e₁ c) :=
rfl
#align continuous_linear_equiv.trans_apply ContinuousLinearEquiv.trans_apply
@[simp]
theorem apply_symm_apply (e : M₁ ≃SL[σ₁₂] M₂) (c : M₂) : e (e.symm c) = c :=
e.1.right_inv c
#align continuous_linear_equiv.apply_symm_apply ContinuousLinearEquiv.apply_symm_apply
@[simp]
theorem symm_apply_apply (e : M₁ ≃SL[σ₁₂] M₂) (b : M₁) : e.symm (e b) = b :=
e.1.left_inv b
#align continuous_linear_equiv.symm_apply_apply ContinuousLinearEquiv.symm_apply_apply
@[simp]
theorem symm_trans_apply (e₁ : M₂ ≃SL[σ₂₁] M₁) (e₂ : M₃ ≃SL[σ₃₂] M₂) (c : M₁) :
(e₂.trans e₁).symm c = e₂.symm (e₁.symm c) :=
rfl
#align continuous_linear_equiv.symm_trans_apply ContinuousLinearEquiv.symm_trans_apply
@[simp]
theorem symm_image_image (e : M₁ ≃SL[σ₁₂] M₂) (s : Set M₁) : e.symm '' (e '' s) = s :=
e.toLinearEquiv.toEquiv.symm_image_image s
#align continuous_linear_equiv.symm_image_image ContinuousLinearEquiv.symm_image_image
@[simp]
theorem image_symm_image (e : M₁ ≃SL[σ₁₂] M₂) (s : Set M₂) : e '' (e.symm '' s) = s :=
e.symm.symm_image_image s
#align continuous_linear_equiv.image_symm_image ContinuousLinearEquiv.image_symm_image
@[simp, norm_cast]
theorem comp_coe (f : M₁ ≃SL[σ₁₂] M₂) (f' : M₂ ≃SL[σ₂₃] M₃) :
(f' : M₂ →SL[σ₂₃] M₃).comp (f : M₁ →SL[σ₁₂] M₂) = (f.trans f' : M₁ →SL[σ₁₃] M₃) :=
rfl
#align continuous_linear_equiv.comp_coe ContinuousLinearEquiv.comp_coe
-- Porting note: The priority should be higher than `comp_coe`.
@[simp high]
theorem coe_comp_coe_symm (e : M₁ ≃SL[σ₁₂] M₂) :
(e : M₁ →SL[σ₁₂] M₂).comp (e.symm : M₂ →SL[σ₂₁] M₁) = ContinuousLinearMap.id R₂ M₂ :=
ContinuousLinearMap.ext e.apply_symm_apply
#align continuous_linear_equiv.coe_comp_coe_symm ContinuousLinearEquiv.coe_comp_coe_symm
-- Porting note: The priority should be higher than `comp_coe`.
@[simp high]
theorem coe_symm_comp_coe (e : M₁ ≃SL[σ₁₂] M₂) :
(e.symm : M₂ →SL[σ₂₁] M₁).comp (e : M₁ →SL[σ₁₂] M₂) = ContinuousLinearMap.id R₁ M₁ :=
ContinuousLinearMap.ext e.symm_apply_apply
#align continuous_linear_equiv.coe_symm_comp_coe ContinuousLinearEquiv.coe_symm_comp_coe
@[simp]
theorem symm_comp_self (e : M₁ ≃SL[σ₁₂] M₂) : (e.symm : M₂ → M₁) ∘ (e : M₁ → M₂) = id := by
ext x
exact symm_apply_apply e x
#align continuous_linear_equiv.symm_comp_self ContinuousLinearEquiv.symm_comp_self
@[simp]
| Mathlib/Topology/Algebra/Module/Basic.lean | 2,210 | 2,212 | theorem self_comp_symm (e : M₁ ≃SL[σ₁₂] M₂) : (e : M₁ → M₂) ∘ (e.symm : M₂ → M₁) = id := by |
ext x
exact apply_symm_apply e x
|
/-
Copyright (c) 2023 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Heather Macbeth
-/
import Mathlib.MeasureTheory.Constructions.Pi
import Mathlib.MeasureTheory.Integral.Lebesgue
/-!
# Marginals of multivariate functions
In this file, we define a convenient way to compute integrals of multivariate functions, especially
if you want to write expressions where you integrate only over some of the variables that the
function depends on. This is common in induction arguments involving integrals of multivariate
functions.
This constructions allows working with iterated integrals and applying Tonelli's theorem
and Fubini's theorem, without using measurable equivalences by changing the representation of your
space (e.g. `((ι ⊕ ι') → ℝ) ≃ (ι → ℝ) × (ι' → ℝ)`).
## Main Definitions
* Assume that `∀ i : ι, π i` is a product of measurable spaces with measures `μ i` on `π i`,
`f : (∀ i, π i) → ℝ≥0∞` is a function and `s : Finset ι`.
Then `lmarginal μ s f` or `∫⋯∫⁻_s, f ∂μ` is the function that integrates `f`
over all variables in `s`. It returns a function that still takes the same variables as `f`,
but is constant in the variables in `s`. Mathematically, if `s = {i₁, ..., iₖ}`,
then `lmarginal μ s f` is the expression
$$
\vec{x}\mapsto \int\!\!\cdots\!\!\int f(\vec{x}[\vec{y}])dy_{i_1}\cdots dy_{i_k}.
$$
where $\vec{x}[\vec{y}]$ is the vector $\vec{x}$ with $x_{i_j}$ replaced by $y_{i_j}$ for all
$1 \le j \le k$.
If `f` is the distribution of a random variable, this is the marginal distribution of all
variables not in `s` (but not the most general notion, since we only consider product measures
here).
Note that the notation `∫⋯∫⁻_s, f ∂μ` is not a binder, and returns a function.
## Main Results
* `lmarginal_union` is the analogue of Tonelli's theorem for iterated integrals. It states that
for measurable functions `f` and disjoint finsets `s` and `t` we have
`∫⋯∫⁻_s ∪ t, f ∂μ = ∫⋯∫⁻_s, ∫⋯∫⁻_t, f ∂μ ∂μ`.
## Implementation notes
The function `f` can have an arbitrary product as its domain (even infinite products), but the
set `s` of integration variables is a `Finset`. We are assuming that the function `f` is measurable
for most of this file. Note that asking whether it is `AEMeasurable` is not even well-posed,
since there is no well-behaved measure on the domain of `f`.
## Todo
* Define the marginal function for functions taking values in a Banach space.
-/
open scoped Classical ENNReal
open Set Function Equiv Finset
noncomputable section
namespace MeasureTheory
section LMarginal
variable {δ δ' : Type*} {π : δ → Type*} [∀ x, MeasurableSpace (π x)]
variable {μ : ∀ i, Measure (π i)} [∀ i, SigmaFinite (μ i)] [DecidableEq δ]
variable {s t : Finset δ} {f g : (∀ i, π i) → ℝ≥0∞} {x y : ∀ i, π i} {i : δ}
/-- Integrate `f(x₁,…,xₙ)` over all variables `xᵢ` where `i ∈ s`. Return a function in the
remaining variables (it will be constant in the `xᵢ` for `i ∈ s`).
This is the marginal distribution of all variables not in `s` when the considered measure
is the product measure. -/
def lmarginal (μ : ∀ i, Measure (π i)) (s : Finset δ) (f : (∀ i, π i) → ℝ≥0∞)
(x : ∀ i, π i) : ℝ≥0∞ :=
∫⁻ y : ∀ i : s, π i, f (updateFinset x s y) ∂Measure.pi fun i : s => μ i
-- Note: this notation is not a binder. This is more convenient since it returns a function.
@[inherit_doc]
notation "∫⋯∫⁻_" s ", " f " ∂" μ:70 => lmarginal μ s f
@[inherit_doc]
notation "∫⋯∫⁻_" s ", " f => lmarginal (fun _ ↦ volume) s f
variable (μ)
theorem _root_.Measurable.lmarginal (hf : Measurable f) : Measurable (∫⋯∫⁻_s, f ∂μ) := by
refine Measurable.lintegral_prod_right ?_
refine hf.comp ?_
rw [measurable_pi_iff]; intro i
by_cases hi : i ∈ s
· simp [hi, updateFinset]
exact measurable_pi_iff.1 measurable_snd _
· simp [hi, updateFinset]
exact measurable_pi_iff.1 measurable_fst _
@[simp] theorem lmarginal_empty (f : (∀ i, π i) → ℝ≥0∞) : ∫⋯∫⁻_∅, f ∂μ = f := by
ext1 x
simp_rw [lmarginal, Measure.pi_of_empty fun i : (∅ : Finset δ) => μ i]
apply lintegral_dirac'
exact Subsingleton.measurable
/-- The marginal distribution is independent of the variables in `s`. -/
| Mathlib/MeasureTheory/Integral/Marginal.lean | 105 | 108 | theorem lmarginal_congr {x y : ∀ i, π i} (f : (∀ i, π i) → ℝ≥0∞)
(h : ∀ i ∉ s, x i = y i) :
(∫⋯∫⁻_s, f ∂μ) x = (∫⋯∫⁻_s, f ∂μ) y := by |
dsimp [lmarginal, updateFinset_def]; rcongr; exact h _ ‹_›
|
/-
Copyright (c) 2022 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Jireh Loreaux
-/
import Mathlib.Algebra.Star.Center
import Mathlib.Algebra.Star.StarAlgHom
import Mathlib.Algebra.Algebra.Subalgebra.Basic
import Mathlib.Algebra.Star.Pointwise
import Mathlib.Algebra.Star.Module
import Mathlib.RingTheory.Adjoin.Basic
#align_import algebra.star.subalgebra from "leanprover-community/mathlib"@"160ef3e338a2a4f21a280e4c152d4016156e516d"
/-!
# Star subalgebras
A *-subalgebra is a subalgebra of a *-algebra which is closed under *.
The centralizer of a *-closed set is a *-subalgebra.
-/
universe u v
/-- A *-subalgebra is a subalgebra of a *-algebra which is closed under *. -/
structure StarSubalgebra (R : Type u) (A : Type v) [CommSemiring R] [StarRing R] [Semiring A]
[StarRing A] [Algebra R A] [StarModule R A] extends Subalgebra R A : Type v where
/-- The `carrier` is closed under the `star` operation. -/
star_mem' {a} : a ∈ carrier → star a ∈ carrier
#align star_subalgebra StarSubalgebra
namespace StarSubalgebra
/-- Forgetting that a *-subalgebra is closed under *.
-/
add_decl_doc StarSubalgebra.toSubalgebra
variable {F R A B C : Type*} [CommSemiring R] [StarRing R]
variable [Semiring A] [StarRing A] [Algebra R A] [StarModule R A]
variable [Semiring B] [StarRing B] [Algebra R B] [StarModule R B]
variable [Semiring C] [StarRing C] [Algebra R C] [StarModule R C]
instance setLike : SetLike (StarSubalgebra R A) A where
coe S := S.carrier
coe_injective' p q h := by obtain ⟨⟨⟨⟨⟨_, _⟩, _⟩, _⟩, _⟩, _⟩ := p; cases q; congr
instance starMemClass : StarMemClass (StarSubalgebra R A) A where
star_mem {s} := s.star_mem'
instance subsemiringClass : SubsemiringClass (StarSubalgebra R A) A where
add_mem {s} := s.add_mem'
mul_mem {s} := s.mul_mem'
one_mem {s} := s.one_mem'
zero_mem {s} := s.zero_mem'
instance smulMemClass : SMulMemClass (StarSubalgebra R A) R A where
smul_mem {s} r a (ha : a ∈ s.toSubalgebra) :=
(SMulMemClass.smul_mem r ha : r • a ∈ s.toSubalgebra)
instance subringClass {R A} [CommRing R] [StarRing R] [Ring A] [StarRing A] [Algebra R A]
[StarModule R A] : SubringClass (StarSubalgebra R A) A where
neg_mem {s a} ha := show -a ∈ s.toSubalgebra from neg_mem ha
-- this uses the `Star` instance `s` inherits from `StarMemClass (StarSubalgebra R A) A`
instance starRing (s : StarSubalgebra R A) : StarRing s :=
{ StarMemClass.instStar s with
star_involutive := fun r => Subtype.ext (star_star (r : A))
star_mul := fun r₁ r₂ => Subtype.ext (star_mul (r₁ : A) (r₂ : A))
star_add := fun r₁ r₂ => Subtype.ext (star_add (r₁ : A) (r₂ : A)) }
instance algebra (s : StarSubalgebra R A) : Algebra R s :=
s.toSubalgebra.algebra'
instance starModule (s : StarSubalgebra R A) : StarModule R s where
star_smul r a := Subtype.ext (star_smul r (a : A))
@[simp, nolint simpNF] -- porting note (#10618): `simpNF` says `simp` can prove this, but it can't
theorem mem_carrier {s : StarSubalgebra R A} {x : A} : x ∈ s.carrier ↔ x ∈ s :=
Iff.rfl
#align star_subalgebra.mem_carrier StarSubalgebra.mem_carrier
@[ext]
theorem ext {S T : StarSubalgebra R A} (h : ∀ x : A, x ∈ S ↔ x ∈ T) : S = T :=
SetLike.ext h
#align star_subalgebra.ext StarSubalgebra.ext
@[simp]
lemma coe_mk (S : Subalgebra R A) (h) : ((⟨S, h⟩ : StarSubalgebra R A) : Set A) = S := rfl
@[simp]
theorem mem_toSubalgebra {S : StarSubalgebra R A} {x} : x ∈ S.toSubalgebra ↔ x ∈ S :=
Iff.rfl
#align star_subalgebra.mem_to_subalgebra StarSubalgebra.mem_toSubalgebra
@[simp]
theorem coe_toSubalgebra (S : StarSubalgebra R A) : (S.toSubalgebra : Set A) = S :=
rfl
#align star_subalgebra.coe_to_subalgebra StarSubalgebra.coe_toSubalgebra
theorem toSubalgebra_injective :
Function.Injective (toSubalgebra : StarSubalgebra R A → Subalgebra R A) := fun S T h =>
ext fun x => by rw [← mem_toSubalgebra, ← mem_toSubalgebra, h]
#align star_subalgebra.to_subalgebra_injective StarSubalgebra.toSubalgebra_injective
theorem toSubalgebra_inj {S U : StarSubalgebra R A} : S.toSubalgebra = U.toSubalgebra ↔ S = U :=
toSubalgebra_injective.eq_iff
#align star_subalgebra.to_subalgebra_inj StarSubalgebra.toSubalgebra_inj
theorem toSubalgebra_le_iff {S₁ S₂ : StarSubalgebra R A} :
S₁.toSubalgebra ≤ S₂.toSubalgebra ↔ S₁ ≤ S₂ :=
Iff.rfl
#align star_subalgebra.to_subalgebra_le_iff StarSubalgebra.toSubalgebra_le_iff
/-- Copy of a star subalgebra with a new `carrier` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (S : StarSubalgebra R A) (s : Set A) (hs : s = ↑S) : StarSubalgebra R A where
toSubalgebra := Subalgebra.copy S.toSubalgebra s hs
star_mem' := @fun a ha => hs ▸ (S.star_mem' (by simpa [hs] using ha) : star a ∈ (S : Set A))
-- Porting note: the old proof kept crashing Lean
#align star_subalgebra.copy StarSubalgebra.copy
@[simp]
theorem coe_copy (S : StarSubalgebra R A) (s : Set A) (hs : s = ↑S) : (S.copy s hs : Set A) = s :=
rfl
#align star_subalgebra.coe_copy StarSubalgebra.coe_copy
theorem copy_eq (S : StarSubalgebra R A) (s : Set A) (hs : s = ↑S) : S.copy s hs = S :=
SetLike.coe_injective hs
#align star_subalgebra.copy_eq StarSubalgebra.copy_eq
variable (S : StarSubalgebra R A)
theorem algebraMap_mem (r : R) : algebraMap R A r ∈ S :=
S.algebraMap_mem' r
#align star_subalgebra.algebra_map_mem StarSubalgebra.algebraMap_mem
theorem rangeS_le : (algebraMap R A).rangeS ≤ S.toSubalgebra.toSubsemiring := fun _x ⟨r, hr⟩ =>
hr ▸ S.algebraMap_mem r
#align star_subalgebra.srange_le StarSubalgebra.rangeS_le
theorem range_subset : Set.range (algebraMap R A) ⊆ S := fun _x ⟨r, hr⟩ => hr ▸ S.algebraMap_mem r
#align star_subalgebra.range_subset StarSubalgebra.range_subset
theorem range_le : Set.range (algebraMap R A) ≤ S :=
S.range_subset
#align star_subalgebra.range_le StarSubalgebra.range_le
protected theorem smul_mem {x : A} (hx : x ∈ S) (r : R) : r • x ∈ S :=
(Algebra.smul_def r x).symm ▸ mul_mem (S.algebraMap_mem r) hx
#align star_subalgebra.smul_mem StarSubalgebra.smul_mem
/-- Embedding of a subalgebra into the algebra. -/
def subtype : S →⋆ₐ[R] A where
toFun := ((↑) : S → A)
map_one' := rfl
map_mul' _ _ := rfl
map_zero' := rfl
map_add' _ _ := rfl
commutes' _ := rfl
map_star' _ := rfl
#align star_subalgebra.subtype StarSubalgebra.subtype
@[simp]
theorem coe_subtype : (S.subtype : S → A) = Subtype.val :=
rfl
#align star_subalgebra.coe_subtype StarSubalgebra.coe_subtype
theorem subtype_apply (x : S) : S.subtype x = (x : A) :=
rfl
#align star_subalgebra.subtype_apply StarSubalgebra.subtype_apply
@[simp]
theorem toSubalgebra_subtype : S.toSubalgebra.val = S.subtype.toAlgHom :=
rfl
#align star_subalgebra.to_subalgebra_subtype StarSubalgebra.toSubalgebra_subtype
/-- The inclusion map between `StarSubalgebra`s given by `Subtype.map id` as a `StarAlgHom`. -/
@[simps]
def inclusion {S₁ S₂ : StarSubalgebra R A} (h : S₁ ≤ S₂) : S₁ →⋆ₐ[R] S₂ where
toFun := Subtype.map id h
map_one' := rfl
map_mul' _ _ := rfl
map_zero' := rfl
map_add' _ _ := rfl
commutes' _ := rfl
map_star' _ := rfl
#align star_subalgebra.inclusion StarSubalgebra.inclusion
theorem inclusion_injective {S₁ S₂ : StarSubalgebra R A} (h : S₁ ≤ S₂) :
Function.Injective <| inclusion h :=
Set.inclusion_injective h
#align star_subalgebra.inclusion_injective StarSubalgebra.inclusion_injective
@[simp]
theorem subtype_comp_inclusion {S₁ S₂ : StarSubalgebra R A} (h : S₁ ≤ S₂) :
S₂.subtype.comp (inclusion h) = S₁.subtype :=
rfl
#align star_subalgebra.subtype_comp_inclusion StarSubalgebra.subtype_comp_inclusion
section Map
/-- Transport a star subalgebra via a star algebra homomorphism. -/
def map (f : A →⋆ₐ[R] B) (S : StarSubalgebra R A) : StarSubalgebra R B :=
{ S.toSubalgebra.map f.toAlgHom with
star_mem' := by
rintro _ ⟨a, ha, rfl⟩
exact map_star f a ▸ Set.mem_image_of_mem _ (S.star_mem' ha) }
#align star_subalgebra.map StarSubalgebra.map
theorem map_mono {S₁ S₂ : StarSubalgebra R A} {f : A →⋆ₐ[R] B} : S₁ ≤ S₂ → S₁.map f ≤ S₂.map f :=
Set.image_subset f
#align star_subalgebra.map_mono StarSubalgebra.map_mono
theorem map_injective {f : A →⋆ₐ[R] B} (hf : Function.Injective f) : Function.Injective (map f) :=
fun _S₁ _S₂ ih =>
ext <| Set.ext_iff.1 <| Set.image_injective.2 hf <| Set.ext <| SetLike.ext_iff.mp ih
#align star_subalgebra.map_injective StarSubalgebra.map_injective
@[simp]
theorem map_id (S : StarSubalgebra R A) : S.map (StarAlgHom.id R A) = S :=
SetLike.coe_injective <| Set.image_id _
#align star_subalgebra.map_id StarSubalgebra.map_id
theorem map_map (S : StarSubalgebra R A) (g : B →⋆ₐ[R] C) (f : A →⋆ₐ[R] B) :
(S.map f).map g = S.map (g.comp f) :=
SetLike.coe_injective <| Set.image_image _ _ _
#align star_subalgebra.map_map StarSubalgebra.map_map
@[simp]
theorem mem_map {S : StarSubalgebra R A} {f : A →⋆ₐ[R] B} {y : B} :
y ∈ map f S ↔ ∃ x ∈ S, f x = y :=
Subsemiring.mem_map
#align star_subalgebra.mem_map StarSubalgebra.mem_map
theorem map_toSubalgebra {S : StarSubalgebra R A} {f : A →⋆ₐ[R] B} :
(S.map f).toSubalgebra = S.toSubalgebra.map f.toAlgHom :=
SetLike.coe_injective rfl
#align star_subalgebra.map_to_subalgebra StarSubalgebra.map_toSubalgebra
@[simp]
theorem coe_map (S : StarSubalgebra R A) (f : A →⋆ₐ[R] B) : (S.map f : Set B) = f '' S :=
rfl
#align star_subalgebra.coe_map StarSubalgebra.coe_map
/-- Preimage of a star subalgebra under a star algebra homomorphism. -/
def comap (f : A →⋆ₐ[R] B) (S : StarSubalgebra R B) : StarSubalgebra R A :=
{ S.toSubalgebra.comap f.toAlgHom with
star_mem' := @fun a ha => show f (star a) ∈ S from (map_star f a).symm ▸ star_mem ha }
#align star_subalgebra.comap StarSubalgebra.comap
theorem map_le_iff_le_comap {S : StarSubalgebra R A} {f : A →⋆ₐ[R] B} {U : StarSubalgebra R B} :
map f S ≤ U ↔ S ≤ comap f U :=
Set.image_subset_iff
#align star_subalgebra.map_le_iff_le_comap StarSubalgebra.map_le_iff_le_comap
theorem gc_map_comap (f : A →⋆ₐ[R] B) : GaloisConnection (map f) (comap f) := fun _S _U =>
map_le_iff_le_comap
#align star_subalgebra.gc_map_comap StarSubalgebra.gc_map_comap
theorem comap_mono {S₁ S₂ : StarSubalgebra R B} {f : A →⋆ₐ[R] B} :
S₁ ≤ S₂ → S₁.comap f ≤ S₂.comap f :=
Set.preimage_mono
#align star_subalgebra.comap_mono StarSubalgebra.comap_mono
theorem comap_injective {f : A →⋆ₐ[R] B} (hf : Function.Surjective f) :
Function.Injective (comap f) := fun _S₁ _S₂ h =>
ext fun b =>
let ⟨x, hx⟩ := hf b
let this := SetLike.ext_iff.1 h x
hx ▸ this
#align star_subalgebra.comap_injective StarSubalgebra.comap_injective
@[simp]
theorem comap_id (S : StarSubalgebra R A) : S.comap (StarAlgHom.id R A) = S :=
SetLike.coe_injective <| Set.preimage_id
#align star_subalgebra.comap_id StarSubalgebra.comap_id
theorem comap_comap (S : StarSubalgebra R C) (g : B →⋆ₐ[R] C) (f : A →⋆ₐ[R] B) :
(S.comap g).comap f = S.comap (g.comp f) :=
SetLike.coe_injective <| by exact Set.preimage_preimage
-- Porting note: the `by exact` trick still works sometimes
#align star_subalgebra.comap_comap StarSubalgebra.comap_comap
@[simp]
theorem mem_comap (S : StarSubalgebra R B) (f : A →⋆ₐ[R] B) (x : A) : x ∈ S.comap f ↔ f x ∈ S :=
Iff.rfl
#align star_subalgebra.mem_comap StarSubalgebra.mem_comap
@[simp, norm_cast]
theorem coe_comap (S : StarSubalgebra R B) (f : A →⋆ₐ[R] B) :
(S.comap f : Set A) = f ⁻¹' (S : Set B) :=
rfl
#align star_subalgebra.coe_comap StarSubalgebra.coe_comap
end Map
section Centralizer
variable (R)
/-- The centralizer, or commutant, of the star-closure of a set as a star subalgebra. -/
def centralizer (s : Set A) : StarSubalgebra R A where
toSubalgebra := Subalgebra.centralizer R (s ∪ star s)
star_mem' := Set.star_mem_centralizer
#align star_subalgebra.centralizer StarSubalgebra.centralizer
@[simp, norm_cast]
theorem coe_centralizer (s : Set A) : (centralizer R s : Set A) = (s ∪ star s).centralizer :=
rfl
#align star_subalgebra.coe_centralizer StarSubalgebra.coe_centralizer
theorem mem_centralizer_iff {s : Set A} {z : A} :
z ∈ centralizer R s ↔ ∀ g ∈ s, g * z = z * g ∧ star g * z = z * star g := by
show (∀ g ∈ s ∪ star s, g * z = z * g) ↔ ∀ g ∈ s, g * z = z * g ∧ star g * z = z * star g
simp only [Set.mem_union, or_imp, forall_and, and_congr_right_iff]
exact fun _ =>
⟨fun hz a ha => hz _ (Set.star_mem_star.mpr ha), fun hz a ha => star_star a ▸ hz _ ha⟩
#align star_subalgebra.mem_centralizer_iff StarSubalgebra.mem_centralizer_iff
theorem centralizer_le (s t : Set A) (h : s ⊆ t) : centralizer R t ≤ centralizer R s :=
Set.centralizer_subset (Set.union_subset_union h <| Set.preimage_mono h)
#align star_subalgebra.centralizer_le StarSubalgebra.centralizer_le
end Centralizer
end StarSubalgebra
/-! ### The star closure of a subalgebra -/
namespace Subalgebra
open Pointwise
variable {F R A B : Type*} [CommSemiring R] [StarRing R]
variable [Semiring A] [Algebra R A] [StarRing A] [StarModule R A]
variable [Semiring B] [Algebra R B] [StarRing B] [StarModule R B]
/-- The pointwise `star` of a subalgebra is a subalgebra. -/
instance involutiveStar : InvolutiveStar (Subalgebra R A) where
star S :=
{ carrier := star S.carrier
mul_mem' := fun {x y} hx hy => by
simp only [Set.mem_star, Subalgebra.mem_carrier] at *
exact (star_mul x y).symm ▸ mul_mem hy hx
one_mem' := Set.mem_star.mp ((star_one A).symm ▸ one_mem S : star (1 : A) ∈ S)
add_mem' := fun {x y} hx hy => by
simp only [Set.mem_star, Subalgebra.mem_carrier] at *
exact (star_add x y).symm ▸ add_mem hx hy
zero_mem' := Set.mem_star.mp ((star_zero A).symm ▸ zero_mem S : star (0 : A) ∈ S)
algebraMap_mem' := fun r => by
simpa only [Set.mem_star, Subalgebra.mem_carrier, ← algebraMap_star_comm] using
S.algebraMap_mem (star r) }
star_involutive S :=
Subalgebra.ext fun x =>
⟨fun hx => star_star x ▸ hx, fun hx => ((star_star x).symm ▸ hx : star (star x) ∈ S)⟩
@[simp]
theorem mem_star_iff (S : Subalgebra R A) (x : A) : x ∈ star S ↔ star x ∈ S :=
Iff.rfl
#align subalgebra.mem_star_iff Subalgebra.mem_star_iff
-- Porting note: removed `@[simp]` tag because `simp` can prove this
theorem star_mem_star_iff (S : Subalgebra R A) (x : A) : star x ∈ star S ↔ x ∈ S := by
simp only [mem_star_iff, star_star]
#align subalgebra.star_mem_star_iff Subalgebra.star_mem_star_iff
@[simp]
theorem coe_star (S : Subalgebra R A) : ((star S : Subalgebra R A) : Set A) = star (S : Set A) :=
rfl
#align subalgebra.coe_star Subalgebra.coe_star
theorem star_mono : Monotone (star : Subalgebra R A → Subalgebra R A) := fun _ _ h _ hx => h hx
#align subalgebra.star_mono Subalgebra.star_mono
variable (R)
/-- The star operation on `Subalgebra` commutes with `Algebra.adjoin`. -/
theorem star_adjoin_comm (s : Set A) : star (Algebra.adjoin R s) = Algebra.adjoin R (star s) :=
have this : ∀ t : Set A, Algebra.adjoin R (star t) ≤ star (Algebra.adjoin R t) := fun t =>
Algebra.adjoin_le fun x hx => Algebra.subset_adjoin hx
le_antisymm (by simpa only [star_star] using Subalgebra.star_mono (this (star s))) (this s)
#align subalgebra.star_adjoin_comm Subalgebra.star_adjoin_comm
variable {R}
/-- The `StarSubalgebra` obtained from `S : Subalgebra R A` by taking the smallest subalgebra
containing both `S` and `star S`. -/
@[simps!]
def starClosure (S : Subalgebra R A) : StarSubalgebra R A where
toSubalgebra := S ⊔ star S
star_mem' := fun {a} ha => by
simp only [Subalgebra.mem_carrier, ← (@Algebra.gi R A _ _ _).l_sup_u _ _] at *
rw [← mem_star_iff _ a, star_adjoin_comm, sup_comm]
simpa using ha
#align subalgebra.star_closure Subalgebra.starClosure
theorem starClosure_toSubalgebra (S : Subalgebra R A) : S.starClosure.toSubalgebra = S ⊔ star S :=
rfl
theorem starClosure_le {S₁ : Subalgebra R A} {S₂ : StarSubalgebra R A} (h : S₁ ≤ S₂.toSubalgebra) :
S₁.starClosure ≤ S₂ :=
StarSubalgebra.toSubalgebra_le_iff.1 <|
sup_le h fun x hx =>
(star_star x ▸ star_mem (show star x ∈ S₂ from h <| (S₁.mem_star_iff _).1 hx) : x ∈ S₂)
#align subalgebra.star_closure_le Subalgebra.starClosure_le
theorem starClosure_le_iff {S₁ : Subalgebra R A} {S₂ : StarSubalgebra R A} :
S₁.starClosure ≤ S₂ ↔ S₁ ≤ S₂.toSubalgebra :=
⟨fun h => le_sup_left.trans h, starClosure_le⟩
#align subalgebra.star_closure_le_iff Subalgebra.starClosure_le_iff
end Subalgebra
/-! ### The star subalgebra generated by a set -/
namespace StarAlgebra
open StarSubalgebra
variable {F R A B : Type*} [CommSemiring R] [StarRing R]
variable [Semiring A] [Algebra R A] [StarRing A] [StarModule R A]
variable [Semiring B] [Algebra R B] [StarRing B] [StarModule R B]
variable (R)
/-- The minimal star subalgebra that contains `s`. -/
@[simps!]
def adjoin (s : Set A) : StarSubalgebra R A :=
{ Algebra.adjoin R (s ∪ star s) with
star_mem' := fun hx => by
rwa [Subalgebra.mem_carrier, ← Subalgebra.mem_star_iff, Subalgebra.star_adjoin_comm,
Set.union_star, star_star, Set.union_comm] }
#align star_subalgebra.adjoin StarAlgebra.adjoin
theorem adjoin_eq_starClosure_adjoin (s : Set A) : adjoin R s = (Algebra.adjoin R s).starClosure :=
toSubalgebra_injective <|
show Algebra.adjoin R (s ∪ star s) = Algebra.adjoin R s ⊔ star (Algebra.adjoin R s) from
(Subalgebra.star_adjoin_comm R s).symm ▸ Algebra.adjoin_union s (star s)
#align star_subalgebra.adjoin_eq_star_closure_adjoin StarAlgebra.adjoin_eq_starClosure_adjoin
theorem adjoin_toSubalgebra (s : Set A) :
(adjoin R s).toSubalgebra = Algebra.adjoin R (s ∪ star s) :=
rfl
#align star_subalgebra.adjoin_to_subalgebra StarAlgebra.adjoin_toSubalgebra
@[aesop safe 20 apply (rule_sets := [SetLike])]
theorem subset_adjoin (s : Set A) : s ⊆ adjoin R s :=
Set.subset_union_left.trans Algebra.subset_adjoin
#align star_subalgebra.subset_adjoin StarAlgebra.subset_adjoin
theorem star_subset_adjoin (s : Set A) : star s ⊆ adjoin R s :=
Set.subset_union_right.trans Algebra.subset_adjoin
#align star_subalgebra.star_subset_adjoin StarAlgebra.star_subset_adjoin
theorem self_mem_adjoin_singleton (x : A) : x ∈ adjoin R ({x} : Set A) :=
Algebra.subset_adjoin <| Set.mem_union_left _ (Set.mem_singleton x)
#align star_subalgebra.self_mem_adjoin_singleton StarAlgebra.self_mem_adjoin_singleton
theorem star_self_mem_adjoin_singleton (x : A) : star x ∈ adjoin R ({x} : Set A) :=
star_mem <| self_mem_adjoin_singleton R x
#align star_subalgebra.star_self_mem_adjoin_singleton StarAlgebra.star_self_mem_adjoin_singleton
variable {R}
protected theorem gc : GaloisConnection (adjoin R : Set A → StarSubalgebra R A) (↑) := by
intro s S
rw [← toSubalgebra_le_iff, adjoin_toSubalgebra, Algebra.adjoin_le_iff, coe_toSubalgebra]
exact
⟨fun h => Set.subset_union_left.trans h, fun h =>
Set.union_subset h fun x hx => star_star x ▸ star_mem (show star x ∈ S from h hx)⟩
#align star_subalgebra.gc StarAlgebra.gc
/-- Galois insertion between `adjoin` and `coe`. -/
protected def gi : GaloisInsertion (adjoin R : Set A → StarSubalgebra R A) (↑) where
choice s hs := (adjoin R s).copy s <| le_antisymm (StarAlgebra.gc.le_u_l s) hs
gc := StarAlgebra.gc
le_l_u S := (StarAlgebra.gc (S : Set A) (adjoin R S)).1 <| le_rfl
choice_eq _ _ := StarSubalgebra.copy_eq _ _ _
#align star_subalgebra.gi StarAlgebra.gi
theorem adjoin_le {S : StarSubalgebra R A} {s : Set A} (hs : s ⊆ S) : adjoin R s ≤ S :=
StarAlgebra.gc.l_le hs
#align star_subalgebra.adjoin_le StarAlgebra.adjoin_le
theorem adjoin_le_iff {S : StarSubalgebra R A} {s : Set A} : adjoin R s ≤ S ↔ s ⊆ S :=
StarAlgebra.gc _ _
#align star_subalgebra.adjoin_le_iff StarAlgebra.adjoin_le_iff
lemma adjoin_eq (S : StarSubalgebra R A) : adjoin R (S : Set A) = S :=
le_antisymm (adjoin_le le_rfl) (subset_adjoin R (S : Set A))
open Submodule in
lemma adjoin_eq_span (s : Set A) :
Subalgebra.toSubmodule (adjoin R s).toSubalgebra = span R (Submonoid.closure (s ∪ star s)) := by
rw [adjoin_toSubalgebra, Algebra.adjoin_eq_span]
theorem _root_.Subalgebra.starClosure_eq_adjoin (S : Subalgebra R A) :
S.starClosure = adjoin R (S : Set A) :=
le_antisymm (Subalgebra.starClosure_le_iff.2 <| subset_adjoin R (S : Set A))
(adjoin_le (le_sup_left : S ≤ S ⊔ star S))
#align subalgebra.star_closure_eq_adjoin Subalgebra.starClosure_eq_adjoin
/-- If some predicate holds for all `x ∈ (s : Set A)` and this predicate is closed under the
`algebraMap`, addition, multiplication and star operations, then it holds for `a ∈ adjoin R s`. -/
@[elab_as_elim]
theorem adjoin_induction {s : Set A} {p : A → Prop} {a : A} (h : a ∈ adjoin R s)
(mem : ∀ x : A, x ∈ s → p x) (algebraMap : ∀ r : R, p (algebraMap R A r))
(add : ∀ x y : A, p x → p y → p (x + y)) (mul : ∀ x y : A, p x → p y → p (x * y))
(star : ∀ x : A, p x → p (star x)) : p a :=
Algebra.adjoin_induction h
(fun x hx => hx.elim (fun hx => mem x hx) fun hx => star_star x ▸ star _ (mem _ hx))
algebraMap add mul
#align star_subalgebra.adjoin_induction StarAlgebra.adjoin_induction
@[elab_as_elim]
theorem adjoin_induction₂ {s : Set A} {p : A → A → Prop} {a b : A} (ha : a ∈ adjoin R s)
(hb : b ∈ adjoin R s) (Hs : ∀ x : A, x ∈ s → ∀ y : A, y ∈ s → p x y)
(Halg : ∀ r₁ r₂ : R, p (algebraMap R A r₁) (algebraMap R A r₂))
(Halg_left : ∀ (r : R) (x : A), x ∈ s → p (algebraMap R A r) x)
(Halg_right : ∀ (r : R) (x : A), x ∈ s → p x (algebraMap R A r))
(Hadd_left : ∀ x₁ x₂ y : A, p x₁ y → p x₂ y → p (x₁ + x₂) y)
(Hadd_right : ∀ x y₁ y₂ : A, p x y₁ → p x y₂ → p x (y₁ + y₂))
(Hmul_left : ∀ x₁ x₂ y : A, p x₁ y → p x₂ y → p (x₁ * x₂) y)
(Hmul_right : ∀ x y₁ y₂ : A, p x y₁ → p x y₂ → p x (y₁ * y₂))
(Hstar : ∀ x y : A, p x y → p (star x) (star y)) (Hstar_left : ∀ x y : A, p x y → p (star x) y)
(Hstar_right : ∀ x y : A, p x y → p x (star y)) : p a b := by
refine
Algebra.adjoin_induction₂ ha hb (fun x hx y hy => ?_) Halg (fun r x hx => ?_) (fun r x hx => ?_)
Hadd_left Hadd_right Hmul_left Hmul_right
· cases' hx with hx hx <;> cases' hy with hy hy
· exact Hs x hx y hy
· exact star_star y ▸ Hstar_right _ _ (Hs _ hx _ hy)
· exact star_star x ▸ Hstar_left _ _ (Hs _ hx _ hy)
· exact star_star x ▸ star_star y ▸ Hstar _ _ (Hs _ hx _ hy)
· cases' hx with hx hx
· exact Halg_left _ _ hx
· exact star_star x ▸ Hstar_right _ _ (Halg_left r _ hx)
· cases' hx with hx hx
· exact Halg_right _ _ hx
· exact star_star x ▸ Hstar_left _ _ (Halg_right r _ hx)
#align star_subalgebra.adjoin_induction₂ StarAlgebra.adjoin_induction₂
/-- The difference with `StarSubalgebra.adjoin_induction` is that this acts on the subtype. -/
@[elab_as_elim]
theorem adjoin_induction' {s : Set A} {p : adjoin R s → Prop} (a : adjoin R s)
(mem : ∀ (x) (h : x ∈ s), p ⟨x, subset_adjoin R s h⟩) (algebraMap : ∀ r, p (algebraMap R _ r))
(add : ∀ x y, p x → p y → p (x + y)) (mul : ∀ x y, p x → p y → p (x * y))
(star : ∀ x, p x → p (star x)) : p a :=
Subtype.recOn a fun b hb => by
refine Exists.elim ?_ fun (hb : b ∈ adjoin R s) (hc : p ⟨b, hb⟩) => hc
refine adjoin_induction hb ?_ ?_ ?_ ?_ ?_
exacts [fun x hx => ⟨subset_adjoin R s hx, mem x hx⟩, fun r =>
⟨StarSubalgebra.algebraMap_mem _ r, algebraMap r⟩, 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 x y hx hy =>
Exists.elim hx fun hx' hx => Exists.elim hy fun hy' hy => ⟨mul_mem hx' hy', mul _ _ hx hy⟩,
fun x hx => Exists.elim hx fun hx' hx => ⟨star_mem hx', star _ hx⟩]
#align star_subalgebra.adjoin_induction' StarAlgebra.adjoin_induction'
variable (R)
/-- If all elements of `s : Set A` commute pairwise and also commute pairwise with elements of
`star s`, then `StarSubalgebra.adjoin R s` is commutative. See note [reducible non-instances]. -/
abbrev adjoinCommSemiringOfComm {s : Set A}
(hcomm : ∀ a : A, a ∈ s → ∀ b : A, b ∈ s → a * b = b * a)
(hcomm_star : ∀ a : A, a ∈ s → ∀ b : A, b ∈ s → a * star b = star b * a) :
CommSemiring (adjoin R s) :=
{ (adjoin R s).toSubalgebra.toSemiring with
mul_comm := by
rintro ⟨x, hx⟩ ⟨y, hy⟩
ext
simp only [MulMemClass.mk_mul_mk]
rw [← mem_toSubalgebra, adjoin_toSubalgebra] at hx hy
letI : CommSemiring (Algebra.adjoin R (s ∪ star s)) :=
Algebra.adjoinCommSemiringOfComm R
(by
intro a ha b hb
cases' ha with ha ha <;> cases' hb with hb hb
· exact hcomm _ ha _ hb
· exact star_star b ▸ hcomm_star _ ha _ hb
· exact star_star a ▸ (hcomm_star _ hb _ ha).symm
· simpa only [star_mul, star_star] using congr_arg star (hcomm _ hb _ ha))
exact congr_arg Subtype.val (mul_comm (⟨x, hx⟩ : Algebra.adjoin R (s ∪ star s)) ⟨y, hy⟩) }
#align star_subalgebra.adjoin_comm_semiring_of_comm StarAlgebra.adjoinCommSemiringOfComm
/-- If all elements of `s : Set A` commute pairwise and also commute pairwise with elements of
`star s`, then `StarSubalgebra.adjoin R s` is commutative. See note [reducible non-instances]. -/
abbrev adjoinCommRingOfComm (R : Type u) {A : Type v} [CommRing R] [StarRing R] [Ring A]
[Algebra R A] [StarRing A] [StarModule R A] {s : Set A}
(hcomm : ∀ a : A, a ∈ s → ∀ b : A, b ∈ s → a * b = b * a)
(hcomm_star : ∀ a : A, a ∈ s → ∀ b : A, b ∈ s → a * star b = star b * a) :
CommRing (adjoin R s) :=
{ StarAlgebra.adjoinCommSemiringOfComm R hcomm hcomm_star,
(adjoin R s).toSubalgebra.toRing with }
#align star_subalgebra.adjoin_comm_ring_of_comm StarAlgebra.adjoinCommRingOfComm
/-- The star subalgebra `StarSubalgebra.adjoin R {x}` generated by a single `x : A` is commutative
if `x` is normal. -/
instance adjoinCommSemiringOfIsStarNormal (x : A) [IsStarNormal x] :
CommSemiring (adjoin R ({x} : Set A)) :=
adjoinCommSemiringOfComm R
(fun a ha b hb => by
rw [Set.mem_singleton_iff] at ha hb
rw [ha, hb])
fun a ha b hb => by
rw [Set.mem_singleton_iff] at ha hb
simpa only [ha, hb] using (star_comm_self' x).symm
#align star_subalgebra.adjoin_comm_semiring_of_is_star_normal StarAlgebra.adjoinCommSemiringOfIsStarNormal
/-- The star subalgebra `StarSubalgebra.adjoin R {x}` generated by a single `x : A` is commutative
if `x` is normal. -/
instance adjoinCommRingOfIsStarNormal (R : Type u) {A : Type v} [CommRing R] [StarRing R] [Ring A]
[Algebra R A] [StarRing A] [StarModule R A] (x : A) [IsStarNormal x] :
CommRing (adjoin R ({x} : Set A)) :=
{ (adjoin R ({x} : Set A)).toSubalgebra.toRing with mul_comm := mul_comm }
#align star_subalgebra.adjoin_comm_ring_of_is_star_normal StarAlgebra.adjoinCommRingOfIsStarNormal
/-! ### Complete lattice structure -/
end StarAlgebra
namespace StarSubalgebra
variable {F R A B : Type*} [CommSemiring R] [StarRing R]
variable [Semiring A] [Algebra R A] [StarRing A] [StarModule R A]
variable [Semiring B] [Algebra R B] [StarRing B] [StarModule R B]
instance completeLattice : CompleteLattice (StarSubalgebra R A) where
__ := GaloisInsertion.liftCompleteLattice StarAlgebra.gi
bot := { toSubalgebra := ⊥, star_mem' := fun ⟨r, hr⟩ => ⟨star r, hr ▸ algebraMap_star_comm _⟩ }
bot_le S := (bot_le : ⊥ ≤ S.toSubalgebra)
instance inhabited : Inhabited (StarSubalgebra R A) :=
⟨⊤⟩
@[simp]
theorem coe_top : (↑(⊤ : StarSubalgebra R A) : Set A) = Set.univ :=
rfl
#align star_subalgebra.coe_top StarSubalgebra.coe_top
@[simp]
theorem mem_top {x : A} : x ∈ (⊤ : StarSubalgebra R A) :=
Set.mem_univ x
#align star_subalgebra.mem_top StarSubalgebra.mem_top
@[simp]
theorem top_toSubalgebra : (⊤ : StarSubalgebra R A).toSubalgebra = ⊤ := by ext; simp
-- Porting note: Lean can no longer prove this by `rfl`, it times out
#align star_subalgebra.top_to_subalgebra StarSubalgebra.top_toSubalgebra
@[simp]
theorem toSubalgebra_eq_top {S : StarSubalgebra R A} : S.toSubalgebra = ⊤ ↔ S = ⊤ :=
StarSubalgebra.toSubalgebra_injective.eq_iff' top_toSubalgebra
#align star_subalgebra.to_subalgebra_eq_top StarSubalgebra.toSubalgebra_eq_top
theorem mem_sup_left {S T : StarSubalgebra R A} : ∀ {x : A}, x ∈ S → x ∈ S ⊔ T :=
have : S ≤ S ⊔ T := le_sup_left; (this ·) -- Porting note: need `have` instead of `show`
#align star_subalgebra.mem_sup_left StarSubalgebra.mem_sup_left
theorem mem_sup_right {S T : StarSubalgebra R A} : ∀ {x : A}, x ∈ T → x ∈ S ⊔ T :=
have : T ≤ S ⊔ T := le_sup_right; (this ·) -- Porting note: need `have` instead of `show`
#align star_subalgebra.mem_sup_right StarSubalgebra.mem_sup_right
theorem mul_mem_sup {S T : StarSubalgebra R A} {x y : A} (hx : x ∈ S) (hy : y ∈ T) :
x * y ∈ S ⊔ T :=
mul_mem (mem_sup_left hx) (mem_sup_right hy)
#align star_subalgebra.mul_mem_sup StarSubalgebra.mul_mem_sup
theorem map_sup (f : A →⋆ₐ[R] B) (S T : StarSubalgebra R A) : map f (S ⊔ T) = map f S ⊔ map f T :=
(StarSubalgebra.gc_map_comap f).l_sup
#align star_subalgebra.map_sup StarSubalgebra.map_sup
@[simp, norm_cast]
theorem coe_inf (S T : StarSubalgebra R A) : (↑(S ⊓ T) : Set A) = (S : Set A) ∩ T :=
rfl
#align star_subalgebra.coe_inf StarSubalgebra.coe_inf
@[simp]
theorem mem_inf {S T : StarSubalgebra R A} {x : A} : x ∈ S ⊓ T ↔ x ∈ S ∧ x ∈ T :=
Iff.rfl
#align star_subalgebra.mem_inf StarSubalgebra.mem_inf
@[simp]
theorem inf_toSubalgebra (S T : StarSubalgebra R A) :
(S ⊓ T).toSubalgebra = S.toSubalgebra ⊓ T.toSubalgebra := by
ext; simp
-- Porting note: Lean can no longer prove this by `rfl`, it times out
#align star_subalgebra.inf_to_subalgebra StarSubalgebra.inf_toSubalgebra
@[simp, norm_cast]
theorem coe_sInf (S : Set (StarSubalgebra R A)) : (↑(sInf S) : Set A) = ⋂ s ∈ S, ↑s :=
sInf_image
#align star_subalgebra.coe_Inf StarSubalgebra.coe_sInf
theorem mem_sInf {S : Set (StarSubalgebra R A)} {x : A} : x ∈ sInf S ↔ ∀ p ∈ S, x ∈ p := by
simp only [← SetLike.mem_coe, coe_sInf, Set.mem_iInter₂]
#align star_subalgebra.mem_Inf StarSubalgebra.mem_sInf
@[simp]
theorem sInf_toSubalgebra (S : Set (StarSubalgebra R A)) :
(sInf S).toSubalgebra = sInf (StarSubalgebra.toSubalgebra '' S) :=
SetLike.coe_injective <| by simp
#align star_subalgebra.Inf_to_subalgebra StarSubalgebra.sInf_toSubalgebra
@[simp, norm_cast]
| Mathlib/Algebra/Star/Subalgebra.lean | 711 | 712 | theorem coe_iInf {ι : Sort*} {S : ι → StarSubalgebra R A} : (↑(⨅ i, S i) : Set A) = ⋂ i, S i := by |
simp [iInf]
|
/-
Copyright (c) 2022 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.Probability.Variance
#align_import probability.moments from "leanprover-community/mathlib"@"85453a2a14be8da64caf15ca50930cf4c6e5d8de"
/-!
# Moments and moment generating function
## Main definitions
* `ProbabilityTheory.moment X p μ`: `p`th moment of a real random variable `X` with respect to
measure `μ`, `μ[X^p]`
* `ProbabilityTheory.centralMoment X p μ`:`p`th central moment of `X` with respect to measure `μ`,
`μ[(X - μ[X])^p]`
* `ProbabilityTheory.mgf X μ t`: moment generating function of `X` with respect to measure `μ`,
`μ[exp(t*X)]`
* `ProbabilityTheory.cgf X μ t`: cumulant generating function, logarithm of the moment generating
function
## Main results
* `ProbabilityTheory.IndepFun.mgf_add`: if two real random variables `X` and `Y` are independent
and their mgfs are defined at `t`, then `mgf (X + Y) μ t = mgf X μ t * mgf Y μ t`
* `ProbabilityTheory.IndepFun.cgf_add`: if two real random variables `X` and `Y` are independent
and their cgfs are defined at `t`, then `cgf (X + Y) μ t = cgf X μ t + cgf Y μ t`
* `ProbabilityTheory.measure_ge_le_exp_cgf` and `ProbabilityTheory.measure_le_le_exp_cgf`:
Chernoff bound on the upper (resp. lower) tail of a random variable. For `t` nonnegative such that
the cgf exists, `ℙ(ε ≤ X) ≤ exp(- t*ε + cgf X ℙ t)`. See also
`ProbabilityTheory.measure_ge_le_exp_mul_mgf` and
`ProbabilityTheory.measure_le_le_exp_mul_mgf` for versions of these results using `mgf` instead
of `cgf`.
-/
open MeasureTheory Filter Finset Real
noncomputable section
open scoped MeasureTheory ProbabilityTheory ENNReal NNReal
namespace ProbabilityTheory
variable {Ω ι : Type*} {m : MeasurableSpace Ω} {X : Ω → ℝ} {p : ℕ} {μ : Measure Ω}
/-- Moment of a real random variable, `μ[X ^ p]`. -/
def moment (X : Ω → ℝ) (p : ℕ) (μ : Measure Ω) : ℝ :=
μ[X ^ p]
#align probability_theory.moment ProbabilityTheory.moment
/-- Central moment of a real random variable, `μ[(X - μ[X]) ^ p]`. -/
def centralMoment (X : Ω → ℝ) (p : ℕ) (μ : Measure Ω) : ℝ := by
have m := fun (x : Ω) => μ[X] -- Porting note: Lean deems `μ[(X - fun x => μ[X]) ^ p]` ambiguous
exact μ[(X - m) ^ p]
#align probability_theory.central_moment ProbabilityTheory.centralMoment
@[simp]
theorem moment_zero (hp : p ≠ 0) : moment 0 p μ = 0 := by
simp only [moment, hp, zero_pow, Ne, not_false_iff, Pi.zero_apply, integral_const,
smul_eq_mul, mul_zero, integral_zero]
#align probability_theory.moment_zero ProbabilityTheory.moment_zero
@[simp]
theorem centralMoment_zero (hp : p ≠ 0) : centralMoment 0 p μ = 0 := by
simp only [centralMoment, hp, Pi.zero_apply, integral_const, smul_eq_mul,
mul_zero, zero_sub, Pi.pow_apply, Pi.neg_apply, neg_zero, zero_pow, Ne, not_false_iff]
#align probability_theory.central_moment_zero ProbabilityTheory.centralMoment_zero
theorem centralMoment_one' [IsFiniteMeasure μ] (h_int : Integrable X μ) :
centralMoment X 1 μ = (1 - (μ Set.univ).toReal) * μ[X] := by
simp only [centralMoment, Pi.sub_apply, pow_one]
rw [integral_sub h_int (integrable_const _)]
simp only [sub_mul, integral_const, smul_eq_mul, one_mul]
#align probability_theory.central_moment_one' ProbabilityTheory.centralMoment_one'
@[simp]
theorem centralMoment_one [IsProbabilityMeasure μ] : centralMoment X 1 μ = 0 := by
by_cases h_int : Integrable X μ
· rw [centralMoment_one' h_int]
simp only [measure_univ, ENNReal.one_toReal, sub_self, zero_mul]
· simp only [centralMoment, Pi.sub_apply, pow_one]
have : ¬Integrable (fun x => X x - integral μ X) μ := by
refine fun h_sub => h_int ?_
have h_add : X = (fun x => X x - integral μ X) + fun _ => integral μ X := by ext1 x; simp
rw [h_add]
exact h_sub.add (integrable_const _)
rw [integral_undef this]
#align probability_theory.central_moment_one ProbabilityTheory.centralMoment_one
theorem centralMoment_two_eq_variance [IsFiniteMeasure μ] (hX : Memℒp X 2 μ) :
centralMoment X 2 μ = variance X μ := by rw [hX.variance_eq]; rfl
#align probability_theory.central_moment_two_eq_variance ProbabilityTheory.centralMoment_two_eq_variance
section MomentGeneratingFunction
variable {t : ℝ}
/-- Moment generating function of a real random variable `X`: `fun t => μ[exp(t*X)]`. -/
def mgf (X : Ω → ℝ) (μ : Measure Ω) (t : ℝ) : ℝ :=
μ[fun ω => exp (t * X ω)]
#align probability_theory.mgf ProbabilityTheory.mgf
/-- Cumulant generating function of a real random variable `X`: `fun t => log μ[exp(t*X)]`. -/
def cgf (X : Ω → ℝ) (μ : Measure Ω) (t : ℝ) : ℝ :=
log (mgf X μ t)
#align probability_theory.cgf ProbabilityTheory.cgf
@[simp]
theorem mgf_zero_fun : mgf 0 μ t = (μ Set.univ).toReal := by
simp only [mgf, Pi.zero_apply, mul_zero, exp_zero, integral_const, smul_eq_mul, mul_one]
#align probability_theory.mgf_zero_fun ProbabilityTheory.mgf_zero_fun
@[simp]
theorem cgf_zero_fun : cgf 0 μ t = log (μ Set.univ).toReal := by simp only [cgf, mgf_zero_fun]
#align probability_theory.cgf_zero_fun ProbabilityTheory.cgf_zero_fun
@[simp]
theorem mgf_zero_measure : mgf X (0 : Measure Ω) t = 0 := by simp only [mgf, integral_zero_measure]
#align probability_theory.mgf_zero_measure ProbabilityTheory.mgf_zero_measure
@[simp]
theorem cgf_zero_measure : cgf X (0 : Measure Ω) t = 0 := by
simp only [cgf, log_zero, mgf_zero_measure]
#align probability_theory.cgf_zero_measure ProbabilityTheory.cgf_zero_measure
@[simp]
theorem mgf_const' (c : ℝ) : mgf (fun _ => c) μ t = (μ Set.univ).toReal * exp (t * c) := by
simp only [mgf, integral_const, smul_eq_mul]
#align probability_theory.mgf_const' ProbabilityTheory.mgf_const'
-- @[simp] -- Porting note: `simp only` already proves this
theorem mgf_const (c : ℝ) [IsProbabilityMeasure μ] : mgf (fun _ => c) μ t = exp (t * c) := by
simp only [mgf_const', measure_univ, ENNReal.one_toReal, one_mul]
#align probability_theory.mgf_const ProbabilityTheory.mgf_const
@[simp]
theorem cgf_const' [IsFiniteMeasure μ] (hμ : μ ≠ 0) (c : ℝ) :
cgf (fun _ => c) μ t = log (μ Set.univ).toReal + t * c := by
simp only [cgf, mgf_const']
rw [log_mul _ (exp_pos _).ne']
· rw [log_exp _]
· rw [Ne, ENNReal.toReal_eq_zero_iff, Measure.measure_univ_eq_zero]
simp only [hμ, measure_ne_top μ Set.univ, or_self_iff, not_false_iff]
#align probability_theory.cgf_const' ProbabilityTheory.cgf_const'
@[simp]
theorem cgf_const [IsProbabilityMeasure μ] (c : ℝ) : cgf (fun _ => c) μ t = t * c := by
simp only [cgf, mgf_const, log_exp]
#align probability_theory.cgf_const ProbabilityTheory.cgf_const
@[simp]
theorem mgf_zero' : mgf X μ 0 = (μ Set.univ).toReal := by
simp only [mgf, zero_mul, exp_zero, integral_const, smul_eq_mul, mul_one]
#align probability_theory.mgf_zero' ProbabilityTheory.mgf_zero'
-- @[simp] -- Porting note: `simp only` already proves this
theorem mgf_zero [IsProbabilityMeasure μ] : mgf X μ 0 = 1 := by
simp only [mgf_zero', measure_univ, ENNReal.one_toReal]
#align probability_theory.mgf_zero ProbabilityTheory.mgf_zero
@[simp]
| Mathlib/Probability/Moments.lean | 166 | 166 | theorem cgf_zero' : cgf X μ 0 = log (μ Set.univ).toReal := by | simp only [cgf, mgf_zero']
|
/-
Copyright (c) 2022 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johanes Hölzl, Patrick Massot, Yury Kudryashov, Kevin Wilson, Heather Macbeth
-/
import Mathlib.Order.Filter.Basic
#align_import order.filter.prod from "leanprover-community/mathlib"@"d6fad0e5bf2d6f48da9175d25c3dc5706b3834ce"
/-!
# Product and coproduct filters
In this file we define `Filter.prod f g` (notation: `f ×ˢ g`) and `Filter.coprod f g`. The product
of two filters is the largest filter `l` such that `Filter.Tendsto Prod.fst l f` and
`Filter.Tendsto Prod.snd l g`.
## Implementation details
The product filter cannot be defined using the monad structure on filters. For example:
```lean
F := do {x ← seq, y ← top, return (x, y)}
G := do {y ← top, x ← seq, return (x, y)}
```
hence:
```lean
s ∈ F ↔ ∃ n, [n..∞] × univ ⊆ s
s ∈ G ↔ ∀ i:ℕ, ∃ n, [n..∞] × {i} ⊆ s
```
Now `⋃ i, [i..∞] × {i}` is in `G` but not in `F`.
As product filter we want to have `F` as result.
## Notations
* `f ×ˢ g` : `Filter.prod f g`, localized in `Filter`.
-/
open Set
open Filter
namespace Filter
variable {α β γ δ : Type*} {ι : Sort*}
section Prod
variable {s : Set α} {t : Set β} {f : Filter α} {g : Filter β}
/-- Product of filters. This is the filter generated by cartesian products
of elements of the component filters. -/
protected def prod (f : Filter α) (g : Filter β) : Filter (α × β) :=
f.comap Prod.fst ⊓ g.comap Prod.snd
#align filter.prod Filter.prod
instance instSProd : SProd (Filter α) (Filter β) (Filter (α × β)) where
sprod := Filter.prod
theorem prod_mem_prod (hs : s ∈ f) (ht : t ∈ g) : s ×ˢ t ∈ f ×ˢ g :=
inter_mem_inf (preimage_mem_comap hs) (preimage_mem_comap ht)
#align filter.prod_mem_prod Filter.prod_mem_prod
theorem mem_prod_iff {s : Set (α × β)} {f : Filter α} {g : Filter β} :
s ∈ f ×ˢ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ×ˢ t₂ ⊆ s := by
simp only [SProd.sprod, Filter.prod]
constructor
· rintro ⟨t₁, ⟨s₁, hs₁, hts₁⟩, t₂, ⟨s₂, hs₂, hts₂⟩, rfl⟩
exact ⟨s₁, hs₁, s₂, hs₂, fun p ⟨h, h'⟩ => ⟨hts₁ h, hts₂ h'⟩⟩
· rintro ⟨t₁, ht₁, t₂, ht₂, h⟩
exact mem_inf_of_inter (preimage_mem_comap ht₁) (preimage_mem_comap ht₂) h
#align filter.mem_prod_iff Filter.mem_prod_iff
@[simp]
theorem prod_mem_prod_iff [f.NeBot] [g.NeBot] : s ×ˢ t ∈ f ×ˢ g ↔ s ∈ f ∧ t ∈ g :=
⟨fun h =>
let ⟨_s', hs', _t', ht', H⟩ := mem_prod_iff.1 h
(prod_subset_prod_iff.1 H).elim
(fun ⟨hs's, ht't⟩ => ⟨mem_of_superset hs' hs's, mem_of_superset ht' ht't⟩) fun h =>
h.elim (fun hs'e => absurd hs'e (nonempty_of_mem hs').ne_empty) fun ht'e =>
absurd ht'e (nonempty_of_mem ht').ne_empty,
fun h => prod_mem_prod h.1 h.2⟩
#align filter.prod_mem_prod_iff Filter.prod_mem_prod_iff
theorem mem_prod_principal {s : Set (α × β)} :
s ∈ f ×ˢ 𝓟 t ↔ { a | ∀ b ∈ t, (a, b) ∈ s } ∈ f := by
rw [← @exists_mem_subset_iff _ f, mem_prod_iff]
refine exists_congr fun u => Iff.rfl.and ⟨?_, fun h => ⟨t, mem_principal_self t, ?_⟩⟩
· rintro ⟨v, v_in, hv⟩ a a_in b b_in
exact hv (mk_mem_prod a_in <| v_in b_in)
· rintro ⟨x, y⟩ ⟨hx, hy⟩
exact h hx y hy
#align filter.mem_prod_principal Filter.mem_prod_principal
theorem mem_prod_top {s : Set (α × β)} :
s ∈ f ×ˢ (⊤ : Filter β) ↔ { a | ∀ b, (a, b) ∈ s } ∈ f := by
rw [← principal_univ, mem_prod_principal]
simp only [mem_univ, forall_true_left]
#align filter.mem_prod_top Filter.mem_prod_top
theorem eventually_prod_principal_iff {p : α × β → Prop} {s : Set β} :
(∀ᶠ x : α × β in f ×ˢ 𝓟 s, p x) ↔ ∀ᶠ x : α in f, ∀ y : β, y ∈ s → p (x, y) := by
rw [eventually_iff, eventually_iff, mem_prod_principal]
simp only [mem_setOf_eq]
#align filter.eventually_prod_principal_iff Filter.eventually_prod_principal_iff
theorem comap_prod (f : α → β × γ) (b : Filter β) (c : Filter γ) :
comap f (b ×ˢ c) = comap (Prod.fst ∘ f) b ⊓ comap (Prod.snd ∘ f) c := by
erw [comap_inf, Filter.comap_comap, Filter.comap_comap]
#align filter.comap_prod Filter.comap_prod
theorem prod_top : f ×ˢ (⊤ : Filter β) = f.comap Prod.fst := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_top, inf_top_eq]
#align filter.prod_top Filter.prod_top
theorem top_prod : (⊤ : Filter α) ×ˢ g = g.comap Prod.snd := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_top, top_inf_eq]
theorem sup_prod (f₁ f₂ : Filter α) (g : Filter β) : (f₁ ⊔ f₂) ×ˢ g = (f₁ ×ˢ g) ⊔ (f₂ ×ˢ g) := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_sup, inf_sup_right, ← Filter.prod, ← Filter.prod]
#align filter.sup_prod Filter.sup_prod
theorem prod_sup (f : Filter α) (g₁ g₂ : Filter β) : f ×ˢ (g₁ ⊔ g₂) = (f ×ˢ g₁) ⊔ (f ×ˢ g₂) := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_sup, inf_sup_left, ← Filter.prod, ← Filter.prod]
#align filter.prod_sup Filter.prod_sup
theorem eventually_prod_iff {p : α × β → Prop} :
(∀ᶠ x in f ×ˢ g, p x) ↔
∃ pa : α → Prop, (∀ᶠ x in f, pa x) ∧ ∃ pb : β → Prop, (∀ᶠ y in g, pb y) ∧
∀ {x}, pa x → ∀ {y}, pb y → p (x, y) := by
simpa only [Set.prod_subset_iff] using @mem_prod_iff α β p f g
#align filter.eventually_prod_iff Filter.eventually_prod_iff
theorem tendsto_fst : Tendsto Prod.fst (f ×ˢ g) f :=
tendsto_inf_left tendsto_comap
#align filter.tendsto_fst Filter.tendsto_fst
theorem tendsto_snd : Tendsto Prod.snd (f ×ˢ g) g :=
tendsto_inf_right tendsto_comap
#align filter.tendsto_snd Filter.tendsto_snd
/-- If a function tends to a product `g ×ˢ h` of filters, then its first component tends to
`g`. See also `Filter.Tendsto.fst_nhds` for the special case of converging to a point in a
product of two topological spaces. -/
theorem Tendsto.fst {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) :
Tendsto (fun a ↦ (m a).1) f g :=
tendsto_fst.comp H
/-- If a function tends to a product `g ×ˢ h` of filters, then its second component tends to
`h`. See also `Filter.Tendsto.snd_nhds` for the special case of converging to a point in a
product of two topological spaces. -/
theorem Tendsto.snd {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) :
Tendsto (fun a ↦ (m a).2) f h :=
tendsto_snd.comp H
theorem Tendsto.prod_mk {h : Filter γ} {m₁ : α → β} {m₂ : α → γ}
(h₁ : Tendsto m₁ f g) (h₂ : Tendsto m₂ f h) : Tendsto (fun x => (m₁ x, m₂ x)) f (g ×ˢ h) :=
tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩
#align filter.tendsto.prod_mk Filter.Tendsto.prod_mk
theorem tendsto_prod_swap : Tendsto (Prod.swap : α × β → β × α) (f ×ˢ g) (g ×ˢ f) :=
tendsto_snd.prod_mk tendsto_fst
#align filter.tendsto_prod_swap Filter.tendsto_prod_swap
theorem Eventually.prod_inl {la : Filter α} {p : α → Prop} (h : ∀ᶠ x in la, p x) (lb : Filter β) :
∀ᶠ x in la ×ˢ lb, p (x : α × β).1 :=
tendsto_fst.eventually h
#align filter.eventually.prod_inl Filter.Eventually.prod_inl
theorem Eventually.prod_inr {lb : Filter β} {p : β → Prop} (h : ∀ᶠ x in lb, p x) (la : Filter α) :
∀ᶠ x in la ×ˢ lb, p (x : α × β).2 :=
tendsto_snd.eventually h
#align filter.eventually.prod_inr Filter.Eventually.prod_inr
theorem Eventually.prod_mk {la : Filter α} {pa : α → Prop} (ha : ∀ᶠ x in la, pa x) {lb : Filter β}
{pb : β → Prop} (hb : ∀ᶠ y in lb, pb y) : ∀ᶠ p in la ×ˢ lb, pa (p : α × β).1 ∧ pb p.2 :=
(ha.prod_inl lb).and (hb.prod_inr la)
#align filter.eventually.prod_mk Filter.Eventually.prod_mk
theorem EventuallyEq.prod_map {δ} {la : Filter α} {fa ga : α → γ} (ha : fa =ᶠ[la] ga)
{lb : Filter β} {fb gb : β → δ} (hb : fb =ᶠ[lb] gb) :
Prod.map fa fb =ᶠ[la ×ˢ lb] Prod.map ga gb :=
(Eventually.prod_mk ha hb).mono fun _ h => Prod.ext h.1 h.2
#align filter.eventually_eq.prod_map Filter.EventuallyEq.prod_map
theorem EventuallyLE.prod_map {δ} [LE γ] [LE δ] {la : Filter α} {fa ga : α → γ} (ha : fa ≤ᶠ[la] ga)
{lb : Filter β} {fb gb : β → δ} (hb : fb ≤ᶠ[lb] gb) :
Prod.map fa fb ≤ᶠ[la ×ˢ lb] Prod.map ga gb :=
Eventually.prod_mk ha hb
#align filter.eventually_le.prod_map Filter.EventuallyLE.prod_map
theorem Eventually.curry {la : Filter α} {lb : Filter β} {p : α × β → Prop}
(h : ∀ᶠ x in la ×ˢ lb, p x) : ∀ᶠ x in la, ∀ᶠ y in lb, p (x, y) := by
rcases eventually_prod_iff.1 h with ⟨pa, ha, pb, hb, h⟩
exact ha.mono fun a ha => hb.mono fun b hb => h ha hb
#align filter.eventually.curry Filter.Eventually.curry
protected lemma Frequently.uncurry {la : Filter α} {lb : Filter β} {p : α → β → Prop}
(h : ∃ᶠ x in la, ∃ᶠ y in lb, p x y) : ∃ᶠ xy in la ×ˢ lb, p xy.1 xy.2 :=
mt (fun h ↦ by simpa only [not_frequently] using h.curry) h
/-- A fact that is eventually true about all pairs `l ×ˢ l` is eventually true about
all diagonal pairs `(i, i)` -/
theorem Eventually.diag_of_prod {p : α × α → Prop} (h : ∀ᶠ i in f ×ˢ f, p i) :
∀ᶠ i in f, p (i, i) := by
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
apply (ht.and hs).mono fun x hx => hst hx.1 hx.2
#align filter.eventually.diag_of_prod Filter.Eventually.diag_of_prod
theorem Eventually.diag_of_prod_left {f : Filter α} {g : Filter γ} {p : (α × α) × γ → Prop} :
(∀ᶠ x in (f ×ˢ f) ×ˢ g, p x) → ∀ᶠ x : α × γ in f ×ˢ g, p ((x.1, x.1), x.2) := by
intro h
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
exact (ht.diag_of_prod.prod_mk hs).mono fun x hx => by simp only [hst hx.1 hx.2]
#align filter.eventually.diag_of_prod_left Filter.Eventually.diag_of_prod_left
theorem Eventually.diag_of_prod_right {f : Filter α} {g : Filter γ} {p : α × γ × γ → Prop} :
(∀ᶠ x in f ×ˢ (g ×ˢ g), p x) → ∀ᶠ x : α × γ in f ×ˢ g, p (x.1, x.2, x.2) := by
intro h
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
exact (ht.prod_mk hs.diag_of_prod).mono fun x hx => by simp only [hst hx.1 hx.2]
#align filter.eventually.diag_of_prod_right Filter.Eventually.diag_of_prod_right
theorem tendsto_diag : Tendsto (fun i => (i, i)) f (f ×ˢ f) :=
tendsto_iff_eventually.mpr fun _ hpr => hpr.diag_of_prod
#align filter.tendsto_diag Filter.tendsto_diag
theorem prod_iInf_left [Nonempty ι] {f : ι → Filter α} {g : Filter β} :
(⨅ i, f i) ×ˢ g = ⨅ i, f i ×ˢ g := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_iInf, iInf_inf]
simp only [Filter.prod, eq_self_iff_true]
#align filter.prod_infi_left Filter.prod_iInf_left
theorem prod_iInf_right [Nonempty ι] {f : Filter α} {g : ι → Filter β} :
(f ×ˢ ⨅ i, g i) = ⨅ i, f ×ˢ g i := by
dsimp only [SProd.sprod]
rw [Filter.prod, comap_iInf, inf_iInf]
simp only [Filter.prod, eq_self_iff_true]
#align filter.prod_infi_right Filter.prod_iInf_right
@[mono, gcongr]
theorem prod_mono {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) :
f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ :=
inf_le_inf (comap_mono hf) (comap_mono hg)
#align filter.prod_mono Filter.prod_mono
@[gcongr]
theorem prod_mono_left (g : Filter β) {f₁ f₂ : Filter α} (hf : f₁ ≤ f₂) : f₁ ×ˢ g ≤ f₂ ×ˢ g :=
Filter.prod_mono hf rfl.le
#align filter.prod_mono_left Filter.prod_mono_left
@[gcongr]
theorem prod_mono_right (f : Filter α) {g₁ g₂ : Filter β} (hf : g₁ ≤ g₂) : f ×ˢ g₁ ≤ f ×ˢ g₂ :=
Filter.prod_mono rfl.le hf
#align filter.prod_mono_right Filter.prod_mono_right
theorem prod_comap_comap_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x}
{f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : β₁ → α₁} {m₂ : β₂ → α₂} :
comap m₁ f₁ ×ˢ comap m₂ f₂ = comap (fun p : β₁ × β₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) := by
simp only [SProd.sprod, Filter.prod, comap_comap, comap_inf, (· ∘ ·)]
#align filter.prod_comap_comap_eq Filter.prod_comap_comap_eq
theorem prod_comm' : f ×ˢ g = comap Prod.swap (g ×ˢ f) := by
simp only [SProd.sprod, Filter.prod, comap_comap, (· ∘ ·), inf_comm, Prod.swap, comap_inf]
#align filter.prod_comm' Filter.prod_comm'
theorem prod_comm : f ×ˢ g = map (fun p : β × α => (p.2, p.1)) (g ×ˢ f) := by
rw [prod_comm', ← map_swap_eq_comap_swap]
rfl
#align filter.prod_comm Filter.prod_comm
theorem mem_prod_iff_left {s : Set (α × β)} :
s ∈ f ×ˢ g ↔ ∃ t ∈ f, ∀ᶠ y in g, ∀ x ∈ t, (x, y) ∈ s := by
simp only [mem_prod_iff, prod_subset_iff]
refine exists_congr fun _ => Iff.rfl.and <| Iff.trans ?_ exists_mem_subset_iff
exact exists_congr fun _ => Iff.rfl.and forall₂_swap
theorem mem_prod_iff_right {s : Set (α × β)} :
s ∈ f ×ˢ g ↔ ∃ t ∈ g, ∀ᶠ x in f, ∀ y ∈ t, (x, y) ∈ s := by
rw [prod_comm, mem_map, mem_prod_iff_left]; rfl
@[simp]
| Mathlib/Order/Filter/Prod.lean | 288 | 291 | theorem map_fst_prod (f : Filter α) (g : Filter β) [NeBot g] : map Prod.fst (f ×ˢ g) = f := by |
ext s
simp only [mem_map, mem_prod_iff_left, mem_preimage, eventually_const, ← subset_def,
exists_mem_subset_iff]
|
/-
Copyright (c) 2021 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Data.Int.Interval
import Mathlib.RingTheory.Binomial
import Mathlib.RingTheory.HahnSeries.PowerSeries
import Mathlib.RingTheory.HahnSeries.Summable
import Mathlib.FieldTheory.RatFunc.AsPolynomial
import Mathlib.RingTheory.Localization.FractionRing
#align_import ring_theory.laurent_series from "leanprover-community/mathlib"@"831c494092374cfe9f50591ed0ac81a25efc5b86"
/-!
# Laurent Series
## Main Definitions
* Defines `LaurentSeries` as an abbreviation for `HahnSeries ℤ`.
* Defines `hasseDeriv` of a Laurent series with coefficients in a module over a ring.
* Provides a coercion `PowerSeries R` into `LaurentSeries R` given by
`HahnSeries.ofPowerSeries`.
* Defines `LaurentSeries.powerSeriesPart`
* Defines the localization map `LaurentSeries.of_powerSeries_localization` which evaluates to
`HahnSeries.ofPowerSeries`.
* Embedding of rational functions into Laurent series, provided as a coercion, utilizing
the underlying `RatFunc.coeAlgHom`.
## Main Results
* Basic properties of Hasse derivatives
-/
universe u
open scoped Classical
open HahnSeries Polynomial
noncomputable section
/-- A `LaurentSeries` is implemented as a `HahnSeries` with value group `ℤ`. -/
abbrev LaurentSeries (R : Type u) [Zero R] :=
HahnSeries ℤ R
#align laurent_series LaurentSeries
variable {R : Type*}
namespace LaurentSeries
section HasseDeriv
/-- The Hasse derivative of Laurent series, as a linear map. -/
@[simps]
def hasseDeriv (R : Type*) {V : Type*} [AddCommGroup V] [Semiring R] [Module R V] (k : ℕ) :
LaurentSeries V →ₗ[R] LaurentSeries V where
toFun f := HahnSeries.ofSuppBddBelow (fun (n : ℤ) => (Ring.choose (n + k) k) • f.coeff (n + k))
(forallLTEqZero_supp_BddBelow _ (f.order - k : ℤ)
(fun _ h_lt ↦ by rw [coeff_eq_zero_of_lt_order <| lt_sub_iff_add_lt.mp h_lt, smul_zero]))
map_add' f g := by
ext
simp only [ofSuppBddBelow, add_coeff', Pi.add_apply, smul_add]
map_smul' r f := by
ext
simp only [ofSuppBddBelow, smul_coeff, RingHom.id_apply, smul_comm r]
variable [Semiring R] {V : Type*} [AddCommGroup V] [Module R V]
theorem hasseDeriv_coeff (k : ℕ) (f : LaurentSeries V) (n : ℤ) :
(hasseDeriv R k f).coeff n = Ring.choose (n + k) k • f.coeff (n + k) :=
rfl
end HasseDeriv
section Semiring
variable [Semiring R]
instance : Coe (PowerSeries R) (LaurentSeries R) :=
⟨HahnSeries.ofPowerSeries ℤ R⟩
/- Porting note: now a syntactic tautology and not needed elsewhere
theorem coe_powerSeries (x : PowerSeries R) :
(x : LaurentSeries R) = HahnSeries.ofPowerSeries ℤ R x :=
rfl -/
#noalign laurent_series.coe_power_series
@[simp]
theorem coeff_coe_powerSeries (x : PowerSeries R) (n : ℕ) :
HahnSeries.coeff (x : LaurentSeries R) n = PowerSeries.coeff R n x := by
rw [ofPowerSeries_apply_coeff]
#align laurent_series.coeff_coe_power_series LaurentSeries.coeff_coe_powerSeries
/-- This is a power series that can be multiplied by an integer power of `X` to give our
Laurent series. If the Laurent series is nonzero, `powerSeriesPart` has a nonzero
constant term. -/
def powerSeriesPart (x : LaurentSeries R) : PowerSeries R :=
PowerSeries.mk fun n => x.coeff (x.order + n)
#align laurent_series.power_series_part LaurentSeries.powerSeriesPart
@[simp]
theorem powerSeriesPart_coeff (x : LaurentSeries R) (n : ℕ) :
PowerSeries.coeff R n x.powerSeriesPart = x.coeff (x.order + n) :=
PowerSeries.coeff_mk _ _
#align laurent_series.power_series_part_coeff LaurentSeries.powerSeriesPart_coeff
@[simp]
theorem powerSeriesPart_zero : powerSeriesPart (0 : LaurentSeries R) = 0 := by
ext
simp [(PowerSeries.coeff _ _).map_zero] -- Note: this doesn't get picked up any more
#align laurent_series.power_series_part_zero LaurentSeries.powerSeriesPart_zero
@[simp]
theorem powerSeriesPart_eq_zero (x : LaurentSeries R) : x.powerSeriesPart = 0 ↔ x = 0 := by
constructor
· contrapose!
simp only [ne_eq]
intro h
rw [PowerSeries.ext_iff, not_forall]
refine ⟨0, ?_⟩
simp [coeff_order_ne_zero h]
· rintro rfl
simp
#align laurent_series.power_series_part_eq_zero LaurentSeries.powerSeriesPart_eq_zero
@[simp]
theorem single_order_mul_powerSeriesPart (x : LaurentSeries R) :
(single x.order 1 : LaurentSeries R) * x.powerSeriesPart = x := by
ext n
rw [← sub_add_cancel n x.order, single_mul_coeff_add, sub_add_cancel, one_mul]
by_cases h : x.order ≤ n
· rw [Int.eq_natAbs_of_zero_le (sub_nonneg_of_le h), coeff_coe_powerSeries,
powerSeriesPart_coeff, ← Int.eq_natAbs_of_zero_le (sub_nonneg_of_le h),
add_sub_cancel]
· rw [ofPowerSeries_apply, embDomain_notin_range]
· contrapose! h
exact order_le_of_coeff_ne_zero h.symm
· contrapose! h
simp only [Set.mem_range, RelEmbedding.coe_mk, Function.Embedding.coeFn_mk] at h
obtain ⟨m, hm⟩ := h
rw [← sub_nonneg, ← hm]
simp only [Nat.cast_nonneg]
#align laurent_series.single_order_mul_power_series_part LaurentSeries.single_order_mul_powerSeriesPart
theorem ofPowerSeries_powerSeriesPart (x : LaurentSeries R) :
ofPowerSeries ℤ R x.powerSeriesPart = single (-x.order) 1 * x := by
refine Eq.trans ?_ (congr rfl x.single_order_mul_powerSeriesPart)
rw [← mul_assoc, single_mul_single, neg_add_self, mul_one, ← C_apply, C_one, one_mul]
#align laurent_series.of_power_series_power_series_part LaurentSeries.ofPowerSeries_powerSeriesPart
end Semiring
instance [CommSemiring R] : Algebra (PowerSeries R) (LaurentSeries R) :=
(HahnSeries.ofPowerSeries ℤ R).toAlgebra
@[simp]
theorem coe_algebraMap [CommSemiring R] :
⇑(algebraMap (PowerSeries R) (LaurentSeries R)) = HahnSeries.ofPowerSeries ℤ R :=
rfl
#align laurent_series.coe_algebra_map LaurentSeries.coe_algebraMap
/-- The localization map from power series to Laurent series. -/
@[simps (config := { rhsMd := .all, simpRhs := true })]
instance of_powerSeries_localization [CommRing R] :
IsLocalization (Submonoid.powers (PowerSeries.X : PowerSeries R)) (LaurentSeries R) where
map_units' := by
rintro ⟨_, n, rfl⟩
refine ⟨⟨single (n : ℤ) 1, single (-n : ℤ) 1, ?_, ?_⟩, ?_⟩
· simp only [single_mul_single, mul_one, add_right_neg]
rfl
· simp only [single_mul_single, mul_one, add_left_neg]
rfl
· dsimp; rw [ofPowerSeries_X_pow]
surj' z := by
by_cases h : 0 ≤ z.order
· refine ⟨⟨PowerSeries.X ^ Int.natAbs z.order * powerSeriesPart z, 1⟩, ?_⟩
simp only [RingHom.map_one, mul_one, RingHom.map_mul, coe_algebraMap, ofPowerSeries_X_pow,
Submonoid.coe_one]
rw [Int.natAbs_of_nonneg h, single_order_mul_powerSeriesPart]
· refine ⟨⟨powerSeriesPart z, PowerSeries.X ^ Int.natAbs z.order, ⟨_, rfl⟩⟩, ?_⟩
simp only [coe_algebraMap, ofPowerSeries_powerSeriesPart]
rw [mul_comm _ z]
refine congr rfl ?_
rw [ofPowerSeries_X_pow, Int.ofNat_natAbs_of_nonpos]
exact le_of_not_ge h
exists_of_eq {x y} := by
rw [coe_algebraMap, ofPowerSeries_injective.eq_iff]
rintro rfl
exact ⟨1, rfl⟩
#align laurent_series.of_power_series_localization LaurentSeries.of_powerSeries_localization
instance {K : Type*} [Field K] : IsFractionRing (PowerSeries K) (LaurentSeries K) :=
IsLocalization.of_le (Submonoid.powers (PowerSeries.X : PowerSeries K)) _
(powers_le_nonZeroDivisors_of_noZeroDivisors PowerSeries.X_ne_zero) fun _ hf =>
isUnit_of_mem_nonZeroDivisors <| map_mem_nonZeroDivisors _ HahnSeries.ofPowerSeries_injective hf
end LaurentSeries
namespace PowerSeries
open LaurentSeries
variable {R' : Type*} [Semiring R] [Ring R'] (f g : PowerSeries R) (f' g' : PowerSeries R')
@[norm_cast] -- Porting note (#10618): simp can prove this
theorem coe_zero : ((0 : PowerSeries R) : LaurentSeries R) = 0 :=
(ofPowerSeries ℤ R).map_zero
#align power_series.coe_zero PowerSeries.coe_zero
@[norm_cast] -- Porting note (#10618): simp can prove this
theorem coe_one : ((1 : PowerSeries R) : LaurentSeries R) = 1 :=
(ofPowerSeries ℤ R).map_one
#align power_series.coe_one PowerSeries.coe_one
@[norm_cast] -- Porting note (#10618): simp can prove this
theorem coe_add : ((f + g : PowerSeries R) : LaurentSeries R) = f + g :=
(ofPowerSeries ℤ R).map_add _ _
#align power_series.coe_add PowerSeries.coe_add
@[norm_cast]
theorem coe_sub : ((f' - g' : PowerSeries R') : LaurentSeries R') = f' - g' :=
(ofPowerSeries ℤ R').map_sub _ _
#align power_series.coe_sub PowerSeries.coe_sub
@[norm_cast]
theorem coe_neg : ((-f' : PowerSeries R') : LaurentSeries R') = -f' :=
(ofPowerSeries ℤ R').map_neg _
#align power_series.coe_neg PowerSeries.coe_neg
@[norm_cast] -- Porting note (#10618): simp can prove this
theorem coe_mul : ((f * g : PowerSeries R) : LaurentSeries R) = f * g :=
(ofPowerSeries ℤ R).map_mul _ _
#align power_series.coe_mul PowerSeries.coe_mul
theorem coeff_coe (i : ℤ) :
((f : PowerSeries R) : LaurentSeries R).coeff i =
if i < 0 then 0 else PowerSeries.coeff R i.natAbs f := by
cases i
· rw [Int.ofNat_eq_coe, coeff_coe_powerSeries, if_neg (Int.natCast_nonneg _).not_lt,
Int.natAbs_ofNat]
· rw [ofPowerSeries_apply, embDomain_notin_image_support, if_pos (Int.negSucc_lt_zero _)]
simp only [not_exists, RelEmbedding.coe_mk, Set.mem_image, not_and, Function.Embedding.coeFn_mk,
Ne, toPowerSeries_symm_apply_coeff, mem_support, imp_true_iff,
not_false_iff]
#align power_series.coeff_coe PowerSeries.coeff_coe
-- Porting note (#10618): simp can prove this
-- Porting note: removed norm_cast attribute
theorem coe_C (r : R) : ((C R r : PowerSeries R) : LaurentSeries R) = HahnSeries.C r :=
ofPowerSeries_C _
set_option linter.uppercaseLean3 false in
#align power_series.coe_C PowerSeries.coe_C
-- @[simp] -- Porting note (#10618): simp can prove this
theorem coe_X : ((X : PowerSeries R) : LaurentSeries R) = single 1 1 :=
ofPowerSeries_X
set_option linter.uppercaseLean3 false in
#align power_series.coe_X PowerSeries.coe_X
@[simp, norm_cast]
theorem coe_smul {S : Type*} [Semiring S] [Module R S] (r : R) (x : PowerSeries S) :
((r • x : PowerSeries S) : LaurentSeries S) = r • (ofPowerSeries ℤ S x) := by
ext
simp [coeff_coe, coeff_smul, smul_ite]
#align power_series.coe_smul PowerSeries.coe_smul
-- Porting note: RingHom.map_bit0 and RingHom.map_bit1 no longer exist
#noalign power_series.coe_bit0
#noalign power_series.coe_bit1
@[norm_cast]
theorem coe_pow (n : ℕ) : ((f ^ n : PowerSeries R) : LaurentSeries R) = (ofPowerSeries ℤ R f) ^ n :=
(ofPowerSeries ℤ R).map_pow _ _
#align power_series.coe_pow PowerSeries.coe_pow
end PowerSeries
namespace RatFunc
section RatFunc
open RatFunc
variable {F : Type u} [Field F] (p q : F[X]) (f g : RatFunc F)
/-- The coercion `RatFunc F → LaurentSeries F` as bundled alg hom. -/
def coeAlgHom (F : Type u) [Field F] : RatFunc F →ₐ[F[X]] LaurentSeries F :=
liftAlgHom (Algebra.ofId _ _) <|
nonZeroDivisors_le_comap_nonZeroDivisors_of_injective _ <|
Polynomial.algebraMap_hahnSeries_injective _
#align ratfunc.coe_alg_hom RatFunc.coeAlgHom
/-- The coercion `RatFunc F → LaurentSeries F` as a function.
This is the implementation of `coeToLaurentSeries`.
-/
@[coe]
def coeToLaurentSeries_fun {F : Type u} [Field F] : RatFunc F → LaurentSeries F :=
coeAlgHom F
instance coeToLaurentSeries : Coe (RatFunc F) (LaurentSeries F) :=
⟨coeToLaurentSeries_fun⟩
#align ratfunc.coe_to_laurent_series RatFunc.coeToLaurentSeries
theorem coe_def : (f : LaurentSeries F) = coeAlgHom F f :=
rfl
#align ratfunc.coe_def RatFunc.coe_def
theorem coe_num_denom : (f : LaurentSeries F) = f.num / f.denom :=
liftAlgHom_apply _ _ f
#align ratfunc.coe_num_denom RatFunc.coe_num_denom
theorem coe_injective : Function.Injective ((↑) : RatFunc F → LaurentSeries F) :=
liftAlgHom_injective _ (Polynomial.algebraMap_hahnSeries_injective _)
#align ratfunc.coe_injective RatFunc.coe_injective
-- Porting note: removed the `norm_cast` tag:
-- `norm_cast: badly shaped lemma, rhs can't start with coe `↑(coeAlgHom F) f`
@[simp]
theorem coe_apply : coeAlgHom F f = f :=
rfl
#align ratfunc.coe_apply RatFunc.coe_apply
theorem coe_coe (P : Polynomial F) : (P : LaurentSeries F) = (P : RatFunc F) := by
simp only [coePolynomial, coe_def, AlgHom.commutes, algebraMap_hahnSeries_apply]
@[simp, norm_cast]
theorem coe_zero : ((0 : RatFunc F) : LaurentSeries F) = 0 :=
(coeAlgHom F).map_zero
#align ratfunc.coe_zero RatFunc.coe_zero
theorem coe_ne_zero {f : Polynomial F} (hf : f ≠ 0) : (↑f : PowerSeries F) ≠ 0 := by
simp only [ne_eq, Polynomial.coe_eq_zero_iff, hf, not_false_eq_true]
@[simp, norm_cast]
theorem coe_one : ((1 : RatFunc F) : LaurentSeries F) = 1 :=
(coeAlgHom F).map_one
#align ratfunc.coe_one RatFunc.coe_one
@[simp, norm_cast]
theorem coe_add : ((f + g : RatFunc F) : LaurentSeries F) = f + g :=
(coeAlgHom F).map_add _ _
#align ratfunc.coe_add RatFunc.coe_add
@[simp, norm_cast]
theorem coe_sub : ((f - g : RatFunc F) : LaurentSeries F) = f - g :=
(coeAlgHom F).map_sub _ _
#align ratfunc.coe_sub RatFunc.coe_sub
@[simp, norm_cast]
theorem coe_neg : ((-f : RatFunc F) : LaurentSeries F) = -f :=
(coeAlgHom F).map_neg _
#align ratfunc.coe_neg RatFunc.coe_neg
@[simp, norm_cast]
theorem coe_mul : ((f * g : RatFunc F) : LaurentSeries F) = f * g :=
(coeAlgHom F).map_mul _ _
#align ratfunc.coe_mul RatFunc.coe_mul
@[simp, norm_cast]
theorem coe_pow (n : ℕ) : ((f ^ n : RatFunc F) : LaurentSeries F) = (f : LaurentSeries F) ^ n :=
(coeAlgHom F).map_pow _ _
#align ratfunc.coe_pow RatFunc.coe_pow
@[simp, norm_cast]
theorem coe_div :
((f / g : RatFunc F) : LaurentSeries F) = (f : LaurentSeries F) / (g : LaurentSeries F) :=
map_div₀ (coeAlgHom F) _ _
#align ratfunc.coe_div RatFunc.coe_div
@[simp, norm_cast]
theorem coe_C (r : F) : ((RatFunc.C r : RatFunc F) : LaurentSeries F) = HahnSeries.C r := by
rw [coe_num_denom, num_C, denom_C, Polynomial.coe_C, -- Porting note: removed `coe_C`
Polynomial.coe_one,
PowerSeries.coe_one, div_one]
simp only [algebraMap_eq_C, ofPowerSeries_C, C_apply] -- Porting note: added
set_option linter.uppercaseLean3 false in
#align ratfunc.coe_C RatFunc.coe_C
-- TODO: generalize over other modules
@[simp, norm_cast]
theorem coe_smul (r : F) : ((r • f : RatFunc F) : LaurentSeries F) = r • (f : LaurentSeries F) := by
rw [RatFunc.smul_eq_C_mul, ← C_mul_eq_smul, coe_mul, coe_C]
#align ratfunc.coe_smul RatFunc.coe_smul
-- Porting note: removed `norm_cast` because "badly shaped lemma, rhs can't start with coe"
-- even though `single 1 1` is a bundled function application, not a "real" coercion
@[simp, nolint simpNF] -- Added `simpNF` to avoid timeout #8386
theorem coe_X : ((X : RatFunc F) : LaurentSeries F) = single 1 1 := by
rw [coe_num_denom, num_X, denom_X, Polynomial.coe_X, -- Porting note: removed `coe_C`
Polynomial.coe_one,
PowerSeries.coe_one, div_one]
simp only [ofPowerSeries_X] -- Porting note: added
set_option linter.uppercaseLean3 false in
#align ratfunc.coe_X RatFunc.coe_X
| Mathlib/RingTheory/LaurentSeries.lean | 394 | 400 | theorem single_one_eq_pow {R : Type _} [Ring R] (n : ℕ) :
single (n : ℤ) (1 : R) = single (1 : ℤ) 1 ^ n := by |
induction' n with n h_ind
· simp only [Nat.cast_zero, pow_zero]
rfl
· rw [← Int.ofNat_add_one_out, pow_succ', ← h_ind, HahnSeries.single_mul_single, one_mul,
add_comm]
|
/-
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
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 727 | 728 | 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]
|
/-
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.FieldTheory.PrimitiveElement
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly
import Mathlib.LinearAlgebra.Matrix.ToLinearEquiv
import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure
import Mathlib.FieldTheory.Galois
#align_import ring_theory.norm from "leanprover-community/mathlib"@"fecd3520d2a236856f254f27714b80dcfe28ea57"
/-!
# Norm for (finite) ring extensions
Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`,
the determinant of the linear map given by multiplying by `s` gives information
about the roots of the minimal polynomial of `s` over `R`.
## Implementation notes
Typically, the norm is defined specifically for finite field extensions.
The current definition is as general as possible and the assumption that we have
fields or that the extension is finite is added to the lemmas as needed.
We only define the norm for left multiplication (`Algebra.leftMulMatrix`,
i.e. `LinearMap.mulLeft`).
For now, the definitions assume `S` is commutative, so the choice doesn't
matter anyway.
See also `Algebra.trace`, which is defined similarly as the trace of
`Algebra.leftMulMatrix`.
## References
* https://en.wikipedia.org/wiki/Field_norm
-/
universe u v w
variable {R S T : Type*} [CommRing R] [Ring S]
variable [Algebra R S]
variable {K L F : Type*} [Field K] [Field L] [Field F]
variable [Algebra K L] [Algebra K F]
variable {ι : Type w}
open FiniteDimensional
open LinearMap
open Matrix Polynomial
open scoped Matrix
namespace Algebra
variable (R)
/-- The norm of an element `s` of an `R`-algebra is the determinant of `(*) s`. -/
noncomputable def norm : S →* R :=
LinearMap.det.comp (lmul R S).toRingHom.toMonoidHom
#align algebra.norm Algebra.norm
theorem norm_apply (x : S) : norm R x = LinearMap.det (lmul R S x) := rfl
#align algebra.norm_apply Algebra.norm_apply
theorem norm_eq_one_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) (x : S) :
norm R x = 1 := by rw [norm_apply, LinearMap.det]; split_ifs <;> trivial
#align algebra.norm_eq_one_of_not_exists_basis Algebra.norm_eq_one_of_not_exists_basis
variable {R}
theorem norm_eq_one_of_not_module_finite (h : ¬Module.Finite R S) (x : S) : norm R x = 1 := by
refine norm_eq_one_of_not_exists_basis _ (mt ?_ h) _
rintro ⟨s, ⟨b⟩⟩
exact Module.Finite.of_basis b
#align algebra.norm_eq_one_of_not_module_finite Algebra.norm_eq_one_of_not_module_finite
-- Can't be a `simp` lemma because it depends on a choice of basis
theorem norm_eq_matrix_det [Fintype ι] [DecidableEq ι] (b : Basis ι R S) (s : S) :
norm R s = Matrix.det (Algebra.leftMulMatrix b s) := by
rw [norm_apply, ← LinearMap.det_toMatrix b, ← toMatrix_lmul_eq]; rfl
#align algebra.norm_eq_matrix_det Algebra.norm_eq_matrix_det
/-- If `x` is in the base ring `K`, then the norm is `x ^ [L : K]`. -/
theorem norm_algebraMap_of_basis [Fintype ι] (b : Basis ι R S) (x : R) :
norm R (algebraMap R S x) = x ^ Fintype.card ι := by
haveI := Classical.decEq ι
rw [norm_apply, ← det_toMatrix b, lmul_algebraMap]
convert @det_diagonal _ _ _ _ _ fun _ : ι => x
· ext (i j); rw [toMatrix_lsmul]
· rw [Finset.prod_const, Finset.card_univ]
#align algebra.norm_algebra_map_of_basis Algebra.norm_algebraMap_of_basis
/-- If `x` is in the base field `K`, then the norm is `x ^ [L : K]`.
(If `L` is not finite-dimensional over `K`, then `norm = 1 = x ^ 0 = x ^ (finrank L K)`.)
-/
@[simp]
protected theorem norm_algebraMap {L : Type*} [Ring L] [Algebra K L] (x : K) :
norm K (algebraMap K L x) = x ^ finrank K L := by
by_cases H : ∃ s : Finset L, Nonempty (Basis s K L)
· rw [norm_algebraMap_of_basis H.choose_spec.some, finrank_eq_card_basis H.choose_spec.some]
· rw [norm_eq_one_of_not_exists_basis K H, finrank_eq_zero_of_not_exists_basis, pow_zero]
rintro ⟨s, ⟨b⟩⟩
exact H ⟨s, ⟨b⟩⟩
#align algebra.norm_algebra_map Algebra.norm_algebraMap
section EqProdRoots
/-- Given `pb : PowerBasis K S`, then the norm of `pb.gen` is
`(-1) ^ pb.dim * coeff (minpoly K pb.gen) 0`. -/
theorem PowerBasis.norm_gen_eq_coeff_zero_minpoly (pb : PowerBasis R S) :
norm R pb.gen = (-1) ^ pb.dim * coeff (minpoly R pb.gen) 0 := by
rw [norm_eq_matrix_det pb.basis, det_eq_sign_charpoly_coeff, charpoly_leftMulMatrix,
Fintype.card_fin]
#align algebra.power_basis.norm_gen_eq_coeff_zero_minpoly Algebra.PowerBasis.norm_gen_eq_coeff_zero_minpoly
/-- Given `pb : PowerBasis R S`, then the norm of `pb.gen` is
`((minpoly R pb.gen).aroots F).prod`. -/
theorem PowerBasis.norm_gen_eq_prod_roots [Algebra R F] (pb : PowerBasis R S)
(hf : (minpoly R pb.gen).Splits (algebraMap R F)) :
algebraMap R F (norm R pb.gen) = ((minpoly R pb.gen).aroots F).prod := by
haveI := Module.nontrivial R F
have := minpoly.monic pb.isIntegral_gen
rw [PowerBasis.norm_gen_eq_coeff_zero_minpoly, ← pb.natDegree_minpoly, RingHom.map_mul,
← coeff_map,
prod_roots_eq_coeff_zero_of_monic_of_split (this.map _) ((splits_id_iff_splits _).2 hf),
this.natDegree_map, map_pow, ← mul_assoc, ← mul_pow]
simp only [map_neg, _root_.map_one, neg_mul, neg_neg, one_pow, one_mul]
#align algebra.power_basis.norm_gen_eq_prod_roots Algebra.PowerBasis.norm_gen_eq_prod_roots
end EqProdRoots
section EqZeroIff
variable [Finite ι]
@[simp]
theorem norm_zero [Nontrivial S] [Module.Free R S] [Module.Finite R S] : norm R (0 : S) = 0 := by
nontriviality
rw [norm_apply, coe_lmul_eq_mul, map_zero, LinearMap.det_zero' (Module.Free.chooseBasis R S)]
#align algebra.norm_zero Algebra.norm_zero
@[simp]
theorem norm_eq_zero_iff [IsDomain R] [IsDomain S] [Module.Free R S] [Module.Finite R S] {x : S} :
norm R x = 0 ↔ x = 0 := by
constructor
on_goal 1 => let b := Module.Free.chooseBasis R S
swap
· rintro rfl; exact norm_zero
· letI := Classical.decEq (Module.Free.ChooseBasisIndex R S)
rw [norm_eq_matrix_det b, ← Matrix.exists_mulVec_eq_zero_iff]
rintro ⟨v, v_ne, hv⟩
rw [← b.equivFun.apply_symm_apply v, b.equivFun_symm_apply, b.equivFun_apply,
leftMulMatrix_mulVec_repr] at hv
refine (mul_eq_zero.mp (b.ext_elem fun i => ?_)).resolve_right (show ∑ i, v i • b i ≠ 0 from ?_)
· simpa only [LinearEquiv.map_zero, Pi.zero_apply] using congr_fun hv i
· contrapose! v_ne with sum_eq
apply b.equivFun.symm.injective
rw [b.equivFun_symm_apply, sum_eq, LinearEquiv.map_zero]
#align algebra.norm_eq_zero_iff Algebra.norm_eq_zero_iff
theorem norm_ne_zero_iff [IsDomain R] [IsDomain S] [Module.Free R S] [Module.Finite R S] {x : S} :
norm R x ≠ 0 ↔ x ≠ 0 := not_iff_not.mpr norm_eq_zero_iff
#align algebra.norm_ne_zero_iff Algebra.norm_ne_zero_iff
/-- This is `Algebra.norm_eq_zero_iff` composed with `Algebra.norm_apply`. -/
@[simp]
theorem norm_eq_zero_iff' [IsDomain R] [IsDomain S] [Module.Free R S] [Module.Finite R S] {x : S} :
LinearMap.det (LinearMap.mul R S x) = 0 ↔ x = 0 := norm_eq_zero_iff
#align algebra.norm_eq_zero_iff' Algebra.norm_eq_zero_iff'
theorem norm_eq_zero_iff_of_basis [IsDomain R] [IsDomain S] (b : Basis ι R S) {x : S} :
Algebra.norm R x = 0 ↔ x = 0 := by
haveI : Module.Free R S := Module.Free.of_basis b
haveI : Module.Finite R S := Module.Finite.of_basis b
exact norm_eq_zero_iff
#align algebra.norm_eq_zero_iff_of_basis Algebra.norm_eq_zero_iff_of_basis
theorem norm_ne_zero_iff_of_basis [IsDomain R] [IsDomain S] (b : Basis ι R S) {x : S} :
Algebra.norm R x ≠ 0 ↔ x ≠ 0 :=
not_iff_not.mpr (norm_eq_zero_iff_of_basis b)
#align algebra.norm_ne_zero_iff_of_basis Algebra.norm_ne_zero_iff_of_basis
end EqZeroIff
open IntermediateField
variable (K)
theorem norm_eq_norm_adjoin [FiniteDimensional K L] [IsSeparable K L] (x : L) :
norm K x = norm K (AdjoinSimple.gen K x) ^ finrank K⟮x⟯ L := by
letI := isSeparable_tower_top_of_isSeparable K K⟮x⟯ L
let pbL := Field.powerBasisOfFiniteOfSeparable K⟮x⟯ L
let pbx := IntermediateField.adjoin.powerBasis (IsSeparable.isIntegral K x)
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [← AdjoinSimple.algebraMap_gen K x, norm_eq_matrix_det (pbx.basis.smul pbL.basis) _,
smul_leftMulMatrix_algebraMap, det_blockDiagonal, norm_eq_matrix_det pbx.basis]
simp only [Finset.card_fin, Finset.prod_const]
congr
rw [← PowerBasis.finrank, AdjoinSimple.algebraMap_gen K x]
#align algebra.norm_eq_norm_adjoin Algebra.norm_eq_norm_adjoin
variable {K}
section IntermediateField
theorem _root_.IntermediateField.AdjoinSimple.norm_gen_eq_one {x : L} (hx : ¬IsIntegral K x) :
norm K (AdjoinSimple.gen K x) = 1 := by
rw [norm_eq_one_of_not_exists_basis]
contrapose! hx
obtain ⟨s, ⟨b⟩⟩ := hx
refine .of_mem_of_fg K⟮x⟯.toSubalgebra ?_ x ?_
· exact (Submodule.fg_iff_finiteDimensional _).mpr (of_fintype_basis b)
· exact IntermediateField.subset_adjoin K _ (Set.mem_singleton x)
#align intermediate_field.adjoin_simple.norm_gen_eq_one IntermediateField.AdjoinSimple.norm_gen_eq_one
theorem _root_.IntermediateField.AdjoinSimple.norm_gen_eq_prod_roots (x : L)
(hf : (minpoly K x).Splits (algebraMap K F)) :
(algebraMap K F) (norm K (AdjoinSimple.gen K x)) =
((minpoly K x).aroots F).prod := by
have injKxL := (algebraMap K⟮x⟯ L).injective
by_cases hx : IsIntegral K x; swap
· simp [minpoly.eq_zero hx, IntermediateField.AdjoinSimple.norm_gen_eq_one hx, aroots_def]
rw [← adjoin.powerBasis_gen hx, PowerBasis.norm_gen_eq_prod_roots] <;>
rw [adjoin.powerBasis_gen hx, ← minpoly.algebraMap_eq injKxL] <;>
try simp only [AdjoinSimple.algebraMap_gen _ _]
exact hf
#align intermediate_field.adjoin_simple.norm_gen_eq_prod_roots IntermediateField.AdjoinSimple.norm_gen_eq_prod_roots
end IntermediateField
section EqProdEmbeddings
open IntermediateField IntermediateField.AdjoinSimple Polynomial
variable (F) (E : Type*) [Field E] [Algebra K E]
theorem norm_eq_prod_embeddings_gen [Algebra R F] (pb : PowerBasis R S)
(hE : (minpoly R pb.gen).Splits (algebraMap R F)) (hfx : (minpoly R pb.gen).Separable) :
algebraMap R F (norm R pb.gen) =
(@Finset.univ _ (PowerBasis.AlgHom.fintype pb)).prod fun σ => σ pb.gen := by
letI := Classical.decEq F
rw [PowerBasis.norm_gen_eq_prod_roots pb hE]
rw [@Fintype.prod_equiv (S →ₐ[R] F) _ _ (PowerBasis.AlgHom.fintype pb) _ _ pb.liftEquiv'
(fun σ => σ pb.gen) (fun x => x) ?_]
· rw [Finset.prod_mem_multiset, Finset.prod_eq_multiset_prod, Multiset.toFinset_val,
Multiset.dedup_eq_self.mpr, Multiset.map_id]
· exact nodup_roots hfx.map
· intro x; rfl
· intro σ; simp only [PowerBasis.liftEquiv'_apply_coe]
#align algebra.norm_eq_prod_embeddings_gen Algebra.norm_eq_prod_embeddings_gen
theorem norm_eq_prod_roots [IsSeparable K L] [FiniteDimensional K L] {x : L}
(hF : (minpoly K x).Splits (algebraMap K F)) :
algebraMap K F (norm K x) =
((minpoly K x).aroots F).prod ^ finrank K⟮x⟯ L := by
rw [norm_eq_norm_adjoin K x, map_pow, IntermediateField.AdjoinSimple.norm_gen_eq_prod_roots _ hF]
#align algebra.norm_eq_prod_roots Algebra.norm_eq_prod_roots
theorem prod_embeddings_eq_finrank_pow [Algebra L F] [IsScalarTower K L F] [IsAlgClosed E]
[IsSeparable K F] [FiniteDimensional K F] (pb : PowerBasis K L) :
∏ σ : F →ₐ[K] E, σ (algebraMap L F pb.gen) =
((@Finset.univ _ (PowerBasis.AlgHom.fintype pb)).prod
fun σ : L →ₐ[K] E => σ pb.gen) ^ finrank L F := by
haveI : FiniteDimensional L F := FiniteDimensional.right K L F
haveI : IsSeparable L F := isSeparable_tower_top_of_isSeparable K L F
letI : Fintype (L →ₐ[K] E) := PowerBasis.AlgHom.fintype pb
rw [Fintype.prod_equiv algHomEquivSigma (fun σ : F →ₐ[K] E => _) fun σ => σ.1 pb.gen,
← Finset.univ_sigma_univ, Finset.prod_sigma, ← Finset.prod_pow]
· refine Finset.prod_congr rfl fun σ _ => ?_
letI : Algebra L E := σ.toRingHom.toAlgebra
simp_rw [Finset.prod_const]
congr
exact AlgHom.card L F E
· intro σ
simp only [algHomEquivSigma, Equiv.coe_fn_mk, AlgHom.restrictDomain, AlgHom.comp_apply,
IsScalarTower.coe_toAlgHom']
#align algebra.prod_embeddings_eq_finrank_pow Algebra.prod_embeddings_eq_finrank_pow
variable (K)
/-- For `L/K` a finite separable extension of fields and `E` an algebraically closed extension
of `K`, the norm (down to `K`) of an element `x` of `L` is equal to the product of the images
of `x` over all the `K`-embeddings `σ` of `L` into `E`. -/
theorem norm_eq_prod_embeddings [FiniteDimensional K L] [IsSeparable K L] [IsAlgClosed E] (x : L) :
algebraMap K E (norm K x) = ∏ σ : L →ₐ[K] E, σ x := by
have hx := IsSeparable.isIntegral K x
rw [norm_eq_norm_adjoin K x, RingHom.map_pow, ← adjoin.powerBasis_gen hx,
norm_eq_prod_embeddings_gen E (adjoin.powerBasis hx) (IsAlgClosed.splits_codomain _)]
· exact (prod_embeddings_eq_finrank_pow L (L := K⟮x⟯) E (adjoin.powerBasis hx)).symm
· haveI := isSeparable_tower_bot_of_isSeparable K K⟮x⟯ L
exact IsSeparable.separable K _
#align algebra.norm_eq_prod_embeddings Algebra.norm_eq_prod_embeddings
| Mathlib/RingTheory/Norm.lean | 302 | 310 | theorem norm_eq_prod_automorphisms [FiniteDimensional K L] [IsGalois K L] (x : L) :
algebraMap K L (norm K x) = ∏ σ : L ≃ₐ[K] L, σ x := by |
apply NoZeroSMulDivisors.algebraMap_injective L (AlgebraicClosure L)
rw [map_prod (algebraMap L (AlgebraicClosure L))]
rw [← Fintype.prod_equiv (Normal.algHomEquivAut K (AlgebraicClosure L) L)]
· rw [← norm_eq_prod_embeddings _ _ x, ← IsScalarTower.algebraMap_apply]
· intro σ
simp only [Normal.algHomEquivAut, AlgHom.restrictNormal', Equiv.coe_fn_mk,
AlgEquiv.coe_ofBijective, AlgHom.restrictNormal_commutes, id.map_eq_id, RingHom.id_apply]
|
/-
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.Topology.Order
#align_import topology.maps from "leanprover-community/mathlib"@"d91e7f7a7f1c7e9f0e18fdb6bde4f652004c735d"
/-!
# Specific classes of maps between topological spaces
This file introduces the following properties of a map `f : X → Y` between topological spaces:
* `IsOpenMap f` means the image of an open set under `f` is open.
* `IsClosedMap f` means the image of a closed set under `f` is closed.
(Open and closed maps need not be continuous.)
* `Inducing f` means the topology on `X` is the one induced via `f` from the topology on `Y`.
These behave like embeddings except they need not be injective. Instead, points of `X` which
are identified by `f` are also inseparable in the topology on `X`.
* `Embedding f` means `f` is inducing and also injective. Equivalently, `f` identifies `X` with
a subspace of `Y`.
* `OpenEmbedding f` means `f` is an embedding with open image, so it identifies `X` with an
open subspace of `Y`. Equivalently, `f` is an embedding and an open map.
* `ClosedEmbedding f` similarly means `f` is an embedding with closed image, so it identifies
`X` with a closed subspace of `Y`. Equivalently, `f` is an embedding and a closed map.
* `QuotientMap f` is the dual condition to `Embedding f`: `f` is surjective and the topology
on `Y` is the one coinduced via `f` from the topology on `X`. Equivalently, `f` identifies
`Y` with a quotient of `X`. Quotient maps are also sometimes known as identification maps.
## References
* <https://en.wikipedia.org/wiki/Open_and_closed_maps>
* <https://en.wikipedia.org/wiki/Embedding#General_topology>
* <https://en.wikipedia.org/wiki/Quotient_space_(topology)#Quotient_map>
## Tags
open map, closed map, embedding, quotient map, identification map
-/
open Set Filter Function
open TopologicalSpace Topology Filter
variable {X : Type*} {Y : Type*} {Z : Type*} {ι : Type*} {f : X → Y} {g : Y → Z}
section Inducing
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z]
theorem inducing_induced (f : X → Y) : @Inducing X Y (TopologicalSpace.induced f ‹_›) _ f :=
@Inducing.mk _ _ (TopologicalSpace.induced f ‹_›) _ _ rfl
theorem inducing_id : Inducing (@id X) :=
⟨induced_id.symm⟩
#align inducing_id inducing_id
protected theorem Inducing.comp (hg : Inducing g) (hf : Inducing f) :
Inducing (g ∘ f) :=
⟨by rw [hf.induced, hg.induced, induced_compose]⟩
#align inducing.comp Inducing.comp
theorem Inducing.of_comp_iff (hg : Inducing g) :
Inducing (g ∘ f) ↔ Inducing f := by
refine ⟨fun h ↦ ?_, hg.comp⟩
rw [inducing_iff, hg.induced, induced_compose, h.induced]
#align inducing.inducing_iff Inducing.of_comp_iff
theorem inducing_of_inducing_compose
(hf : Continuous f) (hg : Continuous g) (hgf : Inducing (g ∘ f)) : Inducing f :=
⟨le_antisymm (by rwa [← continuous_iff_le_induced])
(by
rw [hgf.induced, ← induced_compose]
exact induced_mono hg.le_induced)⟩
#align inducing_of_inducing_compose inducing_of_inducing_compose
theorem inducing_iff_nhds : Inducing f ↔ ∀ x, 𝓝 x = comap f (𝓝 (f x)) :=
(inducing_iff _).trans (induced_iff_nhds_eq f)
#align inducing_iff_nhds inducing_iff_nhds
namespace Inducing
theorem nhds_eq_comap (hf : Inducing f) : ∀ x : X, 𝓝 x = comap f (𝓝 <| f x) :=
inducing_iff_nhds.1 hf
#align inducing.nhds_eq_comap Inducing.nhds_eq_comap
theorem basis_nhds {p : ι → Prop} {s : ι → Set Y} (hf : Inducing f) {x : X}
(h_basis : (𝓝 (f x)).HasBasis p s) : (𝓝 x).HasBasis p (preimage f ∘ s) :=
hf.nhds_eq_comap x ▸ h_basis.comap f
theorem nhdsSet_eq_comap (hf : Inducing f) (s : Set X) :
𝓝ˢ s = comap f (𝓝ˢ (f '' s)) := by
simp only [nhdsSet, sSup_image, comap_iSup, hf.nhds_eq_comap, iSup_image]
#align inducing.nhds_set_eq_comap Inducing.nhdsSet_eq_comap
theorem map_nhds_eq (hf : Inducing f) (x : X) : (𝓝 x).map f = 𝓝[range f] f x :=
hf.induced.symm ▸ map_nhds_induced_eq x
#align inducing.map_nhds_eq Inducing.map_nhds_eq
theorem map_nhds_of_mem (hf : Inducing f) (x : X) (h : range f ∈ 𝓝 (f x)) :
(𝓝 x).map f = 𝓝 (f x) :=
hf.induced.symm ▸ map_nhds_induced_of_mem h
#align inducing.map_nhds_of_mem Inducing.map_nhds_of_mem
-- Porting note (#10756): new lemma
theorem mapClusterPt_iff (hf : Inducing f) {x : X} {l : Filter X} :
MapClusterPt (f x) l f ↔ ClusterPt x l := by
delta MapClusterPt ClusterPt
rw [← Filter.push_pull', ← hf.nhds_eq_comap, map_neBot_iff]
theorem image_mem_nhdsWithin (hf : Inducing f) {x : X} {s : Set X} (hs : s ∈ 𝓝 x) :
f '' s ∈ 𝓝[range f] f x :=
hf.map_nhds_eq x ▸ image_mem_map hs
#align inducing.image_mem_nhds_within Inducing.image_mem_nhdsWithin
theorem tendsto_nhds_iff {f : ι → Y} {l : Filter ι} {y : Y} (hg : Inducing g) :
Tendsto f l (𝓝 y) ↔ Tendsto (g ∘ f) l (𝓝 (g y)) := by
rw [hg.nhds_eq_comap, tendsto_comap_iff]
#align inducing.tendsto_nhds_iff Inducing.tendsto_nhds_iff
theorem continuousAt_iff (hg : Inducing g) {x : X} :
ContinuousAt f x ↔ ContinuousAt (g ∘ f) x :=
hg.tendsto_nhds_iff
#align inducing.continuous_at_iff Inducing.continuousAt_iff
| Mathlib/Topology/Maps.lean | 132 | 134 | theorem continuous_iff (hg : Inducing g) :
Continuous f ↔ Continuous (g ∘ f) := by |
simp_rw [continuous_iff_continuousAt, hg.continuousAt_iff]
|
/-
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.MonoidAlgebra.Basic
import Mathlib.LinearAlgebra.Basis.VectorSpace
import Mathlib.RingTheory.SimpleModule
#align_import representation_theory.maschke from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Maschke's theorem
We prove **Maschke's theorem** for finite groups,
in the formulation that every submodule of a `k[G]` module has a complement,
when `k` is a field with `Invertible (Fintype.card G : k)`.
We do the core computation in greater generality.
For any `[CommRing k]` in which `[Invertible (Fintype.card G : k)]`,
and a `k[G]`-linear map `i : V → W` which admits a `k`-linear retraction `π`,
we produce a `k[G]`-linear retraction by
taking the average over `G` of the conjugates of `π`.
## Implementation Notes
* These results assume `Invertible (Fintype.card G : k)` which is equivalent to the more
familiar `¬(ringChar k ∣ Fintype.card G)`. It is possible to convert between them using
`invertibleOfRingCharNotDvd` and `not_ringChar_dvd_of_invertible`.
## Future work
It's not so far to give the usual statement, that every finite dimensional representation
of a finite group is semisimple (i.e. a direct sum of irreducibles).
-/
universe u v w
noncomputable section
open Module MonoidAlgebra
/-!
We now do the key calculation in Maschke's theorem.
Given `V → W`, an inclusion of `k[G]` modules,
assume we have some retraction `π` (i.e. `∀ v, π (i v) = v`),
just as a `k`-linear map.
(When `k` is a field, this will be available cheaply, by choosing a basis.)
We now construct a retraction of the inclusion as a `k[G]`-linear map,
by the formula
$$ \frac{1}{|G|} \sum_{g \in G} g⁻¹ • π(g • -). $$
-/
namespace LinearMap
-- At first we work with any `[CommRing k]`, and add the assumption that
-- `[Invertible (Fintype.card G : k)]` when it is required.
variable {k : Type u} [CommRing k] {G : Type u} [Group G]
variable {V : Type v} [AddCommGroup V] [Module k V] [Module (MonoidAlgebra k G) V]
variable [IsScalarTower k (MonoidAlgebra k G) V]
variable {W : Type w} [AddCommGroup W] [Module k W] [Module (MonoidAlgebra k G) W]
variable [IsScalarTower k (MonoidAlgebra k G) W]
variable (π : W →ₗ[k] V)
/-- We define the conjugate of `π` by `g`, as a `k`-linear map. -/
def conjugate (g : G) : W →ₗ[k] V :=
.comp (.comp (GroupSMul.linearMap k V g⁻¹) π) (GroupSMul.linearMap k W g)
#align linear_map.conjugate LinearMap.conjugate
theorem conjugate_apply (g : G) (v : W) :
π.conjugate g v = MonoidAlgebra.single g⁻¹ (1 : k) • π (MonoidAlgebra.single g (1 : k) • v) :=
rfl
variable (i : V →ₗ[MonoidAlgebra k G] W) (h : ∀ v : V, (π : W → V) (i v) = v)
section
theorem conjugate_i (g : G) (v : V) : (conjugate π g : W → V) (i v) = v := by
rw [conjugate_apply, ← i.map_smul, h, ← mul_smul, single_mul_single, mul_one, mul_left_inv,
← one_def, one_smul]
#align linear_map.conjugate_i LinearMap.conjugate_i
end
variable (G) [Fintype G]
/-- The sum of the conjugates of `π` by each element `g : G`, as a `k`-linear map.
(We postpone dividing by the size of the group as long as possible.)
-/
def sumOfConjugates : W →ₗ[k] V :=
∑ g : G, π.conjugate g
#align linear_map.sum_of_conjugates LinearMap.sumOfConjugates
lemma sumOfConjugates_apply (v : W) : π.sumOfConjugates G v = ∑ g : G, π.conjugate g v :=
LinearMap.sum_apply _ _ _
/-- In fact, the sum over `g : G` of the conjugate of `π` by `g` is a `k[G]`-linear map.
-/
def sumOfConjugatesEquivariant : W →ₗ[MonoidAlgebra k G] V :=
MonoidAlgebra.equivariantOfLinearOfComm (π.sumOfConjugates G) fun g v => by
simp only [sumOfConjugates_apply, Finset.smul_sum, conjugate_apply]
refine Fintype.sum_bijective (· * g) (Group.mulRight_bijective g) _ _ fun i ↦ ?_
simp only [smul_smul, single_mul_single, mul_inv_rev, mul_inv_cancel_left, one_mul]
#align linear_map.sum_of_conjugates_equivariant LinearMap.sumOfConjugatesEquivariant
theorem sumOfConjugatesEquivariant_apply (v : W) :
π.sumOfConjugatesEquivariant G v = ∑ g : G, π.conjugate g v :=
π.sumOfConjugates_apply G v
section
variable [Invertible (Fintype.card G : k)]
/-- We construct our `k[G]`-linear retraction of `i` as
$$ \frac{1}{|G|} \sum_{g \in G} g⁻¹ • π(g • -). $$
-/
def equivariantProjection : W →ₗ[MonoidAlgebra k G] V :=
⅟(Fintype.card G : k) • π.sumOfConjugatesEquivariant G
#align linear_map.equivariant_projection LinearMap.equivariantProjection
theorem equivariantProjection_apply (v : W) :
π.equivariantProjection G v = ⅟(Fintype.card G : k) • ∑ g : G, π.conjugate g v := by
simp only [equivariantProjection, smul_apply, sumOfConjugatesEquivariant_apply]
theorem equivariantProjection_condition (v : V) : (π.equivariantProjection G) (i v) = v := by
rw [equivariantProjection_apply]
simp only [conjugate_i π i h]
rw [Finset.sum_const, Finset.card_univ, nsmul_eq_smul_cast k, smul_smul,
Invertible.invOf_mul_self, one_smul]
#align linear_map.equivariant_projection_condition LinearMap.equivariantProjection_condition
end
end LinearMap
end
namespace MonoidAlgebra
-- Now we work over a `[Field k]`.
variable {k : Type u} [Field k] {G : Type u} [Fintype G] [Invertible (Fintype.card G : k)]
variable [Group G]
variable {V : Type u} [AddCommGroup V] [Module (MonoidAlgebra k G) V]
variable {W : Type u} [AddCommGroup W] [Module (MonoidAlgebra k G) W]
| Mathlib/RepresentationTheory/Maschke.lean | 150 | 161 | theorem exists_leftInverse_of_injective (f : V →ₗ[MonoidAlgebra k G] W)
(hf : LinearMap.ker f = ⊥) :
∃ g : W →ₗ[MonoidAlgebra k G] V, g.comp f = LinearMap.id := by |
let A := MonoidAlgebra k G
letI : Module k W := .compHom W (algebraMap k A)
letI : Module k V := .compHom V (algebraMap k A)
have := IsScalarTower.of_compHom k A W
have := IsScalarTower.of_compHom k A V
obtain ⟨φ, hφ⟩ := (f.restrictScalars k).exists_leftInverse_of_injective <| by
simp only [hf, Submodule.restrictScalars_bot, LinearMap.ker_restrictScalars]
refine ⟨φ.equivariantProjection G, DFunLike.ext _ _ ?_⟩
exact φ.equivariantProjection_condition G _ <| DFunLike.congr_fun hφ
|
/-
Copyright (c) 2024 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Alex J. Best
-/
import Mathlib.Algebra.Polynomial.Roots
import Mathlib.Tactic.IntervalCases
/-!
# Polynomials of specific degree
Facts about polynomials that have a specific integer degree.
-/
namespace Polynomial
section IsDomain
variable {R : Type*} [CommRing R] [IsDomain R]
/-- A polynomial of degree 2 or 3 is irreducible iff it doesn't have roots. -/
| Mathlib/Algebra/Polynomial/SpecificDegree.lean | 22 | 34 | theorem Monic.irreducible_iff_roots_eq_zero_of_degree_le_three {p : R[X]} (hp : p.Monic)
(hp2 : 2 ≤ p.natDegree) (hp3 : p.natDegree ≤ 3) : Irreducible p ↔ p.roots = 0 := by |
have hp0 : p ≠ 0 := hp.ne_zero
have hp1 : p ≠ 1 := by rintro rfl; rw [natDegree_one] at hp2; cases hp2
rw [hp.irreducible_iff_lt_natDegree_lt hp1]
simp_rw [show p.natDegree / 2 = 1 from
(Nat.div_le_div_right hp3).antisymm
(by apply Nat.div_le_div_right (c := 2) hp2),
show Finset.Ioc 0 1 = {1} from rfl,
Finset.mem_singleton, Multiset.eq_zero_iff_forall_not_mem, mem_roots hp0, ← dvd_iff_isRoot]
refine ⟨fun h r ↦ h _ (monic_X_sub_C r) (natDegree_X_sub_C r), fun h q hq hq1 ↦ ?_⟩
rw [hq.eq_X_add_C hq1, ← sub_neg_eq_add, ← C_neg]
apply h
|
/-
Copyright (c) 2022 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Scott Morrison, Joël Riou
-/
import Mathlib.CategoryTheory.Preadditive.Injective
import Mathlib.Algebra.Homology.ShortComplex.HomologicalComplex
import Mathlib.Algebra.Homology.QuasiIso
#align_import category_theory.preadditive.injective_resolution from "leanprover-community/mathlib"@"14b69e9f3c16630440a2cbd46f1ddad0d561dee7"
/-!
# Injective resolutions
An injective resolution `I : InjectiveResolution Z` of an object `Z : C` consists of
an `ℕ`-indexed cochain complex `I.cocomplex` of injective objects,
along with a quasi-isomorphism `I.ι` from the cochain complex consisting just of `Z`
in degree zero to `I.cocomplex`.
```
Z ----> 0 ----> ... ----> 0 ----> ...
| | |
| | |
v v v
I⁰ ---> I¹ ---> ... ----> Iⁿ ---> ...
```
-/
noncomputable section
universe v u
namespace CategoryTheory
open Limits HomologicalComplex CochainComplex
variable {C : Type u} [Category.{v} C] [HasZeroObject C] [HasZeroMorphisms C]
/--
An `InjectiveResolution Z` consists of a bundled `ℕ`-indexed cochain complex of injective objects,
along with a quasi-isomorphism from the complex consisting of just `Z` supported in degree `0`.
-/
-- Porting note(#5171): this linter isn't ported yet.
-- @[nolint has_nonempty_instance]
structure InjectiveResolution (Z : C) where
/-- the cochain complex involved in the resolution -/
cocomplex : CochainComplex C ℕ
/-- the cochain complex must be degreewise injective -/
injective : ∀ n, Injective (cocomplex.X n) := by infer_instance
/-- the cochain complex must have homology -/
[hasHomology : ∀ i, cocomplex.HasHomology i]
/-- the morphism from the single cochain complex with `Z` in degree `0` -/
ι : (single₀ C).obj Z ⟶ cocomplex
/-- the morphism from the single cochain complex with `Z` in degree `0` is a quasi-isomorphism -/
quasiIso : QuasiIso ι := by infer_instance
set_option linter.uppercaseLean3 false in
#align category_theory.InjectiveResolution CategoryTheory.InjectiveResolution
open InjectiveResolution in
attribute [instance] injective hasHomology InjectiveResolution.quasiIso
/-- An object admits an injective resolution. -/
class HasInjectiveResolution (Z : C) : Prop where
out : Nonempty (InjectiveResolution Z)
#align category_theory.has_injective_resolution CategoryTheory.HasInjectiveResolution
attribute [inherit_doc HasInjectiveResolution] HasInjectiveResolution.out
section
variable (C)
/-- You will rarely use this typeclass directly: it is implied by the combination
`[EnoughInjectives C]` and `[Abelian C]`. -/
class HasInjectiveResolutions : Prop where
out : ∀ Z : C, HasInjectiveResolution Z
#align category_theory.has_injective_resolutions CategoryTheory.HasInjectiveResolutions
attribute [instance 100] HasInjectiveResolutions.out
end
namespace InjectiveResolution
variable {Z : C} (I : InjectiveResolution Z)
lemma cocomplex_exactAt_succ (n : ℕ) :
I.cocomplex.ExactAt (n + 1) := by
rw [← quasiIsoAt_iff_exactAt I.ι (n + 1) (exactAt_succ_single_obj _ _)]
infer_instance
lemma exact_succ (n : ℕ):
(ShortComplex.mk _ _ (I.cocomplex.d_comp_d n (n + 1) (n + 2))).Exact :=
(HomologicalComplex.exactAt_iff' _ n (n + 1) (n + 2) (by simp)
(by simp only [CochainComplex.next]; rfl)).1 (I.cocomplex_exactAt_succ n)
@[simp]
theorem ι_f_succ (n : ℕ) : I.ι.f (n + 1) = 0 :=
(isZero_single_obj_X _ _ _ _ (by simp)).eq_of_src _ _
set_option linter.uppercaseLean3 false in
#align category_theory.InjectiveResolution.ι_f_succ CategoryTheory.InjectiveResolution.ι_f_succ
-- Porting note (#10618): removed @[simp] simp can prove this
@[reassoc]
theorem ι_f_zero_comp_complex_d :
I.ι.f 0 ≫ I.cocomplex.d 0 1 = 0 := by
simp
set_option linter.uppercaseLean3 false in
#align category_theory.InjectiveResolution.ι_f_zero_comp_complex_d CategoryTheory.InjectiveResolution.ι_f_zero_comp_complex_d
-- Porting note (#10618): removed @[simp] simp can prove this
| Mathlib/CategoryTheory/Preadditive/InjectiveResolution.lean | 111 | 113 | theorem complex_d_comp (n : ℕ) :
I.cocomplex.d n (n + 1) ≫ I.cocomplex.d (n + 1) (n + 2) = 0 := by |
simp
|
/-
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.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Matrix.GeneralLinearGroup
import Mathlib.LinearAlgebra.Matrix.Nondegenerate
import Mathlib.LinearAlgebra.Matrix.NonsingularInverse
import Mathlib.LinearAlgebra.Matrix.ToLin
import Mathlib.RingTheory.Localization.FractionRing
import Mathlib.RingTheory.Localization.Integer
#align_import linear_algebra.matrix.to_linear_equiv from "leanprover-community/mathlib"@"e42cfdb03b7902f8787a1eb552cb8f77766b45b9"
/-!
# Matrices and linear equivalences
This file gives the map `Matrix.toLinearEquiv` from matrices with invertible determinant,
to linear equivs.
## Main definitions
* `Matrix.toLinearEquiv`: a matrix with an invertible determinant forms a linear equiv
## Main results
* `Matrix.exists_mulVec_eq_zero_iff`: `M` maps some `v ≠ 0` to zero iff `det M = 0`
## Tags
matrix, linear_equiv, determinant, inverse
-/
variable {n : Type*} [Fintype n]
namespace Matrix
section LinearEquiv
open LinearMap
variable {R M : Type*} [CommRing R] [AddCommGroup M] [Module R M]
section ToLinearEquiv'
variable [DecidableEq n]
/-- An invertible matrix yields a linear equivalence from the free module to itself.
See `Matrix.toLinearEquiv` for the same map on arbitrary modules.
-/
def toLinearEquiv' (P : Matrix n n R) (_ : Invertible P) : (n → R) ≃ₗ[R] n → R :=
GeneralLinearGroup.generalLinearEquiv _ _ <|
Matrix.GeneralLinearGroup.toLinear <| unitOfInvertible P
#align matrix.to_linear_equiv' Matrix.toLinearEquiv'
@[simp]
theorem toLinearEquiv'_apply (P : Matrix n n R) (h : Invertible P) :
(P.toLinearEquiv' h : Module.End R (n → R)) = Matrix.toLin' P :=
rfl
#align matrix.to_linear_equiv'_apply Matrix.toLinearEquiv'_apply
@[simp]
theorem toLinearEquiv'_symm_apply (P : Matrix n n R) (h : Invertible P) :
(↑(P.toLinearEquiv' h).symm : Module.End R (n → R)) = Matrix.toLin' (⅟ P) :=
rfl
#align matrix.to_linear_equiv'_symm_apply Matrix.toLinearEquiv'_symm_apply
end ToLinearEquiv'
section ToLinearEquiv
variable (b : Basis n R M)
/-- Given `hA : IsUnit A.det` and `b : Basis R b`, `A.toLinearEquiv b hA` is
the `LinearEquiv` arising from `toLin b b A`.
See `Matrix.toLinearEquiv'` for this result on `n → R`.
-/
@[simps apply]
noncomputable def toLinearEquiv [DecidableEq n] (A : Matrix n n R) (hA : IsUnit A.det) :
M ≃ₗ[R] M where
__ := toLin b b A
toFun := toLin b b A
invFun := toLin b b A⁻¹
left_inv x := by
simp_rw [← LinearMap.comp_apply, ← Matrix.toLin_mul b b b, Matrix.nonsing_inv_mul _ hA,
toLin_one, LinearMap.id_apply]
right_inv x := by
simp_rw [← LinearMap.comp_apply, ← Matrix.toLin_mul b b b, Matrix.mul_nonsing_inv _ hA,
toLin_one, LinearMap.id_apply]
#align matrix.to_linear_equiv Matrix.toLinearEquiv
theorem ker_toLin_eq_bot [DecidableEq n] (A : Matrix n n R) (hA : IsUnit A.det) :
LinearMap.ker (toLin b b A) = ⊥ :=
ker_eq_bot.mpr (toLinearEquiv b A hA).injective
#align matrix.ker_to_lin_eq_bot Matrix.ker_toLin_eq_bot
theorem range_toLin_eq_top [DecidableEq n] (A : Matrix n n R) (hA : IsUnit A.det) :
LinearMap.range (toLin b b A) = ⊤ :=
range_eq_top.mpr (toLinearEquiv b A hA).surjective
#align matrix.range_to_lin_eq_top Matrix.range_toLin_eq_top
end ToLinearEquiv
section Nondegenerate
open Matrix
/-- This holds for all integral domains (see `Matrix.exists_mulVec_eq_zero_iff`),
not just fields, but it's easier to prove it for the field of fractions first. -/
| Mathlib/LinearAlgebra/Matrix/ToLinearEquiv.lean | 114 | 132 | theorem exists_mulVec_eq_zero_iff_aux {K : Type*} [DecidableEq n] [Field K] {M : Matrix n n K} :
(∃ v ≠ 0, M *ᵥ v = 0) ↔ M.det = 0 := by |
constructor
· rintro ⟨v, hv, mul_eq⟩
contrapose! hv
exact eq_zero_of_mulVec_eq_zero hv mul_eq
· contrapose!
intro h
have : Function.Injective (Matrix.toLin' M) := by
simpa only [← LinearMap.ker_eq_bot, ker_toLin'_eq_bot_iff, not_imp_not] using h
have :
M *
LinearMap.toMatrix'
((LinearEquiv.ofInjectiveEndo (Matrix.toLin' M) this).symm : (n → K) →ₗ[K] n → K) =
1 := by
refine Matrix.toLin'.injective (LinearMap.ext fun v => ?_)
rw [Matrix.toLin'_mul, Matrix.toLin'_one, Matrix.toLin'_toMatrix', LinearMap.comp_apply]
exact (LinearEquiv.ofInjectiveEndo (Matrix.toLin' M) this).apply_symm_apply v
exact Matrix.det_ne_zero_of_right_inverse this
|
/-
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.Complex.Log
#align_import analysis.special_functions.pow.complex from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-! # Power function on `ℂ`
We construct the power functions `x ^ y`, where `x` and `y` are complex numbers.
-/
open scoped Classical
open Real Topology Filter ComplexConjugate Finset Set
namespace Complex
/-- The complex power function `x ^ y`, given by `x ^ y = exp(y log x)` (where `log` is the
principal determination of the logarithm), unless `x = 0` where one sets `0 ^ 0 = 1` and
`0 ^ y = 0` for `y ≠ 0`. -/
noncomputable def cpow (x y : ℂ) : ℂ :=
if x = 0 then if y = 0 then 1 else 0 else exp (log x * y)
#align complex.cpow Complex.cpow
noncomputable instance : Pow ℂ ℂ :=
⟨cpow⟩
@[simp]
theorem cpow_eq_pow (x y : ℂ) : cpow x y = x ^ y :=
rfl
#align complex.cpow_eq_pow Complex.cpow_eq_pow
theorem cpow_def (x y : ℂ) : x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) :=
rfl
#align complex.cpow_def Complex.cpow_def
theorem cpow_def_of_ne_zero {x : ℂ} (hx : x ≠ 0) (y : ℂ) : x ^ y = exp (log x * y) :=
if_neg hx
#align complex.cpow_def_of_ne_zero Complex.cpow_def_of_ne_zero
@[simp]
theorem cpow_zero (x : ℂ) : x ^ (0 : ℂ) = 1 := by simp [cpow_def]
#align complex.cpow_zero Complex.cpow_zero
@[simp]
theorem cpow_eq_zero_iff (x y : ℂ) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [cpow_def]
split_ifs <;> simp [*, exp_ne_zero]
#align complex.cpow_eq_zero_iff Complex.cpow_eq_zero_iff
@[simp]
theorem zero_cpow {x : ℂ} (h : x ≠ 0) : (0 : ℂ) ^ x = 0 := by simp [cpow_def, *]
#align complex.zero_cpow Complex.zero_cpow
| Mathlib/Analysis/SpecialFunctions/Pow/Complex.lean | 58 | 72 | theorem zero_cpow_eq_iff {x : ℂ} {a : ℂ} : (0 : ℂ) ^ x = a ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by |
constructor
· intro hyp
simp only [cpow_def, eq_self_iff_true, if_true] at hyp
by_cases h : x = 0
· subst h
simp only [if_true, eq_self_iff_true] at hyp
right
exact ⟨rfl, hyp.symm⟩
· rw [if_neg h] at hyp
left
exact ⟨h, hyp.symm⟩
· rintro (⟨h, rfl⟩ | ⟨rfl, rfl⟩)
· exact zero_cpow h
· exact cpow_zero _
|
/-
Copyright (c) 2022 David Kurniadi Angdinata. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Kurniadi Angdinata
-/
import Mathlib.Algebra.Polynomial.Splits
#align_import algebra.cubic_discriminant from "leanprover-community/mathlib"@"930133160e24036d5242039fe4972407cd4f1222"
/-!
# Cubics and discriminants
This file defines cubic polynomials over a semiring and their discriminants over a splitting field.
## Main definitions
* `Cubic`: the structure representing a cubic polynomial.
* `Cubic.disc`: the discriminant of a cubic polynomial.
## Main statements
* `Cubic.disc_ne_zero_iff_roots_nodup`: the cubic discriminant is not equal to zero if and only if
the cubic has no duplicate roots.
## References
* https://en.wikipedia.org/wiki/Cubic_equation
* https://en.wikipedia.org/wiki/Discriminant
## Tags
cubic, discriminant, polynomial, root
-/
noncomputable section
/-- The structure representing a cubic polynomial. -/
@[ext]
structure Cubic (R : Type*) where
(a b c d : R)
#align cubic Cubic
namespace Cubic
open Cubic Polynomial
open Polynomial
variable {R S F K : Type*}
instance [Inhabited R] : Inhabited (Cubic R) :=
⟨⟨default, default, default, default⟩⟩
instance [Zero R] : Zero (Cubic R) :=
⟨⟨0, 0, 0, 0⟩⟩
section Basic
variable {P Q : Cubic R} {a b c d a' b' c' d' : R} [Semiring R]
/-- Convert a cubic polynomial to a polynomial. -/
def toPoly (P : Cubic R) : R[X] :=
C P.a * X ^ 3 + C P.b * X ^ 2 + C P.c * X + C P.d
#align cubic.to_poly Cubic.toPoly
theorem C_mul_prod_X_sub_C_eq [CommRing S] {w x y z : S} :
C w * (X - C x) * (X - C y) * (X - C z) =
toPoly ⟨w, w * -(x + y + z), w * (x * y + x * z + y * z), w * -(x * y * z)⟩ := by
simp only [toPoly, C_neg, C_add, C_mul]
ring1
set_option linter.uppercaseLean3 false in
#align cubic.C_mul_prod_X_sub_C_eq Cubic.C_mul_prod_X_sub_C_eq
theorem prod_X_sub_C_eq [CommRing S] {x y z : S} :
(X - C x) * (X - C y) * (X - C z) =
toPoly ⟨1, -(x + y + z), x * y + x * z + y * z, -(x * y * z)⟩ := by
rw [← one_mul <| X - C x, ← C_1, C_mul_prod_X_sub_C_eq, one_mul, one_mul, one_mul]
set_option linter.uppercaseLean3 false in
#align cubic.prod_X_sub_C_eq Cubic.prod_X_sub_C_eq
/-! ### Coefficients -/
section Coeff
private theorem coeffs : (∀ n > 3, P.toPoly.coeff n = 0) ∧ P.toPoly.coeff 3 = P.a ∧
P.toPoly.coeff 2 = P.b ∧ P.toPoly.coeff 1 = P.c ∧ P.toPoly.coeff 0 = P.d := by
simp only [toPoly, coeff_add, coeff_C, coeff_C_mul_X, coeff_C_mul_X_pow]
set_option tactic.skipAssignedInstances false in norm_num
intro n hn
repeat' rw [if_neg]
any_goals linarith only [hn]
repeat' rw [zero_add]
@[simp]
theorem coeff_eq_zero {n : ℕ} (hn : 3 < n) : P.toPoly.coeff n = 0 :=
coeffs.1 n hn
#align cubic.coeff_eq_zero Cubic.coeff_eq_zero
@[simp]
theorem coeff_eq_a : P.toPoly.coeff 3 = P.a :=
coeffs.2.1
#align cubic.coeff_eq_a Cubic.coeff_eq_a
@[simp]
theorem coeff_eq_b : P.toPoly.coeff 2 = P.b :=
coeffs.2.2.1
#align cubic.coeff_eq_b Cubic.coeff_eq_b
@[simp]
theorem coeff_eq_c : P.toPoly.coeff 1 = P.c :=
coeffs.2.2.2.1
#align cubic.coeff_eq_c Cubic.coeff_eq_c
@[simp]
theorem coeff_eq_d : P.toPoly.coeff 0 = P.d :=
coeffs.2.2.2.2
#align cubic.coeff_eq_d Cubic.coeff_eq_d
theorem a_of_eq (h : P.toPoly = Q.toPoly) : P.a = Q.a := by rw [← coeff_eq_a, h, coeff_eq_a]
#align cubic.a_of_eq Cubic.a_of_eq
theorem b_of_eq (h : P.toPoly = Q.toPoly) : P.b = Q.b := by rw [← coeff_eq_b, h, coeff_eq_b]
#align cubic.b_of_eq Cubic.b_of_eq
theorem c_of_eq (h : P.toPoly = Q.toPoly) : P.c = Q.c := by rw [← coeff_eq_c, h, coeff_eq_c]
#align cubic.c_of_eq Cubic.c_of_eq
theorem d_of_eq (h : P.toPoly = Q.toPoly) : P.d = Q.d := by rw [← coeff_eq_d, h, coeff_eq_d]
#align cubic.d_of_eq Cubic.d_of_eq
theorem toPoly_injective (P Q : Cubic R) : P.toPoly = Q.toPoly ↔ P = Q :=
⟨fun h ↦ Cubic.ext P Q (a_of_eq h) (b_of_eq h) (c_of_eq h) (d_of_eq h), congr_arg toPoly⟩
#align cubic.to_poly_injective Cubic.toPoly_injective
theorem of_a_eq_zero (ha : P.a = 0) : P.toPoly = C P.b * X ^ 2 + C P.c * X + C P.d := by
rw [toPoly, ha, C_0, zero_mul, zero_add]
#align cubic.of_a_eq_zero Cubic.of_a_eq_zero
theorem of_a_eq_zero' : toPoly ⟨0, b, c, d⟩ = C b * X ^ 2 + C c * X + C d :=
of_a_eq_zero rfl
#align cubic.of_a_eq_zero' Cubic.of_a_eq_zero'
theorem of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly = C P.c * X + C P.d := by
rw [of_a_eq_zero ha, hb, C_0, zero_mul, zero_add]
#align cubic.of_b_eq_zero Cubic.of_b_eq_zero
theorem of_b_eq_zero' : toPoly ⟨0, 0, c, d⟩ = C c * X + C d :=
of_b_eq_zero rfl rfl
#align cubic.of_b_eq_zero' Cubic.of_b_eq_zero'
theorem of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) : P.toPoly = C P.d := by
rw [of_b_eq_zero ha hb, hc, C_0, zero_mul, zero_add]
#align cubic.of_c_eq_zero Cubic.of_c_eq_zero
theorem of_c_eq_zero' : toPoly ⟨0, 0, 0, d⟩ = C d :=
of_c_eq_zero rfl rfl rfl
#align cubic.of_c_eq_zero' Cubic.of_c_eq_zero'
theorem of_d_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 0) :
P.toPoly = 0 := by
rw [of_c_eq_zero ha hb hc, hd, C_0]
#align cubic.of_d_eq_zero Cubic.of_d_eq_zero
theorem of_d_eq_zero' : (⟨0, 0, 0, 0⟩ : Cubic R).toPoly = 0 :=
of_d_eq_zero rfl rfl rfl rfl
#align cubic.of_d_eq_zero' Cubic.of_d_eq_zero'
theorem zero : (0 : Cubic R).toPoly = 0 :=
of_d_eq_zero'
#align cubic.zero Cubic.zero
theorem toPoly_eq_zero_iff (P : Cubic R) : P.toPoly = 0 ↔ P = 0 := by
rw [← zero, toPoly_injective]
#align cubic.to_poly_eq_zero_iff Cubic.toPoly_eq_zero_iff
private theorem ne_zero (h0 : P.a ≠ 0 ∨ P.b ≠ 0 ∨ P.c ≠ 0 ∨ P.d ≠ 0) : P.toPoly ≠ 0 := by
contrapose! h0
rw [(toPoly_eq_zero_iff P).mp h0]
exact ⟨rfl, rfl, rfl, rfl⟩
theorem ne_zero_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp ne_zero).1 ha
#align cubic.ne_zero_of_a_ne_zero Cubic.ne_zero_of_a_ne_zero
theorem ne_zero_of_b_ne_zero (hb : P.b ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp ne_zero).2).1 hb
#align cubic.ne_zero_of_b_ne_zero Cubic.ne_zero_of_b_ne_zero
theorem ne_zero_of_c_ne_zero (hc : P.c ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp (or_imp.mp ne_zero).2).2).1 hc
#align cubic.ne_zero_of_c_ne_zero Cubic.ne_zero_of_c_ne_zero
theorem ne_zero_of_d_ne_zero (hd : P.d ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp (or_imp.mp ne_zero).2).2).2 hd
#align cubic.ne_zero_of_d_ne_zero Cubic.ne_zero_of_d_ne_zero
@[simp]
theorem leadingCoeff_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.leadingCoeff = P.a :=
leadingCoeff_cubic ha
#align cubic.leading_coeff_of_a_ne_zero Cubic.leadingCoeff_of_a_ne_zero
@[simp]
theorem leadingCoeff_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).leadingCoeff = a :=
leadingCoeff_of_a_ne_zero ha
#align cubic.leading_coeff_of_a_ne_zero' Cubic.leadingCoeff_of_a_ne_zero'
@[simp]
theorem leadingCoeff_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.leadingCoeff = P.b := by
rw [of_a_eq_zero ha, leadingCoeff_quadratic hb]
#align cubic.leading_coeff_of_b_ne_zero Cubic.leadingCoeff_of_b_ne_zero
@[simp]
theorem leadingCoeff_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).leadingCoeff = b :=
leadingCoeff_of_b_ne_zero rfl hb
#align cubic.leading_coeff_of_b_ne_zero' Cubic.leadingCoeff_of_b_ne_zero'
@[simp]
theorem leadingCoeff_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) :
P.toPoly.leadingCoeff = P.c := by
rw [of_b_eq_zero ha hb, leadingCoeff_linear hc]
#align cubic.leading_coeff_of_c_ne_zero Cubic.leadingCoeff_of_c_ne_zero
@[simp]
theorem leadingCoeff_of_c_ne_zero' (hc : c ≠ 0) : (toPoly ⟨0, 0, c, d⟩).leadingCoeff = c :=
leadingCoeff_of_c_ne_zero rfl rfl hc
#align cubic.leading_coeff_of_c_ne_zero' Cubic.leadingCoeff_of_c_ne_zero'
@[simp]
theorem leadingCoeff_of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) :
P.toPoly.leadingCoeff = P.d := by
rw [of_c_eq_zero ha hb hc, leadingCoeff_C]
#align cubic.leading_coeff_of_c_eq_zero Cubic.leadingCoeff_of_c_eq_zero
-- @[simp] -- porting note (#10618): simp can prove this
theorem leadingCoeff_of_c_eq_zero' : (toPoly ⟨0, 0, 0, d⟩).leadingCoeff = d :=
leadingCoeff_of_c_eq_zero rfl rfl rfl
#align cubic.leading_coeff_of_c_eq_zero' Cubic.leadingCoeff_of_c_eq_zero'
theorem monic_of_a_eq_one (ha : P.a = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_a_ne_zero (ha ▸ one_ne_zero), ha]
#align cubic.monic_of_a_eq_one Cubic.monic_of_a_eq_one
theorem monic_of_a_eq_one' : (toPoly ⟨1, b, c, d⟩).Monic :=
monic_of_a_eq_one rfl
#align cubic.monic_of_a_eq_one' Cubic.monic_of_a_eq_one'
theorem monic_of_b_eq_one (ha : P.a = 0) (hb : P.b = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_b_ne_zero ha (hb ▸ one_ne_zero), hb]
#align cubic.monic_of_b_eq_one Cubic.monic_of_b_eq_one
theorem monic_of_b_eq_one' : (toPoly ⟨0, 1, c, d⟩).Monic :=
monic_of_b_eq_one rfl rfl
#align cubic.monic_of_b_eq_one' Cubic.monic_of_b_eq_one'
theorem monic_of_c_eq_one (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_c_ne_zero ha hb (hc ▸ one_ne_zero), hc]
#align cubic.monic_of_c_eq_one Cubic.monic_of_c_eq_one
theorem monic_of_c_eq_one' : (toPoly ⟨0, 0, 1, d⟩).Monic :=
monic_of_c_eq_one rfl rfl rfl
#align cubic.monic_of_c_eq_one' Cubic.monic_of_c_eq_one'
theorem monic_of_d_eq_one (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 1) :
P.toPoly.Monic := by
rw [Monic, leadingCoeff_of_c_eq_zero ha hb hc, hd]
#align cubic.monic_of_d_eq_one Cubic.monic_of_d_eq_one
theorem monic_of_d_eq_one' : (toPoly ⟨0, 0, 0, 1⟩).Monic :=
monic_of_d_eq_one rfl rfl rfl rfl
#align cubic.monic_of_d_eq_one' Cubic.monic_of_d_eq_one'
end Coeff
/-! ### Degrees -/
section Degree
/-- The equivalence between cubic polynomials and polynomials of degree at most three. -/
@[simps]
def equiv : Cubic R ≃ { p : R[X] // p.degree ≤ 3 } where
toFun P := ⟨P.toPoly, degree_cubic_le⟩
invFun f := ⟨coeff f 3, coeff f 2, coeff f 1, coeff f 0⟩
left_inv P := by ext <;> simp only [Subtype.coe_mk, coeffs]
right_inv f := by
-- Porting note: Added `simp only [Nat.zero_eq, Nat.succ_eq_add_one] <;> ring_nf`
-- There's probably a better way to do this.
ext (_ | _ | _ | _ | n) <;> simp only [Nat.zero_eq, Nat.succ_eq_add_one] <;> ring_nf
<;> try simp only [coeffs]
have h3 : 3 < 4 + n := by linarith only
rw [coeff_eq_zero h3,
(degree_le_iff_coeff_zero (f : R[X]) 3).mp f.2 _ <| WithBot.coe_lt_coe.mpr (by exact h3)]
#align cubic.equiv Cubic.equiv
@[simp]
theorem degree_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.degree = 3 :=
degree_cubic ha
#align cubic.degree_of_a_ne_zero Cubic.degree_of_a_ne_zero
@[simp]
theorem degree_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).degree = 3 :=
degree_of_a_ne_zero ha
#align cubic.degree_of_a_ne_zero' Cubic.degree_of_a_ne_zero'
theorem degree_of_a_eq_zero (ha : P.a = 0) : P.toPoly.degree ≤ 2 := by
simpa only [of_a_eq_zero ha] using degree_quadratic_le
#align cubic.degree_of_a_eq_zero Cubic.degree_of_a_eq_zero
theorem degree_of_a_eq_zero' : (toPoly ⟨0, b, c, d⟩).degree ≤ 2 :=
degree_of_a_eq_zero rfl
#align cubic.degree_of_a_eq_zero' Cubic.degree_of_a_eq_zero'
@[simp]
theorem degree_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.degree = 2 := by
rw [of_a_eq_zero ha, degree_quadratic hb]
#align cubic.degree_of_b_ne_zero Cubic.degree_of_b_ne_zero
@[simp]
theorem degree_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).degree = 2 :=
degree_of_b_ne_zero rfl hb
#align cubic.degree_of_b_ne_zero' Cubic.degree_of_b_ne_zero'
theorem degree_of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly.degree ≤ 1 := by
simpa only [of_b_eq_zero ha hb] using degree_linear_le
#align cubic.degree_of_b_eq_zero Cubic.degree_of_b_eq_zero
theorem degree_of_b_eq_zero' : (toPoly ⟨0, 0, c, d⟩).degree ≤ 1 :=
degree_of_b_eq_zero rfl rfl
#align cubic.degree_of_b_eq_zero' Cubic.degree_of_b_eq_zero'
@[simp]
| Mathlib/Algebra/CubicDiscriminant.lean | 337 | 338 | theorem degree_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) : P.toPoly.degree = 1 := by |
rw [of_b_eq_zero ha hb, degree_linear hc]
|
/-
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.Asymptotics.AsymptoticEquivalent
import Mathlib.Analysis.Normed.Group.Lemmas
import Mathlib.Analysis.NormedSpace.AddTorsor
import Mathlib.Analysis.NormedSpace.AffineIsometry
import Mathlib.Analysis.NormedSpace.OperatorNorm.NormedSpace
import Mathlib.Analysis.NormedSpace.RieszLemma
import Mathlib.Analysis.NormedSpace.Pointwise
import Mathlib.Topology.Algebra.Module.FiniteDimension
import Mathlib.Topology.Algebra.InfiniteSum.Module
import Mathlib.Topology.Instances.Matrix
#align_import analysis.normed_space.finite_dimension from "leanprover-community/mathlib"@"9425b6f8220e53b059f5a4904786c3c4b50fc057"
/-!
# Finite dimensional normed spaces over complete fields
Over a complete nontrivially normed field, in finite dimension, all norms are equivalent and all
linear maps are continuous. Moreover, a finite-dimensional subspace is always complete and closed.
## Main results:
* `FiniteDimensional.complete` : a finite-dimensional space over a complete field is complete. This
is not registered as an instance, as the field would be an unknown metavariable in typeclass
resolution.
* `Submodule.closed_of_finiteDimensional` : a finite-dimensional subspace over a complete field is
closed
* `FiniteDimensional.proper` : a finite-dimensional space over a proper field is proper. This
is not registered as an instance, as the field would be an unknown metavariable in typeclass
resolution. It is however registered as an instance for `𝕜 = ℝ` and `𝕜 = ℂ`. As properness
implies completeness, there is no need to also register `FiniteDimensional.complete` on `ℝ` or
`ℂ`.
* `FiniteDimensional.of_isCompact_closedBall`: Riesz' theorem: if the closed unit ball is
compact, then the space is finite-dimensional.
## Implementation notes
The fact that all norms are equivalent is not written explicitly, as it would mean having two norms
on a single space, which is not the way type classes work. However, if one has a
finite-dimensional vector space `E` with a norm, and a copy `E'` of this type with another norm,
then the identities from `E` to `E'` and from `E'`to `E` are continuous thanks to
`LinearMap.continuous_of_finiteDimensional`. This gives the desired norm equivalence.
-/
universe u v w x
noncomputable section
open Set FiniteDimensional TopologicalSpace Filter Asymptotics Classical Topology
NNReal Metric
namespace LinearIsometry
open LinearMap
variable {R : Type*} [Semiring R]
variable {F E₁ : Type*} [SeminormedAddCommGroup F] [NormedAddCommGroup E₁] [Module R E₁]
variable {R₁ : Type*} [Field R₁] [Module R₁ E₁] [Module R₁ F] [FiniteDimensional R₁ E₁]
[FiniteDimensional R₁ F]
/-- A linear isometry between finite dimensional spaces of equal dimension can be upgraded
to a linear isometry equivalence. -/
def toLinearIsometryEquiv (li : E₁ →ₗᵢ[R₁] F) (h : finrank R₁ E₁ = finrank R₁ F) :
E₁ ≃ₗᵢ[R₁] F where
toLinearEquiv := li.toLinearMap.linearEquivOfInjective li.injective h
norm_map' := li.norm_map'
#align linear_isometry.to_linear_isometry_equiv LinearIsometry.toLinearIsometryEquiv
@[simp]
theorem coe_toLinearIsometryEquiv (li : E₁ →ₗᵢ[R₁] F) (h : finrank R₁ E₁ = finrank R₁ F) :
(li.toLinearIsometryEquiv h : E₁ → F) = li :=
rfl
#align linear_isometry.coe_to_linear_isometry_equiv LinearIsometry.coe_toLinearIsometryEquiv
@[simp]
theorem toLinearIsometryEquiv_apply (li : E₁ →ₗᵢ[R₁] F) (h : finrank R₁ E₁ = finrank R₁ F)
(x : E₁) : (li.toLinearIsometryEquiv h) x = li x :=
rfl
#align linear_isometry.to_linear_isometry_equiv_apply LinearIsometry.toLinearIsometryEquiv_apply
end LinearIsometry
namespace AffineIsometry
open AffineMap
variable {𝕜 : Type*} {V₁ V₂ : Type*} {P₁ P₂ : Type*} [NormedField 𝕜] [NormedAddCommGroup V₁]
[SeminormedAddCommGroup V₂] [NormedSpace 𝕜 V₁] [NormedSpace 𝕜 V₂] [MetricSpace P₁]
[PseudoMetricSpace P₂] [NormedAddTorsor V₁ P₁] [NormedAddTorsor V₂ P₂]
variable [FiniteDimensional 𝕜 V₁] [FiniteDimensional 𝕜 V₂]
/-- An affine isometry between finite dimensional spaces of equal dimension can be upgraded
to an affine isometry equivalence. -/
def toAffineIsometryEquiv [Inhabited P₁] (li : P₁ →ᵃⁱ[𝕜] P₂) (h : finrank 𝕜 V₁ = finrank 𝕜 V₂) :
P₁ ≃ᵃⁱ[𝕜] P₂ :=
AffineIsometryEquiv.mk' li (li.linearIsometry.toLinearIsometryEquiv h)
(Inhabited.default (α := P₁)) fun p => by simp
#align affine_isometry.to_affine_isometry_equiv AffineIsometry.toAffineIsometryEquiv
@[simp]
theorem coe_toAffineIsometryEquiv [Inhabited P₁] (li : P₁ →ᵃⁱ[𝕜] P₂)
(h : finrank 𝕜 V₁ = finrank 𝕜 V₂) : (li.toAffineIsometryEquiv h : P₁ → P₂) = li :=
rfl
#align affine_isometry.coe_to_affine_isometry_equiv AffineIsometry.coe_toAffineIsometryEquiv
@[simp]
theorem toAffineIsometryEquiv_apply [Inhabited P₁] (li : P₁ →ᵃⁱ[𝕜] P₂)
(h : finrank 𝕜 V₁ = finrank 𝕜 V₂) (x : P₁) : (li.toAffineIsometryEquiv h) x = li x :=
rfl
#align affine_isometry.to_affine_isometry_equiv_apply AffineIsometry.toAffineIsometryEquiv_apply
end AffineIsometry
section CompleteField
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type v} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {F : Type w} [NormedAddCommGroup F] [NormedSpace 𝕜 F] {F' : Type x}
[AddCommGroup F'] [Module 𝕜 F'] [TopologicalSpace F'] [TopologicalAddGroup F']
[ContinuousSMul 𝕜 F'] [CompleteSpace 𝕜]
section Affine
variable {PE PF : Type*} [MetricSpace PE] [NormedAddTorsor E PE] [MetricSpace PF]
[NormedAddTorsor F PF] [FiniteDimensional 𝕜 E]
theorem AffineMap.continuous_of_finiteDimensional (f : PE →ᵃ[𝕜] PF) : Continuous f :=
AffineMap.continuous_linear_iff.1 f.linear.continuous_of_finiteDimensional
#align affine_map.continuous_of_finite_dimensional AffineMap.continuous_of_finiteDimensional
theorem AffineEquiv.continuous_of_finiteDimensional (f : PE ≃ᵃ[𝕜] PF) : Continuous f :=
f.toAffineMap.continuous_of_finiteDimensional
#align affine_equiv.continuous_of_finite_dimensional AffineEquiv.continuous_of_finiteDimensional
/-- Reinterpret an affine equivalence as a homeomorphism. -/
def AffineEquiv.toHomeomorphOfFiniteDimensional (f : PE ≃ᵃ[𝕜] PF) : PE ≃ₜ PF where
toEquiv := f.toEquiv
continuous_toFun := f.continuous_of_finiteDimensional
continuous_invFun :=
haveI : FiniteDimensional 𝕜 F := f.linear.finiteDimensional
f.symm.continuous_of_finiteDimensional
#align affine_equiv.to_homeomorph_of_finite_dimensional AffineEquiv.toHomeomorphOfFiniteDimensional
@[simp]
theorem AffineEquiv.coe_toHomeomorphOfFiniteDimensional (f : PE ≃ᵃ[𝕜] PF) :
⇑f.toHomeomorphOfFiniteDimensional = f :=
rfl
#align affine_equiv.coe_to_homeomorph_of_finite_dimensional AffineEquiv.coe_toHomeomorphOfFiniteDimensional
@[simp]
theorem AffineEquiv.coe_toHomeomorphOfFiniteDimensional_symm (f : PE ≃ᵃ[𝕜] PF) :
⇑f.toHomeomorphOfFiniteDimensional.symm = f.symm :=
rfl
#align affine_equiv.coe_to_homeomorph_of_finite_dimensional_symm AffineEquiv.coe_toHomeomorphOfFiniteDimensional_symm
end Affine
theorem ContinuousLinearMap.continuous_det : Continuous fun f : E →L[𝕜] E => f.det := by
change Continuous fun f : E →L[𝕜] E => LinearMap.det (f : E →ₗ[𝕜] E)
-- Porting note: this could be easier with `det_cases`
by_cases h : ∃ s : Finset E, Nonempty (Basis (↥s) 𝕜 E)
· rcases h with ⟨s, ⟨b⟩⟩
haveI : FiniteDimensional 𝕜 E := FiniteDimensional.of_fintype_basis b
simp_rw [LinearMap.det_eq_det_toMatrix_of_finset b]
refine Continuous.matrix_det ?_
exact
((LinearMap.toMatrix b b).toLinearMap.comp
(ContinuousLinearMap.coeLM 𝕜)).continuous_of_finiteDimensional
· -- Porting note: was `unfold LinearMap.det`
rw [LinearMap.det_def]
simpa only [h, MonoidHom.one_apply, dif_neg, not_false_iff] using continuous_const
#align continuous_linear_map.continuous_det ContinuousLinearMap.continuous_det
/-- Any `K`-Lipschitz map from a subset `s` of a metric space `α` to a finite-dimensional real
vector space `E'` can be extended to a Lipschitz map on the whole space `α`, with a slightly worse
constant `C * K` where `C` only depends on `E'`. We record a working value for this constant `C`
as `lipschitzExtensionConstant E'`. -/
irreducible_def lipschitzExtensionConstant (E' : Type*) [NormedAddCommGroup E'] [NormedSpace ℝ E']
[FiniteDimensional ℝ E'] : ℝ≥0 :=
let A := (Basis.ofVectorSpace ℝ E').equivFun.toContinuousLinearEquiv
max (‖A.symm.toContinuousLinearMap‖₊ * ‖A.toContinuousLinearMap‖₊) 1
#align lipschitz_extension_constant lipschitzExtensionConstant
theorem lipschitzExtensionConstant_pos (E' : Type*) [NormedAddCommGroup E'] [NormedSpace ℝ E']
[FiniteDimensional ℝ E'] : 0 < lipschitzExtensionConstant E' := by
rw [lipschitzExtensionConstant]
exact zero_lt_one.trans_le (le_max_right _ _)
#align lipschitz_extension_constant_pos lipschitzExtensionConstant_pos
/-- Any `K`-Lipschitz map from a subset `s` of a metric space `α` to a finite-dimensional real
vector space `E'` can be extended to a Lipschitz map on the whole space `α`, with a slightly worse
constant `lipschitzExtensionConstant E' * K`. -/
theorem LipschitzOnWith.extend_finite_dimension {α : Type*} [PseudoMetricSpace α] {E' : Type*}
[NormedAddCommGroup E'] [NormedSpace ℝ E'] [FiniteDimensional ℝ E'] {s : Set α} {f : α → E'}
{K : ℝ≥0} (hf : LipschitzOnWith K f s) :
∃ g : α → E', LipschitzWith (lipschitzExtensionConstant E' * K) g ∧ EqOn f g s := by
/- This result is already known for spaces `ι → ℝ`. We use a continuous linear equiv between
`E'` and such a space to transfer the result to `E'`. -/
let ι : Type _ := Basis.ofVectorSpaceIndex ℝ E'
let A := (Basis.ofVectorSpace ℝ E').equivFun.toContinuousLinearEquiv
have LA : LipschitzWith ‖A.toContinuousLinearMap‖₊ A := by apply A.lipschitz
have L : LipschitzOnWith (‖A.toContinuousLinearMap‖₊ * K) (A ∘ f) s :=
LA.comp_lipschitzOnWith hf
obtain ⟨g, hg, gs⟩ :
∃ g : α → ι → ℝ, LipschitzWith (‖A.toContinuousLinearMap‖₊ * K) g ∧ EqOn (A ∘ f) g s :=
L.extend_pi
refine ⟨A.symm ∘ g, ?_, ?_⟩
· have LAsymm : LipschitzWith ‖A.symm.toContinuousLinearMap‖₊ A.symm := by
apply A.symm.lipschitz
apply (LAsymm.comp hg).weaken
rw [lipschitzExtensionConstant, ← mul_assoc]
exact mul_le_mul' (le_max_left _ _) le_rfl
· intro x hx
have : A (f x) = g x := gs hx
simp only [(· ∘ ·), ← this, A.symm_apply_apply]
#align lipschitz_on_with.extend_finite_dimension LipschitzOnWith.extend_finite_dimension
theorem LinearMap.exists_antilipschitzWith [FiniteDimensional 𝕜 E] (f : E →ₗ[𝕜] F)
(hf : LinearMap.ker f = ⊥) : ∃ K > 0, AntilipschitzWith K f := by
cases subsingleton_or_nontrivial E
· exact ⟨1, zero_lt_one, AntilipschitzWith.of_subsingleton⟩
· rw [LinearMap.ker_eq_bot] at hf
let e : E ≃L[𝕜] LinearMap.range f := (LinearEquiv.ofInjective f hf).toContinuousLinearEquiv
exact ⟨_, e.nnnorm_symm_pos, e.antilipschitz⟩
#align linear_map.exists_antilipschitz_with LinearMap.exists_antilipschitzWith
open Function in
/-- A `LinearMap` on a finite-dimensional space over a complete field
is injective iff it is anti-Lipschitz. -/
theorem LinearMap.injective_iff_antilipschitz [FiniteDimensional 𝕜 E] (f : E →ₗ[𝕜] F) :
Injective f ↔ ∃ K > 0, AntilipschitzWith K f := by
constructor
· rw [← LinearMap.ker_eq_bot]
exact f.exists_antilipschitzWith
· rintro ⟨K, -, H⟩
exact H.injective
open Function in
/-- The set of injective continuous linear maps `E → F` is open,
if `E` is finite-dimensional over a complete field. -/
theorem ContinuousLinearMap.isOpen_injective [FiniteDimensional 𝕜 E] :
IsOpen { L : E →L[𝕜] F | Injective L } := by
rw [isOpen_iff_eventually]
rintro φ₀ hφ₀
rcases φ₀.injective_iff_antilipschitz.mp hφ₀ with ⟨K, K_pos, H⟩
have : ∀ᶠ φ in 𝓝 φ₀, ‖φ - φ₀‖₊ < K⁻¹ := eventually_nnnorm_sub_lt _ <| inv_pos_of_pos K_pos
filter_upwards [this] with φ hφ
apply φ.injective_iff_antilipschitz.mpr
exact ⟨(K⁻¹ - ‖φ - φ₀‖₊)⁻¹, inv_pos_of_pos (tsub_pos_of_lt hφ),
H.add_sub_lipschitzWith (φ - φ₀).lipschitz hφ⟩
protected theorem LinearIndependent.eventually {ι} [Finite ι] {f : ι → E}
(hf : LinearIndependent 𝕜 f) : ∀ᶠ g in 𝓝 f, LinearIndependent 𝕜 g := by
cases nonempty_fintype ι
simp only [Fintype.linearIndependent_iff'] at hf ⊢
rcases LinearMap.exists_antilipschitzWith _ hf with ⟨K, K0, hK⟩
have : Tendsto (fun g : ι → E => ∑ i, ‖g i - f i‖) (𝓝 f) (𝓝 <| ∑ i, ‖f i - f i‖) :=
tendsto_finset_sum _ fun i _ =>
Tendsto.norm <| ((continuous_apply i).tendsto _).sub tendsto_const_nhds
simp only [sub_self, norm_zero, Finset.sum_const_zero] at this
refine (this.eventually (gt_mem_nhds <| inv_pos.2 K0)).mono fun g hg => ?_
replace hg : ∑ i, ‖g i - f i‖₊ < K⁻¹ := by
rw [← NNReal.coe_lt_coe]
push_cast
exact hg
rw [LinearMap.ker_eq_bot]
refine (hK.add_sub_lipschitzWith (LipschitzWith.of_dist_le_mul fun v u => ?_) hg).injective
simp only [dist_eq_norm, LinearMap.lsum_apply, Pi.sub_apply, LinearMap.sum_apply,
LinearMap.comp_apply, LinearMap.proj_apply, LinearMap.smulRight_apply, LinearMap.id_apply, ←
Finset.sum_sub_distrib, ← smul_sub, ← sub_smul, NNReal.coe_sum, coe_nnnorm, Finset.sum_mul]
refine norm_sum_le_of_le _ fun i _ => ?_
rw [norm_smul, mul_comm]
gcongr
exact norm_le_pi_norm (v - u) i
#align linear_independent.eventually LinearIndependent.eventually
theorem isOpen_setOf_linearIndependent {ι : Type*} [Finite ι] :
IsOpen { f : ι → E | LinearIndependent 𝕜 f } :=
isOpen_iff_mem_nhds.2 fun _ => LinearIndependent.eventually
#align is_open_set_of_linear_independent isOpen_setOf_linearIndependent
theorem isOpen_setOf_nat_le_rank (n : ℕ) :
IsOpen { f : E →L[𝕜] F | ↑n ≤ (f : E →ₗ[𝕜] F).rank } := by
simp only [LinearMap.le_rank_iff_exists_linearIndependent_finset, setOf_exists, ← exists_prop]
refine isOpen_biUnion fun t _ => ?_
have : Continuous fun f : E →L[𝕜] F => fun x : (t : Set E) => f x :=
continuous_pi fun x => (ContinuousLinearMap.apply 𝕜 F (x : E)).continuous
exact isOpen_setOf_linearIndependent.preimage this
#align is_open_set_of_nat_le_rank isOpen_setOf_nat_le_rank
theorem Basis.opNNNorm_le {ι : Type*} [Fintype ι] (v : Basis ι 𝕜 E) {u : E →L[𝕜] F} (M : ℝ≥0)
(hu : ∀ i, ‖u (v i)‖₊ ≤ M) : ‖u‖₊ ≤ Fintype.card ι • ‖v.equivFunL.toContinuousLinearMap‖₊ * M :=
u.opNNNorm_le_bound _ fun e => by
set φ := v.equivFunL.toContinuousLinearMap
calc
‖u e‖₊ = ‖u (∑ i, v.equivFun e i • v i)‖₊ := by rw [v.sum_equivFun]
_ = ‖∑ i, v.equivFun e i • (u <| v i)‖₊ := by simp [map_sum, LinearMap.map_smul]
_ ≤ ∑ i, ‖v.equivFun e i • (u <| v i)‖₊ := nnnorm_sum_le _ _
_ = ∑ i, ‖v.equivFun e i‖₊ * ‖u (v i)‖₊ := by simp only [nnnorm_smul]
_ ≤ ∑ i, ‖v.equivFun e i‖₊ * M := by gcongr; apply hu
_ = (∑ i, ‖v.equivFun e i‖₊) * M := by rw [Finset.sum_mul]
_ ≤ Fintype.card ι • (‖φ‖₊ * ‖e‖₊) * M := by
gcongr
calc
∑ i, ‖v.equivFun e i‖₊ ≤ Fintype.card ι • ‖φ e‖₊ := Pi.sum_nnnorm_apply_le_nnnorm _
_ ≤ Fintype.card ι • (‖φ‖₊ * ‖e‖₊) := nsmul_le_nsmul_right (φ.le_opNNNorm e) _
_ = Fintype.card ι • ‖φ‖₊ * M * ‖e‖₊ := by simp only [smul_mul_assoc, mul_right_comm]
#align basis.op_nnnorm_le Basis.opNNNorm_le
@[deprecated (since := "2024-02-02")] alias Basis.op_nnnorm_le := Basis.opNNNorm_le
theorem Basis.opNorm_le {ι : Type*} [Fintype ι] (v : Basis ι 𝕜 E) {u : E →L[𝕜] F} {M : ℝ}
(hM : 0 ≤ M) (hu : ∀ i, ‖u (v i)‖ ≤ M) :
‖u‖ ≤ Fintype.card ι • ‖v.equivFunL.toContinuousLinearMap‖ * M := by
simpa using NNReal.coe_le_coe.mpr (v.opNNNorm_le ⟨M, hM⟩ hu)
#align basis.op_norm_le Basis.opNorm_le
@[deprecated (since := "2024-02-02")] alias Basis.op_norm_le := Basis.opNorm_le
/-- A weaker version of `Basis.opNNNorm_le` that abstracts away the value of `C`. -/
theorem Basis.exists_opNNNorm_le {ι : Type*} [Finite ι] (v : Basis ι 𝕜 E) :
∃ C > (0 : ℝ≥0), ∀ {u : E →L[𝕜] F} (M : ℝ≥0), (∀ i, ‖u (v i)‖₊ ≤ M) → ‖u‖₊ ≤ C * M := by
cases nonempty_fintype ι
exact
⟨max (Fintype.card ι • ‖v.equivFunL.toContinuousLinearMap‖₊) 1,
zero_lt_one.trans_le (le_max_right _ _), fun {u} M hu =>
(v.opNNNorm_le M hu).trans <| mul_le_mul_of_nonneg_right (le_max_left _ _) (zero_le M)⟩
#align basis.exists_op_nnnorm_le Basis.exists_opNNNorm_le
@[deprecated (since := "2024-02-02")] alias Basis.exists_op_nnnorm_le := Basis.exists_opNNNorm_le
/-- A weaker version of `Basis.opNorm_le` that abstracts away the value of `C`. -/
theorem Basis.exists_opNorm_le {ι : Type*} [Finite ι] (v : Basis ι 𝕜 E) :
∃ C > (0 : ℝ), ∀ {u : E →L[𝕜] F} {M : ℝ}, 0 ≤ M → (∀ i, ‖u (v i)‖ ≤ M) → ‖u‖ ≤ C * M := by
obtain ⟨C, hC, h⟩ := v.exists_opNNNorm_le (F := F)
-- Porting note: used `Subtype.forall'` below
refine ⟨C, hC, ?_⟩
intro u M hM H
simpa using h ⟨M, hM⟩ H
#align basis.exists_op_norm_le Basis.exists_opNorm_le
@[deprecated (since := "2024-02-02")] alias Basis.exists_op_norm_le := Basis.exists_opNorm_le
instance [FiniteDimensional 𝕜 E] [SecondCountableTopology F] :
SecondCountableTopology (E →L[𝕜] F) := by
set d := FiniteDimensional.finrank 𝕜 E
suffices
∀ ε > (0 : ℝ), ∃ n : (E →L[𝕜] F) → Fin d → ℕ, ∀ f g : E →L[𝕜] F, n f = n g → dist f g ≤ ε from
Metric.secondCountable_of_countable_discretization fun ε ε_pos =>
⟨Fin d → ℕ, by infer_instance, this ε ε_pos⟩
intro ε ε_pos
obtain ⟨u : ℕ → F, hu : DenseRange u⟩ := exists_dense_seq F
let v := FiniteDimensional.finBasis 𝕜 E
obtain
⟨C : ℝ, C_pos : 0 < C, hC :
∀ {φ : E →L[𝕜] F} {M : ℝ}, 0 ≤ M → (∀ i, ‖φ (v i)‖ ≤ M) → ‖φ‖ ≤ C * M⟩ :=
v.exists_opNorm_le (E := E) (F := F)
have h_2C : 0 < 2 * C := mul_pos zero_lt_two C_pos
have hε2C : 0 < ε / (2 * C) := div_pos ε_pos h_2C
have : ∀ φ : E →L[𝕜] F, ∃ n : Fin d → ℕ, ‖φ - (v.constrL <| u ∘ n)‖ ≤ ε / 2 := by
intro φ
have : ∀ i, ∃ n, ‖φ (v i) - u n‖ ≤ ε / (2 * C) := by
simp only [norm_sub_rev]
intro i
have : φ (v i) ∈ closure (range u) := hu _
obtain ⟨n, hn⟩ : ∃ n, ‖u n - φ (v i)‖ < ε / (2 * C) := by
rw [mem_closure_iff_nhds_basis Metric.nhds_basis_ball] at this
specialize this (ε / (2 * C)) hε2C
simpa [dist_eq_norm]
exact ⟨n, le_of_lt hn⟩
choose n hn using this
use n
replace hn : ∀ i : Fin d, ‖(φ - (v.constrL <| u ∘ n)) (v i)‖ ≤ ε / (2 * C) := by simp [hn]
have : C * (ε / (2 * C)) = ε / 2 := by
rw [eq_div_iff (two_ne_zero : (2 : ℝ) ≠ 0), mul_comm, ← mul_assoc,
mul_div_cancel₀ _ (ne_of_gt h_2C)]
specialize hC (le_of_lt hε2C) hn
rwa [this] at hC
choose n hn using this
set Φ := fun φ : E →L[𝕜] F => v.constrL <| u ∘ n φ
change ∀ z, dist z (Φ z) ≤ ε / 2 at hn
use n
intro x y hxy
calc
dist x y ≤ dist x (Φ x) + dist (Φ x) y := dist_triangle _ _ _
_ = dist x (Φ x) + dist y (Φ y) := by simp [Φ, hxy, dist_comm]
_ ≤ ε := by linarith [hn x, hn y]
theorem AffineSubspace.closed_of_finiteDimensional {P : Type*} [MetricSpace P]
[NormedAddTorsor E P] (s : AffineSubspace 𝕜 P) [FiniteDimensional 𝕜 s.direction] :
IsClosed (s : Set P) :=
s.isClosed_direction_iff.mp s.direction.closed_of_finiteDimensional
#align affine_subspace.closed_of_finite_dimensional AffineSubspace.closed_of_finiteDimensional
section Riesz
/-- In an infinite dimensional space, given a finite number of points, one may find a point
with norm at most `R` which is at distance at least `1` of all these points. -/
theorem exists_norm_le_le_norm_sub_of_finset {c : 𝕜} (hc : 1 < ‖c‖) {R : ℝ} (hR : ‖c‖ < R)
(h : ¬FiniteDimensional 𝕜 E) (s : Finset E) : ∃ x : E, ‖x‖ ≤ R ∧ ∀ y ∈ s, 1 ≤ ‖y - x‖ := by
let F := Submodule.span 𝕜 (s : Set E)
haveI : FiniteDimensional 𝕜 F :=
Module.finite_def.2
((Submodule.fg_top _).2 (Submodule.fg_def.2 ⟨s, Finset.finite_toSet _, rfl⟩))
have Fclosed : IsClosed (F : Set E) := Submodule.closed_of_finiteDimensional _
have : ∃ x, x ∉ F := by
contrapose! h
have : (⊤ : Submodule 𝕜 E) = F := by
ext x
simp [h]
have : FiniteDimensional 𝕜 (⊤ : Submodule 𝕜 E) := by rwa [this]
exact Module.finite_def.2 ((Submodule.fg_top _).1 (Module.finite_def.1 this))
obtain ⟨x, xR, hx⟩ : ∃ x : E, ‖x‖ ≤ R ∧ ∀ y : E, y ∈ F → 1 ≤ ‖x - y‖ :=
riesz_lemma_of_norm_lt hc hR Fclosed this
have hx' : ∀ y : E, y ∈ F → 1 ≤ ‖y - x‖ := by
intro y hy
rw [← norm_neg]
simpa using hx y hy
exact ⟨x, xR, fun y hy => hx' _ (Submodule.subset_span hy)⟩
#align exists_norm_le_le_norm_sub_of_finset exists_norm_le_le_norm_sub_of_finset
/-- In an infinite-dimensional normed space, there exists a sequence of points which are all
bounded by `R` and at distance at least `1`. For a version not assuming `c` and `R`, see
`exists_seq_norm_le_one_le_norm_sub`. -/
theorem exists_seq_norm_le_one_le_norm_sub' {c : 𝕜} (hc : 1 < ‖c‖) {R : ℝ} (hR : ‖c‖ < R)
(h : ¬FiniteDimensional 𝕜 E) :
∃ f : ℕ → E, (∀ n, ‖f n‖ ≤ R) ∧ Pairwise fun m n => 1 ≤ ‖f m - f n‖ := by
have : IsSymm E fun x y : E => 1 ≤ ‖x - y‖ := by
constructor
intro x y hxy
rw [← norm_neg]
simpa
apply
exists_seq_of_forall_finset_exists' (fun x : E => ‖x‖ ≤ R) fun (x : E) (y : E) => 1 ≤ ‖x - y‖
rintro s -
exact exists_norm_le_le_norm_sub_of_finset hc hR h s
#align exists_seq_norm_le_one_le_norm_sub' exists_seq_norm_le_one_le_norm_sub'
theorem exists_seq_norm_le_one_le_norm_sub (h : ¬FiniteDimensional 𝕜 E) :
∃ (R : ℝ) (f : ℕ → E), 1 < R ∧ (∀ n, ‖f n‖ ≤ R) ∧ Pairwise fun m n => 1 ≤ ‖f m - f n‖ := by
obtain ⟨c, hc⟩ : ∃ c : 𝕜, 1 < ‖c‖ := NormedField.exists_one_lt_norm 𝕜
have A : ‖c‖ < ‖c‖ + 1 := by linarith
rcases exists_seq_norm_le_one_le_norm_sub' hc A h with ⟨f, hf⟩
exact ⟨‖c‖ + 1, f, hc.trans A, hf.1, hf.2⟩
#align exists_seq_norm_le_one_le_norm_sub exists_seq_norm_le_one_le_norm_sub
variable (𝕜)
/-- **Riesz's theorem**: if a closed ball with center zero of positive radius is compact in a vector
space, then the space is finite-dimensional. -/
theorem FiniteDimensional.of_isCompact_closedBall₀ {r : ℝ} (rpos : 0 < r)
(h : IsCompact (Metric.closedBall (0 : E) r)) : FiniteDimensional 𝕜 E := by
by_contra hfin
obtain ⟨R, f, Rgt, fle, lef⟩ :
∃ (R : ℝ) (f : ℕ → E), 1 < R ∧ (∀ n, ‖f n‖ ≤ R) ∧ Pairwise fun m n => 1 ≤ ‖f m - f n‖ :=
exists_seq_norm_le_one_le_norm_sub hfin
have rRpos : 0 < r / R := div_pos rpos (zero_lt_one.trans Rgt)
obtain ⟨c, hc⟩ : ∃ c : 𝕜, 0 < ‖c‖ ∧ ‖c‖ < r / R := NormedField.exists_norm_lt _ rRpos
let g := fun n : ℕ => c • f n
have A : ∀ n, g n ∈ Metric.closedBall (0 : E) r := by
intro n
simp only [g, norm_smul, dist_zero_right, Metric.mem_closedBall]
calc
‖c‖ * ‖f n‖ ≤ r / R * R := by
gcongr
· exact hc.2.le
· apply fle
_ = r := by field_simp [(zero_lt_one.trans Rgt).ne']
-- Porting note: moved type ascriptions because of exists_prop changes
obtain ⟨x : E, _ : x ∈ Metric.closedBall (0 : E) r, φ : ℕ → ℕ, φmono : StrictMono φ,
φlim : Tendsto (g ∘ φ) atTop (𝓝 x)⟩ := h.tendsto_subseq A
have B : CauchySeq (g ∘ φ) := φlim.cauchySeq
obtain ⟨N, hN⟩ : ∃ N : ℕ, ∀ n : ℕ, N ≤ n → dist ((g ∘ φ) n) ((g ∘ φ) N) < ‖c‖ :=
Metric.cauchySeq_iff'.1 B ‖c‖ hc.1
apply lt_irrefl ‖c‖
calc
‖c‖ ≤ dist (g (φ (N + 1))) (g (φ N)) := by
conv_lhs => rw [← mul_one ‖c‖]
simp only [g, dist_eq_norm, ← smul_sub, norm_smul]
gcongr
apply lef (ne_of_gt _)
exact φmono (Nat.lt_succ_self N)
_ < ‖c‖ := hN (N + 1) (Nat.le_succ N)
#align finite_dimensional_of_is_compact_closed_ball₀ FiniteDimensional.of_isCompact_closedBall₀
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_isCompact_closedBall₀ := FiniteDimensional.of_isCompact_closedBall₀
/-- **Riesz's theorem**: if a closed ball of positive radius is compact in a vector space, then the
space is finite-dimensional. -/
theorem FiniteDimensional.of_isCompact_closedBall {r : ℝ} (rpos : 0 < r) {c : E}
(h : IsCompact (Metric.closedBall c r)) : FiniteDimensional 𝕜 E :=
.of_isCompact_closedBall₀ 𝕜 rpos <| by simpa using h.vadd (-c)
#align finite_dimensional_of_is_compact_closed_ball FiniteDimensional.of_isCompact_closedBall
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_isCompact_closedBall := FiniteDimensional.of_isCompact_closedBall
/-- **Riesz's theorem**: a locally compact normed vector space is finite-dimensional. -/
theorem FiniteDimensional.of_locallyCompactSpace [LocallyCompactSpace E] :
FiniteDimensional 𝕜 E :=
let ⟨_r, rpos, hr⟩ := exists_isCompact_closedBall (0 : E)
.of_isCompact_closedBall₀ 𝕜 rpos hr
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_locallyCompactSpace := FiniteDimensional.of_locallyCompactSpace
/-- If a function has compact support, then either the function is trivial
or the space is finite-dimensional. -/
theorem HasCompactSupport.eq_zero_or_finiteDimensional {X : Type*} [TopologicalSpace X] [Zero X]
[T1Space X] {f : E → X} (hf : HasCompactSupport f) (h'f : Continuous f) :
f = 0 ∨ FiniteDimensional 𝕜 E :=
(HasCompactSupport.eq_zero_or_locallyCompactSpace_of_addGroup hf h'f).imp_right fun h ↦
-- TODO: Lean doesn't find the instance without this `have`
have : LocallyCompactSpace E := h; .of_locallyCompactSpace 𝕜
#align has_compact_support.eq_zero_or_finite_dimensional HasCompactSupport.eq_zero_or_finiteDimensional
/-- If a function has compact multiplicative support, then either the function is trivial
or the space is finite-dimensional. -/
@[to_additive existing]
theorem HasCompactMulSupport.eq_one_or_finiteDimensional {X : Type*} [TopologicalSpace X] [One X]
[T1Space X] {f : E → X} (hf : HasCompactMulSupport f) (h'f : Continuous f) :
f = 1 ∨ FiniteDimensional 𝕜 E :=
have : T1Space (Additive X) := ‹_›
HasCompactSupport.eq_zero_or_finiteDimensional (X := Additive X) 𝕜 hf h'f
#align has_compact_mul_support.eq_one_or_finite_dimensional HasCompactMulSupport.eq_one_or_finiteDimensional
/-- A locally compact normed vector space is proper. -/
lemma ProperSpace.of_locallyCompactSpace (𝕜 : Type*) [NontriviallyNormedField 𝕜]
{E : Type*} [SeminormedAddCommGroup E] [NormedSpace 𝕜 E] [LocallyCompactSpace E] :
ProperSpace E := by
rcases exists_isCompact_closedBall (0 : E) with ⟨r, rpos, hr⟩
rcases NormedField.exists_one_lt_norm 𝕜 with ⟨c, hc⟩
have hC : ∀ n, IsCompact (closedBall (0 : E) (‖c‖^n * r)) := fun n ↦ by
have : c ^ n ≠ 0 := pow_ne_zero _ <| fun h ↦ by simp [h, zero_le_one.not_lt] at hc
simpa [_root_.smul_closedBall' this] using hr.smul (c ^ n)
have hTop : Tendsto (fun n ↦ ‖c‖^n * r) atTop atTop :=
Tendsto.atTop_mul_const rpos (tendsto_pow_atTop_atTop_of_one_lt hc)
exact .of_seq_closedBall hTop (eventually_of_forall hC)
@[deprecated (since := "2024-01-31")]
alias properSpace_of_locallyCompactSpace := ProperSpace.of_locallyCompactSpace
variable (E)
lemma ProperSpace.of_locallyCompact_module [Nontrivial E] [LocallyCompactSpace E] :
ProperSpace 𝕜 :=
have : LocallyCompactSpace 𝕜 := by
obtain ⟨v, hv⟩ : ∃ v : E, v ≠ 0 := exists_ne 0
let L : 𝕜 → E := fun t ↦ t • v
have : ClosedEmbedding L := closedEmbedding_smul_left hv
apply ClosedEmbedding.locallyCompactSpace this
.of_locallyCompactSpace 𝕜
@[deprecated (since := "2024-01-31")]
alias properSpace_of_locallyCompact_module := ProperSpace.of_locallyCompact_module
end Riesz
open ContinuousLinearMap
/-- Continuous linear equivalence between continuous linear functions `𝕜ⁿ → E` and `Eⁿ`.
The spaces `𝕜ⁿ` and `Eⁿ` are represented as `ι → 𝕜` and `ι → E`, respectively,
where `ι` is a finite type. -/
def ContinuousLinearEquiv.piRing (ι : Type*) [Fintype ι] [DecidableEq ι] :
((ι → 𝕜) →L[𝕜] E) ≃L[𝕜] ι → E :=
{ LinearMap.toContinuousLinearMap.symm.trans (LinearEquiv.piRing 𝕜 E ι 𝕜) with
continuous_toFun := by
refine continuous_pi fun i => ?_
exact (ContinuousLinearMap.apply 𝕜 E (Pi.single i 1)).continuous
continuous_invFun := by
simp_rw [LinearEquiv.invFun_eq_symm, LinearEquiv.trans_symm, LinearEquiv.symm_symm]
-- Note: added explicit type and removed `change` that tried to achieve the same
refine AddMonoidHomClass.continuous_of_bound
(LinearMap.toContinuousLinearMap.toLinearMap.comp
(LinearEquiv.piRing 𝕜 E ι 𝕜).symm.toLinearMap)
(Fintype.card ι : ℝ) fun g => ?_
rw [← nsmul_eq_mul]
refine opNorm_le_bound _ (nsmul_nonneg (norm_nonneg g) (Fintype.card ι)) fun t => ?_
simp_rw [LinearMap.coe_comp, LinearEquiv.coe_toLinearMap, Function.comp_apply,
LinearMap.coe_toContinuousLinearMap', LinearEquiv.piRing_symm_apply]
apply le_trans (norm_sum_le _ _)
rw [smul_mul_assoc]
refine Finset.sum_le_card_nsmul _ _ _ fun i _ => ?_
rw [norm_smul, mul_comm]
gcongr <;> apply norm_le_pi_norm }
#align continuous_linear_equiv.pi_ring ContinuousLinearEquiv.piRing
/-- A family of continuous linear maps is continuous on `s` if all its applications are. -/
theorem continuousOn_clm_apply {X : Type*} [TopologicalSpace X] [FiniteDimensional 𝕜 E]
{f : X → E →L[𝕜] F} {s : Set X} : ContinuousOn f s ↔ ∀ y, ContinuousOn (fun x => f x y) s := by
refine ⟨fun h y => (ContinuousLinearMap.apply 𝕜 F y).continuous.comp_continuousOn h, fun h => ?_⟩
let d := finrank 𝕜 E
have hd : d = finrank 𝕜 (Fin d → 𝕜) := (finrank_fin_fun 𝕜).symm
let e₁ : E ≃L[𝕜] Fin d → 𝕜 := ContinuousLinearEquiv.ofFinrankEq hd
let e₂ : (E →L[𝕜] F) ≃L[𝕜] Fin d → F :=
(e₁.arrowCongr (1 : F ≃L[𝕜] F)).trans (ContinuousLinearEquiv.piRing (Fin d))
rw [← f.id_comp, ← e₂.symm_comp_self]
exact e₂.symm.continuous.comp_continuousOn (continuousOn_pi.mpr fun i => h _)
#align continuous_on_clm_apply continuousOn_clm_apply
| Mathlib/Analysis/NormedSpace/FiniteDimension.lean | 606 | 608 | theorem continuous_clm_apply {X : Type*} [TopologicalSpace X] [FiniteDimensional 𝕜 E]
{f : X → E →L[𝕜] F} : Continuous f ↔ ∀ y, Continuous (f · y) := by |
simp_rw [continuous_iff_continuousOn_univ, continuousOn_clm_apply]
|
/-
Copyright (c) 2023 Felix Weilacher. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Felix Weilacher, Yury G. Kudryashov, Rémy Degenne
-/
import Mathlib.MeasureTheory.MeasurableSpace.Basic
import Mathlib.Data.Set.MemPartition
import Mathlib.Order.Filter.CountableSeparatingOn
/-!
# Countably generated measurable spaces
We say a measurable space is countably generated if it can be generated by a countable set of sets.
In such a space, we can also build a sequence of finer and finer finite measurable partitions of
the space such that the measurable space is generated by the union of all partitions.
## Main definitions
* `MeasurableSpace.CountablyGenerated`: class stating that a measurable space is countably
generated.
* `MeasurableSpace.countableGeneratingSet`: a countable set of sets that generates the σ-algebra.
* `MeasurableSpace.countablePartition`: sequences of finer and finer partitions of
a countably generated space, defined by taking the `memPartion` of an enumeration of the sets in
`countableGeneratingSet`.
* `MeasurableSpace.SeparatesPoints` : class stating that a measurable space separates points.
## Main statements
* `MeasurableSpace.measurable_equiv_nat_bool_of_countablyGenerated`: if a measurable space is
countably generated and separates points, it is measure equivalent to a subset of the Cantor Space
`ℕ → Bool` (equipped with the product sigma algebra).
* `MeasurableSpace.measurable_injection_nat_bool_of_countablyGenerated`: If a measurable space
admits a countable sequence of measurable sets separating points,
it admits a measurable injection into the Cantor space `ℕ → Bool`
`ℕ → Bool` (equipped with the product sigma algebra).
The file also contains measurability results about `memPartition`, from which the properties of
`countablePartition` are deduced.
-/
open Set MeasureTheory
namespace MeasurableSpace
variable {α β : Type*}
/-- We say a measurable space is countably generated
if it can be generated by a countable set of sets. -/
class CountablyGenerated (α : Type*) [m : MeasurableSpace α] : Prop where
isCountablyGenerated : ∃ b : Set (Set α), b.Countable ∧ m = generateFrom b
#align measurable_space.countably_generated MeasurableSpace.CountablyGenerated
/-- A countable set of sets that generate the measurable space.
We insert `∅` to ensure it is nonempty. -/
def countableGeneratingSet (α : Type*) [MeasurableSpace α] [h : CountablyGenerated α] :
Set (Set α) :=
insert ∅ h.isCountablyGenerated.choose
lemma countable_countableGeneratingSet [MeasurableSpace α] [h : CountablyGenerated α] :
Set.Countable (countableGeneratingSet α) :=
Countable.insert _ h.isCountablyGenerated.choose_spec.1
lemma generateFrom_countableGeneratingSet [m : MeasurableSpace α] [h : CountablyGenerated α] :
generateFrom (countableGeneratingSet α) = m :=
(generateFrom_insert_empty _).trans <| h.isCountablyGenerated.choose_spec.2.symm
lemma empty_mem_countableGeneratingSet [MeasurableSpace α] [CountablyGenerated α] :
∅ ∈ countableGeneratingSet α := mem_insert _ _
lemma nonempty_countableGeneratingSet [MeasurableSpace α] [CountablyGenerated α] :
Set.Nonempty (countableGeneratingSet α) :=
⟨∅, mem_insert _ _⟩
lemma measurableSet_countableGeneratingSet [MeasurableSpace α] [CountablyGenerated α]
{s : Set α} (hs : s ∈ countableGeneratingSet α) :
MeasurableSet s := by
rw [← generateFrom_countableGeneratingSet (α := α)]
exact measurableSet_generateFrom hs
/-- A countable sequence of sets generating the measurable space. -/
def natGeneratingSequence (α : Type*) [MeasurableSpace α] [CountablyGenerated α] : ℕ → (Set α) :=
enumerateCountable (countable_countableGeneratingSet (α := α)) ∅
lemma generateFrom_natGeneratingSequence (α : Type*) [m : MeasurableSpace α]
[CountablyGenerated α] : generateFrom (range (natGeneratingSequence _)) = m := by
rw [natGeneratingSequence, range_enumerateCountable_of_mem _ empty_mem_countableGeneratingSet,
generateFrom_countableGeneratingSet]
lemma measurableSet_natGeneratingSequence [MeasurableSpace α] [CountablyGenerated α] (n : ℕ) :
MeasurableSet (natGeneratingSequence α n) :=
measurableSet_countableGeneratingSet $ Set.enumerateCountable_mem _
empty_mem_countableGeneratingSet n
theorem CountablyGenerated.comap [m : MeasurableSpace β] [h : CountablyGenerated β] (f : α → β) :
@CountablyGenerated α (.comap f m) := by
rcases h with ⟨⟨b, hbc, rfl⟩⟩
rw [comap_generateFrom]
letI := generateFrom (preimage f '' b)
exact ⟨_, hbc.image _, rfl⟩
theorem CountablyGenerated.sup {m₁ m₂ : MeasurableSpace β} (h₁ : @CountablyGenerated β m₁)
(h₂ : @CountablyGenerated β m₂) : @CountablyGenerated β (m₁ ⊔ m₂) := by
rcases h₁ with ⟨⟨b₁, hb₁c, rfl⟩⟩
rcases h₂ with ⟨⟨b₂, hb₂c, rfl⟩⟩
exact @mk _ (_ ⊔ _) ⟨_, hb₁c.union hb₂c, generateFrom_sup_generateFrom⟩
/-- Any measurable space structure on a countable space is countably generated. -/
instance (priority := 100) [MeasurableSpace α] [Countable α] : CountablyGenerated α where
isCountablyGenerated := by
refine ⟨⋃ y, {measurableAtom y}, countable_iUnion (fun i ↦ countable_singleton _), ?_⟩
refine le_antisymm ?_ (generateFrom_le (by simp [MeasurableSet.measurableAtom_of_countable]))
intro s hs
have : s = ⋃ y ∈ s, measurableAtom y := by
apply Subset.antisymm
· intro x hx
simpa using ⟨x, hx, by simp⟩
· simp only [iUnion_subset_iff]
intro x hx
exact measurableAtom_subset hs hx
rw [this]
apply MeasurableSet.biUnion (to_countable s) (fun x _hx ↦ ?_)
apply measurableSet_generateFrom
simp
instance [MeasurableSpace α] [CountablyGenerated α] {p : α → Prop} :
CountablyGenerated { x // p x } := .comap _
instance [MeasurableSpace α] [CountablyGenerated α] [MeasurableSpace β] [CountablyGenerated β] :
CountablyGenerated (α × β) :=
.sup (.comap Prod.fst) (.comap Prod.snd)
section SeparatesPoints
/-- We say that a measurable space separates points if for any two distinct points,
there is a measurable set containing one but not the other. -/
class SeparatesPoints (α : Type*) [m : MeasurableSpace α] : Prop where
separates : ∀ x y : α, (∀ s, MeasurableSet s → (x ∈ s → y ∈ s)) → x = y
theorem separatesPoints_def [MeasurableSpace α] [hs : SeparatesPoints α] {x y : α}
(h : ∀ s, MeasurableSet s → (x ∈ s → y ∈ s)) : x = y := hs.separates _ _ h
| Mathlib/MeasureTheory/MeasurableSpace/CountablyGenerated.lean | 144 | 147 | theorem exists_measurableSet_of_ne [MeasurableSpace α] [SeparatesPoints α] {x y : α}
(h : x ≠ y) : ∃ s, MeasurableSet s ∧ x ∈ s ∧ y ∉ s := by |
contrapose! h
exact separatesPoints_def 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.Data.Set.Prod
#align_import data.set.n_ary from "leanprover-community/mathlib"@"5e526d18cea33550268dcbbddcb822d5cde40654"
/-!
# N-ary images of sets
This file defines `Set.image2`, the binary image of sets.
This is mostly useful to define pointwise operations and `Set.seq`.
## Notes
This file is very similar to `Data.Finset.NAry`, to `Order.Filter.NAry`, and to
`Data.Option.NAry`. Please keep them in sync.
-/
open Function
namespace Set
variable {α α' β β' γ γ' δ δ' ε ε' ζ ζ' ν : Type*} {f f' : α → β → γ} {g g' : α → β → γ → δ}
variable {s s' : Set α} {t t' : Set β} {u u' : Set γ} {v : Set δ} {a a' : α} {b b' : β} {c c' : γ}
{d d' : δ}
theorem mem_image2_iff (hf : Injective2 f) : f a b ∈ image2 f s t ↔ a ∈ s ∧ b ∈ t :=
⟨by
rintro ⟨a', ha', b', hb', h⟩
rcases hf h with ⟨rfl, rfl⟩
exact ⟨ha', hb'⟩, fun ⟨ha, hb⟩ => mem_image2_of_mem ha hb⟩
#align set.mem_image2_iff Set.mem_image2_iff
/-- image2 is monotone with respect to `⊆`. -/
theorem image2_subset (hs : s ⊆ s') (ht : t ⊆ t') : image2 f s t ⊆ image2 f s' t' := by
rintro _ ⟨a, ha, b, hb, rfl⟩
exact mem_image2_of_mem (hs ha) (ht hb)
#align set.image2_subset Set.image2_subset
theorem image2_subset_left (ht : t ⊆ t') : image2 f s t ⊆ image2 f s t' :=
image2_subset Subset.rfl ht
#align set.image2_subset_left Set.image2_subset_left
theorem image2_subset_right (hs : s ⊆ s') : image2 f s t ⊆ image2 f s' t :=
image2_subset hs Subset.rfl
#align set.image2_subset_right Set.image2_subset_right
theorem image_subset_image2_left (hb : b ∈ t) : (fun a => f a b) '' s ⊆ image2 f s t :=
forall_mem_image.2 fun _ ha => mem_image2_of_mem ha hb
#align set.image_subset_image2_left Set.image_subset_image2_left
theorem image_subset_image2_right (ha : a ∈ s) : f a '' t ⊆ image2 f s t :=
forall_mem_image.2 fun _ => mem_image2_of_mem ha
#align set.image_subset_image2_right Set.image_subset_image2_right
theorem forall_image2_iff {p : γ → Prop} :
(∀ z ∈ image2 f s t, p z) ↔ ∀ x ∈ s, ∀ y ∈ t, p (f x y) :=
⟨fun h x hx y hy => h _ ⟨x, hx, y, hy, rfl⟩, fun h _ ⟨x, hx, y, hy, hz⟩ => hz ▸ h x hx y hy⟩
#align set.forall_image2_iff Set.forall_image2_iff
@[simp]
theorem image2_subset_iff {u : Set γ} : image2 f s t ⊆ u ↔ ∀ x ∈ s, ∀ y ∈ t, f x y ∈ u :=
forall_image2_iff
#align set.image2_subset_iff Set.image2_subset_iff
theorem image2_subset_iff_left : image2 f s t ⊆ u ↔ ∀ a ∈ s, (fun b => f a b) '' t ⊆ u := by
simp_rw [image2_subset_iff, image_subset_iff, subset_def, mem_preimage]
#align set.image2_subset_iff_left Set.image2_subset_iff_left
theorem image2_subset_iff_right : image2 f s t ⊆ u ↔ ∀ b ∈ t, (fun a => f a b) '' s ⊆ u := by
simp_rw [image2_subset_iff, image_subset_iff, subset_def, mem_preimage, @forall₂_swap α]
#align set.image2_subset_iff_right Set.image2_subset_iff_right
variable (f)
-- Porting note: Removing `simp` - LHS does not simplify
lemma image_prod : (fun x : α × β ↦ f x.1 x.2) '' s ×ˢ t = image2 f s t :=
ext fun _ ↦ by simp [and_assoc]
#align set.image_prod Set.image_prod
@[simp] lemma image_uncurry_prod (s : Set α) (t : Set β) : uncurry f '' s ×ˢ t = image2 f s t :=
image_prod _
#align set.image_uncurry_prod Set.image_uncurry_prod
@[simp] lemma image2_mk_eq_prod : image2 Prod.mk s t = s ×ˢ t := ext <| by simp
#align set.image2_mk_eq_prod Set.image2_mk_eq_prod
-- Porting note: Removing `simp` - LHS does not simplify
lemma image2_curry (f : α × β → γ) (s : Set α) (t : Set β) :
image2 (fun a b ↦ f (a, b)) s t = f '' s ×ˢ t := by
simp [← image_uncurry_prod, uncurry]
#align set.image2_curry Set.image2_curry
theorem image2_swap (s : Set α) (t : Set β) : image2 f s t = image2 (fun a b => f b a) t s := by
ext
constructor <;> rintro ⟨a, ha, b, hb, rfl⟩ <;> exact ⟨b, hb, a, ha, rfl⟩
#align set.image2_swap Set.image2_swap
variable {f}
theorem image2_union_left : image2 f (s ∪ s') t = image2 f s t ∪ image2 f s' t := by
simp_rw [← image_prod, union_prod, image_union]
#align set.image2_union_left Set.image2_union_left
theorem image2_union_right : image2 f s (t ∪ t') = image2 f s t ∪ image2 f s t' := by
rw [← image2_swap, image2_union_left, image2_swap f, image2_swap f]
#align set.image2_union_right Set.image2_union_right
lemma image2_inter_left (hf : Injective2 f) :
image2 f (s ∩ s') t = image2 f s t ∩ image2 f s' t := by
simp_rw [← image_uncurry_prod, inter_prod, image_inter hf.uncurry]
#align set.image2_inter_left Set.image2_inter_left
lemma image2_inter_right (hf : Injective2 f) :
image2 f s (t ∩ t') = image2 f s t ∩ image2 f s t' := by
simp_rw [← image_uncurry_prod, prod_inter, image_inter hf.uncurry]
#align set.image2_inter_right Set.image2_inter_right
@[simp]
theorem image2_empty_left : image2 f ∅ t = ∅ :=
ext <| by simp
#align set.image2_empty_left Set.image2_empty_left
@[simp]
theorem image2_empty_right : image2 f s ∅ = ∅ :=
ext <| by simp
#align set.image2_empty_right Set.image2_empty_right
theorem Nonempty.image2 : s.Nonempty → t.Nonempty → (image2 f s t).Nonempty :=
fun ⟨_, ha⟩ ⟨_, hb⟩ => ⟨_, mem_image2_of_mem ha hb⟩
#align set.nonempty.image2 Set.Nonempty.image2
@[simp]
theorem image2_nonempty_iff : (image2 f s t).Nonempty ↔ s.Nonempty ∧ t.Nonempty :=
⟨fun ⟨_, a, ha, b, hb, _⟩ => ⟨⟨a, ha⟩, b, hb⟩, fun h => h.1.image2 h.2⟩
#align set.image2_nonempty_iff Set.image2_nonempty_iff
theorem Nonempty.of_image2_left (h : (Set.image2 f s t).Nonempty) : s.Nonempty :=
(image2_nonempty_iff.1 h).1
#align set.nonempty.of_image2_left Set.Nonempty.of_image2_left
theorem Nonempty.of_image2_right (h : (Set.image2 f s t).Nonempty) : t.Nonempty :=
(image2_nonempty_iff.1 h).2
#align set.nonempty.of_image2_right Set.Nonempty.of_image2_right
@[simp]
theorem image2_eq_empty_iff : image2 f s t = ∅ ↔ s = ∅ ∨ t = ∅ := by
rw [← not_nonempty_iff_eq_empty, image2_nonempty_iff, not_and_or]
simp [not_nonempty_iff_eq_empty]
#align set.image2_eq_empty_iff Set.image2_eq_empty_iff
theorem Subsingleton.image2 (hs : s.Subsingleton) (ht : t.Subsingleton) (f : α → β → γ) :
(image2 f s t).Subsingleton := by
rw [← image_prod]
apply (hs.prod ht).image
theorem image2_inter_subset_left : image2 f (s ∩ s') t ⊆ image2 f s t ∩ image2 f s' t :=
Monotone.map_inf_le (fun _ _ ↦ image2_subset_right) s s'
#align set.image2_inter_subset_left Set.image2_inter_subset_left
theorem image2_inter_subset_right : image2 f s (t ∩ t') ⊆ image2 f s t ∩ image2 f s t' :=
Monotone.map_inf_le (fun _ _ ↦ image2_subset_left) t t'
#align set.image2_inter_subset_right Set.image2_inter_subset_right
@[simp]
theorem image2_singleton_left : image2 f {a} t = f a '' t :=
ext fun x => by simp
#align set.image2_singleton_left Set.image2_singleton_left
@[simp]
theorem image2_singleton_right : image2 f s {b} = (fun a => f a b) '' s :=
ext fun x => by simp
#align set.image2_singleton_right Set.image2_singleton_right
theorem image2_singleton : image2 f {a} {b} = {f a b} := by simp
#align set.image2_singleton Set.image2_singleton
@[simp]
theorem image2_insert_left : image2 f (insert a s) t = (fun b => f a b) '' t ∪ image2 f s t := by
rw [insert_eq, image2_union_left, image2_singleton_left]
#align set.image2_insert_left Set.image2_insert_left
@[simp]
theorem image2_insert_right : image2 f s (insert b t) = (fun a => f a b) '' s ∪ image2 f s t := by
rw [insert_eq, image2_union_right, image2_singleton_right]
#align set.image2_insert_right Set.image2_insert_right
@[congr]
theorem image2_congr (h : ∀ a ∈ s, ∀ b ∈ t, f a b = f' a b) : image2 f s t = image2 f' s t := by
ext
constructor <;> rintro ⟨a, ha, b, hb, rfl⟩ <;> exact ⟨a, ha, b, hb, by rw [h a ha b hb]⟩
#align set.image2_congr Set.image2_congr
/-- A common special case of `image2_congr` -/
theorem image2_congr' (h : ∀ a b, f a b = f' a b) : image2 f s t = image2 f' s t :=
image2_congr fun a _ b _ => h a b
#align set.image2_congr' Set.image2_congr'
#noalign set.image3
#noalign set.mem_image3
#noalign set.image3_mono
#noalign set.image3_congr
#noalign set.image3_congr'
#noalign set.image2_image2_left
#noalign set.image2_image2_right
theorem image_image2 (f : α → β → γ) (g : γ → δ) :
g '' image2 f s t = image2 (fun a b => g (f a b)) s t := by
simp only [← image_prod, image_image]
#align set.image_image2 Set.image_image2
theorem image2_image_left (f : γ → β → δ) (g : α → γ) :
image2 f (g '' s) t = image2 (fun a b => f (g a) b) s t := by
ext; simp
#align set.image2_image_left Set.image2_image_left
theorem image2_image_right (f : α → γ → δ) (g : β → γ) :
image2 f s (g '' t) = image2 (fun a b => f a (g b)) s t := by
ext; simp
#align set.image2_image_right Set.image2_image_right
@[simp]
theorem image2_left (h : t.Nonempty) : image2 (fun x _ => x) s t = s := by
simp [nonempty_def.mp h, ext_iff]
#align set.image2_left Set.image2_left
@[simp]
theorem image2_right (h : s.Nonempty) : image2 (fun _ y => y) s t = t := by
simp [nonempty_def.mp h, ext_iff]
#align set.image2_right Set.image2_right
lemma image2_range (f : α' → β' → γ) (g : α → α') (h : β → β') :
image2 f (range g) (range h) = range fun x : α × β ↦ f (g x.1) (h x.2) := by
simp_rw [← image_univ, image2_image_left, image2_image_right, ← image_prod, univ_prod_univ]
theorem image2_assoc {f : δ → γ → ε} {g : α → β → δ} {f' : α → ε' → ε} {g' : β → γ → ε'}
(h_assoc : ∀ a b c, f (g a b) c = f' a (g' b c)) :
image2 f (image2 g s t) u = image2 f' s (image2 g' t u) :=
eq_of_forall_subset_iff fun _ ↦ by simp only [image2_subset_iff, forall_image2_iff, h_assoc]
#align set.image2_assoc Set.image2_assoc
theorem image2_comm {g : β → α → γ} (h_comm : ∀ a b, f a b = g b a) : image2 f s t = image2 g t s :=
(image2_swap _ _ _).trans <| by simp_rw [h_comm]
#align set.image2_comm Set.image2_comm
theorem image2_left_comm {f : α → δ → ε} {g : β → γ → δ} {f' : α → γ → δ'} {g' : β → δ' → ε}
(h_left_comm : ∀ a b c, f a (g b c) = g' b (f' a c)) :
image2 f s (image2 g t u) = image2 g' t (image2 f' s u) := by
rw [image2_swap f', image2_swap f]
exact image2_assoc fun _ _ _ => h_left_comm _ _ _
#align set.image2_left_comm Set.image2_left_comm
theorem image2_right_comm {f : δ → γ → ε} {g : α → β → δ} {f' : α → γ → δ'} {g' : δ' → β → ε}
(h_right_comm : ∀ a b c, f (g a b) c = g' (f' a c) b) :
image2 f (image2 g s t) u = image2 g' (image2 f' s u) t := by
rw [image2_swap g, image2_swap g']
exact image2_assoc fun _ _ _ => h_right_comm _ _ _
#align set.image2_right_comm Set.image2_right_comm
theorem image2_image2_image2_comm {f : ε → ζ → ν} {g : α → β → ε} {h : γ → δ → ζ} {f' : ε' → ζ' → ν}
{g' : α → γ → ε'} {h' : β → δ → ζ'}
(h_comm : ∀ a b c d, f (g a b) (h c d) = f' (g' a c) (h' b d)) :
image2 f (image2 g s t) (image2 h u v) = image2 f' (image2 g' s u) (image2 h' t v) := by
ext; constructor
· rintro ⟨_, ⟨a, ha, b, hb, rfl⟩, _, ⟨c, hc, d, hd, rfl⟩, rfl⟩
exact ⟨_, ⟨a, ha, c, hc, rfl⟩, _, ⟨b, hb, d, hd, rfl⟩, (h_comm _ _ _ _).symm⟩
· rintro ⟨_, ⟨a, ha, c, hc, rfl⟩, _, ⟨b, hb, d, hd, rfl⟩, rfl⟩
exact ⟨_, ⟨a, ha, b, hb, rfl⟩, _, ⟨c, hc, d, hd, rfl⟩, h_comm _ _ _ _⟩
#align set.image2_image2_image2_comm Set.image2_image2_image2_comm
theorem image_image2_distrib {g : γ → δ} {f' : α' → β' → δ} {g₁ : α → α'} {g₂ : β → β'}
(h_distrib : ∀ a b, g (f a b) = f' (g₁ a) (g₂ b)) :
(image2 f s t).image g = image2 f' (s.image g₁) (t.image g₂) := by
simp_rw [image_image2, image2_image_left, image2_image_right, h_distrib]
#align set.image_image2_distrib Set.image_image2_distrib
/-- Symmetric statement to `Set.image2_image_left_comm`. -/
theorem image_image2_distrib_left {g : γ → δ} {f' : α' → β → δ} {g' : α → α'}
(h_distrib : ∀ a b, g (f a b) = f' (g' a) b) :
(image2 f s t).image g = image2 f' (s.image g') t :=
(image_image2_distrib h_distrib).trans <| by rw [image_id']
#align set.image_image2_distrib_left Set.image_image2_distrib_left
/-- Symmetric statement to `Set.image_image2_right_comm`. -/
theorem image_image2_distrib_right {g : γ → δ} {f' : α → β' → δ} {g' : β → β'}
(h_distrib : ∀ a b, g (f a b) = f' a (g' b)) :
(image2 f s t).image g = image2 f' s (t.image g') :=
(image_image2_distrib h_distrib).trans <| by rw [image_id']
#align set.image_image2_distrib_right Set.image_image2_distrib_right
/-- Symmetric statement to `Set.image_image2_distrib_left`. -/
theorem image2_image_left_comm {f : α' → β → γ} {g : α → α'} {f' : α → β → δ} {g' : δ → γ}
(h_left_comm : ∀ a b, f (g a) b = g' (f' a b)) :
image2 f (s.image g) t = (image2 f' s t).image g' :=
(image_image2_distrib_left fun a b => (h_left_comm a b).symm).symm
#align set.image2_image_left_comm Set.image2_image_left_comm
/-- Symmetric statement to `Set.image_image2_distrib_right`. -/
theorem image_image2_right_comm {f : α → β' → γ} {g : β → β'} {f' : α → β → δ} {g' : δ → γ}
(h_right_comm : ∀ a b, f a (g b) = g' (f' a b)) :
image2 f s (t.image g) = (image2 f' s t).image g' :=
(image_image2_distrib_right fun a b => (h_right_comm a b).symm).symm
#align set.image_image2_right_comm Set.image_image2_right_comm
/-- The other direction does not hold because of the `s`-`s` cross terms on the RHS. -/
theorem image2_distrib_subset_left {f : α → δ → ε} {g : β → γ → δ} {f₁ : α → β → β'}
{f₂ : α → γ → γ'} {g' : β' → γ' → ε} (h_distrib : ∀ a b c, f a (g b c) = g' (f₁ a b) (f₂ a c)) :
image2 f s (image2 g t u) ⊆ image2 g' (image2 f₁ s t) (image2 f₂ s u) := by
rintro _ ⟨a, ha, _, ⟨b, hb, c, hc, rfl⟩, rfl⟩
rw [h_distrib]
exact mem_image2_of_mem (mem_image2_of_mem ha hb) (mem_image2_of_mem ha hc)
#align set.image2_distrib_subset_left Set.image2_distrib_subset_left
/-- The other direction does not hold because of the `u`-`u` cross terms on the RHS. -/
theorem image2_distrib_subset_right {f : δ → γ → ε} {g : α → β → δ} {f₁ : α → γ → α'}
{f₂ : β → γ → β'} {g' : α' → β' → ε} (h_distrib : ∀ a b c, f (g a b) c = g' (f₁ a c) (f₂ b c)) :
image2 f (image2 g s t) u ⊆ image2 g' (image2 f₁ s u) (image2 f₂ t u) := by
rintro _ ⟨_, ⟨a, ha, b, hb, rfl⟩, c, hc, rfl⟩
rw [h_distrib]
exact mem_image2_of_mem (mem_image2_of_mem ha hc) (mem_image2_of_mem hb hc)
#align set.image2_distrib_subset_right Set.image2_distrib_subset_right
| Mathlib/Data/Set/NAry.lean | 325 | 329 | theorem image_image2_antidistrib {g : γ → δ} {f' : β' → α' → δ} {g₁ : β → β'} {g₂ : α → α'}
(h_antidistrib : ∀ a b, g (f a b) = f' (g₁ b) (g₂ a)) :
(image2 f s t).image g = image2 f' (t.image g₁) (s.image g₂) := by |
rw [image2_swap f]
exact image_image2_distrib fun _ _ => h_antidistrib _ _
|
/-
Copyright (c) 2022 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz, Amelia Livingston
-/
import Mathlib.Algebra.Homology.Additive
import Mathlib.CategoryTheory.Abelian.Pseudoelements
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Images
#align_import category_theory.abelian.homology from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
The object `homology' f g w`, where `w : f ≫ g = 0`, can be identified with either a
cokernel or a kernel. The isomorphism with a cokernel is `homology'IsoCokernelLift`, which
was obtained elsewhere. In the case of an abelian category, this file shows the isomorphism
with a kernel as well.
We use these isomorphisms to obtain the analogous api for `homology'`:
- `homology'.ι` is the map from `homology' f g w` into the cokernel of `f`.
- `homology'.π'` is the map from `kernel g` to `homology' f g w`.
- `homology'.desc'` constructs a morphism from `homology' f g w`, when it is viewed as a cokernel.
- `homology'.lift` constructs a morphism to `homology' f g w`, when it is viewed as a kernel.
- Various small lemmas are proved as well, mimicking the API for (co)kernels.
With these definitions and lemmas, the isomorphisms between homology and a (co)kernel need not
be used directly.
Note: As part of the homology refactor, it is planned to remove the definitions in this file,
because it can be replaced by the content of `Algebra.Homology.ShortComplex.Homology`.
-/
open CategoryTheory.Limits
open CategoryTheory
noncomputable section
universe v u
variable {A : Type u} [Category.{v} A] [Abelian A]
variable {X Y Z : A} (f : X ⟶ Y) (g : Y ⟶ Z) (w : f ≫ g = 0)
namespace CategoryTheory.Abelian
/-- The cokernel of `kernel.lift g f w`. This is isomorphic to `homology f g w`.
See `homologyIsoCokernelLift`. -/
abbrev homologyC : A :=
cokernel (kernel.lift g f w)
#align category_theory.abelian.homology_c CategoryTheory.Abelian.homologyC
/-- The kernel of `cokernel.desc f g w`. This is isomorphic to `homology f g w`.
See `homologyIsoKernelDesc`. -/
abbrev homologyK : A :=
kernel (cokernel.desc f g w)
#align category_theory.abelian.homology_k CategoryTheory.Abelian.homologyK
/-- The canonical map from `homologyC` to `homologyK`.
This is an isomorphism, and it is used in obtaining the API for `homology f g w`
in the bottom of this file. -/
abbrev homologyCToK : homologyC f g w ⟶ homologyK f g w :=
cokernel.desc _ (kernel.lift _ (kernel.ι _ ≫ cokernel.π _) (by simp)) (by ext; simp)
#align category_theory.abelian.homology_c_to_k CategoryTheory.Abelian.homologyCToK
attribute [local instance] Pseudoelement.homToFun Pseudoelement.hasZero
instance : Mono (homologyCToK f g w) := by
apply Pseudoelement.mono_of_zero_of_map_zero
intro a ha
obtain ⟨a, rfl⟩ := Pseudoelement.pseudo_surjective_of_epi (cokernel.π (kernel.lift g f w)) a
apply_fun kernel.ι (cokernel.desc f g w) at ha
simp only [← Pseudoelement.comp_apply, cokernel.π_desc, kernel.lift_ι,
Pseudoelement.apply_zero] at ha
simp only [Pseudoelement.comp_apply] at ha
obtain ⟨b, hb⟩ : ∃ b, f b = _ := (Pseudoelement.pseudo_exact_of_exact (exact_cokernel f)).2 _ ha
rsuffices ⟨c, rfl⟩ : ∃ c, kernel.lift g f w c = a
· simp [← Pseudoelement.comp_apply]
use b
apply_fun kernel.ι g
swap; · apply Pseudoelement.pseudo_injective_of_mono
simpa [← Pseudoelement.comp_apply]
instance : Epi (homologyCToK f g w) := by
apply Pseudoelement.epi_of_pseudo_surjective
intro a
let b := kernel.ι (cokernel.desc f g w) a
obtain ⟨c, hc⟩ : ∃ c, cokernel.π f c = b := by
apply Pseudoelement.pseudo_surjective_of_epi (cokernel.π f)
have : g c = 0 := by
rw [show g = cokernel.π f ≫ cokernel.desc f g w by simp, Pseudoelement.comp_apply, hc]
simp [b, ← Pseudoelement.comp_apply]
obtain ⟨d, hd⟩ : ∃ d, kernel.ι g d = c := by
apply (Pseudoelement.pseudo_exact_of_exact exact_kernel_ι).2 _ this
use cokernel.π (kernel.lift g f w) d
apply_fun kernel.ι (cokernel.desc f g w)
swap
· apply Pseudoelement.pseudo_injective_of_mono
simp only [← Pseudoelement.comp_apply, cokernel.π_desc, kernel.lift_ι]
simp only [Pseudoelement.comp_apply, hd, hc]
instance (w : f ≫ g = 0) : IsIso (homologyCToK f g w) :=
isIso_of_mono_of_epi _
end CategoryTheory.Abelian
/-- The homology associated to `f` and `g` is isomorphic to a kernel. -/
def homology'IsoKernelDesc : homology' f g w ≅ kernel (cokernel.desc f g w) :=
homology'IsoCokernelLift _ _ _ ≪≫ asIso (CategoryTheory.Abelian.homologyCToK _ _ _)
#align homology_iso_kernel_desc homology'IsoKernelDesc
namespace homology'
-- `homology'.π` is taken
/-- The canonical map from the kernel of `g` to the homology of `f` and `g`. -/
def π' : kernel g ⟶ homology' f g w :=
cokernel.π _ ≫ (homology'IsoCokernelLift _ _ _).inv
#align homology.π' homology'.π'
/-- The canonical map from the homology of `f` and `g` to the cokernel of `f`. -/
def ι : homology' f g w ⟶ cokernel f :=
(homology'IsoKernelDesc _ _ _).hom ≫ kernel.ι _
#align homology.ι homology'.ι
/-- Obtain a morphism from the homology, given a morphism from the kernel. -/
def desc' {W : A} (e : kernel g ⟶ W) (he : kernel.lift g f w ≫ e = 0) : homology' f g w ⟶ W :=
(homology'IsoCokernelLift _ _ _).hom ≫ cokernel.desc _ e he
#align homology.desc' homology'.desc'
/-- Obtain a morphism to the homology, given a morphism to the kernel. -/
def lift {W : A} (e : W ⟶ cokernel f) (he : e ≫ cokernel.desc f g w = 0) : W ⟶ homology' f g w :=
kernel.lift _ e he ≫ (homology'IsoKernelDesc _ _ _).inv
#align homology.lift homology'.lift
@[reassoc (attr := simp)]
theorem π'_desc' {W : A} (e : kernel g ⟶ W) (he : kernel.lift g f w ≫ e = 0) :
π' f g w ≫ desc' f g w e he = e := by
dsimp [π', desc']
simp
#align homology.π'_desc' homology'.π'_desc'
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Abelian/Homology.lean | 144 | 147 | theorem lift_ι {W : A} (e : W ⟶ cokernel f) (he : e ≫ cokernel.desc f g w = 0) :
lift f g w e he ≫ ι _ _ _ = e := by |
dsimp [ι, lift]
simp
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.Algebra.BigOperators.WithTop
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Data.ENNReal.Basic
#align_import data.real.ennreal from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520"
/-!
# Properties of addition, multiplication and subtraction on extended non-negative real numbers
In this file we prove elementary properties of algebraic operations on `ℝ≥0∞`, including addition,
multiplication, natural powers and truncated subtraction, as well as how these interact with the
order structure on `ℝ≥0∞`. Notably excluded from this list are inversion and division, the
definitions and properties of which can be found in `Data.ENNReal.Inv`.
Note: the definitions of the operations included in this file can be found in `Data.ENNReal.Basic`.
-/
open Set NNReal ENNReal
namespace ENNReal
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0}
section Mul
-- Porting note (#11215): TODO: generalize to `WithTop`
@[mono, gcongr]
| Mathlib/Data/ENNReal/Operations.lean | 33 | 41 | theorem mul_lt_mul (ac : a < c) (bd : b < d) : a * b < c * d := by |
rcases lt_iff_exists_nnreal_btwn.1 ac with ⟨a', aa', a'c⟩
lift a to ℝ≥0 using ne_top_of_lt aa'
rcases lt_iff_exists_nnreal_btwn.1 bd with ⟨b', bb', b'd⟩
lift b to ℝ≥0 using ne_top_of_lt bb'
norm_cast at *
calc
↑(a * b) < ↑(a' * b') := coe_lt_coe.2 (mul_lt_mul₀ aa' bb')
_ ≤ c * d := mul_le_mul' a'c.le b'd.le
|
/-
Copyright (c) 2023 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.ModelTheory.Syntax
import Mathlib.ModelTheory.Semantics
import Mathlib.Algebra.Ring.Equiv
/-!
# First Order Language of Rings
This file defines the first order language of rings, as well as defining instance of `Add`, `Mul`,
etc. on terms in the language.
## Main Definitions
* `FirstOrder.Language.ring` : the language of rings, with function symbols `+`, `*`, `-`, `0`, `1`
* `FirstOrder.Ring.CompatibleRing` : A class stating that a type is a `Language.ring.Structure`, and
that this structure is the same as the structure given by the classes `Add`, `Mul`, etc. already on
`R`.
* `FirstOrder.Ring.compatibleRingOfRing` : Given a type `R` with instances for each of the `Ring`
operations, make a `compatibleRing` instance.
## Implementation Notes
There are implementation difficulties with the model theory of rings caused by the fact that there
are two different ways to say that `R` is a `Ring`. We can say `Ring R` or
`Language.ring.Structure R` and `Theory.ring.Model R` (The theory of rings is not implemented yet).
The recommended way to use this library is to use the hypotheses `CompatibleRing R` and `Ring R`
on any theorem that requires both a `Ring` instance and a `Language.ring.Structure` instance
in order to state the theorem. To apply such a theorem to a ring `R` with a `Ring` instance,
use the tactic `let _ := compatibleRingOfRing R`. To apply the theorem to `K`
a `Language.ring.Structure K` instance and for example an instance of `Theory.field.Model K`,
you must add local instances with definitions like `ModelTheory.Field.fieldOfModelField K` and
`FirstOrder.Ring.compatibleRingOfModelField K`.
(in `Mathlib/ModelTheory/Algebra/Field/Basic.lean`), depending on the Theory.
-/
variable {α : Type*}
namespace FirstOrder
open FirstOrder
/-- The type of Ring functions, to be used in the definition of the language of rings.
It contains the operations (+,*,-,0,1) -/
inductive ringFunc : ℕ → Type
| add : ringFunc 2
| mul : ringFunc 2
| neg : ringFunc 1
| zero : ringFunc 0
| one : ringFunc 0
deriving DecidableEq
/-- The language of rings contains the operations (+,*,-,0,1) -/
def Language.ring : Language :=
{ Functions := ringFunc
Relations := fun _ => Empty }
namespace Ring
open ringFunc Language
instance (n : ℕ) : DecidableEq (Language.ring.Functions n) := by
dsimp [Language.ring]; infer_instance
instance (n : ℕ) : DecidableEq (Language.ring.Relations n) := by
dsimp [Language.ring]; infer_instance
/-- `RingFunc.add`, but with the defeq type `Language.ring.Functions 2` instead
of `RingFunc 2` -/
abbrev addFunc : Language.ring.Functions 2 := add
/-- `RingFunc.mul`, but with the defeq type `Language.ring.Functions 2` instead
of `RingFunc 2` -/
abbrev mulFunc : Language.ring.Functions 2 := mul
/-- `RingFunc.neg`, but with the defeq type `Language.ring.Functions 1` instead
of `RingFunc 1` -/
abbrev negFunc : Language.ring.Functions 1 := neg
/-- `RingFunc.zero`, but with the defeq type `Language.ring.Functions 0` instead
of `RingFunc 0` -/
abbrev zeroFunc : Language.ring.Functions 0 := zero
/-- `RingFunc.one`, but with the defeq type `Language.ring.Functions 0` instead
of `RingFunc 0` -/
abbrev oneFunc : Language.ring.Functions 0 := one
instance (α : Type*) : Zero (Language.ring.Term α) :=
{ zero := Constants.term zeroFunc }
theorem zero_def (α : Type*) : (0 : Language.ring.Term α) = Constants.term zeroFunc := rfl
instance (α : Type*) : One (Language.ring.Term α) :=
{ one := Constants.term oneFunc }
theorem one_def (α : Type*) : (1 : Language.ring.Term α) = Constants.term oneFunc := rfl
instance (α : Type*) : Add (Language.ring.Term α) :=
{ add := addFunc.apply₂ }
theorem add_def (α : Type*) (t₁ t₂ : Language.ring.Term α) :
t₁ + t₂ = addFunc.apply₂ t₁ t₂ := rfl
instance (α : Type*) : Mul (Language.ring.Term α) :=
{ mul := mulFunc.apply₂ }
theorem mul_def (α : Type*) (t₁ t₂ : Language.ring.Term α) :
t₁ * t₂ = mulFunc.apply₂ t₁ t₂ := rfl
instance (α : Type*) : Neg (Language.ring.Term α) :=
{ neg := negFunc.apply₁ }
theorem neg_def (α : Type*) (t : Language.ring.Term α) :
-t = negFunc.apply₁ t := rfl
instance : Fintype Language.ring.Symbols :=
⟨⟨Multiset.ofList
[Sum.inl ⟨2, .add⟩,
Sum.inl ⟨2, .mul⟩,
Sum.inl ⟨1, .neg⟩,
Sum.inl ⟨0, .zero⟩,
Sum.inl ⟨0, .one⟩], by
dsimp [Language.Symbols]; decide⟩, by
intro x
dsimp [Language.Symbols]
rcases x with ⟨_, f⟩ | ⟨_, f⟩
· cases f <;> decide
· cases f ⟩
@[simp]
theorem card_ring : card Language.ring = 5 := by
have : Fintype.card Language.ring.Symbols = 5 := rfl
simp [Language.card, this]
open Language ring Structure
/-- A Type `R` is a `CompatibleRing` if it is a structure for the language of rings and this
structure is the same as the structure already given on `R` by the classes `Add`, `Mul` etc.
It is recommended to use this type class as a hypothesis to any theorem whose statement
requires a type to have be both a `Ring` (or `Field` etc.) and a
`Language.ring.Structure` -/
/- This class does not extend `Add` etc, because this way it can be used in
combination with a `Ring`, or `Field` instance without having multiple different
`Add` structures on the Type. -/
class CompatibleRing (R : Type*) [Add R] [Mul R] [Neg R] [One R] [Zero R]
extends Language.ring.Structure R where
/-- Addition in the `Language.ring.Structure` is the same as the addition given by the
`Add` instance -/
funMap_add : ∀ x, funMap addFunc x = x 0 + x 1
/-- Multiplication in the `Language.ring.Structure` is the same as the multiplication given by the
`Mul` instance -/
funMap_mul : ∀ x, funMap mulFunc x = x 0 * x 1
/-- Negation in the `Language.ring.Structure` is the same as the negation given by the
`Neg` instance -/
funMap_neg : ∀ x, funMap negFunc x = -x 0
/-- The constant `0` in the `Language.ring.Structure` is the same as the constant given by the
`Zero` instance -/
funMap_zero : ∀ x, funMap (zeroFunc : Language.ring.Constants) x = 0
/-- The constant `1` in the `Language.ring.Structure` is the same as the constant given by the
`One` instance -/
funMap_one : ∀ x, funMap (oneFunc : Language.ring.Constants) x = 1
open CompatibleRing
attribute [simp] funMap_add funMap_mul funMap_neg funMap_zero funMap_one
section
variable {R : Type*} [Add R] [Mul R] [Neg R] [One R] [Zero R] [CompatibleRing R]
@[simp]
theorem realize_add (x y : ring.Term α) (v : α → R) :
Term.realize v (x + y) = Term.realize v x + Term.realize v y := by
simp [add_def, funMap_add]
@[simp]
| Mathlib/ModelTheory/Algebra/Ring/Basic.lean | 185 | 187 | theorem realize_mul (x y : ring.Term α) (v : α → R) :
Term.realize v (x * y) = Term.realize v x * Term.realize v y := by |
simp [mul_def, funMap_mul]
|
/-
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 -/
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 1,081 | 1,106 | 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) _
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker, Johan Commelin
-/
import Mathlib.Algebra.Polynomial.RingDivision
import Mathlib.RingTheory.Localization.FractionRing
#align_import data.polynomial.ring_division from "leanprover-community/mathlib"@"8efcf8022aac8e01df8d302dcebdbc25d6a886c8"
/-!
# Theory of univariate polynomials
We define the multiset of roots of a polynomial, and prove basic results about it.
## Main definitions
* `Polynomial.roots p`: The multiset containing all the roots of `p`, including their
multiplicities.
* `Polynomial.rootSet p E`: The set of distinct roots of `p` in an algebra `E`.
## Main statements
* `Polynomial.C_leadingCoeff_mul_prod_multiset_X_sub_C`: If a polynomial has as many roots as its
degree, it can be written as the product of its leading coefficient with `∏ (X - a)` where `a`
ranges through its roots.
-/
noncomputable section
namespace Polynomial
universe u v w z
variable {R : Type u} {S : Type v} {T : Type w} {a b : R} {n : ℕ}
section CommRing
variable [CommRing R] [IsDomain R] {p q : R[X]}
section Roots
open Multiset Finset
/-- `roots p` noncomputably gives a multiset containing all the roots of `p`,
including their multiplicities. -/
noncomputable def roots (p : R[X]) : Multiset R :=
haveI := Classical.decEq R
haveI := Classical.dec (p = 0)
if h : p = 0 then ∅ else Classical.choose (exists_multiset_roots h)
#align polynomial.roots Polynomial.roots
theorem roots_def [DecidableEq R] (p : R[X]) [Decidable (p = 0)] :
p.roots = if h : p = 0 then ∅ else Classical.choose (exists_multiset_roots h) := by
-- porting noteL `‹_›` doesn't work for instance arguments
rename_i iR ip0
obtain rfl := Subsingleton.elim iR (Classical.decEq R)
obtain rfl := Subsingleton.elim ip0 (Classical.dec (p = 0))
rfl
#align polynomial.roots_def Polynomial.roots_def
@[simp]
theorem roots_zero : (0 : R[X]).roots = 0 :=
dif_pos rfl
#align polynomial.roots_zero Polynomial.roots_zero
theorem card_roots (hp0 : p ≠ 0) : (Multiset.card (roots p) : WithBot ℕ) ≤ degree p := by
classical
unfold roots
rw [dif_neg hp0]
exact (Classical.choose_spec (exists_multiset_roots hp0)).1
#align polynomial.card_roots Polynomial.card_roots
theorem card_roots' (p : R[X]) : Multiset.card p.roots ≤ natDegree p := by
by_cases hp0 : p = 0
· simp [hp0]
exact WithBot.coe_le_coe.1 (le_trans (card_roots hp0) (le_of_eq <| degree_eq_natDegree hp0))
#align polynomial.card_roots' Polynomial.card_roots'
theorem card_roots_sub_C {p : R[X]} {a : R} (hp0 : 0 < degree p) :
(Multiset.card (p - C a).roots : WithBot ℕ) ≤ degree p :=
calc
(Multiset.card (p - C a).roots : WithBot ℕ) ≤ degree (p - C a) :=
card_roots <| mt sub_eq_zero.1 fun h => not_le_of_gt hp0 <| h.symm ▸ degree_C_le
_ = degree p := by rw [sub_eq_add_neg, ← C_neg]; exact degree_add_C hp0
set_option linter.uppercaseLean3 false in
#align polynomial.card_roots_sub_C Polynomial.card_roots_sub_C
theorem card_roots_sub_C' {p : R[X]} {a : R} (hp0 : 0 < degree p) :
Multiset.card (p - C a).roots ≤ natDegree p :=
WithBot.coe_le_coe.1
(le_trans (card_roots_sub_C hp0)
(le_of_eq <| degree_eq_natDegree fun h => by simp_all [lt_irrefl]))
set_option linter.uppercaseLean3 false in
#align polynomial.card_roots_sub_C' Polynomial.card_roots_sub_C'
@[simp]
theorem count_roots [DecidableEq R] (p : R[X]) : p.roots.count a = rootMultiplicity a p := by
classical
by_cases hp : p = 0
· simp [hp]
rw [roots_def, dif_neg hp]
exact (Classical.choose_spec (exists_multiset_roots hp)).2 a
#align polynomial.count_roots Polynomial.count_roots
@[simp]
theorem mem_roots' : a ∈ p.roots ↔ p ≠ 0 ∧ IsRoot p a := by
classical
rw [← count_pos, count_roots p, rootMultiplicity_pos']
#align polynomial.mem_roots' Polynomial.mem_roots'
theorem mem_roots (hp : p ≠ 0) : a ∈ p.roots ↔ IsRoot p a :=
mem_roots'.trans <| and_iff_right hp
#align polynomial.mem_roots Polynomial.mem_roots
theorem ne_zero_of_mem_roots (h : a ∈ p.roots) : p ≠ 0 :=
(mem_roots'.1 h).1
#align polynomial.ne_zero_of_mem_roots Polynomial.ne_zero_of_mem_roots
theorem isRoot_of_mem_roots (h : a ∈ p.roots) : IsRoot p a :=
(mem_roots'.1 h).2
#align polynomial.is_root_of_mem_roots Polynomial.isRoot_of_mem_roots
-- Porting note: added during port.
lemma mem_roots_iff_aeval_eq_zero {x : R} (w : p ≠ 0) : x ∈ roots p ↔ aeval x p = 0 := by
rw [mem_roots w, IsRoot.def, aeval_def, eval₂_eq_eval_map]
simp
theorem card_le_degree_of_subset_roots {p : R[X]} {Z : Finset R} (h : Z.val ⊆ p.roots) :
Z.card ≤ p.natDegree :=
(Multiset.card_le_card (Finset.val_le_iff_val_subset.2 h)).trans (Polynomial.card_roots' p)
#align polynomial.card_le_degree_of_subset_roots Polynomial.card_le_degree_of_subset_roots
theorem finite_setOf_isRoot {p : R[X]} (hp : p ≠ 0) : Set.Finite { x | IsRoot p x } := by
classical
simpa only [← Finset.setOf_mem, Multiset.mem_toFinset, mem_roots hp]
using p.roots.toFinset.finite_toSet
#align polynomial.finite_set_of_is_root Polynomial.finite_setOf_isRoot
theorem eq_zero_of_infinite_isRoot (p : R[X]) (h : Set.Infinite { x | IsRoot p x }) : p = 0 :=
not_imp_comm.mp finite_setOf_isRoot h
#align polynomial.eq_zero_of_infinite_is_root Polynomial.eq_zero_of_infinite_isRoot
theorem exists_max_root [LinearOrder R] (p : R[X]) (hp : p ≠ 0) : ∃ x₀, ∀ x, p.IsRoot x → x ≤ x₀ :=
Set.exists_upper_bound_image _ _ <| finite_setOf_isRoot hp
#align polynomial.exists_max_root Polynomial.exists_max_root
theorem exists_min_root [LinearOrder R] (p : R[X]) (hp : p ≠ 0) : ∃ x₀, ∀ x, p.IsRoot x → x₀ ≤ x :=
Set.exists_lower_bound_image _ _ <| finite_setOf_isRoot hp
#align polynomial.exists_min_root Polynomial.exists_min_root
theorem eq_of_infinite_eval_eq (p q : R[X]) (h : Set.Infinite { x | eval x p = eval x q }) :
p = q := by
rw [← sub_eq_zero]
apply eq_zero_of_infinite_isRoot
simpa only [IsRoot, eval_sub, sub_eq_zero]
#align polynomial.eq_of_infinite_eval_eq Polynomial.eq_of_infinite_eval_eq
theorem roots_mul {p q : R[X]} (hpq : p * q ≠ 0) : (p * q).roots = p.roots + q.roots := by
classical
exact Multiset.ext.mpr fun r => by
rw [count_add, count_roots, count_roots, count_roots, rootMultiplicity_mul hpq]
#align polynomial.roots_mul Polynomial.roots_mul
theorem roots.le_of_dvd (h : q ≠ 0) : p ∣ q → roots p ≤ roots q := by
rintro ⟨k, rfl⟩
exact Multiset.le_iff_exists_add.mpr ⟨k.roots, roots_mul h⟩
#align polynomial.roots.le_of_dvd Polynomial.roots.le_of_dvd
theorem mem_roots_sub_C' {p : R[X]} {a x : R} : x ∈ (p - C a).roots ↔ p ≠ C a ∧ p.eval x = a := by
rw [mem_roots', IsRoot.def, sub_ne_zero, eval_sub, sub_eq_zero, eval_C]
set_option linter.uppercaseLean3 false in
#align polynomial.mem_roots_sub_C' Polynomial.mem_roots_sub_C'
theorem mem_roots_sub_C {p : R[X]} {a x : R} (hp0 : 0 < degree p) :
x ∈ (p - C a).roots ↔ p.eval x = a :=
mem_roots_sub_C'.trans <| and_iff_right fun hp => hp0.not_le <| hp.symm ▸ degree_C_le
set_option linter.uppercaseLean3 false in
#align polynomial.mem_roots_sub_C Polynomial.mem_roots_sub_C
@[simp]
theorem roots_X_sub_C (r : R) : roots (X - C r) = {r} := by
classical
ext s
rw [count_roots, rootMultiplicity_X_sub_C, count_singleton]
set_option linter.uppercaseLean3 false in
#align polynomial.roots_X_sub_C Polynomial.roots_X_sub_C
@[simp]
theorem roots_X : roots (X : R[X]) = {0} := by rw [← roots_X_sub_C, C_0, sub_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.roots_X Polynomial.roots_X
@[simp]
theorem roots_C (x : R) : (C x).roots = 0 := by
classical exact
if H : x = 0 then by rw [H, C_0, roots_zero]
else
Multiset.ext.mpr fun r => (by
rw [count_roots, count_zero, rootMultiplicity_eq_zero (not_isRoot_C _ _ H)])
set_option linter.uppercaseLean3 false in
#align polynomial.roots_C Polynomial.roots_C
@[simp]
theorem roots_one : (1 : R[X]).roots = ∅ :=
roots_C 1
#align polynomial.roots_one Polynomial.roots_one
@[simp]
theorem roots_C_mul (p : R[X]) (ha : a ≠ 0) : (C a * p).roots = p.roots := by
by_cases hp : p = 0 <;>
simp only [roots_mul, *, Ne, mul_eq_zero, C_eq_zero, or_self_iff, not_false_iff, roots_C,
zero_add, mul_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.roots_C_mul Polynomial.roots_C_mul
@[simp]
theorem roots_smul_nonzero (p : R[X]) (ha : a ≠ 0) : (a • p).roots = p.roots := by
rw [smul_eq_C_mul, roots_C_mul _ ha]
#align polynomial.roots_smul_nonzero Polynomial.roots_smul_nonzero
@[simp]
lemma roots_neg (p : R[X]) : (-p).roots = p.roots := by
rw [← neg_one_smul R p, roots_smul_nonzero p (neg_ne_zero.mpr one_ne_zero)]
theorem roots_list_prod (L : List R[X]) :
(0 : R[X]) ∉ L → L.prod.roots = (L : Multiset R[X]).bind roots :=
List.recOn L (fun _ => roots_one) fun hd tl ih H => by
rw [List.mem_cons, not_or] at H
rw [List.prod_cons, roots_mul (mul_ne_zero (Ne.symm H.1) <| List.prod_ne_zero H.2), ←
Multiset.cons_coe, Multiset.cons_bind, ih H.2]
#align polynomial.roots_list_prod Polynomial.roots_list_prod
theorem roots_multiset_prod (m : Multiset R[X]) : (0 : R[X]) ∉ m → m.prod.roots = m.bind roots := by
rcases m with ⟨L⟩
simpa only [Multiset.prod_coe, quot_mk_to_coe''] using roots_list_prod L
#align polynomial.roots_multiset_prod Polynomial.roots_multiset_prod
theorem roots_prod {ι : Type*} (f : ι → R[X]) (s : Finset ι) :
s.prod f ≠ 0 → (s.prod f).roots = s.val.bind fun i => roots (f i) := by
rcases s with ⟨m, hm⟩
simpa [Multiset.prod_eq_zero_iff, Multiset.bind_map] using roots_multiset_prod (m.map f)
#align polynomial.roots_prod Polynomial.roots_prod
@[simp]
theorem roots_pow (p : R[X]) (n : ℕ) : (p ^ n).roots = n • p.roots := by
induction' n with n ihn
· rw [pow_zero, roots_one, zero_smul, empty_eq_zero]
· rcases eq_or_ne p 0 with (rfl | hp)
· rw [zero_pow n.succ_ne_zero, roots_zero, smul_zero]
· rw [pow_succ, roots_mul (mul_ne_zero (pow_ne_zero _ hp) hp), ihn, add_smul, one_smul]
#align polynomial.roots_pow Polynomial.roots_pow
theorem roots_X_pow (n : ℕ) : (X ^ n : R[X]).roots = n • ({0} : Multiset R) := by
rw [roots_pow, roots_X]
set_option linter.uppercaseLean3 false in
#align polynomial.roots_X_pow Polynomial.roots_X_pow
theorem roots_C_mul_X_pow (ha : a ≠ 0) (n : ℕ) :
Polynomial.roots (C a * X ^ n) = n • ({0} : Multiset R) := by
rw [roots_C_mul _ ha, roots_X_pow]
set_option linter.uppercaseLean3 false in
#align polynomial.roots_C_mul_X_pow Polynomial.roots_C_mul_X_pow
@[simp]
theorem roots_monomial (ha : a ≠ 0) (n : ℕ) : (monomial n a).roots = n • ({0} : Multiset R) := by
rw [← C_mul_X_pow_eq_monomial, roots_C_mul_X_pow ha]
#align polynomial.roots_monomial Polynomial.roots_monomial
theorem roots_prod_X_sub_C (s : Finset R) : (s.prod fun a => X - C a).roots = s.val := by
apply (roots_prod (fun a => X - C a) s ?_).trans
· simp_rw [roots_X_sub_C]
rw [Multiset.bind_singleton, Multiset.map_id']
· refine prod_ne_zero_iff.mpr (fun a _ => X_sub_C_ne_zero a)
set_option linter.uppercaseLean3 false in
#align polynomial.roots_prod_X_sub_C Polynomial.roots_prod_X_sub_C
@[simp]
theorem roots_multiset_prod_X_sub_C (s : Multiset R) : (s.map fun a => X - C a).prod.roots = s := by
rw [roots_multiset_prod, Multiset.bind_map]
· simp_rw [roots_X_sub_C]
rw [Multiset.bind_singleton, Multiset.map_id']
· rw [Multiset.mem_map]
rintro ⟨a, -, h⟩
exact X_sub_C_ne_zero a h
set_option linter.uppercaseLean3 false in
#align polynomial.roots_multiset_prod_X_sub_C Polynomial.roots_multiset_prod_X_sub_C
theorem card_roots_X_pow_sub_C {n : ℕ} (hn : 0 < n) (a : R) :
Multiset.card (roots ((X : R[X]) ^ n - C a)) ≤ n :=
WithBot.coe_le_coe.1 <|
calc
(Multiset.card (roots ((X : R[X]) ^ n - C a)) : WithBot ℕ) ≤ degree ((X : R[X]) ^ n - C a) :=
card_roots (X_pow_sub_C_ne_zero hn a)
_ = n := degree_X_pow_sub_C hn a
set_option linter.uppercaseLean3 false in
#align polynomial.card_roots_X_pow_sub_C Polynomial.card_roots_X_pow_sub_C
section NthRoots
/-- `nthRoots n a` noncomputably returns the solutions to `x ^ n = a`-/
def nthRoots (n : ℕ) (a : R) : Multiset R :=
roots ((X : R[X]) ^ n - C a)
#align polynomial.nth_roots Polynomial.nthRoots
@[simp]
theorem mem_nthRoots {n : ℕ} (hn : 0 < n) {a x : R} : x ∈ nthRoots n a ↔ x ^ n = a := by
rw [nthRoots, mem_roots (X_pow_sub_C_ne_zero hn a), IsRoot.def, eval_sub, eval_C, eval_pow,
eval_X, sub_eq_zero]
#align polynomial.mem_nth_roots Polynomial.mem_nthRoots
@[simp]
theorem nthRoots_zero (r : R) : nthRoots 0 r = 0 := by
simp only [empty_eq_zero, pow_zero, nthRoots, ← C_1, ← C_sub, roots_C]
#align polynomial.nth_roots_zero Polynomial.nthRoots_zero
@[simp]
theorem nthRoots_zero_right {R} [CommRing R] [IsDomain R] (n : ℕ) :
nthRoots n (0 : R) = Multiset.replicate n 0 := by
rw [nthRoots, C.map_zero, sub_zero, roots_pow, roots_X, Multiset.nsmul_singleton]
theorem card_nthRoots (n : ℕ) (a : R) : Multiset.card (nthRoots n a) ≤ n := by
classical exact
(if hn : n = 0 then
if h : (X : R[X]) ^ n - C a = 0 then by
simp [Nat.zero_le, nthRoots, roots, h, dif_pos rfl, empty_eq_zero, Multiset.card_zero]
else
WithBot.coe_le_coe.1
(le_trans (card_roots h)
(by
rw [hn, pow_zero, ← C_1, ← RingHom.map_sub]
exact degree_C_le))
else by
rw [← Nat.cast_le (α := WithBot ℕ)]
rw [← degree_X_pow_sub_C (Nat.pos_of_ne_zero hn) a]
exact card_roots (X_pow_sub_C_ne_zero (Nat.pos_of_ne_zero hn) a))
#align polynomial.card_nth_roots Polynomial.card_nthRoots
@[simp]
theorem nthRoots_two_eq_zero_iff {r : R} : nthRoots 2 r = 0 ↔ ¬IsSquare r := by
simp_rw [isSquare_iff_exists_sq, eq_zero_iff_forall_not_mem, mem_nthRoots (by norm_num : 0 < 2),
← not_exists, eq_comm]
#align polynomial.nth_roots_two_eq_zero_iff Polynomial.nthRoots_two_eq_zero_iff
/-- The multiset `nthRoots ↑n (1 : R)` as a Finset. -/
def nthRootsFinset (n : ℕ) (R : Type*) [CommRing R] [IsDomain R] : Finset R :=
haveI := Classical.decEq R
Multiset.toFinset (nthRoots n (1 : R))
#align polynomial.nth_roots_finset Polynomial.nthRootsFinset
-- Porting note (#10756): new lemma
lemma nthRootsFinset_def (n : ℕ) (R : Type*) [CommRing R] [IsDomain R] [DecidableEq R] :
nthRootsFinset n R = Multiset.toFinset (nthRoots n (1 : R)) := by
unfold nthRootsFinset
convert rfl
@[simp]
theorem mem_nthRootsFinset {n : ℕ} (h : 0 < n) {x : R} :
x ∈ nthRootsFinset n R ↔ x ^ (n : ℕ) = 1 := by
classical
rw [nthRootsFinset_def, mem_toFinset, mem_nthRoots h]
#align polynomial.mem_nth_roots_finset Polynomial.mem_nthRootsFinset
@[simp]
theorem nthRootsFinset_zero : nthRootsFinset 0 R = ∅ := by classical simp [nthRootsFinset_def]
#align polynomial.nth_roots_finset_zero Polynomial.nthRootsFinset_zero
theorem mul_mem_nthRootsFinset
{η₁ η₂ : R} (hη₁ : η₁ ∈ nthRootsFinset n R) (hη₂ : η₂ ∈ nthRootsFinset n R) :
η₁ * η₂ ∈ nthRootsFinset n R := by
cases n with
| zero =>
simp only [Nat.zero_eq, nthRootsFinset_zero, not_mem_empty] at hη₁
| succ n =>
rw [mem_nthRootsFinset n.succ_pos] at hη₁ hη₂ ⊢
rw [mul_pow, hη₁, hη₂, one_mul]
theorem ne_zero_of_mem_nthRootsFinset {η : R} (hη : η ∈ nthRootsFinset n R) : η ≠ 0 := by
nontriviality R
rintro rfl
cases n with
| zero =>
simp only [Nat.zero_eq, nthRootsFinset_zero, not_mem_empty] at hη
| succ n =>
rw [mem_nthRootsFinset n.succ_pos, zero_pow n.succ_ne_zero] at hη
exact zero_ne_one hη
| Mathlib/Algebra/Polynomial/Roots.lean | 390 | 391 | theorem one_mem_nthRootsFinset (hn : 0 < n) : 1 ∈ nthRootsFinset n R := by |
rw [mem_nthRootsFinset hn, one_pow]
|
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Ring.Divisibility.Lemmas
import Mathlib.Algebra.Lie.Nilpotent
import Mathlib.Algebra.Lie.Engel
import Mathlib.LinearAlgebra.Eigenspace.Triangularizable
import Mathlib.RingTheory.Artinian
import Mathlib.LinearAlgebra.Trace
import Mathlib.LinearAlgebra.FreeModule.PID
#align_import algebra.lie.weights from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1"
/-!
# Weight spaces of Lie modules of nilpotent Lie algebras
Just as a key tool when studying the behaviour of a linear operator is to decompose the space on
which it acts into a sum of (generalised) eigenspaces, a key tool when studying a representation `M`
of Lie algebra `L` is to decompose `M` into a sum of simultaneous eigenspaces of `x` as `x` ranges
over `L`. These simultaneous generalised eigenspaces are known as the weight spaces of `M`.
When `L` is nilpotent, it follows from the binomial theorem that weight spaces are Lie submodules.
Basic definitions and properties of the above ideas are provided in this file.
## Main definitions
* `LieModule.weightSpaceOf`
* `LieModule.weightSpace`
* `LieModule.Weight`
* `LieModule.posFittingCompOf`
* `LieModule.posFittingComp`
* `LieModule.iSup_ucs_eq_weightSpace_zero`
* `LieModule.iInf_lowerCentralSeries_eq_posFittingComp`
* `LieModule.isCompl_weightSpace_zero_posFittingComp`
* `LieModule.independent_weightSpace`
* `LieModule.iSup_weightSpace_eq_top`
## References
* [N. Bourbaki, *Lie Groups and Lie Algebras, Chapters 7--9*](bourbaki1975b)
## Tags
lie character, eigenvalue, eigenspace, weight, weight vector, root, root vector
-/
variable {K R L M : Type*} [CommRing R] [LieRing L] [LieAlgebra R L] [LieAlgebra.IsNilpotent R L]
[AddCommGroup M] [Module R M] [LieRingModule L M] [LieModule R L M]
namespace LieModule
open Set Function LieAlgebra TensorProduct TensorProduct.LieModule
open scoped TensorProduct
section notation_weightSpaceOf
/-- Until we define `LieModule.weightSpaceOf`, it is useful to have some notation as follows: -/
local notation3 "𝕎("M", " χ", " x")" => (toEnd R L M x).maxGenEigenspace χ
/-- See also `bourbaki1975b` Chapter VII §1.1, Proposition 2 (ii). -/
protected theorem weight_vector_multiplication (M₁ M₂ M₃ : Type*)
[AddCommGroup M₁] [Module R M₁] [LieRingModule L M₁] [LieModule R L M₁] [AddCommGroup M₂]
[Module R M₂] [LieRingModule L M₂] [LieModule R L M₂] [AddCommGroup M₃] [Module R M₃]
[LieRingModule L M₃] [LieModule R L M₃] (g : M₁ ⊗[R] M₂ →ₗ⁅R,L⁆ M₃) (χ₁ χ₂ : R) (x : L) :
LinearMap.range ((g : M₁ ⊗[R] M₂ →ₗ[R] M₃).comp (mapIncl 𝕎(M₁, χ₁, x) 𝕎(M₂, χ₂, x))) ≤
𝕎(M₃, χ₁ + χ₂, x) := by
-- Unpack the statement of the goal.
intro m₃
simp only [TensorProduct.mapIncl, LinearMap.mem_range, LinearMap.coe_comp,
LieModuleHom.coe_toLinearMap, Function.comp_apply, Pi.add_apply, exists_imp,
Module.End.mem_maxGenEigenspace]
rintro t rfl
-- Set up some notation.
let F : Module.End R M₃ := toEnd R L M₃ x - (χ₁ + χ₂) • ↑1
-- The goal is linear in `t` so use induction to reduce to the case that `t` is a pure tensor.
refine t.induction_on ?_ ?_ ?_
· use 0; simp only [LinearMap.map_zero, LieModuleHom.map_zero]
swap
· rintro t₁ t₂ ⟨k₁, hk₁⟩ ⟨k₂, hk₂⟩; use max k₁ k₂
simp only [LieModuleHom.map_add, LinearMap.map_add,
LinearMap.pow_map_zero_of_le (le_max_left k₁ k₂) hk₁,
LinearMap.pow_map_zero_of_le (le_max_right k₁ k₂) hk₂, add_zero]
-- Now the main argument: pure tensors.
rintro ⟨m₁, hm₁⟩ ⟨m₂, hm₂⟩
change ∃ k, (F ^ k) ((g : M₁ ⊗[R] M₂ →ₗ[R] M₃) (m₁ ⊗ₜ m₂)) = (0 : M₃)
-- Eliminate `g` from the picture.
let f₁ : Module.End R (M₁ ⊗[R] M₂) := (toEnd R L M₁ x - χ₁ • ↑1).rTensor M₂
let f₂ : Module.End R (M₁ ⊗[R] M₂) := (toEnd R L M₂ x - χ₂ • ↑1).lTensor M₁
have h_comm_square : F ∘ₗ ↑g = (g : M₁ ⊗[R] M₂ →ₗ[R] M₃).comp (f₁ + f₂) := by
ext m₁ m₂;
simp only [f₁, f₂, F, ← g.map_lie x (m₁ ⊗ₜ m₂), add_smul, sub_tmul, tmul_sub, smul_tmul,
lie_tmul_right, tmul_smul, toEnd_apply_apply, LieModuleHom.map_smul,
LinearMap.one_apply, LieModuleHom.coe_toLinearMap, LinearMap.smul_apply, Function.comp_apply,
LinearMap.coe_comp, LinearMap.rTensor_tmul, LieModuleHom.map_add, LinearMap.add_apply,
LieModuleHom.map_sub, LinearMap.sub_apply, LinearMap.lTensor_tmul,
AlgebraTensorModule.curry_apply, TensorProduct.curry_apply, LinearMap.toFun_eq_coe,
LinearMap.coe_restrictScalars]
abel
rsuffices ⟨k, hk⟩ : ∃ k : ℕ, ((f₁ + f₂) ^ k) (m₁ ⊗ₜ m₂) = 0
· use k
change (F ^ k) (g.toLinearMap (m₁ ⊗ₜ[R] m₂)) = 0
rw [← LinearMap.comp_apply, LinearMap.commute_pow_left_of_commute h_comm_square,
LinearMap.comp_apply, hk, LinearMap.map_zero]
-- Unpack the information we have about `m₁`, `m₂`.
simp only [Module.End.mem_maxGenEigenspace] at hm₁ hm₂
obtain ⟨k₁, hk₁⟩ := hm₁
obtain ⟨k₂, hk₂⟩ := hm₂
have hf₁ : (f₁ ^ k₁) (m₁ ⊗ₜ m₂) = 0 := by
simp only [f₁, hk₁, zero_tmul, LinearMap.rTensor_tmul, LinearMap.rTensor_pow]
have hf₂ : (f₂ ^ k₂) (m₁ ⊗ₜ m₂) = 0 := by
simp only [f₂, hk₂, tmul_zero, LinearMap.lTensor_tmul, LinearMap.lTensor_pow]
-- It's now just an application of the binomial theorem.
use k₁ + k₂ - 1
have hf_comm : Commute f₁ f₂ := by
ext m₁ m₂
simp only [f₁, f₂, LinearMap.mul_apply, LinearMap.rTensor_tmul, LinearMap.lTensor_tmul,
AlgebraTensorModule.curry_apply, LinearMap.toFun_eq_coe, LinearMap.lTensor_tmul,
TensorProduct.curry_apply, LinearMap.coe_restrictScalars]
rw [hf_comm.add_pow']
simp only [TensorProduct.mapIncl, Submodule.subtype_apply, Finset.sum_apply, Submodule.coe_mk,
LinearMap.coeFn_sum, TensorProduct.map_tmul, LinearMap.smul_apply]
-- The required sum is zero because each individual term is zero.
apply Finset.sum_eq_zero
rintro ⟨i, j⟩ hij
-- Eliminate the binomial coefficients from the picture.
suffices (f₁ ^ i * f₂ ^ j) (m₁ ⊗ₜ m₂) = 0 by rw [this]; apply smul_zero
-- Finish off with appropriate case analysis.
cases' Nat.le_or_le_of_add_eq_add_pred (Finset.mem_antidiagonal.mp hij) with hi hj
· rw [(hf_comm.pow_pow i j).eq, LinearMap.mul_apply, LinearMap.pow_map_zero_of_le hi hf₁,
LinearMap.map_zero]
· rw [LinearMap.mul_apply, LinearMap.pow_map_zero_of_le hj hf₂, LinearMap.map_zero]
lemma lie_mem_maxGenEigenspace_toEnd
{χ₁ χ₂ : R} {x y : L} {m : M} (hy : y ∈ 𝕎(L, χ₁, x)) (hm : m ∈ 𝕎(M, χ₂, x)) :
⁅y, m⁆ ∈ 𝕎(M, χ₁ + χ₂, x) := by
apply LieModule.weight_vector_multiplication L M M (toModuleHom R L M) χ₁ χ₂
simp only [LieModuleHom.coe_toLinearMap, Function.comp_apply, LinearMap.coe_comp,
TensorProduct.mapIncl, LinearMap.mem_range]
use ⟨y, hy⟩ ⊗ₜ ⟨m, hm⟩
simp only [Submodule.subtype_apply, toModuleHom_apply, TensorProduct.map_tmul]
variable (M)
/-- If `M` is a representation of a nilpotent Lie algebra `L`, `χ` is a scalar, and `x : L`, then
`weightSpaceOf M χ x` is the maximal generalized `χ`-eigenspace of the action of `x` on `M`.
It is a Lie submodule because `L` is nilpotent. -/
def weightSpaceOf (χ : R) (x : L) : LieSubmodule R L M :=
{ 𝕎(M, χ, x) with
lie_mem := by
intro y m hm
simp only [AddSubsemigroup.mem_carrier, AddSubmonoid.mem_toSubsemigroup,
Submodule.mem_toAddSubmonoid] at hm ⊢
rw [← zero_add χ]
exact lie_mem_maxGenEigenspace_toEnd (by simp) hm }
end notation_weightSpaceOf
variable (M)
theorem mem_weightSpaceOf (χ : R) (x : L) (m : M) :
m ∈ weightSpaceOf M χ x ↔ ∃ k : ℕ, ((toEnd R L M x - χ • ↑1) ^ k) m = 0 := by
simp [weightSpaceOf]
theorem coe_weightSpaceOf_zero (x : L) :
↑(weightSpaceOf M (0 : R) x) = ⨆ k, LinearMap.ker (toEnd R L M x ^ k) := by
simp [weightSpaceOf, Module.End.maxGenEigenspace]
/-- If `M` is a representation of a nilpotent Lie algebra `L` and `χ : L → R` is a family of
scalars, then `weightSpace M χ` is the intersection of the maximal generalized `χ x`-eigenspaces of
the action of `x` on `M` as `x` ranges over `L`.
It is a Lie submodule because `L` is nilpotent. -/
def weightSpace (χ : L → R) : LieSubmodule R L M :=
⨅ x, weightSpaceOf M (χ x) x
theorem mem_weightSpace (χ : L → R) (m : M) :
m ∈ weightSpace M χ ↔ ∀ x, ∃ k : ℕ, ((toEnd R L M x - χ x • ↑1) ^ k) m = 0 := by
simp [weightSpace, mem_weightSpaceOf]
lemma weightSpace_le_weightSpaceOf (x : L) (χ : L → R) :
weightSpace M χ ≤ weightSpaceOf M (χ x) x :=
iInf_le _ x
variable (R L) in
/-- A weight of a Lie module is a map `L → R` such that the corresponding weight space is
non-trivial. -/
structure Weight where
/-- The family of eigenvalues corresponding to a weight. -/
toFun : L → R
weightSpace_ne_bot' : weightSpace M toFun ≠ ⊥
namespace Weight
instance instFunLike : FunLike (Weight R L M) L R where
coe χ := χ.1
coe_injective' χ₁ χ₂ h := by cases χ₁; cases χ₂; simp_all
@[simp] lemma coe_weight_mk (χ : L → R) (h) :
(↑(⟨χ, h⟩ : Weight R L M) : L → R) = χ :=
rfl
lemma weightSpace_ne_bot (χ : Weight R L M) : weightSpace M χ ≠ ⊥ := χ.weightSpace_ne_bot'
variable {M}
@[ext] lemma ext {χ₁ χ₂ : Weight R L M} (h : ∀ x, χ₁ x = χ₂ x) : χ₁ = χ₂ := by
cases' χ₁ with f₁ _; cases' χ₂ with f₂ _; aesop
lemma ext_iff {χ₁ χ₂ : Weight R L M} : (χ₁ : L → R) = χ₂ ↔ χ₁ = χ₂ := by aesop
lemma exists_ne_zero (χ : Weight R L M) :
∃ x ∈ weightSpace M χ, x ≠ 0 := by
simpa [LieSubmodule.eq_bot_iff] using χ.weightSpace_ne_bot
instance [Subsingleton M] : IsEmpty (Weight R L M) :=
⟨fun h ↦ h.2 (Subsingleton.elim _ _)⟩
instance [Nontrivial (weightSpace M (0 : L → R))] : Zero (Weight R L M) :=
⟨0, fun e ↦ not_nontrivial (⊥ : LieSubmodule R L M) (e ▸ ‹_›)⟩
@[simp]
lemma coe_zero [Nontrivial (weightSpace M (0 : L → R))] : ((0 : Weight R L M) : L → R) = 0 := rfl
lemma zero_apply [Nontrivial (weightSpace M (0 : L → R))] (x) : (0 : Weight R L M) x = 0 := rfl
/-- The proposition that a weight of a Lie module is zero.
We make this definition because we cannot define a `Zero (Weight R L M)` instance since the weight
space of the zero function can be trivial. -/
def IsZero (χ : Weight R L M) := (χ : L → R) = 0
@[simp] lemma IsZero.eq {χ : Weight R L M} (hχ : χ.IsZero) : (χ : L → R) = 0 := hχ
@[simp] lemma coe_eq_zero_iff (χ : Weight R L M) : (χ : L → R) = 0 ↔ χ.IsZero := Iff.rfl
lemma isZero_iff_eq_zero [Nontrivial (weightSpace M (0 : L → R))] {χ : Weight R L M} :
χ.IsZero ↔ χ = 0 := ext_iff (χ₂ := 0)
lemma isZero_zero [Nontrivial (weightSpace M (0 : L → R))] : IsZero (0 : Weight R L M) := rfl
/-- The proposition that a weight of a Lie module is non-zero. -/
abbrev IsNonZero (χ : Weight R L M) := ¬ IsZero (χ : Weight R L M)
lemma isNonZero_iff_ne_zero [Nontrivial (weightSpace M (0 : L → R))] {χ : Weight R L M} :
χ.IsNonZero ↔ χ ≠ 0 := isZero_iff_eq_zero.not
variable (R L M) in
/-- The set of weights is equivalent to a subtype. -/
def equivSetOf : Weight R L M ≃ {χ : L → R | weightSpace M χ ≠ ⊥} where
toFun w := ⟨w.1, w.2⟩
invFun w := ⟨w.1, w.2⟩
left_inv w := by simp
right_inv w := by simp
lemma weightSpaceOf_ne_bot (χ : Weight R L M) (x : L) :
weightSpaceOf M (χ x) x ≠ ⊥ := by
have : ⨅ x, weightSpaceOf M (χ x) x ≠ ⊥ := χ.weightSpace_ne_bot
contrapose! this
rw [eq_bot_iff]
exact le_of_le_of_eq (iInf_le _ _) this
lemma hasEigenvalueAt (χ : Weight R L M) (x : L) :
(toEnd R L M x).HasEigenvalue (χ x) := by
obtain ⟨k : ℕ, hk : (toEnd R L M x).genEigenspace (χ x) k ≠ ⊥⟩ := by
simpa [Module.End.maxGenEigenspace, weightSpaceOf] using χ.weightSpaceOf_ne_bot x
exact Module.End.hasEigenvalue_of_hasGenEigenvalue hk
lemma apply_eq_zero_of_isNilpotent [NoZeroSMulDivisors R M] [IsReduced R]
(x : L) (h : _root_.IsNilpotent (toEnd R L M x)) (χ : Weight R L M) :
χ x = 0 :=
((χ.hasEigenvalueAt x).isNilpotent_of_isNilpotent h).eq_zero
end Weight
/-- See also the more useful form `LieModule.zero_weightSpace_eq_top_of_nilpotent`. -/
@[simp]
theorem zero_weightSpace_eq_top_of_nilpotent' [IsNilpotent R L M] :
weightSpace M (0 : L → R) = ⊤ := by
ext
simp [weightSpace, weightSpaceOf]
#align lie_module.zero_weight_space_eq_top_of_nilpotent' LieModule.zero_weightSpace_eq_top_of_nilpotent'
theorem coe_weightSpace_of_top (χ : L → R) :
(weightSpace M (χ ∘ (⊤ : LieSubalgebra R L).incl) : Submodule R M) = weightSpace M χ := by
ext m
simp only [mem_weightSpace, LieSubmodule.mem_coeSubmodule, Subtype.forall]
apply forall_congr'
simp
#align lie_module.coe_weight_space_of_top LieModule.coe_weightSpace_of_top
@[simp]
theorem zero_weightSpace_eq_top_of_nilpotent [IsNilpotent R L M] :
weightSpace M (0 : (⊤ : LieSubalgebra R L) → R) = ⊤ := by
ext m
simp only [mem_weightSpace, Pi.zero_apply, zero_smul, sub_zero, Subtype.forall, forall_true_left,
LieSubalgebra.toEnd_mk, LieSubalgebra.mem_top, LieSubmodule.mem_top, iff_true]
intro x
obtain ⟨k, hk⟩ := exists_forall_pow_toEnd_eq_zero R L M
exact ⟨k, by simp [hk x]⟩
#align lie_module.zero_weight_space_eq_top_of_nilpotent LieModule.zero_weightSpace_eq_top_of_nilpotent
theorem exists_weightSpace_le_ker_of_isNoetherian [IsNoetherian R M] (χ : L → R) (x : L) :
∃ k : ℕ,
weightSpace M χ ≤ LinearMap.ker ((toEnd R L M x - algebraMap R _ (χ x)) ^ k) := by
use (toEnd R L M x).maxGenEigenspaceIndex (χ x)
intro m hm
replace hm : m ∈ (toEnd R L M x).maxGenEigenspace (χ x) :=
weightSpace_le_weightSpaceOf M x χ hm
rwa [Module.End.maxGenEigenspace_eq] at hm
variable (R) in
| Mathlib/Algebra/Lie/Weights/Basic.lean | 316 | 319 | theorem exists_weightSpace_zero_le_ker_of_isNoetherian
[IsNoetherian R M] (x : L) :
∃ k : ℕ, weightSpace M (0 : L → R) ≤ LinearMap.ker (toEnd R L M x ^ k) := by |
simpa using exists_weightSpace_le_ker_of_isNoetherian M (0 : L → R) x
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.MonoidAlgebra.Degree
import Mathlib.Algebra.MvPolynomial.Rename
import Mathlib.Algebra.Order.BigOperators.Ring.Finset
#align_import data.mv_polynomial.variables from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Degrees of polynomials
This file establishes many results about the degree of a multivariate polynomial.
The *degree set* of a polynomial $P \in R[X]$ is a `Multiset` containing, for each $x$ in the
variable set, $n$ copies of $x$, where $n$ is the maximum number of copies of $x$ appearing in a
monomial of $P$.
## Main declarations
* `MvPolynomial.degrees p` : the multiset of variables representing the union of the multisets
corresponding to each non-zero monomial in `p`.
For example if `7 ≠ 0` in `R` and `p = x²y+7y³` then `degrees p = {x, x, y, y, y}`
* `MvPolynomial.degreeOf n p : ℕ` : the total degree of `p` with respect to the variable `n`.
For example if `p = x⁴y+yz` then `degreeOf y p = 1`.
* `MvPolynomial.totalDegree p : ℕ` :
the max of the sizes of the multisets `s` whose monomials `X^s` occur in `p`.
For example if `p = x⁴y+yz` then `totalDegree p = 5`.
## Notation
As in other polynomial files, we typically use the notation:
+ `σ τ : Type*` (indexing the variables)
+ `R : Type*` `[CommSemiring R]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `r : R`
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ R`
-/
noncomputable section
open Set Function Finsupp AddMonoidAlgebra
universe u v w
variable {R : Type u} {S : Type v}
namespace MvPolynomial
variable {σ τ : Type*} {r : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ}
section CommSemiring
variable [CommSemiring R] {p q : MvPolynomial σ R}
section Degrees
/-! ### `degrees` -/
/-- The maximal degrees of each variable in a multi-variable polynomial, expressed as a multiset.
(For example, `degrees (x^2 * y + y^3)` would be `{x, x, y, y, y}`.)
-/
def degrees (p : MvPolynomial σ R) : Multiset σ :=
letI := Classical.decEq σ
p.support.sup fun s : σ →₀ ℕ => toMultiset s
#align mv_polynomial.degrees MvPolynomial.degrees
theorem degrees_def [DecidableEq σ] (p : MvPolynomial σ R) :
p.degrees = p.support.sup fun s : σ →₀ ℕ => Finsupp.toMultiset s := by rw [degrees]; convert rfl
#align mv_polynomial.degrees_def MvPolynomial.degrees_def
theorem degrees_monomial (s : σ →₀ ℕ) (a : R) : degrees (monomial s a) ≤ toMultiset s := by
classical
refine (supDegree_single s a).trans_le ?_
split_ifs
exacts [bot_le, le_rfl]
#align mv_polynomial.degrees_monomial MvPolynomial.degrees_monomial
theorem degrees_monomial_eq (s : σ →₀ ℕ) (a : R) (ha : a ≠ 0) :
degrees (monomial s a) = toMultiset s := by
classical
exact (supDegree_single s a).trans (if_neg ha)
#align mv_polynomial.degrees_monomial_eq MvPolynomial.degrees_monomial_eq
theorem degrees_C (a : R) : degrees (C a : MvPolynomial σ R) = 0 :=
Multiset.le_zero.1 <| degrees_monomial _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.degrees_C MvPolynomial.degrees_C
theorem degrees_X' (n : σ) : degrees (X n : MvPolynomial σ R) ≤ {n} :=
le_trans (degrees_monomial _ _) <| le_of_eq <| toMultiset_single _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.degrees_X' MvPolynomial.degrees_X'
@[simp]
theorem degrees_X [Nontrivial R] (n : σ) : degrees (X n : MvPolynomial σ R) = {n} :=
(degrees_monomial_eq _ (1 : R) one_ne_zero).trans (toMultiset_single _ _)
set_option linter.uppercaseLean3 false in
#align mv_polynomial.degrees_X MvPolynomial.degrees_X
@[simp]
theorem degrees_zero : degrees (0 : MvPolynomial σ R) = 0 := by
rw [← C_0]
exact degrees_C 0
#align mv_polynomial.degrees_zero MvPolynomial.degrees_zero
@[simp]
theorem degrees_one : degrees (1 : MvPolynomial σ R) = 0 :=
degrees_C 1
#align mv_polynomial.degrees_one MvPolynomial.degrees_one
theorem degrees_add [DecidableEq σ] (p q : MvPolynomial σ R) :
(p + q).degrees ≤ p.degrees ⊔ q.degrees := by
simp_rw [degrees_def]; exact supDegree_add_le
#align mv_polynomial.degrees_add MvPolynomial.degrees_add
| Mathlib/Algebra/MvPolynomial/Degrees.lean | 133 | 135 | theorem degrees_sum {ι : Type*} [DecidableEq σ] (s : Finset ι) (f : ι → MvPolynomial σ R) :
(∑ i ∈ s, f i).degrees ≤ s.sup fun i => (f i).degrees := by |
simp_rw [degrees_def]; exact supDegree_sum_le
|
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Order.Interval.Finset.Nat
import Mathlib.Data.PNat.Defs
#align_import data.pnat.interval from "leanprover-community/mathlib"@"1d29de43a5ba4662dd33b5cfeecfc2a27a5a8a29"
/-!
# Finite intervals of positive naturals
This file proves that `ℕ+` is a `LocallyFiniteOrder` and calculates the cardinality of its
intervals as finsets and fintypes.
-/
open Finset Function PNat
namespace PNat
variable (a b : ℕ+)
instance instLocallyFiniteOrder : LocallyFiniteOrder ℕ+ := Subtype.instLocallyFiniteOrder _
theorem Icc_eq_finset_subtype : Icc a b = (Icc (a : ℕ) b).subtype fun n : ℕ => 0 < n :=
rfl
#align pnat.Icc_eq_finset_subtype PNat.Icc_eq_finset_subtype
theorem Ico_eq_finset_subtype : Ico a b = (Ico (a : ℕ) b).subtype fun n : ℕ => 0 < n :=
rfl
#align pnat.Ico_eq_finset_subtype PNat.Ico_eq_finset_subtype
theorem Ioc_eq_finset_subtype : Ioc a b = (Ioc (a : ℕ) b).subtype fun n : ℕ => 0 < n :=
rfl
#align pnat.Ioc_eq_finset_subtype PNat.Ioc_eq_finset_subtype
theorem Ioo_eq_finset_subtype : Ioo a b = (Ioo (a : ℕ) b).subtype fun n : ℕ => 0 < n :=
rfl
#align pnat.Ioo_eq_finset_subtype PNat.Ioo_eq_finset_subtype
theorem uIcc_eq_finset_subtype : uIcc a b = (uIcc (a : ℕ) b).subtype fun n : ℕ => 0 < n := rfl
#align pnat.uIcc_eq_finset_subtype PNat.uIcc_eq_finset_subtype
theorem map_subtype_embedding_Icc : (Icc a b).map (Embedding.subtype _) = Icc ↑a ↑b :=
Finset.map_subtype_embedding_Icc _ _ _ fun _c _ _x hx _ hc _ => hc.trans_le hx
#align pnat.map_subtype_embedding_Icc PNat.map_subtype_embedding_Icc
theorem map_subtype_embedding_Ico : (Ico a b).map (Embedding.subtype _) = Ico ↑a ↑b :=
Finset.map_subtype_embedding_Ico _ _ _ fun _c _ _x hx _ hc _ => hc.trans_le hx
#align pnat.map_subtype_embedding_Ico PNat.map_subtype_embedding_Ico
theorem map_subtype_embedding_Ioc : (Ioc a b).map (Embedding.subtype _) = Ioc ↑a ↑b :=
Finset.map_subtype_embedding_Ioc _ _ _ fun _c _ _x hx _ hc _ => hc.trans_le hx
#align pnat.map_subtype_embedding_Ioc PNat.map_subtype_embedding_Ioc
theorem map_subtype_embedding_Ioo : (Ioo a b).map (Embedding.subtype _) = Ioo ↑a ↑b :=
Finset.map_subtype_embedding_Ioo _ _ _ fun _c _ _x hx _ hc _ => hc.trans_le hx
#align pnat.map_subtype_embedding_Ioo PNat.map_subtype_embedding_Ioo
theorem map_subtype_embedding_uIcc : (uIcc a b).map (Embedding.subtype _) = uIcc ↑a ↑b :=
map_subtype_embedding_Icc _ _
#align pnat.map_subtype_embedding_uIcc PNat.map_subtype_embedding_uIcc
@[simp]
theorem card_Icc : (Icc a b).card = b + 1 - a := by
rw [← Nat.card_Icc]
-- Porting note: I had to change this to `erw` *and* provide the proof, yuck.
-- https://github.com/leanprover-community/mathlib4/issues/5164
erw [← Finset.map_subtype_embedding_Icc _ a b (fun c x _ hx _ hc _ => hc.trans_le hx)]
rw [card_map]
#align pnat.card_Icc PNat.card_Icc
@[simp]
theorem card_Ico : (Ico a b).card = b - a := by
rw [← Nat.card_Ico]
-- Porting note: I had to change this to `erw` *and* provide the proof, yuck.
-- https://github.com/leanprover-community/mathlib4/issues/5164
erw [← Finset.map_subtype_embedding_Ico _ a b (fun c x _ hx _ hc _ => hc.trans_le hx)]
rw [card_map]
#align pnat.card_Ico PNat.card_Ico
@[simp]
| Mathlib/Data/PNat/Interval.lean | 85 | 90 | theorem card_Ioc : (Ioc a b).card = b - a := by |
rw [← Nat.card_Ioc]
-- Porting note: I had to change this to `erw` *and* provide the proof, yuck.
-- https://github.com/leanprover-community/mathlib4/issues/5164
erw [← Finset.map_subtype_embedding_Ioc _ a b (fun c x _ hx _ hc _ => hc.trans_le hx)]
rw [card_map]
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.Algebra.Polynomial.Module.Basic
import Mathlib.Algebra.Ring.Idempotents
import Mathlib.RingTheory.Ideal.LocalRing
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.ReesAlgebra
import Mathlib.RingTheory.Finiteness
import Mathlib.Order.Basic
import Mathlib.Order.Hom.Lattice
#align_import ring_theory.filtration from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# `I`-filtrations of modules
This file contains the definitions and basic results around (stable) `I`-filtrations of modules.
## Main results
- `Ideal.Filtration`:
An `I`-filtration on the module `M` is a sequence of decreasing submodules `N i` such that
`∀ i, I • (N i) ≤ N (i + 1)`. Note that we do not require the filtration to start from `⊤`.
- `Ideal.Filtration.Stable`: An `I`-filtration is stable if `I • (N i) = N (i + 1)` for large
enough `i`.
- `Ideal.Filtration.submodule`: The associated module `⨁ Nᵢ` of a filtration, implemented as a
submodule of `M[X]`.
- `Ideal.Filtration.submodule_fg_iff_stable`: If `F.N i` are all finitely generated, then
`F.Stable` iff `F.submodule.FG`.
- `Ideal.Filtration.Stable.of_le`: In a finite module over a noetherian ring,
if `F' ≤ F`, then `F.Stable → F'.Stable`.
- `Ideal.exists_pow_inf_eq_pow_smul`: **Artin-Rees lemma**.
given `N ≤ M`, there exists a `k` such that `IⁿM ⊓ N = Iⁿ⁻ᵏ(IᵏM ⊓ N)` for all `n ≥ k`.
- `Ideal.iInf_pow_eq_bot_of_localRing`:
**Krull's intersection theorem** (`⨅ i, I ^ i = ⊥`) for noetherian local rings.
- `Ideal.iInf_pow_eq_bot_of_isDomain`:
**Krull's intersection theorem** (`⨅ i, I ^ i = ⊥`) for noetherian domains.
-/
universe u v
variable {R M : Type u} [CommRing R] [AddCommGroup M] [Module R M] (I : Ideal R)
open Polynomial
open scoped Polynomial
/-- An `I`-filtration on the module `M` is a sequence of decreasing submodules `N i` such that
`I • (N i) ≤ N (i + 1)`. Note that we do not require the filtration to start from `⊤`. -/
@[ext]
structure Ideal.Filtration (M : Type u) [AddCommGroup M] [Module R M] where
N : ℕ → Submodule R M
mono : ∀ i, N (i + 1) ≤ N i
smul_le : ∀ i, I • N i ≤ N (i + 1)
#align ideal.filtration Ideal.Filtration
variable (F F' : I.Filtration M) {I}
namespace Ideal.Filtration
theorem pow_smul_le (i j : ℕ) : I ^ i • F.N j ≤ F.N (i + j) := by
induction' i with _ ih
· simp
· rw [pow_succ', mul_smul, add_assoc, add_comm 1, ← add_assoc]
exact (smul_mono_right _ ih).trans (F.smul_le _)
#align ideal.filtration.pow_smul_le Ideal.Filtration.pow_smul_le
theorem pow_smul_le_pow_smul (i j k : ℕ) : I ^ (i + k) • F.N j ≤ I ^ k • F.N (i + j) := by
rw [add_comm, pow_add, mul_smul]
exact smul_mono_right _ (F.pow_smul_le i j)
#align ideal.filtration.pow_smul_le_pow_smul Ideal.Filtration.pow_smul_le_pow_smul
protected theorem antitone : Antitone F.N :=
antitone_nat_of_succ_le F.mono
#align ideal.filtration.antitone Ideal.Filtration.antitone
/-- The trivial `I`-filtration of `N`. -/
@[simps]
def _root_.Ideal.trivialFiltration (I : Ideal R) (N : Submodule R M) : I.Filtration M where
N _ := N
mono _ := le_rfl
smul_le _ := Submodule.smul_le_right
#align ideal.trivial_filtration Ideal.trivialFiltration
/-- The `sup` of two `I.Filtration`s is an `I.Filtration`. -/
instance : Sup (I.Filtration M) :=
⟨fun F F' =>
⟨F.N ⊔ F'.N, fun i => sup_le_sup (F.mono i) (F'.mono i), fun i =>
(Submodule.smul_sup _ _ _).trans_le <| sup_le_sup (F.smul_le i) (F'.smul_le i)⟩⟩
/-- The `sSup` of a family of `I.Filtration`s is an `I.Filtration`. -/
instance : SupSet (I.Filtration M) :=
⟨fun S =>
{ N := sSup (Ideal.Filtration.N '' S)
mono := fun i => by
apply sSup_le_sSup_of_forall_exists_le _
rintro _ ⟨⟨_, F, hF, rfl⟩, rfl⟩
exact ⟨_, ⟨⟨_, F, hF, rfl⟩, rfl⟩, F.mono i⟩
smul_le := fun i => by
rw [sSup_eq_iSup', iSup_apply, Submodule.smul_iSup, iSup_apply]
apply iSup_mono _
rintro ⟨_, F, hF, rfl⟩
exact F.smul_le i }⟩
/-- The `inf` of two `I.Filtration`s is an `I.Filtration`. -/
instance : Inf (I.Filtration M) :=
⟨fun F F' =>
⟨F.N ⊓ F'.N, fun i => inf_le_inf (F.mono i) (F'.mono i), fun i =>
(smul_inf_le _ _ _).trans <| inf_le_inf (F.smul_le i) (F'.smul_le i)⟩⟩
/-- The `sInf` of a family of `I.Filtration`s is an `I.Filtration`. -/
instance : InfSet (I.Filtration M) :=
⟨fun S =>
{ N := sInf (Ideal.Filtration.N '' S)
mono := fun i => by
apply sInf_le_sInf_of_forall_exists_le _
rintro _ ⟨⟨_, F, hF, rfl⟩, rfl⟩
exact ⟨_, ⟨⟨_, F, hF, rfl⟩, rfl⟩, F.mono i⟩
smul_le := fun i => by
rw [sInf_eq_iInf', iInf_apply, iInf_apply]
refine smul_iInf_le.trans ?_
apply iInf_mono _
rintro ⟨_, F, hF, rfl⟩
exact F.smul_le i }⟩
instance : Top (I.Filtration M) :=
⟨I.trivialFiltration ⊤⟩
instance : Bot (I.Filtration M) :=
⟨I.trivialFiltration ⊥⟩
@[simp]
theorem sup_N : (F ⊔ F').N = F.N ⊔ F'.N :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.sup_N Ideal.Filtration.sup_N
@[simp]
theorem sSup_N (S : Set (I.Filtration M)) : (sSup S).N = sSup (Ideal.Filtration.N '' S) :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.Sup_N Ideal.Filtration.sSup_N
@[simp]
theorem inf_N : (F ⊓ F').N = F.N ⊓ F'.N :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.inf_N Ideal.Filtration.inf_N
@[simp]
theorem sInf_N (S : Set (I.Filtration M)) : (sInf S).N = sInf (Ideal.Filtration.N '' S) :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.Inf_N Ideal.Filtration.sInf_N
@[simp]
theorem top_N : (⊤ : I.Filtration M).N = ⊤ :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.top_N Ideal.Filtration.top_N
@[simp]
theorem bot_N : (⊥ : I.Filtration M).N = ⊥ :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.bot_N Ideal.Filtration.bot_N
@[simp]
theorem iSup_N {ι : Sort*} (f : ι → I.Filtration M) : (iSup f).N = ⨆ i, (f i).N :=
congr_arg sSup (Set.range_comp _ _).symm
set_option linter.uppercaseLean3 false in
#align ideal.filtration.supr_N Ideal.Filtration.iSup_N
@[simp]
theorem iInf_N {ι : Sort*} (f : ι → I.Filtration M) : (iInf f).N = ⨅ i, (f i).N :=
congr_arg sInf (Set.range_comp _ _).symm
set_option linter.uppercaseLean3 false in
#align ideal.filtration.infi_N Ideal.Filtration.iInf_N
instance : CompleteLattice (I.Filtration M) :=
Function.Injective.completeLattice Ideal.Filtration.N Ideal.Filtration.ext sup_N inf_N
(fun _ => sSup_image) (fun _ => sInf_image) top_N bot_N
instance : Inhabited (I.Filtration M) :=
⟨⊥⟩
/-- An `I` filtration is stable if `I • F.N n = F.N (n+1)` for large enough `n`. -/
def Stable : Prop :=
∃ n₀, ∀ n ≥ n₀, I • F.N n = F.N (n + 1)
#align ideal.filtration.stable Ideal.Filtration.Stable
/-- The trivial stable `I`-filtration of `N`. -/
@[simps]
def _root_.Ideal.stableFiltration (I : Ideal R) (N : Submodule R M) : I.Filtration M where
N i := I ^ i • N
mono i := by dsimp only; rw [add_comm, pow_add, mul_smul]; exact Submodule.smul_le_right
smul_le i := by dsimp only; rw [add_comm, pow_add, mul_smul, pow_one]
#align ideal.stable_filtration Ideal.stableFiltration
theorem _root_.Ideal.stableFiltration_stable (I : Ideal R) (N : Submodule R M) :
(I.stableFiltration N).Stable := by
use 0
intro n _
dsimp
rw [add_comm, pow_add, mul_smul, pow_one]
#align ideal.stable_filtration_stable Ideal.stableFiltration_stable
variable {F F'} (h : F.Stable)
theorem Stable.exists_pow_smul_eq : ∃ n₀, ∀ k, F.N (n₀ + k) = I ^ k • F.N n₀ := by
obtain ⟨n₀, hn⟩ := h
use n₀
intro k
induction' k with _ ih
· simp
· rw [← add_assoc, ← hn, ih, add_comm, pow_add, mul_smul, pow_one]
omega
#align ideal.filtration.stable.exists_pow_smul_eq Ideal.Filtration.Stable.exists_pow_smul_eq
theorem Stable.exists_pow_smul_eq_of_ge : ∃ n₀, ∀ n ≥ n₀, F.N n = I ^ (n - n₀) • F.N n₀ := by
obtain ⟨n₀, hn₀⟩ := h.exists_pow_smul_eq
use n₀
intro n hn
convert hn₀ (n - n₀)
rw [add_comm, tsub_add_cancel_of_le hn]
#align ideal.filtration.stable.exists_pow_smul_eq_of_ge Ideal.Filtration.Stable.exists_pow_smul_eq_of_ge
theorem stable_iff_exists_pow_smul_eq_of_ge :
F.Stable ↔ ∃ n₀, ∀ n ≥ n₀, F.N n = I ^ (n - n₀) • F.N n₀ := by
refine ⟨Stable.exists_pow_smul_eq_of_ge, fun h => ⟨h.choose, fun n hn => ?_⟩⟩
rw [h.choose_spec n hn, h.choose_spec (n + 1) (by omega), smul_smul, ← pow_succ',
tsub_add_eq_add_tsub hn]
#align ideal.filtration.stable_iff_exists_pow_smul_eq_of_ge Ideal.Filtration.stable_iff_exists_pow_smul_eq_of_ge
theorem Stable.exists_forall_le (h : F.Stable) (e : F.N 0 ≤ F'.N 0) :
∃ n₀, ∀ n, F.N (n + n₀) ≤ F'.N n := by
obtain ⟨n₀, hF⟩ := h
use n₀
intro n
induction' n with n hn
· refine (F.antitone ?_).trans e; simp
· rw [add_right_comm, ← hF]
· exact (smul_mono_right _ hn).trans (F'.smul_le _)
simp
#align ideal.filtration.stable.exists_forall_le Ideal.Filtration.Stable.exists_forall_le
theorem Stable.bounded_difference (h : F.Stable) (h' : F'.Stable) (e : F.N 0 = F'.N 0) :
∃ n₀, ∀ n, F.N (n + n₀) ≤ F'.N n ∧ F'.N (n + n₀) ≤ F.N n := by
obtain ⟨n₁, h₁⟩ := h.exists_forall_le (le_of_eq e)
obtain ⟨n₂, h₂⟩ := h'.exists_forall_le (le_of_eq e.symm)
use max n₁ n₂
intro n
refine ⟨(F.antitone ?_).trans (h₁ n), (F'.antitone ?_).trans (h₂ n)⟩ <;> simp
#align ideal.filtration.stable.bounded_difference Ideal.Filtration.Stable.bounded_difference
open PolynomialModule
variable (F F')
/-- The `R[IX]`-submodule of `M[X]` associated with an `I`-filtration. -/
protected def submodule : Submodule (reesAlgebra I) (PolynomialModule R M) where
carrier := { f | ∀ i, f i ∈ F.N i }
add_mem' hf hg i := Submodule.add_mem _ (hf i) (hg i)
zero_mem' i := Submodule.zero_mem _
smul_mem' r f hf i := by
rw [Subalgebra.smul_def, PolynomialModule.smul_apply]
apply Submodule.sum_mem
rintro ⟨j, k⟩ e
rw [Finset.mem_antidiagonal] at e
subst e
exact F.pow_smul_le j k (Submodule.smul_mem_smul (r.2 j) (hf k))
#align ideal.filtration.submodule Ideal.Filtration.submodule
@[simp]
theorem mem_submodule (f : PolynomialModule R M) : f ∈ F.submodule ↔ ∀ i, f i ∈ F.N i :=
Iff.rfl
#align ideal.filtration.mem_submodule Ideal.Filtration.mem_submodule
theorem inf_submodule : (F ⊓ F').submodule = F.submodule ⊓ F'.submodule := by
ext
exact forall_and
#align ideal.filtration.inf_submodule Ideal.Filtration.inf_submodule
variable (I M)
/-- `Ideal.Filtration.submodule` as an `InfHom`. -/
def submoduleInfHom :
InfHom (I.Filtration M) (Submodule (reesAlgebra I) (PolynomialModule R M)) where
toFun := Ideal.Filtration.submodule
map_inf' := inf_submodule
#align ideal.filtration.submodule_inf_hom Ideal.Filtration.submoduleInfHom
variable {I M}
theorem submodule_closure_single :
AddSubmonoid.closure (⋃ i, single R i '' (F.N i : Set M)) = F.submodule.toAddSubmonoid := by
apply le_antisymm
· rw [AddSubmonoid.closure_le, Set.iUnion_subset_iff]
rintro i _ ⟨m, hm, rfl⟩ j
rw [single_apply]
split_ifs with h
· rwa [← h]
· exact (F.N j).zero_mem
· intro f hf
rw [← f.sum_single]
apply AddSubmonoid.sum_mem _ _
rintro c -
exact AddSubmonoid.subset_closure (Set.subset_iUnion _ c <| Set.mem_image_of_mem _ (hf c))
#align ideal.filtration.submodule_closure_single Ideal.Filtration.submodule_closure_single
theorem submodule_span_single :
Submodule.span (reesAlgebra I) (⋃ i, single R i '' (F.N i : Set M)) = F.submodule := by
rw [← Submodule.span_closure, submodule_closure_single, Submodule.coe_toAddSubmonoid]
exact Submodule.span_eq (Filtration.submodule F)
#align ideal.filtration.submodule_span_single Ideal.Filtration.submodule_span_single
theorem submodule_eq_span_le_iff_stable_ge (n₀ : ℕ) :
F.submodule = Submodule.span _ (⋃ i ≤ n₀, single R i '' (F.N i : Set M)) ↔
∀ n ≥ n₀, I • F.N n = F.N (n + 1) := by
rw [← submodule_span_single, ← LE.le.le_iff_eq, Submodule.span_le, Set.iUnion_subset_iff]
swap; · exact Submodule.span_mono (Set.iUnion₂_subset_iUnion _ _)
constructor
· intro H n hn
refine (F.smul_le n).antisymm ?_
intro x hx
obtain ⟨l, hl⟩ := (Finsupp.mem_span_iff_total _ _ _).mp (H _ ⟨x, hx, rfl⟩)
replace hl := congr_arg (fun f : ℕ →₀ M => f (n + 1)) hl
dsimp only at hl
erw [Finsupp.single_eq_same] at hl
rw [← hl, Finsupp.total_apply, Finsupp.sum_apply]
apply Submodule.sum_mem _ _
rintro ⟨_, _, ⟨n', rfl⟩, _, ⟨hn', rfl⟩, m, hm, rfl⟩ -
dsimp only [Subtype.coe_mk]
rw [Subalgebra.smul_def, smul_single_apply, if_pos (show n' ≤ n + 1 by omega)]
have e : n' ≤ n := by omega
have := F.pow_smul_le_pow_smul (n - n') n' 1
rw [tsub_add_cancel_of_le e, pow_one, add_comm _ 1, ← add_tsub_assoc_of_le e, add_comm] at this
exact this (Submodule.smul_mem_smul ((l _).2 <| n + 1 - n') hm)
· let F' := Submodule.span (reesAlgebra I) (⋃ i ≤ n₀, single R i '' (F.N i : Set M))
intro hF i
have : ∀ i ≤ n₀, single R i '' (F.N i : Set M) ⊆ F' := by
-- Porting note: Original proof was
-- `fun i hi => Set.Subset.trans (Set.subset_iUnion₂ i hi) Submodule.subset_span`
intro i hi
refine Set.Subset.trans ?_ Submodule.subset_span
refine @Set.subset_iUnion₂ _ _ _ (fun i => fun _ => ↑((single R i) '' ((N F i) : Set M))) i ?_
exact hi
induction' i with j hj
· exact this _ (zero_le _)
by_cases hj' : j.succ ≤ n₀
· exact this _ hj'
simp only [not_le, Nat.lt_succ_iff] at hj'
rw [← hF _ hj']
rintro _ ⟨m, hm, rfl⟩
refine Submodule.smul_induction_on hm (fun r hr m' hm' => ?_) (fun x y hx hy => ?_)
· rw [add_comm, ← monomial_smul_single]
exact F'.smul_mem
⟨_, reesAlgebra.monomial_mem.mpr (by rwa [pow_one])⟩ (hj <| Set.mem_image_of_mem _ hm')
· rw [map_add]
exact F'.add_mem hx hy
#align ideal.filtration.submodule_eq_span_le_iff_stable_ge Ideal.Filtration.submodule_eq_span_le_iff_stable_ge
/-- If the components of a filtration are finitely generated, then the filtration is stable iff
its associated submodule of is finitely generated. -/
| Mathlib/RingTheory/Filtration.lean | 371 | 403 | theorem submodule_fg_iff_stable (hF' : ∀ i, (F.N i).FG) : F.submodule.FG ↔ F.Stable := by |
classical
delta Ideal.Filtration.Stable
simp_rw [← F.submodule_eq_span_le_iff_stable_ge]
constructor
· rintro H
refine H.stabilizes_of_iSup_eq
⟨fun n₀ => Submodule.span _ (⋃ (i : ℕ) (_ : i ≤ n₀), single R i '' ↑(F.N i)), ?_⟩ ?_
· intro n m e
rw [Submodule.span_le, Set.iUnion₂_subset_iff]
intro i hi
refine Set.Subset.trans ?_ Submodule.subset_span
refine @Set.subset_iUnion₂ _ _ _ (fun i => fun _ => ↑((single R i) '' ((N F i) : Set M))) i ?_
exact hi.trans e
· dsimp
rw [← Submodule.span_iUnion, ← submodule_span_single]
congr 1
ext
simp only [Set.mem_iUnion, Set.mem_image, SetLike.mem_coe, exists_prop]
constructor
· rintro ⟨-, i, -, e⟩; exact ⟨i, e⟩
· rintro ⟨i, e⟩; exact ⟨i, i, le_refl i, e⟩
· rintro ⟨n, hn⟩
rw [hn]
simp_rw [Submodule.span_iUnion₂, ← Finset.mem_range_succ_iff, iSup_subtype']
apply Submodule.fg_iSup
rintro ⟨i, hi⟩
obtain ⟨s, hs⟩ := hF' i
have : Submodule.span (reesAlgebra I) (s.image (lsingle R i) : Set (PolynomialModule R M)) =
Submodule.span _ (single R i '' (F.N i : Set M)) := by
rw [Finset.coe_image, ← Submodule.span_span_of_tower R, ← Submodule.map_span, hs]; rfl
rw [Subtype.coe_mk, ← this]
exact ⟨_, rfl⟩
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Yury Kudryashov
-/
import Mathlib.Tactic.ApplyFun
import Mathlib.Topology.UniformSpace.Basic
import Mathlib.Topology.Separation
#align_import topology.uniform_space.separation from "leanprover-community/mathlib"@"0c1f285a9f6e608ae2bdffa3f993eafb01eba829"
/-!
# Hausdorff properties of uniform spaces. Separation quotient.
Two points of a topological space are called `Inseparable`,
if their neighborhoods filter are equal.
Equivalently, `Inseparable x y` means that any open set that contains `x` must contain `y`
and vice versa.
In a uniform space, points `x` and `y` are inseparable
if and only if `(x, y)` belongs to all entourages,
see `inseparable_iff_ker_uniformity`.
A uniform space is a regular topological space,
hence separation axioms `T0Space`, `T1Space`, `T2Space`, and `T3Space`
are equivalent for uniform spaces,
and Lean typeclass search can automatically convert from one assumption to another.
We say that a uniform space is *separated*, if it satisfies these axioms.
If you need an `Iff` statement (e.g., to rewrite),
then see `R1Space.t0Space_iff_t2Space` and `RegularSpace.t0Space_iff_t3Space`.
In this file we prove several facts
that relate `Inseparable` and `Specializes` to the uniformity filter.
Most of them are simple corollaries of `Filter.HasBasis.inseparable_iff_uniformity`
for different filter bases of `𝓤 α`.
Then we study the Kolmogorov quotient `SeparationQuotient X` of a uniform space.
For a general topological space,
this quotient is defined as the quotient by `Inseparable` equivalence relation.
It is the maximal T₀ quotient of a topological space.
In case of a uniform space, we equip this quotient with a `UniformSpace` structure
that agrees with the quotient topology.
We also prove that the quotient map induces uniformity on the original space.
Finally, we turn `SeparationQuotient` into a functor
(not in terms of `CategoryTheory.Functor` to avoid extra imports)
by defining `SeparationQuotient.lift'` and `SeparationQuotient.map` operations.
## Main definitions
* `SeparationQuotient.instUniformSpace`: uniform space structure on `SeparationQuotient α`,
where `α` is a uniform space;
* `SeparationQuotient.lift'`: given a map `f : α → β`
from a uniform space to a separated uniform space,
lift it to a map `SeparationQuotient α → β`;
if the original map is not uniformly continuous, then returns a constant map.
* `SeparationQuotient.map`: given a map `f : α → β` between uniform spaces,
returns a map `SeparationQuotient α → SeparationQuotient β`.
If the original map is not uniformly continuous, then returns a constant map.
Otherwise, `SeparationQuotient.map f (SeparationQuotient.mk x) = SeparationQuotient.mk (f x)`.
## Main results
* `SeparationQuotient.uniformity_eq`: the uniformity filter on `SeparationQuotient α`
is the push forward of the uniformity filter on `α`.
* `SeparationQuotient.comap_mk_uniformity`: the quotient map `α → SeparationQuotient α`
induces uniform space structure on the original space.
* `SeparationQuotient.uniformContinuous_lift'`: factoring a uniformly continuous map through the
separation quotient gives a uniformly continuous map.
* `SeparationQuotient.uniformContinuous_map`: maps induced between separation quotients are
uniformly continuous.
## Implementation notes
This files used to contain definitions of `separationRel α` and `UniformSpace.SeparationQuotient α`.
These definitions were equal (but not definitionally equal)
to `{x : α × α | Inseparable x.1 x.2}` and `SeparationQuotient α`, respectively,
and were added to the library before their geneeralizations to topological spaces.
In #10644, we migrated from these definitions
to more general `Inseparable` and `SeparationQuotient`.
## TODO
Definitions `SeparationQuotient.lift'` and `SeparationQuotient.map`
rely on `UniformSpace` structures in the domain and in the codomain.
We should generalize them to topological spaces.
This generalization will drop `UniformContinuous` assumptions in some lemmas,
and add these assumptions in other lemmas,
so it was not done in #10644 to keep it reasonably sized.
## Keywords
uniform space, separated space, Hausdorff space, separation quotient
-/
open Filter Set Function Topology Uniformity UniformSpace
open scoped Classical
noncomputable section
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w}
variable [UniformSpace α] [UniformSpace β] [UniformSpace γ]
/-!
### Separated uniform spaces
-/
instance (priority := 100) UniformSpace.to_regularSpace : RegularSpace α :=
.of_hasBasis
(fun _ ↦ nhds_basis_uniformity' uniformity_hasBasis_closed)
fun a _V hV ↦ isClosed_ball a hV.2
#align uniform_space.to_regular_space UniformSpace.to_regularSpace
#align separation_rel Inseparable
#noalign separated_equiv
#align separation_rel_iff_specializes specializes_iff_inseparable
#noalign separation_rel_iff_inseparable
theorem Filter.HasBasis.specializes_iff_uniformity {ι : Sort*} {p : ι → Prop} {s : ι → Set (α × α)}
(h : (𝓤 α).HasBasis p s) {x y : α} : x ⤳ y ↔ ∀ i, p i → (x, y) ∈ s i :=
(nhds_basis_uniformity h).specializes_iff
theorem Filter.HasBasis.inseparable_iff_uniformity {ι : Sort*} {p : ι → Prop} {s : ι → Set (α × α)}
(h : (𝓤 α).HasBasis p s) {x y : α} : Inseparable x y ↔ ∀ i, p i → (x, y) ∈ s i :=
specializes_iff_inseparable.symm.trans h.specializes_iff_uniformity
#align filter.has_basis.mem_separation_rel Filter.HasBasis.inseparable_iff_uniformity
theorem inseparable_iff_ker_uniformity {x y : α} : Inseparable x y ↔ (x, y) ∈ (𝓤 α).ker :=
(𝓤 α).basis_sets.inseparable_iff_uniformity
protected theorem Inseparable.nhds_le_uniformity {x y : α} (h : Inseparable x y) :
𝓝 (x, y) ≤ 𝓤 α := by
rw [h.prod rfl]
apply nhds_le_uniformity
theorem inseparable_iff_clusterPt_uniformity {x y : α} :
Inseparable x y ↔ ClusterPt (x, y) (𝓤 α) := by
refine ⟨fun h ↦ .of_nhds_le h.nhds_le_uniformity, fun h ↦ ?_⟩
simp_rw [uniformity_hasBasis_closed.inseparable_iff_uniformity, isClosed_iff_clusterPt]
exact fun U ⟨hU, hUc⟩ ↦ hUc _ <| h.mono <| le_principal_iff.2 hU
#align separated_space T0Space
theorem t0Space_iff_uniformity :
T0Space α ↔ ∀ x y, (∀ r ∈ 𝓤 α, (x, y) ∈ r) → x = y := by
simp only [t0Space_iff_inseparable, inseparable_iff_ker_uniformity, mem_ker, id]
#align separated_def t0Space_iff_uniformity
theorem t0Space_iff_uniformity' :
T0Space α ↔ Pairwise fun x y ↦ ∃ r ∈ 𝓤 α, (x, y) ∉ r := by
simp [t0Space_iff_not_inseparable, inseparable_iff_ker_uniformity]
#align separated_def' t0Space_iff_uniformity'
theorem t0Space_iff_ker_uniformity : T0Space α ↔ (𝓤 α).ker = diagonal α := by
simp_rw [t0Space_iff_uniformity, subset_antisymm_iff, diagonal_subset_iff, subset_def,
Prod.forall, Filter.mem_ker, mem_diagonal_iff, iff_self_and]
exact fun _ x s hs ↦ refl_mem_uniformity hs
#align separated_space_iff t0Space_iff_ker_uniformity
theorem eq_of_uniformity {α : Type*} [UniformSpace α] [T0Space α] {x y : α}
(h : ∀ {V}, V ∈ 𝓤 α → (x, y) ∈ V) : x = y :=
t0Space_iff_uniformity.mp ‹T0Space α› x y @h
#align eq_of_uniformity eq_of_uniformity
theorem eq_of_uniformity_basis {α : Type*} [UniformSpace α] [T0Space α] {ι : Sort*}
{p : ι → Prop} {s : ι → Set (α × α)} (hs : (𝓤 α).HasBasis p s) {x y : α}
(h : ∀ {i}, p i → (x, y) ∈ s i) : x = y :=
(hs.inseparable_iff_uniformity.2 @h).eq
#align eq_of_uniformity_basis eq_of_uniformity_basis
theorem eq_of_forall_symmetric {α : Type*} [UniformSpace α] [T0Space α] {x y : α}
(h : ∀ {V}, V ∈ 𝓤 α → SymmetricRel V → (x, y) ∈ V) : x = y :=
eq_of_uniformity_basis hasBasis_symmetric (by simpa)
#align eq_of_forall_symmetric eq_of_forall_symmetric
theorem eq_of_clusterPt_uniformity [T0Space α] {x y : α} (h : ClusterPt (x, y) (𝓤 α)) : x = y :=
(inseparable_iff_clusterPt_uniformity.2 h).eq
#align eq_of_cluster_pt_uniformity eq_of_clusterPt_uniformity
theorem Filter.Tendsto.inseparable_iff_uniformity {l : Filter β} [NeBot l] {f g : β → α} {a b : α}
(ha : Tendsto f l (𝓝 a)) (hb : Tendsto g l (𝓝 b)) :
Inseparable a b ↔ Tendsto (fun x ↦ (f x, g x)) l (𝓤 α) := by
refine ⟨fun h ↦ (ha.prod_mk_nhds hb).mono_right h.nhds_le_uniformity, fun h ↦ ?_⟩
rw [inseparable_iff_clusterPt_uniformity]
exact (ClusterPt.of_le_nhds (ha.prod_mk_nhds hb)).mono h
#align id_rel_sub_separation_relation Inseparable.rfl
#align separation_rel_comap Inducing.inseparable_iff
#align filter.has_basis.separation_rel Filter.HasBasis.ker
#noalign separation_rel_eq_inter_closure
#align is_closed_separation_rel isClosed_setOf_inseparable
#align separated_iff_t2 R1Space.t2Space_iff_t0Space
#align separated_t3 RegularSpace.t3Space_iff_t0Space
#align subtype.separated_space Subtype.t0Space
theorem isClosed_of_spaced_out [T0Space α] {V₀ : Set (α × α)} (V₀_in : V₀ ∈ 𝓤 α) {s : Set α}
(hs : s.Pairwise fun x y => (x, y) ∉ V₀) : IsClosed s := by
rcases comp_symm_mem_uniformity_sets V₀_in with ⟨V₁, V₁_in, V₁_symm, h_comp⟩
apply isClosed_of_closure_subset
intro x hx
rw [mem_closure_iff_ball] at hx
rcases hx V₁_in with ⟨y, hy, hy'⟩
suffices x = y by rwa [this]
apply eq_of_forall_symmetric
intro V V_in _
rcases hx (inter_mem V₁_in V_in) with ⟨z, hz, hz'⟩
obtain rfl : z = y := by
by_contra hzy
exact hs hz' hy' hzy (h_comp <| mem_comp_of_mem_ball V₁_symm (ball_inter_left x _ _ hz) hy)
exact ball_inter_right x _ _ hz
#align is_closed_of_spaced_out isClosed_of_spaced_out
theorem isClosed_range_of_spaced_out {ι} [T0Space α] {V₀ : Set (α × α)} (V₀_in : V₀ ∈ 𝓤 α)
{f : ι → α} (hf : Pairwise fun x y => (f x, f y) ∉ V₀) : IsClosed (range f) :=
isClosed_of_spaced_out V₀_in <| by
rintro _ ⟨x, rfl⟩ _ ⟨y, rfl⟩ h
exact hf (ne_of_apply_ne f h)
#align is_closed_range_of_spaced_out isClosed_range_of_spaced_out
/-!
### Separation quotient
-/
#align uniform_space.separation_setoid inseparableSetoid
namespace SeparationQuotient
theorem comap_map_mk_uniformity : comap (Prod.map mk mk) (map (Prod.map mk mk) (𝓤 α)) = 𝓤 α := by
refine le_antisymm ?_ le_comap_map
refine ((((𝓤 α).basis_sets.map _).comap _).le_basis_iff uniformity_hasBasis_open).2 fun U hU ↦ ?_
refine ⟨U, hU.1, fun (x₁, x₂) ⟨(y₁, y₂), hyU, hxy⟩ ↦ ?_⟩
simp only [Prod.map, Prod.ext_iff, mk_eq_mk] at hxy
exact ((hxy.1.prod hxy.2).mem_open_iff hU.2).1 hyU
instance instUniformSpace : UniformSpace (SeparationQuotient α) where
uniformity := map (Prod.map mk mk) (𝓤 α)
symm := tendsto_map' <| tendsto_map.comp tendsto_swap_uniformity
comp := fun t ht ↦ by
rcases comp_open_symm_mem_uniformity_sets ht with ⟨U, hU, hUo, -, hUt⟩
refine mem_of_superset (mem_lift' <| image_mem_map hU) ?_
simp only [subset_def, Prod.forall, mem_compRel, mem_image, Prod.ext_iff]
rintro _ _ ⟨_, ⟨⟨x, y⟩, hxyU, rfl, rfl⟩, ⟨⟨y', z⟩, hyzU, hy, rfl⟩⟩
have : y' ⤳ y := (mk_eq_mk.1 hy).specializes
exact @hUt (x, z) ⟨y', this.mem_open (UniformSpace.isOpen_ball _ hUo) hxyU, hyzU⟩
nhds_eq_comap_uniformity := surjective_mk.forall.2 fun x ↦ comap_injective surjective_mk <| by
conv_lhs => rw [comap_mk_nhds_mk, nhds_eq_comap_uniformity, ← comap_map_mk_uniformity]
simp only [Filter.comap_comap, Function.comp, Prod.map_apply]
theorem uniformity_eq : 𝓤 (SeparationQuotient α) = (𝓤 α).map (Prod.map mk mk) := rfl
#align uniform_space.uniformity_quotient SeparationQuotient.uniformity_eq
theorem uniformContinuous_mk : UniformContinuous (mk : α → SeparationQuotient α) :=
le_rfl
#align uniform_space.uniform_continuous_quotient_mk SeparationQuotient.uniformContinuous_mk
theorem uniformContinuous_dom {f : SeparationQuotient α → β} :
UniformContinuous f ↔ UniformContinuous (f ∘ mk) :=
.rfl
#align uniform_space.uniform_continuous_quotient SeparationQuotient.uniformContinuous_dom
| Mathlib/Topology/UniformSpace/Separation.lean | 267 | 271 | theorem uniformContinuous_dom₂ {f : SeparationQuotient α × SeparationQuotient β → γ} :
UniformContinuous f ↔ UniformContinuous fun p : α × β ↦ f (mk p.1, mk p.2) := by |
simp only [UniformContinuous, uniformity_prod_eq_prod, uniformity_eq, prod_map_map_eq,
tendsto_map'_iff]
rfl
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.Geometry.RingedSpace.PresheafedSpace
import Mathlib.CategoryTheory.Limits.Final
import Mathlib.Topology.Sheaves.Stalks
#align_import algebraic_geometry.stalks from "leanprover-community/mathlib"@"d39590fc8728fbf6743249802486f8c91ffe07bc"
/-!
# Stalks for presheaved spaces
This file lifts constructions of stalks and pushforwards of stalks to work with
the category of presheafed spaces. Additionally, we prove that restriction of
presheafed spaces does not change the stalks.
-/
noncomputable section
universe v u v' u'
open Opposite CategoryTheory CategoryTheory.Category CategoryTheory.Functor CategoryTheory.Limits
AlgebraicGeometry TopologicalSpace
variable {C : Type u} [Category.{v} C] [HasColimits C]
-- Porting note: no tidy tactic
-- attribute [local tidy] tactic.auto_cases_opens
-- this could be replaced by
-- attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Opens
-- but it doesn't appear to be needed here.
open TopCat.Presheaf
namespace AlgebraicGeometry.PresheafedSpace
/-- The stalk at `x` of a `PresheafedSpace`.
-/
abbrev stalk (X : PresheafedSpace C) (x : X) : C :=
X.presheaf.stalk x
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.stalk AlgebraicGeometry.PresheafedSpace.stalk
/-- A morphism of presheafed spaces induces a morphism of stalks.
-/
def stalkMap {X Y : PresheafedSpace.{_, _, v} C} (α : X ⟶ Y) (x : X) :
Y.stalk (α.base x) ⟶ X.stalk x :=
(stalkFunctor C (α.base x)).map α.c ≫ X.presheaf.stalkPushforward C α.base x
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.stalk_map AlgebraicGeometry.PresheafedSpace.stalkMap
@[elementwise, reassoc]
theorem stalkMap_germ {X Y : PresheafedSpace.{_, _, v} C} (α : X ⟶ Y) (U : Opens Y)
(x : (Opens.map α.base).obj U) :
Y.presheaf.germ ⟨α.base x.1, x.2⟩ ≫ stalkMap α ↑x = α.c.app (op U) ≫ X.presheaf.germ x := by
rw [stalkMap, stalkFunctor_map_germ_assoc, stalkPushforward_germ]
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.stalk_map_germ AlgebraicGeometry.PresheafedSpace.stalkMap_germ
@[simp, elementwise, reassoc]
theorem stalkMap_germ' {X Y : PresheafedSpace.{_, _, v} C}
(α : X ⟶ Y) (U : Opens Y) (x : X) (hx : α.base x ∈ U) :
Y.presheaf.germ ⟨α.base x, hx⟩ ≫ stalkMap α x = α.c.app (op U) ≫
X.presheaf.germ (U := (Opens.map α.base).obj U) ⟨x, hx⟩ :=
PresheafedSpace.stalkMap_germ α U ⟨x, hx⟩
section Restrict
/-- For an open embedding `f : U ⟶ X` and a point `x : U`, we get an isomorphism between the stalk
of `X` at `f x` and the stalk of the restriction of `X` along `f` at t `x`.
-/
def restrictStalkIso {U : TopCat} (X : PresheafedSpace.{_, _, v} C) {f : U ⟶ (X : TopCat.{v})}
(h : OpenEmbedding f) (x : U) : (X.restrict h).stalk x ≅ X.stalk (f x) :=
haveI := initial_of_adjunction (h.isOpenMap.adjunctionNhds x)
Final.colimitIso (h.isOpenMap.functorNhds x).op ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf)
-- As a left adjoint, the functor `h.is_open_map.functor_nhds x` is initial.
-- Typeclass resolution knows that the opposite of an initial functor is final. The result
-- follows from the general fact that postcomposing with a final functor doesn't change colimits.
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.restrict_stalk_iso AlgebraicGeometry.PresheafedSpace.restrictStalkIso
-- Porting note (#11119): removed `simp` attribute, for left hand side is not in simple normal form.
@[elementwise, reassoc]
theorem restrictStalkIso_hom_eq_germ {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : OpenEmbedding f) (V : Opens U) (x : U) (hx : x ∈ V) :
(X.restrict h).presheaf.germ ⟨x, hx⟩ ≫ (restrictStalkIso X h x).hom =
X.presheaf.germ ⟨f x, show f x ∈ h.isOpenMap.functor.obj V from ⟨x, hx, rfl⟩⟩ :=
colimit.ι_pre ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf) (h.isOpenMap.functorNhds x).op
(op ⟨V, hx⟩)
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.restrict_stalk_iso_hom_eq_germ AlgebraicGeometry.PresheafedSpace.restrictStalkIso_hom_eq_germ
-- We intentionally leave `simp` off the lemmas generated by `elementwise` and `reassoc`,
-- as the simpNF linter claims they never apply.
@[simp, elementwise, reassoc]
theorem restrictStalkIso_inv_eq_germ {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : OpenEmbedding f) (V : Opens U) (x : U) (hx : x ∈ V) :
X.presheaf.germ ⟨f x, show f x ∈ h.isOpenMap.functor.obj V from ⟨x, hx, rfl⟩⟩ ≫
(restrictStalkIso X h x).inv =
(X.restrict h).presheaf.germ ⟨x, hx⟩ := by
rw [← restrictStalkIso_hom_eq_germ, Category.assoc, Iso.hom_inv_id, Category.comp_id]
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.restrict_stalk_iso_inv_eq_germ AlgebraicGeometry.PresheafedSpace.restrictStalkIso_inv_eq_germ
theorem restrictStalkIso_inv_eq_ofRestrict {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : OpenEmbedding f) (x : U) :
(X.restrictStalkIso h x).inv = stalkMap (X.ofRestrict h) x := by
-- We can't use `ext` here due to https://github.com/leanprover/std4/pull/159
refine colimit.hom_ext fun V => ?_
induction V with | h V => ?_
let i : (h.isOpenMap.functorNhds x).obj ((OpenNhds.map f x).obj V) ⟶ V :=
homOfLE (Set.image_preimage_subset f _)
erw [Iso.comp_inv_eq, colimit.ι_map_assoc, colimit.ι_map_assoc, colimit.ι_pre]
simp_rw [Category.assoc]
erw [colimit.ι_pre ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf)
(h.isOpenMap.functorNhds x).op]
erw [← X.presheaf.map_comp_assoc]
exact (colimit.w ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf) i.op).symm
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.restrict_stalk_iso_inv_eq_of_restrict AlgebraicGeometry.PresheafedSpace.restrictStalkIso_inv_eq_ofRestrict
instance ofRestrict_stalkMap_isIso {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : OpenEmbedding f) (x : U) :
IsIso (stalkMap (X.ofRestrict h) x) := by
rw [← restrictStalkIso_inv_eq_ofRestrict]; infer_instance
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.of_restrict_stalk_map_is_iso AlgebraicGeometry.PresheafedSpace.ofRestrict_stalkMap_isIso
end Restrict
namespace stalkMap
@[simp]
theorem id (X : PresheafedSpace.{_, _, v} C) (x : X) :
stalkMap (𝟙 X) x = 𝟙 (X.stalk x) := by
dsimp [stalkMap]
simp only [stalkPushforward.id]
erw [← map_comp]
convert (stalkFunctor C x).map_id X.presheaf
ext
simp only [id_c, id_comp, Pushforward.id_hom_app, op_obj, eqToHom_refl, map_id]
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.stalk_map.id AlgebraicGeometry.PresheafedSpace.stalkMap.id
@[simp]
theorem comp {X Y Z : PresheafedSpace.{_, _, v} C} (α : X ⟶ Y) (β : Y ⟶ Z) (x : X) :
stalkMap (α ≫ β) x =
(stalkMap β (α.base x) : Z.stalk (β.base (α.base x)) ⟶ Y.stalk (α.base x)) ≫
(stalkMap α x : Y.stalk (α.base x) ⟶ X.stalk x) := by
dsimp [stalkMap, stalkFunctor, stalkPushforward]
-- We can't use `ext` here due to https://github.com/leanprover/std4/pull/159
refine colimit.hom_ext fun U => ?_
induction U with | h U => ?_
cases U
simp only [whiskeringLeft_obj_obj, comp_obj, op_obj, unop_op, OpenNhds.inclusion_obj,
ι_colimMap_assoc, pushforwardObj_obj, Opens.map_comp_obj, whiskerLeft_app, comp_c_app,
OpenNhds.map_obj, whiskerRight_app, NatTrans.id_app, map_id, colimit.ι_pre, id_comp, assoc,
colimit.ι_pre_assoc]
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.stalk_map.comp AlgebraicGeometry.PresheafedSpace.stalkMap.comp
/-- If `α = β` and `x = x'`, we would like to say that `stalk_map α x = stalk_map β x'`.
Unfortunately, this equality is not well-formed, as their types are not _definitionally_ the same.
To get a proper congruence lemma, we therefore have to introduce these `eqToHom` arrows on
either side of the equality.
-/
theorem congr {X Y : PresheafedSpace.{_, _, v} C} (α β : X ⟶ Y)
(h₁ : α = β) (x x' : X) (h₂ : x = x') :
stalkMap α x ≫ eqToHom (show X.stalk x = X.stalk x' by rw [h₂]) =
eqToHom (show Y.stalk (α.base x) = Y.stalk (β.base x') by rw [h₁, h₂]) ≫ stalkMap β x' := by
ext
substs h₁ h₂
simp
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.stalk_map.congr AlgebraicGeometry.PresheafedSpace.stalkMap.congr
| Mathlib/Geometry/RingedSpace/Stalks.lean | 181 | 184 | theorem congr_hom {X Y : PresheafedSpace.{_, _, v} C} (α β : X ⟶ Y) (h : α = β) (x : X) :
stalkMap α x =
eqToHom (show Y.stalk (α.base x) = Y.stalk (β.base x) by rw [h]) ≫ stalkMap β x := by |
rw [← stalkMap.congr α β h x x rfl, eqToHom_refl, Category.comp_id]
|
/-
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
| Mathlib/Data/Finset/Lattice.lean | 298 | 299 | theorem sup_id_eq_sSup [CompleteLattice α] (s : Finset α) : s.sup id = sSup s := by |
simp [sSup_eq_iSup, sup_eq_iSup]
|
/-
Copyright (c) 2022 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp
-/
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.LinearAlgebra.Matrix.ZPow
#align_import linear_algebra.matrix.hermitian from "leanprover-community/mathlib"@"caa58cbf5bfb7f81ccbaca4e8b8ac4bc2b39cc1c"
/-! # Hermitian matrices
This file defines hermitian matrices and some basic results about them.
See also `IsSelfAdjoint`, which generalizes this definition to other star rings.
## Main definition
* `Matrix.IsHermitian` : a matrix `A : Matrix n n α` is hermitian if `Aᴴ = A`.
## Tags
self-adjoint matrix, hermitian matrix
-/
namespace Matrix
variable {α β : Type*} {m n : Type*} {A : Matrix n n α}
open scoped Matrix
local notation "⟪" x ", " y "⟫" => @inner α _ _ x y
section Star
variable [Star α] [Star β]
/-- A matrix is hermitian if it is equal to its conjugate transpose. On the reals, this definition
captures symmetric matrices. -/
def IsHermitian (A : Matrix n n α) : Prop := Aᴴ = A
#align matrix.is_hermitian Matrix.IsHermitian
instance (A : Matrix n n α) [Decidable (Aᴴ = A)] : Decidable (IsHermitian A) :=
inferInstanceAs <| Decidable (_ = _)
theorem IsHermitian.eq {A : Matrix n n α} (h : A.IsHermitian) : Aᴴ = A := h
#align matrix.is_hermitian.eq Matrix.IsHermitian.eq
protected theorem IsHermitian.isSelfAdjoint {A : Matrix n n α} (h : A.IsHermitian) :
IsSelfAdjoint A := h
#align matrix.is_hermitian.is_self_adjoint Matrix.IsHermitian.isSelfAdjoint
-- @[ext] -- Porting note: incorrect ext, not a structure or a lemma proving x = y
theorem IsHermitian.ext {A : Matrix n n α} : (∀ i j, star (A j i) = A i j) → A.IsHermitian := by
intro h; ext i j; exact h i j
#align matrix.is_hermitian.ext Matrix.IsHermitian.ext
theorem IsHermitian.apply {A : Matrix n n α} (h : A.IsHermitian) (i j : n) : star (A j i) = A i j :=
congr_fun (congr_fun h _) _
#align matrix.is_hermitian.apply Matrix.IsHermitian.apply
theorem IsHermitian.ext_iff {A : Matrix n n α} : A.IsHermitian ↔ ∀ i j, star (A j i) = A i j :=
⟨IsHermitian.apply, IsHermitian.ext⟩
#align matrix.is_hermitian.ext_iff Matrix.IsHermitian.ext_iff
@[simp]
theorem IsHermitian.map {A : Matrix n n α} (h : A.IsHermitian) (f : α → β)
(hf : Function.Semiconj f star star) : (A.map f).IsHermitian :=
(conjTranspose_map f hf).symm.trans <| h.eq.symm ▸ rfl
#align matrix.is_hermitian.map Matrix.IsHermitian.map
theorem IsHermitian.transpose {A : Matrix n n α} (h : A.IsHermitian) : Aᵀ.IsHermitian := by
rw [IsHermitian, conjTranspose, transpose_map]
exact congr_arg Matrix.transpose h
#align matrix.is_hermitian.transpose Matrix.IsHermitian.transpose
@[simp]
theorem isHermitian_transpose_iff (A : Matrix n n α) : Aᵀ.IsHermitian ↔ A.IsHermitian :=
⟨by intro h; rw [← transpose_transpose A]; exact IsHermitian.transpose h, IsHermitian.transpose⟩
#align matrix.is_hermitian_transpose_iff Matrix.isHermitian_transpose_iff
theorem IsHermitian.conjTranspose {A : Matrix n n α} (h : A.IsHermitian) : Aᴴ.IsHermitian :=
h.transpose.map _ fun _ => rfl
#align matrix.is_hermitian.conj_transpose Matrix.IsHermitian.conjTranspose
@[simp]
theorem IsHermitian.submatrix {A : Matrix n n α} (h : A.IsHermitian) (f : m → n) :
(A.submatrix f f).IsHermitian := (conjTranspose_submatrix _ _ _).trans (h.symm ▸ rfl)
#align matrix.is_hermitian.submatrix Matrix.IsHermitian.submatrix
@[simp]
theorem isHermitian_submatrix_equiv {A : Matrix n n α} (e : m ≃ n) :
(A.submatrix e e).IsHermitian ↔ A.IsHermitian :=
⟨fun h => by simpa using h.submatrix e.symm, fun h => h.submatrix _⟩
#align matrix.is_hermitian_submatrix_equiv Matrix.isHermitian_submatrix_equiv
end Star
section InvolutiveStar
variable [InvolutiveStar α]
@[simp]
theorem isHermitian_conjTranspose_iff (A : Matrix n n α) : Aᴴ.IsHermitian ↔ A.IsHermitian :=
IsSelfAdjoint.star_iff
#align matrix.is_hermitian_conj_transpose_iff Matrix.isHermitian_conjTranspose_iff
/-- A block matrix `A.from_blocks B C D` is hermitian,
if `A` and `D` are hermitian and `Bᴴ = C`. -/
theorem IsHermitian.fromBlocks {A : Matrix m m α} {B : Matrix m n α} {C : Matrix n m α}
{D : Matrix n n α} (hA : A.IsHermitian) (hBC : Bᴴ = C) (hD : D.IsHermitian) :
(A.fromBlocks B C D).IsHermitian := by
have hCB : Cᴴ = B := by rw [← hBC, conjTranspose_conjTranspose]
unfold Matrix.IsHermitian
rw [fromBlocks_conjTranspose, hBC, hCB, hA, hD]
#align matrix.is_hermitian.from_blocks Matrix.IsHermitian.fromBlocks
/-- This is the `iff` version of `Matrix.IsHermitian.fromBlocks`. -/
theorem isHermitian_fromBlocks_iff {A : Matrix m m α} {B : Matrix m n α} {C : Matrix n m α}
{D : Matrix n n α} :
(A.fromBlocks B C D).IsHermitian ↔ A.IsHermitian ∧ Bᴴ = C ∧ Cᴴ = B ∧ D.IsHermitian :=
⟨fun h =>
⟨congr_arg toBlocks₁₁ h, congr_arg toBlocks₂₁ h, congr_arg toBlocks₁₂ h,
congr_arg toBlocks₂₂ h⟩,
fun ⟨hA, hBC, _hCB, hD⟩ => IsHermitian.fromBlocks hA hBC hD⟩
#align matrix.is_hermitian_from_blocks_iff Matrix.isHermitian_fromBlocks_iff
end InvolutiveStar
section AddMonoid
variable [AddMonoid α] [StarAddMonoid α] [AddMonoid β] [StarAddMonoid β]
/-- A diagonal matrix is hermitian if the entries are self-adjoint (as a vector) -/
theorem isHermitian_diagonal_of_self_adjoint [DecidableEq n] (v : n → α) (h : IsSelfAdjoint v) :
(diagonal v).IsHermitian :=
(-- TODO: add a `pi.has_trivial_star` instance and remove the `funext`
diagonal_conjTranspose v).trans <| congr_arg _ h
#align matrix.is_hermitian_diagonal_of_self_adjoint Matrix.isHermitian_diagonal_of_self_adjoint
/-- A diagonal matrix is hermitian if each diagonal entry is self-adjoint -/
lemma isHermitian_diagonal_iff [DecidableEq n] {d : n → α} :
IsHermitian (diagonal d) ↔ (∀ i : n, IsSelfAdjoint (d i)) := by
simp [isSelfAdjoint_iff, IsHermitian, conjTranspose, diagonal_transpose, diagonal_map]
/-- A diagonal matrix is hermitian if the entries have the trivial `star` operation
(such as on the reals). -/
@[simp]
theorem isHermitian_diagonal [TrivialStar α] [DecidableEq n] (v : n → α) :
(diagonal v).IsHermitian :=
isHermitian_diagonal_of_self_adjoint _ (IsSelfAdjoint.all _)
#align matrix.is_hermitian_diagonal Matrix.isHermitian_diagonal
@[simp]
theorem isHermitian_zero : (0 : Matrix n n α).IsHermitian :=
isSelfAdjoint_zero _
#align matrix.is_hermitian_zero Matrix.isHermitian_zero
@[simp]
theorem IsHermitian.add {A B : Matrix n n α} (hA : A.IsHermitian) (hB : B.IsHermitian) :
(A + B).IsHermitian :=
IsSelfAdjoint.add hA hB
#align matrix.is_hermitian.add Matrix.IsHermitian.add
end AddMonoid
section AddCommMonoid
variable [AddCommMonoid α] [StarAddMonoid α]
theorem isHermitian_add_transpose_self (A : Matrix n n α) : (A + Aᴴ).IsHermitian :=
isSelfAdjoint_add_star_self A
#align matrix.is_hermitian_add_transpose_self Matrix.isHermitian_add_transpose_self
theorem isHermitian_transpose_add_self (A : Matrix n n α) : (Aᴴ + A).IsHermitian :=
isSelfAdjoint_star_add_self A
#align matrix.is_hermitian_transpose_add_self Matrix.isHermitian_transpose_add_self
end AddCommMonoid
section AddGroup
variable [AddGroup α] [StarAddMonoid α]
@[simp]
theorem IsHermitian.neg {A : Matrix n n α} (h : A.IsHermitian) : (-A).IsHermitian :=
IsSelfAdjoint.neg h
#align matrix.is_hermitian.neg Matrix.IsHermitian.neg
@[simp]
theorem IsHermitian.sub {A B : Matrix n n α} (hA : A.IsHermitian) (hB : B.IsHermitian) :
(A - B).IsHermitian :=
IsSelfAdjoint.sub hA hB
#align matrix.is_hermitian.sub Matrix.IsHermitian.sub
end AddGroup
section NonUnitalSemiring
variable [NonUnitalSemiring α] [StarRing α] [NonUnitalSemiring β] [StarRing β]
/-- Note this is more general than `IsSelfAdjoint.mul_star_self` as `B` can be rectangular. -/
theorem isHermitian_mul_conjTranspose_self [Fintype n] (A : Matrix m n α) :
(A * Aᴴ).IsHermitian := by rw [IsHermitian, conjTranspose_mul, conjTranspose_conjTranspose]
#align matrix.is_hermitian_mul_conj_transpose_self Matrix.isHermitian_mul_conjTranspose_self
/-- Note this is more general than `IsSelfAdjoint.star_mul_self` as `B` can be rectangular. -/
theorem isHermitian_transpose_mul_self [Fintype m] (A : Matrix m n α) : (Aᴴ * A).IsHermitian := by
rw [IsHermitian, conjTranspose_mul, conjTranspose_conjTranspose]
#align matrix.is_hermitian_transpose_mul_self Matrix.isHermitian_transpose_mul_self
/-- Note this is more general than `IsSelfAdjoint.conjugate'` as `B` can be rectangular. -/
theorem isHermitian_conjTranspose_mul_mul [Fintype m] {A : Matrix m m α} (B : Matrix m n α)
(hA : A.IsHermitian) : (Bᴴ * A * B).IsHermitian := by
simp only [IsHermitian, conjTranspose_mul, conjTranspose_conjTranspose, hA.eq, Matrix.mul_assoc]
#align matrix.is_hermitian_conj_transpose_mul_mul Matrix.isHermitian_conjTranspose_mul_mul
/-- Note this is more general than `IsSelfAdjoint.conjugate` as `B` can be rectangular. -/
theorem isHermitian_mul_mul_conjTranspose [Fintype m] {A : Matrix m m α} (B : Matrix n m α)
(hA : A.IsHermitian) : (B * A * Bᴴ).IsHermitian := by
simp only [IsHermitian, conjTranspose_mul, conjTranspose_conjTranspose, hA.eq, Matrix.mul_assoc]
#align matrix.is_hermitian_mul_mul_conj_transpose Matrix.isHermitian_mul_mul_conjTranspose
lemma commute_iff [Fintype n] {A B : Matrix n n α}
(hA : A.IsHermitian) (hB : B.IsHermitian) : Commute A B ↔ (A * B).IsHermitian :=
hA.isSelfAdjoint.commute_iff hB.isSelfAdjoint
end NonUnitalSemiring
section Semiring
variable [Semiring α] [StarRing α] [Semiring β] [StarRing β]
/-- Note this is more general for matrices than `isSelfAdjoint_one` as it does not
require `Fintype n`, which is necessary for `Monoid (Matrix n n R)`. -/
@[simp]
theorem isHermitian_one [DecidableEq n] : (1 : Matrix n n α).IsHermitian :=
conjTranspose_one
#align matrix.is_hermitian_one Matrix.isHermitian_one
theorem IsHermitian.pow [Fintype n] [DecidableEq n] {A : Matrix n n α} (h : A.IsHermitian) (k : ℕ) :
(A ^ k).IsHermitian := IsSelfAdjoint.pow h _
end Semiring
section CommRing
variable [CommRing α] [StarRing α]
theorem IsHermitian.inv [Fintype m] [DecidableEq m] {A : Matrix m m α} (hA : A.IsHermitian) :
A⁻¹.IsHermitian := by simp [IsHermitian, conjTranspose_nonsing_inv, hA.eq]
#align matrix.is_hermitian.inv Matrix.IsHermitian.inv
@[simp]
theorem isHermitian_inv [Fintype m] [DecidableEq m] (A : Matrix m m α) [Invertible A] :
A⁻¹.IsHermitian ↔ A.IsHermitian :=
⟨fun h => by rw [← inv_inv_of_invertible A]; exact IsHermitian.inv h, IsHermitian.inv⟩
#align matrix.is_hermitian_inv Matrix.isHermitian_inv
theorem IsHermitian.adjugate [Fintype m] [DecidableEq m] {A : Matrix m m α} (hA : A.IsHermitian) :
A.adjugate.IsHermitian := by simp [IsHermitian, adjugate_conjTranspose, hA.eq]
#align matrix.is_hermitian.adjugate Matrix.IsHermitian.adjugate
/-- Note that `IsSelfAdjoint.zpow` does not apply to matrices as they are not a division ring. -/
theorem IsHermitian.zpow [Fintype m] [DecidableEq m] {A : Matrix m m α} (h : A.IsHermitian)
(k : ℤ) :
(A ^ k).IsHermitian := by
rw [IsHermitian, conjTranspose_zpow, h]
end CommRing
section RCLike
open RCLike
variable [RCLike α] [RCLike β]
/-- The diagonal elements of a complex hermitian matrix are real. -/
| Mathlib/LinearAlgebra/Matrix/Hermitian.lean | 281 | 282 | theorem IsHermitian.coe_re_apply_self {A : Matrix n n α} (h : A.IsHermitian) (i : n) :
(re (A i i) : α) = A i i := by | rw [← conj_eq_iff_re, ← star_def, ← conjTranspose_apply, h.eq]
|
/-
Copyright (c) 2021 . All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.Group.Subgroup.ZPowers
import Mathlib.Algebra.Ring.Action.Basic
import Mathlib.GroupTheory.GroupAction.Basic
#align_import group_theory.group_action.conj_act from "leanprover-community/mathlib"@"4be589053caf347b899a494da75410deb55fb3ef"
/-!
# Conjugation action of a group on itself
This file defines the conjugation action of a group on itself. See also `MulAut.conj` for
the definition of conjugation as a homomorphism into the automorphism group.
## Main definitions
A type alias `ConjAct G` is introduced for a group `G`. The group `ConjAct G` acts on `G`
by conjugation. The group `ConjAct G` also acts on any normal subgroup of `G` by conjugation.
As a generalization, this also allows:
* `ConjAct Mˣ` to act on `M`, when `M` is a `Monoid`
* `ConjAct G₀` to act on `G₀`, when `G₀` is a `GroupWithZero`
## Implementation Notes
The scalar action in defined in this file can also be written using `MulAut.conj g • h`. This
has the advantage of not using the type alias `ConjAct`, but the downside of this approach
is that some theorems about the group actions will not apply when since this
`MulAut.conj g • h` describes an action of `MulAut G` on `G`, and not an action of `G`.
-/
variable (α M G G₀ R K : Type*)
/-- A type alias for a group `G`. `ConjAct G` acts on `G` by conjugation -/
def ConjAct : Type _ :=
G
#align conj_act ConjAct
namespace ConjAct
open MulAction Subgroup
variable {M G G₀ R K}
instance [Group G] : Group (ConjAct G) := ‹Group G›
instance [DivInvMonoid G] : DivInvMonoid (ConjAct G) := ‹DivInvMonoid G›
instance [GroupWithZero G] : GroupWithZero (ConjAct G) := ‹GroupWithZero G›
instance [Fintype G] : Fintype (ConjAct G) := ‹Fintype G›
@[simp]
theorem card [Fintype G] : Fintype.card (ConjAct G) = Fintype.card G :=
rfl
#align conj_act.card ConjAct.card
section DivInvMonoid
variable [DivInvMonoid G]
instance : Inhabited (ConjAct G) :=
⟨1⟩
/-- Reinterpret `g : ConjAct G` as an element of `G`. -/
def ofConjAct : ConjAct G ≃* G where
toFun := id
invFun := id
left_inv := fun _ => rfl
right_inv := fun _ => rfl
map_mul' := fun _ _ => rfl
#align conj_act.of_conj_act ConjAct.ofConjAct
/-- Reinterpret `g : G` as an element of `ConjAct G`. -/
def toConjAct : G ≃* ConjAct G :=
ofConjAct.symm
#align conj_act.to_conj_act ConjAct.toConjAct
/-- A recursor for `ConjAct`, for use as `induction x using ConjAct.rec` when `x : ConjAct G`. -/
protected def rec {C : ConjAct G → Sort*} (h : ∀ g, C (toConjAct g)) : ∀ g, C g :=
h
#align conj_act.rec ConjAct.rec
@[simp]
theorem «forall» (p : ConjAct G → Prop) : (∀ x : ConjAct G, p x) ↔ ∀ x : G, p (toConjAct x) :=
id Iff.rfl
#align conj_act.forall ConjAct.forall
@[simp]
theorem of_mul_symm_eq : (@ofConjAct G _).symm = toConjAct :=
rfl
#align conj_act.of_mul_symm_eq ConjAct.of_mul_symm_eq
@[simp]
theorem to_mul_symm_eq : (@toConjAct G _).symm = ofConjAct :=
rfl
#align conj_act.to_mul_symm_eq ConjAct.to_mul_symm_eq
@[simp]
theorem toConjAct_ofConjAct (x : ConjAct G) : toConjAct (ofConjAct x) = x :=
rfl
#align conj_act.to_conj_act_of_conj_act ConjAct.toConjAct_ofConjAct
@[simp]
theorem ofConjAct_toConjAct (x : G) : ofConjAct (toConjAct x) = x :=
rfl
#align conj_act.of_conj_act_to_conj_act ConjAct.ofConjAct_toConjAct
-- Porting note (#11119): removed `simp` attribute because `simpNF` says it can prove it
theorem ofConjAct_one : ofConjAct (1 : ConjAct G) = 1 :=
rfl
#align conj_act.of_conj_act_one ConjAct.ofConjAct_one
-- Porting note (#11119): removed `simp` attribute because `simpNF` says it can prove it
theorem toConjAct_one : toConjAct (1 : G) = 1 :=
rfl
#align conj_act.to_conj_act_one ConjAct.toConjAct_one
@[simp]
theorem ofConjAct_inv (x : ConjAct G) : ofConjAct x⁻¹ = (ofConjAct x)⁻¹ :=
rfl
#align conj_act.of_conj_act_inv ConjAct.ofConjAct_inv
@[simp]
theorem toConjAct_inv (x : G) : toConjAct x⁻¹ = (toConjAct x)⁻¹ :=
rfl
#align conj_act.to_conj_act_inv ConjAct.toConjAct_inv
-- Porting note (#11119): removed `simp` attribute because `simpNF` says it can prove it
theorem ofConjAct_mul (x y : ConjAct G) : ofConjAct (x * y) = ofConjAct x * ofConjAct y :=
rfl
#align conj_act.of_conj_act_mul ConjAct.ofConjAct_mul
-- Porting note (#11119): removed `simp` attribute because `simpNF` says it can prove it
theorem toConjAct_mul (x y : G) : toConjAct (x * y) = toConjAct x * toConjAct y :=
rfl
#align conj_act.to_conj_act_mul ConjAct.toConjAct_mul
instance : SMul (ConjAct G) G where smul g h := ofConjAct g * h * (ofConjAct g)⁻¹
theorem smul_def (g : ConjAct G) (h : G) : g • h = ofConjAct g * h * (ofConjAct g)⁻¹ :=
rfl
#align conj_act.smul_def ConjAct.smul_def
end DivInvMonoid
section Units
section Monoid
variable [Monoid M]
instance unitsScalar : SMul (ConjAct Mˣ) M where smul g h := ofConjAct g * h * ↑(ofConjAct g)⁻¹
#align conj_act.has_units_scalar ConjAct.unitsScalar
theorem units_smul_def (g : ConjAct Mˣ) (h : M) : g • h = ofConjAct g * h * ↑(ofConjAct g)⁻¹ :=
rfl
#align conj_act.units_smul_def ConjAct.units_smul_def
-- porting note (#11083): very slow without `simp only` and need to separate `units_smul_def`
-- so that things trigger appropriately
instance unitsMulDistribMulAction : MulDistribMulAction (ConjAct Mˣ) M where
one_smul := by simp only [units_smul_def, ofConjAct_one, Units.val_one, one_mul, inv_one,
mul_one, forall_const]
mul_smul := by
simp only [units_smul_def]
simp only [map_mul, Units.val_mul, mul_assoc, mul_inv_rev, forall_const, «forall»]
smul_mul := by
simp only [units_smul_def]
simp only [mul_assoc, Units.inv_mul_cancel_left, forall_const, «forall»]
smul_one := by simp [units_smul_def, mul_one, Units.mul_inv, «forall», forall_const]
#align conj_act.units_mul_distrib_mul_action ConjAct.unitsMulDistribMulAction
instance unitsSMulCommClass [SMul α M] [SMulCommClass α M M] [IsScalarTower α M M] :
SMulCommClass α (ConjAct Mˣ) M where
smul_comm a um m := by rw [units_smul_def, units_smul_def, mul_smul_comm, smul_mul_assoc]
#align conj_act.units_smul_comm_class ConjAct.unitsSMulCommClass
instance unitsSMulCommClass' [SMul α M] [SMulCommClass M α M] [IsScalarTower α M M] :
SMulCommClass (ConjAct Mˣ) α M :=
haveI : SMulCommClass α M M := SMulCommClass.symm _ _ _
SMulCommClass.symm _ _ _
#align conj_act.units_smul_comm_class' ConjAct.unitsSMulCommClass'
end Monoid
section Semiring
variable [Semiring R]
-- porting note (#11083): very slow without `simp only` and need to separate `units_smul_def`
-- so that things trigger appropriately
instance unitsMulSemiringAction : MulSemiringAction (ConjAct Rˣ) R :=
{ ConjAct.unitsMulDistribMulAction with
smul_zero := by
simp only [units_smul_def, mul_zero, zero_mul, «forall», forall_const]
smul_add := by
simp only [units_smul_def]
simp only [mul_add, add_mul, forall_const, «forall»] }
#align conj_act.units_mul_semiring_action ConjAct.unitsMulSemiringAction
end Semiring
end Units
section GroupWithZero
variable [GroupWithZero G₀]
-- Porting note (#11119): removed `simp` attribute because `simpNF` says it can prove it
theorem ofConjAct_zero : ofConjAct (0 : ConjAct G₀) = 0 :=
rfl
#align conj_act.of_conj_act_zero ConjAct.ofConjAct_zero
-- Porting note (#11119): removed `simp` attribute because `simpNF` says it can prove it
theorem toConjAct_zero : toConjAct (0 : G₀) = 0 :=
rfl
#align conj_act.to_conj_act_zero ConjAct.toConjAct_zero
-- porting note (#11083): very slow without `simp only` and need to separate `smul_def`
-- so that things trigger appropriately
instance mulAction₀ : MulAction (ConjAct G₀) G₀ where
one_smul := by
simp only [smul_def]
simp only [map_one, one_mul, inv_one, mul_one, forall_const]
mul_smul := by
simp only [smul_def]
simp only [map_mul, mul_assoc, mul_inv_rev, forall_const, «forall»]
#align conj_act.mul_action₀ ConjAct.mulAction₀
instance smulCommClass₀ [SMul α G₀] [SMulCommClass α G₀ G₀] [IsScalarTower α G₀ G₀] :
SMulCommClass α (ConjAct G₀) G₀ where
smul_comm a ug g := by rw [smul_def, smul_def, mul_smul_comm, smul_mul_assoc]
#align conj_act.smul_comm_class₀ ConjAct.smulCommClass₀
instance smulCommClass₀' [SMul α G₀] [SMulCommClass G₀ α G₀] [IsScalarTower α G₀ G₀] :
SMulCommClass (ConjAct G₀) α G₀ :=
haveI := SMulCommClass.symm G₀ α G₀
SMulCommClass.symm _ _ _
#align conj_act.smul_comm_class₀' ConjAct.smulCommClass₀'
end GroupWithZero
section DivisionRing
variable [DivisionRing K]
-- porting note (#11083): very slow without `simp only` and need to separate `smul_def`
-- so that things trigger appropriately
instance distribMulAction₀ : DistribMulAction (ConjAct K) K :=
{ ConjAct.mulAction₀ with
smul_zero := by
simp only [smul_def]
simp only [mul_zero, zero_mul, «forall», forall_const]
smul_add := by
simp only [smul_def]
simp only [mul_add, add_mul, forall_const, «forall»] }
#align conj_act.distrib_mul_action₀ ConjAct.distribMulAction₀
end DivisionRing
variable [Group G]
-- todo: this file is not in good order; I will refactor this after the PR
-- porting note (#11083): very slow without `simp only` and need to separate `smul_def`
-- so that things trigger appropriately
instance : MulDistribMulAction (ConjAct G) G where
smul_mul := by
simp only [smul_def]
simp only [mul_assoc, inv_mul_cancel_left, forall_const, «forall»]
smul_one := by simp only [smul_def, mul_one, mul_right_inv, «forall», forall_const]
one_smul := by simp only [smul_def, ofConjAct_one, one_mul, inv_one, mul_one, forall_const]
mul_smul := by
simp only [smul_def]
simp only [map_mul, mul_assoc, mul_inv_rev, forall_const, «forall»]
instance smulCommClass [SMul α G] [SMulCommClass α G G] [IsScalarTower α G G] :
SMulCommClass α (ConjAct G) G where
smul_comm a ug g := by rw [smul_def, smul_def, mul_smul_comm, smul_mul_assoc]
#align conj_act.smul_comm_class ConjAct.smulCommClass
instance smulCommClass' [SMul α G] [SMulCommClass G α G] [IsScalarTower α G G] :
SMulCommClass (ConjAct G) α G :=
haveI := SMulCommClass.symm G α G
SMulCommClass.symm _ _ _
#align conj_act.smul_comm_class' ConjAct.smulCommClass'
theorem smul_eq_mulAut_conj (g : ConjAct G) (h : G) : g • h = MulAut.conj (ofConjAct g) h :=
rfl
#align conj_act.smul_eq_mul_aut_conj ConjAct.smul_eq_mulAut_conj
/-- The set of fixed points of the conjugation action of `G` on itself is the center of `G`. -/
theorem fixedPoints_eq_center : fixedPoints (ConjAct G) G = center G := by
ext x
simp [mem_center_iff, smul_def, mul_inv_eq_iff_eq_mul]
#align conj_act.fixed_points_eq_center ConjAct.fixedPoints_eq_center
@[simp]
| Mathlib/GroupTheory/GroupAction/ConjAct.lean | 306 | 307 | theorem mem_orbit_conjAct {g h : G} : g ∈ orbit (ConjAct G) h ↔ IsConj g h := by |
rw [isConj_comm, isConj_iff, mem_orbit_iff]; rfl
|
/-
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.Probability.Kernel.Composition
import Mathlib.MeasureTheory.Integral.SetIntegral
#align_import probability.kernel.integral_comp_prod from "leanprover-community/mathlib"@"c0d694db494dd4f9aa57f2714b6e4c82b4ebc113"
/-!
# Bochner integral of a function against the composition-product of two kernels
We prove properties of the composition-product of two kernels. If `κ` is an s-finite kernel from
`α` to `β` and `η` is an s-finite kernel from `α × β` to `γ`, we can form their composition-product
`κ ⊗ₖ η : kernel α (β × γ)`. We proved in `ProbabilityTheory.kernel.lintegral_compProd` that it
verifies `∫⁻ bc, f bc ∂((κ ⊗ₖ η) a) = ∫⁻ b, ∫⁻ c, f (b, c) ∂(η (a, b)) ∂(κ a)`. In this file, we
prove the same equality for the Bochner integral.
## Main statements
* `ProbabilityTheory.integral_compProd`: the integral against the composition-product is
`∫ z, f z ∂((κ ⊗ₖ η) a) = ∫ x, ∫ y, f (x, y) ∂(η (a, x)) ∂(κ a)`
## Implementation details
This file is to a large extent a copy of part of
`Mathlib/MeasureTheory/Constructions/Prod/Basic.lean`. The product of
two measures is a particular case of composition-product of kernels and it turns out that once the
measurablity of the Lebesgue integral of a kernel is proved, almost all proofs about integrals
against products of measures extend with minimal modifications to the composition-product of two
kernels.
-/
noncomputable section
open scoped Topology ENNReal MeasureTheory ProbabilityTheory
open Set Function Real ENNReal MeasureTheory Filter ProbabilityTheory ProbabilityTheory.kernel
variable {α β γ E : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β}
{mγ : MeasurableSpace γ} [NormedAddCommGroup E] {κ : kernel α β} [IsSFiniteKernel κ]
{η : kernel (α × β) γ} [IsSFiniteKernel η] {a : α}
namespace ProbabilityTheory
theorem hasFiniteIntegral_prod_mk_left (a : α) {s : Set (β × γ)} (h2s : (κ ⊗ₖ η) a s ≠ ∞) :
HasFiniteIntegral (fun b => (η (a, b) (Prod.mk b ⁻¹' s)).toReal) (κ a) := by
let t := toMeasurable ((κ ⊗ₖ η) a) s
simp_rw [HasFiniteIntegral, ennnorm_eq_ofReal toReal_nonneg]
calc
∫⁻ b, ENNReal.ofReal (η (a, b) (Prod.mk b ⁻¹' s)).toReal ∂κ a
_ ≤ ∫⁻ b, η (a, b) (Prod.mk b ⁻¹' t) ∂κ a := by
refine lintegral_mono_ae ?_
filter_upwards [ae_kernel_lt_top a h2s] with b hb
rw [ofReal_toReal hb.ne]
exact measure_mono (preimage_mono (subset_toMeasurable _ _))
_ ≤ (κ ⊗ₖ η) a t := le_compProd_apply _ _ _ _
_ = (κ ⊗ₖ η) a s := measure_toMeasurable s
_ < ⊤ := h2s.lt_top
#align probability_theory.has_finite_integral_prod_mk_left ProbabilityTheory.hasFiniteIntegral_prod_mk_left
theorem integrable_kernel_prod_mk_left (a : α) {s : Set (β × γ)} (hs : MeasurableSet s)
(h2s : (κ ⊗ₖ η) a s ≠ ∞) : Integrable (fun b => (η (a, b) (Prod.mk b ⁻¹' s)).toReal) (κ a) := by
constructor
· exact (measurable_kernel_prod_mk_left' hs a).ennreal_toReal.aestronglyMeasurable
· exact hasFiniteIntegral_prod_mk_left a h2s
#align probability_theory.integrable_kernel_prod_mk_left ProbabilityTheory.integrable_kernel_prod_mk_left
theorem _root_.MeasureTheory.AEStronglyMeasurable.integral_kernel_compProd [NormedSpace ℝ E]
⦃f : β × γ → E⦄ (hf : AEStronglyMeasurable f ((κ ⊗ₖ η) a)) :
AEStronglyMeasurable (fun x => ∫ y, f (x, y) ∂η (a, x)) (κ a) :=
⟨fun x => ∫ y, hf.mk f (x, y) ∂η (a, x), hf.stronglyMeasurable_mk.integral_kernel_prod_right'', by
filter_upwards [ae_ae_of_ae_compProd hf.ae_eq_mk] with _ hx using integral_congr_ae hx⟩
#align measure_theory.ae_strongly_measurable.integral_kernel_comp_prod MeasureTheory.AEStronglyMeasurable.integral_kernel_compProd
theorem _root_.MeasureTheory.AEStronglyMeasurable.compProd_mk_left {δ : Type*} [TopologicalSpace δ]
{f : β × γ → δ} (hf : AEStronglyMeasurable f ((κ ⊗ₖ η) a)) :
∀ᵐ x ∂κ a, AEStronglyMeasurable (fun y => f (x, y)) (η (a, x)) := by
filter_upwards [ae_ae_of_ae_compProd hf.ae_eq_mk] with x hx using
⟨fun y => hf.mk f (x, y), hf.stronglyMeasurable_mk.comp_measurable measurable_prod_mk_left, hx⟩
#align measure_theory.ae_strongly_measurable.comp_prod_mk_left MeasureTheory.AEStronglyMeasurable.compProd_mk_left
/-! ### Integrability -/
theorem hasFiniteIntegral_compProd_iff ⦃f : β × γ → E⦄ (h1f : StronglyMeasurable f) :
HasFiniteIntegral f ((κ ⊗ₖ η) a) ↔
(∀ᵐ x ∂κ a, HasFiniteIntegral (fun y => f (x, y)) (η (a, x))) ∧
HasFiniteIntegral (fun x => ∫ y, ‖f (x, y)‖ ∂η (a, x)) (κ a) := by
simp only [HasFiniteIntegral]
rw [kernel.lintegral_compProd _ _ _ h1f.ennnorm]
have : ∀ x, ∀ᵐ y ∂η (a, x), 0 ≤ ‖f (x, y)‖ := fun x => eventually_of_forall fun y => norm_nonneg _
simp_rw [integral_eq_lintegral_of_nonneg_ae (this _)
(h1f.norm.comp_measurable measurable_prod_mk_left).aestronglyMeasurable,
ennnorm_eq_ofReal toReal_nonneg, ofReal_norm_eq_coe_nnnorm]
have : ∀ {p q r : Prop} (_ : r → p), (r ↔ p ∧ q) ↔ p → (r ↔ q) := fun {p q r} h1 => by
rw [← and_congr_right_iff, and_iff_right_of_imp h1]
rw [this]
· intro h2f; rw [lintegral_congr_ae]
filter_upwards [h2f] with x hx
rw [ofReal_toReal]; rw [← lt_top_iff_ne_top]; exact hx
· intro h2f; refine ae_lt_top ?_ h2f.ne; exact h1f.ennnorm.lintegral_kernel_prod_right''
#align probability_theory.has_finite_integral_comp_prod_iff ProbabilityTheory.hasFiniteIntegral_compProd_iff
theorem hasFiniteIntegral_compProd_iff' ⦃f : β × γ → E⦄
(h1f : AEStronglyMeasurable f ((κ ⊗ₖ η) a)) :
HasFiniteIntegral f ((κ ⊗ₖ η) a) ↔
(∀ᵐ x ∂κ a, HasFiniteIntegral (fun y => f (x, y)) (η (a, x))) ∧
HasFiniteIntegral (fun x => ∫ y, ‖f (x, y)‖ ∂η (a, x)) (κ a) := by
rw [hasFiniteIntegral_congr h1f.ae_eq_mk,
hasFiniteIntegral_compProd_iff h1f.stronglyMeasurable_mk]
apply and_congr
· apply eventually_congr
filter_upwards [ae_ae_of_ae_compProd h1f.ae_eq_mk.symm] with x hx using
hasFiniteIntegral_congr hx
· apply hasFiniteIntegral_congr
filter_upwards [ae_ae_of_ae_compProd h1f.ae_eq_mk.symm] with _ hx using
integral_congr_ae (EventuallyEq.fun_comp hx _)
#align probability_theory.has_finite_integral_comp_prod_iff' ProbabilityTheory.hasFiniteIntegral_compProd_iff'
| Mathlib/Probability/Kernel/IntegralCompProd.lean | 123 | 128 | theorem integrable_compProd_iff ⦃f : β × γ → E⦄ (hf : AEStronglyMeasurable f ((κ ⊗ₖ η) a)) :
Integrable f ((κ ⊗ₖ η) a) ↔
(∀ᵐ x ∂κ a, Integrable (fun y => f (x, y)) (η (a, x))) ∧
Integrable (fun x => ∫ y, ‖f (x, y)‖ ∂η (a, x)) (κ a) := by |
simp only [Integrable, hasFiniteIntegral_compProd_iff' hf, hf.norm.integral_kernel_compProd,
hf, hf.compProd_mk_left, eventually_and, true_and_iff]
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.GroupRingAction
import Mathlib.Algebra.Ring.Action.Invariant
import Mathlib.FieldTheory.Normal
import Mathlib.FieldTheory.Separable
import Mathlib.FieldTheory.Tower
#align_import field_theory.fixed from "leanprover-community/mathlib"@"039a089d2a4b93c761b234f3e5f5aeb752bac60f"
/-!
# Fixed field under a group action.
This is the basis of the Fundamental Theorem of Galois Theory.
Given a (finite) group `G` that acts on a field `F`, we define `FixedPoints.subfield G F`,
the subfield consisting of elements of `F` fixed_points by every element of `G`.
This subfield is then normal and separable, and in addition (TODO) if `G` acts faithfully on `F`
then `finrank (FixedPoints.subfield G F) F = Fintype.card G`.
## Main Definitions
- `FixedPoints.subfield G F`, the subfield consisting of elements of `F` fixed_points by every
element of `G`, where `G` is a group that acts on `F`.
-/
noncomputable section
open scoped Classical
open MulAction Finset FiniteDimensional
universe u v w
variable {M : Type u} [Monoid M]
variable (G : Type u) [Group G]
variable (F : Type v) [Field F] [MulSemiringAction M F] [MulSemiringAction G F] (m : M)
/-- The subfield of F fixed by the field endomorphism `m`. -/
def FixedBy.subfield : Subfield F where
carrier := fixedBy F m
zero_mem' := smul_zero m
add_mem' hx hy := (smul_add m _ _).trans <| congr_arg₂ _ hx hy
neg_mem' hx := (smul_neg m _).trans <| congr_arg _ hx
one_mem' := smul_one m
mul_mem' hx hy := (smul_mul' m _ _).trans <| congr_arg₂ _ hx hy
inv_mem' x hx := (smul_inv'' m x).trans <| congr_arg _ hx
#align fixed_by.subfield FixedBy.subfield
section InvariantSubfields
variable (M) {F}
/-- A typeclass for subrings invariant under a `MulSemiringAction`. -/
class IsInvariantSubfield (S : Subfield F) : Prop where
smul_mem : ∀ (m : M) {x : F}, x ∈ S → m • x ∈ S
#align is_invariant_subfield IsInvariantSubfield
variable (S : Subfield F)
instance IsInvariantSubfield.toMulSemiringAction [IsInvariantSubfield M S] :
MulSemiringAction M S where
smul m x := ⟨m • x.1, IsInvariantSubfield.smul_mem m x.2⟩
one_smul s := Subtype.eq <| one_smul M s.1
mul_smul m₁ m₂ s := Subtype.eq <| mul_smul m₁ m₂ s.1
smul_add m s₁ s₂ := Subtype.eq <| smul_add m s₁.1 s₂.1
smul_zero m := Subtype.eq <| smul_zero m
smul_one m := Subtype.eq <| smul_one m
smul_mul m s₁ s₂ := Subtype.eq <| smul_mul' m s₁.1 s₂.1
#align is_invariant_subfield.to_mul_semiring_action IsInvariantSubfield.toMulSemiringAction
instance [IsInvariantSubfield M S] : IsInvariantSubring M S.toSubring where
smul_mem := IsInvariantSubfield.smul_mem
end InvariantSubfields
namespace FixedPoints
variable (M)
-- we use `Subfield.copy` so that the underlying set is `fixedPoints M F`
/-- The subfield of fixed points by a monoid action. -/
def subfield : Subfield F :=
Subfield.copy (⨅ m : M, FixedBy.subfield F m) (fixedPoints M F)
(by ext z; simp [fixedPoints, FixedBy.subfield, iInf, Subfield.mem_sInf]; rfl)
#align fixed_points.subfield FixedPoints.subfield
instance : IsInvariantSubfield M (FixedPoints.subfield M F) where
smul_mem g x hx g' := by rw [hx, hx]
instance : SMulCommClass M (FixedPoints.subfield M F) F where
smul_comm m f f' := show m • (↑f * f') = f * m • f' by rw [smul_mul', f.prop m]
instance smulCommClass' : SMulCommClass (FixedPoints.subfield M F) M F :=
SMulCommClass.symm _ _ _
#align fixed_points.smul_comm_class' FixedPoints.smulCommClass'
@[simp]
theorem smul (m : M) (x : FixedPoints.subfield M F) : m • x = x :=
Subtype.eq <| x.2 m
#align fixed_points.smul FixedPoints.smul
-- Why is this so slow?
@[simp]
theorem smul_polynomial (m : M) (p : Polynomial (FixedPoints.subfield M F)) : m • p = p :=
Polynomial.induction_on p (fun x => by rw [Polynomial.smul_C, smul])
(fun p q ihp ihq => by rw [smul_add, ihp, ihq]) fun n x _ => by
rw [smul_mul', Polynomial.smul_C, smul, smul_pow', Polynomial.smul_X]
#align fixed_points.smul_polynomial FixedPoints.smul_polynomial
instance : Algebra (FixedPoints.subfield M F) F := by infer_instance
theorem coe_algebraMap :
algebraMap (FixedPoints.subfield M F) F = Subfield.subtype (FixedPoints.subfield M F) :=
rfl
#align fixed_points.coe_algebra_map FixedPoints.coe_algebraMap
theorem linearIndependent_smul_of_linearIndependent {s : Finset F} :
(LinearIndependent (FixedPoints.subfield G F) fun i : (s : Set F) => (i : F)) →
LinearIndependent F fun i : (s : Set F) => MulAction.toFun G F i := by
haveI : IsEmpty ((∅ : Finset F) : Set F) := by simp
refine Finset.induction_on s (fun _ => linearIndependent_empty_type) fun a s has ih hs => ?_
rw [coe_insert] at hs ⊢
rw [linearIndependent_insert (mt mem_coe.1 has)] at hs
rw [linearIndependent_insert' (mt mem_coe.1 has)]; refine ⟨ih hs.1, fun ha => ?_⟩
rw [Finsupp.mem_span_image_iff_total] at ha; rcases ha with ⟨l, hl, hla⟩
rw [Finsupp.total_apply_of_mem_supported F hl] at hla
suffices ∀ i ∈ s, l i ∈ FixedPoints.subfield G F by
replace hla := (sum_apply _ _ fun i => l i • toFun G F i).symm.trans (congr_fun hla 1)
simp_rw [Pi.smul_apply, toFun_apply, one_smul] at hla
refine hs.2 (hla ▸ Submodule.sum_mem _ fun c hcs => ?_)
change (⟨l c, this c hcs⟩ : FixedPoints.subfield G F) • c ∈ _
exact Submodule.smul_mem _ _ (Submodule.subset_span <| mem_coe.2 hcs)
intro i his g
refine
eq_of_sub_eq_zero
(linearIndependent_iff'.1 (ih hs.1) s.attach (fun i => g • l i - l i) ?_ ⟨i, his⟩
(mem_attach _ _) :
_)
refine (sum_attach s fun i ↦ (g • l i - l i) • MulAction.toFun G F i).trans ?_
ext g'; dsimp only
conv_lhs =>
rw [sum_apply]
congr
· skip
· ext
rw [Pi.smul_apply, sub_smul, smul_eq_mul]
rw [sum_sub_distrib, Pi.zero_apply, sub_eq_zero]
conv_lhs =>
congr
· skip
· ext x
rw [toFun_apply, ← mul_inv_cancel_left g g', mul_smul, ← smul_mul', ← toFun_apply _ x]
show
(∑ x ∈ s, g • (fun y => l y • MulAction.toFun G F y) x (g⁻¹ * g')) =
∑ x ∈ s, (fun y => l y • MulAction.toFun G F y) x g'
rw [← smul_sum, ← sum_apply _ _ fun y => l y • toFun G F y, ←
sum_apply _ _ fun y => l y • toFun G F y]
rw [hla, toFun_apply, toFun_apply, smul_smul, mul_inv_cancel_left]
#align fixed_points.linear_independent_smul_of_linear_independent FixedPoints.linearIndependent_smul_of_linearIndependent
section Fintype
variable [Fintype G] (x : F)
/-- `minpoly G F x` is the minimal polynomial of `(x : F)` over `FixedPoints.subfield G F`. -/
def minpoly : Polynomial (FixedPoints.subfield G F) :=
(prodXSubSMul G F x).toSubring (FixedPoints.subfield G F).toSubring fun _ hc g =>
let ⟨n, _, hn⟩ := Polynomial.mem_coeffs_iff.1 hc
hn.symm ▸ prodXSubSMul.coeff G F x g n
#align fixed_points.minpoly FixedPoints.minpoly
namespace minpoly
theorem monic : (minpoly G F x).Monic := by
simp only [minpoly, Polynomial.monic_toSubring];
exact prodXSubSMul.monic G F x
#align fixed_points.minpoly.monic FixedPoints.minpoly.monic
theorem eval₂ :
Polynomial.eval₂ (Subring.subtype <| (FixedPoints.subfield G F).toSubring) x (minpoly G F x) =
0 := by
rw [← prodXSubSMul.eval G F x, Polynomial.eval₂_eq_eval_map]
simp only [minpoly, Polynomial.map_toSubring]
#align fixed_points.minpoly.eval₂ FixedPoints.minpoly.eval₂
theorem eval₂' :
Polynomial.eval₂ (Subfield.subtype <| FixedPoints.subfield G F) x (minpoly G F x) = 0 :=
eval₂ G F x
#align fixed_points.minpoly.eval₂' FixedPoints.minpoly.eval₂'
theorem ne_one : minpoly G F x ≠ (1 : Polynomial (FixedPoints.subfield G F)) := fun H =>
have := eval₂ G F x
(one_ne_zero : (1 : F) ≠ 0) <| by rwa [H, Polynomial.eval₂_one] at this
#align fixed_points.minpoly.ne_one FixedPoints.minpoly.ne_one
theorem of_eval₂ (f : Polynomial (FixedPoints.subfield G F))
(hf : Polynomial.eval₂ (Subfield.subtype <| FixedPoints.subfield G F) x f = 0) :
minpoly G F x ∣ f := by
-- Porting note: the two `have` below were not needed.
have : (subfield G F).subtype = (subfield G F).toSubring.subtype := rfl
have h : Polynomial.map (MulSemiringActionHom.toRingHom (IsInvariantSubring.subtypeHom G
(subfield G F).toSubring)) f = Polynomial.map
((IsInvariantSubring.subtypeHom G (subfield G F).toSubring)) f := rfl
erw [← Polynomial.map_dvd_map' (Subfield.subtype <| FixedPoints.subfield G F), minpoly, this,
Polynomial.map_toSubring _ _, prodXSubSMul]
refine
Fintype.prod_dvd_of_coprime
(Polynomial.pairwise_coprime_X_sub_C <| MulAction.injective_ofQuotientStabilizer G x) fun y =>
QuotientGroup.induction_on y fun g => ?_
rw [Polynomial.dvd_iff_isRoot, Polynomial.IsRoot.def, MulAction.ofQuotientStabilizer_mk,
Polynomial.eval_smul', ← this, ← Subfield.toSubring_subtype_eq_subtype, ←
IsInvariantSubring.coe_subtypeHom' G (FixedPoints.subfield G F).toSubring, h,
← MulSemiringActionHom.coe_polynomial, ← MulSemiringActionHom.map_smul, smul_polynomial,
MulSemiringActionHom.coe_polynomial, ← h, IsInvariantSubring.coe_subtypeHom',
Polynomial.eval_map, Subfield.toSubring_subtype_eq_subtype, hf, smul_zero]
#align fixed_points.minpoly.of_eval₂ FixedPoints.minpoly.of_eval₂
-- Why is this so slow?
| Mathlib/FieldTheory/Fixed.lean | 225 | 241 | theorem irreducible_aux (f g : Polynomial (FixedPoints.subfield G F)) (hf : f.Monic) (hg : g.Monic)
(hfg : f * g = minpoly G F x) : f = 1 ∨ g = 1 := by |
have hf2 : f ∣ minpoly G F x := by rw [← hfg]; exact dvd_mul_right _ _
have hg2 : g ∣ minpoly G F x := by rw [← hfg]; exact dvd_mul_left _ _
have := eval₂ G F x
rw [← hfg, Polynomial.eval₂_mul, mul_eq_zero] at this
cases' this with this this
· right
have hf3 : f = minpoly G F x :=
Polynomial.eq_of_monic_of_associated hf (monic G F x)
(associated_of_dvd_dvd hf2 <| @of_eval₂ G _ F _ _ _ x f this)
rwa [← mul_one (minpoly G F x), hf3, mul_right_inj' (monic G F x).ne_zero] at hfg
· left
have hg3 : g = minpoly G F x :=
Polynomial.eq_of_monic_of_associated hg (monic G F x)
(associated_of_dvd_dvd hg2 <| @of_eval₂ G _ F _ _ _ x g this)
rwa [← one_mul (minpoly G F x), hg3, mul_left_inj' (monic G F x).ne_zero] at hfg
|
/-
Copyright (c) 2022 Alex J. Best. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex J. Best, Yaël Dillies
-/
import Mathlib.Algebra.Order.Hom.Ring
import Mathlib.Algebra.Order.Pointwise
import Mathlib.Analysis.SpecialFunctions.Pow.Real
#align_import algebra.order.complete_field from "leanprover-community/mathlib"@"0b9eaaa7686280fad8cce467f5c3c57ee6ce77f8"
/-!
# Conditionally complete linear ordered fields
This file shows that the reals are unique, or, more formally, given a type satisfying the common
axioms of the reals (field, conditionally complete, linearly ordered) that there is an isomorphism
preserving these properties to the reals. This is `LinearOrderedField.inducedOrderRingIso` for `ℚ`.
Moreover this isomorphism is unique.
We introduce definitions of conditionally complete linear ordered fields, and show all such are
archimedean. We also construct the natural map from a `LinearOrderedField` to such a field.
## Main definitions
* `ConditionallyCompleteLinearOrderedField`: A field satisfying the standard axiomatization of
the real numbers, being a Dedekind complete and linear ordered field.
* `LinearOrderedField.inducedMap`: A (unique) map from any archimedean linear ordered field to a
conditionally complete linear ordered field. Various bundlings are available.
## Main results
* `LinearOrderedField.uniqueOrderRingHom` : Uniqueness of `OrderRingHom`s from an archimedean
linear ordered field to a conditionally complete linear ordered field.
* `LinearOrderedField.uniqueOrderRingIso` : Uniqueness of `OrderRingIso`s between two
conditionally complete linearly ordered fields.
## References
* https://mathoverflow.net/questions/362991/
who-first-characterized-the-real-numbers-as-the-unique-complete-ordered-field
## Tags
reals, conditionally complete, ordered field, uniqueness
-/
variable {F α β γ : Type*}
noncomputable section
open Function Rat Real Set
open scoped Classical Pointwise
/-- A field which is both linearly ordered and conditionally complete with respect to the order.
This axiomatizes the reals. -/
-- @[protect_proj] -- Porting note: does not exist anymore
class ConditionallyCompleteLinearOrderedField (α : Type*) extends
LinearOrderedField α, ConditionallyCompleteLinearOrder α
#align conditionally_complete_linear_ordered_field ConditionallyCompleteLinearOrderedField
-- see Note [lower instance priority]
/-- Any conditionally complete linearly ordered field is archimedean. -/
instance (priority := 100) ConditionallyCompleteLinearOrderedField.to_archimedean
[ConditionallyCompleteLinearOrderedField α] : Archimedean α :=
archimedean_iff_nat_lt.2
(by
by_contra! h
obtain ⟨x, h⟩ := h
have := csSup_le _ _ (range_nonempty Nat.cast)
(forall_mem_range.2 fun m =>
le_sub_iff_add_le.2 <| le_csSup _ _ ⟨x, forall_mem_range.2 h⟩ ⟨m+1, Nat.cast_succ m⟩)
linarith)
#align conditionally_complete_linear_ordered_field.to_archimedean ConditionallyCompleteLinearOrderedField.to_archimedean
/-- The reals are a conditionally complete linearly ordered field. -/
instance : ConditionallyCompleteLinearOrderedField ℝ :=
{ (inferInstance : LinearOrderedField ℝ),
(inferInstance : ConditionallyCompleteLinearOrder ℝ) with }
namespace LinearOrderedField
/-!
### Rational cut map
The idea is that a conditionally complete linear ordered field is fully characterized by its copy of
the rationals. Hence we define `LinearOrderedField.cutMap β : α → Set β` which sends `a : α` to the
"rationals in `β`" that are less than `a`.
-/
section CutMap
variable [LinearOrderedField α]
section DivisionRing
variable (β) [DivisionRing β] {a a₁ a₂ : α} {b : β} {q : ℚ}
/-- The lower cut of rationals inside a linear ordered field that are less than a given element of
another linear ordered field. -/
def cutMap (a : α) : Set β :=
(Rat.cast : ℚ → β) '' {t | ↑t < a}
#align linear_ordered_field.cut_map LinearOrderedField.cutMap
theorem cutMap_mono (h : a₁ ≤ a₂) : cutMap β a₁ ⊆ cutMap β a₂ := image_subset _ fun _ => h.trans_lt'
#align linear_ordered_field.cut_map_mono LinearOrderedField.cutMap_mono
variable {β}
@[simp]
theorem mem_cutMap_iff : b ∈ cutMap β a ↔ ∃ q : ℚ, (q : α) < a ∧ (q : β) = b := Iff.rfl
#align linear_ordered_field.mem_cut_map_iff LinearOrderedField.mem_cutMap_iff
-- @[simp] -- Porting note: not in simpNF
theorem coe_mem_cutMap_iff [CharZero β] : (q : β) ∈ cutMap β a ↔ (q : α) < a :=
Rat.cast_injective.mem_set_image
#align linear_ordered_field.coe_mem_cut_map_iff LinearOrderedField.coe_mem_cutMap_iff
theorem cutMap_self (a : α) : cutMap α a = Iio a ∩ range (Rat.cast : ℚ → α) := by
ext
constructor
· rintro ⟨q, h, rfl⟩
exact ⟨h, q, rfl⟩
· rintro ⟨h, q, rfl⟩
exact ⟨q, h, rfl⟩
#align linear_ordered_field.cut_map_self LinearOrderedField.cutMap_self
end DivisionRing
variable (β) [LinearOrderedField β] {a a₁ a₂ : α} {b : β} {q : ℚ}
| Mathlib/Algebra/Order/CompleteField.lean | 134 | 135 | theorem cutMap_coe (q : ℚ) : cutMap β (q : α) = Rat.cast '' {r : ℚ | (r : β) < q} := by |
simp_rw [cutMap, Rat.cast_lt]
|
/-
Copyright (c) 2022 Violeta Hernández Palacios. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.FixedPoint
#align_import set_theory.ordinal.principal from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
### Principal ordinals
We define principal or indecomposable ordinals, and we prove the standard properties about them.
### Main definitions and results
* `Principal`: A principal or indecomposable ordinal under some binary operation. We include 0 and
any other typically excluded edge cases for simplicity.
* `unbounded_principal`: Principal ordinals are unbounded.
* `principal_add_iff_zero_or_omega_opow`: The main characterization theorem for additive principal
ordinals.
* `principal_mul_iff_le_two_or_omega_opow_opow`: The main characterization theorem for
multiplicative principal ordinals.
### Todo
* Prove that exponential principal ordinals are 0, 1, 2, ω, or epsilon numbers, i.e. fixed points
of `fun x ↦ ω ^ x`.
-/
universe u v w
noncomputable section
open Order
namespace Ordinal
-- Porting note: commented out, doesn't seem necessary
--local infixr:0 "^" => @pow Ordinal Ordinal Ordinal.hasPow
/-! ### Principal ordinals -/
/-- An ordinal `o` is said to be principal or indecomposable under an operation when the set of
ordinals less than it is closed under that operation. In standard mathematical usage, this term is
almost exclusively used for additive and multiplicative principal ordinals.
For simplicity, we break usual convention and regard 0 as principal. -/
def Principal (op : Ordinal → Ordinal → Ordinal) (o : Ordinal) : Prop :=
∀ ⦃a b⦄, a < o → b < o → op a b < o
#align ordinal.principal Ordinal.Principal
| Mathlib/SetTheory/Ordinal/Principal.lean | 52 | 54 | theorem principal_iff_principal_swap {op : Ordinal → Ordinal → Ordinal} {o : Ordinal} :
Principal op o ↔ Principal (Function.swap op) o := by |
constructor <;> exact fun h a b ha hb => h hb ha
|
/-
Copyright (c) 2020 Fox Thomson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Fox Thomson
-/
import Mathlib.SetTheory.Game.Basic
import Mathlib.Tactic.NthRewrite
#align_import set_theory.game.impartial from "leanprover-community/mathlib"@"2e0975f6a25dd3fbfb9e41556a77f075f6269748"
/-!
# Basic definitions about impartial (pre-)games
We will define an impartial game, one in which left and right can make exactly the same moves.
Our definition differs slightly by saying that the game is always equivalent to its negative,
no matter what moves are played. This allows for games such as poker-nim to be classified as
impartial.
-/
universe u
namespace SetTheory
open scoped PGame
namespace PGame
/-- The definition for an impartial game, defined using Conway induction. -/
def ImpartialAux : PGame → Prop
| G => (G ≈ -G) ∧ (∀ i, ImpartialAux (G.moveLeft i)) ∧ ∀ j, ImpartialAux (G.moveRight j)
termination_by G => G -- Porting note: Added `termination_by`
#align pgame.impartial_aux SetTheory.PGame.ImpartialAux
theorem impartialAux_def {G : PGame} :
G.ImpartialAux ↔
(G ≈ -G) ∧ (∀ i, ImpartialAux (G.moveLeft i)) ∧ ∀ j, ImpartialAux (G.moveRight j) := by
rw [ImpartialAux]
#align pgame.impartial_aux_def SetTheory.PGame.impartialAux_def
/-- A typeclass on impartial games. -/
class Impartial (G : PGame) : Prop where
out : ImpartialAux G
#align pgame.impartial SetTheory.PGame.Impartial
theorem impartial_iff_aux {G : PGame} : G.Impartial ↔ G.ImpartialAux :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align pgame.impartial_iff_aux SetTheory.PGame.impartial_iff_aux
theorem impartial_def {G : PGame} :
G.Impartial ↔ (G ≈ -G) ∧ (∀ i, Impartial (G.moveLeft i)) ∧ ∀ j, Impartial (G.moveRight j) := by
simpa only [impartial_iff_aux] using impartialAux_def
#align pgame.impartial_def SetTheory.PGame.impartial_def
namespace Impartial
instance impartial_zero : Impartial 0 := by rw [impartial_def]; dsimp; simp
#align pgame.impartial.impartial_zero SetTheory.PGame.Impartial.impartial_zero
instance impartial_star : Impartial star := by
rw [impartial_def]; simpa using Impartial.impartial_zero
#align pgame.impartial.impartial_star SetTheory.PGame.Impartial.impartial_star
theorem neg_equiv_self (G : PGame) [h : G.Impartial] : G ≈ -G :=
(impartial_def.1 h).1
#align pgame.impartial.neg_equiv_self SetTheory.PGame.Impartial.neg_equiv_self
-- Porting note: Changed `-⟦G⟧` to `-(⟦G⟧ : Quotient setoid)`
@[simp]
theorem mk'_neg_equiv_self (G : PGame) [G.Impartial] : -(⟦G⟧ : Quotient setoid) = ⟦G⟧ :=
Quot.sound (Equiv.symm (neg_equiv_self G))
#align pgame.impartial.mk_neg_equiv_self SetTheory.PGame.Impartial.mk'_neg_equiv_self
instance moveLeft_impartial {G : PGame} [h : G.Impartial] (i : G.LeftMoves) :
(G.moveLeft i).Impartial :=
(impartial_def.1 h).2.1 i
#align pgame.impartial.move_left_impartial SetTheory.PGame.Impartial.moveLeft_impartial
instance moveRight_impartial {G : PGame} [h : G.Impartial] (j : G.RightMoves) :
(G.moveRight j).Impartial :=
(impartial_def.1 h).2.2 j
#align pgame.impartial.move_right_impartial SetTheory.PGame.Impartial.moveRight_impartial
theorem impartial_congr : ∀ {G H : PGame} (_ : G ≡r H) [G.Impartial], H.Impartial
| G, H => fun e => by
intro h
exact impartial_def.2
⟨Equiv.trans e.symm.equiv (Equiv.trans (neg_equiv_self G) (neg_equiv_neg_iff.2 e.equiv)),
fun i => impartial_congr (e.moveLeftSymm i), fun j => impartial_congr (e.moveRightSymm j)⟩
termination_by G H => (G, H)
#align pgame.impartial.impartial_congr SetTheory.PGame.Impartial.impartial_congr
instance impartial_add : ∀ (G H : PGame) [G.Impartial] [H.Impartial], (G + H).Impartial
| G, H, _, _ => by
rw [impartial_def]
refine ⟨Equiv.trans (add_congr (neg_equiv_self G) (neg_equiv_self _))
(Equiv.symm (negAddRelabelling _ _).equiv), fun k => ?_, fun k => ?_⟩
· apply leftMoves_add_cases k
all_goals
intro i; simp only [add_moveLeft_inl, add_moveLeft_inr]
apply impartial_add
· apply rightMoves_add_cases k
all_goals
intro i; simp only [add_moveRight_inl, add_moveRight_inr]
apply impartial_add
termination_by G H => (G, H)
#align pgame.impartial.impartial_add SetTheory.PGame.Impartial.impartial_add
instance impartial_neg : ∀ (G : PGame) [G.Impartial], (-G).Impartial
| G, _ => by
rw [impartial_def]
refine ⟨?_, fun i => ?_, fun i => ?_⟩
· rw [neg_neg]
exact Equiv.symm (neg_equiv_self G)
· rw [moveLeft_neg']
apply impartial_neg
· rw [moveRight_neg']
apply impartial_neg
termination_by G => G
#align pgame.impartial.impartial_neg SetTheory.PGame.Impartial.impartial_neg
variable (G : PGame) [Impartial G]
theorem nonpos : ¬0 < G := fun h => by
have h' := neg_lt_neg_iff.2 h
rw [neg_zero, lt_congr_left (Equiv.symm (neg_equiv_self G))] at h'
exact (h.trans h').false
#align pgame.impartial.nonpos SetTheory.PGame.Impartial.nonpos
theorem nonneg : ¬G < 0 := fun h => by
have h' := neg_lt_neg_iff.2 h
rw [neg_zero, lt_congr_right (Equiv.symm (neg_equiv_self G))] at h'
exact (h.trans h').false
#align pgame.impartial.nonneg SetTheory.PGame.Impartial.nonneg
/-- In an impartial game, either the first player always wins, or the second player always wins. -/
theorem equiv_or_fuzzy_zero : (G ≈ 0) ∨ G ‖ 0 := by
rcases lt_or_equiv_or_gt_or_fuzzy G 0 with (h | h | h | h)
· exact ((nonneg G) h).elim
· exact Or.inl h
· exact ((nonpos G) h).elim
· exact Or.inr h
#align pgame.impartial.equiv_or_fuzzy_zero SetTheory.PGame.Impartial.equiv_or_fuzzy_zero
@[simp]
theorem not_equiv_zero_iff : ¬(G ≈ 0) ↔ G ‖ 0 :=
⟨(equiv_or_fuzzy_zero G).resolve_left, Fuzzy.not_equiv⟩
#align pgame.impartial.not_equiv_zero_iff SetTheory.PGame.Impartial.not_equiv_zero_iff
@[simp]
theorem not_fuzzy_zero_iff : ¬G ‖ 0 ↔ (G ≈ 0) :=
⟨(equiv_or_fuzzy_zero G).resolve_right, Equiv.not_fuzzy⟩
#align pgame.impartial.not_fuzzy_zero_iff SetTheory.PGame.Impartial.not_fuzzy_zero_iff
theorem add_self : G + G ≈ 0 :=
Equiv.trans (add_congr_left (neg_equiv_self G)) (add_left_neg_equiv G)
#align pgame.impartial.add_self SetTheory.PGame.Impartial.add_self
-- Porting note: Changed `⟦G⟧` to `(⟦G⟧ : Quotient setoid)`
@[simp]
theorem mk'_add_self : (⟦G⟧ : Quotient setoid) + ⟦G⟧ = 0 :=
Quot.sound (add_self G)
#align pgame.impartial.mk_add_self SetTheory.PGame.Impartial.mk'_add_self
/-- This lemma doesn't require `H` to be impartial. -/
theorem equiv_iff_add_equiv_zero (H : PGame) : (H ≈ G) ↔ (H + G ≈ 0) := by
rw [Game.PGame.equiv_iff_game_eq, ← @add_right_cancel_iff _ _ _ ⟦G⟧, mk'_add_self, ← quot_add,
Game.PGame.equiv_iff_game_eq]
rfl
#align pgame.impartial.equiv_iff_add_equiv_zero SetTheory.PGame.Impartial.equiv_iff_add_equiv_zero
/-- This lemma doesn't require `H` to be impartial. -/
theorem equiv_iff_add_equiv_zero' (H : PGame) : (G ≈ H) ↔ (G + H ≈ 0) := by
rw [Game.PGame.equiv_iff_game_eq, ← @add_left_cancel_iff _ _ _ ⟦G⟧, mk'_add_self, ← quot_add,
Game.PGame.equiv_iff_game_eq]
exact ⟨Eq.symm, Eq.symm⟩
#align pgame.impartial.equiv_iff_add_equiv_zero' SetTheory.PGame.Impartial.equiv_iff_add_equiv_zero'
theorem le_zero_iff {G : PGame} [G.Impartial] : G ≤ 0 ↔ 0 ≤ G := by
rw [← zero_le_neg_iff, le_congr_right (neg_equiv_self G)]
#align pgame.impartial.le_zero_iff SetTheory.PGame.Impartial.le_zero_iff
theorem lf_zero_iff {G : PGame} [G.Impartial] : G ⧏ 0 ↔ 0 ⧏ G := by
rw [← zero_lf_neg_iff, lf_congr_right (neg_equiv_self G)]
#align pgame.impartial.lf_zero_iff SetTheory.PGame.Impartial.lf_zero_iff
theorem equiv_zero_iff_le : (G ≈ 0) ↔ G ≤ 0 :=
⟨And.left, fun h => ⟨h, le_zero_iff.1 h⟩⟩
#align pgame.impartial.equiv_zero_iff_le SetTheory.PGame.Impartial.equiv_zero_iff_le
theorem fuzzy_zero_iff_lf : G ‖ 0 ↔ G ⧏ 0 :=
⟨And.left, fun h => ⟨h, lf_zero_iff.1 h⟩⟩
#align pgame.impartial.fuzzy_zero_iff_lf SetTheory.PGame.Impartial.fuzzy_zero_iff_lf
theorem equiv_zero_iff_ge : (G ≈ 0) ↔ 0 ≤ G :=
⟨And.right, fun h => ⟨le_zero_iff.2 h, h⟩⟩
#align pgame.impartial.equiv_zero_iff_ge SetTheory.PGame.Impartial.equiv_zero_iff_ge
theorem fuzzy_zero_iff_gf : G ‖ 0 ↔ 0 ⧏ G :=
⟨And.right, fun h => ⟨lf_zero_iff.2 h, h⟩⟩
#align pgame.impartial.fuzzy_zero_iff_gf SetTheory.PGame.Impartial.fuzzy_zero_iff_gf
theorem forall_leftMoves_fuzzy_iff_equiv_zero : (∀ i, G.moveLeft i ‖ 0) ↔ (G ≈ 0) := by
refine ⟨fun hb => ?_, fun hp i => ?_⟩
· rw [equiv_zero_iff_le G, le_zero_lf]
exact fun i => (hb i).1
· rw [fuzzy_zero_iff_lf]
exact hp.1.moveLeft_lf i
#align pgame.impartial.forall_left_moves_fuzzy_iff_equiv_zero SetTheory.PGame.Impartial.forall_leftMoves_fuzzy_iff_equiv_zero
theorem forall_rightMoves_fuzzy_iff_equiv_zero : (∀ j, G.moveRight j ‖ 0) ↔ (G ≈ 0) := by
refine ⟨fun hb => ?_, fun hp i => ?_⟩
· rw [equiv_zero_iff_ge G, zero_le_lf]
exact fun i => (hb i).2
· rw [fuzzy_zero_iff_gf]
exact hp.2.lf_moveRight i
#align pgame.impartial.forall_right_moves_fuzzy_iff_equiv_zero SetTheory.PGame.Impartial.forall_rightMoves_fuzzy_iff_equiv_zero
theorem exists_left_move_equiv_iff_fuzzy_zero : (∃ i, G.moveLeft i ≈ 0) ↔ G ‖ 0 := by
refine ⟨fun ⟨i, hi⟩ => (fuzzy_zero_iff_gf G).2 (lf_of_le_moveLeft hi.2), fun hn => ?_⟩
rw [fuzzy_zero_iff_gf G, zero_lf_le] at hn
cases' hn with i hi
exact ⟨i, (equiv_zero_iff_ge _).2 hi⟩
#align pgame.impartial.exists_left_move_equiv_iff_fuzzy_zero SetTheory.PGame.Impartial.exists_left_move_equiv_iff_fuzzy_zero
| Mathlib/SetTheory/Game/Impartial.lean | 226 | 230 | theorem exists_right_move_equiv_iff_fuzzy_zero : (∃ j, G.moveRight j ≈ 0) ↔ G ‖ 0 := by |
refine ⟨fun ⟨i, hi⟩ => (fuzzy_zero_iff_lf G).2 (lf_of_moveRight_le hi.1), fun hn => ?_⟩
rw [fuzzy_zero_iff_lf G, lf_zero_le] at hn
cases' hn with i hi
exact ⟨i, (equiv_zero_iff_le _).2 hi⟩
|
/-
Copyright (c) 2018 Ellen Arlt. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Ellen Arlt, Blair Shi, Sean Leather, Mario Carneiro, Johan Commelin, Lu-Ming Zhang
-/
import Mathlib.Algebra.Algebra.Opposite
import Mathlib.Algebra.Algebra.Pi
import Mathlib.Algebra.BigOperators.Pi
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Algebra.BigOperators.RingEquiv
import Mathlib.Algebra.Module.LinearMap.Basic
import Mathlib.Algebra.Module.Pi
import Mathlib.Algebra.Star.BigOperators
import Mathlib.Algebra.Star.Module
import Mathlib.Algebra.Star.Pi
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.GroupAction.BigOperators
#align_import data.matrix.basic from "leanprover-community/mathlib"@"eba5bb3155cab51d80af00e8d7d69fa271b1302b"
/-!
# Matrices
This file defines basic properties of matrices.
Matrices with rows indexed by `m`, columns indexed by `n`, and entries of type `α` are represented
with `Matrix m n α`. For the typical approach of counting rows and columns,
`Matrix (Fin m) (Fin n) α` can be used.
## Notation
The locale `Matrix` gives the following notation:
* `⬝ᵥ` for `Matrix.dotProduct`
* `*ᵥ` for `Matrix.mulVec`
* `ᵥ*` for `Matrix.vecMul`
* `ᵀ` for `Matrix.transpose`
* `ᴴ` for `Matrix.conjTranspose`
## Implementation notes
For convenience, `Matrix m n α` is defined as `m → n → α`, as this allows elements of the matrix
to be accessed with `A i j`. However, it is not advisable to _construct_ matrices using terms of the
form `fun i j ↦ _` or even `(fun i j ↦ _ : Matrix m n α)`, as these are not recognized by Lean
as having the right type. Instead, `Matrix.of` should be used.
## TODO
Under various conditions, multiplication of infinite matrices makes sense.
These have not yet been implemented.
-/
universe u u' v w
/-- `Matrix m n R` is the type of matrices with entries in `R`, whose rows are indexed by `m`
and whose columns are indexed by `n`. -/
def Matrix (m : Type u) (n : Type u') (α : Type v) : Type max u u' v :=
m → n → α
#align matrix Matrix
variable {l m n o : Type*} {m' : o → Type*} {n' : o → Type*}
variable {R : Type*} {S : Type*} {α : Type v} {β : Type w} {γ : Type*}
namespace Matrix
section Ext
variable {M N : Matrix m n α}
theorem ext_iff : (∀ i j, M i j = N i j) ↔ M = N :=
⟨fun h => funext fun i => funext <| h i, fun h => by simp [h]⟩
#align matrix.ext_iff Matrix.ext_iff
@[ext]
theorem ext : (∀ i j, M i j = N i j) → M = N :=
ext_iff.mp
#align matrix.ext Matrix.ext
end Ext
/-- Cast a function into a matrix.
The two sides of the equivalence are definitionally equal types. We want to use an explicit cast
to distinguish the types because `Matrix` has different instances to pi types (such as `Pi.mul`,
which performs elementwise multiplication, vs `Matrix.mul`).
If you are defining a matrix, in terms of its entries, use `of (fun i j ↦ _)`. The
purpose of this approach is to ensure that terms of the form `(fun i j ↦ _) * (fun i j ↦ _)` do not
appear, as the type of `*` can be misleading.
Porting note: In Lean 3, it is also safe to use pattern matching in a definition as `| i j := _`,
which can only be unfolded when fully-applied. leanprover/lean4#2042 means this does not
(currently) work in Lean 4.
-/
def of : (m → n → α) ≃ Matrix m n α :=
Equiv.refl _
#align matrix.of Matrix.of
@[simp]
theorem of_apply (f : m → n → α) (i j) : of f i j = f i j :=
rfl
#align matrix.of_apply Matrix.of_apply
@[simp]
theorem of_symm_apply (f : Matrix m n α) (i j) : of.symm f i j = f i j :=
rfl
#align matrix.of_symm_apply Matrix.of_symm_apply
/-- `M.map f` is the matrix obtained by applying `f` to each entry of the matrix `M`.
This is available in bundled forms as:
* `AddMonoidHom.mapMatrix`
* `LinearMap.mapMatrix`
* `RingHom.mapMatrix`
* `AlgHom.mapMatrix`
* `Equiv.mapMatrix`
* `AddEquiv.mapMatrix`
* `LinearEquiv.mapMatrix`
* `RingEquiv.mapMatrix`
* `AlgEquiv.mapMatrix`
-/
def map (M : Matrix m n α) (f : α → β) : Matrix m n β :=
of fun i j => f (M i j)
#align matrix.map Matrix.map
@[simp]
theorem map_apply {M : Matrix m n α} {f : α → β} {i : m} {j : n} : M.map f i j = f (M i j) :=
rfl
#align matrix.map_apply Matrix.map_apply
@[simp]
theorem map_id (M : Matrix m n α) : M.map id = M := by
ext
rfl
#align matrix.map_id Matrix.map_id
@[simp]
theorem map_id' (M : Matrix m n α) : M.map (·) = M := map_id M
@[simp]
theorem map_map {M : Matrix m n α} {β γ : Type*} {f : α → β} {g : β → γ} :
(M.map f).map g = M.map (g ∘ f) := by
ext
rfl
#align matrix.map_map Matrix.map_map
theorem map_injective {f : α → β} (hf : Function.Injective f) :
Function.Injective fun M : Matrix m n α => M.map f := fun _ _ h =>
ext fun i j => hf <| ext_iff.mpr h i j
#align matrix.map_injective Matrix.map_injective
/-- The transpose of a matrix. -/
def transpose (M : Matrix m n α) : Matrix n m α :=
of fun x y => M y x
#align matrix.transpose Matrix.transpose
-- TODO: set as an equation lemma for `transpose`, see mathlib4#3024
@[simp]
theorem transpose_apply (M : Matrix m n α) (i j) : transpose M i j = M j i :=
rfl
#align matrix.transpose_apply Matrix.transpose_apply
@[inherit_doc]
scoped postfix:1024 "ᵀ" => Matrix.transpose
/-- The conjugate transpose of a matrix defined in term of `star`. -/
def conjTranspose [Star α] (M : Matrix m n α) : Matrix n m α :=
M.transpose.map star
#align matrix.conj_transpose Matrix.conjTranspose
@[inherit_doc]
scoped postfix:1024 "ᴴ" => Matrix.conjTranspose
instance inhabited [Inhabited α] : Inhabited (Matrix m n α) :=
inferInstanceAs <| Inhabited <| m → n → α
-- Porting note: new, Lean3 found this automatically
instance decidableEq [DecidableEq α] [Fintype m] [Fintype n] : DecidableEq (Matrix m n α) :=
Fintype.decidablePiFintype
instance {n m} [Fintype m] [DecidableEq m] [Fintype n] [DecidableEq n] (α) [Fintype α] :
Fintype (Matrix m n α) := inferInstanceAs (Fintype (m → n → α))
instance {n m} [Finite m] [Finite n] (α) [Finite α] :
Finite (Matrix m n α) := inferInstanceAs (Finite (m → n → α))
instance add [Add α] : Add (Matrix m n α) :=
Pi.instAdd
instance addSemigroup [AddSemigroup α] : AddSemigroup (Matrix m n α) :=
Pi.addSemigroup
instance addCommSemigroup [AddCommSemigroup α] : AddCommSemigroup (Matrix m n α) :=
Pi.addCommSemigroup
instance zero [Zero α] : Zero (Matrix m n α) :=
Pi.instZero
instance addZeroClass [AddZeroClass α] : AddZeroClass (Matrix m n α) :=
Pi.addZeroClass
instance addMonoid [AddMonoid α] : AddMonoid (Matrix m n α) :=
Pi.addMonoid
instance addCommMonoid [AddCommMonoid α] : AddCommMonoid (Matrix m n α) :=
Pi.addCommMonoid
instance neg [Neg α] : Neg (Matrix m n α) :=
Pi.instNeg
instance sub [Sub α] : Sub (Matrix m n α) :=
Pi.instSub
instance addGroup [AddGroup α] : AddGroup (Matrix m n α) :=
Pi.addGroup
instance addCommGroup [AddCommGroup α] : AddCommGroup (Matrix m n α) :=
Pi.addCommGroup
instance unique [Unique α] : Unique (Matrix m n α) :=
Pi.unique
instance subsingleton [Subsingleton α] : Subsingleton (Matrix m n α) :=
inferInstanceAs <| Subsingleton <| m → n → α
instance nonempty [Nonempty m] [Nonempty n] [Nontrivial α] : Nontrivial (Matrix m n α) :=
Function.nontrivial
instance smul [SMul R α] : SMul R (Matrix m n α) :=
Pi.instSMul
instance smulCommClass [SMul R α] [SMul S α] [SMulCommClass R S α] :
SMulCommClass R S (Matrix m n α) :=
Pi.smulCommClass
instance isScalarTower [SMul R S] [SMul R α] [SMul S α] [IsScalarTower R S α] :
IsScalarTower R S (Matrix m n α) :=
Pi.isScalarTower
instance isCentralScalar [SMul R α] [SMul Rᵐᵒᵖ α] [IsCentralScalar R α] :
IsCentralScalar R (Matrix m n α) :=
Pi.isCentralScalar
instance mulAction [Monoid R] [MulAction R α] : MulAction R (Matrix m n α) :=
Pi.mulAction _
instance distribMulAction [Monoid R] [AddMonoid α] [DistribMulAction R α] :
DistribMulAction R (Matrix m n α) :=
Pi.distribMulAction _
instance module [Semiring R] [AddCommMonoid α] [Module R α] : Module R (Matrix m n α) :=
Pi.module _ _ _
-- Porting note (#10756): added the following section with simp lemmas because `simp` fails
-- to apply the corresponding lemmas in the namespace `Pi`.
-- (e.g. `Pi.zero_apply` used on `OfNat.ofNat 0 i j`)
section
@[simp]
theorem zero_apply [Zero α] (i : m) (j : n) : (0 : Matrix m n α) i j = 0 := rfl
@[simp]
theorem add_apply [Add α] (A B : Matrix m n α) (i : m) (j : n) :
(A + B) i j = (A i j) + (B i j) := rfl
@[simp]
theorem smul_apply [SMul β α] (r : β) (A : Matrix m n α) (i : m) (j : n) :
(r • A) i j = r • (A i j) := rfl
@[simp]
theorem sub_apply [Sub α] (A B : Matrix m n α) (i : m) (j : n) :
(A - B) i j = (A i j) - (B i j) := rfl
@[simp]
theorem neg_apply [Neg α] (A : Matrix m n α) (i : m) (j : n) :
(-A) i j = -(A i j) := rfl
end
/-! simp-normal form pulls `of` to the outside. -/
@[simp]
theorem of_zero [Zero α] : of (0 : m → n → α) = 0 :=
rfl
#align matrix.of_zero Matrix.of_zero
@[simp]
theorem of_add_of [Add α] (f g : m → n → α) : of f + of g = of (f + g) :=
rfl
#align matrix.of_add_of Matrix.of_add_of
@[simp]
theorem of_sub_of [Sub α] (f g : m → n → α) : of f - of g = of (f - g) :=
rfl
#align matrix.of_sub_of Matrix.of_sub_of
@[simp]
theorem neg_of [Neg α] (f : m → n → α) : -of f = of (-f) :=
rfl
#align matrix.neg_of Matrix.neg_of
@[simp]
theorem smul_of [SMul R α] (r : R) (f : m → n → α) : r • of f = of (r • f) :=
rfl
#align matrix.smul_of Matrix.smul_of
@[simp]
protected theorem map_zero [Zero α] [Zero β] (f : α → β) (h : f 0 = 0) :
(0 : Matrix m n α).map f = 0 := by
ext
simp [h]
#align matrix.map_zero Matrix.map_zero
protected theorem map_add [Add α] [Add β] (f : α → β) (hf : ∀ a₁ a₂, f (a₁ + a₂) = f a₁ + f a₂)
(M N : Matrix m n α) : (M + N).map f = M.map f + N.map f :=
ext fun _ _ => hf _ _
#align matrix.map_add Matrix.map_add
protected theorem map_sub [Sub α] [Sub β] (f : α → β) (hf : ∀ a₁ a₂, f (a₁ - a₂) = f a₁ - f a₂)
(M N : Matrix m n α) : (M - N).map f = M.map f - N.map f :=
ext fun _ _ => hf _ _
#align matrix.map_sub Matrix.map_sub
theorem map_smul [SMul R α] [SMul R β] (f : α → β) (r : R) (hf : ∀ a, f (r • a) = r • f a)
(M : Matrix m n α) : (r • M).map f = r • M.map f :=
ext fun _ _ => hf _
#align matrix.map_smul Matrix.map_smul
/-- The scalar action via `Mul.toSMul` is transformed by the same map as the elements
of the matrix, when `f` preserves multiplication. -/
theorem map_smul' [Mul α] [Mul β] (f : α → β) (r : α) (A : Matrix n n α)
(hf : ∀ a₁ a₂, f (a₁ * a₂) = f a₁ * f a₂) : (r • A).map f = f r • A.map f :=
ext fun _ _ => hf _ _
#align matrix.map_smul' Matrix.map_smul'
/-- The scalar action via `mul.toOppositeSMul` is transformed by the same map as the
elements of the matrix, when `f` preserves multiplication. -/
theorem map_op_smul' [Mul α] [Mul β] (f : α → β) (r : α) (A : Matrix n n α)
(hf : ∀ a₁ a₂, f (a₁ * a₂) = f a₁ * f a₂) :
(MulOpposite.op r • A).map f = MulOpposite.op (f r) • A.map f :=
ext fun _ _ => hf _ _
#align matrix.map_op_smul' Matrix.map_op_smul'
theorem _root_.IsSMulRegular.matrix [SMul R S] {k : R} (hk : IsSMulRegular S k) :
IsSMulRegular (Matrix m n S) k :=
IsSMulRegular.pi fun _ => IsSMulRegular.pi fun _ => hk
#align is_smul_regular.matrix IsSMulRegular.matrix
theorem _root_.IsLeftRegular.matrix [Mul α] {k : α} (hk : IsLeftRegular k) :
IsSMulRegular (Matrix m n α) k :=
hk.isSMulRegular.matrix
#align is_left_regular.matrix IsLeftRegular.matrix
instance subsingleton_of_empty_left [IsEmpty m] : Subsingleton (Matrix m n α) :=
⟨fun M N => by
ext i
exact isEmptyElim i⟩
#align matrix.subsingleton_of_empty_left Matrix.subsingleton_of_empty_left
instance subsingleton_of_empty_right [IsEmpty n] : Subsingleton (Matrix m n α) :=
⟨fun M N => by
ext i j
exact isEmptyElim j⟩
#align matrix.subsingleton_of_empty_right Matrix.subsingleton_of_empty_right
end Matrix
open Matrix
namespace Matrix
section Diagonal
variable [DecidableEq n]
/-- `diagonal d` is the square matrix such that `(diagonal d) i i = d i` and `(diagonal d) i j = 0`
if `i ≠ j`.
Note that bundled versions exist as:
* `Matrix.diagonalAddMonoidHom`
* `Matrix.diagonalLinearMap`
* `Matrix.diagonalRingHom`
* `Matrix.diagonalAlgHom`
-/
def diagonal [Zero α] (d : n → α) : Matrix n n α :=
of fun i j => if i = j then d i else 0
#align matrix.diagonal Matrix.diagonal
-- TODO: set as an equation lemma for `diagonal`, see mathlib4#3024
theorem diagonal_apply [Zero α] (d : n → α) (i j) : diagonal d i j = if i = j then d i else 0 :=
rfl
#align matrix.diagonal_apply Matrix.diagonal_apply
@[simp]
theorem diagonal_apply_eq [Zero α] (d : n → α) (i : n) : (diagonal d) i i = d i := by
simp [diagonal]
#align matrix.diagonal_apply_eq Matrix.diagonal_apply_eq
@[simp]
theorem diagonal_apply_ne [Zero α] (d : n → α) {i j : n} (h : i ≠ j) : (diagonal d) i j = 0 := by
simp [diagonal, h]
#align matrix.diagonal_apply_ne Matrix.diagonal_apply_ne
theorem diagonal_apply_ne' [Zero α] (d : n → α) {i j : n} (h : j ≠ i) : (diagonal d) i j = 0 :=
diagonal_apply_ne d h.symm
#align matrix.diagonal_apply_ne' Matrix.diagonal_apply_ne'
@[simp]
theorem diagonal_eq_diagonal_iff [Zero α] {d₁ d₂ : n → α} :
diagonal d₁ = diagonal d₂ ↔ ∀ i, d₁ i = d₂ i :=
⟨fun h i => by simpa using congr_arg (fun m : Matrix n n α => m i i) h, fun h => by
rw [show d₁ = d₂ from funext h]⟩
#align matrix.diagonal_eq_diagonal_iff Matrix.diagonal_eq_diagonal_iff
theorem diagonal_injective [Zero α] : Function.Injective (diagonal : (n → α) → Matrix n n α) :=
fun d₁ d₂ h => funext fun i => by simpa using Matrix.ext_iff.mpr h i i
#align matrix.diagonal_injective Matrix.diagonal_injective
@[simp]
theorem diagonal_zero [Zero α] : (diagonal fun _ => 0 : Matrix n n α) = 0 := by
ext
simp [diagonal]
#align matrix.diagonal_zero Matrix.diagonal_zero
@[simp]
theorem diagonal_transpose [Zero α] (v : n → α) : (diagonal v)ᵀ = diagonal v := by
ext i j
by_cases h : i = j
· simp [h, transpose]
· simp [h, transpose, diagonal_apply_ne' _ h]
#align matrix.diagonal_transpose Matrix.diagonal_transpose
@[simp]
theorem diagonal_add [AddZeroClass α] (d₁ d₂ : n → α) :
diagonal d₁ + diagonal d₂ = diagonal fun i => d₁ i + d₂ i := by
ext i j
by_cases h : i = j <;>
simp [h]
#align matrix.diagonal_add Matrix.diagonal_add
@[simp]
theorem diagonal_smul [Zero α] [SMulZeroClass R α] (r : R) (d : n → α) :
diagonal (r • d) = r • diagonal d := by
ext i j
by_cases h : i = j <;> simp [h]
#align matrix.diagonal_smul Matrix.diagonal_smul
@[simp]
theorem diagonal_neg [NegZeroClass α] (d : n → α) :
-diagonal d = diagonal fun i => -d i := by
ext i j
by_cases h : i = j <;>
simp [h]
#align matrix.diagonal_neg Matrix.diagonal_neg
@[simp]
theorem diagonal_sub [SubNegZeroMonoid α] (d₁ d₂ : n → α) :
diagonal d₁ - diagonal d₂ = diagonal fun i => d₁ i - d₂ i := by
ext i j
by_cases h : i = j <;>
simp [h]
instance [Zero α] [NatCast α] : NatCast (Matrix n n α) where
natCast m := diagonal fun _ => m
@[norm_cast]
theorem diagonal_natCast [Zero α] [NatCast α] (m : ℕ) : diagonal (fun _ : n => (m : α)) = m := rfl
@[norm_cast]
theorem diagonal_natCast' [Zero α] [NatCast α] (m : ℕ) : diagonal ((m : n → α)) = m := rfl
-- See note [no_index around OfNat.ofNat]
theorem diagonal_ofNat [Zero α] [NatCast α] (m : ℕ) [m.AtLeastTwo] :
diagonal (fun _ : n => no_index (OfNat.ofNat m : α)) = OfNat.ofNat m := rfl
-- See note [no_index around OfNat.ofNat]
theorem diagonal_ofNat' [Zero α] [NatCast α] (m : ℕ) [m.AtLeastTwo] :
diagonal (no_index (OfNat.ofNat m : n → α)) = OfNat.ofNat m := rfl
instance [Zero α] [IntCast α] : IntCast (Matrix n n α) where
intCast m := diagonal fun _ => m
@[norm_cast]
theorem diagonal_intCast [Zero α] [IntCast α] (m : ℤ) : diagonal (fun _ : n => (m : α)) = m := rfl
@[norm_cast]
theorem diagonal_intCast' [Zero α] [IntCast α] (m : ℤ) : diagonal ((m : n → α)) = m := rfl
variable (n α)
/-- `Matrix.diagonal` as an `AddMonoidHom`. -/
@[simps]
def diagonalAddMonoidHom [AddZeroClass α] : (n → α) →+ Matrix n n α where
toFun := diagonal
map_zero' := diagonal_zero
map_add' x y := (diagonal_add x y).symm
#align matrix.diagonal_add_monoid_hom Matrix.diagonalAddMonoidHom
variable (R)
/-- `Matrix.diagonal` as a `LinearMap`. -/
@[simps]
def diagonalLinearMap [Semiring R] [AddCommMonoid α] [Module R α] : (n → α) →ₗ[R] Matrix n n α :=
{ diagonalAddMonoidHom n α with map_smul' := diagonal_smul }
#align matrix.diagonal_linear_map Matrix.diagonalLinearMap
variable {n α R}
@[simp]
theorem diagonal_map [Zero α] [Zero β] {f : α → β} (h : f 0 = 0) {d : n → α} :
(diagonal d).map f = diagonal fun m => f (d m) := by
ext
simp only [diagonal_apply, map_apply]
split_ifs <;> simp [h]
#align matrix.diagonal_map Matrix.diagonal_map
@[simp]
theorem diagonal_conjTranspose [AddMonoid α] [StarAddMonoid α] (v : n → α) :
(diagonal v)ᴴ = diagonal (star v) := by
rw [conjTranspose, diagonal_transpose, diagonal_map (star_zero _)]
rfl
#align matrix.diagonal_conj_transpose Matrix.diagonal_conjTranspose
section One
variable [Zero α] [One α]
instance one : One (Matrix n n α) :=
⟨diagonal fun _ => 1⟩
@[simp]
theorem diagonal_one : (diagonal fun _ => 1 : Matrix n n α) = 1 :=
rfl
#align matrix.diagonal_one Matrix.diagonal_one
theorem one_apply {i j} : (1 : Matrix n n α) i j = if i = j then 1 else 0 :=
rfl
#align matrix.one_apply Matrix.one_apply
@[simp]
theorem one_apply_eq (i) : (1 : Matrix n n α) i i = 1 :=
diagonal_apply_eq _ i
#align matrix.one_apply_eq Matrix.one_apply_eq
@[simp]
theorem one_apply_ne {i j} : i ≠ j → (1 : Matrix n n α) i j = 0 :=
diagonal_apply_ne _
#align matrix.one_apply_ne Matrix.one_apply_ne
theorem one_apply_ne' {i j} : j ≠ i → (1 : Matrix n n α) i j = 0 :=
diagonal_apply_ne' _
#align matrix.one_apply_ne' Matrix.one_apply_ne'
@[simp]
theorem map_one [Zero β] [One β] (f : α → β) (h₀ : f 0 = 0) (h₁ : f 1 = 1) :
(1 : Matrix n n α).map f = (1 : Matrix n n β) := by
ext
simp only [one_apply, map_apply]
split_ifs <;> simp [h₀, h₁]
#align matrix.map_one Matrix.map_one
-- Porting note: added implicit argument `(f := fun_ => α)`, why is that needed?
theorem one_eq_pi_single {i j} : (1 : Matrix n n α) i j = Pi.single (f := fun _ => α) i 1 j := by
simp only [one_apply, Pi.single_apply, eq_comm]
#align matrix.one_eq_pi_single Matrix.one_eq_pi_single
lemma zero_le_one_elem [Preorder α] [ZeroLEOneClass α] (i j : n) :
0 ≤ (1 : Matrix n n α) i j := by
by_cases hi : i = j <;> simp [hi]
lemma zero_le_one_row [Preorder α] [ZeroLEOneClass α] (i : n) :
0 ≤ (1 : Matrix n n α) i :=
zero_le_one_elem i
end One
instance instAddMonoidWithOne [AddMonoidWithOne α] : AddMonoidWithOne (Matrix n n α) where
natCast_zero := show diagonal _ = _ by
rw [Nat.cast_zero, diagonal_zero]
natCast_succ n := show diagonal _ = diagonal _ + _ by
rw [Nat.cast_succ, ← diagonal_add, diagonal_one]
instance instAddGroupWithOne [AddGroupWithOne α] : AddGroupWithOne (Matrix n n α) where
intCast_ofNat n := show diagonal _ = diagonal _ by
rw [Int.cast_natCast]
intCast_negSucc n := show diagonal _ = -(diagonal _) by
rw [Int.cast_negSucc, diagonal_neg]
__ := addGroup
__ := instAddMonoidWithOne
instance instAddCommMonoidWithOne [AddCommMonoidWithOne α] :
AddCommMonoidWithOne (Matrix n n α) where
__ := addCommMonoid
__ := instAddMonoidWithOne
instance instAddCommGroupWithOne [AddCommGroupWithOne α] :
AddCommGroupWithOne (Matrix n n α) where
__ := addCommGroup
__ := instAddGroupWithOne
section Numeral
set_option linter.deprecated false
@[deprecated, simp]
theorem bit0_apply [Add α] (M : Matrix m m α) (i : m) (j : m) : (bit0 M) i j = bit0 (M i j) :=
rfl
#align matrix.bit0_apply Matrix.bit0_apply
variable [AddZeroClass α] [One α]
@[deprecated]
theorem bit1_apply (M : Matrix n n α) (i : n) (j : n) :
(bit1 M) i j = if i = j then bit1 (M i j) else bit0 (M i j) := by
dsimp [bit1]
by_cases h : i = j <;>
simp [h]
#align matrix.bit1_apply Matrix.bit1_apply
@[deprecated, simp]
theorem bit1_apply_eq (M : Matrix n n α) (i : n) : (bit1 M) i i = bit1 (M i i) := by
simp [bit1_apply]
#align matrix.bit1_apply_eq Matrix.bit1_apply_eq
@[deprecated, simp]
theorem bit1_apply_ne (M : Matrix n n α) {i j : n} (h : i ≠ j) : (bit1 M) i j = bit0 (M i j) := by
simp [bit1_apply, h]
#align matrix.bit1_apply_ne Matrix.bit1_apply_ne
end Numeral
end Diagonal
section Diag
/-- The diagonal of a square matrix. -/
-- @[simp] -- Porting note: simpNF does not like this.
def diag (A : Matrix n n α) (i : n) : α :=
A i i
#align matrix.diag Matrix.diag
-- Porting note: new, because of removed `simp` above.
-- TODO: set as an equation lemma for `diag`, see mathlib4#3024
@[simp]
theorem diag_apply (A : Matrix n n α) (i) : diag A i = A i i :=
rfl
@[simp]
theorem diag_diagonal [DecidableEq n] [Zero α] (a : n → α) : diag (diagonal a) = a :=
funext <| @diagonal_apply_eq _ _ _ _ a
#align matrix.diag_diagonal Matrix.diag_diagonal
@[simp]
theorem diag_transpose (A : Matrix n n α) : diag Aᵀ = diag A :=
rfl
#align matrix.diag_transpose Matrix.diag_transpose
@[simp]
theorem diag_zero [Zero α] : diag (0 : Matrix n n α) = 0 :=
rfl
#align matrix.diag_zero Matrix.diag_zero
@[simp]
theorem diag_add [Add α] (A B : Matrix n n α) : diag (A + B) = diag A + diag B :=
rfl
#align matrix.diag_add Matrix.diag_add
@[simp]
theorem diag_sub [Sub α] (A B : Matrix n n α) : diag (A - B) = diag A - diag B :=
rfl
#align matrix.diag_sub Matrix.diag_sub
@[simp]
theorem diag_neg [Neg α] (A : Matrix n n α) : diag (-A) = -diag A :=
rfl
#align matrix.diag_neg Matrix.diag_neg
@[simp]
theorem diag_smul [SMul R α] (r : R) (A : Matrix n n α) : diag (r • A) = r • diag A :=
rfl
#align matrix.diag_smul Matrix.diag_smul
@[simp]
theorem diag_one [DecidableEq n] [Zero α] [One α] : diag (1 : Matrix n n α) = 1 :=
diag_diagonal _
#align matrix.diag_one Matrix.diag_one
variable (n α)
/-- `Matrix.diag` as an `AddMonoidHom`. -/
@[simps]
def diagAddMonoidHom [AddZeroClass α] : Matrix n n α →+ n → α where
toFun := diag
map_zero' := diag_zero
map_add' := diag_add
#align matrix.diag_add_monoid_hom Matrix.diagAddMonoidHom
variable (R)
/-- `Matrix.diag` as a `LinearMap`. -/
@[simps]
def diagLinearMap [Semiring R] [AddCommMonoid α] [Module R α] : Matrix n n α →ₗ[R] n → α :=
{ diagAddMonoidHom n α with map_smul' := diag_smul }
#align matrix.diag_linear_map Matrix.diagLinearMap
variable {n α R}
theorem diag_map {f : α → β} {A : Matrix n n α} : diag (A.map f) = f ∘ diag A :=
rfl
#align matrix.diag_map Matrix.diag_map
@[simp]
theorem diag_conjTranspose [AddMonoid α] [StarAddMonoid α] (A : Matrix n n α) :
diag Aᴴ = star (diag A) :=
rfl
#align matrix.diag_conj_transpose Matrix.diag_conjTranspose
@[simp]
theorem diag_list_sum [AddMonoid α] (l : List (Matrix n n α)) : diag l.sum = (l.map diag).sum :=
map_list_sum (diagAddMonoidHom n α) l
#align matrix.diag_list_sum Matrix.diag_list_sum
@[simp]
theorem diag_multiset_sum [AddCommMonoid α] (s : Multiset (Matrix n n α)) :
diag s.sum = (s.map diag).sum :=
map_multiset_sum (diagAddMonoidHom n α) s
#align matrix.diag_multiset_sum Matrix.diag_multiset_sum
@[simp]
theorem diag_sum {ι} [AddCommMonoid α] (s : Finset ι) (f : ι → Matrix n n α) :
diag (∑ i ∈ s, f i) = ∑ i ∈ s, diag (f i) :=
map_sum (diagAddMonoidHom n α) f s
#align matrix.diag_sum Matrix.diag_sum
end Diag
section DotProduct
variable [Fintype m] [Fintype n]
/-- `dotProduct v w` is the sum of the entrywise products `v i * w i` -/
def dotProduct [Mul α] [AddCommMonoid α] (v w : m → α) : α :=
∑ i, v i * w i
#align matrix.dot_product Matrix.dotProduct
/- The precedence of 72 comes immediately after ` • ` for `SMul.smul`,
so that `r₁ • a ⬝ᵥ r₂ • b` is parsed as `(r₁ • a) ⬝ᵥ (r₂ • b)` here. -/
@[inherit_doc]
scoped infixl:72 " ⬝ᵥ " => Matrix.dotProduct
theorem dotProduct_assoc [NonUnitalSemiring α] (u : m → α) (w : n → α) (v : Matrix m n α) :
(fun j => u ⬝ᵥ fun i => v i j) ⬝ᵥ w = u ⬝ᵥ fun i => v i ⬝ᵥ w := by
simpa [dotProduct, Finset.mul_sum, Finset.sum_mul, mul_assoc] using Finset.sum_comm
#align matrix.dot_product_assoc Matrix.dotProduct_assoc
theorem dotProduct_comm [AddCommMonoid α] [CommSemigroup α] (v w : m → α) : v ⬝ᵥ w = w ⬝ᵥ v := by
simp_rw [dotProduct, mul_comm]
#align matrix.dot_product_comm Matrix.dotProduct_comm
@[simp]
theorem dotProduct_pUnit [AddCommMonoid α] [Mul α] (v w : PUnit → α) : v ⬝ᵥ w = v ⟨⟩ * w ⟨⟩ := by
simp [dotProduct]
#align matrix.dot_product_punit Matrix.dotProduct_pUnit
section MulOneClass
variable [MulOneClass α] [AddCommMonoid α]
theorem dotProduct_one (v : n → α) : v ⬝ᵥ 1 = ∑ i, v i := by simp [(· ⬝ᵥ ·)]
#align matrix.dot_product_one Matrix.dotProduct_one
theorem one_dotProduct (v : n → α) : 1 ⬝ᵥ v = ∑ i, v i := by simp [(· ⬝ᵥ ·)]
#align matrix.one_dot_product Matrix.one_dotProduct
end MulOneClass
section NonUnitalNonAssocSemiring
variable [NonUnitalNonAssocSemiring α] (u v w : m → α) (x y : n → α)
@[simp]
theorem dotProduct_zero : v ⬝ᵥ 0 = 0 := by simp [dotProduct]
#align matrix.dot_product_zero Matrix.dotProduct_zero
@[simp]
theorem dotProduct_zero' : (v ⬝ᵥ fun _ => 0) = 0 :=
dotProduct_zero v
#align matrix.dot_product_zero' Matrix.dotProduct_zero'
@[simp]
theorem zero_dotProduct : 0 ⬝ᵥ v = 0 := by simp [dotProduct]
#align matrix.zero_dot_product Matrix.zero_dotProduct
@[simp]
theorem zero_dotProduct' : (fun _ => (0 : α)) ⬝ᵥ v = 0 :=
zero_dotProduct v
#align matrix.zero_dot_product' Matrix.zero_dotProduct'
@[simp]
theorem add_dotProduct : (u + v) ⬝ᵥ w = u ⬝ᵥ w + v ⬝ᵥ w := by
simp [dotProduct, add_mul, Finset.sum_add_distrib]
#align matrix.add_dot_product Matrix.add_dotProduct
@[simp]
theorem dotProduct_add : u ⬝ᵥ (v + w) = u ⬝ᵥ v + u ⬝ᵥ w := by
simp [dotProduct, mul_add, Finset.sum_add_distrib]
#align matrix.dot_product_add Matrix.dotProduct_add
@[simp]
theorem sum_elim_dotProduct_sum_elim : Sum.elim u x ⬝ᵥ Sum.elim v y = u ⬝ᵥ v + x ⬝ᵥ y := by
simp [dotProduct]
#align matrix.sum_elim_dot_product_sum_elim Matrix.sum_elim_dotProduct_sum_elim
/-- Permuting a vector on the left of a dot product can be transferred to the right. -/
@[simp]
theorem comp_equiv_symm_dotProduct (e : m ≃ n) : u ∘ e.symm ⬝ᵥ x = u ⬝ᵥ x ∘ e :=
(e.sum_comp _).symm.trans <|
Finset.sum_congr rfl fun _ _ => by simp only [Function.comp, Equiv.symm_apply_apply]
#align matrix.comp_equiv_symm_dot_product Matrix.comp_equiv_symm_dotProduct
/-- Permuting a vector on the right of a dot product can be transferred to the left. -/
@[simp]
theorem dotProduct_comp_equiv_symm (e : n ≃ m) : u ⬝ᵥ x ∘ e.symm = u ∘ e ⬝ᵥ x := by
simpa only [Equiv.symm_symm] using (comp_equiv_symm_dotProduct u x e.symm).symm
#align matrix.dot_product_comp_equiv_symm Matrix.dotProduct_comp_equiv_symm
/-- Permuting vectors on both sides of a dot product is a no-op. -/
@[simp]
theorem comp_equiv_dotProduct_comp_equiv (e : m ≃ n) : x ∘ e ⬝ᵥ y ∘ e = x ⬝ᵥ y := by
-- Porting note: was `simp only` with all three lemmas
rw [← dotProduct_comp_equiv_symm]; simp only [Function.comp, Equiv.apply_symm_apply]
#align matrix.comp_equiv_dot_product_comp_equiv Matrix.comp_equiv_dotProduct_comp_equiv
end NonUnitalNonAssocSemiring
section NonUnitalNonAssocSemiringDecidable
variable [DecidableEq m] [NonUnitalNonAssocSemiring α] (u v w : m → α)
@[simp]
theorem diagonal_dotProduct (i : m) : diagonal v i ⬝ᵥ w = v i * w i := by
have : ∀ j ≠ i, diagonal v i j * w j = 0 := fun j hij => by
simp [diagonal_apply_ne' _ hij]
convert Finset.sum_eq_single i (fun j _ => this j) _ using 1 <;> simp
#align matrix.diagonal_dot_product Matrix.diagonal_dotProduct
@[simp]
theorem dotProduct_diagonal (i : m) : v ⬝ᵥ diagonal w i = v i * w i := by
have : ∀ j ≠ i, v j * diagonal w i j = 0 := fun j hij => by
simp [diagonal_apply_ne' _ hij]
convert Finset.sum_eq_single i (fun j _ => this j) _ using 1 <;> simp
#align matrix.dot_product_diagonal Matrix.dotProduct_diagonal
@[simp]
theorem dotProduct_diagonal' (i : m) : (v ⬝ᵥ fun j => diagonal w j i) = v i * w i := by
have : ∀ j ≠ i, v j * diagonal w j i = 0 := fun j hij => by
simp [diagonal_apply_ne _ hij]
convert Finset.sum_eq_single i (fun j _ => this j) _ using 1 <;> simp
#align matrix.dot_product_diagonal' Matrix.dotProduct_diagonal'
@[simp]
theorem single_dotProduct (x : α) (i : m) : Pi.single i x ⬝ᵥ v = x * v i := by
-- Porting note: (implicit arg) added `(f := fun _ => α)`
have : ∀ j ≠ i, Pi.single (f := fun _ => α) i x j * v j = 0 := fun j hij => by
simp [Pi.single_eq_of_ne hij]
convert Finset.sum_eq_single i (fun j _ => this j) _ using 1 <;> simp
#align matrix.single_dot_product Matrix.single_dotProduct
@[simp]
theorem dotProduct_single (x : α) (i : m) : v ⬝ᵥ Pi.single i x = v i * x := by
-- Porting note: (implicit arg) added `(f := fun _ => α)`
have : ∀ j ≠ i, v j * Pi.single (f := fun _ => α) i x j = 0 := fun j hij => by
simp [Pi.single_eq_of_ne hij]
convert Finset.sum_eq_single i (fun j _ => this j) _ using 1 <;> simp
#align matrix.dot_product_single Matrix.dotProduct_single
end NonUnitalNonAssocSemiringDecidable
section NonAssocSemiring
variable [NonAssocSemiring α]
@[simp]
theorem one_dotProduct_one : (1 : n → α) ⬝ᵥ 1 = Fintype.card n := by
simp [dotProduct]
#align matrix.one_dot_product_one Matrix.one_dotProduct_one
end NonAssocSemiring
section NonUnitalNonAssocRing
variable [NonUnitalNonAssocRing α] (u v w : m → α)
@[simp]
theorem neg_dotProduct : -v ⬝ᵥ w = -(v ⬝ᵥ w) := by simp [dotProduct]
#align matrix.neg_dot_product Matrix.neg_dotProduct
@[simp]
theorem dotProduct_neg : v ⬝ᵥ -w = -(v ⬝ᵥ w) := by simp [dotProduct]
#align matrix.dot_product_neg Matrix.dotProduct_neg
lemma neg_dotProduct_neg : -v ⬝ᵥ -w = v ⬝ᵥ w := by
rw [neg_dotProduct, dotProduct_neg, neg_neg]
@[simp]
theorem sub_dotProduct : (u - v) ⬝ᵥ w = u ⬝ᵥ w - v ⬝ᵥ w := by simp [sub_eq_add_neg]
#align matrix.sub_dot_product Matrix.sub_dotProduct
@[simp]
theorem dotProduct_sub : u ⬝ᵥ (v - w) = u ⬝ᵥ v - u ⬝ᵥ w := by simp [sub_eq_add_neg]
#align matrix.dot_product_sub Matrix.dotProduct_sub
end NonUnitalNonAssocRing
section DistribMulAction
variable [Monoid R] [Mul α] [AddCommMonoid α] [DistribMulAction R α]
@[simp]
theorem smul_dotProduct [IsScalarTower R α α] (x : R) (v w : m → α) :
x • v ⬝ᵥ w = x • (v ⬝ᵥ w) := by simp [dotProduct, Finset.smul_sum, smul_mul_assoc]
#align matrix.smul_dot_product Matrix.smul_dotProduct
@[simp]
theorem dotProduct_smul [SMulCommClass R α α] (x : R) (v w : m → α) :
v ⬝ᵥ x • w = x • (v ⬝ᵥ w) := by simp [dotProduct, Finset.smul_sum, mul_smul_comm]
#align matrix.dot_product_smul Matrix.dotProduct_smul
end DistribMulAction
section StarRing
variable [NonUnitalSemiring α] [StarRing α] (v w : m → α)
theorem star_dotProduct_star : star v ⬝ᵥ star w = star (w ⬝ᵥ v) := by simp [dotProduct]
#align matrix.star_dot_product_star Matrix.star_dotProduct_star
theorem star_dotProduct : star v ⬝ᵥ w = star (star w ⬝ᵥ v) := by simp [dotProduct]
#align matrix.star_dot_product Matrix.star_dotProduct
theorem dotProduct_star : v ⬝ᵥ star w = star (w ⬝ᵥ star v) := by simp [dotProduct]
#align matrix.dot_product_star Matrix.dotProduct_star
end StarRing
end DotProduct
open Matrix
/-- `M * N` is the usual product of matrices `M` and `N`, i.e. we have that
`(M * N) i k` is the dot product of the `i`-th row of `M` by the `k`-th column of `N`.
This is currently only defined when `m` is finite. -/
-- We want to be lower priority than `instHMul`, but without this we can't have operands with
-- implicit dimensions.
@[default_instance 100]
instance [Fintype m] [Mul α] [AddCommMonoid α] :
HMul (Matrix l m α) (Matrix m n α) (Matrix l n α) where
hMul M N := fun i k => (fun j => M i j) ⬝ᵥ fun j => N j k
#align matrix.mul HMul.hMul
theorem mul_apply [Fintype m] [Mul α] [AddCommMonoid α] {M : Matrix l m α} {N : Matrix m n α}
{i k} : (M * N) i k = ∑ j, M i j * N j k :=
rfl
#align matrix.mul_apply Matrix.mul_apply
instance [Fintype n] [Mul α] [AddCommMonoid α] : Mul (Matrix n n α) where mul M N := M * N
#noalign matrix.mul_eq_mul
theorem mul_apply' [Fintype m] [Mul α] [AddCommMonoid α] {M : Matrix l m α} {N : Matrix m n α}
{i k} : (M * N) i k = (fun j => M i j) ⬝ᵥ fun j => N j k :=
rfl
#align matrix.mul_apply' Matrix.mul_apply'
theorem sum_apply [AddCommMonoid α] (i : m) (j : n) (s : Finset β) (g : β → Matrix m n α) :
(∑ c ∈ s, g c) i j = ∑ c ∈ s, g c i j :=
(congr_fun (s.sum_apply i g) j).trans (s.sum_apply j _)
#align matrix.sum_apply Matrix.sum_apply
theorem two_mul_expl {R : Type*} [CommRing R] (A B : Matrix (Fin 2) (Fin 2) R) :
(A * B) 0 0 = A 0 0 * B 0 0 + A 0 1 * B 1 0 ∧
(A * B) 0 1 = A 0 0 * B 0 1 + A 0 1 * B 1 1 ∧
(A * B) 1 0 = A 1 0 * B 0 0 + A 1 1 * B 1 0 ∧
(A * B) 1 1 = A 1 0 * B 0 1 + A 1 1 * B 1 1 := by
refine ⟨?_, ?_, ?_, ?_⟩ <;>
· rw [Matrix.mul_apply, Finset.sum_fin_eq_sum_range, Finset.sum_range_succ, Finset.sum_range_succ]
simp
#align matrix.two_mul_expl Matrix.two_mul_expl
section AddCommMonoid
variable [AddCommMonoid α] [Mul α]
@[simp]
theorem smul_mul [Fintype n] [Monoid R] [DistribMulAction R α] [IsScalarTower R α α] (a : R)
(M : Matrix m n α) (N : Matrix n l α) : (a • M) * N = a • (M * N) := by
ext
apply smul_dotProduct a
#align matrix.smul_mul Matrix.smul_mul
@[simp]
theorem mul_smul [Fintype n] [Monoid R] [DistribMulAction R α] [SMulCommClass R α α]
(M : Matrix m n α) (a : R) (N : Matrix n l α) : M * (a • N) = a • (M * N) := by
ext
apply dotProduct_smul
#align matrix.mul_smul Matrix.mul_smul
end AddCommMonoid
section NonUnitalNonAssocSemiring
variable [NonUnitalNonAssocSemiring α]
@[simp]
protected theorem mul_zero [Fintype n] (M : Matrix m n α) : M * (0 : Matrix n o α) = 0 := by
ext
apply dotProduct_zero
#align matrix.mul_zero Matrix.mul_zero
@[simp]
protected theorem zero_mul [Fintype m] (M : Matrix m n α) : (0 : Matrix l m α) * M = 0 := by
ext
apply zero_dotProduct
#align matrix.zero_mul Matrix.zero_mul
protected theorem mul_add [Fintype n] (L : Matrix m n α) (M N : Matrix n o α) :
L * (M + N) = L * M + L * N := by
ext
apply dotProduct_add
#align matrix.mul_add Matrix.mul_add
protected theorem add_mul [Fintype m] (L M : Matrix l m α) (N : Matrix m n α) :
(L + M) * N = L * N + M * N := by
ext
apply add_dotProduct
#align matrix.add_mul Matrix.add_mul
instance nonUnitalNonAssocSemiring [Fintype n] : NonUnitalNonAssocSemiring (Matrix n n α) :=
{ Matrix.addCommMonoid with
mul_zero := Matrix.mul_zero
zero_mul := Matrix.zero_mul
left_distrib := Matrix.mul_add
right_distrib := Matrix.add_mul }
@[simp]
theorem diagonal_mul [Fintype m] [DecidableEq m] (d : m → α) (M : Matrix m n α) (i j) :
(diagonal d * M) i j = d i * M i j :=
diagonal_dotProduct _ _ _
#align matrix.diagonal_mul Matrix.diagonal_mul
@[simp]
theorem mul_diagonal [Fintype n] [DecidableEq n] (d : n → α) (M : Matrix m n α) (i j) :
(M * diagonal d) i j = M i j * d j := by
rw [← diagonal_transpose]
apply dotProduct_diagonal
#align matrix.mul_diagonal Matrix.mul_diagonal
@[simp]
theorem diagonal_mul_diagonal [Fintype n] [DecidableEq n] (d₁ d₂ : n → α) :
diagonal d₁ * diagonal d₂ = diagonal fun i => d₁ i * d₂ i := by
ext i j
by_cases h : i = j <;>
simp [h]
#align matrix.diagonal_mul_diagonal Matrix.diagonal_mul_diagonal
theorem diagonal_mul_diagonal' [Fintype n] [DecidableEq n] (d₁ d₂ : n → α) :
diagonal d₁ * diagonal d₂ = diagonal fun i => d₁ i * d₂ i :=
diagonal_mul_diagonal _ _
#align matrix.diagonal_mul_diagonal' Matrix.diagonal_mul_diagonal'
theorem smul_eq_diagonal_mul [Fintype m] [DecidableEq m] (M : Matrix m n α) (a : α) :
a • M = (diagonal fun _ => a) * M := by
ext
simp
#align matrix.smul_eq_diagonal_mul Matrix.smul_eq_diagonal_mul
theorem op_smul_eq_mul_diagonal [Fintype n] [DecidableEq n] (M : Matrix m n α) (a : α) :
MulOpposite.op a • M = M * (diagonal fun _ : n => a) := by
ext
simp
/-- Left multiplication by a matrix, as an `AddMonoidHom` from matrices to matrices. -/
@[simps]
def addMonoidHomMulLeft [Fintype m] (M : Matrix l m α) : Matrix m n α →+ Matrix l n α where
toFun x := M * x
map_zero' := Matrix.mul_zero _
map_add' := Matrix.mul_add _
#align matrix.add_monoid_hom_mul_left Matrix.addMonoidHomMulLeft
/-- Right multiplication by a matrix, as an `AddMonoidHom` from matrices to matrices. -/
@[simps]
def addMonoidHomMulRight [Fintype m] (M : Matrix m n α) : Matrix l m α →+ Matrix l n α where
toFun x := x * M
map_zero' := Matrix.zero_mul _
map_add' _ _ := Matrix.add_mul _ _ _
#align matrix.add_monoid_hom_mul_right Matrix.addMonoidHomMulRight
protected theorem sum_mul [Fintype m] (s : Finset β) (f : β → Matrix l m α) (M : Matrix m n α) :
(∑ a ∈ s, f a) * M = ∑ a ∈ s, f a * M :=
map_sum (addMonoidHomMulRight M) f s
#align matrix.sum_mul Matrix.sum_mul
protected theorem mul_sum [Fintype m] (s : Finset β) (f : β → Matrix m n α) (M : Matrix l m α) :
(M * ∑ a ∈ s, f a) = ∑ a ∈ s, M * f a :=
map_sum (addMonoidHomMulLeft M) f s
#align matrix.mul_sum Matrix.mul_sum
/-- This instance enables use with `smul_mul_assoc`. -/
instance Semiring.isScalarTower [Fintype n] [Monoid R] [DistribMulAction R α]
[IsScalarTower R α α] : IsScalarTower R (Matrix n n α) (Matrix n n α) :=
⟨fun r m n => Matrix.smul_mul r m n⟩
#align matrix.semiring.is_scalar_tower Matrix.Semiring.isScalarTower
/-- This instance enables use with `mul_smul_comm`. -/
instance Semiring.smulCommClass [Fintype n] [Monoid R] [DistribMulAction R α]
[SMulCommClass R α α] : SMulCommClass R (Matrix n n α) (Matrix n n α) :=
⟨fun r m n => (Matrix.mul_smul m r n).symm⟩
#align matrix.semiring.smul_comm_class Matrix.Semiring.smulCommClass
end NonUnitalNonAssocSemiring
section NonAssocSemiring
variable [NonAssocSemiring α]
@[simp]
protected theorem one_mul [Fintype m] [DecidableEq m] (M : Matrix m n α) :
(1 : Matrix m m α) * M = M := by
ext
rw [← diagonal_one, diagonal_mul, one_mul]
#align matrix.one_mul Matrix.one_mul
@[simp]
protected theorem mul_one [Fintype n] [DecidableEq n] (M : Matrix m n α) :
M * (1 : Matrix n n α) = M := by
ext
rw [← diagonal_one, mul_diagonal, mul_one]
#align matrix.mul_one Matrix.mul_one
instance nonAssocSemiring [Fintype n] [DecidableEq n] : NonAssocSemiring (Matrix n n α) :=
{ Matrix.nonUnitalNonAssocSemiring, Matrix.instAddCommMonoidWithOne with
one := 1
one_mul := Matrix.one_mul
mul_one := Matrix.mul_one }
@[simp]
theorem map_mul [Fintype n] {L : Matrix m n α} {M : Matrix n o α} [NonAssocSemiring β]
{f : α →+* β} : (L * M).map f = L.map f * M.map f := by
ext
simp [mul_apply, map_sum]
#align matrix.map_mul Matrix.map_mul
theorem smul_one_eq_diagonal [DecidableEq m] (a : α) :
a • (1 : Matrix m m α) = diagonal fun _ => a := by
simp_rw [← diagonal_one, ← diagonal_smul, Pi.smul_def, smul_eq_mul, mul_one]
theorem op_smul_one_eq_diagonal [DecidableEq m] (a : α) :
MulOpposite.op a • (1 : Matrix m m α) = diagonal fun _ => a := by
simp_rw [← diagonal_one, ← diagonal_smul, Pi.smul_def, op_smul_eq_mul, one_mul]
variable (α n)
/-- `Matrix.diagonal` as a `RingHom`. -/
@[simps]
def diagonalRingHom [Fintype n] [DecidableEq n] : (n → α) →+* Matrix n n α :=
{ diagonalAddMonoidHom n α with
toFun := diagonal
map_one' := diagonal_one
map_mul' := fun _ _ => (diagonal_mul_diagonal' _ _).symm }
#align matrix.diagonal_ring_hom Matrix.diagonalRingHom
end NonAssocSemiring
section NonUnitalSemiring
variable [NonUnitalSemiring α] [Fintype m] [Fintype n]
protected theorem mul_assoc (L : Matrix l m α) (M : Matrix m n α) (N : Matrix n o α) :
L * M * N = L * (M * N) := by
ext
apply dotProduct_assoc
#align matrix.mul_assoc Matrix.mul_assoc
instance nonUnitalSemiring : NonUnitalSemiring (Matrix n n α) :=
{ Matrix.nonUnitalNonAssocSemiring with mul_assoc := Matrix.mul_assoc }
end NonUnitalSemiring
section Semiring
variable [Semiring α]
instance semiring [Fintype n] [DecidableEq n] : Semiring (Matrix n n α) :=
{ Matrix.nonUnitalSemiring, Matrix.nonAssocSemiring with }
end Semiring
section NonUnitalNonAssocRing
variable [NonUnitalNonAssocRing α] [Fintype n]
@[simp]
protected theorem neg_mul (M : Matrix m n α) (N : Matrix n o α) : (-M) * N = -(M * N) := by
ext
apply neg_dotProduct
#align matrix.neg_mul Matrix.neg_mul
@[simp]
protected theorem mul_neg (M : Matrix m n α) (N : Matrix n o α) : M * (-N) = -(M * N) := by
ext
apply dotProduct_neg
#align matrix.mul_neg Matrix.mul_neg
protected theorem sub_mul (M M' : Matrix m n α) (N : Matrix n o α) :
(M - M') * N = M * N - M' * N := by
rw [sub_eq_add_neg, Matrix.add_mul, Matrix.neg_mul, sub_eq_add_neg]
#align matrix.sub_mul Matrix.sub_mul
protected theorem mul_sub (M : Matrix m n α) (N N' : Matrix n o α) :
M * (N - N') = M * N - M * N' := by
rw [sub_eq_add_neg, Matrix.mul_add, Matrix.mul_neg, sub_eq_add_neg]
#align matrix.mul_sub Matrix.mul_sub
instance nonUnitalNonAssocRing : NonUnitalNonAssocRing (Matrix n n α) :=
{ Matrix.nonUnitalNonAssocSemiring, Matrix.addCommGroup with }
end NonUnitalNonAssocRing
instance instNonUnitalRing [Fintype n] [NonUnitalRing α] : NonUnitalRing (Matrix n n α) :=
{ Matrix.nonUnitalSemiring, Matrix.addCommGroup with }
#align matrix.non_unital_ring Matrix.instNonUnitalRing
instance instNonAssocRing [Fintype n] [DecidableEq n] [NonAssocRing α] :
NonAssocRing (Matrix n n α) :=
{ Matrix.nonAssocSemiring, Matrix.instAddCommGroupWithOne with }
#align matrix.non_assoc_ring Matrix.instNonAssocRing
instance instRing [Fintype n] [DecidableEq n] [Ring α] : Ring (Matrix n n α) :=
{ Matrix.semiring, Matrix.instAddCommGroupWithOne with }
#align matrix.ring Matrix.instRing
section Semiring
variable [Semiring α]
theorem diagonal_pow [Fintype n] [DecidableEq n] (v : n → α) (k : ℕ) :
diagonal v ^ k = diagonal (v ^ k) :=
(map_pow (diagonalRingHom n α) v k).symm
#align matrix.diagonal_pow Matrix.diagonal_pow
@[simp]
theorem mul_mul_left [Fintype n] (M : Matrix m n α) (N : Matrix n o α) (a : α) :
(of fun i j => a * M i j) * N = a • (M * N) :=
smul_mul a M N
#align matrix.mul_mul_left Matrix.mul_mul_left
/-- The ring homomorphism `α →+* Matrix n n α`
sending `a` to the diagonal matrix with `a` on the diagonal.
-/
def scalar (n : Type u) [DecidableEq n] [Fintype n] : α →+* Matrix n n α :=
(diagonalRingHom n α).comp <| Pi.constRingHom n α
#align matrix.scalar Matrix.scalar
section Scalar
variable [DecidableEq n] [Fintype n]
@[simp]
theorem scalar_apply (a : α) : scalar n a = diagonal fun _ => a :=
rfl
#align matrix.coe_scalar Matrix.scalar_applyₓ
#noalign matrix.scalar_apply_eq
#noalign matrix.scalar_apply_ne
theorem scalar_inj [Nonempty n] {r s : α} : scalar n r = scalar n s ↔ r = s :=
(diagonal_injective.comp Function.const_injective).eq_iff
#align matrix.scalar_inj Matrix.scalar_inj
theorem scalar_commute_iff {r : α} {M : Matrix n n α} :
Commute (scalar n r) M ↔ r • M = MulOpposite.op r • M := by
simp_rw [Commute, SemiconjBy, scalar_apply, ← smul_eq_diagonal_mul, ← op_smul_eq_mul_diagonal]
theorem scalar_commute (r : α) (hr : ∀ r', Commute r r') (M : Matrix n n α) :
Commute (scalar n r) M := scalar_commute_iff.2 <| ext fun _ _ => hr _
#align matrix.scalar.commute Matrix.scalar_commuteₓ
end Scalar
end Semiring
section CommSemiring
variable [CommSemiring α]
theorem smul_eq_mul_diagonal [Fintype n] [DecidableEq n] (M : Matrix m n α) (a : α) :
a • M = M * diagonal fun _ => a := by
ext
simp [mul_comm]
#align matrix.smul_eq_mul_diagonal Matrix.smul_eq_mul_diagonal
@[simp]
theorem mul_mul_right [Fintype n] (M : Matrix m n α) (N : Matrix n o α) (a : α) :
(M * of fun i j => a * N i j) = a • (M * N) :=
mul_smul M a N
#align matrix.mul_mul_right Matrix.mul_mul_right
end CommSemiring
section Algebra
variable [Fintype n] [DecidableEq n]
variable [CommSemiring R] [Semiring α] [Semiring β] [Algebra R α] [Algebra R β]
instance instAlgebra : Algebra R (Matrix n n α) where
toRingHom := (Matrix.scalar n).comp (algebraMap R α)
commutes' r x := scalar_commute _ (fun r' => Algebra.commutes _ _) _
smul_def' r x := by ext; simp [Matrix.scalar, Algebra.smul_def r]
#align matrix.algebra Matrix.instAlgebra
theorem algebraMap_matrix_apply {r : R} {i j : n} :
algebraMap R (Matrix n n α) r i j = if i = j then algebraMap R α r else 0 := by
dsimp [algebraMap, Algebra.toRingHom, Matrix.scalar]
split_ifs with h <;> simp [h, Matrix.one_apply_ne]
#align matrix.algebra_map_matrix_apply Matrix.algebraMap_matrix_apply
theorem algebraMap_eq_diagonal (r : R) :
algebraMap R (Matrix n n α) r = diagonal (algebraMap R (n → α) r) := rfl
#align matrix.algebra_map_eq_diagonal Matrix.algebraMap_eq_diagonal
#align matrix.algebra_map_eq_smul Algebra.algebraMap_eq_smul_one
theorem algebraMap_eq_diagonalRingHom :
algebraMap R (Matrix n n α) = (diagonalRingHom n α).comp (algebraMap R _) := rfl
#align matrix.algebra_map_eq_diagonal_ring_hom Matrix.algebraMap_eq_diagonalRingHom
@[simp]
theorem map_algebraMap (r : R) (f : α → β) (hf : f 0 = 0)
(hf₂ : f (algebraMap R α r) = algebraMap R β r) :
(algebraMap R (Matrix n n α) r).map f = algebraMap R (Matrix n n β) r := by
rw [algebraMap_eq_diagonal, algebraMap_eq_diagonal, diagonal_map hf]
-- Porting note: (congr) the remaining proof was
-- ```
-- congr 1
-- simp only [hf₂, Pi.algebraMap_apply]
-- ```
-- But some `congr 1` doesn't quite work.
simp only [Pi.algebraMap_apply, diagonal_eq_diagonal_iff]
intro
rw [hf₂]
#align matrix.map_algebra_map Matrix.map_algebraMap
variable (R)
/-- `Matrix.diagonal` as an `AlgHom`. -/
@[simps]
def diagonalAlgHom : (n → α) →ₐ[R] Matrix n n α :=
{ diagonalRingHom n α with
toFun := diagonal
commutes' := fun r => (algebraMap_eq_diagonal r).symm }
#align matrix.diagonal_alg_hom Matrix.diagonalAlgHom
end Algebra
end Matrix
/-!
### Bundled versions of `Matrix.map`
-/
namespace Equiv
/-- The `Equiv` between spaces of matrices induced by an `Equiv` between their
coefficients. This is `Matrix.map` as an `Equiv`. -/
@[simps apply]
def mapMatrix (f : α ≃ β) : Matrix m n α ≃ Matrix m n β where
toFun M := M.map f
invFun M := M.map f.symm
left_inv _ := Matrix.ext fun _ _ => f.symm_apply_apply _
right_inv _ := Matrix.ext fun _ _ => f.apply_symm_apply _
#align equiv.map_matrix Equiv.mapMatrix
@[simp]
theorem mapMatrix_refl : (Equiv.refl α).mapMatrix = Equiv.refl (Matrix m n α) :=
rfl
#align equiv.map_matrix_refl Equiv.mapMatrix_refl
@[simp]
theorem mapMatrix_symm (f : α ≃ β) : f.mapMatrix.symm = (f.symm.mapMatrix : Matrix m n β ≃ _) :=
rfl
#align equiv.map_matrix_symm Equiv.mapMatrix_symm
@[simp]
theorem mapMatrix_trans (f : α ≃ β) (g : β ≃ γ) :
f.mapMatrix.trans g.mapMatrix = ((f.trans g).mapMatrix : Matrix m n α ≃ _) :=
rfl
#align equiv.map_matrix_trans Equiv.mapMatrix_trans
end Equiv
namespace AddMonoidHom
variable [AddZeroClass α] [AddZeroClass β] [AddZeroClass γ]
/-- The `AddMonoidHom` between spaces of matrices induced by an `AddMonoidHom` between their
coefficients. This is `Matrix.map` as an `AddMonoidHom`. -/
@[simps]
def mapMatrix (f : α →+ β) : Matrix m n α →+ Matrix m n β where
toFun M := M.map f
map_zero' := Matrix.map_zero f f.map_zero
map_add' := Matrix.map_add f f.map_add
#align add_monoid_hom.map_matrix AddMonoidHom.mapMatrix
@[simp]
theorem mapMatrix_id : (AddMonoidHom.id α).mapMatrix = AddMonoidHom.id (Matrix m n α) :=
rfl
#align add_monoid_hom.map_matrix_id AddMonoidHom.mapMatrix_id
@[simp]
theorem mapMatrix_comp (f : β →+ γ) (g : α →+ β) :
f.mapMatrix.comp g.mapMatrix = ((f.comp g).mapMatrix : Matrix m n α →+ _) :=
rfl
#align add_monoid_hom.map_matrix_comp AddMonoidHom.mapMatrix_comp
end AddMonoidHom
namespace AddEquiv
variable [Add α] [Add β] [Add γ]
/-- The `AddEquiv` between spaces of matrices induced by an `AddEquiv` between their
coefficients. This is `Matrix.map` as an `AddEquiv`. -/
@[simps apply]
def mapMatrix (f : α ≃+ β) : Matrix m n α ≃+ Matrix m n β :=
{ f.toEquiv.mapMatrix with
toFun := fun M => M.map f
invFun := fun M => M.map f.symm
map_add' := Matrix.map_add f f.map_add }
#align add_equiv.map_matrix AddEquiv.mapMatrix
@[simp]
theorem mapMatrix_refl : (AddEquiv.refl α).mapMatrix = AddEquiv.refl (Matrix m n α) :=
rfl
#align add_equiv.map_matrix_refl AddEquiv.mapMatrix_refl
@[simp]
theorem mapMatrix_symm (f : α ≃+ β) : f.mapMatrix.symm = (f.symm.mapMatrix : Matrix m n β ≃+ _) :=
rfl
#align add_equiv.map_matrix_symm AddEquiv.mapMatrix_symm
@[simp]
theorem mapMatrix_trans (f : α ≃+ β) (g : β ≃+ γ) :
f.mapMatrix.trans g.mapMatrix = ((f.trans g).mapMatrix : Matrix m n α ≃+ _) :=
rfl
#align add_equiv.map_matrix_trans AddEquiv.mapMatrix_trans
end AddEquiv
namespace LinearMap
variable [Semiring R] [AddCommMonoid α] [AddCommMonoid β] [AddCommMonoid γ]
variable [Module R α] [Module R β] [Module R γ]
/-- The `LinearMap` between spaces of matrices induced by a `LinearMap` between their
coefficients. This is `Matrix.map` as a `LinearMap`. -/
@[simps]
def mapMatrix (f : α →ₗ[R] β) : Matrix m n α →ₗ[R] Matrix m n β where
toFun M := M.map f
map_add' := Matrix.map_add f f.map_add
map_smul' r := Matrix.map_smul f r (f.map_smul r)
#align linear_map.map_matrix LinearMap.mapMatrix
@[simp]
theorem mapMatrix_id : LinearMap.id.mapMatrix = (LinearMap.id : Matrix m n α →ₗ[R] _) :=
rfl
#align linear_map.map_matrix_id LinearMap.mapMatrix_id
@[simp]
theorem mapMatrix_comp (f : β →ₗ[R] γ) (g : α →ₗ[R] β) :
f.mapMatrix.comp g.mapMatrix = ((f.comp g).mapMatrix : Matrix m n α →ₗ[R] _) :=
rfl
#align linear_map.map_matrix_comp LinearMap.mapMatrix_comp
end LinearMap
namespace LinearEquiv
variable [Semiring R] [AddCommMonoid α] [AddCommMonoid β] [AddCommMonoid γ]
variable [Module R α] [Module R β] [Module R γ]
/-- The `LinearEquiv` between spaces of matrices induced by a `LinearEquiv` between their
coefficients. This is `Matrix.map` as a `LinearEquiv`. -/
@[simps apply]
def mapMatrix (f : α ≃ₗ[R] β) : Matrix m n α ≃ₗ[R] Matrix m n β :=
{ f.toEquiv.mapMatrix,
f.toLinearMap.mapMatrix with
toFun := fun M => M.map f
invFun := fun M => M.map f.symm }
#align linear_equiv.map_matrix LinearEquiv.mapMatrix
@[simp]
theorem mapMatrix_refl : (LinearEquiv.refl R α).mapMatrix = LinearEquiv.refl R (Matrix m n α) :=
rfl
#align linear_equiv.map_matrix_refl LinearEquiv.mapMatrix_refl
@[simp]
theorem mapMatrix_symm (f : α ≃ₗ[R] β) :
f.mapMatrix.symm = (f.symm.mapMatrix : Matrix m n β ≃ₗ[R] _) :=
rfl
#align linear_equiv.map_matrix_symm LinearEquiv.mapMatrix_symm
@[simp]
theorem mapMatrix_trans (f : α ≃ₗ[R] β) (g : β ≃ₗ[R] γ) :
f.mapMatrix.trans g.mapMatrix = ((f.trans g).mapMatrix : Matrix m n α ≃ₗ[R] _) :=
rfl
#align linear_equiv.map_matrix_trans LinearEquiv.mapMatrix_trans
end LinearEquiv
namespace RingHom
variable [Fintype m] [DecidableEq m]
variable [NonAssocSemiring α] [NonAssocSemiring β] [NonAssocSemiring γ]
/-- The `RingHom` between spaces of square matrices induced by a `RingHom` between their
coefficients. This is `Matrix.map` as a `RingHom`. -/
@[simps]
def mapMatrix (f : α →+* β) : Matrix m m α →+* Matrix m m β :=
{ f.toAddMonoidHom.mapMatrix with
toFun := fun M => M.map f
map_one' := by simp
map_mul' := fun L M => Matrix.map_mul }
#align ring_hom.map_matrix RingHom.mapMatrix
@[simp]
theorem mapMatrix_id : (RingHom.id α).mapMatrix = RingHom.id (Matrix m m α) :=
rfl
#align ring_hom.map_matrix_id RingHom.mapMatrix_id
@[simp]
theorem mapMatrix_comp (f : β →+* γ) (g : α →+* β) :
f.mapMatrix.comp g.mapMatrix = ((f.comp g).mapMatrix : Matrix m m α →+* _) :=
rfl
#align ring_hom.map_matrix_comp RingHom.mapMatrix_comp
end RingHom
namespace RingEquiv
variable [Fintype m] [DecidableEq m]
variable [NonAssocSemiring α] [NonAssocSemiring β] [NonAssocSemiring γ]
/-- The `RingEquiv` between spaces of square matrices induced by a `RingEquiv` between their
coefficients. This is `Matrix.map` as a `RingEquiv`. -/
@[simps apply]
def mapMatrix (f : α ≃+* β) : Matrix m m α ≃+* Matrix m m β :=
{ f.toRingHom.mapMatrix,
f.toAddEquiv.mapMatrix with
toFun := fun M => M.map f
invFun := fun M => M.map f.symm }
#align ring_equiv.map_matrix RingEquiv.mapMatrix
@[simp]
theorem mapMatrix_refl : (RingEquiv.refl α).mapMatrix = RingEquiv.refl (Matrix m m α) :=
rfl
#align ring_equiv.map_matrix_refl RingEquiv.mapMatrix_refl
@[simp]
theorem mapMatrix_symm (f : α ≃+* β) : f.mapMatrix.symm = (f.symm.mapMatrix : Matrix m m β ≃+* _) :=
rfl
#align ring_equiv.map_matrix_symm RingEquiv.mapMatrix_symm
@[simp]
theorem mapMatrix_trans (f : α ≃+* β) (g : β ≃+* γ) :
f.mapMatrix.trans g.mapMatrix = ((f.trans g).mapMatrix : Matrix m m α ≃+* _) :=
rfl
#align ring_equiv.map_matrix_trans RingEquiv.mapMatrix_trans
end RingEquiv
namespace AlgHom
variable [Fintype m] [DecidableEq m]
variable [CommSemiring R] [Semiring α] [Semiring β] [Semiring γ]
variable [Algebra R α] [Algebra R β] [Algebra R γ]
/-- The `AlgHom` between spaces of square matrices induced by an `AlgHom` between their
coefficients. This is `Matrix.map` as an `AlgHom`. -/
@[simps]
def mapMatrix (f : α →ₐ[R] β) : Matrix m m α →ₐ[R] Matrix m m β :=
{ f.toRingHom.mapMatrix with
toFun := fun M => M.map f
commutes' := fun r => Matrix.map_algebraMap r f f.map_zero (f.commutes r) }
#align alg_hom.map_matrix AlgHom.mapMatrix
@[simp]
theorem mapMatrix_id : (AlgHom.id R α).mapMatrix = AlgHom.id R (Matrix m m α) :=
rfl
#align alg_hom.map_matrix_id AlgHom.mapMatrix_id
@[simp]
theorem mapMatrix_comp (f : β →ₐ[R] γ) (g : α →ₐ[R] β) :
f.mapMatrix.comp g.mapMatrix = ((f.comp g).mapMatrix : Matrix m m α →ₐ[R] _) :=
rfl
#align alg_hom.map_matrix_comp AlgHom.mapMatrix_comp
end AlgHom
namespace AlgEquiv
variable [Fintype m] [DecidableEq m]
variable [CommSemiring R] [Semiring α] [Semiring β] [Semiring γ]
variable [Algebra R α] [Algebra R β] [Algebra R γ]
/-- The `AlgEquiv` between spaces of square matrices induced by an `AlgEquiv` between their
coefficients. This is `Matrix.map` as an `AlgEquiv`. -/
@[simps apply]
def mapMatrix (f : α ≃ₐ[R] β) : Matrix m m α ≃ₐ[R] Matrix m m β :=
{ f.toAlgHom.mapMatrix,
f.toRingEquiv.mapMatrix with
toFun := fun M => M.map f
invFun := fun M => M.map f.symm }
#align alg_equiv.map_matrix AlgEquiv.mapMatrix
@[simp]
theorem mapMatrix_refl : AlgEquiv.refl.mapMatrix = (AlgEquiv.refl : Matrix m m α ≃ₐ[R] _) :=
rfl
#align alg_equiv.map_matrix_refl AlgEquiv.mapMatrix_refl
@[simp]
theorem mapMatrix_symm (f : α ≃ₐ[R] β) :
f.mapMatrix.symm = (f.symm.mapMatrix : Matrix m m β ≃ₐ[R] _) :=
rfl
#align alg_equiv.map_matrix_symm AlgEquiv.mapMatrix_symm
@[simp]
theorem mapMatrix_trans (f : α ≃ₐ[R] β) (g : β ≃ₐ[R] γ) :
f.mapMatrix.trans g.mapMatrix = ((f.trans g).mapMatrix : Matrix m m α ≃ₐ[R] _) :=
rfl
#align alg_equiv.map_matrix_trans AlgEquiv.mapMatrix_trans
end AlgEquiv
open Matrix
namespace Matrix
/-- For two vectors `w` and `v`, `vecMulVec w v i j` is defined to be `w i * v j`.
Put another way, `vecMulVec w v` is exactly `col w * row v`. -/
def vecMulVec [Mul α] (w : m → α) (v : n → α) : Matrix m n α :=
of fun x y => w x * v y
#align matrix.vec_mul_vec Matrix.vecMulVec
-- TODO: set as an equation lemma for `vecMulVec`, see mathlib4#3024
theorem vecMulVec_apply [Mul α] (w : m → α) (v : n → α) (i j) : vecMulVec w v i j = w i * v j :=
rfl
#align matrix.vec_mul_vec_apply Matrix.vecMulVec_apply
section NonUnitalNonAssocSemiring
variable [NonUnitalNonAssocSemiring α]
/--
`M *ᵥ v` (notation for `mulVec M v`) is the matrix-vector product of matrix `M` and vector `v`,
where `v` is seen as a column vector.
Put another way, `M *ᵥ v` is the vector whose entries are those of `M * col v` (see `col_mulVec`).
The notation has precedence 73, which comes immediately before ` ⬝ᵥ ` for `Matrix.dotProduct`,
so that `A *ᵥ v ⬝ᵥ B *ᵥ w` is parsed as `(A *ᵥ v) ⬝ᵥ (B *ᵥ w)`.
-/
def mulVec [Fintype n] (M : Matrix m n α) (v : n → α) : m → α
| i => (fun j => M i j) ⬝ᵥ v
#align matrix.mul_vec Matrix.mulVec
@[inherit_doc]
scoped infixr:73 " *ᵥ " => Matrix.mulVec
/--
`v ᵥ* M` (notation for `vecMul v M`) is the vector-matrix product of vector `v` and matrix `M`,
where `v` is seen as a row vector.
Put another way, `v ᵥ* M` is the vector whose entries are those of `row v * M` (see `row_vecMul`).
The notation has precedence 73, which comes immediately before ` ⬝ᵥ ` for `Matrix.dotProduct`,
so that `v ᵥ* A ⬝ᵥ w ᵥ* B` is parsed as `(v ᵥ* A) ⬝ᵥ (w ᵥ* B)`.
-/
def vecMul [Fintype m] (v : m → α) (M : Matrix m n α) : n → α
| j => v ⬝ᵥ fun i => M i j
#align matrix.vec_mul Matrix.vecMul
@[inherit_doc]
scoped infixl:73 " ᵥ* " => Matrix.vecMul
/-- Left multiplication by a matrix, as an `AddMonoidHom` from vectors to vectors. -/
@[simps]
def mulVec.addMonoidHomLeft [Fintype n] (v : n → α) : Matrix m n α →+ m → α where
toFun M := M *ᵥ v
map_zero' := by
ext
simp [mulVec]
map_add' x y := by
ext m
apply add_dotProduct
#align matrix.mul_vec.add_monoid_hom_left Matrix.mulVec.addMonoidHomLeft
/-- The `i`th row of the multiplication is the same as the `vecMul` with the `i`th row of `A`. -/
theorem mul_apply_eq_vecMul [Fintype n] (A : Matrix m n α) (B : Matrix n o α) (i : m) :
(A * B) i = A i ᵥ* B :=
rfl
theorem mulVec_diagonal [Fintype m] [DecidableEq m] (v w : m → α) (x : m) :
(diagonal v *ᵥ w) x = v x * w x :=
diagonal_dotProduct v w x
#align matrix.mul_vec_diagonal Matrix.mulVec_diagonal
theorem vecMul_diagonal [Fintype m] [DecidableEq m] (v w : m → α) (x : m) :
(v ᵥ* diagonal w) x = v x * w x :=
dotProduct_diagonal' v w x
#align matrix.vec_mul_diagonal Matrix.vecMul_diagonal
/-- Associate the dot product of `mulVec` to the left. -/
theorem dotProduct_mulVec [Fintype n] [Fintype m] [NonUnitalSemiring R] (v : m → R)
(A : Matrix m n R) (w : n → R) : v ⬝ᵥ A *ᵥ w = v ᵥ* A ⬝ᵥ w := by
simp only [dotProduct, vecMul, mulVec, Finset.mul_sum, Finset.sum_mul, mul_assoc]
exact Finset.sum_comm
#align matrix.dot_product_mul_vec Matrix.dotProduct_mulVec
@[simp]
theorem mulVec_zero [Fintype n] (A : Matrix m n α) : A *ᵥ 0 = 0 := by
ext
simp [mulVec]
#align matrix.mul_vec_zero Matrix.mulVec_zero
@[simp]
theorem zero_vecMul [Fintype m] (A : Matrix m n α) : 0 ᵥ* A = 0 := by
ext
simp [vecMul]
#align matrix.zero_vec_mul Matrix.zero_vecMul
@[simp]
theorem zero_mulVec [Fintype n] (v : n → α) : (0 : Matrix m n α) *ᵥ v = 0 := by
ext
simp [mulVec]
#align matrix.zero_mul_vec Matrix.zero_mulVec
@[simp]
theorem vecMul_zero [Fintype m] (v : m → α) : v ᵥ* (0 : Matrix m n α) = 0 := by
ext
simp [vecMul]
#align matrix.vec_mul_zero Matrix.vecMul_zero
theorem smul_mulVec_assoc [Fintype n] [Monoid R] [DistribMulAction R α] [IsScalarTower R α α]
(a : R) (A : Matrix m n α) (b : n → α) : (a • A) *ᵥ b = a • A *ᵥ b := by
ext
apply smul_dotProduct
#align matrix.smul_mul_vec_assoc Matrix.smul_mulVec_assoc
theorem mulVec_add [Fintype n] (A : Matrix m n α) (x y : n → α) :
A *ᵥ (x + y) = A *ᵥ x + A *ᵥ y := by
ext
apply dotProduct_add
#align matrix.mul_vec_add Matrix.mulVec_add
theorem add_mulVec [Fintype n] (A B : Matrix m n α) (x : n → α) :
(A + B) *ᵥ x = A *ᵥ x + B *ᵥ x := by
ext
apply add_dotProduct
#align matrix.add_mul_vec Matrix.add_mulVec
theorem vecMul_add [Fintype m] (A B : Matrix m n α) (x : m → α) :
x ᵥ* (A + B) = x ᵥ* A + x ᵥ* B := by
ext
apply dotProduct_add
#align matrix.vec_mul_add Matrix.vecMul_add
theorem add_vecMul [Fintype m] (A : Matrix m n α) (x y : m → α) :
(x + y) ᵥ* A = x ᵥ* A + y ᵥ* A := by
ext
apply add_dotProduct
#align matrix.add_vec_mul Matrix.add_vecMul
theorem vecMul_smul [Fintype n] [Monoid R] [NonUnitalNonAssocSemiring S] [DistribMulAction R S]
[IsScalarTower R S S] (M : Matrix n m S) (b : R) (v : n → S) :
(b • v) ᵥ* M = b • v ᵥ* M := by
ext i
simp only [vecMul, dotProduct, Finset.smul_sum, Pi.smul_apply, smul_mul_assoc]
#align matrix.vec_mul_smul Matrix.vecMul_smul
theorem mulVec_smul [Fintype n] [Monoid R] [NonUnitalNonAssocSemiring S] [DistribMulAction R S]
[SMulCommClass R S S] (M : Matrix m n S) (b : R) (v : n → S) :
M *ᵥ (b • v) = b • M *ᵥ v := by
ext i
simp only [mulVec, dotProduct, Finset.smul_sum, Pi.smul_apply, mul_smul_comm]
#align matrix.mul_vec_smul Matrix.mulVec_smul
@[simp]
theorem mulVec_single [Fintype n] [DecidableEq n] [NonUnitalNonAssocSemiring R] (M : Matrix m n R)
(j : n) (x : R) : M *ᵥ Pi.single j x = fun i => M i j * x :=
funext fun _ => dotProduct_single _ _ _
#align matrix.mul_vec_single Matrix.mulVec_single
@[simp]
theorem single_vecMul [Fintype m] [DecidableEq m] [NonUnitalNonAssocSemiring R] (M : Matrix m n R)
(i : m) (x : R) : Pi.single i x ᵥ* M = fun j => x * M i j :=
funext fun _ => single_dotProduct _ _ _
#align matrix.single_vec_mul Matrix.single_vecMul
-- @[simp] -- Porting note: not in simpNF
theorem diagonal_mulVec_single [Fintype n] [DecidableEq n] [NonUnitalNonAssocSemiring R] (v : n → R)
(j : n) (x : R) : diagonal v *ᵥ Pi.single j x = Pi.single j (v j * x) := by
ext i
rw [mulVec_diagonal]
exact Pi.apply_single (fun i x => v i * x) (fun i => mul_zero _) j x i
#align matrix.diagonal_mul_vec_single Matrix.diagonal_mulVec_single
-- @[simp] -- Porting note: not in simpNF
theorem single_vecMul_diagonal [Fintype n] [DecidableEq n] [NonUnitalNonAssocSemiring R] (v : n → R)
(j : n) (x : R) : (Pi.single j x) ᵥ* (diagonal v) = Pi.single j (x * v j) := by
ext i
rw [vecMul_diagonal]
exact Pi.apply_single (fun i x => x * v i) (fun i => zero_mul _) j x i
#align matrix.single_vec_mul_diagonal Matrix.single_vecMul_diagonal
end NonUnitalNonAssocSemiring
section NonUnitalSemiring
variable [NonUnitalSemiring α]
@[simp]
theorem vecMul_vecMul [Fintype n] [Fintype m] (v : m → α) (M : Matrix m n α) (N : Matrix n o α) :
v ᵥ* M ᵥ* N = v ᵥ* (M * N) := by
ext
apply dotProduct_assoc
#align matrix.vec_mul_vec_mul Matrix.vecMul_vecMul
@[simp]
theorem mulVec_mulVec [Fintype n] [Fintype o] (v : o → α) (M : Matrix m n α) (N : Matrix n o α) :
M *ᵥ N *ᵥ v = (M * N) *ᵥ v := by
ext
symm
apply dotProduct_assoc
#align matrix.mul_vec_mul_vec Matrix.mulVec_mulVec
theorem star_mulVec [Fintype n] [StarRing α] (M : Matrix m n α) (v : n → α) :
star (M *ᵥ v) = star v ᵥ* Mᴴ :=
funext fun _ => (star_dotProduct_star _ _).symm
#align matrix.star_mul_vec Matrix.star_mulVec
theorem star_vecMul [Fintype m] [StarRing α] (M : Matrix m n α) (v : m → α) :
star (v ᵥ* M) = Mᴴ *ᵥ star v :=
funext fun _ => (star_dotProduct_star _ _).symm
#align matrix.star_vec_mul Matrix.star_vecMul
theorem mulVec_conjTranspose [Fintype m] [StarRing α] (A : Matrix m n α) (x : m → α) :
Aᴴ *ᵥ x = star (star x ᵥ* A) :=
funext fun _ => star_dotProduct _ _
#align matrix.mul_vec_conj_transpose Matrix.mulVec_conjTranspose
theorem vecMul_conjTranspose [Fintype n] [StarRing α] (A : Matrix m n α) (x : n → α) :
x ᵥ* Aᴴ = star (A *ᵥ star x) :=
funext fun _ => dotProduct_star _ _
#align matrix.vec_mul_conj_transpose Matrix.vecMul_conjTranspose
theorem mul_mul_apply [Fintype n] (A B C : Matrix n n α) (i j : n) :
(A * B * C) i j = A i ⬝ᵥ B *ᵥ (Cᵀ j) := by
rw [Matrix.mul_assoc]
simp only [mul_apply, dotProduct, mulVec]
rfl
#align matrix.mul_mul_apply Matrix.mul_mul_apply
end NonUnitalSemiring
section NonAssocSemiring
variable [NonAssocSemiring α]
theorem mulVec_one [Fintype n] (A : Matrix m n α) : A *ᵥ 1 = fun i => ∑ j, A i j := by
ext; simp [mulVec, dotProduct]
#align matrix.mul_vec_one Matrix.mulVec_one
theorem vec_one_mul [Fintype m] (A : Matrix m n α) : 1 ᵥ* A = fun j => ∑ i, A i j := by
ext; simp [vecMul, dotProduct]
#align matrix.vec_one_mul Matrix.vec_one_mul
variable [Fintype m] [Fintype n] [DecidableEq m]
@[simp]
theorem one_mulVec (v : m → α) : 1 *ᵥ v = v := by
ext
rw [← diagonal_one, mulVec_diagonal, one_mul]
#align matrix.one_mul_vec Matrix.one_mulVec
@[simp]
theorem vecMul_one (v : m → α) : v ᵥ* 1 = v := by
ext
rw [← diagonal_one, vecMul_diagonal, mul_one]
#align matrix.vec_mul_one Matrix.vecMul_one
@[simp]
theorem diagonal_const_mulVec (x : α) (v : m → α) :
(diagonal fun _ => x) *ᵥ v = x • v := by
ext; simp [mulVec_diagonal]
@[simp]
theorem vecMul_diagonal_const (x : α) (v : m → α) :
v ᵥ* (diagonal fun _ => x) = MulOpposite.op x • v := by
ext; simp [vecMul_diagonal]
@[simp]
theorem natCast_mulVec (x : ℕ) (v : m → α) : x *ᵥ v = (x : α) • v :=
diagonal_const_mulVec _ _
@[simp]
theorem vecMul_natCast (x : ℕ) (v : m → α) : v ᵥ* x = MulOpposite.op (x : α) • v :=
vecMul_diagonal_const _ _
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem ofNat_mulVec (x : ℕ) [x.AtLeastTwo] (v : m → α) :
OfNat.ofNat (no_index x) *ᵥ v = (OfNat.ofNat x : α) • v :=
natCast_mulVec _ _
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem vecMul_ofNat (x : ℕ) [x.AtLeastTwo] (v : m → α) :
v ᵥ* OfNat.ofNat (no_index x) = MulOpposite.op (OfNat.ofNat x : α) • v :=
vecMul_natCast _ _
end NonAssocSemiring
section NonUnitalNonAssocRing
variable [NonUnitalNonAssocRing α]
theorem neg_vecMul [Fintype m] (v : m → α) (A : Matrix m n α) : (-v) ᵥ* A = - (v ᵥ* A) := by
ext
apply neg_dotProduct
#align matrix.neg_vec_mul Matrix.neg_vecMul
theorem vecMul_neg [Fintype m] (v : m → α) (A : Matrix m n α) : v ᵥ* (-A) = - (v ᵥ* A) := by
ext
apply dotProduct_neg
#align matrix.vec_mul_neg Matrix.vecMul_neg
lemma neg_vecMul_neg [Fintype m] (v : m → α) (A : Matrix m n α) : (-v) ᵥ* (-A) = v ᵥ* A := by
rw [vecMul_neg, neg_vecMul, neg_neg]
theorem neg_mulVec [Fintype n] (v : n → α) (A : Matrix m n α) : (-A) *ᵥ v = - (A *ᵥ v) := by
ext
apply neg_dotProduct
#align matrix.neg_mul_vec Matrix.neg_mulVec
theorem mulVec_neg [Fintype n] (v : n → α) (A : Matrix m n α) : A *ᵥ (-v) = - (A *ᵥ v) := by
ext
apply dotProduct_neg
#align matrix.mul_vec_neg Matrix.mulVec_neg
lemma neg_mulVec_neg [Fintype n] (v : n → α) (A : Matrix m n α) : (-A) *ᵥ (-v) = A *ᵥ v := by
rw [mulVec_neg, neg_mulVec, neg_neg]
theorem mulVec_sub [Fintype n] (A : Matrix m n α) (x y : n → α) :
A *ᵥ (x - y) = A *ᵥ x - A *ᵥ y := by
ext
apply dotProduct_sub
theorem sub_mulVec [Fintype n] (A B : Matrix m n α) (x : n → α) :
(A - B) *ᵥ x = A *ᵥ x - B *ᵥ x := by simp [sub_eq_add_neg, add_mulVec, neg_mulVec]
#align matrix.sub_mul_vec Matrix.sub_mulVec
theorem vecMul_sub [Fintype m] (A B : Matrix m n α) (x : m → α) :
x ᵥ* (A - B) = x ᵥ* A - x ᵥ* B := by simp [sub_eq_add_neg, vecMul_add, vecMul_neg]
#align matrix.vec_mul_sub Matrix.vecMul_sub
theorem sub_vecMul [Fintype m] (A : Matrix m n α) (x y : m → α) :
(x - y) ᵥ* A = x ᵥ* A - y ᵥ* A := by
ext
apply sub_dotProduct
end NonUnitalNonAssocRing
section NonUnitalCommSemiring
variable [NonUnitalCommSemiring α]
theorem mulVec_transpose [Fintype m] (A : Matrix m n α) (x : m → α) : Aᵀ *ᵥ x = x ᵥ* A := by
ext
apply dotProduct_comm
#align matrix.mul_vec_transpose Matrix.mulVec_transpose
theorem vecMul_transpose [Fintype n] (A : Matrix m n α) (x : n → α) : x ᵥ* Aᵀ = A *ᵥ x := by
ext
apply dotProduct_comm
#align matrix.vec_mul_transpose Matrix.vecMul_transpose
theorem mulVec_vecMul [Fintype n] [Fintype o] (A : Matrix m n α) (B : Matrix o n α) (x : o → α) :
A *ᵥ (x ᵥ* B) = (A * Bᵀ) *ᵥ x := by rw [← mulVec_mulVec, mulVec_transpose]
#align matrix.mul_vec_vec_mul Matrix.mulVec_vecMul
theorem vecMul_mulVec [Fintype m] [Fintype n] (A : Matrix m n α) (B : Matrix m o α) (x : n → α) :
(A *ᵥ x) ᵥ* B = x ᵥ* (Aᵀ * B) := by rw [← vecMul_vecMul, vecMul_transpose]
#align matrix.vec_mul_mul_vec Matrix.vecMul_mulVec
end NonUnitalCommSemiring
section CommSemiring
variable [CommSemiring α]
theorem mulVec_smul_assoc [Fintype n] (A : Matrix m n α) (b : n → α) (a : α) :
A *ᵥ (a • b) = a • A *ᵥ b := by
ext
apply dotProduct_smul
#align matrix.mul_vec_smul_assoc Matrix.mulVec_smul_assoc
end CommSemiring
section NonAssocRing
variable [NonAssocRing α]
variable [Fintype m] [DecidableEq m]
@[simp]
theorem intCast_mulVec (x : ℤ) (v : m → α) : x *ᵥ v = (x : α) • v :=
diagonal_const_mulVec _ _
@[simp]
theorem vecMul_intCast (x : ℤ) (v : m → α) : v ᵥ* x = MulOpposite.op (x : α) • v :=
vecMul_diagonal_const _ _
end NonAssocRing
section Transpose
open Matrix
@[simp]
theorem transpose_transpose (M : Matrix m n α) : Mᵀᵀ = M := by
ext
rfl
#align matrix.transpose_transpose Matrix.transpose_transpose
theorem transpose_injective : Function.Injective (transpose : Matrix m n α → Matrix n m α) :=
fun _ _ h => ext fun i j => ext_iff.2 h j i
@[simp] theorem transpose_inj {A B : Matrix m n α} : Aᵀ = Bᵀ ↔ A = B := transpose_injective.eq_iff
@[simp]
theorem transpose_zero [Zero α] : (0 : Matrix m n α)ᵀ = 0 := by
ext
rfl
#align matrix.transpose_zero Matrix.transpose_zero
@[simp]
theorem transpose_eq_zero [Zero α] {M : Matrix m n α} : Mᵀ = 0 ↔ M = 0 := transpose_inj
@[simp]
| Mathlib/Data/Matrix/Basic.lean | 2,061 | 2,066 | theorem transpose_one [DecidableEq n] [Zero α] [One α] : (1 : Matrix n n α)ᵀ = 1 := by |
ext i j
rw [transpose_apply, ← diagonal_one]
by_cases h : i = j
· simp only [h, diagonal_apply_eq]
· simp only [diagonal_apply_ne _ h, diagonal_apply_ne' _ h]
|
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Floris van Doorn
-/
import Mathlib.Algebra.Group.Equiv.Basic
import Mathlib.Algebra.Group.Units.Hom
import Mathlib.Algebra.Opposites
import Mathlib.Algebra.Order.GroupWithZero.Synonym
import Mathlib.Algebra.Order.Ring.Nat
import Mathlib.Data.Set.Lattice
import Mathlib.Tactic.Common
#align_import data.set.pointwise.basic from "leanprover-community/mathlib"@"5e526d18cea33550268dcbbddcb822d5cde40654"
/-!
# Pointwise operations of sets
This file defines pointwise algebraic operations on sets.
## Main declarations
For sets `s` and `t` and scalar `a`:
* `s * t`: Multiplication, set of all `x * y` where `x ∈ s` and `y ∈ t`.
* `s + t`: Addition, set of all `x + y` where `x ∈ s` and `y ∈ t`.
* `s⁻¹`: Inversion, set of all `x⁻¹` where `x ∈ s`.
* `-s`: Negation, set of all `-x` where `x ∈ s`.
* `s / t`: Division, set of all `x / y` where `x ∈ s` and `y ∈ t`.
* `s - t`: Subtraction, set of all `x - y` where `x ∈ s` and `y ∈ t`.
For `α` a semigroup/monoid, `Set α` is a semigroup/monoid.
As an unfortunate side effect, this means that `n • s`, where `n : ℕ`, is ambiguous between
pointwise scaling and repeated pointwise addition; the former has `(2 : ℕ) • {1, 2} = {2, 4}`, while
the latter has `(2 : ℕ) • {1, 2} = {2, 3, 4}`. See note [pointwise nat action].
Appropriate definitions and results are also transported to the additive theory via `to_additive`.
## Implementation notes
* The following expressions are considered in simp-normal form in a group:
`(fun h ↦ h * g) ⁻¹' s`, `(fun h ↦ g * h) ⁻¹' s`, `(fun h ↦ h * g⁻¹) ⁻¹' s`,
`(fun h ↦ g⁻¹ * h) ⁻¹' s`, `s * t`, `s⁻¹`, `(1 : Set _)` (and similarly for additive variants).
Expressions equal to one of these will be simplified.
* We put all instances in the locale `Pointwise`, so that these instances are not available by
default. Note that we do not mark them as reducible (as argued by note [reducible non-instances])
since we expect the locale to be open whenever the instances are actually used (and making the
instances reducible changes the behavior of `simp`.
## Tags
set multiplication, set addition, pointwise addition, pointwise multiplication,
pointwise subtraction
-/
library_note "pointwise nat action"/--
Pointwise monoids (`Set`, `Finset`, `Filter`) have derived pointwise actions of the form
`SMul α β → SMul α (Set β)`. When `α` is `ℕ` or `ℤ`, this action conflicts with the
nat or int action coming from `Set β` being a `Monoid` or `DivInvMonoid`. For example,
`2 • {a, b}` can both be `{2 • a, 2 • b}` (pointwise action, pointwise repeated addition,
`Set.smulSet`) and `{a + a, a + b, b + a, b + b}` (nat or int action, repeated pointwise
addition, `Set.NSMul`).
Because the pointwise action can easily be spelled out in such cases, we give higher priority to the
nat and int actions.
-/
open Function
variable {F α β γ : Type*}
namespace Set
/-! ### `0`/`1` as sets -/
section One
variable [One α] {s : Set α} {a : α}
/-- The set `1 : Set α` is defined as `{1}` in locale `Pointwise`. -/
@[to_additive "The set `0 : Set α` is defined as `{0}` in locale `Pointwise`."]
protected noncomputable def one : One (Set α) :=
⟨{1}⟩
#align set.has_one Set.one
#align set.has_zero Set.zero
scoped[Pointwise] attribute [instance] Set.one Set.zero
open Pointwise
@[to_additive]
theorem singleton_one : ({1} : Set α) = 1 :=
rfl
#align set.singleton_one Set.singleton_one
#align set.singleton_zero Set.singleton_zero
@[to_additive (attr := simp)]
theorem mem_one : a ∈ (1 : Set α) ↔ a = 1 :=
Iff.rfl
#align set.mem_one Set.mem_one
#align set.mem_zero Set.mem_zero
@[to_additive]
theorem one_mem_one : (1 : α) ∈ (1 : Set α) :=
Eq.refl _
#align set.one_mem_one Set.one_mem_one
#align set.zero_mem_zero Set.zero_mem_zero
@[to_additive (attr := simp)]
theorem one_subset : 1 ⊆ s ↔ (1 : α) ∈ s :=
singleton_subset_iff
#align set.one_subset Set.one_subset
#align set.zero_subset Set.zero_subset
@[to_additive]
theorem one_nonempty : (1 : Set α).Nonempty :=
⟨1, rfl⟩
#align set.one_nonempty Set.one_nonempty
#align set.zero_nonempty Set.zero_nonempty
@[to_additive (attr := simp)]
theorem image_one {f : α → β} : f '' 1 = {f 1} :=
image_singleton
#align set.image_one Set.image_one
#align set.image_zero Set.image_zero
@[to_additive]
theorem subset_one_iff_eq : s ⊆ 1 ↔ s = ∅ ∨ s = 1 :=
subset_singleton_iff_eq
#align set.subset_one_iff_eq Set.subset_one_iff_eq
#align set.subset_zero_iff_eq Set.subset_zero_iff_eq
@[to_additive]
theorem Nonempty.subset_one_iff (h : s.Nonempty) : s ⊆ 1 ↔ s = 1 :=
h.subset_singleton_iff
#align set.nonempty.subset_one_iff Set.Nonempty.subset_one_iff
#align set.nonempty.subset_zero_iff Set.Nonempty.subset_zero_iff
/-- The singleton operation as a `OneHom`. -/
@[to_additive "The singleton operation as a `ZeroHom`."]
noncomputable def singletonOneHom : OneHom α (Set α) where
toFun := singleton; map_one' := singleton_one
#align set.singleton_one_hom Set.singletonOneHom
#align set.singleton_zero_hom Set.singletonZeroHom
@[to_additive (attr := simp)]
theorem coe_singletonOneHom : (singletonOneHom : α → Set α) = singleton :=
rfl
#align set.coe_singleton_one_hom Set.coe_singletonOneHom
#align set.coe_singleton_zero_hom Set.coe_singletonZeroHom
end One
/-! ### Set negation/inversion -/
section Inv
/-- The pointwise inversion of set `s⁻¹` is defined as `{x | x⁻¹ ∈ s}` in locale `Pointwise`. It is
equal to `{x⁻¹ | x ∈ s}`, see `Set.image_inv`. -/
@[to_additive
"The pointwise negation of set `-s` is defined as `{x | -x ∈ s}` in locale `Pointwise`.
It is equal to `{-x | x ∈ s}`, see `Set.image_neg`."]
protected def inv [Inv α] : Inv (Set α) :=
⟨preimage Inv.inv⟩
#align set.has_inv Set.inv
#align set.has_neg Set.neg
scoped[Pointwise] attribute [instance] Set.inv Set.neg
open Pointwise
section Inv
variable {ι : Sort*} [Inv α] {s t : Set α} {a : α}
@[to_additive (attr := simp)]
theorem mem_inv : a ∈ s⁻¹ ↔ a⁻¹ ∈ s :=
Iff.rfl
#align set.mem_inv Set.mem_inv
#align set.mem_neg Set.mem_neg
@[to_additive (attr := simp)]
theorem inv_preimage : Inv.inv ⁻¹' s = s⁻¹ :=
rfl
#align set.inv_preimage Set.inv_preimage
#align set.neg_preimage Set.neg_preimage
@[to_additive (attr := simp)]
theorem inv_empty : (∅ : Set α)⁻¹ = ∅ :=
rfl
#align set.inv_empty Set.inv_empty
#align set.neg_empty Set.neg_empty
@[to_additive (attr := simp)]
theorem inv_univ : (univ : Set α)⁻¹ = univ :=
rfl
#align set.inv_univ Set.inv_univ
#align set.neg_univ Set.neg_univ
@[to_additive (attr := simp)]
theorem inter_inv : (s ∩ t)⁻¹ = s⁻¹ ∩ t⁻¹ :=
preimage_inter
#align set.inter_inv Set.inter_inv
#align set.inter_neg Set.inter_neg
@[to_additive (attr := simp)]
theorem union_inv : (s ∪ t)⁻¹ = s⁻¹ ∪ t⁻¹ :=
preimage_union
#align set.union_inv Set.union_inv
#align set.union_neg Set.union_neg
@[to_additive (attr := simp)]
theorem iInter_inv (s : ι → Set α) : (⋂ i, s i)⁻¹ = ⋂ i, (s i)⁻¹ :=
preimage_iInter
#align set.Inter_inv Set.iInter_inv
#align set.Inter_neg Set.iInter_neg
@[to_additive (attr := simp)]
theorem iUnion_inv (s : ι → Set α) : (⋃ i, s i)⁻¹ = ⋃ i, (s i)⁻¹ :=
preimage_iUnion
#align set.Union_inv Set.iUnion_inv
#align set.Union_neg Set.iUnion_neg
@[to_additive (attr := simp)]
theorem compl_inv : sᶜ⁻¹ = s⁻¹ᶜ :=
preimage_compl
#align set.compl_inv Set.compl_inv
#align set.compl_neg Set.compl_neg
end Inv
section InvolutiveInv
variable [InvolutiveInv α] {s t : Set α} {a : α}
@[to_additive]
theorem inv_mem_inv : a⁻¹ ∈ s⁻¹ ↔ a ∈ s := by simp only [mem_inv, inv_inv]
#align set.inv_mem_inv Set.inv_mem_inv
#align set.neg_mem_neg Set.neg_mem_neg
@[to_additive (attr := simp)]
theorem nonempty_inv : s⁻¹.Nonempty ↔ s.Nonempty :=
inv_involutive.surjective.nonempty_preimage
#align set.nonempty_inv Set.nonempty_inv
#align set.nonempty_neg Set.nonempty_neg
@[to_additive]
theorem Nonempty.inv (h : s.Nonempty) : s⁻¹.Nonempty :=
nonempty_inv.2 h
#align set.nonempty.inv Set.Nonempty.inv
#align set.nonempty.neg Set.Nonempty.neg
@[to_additive (attr := simp)]
theorem image_inv : Inv.inv '' s = s⁻¹ :=
congr_fun (image_eq_preimage_of_inverse inv_involutive.leftInverse inv_involutive.rightInverse) _
#align set.image_inv Set.image_inv
#align set.image_neg Set.image_neg
@[to_additive (attr := simp)]
theorem inv_eq_empty : s⁻¹ = ∅ ↔ s = ∅ := by
rw [← image_inv, image_eq_empty]
@[to_additive (attr := simp)]
noncomputable instance involutiveInv : InvolutiveInv (Set α) where
inv := Inv.inv
inv_inv s := by simp only [← inv_preimage, preimage_preimage, inv_inv, preimage_id']
@[to_additive (attr := simp)]
theorem inv_subset_inv : s⁻¹ ⊆ t⁻¹ ↔ s ⊆ t :=
(Equiv.inv α).surjective.preimage_subset_preimage_iff
#align set.inv_subset_inv Set.inv_subset_inv
#align set.neg_subset_neg Set.neg_subset_neg
@[to_additive]
theorem inv_subset : s⁻¹ ⊆ t ↔ s ⊆ t⁻¹ := by rw [← inv_subset_inv, inv_inv]
#align set.inv_subset Set.inv_subset
#align set.neg_subset Set.neg_subset
@[to_additive (attr := simp)]
| Mathlib/Data/Set/Pointwise/Basic.lean | 283 | 283 | theorem inv_singleton (a : α) : ({a} : Set α)⁻¹ = {a⁻¹} := by | rw [← image_inv, image_singleton]
|
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Algebra.BigOperators.Option
import Mathlib.Analysis.BoxIntegral.Box.Basic
import Mathlib.Data.Set.Pairwise.Lattice
#align_import analysis.box_integral.partition.basic from "leanprover-community/mathlib"@"84dc0bd6619acaea625086d6f53cb35cdd554219"
/-!
# Partitions of rectangular boxes in `ℝⁿ`
In this file we define (pre)partitions of rectangular boxes in `ℝⁿ`. A partition of a box `I` in
`ℝⁿ` (see `BoxIntegral.Prepartition` and `BoxIntegral.Prepartition.IsPartition`) is a finite set
of pairwise disjoint boxes such that their union is exactly `I`. We use `boxes : Finset (Box ι)` to
store the set of boxes.
Many lemmas about box integrals deal with pairwise disjoint collections of subboxes, so we define a
structure `BoxIntegral.Prepartition (I : BoxIntegral.Box ι)` that stores a collection of boxes
such that
* each box `J ∈ boxes` is a subbox of `I`;
* the boxes are pairwise disjoint as sets in `ℝⁿ`.
Then we define a predicate `BoxIntegral.Prepartition.IsPartition`; `π.IsPartition` means that the
boxes of `π` actually cover the whole `I`. We also define some operations on prepartitions:
* `BoxIntegral.Prepartition.biUnion`: split each box of a partition into smaller boxes;
* `BoxIntegral.Prepartition.restrict`: restrict a partition to a smaller box.
We also define a `SemilatticeInf` structure on `BoxIntegral.Prepartition I` for all
`I : BoxIntegral.Box ι`.
## Tags
rectangular box, partition
-/
open Set Finset Function
open scoped Classical
open NNReal
noncomputable section
namespace BoxIntegral
variable {ι : Type*}
/-- A prepartition of `I : BoxIntegral.Box ι` is a finite set of pairwise disjoint subboxes of
`I`. -/
structure Prepartition (I : Box ι) where
/-- The underlying set of boxes -/
boxes : Finset (Box ι)
/-- Each box is a sub-box of `I` -/
le_of_mem' : ∀ J ∈ boxes, J ≤ I
/-- The boxes in a prepartition are pairwise disjoint. -/
pairwiseDisjoint : Set.Pairwise (↑boxes) (Disjoint on ((↑) : Box ι → Set (ι → ℝ)))
#align box_integral.prepartition BoxIntegral.Prepartition
namespace Prepartition
variable {I J J₁ J₂ : Box ι} (π : Prepartition I) {π₁ π₂ : Prepartition I} {x : ι → ℝ}
instance : Membership (Box ι) (Prepartition I) :=
⟨fun J π => J ∈ π.boxes⟩
@[simp]
theorem mem_boxes : J ∈ π.boxes ↔ J ∈ π := Iff.rfl
#align box_integral.prepartition.mem_boxes BoxIntegral.Prepartition.mem_boxes
@[simp]
theorem mem_mk {s h₁ h₂} : J ∈ (mk s h₁ h₂ : Prepartition I) ↔ J ∈ s := Iff.rfl
#align box_integral.prepartition.mem_mk BoxIntegral.Prepartition.mem_mk
theorem disjoint_coe_of_mem (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (h : J₁ ≠ J₂) :
Disjoint (J₁ : Set (ι → ℝ)) J₂ :=
π.pairwiseDisjoint h₁ h₂ h
#align box_integral.prepartition.disjoint_coe_of_mem BoxIntegral.Prepartition.disjoint_coe_of_mem
theorem eq_of_mem_of_mem (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (hx₁ : x ∈ J₁) (hx₂ : x ∈ J₂) : J₁ = J₂ :=
by_contra fun H => (π.disjoint_coe_of_mem h₁ h₂ H).le_bot ⟨hx₁, hx₂⟩
#align box_integral.prepartition.eq_of_mem_of_mem BoxIntegral.Prepartition.eq_of_mem_of_mem
theorem eq_of_le_of_le (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (hle₁ : J ≤ J₁) (hle₂ : J ≤ J₂) : J₁ = J₂ :=
π.eq_of_mem_of_mem h₁ h₂ (hle₁ J.upper_mem) (hle₂ J.upper_mem)
#align box_integral.prepartition.eq_of_le_of_le BoxIntegral.Prepartition.eq_of_le_of_le
theorem eq_of_le (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (hle : J₁ ≤ J₂) : J₁ = J₂ :=
π.eq_of_le_of_le h₁ h₂ le_rfl hle
#align box_integral.prepartition.eq_of_le BoxIntegral.Prepartition.eq_of_le
theorem le_of_mem (hJ : J ∈ π) : J ≤ I :=
π.le_of_mem' J hJ
#align box_integral.prepartition.le_of_mem BoxIntegral.Prepartition.le_of_mem
theorem lower_le_lower (hJ : J ∈ π) : I.lower ≤ J.lower :=
Box.antitone_lower (π.le_of_mem hJ)
#align box_integral.prepartition.lower_le_lower BoxIntegral.Prepartition.lower_le_lower
theorem upper_le_upper (hJ : J ∈ π) : J.upper ≤ I.upper :=
Box.monotone_upper (π.le_of_mem hJ)
#align box_integral.prepartition.upper_le_upper BoxIntegral.Prepartition.upper_le_upper
theorem injective_boxes : Function.Injective (boxes : Prepartition I → Finset (Box ι)) := by
rintro ⟨s₁, h₁, h₁'⟩ ⟨s₂, h₂, h₂'⟩ (rfl : s₁ = s₂)
rfl
#align box_integral.prepartition.injective_boxes BoxIntegral.Prepartition.injective_boxes
@[ext]
theorem ext (h : ∀ J, J ∈ π₁ ↔ J ∈ π₂) : π₁ = π₂ :=
injective_boxes <| Finset.ext h
#align box_integral.prepartition.ext BoxIntegral.Prepartition.ext
/-- The singleton prepartition `{J}`, `J ≤ I`. -/
@[simps]
def single (I J : Box ι) (h : J ≤ I) : Prepartition I :=
⟨{J}, by simpa, by simp⟩
#align box_integral.prepartition.single BoxIntegral.Prepartition.single
@[simp]
theorem mem_single {J'} (h : J ≤ I) : J' ∈ single I J h ↔ J' = J :=
mem_singleton
#align box_integral.prepartition.mem_single BoxIntegral.Prepartition.mem_single
/-- We say that `π ≤ π'` if each box of `π` is a subbox of some box of `π'`. -/
instance : LE (Prepartition I) :=
⟨fun π π' => ∀ ⦃I⦄, I ∈ π → ∃ I' ∈ π', I ≤ I'⟩
instance partialOrder : PartialOrder (Prepartition I) where
le := (· ≤ ·)
le_refl π I hI := ⟨I, hI, le_rfl⟩
le_trans π₁ π₂ π₃ h₁₂ h₂₃ I₁ hI₁ :=
let ⟨I₂, hI₂, hI₁₂⟩ := h₁₂ hI₁
let ⟨I₃, hI₃, hI₂₃⟩ := h₂₃ hI₂
⟨I₃, hI₃, hI₁₂.trans hI₂₃⟩
le_antisymm := by
suffices ∀ {π₁ π₂ : Prepartition I}, π₁ ≤ π₂ → π₂ ≤ π₁ → π₁.boxes ⊆ π₂.boxes from
fun π₁ π₂ h₁ h₂ => injective_boxes (Subset.antisymm (this h₁ h₂) (this h₂ h₁))
intro π₁ π₂ h₁ h₂ J hJ
rcases h₁ hJ with ⟨J', hJ', hle⟩; rcases h₂ hJ' with ⟨J'', hJ'', hle'⟩
obtain rfl : J = J'' := π₁.eq_of_le hJ hJ'' (hle.trans hle')
obtain rfl : J' = J := le_antisymm ‹_› ‹_›
assumption
instance : OrderTop (Prepartition I) where
top := single I I le_rfl
le_top π J hJ := ⟨I, by simp, π.le_of_mem hJ⟩
instance : OrderBot (Prepartition I) where
bot := ⟨∅,
fun _ hJ => (Finset.not_mem_empty _ hJ).elim,
fun _ hJ => (Set.not_mem_empty _ <| Finset.coe_empty ▸ hJ).elim⟩
bot_le _ _ hJ := (Finset.not_mem_empty _ hJ).elim
instance : Inhabited (Prepartition I) := ⟨⊤⟩
theorem le_def : π₁ ≤ π₂ ↔ ∀ J ∈ π₁, ∃ J' ∈ π₂, J ≤ J' := Iff.rfl
#align box_integral.prepartition.le_def BoxIntegral.Prepartition.le_def
@[simp]
theorem mem_top : J ∈ (⊤ : Prepartition I) ↔ J = I :=
mem_singleton
#align box_integral.prepartition.mem_top BoxIntegral.Prepartition.mem_top
@[simp]
theorem top_boxes : (⊤ : Prepartition I).boxes = {I} := rfl
#align box_integral.prepartition.top_boxes BoxIntegral.Prepartition.top_boxes
@[simp]
theorem not_mem_bot : J ∉ (⊥ : Prepartition I) :=
Finset.not_mem_empty _
#align box_integral.prepartition.not_mem_bot BoxIntegral.Prepartition.not_mem_bot
@[simp]
theorem bot_boxes : (⊥ : Prepartition I).boxes = ∅ := rfl
#align box_integral.prepartition.bot_boxes BoxIntegral.Prepartition.bot_boxes
/-- An auxiliary lemma used to prove that the same point can't belong to more than
`2 ^ Fintype.card ι` closed boxes of a prepartition. -/
theorem injOn_setOf_mem_Icc_setOf_lower_eq (x : ι → ℝ) :
InjOn (fun J : Box ι => { i | J.lower i = x i }) { J | J ∈ π ∧ x ∈ Box.Icc J } := by
rintro J₁ ⟨h₁, hx₁⟩ J₂ ⟨h₂, hx₂⟩ (H : { i | J₁.lower i = x i } = { i | J₂.lower i = x i })
suffices ∀ i, (Ioc (J₁.lower i) (J₁.upper i) ∩ Ioc (J₂.lower i) (J₂.upper i)).Nonempty by
choose y hy₁ hy₂ using this
exact π.eq_of_mem_of_mem h₁ h₂ hy₁ hy₂
intro i
simp only [Set.ext_iff, mem_setOf] at H
rcases (hx₁.1 i).eq_or_lt with hi₁ | hi₁
· have hi₂ : J₂.lower i = x i := (H _).1 hi₁
have H₁ : x i < J₁.upper i := by simpa only [hi₁] using J₁.lower_lt_upper i
have H₂ : x i < J₂.upper i := by simpa only [hi₂] using J₂.lower_lt_upper i
rw [Ioc_inter_Ioc, hi₁, hi₂, sup_idem, Set.nonempty_Ioc]
exact lt_min H₁ H₂
· have hi₂ : J₂.lower i < x i := (hx₂.1 i).lt_of_ne (mt (H _).2 hi₁.ne)
exact ⟨x i, ⟨hi₁, hx₁.2 i⟩, ⟨hi₂, hx₂.2 i⟩⟩
#align box_integral.prepartition.inj_on_set_of_mem_Icc_set_of_lower_eq BoxIntegral.Prepartition.injOn_setOf_mem_Icc_setOf_lower_eq
/-- The set of boxes of a prepartition that contain `x` in their closures has cardinality
at most `2 ^ Fintype.card ι`. -/
theorem card_filter_mem_Icc_le [Fintype ι] (x : ι → ℝ) :
(π.boxes.filter fun J : Box ι => x ∈ Box.Icc J).card ≤ 2 ^ Fintype.card ι := by
rw [← Fintype.card_set]
refine Finset.card_le_card_of_inj_on (fun J : Box ι => { i | J.lower i = x i })
(fun _ _ => Finset.mem_univ _) ?_
simpa only [Finset.mem_filter] using π.injOn_setOf_mem_Icc_setOf_lower_eq x
#align box_integral.prepartition.card_filter_mem_Icc_le BoxIntegral.Prepartition.card_filter_mem_Icc_le
/-- Given a prepartition `π : BoxIntegral.Prepartition I`, `π.iUnion` is the part of `I` covered by
the boxes of `π`. -/
protected def iUnion : Set (ι → ℝ) :=
⋃ J ∈ π, ↑J
#align box_integral.prepartition.Union BoxIntegral.Prepartition.iUnion
theorem iUnion_def : π.iUnion = ⋃ J ∈ π, ↑J := rfl
#align box_integral.prepartition.Union_def BoxIntegral.Prepartition.iUnion_def
theorem iUnion_def' : π.iUnion = ⋃ J ∈ π.boxes, ↑J := rfl
#align box_integral.prepartition.Union_def' BoxIntegral.Prepartition.iUnion_def'
-- Porting note: Previous proof was `:= Set.mem_iUnion₂`
@[simp]
theorem mem_iUnion : x ∈ π.iUnion ↔ ∃ J ∈ π, x ∈ J := by
convert Set.mem_iUnion₂
rw [Box.mem_coe, exists_prop]
#align box_integral.prepartition.mem_Union BoxIntegral.Prepartition.mem_iUnion
@[simp]
theorem iUnion_single (h : J ≤ I) : (single I J h).iUnion = J := by simp [iUnion_def]
#align box_integral.prepartition.Union_single BoxIntegral.Prepartition.iUnion_single
@[simp]
theorem iUnion_top : (⊤ : Prepartition I).iUnion = I := by simp [Prepartition.iUnion]
#align box_integral.prepartition.Union_top BoxIntegral.Prepartition.iUnion_top
@[simp]
theorem iUnion_eq_empty : π₁.iUnion = ∅ ↔ π₁ = ⊥ := by
simp [← injective_boxes.eq_iff, Finset.ext_iff, Prepartition.iUnion, imp_false]
#align box_integral.prepartition.Union_eq_empty BoxIntegral.Prepartition.iUnion_eq_empty
@[simp]
theorem iUnion_bot : (⊥ : Prepartition I).iUnion = ∅ :=
iUnion_eq_empty.2 rfl
#align box_integral.prepartition.Union_bot BoxIntegral.Prepartition.iUnion_bot
theorem subset_iUnion (h : J ∈ π) : ↑J ⊆ π.iUnion :=
subset_biUnion_of_mem h
#align box_integral.prepartition.subset_Union BoxIntegral.Prepartition.subset_iUnion
theorem iUnion_subset : π.iUnion ⊆ I :=
iUnion₂_subset π.le_of_mem'
#align box_integral.prepartition.Union_subset BoxIntegral.Prepartition.iUnion_subset
@[mono]
theorem iUnion_mono (h : π₁ ≤ π₂) : π₁.iUnion ⊆ π₂.iUnion := fun _ hx =>
let ⟨_, hJ₁, hx⟩ := π₁.mem_iUnion.1 hx
let ⟨J₂, hJ₂, hle⟩ := h hJ₁
π₂.mem_iUnion.2 ⟨J₂, hJ₂, hle hx⟩
#align box_integral.prepartition.Union_mono BoxIntegral.Prepartition.iUnion_mono
theorem disjoint_boxes_of_disjoint_iUnion (h : Disjoint π₁.iUnion π₂.iUnion) :
Disjoint π₁.boxes π₂.boxes :=
Finset.disjoint_left.2 fun J h₁ h₂ =>
Disjoint.le_bot (h.mono (π₁.subset_iUnion h₁) (π₂.subset_iUnion h₂)) ⟨J.upper_mem, J.upper_mem⟩
#align box_integral.prepartition.disjoint_boxes_of_disjoint_Union BoxIntegral.Prepartition.disjoint_boxes_of_disjoint_iUnion
theorem le_iff_nonempty_imp_le_and_iUnion_subset :
π₁ ≤ π₂ ↔
(∀ J ∈ π₁, ∀ J' ∈ π₂, (J ∩ J' : Set (ι → ℝ)).Nonempty → J ≤ J') ∧ π₁.iUnion ⊆ π₂.iUnion := by
constructor
· refine fun H => ⟨fun J hJ J' hJ' Hne => ?_, iUnion_mono H⟩
rcases H hJ with ⟨J'', hJ'', Hle⟩
rcases Hne with ⟨x, hx, hx'⟩
rwa [π₂.eq_of_mem_of_mem hJ' hJ'' hx' (Hle hx)]
· rintro ⟨H, HU⟩ J hJ
simp only [Set.subset_def, mem_iUnion] at HU
rcases HU J.upper ⟨J, hJ, J.upper_mem⟩ with ⟨J₂, hJ₂, hx⟩
exact ⟨J₂, hJ₂, H _ hJ _ hJ₂ ⟨_, J.upper_mem, hx⟩⟩
#align box_integral.prepartition.le_iff_nonempty_imp_le_and_Union_subset BoxIntegral.Prepartition.le_iff_nonempty_imp_le_and_iUnion_subset
theorem eq_of_boxes_subset_iUnion_superset (h₁ : π₁.boxes ⊆ π₂.boxes) (h₂ : π₂.iUnion ⊆ π₁.iUnion) :
π₁ = π₂ :=
le_antisymm (fun J hJ => ⟨J, h₁ hJ, le_rfl⟩) <|
le_iff_nonempty_imp_le_and_iUnion_subset.2
⟨fun _ hJ₁ _ hJ₂ Hne =>
(π₂.eq_of_mem_of_mem hJ₁ (h₁ hJ₂) Hne.choose_spec.1 Hne.choose_spec.2).le, h₂⟩
#align box_integral.prepartition.eq_of_boxes_subset_Union_superset BoxIntegral.Prepartition.eq_of_boxes_subset_iUnion_superset
/-- Given a prepartition `π` of a box `I` and a collection of prepartitions `πi J` of all boxes
`J ∈ π`, returns the prepartition of `I` into the union of the boxes of all `πi J`.
Though we only use the values of `πi` on the boxes of `π`, we require `πi` to be a globally defined
function. -/
@[simps]
def biUnion (πi : ∀ J : Box ι, Prepartition J) : Prepartition I where
boxes := π.boxes.biUnion fun J => (πi J).boxes
le_of_mem' J hJ := by
simp only [Finset.mem_biUnion, exists_prop, mem_boxes] at hJ
rcases hJ with ⟨J', hJ', hJ⟩
exact ((πi J').le_of_mem hJ).trans (π.le_of_mem hJ')
pairwiseDisjoint := by
simp only [Set.Pairwise, Finset.mem_coe, Finset.mem_biUnion]
rintro J₁' ⟨J₁, hJ₁, hJ₁'⟩ J₂' ⟨J₂, hJ₂, hJ₂'⟩ Hne
rw [Function.onFun, Set.disjoint_left]
rintro x hx₁ hx₂; apply Hne
obtain rfl : J₁ = J₂ :=
π.eq_of_mem_of_mem hJ₁ hJ₂ ((πi J₁).le_of_mem hJ₁' hx₁) ((πi J₂).le_of_mem hJ₂' hx₂)
exact (πi J₁).eq_of_mem_of_mem hJ₁' hJ₂' hx₁ hx₂
#align box_integral.prepartition.bUnion BoxIntegral.Prepartition.biUnion
variable {πi πi₁ πi₂ : ∀ J : Box ι, Prepartition J}
@[simp]
theorem mem_biUnion : J ∈ π.biUnion πi ↔ ∃ J' ∈ π, J ∈ πi J' := by simp [biUnion]
#align box_integral.prepartition.mem_bUnion BoxIntegral.Prepartition.mem_biUnion
theorem biUnion_le (πi : ∀ J, Prepartition J) : π.biUnion πi ≤ π := fun _ hJ =>
let ⟨J', hJ', hJ⟩ := π.mem_biUnion.1 hJ
⟨J', hJ', (πi J').le_of_mem hJ⟩
#align box_integral.prepartition.bUnion_le BoxIntegral.Prepartition.biUnion_le
@[simp]
theorem biUnion_top : (π.biUnion fun _ => ⊤) = π := by
ext
simp
#align box_integral.prepartition.bUnion_top BoxIntegral.Prepartition.biUnion_top
@[congr]
theorem biUnion_congr (h : π₁ = π₂) (hi : ∀ J ∈ π₁, πi₁ J = πi₂ J) :
π₁.biUnion πi₁ = π₂.biUnion πi₂ := by
subst π₂
ext J
simp only [mem_biUnion]
constructor <;> exact fun ⟨J', h₁, h₂⟩ => ⟨J', h₁, hi J' h₁ ▸ h₂⟩
#align box_integral.prepartition.bUnion_congr BoxIntegral.Prepartition.biUnion_congr
theorem biUnion_congr_of_le (h : π₁ = π₂) (hi : ∀ J ≤ I, πi₁ J = πi₂ J) :
π₁.biUnion πi₁ = π₂.biUnion πi₂ :=
biUnion_congr h fun J hJ => hi J (π₁.le_of_mem hJ)
#align box_integral.prepartition.bUnion_congr_of_le BoxIntegral.Prepartition.biUnion_congr_of_le
@[simp]
theorem iUnion_biUnion (πi : ∀ J : Box ι, Prepartition J) :
(π.biUnion πi).iUnion = ⋃ J ∈ π, (πi J).iUnion := by simp [Prepartition.iUnion]
#align box_integral.prepartition.Union_bUnion BoxIntegral.Prepartition.iUnion_biUnion
@[simp]
theorem sum_biUnion_boxes {M : Type*} [AddCommMonoid M] (π : Prepartition I)
(πi : ∀ J, Prepartition J) (f : Box ι → M) :
(∑ J ∈ π.boxes.biUnion fun J => (πi J).boxes, f J) =
∑ J ∈ π.boxes, ∑ J' ∈ (πi J).boxes, f J' := by
refine Finset.sum_biUnion fun J₁ h₁ J₂ h₂ hne => Finset.disjoint_left.2 fun J' h₁' h₂' => ?_
exact hne (π.eq_of_le_of_le h₁ h₂ ((πi J₁).le_of_mem h₁') ((πi J₂).le_of_mem h₂'))
#align box_integral.prepartition.sum_bUnion_boxes BoxIntegral.Prepartition.sum_biUnion_boxes
/-- Given a box `J ∈ π.biUnion πi`, returns the box `J' ∈ π` such that `J ∈ πi J'`.
For `J ∉ π.biUnion πi`, returns `I`. -/
def biUnionIndex (πi : ∀ (J : Box ι), Prepartition J) (J : Box ι) : Box ι :=
if hJ : J ∈ π.biUnion πi then (π.mem_biUnion.1 hJ).choose else I
#align box_integral.prepartition.bUnion_index BoxIntegral.Prepartition.biUnionIndex
theorem biUnionIndex_mem (hJ : J ∈ π.biUnion πi) : π.biUnionIndex πi J ∈ π := by
rw [biUnionIndex, dif_pos hJ]
exact (π.mem_biUnion.1 hJ).choose_spec.1
#align box_integral.prepartition.bUnion_index_mem BoxIntegral.Prepartition.biUnionIndex_mem
theorem biUnionIndex_le (πi : ∀ J, Prepartition J) (J : Box ι) : π.biUnionIndex πi J ≤ I := by
by_cases hJ : J ∈ π.biUnion πi
· exact π.le_of_mem (π.biUnionIndex_mem hJ)
· rw [biUnionIndex, dif_neg hJ]
#align box_integral.prepartition.bUnion_index_le BoxIntegral.Prepartition.biUnionIndex_le
theorem mem_biUnionIndex (hJ : J ∈ π.biUnion πi) : J ∈ πi (π.biUnionIndex πi J) := by
convert (π.mem_biUnion.1 hJ).choose_spec.2 <;> exact dif_pos hJ
#align box_integral.prepartition.mem_bUnion_index BoxIntegral.Prepartition.mem_biUnionIndex
theorem le_biUnionIndex (hJ : J ∈ π.biUnion πi) : J ≤ π.biUnionIndex πi J :=
le_of_mem _ (π.mem_biUnionIndex hJ)
#align box_integral.prepartition.le_bUnion_index BoxIntegral.Prepartition.le_biUnionIndex
/-- Uniqueness property of `BoxIntegral.Prepartition.biUnionIndex`. -/
theorem biUnionIndex_of_mem (hJ : J ∈ π) {J'} (hJ' : J' ∈ πi J) : π.biUnionIndex πi J' = J :=
have : J' ∈ π.biUnion πi := π.mem_biUnion.2 ⟨J, hJ, hJ'⟩
π.eq_of_le_of_le (π.biUnionIndex_mem this) hJ (π.le_biUnionIndex this) (le_of_mem _ hJ')
#align box_integral.prepartition.bUnion_index_of_mem BoxIntegral.Prepartition.biUnionIndex_of_mem
theorem biUnion_assoc (πi : ∀ J, Prepartition J) (πi' : Box ι → ∀ J : Box ι, Prepartition J) :
(π.biUnion fun J => (πi J).biUnion (πi' J)) =
(π.biUnion πi).biUnion fun J => πi' (π.biUnionIndex πi J) J := by
ext J
simp only [mem_biUnion, exists_prop]
constructor
· rintro ⟨J₁, hJ₁, J₂, hJ₂, hJ⟩
refine ⟨J₂, ⟨J₁, hJ₁, hJ₂⟩, ?_⟩
rwa [π.biUnionIndex_of_mem hJ₁ hJ₂]
· rintro ⟨J₁, ⟨J₂, hJ₂, hJ₁⟩, hJ⟩
refine ⟨J₂, hJ₂, J₁, hJ₁, ?_⟩
rwa [π.biUnionIndex_of_mem hJ₂ hJ₁] at hJ
#align box_integral.prepartition.bUnion_assoc BoxIntegral.Prepartition.biUnion_assoc
/-- Create a `BoxIntegral.Prepartition` from a collection of possibly empty boxes by filtering out
the empty one if it exists. -/
def ofWithBot (boxes : Finset (WithBot (Box ι)))
(le_of_mem : ∀ J ∈ boxes, (J : WithBot (Box ι)) ≤ I)
(pairwise_disjoint : Set.Pairwise (boxes : Set (WithBot (Box ι))) Disjoint) :
Prepartition I where
boxes := Finset.eraseNone boxes
le_of_mem' J hJ := by
rw [mem_eraseNone] at hJ
simpa only [WithBot.some_eq_coe, WithBot.coe_le_coe] using le_of_mem _ hJ
pairwiseDisjoint J₁ h₁ J₂ h₂ hne := by
simp only [mem_coe, mem_eraseNone] at h₁ h₂
exact Box.disjoint_coe.1 (pairwise_disjoint h₁ h₂ (mt Option.some_inj.1 hne))
#align box_integral.prepartition.of_with_bot BoxIntegral.Prepartition.ofWithBot
@[simp]
theorem mem_ofWithBot {boxes : Finset (WithBot (Box ι))} {h₁ h₂} :
J ∈ (ofWithBot boxes h₁ h₂ : Prepartition I) ↔ (J : WithBot (Box ι)) ∈ boxes :=
mem_eraseNone
#align box_integral.prepartition.mem_of_with_bot BoxIntegral.Prepartition.mem_ofWithBot
@[simp]
theorem iUnion_ofWithBot (boxes : Finset (WithBot (Box ι)))
(le_of_mem : ∀ J ∈ boxes, (J : WithBot (Box ι)) ≤ I)
(pairwise_disjoint : Set.Pairwise (boxes : Set (WithBot (Box ι))) Disjoint) :
(ofWithBot boxes le_of_mem pairwise_disjoint).iUnion = ⋃ J ∈ boxes, ↑J := by
suffices ⋃ (J : Box ι) (_ : ↑J ∈ boxes), ↑J = ⋃ J ∈ boxes, (J : Set (ι → ℝ)) by
simpa [ofWithBot, Prepartition.iUnion]
simp only [← Box.biUnion_coe_eq_coe, @iUnion_comm _ _ (Box ι), @iUnion_comm _ _ (@Eq _ _ _),
iUnion_iUnion_eq_right]
#align box_integral.prepartition.Union_of_with_bot BoxIntegral.Prepartition.iUnion_ofWithBot
theorem ofWithBot_le {boxes : Finset (WithBot (Box ι))}
{le_of_mem : ∀ J ∈ boxes, (J : WithBot (Box ι)) ≤ I}
{pairwise_disjoint : Set.Pairwise (boxes : Set (WithBot (Box ι))) Disjoint}
(H : ∀ J ∈ boxes, J ≠ ⊥ → ∃ J' ∈ π, J ≤ ↑J') :
ofWithBot boxes le_of_mem pairwise_disjoint ≤ π := by
have : ∀ J : Box ι, ↑J ∈ boxes → ∃ J' ∈ π, J ≤ J' := fun J hJ => by
simpa only [WithBot.coe_le_coe] using H J hJ WithBot.coe_ne_bot
simpa [ofWithBot, le_def]
#align box_integral.prepartition.of_with_bot_le BoxIntegral.Prepartition.ofWithBot_le
theorem le_ofWithBot {boxes : Finset (WithBot (Box ι))}
{le_of_mem : ∀ J ∈ boxes, (J : WithBot (Box ι)) ≤ I}
{pairwise_disjoint : Set.Pairwise (boxes : Set (WithBot (Box ι))) Disjoint}
(H : ∀ J ∈ π, ∃ J' ∈ boxes, ↑J ≤ J') : π ≤ ofWithBot boxes le_of_mem pairwise_disjoint := by
intro J hJ
rcases H J hJ with ⟨J', J'mem, hle⟩
lift J' to Box ι using ne_bot_of_le_ne_bot WithBot.coe_ne_bot hle
exact ⟨J', mem_ofWithBot.2 J'mem, WithBot.coe_le_coe.1 hle⟩
#align box_integral.prepartition.le_of_with_bot BoxIntegral.Prepartition.le_ofWithBot
theorem ofWithBot_mono {boxes₁ : Finset (WithBot (Box ι))}
{le_of_mem₁ : ∀ J ∈ boxes₁, (J : WithBot (Box ι)) ≤ I}
{pairwise_disjoint₁ : Set.Pairwise (boxes₁ : Set (WithBot (Box ι))) Disjoint}
{boxes₂ : Finset (WithBot (Box ι))} {le_of_mem₂ : ∀ J ∈ boxes₂, (J : WithBot (Box ι)) ≤ I}
{pairwise_disjoint₂ : Set.Pairwise (boxes₂ : Set (WithBot (Box ι))) Disjoint}
(H : ∀ J ∈ boxes₁, J ≠ ⊥ → ∃ J' ∈ boxes₂, J ≤ J') :
ofWithBot boxes₁ le_of_mem₁ pairwise_disjoint₁ ≤
ofWithBot boxes₂ le_of_mem₂ pairwise_disjoint₂ :=
le_ofWithBot _ fun J hJ => H J (mem_ofWithBot.1 hJ) WithBot.coe_ne_bot
#align box_integral.prepartition.of_with_bot_mono BoxIntegral.Prepartition.ofWithBot_mono
theorem sum_ofWithBot {M : Type*} [AddCommMonoid M] (boxes : Finset (WithBot (Box ι)))
(le_of_mem : ∀ J ∈ boxes, (J : WithBot (Box ι)) ≤ I)
(pairwise_disjoint : Set.Pairwise (boxes : Set (WithBot (Box ι))) Disjoint) (f : Box ι → M) :
(∑ J ∈ (ofWithBot boxes le_of_mem pairwise_disjoint).boxes, f J) =
∑ J ∈ boxes, Option.elim' 0 f J :=
Finset.sum_eraseNone _ _
#align box_integral.prepartition.sum_of_with_bot BoxIntegral.Prepartition.sum_ofWithBot
/-- Restrict a prepartition to a box. -/
def restrict (π : Prepartition I) (J : Box ι) : Prepartition J :=
ofWithBot (π.boxes.image fun J' : Box ι => J ⊓ J')
(fun J' hJ' => by
rcases Finset.mem_image.1 hJ' with ⟨J', -, rfl⟩
exact inf_le_left)
(by
simp only [Set.Pairwise, onFun, Finset.mem_coe, Finset.mem_image]
rintro _ ⟨J₁, h₁, rfl⟩ _ ⟨J₂, h₂, rfl⟩ Hne
have : J₁ ≠ J₂ := by
rintro rfl
exact Hne rfl
exact ((Box.disjoint_coe.2 <| π.disjoint_coe_of_mem h₁ h₂ this).inf_left' _).inf_right' _)
#align box_integral.prepartition.restrict BoxIntegral.Prepartition.restrict
@[simp]
theorem mem_restrict : J₁ ∈ π.restrict J ↔ ∃ J' ∈ π, (J₁ : WithBot (Box ι)) = ↑J ⊓ ↑J' := by
simp [restrict, eq_comm]
#align box_integral.prepartition.mem_restrict BoxIntegral.Prepartition.mem_restrict
theorem mem_restrict' : J₁ ∈ π.restrict J ↔ ∃ J' ∈ π, (J₁ : Set (ι → ℝ)) = ↑J ∩ ↑J' := by
simp only [mem_restrict, ← Box.withBotCoe_inj, Box.coe_inf, Box.coe_coe]
#align box_integral.prepartition.mem_restrict' BoxIntegral.Prepartition.mem_restrict'
@[mono]
theorem restrict_mono {π₁ π₂ : Prepartition I} (Hle : π₁ ≤ π₂) : π₁.restrict J ≤ π₂.restrict J := by
refine ofWithBot_mono fun J₁ hJ₁ hne => ?_
rw [Finset.mem_image] at hJ₁; rcases hJ₁ with ⟨J₁, hJ₁, rfl⟩
rcases Hle hJ₁ with ⟨J₂, hJ₂, hle⟩
exact ⟨_, Finset.mem_image_of_mem _ hJ₂, inf_le_inf_left _ <| WithBot.coe_le_coe.2 hle⟩
#align box_integral.prepartition.restrict_mono BoxIntegral.Prepartition.restrict_mono
theorem monotone_restrict : Monotone fun π : Prepartition I => restrict π J :=
fun _ _ => restrict_mono
#align box_integral.prepartition.monotone_restrict BoxIntegral.Prepartition.monotone_restrict
/-- Restricting to a larger box does not change the set of boxes. We cannot claim equality
of prepartitions because they have different types. -/
theorem restrict_boxes_of_le (π : Prepartition I) (h : I ≤ J) : (π.restrict J).boxes = π.boxes := by
simp only [restrict, ofWithBot, eraseNone_eq_biUnion]
refine Finset.image_biUnion.trans ?_
refine (Finset.biUnion_congr rfl ?_).trans Finset.biUnion_singleton_eq_self
intro J' hJ'
rw [inf_of_le_right, ← WithBot.some_eq_coe, Option.toFinset_some]
exact WithBot.coe_le_coe.2 ((π.le_of_mem hJ').trans h)
#align box_integral.prepartition.restrict_boxes_of_le BoxIntegral.Prepartition.restrict_boxes_of_le
@[simp]
theorem restrict_self : π.restrict I = π :=
injective_boxes <| restrict_boxes_of_le π le_rfl
#align box_integral.prepartition.restrict_self BoxIntegral.Prepartition.restrict_self
@[simp]
theorem iUnion_restrict : (π.restrict J).iUnion = (J : Set (ι → ℝ)) ∩ (π.iUnion) := by
simp [restrict, ← inter_iUnion, ← iUnion_def]
#align box_integral.prepartition.Union_restrict BoxIntegral.Prepartition.iUnion_restrict
@[simp]
theorem restrict_biUnion (πi : ∀ J, Prepartition J) (hJ : J ∈ π) :
(π.biUnion πi).restrict J = πi J := by
refine (eq_of_boxes_subset_iUnion_superset (fun J₁ h₁ => ?_) ?_).symm
· refine (mem_restrict _).2 ⟨J₁, π.mem_biUnion.2 ⟨J, hJ, h₁⟩, (inf_of_le_right ?_).symm⟩
exact WithBot.coe_le_coe.2 (le_of_mem _ h₁)
· simp only [iUnion_restrict, iUnion_biUnion, Set.subset_def, Set.mem_inter_iff, Set.mem_iUnion]
rintro x ⟨hxJ, J₁, h₁, hx⟩
obtain rfl : J = J₁ := π.eq_of_mem_of_mem hJ h₁ hxJ (iUnion_subset _ hx)
exact hx
#align box_integral.prepartition.restrict_bUnion BoxIntegral.Prepartition.restrict_biUnion
theorem biUnion_le_iff {πi : ∀ J, Prepartition J} {π' : Prepartition I} :
π.biUnion πi ≤ π' ↔ ∀ J ∈ π, πi J ≤ π'.restrict J := by
constructor <;> intro H J hJ
· rw [← π.restrict_biUnion πi hJ]
exact restrict_mono H
· rw [mem_biUnion] at hJ
rcases hJ with ⟨J₁, h₁, hJ⟩
rcases H J₁ h₁ hJ with ⟨J₂, h₂, Hle⟩
rcases π'.mem_restrict.mp h₂ with ⟨J₃, h₃, H⟩
exact ⟨J₃, h₃, Hle.trans <| WithBot.coe_le_coe.1 <| H.trans_le inf_le_right⟩
#align box_integral.prepartition.bUnion_le_iff BoxIntegral.Prepartition.biUnion_le_iff
theorem le_biUnion_iff {πi : ∀ J, Prepartition J} {π' : Prepartition I} :
π' ≤ π.biUnion πi ↔ π' ≤ π ∧ ∀ J ∈ π, π'.restrict J ≤ πi J := by
refine ⟨fun H => ⟨H.trans (π.biUnion_le πi), fun J hJ => ?_⟩, ?_⟩
· rw [← π.restrict_biUnion πi hJ]
exact restrict_mono H
· rintro ⟨H, Hi⟩ J' hJ'
rcases H hJ' with ⟨J, hJ, hle⟩
have : J' ∈ π'.restrict J :=
π'.mem_restrict.2 ⟨J', hJ', (inf_of_le_right <| WithBot.coe_le_coe.2 hle).symm⟩
rcases Hi J hJ this with ⟨Ji, hJi, hlei⟩
exact ⟨Ji, π.mem_biUnion.2 ⟨J, hJ, hJi⟩, hlei⟩
#align box_integral.prepartition.le_bUnion_iff BoxIntegral.Prepartition.le_biUnion_iff
instance inf : Inf (Prepartition I) :=
⟨fun π₁ π₂ => π₁.biUnion fun J => π₂.restrict J⟩
theorem inf_def (π₁ π₂ : Prepartition I) : π₁ ⊓ π₂ = π₁.biUnion fun J => π₂.restrict J := rfl
#align box_integral.prepartition.inf_def BoxIntegral.Prepartition.inf_def
@[simp]
theorem mem_inf {π₁ π₂ : Prepartition I} :
J ∈ π₁ ⊓ π₂ ↔ ∃ J₁ ∈ π₁, ∃ J₂ ∈ π₂, (J : WithBot (Box ι)) = ↑J₁ ⊓ ↑J₂ := by
simp only [inf_def, mem_biUnion, mem_restrict]
#align box_integral.prepartition.mem_inf BoxIntegral.Prepartition.mem_inf
@[simp]
theorem iUnion_inf (π₁ π₂ : Prepartition I) : (π₁ ⊓ π₂).iUnion = π₁.iUnion ∩ π₂.iUnion := by
simp only [inf_def, iUnion_biUnion, iUnion_restrict, ← iUnion_inter, ← iUnion_def]
#align box_integral.prepartition.Union_inf BoxIntegral.Prepartition.iUnion_inf
instance : SemilatticeInf (Prepartition I) :=
{ Prepartition.inf,
Prepartition.partialOrder with
inf_le_left := fun π₁ _ => π₁.biUnion_le _
inf_le_right := fun _ _ => (biUnion_le_iff _).2 fun _ _ => le_rfl
le_inf := fun _ π₁ _ h₁ h₂ => π₁.le_biUnion_iff.2 ⟨h₁, fun _ _ => restrict_mono h₂⟩ }
/-- The prepartition with boxes `{J ∈ π | p J}`. -/
@[simps]
def filter (π : Prepartition I) (p : Box ι → Prop) : Prepartition I where
boxes := π.boxes.filter p
le_of_mem' _ hJ := π.le_of_mem (mem_filter.1 hJ).1
pairwiseDisjoint _ h₁ _ h₂ := π.disjoint_coe_of_mem (mem_filter.1 h₁).1 (mem_filter.1 h₂).1
#align box_integral.prepartition.filter BoxIntegral.Prepartition.filter
@[simp]
theorem mem_filter {p : Box ι → Prop} : J ∈ π.filter p ↔ J ∈ π ∧ p J :=
Finset.mem_filter
#align box_integral.prepartition.mem_filter BoxIntegral.Prepartition.mem_filter
theorem filter_le (π : Prepartition I) (p : Box ι → Prop) : π.filter p ≤ π := fun J hJ =>
let ⟨hπ, _⟩ := π.mem_filter.1 hJ
⟨J, hπ, le_rfl⟩
#align box_integral.prepartition.filter_le BoxIntegral.Prepartition.filter_le
theorem filter_of_true {p : Box ι → Prop} (hp : ∀ J ∈ π, p J) : π.filter p = π := by
ext J
simpa using hp J
#align box_integral.prepartition.filter_of_true BoxIntegral.Prepartition.filter_of_true
@[simp]
theorem filter_true : (π.filter fun _ => True) = π :=
π.filter_of_true fun _ _ => trivial
#align box_integral.prepartition.filter_true BoxIntegral.Prepartition.filter_true
@[simp]
| Mathlib/Analysis/BoxIntegral/Partition/Basic.lean | 622 | 630 | theorem iUnion_filter_not (π : Prepartition I) (p : Box ι → Prop) :
(π.filter fun J => ¬p J).iUnion = π.iUnion \ (π.filter p).iUnion := by |
simp only [Prepartition.iUnion]
convert (@Set.biUnion_diff_biUnion_eq (ι → ℝ) (Box ι) π.boxes (π.filter p).boxes (↑) _).symm
· simp (config := { contextual := true })
· rw [Set.PairwiseDisjoint]
convert π.pairwiseDisjoint
rw [Set.union_eq_left, filter_boxes, coe_filter]
exact fun _ ⟨h, _⟩ => h
|
/-
Copyright (c) 2020 Nicolò Cavalleri. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nicolò Cavalleri, Andrew Yang
-/
import Mathlib.RingTheory.Derivation.ToSquareZero
import Mathlib.RingTheory.Ideal.Cotangent
import Mathlib.RingTheory.IsTensorProduct
import Mathlib.Algebra.Exact
import Mathlib.Algebra.MvPolynomial.PDeriv
import Mathlib.Algebra.Polynomial.Derivation
#align_import ring_theory.kaehler from "leanprover-community/mathlib"@"4b92a463033b5587bb011657e25e4710bfca7364"
/-!
# The module of kaehler differentials
## Main results
- `KaehlerDifferential`: The module of kaehler differentials. For an `R`-algebra `S`, we provide
the notation `Ω[S⁄R]` for `KaehlerDifferential R S`.
Note that the slash is `\textfractionsolidus`.
- `KaehlerDifferential.D`: The derivation into the module of kaehler differentials.
- `KaehlerDifferential.span_range_derivation`: The image of `D` spans `Ω[S⁄R]` as an `S`-module.
- `KaehlerDifferential.linearMapEquivDerivation`:
The isomorphism `Hom_R(Ω[S⁄R], M) ≃ₗ[S] Der_R(S, M)`.
- `KaehlerDifferential.quotKerTotalEquiv`: An alternative description of `Ω[S⁄R]` as `S` copies
of `S` with kernel (`KaehlerDifferential.kerTotal`) generated by the relations:
1. `dx + dy = d(x + y)`
2. `x dy + y dx = d(x * y)`
3. `dr = 0` for `r ∈ R`
- `KaehlerDifferential.map`: Given a map between the arrows `R →+* A` and `S →+* B`, we have an
`A`-linear map `Ω[A⁄R] → Ω[B⁄S]`.
- `KaehlerDifferential.map_surjective`:
The sequence `Ω[B⁄R] → Ω[B⁄A] → 0` is exact.
- `KaehlerDifferential.exact_mapBaseChange_map`:
The sequence `B ⊗[A] Ω[A⁄R] → Ω[B⁄R] → Ω[B⁄A]` is exact.
## Future project
- Define the `IsKaehlerDifferential` predicate.
-/
suppress_compilation
section KaehlerDifferential
open scoped TensorProduct
open Algebra
universe u v
variable (R : Type u) (S : Type v) [CommRing R] [CommRing S] [Algebra R S]
/-- The kernel of the multiplication map `S ⊗[R] S →ₐ[R] S`. -/
abbrev KaehlerDifferential.ideal : Ideal (S ⊗[R] S) :=
RingHom.ker (TensorProduct.lmul' R : S ⊗[R] S →ₐ[R] S)
#align kaehler_differential.ideal KaehlerDifferential.ideal
variable {S}
theorem KaehlerDifferential.one_smul_sub_smul_one_mem_ideal (a : S) :
(1 : S) ⊗ₜ[R] a - a ⊗ₜ[R] (1 : S) ∈ KaehlerDifferential.ideal R S := by simp [RingHom.mem_ker]
#align kaehler_differential.one_smul_sub_smul_one_mem_ideal KaehlerDifferential.one_smul_sub_smul_one_mem_ideal
variable {R}
variable {M : Type*} [AddCommGroup M] [Module R M] [Module S M] [IsScalarTower R S M]
/-- For a `R`-derivation `S → M`, this is the map `S ⊗[R] S →ₗ[S] M` sending `s ⊗ₜ t ↦ s • D t`. -/
def Derivation.tensorProductTo (D : Derivation R S M) : S ⊗[R] S →ₗ[S] M :=
TensorProduct.AlgebraTensorModule.lift ((LinearMap.lsmul S (S →ₗ[R] M)).flip D.toLinearMap)
#align derivation.tensor_product_to Derivation.tensorProductTo
theorem Derivation.tensorProductTo_tmul (D : Derivation R S M) (s t : S) :
D.tensorProductTo (s ⊗ₜ t) = s • D t := rfl
#align derivation.tensor_product_to_tmul Derivation.tensorProductTo_tmul
theorem Derivation.tensorProductTo_mul (D : Derivation R S M) (x y : S ⊗[R] S) :
D.tensorProductTo (x * y) =
TensorProduct.lmul' (S := S) R x • D.tensorProductTo y +
TensorProduct.lmul' (S := S) R y • D.tensorProductTo x := by
refine TensorProduct.induction_on x ?_ ?_ ?_
· rw [zero_mul, map_zero, map_zero, zero_smul, smul_zero, add_zero]
swap
· intro x₁ y₁ h₁ h₂
rw [add_mul, map_add, map_add, map_add, add_smul, smul_add, h₁, h₂, add_add_add_comm]
intro x₁ x₂
refine TensorProduct.induction_on y ?_ ?_ ?_
· rw [mul_zero, map_zero, map_zero, zero_smul, smul_zero, add_zero]
swap
· intro x₁ y₁ h₁ h₂
rw [mul_add, map_add, map_add, map_add, add_smul, smul_add, h₁, h₂, add_add_add_comm]
intro x y
simp only [TensorProduct.tmul_mul_tmul, Derivation.tensorProductTo,
TensorProduct.AlgebraTensorModule.lift_apply, TensorProduct.lift.tmul',
TensorProduct.lmul'_apply_tmul]
dsimp
rw [D.leibniz]
simp only [smul_smul, smul_add, mul_comm (x * y) x₁, mul_right_comm x₁ x₂, ← mul_assoc]
#align derivation.tensor_product_to_mul Derivation.tensorProductTo_mul
variable (R S)
/-- The kernel of `S ⊗[R] S →ₐ[R] S` is generated by `1 ⊗ s - s ⊗ 1` as a `S`-module. -/
| Mathlib/RingTheory/Kaehler.lean | 105 | 128 | theorem KaehlerDifferential.submodule_span_range_eq_ideal :
Submodule.span S (Set.range fun s : S => (1 : S) ⊗ₜ[R] s - s ⊗ₜ[R] (1 : S)) =
(KaehlerDifferential.ideal R S).restrictScalars S := by |
apply le_antisymm
· rw [Submodule.span_le]
rintro _ ⟨s, rfl⟩
exact KaehlerDifferential.one_smul_sub_smul_one_mem_ideal _ _
· rintro x (hx : _ = _)
have : x - TensorProduct.lmul' (S := S) R x ⊗ₜ[R] (1 : S) = x := by
rw [hx, TensorProduct.zero_tmul, sub_zero]
rw [← this]
clear this hx
refine TensorProduct.induction_on x ?_ ?_ ?_
· rw [map_zero, TensorProduct.zero_tmul, sub_zero]; exact zero_mem _
· intro x y
have : x ⊗ₜ[R] y - (x * y) ⊗ₜ[R] (1 : S) = x • ((1 : S) ⊗ₜ y - y ⊗ₜ (1 : S)) := by
simp_rw [smul_sub, TensorProduct.smul_tmul', smul_eq_mul, mul_one]
rw [TensorProduct.lmul'_apply_tmul, this]
refine Submodule.smul_mem _ x ?_
apply Submodule.subset_span
exact Set.mem_range_self y
· intro x y hx hy
rw [map_add, TensorProduct.add_tmul, ← sub_add_sub_comm]
exact add_mem hx hy
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Mario Carneiro
-/
import Mathlib.Algebra.Module.Submodule.Bilinear
import Mathlib.GroupTheory.Congruence.Basic
import Mathlib.LinearAlgebra.Basic
import Mathlib.Tactic.SuppressCompilation
#align_import linear_algebra.tensor_product from "leanprover-community/mathlib"@"88fcdc3da43943f5b01925deddaa5bf0c0e85e4e"
/-!
# Tensor product of modules over commutative semirings.
This file constructs the tensor product of modules over commutative semirings. Given a semiring
`R` and modules over it `M` and `N`, the standard construction of the tensor product is
`TensorProduct R M N`. It is also a module over `R`.
It comes with a canonical bilinear map `M → N → TensorProduct R M N`.
Given any bilinear map `M → N → P`, there is a unique linear map `TensorProduct R M N → P` whose
composition with the canonical bilinear map `M → N → TensorProduct R M N` is the given bilinear
map `M → N → P`.
We start by proving basic lemmas about bilinear maps.
## Notations
This file uses the localized notation `M ⊗ N` and `M ⊗[R] N` for `TensorProduct R M N`, as well
as `m ⊗ₜ n` and `m ⊗ₜ[R] n` for `TensorProduct.tmul R m n`.
## Tags
bilinear, tensor, tensor product
-/
suppress_compilation
section Semiring
variable {R : Type*} [CommSemiring R]
variable {R' : Type*} [Monoid R']
variable {R'' : Type*} [Semiring R'']
variable {M : Type*} {N : Type*} {P : Type*} {Q : Type*} {S : Type*} {T : Type*}
variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P]
variable [AddCommMonoid Q] [AddCommMonoid S] [AddCommMonoid T]
variable [Module R M] [Module R N] [Module R P] [Module R Q] [Module R S] [Module R T]
variable [DistribMulAction R' M]
variable [Module R'' M]
variable (M N)
namespace TensorProduct
section
variable (R)
/-- The relation on `FreeAddMonoid (M × N)` that generates a congruence whose quotient is
the tensor product. -/
inductive Eqv : FreeAddMonoid (M × N) → FreeAddMonoid (M × N) → Prop
| of_zero_left : ∀ n : N, Eqv (.of (0, n)) 0
| of_zero_right : ∀ m : M, Eqv (.of (m, 0)) 0
| of_add_left : ∀ (m₁ m₂ : M) (n : N), Eqv (.of (m₁, n) + .of (m₂, n)) (.of (m₁ + m₂, n))
| of_add_right : ∀ (m : M) (n₁ n₂ : N), Eqv (.of (m, n₁) + .of (m, n₂)) (.of (m, n₁ + n₂))
| of_smul : ∀ (r : R) (m : M) (n : N), Eqv (.of (r • m, n)) (.of (m, r • n))
| add_comm : ∀ x y, Eqv (x + y) (y + x)
#align tensor_product.eqv TensorProduct.Eqv
end
end TensorProduct
variable (R)
/-- The tensor product of two modules `M` and `N` over the same commutative semiring `R`.
The localized notations are `M ⊗ N` and `M ⊗[R] N`, accessed by `open scoped TensorProduct`. -/
def TensorProduct : Type _ :=
(addConGen (TensorProduct.Eqv R M N)).Quotient
#align tensor_product TensorProduct
variable {R}
set_option quotPrecheck false in
@[inherit_doc TensorProduct] scoped[TensorProduct] infixl:100 " ⊗ " => TensorProduct _
@[inherit_doc] scoped[TensorProduct] notation:100 M " ⊗[" R "] " N:100 => TensorProduct R M N
namespace TensorProduct
section Module
protected instance add : Add (M ⊗[R] N) :=
(addConGen (TensorProduct.Eqv R M N)).hasAdd
instance addZeroClass : AddZeroClass (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
/- The `toAdd` field is given explicitly as `TensorProduct.add` for performance reasons.
This avoids any need to unfold `Con.addMonoid` when the type checker is checking
that instance diagrams commute -/
toAdd := TensorProduct.add _ _ }
instance addSemigroup : AddSemigroup (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
toAdd := TensorProduct.add _ _ }
instance addCommSemigroup : AddCommSemigroup (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
toAddSemigroup := TensorProduct.addSemigroup _ _
add_comm := fun x y =>
AddCon.induction_on₂ x y fun _ _ =>
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.add_comm _ _ }
instance : Inhabited (M ⊗[R] N) :=
⟨0⟩
variable (R) {M N}
/-- The canonical function `M → N → M ⊗ N`. The localized notations are `m ⊗ₜ n` and `m ⊗ₜ[R] n`,
accessed by `open scoped TensorProduct`. -/
def tmul (m : M) (n : N) : M ⊗[R] N :=
AddCon.mk' _ <| FreeAddMonoid.of (m, n)
#align tensor_product.tmul TensorProduct.tmul
variable {R}
/-- The canonical function `M → N → M ⊗ N`. -/
infixl:100 " ⊗ₜ " => tmul _
/-- The canonical function `M → N → M ⊗ N`. -/
notation:100 x " ⊗ₜ[" R "] " y:100 => tmul R x y
-- Porting note: make the arguments of induction_on explicit
@[elab_as_elim]
protected theorem induction_on {motive : M ⊗[R] N → Prop} (z : M ⊗[R] N)
(zero : motive 0)
(tmul : ∀ x y, motive <| x ⊗ₜ[R] y)
(add : ∀ x y, motive x → motive y → motive (x + y)) : motive z :=
AddCon.induction_on z fun x =>
FreeAddMonoid.recOn x zero fun ⟨m, n⟩ y ih => by
rw [AddCon.coe_add]
exact add _ _ (tmul ..) ih
#align tensor_product.induction_on TensorProduct.induction_on
/-- Lift an `R`-balanced map to the tensor product.
A map `f : M →+ N →+ P` additive in both components is `R`-balanced, or middle linear with respect
to `R`, if scalar multiplication in either argument is equivalent, `f (r • m) n = f m (r • n)`.
Note that strictly the first action should be a right-action by `R`, but for now `R` is commutative
so it doesn't matter. -/
-- TODO: use this to implement `lift` and `SMul.aux`. For now we do not do this as it causes
-- performance issues elsewhere.
def liftAddHom (f : M →+ N →+ P)
(hf : ∀ (r : R) (m : M) (n : N), f (r • m) n = f m (r • n)) :
M ⊗[R] N →+ P :=
(addConGen (TensorProduct.Eqv R M N)).lift (FreeAddMonoid.lift (fun mn : M × N => f mn.1 mn.2)) <|
AddCon.addConGen_le fun x y hxy =>
match x, y, hxy with
| _, _, .of_zero_left n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, FreeAddMonoid.lift_eval_of, map_zero,
AddMonoidHom.zero_apply]
| _, _, .of_zero_right m =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, FreeAddMonoid.lift_eval_of, map_zero]
| _, _, .of_add_left m₁ m₂ n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, FreeAddMonoid.lift_eval_of, map_add,
AddMonoidHom.add_apply]
| _, _, .of_add_right m n₁ n₂ =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, FreeAddMonoid.lift_eval_of, map_add]
| _, _, .of_smul s m n =>
(AddCon.ker_rel _).2 <| by rw [FreeAddMonoid.lift_eval_of, FreeAddMonoid.lift_eval_of, hf]
| _, _, .add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, add_comm]
@[simp]
theorem liftAddHom_tmul (f : M →+ N →+ P)
(hf : ∀ (r : R) (m : M) (n : N), f (r • m) n = f m (r • n)) (m : M) (n : N) :
liftAddHom f hf (m ⊗ₜ n) = f m n :=
rfl
variable (M)
@[simp]
theorem zero_tmul (n : N) : (0 : M) ⊗ₜ[R] n = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_left _
#align tensor_product.zero_tmul TensorProduct.zero_tmul
variable {M}
theorem add_tmul (m₁ m₂ : M) (n : N) : (m₁ + m₂) ⊗ₜ n = m₁ ⊗ₜ n + m₂ ⊗ₜ[R] n :=
Eq.symm <| Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_add_left _ _ _
#align tensor_product.add_tmul TensorProduct.add_tmul
variable (N)
@[simp]
theorem tmul_zero (m : M) : m ⊗ₜ[R] (0 : N) = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_right _
#align tensor_product.tmul_zero TensorProduct.tmul_zero
variable {N}
theorem tmul_add (m : M) (n₁ n₂ : N) : m ⊗ₜ (n₁ + n₂) = m ⊗ₜ n₁ + m ⊗ₜ[R] n₂ :=
Eq.symm <| Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_add_right _ _ _
#align tensor_product.tmul_add TensorProduct.tmul_add
instance uniqueLeft [Subsingleton M] : Unique (M ⊗[R] N) where
default := 0
uniq z := z.induction_on rfl (fun x y ↦ by rw [Subsingleton.elim x 0, zero_tmul]; rfl) <| by
rintro _ _ rfl rfl; apply add_zero
instance uniqueRight [Subsingleton N] : Unique (M ⊗[R] N) where
default := 0
uniq z := z.induction_on rfl (fun x y ↦ by rw [Subsingleton.elim y 0, tmul_zero]; rfl) <| by
rintro _ _ rfl rfl; apply add_zero
section
variable (R R' M N)
/-- A typeclass for `SMul` structures which can be moved across a tensor product.
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
`R` does not support negation.
Note that `Module R' (M ⊗[R] N)` is available even without this typeclass on `R'`; it's only
needed if `TensorProduct.smul_tmul`, `TensorProduct.smul_tmul'`, or `TensorProduct.tmul_smul` is
used.
-/
class CompatibleSMul [DistribMulAction R' N] : Prop where
smul_tmul : ∀ (r : R') (m : M) (n : N), (r • m) ⊗ₜ n = m ⊗ₜ[R] (r • n)
#align tensor_product.compatible_smul TensorProduct.CompatibleSMul
end
/-- Note that this provides the default `compatible_smul R R M N` instance through
`IsScalarTower.left`. -/
instance (priority := 100) CompatibleSMul.isScalarTower [SMul R' R] [IsScalarTower R' R M]
[DistribMulAction R' N] [IsScalarTower R' R N] : CompatibleSMul R R' M N :=
⟨fun r m n => by
conv_lhs => rw [← one_smul R m]
conv_rhs => rw [← one_smul R n]
rw [← smul_assoc, ← smul_assoc]
exact Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_smul _ _ _⟩
#align tensor_product.compatible_smul.is_scalar_tower TensorProduct.CompatibleSMul.isScalarTower
/-- `smul` can be moved from one side of the product to the other . -/
theorem smul_tmul [DistribMulAction R' N] [CompatibleSMul R R' M N] (r : R') (m : M) (n : N) :
(r • m) ⊗ₜ n = m ⊗ₜ[R] (r • n) :=
CompatibleSMul.smul_tmul _ _ _
#align tensor_product.smul_tmul TensorProduct.smul_tmul
-- Porting note: This is added as a local instance for `SMul.aux`.
-- For some reason type-class inference in Lean 3 unfolded this definition.
private def addMonoidWithWrongNSMul : AddMonoid (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with }
attribute [local instance] addMonoidWithWrongNSMul in
/-- Auxiliary function to defining scalar multiplication on tensor product. -/
def SMul.aux {R' : Type*} [SMul R' M] (r : R') : FreeAddMonoid (M × N) →+ M ⊗[R] N :=
FreeAddMonoid.lift fun p : M × N => (r • p.1) ⊗ₜ p.2
#align tensor_product.smul.aux TensorProduct.SMul.aux
theorem SMul.aux_of {R' : Type*} [SMul R' M] (r : R') (m : M) (n : N) :
SMul.aux r (.of (m, n)) = (r • m) ⊗ₜ[R] n :=
rfl
#align tensor_product.smul.aux_of TensorProduct.SMul.aux_of
variable [SMulCommClass R R' M] [SMulCommClass R R'' M]
/-- Given two modules over a commutative semiring `R`, if one of the factors carries a
(distributive) action of a second type of scalars `R'`, which commutes with the action of `R`, then
the tensor product (over `R`) carries an action of `R'`.
This instance defines this `R'` action in the case that it is the left module which has the `R'`
action. Two natural ways in which this situation arises are:
* Extension of scalars
* A tensor product of a group representation with a module not carrying an action
Note that in the special case that `R = R'`, since `R` is commutative, we just get the usual scalar
action on a tensor product of two modules. This special case is important enough that, for
performance reasons, we define it explicitly below. -/
instance leftHasSMul : SMul R' (M ⊗[R] N) :=
⟨fun r =>
(addConGen (TensorProduct.Eqv R M N)).lift (SMul.aux r : _ →+ M ⊗[R] N) <|
AddCon.addConGen_le fun x y hxy =>
match x, y, hxy with
| _, _, .of_zero_left n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, SMul.aux_of, smul_zero, zero_tmul]
| _, _, .of_zero_right m =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, SMul.aux_of, tmul_zero]
| _, _, .of_add_left m₁ m₂ n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, SMul.aux_of, smul_add, add_tmul]
| _, _, .of_add_right m n₁ n₂ =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, SMul.aux_of, tmul_add]
| _, _, .of_smul s m n =>
(AddCon.ker_rel _).2 <| by rw [SMul.aux_of, SMul.aux_of, ← smul_comm, smul_tmul]
| _, _, .add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, add_comm]⟩
#align tensor_product.left_has_smul TensorProduct.leftHasSMul
instance : SMul R (M ⊗[R] N) :=
TensorProduct.leftHasSMul
protected theorem smul_zero (r : R') : r • (0 : M ⊗[R] N) = 0 :=
AddMonoidHom.map_zero _
#align tensor_product.smul_zero TensorProduct.smul_zero
protected theorem smul_add (r : R') (x y : M ⊗[R] N) : r • (x + y) = r • x + r • y :=
AddMonoidHom.map_add _ _ _
#align tensor_product.smul_add TensorProduct.smul_add
protected theorem zero_smul (x : M ⊗[R] N) : (0 : R'') • x = 0 :=
have : ∀ (r : R'') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by rw [TensorProduct.smul_zero])
(fun m n => by rw [this, zero_smul, zero_tmul]) fun x y ihx ihy => by
rw [TensorProduct.smul_add, ihx, ihy, add_zero]
#align tensor_product.zero_smul TensorProduct.zero_smul
protected theorem one_smul (x : M ⊗[R] N) : (1 : R') • x = x :=
have : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by rw [TensorProduct.smul_zero])
(fun m n => by rw [this, one_smul])
fun x y ihx ihy => by rw [TensorProduct.smul_add, ihx, ihy]
#align tensor_product.one_smul TensorProduct.one_smul
protected theorem add_smul (r s : R'') (x : M ⊗[R] N) : (r + s) • x = r • x + s • x :=
have : ∀ (r : R'') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by simp_rw [TensorProduct.smul_zero, add_zero])
(fun m n => by simp_rw [this, add_smul, add_tmul]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]
rw [ihx, ihy, add_add_add_comm]
#align tensor_product.add_smul TensorProduct.add_smul
instance addMonoid : AddMonoid (M ⊗[R] N) :=
{ TensorProduct.addZeroClass _ _ with
toAddSemigroup := TensorProduct.addSemigroup _ _
toZero := (TensorProduct.addZeroClass _ _).toZero
nsmul := fun n v => n • v
nsmul_zero := by simp [TensorProduct.zero_smul]
nsmul_succ := by simp only [TensorProduct.one_smul, TensorProduct.add_smul, add_comm,
forall_const] }
instance addCommMonoid : AddCommMonoid (M ⊗[R] N) :=
{ TensorProduct.addCommSemigroup _ _ with
toAddMonoid := TensorProduct.addMonoid }
instance leftDistribMulAction : DistribMulAction R' (M ⊗[R] N) :=
have : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
{ smul_add := fun r x y => TensorProduct.smul_add r x y
mul_smul := fun r s x =>
x.induction_on (by simp_rw [TensorProduct.smul_zero])
(fun m n => by simp_rw [this, mul_smul]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]
rw [ihx, ihy]
one_smul := TensorProduct.one_smul
smul_zero := TensorProduct.smul_zero }
#align tensor_product.left_distrib_mul_action TensorProduct.leftDistribMulAction
instance : DistribMulAction R (M ⊗[R] N) :=
TensorProduct.leftDistribMulAction
theorem smul_tmul' (r : R') (m : M) (n : N) : r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n :=
rfl
#align tensor_product.smul_tmul' TensorProduct.smul_tmul'
@[simp]
theorem tmul_smul [DistribMulAction R' N] [CompatibleSMul R R' M N] (r : R') (x : M) (y : N) :
x ⊗ₜ (r • y) = r • x ⊗ₜ[R] y :=
(smul_tmul _ _ _).symm
#align tensor_product.tmul_smul TensorProduct.tmul_smul
theorem smul_tmul_smul (r s : R) (m : M) (n : N) : (r • m) ⊗ₜ[R] (s • n) = (r * s) • m ⊗ₜ[R] n := by
simp_rw [smul_tmul, tmul_smul, mul_smul]
#align tensor_product.smul_tmul_smul TensorProduct.smul_tmul_smul
instance leftModule : Module R'' (M ⊗[R] N) :=
{ add_smul := TensorProduct.add_smul
zero_smul := TensorProduct.zero_smul }
#align tensor_product.left_module TensorProduct.leftModule
instance : Module R (M ⊗[R] N) :=
TensorProduct.leftModule
instance [Module R''ᵐᵒᵖ M] [IsCentralScalar R'' M] : IsCentralScalar R'' (M ⊗[R] N) where
op_smul_eq_smul r x :=
x.induction_on (by rw [smul_zero, smul_zero])
(fun x y => by rw [smul_tmul', smul_tmul', op_smul_eq_smul]) fun x y hx hy => by
rw [smul_add, smul_add, hx, hy]
section
-- Like `R'`, `R'₂` provides a `DistribMulAction R'₂ (M ⊗[R] N)`
variable {R'₂ : Type*} [Monoid R'₂] [DistribMulAction R'₂ M]
variable [SMulCommClass R R'₂ M]
/-- `SMulCommClass R' R'₂ M` implies `SMulCommClass R' R'₂ (M ⊗[R] N)` -/
instance smulCommClass_left [SMulCommClass R' R'₂ M] : SMulCommClass R' R'₂ (M ⊗[R] N) where
smul_comm r' r'₂ x :=
TensorProduct.induction_on x (by simp_rw [TensorProduct.smul_zero])
(fun m n => by simp_rw [smul_tmul', smul_comm]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]; rw [ihx, ihy]
#align tensor_product.smul_comm_class_left TensorProduct.smulCommClass_left
variable [SMul R'₂ R']
/-- `IsScalarTower R'₂ R' M` implies `IsScalarTower R'₂ R' (M ⊗[R] N)` -/
instance isScalarTower_left [IsScalarTower R'₂ R' M] : IsScalarTower R'₂ R' (M ⊗[R] N) :=
⟨fun s r x =>
x.induction_on (by simp)
(fun m n => by rw [smul_tmul', smul_tmul', smul_tmul', smul_assoc]) fun x y ihx ihy => by
rw [smul_add, smul_add, smul_add, ihx, ihy]⟩
#align tensor_product.is_scalar_tower_left TensorProduct.isScalarTower_left
variable [DistribMulAction R'₂ N] [DistribMulAction R' N]
variable [CompatibleSMul R R'₂ M N] [CompatibleSMul R R' M N]
/-- `IsScalarTower R'₂ R' N` implies `IsScalarTower R'₂ R' (M ⊗[R] N)` -/
instance isScalarTower_right [IsScalarTower R'₂ R' N] : IsScalarTower R'₂ R' (M ⊗[R] N) :=
⟨fun s r x =>
x.induction_on (by simp)
(fun m n => by rw [← tmul_smul, ← tmul_smul, ← tmul_smul, smul_assoc]) fun x y ihx ihy => by
rw [smul_add, smul_add, smul_add, ihx, ihy]⟩
#align tensor_product.is_scalar_tower_right TensorProduct.isScalarTower_right
end
/-- A short-cut instance for the common case, where the requirements for the `compatible_smul`
instances are sufficient. -/
instance isScalarTower [SMul R' R] [IsScalarTower R' R M] : IsScalarTower R' R (M ⊗[R] N) :=
TensorProduct.isScalarTower_left
#align tensor_product.is_scalar_tower TensorProduct.isScalarTower
-- or right
variable (R M N)
/-- The canonical bilinear map `M → N → M ⊗[R] N`. -/
def mk : M →ₗ[R] N →ₗ[R] M ⊗[R] N :=
LinearMap.mk₂ R (· ⊗ₜ ·) add_tmul (fun c m n => by simp_rw [smul_tmul, tmul_smul])
tmul_add tmul_smul
#align tensor_product.mk TensorProduct.mk
variable {R M N}
@[simp]
theorem mk_apply (m : M) (n : N) : mk R M N m n = m ⊗ₜ n :=
rfl
#align tensor_product.mk_apply TensorProduct.mk_apply
theorem ite_tmul (x₁ : M) (x₂ : N) (P : Prop) [Decidable P] :
(if P then x₁ else 0) ⊗ₜ[R] x₂ = if P then x₁ ⊗ₜ x₂ else 0 := by split_ifs <;> simp
#align tensor_product.ite_tmul TensorProduct.ite_tmul
theorem tmul_ite (x₁ : M) (x₂ : N) (P : Prop) [Decidable P] :
(x₁ ⊗ₜ[R] if P then x₂ else 0) = if P then x₁ ⊗ₜ x₂ else 0 := by split_ifs <;> simp
#align tensor_product.tmul_ite TensorProduct.tmul_ite
section
theorem sum_tmul {α : Type*} (s : Finset α) (m : α → M) (n : N) :
(∑ a ∈ s, m a) ⊗ₜ[R] n = ∑ a ∈ s, m a ⊗ₜ[R] n := by
classical
induction' s using Finset.induction with a s has ih h
· simp
· simp [Finset.sum_insert has, add_tmul, ih]
#align tensor_product.sum_tmul TensorProduct.sum_tmul
theorem tmul_sum (m : M) {α : Type*} (s : Finset α) (n : α → N) :
(m ⊗ₜ[R] ∑ a ∈ s, n a) = ∑ a ∈ s, m ⊗ₜ[R] n a := by
classical
induction' s using Finset.induction with a s has ih h
· simp
· simp [Finset.sum_insert has, tmul_add, ih]
#align tensor_product.tmul_sum TensorProduct.tmul_sum
end
variable (R M N)
/-- The simple (aka pure) elements span the tensor product. -/
theorem span_tmul_eq_top : Submodule.span R { t : M ⊗[R] N | ∃ m n, m ⊗ₜ n = t } = ⊤ := by
ext t; simp only [Submodule.mem_top, iff_true_iff]
refine t.induction_on ?_ ?_ ?_
· exact Submodule.zero_mem _
· intro m n
apply Submodule.subset_span
use m, n
· intro t₁ t₂ ht₁ ht₂
exact Submodule.add_mem _ ht₁ ht₂
#align tensor_product.span_tmul_eq_top TensorProduct.span_tmul_eq_top
@[simp]
| Mathlib/LinearAlgebra/TensorProduct/Basic.lean | 494 | 496 | theorem map₂_mk_top_top_eq_top : Submodule.map₂ (mk R M N) ⊤ ⊤ = ⊤ := by |
rw [← top_le_iff, ← span_tmul_eq_top, Submodule.map₂_eq_span_image2]
exact Submodule.span_mono fun _ ⟨m, n, h⟩ => ⟨m, trivial, n, trivial, h⟩
|
/-
Copyright (c) 2021 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Damiano Testa, Jens Wagemaker
-/
import Mathlib.Algebra.MonoidAlgebra.Division
import Mathlib.Algebra.Polynomial.Degree.Definitions
import Mathlib.Algebra.Polynomial.Induction
import Mathlib.Algebra.Polynomial.EraseLead
import Mathlib.Order.Interval.Finset.Nat
#align_import data.polynomial.inductions from "leanprover-community/mathlib"@"57e09a1296bfb4330ddf6624f1028ba186117d82"
/-!
# Induction on polynomials
This file contains lemmas dealing with different flavours of induction on polynomials.
-/
noncomputable section
open Polynomial
open Finset
namespace Polynomial
universe u v w z
variable {R : Type u} {S : Type v} {T : Type w} {A : Type z} {a b : R} {n : ℕ}
section Semiring
variable [Semiring R] {p q : R[X]}
/-- `divX p` returns a polynomial `q` such that `q * X + C (p.coeff 0) = p`.
It can be used in a semiring where the usual division algorithm is not possible -/
def divX (p : R[X]) : R[X] :=
⟨AddMonoidAlgebra.divOf p.toFinsupp 1⟩
set_option linter.uppercaseLean3 false in
#align polynomial.div_X Polynomial.divX
@[simp]
theorem coeff_divX : (divX p).coeff n = p.coeff (n + 1) := by
rw [add_comm]; cases p; rfl
set_option linter.uppercaseLean3 false in
#align polynomial.coeff_div_X Polynomial.coeff_divX
theorem divX_mul_X_add (p : R[X]) : divX p * X + C (p.coeff 0) = p :=
ext <| by rintro ⟨_ | _⟩ <;> simp [coeff_C, Nat.succ_ne_zero, coeff_mul_X]
set_option linter.uppercaseLean3 false in
#align polynomial.div_X_mul_X_add Polynomial.divX_mul_X_add
@[simp]
theorem X_mul_divX_add (p : R[X]) : X * divX p + C (p.coeff 0) = p :=
ext <| by rintro ⟨_ | _⟩ <;> simp [coeff_C, Nat.succ_ne_zero, coeff_mul_X]
@[simp]
theorem divX_C (a : R) : divX (C a) = 0 :=
ext fun n => by simp [coeff_divX, coeff_C, Finsupp.single_eq_of_ne _]
set_option linter.uppercaseLean3 false in
#align polynomial.div_X_C Polynomial.divX_C
theorem divX_eq_zero_iff : divX p = 0 ↔ p = C (p.coeff 0) :=
⟨fun h => by simpa [eq_comm, h] using divX_mul_X_add p, fun h => by rw [h, divX_C]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.div_X_eq_zero_iff Polynomial.divX_eq_zero_iff
theorem divX_add : divX (p + q) = divX p + divX q :=
ext <| by simp
set_option linter.uppercaseLean3 false in
#align polynomial.div_X_add Polynomial.divX_add
@[simp]
theorem divX_zero : divX (0 : R[X]) = 0 := leadingCoeff_eq_zero.mp rfl
@[simp]
theorem divX_one : divX (1 : R[X]) = 0 := by
ext
simpa only [coeff_divX, coeff_zero] using coeff_one
@[simp]
theorem divX_C_mul : divX (C a * p) = C a * divX p := by
ext
simp
theorem divX_X_pow : divX (X ^ n : R[X]) = if (n = 0) then 0 else X ^ (n - 1) := by
cases n
· simp
· ext n
simp [coeff_X_pow]
/-- `divX` as an additive homomorphism. -/
noncomputable
def divX_hom : R[X] →+ R[X] :=
{ toFun := divX
map_zero' := divX_zero
map_add' := fun _ _ => divX_add }
@[simp] theorem divX_hom_toFun : divX_hom p = divX p := rfl
theorem natDegree_divX_eq_natDegree_tsub_one : p.divX.natDegree = p.natDegree - 1 := by
apply map_natDegree_eq_sub (φ := divX_hom)
· intro f
simpa [divX_hom, divX_eq_zero_iff] using eq_C_of_natDegree_eq_zero
· intros n c c0
rw [← C_mul_X_pow_eq_monomial, divX_hom_toFun, divX_C_mul, divX_X_pow]
split_ifs with n0
· simp [n0]
· exact natDegree_C_mul_X_pow (n - 1) c c0
theorem natDegree_divX_le : p.divX.natDegree ≤ p.natDegree :=
natDegree_divX_eq_natDegree_tsub_one.trans_le (Nat.pred_le _)
theorem divX_C_mul_X_pow : divX (C a * X ^ n) = if n = 0 then 0 else C a * X ^ (n - 1) := by
simp only [divX_C_mul, divX_X_pow, mul_ite, mul_zero]
| Mathlib/Algebra/Polynomial/Inductions.lean | 119 | 143 | theorem degree_divX_lt (hp0 : p ≠ 0) : (divX p).degree < p.degree := by |
haveI := Nontrivial.of_polynomial_ne hp0
calc
degree (divX p) < (divX p * X + C (p.coeff 0)).degree :=
if h : degree p ≤ 0 then by
have h' : C (p.coeff 0) ≠ 0 := by rwa [← eq_C_of_degree_le_zero h]
rw [eq_C_of_degree_le_zero h, divX_C, degree_zero, zero_mul, zero_add]
exact lt_of_le_of_ne bot_le (Ne.symm (mt degree_eq_bot.1 <| by simpa using h'))
else by
have hXp0 : divX p ≠ 0 := by
simpa [divX_eq_zero_iff, -not_le, degree_le_zero_iff] using h
have : leadingCoeff (divX p) * leadingCoeff X ≠ 0 := by simpa
have : degree (C (p.coeff 0)) < degree (divX p * X) :=
calc
degree (C (p.coeff 0)) ≤ 0 := degree_C_le
_ < 1 := by decide
_ = degree (X : R[X]) := degree_X.symm
_ ≤ degree (divX p * X) := by
rw [← zero_add (degree X), degree_mul' this]
exact add_le_add
(by rw [zero_le_degree_iff, Ne, divX_eq_zero_iff]
exact fun h0 => h (h0.symm ▸ degree_C_le))
le_rfl
rw [degree_add_eq_left_of_degree_lt this]; exact degree_lt_degree_mul_X hXp0
_ = degree p := congr_arg _ (divX_mul_X_add _)
|
/-
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.Algebra.Homology.Linear
import Mathlib.Algebra.Homology.ShortComplex.HomologicalComplex
import Mathlib.Tactic.Abel
#align_import algebra.homology.homotopy from "leanprover-community/mathlib"@"618ea3d5c99240cd7000d8376924906a148bf9ff"
/-!
# Chain homotopies
We define chain homotopies, and prove that homotopic chain maps induce the same map on homology.
-/
universe v u
open scoped Classical
noncomputable section
open CategoryTheory Category Limits HomologicalComplex
variable {ι : Type*}
variable {V : Type u} [Category.{v} V] [Preadditive V]
variable {c : ComplexShape ι} {C D E : HomologicalComplex V c}
variable (f g : C ⟶ D) (h k : D ⟶ E) (i : ι)
section
/-- The composition of `C.d i (c.next i) ≫ f (c.next i) i`. -/
def dNext (i : ι) : (∀ i j, C.X i ⟶ D.X j) →+ (C.X i ⟶ D.X i) :=
AddMonoidHom.mk' (fun f => C.d i (c.next i) ≫ f (c.next i) i) fun _ _ =>
Preadditive.comp_add _ _ _ _ _ _
#align d_next dNext
/-- `f (c.next i) i`. -/
def fromNext (i : ι) : (∀ i j, C.X i ⟶ D.X j) →+ (C.xNext i ⟶ D.X i) :=
AddMonoidHom.mk' (fun f => f (c.next i) i) fun _ _ => rfl
#align from_next fromNext
@[simp]
theorem dNext_eq_dFrom_fromNext (f : ∀ i j, C.X i ⟶ D.X j) (i : ι) :
dNext i f = C.dFrom i ≫ fromNext i f :=
rfl
#align d_next_eq_d_from_from_next dNext_eq_dFrom_fromNext
theorem dNext_eq (f : ∀ i j, C.X i ⟶ D.X j) {i i' : ι} (w : c.Rel i i') :
dNext i f = C.d i i' ≫ f i' i := by
obtain rfl := c.next_eq' w
rfl
#align d_next_eq dNext_eq
lemma dNext_eq_zero (f : ∀ i j, C.X i ⟶ D.X j) (i : ι) (hi : ¬ c.Rel i (c.next i)) :
dNext i f = 0 := by
dsimp [dNext]
rw [shape _ _ _ hi, zero_comp]
@[simp 1100]
theorem dNext_comp_left (f : C ⟶ D) (g : ∀ i j, D.X i ⟶ E.X j) (i : ι) :
(dNext i fun i j => f.f i ≫ g i j) = f.f i ≫ dNext i g :=
(f.comm_assoc _ _ _).symm
#align d_next_comp_left dNext_comp_left
@[simp 1100]
theorem dNext_comp_right (f : ∀ i j, C.X i ⟶ D.X j) (g : D ⟶ E) (i : ι) :
(dNext i fun i j => f i j ≫ g.f j) = dNext i f ≫ g.f i :=
(assoc _ _ _).symm
#align d_next_comp_right dNext_comp_right
/-- The composition `f j (c.prev j) ≫ D.d (c.prev j) j`. -/
def prevD (j : ι) : (∀ i j, C.X i ⟶ D.X j) →+ (C.X j ⟶ D.X j) :=
AddMonoidHom.mk' (fun f => f j (c.prev j) ≫ D.d (c.prev j) j) fun _ _ =>
Preadditive.add_comp _ _ _ _ _ _
#align prev_d prevD
lemma prevD_eq_zero (f : ∀ i j, C.X i ⟶ D.X j) (i : ι) (hi : ¬ c.Rel (c.prev i) i) :
prevD i f = 0 := by
dsimp [prevD]
rw [shape _ _ _ hi, comp_zero]
/-- `f j (c.prev j)`. -/
def toPrev (j : ι) : (∀ i j, C.X i ⟶ D.X j) →+ (C.X j ⟶ D.xPrev j) :=
AddMonoidHom.mk' (fun f => f j (c.prev j)) fun _ _ => rfl
#align to_prev toPrev
@[simp]
theorem prevD_eq_toPrev_dTo (f : ∀ i j, C.X i ⟶ D.X j) (j : ι) :
prevD j f = toPrev j f ≫ D.dTo j :=
rfl
#align prev_d_eq_to_prev_d_to prevD_eq_toPrev_dTo
theorem prevD_eq (f : ∀ i j, C.X i ⟶ D.X j) {j j' : ι} (w : c.Rel j' j) :
prevD j f = f j j' ≫ D.d j' j := by
obtain rfl := c.prev_eq' w
rfl
#align prev_d_eq prevD_eq
@[simp 1100]
theorem prevD_comp_left (f : C ⟶ D) (g : ∀ i j, D.X i ⟶ E.X j) (j : ι) :
(prevD j fun i j => f.f i ≫ g i j) = f.f j ≫ prevD j g :=
assoc _ _ _
#align prev_d_comp_left prevD_comp_left
@[simp 1100]
theorem prevD_comp_right (f : ∀ i j, C.X i ⟶ D.X j) (g : D ⟶ E) (j : ι) :
(prevD j fun i j => f i j ≫ g.f j) = prevD j f ≫ g.f j := by
dsimp [prevD]
simp only [assoc, g.comm]
#align prev_d_comp_right prevD_comp_right
theorem dNext_nat (C D : ChainComplex V ℕ) (i : ℕ) (f : ∀ i j, C.X i ⟶ D.X j) :
dNext i f = C.d i (i - 1) ≫ f (i - 1) i := by
dsimp [dNext]
cases i
· simp only [shape, ChainComplex.next_nat_zero, ComplexShape.down_Rel, Nat.one_ne_zero,
not_false_iff, zero_comp]
· congr <;> simp
#align d_next_nat dNext_nat
theorem prevD_nat (C D : CochainComplex V ℕ) (i : ℕ) (f : ∀ i j, C.X i ⟶ D.X j) :
prevD i f = f i (i - 1) ≫ D.d (i - 1) i := by
dsimp [prevD]
cases i
· simp only [shape, CochainComplex.prev_nat_zero, ComplexShape.up_Rel, Nat.one_ne_zero,
not_false_iff, comp_zero]
· congr <;> simp
#align prev_d_nat prevD_nat
-- Porting note(#5171): removed @[has_nonempty_instance]
/-- A homotopy `h` between chain maps `f` and `g` consists of components `h i j : C.X i ⟶ D.X j`
which are zero unless `c.Rel j i`, satisfying the homotopy condition.
-/
@[ext]
structure Homotopy (f g : C ⟶ D) where
hom : ∀ i j, C.X i ⟶ D.X j
zero : ∀ i j, ¬c.Rel j i → hom i j = 0 := by aesop_cat
comm : ∀ i, f.f i = dNext i hom + prevD i hom + g.f i := by aesop_cat
#align homotopy Homotopy
variable {f g}
namespace Homotopy
/-- `f` is homotopic to `g` iff `f - g` is homotopic to `0`.
-/
def equivSubZero : Homotopy f g ≃ Homotopy (f - g) 0 where
toFun h :=
{ hom := fun i j => h.hom i j
zero := fun i j w => h.zero _ _ w
comm := fun i => by simp [h.comm] }
invFun h :=
{ hom := fun i j => h.hom i j
zero := fun i j w => h.zero _ _ w
comm := fun i => by simpa [sub_eq_iff_eq_add] using h.comm i }
left_inv := by aesop_cat
right_inv := by aesop_cat
#align homotopy.equiv_sub_zero Homotopy.equivSubZero
/-- Equal chain maps are homotopic. -/
@[simps]
def ofEq (h : f = g) : Homotopy f g where
hom := 0
zero _ _ _ := rfl
#align homotopy.of_eq Homotopy.ofEq
/-- Every chain map is homotopic to itself. -/
@[simps!, refl]
def refl (f : C ⟶ D) : Homotopy f f :=
ofEq (rfl : f = f)
#align homotopy.refl Homotopy.refl
/-- `f` is homotopic to `g` iff `g` is homotopic to `f`. -/
@[simps!, symm]
def symm {f g : C ⟶ D} (h : Homotopy f g) : Homotopy g f where
hom := -h.hom
zero i j w := by rw [Pi.neg_apply, Pi.neg_apply, h.zero i j w, neg_zero]
comm i := by
rw [AddMonoidHom.map_neg, AddMonoidHom.map_neg, h.comm, ← neg_add, ← add_assoc, neg_add_self,
zero_add]
#align homotopy.symm Homotopy.symm
/-- homotopy is a transitive relation. -/
@[simps!, trans]
def trans {e f g : C ⟶ D} (h : Homotopy e f) (k : Homotopy f g) : Homotopy e g where
hom := h.hom + k.hom
zero i j w := by rw [Pi.add_apply, Pi.add_apply, h.zero i j w, k.zero i j w, zero_add]
comm i := by
rw [AddMonoidHom.map_add, AddMonoidHom.map_add, h.comm, k.comm]
abel
#align homotopy.trans Homotopy.trans
/-- the sum of two homotopies is a homotopy between the sum of the respective morphisms. -/
@[simps!]
def add {f₁ g₁ f₂ g₂ : C ⟶ D} (h₁ : Homotopy f₁ g₁) (h₂ : Homotopy f₂ g₂) :
Homotopy (f₁ + f₂) (g₁ + g₂) where
hom := h₁.hom + h₂.hom
zero i j hij := by rw [Pi.add_apply, Pi.add_apply, h₁.zero i j hij, h₂.zero i j hij, add_zero]
comm i := by
simp only [HomologicalComplex.add_f_apply, h₁.comm, h₂.comm, AddMonoidHom.map_add]
abel
#align homotopy.add Homotopy.add
/-- the scalar multiplication of an homotopy -/
@[simps!]
def smul {R : Type*} [Semiring R] [Linear R V] (h : Homotopy f g) (a : R) :
Homotopy (a • f) (a • g) where
hom i j := a • h.hom i j
zero i j hij := by
dsimp
rw [h.zero i j hij, smul_zero]
comm i := by
dsimp
rw [h.comm]
dsimp [fromNext, toPrev]
simp only [smul_add, Linear.comp_smul, Linear.smul_comp]
/-- homotopy is closed under composition (on the right) -/
@[simps]
def compRight {e f : C ⟶ D} (h : Homotopy e f) (g : D ⟶ E) : Homotopy (e ≫ g) (f ≫ g) where
hom i j := h.hom i j ≫ g.f j
zero i j w := by dsimp; rw [h.zero i j w, zero_comp]
comm i := by rw [comp_f, h.comm i, dNext_comp_right, prevD_comp_right, Preadditive.add_comp,
comp_f, Preadditive.add_comp]
#align homotopy.comp_right Homotopy.compRight
/-- homotopy is closed under composition (on the left) -/
@[simps]
def compLeft {f g : D ⟶ E} (h : Homotopy f g) (e : C ⟶ D) : Homotopy (e ≫ f) (e ≫ g) where
hom i j := e.f i ≫ h.hom i j
zero i j w := by dsimp; rw [h.zero i j w, comp_zero]
comm i := by rw [comp_f, h.comm i, dNext_comp_left, prevD_comp_left, comp_f,
Preadditive.comp_add, Preadditive.comp_add]
#align homotopy.comp_left Homotopy.compLeft
/-- homotopy is closed under composition -/
@[simps!]
def comp {C₁ C₂ C₃ : HomologicalComplex V c} {f₁ g₁ : C₁ ⟶ C₂} {f₂ g₂ : C₂ ⟶ C₃}
(h₁ : Homotopy f₁ g₁) (h₂ : Homotopy f₂ g₂) : Homotopy (f₁ ≫ f₂) (g₁ ≫ g₂) :=
(h₁.compRight _).trans (h₂.compLeft _)
#align homotopy.comp Homotopy.comp
/-- a variant of `Homotopy.compRight` useful for dealing with homotopy equivalences. -/
@[simps!]
def compRightId {f : C ⟶ C} (h : Homotopy f (𝟙 C)) (g : C ⟶ D) : Homotopy (f ≫ g) g :=
(h.compRight g).trans (ofEq <| id_comp _)
#align homotopy.comp_right_id Homotopy.compRightId
/-- a variant of `Homotopy.compLeft` useful for dealing with homotopy equivalences. -/
@[simps!]
def compLeftId {f : D ⟶ D} (h : Homotopy f (𝟙 D)) (g : C ⟶ D) : Homotopy (g ≫ f) g :=
(h.compLeft g).trans (ofEq <| comp_id _)
#align homotopy.comp_left_id Homotopy.compLeftId
/-!
Null homotopic maps can be constructed using the formula `hd+dh`. We show that
these morphisms are homotopic to `0` and provide some convenient simplification
lemmas that give a degreewise description of `hd+dh`, depending on whether we have
two differentials going to and from a certain degree, only one, or none.
-/
/-- The null homotopic map associated to a family `hom` of morphisms `C_i ⟶ D_j`.
This is the same datum as for the field `hom` in the structure `Homotopy`. For
this definition, we do not need the field `zero` of that structure
as this definition uses only the maps `C_i ⟶ C_j` when `c.Rel j i`. -/
def nullHomotopicMap (hom : ∀ i j, C.X i ⟶ D.X j) : C ⟶ D where
f i := dNext i hom + prevD i hom
comm' i j hij := by
have eq1 : prevD i hom ≫ D.d i j = 0 := by
simp only [prevD, AddMonoidHom.mk'_apply, assoc, d_comp_d, comp_zero]
have eq2 : C.d i j ≫ dNext j hom = 0 := by
simp only [dNext, AddMonoidHom.mk'_apply, d_comp_d_assoc, zero_comp]
dsimp only
rw [dNext_eq hom hij, prevD_eq hom hij, Preadditive.comp_add, Preadditive.add_comp, eq1, eq2,
add_zero, zero_add, assoc]
#align homotopy.null_homotopic_map Homotopy.nullHomotopicMap
/-- Variant of `nullHomotopicMap` where the input consists only of the
relevant maps `C_i ⟶ D_j` such that `c.Rel j i`. -/
def nullHomotopicMap' (h : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) : C ⟶ D :=
nullHomotopicMap fun i j => dite (c.Rel j i) (h i j) fun _ => 0
#align homotopy.null_homotopic_map' Homotopy.nullHomotopicMap'
/-- Compatibility of `nullHomotopicMap` with the postcomposition by a morphism
of complexes. -/
theorem nullHomotopicMap_comp (hom : ∀ i j, C.X i ⟶ D.X j) (g : D ⟶ E) :
nullHomotopicMap hom ≫ g = nullHomotopicMap fun i j => hom i j ≫ g.f j := by
ext n
dsimp [nullHomotopicMap, fromNext, toPrev, AddMonoidHom.mk'_apply]
simp only [Preadditive.add_comp, assoc, g.comm]
#align homotopy.null_homotopic_map_comp Homotopy.nullHomotopicMap_comp
/-- Compatibility of `nullHomotopicMap'` with the postcomposition by a morphism
of complexes. -/
theorem nullHomotopicMap'_comp (hom : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) (g : D ⟶ E) :
nullHomotopicMap' hom ≫ g = nullHomotopicMap' fun i j hij => hom i j hij ≫ g.f j := by
ext n
erw [nullHomotopicMap_comp]
congr
ext i j
split_ifs
· rfl
· rw [zero_comp]
#align homotopy.null_homotopic_map'_comp Homotopy.nullHomotopicMap'_comp
/-- Compatibility of `nullHomotopicMap` with the precomposition by a morphism
of complexes. -/
theorem comp_nullHomotopicMap (f : C ⟶ D) (hom : ∀ i j, D.X i ⟶ E.X j) :
f ≫ nullHomotopicMap hom = nullHomotopicMap fun i j => f.f i ≫ hom i j := by
ext n
dsimp [nullHomotopicMap, fromNext, toPrev, AddMonoidHom.mk'_apply]
simp only [Preadditive.comp_add, assoc, f.comm_assoc]
#align homotopy.comp_null_homotopic_map Homotopy.comp_nullHomotopicMap
/-- Compatibility of `nullHomotopicMap'` with the precomposition by a morphism
of complexes. -/
theorem comp_nullHomotopicMap' (f : C ⟶ D) (hom : ∀ i j, c.Rel j i → (D.X i ⟶ E.X j)) :
f ≫ nullHomotopicMap' hom = nullHomotopicMap' fun i j hij => f.f i ≫ hom i j hij := by
ext n
erw [comp_nullHomotopicMap]
congr
ext i j
split_ifs
· rfl
· rw [comp_zero]
#align homotopy.comp_null_homotopic_map' Homotopy.comp_nullHomotopicMap'
/-- Compatibility of `nullHomotopicMap` with the application of additive functors -/
theorem map_nullHomotopicMap {W : Type*} [Category W] [Preadditive W] (G : V ⥤ W) [G.Additive]
(hom : ∀ i j, C.X i ⟶ D.X j) :
(G.mapHomologicalComplex c).map (nullHomotopicMap hom) =
nullHomotopicMap (fun i j => by exact G.map (hom i j)) := by
ext i
dsimp [nullHomotopicMap, dNext, prevD]
simp only [G.map_comp, Functor.map_add]
#align homotopy.map_null_homotopic_map Homotopy.map_nullHomotopicMap
/-- Compatibility of `nullHomotopicMap'` with the application of additive functors -/
theorem map_nullHomotopicMap' {W : Type*} [Category W] [Preadditive W] (G : V ⥤ W) [G.Additive]
(hom : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) :
(G.mapHomologicalComplex c).map (nullHomotopicMap' hom) =
nullHomotopicMap' fun i j hij => by exact G.map (hom i j hij) := by
ext n
erw [map_nullHomotopicMap]
congr
ext i j
split_ifs
· rfl
· rw [G.map_zero]
#align homotopy.map_null_homotopic_map' Homotopy.map_nullHomotopicMap'
/-- Tautological construction of the `Homotopy` to zero for maps constructed by
`nullHomotopicMap`, at least when we have the `zero` condition. -/
@[simps]
def nullHomotopy (hom : ∀ i j, C.X i ⟶ D.X j) (zero : ∀ i j, ¬c.Rel j i → hom i j = 0) :
Homotopy (nullHomotopicMap hom) 0 :=
{ hom := hom
zero := zero
comm := by
intro i
rw [HomologicalComplex.zero_f_apply, add_zero]
rfl }
#align homotopy.null_homotopy Homotopy.nullHomotopy
/-- Homotopy to zero for maps constructed with `nullHomotopicMap'` -/
@[simps!]
def nullHomotopy' (h : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) : Homotopy (nullHomotopicMap' h) 0 := by
apply nullHomotopy fun i j => dite (c.Rel j i) (h i j) fun _ => 0
intro i j hij
rw [dite_eq_right_iff]
intro hij'
exfalso
exact hij hij'
#align homotopy.null_homotopy' Homotopy.nullHomotopy'
/-! This lemma and the following ones can be used in order to compute
the degreewise morphisms induced by the null homotopic maps constructed
with `nullHomotopicMap` or `nullHomotopicMap'` -/
@[simp]
theorem nullHomotopicMap_f {k₂ k₁ k₀ : ι} (r₂₁ : c.Rel k₂ k₁) (r₁₀ : c.Rel k₁ k₀)
(hom : ∀ i j, C.X i ⟶ D.X j) :
(nullHomotopicMap hom).f k₁ = C.d k₁ k₀ ≫ hom k₀ k₁ + hom k₁ k₂ ≫ D.d k₂ k₁ := by
dsimp only [nullHomotopicMap]
rw [dNext_eq hom r₁₀, prevD_eq hom r₂₁]
#align homotopy.null_homotopic_map_f Homotopy.nullHomotopicMap_f
@[simp]
theorem nullHomotopicMap'_f {k₂ k₁ k₀ : ι} (r₂₁ : c.Rel k₂ k₁) (r₁₀ : c.Rel k₁ k₀)
(h : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) :
(nullHomotopicMap' h).f k₁ = C.d k₁ k₀ ≫ h k₀ k₁ r₁₀ + h k₁ k₂ r₂₁ ≫ D.d k₂ k₁ := by
simp only [nullHomotopicMap']
rw [nullHomotopicMap_f r₂₁ r₁₀]
split_ifs
rfl
#align homotopy.null_homotopic_map'_f Homotopy.nullHomotopicMap'_f
@[simp]
theorem nullHomotopicMap_f_of_not_rel_left {k₁ k₀ : ι} (r₁₀ : c.Rel k₁ k₀)
(hk₀ : ∀ l : ι, ¬c.Rel k₀ l) (hom : ∀ i j, C.X i ⟶ D.X j) :
(nullHomotopicMap hom).f k₀ = hom k₀ k₁ ≫ D.d k₁ k₀ := by
dsimp only [nullHomotopicMap]
rw [prevD_eq hom r₁₀, dNext, AddMonoidHom.mk'_apply, C.shape, zero_comp, zero_add]
exact hk₀ _
#align homotopy.null_homotopic_map_f_of_not_rel_left Homotopy.nullHomotopicMap_f_of_not_rel_left
@[simp]
theorem nullHomotopicMap'_f_of_not_rel_left {k₁ k₀ : ι} (r₁₀ : c.Rel k₁ k₀)
(hk₀ : ∀ l : ι, ¬c.Rel k₀ l) (h : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) :
(nullHomotopicMap' h).f k₀ = h k₀ k₁ r₁₀ ≫ D.d k₁ k₀ := by
simp only [nullHomotopicMap']
rw [nullHomotopicMap_f_of_not_rel_left r₁₀ hk₀]
split_ifs
rfl
#align homotopy.null_homotopic_map'_f_of_not_rel_left Homotopy.nullHomotopicMap'_f_of_not_rel_left
@[simp]
theorem nullHomotopicMap_f_of_not_rel_right {k₁ k₀ : ι} (r₁₀ : c.Rel k₁ k₀)
(hk₁ : ∀ l : ι, ¬c.Rel l k₁) (hom : ∀ i j, C.X i ⟶ D.X j) :
(nullHomotopicMap hom).f k₁ = C.d k₁ k₀ ≫ hom k₀ k₁ := by
dsimp only [nullHomotopicMap]
rw [dNext_eq hom r₁₀, prevD, AddMonoidHom.mk'_apply, D.shape, comp_zero, add_zero]
exact hk₁ _
#align homotopy.null_homotopic_map_f_of_not_rel_right Homotopy.nullHomotopicMap_f_of_not_rel_right
@[simp]
theorem nullHomotopicMap'_f_of_not_rel_right {k₁ k₀ : ι} (r₁₀ : c.Rel k₁ k₀)
(hk₁ : ∀ l : ι, ¬c.Rel l k₁) (h : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) :
(nullHomotopicMap' h).f k₁ = C.d k₁ k₀ ≫ h k₀ k₁ r₁₀ := by
simp only [nullHomotopicMap']
rw [nullHomotopicMap_f_of_not_rel_right r₁₀ hk₁]
split_ifs
rfl
#align homotopy.null_homotopic_map'_f_of_not_rel_right Homotopy.nullHomotopicMap'_f_of_not_rel_right
@[simp]
theorem nullHomotopicMap_f_eq_zero {k₀ : ι} (hk₀ : ∀ l : ι, ¬c.Rel k₀ l)
(hk₀' : ∀ l : ι, ¬c.Rel l k₀) (hom : ∀ i j, C.X i ⟶ D.X j) :
(nullHomotopicMap hom).f k₀ = 0 := by
dsimp [nullHomotopicMap, dNext, prevD]
rw [C.shape, D.shape, zero_comp, comp_zero, add_zero] <;> apply_assumption
#align homotopy.null_homotopic_map_f_eq_zero Homotopy.nullHomotopicMap_f_eq_zero
@[simp]
theorem nullHomotopicMap'_f_eq_zero {k₀ : ι} (hk₀ : ∀ l : ι, ¬c.Rel k₀ l)
(hk₀' : ∀ l : ι, ¬c.Rel l k₀) (h : ∀ i j, c.Rel j i → (C.X i ⟶ D.X j)) :
(nullHomotopicMap' h).f k₀ = 0 := by
simp only [nullHomotopicMap']
apply nullHomotopicMap_f_eq_zero hk₀ hk₀'
#align homotopy.null_homotopic_map'_f_eq_zero Homotopy.nullHomotopicMap'_f_eq_zero
/-!
`Homotopy.mkInductive` allows us to build a homotopy of chain complexes inductively,
so that as we construct each component, we have available the previous two components,
and the fact that they satisfy the homotopy condition.
To simplify the situation, we only construct homotopies of the form `Homotopy e 0`.
`Homotopy.equivSubZero` can provide the general case.
Notice however, that this construction does not have particularly good definitional properties:
we have to insert `eqToHom` in several places.
Hopefully this is okay in most applications, where we only need to have the existence of some
homotopy.
-/
section MkInductive
variable {P Q : ChainComplex V ℕ}
@[simp 1100]
theorem prevD_chainComplex (f : ∀ i j, P.X i ⟶ Q.X j) (j : ℕ) :
prevD j f = f j (j + 1) ≫ Q.d _ _ := by
dsimp [prevD]
have : (ComplexShape.down ℕ).prev j = j + 1 := ChainComplex.prev ℕ j
congr 2
#align homotopy.prev_d_chain_complex Homotopy.prevD_chainComplex
@[simp 1100]
theorem dNext_succ_chainComplex (f : ∀ i j, P.X i ⟶ Q.X j) (i : ℕ) :
dNext (i + 1) f = P.d _ _ ≫ f i (i + 1) := by
dsimp [dNext]
have : (ComplexShape.down ℕ).next (i + 1) = i := ChainComplex.next_nat_succ _
congr 2
#align homotopy.d_next_succ_chain_complex Homotopy.dNext_succ_chainComplex
@[simp 1100]
| Mathlib/Algebra/Homology/Homotopy.lean | 493 | 496 | theorem dNext_zero_chainComplex (f : ∀ i j, P.X i ⟶ Q.X j) : dNext 0 f = 0 := by |
dsimp [dNext]
rw [P.shape, zero_comp]
rw [ChainComplex.next_nat_zero]; dsimp; decide
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jeremy Avigad
-/
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Data.Set.Finite
#align_import order.filter.basic from "leanprover-community/mathlib"@"d4f691b9e5f94cfc64639973f3544c95f8d5d494"
/-!
# Theory of filters on sets
## Main definitions
* `Filter` : filters on a set;
* `Filter.principal` : filter of all sets containing a given set;
* `Filter.map`, `Filter.comap` : operations on filters;
* `Filter.Tendsto` : limit with respect to filters;
* `Filter.Eventually` : `f.eventually p` means `{x | p x} ∈ f`;
* `Filter.Frequently` : `f.frequently p` means `{x | ¬p x} ∉ f`;
* `filter_upwards [h₁, ..., hₙ]` :
a tactic that takes a list of proofs `hᵢ : sᵢ ∈ f`,
and replaces a goal `s ∈ f` with `∀ x, x ∈ s₁ → ... → x ∈ sₙ → x ∈ s`;
* `Filter.NeBot f` : a utility class stating that `f` is a non-trivial filter.
Filters on a type `X` are sets of sets of `X` satisfying three conditions. They are mostly used to
abstract two related kinds of ideas:
* *limits*, including finite or infinite limits of sequences, finite or infinite limits of functions
at a point or at infinity, etc...
* *things happening eventually*, including things happening for large enough `n : ℕ`, or near enough
a point `x`, or for close enough pairs of points, or things happening almost everywhere in the
sense of measure theory. Dually, filters can also express the idea of *things happening often*:
for arbitrarily large `n`, or at a point in any neighborhood of given a point etc...
In this file, we define the type `Filter X` of filters on `X`, and endow it with a complete lattice
structure. This structure is lifted from the lattice structure on `Set (Set X)` using the Galois
insertion which maps a filter to its elements in one direction, and an arbitrary set of sets to
the smallest filter containing it in the other direction.
We also prove `Filter` is a monadic functor, with a push-forward operation
`Filter.map` and a pull-back operation `Filter.comap` that form a Galois connections for the
order on filters.
The examples of filters appearing in the description of the two motivating ideas are:
* `(Filter.atTop : Filter ℕ)` : made of sets of `ℕ` containing `{n | n ≥ N}` for some `N`
* `𝓝 x` : made of neighborhoods of `x` in a topological space (defined in topology.basic)
* `𝓤 X` : made of entourages of a uniform space (those space are generalizations of metric spaces
defined in `Mathlib/Topology/UniformSpace/Basic.lean`)
* `MeasureTheory.ae` : made of sets whose complement has zero measure with respect to `μ`
(defined in `Mathlib/MeasureTheory/OuterMeasure/AE`)
The general notion of limit of a map with respect to filters on the source and target types
is `Filter.Tendsto`. It is defined in terms of the order and the push-forward operation.
The predicate "happening eventually" is `Filter.Eventually`, and "happening often" is
`Filter.Frequently`, whose definitions are immediate after `Filter` is defined (but they come
rather late in this file in order to immediately relate them to the lattice structure).
For instance, anticipating on Topology.Basic, the statement: "if a sequence `u` converges to
some `x` and `u n` belongs to a set `M` for `n` large enough then `x` is in the closure of
`M`" is formalized as: `Tendsto u atTop (𝓝 x) → (∀ᶠ n in atTop, u n ∈ M) → x ∈ closure M`,
which is a special case of `mem_closure_of_tendsto` from Topology.Basic.
## Notations
* `∀ᶠ x in f, p x` : `f.Eventually p`;
* `∃ᶠ x in f, p x` : `f.Frequently p`;
* `f =ᶠ[l] g` : `∀ᶠ x in l, f x = g x`;
* `f ≤ᶠ[l] g` : `∀ᶠ x in l, f x ≤ g x`;
* `𝓟 s` : `Filter.Principal s`, localized in `Filter`.
## References
* [N. Bourbaki, *General Topology*][bourbaki1966]
Important note: Bourbaki requires that a filter on `X` cannot contain all sets of `X`, which
we do *not* require. This gives `Filter X` better formal properties, in particular a bottom element
`⊥` for its lattice structure, at the cost of including the assumption
`[NeBot f]` in a number of lemmas and definitions.
-/
set_option autoImplicit true
open Function Set Order
open scoped Classical
universe u v w x y
/-- A filter `F` on a type `α` is a collection of sets of `α` which contains the whole `α`,
is upwards-closed, and is stable under intersection. We do not forbid this collection to be
all sets of `α`. -/
structure Filter (α : Type*) where
/-- The set of sets that belong to the filter. -/
sets : Set (Set α)
/-- The set `Set.univ` belongs to any filter. -/
univ_sets : Set.univ ∈ sets
/-- If a set belongs to a filter, then its superset belongs to the filter as well. -/
sets_of_superset {x y} : x ∈ sets → x ⊆ y → y ∈ sets
/-- If two sets belong to a filter, then their intersection belongs to the filter as well. -/
inter_sets {x y} : x ∈ sets → y ∈ sets → x ∩ y ∈ sets
#align filter Filter
/-- If `F` is a filter on `α`, and `U` a subset of `α` then we can write `U ∈ F` as on paper. -/
instance {α : Type*} : Membership (Set α) (Filter α) :=
⟨fun U F => U ∈ F.sets⟩
namespace Filter
variable {α : Type u} {f g : Filter α} {s t : Set α}
@[simp]
protected theorem mem_mk {t : Set (Set α)} {h₁ h₂ h₃} : s ∈ mk t h₁ h₂ h₃ ↔ s ∈ t :=
Iff.rfl
#align filter.mem_mk Filter.mem_mk
@[simp]
protected theorem mem_sets : s ∈ f.sets ↔ s ∈ f :=
Iff.rfl
#align filter.mem_sets Filter.mem_sets
instance inhabitedMem : Inhabited { s : Set α // s ∈ f } :=
⟨⟨univ, f.univ_sets⟩⟩
#align filter.inhabited_mem Filter.inhabitedMem
theorem filter_eq : ∀ {f g : Filter α}, f.sets = g.sets → f = g
| ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, rfl => rfl
#align filter.filter_eq Filter.filter_eq
theorem filter_eq_iff : f = g ↔ f.sets = g.sets :=
⟨congr_arg _, filter_eq⟩
#align filter.filter_eq_iff Filter.filter_eq_iff
protected theorem ext_iff : f = g ↔ ∀ s, s ∈ f ↔ s ∈ g := by
simp only [filter_eq_iff, ext_iff, Filter.mem_sets]
#align filter.ext_iff Filter.ext_iff
@[ext]
protected theorem ext : (∀ s, s ∈ f ↔ s ∈ g) → f = g :=
Filter.ext_iff.2
#align filter.ext Filter.ext
/-- An extensionality lemma that is useful for filters with good lemmas about `sᶜ ∈ f` (e.g.,
`Filter.comap`, `Filter.coprod`, `Filter.Coprod`, `Filter.cofinite`). -/
protected theorem coext (h : ∀ s, sᶜ ∈ f ↔ sᶜ ∈ g) : f = g :=
Filter.ext <| compl_surjective.forall.2 h
#align filter.coext Filter.coext
@[simp]
theorem univ_mem : univ ∈ f :=
f.univ_sets
#align filter.univ_mem Filter.univ_mem
theorem mem_of_superset {x y : Set α} (hx : x ∈ f) (hxy : x ⊆ y) : y ∈ f :=
f.sets_of_superset hx hxy
#align filter.mem_of_superset Filter.mem_of_superset
instance : Trans (· ⊇ ·) ((· ∈ ·) : Set α → Filter α → Prop) (· ∈ ·) where
trans h₁ h₂ := mem_of_superset h₂ h₁
theorem inter_mem {s t : Set α} (hs : s ∈ f) (ht : t ∈ f) : s ∩ t ∈ f :=
f.inter_sets hs ht
#align filter.inter_mem Filter.inter_mem
@[simp]
theorem inter_mem_iff {s t : Set α} : s ∩ t ∈ f ↔ s ∈ f ∧ t ∈ f :=
⟨fun h => ⟨mem_of_superset h inter_subset_left, mem_of_superset h inter_subset_right⟩,
and_imp.2 inter_mem⟩
#align filter.inter_mem_iff Filter.inter_mem_iff
theorem diff_mem {s t : Set α} (hs : s ∈ f) (ht : tᶜ ∈ f) : s \ t ∈ f :=
inter_mem hs ht
#align filter.diff_mem Filter.diff_mem
theorem univ_mem' (h : ∀ a, a ∈ s) : s ∈ f :=
mem_of_superset univ_mem fun x _ => h x
#align filter.univ_mem' Filter.univ_mem'
theorem mp_mem (hs : s ∈ f) (h : { x | x ∈ s → x ∈ t } ∈ f) : t ∈ f :=
mem_of_superset (inter_mem hs h) fun _ ⟨h₁, h₂⟩ => h₂ h₁
#align filter.mp_mem Filter.mp_mem
theorem congr_sets (h : { x | x ∈ s ↔ x ∈ t } ∈ f) : s ∈ f ↔ t ∈ f :=
⟨fun hs => mp_mem hs (mem_of_superset h fun _ => Iff.mp), fun hs =>
mp_mem hs (mem_of_superset h fun _ => Iff.mpr)⟩
#align filter.congr_sets Filter.congr_sets
/-- Override `sets` field of a filter to provide better definitional equality. -/
protected def copy (f : Filter α) (S : Set (Set α)) (hmem : ∀ s, s ∈ S ↔ s ∈ f) : Filter α where
sets := S
univ_sets := (hmem _).2 univ_mem
sets_of_superset h hsub := (hmem _).2 <| mem_of_superset ((hmem _).1 h) hsub
inter_sets h₁ h₂ := (hmem _).2 <| inter_mem ((hmem _).1 h₁) ((hmem _).1 h₂)
lemma copy_eq {S} (hmem : ∀ s, s ∈ S ↔ s ∈ f) : f.copy S hmem = f := Filter.ext hmem
@[simp] lemma mem_copy {S hmem} : s ∈ f.copy S hmem ↔ s ∈ S := Iff.rfl
@[simp]
theorem biInter_mem {β : Type v} {s : β → Set α} {is : Set β} (hf : is.Finite) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f :=
Finite.induction_on hf (by simp) fun _ _ hs => by simp [hs]
#align filter.bInter_mem Filter.biInter_mem
@[simp]
theorem biInter_finset_mem {β : Type v} {s : β → Set α} (is : Finset β) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f :=
biInter_mem is.finite_toSet
#align filter.bInter_finset_mem Filter.biInter_finset_mem
alias _root_.Finset.iInter_mem_sets := biInter_finset_mem
#align finset.Inter_mem_sets Finset.iInter_mem_sets
-- attribute [protected] Finset.iInter_mem_sets porting note: doesn't work
@[simp]
theorem sInter_mem {s : Set (Set α)} (hfin : s.Finite) : ⋂₀ s ∈ f ↔ ∀ U ∈ s, U ∈ f := by
rw [sInter_eq_biInter, biInter_mem hfin]
#align filter.sInter_mem Filter.sInter_mem
@[simp]
theorem iInter_mem {β : Sort v} {s : β → Set α} [Finite β] : (⋂ i, s i) ∈ f ↔ ∀ i, s i ∈ f :=
(sInter_mem (finite_range _)).trans forall_mem_range
#align filter.Inter_mem Filter.iInter_mem
theorem exists_mem_subset_iff : (∃ t ∈ f, t ⊆ s) ↔ s ∈ f :=
⟨fun ⟨_, ht, ts⟩ => mem_of_superset ht ts, fun hs => ⟨s, hs, Subset.rfl⟩⟩
#align filter.exists_mem_subset_iff Filter.exists_mem_subset_iff
theorem monotone_mem {f : Filter α} : Monotone fun s => s ∈ f := fun _ _ hst h =>
mem_of_superset h hst
#align filter.monotone_mem Filter.monotone_mem
theorem exists_mem_and_iff {P : Set α → Prop} {Q : Set α → Prop} (hP : Antitone P)
(hQ : Antitone Q) : ((∃ u ∈ f, P u) ∧ ∃ u ∈ f, Q u) ↔ ∃ u ∈ f, P u ∧ Q u := by
constructor
· rintro ⟨⟨u, huf, hPu⟩, v, hvf, hQv⟩
exact
⟨u ∩ v, inter_mem huf hvf, hP inter_subset_left hPu, hQ inter_subset_right hQv⟩
· rintro ⟨u, huf, hPu, hQu⟩
exact ⟨⟨u, huf, hPu⟩, u, huf, hQu⟩
#align filter.exists_mem_and_iff Filter.exists_mem_and_iff
theorem forall_in_swap {β : Type*} {p : Set α → β → Prop} :
(∀ a ∈ f, ∀ (b), p a b) ↔ ∀ (b), ∀ a ∈ f, p a b :=
Set.forall_in_swap
#align filter.forall_in_swap Filter.forall_in_swap
end Filter
namespace Mathlib.Tactic
open Lean Meta Elab Tactic
/--
`filter_upwards [h₁, ⋯, hₙ]` replaces a goal of the form `s ∈ f` and terms
`h₁ : t₁ ∈ f, ⋯, hₙ : tₙ ∈ f` with `∀ x, x ∈ t₁ → ⋯ → x ∈ tₙ → x ∈ s`.
The list is an optional parameter, `[]` being its default value.
`filter_upwards [h₁, ⋯, hₙ] with a₁ a₂ ⋯ aₖ` is a short form for
`{ filter_upwards [h₁, ⋯, hₙ], intros a₁ a₂ ⋯ aₖ }`.
`filter_upwards [h₁, ⋯, hₙ] using e` is a short form for
`{ filter_upwards [h1, ⋯, hn], exact e }`.
Combining both shortcuts is done by writing `filter_upwards [h₁, ⋯, hₙ] with a₁ a₂ ⋯ aₖ using e`.
Note that in this case, the `aᵢ` terms can be used in `e`.
-/
syntax (name := filterUpwards) "filter_upwards" (" [" term,* "]")?
(" with" (ppSpace colGt term:max)*)? (" using " term)? : tactic
elab_rules : tactic
| `(tactic| filter_upwards $[[$[$args],*]]? $[with $wth*]? $[using $usingArg]?) => do
let config : ApplyConfig := {newGoals := ApplyNewGoals.nonDependentOnly}
for e in args.getD #[] |>.reverse do
let goal ← getMainGoal
replaceMainGoal <| ← goal.withContext <| runTermElab do
let m ← mkFreshExprMVar none
let lem ← Term.elabTermEnsuringType
(← ``(Filter.mp_mem $e $(← Term.exprToSyntax m))) (← goal.getType)
goal.assign lem
return [m.mvarId!]
liftMetaTactic fun goal => do
goal.apply (← mkConstWithFreshMVarLevels ``Filter.univ_mem') config
evalTactic <|← `(tactic| dsimp (config := {zeta := false}) only [Set.mem_setOf_eq])
if let some l := wth then
evalTactic <|← `(tactic| intro $[$l]*)
if let some e := usingArg then
evalTactic <|← `(tactic| exact $e)
end Mathlib.Tactic
namespace Filter
variable {α : Type u} {β : Type v} {γ : Type w} {δ : Type*} {ι : Sort x}
section Principal
/-- The principal filter of `s` is the collection of all supersets of `s`. -/
def principal (s : Set α) : Filter α where
sets := { t | s ⊆ t }
univ_sets := subset_univ s
sets_of_superset hx := Subset.trans hx
inter_sets := subset_inter
#align filter.principal Filter.principal
@[inherit_doc]
scoped notation "𝓟" => Filter.principal
@[simp] theorem mem_principal {s t : Set α} : s ∈ 𝓟 t ↔ t ⊆ s := Iff.rfl
#align filter.mem_principal Filter.mem_principal
theorem mem_principal_self (s : Set α) : s ∈ 𝓟 s := Subset.rfl
#align filter.mem_principal_self Filter.mem_principal_self
end Principal
open Filter
section Join
/-- The join of a filter of filters is defined by the relation `s ∈ join f ↔ {t | s ∈ t} ∈ f`. -/
def join (f : Filter (Filter α)) : Filter α where
sets := { s | { t : Filter α | s ∈ t } ∈ f }
univ_sets := by simp only [mem_setOf_eq, univ_sets, ← Filter.mem_sets, setOf_true]
sets_of_superset hx xy := mem_of_superset hx fun f h => mem_of_superset h xy
inter_sets hx hy := mem_of_superset (inter_mem hx hy) fun f ⟨h₁, h₂⟩ => inter_mem h₁ h₂
#align filter.join Filter.join
@[simp]
theorem mem_join {s : Set α} {f : Filter (Filter α)} : s ∈ join f ↔ { t | s ∈ t } ∈ f :=
Iff.rfl
#align filter.mem_join Filter.mem_join
end Join
section Lattice
variable {f g : Filter α} {s t : Set α}
instance : PartialOrder (Filter α) where
le f g := ∀ ⦃U : Set α⦄, U ∈ g → U ∈ f
le_antisymm a b h₁ h₂ := filter_eq <| Subset.antisymm h₂ h₁
le_refl a := Subset.rfl
le_trans a b c h₁ h₂ := Subset.trans h₂ h₁
theorem le_def : f ≤ g ↔ ∀ x ∈ g, x ∈ f :=
Iff.rfl
#align filter.le_def Filter.le_def
protected theorem not_le : ¬f ≤ g ↔ ∃ s ∈ g, s ∉ f := by simp_rw [le_def, not_forall, exists_prop]
#align filter.not_le Filter.not_le
/-- `GenerateSets g s`: `s` is in the filter closure of `g`. -/
inductive GenerateSets (g : Set (Set α)) : Set α → Prop
| basic {s : Set α} : s ∈ g → GenerateSets g s
| univ : GenerateSets g univ
| superset {s t : Set α} : GenerateSets g s → s ⊆ t → GenerateSets g t
| inter {s t : Set α} : GenerateSets g s → GenerateSets g t → GenerateSets g (s ∩ t)
#align filter.generate_sets Filter.GenerateSets
/-- `generate g` is the largest filter containing the sets `g`. -/
def generate (g : Set (Set α)) : Filter α where
sets := {s | GenerateSets g s}
univ_sets := GenerateSets.univ
sets_of_superset := GenerateSets.superset
inter_sets := GenerateSets.inter
#align filter.generate Filter.generate
lemma mem_generate_of_mem {s : Set <| Set α} {U : Set α} (h : U ∈ s) :
U ∈ generate s := GenerateSets.basic h
theorem le_generate_iff {s : Set (Set α)} {f : Filter α} : f ≤ generate s ↔ s ⊆ f.sets :=
Iff.intro (fun h _ hu => h <| GenerateSets.basic <| hu) fun h _ hu =>
hu.recOn (fun h' => h h') univ_mem (fun _ hxy hx => mem_of_superset hx hxy) fun _ _ hx hy =>
inter_mem hx hy
#align filter.sets_iff_generate Filter.le_generate_iff
theorem mem_generate_iff {s : Set <| Set α} {U : Set α} :
U ∈ generate s ↔ ∃ t ⊆ s, Set.Finite t ∧ ⋂₀ t ⊆ U := by
constructor <;> intro h
· induction h with
| @basic V V_in =>
exact ⟨{V}, singleton_subset_iff.2 V_in, finite_singleton _, (sInter_singleton _).subset⟩
| univ => exact ⟨∅, empty_subset _, finite_empty, subset_univ _⟩
| superset _ hVW hV =>
rcases hV with ⟨t, hts, ht, htV⟩
exact ⟨t, hts, ht, htV.trans hVW⟩
| inter _ _ hV hW =>
rcases hV, hW with ⟨⟨t, hts, ht, htV⟩, u, hus, hu, huW⟩
exact
⟨t ∪ u, union_subset hts hus, ht.union hu,
(sInter_union _ _).subset.trans <| inter_subset_inter htV huW⟩
· rcases h with ⟨t, hts, tfin, h⟩
exact mem_of_superset ((sInter_mem tfin).2 fun V hV => GenerateSets.basic <| hts hV) h
#align filter.mem_generate_iff Filter.mem_generate_iff
@[simp] lemma generate_singleton (s : Set α) : generate {s} = 𝓟 s :=
le_antisymm (fun _t ht ↦ mem_of_superset (mem_generate_of_mem <| mem_singleton _) ht) <|
le_generate_iff.2 <| singleton_subset_iff.2 Subset.rfl
/-- `mkOfClosure s hs` constructs a filter on `α` whose elements set is exactly
`s : Set (Set α)`, provided one gives the assumption `hs : (generate s).sets = s`. -/
protected def mkOfClosure (s : Set (Set α)) (hs : (generate s).sets = s) : Filter α where
sets := s
univ_sets := hs ▸ univ_mem
sets_of_superset := hs ▸ mem_of_superset
inter_sets := hs ▸ inter_mem
#align filter.mk_of_closure Filter.mkOfClosure
theorem mkOfClosure_sets {s : Set (Set α)} {hs : (generate s).sets = s} :
Filter.mkOfClosure s hs = generate s :=
Filter.ext fun u =>
show u ∈ (Filter.mkOfClosure s hs).sets ↔ u ∈ (generate s).sets from hs.symm ▸ Iff.rfl
#align filter.mk_of_closure_sets Filter.mkOfClosure_sets
/-- Galois insertion from sets of sets into filters. -/
def giGenerate (α : Type*) :
@GaloisInsertion (Set (Set α)) (Filter α)ᵒᵈ _ _ Filter.generate Filter.sets where
gc _ _ := le_generate_iff
le_l_u _ _ h := GenerateSets.basic h
choice s hs := Filter.mkOfClosure s (le_antisymm hs <| le_generate_iff.1 <| le_rfl)
choice_eq _ _ := mkOfClosure_sets
#align filter.gi_generate Filter.giGenerate
/-- The infimum of filters is the filter generated by intersections
of elements of the two filters. -/
instance : Inf (Filter α) :=
⟨fun f g : Filter α =>
{ sets := { s | ∃ a ∈ f, ∃ b ∈ g, s = a ∩ b }
univ_sets := ⟨_, univ_mem, _, univ_mem, by simp⟩
sets_of_superset := by
rintro x y ⟨a, ha, b, hb, rfl⟩ xy
refine
⟨a ∪ y, mem_of_superset ha subset_union_left, b ∪ y,
mem_of_superset hb subset_union_left, ?_⟩
rw [← inter_union_distrib_right, union_eq_self_of_subset_left xy]
inter_sets := by
rintro x y ⟨a, ha, b, hb, rfl⟩ ⟨c, hc, d, hd, rfl⟩
refine ⟨a ∩ c, inter_mem ha hc, b ∩ d, inter_mem hb hd, ?_⟩
ac_rfl }⟩
theorem mem_inf_iff {f g : Filter α} {s : Set α} : s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, s = t₁ ∩ t₂ :=
Iff.rfl
#align filter.mem_inf_iff Filter.mem_inf_iff
theorem mem_inf_of_left {f g : Filter α} {s : Set α} (h : s ∈ f) : s ∈ f ⊓ g :=
⟨s, h, univ, univ_mem, (inter_univ s).symm⟩
#align filter.mem_inf_of_left Filter.mem_inf_of_left
theorem mem_inf_of_right {f g : Filter α} {s : Set α} (h : s ∈ g) : s ∈ f ⊓ g :=
⟨univ, univ_mem, s, h, (univ_inter s).symm⟩
#align filter.mem_inf_of_right Filter.mem_inf_of_right
theorem inter_mem_inf {α : Type u} {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) :
s ∩ t ∈ f ⊓ g :=
⟨s, hs, t, ht, rfl⟩
#align filter.inter_mem_inf Filter.inter_mem_inf
theorem mem_inf_of_inter {f g : Filter α} {s t u : Set α} (hs : s ∈ f) (ht : t ∈ g)
(h : s ∩ t ⊆ u) : u ∈ f ⊓ g :=
mem_of_superset (inter_mem_inf hs ht) h
#align filter.mem_inf_of_inter Filter.mem_inf_of_inter
theorem mem_inf_iff_superset {f g : Filter α} {s : Set α} :
s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ∩ t₂ ⊆ s :=
⟨fun ⟨t₁, h₁, t₂, h₂, Eq⟩ => ⟨t₁, h₁, t₂, h₂, Eq ▸ Subset.rfl⟩, fun ⟨_, h₁, _, h₂, sub⟩ =>
mem_inf_of_inter h₁ h₂ sub⟩
#align filter.mem_inf_iff_superset Filter.mem_inf_iff_superset
instance : Top (Filter α) :=
⟨{ sets := { s | ∀ x, x ∈ s }
univ_sets := fun x => mem_univ x
sets_of_superset := fun hx hxy a => hxy (hx a)
inter_sets := fun hx hy _ => mem_inter (hx _) (hy _) }⟩
theorem mem_top_iff_forall {s : Set α} : s ∈ (⊤ : Filter α) ↔ ∀ x, x ∈ s :=
Iff.rfl
#align filter.mem_top_iff_forall Filter.mem_top_iff_forall
@[simp]
theorem mem_top {s : Set α} : s ∈ (⊤ : Filter α) ↔ s = univ := by
rw [mem_top_iff_forall, eq_univ_iff_forall]
#align filter.mem_top Filter.mem_top
section CompleteLattice
/- We lift the complete lattice along the Galois connection `generate` / `sets`. Unfortunately,
we want to have different definitional equalities for some lattice operations. So we define them
upfront and change the lattice operations for the complete lattice instance. -/
instance instCompleteLatticeFilter : CompleteLattice (Filter α) :=
{ @OrderDual.instCompleteLattice _ (giGenerate α).liftCompleteLattice with
le := (· ≤ ·)
top := ⊤
le_top := fun _ _s hs => (mem_top.1 hs).symm ▸ univ_mem
inf := (· ⊓ ·)
inf_le_left := fun _ _ _ => mem_inf_of_left
inf_le_right := fun _ _ _ => mem_inf_of_right
le_inf := fun _ _ _ h₁ h₂ _s ⟨_a, ha, _b, hb, hs⟩ => hs.symm ▸ inter_mem (h₁ ha) (h₂ hb)
sSup := join ∘ 𝓟
le_sSup := fun _ _f hf _s hs => hs hf
sSup_le := fun _ _f hf _s hs _g hg => hf _ hg hs }
instance : Inhabited (Filter α) := ⟨⊥⟩
end CompleteLattice
/-- A filter is `NeBot` if it is not equal to `⊥`, or equivalently the empty set does not belong to
the filter. Bourbaki include this assumption in the definition of a filter but we prefer to have a
`CompleteLattice` structure on `Filter _`, so we use a typeclass argument in lemmas instead. -/
class NeBot (f : Filter α) : Prop where
/-- The filter is nontrivial: `f ≠ ⊥` or equivalently, `∅ ∉ f`. -/
ne' : f ≠ ⊥
#align filter.ne_bot Filter.NeBot
theorem neBot_iff {f : Filter α} : NeBot f ↔ f ≠ ⊥ :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align filter.ne_bot_iff Filter.neBot_iff
theorem NeBot.ne {f : Filter α} (hf : NeBot f) : f ≠ ⊥ := hf.ne'
#align filter.ne_bot.ne Filter.NeBot.ne
@[simp] theorem not_neBot {f : Filter α} : ¬f.NeBot ↔ f = ⊥ := neBot_iff.not_left
#align filter.not_ne_bot Filter.not_neBot
theorem NeBot.mono {f g : Filter α} (hf : NeBot f) (hg : f ≤ g) : NeBot g :=
⟨ne_bot_of_le_ne_bot hf.1 hg⟩
#align filter.ne_bot.mono Filter.NeBot.mono
theorem neBot_of_le {f g : Filter α} [hf : NeBot f] (hg : f ≤ g) : NeBot g :=
hf.mono hg
#align filter.ne_bot_of_le Filter.neBot_of_le
@[simp] theorem sup_neBot {f g : Filter α} : NeBot (f ⊔ g) ↔ NeBot f ∨ NeBot g := by
simp only [neBot_iff, not_and_or, Ne, sup_eq_bot_iff]
#align filter.sup_ne_bot Filter.sup_neBot
theorem not_disjoint_self_iff : ¬Disjoint f f ↔ f.NeBot := by rw [disjoint_self, neBot_iff]
#align filter.not_disjoint_self_iff Filter.not_disjoint_self_iff
theorem bot_sets_eq : (⊥ : Filter α).sets = univ := rfl
#align filter.bot_sets_eq Filter.bot_sets_eq
/-- Either `f = ⊥` or `Filter.NeBot f`. This is a version of `eq_or_ne` that uses `Filter.NeBot`
as the second alternative, to be used as an instance. -/
theorem eq_or_neBot (f : Filter α) : f = ⊥ ∨ NeBot f := (eq_or_ne f ⊥).imp_right NeBot.mk
theorem sup_sets_eq {f g : Filter α} : (f ⊔ g).sets = f.sets ∩ g.sets :=
(giGenerate α).gc.u_inf
#align filter.sup_sets_eq Filter.sup_sets_eq
theorem sSup_sets_eq {s : Set (Filter α)} : (sSup s).sets = ⋂ f ∈ s, (f : Filter α).sets :=
(giGenerate α).gc.u_sInf
#align filter.Sup_sets_eq Filter.sSup_sets_eq
theorem iSup_sets_eq {f : ι → Filter α} : (iSup f).sets = ⋂ i, (f i).sets :=
(giGenerate α).gc.u_iInf
#align filter.supr_sets_eq Filter.iSup_sets_eq
theorem generate_empty : Filter.generate ∅ = (⊤ : Filter α) :=
(giGenerate α).gc.l_bot
#align filter.generate_empty Filter.generate_empty
theorem generate_univ : Filter.generate univ = (⊥ : Filter α) :=
bot_unique fun _ _ => GenerateSets.basic (mem_univ _)
#align filter.generate_univ Filter.generate_univ
theorem generate_union {s t : Set (Set α)} :
Filter.generate (s ∪ t) = Filter.generate s ⊓ Filter.generate t :=
(giGenerate α).gc.l_sup
#align filter.generate_union Filter.generate_union
theorem generate_iUnion {s : ι → Set (Set α)} :
Filter.generate (⋃ i, s i) = ⨅ i, Filter.generate (s i) :=
(giGenerate α).gc.l_iSup
#align filter.generate_Union Filter.generate_iUnion
@[simp]
theorem mem_bot {s : Set α} : s ∈ (⊥ : Filter α) :=
trivial
#align filter.mem_bot Filter.mem_bot
@[simp]
theorem mem_sup {f g : Filter α} {s : Set α} : s ∈ f ⊔ g ↔ s ∈ f ∧ s ∈ g :=
Iff.rfl
#align filter.mem_sup Filter.mem_sup
theorem union_mem_sup {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) : s ∪ t ∈ f ⊔ g :=
⟨mem_of_superset hs subset_union_left, mem_of_superset ht subset_union_right⟩
#align filter.union_mem_sup Filter.union_mem_sup
@[simp]
theorem mem_sSup {x : Set α} {s : Set (Filter α)} : x ∈ sSup s ↔ ∀ f ∈ s, x ∈ (f : Filter α) :=
Iff.rfl
#align filter.mem_Sup Filter.mem_sSup
@[simp]
theorem mem_iSup {x : Set α} {f : ι → Filter α} : x ∈ iSup f ↔ ∀ i, x ∈ f i := by
simp only [← Filter.mem_sets, iSup_sets_eq, iff_self_iff, mem_iInter]
#align filter.mem_supr Filter.mem_iSup
@[simp]
theorem iSup_neBot {f : ι → Filter α} : (⨆ i, f i).NeBot ↔ ∃ i, (f i).NeBot := by
simp [neBot_iff]
#align filter.supr_ne_bot Filter.iSup_neBot
theorem iInf_eq_generate (s : ι → Filter α) : iInf s = generate (⋃ i, (s i).sets) :=
show generate _ = generate _ from congr_arg _ <| congr_arg sSup <| (range_comp _ _).symm
#align filter.infi_eq_generate Filter.iInf_eq_generate
theorem mem_iInf_of_mem {f : ι → Filter α} (i : ι) {s} (hs : s ∈ f i) : s ∈ ⨅ i, f i :=
iInf_le f i hs
#align filter.mem_infi_of_mem Filter.mem_iInf_of_mem
theorem mem_iInf_of_iInter {ι} {s : ι → Filter α} {U : Set α} {I : Set ι} (I_fin : I.Finite)
{V : I → Set α} (hV : ∀ i, V i ∈ s i) (hU : ⋂ i, V i ⊆ U) : U ∈ ⨅ i, s i := by
haveI := I_fin.fintype
refine mem_of_superset (iInter_mem.2 fun i => ?_) hU
exact mem_iInf_of_mem (i : ι) (hV _)
#align filter.mem_infi_of_Inter Filter.mem_iInf_of_iInter
theorem mem_iInf {ι} {s : ι → Filter α} {U : Set α} :
(U ∈ ⨅ i, s i) ↔ ∃ I : Set ι, I.Finite ∧ ∃ V : I → Set α, (∀ i, V i ∈ s i) ∧ U = ⋂ i, V i := by
constructor
· rw [iInf_eq_generate, mem_generate_iff]
rintro ⟨t, tsub, tfin, tinter⟩
rcases eq_finite_iUnion_of_finite_subset_iUnion tfin tsub with ⟨I, Ifin, σ, σfin, σsub, rfl⟩
rw [sInter_iUnion] at tinter
set V := fun i => U ∪ ⋂₀ σ i with hV
have V_in : ∀ i, V i ∈ s i := by
rintro i
have : ⋂₀ σ i ∈ s i := by
rw [sInter_mem (σfin _)]
apply σsub
exact mem_of_superset this subset_union_right
refine ⟨I, Ifin, V, V_in, ?_⟩
rwa [hV, ← union_iInter, union_eq_self_of_subset_right]
· rintro ⟨I, Ifin, V, V_in, rfl⟩
exact mem_iInf_of_iInter Ifin V_in Subset.rfl
#align filter.mem_infi Filter.mem_iInf
theorem mem_iInf' {ι} {s : ι → Filter α} {U : Set α} :
(U ∈ ⨅ i, s i) ↔
∃ I : Set ι, I.Finite ∧ ∃ V : ι → Set α, (∀ i, V i ∈ s i) ∧
(∀ i ∉ I, V i = univ) ∧ (U = ⋂ i ∈ I, V i) ∧ U = ⋂ i, V i := by
simp only [mem_iInf, SetCoe.forall', biInter_eq_iInter]
refine ⟨?_, fun ⟨I, If, V, hVs, _, hVU, _⟩ => ⟨I, If, fun i => V i, fun i => hVs i, hVU⟩⟩
rintro ⟨I, If, V, hV, rfl⟩
refine ⟨I, If, fun i => if hi : i ∈ I then V ⟨i, hi⟩ else univ, fun i => ?_, fun i hi => ?_, ?_⟩
· dsimp only
split_ifs
exacts [hV _, univ_mem]
· exact dif_neg hi
· simp only [iInter_dite, biInter_eq_iInter, dif_pos (Subtype.coe_prop _), Subtype.coe_eta,
iInter_univ, inter_univ, eq_self_iff_true, true_and_iff]
#align filter.mem_infi' Filter.mem_iInf'
theorem exists_iInter_of_mem_iInf {ι : Type*} {α : Type*} {f : ι → Filter α} {s}
(hs : s ∈ ⨅ i, f i) : ∃ t : ι → Set α, (∀ i, t i ∈ f i) ∧ s = ⋂ i, t i :=
let ⟨_, _, V, hVs, _, _, hVU'⟩ := mem_iInf'.1 hs; ⟨V, hVs, hVU'⟩
#align filter.exists_Inter_of_mem_infi Filter.exists_iInter_of_mem_iInf
theorem mem_iInf_of_finite {ι : Type*} [Finite ι] {α : Type*} {f : ι → Filter α} (s) :
(s ∈ ⨅ i, f i) ↔ ∃ t : ι → Set α, (∀ i, t i ∈ f i) ∧ s = ⋂ i, t i := by
refine ⟨exists_iInter_of_mem_iInf, ?_⟩
rintro ⟨t, ht, rfl⟩
exact iInter_mem.2 fun i => mem_iInf_of_mem i (ht i)
#align filter.mem_infi_of_finite Filter.mem_iInf_of_finite
@[simp]
theorem le_principal_iff {s : Set α} {f : Filter α} : f ≤ 𝓟 s ↔ s ∈ f :=
⟨fun h => h Subset.rfl, fun hs _ ht => mem_of_superset hs ht⟩
#align filter.le_principal_iff Filter.le_principal_iff
theorem Iic_principal (s : Set α) : Iic (𝓟 s) = { l | s ∈ l } :=
Set.ext fun _ => le_principal_iff
#align filter.Iic_principal Filter.Iic_principal
theorem principal_mono {s t : Set α} : 𝓟 s ≤ 𝓟 t ↔ s ⊆ t := by
simp only [le_principal_iff, iff_self_iff, mem_principal]
#align filter.principal_mono Filter.principal_mono
@[gcongr] alias ⟨_, _root_.GCongr.filter_principal_mono⟩ := principal_mono
@[mono]
theorem monotone_principal : Monotone (𝓟 : Set α → Filter α) := fun _ _ => principal_mono.2
#align filter.monotone_principal Filter.monotone_principal
@[simp] theorem principal_eq_iff_eq {s t : Set α} : 𝓟 s = 𝓟 t ↔ s = t := by
simp only [le_antisymm_iff, le_principal_iff, mem_principal]; rfl
#align filter.principal_eq_iff_eq Filter.principal_eq_iff_eq
@[simp] theorem join_principal_eq_sSup {s : Set (Filter α)} : join (𝓟 s) = sSup s := rfl
#align filter.join_principal_eq_Sup Filter.join_principal_eq_sSup
@[simp] theorem principal_univ : 𝓟 (univ : Set α) = ⊤ :=
top_unique <| by simp only [le_principal_iff, mem_top, eq_self_iff_true]
#align filter.principal_univ Filter.principal_univ
@[simp]
theorem principal_empty : 𝓟 (∅ : Set α) = ⊥ :=
bot_unique fun _ _ => empty_subset _
#align filter.principal_empty Filter.principal_empty
theorem generate_eq_biInf (S : Set (Set α)) : generate S = ⨅ s ∈ S, 𝓟 s :=
eq_of_forall_le_iff fun f => by simp [le_generate_iff, le_principal_iff, subset_def]
#align filter.generate_eq_binfi Filter.generate_eq_biInf
/-! ### Lattice equations -/
theorem empty_mem_iff_bot {f : Filter α} : ∅ ∈ f ↔ f = ⊥ :=
⟨fun h => bot_unique fun s _ => mem_of_superset h (empty_subset s), fun h => h.symm ▸ mem_bot⟩
#align filter.empty_mem_iff_bot Filter.empty_mem_iff_bot
theorem nonempty_of_mem {f : Filter α} [hf : NeBot f] {s : Set α} (hs : s ∈ f) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun h => absurd hs (h.symm ▸ mt empty_mem_iff_bot.mp hf.1)) id
#align filter.nonempty_of_mem Filter.nonempty_of_mem
theorem NeBot.nonempty_of_mem {f : Filter α} (hf : NeBot f) {s : Set α} (hs : s ∈ f) : s.Nonempty :=
@Filter.nonempty_of_mem α f hf s hs
#align filter.ne_bot.nonempty_of_mem Filter.NeBot.nonempty_of_mem
@[simp]
theorem empty_not_mem (f : Filter α) [NeBot f] : ¬∅ ∈ f := fun h => (nonempty_of_mem h).ne_empty rfl
#align filter.empty_not_mem Filter.empty_not_mem
theorem nonempty_of_neBot (f : Filter α) [NeBot f] : Nonempty α :=
nonempty_of_exists <| nonempty_of_mem (univ_mem : univ ∈ f)
#align filter.nonempty_of_ne_bot Filter.nonempty_of_neBot
theorem compl_not_mem {f : Filter α} {s : Set α} [NeBot f] (h : s ∈ f) : sᶜ ∉ f := fun hsc =>
(nonempty_of_mem (inter_mem h hsc)).ne_empty <| inter_compl_self s
#align filter.compl_not_mem Filter.compl_not_mem
theorem filter_eq_bot_of_isEmpty [IsEmpty α] (f : Filter α) : f = ⊥ :=
empty_mem_iff_bot.mp <| univ_mem' isEmptyElim
#align filter.filter_eq_bot_of_is_empty Filter.filter_eq_bot_of_isEmpty
protected lemma disjoint_iff {f g : Filter α} : Disjoint f g ↔ ∃ s ∈ f, ∃ t ∈ g, Disjoint s t := by
simp only [disjoint_iff, ← empty_mem_iff_bot, mem_inf_iff, inf_eq_inter, bot_eq_empty,
@eq_comm _ ∅]
#align filter.disjoint_iff Filter.disjoint_iff
theorem disjoint_of_disjoint_of_mem {f g : Filter α} {s t : Set α} (h : Disjoint s t) (hs : s ∈ f)
(ht : t ∈ g) : Disjoint f g :=
Filter.disjoint_iff.mpr ⟨s, hs, t, ht, h⟩
#align filter.disjoint_of_disjoint_of_mem Filter.disjoint_of_disjoint_of_mem
theorem NeBot.not_disjoint (hf : f.NeBot) (hs : s ∈ f) (ht : t ∈ f) : ¬Disjoint s t := fun h =>
not_disjoint_self_iff.2 hf <| Filter.disjoint_iff.2 ⟨s, hs, t, ht, h⟩
#align filter.ne_bot.not_disjoint Filter.NeBot.not_disjoint
theorem inf_eq_bot_iff {f g : Filter α} : f ⊓ g = ⊥ ↔ ∃ U ∈ f, ∃ V ∈ g, U ∩ V = ∅ := by
simp only [← disjoint_iff, Filter.disjoint_iff, Set.disjoint_iff_inter_eq_empty]
#align filter.inf_eq_bot_iff Filter.inf_eq_bot_iff
theorem _root_.Pairwise.exists_mem_filter_of_disjoint {ι : Type*} [Finite ι] {l : ι → Filter α}
(hd : Pairwise (Disjoint on l)) :
∃ s : ι → Set α, (∀ i, s i ∈ l i) ∧ Pairwise (Disjoint on s) := by
have : Pairwise fun i j => ∃ (s : {s // s ∈ l i}) (t : {t // t ∈ l j}), Disjoint s.1 t.1 := by
simpa only [Pairwise, Function.onFun, Filter.disjoint_iff, exists_prop, Subtype.exists] using hd
choose! s t hst using this
refine ⟨fun i => ⋂ j, @s i j ∩ @t j i, fun i => ?_, fun i j hij => ?_⟩
exacts [iInter_mem.2 fun j => inter_mem (@s i j).2 (@t j i).2,
(hst hij).mono ((iInter_subset _ j).trans inter_subset_left)
((iInter_subset _ i).trans inter_subset_right)]
#align pairwise.exists_mem_filter_of_disjoint Pairwise.exists_mem_filter_of_disjoint
theorem _root_.Set.PairwiseDisjoint.exists_mem_filter {ι : Type*} {l : ι → Filter α} {t : Set ι}
(hd : t.PairwiseDisjoint l) (ht : t.Finite) :
∃ s : ι → Set α, (∀ i, s i ∈ l i) ∧ t.PairwiseDisjoint s := by
haveI := ht.to_subtype
rcases (hd.subtype _ _).exists_mem_filter_of_disjoint with ⟨s, hsl, hsd⟩
lift s to (i : t) → {s // s ∈ l i} using hsl
rcases @Subtype.exists_pi_extension ι (fun i => { s // s ∈ l i }) _ _ s with ⟨s, rfl⟩
exact ⟨fun i => s i, fun i => (s i).2, hsd.set_of_subtype _ _⟩
#align set.pairwise_disjoint.exists_mem_filter Set.PairwiseDisjoint.exists_mem_filter
/-- There is exactly one filter on an empty type. -/
instance unique [IsEmpty α] : Unique (Filter α) where
default := ⊥
uniq := filter_eq_bot_of_isEmpty
#align filter.unique Filter.unique
theorem NeBot.nonempty (f : Filter α) [hf : f.NeBot] : Nonempty α :=
not_isEmpty_iff.mp fun _ ↦ hf.ne (Subsingleton.elim _ _)
/-- There are only two filters on a `Subsingleton`: `⊥` and `⊤`. If the type is empty, then they are
equal. -/
theorem eq_top_of_neBot [Subsingleton α] (l : Filter α) [NeBot l] : l = ⊤ := by
refine top_unique fun s hs => ?_
obtain rfl : s = univ := Subsingleton.eq_univ_of_nonempty (nonempty_of_mem hs)
exact univ_mem
#align filter.eq_top_of_ne_bot Filter.eq_top_of_neBot
theorem forall_mem_nonempty_iff_neBot {f : Filter α} :
(∀ s : Set α, s ∈ f → s.Nonempty) ↔ NeBot f :=
⟨fun h => ⟨fun hf => not_nonempty_empty (h ∅ <| hf.symm ▸ mem_bot)⟩, @nonempty_of_mem _ _⟩
#align filter.forall_mem_nonempty_iff_ne_bot Filter.forall_mem_nonempty_iff_neBot
instance instNontrivialFilter [Nonempty α] : Nontrivial (Filter α) :=
⟨⟨⊤, ⊥, NeBot.ne <| forall_mem_nonempty_iff_neBot.1
fun s hs => by rwa [mem_top.1 hs, ← nonempty_iff_univ_nonempty]⟩⟩
theorem nontrivial_iff_nonempty : Nontrivial (Filter α) ↔ Nonempty α :=
⟨fun _ =>
by_contra fun h' =>
haveI := not_nonempty_iff.1 h'
not_subsingleton (Filter α) inferInstance,
@Filter.instNontrivialFilter α⟩
#align filter.nontrivial_iff_nonempty Filter.nontrivial_iff_nonempty
theorem eq_sInf_of_mem_iff_exists_mem {S : Set (Filter α)} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ f ∈ S, s ∈ f) : l = sInf S :=
le_antisymm (le_sInf fun f hf _ hs => h.2 ⟨f, hf, hs⟩)
fun _ hs => let ⟨_, hf, hs⟩ := h.1 hs; (sInf_le hf) hs
#align filter.eq_Inf_of_mem_iff_exists_mem Filter.eq_sInf_of_mem_iff_exists_mem
theorem eq_iInf_of_mem_iff_exists_mem {f : ι → Filter α} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, s ∈ f i) : l = iInf f :=
eq_sInf_of_mem_iff_exists_mem <| h.trans exists_range_iff.symm
#align filter.eq_infi_of_mem_iff_exists_mem Filter.eq_iInf_of_mem_iff_exists_mem
theorem eq_biInf_of_mem_iff_exists_mem {f : ι → Filter α} {p : ι → Prop} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, p i ∧ s ∈ f i) : l = ⨅ (i) (_ : p i), f i := by
rw [iInf_subtype']
exact eq_iInf_of_mem_iff_exists_mem fun {_} => by simp only [Subtype.exists, h, exists_prop]
#align filter.eq_binfi_of_mem_iff_exists_mem Filter.eq_biInf_of_mem_iff_exists_memₓ
theorem iInf_sets_eq {f : ι → Filter α} (h : Directed (· ≥ ·) f) [ne : Nonempty ι] :
(iInf f).sets = ⋃ i, (f i).sets :=
let ⟨i⟩ := ne
let u :=
{ sets := ⋃ i, (f i).sets
univ_sets := mem_iUnion.2 ⟨i, univ_mem⟩
sets_of_superset := by
simp only [mem_iUnion, exists_imp]
exact fun i hx hxy => ⟨i, mem_of_superset hx hxy⟩
inter_sets := by
simp only [mem_iUnion, exists_imp]
intro x y a hx b hy
rcases h a b with ⟨c, ha, hb⟩
exact ⟨c, inter_mem (ha hx) (hb hy)⟩ }
have : u = iInf f := eq_iInf_of_mem_iff_exists_mem mem_iUnion
-- Porting note: it was just `congr_arg filter.sets this.symm`
(congr_arg Filter.sets this.symm).trans <| by simp only
#align filter.infi_sets_eq Filter.iInf_sets_eq
theorem mem_iInf_of_directed {f : ι → Filter α} (h : Directed (· ≥ ·) f) [Nonempty ι] (s) :
s ∈ iInf f ↔ ∃ i, s ∈ f i := by
simp only [← Filter.mem_sets, iInf_sets_eq h, mem_iUnion]
#align filter.mem_infi_of_directed Filter.mem_iInf_of_directed
theorem mem_biInf_of_directed {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) {t : Set α} : (t ∈ ⨅ i ∈ s, f i) ↔ ∃ i ∈ s, t ∈ f i := by
haveI := ne.to_subtype
simp_rw [iInf_subtype', mem_iInf_of_directed h.directed_val, Subtype.exists, exists_prop]
#align filter.mem_binfi_of_directed Filter.mem_biInf_of_directed
theorem biInf_sets_eq {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) : (⨅ i ∈ s, f i).sets = ⋃ i ∈ s, (f i).sets :=
ext fun t => by simp [mem_biInf_of_directed h ne]
#align filter.binfi_sets_eq Filter.biInf_sets_eq
theorem iInf_sets_eq_finite {ι : Type*} (f : ι → Filter α) :
(⨅ i, f i).sets = ⋃ t : Finset ι, (⨅ i ∈ t, f i).sets := by
rw [iInf_eq_iInf_finset, iInf_sets_eq]
exact directed_of_isDirected_le fun _ _ => biInf_mono
#align filter.infi_sets_eq_finite Filter.iInf_sets_eq_finite
theorem iInf_sets_eq_finite' (f : ι → Filter α) :
(⨅ i, f i).sets = ⋃ t : Finset (PLift ι), (⨅ i ∈ t, f (PLift.down i)).sets := by
rw [← iInf_sets_eq_finite, ← Equiv.plift.surjective.iInf_comp, Equiv.plift_apply]
#align filter.infi_sets_eq_finite' Filter.iInf_sets_eq_finite'
theorem mem_iInf_finite {ι : Type*} {f : ι → Filter α} (s) :
s ∈ iInf f ↔ ∃ t : Finset ι, s ∈ ⨅ i ∈ t, f i :=
(Set.ext_iff.1 (iInf_sets_eq_finite f) s).trans mem_iUnion
#align filter.mem_infi_finite Filter.mem_iInf_finite
theorem mem_iInf_finite' {f : ι → Filter α} (s) :
s ∈ iInf f ↔ ∃ t : Finset (PLift ι), s ∈ ⨅ i ∈ t, f (PLift.down i) :=
(Set.ext_iff.1 (iInf_sets_eq_finite' f) s).trans mem_iUnion
#align filter.mem_infi_finite' Filter.mem_iInf_finite'
@[simp]
theorem sup_join {f₁ f₂ : Filter (Filter α)} : join f₁ ⊔ join f₂ = join (f₁ ⊔ f₂) :=
Filter.ext fun x => by simp only [mem_sup, mem_join]
#align filter.sup_join Filter.sup_join
@[simp]
theorem iSup_join {ι : Sort w} {f : ι → Filter (Filter α)} : ⨆ x, join (f x) = join (⨆ x, f x) :=
Filter.ext fun x => by simp only [mem_iSup, mem_join]
#align filter.supr_join Filter.iSup_join
instance : DistribLattice (Filter α) :=
{ Filter.instCompleteLatticeFilter with
le_sup_inf := by
intro x y z s
simp only [and_assoc, mem_inf_iff, mem_sup, exists_prop, exists_imp, and_imp]
rintro hs t₁ ht₁ t₂ ht₂ rfl
exact
⟨t₁, x.sets_of_superset hs inter_subset_left, ht₁, t₂,
x.sets_of_superset hs inter_subset_right, ht₂, rfl⟩ }
-- The dual version does not hold! `Filter α` is not a `CompleteDistribLattice`. -/
instance : Coframe (Filter α) :=
{ Filter.instCompleteLatticeFilter with
iInf_sup_le_sup_sInf := fun f s t ⟨h₁, h₂⟩ => by
rw [iInf_subtype']
rw [sInf_eq_iInf', iInf_sets_eq_finite, mem_iUnion] at h₂
obtain ⟨u, hu⟩ := h₂
rw [← Finset.inf_eq_iInf] at hu
suffices ⨅ i : s, f ⊔ ↑i ≤ f ⊔ u.inf fun i => ↑i from this ⟨h₁, hu⟩
refine Finset.induction_on u (le_sup_of_le_right le_top) ?_
rintro ⟨i⟩ u _ ih
rw [Finset.inf_insert, sup_inf_left]
exact le_inf (iInf_le _ _) ih }
theorem mem_iInf_finset {s : Finset α} {f : α → Filter β} {t : Set β} :
(t ∈ ⨅ a ∈ s, f a) ↔ ∃ p : α → Set β, (∀ a ∈ s, p a ∈ f a) ∧ t = ⋂ a ∈ s, p a := by
simp only [← Finset.set_biInter_coe, biInter_eq_iInter, iInf_subtype']
refine ⟨fun h => ?_, ?_⟩
· rcases (mem_iInf_of_finite _).1 h with ⟨p, hp, rfl⟩
refine ⟨fun a => if h : a ∈ s then p ⟨a, h⟩ else univ,
fun a ha => by simpa [ha] using hp ⟨a, ha⟩, ?_⟩
refine iInter_congr_of_surjective id surjective_id ?_
rintro ⟨a, ha⟩
simp [ha]
· rintro ⟨p, hpf, rfl⟩
exact iInter_mem.2 fun a => mem_iInf_of_mem a (hpf a a.2)
#align filter.mem_infi_finset Filter.mem_iInf_finset
/-- If `f : ι → Filter α` is directed, `ι` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed` for a version assuming `Nonempty α` instead of `Nonempty ι`. -/
theorem iInf_neBot_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
(∀ i, NeBot (f i)) → NeBot (iInf f) :=
not_imp_not.1 <| by simpa only [not_forall, not_neBot, ← empty_mem_iff_bot,
mem_iInf_of_directed hd] using id
#align filter.infi_ne_bot_of_directed' Filter.iInf_neBot_of_directed'
/-- If `f : ι → Filter α` is directed, `α` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed'` for a version assuming `Nonempty ι` instead of `Nonempty α`. -/
theorem iInf_neBot_of_directed {f : ι → Filter α} [hn : Nonempty α] (hd : Directed (· ≥ ·) f)
(hb : ∀ i, NeBot (f i)) : NeBot (iInf f) := by
cases isEmpty_or_nonempty ι
· constructor
simp [iInf_of_empty f, top_ne_bot]
· exact iInf_neBot_of_directed' hd hb
#align filter.infi_ne_bot_of_directed Filter.iInf_neBot_of_directed
theorem sInf_neBot_of_directed' {s : Set (Filter α)} (hne : s.Nonempty) (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
@iInf_neBot_of_directed' _ _ _ hne.to_subtype hd.directed_val fun ⟨_, hf⟩ =>
⟨ne_of_mem_of_not_mem hf hbot⟩
#align filter.Inf_ne_bot_of_directed' Filter.sInf_neBot_of_directed'
theorem sInf_neBot_of_directed [Nonempty α] {s : Set (Filter α)} (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
iInf_neBot_of_directed hd.directed_val fun ⟨_, hf⟩ => ⟨ne_of_mem_of_not_mem hf hbot⟩
#align filter.Inf_ne_bot_of_directed Filter.sInf_neBot_of_directed
theorem iInf_neBot_iff_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed' hd⟩
#align filter.infi_ne_bot_iff_of_directed' Filter.iInf_neBot_iff_of_directed'
theorem iInf_neBot_iff_of_directed {f : ι → Filter α} [Nonempty α] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed hd⟩
#align filter.infi_ne_bot_iff_of_directed Filter.iInf_neBot_iff_of_directed
@[elab_as_elim]
theorem iInf_sets_induct {f : ι → Filter α} {s : Set α} (hs : s ∈ iInf f) {p : Set α → Prop}
(uni : p univ) (ins : ∀ {i s₁ s₂}, s₁ ∈ f i → p s₂ → p (s₁ ∩ s₂)) : p s := by
rw [mem_iInf_finite'] at hs
simp only [← Finset.inf_eq_iInf] at hs
rcases hs with ⟨is, his⟩
induction is using Finset.induction_on generalizing s with
| empty => rwa [mem_top.1 his]
| insert _ ih =>
rw [Finset.inf_insert, mem_inf_iff] at his
rcases his with ⟨s₁, hs₁, s₂, hs₂, rfl⟩
exact ins hs₁ (ih hs₂)
#align filter.infi_sets_induct Filter.iInf_sets_induct
/-! #### `principal` equations -/
@[simp]
theorem inf_principal {s t : Set α} : 𝓟 s ⊓ 𝓟 t = 𝓟 (s ∩ t) :=
le_antisymm
(by simp only [le_principal_iff, mem_inf_iff]; exact ⟨s, Subset.rfl, t, Subset.rfl, rfl⟩)
(by simp [le_inf_iff, inter_subset_left, inter_subset_right])
#align filter.inf_principal Filter.inf_principal
@[simp]
theorem sup_principal {s t : Set α} : 𝓟 s ⊔ 𝓟 t = 𝓟 (s ∪ t) :=
Filter.ext fun u => by simp only [union_subset_iff, mem_sup, mem_principal]
#align filter.sup_principal Filter.sup_principal
@[simp]
theorem iSup_principal {ι : Sort w} {s : ι → Set α} : ⨆ x, 𝓟 (s x) = 𝓟 (⋃ i, s i) :=
Filter.ext fun x => by simp only [mem_iSup, mem_principal, iUnion_subset_iff]
#align filter.supr_principal Filter.iSup_principal
@[simp]
theorem principal_eq_bot_iff {s : Set α} : 𝓟 s = ⊥ ↔ s = ∅ :=
empty_mem_iff_bot.symm.trans <| mem_principal.trans subset_empty_iff
#align filter.principal_eq_bot_iff Filter.principal_eq_bot_iff
@[simp]
theorem principal_neBot_iff {s : Set α} : NeBot (𝓟 s) ↔ s.Nonempty :=
neBot_iff.trans <| (not_congr principal_eq_bot_iff).trans nonempty_iff_ne_empty.symm
#align filter.principal_ne_bot_iff Filter.principal_neBot_iff
alias ⟨_, _root_.Set.Nonempty.principal_neBot⟩ := principal_neBot_iff
#align set.nonempty.principal_ne_bot Set.Nonempty.principal_neBot
theorem isCompl_principal (s : Set α) : IsCompl (𝓟 s) (𝓟 sᶜ) :=
IsCompl.of_eq (by rw [inf_principal, inter_compl_self, principal_empty]) <| by
rw [sup_principal, union_compl_self, principal_univ]
#align filter.is_compl_principal Filter.isCompl_principal
theorem mem_inf_principal' {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ tᶜ ∪ s ∈ f := by
simp only [← le_principal_iff, (isCompl_principal s).le_left_iff, disjoint_assoc, inf_principal,
← (isCompl_principal (t ∩ sᶜ)).le_right_iff, compl_inter, compl_compl]
#align filter.mem_inf_principal' Filter.mem_inf_principal'
lemma mem_inf_principal {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ { x | x ∈ t → x ∈ s } ∈ f := by
simp only [mem_inf_principal', imp_iff_not_or, setOf_or, compl_def, setOf_mem_eq]
#align filter.mem_inf_principal Filter.mem_inf_principal
lemma iSup_inf_principal (f : ι → Filter α) (s : Set α) : ⨆ i, f i ⊓ 𝓟 s = (⨆ i, f i) ⊓ 𝓟 s := by
ext
simp only [mem_iSup, mem_inf_principal]
#align filter.supr_inf_principal Filter.iSup_inf_principal
theorem inf_principal_eq_bot {f : Filter α} {s : Set α} : f ⊓ 𝓟 s = ⊥ ↔ sᶜ ∈ f := by
rw [← empty_mem_iff_bot, mem_inf_principal]
simp only [mem_empty_iff_false, imp_false, compl_def]
#align filter.inf_principal_eq_bot Filter.inf_principal_eq_bot
theorem mem_of_eq_bot {f : Filter α} {s : Set α} (h : f ⊓ 𝓟 sᶜ = ⊥) : s ∈ f := by
rwa [inf_principal_eq_bot, compl_compl] at h
#align filter.mem_of_eq_bot Filter.mem_of_eq_bot
theorem diff_mem_inf_principal_compl {f : Filter α} {s : Set α} (hs : s ∈ f) (t : Set α) :
s \ t ∈ f ⊓ 𝓟 tᶜ :=
inter_mem_inf hs <| mem_principal_self tᶜ
#align filter.diff_mem_inf_principal_compl Filter.diff_mem_inf_principal_compl
theorem principal_le_iff {s : Set α} {f : Filter α} : 𝓟 s ≤ f ↔ ∀ V ∈ f, s ⊆ V := by
simp_rw [le_def, mem_principal]
#align filter.principal_le_iff Filter.principal_le_iff
@[simp]
theorem iInf_principal_finset {ι : Type w} (s : Finset ι) (f : ι → Set α) :
⨅ i ∈ s, 𝓟 (f i) = 𝓟 (⋂ i ∈ s, f i) := by
induction' s using Finset.induction_on with i s _ hs
· simp
· rw [Finset.iInf_insert, Finset.set_biInter_insert, hs, inf_principal]
#align filter.infi_principal_finset Filter.iInf_principal_finset
theorem iInf_principal {ι : Sort w} [Finite ι] (f : ι → Set α) : ⨅ i, 𝓟 (f i) = 𝓟 (⋂ i, f i) := by
cases nonempty_fintype (PLift ι)
rw [← iInf_plift_down, ← iInter_plift_down]
simpa using iInf_principal_finset Finset.univ (f <| PLift.down ·)
/-- A special case of `iInf_principal` that is safe to mark `simp`. -/
@[simp]
theorem iInf_principal' {ι : Type w} [Finite ι] (f : ι → Set α) : ⨅ i, 𝓟 (f i) = 𝓟 (⋂ i, f i) :=
iInf_principal _
#align filter.infi_principal Filter.iInf_principal
theorem iInf_principal_finite {ι : Type w} {s : Set ι} (hs : s.Finite) (f : ι → Set α) :
⨅ i ∈ s, 𝓟 (f i) = 𝓟 (⋂ i ∈ s, f i) := by
lift s to Finset ι using hs
exact mod_cast iInf_principal_finset s f
#align filter.infi_principal_finite Filter.iInf_principal_finite
end Lattice
@[mono, gcongr]
theorem join_mono {f₁ f₂ : Filter (Filter α)} (h : f₁ ≤ f₂) : join f₁ ≤ join f₂ := fun _ hs => h hs
#align filter.join_mono Filter.join_mono
/-! ### Eventually -/
/-- `f.Eventually p` or `∀ᶠ x in f, p x` mean that `{x | p x} ∈ f`. E.g., `∀ᶠ x in atTop, p x`
means that `p` holds true for sufficiently large `x`. -/
protected def Eventually (p : α → Prop) (f : Filter α) : Prop :=
{ x | p x } ∈ f
#align filter.eventually Filter.Eventually
@[inherit_doc Filter.Eventually]
notation3 "∀ᶠ "(...)" in "f", "r:(scoped p => Filter.Eventually p f) => r
theorem eventually_iff {f : Filter α} {P : α → Prop} : (∀ᶠ x in f, P x) ↔ { x | P x } ∈ f :=
Iff.rfl
#align filter.eventually_iff Filter.eventually_iff
@[simp]
theorem eventually_mem_set {s : Set α} {l : Filter α} : (∀ᶠ x in l, x ∈ s) ↔ s ∈ l :=
Iff.rfl
#align filter.eventually_mem_set Filter.eventually_mem_set
protected theorem ext' {f₁ f₂ : Filter α}
(h : ∀ p : α → Prop, (∀ᶠ x in f₁, p x) ↔ ∀ᶠ x in f₂, p x) : f₁ = f₂ :=
Filter.ext h
#align filter.ext' Filter.ext'
theorem Eventually.filter_mono {f₁ f₂ : Filter α} (h : f₁ ≤ f₂) {p : α → Prop}
(hp : ∀ᶠ x in f₂, p x) : ∀ᶠ x in f₁, p x :=
h hp
#align filter.eventually.filter_mono Filter.Eventually.filter_mono
theorem eventually_of_mem {f : Filter α} {P : α → Prop} {U : Set α} (hU : U ∈ f)
(h : ∀ x ∈ U, P x) : ∀ᶠ x in f, P x :=
mem_of_superset hU h
#align filter.eventually_of_mem Filter.eventually_of_mem
protected theorem Eventually.and {p q : α → Prop} {f : Filter α} :
f.Eventually p → f.Eventually q → ∀ᶠ x in f, p x ∧ q x :=
inter_mem
#align filter.eventually.and Filter.Eventually.and
@[simp] theorem eventually_true (f : Filter α) : ∀ᶠ _ in f, True := univ_mem
#align filter.eventually_true Filter.eventually_true
theorem eventually_of_forall {p : α → Prop} {f : Filter α} (hp : ∀ x, p x) : ∀ᶠ x in f, p x :=
univ_mem' hp
#align filter.eventually_of_forall Filter.eventually_of_forall
@[simp]
theorem eventually_false_iff_eq_bot {f : Filter α} : (∀ᶠ _ in f, False) ↔ f = ⊥ :=
empty_mem_iff_bot
#align filter.eventually_false_iff_eq_bot Filter.eventually_false_iff_eq_bot
@[simp]
theorem eventually_const {f : Filter α} [t : NeBot f] {p : Prop} : (∀ᶠ _ in f, p) ↔ p := by
by_cases h : p <;> simp [h, t.ne]
#align filter.eventually_const Filter.eventually_const
theorem eventually_iff_exists_mem {p : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x) ↔ ∃ v ∈ f, ∀ y ∈ v, p y :=
exists_mem_subset_iff.symm
#align filter.eventually_iff_exists_mem Filter.eventually_iff_exists_mem
theorem Eventually.exists_mem {p : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x) :
∃ v ∈ f, ∀ y ∈ v, p y :=
eventually_iff_exists_mem.1 hp
#align filter.eventually.exists_mem Filter.Eventually.exists_mem
theorem Eventually.mp {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ᶠ x in f, p x → q x) : ∀ᶠ x in f, q x :=
mp_mem hp hq
#align filter.eventually.mp Filter.Eventually.mp
theorem Eventually.mono {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ x, p x → q x) : ∀ᶠ x in f, q x :=
hp.mp (eventually_of_forall hq)
#align filter.eventually.mono Filter.Eventually.mono
theorem forall_eventually_of_eventually_forall {f : Filter α} {p : α → β → Prop}
(h : ∀ᶠ x in f, ∀ y, p x y) : ∀ y, ∀ᶠ x in f, p x y :=
fun y => h.mono fun _ h => h y
#align filter.forall_eventually_of_eventually_forall Filter.forall_eventually_of_eventually_forall
@[simp]
theorem eventually_and {p q : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x ∧ q x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in f, q x :=
inter_mem_iff
#align filter.eventually_and Filter.eventually_and
theorem Eventually.congr {f : Filter α} {p q : α → Prop} (h' : ∀ᶠ x in f, p x)
(h : ∀ᶠ x in f, p x ↔ q x) : ∀ᶠ x in f, q x :=
h'.mp (h.mono fun _ hx => hx.mp)
#align filter.eventually.congr Filter.Eventually.congr
theorem eventually_congr {f : Filter α} {p q : α → Prop} (h : ∀ᶠ x in f, p x ↔ q x) :
(∀ᶠ x in f, p x) ↔ ∀ᶠ x in f, q x :=
⟨fun hp => hp.congr h, fun hq => hq.congr <| by simpa only [Iff.comm] using h⟩
#align filter.eventually_congr Filter.eventually_congr
@[simp]
theorem eventually_all {ι : Sort*} [Finite ι] {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i, p i x) ↔ ∀ i, ∀ᶠ x in l, p i x := by
simpa only [Filter.Eventually, setOf_forall] using iInter_mem
#align filter.eventually_all Filter.eventually_all
@[simp]
theorem eventually_all_finite {ι} {I : Set ι} (hI : I.Finite) {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i ∈ I, p i x) ↔ ∀ i ∈ I, ∀ᶠ x in l, p i x := by
simpa only [Filter.Eventually, setOf_forall] using biInter_mem hI
#align filter.eventually_all_finite Filter.eventually_all_finite
alias _root_.Set.Finite.eventually_all := eventually_all_finite
#align set.finite.eventually_all Set.Finite.eventually_all
-- attribute [protected] Set.Finite.eventually_all
@[simp] theorem eventually_all_finset {ι} (I : Finset ι) {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i ∈ I, p i x) ↔ ∀ i ∈ I, ∀ᶠ x in l, p i x :=
I.finite_toSet.eventually_all
#align filter.eventually_all_finset Filter.eventually_all_finset
alias _root_.Finset.eventually_all := eventually_all_finset
#align finset.eventually_all Finset.eventually_all
-- attribute [protected] Finset.eventually_all
@[simp]
theorem eventually_or_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p ∨ q x) ↔ p ∨ ∀ᶠ x in f, q x :=
by_cases (fun h : p => by simp [h]) fun h => by simp [h]
#align filter.eventually_or_distrib_left Filter.eventually_or_distrib_left
@[simp]
theorem eventually_or_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x ∨ q) ↔ (∀ᶠ x in f, p x) ∨ q := by
simp only [@or_comm _ q, eventually_or_distrib_left]
#align filter.eventually_or_distrib_right Filter.eventually_or_distrib_right
theorem eventually_imp_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p → q x) ↔ p → ∀ᶠ x in f, q x :=
eventually_all
#align filter.eventually_imp_distrib_left Filter.eventually_imp_distrib_left
@[simp]
theorem eventually_bot {p : α → Prop} : ∀ᶠ x in ⊥, p x :=
⟨⟩
#align filter.eventually_bot Filter.eventually_bot
@[simp]
theorem eventually_top {p : α → Prop} : (∀ᶠ x in ⊤, p x) ↔ ∀ x, p x :=
Iff.rfl
#align filter.eventually_top Filter.eventually_top
@[simp]
theorem eventually_sup {p : α → Prop} {f g : Filter α} :
(∀ᶠ x in f ⊔ g, p x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in g, p x :=
Iff.rfl
#align filter.eventually_sup Filter.eventually_sup
@[simp]
theorem eventually_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∀ᶠ x in sSup fs, p x) ↔ ∀ f ∈ fs, ∀ᶠ x in f, p x :=
Iff.rfl
#align filter.eventually_Sup Filter.eventually_sSup
@[simp]
theorem eventually_iSup {p : α → Prop} {fs : ι → Filter α} :
(∀ᶠ x in ⨆ b, fs b, p x) ↔ ∀ b, ∀ᶠ x in fs b, p x :=
mem_iSup
#align filter.eventually_supr Filter.eventually_iSup
@[simp]
theorem eventually_principal {a : Set α} {p : α → Prop} : (∀ᶠ x in 𝓟 a, p x) ↔ ∀ x ∈ a, p x :=
Iff.rfl
#align filter.eventually_principal Filter.eventually_principal
theorem Eventually.forall_mem {α : Type*} {f : Filter α} {s : Set α} {P : α → Prop}
(hP : ∀ᶠ x in f, P x) (hf : 𝓟 s ≤ f) : ∀ x ∈ s, P x :=
Filter.eventually_principal.mp (hP.filter_mono hf)
theorem eventually_inf {f g : Filter α} {p : α → Prop} :
(∀ᶠ x in f ⊓ g, p x) ↔ ∃ s ∈ f, ∃ t ∈ g, ∀ x ∈ s ∩ t, p x :=
mem_inf_iff_superset
#align filter.eventually_inf Filter.eventually_inf
theorem eventually_inf_principal {f : Filter α} {p : α → Prop} {s : Set α} :
(∀ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∀ᶠ x in f, x ∈ s → p x :=
mem_inf_principal
#align filter.eventually_inf_principal Filter.eventually_inf_principal
/-! ### Frequently -/
/-- `f.Frequently p` or `∃ᶠ x in f, p x` mean that `{x | ¬p x} ∉ f`. E.g., `∃ᶠ x in atTop, p x`
means that there exist arbitrarily large `x` for which `p` holds true. -/
protected def Frequently (p : α → Prop) (f : Filter α) : Prop :=
¬∀ᶠ x in f, ¬p x
#align filter.frequently Filter.Frequently
@[inherit_doc Filter.Frequently]
notation3 "∃ᶠ "(...)" in "f", "r:(scoped p => Filter.Frequently p f) => r
theorem Eventually.frequently {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ᶠ x in f, p x) :
∃ᶠ x in f, p x :=
compl_not_mem h
#align filter.eventually.frequently Filter.Eventually.frequently
theorem frequently_of_forall {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ x, p x) :
∃ᶠ x in f, p x :=
Eventually.frequently (eventually_of_forall h)
#align filter.frequently_of_forall Filter.frequently_of_forall
theorem Frequently.mp {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ᶠ x in f, p x → q x) : ∃ᶠ x in f, q x :=
mt (fun hq => hq.mp <| hpq.mono fun _ => mt) h
#align filter.frequently.mp Filter.Frequently.mp
theorem Frequently.filter_mono {p : α → Prop} {f g : Filter α} (h : ∃ᶠ x in f, p x) (hle : f ≤ g) :
∃ᶠ x in g, p x :=
mt (fun h' => h'.filter_mono hle) h
#align filter.frequently.filter_mono Filter.Frequently.filter_mono
theorem Frequently.mono {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ x, p x → q x) : ∃ᶠ x in f, q x :=
h.mp (eventually_of_forall hpq)
#align filter.frequently.mono Filter.Frequently.mono
theorem Frequently.and_eventually {p q : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x)
(hq : ∀ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
refine mt (fun h => hq.mp <| h.mono ?_) hp
exact fun x hpq hq hp => hpq ⟨hp, hq⟩
#align filter.frequently.and_eventually Filter.Frequently.and_eventually
theorem Eventually.and_frequently {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∃ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
simpa only [and_comm] using hq.and_eventually hp
#align filter.eventually.and_frequently Filter.Eventually.and_frequently
theorem Frequently.exists {p : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x) : ∃ x, p x := by
by_contra H
replace H : ∀ᶠ x in f, ¬p x := eventually_of_forall (not_exists.1 H)
exact hp H
#align filter.frequently.exists Filter.Frequently.exists
theorem Eventually.exists {p : α → Prop} {f : Filter α} [NeBot f] (hp : ∀ᶠ x in f, p x) :
∃ x, p x :=
hp.frequently.exists
#align filter.eventually.exists Filter.Eventually.exists
lemma frequently_iff_neBot {p : α → Prop} : (∃ᶠ x in l, p x) ↔ NeBot (l ⊓ 𝓟 {x | p x}) := by
rw [neBot_iff, Ne, inf_principal_eq_bot]; rfl
lemma frequently_mem_iff_neBot {s : Set α} : (∃ᶠ x in l, x ∈ s) ↔ NeBot (l ⊓ 𝓟 s) :=
frequently_iff_neBot
theorem frequently_iff_forall_eventually_exists_and {p : α → Prop} {f : Filter α} :
(∃ᶠ x in f, p x) ↔ ∀ {q : α → Prop}, (∀ᶠ x in f, q x) → ∃ x, p x ∧ q x :=
⟨fun hp q hq => (hp.and_eventually hq).exists, fun H hp => by
simpa only [and_not_self_iff, exists_false] using H hp⟩
#align filter.frequently_iff_forall_eventually_exists_and Filter.frequently_iff_forall_eventually_exists_and
theorem frequently_iff {f : Filter α} {P : α → Prop} :
(∃ᶠ x in f, P x) ↔ ∀ {U}, U ∈ f → ∃ x ∈ U, P x := by
simp only [frequently_iff_forall_eventually_exists_and, @and_comm (P _)]
rfl
#align filter.frequently_iff Filter.frequently_iff
@[simp]
theorem not_eventually {p : α → Prop} {f : Filter α} : (¬∀ᶠ x in f, p x) ↔ ∃ᶠ x in f, ¬p x := by
simp [Filter.Frequently]
#align filter.not_eventually Filter.not_eventually
@[simp]
theorem not_frequently {p : α → Prop} {f : Filter α} : (¬∃ᶠ x in f, p x) ↔ ∀ᶠ x in f, ¬p x := by
simp only [Filter.Frequently, not_not]
#align filter.not_frequently Filter.not_frequently
@[simp]
theorem frequently_true_iff_neBot (f : Filter α) : (∃ᶠ _ in f, True) ↔ NeBot f := by
simp [frequently_iff_neBot]
#align filter.frequently_true_iff_ne_bot Filter.frequently_true_iff_neBot
@[simp]
theorem frequently_false (f : Filter α) : ¬∃ᶠ _ in f, False := by simp
#align filter.frequently_false Filter.frequently_false
@[simp]
theorem frequently_const {f : Filter α} [NeBot f] {p : Prop} : (∃ᶠ _ in f, p) ↔ p := by
by_cases p <;> simp [*]
#align filter.frequently_const Filter.frequently_const
@[simp]
theorem frequently_or_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x ∨ q x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, ← not_and_or, not_or, eventually_and]
#align filter.frequently_or_distrib Filter.frequently_or_distrib
theorem frequently_or_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∨ q x) ↔ p ∨ ∃ᶠ x in f, q x := by simp
#align filter.frequently_or_distrib_left Filter.frequently_or_distrib_left
theorem frequently_or_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∨ q) ↔ (∃ᶠ x in f, p x) ∨ q := by simp
#align filter.frequently_or_distrib_right Filter.frequently_or_distrib_right
theorem frequently_imp_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x → q x) ↔ (∀ᶠ x in f, p x) → ∃ᶠ x in f, q x := by
simp [imp_iff_not_or]
#align filter.frequently_imp_distrib Filter.frequently_imp_distrib
theorem frequently_imp_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p → q x) ↔ p → ∃ᶠ x in f, q x := by simp [frequently_imp_distrib]
#align filter.frequently_imp_distrib_left Filter.frequently_imp_distrib_left
theorem frequently_imp_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x → q) ↔ (∀ᶠ x in f, p x) → q := by
set_option tactic.skipAssignedInstances false in simp [frequently_imp_distrib]
#align filter.frequently_imp_distrib_right Filter.frequently_imp_distrib_right
theorem eventually_imp_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x → q) ↔ (∃ᶠ x in f, p x) → q := by
simp only [imp_iff_not_or, eventually_or_distrib_right, not_frequently]
#align filter.eventually_imp_distrib_right Filter.eventually_imp_distrib_right
@[simp]
theorem frequently_and_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∧ q x) ↔ p ∧ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, not_and, eventually_imp_distrib_left, Classical.not_imp]
#align filter.frequently_and_distrib_left Filter.frequently_and_distrib_left
@[simp]
theorem frequently_and_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∧ q) ↔ (∃ᶠ x in f, p x) ∧ q := by
simp only [@and_comm _ q, frequently_and_distrib_left]
#align filter.frequently_and_distrib_right Filter.frequently_and_distrib_right
@[simp]
theorem frequently_bot {p : α → Prop} : ¬∃ᶠ x in ⊥, p x := by simp
#align filter.frequently_bot Filter.frequently_bot
@[simp]
theorem frequently_top {p : α → Prop} : (∃ᶠ x in ⊤, p x) ↔ ∃ x, p x := by simp [Filter.Frequently]
#align filter.frequently_top Filter.frequently_top
@[simp]
theorem frequently_principal {a : Set α} {p : α → Prop} : (∃ᶠ x in 𝓟 a, p x) ↔ ∃ x ∈ a, p x := by
simp [Filter.Frequently, not_forall]
#align filter.frequently_principal Filter.frequently_principal
theorem frequently_inf_principal {f : Filter α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∃ᶠ x in f, x ∈ s ∧ p x := by
simp only [Filter.Frequently, eventually_inf_principal, not_and]
alias ⟨Frequently.of_inf_principal, Frequently.inf_principal⟩ := frequently_inf_principal
theorem frequently_sup {p : α → Prop} {f g : Filter α} :
(∃ᶠ x in f ⊔ g, p x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in g, p x := by
simp only [Filter.Frequently, eventually_sup, not_and_or]
#align filter.frequently_sup Filter.frequently_sup
@[simp]
theorem frequently_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∃ᶠ x in sSup fs, p x) ↔ ∃ f ∈ fs, ∃ᶠ x in f, p x := by
simp only [Filter.Frequently, not_forall, eventually_sSup, exists_prop]
#align filter.frequently_Sup Filter.frequently_sSup
@[simp]
theorem frequently_iSup {p : α → Prop} {fs : β → Filter α} :
(∃ᶠ x in ⨆ b, fs b, p x) ↔ ∃ b, ∃ᶠ x in fs b, p x := by
simp only [Filter.Frequently, eventually_iSup, not_forall]
#align filter.frequently_supr Filter.frequently_iSup
theorem Eventually.choice {r : α → β → Prop} {l : Filter α} [l.NeBot] (h : ∀ᶠ x in l, ∃ y, r x y) :
∃ f : α → β, ∀ᶠ x in l, r x (f x) := by
haveI : Nonempty β := let ⟨_, hx⟩ := h.exists; hx.nonempty
choose! f hf using fun x (hx : ∃ y, r x y) => hx
exact ⟨f, h.mono hf⟩
#align filter.eventually.choice Filter.Eventually.choice
/-!
### Relation “eventually equal”
-/
/-- Two functions `f` and `g` are *eventually equal* along a filter `l` if the set of `x` such that
`f x = g x` belongs to `l`. -/
def EventuallyEq (l : Filter α) (f g : α → β) : Prop :=
∀ᶠ x in l, f x = g x
#align filter.eventually_eq Filter.EventuallyEq
@[inherit_doc]
notation:50 f " =ᶠ[" l:50 "] " g:50 => EventuallyEq l f g
theorem EventuallyEq.eventually {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) :
∀ᶠ x in l, f x = g x :=
h
#align filter.eventually_eq.eventually Filter.EventuallyEq.eventually
theorem EventuallyEq.rw {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) (p : α → β → Prop)
(hf : ∀ᶠ x in l, p x (f x)) : ∀ᶠ x in l, p x (g x) :=
hf.congr <| h.mono fun _ hx => hx ▸ Iff.rfl
#align filter.eventually_eq.rw Filter.EventuallyEq.rw
theorem eventuallyEq_set {s t : Set α} {l : Filter α} : s =ᶠ[l] t ↔ ∀ᶠ x in l, x ∈ s ↔ x ∈ t :=
eventually_congr <| eventually_of_forall fun _ ↦ eq_iff_iff
#align filter.eventually_eq_set Filter.eventuallyEq_set
alias ⟨EventuallyEq.mem_iff, Eventually.set_eq⟩ := eventuallyEq_set
#align filter.eventually_eq.mem_iff Filter.EventuallyEq.mem_iff
#align filter.eventually.set_eq Filter.Eventually.set_eq
@[simp]
theorem eventuallyEq_univ {s : Set α} {l : Filter α} : s =ᶠ[l] univ ↔ s ∈ l := by
simp [eventuallyEq_set]
#align filter.eventually_eq_univ Filter.eventuallyEq_univ
theorem EventuallyEq.exists_mem {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) :
∃ s ∈ l, EqOn f g s :=
Eventually.exists_mem h
#align filter.eventually_eq.exists_mem Filter.EventuallyEq.exists_mem
theorem eventuallyEq_of_mem {l : Filter α} {f g : α → β} {s : Set α} (hs : s ∈ l) (h : EqOn f g s) :
f =ᶠ[l] g :=
eventually_of_mem hs h
#align filter.eventually_eq_of_mem Filter.eventuallyEq_of_mem
theorem eventuallyEq_iff_exists_mem {l : Filter α} {f g : α → β} :
f =ᶠ[l] g ↔ ∃ s ∈ l, EqOn f g s :=
eventually_iff_exists_mem
#align filter.eventually_eq_iff_exists_mem Filter.eventuallyEq_iff_exists_mem
theorem EventuallyEq.filter_mono {l l' : Filter α} {f g : α → β} (h₁ : f =ᶠ[l] g) (h₂ : l' ≤ l) :
f =ᶠ[l'] g :=
h₂ h₁
#align filter.eventually_eq.filter_mono Filter.EventuallyEq.filter_mono
@[refl, simp]
theorem EventuallyEq.refl (l : Filter α) (f : α → β) : f =ᶠ[l] f :=
eventually_of_forall fun _ => rfl
#align filter.eventually_eq.refl Filter.EventuallyEq.refl
protected theorem EventuallyEq.rfl {l : Filter α} {f : α → β} : f =ᶠ[l] f :=
EventuallyEq.refl l f
#align filter.eventually_eq.rfl Filter.EventuallyEq.rfl
@[symm]
theorem EventuallyEq.symm {f g : α → β} {l : Filter α} (H : f =ᶠ[l] g) : g =ᶠ[l] f :=
H.mono fun _ => Eq.symm
#align filter.eventually_eq.symm Filter.EventuallyEq.symm
@[trans]
theorem EventuallyEq.trans {l : Filter α} {f g h : α → β} (H₁ : f =ᶠ[l] g) (H₂ : g =ᶠ[l] h) :
f =ᶠ[l] h :=
H₂.rw (fun x y => f x = y) H₁
#align filter.eventually_eq.trans Filter.EventuallyEq.trans
instance : Trans ((· =ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· =ᶠ[l] ·) (· =ᶠ[l] ·) where
trans := EventuallyEq.trans
theorem EventuallyEq.prod_mk {l} {f f' : α → β} (hf : f =ᶠ[l] f') {g g' : α → γ} (hg : g =ᶠ[l] g') :
(fun x => (f x, g x)) =ᶠ[l] fun x => (f' x, g' x) :=
hf.mp <|
hg.mono <| by
intros
simp only [*]
#align filter.eventually_eq.prod_mk Filter.EventuallyEq.prod_mk
-- See `EventuallyEq.comp_tendsto` further below for a similar statement w.r.t.
-- composition on the right.
theorem EventuallyEq.fun_comp {f g : α → β} {l : Filter α} (H : f =ᶠ[l] g) (h : β → γ) :
h ∘ f =ᶠ[l] h ∘ g :=
H.mono fun _ hx => congr_arg h hx
#align filter.eventually_eq.fun_comp Filter.EventuallyEq.fun_comp
theorem EventuallyEq.comp₂ {δ} {f f' : α → β} {g g' : α → γ} {l} (Hf : f =ᶠ[l] f') (h : β → γ → δ)
(Hg : g =ᶠ[l] g') : (fun x => h (f x) (g x)) =ᶠ[l] fun x => h (f' x) (g' x) :=
(Hf.prod_mk Hg).fun_comp (uncurry h)
#align filter.eventually_eq.comp₂ Filter.EventuallyEq.comp₂
@[to_additive]
theorem EventuallyEq.mul [Mul β] {f f' g g' : α → β} {l : Filter α} (h : f =ᶠ[l] g)
(h' : f' =ᶠ[l] g') : (fun x => f x * f' x) =ᶠ[l] fun x => g x * g' x :=
h.comp₂ (· * ·) h'
#align filter.eventually_eq.mul Filter.EventuallyEq.mul
#align filter.eventually_eq.add Filter.EventuallyEq.add
@[to_additive const_smul]
theorem EventuallyEq.pow_const {γ} [Pow β γ] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) (c : γ):
(fun x => f x ^ c) =ᶠ[l] fun x => g x ^ c :=
h.fun_comp (· ^ c)
#align filter.eventually_eq.const_smul Filter.EventuallyEq.const_smul
@[to_additive]
theorem EventuallyEq.inv [Inv β] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) :
(fun x => (f x)⁻¹) =ᶠ[l] fun x => (g x)⁻¹ :=
h.fun_comp Inv.inv
#align filter.eventually_eq.inv Filter.EventuallyEq.inv
#align filter.eventually_eq.neg Filter.EventuallyEq.neg
@[to_additive]
theorem EventuallyEq.div [Div β] {f f' g g' : α → β} {l : Filter α} (h : f =ᶠ[l] g)
(h' : f' =ᶠ[l] g') : (fun x => f x / f' x) =ᶠ[l] fun x => g x / g' x :=
h.comp₂ (· / ·) h'
#align filter.eventually_eq.div Filter.EventuallyEq.div
#align filter.eventually_eq.sub Filter.EventuallyEq.sub
attribute [to_additive] EventuallyEq.const_smul
#align filter.eventually_eq.const_vadd Filter.EventuallyEq.const_vadd
@[to_additive]
theorem EventuallyEq.smul {𝕜} [SMul 𝕜 β] {l : Filter α} {f f' : α → 𝕜} {g g' : α → β}
(hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') : (fun x => f x • g x) =ᶠ[l] fun x => f' x • g' x :=
hf.comp₂ (· • ·) hg
#align filter.eventually_eq.smul Filter.EventuallyEq.smul
#align filter.eventually_eq.vadd Filter.EventuallyEq.vadd
theorem EventuallyEq.sup [Sup β] {l : Filter α} {f f' g g' : α → β} (hf : f =ᶠ[l] f')
(hg : g =ᶠ[l] g') : (fun x => f x ⊔ g x) =ᶠ[l] fun x => f' x ⊔ g' x :=
hf.comp₂ (· ⊔ ·) hg
#align filter.eventually_eq.sup Filter.EventuallyEq.sup
theorem EventuallyEq.inf [Inf β] {l : Filter α} {f f' g g' : α → β} (hf : f =ᶠ[l] f')
(hg : g =ᶠ[l] g') : (fun x => f x ⊓ g x) =ᶠ[l] fun x => f' x ⊓ g' x :=
hf.comp₂ (· ⊓ ·) hg
#align filter.eventually_eq.inf Filter.EventuallyEq.inf
theorem EventuallyEq.preimage {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) (s : Set β) :
f ⁻¹' s =ᶠ[l] g ⁻¹' s :=
h.fun_comp s
#align filter.eventually_eq.preimage Filter.EventuallyEq.preimage
theorem EventuallyEq.inter {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s ∩ s' : Set α) =ᶠ[l] (t ∩ t' : Set α) :=
h.comp₂ (· ∧ ·) h'
#align filter.eventually_eq.inter Filter.EventuallyEq.inter
theorem EventuallyEq.union {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s ∪ s' : Set α) =ᶠ[l] (t ∪ t' : Set α) :=
h.comp₂ (· ∨ ·) h'
#align filter.eventually_eq.union Filter.EventuallyEq.union
theorem EventuallyEq.compl {s t : Set α} {l : Filter α} (h : s =ᶠ[l] t) :
(sᶜ : Set α) =ᶠ[l] (tᶜ : Set α) :=
h.fun_comp Not
#align filter.eventually_eq.compl Filter.EventuallyEq.compl
theorem EventuallyEq.diff {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s \ s' : Set α) =ᶠ[l] (t \ t' : Set α) :=
h.inter h'.compl
#align filter.eventually_eq.diff Filter.EventuallyEq.diff
theorem eventuallyEq_empty {s : Set α} {l : Filter α} : s =ᶠ[l] (∅ : Set α) ↔ ∀ᶠ x in l, x ∉ s :=
eventuallyEq_set.trans <| by simp
#align filter.eventually_eq_empty Filter.eventuallyEq_empty
theorem inter_eventuallyEq_left {s t : Set α} {l : Filter α} :
(s ∩ t : Set α) =ᶠ[l] s ↔ ∀ᶠ x in l, x ∈ s → x ∈ t := by
simp only [eventuallyEq_set, mem_inter_iff, and_iff_left_iff_imp]
#align filter.inter_eventually_eq_left Filter.inter_eventuallyEq_left
theorem inter_eventuallyEq_right {s t : Set α} {l : Filter α} :
(s ∩ t : Set α) =ᶠ[l] t ↔ ∀ᶠ x in l, x ∈ t → x ∈ s := by
rw [inter_comm, inter_eventuallyEq_left]
#align filter.inter_eventually_eq_right Filter.inter_eventuallyEq_right
@[simp]
theorem eventuallyEq_principal {s : Set α} {f g : α → β} : f =ᶠ[𝓟 s] g ↔ EqOn f g s :=
Iff.rfl
#align filter.eventually_eq_principal Filter.eventuallyEq_principal
theorem eventuallyEq_inf_principal_iff {F : Filter α} {s : Set α} {f g : α → β} :
f =ᶠ[F ⊓ 𝓟 s] g ↔ ∀ᶠ x in F, x ∈ s → f x = g x :=
eventually_inf_principal
#align filter.eventually_eq_inf_principal_iff Filter.eventuallyEq_inf_principal_iff
theorem EventuallyEq.sub_eq [AddGroup β] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) :
f - g =ᶠ[l] 0 := by simpa using ((EventuallyEq.refl l f).sub h).symm
#align filter.eventually_eq.sub_eq Filter.EventuallyEq.sub_eq
theorem eventuallyEq_iff_sub [AddGroup β] {f g : α → β} {l : Filter α} :
f =ᶠ[l] g ↔ f - g =ᶠ[l] 0 :=
⟨fun h => h.sub_eq, fun h => by simpa using h.add (EventuallyEq.refl l g)⟩
#align filter.eventually_eq_iff_sub Filter.eventuallyEq_iff_sub
section LE
variable [LE β] {l : Filter α}
/-- A function `f` is eventually less than or equal to a function `g` at a filter `l`. -/
def EventuallyLE (l : Filter α) (f g : α → β) : Prop :=
∀ᶠ x in l, f x ≤ g x
#align filter.eventually_le Filter.EventuallyLE
@[inherit_doc]
notation:50 f " ≤ᶠ[" l:50 "] " g:50 => EventuallyLE l f g
theorem EventuallyLE.congr {f f' g g' : α → β} (H : f ≤ᶠ[l] g) (hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') :
f' ≤ᶠ[l] g' :=
H.mp <| hg.mp <| hf.mono fun x hf hg H => by rwa [hf, hg] at H
#align filter.eventually_le.congr Filter.EventuallyLE.congr
theorem eventuallyLE_congr {f f' g g' : α → β} (hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') :
f ≤ᶠ[l] g ↔ f' ≤ᶠ[l] g' :=
⟨fun H => H.congr hf hg, fun H => H.congr hf.symm hg.symm⟩
#align filter.eventually_le_congr Filter.eventuallyLE_congr
end LE
section Preorder
variable [Preorder β] {l : Filter α} {f g h : α → β}
theorem EventuallyEq.le (h : f =ᶠ[l] g) : f ≤ᶠ[l] g :=
h.mono fun _ => le_of_eq
#align filter.eventually_eq.le Filter.EventuallyEq.le
@[refl]
theorem EventuallyLE.refl (l : Filter α) (f : α → β) : f ≤ᶠ[l] f :=
EventuallyEq.rfl.le
#align filter.eventually_le.refl Filter.EventuallyLE.refl
theorem EventuallyLE.rfl : f ≤ᶠ[l] f :=
EventuallyLE.refl l f
#align filter.eventually_le.rfl Filter.EventuallyLE.rfl
@[trans]
theorem EventuallyLE.trans (H₁ : f ≤ᶠ[l] g) (H₂ : g ≤ᶠ[l] h) : f ≤ᶠ[l] h :=
H₂.mp <| H₁.mono fun _ => le_trans
#align filter.eventually_le.trans Filter.EventuallyLE.trans
instance : Trans ((· ≤ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· ≤ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyLE.trans
@[trans]
theorem EventuallyEq.trans_le (H₁ : f =ᶠ[l] g) (H₂ : g ≤ᶠ[l] h) : f ≤ᶠ[l] h :=
H₁.le.trans H₂
#align filter.eventually_eq.trans_le Filter.EventuallyEq.trans_le
instance : Trans ((· =ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· ≤ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyEq.trans_le
@[trans]
theorem EventuallyLE.trans_eq (H₁ : f ≤ᶠ[l] g) (H₂ : g =ᶠ[l] h) : f ≤ᶠ[l] h :=
H₁.trans H₂.le
#align filter.eventually_le.trans_eq Filter.EventuallyLE.trans_eq
instance : Trans ((· ≤ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· =ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyLE.trans_eq
end Preorder
theorem EventuallyLE.antisymm [PartialOrder β] {l : Filter α} {f g : α → β} (h₁ : f ≤ᶠ[l] g)
(h₂ : g ≤ᶠ[l] f) : f =ᶠ[l] g :=
h₂.mp <| h₁.mono fun _ => le_antisymm
#align filter.eventually_le.antisymm Filter.EventuallyLE.antisymm
theorem eventuallyLE_antisymm_iff [PartialOrder β] {l : Filter α} {f g : α → β} :
f =ᶠ[l] g ↔ f ≤ᶠ[l] g ∧ g ≤ᶠ[l] f := by
simp only [EventuallyEq, EventuallyLE, le_antisymm_iff, eventually_and]
#align filter.eventually_le_antisymm_iff Filter.eventuallyLE_antisymm_iff
theorem EventuallyLE.le_iff_eq [PartialOrder β] {l : Filter α} {f g : α → β} (h : f ≤ᶠ[l] g) :
g ≤ᶠ[l] f ↔ g =ᶠ[l] f :=
⟨fun h' => h'.antisymm h, EventuallyEq.le⟩
#align filter.eventually_le.le_iff_eq Filter.EventuallyLE.le_iff_eq
theorem Eventually.ne_of_lt [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ᶠ x in l, f x < g x) :
∀ᶠ x in l, f x ≠ g x :=
h.mono fun _ hx => hx.ne
#align filter.eventually.ne_of_lt Filter.Eventually.ne_of_lt
theorem Eventually.ne_top_of_lt [PartialOrder β] [OrderTop β] {l : Filter α} {f g : α → β}
(h : ∀ᶠ x in l, f x < g x) : ∀ᶠ x in l, f x ≠ ⊤ :=
h.mono fun _ hx => hx.ne_top
#align filter.eventually.ne_top_of_lt Filter.Eventually.ne_top_of_lt
theorem Eventually.lt_top_of_ne [PartialOrder β] [OrderTop β] {l : Filter α} {f : α → β}
(h : ∀ᶠ x in l, f x ≠ ⊤) : ∀ᶠ x in l, f x < ⊤ :=
h.mono fun _ hx => hx.lt_top
#align filter.eventually.lt_top_of_ne Filter.Eventually.lt_top_of_ne
theorem Eventually.lt_top_iff_ne_top [PartialOrder β] [OrderTop β] {l : Filter α} {f : α → β} :
(∀ᶠ x in l, f x < ⊤) ↔ ∀ᶠ x in l, f x ≠ ⊤ :=
⟨Eventually.ne_of_lt, Eventually.lt_top_of_ne⟩
#align filter.eventually.lt_top_iff_ne_top Filter.Eventually.lt_top_iff_ne_top
@[mono]
theorem EventuallyLE.inter {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : s' ≤ᶠ[l] t') :
(s ∩ s' : Set α) ≤ᶠ[l] (t ∩ t' : Set α) :=
h'.mp <| h.mono fun _ => And.imp
#align filter.eventually_le.inter Filter.EventuallyLE.inter
@[mono]
theorem EventuallyLE.union {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : s' ≤ᶠ[l] t') :
(s ∪ s' : Set α) ≤ᶠ[l] (t ∪ t' : Set α) :=
h'.mp <| h.mono fun _ => Or.imp
#align filter.eventually_le.union Filter.EventuallyLE.union
protected lemma EventuallyLE.iUnion [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i ≤ᶠ[l] t i) : (⋃ i, s i) ≤ᶠ[l] ⋃ i, t i :=
(eventually_all.2 h).mono fun _x hx hx' ↦
let ⟨i, hi⟩ := mem_iUnion.1 hx'; mem_iUnion.2 ⟨i, hx i hi⟩
protected lemma EventuallyEq.iUnion [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i =ᶠ[l] t i) : (⋃ i, s i) =ᶠ[l] ⋃ i, t i :=
(EventuallyLE.iUnion fun i ↦ (h i).le).antisymm <| .iUnion fun i ↦ (h i).symm.le
protected lemma EventuallyLE.iInter [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i ≤ᶠ[l] t i) : (⋂ i, s i) ≤ᶠ[l] ⋂ i, t i :=
(eventually_all.2 h).mono fun _x hx hx' ↦ mem_iInter.2 fun i ↦ hx i (mem_iInter.1 hx' i)
protected lemma EventuallyEq.iInter [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i =ᶠ[l] t i) : (⋂ i, s i) =ᶠ[l] ⋂ i, t i :=
(EventuallyLE.iInter fun i ↦ (h i).le).antisymm <| .iInter fun i ↦ (h i).symm.le
lemma _root_.Set.Finite.eventuallyLE_iUnion {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋃ i ∈ s, f i) ≤ᶠ[l] (⋃ i ∈ s, g i) := by
have := hs.to_subtype
rw [biUnion_eq_iUnion, biUnion_eq_iUnion]
exact .iUnion fun i ↦ hle i.1 i.2
alias EventuallyLE.biUnion := Set.Finite.eventuallyLE_iUnion
lemma _root_.Set.Finite.eventuallyEq_iUnion {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋃ i ∈ s, f i) =ᶠ[l] (⋃ i ∈ s, g i) :=
(EventuallyLE.biUnion hs fun i hi ↦ (heq i hi).le).antisymm <|
.biUnion hs fun i hi ↦ (heq i hi).symm.le
alias EventuallyEq.biUnion := Set.Finite.eventuallyEq_iUnion
lemma _root_.Set.Finite.eventuallyLE_iInter {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋂ i ∈ s, f i) ≤ᶠ[l] (⋂ i ∈ s, g i) := by
have := hs.to_subtype
rw [biInter_eq_iInter, biInter_eq_iInter]
exact .iInter fun i ↦ hle i.1 i.2
alias EventuallyLE.biInter := Set.Finite.eventuallyLE_iInter
lemma _root_.Set.Finite.eventuallyEq_iInter {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋂ i ∈ s, f i) =ᶠ[l] (⋂ i ∈ s, g i) :=
(EventuallyLE.biInter hs fun i hi ↦ (heq i hi).le).antisymm <|
.biInter hs fun i hi ↦ (heq i hi).symm.le
alias EventuallyEq.biInter := Set.Finite.eventuallyEq_iInter
lemma _root_.Finset.eventuallyLE_iUnion {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋃ i ∈ s, f i) ≤ᶠ[l] (⋃ i ∈ s, g i) :=
.biUnion s.finite_toSet hle
lemma _root_.Finset.eventuallyEq_iUnion {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋃ i ∈ s, f i) =ᶠ[l] (⋃ i ∈ s, g i) :=
.biUnion s.finite_toSet heq
lemma _root_.Finset.eventuallyLE_iInter {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋂ i ∈ s, f i) ≤ᶠ[l] (⋂ i ∈ s, g i) :=
.biInter s.finite_toSet hle
lemma _root_.Finset.eventuallyEq_iInter {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋂ i ∈ s, f i) =ᶠ[l] (⋂ i ∈ s, g i) :=
.biInter s.finite_toSet heq
@[mono]
theorem EventuallyLE.compl {s t : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) :
(tᶜ : Set α) ≤ᶠ[l] (sᶜ : Set α) :=
h.mono fun _ => mt
#align filter.eventually_le.compl Filter.EventuallyLE.compl
@[mono]
theorem EventuallyLE.diff {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : t' ≤ᶠ[l] s') :
(s \ s' : Set α) ≤ᶠ[l] (t \ t' : Set α) :=
h.inter h'.compl
#align filter.eventually_le.diff Filter.EventuallyLE.diff
theorem set_eventuallyLE_iff_mem_inf_principal {s t : Set α} {l : Filter α} :
s ≤ᶠ[l] t ↔ t ∈ l ⊓ 𝓟 s :=
eventually_inf_principal.symm
#align filter.set_eventually_le_iff_mem_inf_principal Filter.set_eventuallyLE_iff_mem_inf_principal
theorem set_eventuallyLE_iff_inf_principal_le {s t : Set α} {l : Filter α} :
s ≤ᶠ[l] t ↔ l ⊓ 𝓟 s ≤ l ⊓ 𝓟 t :=
set_eventuallyLE_iff_mem_inf_principal.trans <| by
simp only [le_inf_iff, inf_le_left, true_and_iff, le_principal_iff]
#align filter.set_eventually_le_iff_inf_principal_le Filter.set_eventuallyLE_iff_inf_principal_le
theorem set_eventuallyEq_iff_inf_principal {s t : Set α} {l : Filter α} :
s =ᶠ[l] t ↔ l ⊓ 𝓟 s = l ⊓ 𝓟 t := by
simp only [eventuallyLE_antisymm_iff, le_antisymm_iff, set_eventuallyLE_iff_inf_principal_le]
#align filter.set_eventually_eq_iff_inf_principal Filter.set_eventuallyEq_iff_inf_principal
theorem EventuallyLE.mul_le_mul [MulZeroClass β] [PartialOrder β] [PosMulMono β] [MulPosMono β]
{l : Filter α} {f₁ f₂ g₁ g₂ : α → β} (hf : f₁ ≤ᶠ[l] f₂) (hg : g₁ ≤ᶠ[l] g₂) (hg₀ : 0 ≤ᶠ[l] g₁)
(hf₀ : 0 ≤ᶠ[l] f₂) : f₁ * g₁ ≤ᶠ[l] f₂ * g₂ := by
filter_upwards [hf, hg, hg₀, hf₀] with x using _root_.mul_le_mul
#align filter.eventually_le.mul_le_mul Filter.EventuallyLE.mul_le_mul
@[to_additive EventuallyLE.add_le_add]
theorem EventuallyLE.mul_le_mul' [Mul β] [Preorder β] [CovariantClass β β (· * ·) (· ≤ ·)]
[CovariantClass β β (swap (· * ·)) (· ≤ ·)] {l : Filter α} {f₁ f₂ g₁ g₂ : α → β}
(hf : f₁ ≤ᶠ[l] f₂) (hg : g₁ ≤ᶠ[l] g₂) : f₁ * g₁ ≤ᶠ[l] f₂ * g₂ := by
filter_upwards [hf, hg] with x hfx hgx using _root_.mul_le_mul' hfx hgx
#align filter.eventually_le.mul_le_mul' Filter.EventuallyLE.mul_le_mul'
#align filter.eventually_le.add_le_add Filter.EventuallyLE.add_le_add
theorem EventuallyLE.mul_nonneg [OrderedSemiring β] {l : Filter α} {f g : α → β} (hf : 0 ≤ᶠ[l] f)
(hg : 0 ≤ᶠ[l] g) : 0 ≤ᶠ[l] f * g := by filter_upwards [hf, hg] with x using _root_.mul_nonneg
#align filter.eventually_le.mul_nonneg Filter.EventuallyLE.mul_nonneg
theorem eventually_sub_nonneg [OrderedRing β] {l : Filter α} {f g : α → β} :
0 ≤ᶠ[l] g - f ↔ f ≤ᶠ[l] g :=
eventually_congr <| eventually_of_forall fun _ => sub_nonneg
#align filter.eventually_sub_nonneg Filter.eventually_sub_nonneg
theorem EventuallyLE.sup [SemilatticeSup β] {l : Filter α} {f₁ f₂ g₁ g₂ : α → β} (hf : f₁ ≤ᶠ[l] f₂)
(hg : g₁ ≤ᶠ[l] g₂) : f₁ ⊔ g₁ ≤ᶠ[l] f₂ ⊔ g₂ := by
filter_upwards [hf, hg] with x hfx hgx using sup_le_sup hfx hgx
#align filter.eventually_le.sup Filter.EventuallyLE.sup
theorem EventuallyLE.sup_le [SemilatticeSup β] {l : Filter α} {f g h : α → β} (hf : f ≤ᶠ[l] h)
(hg : g ≤ᶠ[l] h) : f ⊔ g ≤ᶠ[l] h := by
filter_upwards [hf, hg] with x hfx hgx using _root_.sup_le hfx hgx
#align filter.eventually_le.sup_le Filter.EventuallyLE.sup_le
theorem EventuallyLE.le_sup_of_le_left [SemilatticeSup β] {l : Filter α} {f g h : α → β}
(hf : h ≤ᶠ[l] f) : h ≤ᶠ[l] f ⊔ g :=
hf.mono fun _ => _root_.le_sup_of_le_left
#align filter.eventually_le.le_sup_of_le_left Filter.EventuallyLE.le_sup_of_le_left
theorem EventuallyLE.le_sup_of_le_right [SemilatticeSup β] {l : Filter α} {f g h : α → β}
(hg : h ≤ᶠ[l] g) : h ≤ᶠ[l] f ⊔ g :=
hg.mono fun _ => _root_.le_sup_of_le_right
#align filter.eventually_le.le_sup_of_le_right Filter.EventuallyLE.le_sup_of_le_right
theorem join_le {f : Filter (Filter α)} {l : Filter α} (h : ∀ᶠ m in f, m ≤ l) : join f ≤ l :=
fun _ hs => h.mono fun _ hm => hm hs
#align filter.join_le Filter.join_le
/-! ### Push-forwards, pull-backs, and the monad structure -/
section Map
/-- The forward map of a filter -/
def map (m : α → β) (f : Filter α) : Filter β where
sets := preimage m ⁻¹' f.sets
univ_sets := univ_mem
sets_of_superset hs st := mem_of_superset hs <| preimage_mono st
inter_sets hs ht := inter_mem hs ht
#align filter.map Filter.map
@[simp]
theorem map_principal {s : Set α} {f : α → β} : map f (𝓟 s) = 𝓟 (Set.image f s) :=
Filter.ext fun _ => image_subset_iff.symm
#align filter.map_principal Filter.map_principal
variable {f : Filter α} {m : α → β} {m' : β → γ} {s : Set α} {t : Set β}
@[simp]
theorem eventually_map {P : β → Prop} : (∀ᶠ b in map m f, P b) ↔ ∀ᶠ a in f, P (m a) :=
Iff.rfl
#align filter.eventually_map Filter.eventually_map
@[simp]
theorem frequently_map {P : β → Prop} : (∃ᶠ b in map m f, P b) ↔ ∃ᶠ a in f, P (m a) :=
Iff.rfl
#align filter.frequently_map Filter.frequently_map
@[simp]
theorem mem_map : t ∈ map m f ↔ m ⁻¹' t ∈ f :=
Iff.rfl
#align filter.mem_map Filter.mem_map
theorem mem_map' : t ∈ map m f ↔ { x | m x ∈ t } ∈ f :=
Iff.rfl
#align filter.mem_map' Filter.mem_map'
theorem image_mem_map (hs : s ∈ f) : m '' s ∈ map m f :=
f.sets_of_superset hs <| subset_preimage_image m s
#align filter.image_mem_map Filter.image_mem_map
-- The simpNF linter says that the LHS can be simplified via `Filter.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem image_mem_map_iff (hf : Injective m) : m '' s ∈ map m f ↔ s ∈ f :=
⟨fun h => by rwa [← preimage_image_eq s hf], image_mem_map⟩
#align filter.image_mem_map_iff Filter.image_mem_map_iff
theorem range_mem_map : range m ∈ map m f := by
rw [← image_univ]
exact image_mem_map univ_mem
#align filter.range_mem_map Filter.range_mem_map
theorem mem_map_iff_exists_image : t ∈ map m f ↔ ∃ s ∈ f, m '' s ⊆ t :=
⟨fun ht => ⟨m ⁻¹' t, ht, image_preimage_subset _ _⟩, fun ⟨_, hs, ht⟩ =>
mem_of_superset (image_mem_map hs) ht⟩
#align filter.mem_map_iff_exists_image Filter.mem_map_iff_exists_image
@[simp]
theorem map_id : Filter.map id f = f :=
filter_eq <| rfl
#align filter.map_id Filter.map_id
@[simp]
theorem map_id' : Filter.map (fun x => x) f = f :=
map_id
#align filter.map_id' Filter.map_id'
@[simp]
theorem map_compose : Filter.map m' ∘ Filter.map m = Filter.map (m' ∘ m) :=
funext fun _ => filter_eq <| rfl
#align filter.map_compose Filter.map_compose
@[simp]
theorem map_map : Filter.map m' (Filter.map m f) = Filter.map (m' ∘ m) f :=
congr_fun Filter.map_compose f
#align filter.map_map Filter.map_map
/-- If functions `m₁` and `m₂` are eventually equal at a filter `f`, then
they map this filter to the same filter. -/
theorem map_congr {m₁ m₂ : α → β} {f : Filter α} (h : m₁ =ᶠ[f] m₂) : map m₁ f = map m₂ f :=
Filter.ext' fun _ => eventually_congr (h.mono fun _ hx => hx ▸ Iff.rfl)
#align filter.map_congr Filter.map_congr
end Map
section Comap
/-- The inverse map of a filter. A set `s` belongs to `Filter.comap m f` if either of the following
equivalent conditions hold.
1. There exists a set `t ∈ f` such that `m ⁻¹' t ⊆ s`. This is used as a definition.
2. The set `kernImage m s = {y | ∀ x, m x = y → x ∈ s}` belongs to `f`, see `Filter.mem_comap'`.
3. The set `(m '' sᶜ)ᶜ` belongs to `f`, see `Filter.mem_comap_iff_compl` and
`Filter.compl_mem_comap`. -/
def comap (m : α → β) (f : Filter β) : Filter α where
sets := { s | ∃ t ∈ f, m ⁻¹' t ⊆ s }
univ_sets := ⟨univ, univ_mem, by simp only [subset_univ, preimage_univ]⟩
sets_of_superset := fun ⟨a', ha', ma'a⟩ ab => ⟨a', ha', ma'a.trans ab⟩
inter_sets := fun ⟨a', ha₁, ha₂⟩ ⟨b', hb₁, hb₂⟩ =>
⟨a' ∩ b', inter_mem ha₁ hb₁, inter_subset_inter ha₂ hb₂⟩
#align filter.comap Filter.comap
variable {f : α → β} {l : Filter β} {p : α → Prop} {s : Set α}
theorem mem_comap' : s ∈ comap f l ↔ { y | ∀ ⦃x⦄, f x = y → x ∈ s } ∈ l :=
⟨fun ⟨t, ht, hts⟩ => mem_of_superset ht fun y hy x hx => hts <| mem_preimage.2 <| by rwa [hx],
fun h => ⟨_, h, fun x hx => hx rfl⟩⟩
#align filter.mem_comap' Filter.mem_comap'
-- TODO: it would be nice to use `kernImage` much more to take advantage of common name and API,
-- and then this would become `mem_comap'`
theorem mem_comap'' : s ∈ comap f l ↔ kernImage f s ∈ l :=
mem_comap'
/-- RHS form is used, e.g., in the definition of `UniformSpace`. -/
lemma mem_comap_prod_mk {x : α} {s : Set β} {F : Filter (α × β)} :
s ∈ comap (Prod.mk x) F ↔ {p : α × β | p.fst = x → p.snd ∈ s} ∈ F := by
simp_rw [mem_comap', Prod.ext_iff, and_imp, @forall_swap β (_ = _), forall_eq, eq_comm]
#align filter.mem_comap_prod_mk Filter.mem_comap_prod_mk
@[simp]
theorem eventually_comap : (∀ᶠ a in comap f l, p a) ↔ ∀ᶠ b in l, ∀ a, f a = b → p a :=
mem_comap'
#align filter.eventually_comap Filter.eventually_comap
@[simp]
theorem frequently_comap : (∃ᶠ a in comap f l, p a) ↔ ∃ᶠ b in l, ∃ a, f a = b ∧ p a := by
simp only [Filter.Frequently, eventually_comap, not_exists, _root_.not_and]
#align filter.frequently_comap Filter.frequently_comap
theorem mem_comap_iff_compl : s ∈ comap f l ↔ (f '' sᶜ)ᶜ ∈ l := by
simp only [mem_comap'', kernImage_eq_compl]
#align filter.mem_comap_iff_compl Filter.mem_comap_iff_compl
theorem compl_mem_comap : sᶜ ∈ comap f l ↔ (f '' s)ᶜ ∈ l := by rw [mem_comap_iff_compl, compl_compl]
#align filter.compl_mem_comap Filter.compl_mem_comap
end Comap
section KernMap
/-- The analog of `kernImage` for filters. A set `s` belongs to `Filter.kernMap m f` if either of
the following equivalent conditions hold.
1. There exists a set `t ∈ f` such that `s = kernImage m t`. This is used as a definition.
2. There exists a set `t` such that `tᶜ ∈ f` and `sᶜ = m '' t`, see `Filter.mem_kernMap_iff_compl`
and `Filter.compl_mem_kernMap`.
This definition because it gives a right adjoint to `Filter.comap`, and because it has a nice
interpretation when working with `co-` filters (`Filter.cocompact`, `Filter.cofinite`, ...).
For example, `kernMap m (cocompact α)` is the filter generated by the complements of the sets
`m '' K` where `K` is a compact subset of `α`. -/
def kernMap (m : α → β) (f : Filter α) : Filter β where
sets := (kernImage m) '' f.sets
univ_sets := ⟨univ, f.univ_sets, by simp [kernImage_eq_compl]⟩
sets_of_superset := by
rintro _ t ⟨s, hs, rfl⟩ hst
refine ⟨s ∪ m ⁻¹' t, mem_of_superset hs subset_union_left, ?_⟩
rw [kernImage_union_preimage, union_eq_right.mpr hst]
inter_sets := by
rintro _ _ ⟨s₁, h₁, rfl⟩ ⟨s₂, h₂, rfl⟩
exact ⟨s₁ ∩ s₂, f.inter_sets h₁ h₂, Set.preimage_kernImage.u_inf⟩
variable {m : α → β} {f : Filter α}
theorem mem_kernMap {s : Set β} : s ∈ kernMap m f ↔ ∃ t ∈ f, kernImage m t = s :=
Iff.rfl
theorem mem_kernMap_iff_compl {s : Set β} : s ∈ kernMap m f ↔ ∃ t, tᶜ ∈ f ∧ m '' t = sᶜ := by
rw [mem_kernMap, compl_surjective.exists]
refine exists_congr (fun x ↦ and_congr_right fun _ ↦ ?_)
rw [kernImage_compl, compl_eq_comm, eq_comm]
theorem compl_mem_kernMap {s : Set β} : sᶜ ∈ kernMap m f ↔ ∃ t, tᶜ ∈ f ∧ m '' t = s := by
simp_rw [mem_kernMap_iff_compl, compl_compl]
end KernMap
/-- The monadic bind operation on filter is defined the usual way in terms of `map` and `join`.
Unfortunately, this `bind` does not result in the expected applicative. See `Filter.seq` for the
applicative instance. -/
def bind (f : Filter α) (m : α → Filter β) : Filter β :=
join (map m f)
#align filter.bind Filter.bind
/-- The applicative sequentiation operation. This is not induced by the bind operation. -/
def seq (f : Filter (α → β)) (g : Filter α) : Filter β where
sets := { s | ∃ u ∈ f, ∃ t ∈ g, ∀ m ∈ u, ∀ x ∈ t, (m : α → β) x ∈ s }
univ_sets := ⟨univ, univ_mem, univ, univ_mem, fun _ _ _ _ => trivial⟩
sets_of_superset := fun ⟨t₀, t₁, h₀, h₁, h⟩ hst =>
⟨t₀, t₁, h₀, h₁, fun _ hx _ hy => hst <| h _ hx _ hy⟩
inter_sets := fun ⟨t₀, ht₀, t₁, ht₁, ht⟩ ⟨u₀, hu₀, u₁, hu₁, hu⟩ =>
⟨t₀ ∩ u₀, inter_mem ht₀ hu₀, t₁ ∩ u₁, inter_mem ht₁ hu₁, fun _ ⟨hx₀, hx₁⟩ _ ⟨hy₀, hy₁⟩ =>
⟨ht _ hx₀ _ hy₀, hu _ hx₁ _ hy₁⟩⟩
#align filter.seq Filter.seq
/-- `pure x` is the set of sets that contain `x`. It is equal to `𝓟 {x}` but
with this definition we have `s ∈ pure a` defeq `a ∈ s`. -/
instance : Pure Filter :=
⟨fun x =>
{ sets := { s | x ∈ s }
inter_sets := And.intro
sets_of_superset := fun hs hst => hst hs
univ_sets := trivial }⟩
instance : Bind Filter :=
⟨@Filter.bind⟩
instance : Functor Filter where map := @Filter.map
instance : LawfulFunctor (Filter : Type u → Type u) where
id_map _ := map_id
comp_map _ _ _ := map_map.symm
map_const := rfl
theorem pure_sets (a : α) : (pure a : Filter α).sets = { s | a ∈ s } :=
rfl
#align filter.pure_sets Filter.pure_sets
@[simp]
theorem mem_pure {a : α} {s : Set α} : s ∈ (pure a : Filter α) ↔ a ∈ s :=
Iff.rfl
#align filter.mem_pure Filter.mem_pure
@[simp]
theorem eventually_pure {a : α} {p : α → Prop} : (∀ᶠ x in pure a, p x) ↔ p a :=
Iff.rfl
#align filter.eventually_pure Filter.eventually_pure
@[simp]
theorem principal_singleton (a : α) : 𝓟 {a} = pure a :=
Filter.ext fun s => by simp only [mem_pure, mem_principal, singleton_subset_iff]
#align filter.principal_singleton Filter.principal_singleton
@[simp]
theorem map_pure (f : α → β) (a : α) : map f (pure a) = pure (f a) :=
rfl
#align filter.map_pure Filter.map_pure
theorem pure_le_principal (a : α) : pure a ≤ 𝓟 s ↔ a ∈ s := by
simp
@[simp] theorem join_pure (f : Filter α) : join (pure f) = f := rfl
#align filter.join_pure Filter.join_pure
@[simp]
theorem pure_bind (a : α) (m : α → Filter β) : bind (pure a) m = m a := by
simp only [Bind.bind, bind, map_pure, join_pure]
#align filter.pure_bind Filter.pure_bind
theorem map_bind {α β} (m : β → γ) (f : Filter α) (g : α → Filter β) :
map m (bind f g) = bind f (map m ∘ g) :=
rfl
theorem bind_map {α β} (m : α → β) (f : Filter α) (g : β → Filter γ) :
(bind (map m f) g) = bind f (g ∘ m) :=
rfl
/-!
### `Filter` as a `Monad`
In this section we define `Filter.monad`, a `Monad` structure on `Filter`s. This definition is not
an instance because its `Seq` projection is not equal to the `Filter.seq` function we use in the
`Applicative` instance on `Filter`.
-/
section
/-- The monad structure on filters. -/
protected def monad : Monad Filter where map := @Filter.map
#align filter.monad Filter.monad
attribute [local instance] Filter.monad
protected theorem lawfulMonad : LawfulMonad Filter where
map_const := rfl
id_map _ := rfl
seqLeft_eq _ _ := rfl
seqRight_eq _ _ := rfl
pure_seq _ _ := rfl
bind_pure_comp _ _ := rfl
bind_map _ _ := rfl
pure_bind _ _ := rfl
bind_assoc _ _ _ := rfl
#align filter.is_lawful_monad Filter.lawfulMonad
end
instance : Alternative Filter where
seq := fun x y => x.seq (y ())
failure := ⊥
orElse x y := x ⊔ y ()
@[simp]
theorem map_def {α β} (m : α → β) (f : Filter α) : m <$> f = map m f :=
rfl
#align filter.map_def Filter.map_def
@[simp]
theorem bind_def {α β} (f : Filter α) (m : α → Filter β) : f >>= m = bind f m :=
rfl
#align filter.bind_def Filter.bind_def
/-! #### `map` and `comap` equations -/
section Map
variable {f f₁ f₂ : Filter α} {g g₁ g₂ : Filter β} {m : α → β} {m' : β → γ} {s : Set α} {t : Set β}
@[simp] theorem mem_comap : s ∈ comap m g ↔ ∃ t ∈ g, m ⁻¹' t ⊆ s := Iff.rfl
#align filter.mem_comap Filter.mem_comap
theorem preimage_mem_comap (ht : t ∈ g) : m ⁻¹' t ∈ comap m g :=
⟨t, ht, Subset.rfl⟩
#align filter.preimage_mem_comap Filter.preimage_mem_comap
theorem Eventually.comap {p : β → Prop} (hf : ∀ᶠ b in g, p b) (f : α → β) :
∀ᶠ a in comap f g, p (f a) :=
preimage_mem_comap hf
#align filter.eventually.comap Filter.Eventually.comap
theorem comap_id : comap id f = f :=
le_antisymm (fun _ => preimage_mem_comap) fun _ ⟨_, ht, hst⟩ => mem_of_superset ht hst
#align filter.comap_id Filter.comap_id
theorem comap_id' : comap (fun x => x) f = f := comap_id
#align filter.comap_id' Filter.comap_id'
theorem comap_const_of_not_mem {x : β} (ht : t ∈ g) (hx : x ∉ t) : comap (fun _ : α => x) g = ⊥ :=
empty_mem_iff_bot.1 <| mem_comap'.2 <| mem_of_superset ht fun _ hx' _ h => hx <| h.symm ▸ hx'
#align filter.comap_const_of_not_mem Filter.comap_const_of_not_mem
theorem comap_const_of_mem {x : β} (h : ∀ t ∈ g, x ∈ t) : comap (fun _ : α => x) g = ⊤ :=
top_unique fun _ hs => univ_mem' fun _ => h _ (mem_comap'.1 hs) rfl
#align filter.comap_const_of_mem Filter.comap_const_of_mem
theorem map_const [NeBot f] {c : β} : (f.map fun _ => c) = pure c := by
ext s
by_cases h : c ∈ s <;> simp [h]
#align filter.map_const Filter.map_const
theorem comap_comap {m : γ → β} {n : β → α} : comap m (comap n f) = comap (n ∘ m) f :=
Filter.coext fun s => by simp only [compl_mem_comap, image_image, (· ∘ ·)]
#align filter.comap_comap Filter.comap_comap
section comm
/-!
The variables in the following lemmas are used as in this diagram:
```
φ
α → β
θ ↓ ↓ ψ
γ → δ
ρ
```
-/
variable {φ : α → β} {θ : α → γ} {ψ : β → δ} {ρ : γ → δ} (H : ψ ∘ φ = ρ ∘ θ)
theorem map_comm (F : Filter α) : map ψ (map φ F) = map ρ (map θ F) := by
rw [Filter.map_map, H, ← Filter.map_map]
#align filter.map_comm Filter.map_comm
theorem comap_comm (G : Filter δ) : comap φ (comap ψ G) = comap θ (comap ρ G) := by
rw [Filter.comap_comap, H, ← Filter.comap_comap]
#align filter.comap_comm Filter.comap_comm
end comm
theorem _root_.Function.Semiconj.filter_map {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (map f) (map ga) (map gb) :=
map_comm h.comp_eq
#align function.semiconj.filter_map Function.Semiconj.filter_map
theorem _root_.Function.Commute.filter_map {f g : α → α} (h : Function.Commute f g) :
Function.Commute (map f) (map g) :=
h.semiconj.filter_map
#align function.commute.filter_map Function.Commute.filter_map
theorem _root_.Function.Semiconj.filter_comap {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (comap f) (comap gb) (comap ga) :=
comap_comm h.comp_eq.symm
#align function.semiconj.filter_comap Function.Semiconj.filter_comap
theorem _root_.Function.Commute.filter_comap {f g : α → α} (h : Function.Commute f g) :
Function.Commute (comap f) (comap g) :=
h.semiconj.filter_comap
#align function.commute.filter_comap Function.Commute.filter_comap
section
open Filter
theorem _root_.Function.LeftInverse.filter_map {f : α → β} {g : β → α} (hfg : LeftInverse g f) :
LeftInverse (map g) (map f) := fun F ↦ by
rw [map_map, hfg.comp_eq_id, map_id]
theorem _root_.Function.LeftInverse.filter_comap {f : α → β} {g : β → α} (hfg : LeftInverse g f) :
RightInverse (comap g) (comap f) := fun F ↦ by
rw [comap_comap, hfg.comp_eq_id, comap_id]
nonrec theorem _root_.Function.RightInverse.filter_map {f : α → β} {g : β → α}
(hfg : RightInverse g f) : RightInverse (map g) (map f) :=
hfg.filter_map
nonrec theorem _root_.Function.RightInverse.filter_comap {f : α → β} {g : β → α}
(hfg : RightInverse g f) : LeftInverse (comap g) (comap f) :=
hfg.filter_comap
theorem _root_.Set.LeftInvOn.filter_map_Iic {f : α → β} {g : β → α} (hfg : LeftInvOn g f s) :
LeftInvOn (map g) (map f) (Iic <| 𝓟 s) := fun F (hF : F ≤ 𝓟 s) ↦ by
have : (g ∘ f) =ᶠ[𝓟 s] id := by simpa only [eventuallyEq_principal] using hfg
rw [map_map, map_congr (this.filter_mono hF), map_id]
nonrec theorem _root_.Set.RightInvOn.filter_map_Iic {f : α → β} {g : β → α}
(hfg : RightInvOn g f t) : RightInvOn (map g) (map f) (Iic <| 𝓟 t) :=
hfg.filter_map_Iic
end
@[simp]
theorem comap_principal {t : Set β} : comap m (𝓟 t) = 𝓟 (m ⁻¹' t) :=
Filter.ext fun _ => ⟨fun ⟨_u, hu, b⟩ => (preimage_mono hu).trans b,
fun h => ⟨t, Subset.rfl, h⟩⟩
#align filter.comap_principal Filter.comap_principal
theorem principal_subtype {α : Type*} (s : Set α) (t : Set s) :
𝓟 t = comap (↑) (𝓟 (((↑) : s → α) '' t)) := by
rw [comap_principal, preimage_image_eq _ Subtype.coe_injective]
#align principal_subtype Filter.principal_subtype
@[simp]
theorem comap_pure {b : β} : comap m (pure b) = 𝓟 (m ⁻¹' {b}) := by
rw [← principal_singleton, comap_principal]
#align filter.comap_pure Filter.comap_pure
theorem map_le_iff_le_comap : map m f ≤ g ↔ f ≤ comap m g :=
⟨fun h _ ⟨_, ht, hts⟩ => mem_of_superset (h ht) hts, fun h _ ht => h ⟨_, ht, Subset.rfl⟩⟩
#align filter.map_le_iff_le_comap Filter.map_le_iff_le_comap
theorem gc_map_comap (m : α → β) : GaloisConnection (map m) (comap m) :=
fun _ _ => map_le_iff_le_comap
#align filter.gc_map_comap Filter.gc_map_comap
theorem comap_le_iff_le_kernMap : comap m g ≤ f ↔ g ≤ kernMap m f := by
simp [Filter.le_def, mem_comap'', mem_kernMap, -mem_comap]
theorem gc_comap_kernMap (m : α → β) : GaloisConnection (comap m) (kernMap m) :=
fun _ _ ↦ comap_le_iff_le_kernMap
theorem kernMap_principal {s : Set α} : kernMap m (𝓟 s) = 𝓟 (kernImage m s) := by
refine eq_of_forall_le_iff (fun g ↦ ?_)
rw [← comap_le_iff_le_kernMap, le_principal_iff, le_principal_iff, mem_comap'']
@[mono]
theorem map_mono : Monotone (map m) :=
(gc_map_comap m).monotone_l
#align filter.map_mono Filter.map_mono
@[mono]
theorem comap_mono : Monotone (comap m) :=
(gc_map_comap m).monotone_u
#align filter.comap_mono Filter.comap_mono
/-- Temporary lemma that we can tag with `gcongr` -/
@[gcongr, deprecated] theorem map_le_map (h : F ≤ G) : map m F ≤ map m G := map_mono h
/-- Temporary lemma that we can tag with `gcongr` -/
@[gcongr, deprecated] theorem comap_le_comap (h : F ≤ G) : comap m F ≤ comap m G := comap_mono h
@[simp] theorem map_bot : map m ⊥ = ⊥ := (gc_map_comap m).l_bot
#align filter.map_bot Filter.map_bot
@[simp] theorem map_sup : map m (f₁ ⊔ f₂) = map m f₁ ⊔ map m f₂ := (gc_map_comap m).l_sup
#align filter.map_sup Filter.map_sup
@[simp]
theorem map_iSup {f : ι → Filter α} : map m (⨆ i, f i) = ⨆ i, map m (f i) :=
(gc_map_comap m).l_iSup
#align filter.map_supr Filter.map_iSup
@[simp]
theorem map_top (f : α → β) : map f ⊤ = 𝓟 (range f) := by
rw [← principal_univ, map_principal, image_univ]
#align filter.map_top Filter.map_top
@[simp] theorem comap_top : comap m ⊤ = ⊤ := (gc_map_comap m).u_top
#align filter.comap_top Filter.comap_top
@[simp] theorem comap_inf : comap m (g₁ ⊓ g₂) = comap m g₁ ⊓ comap m g₂ := (gc_map_comap m).u_inf
#align filter.comap_inf Filter.comap_inf
@[simp]
theorem comap_iInf {f : ι → Filter β} : comap m (⨅ i, f i) = ⨅ i, comap m (f i) :=
(gc_map_comap m).u_iInf
#align filter.comap_infi Filter.comap_iInf
theorem le_comap_top (f : α → β) (l : Filter α) : l ≤ comap f ⊤ := by
rw [comap_top]
exact le_top
#align filter.le_comap_top Filter.le_comap_top
theorem map_comap_le : map m (comap m g) ≤ g :=
(gc_map_comap m).l_u_le _
#align filter.map_comap_le Filter.map_comap_le
theorem le_comap_map : f ≤ comap m (map m f) :=
(gc_map_comap m).le_u_l _
#align filter.le_comap_map Filter.le_comap_map
@[simp]
theorem comap_bot : comap m ⊥ = ⊥ :=
bot_unique fun s _ => ⟨∅, mem_bot, by simp only [empty_subset, preimage_empty]⟩
#align filter.comap_bot Filter.comap_bot
theorem neBot_of_comap (h : (comap m g).NeBot) : g.NeBot := by
rw [neBot_iff] at *
contrapose! h
rw [h]
exact comap_bot
#align filter.ne_bot_of_comap Filter.neBot_of_comap
theorem comap_inf_principal_range : comap m (g ⊓ 𝓟 (range m)) = comap m g := by
simp
#align filter.comap_inf_principal_range Filter.comap_inf_principal_range
theorem disjoint_comap (h : Disjoint g₁ g₂) : Disjoint (comap m g₁) (comap m g₂) := by
simp only [disjoint_iff, ← comap_inf, h.eq_bot, comap_bot]
#align filter.disjoint_comap Filter.disjoint_comap
theorem comap_iSup {ι} {f : ι → Filter β} {m : α → β} : comap m (iSup f) = ⨆ i, comap m (f i) :=
(gc_comap_kernMap m).l_iSup
#align filter.comap_supr Filter.comap_iSup
theorem comap_sSup {s : Set (Filter β)} {m : α → β} : comap m (sSup s) = ⨆ f ∈ s, comap m f := by
simp only [sSup_eq_iSup, comap_iSup, eq_self_iff_true]
#align filter.comap_Sup Filter.comap_sSup
theorem comap_sup : comap m (g₁ ⊔ g₂) = comap m g₁ ⊔ comap m g₂ := by
rw [sup_eq_iSup, comap_iSup, iSup_bool_eq, Bool.cond_true, Bool.cond_false]
#align filter.comap_sup Filter.comap_sup
theorem map_comap (f : Filter β) (m : α → β) : (f.comap m).map m = f ⊓ 𝓟 (range m) := by
refine le_antisymm (le_inf map_comap_le <| le_principal_iff.2 range_mem_map) ?_
rintro t' ⟨t, ht, sub⟩
refine mem_inf_principal.2 (mem_of_superset ht ?_)
rintro _ hxt ⟨x, rfl⟩
exact sub hxt
#align filter.map_comap Filter.map_comap
theorem map_comap_setCoe_val (f : Filter β) (s : Set β) :
(f.comap ((↑) : s → β)).map (↑) = f ⊓ 𝓟 s := by
rw [map_comap, Subtype.range_val]
theorem map_comap_of_mem {f : Filter β} {m : α → β} (hf : range m ∈ f) : (f.comap m).map m = f := by
rw [map_comap, inf_eq_left.2 (le_principal_iff.2 hf)]
#align filter.map_comap_of_mem Filter.map_comap_of_mem
instance canLift (c) (p) [CanLift α β c p] :
CanLift (Filter α) (Filter β) (map c) fun f => ∀ᶠ x : α in f, p x where
prf f hf := ⟨comap c f, map_comap_of_mem <| hf.mono CanLift.prf⟩
#align filter.can_lift Filter.canLift
theorem comap_le_comap_iff {f g : Filter β} {m : α → β} (hf : range m ∈ f) :
comap m f ≤ comap m g ↔ f ≤ g :=
⟨fun h => map_comap_of_mem hf ▸ (map_mono h).trans map_comap_le, fun h => comap_mono h⟩
#align filter.comap_le_comap_iff Filter.comap_le_comap_iff
theorem map_comap_of_surjective {f : α → β} (hf : Surjective f) (l : Filter β) :
map f (comap f l) = l :=
map_comap_of_mem <| by simp only [hf.range_eq, univ_mem]
#align filter.map_comap_of_surjective Filter.map_comap_of_surjective
theorem comap_injective {f : α → β} (hf : Surjective f) : Injective (comap f) :=
LeftInverse.injective <| map_comap_of_surjective hf
theorem _root_.Function.Surjective.filter_map_top {f : α → β} (hf : Surjective f) : map f ⊤ = ⊤ :=
(congr_arg _ comap_top).symm.trans <| map_comap_of_surjective hf ⊤
#align function.surjective.filter_map_top Function.Surjective.filter_map_top
theorem subtype_coe_map_comap (s : Set α) (f : Filter α) :
map ((↑) : s → α) (comap ((↑) : s → α) f) = f ⊓ 𝓟 s := by rw [map_comap, Subtype.range_coe]
#align filter.subtype_coe_map_comap Filter.subtype_coe_map_comap
theorem image_mem_of_mem_comap {f : Filter α} {c : β → α} (h : range c ∈ f) {W : Set β}
(W_in : W ∈ comap c f) : c '' W ∈ f := by
rw [← map_comap_of_mem h]
exact image_mem_map W_in
#align filter.image_mem_of_mem_comap Filter.image_mem_of_mem_comap
theorem image_coe_mem_of_mem_comap {f : Filter α} {U : Set α} (h : U ∈ f) {W : Set U}
(W_in : W ∈ comap ((↑) : U → α) f) : (↑) '' W ∈ f :=
image_mem_of_mem_comap (by simp [h]) W_in
#align filter.image_coe_mem_of_mem_comap Filter.image_coe_mem_of_mem_comap
theorem comap_map {f : Filter α} {m : α → β} (h : Injective m) : comap m (map m f) = f :=
le_antisymm
(fun s hs =>
mem_of_superset (preimage_mem_comap <| image_mem_map hs) <| by
simp only [preimage_image_eq s h, Subset.rfl])
le_comap_map
#align filter.comap_map Filter.comap_map
theorem mem_comap_iff {f : Filter β} {m : α → β} (inj : Injective m) (large : Set.range m ∈ f)
{S : Set α} : S ∈ comap m f ↔ m '' S ∈ f := by
rw [← image_mem_map_iff inj, map_comap_of_mem large]
#align filter.mem_comap_iff Filter.mem_comap_iff
theorem map_le_map_iff_of_injOn {l₁ l₂ : Filter α} {f : α → β} {s : Set α} (h₁ : s ∈ l₁)
(h₂ : s ∈ l₂) (hinj : InjOn f s) : map f l₁ ≤ map f l₂ ↔ l₁ ≤ l₂ :=
⟨fun h _t ht =>
mp_mem h₁ <|
mem_of_superset (h <| image_mem_map (inter_mem h₂ ht)) fun _y ⟨_x, ⟨hxs, hxt⟩, hxy⟩ hys =>
hinj hxs hys hxy ▸ hxt,
fun h => map_mono h⟩
#align filter.map_le_map_iff_of_inj_on Filter.map_le_map_iff_of_injOn
theorem map_le_map_iff {f g : Filter α} {m : α → β} (hm : Injective m) :
map m f ≤ map m g ↔ f ≤ g := by rw [map_le_iff_le_comap, comap_map hm]
#align filter.map_le_map_iff Filter.map_le_map_iff
theorem map_eq_map_iff_of_injOn {f g : Filter α} {m : α → β} {s : Set α} (hsf : s ∈ f) (hsg : s ∈ g)
(hm : InjOn m s) : map m f = map m g ↔ f = g := by
simp only [le_antisymm_iff, map_le_map_iff_of_injOn hsf hsg hm,
map_le_map_iff_of_injOn hsg hsf hm]
#align filter.map_eq_map_iff_of_inj_on Filter.map_eq_map_iff_of_injOn
theorem map_inj {f g : Filter α} {m : α → β} (hm : Injective m) : map m f = map m g ↔ f = g :=
map_eq_map_iff_of_injOn univ_mem univ_mem hm.injOn
#align filter.map_inj Filter.map_inj
theorem map_injective {m : α → β} (hm : Injective m) : Injective (map m) := fun _ _ =>
(map_inj hm).1
#align filter.map_injective Filter.map_injective
theorem comap_neBot_iff {f : Filter β} {m : α → β} : NeBot (comap m f) ↔ ∀ t ∈ f, ∃ a, m a ∈ t := by
simp only [← forall_mem_nonempty_iff_neBot, mem_comap, forall_exists_index, and_imp]
exact ⟨fun h t t_in => h (m ⁻¹' t) t t_in Subset.rfl, fun h s t ht hst => (h t ht).imp hst⟩
#align filter.comap_ne_bot_iff Filter.comap_neBot_iff
theorem comap_neBot {f : Filter β} {m : α → β} (hm : ∀ t ∈ f, ∃ a, m a ∈ t) : NeBot (comap m f) :=
comap_neBot_iff.mpr hm
#align filter.comap_ne_bot Filter.comap_neBot
theorem comap_neBot_iff_frequently {f : Filter β} {m : α → β} :
NeBot (comap m f) ↔ ∃ᶠ y in f, y ∈ range m := by
simp only [comap_neBot_iff, frequently_iff, mem_range, @and_comm (_ ∈ _), exists_exists_eq_and]
#align filter.comap_ne_bot_iff_frequently Filter.comap_neBot_iff_frequently
theorem comap_neBot_iff_compl_range {f : Filter β} {m : α → β} :
NeBot (comap m f) ↔ (range m)ᶜ ∉ f :=
comap_neBot_iff_frequently
#align filter.comap_ne_bot_iff_compl_range Filter.comap_neBot_iff_compl_range
theorem comap_eq_bot_iff_compl_range {f : Filter β} {m : α → β} : comap m f = ⊥ ↔ (range m)ᶜ ∈ f :=
not_iff_not.mp <| neBot_iff.symm.trans comap_neBot_iff_compl_range
#align filter.comap_eq_bot_iff_compl_range Filter.comap_eq_bot_iff_compl_range
theorem comap_surjective_eq_bot {f : Filter β} {m : α → β} (hm : Surjective m) :
comap m f = ⊥ ↔ f = ⊥ := by
rw [comap_eq_bot_iff_compl_range, hm.range_eq, compl_univ, empty_mem_iff_bot]
#align filter.comap_surjective_eq_bot Filter.comap_surjective_eq_bot
theorem disjoint_comap_iff (h : Surjective m) :
Disjoint (comap m g₁) (comap m g₂) ↔ Disjoint g₁ g₂ := by
rw [disjoint_iff, disjoint_iff, ← comap_inf, comap_surjective_eq_bot h]
#align filter.disjoint_comap_iff Filter.disjoint_comap_iff
theorem NeBot.comap_of_range_mem {f : Filter β} {m : α → β} (_ : NeBot f) (hm : range m ∈ f) :
NeBot (comap m f) :=
comap_neBot_iff_frequently.2 <| Eventually.frequently hm
#align filter.ne_bot.comap_of_range_mem Filter.NeBot.comap_of_range_mem
@[simp]
theorem comap_fst_neBot_iff {f : Filter α} :
(f.comap (Prod.fst : α × β → α)).NeBot ↔ f.NeBot ∧ Nonempty β := by
cases isEmpty_or_nonempty β
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]; simp [*]
· simp [comap_neBot_iff_frequently, *]
#align filter.comap_fst_ne_bot_iff Filter.comap_fst_neBot_iff
@[instance]
theorem comap_fst_neBot [Nonempty β] {f : Filter α} [NeBot f] :
(f.comap (Prod.fst : α × β → α)).NeBot :=
comap_fst_neBot_iff.2 ⟨‹_›, ‹_›⟩
#align filter.comap_fst_ne_bot Filter.comap_fst_neBot
@[simp]
theorem comap_snd_neBot_iff {f : Filter β} :
(f.comap (Prod.snd : α × β → β)).NeBot ↔ Nonempty α ∧ f.NeBot := by
cases' isEmpty_or_nonempty α with hα hα
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]; simp
· simp [comap_neBot_iff_frequently, hα]
#align filter.comap_snd_ne_bot_iff Filter.comap_snd_neBot_iff
@[instance]
theorem comap_snd_neBot [Nonempty α] {f : Filter β} [NeBot f] :
(f.comap (Prod.snd : α × β → β)).NeBot :=
comap_snd_neBot_iff.2 ⟨‹_›, ‹_›⟩
#align filter.comap_snd_ne_bot Filter.comap_snd_neBot
| Mathlib/Order/Filter/Basic.lean | 2,628 | 2,634 | theorem comap_eval_neBot_iff' {ι : Type*} {α : ι → Type*} {i : ι} {f : Filter (α i)} :
(comap (eval i) f).NeBot ↔ (∀ j, Nonempty (α j)) ∧ NeBot f := by |
cases' isEmpty_or_nonempty (∀ j, α j) with H H
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]
simp [← Classical.nonempty_pi]
· have : ∀ j, Nonempty (α j) := Classical.nonempty_pi.1 H
simp [comap_neBot_iff_frequently, *]
|
/-
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.Prod
import Mathlib.Data.Set.Finite
#align_import data.finset.n_ary from "leanprover-community/mathlib"@"eba7871095e834365616b5e43c8c7bb0b37058d0"
/-!
# N-ary images of finsets
This file defines `Finset.image₂`, the binary image of finsets. This is the finset version of
`Set.image2`. This is mostly useful to define pointwise operations.
## Notes
This file is very similar to `Data.Set.NAry`, `Order.Filter.NAry` and `Data.Option.NAry`. Please
keep them in sync.
We do not define `Finset.image₃` as its only purpose would be to prove properties of `Finset.image₂`
and `Set.image2` already fulfills this task.
-/
open Function Set
variable {α α' β β' γ γ' δ δ' ε ε' ζ ζ' ν : Type*}
namespace Finset
variable [DecidableEq α'] [DecidableEq β'] [DecidableEq γ] [DecidableEq γ'] [DecidableEq δ]
[DecidableEq δ'] [DecidableEq ε] [DecidableEq ε'] {f f' : α → β → γ} {g g' : α → β → γ → δ}
{s s' : Finset α} {t t' : Finset β} {u u' : Finset γ} {a a' : α} {b b' : β} {c : γ}
/-- The image of a binary function `f : α → β → γ` as a function `Finset α → Finset β → Finset γ`.
Mathematically this should be thought of as the image of the corresponding function `α × β → γ`. -/
def image₂ (f : α → β → γ) (s : Finset α) (t : Finset β) : Finset γ :=
(s ×ˢ t).image <| uncurry f
#align finset.image₂ Finset.image₂
@[simp]
theorem mem_image₂ : c ∈ image₂ f s t ↔ ∃ a ∈ s, ∃ b ∈ t, f a b = c := by
simp [image₂, and_assoc]
#align finset.mem_image₂ Finset.mem_image₂
@[simp, norm_cast]
theorem coe_image₂ (f : α → β → γ) (s : Finset α) (t : Finset β) :
(image₂ f s t : Set γ) = Set.image2 f s t :=
Set.ext fun _ => mem_image₂
#align finset.coe_image₂ Finset.coe_image₂
theorem card_image₂_le (f : α → β → γ) (s : Finset α) (t : Finset β) :
(image₂ f s t).card ≤ s.card * t.card :=
card_image_le.trans_eq <| card_product _ _
#align finset.card_image₂_le Finset.card_image₂_le
theorem card_image₂_iff :
(image₂ f s t).card = s.card * t.card ↔ (s ×ˢ t : Set (α × β)).InjOn fun x => f x.1 x.2 := by
rw [← card_product, ← coe_product]
exact card_image_iff
#align finset.card_image₂_iff Finset.card_image₂_iff
theorem card_image₂ (hf : Injective2 f) (s : Finset α) (t : Finset β) :
(image₂ f s t).card = s.card * t.card :=
(card_image_of_injective _ hf.uncurry).trans <| card_product _ _
#align finset.card_image₂ Finset.card_image₂
theorem mem_image₂_of_mem (ha : a ∈ s) (hb : b ∈ t) : f a b ∈ image₂ f s t :=
mem_image₂.2 ⟨a, ha, b, hb, rfl⟩
#align finset.mem_image₂_of_mem Finset.mem_image₂_of_mem
theorem mem_image₂_iff (hf : Injective2 f) : f a b ∈ image₂ f s t ↔ a ∈ s ∧ b ∈ t := by
rw [← mem_coe, coe_image₂, mem_image2_iff hf, mem_coe, mem_coe]
#align finset.mem_image₂_iff Finset.mem_image₂_iff
theorem image₂_subset (hs : s ⊆ s') (ht : t ⊆ t') : image₂ f s t ⊆ image₂ f s' t' := by
rw [← coe_subset, coe_image₂, coe_image₂]
exact image2_subset hs ht
#align finset.image₂_subset Finset.image₂_subset
theorem image₂_subset_left (ht : t ⊆ t') : image₂ f s t ⊆ image₂ f s t' :=
image₂_subset Subset.rfl ht
#align finset.image₂_subset_left Finset.image₂_subset_left
theorem image₂_subset_right (hs : s ⊆ s') : image₂ f s t ⊆ image₂ f s' t :=
image₂_subset hs Subset.rfl
#align finset.image₂_subset_right Finset.image₂_subset_right
theorem image_subset_image₂_left (hb : b ∈ t) : s.image (fun a => f a b) ⊆ image₂ f s t :=
image_subset_iff.2 fun _ ha => mem_image₂_of_mem ha hb
#align finset.image_subset_image₂_left Finset.image_subset_image₂_left
theorem image_subset_image₂_right (ha : a ∈ s) : t.image (fun b => f a b) ⊆ image₂ f s t :=
image_subset_iff.2 fun _ => mem_image₂_of_mem ha
#align finset.image_subset_image₂_right Finset.image_subset_image₂_right
theorem forall_image₂_iff {p : γ → Prop} :
(∀ z ∈ image₂ f s t, p z) ↔ ∀ x ∈ s, ∀ y ∈ t, p (f x y) := by
simp_rw [← mem_coe, coe_image₂, forall_image2_iff]
#align finset.forall_image₂_iff Finset.forall_image₂_iff
@[simp]
theorem image₂_subset_iff : image₂ f s t ⊆ u ↔ ∀ x ∈ s, ∀ y ∈ t, f x y ∈ u :=
forall_image₂_iff
#align finset.image₂_subset_iff Finset.image₂_subset_iff
theorem image₂_subset_iff_left : image₂ f s t ⊆ u ↔ ∀ a ∈ s, (t.image fun b => f a b) ⊆ u := by
simp_rw [image₂_subset_iff, image_subset_iff]
#align finset.image₂_subset_iff_left Finset.image₂_subset_iff_left
theorem image₂_subset_iff_right : image₂ f s t ⊆ u ↔ ∀ b ∈ t, (s.image fun a => f a b) ⊆ u := by
simp_rw [image₂_subset_iff, image_subset_iff, @forall₂_swap α]
#align finset.image₂_subset_iff_right Finset.image₂_subset_iff_right
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem image₂_nonempty_iff : (image₂ f s t).Nonempty ↔ s.Nonempty ∧ t.Nonempty := by
rw [← coe_nonempty, coe_image₂]
exact image2_nonempty_iff
#align finset.image₂_nonempty_iff Finset.image₂_nonempty_iff
theorem Nonempty.image₂ (hs : s.Nonempty) (ht : t.Nonempty) : (image₂ f s t).Nonempty :=
image₂_nonempty_iff.2 ⟨hs, ht⟩
#align finset.nonempty.image₂ Finset.Nonempty.image₂
theorem Nonempty.of_image₂_left (h : (s.image₂ f t).Nonempty) : s.Nonempty :=
(image₂_nonempty_iff.1 h).1
#align finset.nonempty.of_image₂_left Finset.Nonempty.of_image₂_left
theorem Nonempty.of_image₂_right (h : (s.image₂ f t).Nonempty) : t.Nonempty :=
(image₂_nonempty_iff.1 h).2
#align finset.nonempty.of_image₂_right Finset.Nonempty.of_image₂_right
@[simp]
theorem image₂_empty_left : image₂ f ∅ t = ∅ :=
coe_injective <| by simp
#align finset.image₂_empty_left Finset.image₂_empty_left
@[simp]
theorem image₂_empty_right : image₂ f s ∅ = ∅ :=
coe_injective <| by simp
#align finset.image₂_empty_right Finset.image₂_empty_right
@[simp]
theorem image₂_eq_empty_iff : image₂ f s t = ∅ ↔ s = ∅ ∨ t = ∅ := by
simp_rw [← not_nonempty_iff_eq_empty, image₂_nonempty_iff, not_and_or]
#align finset.image₂_eq_empty_iff Finset.image₂_eq_empty_iff
@[simp]
theorem image₂_singleton_left : image₂ f {a} t = t.image fun b => f a b :=
ext fun x => by simp
#align finset.image₂_singleton_left Finset.image₂_singleton_left
@[simp]
theorem image₂_singleton_right : image₂ f s {b} = s.image fun a => f a b :=
ext fun x => by simp
#align finset.image₂_singleton_right Finset.image₂_singleton_right
theorem image₂_singleton_left' : image₂ f {a} t = t.image (f a) :=
image₂_singleton_left
#align finset.image₂_singleton_left' Finset.image₂_singleton_left'
theorem image₂_singleton : image₂ f {a} {b} = {f a b} := by simp
#align finset.image₂_singleton Finset.image₂_singleton
theorem image₂_union_left [DecidableEq α] : image₂ f (s ∪ s') t = image₂ f s t ∪ image₂ f s' t :=
coe_injective <| by
push_cast
exact image2_union_left
#align finset.image₂_union_left Finset.image₂_union_left
theorem image₂_union_right [DecidableEq β] : image₂ f s (t ∪ t') = image₂ f s t ∪ image₂ f s t' :=
coe_injective <| by
push_cast
exact image2_union_right
#align finset.image₂_union_right Finset.image₂_union_right
@[simp]
theorem image₂_insert_left [DecidableEq α] :
image₂ f (insert a s) t = (t.image fun b => f a b) ∪ image₂ f s t :=
coe_injective <| by
push_cast
exact image2_insert_left
#align finset.image₂_insert_left Finset.image₂_insert_left
@[simp]
theorem image₂_insert_right [DecidableEq β] :
image₂ f s (insert b t) = (s.image fun a => f a b) ∪ image₂ f s t :=
coe_injective <| by
push_cast
exact image2_insert_right
#align finset.image₂_insert_right Finset.image₂_insert_right
theorem image₂_inter_left [DecidableEq α] (hf : Injective2 f) :
image₂ f (s ∩ s') t = image₂ f s t ∩ image₂ f s' t :=
coe_injective <| by
push_cast
exact image2_inter_left hf
#align finset.image₂_inter_left Finset.image₂_inter_left
theorem image₂_inter_right [DecidableEq β] (hf : Injective2 f) :
image₂ f s (t ∩ t') = image₂ f s t ∩ image₂ f s t' :=
coe_injective <| by
push_cast
exact image2_inter_right hf
#align finset.image₂_inter_right Finset.image₂_inter_right
theorem image₂_inter_subset_left [DecidableEq α] :
image₂ f (s ∩ s') t ⊆ image₂ f s t ∩ image₂ f s' t :=
coe_subset.1 <| by
push_cast
exact image2_inter_subset_left
#align finset.image₂_inter_subset_left Finset.image₂_inter_subset_left
theorem image₂_inter_subset_right [DecidableEq β] :
image₂ f s (t ∩ t') ⊆ image₂ f s t ∩ image₂ f s t' :=
coe_subset.1 <| by
push_cast
exact image2_inter_subset_right
#align finset.image₂_inter_subset_right Finset.image₂_inter_subset_right
theorem image₂_congr (h : ∀ a ∈ s, ∀ b ∈ t, f a b = f' a b) : image₂ f s t = image₂ f' s t :=
coe_injective <| by
push_cast
exact image2_congr h
#align finset.image₂_congr Finset.image₂_congr
/-- A common special case of `image₂_congr` -/
theorem image₂_congr' (h : ∀ a b, f a b = f' a b) : image₂ f s t = image₂ f' s t :=
image₂_congr fun a _ b _ => h a b
#align finset.image₂_congr' Finset.image₂_congr'
variable (s t)
theorem card_image₂_singleton_left (hf : Injective (f a)) : (image₂ f {a} t).card = t.card := by
rw [image₂_singleton_left, card_image_of_injective _ hf]
#align finset.card_image₂_singleton_left Finset.card_image₂_singleton_left
theorem card_image₂_singleton_right (hf : Injective fun a => f a b) :
(image₂ f s {b}).card = s.card := by rw [image₂_singleton_right, card_image_of_injective _ hf]
#align finset.card_image₂_singleton_right Finset.card_image₂_singleton_right
theorem image₂_singleton_inter [DecidableEq β] (t₁ t₂ : Finset β) (hf : Injective (f a)) :
image₂ f {a} (t₁ ∩ t₂) = image₂ f {a} t₁ ∩ image₂ f {a} t₂ := by
simp_rw [image₂_singleton_left, image_inter _ _ hf]
#align finset.image₂_singleton_inter Finset.image₂_singleton_inter
theorem image₂_inter_singleton [DecidableEq α] (s₁ s₂ : Finset α) (hf : Injective fun a => f a b) :
image₂ f (s₁ ∩ s₂) {b} = image₂ f s₁ {b} ∩ image₂ f s₂ {b} := by
simp_rw [image₂_singleton_right, image_inter _ _ hf]
#align finset.image₂_inter_singleton Finset.image₂_inter_singleton
theorem card_le_card_image₂_left {s : Finset α} (hs : s.Nonempty) (hf : ∀ a, Injective (f a)) :
t.card ≤ (image₂ f s t).card := by
obtain ⟨a, ha⟩ := hs
rw [← card_image₂_singleton_left _ (hf a)]
exact card_le_card (image₂_subset_right <| singleton_subset_iff.2 ha)
#align finset.card_le_card_image₂_left Finset.card_le_card_image₂_left
theorem card_le_card_image₂_right {t : Finset β} (ht : t.Nonempty)
(hf : ∀ b, Injective fun a => f a b) : s.card ≤ (image₂ f s t).card := by
obtain ⟨b, hb⟩ := ht
rw [← card_image₂_singleton_right _ (hf b)]
exact card_le_card (image₂_subset_left <| singleton_subset_iff.2 hb)
#align finset.card_le_card_image₂_right Finset.card_le_card_image₂_right
variable {s t}
theorem biUnion_image_left : (s.biUnion fun a => t.image <| f a) = image₂ f s t :=
coe_injective <| by
push_cast
exact Set.iUnion_image_left _
#align finset.bUnion_image_left Finset.biUnion_image_left
theorem biUnion_image_right : (t.biUnion fun b => s.image fun a => f a b) = image₂ f s t :=
coe_injective <| by
push_cast
exact Set.iUnion_image_right _
#align finset.bUnion_image_right Finset.biUnion_image_right
/-!
### Algebraic replacement rules
A collection of lemmas to transfer associativity, commutativity, distributivity, ... of operations
to the associativity, commutativity, distributivity, ... of `Finset.image₂` of those operations.
The proof pattern is `image₂_lemma operation_lemma`. For example, `image₂_comm mul_comm` proves that
`image₂ (*) f g = image₂ (*) g f` in a `CommSemigroup`.
-/
theorem image_image₂ (f : α → β → γ) (g : γ → δ) :
(image₂ f s t).image g = image₂ (fun a b => g (f a b)) s t :=
coe_injective <| by
push_cast
exact image_image2 _ _
#align finset.image_image₂ Finset.image_image₂
theorem image₂_image_left (f : γ → β → δ) (g : α → γ) :
image₂ f (s.image g) t = image₂ (fun a b => f (g a) b) s t :=
coe_injective <| by
push_cast
exact image2_image_left _ _
#align finset.image₂_image_left Finset.image₂_image_left
theorem image₂_image_right (f : α → γ → δ) (g : β → γ) :
image₂ f s (t.image g) = image₂ (fun a b => f a (g b)) s t :=
coe_injective <| by
push_cast
exact image2_image_right _ _
#align finset.image₂_image_right Finset.image₂_image_right
@[simp]
theorem image₂_mk_eq_product [DecidableEq α] [DecidableEq β] (s : Finset α) (t : Finset β) :
image₂ Prod.mk s t = s ×ˢ t := by ext; simp [Prod.ext_iff]
#align finset.image₂_mk_eq_product Finset.image₂_mk_eq_product
@[simp]
theorem image₂_curry (f : α × β → γ) (s : Finset α) (t : Finset β) :
image₂ (curry f) s t = (s ×ˢ t).image f := rfl
#align finset.image₂_curry Finset.image₂_curry
@[simp]
theorem image_uncurry_product (f : α → β → γ) (s : Finset α) (t : Finset β) :
(s ×ˢ t).image (uncurry f) = image₂ f s t := rfl
#align finset.image_uncurry_product Finset.image_uncurry_product
theorem image₂_swap (f : α → β → γ) (s : Finset α) (t : Finset β) :
image₂ f s t = image₂ (fun a b => f b a) t s :=
coe_injective <| by
push_cast
exact image2_swap _ _ _
#align finset.image₂_swap Finset.image₂_swap
@[simp]
theorem image₂_left [DecidableEq α] (h : t.Nonempty) : image₂ (fun x _ => x) s t = s :=
coe_injective <| by
push_cast
exact image2_left h
#align finset.image₂_left Finset.image₂_left
@[simp]
theorem image₂_right [DecidableEq β] (h : s.Nonempty) : image₂ (fun _ y => y) s t = t :=
coe_injective <| by
push_cast
exact image2_right h
#align finset.image₂_right Finset.image₂_right
theorem image₂_assoc {γ : Type*} {u : Finset γ} {f : δ → γ → ε} {g : α → β → δ} {f' : α → ε' → ε}
{g' : β → γ → ε'} (h_assoc : ∀ a b c, f (g a b) c = f' a (g' b c)) :
image₂ f (image₂ g s t) u = image₂ f' s (image₂ g' t u) :=
coe_injective <| by
push_cast
exact image2_assoc h_assoc
#align finset.image₂_assoc Finset.image₂_assoc
theorem image₂_comm {g : β → α → γ} (h_comm : ∀ a b, f a b = g b a) : image₂ f s t = image₂ g t s :=
(image₂_swap _ _ _).trans <| by simp_rw [h_comm]
#align finset.image₂_comm Finset.image₂_comm
theorem image₂_left_comm {γ : Type*} {u : Finset γ} {f : α → δ → ε} {g : β → γ → δ}
{f' : α → γ → δ'} {g' : β → δ' → ε} (h_left_comm : ∀ a b c, f a (g b c) = g' b (f' a c)) :
image₂ f s (image₂ g t u) = image₂ g' t (image₂ f' s u) :=
coe_injective <| by
push_cast
exact image2_left_comm h_left_comm
#align finset.image₂_left_comm Finset.image₂_left_comm
theorem image₂_right_comm {γ : Type*} {u : Finset γ} {f : δ → γ → ε} {g : α → β → δ}
{f' : α → γ → δ'} {g' : δ' → β → ε} (h_right_comm : ∀ a b c, f (g a b) c = g' (f' a c) b) :
image₂ f (image₂ g s t) u = image₂ g' (image₂ f' s u) t :=
coe_injective <| by
push_cast
exact image2_right_comm h_right_comm
#align finset.image₂_right_comm Finset.image₂_right_comm
theorem image₂_image₂_image₂_comm {γ δ : Type*} {u : Finset γ} {v : Finset δ} [DecidableEq ζ]
[DecidableEq ζ'] [DecidableEq ν] {f : ε → ζ → ν} {g : α → β → ε} {h : γ → δ → ζ}
{f' : ε' → ζ' → ν} {g' : α → γ → ε'} {h' : β → δ → ζ'}
(h_comm : ∀ a b c d, f (g a b) (h c d) = f' (g' a c) (h' b d)) :
image₂ f (image₂ g s t) (image₂ h u v) = image₂ f' (image₂ g' s u) (image₂ h' t v) :=
coe_injective <| by
push_cast
exact image2_image2_image2_comm h_comm
#align finset.image₂_image₂_image₂_comm Finset.image₂_image₂_image₂_comm
theorem image_image₂_distrib {g : γ → δ} {f' : α' → β' → δ} {g₁ : α → α'} {g₂ : β → β'}
(h_distrib : ∀ a b, g (f a b) = f' (g₁ a) (g₂ b)) :
(image₂ f s t).image g = image₂ f' (s.image g₁) (t.image g₂) :=
coe_injective <| by
push_cast
exact image_image2_distrib h_distrib
#align finset.image_image₂_distrib Finset.image_image₂_distrib
/-- Symmetric statement to `Finset.image₂_image_left_comm`. -/
theorem image_image₂_distrib_left {g : γ → δ} {f' : α' → β → δ} {g' : α → α'}
(h_distrib : ∀ a b, g (f a b) = f' (g' a) b) :
(image₂ f s t).image g = image₂ f' (s.image g') t :=
coe_injective <| by
push_cast
exact image_image2_distrib_left h_distrib
#align finset.image_image₂_distrib_left Finset.image_image₂_distrib_left
/-- Symmetric statement to `Finset.image_image₂_right_comm`. -/
theorem image_image₂_distrib_right {g : γ → δ} {f' : α → β' → δ} {g' : β → β'}
(h_distrib : ∀ a b, g (f a b) = f' a (g' b)) :
(image₂ f s t).image g = image₂ f' s (t.image g') :=
coe_injective <| by
push_cast
exact image_image2_distrib_right h_distrib
#align finset.image_image₂_distrib_right Finset.image_image₂_distrib_right
/-- Symmetric statement to `Finset.image_image₂_distrib_left`. -/
theorem image₂_image_left_comm {f : α' → β → γ} {g : α → α'} {f' : α → β → δ} {g' : δ → γ}
(h_left_comm : ∀ a b, f (g a) b = g' (f' a b)) :
image₂ f (s.image g) t = (image₂ f' s t).image g' :=
(image_image₂_distrib_left fun a b => (h_left_comm a b).symm).symm
#align finset.image₂_image_left_comm Finset.image₂_image_left_comm
/-- Symmetric statement to `Finset.image_image₂_distrib_right`. -/
theorem image_image₂_right_comm {f : α → β' → γ} {g : β → β'} {f' : α → β → δ} {g' : δ → γ}
(h_right_comm : ∀ a b, f a (g b) = g' (f' a b)) :
image₂ f s (t.image g) = (image₂ f' s t).image g' :=
(image_image₂_distrib_right fun a b => (h_right_comm a b).symm).symm
#align finset.image_image₂_right_comm Finset.image_image₂_right_comm
/-- The other direction does not hold because of the `s`-`s` cross terms on the RHS. -/
theorem image₂_distrib_subset_left {γ : Type*} {u : Finset γ} {f : α → δ → ε} {g : β → γ → δ}
{f₁ : α → β → β'} {f₂ : α → γ → γ'} {g' : β' → γ' → ε}
(h_distrib : ∀ a b c, f a (g b c) = g' (f₁ a b) (f₂ a c)) :
image₂ f s (image₂ g t u) ⊆ image₂ g' (image₂ f₁ s t) (image₂ f₂ s u) :=
coe_subset.1 <| by
push_cast
exact Set.image2_distrib_subset_left h_distrib
#align finset.image₂_distrib_subset_left Finset.image₂_distrib_subset_left
/-- The other direction does not hold because of the `u`-`u` cross terms on the RHS. -/
theorem image₂_distrib_subset_right {γ : Type*} {u : Finset γ} {f : δ → γ → ε} {g : α → β → δ}
{f₁ : α → γ → α'} {f₂ : β → γ → β'} {g' : α' → β' → ε}
(h_distrib : ∀ a b c, f (g a b) c = g' (f₁ a c) (f₂ b c)) :
image₂ f (image₂ g s t) u ⊆ image₂ g' (image₂ f₁ s u) (image₂ f₂ t u) :=
coe_subset.1 <| by
push_cast
exact Set.image2_distrib_subset_right h_distrib
#align finset.image₂_distrib_subset_right Finset.image₂_distrib_subset_right
theorem image_image₂_antidistrib {g : γ → δ} {f' : β' → α' → δ} {g₁ : β → β'} {g₂ : α → α'}
(h_antidistrib : ∀ a b, g (f a b) = f' (g₁ b) (g₂ a)) :
(image₂ f s t).image g = image₂ f' (t.image g₁) (s.image g₂) := by
rw [image₂_swap f]
exact image_image₂_distrib fun _ _ => h_antidistrib _ _
#align finset.image_image₂_antidistrib Finset.image_image₂_antidistrib
/-- Symmetric statement to `Finset.image₂_image_left_anticomm`. -/
theorem image_image₂_antidistrib_left {g : γ → δ} {f' : β' → α → δ} {g' : β → β'}
(h_antidistrib : ∀ a b, g (f a b) = f' (g' b) a) :
(image₂ f s t).image g = image₂ f' (t.image g') s :=
coe_injective <| by
push_cast
exact image_image2_antidistrib_left h_antidistrib
#align finset.image_image₂_antidistrib_left Finset.image_image₂_antidistrib_left
/-- Symmetric statement to `Finset.image_image₂_right_anticomm`. -/
theorem image_image₂_antidistrib_right {g : γ → δ} {f' : β → α' → δ} {g' : α → α'}
(h_antidistrib : ∀ a b, g (f a b) = f' b (g' a)) :
(image₂ f s t).image g = image₂ f' t (s.image g') :=
coe_injective <| by
push_cast
exact image_image2_antidistrib_right h_antidistrib
#align finset.image_image₂_antidistrib_right Finset.image_image₂_antidistrib_right
/-- Symmetric statement to `Finset.image_image₂_antidistrib_left`. -/
theorem image₂_image_left_anticomm {f : α' → β → γ} {g : α → α'} {f' : β → α → δ} {g' : δ → γ}
(h_left_anticomm : ∀ a b, f (g a) b = g' (f' b a)) :
image₂ f (s.image g) t = (image₂ f' t s).image g' :=
(image_image₂_antidistrib_left fun a b => (h_left_anticomm b a).symm).symm
#align finset.image₂_image_left_anticomm Finset.image₂_image_left_anticomm
/-- Symmetric statement to `Finset.image_image₂_antidistrib_right`. -/
theorem image_image₂_right_anticomm {f : α → β' → γ} {g : β → β'} {f' : β → α → δ} {g' : δ → γ}
(h_right_anticomm : ∀ a b, f a (g b) = g' (f' b a)) :
image₂ f s (t.image g) = (image₂ f' t s).image g' :=
(image_image₂_antidistrib_right fun a b => (h_right_anticomm b a).symm).symm
#align finset.image_image₂_right_anticomm Finset.image_image₂_right_anticomm
/-- If `a` is a left identity for `f : α → β → β`, then `{a}` is a left identity for
`Finset.image₂ f`. -/
theorem image₂_left_identity {f : α → γ → γ} {a : α} (h : ∀ b, f a b = b) (t : Finset γ) :
image₂ f {a} t = t :=
coe_injective <| by rw [coe_image₂, coe_singleton, Set.image2_left_identity h]
#align finset.image₂_left_identity Finset.image₂_left_identity
/-- If `b` is a right identity for `f : α → β → α`, then `{b}` is a right identity for
`Finset.image₂ f`. -/
| Mathlib/Data/Finset/NAry.lean | 494 | 495 | theorem image₂_right_identity {f : γ → β → γ} {b : β} (h : ∀ a, f a b = a) (s : Finset γ) :
image₂ f s {b} = s := by | rw [image₂_singleton_right, funext h, image_id']
|
/-
Copyright (c) 2022 Violeta Hernández Palacios. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Arithmetic
import Mathlib.Tactic.Abel
#align_import set_theory.ordinal.natural_ops from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Natural operations on ordinals
The goal of this file is to define natural addition and multiplication on ordinals, also known as
the Hessenberg sum and product, and provide a basic API. The natural addition of two ordinals
`a ♯ b` is recursively defined as the least ordinal greater than `a' ♯ b` and `a ♯ b'` for `a' < a`
and `b' < b`. The natural multiplication `a ⨳ b` is likewise recursively defined as the least
ordinal such that `a ⨳ b ♯ a' ⨳ b'` is greater than `a' ⨳ b ♯ a ⨳ b'` for any `a' < a` and
`b' < b`.
These operations form a rich algebraic structure: they're commutative, associative, preserve order,
have the usual `0` and `1` from ordinals, and distribute over one another.
Moreover, these operations are the addition and multiplication of ordinals when viewed as
combinatorial `Game`s. This makes them particularly useful for game theory.
Finally, both operations admit simple, intuitive descriptions in terms of the Cantor normal form.
The natural addition of two ordinals corresponds to adding their Cantor normal forms as if they were
polynomials in `ω`. Likewise, their natural multiplication corresponds to multiplying the Cantor
normal forms as polynomials.
# Implementation notes
Given the rich algebraic structure of these two operations, we choose to create a type synonym
`NatOrdinal`, where we provide the appropriate instances. However, to avoid casting back and forth
between both types, we attempt to prove and state most results on `Ordinal`.
# Todo
- Prove the characterizations of natural addition and multiplication in terms of the Cantor normal
form.
-/
set_option autoImplicit true
universe u v
open Function Order
noncomputable section
/-! ### Basic casts between `Ordinal` and `NatOrdinal` -/
/-- A type synonym for ordinals with natural addition and multiplication. -/
def NatOrdinal : Type _ :=
-- Porting note: used to derive LinearOrder & SuccOrder but need to manually define
Ordinal deriving Zero, Inhabited, One, WellFoundedRelation
#align nat_ordinal NatOrdinal
instance NatOrdinal.linearOrder : LinearOrder NatOrdinal := {Ordinal.linearOrder with}
instance NatOrdinal.succOrder : SuccOrder NatOrdinal := {Ordinal.succOrder with}
/-- The identity function between `Ordinal` and `NatOrdinal`. -/
@[match_pattern]
def Ordinal.toNatOrdinal : Ordinal ≃o NatOrdinal :=
OrderIso.refl _
#align ordinal.to_nat_ordinal Ordinal.toNatOrdinal
/-- The identity function between `NatOrdinal` and `Ordinal`. -/
@[match_pattern]
def NatOrdinal.toOrdinal : NatOrdinal ≃o Ordinal :=
OrderIso.refl _
#align nat_ordinal.to_ordinal NatOrdinal.toOrdinal
namespace NatOrdinal
open Ordinal
@[simp]
theorem toOrdinal_symm_eq : NatOrdinal.toOrdinal.symm = Ordinal.toNatOrdinal :=
rfl
#align nat_ordinal.to_ordinal_symm_eq NatOrdinal.toOrdinal_symm_eq
-- Porting note: used to use dot notation, but doesn't work in Lean 4 with `OrderIso`
@[simp]
theorem toOrdinal_toNatOrdinal (a : NatOrdinal) :
Ordinal.toNatOrdinal (NatOrdinal.toOrdinal a) = a := rfl
#align nat_ordinal.to_ordinal_to_nat_ordinal NatOrdinal.toOrdinal_toNatOrdinal
theorem lt_wf : @WellFounded NatOrdinal (· < ·) :=
Ordinal.lt_wf
#align nat_ordinal.lt_wf NatOrdinal.lt_wf
instance : WellFoundedLT NatOrdinal :=
Ordinal.wellFoundedLT
instance : IsWellOrder NatOrdinal (· < ·) :=
Ordinal.isWellOrder
@[simp]
theorem toOrdinal_zero : toOrdinal 0 = 0 :=
rfl
#align nat_ordinal.to_ordinal_zero NatOrdinal.toOrdinal_zero
@[simp]
theorem toOrdinal_one : toOrdinal 1 = 1 :=
rfl
#align nat_ordinal.to_ordinal_one NatOrdinal.toOrdinal_one
@[simp]
theorem toOrdinal_eq_zero (a) : toOrdinal a = 0 ↔ a = 0 :=
Iff.rfl
#align nat_ordinal.to_ordinal_eq_zero NatOrdinal.toOrdinal_eq_zero
@[simp]
theorem toOrdinal_eq_one (a) : toOrdinal a = 1 ↔ a = 1 :=
Iff.rfl
#align nat_ordinal.to_ordinal_eq_one NatOrdinal.toOrdinal_eq_one
@[simp]
theorem toOrdinal_max : toOrdinal (max a b) = max (toOrdinal a) (toOrdinal b) :=
rfl
#align nat_ordinal.to_ordinal_max NatOrdinal.toOrdinal_max
@[simp]
theorem toOrdinal_min : toOrdinal (min a b)= min (toOrdinal a) (toOrdinal b) :=
rfl
#align nat_ordinal.to_ordinal_min NatOrdinal.toOrdinal_min
theorem succ_def (a : NatOrdinal) : succ a = toNatOrdinal (toOrdinal a + 1) :=
rfl
#align nat_ordinal.succ_def NatOrdinal.succ_def
/-- A recursor for `NatOrdinal`. Use as `induction x using NatOrdinal.rec`. -/
protected def rec {β : NatOrdinal → Sort*} (h : ∀ a, β (toNatOrdinal a)) : ∀ a, β a := fun a =>
h (toOrdinal a)
#align nat_ordinal.rec NatOrdinal.rec
/-- `Ordinal.induction` but for `NatOrdinal`. -/
theorem induction {p : NatOrdinal → Prop} : ∀ (i) (_ : ∀ j, (∀ k, k < j → p k) → p j), p i :=
Ordinal.induction
#align nat_ordinal.induction NatOrdinal.induction
end NatOrdinal
namespace Ordinal
variable {a b c : Ordinal.{u}}
@[simp]
theorem toNatOrdinal_symm_eq : toNatOrdinal.symm = NatOrdinal.toOrdinal :=
rfl
#align ordinal.to_nat_ordinal_symm_eq Ordinal.toNatOrdinal_symm_eq
@[simp]
theorem toNatOrdinal_toOrdinal (a : Ordinal) : NatOrdinal.toOrdinal (toNatOrdinal a) = a :=
rfl
#align ordinal.to_nat_ordinal_to_ordinal Ordinal.toNatOrdinal_toOrdinal
@[simp]
theorem toNatOrdinal_zero : toNatOrdinal 0 = 0 :=
rfl
#align ordinal.to_nat_ordinal_zero Ordinal.toNatOrdinal_zero
@[simp]
theorem toNatOrdinal_one : toNatOrdinal 1 = 1 :=
rfl
#align ordinal.to_nat_ordinal_one Ordinal.toNatOrdinal_one
@[simp]
theorem toNatOrdinal_eq_zero (a) : toNatOrdinal a = 0 ↔ a = 0 :=
Iff.rfl
#align ordinal.to_nat_ordinal_eq_zero Ordinal.toNatOrdinal_eq_zero
@[simp]
theorem toNatOrdinal_eq_one (a) : toNatOrdinal a = 1 ↔ a = 1 :=
Iff.rfl
#align ordinal.to_nat_ordinal_eq_one Ordinal.toNatOrdinal_eq_one
@[simp]
theorem toNatOrdinal_max (a b : Ordinal) :
toNatOrdinal (max a b) = max (toNatOrdinal a) (toNatOrdinal b) :=
rfl
#align ordinal.to_nat_ordinal_max Ordinal.toNatOrdinal_max
@[simp]
theorem toNatOrdinal_min (a b : Ordinal) :
toNatOrdinal (linearOrder.min a b) = linearOrder.min (toNatOrdinal a) (toNatOrdinal b) :=
rfl
#align ordinal.to_nat_ordinal_min Ordinal.toNatOrdinal_min
/-! We place the definitions of `nadd` and `nmul` before actually developing their API, as this
guarantees we only need to open the `NaturalOps` locale once. -/
/-- Natural addition on ordinals `a ♯ b`, also known as the Hessenberg sum, is recursively defined
as the least ordinal greater than `a' ♯ b` and `a ♯ b'` for all `a' < a` and `b' < b`. In contrast
to normal ordinal addition, it is commutative.
Natural addition can equivalently be characterized as the ordinal resulting from adding up
corresponding coefficients in the Cantor normal forms of `a` and `b`. -/
noncomputable def nadd : Ordinal → Ordinal → Ordinal
| a, b =>
max (blsub.{u, u} a fun a' _ => nadd a' b) (blsub.{u, u} b fun b' _ => nadd a b')
termination_by o₁ o₂ => (o₁, o₂)
#align ordinal.nadd Ordinal.nadd
@[inherit_doc]
scoped[NaturalOps] infixl:65 " ♯ " => Ordinal.nadd
open NaturalOps
/-- Natural multiplication on ordinals `a ⨳ b`, also known as the Hessenberg product, is recursively
defined as the least ordinal such that `a ⨳ b + a' ⨳ b'` is greater than `a' ⨳ b + a ⨳ b'` for all
`a' < a` and `b < b'`. In contrast to normal ordinal multiplication, it is commutative and
distributive (over natural addition).
Natural multiplication can equivalently be characterized as the ordinal resulting from multiplying
the Cantor normal forms of `a` and `b` as if they were polynomials in `ω`. Addition of exponents is
done via natural addition. -/
noncomputable def nmul : Ordinal.{u} → Ordinal.{u} → Ordinal.{u}
| a, b => sInf {c | ∀ a' < a, ∀ b' < b, nmul a' b ♯ nmul a b' < c ♯ nmul a' b'}
termination_by a b => (a, b)
#align ordinal.nmul Ordinal.nmul
@[inherit_doc]
scoped[NaturalOps] infixl:70 " ⨳ " => Ordinal.nmul
/-! ### Natural addition -/
theorem nadd_def (a b : Ordinal) :
a ♯ b = max (blsub.{u, u} a fun a' _ => a' ♯ b) (blsub.{u, u} b fun b' _ => a ♯ b') := by
rw [nadd]
#align ordinal.nadd_def Ordinal.nadd_def
theorem lt_nadd_iff : a < b ♯ c ↔ (∃ b' < b, a ≤ b' ♯ c) ∨ ∃ c' < c, a ≤ b ♯ c' := by
rw [nadd_def]
simp [lt_blsub_iff]
#align ordinal.lt_nadd_iff Ordinal.lt_nadd_iff
theorem nadd_le_iff : b ♯ c ≤ a ↔ (∀ b' < b, b' ♯ c < a) ∧ ∀ c' < c, b ♯ c' < a := by
rw [nadd_def]
simp [blsub_le_iff]
#align ordinal.nadd_le_iff Ordinal.nadd_le_iff
theorem nadd_lt_nadd_left (h : b < c) (a) : a ♯ b < a ♯ c :=
lt_nadd_iff.2 (Or.inr ⟨b, h, le_rfl⟩)
#align ordinal.nadd_lt_nadd_left Ordinal.nadd_lt_nadd_left
theorem nadd_lt_nadd_right (h : b < c) (a) : b ♯ a < c ♯ a :=
lt_nadd_iff.2 (Or.inl ⟨b, h, le_rfl⟩)
#align ordinal.nadd_lt_nadd_right Ordinal.nadd_lt_nadd_right
theorem nadd_le_nadd_left (h : b ≤ c) (a) : a ♯ b ≤ a ♯ c := by
rcases lt_or_eq_of_le h with (h | rfl)
· exact (nadd_lt_nadd_left h a).le
· exact le_rfl
#align ordinal.nadd_le_nadd_left Ordinal.nadd_le_nadd_left
theorem nadd_le_nadd_right (h : b ≤ c) (a) : b ♯ a ≤ c ♯ a := by
rcases lt_or_eq_of_le h with (h | rfl)
· exact (nadd_lt_nadd_right h a).le
· exact le_rfl
#align ordinal.nadd_le_nadd_right Ordinal.nadd_le_nadd_right
variable (a b)
theorem nadd_comm : ∀ a b, a ♯ b = b ♯ a
| a, b => by
rw [nadd_def, nadd_def, max_comm]
congr <;> ext <;> apply nadd_comm
termination_by a b => (a,b)
#align ordinal.nadd_comm Ordinal.nadd_comm
theorem blsub_nadd_of_mono {f : ∀ c < a ♯ b, Ordinal.{max u v}}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) :
-- Porting note: needed to add universe hint blsub.{u,v} in the line below
blsub.{u,v} _ f =
max (blsub.{u, v} a fun a' ha' => f (a' ♯ b) <| nadd_lt_nadd_right ha' b)
(blsub.{u, v} b fun b' hb' => f (a ♯ b') <| nadd_lt_nadd_left hb' a) := by
apply (blsub_le_iff.2 fun i h => _).antisymm (max_le _ _)
· intro i h
rcases lt_nadd_iff.1 h with (⟨a', ha', hi⟩ | ⟨b', hb', hi⟩)
· exact lt_max_of_lt_left ((hf h (nadd_lt_nadd_right ha' b) hi).trans_lt (lt_blsub _ _ ha'))
· exact lt_max_of_lt_right ((hf h (nadd_lt_nadd_left hb' a) hi).trans_lt (lt_blsub _ _ hb'))
all_goals
apply blsub_le_of_brange_subset.{u, u, v}
rintro c ⟨d, hd, rfl⟩
apply mem_brange_self
#align ordinal.blsub_nadd_of_mono Ordinal.blsub_nadd_of_mono
theorem nadd_assoc (a b c) : a ♯ b ♯ c = a ♯ (b ♯ c) := by
rw [nadd_def a (b ♯ c), nadd_def, blsub_nadd_of_mono, blsub_nadd_of_mono, max_assoc]
· congr <;> ext <;> apply nadd_assoc
· exact fun _ _ h => nadd_le_nadd_left h a
· exact fun _ _ h => nadd_le_nadd_right h c
termination_by (a, b, c)
#align ordinal.nadd_assoc Ordinal.nadd_assoc
@[simp]
theorem nadd_zero : a ♯ 0 = a := by
induction' a using Ordinal.induction with a IH
rw [nadd_def, blsub_zero, max_zero_right]
convert blsub_id a
rename_i hb
exact IH _ hb
#align ordinal.nadd_zero Ordinal.nadd_zero
@[simp]
theorem zero_nadd : 0 ♯ a = a := by rw [nadd_comm, nadd_zero]
#align ordinal.zero_nadd Ordinal.zero_nadd
@[simp]
theorem nadd_one : a ♯ 1 = succ a := by
induction' a using Ordinal.induction with a IH
rw [nadd_def, blsub_one, nadd_zero, max_eq_right_iff, blsub_le_iff]
intro i hi
rwa [IH i hi, succ_lt_succ_iff]
#align ordinal.nadd_one Ordinal.nadd_one
@[simp]
theorem one_nadd : 1 ♯ a = succ a := by rw [nadd_comm, nadd_one]
#align ordinal.one_nadd Ordinal.one_nadd
| Mathlib/SetTheory/Ordinal/NaturalOps.lean | 326 | 326 | theorem nadd_succ : a ♯ succ b = succ (a ♯ b) := by | rw [← nadd_one (a ♯ b), nadd_assoc, nadd_one]
|
/-
Copyright (c) 2021 Yuma Mizuno. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yuma Mizuno
-/
import Mathlib.CategoryTheory.NatIso
#align_import category_theory.bicategory.basic from "leanprover-community/mathlib"@"4c19a16e4b705bf135cf9a80ac18fcc99c438514"
/-!
# Bicategories
In this file we define typeclass for bicategories.
A bicategory `B` consists of
* objects `a : B`,
* 1-morphisms `f : a ⟶ b` between objects `a b : B`, and
* 2-morphisms `η : f ⟶ g` between 1-morphisms `f g : a ⟶ b` between objects `a b : B`.
We use `u`, `v`, and `w` as the universe variables for objects, 1-morphisms, and 2-morphisms,
respectively.
A typeclass for bicategories extends `CategoryTheory.CategoryStruct` typeclass. This means that
we have
* a composition `f ≫ g : a ⟶ c` for each 1-morphisms `f : a ⟶ b` and `g : b ⟶ c`, and
* an identity `𝟙 a : a ⟶ a` for each object `a : B`.
For each object `a b : B`, the collection of 1-morphisms `a ⟶ b` has a category structure. The
2-morphisms in the bicategory are implemented as the morphisms in this family of categories.
The composition of 1-morphisms is in fact an object part of a functor
`(a ⟶ b) ⥤ (b ⟶ c) ⥤ (a ⟶ c)`. The definition of bicategories in this file does not
require this functor directly. Instead, it requires the whiskering functions. For a 1-morphism
`f : a ⟶ b` and a 2-morphism `η : g ⟶ h` between 1-morphisms `g h : b ⟶ c`, there is a
2-morphism `whiskerLeft f η : f ≫ g ⟶ f ≫ h`. Similarly, for a 2-morphism `η : f ⟶ g`
between 1-morphisms `f g : a ⟶ b` and a 1-morphism `f : b ⟶ c`, there is a 2-morphism
`whiskerRight η h : f ≫ h ⟶ g ≫ h`. These satisfy the exchange law
`whiskerLeft f θ ≫ whiskerRight η i = whiskerRight η h ≫ whiskerLeft g θ`,
which is required as an axiom in the definition here.
-/
namespace CategoryTheory
universe w v u
open Category Iso
-- intended to be used with explicit universe parameters
/-- In a bicategory, we can compose the 1-morphisms `f : a ⟶ b` and `g : b ⟶ c` to obtain
a 1-morphism `f ≫ g : a ⟶ c`. This composition does not need to be strictly associative,
but there is a specified associator, `α_ f g h : (f ≫ g) ≫ h ≅ f ≫ (g ≫ h)`.
There is an identity 1-morphism `𝟙 a : a ⟶ a`, with specified left and right unitor
isomorphisms `λ_ f : 𝟙 a ≫ f ≅ f` and `ρ_ f : f ≫ 𝟙 a ≅ f`.
These associators and unitors satisfy the pentagon and triangle equations.
See https://ncatlab.org/nlab/show/bicategory.
-/
@[nolint checkUnivs]
class Bicategory (B : Type u) extends CategoryStruct.{v} B where
-- category structure on the collection of 1-morphisms:
homCategory : ∀ a b : B, Category.{w} (a ⟶ b) := by infer_instance
-- left whiskering:
whiskerLeft {a b c : B} (f : a ⟶ b) {g h : b ⟶ c} (η : g ⟶ h) : f ≫ g ⟶ f ≫ h
-- right whiskering:
whiskerRight {a b c : B} {f g : a ⟶ b} (η : f ⟶ g) (h : b ⟶ c) : f ≫ h ⟶ g ≫ h
-- associator:
associator {a b c d : B} (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) : (f ≫ g) ≫ h ≅ f ≫ g ≫ h
-- left unitor:
leftUnitor {a b : B} (f : a ⟶ b) : 𝟙 a ≫ f ≅ f
-- right unitor:
rightUnitor {a b : B} (f : a ⟶ b) : f ≫ 𝟙 b ≅ f
-- axioms for left whiskering:
whiskerLeft_id : ∀ {a b c} (f : a ⟶ b) (g : b ⟶ c), whiskerLeft f (𝟙 g) = 𝟙 (f ≫ g) := by
aesop_cat
whiskerLeft_comp :
∀ {a b c} (f : a ⟶ b) {g h i : b ⟶ c} (η : g ⟶ h) (θ : h ⟶ i),
whiskerLeft f (η ≫ θ) = whiskerLeft f η ≫ whiskerLeft f θ := by
aesop_cat
id_whiskerLeft :
∀ {a b} {f g : a ⟶ b} (η : f ⟶ g),
whiskerLeft (𝟙 a) η = (leftUnitor f).hom ≫ η ≫ (leftUnitor g).inv := by
aesop_cat
comp_whiskerLeft :
∀ {a b c d} (f : a ⟶ b) (g : b ⟶ c) {h h' : c ⟶ d} (η : h ⟶ h'),
whiskerLeft (f ≫ g) η =
(associator f g h).hom ≫ whiskerLeft f (whiskerLeft g η) ≫ (associator f g h').inv := by
aesop_cat
-- axioms for right whiskering:
id_whiskerRight : ∀ {a b c} (f : a ⟶ b) (g : b ⟶ c), whiskerRight (𝟙 f) g = 𝟙 (f ≫ g) := by
aesop_cat
comp_whiskerRight :
∀ {a b c} {f g h : a ⟶ b} (η : f ⟶ g) (θ : g ⟶ h) (i : b ⟶ c),
whiskerRight (η ≫ θ) i = whiskerRight η i ≫ whiskerRight θ i := by
aesop_cat
whiskerRight_id :
∀ {a b} {f g : a ⟶ b} (η : f ⟶ g),
whiskerRight η (𝟙 b) = (rightUnitor f).hom ≫ η ≫ (rightUnitor g).inv := by
aesop_cat
whiskerRight_comp :
∀ {a b c d} {f f' : a ⟶ b} (η : f ⟶ f') (g : b ⟶ c) (h : c ⟶ d),
whiskerRight η (g ≫ h) =
(associator f g h).inv ≫ whiskerRight (whiskerRight η g) h ≫ (associator f' g h).hom := by
aesop_cat
-- associativity of whiskerings:
whisker_assoc :
∀ {a b c d} (f : a ⟶ b) {g g' : b ⟶ c} (η : g ⟶ g') (h : c ⟶ d),
whiskerRight (whiskerLeft f η) h =
(associator f g h).hom ≫ whiskerLeft f (whiskerRight η h) ≫ (associator f g' h).inv := by
aesop_cat
-- exchange law of left and right whiskerings:
whisker_exchange :
∀ {a b c} {f g : a ⟶ b} {h i : b ⟶ c} (η : f ⟶ g) (θ : h ⟶ i),
whiskerLeft f θ ≫ whiskerRight η i = whiskerRight η h ≫ whiskerLeft g θ := by
aesop_cat
-- pentagon identity:
pentagon :
∀ {a b c d e} (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e),
whiskerRight (associator f g h).hom i ≫
(associator f (g ≫ h) i).hom ≫ whiskerLeft f (associator g h i).hom =
(associator (f ≫ g) h i).hom ≫ (associator f g (h ≫ i)).hom := by
aesop_cat
-- triangle identity:
triangle :
∀ {a b c} (f : a ⟶ b) (g : b ⟶ c),
(associator f (𝟙 b) g).hom ≫ whiskerLeft f (leftUnitor g).hom
= whiskerRight (rightUnitor f).hom g := by
aesop_cat
#align category_theory.bicategory CategoryTheory.Bicategory
#align category_theory.bicategory.hom_category CategoryTheory.Bicategory.homCategory
#align category_theory.bicategory.whisker_left CategoryTheory.Bicategory.whiskerLeft
#align category_theory.bicategory.whisker_right CategoryTheory.Bicategory.whiskerRight
#align category_theory.bicategory.left_unitor CategoryTheory.Bicategory.leftUnitor
#align category_theory.bicategory.right_unitor CategoryTheory.Bicategory.rightUnitor
#align category_theory.bicategory.whisker_left_id' CategoryTheory.Bicategory.whiskerLeft_id
#align category_theory.bicategory.whisker_left_comp' CategoryTheory.Bicategory.whiskerLeft_comp
#align category_theory.bicategory.id_whisker_left' CategoryTheory.Bicategory.id_whiskerLeft
#align category_theory.bicategory.comp_whisker_left' CategoryTheory.Bicategory.comp_whiskerLeft
#align category_theory.bicategory.id_whisker_right' CategoryTheory.Bicategory.id_whiskerRight
#align category_theory.bicategory.comp_whisker_right' CategoryTheory.Bicategory.comp_whiskerRight
#align category_theory.bicategory.whisker_right_id' CategoryTheory.Bicategory.whiskerRight_id
#align category_theory.bicategory.whisker_right_comp' CategoryTheory.Bicategory.whiskerRight_comp
#align category_theory.bicategory.whisker_assoc' CategoryTheory.Bicategory.whisker_assoc
#align category_theory.bicategory.whisker_exchange' CategoryTheory.Bicategory.whisker_exchange
#align category_theory.bicategory.pentagon' CategoryTheory.Bicategory.pentagon
#align category_theory.bicategory.triangle' CategoryTheory.Bicategory.triangle
namespace Bicategory
scoped infixr:81 " ◁ " => Bicategory.whiskerLeft
scoped infixl:81 " ▷ " => Bicategory.whiskerRight
scoped notation "α_" => Bicategory.associator
scoped notation "λ_" => Bicategory.leftUnitor
scoped notation "ρ_" => Bicategory.rightUnitor
/-!
### Simp-normal form for 2-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 2-morphisms into simp-normal
form defined below. Rewriting into simp-normal form is also useful when applying (forthcoming)
`coherence` tactic.
The simp-normal form of 2-morphisms is defined to be an expression that has the minimal number of
parentheses. More precisely,
1. it is a composition of 2-morphisms like `η₁ ≫ η₂ ≫ η₃ ≫ η₄ ≫ η₅` such that each `ηᵢ` is
either a structural 2-morphisms (2-morphisms made up only of identities, associators, unitors)
or non-structural 2-morphisms, and
2. each non-structural 2-morphism in the composition is of the form `f₁ ◁ f₂ ◁ f₃ ◁ η ▷ f₄ ▷ f₅`,
where each `fᵢ` is a 1-morphism that is not the identity or a composite and `η` is a
non-structural 2-morphisms that is also not the identity or a composite.
Note that `f₁ ◁ f₂ ◁ f₃ ◁ η ▷ f₄ ▷ f₅` is actually `f₁ ◁ (f₂ ◁ (f₃ ◁ ((η ▷ f₄) ▷ f₅)))`.
-/
attribute [instance] homCategory
attribute [reassoc]
whiskerLeft_comp id_whiskerLeft comp_whiskerLeft comp_whiskerRight whiskerRight_id
whiskerRight_comp whisker_assoc whisker_exchange
attribute [reassoc (attr := simp)] pentagon triangle
/-
The following simp attributes are put in order to rewrite any 2-morphisms into normal forms. There
are associators and unitors in the RHS in the several simp lemmas here (e.g. `id_whiskerLeft`),
which at first glance look more complicated than the LHS, but they will be eventually reduced by
the pentagon or the triangle identities, and more generally, (forthcoming) `coherence` tactic.
-/
attribute [simp]
whiskerLeft_id whiskerLeft_comp id_whiskerLeft comp_whiskerLeft id_whiskerRight comp_whiskerRight
whiskerRight_id whiskerRight_comp whisker_assoc
variable {B : Type u} [Bicategory.{w, v} B] {a b c d e : B}
@[reassoc (attr := simp)]
theorem whiskerLeft_hom_inv (f : a ⟶ b) {g h : b ⟶ c} (η : g ≅ h) :
f ◁ η.hom ≫ f ◁ η.inv = 𝟙 (f ≫ g) := by rw [← whiskerLeft_comp, hom_inv_id, whiskerLeft_id]
#align category_theory.bicategory.hom_inv_whisker_left CategoryTheory.Bicategory.whiskerLeft_hom_inv
@[reassoc (attr := simp)]
theorem hom_inv_whiskerRight {f g : a ⟶ b} (η : f ≅ g) (h : b ⟶ c) :
η.hom ▷ h ≫ η.inv ▷ h = 𝟙 (f ≫ h) := by rw [← comp_whiskerRight, hom_inv_id, id_whiskerRight]
#align category_theory.bicategory.hom_inv_whisker_right CategoryTheory.Bicategory.hom_inv_whiskerRight
@[reassoc (attr := simp)]
theorem whiskerLeft_inv_hom (f : a ⟶ b) {g h : b ⟶ c} (η : g ≅ h) :
f ◁ η.inv ≫ f ◁ η.hom = 𝟙 (f ≫ h) := by rw [← whiskerLeft_comp, inv_hom_id, whiskerLeft_id]
#align category_theory.bicategory.inv_hom_whisker_left CategoryTheory.Bicategory.whiskerLeft_inv_hom
@[reassoc (attr := simp)]
theorem inv_hom_whiskerRight {f g : a ⟶ b} (η : f ≅ g) (h : b ⟶ c) :
η.inv ▷ h ≫ η.hom ▷ h = 𝟙 (g ≫ h) := by rw [← comp_whiskerRight, inv_hom_id, id_whiskerRight]
#align category_theory.bicategory.inv_hom_whisker_right CategoryTheory.Bicategory.inv_hom_whiskerRight
/-- The left whiskering of a 2-isomorphism is a 2-isomorphism. -/
@[simps]
def whiskerLeftIso (f : a ⟶ b) {g h : b ⟶ c} (η : g ≅ h) : f ≫ g ≅ f ≫ h where
hom := f ◁ η.hom
inv := f ◁ η.inv
#align category_theory.bicategory.whisker_left_iso CategoryTheory.Bicategory.whiskerLeftIso
instance whiskerLeft_isIso (f : a ⟶ b) {g h : b ⟶ c} (η : g ⟶ h) [IsIso η] : IsIso (f ◁ η) :=
(whiskerLeftIso f (asIso η)).isIso_hom
#align category_theory.bicategory.whisker_left_is_iso CategoryTheory.Bicategory.whiskerLeft_isIso
@[simp]
theorem inv_whiskerLeft (f : a ⟶ b) {g h : b ⟶ c} (η : g ⟶ h) [IsIso η] :
inv (f ◁ η) = f ◁ inv η := by
apply IsIso.inv_eq_of_hom_inv_id
simp only [← whiskerLeft_comp, whiskerLeft_id, IsIso.hom_inv_id]
#align category_theory.bicategory.inv_whisker_left CategoryTheory.Bicategory.inv_whiskerLeft
/-- The right whiskering of a 2-isomorphism is a 2-isomorphism. -/
@[simps!]
def whiskerRightIso {f g : a ⟶ b} (η : f ≅ g) (h : b ⟶ c) : f ≫ h ≅ g ≫ h where
hom := η.hom ▷ h
inv := η.inv ▷ h
#align category_theory.bicategory.whisker_right_iso CategoryTheory.Bicategory.whiskerRightIso
instance whiskerRight_isIso {f g : a ⟶ b} (η : f ⟶ g) (h : b ⟶ c) [IsIso η] : IsIso (η ▷ h) :=
(whiskerRightIso (asIso η) h).isIso_hom
#align category_theory.bicategory.whisker_right_is_iso CategoryTheory.Bicategory.whiskerRight_isIso
@[simp]
theorem inv_whiskerRight {f g : a ⟶ b} (η : f ⟶ g) (h : b ⟶ c) [IsIso η] :
inv (η ▷ h) = inv η ▷ h := by
apply IsIso.inv_eq_of_hom_inv_id
simp only [← comp_whiskerRight, id_whiskerRight, IsIso.hom_inv_id]
#align category_theory.bicategory.inv_whisker_right CategoryTheory.Bicategory.inv_whiskerRight
@[reassoc (attr := simp)]
theorem pentagon_inv (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
f ◁ (α_ g h i).inv ≫ (α_ f (g ≫ h) i).inv ≫ (α_ f g h).inv ▷ i =
(α_ f g (h ≫ i)).inv ≫ (α_ (f ≫ g) h i).inv :=
eq_of_inv_eq_inv (by simp)
#align category_theory.bicategory.pentagon_inv CategoryTheory.Bicategory.pentagon_inv
@[reassoc (attr := simp)]
theorem pentagon_inv_inv_hom_hom_inv (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ f (g ≫ h) i).inv ≫ (α_ f g h).inv ▷ i ≫ (α_ (f ≫ g) h i).hom =
f ◁ (α_ g h i).hom ≫ (α_ f g (h ≫ i)).inv := by
rw [← cancel_epi (f ◁ (α_ g h i).inv), ← cancel_mono (α_ (f ≫ g) h i).inv]
simp
#align category_theory.bicategory.pentagon_inv_inv_hom_hom_inv CategoryTheory.Bicategory.pentagon_inv_inv_hom_hom_inv
@[reassoc (attr := simp)]
theorem pentagon_inv_hom_hom_hom_inv (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ (f ≫ g) h i).inv ≫ (α_ f g h).hom ▷ i ≫ (α_ f (g ≫ h) i).hom =
(α_ f g (h ≫ i)).hom ≫ f ◁ (α_ g h i).inv :=
eq_of_inv_eq_inv (by simp)
#align category_theory.bicategory.pentagon_inv_hom_hom_hom_inv CategoryTheory.Bicategory.pentagon_inv_hom_hom_hom_inv
@[reassoc (attr := simp)]
theorem pentagon_hom_inv_inv_inv_inv (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
f ◁ (α_ g h i).hom ≫ (α_ f g (h ≫ i)).inv ≫ (α_ (f ≫ g) h i).inv =
(α_ f (g ≫ h) i).inv ≫ (α_ f g h).inv ▷ i := by
simp [← cancel_epi (f ◁ (α_ g h i).inv)]
#align category_theory.bicategory.pentagon_hom_inv_inv_inv_inv CategoryTheory.Bicategory.pentagon_hom_inv_inv_inv_inv
@[reassoc (attr := simp)]
theorem pentagon_hom_hom_inv_hom_hom (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ (f ≫ g) h i).hom ≫ (α_ f g (h ≫ i)).hom ≫ f ◁ (α_ g h i).inv =
(α_ f g h).hom ▷ i ≫ (α_ f (g ≫ h) i).hom :=
eq_of_inv_eq_inv (by simp)
#align category_theory.bicategory.pentagon_hom_hom_inv_hom_hom CategoryTheory.Bicategory.pentagon_hom_hom_inv_hom_hom
@[reassoc (attr := simp)]
theorem pentagon_hom_inv_inv_inv_hom (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ f g (h ≫ i)).hom ≫ f ◁ (α_ g h i).inv ≫ (α_ f (g ≫ h) i).inv =
(α_ (f ≫ g) h i).inv ≫ (α_ f g h).hom ▷ i := by
rw [← cancel_epi (α_ f g (h ≫ i)).inv, ← cancel_mono ((α_ f g h).inv ▷ i)]
simp
#align category_theory.bicategory.pentagon_hom_inv_inv_inv_hom CategoryTheory.Bicategory.pentagon_hom_inv_inv_inv_hom
@[reassoc (attr := simp)]
theorem pentagon_hom_hom_inv_inv_hom (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ f (g ≫ h) i).hom ≫ f ◁ (α_ g h i).hom ≫ (α_ f g (h ≫ i)).inv =
(α_ f g h).inv ▷ i ≫ (α_ (f ≫ g) h i).hom :=
eq_of_inv_eq_inv (by simp)
#align category_theory.bicategory.pentagon_hom_hom_inv_inv_hom CategoryTheory.Bicategory.pentagon_hom_hom_inv_inv_hom
@[reassoc (attr := simp)]
theorem pentagon_inv_hom_hom_hom_hom (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ f g h).inv ▷ i ≫ (α_ (f ≫ g) h i).hom ≫ (α_ f g (h ≫ i)).hom =
(α_ f (g ≫ h) i).hom ≫ f ◁ (α_ g h i).hom := by
simp [← cancel_epi ((α_ f g h).hom ▷ i)]
#align category_theory.bicategory.pentagon_inv_hom_hom_hom_hom CategoryTheory.Bicategory.pentagon_inv_hom_hom_hom_hom
@[reassoc (attr := simp)]
theorem pentagon_inv_inv_hom_inv_inv (f : a ⟶ b) (g : b ⟶ c) (h : c ⟶ d) (i : d ⟶ e) :
(α_ f g (h ≫ i)).inv ≫ (α_ (f ≫ g) h i).inv ≫ (α_ f g h).hom ▷ i =
f ◁ (α_ g h i).inv ≫ (α_ f (g ≫ h) i).inv :=
eq_of_inv_eq_inv (by simp)
#align category_theory.bicategory.pentagon_inv_inv_hom_inv_inv CategoryTheory.Bicategory.pentagon_inv_inv_hom_inv_inv
theorem triangle_assoc_comp_left (f : a ⟶ b) (g : b ⟶ c) :
(α_ f (𝟙 b) g).hom ≫ f ◁ (λ_ g).hom = (ρ_ f).hom ▷ g :=
triangle f g
#align category_theory.bicategory.triangle_assoc_comp_left CategoryTheory.Bicategory.triangle_assoc_comp_left
@[reassoc (attr := simp)]
theorem triangle_assoc_comp_right (f : a ⟶ b) (g : b ⟶ c) :
(α_ f (𝟙 b) g).inv ≫ (ρ_ f).hom ▷ g = f ◁ (λ_ g).hom := by rw [← triangle, inv_hom_id_assoc]
#align category_theory.bicategory.triangle_assoc_comp_right CategoryTheory.Bicategory.triangle_assoc_comp_right
@[reassoc (attr := simp)]
theorem triangle_assoc_comp_right_inv (f : a ⟶ b) (g : b ⟶ c) :
(ρ_ f).inv ▷ g ≫ (α_ f (𝟙 b) g).hom = f ◁ (λ_ g).inv := by
simp [← cancel_mono (f ◁ (λ_ g).hom)]
#align category_theory.bicategory.triangle_assoc_comp_right_inv CategoryTheory.Bicategory.triangle_assoc_comp_right_inv
@[reassoc (attr := simp)]
theorem triangle_assoc_comp_left_inv (f : a ⟶ b) (g : b ⟶ c) :
f ◁ (λ_ g).inv ≫ (α_ f (𝟙 b) g).inv = (ρ_ f).inv ▷ g := by
simp [← cancel_mono ((ρ_ f).hom ▷ g)]
#align category_theory.bicategory.triangle_assoc_comp_left_inv CategoryTheory.Bicategory.triangle_assoc_comp_left_inv
@[reassoc]
theorem associator_naturality_left {f f' : a ⟶ b} (η : f ⟶ f') (g : b ⟶ c) (h : c ⟶ d) :
η ▷ g ▷ h ≫ (α_ f' g h).hom = (α_ f g h).hom ≫ η ▷ (g ≫ h) := by simp
#align category_theory.bicategory.associator_naturality_left CategoryTheory.Bicategory.associator_naturality_left
@[reassoc]
theorem associator_inv_naturality_left {f f' : a ⟶ b} (η : f ⟶ f') (g : b ⟶ c) (h : c ⟶ d) :
η ▷ (g ≫ h) ≫ (α_ f' g h).inv = (α_ f g h).inv ≫ η ▷ g ▷ h := by simp
#align category_theory.bicategory.associator_inv_naturality_left CategoryTheory.Bicategory.associator_inv_naturality_left
@[reassoc]
theorem whiskerRight_comp_symm {f f' : a ⟶ b} (η : f ⟶ f') (g : b ⟶ c) (h : c ⟶ d) :
η ▷ g ▷ h = (α_ f g h).hom ≫ η ▷ (g ≫ h) ≫ (α_ f' g h).inv := by simp
#align category_theory.bicategory.whisker_right_comp_symm CategoryTheory.Bicategory.whiskerRight_comp_symm
@[reassoc]
theorem associator_naturality_middle (f : a ⟶ b) {g g' : b ⟶ c} (η : g ⟶ g') (h : c ⟶ d) :
(f ◁ η) ▷ h ≫ (α_ f g' h).hom = (α_ f g h).hom ≫ f ◁ η ▷ h := by simp
#align category_theory.bicategory.associator_naturality_middle CategoryTheory.Bicategory.associator_naturality_middle
@[reassoc]
theorem associator_inv_naturality_middle (f : a ⟶ b) {g g' : b ⟶ c} (η : g ⟶ g') (h : c ⟶ d) :
f ◁ η ▷ h ≫ (α_ f g' h).inv = (α_ f g h).inv ≫ (f ◁ η) ▷ h := by simp
#align category_theory.bicategory.associator_inv_naturality_middle CategoryTheory.Bicategory.associator_inv_naturality_middle
@[reassoc]
theorem whisker_assoc_symm (f : a ⟶ b) {g g' : b ⟶ c} (η : g ⟶ g') (h : c ⟶ d) :
f ◁ η ▷ h = (α_ f g h).inv ≫ (f ◁ η) ▷ h ≫ (α_ f g' h).hom := by simp
#align category_theory.bicategory.whisker_assoc_symm CategoryTheory.Bicategory.whisker_assoc_symm
@[reassoc]
| Mathlib/CategoryTheory/Bicategory/Basic.lean | 369 | 370 | theorem associator_naturality_right (f : a ⟶ b) (g : b ⟶ c) {h h' : c ⟶ d} (η : h ⟶ h') :
(f ≫ g) ◁ η ≫ (α_ f g h').hom = (α_ f g h).hom ≫ f ◁ g ◁ η := by | simp
|
/-
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.List.Basic
#align_import data.list.infix from "leanprover-community/mathlib"@"26f081a2fb920140ed5bc5cc5344e84bcc7cb2b2"
/-!
# Prefixes, suffixes, infixes
This file proves properties about
* `List.isPrefix`: `l₁` is a prefix of `l₂` if `l₂` starts with `l₁`.
* `List.isSuffix`: `l₁` is a suffix of `l₂` if `l₂` ends with `l₁`.
* `List.isInfix`: `l₁` is an infix of `l₂` if `l₁` is a prefix of some suffix of `l₂`.
* `List.inits`: The list of prefixes of a list.
* `List.tails`: The list of prefixes of a list.
* `insert` on lists
All those (except `insert`) are defined in `Mathlib.Data.List.Defs`.
## Notation
* `l₁ <+: l₂`: `l₁` is a prefix of `l₂`.
* `l₁ <:+ l₂`: `l₁` is a suffix of `l₂`.
* `l₁ <:+: l₂`: `l₁` is an infix of `l₂`.
-/
open Nat
variable {α β : Type*}
namespace List
variable {l l₁ l₂ l₃ : List α} {a b : α} {m n : ℕ}
/-! ### prefix, suffix, infix -/
section Fix
#align list.prefix_append List.prefix_append
#align list.suffix_append List.suffix_append
#align list.infix_append List.infix_append
#align list.infix_append' List.infix_append'
#align list.is_prefix.is_infix List.IsPrefix.isInfix
#align list.is_suffix.is_infix List.IsSuffix.isInfix
#align list.nil_prefix List.nil_prefix
#align list.nil_suffix List.nil_suffix
#align list.nil_infix List.nil_infix
#align list.prefix_refl List.prefix_refl
#align list.suffix_refl List.suffix_refl
#align list.infix_refl List.infix_refl
theorem prefix_rfl : l <+: l :=
prefix_refl _
#align list.prefix_rfl List.prefix_rfl
theorem suffix_rfl : l <:+ l :=
suffix_refl _
#align list.suffix_rfl List.suffix_rfl
theorem infix_rfl : l <:+: l :=
infix_refl _
#align list.infix_rfl List.infix_rfl
#align list.suffix_cons List.suffix_cons
theorem prefix_concat (a : α) (l) : l <+: concat l a := by simp
#align list.prefix_concat List.prefix_concat
theorem prefix_concat_iff {l₁ l₂ : List α} {a : α} :
l₁ <+: l₂ ++ [a] ↔ l₁ = l₂ ++ [a] ∨ l₁ <+: l₂ := by
simpa only [← reverse_concat', reverse_inj, reverse_suffix] using
suffix_cons_iff (l₁ := l₁.reverse) (l₂ := l₂.reverse)
#align list.infix_cons List.infix_cons
#align list.infix_concat List.infix_concat
#align list.is_prefix.trans List.IsPrefix.trans
#align list.is_suffix.trans List.IsSuffix.trans
#align list.is_infix.trans List.IsInfix.trans
#align list.is_infix.sublist List.IsInfix.sublist
#align list.is_infix.subset List.IsInfix.subset
#align list.is_prefix.sublist List.IsPrefix.sublist
#align list.is_prefix.subset List.IsPrefix.subset
#align list.is_suffix.sublist List.IsSuffix.sublist
#align list.is_suffix.subset List.IsSuffix.subset
#align list.reverse_suffix List.reverse_suffix
#align list.reverse_prefix List.reverse_prefix
#align list.reverse_infix List.reverse_infix
protected alias ⟨_, isSuffix.reverse⟩ := reverse_prefix
#align list.is_suffix.reverse List.isSuffix.reverse
protected alias ⟨_, isPrefix.reverse⟩ := reverse_suffix
#align list.is_prefix.reverse List.isPrefix.reverse
protected alias ⟨_, isInfix.reverse⟩ := reverse_infix
#align list.is_infix.reverse List.isInfix.reverse
#align list.is_infix.length_le List.IsInfix.length_le
#align list.is_prefix.length_le List.IsPrefix.length_le
#align list.is_suffix.length_le List.IsSuffix.length_le
#align list.infix_nil_iff List.infix_nil
#align list.prefix_nil_iff List.prefix_nil
#align list.suffix_nil_iff List.suffix_nil
alias ⟨eq_nil_of_infix_nil, _⟩ := infix_nil
#align list.eq_nil_of_infix_nil List.eq_nil_of_infix_nil
alias ⟨eq_nil_of_prefix_nil, _⟩ := prefix_nil
#align list.eq_nil_of_prefix_nil List.eq_nil_of_prefix_nil
alias ⟨eq_nil_of_suffix_nil, _⟩ := suffix_nil
#align list.eq_nil_of_suffix_nil List.eq_nil_of_suffix_nil
#align list.infix_iff_prefix_suffix List.infix_iff_prefix_suffix
theorem eq_of_infix_of_length_eq (h : l₁ <:+: l₂) : l₁.length = l₂.length → l₁ = l₂ :=
h.sublist.eq_of_length
#align list.eq_of_infix_of_length_eq List.eq_of_infix_of_length_eq
theorem eq_of_prefix_of_length_eq (h : l₁ <+: l₂) : l₁.length = l₂.length → l₁ = l₂ :=
h.sublist.eq_of_length
#align list.eq_of_prefix_of_length_eq List.eq_of_prefix_of_length_eq
theorem eq_of_suffix_of_length_eq (h : l₁ <:+ l₂) : l₁.length = l₂.length → l₁ = l₂ :=
h.sublist.eq_of_length
#align list.eq_of_suffix_of_length_eq List.eq_of_suffix_of_length_eq
#align list.prefix_of_prefix_length_le List.prefix_of_prefix_length_le
#align list.prefix_or_prefix_of_prefix List.prefix_or_prefix_of_prefix
#align list.suffix_of_suffix_length_le List.suffix_of_suffix_length_le
#align list.suffix_or_suffix_of_suffix List.suffix_or_suffix_of_suffix
#align list.suffix_cons_iff List.suffix_cons_iff
#align list.infix_cons_iff List.infix_cons_iff
#align list.infix_of_mem_join List.infix_of_mem_join
#align list.prefix_append_right_inj List.prefix_append_right_inj
#align list.prefix_cons_inj List.prefix_cons_inj
#align list.take_prefix List.take_prefix
#align list.drop_suffix List.drop_suffix
#align list.take_sublist List.take_sublist
#align list.drop_sublist List.drop_sublist
#align list.take_subset List.take_subset
#align list.drop_subset List.drop_subset
#align list.mem_of_mem_take List.mem_of_mem_take
#align list.mem_of_mem_drop List.mem_of_mem_drop
lemma dropSlice_sublist (n m : ℕ) (l : List α) : l.dropSlice n m <+ l :=
calc
l.dropSlice n m = take n l ++ drop m (drop n l) := by rw [dropSlice_eq, drop_drop, Nat.add_comm]
_ <+ take n l ++ drop n l := (Sublist.refl _).append (drop_sublist _ _)
_ = _ := take_append_drop _ _
#align list.slice_sublist List.dropSlice_sublist
lemma dropSlice_subset (n m : ℕ) (l : List α) : l.dropSlice n m ⊆ l :=
(dropSlice_sublist n m l).subset
#align list.slice_subset List.dropSlice_subset
lemma mem_of_mem_dropSlice {n m : ℕ} {l : List α} {a : α} (h : a ∈ l.dropSlice n m) : a ∈ l :=
dropSlice_subset n m l h
#align list.mem_of_mem_slice List.mem_of_mem_dropSlice
theorem takeWhile_prefix (p : α → Bool) : l.takeWhile p <+: l :=
⟨l.dropWhile p, takeWhile_append_dropWhile p l⟩
#align list.take_while_prefix List.takeWhile_prefix
theorem dropWhile_suffix (p : α → Bool) : l.dropWhile p <:+ l :=
⟨l.takeWhile p, takeWhile_append_dropWhile p l⟩
#align list.drop_while_suffix List.dropWhile_suffix
theorem dropLast_prefix : ∀ l : List α, l.dropLast <+: l
| [] => ⟨nil, by rw [dropLast, List.append_nil]⟩
| a :: l => ⟨_, dropLast_append_getLast (cons_ne_nil a l)⟩
#align list.init_prefix List.dropLast_prefix
theorem tail_suffix (l : List α) : tail l <:+ l := by rw [← drop_one]; apply drop_suffix
#align list.tail_suffix List.tail_suffix
theorem dropLast_sublist (l : List α) : l.dropLast <+ l :=
(dropLast_prefix l).sublist
#align list.init_sublist List.dropLast_sublist
@[gcongr]
theorem drop_sublist_drop_left (l : List α) {m n : ℕ} (h : m ≤ n) : drop n l <+ drop m l := by
rw [← Nat.sub_add_cancel h, drop_add]
apply drop_sublist
theorem dropLast_subset (l : List α) : l.dropLast ⊆ l :=
(dropLast_sublist l).subset
#align list.init_subset List.dropLast_subset
theorem tail_subset (l : List α) : tail l ⊆ l :=
(tail_sublist l).subset
#align list.tail_subset List.tail_subset
theorem mem_of_mem_dropLast (h : a ∈ l.dropLast) : a ∈ l :=
dropLast_subset l h
#align list.mem_of_mem_init List.mem_of_mem_dropLast
theorem mem_of_mem_tail (h : a ∈ l.tail) : a ∈ l :=
tail_subset l h
#align list.mem_of_mem_tail List.mem_of_mem_tail
@[gcongr]
protected theorem Sublist.drop : ∀ {l₁ l₂ : List α}, l₁ <+ l₂ → ∀ n, l₁.drop n <+ l₂.drop n
| _, _, h, 0 => h
| _, _, h, n + 1 => by rw [← drop_tail, ← drop_tail]; exact h.tail.drop n
theorem prefix_iff_eq_append : l₁ <+: l₂ ↔ l₁ ++ drop (length l₁) l₂ = l₂ :=
⟨by rintro ⟨r, rfl⟩; rw [drop_left], fun e => ⟨_, e⟩⟩
#align list.prefix_iff_eq_append List.prefix_iff_eq_append
theorem suffix_iff_eq_append : l₁ <:+ l₂ ↔ take (length l₂ - length l₁) l₂ ++ l₁ = l₂ :=
⟨by rintro ⟨r, rfl⟩; simp only [length_append, Nat.add_sub_cancel_right, take_left], fun e =>
⟨_, e⟩⟩
#align list.suffix_iff_eq_append List.suffix_iff_eq_append
theorem prefix_iff_eq_take : l₁ <+: l₂ ↔ l₁ = take (length l₁) l₂ :=
⟨fun h => append_cancel_right <| (prefix_iff_eq_append.1 h).trans (take_append_drop _ _).symm,
fun e => e.symm ▸ take_prefix _ _⟩
#align list.prefix_iff_eq_take List.prefix_iff_eq_take
theorem prefix_take_iff {x y : List α} {n : ℕ} : x <+: y.take n ↔ x <+: y ∧ x.length ≤ n := by
constructor
· intro h
constructor
· exact List.IsPrefix.trans h <| List.take_prefix n y
· replace h := h.length_le
rw [length_take, Nat.le_min] at h
exact h.left
· intro ⟨hp, hl⟩
have hl' := hp.length_le
rw [List.prefix_iff_eq_take] at *
rw [hp, List.take_take]
simp [min_eq_left, hl, hl']
theorem concat_get_prefix {x y : List α} (h : x <+: y) (hl : x.length < y.length) :
x ++ [y.get ⟨x.length, hl⟩] <+: y := by
use y.drop (x.length + 1)
nth_rw 1 [List.prefix_iff_eq_take.mp h]
convert List.take_append_drop (x.length + 1) y using 2
rw [← List.take_concat_get, List.concat_eq_append]; rfl
theorem suffix_iff_eq_drop : l₁ <:+ l₂ ↔ l₁ = drop (length l₂ - length l₁) l₂ :=
⟨fun h => append_cancel_left <| (suffix_iff_eq_append.1 h).trans (take_append_drop _ _).symm,
fun e => e.symm ▸ drop_suffix _ _⟩
#align list.suffix_iff_eq_drop List.suffix_iff_eq_drop
instance decidablePrefix [DecidableEq α] : ∀ l₁ l₂ : List α, Decidable (l₁ <+: l₂)
| [], l₂ => isTrue ⟨l₂, rfl⟩
| a :: l₁, [] => isFalse fun ⟨t, te⟩ => List.noConfusion te
| a :: l₁, b :: l₂ =>
if h : a = b then
@decidable_of_decidable_of_iff _ _ (decidablePrefix l₁ l₂) (by rw [← h, prefix_cons_inj])
else
isFalse fun ⟨t, te⟩ => h <| by injection te
#align list.decidable_prefix List.decidablePrefix
-- Alternatively, use mem_tails
instance decidableSuffix [DecidableEq α] : ∀ l₁ l₂ : List α, Decidable (l₁ <:+ l₂)
| [], l₂ => isTrue ⟨l₂, append_nil _⟩
| a :: l₁, [] => isFalse <| mt (Sublist.length_le ∘ IsSuffix.sublist) (by simp)
| l₁, b :: l₂ =>
@decidable_of_decidable_of_iff _ _
(@instDecidableOr _ _ _ (l₁.decidableSuffix l₂))
suffix_cons_iff.symm
#align list.decidable_suffix List.decidableSuffix
instance decidableInfix [DecidableEq α] : ∀ l₁ l₂ : List α, Decidable (l₁ <:+: l₂)
| [], l₂ => isTrue ⟨[], l₂, rfl⟩
| a :: l₁, [] => isFalse fun ⟨s, t, te⟩ => by simp at te
| l₁, b :: l₂ =>
@decidable_of_decidable_of_iff _ _
(@instDecidableOr _ _ (l₁.decidablePrefix (b :: l₂)) (l₁.decidableInfix l₂))
infix_cons_iff.symm
#align list.decidable_infix List.decidableInfix
theorem prefix_take_le_iff {L : List (List (Option α))} (hm : m < L.length) :
L.take m <+: L.take n ↔ m ≤ n := by
simp only [prefix_iff_eq_take, length_take]
induction m generalizing L n with
| zero => simp [min_eq_left, eq_self_iff_true, Nat.zero_le, take]
| succ m IH =>
cases L with
| nil => simp_all
| cons l ls =>
cases n with
| zero =>
simp
| succ n =>
simp only [length_cons, succ_eq_add_one, Nat.add_lt_add_iff_right] at hm
simp [← @IH n ls hm, Nat.min_eq_left, Nat.le_of_lt hm]
#align list.prefix_take_le_iff List.prefix_take_le_iff
theorem cons_prefix_iff : a :: l₁ <+: b :: l₂ ↔ a = b ∧ l₁ <+: l₂ := by
constructor
· rintro ⟨L, hL⟩
simp only [cons_append] at hL
injection hL with hLLeft hLRight
exact ⟨hLLeft, ⟨L, hLRight⟩⟩
· rintro ⟨rfl, h⟩
rwa [prefix_cons_inj]
#align list.cons_prefix_iff List.cons_prefix_iff
protected theorem IsPrefix.map (h : l₁ <+: l₂) (f : α → β) : l₁.map f <+: l₂.map f := by
induction' l₁ with hd tl hl generalizing l₂
· simp only [nil_prefix, map_nil]
· cases' l₂ with hd₂ tl₂
· simpa only using eq_nil_of_prefix_nil h
· rw [cons_prefix_iff] at h
simp only [List.map_cons, h, prefix_cons_inj, hl, map]
#align list.is_prefix.map List.IsPrefix.map
protected theorem IsPrefix.filterMap (h : l₁ <+: l₂) (f : α → Option β) :
l₁.filterMap f <+: l₂.filterMap f := by
induction' l₁ with hd₁ tl₁ hl generalizing l₂
· simp only [nil_prefix, filterMap_nil]
· cases' l₂ with hd₂ tl₂
· simpa only using eq_nil_of_prefix_nil h
· rw [cons_prefix_iff] at h
rw [← @singleton_append _ hd₁ _, ← @singleton_append _ hd₂ _, filterMap_append,
filterMap_append, h.left, prefix_append_right_inj]
exact hl h.right
#align list.is_prefix.filter_map List.IsPrefix.filterMap
@[deprecated (since := "2024-03-26")] alias IsPrefix.filter_map := IsPrefix.filterMap
protected theorem IsPrefix.reduceOption {l₁ l₂ : List (Option α)} (h : l₁ <+: l₂) :
l₁.reduceOption <+: l₂.reduceOption :=
h.filterMap id
#align list.is_prefix.reduce_option List.IsPrefix.reduceOption
#align list.is_prefix.filter List.IsPrefix.filter
#align list.is_suffix.filter List.IsSuffix.filter
#align list.is_infix.filter List.IsInfix.filter
instance : IsPartialOrder (List α) (· <+: ·) where
refl := prefix_refl
trans _ _ _ := IsPrefix.trans
antisymm _ _ h₁ h₂ := eq_of_prefix_of_length_eq h₁ <| h₁.length_le.antisymm h₂.length_le
instance : IsPartialOrder (List α) (· <:+ ·) where
refl := suffix_refl
trans _ _ _ := IsSuffix.trans
antisymm _ _ h₁ h₂ := eq_of_suffix_of_length_eq h₁ <| h₁.length_le.antisymm h₂.length_le
instance : IsPartialOrder (List α) (· <:+: ·) where
refl := infix_refl
trans _ _ _ := IsInfix.trans
antisymm _ _ h₁ h₂ := eq_of_infix_of_length_eq h₁ <| h₁.length_le.antisymm h₂.length_le
end Fix
section InitsTails
@[simp]
theorem mem_inits : ∀ s t : List α, s ∈ inits t ↔ s <+: t
| s, [] =>
suffices s = nil ↔ s <+: nil by simpa only [inits, mem_singleton]
⟨fun h => h.symm ▸ prefix_refl [], eq_nil_of_prefix_nil⟩
| s, a :: t =>
suffices (s = nil ∨ ∃ l ∈ inits t, a :: l = s) ↔ s <+: a :: t by simpa
⟨fun o =>
match s, o with
| _, Or.inl rfl => ⟨_, rfl⟩
| s, Or.inr ⟨r, hr, hs⟩ => by
let ⟨s, ht⟩ := (mem_inits _ _).1 hr
rw [← hs, ← ht]; exact ⟨s, rfl⟩,
fun mi =>
match s, mi with
| [], ⟨_, rfl⟩ => Or.inl rfl
| b :: s, ⟨r, hr⟩ =>
(List.noConfusion hr) fun ba (st : s ++ r = t) =>
Or.inr <| by rw [ba]; exact ⟨_, (mem_inits _ _).2 ⟨_, st⟩, rfl⟩⟩
#align list.mem_inits List.mem_inits
@[simp]
theorem mem_tails : ∀ s t : List α, s ∈ tails t ↔ s <:+ t
| s, [] => by
simp only [tails, mem_singleton, suffix_nil]
| s, a :: t => by
simp only [tails, mem_cons, mem_tails s t];
exact
show s = a :: t ∨ s <:+ t ↔ s <:+ a :: t from
⟨fun o =>
match s, t, o with
| _, t, Or.inl rfl => suffix_rfl
| s, _, Or.inr ⟨l, rfl⟩ => ⟨a :: l, rfl⟩,
fun e =>
match s, t, e with
| _, t, ⟨[], rfl⟩ => Or.inl rfl
| s, t, ⟨b :: l, he⟩ => List.noConfusion he fun _ lt => Or.inr ⟨l, lt⟩⟩
#align list.mem_tails List.mem_tails
theorem inits_cons (a : α) (l : List α) : inits (a :: l) = [] :: l.inits.map fun t => a :: t := by
simp
#align list.inits_cons List.inits_cons
theorem tails_cons (a : α) (l : List α) : tails (a :: l) = (a :: l) :: l.tails := by simp
#align list.tails_cons List.tails_cons
@[simp]
theorem inits_append : ∀ s t : List α, inits (s ++ t) = s.inits ++ t.inits.tail.map fun l => s ++ l
| [], [] => by simp
| [], a :: t => by simp [· ∘ ·]
| a :: s, t => by simp [inits_append s t, · ∘ ·]
#align list.inits_append List.inits_append
@[simp]
theorem tails_append :
∀ s t : List α, tails (s ++ t) = (s.tails.map fun l => l ++ t) ++ t.tails.tail
| [], [] => by simp
| [], a :: t => by simp
| a :: s, t => by simp [tails_append s t]
#align list.tails_append List.tails_append
-- the lemma names `inits_eq_tails` and `tails_eq_inits` are like `sublists_eq_sublists'`
theorem inits_eq_tails : ∀ l : List α, l.inits = (reverse <| map reverse <| tails <| reverse l)
| [] => by simp
| a :: l => by simp [inits_eq_tails l, map_eq_map_iff, reverse_map]
#align list.inits_eq_tails List.inits_eq_tails
theorem tails_eq_inits : ∀ l : List α, l.tails = (reverse <| map reverse <| inits <| reverse l)
| [] => by simp
| a :: l => by simp [tails_eq_inits l, append_left_inj]
#align list.tails_eq_inits List.tails_eq_inits
theorem inits_reverse (l : List α) : inits (reverse l) = reverse (map reverse l.tails) := by
rw [tails_eq_inits l]
simp [reverse_involutive.comp_self, reverse_map]
#align list.inits_reverse List.inits_reverse
theorem tails_reverse (l : List α) : tails (reverse l) = reverse (map reverse l.inits) := by
rw [inits_eq_tails l]
simp [reverse_involutive.comp_self, reverse_map]
#align list.tails_reverse List.tails_reverse
| Mathlib/Data/List/Infix.lean | 440 | 442 | theorem map_reverse_inits (l : List α) : map reverse l.inits = (reverse <| tails <| reverse l) := by |
rw [inits_eq_tails l]
simp [reverse_involutive.comp_self, reverse_map]
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Finsupp.Encodable
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Span
import Mathlib.Data.Set.Countable
#align_import linear_algebra.finsupp from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Properties of the module `α →₀ M`
Given an `R`-module `M`, the `R`-module structure on `α →₀ M` is defined in
`Data.Finsupp.Basic`.
In this file we define `Finsupp.supported s` to be the set `{f : α →₀ M | f.support ⊆ s}`
interpreted as a submodule of `α →₀ M`. We also define `LinearMap` versions of various maps:
* `Finsupp.lsingle a : M →ₗ[R] ι →₀ M`: `Finsupp.single a` as a linear map;
* `Finsupp.lapply a : (ι →₀ M) →ₗ[R] M`: the map `fun f ↦ f a` as a linear map;
* `Finsupp.lsubtypeDomain (s : Set α) : (α →₀ M) →ₗ[R] (s →₀ M)`: restriction to a subtype as a
linear map;
* `Finsupp.restrictDom`: `Finsupp.filter` as a linear map to `Finsupp.supported s`;
* `Finsupp.lsum`: `Finsupp.sum` or `Finsupp.liftAddHom` as a `LinearMap`;
* `Finsupp.total α M R (v : ι → M)`: sends `l : ι → R` to the linear combination of `v i` with
coefficients `l i`;
* `Finsupp.totalOn`: a restricted version of `Finsupp.total` with domain `Finsupp.supported R R s`
and codomain `Submodule.span R (v '' s)`;
* `Finsupp.supportedEquivFinsupp`: a linear equivalence between the functions `α →₀ M` supported
on `s` and the functions `s →₀ M`;
* `Finsupp.lmapDomain`: a linear map version of `Finsupp.mapDomain`;
* `Finsupp.domLCongr`: a `LinearEquiv` version of `Finsupp.domCongr`;
* `Finsupp.congr`: if the sets `s` and `t` are equivalent, then `supported M R s` is equivalent to
`supported M R t`;
* `Finsupp.lcongr`: a `LinearEquiv`alence between `α →₀ M` and `β →₀ N` constructed using
`e : α ≃ β` and `e' : M ≃ₗ[R] N`.
## Tags
function with finite support, module, linear algebra
-/
noncomputable section
open Set LinearMap Submodule
namespace Finsupp
section SMul
variable {α : Type*} {β : Type*} {R : Type*} {M : Type*} {M₂ : Type*}
theorem smul_sum [Zero β] [AddCommMonoid M] [DistribSMul R M] {v : α →₀ β} {c : R} {h : α → β → M} :
c • v.sum h = v.sum fun a b => c • h a b :=
Finset.smul_sum
#align finsupp.smul_sum Finsupp.smul_sum
@[simp]
theorem sum_smul_index_linearMap' [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M₂]
[Module R M₂] {v : α →₀ M} {c : R} {h : α → M →ₗ[R] M₂} :
((c • v).sum fun a => h a) = c • v.sum fun a => h a := by
rw [Finsupp.sum_smul_index', Finsupp.smul_sum]
· simp only [map_smul]
· intro i
exact (h i).map_zero
#align finsupp.sum_smul_index_linear_map' Finsupp.sum_smul_index_linearMap'
end SMul
section LinearEquivFunOnFinite
variable (R : Type*) {S : Type*} (M : Type*) (α : Type*)
variable [Finite α] [AddCommMonoid M] [Semiring R] [Module R M]
/-- Given `Finite α`, `linearEquivFunOnFinite R` is the natural `R`-linear equivalence between
`α →₀ β` and `α → β`. -/
@[simps apply]
noncomputable def linearEquivFunOnFinite : (α →₀ M) ≃ₗ[R] α → M :=
{ equivFunOnFinite with
toFun := (⇑)
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv_fun_on_finite Finsupp.linearEquivFunOnFinite
@[simp]
theorem linearEquivFunOnFinite_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α) (single x m) = Pi.single x m :=
equivFunOnFinite_single x m
#align finsupp.linear_equiv_fun_on_finite_single Finsupp.linearEquivFunOnFinite_single
@[simp]
theorem linearEquivFunOnFinite_symm_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α).symm (Pi.single x m) = single x m :=
equivFunOnFinite_symm_single x m
#align finsupp.linear_equiv_fun_on_finite_symm_single Finsupp.linearEquivFunOnFinite_symm_single
@[simp]
theorem linearEquivFunOnFinite_symm_coe (f : α →₀ M) : (linearEquivFunOnFinite R M α).symm f = f :=
(linearEquivFunOnFinite R M α).symm_apply_apply f
#align finsupp.linear_equiv_fun_on_finite_symm_coe Finsupp.linearEquivFunOnFinite_symm_coe
end LinearEquivFunOnFinite
section LinearEquiv.finsuppUnique
variable (R : Type*) {S : Type*} (M : Type*)
variable [AddCommMonoid M] [Semiring R] [Module R M]
variable (α : Type*) [Unique α]
/-- If `α` has a unique term, then the type of finitely supported functions `α →₀ M` is
`R`-linearly equivalent to `M`. -/
noncomputable def LinearEquiv.finsuppUnique : (α →₀ M) ≃ₗ[R] M :=
{ Finsupp.equivFunOnFinite.trans (Equiv.funUnique α M) with
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv.finsupp_unique Finsupp.LinearEquiv.finsuppUnique
variable {R M}
@[simp]
theorem LinearEquiv.finsuppUnique_apply (f : α →₀ M) :
LinearEquiv.finsuppUnique R M α f = f default :=
rfl
#align finsupp.linear_equiv.finsupp_unique_apply Finsupp.LinearEquiv.finsuppUnique_apply
variable {α}
@[simp]
theorem LinearEquiv.finsuppUnique_symm_apply [Unique α] (m : M) :
(LinearEquiv.finsuppUnique R M α).symm m = Finsupp.single default m := by
ext; simp [LinearEquiv.finsuppUnique, Equiv.funUnique, single, Pi.single,
equivFunOnFinite, Function.update]
#align finsupp.linear_equiv.finsupp_unique_symm_apply Finsupp.LinearEquiv.finsuppUnique_symm_apply
end LinearEquiv.finsuppUnique
variable {α : Type*} {M : Type*} {N : Type*} {P : Type*} {R : Type*} {S : Type*}
variable [Semiring R] [Semiring S] [AddCommMonoid M] [Module R M]
variable [AddCommMonoid N] [Module R N]
variable [AddCommMonoid P] [Module R P]
/-- Interpret `Finsupp.single a` as a linear map. -/
def lsingle (a : α) : M →ₗ[R] α →₀ M :=
{ Finsupp.singleAddHom a with map_smul' := fun _ _ => (smul_single _ _ _).symm }
#align finsupp.lsingle Finsupp.lsingle
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere. -/
theorem lhom_ext ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a b, φ (single a b) = ψ (single a b)) : φ = ψ :=
LinearMap.toAddMonoidHom_injective <| addHom_ext h
#align finsupp.lhom_ext Finsupp.lhom_ext
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere.
We formulate this fact using equality of linear maps `φ.comp (lsingle a)` and `ψ.comp (lsingle a)`
so that the `ext` tactic can apply a type-specific extensionality lemma to prove equality of these
maps. E.g., if `M = R`, then it suffices to verify `φ (single a 1) = ψ (single a 1)`. -/
-- Porting note: The priority should be higher than `LinearMap.ext`.
@[ext high]
theorem lhom_ext' ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a, φ.comp (lsingle a) = ψ.comp (lsingle a)) :
φ = ψ :=
lhom_ext fun a => LinearMap.congr_fun (h a)
#align finsupp.lhom_ext' Finsupp.lhom_ext'
/-- Interpret `fun f : α →₀ M ↦ f a` as a linear map. -/
def lapply (a : α) : (α →₀ M) →ₗ[R] M :=
{ Finsupp.applyAddHom a with map_smul' := fun _ _ => rfl }
#align finsupp.lapply Finsupp.lapply
section CompatibleSMul
variable (R S M N ι : Type*)
variable [Semiring S] [AddCommMonoid M] [AddCommMonoid N] [Module S M] [Module S N]
instance _root_.LinearMap.CompatibleSMul.finsupp_dom [SMulZeroClass R M] [DistribSMul R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul (ι →₀ M) N R S where
map_smul f r m := by
conv_rhs => rw [← sum_single m, map_finsupp_sum, smul_sum]
erw [← sum_single (r • m), sum_mapRange_index single_zero, map_finsupp_sum]
congr; ext i m; exact (f.comp <| lsingle i).map_smul_of_tower r m
instance _root_.LinearMap.CompatibleSMul.finsupp_cod [SMul R M] [SMulZeroClass R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul M (ι →₀ N) R S where
map_smul f r m := by ext i; apply ((lapply i).comp f).map_smul_of_tower
end CompatibleSMul
/-- Forget that a function is finitely supported.
This is the linear version of `Finsupp.toFun`. -/
@[simps]
def lcoeFun : (α →₀ M) →ₗ[R] α → M where
toFun := (⇑)
map_add' x y := by
ext
simp
map_smul' x y := by
ext
simp
#align finsupp.lcoe_fun Finsupp.lcoeFun
section LSubtypeDomain
variable (s : Set α)
/-- Interpret `Finsupp.subtypeDomain s` as a linear map. -/
def lsubtypeDomain : (α →₀ M) →ₗ[R] s →₀ M where
toFun := subtypeDomain fun x => x ∈ s
map_add' _ _ := subtypeDomain_add
map_smul' _ _ := ext fun _ => rfl
#align finsupp.lsubtype_domain Finsupp.lsubtypeDomain
theorem lsubtypeDomain_apply (f : α →₀ M) :
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M) f = subtypeDomain (fun x => x ∈ s) f :=
rfl
#align finsupp.lsubtype_domain_apply Finsupp.lsubtypeDomain_apply
end LSubtypeDomain
@[simp]
theorem lsingle_apply (a : α) (b : M) : (lsingle a : M →ₗ[R] α →₀ M) b = single a b :=
rfl
#align finsupp.lsingle_apply Finsupp.lsingle_apply
@[simp]
theorem lapply_apply (a : α) (f : α →₀ M) : (lapply a : (α →₀ M) →ₗ[R] M) f = f a :=
rfl
#align finsupp.lapply_apply Finsupp.lapply_apply
@[simp]
theorem lapply_comp_lsingle_same (a : α) : lapply a ∘ₗ lsingle a = (.id : M →ₗ[R] M) := by ext; simp
@[simp]
theorem lapply_comp_lsingle_of_ne (a a' : α) (h : a ≠ a') :
lapply a ∘ₗ lsingle a' = (0 : M →ₗ[R] M) := by ext; simp [h.symm]
@[simp]
theorem ker_lsingle (a : α) : ker (lsingle a : M →ₗ[R] α →₀ M) = ⊥ :=
ker_eq_bot_of_injective (single_injective a)
#align finsupp.ker_lsingle Finsupp.ker_lsingle
theorem lsingle_range_le_ker_lapply (s t : Set α) (h : Disjoint s t) :
⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) ≤
⨅ a ∈ t, ker (lapply a : (α →₀ M) →ₗ[R] M) := by
refine iSup_le fun a₁ => iSup_le fun h₁ => range_le_iff_comap.2 ?_
simp only [(ker_comp _ _).symm, eq_top_iff, SetLike.le_def, mem_ker, comap_iInf, mem_iInf]
intro b _ a₂ h₂
have : a₁ ≠ a₂ := fun eq => h.le_bot ⟨h₁, eq.symm ▸ h₂⟩
exact single_eq_of_ne this
#align finsupp.lsingle_range_le_ker_lapply Finsupp.lsingle_range_le_ker_lapply
theorem iInf_ker_lapply_le_bot : ⨅ a, ker (lapply a : (α →₀ M) →ₗ[R] M) ≤ ⊥ := by
simp only [SetLike.le_def, mem_iInf, mem_ker, mem_bot, lapply_apply]
exact fun a h => Finsupp.ext h
#align finsupp.infi_ker_lapply_le_bot Finsupp.iInf_ker_lapply_le_bot
theorem iSup_lsingle_range : ⨆ a, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) = ⊤ := by
refine eq_top_iff.2 <| SetLike.le_def.2 fun f _ => ?_
rw [← sum_single f]
exact sum_mem fun a _ => Submodule.mem_iSup_of_mem a ⟨_, rfl⟩
#align finsupp.supr_lsingle_range Finsupp.iSup_lsingle_range
theorem disjoint_lsingle_lsingle (s t : Set α) (hs : Disjoint s t) :
Disjoint (⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M))
(⨆ a ∈ t, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M)) := by
-- Porting note: 2 placeholders are added to prevent timeout.
refine
(Disjoint.mono
(lsingle_range_le_ker_lapply s sᶜ ?_)
(lsingle_range_le_ker_lapply t tᶜ ?_))
?_
· apply disjoint_compl_right
· apply disjoint_compl_right
rw [disjoint_iff_inf_le]
refine le_trans (le_iInf fun i => ?_) iInf_ker_lapply_le_bot
classical
by_cases his : i ∈ s
· by_cases hit : i ∈ t
· exact (hs.le_bot ⟨his, hit⟩).elim
exact inf_le_of_right_le (iInf_le_of_le i <| iInf_le _ hit)
exact inf_le_of_left_le (iInf_le_of_le i <| iInf_le _ his)
#align finsupp.disjoint_lsingle_lsingle Finsupp.disjoint_lsingle_lsingle
theorem span_single_image (s : Set M) (a : α) :
Submodule.span R (single a '' s) = (Submodule.span R s).map (lsingle a : M →ₗ[R] α →₀ M) := by
rw [← span_image]; rfl
#align finsupp.span_single_image Finsupp.span_single_image
variable (M R)
/-- `Finsupp.supported M R s` is the `R`-submodule of all `p : α →₀ M` such that `p.support ⊆ s`. -/
def supported (s : Set α) : Submodule R (α →₀ M) where
carrier := { p | ↑p.support ⊆ s }
add_mem' {p q} hp hq := by
classical
refine Subset.trans (Subset.trans (Finset.coe_subset.2 support_add) ?_) (union_subset hp hq)
rw [Finset.coe_union]
zero_mem' := by
simp only [subset_def, Finset.mem_coe, Set.mem_setOf_eq, mem_support_iff, zero_apply]
intro h ha
exact (ha rfl).elim
smul_mem' a p hp := Subset.trans (Finset.coe_subset.2 support_smul) hp
#align finsupp.supported Finsupp.supported
variable {M}
theorem mem_supported {s : Set α} (p : α →₀ M) : p ∈ supported M R s ↔ ↑p.support ⊆ s :=
Iff.rfl
#align finsupp.mem_supported Finsupp.mem_supported
theorem mem_supported' {s : Set α} (p : α →₀ M) :
p ∈ supported M R s ↔ ∀ x ∉ s, p x = 0 := by
haveI := Classical.decPred fun x : α => x ∈ s; simp [mem_supported, Set.subset_def, not_imp_comm]
#align finsupp.mem_supported' Finsupp.mem_supported'
theorem mem_supported_support (p : α →₀ M) : p ∈ Finsupp.supported M R (p.support : Set α) := by
rw [Finsupp.mem_supported]
#align finsupp.mem_supported_support Finsupp.mem_supported_support
theorem single_mem_supported {s : Set α} {a : α} (b : M) (h : a ∈ s) :
single a b ∈ supported M R s :=
Set.Subset.trans support_single_subset (Finset.singleton_subset_set_iff.2 h)
#align finsupp.single_mem_supported Finsupp.single_mem_supported
theorem supported_eq_span_single (s : Set α) :
supported R R s = span R ((fun i => single i 1) '' s) := by
refine (span_eq_of_le _ ?_ (SetLike.le_def.2 fun l hl => ?_)).symm
· rintro _ ⟨_, hp, rfl⟩
exact single_mem_supported R 1 hp
· rw [← l.sum_single]
refine sum_mem fun i il => ?_
-- Porting note: Needed to help this convert quite a bit replacing underscores
convert smul_mem (M := α →₀ R) (x := single i 1) (span R ((fun i => single i 1) '' s)) (l i) ?_
· simp [span]
· apply subset_span
apply Set.mem_image_of_mem _ (hl il)
#align finsupp.supported_eq_span_single Finsupp.supported_eq_span_single
variable (M)
/-- Interpret `Finsupp.filter s` as a linear map from `α →₀ M` to `supported M R s`. -/
def restrictDom (s : Set α) [DecidablePred (· ∈ s)] : (α →₀ M) →ₗ[R] supported M R s :=
LinearMap.codRestrict _
{ toFun := filter (· ∈ s)
map_add' := fun _ _ => filter_add
map_smul' := fun _ _ => filter_smul } fun l =>
(mem_supported' _ _).2 fun _ => filter_apply_neg (· ∈ s) l
#align finsupp.restrict_dom Finsupp.restrictDom
variable {M R}
section
@[simp]
theorem restrictDom_apply (s : Set α) (l : α →₀ M) [DecidablePred (· ∈ s)]:
(restrictDom M R s l : α →₀ M) = Finsupp.filter (· ∈ s) l := rfl
#align finsupp.restrict_dom_apply Finsupp.restrictDom_apply
end
theorem restrictDom_comp_subtype (s : Set α) [DecidablePred (· ∈ s)] :
(restrictDom M R s).comp (Submodule.subtype _) = LinearMap.id := by
ext l a
by_cases h : a ∈ s <;> simp [h]
exact ((mem_supported' R l.1).1 l.2 a h).symm
#align finsupp.restrict_dom_comp_subtype Finsupp.restrictDom_comp_subtype
theorem range_restrictDom (s : Set α) [DecidablePred (· ∈ s)] :
LinearMap.range (restrictDom M R s) = ⊤ :=
range_eq_top.2 <|
Function.RightInverse.surjective <| LinearMap.congr_fun (restrictDom_comp_subtype s)
#align finsupp.range_restrict_dom Finsupp.range_restrictDom
theorem supported_mono {s t : Set α} (st : s ⊆ t) : supported M R s ≤ supported M R t := fun _ h =>
Set.Subset.trans h st
#align finsupp.supported_mono Finsupp.supported_mono
@[simp]
theorem supported_empty : supported M R (∅ : Set α) = ⊥ :=
eq_bot_iff.2 fun l h => (Submodule.mem_bot R).2 <| by ext; simp_all [mem_supported']
#align finsupp.supported_empty Finsupp.supported_empty
@[simp]
theorem supported_univ : supported M R (Set.univ : Set α) = ⊤ :=
eq_top_iff.2 fun _ _ => Set.subset_univ _
#align finsupp.supported_univ Finsupp.supported_univ
theorem supported_iUnion {δ : Type*} (s : δ → Set α) :
supported M R (⋃ i, s i) = ⨆ i, supported M R (s i) := by
refine le_antisymm ?_ (iSup_le fun i => supported_mono <| Set.subset_iUnion _ _)
haveI := Classical.decPred fun x => x ∈ ⋃ i, s i
suffices
LinearMap.range ((Submodule.subtype _).comp (restrictDom M R (⋃ i, s i))) ≤
⨆ i, supported M R (s i) by
rwa [LinearMap.range_comp, range_restrictDom, Submodule.map_top, range_subtype] at this
rw [range_le_iff_comap, eq_top_iff]
rintro l ⟨⟩
-- Porting note: Was ported as `induction l using Finsupp.induction`
refine Finsupp.induction l ?_ ?_
· exact zero_mem _
· refine fun x a l _ _ => add_mem ?_
by_cases h : ∃ i, x ∈ s i <;> simp [h]
cases' h with i hi
exact le_iSup (fun i => supported M R (s i)) i (single_mem_supported R _ hi)
#align finsupp.supported_Union Finsupp.supported_iUnion
theorem supported_union (s t : Set α) :
supported M R (s ∪ t) = supported M R s ⊔ supported M R t := by
erw [Set.union_eq_iUnion, supported_iUnion, iSup_bool_eq]; rfl
#align finsupp.supported_union Finsupp.supported_union
theorem supported_iInter {ι : Type*} (s : ι → Set α) :
supported M R (⋂ i, s i) = ⨅ i, supported M R (s i) :=
Submodule.ext fun x => by simp [mem_supported, subset_iInter_iff]
#align finsupp.supported_Inter Finsupp.supported_iInter
theorem supported_inter (s t : Set α) :
supported M R (s ∩ t) = supported M R s ⊓ supported M R t := by
rw [Set.inter_eq_iInter, supported_iInter, iInf_bool_eq]; rfl
#align finsupp.supported_inter Finsupp.supported_inter
theorem disjoint_supported_supported {s t : Set α} (h : Disjoint s t) :
Disjoint (supported M R s) (supported M R t) :=
disjoint_iff.2 <| by rw [← supported_inter, disjoint_iff_inter_eq_empty.1 h, supported_empty]
#align finsupp.disjoint_supported_supported Finsupp.disjoint_supported_supported
theorem disjoint_supported_supported_iff [Nontrivial M] {s t : Set α} :
Disjoint (supported M R s) (supported M R t) ↔ Disjoint s t := by
refine ⟨fun h => Set.disjoint_left.mpr fun x hx1 hx2 => ?_, disjoint_supported_supported⟩
rcases exists_ne (0 : M) with ⟨y, hy⟩
have := h.le_bot ⟨single_mem_supported R y hx1, single_mem_supported R y hx2⟩
rw [mem_bot, single_eq_zero] at this
exact hy this
#align finsupp.disjoint_supported_supported_iff Finsupp.disjoint_supported_supported_iff
/-- Interpret `Finsupp.restrictSupportEquiv` as a linear equivalence between
`supported M R s` and `s →₀ M`. -/
def supportedEquivFinsupp (s : Set α) : supported M R s ≃ₗ[R] s →₀ M := by
let F : supported M R s ≃ (s →₀ M) := restrictSupportEquiv s M
refine F.toLinearEquiv ?_
have :
(F : supported M R s → ↥s →₀ M) =
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M).comp (Submodule.subtype (supported M R s)) :=
rfl
rw [this]
exact LinearMap.isLinear _
#align finsupp.supported_equiv_finsupp Finsupp.supportedEquivFinsupp
section LSum
variable (S)
variable [Module S N] [SMulCommClass R S N]
/-- Lift a family of linear maps `M →ₗ[R] N` indexed by `x : α` to a linear map from `α →₀ M` to
`N` using `Finsupp.sum`. This is an upgraded version of `Finsupp.liftAddHom`.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used.
-/
def lsum : (α → M →ₗ[R] N) ≃ₗ[S] (α →₀ M) →ₗ[R] N where
toFun F :=
{ toFun := fun d => d.sum fun i => F i
map_add' := (liftAddHom (α := α) (M := M) (N := N) fun x => (F x).toAddMonoidHom).map_add
map_smul' := fun c f => by simp [sum_smul_index', smul_sum] }
invFun F x := F.comp (lsingle x)
left_inv F := by
ext x y
simp
right_inv F := by
ext x y
simp
map_add' F G := by
ext x y
simp
map_smul' F G := by
ext x y
simp
#align finsupp.lsum Finsupp.lsum
@[simp]
theorem coe_lsum (f : α → M →ₗ[R] N) : (lsum S f : (α →₀ M) → N) = fun d => d.sum fun i => f i :=
rfl
#align finsupp.coe_lsum Finsupp.coe_lsum
theorem lsum_apply (f : α → M →ₗ[R] N) (l : α →₀ M) : Finsupp.lsum S f l = l.sum fun b => f b :=
rfl
#align finsupp.lsum_apply Finsupp.lsum_apply
theorem lsum_single (f : α → M →ₗ[R] N) (i : α) (m : M) :
Finsupp.lsum S f (Finsupp.single i m) = f i m :=
Finsupp.sum_single_index (f i).map_zero
#align finsupp.lsum_single Finsupp.lsum_single
@[simp] theorem lsum_comp_lsingle (f : α → M →ₗ[R] N) (i : α) :
Finsupp.lsum S f ∘ₗ lsingle i = f i := by ext; simp
theorem lsum_symm_apply (f : (α →₀ M) →ₗ[R] N) (x : α) : (lsum S).symm f x = f.comp (lsingle x) :=
rfl
#align finsupp.lsum_symm_apply Finsupp.lsum_symm_apply
end LSum
section
variable (M) (R) (X : Type*) (S)
variable [Module S M] [SMulCommClass R S M]
/-- A slight rearrangement from `lsum` gives us
the bijection underlying the free-forgetful adjunction for R-modules.
-/
noncomputable def lift : (X → M) ≃+ ((X →₀ R) →ₗ[R] M) :=
(AddEquiv.arrowCongr (Equiv.refl X) (ringLmapEquivSelf R ℕ M).toAddEquiv.symm).trans
(lsum _ : _ ≃ₗ[ℕ] _).toAddEquiv
#align finsupp.lift Finsupp.lift
@[simp]
theorem lift_symm_apply (f) (x) : ((lift M R X).symm f) x = f (single x 1) :=
rfl
#align finsupp.lift_symm_apply Finsupp.lift_symm_apply
@[simp]
theorem lift_apply (f) (g) : ((lift M R X) f) g = g.sum fun x r => r • f x :=
rfl
#align finsupp.lift_apply Finsupp.lift_apply
/-- Given compatible `S` and `R`-module structures on `M` and a type `X`, the set of functions
`X → M` is `S`-linearly equivalent to the `R`-linear maps from the free `R`-module
on `X` to `M`. -/
noncomputable def llift : (X → M) ≃ₗ[S] (X →₀ R) →ₗ[R] M :=
{ lift M R X with
map_smul' := by
intros
dsimp
ext
simp only [coe_comp, Function.comp_apply, lsingle_apply, lift_apply, Pi.smul_apply,
sum_single_index, zero_smul, one_smul, LinearMap.smul_apply] }
#align finsupp.llift Finsupp.llift
@[simp]
theorem llift_apply (f : X → M) (x : X →₀ R) : llift M R S X f x = lift M R X f x :=
rfl
#align finsupp.llift_apply Finsupp.llift_apply
@[simp]
theorem llift_symm_apply (f : (X →₀ R) →ₗ[R] M) (x : X) :
(llift M R S X).symm f x = f (single x 1) :=
rfl
#align finsupp.llift_symm_apply Finsupp.llift_symm_apply
end
section LMapDomain
variable {α' : Type*} {α'' : Type*} (M R)
/-- Interpret `Finsupp.mapDomain` as a linear map. -/
def lmapDomain (f : α → α') : (α →₀ M) →ₗ[R] α' →₀ M where
toFun := mapDomain f
map_add' _ _ := mapDomain_add
map_smul' := mapDomain_smul
#align finsupp.lmap_domain Finsupp.lmapDomain
@[simp]
theorem lmapDomain_apply (f : α → α') (l : α →₀ M) :
(lmapDomain M R f : (α →₀ M) →ₗ[R] α' →₀ M) l = mapDomain f l :=
rfl
#align finsupp.lmap_domain_apply Finsupp.lmapDomain_apply
@[simp]
theorem lmapDomain_id : (lmapDomain M R _root_.id : (α →₀ M) →ₗ[R] α →₀ M) = LinearMap.id :=
LinearMap.ext fun _ => mapDomain_id
#align finsupp.lmap_domain_id Finsupp.lmapDomain_id
theorem lmapDomain_comp (f : α → α') (g : α' → α'') :
lmapDomain M R (g ∘ f) = (lmapDomain M R g).comp (lmapDomain M R f) :=
LinearMap.ext fun _ => mapDomain_comp
#align finsupp.lmap_domain_comp Finsupp.lmapDomain_comp
theorem supported_comap_lmapDomain (f : α → α') (s : Set α') :
supported M R (f ⁻¹' s) ≤ (supported M R s).comap (lmapDomain M R f) := by
classical
intro l (hl : (l.support : Set α) ⊆ f ⁻¹' s)
show ↑(mapDomain f l).support ⊆ s
rw [← Set.image_subset_iff, ← Finset.coe_image] at hl
exact Set.Subset.trans mapDomain_support hl
#align finsupp.supported_comap_lmap_domain Finsupp.supported_comap_lmapDomain
theorem lmapDomain_supported (f : α → α') (s : Set α) :
(supported M R s).map (lmapDomain M R f) = supported M R (f '' s) := by
classical
cases isEmpty_or_nonempty α
· simp [s.eq_empty_of_isEmpty]
refine
le_antisymm
(map_le_iff_le_comap.2 <|
le_trans (supported_mono <| Set.subset_preimage_image _ _)
(supported_comap_lmapDomain M R _ _))
?_
intro l hl
refine ⟨(lmapDomain M R (Function.invFunOn f s) : (α' →₀ M) →ₗ[R] α →₀ M) l, fun x hx => ?_, ?_⟩
· rcases Finset.mem_image.1 (mapDomain_support hx) with ⟨c, hc, rfl⟩
exact Function.invFunOn_mem (by simpa using hl hc)
· rw [← LinearMap.comp_apply, ← lmapDomain_comp]
refine (mapDomain_congr fun c hc => ?_).trans mapDomain_id
exact Function.invFunOn_eq (by simpa using hl hc)
#align finsupp.lmap_domain_supported Finsupp.lmapDomain_supported
theorem lmapDomain_disjoint_ker (f : α → α') {s : Set α}
(H : ∀ a ∈ s, ∀ b ∈ s, f a = f b → a = b) :
Disjoint (supported M R s) (ker (lmapDomain M R f)) := by
rw [disjoint_iff_inf_le]
rintro l ⟨h₁, h₂⟩
rw [SetLike.mem_coe, mem_ker, lmapDomain_apply, mapDomain] at h₂
simp; ext x
haveI := Classical.decPred fun x => x ∈ s
by_cases xs : x ∈ s
· have : Finsupp.sum l (fun a => Finsupp.single (f a)) (f x) = 0 := by
rw [h₂]
rfl
rw [Finsupp.sum_apply, Finsupp.sum_eq_single x, single_eq_same] at this
· simpa
· intro y hy xy
simp only [SetLike.mem_coe, mem_supported, subset_def, Finset.mem_coe, mem_support_iff] at h₁
simp [mt (H _ (h₁ _ hy) _ xs) xy]
· simp (config := { contextual := true })
· by_contra h
exact xs (h₁ <| Finsupp.mem_support_iff.2 h)
#align finsupp.lmap_domain_disjoint_ker Finsupp.lmapDomain_disjoint_ker
end LMapDomain
section LComapDomain
variable {β : Type*}
/-- Given `f : α → β` and a proof `hf` that `f` is injective, `lcomapDomain f hf` is the linear map
sending `l : β →₀ M` to the finitely supported function from `α` to `M` given by composing
`l` with `f`.
This is the linear version of `Finsupp.comapDomain`. -/
def lcomapDomain (f : α → β) (hf : Function.Injective f) : (β →₀ M) →ₗ[R] α →₀ M where
toFun l := Finsupp.comapDomain f l hf.injOn
map_add' x y := by ext; simp
map_smul' c x := by ext; simp
#align finsupp.lcomap_domain Finsupp.lcomapDomain
end LComapDomain
section Total
variable (α) (M) (R)
variable {α' : Type*} {M' : Type*} [AddCommMonoid M'] [Module R M'] (v : α → M) {v' : α' → M'}
/-- Interprets (l : α →₀ R) as linear combination of the elements in the family (v : α → M) and
evaluates this linear combination. -/
protected def total : (α →₀ R) →ₗ[R] M :=
Finsupp.lsum ℕ fun i => LinearMap.id.smulRight (v i)
#align finsupp.total Finsupp.total
variable {α M v}
theorem total_apply (l : α →₀ R) : Finsupp.total α M R v l = l.sum fun i a => a • v i :=
rfl
#align finsupp.total_apply Finsupp.total_apply
theorem total_apply_of_mem_supported {l : α →₀ R} {s : Finset α}
(hs : l ∈ supported R R (↑s : Set α)) : Finsupp.total α M R v l = s.sum fun i => l i • v i :=
Finset.sum_subset hs fun x _ hxg =>
show l x • v x = 0 by rw [not_mem_support_iff.1 hxg, zero_smul]
#align finsupp.total_apply_of_mem_supported Finsupp.total_apply_of_mem_supported
@[simp]
theorem total_single (c : R) (a : α) : Finsupp.total α M R v (single a c) = c • v a := by
simp [total_apply, sum_single_index]
#align finsupp.total_single Finsupp.total_single
theorem total_zero_apply (x : α →₀ R) : (Finsupp.total α M R 0) x = 0 := by
simp [Finsupp.total_apply]
#align finsupp.total_zero_apply Finsupp.total_zero_apply
variable (α M)
@[simp]
theorem total_zero : Finsupp.total α M R 0 = 0 :=
LinearMap.ext (total_zero_apply R)
#align finsupp.total_zero Finsupp.total_zero
variable {α M}
theorem apply_total (f : M →ₗ[R] M') (v) (l : α →₀ R) :
f (Finsupp.total α M R v l) = Finsupp.total α M' R (f ∘ v) l := by
apply Finsupp.induction_linear l <;> simp (config := { contextual := true })
#align finsupp.apply_total Finsupp.apply_total
theorem apply_total_id (f : M →ₗ[R] M') (l : M →₀ R) :
f (Finsupp.total M M R _root_.id l) = Finsupp.total M M' R f l :=
apply_total ..
theorem total_unique [Unique α] (l : α →₀ R) (v) :
Finsupp.total α M R v l = l default • v default := by rw [← total_single, ← unique_single l]
#align finsupp.total_unique Finsupp.total_unique
theorem total_surjective (h : Function.Surjective v) :
Function.Surjective (Finsupp.total α M R v) := by
intro x
obtain ⟨y, hy⟩ := h x
exact ⟨Finsupp.single y 1, by simp [hy]⟩
#align finsupp.total_surjective Finsupp.total_surjective
theorem total_range (h : Function.Surjective v) : LinearMap.range (Finsupp.total α M R v) = ⊤ :=
range_eq_top.2 <| total_surjective R h
#align finsupp.total_range Finsupp.total_range
/-- Any module is a quotient of a free module. This is stated as surjectivity of
`Finsupp.total M M R id : (M →₀ R) →ₗ[R] M`. -/
theorem total_id_surjective (M) [AddCommMonoid M] [Module R M] :
Function.Surjective (Finsupp.total M M R _root_.id) :=
total_surjective R Function.surjective_id
#align finsupp.total_id_surjective Finsupp.total_id_surjective
theorem range_total : LinearMap.range (Finsupp.total α M R v) = span R (range v) := by
ext x
constructor
· intro hx
rw [LinearMap.mem_range] at hx
rcases hx with ⟨l, hl⟩
rw [← hl]
rw [Finsupp.total_apply]
exact sum_mem fun i _ => Submodule.smul_mem _ _ (subset_span (mem_range_self i))
· apply span_le.2
intro x hx
rcases hx with ⟨i, hi⟩
rw [SetLike.mem_coe, LinearMap.mem_range]
use Finsupp.single i 1
simp [hi]
#align finsupp.range_total Finsupp.range_total
theorem lmapDomain_total (f : α → α') (g : M →ₗ[R] M') (h : ∀ i, g (v i) = v' (f i)) :
(Finsupp.total α' M' R v').comp (lmapDomain R R f) = g.comp (Finsupp.total α M R v) := by
ext l
simp [total_apply, Finsupp.sum_mapDomain_index, add_smul, h]
#align finsupp.lmap_domain_total Finsupp.lmapDomain_total
theorem total_comp_lmapDomain (f : α → α') :
(Finsupp.total α' M' R v').comp (Finsupp.lmapDomain R R f) = Finsupp.total α M' R (v' ∘ f) := by
ext
simp
#align finsupp.total_comp_lmap_domain Finsupp.total_comp_lmapDomain
@[simp]
theorem total_embDomain (f : α ↪ α') (l : α →₀ R) :
(Finsupp.total α' M' R v') (embDomain f l) = (Finsupp.total α M' R (v' ∘ f)) l := by
simp [total_apply, Finsupp.sum, support_embDomain, embDomain_apply]
#align finsupp.total_emb_domain Finsupp.total_embDomain
@[simp]
theorem total_mapDomain (f : α → α') (l : α →₀ R) :
(Finsupp.total α' M' R v') (mapDomain f l) = (Finsupp.total α M' R (v' ∘ f)) l :=
LinearMap.congr_fun (total_comp_lmapDomain _ _) l
#align finsupp.total_map_domain Finsupp.total_mapDomain
@[simp]
theorem total_equivMapDomain (f : α ≃ α') (l : α →₀ R) :
(Finsupp.total α' M' R v') (equivMapDomain f l) = (Finsupp.total α M' R (v' ∘ f)) l := by
rw [equivMapDomain_eq_mapDomain, total_mapDomain]
#align finsupp.total_equiv_map_domain Finsupp.total_equivMapDomain
/-- A version of `Finsupp.range_total` which is useful for going in the other direction -/
theorem span_eq_range_total (s : Set M) : span R s = LinearMap.range (Finsupp.total s M R (↑)) := by
rw [range_total, Subtype.range_coe_subtype, Set.setOf_mem_eq]
#align finsupp.span_eq_range_total Finsupp.span_eq_range_total
theorem mem_span_iff_total (s : Set M) (x : M) :
x ∈ span R s ↔ ∃ l : s →₀ R, Finsupp.total s M R (↑) l = x :=
(SetLike.ext_iff.1 <| span_eq_range_total _ _) x
#align finsupp.mem_span_iff_total Finsupp.mem_span_iff_total
variable {R}
theorem mem_span_range_iff_exists_finsupp {v : α → M} {x : M} :
x ∈ span R (range v) ↔ ∃ c : α →₀ R, (c.sum fun i a => a • v i) = x := by
simp only [← Finsupp.range_total, LinearMap.mem_range, Finsupp.total_apply]
#align finsupp.mem_span_range_iff_exists_finsupp Finsupp.mem_span_range_iff_exists_finsupp
variable (R)
theorem span_image_eq_map_total (s : Set α) :
span R (v '' s) = Submodule.map (Finsupp.total α M R v) (supported R R s) := by
apply span_eq_of_le
· intro x hx
rw [Set.mem_image] at hx
apply Exists.elim hx
intro i hi
exact ⟨_, Finsupp.single_mem_supported R 1 hi.1, by simp [hi.2]⟩
· refine map_le_iff_le_comap.2 fun z hz => ?_
have : ∀ i, z i • v i ∈ span R (v '' s) := by
intro c
haveI := Classical.decPred fun x => x ∈ s
by_cases h : c ∈ s
· exact smul_mem _ _ (subset_span (Set.mem_image_of_mem _ h))
· simp [(Finsupp.mem_supported' R _).1 hz _ h]
-- Porting note: `rw` is required to infer metavariables in `sum_mem`.
rw [mem_comap, total_apply]
refine sum_mem ?_
simp [this]
#align finsupp.span_image_eq_map_total Finsupp.span_image_eq_map_total
theorem mem_span_image_iff_total {s : Set α} {x : M} :
x ∈ span R (v '' s) ↔ ∃ l ∈ supported R R s, Finsupp.total α M R v l = x := by
rw [span_image_eq_map_total]
simp
#align finsupp.mem_span_image_iff_total Finsupp.mem_span_image_iff_total
theorem total_option (v : Option α → M) (f : Option α →₀ R) :
Finsupp.total (Option α) M R v f =
f none • v none + Finsupp.total α M R (v ∘ Option.some) f.some := by
rw [total_apply, sum_option_index_smul, total_apply]; simp
#align finsupp.total_option Finsupp.total_option
theorem total_total {α β : Type*} (A : α → M) (B : β → α →₀ R) (f : β →₀ R) :
Finsupp.total α M R A (Finsupp.total β (α →₀ R) R B f) =
Finsupp.total β M R (fun b => Finsupp.total α M R A (B b)) f := by
classical
simp only [total_apply]
apply induction_linear f
· simp only [sum_zero_index]
· intro f₁ f₂ h₁ h₂
simp [sum_add_index, h₁, h₂, add_smul]
· simp [sum_single_index, sum_smul_index, smul_sum, mul_smul]
#align finsupp.total_total Finsupp.total_total
@[simp]
theorem total_fin_zero (f : Fin 0 → M) : Finsupp.total (Fin 0) M R f = 0 := by
ext i
apply finZeroElim i
#align finsupp.total_fin_zero Finsupp.total_fin_zero
variable (α) (M) (v)
/-- `Finsupp.totalOn M v s` interprets `p : α →₀ R` as a linear combination of a
subset of the vectors in `v`, mapping it to the span of those vectors.
The subset is indicated by a set `s : Set α` of indices.
-/
protected def totalOn (s : Set α) : supported R R s →ₗ[R] span R (v '' s) :=
LinearMap.codRestrict _ ((Finsupp.total _ _ _ v).comp (Submodule.subtype (supported R R s)))
fun ⟨l, hl⟩ => (mem_span_image_iff_total _).2 ⟨l, hl, rfl⟩
#align finsupp.total_on Finsupp.totalOn
variable {α} {M} {v}
theorem totalOn_range (s : Set α) : LinearMap.range (Finsupp.totalOn α M R v s) = ⊤ := by
rw [Finsupp.totalOn, LinearMap.range_eq_map, LinearMap.map_codRestrict,
← LinearMap.range_le_iff_comap, range_subtype, Submodule.map_top, LinearMap.range_comp,
range_subtype]
exact (span_image_eq_map_total _ _).le
#align finsupp.total_on_range Finsupp.totalOn_range
theorem total_comp (f : α' → α) :
Finsupp.total α' M R (v ∘ f) = (Finsupp.total α M R v).comp (lmapDomain R R f) := by
ext
simp [total_apply]
#align finsupp.total_comp Finsupp.total_comp
| Mathlib/LinearAlgebra/Finsupp.lean | 867 | 870 | theorem total_comapDomain (f : α → α') (l : α' →₀ R) (hf : Set.InjOn f (f ⁻¹' ↑l.support)) :
Finsupp.total α M R v (Finsupp.comapDomain f l hf) =
(l.support.preimage f hf).sum fun i => l (f i) • v i := by |
rw [Finsupp.total_apply]; rfl
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn, Mario Carneiro, Martin Dvorak
-/
import Mathlib.Data.List.Basic
#align_import data.list.join from "leanprover-community/mathlib"@"18a5306c091183ac90884daa9373fa3b178e8607"
/-!
# Join of a list of lists
This file proves basic properties of `List.join`, which concatenates a list of lists. It is defined
in `Init.Data.List.Basic`.
-/
-- Make sure we don't import algebra
assert_not_exists Monoid
variable {α β : Type*}
namespace List
attribute [simp] join
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem join_singleton (l : List α) : [l].join = l := by rw [join, join, append_nil]
#align list.join_singleton List.join_singleton
@[simp]
theorem join_eq_nil : ∀ {L : List (List α)}, join L = [] ↔ ∀ l ∈ L, l = []
| [] => iff_of_true rfl (forall_mem_nil _)
| l :: L => by simp only [join, append_eq_nil, join_eq_nil, forall_mem_cons]
#align list.join_eq_nil List.join_eq_nil
@[simp]
theorem join_append (L₁ L₂ : List (List α)) : join (L₁ ++ L₂) = join L₁ ++ join L₂ := by
induction L₁
· rfl
· simp [*]
#align list.join_append List.join_append
theorem join_concat (L : List (List α)) (l : List α) : join (L.concat l) = join L ++ l := by simp
#align list.join_concat List.join_concat
@[simp]
theorem join_filter_not_isEmpty :
∀ {L : List (List α)}, join (L.filter fun l => !l.isEmpty) = L.join
| [] => rfl
| [] :: L => by
simp [join_filter_not_isEmpty (L := L), isEmpty_iff_eq_nil]
| (a :: l) :: L => by
simp [join_filter_not_isEmpty (L := L)]
#align list.join_filter_empty_eq_ff List.join_filter_not_isEmpty
@[deprecated (since := "2024-02-25")] alias join_filter_isEmpty_eq_false := join_filter_not_isEmpty
@[simp]
theorem join_filter_ne_nil [DecidablePred fun l : List α => l ≠ []] {L : List (List α)} :
join (L.filter fun l => l ≠ []) = L.join := by
simp [join_filter_not_isEmpty, ← isEmpty_iff_eq_nil]
#align list.join_filter_ne_nil List.join_filter_ne_nil
theorem join_join (l : List (List (List α))) : l.join.join = (l.map join).join := by
induction l <;> simp [*]
#align list.join_join List.join_join
/-- See `List.length_join` for the corresponding statement using `List.sum`. -/
lemma length_join' (L : List (List α)) : length (join L) = Nat.sum (map length L) := by
induction L <;> [rfl; simp only [*, join, map, Nat.sum_cons, length_append]]
/-- See `List.countP_join` for the corresponding statement using `List.sum`. -/
lemma countP_join' (p : α → Bool) :
∀ L : List (List α), countP p L.join = Nat.sum (L.map (countP p))
| [] => rfl
| a :: l => by rw [join, countP_append, map_cons, Nat.sum_cons, countP_join' _ l]
/-- See `List.count_join` for the corresponding statement using `List.sum`. -/
lemma count_join' [BEq α] (L : List (List α)) (a : α) :
L.join.count a = Nat.sum (L.map (count a)) := countP_join' _ _
/-- See `List.length_bind` for the corresponding statement using `List.sum`. -/
lemma length_bind' (l : List α) (f : α → List β) :
length (l.bind f) = Nat.sum (map (length ∘ f) l) := by rw [List.bind, length_join', map_map]
/-- See `List.countP_bind` for the corresponding statement using `List.sum`. -/
lemma countP_bind' (p : β → Bool) (l : List α) (f : α → List β) :
countP p (l.bind f) = Nat.sum (map (countP p ∘ f) l) := by rw [List.bind, countP_join', map_map]
/-- See `List.count_bind` for the corresponding statement using `List.sum`. -/
lemma count_bind' [BEq β] (l : List α) (f : α → List β) (x : β) :
count x (l.bind f) = Nat.sum (map (count x ∘ f) l) := countP_bind' _ _ _
@[simp]
theorem bind_eq_nil {l : List α} {f : α → List β} : List.bind l f = [] ↔ ∀ x ∈ l, f x = [] :=
join_eq_nil.trans <| by
simp only [mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂]
#align list.bind_eq_nil List.bind_eq_nil
/-- In a join, taking the first elements up to an index which is the sum of the lengths of the
first `i` sublists, is the same as taking the join of the first `i` sublists.
See `List.take_sum_join` for the corresponding statement using `List.sum`. -/
theorem take_sum_join' (L : List (List α)) (i : ℕ) :
L.join.take (Nat.sum ((L.map length).take i)) = (L.take i).join := by
induction L generalizing i
· simp
· cases i <;> simp [take_append, *]
/-- In a join, dropping all the elements up to an index which is the sum of the lengths of the
first `i` sublists, is the same as taking the join after dropping the first `i` sublists.
See `List.drop_sum_join` for the corresponding statement using `List.sum`. -/
| Mathlib/Data/List/Join.lean | 115 | 119 | theorem drop_sum_join' (L : List (List α)) (i : ℕ) :
L.join.drop (Nat.sum ((L.map length).take i)) = (L.drop i).join := by |
induction L generalizing i
· simp
· cases i <;> simp [drop_append, *]
|
/-
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.FieldTheory.Fixed
import Mathlib.FieldTheory.NormalClosure
import Mathlib.FieldTheory.PrimitiveElement
import Mathlib.GroupTheory.GroupAction.FixingSubgroup
#align_import field_theory.galois from "leanprover-community/mathlib"@"9fb8964792b4237dac6200193a0d533f1b3f7423"
/-!
# Galois Extensions
In this file we define Galois extensions as extensions which are both separable and normal.
## Main definitions
- `IsGalois F E` where `E` is an extension of `F`
- `fixedField H` where `H : Subgroup (E ≃ₐ[F] E)`
- `fixingSubgroup K` where `K : IntermediateField F E`
- `intermediateFieldEquivSubgroup` where `E/F` is finite dimensional and Galois
## Main results
- `IntermediateField.fixingSubgroup_fixedField` : If `E/F` is finite dimensional (but not
necessarily Galois) then `fixingSubgroup (fixedField H) = H`
- `IntermediateField.fixedField_fixingSubgroup`: If `E/F` is finite dimensional and Galois
then `fixedField (fixingSubgroup K) = K`
Together, these two results prove the Galois correspondence.
- `IsGalois.tfae` : Equivalent characterizations of a Galois extension of finite degree
-/
open scoped Polynomial IntermediateField
open FiniteDimensional AlgEquiv
section
variable (F : Type*) [Field F] (E : Type*) [Field E] [Algebra F E]
/-- A field extension E/F is Galois if it is both separable and normal. Note that in mathlib
a separable extension of fields is by definition algebraic. -/
class IsGalois : Prop where
[to_isSeparable : IsSeparable F E]
[to_normal : Normal F E]
#align is_galois IsGalois
variable {F E}
theorem isGalois_iff : IsGalois F E ↔ IsSeparable F E ∧ Normal F E :=
⟨fun h => ⟨h.1, h.2⟩, fun h =>
{ to_isSeparable := h.1
to_normal := h.2 }⟩
#align is_galois_iff isGalois_iff
attribute [instance 100] IsGalois.to_isSeparable IsGalois.to_normal
-- see Note [lower instance priority]
variable (F E)
namespace IsGalois
instance self : IsGalois F F :=
⟨⟩
#align is_galois.self IsGalois.self
variable {E}
theorem integral [IsGalois F E] (x : E) : IsIntegral F x :=
to_normal.isIntegral x
#align is_galois.integral IsGalois.integral
theorem separable [IsGalois F E] (x : E) : (minpoly F x).Separable :=
IsSeparable.separable F x
#align is_galois.separable IsGalois.separable
theorem splits [IsGalois F E] (x : E) : (minpoly F x).Splits (algebraMap F E) :=
Normal.splits' x
#align is_galois.splits IsGalois.splits
variable (E)
instance of_fixed_field (G : Type*) [Group G] [Finite G] [MulSemiringAction G E] :
IsGalois (FixedPoints.subfield G E) E :=
⟨⟩
#align is_galois.of_fixed_field IsGalois.of_fixed_field
theorem IntermediateField.AdjoinSimple.card_aut_eq_finrank [FiniteDimensional F E] {α : E}
(hα : IsIntegral F α) (h_sep : (minpoly F α).Separable)
(h_splits : (minpoly F α).Splits (algebraMap F F⟮α⟯)) :
Fintype.card (F⟮α⟯ ≃ₐ[F] F⟮α⟯) = finrank F F⟮α⟯ := by
letI : Fintype (F⟮α⟯ →ₐ[F] F⟮α⟯) := IntermediateField.fintypeOfAlgHomAdjoinIntegral F hα
rw [IntermediateField.adjoin.finrank hα]
rw [← IntermediateField.card_algHom_adjoin_integral F hα h_sep h_splits]
exact Fintype.card_congr (algEquivEquivAlgHom F F⟮α⟯)
#align is_galois.intermediate_field.adjoin_simple.card_aut_eq_finrank IsGalois.IntermediateField.AdjoinSimple.card_aut_eq_finrank
theorem card_aut_eq_finrank [FiniteDimensional F E] [IsGalois F E] :
Fintype.card (E ≃ₐ[F] E) = finrank F E := by
cases' Field.exists_primitive_element F E with α hα
let iso : F⟮α⟯ ≃ₐ[F] E :=
{ toFun := fun e => e.val
invFun := fun e => ⟨e, by rw [hα]; exact IntermediateField.mem_top⟩
left_inv := fun _ => by ext; rfl
right_inv := fun _ => rfl
map_mul' := fun _ _ => rfl
map_add' := fun _ _ => rfl
commutes' := fun _ => rfl }
have H : IsIntegral F α := IsGalois.integral F α
have h_sep : (minpoly F α).Separable := IsGalois.separable F α
have h_splits : (minpoly F α).Splits (algebraMap F E) := IsGalois.splits F α
replace h_splits : Polynomial.Splits (algebraMap F F⟮α⟯) (minpoly F α) := by
simpa using
Polynomial.splits_comp_of_splits (algebraMap F E) iso.symm.toAlgHom.toRingHom h_splits
rw [← LinearEquiv.finrank_eq iso.toLinearEquiv]
rw [← IntermediateField.AdjoinSimple.card_aut_eq_finrank F E H h_sep h_splits]
apply Fintype.card_congr
apply Equiv.mk (fun ϕ => iso.trans (ϕ.trans iso.symm)) fun ϕ => iso.symm.trans (ϕ.trans iso)
· intro ϕ; ext1; simp only [trans_apply, apply_symm_apply]
· intro ϕ; ext1; simp only [trans_apply, symm_apply_apply]
#align is_galois.card_aut_eq_finrank IsGalois.card_aut_eq_finrank
end IsGalois
end
section IsGaloisTower
variable (F K E : Type*) [Field F] [Field K] [Field E] {E' : Type*} [Field E'] [Algebra F E']
variable [Algebra F K] [Algebra F E] [Algebra K E] [IsScalarTower F K E]
theorem IsGalois.tower_top_of_isGalois [IsGalois F E] : IsGalois K E :=
{ to_isSeparable := isSeparable_tower_top_of_isSeparable F K E
to_normal := Normal.tower_top_of_normal F K E }
#align is_galois.tower_top_of_is_galois IsGalois.tower_top_of_isGalois
variable {F E}
-- see Note [lower instance priority]
instance (priority := 100) IsGalois.tower_top_intermediateField (K : IntermediateField F E)
[IsGalois F E] : IsGalois K E :=
IsGalois.tower_top_of_isGalois F K E
#align is_galois.tower_top_intermediate_field IsGalois.tower_top_intermediateField
theorem isGalois_iff_isGalois_bot : IsGalois (⊥ : IntermediateField F E) E ↔ IsGalois F E := by
constructor
· intro h
exact IsGalois.tower_top_of_isGalois (⊥ : IntermediateField F E) F E
· intro h; infer_instance
#align is_galois_iff_is_galois_bot isGalois_iff_isGalois_bot
theorem IsGalois.of_algEquiv [IsGalois F E] (f : E ≃ₐ[F] E') : IsGalois F E' :=
{ to_isSeparable := IsSeparable.of_algHom F E f.symm
to_normal := Normal.of_algEquiv f }
#align is_galois.of_alg_equiv IsGalois.of_algEquiv
theorem AlgEquiv.transfer_galois (f : E ≃ₐ[F] E') : IsGalois F E ↔ IsGalois F E' :=
⟨fun _ => IsGalois.of_algEquiv f, fun _ => IsGalois.of_algEquiv f.symm⟩
#align alg_equiv.transfer_galois AlgEquiv.transfer_galois
theorem isGalois_iff_isGalois_top : IsGalois F (⊤ : IntermediateField F E) ↔ IsGalois F E :=
(IntermediateField.topEquiv : (⊤ : IntermediateField F E) ≃ₐ[F] E).transfer_galois
#align is_galois_iff_is_galois_top isGalois_iff_isGalois_top
instance isGalois_bot : IsGalois F (⊥ : IntermediateField F E) :=
(IntermediateField.botEquiv F E).transfer_galois.mpr (IsGalois.self F)
#align is_galois_bot isGalois_bot
end IsGaloisTower
section GaloisCorrespondence
variable {F : Type*} [Field F] {E : Type*} [Field E] [Algebra F E]
variable (H : Subgroup (E ≃ₐ[F] E)) (K : IntermediateField F E)
/-- The intermediate field of fixed points fixed by a monoid action that commutes with the
`F`-action on `E`. -/
def FixedPoints.intermediateField (M : Type*) [Monoid M] [MulSemiringAction M E]
[SMulCommClass M F E] : IntermediateField F E :=
{ FixedPoints.subfield M E with
carrier := MulAction.fixedPoints M E
algebraMap_mem' := fun a g => smul_algebraMap g a }
#align fixed_points.intermediate_field FixedPoints.intermediateField
namespace IntermediateField
/-- The intermediate field fixed by a subgroup -/
def fixedField : IntermediateField F E :=
FixedPoints.intermediateField H
#align intermediate_field.fixed_field IntermediateField.fixedField
theorem finrank_fixedField_eq_card [FiniteDimensional F E] [DecidablePred (· ∈ H)] :
finrank (fixedField H) E = Fintype.card H :=
FixedPoints.finrank_eq_card H E
#align intermediate_field.finrank_fixed_field_eq_card IntermediateField.finrank_fixedField_eq_card
/-- The subgroup fixing an intermediate field -/
nonrec def fixingSubgroup : Subgroup (E ≃ₐ[F] E) :=
fixingSubgroup (E ≃ₐ[F] E) (K : Set E)
#align intermediate_field.fixing_subgroup IntermediateField.fixingSubgroup
theorem le_iff_le : K ≤ fixedField H ↔ H ≤ fixingSubgroup K :=
⟨fun h g hg x => h (Subtype.mem x) ⟨g, hg⟩, fun h x hx g => h (Subtype.mem g) ⟨x, hx⟩⟩
#align intermediate_field.le_iff_le IntermediateField.le_iff_le
/-- The fixing subgroup of `K : IntermediateField F E` is isomorphic to `E ≃ₐ[K] E` -/
def fixingSubgroupEquiv : fixingSubgroup K ≃* E ≃ₐ[K] E where
toFun ϕ := { AlgEquiv.toRingEquiv (ϕ : E ≃ₐ[F] E) with commutes' := ϕ.mem }
invFun ϕ := ⟨ϕ.restrictScalars _, ϕ.commutes⟩
left_inv _ := by ext; rfl
right_inv _ := by ext; rfl
map_mul' _ _ := by ext; rfl
#align intermediate_field.fixing_subgroup_equiv IntermediateField.fixingSubgroupEquiv
theorem fixingSubgroup_fixedField [FiniteDimensional F E] : fixingSubgroup (fixedField H) = H := by
have H_le : H ≤ fixingSubgroup (fixedField H) := (le_iff_le _ _).mp le_rfl
classical
suffices Fintype.card H = Fintype.card (fixingSubgroup (fixedField H)) by
exact SetLike.coe_injective (Set.eq_of_inclusion_surjective
((Fintype.bijective_iff_injective_and_card (Set.inclusion H_le)).mpr
⟨Set.inclusion_injective H_le, this⟩).2).symm
apply Fintype.card_congr
refine (FixedPoints.toAlgHomEquiv H E).trans ?_
refine (algEquivEquivAlgHom (fixedField H) E).toEquiv.symm.trans ?_
exact (fixingSubgroupEquiv (fixedField H)).toEquiv.symm
#align intermediate_field.fixing_subgroup_fixed_field IntermediateField.fixingSubgroup_fixedField
-- Porting note: added `fixedField.smul` for `fixedField.isScalarTower`
instance fixedField.smul : SMul K (fixedField (fixingSubgroup K)) where
smul x y := ⟨x * y, fun ϕ => by
rw [smul_mul', show ϕ • (x : E) = ↑x from ϕ.2 x, show ϕ • (y : E) = ↑y from y.2 ϕ]⟩
instance fixedField.algebra : Algebra K (fixedField (fixingSubgroup K)) where
toFun x := ⟨x, fun ϕ => Subtype.mem ϕ x⟩
map_zero' := rfl
map_add' _ _ := rfl
map_one' := rfl
map_mul' _ _ := rfl
commutes' _ _ := mul_comm _ _
smul_def' _ _ := rfl
#align intermediate_field.fixed_field.algebra IntermediateField.fixedField.algebra
instance fixedField.isScalarTower : IsScalarTower K (fixedField (fixingSubgroup K)) E :=
⟨fun _ _ _ => mul_assoc _ _ _⟩
#align intermediate_field.fixed_field.is_scalar_tower IntermediateField.fixedField.isScalarTower
end IntermediateField
namespace IsGalois
theorem fixedField_fixingSubgroup [FiniteDimensional F E] [h : IsGalois F E] :
IntermediateField.fixedField (IntermediateField.fixingSubgroup K) = K := by
have K_le : K ≤ IntermediateField.fixedField (IntermediateField.fixingSubgroup K) :=
(IntermediateField.le_iff_le _ _).mpr le_rfl
suffices
finrank K E = finrank (IntermediateField.fixedField (IntermediateField.fixingSubgroup K)) E by
exact (IntermediateField.eq_of_le_of_finrank_eq' K_le this).symm
classical
rw [IntermediateField.finrank_fixedField_eq_card,
Fintype.card_congr (IntermediateField.fixingSubgroupEquiv K).toEquiv]
exact (card_aut_eq_finrank K E).symm
#align is_galois.fixed_field_fixing_subgroup IsGalois.fixedField_fixingSubgroup
theorem card_fixingSubgroup_eq_finrank [DecidablePred (· ∈ IntermediateField.fixingSubgroup K)]
[FiniteDimensional F E] [IsGalois F E] :
Fintype.card (IntermediateField.fixingSubgroup K) = finrank K E := by
conv_rhs => rw [← fixedField_fixingSubgroup K, IntermediateField.finrank_fixedField_eq_card]
#align is_galois.card_fixing_subgroup_eq_finrank IsGalois.card_fixingSubgroup_eq_finrank
/-- The Galois correspondence from intermediate fields to subgroups -/
def intermediateFieldEquivSubgroup [FiniteDimensional F E] [IsGalois F E] :
IntermediateField F E ≃o (Subgroup (E ≃ₐ[F] E))ᵒᵈ where
toFun := IntermediateField.fixingSubgroup
invFun := IntermediateField.fixedField
left_inv K := fixedField_fixingSubgroup K
right_inv H := IntermediateField.fixingSubgroup_fixedField H
map_rel_iff' {K L} := by
rw [← fixedField_fixingSubgroup L, IntermediateField.le_iff_le, fixedField_fixingSubgroup L]
rfl
#align is_galois.intermediate_field_equiv_subgroup IsGalois.intermediateFieldEquivSubgroup
/-- The Galois correspondence as a `GaloisInsertion` -/
def galoisInsertionIntermediateFieldSubgroup [FiniteDimensional F E] :
GaloisInsertion (OrderDual.toDual ∘
(IntermediateField.fixingSubgroup : IntermediateField F E → Subgroup (E ≃ₐ[F] E)))
((IntermediateField.fixedField : Subgroup (E ≃ₐ[F] E) → IntermediateField F E) ∘
OrderDual.toDual) where
choice K _ := IntermediateField.fixingSubgroup K
gc K H := (IntermediateField.le_iff_le H K).symm
le_l_u H := le_of_eq (IntermediateField.fixingSubgroup_fixedField H).symm
choice_eq _ _ := rfl
#align is_galois.galois_insertion_intermediate_field_subgroup IsGalois.galoisInsertionIntermediateFieldSubgroup
/-- The Galois correspondence as a `GaloisCoinsertion` -/
def galoisCoinsertionIntermediateFieldSubgroup [FiniteDimensional F E] [IsGalois F E] :
GaloisCoinsertion (OrderDual.toDual ∘
(IntermediateField.fixingSubgroup : IntermediateField F E → Subgroup (E ≃ₐ[F] E)))
((IntermediateField.fixedField : Subgroup (E ≃ₐ[F] E) → IntermediateField F E) ∘
OrderDual.toDual) where
choice H _ := IntermediateField.fixedField H
gc K H := (IntermediateField.le_iff_le H K).symm
u_l_le K := le_of_eq (fixedField_fixingSubgroup K)
choice_eq _ _ := rfl
#align is_galois.galois_coinsertion_intermediate_field_subgroup IsGalois.galoisCoinsertionIntermediateFieldSubgroup
end IsGalois
end GaloisCorrespondence
section GaloisEquivalentDefinitions
variable (F : Type*) [Field F] (E : Type*) [Field E] [Algebra F E]
namespace IsGalois
theorem is_separable_splitting_field [FiniteDimensional F E] [IsGalois F E] :
∃ p : F[X], p.Separable ∧ p.IsSplittingField F E := by
cases' Field.exists_primitive_element F E with α h1
use minpoly F α, separable F α, IsGalois.splits F α
rw [eq_top_iff, ← IntermediateField.top_toSubalgebra, ← h1]
rw [IntermediateField.adjoin_simple_toSubalgebra_of_integral (integral F α)]
apply Algebra.adjoin_mono
rw [Set.singleton_subset_iff, Polynomial.mem_rootSet]
exact ⟨minpoly.ne_zero (integral F α), minpoly.aeval _ _⟩
#align is_galois.is_separable_splitting_field IsGalois.is_separable_splitting_field
theorem of_fixedField_eq_bot [FiniteDimensional F E]
(h : IntermediateField.fixedField (⊤ : Subgroup (E ≃ₐ[F] E)) = ⊥) : IsGalois F E := by
rw [← isGalois_iff_isGalois_bot, ← h]
classical exact IsGalois.of_fixed_field E (⊤ : Subgroup (E ≃ₐ[F] E))
#align is_galois.of_fixed_field_eq_bot IsGalois.of_fixedField_eq_bot
theorem of_card_aut_eq_finrank [FiniteDimensional F E]
(h : Fintype.card (E ≃ₐ[F] E) = finrank F E) : IsGalois F E := by
apply of_fixedField_eq_bot
have p : 0 < finrank (IntermediateField.fixedField (⊤ : Subgroup (E ≃ₐ[F] E))) E := finrank_pos
classical
rw [← IntermediateField.finrank_eq_one_iff, ← mul_left_inj' (ne_of_lt p).symm,
finrank_mul_finrank, ← h, one_mul, IntermediateField.finrank_fixedField_eq_card]
apply Fintype.card_congr
exact
{ toFun := fun g => ⟨g, Subgroup.mem_top g⟩
invFun := (↑)
left_inv := fun g => rfl
right_inv := fun _ => by ext; rfl }
#align is_galois.of_card_aut_eq_finrank IsGalois.of_card_aut_eq_finrank
variable {F} {E}
variable {p : F[X]}
theorem of_separable_splitting_field_aux [hFE : FiniteDimensional F E] [sp : p.IsSplittingField F E]
(hp : p.Separable) (K : Type*) [Field K] [Algebra F K] [Algebra K E] [IsScalarTower F K E]
{x : E} (hx : x ∈ p.aroots E)
-- these are both implied by `hFE`, but as they carry data this makes the lemma more general
[Fintype (K →ₐ[F] E)]
[Fintype (K⟮x⟯.restrictScalars F →ₐ[F] E)] :
Fintype.card (K⟮x⟯.restrictScalars F →ₐ[F] E) = Fintype.card (K →ₐ[F] E) * finrank K K⟮x⟯ := by
have h : IsIntegral K x := (isIntegral_of_noetherian (IsNoetherian.iff_fg.2 hFE) x).tower_top
have h1 : p ≠ 0 := fun hp => by
rw [hp, Polynomial.aroots_zero] at hx
exact Multiset.not_mem_zero x hx
have h2 : minpoly K x ∣ p.map (algebraMap F K) := by
apply minpoly.dvd
rw [Polynomial.aeval_def, Polynomial.eval₂_map, ← Polynomial.eval_map, ←
IsScalarTower.algebraMap_eq]
exact (Polynomial.mem_roots (Polynomial.map_ne_zero h1)).mp hx
let key_equiv : (K⟮x⟯.restrictScalars F →ₐ[F] E) ≃
Σ f : K →ₐ[F] E, @AlgHom K K⟮x⟯ E _ _ _ _ (RingHom.toAlgebra f) := by
change (K⟮x⟯ →ₐ[F] E) ≃ Σ f : K →ₐ[F] E, _
exact algHomEquivSigma
haveI : ∀ f : K →ₐ[F] E, Fintype (@AlgHom K K⟮x⟯ E _ _ _ _ (RingHom.toAlgebra f)) := fun f => by
have := Fintype.ofEquiv _ key_equiv
apply Fintype.ofInjective (Sigma.mk f) fun _ _ H => eq_of_heq (Sigma.ext_iff.mp H).2
rw [Fintype.card_congr key_equiv, Fintype.card_sigma, IntermediateField.adjoin.finrank h]
apply Finset.sum_const_nat
intro f _
rw [← @IntermediateField.card_algHom_adjoin_integral K _ E _ _ x E _ (RingHom.toAlgebra f) h]
· congr!
· exact Polynomial.Separable.of_dvd ((Polynomial.separable_map (algebraMap F K)).mpr hp) h2
· refine Polynomial.splits_of_splits_of_dvd _ (Polynomial.map_ne_zero h1) ?_ h2
-- Porting note: use unification instead of synthesis for one argument of `algebraMap_eq`
rw [Polynomial.splits_map_iff, ← @IsScalarTower.algebraMap_eq _ _ _ _ _ _ _ (_) _ _]
exact sp.splits
#align is_galois.of_separable_splitting_field_aux IsGalois.of_separable_splitting_field_aux
theorem of_separable_splitting_field [sp : p.IsSplittingField F E] (hp : p.Separable) :
IsGalois F E := by
haveI hFE : FiniteDimensional F E := Polynomial.IsSplittingField.finiteDimensional E p
letI := Classical.decEq E
let s := p.rootSet E
have adjoin_root : IntermediateField.adjoin F s = ⊤ := by
apply IntermediateField.toSubalgebra_injective
rw [IntermediateField.top_toSubalgebra, ← top_le_iff, ← sp.adjoin_rootSet]
apply IntermediateField.algebra_adjoin_le_adjoin
let P : IntermediateField F E → Prop := fun K => Fintype.card (K →ₐ[F] E) = finrank F K
suffices P (IntermediateField.adjoin F s) by
rw [adjoin_root] at this
apply of_card_aut_eq_finrank
rw [← Eq.trans this (LinearEquiv.finrank_eq IntermediateField.topEquiv.toLinearEquiv)]
exact Fintype.card_congr ((algEquivEquivAlgHom F E).toEquiv.trans
(IntermediateField.topEquiv.symm.arrowCongr AlgEquiv.refl))
apply IntermediateField.induction_on_adjoin_finset _ P
· have key := IntermediateField.card_algHom_adjoin_integral F (K := E)
(show IsIntegral F (0 : E) from isIntegral_zero)
rw [minpoly.zero, Polynomial.natDegree_X] at key
specialize key Polynomial.separable_X (Polynomial.splits_X (algebraMap F E))
rw [← @Subalgebra.finrank_bot F E _ _ _, ← IntermediateField.bot_toSubalgebra] at key
refine Eq.trans ?_ key
-- Porting note: use unification instead of synthesis for one argument of `card_congr`
apply @Fintype.card_congr _ _ _ (_) _
rw [IntermediateField.adjoin_zero]
intro K x hx hK
simp only [P] at *
-- Porting note: need to specify two implicit arguments of `finrank_mul_finrank`
letI := K⟮x⟯.module
letI := K⟮x⟯.isScalarTower (R := F)
rw [of_separable_splitting_field_aux hp K (Multiset.mem_toFinset.mp hx), hK, finrank_mul_finrank]
symm
refine LinearEquiv.finrank_eq ?_
rfl
#align is_galois.of_separable_splitting_field IsGalois.of_separable_splitting_field
/-- Equivalent characterizations of a Galois extension of finite degree-/
| Mathlib/FieldTheory/Galois.lean | 429 | 444 | theorem tfae [FiniteDimensional F E] :
List.TFAE [IsGalois F E, IntermediateField.fixedField (⊤ : Subgroup (E ≃ₐ[F] E)) = ⊥,
Fintype.card (E ≃ₐ[F] E) = finrank F E, ∃ p: F[X], p.Separable ∧ p.IsSplittingField F E] := by |
tfae_have 1 → 2
· exact fun h => OrderIso.map_bot (@intermediateFieldEquivSubgroup F _ E _ _ _ h).symm
tfae_have 1 → 3
· intro; exact card_aut_eq_finrank F E
tfae_have 1 → 4
· intro; exact is_separable_splitting_field F E
tfae_have 2 → 1
· exact of_fixedField_eq_bot F E
tfae_have 3 → 1
· exact of_card_aut_eq_finrank F E
tfae_have 4 → 1
· rintro ⟨h, hp1, _⟩; exact of_separable_splitting_field hp1
tfae_finish
|
/-
Copyright (c) 2021 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Measure.Typeclasses
import Mathlib.Analysis.Complex.Basic
#align_import measure_theory.measure.vector_measure from "leanprover-community/mathlib"@"70a4f2197832bceab57d7f41379b2592d1110570"
/-!
# Vector valued measures
This file defines vector valued measures, which are σ-additive functions from a set to an add monoid
`M` such that it maps the empty set and non-measurable sets to zero. In the case
that `M = ℝ`, we called the vector measure a signed measure and write `SignedMeasure α`.
Similarly, when `M = ℂ`, we call the measure a complex measure and write `ComplexMeasure α`.
## Main definitions
* `MeasureTheory.VectorMeasure` is a vector valued, σ-additive function that maps the empty
and non-measurable set to zero.
* `MeasureTheory.VectorMeasure.map` is the pushforward of a vector measure along a function.
* `MeasureTheory.VectorMeasure.restrict` is the restriction of a vector measure on some set.
## Notation
* `v ≤[i] w` means that the vector measure `v` restricted on the set `i` is less than or equal
to the vector measure `w` restricted on `i`, i.e. `v.restrict i ≤ w.restrict i`.
## Implementation notes
We require all non-measurable sets to be mapped to zero in order for the extensionality lemma
to only compare the underlying functions for measurable sets.
We use `HasSum` instead of `tsum` in the definition of vector measures in comparison to `Measure`
since this provides summability.
## Tags
vector measure, signed measure, complex measure
-/
noncomputable section
open scoped Classical
open NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β : Type*} {m : MeasurableSpace α}
/-- A vector measure on a measurable space `α` is a σ-additive `M`-valued function (for some `M`
an add monoid) such that the empty set and non-measurable sets are mapped to zero. -/
structure VectorMeasure (α : Type*) [MeasurableSpace α] (M : Type*) [AddCommMonoid M]
[TopologicalSpace M] where
measureOf' : Set α → M
empty' : measureOf' ∅ = 0
not_measurable' ⦃i : Set α⦄ : ¬MeasurableSet i → measureOf' i = 0
m_iUnion' ⦃f : ℕ → Set α⦄ : (∀ i, MeasurableSet (f i)) → Pairwise (Disjoint on f) →
HasSum (fun i => measureOf' (f i)) (measureOf' (⋃ i, f i))
#align measure_theory.vector_measure MeasureTheory.VectorMeasure
#align measure_theory.vector_measure.measure_of' MeasureTheory.VectorMeasure.measureOf'
#align measure_theory.vector_measure.empty' MeasureTheory.VectorMeasure.empty'
#align measure_theory.vector_measure.not_measurable' MeasureTheory.VectorMeasure.not_measurable'
#align measure_theory.vector_measure.m_Union' MeasureTheory.VectorMeasure.m_iUnion'
/-- A `SignedMeasure` is an `ℝ`-vector measure. -/
abbrev SignedMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℝ
#align measure_theory.signed_measure MeasureTheory.SignedMeasure
/-- A `ComplexMeasure` is a `ℂ`-vector measure. -/
abbrev ComplexMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℂ
#align measure_theory.complex_measure MeasureTheory.ComplexMeasure
open Set MeasureTheory
namespace VectorMeasure
section
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
attribute [coe] VectorMeasure.measureOf'
instance instCoeFun : CoeFun (VectorMeasure α M) fun _ => Set α → M :=
⟨VectorMeasure.measureOf'⟩
#align measure_theory.vector_measure.has_coe_to_fun MeasureTheory.VectorMeasure.instCoeFun
initialize_simps_projections VectorMeasure (measureOf' → apply)
#noalign measure_theory.vector_measure.measure_of_eq_coe
@[simp]
theorem empty (v : VectorMeasure α M) : v ∅ = 0 :=
v.empty'
#align measure_theory.vector_measure.empty MeasureTheory.VectorMeasure.empty
theorem not_measurable (v : VectorMeasure α M) {i : Set α} (hi : ¬MeasurableSet i) : v i = 0 :=
v.not_measurable' hi
#align measure_theory.vector_measure.not_measurable MeasureTheory.VectorMeasure.not_measurable
theorem m_iUnion (v : VectorMeasure α M) {f : ℕ → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) :=
v.m_iUnion' hf₁ hf₂
#align measure_theory.vector_measure.m_Union MeasureTheory.VectorMeasure.m_iUnion
theorem of_disjoint_iUnion_nat [T2Space M] (v : VectorMeasure α M) {f : ℕ → Set α}
(hf₁ : ∀ i, MeasurableSet (f i)) (hf₂ : Pairwise (Disjoint on f)) :
v (⋃ i, f i) = ∑' i, v (f i) :=
(v.m_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union_nat MeasureTheory.VectorMeasure.of_disjoint_iUnion_nat
theorem coe_injective : @Function.Injective (VectorMeasure α M) (Set α → M) (⇑) := fun v w h => by
cases v
cases w
congr
#align measure_theory.vector_measure.coe_injective MeasureTheory.VectorMeasure.coe_injective
theorem ext_iff' (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, v i = w i := by
rw [← coe_injective.eq_iff, Function.funext_iff]
#align measure_theory.vector_measure.ext_iff' MeasureTheory.VectorMeasure.ext_iff'
theorem ext_iff (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, MeasurableSet i → v i = w i := by
constructor
· rintro rfl _ _
rfl
· rw [ext_iff']
intro h i
by_cases hi : MeasurableSet i
· exact h i hi
· simp_rw [not_measurable _ hi]
#align measure_theory.vector_measure.ext_iff MeasureTheory.VectorMeasure.ext_iff
@[ext]
theorem ext {s t : VectorMeasure α M} (h : ∀ i : Set α, MeasurableSet i → s i = t i) : s = t :=
(ext_iff s t).2 h
#align measure_theory.vector_measure.ext MeasureTheory.VectorMeasure.ext
variable [T2Space M] {v : VectorMeasure α M} {f : ℕ → Set α}
theorem hasSum_of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) := by
cases nonempty_encodable β
set g := fun i : ℕ => ⋃ (b : β) (_ : b ∈ Encodable.decode₂ β i), f b with hg
have hg₁ : ∀ i, MeasurableSet (g i) :=
fun _ => MeasurableSet.iUnion fun b => MeasurableSet.iUnion fun _ => hf₁ b
have hg₂ : Pairwise (Disjoint on g) := Encodable.iUnion_decode₂_disjoint_on hf₂
have := v.of_disjoint_iUnion_nat hg₁ hg₂
rw [hg, Encodable.iUnion_decode₂] at this
have hg₃ : (fun i : β => v (f i)) = fun i => v (g (Encodable.encode i)) := by
ext x
rw [hg]
simp only
congr
ext y
simp only [exists_prop, Set.mem_iUnion, Option.mem_def]
constructor
· intro hy
exact ⟨x, (Encodable.decode₂_is_partial_inv _ _).2 rfl, hy⟩
· rintro ⟨b, hb₁, hb₂⟩
rw [Encodable.decode₂_is_partial_inv _ _] at hb₁
rwa [← Encodable.encode_injective hb₁]
rw [Summable.hasSum_iff, this, ← tsum_iUnion_decode₂]
· exact v.empty
· rw [hg₃]
change Summable ((fun i => v (g i)) ∘ Encodable.encode)
rw [Function.Injective.summable_iff Encodable.encode_injective]
· exact (v.m_iUnion hg₁ hg₂).summable
· intro x hx
convert v.empty
simp only [g, Set.iUnion_eq_empty, Option.mem_def, not_exists, Set.mem_range] at hx ⊢
intro i hi
exact False.elim ((hx i) ((Encodable.decode₂_is_partial_inv _ _).1 hi))
#align measure_theory.vector_measure.has_sum_of_disjoint_Union MeasureTheory.VectorMeasure.hasSum_of_disjoint_iUnion
theorem of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : v (⋃ i, f i) = ∑' i, v (f i) :=
(hasSum_of_disjoint_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union MeasureTheory.VectorMeasure.of_disjoint_iUnion
theorem of_union {A B : Set α} (h : Disjoint A B) (hA : MeasurableSet A) (hB : MeasurableSet B) :
v (A ∪ B) = v A + v B := by
rw [Set.union_eq_iUnion, of_disjoint_iUnion, tsum_fintype, Fintype.sum_bool, cond, cond]
exacts [fun b => Bool.casesOn b hB hA, pairwise_disjoint_on_bool.2 h]
#align measure_theory.vector_measure.of_union MeasureTheory.VectorMeasure.of_union
theorem of_add_of_diff {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B) (h : A ⊆ B) :
v A + v (B \ A) = v B := by
rw [← of_union (@Set.disjoint_sdiff_right _ A B) hA (hB.diff hA), Set.union_diff_cancel h]
#align measure_theory.vector_measure.of_add_of_diff MeasureTheory.VectorMeasure.of_add_of_diff
theorem of_diff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [T2Space M]
{v : VectorMeasure α M} {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h : A ⊆ B) : v (B \ A) = v B - v A := by
rw [← of_add_of_diff hA hB h, add_sub_cancel_left]
#align measure_theory.vector_measure.of_diff MeasureTheory.VectorMeasure.of_diff
theorem of_diff_of_diff_eq_zero {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h' : v (B \ A) = 0) : v (A \ B) + v B = v A := by
symm
calc
v A = v (A \ B ∪ A ∩ B) := by simp only [Set.diff_union_inter]
_ = v (A \ B) + v (A ∩ B) := by
rw [of_union]
· rw [disjoint_comm]
exact Set.disjoint_of_subset_left A.inter_subset_right disjoint_sdiff_self_right
· exact hA.diff hB
· exact hA.inter hB
_ = v (A \ B) + v (A ∩ B ∪ B \ A) := by
rw [of_union, h', add_zero]
· exact Set.disjoint_of_subset_left A.inter_subset_left disjoint_sdiff_self_right
· exact hA.inter hB
· exact hB.diff hA
_ = v (A \ B) + v B := by rw [Set.union_comm, Set.inter_comm, Set.diff_union_inter]
#align measure_theory.vector_measure.of_diff_of_diff_eq_zero MeasureTheory.VectorMeasure.of_diff_of_diff_eq_zero
theorem of_iUnion_nonneg {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, 0 ≤ v (f i)) : 0 ≤ v (⋃ i, f i) :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonneg hf₃
#align measure_theory.vector_measure.of_Union_nonneg MeasureTheory.VectorMeasure.of_iUnion_nonneg
theorem of_iUnion_nonpos {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, v (f i) ≤ 0) : v (⋃ i, f i) ≤ 0 :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonpos hf₃
#align measure_theory.vector_measure.of_Union_nonpos MeasureTheory.VectorMeasure.of_iUnion_nonpos
theorem of_nonneg_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : 0 ≤ s A) (hB₂ : 0 ≤ s B)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonneg_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonneg_disjoint_union_eq_zero
theorem of_nonpos_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : s A ≤ 0) (hB₂ : s B ≤ 0)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonpos_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonpos_disjoint_union_eq_zero
end
section SMul
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
/-- Given a real number `r` and a signed measure `s`, `smul r s` is the signed
measure corresponding to the function `r • s`. -/
def smul (r : R) (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := r • ⇑v
empty' := by rw [Pi.smul_apply, empty, smul_zero]
not_measurable' _ hi := by rw [Pi.smul_apply, v.not_measurable hi, smul_zero]
m_iUnion' _ hf₁ hf₂ := by exact HasSum.const_smul _ (v.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.smul MeasureTheory.VectorMeasure.smul
instance instSMul : SMul R (VectorMeasure α M) :=
⟨smul⟩
#align measure_theory.vector_measure.has_smul MeasureTheory.VectorMeasure.instSMul
@[simp]
theorem coe_smul (r : R) (v : VectorMeasure α M) : ⇑(r • v) = r • ⇑v := rfl
#align measure_theory.vector_measure.coe_smul MeasureTheory.VectorMeasure.coe_smul
theorem smul_apply (r : R) (v : VectorMeasure α M) (i : Set α) : (r • v) i = r • v i := rfl
#align measure_theory.vector_measure.smul_apply MeasureTheory.VectorMeasure.smul_apply
end SMul
section AddCommMonoid
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
instance instZero : Zero (VectorMeasure α M) :=
⟨⟨0, rfl, fun _ _ => rfl, fun _ _ _ => hasSum_zero⟩⟩
#align measure_theory.vector_measure.has_zero MeasureTheory.VectorMeasure.instZero
instance instInhabited : Inhabited (VectorMeasure α M) :=
⟨0⟩
#align measure_theory.vector_measure.inhabited MeasureTheory.VectorMeasure.instInhabited
@[simp]
theorem coe_zero : ⇑(0 : VectorMeasure α M) = 0 := rfl
#align measure_theory.vector_measure.coe_zero MeasureTheory.VectorMeasure.coe_zero
theorem zero_apply (i : Set α) : (0 : VectorMeasure α M) i = 0 := rfl
#align measure_theory.vector_measure.zero_apply MeasureTheory.VectorMeasure.zero_apply
variable [ContinuousAdd M]
/-- The sum of two vector measure is a vector measure. -/
def add (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v + w
empty' := by simp
not_measurable' _ hi := by rw [Pi.add_apply, v.not_measurable hi, w.not_measurable hi, add_zero]
m_iUnion' f hf₁ hf₂ := HasSum.add (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.add MeasureTheory.VectorMeasure.add
instance instAdd : Add (VectorMeasure α M) :=
⟨add⟩
#align measure_theory.vector_measure.has_add MeasureTheory.VectorMeasure.instAdd
@[simp]
theorem coe_add (v w : VectorMeasure α M) : ⇑(v + w) = v + w := rfl
#align measure_theory.vector_measure.coe_add MeasureTheory.VectorMeasure.coe_add
theorem add_apply (v w : VectorMeasure α M) (i : Set α) : (v + w) i = v i + w i := rfl
#align measure_theory.vector_measure.add_apply MeasureTheory.VectorMeasure.add_apply
instance instAddCommMonoid : AddCommMonoid (VectorMeasure α M) :=
Function.Injective.addCommMonoid _ coe_injective coe_zero coe_add fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_monoid MeasureTheory.VectorMeasure.instAddCommMonoid
/-- `(⇑)` is an `AddMonoidHom`. -/
@[simps]
def coeFnAddMonoidHom : VectorMeasure α M →+ Set α → M where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
#align measure_theory.vector_measure.coe_fn_add_monoid_hom MeasureTheory.VectorMeasure.coeFnAddMonoidHom
end AddCommMonoid
section AddCommGroup
variable {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
/-- The negative of a vector measure is a vector measure. -/
def neg (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := -v
empty' := by simp
not_measurable' _ hi := by rw [Pi.neg_apply, neg_eq_zero, v.not_measurable hi]
m_iUnion' f hf₁ hf₂ := HasSum.neg <| v.m_iUnion hf₁ hf₂
#align measure_theory.vector_measure.neg MeasureTheory.VectorMeasure.neg
instance instNeg : Neg (VectorMeasure α M) :=
⟨neg⟩
#align measure_theory.vector_measure.has_neg MeasureTheory.VectorMeasure.instNeg
@[simp]
theorem coe_neg (v : VectorMeasure α M) : ⇑(-v) = -v := rfl
#align measure_theory.vector_measure.coe_neg MeasureTheory.VectorMeasure.coe_neg
theorem neg_apply (v : VectorMeasure α M) (i : Set α) : (-v) i = -v i := rfl
#align measure_theory.vector_measure.neg_apply MeasureTheory.VectorMeasure.neg_apply
/-- The difference of two vector measure is a vector measure. -/
def sub (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v - w
empty' := by simp
not_measurable' _ hi := by rw [Pi.sub_apply, v.not_measurable hi, w.not_measurable hi, sub_zero]
m_iUnion' f hf₁ hf₂ := HasSum.sub (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.sub MeasureTheory.VectorMeasure.sub
instance instSub : Sub (VectorMeasure α M) :=
⟨sub⟩
#align measure_theory.vector_measure.has_sub MeasureTheory.VectorMeasure.instSub
@[simp]
theorem coe_sub (v w : VectorMeasure α M) : ⇑(v - w) = v - w := rfl
#align measure_theory.vector_measure.coe_sub MeasureTheory.VectorMeasure.coe_sub
theorem sub_apply (v w : VectorMeasure α M) (i : Set α) : (v - w) i = v i - w i := rfl
#align measure_theory.vector_measure.sub_apply MeasureTheory.VectorMeasure.sub_apply
instance instAddCommGroup : AddCommGroup (VectorMeasure α M) :=
Function.Injective.addCommGroup _ coe_injective coe_zero coe_add coe_neg coe_sub
(fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_group MeasureTheory.VectorMeasure.instAddCommGroup
end AddCommGroup
section DistribMulAction
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
instance instDistribMulAction [ContinuousAdd M] : DistribMulAction R (VectorMeasure α M) :=
Function.Injective.distribMulAction coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.distrib_mul_action MeasureTheory.VectorMeasure.instDistribMulAction
end DistribMulAction
section Module
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M]
instance instModule [ContinuousAdd M] : Module R (VectorMeasure α M) :=
Function.Injective.module R coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.module MeasureTheory.VectorMeasure.instModule
end Module
end VectorMeasure
namespace Measure
/-- A finite measure coerced into a real function is a signed measure. -/
@[simps]
def toSignedMeasure (μ : Measure α) [hμ : IsFiniteMeasure μ] : SignedMeasure α where
measureOf' := fun s : Set α => if MeasurableSet s then (μ s).toReal else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' f hf₁ hf₂ := by
simp only [*, MeasurableSet.iUnion hf₁, if_true, measure_iUnion hf₂ hf₁]
rw [ENNReal.tsum_toReal_eq]
exacts [(summable_measure_toReal hf₁ hf₂).hasSum, fun _ ↦ measure_ne_top _ _]
#align measure_theory.measure.to_signed_measure MeasureTheory.Measure.toSignedMeasure
theorem toSignedMeasure_apply_measurable {μ : Measure α} [IsFiniteMeasure μ] {i : Set α}
(hi : MeasurableSet i) : μ.toSignedMeasure i = (μ i).toReal :=
if_pos hi
#align measure_theory.measure.to_signed_measure_apply_measurable MeasureTheory.Measure.toSignedMeasure_apply_measurable
-- Without this lemma, `singularPart_neg` in `MeasureTheory.Decomposition.Lebesgue` is
-- extremely slow
theorem toSignedMeasure_congr {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
(h : μ = ν) : μ.toSignedMeasure = ν.toSignedMeasure := by
congr
#align measure_theory.measure.to_signed_measure_congr MeasureTheory.Measure.toSignedMeasure_congr
theorem toSignedMeasure_eq_toSignedMeasure_iff {μ ν : Measure α} [IsFiniteMeasure μ]
[IsFiniteMeasure ν] : μ.toSignedMeasure = ν.toSignedMeasure ↔ μ = ν := by
refine ⟨fun h => ?_, fun h => ?_⟩
· ext1 i hi
have : μ.toSignedMeasure i = ν.toSignedMeasure i := by rw [h]
rwa [toSignedMeasure_apply_measurable hi, toSignedMeasure_apply_measurable hi,
ENNReal.toReal_eq_toReal] at this
<;> exact measure_ne_top _ _
· congr
#align measure_theory.measure.to_signed_measure_eq_to_signed_measure_iff MeasureTheory.Measure.toSignedMeasure_eq_toSignedMeasure_iff
@[simp]
theorem toSignedMeasure_zero : (0 : Measure α).toSignedMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_signed_measure_zero MeasureTheory.Measure.toSignedMeasure_zero
@[simp]
theorem toSignedMeasure_add (μ ν : Measure α) [IsFiniteMeasure μ] [IsFiniteMeasure ν] :
(μ + ν).toSignedMeasure = μ.toSignedMeasure + ν.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, add_apply,
ENNReal.toReal_add (ne_of_lt (measure_lt_top _ _)) (ne_of_lt (measure_lt_top _ _)),
VectorMeasure.add_apply, toSignedMeasure_apply_measurable hi,
toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_add MeasureTheory.Measure.toSignedMeasure_add
@[simp]
theorem toSignedMeasure_smul (μ : Measure α) [IsFiniteMeasure μ] (r : ℝ≥0) :
(r • μ).toSignedMeasure = r • μ.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, VectorMeasure.smul_apply,
toSignedMeasure_apply_measurable hi, coe_smul, Pi.smul_apply, ENNReal.toReal_smul]
#align measure_theory.measure.to_signed_measure_smul MeasureTheory.Measure.toSignedMeasure_smul
/-- A measure is a vector measure over `ℝ≥0∞`. -/
@[simps]
def toENNRealVectorMeasure (μ : Measure α) : VectorMeasure α ℝ≥0∞ where
measureOf' := fun i : Set α => if MeasurableSet i then μ i else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' _ hf₁ hf₂ := by
simp only
rw [Summable.hasSum_iff ENNReal.summable, if_pos (MeasurableSet.iUnion hf₁),
MeasureTheory.measure_iUnion hf₂ hf₁]
exact tsum_congr fun n => if_pos (hf₁ n)
#align measure_theory.measure.to_ennreal_vector_measure MeasureTheory.Measure.toENNRealVectorMeasure
theorem toENNRealVectorMeasure_apply_measurable {μ : Measure α} {i : Set α} (hi : MeasurableSet i) :
μ.toENNRealVectorMeasure i = μ i :=
if_pos hi
#align measure_theory.measure.to_ennreal_vector_measure_apply_measurable MeasureTheory.Measure.toENNRealVectorMeasure_apply_measurable
@[simp]
theorem toENNRealVectorMeasure_zero : (0 : Measure α).toENNRealVectorMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_ennreal_vector_measure_zero MeasureTheory.Measure.toENNRealVectorMeasure_zero
@[simp]
theorem toENNRealVectorMeasure_add (μ ν : Measure α) :
(μ + ν).toENNRealVectorMeasure = μ.toENNRealVectorMeasure + ν.toENNRealVectorMeasure := by
refine MeasureTheory.VectorMeasure.ext fun i hi => ?_
rw [toENNRealVectorMeasure_apply_measurable hi, add_apply, VectorMeasure.add_apply,
toENNRealVectorMeasure_apply_measurable hi, toENNRealVectorMeasure_apply_measurable hi]
#align measure_theory.measure.to_ennreal_vector_measure_add MeasureTheory.Measure.toENNRealVectorMeasure_add
theorem toSignedMeasure_sub_apply {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
{i : Set α} (hi : MeasurableSet i) :
(μ.toSignedMeasure - ν.toSignedMeasure) i = (μ i).toReal - (ν i).toReal := by
rw [VectorMeasure.sub_apply, toSignedMeasure_apply_measurable hi,
Measure.toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_sub_apply MeasureTheory.Measure.toSignedMeasure_sub_apply
end Measure
namespace VectorMeasure
open Measure
section
/-- A vector measure over `ℝ≥0∞` is a measure. -/
def ennrealToMeasure {_ : MeasurableSpace α} (v : VectorMeasure α ℝ≥0∞) : Measure α :=
ofMeasurable (fun s _ => v s) v.empty fun _ hf₁ hf₂ => v.of_disjoint_iUnion_nat hf₁ hf₂
#align measure_theory.vector_measure.ennreal_to_measure MeasureTheory.VectorMeasure.ennrealToMeasure
theorem ennrealToMeasure_apply {m : MeasurableSpace α} {v : VectorMeasure α ℝ≥0∞} {s : Set α}
(hs : MeasurableSet s) : ennrealToMeasure v s = v s := by
rw [ennrealToMeasure, ofMeasurable_apply _ hs]
#align measure_theory.vector_measure.ennreal_to_measure_apply MeasureTheory.VectorMeasure.ennrealToMeasure_apply
@[simp]
theorem _root_.MeasureTheory.Measure.toENNRealVectorMeasure_ennrealToMeasure
(μ : VectorMeasure α ℝ≥0∞) :
toENNRealVectorMeasure (ennrealToMeasure μ) = μ := ext fun s hs => by
rw [toENNRealVectorMeasure_apply_measurable hs, ennrealToMeasure_apply hs]
@[simp]
theorem ennrealToMeasure_toENNRealVectorMeasure (μ : Measure α) :
ennrealToMeasure (toENNRealVectorMeasure μ) = μ := Measure.ext fun s hs => by
rw [ennrealToMeasure_apply hs, toENNRealVectorMeasure_apply_measurable hs]
/-- The equiv between `VectorMeasure α ℝ≥0∞` and `Measure α` formed by
`MeasureTheory.VectorMeasure.ennrealToMeasure` and
`MeasureTheory.Measure.toENNRealVectorMeasure`. -/
@[simps]
def equivMeasure [MeasurableSpace α] : VectorMeasure α ℝ≥0∞ ≃ Measure α where
toFun := ennrealToMeasure
invFun := toENNRealVectorMeasure
left_inv := toENNRealVectorMeasure_ennrealToMeasure
right_inv := ennrealToMeasure_toENNRealVectorMeasure
#align measure_theory.vector_measure.equiv_measure MeasureTheory.VectorMeasure.equivMeasure
end
section
variable [MeasurableSpace α] [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable (v : VectorMeasure α M)
/-- The pushforward of a vector measure along a function. -/
def map (v : VectorMeasure α M) (f : α → β) : VectorMeasure β M :=
if hf : Measurable f then
{ measureOf' := fun s => if MeasurableSet s then v (f ⁻¹' s) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro g hg₁ hg₂
simp only
convert v.m_iUnion (fun i => hf (hg₁ i)) fun i j hij => (hg₂ hij).preimage _
· rw [if_pos (hg₁ _)]
· rw [Set.preimage_iUnion, if_pos (MeasurableSet.iUnion hg₁)] }
else 0
#align measure_theory.vector_measure.map MeasureTheory.VectorMeasure.map
theorem map_not_measurable {f : α → β} (hf : ¬Measurable f) : v.map f = 0 :=
dif_neg hf
#align measure_theory.vector_measure.map_not_measurable MeasureTheory.VectorMeasure.map_not_measurable
theorem map_apply {f : α → β} (hf : Measurable f) {s : Set β} (hs : MeasurableSet s) :
v.map f s = v (f ⁻¹' s) := by
rw [map, dif_pos hf]
exact if_pos hs
#align measure_theory.vector_measure.map_apply MeasureTheory.VectorMeasure.map_apply
@[simp]
theorem map_id : v.map id = v :=
ext fun i hi => by rw [map_apply v measurable_id hi, Set.preimage_id]
#align measure_theory.vector_measure.map_id MeasureTheory.VectorMeasure.map_id
@[simp]
theorem map_zero (f : α → β) : (0 : VectorMeasure α M).map f = 0 := by
by_cases hf : Measurable f
· ext i hi
rw [map_apply _ hf hi, zero_apply, zero_apply]
· exact dif_neg hf
#align measure_theory.vector_measure.map_zero MeasureTheory.VectorMeasure.map_zero
section
variable {N : Type*} [AddCommMonoid N] [TopologicalSpace N]
/-- Given a vector measure `v` on `M` and a continuous `AddMonoidHom` `f : M → N`, `f ∘ v` is a
vector measure on `N`. -/
def mapRange (v : VectorMeasure α M) (f : M →+ N) (hf : Continuous f) : VectorMeasure α N where
measureOf' s := f (v s)
empty' := by simp only; rw [empty, AddMonoidHom.map_zero]
not_measurable' i hi := by simp only; rw [not_measurable v hi, AddMonoidHom.map_zero]
m_iUnion' g hg₁ hg₂ := HasSum.map (v.m_iUnion hg₁ hg₂) f hf
#align measure_theory.vector_measure.map_range MeasureTheory.VectorMeasure.mapRange
@[simp]
theorem mapRange_apply {f : M →+ N} (hf : Continuous f) {s : Set α} : v.mapRange f hf s = f (v s) :=
rfl
#align measure_theory.vector_measure.map_range_apply MeasureTheory.VectorMeasure.mapRange_apply
@[simp]
theorem mapRange_id : v.mapRange (AddMonoidHom.id M) continuous_id = v := by
ext
rfl
#align measure_theory.vector_measure.map_range_id MeasureTheory.VectorMeasure.mapRange_id
@[simp]
theorem mapRange_zero {f : M →+ N} (hf : Continuous f) :
mapRange (0 : VectorMeasure α M) f hf = 0 := by
ext
simp
#align measure_theory.vector_measure.map_range_zero MeasureTheory.VectorMeasure.mapRange_zero
section ContinuousAdd
variable [ContinuousAdd M] [ContinuousAdd N]
@[simp]
theorem mapRange_add {v w : VectorMeasure α M} {f : M →+ N} (hf : Continuous f) :
(v + w).mapRange f hf = v.mapRange f hf + w.mapRange f hf := by
ext
simp
#align measure_theory.vector_measure.map_range_add MeasureTheory.VectorMeasure.mapRange_add
/-- Given a continuous `AddMonoidHom` `f : M → N`, `mapRangeHom` is the `AddMonoidHom` mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeHom (f : M →+ N) (hf : Continuous f) : VectorMeasure α M →+ VectorMeasure α N where
toFun v := v.mapRange f hf
map_zero' := mapRange_zero hf
map_add' _ _ := mapRange_add hf
#align measure_theory.vector_measure.map_range_hom MeasureTheory.VectorMeasure.mapRangeHom
end ContinuousAdd
section Module
variable {R : Type*} [Semiring R] [Module R M] [Module R N]
variable [ContinuousAdd M] [ContinuousAdd N] [ContinuousConstSMul R M] [ContinuousConstSMul R N]
/-- Given a continuous linear map `f : M → N`, `mapRangeₗ` is the linear map mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeₗ (f : M →ₗ[R] N) (hf : Continuous f) : VectorMeasure α M →ₗ[R] VectorMeasure α N where
toFun v := v.mapRange f.toAddMonoidHom hf
map_add' _ _ := mapRange_add hf
map_smul' := by
intros
ext
simp
#align measure_theory.vector_measure.map_rangeₗ MeasureTheory.VectorMeasure.mapRangeₗ
end Module
end
/-- The restriction of a vector measure on some set. -/
def restrict (v : VectorMeasure α M) (i : Set α) : VectorMeasure α M :=
if hi : MeasurableSet i then
{ measureOf' := fun s => if MeasurableSet s then v (s ∩ i) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro f hf₁ hf₂
simp only
convert v.m_iUnion (fun n => (hf₁ n).inter hi)
(hf₂.mono fun i j => Disjoint.mono inf_le_left inf_le_left)
· rw [if_pos (hf₁ _)]
· rw [Set.iUnion_inter, if_pos (MeasurableSet.iUnion hf₁)] }
else 0
#align measure_theory.vector_measure.restrict MeasureTheory.VectorMeasure.restrict
theorem restrict_not_measurable {i : Set α} (hi : ¬MeasurableSet i) : v.restrict i = 0 :=
dif_neg hi
#align measure_theory.vector_measure.restrict_not_measurable MeasureTheory.VectorMeasure.restrict_not_measurable
theorem restrict_apply {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j) :
v.restrict i j = v (j ∩ i) := by
rw [restrict, dif_pos hi]
exact if_pos hj
#align measure_theory.vector_measure.restrict_apply MeasureTheory.VectorMeasure.restrict_apply
theorem restrict_eq_self {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j)
(hij : j ⊆ i) : v.restrict i j = v j := by
rw [restrict_apply v hi hj, Set.inter_eq_left.2 hij]
#align measure_theory.vector_measure.restrict_eq_self MeasureTheory.VectorMeasure.restrict_eq_self
@[simp]
theorem restrict_empty : v.restrict ∅ = 0 :=
ext fun i hi => by
rw [restrict_apply v MeasurableSet.empty hi, Set.inter_empty, v.empty, zero_apply]
#align measure_theory.vector_measure.restrict_empty MeasureTheory.VectorMeasure.restrict_empty
@[simp]
theorem restrict_univ : v.restrict Set.univ = v :=
ext fun i hi => by rw [restrict_apply v MeasurableSet.univ hi, Set.inter_univ]
#align measure_theory.vector_measure.restrict_univ MeasureTheory.VectorMeasure.restrict_univ
@[simp]
theorem restrict_zero {i : Set α} : (0 : VectorMeasure α M).restrict i = 0 := by
by_cases hi : MeasurableSet i
· ext j hj
rw [restrict_apply 0 hi hj, zero_apply, zero_apply]
· exact dif_neg hi
#align measure_theory.vector_measure.restrict_zero MeasureTheory.VectorMeasure.restrict_zero
section ContinuousAdd
variable [ContinuousAdd M]
theorem map_add (v w : VectorMeasure α M) (f : α → β) : (v + w).map f = v.map f + w.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp [map, dif_neg hf]
#align measure_theory.vector_measure.map_add MeasureTheory.VectorMeasure.map_add
/-- `VectorMeasure.map` as an additive monoid homomorphism. -/
@[simps]
def mapGm (f : α → β) : VectorMeasure α M →+ VectorMeasure β M where
toFun v := v.map f
map_zero' := map_zero f
map_add' _ _ := map_add _ _ f
#align measure_theory.vector_measure.map_gm MeasureTheory.VectorMeasure.mapGm
theorem restrict_add (v w : VectorMeasure α M) (i : Set α) :
(v + w).restrict i = v.restrict i + w.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp [restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_add MeasureTheory.VectorMeasure.restrict_add
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictGm (i : Set α) : VectorMeasure α M →+ VectorMeasure α M where
toFun v := v.restrict i
map_zero' := restrict_zero
map_add' _ _ := restrict_add _ _ i
#align measure_theory.vector_measure.restrict_gm MeasureTheory.VectorMeasure.restrictGm
end ContinuousAdd
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
@[simp]
theorem map_smul {v : VectorMeasure α M} {f : α → β} (c : R) : (c • v).map f = c • v.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp only [map, dif_neg hf]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext i
simp
#align measure_theory.vector_measure.map_smul MeasureTheory.VectorMeasure.map_smul
@[simp]
theorem restrict_smul {v : VectorMeasure α M} {i : Set α} (c : R) :
(c • v).restrict i = c • v.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp only [restrict_not_measurable _ hi]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext j
simp
#align measure_theory.vector_measure.restrict_smul MeasureTheory.VectorMeasure.restrict_smul
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M] [ContinuousAdd M]
/-- `VectorMeasure.map` as a linear map. -/
@[simps]
def mapₗ (f : α → β) : VectorMeasure α M →ₗ[R] VectorMeasure β M where
toFun v := v.map f
map_add' _ _ := map_add _ _ f
map_smul' _ _ := map_smul _
#align measure_theory.vector_measure.mapₗ MeasureTheory.VectorMeasure.mapₗ
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictₗ (i : Set α) : VectorMeasure α M →ₗ[R] VectorMeasure α M where
toFun v := v.restrict i
map_add' _ _ := restrict_add _ _ i
map_smul' _ _ := restrict_smul _
#align measure_theory.vector_measure.restrictₗ MeasureTheory.VectorMeasure.restrictₗ
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
/-- Vector measures over a partially ordered monoid is partially ordered.
This definition is consistent with `Measure.instPartialOrder`. -/
instance instPartialOrder : PartialOrder (VectorMeasure α M) where
le v w := ∀ i, MeasurableSet i → v i ≤ w i
le_refl v i _ := le_rfl
le_trans u v w h₁ h₂ i hi := le_trans (h₁ i hi) (h₂ i hi)
le_antisymm v w h₁ h₂ := ext fun i hi => le_antisymm (h₁ i hi) (h₂ i hi)
variable {u v w : VectorMeasure α M}
theorem le_iff : v ≤ w ↔ ∀ i, MeasurableSet i → v i ≤ w i := Iff.rfl
#align measure_theory.vector_measure.le_iff MeasureTheory.VectorMeasure.le_iff
theorem le_iff' : v ≤ w ↔ ∀ i, v i ≤ w i := by
refine ⟨fun h i => ?_, fun h i _ => h i⟩
by_cases hi : MeasurableSet i
· exact h i hi
· rw [v.not_measurable hi, w.not_measurable hi]
#align measure_theory.vector_measure.le_iff' MeasureTheory.VectorMeasure.le_iff'
end
set_option quotPrecheck false in -- Porting note: error message suggested to do this
scoped[MeasureTheory]
notation:50 v " ≤[" i:50 "] " w:50 =>
MeasureTheory.VectorMeasure.restrict v i ≤ MeasureTheory.VectorMeasure.restrict w i
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
variable (v w : VectorMeasure α M)
theorem restrict_le_restrict_iff {i : Set α} (hi : MeasurableSet i) :
v ≤[i] w ↔ ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j :=
⟨fun h j hj₁ hj₂ => restrict_eq_self v hi hj₁ hj₂ ▸ restrict_eq_self w hi hj₁ hj₂ ▸ h j hj₁,
fun h => le_iff.1 fun _ hj =>
(restrict_apply v hi hj).symm ▸ (restrict_apply w hi hj).symm ▸
h (hj.inter hi) Set.inter_subset_right⟩
#align measure_theory.vector_measure.restrict_le_restrict_iff MeasureTheory.VectorMeasure.restrict_le_restrict_iff
theorem subset_le_of_restrict_le_restrict {i : Set α} (hi : MeasurableSet i) (hi₂ : v ≤[i] w)
{j : Set α} (hj : j ⊆ i) : v j ≤ w j := by
by_cases hj₁ : MeasurableSet j
· exact (restrict_le_restrict_iff _ _ hi).1 hi₂ hj₁ hj
· rw [v.not_measurable hj₁, w.not_measurable hj₁]
#align measure_theory.vector_measure.subset_le_of_restrict_le_restrict MeasureTheory.VectorMeasure.subset_le_of_restrict_le_restrict
theorem restrict_le_restrict_of_subset_le {i : Set α}
(h : ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j) : v ≤[i] w := by
by_cases hi : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi).2 h
· rw [restrict_not_measurable v hi, restrict_not_measurable w hi]
#align measure_theory.vector_measure.restrict_le_restrict_of_subset_le MeasureTheory.VectorMeasure.restrict_le_restrict_of_subset_le
theorem restrict_le_restrict_subset {i j : Set α} (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w)
(hij : j ⊆ i) : v ≤[j] w :=
restrict_le_restrict_of_subset_le v w fun _ _ hk₂ =>
subset_le_of_restrict_le_restrict v w hi₁ hi₂ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_restrict_subset MeasureTheory.VectorMeasure.restrict_le_restrict_subset
theorem le_restrict_empty : v ≤[∅] w := by
intro j _
rw [restrict_empty, restrict_empty]
#align measure_theory.vector_measure.le_restrict_empty MeasureTheory.VectorMeasure.le_restrict_empty
theorem le_restrict_univ_iff_le : v ≤[Set.univ] w ↔ v ≤ w := by
constructor
· intro h s hs
have := h s hs
rwa [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ] at this
· intro h s hs
rw [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ]
exact h s hs
#align measure_theory.vector_measure.le_restrict_univ_iff_le MeasureTheory.VectorMeasure.le_restrict_univ_iff_le
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommGroup M] [TopologicalAddGroup M]
variable (v w : VectorMeasure α M)
nonrec theorem neg_le_neg {i : Set α} (hi : MeasurableSet i) (h : v ≤[i] w) : -w ≤[i] -v := by
intro j hj₁
rw [restrict_apply _ hi hj₁, restrict_apply _ hi hj₁, neg_apply, neg_apply]
refine neg_le_neg ?_
rw [← restrict_apply _ hi hj₁, ← restrict_apply _ hi hj₁]
exact h j hj₁
#align measure_theory.vector_measure.neg_le_neg MeasureTheory.VectorMeasure.neg_le_neg
@[simp]
theorem neg_le_neg_iff {i : Set α} (hi : MeasurableSet i) : -w ≤[i] -v ↔ v ≤[i] w :=
⟨fun h => neg_neg v ▸ neg_neg w ▸ neg_le_neg _ _ hi h, fun h => neg_le_neg _ _ hi h⟩
#align measure_theory.vector_measure.neg_le_neg_iff MeasureTheory.VectorMeasure.neg_le_neg_iff
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M] [OrderClosedTopology M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem restrict_le_restrict_iUnion {f : ℕ → Set α} (hf₁ : ∀ n, MeasurableSet (f n))
(hf₂ : ∀ n, v ≤[f n] w) : v ≤[⋃ n, f n] w := by
refine restrict_le_restrict_of_subset_le v w fun a ha₁ ha₂ => ?_
have ha₃ : ⋃ n, a ∩ disjointed f n = a := by
rwa [← Set.inter_iUnion, iUnion_disjointed, Set.inter_eq_left]
have ha₄ : Pairwise (Disjoint on fun n => a ∩ disjointed f n) :=
(disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
rw [← ha₃, v.of_disjoint_iUnion_nat _ ha₄, w.of_disjoint_iUnion_nat _ ha₄]
· refine tsum_le_tsum (fun n => (restrict_le_restrict_iff v w (hf₁ n)).1 (hf₂ n) ?_ ?_) ?_ ?_
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact Set.Subset.trans Set.inter_subset_right (disjointed_subset _ _)
· refine (v.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· refine (w.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· intro n
exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact fun n => ha₁.inter (MeasurableSet.disjointed hf₁ n)
#align measure_theory.vector_measure.restrict_le_restrict_Union MeasureTheory.VectorMeasure.restrict_le_restrict_iUnion
theorem restrict_le_restrict_countable_iUnion [Countable β] {f : β → Set α}
(hf₁ : ∀ b, MeasurableSet (f b)) (hf₂ : ∀ b, v ≤[f b] w) : v ≤[⋃ b, f b] w := by
cases nonempty_encodable β
rw [← Encodable.iUnion_decode₂]
refine restrict_le_restrict_iUnion v w ?_ ?_
· intro n
measurability
· intro n
cases' Encodable.decode₂ β n with b
· simp
· simp [hf₂ b]
#align measure_theory.vector_measure.restrict_le_restrict_countable_Union MeasureTheory.VectorMeasure.restrict_le_restrict_countable_iUnion
theorem restrict_le_restrict_union (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w) (hj₁ : MeasurableSet j)
(hj₂ : v ≤[j] w) : v ≤[i ∪ j] w := by
rw [Set.union_eq_iUnion]
refine restrict_le_restrict_countable_iUnion v w ?_ ?_
· measurability
· rintro (_ | _) <;> simpa
#align measure_theory.vector_measure.restrict_le_restrict_union MeasureTheory.VectorMeasure.restrict_le_restrict_union
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem nonneg_of_zero_le_restrict (hi₂ : 0 ≤[i] v) : 0 ≤ v i := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonneg_of_zero_le_restrict MeasureTheory.VectorMeasure.nonneg_of_zero_le_restrict
theorem nonpos_of_restrict_le_zero (hi₂ : v ≤[i] 0) : v i ≤ 0 := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonpos_of_restrict_le_zero MeasureTheory.VectorMeasure.nonpos_of_restrict_le_zero
theorem zero_le_restrict_not_measurable (hi : ¬MeasurableSet i) : 0 ≤[i] v := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.zero_le_restrict_not_measurable MeasureTheory.VectorMeasure.zero_le_restrict_not_measurable
theorem restrict_le_zero_of_not_measurable (hi : ¬MeasurableSet i) : v ≤[i] 0 := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_le_zero_of_not_measurable MeasureTheory.VectorMeasure.restrict_le_zero_of_not_measurable
theorem measurable_of_not_zero_le_restrict (hi : ¬0 ≤[i] v) : MeasurableSet i :=
Not.imp_symm (zero_le_restrict_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_zero_le_restrict MeasureTheory.VectorMeasure.measurable_of_not_zero_le_restrict
theorem measurable_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) : MeasurableSet i :=
Not.imp_symm (restrict_le_zero_of_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_restrict_le_zero MeasureTheory.VectorMeasure.measurable_of_not_restrict_le_zero
theorem zero_le_restrict_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : 0 ≤[i] v) : 0 ≤[j] v :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.zero_le_restrict_subset MeasureTheory.VectorMeasure.zero_le_restrict_subset
theorem restrict_le_zero_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : v ≤[i] 0) : v ≤[j] 0 :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_zero_subset MeasureTheory.VectorMeasure.restrict_le_zero_subset
end
section
variable {M : Type*} [TopologicalSpace M] [LinearOrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem exists_pos_measure_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) :
∃ j : Set α, MeasurableSet j ∧ j ⊆ i ∧ 0 < v j := by
have hi₁ : MeasurableSet i := measurable_of_not_restrict_le_zero _ hi
rw [restrict_le_restrict_iff _ _ hi₁] at hi
push_neg at hi
exact hi
#align measure_theory.vector_measure.exists_pos_measure_of_not_restrict_le_zero MeasureTheory.VectorMeasure.exists_pos_measure_of_not_restrict_le_zero
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
[CovariantClass M M (· + ·) (· ≤ ·)] [ContinuousAdd M]
instance covariant_add_le :
CovariantClass (VectorMeasure α M) (VectorMeasure α M) (· + ·) (· ≤ ·) :=
⟨fun _ _ _ h i hi => add_le_add_left (h i hi) _⟩
#align measure_theory.vector_measure.covariant_add_le MeasureTheory.VectorMeasure.covariant_add_le
end
section
variable {L M N : Type*}
variable [AddCommMonoid L] [TopologicalSpace L] [AddCommMonoid M] [TopologicalSpace M]
[AddCommMonoid N] [TopologicalSpace N]
/-- A vector measure `v` is absolutely continuous with respect to a measure `μ` if for all sets
`s`, `μ s = 0`, we have `v s = 0`. -/
def AbsolutelyContinuous (v : VectorMeasure α M) (w : VectorMeasure α N) :=
∀ ⦃s : Set α⦄, w s = 0 → v s = 0
#align measure_theory.vector_measure.absolutely_continuous MeasureTheory.VectorMeasure.AbsolutelyContinuous
@[inherit_doc VectorMeasure.AbsolutelyContinuous]
scoped[MeasureTheory] infixl:50 " ≪ᵥ " => MeasureTheory.VectorMeasure.AbsolutelyContinuous
open MeasureTheory
namespace AbsolutelyContinuous
variable {v : VectorMeasure α M} {w : VectorMeasure α N}
theorem mk (h : ∀ ⦃s : Set α⦄, MeasurableSet s → w s = 0 → v s = 0) : v ≪ᵥ w := by
intro s hs
by_cases hmeas : MeasurableSet s
· exact h hmeas hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.mk MeasureTheory.VectorMeasure.AbsolutelyContinuous.mk
theorem eq {w : VectorMeasure α M} (h : v = w) : v ≪ᵥ w :=
fun _ hs => h.symm ▸ hs
#align measure_theory.vector_measure.absolutely_continuous.eq MeasureTheory.VectorMeasure.AbsolutelyContinuous.eq
@[refl]
theorem refl (v : VectorMeasure α M) : v ≪ᵥ v :=
eq rfl
#align measure_theory.vector_measure.absolutely_continuous.refl MeasureTheory.VectorMeasure.AbsolutelyContinuous.refl
@[trans]
theorem trans {u : VectorMeasure α L} {v : VectorMeasure α M} {w : VectorMeasure α N} (huv : u ≪ᵥ v)
(hvw : v ≪ᵥ w) : u ≪ᵥ w :=
fun _ hs => huv <| hvw hs
#align measure_theory.vector_measure.absolutely_continuous.trans MeasureTheory.VectorMeasure.AbsolutelyContinuous.trans
theorem zero (v : VectorMeasure α N) : (0 : VectorMeasure α M) ≪ᵥ v :=
fun s _ => VectorMeasure.zero_apply s
#align measure_theory.vector_measure.absolutely_continuous.zero MeasureTheory.VectorMeasure.AbsolutelyContinuous.zero
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : -v ≪ᵥ w := by
intro s hs
rw [neg_apply, h hs, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.neg_left MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : v ≪ᵥ -w := by
intro s hs
rw [neg_apply, neg_eq_zero] at hs
exact h hs
#align measure_theory.vector_measure.absolutely_continuous.neg_right MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_right
theorem add [ContinuousAdd M] {v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w)
(hv₂ : v₂ ≪ᵥ w) : v₁ + v₂ ≪ᵥ w := by
intro s hs
rw [add_apply, hv₁ hs, hv₂ hs, zero_add]
#align measure_theory.vector_measure.absolutely_continuous.add MeasureTheory.VectorMeasure.AbsolutelyContinuous.add
theorem sub {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w) (hv₂ : v₂ ≪ᵥ w) :
v₁ - v₂ ≪ᵥ w := by
intro s hs
rw [sub_apply, hv₁ hs, hv₂ hs, zero_sub, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.sub MeasureTheory.VectorMeasure.AbsolutelyContinuous.sub
theorem smul {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] {r : R}
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : r • v ≪ᵥ w := by
intro s hs
rw [smul_apply, h hs, smul_zero]
#align measure_theory.vector_measure.absolutely_continuous.smul MeasureTheory.VectorMeasure.AbsolutelyContinuous.smul
theorem map [MeasureSpace β] (h : v ≪ᵥ w) (f : α → β) : v.map f ≪ᵥ w.map f := by
by_cases hf : Measurable f
· refine mk fun s hs hws => ?_
rw [map_apply _ hf hs] at hws ⊢
exact h hws
· intro s _
rw [map_not_measurable v hf, zero_apply]
#align measure_theory.vector_measure.absolutely_continuous.map MeasureTheory.VectorMeasure.AbsolutelyContinuous.map
theorem ennrealToMeasure {μ : VectorMeasure α ℝ≥0∞} :
(∀ ⦃s : Set α⦄, μ.ennrealToMeasure s = 0 → v s = 0) ↔ v ≪ᵥ μ := by
constructor <;> intro h
· refine mk fun s hmeas hs => h ?_
rw [← hs, ennrealToMeasure_apply hmeas]
· intro s hs
by_cases hmeas : MeasurableSet s
· rw [ennrealToMeasure_apply hmeas] at hs
exact h hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.ennreal_to_measure MeasureTheory.VectorMeasure.AbsolutelyContinuous.ennrealToMeasure
end AbsolutelyContinuous
/-- Two vector measures `v` and `w` are said to be mutually singular if there exists a measurable
set `s`, such that for all `t ⊆ s`, `v t = 0` and for all `t ⊆ sᶜ`, `w t = 0`.
We note that we do not require the measurability of `t` in the definition since this makes it easier
to use. This is equivalent to the definition which requires measurability. To prove
`MutuallySingular` with the measurability condition, use
`MeasureTheory.VectorMeasure.MutuallySingular.mk`. -/
def MutuallySingular (v : VectorMeasure α M) (w : VectorMeasure α N) : Prop :=
∃ s : Set α, MeasurableSet s ∧ (∀ t ⊆ s, v t = 0) ∧ ∀ t ⊆ sᶜ, w t = 0
#align measure_theory.vector_measure.mutually_singular MeasureTheory.VectorMeasure.MutuallySingular
@[inherit_doc VectorMeasure.MutuallySingular]
scoped[MeasureTheory] infixl:60 " ⟂ᵥ " => MeasureTheory.VectorMeasure.MutuallySingular
namespace MutuallySingular
variable {v v₁ v₂ : VectorMeasure α M} {w w₁ w₂ : VectorMeasure α N}
theorem mk (s : Set α) (hs : MeasurableSet s) (h₁ : ∀ t ⊆ s, MeasurableSet t → v t = 0)
(h₂ : ∀ t ⊆ sᶜ, MeasurableSet t → w t = 0) : v ⟂ᵥ w := by
refine ⟨s, hs, fun t hst => ?_, fun t hst => ?_⟩ <;> by_cases ht : MeasurableSet t
· exact h₁ t hst ht
· exact not_measurable v ht
· exact h₂ t hst ht
· exact not_measurable w ht
#align measure_theory.vector_measure.mutually_singular.mk MeasureTheory.VectorMeasure.MutuallySingular.mk
theorem symm (h : v ⟂ᵥ w) : w ⟂ᵥ v :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨sᶜ, hmeas.compl, hs₂, fun t ht => hs₁ _ (compl_compl s ▸ ht : t ⊆ s)⟩
#align measure_theory.vector_measure.mutually_singular.symm MeasureTheory.VectorMeasure.MutuallySingular.symm
theorem zero_right : v ⟂ᵥ (0 : VectorMeasure α N) :=
⟨∅, MeasurableSet.empty, fun _ ht => (Set.subset_empty_iff.1 ht).symm ▸ v.empty,
fun _ _ => zero_apply _⟩
#align measure_theory.vector_measure.mutually_singular.zero_right MeasureTheory.VectorMeasure.MutuallySingular.zero_right
theorem zero_left : (0 : VectorMeasure α M) ⟂ᵥ w :=
zero_right.symm
#align measure_theory.vector_measure.mutually_singular.zero_left MeasureTheory.VectorMeasure.MutuallySingular.zero_left
theorem add_left [T2Space N] [ContinuousAdd M] (h₁ : v₁ ⟂ᵥ w) (h₂ : v₂ ⟂ᵥ w) : v₁ + v₂ ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h₁
obtain ⟨v, hmv, hv₁, hv₂⟩ := h₂
refine mk (u ∩ v) (hmu.inter hmv) (fun t ht _ => ?_) fun t ht hmt => ?_
· rw [add_apply, hu₁ _ (Set.subset_inter_iff.1 ht).1, hv₁ _ (Set.subset_inter_iff.1 ht).2,
zero_add]
· rw [Set.compl_inter] at ht
rw [(_ : t = uᶜ ∩ t ∪ vᶜ \ uᶜ ∩ t),
of_union _ (hmu.compl.inter hmt) ((hmv.compl.diff hmu.compl).inter hmt), hu₂, hv₂, add_zero]
· exact Set.Subset.trans Set.inter_subset_left diff_subset
· exact Set.inter_subset_left
· exact disjoint_sdiff_self_right.mono Set.inter_subset_left Set.inter_subset_left
· apply Set.Subset.antisymm <;> intro x hx
· by_cases hxu' : x ∈ uᶜ
· exact Or.inl ⟨hxu', hx⟩
rcases ht hx with (hxu | hxv)
exacts [False.elim (hxu' hxu), Or.inr ⟨⟨hxv, hxu'⟩, hx⟩]
· cases' hx with hx hx <;> exact hx.2
#align measure_theory.vector_measure.mutually_singular.add_left MeasureTheory.VectorMeasure.MutuallySingular.add_left
theorem add_right [T2Space M] [ContinuousAdd N] (h₁ : v ⟂ᵥ w₁) (h₂ : v ⟂ᵥ w₂) : v ⟂ᵥ w₁ + w₂ :=
(add_left h₁.symm h₂.symm).symm
#align measure_theory.vector_measure.mutually_singular.add_right MeasureTheory.VectorMeasure.MutuallySingular.add_right
theorem smul_right {R : Type*} [Semiring R] [DistribMulAction R N] [ContinuousConstSMul R N]
(r : R) (h : v ⟂ᵥ w) : v ⟂ᵥ r • w :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨s, hmeas, hs₁, fun t ht => by simp only [coe_smul, Pi.smul_apply, hs₂ t ht, smul_zero]⟩
#align measure_theory.vector_measure.mutually_singular.smul_right MeasureTheory.VectorMeasure.MutuallySingular.smul_right
theorem smul_left {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] (r : R)
(h : v ⟂ᵥ w) : r • v ⟂ᵥ w :=
(smul_right r h.symm).symm
#align measure_theory.vector_measure.mutually_singular.smul_left MeasureTheory.VectorMeasure.MutuallySingular.smul_left
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : -v ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h
refine ⟨u, hmu, fun s hs => ?_, hu₂⟩
rw [neg_apply v s, neg_eq_zero]
exact hu₁ s hs
#align measure_theory.vector_measure.mutually_singular.neg_left MeasureTheory.VectorMeasure.MutuallySingular.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : v ⟂ᵥ -w :=
h.symm.neg_left.symm
#align measure_theory.vector_measure.mutually_singular.neg_right MeasureTheory.VectorMeasure.MutuallySingular.neg_right
@[simp]
theorem neg_left_iff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} : -v ⟂ᵥ w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg v ▸ h.neg_left, neg_left⟩
#align measure_theory.vector_measure.mutually_singular.neg_left_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_left_iff
@[simp]
theorem neg_right_iff {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} : v ⟂ᵥ -w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg w ▸ h.neg_right, neg_right⟩
#align measure_theory.vector_measure.mutually_singular.neg_right_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_right_iff
end MutuallySingular
section Trim
/-- Restriction of a vector measure onto a sub-σ-algebra. -/
@[simps]
def trim {m n : MeasurableSpace α} (v : VectorMeasure α M) (hle : m ≤ n) :
@VectorMeasure α m M _ _ :=
@VectorMeasure.mk α m M _ _
(fun i => if MeasurableSet[m] i then v i else 0)
(by dsimp only; rw [if_pos (@MeasurableSet.empty _ m), v.empty])
(fun i hi => by dsimp only; rw [if_neg hi])
(fun f hf₁ hf₂ => by
dsimp only
have hf₁' : ∀ k, MeasurableSet[n] (f k) := fun k => hle _ (hf₁ k)
convert v.m_iUnion hf₁' hf₂ using 1
· ext n
rw [if_pos (hf₁ n)]
· rw [if_pos (@MeasurableSet.iUnion _ _ m _ _ hf₁)])
#align measure_theory.vector_measure.trim MeasureTheory.VectorMeasure.trim
variable {n : MeasurableSpace α} {v : VectorMeasure α M}
theorem trim_eq_self : v.trim le_rfl = v := by
ext i hi
exact if_pos hi
#align measure_theory.vector_measure.trim_eq_self MeasureTheory.VectorMeasure.trim_eq_self
@[simp]
theorem zero_trim (hle : m ≤ n) : (0 : VectorMeasure α M).trim hle = 0 := by
ext i hi
exact if_pos hi
#align measure_theory.vector_measure.zero_trim MeasureTheory.VectorMeasure.zero_trim
theorem trim_measurableSet_eq (hle : m ≤ n) {i : Set α} (hi : MeasurableSet[m] i) :
v.trim hle i = v i :=
if_pos hi
#align measure_theory.vector_measure.trim_measurable_set_eq MeasureTheory.VectorMeasure.trim_measurableSet_eq
| Mathlib/MeasureTheory/Measure/VectorMeasure.lean | 1,274 | 1,278 | theorem restrict_trim (hle : m ≤ n) {i : Set α} (hi : MeasurableSet[m] i) :
@VectorMeasure.restrict α m M _ _ (v.trim hle) i = (v.restrict i).trim hle := by |
ext j hj
rw [@restrict_apply _ m, trim_measurableSet_eq hle hj, restrict_apply, trim_measurableSet_eq]
all_goals measurability
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Group.Nat
import Mathlib.Algebra.Order.Sub.Canonical
import Mathlib.Data.List.Perm
import Mathlib.Data.Set.List
import Mathlib.Init.Quot
import Mathlib.Order.Hom.Basic
#align_import data.multiset.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Multisets
These are implemented as the quotient of a list by permutations.
## Notation
We define the global infix notation `::ₘ` for `Multiset.cons`.
-/
universe v
open List Subtype Nat Function
variable {α : Type*} {β : Type v} {γ : Type*}
/-- `Multiset α` is the quotient of `List α` by list permutation. The result
is a type of finite sets with duplicates allowed. -/
def Multiset.{u} (α : Type u) : Type u :=
Quotient (List.isSetoid α)
#align multiset Multiset
namespace Multiset
-- Porting note: new
/-- The quotient map from `List α` to `Multiset α`. -/
@[coe]
def ofList : List α → Multiset α :=
Quot.mk _
instance : Coe (List α) (Multiset α) :=
⟨ofList⟩
@[simp]
theorem quot_mk_to_coe (l : List α) : @Eq (Multiset α) ⟦l⟧ l :=
rfl
#align multiset.quot_mk_to_coe Multiset.quot_mk_to_coe
@[simp]
theorem quot_mk_to_coe' (l : List α) : @Eq (Multiset α) (Quot.mk (· ≈ ·) l) l :=
rfl
#align multiset.quot_mk_to_coe' Multiset.quot_mk_to_coe'
@[simp]
theorem quot_mk_to_coe'' (l : List α) : @Eq (Multiset α) (Quot.mk Setoid.r l) l :=
rfl
#align multiset.quot_mk_to_coe'' Multiset.quot_mk_to_coe''
@[simp]
theorem coe_eq_coe {l₁ l₂ : List α} : (l₁ : Multiset α) = l₂ ↔ l₁ ~ l₂ :=
Quotient.eq
#align multiset.coe_eq_coe Multiset.coe_eq_coe
-- Porting note: new instance;
-- Porting note (#11215): TODO: move to better place
instance [DecidableEq α] (l₁ l₂ : List α) : Decidable (l₁ ≈ l₂) :=
inferInstanceAs (Decidable (l₁ ~ l₂))
-- Porting note: `Quotient.recOnSubsingleton₂ s₁ s₂` was in parens which broke elaboration
instance decidableEq [DecidableEq α] : DecidableEq (Multiset α)
| s₁, s₂ => Quotient.recOnSubsingleton₂ s₁ s₂ fun _ _ => decidable_of_iff' _ Quotient.eq
#align multiset.has_decidable_eq Multiset.decidableEq
/-- defines a size for a multiset by referring to the size of the underlying list -/
protected
def sizeOf [SizeOf α] (s : Multiset α) : ℕ :=
(Quot.liftOn s SizeOf.sizeOf) fun _ _ => Perm.sizeOf_eq_sizeOf
#align multiset.sizeof Multiset.sizeOf
instance [SizeOf α] : SizeOf (Multiset α) :=
⟨Multiset.sizeOf⟩
/-! ### Empty multiset -/
/-- `0 : Multiset α` is the empty set -/
protected def zero : Multiset α :=
@nil α
#align multiset.zero Multiset.zero
instance : Zero (Multiset α) :=
⟨Multiset.zero⟩
instance : EmptyCollection (Multiset α) :=
⟨0⟩
instance inhabitedMultiset : Inhabited (Multiset α) :=
⟨0⟩
#align multiset.inhabited_multiset Multiset.inhabitedMultiset
instance [IsEmpty α] : Unique (Multiset α) where
default := 0
uniq := by rintro ⟨_ | ⟨a, l⟩⟩; exacts [rfl, isEmptyElim a]
@[simp]
theorem coe_nil : (@nil α : Multiset α) = 0 :=
rfl
#align multiset.coe_nil Multiset.coe_nil
@[simp]
theorem empty_eq_zero : (∅ : Multiset α) = 0 :=
rfl
#align multiset.empty_eq_zero Multiset.empty_eq_zero
@[simp]
theorem coe_eq_zero (l : List α) : (l : Multiset α) = 0 ↔ l = [] :=
Iff.trans coe_eq_coe perm_nil
#align multiset.coe_eq_zero Multiset.coe_eq_zero
theorem coe_eq_zero_iff_isEmpty (l : List α) : (l : Multiset α) = 0 ↔ l.isEmpty :=
Iff.trans (coe_eq_zero l) isEmpty_iff_eq_nil.symm
#align multiset.coe_eq_zero_iff_empty Multiset.coe_eq_zero_iff_isEmpty
/-! ### `Multiset.cons` -/
/-- `cons a s` is the multiset which contains `s` plus one more instance of `a`. -/
def cons (a : α) (s : Multiset α) : Multiset α :=
Quot.liftOn s (fun l => (a :: l : Multiset α)) fun _ _ p => Quot.sound (p.cons a)
#align multiset.cons Multiset.cons
@[inherit_doc Multiset.cons]
infixr:67 " ::ₘ " => Multiset.cons
instance : Insert α (Multiset α) :=
⟨cons⟩
@[simp]
theorem insert_eq_cons (a : α) (s : Multiset α) : insert a s = a ::ₘ s :=
rfl
#align multiset.insert_eq_cons Multiset.insert_eq_cons
@[simp]
theorem cons_coe (a : α) (l : List α) : (a ::ₘ l : Multiset α) = (a :: l : List α) :=
rfl
#align multiset.cons_coe Multiset.cons_coe
@[simp]
theorem cons_inj_left {a b : α} (s : Multiset α) : a ::ₘ s = b ::ₘ s ↔ a = b :=
⟨Quot.inductionOn s fun l e =>
have : [a] ++ l ~ [b] ++ l := Quotient.exact e
singleton_perm_singleton.1 <| (perm_append_right_iff _).1 this,
congr_arg (· ::ₘ _)⟩
#align multiset.cons_inj_left Multiset.cons_inj_left
@[simp]
theorem cons_inj_right (a : α) : ∀ {s t : Multiset α}, a ::ₘ s = a ::ₘ t ↔ s = t := by
rintro ⟨l₁⟩ ⟨l₂⟩; simp
#align multiset.cons_inj_right Multiset.cons_inj_right
@[elab_as_elim]
protected theorem induction {p : Multiset α → Prop} (empty : p 0)
(cons : ∀ (a : α) (s : Multiset α), p s → p (a ::ₘ s)) : ∀ s, p s := by
rintro ⟨l⟩; induction' l with _ _ ih <;> [exact empty; exact cons _ _ ih]
#align multiset.induction Multiset.induction
@[elab_as_elim]
protected theorem induction_on {p : Multiset α → Prop} (s : Multiset α) (empty : p 0)
(cons : ∀ (a : α) (s : Multiset α), p s → p (a ::ₘ s)) : p s :=
Multiset.induction empty cons s
#align multiset.induction_on Multiset.induction_on
theorem cons_swap (a b : α) (s : Multiset α) : a ::ₘ b ::ₘ s = b ::ₘ a ::ₘ s :=
Quot.inductionOn s fun _ => Quotient.sound <| Perm.swap _ _ _
#align multiset.cons_swap Multiset.cons_swap
section Rec
variable {C : Multiset α → Sort*}
/-- Dependent recursor on multisets.
TODO: should be @[recursor 6], but then the definition of `Multiset.pi` fails with a stack
overflow in `whnf`.
-/
protected
def rec (C_0 : C 0) (C_cons : ∀ a m, C m → C (a ::ₘ m))
(C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b)))
(m : Multiset α) : C m :=
Quotient.hrecOn m (@List.rec α (fun l => C ⟦l⟧) C_0 fun a l b => C_cons a ⟦l⟧ b) fun l l' h =>
h.rec_heq
(fun hl _ ↦ by congr 1; exact Quot.sound hl)
(C_cons_heq _ _ ⟦_⟧ _)
#align multiset.rec Multiset.rec
/-- Companion to `Multiset.rec` with more convenient argument order. -/
@[elab_as_elim]
protected
def recOn (m : Multiset α) (C_0 : C 0) (C_cons : ∀ a m, C m → C (a ::ₘ m))
(C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b))) :
C m :=
Multiset.rec C_0 C_cons C_cons_heq m
#align multiset.rec_on Multiset.recOn
variable {C_0 : C 0} {C_cons : ∀ a m, C m → C (a ::ₘ m)}
{C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b))}
@[simp]
theorem recOn_0 : @Multiset.recOn α C (0 : Multiset α) C_0 C_cons C_cons_heq = C_0 :=
rfl
#align multiset.rec_on_0 Multiset.recOn_0
@[simp]
theorem recOn_cons (a : α) (m : Multiset α) :
(a ::ₘ m).recOn C_0 C_cons C_cons_heq = C_cons a m (m.recOn C_0 C_cons C_cons_heq) :=
Quotient.inductionOn m fun _ => rfl
#align multiset.rec_on_cons Multiset.recOn_cons
end Rec
section Mem
/-- `a ∈ s` means that `a` has nonzero multiplicity in `s`. -/
def Mem (a : α) (s : Multiset α) : Prop :=
Quot.liftOn s (fun l => a ∈ l) fun l₁ l₂ (e : l₁ ~ l₂) => propext <| e.mem_iff
#align multiset.mem Multiset.Mem
instance : Membership α (Multiset α) :=
⟨Mem⟩
@[simp]
theorem mem_coe {a : α} {l : List α} : a ∈ (l : Multiset α) ↔ a ∈ l :=
Iff.rfl
#align multiset.mem_coe Multiset.mem_coe
instance decidableMem [DecidableEq α] (a : α) (s : Multiset α) : Decidable (a ∈ s) :=
Quot.recOnSubsingleton' s fun l ↦ inferInstanceAs (Decidable (a ∈ l))
#align multiset.decidable_mem Multiset.decidableMem
@[simp]
theorem mem_cons {a b : α} {s : Multiset α} : a ∈ b ::ₘ s ↔ a = b ∨ a ∈ s :=
Quot.inductionOn s fun _ => List.mem_cons
#align multiset.mem_cons Multiset.mem_cons
theorem mem_cons_of_mem {a b : α} {s : Multiset α} (h : a ∈ s) : a ∈ b ::ₘ s :=
mem_cons.2 <| Or.inr h
#align multiset.mem_cons_of_mem Multiset.mem_cons_of_mem
-- @[simp] -- Porting note (#10618): simp can prove this
theorem mem_cons_self (a : α) (s : Multiset α) : a ∈ a ::ₘ s :=
mem_cons.2 (Or.inl rfl)
#align multiset.mem_cons_self Multiset.mem_cons_self
theorem forall_mem_cons {p : α → Prop} {a : α} {s : Multiset α} :
(∀ x ∈ a ::ₘ s, p x) ↔ p a ∧ ∀ x ∈ s, p x :=
Quotient.inductionOn' s fun _ => List.forall_mem_cons
#align multiset.forall_mem_cons Multiset.forall_mem_cons
theorem exists_cons_of_mem {s : Multiset α} {a : α} : a ∈ s → ∃ t, s = a ::ₘ t :=
Quot.inductionOn s fun l (h : a ∈ l) =>
let ⟨l₁, l₂, e⟩ := append_of_mem h
e.symm ▸ ⟨(l₁ ++ l₂ : List α), Quot.sound perm_middle⟩
#align multiset.exists_cons_of_mem Multiset.exists_cons_of_mem
@[simp]
theorem not_mem_zero (a : α) : a ∉ (0 : Multiset α) :=
List.not_mem_nil _
#align multiset.not_mem_zero Multiset.not_mem_zero
theorem eq_zero_of_forall_not_mem {s : Multiset α} : (∀ x, x ∉ s) → s = 0 :=
Quot.inductionOn s fun l H => by rw [eq_nil_iff_forall_not_mem.mpr H]; rfl
#align multiset.eq_zero_of_forall_not_mem Multiset.eq_zero_of_forall_not_mem
theorem eq_zero_iff_forall_not_mem {s : Multiset α} : s = 0 ↔ ∀ a, a ∉ s :=
⟨fun h => h.symm ▸ fun _ => not_mem_zero _, eq_zero_of_forall_not_mem⟩
#align multiset.eq_zero_iff_forall_not_mem Multiset.eq_zero_iff_forall_not_mem
theorem exists_mem_of_ne_zero {s : Multiset α} : s ≠ 0 → ∃ a : α, a ∈ s :=
Quot.inductionOn s fun l hl =>
match l, hl with
| [], h => False.elim <| h rfl
| a :: l, _ => ⟨a, by simp⟩
#align multiset.exists_mem_of_ne_zero Multiset.exists_mem_of_ne_zero
theorem empty_or_exists_mem (s : Multiset α) : s = 0 ∨ ∃ a, a ∈ s :=
or_iff_not_imp_left.mpr Multiset.exists_mem_of_ne_zero
#align multiset.empty_or_exists_mem Multiset.empty_or_exists_mem
@[simp]
theorem zero_ne_cons {a : α} {m : Multiset α} : 0 ≠ a ::ₘ m := fun h =>
have : a ∈ (0 : Multiset α) := h.symm ▸ mem_cons_self _ _
not_mem_zero _ this
#align multiset.zero_ne_cons Multiset.zero_ne_cons
@[simp]
theorem cons_ne_zero {a : α} {m : Multiset α} : a ::ₘ m ≠ 0 :=
zero_ne_cons.symm
#align multiset.cons_ne_zero Multiset.cons_ne_zero
theorem cons_eq_cons {a b : α} {as bs : Multiset α} :
a ::ₘ as = b ::ₘ bs ↔ a = b ∧ as = bs ∨ a ≠ b ∧ ∃ cs, as = b ::ₘ cs ∧ bs = a ::ₘ cs := by
haveI : DecidableEq α := Classical.decEq α
constructor
· intro eq
by_cases h : a = b
· subst h
simp_all
· have : a ∈ b ::ₘ bs := eq ▸ mem_cons_self _ _
have : a ∈ bs := by simpa [h]
rcases exists_cons_of_mem this with ⟨cs, hcs⟩
simp only [h, hcs, false_and, ne_eq, not_false_eq_true, cons_inj_right, exists_eq_right',
true_and, false_or]
have : a ::ₘ as = b ::ₘ a ::ₘ cs := by simp [eq, hcs]
have : a ::ₘ as = a ::ₘ b ::ₘ cs := by rwa [cons_swap]
simpa using this
· intro h
rcases h with (⟨eq₁, eq₂⟩ | ⟨_, cs, eq₁, eq₂⟩)
· simp [*]
· simp [*, cons_swap a b]
#align multiset.cons_eq_cons Multiset.cons_eq_cons
end Mem
/-! ### Singleton -/
instance : Singleton α (Multiset α) :=
⟨fun a => a ::ₘ 0⟩
instance : LawfulSingleton α (Multiset α) :=
⟨fun _ => rfl⟩
@[simp]
theorem cons_zero (a : α) : a ::ₘ 0 = {a} :=
rfl
#align multiset.cons_zero Multiset.cons_zero
@[simp, norm_cast]
theorem coe_singleton (a : α) : ([a] : Multiset α) = {a} :=
rfl
#align multiset.coe_singleton Multiset.coe_singleton
@[simp]
theorem mem_singleton {a b : α} : b ∈ ({a} : Multiset α) ↔ b = a := by
simp only [← cons_zero, mem_cons, iff_self_iff, or_false_iff, not_mem_zero]
#align multiset.mem_singleton Multiset.mem_singleton
theorem mem_singleton_self (a : α) : a ∈ ({a} : Multiset α) := by
rw [← cons_zero]
exact mem_cons_self _ _
#align multiset.mem_singleton_self Multiset.mem_singleton_self
@[simp]
theorem singleton_inj {a b : α} : ({a} : Multiset α) = {b} ↔ a = b := by
simp_rw [← cons_zero]
exact cons_inj_left _
#align multiset.singleton_inj Multiset.singleton_inj
@[simp, norm_cast]
theorem coe_eq_singleton {l : List α} {a : α} : (l : Multiset α) = {a} ↔ l = [a] := by
rw [← coe_singleton, coe_eq_coe, List.perm_singleton]
#align multiset.coe_eq_singleton Multiset.coe_eq_singleton
@[simp]
theorem singleton_eq_cons_iff {a b : α} (m : Multiset α) : {a} = b ::ₘ m ↔ a = b ∧ m = 0 := by
rw [← cons_zero, cons_eq_cons]
simp [eq_comm]
#align multiset.singleton_eq_cons_iff Multiset.singleton_eq_cons_iff
theorem pair_comm (x y : α) : ({x, y} : Multiset α) = {y, x} :=
cons_swap x y 0
#align multiset.pair_comm Multiset.pair_comm
/-! ### `Multiset.Subset` -/
section Subset
variable {s : Multiset α} {a : α}
/-- `s ⊆ t` is the lift of the list subset relation. It means that any
element with nonzero multiplicity in `s` has nonzero multiplicity in `t`,
but it does not imply that the multiplicity of `a` in `s` is less or equal than in `t`;
see `s ≤ t` for this relation. -/
protected def Subset (s t : Multiset α) : Prop :=
∀ ⦃a : α⦄, a ∈ s → a ∈ t
#align multiset.subset Multiset.Subset
instance : HasSubset (Multiset α) :=
⟨Multiset.Subset⟩
instance : HasSSubset (Multiset α) :=
⟨fun s t => s ⊆ t ∧ ¬t ⊆ s⟩
instance instIsNonstrictStrictOrder : IsNonstrictStrictOrder (Multiset α) (· ⊆ ·) (· ⊂ ·) where
right_iff_left_not_left _ _ := Iff.rfl
@[simp]
theorem coe_subset {l₁ l₂ : List α} : (l₁ : Multiset α) ⊆ l₂ ↔ l₁ ⊆ l₂ :=
Iff.rfl
#align multiset.coe_subset Multiset.coe_subset
@[simp]
theorem Subset.refl (s : Multiset α) : s ⊆ s := fun _ h => h
#align multiset.subset.refl Multiset.Subset.refl
theorem Subset.trans {s t u : Multiset α} : s ⊆ t → t ⊆ u → s ⊆ u := fun h₁ h₂ _ m => h₂ (h₁ m)
#align multiset.subset.trans Multiset.Subset.trans
theorem subset_iff {s t : Multiset α} : s ⊆ t ↔ ∀ ⦃x⦄, x ∈ s → x ∈ t :=
Iff.rfl
#align multiset.subset_iff Multiset.subset_iff
theorem mem_of_subset {s t : Multiset α} {a : α} (h : s ⊆ t) : a ∈ s → a ∈ t :=
@h _
#align multiset.mem_of_subset Multiset.mem_of_subset
@[simp]
theorem zero_subset (s : Multiset α) : 0 ⊆ s := fun a => (not_mem_nil a).elim
#align multiset.zero_subset Multiset.zero_subset
theorem subset_cons (s : Multiset α) (a : α) : s ⊆ a ::ₘ s := fun _ => mem_cons_of_mem
#align multiset.subset_cons Multiset.subset_cons
theorem ssubset_cons {s : Multiset α} {a : α} (ha : a ∉ s) : s ⊂ a ::ₘ s :=
⟨subset_cons _ _, fun h => ha <| h <| mem_cons_self _ _⟩
#align multiset.ssubset_cons Multiset.ssubset_cons
@[simp]
theorem cons_subset {a : α} {s t : Multiset α} : a ::ₘ s ⊆ t ↔ a ∈ t ∧ s ⊆ t := by
simp [subset_iff, or_imp, forall_and]
#align multiset.cons_subset Multiset.cons_subset
theorem cons_subset_cons {a : α} {s t : Multiset α} : s ⊆ t → a ::ₘ s ⊆ a ::ₘ t :=
Quotient.inductionOn₂ s t fun _ _ => List.cons_subset_cons _
#align multiset.cons_subset_cons Multiset.cons_subset_cons
theorem eq_zero_of_subset_zero {s : Multiset α} (h : s ⊆ 0) : s = 0 :=
eq_zero_of_forall_not_mem fun _ hx ↦ not_mem_zero _ (h hx)
#align multiset.eq_zero_of_subset_zero Multiset.eq_zero_of_subset_zero
@[simp] lemma subset_zero : s ⊆ 0 ↔ s = 0 :=
⟨eq_zero_of_subset_zero, fun xeq => xeq.symm ▸ Subset.refl 0⟩
#align multiset.subset_zero Multiset.subset_zero
@[simp] lemma zero_ssubset : 0 ⊂ s ↔ s ≠ 0 := by simp [ssubset_iff_subset_not_subset]
@[simp] lemma singleton_subset : {a} ⊆ s ↔ a ∈ s := by simp [subset_iff]
theorem induction_on' {p : Multiset α → Prop} (S : Multiset α) (h₁ : p 0)
(h₂ : ∀ {a s}, a ∈ S → s ⊆ S → p s → p (insert a s)) : p S :=
@Multiset.induction_on α (fun T => T ⊆ S → p T) S (fun _ => h₁)
(fun _ _ hps hs =>
let ⟨hS, sS⟩ := cons_subset.1 hs
h₂ hS sS (hps sS))
(Subset.refl S)
#align multiset.induction_on' Multiset.induction_on'
end Subset
/-! ### `Multiset.toList` -/
section ToList
/-- Produces a list of the elements in the multiset using choice. -/
noncomputable def toList (s : Multiset α) :=
s.out'
#align multiset.to_list Multiset.toList
@[simp, norm_cast]
theorem coe_toList (s : Multiset α) : (s.toList : Multiset α) = s :=
s.out_eq'
#align multiset.coe_to_list Multiset.coe_toList
@[simp]
theorem toList_eq_nil {s : Multiset α} : s.toList = [] ↔ s = 0 := by
rw [← coe_eq_zero, coe_toList]
#align multiset.to_list_eq_nil Multiset.toList_eq_nil
@[simp]
theorem empty_toList {s : Multiset α} : s.toList.isEmpty ↔ s = 0 :=
isEmpty_iff_eq_nil.trans toList_eq_nil
#align multiset.empty_to_list Multiset.empty_toList
@[simp]
theorem toList_zero : (Multiset.toList 0 : List α) = [] :=
toList_eq_nil.mpr rfl
#align multiset.to_list_zero Multiset.toList_zero
@[simp]
theorem mem_toList {a : α} {s : Multiset α} : a ∈ s.toList ↔ a ∈ s := by
rw [← mem_coe, coe_toList]
#align multiset.mem_to_list Multiset.mem_toList
@[simp]
theorem toList_eq_singleton_iff {a : α} {m : Multiset α} : m.toList = [a] ↔ m = {a} := by
rw [← perm_singleton, ← coe_eq_coe, coe_toList, coe_singleton]
#align multiset.to_list_eq_singleton_iff Multiset.toList_eq_singleton_iff
@[simp]
theorem toList_singleton (a : α) : ({a} : Multiset α).toList = [a] :=
Multiset.toList_eq_singleton_iff.2 rfl
#align multiset.to_list_singleton Multiset.toList_singleton
end ToList
/-! ### Partial order on `Multiset`s -/
/-- `s ≤ t` means that `s` is a sublist of `t` (up to permutation).
Equivalently, `s ≤ t` means that `count a s ≤ count a t` for all `a`. -/
protected def Le (s t : Multiset α) : Prop :=
(Quotient.liftOn₂ s t (· <+~ ·)) fun _ _ _ _ p₁ p₂ =>
propext (p₂.subperm_left.trans p₁.subperm_right)
#align multiset.le Multiset.Le
instance : PartialOrder (Multiset α) where
le := Multiset.Le
le_refl := by rintro ⟨l⟩; exact Subperm.refl _
le_trans := by rintro ⟨l₁⟩ ⟨l₂⟩ ⟨l₃⟩; exact @Subperm.trans _ _ _ _
le_antisymm := by rintro ⟨l₁⟩ ⟨l₂⟩ h₁ h₂; exact Quot.sound (Subperm.antisymm h₁ h₂)
instance decidableLE [DecidableEq α] : DecidableRel ((· ≤ ·) : Multiset α → Multiset α → Prop) :=
fun s t => Quotient.recOnSubsingleton₂ s t List.decidableSubperm
#align multiset.decidable_le Multiset.decidableLE
section
variable {s t : Multiset α} {a : α}
theorem subset_of_le : s ≤ t → s ⊆ t :=
Quotient.inductionOn₂ s t fun _ _ => Subperm.subset
#align multiset.subset_of_le Multiset.subset_of_le
alias Le.subset := subset_of_le
#align multiset.le.subset Multiset.Le.subset
theorem mem_of_le (h : s ≤ t) : a ∈ s → a ∈ t :=
mem_of_subset (subset_of_le h)
#align multiset.mem_of_le Multiset.mem_of_le
theorem not_mem_mono (h : s ⊆ t) : a ∉ t → a ∉ s :=
mt <| @h _
#align multiset.not_mem_mono Multiset.not_mem_mono
@[simp]
theorem coe_le {l₁ l₂ : List α} : (l₁ : Multiset α) ≤ l₂ ↔ l₁ <+~ l₂ :=
Iff.rfl
#align multiset.coe_le Multiset.coe_le
@[elab_as_elim]
theorem leInductionOn {C : Multiset α → Multiset α → Prop} {s t : Multiset α} (h : s ≤ t)
(H : ∀ {l₁ l₂ : List α}, l₁ <+ l₂ → C l₁ l₂) : C s t :=
Quotient.inductionOn₂ s t (fun l₁ _ ⟨l, p, s⟩ => (show ⟦l⟧ = ⟦l₁⟧ from Quot.sound p) ▸ H s) h
#align multiset.le_induction_on Multiset.leInductionOn
theorem zero_le (s : Multiset α) : 0 ≤ s :=
Quot.inductionOn s fun l => (nil_sublist l).subperm
#align multiset.zero_le Multiset.zero_le
instance : OrderBot (Multiset α) where
bot := 0
bot_le := zero_le
/-- This is a `rfl` and `simp` version of `bot_eq_zero`. -/
@[simp]
theorem bot_eq_zero : (⊥ : Multiset α) = 0 :=
rfl
#align multiset.bot_eq_zero Multiset.bot_eq_zero
theorem le_zero : s ≤ 0 ↔ s = 0 :=
le_bot_iff
#align multiset.le_zero Multiset.le_zero
theorem lt_cons_self (s : Multiset α) (a : α) : s < a ::ₘ s :=
Quot.inductionOn s fun l =>
suffices l <+~ a :: l ∧ ¬l ~ a :: l by simpa [lt_iff_le_and_ne]
⟨(sublist_cons _ _).subperm, fun p => _root_.ne_of_lt (lt_succ_self (length l)) p.length_eq⟩
#align multiset.lt_cons_self Multiset.lt_cons_self
theorem le_cons_self (s : Multiset α) (a : α) : s ≤ a ::ₘ s :=
le_of_lt <| lt_cons_self _ _
#align multiset.le_cons_self Multiset.le_cons_self
theorem cons_le_cons_iff (a : α) : a ::ₘ s ≤ a ::ₘ t ↔ s ≤ t :=
Quotient.inductionOn₂ s t fun _ _ => subperm_cons a
#align multiset.cons_le_cons_iff Multiset.cons_le_cons_iff
theorem cons_le_cons (a : α) : s ≤ t → a ::ₘ s ≤ a ::ₘ t :=
(cons_le_cons_iff a).2
#align multiset.cons_le_cons Multiset.cons_le_cons
@[simp] lemma cons_lt_cons_iff : a ::ₘ s < a ::ₘ t ↔ s < t :=
lt_iff_lt_of_le_iff_le' (cons_le_cons_iff _) (cons_le_cons_iff _)
lemma cons_lt_cons (a : α) (h : s < t) : a ::ₘ s < a ::ₘ t := cons_lt_cons_iff.2 h
theorem le_cons_of_not_mem (m : a ∉ s) : s ≤ a ::ₘ t ↔ s ≤ t := by
refine ⟨?_, fun h => le_trans h <| le_cons_self _ _⟩
suffices ∀ {t'}, s ≤ t' → a ∈ t' → a ::ₘ s ≤ t' by
exact fun h => (cons_le_cons_iff a).1 (this h (mem_cons_self _ _))
introv h
revert m
refine leInductionOn h ?_
introv s m₁ m₂
rcases append_of_mem m₂ with ⟨r₁, r₂, rfl⟩
exact
perm_middle.subperm_left.2
((subperm_cons _).2 <| ((sublist_or_mem_of_sublist s).resolve_right m₁).subperm)
#align multiset.le_cons_of_not_mem Multiset.le_cons_of_not_mem
@[simp]
theorem singleton_ne_zero (a : α) : ({a} : Multiset α) ≠ 0 :=
ne_of_gt (lt_cons_self _ _)
#align multiset.singleton_ne_zero Multiset.singleton_ne_zero
@[simp]
theorem singleton_le {a : α} {s : Multiset α} : {a} ≤ s ↔ a ∈ s :=
⟨fun h => mem_of_le h (mem_singleton_self _), fun h =>
let ⟨_t, e⟩ := exists_cons_of_mem h
e.symm ▸ cons_le_cons _ (zero_le _)⟩
#align multiset.singleton_le Multiset.singleton_le
@[simp] lemma le_singleton : s ≤ {a} ↔ s = 0 ∨ s = {a} :=
Quot.induction_on s fun l ↦ by simp only [cons_zero, ← coe_singleton, quot_mk_to_coe'', coe_le,
coe_eq_zero, coe_eq_coe, perm_singleton, subperm_singleton_iff]
@[simp] lemma lt_singleton : s < {a} ↔ s = 0 := by
simp only [lt_iff_le_and_ne, le_singleton, or_and_right, Ne, and_not_self, or_false,
and_iff_left_iff_imp]
rintro rfl
exact (singleton_ne_zero _).symm
@[simp] lemma ssubset_singleton_iff : s ⊂ {a} ↔ s = 0 := by
refine ⟨fun hs ↦ eq_zero_of_subset_zero fun b hb ↦ (hs.2 ?_).elim, ?_⟩
· obtain rfl := mem_singleton.1 (hs.1 hb)
rwa [singleton_subset]
· rintro rfl
simp
end
/-! ### Additive monoid -/
/-- The sum of two multisets is the lift of the list append operation.
This adds the multiplicities of each element,
i.e. `count a (s + t) = count a s + count a t`. -/
protected def add (s₁ s₂ : Multiset α) : Multiset α :=
(Quotient.liftOn₂ s₁ s₂ fun l₁ l₂ => ((l₁ ++ l₂ : List α) : Multiset α)) fun _ _ _ _ p₁ p₂ =>
Quot.sound <| p₁.append p₂
#align multiset.add Multiset.add
instance : Add (Multiset α) :=
⟨Multiset.add⟩
@[simp]
theorem coe_add (s t : List α) : (s + t : Multiset α) = (s ++ t : List α) :=
rfl
#align multiset.coe_add Multiset.coe_add
@[simp]
theorem singleton_add (a : α) (s : Multiset α) : {a} + s = a ::ₘ s :=
rfl
#align multiset.singleton_add Multiset.singleton_add
private theorem add_le_add_iff_left' {s t u : Multiset α} : s + t ≤ s + u ↔ t ≤ u :=
Quotient.inductionOn₃ s t u fun _ _ _ => subperm_append_left _
instance : CovariantClass (Multiset α) (Multiset α) (· + ·) (· ≤ ·) :=
⟨fun _s _t _u => add_le_add_iff_left'.2⟩
instance : ContravariantClass (Multiset α) (Multiset α) (· + ·) (· ≤ ·) :=
⟨fun _s _t _u => add_le_add_iff_left'.1⟩
instance : OrderedCancelAddCommMonoid (Multiset α) where
zero := 0
add := (· + ·)
add_comm := fun s t => Quotient.inductionOn₂ s t fun l₁ l₂ => Quot.sound perm_append_comm
add_assoc := fun s₁ s₂ s₃ =>
Quotient.inductionOn₃ s₁ s₂ s₃ fun l₁ l₂ l₃ => congr_arg _ <| append_assoc l₁ l₂ l₃
zero_add := fun s => Quot.inductionOn s fun l => rfl
add_zero := fun s => Quotient.inductionOn s fun l => congr_arg _ <| append_nil l
add_le_add_left := fun s₁ s₂ => add_le_add_left
le_of_add_le_add_left := fun s₁ s₂ s₃ => le_of_add_le_add_left
nsmul := nsmulRec
theorem le_add_right (s t : Multiset α) : s ≤ s + t := by simpa using add_le_add_left (zero_le t) s
#align multiset.le_add_right Multiset.le_add_right
theorem le_add_left (s t : Multiset α) : s ≤ t + s := by simpa using add_le_add_right (zero_le t) s
#align multiset.le_add_left Multiset.le_add_left
theorem le_iff_exists_add {s t : Multiset α} : s ≤ t ↔ ∃ u, t = s + u :=
⟨fun h =>
leInductionOn h fun s =>
let ⟨l, p⟩ := s.exists_perm_append
⟨l, Quot.sound p⟩,
fun ⟨_u, e⟩ => e.symm ▸ le_add_right _ _⟩
#align multiset.le_iff_exists_add Multiset.le_iff_exists_add
instance : CanonicallyOrderedAddCommMonoid (Multiset α) where
__ := inferInstanceAs (OrderBot (Multiset α))
le_self_add := le_add_right
exists_add_of_le h := leInductionOn h fun s =>
let ⟨l, p⟩ := s.exists_perm_append
⟨l, Quot.sound p⟩
@[simp]
theorem cons_add (a : α) (s t : Multiset α) : a ::ₘ s + t = a ::ₘ (s + t) := by
rw [← singleton_add, ← singleton_add, add_assoc]
#align multiset.cons_add Multiset.cons_add
@[simp]
theorem add_cons (a : α) (s t : Multiset α) : s + a ::ₘ t = a ::ₘ (s + t) := by
rw [add_comm, cons_add, add_comm]
#align multiset.add_cons Multiset.add_cons
@[simp]
theorem mem_add {a : α} {s t : Multiset α} : a ∈ s + t ↔ a ∈ s ∨ a ∈ t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => mem_append
#align multiset.mem_add Multiset.mem_add
theorem mem_of_mem_nsmul {a : α} {s : Multiset α} {n : ℕ} (h : a ∈ n • s) : a ∈ s := by
induction' n with n ih
· rw [zero_nsmul] at h
exact absurd h (not_mem_zero _)
· rw [succ_nsmul, mem_add] at h
exact h.elim ih id
#align multiset.mem_of_mem_nsmul Multiset.mem_of_mem_nsmul
@[simp]
theorem mem_nsmul {a : α} {s : Multiset α} {n : ℕ} (h0 : n ≠ 0) : a ∈ n • s ↔ a ∈ s := by
refine ⟨mem_of_mem_nsmul, fun h => ?_⟩
obtain ⟨n, rfl⟩ := exists_eq_succ_of_ne_zero h0
rw [succ_nsmul, mem_add]
exact Or.inr h
#align multiset.mem_nsmul Multiset.mem_nsmul
theorem nsmul_cons {s : Multiset α} (n : ℕ) (a : α) :
n • (a ::ₘ s) = n • ({a} : Multiset α) + n • s := by
rw [← singleton_add, nsmul_add]
#align multiset.nsmul_cons Multiset.nsmul_cons
/-! ### Cardinality -/
/-- The cardinality of a multiset is the sum of the multiplicities
of all its elements, or simply the length of the underlying list. -/
def card : Multiset α →+ ℕ where
toFun s := (Quot.liftOn s length) fun _l₁ _l₂ => Perm.length_eq
map_zero' := rfl
map_add' s t := Quotient.inductionOn₂ s t length_append
#align multiset.card Multiset.card
@[simp]
theorem coe_card (l : List α) : card (l : Multiset α) = length l :=
rfl
#align multiset.coe_card Multiset.coe_card
@[simp]
theorem length_toList (s : Multiset α) : s.toList.length = card s := by
rw [← coe_card, coe_toList]
#align multiset.length_to_list Multiset.length_toList
@[simp, nolint simpNF] -- Porting note (#10675): `dsimp` can not prove this, yet linter complains
theorem card_zero : @card α 0 = 0 :=
rfl
#align multiset.card_zero Multiset.card_zero
theorem card_add (s t : Multiset α) : card (s + t) = card s + card t :=
card.map_add s t
#align multiset.card_add Multiset.card_add
theorem card_nsmul (s : Multiset α) (n : ℕ) : card (n • s) = n * card s := by
rw [card.map_nsmul s n, Nat.nsmul_eq_mul]
#align multiset.card_nsmul Multiset.card_nsmul
@[simp]
theorem card_cons (a : α) (s : Multiset α) : card (a ::ₘ s) = card s + 1 :=
Quot.inductionOn s fun _l => rfl
#align multiset.card_cons Multiset.card_cons
@[simp]
theorem card_singleton (a : α) : card ({a} : Multiset α) = 1 := by
simp only [← cons_zero, card_zero, eq_self_iff_true, zero_add, card_cons]
#align multiset.card_singleton Multiset.card_singleton
theorem card_pair (a b : α) : card {a, b} = 2 := by
rw [insert_eq_cons, card_cons, card_singleton]
#align multiset.card_pair Multiset.card_pair
theorem card_eq_one {s : Multiset α} : card s = 1 ↔ ∃ a, s = {a} :=
⟨Quot.inductionOn s fun _l h => (List.length_eq_one.1 h).imp fun _a => congr_arg _,
fun ⟨_a, e⟩ => e.symm ▸ rfl⟩
#align multiset.card_eq_one Multiset.card_eq_one
theorem card_le_card {s t : Multiset α} (h : s ≤ t) : card s ≤ card t :=
leInductionOn h Sublist.length_le
#align multiset.card_le_of_le Multiset.card_le_card
@[mono]
theorem card_mono : Monotone (@card α) := fun _a _b => card_le_card
#align multiset.card_mono Multiset.card_mono
theorem eq_of_le_of_card_le {s t : Multiset α} (h : s ≤ t) : card t ≤ card s → s = t :=
leInductionOn h fun s h₂ => congr_arg _ <| s.eq_of_length_le h₂
#align multiset.eq_of_le_of_card_le Multiset.eq_of_le_of_card_le
theorem card_lt_card {s t : Multiset α} (h : s < t) : card s < card t :=
lt_of_not_ge fun h₂ => _root_.ne_of_lt h <| eq_of_le_of_card_le (le_of_lt h) h₂
#align multiset.card_lt_card Multiset.card_lt_card
lemma card_strictMono : StrictMono (card : Multiset α → ℕ) := fun _ _ ↦ card_lt_card
theorem lt_iff_cons_le {s t : Multiset α} : s < t ↔ ∃ a, a ::ₘ s ≤ t :=
⟨Quotient.inductionOn₂ s t fun _l₁ _l₂ h =>
Subperm.exists_of_length_lt (le_of_lt h) (card_lt_card h),
fun ⟨_a, h⟩ => lt_of_lt_of_le (lt_cons_self _ _) h⟩
#align multiset.lt_iff_cons_le Multiset.lt_iff_cons_le
@[simp]
theorem card_eq_zero {s : Multiset α} : card s = 0 ↔ s = 0 :=
⟨fun h => (eq_of_le_of_card_le (zero_le _) (le_of_eq h)).symm, fun e => by simp [e]⟩
#align multiset.card_eq_zero Multiset.card_eq_zero
theorem card_pos {s : Multiset α} : 0 < card s ↔ s ≠ 0 :=
Nat.pos_iff_ne_zero.trans <| not_congr card_eq_zero
#align multiset.card_pos Multiset.card_pos
theorem card_pos_iff_exists_mem {s : Multiset α} : 0 < card s ↔ ∃ a, a ∈ s :=
Quot.inductionOn s fun _l => length_pos_iff_exists_mem
#align multiset.card_pos_iff_exists_mem Multiset.card_pos_iff_exists_mem
theorem card_eq_two {s : Multiset α} : card s = 2 ↔ ∃ x y, s = {x, y} :=
⟨Quot.inductionOn s fun _l h =>
(List.length_eq_two.mp h).imp fun _a => Exists.imp fun _b => congr_arg _,
fun ⟨_a, _b, e⟩ => e.symm ▸ rfl⟩
#align multiset.card_eq_two Multiset.card_eq_two
theorem card_eq_three {s : Multiset α} : card s = 3 ↔ ∃ x y z, s = {x, y, z} :=
⟨Quot.inductionOn s fun _l h =>
(List.length_eq_three.mp h).imp fun _a =>
Exists.imp fun _b => Exists.imp fun _c => congr_arg _,
fun ⟨_a, _b, _c, e⟩ => e.symm ▸ rfl⟩
#align multiset.card_eq_three Multiset.card_eq_three
/-! ### Induction principles -/
/-- The strong induction principle for multisets. -/
@[elab_as_elim]
def strongInductionOn {p : Multiset α → Sort*} (s : Multiset α) (ih : ∀ s, (∀ t < s, p t) → p s) :
p s :=
(ih s) fun t _h =>
strongInductionOn t ih
termination_by card s
decreasing_by exact card_lt_card _h
#align multiset.strong_induction_on Multiset.strongInductionOnₓ -- Porting note: reorderd universes
theorem strongInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) (H) :
@strongInductionOn _ p s H = H s fun t _h => @strongInductionOn _ p t H := by
rw [strongInductionOn]
#align multiset.strong_induction_eq Multiset.strongInductionOn_eq
@[elab_as_elim]
theorem case_strongInductionOn {p : Multiset α → Prop} (s : Multiset α) (h₀ : p 0)
(h₁ : ∀ a s, (∀ t ≤ s, p t) → p (a ::ₘ s)) : p s :=
Multiset.strongInductionOn s fun s =>
Multiset.induction_on s (fun _ => h₀) fun _a _s _ ih =>
(h₁ _ _) fun _t h => ih _ <| lt_of_le_of_lt h <| lt_cons_self _ _
#align multiset.case_strong_induction_on Multiset.case_strongInductionOn
/-- Suppose that, given that `p t` can be defined on all supersets of `s` of cardinality less than
`n`, one knows how to define `p s`. Then one can inductively define `p s` for all multisets `s` of
cardinality less than `n`, starting from multisets of card `n` and iterating. This
can be used either to define data, or to prove properties. -/
def strongDownwardInduction {p : Multiset α → Sort*} {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁)
(s : Multiset α) :
card s ≤ n → p s :=
H s fun {t} ht _h =>
strongDownwardInduction H t ht
termination_by n - card s
decreasing_by simp_wf; have := (card_lt_card _h); omega
-- Porting note: reorderd universes
#align multiset.strong_downward_induction Multiset.strongDownwardInductionₓ
theorem strongDownwardInduction_eq {p : Multiset α → Sort*} {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁)
(s : Multiset α) :
strongDownwardInduction H s = H s fun ht _hst => strongDownwardInduction H _ ht := by
rw [strongDownwardInduction]
#align multiset.strong_downward_induction_eq Multiset.strongDownwardInduction_eq
/-- Analogue of `strongDownwardInduction` with order of arguments swapped. -/
@[elab_as_elim]
def strongDownwardInductionOn {p : Multiset α → Sort*} {n : ℕ} :
∀ s : Multiset α,
(∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) →
card s ≤ n → p s :=
fun s H => strongDownwardInduction H s
#align multiset.strong_downward_induction_on Multiset.strongDownwardInductionOn
theorem strongDownwardInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) :
s.strongDownwardInductionOn H = H s fun {t} ht _h => t.strongDownwardInductionOn H ht := by
dsimp only [strongDownwardInductionOn]
rw [strongDownwardInduction]
#align multiset.strong_downward_induction_on_eq Multiset.strongDownwardInductionOn_eq
#align multiset.well_founded_lt wellFounded_lt
/-- Another way of expressing `strongInductionOn`: the `(<)` relation is well-founded. -/
instance instWellFoundedLT : WellFoundedLT (Multiset α) :=
⟨Subrelation.wf Multiset.card_lt_card (measure Multiset.card).2⟩
#align multiset.is_well_founded_lt Multiset.instWellFoundedLT
/-! ### `Multiset.replicate` -/
/-- `replicate n a` is the multiset containing only `a` with multiplicity `n`. -/
def replicate (n : ℕ) (a : α) : Multiset α :=
List.replicate n a
#align multiset.replicate Multiset.replicate
theorem coe_replicate (n : ℕ) (a : α) : (List.replicate n a : Multiset α) = replicate n a := rfl
#align multiset.coe_replicate Multiset.coe_replicate
@[simp] theorem replicate_zero (a : α) : replicate 0 a = 0 := rfl
#align multiset.replicate_zero Multiset.replicate_zero
@[simp] theorem replicate_succ (a : α) (n) : replicate (n + 1) a = a ::ₘ replicate n a := rfl
#align multiset.replicate_succ Multiset.replicate_succ
theorem replicate_add (m n : ℕ) (a : α) : replicate (m + n) a = replicate m a + replicate n a :=
congr_arg _ <| List.replicate_add ..
#align multiset.replicate_add Multiset.replicate_add
/-- `Multiset.replicate` as an `AddMonoidHom`. -/
@[simps]
def replicateAddMonoidHom (a : α) : ℕ →+ Multiset α where
toFun := fun n => replicate n a
map_zero' := replicate_zero a
map_add' := fun _ _ => replicate_add _ _ a
#align multiset.replicate_add_monoid_hom Multiset.replicateAddMonoidHom
#align multiset.replicate_add_monoid_hom_apply Multiset.replicateAddMonoidHom_apply
theorem replicate_one (a : α) : replicate 1 a = {a} := rfl
#align multiset.replicate_one Multiset.replicate_one
@[simp] theorem card_replicate (n) (a : α) : card (replicate n a) = n :=
length_replicate n a
#align multiset.card_replicate Multiset.card_replicate
theorem mem_replicate {a b : α} {n : ℕ} : b ∈ replicate n a ↔ n ≠ 0 ∧ b = a :=
List.mem_replicate
#align multiset.mem_replicate Multiset.mem_replicate
theorem eq_of_mem_replicate {a b : α} {n} : b ∈ replicate n a → b = a :=
List.eq_of_mem_replicate
#align multiset.eq_of_mem_replicate Multiset.eq_of_mem_replicate
theorem eq_replicate_card {a : α} {s : Multiset α} : s = replicate (card s) a ↔ ∀ b ∈ s, b = a :=
Quot.inductionOn s fun _l => coe_eq_coe.trans <| perm_replicate.trans eq_replicate_length
#align multiset.eq_replicate_card Multiset.eq_replicate_card
alias ⟨_, eq_replicate_of_mem⟩ := eq_replicate_card
#align multiset.eq_replicate_of_mem Multiset.eq_replicate_of_mem
theorem eq_replicate {a : α} {n} {s : Multiset α} :
s = replicate n a ↔ card s = n ∧ ∀ b ∈ s, b = a :=
⟨fun h => h.symm ▸ ⟨card_replicate _ _, fun _b => eq_of_mem_replicate⟩,
fun ⟨e, al⟩ => e ▸ eq_replicate_of_mem al⟩
#align multiset.eq_replicate Multiset.eq_replicate
theorem replicate_right_injective {n : ℕ} (hn : n ≠ 0) : Injective (@replicate α n) :=
fun _ _ h => (eq_replicate.1 h).2 _ <| mem_replicate.2 ⟨hn, rfl⟩
#align multiset.replicate_right_injective Multiset.replicate_right_injective
@[simp] theorem replicate_right_inj {a b : α} {n : ℕ} (h : n ≠ 0) :
replicate n a = replicate n b ↔ a = b :=
(replicate_right_injective h).eq_iff
#align multiset.replicate_right_inj Multiset.replicate_right_inj
theorem replicate_left_injective (a : α) : Injective (replicate · a) :=
-- Porting note: was `fun m n h => by rw [← (eq_replicate.1 h).1, card_replicate]`
LeftInverse.injective (card_replicate · a)
#align multiset.replicate_left_injective Multiset.replicate_left_injective
theorem replicate_subset_singleton (n : ℕ) (a : α) : replicate n a ⊆ {a} :=
List.replicate_subset_singleton n a
#align multiset.replicate_subset_singleton Multiset.replicate_subset_singleton
theorem replicate_le_coe {a : α} {n} {l : List α} : replicate n a ≤ l ↔ List.replicate n a <+ l :=
⟨fun ⟨_l', p, s⟩ => perm_replicate.1 p ▸ s, Sublist.subperm⟩
#align multiset.replicate_le_coe Multiset.replicate_le_coe
theorem nsmul_replicate {a : α} (n m : ℕ) : n • replicate m a = replicate (n * m) a :=
((replicateAddMonoidHom a).map_nsmul _ _).symm
#align multiset.nsmul_replicate Multiset.nsmul_replicate
theorem nsmul_singleton (a : α) (n) : n • ({a} : Multiset α) = replicate n a := by
rw [← replicate_one, nsmul_replicate, mul_one]
#align multiset.nsmul_singleton Multiset.nsmul_singleton
theorem replicate_le_replicate (a : α) {k n : ℕ} : replicate k a ≤ replicate n a ↔ k ≤ n :=
_root_.trans (by rw [← replicate_le_coe, coe_replicate]) (List.replicate_sublist_replicate a)
#align multiset.replicate_le_replicate Multiset.replicate_le_replicate
theorem le_replicate_iff {m : Multiset α} {a : α} {n : ℕ} :
m ≤ replicate n a ↔ ∃ k ≤ n, m = replicate k a :=
⟨fun h => ⟨card m, (card_mono h).trans_eq (card_replicate _ _),
eq_replicate_card.2 fun _ hb => eq_of_mem_replicate <| subset_of_le h hb⟩,
fun ⟨_, hkn, hm⟩ => hm.symm ▸ (replicate_le_replicate _).2 hkn⟩
#align multiset.le_replicate_iff Multiset.le_replicate_iff
theorem lt_replicate_succ {m : Multiset α} {x : α} {n : ℕ} :
m < replicate (n + 1) x ↔ m ≤ replicate n x := by
rw [lt_iff_cons_le]
constructor
· rintro ⟨x', hx'⟩
have := eq_of_mem_replicate (mem_of_le hx' (mem_cons_self _ _))
rwa [this, replicate_succ, cons_le_cons_iff] at hx'
· intro h
rw [replicate_succ]
exact ⟨x, cons_le_cons _ h⟩
#align multiset.lt_replicate_succ Multiset.lt_replicate_succ
/-! ### Erasing one copy of an element -/
section Erase
variable [DecidableEq α] {s t : Multiset α} {a b : α}
/-- `erase s a` is the multiset that subtracts 1 from the multiplicity of `a`. -/
def erase (s : Multiset α) (a : α) : Multiset α :=
Quot.liftOn s (fun l => (l.erase a : Multiset α)) fun _l₁ _l₂ p => Quot.sound (p.erase a)
#align multiset.erase Multiset.erase
@[simp]
theorem coe_erase (l : List α) (a : α) : erase (l : Multiset α) a = l.erase a :=
rfl
#align multiset.coe_erase Multiset.coe_erase
@[simp, nolint simpNF] -- Porting note (#10675): `dsimp` can not prove this, yet linter complains
theorem erase_zero (a : α) : (0 : Multiset α).erase a = 0 :=
rfl
#align multiset.erase_zero Multiset.erase_zero
@[simp]
theorem erase_cons_head (a : α) (s : Multiset α) : (a ::ₘ s).erase a = s :=
Quot.inductionOn s fun l => congr_arg _ <| List.erase_cons_head a l
#align multiset.erase_cons_head Multiset.erase_cons_head
@[simp]
theorem erase_cons_tail {a b : α} (s : Multiset α) (h : b ≠ a) :
(b ::ₘ s).erase a = b ::ₘ s.erase a :=
Quot.inductionOn s fun l => congr_arg _ <| List.erase_cons_tail l (not_beq_of_ne h)
#align multiset.erase_cons_tail Multiset.erase_cons_tail
@[simp]
theorem erase_singleton (a : α) : ({a} : Multiset α).erase a = 0 :=
erase_cons_head a 0
#align multiset.erase_singleton Multiset.erase_singleton
@[simp]
theorem erase_of_not_mem {a : α} {s : Multiset α} : a ∉ s → s.erase a = s :=
Quot.inductionOn s fun _l h => congr_arg _ <| List.erase_of_not_mem h
#align multiset.erase_of_not_mem Multiset.erase_of_not_mem
@[simp]
theorem cons_erase {s : Multiset α} {a : α} : a ∈ s → a ::ₘ s.erase a = s :=
Quot.inductionOn s fun _l h => Quot.sound (perm_cons_erase h).symm
#align multiset.cons_erase Multiset.cons_erase
theorem erase_cons_tail_of_mem (h : a ∈ s) :
(b ::ₘ s).erase a = b ::ₘ s.erase a := by
rcases eq_or_ne a b with rfl | hab
· simp [cons_erase h]
· exact s.erase_cons_tail hab.symm
theorem le_cons_erase (s : Multiset α) (a : α) : s ≤ a ::ₘ s.erase a :=
if h : a ∈ s then le_of_eq (cons_erase h).symm
else by rw [erase_of_not_mem h]; apply le_cons_self
#align multiset.le_cons_erase Multiset.le_cons_erase
theorem add_singleton_eq_iff {s t : Multiset α} {a : α} : s + {a} = t ↔ a ∈ t ∧ s = t.erase a := by
rw [add_comm, singleton_add]; constructor
· rintro rfl
exact ⟨s.mem_cons_self a, (s.erase_cons_head a).symm⟩
· rintro ⟨h, rfl⟩
exact cons_erase h
#align multiset.add_singleton_eq_iff Multiset.add_singleton_eq_iff
theorem erase_add_left_pos {a : α} {s : Multiset α} (t) : a ∈ s → (s + t).erase a = s.erase a + t :=
Quotient.inductionOn₂ s t fun _l₁ l₂ h => congr_arg _ <| erase_append_left l₂ h
#align multiset.erase_add_left_pos Multiset.erase_add_left_pos
theorem erase_add_right_pos {a : α} (s) {t : Multiset α} (h : a ∈ t) :
(s + t).erase a = s + t.erase a := by rw [add_comm, erase_add_left_pos s h, add_comm]
#align multiset.erase_add_right_pos Multiset.erase_add_right_pos
theorem erase_add_right_neg {a : α} {s : Multiset α} (t) :
a ∉ s → (s + t).erase a = s + t.erase a :=
Quotient.inductionOn₂ s t fun _l₁ l₂ h => congr_arg _ <| erase_append_right l₂ h
#align multiset.erase_add_right_neg Multiset.erase_add_right_neg
theorem erase_add_left_neg {a : α} (s) {t : Multiset α} (h : a ∉ t) :
(s + t).erase a = s.erase a + t := by rw [add_comm, erase_add_right_neg s h, add_comm]
#align multiset.erase_add_left_neg Multiset.erase_add_left_neg
theorem erase_le (a : α) (s : Multiset α) : s.erase a ≤ s :=
Quot.inductionOn s fun l => (erase_sublist a l).subperm
#align multiset.erase_le Multiset.erase_le
@[simp]
theorem erase_lt {a : α} {s : Multiset α} : s.erase a < s ↔ a ∈ s :=
⟨fun h => not_imp_comm.1 erase_of_not_mem (ne_of_lt h), fun h => by
simpa [h] using lt_cons_self (s.erase a) a⟩
#align multiset.erase_lt Multiset.erase_lt
theorem erase_subset (a : α) (s : Multiset α) : s.erase a ⊆ s :=
subset_of_le (erase_le a s)
#align multiset.erase_subset Multiset.erase_subset
theorem mem_erase_of_ne {a b : α} {s : Multiset α} (ab : a ≠ b) : a ∈ s.erase b ↔ a ∈ s :=
Quot.inductionOn s fun _l => List.mem_erase_of_ne ab
#align multiset.mem_erase_of_ne Multiset.mem_erase_of_ne
theorem mem_of_mem_erase {a b : α} {s : Multiset α} : a ∈ s.erase b → a ∈ s :=
mem_of_subset (erase_subset _ _)
#align multiset.mem_of_mem_erase Multiset.mem_of_mem_erase
theorem erase_comm (s : Multiset α) (a b : α) : (s.erase a).erase b = (s.erase b).erase a :=
Quot.inductionOn s fun l => congr_arg _ <| l.erase_comm a b
#align multiset.erase_comm Multiset.erase_comm
theorem erase_le_erase {s t : Multiset α} (a : α) (h : s ≤ t) : s.erase a ≤ t.erase a :=
leInductionOn h fun h => (h.erase _).subperm
#align multiset.erase_le_erase Multiset.erase_le_erase
theorem erase_le_iff_le_cons {s t : Multiset α} {a : α} : s.erase a ≤ t ↔ s ≤ a ::ₘ t :=
⟨fun h => le_trans (le_cons_erase _ _) (cons_le_cons _ h), fun h =>
if m : a ∈ s then by rw [← cons_erase m] at h; exact (cons_le_cons_iff _).1 h
else le_trans (erase_le _ _) ((le_cons_of_not_mem m).1 h)⟩
#align multiset.erase_le_iff_le_cons Multiset.erase_le_iff_le_cons
@[simp]
theorem card_erase_of_mem {a : α} {s : Multiset α} : a ∈ s → card (s.erase a) = pred (card s) :=
Quot.inductionOn s fun _l => length_erase_of_mem
#align multiset.card_erase_of_mem Multiset.card_erase_of_mem
@[simp]
theorem card_erase_add_one {a : α} {s : Multiset α} : a ∈ s → card (s.erase a) + 1 = card s :=
Quot.inductionOn s fun _l => length_erase_add_one
#align multiset.card_erase_add_one Multiset.card_erase_add_one
theorem card_erase_lt_of_mem {a : α} {s : Multiset α} : a ∈ s → card (s.erase a) < card s :=
fun h => card_lt_card (erase_lt.mpr h)
#align multiset.card_erase_lt_of_mem Multiset.card_erase_lt_of_mem
theorem card_erase_le {a : α} {s : Multiset α} : card (s.erase a) ≤ card s :=
card_le_card (erase_le a s)
#align multiset.card_erase_le Multiset.card_erase_le
theorem card_erase_eq_ite {a : α} {s : Multiset α} :
card (s.erase a) = if a ∈ s then pred (card s) else card s := by
by_cases h : a ∈ s
· rwa [card_erase_of_mem h, if_pos]
· rwa [erase_of_not_mem h, if_neg]
#align multiset.card_erase_eq_ite Multiset.card_erase_eq_ite
end Erase
@[simp]
theorem coe_reverse (l : List α) : (reverse l : Multiset α) = l :=
Quot.sound <| reverse_perm _
#align multiset.coe_reverse Multiset.coe_reverse
/-! ### `Multiset.map` -/
/-- `map f s` is the lift of the list `map` operation. The multiplicity
of `b` in `map f s` is the number of `a ∈ s` (counting multiplicity)
such that `f a = b`. -/
def map (f : α → β) (s : Multiset α) : Multiset β :=
Quot.liftOn s (fun l : List α => (l.map f : Multiset β)) fun _l₁ _l₂ p => Quot.sound (p.map f)
#align multiset.map Multiset.map
@[congr]
theorem map_congr {f g : α → β} {s t : Multiset α} :
s = t → (∀ x ∈ t, f x = g x) → map f s = map g t := by
rintro rfl h
induction s using Quot.inductionOn
exact congr_arg _ (List.map_congr h)
#align multiset.map_congr Multiset.map_congr
theorem map_hcongr {β' : Type v} {m : Multiset α} {f : α → β} {f' : α → β'} (h : β = β')
(hf : ∀ a ∈ m, HEq (f a) (f' a)) : HEq (map f m) (map f' m) := by
subst h; simp at hf
simp [map_congr rfl hf]
#align multiset.map_hcongr Multiset.map_hcongr
theorem forall_mem_map_iff {f : α → β} {p : β → Prop} {s : Multiset α} :
(∀ y ∈ s.map f, p y) ↔ ∀ x ∈ s, p (f x) :=
Quotient.inductionOn' s fun _L => List.forall_mem_map_iff
#align multiset.forall_mem_map_iff Multiset.forall_mem_map_iff
@[simp, norm_cast] lemma map_coe (f : α → β) (l : List α) : map f l = l.map f := rfl
#align multiset.coe_map Multiset.map_coe
@[simp]
theorem map_zero (f : α → β) : map f 0 = 0 :=
rfl
#align multiset.map_zero Multiset.map_zero
@[simp]
theorem map_cons (f : α → β) (a s) : map f (a ::ₘ s) = f a ::ₘ map f s :=
Quot.inductionOn s fun _l => rfl
#align multiset.map_cons Multiset.map_cons
theorem map_comp_cons (f : α → β) (t) : map f ∘ cons t = cons (f t) ∘ map f := by
ext
simp
#align multiset.map_comp_cons Multiset.map_comp_cons
@[simp]
theorem map_singleton (f : α → β) (a : α) : ({a} : Multiset α).map f = {f a} :=
rfl
#align multiset.map_singleton Multiset.map_singleton
@[simp]
theorem map_replicate (f : α → β) (k : ℕ) (a : α) : (replicate k a).map f = replicate k (f a) := by
simp only [← coe_replicate, map_coe, List.map_replicate]
#align multiset.map_replicate Multiset.map_replicate
@[simp]
theorem map_add (f : α → β) (s t) : map f (s + t) = map f s + map f t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => congr_arg _ <| map_append _ _ _
#align multiset.map_add Multiset.map_add
/-- If each element of `s : Multiset α` can be lifted to `β`, then `s` can be lifted to
`Multiset β`. -/
instance canLift (c) (p) [CanLift α β c p] :
CanLift (Multiset α) (Multiset β) (map c) fun s => ∀ x ∈ s, p x where
prf := by
rintro ⟨l⟩ hl
lift l to List β using hl
exact ⟨l, map_coe _ _⟩
#align multiset.can_lift Multiset.canLift
/-- `Multiset.map` as an `AddMonoidHom`. -/
def mapAddMonoidHom (f : α → β) : Multiset α →+ Multiset β where
toFun := map f
map_zero' := map_zero _
map_add' := map_add _
#align multiset.map_add_monoid_hom Multiset.mapAddMonoidHom
@[simp]
theorem coe_mapAddMonoidHom (f : α → β) :
(mapAddMonoidHom f : Multiset α → Multiset β) = map f :=
rfl
#align multiset.coe_map_add_monoid_hom Multiset.coe_mapAddMonoidHom
theorem map_nsmul (f : α → β) (n : ℕ) (s) : map f (n • s) = n • map f s :=
(mapAddMonoidHom f).map_nsmul _ _
#align multiset.map_nsmul Multiset.map_nsmul
@[simp]
theorem mem_map {f : α → β} {b : β} {s : Multiset α} : b ∈ map f s ↔ ∃ a, a ∈ s ∧ f a = b :=
Quot.inductionOn s fun _l => List.mem_map
#align multiset.mem_map Multiset.mem_map
@[simp]
theorem card_map (f : α → β) (s) : card (map f s) = card s :=
Quot.inductionOn s fun _l => length_map _ _
#align multiset.card_map Multiset.card_map
@[simp]
theorem map_eq_zero {s : Multiset α} {f : α → β} : s.map f = 0 ↔ s = 0 := by
rw [← Multiset.card_eq_zero, Multiset.card_map, Multiset.card_eq_zero]
#align multiset.map_eq_zero Multiset.map_eq_zero
theorem mem_map_of_mem (f : α → β) {a : α} {s : Multiset α} (h : a ∈ s) : f a ∈ map f s :=
mem_map.2 ⟨_, h, rfl⟩
#align multiset.mem_map_of_mem Multiset.mem_map_of_mem
theorem map_eq_singleton {f : α → β} {s : Multiset α} {b : β} :
map f s = {b} ↔ ∃ a : α, s = {a} ∧ f a = b := by
constructor
· intro h
obtain ⟨a, ha⟩ : ∃ a, s = {a} := by rw [← card_eq_one, ← card_map, h, card_singleton]
refine ⟨a, ha, ?_⟩
rw [← mem_singleton, ← h, ha, map_singleton, mem_singleton]
· rintro ⟨a, rfl, rfl⟩
simp
#align multiset.map_eq_singleton Multiset.map_eq_singleton
theorem map_eq_cons [DecidableEq α] (f : α → β) (s : Multiset α) (t : Multiset β) (b : β) :
(∃ a ∈ s, f a = b ∧ (s.erase a).map f = t) ↔ s.map f = b ::ₘ t := by
constructor
· rintro ⟨a, ha, rfl, rfl⟩
rw [← map_cons, Multiset.cons_erase ha]
· intro h
have : b ∈ s.map f := by
rw [h]
exact mem_cons_self _ _
obtain ⟨a, h1, rfl⟩ := mem_map.mp this
obtain ⟨u, rfl⟩ := exists_cons_of_mem h1
rw [map_cons, cons_inj_right] at h
refine ⟨a, mem_cons_self _ _, rfl, ?_⟩
rw [Multiset.erase_cons_head, h]
#align multiset.map_eq_cons Multiset.map_eq_cons
-- The simpNF linter says that the LHS can be simplified via `Multiset.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem mem_map_of_injective {f : α → β} (H : Function.Injective f) {a : α} {s : Multiset α} :
f a ∈ map f s ↔ a ∈ s :=
Quot.inductionOn s fun _l => List.mem_map_of_injective H
#align multiset.mem_map_of_injective Multiset.mem_map_of_injective
@[simp]
theorem map_map (g : β → γ) (f : α → β) (s : Multiset α) : map g (map f s) = map (g ∘ f) s :=
Quot.inductionOn s fun _l => congr_arg _ <| List.map_map _ _ _
#align multiset.map_map Multiset.map_map
theorem map_id (s : Multiset α) : map id s = s :=
Quot.inductionOn s fun _l => congr_arg _ <| List.map_id _
#align multiset.map_id Multiset.map_id
@[simp]
theorem map_id' (s : Multiset α) : map (fun x => x) s = s :=
map_id s
#align multiset.map_id' Multiset.map_id'
-- Porting note: was a `simp` lemma in mathlib3
theorem map_const (s : Multiset α) (b : β) : map (const α b) s = replicate (card s) b :=
Quot.inductionOn s fun _ => congr_arg _ <| List.map_const' _ _
#align multiset.map_const Multiset.map_const
-- Porting note: was not a `simp` lemma in mathlib3 because `Function.const` was reducible
@[simp] theorem map_const' (s : Multiset α) (b : β) : map (fun _ ↦ b) s = replicate (card s) b :=
map_const _ _
#align multiset.map_const' Multiset.map_const'
theorem eq_of_mem_map_const {b₁ b₂ : β} {l : List α} (h : b₁ ∈ map (Function.const α b₂) l) :
b₁ = b₂ :=
eq_of_mem_replicate <| by rwa [map_const] at h
#align multiset.eq_of_mem_map_const Multiset.eq_of_mem_map_const
@[simp]
theorem map_le_map {f : α → β} {s t : Multiset α} (h : s ≤ t) : map f s ≤ map f t :=
leInductionOn h fun h => (h.map f).subperm
#align multiset.map_le_map Multiset.map_le_map
@[simp]
theorem map_lt_map {f : α → β} {s t : Multiset α} (h : s < t) : s.map f < t.map f := by
refine (map_le_map h.le).lt_of_not_le fun H => h.ne <| eq_of_le_of_card_le h.le ?_
rw [← s.card_map f, ← t.card_map f]
exact card_le_card H
#align multiset.map_lt_map Multiset.map_lt_map
theorem map_mono (f : α → β) : Monotone (map f) := fun _ _ => map_le_map
#align multiset.map_mono Multiset.map_mono
theorem map_strictMono (f : α → β) : StrictMono (map f) := fun _ _ => map_lt_map
#align multiset.map_strict_mono Multiset.map_strictMono
@[simp]
theorem map_subset_map {f : α → β} {s t : Multiset α} (H : s ⊆ t) : map f s ⊆ map f t := fun _b m =>
let ⟨a, h, e⟩ := mem_map.1 m
mem_map.2 ⟨a, H h, e⟩
#align multiset.map_subset_map Multiset.map_subset_map
theorem map_erase [DecidableEq α] [DecidableEq β] (f : α → β) (hf : Function.Injective f) (x : α)
(s : Multiset α) : (s.erase x).map f = (s.map f).erase (f x) := by
induction' s using Multiset.induction_on with y s ih
· simp
by_cases hxy : y = x
· cases hxy
simp
· rw [s.erase_cons_tail hxy, map_cons, map_cons, (s.map f).erase_cons_tail (hf.ne hxy), ih]
#align multiset.map_erase Multiset.map_erase
theorem map_erase_of_mem [DecidableEq α] [DecidableEq β] (f : α → β)
(s : Multiset α) {x : α} (h : x ∈ s) : (s.erase x).map f = (s.map f).erase (f x) := by
induction' s using Multiset.induction_on with y s ih
· simp
rcases eq_or_ne y x with rfl | hxy
· simp
replace h : x ∈ s := by simpa [hxy.symm] using h
rw [s.erase_cons_tail hxy, map_cons, map_cons, ih h, erase_cons_tail_of_mem (mem_map_of_mem f h)]
theorem map_surjective_of_surjective {f : α → β} (hf : Function.Surjective f) :
Function.Surjective (map f) := by
intro s
induction' s using Multiset.induction_on with x s ih
· exact ⟨0, map_zero _⟩
· obtain ⟨y, rfl⟩ := hf x
obtain ⟨t, rfl⟩ := ih
exact ⟨y ::ₘ t, map_cons _ _ _⟩
#align multiset.map_surjective_of_surjective Multiset.map_surjective_of_surjective
/-! ### `Multiset.fold` -/
/-- `foldl f H b s` is the lift of the list operation `foldl f b l`,
which folds `f` over the multiset. It is well defined when `f` is right-commutative,
that is, `f (f b a₁) a₂ = f (f b a₂) a₁`. -/
def foldl (f : β → α → β) (H : RightCommutative f) (b : β) (s : Multiset α) : β :=
Quot.liftOn s (fun l => List.foldl f b l) fun _l₁ _l₂ p => p.foldl_eq H b
#align multiset.foldl Multiset.foldl
@[simp]
theorem foldl_zero (f : β → α → β) (H b) : foldl f H b 0 = b :=
rfl
#align multiset.foldl_zero Multiset.foldl_zero
@[simp]
theorem foldl_cons (f : β → α → β) (H b a s) : foldl f H b (a ::ₘ s) = foldl f H (f b a) s :=
Quot.inductionOn s fun _l => rfl
#align multiset.foldl_cons Multiset.foldl_cons
@[simp]
theorem foldl_add (f : β → α → β) (H b s t) : foldl f H b (s + t) = foldl f H (foldl f H b s) t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => foldl_append _ _ _ _
#align multiset.foldl_add Multiset.foldl_add
/-- `foldr f H b s` is the lift of the list operation `foldr f b l`,
which folds `f` over the multiset. It is well defined when `f` is left-commutative,
that is, `f a₁ (f a₂ b) = f a₂ (f a₁ b)`. -/
def foldr (f : α → β → β) (H : LeftCommutative f) (b : β) (s : Multiset α) : β :=
Quot.liftOn s (fun l => List.foldr f b l) fun _l₁ _l₂ p => p.foldr_eq H b
#align multiset.foldr Multiset.foldr
@[simp]
theorem foldr_zero (f : α → β → β) (H b) : foldr f H b 0 = b :=
rfl
#align multiset.foldr_zero Multiset.foldr_zero
@[simp]
theorem foldr_cons (f : α → β → β) (H b a s) : foldr f H b (a ::ₘ s) = f a (foldr f H b s) :=
Quot.inductionOn s fun _l => rfl
#align multiset.foldr_cons Multiset.foldr_cons
@[simp]
theorem foldr_singleton (f : α → β → β) (H b a) : foldr f H b ({a} : Multiset α) = f a b :=
rfl
#align multiset.foldr_singleton Multiset.foldr_singleton
@[simp]
theorem foldr_add (f : α → β → β) (H b s t) : foldr f H b (s + t) = foldr f H (foldr f H b t) s :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => foldr_append _ _ _ _
#align multiset.foldr_add Multiset.foldr_add
@[simp]
theorem coe_foldr (f : α → β → β) (H : LeftCommutative f) (b : β) (l : List α) :
foldr f H b l = l.foldr f b :=
rfl
#align multiset.coe_foldr Multiset.coe_foldr
@[simp]
theorem coe_foldl (f : β → α → β) (H : RightCommutative f) (b : β) (l : List α) :
foldl f H b l = l.foldl f b :=
rfl
#align multiset.coe_foldl Multiset.coe_foldl
theorem coe_foldr_swap (f : α → β → β) (H : LeftCommutative f) (b : β) (l : List α) :
foldr f H b l = l.foldl (fun x y => f y x) b :=
(congr_arg (foldr f H b) (coe_reverse l)).symm.trans <| foldr_reverse _ _ _
#align multiset.coe_foldr_swap Multiset.coe_foldr_swap
theorem foldr_swap (f : α → β → β) (H : LeftCommutative f) (b : β) (s : Multiset α) :
foldr f H b s = foldl (fun x y => f y x) (fun _x _y _z => (H _ _ _).symm) b s :=
Quot.inductionOn s fun _l => coe_foldr_swap _ _ _ _
#align multiset.foldr_swap Multiset.foldr_swap
theorem foldl_swap (f : β → α → β) (H : RightCommutative f) (b : β) (s : Multiset α) :
foldl f H b s = foldr (fun x y => f y x) (fun _x _y _z => (H _ _ _).symm) b s :=
(foldr_swap _ _ _ _).symm
#align multiset.foldl_swap Multiset.foldl_swap
theorem foldr_induction' (f : α → β → β) (H : LeftCommutative f) (x : β) (q : α → Prop)
(p : β → Prop) (s : Multiset α) (hpqf : ∀ a b, q a → p b → p (f a b)) (px : p x)
(q_s : ∀ a ∈ s, q a) : p (foldr f H x s) := by
induction s using Multiset.induction with
| empty => simpa
| cons a s ihs =>
simp only [forall_mem_cons, foldr_cons] at q_s ⊢
exact hpqf _ _ q_s.1 (ihs q_s.2)
#align multiset.foldr_induction' Multiset.foldr_induction'
theorem foldr_induction (f : α → α → α) (H : LeftCommutative f) (x : α) (p : α → Prop)
(s : Multiset α) (p_f : ∀ a b, p a → p b → p (f a b)) (px : p x) (p_s : ∀ a ∈ s, p a) :
p (foldr f H x s) :=
foldr_induction' f H x p p s p_f px p_s
#align multiset.foldr_induction Multiset.foldr_induction
theorem foldl_induction' (f : β → α → β) (H : RightCommutative f) (x : β) (q : α → Prop)
(p : β → Prop) (s : Multiset α) (hpqf : ∀ a b, q a → p b → p (f b a)) (px : p x)
(q_s : ∀ a ∈ s, q a) : p (foldl f H x s) := by
rw [foldl_swap]
exact foldr_induction' (fun x y => f y x) (fun x y z => (H _ _ _).symm) x q p s hpqf px q_s
#align multiset.foldl_induction' Multiset.foldl_induction'
theorem foldl_induction (f : α → α → α) (H : RightCommutative f) (x : α) (p : α → Prop)
(s : Multiset α) (p_f : ∀ a b, p a → p b → p (f b a)) (px : p x) (p_s : ∀ a ∈ s, p a) :
p (foldl f H x s) :=
foldl_induction' f H x p p s p_f px p_s
#align multiset.foldl_induction Multiset.foldl_induction
/-! ### Map for partial functions -/
/-- Lift of the list `pmap` operation. Map a partial function `f` over a multiset
`s` whose elements are all in the domain of `f`. -/
nonrec def pmap {p : α → Prop} (f : ∀ a, p a → β) (s : Multiset α) : (∀ a ∈ s, p a) → Multiset β :=
Quot.recOn' s (fun l H => ↑(pmap f l H)) fun l₁ l₂ (pp : l₁ ~ l₂) =>
funext fun H₂ : ∀ a ∈ l₂, p a =>
have H₁ : ∀ a ∈ l₁, p a := fun a h => H₂ a (pp.subset h)
have : ∀ {s₂ e H}, @Eq.ndrec (Multiset α) l₁ (fun s => (∀ a ∈ s, p a) → Multiset β)
(fun _ => ↑(pmap f l₁ H₁)) s₂ e H = ↑(pmap f l₁ H₁) := by
intro s₂ e _; subst e; rfl
this.trans <| Quot.sound <| pp.pmap f
#align multiset.pmap Multiset.pmap
@[simp]
theorem coe_pmap {p : α → Prop} (f : ∀ a, p a → β) (l : List α) (H : ∀ a ∈ l, p a) :
pmap f l H = l.pmap f H :=
rfl
#align multiset.coe_pmap Multiset.coe_pmap
@[simp]
theorem pmap_zero {p : α → Prop} (f : ∀ a, p a → β) (h : ∀ a ∈ (0 : Multiset α), p a) :
pmap f 0 h = 0 :=
rfl
#align multiset.pmap_zero Multiset.pmap_zero
@[simp]
theorem pmap_cons {p : α → Prop} (f : ∀ a, p a → β) (a : α) (m : Multiset α) :
∀ h : ∀ b ∈ a ::ₘ m, p b,
pmap f (a ::ₘ m) h =
f a (h a (mem_cons_self a m)) ::ₘ pmap f m fun a ha => h a <| mem_cons_of_mem ha :=
Quotient.inductionOn m fun _l _h => rfl
#align multiset.pmap_cons Multiset.pmap_cons
/-- "Attach" a proof that `a ∈ s` to each element `a` in `s` to produce
a multiset on `{x // x ∈ s}`. -/
def attach (s : Multiset α) : Multiset { x // x ∈ s } :=
pmap Subtype.mk s fun _a => id
#align multiset.attach Multiset.attach
@[simp]
theorem coe_attach (l : List α) : @Eq (Multiset { x // x ∈ l }) (@attach α l) l.attach :=
rfl
#align multiset.coe_attach Multiset.coe_attach
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Multiset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
induction' s using Quot.inductionOn with l a b
exact List.sizeOf_lt_sizeOf_of_mem hx
#align multiset.sizeof_lt_sizeof_of_mem Multiset.sizeOf_lt_sizeOf_of_mem
theorem pmap_eq_map (p : α → Prop) (f : α → β) (s : Multiset α) :
∀ H, @pmap _ _ p (fun a _ => f a) s H = map f s :=
Quot.inductionOn s fun l H => congr_arg _ <| List.pmap_eq_map p f l H
#align multiset.pmap_eq_map Multiset.pmap_eq_map
theorem pmap_congr {p q : α → Prop} {f : ∀ a, p a → β} {g : ∀ a, q a → β} (s : Multiset α) :
∀ {H₁ H₂}, (∀ a ∈ s, ∀ (h₁ h₂), f a h₁ = g a h₂) → pmap f s H₁ = pmap g s H₂ :=
@(Quot.inductionOn s (fun l _H₁ _H₂ h => congr_arg _ <| List.pmap_congr l h))
#align multiset.pmap_congr Multiset.pmap_congr
theorem map_pmap {p : α → Prop} (g : β → γ) (f : ∀ a, p a → β) (s) :
∀ H, map g (pmap f s H) = pmap (fun a h => g (f a h)) s H :=
Quot.inductionOn s fun l H => congr_arg _ <| List.map_pmap g f l H
#align multiset.map_pmap Multiset.map_pmap
theorem pmap_eq_map_attach {p : α → Prop} (f : ∀ a, p a → β) (s) :
∀ H, pmap f s H = s.attach.map fun x => f x.1 (H _ x.2) :=
Quot.inductionOn s fun l H => congr_arg _ <| List.pmap_eq_map_attach f l H
#align multiset.pmap_eq_map_attach Multiset.pmap_eq_map_attach
-- @[simp] -- Porting note: Left hand does not simplify
theorem attach_map_val' (s : Multiset α) (f : α → β) : (s.attach.map fun i => f i.val) = s.map f :=
Quot.inductionOn s fun l => congr_arg _ <| List.attach_map_coe' l f
#align multiset.attach_map_coe' Multiset.attach_map_val'
#align multiset.attach_map_val' Multiset.attach_map_val'
@[simp]
theorem attach_map_val (s : Multiset α) : s.attach.map Subtype.val = s :=
(attach_map_val' _ _).trans s.map_id
#align multiset.attach_map_coe Multiset.attach_map_val
#align multiset.attach_map_val Multiset.attach_map_val
@[simp]
theorem mem_attach (s : Multiset α) : ∀ x, x ∈ s.attach :=
Quot.inductionOn s fun _l => List.mem_attach _
#align multiset.mem_attach Multiset.mem_attach
@[simp]
theorem mem_pmap {p : α → Prop} {f : ∀ a, p a → β} {s H b} :
b ∈ pmap f s H ↔ ∃ (a : _) (h : a ∈ s), f a (H a h) = b :=
Quot.inductionOn s (fun _l _H => List.mem_pmap) H
#align multiset.mem_pmap Multiset.mem_pmap
@[simp]
theorem card_pmap {p : α → Prop} (f : ∀ a, p a → β) (s H) : card (pmap f s H) = card s :=
Quot.inductionOn s (fun _l _H => length_pmap) H
#align multiset.card_pmap Multiset.card_pmap
@[simp]
theorem card_attach {m : Multiset α} : card (attach m) = card m :=
card_pmap _ _ _
#align multiset.card_attach Multiset.card_attach
@[simp]
theorem attach_zero : (0 : Multiset α).attach = 0 :=
rfl
#align multiset.attach_zero Multiset.attach_zero
theorem attach_cons (a : α) (m : Multiset α) :
(a ::ₘ m).attach =
⟨a, mem_cons_self a m⟩ ::ₘ m.attach.map fun p => ⟨p.1, mem_cons_of_mem p.2⟩ :=
Quotient.inductionOn m fun l =>
congr_arg _ <|
congr_arg (List.cons _) <| by
rw [List.map_pmap]; exact List.pmap_congr _ fun _ _ _ _ => Subtype.eq rfl
#align multiset.attach_cons Multiset.attach_cons
section DecidablePiExists
variable {m : Multiset α}
/-- If `p` is a decidable predicate,
so is the predicate that all elements of a multiset satisfy `p`. -/
protected def decidableForallMultiset {p : α → Prop} [hp : ∀ a, Decidable (p a)] :
Decidable (∀ a ∈ m, p a) :=
Quotient.recOnSubsingleton m fun l => decidable_of_iff (∀ a ∈ l, p a) <| by simp
#align multiset.decidable_forall_multiset Multiset.decidableForallMultiset
instance decidableDforallMultiset {p : ∀ a ∈ m, Prop} [_hp : ∀ (a) (h : a ∈ m), Decidable (p a h)] :
Decidable (∀ (a) (h : a ∈ m), p a h) :=
@decidable_of_iff _ _
(Iff.intro (fun h a ha => h ⟨a, ha⟩ (mem_attach _ _)) fun h ⟨_a, _ha⟩ _ => h _ _)
(@Multiset.decidableForallMultiset _ m.attach (fun a => p a.1 a.2) _)
#align multiset.decidable_dforall_multiset Multiset.decidableDforallMultiset
/-- decidable equality for functions whose domain is bounded by multisets -/
instance decidableEqPiMultiset {β : α → Type*} [h : ∀ a, DecidableEq (β a)] :
DecidableEq (∀ a ∈ m, β a) := fun f g =>
decidable_of_iff (∀ (a) (h : a ∈ m), f a h = g a h) (by simp [Function.funext_iff])
#align multiset.decidable_eq_pi_multiset Multiset.decidableEqPiMultiset
/-- If `p` is a decidable predicate,
so is the existence of an element in a multiset satisfying `p`. -/
protected def decidableExistsMultiset {p : α → Prop} [DecidablePred p] : Decidable (∃ x ∈ m, p x) :=
Quotient.recOnSubsingleton m fun l => decidable_of_iff (∃ a ∈ l, p a) <| by simp
#align multiset.decidable_exists_multiset Multiset.decidableExistsMultiset
instance decidableDexistsMultiset {p : ∀ a ∈ m, Prop} [_hp : ∀ (a) (h : a ∈ m), Decidable (p a h)] :
Decidable (∃ (a : _) (h : a ∈ m), p a h) :=
@decidable_of_iff _ _
(Iff.intro (fun ⟨⟨a, ha₁⟩, _, ha₂⟩ => ⟨a, ha₁, ha₂⟩) fun ⟨a, ha₁, ha₂⟩ =>
⟨⟨a, ha₁⟩, mem_attach _ _, ha₂⟩)
(@Multiset.decidableExistsMultiset { a // a ∈ m } m.attach (fun a => p a.1 a.2) _)
#align multiset.decidable_dexists_multiset Multiset.decidableDexistsMultiset
end DecidablePiExists
/-! ### Subtraction -/
section
variable [DecidableEq α] {s t u : Multiset α} {a b : α}
/-- `s - t` is the multiset such that `count a (s - t) = count a s - count a t` for all `a`
(note that it is truncated subtraction, so it is `0` if `count a t ≥ count a s`). -/
protected def sub (s t : Multiset α) : Multiset α :=
(Quotient.liftOn₂ s t fun l₁ l₂ => (l₁.diff l₂ : Multiset α)) fun _v₁ _v₂ _w₁ _w₂ p₁ p₂ =>
Quot.sound <| p₁.diff p₂
#align multiset.sub Multiset.sub
instance : Sub (Multiset α) :=
⟨Multiset.sub⟩
@[simp]
theorem coe_sub (s t : List α) : (s - t : Multiset α) = (s.diff t : List α) :=
rfl
#align multiset.coe_sub Multiset.coe_sub
/-- This is a special case of `tsub_zero`, which should be used instead of this.
This is needed to prove `OrderedSub (Multiset α)`. -/
protected theorem sub_zero (s : Multiset α) : s - 0 = s :=
Quot.inductionOn s fun _l => rfl
#align multiset.sub_zero Multiset.sub_zero
@[simp]
theorem sub_cons (a : α) (s t : Multiset α) : s - a ::ₘ t = s.erase a - t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => congr_arg _ <| diff_cons _ _ _
#align multiset.sub_cons Multiset.sub_cons
/-- This is a special case of `tsub_le_iff_right`, which should be used instead of this.
This is needed to prove `OrderedSub (Multiset α)`. -/
protected theorem sub_le_iff_le_add : s - t ≤ u ↔ s ≤ u + t := by
revert s
exact @(Multiset.induction_on t (by simp [Multiset.sub_zero]) fun a t IH s => by
simp [IH, erase_le_iff_le_cons])
#align multiset.sub_le_iff_le_add Multiset.sub_le_iff_le_add
instance : OrderedSub (Multiset α) :=
⟨fun _n _m _k => Multiset.sub_le_iff_le_add⟩
theorem cons_sub_of_le (a : α) {s t : Multiset α} (h : t ≤ s) : a ::ₘ s - t = a ::ₘ (s - t) := by
rw [← singleton_add, ← singleton_add, add_tsub_assoc_of_le h]
#align multiset.cons_sub_of_le Multiset.cons_sub_of_le
theorem sub_eq_fold_erase (s t : Multiset α) : s - t = foldl erase erase_comm s t :=
Quotient.inductionOn₂ s t fun l₁ l₂ => by
show ofList (l₁.diff l₂) = foldl erase erase_comm l₁ l₂
rw [diff_eq_foldl l₁ l₂]
symm
exact foldl_hom _ _ _ _ _ fun x y => rfl
#align multiset.sub_eq_fold_erase Multiset.sub_eq_fold_erase
@[simp]
theorem card_sub {s t : Multiset α} (h : t ≤ s) : card (s - t) = card s - card t :=
Nat.eq_sub_of_add_eq $ by rw [← card_add, tsub_add_cancel_of_le h]
#align multiset.card_sub Multiset.card_sub
/-! ### Union -/
/-- `s ∪ t` is the lattice join operation with respect to the
multiset `≤`. The multiplicity of `a` in `s ∪ t` is the maximum
of the multiplicities in `s` and `t`. -/
def union (s t : Multiset α) : Multiset α :=
s - t + t
#align multiset.union Multiset.union
instance : Union (Multiset α) :=
⟨union⟩
theorem union_def (s t : Multiset α) : s ∪ t = s - t + t :=
rfl
#align multiset.union_def Multiset.union_def
theorem le_union_left (s t : Multiset α) : s ≤ s ∪ t :=
le_tsub_add
#align multiset.le_union_left Multiset.le_union_left
theorem le_union_right (s t : Multiset α) : t ≤ s ∪ t :=
le_add_left _ _
#align multiset.le_union_right Multiset.le_union_right
theorem eq_union_left : t ≤ s → s ∪ t = s :=
tsub_add_cancel_of_le
#align multiset.eq_union_left Multiset.eq_union_left
theorem union_le_union_right (h : s ≤ t) (u) : s ∪ u ≤ t ∪ u :=
add_le_add_right (tsub_le_tsub_right h _) u
#align multiset.union_le_union_right Multiset.union_le_union_right
theorem union_le (h₁ : s ≤ u) (h₂ : t ≤ u) : s ∪ t ≤ u := by
rw [← eq_union_left h₂]; exact union_le_union_right h₁ t
#align multiset.union_le Multiset.union_le
@[simp]
theorem mem_union : a ∈ s ∪ t ↔ a ∈ s ∨ a ∈ t :=
⟨fun h => (mem_add.1 h).imp_left (mem_of_le tsub_le_self),
(Or.elim · (mem_of_le <| le_union_left _ _) (mem_of_le <| le_union_right _ _))⟩
#align multiset.mem_union Multiset.mem_union
@[simp]
theorem map_union [DecidableEq β] {f : α → β} (finj : Function.Injective f) {s t : Multiset α} :
map f (s ∪ t) = map f s ∪ map f t :=
Quotient.inductionOn₂ s t fun l₁ l₂ =>
congr_arg ofList (by rw [List.map_append f, List.map_diff finj])
#align multiset.map_union Multiset.map_union
-- Porting note (#10756): new theorem
@[simp] theorem zero_union : 0 ∪ s = s := by
simp [union_def]
-- Porting note (#10756): new theorem
@[simp] theorem union_zero : s ∪ 0 = s := by
simp [union_def]
/-! ### Intersection -/
/-- `s ∩ t` is the lattice meet operation with respect to the
multiset `≤`. The multiplicity of `a` in `s ∩ t` is the minimum
of the multiplicities in `s` and `t`. -/
def inter (s t : Multiset α) : Multiset α :=
Quotient.liftOn₂ s t (fun l₁ l₂ => (l₁.bagInter l₂ : Multiset α)) fun _v₁ _v₂ _w₁ _w₂ p₁ p₂ =>
Quot.sound <| p₁.bagInter p₂
#align multiset.inter Multiset.inter
instance : Inter (Multiset α) :=
⟨inter⟩
@[simp]
theorem inter_zero (s : Multiset α) : s ∩ 0 = 0 :=
Quot.inductionOn s fun l => congr_arg ofList l.bagInter_nil
#align multiset.inter_zero Multiset.inter_zero
@[simp]
theorem zero_inter (s : Multiset α) : 0 ∩ s = 0 :=
Quot.inductionOn s fun l => congr_arg ofList l.nil_bagInter
#align multiset.zero_inter Multiset.zero_inter
@[simp]
theorem cons_inter_of_pos {a} (s : Multiset α) {t} : a ∈ t → (a ::ₘ s) ∩ t = a ::ₘ s ∩ t.erase a :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ h => congr_arg ofList <| cons_bagInter_of_pos _ h
#align multiset.cons_inter_of_pos Multiset.cons_inter_of_pos
@[simp]
theorem cons_inter_of_neg {a} (s : Multiset α) {t} : a ∉ t → (a ::ₘ s) ∩ t = s ∩ t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ h => congr_arg ofList <| cons_bagInter_of_neg _ h
#align multiset.cons_inter_of_neg Multiset.cons_inter_of_neg
theorem inter_le_left (s t : Multiset α) : s ∩ t ≤ s :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => (bagInter_sublist_left _ _).subperm
#align multiset.inter_le_left Multiset.inter_le_left
theorem inter_le_right (s : Multiset α) : ∀ t, s ∩ t ≤ t :=
Multiset.induction_on s (fun t => (zero_inter t).symm ▸ zero_le _) fun a s IH t =>
if h : a ∈ t then by simpa [h] using cons_le_cons a (IH (t.erase a)) else by simp [h, IH]
#align multiset.inter_le_right Multiset.inter_le_right
theorem le_inter (h₁ : s ≤ t) (h₂ : s ≤ u) : s ≤ t ∩ u := by
revert s u; refine @(Multiset.induction_on t ?_ fun a t IH => ?_) <;> intros s u h₁ h₂
· simpa only [zero_inter, nonpos_iff_eq_zero] using h₁
by_cases h : a ∈ u
· rw [cons_inter_of_pos _ h, ← erase_le_iff_le_cons]
exact IH (erase_le_iff_le_cons.2 h₁) (erase_le_erase _ h₂)
· rw [cons_inter_of_neg _ h]
exact IH ((le_cons_of_not_mem <| mt (mem_of_le h₂) h).1 h₁) h₂
#align multiset.le_inter Multiset.le_inter
@[simp]
theorem mem_inter : a ∈ s ∩ t ↔ a ∈ s ∧ a ∈ t :=
⟨fun h => ⟨mem_of_le (inter_le_left _ _) h, mem_of_le (inter_le_right _ _) h⟩, fun ⟨h₁, h₂⟩ => by
rw [← cons_erase h₁, cons_inter_of_pos _ h₂]; apply mem_cons_self⟩
#align multiset.mem_inter Multiset.mem_inter
instance : Lattice (Multiset α) :=
{ sup := (· ∪ ·)
sup_le := @union_le _ _
le_sup_left := le_union_left
le_sup_right := le_union_right
inf := (· ∩ ·)
le_inf := @le_inter _ _
inf_le_left := inter_le_left
inf_le_right := inter_le_right }
@[simp]
theorem sup_eq_union (s t : Multiset α) : s ⊔ t = s ∪ t :=
rfl
#align multiset.sup_eq_union Multiset.sup_eq_union
@[simp]
theorem inf_eq_inter (s t : Multiset α) : s ⊓ t = s ∩ t :=
rfl
#align multiset.inf_eq_inter Multiset.inf_eq_inter
@[simp]
theorem le_inter_iff : s ≤ t ∩ u ↔ s ≤ t ∧ s ≤ u :=
le_inf_iff
#align multiset.le_inter_iff Multiset.le_inter_iff
@[simp]
theorem union_le_iff : s ∪ t ≤ u ↔ s ≤ u ∧ t ≤ u :=
sup_le_iff
#align multiset.union_le_iff Multiset.union_le_iff
theorem union_comm (s t : Multiset α) : s ∪ t = t ∪ s := sup_comm _ _
#align multiset.union_comm Multiset.union_comm
theorem inter_comm (s t : Multiset α) : s ∩ t = t ∩ s := inf_comm _ _
#align multiset.inter_comm Multiset.inter_comm
theorem eq_union_right (h : s ≤ t) : s ∪ t = t := by rw [union_comm, eq_union_left h]
#align multiset.eq_union_right Multiset.eq_union_right
theorem union_le_union_left (h : s ≤ t) (u) : u ∪ s ≤ u ∪ t :=
sup_le_sup_left h _
#align multiset.union_le_union_left Multiset.union_le_union_left
theorem union_le_add (s t : Multiset α) : s ∪ t ≤ s + t :=
union_le (le_add_right _ _) (le_add_left _ _)
#align multiset.union_le_add Multiset.union_le_add
theorem union_add_distrib (s t u : Multiset α) : s ∪ t + u = s + u ∪ (t + u) := by
simpa [(· ∪ ·), union, eq_comm, add_assoc] using
show s + u - (t + u) = s - t by rw [add_comm t, tsub_add_eq_tsub_tsub, add_tsub_cancel_right]
#align multiset.union_add_distrib Multiset.union_add_distrib
theorem add_union_distrib (s t u : Multiset α) : s + (t ∪ u) = s + t ∪ (s + u) := by
rw [add_comm, union_add_distrib, add_comm s, add_comm s]
#align multiset.add_union_distrib Multiset.add_union_distrib
theorem cons_union_distrib (a : α) (s t : Multiset α) : a ::ₘ (s ∪ t) = a ::ₘ s ∪ a ::ₘ t := by
simpa using add_union_distrib (a ::ₘ 0) s t
#align multiset.cons_union_distrib Multiset.cons_union_distrib
theorem inter_add_distrib (s t u : Multiset α) : s ∩ t + u = (s + u) ∩ (t + u) := by
by_contra h
cases'
lt_iff_cons_le.1
(lt_of_le_of_ne
(le_inter (add_le_add_right (inter_le_left s t) u)
(add_le_add_right (inter_le_right s t) u))
h) with
a hl
rw [← cons_add] at hl
exact
not_le_of_lt (lt_cons_self (s ∩ t) a)
(le_inter (le_of_add_le_add_right (le_trans hl (inter_le_left _ _)))
(le_of_add_le_add_right (le_trans hl (inter_le_right _ _))))
#align multiset.inter_add_distrib Multiset.inter_add_distrib
theorem add_inter_distrib (s t u : Multiset α) : s + t ∩ u = (s + t) ∩ (s + u) := by
rw [add_comm, inter_add_distrib, add_comm s, add_comm s]
#align multiset.add_inter_distrib Multiset.add_inter_distrib
theorem cons_inter_distrib (a : α) (s t : Multiset α) : a ::ₘ s ∩ t = (a ::ₘ s) ∩ (a ::ₘ t) := by
simp
#align multiset.cons_inter_distrib Multiset.cons_inter_distrib
theorem union_add_inter (s t : Multiset α) : s ∪ t + s ∩ t = s + t := by
apply _root_.le_antisymm
· rw [union_add_distrib]
refine union_le (add_le_add_left (inter_le_right _ _) _) ?_
rw [add_comm]
exact add_le_add_right (inter_le_left _ _) _
· rw [add_comm, add_inter_distrib]
refine le_inter (add_le_add_right (le_union_right _ _) _) ?_
rw [add_comm]
exact add_le_add_right (le_union_left _ _) _
#align multiset.union_add_inter Multiset.union_add_inter
theorem sub_add_inter (s t : Multiset α) : s - t + s ∩ t = s := by
rw [inter_comm]
revert s; refine Multiset.induction_on t (by simp) fun a t IH s => ?_
by_cases h : a ∈ s
· rw [cons_inter_of_pos _ h, sub_cons, add_cons, IH, cons_erase h]
· rw [cons_inter_of_neg _ h, sub_cons, erase_of_not_mem h, IH]
#align multiset.sub_add_inter Multiset.sub_add_inter
theorem sub_inter (s t : Multiset α) : s - s ∩ t = s - t :=
add_right_cancel <| by rw [sub_add_inter s t, tsub_add_cancel_of_le (inter_le_left s t)]
#align multiset.sub_inter Multiset.sub_inter
end
/-! ### `Multiset.filter` -/
section
variable (p : α → Prop) [DecidablePred p]
/-- `Filter p s` returns the elements in `s` (with the same multiplicities)
which satisfy `p`, and removes the rest. -/
def filter (s : Multiset α) : Multiset α :=
Quot.liftOn s (fun l => (List.filter p l : Multiset α)) fun _l₁ _l₂ h => Quot.sound <| h.filter p
#align multiset.filter Multiset.filter
@[simp, norm_cast] lemma filter_coe (l : List α) : filter p l = l.filter p := rfl
#align multiset.coe_filter Multiset.filter_coe
@[simp]
theorem filter_zero : filter p 0 = 0 :=
rfl
#align multiset.filter_zero Multiset.filter_zero
theorem filter_congr {p q : α → Prop} [DecidablePred p] [DecidablePred q] {s : Multiset α} :
(∀ x ∈ s, p x ↔ q x) → filter p s = filter q s :=
Quot.inductionOn s fun _l h => congr_arg ofList <| filter_congr' <| by simpa using h
#align multiset.filter_congr Multiset.filter_congr
@[simp]
theorem filter_add (s t : Multiset α) : filter p (s + t) = filter p s + filter p t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => congr_arg ofList <| filter_append _ _
#align multiset.filter_add Multiset.filter_add
@[simp]
theorem filter_le (s : Multiset α) : filter p s ≤ s :=
Quot.inductionOn s fun _l => (filter_sublist _).subperm
#align multiset.filter_le Multiset.filter_le
@[simp]
theorem filter_subset (s : Multiset α) : filter p s ⊆ s :=
subset_of_le <| filter_le _ _
#align multiset.filter_subset Multiset.filter_subset
theorem filter_le_filter {s t} (h : s ≤ t) : filter p s ≤ filter p t :=
leInductionOn h fun h => (h.filter (p ·)).subperm
#align multiset.filter_le_filter Multiset.filter_le_filter
theorem monotone_filter_left : Monotone (filter p) := fun _s _t => filter_le_filter p
#align multiset.monotone_filter_left Multiset.monotone_filter_left
theorem monotone_filter_right (s : Multiset α) ⦃p q : α → Prop⦄ [DecidablePred p] [DecidablePred q]
(h : ∀ b, p b → q b) :
s.filter p ≤ s.filter q :=
Quotient.inductionOn s fun l => (l.monotone_filter_right <| by simpa using h).subperm
#align multiset.monotone_filter_right Multiset.monotone_filter_right
variable {p}
@[simp]
theorem filter_cons_of_pos {a : α} (s) : p a → filter p (a ::ₘ s) = a ::ₘ filter p s :=
Quot.inductionOn s fun l h => congr_arg ofList <| List.filter_cons_of_pos l <| by simpa using h
#align multiset.filter_cons_of_pos Multiset.filter_cons_of_pos
@[simp]
theorem filter_cons_of_neg {a : α} (s) : ¬p a → filter p (a ::ₘ s) = filter p s :=
Quot.inductionOn s fun l h => congr_arg ofList <| List.filter_cons_of_neg l <| by simpa using h
#align multiset.filter_cons_of_neg Multiset.filter_cons_of_neg
@[simp]
theorem mem_filter {a : α} {s} : a ∈ filter p s ↔ a ∈ s ∧ p a :=
Quot.inductionOn s fun _l => by simpa using List.mem_filter (p := (p ·))
#align multiset.mem_filter Multiset.mem_filter
theorem of_mem_filter {a : α} {s} (h : a ∈ filter p s) : p a :=
(mem_filter.1 h).2
#align multiset.of_mem_filter Multiset.of_mem_filter
theorem mem_of_mem_filter {a : α} {s} (h : a ∈ filter p s) : a ∈ s :=
(mem_filter.1 h).1
#align multiset.mem_of_mem_filter Multiset.mem_of_mem_filter
theorem mem_filter_of_mem {a : α} {l} (m : a ∈ l) (h : p a) : a ∈ filter p l :=
mem_filter.2 ⟨m, h⟩
#align multiset.mem_filter_of_mem Multiset.mem_filter_of_mem
theorem filter_eq_self {s} : filter p s = s ↔ ∀ a ∈ s, p a :=
Quot.inductionOn s fun _l =>
Iff.trans ⟨fun h => (filter_sublist _).eq_of_length (@congr_arg _ _ _ _ card h),
congr_arg ofList⟩ <| by simp
#align multiset.filter_eq_self Multiset.filter_eq_self
theorem filter_eq_nil {s} : filter p s = 0 ↔ ∀ a ∈ s, ¬p a :=
Quot.inductionOn s fun _l =>
Iff.trans ⟨fun h => eq_nil_of_length_eq_zero (@congr_arg _ _ _ _ card h), congr_arg ofList⟩ <|
by simpa using List.filter_eq_nil (p := (p ·))
#align multiset.filter_eq_nil Multiset.filter_eq_nil
theorem le_filter {s t} : s ≤ filter p t ↔ s ≤ t ∧ ∀ a ∈ s, p a :=
⟨fun h => ⟨le_trans h (filter_le _ _), fun _a m => of_mem_filter (mem_of_le h m)⟩, fun ⟨h, al⟩ =>
filter_eq_self.2 al ▸ filter_le_filter p h⟩
#align multiset.le_filter Multiset.le_filter
theorem filter_cons {a : α} (s : Multiset α) :
filter p (a ::ₘ s) = (if p a then {a} else 0) + filter p s := by
split_ifs with h
· rw [filter_cons_of_pos _ h, singleton_add]
· rw [filter_cons_of_neg _ h, zero_add]
#align multiset.filter_cons Multiset.filter_cons
theorem filter_singleton {a : α} (p : α → Prop) [DecidablePred p] :
filter p {a} = if p a then {a} else ∅ := by
simp only [singleton, filter_cons, filter_zero, add_zero, empty_eq_zero]
#align multiset.filter_singleton Multiset.filter_singleton
theorem filter_nsmul (s : Multiset α) (n : ℕ) : filter p (n • s) = n • filter p s := by
refine s.induction_on ?_ ?_
· simp only [filter_zero, nsmul_zero]
· intro a ha ih
rw [nsmul_cons, filter_add, ih, filter_cons, nsmul_add]
congr
split_ifs with hp <;>
· simp only [filter_eq_self, nsmul_zero, filter_eq_nil]
intro b hb
rwa [mem_singleton.mp (mem_of_mem_nsmul hb)]
#align multiset.filter_nsmul Multiset.filter_nsmul
variable (p)
@[simp]
theorem filter_sub [DecidableEq α] (s t : Multiset α) :
filter p (s - t) = filter p s - filter p t := by
revert s; refine Multiset.induction_on t (by simp) fun a t IH s => ?_
rw [sub_cons, IH]
by_cases h : p a
· rw [filter_cons_of_pos _ h, sub_cons]
congr
by_cases m : a ∈ s
· rw [← cons_inj_right a, ← filter_cons_of_pos _ h, cons_erase (mem_filter_of_mem m h),
cons_erase m]
· rw [erase_of_not_mem m, erase_of_not_mem (mt mem_of_mem_filter m)]
· rw [filter_cons_of_neg _ h]
by_cases m : a ∈ s
· rw [(by rw [filter_cons_of_neg _ h] : filter p (erase s a) = filter p (a ::ₘ erase s a)),
cons_erase m]
· rw [erase_of_not_mem m]
#align multiset.filter_sub Multiset.filter_sub
@[simp]
theorem filter_union [DecidableEq α] (s t : Multiset α) :
filter p (s ∪ t) = filter p s ∪ filter p t := by simp [(· ∪ ·), union]
#align multiset.filter_union Multiset.filter_union
@[simp]
theorem filter_inter [DecidableEq α] (s t : Multiset α) :
filter p (s ∩ t) = filter p s ∩ filter p t :=
le_antisymm
(le_inter (filter_le_filter _ <| inter_le_left _ _)
(filter_le_filter _ <| inter_le_right _ _)) <|
le_filter.2
⟨inf_le_inf (filter_le _ _) (filter_le _ _), fun _a h =>
of_mem_filter (mem_of_le (inter_le_left _ _) h)⟩
#align multiset.filter_inter Multiset.filter_inter
@[simp]
theorem filter_filter (q) [DecidablePred q] (s : Multiset α) :
filter p (filter q s) = filter (fun a => p a ∧ q a) s :=
Quot.inductionOn s fun l => by simp
#align multiset.filter_filter Multiset.filter_filter
lemma filter_comm (q) [DecidablePred q] (s : Multiset α) :
filter p (filter q s) = filter q (filter p s) := by simp [and_comm]
#align multiset.filter_comm Multiset.filter_comm
theorem filter_add_filter (q) [DecidablePred q] (s : Multiset α) :
filter p s + filter q s = filter (fun a => p a ∨ q a) s + filter (fun a => p a ∧ q a) s :=
Multiset.induction_on s rfl fun a s IH => by by_cases p a <;> by_cases q a <;> simp [*]
#align multiset.filter_add_filter Multiset.filter_add_filter
theorem filter_add_not (s : Multiset α) : filter p s + filter (fun a => ¬p a) s = s := by
rw [filter_add_filter, filter_eq_self.2, filter_eq_nil.2]
· simp only [add_zero]
· simp [Decidable.em, -Bool.not_eq_true, -not_and, not_and_or, or_comm]
· simp only [Bool.not_eq_true, decide_eq_true_eq, Bool.eq_false_or_eq_true,
decide_True, implies_true, Decidable.em]
#align multiset.filter_add_not Multiset.filter_add_not
theorem map_filter (f : β → α) (s : Multiset β) : filter p (map f s) = map f (filter (p ∘ f) s) :=
Quot.inductionOn s fun l => by simp [List.map_filter]; rfl
#align multiset.map_filter Multiset.map_filter
lemma map_filter' {f : α → β} (hf : Injective f) (s : Multiset α)
[DecidablePred fun b => ∃ a, p a ∧ f a = b] :
(s.filter p).map f = (s.map f).filter fun b => ∃ a, p a ∧ f a = b := by
simp [(· ∘ ·), map_filter, hf.eq_iff]
#align multiset.map_filter' Multiset.map_filter'
lemma card_filter_le_iff (s : Multiset α) (P : α → Prop) [DecidablePred P] (n : ℕ) :
card (s.filter P) ≤ n ↔ ∀ s' ≤ s, n < card s' → ∃ a ∈ s', ¬ P a := by
fconstructor
· intro H s' hs' s'_card
by_contra! rid
have card := card_le_card (monotone_filter_left P hs') |>.trans H
exact s'_card.not_le (filter_eq_self.mpr rid ▸ card)
· contrapose!
exact fun H ↦ ⟨s.filter P, filter_le _ _, H, fun a ha ↦ (mem_filter.mp ha).2⟩
/-! ### Simultaneously filter and map elements of a multiset -/
/-- `filterMap f s` is a combination filter/map operation on `s`.
The function `f : α → Option β` is applied to each element of `s`;
if `f a` is `some b` then `b` is added to the result, otherwise
`a` is removed from the resulting multiset. -/
def filterMap (f : α → Option β) (s : Multiset α) : Multiset β :=
Quot.liftOn s (fun l => (List.filterMap f l : Multiset β))
fun _l₁ _l₂ h => Quot.sound <| h.filterMap f
#align multiset.filter_map Multiset.filterMap
@[simp, norm_cast]
lemma filterMap_coe (f : α → Option β) (l : List α) : filterMap f l = l.filterMap f := rfl
#align multiset.coe_filter_map Multiset.filterMap_coe
@[simp]
theorem filterMap_zero (f : α → Option β) : filterMap f 0 = 0 :=
rfl
#align multiset.filter_map_zero Multiset.filterMap_zero
@[simp]
theorem filterMap_cons_none {f : α → Option β} (a : α) (s : Multiset α) (h : f a = none) :
filterMap f (a ::ₘ s) = filterMap f s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_cons_none a l h
#align multiset.filter_map_cons_none Multiset.filterMap_cons_none
@[simp]
theorem filterMap_cons_some (f : α → Option β) (a : α) (s : Multiset α) {b : β}
(h : f a = some b) : filterMap f (a ::ₘ s) = b ::ₘ filterMap f s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_cons_some f a l h
#align multiset.filter_map_cons_some Multiset.filterMap_cons_some
theorem filterMap_eq_map (f : α → β) : filterMap (some ∘ f) = map f :=
funext fun s =>
Quot.inductionOn s fun l => congr_arg ofList <| congr_fun (List.filterMap_eq_map f) l
#align multiset.filter_map_eq_map Multiset.filterMap_eq_map
theorem filterMap_eq_filter : filterMap (Option.guard p) = filter p :=
funext fun s =>
Quot.inductionOn s fun l => congr_arg ofList <| by
rw [← List.filterMap_eq_filter]
congr; funext a; simp
#align multiset.filter_map_eq_filter Multiset.filterMap_eq_filter
theorem filterMap_filterMap (f : α → Option β) (g : β → Option γ) (s : Multiset α) :
filterMap g (filterMap f s) = filterMap (fun x => (f x).bind g) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_filterMap f g l
#align multiset.filter_map_filter_map Multiset.filterMap_filterMap
theorem map_filterMap (f : α → Option β) (g : β → γ) (s : Multiset α) :
map g (filterMap f s) = filterMap (fun x => (f x).map g) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.map_filterMap f g l
#align multiset.map_filter_map Multiset.map_filterMap
theorem filterMap_map (f : α → β) (g : β → Option γ) (s : Multiset α) :
filterMap g (map f s) = filterMap (g ∘ f) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_map f g l
#align multiset.filter_map_map Multiset.filterMap_map
theorem filter_filterMap (f : α → Option β) (p : β → Prop) [DecidablePred p] (s : Multiset α) :
filter p (filterMap f s) = filterMap (fun x => (f x).filter p) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filter_filterMap f p l
#align multiset.filter_filter_map Multiset.filter_filterMap
theorem filterMap_filter (f : α → Option β) (s : Multiset α) :
filterMap f (filter p s) = filterMap (fun x => if p x then f x else none) s :=
Quot.inductionOn s fun l => congr_arg ofList <| by simpa using List.filterMap_filter p f l
#align multiset.filter_map_filter Multiset.filterMap_filter
@[simp]
theorem filterMap_some (s : Multiset α) : filterMap some s = s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_some l
#align multiset.filter_map_some Multiset.filterMap_some
@[simp]
theorem mem_filterMap (f : α → Option β) (s : Multiset α) {b : β} :
b ∈ filterMap f s ↔ ∃ a, a ∈ s ∧ f a = some b :=
Quot.inductionOn s fun l => List.mem_filterMap f l
#align multiset.mem_filter_map Multiset.mem_filterMap
theorem map_filterMap_of_inv (f : α → Option β) (g : β → α) (H : ∀ x : α, (f x).map g = some x)
(s : Multiset α) : map g (filterMap f s) = s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.map_filterMap_of_inv f g H l
#align multiset.map_filter_map_of_inv Multiset.map_filterMap_of_inv
theorem filterMap_le_filterMap (f : α → Option β) {s t : Multiset α} (h : s ≤ t) :
filterMap f s ≤ filterMap f t :=
leInductionOn h fun h => (h.filterMap _).subperm
#align multiset.filter_map_le_filter_map Multiset.filterMap_le_filterMap
/-! ### countP -/
/-- `countP p s` counts the number of elements of `s` (with multiplicity) that
satisfy `p`. -/
def countP (s : Multiset α) : ℕ :=
Quot.liftOn s (List.countP p) fun _l₁ _l₂ => Perm.countP_eq (p ·)
#align multiset.countp Multiset.countP
@[simp]
theorem coe_countP (l : List α) : countP p l = l.countP p :=
rfl
#align multiset.coe_countp Multiset.coe_countP
@[simp]
theorem countP_zero : countP p 0 = 0 :=
rfl
#align multiset.countp_zero Multiset.countP_zero
variable {p}
@[simp]
theorem countP_cons_of_pos {a : α} (s) : p a → countP p (a ::ₘ s) = countP p s + 1 :=
Quot.inductionOn s <| by simpa using List.countP_cons_of_pos (p ·)
#align multiset.countp_cons_of_pos Multiset.countP_cons_of_pos
@[simp]
theorem countP_cons_of_neg {a : α} (s) : ¬p a → countP p (a ::ₘ s) = countP p s :=
Quot.inductionOn s <| by simpa using List.countP_cons_of_neg (p ·)
#align multiset.countp_cons_of_neg Multiset.countP_cons_of_neg
variable (p)
theorem countP_cons (b : α) (s) : countP p (b ::ₘ s) = countP p s + if p b then 1 else 0 :=
Quot.inductionOn s <| by simp [List.countP_cons]
#align multiset.countp_cons Multiset.countP_cons
theorem countP_eq_card_filter (s) : countP p s = card (filter p s) :=
Quot.inductionOn s fun l => l.countP_eq_length_filter (p ·)
#align multiset.countp_eq_card_filter Multiset.countP_eq_card_filter
theorem countP_le_card (s) : countP p s ≤ card s :=
Quot.inductionOn s fun _l => countP_le_length (p ·)
#align multiset.countp_le_card Multiset.countP_le_card
@[simp]
theorem countP_add (s t) : countP p (s + t) = countP p s + countP p t := by
simp [countP_eq_card_filter]
#align multiset.countp_add Multiset.countP_add
@[simp]
theorem countP_nsmul (s) (n : ℕ) : countP p (n • s) = n * countP p s := by
induction n <;> simp [*, succ_nsmul, succ_mul, zero_nsmul]
#align multiset.countp_nsmul Multiset.countP_nsmul
theorem card_eq_countP_add_countP (s) : card s = countP p s + countP (fun x => ¬p x) s :=
Quot.inductionOn s fun l => by simp [l.length_eq_countP_add_countP p]
#align multiset.card_eq_countp_add_countp Multiset.card_eq_countP_add_countP
/-- `countP p`, the number of elements of a multiset satisfying `p`, promoted to an
`AddMonoidHom`. -/
def countPAddMonoidHom : Multiset α →+ ℕ where
toFun := countP p
map_zero' := countP_zero _
map_add' := countP_add _
#align multiset.countp_add_monoid_hom Multiset.countPAddMonoidHom
@[simp]
theorem coe_countPAddMonoidHom : (countPAddMonoidHom p : Multiset α → ℕ) = countP p :=
rfl
#align multiset.coe_countp_add_monoid_hom Multiset.coe_countPAddMonoidHom
@[simp]
theorem countP_sub [DecidableEq α] {s t : Multiset α} (h : t ≤ s) :
countP p (s - t) = countP p s - countP p t := by
simp [countP_eq_card_filter, h, filter_le_filter]
#align multiset.countp_sub Multiset.countP_sub
theorem countP_le_of_le {s t} (h : s ≤ t) : countP p s ≤ countP p t := by
simpa [countP_eq_card_filter] using card_le_card (filter_le_filter p h)
#align multiset.countp_le_of_le Multiset.countP_le_of_le
@[simp]
theorem countP_filter (q) [DecidablePred q] (s : Multiset α) :
countP p (filter q s) = countP (fun a => p a ∧ q a) s := by simp [countP_eq_card_filter]
#align multiset.countp_filter Multiset.countP_filter
theorem countP_eq_countP_filter_add (s) (p q : α → Prop) [DecidablePred p] [DecidablePred q] :
countP p s = (filter q s).countP p + (filter (fun a => ¬q a) s).countP p :=
Quot.inductionOn s fun l => by
convert l.countP_eq_countP_filter_add (p ·) (q ·)
simp [countP_filter]
#align multiset.countp_eq_countp_filter_add Multiset.countP_eq_countP_filter_add
@[simp]
theorem countP_True {s : Multiset α} : countP (fun _ => True) s = card s :=
Quot.inductionOn s fun _l => List.countP_true
#align multiset.countp_true Multiset.countP_True
@[simp]
theorem countP_False {s : Multiset α} : countP (fun _ => False) s = 0 :=
Quot.inductionOn s fun _l => List.countP_false
#align multiset.countp_false Multiset.countP_False
theorem countP_map (f : α → β) (s : Multiset α) (p : β → Prop) [DecidablePred p] :
countP p (map f s) = card (s.filter fun a => p (f a)) := by
refine Multiset.induction_on s ?_ fun a t IH => ?_
· rw [map_zero, countP_zero, filter_zero, card_zero]
· rw [map_cons, countP_cons, IH, filter_cons, card_add, apply_ite card, card_zero, card_singleton,
add_comm]
#align multiset.countp_map Multiset.countP_map
-- Porting note: `Lean.Internal.coeM` forces us to type-ascript `{a // a ∈ s}`
lemma countP_attach (s : Multiset α) : s.attach.countP (fun a : {a // a ∈ s} ↦ p a) = s.countP p :=
Quotient.inductionOn s fun l => by
simp only [quot_mk_to_coe, coe_countP]
-- Porting note: was
-- rw [quot_mk_to_coe, coe_attach, coe_countP]
-- exact List.countP_attach _ _
rw [coe_attach]
refine (coe_countP _ _).trans ?_
convert List.countP_attach _ _
rfl
#align multiset.countp_attach Multiset.countP_attach
lemma filter_attach (s : Multiset α) (p : α → Prop) [DecidablePred p] :
(s.attach.filter fun a : {a // a ∈ s} ↦ p ↑a) =
(s.filter p).attach.map (Subtype.map id fun _ ↦ Multiset.mem_of_mem_filter) :=
Quotient.inductionOn s fun l ↦ congr_arg _ (List.filter_attach l p)
#align multiset.filter_attach Multiset.filter_attach
variable {p}
theorem countP_pos {s} : 0 < countP p s ↔ ∃ a ∈ s, p a :=
Quot.inductionOn s fun _l => by simpa using List.countP_pos (p ·)
#align multiset.countp_pos Multiset.countP_pos
theorem countP_eq_zero {s} : countP p s = 0 ↔ ∀ a ∈ s, ¬p a :=
Quot.inductionOn s fun _l => by simp [List.countP_eq_zero]
#align multiset.countp_eq_zero Multiset.countP_eq_zero
theorem countP_eq_card {s} : countP p s = card s ↔ ∀ a ∈ s, p a :=
Quot.inductionOn s fun _l => by simp [List.countP_eq_length]
#align multiset.countp_eq_card Multiset.countP_eq_card
theorem countP_pos_of_mem {s a} (h : a ∈ s) (pa : p a) : 0 < countP p s :=
countP_pos.2 ⟨_, h, pa⟩
#align multiset.countp_pos_of_mem Multiset.countP_pos_of_mem
theorem countP_congr {s s' : Multiset α} (hs : s = s')
{p p' : α → Prop} [DecidablePred p] [DecidablePred p']
(hp : ∀ x ∈ s, p x = p' x) : s.countP p = s'.countP p' := by
revert hs hp
exact Quot.induction_on₂ s s'
(fun l l' hs hp => by
simp only [quot_mk_to_coe'', coe_eq_coe] at hs
apply hs.countP_congr
simpa using hp)
#align multiset.countp_congr Multiset.countP_congr
end
/-! ### Multiplicity of an element -/
section
variable [DecidableEq α] {s : Multiset α}
/-- `count a s` is the multiplicity of `a` in `s`. -/
def count (a : α) : Multiset α → ℕ :=
countP (a = ·)
#align multiset.count Multiset.count
@[simp]
theorem coe_count (a : α) (l : List α) : count a (ofList l) = l.count a := by
simp_rw [count, List.count, coe_countP (a = ·) l, @eq_comm _ a]
rfl
#align multiset.coe_count Multiset.coe_count
@[simp, nolint simpNF] -- Porting note (#10618): simp can prove this at EOF, but not right now
theorem count_zero (a : α) : count a 0 = 0 :=
rfl
#align multiset.count_zero Multiset.count_zero
@[simp]
theorem count_cons_self (a : α) (s : Multiset α) : count a (a ::ₘ s) = count a s + 1 :=
countP_cons_of_pos _ <| rfl
#align multiset.count_cons_self Multiset.count_cons_self
@[simp]
theorem count_cons_of_ne {a b : α} (h : a ≠ b) (s : Multiset α) : count a (b ::ₘ s) = count a s :=
countP_cons_of_neg _ <| h
#align multiset.count_cons_of_ne Multiset.count_cons_of_ne
theorem count_le_card (a : α) (s) : count a s ≤ card s :=
countP_le_card _ _
#align multiset.count_le_card Multiset.count_le_card
theorem count_le_of_le (a : α) {s t} : s ≤ t → count a s ≤ count a t :=
countP_le_of_le _
#align multiset.count_le_of_le Multiset.count_le_of_le
theorem count_le_count_cons (a b : α) (s : Multiset α) : count a s ≤ count a (b ::ₘ s) :=
count_le_of_le _ (le_cons_self _ _)
#align multiset.count_le_count_cons Multiset.count_le_count_cons
theorem count_cons (a b : α) (s : Multiset α) :
count a (b ::ₘ s) = count a s + if a = b then 1 else 0 :=
countP_cons (a = ·) _ _
#align multiset.count_cons Multiset.count_cons
theorem count_singleton_self (a : α) : count a ({a} : Multiset α) = 1 :=
count_eq_one_of_mem (nodup_singleton a) <| mem_singleton_self a
#align multiset.count_singleton_self Multiset.count_singleton_self
theorem count_singleton (a b : α) : count a ({b} : Multiset α) = if a = b then 1 else 0 := by
simp only [count_cons, ← cons_zero, count_zero, zero_add]
#align multiset.count_singleton Multiset.count_singleton
@[simp]
theorem count_add (a : α) : ∀ s t, count a (s + t) = count a s + count a t :=
countP_add _
#align multiset.count_add Multiset.count_add
/-- `count a`, the multiplicity of `a` in a multiset, promoted to an `AddMonoidHom`. -/
def countAddMonoidHom (a : α) : Multiset α →+ ℕ :=
countPAddMonoidHom (a = ·)
#align multiset.count_add_monoid_hom Multiset.countAddMonoidHom
@[simp]
theorem coe_countAddMonoidHom {a : α} : (countAddMonoidHom a : Multiset α → ℕ) = count a :=
rfl
#align multiset.coe_count_add_monoid_hom Multiset.coe_countAddMonoidHom
@[simp]
theorem count_nsmul (a : α) (n s) : count a (n • s) = n * count a s := by
induction n <;> simp [*, succ_nsmul, succ_mul, zero_nsmul]
#align multiset.count_nsmul Multiset.count_nsmul
@[simp]
lemma count_attach (a : {x // x ∈ s}) : s.attach.count a = s.count ↑a :=
Eq.trans (countP_congr rfl fun _ _ => by simp [Subtype.ext_iff]) <| countP_attach _ _
#align multiset.count_attach Multiset.count_attach
theorem count_pos {a : α} {s : Multiset α} : 0 < count a s ↔ a ∈ s := by simp [count, countP_pos]
#align multiset.count_pos Multiset.count_pos
theorem one_le_count_iff_mem {a : α} {s : Multiset α} : 1 ≤ count a s ↔ a ∈ s := by
rw [succ_le_iff, count_pos]
#align multiset.one_le_count_iff_mem Multiset.one_le_count_iff_mem
@[simp]
theorem count_eq_zero_of_not_mem {a : α} {s : Multiset α} (h : a ∉ s) : count a s = 0 :=
by_contradiction fun h' => h <| count_pos.1 (Nat.pos_of_ne_zero h')
#align multiset.count_eq_zero_of_not_mem Multiset.count_eq_zero_of_not_mem
lemma count_ne_zero {a : α} : count a s ≠ 0 ↔ a ∈ s := Nat.pos_iff_ne_zero.symm.trans count_pos
#align multiset.count_ne_zero Multiset.count_ne_zero
@[simp] lemma count_eq_zero {a : α} : count a s = 0 ↔ a ∉ s := count_ne_zero.not_right
#align multiset.count_eq_zero Multiset.count_eq_zero
theorem count_eq_card {a : α} {s} : count a s = card s ↔ ∀ x ∈ s, a = x := by
simp [countP_eq_card, count, @eq_comm _ a]
#align multiset.count_eq_card Multiset.count_eq_card
@[simp]
theorem count_replicate_self (a : α) (n : ℕ) : count a (replicate n a) = n := by
convert List.count_replicate_self a n
rw [← coe_count, coe_replicate]
#align multiset.count_replicate_self Multiset.count_replicate_self
theorem count_replicate (a b : α) (n : ℕ) : count a (replicate n b) = if a = b then n else 0 := by
convert List.count_replicate a b n
rw [← coe_count, coe_replicate]
#align multiset.count_replicate Multiset.count_replicate
@[simp]
theorem count_erase_self (a : α) (s : Multiset α) : count a (erase s a) = count a s - 1 :=
Quotient.inductionOn s fun l => by
convert List.count_erase_self a l <;> rw [← coe_count] <;> simp
#align multiset.count_erase_self Multiset.count_erase_self
@[simp]
theorem count_erase_of_ne {a b : α} (ab : a ≠ b) (s : Multiset α) :
count a (erase s b) = count a s :=
Quotient.inductionOn s fun l => by
convert List.count_erase_of_ne ab l <;> rw [← coe_count] <;> simp
#align multiset.count_erase_of_ne Multiset.count_erase_of_ne
@[simp]
theorem count_sub (a : α) (s t : Multiset α) : count a (s - t) = count a s - count a t := by
revert s; refine Multiset.induction_on t (by simp) fun b t IH s => ?_
rw [sub_cons, IH]
rcases Decidable.eq_or_ne a b with rfl | ab
· rw [count_erase_self, count_cons_self, Nat.sub_sub, add_comm]
· rw [count_erase_of_ne ab, count_cons_of_ne ab]
#align multiset.count_sub Multiset.count_sub
@[simp]
theorem count_union (a : α) (s t : Multiset α) : count a (s ∪ t) = max (count a s) (count a t) := by
simp [(· ∪ ·), union, Nat.sub_add_eq_max]
#align multiset.count_union Multiset.count_union
@[simp]
theorem count_inter (a : α) (s t : Multiset α) : count a (s ∩ t) = min (count a s) (count a t) := by
apply @Nat.add_left_cancel (count a (s - t))
rw [← count_add, sub_add_inter, count_sub, Nat.sub_add_min_cancel]
#align multiset.count_inter Multiset.count_inter
theorem le_count_iff_replicate_le {a : α} {s : Multiset α} {n : ℕ} :
n ≤ count a s ↔ replicate n a ≤ s :=
Quot.inductionOn s fun _l => by
simp only [quot_mk_to_coe'', mem_coe, coe_count]
exact le_count_iff_replicate_sublist.trans replicate_le_coe.symm
#align multiset.le_count_iff_replicate_le Multiset.le_count_iff_replicate_le
@[simp]
theorem count_filter_of_pos {p} [DecidablePred p] {a} {s : Multiset α} (h : p a) :
count a (filter p s) = count a s :=
Quot.inductionOn s fun _l => by
simp only [quot_mk_to_coe'', filter_coe, mem_coe, coe_count, decide_eq_true_eq]
apply count_filter
simpa using h
#align multiset.count_filter_of_pos Multiset.count_filter_of_pos
@[simp]
theorem count_filter_of_neg {p} [DecidablePred p] {a} {s : Multiset α} (h : ¬p a) :
count a (filter p s) = 0 :=
Multiset.count_eq_zero_of_not_mem fun t => h (of_mem_filter t)
#align multiset.count_filter_of_neg Multiset.count_filter_of_neg
theorem count_filter {p} [DecidablePred p] {a} {s : Multiset α} :
count a (filter p s) = if p a then count a s else 0 := by
split_ifs with h
· exact count_filter_of_pos h
· exact count_filter_of_neg h
#align multiset.count_filter Multiset.count_filter
theorem ext {s t : Multiset α} : s = t ↔ ∀ a, count a s = count a t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => Quotient.eq.trans <| by
simp only [quot_mk_to_coe, filter_coe, mem_coe, coe_count, decide_eq_true_eq]
apply perm_iff_count
#align multiset.ext Multiset.ext
@[ext]
theorem ext' {s t : Multiset α} : (∀ a, count a s = count a t) → s = t :=
ext.2
#align multiset.ext' Multiset.ext'
@[simp]
theorem coe_inter (s t : List α) : (s ∩ t : Multiset α) = (s.bagInter t : List α) := by ext; simp
#align multiset.coe_inter Multiset.coe_inter
theorem le_iff_count {s t : Multiset α} : s ≤ t ↔ ∀ a, count a s ≤ count a t :=
⟨fun h a => count_le_of_le a h, fun al => by
rw [← (ext.2 fun a => by simp [max_eq_right (al a)] : s ∪ t = t)]; apply le_union_left⟩
#align multiset.le_iff_count Multiset.le_iff_count
instance : DistribLattice (Multiset α) :=
{ le_sup_inf := fun s t u =>
le_of_eq <|
Eq.symm <|
ext.2 fun a => by
simp only [max_min_distrib_left, Multiset.count_inter, Multiset.sup_eq_union,
Multiset.count_union, Multiset.inf_eq_inter] }
theorem count_map {α β : Type*} (f : α → β) (s : Multiset α) [DecidableEq β] (b : β) :
count b (map f s) = card (s.filter fun a => b = f a) := by
simp [Bool.beq_eq_decide_eq, eq_comm, count, countP_map]
#align multiset.count_map Multiset.count_map
/-- `Multiset.map f` preserves `count` if `f` is injective on the set of elements contained in
the multiset -/
theorem count_map_eq_count [DecidableEq β] (f : α → β) (s : Multiset α)
(hf : Set.InjOn f { x : α | x ∈ s }) (x) (H : x ∈ s) : (s.map f).count (f x) = s.count x := by
suffices (filter (fun a : α => f x = f a) s).count x = card (filter (fun a : α => f x = f a) s) by
rw [count, countP_map, ← this]
exact count_filter_of_pos <| rfl
· rw [eq_replicate_card.2 fun b hb => (hf H (mem_filter.1 hb).left _).symm]
· simp only [count_replicate, eq_self_iff_true, if_true, card_replicate]
· simp only [mem_filter, beq_iff_eq, and_imp, @eq_comm _ (f x), imp_self, implies_true]
#align multiset.count_map_eq_count Multiset.count_map_eq_count
/-- `Multiset.map f` preserves `count` if `f` is injective -/
theorem count_map_eq_count' [DecidableEq β] (f : α → β) (s : Multiset α) (hf : Function.Injective f)
(x : α) : (s.map f).count (f x) = s.count x := by
by_cases H : x ∈ s
· exact count_map_eq_count f _ hf.injOn _ H
· rw [count_eq_zero_of_not_mem H, count_eq_zero, mem_map]
rintro ⟨k, hks, hkx⟩
rw [hf hkx] at hks
contradiction
#align multiset.count_map_eq_count' Multiset.count_map_eq_count'
@[simp]
| Mathlib/Data/Multiset/Basic.lean | 2,654 | 2,656 | theorem sub_filter_eq_filter_not [DecidableEq α] (p) [DecidablePred p] (s : Multiset α) :
s - s.filter p = s.filter (fun a ↦ ¬ p a) := by |
ext a; by_cases h : p a <;> simp [h]
|
/-
Copyright (c) 2021 Kalle Kytölä. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kalle Kytölä
-/
import Mathlib.Topology.MetricSpace.HausdorffDistance
#align_import topology.metric_space.hausdorff_distance from "leanprover-community/mathlib"@"bc91ed7093bf098d253401e69df601fc33dde156"
/-!
# Thickenings in pseudo-metric spaces
## Main definitions
* `Metric.thickening δ s`, the open thickening by radius `δ` of a set `s` in a pseudo emetric space.
* `Metric.cthickening δ s`, the closed thickening by radius `δ` of a set `s` in a pseudo emetric
space.
## Main results
* `Disjoint.exists_thickenings`: two disjoint sets admit disjoint thickenings
* `Disjoint.exists_cthickenings`: two disjoint sets admit disjoint closed thickenings
* `IsCompact.exists_cthickening_subset_open`: if `s` is compact, `t` is open and `s ⊆ t`,
some `cthickening` of `s` is contained in `t`.
* `Metric.hasBasis_nhdsSet_cthickening`: the `cthickening`s of a compact set `K` form a basis
of the neighbourhoods of `K`
* `Metric.closure_eq_iInter_cthickening'`: the closure of a set equals the intersection
of its closed thickenings of positive radii accumulating at zero.
The same holds for open thickenings.
* `IsCompact.cthickening_eq_biUnion_closedBall`: if `s` is compact, `cthickening δ s` is the union
of `closedBall`s of radius `δ` around `x : E`.
-/
noncomputable section
open NNReal ENNReal Topology Set Filter Bornology
universe u v w
variable {ι : Sort*} {α : Type u} {β : Type v}
namespace Metric
section Thickening
variable [PseudoEMetricSpace α] {δ : ℝ} {s : Set α} {x : α}
open EMetric
/-- The (open) `δ`-thickening `Metric.thickening δ E` of a subset `E` in a pseudo emetric space
consists of those points that are at distance less than `δ` from some point of `E`. -/
def thickening (δ : ℝ) (E : Set α) : Set α :=
{ x : α | infEdist x E < ENNReal.ofReal δ }
#align metric.thickening Metric.thickening
theorem mem_thickening_iff_infEdist_lt : x ∈ thickening δ s ↔ infEdist x s < ENNReal.ofReal δ :=
Iff.rfl
#align metric.mem_thickening_iff_inf_edist_lt Metric.mem_thickening_iff_infEdist_lt
/-- An exterior point of a subset `E` (i.e., a point outside the closure of `E`) is not in the
(open) `δ`-thickening of `E` for small enough positive `δ`. -/
lemma eventually_not_mem_thickening_of_infEdist_pos {E : Set α} {x : α} (h : x ∉ closure E) :
∀ᶠ δ in 𝓝 (0 : ℝ), x ∉ Metric.thickening δ E := by
obtain ⟨ε, ⟨ε_pos, ε_lt⟩⟩ := exists_real_pos_lt_infEdist_of_not_mem_closure h
filter_upwards [eventually_lt_nhds ε_pos] with δ hδ
simp only [thickening, mem_setOf_eq, not_lt]
exact (ENNReal.ofReal_le_ofReal hδ.le).trans ε_lt.le
/-- The (open) thickening equals the preimage of an open interval under `EMetric.infEdist`. -/
theorem thickening_eq_preimage_infEdist (δ : ℝ) (E : Set α) :
thickening δ E = (infEdist · E) ⁻¹' Iio (ENNReal.ofReal δ) :=
rfl
#align metric.thickening_eq_preimage_inf_edist Metric.thickening_eq_preimage_infEdist
/-- The (open) thickening is an open set. -/
theorem isOpen_thickening {δ : ℝ} {E : Set α} : IsOpen (thickening δ E) :=
Continuous.isOpen_preimage continuous_infEdist _ isOpen_Iio
#align metric.is_open_thickening Metric.isOpen_thickening
/-- The (open) thickening of the empty set is empty. -/
@[simp]
theorem thickening_empty (δ : ℝ) : thickening δ (∅ : Set α) = ∅ := by
simp only [thickening, setOf_false, infEdist_empty, not_top_lt]
#align metric.thickening_empty Metric.thickening_empty
theorem thickening_of_nonpos (hδ : δ ≤ 0) (s : Set α) : thickening δ s = ∅ :=
eq_empty_of_forall_not_mem fun _ => ((ENNReal.ofReal_of_nonpos hδ).trans_le bot_le).not_lt
#align metric.thickening_of_nonpos Metric.thickening_of_nonpos
/-- The (open) thickening `Metric.thickening δ E` of a fixed subset `E` is an increasing function of
the thickening radius `δ`. -/
theorem thickening_mono {δ₁ δ₂ : ℝ} (hle : δ₁ ≤ δ₂) (E : Set α) :
thickening δ₁ E ⊆ thickening δ₂ E :=
preimage_mono (Iio_subset_Iio (ENNReal.ofReal_le_ofReal hle))
#align metric.thickening_mono Metric.thickening_mono
/-- The (open) thickening `Metric.thickening δ E` with a fixed thickening radius `δ` is
an increasing function of the subset `E`. -/
theorem thickening_subset_of_subset (δ : ℝ) {E₁ E₂ : Set α} (h : E₁ ⊆ E₂) :
thickening δ E₁ ⊆ thickening δ E₂ := fun _ hx => lt_of_le_of_lt (infEdist_anti h) hx
#align metric.thickening_subset_of_subset Metric.thickening_subset_of_subset
theorem mem_thickening_iff_exists_edist_lt {δ : ℝ} (E : Set α) (x : α) :
x ∈ thickening δ E ↔ ∃ z ∈ E, edist x z < ENNReal.ofReal δ :=
infEdist_lt_iff
#align metric.mem_thickening_iff_exists_edist_lt Metric.mem_thickening_iff_exists_edist_lt
/-- The frontier of the (open) thickening of a set is contained in an `EMetric.infEdist` level
set. -/
theorem frontier_thickening_subset (E : Set α) {δ : ℝ} :
frontier (thickening δ E) ⊆ { x : α | infEdist x E = ENNReal.ofReal δ } :=
frontier_lt_subset_eq continuous_infEdist continuous_const
#align metric.frontier_thickening_subset Metric.frontier_thickening_subset
theorem frontier_thickening_disjoint (A : Set α) :
Pairwise (Disjoint on fun r : ℝ => frontier (thickening r A)) := by
refine (pairwise_disjoint_on _).2 fun r₁ r₂ hr => ?_
rcases le_total r₁ 0 with h₁ | h₁
· simp [thickening_of_nonpos h₁]
refine ((disjoint_singleton.2 fun h => hr.ne ?_).preimage _).mono (frontier_thickening_subset _)
(frontier_thickening_subset _)
apply_fun ENNReal.toReal at h
rwa [ENNReal.toReal_ofReal h₁, ENNReal.toReal_ofReal (h₁.trans hr.le)] at h
#align metric.frontier_thickening_disjoint Metric.frontier_thickening_disjoint
/-- Any set is contained in the complement of the δ-thickening of the complement of its
δ-thickening. -/
lemma subset_compl_thickening_compl_thickening_self (δ : ℝ) (E : Set α) :
E ⊆ (thickening δ (thickening δ E)ᶜ)ᶜ := by
intro x x_in_E
simp only [thickening, mem_compl_iff, mem_setOf_eq, not_lt]
apply EMetric.le_infEdist.mpr fun y hy ↦ ?_
simp only [mem_compl_iff, mem_setOf_eq, not_lt] at hy
simpa only [edist_comm] using le_trans hy <| EMetric.infEdist_le_edist_of_mem x_in_E
/-- The δ-thickening of the complement of the δ-thickening of a set is contained in the complement
of the set. -/
lemma thickening_compl_thickening_self_subset_compl (δ : ℝ) (E : Set α) :
thickening δ (thickening δ E)ᶜ ⊆ Eᶜ := by
apply compl_subset_compl.mp
simpa only [compl_compl] using subset_compl_thickening_compl_thickening_self δ E
variable {X : Type u} [PseudoMetricSpace X]
-- Porting note (#10756): new lemma
theorem mem_thickening_iff_infDist_lt {E : Set X} {x : X} (h : E.Nonempty) :
x ∈ thickening δ E ↔ infDist x E < δ :=
lt_ofReal_iff_toReal_lt (infEdist_ne_top h)
/-- A point in a metric space belongs to the (open) `δ`-thickening of a subset `E` if and only if
it is at distance less than `δ` from some point of `E`. -/
theorem mem_thickening_iff {E : Set X} {x : X} : x ∈ thickening δ E ↔ ∃ z ∈ E, dist x z < δ := by
have key_iff : ∀ z : X, edist x z < ENNReal.ofReal δ ↔ dist x z < δ := fun z ↦ by
rw [dist_edist, lt_ofReal_iff_toReal_lt (edist_ne_top _ _)]
simp_rw [mem_thickening_iff_exists_edist_lt, key_iff]
#align metric.mem_thickening_iff Metric.mem_thickening_iff
@[simp]
theorem thickening_singleton (δ : ℝ) (x : X) : thickening δ ({x} : Set X) = ball x δ := by
ext
simp [mem_thickening_iff]
#align metric.thickening_singleton Metric.thickening_singleton
theorem ball_subset_thickening {x : X} {E : Set X} (hx : x ∈ E) (δ : ℝ) :
ball x δ ⊆ thickening δ E :=
Subset.trans (by simp [Subset.rfl]) (thickening_subset_of_subset δ <| singleton_subset_iff.mpr hx)
#align metric.ball_subset_thickening Metric.ball_subset_thickening
/-- The (open) `δ`-thickening `Metric.thickening δ E` of a subset `E` in a metric space equals the
union of balls of radius `δ` centered at points of `E`. -/
theorem thickening_eq_biUnion_ball {δ : ℝ} {E : Set X} : thickening δ E = ⋃ x ∈ E, ball x δ := by
ext x
simp only [mem_iUnion₂, exists_prop]
exact mem_thickening_iff
#align metric.thickening_eq_bUnion_ball Metric.thickening_eq_biUnion_ball
protected theorem _root_.Bornology.IsBounded.thickening {δ : ℝ} {E : Set X} (h : IsBounded E) :
IsBounded (thickening δ E) := by
rcases E.eq_empty_or_nonempty with rfl | ⟨x, hx⟩
· simp
· refine (isBounded_iff_subset_closedBall x).2 ⟨δ + diam E, fun y hy ↦ ?_⟩
calc
dist y x ≤ infDist y E + diam E := dist_le_infDist_add_diam (x := y) h hx
_ ≤ δ + diam E := add_le_add_right ((mem_thickening_iff_infDist_lt ⟨x, hx⟩).1 hy).le _
#align metric.bounded.thickening Bornology.IsBounded.thickening
end Thickening
section Cthickening
variable [PseudoEMetricSpace α] {δ ε : ℝ} {s t : Set α} {x : α}
open EMetric
/-- The closed `δ`-thickening `Metric.cthickening δ E` of a subset `E` in a pseudo emetric space
consists of those points that are at infimum distance at most `δ` from `E`. -/
def cthickening (δ : ℝ) (E : Set α) : Set α :=
{ x : α | infEdist x E ≤ ENNReal.ofReal δ }
#align metric.cthickening Metric.cthickening
@[simp]
theorem mem_cthickening_iff : x ∈ cthickening δ s ↔ infEdist x s ≤ ENNReal.ofReal δ :=
Iff.rfl
#align metric.mem_cthickening_iff Metric.mem_cthickening_iff
/-- An exterior point of a subset `E` (i.e., a point outside the closure of `E`) is not in the
closed `δ`-thickening of `E` for small enough positive `δ`. -/
lemma eventually_not_mem_cthickening_of_infEdist_pos {E : Set α} {x : α} (h : x ∉ closure E) :
∀ᶠ δ in 𝓝 (0 : ℝ), x ∉ Metric.cthickening δ E := by
obtain ⟨ε, ⟨ε_pos, ε_lt⟩⟩ := exists_real_pos_lt_infEdist_of_not_mem_closure h
filter_upwards [eventually_lt_nhds ε_pos] with δ hδ
simp only [cthickening, mem_setOf_eq, not_le]
exact ((ofReal_lt_ofReal_iff ε_pos).mpr hδ).trans ε_lt
theorem mem_cthickening_of_edist_le (x y : α) (δ : ℝ) (E : Set α) (h : y ∈ E)
(h' : edist x y ≤ ENNReal.ofReal δ) : x ∈ cthickening δ E :=
(infEdist_le_edist_of_mem h).trans h'
#align metric.mem_cthickening_of_edist_le Metric.mem_cthickening_of_edist_le
theorem mem_cthickening_of_dist_le {α : Type*} [PseudoMetricSpace α] (x y : α) (δ : ℝ) (E : Set α)
(h : y ∈ E) (h' : dist x y ≤ δ) : x ∈ cthickening δ E := by
apply mem_cthickening_of_edist_le x y δ E h
rw [edist_dist]
exact ENNReal.ofReal_le_ofReal h'
#align metric.mem_cthickening_of_dist_le Metric.mem_cthickening_of_dist_le
theorem cthickening_eq_preimage_infEdist (δ : ℝ) (E : Set α) :
cthickening δ E = (fun x => infEdist x E) ⁻¹' Iic (ENNReal.ofReal δ) :=
rfl
#align metric.cthickening_eq_preimage_inf_edist Metric.cthickening_eq_preimage_infEdist
/-- The closed thickening is a closed set. -/
theorem isClosed_cthickening {δ : ℝ} {E : Set α} : IsClosed (cthickening δ E) :=
IsClosed.preimage continuous_infEdist isClosed_Iic
#align metric.is_closed_cthickening Metric.isClosed_cthickening
/-- The closed thickening of the empty set is empty. -/
@[simp]
theorem cthickening_empty (δ : ℝ) : cthickening δ (∅ : Set α) = ∅ := by
simp only [cthickening, ENNReal.ofReal_ne_top, setOf_false, infEdist_empty, top_le_iff]
#align metric.cthickening_empty Metric.cthickening_empty
theorem cthickening_of_nonpos {δ : ℝ} (hδ : δ ≤ 0) (E : Set α) : cthickening δ E = closure E := by
ext x
simp [mem_closure_iff_infEdist_zero, cthickening, ENNReal.ofReal_eq_zero.2 hδ]
#align metric.cthickening_of_nonpos Metric.cthickening_of_nonpos
/-- The closed thickening with radius zero is the closure of the set. -/
@[simp]
theorem cthickening_zero (E : Set α) : cthickening 0 E = closure E :=
cthickening_of_nonpos le_rfl E
#align metric.cthickening_zero Metric.cthickening_zero
theorem cthickening_max_zero (δ : ℝ) (E : Set α) : cthickening (max 0 δ) E = cthickening δ E := by
cases le_total δ 0 <;> simp [cthickening_of_nonpos, *]
#align metric.cthickening_max_zero Metric.cthickening_max_zero
/-- The closed thickening `Metric.cthickening δ E` of a fixed subset `E` is an increasing function
of the thickening radius `δ`. -/
theorem cthickening_mono {δ₁ δ₂ : ℝ} (hle : δ₁ ≤ δ₂) (E : Set α) :
cthickening δ₁ E ⊆ cthickening δ₂ E :=
preimage_mono (Iic_subset_Iic.mpr (ENNReal.ofReal_le_ofReal hle))
#align metric.cthickening_mono Metric.cthickening_mono
@[simp]
theorem cthickening_singleton {α : Type*} [PseudoMetricSpace α] (x : α) {δ : ℝ} (hδ : 0 ≤ δ) :
cthickening δ ({x} : Set α) = closedBall x δ := by
ext y
simp [cthickening, edist_dist, ENNReal.ofReal_le_ofReal_iff hδ]
#align metric.cthickening_singleton Metric.cthickening_singleton
theorem closedBall_subset_cthickening_singleton {α : Type*} [PseudoMetricSpace α] (x : α) (δ : ℝ) :
closedBall x δ ⊆ cthickening δ ({x} : Set α) := by
rcases lt_or_le δ 0 with (hδ | hδ)
· simp only [closedBall_eq_empty.mpr hδ, empty_subset]
· simp only [cthickening_singleton x hδ, Subset.rfl]
#align metric.closed_ball_subset_cthickening_singleton Metric.closedBall_subset_cthickening_singleton
/-- The closed thickening `Metric.cthickening δ E` with a fixed thickening radius `δ` is
an increasing function of the subset `E`. -/
theorem cthickening_subset_of_subset (δ : ℝ) {E₁ E₂ : Set α} (h : E₁ ⊆ E₂) :
cthickening δ E₁ ⊆ cthickening δ E₂ := fun _ hx => le_trans (infEdist_anti h) hx
#align metric.cthickening_subset_of_subset Metric.cthickening_subset_of_subset
theorem cthickening_subset_thickening {δ₁ : ℝ≥0} {δ₂ : ℝ} (hlt : (δ₁ : ℝ) < δ₂) (E : Set α) :
cthickening δ₁ E ⊆ thickening δ₂ E := fun _ hx =>
hx.out.trans_lt ((ENNReal.ofReal_lt_ofReal_iff (lt_of_le_of_lt δ₁.prop hlt)).mpr hlt)
#align metric.cthickening_subset_thickening Metric.cthickening_subset_thickening
/-- The closed thickening `Metric.cthickening δ₁ E` is contained in the open thickening
`Metric.thickening δ₂ E` if the radius of the latter is positive and larger. -/
theorem cthickening_subset_thickening' {δ₁ δ₂ : ℝ} (δ₂_pos : 0 < δ₂) (hlt : δ₁ < δ₂) (E : Set α) :
cthickening δ₁ E ⊆ thickening δ₂ E := fun _ hx =>
lt_of_le_of_lt hx.out ((ENNReal.ofReal_lt_ofReal_iff δ₂_pos).mpr hlt)
#align metric.cthickening_subset_thickening' Metric.cthickening_subset_thickening'
/-- The open thickening `Metric.thickening δ E` is contained in the closed thickening
`Metric.cthickening δ E` with the same radius. -/
theorem thickening_subset_cthickening (δ : ℝ) (E : Set α) : thickening δ E ⊆ cthickening δ E := by
intro x hx
rw [thickening, mem_setOf_eq] at hx
exact hx.le
#align metric.thickening_subset_cthickening Metric.thickening_subset_cthickening
theorem thickening_subset_cthickening_of_le {δ₁ δ₂ : ℝ} (hle : δ₁ ≤ δ₂) (E : Set α) :
thickening δ₁ E ⊆ cthickening δ₂ E :=
(thickening_subset_cthickening δ₁ E).trans (cthickening_mono hle E)
#align metric.thickening_subset_cthickening_of_le Metric.thickening_subset_cthickening_of_le
theorem _root_.Bornology.IsBounded.cthickening {α : Type*} [PseudoMetricSpace α] {δ : ℝ} {E : Set α}
(h : IsBounded E) : IsBounded (cthickening δ E) := by
have : IsBounded (thickening (max (δ + 1) 1) E) := h.thickening
apply this.subset
exact cthickening_subset_thickening' (zero_lt_one.trans_le (le_max_right _ _))
((lt_add_one _).trans_le (le_max_left _ _)) _
#align metric.bounded.cthickening Bornology.IsBounded.cthickening
protected theorem _root_.IsCompact.cthickening
{α : Type*} [PseudoMetricSpace α] [ProperSpace α] {s : Set α}
(hs : IsCompact s) {r : ℝ} : IsCompact (cthickening r s) :=
isCompact_of_isClosed_isBounded isClosed_cthickening hs.isBounded.cthickening
theorem thickening_subset_interior_cthickening (δ : ℝ) (E : Set α) :
thickening δ E ⊆ interior (cthickening δ E) :=
(subset_interior_iff_isOpen.mpr isOpen_thickening).trans
(interior_mono (thickening_subset_cthickening δ E))
#align metric.thickening_subset_interior_cthickening Metric.thickening_subset_interior_cthickening
theorem closure_thickening_subset_cthickening (δ : ℝ) (E : Set α) :
closure (thickening δ E) ⊆ cthickening δ E :=
(closure_mono (thickening_subset_cthickening δ E)).trans isClosed_cthickening.closure_subset
#align metric.closure_thickening_subset_cthickening Metric.closure_thickening_subset_cthickening
/-- The closed thickening of a set contains the closure of the set. -/
theorem closure_subset_cthickening (δ : ℝ) (E : Set α) : closure E ⊆ cthickening δ E := by
rw [← cthickening_of_nonpos (min_le_right δ 0)]
exact cthickening_mono (min_le_left δ 0) E
#align metric.closure_subset_cthickening Metric.closure_subset_cthickening
/-- The (open) thickening of a set contains the closure of the set. -/
theorem closure_subset_thickening {δ : ℝ} (δ_pos : 0 < δ) (E : Set α) :
closure E ⊆ thickening δ E := by
rw [← cthickening_zero]
exact cthickening_subset_thickening' δ_pos δ_pos E
#align metric.closure_subset_thickening Metric.closure_subset_thickening
/-- A set is contained in its own (open) thickening. -/
theorem self_subset_thickening {δ : ℝ} (δ_pos : 0 < δ) (E : Set α) : E ⊆ thickening δ E :=
(@subset_closure _ E).trans (closure_subset_thickening δ_pos E)
#align metric.self_subset_thickening Metric.self_subset_thickening
/-- A set is contained in its own closed thickening. -/
theorem self_subset_cthickening {δ : ℝ} (E : Set α) : E ⊆ cthickening δ E :=
subset_closure.trans (closure_subset_cthickening δ E)
#align metric.self_subset_cthickening Metric.self_subset_cthickening
theorem thickening_mem_nhdsSet (E : Set α) {δ : ℝ} (hδ : 0 < δ) : thickening δ E ∈ 𝓝ˢ E :=
isOpen_thickening.mem_nhdsSet.2 <| self_subset_thickening hδ E
#align metric.thickening_mem_nhds_set Metric.thickening_mem_nhdsSet
theorem cthickening_mem_nhdsSet (E : Set α) {δ : ℝ} (hδ : 0 < δ) : cthickening δ E ∈ 𝓝ˢ E :=
mem_of_superset (thickening_mem_nhdsSet E hδ) (thickening_subset_cthickening _ _)
#align metric.cthickening_mem_nhds_set Metric.cthickening_mem_nhdsSet
@[simp]
theorem thickening_union (δ : ℝ) (s t : Set α) :
thickening δ (s ∪ t) = thickening δ s ∪ thickening δ t := by
simp_rw [thickening, infEdist_union, inf_eq_min, min_lt_iff, setOf_or]
#align metric.thickening_union Metric.thickening_union
@[simp]
theorem cthickening_union (δ : ℝ) (s t : Set α) :
cthickening δ (s ∪ t) = cthickening δ s ∪ cthickening δ t := by
simp_rw [cthickening, infEdist_union, inf_eq_min, min_le_iff, setOf_or]
#align metric.cthickening_union Metric.cthickening_union
@[simp]
theorem thickening_iUnion (δ : ℝ) (f : ι → Set α) :
thickening δ (⋃ i, f i) = ⋃ i, thickening δ (f i) := by
simp_rw [thickening, infEdist_iUnion, iInf_lt_iff, setOf_exists]
#align metric.thickening_Union Metric.thickening_iUnion
lemma thickening_biUnion {ι : Type*} (δ : ℝ) (f : ι → Set α) (I : Set ι) :
thickening δ (⋃ i ∈ I, f i) = ⋃ i ∈ I, thickening δ (f i) := by simp only [thickening_iUnion]
theorem ediam_cthickening_le (ε : ℝ≥0) :
EMetric.diam (cthickening ε s) ≤ EMetric.diam s + 2 * ε := by
refine diam_le fun x hx y hy => ENNReal.le_of_forall_pos_le_add fun δ hδ _ => ?_
rw [mem_cthickening_iff, ENNReal.ofReal_coe_nnreal] at hx hy
have hε : (ε : ℝ≥0∞) < ε + δ := ENNReal.coe_lt_coe.2 (lt_add_of_pos_right _ hδ)
replace hx := hx.trans_lt hε
obtain ⟨x', hx', hxx'⟩ := infEdist_lt_iff.mp hx
calc
edist x y ≤ edist x x' + edist y x' := edist_triangle_right _ _ _
_ ≤ ε + δ + (infEdist y s + EMetric.diam s) :=
add_le_add hxx'.le (edist_le_infEdist_add_ediam hx')
_ ≤ ε + δ + (ε + EMetric.diam s) := add_le_add_left (add_le_add_right hy _) _
_ = _ := by rw [two_mul]; ac_rfl
#align metric.ediam_cthickening_le Metric.ediam_cthickening_le
theorem ediam_thickening_le (ε : ℝ≥0) : EMetric.diam (thickening ε s) ≤ EMetric.diam s + 2 * ε :=
(EMetric.diam_mono <| thickening_subset_cthickening _ _).trans <| ediam_cthickening_le _
#align metric.ediam_thickening_le Metric.ediam_thickening_le
theorem diam_cthickening_le {α : Type*} [PseudoMetricSpace α] (s : Set α) (hε : 0 ≤ ε) :
diam (cthickening ε s) ≤ diam s + 2 * ε := by
lift ε to ℝ≥0 using hε
refine (toReal_le_add' (ediam_cthickening_le _) ?_ ?_).trans_eq ?_
· exact fun h ↦ top_unique <| h ▸ EMetric.diam_mono (self_subset_cthickening _)
· simp [mul_eq_top]
· simp [diam]
#align metric.diam_cthickening_le Metric.diam_cthickening_le
theorem diam_thickening_le {α : Type*} [PseudoMetricSpace α] (s : Set α) (hε : 0 ≤ ε) :
diam (thickening ε s) ≤ diam s + 2 * ε := by
by_cases hs : IsBounded s
· exact (diam_mono (thickening_subset_cthickening _ _) hs.cthickening).trans
(diam_cthickening_le _ hε)
obtain rfl | hε := hε.eq_or_lt
· simp [thickening_of_nonpos, diam_nonneg]
· rw [diam_eq_zero_of_unbounded (mt (IsBounded.subset · <| self_subset_thickening hε _) hs)]
positivity
#align metric.diam_thickening_le Metric.diam_thickening_le
@[simp]
theorem thickening_closure : thickening δ (closure s) = thickening δ s := by
simp_rw [thickening, infEdist_closure]
#align metric.thickening_closure Metric.thickening_closure
@[simp]
theorem cthickening_closure : cthickening δ (closure s) = cthickening δ s := by
simp_rw [cthickening, infEdist_closure]
#align metric.cthickening_closure Metric.cthickening_closure
open ENNReal
theorem _root_.Disjoint.exists_thickenings (hst : Disjoint s t) (hs : IsCompact s)
(ht : IsClosed t) :
∃ δ, 0 < δ ∧ Disjoint (thickening δ s) (thickening δ t) := by
obtain ⟨r, hr, h⟩ := exists_pos_forall_lt_edist hs ht hst
refine ⟨r / 2, half_pos (NNReal.coe_pos.2 hr), ?_⟩
rw [disjoint_iff_inf_le]
rintro z ⟨hzs, hzt⟩
rw [mem_thickening_iff_exists_edist_lt] at hzs hzt
rw [← NNReal.coe_two, ← NNReal.coe_div, ENNReal.ofReal_coe_nnreal] at hzs hzt
obtain ⟨x, hx, hzx⟩ := hzs
obtain ⟨y, hy, hzy⟩ := hzt
refine (h x hx y hy).not_le ?_
calc
edist x y ≤ edist z x + edist z y := edist_triangle_left _ _ _
_ ≤ ↑(r / 2) + ↑(r / 2) := add_le_add hzx.le hzy.le
_ = r := by rw [← ENNReal.coe_add, add_halves]
#align disjoint.exists_thickenings Disjoint.exists_thickenings
theorem _root_.Disjoint.exists_cthickenings (hst : Disjoint s t) (hs : IsCompact s)
(ht : IsClosed t) :
∃ δ, 0 < δ ∧ Disjoint (cthickening δ s) (cthickening δ t) := by
obtain ⟨δ, hδ, h⟩ := hst.exists_thickenings hs ht
refine ⟨δ / 2, half_pos hδ, h.mono ?_ ?_⟩ <;>
exact cthickening_subset_thickening' hδ (half_lt_self hδ) _
#align disjoint.exists_cthickenings Disjoint.exists_cthickenings
/-- If `s` is compact, `t` is open and `s ⊆ t`, some `cthickening` of `s` is contained in `t`. -/
theorem _root_.IsCompact.exists_cthickening_subset_open (hs : IsCompact s) (ht : IsOpen t)
(hst : s ⊆ t) :
∃ δ, 0 < δ ∧ cthickening δ s ⊆ t :=
(hst.disjoint_compl_right.exists_cthickenings hs ht.isClosed_compl).imp fun _ h =>
⟨h.1, disjoint_compl_right_iff_subset.1 <| h.2.mono_right <| self_subset_cthickening _⟩
#align is_compact.exists_cthickening_subset_open IsCompact.exists_cthickening_subset_open
theorem _root_.IsCompact.exists_isCompact_cthickening [LocallyCompactSpace α] (hs : IsCompact s) :
∃ δ, 0 < δ ∧ IsCompact (cthickening δ s) := by
rcases exists_compact_superset hs with ⟨K, K_compact, hK⟩
rcases hs.exists_cthickening_subset_open isOpen_interior hK with ⟨δ, δpos, hδ⟩
refine ⟨δ, δpos, ?_⟩
exact K_compact.of_isClosed_subset isClosed_cthickening (hδ.trans interior_subset)
theorem _root_.IsCompact.exists_thickening_subset_open (hs : IsCompact s) (ht : IsOpen t)
(hst : s ⊆ t) : ∃ δ, 0 < δ ∧ thickening δ s ⊆ t :=
let ⟨δ, h₀, hδ⟩ := hs.exists_cthickening_subset_open ht hst
⟨δ, h₀, (thickening_subset_cthickening _ _).trans hδ⟩
#align is_compact.exists_thickening_subset_open IsCompact.exists_thickening_subset_open
theorem hasBasis_nhdsSet_thickening {K : Set α} (hK : IsCompact K) :
(𝓝ˢ K).HasBasis (fun δ : ℝ => 0 < δ) fun δ => thickening δ K :=
(hasBasis_nhdsSet K).to_hasBasis' (fun _U hU => hK.exists_thickening_subset_open hU.1 hU.2)
fun _ => thickening_mem_nhdsSet K
#align metric.has_basis_nhds_set_thickening Metric.hasBasis_nhdsSet_thickening
theorem hasBasis_nhdsSet_cthickening {K : Set α} (hK : IsCompact K) :
(𝓝ˢ K).HasBasis (fun δ : ℝ => 0 < δ) fun δ => cthickening δ K :=
(hasBasis_nhdsSet K).to_hasBasis' (fun _U hU => hK.exists_cthickening_subset_open hU.1 hU.2)
fun _ => cthickening_mem_nhdsSet K
#align metric.has_basis_nhds_set_cthickening Metric.hasBasis_nhdsSet_cthickening
theorem cthickening_eq_iInter_cthickening' {δ : ℝ} (s : Set ℝ) (hsδ : s ⊆ Ioi δ)
(hs : ∀ ε, δ < ε → (s ∩ Ioc δ ε).Nonempty) (E : Set α) :
cthickening δ E = ⋂ ε ∈ s, cthickening ε E := by
apply Subset.antisymm
· exact subset_iInter₂ fun _ hε => cthickening_mono (le_of_lt (hsδ hε)) E
· unfold cthickening
intro x hx
simp only [mem_iInter, mem_setOf_eq] at *
apply ENNReal.le_of_forall_pos_le_add
intro η η_pos _
rcases hs (δ + η) (lt_add_of_pos_right _ (NNReal.coe_pos.mpr η_pos)) with ⟨ε, ⟨hsε, hε⟩⟩
apply ((hx ε hsε).trans (ENNReal.ofReal_le_ofReal hε.2)).trans
rw [ENNReal.coe_nnreal_eq η]
exact ENNReal.ofReal_add_le
#align metric.cthickening_eq_Inter_cthickening' Metric.cthickening_eq_iInter_cthickening'
theorem cthickening_eq_iInter_cthickening {δ : ℝ} (E : Set α) :
cthickening δ E = ⋂ (ε : ℝ) (_ : δ < ε), cthickening ε E := by
apply cthickening_eq_iInter_cthickening' (Ioi δ) rfl.subset
simp_rw [inter_eq_right.mpr Ioc_subset_Ioi_self]
exact fun _ hε => nonempty_Ioc.mpr hε
#align metric.cthickening_eq_Inter_cthickening Metric.cthickening_eq_iInter_cthickening
theorem cthickening_eq_iInter_thickening' {δ : ℝ} (δ_nn : 0 ≤ δ) (s : Set ℝ) (hsδ : s ⊆ Ioi δ)
(hs : ∀ ε, δ < ε → (s ∩ Ioc δ ε).Nonempty) (E : Set α) :
cthickening δ E = ⋂ ε ∈ s, thickening ε E := by
refine (subset_iInter₂ fun ε hε => ?_).antisymm ?_
· obtain ⟨ε', -, hε'⟩ := hs ε (hsδ hε)
have ss := cthickening_subset_thickening' (lt_of_le_of_lt δ_nn hε'.1) hε'.1 E
exact ss.trans (thickening_mono hε'.2 E)
· rw [cthickening_eq_iInter_cthickening' s hsδ hs E]
exact iInter₂_mono fun ε _ => thickening_subset_cthickening ε E
#align metric.cthickening_eq_Inter_thickening' Metric.cthickening_eq_iInter_thickening'
theorem cthickening_eq_iInter_thickening {δ : ℝ} (δ_nn : 0 ≤ δ) (E : Set α) :
cthickening δ E = ⋂ (ε : ℝ) (_ : δ < ε), thickening ε E := by
apply cthickening_eq_iInter_thickening' δ_nn (Ioi δ) rfl.subset
simp_rw [inter_eq_right.mpr Ioc_subset_Ioi_self]
exact fun _ hε => nonempty_Ioc.mpr hε
#align metric.cthickening_eq_Inter_thickening Metric.cthickening_eq_iInter_thickening
theorem cthickening_eq_iInter_thickening'' (δ : ℝ) (E : Set α) :
cthickening δ E = ⋂ (ε : ℝ) (_ : max 0 δ < ε), thickening ε E := by
rw [← cthickening_max_zero, cthickening_eq_iInter_thickening]
exact le_max_left _ _
#align metric.cthickening_eq_Inter_thickening'' Metric.cthickening_eq_iInter_thickening''
/-- The closure of a set equals the intersection of its closed thickenings of positive radii
accumulating at zero. -/
theorem closure_eq_iInter_cthickening' (E : Set α) (s : Set ℝ)
(hs : ∀ ε, 0 < ε → (s ∩ Ioc 0 ε).Nonempty) : closure E = ⋂ δ ∈ s, cthickening δ E := by
by_cases hs₀ : s ⊆ Ioi 0
· rw [← cthickening_zero]
apply cthickening_eq_iInter_cthickening' _ hs₀ hs
obtain ⟨δ, hδs, δ_nonpos⟩ := not_subset.mp hs₀
rw [Set.mem_Ioi, not_lt] at δ_nonpos
apply Subset.antisymm
· exact subset_iInter₂ fun ε _ => closure_subset_cthickening ε E
· rw [← cthickening_of_nonpos δ_nonpos E]
exact biInter_subset_of_mem hδs
#align metric.closure_eq_Inter_cthickening' Metric.closure_eq_iInter_cthickening'
/-- The closure of a set equals the intersection of its closed thickenings of positive radii. -/
theorem closure_eq_iInter_cthickening (E : Set α) :
closure E = ⋂ (δ : ℝ) (_ : 0 < δ), cthickening δ E := by
rw [← cthickening_zero]
exact cthickening_eq_iInter_cthickening E
#align metric.closure_eq_Inter_cthickening Metric.closure_eq_iInter_cthickening
/-- The closure of a set equals the intersection of its open thickenings of positive radii
accumulating at zero. -/
theorem closure_eq_iInter_thickening' (E : Set α) (s : Set ℝ) (hs₀ : s ⊆ Ioi 0)
(hs : ∀ ε, 0 < ε → (s ∩ Ioc 0 ε).Nonempty) : closure E = ⋂ δ ∈ s, thickening δ E := by
rw [← cthickening_zero]
apply cthickening_eq_iInter_thickening' le_rfl _ hs₀ hs
#align metric.closure_eq_Inter_thickening' Metric.closure_eq_iInter_thickening'
/-- The closure of a set equals the intersection of its (open) thickenings of positive radii. -/
theorem closure_eq_iInter_thickening (E : Set α) :
closure E = ⋂ (δ : ℝ) (_ : 0 < δ), thickening δ E := by
rw [← cthickening_zero]
exact cthickening_eq_iInter_thickening rfl.ge E
#align metric.closure_eq_Inter_thickening Metric.closure_eq_iInter_thickening
/-- The frontier of the closed thickening of a set is contained in an `EMetric.infEdist` level
set. -/
theorem frontier_cthickening_subset (E : Set α) {δ : ℝ} :
frontier (cthickening δ E) ⊆ { x : α | infEdist x E = ENNReal.ofReal δ } :=
frontier_le_subset_eq continuous_infEdist continuous_const
#align metric.frontier_cthickening_subset Metric.frontier_cthickening_subset
/-- The closed ball of radius `δ` centered at a point of `E` is included in the closed
thickening of `E`. -/
theorem closedBall_subset_cthickening {α : Type*} [PseudoMetricSpace α] {x : α} {E : Set α}
(hx : x ∈ E) (δ : ℝ) : closedBall x δ ⊆ cthickening δ E := by
refine (closedBall_subset_cthickening_singleton _ _).trans (cthickening_subset_of_subset _ ?_)
simpa using hx
#align metric.closed_ball_subset_cthickening Metric.closedBall_subset_cthickening
theorem cthickening_subset_iUnion_closedBall_of_lt {α : Type*} [PseudoMetricSpace α] (E : Set α)
{δ δ' : ℝ} (hδ₀ : 0 < δ') (hδδ' : δ < δ') : cthickening δ E ⊆ ⋃ x ∈ E, closedBall x δ' := by
refine (cthickening_subset_thickening' hδ₀ hδδ' E).trans fun x hx => ?_
obtain ⟨y, hy₁, hy₂⟩ := mem_thickening_iff.mp hx
exact mem_iUnion₂.mpr ⟨y, hy₁, hy₂.le⟩
#align metric.cthickening_subset_Union_closed_ball_of_lt Metric.cthickening_subset_iUnion_closedBall_of_lt
/-- The closed thickening of a compact set `E` is the union of the balls `Metric.closedBall x δ`
over `x ∈ E`.
See also `Metric.cthickening_eq_biUnion_closedBall`. -/
theorem _root_.IsCompact.cthickening_eq_biUnion_closedBall {α : Type*} [PseudoMetricSpace α]
{δ : ℝ} {E : Set α} (hE : IsCompact E) (hδ : 0 ≤ δ) :
cthickening δ E = ⋃ x ∈ E, closedBall x δ := by
rcases eq_empty_or_nonempty E with (rfl | hne)
· simp only [cthickening_empty, biUnion_empty]
refine Subset.antisymm (fun x hx ↦ ?_)
(iUnion₂_subset fun x hx ↦ closedBall_subset_cthickening hx _)
obtain ⟨y, yE, hy⟩ : ∃ y ∈ E, infEdist x E = edist x y := hE.exists_infEdist_eq_edist hne _
have D1 : edist x y ≤ ENNReal.ofReal δ := (le_of_eq hy.symm).trans hx
have D2 : dist x y ≤ δ := by
rw [edist_dist] at D1
exact (ENNReal.ofReal_le_ofReal_iff hδ).1 D1
exact mem_biUnion yE D2
#align is_compact.cthickening_eq_bUnion_closed_ball IsCompact.cthickening_eq_biUnion_closedBall
theorem cthickening_eq_biUnion_closedBall {α : Type*} [PseudoMetricSpace α] [ProperSpace α]
(E : Set α) (hδ : 0 ≤ δ) : cthickening δ E = ⋃ x ∈ closure E, closedBall x δ := by
rcases eq_empty_or_nonempty E with (rfl | hne)
· simp only [cthickening_empty, biUnion_empty, closure_empty]
rw [← cthickening_closure]
refine Subset.antisymm (fun x hx ↦ ?_)
(iUnion₂_subset fun x hx ↦ closedBall_subset_cthickening hx _)
obtain ⟨y, yE, hy⟩ : ∃ y ∈ closure E, infDist x (closure E) = dist x y :=
isClosed_closure.exists_infDist_eq_dist (closure_nonempty_iff.mpr hne) x
replace hy : dist x y ≤ δ :=
(ENNReal.ofReal_le_ofReal_iff hδ).mp
(((congr_arg ENNReal.ofReal hy.symm).le.trans ENNReal.ofReal_toReal_le).trans hx)
exact mem_biUnion yE hy
#align metric.cthickening_eq_bUnion_closed_ball Metric.cthickening_eq_biUnion_closedBall
nonrec theorem _root_.IsClosed.cthickening_eq_biUnion_closedBall {α : Type*} [PseudoMetricSpace α]
[ProperSpace α] {E : Set α} (hE : IsClosed E) (hδ : 0 ≤ δ) :
cthickening δ E = ⋃ x ∈ E, closedBall x δ := by
rw [cthickening_eq_biUnion_closedBall E hδ, hE.closure_eq]
#align is_closed.cthickening_eq_bUnion_closed_ball IsClosed.cthickening_eq_biUnion_closedBall
/-- For the equality, see `infEdist_cthickening`. -/
theorem infEdist_le_infEdist_cthickening_add :
infEdist x s ≤ infEdist x (cthickening δ s) + ENNReal.ofReal δ := by
refine le_of_forall_lt' fun r h => ?_
simp_rw [← lt_tsub_iff_right, infEdist_lt_iff, mem_cthickening_iff] at h
obtain ⟨y, hy, hxy⟩ := h
exact infEdist_le_edist_add_infEdist.trans_lt
((ENNReal.add_lt_add_of_lt_of_le (hy.trans_lt ENNReal.ofReal_lt_top).ne hxy hy).trans_eq
(tsub_add_cancel_of_le <| le_self_add.trans (lt_tsub_iff_left.1 hxy).le))
#align metric.inf_edist_le_inf_edist_cthickening_add Metric.infEdist_le_infEdist_cthickening_add
/-- For the equality, see `infEdist_thickening`. -/
theorem infEdist_le_infEdist_thickening_add :
infEdist x s ≤ infEdist x (thickening δ s) + ENNReal.ofReal δ :=
infEdist_le_infEdist_cthickening_add.trans <|
add_le_add_right (infEdist_anti <| thickening_subset_cthickening _ _) _
#align metric.inf_edist_le_inf_edist_thickening_add Metric.infEdist_le_infEdist_thickening_add
/-- For the equality, see `thickening_thickening`. -/
@[simp]
theorem thickening_thickening_subset (ε δ : ℝ) (s : Set α) :
thickening ε (thickening δ s) ⊆ thickening (ε + δ) s := by
obtain hε | hε := le_total ε 0
· simp only [thickening_of_nonpos hε, empty_subset]
obtain hδ | hδ := le_total δ 0
· simp only [thickening_of_nonpos hδ, thickening_empty, empty_subset]
intro x
simp_rw [mem_thickening_iff_exists_edist_lt, ENNReal.ofReal_add hε hδ]
exact fun ⟨y, ⟨z, hz, hy⟩, hx⟩ =>
⟨z, hz, (edist_triangle _ _ _).trans_lt <| ENNReal.add_lt_add hx hy⟩
#align metric.thickening_thickening_subset Metric.thickening_thickening_subset
/-- For the equality, see `thickening_cthickening`. -/
@[simp]
theorem thickening_cthickening_subset (ε : ℝ) (hδ : 0 ≤ δ) (s : Set α) :
thickening ε (cthickening δ s) ⊆ thickening (ε + δ) s := by
obtain hε | hε := le_total ε 0
· simp only [thickening_of_nonpos hε, empty_subset]
intro x
simp_rw [mem_thickening_iff_exists_edist_lt, mem_cthickening_iff, ← infEdist_lt_iff,
ENNReal.ofReal_add hε hδ]
rintro ⟨y, hy, hxy⟩
exact infEdist_le_edist_add_infEdist.trans_lt
(ENNReal.add_lt_add_of_lt_of_le (hy.trans_lt ENNReal.ofReal_lt_top).ne hxy hy)
#align metric.thickening_cthickening_subset Metric.thickening_cthickening_subset
/-- For the equality, see `cthickening_thickening`. -/
@[simp]
| Mathlib/Topology/MetricSpace/Thickening.lean | 689 | 695 | theorem cthickening_thickening_subset (hε : 0 ≤ ε) (δ : ℝ) (s : Set α) :
cthickening ε (thickening δ s) ⊆ cthickening (ε + δ) s := by |
obtain hδ | hδ := le_total δ 0
· simp only [thickening_of_nonpos hδ, cthickening_empty, empty_subset]
intro x
simp_rw [mem_cthickening_iff, ENNReal.ofReal_add hε hδ]
exact fun hx => infEdist_le_infEdist_thickening_add.trans (add_le_add_right hx _)
|
/-
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.LinearAlgebra.AffineSpace.AffineEquiv
#align_import linear_algebra.affine_space.affine_subspace from "leanprover-community/mathlib"@"e96bdfbd1e8c98a09ff75f7ac6204d142debc840"
/-!
# Affine spaces
This file defines affine subspaces (over modules) and the affine span of a set of points.
## Main definitions
* `AffineSubspace k P` is the type of affine subspaces. Unlike affine spaces, affine subspaces are
allowed to be empty, and lemmas that do not apply to empty affine subspaces have `Nonempty`
hypotheses. There is a `CompleteLattice` structure on affine subspaces.
* `AffineSubspace.direction` gives the `Submodule` spanned by the pairwise differences of points
in an `AffineSubspace`. There are various lemmas relating to the set of vectors in the
`direction`, and relating the lattice structure on affine subspaces to that on their directions.
* `AffineSubspace.parallel`, notation `∥`, gives the property of two affine subspaces being
parallel (one being a translate of the other).
* `affineSpan` gives the affine subspace spanned by a set of points, with `vectorSpan` giving its
direction. The `affineSpan` is defined in terms of `spanPoints`, which gives an explicit
description of the points contained in the affine span; `spanPoints` itself should generally only
be used when that description is required, with `affineSpan` being the main definition for other
purposes. Two other descriptions of the affine span are proved equivalent: it is the `sInf` of
affine subspaces containing the points, and (if `[Nontrivial k]`) it contains exactly those points
that are affine combinations of points in the given set.
## 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
-/
noncomputable section
open Affine
open Set
section
variable (k : Type*) {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
variable [AffineSpace V P]
/-- The submodule spanning the differences of a (possibly empty) set of points. -/
def vectorSpan (s : Set P) : Submodule k V :=
Submodule.span k (s -ᵥ s)
#align vector_span vectorSpan
/-- The definition of `vectorSpan`, for rewriting. -/
theorem vectorSpan_def (s : Set P) : vectorSpan k s = Submodule.span k (s -ᵥ s) :=
rfl
#align vector_span_def vectorSpan_def
/-- `vectorSpan` is monotone. -/
theorem vectorSpan_mono {s₁ s₂ : Set P} (h : s₁ ⊆ s₂) : vectorSpan k s₁ ≤ vectorSpan k s₂ :=
Submodule.span_mono (vsub_self_mono h)
#align vector_span_mono vectorSpan_mono
variable (P)
/-- The `vectorSpan` of the empty set is `⊥`. -/
@[simp]
theorem vectorSpan_empty : vectorSpan k (∅ : Set P) = (⊥ : Submodule k V) := by
rw [vectorSpan_def, vsub_empty, Submodule.span_empty]
#align vector_span_empty vectorSpan_empty
variable {P}
/-- The `vectorSpan` of a single point is `⊥`. -/
@[simp]
theorem vectorSpan_singleton (p : P) : vectorSpan k ({p} : Set P) = ⊥ := by simp [vectorSpan_def]
#align vector_span_singleton vectorSpan_singleton
/-- The `s -ᵥ s` lies within the `vectorSpan k s`. -/
theorem vsub_set_subset_vectorSpan (s : Set P) : s -ᵥ s ⊆ ↑(vectorSpan k s) :=
Submodule.subset_span
#align vsub_set_subset_vector_span vsub_set_subset_vectorSpan
/-- Each pairwise difference is in the `vectorSpan`. -/
theorem vsub_mem_vectorSpan {s : Set P} {p1 p2 : P} (hp1 : p1 ∈ s) (hp2 : p2 ∈ s) :
p1 -ᵥ p2 ∈ vectorSpan k s :=
vsub_set_subset_vectorSpan k s (vsub_mem_vsub hp1 hp2)
#align vsub_mem_vector_span vsub_mem_vectorSpan
/-- The points in the affine span of a (possibly empty) set of points. Use `affineSpan` instead to
get an `AffineSubspace k P`. -/
def spanPoints (s : Set P) : Set P :=
{ p | ∃ p1 ∈ s, ∃ v ∈ vectorSpan k s, p = v +ᵥ p1 }
#align span_points spanPoints
/-- A point in a set is in its affine span. -/
theorem mem_spanPoints (p : P) (s : Set P) : p ∈ s → p ∈ spanPoints k s
| hp => ⟨p, hp, 0, Submodule.zero_mem _, (zero_vadd V p).symm⟩
#align mem_span_points mem_spanPoints
/-- A set is contained in its `spanPoints`. -/
theorem subset_spanPoints (s : Set P) : s ⊆ spanPoints k s := fun p => mem_spanPoints k p s
#align subset_span_points subset_spanPoints
/-- The `spanPoints` of a set is nonempty if and only if that set is. -/
@[simp]
theorem spanPoints_nonempty (s : Set P) : (spanPoints k s).Nonempty ↔ s.Nonempty := by
constructor
· contrapose
rw [Set.not_nonempty_iff_eq_empty, Set.not_nonempty_iff_eq_empty]
intro h
simp [h, spanPoints]
· exact fun h => h.mono (subset_spanPoints _ _)
#align span_points_nonempty spanPoints_nonempty
/-- Adding a point in the affine span and a vector in the spanning submodule produces a point in the
affine span. -/
theorem vadd_mem_spanPoints_of_mem_spanPoints_of_mem_vectorSpan {s : Set P} {p : P} {v : V}
(hp : p ∈ spanPoints k s) (hv : v ∈ vectorSpan k s) : v +ᵥ p ∈ spanPoints k s := by
rcases hp with ⟨p2, ⟨hp2, ⟨v2, ⟨hv2, hv2p⟩⟩⟩⟩
rw [hv2p, vadd_vadd]
exact ⟨p2, hp2, v + v2, (vectorSpan k s).add_mem hv hv2, rfl⟩
#align vadd_mem_span_points_of_mem_span_points_of_mem_vector_span vadd_mem_spanPoints_of_mem_spanPoints_of_mem_vectorSpan
/-- Subtracting two points in the affine span produces a vector in the spanning submodule. -/
theorem vsub_mem_vectorSpan_of_mem_spanPoints_of_mem_spanPoints {s : Set P} {p1 p2 : P}
(hp1 : p1 ∈ spanPoints k s) (hp2 : p2 ∈ spanPoints k s) : p1 -ᵥ p2 ∈ vectorSpan k s := by
rcases hp1 with ⟨p1a, ⟨hp1a, ⟨v1, ⟨hv1, hv1p⟩⟩⟩⟩
rcases hp2 with ⟨p2a, ⟨hp2a, ⟨v2, ⟨hv2, hv2p⟩⟩⟩⟩
rw [hv1p, hv2p, vsub_vadd_eq_vsub_sub (v1 +ᵥ p1a), vadd_vsub_assoc, add_comm, add_sub_assoc]
have hv1v2 : v1 - v2 ∈ vectorSpan k s := (vectorSpan k s).sub_mem hv1 hv2
refine (vectorSpan k s).add_mem ?_ hv1v2
exact vsub_mem_vectorSpan k hp1a hp2a
#align vsub_mem_vector_span_of_mem_span_points_of_mem_span_points vsub_mem_vectorSpan_of_mem_spanPoints_of_mem_spanPoints
end
/-- An `AffineSubspace k P` is a subset of an `AffineSpace V P` that, if not empty, has an affine
space structure induced by a corresponding subspace of the `Module k V`. -/
structure AffineSubspace (k : Type*) {V : Type*} (P : Type*) [Ring k] [AddCommGroup V]
[Module k V] [AffineSpace V P] where
/-- The affine subspace seen as a subset. -/
carrier : Set P
smul_vsub_vadd_mem :
∀ (c : k) {p1 p2 p3 : P},
p1 ∈ carrier → p2 ∈ carrier → p3 ∈ carrier → c • (p1 -ᵥ p2 : V) +ᵥ p3 ∈ carrier
#align affine_subspace AffineSubspace
namespace Submodule
variable {k V : Type*} [Ring k] [AddCommGroup V] [Module k V]
/-- Reinterpret `p : Submodule k V` as an `AffineSubspace k V`. -/
def toAffineSubspace (p : Submodule k V) : AffineSubspace k V where
carrier := p
smul_vsub_vadd_mem _ _ _ _ h₁ h₂ h₃ := p.add_mem (p.smul_mem _ (p.sub_mem h₁ h₂)) h₃
#align submodule.to_affine_subspace Submodule.toAffineSubspace
end Submodule
namespace AffineSubspace
variable (k : Type*) {V : Type*} (P : Type*) [Ring k] [AddCommGroup V] [Module k V]
[AffineSpace V P]
instance : SetLike (AffineSubspace k P) P where
coe := carrier
coe_injective' p q _ := by cases p; cases q; congr
/-- A point is in an affine subspace coerced to a set if and only if it is in that affine
subspace. -/
-- Porting note: removed `simp`, proof is `simp only [SetLike.mem_coe]`
theorem mem_coe (p : P) (s : AffineSubspace k P) : p ∈ (s : Set P) ↔ p ∈ s :=
Iff.rfl
#align affine_subspace.mem_coe AffineSubspace.mem_coe
variable {k P}
/-- The direction of an affine subspace is the submodule spanned by
the pairwise differences of points. (Except in the case of an empty
affine subspace, where the direction is the zero submodule, every
vector in the direction is the difference of two points in the affine
subspace.) -/
def direction (s : AffineSubspace k P) : Submodule k V :=
vectorSpan k (s : Set P)
#align affine_subspace.direction AffineSubspace.direction
/-- The direction equals the `vectorSpan`. -/
theorem direction_eq_vectorSpan (s : AffineSubspace k P) : s.direction = vectorSpan k (s : Set P) :=
rfl
#align affine_subspace.direction_eq_vector_span AffineSubspace.direction_eq_vectorSpan
/-- Alternative definition of the direction when the affine subspace is nonempty. This is defined so
that the order on submodules (as used in the definition of `Submodule.span`) can be used in the
proof of `coe_direction_eq_vsub_set`, and is not intended to be used beyond that proof. -/
def directionOfNonempty {s : AffineSubspace k P} (h : (s : Set P).Nonempty) : Submodule k V where
carrier := (s : Set P) -ᵥ s
zero_mem' := by
cases' h with p hp
exact vsub_self p ▸ vsub_mem_vsub hp hp
add_mem' := by
rintro _ _ ⟨p1, hp1, p2, hp2, rfl⟩ ⟨p3, hp3, p4, hp4, rfl⟩
rw [← vadd_vsub_assoc]
refine vsub_mem_vsub ?_ hp4
convert s.smul_vsub_vadd_mem 1 hp1 hp2 hp3
rw [one_smul]
smul_mem' := by
rintro c _ ⟨p1, hp1, p2, hp2, rfl⟩
rw [← vadd_vsub (c • (p1 -ᵥ p2)) p2]
refine vsub_mem_vsub ?_ hp2
exact s.smul_vsub_vadd_mem c hp1 hp2 hp2
#align affine_subspace.direction_of_nonempty AffineSubspace.directionOfNonempty
/-- `direction_of_nonempty` gives the same submodule as `direction`. -/
theorem directionOfNonempty_eq_direction {s : AffineSubspace k P} (h : (s : Set P).Nonempty) :
directionOfNonempty h = s.direction := by
refine le_antisymm ?_ (Submodule.span_le.2 Set.Subset.rfl)
rw [← SetLike.coe_subset_coe, directionOfNonempty, direction, Submodule.coe_set_mk,
AddSubmonoid.coe_set_mk]
exact vsub_set_subset_vectorSpan k _
#align affine_subspace.direction_of_nonempty_eq_direction AffineSubspace.directionOfNonempty_eq_direction
/-- The set of vectors in the direction of a nonempty affine subspace is given by `vsub_set`. -/
theorem coe_direction_eq_vsub_set {s : AffineSubspace k P} (h : (s : Set P).Nonempty) :
(s.direction : Set V) = (s : Set P) -ᵥ s :=
directionOfNonempty_eq_direction h ▸ rfl
#align affine_subspace.coe_direction_eq_vsub_set AffineSubspace.coe_direction_eq_vsub_set
/-- A vector is in the direction of a nonempty affine subspace if and only if it is the subtraction
of two vectors in the subspace. -/
theorem mem_direction_iff_eq_vsub {s : AffineSubspace k P} (h : (s : Set P).Nonempty) (v : V) :
v ∈ s.direction ↔ ∃ p1 ∈ s, ∃ p2 ∈ s, v = p1 -ᵥ p2 := by
rw [← SetLike.mem_coe, coe_direction_eq_vsub_set h, Set.mem_vsub]
simp only [SetLike.mem_coe, eq_comm]
#align affine_subspace.mem_direction_iff_eq_vsub AffineSubspace.mem_direction_iff_eq_vsub
/-- Adding a vector in the direction to a point in the subspace produces a point in the
subspace. -/
theorem vadd_mem_of_mem_direction {s : AffineSubspace k P} {v : V} (hv : v ∈ s.direction) {p : P}
(hp : p ∈ s) : v +ᵥ p ∈ s := by
rw [mem_direction_iff_eq_vsub ⟨p, hp⟩] at hv
rcases hv with ⟨p1, hp1, p2, hp2, hv⟩
rw [hv]
convert s.smul_vsub_vadd_mem 1 hp1 hp2 hp
rw [one_smul]
exact s.mem_coe k P _
#align affine_subspace.vadd_mem_of_mem_direction AffineSubspace.vadd_mem_of_mem_direction
/-- Subtracting two points in the subspace produces a vector in the direction. -/
theorem vsub_mem_direction {s : AffineSubspace k P} {p1 p2 : P} (hp1 : p1 ∈ s) (hp2 : p2 ∈ s) :
p1 -ᵥ p2 ∈ s.direction :=
vsub_mem_vectorSpan k hp1 hp2
#align affine_subspace.vsub_mem_direction AffineSubspace.vsub_mem_direction
/-- Adding a vector to a point in a subspace produces a point in the subspace if and only if the
vector is in the direction. -/
theorem vadd_mem_iff_mem_direction {s : AffineSubspace k P} (v : V) {p : P} (hp : p ∈ s) :
v +ᵥ p ∈ s ↔ v ∈ s.direction :=
⟨fun h => by simpa using vsub_mem_direction h hp, fun h => vadd_mem_of_mem_direction h hp⟩
#align affine_subspace.vadd_mem_iff_mem_direction AffineSubspace.vadd_mem_iff_mem_direction
/-- Adding a vector in the direction to a point produces a point in the subspace if and only if
the original point is in the subspace. -/
theorem vadd_mem_iff_mem_of_mem_direction {s : AffineSubspace k P} {v : V} (hv : v ∈ s.direction)
{p : P} : v +ᵥ p ∈ s ↔ p ∈ s := by
refine ⟨fun h => ?_, fun h => vadd_mem_of_mem_direction hv h⟩
convert vadd_mem_of_mem_direction (Submodule.neg_mem _ hv) h
simp
#align affine_subspace.vadd_mem_iff_mem_of_mem_direction AffineSubspace.vadd_mem_iff_mem_of_mem_direction
/-- Given a point in an affine subspace, the set of vectors in its direction equals the set of
vectors subtracting that point on the right. -/
theorem coe_direction_eq_vsub_set_right {s : AffineSubspace k P} {p : P} (hp : p ∈ s) :
(s.direction : Set V) = (· -ᵥ p) '' s := by
rw [coe_direction_eq_vsub_set ⟨p, hp⟩]
refine le_antisymm ?_ ?_
· rintro v ⟨p1, hp1, p2, hp2, rfl⟩
exact ⟨p1 -ᵥ p2 +ᵥ p, vadd_mem_of_mem_direction (vsub_mem_direction hp1 hp2) hp, vadd_vsub _ _⟩
· rintro v ⟨p2, hp2, rfl⟩
exact ⟨p2, hp2, p, hp, rfl⟩
#align affine_subspace.coe_direction_eq_vsub_set_right AffineSubspace.coe_direction_eq_vsub_set_right
/-- Given a point in an affine subspace, the set of vectors in its direction equals the set of
vectors subtracting that point on the left. -/
theorem coe_direction_eq_vsub_set_left {s : AffineSubspace k P} {p : P} (hp : p ∈ s) :
(s.direction : Set V) = (p -ᵥ ·) '' s := by
ext v
rw [SetLike.mem_coe, ← Submodule.neg_mem_iff, ← SetLike.mem_coe,
coe_direction_eq_vsub_set_right hp, Set.mem_image, Set.mem_image]
conv_lhs =>
congr
ext
rw [← neg_vsub_eq_vsub_rev, neg_inj]
#align affine_subspace.coe_direction_eq_vsub_set_left AffineSubspace.coe_direction_eq_vsub_set_left
/-- Given a point in an affine subspace, a vector is in its direction if and only if it results from
subtracting that point on the right. -/
theorem mem_direction_iff_eq_vsub_right {s : AffineSubspace k P} {p : P} (hp : p ∈ s) (v : V) :
v ∈ s.direction ↔ ∃ p2 ∈ s, v = p2 -ᵥ p := by
rw [← SetLike.mem_coe, coe_direction_eq_vsub_set_right hp]
exact ⟨fun ⟨p2, hp2, hv⟩ => ⟨p2, hp2, hv.symm⟩, fun ⟨p2, hp2, hv⟩ => ⟨p2, hp2, hv.symm⟩⟩
#align affine_subspace.mem_direction_iff_eq_vsub_right AffineSubspace.mem_direction_iff_eq_vsub_right
/-- Given a point in an affine subspace, a vector is in its direction if and only if it results from
subtracting that point on the left. -/
theorem mem_direction_iff_eq_vsub_left {s : AffineSubspace k P} {p : P} (hp : p ∈ s) (v : V) :
v ∈ s.direction ↔ ∃ p2 ∈ s, v = p -ᵥ p2 := by
rw [← SetLike.mem_coe, coe_direction_eq_vsub_set_left hp]
exact ⟨fun ⟨p2, hp2, hv⟩ => ⟨p2, hp2, hv.symm⟩, fun ⟨p2, hp2, hv⟩ => ⟨p2, hp2, hv.symm⟩⟩
#align affine_subspace.mem_direction_iff_eq_vsub_left AffineSubspace.mem_direction_iff_eq_vsub_left
/-- Given a point in an affine subspace, a result of subtracting that point on the right is in the
direction if and only if the other point is in the subspace. -/
theorem vsub_right_mem_direction_iff_mem {s : AffineSubspace k P} {p : P} (hp : p ∈ s) (p2 : P) :
p2 -ᵥ p ∈ s.direction ↔ p2 ∈ s := by
rw [mem_direction_iff_eq_vsub_right hp]
simp
#align affine_subspace.vsub_right_mem_direction_iff_mem AffineSubspace.vsub_right_mem_direction_iff_mem
/-- Given a point in an affine subspace, a result of subtracting that point on the left is in the
direction if and only if the other point is in the subspace. -/
theorem vsub_left_mem_direction_iff_mem {s : AffineSubspace k P} {p : P} (hp : p ∈ s) (p2 : P) :
p -ᵥ p2 ∈ s.direction ↔ p2 ∈ s := by
rw [mem_direction_iff_eq_vsub_left hp]
simp
#align affine_subspace.vsub_left_mem_direction_iff_mem AffineSubspace.vsub_left_mem_direction_iff_mem
/-- Two affine subspaces are equal if they have the same points. -/
theorem coe_injective : Function.Injective ((↑) : AffineSubspace k P → Set P) :=
SetLike.coe_injective
#align affine_subspace.coe_injective AffineSubspace.coe_injective
@[ext]
theorem ext {p q : AffineSubspace k P} (h : ∀ x, x ∈ p ↔ x ∈ q) : p = q :=
SetLike.ext h
#align affine_subspace.ext AffineSubspace.ext
-- Porting note: removed `simp`, proof is `simp only [SetLike.ext'_iff]`
theorem ext_iff (s₁ s₂ : AffineSubspace k P) : (s₁ : Set P) = s₂ ↔ s₁ = s₂ :=
SetLike.ext'_iff.symm
#align affine_subspace.ext_iff AffineSubspace.ext_iff
/-- Two affine subspaces with the same direction and nonempty intersection are equal. -/
theorem ext_of_direction_eq {s1 s2 : AffineSubspace k P} (hd : s1.direction = s2.direction)
(hn : ((s1 : Set P) ∩ s2).Nonempty) : s1 = s2 := by
ext p
have hq1 := Set.mem_of_mem_inter_left hn.some_mem
have hq2 := Set.mem_of_mem_inter_right hn.some_mem
constructor
· intro hp
rw [← vsub_vadd p hn.some]
refine vadd_mem_of_mem_direction ?_ hq2
rw [← hd]
exact vsub_mem_direction hp hq1
· intro hp
rw [← vsub_vadd p hn.some]
refine vadd_mem_of_mem_direction ?_ hq1
rw [hd]
exact vsub_mem_direction hp hq2
#align affine_subspace.ext_of_direction_eq AffineSubspace.ext_of_direction_eq
-- See note [reducible non instances]
/-- This is not an instance because it loops with `AddTorsor.nonempty`. -/
abbrev toAddTorsor (s : AffineSubspace k P) [Nonempty s] : AddTorsor s.direction s where
vadd a b := ⟨(a : V) +ᵥ (b : P), vadd_mem_of_mem_direction a.2 b.2⟩
zero_vadd := fun a => by
ext
exact zero_vadd _ _
add_vadd a b c := by
ext
apply add_vadd
vsub a b := ⟨(a : P) -ᵥ (b : P), (vsub_left_mem_direction_iff_mem a.2 _).mpr b.2⟩
vsub_vadd' a b := by
ext
apply AddTorsor.vsub_vadd'
vadd_vsub' a b := by
ext
apply AddTorsor.vadd_vsub'
#align affine_subspace.to_add_torsor AffineSubspace.toAddTorsor
attribute [local instance] toAddTorsor
@[simp, norm_cast]
theorem coe_vsub (s : AffineSubspace k P) [Nonempty s] (a b : s) : ↑(a -ᵥ b) = (a : P) -ᵥ (b : P) :=
rfl
#align affine_subspace.coe_vsub AffineSubspace.coe_vsub
@[simp, norm_cast]
theorem coe_vadd (s : AffineSubspace k P) [Nonempty s] (a : s.direction) (b : s) :
↑(a +ᵥ b) = (a : V) +ᵥ (b : P) :=
rfl
#align affine_subspace.coe_vadd AffineSubspace.coe_vadd
/-- Embedding of an affine subspace to the ambient space, as an affine map. -/
protected def subtype (s : AffineSubspace k P) [Nonempty s] : s →ᵃ[k] P where
toFun := (↑)
linear := s.direction.subtype
map_vadd' _ _ := rfl
#align affine_subspace.subtype AffineSubspace.subtype
@[simp]
theorem subtype_linear (s : AffineSubspace k P) [Nonempty s] :
s.subtype.linear = s.direction.subtype := rfl
#align affine_subspace.subtype_linear AffineSubspace.subtype_linear
theorem subtype_apply (s : AffineSubspace k P) [Nonempty s] (p : s) : s.subtype p = p :=
rfl
#align affine_subspace.subtype_apply AffineSubspace.subtype_apply
@[simp]
theorem coeSubtype (s : AffineSubspace k P) [Nonempty s] : (s.subtype : s → P) = ((↑) : s → P) :=
rfl
#align affine_subspace.coe_subtype AffineSubspace.coeSubtype
theorem injective_subtype (s : AffineSubspace k P) [Nonempty s] : Function.Injective s.subtype :=
Subtype.coe_injective
#align affine_subspace.injective_subtype AffineSubspace.injective_subtype
/-- Two affine subspaces with nonempty intersection are equal if and only if their directions are
equal. -/
theorem eq_iff_direction_eq_of_mem {s₁ s₂ : AffineSubspace k P} {p : P} (h₁ : p ∈ s₁)
(h₂ : p ∈ s₂) : s₁ = s₂ ↔ s₁.direction = s₂.direction :=
⟨fun h => h ▸ rfl, fun h => ext_of_direction_eq h ⟨p, h₁, h₂⟩⟩
#align affine_subspace.eq_iff_direction_eq_of_mem AffineSubspace.eq_iff_direction_eq_of_mem
/-- Construct an affine subspace from a point and a direction. -/
def mk' (p : P) (direction : Submodule k V) : AffineSubspace k P where
carrier := { q | ∃ v ∈ direction, q = v +ᵥ p }
smul_vsub_vadd_mem c p1 p2 p3 hp1 hp2 hp3 := by
rcases hp1 with ⟨v1, hv1, hp1⟩
rcases hp2 with ⟨v2, hv2, hp2⟩
rcases hp3 with ⟨v3, hv3, hp3⟩
use c • (v1 - v2) + v3, direction.add_mem (direction.smul_mem c (direction.sub_mem hv1 hv2)) hv3
simp [hp1, hp2, hp3, vadd_vadd]
#align affine_subspace.mk' AffineSubspace.mk'
/-- An affine subspace constructed from a point and a direction contains that point. -/
theorem self_mem_mk' (p : P) (direction : Submodule k V) : p ∈ mk' p direction :=
⟨0, ⟨direction.zero_mem, (zero_vadd _ _).symm⟩⟩
#align affine_subspace.self_mem_mk' AffineSubspace.self_mem_mk'
/-- An affine subspace constructed from a point and a direction contains the result of adding a
vector in that direction to that point. -/
theorem vadd_mem_mk' {v : V} (p : P) {direction : Submodule k V} (hv : v ∈ direction) :
v +ᵥ p ∈ mk' p direction :=
⟨v, hv, rfl⟩
#align affine_subspace.vadd_mem_mk' AffineSubspace.vadd_mem_mk'
/-- An affine subspace constructed from a point and a direction is nonempty. -/
theorem mk'_nonempty (p : P) (direction : Submodule k V) : (mk' p direction : Set P).Nonempty :=
⟨p, self_mem_mk' p direction⟩
#align affine_subspace.mk'_nonempty AffineSubspace.mk'_nonempty
/-- The direction of an affine subspace constructed from a point and a direction. -/
@[simp]
theorem direction_mk' (p : P) (direction : Submodule k V) :
(mk' p direction).direction = direction := by
ext v
rw [mem_direction_iff_eq_vsub (mk'_nonempty _ _)]
constructor
· rintro ⟨p1, ⟨v1, hv1, hp1⟩, p2, ⟨v2, hv2, hp2⟩, hv⟩
rw [hv, hp1, hp2, vadd_vsub_vadd_cancel_right]
exact direction.sub_mem hv1 hv2
· exact fun hv => ⟨v +ᵥ p, vadd_mem_mk' _ hv, p, self_mem_mk' _ _, (vadd_vsub _ _).symm⟩
#align affine_subspace.direction_mk' AffineSubspace.direction_mk'
/-- A point lies in an affine subspace constructed from another point and a direction if and only
if their difference is in that direction. -/
theorem mem_mk'_iff_vsub_mem {p₁ p₂ : P} {direction : Submodule k V} :
p₂ ∈ mk' p₁ direction ↔ p₂ -ᵥ p₁ ∈ direction := by
refine ⟨fun h => ?_, fun h => ?_⟩
· rw [← direction_mk' p₁ direction]
exact vsub_mem_direction h (self_mem_mk' _ _)
· rw [← vsub_vadd p₂ p₁]
exact vadd_mem_mk' p₁ h
#align affine_subspace.mem_mk'_iff_vsub_mem AffineSubspace.mem_mk'_iff_vsub_mem
/-- Constructing an affine subspace from a point in a subspace and that subspace's direction
yields the original subspace. -/
@[simp]
theorem mk'_eq {s : AffineSubspace k P} {p : P} (hp : p ∈ s) : mk' p s.direction = s :=
ext_of_direction_eq (direction_mk' p s.direction) ⟨p, Set.mem_inter (self_mem_mk' _ _) hp⟩
#align affine_subspace.mk'_eq AffineSubspace.mk'_eq
/-- If an affine subspace contains a set of points, it contains the `spanPoints` of that set. -/
theorem spanPoints_subset_coe_of_subset_coe {s : Set P} {s1 : AffineSubspace k P} (h : s ⊆ s1) :
spanPoints k s ⊆ s1 := by
rintro p ⟨p1, hp1, v, hv, hp⟩
rw [hp]
have hp1s1 : p1 ∈ (s1 : Set P) := Set.mem_of_mem_of_subset hp1 h
refine vadd_mem_of_mem_direction ?_ hp1s1
have hs : vectorSpan k s ≤ s1.direction := vectorSpan_mono k h
rw [SetLike.le_def] at hs
rw [← SetLike.mem_coe]
exact Set.mem_of_mem_of_subset hv hs
#align affine_subspace.span_points_subset_coe_of_subset_coe AffineSubspace.spanPoints_subset_coe_of_subset_coe
end AffineSubspace
namespace Submodule
variable {k V : Type*} [Ring k] [AddCommGroup V] [Module k V]
@[simp]
theorem mem_toAffineSubspace {p : Submodule k V} {x : V} :
x ∈ p.toAffineSubspace ↔ x ∈ p :=
Iff.rfl
@[simp]
theorem toAffineSubspace_direction (s : Submodule k V) : s.toAffineSubspace.direction = s := by
ext x; simp [← s.toAffineSubspace.vadd_mem_iff_mem_direction _ s.zero_mem]
end Submodule
theorem AffineMap.lineMap_mem {k V P : Type*} [Ring k] [AddCommGroup V] [Module k V]
[AddTorsor V P] {Q : AffineSubspace k P} {p₀ p₁ : P} (c : k) (h₀ : p₀ ∈ Q) (h₁ : p₁ ∈ Q) :
AffineMap.lineMap p₀ p₁ c ∈ Q := by
rw [AffineMap.lineMap_apply]
exact Q.smul_vsub_vadd_mem c h₁ h₀ h₀
#align affine_map.line_map_mem AffineMap.lineMap_mem
section affineSpan
variable (k : Type*) {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
[AffineSpace V P]
/-- The affine span of a set of points is the smallest affine subspace containing those points.
(Actually defined here in terms of spans in modules.) -/
def affineSpan (s : Set P) : AffineSubspace k P where
carrier := spanPoints k s
smul_vsub_vadd_mem c _ _ _ hp1 hp2 hp3 :=
vadd_mem_spanPoints_of_mem_spanPoints_of_mem_vectorSpan k hp3
((vectorSpan k s).smul_mem c
(vsub_mem_vectorSpan_of_mem_spanPoints_of_mem_spanPoints k hp1 hp2))
#align affine_span affineSpan
/-- The affine span, converted to a set, is `spanPoints`. -/
@[simp]
theorem coe_affineSpan (s : Set P) : (affineSpan k s : Set P) = spanPoints k s :=
rfl
#align coe_affine_span coe_affineSpan
/-- A set is contained in its affine span. -/
theorem subset_affineSpan (s : Set P) : s ⊆ affineSpan k s :=
subset_spanPoints k s
#align subset_affine_span subset_affineSpan
/-- The direction of the affine span is the `vectorSpan`. -/
theorem direction_affineSpan (s : Set P) : (affineSpan k s).direction = vectorSpan k s := by
apply le_antisymm
· refine Submodule.span_le.2 ?_
rintro v ⟨p1, ⟨p2, hp2, v1, hv1, hp1⟩, p3, ⟨p4, hp4, v2, hv2, hp3⟩, rfl⟩
simp only [SetLike.mem_coe]
rw [hp1, hp3, vsub_vadd_eq_vsub_sub, vadd_vsub_assoc]
exact
(vectorSpan k s).sub_mem ((vectorSpan k s).add_mem hv1 (vsub_mem_vectorSpan k hp2 hp4)) hv2
· exact vectorSpan_mono k (subset_spanPoints k s)
#align direction_affine_span direction_affineSpan
/-- A point in a set is in its affine span. -/
theorem mem_affineSpan {p : P} {s : Set P} (hp : p ∈ s) : p ∈ affineSpan k s :=
mem_spanPoints k p s hp
#align mem_affine_span mem_affineSpan
end affineSpan
namespace AffineSubspace
variable {k : Type*} {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
[S : AffineSpace V P]
instance : CompleteLattice (AffineSubspace k P) :=
{
PartialOrder.lift ((↑) : AffineSubspace k P → Set P)
coe_injective with
sup := fun s1 s2 => affineSpan k (s1 ∪ s2)
le_sup_left := fun s1 s2 =>
Set.Subset.trans Set.subset_union_left (subset_spanPoints k _)
le_sup_right := fun s1 s2 =>
Set.Subset.trans Set.subset_union_right (subset_spanPoints k _)
sup_le := fun s1 s2 s3 hs1 hs2 => spanPoints_subset_coe_of_subset_coe (Set.union_subset hs1 hs2)
inf := fun s1 s2 =>
mk (s1 ∩ s2) fun c p1 p2 p3 hp1 hp2 hp3 =>
⟨s1.smul_vsub_vadd_mem c hp1.1 hp2.1 hp3.1, s2.smul_vsub_vadd_mem c hp1.2 hp2.2 hp3.2⟩
inf_le_left := fun _ _ => Set.inter_subset_left
inf_le_right := fun _ _ => Set.inter_subset_right
le_sInf := fun S s1 hs1 => by
-- Porting note: surely there is an easier way?
refine Set.subset_sInter (t := (s1 : Set P)) ?_
rintro t ⟨s, _hs, rfl⟩
exact Set.subset_iInter (hs1 s)
top :=
{ carrier := Set.univ
smul_vsub_vadd_mem := fun _ _ _ _ _ _ _ => Set.mem_univ _ }
le_top := fun _ _ _ => Set.mem_univ _
bot :=
{ carrier := ∅
smul_vsub_vadd_mem := fun _ _ _ _ => False.elim }
bot_le := fun _ _ => False.elim
sSup := fun s => affineSpan k (⋃ s' ∈ s, (s' : Set P))
sInf := fun s =>
mk (⋂ s' ∈ s, (s' : Set P)) fun c p1 p2 p3 hp1 hp2 hp3 =>
Set.mem_iInter₂.2 fun s2 hs2 => by
rw [Set.mem_iInter₂] at *
exact s2.smul_vsub_vadd_mem c (hp1 s2 hs2) (hp2 s2 hs2) (hp3 s2 hs2)
le_sSup := fun _ _ h => Set.Subset.trans (Set.subset_biUnion_of_mem h) (subset_spanPoints k _)
sSup_le := fun _ _ h => spanPoints_subset_coe_of_subset_coe (Set.iUnion₂_subset h)
sInf_le := fun _ _ => Set.biInter_subset_of_mem
le_inf := fun _ _ _ => Set.subset_inter }
instance : Inhabited (AffineSubspace k P) :=
⟨⊤⟩
/-- The `≤` order on subspaces is the same as that on the corresponding sets. -/
theorem le_def (s1 s2 : AffineSubspace k P) : s1 ≤ s2 ↔ (s1 : Set P) ⊆ s2 :=
Iff.rfl
#align affine_subspace.le_def AffineSubspace.le_def
/-- One subspace is less than or equal to another if and only if all its points are in the second
subspace. -/
theorem le_def' (s1 s2 : AffineSubspace k P) : s1 ≤ s2 ↔ ∀ p ∈ s1, p ∈ s2 :=
Iff.rfl
#align affine_subspace.le_def' AffineSubspace.le_def'
/-- The `<` order on subspaces is the same as that on the corresponding sets. -/
theorem lt_def (s1 s2 : AffineSubspace k P) : s1 < s2 ↔ (s1 : Set P) ⊂ s2 :=
Iff.rfl
#align affine_subspace.lt_def AffineSubspace.lt_def
/-- One subspace is not less than or equal to another if and only if it has a point not in the
second subspace. -/
theorem not_le_iff_exists (s1 s2 : AffineSubspace k P) : ¬s1 ≤ s2 ↔ ∃ p ∈ s1, p ∉ s2 :=
Set.not_subset
#align affine_subspace.not_le_iff_exists AffineSubspace.not_le_iff_exists
/-- If a subspace is less than another, there is a point only in the second. -/
theorem exists_of_lt {s1 s2 : AffineSubspace k P} (h : s1 < s2) : ∃ p ∈ s2, p ∉ s1 :=
Set.exists_of_ssubset h
#align affine_subspace.exists_of_lt AffineSubspace.exists_of_lt
/-- A subspace is less than another if and only if it is less than or equal to the second subspace
and there is a point only in the second. -/
theorem lt_iff_le_and_exists (s1 s2 : AffineSubspace k P) :
s1 < s2 ↔ s1 ≤ s2 ∧ ∃ p ∈ s2, p ∉ s1 := by
rw [lt_iff_le_not_le, not_le_iff_exists]
#align affine_subspace.lt_iff_le_and_exists AffineSubspace.lt_iff_le_and_exists
/-- If an affine subspace is nonempty and contained in another with the same direction, they are
equal. -/
theorem eq_of_direction_eq_of_nonempty_of_le {s₁ s₂ : AffineSubspace k P}
(hd : s₁.direction = s₂.direction) (hn : (s₁ : Set P).Nonempty) (hle : s₁ ≤ s₂) : s₁ = s₂ :=
let ⟨p, hp⟩ := hn
ext_of_direction_eq hd ⟨p, hp, hle hp⟩
#align affine_subspace.eq_of_direction_eq_of_nonempty_of_le AffineSubspace.eq_of_direction_eq_of_nonempty_of_le
variable (k V)
/-- The affine span is the `sInf` of subspaces containing the given points. -/
theorem affineSpan_eq_sInf (s : Set P) :
affineSpan k s = sInf { s' : AffineSubspace k P | s ⊆ s' } :=
le_antisymm (spanPoints_subset_coe_of_subset_coe <| Set.subset_iInter₂ fun _ => id)
(sInf_le (subset_spanPoints k _))
#align affine_subspace.affine_span_eq_Inf AffineSubspace.affineSpan_eq_sInf
variable (P)
/-- The Galois insertion formed by `affineSpan` and coercion back to a set. -/
protected def gi : GaloisInsertion (affineSpan k) ((↑) : AffineSubspace k P → Set P) where
choice s _ := affineSpan k s
gc s1 _s2 :=
⟨fun h => Set.Subset.trans (subset_spanPoints k s1) h, spanPoints_subset_coe_of_subset_coe⟩
le_l_u _ := subset_spanPoints k _
choice_eq _ _ := rfl
#align affine_subspace.gi AffineSubspace.gi
/-- The span of the empty set is `⊥`. -/
@[simp]
theorem span_empty : affineSpan k (∅ : Set P) = ⊥ :=
(AffineSubspace.gi k V P).gc.l_bot
#align affine_subspace.span_empty AffineSubspace.span_empty
/-- The span of `univ` is `⊤`. -/
@[simp]
theorem span_univ : affineSpan k (Set.univ : Set P) = ⊤ :=
eq_top_iff.2 <| subset_spanPoints k _
#align affine_subspace.span_univ AffineSubspace.span_univ
variable {k V P}
theorem _root_.affineSpan_le {s : Set P} {Q : AffineSubspace k P} :
affineSpan k s ≤ Q ↔ s ⊆ (Q : Set P) :=
(AffineSubspace.gi k V P).gc _ _
#align affine_span_le affineSpan_le
variable (k V) {p₁ p₂ : P}
/-- The affine span of a single point, coerced to a set, contains just that point. -/
@[simp 1001] -- Porting note: this needs to take priority over `coe_affineSpan`
theorem coe_affineSpan_singleton (p : P) : (affineSpan k ({p} : Set P) : Set P) = {p} := by
ext x
rw [mem_coe, ← vsub_right_mem_direction_iff_mem (mem_affineSpan k (Set.mem_singleton p)) _,
direction_affineSpan]
simp
#align affine_subspace.coe_affine_span_singleton AffineSubspace.coe_affineSpan_singleton
/-- A point is in the affine span of a single point if and only if they are equal. -/
@[simp]
theorem mem_affineSpan_singleton : p₁ ∈ affineSpan k ({p₂} : Set P) ↔ p₁ = p₂ := by
simp [← mem_coe]
#align affine_subspace.mem_affine_span_singleton AffineSubspace.mem_affineSpan_singleton
@[simp]
theorem preimage_coe_affineSpan_singleton (x : P) :
((↑) : affineSpan k ({x} : Set P) → P) ⁻¹' {x} = univ :=
eq_univ_of_forall fun y => (AffineSubspace.mem_affineSpan_singleton _ _).1 y.2
#align affine_subspace.preimage_coe_affine_span_singleton AffineSubspace.preimage_coe_affineSpan_singleton
/-- The span of a union of sets is the sup of their spans. -/
theorem span_union (s t : Set P) : affineSpan k (s ∪ t) = affineSpan k s ⊔ affineSpan k t :=
(AffineSubspace.gi k V P).gc.l_sup
#align affine_subspace.span_union AffineSubspace.span_union
/-- The span of a union of an indexed family of sets is the sup of their spans. -/
theorem span_iUnion {ι : Type*} (s : ι → Set P) :
affineSpan k (⋃ i, s i) = ⨆ i, affineSpan k (s i) :=
(AffineSubspace.gi k V P).gc.l_iSup
#align affine_subspace.span_Union AffineSubspace.span_iUnion
variable (P)
/-- `⊤`, coerced to a set, is the whole set of points. -/
@[simp]
theorem top_coe : ((⊤ : AffineSubspace k P) : Set P) = Set.univ :=
rfl
#align affine_subspace.top_coe AffineSubspace.top_coe
variable {P}
/-- All points are in `⊤`. -/
@[simp]
theorem mem_top (p : P) : p ∈ (⊤ : AffineSubspace k P) :=
Set.mem_univ p
#align affine_subspace.mem_top AffineSubspace.mem_top
variable (P)
/-- The direction of `⊤` is the whole module as a submodule. -/
@[simp]
theorem direction_top : (⊤ : AffineSubspace k P).direction = ⊤ := by
cases' S.nonempty with p
ext v
refine ⟨imp_intro Submodule.mem_top, fun _hv => ?_⟩
have hpv : (v +ᵥ p -ᵥ p : V) ∈ (⊤ : AffineSubspace k P).direction :=
vsub_mem_direction (mem_top k V _) (mem_top k V _)
rwa [vadd_vsub] at hpv
#align affine_subspace.direction_top AffineSubspace.direction_top
/-- `⊥`, coerced to a set, is the empty set. -/
@[simp]
theorem bot_coe : ((⊥ : AffineSubspace k P) : Set P) = ∅ :=
rfl
#align affine_subspace.bot_coe AffineSubspace.bot_coe
theorem bot_ne_top : (⊥ : AffineSubspace k P) ≠ ⊤ := by
intro contra
rw [← ext_iff, bot_coe, top_coe] at contra
exact Set.empty_ne_univ contra
#align affine_subspace.bot_ne_top AffineSubspace.bot_ne_top
instance : Nontrivial (AffineSubspace k P) :=
⟨⟨⊥, ⊤, bot_ne_top k V P⟩⟩
theorem nonempty_of_affineSpan_eq_top {s : Set P} (h : affineSpan k s = ⊤) : s.Nonempty := by
rw [Set.nonempty_iff_ne_empty]
rintro rfl
rw [AffineSubspace.span_empty] at h
exact bot_ne_top k V P h
#align affine_subspace.nonempty_of_affine_span_eq_top AffineSubspace.nonempty_of_affineSpan_eq_top
/-- If the affine span of a set is `⊤`, then the vector span of the same set is the `⊤`. -/
theorem vectorSpan_eq_top_of_affineSpan_eq_top {s : Set P} (h : affineSpan k s = ⊤) :
vectorSpan k s = ⊤ := by rw [← direction_affineSpan, h, direction_top]
#align affine_subspace.vector_span_eq_top_of_affine_span_eq_top AffineSubspace.vectorSpan_eq_top_of_affineSpan_eq_top
/-- For a nonempty set, the affine span is `⊤` iff its vector span is `⊤`. -/
theorem affineSpan_eq_top_iff_vectorSpan_eq_top_of_nonempty {s : Set P} (hs : s.Nonempty) :
affineSpan k s = ⊤ ↔ vectorSpan k s = ⊤ := by
refine ⟨vectorSpan_eq_top_of_affineSpan_eq_top k V P, ?_⟩
intro h
suffices Nonempty (affineSpan k s) by
obtain ⟨p, hp : p ∈ affineSpan k s⟩ := this
rw [eq_iff_direction_eq_of_mem hp (mem_top k V p), direction_affineSpan, h, direction_top]
obtain ⟨x, hx⟩ := hs
exact ⟨⟨x, mem_affineSpan k hx⟩⟩
#align affine_subspace.affine_span_eq_top_iff_vector_span_eq_top_of_nonempty AffineSubspace.affineSpan_eq_top_iff_vectorSpan_eq_top_of_nonempty
/-- For a non-trivial space, the affine span of a set is `⊤` iff its vector span is `⊤`. -/
theorem affineSpan_eq_top_iff_vectorSpan_eq_top_of_nontrivial {s : Set P} [Nontrivial P] :
affineSpan k s = ⊤ ↔ vectorSpan k s = ⊤ := by
rcases s.eq_empty_or_nonempty with hs | hs
· simp [hs, subsingleton_iff_bot_eq_top, AddTorsor.subsingleton_iff V P, not_subsingleton]
· rw [affineSpan_eq_top_iff_vectorSpan_eq_top_of_nonempty k V P hs]
#align affine_subspace.affine_span_eq_top_iff_vector_span_eq_top_of_nontrivial AffineSubspace.affineSpan_eq_top_iff_vectorSpan_eq_top_of_nontrivial
theorem card_pos_of_affineSpan_eq_top {ι : Type*} [Fintype ι] {p : ι → P}
(h : affineSpan k (range p) = ⊤) : 0 < Fintype.card ι := by
obtain ⟨-, ⟨i, -⟩⟩ := nonempty_of_affineSpan_eq_top k V P h
exact Fintype.card_pos_iff.mpr ⟨i⟩
#align affine_subspace.card_pos_of_affine_span_eq_top AffineSubspace.card_pos_of_affineSpan_eq_top
attribute [local instance] toAddTorsor
/-- The top affine subspace is linearly equivalent to the affine space.
This is the affine version of `Submodule.topEquiv`. -/
@[simps! linear apply symm_apply_coe]
def topEquiv : (⊤ : AffineSubspace k P) ≃ᵃ[k] P where
toEquiv := Equiv.Set.univ P
linear := .ofEq _ _ (direction_top _ _ _) ≪≫ₗ Submodule.topEquiv
map_vadd' _p _v := rfl
variable {P}
/-- No points are in `⊥`. -/
theorem not_mem_bot (p : P) : p ∉ (⊥ : AffineSubspace k P) :=
Set.not_mem_empty p
#align affine_subspace.not_mem_bot AffineSubspace.not_mem_bot
variable (P)
/-- The direction of `⊥` is the submodule `⊥`. -/
@[simp]
theorem direction_bot : (⊥ : AffineSubspace k P).direction = ⊥ := by
rw [direction_eq_vectorSpan, bot_coe, vectorSpan_def, vsub_empty, Submodule.span_empty]
#align affine_subspace.direction_bot AffineSubspace.direction_bot
variable {k V P}
@[simp]
theorem coe_eq_bot_iff (Q : AffineSubspace k P) : (Q : Set P) = ∅ ↔ Q = ⊥ :=
coe_injective.eq_iff' (bot_coe _ _ _)
#align affine_subspace.coe_eq_bot_iff AffineSubspace.coe_eq_bot_iff
@[simp]
theorem coe_eq_univ_iff (Q : AffineSubspace k P) : (Q : Set P) = univ ↔ Q = ⊤ :=
coe_injective.eq_iff' (top_coe _ _ _)
#align affine_subspace.coe_eq_univ_iff AffineSubspace.coe_eq_univ_iff
theorem nonempty_iff_ne_bot (Q : AffineSubspace k P) : (Q : Set P).Nonempty ↔ Q ≠ ⊥ := by
rw [nonempty_iff_ne_empty]
exact not_congr Q.coe_eq_bot_iff
#align affine_subspace.nonempty_iff_ne_bot AffineSubspace.nonempty_iff_ne_bot
theorem eq_bot_or_nonempty (Q : AffineSubspace k P) : Q = ⊥ ∨ (Q : Set P).Nonempty := by
rw [nonempty_iff_ne_bot]
apply eq_or_ne
#align affine_subspace.eq_bot_or_nonempty AffineSubspace.eq_bot_or_nonempty
theorem subsingleton_of_subsingleton_span_eq_top {s : Set P} (h₁ : s.Subsingleton)
(h₂ : affineSpan k s = ⊤) : Subsingleton P := by
obtain ⟨p, hp⟩ := AffineSubspace.nonempty_of_affineSpan_eq_top k V P h₂
have : s = {p} := Subset.antisymm (fun q hq => h₁ hq hp) (by simp [hp])
rw [this, ← AffineSubspace.ext_iff, AffineSubspace.coe_affineSpan_singleton,
AffineSubspace.top_coe, eq_comm, ← subsingleton_iff_singleton (mem_univ _)] at h₂
exact subsingleton_of_univ_subsingleton h₂
#align affine_subspace.subsingleton_of_subsingleton_span_eq_top AffineSubspace.subsingleton_of_subsingleton_span_eq_top
theorem eq_univ_of_subsingleton_span_eq_top {s : Set P} (h₁ : s.Subsingleton)
(h₂ : affineSpan k s = ⊤) : s = (univ : Set P) := by
obtain ⟨p, hp⟩ := AffineSubspace.nonempty_of_affineSpan_eq_top k V P h₂
have : s = {p} := Subset.antisymm (fun q hq => h₁ hq hp) (by simp [hp])
rw [this, eq_comm, ← subsingleton_iff_singleton (mem_univ p), subsingleton_univ_iff]
exact subsingleton_of_subsingleton_span_eq_top h₁ h₂
#align affine_subspace.eq_univ_of_subsingleton_span_eq_top AffineSubspace.eq_univ_of_subsingleton_span_eq_top
/-- A nonempty affine subspace is `⊤` if and only if its direction is `⊤`. -/
@[simp]
theorem direction_eq_top_iff_of_nonempty {s : AffineSubspace k P} (h : (s : Set P).Nonempty) :
s.direction = ⊤ ↔ s = ⊤ := by
constructor
· intro hd
rw [← direction_top k V P] at hd
refine ext_of_direction_eq hd ?_
simp [h]
· rintro rfl
simp
#align affine_subspace.direction_eq_top_iff_of_nonempty AffineSubspace.direction_eq_top_iff_of_nonempty
/-- The inf of two affine subspaces, coerced to a set, is the intersection of the two sets of
points. -/
@[simp]
theorem inf_coe (s1 s2 : AffineSubspace k P) : (s1 ⊓ s2 : Set P) = (s1 : Set P) ∩ s2 :=
rfl
#align affine_subspace.inf_coe AffineSubspace.inf_coe
/-- A point is in the inf of two affine subspaces if and only if it is in both of them. -/
theorem mem_inf_iff (p : P) (s1 s2 : AffineSubspace k P) : p ∈ s1 ⊓ s2 ↔ p ∈ s1 ∧ p ∈ s2 :=
Iff.rfl
#align affine_subspace.mem_inf_iff AffineSubspace.mem_inf_iff
/-- The direction of the inf of two affine subspaces is less than or equal to the inf of their
directions. -/
theorem direction_inf (s1 s2 : AffineSubspace k P) :
(s1 ⊓ s2).direction ≤ s1.direction ⊓ s2.direction := by
simp only [direction_eq_vectorSpan, vectorSpan_def]
exact
le_inf (sInf_le_sInf fun p hp => trans (vsub_self_mono inter_subset_left) hp)
(sInf_le_sInf fun p hp => trans (vsub_self_mono inter_subset_right) hp)
#align affine_subspace.direction_inf AffineSubspace.direction_inf
/-- If two affine subspaces have a point in common, the direction of their inf equals the inf of
their directions. -/
theorem direction_inf_of_mem {s₁ s₂ : AffineSubspace k P} {p : P} (h₁ : p ∈ s₁) (h₂ : p ∈ s₂) :
(s₁ ⊓ s₂).direction = s₁.direction ⊓ s₂.direction := by
ext v
rw [Submodule.mem_inf, ← vadd_mem_iff_mem_direction v h₁, ← vadd_mem_iff_mem_direction v h₂, ←
vadd_mem_iff_mem_direction v ((mem_inf_iff p s₁ s₂).2 ⟨h₁, h₂⟩), mem_inf_iff]
#align affine_subspace.direction_inf_of_mem AffineSubspace.direction_inf_of_mem
/-- If two affine subspaces have a point in their inf, the direction of their inf equals the inf of
their directions. -/
theorem direction_inf_of_mem_inf {s₁ s₂ : AffineSubspace k P} {p : P} (h : p ∈ s₁ ⊓ s₂) :
(s₁ ⊓ s₂).direction = s₁.direction ⊓ s₂.direction :=
direction_inf_of_mem ((mem_inf_iff p s₁ s₂).1 h).1 ((mem_inf_iff p s₁ s₂).1 h).2
#align affine_subspace.direction_inf_of_mem_inf AffineSubspace.direction_inf_of_mem_inf
/-- If one affine subspace is less than or equal to another, the same applies to their
directions. -/
theorem direction_le {s1 s2 : AffineSubspace k P} (h : s1 ≤ s2) : s1.direction ≤ s2.direction := by
simp only [direction_eq_vectorSpan, vectorSpan_def]
exact vectorSpan_mono k h
#align affine_subspace.direction_le AffineSubspace.direction_le
/-- If one nonempty affine subspace is less than another, the same applies to their directions -/
theorem direction_lt_of_nonempty {s1 s2 : AffineSubspace k P} (h : s1 < s2)
(hn : (s1 : Set P).Nonempty) : s1.direction < s2.direction := by
cases' hn with p hp
rw [lt_iff_le_and_exists] at h
rcases h with ⟨hle, p2, hp2, hp2s1⟩
rw [SetLike.lt_iff_le_and_exists]
use direction_le hle, p2 -ᵥ p, vsub_mem_direction hp2 (hle hp)
intro hm
rw [vsub_right_mem_direction_iff_mem hp p2] at hm
exact hp2s1 hm
#align affine_subspace.direction_lt_of_nonempty AffineSubspace.direction_lt_of_nonempty
/-- The sup of the directions of two affine subspaces is less than or equal to the direction of
their sup. -/
theorem sup_direction_le (s1 s2 : AffineSubspace k P) :
s1.direction ⊔ s2.direction ≤ (s1 ⊔ s2).direction := by
simp only [direction_eq_vectorSpan, vectorSpan_def]
exact
sup_le
(sInf_le_sInf fun p hp => Set.Subset.trans (vsub_self_mono (le_sup_left : s1 ≤ s1 ⊔ s2)) hp)
(sInf_le_sInf fun p hp => Set.Subset.trans (vsub_self_mono (le_sup_right : s2 ≤ s1 ⊔ s2)) hp)
#align affine_subspace.sup_direction_le AffineSubspace.sup_direction_le
/-- The sup of the directions of two nonempty affine subspaces with empty intersection is less than
the direction of their sup. -/
theorem sup_direction_lt_of_nonempty_of_inter_empty {s1 s2 : AffineSubspace k P}
(h1 : (s1 : Set P).Nonempty) (h2 : (s2 : Set P).Nonempty) (he : (s1 ∩ s2 : Set P) = ∅) :
s1.direction ⊔ s2.direction < (s1 ⊔ s2).direction := by
cases' h1 with p1 hp1
cases' h2 with p2 hp2
rw [SetLike.lt_iff_le_and_exists]
use sup_direction_le s1 s2, p2 -ᵥ p1,
vsub_mem_direction ((le_sup_right : s2 ≤ s1 ⊔ s2) hp2) ((le_sup_left : s1 ≤ s1 ⊔ s2) hp1)
intro h
rw [Submodule.mem_sup] at h
rcases h with ⟨v1, hv1, v2, hv2, hv1v2⟩
rw [← sub_eq_zero, sub_eq_add_neg, neg_vsub_eq_vsub_rev, add_comm v1, add_assoc, ←
vadd_vsub_assoc, ← neg_neg v2, add_comm, ← sub_eq_add_neg, ← vsub_vadd_eq_vsub_sub,
vsub_eq_zero_iff_eq] at hv1v2
refine Set.Nonempty.ne_empty ?_ he
use v1 +ᵥ p1, vadd_mem_of_mem_direction hv1 hp1
rw [hv1v2]
exact vadd_mem_of_mem_direction (Submodule.neg_mem _ hv2) hp2
#align affine_subspace.sup_direction_lt_of_nonempty_of_inter_empty AffineSubspace.sup_direction_lt_of_nonempty_of_inter_empty
/-- If the directions of two nonempty affine subspaces span the whole module, they have nonempty
intersection. -/
| Mathlib/LinearAlgebra/AffineSpace/AffineSubspace.lean | 992 | 999 | theorem inter_nonempty_of_nonempty_of_sup_direction_eq_top {s1 s2 : AffineSubspace k P}
(h1 : (s1 : Set P).Nonempty) (h2 : (s2 : Set P).Nonempty)
(hd : s1.direction ⊔ s2.direction = ⊤) : ((s1 : Set P) ∩ s2).Nonempty := by |
by_contra h
rw [Set.not_nonempty_iff_eq_empty] at h
have hlt := sup_direction_lt_of_nonempty_of_inter_empty h1 h2 h
rw [hd] at hlt
exact not_top_lt hlt
|
/-
Copyright (c) 2018 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johannes Hölzl, Rémy Degenne
-/
import Mathlib.Order.Filter.Cofinite
import Mathlib.Order.Hom.CompleteLattice
#align_import order.liminf_limsup from "leanprover-community/mathlib"@"ffde2d8a6e689149e44fd95fa862c23a57f8c780"
/-!
# liminfs and limsups of functions and filters
Defines the liminf/limsup of a function taking values in a conditionally complete lattice, with
respect to an arbitrary filter.
We define `limsSup f` (`limsInf f`) where `f` is a filter taking values in a conditionally complete
lattice. `limsSup f` is the smallest element `a` such that, eventually, `u ≤ a` (and vice versa for
`limsInf f`). To work with the Limsup along a function `u` use `limsSup (map u f)`.
Usually, one defines the Limsup as `inf (sup s)` where the Inf is taken over all sets in the filter.
For instance, in ℕ along a function `u`, this is `inf_n (sup_{k ≥ n} u k)` (and the latter quantity
decreases with `n`, so this is in fact a limit.). There is however a difficulty: it is well possible
that `u` is not bounded on the whole space, only eventually (think of `limsup (fun x ↦ 1/x)` on ℝ.
Then there is no guarantee that the quantity above really decreases (the value of the `sup`
beforehand is not really well defined, as one can not use ∞), so that the Inf could be anything.
So one can not use this `inf sup ...` definition in conditionally complete lattices, and one has
to use a less tractable definition.
In conditionally complete lattices, the definition is only useful for filters which are eventually
bounded above (otherwise, the Limsup would morally be +∞, which does not belong to the space) and
which are frequently bounded below (otherwise, the Limsup would morally be -∞, which is not in the
space either). We start with definitions of these concepts for arbitrary filters, before turning to
the definitions of Limsup and Liminf.
In complete lattices, however, it coincides with the `Inf Sup` definition.
-/
set_option autoImplicit true
open Filter Set Function
variable {α β γ ι ι' : Type*}
namespace Filter
section Relation
/-- `f.IsBounded (≺)`: the filter `f` is eventually bounded w.r.t. the relation `≺`, i.e.
eventually, it is bounded by some uniform bound.
`r` will be usually instantiated with `≤` or `≥`. -/
def IsBounded (r : α → α → Prop) (f : Filter α) :=
∃ b, ∀ᶠ x in f, r x b
#align filter.is_bounded Filter.IsBounded
/-- `f.IsBoundedUnder (≺) u`: the image of the filter `f` under `u` is eventually bounded w.r.t.
the relation `≺`, i.e. eventually, it is bounded by some uniform bound. -/
def IsBoundedUnder (r : α → α → Prop) (f : Filter β) (u : β → α) :=
(map u f).IsBounded r
#align filter.is_bounded_under Filter.IsBoundedUnder
variable {r : α → α → Prop} {f g : Filter α}
/-- `f` is eventually bounded if and only if, there exists an admissible set on which it is
bounded. -/
theorem isBounded_iff : f.IsBounded r ↔ ∃ s ∈ f.sets, ∃ b, s ⊆ { x | r x b } :=
Iff.intro (fun ⟨b, hb⟩ => ⟨{ a | r a b }, hb, b, Subset.refl _⟩) fun ⟨_, hs, b, hb⟩ =>
⟨b, mem_of_superset hs hb⟩
#align filter.is_bounded_iff Filter.isBounded_iff
/-- A bounded function `u` is in particular eventually bounded. -/
theorem isBoundedUnder_of {f : Filter β} {u : β → α} : (∃ b, ∀ x, r (u x) b) → f.IsBoundedUnder r u
| ⟨b, hb⟩ => ⟨b, show ∀ᶠ x in f, r (u x) b from eventually_of_forall hb⟩
#align filter.is_bounded_under_of Filter.isBoundedUnder_of
theorem isBounded_bot : IsBounded r ⊥ ↔ Nonempty α := by simp [IsBounded, exists_true_iff_nonempty]
#align filter.is_bounded_bot Filter.isBounded_bot
theorem isBounded_top : IsBounded r ⊤ ↔ ∃ t, ∀ x, r x t := by simp [IsBounded, eq_univ_iff_forall]
#align filter.is_bounded_top Filter.isBounded_top
theorem isBounded_principal (s : Set α) : IsBounded r (𝓟 s) ↔ ∃ t, ∀ x ∈ s, r x t := by
simp [IsBounded, subset_def]
#align filter.is_bounded_principal Filter.isBounded_principal
theorem isBounded_sup [IsTrans α r] [IsDirected α r] :
IsBounded r f → IsBounded r g → IsBounded r (f ⊔ g)
| ⟨b₁, h₁⟩, ⟨b₂, h₂⟩ =>
let ⟨b, rb₁b, rb₂b⟩ := directed_of r b₁ b₂
⟨b, eventually_sup.mpr
⟨h₁.mono fun _ h => _root_.trans h rb₁b, h₂.mono fun _ h => _root_.trans h rb₂b⟩⟩
#align filter.is_bounded_sup Filter.isBounded_sup
theorem IsBounded.mono (h : f ≤ g) : IsBounded r g → IsBounded r f
| ⟨b, hb⟩ => ⟨b, h hb⟩
#align filter.is_bounded.mono Filter.IsBounded.mono
theorem IsBoundedUnder.mono {f g : Filter β} {u : β → α} (h : f ≤ g) :
g.IsBoundedUnder r u → f.IsBoundedUnder r u := fun hg => IsBounded.mono (map_mono h) hg
#align filter.is_bounded_under.mono Filter.IsBoundedUnder.mono
theorem IsBoundedUnder.mono_le [Preorder β] {l : Filter α} {u v : α → β}
(hu : IsBoundedUnder (· ≤ ·) l u) (hv : v ≤ᶠ[l] u) : IsBoundedUnder (· ≤ ·) l v := by
apply hu.imp
exact fun b hb => (eventually_map.1 hb).mp <| hv.mono fun x => le_trans
#align filter.is_bounded_under.mono_le Filter.IsBoundedUnder.mono_le
theorem IsBoundedUnder.mono_ge [Preorder β] {l : Filter α} {u v : α → β}
(hu : IsBoundedUnder (· ≥ ·) l u) (hv : u ≤ᶠ[l] v) : IsBoundedUnder (· ≥ ·) l v :=
IsBoundedUnder.mono_le (β := βᵒᵈ) hu hv
#align filter.is_bounded_under.mono_ge Filter.IsBoundedUnder.mono_ge
theorem isBoundedUnder_const [IsRefl α r] {l : Filter β} {a : α} : IsBoundedUnder r l fun _ => a :=
⟨a, eventually_map.2 <| eventually_of_forall fun _ => refl _⟩
#align filter.is_bounded_under_const Filter.isBoundedUnder_const
theorem IsBounded.isBoundedUnder {q : β → β → Prop} {u : α → β}
(hu : ∀ a₀ a₁, r a₀ a₁ → q (u a₀) (u a₁)) : f.IsBounded r → f.IsBoundedUnder q u
| ⟨b, h⟩ => ⟨u b, show ∀ᶠ x in f, q (u x) (u b) from h.mono fun x => hu x b⟩
#align filter.is_bounded.is_bounded_under Filter.IsBounded.isBoundedUnder
theorem IsBoundedUnder.comp {l : Filter γ} {q : β → β → Prop} {u : γ → α} {v : α → β}
(hv : ∀ a₀ a₁, r a₀ a₁ → q (v a₀) (v a₁)) : l.IsBoundedUnder r u → l.IsBoundedUnder q (v ∘ u)
| ⟨a, h⟩ => ⟨v a, show ∀ᶠ x in map u l, q (v x) (v a) from h.mono fun x => hv x a⟩
/-- A bounded above function `u` is in particular eventually bounded above. -/
lemma _root_.BddAbove.isBoundedUnder [Preorder α] {f : Filter β} {u : β → α} :
BddAbove (Set.range u) → f.IsBoundedUnder (· ≤ ·) u
| ⟨b, hb⟩ => isBoundedUnder_of ⟨b, by simpa [mem_upperBounds] using hb⟩
/-- A bounded below function `u` is in particular eventually bounded below. -/
lemma _root_.BddBelow.isBoundedUnder [Preorder α] {f : Filter β} {u : β → α} :
BddBelow (Set.range u) → f.IsBoundedUnder (· ≥ ·) u
| ⟨b, hb⟩ => isBoundedUnder_of ⟨b, by simpa [mem_lowerBounds] using hb⟩
theorem _root_.Monotone.isBoundedUnder_le_comp [Preorder α] [Preorder β] {l : Filter γ} {u : γ → α}
{v : α → β} (hv : Monotone v) (hl : l.IsBoundedUnder (· ≤ ·) u) :
l.IsBoundedUnder (· ≤ ·) (v ∘ u) :=
hl.comp hv
theorem _root_.Monotone.isBoundedUnder_ge_comp [Preorder α] [Preorder β] {l : Filter γ} {u : γ → α}
{v : α → β} (hv : Monotone v) (hl : l.IsBoundedUnder (· ≥ ·) u) :
l.IsBoundedUnder (· ≥ ·) (v ∘ u) :=
hl.comp (swap hv)
theorem _root_.Antitone.isBoundedUnder_le_comp [Preorder α] [Preorder β] {l : Filter γ} {u : γ → α}
{v : α → β} (hv : Antitone v) (hl : l.IsBoundedUnder (· ≥ ·) u) :
l.IsBoundedUnder (· ≤ ·) (v ∘ u) :=
hl.comp (swap hv)
theorem _root_.Antitone.isBoundedUnder_ge_comp [Preorder α] [Preorder β] {l : Filter γ} {u : γ → α}
{v : α → β} (hv : Antitone v) (hl : l.IsBoundedUnder (· ≤ ·) u) :
l.IsBoundedUnder (· ≥ ·) (v ∘ u) :=
hl.comp hv
theorem not_isBoundedUnder_of_tendsto_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
[l.NeBot] (hf : Tendsto f l atTop) : ¬IsBoundedUnder (· ≤ ·) l f := by
rintro ⟨b, hb⟩
rw [eventually_map] at hb
obtain ⟨b', h⟩ := exists_gt b
have hb' := (tendsto_atTop.mp hf) b'
have : { x : α | f x ≤ b } ∩ { x : α | b' ≤ f x } = ∅ :=
eq_empty_of_subset_empty fun x hx => (not_le_of_lt h) (le_trans hx.2 hx.1)
exact (nonempty_of_mem (hb.and hb')).ne_empty this
#align filter.not_is_bounded_under_of_tendsto_at_top Filter.not_isBoundedUnder_of_tendsto_atTop
theorem not_isBoundedUnder_of_tendsto_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
[l.NeBot] (hf : Tendsto f l atBot) : ¬IsBoundedUnder (· ≥ ·) l f :=
not_isBoundedUnder_of_tendsto_atTop (β := βᵒᵈ) hf
#align filter.not_is_bounded_under_of_tendsto_at_bot Filter.not_isBoundedUnder_of_tendsto_atBot
theorem IsBoundedUnder.bddAbove_range_of_cofinite [Preorder β] [IsDirected β (· ≤ ·)] {f : α → β}
(hf : IsBoundedUnder (· ≤ ·) cofinite f) : BddAbove (range f) := by
rcases hf with ⟨b, hb⟩
haveI : Nonempty β := ⟨b⟩
rw [← image_univ, ← union_compl_self { x | f x ≤ b }, image_union, bddAbove_union]
exact ⟨⟨b, forall_mem_image.2 fun x => id⟩, (hb.image f).bddAbove⟩
#align filter.is_bounded_under.bdd_above_range_of_cofinite Filter.IsBoundedUnder.bddAbove_range_of_cofinite
theorem IsBoundedUnder.bddBelow_range_of_cofinite [Preorder β] [IsDirected β (· ≥ ·)] {f : α → β}
(hf : IsBoundedUnder (· ≥ ·) cofinite f) : BddBelow (range f) :=
IsBoundedUnder.bddAbove_range_of_cofinite (β := βᵒᵈ) hf
#align filter.is_bounded_under.bdd_below_range_of_cofinite Filter.IsBoundedUnder.bddBelow_range_of_cofinite
theorem IsBoundedUnder.bddAbove_range [Preorder β] [IsDirected β (· ≤ ·)] {f : ℕ → β}
(hf : IsBoundedUnder (· ≤ ·) atTop f) : BddAbove (range f) := by
rw [← Nat.cofinite_eq_atTop] at hf
exact hf.bddAbove_range_of_cofinite
#align filter.is_bounded_under.bdd_above_range Filter.IsBoundedUnder.bddAbove_range
theorem IsBoundedUnder.bddBelow_range [Preorder β] [IsDirected β (· ≥ ·)] {f : ℕ → β}
(hf : IsBoundedUnder (· ≥ ·) atTop f) : BddBelow (range f) :=
IsBoundedUnder.bddAbove_range (β := βᵒᵈ) hf
#align filter.is_bounded_under.bdd_below_range Filter.IsBoundedUnder.bddBelow_range
/-- `IsCobounded (≺) f` states that the filter `f` does not tend to infinity w.r.t. `≺`. This is
also called frequently bounded. Will be usually instantiated with `≤` or `≥`.
There is a subtlety in this definition: we want `f.IsCobounded` to hold for any `f` in the case of
complete lattices. This will be relevant to deduce theorems on complete lattices from their
versions on conditionally complete lattices with additional assumptions. We have to be careful in
the edge case of the trivial filter containing the empty set: the other natural definition
`¬ ∀ a, ∀ᶠ n in f, a ≤ n`
would not work as well in this case.
-/
def IsCobounded (r : α → α → Prop) (f : Filter α) :=
∃ b, ∀ a, (∀ᶠ x in f, r x a) → r b a
#align filter.is_cobounded Filter.IsCobounded
/-- `IsCoboundedUnder (≺) f u` states that the image of the filter `f` under the map `u` does not
tend to infinity w.r.t. `≺`. This is also called frequently bounded. Will be usually instantiated
with `≤` or `≥`. -/
def IsCoboundedUnder (r : α → α → Prop) (f : Filter β) (u : β → α) :=
(map u f).IsCobounded r
#align filter.is_cobounded_under Filter.IsCoboundedUnder
/-- To check that a filter is frequently bounded, it suffices to have a witness
which bounds `f` at some point for every admissible set.
This is only an implication, as the other direction is wrong for the trivial filter. -/
theorem IsCobounded.mk [IsTrans α r] (a : α) (h : ∀ s ∈ f, ∃ x ∈ s, r a x) : f.IsCobounded r :=
⟨a, fun _ s =>
let ⟨_, h₁, h₂⟩ := h _ s
_root_.trans h₂ h₁⟩
#align filter.is_cobounded.mk Filter.IsCobounded.mk
/-- A filter which is eventually bounded is in particular frequently bounded (in the opposite
direction). At least if the filter is not trivial. -/
theorem IsBounded.isCobounded_flip [IsTrans α r] [NeBot f] : f.IsBounded r → f.IsCobounded (flip r)
| ⟨a, ha⟩ =>
⟨a, fun b hb =>
let ⟨_, rxa, rbx⟩ := (ha.and hb).exists
show r b a from _root_.trans rbx rxa⟩
#align filter.is_bounded.is_cobounded_flip Filter.IsBounded.isCobounded_flip
theorem IsBounded.isCobounded_ge [Preorder α] [NeBot f] (h : f.IsBounded (· ≤ ·)) :
f.IsCobounded (· ≥ ·) :=
h.isCobounded_flip
#align filter.is_bounded.is_cobounded_ge Filter.IsBounded.isCobounded_ge
theorem IsBounded.isCobounded_le [Preorder α] [NeBot f] (h : f.IsBounded (· ≥ ·)) :
f.IsCobounded (· ≤ ·) :=
h.isCobounded_flip
#align filter.is_bounded.is_cobounded_le Filter.IsBounded.isCobounded_le
theorem IsBoundedUnder.isCoboundedUnder_flip {l : Filter γ} [IsTrans α r] [NeBot l]
(h : l.IsBoundedUnder r u) : l.IsCoboundedUnder (flip r) u :=
h.isCobounded_flip
theorem IsBoundedUnder.isCoboundedUnder_le {u : γ → α} {l : Filter γ} [Preorder α] [NeBot l]
(h : l.IsBoundedUnder (· ≥ ·) u) : l.IsCoboundedUnder (· ≤ ·) u :=
h.isCoboundedUnder_flip
theorem IsBoundedUnder.isCoboundedUnder_ge {u : γ → α} {l : Filter γ} [Preorder α] [NeBot l]
(h : l.IsBoundedUnder (· ≤ ·) u) : l.IsCoboundedUnder (· ≥ ·) u :=
h.isCoboundedUnder_flip
lemma isCoboundedUnder_le_of_eventually_le [Preorder α] (l : Filter ι) [NeBot l] {f : ι → α} {x : α}
(hf : ∀ᶠ i in l, x ≤ f i) :
IsCoboundedUnder (· ≤ ·) l f :=
IsBoundedUnder.isCoboundedUnder_le ⟨x, hf⟩
lemma isCoboundedUnder_ge_of_eventually_le [Preorder α] (l : Filter ι) [NeBot l] {f : ι → α} {x : α}
(hf : ∀ᶠ i in l, f i ≤ x) :
IsCoboundedUnder (· ≥ ·) l f :=
IsBoundedUnder.isCoboundedUnder_ge ⟨x, hf⟩
lemma isCoboundedUnder_le_of_le [Preorder α] (l : Filter ι) [NeBot l] {f : ι → α} {x : α}
(hf : ∀ i, x ≤ f i) :
IsCoboundedUnder (· ≤ ·) l f :=
isCoboundedUnder_le_of_eventually_le l (eventually_of_forall hf)
lemma isCoboundedUnder_ge_of_le [Preorder α] (l : Filter ι) [NeBot l] {f : ι → α} {x : α}
(hf : ∀ i, f i ≤ x) :
IsCoboundedUnder (· ≥ ·) l f :=
isCoboundedUnder_ge_of_eventually_le l (eventually_of_forall hf)
theorem isCobounded_bot : IsCobounded r ⊥ ↔ ∃ b, ∀ x, r b x := by simp [IsCobounded]
#align filter.is_cobounded_bot Filter.isCobounded_bot
theorem isCobounded_top : IsCobounded r ⊤ ↔ Nonempty α := by
simp (config := { contextual := true }) [IsCobounded, eq_univ_iff_forall,
exists_true_iff_nonempty]
#align filter.is_cobounded_top Filter.isCobounded_top
theorem isCobounded_principal (s : Set α) :
(𝓟 s).IsCobounded r ↔ ∃ b, ∀ a, (∀ x ∈ s, r x a) → r b a := by simp [IsCobounded, subset_def]
#align filter.is_cobounded_principal Filter.isCobounded_principal
theorem IsCobounded.mono (h : f ≤ g) : f.IsCobounded r → g.IsCobounded r
| ⟨b, hb⟩ => ⟨b, fun a ha => hb a (h ha)⟩
#align filter.is_cobounded.mono Filter.IsCobounded.mono
end Relation
section Nonempty
variable [Preorder α] [Nonempty α] {f : Filter β} {u : β → α}
theorem isBounded_le_atBot : (atBot : Filter α).IsBounded (· ≤ ·) :=
‹Nonempty α›.elim fun a => ⟨a, eventually_le_atBot _⟩
#align filter.is_bounded_le_at_bot Filter.isBounded_le_atBot
theorem isBounded_ge_atTop : (atTop : Filter α).IsBounded (· ≥ ·) :=
‹Nonempty α›.elim fun a => ⟨a, eventually_ge_atTop _⟩
#align filter.is_bounded_ge_at_top Filter.isBounded_ge_atTop
theorem Tendsto.isBoundedUnder_le_atBot (h : Tendsto u f atBot) : f.IsBoundedUnder (· ≤ ·) u :=
isBounded_le_atBot.mono h
#align filter.tendsto.is_bounded_under_le_at_bot Filter.Tendsto.isBoundedUnder_le_atBot
theorem Tendsto.isBoundedUnder_ge_atTop (h : Tendsto u f atTop) : f.IsBoundedUnder (· ≥ ·) u :=
isBounded_ge_atTop.mono h
#align filter.tendsto.is_bounded_under_ge_at_top Filter.Tendsto.isBoundedUnder_ge_atTop
theorem bddAbove_range_of_tendsto_atTop_atBot [IsDirected α (· ≤ ·)] {u : ℕ → α}
(hx : Tendsto u atTop atBot) : BddAbove (Set.range u) :=
hx.isBoundedUnder_le_atBot.bddAbove_range
#align filter.bdd_above_range_of_tendsto_at_top_at_bot Filter.bddAbove_range_of_tendsto_atTop_atBot
theorem bddBelow_range_of_tendsto_atTop_atTop [IsDirected α (· ≥ ·)] {u : ℕ → α}
(hx : Tendsto u atTop atTop) : BddBelow (Set.range u) :=
hx.isBoundedUnder_ge_atTop.bddBelow_range
#align filter.bdd_below_range_of_tendsto_at_top_at_top Filter.bddBelow_range_of_tendsto_atTop_atTop
end Nonempty
theorem isCobounded_le_of_bot [Preorder α] [OrderBot α] {f : Filter α} : f.IsCobounded (· ≤ ·) :=
⟨⊥, fun _ _ => bot_le⟩
#align filter.is_cobounded_le_of_bot Filter.isCobounded_le_of_bot
theorem isCobounded_ge_of_top [Preorder α] [OrderTop α] {f : Filter α} : f.IsCobounded (· ≥ ·) :=
⟨⊤, fun _ _ => le_top⟩
#align filter.is_cobounded_ge_of_top Filter.isCobounded_ge_of_top
theorem isBounded_le_of_top [Preorder α] [OrderTop α] {f : Filter α} : f.IsBounded (· ≤ ·) :=
⟨⊤, eventually_of_forall fun _ => le_top⟩
#align filter.is_bounded_le_of_top Filter.isBounded_le_of_top
theorem isBounded_ge_of_bot [Preorder α] [OrderBot α] {f : Filter α} : f.IsBounded (· ≥ ·) :=
⟨⊥, eventually_of_forall fun _ => bot_le⟩
#align filter.is_bounded_ge_of_bot Filter.isBounded_ge_of_bot
@[simp]
theorem _root_.OrderIso.isBoundedUnder_le_comp [Preorder α] [Preorder β] (e : α ≃o β) {l : Filter γ}
{u : γ → α} : (IsBoundedUnder (· ≤ ·) l fun x => e (u x)) ↔ IsBoundedUnder (· ≤ ·) l u :=
(Function.Surjective.exists e.surjective).trans <|
exists_congr fun a => by simp only [eventually_map, e.le_iff_le]
#align order_iso.is_bounded_under_le_comp OrderIso.isBoundedUnder_le_comp
@[simp]
theorem _root_.OrderIso.isBoundedUnder_ge_comp [Preorder α] [Preorder β] (e : α ≃o β) {l : Filter γ}
{u : γ → α} : (IsBoundedUnder (· ≥ ·) l fun x => e (u x)) ↔ IsBoundedUnder (· ≥ ·) l u :=
OrderIso.isBoundedUnder_le_comp e.dual
#align order_iso.is_bounded_under_ge_comp OrderIso.isBoundedUnder_ge_comp
@[to_additive (attr := simp)]
theorem isBoundedUnder_le_inv [OrderedCommGroup α] {l : Filter β} {u : β → α} :
(IsBoundedUnder (· ≤ ·) l fun x => (u x)⁻¹) ↔ IsBoundedUnder (· ≥ ·) l u :=
(OrderIso.inv α).isBoundedUnder_ge_comp
#align filter.is_bounded_under_le_inv Filter.isBoundedUnder_le_inv
#align filter.is_bounded_under_le_neg Filter.isBoundedUnder_le_neg
@[to_additive (attr := simp)]
theorem isBoundedUnder_ge_inv [OrderedCommGroup α] {l : Filter β} {u : β → α} :
(IsBoundedUnder (· ≥ ·) l fun x => (u x)⁻¹) ↔ IsBoundedUnder (· ≤ ·) l u :=
(OrderIso.inv α).isBoundedUnder_le_comp
#align filter.is_bounded_under_ge_inv Filter.isBoundedUnder_ge_inv
#align filter.is_bounded_under_ge_neg Filter.isBoundedUnder_ge_neg
theorem IsBoundedUnder.sup [SemilatticeSup α] {f : Filter β} {u v : β → α} :
f.IsBoundedUnder (· ≤ ·) u →
f.IsBoundedUnder (· ≤ ·) v → f.IsBoundedUnder (· ≤ ·) fun a => u a ⊔ v a
| ⟨bu, (hu : ∀ᶠ x in f, u x ≤ bu)⟩, ⟨bv, (hv : ∀ᶠ x in f, v x ≤ bv)⟩ =>
⟨bu ⊔ bv, show ∀ᶠ x in f, u x ⊔ v x ≤ bu ⊔ bv
by filter_upwards [hu, hv] with _ using sup_le_sup⟩
#align filter.is_bounded_under.sup Filter.IsBoundedUnder.sup
@[simp]
theorem isBoundedUnder_le_sup [SemilatticeSup α] {f : Filter β} {u v : β → α} :
(f.IsBoundedUnder (· ≤ ·) fun a => u a ⊔ v a) ↔
f.IsBoundedUnder (· ≤ ·) u ∧ f.IsBoundedUnder (· ≤ ·) v :=
⟨fun h =>
⟨h.mono_le <| eventually_of_forall fun _ => le_sup_left,
h.mono_le <| eventually_of_forall fun _ => le_sup_right⟩,
fun h => h.1.sup h.2⟩
#align filter.is_bounded_under_le_sup Filter.isBoundedUnder_le_sup
theorem IsBoundedUnder.inf [SemilatticeInf α] {f : Filter β} {u v : β → α} :
f.IsBoundedUnder (· ≥ ·) u →
f.IsBoundedUnder (· ≥ ·) v → f.IsBoundedUnder (· ≥ ·) fun a => u a ⊓ v a :=
IsBoundedUnder.sup (α := αᵒᵈ)
#align filter.is_bounded_under.inf Filter.IsBoundedUnder.inf
@[simp]
theorem isBoundedUnder_ge_inf [SemilatticeInf α] {f : Filter β} {u v : β → α} :
(f.IsBoundedUnder (· ≥ ·) fun a => u a ⊓ v a) ↔
f.IsBoundedUnder (· ≥ ·) u ∧ f.IsBoundedUnder (· ≥ ·) v :=
isBoundedUnder_le_sup (α := αᵒᵈ)
#align filter.is_bounded_under_ge_inf Filter.isBoundedUnder_ge_inf
theorem isBoundedUnder_le_abs [LinearOrderedAddCommGroup α] {f : Filter β} {u : β → α} :
(f.IsBoundedUnder (· ≤ ·) fun a => |u a|) ↔
f.IsBoundedUnder (· ≤ ·) u ∧ f.IsBoundedUnder (· ≥ ·) u :=
isBoundedUnder_le_sup.trans <| and_congr Iff.rfl isBoundedUnder_le_neg
#align filter.is_bounded_under_le_abs Filter.isBoundedUnder_le_abs
/-- Filters are automatically bounded or cobounded in complete lattices. To use the same statements
in complete and conditionally complete lattices but let automation fill automatically the
boundedness proofs in complete lattices, we use the tactic `isBoundedDefault` in the statements,
in the form `(hf : f.IsBounded (≥) := by isBoundedDefault)`. -/
macro "isBoundedDefault" : tactic =>
`(tactic| first
| apply isCobounded_le_of_bot
| apply isCobounded_ge_of_top
| apply isBounded_le_of_top
| apply isBounded_ge_of_bot)
-- Porting note: The above is a lean 4 reconstruction of (note that applyc is not available (yet?)):
-- unsafe def is_bounded_default : tactic Unit :=
-- tactic.applyc `` is_cobounded_le_of_bot <|>
-- tactic.applyc `` is_cobounded_ge_of_top <|>
-- tactic.applyc `` is_bounded_le_of_top <|> tactic.applyc `` is_bounded_ge_of_bot
-- #align filter.is_bounded_default filter.IsBounded_default
section ConditionallyCompleteLattice
variable [ConditionallyCompleteLattice α]
-- Porting note: Renamed from Limsup and Liminf to limsSup and limsInf
/-- The `limsSup` of a filter `f` is the infimum of the `a` such that, eventually for `f`,
holds `x ≤ a`. -/
def limsSup (f : Filter α) : α :=
sInf { a | ∀ᶠ n in f, n ≤ a }
set_option linter.uppercaseLean3 false in
#align filter.Limsup Filter.limsSup
set_option linter.uppercaseLean3 false in
/-- The `limsInf` of a filter `f` is the supremum of the `a` such that, eventually for `f`,
holds `x ≥ a`. -/
def limsInf (f : Filter α) : α :=
sSup { a | ∀ᶠ n in f, a ≤ n }
set_option linter.uppercaseLean3 false in
#align filter.Liminf Filter.limsInf
/-- The `limsup` of a function `u` along a filter `f` is the infimum of the `a` such that,
eventually for `f`, holds `u x ≤ a`. -/
def limsup (u : β → α) (f : Filter β) : α :=
limsSup (map u f)
#align filter.limsup Filter.limsup
/-- The `liminf` of a function `u` along a filter `f` is the supremum of the `a` such that,
eventually for `f`, holds `u x ≥ a`. -/
def liminf (u : β → α) (f : Filter β) : α :=
limsInf (map u f)
#align filter.liminf Filter.liminf
/-- The `blimsup` of a function `u` along a filter `f`, bounded by a predicate `p`, is the infimum
of the `a` such that, eventually for `f`, `u x ≤ a` whenever `p x` holds. -/
def blimsup (u : β → α) (f : Filter β) (p : β → Prop) :=
sInf { a | ∀ᶠ x in f, p x → u x ≤ a }
#align filter.blimsup Filter.blimsup
/-- The `bliminf` of a function `u` along a filter `f`, bounded by a predicate `p`, is the supremum
of the `a` such that, eventually for `f`, `a ≤ u x` whenever `p x` holds. -/
def bliminf (u : β → α) (f : Filter β) (p : β → Prop) :=
sSup { a | ∀ᶠ x in f, p x → a ≤ u x }
#align filter.bliminf Filter.bliminf
section
variable {f : Filter β} {u : β → α} {p : β → Prop}
theorem limsup_eq : limsup u f = sInf { a | ∀ᶠ n in f, u n ≤ a } :=
rfl
#align filter.limsup_eq Filter.limsup_eq
theorem liminf_eq : liminf u f = sSup { a | ∀ᶠ n in f, a ≤ u n } :=
rfl
#align filter.liminf_eq Filter.liminf_eq
theorem blimsup_eq : blimsup u f p = sInf { a | ∀ᶠ x in f, p x → u x ≤ a } :=
rfl
#align filter.blimsup_eq Filter.blimsup_eq
theorem bliminf_eq : bliminf u f p = sSup { a | ∀ᶠ x in f, p x → a ≤ u x } :=
rfl
#align filter.bliminf_eq Filter.bliminf_eq
lemma liminf_comp (u : β → α) (v : γ → β) (f : Filter γ) :
liminf (u ∘ v) f = liminf u (map v f) := rfl
lemma limsup_comp (u : β → α) (v : γ → β) (f : Filter γ) :
limsup (u ∘ v) f = limsup u (map v f) := rfl
end
@[simp]
theorem blimsup_true (f : Filter β) (u : β → α) : (blimsup u f fun _ => True) = limsup u f := by
simp [blimsup_eq, limsup_eq]
#align filter.blimsup_true Filter.blimsup_true
@[simp]
theorem bliminf_true (f : Filter β) (u : β → α) : (bliminf u f fun _ => True) = liminf u f := by
simp [bliminf_eq, liminf_eq]
#align filter.bliminf_true Filter.bliminf_true
lemma blimsup_eq_limsup {f : Filter β} {u : β → α} {p : β → Prop} :
blimsup u f p = limsup u (f ⊓ 𝓟 {x | p x}) := by
simp only [blimsup_eq, limsup_eq, eventually_inf_principal, mem_setOf_eq]
lemma bliminf_eq_liminf {f : Filter β} {u : β → α} {p : β → Prop} :
bliminf u f p = liminf u (f ⊓ 𝓟 {x | p x}) :=
blimsup_eq_limsup (α := αᵒᵈ)
theorem blimsup_eq_limsup_subtype {f : Filter β} {u : β → α} {p : β → Prop} :
blimsup u f p = limsup (u ∘ ((↑) : { x | p x } → β)) (comap (↑) f) := by
rw [blimsup_eq_limsup, limsup, limsup, ← map_map, map_comap_setCoe_val]
#align filter.blimsup_eq_limsup_subtype Filter.blimsup_eq_limsup_subtype
theorem bliminf_eq_liminf_subtype {f : Filter β} {u : β → α} {p : β → Prop} :
bliminf u f p = liminf (u ∘ ((↑) : { x | p x } → β)) (comap (↑) f) :=
blimsup_eq_limsup_subtype (α := αᵒᵈ)
#align filter.bliminf_eq_liminf_subtype Filter.bliminf_eq_liminf_subtype
theorem limsSup_le_of_le {f : Filter α} {a}
(hf : f.IsCobounded (· ≤ ·) := by isBoundedDefault)
(h : ∀ᶠ n in f, n ≤ a) : limsSup f ≤ a :=
csInf_le hf h
set_option linter.uppercaseLean3 false in
#align filter.Limsup_le_of_le Filter.limsSup_le_of_le
theorem le_limsInf_of_le {f : Filter α} {a}
(hf : f.IsCobounded (· ≥ ·) := by isBoundedDefault)
(h : ∀ᶠ n in f, a ≤ n) : a ≤ limsInf f :=
le_csSup hf h
set_option linter.uppercaseLean3 false in
#align filter.le_Liminf_of_le Filter.le_limsInf_of_le
theorem limsup_le_of_le {f : Filter β} {u : β → α} {a}
(hf : f.IsCoboundedUnder (· ≤ ·) u := by isBoundedDefault)
(h : ∀ᶠ n in f, u n ≤ a) : limsup u f ≤ a :=
csInf_le hf h
#align filter.limsup_le_of_le Filter.limsSup_le_of_le
theorem le_liminf_of_le {f : Filter β} {u : β → α} {a}
(hf : f.IsCoboundedUnder (· ≥ ·) u := by isBoundedDefault)
(h : ∀ᶠ n in f, a ≤ u n) : a ≤ liminf u f :=
le_csSup hf h
#align filter.le_liminf_of_le Filter.le_liminf_of_le
theorem le_limsSup_of_le {f : Filter α} {a}
(hf : f.IsBounded (· ≤ ·) := by isBoundedDefault)
(h : ∀ b, (∀ᶠ n in f, n ≤ b) → a ≤ b) : a ≤ limsSup f :=
le_csInf hf h
set_option linter.uppercaseLean3 false in
#align filter.le_Limsup_of_le Filter.le_limsSup_of_le
theorem limsInf_le_of_le {f : Filter α} {a}
(hf : f.IsBounded (· ≥ ·) := by isBoundedDefault)
(h : ∀ b, (∀ᶠ n in f, b ≤ n) → b ≤ a) : limsInf f ≤ a :=
csSup_le hf h
set_option linter.uppercaseLean3 false in
#align filter.Liminf_le_of_le Filter.limsInf_le_of_le
theorem le_limsup_of_le {f : Filter β} {u : β → α} {a}
(hf : f.IsBoundedUnder (· ≤ ·) u := by isBoundedDefault)
(h : ∀ b, (∀ᶠ n in f, u n ≤ b) → a ≤ b) : a ≤ limsup u f :=
le_csInf hf h
#align filter.le_limsup_of_le Filter.le_limsup_of_le
theorem liminf_le_of_le {f : Filter β} {u : β → α} {a}
(hf : f.IsBoundedUnder (· ≥ ·) u := by isBoundedDefault)
(h : ∀ b, (∀ᶠ n in f, b ≤ u n) → b ≤ a) : liminf u f ≤ a :=
csSup_le hf h
#align filter.liminf_le_of_le Filter.liminf_le_of_le
theorem limsInf_le_limsSup {f : Filter α} [NeBot f]
(h₁ : f.IsBounded (· ≤ ·) := by isBoundedDefault)
(h₂ : f.IsBounded (· ≥ ·) := by isBoundedDefault):
limsInf f ≤ limsSup f :=
liminf_le_of_le h₂ fun a₀ ha₀ =>
le_limsup_of_le h₁ fun a₁ ha₁ =>
show a₀ ≤ a₁ from
let ⟨_, hb₀, hb₁⟩ := (ha₀.and ha₁).exists
le_trans hb₀ hb₁
set_option linter.uppercaseLean3 false in
#align filter.Liminf_le_Limsup Filter.limsInf_le_limsSup
theorem liminf_le_limsup {f : Filter β} [NeBot f] {u : β → α}
(h : f.IsBoundedUnder (· ≤ ·) u := by isBoundedDefault)
(h' : f.IsBoundedUnder (· ≥ ·) u := by isBoundedDefault):
liminf u f ≤ limsup u f :=
limsInf_le_limsSup h h'
#align filter.liminf_le_limsup Filter.liminf_le_limsup
theorem limsSup_le_limsSup {f g : Filter α}
(hf : f.IsCobounded (· ≤ ·) := by isBoundedDefault)
(hg : g.IsBounded (· ≤ ·) := by isBoundedDefault)
(h : ∀ a, (∀ᶠ n in g, n ≤ a) → ∀ᶠ n in f, n ≤ a) : limsSup f ≤ limsSup g :=
csInf_le_csInf hf hg h
set_option linter.uppercaseLean3 false in
#align filter.Limsup_le_Limsup Filter.limsSup_le_limsSup
theorem limsInf_le_limsInf {f g : Filter α}
(hf : f.IsBounded (· ≥ ·) := by isBoundedDefault)
(hg : g.IsCobounded (· ≥ ·) := by isBoundedDefault)
(h : ∀ a, (∀ᶠ n in f, a ≤ n) → ∀ᶠ n in g, a ≤ n) : limsInf f ≤ limsInf g :=
csSup_le_csSup hg hf h
set_option linter.uppercaseLean3 false in
#align filter.Liminf_le_Liminf Filter.limsInf_le_limsInf
theorem limsup_le_limsup {α : Type*} [ConditionallyCompleteLattice β] {f : Filter α} {u v : α → β}
(h : u ≤ᶠ[f] v)
(hu : f.IsCoboundedUnder (· ≤ ·) u := by isBoundedDefault)
(hv : f.IsBoundedUnder (· ≤ ·) v := by isBoundedDefault) :
limsup u f ≤ limsup v f :=
limsSup_le_limsSup hu hv fun _ => h.trans
#align filter.limsup_le_limsup Filter.limsup_le_limsup
theorem liminf_le_liminf {α : Type*} [ConditionallyCompleteLattice β] {f : Filter α} {u v : α → β}
(h : ∀ᶠ a in f, u a ≤ v a)
(hu : f.IsBoundedUnder (· ≥ ·) u := by isBoundedDefault)
(hv : f.IsCoboundedUnder (· ≥ ·) v := by isBoundedDefault) :
liminf u f ≤ liminf v f :=
limsup_le_limsup (β := βᵒᵈ) h hv hu
#align filter.liminf_le_liminf Filter.liminf_le_liminf
theorem limsSup_le_limsSup_of_le {f g : Filter α} (h : f ≤ g)
(hf : f.IsCobounded (· ≤ ·) := by isBoundedDefault)
(hg : g.IsBounded (· ≤ ·) := by isBoundedDefault) :
limsSup f ≤ limsSup g :=
limsSup_le_limsSup hf hg fun _ ha => h ha
set_option linter.uppercaseLean3 false in
#align filter.Limsup_le_Limsup_of_le Filter.limsSup_le_limsSup_of_le
theorem limsInf_le_limsInf_of_le {f g : Filter α} (h : g ≤ f)
(hf : f.IsBounded (· ≥ ·) := by isBoundedDefault)
(hg : g.IsCobounded (· ≥ ·) := by isBoundedDefault) :
limsInf f ≤ limsInf g :=
limsInf_le_limsInf hf hg fun _ ha => h ha
set_option linter.uppercaseLean3 false in
#align filter.Liminf_le_Liminf_of_le Filter.limsInf_le_limsInf_of_le
theorem limsup_le_limsup_of_le {α β} [ConditionallyCompleteLattice β] {f g : Filter α} (h : f ≤ g)
{u : α → β}
(hf : f.IsCoboundedUnder (· ≤ ·) u := by isBoundedDefault)
(hg : g.IsBoundedUnder (· ≤ ·) u := by isBoundedDefault) :
limsup u f ≤ limsup u g :=
limsSup_le_limsSup_of_le (map_mono h) hf hg
#align filter.limsup_le_limsup_of_le Filter.limsup_le_limsup_of_le
theorem liminf_le_liminf_of_le {α β} [ConditionallyCompleteLattice β] {f g : Filter α} (h : g ≤ f)
{u : α → β}
(hf : f.IsBoundedUnder (· ≥ ·) u := by isBoundedDefault)
(hg : g.IsCoboundedUnder (· ≥ ·) u := by isBoundedDefault) :
liminf u f ≤ liminf u g :=
limsInf_le_limsInf_of_le (map_mono h) hf hg
#align filter.liminf_le_liminf_of_le Filter.liminf_le_liminf_of_le
theorem limsSup_principal {s : Set α} (h : BddAbove s) (hs : s.Nonempty) :
limsSup (𝓟 s) = sSup s := by
simp only [limsSup, eventually_principal]; exact csInf_upper_bounds_eq_csSup h hs
set_option linter.uppercaseLean3 false in
#align filter.Limsup_principal Filter.limsSup_principal
theorem limsInf_principal {s : Set α} (h : BddBelow s) (hs : s.Nonempty) : limsInf (𝓟 s) = sInf s :=
limsSup_principal (α := αᵒᵈ) h hs
set_option linter.uppercaseLean3 false in
#align filter.Liminf_principal Filter.limsInf_principal
theorem limsup_congr {α : Type*} [ConditionallyCompleteLattice β] {f : Filter α} {u v : α → β}
(h : ∀ᶠ a in f, u a = v a) : limsup u f = limsup v f := by
rw [limsup_eq]
congr with b
exact eventually_congr (h.mono fun x hx => by simp [hx])
#align filter.limsup_congr Filter.limsup_congr
theorem blimsup_congr {f : Filter β} {u v : β → α} {p : β → Prop} (h : ∀ᶠ a in f, p a → u a = v a) :
blimsup u f p = blimsup v f p := by
simpa only [blimsup_eq_limsup] using limsup_congr <| eventually_inf_principal.2 h
#align filter.blimsup_congr Filter.blimsup_congr
theorem bliminf_congr {f : Filter β} {u v : β → α} {p : β → Prop} (h : ∀ᶠ a in f, p a → u a = v a) :
bliminf u f p = bliminf v f p :=
blimsup_congr (α := αᵒᵈ) h
#align filter.bliminf_congr Filter.bliminf_congr
theorem liminf_congr {α : Type*} [ConditionallyCompleteLattice β] {f : Filter α} {u v : α → β}
(h : ∀ᶠ a in f, u a = v a) : liminf u f = liminf v f :=
limsup_congr (β := βᵒᵈ) h
#align filter.liminf_congr Filter.liminf_congr
@[simp]
theorem limsup_const {α : Type*} [ConditionallyCompleteLattice β] {f : Filter α} [NeBot f]
(b : β) : limsup (fun _ => b) f = b := by
simpa only [limsup_eq, eventually_const] using csInf_Ici
#align filter.limsup_const Filter.limsup_const
@[simp]
theorem liminf_const {α : Type*} [ConditionallyCompleteLattice β] {f : Filter α} [NeBot f]
(b : β) : liminf (fun _ => b) f = b :=
limsup_const (β := βᵒᵈ) b
#align filter.liminf_const Filter.liminf_const
theorem HasBasis.liminf_eq_sSup_iUnion_iInter {ι ι' : Type*} {f : ι → α} {v : Filter ι}
{p : ι' → Prop} {s : ι' → Set ι} (hv : v.HasBasis p s) :
liminf f v = sSup (⋃ (j : Subtype p), ⋂ (i : s j), Iic (f i)) := by
simp_rw [liminf_eq, hv.eventually_iff]
congr
ext x
simp only [mem_setOf_eq, iInter_coe_set, mem_iUnion, mem_iInter, mem_Iic, Subtype.exists,
exists_prop]
theorem HasBasis.liminf_eq_sSup_univ_of_empty {f : ι → α} {v : Filter ι}
{p : ι' → Prop} {s : ι' → Set ι} (hv : v.HasBasis p s) (i : ι') (hi : p i) (h'i : s i = ∅) :
liminf f v = sSup univ := by
simp [hv.eq_bot_iff.2 ⟨i, hi, h'i⟩, liminf_eq]
theorem HasBasis.limsup_eq_sInf_iUnion_iInter {ι ι' : Type*} {f : ι → α} {v : Filter ι}
{p : ι' → Prop} {s : ι' → Set ι} (hv : v.HasBasis p s) :
limsup f v = sInf (⋃ (j : Subtype p), ⋂ (i : s j), Ici (f i)) :=
HasBasis.liminf_eq_sSup_iUnion_iInter (α := αᵒᵈ) hv
theorem HasBasis.limsup_eq_sInf_univ_of_empty {f : ι → α} {v : Filter ι}
{p : ι' → Prop} {s : ι' → Set ι} (hv : v.HasBasis p s) (i : ι') (hi : p i) (h'i : s i = ∅) :
limsup f v = sInf univ :=
HasBasis.liminf_eq_sSup_univ_of_empty (α := αᵒᵈ) hv i hi h'i
-- Porting note: simp_nf linter incorrectly says: lhs does not simplify when using simp on itself.
@[simp, nolint simpNF]
theorem liminf_nat_add (f : ℕ → α) (k : ℕ) :
liminf (fun i => f (i + k)) atTop = liminf f atTop := by
change liminf (f ∘ (· + k)) atTop = liminf f atTop
rw [liminf, liminf, ← map_map, map_add_atTop_eq_nat]
#align filter.liminf_nat_add Filter.liminf_nat_add
-- Porting note: simp_nf linter incorrectly says: lhs does not simplify when using simp on itself.
@[simp, nolint simpNF]
theorem limsup_nat_add (f : ℕ → α) (k : ℕ) : limsup (fun i => f (i + k)) atTop = limsup f atTop :=
@liminf_nat_add αᵒᵈ _ f k
#align filter.limsup_nat_add Filter.limsup_nat_add
end ConditionallyCompleteLattice
section CompleteLattice
variable [CompleteLattice α]
@[simp]
theorem limsSup_bot : limsSup (⊥ : Filter α) = ⊥ :=
bot_unique <| sInf_le <| by simp
set_option linter.uppercaseLean3 false in
#align filter.Limsup_bot Filter.limsSup_bot
@[simp] theorem limsup_bot (f : β → α) : limsup f ⊥ = ⊥ := by simp [limsup]
@[simp]
theorem limsInf_bot : limsInf (⊥ : Filter α) = ⊤ :=
top_unique <| le_sSup <| by simp
set_option linter.uppercaseLean3 false in
#align filter.Liminf_bot Filter.limsInf_bot
@[simp] theorem liminf_bot (f : β → α) : liminf f ⊥ = ⊤ := by simp [liminf]
@[simp]
theorem limsSup_top : limsSup (⊤ : Filter α) = ⊤ :=
top_unique <| le_sInf <| by simp [eq_univ_iff_forall]; exact fun b hb => top_unique <| hb _
set_option linter.uppercaseLean3 false in
#align filter.Limsup_top Filter.limsSup_top
@[simp]
theorem limsInf_top : limsInf (⊤ : Filter α) = ⊥ :=
bot_unique <| sSup_le <| by simp [eq_univ_iff_forall]; exact fun b hb => bot_unique <| hb _
set_option linter.uppercaseLean3 false in
#align filter.Liminf_top Filter.limsInf_top
@[simp]
theorem blimsup_false {f : Filter β} {u : β → α} : (blimsup u f fun _ => False) = ⊥ := by
simp [blimsup_eq]
#align filter.blimsup_false Filter.blimsup_false
@[simp]
theorem bliminf_false {f : Filter β} {u : β → α} : (bliminf u f fun _ => False) = ⊤ := by
simp [bliminf_eq]
#align filter.bliminf_false Filter.bliminf_false
/-- Same as limsup_const applied to `⊥` but without the `NeBot f` assumption -/
@[simp]
theorem limsup_const_bot {f : Filter β} : limsup (fun _ : β => (⊥ : α)) f = (⊥ : α) := by
rw [limsup_eq, eq_bot_iff]
exact sInf_le (eventually_of_forall fun _ => le_rfl)
#align filter.limsup_const_bot Filter.limsup_const_bot
/-- Same as limsup_const applied to `⊤` but without the `NeBot f` assumption -/
@[simp]
theorem liminf_const_top {f : Filter β} : liminf (fun _ : β => (⊤ : α)) f = (⊤ : α) :=
limsup_const_bot (α := αᵒᵈ)
#align filter.liminf_const_top Filter.liminf_const_top
theorem HasBasis.limsSup_eq_iInf_sSup {ι} {p : ι → Prop} {s} {f : Filter α} (h : f.HasBasis p s) :
limsSup f = ⨅ (i) (_ : p i), sSup (s i) :=
le_antisymm (le_iInf₂ fun i hi => sInf_le <| h.eventually_iff.2 ⟨i, hi, fun _ => le_sSup⟩)
(le_sInf fun _ ha =>
let ⟨_, hi, ha⟩ := h.eventually_iff.1 ha
iInf₂_le_of_le _ hi <| sSup_le ha)
set_option linter.uppercaseLean3 false in
#align filter.has_basis.Limsup_eq_infi_Sup Filter.HasBasis.limsSup_eq_iInf_sSup
theorem HasBasis.limsInf_eq_iSup_sInf {p : ι → Prop} {s : ι → Set α} {f : Filter α}
(h : f.HasBasis p s) : limsInf f = ⨆ (i) (_ : p i), sInf (s i) :=
HasBasis.limsSup_eq_iInf_sSup (α := αᵒᵈ) h
set_option linter.uppercaseLean3 false in
#align filter.has_basis.Liminf_eq_supr_Inf Filter.HasBasis.limsInf_eq_iSup_sInf
theorem limsSup_eq_iInf_sSup {f : Filter α} : limsSup f = ⨅ s ∈ f, sSup s :=
f.basis_sets.limsSup_eq_iInf_sSup
set_option linter.uppercaseLean3 false in
#align filter.Limsup_eq_infi_Sup Filter.limsSup_eq_iInf_sSup
theorem limsInf_eq_iSup_sInf {f : Filter α} : limsInf f = ⨆ s ∈ f, sInf s :=
limsSup_eq_iInf_sSup (α := αᵒᵈ)
set_option linter.uppercaseLean3 false in
#align filter.Liminf_eq_supr_Inf Filter.limsInf_eq_iSup_sInf
theorem limsup_le_iSup {f : Filter β} {u : β → α} : limsup u f ≤ ⨆ n, u n :=
limsup_le_of_le (by isBoundedDefault) (eventually_of_forall (le_iSup u))
#align filter.limsup_le_supr Filter.limsup_le_iSup
theorem iInf_le_liminf {f : Filter β} {u : β → α} : ⨅ n, u n ≤ liminf u f :=
le_liminf_of_le (by isBoundedDefault) (eventually_of_forall (iInf_le u))
#align filter.infi_le_liminf Filter.iInf_le_liminf
/-- In a complete lattice, the limsup of a function is the infimum over sets `s` in the filter
of the supremum of the function over `s` -/
theorem limsup_eq_iInf_iSup {f : Filter β} {u : β → α} : limsup u f = ⨅ s ∈ f, ⨆ a ∈ s, u a :=
(f.basis_sets.map u).limsSup_eq_iInf_sSup.trans <| by simp only [sSup_image, id]
#align filter.limsup_eq_infi_supr Filter.limsup_eq_iInf_iSup
theorem limsup_eq_iInf_iSup_of_nat {u : ℕ → α} : limsup u atTop = ⨅ n : ℕ, ⨆ i ≥ n, u i :=
(atTop_basis.map u).limsSup_eq_iInf_sSup.trans <| by simp only [sSup_image, iInf_const]; rfl
#align filter.limsup_eq_infi_supr_of_nat Filter.limsup_eq_iInf_iSup_of_nat
theorem limsup_eq_iInf_iSup_of_nat' {u : ℕ → α} : limsup u atTop = ⨅ n : ℕ, ⨆ i : ℕ, u (i + n) := by
simp only [limsup_eq_iInf_iSup_of_nat, iSup_ge_eq_iSup_nat_add]
#align filter.limsup_eq_infi_supr_of_nat' Filter.limsup_eq_iInf_iSup_of_nat'
theorem HasBasis.limsup_eq_iInf_iSup {p : ι → Prop} {s : ι → Set β} {f : Filter β} {u : β → α}
(h : f.HasBasis p s) : limsup u f = ⨅ (i) (_ : p i), ⨆ a ∈ s i, u a :=
(h.map u).limsSup_eq_iInf_sSup.trans <| by simp only [sSup_image, id]
#align filter.has_basis.limsup_eq_infi_supr Filter.HasBasis.limsup_eq_iInf_iSup
theorem blimsup_congr' {f : Filter β} {p q : β → Prop} {u : β → α}
(h : ∀ᶠ x in f, u x ≠ ⊥ → (p x ↔ q x)) : blimsup u f p = blimsup u f q := by
simp only [blimsup_eq]
congr with a
refine eventually_congr (h.mono fun b hb => ?_)
rcases eq_or_ne (u b) ⊥ with hu | hu; · simp [hu]
rw [hb hu]
#align filter.blimsup_congr' Filter.blimsup_congr'
theorem bliminf_congr' {f : Filter β} {p q : β → Prop} {u : β → α}
(h : ∀ᶠ x in f, u x ≠ ⊤ → (p x ↔ q x)) : bliminf u f p = bliminf u f q :=
blimsup_congr' (α := αᵒᵈ) h
#align filter.bliminf_congr' Filter.bliminf_congr'
lemma HasBasis.blimsup_eq_iInf_iSup {p : ι → Prop} {s : ι → Set β} {f : Filter β} {u : β → α}
(hf : f.HasBasis p s) {q : β → Prop} :
blimsup u f q = ⨅ (i) (_ : p i), ⨆ a ∈ s i, ⨆ (_ : q a), u a := by
simp only [blimsup_eq_limsup, (hf.inf_principal _).limsup_eq_iInf_iSup, mem_inter_iff, iSup_and,
mem_setOf_eq]
theorem blimsup_eq_iInf_biSup {f : Filter β} {p : β → Prop} {u : β → α} :
blimsup u f p = ⨅ s ∈ f, ⨆ (b) (_ : p b ∧ b ∈ s), u b := by
simp only [f.basis_sets.blimsup_eq_iInf_iSup, iSup_and', id, and_comm]
#align filter.blimsup_eq_infi_bsupr Filter.blimsup_eq_iInf_biSup
theorem blimsup_eq_iInf_biSup_of_nat {p : ℕ → Prop} {u : ℕ → α} :
blimsup u atTop p = ⨅ i, ⨆ (j) (_ : p j ∧ i ≤ j), u j := by
simp only [atTop_basis.blimsup_eq_iInf_iSup, @and_comm (p _), iSup_and, mem_Ici, iInf_true]
#align filter.blimsup_eq_infi_bsupr_of_nat Filter.blimsup_eq_iInf_biSup_of_nat
/-- In a complete lattice, the liminf of a function is the infimum over sets `s` in the filter
of the supremum of the function over `s` -/
theorem liminf_eq_iSup_iInf {f : Filter β} {u : β → α} : liminf u f = ⨆ s ∈ f, ⨅ a ∈ s, u a :=
limsup_eq_iInf_iSup (α := αᵒᵈ)
#align filter.liminf_eq_supr_infi Filter.liminf_eq_iSup_iInf
theorem liminf_eq_iSup_iInf_of_nat {u : ℕ → α} : liminf u atTop = ⨆ n : ℕ, ⨅ i ≥ n, u i :=
@limsup_eq_iInf_iSup_of_nat αᵒᵈ _ u
#align filter.liminf_eq_supr_infi_of_nat Filter.liminf_eq_iSup_iInf_of_nat
theorem liminf_eq_iSup_iInf_of_nat' {u : ℕ → α} : liminf u atTop = ⨆ n : ℕ, ⨅ i : ℕ, u (i + n) :=
@limsup_eq_iInf_iSup_of_nat' αᵒᵈ _ _
#align filter.liminf_eq_supr_infi_of_nat' Filter.liminf_eq_iSup_iInf_of_nat'
theorem HasBasis.liminf_eq_iSup_iInf {p : ι → Prop} {s : ι → Set β} {f : Filter β} {u : β → α}
(h : f.HasBasis p s) : liminf u f = ⨆ (i) (_ : p i), ⨅ a ∈ s i, u a :=
HasBasis.limsup_eq_iInf_iSup (α := αᵒᵈ) h
#align filter.has_basis.liminf_eq_supr_infi Filter.HasBasis.liminf_eq_iSup_iInf
theorem bliminf_eq_iSup_biInf {f : Filter β} {p : β → Prop} {u : β → α} :
bliminf u f p = ⨆ s ∈ f, ⨅ (b) (_ : p b ∧ b ∈ s), u b :=
@blimsup_eq_iInf_biSup αᵒᵈ β _ f p u
#align filter.bliminf_eq_supr_binfi Filter.bliminf_eq_iSup_biInf
theorem bliminf_eq_iSup_biInf_of_nat {p : ℕ → Prop} {u : ℕ → α} :
bliminf u atTop p = ⨆ i, ⨅ (j) (_ : p j ∧ i ≤ j), u j :=
@blimsup_eq_iInf_biSup_of_nat αᵒᵈ _ p u
#align filter.bliminf_eq_supr_binfi_of_nat Filter.bliminf_eq_iSup_biInf_of_nat
theorem limsup_eq_sInf_sSup {ι R : Type*} (F : Filter ι) [CompleteLattice R] (a : ι → R) :
limsup a F = sInf ((fun I => sSup (a '' I)) '' F.sets) := by
apply le_antisymm
· rw [limsup_eq]
refine sInf_le_sInf fun x hx => ?_
rcases (mem_image _ F.sets x).mp hx with ⟨I, ⟨I_mem_F, hI⟩⟩
filter_upwards [I_mem_F] with i hi
exact hI ▸ le_sSup (mem_image_of_mem _ hi)
· refine le_sInf fun b hb => sInf_le_of_le (mem_image_of_mem _ hb) <| sSup_le ?_
rintro _ ⟨_, h, rfl⟩
exact h
set_option linter.uppercaseLean3 false in
#align filter.limsup_eq_Inf_Sup Filter.limsup_eq_sInf_sSup
theorem liminf_eq_sSup_sInf {ι R : Type*} (F : Filter ι) [CompleteLattice R] (a : ι → R) :
liminf a F = sSup ((fun I => sInf (a '' I)) '' F.sets) :=
@Filter.limsup_eq_sInf_sSup ι (OrderDual R) _ _ a
set_option linter.uppercaseLean3 false in
#align filter.liminf_eq_Sup_Inf Filter.liminf_eq_sSup_sInf
theorem liminf_le_of_frequently_le' {α β} [CompleteLattice β] {f : Filter α} {u : α → β} {x : β}
(h : ∃ᶠ a in f, u a ≤ x) : liminf u f ≤ x := by
rw [liminf_eq]
refine sSup_le fun b hb => ?_
have hbx : ∃ᶠ _ in f, b ≤ x := by
revert h
rw [← not_imp_not, not_frequently, not_frequently]
exact fun h => hb.mp (h.mono fun a hbx hba hax => hbx (hba.trans hax))
exact hbx.exists.choose_spec
#align filter.liminf_le_of_frequently_le' Filter.liminf_le_of_frequently_le'
theorem le_limsup_of_frequently_le' {α β} [CompleteLattice β] {f : Filter α} {u : α → β} {x : β}
(h : ∃ᶠ a in f, x ≤ u a) : x ≤ limsup u f :=
liminf_le_of_frequently_le' (β := βᵒᵈ) h
#align filter.le_limsup_of_frequently_le' Filter.le_limsup_of_frequently_le'
/-- If `f : α → α` is a morphism of complete lattices, then the limsup of its iterates of any
`a : α` is a fixed point. -/
@[simp]
theorem CompleteLatticeHom.apply_limsup_iterate (f : CompleteLatticeHom α α) (a : α) :
f (limsup (fun n => f^[n] a) atTop) = limsup (fun n => f^[n] a) atTop := by
rw [limsup_eq_iInf_iSup_of_nat', map_iInf]
simp_rw [_root_.map_iSup, ← Function.comp_apply (f := f), ← Function.iterate_succ' f,
← Nat.add_succ]
conv_rhs => rw [iInf_split _ (0 < ·)]
simp only [not_lt, Nat.le_zero, iInf_iInf_eq_left, add_zero, iInf_nat_gt_zero_eq, left_eq_inf]
refine (iInf_le (fun i => ⨆ j, f^[j + (i + 1)] a) 0).trans ?_
simp only [zero_add, Function.comp_apply, iSup_le_iff]
exact fun i => le_iSup (fun i => f^[i] a) (i + 1)
#align filter.complete_lattice_hom.apply_limsup_iterate Filter.CompleteLatticeHom.apply_limsup_iterate
/-- If `f : α → α` is a morphism of complete lattices, then the liminf of its iterates of any
`a : α` is a fixed point. -/
theorem CompleteLatticeHom.apply_liminf_iterate (f : CompleteLatticeHom α α) (a : α) :
f (liminf (fun n => f^[n] a) atTop) = liminf (fun n => f^[n] a) atTop :=
apply_limsup_iterate (CompleteLatticeHom.dual f) _
#align filter.complete_lattice_hom.apply_liminf_iterate Filter.CompleteLatticeHom.apply_liminf_iterate
variable {f g : Filter β} {p q : β → Prop} {u v : β → α}
theorem blimsup_mono (h : ∀ x, p x → q x) : blimsup u f p ≤ blimsup u f q :=
sInf_le_sInf fun a ha => ha.mono <| by tauto
#align filter.blimsup_mono Filter.blimsup_mono
theorem bliminf_antitone (h : ∀ x, p x → q x) : bliminf u f q ≤ bliminf u f p :=
sSup_le_sSup fun a ha => ha.mono <| by tauto
#align filter.bliminf_antitone Filter.bliminf_antitone
theorem mono_blimsup' (h : ∀ᶠ x in f, p x → u x ≤ v x) : blimsup u f p ≤ blimsup v f p :=
sInf_le_sInf fun _ ha => (ha.and h).mono fun _ hx hx' => (hx.2 hx').trans (hx.1 hx')
#align filter.mono_blimsup' Filter.mono_blimsup'
theorem mono_blimsup (h : ∀ x, p x → u x ≤ v x) : blimsup u f p ≤ blimsup v f p :=
mono_blimsup' <| eventually_of_forall h
#align filter.mono_blimsup Filter.mono_blimsup
theorem mono_bliminf' (h : ∀ᶠ x in f, p x → u x ≤ v x) : bliminf u f p ≤ bliminf v f p :=
sSup_le_sSup fun _ ha => (ha.and h).mono fun _ hx hx' => (hx.1 hx').trans (hx.2 hx')
#align filter.mono_bliminf' Filter.mono_bliminf'
theorem mono_bliminf (h : ∀ x, p x → u x ≤ v x) : bliminf u f p ≤ bliminf v f p :=
mono_bliminf' <| eventually_of_forall h
#align filter.mono_bliminf Filter.mono_bliminf
theorem bliminf_antitone_filter (h : f ≤ g) : bliminf u g p ≤ bliminf u f p :=
sSup_le_sSup fun _ ha => ha.filter_mono h
#align filter.bliminf_antitone_filter Filter.bliminf_antitone_filter
theorem blimsup_monotone_filter (h : f ≤ g) : blimsup u f p ≤ blimsup u g p :=
sInf_le_sInf fun _ ha => ha.filter_mono h
#align filter.blimsup_monotone_filter Filter.blimsup_monotone_filter
-- @[simp] -- Porting note: simp_nf linter, lhs simplifies, added _aux versions below
theorem blimsup_and_le_inf : (blimsup u f fun x => p x ∧ q x) ≤ blimsup u f p ⊓ blimsup u f q :=
le_inf (blimsup_mono <| by tauto) (blimsup_mono <| by tauto)
#align filter.blimsup_and_le_inf Filter.blimsup_and_le_inf
@[simp]
theorem bliminf_sup_le_inf_aux_left :
(blimsup u f fun x => p x ∧ q x) ≤ blimsup u f p :=
blimsup_and_le_inf.trans inf_le_left
@[simp]
theorem bliminf_sup_le_inf_aux_right :
(blimsup u f fun x => p x ∧ q x) ≤ blimsup u f q :=
blimsup_and_le_inf.trans inf_le_right
-- @[simp] -- Porting note: simp_nf linter, lhs simplifies, added _aux simp version below
theorem bliminf_sup_le_and : bliminf u f p ⊔ bliminf u f q ≤ bliminf u f fun x => p x ∧ q x :=
blimsup_and_le_inf (α := αᵒᵈ)
#align filter.bliminf_sup_le_and Filter.bliminf_sup_le_and
@[simp]
theorem bliminf_sup_le_and_aux_left : bliminf u f p ≤ bliminf u f fun x => p x ∧ q x :=
le_sup_left.trans bliminf_sup_le_and
@[simp]
theorem bliminf_sup_le_and_aux_right : bliminf u f q ≤ bliminf u f fun x => p x ∧ q x :=
le_sup_right.trans bliminf_sup_le_and
/-- See also `Filter.blimsup_or_eq_sup`. -/
-- @[simp] -- Porting note: simp_nf linter, lhs simplifies, added _aux simp versions below
theorem blimsup_sup_le_or : blimsup u f p ⊔ blimsup u f q ≤ blimsup u f fun x => p x ∨ q x :=
sup_le (blimsup_mono <| by tauto) (blimsup_mono <| by tauto)
#align filter.blimsup_sup_le_or Filter.blimsup_sup_le_or
@[simp]
theorem bliminf_sup_le_or_aux_left : blimsup u f p ≤ blimsup u f fun x => p x ∨ q x :=
le_sup_left.trans blimsup_sup_le_or
@[simp]
theorem bliminf_sup_le_or_aux_right : blimsup u f q ≤ blimsup u f fun x => p x ∨ q x :=
le_sup_right.trans blimsup_sup_le_or
/-- See also `Filter.bliminf_or_eq_inf`. -/
--@[simp] -- Porting note: simp_nf linter, lhs simplifies, added _aux simp versions below
theorem bliminf_or_le_inf : (bliminf u f fun x => p x ∨ q x) ≤ bliminf u f p ⊓ bliminf u f q :=
blimsup_sup_le_or (α := αᵒᵈ)
#align filter.bliminf_or_le_inf Filter.bliminf_or_le_inf
@[simp]
theorem bliminf_or_le_inf_aux_left : (bliminf u f fun x => p x ∨ q x) ≤ bliminf u f p :=
bliminf_or_le_inf.trans inf_le_left
@[simp]
theorem bliminf_or_le_inf_aux_right : (bliminf u f fun x => p x ∨ q x) ≤ bliminf u f q :=
bliminf_or_le_inf.trans inf_le_right
/- Porting note: Replaced `e` with `DFunLike.coe e` to override the strange
coercion to `↑(RelIso.toRelEmbedding e).toEmbedding`. -/
theorem OrderIso.apply_blimsup [CompleteLattice γ] (e : α ≃o γ) :
DFunLike.coe e (blimsup u f p) = blimsup ((DFunLike.coe e) ∘ u) f p := by
simp only [blimsup_eq, map_sInf, Function.comp_apply]
congr
ext c
obtain ⟨a, rfl⟩ := e.surjective c
simp
#align filter.order_iso.apply_blimsup Filter.OrderIso.apply_blimsup
theorem OrderIso.apply_bliminf [CompleteLattice γ] (e : α ≃o γ) :
e (bliminf u f p) = bliminf (e ∘ u) f p :=
OrderIso.apply_blimsup (α := αᵒᵈ) (γ := γᵒᵈ) e.dual
#align filter.order_iso.apply_bliminf Filter.OrderIso.apply_bliminf
theorem SupHom.apply_blimsup_le [CompleteLattice γ] (g : sSupHom α γ) :
g (blimsup u f p) ≤ blimsup (g ∘ u) f p := by
simp only [blimsup_eq_iInf_biSup, Function.comp]
refine ((OrderHomClass.mono g).map_iInf₂_le _).trans ?_
simp only [_root_.map_iSup, le_refl]
#align filter.Sup_hom.apply_blimsup_le Filter.SupHom.apply_blimsup_le
theorem InfHom.le_apply_bliminf [CompleteLattice γ] (g : sInfHom α γ) :
bliminf (g ∘ u) f p ≤ g (bliminf u f p) :=
SupHom.apply_blimsup_le (α := αᵒᵈ) (γ := γᵒᵈ) (sInfHom.dual g)
#align filter.Inf_hom.le_apply_bliminf Filter.InfHom.le_apply_bliminf
end CompleteLattice
section CompleteDistribLattice
variable [CompleteDistribLattice α] {f : Filter β} {p q : β → Prop} {u : β → α}
lemma limsup_sup_filter {g} : limsup u (f ⊔ g) = limsup u f ⊔ limsup u g := by
refine le_antisymm ?_
(sup_le (limsup_le_limsup_of_le le_sup_left) (limsup_le_limsup_of_le le_sup_right))
simp_rw [limsup_eq, sInf_sup_eq, sup_sInf_eq, mem_setOf_eq, le_iInf₂_iff]
intro a ha b hb
exact sInf_le ⟨ha.mono fun _ h ↦ h.trans le_sup_left, hb.mono fun _ h ↦ h.trans le_sup_right⟩
lemma liminf_sup_filter {g} : liminf u (f ⊔ g) = liminf u f ⊓ liminf u g :=
limsup_sup_filter (α := αᵒᵈ)
@[simp]
theorem blimsup_or_eq_sup : (blimsup u f fun x => p x ∨ q x) = blimsup u f p ⊔ blimsup u f q := by
simp only [blimsup_eq_limsup, ← limsup_sup_filter, ← inf_sup_left, sup_principal, setOf_or]
#align filter.blimsup_or_eq_sup Filter.blimsup_or_eq_sup
@[simp]
theorem bliminf_or_eq_inf : (bliminf u f fun x => p x ∨ q x) = bliminf u f p ⊓ bliminf u f q :=
blimsup_or_eq_sup (α := αᵒᵈ)
#align filter.bliminf_or_eq_inf Filter.bliminf_or_eq_inf
@[simp]
lemma blimsup_sup_not : blimsup u f p ⊔ blimsup u f (¬p ·) = limsup u f := by
simp_rw [← blimsup_or_eq_sup, or_not, blimsup_true]
@[simp]
lemma bliminf_inf_not : bliminf u f p ⊓ bliminf u f (¬p ·) = liminf u f :=
blimsup_sup_not (α := αᵒᵈ)
@[simp]
lemma blimsup_not_sup : blimsup u f (¬p ·) ⊔ blimsup u f p = limsup u f := by
simpa only [not_not] using blimsup_sup_not (p := (¬p ·))
@[simp]
lemma bliminf_not_inf : bliminf u f (¬p ·) ⊓ bliminf u f p = liminf u f :=
blimsup_not_sup (α := αᵒᵈ)
lemma limsup_piecewise {s : Set β} [DecidablePred (· ∈ s)] {v} :
limsup (s.piecewise u v) f = blimsup u f (· ∈ s) ⊔ blimsup v f (· ∉ s) := by
rw [← blimsup_sup_not (p := (· ∈ s))]
refine congr_arg₂ _ (blimsup_congr ?_) (blimsup_congr ?_) <;>
filter_upwards with _ h using by simp [h]
lemma liminf_piecewise {s : Set β} [DecidablePred (· ∈ s)] {v} :
liminf (s.piecewise u v) f = bliminf u f (· ∈ s) ⊓ bliminf v f (· ∉ s) :=
limsup_piecewise (α := αᵒᵈ)
theorem sup_limsup [NeBot f] (a : α) : a ⊔ limsup u f = limsup (fun x => a ⊔ u x) f := by
simp only [limsup_eq_iInf_iSup, iSup_sup_eq, sup_iInf₂_eq]
congr; ext s; congr; ext hs; congr
exact (biSup_const (nonempty_of_mem hs)).symm
#align filter.sup_limsup Filter.sup_limsup
theorem inf_liminf [NeBot f] (a : α) : a ⊓ liminf u f = liminf (fun x => a ⊓ u x) f :=
sup_limsup (α := αᵒᵈ) a
#align filter.inf_liminf Filter.inf_liminf
theorem sup_liminf (a : α) : a ⊔ liminf u f = liminf (fun x => a ⊔ u x) f := by
simp only [liminf_eq_iSup_iInf]
rw [sup_comm, biSup_sup (⟨univ, univ_mem⟩ : ∃ i : Set β, i ∈ f)]
simp_rw [iInf₂_sup_eq, sup_comm (a := a)]
#align filter.sup_liminf Filter.sup_liminf
theorem inf_limsup (a : α) : a ⊓ limsup u f = limsup (fun x => a ⊓ u x) f :=
sup_liminf (α := αᵒᵈ) a
#align filter.inf_limsup Filter.inf_limsup
end CompleteDistribLattice
section CompleteBooleanAlgebra
variable [CompleteBooleanAlgebra α] (f : Filter β) (u : β → α)
theorem limsup_compl : (limsup u f)ᶜ = liminf (compl ∘ u) f := by
simp only [limsup_eq_iInf_iSup, compl_iInf, compl_iSup, liminf_eq_iSup_iInf, Function.comp_apply]
#align filter.limsup_compl Filter.limsup_compl
theorem liminf_compl : (liminf u f)ᶜ = limsup (compl ∘ u) f := by
simp only [limsup_eq_iInf_iSup, compl_iInf, compl_iSup, liminf_eq_iSup_iInf, Function.comp_apply]
#align filter.liminf_compl Filter.liminf_compl
theorem limsup_sdiff (a : α) : limsup u f \ a = limsup (fun b => u b \ a) f := by
simp only [limsup_eq_iInf_iSup, sdiff_eq]
rw [biInf_inf (⟨univ, univ_mem⟩ : ∃ i : Set β, i ∈ f)]
simp_rw [inf_comm, inf_iSup₂_eq, inf_comm]
#align filter.limsup_sdiff Filter.limsup_sdiff
theorem liminf_sdiff [NeBot f] (a : α) : liminf u f \ a = liminf (fun b => u b \ a) f := by
simp only [sdiff_eq, inf_comm _ aᶜ, inf_liminf]
#align filter.liminf_sdiff Filter.liminf_sdiff
theorem sdiff_limsup [NeBot f] (a : α) : a \ limsup u f = liminf (fun b => a \ u b) f := by
rw [← compl_inj_iff]
simp only [sdiff_eq, liminf_compl, (· ∘ ·), compl_inf, compl_compl, sup_limsup]
#align filter.sdiff_limsup Filter.sdiff_limsup
theorem sdiff_liminf (a : α) : a \ liminf u f = limsup (fun b => a \ u b) f := by
rw [← compl_inj_iff]
simp only [sdiff_eq, limsup_compl, (· ∘ ·), compl_inf, compl_compl, sup_liminf]
#align filter.sdiff_liminf Filter.sdiff_liminf
end CompleteBooleanAlgebra
section SetLattice
variable {p : ι → Prop} {s : ι → Set α} {𝓕 : Filter ι} {a : α}
lemma mem_liminf_iff_eventually_mem : (a ∈ liminf s 𝓕) ↔ (∀ᶠ i in 𝓕, a ∈ s i) := by
simpa only [liminf_eq_iSup_iInf, iSup_eq_iUnion, iInf_eq_iInter, mem_iUnion, mem_iInter]
using ⟨fun ⟨S, hS, hS'⟩ ↦ mem_of_superset hS (by tauto), fun h ↦ ⟨{i | a ∈ s i}, h, by tauto⟩⟩
lemma mem_limsup_iff_frequently_mem : (a ∈ limsup s 𝓕) ↔ (∃ᶠ i in 𝓕, a ∈ s i) := by
simp only [Filter.Frequently, iff_not_comm, ← mem_compl_iff, limsup_compl, comp_apply,
mem_liminf_iff_eventually_mem]
theorem cofinite.blimsup_set_eq :
blimsup s cofinite p = { x | { n | p n ∧ x ∈ s n }.Infinite } := by
simp only [blimsup_eq, le_eq_subset, eventually_cofinite, not_forall, sInf_eq_sInter, exists_prop]
ext x
refine ⟨fun h => ?_, fun hx t h => ?_⟩ <;> contrapose! h
· simp only [mem_sInter, mem_setOf_eq, not_forall, exists_prop]
exact ⟨{x}ᶜ, by simpa using h, by simp⟩
· exact hx.mono fun i hi => ⟨hi.1, fun hit => h (hit hi.2)⟩
#align filter.cofinite.blimsup_set_eq Filter.cofinite.blimsup_set_eq
theorem cofinite.bliminf_set_eq : bliminf s cofinite p = { x | { n | p n ∧ x ∉ s n }.Finite } := by
rw [← compl_inj_iff]
simp only [bliminf_eq_iSup_biInf, compl_iInf, compl_iSup, ← blimsup_eq_iInf_biSup,
cofinite.blimsup_set_eq]
rfl
#align filter.cofinite.bliminf_set_eq Filter.cofinite.bliminf_set_eq
/-- In other words, `limsup cofinite s` is the set of elements lying inside the family `s`
infinitely often. -/
theorem cofinite.limsup_set_eq : limsup s cofinite = { x | { n | x ∈ s n }.Infinite } := by
simp only [← cofinite.blimsup_true s, cofinite.blimsup_set_eq, true_and_iff]
#align filter.cofinite.limsup_set_eq Filter.cofinite.limsup_set_eq
/-- In other words, `liminf cofinite s` is the set of elements lying outside the family `s`
finitely often. -/
theorem cofinite.liminf_set_eq : liminf s cofinite = { x | { n | x ∉ s n }.Finite } := by
simp only [← cofinite.bliminf_true s, cofinite.bliminf_set_eq, true_and_iff]
#align filter.cofinite.liminf_set_eq Filter.cofinite.liminf_set_eq
theorem exists_forall_mem_of_hasBasis_mem_blimsup {l : Filter β} {b : ι → Set β} {q : ι → Prop}
(hl : l.HasBasis q b) {u : β → Set α} {p : β → Prop} {x : α} (hx : x ∈ blimsup u l p) :
∃ f : { i | q i } → β, ∀ i, x ∈ u (f i) ∧ p (f i) ∧ f i ∈ b i := by
rw [blimsup_eq_iInf_biSup] at hx
simp only [iSup_eq_iUnion, iInf_eq_iInter, mem_iInter, mem_iUnion, exists_prop] at hx
choose g hg hg' using hx
refine ⟨fun i : { i | q i } => g (b i) (hl.mem_of_mem i.2), fun i => ⟨?_, ?_⟩⟩
· exact hg' (b i) (hl.mem_of_mem i.2)
· exact hg (b i) (hl.mem_of_mem i.2)
#align filter.exists_forall_mem_of_has_basis_mem_blimsup Filter.exists_forall_mem_of_hasBasis_mem_blimsup
theorem exists_forall_mem_of_hasBasis_mem_blimsup' {l : Filter β} {b : ι → Set β}
(hl : l.HasBasis (fun _ => True) b) {u : β → Set α} {p : β → Prop} {x : α}
(hx : x ∈ blimsup u l p) : ∃ f : ι → β, ∀ i, x ∈ u (f i) ∧ p (f i) ∧ f i ∈ b i := by
obtain ⟨f, hf⟩ := exists_forall_mem_of_hasBasis_mem_blimsup hl hx
exact ⟨fun i => f ⟨i, trivial⟩, fun i => hf ⟨i, trivial⟩⟩
#align filter.exists_forall_mem_of_has_basis_mem_blimsup' Filter.exists_forall_mem_of_hasBasis_mem_blimsup'
end SetLattice
section ConditionallyCompleteLinearOrder
theorem frequently_lt_of_lt_limsSup {f : Filter α} [ConditionallyCompleteLinearOrder α] {a : α}
(hf : f.IsCobounded (· ≤ ·) := by isBoundedDefault)
(h : a < limsSup f) : ∃ᶠ n in f, a < n := by
contrapose! h
simp only [not_frequently, not_lt] at h
exact limsSup_le_of_le hf h
set_option linter.uppercaseLean3 false in
#align filter.frequently_lt_of_lt_Limsup Filter.frequently_lt_of_lt_limsSup
theorem frequently_lt_of_limsInf_lt {f : Filter α} [ConditionallyCompleteLinearOrder α] {a : α}
(hf : f.IsCobounded (· ≥ ·) := by isBoundedDefault)
(h : limsInf f < a) : ∃ᶠ n in f, n < a :=
frequently_lt_of_lt_limsSup (α := OrderDual α) hf h
set_option linter.uppercaseLean3 false in
#align filter.frequently_lt_of_Liminf_lt Filter.frequently_lt_of_limsInf_lt
| Mathlib/Order/LiminfLimsup.lean | 1,277 | 1,284 | theorem eventually_lt_of_lt_liminf {f : Filter α} [ConditionallyCompleteLinearOrder β] {u : α → β}
{b : β} (h : b < liminf u f)
(hu : f.IsBoundedUnder (· ≥ ·) u := by | isBoundedDefault) :
∀ᶠ a in f, b < u a := by
obtain ⟨c, hc, hbc⟩ : ∃ (c : β) (_ : c ∈ { c : β | ∀ᶠ n : α in f, c ≤ u n }), b < c := by
simp_rw [exists_prop]
exact exists_lt_of_lt_csSup hu h
exact hc.mono fun x hx => lt_of_lt_of_le hbc hx
|
/-
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.CategoryTheory.Monoidal.Free.Coherence
import Mathlib.CategoryTheory.Monoidal.Discrete
import Mathlib.CategoryTheory.Monoidal.NaturalTransformation
import Mathlib.CategoryTheory.Monoidal.Opposite
import Mathlib.Tactic.CategoryTheory.Coherence
import Mathlib.CategoryTheory.CommSq
#align_import category_theory.monoidal.braided from "leanprover-community/mathlib"@"2efd2423f8d25fa57cf7a179f5d8652ab4d0df44"
/-!
# Braided and symmetric monoidal categories
The basic definitions of braided monoidal categories, and symmetric monoidal categories,
as well as braided functors.
## Implementation note
We make `BraidedCategory` another typeclass, but then have `SymmetricCategory` extend this.
The rationale is that we are not carrying any additional data, just requiring a property.
## Future work
* Construct the Drinfeld center of a monoidal category as a braided monoidal category.
* Say something about pseudo-natural transformations.
## References
* [Pavel Etingof, Shlomo Gelaki, Dmitri Nikshych, Victor Ostrik, *Tensor categories*][egno15]
-/
open CategoryTheory MonoidalCategory
universe v v₁ v₂ v₃ u u₁ u₂ u₃
namespace CategoryTheory
/-- A braided monoidal category is a monoidal category equipped with a braiding isomorphism
`β_ X Y : X ⊗ Y ≅ Y ⊗ X`
which is natural in both arguments,
and also satisfies the two hexagon identities.
-/
class BraidedCategory (C : Type u) [Category.{v} C] [MonoidalCategory.{v} C] where
/-- The braiding natural isomorphism. -/
braiding : ∀ X Y : C, X ⊗ Y ≅ Y ⊗ X
braiding_naturality_right :
∀ (X : C) {Y Z : C} (f : Y ⟶ Z),
X ◁ f ≫ (braiding X Z).hom = (braiding X Y).hom ≫ f ▷ X := by
aesop_cat
braiding_naturality_left :
∀ {X Y : C} (f : X ⟶ Y) (Z : C),
f ▷ Z ≫ (braiding Y Z).hom = (braiding X Z).hom ≫ Z ◁ f := by
aesop_cat
/-- The first hexagon identity. -/
hexagon_forward :
∀ X Y Z : C,
(α_ X Y Z).hom ≫ (braiding X (Y ⊗ Z)).hom ≫ (α_ Y Z X).hom =
((braiding X Y).hom ▷ Z) ≫ (α_ Y X Z).hom ≫ (Y ◁ (braiding X Z).hom) := by
aesop_cat
/-- The second hexagon identity. -/
hexagon_reverse :
∀ X Y Z : C,
(α_ X Y Z).inv ≫ (braiding (X ⊗ Y) Z).hom ≫ (α_ Z X Y).inv =
(X ◁ (braiding Y Z).hom) ≫ (α_ X Z Y).inv ≫ ((braiding X Z).hom ▷ Y) := by
aesop_cat
#align category_theory.braided_category CategoryTheory.BraidedCategory
attribute [reassoc (attr := simp)]
BraidedCategory.braiding_naturality_left
BraidedCategory.braiding_naturality_right
attribute [reassoc] BraidedCategory.hexagon_forward BraidedCategory.hexagon_reverse
open Category
open MonoidalCategory
open BraidedCategory
@[inherit_doc]
notation "β_" => BraidedCategory.braiding
namespace BraidedCategory
variable {C : Type u} [Category.{v} C] [MonoidalCategory.{v} C] [BraidedCategory.{v} C]
@[simp, reassoc]
theorem braiding_tensor_left (X Y Z : C) :
(β_ (X ⊗ Y) Z).hom =
(α_ X Y Z).hom ≫ X ◁ (β_ Y Z).hom ≫ (α_ X Z Y).inv ≫
(β_ X Z).hom ▷ Y ≫ (α_ Z X Y).hom := by
apply (cancel_epi (α_ X Y Z).inv).1
apply (cancel_mono (α_ Z X Y).inv).1
simp [hexagon_reverse]
@[simp, reassoc]
theorem braiding_tensor_right (X Y Z : C) :
(β_ X (Y ⊗ Z)).hom =
(α_ X Y Z).inv ≫ (β_ X Y).hom ▷ Z ≫ (α_ Y X Z).hom ≫
Y ◁ (β_ X Z).hom ≫ (α_ Y Z X).inv := by
apply (cancel_epi (α_ X Y Z).hom).1
apply (cancel_mono (α_ Y Z X).hom).1
simp [hexagon_forward]
@[simp, reassoc]
theorem braiding_inv_tensor_left (X Y Z : C) :
(β_ (X ⊗ Y) Z).inv =
(α_ Z X Y).inv ≫ (β_ X Z).inv ▷ Y ≫ (α_ X Z Y).hom ≫
X ◁ (β_ Y Z).inv ≫ (α_ X Y Z).inv :=
eq_of_inv_eq_inv (by simp)
@[simp, reassoc]
theorem braiding_inv_tensor_right (X Y Z : C) :
(β_ X (Y ⊗ Z)).inv =
(α_ Y Z X).hom ≫ Y ◁ (β_ X Z).inv ≫ (α_ Y X Z).inv ≫
(β_ X Y).inv ▷ Z ≫ (α_ X Y Z).hom :=
eq_of_inv_eq_inv (by simp)
@[reassoc (attr := simp)]
theorem braiding_naturality {X X' Y Y' : C} (f : X ⟶ Y) (g : X' ⟶ Y') :
(f ⊗ g) ≫ (braiding Y Y').hom = (braiding X X').hom ≫ (g ⊗ f) := by
rw [tensorHom_def' f g, tensorHom_def g f]
simp_rw [Category.assoc, braiding_naturality_left, braiding_naturality_right_assoc]
@[reassoc (attr := simp)]
theorem braiding_inv_naturality_right (X : C) {Y Z : C} (f : Y ⟶ Z) :
X ◁ f ≫ (β_ Z X).inv = (β_ Y X).inv ≫ f ▷ X :=
CommSq.w <| .vert_inv <| .mk <| braiding_naturality_left f X
@[reassoc (attr := simp)]
theorem braiding_inv_naturality_left {X Y : C} (f : X ⟶ Y) (Z : C) :
f ▷ Z ≫ (β_ Z Y).inv = (β_ Z X).inv ≫ Z ◁ f :=
CommSq.w <| .vert_inv <| .mk <| braiding_naturality_right Z f
@[reassoc (attr := simp)]
theorem braiding_inv_naturality {X X' Y Y' : C} (f : X ⟶ Y) (g : X' ⟶ Y') :
(f ⊗ g) ≫ (β_ Y' Y).inv = (β_ X' X).inv ≫ (g ⊗ f) :=
CommSq.w <| .vert_inv <| .mk <| braiding_naturality g f
@[reassoc]
theorem yang_baxter (X Y Z : C) :
(α_ X Y Z).inv ≫ (β_ X Y).hom ▷ Z ≫ (α_ Y X Z).hom ≫
Y ◁ (β_ X Z).hom ≫ (α_ Y Z X).inv ≫ (β_ Y Z).hom ▷ X ≫ (α_ Z Y X).hom =
X ◁ (β_ Y Z).hom ≫ (α_ X Z Y).inv ≫ (β_ X Z).hom ▷ Y ≫
(α_ Z X Y).hom ≫ Z ◁ (β_ X Y).hom := by
rw [← braiding_tensor_right_assoc X Y Z, ← cancel_mono (α_ Z Y X).inv]
repeat rw [assoc]
rw [Iso.hom_inv_id, comp_id, ← braiding_naturality_right, braiding_tensor_right]
theorem yang_baxter' (X Y Z : C) :
(β_ X Y).hom ▷ Z ⊗≫ Y ◁ (β_ X Z).hom ⊗≫ (β_ Y Z).hom ▷ X =
𝟙 _ ⊗≫ (X ◁ (β_ Y Z).hom ⊗≫ (β_ X Z).hom ▷ Y ⊗≫ Z ◁ (β_ X Y).hom) ⊗≫ 𝟙 _ := by
rw [← cancel_epi (α_ X Y Z).inv, ← cancel_mono (α_ Z Y X).hom]
convert yang_baxter X Y Z using 1
all_goals coherence
theorem yang_baxter_iso (X Y Z : C) :
(α_ X Y Z).symm ≪≫ whiskerRightIso (β_ X Y) Z ≪≫ α_ Y X Z ≪≫
whiskerLeftIso Y (β_ X Z) ≪≫ (α_ Y Z X).symm ≪≫
whiskerRightIso (β_ Y Z) X ≪≫ (α_ Z Y X) =
whiskerLeftIso X (β_ Y Z) ≪≫ (α_ X Z Y).symm ≪≫
whiskerRightIso (β_ X Z) Y ≪≫ α_ Z X Y ≪≫
whiskerLeftIso Z (β_ X Y) := Iso.ext (yang_baxter X Y Z)
theorem hexagon_forward_iso (X Y Z : C) :
α_ X Y Z ≪≫ β_ X (Y ⊗ Z) ≪≫ α_ Y Z X =
whiskerRightIso (β_ X Y) Z ≪≫ α_ Y X Z ≪≫ whiskerLeftIso Y (β_ X Z) :=
Iso.ext (hexagon_forward X Y Z)
theorem hexagon_reverse_iso (X Y Z : C) :
(α_ X Y Z).symm ≪≫ β_ (X ⊗ Y) Z ≪≫ (α_ Z X Y).symm =
whiskerLeftIso X (β_ Y Z) ≪≫ (α_ X Z Y).symm ≪≫ whiskerRightIso (β_ X Z) Y :=
Iso.ext (hexagon_reverse X Y Z)
@[reassoc]
theorem hexagon_forward_inv (X Y Z : C) :
(α_ Y Z X).inv ≫ (β_ X (Y ⊗ Z)).inv ≫ (α_ X Y Z).inv =
Y ◁ (β_ X Z).inv ≫ (α_ Y X Z).inv ≫ (β_ X Y).inv ▷ Z := by
simp
@[reassoc]
theorem hexagon_reverse_inv (X Y Z : C) :
(α_ Z X Y).hom ≫ (β_ (X ⊗ Y) Z).inv ≫ (α_ X Y Z).hom =
(β_ X Z).inv ▷ Y ≫ (α_ X Z Y).hom ≫ X ◁ (β_ Y Z).inv := by
simp
end BraidedCategory
/--
Verifying the axioms for a braiding by checking that the candidate braiding is sent to a braiding
by a faithful monoidal functor.
-/
def braidedCategoryOfFaithful {C D : Type*} [Category C] [Category D] [MonoidalCategory C]
[MonoidalCategory D] (F : MonoidalFunctor C D) [F.Faithful] [BraidedCategory D]
(β : ∀ X Y : C, X ⊗ Y ≅ Y ⊗ X)
(w : ∀ X Y, F.μ _ _ ≫ F.map (β X Y).hom = (β_ _ _).hom ≫ F.μ _ _) : BraidedCategory C where
braiding := β
braiding_naturality_left := by
intros
apply F.map_injective
refine (cancel_epi (F.μ ?_ ?_)).1 ?_
rw [Functor.map_comp, ← LaxMonoidalFunctor.μ_natural_left_assoc, w, Functor.map_comp,
reassoc_of% w, braiding_naturality_left_assoc, LaxMonoidalFunctor.μ_natural_right]
braiding_naturality_right := by
intros
apply F.map_injective
refine (cancel_epi (F.μ ?_ ?_)).1 ?_
rw [Functor.map_comp, ← LaxMonoidalFunctor.μ_natural_right_assoc, w, Functor.map_comp,
reassoc_of% w, braiding_naturality_right_assoc, LaxMonoidalFunctor.μ_natural_left]
hexagon_forward := by
intros
apply F.map_injective
refine (cancel_epi (F.μ _ _)).1 ?_
refine (cancel_epi (F.μ _ _ ▷ _)).1 ?_
rw [Functor.map_comp, Functor.map_comp, Functor.map_comp, Functor.map_comp, ←
LaxMonoidalFunctor.μ_natural_left_assoc, ← comp_whiskerRight_assoc, w,
comp_whiskerRight_assoc, LaxMonoidalFunctor.associativity_assoc,
LaxMonoidalFunctor.associativity_assoc, ← LaxMonoidalFunctor.μ_natural_right, ←
MonoidalCategory.whiskerLeft_comp_assoc, w, MonoidalCategory.whiskerLeft_comp_assoc,
reassoc_of% w, braiding_naturality_right_assoc,
LaxMonoidalFunctor.associativity, hexagon_forward_assoc]
hexagon_reverse := by
intros
apply F.toFunctor.map_injective
refine (cancel_epi (F.μ _ _)).1 ?_
refine (cancel_epi (_ ◁ F.μ _ _)).1 ?_
rw [Functor.map_comp, Functor.map_comp, Functor.map_comp, Functor.map_comp, ←
LaxMonoidalFunctor.μ_natural_right_assoc, ← MonoidalCategory.whiskerLeft_comp_assoc, w,
MonoidalCategory.whiskerLeft_comp_assoc, LaxMonoidalFunctor.associativity_inv_assoc,
LaxMonoidalFunctor.associativity_inv_assoc, ← LaxMonoidalFunctor.μ_natural_left,
← comp_whiskerRight_assoc, w, comp_whiskerRight_assoc, reassoc_of% w,
braiding_naturality_left_assoc, LaxMonoidalFunctor.associativity_inv, hexagon_reverse_assoc]
#align category_theory.braided_category_of_faithful CategoryTheory.braidedCategoryOfFaithful
/-- Pull back a braiding along a fully faithful monoidal functor. -/
noncomputable def braidedCategoryOfFullyFaithful {C D : Type*} [Category C] [Category D]
[MonoidalCategory C] [MonoidalCategory D] (F : MonoidalFunctor C D) [F.Full]
[F.Faithful] [BraidedCategory D] : BraidedCategory C :=
braidedCategoryOfFaithful F
(fun X Y => F.toFunctor.preimageIso
((asIso (F.μ _ _)).symm ≪≫ β_ (F.obj X) (F.obj Y) ≪≫ asIso (F.μ _ _)))
(by aesop_cat)
#align category_theory.braided_category_of_fully_faithful CategoryTheory.braidedCategoryOfFullyFaithful
section
/-!
We now establish how the braiding interacts with the unitors.
I couldn't find a detailed proof in print, but this is discussed in:
* Proposition 1 of André Joyal and Ross Street,
"Braided monoidal categories", Macquarie Math Reports 860081 (1986).
* Proposition 2.1 of André Joyal and Ross Street,
"Braided tensor categories" , Adv. Math. 102 (1993), 20–78.
* Exercise 8.1.6 of Etingof, Gelaki, Nikshych, Ostrik,
"Tensor categories", vol 25, Mathematical Surveys and Monographs (2015), AMS.
-/
variable (C : Type u₁) [Category.{v₁} C] [MonoidalCategory C] [BraidedCategory C]
theorem braiding_leftUnitor_aux₁ (X : C) :
(α_ (𝟙_ C) (𝟙_ C) X).hom ≫
(𝟙_ C ◁ (β_ X (𝟙_ C)).inv) ≫ (α_ _ X _).inv ≫ ((λ_ X).hom ▷ _) =
((λ_ _).hom ▷ X) ≫ (β_ X (𝟙_ C)).inv := by
coherence
#align category_theory.braiding_left_unitor_aux₁ CategoryTheory.braiding_leftUnitor_aux₁
theorem braiding_leftUnitor_aux₂ (X : C) :
((β_ X (𝟙_ C)).hom ▷ 𝟙_ C) ≫ ((λ_ X).hom ▷ 𝟙_ C) = (ρ_ X).hom ▷ 𝟙_ C :=
calc
((β_ X (𝟙_ C)).hom ▷ 𝟙_ C) ≫ ((λ_ X).hom ▷ 𝟙_ C) =
((β_ X (𝟙_ C)).hom ▷ 𝟙_ C) ≫ (α_ _ _ _).hom ≫ (α_ _ _ _).inv ≫ ((λ_ X).hom ▷ 𝟙_ C) := by
coherence
_ = ((β_ X (𝟙_ C)).hom ▷ 𝟙_ C) ≫ (α_ _ _ _).hom ≫ (_ ◁ (β_ X _).hom) ≫
(_ ◁ (β_ X _).inv) ≫ (α_ _ _ _).inv ≫ ((λ_ X).hom ▷ 𝟙_ C) := by
simp
_ = (α_ _ _ _).hom ≫ (β_ _ _).hom ≫ (α_ _ _ _).hom ≫ (_ ◁ (β_ X _).inv) ≫ (α_ _ _ _).inv ≫
((λ_ X).hom ▷ 𝟙_ C) := by
(slice_lhs 1 3 => rw [← hexagon_forward]); simp only [assoc]
_ = (α_ _ _ _).hom ≫ (β_ _ _).hom ≫ ((λ_ _).hom ▷ X) ≫ (β_ X _).inv := by
rw [braiding_leftUnitor_aux₁]
_ = (α_ _ _ _).hom ≫ (_ ◁ (λ_ _).hom) ≫ (β_ _ _).hom ≫ (β_ X _).inv := by
(slice_lhs 2 3 => rw [← braiding_naturality_right]); simp only [assoc]
_ = (α_ _ _ _).hom ≫ (_ ◁ (λ_ _).hom) := by rw [Iso.hom_inv_id, comp_id]
_ = (ρ_ X).hom ▷ 𝟙_ C := by rw [triangle]
#align category_theory.braiding_left_unitor_aux₂ CategoryTheory.braiding_leftUnitor_aux₂
@[reassoc]
theorem braiding_leftUnitor (X : C) : (β_ X (𝟙_ C)).hom ≫ (λ_ X).hom = (ρ_ X).hom := by
rw [← whiskerRight_iff, comp_whiskerRight, braiding_leftUnitor_aux₂]
#align category_theory.braiding_left_unitor CategoryTheory.braiding_leftUnitor
theorem braiding_rightUnitor_aux₁ (X : C) :
(α_ X (𝟙_ C) (𝟙_ C)).inv ≫
((β_ (𝟙_ C) X).inv ▷ 𝟙_ C) ≫ (α_ _ X _).hom ≫ (_ ◁ (ρ_ X).hom) =
(X ◁ (ρ_ _).hom) ≫ (β_ (𝟙_ C) X).inv := by
coherence
#align category_theory.braiding_right_unitor_aux₁ CategoryTheory.braiding_rightUnitor_aux₁
theorem braiding_rightUnitor_aux₂ (X : C) :
(𝟙_ C ◁ (β_ (𝟙_ C) X).hom) ≫ (𝟙_ C ◁ (ρ_ X).hom) = 𝟙_ C ◁ (λ_ X).hom :=
calc
(𝟙_ C ◁ (β_ (𝟙_ C) X).hom) ≫ (𝟙_ C ◁ (ρ_ X).hom) =
(𝟙_ C ◁ (β_ (𝟙_ C) X).hom) ≫ (α_ _ _ _).inv ≫ (α_ _ _ _).hom ≫ (𝟙_ C ◁ (ρ_ X).hom) := by
coherence
_ = (𝟙_ C ◁ (β_ (𝟙_ C) X).hom) ≫ (α_ _ _ _).inv ≫ ((β_ _ X).hom ▷ _) ≫
((β_ _ X).inv ▷ _) ≫ (α_ _ _ _).hom ≫ (𝟙_ C ◁ (ρ_ X).hom) := by
simp
_ = (α_ _ _ _).inv ≫ (β_ _ _).hom ≫ (α_ _ _ _).inv ≫ ((β_ _ X).inv ▷ _) ≫ (α_ _ _ _).hom ≫
(𝟙_ C ◁ (ρ_ X).hom) := by
(slice_lhs 1 3 => rw [← hexagon_reverse]); simp only [assoc]
_ = (α_ _ _ _).inv ≫ (β_ _ _).hom ≫ (X ◁ (ρ_ _).hom) ≫ (β_ _ X).inv := by
rw [braiding_rightUnitor_aux₁]
_ = (α_ _ _ _).inv ≫ ((ρ_ _).hom ▷ _) ≫ (β_ _ X).hom ≫ (β_ _ _).inv := by
(slice_lhs 2 3 => rw [← braiding_naturality_left]); simp only [assoc]
_ = (α_ _ _ _).inv ≫ ((ρ_ _).hom ▷ _) := by rw [Iso.hom_inv_id, comp_id]
_ = 𝟙_ C ◁ (λ_ X).hom := by rw [triangle_assoc_comp_right]
#align category_theory.braiding_right_unitor_aux₂ CategoryTheory.braiding_rightUnitor_aux₂
@[reassoc]
theorem braiding_rightUnitor (X : C) : (β_ (𝟙_ C) X).hom ≫ (ρ_ X).hom = (λ_ X).hom := by
rw [← whiskerLeft_iff, MonoidalCategory.whiskerLeft_comp, braiding_rightUnitor_aux₂]
#align category_theory.braiding_right_unitor CategoryTheory.braiding_rightUnitor
@[reassoc, simp]
theorem braiding_tensorUnit_left (X : C) : (β_ (𝟙_ C) X).hom = (λ_ X).hom ≫ (ρ_ X).inv := by
simp [← braiding_rightUnitor]
@[reassoc, simp]
theorem braiding_inv_tensorUnit_left (X : C) : (β_ (𝟙_ C) X).inv = (ρ_ X).hom ≫ (λ_ X).inv := by
rw [Iso.inv_ext]
rw [braiding_tensorUnit_left]
coherence
@[reassoc]
| Mathlib/CategoryTheory/Monoidal/Braided/Basic.lean | 342 | 343 | theorem leftUnitor_inv_braiding (X : C) : (λ_ X).inv ≫ (β_ (𝟙_ C) X).hom = (ρ_ X).inv := by |
simp
|
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