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/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.LinearAlgebra.AffineSpace.Basic
import Mathlib.LinearAlgebra.BilinearMap
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Prod
#align_import linear_algebra.affine_space.affine_map from "leanprover-community/mathlib"@"bd1fc183335ea95a9519a1630bcf901fe9326d83"
/-!
# Affine maps
This file defines affine maps.
## Main definitions
* `AffineMap` is the type of affine maps between two affine spaces with the same ring `k`. Various
basic examples of affine maps are defined, including `const`, `id`, `lineMap` and `homothety`.
## Notations
* `P1 →ᵃ[k] P2` is a notation for `AffineMap k P1 P2`;
* `AffineSpace V P`: a localized notation for `AddTorsor V P` defined in
`LinearAlgebra.AffineSpace.Basic`.
## Implementation notes
`outParam` is used in the definition of `[AddTorsor V P]` to make `V` an implicit argument
(deduced from `P`) in most cases. As for modules, `k` is an explicit argument rather than implied by
`P` or `V`.
This file only provides purely algebraic definitions and results. Those depending on analysis or
topology are defined elsewhere; see `Analysis.NormedSpace.AddTorsor` and
`Topology.Algebra.Affine`.
## References
* https://en.wikipedia.org/wiki/Affine_space
* https://en.wikipedia.org/wiki/Principal_homogeneous_space
-/
open Affine
/-- An `AffineMap k P1 P2` (notation: `P1 →ᵃ[k] P2`) is a map from `P1` to `P2` that
induces a corresponding linear map from `V1` to `V2`. -/
structure AffineMap (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*) [Ring k]
[AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] where
toFun : P1 → P2
linear : V1 →ₗ[k] V2
map_vadd' : ∀ (p : P1) (v : V1), toFun (v +ᵥ p) = linear v +ᵥ toFun p
#align affine_map AffineMap
/-- An `AffineMap k P1 P2` (notation: `P1 →ᵃ[k] P2`) is a map from `P1` to `P2` that
induces a corresponding linear map from `V1` to `V2`. -/
notation:25 P1 " →ᵃ[" k:25 "] " P2:0 => AffineMap k P1 P2
instance AffineMap.instFunLike (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*)
[Ring k] [AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] : FunLike (P1 →ᵃ[k] P2) P1 P2 where
coe := AffineMap.toFun
coe_injective' := fun ⟨f, f_linear, f_add⟩ ⟨g, g_linear, g_add⟩ => fun (h : f = g) => by
cases' (AddTorsor.nonempty : Nonempty P1) with p
congr with v
apply vadd_right_cancel (f p)
erw [← f_add, h, ← g_add]
#align affine_map.fun_like AffineMap.instFunLike
instance AffineMap.hasCoeToFun (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*)
[Ring k] [AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] : CoeFun (P1 →ᵃ[k] P2) fun _ => P1 → P2 :=
DFunLike.hasCoeToFun
#align affine_map.has_coe_to_fun AffineMap.hasCoeToFun
namespace LinearMap
variable {k : Type*} {V₁ : Type*} {V₂ : Type*} [Ring k] [AddCommGroup V₁] [Module k V₁]
[AddCommGroup V₂] [Module k V₂] (f : V₁ →ₗ[k] V₂)
/-- Reinterpret a linear map as an affine map. -/
def toAffineMap : V₁ →ᵃ[k] V₂ where
toFun := f
linear := f
map_vadd' p v := f.map_add v p
#align linear_map.to_affine_map LinearMap.toAffineMap
@[simp]
theorem coe_toAffineMap : ⇑f.toAffineMap = f :=
rfl
#align linear_map.coe_to_affine_map LinearMap.coe_toAffineMap
@[simp]
theorem toAffineMap_linear : f.toAffineMap.linear = f :=
rfl
#align linear_map.to_affine_map_linear LinearMap.toAffineMap_linear
end LinearMap
namespace AffineMap
variable {k : Type*} {V1 : Type*} {P1 : Type*} {V2 : Type*} {P2 : Type*} {V3 : Type*}
{P3 : Type*} {V4 : Type*} {P4 : Type*} [Ring k] [AddCommGroup V1] [Module k V1]
[AffineSpace V1 P1] [AddCommGroup V2] [Module k V2] [AffineSpace V2 P2] [AddCommGroup V3]
[Module k V3] [AffineSpace V3 P3] [AddCommGroup V4] [Module k V4] [AffineSpace V4 P4]
/-- Constructing an affine map and coercing back to a function
produces the same map. -/
@[simp]
theorem coe_mk (f : P1 → P2) (linear add) : ((mk f linear add : P1 →ᵃ[k] P2) : P1 → P2) = f :=
rfl
#align affine_map.coe_mk AffineMap.coe_mk
/-- `toFun` is the same as the result of coercing to a function. -/
@[simp]
theorem toFun_eq_coe (f : P1 →ᵃ[k] P2) : f.toFun = ⇑f :=
rfl
#align affine_map.to_fun_eq_coe AffineMap.toFun_eq_coe
/-- An affine map on the result of adding a vector to a point produces
the same result as the linear map applied to that vector, added to the
affine map applied to that point. -/
@[simp]
theorem map_vadd (f : P1 →ᵃ[k] P2) (p : P1) (v : V1) : f (v +ᵥ p) = f.linear v +ᵥ f p :=
f.map_vadd' p v
#align affine_map.map_vadd AffineMap.map_vadd
/-- The linear map on the result of subtracting two points is the
result of subtracting the result of the affine map on those two
points. -/
@[simp]
theorem linearMap_vsub (f : P1 →ᵃ[k] P2) (p1 p2 : P1) : f.linear (p1 -ᵥ p2) = f p1 -ᵥ f p2 := by
conv_rhs => rw [← vsub_vadd p1 p2, map_vadd, vadd_vsub]
#align affine_map.linear_map_vsub AffineMap.linearMap_vsub
/-- Two affine maps are equal if they coerce to the same function. -/
@[ext]
theorem ext {f g : P1 →ᵃ[k] P2} (h : ∀ p, f p = g p) : f = g :=
DFunLike.ext _ _ h
#align affine_map.ext AffineMap.ext
theorem ext_iff {f g : P1 →ᵃ[k] P2} : f = g ↔ ∀ p, f p = g p :=
⟨fun h _ => h ▸ rfl, ext⟩
#align affine_map.ext_iff AffineMap.ext_iff
theorem coeFn_injective : @Function.Injective (P1 →ᵃ[k] P2) (P1 → P2) (⇑) :=
DFunLike.coe_injective
#align affine_map.coe_fn_injective AffineMap.coeFn_injective
protected theorem congr_arg (f : P1 →ᵃ[k] P2) {x y : P1} (h : x = y) : f x = f y :=
congr_arg _ h
#align affine_map.congr_arg AffineMap.congr_arg
protected theorem congr_fun {f g : P1 →ᵃ[k] P2} (h : f = g) (x : P1) : f x = g x :=
h ▸ rfl
#align affine_map.congr_fun AffineMap.congr_fun
/-- Two affine maps are equal if they have equal linear maps and are equal at some point. -/
theorem ext_linear {f g : P1 →ᵃ[k] P2} (h₁ : f.linear = g.linear) {p : P1} (h₂ : f p = g p) :
f = g := by
ext q
have hgl : g.linear (q -ᵥ p) = toFun g ((q -ᵥ p) +ᵥ q) -ᵥ toFun g q := by simp
have := f.map_vadd' q (q -ᵥ p)
rw [h₁, hgl, toFun_eq_coe, map_vadd, linearMap_vsub, h₂] at this
simp at this
exact this
/-- Two affine maps are equal if they have equal linear maps and are equal at some point. -/
theorem ext_linear_iff {f g : P1 →ᵃ[k] P2} : f = g ↔ (f.linear = g.linear) ∧ (∃ p, f p = g p) :=
⟨fun h ↦ ⟨congrArg _ h, by inhabit P1; exact default, by rw [h]⟩,
fun h ↦ Exists.casesOn h.2 fun _ hp ↦ ext_linear h.1 hp⟩
variable (k P1)
/-- The constant function as an `AffineMap`. -/
def const (p : P2) : P1 →ᵃ[k] P2 where
toFun := Function.const P1 p
linear := 0
map_vadd' _ _ :=
letI : AddAction V2 P2 := inferInstance
by simp
#align affine_map.const AffineMap.const
@[simp]
theorem coe_const (p : P2) : ⇑(const k P1 p) = Function.const P1 p :=
rfl
#align affine_map.coe_const AffineMap.coe_const
-- Porting note (#10756): new theorem
@[simp]
theorem const_apply (p : P2) (q : P1) : (const k P1 p) q = p := rfl
@[simp]
theorem const_linear (p : P2) : (const k P1 p).linear = 0 :=
rfl
#align affine_map.const_linear AffineMap.const_linear
variable {k P1}
theorem linear_eq_zero_iff_exists_const (f : P1 →ᵃ[k] P2) :
f.linear = 0 ↔ ∃ q, f = const k P1 q := by
refine ⟨fun h => ?_, fun h => ?_⟩
· use f (Classical.arbitrary P1)
ext
rw [coe_const, Function.const_apply, ← @vsub_eq_zero_iff_eq V2, ← f.linearMap_vsub, h,
LinearMap.zero_apply]
· rcases h with ⟨q, rfl⟩
exact const_linear k P1 q
#align affine_map.linear_eq_zero_iff_exists_const AffineMap.linear_eq_zero_iff_exists_const
instance nonempty : Nonempty (P1 →ᵃ[k] P2) :=
(AddTorsor.nonempty : Nonempty P2).map <| const k P1
#align affine_map.nonempty AffineMap.nonempty
/-- Construct an affine map by verifying the relation between the map and its linear part at one
base point. Namely, this function takes a map `f : P₁ → P₂`, a linear map `f' : V₁ →ₗ[k] V₂`, and
a point `p` such that for any other point `p'` we have `f p' = f' (p' -ᵥ p) +ᵥ f p`. -/
def mk' (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p : P1) (h : ∀ p' : P1, f p' = f' (p' -ᵥ p) +ᵥ f p) :
P1 →ᵃ[k] P2 where
toFun := f
linear := f'
map_vadd' p' v := by rw [h, h p', vadd_vsub_assoc, f'.map_add, vadd_vadd]
#align affine_map.mk' AffineMap.mk'
@[simp]
theorem coe_mk' (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p h) : ⇑(mk' f f' p h) = f :=
rfl
#align affine_map.coe_mk' AffineMap.coe_mk'
@[simp]
theorem mk'_linear (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p h) : (mk' f f' p h).linear = f' :=
rfl
#align affine_map.mk'_linear AffineMap.mk'_linear
section SMul
variable {R : Type*} [Monoid R] [DistribMulAction R V2] [SMulCommClass k R V2]
/-- The space of affine maps to a module inherits an `R`-action from the action on its codomain. -/
instance mulAction : MulAction R (P1 →ᵃ[k] V2) where
-- Porting note: `map_vadd` is `simp`, but we still have to pass it explicitly
smul c f := ⟨c • ⇑f, c • f.linear, fun p v => by simp [smul_add, map_vadd f]⟩
one_smul f := ext fun p => one_smul _ _
mul_smul c₁ c₂ f := ext fun p => mul_smul _ _ _
@[simp, norm_cast]
theorem coe_smul (c : R) (f : P1 →ᵃ[k] V2) : ⇑(c • f) = c • ⇑f :=
rfl
#align affine_map.coe_smul AffineMap.coe_smul
@[simp]
theorem smul_linear (t : R) (f : P1 →ᵃ[k] V2) : (t • f).linear = t • f.linear :=
rfl
#align affine_map.smul_linear AffineMap.smul_linear
instance isCentralScalar [DistribMulAction Rᵐᵒᵖ V2] [IsCentralScalar R V2] :
IsCentralScalar R (P1 →ᵃ[k] V2) where
op_smul_eq_smul _r _x := ext fun _ => op_smul_eq_smul _ _
end SMul
instance : Zero (P1 →ᵃ[k] V2) where zero := ⟨0, 0, fun _ _ => (zero_vadd _ _).symm⟩
instance : Add (P1 →ᵃ[k] V2) where
add f g := ⟨f + g, f.linear + g.linear, fun p v => by simp [add_add_add_comm]⟩
instance : Sub (P1 →ᵃ[k] V2) where
sub f g := ⟨f - g, f.linear - g.linear, fun p v => by simp [sub_add_sub_comm]⟩
instance : Neg (P1 →ᵃ[k] V2) where
neg f := ⟨-f, -f.linear, fun p v => by simp [add_comm, map_vadd f]⟩
@[simp, norm_cast]
theorem coe_zero : ⇑(0 : P1 →ᵃ[k] V2) = 0 :=
rfl
#align affine_map.coe_zero AffineMap.coe_zero
@[simp, norm_cast]
theorem coe_add (f g : P1 →ᵃ[k] V2) : ⇑(f + g) = f + g :=
rfl
#align affine_map.coe_add AffineMap.coe_add
@[simp, norm_cast]
theorem coe_neg (f : P1 →ᵃ[k] V2) : ⇑(-f) = -f :=
rfl
#align affine_map.coe_neg AffineMap.coe_neg
@[simp, norm_cast]
theorem coe_sub (f g : P1 →ᵃ[k] V2) : ⇑(f - g) = f - g :=
rfl
#align affine_map.coe_sub AffineMap.coe_sub
@[simp]
theorem zero_linear : (0 : P1 →ᵃ[k] V2).linear = 0 :=
rfl
#align affine_map.zero_linear AffineMap.zero_linear
@[simp]
theorem add_linear (f g : P1 →ᵃ[k] V2) : (f + g).linear = f.linear + g.linear :=
rfl
#align affine_map.add_linear AffineMap.add_linear
@[simp]
theorem sub_linear (f g : P1 →ᵃ[k] V2) : (f - g).linear = f.linear - g.linear :=
rfl
#align affine_map.sub_linear AffineMap.sub_linear
@[simp]
theorem neg_linear (f : P1 →ᵃ[k] V2) : (-f).linear = -f.linear :=
rfl
#align affine_map.neg_linear AffineMap.neg_linear
/-- The set of affine maps to a vector space is an additive commutative group. -/
instance : AddCommGroup (P1 →ᵃ[k] V2) :=
coeFn_injective.addCommGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_smul _ _)
fun _ _ => coe_smul _ _
/-- The space of affine maps from `P1` to `P2` is an affine space over the space of affine maps
from `P1` to the vector space `V2` corresponding to `P2`. -/
instance : AffineSpace (P1 →ᵃ[k] V2) (P1 →ᵃ[k] P2) where
vadd f g :=
⟨fun p => f p +ᵥ g p, f.linear + g.linear,
fun p v => by simp [vadd_vadd, add_right_comm]⟩
zero_vadd f := ext fun p => zero_vadd _ (f p)
add_vadd f₁ f₂ f₃ := ext fun p => add_vadd (f₁ p) (f₂ p) (f₃ p)
vsub f g :=
⟨fun p => f p -ᵥ g p, f.linear - g.linear, fun p v => by
simp [vsub_vadd_eq_vsub_sub, vadd_vsub_assoc, add_sub, sub_add_eq_add_sub]⟩
vsub_vadd' f g := ext fun p => vsub_vadd (f p) (g p)
vadd_vsub' f g := ext fun p => vadd_vsub (f p) (g p)
@[simp]
theorem vadd_apply (f : P1 →ᵃ[k] V2) (g : P1 →ᵃ[k] P2) (p : P1) : (f +ᵥ g) p = f p +ᵥ g p :=
rfl
#align affine_map.vadd_apply AffineMap.vadd_apply
@[simp]
theorem vsub_apply (f g : P1 →ᵃ[k] P2) (p : P1) : (f -ᵥ g : P1 →ᵃ[k] V2) p = f p -ᵥ g p :=
rfl
#align affine_map.vsub_apply AffineMap.vsub_apply
/-- `Prod.fst` as an `AffineMap`. -/
def fst : P1 × P2 →ᵃ[k] P1 where
toFun := Prod.fst
linear := LinearMap.fst k V1 V2
map_vadd' _ _ := rfl
#align affine_map.fst AffineMap.fst
@[simp]
theorem coe_fst : ⇑(fst : P1 × P2 →ᵃ[k] P1) = Prod.fst :=
rfl
#align affine_map.coe_fst AffineMap.coe_fst
@[simp]
theorem fst_linear : (fst : P1 × P2 →ᵃ[k] P1).linear = LinearMap.fst k V1 V2 :=
rfl
#align affine_map.fst_linear AffineMap.fst_linear
/-- `Prod.snd` as an `AffineMap`. -/
def snd : P1 × P2 →ᵃ[k] P2 where
toFun := Prod.snd
linear := LinearMap.snd k V1 V2
map_vadd' _ _ := rfl
#align affine_map.snd AffineMap.snd
@[simp]
theorem coe_snd : ⇑(snd : P1 × P2 →ᵃ[k] P2) = Prod.snd :=
rfl
#align affine_map.coe_snd AffineMap.coe_snd
@[simp]
theorem snd_linear : (snd : P1 × P2 →ᵃ[k] P2).linear = LinearMap.snd k V1 V2 :=
rfl
#align affine_map.snd_linear AffineMap.snd_linear
variable (k P1)
/-- Identity map as an affine map. -/
nonrec def id : P1 →ᵃ[k] P1 where
toFun := id
linear := LinearMap.id
map_vadd' _ _ := rfl
#align affine_map.id AffineMap.id
/-- The identity affine map acts as the identity. -/
@[simp]
theorem coe_id : ⇑(id k P1) = _root_.id :=
rfl
#align affine_map.coe_id AffineMap.coe_id
@[simp]
theorem id_linear : (id k P1).linear = LinearMap.id :=
rfl
#align affine_map.id_linear AffineMap.id_linear
variable {P1}
/-- The identity affine map acts as the identity. -/
theorem id_apply (p : P1) : id k P1 p = p :=
rfl
#align affine_map.id_apply AffineMap.id_apply
variable {k}
instance : Inhabited (P1 →ᵃ[k] P1) :=
⟨id k P1⟩
/-- Composition of affine maps. -/
def comp (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) : P1 →ᵃ[k] P3 where
toFun := f ∘ g
linear := f.linear.comp g.linear
map_vadd' := by
intro p v
rw [Function.comp_apply, g.map_vadd, f.map_vadd]
rfl
#align affine_map.comp AffineMap.comp
/-- Composition of affine maps acts as applying the two functions. -/
@[simp]
theorem coe_comp (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) : ⇑(f.comp g) = f ∘ g :=
rfl
#align affine_map.coe_comp AffineMap.coe_comp
/-- Composition of affine maps acts as applying the two functions. -/
theorem comp_apply (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) (p : P1) : f.comp g p = f (g p) :=
rfl
#align affine_map.comp_apply AffineMap.comp_apply
@[simp]
theorem comp_id (f : P1 →ᵃ[k] P2) : f.comp (id k P1) = f :=
ext fun _ => rfl
#align affine_map.comp_id AffineMap.comp_id
@[simp]
theorem id_comp (f : P1 →ᵃ[k] P2) : (id k P2).comp f = f :=
ext fun _ => rfl
#align affine_map.id_comp AffineMap.id_comp
theorem comp_assoc (f₃₄ : P3 →ᵃ[k] P4) (f₂₃ : P2 →ᵃ[k] P3) (f₁₂ : P1 →ᵃ[k] P2) :
(f₃₄.comp f₂₃).comp f₁₂ = f₃₄.comp (f₂₃.comp f₁₂) :=
rfl
#align affine_map.comp_assoc AffineMap.comp_assoc
instance : Monoid (P1 →ᵃ[k] P1) where
one := id k P1
mul := comp
one_mul := id_comp
mul_one := comp_id
mul_assoc := comp_assoc
@[simp]
theorem coe_mul (f g : P1 →ᵃ[k] P1) : ⇑(f * g) = f ∘ g :=
rfl
#align affine_map.coe_mul AffineMap.coe_mul
@[simp]
theorem coe_one : ⇑(1 : P1 →ᵃ[k] P1) = _root_.id :=
rfl
#align affine_map.coe_one AffineMap.coe_one
/-- `AffineMap.linear` on endomorphisms is a `MonoidHom`. -/
@[simps]
def linearHom : (P1 →ᵃ[k] P1) →* V1 →ₗ[k] V1 where
toFun := linear
map_one' := rfl
map_mul' _ _ := rfl
#align affine_map.linear_hom AffineMap.linearHom
@[simp]
theorem linear_injective_iff (f : P1 →ᵃ[k] P2) :
Function.Injective f.linear ↔ Function.Injective f := by
obtain ⟨p⟩ := (inferInstance : Nonempty P1)
have h : ⇑f.linear = (Equiv.vaddConst (f p)).symm ∘ f ∘ Equiv.vaddConst p := by
ext v
simp [f.map_vadd, vadd_vsub_assoc]
rw [h, Equiv.comp_injective, Equiv.injective_comp]
#align affine_map.linear_injective_iff AffineMap.linear_injective_iff
@[simp]
theorem linear_surjective_iff (f : P1 →ᵃ[k] P2) :
Function.Surjective f.linear ↔ Function.Surjective f := by
obtain ⟨p⟩ := (inferInstance : Nonempty P1)
have h : ⇑f.linear = (Equiv.vaddConst (f p)).symm ∘ f ∘ Equiv.vaddConst p := by
ext v
simp [f.map_vadd, vadd_vsub_assoc]
rw [h, Equiv.comp_surjective, Equiv.surjective_comp]
#align affine_map.linear_surjective_iff AffineMap.linear_surjective_iff
@[simp]
theorem linear_bijective_iff (f : P1 →ᵃ[k] P2) :
Function.Bijective f.linear ↔ Function.Bijective f :=
and_congr f.linear_injective_iff f.linear_surjective_iff
#align affine_map.linear_bijective_iff AffineMap.linear_bijective_iff
theorem image_vsub_image {s t : Set P1} (f : P1 →ᵃ[k] P2) :
f '' s -ᵥ f '' t = f.linear '' (s -ᵥ t) := by
ext v
-- Porting note: `simp` needs `Set.mem_vsub` to be an expression
simp only [(Set.mem_vsub), Set.mem_image,
exists_exists_and_eq_and, exists_and_left, ← f.linearMap_vsub]
constructor
· rintro ⟨x, hx, y, hy, hv⟩
exact ⟨x -ᵥ y, ⟨x, hx, y, hy, rfl⟩, hv⟩
· rintro ⟨-, ⟨x, hx, y, hy, rfl⟩, rfl⟩
exact ⟨x, hx, y, hy, rfl⟩
#align affine_map.image_vsub_image AffineMap.image_vsub_image
/-! ### Definition of `AffineMap.lineMap` and lemmas about it -/
/-- The affine map from `k` to `P1` sending `0` to `p₀` and `1` to `p₁`. -/
def lineMap (p₀ p₁ : P1) : k →ᵃ[k] P1 :=
((LinearMap.id : k →ₗ[k] k).smulRight (p₁ -ᵥ p₀)).toAffineMap +ᵥ const k k p₀
#align affine_map.line_map AffineMap.lineMap
theorem coe_lineMap (p₀ p₁ : P1) : (lineMap p₀ p₁ : k → P1) = fun c => c • (p₁ -ᵥ p₀) +ᵥ p₀ :=
rfl
#align affine_map.coe_line_map AffineMap.coe_lineMap
theorem lineMap_apply (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c = c • (p₁ -ᵥ p₀) +ᵥ p₀ :=
rfl
#align affine_map.line_map_apply AffineMap.lineMap_apply
theorem lineMap_apply_module' (p₀ p₁ : V1) (c : k) : lineMap p₀ p₁ c = c • (p₁ - p₀) + p₀ :=
rfl
#align affine_map.line_map_apply_module' AffineMap.lineMap_apply_module'
theorem lineMap_apply_module (p₀ p₁ : V1) (c : k) : lineMap p₀ p₁ c = (1 - c) • p₀ + c • p₁ := by
simp [lineMap_apply_module', smul_sub, sub_smul]; abel
#align affine_map.line_map_apply_module AffineMap.lineMap_apply_module
theorem lineMap_apply_ring' (a b c : k) : lineMap a b c = c * (b - a) + a :=
rfl
#align affine_map.line_map_apply_ring' AffineMap.lineMap_apply_ring'
theorem lineMap_apply_ring (a b c : k) : lineMap a b c = (1 - c) * a + c * b :=
lineMap_apply_module a b c
#align affine_map.line_map_apply_ring AffineMap.lineMap_apply_ring
theorem lineMap_vadd_apply (p : P1) (v : V1) (c : k) : lineMap p (v +ᵥ p) c = c • v +ᵥ p := by
rw [lineMap_apply, vadd_vsub]
#align affine_map.line_map_vadd_apply AffineMap.lineMap_vadd_apply
@[simp]
theorem lineMap_linear (p₀ p₁ : P1) :
(lineMap p₀ p₁ : k →ᵃ[k] P1).linear = LinearMap.id.smulRight (p₁ -ᵥ p₀) :=
add_zero _
#align affine_map.line_map_linear AffineMap.lineMap_linear
theorem lineMap_same_apply (p : P1) (c : k) : lineMap p p c = p := by
simp [lineMap_apply]
#align affine_map.line_map_same_apply AffineMap.lineMap_same_apply
@[simp]
theorem lineMap_same (p : P1) : lineMap p p = const k k p :=
ext <| lineMap_same_apply p
#align affine_map.line_map_same AffineMap.lineMap_same
@[simp]
theorem lineMap_apply_zero (p₀ p₁ : P1) : lineMap p₀ p₁ (0 : k) = p₀ := by
simp [lineMap_apply]
#align affine_map.line_map_apply_zero AffineMap.lineMap_apply_zero
@[simp]
theorem lineMap_apply_one (p₀ p₁ : P1) : lineMap p₀ p₁ (1 : k) = p₁ := by
simp [lineMap_apply]
#align affine_map.line_map_apply_one AffineMap.lineMap_apply_one
@[simp]
theorem lineMap_eq_lineMap_iff [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} {c₁ c₂ : k} :
lineMap p₀ p₁ c₁ = lineMap p₀ p₁ c₂ ↔ p₀ = p₁ ∨ c₁ = c₂ := by
rw [lineMap_apply, lineMap_apply, ← @vsub_eq_zero_iff_eq V1, vadd_vsub_vadd_cancel_right, ←
sub_smul, smul_eq_zero, sub_eq_zero, vsub_eq_zero_iff_eq, or_comm, eq_comm]
#align affine_map.line_map_eq_line_map_iff AffineMap.lineMap_eq_lineMap_iff
@[simp]
theorem lineMap_eq_left_iff [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} {c : k} :
lineMap p₀ p₁ c = p₀ ↔ p₀ = p₁ ∨ c = 0 := by
rw [← @lineMap_eq_lineMap_iff k V1, lineMap_apply_zero]
#align affine_map.line_map_eq_left_iff AffineMap.lineMap_eq_left_iff
@[simp]
theorem lineMap_eq_right_iff [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} {c : k} :
lineMap p₀ p₁ c = p₁ ↔ p₀ = p₁ ∨ c = 1 := by
rw [← @lineMap_eq_lineMap_iff k V1, lineMap_apply_one]
#align affine_map.line_map_eq_right_iff AffineMap.lineMap_eq_right_iff
variable (k)
theorem lineMap_injective [NoZeroSMulDivisors k V1] {p₀ p₁ : P1} (h : p₀ ≠ p₁) :
Function.Injective (lineMap p₀ p₁ : k → P1) := fun _c₁ _c₂ hc =>
(lineMap_eq_lineMap_iff.mp hc).resolve_left h
#align affine_map.line_map_injective AffineMap.lineMap_injective
variable {k}
@[simp]
theorem apply_lineMap (f : P1 →ᵃ[k] P2) (p₀ p₁ : P1) (c : k) :
f (lineMap p₀ p₁ c) = lineMap (f p₀) (f p₁) c := by
simp [lineMap_apply]
#align affine_map.apply_line_map AffineMap.apply_lineMap
@[simp]
theorem comp_lineMap (f : P1 →ᵃ[k] P2) (p₀ p₁ : P1) :
f.comp (lineMap p₀ p₁) = lineMap (f p₀) (f p₁) :=
ext <| f.apply_lineMap p₀ p₁
#align affine_map.comp_line_map AffineMap.comp_lineMap
@[simp]
theorem fst_lineMap (p₀ p₁ : P1 × P2) (c : k) : (lineMap p₀ p₁ c).1 = lineMap p₀.1 p₁.1 c :=
fst.apply_lineMap p₀ p₁ c
#align affine_map.fst_line_map AffineMap.fst_lineMap
@[simp]
theorem snd_lineMap (p₀ p₁ : P1 × P2) (c : k) : (lineMap p₀ p₁ c).2 = lineMap p₀.2 p₁.2 c :=
snd.apply_lineMap p₀ p₁ c
#align affine_map.snd_line_map AffineMap.snd_lineMap
theorem lineMap_symm (p₀ p₁ : P1) :
lineMap p₀ p₁ = (lineMap p₁ p₀).comp (lineMap (1 : k) (0 : k)) := by
rw [comp_lineMap]
simp
#align affine_map.line_map_symm AffineMap.lineMap_symm
theorem lineMap_apply_one_sub (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ (1 - c) = lineMap p₁ p₀ c := by
rw [lineMap_symm p₀, comp_apply]
congr
simp [lineMap_apply]
#align affine_map.line_map_apply_one_sub AffineMap.lineMap_apply_one_sub
@[simp]
theorem lineMap_vsub_left (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c -ᵥ p₀ = c • (p₁ -ᵥ p₀) :=
vadd_vsub _ _
#align affine_map.line_map_vsub_left AffineMap.lineMap_vsub_left
@[simp]
theorem left_vsub_lineMap (p₀ p₁ : P1) (c : k) : p₀ -ᵥ lineMap p₀ p₁ c = c • (p₀ -ᵥ p₁) := by
rw [← neg_vsub_eq_vsub_rev, lineMap_vsub_left, ← smul_neg, neg_vsub_eq_vsub_rev]
#align affine_map.left_vsub_line_map AffineMap.left_vsub_lineMap
@[simp]
theorem lineMap_vsub_right (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c -ᵥ p₁ = (1 - c) • (p₀ -ᵥ p₁) := by
rw [← lineMap_apply_one_sub, lineMap_vsub_left]
#align affine_map.line_map_vsub_right AffineMap.lineMap_vsub_right
@[simp]
theorem right_vsub_lineMap (p₀ p₁ : P1) (c : k) : p₁ -ᵥ lineMap p₀ p₁ c = (1 - c) • (p₁ -ᵥ p₀) := by
rw [← lineMap_apply_one_sub, left_vsub_lineMap]
#align affine_map.right_vsub_line_map AffineMap.right_vsub_lineMap
theorem lineMap_vadd_lineMap (v₁ v₂ : V1) (p₁ p₂ : P1) (c : k) :
lineMap v₁ v₂ c +ᵥ lineMap p₁ p₂ c = lineMap (v₁ +ᵥ p₁) (v₂ +ᵥ p₂) c :=
((fst : V1 × P1 →ᵃ[k] V1) +ᵥ (snd : V1 × P1 →ᵃ[k] P1)).apply_lineMap (v₁, p₁) (v₂, p₂) c
#align affine_map.line_map_vadd_line_map AffineMap.lineMap_vadd_lineMap
theorem lineMap_vsub_lineMap (p₁ p₂ p₃ p₄ : P1) (c : k) :
lineMap p₁ p₂ c -ᵥ lineMap p₃ p₄ c = lineMap (p₁ -ᵥ p₃) (p₂ -ᵥ p₄) c :=
((fst : P1 × P1 →ᵃ[k] P1) -ᵥ (snd : P1 × P1 →ᵃ[k] P1)).apply_lineMap (_, _) (_, _) c
#align affine_map.line_map_vsub_line_map AffineMap.lineMap_vsub_lineMap
/-- Decomposition of an affine map in the special case when the point space and vector space
are the same. -/
theorem decomp (f : V1 →ᵃ[k] V2) : (f : V1 → V2) = ⇑f.linear + fun _ => f 0 := by
ext x
calc
f x = f.linear x +ᵥ f 0 := by rw [← f.map_vadd, vadd_eq_add, add_zero]
_ = (f.linear + fun _ : V1 => f 0) x := rfl
#align affine_map.decomp AffineMap.decomp
/-- Decomposition of an affine map in the special case when the point space and vector space
are the same. -/
theorem decomp' (f : V1 →ᵃ[k] V2) : (f.linear : V1 → V2) = ⇑f - fun _ => f 0 := by
rw [decomp]
simp only [LinearMap.map_zero, Pi.add_apply, add_sub_cancel_right, zero_add]
#align affine_map.decomp' AffineMap.decomp'
theorem image_uIcc {k : Type*} [LinearOrderedField k] (f : k →ᵃ[k] k) (a b : k) :
f '' Set.uIcc a b = Set.uIcc (f a) (f b) := by
have : ⇑f = (fun x => x + f 0) ∘ fun x => x * (f 1 - f 0) := by
ext x
change f x = x • (f 1 -ᵥ f 0) +ᵥ f 0
rw [← f.linearMap_vsub, ← f.linear.map_smul, ← f.map_vadd]
simp only [vsub_eq_sub, add_zero, mul_one, vadd_eq_add, sub_zero, smul_eq_mul]
rw [this, Set.image_comp]
simp only [Set.image_add_const_uIcc, Set.image_mul_const_uIcc, Function.comp_apply]
#align affine_map.image_uIcc AffineMap.image_uIcc
section
variable {ι : Type*} {V : ι → Type*} {P : ι → Type*} [∀ i, AddCommGroup (V i)]
[∀ i, Module k (V i)] [∀ i, AddTorsor (V i) (P i)]
/-- Evaluation at a point as an affine map. -/
def proj (i : ι) : (∀ i : ι, P i) →ᵃ[k] P i where
toFun f := f i
linear := @LinearMap.proj k ι _ V _ _ i
map_vadd' _ _ := rfl
#align affine_map.proj AffineMap.proj
@[simp]
theorem proj_apply (i : ι) (f : ∀ i, P i) : @proj k _ ι V P _ _ _ i f = f i :=
rfl
#align affine_map.proj_apply AffineMap.proj_apply
@[simp]
theorem proj_linear (i : ι) : (@proj k _ ι V P _ _ _ i).linear = @LinearMap.proj k ι _ V _ _ i :=
rfl
#align affine_map.proj_linear AffineMap.proj_linear
theorem pi_lineMap_apply (f g : ∀ i, P i) (c : k) (i : ι) :
lineMap f g c i = lineMap (f i) (g i) c :=
(proj i : (∀ i, P i) →ᵃ[k] P i).apply_lineMap f g c
#align affine_map.pi_line_map_apply AffineMap.pi_lineMap_apply
end
end AffineMap
namespace AffineMap
variable {R k V1 P1 V2 P2 V3 P3 : Type*}
section Ring
variable [Ring k] [AddCommGroup V1] [AffineSpace V1 P1] [AddCommGroup V2] [AffineSpace V2 P2]
variable [AddCommGroup V3] [AffineSpace V3 P3] [Module k V1] [Module k V2] [Module k V3]
section DistribMulAction
variable [Monoid R] [DistribMulAction R V2] [SMulCommClass k R V2]
/-- The space of affine maps to a module inherits an `R`-action from the action on its codomain. -/
instance distribMulAction : DistribMulAction R (P1 →ᵃ[k] V2) where
smul_add _ _ _ := ext fun _ => smul_add _ _ _
smul_zero _ := ext fun _ => smul_zero _
end DistribMulAction
section Module
variable [Semiring R] [Module R V2] [SMulCommClass k R V2]
/-- The space of affine maps taking values in an `R`-module is an `R`-module. -/
instance : Module R (P1 →ᵃ[k] V2) :=
{ AffineMap.distribMulAction with
add_smul := fun _ _ _ => ext fun _ => add_smul _ _ _
zero_smul := fun _ => ext fun _ => zero_smul _ _ }
variable (R)
/-- The space of affine maps between two modules is linearly equivalent to the product of the
domain with the space of linear maps, by taking the value of the affine map at `(0 : V1)` and the
linear part.
See note [bundled maps over different rings]-/
@[simps]
def toConstProdLinearMap : (V1 →ᵃ[k] V2) ≃ₗ[R] V2 × (V1 →ₗ[k] V2) where
toFun f := ⟨f 0, f.linear⟩
invFun p := p.2.toAffineMap + const k V1 p.1
left_inv f := by
ext
rw [f.decomp]
simp [const_apply _ _] -- Porting note: `simp` needs `_`s to use this lemma
right_inv := by
rintro ⟨v, f⟩
ext <;> simp [const_apply _ _, const_linear _ _] -- Porting note: `simp` needs `_`s
map_add' := by simp
map_smul' := by simp
#align affine_map.to_const_prod_linear_map AffineMap.toConstProdLinearMap
end Module
section Pi
variable {ι : Type*} {φv φp : ι → Type*} [(i : ι) → AddCommGroup (φv i)]
[(i : ι) → Module k (φv i)] [(i : ι) → AffineSpace (φv i) (φp i)]
/-- `pi` construction for affine maps. From a family of affine maps it produces an affine
map into a family of affine spaces.
This is the affine version of `LinearMap.pi`.
-/
def pi (f : (i : ι) → (P1 →ᵃ[k] φp i)) : P1 →ᵃ[k] ((i : ι) → φp i) where
toFun m a := f a m
linear := LinearMap.pi (fun a ↦ (f a).linear)
map_vadd' _ _ := funext fun _ ↦ map_vadd _ _ _
--fp for when the image is a dependent AffineSpace φp i, fv for when the
--image is a Module φv i, f' for when the image isn't dependent.
variable (fp : (i : ι) → (P1 →ᵃ[k] φp i)) (fv : (i : ι) → (P1 →ᵃ[k] φv i))
(f' : ι → P1 →ᵃ[k] P2)
@[simp]
theorem pi_apply (c : P1) (i : ι) : pi fp c i = fp i c :=
rfl
theorem pi_comp (g : P3 →ᵃ[k] P1) : (pi fp).comp g = pi (fun i => (fp i).comp g) :=
rfl
theorem pi_eq_zero : pi fv = 0 ↔ ∀ i, fv i = 0 := by
simp only [AffineMap.ext_iff, Function.funext_iff, pi_apply]
exact forall_comm
theorem pi_zero : pi (fun _ ↦ 0 : (i : ι) → P1 →ᵃ[k] φv i) = 0 := by
ext; rfl
theorem proj_pi (i : ι) : (proj i).comp (pi fp) = fp i :=
ext fun _ => rfl
section Ext
variable [Finite ι] [DecidableEq ι] {f g : ((i : ι) → φv i) →ᵃ[k] P2}
/-- Two affine maps from a Pi-tyoe of modules `(i : ι) → φv i` are equal if they are equal in their
operation on `Pi.single` and at zero. Analogous to `LinearMap.pi_ext`. See also `pi_ext_nonempty`,
which instead of agrement at zero requires `Nonempty ι`. -/
| Mathlib/LinearAlgebra/AffineSpace/AffineMap.lean | 815 | 829 | theorem pi_ext_zero (h : ∀ i x, f (Pi.single i x) = g (Pi.single i x)) (h₂ : f 0 = g 0) :
f = g := by |
apply ext_linear
next =>
apply LinearMap.pi_ext
intro i x
have s₁ := h i x
have s₂ := f.map_vadd 0 (Pi.single i x)
have s₃ := g.map_vadd 0 (Pi.single i x)
rw [vadd_eq_add, add_zero] at s₂ s₃
replace h₂ := h i 0
simp at h₂
rwa [s₂, s₃, h₂, vadd_right_cancel_iff] at s₁
next =>
exact h₂
|
/-
Copyright (c) 2023 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.Analysis.Fourier.AddCircle
import Mathlib.Analysis.Fourier.FourierTransform
import Mathlib.Analysis.PSeries
import Mathlib.Analysis.Distribution.SchwartzSpace
import Mathlib.MeasureTheory.Measure.Lebesgue.Integral
#align_import analysis.fourier.poisson_summation from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Poisson's summation formula
We prove Poisson's summation formula `∑ (n : ℤ), f n = ∑ (n : ℤ), 𝓕 f n`, where `𝓕 f` is the
Fourier transform of `f`, under the following hypotheses:
* `f` is a continuous function `ℝ → ℂ`.
* The sum `∑ (n : ℤ), 𝓕 f n` is convergent.
* For all compacts `K ⊂ ℝ`, the sum `∑ (n : ℤ), sup { ‖f(x + n)‖ | x ∈ K }` is convergent.
See `Real.tsum_eq_tsum_fourierIntegral` for this formulation.
These hypotheses are potentially a little awkward to apply, so we also provide the less general but
easier-to-use result `Real.tsum_eq_tsum_fourierIntegral_of_rpow_decay`, in which we assume `f` and
`𝓕 f` both decay as `|x| ^ (-b)` for some `b > 1`, and the even more specific result
`SchwartzMap.tsum_eq_tsum_fourierIntegral`, where we assume that both `f` and `𝓕 f` are Schwartz
functions.
## TODO
At the moment `SchwartzMap.tsum_eq_tsum_fourierIntegral` requires separate proofs that both `f`
and `𝓕 f` are Schwartz functions. In fact, `𝓕 f` is automatically Schwartz if `f` is; and once
we have this lemma in the library, we should adjust the hypotheses here accordingly.
-/
noncomputable section
open Function hiding comp_apply
open Set hiding restrict_apply
open Complex hiding abs_of_nonneg
open Real
open TopologicalSpace Filter MeasureTheory Asymptotics
open scoped Real Filter FourierTransform
open ContinuousMap
/-- The key lemma for Poisson summation: the `m`-th Fourier coefficient of the periodic function
`∑' n : ℤ, f (x + n)` is the value at `m` of the Fourier transform of `f`. -/
| Mathlib/Analysis/Fourier/PoissonSummation.lean | 56 | 103 | theorem Real.fourierCoeff_tsum_comp_add {f : C(ℝ, ℂ)}
(hf : ∀ K : Compacts ℝ, Summable fun n : ℤ => ‖(f.comp (ContinuousMap.addRight n)).restrict K‖)
(m : ℤ) : fourierCoeff (Periodic.lift <| f.periodic_tsum_comp_add_zsmul 1) m = 𝓕 f m := by |
-- NB: This proof can be shortened somewhat by telescoping together some of the steps in the calc
-- block, but I think it's more legible this way. We start with preliminaries about the integrand.
let e : C(ℝ, ℂ) := (fourier (-m)).comp ⟨((↑) : ℝ → UnitAddCircle), continuous_quotient_mk'⟩
have neK : ∀ (K : Compacts ℝ) (g : C(ℝ, ℂ)), ‖(e * g).restrict K‖ = ‖g.restrict K‖ := by
have (x : ℝ) : ‖e x‖ = 1 := abs_coe_circle (AddCircle.toCircle (-m • x))
intro K g
simp_rw [norm_eq_iSup_norm, restrict_apply, mul_apply, norm_mul, this, one_mul]
have eadd : ∀ (n : ℤ), e.comp (ContinuousMap.addRight n) = e := by
intro n; ext1 x
have : Periodic e 1 := Periodic.comp (fun x => AddCircle.coe_add_period 1 x) (fourier (-m))
simpa only [mul_one] using this.int_mul n x
-- Now the main argument. First unwind some definitions.
calc
fourierCoeff (Periodic.lift <| f.periodic_tsum_comp_add_zsmul 1) m =
∫ x in (0 : ℝ)..1, e x * (∑' n : ℤ, f.comp (ContinuousMap.addRight n)) x := by
simp_rw [fourierCoeff_eq_intervalIntegral _ m 0, div_one, one_smul, zero_add, e, comp_apply,
coe_mk, Periodic.lift_coe, zsmul_one, smul_eq_mul]
-- Transform sum in C(ℝ, ℂ) evaluated at x into pointwise sum of values.
_ = ∫ x in (0:ℝ)..1, ∑' n : ℤ, (e * f.comp (ContinuousMap.addRight n)) x := by
simp_rw [coe_mul, Pi.mul_apply,
← ContinuousMap.tsum_apply (summable_of_locally_summable_norm hf), tsum_mul_left]
-- Swap sum and integral.
_ = ∑' n : ℤ, ∫ x in (0:ℝ)..1, (e * f.comp (ContinuousMap.addRight n)) x := by
refine (intervalIntegral.tsum_intervalIntegral_eq_of_summable_norm ?_).symm
convert hf ⟨uIcc 0 1, isCompact_uIcc⟩ using 1
exact funext fun n => neK _ _
_ = ∑' n : ℤ, ∫ x in (0:ℝ)..1, (e * f).comp (ContinuousMap.addRight n) x := by
simp only [ContinuousMap.comp_apply, mul_comp] at eadd ⊢
simp_rw [eadd]
-- Rearrange sum of interval integrals into an integral over `ℝ`.
_ = ∫ x, e x * f x := by
suffices Integrable (e * f) from this.hasSum_intervalIntegral_comp_add_int.tsum_eq
apply integrable_of_summable_norm_Icc
convert hf ⟨Icc 0 1, isCompact_Icc⟩ using 1
simp_rw [mul_comp] at eadd ⊢
simp_rw [eadd]
exact funext fun n => neK ⟨Icc 0 1, isCompact_Icc⟩ _
-- Minor tidying to finish
_ = 𝓕 f m := by
rw [fourierIntegral_real_eq_integral_exp_smul]
congr 1 with x : 1
rw [smul_eq_mul, comp_apply, coe_mk, coe_mk, ContinuousMap.toFun_eq_coe, fourier_coe_apply]
congr 2
push_cast
ring
|
/-
Copyright (c) 2020 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Constructions.Prod.Basic
import Mathlib.MeasureTheory.Integral.DominatedConvergence
import Mathlib.MeasureTheory.Integral.SetIntegral
#align_import measure_theory.constructions.prod.integral from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Integration with respect to the product measure
In this file we prove Fubini's theorem.
## Main results
* `MeasureTheory.integrable_prod_iff` states that a binary function is integrable iff both
* `y ↦ f (x, y)` is integrable for almost every `x`, and
* the function `x ↦ ∫ ‖f (x, y)‖ dy` is integrable.
* `MeasureTheory.integral_prod`: Fubini's theorem. It states that for an integrable function
`α × β → E` (where `E` is a second countable Banach space) we have
`∫ z, f z ∂(μ.prod ν) = ∫ x, ∫ y, f (x, y) ∂ν ∂μ`. This theorem has the same variants as
Tonelli's theorem (see `MeasureTheory.lintegral_prod`). The lemma
`MeasureTheory.Integrable.integral_prod_right` states that the inner integral of the right-hand
side is integrable.
* `MeasureTheory.integral_integral_swap_of_hasCompactSupport`: a version of Fubini theorem for
continuous functions with compact support, which does not assume that the measures are σ-finite
contrary to all the usual versions of Fubini.
## Tags
product measure, Fubini's theorem, Fubini-Tonelli theorem
-/
noncomputable section
open scoped Classical Topology ENNReal MeasureTheory
open Set Function Real ENNReal
open MeasureTheory MeasurableSpace MeasureTheory.Measure
open TopologicalSpace
open Filter hiding prod_eq map
variable {α α' β β' γ E : Type*}
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.
-/
theorem measurableSet_integrable [SigmaFinite ν] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : MeasurableSet {x | Integrable (f x) ν} := by
simp_rw [Integrable, hf.of_uncurry_left.aestronglyMeasurable, true_and_iff]
exact measurableSet_lt (Measurable.lintegral_prod_right hf.ennnorm) measurable_const
#align measurable_set_integrable measurableSet_integrable
section
variable [NormedSpace ℝ E]
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
Fubini's theorem is measurable.
This version has `f` in curried form. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_right [SigmaFinite ν] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : StronglyMeasurable fun x => ∫ y, f x y ∂ν := by
by_cases hE : CompleteSpace E; swap; · simp [integral, hE, stronglyMeasurable_const]
borelize E
haveI : SeparableSpace (range (uncurry f) ∪ {0} : Set E) :=
hf.separableSpace_range_union_singleton
let s : ℕ → SimpleFunc (α × β) E :=
SimpleFunc.approxOn _ hf.measurable (range (uncurry f) ∪ {0}) 0 (by simp)
let s' : ℕ → α → SimpleFunc β E := fun n x => (s n).comp (Prod.mk x) measurable_prod_mk_left
let f' : ℕ → α → E := fun n => {x | Integrable (f x) ν}.indicator fun x => (s' n x).integral ν
have hf' : ∀ n, StronglyMeasurable (f' n) := by
intro n; refine StronglyMeasurable.indicator ?_ (measurableSet_integrable hf)
have : ∀ x, ((s' n x).range.filter fun x => x ≠ 0) ⊆ (s n).range := by
intro x; refine Finset.Subset.trans (Finset.filter_subset _ _) ?_; intro y
simp_rw [SimpleFunc.mem_range]; rintro ⟨z, rfl⟩; exact ⟨(x, z), rfl⟩
simp only [SimpleFunc.integral_eq_sum_of_subset (this _)]
refine Finset.stronglyMeasurable_sum _ fun x _ => ?_
refine (Measurable.ennreal_toReal ?_).stronglyMeasurable.smul_const _
simp only [s', SimpleFunc.coe_comp, preimage_comp]
apply measurable_measure_prod_mk_left
exact (s n).measurableSet_fiber x
have h2f' : Tendsto f' atTop (𝓝 fun x : α => ∫ y : β, f x y ∂ν) := by
rw [tendsto_pi_nhds]; intro x
by_cases hfx : Integrable (f x) ν
· have (n) : Integrable (s' n x) ν := by
apply (hfx.norm.add hfx.norm).mono' (s' n x).aestronglyMeasurable
filter_upwards with y
simp_rw [s', SimpleFunc.coe_comp]; exact SimpleFunc.norm_approxOn_zero_le _ _ (x, y) n
simp only [f', hfx, SimpleFunc.integral_eq_integral _ (this _), indicator_of_mem,
mem_setOf_eq]
refine
tendsto_integral_of_dominated_convergence (fun y => ‖f x y‖ + ‖f x y‖)
(fun n => (s' n x).aestronglyMeasurable) (hfx.norm.add hfx.norm) ?_ ?_
· refine fun n => eventually_of_forall fun y =>
SimpleFunc.norm_approxOn_zero_le ?_ ?_ (x, y) n
-- Porting note: Lean 3 solved the following two subgoals on its own
· exact hf.measurable
· simp
· refine eventually_of_forall fun y => SimpleFunc.tendsto_approxOn ?_ ?_ ?_
-- Porting note: Lean 3 solved the following two subgoals on its own
· exact hf.measurable.of_uncurry_left
· simp
apply subset_closure
simp [-uncurry_apply_pair]
· simp [f', hfx, integral_undef]
exact stronglyMeasurable_of_tendsto _ hf' h2f'
#align measure_theory.strongly_measurable.integral_prod_right MeasureTheory.StronglyMeasurable.integral_prod_right
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
Fubini's theorem is measurable. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_right' [SigmaFinite ν] ⦃f : α × β → E⦄
(hf : StronglyMeasurable f) : StronglyMeasurable fun x => ∫ y, f (x, y) ∂ν := by
rw [← uncurry_curry f] at hf; exact hf.integral_prod_right
#align measure_theory.strongly_measurable.integral_prod_right' MeasureTheory.StronglyMeasurable.integral_prod_right'
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Fubini's theorem is measurable.
This version has `f` in curried form. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_left [SigmaFinite μ] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : StronglyMeasurable fun y => ∫ x, f x y ∂μ :=
(hf.comp_measurable measurable_swap).integral_prod_right'
#align measure_theory.strongly_measurable.integral_prod_left MeasureTheory.StronglyMeasurable.integral_prod_left
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Fubini's theorem is measurable. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_left' [SigmaFinite μ] ⦃f : α × β → E⦄
(hf : StronglyMeasurable f) : StronglyMeasurable fun y => ∫ x, f (x, y) ∂μ :=
(hf.comp_measurable measurable_swap).integral_prod_right'
#align measure_theory.strongly_measurable.integral_prod_left' MeasureTheory.StronglyMeasurable.integral_prod_left'
end
/-! ### The product measure -/
namespace MeasureTheory
namespace Measure
variable [SigmaFinite ν]
theorem integrable_measure_prod_mk_left {s : Set (α × β)} (hs : MeasurableSet s)
(h2s : (μ.prod ν) s ≠ ∞) : Integrable (fun x => (ν (Prod.mk x ⁻¹' s)).toReal) μ := by
refine ⟨(measurable_measure_prod_mk_left hs).ennreal_toReal.aemeasurable.aestronglyMeasurable, ?_⟩
simp_rw [HasFiniteIntegral, ennnorm_eq_ofReal toReal_nonneg]
convert h2s.lt_top using 1
-- Porting note: was `simp_rw`
rw [prod_apply hs]
apply lintegral_congr_ae
filter_upwards [ae_measure_lt_top hs h2s] with x hx
rw [lt_top_iff_ne_top] at hx; simp [ofReal_toReal, hx]
#align measure_theory.measure.integrable_measure_prod_mk_left MeasureTheory.Measure.integrable_measure_prod_mk_left
end Measure
open Measure
end MeasureTheory
open MeasureTheory.Measure
section
nonrec theorem MeasureTheory.AEStronglyMeasurable.prod_swap {γ : Type*} [TopologicalSpace γ]
[SigmaFinite μ] [SigmaFinite ν] {f : β × α → γ} (hf : AEStronglyMeasurable f (ν.prod μ)) :
AEStronglyMeasurable (fun z : α × β => f z.swap) (μ.prod ν) := by
rw [← prod_swap] at hf
exact hf.comp_measurable measurable_swap
#align measure_theory.ae_strongly_measurable.prod_swap MeasureTheory.AEStronglyMeasurable.prod_swap
theorem MeasureTheory.AEStronglyMeasurable.fst {γ} [TopologicalSpace γ] [SigmaFinite ν] {f : α → γ}
(hf : AEStronglyMeasurable f μ) : AEStronglyMeasurable (fun z : α × β => f z.1) (μ.prod ν) :=
hf.comp_quasiMeasurePreserving quasiMeasurePreserving_fst
#align measure_theory.ae_strongly_measurable.fst MeasureTheory.AEStronglyMeasurable.fst
theorem MeasureTheory.AEStronglyMeasurable.snd {γ} [TopologicalSpace γ] [SigmaFinite ν] {f : β → γ}
(hf : AEStronglyMeasurable f ν) : AEStronglyMeasurable (fun z : α × β => f z.2) (μ.prod ν) :=
hf.comp_quasiMeasurePreserving quasiMeasurePreserving_snd
#align measure_theory.ae_strongly_measurable.snd MeasureTheory.AEStronglyMeasurable.snd
/-- The Bochner integral is a.e.-measurable.
This shows that the integrand of (the right-hand-side of) Fubini's theorem is a.e.-measurable. -/
theorem MeasureTheory.AEStronglyMeasurable.integral_prod_right' [SigmaFinite ν] [NormedSpace ℝ E]
⦃f : α × β → E⦄ (hf : AEStronglyMeasurable f (μ.prod ν)) :
AEStronglyMeasurable (fun x => ∫ y, f (x, y) ∂ν) μ :=
⟨fun x => ∫ y, hf.mk f (x, y) ∂ν, hf.stronglyMeasurable_mk.integral_prod_right', by
filter_upwards [ae_ae_of_ae_prod hf.ae_eq_mk] with _ hx using integral_congr_ae hx⟩
#align measure_theory.ae_strongly_measurable.integral_prod_right' MeasureTheory.AEStronglyMeasurable.integral_prod_right'
theorem MeasureTheory.AEStronglyMeasurable.prod_mk_left {γ : Type*} [SigmaFinite ν]
[TopologicalSpace γ] {f : α × β → γ} (hf : AEStronglyMeasurable f (μ.prod ν)) :
∀ᵐ x ∂μ, AEStronglyMeasurable (fun y => f (x, y)) ν := by
filter_upwards [ae_ae_of_ae_prod hf.ae_eq_mk] with x hx
exact
⟨fun y => hf.mk f (x, y), hf.stronglyMeasurable_mk.comp_measurable measurable_prod_mk_left, hx⟩
#align measure_theory.ae_strongly_measurable.prod_mk_left MeasureTheory.AEStronglyMeasurable.prod_mk_left
end
namespace MeasureTheory
variable [SigmaFinite ν]
/-! ### Integrability on a product -/
section
theorem integrable_swap_iff [SigmaFinite μ] {f : α × β → E} :
Integrable (f ∘ Prod.swap) (ν.prod μ) ↔ Integrable f (μ.prod ν) :=
measurePreserving_swap.integrable_comp_emb MeasurableEquiv.prodComm.measurableEmbedding
#align measure_theory.integrable_swap_iff MeasureTheory.integrable_swap_iff
theorem Integrable.swap [SigmaFinite μ] ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
Integrable (f ∘ Prod.swap) (ν.prod μ) :=
integrable_swap_iff.2 hf
#align measure_theory.integrable.swap MeasureTheory.Integrable.swap
theorem hasFiniteIntegral_prod_iff ⦃f : α × β → E⦄ (h1f : StronglyMeasurable f) :
HasFiniteIntegral f (μ.prod ν) ↔
(∀ᵐ x ∂μ, HasFiniteIntegral (fun y => f (x, y)) ν) ∧
HasFiniteIntegral (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ := by
simp only [HasFiniteIntegral, lintegral_prod_of_measurable _ h1f.ennnorm]
have (x) : ∀ᵐ y ∂ν, 0 ≤ ‖f (x, y)‖ := by filter_upwards with y using 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]
-- this fact is probably too specialized to be its own lemma
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_prod_right'
#align measure_theory.has_finite_integral_prod_iff MeasureTheory.hasFiniteIntegral_prod_iff
theorem hasFiniteIntegral_prod_iff' ⦃f : α × β → E⦄ (h1f : AEStronglyMeasurable f (μ.prod ν)) :
HasFiniteIntegral f (μ.prod ν) ↔
(∀ᵐ x ∂μ, HasFiniteIntegral (fun y => f (x, y)) ν) ∧
HasFiniteIntegral (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ := by
rw [hasFiniteIntegral_congr h1f.ae_eq_mk,
hasFiniteIntegral_prod_iff h1f.stronglyMeasurable_mk]
apply and_congr
· apply eventually_congr
filter_upwards [ae_ae_of_ae_prod h1f.ae_eq_mk.symm]
intro x hx
exact hasFiniteIntegral_congr hx
· apply hasFiniteIntegral_congr
filter_upwards [ae_ae_of_ae_prod h1f.ae_eq_mk.symm] with _ hx using
integral_congr_ae (EventuallyEq.fun_comp hx _)
#align measure_theory.has_finite_integral_prod_iff' MeasureTheory.hasFiniteIntegral_prod_iff'
/-- A binary function is integrable if the function `y ↦ f (x, y)` is integrable for almost every
`x` and the function `x ↦ ∫ ‖f (x, y)‖ dy` is integrable. -/
theorem integrable_prod_iff ⦃f : α × β → E⦄ (h1f : AEStronglyMeasurable f (μ.prod ν)) :
Integrable f (μ.prod ν) ↔
(∀ᵐ x ∂μ, Integrable (fun y => f (x, y)) ν) ∧ Integrable (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ := by
simp [Integrable, h1f, hasFiniteIntegral_prod_iff', h1f.norm.integral_prod_right',
h1f.prod_mk_left]
#align measure_theory.integrable_prod_iff MeasureTheory.integrable_prod_iff
/-- A binary function is integrable if the function `x ↦ f (x, y)` is integrable for almost every
`y` and the function `y ↦ ∫ ‖f (x, y)‖ dx` is integrable. -/
theorem integrable_prod_iff' [SigmaFinite μ] ⦃f : α × β → E⦄
(h1f : AEStronglyMeasurable f (μ.prod ν)) :
Integrable f (μ.prod ν) ↔
(∀ᵐ y ∂ν, Integrable (fun x => f (x, y)) μ) ∧ Integrable (fun y => ∫ x, ‖f (x, y)‖ ∂μ) ν := by
convert integrable_prod_iff h1f.prod_swap using 1
rw [funext fun _ => Function.comp_apply.symm, integrable_swap_iff]
#align measure_theory.integrable_prod_iff' MeasureTheory.integrable_prod_iff'
theorem Integrable.prod_left_ae [SigmaFinite μ] ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
∀ᵐ y ∂ν, Integrable (fun x => f (x, y)) μ :=
((integrable_prod_iff' hf.aestronglyMeasurable).mp hf).1
#align measure_theory.integrable.prod_left_ae MeasureTheory.Integrable.prod_left_ae
theorem Integrable.prod_right_ae [SigmaFinite μ] ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
∀ᵐ x ∂μ, Integrable (fun y => f (x, y)) ν :=
hf.swap.prod_left_ae
#align measure_theory.integrable.prod_right_ae MeasureTheory.Integrable.prod_right_ae
theorem Integrable.integral_norm_prod_left ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
Integrable (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ :=
((integrable_prod_iff hf.aestronglyMeasurable).mp hf).2
#align measure_theory.integrable.integral_norm_prod_left MeasureTheory.Integrable.integral_norm_prod_left
theorem Integrable.integral_norm_prod_right [SigmaFinite μ] ⦃f : α × β → E⦄
(hf : Integrable f (μ.prod ν)) : Integrable (fun y => ∫ x, ‖f (x, y)‖ ∂μ) ν :=
hf.swap.integral_norm_prod_left
#align measure_theory.integrable.integral_norm_prod_right MeasureTheory.Integrable.integral_norm_prod_right
theorem Integrable.prod_smul {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E]
{f : α → 𝕜} {g : β → E} (hf : Integrable f μ) (hg : Integrable g ν) :
Integrable (fun z : α × β => f z.1 • g z.2) (μ.prod ν) := by
refine (integrable_prod_iff ?_).2 ⟨?_, ?_⟩
· exact hf.1.fst.smul hg.1.snd
· exact eventually_of_forall fun x => hg.smul (f x)
· simpa only [norm_smul, integral_mul_left] using hf.norm.mul_const _
theorem Integrable.prod_mul {L : Type*} [RCLike L] {f : α → L} {g : β → L} (hf : Integrable f μ)
(hg : Integrable g ν) : Integrable (fun z : α × β => f z.1 * g z.2) (μ.prod ν) :=
hf.prod_smul hg
#align measure_theory.integrable_prod_mul MeasureTheory.Integrable.prod_mul
end
variable [NormedSpace ℝ E]
theorem Integrable.integral_prod_left ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
Integrable (fun x => ∫ y, f (x, y) ∂ν) μ :=
Integrable.mono hf.integral_norm_prod_left hf.aestronglyMeasurable.integral_prod_right' <|
eventually_of_forall fun x =>
(norm_integral_le_integral_norm _).trans_eq <|
(norm_of_nonneg <|
integral_nonneg_of_ae <|
eventually_of_forall fun y => (norm_nonneg (f (x, y)) : _)).symm
#align measure_theory.integrable.integral_prod_left MeasureTheory.Integrable.integral_prod_left
theorem Integrable.integral_prod_right [SigmaFinite μ] ⦃f : α × β → E⦄
(hf : Integrable f (μ.prod ν)) : Integrable (fun y => ∫ x, f (x, y) ∂μ) ν :=
hf.swap.integral_prod_left
#align measure_theory.integrable.integral_prod_right MeasureTheory.Integrable.integral_prod_right
/-! ### The Bochner integral on a product -/
variable [SigmaFinite μ]
theorem integral_prod_swap (f : α × β → E) :
∫ z, f z.swap ∂ν.prod μ = ∫ z, f z ∂μ.prod ν :=
measurePreserving_swap.integral_comp MeasurableEquiv.prodComm.measurableEmbedding _
#align measure_theory.integral_prod_swap MeasureTheory.integral_prod_swap
variable {E' : Type*} [NormedAddCommGroup E'] [NormedSpace ℝ E']
/-! Some rules about the sum/difference of double integrals. They follow from `integral_add`, but
we separate them out as separate lemmas, because they involve quite some steps. -/
/-- Integrals commute with addition inside another integral. `F` can be any function. -/
theorem integral_fn_integral_add ⦃f g : α × β → E⦄ (F : E → E') (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, F (∫ y, f (x, y) + g (x, y) ∂ν) ∂μ) =
∫ x, F ((∫ y, f (x, y) ∂ν) + ∫ y, g (x, y) ∂ν) ∂μ := by
refine integral_congr_ae ?_
filter_upwards [hf.prod_right_ae, hg.prod_right_ae] with _ h2f h2g
simp [integral_add h2f h2g]
#align measure_theory.integral_fn_integral_add MeasureTheory.integral_fn_integral_add
/-- Integrals commute with subtraction inside another integral.
`F` can be any measurable function. -/
theorem integral_fn_integral_sub ⦃f g : α × β → E⦄ (F : E → E') (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, F (∫ y, f (x, y) - g (x, y) ∂ν) ∂μ) =
∫ x, F ((∫ y, f (x, y) ∂ν) - ∫ y, g (x, y) ∂ν) ∂μ := by
refine integral_congr_ae ?_
filter_upwards [hf.prod_right_ae, hg.prod_right_ae] with _ h2f h2g
simp [integral_sub h2f h2g]
#align measure_theory.integral_fn_integral_sub MeasureTheory.integral_fn_integral_sub
/-- Integrals commute with subtraction inside a lower Lebesgue integral.
`F` can be any function. -/
theorem lintegral_fn_integral_sub ⦃f g : α × β → E⦄ (F : E → ℝ≥0∞) (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫⁻ x, F (∫ y, f (x, y) - g (x, y) ∂ν) ∂μ) =
∫⁻ x, F ((∫ y, f (x, y) ∂ν) - ∫ y, g (x, y) ∂ν) ∂μ := by
refine lintegral_congr_ae ?_
filter_upwards [hf.prod_right_ae, hg.prod_right_ae] with _ h2f h2g
simp [integral_sub h2f h2g]
#align measure_theory.lintegral_fn_integral_sub MeasureTheory.lintegral_fn_integral_sub
/-- Double integrals commute with addition. -/
theorem integral_integral_add ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, f (x, y) + g (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) + ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
(integral_fn_integral_add id hf hg).trans <|
integral_add hf.integral_prod_left hg.integral_prod_left
#align measure_theory.integral_integral_add MeasureTheory.integral_integral_add
/-- Double integrals commute with addition. This is the version with `(f + g) (x, y)`
(instead of `f (x, y) + g (x, y)`) in the LHS. -/
theorem integral_integral_add' ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, (f + g) (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) + ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
integral_integral_add hf hg
#align measure_theory.integral_integral_add' MeasureTheory.integral_integral_add'
/-- Double integrals commute with subtraction. -/
theorem integral_integral_sub ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, f (x, y) - g (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) - ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
(integral_fn_integral_sub id hf hg).trans <|
integral_sub hf.integral_prod_left hg.integral_prod_left
#align measure_theory.integral_integral_sub MeasureTheory.integral_integral_sub
/-- Double integrals commute with subtraction. This is the version with `(f - g) (x, y)`
(instead of `f (x, y) - g (x, y)`) in the LHS. -/
theorem integral_integral_sub' ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, (f - g) (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) - ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
integral_integral_sub hf hg
#align measure_theory.integral_integral_sub' MeasureTheory.integral_integral_sub'
/-- The map that sends an L¹-function `f : α × β → E` to `∫∫f` is continuous. -/
theorem continuous_integral_integral :
Continuous fun f : α × β →₁[μ.prod ν] E => ∫ x, ∫ y, f (x, y) ∂ν ∂μ := by
rw [continuous_iff_continuousAt]; intro g
refine
tendsto_integral_of_L1 _ (L1.integrable_coeFn g).integral_prod_left
(eventually_of_forall fun h => (L1.integrable_coeFn h).integral_prod_left) ?_
simp_rw [←
lintegral_fn_integral_sub (fun x => (‖x‖₊ : ℝ≥0∞)) (L1.integrable_coeFn _)
(L1.integrable_coeFn g)]
apply tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds _ (fun i => zero_le _) _
· exact fun i => ∫⁻ x, ∫⁻ y, ‖i (x, y) - g (x, y)‖₊ ∂ν ∂μ
swap; · exact fun i => lintegral_mono fun x => ennnorm_integral_le_lintegral_ennnorm _
show
Tendsto (fun i : α × β →₁[μ.prod ν] E => ∫⁻ x, ∫⁻ y : β, ‖i (x, y) - g (x, y)‖₊ ∂ν ∂μ) (𝓝 g)
(𝓝 0)
have : ∀ i : α × β →₁[μ.prod ν] E, Measurable fun z => (‖i z - g z‖₊ : ℝ≥0∞) := fun i =>
((Lp.stronglyMeasurable i).sub (Lp.stronglyMeasurable g)).ennnorm
-- Porting note: was
-- simp_rw [← lintegral_prod_of_measurable _ (this _), ← L1.ofReal_norm_sub_eq_lintegral, ←
-- ofReal_zero]
conv =>
congr
ext
rw [← lintegral_prod_of_measurable _ (this _), ← L1.ofReal_norm_sub_eq_lintegral]
rw [← ofReal_zero]
refine (continuous_ofReal.tendsto 0).comp ?_
rw [← tendsto_iff_norm_sub_tendsto_zero]; exact tendsto_id
#align measure_theory.continuous_integral_integral MeasureTheory.continuous_integral_integral
/-- **Fubini's Theorem**: For integrable functions on `α × β`,
the Bochner integral of `f` is equal to the iterated Bochner integral.
`integrable_prod_iff` can be useful to show that the function in question in integrable.
`MeasureTheory.Integrable.integral_prod_right` is useful to show that the inner integral
of the right-hand side is integrable. -/
theorem integral_prod (f : α × β → E) (hf : Integrable f (μ.prod ν)) :
∫ z, f z ∂μ.prod ν = ∫ x, ∫ y, f (x, y) ∂ν ∂μ := by
by_cases hE : CompleteSpace E; swap; · simp only [integral, dif_neg hE]
revert f
apply Integrable.induction
· intro c s hs h2s
simp_rw [integral_indicator hs, ← indicator_comp_right, Function.comp,
integral_indicator (measurable_prod_mk_left hs), setIntegral_const, integral_smul_const,
integral_toReal (measurable_measure_prod_mk_left hs).aemeasurable
(ae_measure_lt_top hs h2s.ne)]
-- Porting note: was `simp_rw`
rw [prod_apply hs]
· rintro f g - i_f i_g hf hg
simp_rw [integral_add' i_f i_g, integral_integral_add' i_f i_g, hf, hg]
· exact isClosed_eq continuous_integral continuous_integral_integral
· rintro f g hfg - hf; convert hf using 1
· exact integral_congr_ae hfg.symm
· apply integral_congr_ae
filter_upwards [ae_ae_of_ae_prod hfg] with x hfgx using integral_congr_ae (ae_eq_symm hfgx)
#align measure_theory.integral_prod MeasureTheory.integral_prod
/-- Symmetric version of **Fubini's Theorem**: For integrable functions on `α × β`,
the Bochner integral of `f` is equal to the iterated Bochner integral.
This version has the integrals on the right-hand side in the other order. -/
theorem integral_prod_symm (f : α × β → E) (hf : Integrable f (μ.prod ν)) :
∫ z, f z ∂μ.prod ν = ∫ y, ∫ x, f (x, y) ∂μ ∂ν := by
rw [← integral_prod_swap f]; exact integral_prod _ hf.swap
#align measure_theory.integral_prod_symm MeasureTheory.integral_prod_symm
/-- Reversed version of **Fubini's Theorem**. -/
theorem integral_integral {f : α → β → E} (hf : Integrable (uncurry f) (μ.prod ν)) :
∫ x, ∫ y, f x y ∂ν ∂μ = ∫ z, f z.1 z.2 ∂μ.prod ν :=
(integral_prod _ hf).symm
#align measure_theory.integral_integral MeasureTheory.integral_integral
/-- Reversed version of **Fubini's Theorem** (symmetric version). -/
theorem integral_integral_symm {f : α → β → E} (hf : Integrable (uncurry f) (μ.prod ν)) :
∫ x, ∫ y, f x y ∂ν ∂μ = ∫ z, f z.2 z.1 ∂ν.prod μ :=
(integral_prod_symm _ hf.swap).symm
#align measure_theory.integral_integral_symm MeasureTheory.integral_integral_symm
/-- Change the order of Bochner integration. -/
theorem integral_integral_swap ⦃f : α → β → E⦄ (hf : Integrable (uncurry f) (μ.prod ν)) :
∫ x, ∫ y, f x y ∂ν ∂μ = ∫ y, ∫ x, f x y ∂μ ∂ν :=
(integral_integral hf).trans (integral_prod_symm _ hf)
#align measure_theory.integral_integral_swap MeasureTheory.integral_integral_swap
/-- **Fubini's Theorem** for set integrals. -/
| Mathlib/MeasureTheory/Constructions/Prod/Integral.lean | 502 | 506 | theorem setIntegral_prod (f : α × β → E) {s : Set α} {t : Set β}
(hf : IntegrableOn f (s ×ˢ t) (μ.prod ν)) :
∫ z in s ×ˢ t, f z ∂μ.prod ν = ∫ x in s, ∫ y in t, f (x, y) ∂ν ∂μ := by |
simp only [← Measure.prod_restrict s t, IntegrableOn] at hf ⊢
exact integral_prod f hf
|
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Mario Carneiro, Yaël Dillies
-/
import Mathlib.Algebra.CharZero.Defs
import Mathlib.Algebra.Group.Pi.Basic
import Mathlib.Algebra.Group.Units
import Mathlib.Algebra.GroupWithZero.NeZero
import Mathlib.Algebra.Order.Group.Defs
import Mathlib.Algebra.Order.GroupWithZero.Unbundled
import Mathlib.Algebra.Order.Monoid.Canonical.Defs
import Mathlib.Algebra.Order.Monoid.NatCast
import Mathlib.Algebra.Order.Monoid.Unbundled.MinMax
import Mathlib.Algebra.Ring.Defs
import Mathlib.Tactic.Tauto
#align_import algebra.order.ring.char_zero from "leanprover-community/mathlib"@"655994e298904d7e5bbd1e18c95defd7b543eb94"
#align_import algebra.order.ring.defs from "leanprover-community/mathlib"@"44e29dbcff83ba7114a464d592b8c3743987c1e5"
/-!
# Ordered rings and semirings
This file develops the basics of ordered (semi)rings.
Each typeclass here comprises
* an algebraic class (`Semiring`, `CommSemiring`, `Ring`, `CommRing`)
* an order class (`PartialOrder`, `LinearOrder`)
* assumptions on how both interact ((strict) monotonicity, canonicity)
For short,
* "`+` respects `≤`" means "monotonicity of addition"
* "`+` respects `<`" means "strict monotonicity of addition"
* "`*` respects `≤`" means "monotonicity of multiplication by a nonnegative number".
* "`*` respects `<`" means "strict monotonicity of multiplication by a positive number".
## Typeclasses
* `OrderedSemiring`: Semiring with a partial order such that `+` and `*` respect `≤`.
* `StrictOrderedSemiring`: Nontrivial semiring with a partial order such that `+` and `*` respects
`<`.
* `OrderedCommSemiring`: Commutative semiring with a partial order such that `+` and `*` respect
`≤`.
* `StrictOrderedCommSemiring`: Nontrivial commutative semiring with a partial order such that `+`
and `*` respect `<`.
* `OrderedRing`: Ring with a partial order such that `+` respects `≤` and `*` respects `<`.
* `OrderedCommRing`: Commutative ring with a partial order such that `+` respects `≤` and
`*` respects `<`.
* `LinearOrderedSemiring`: Nontrivial semiring with a linear order such that `+` respects `≤` and
`*` respects `<`.
* `LinearOrderedCommSemiring`: Nontrivial commutative semiring with a linear order such that `+`
respects `≤` and `*` respects `<`.
* `LinearOrderedRing`: Nontrivial ring with a linear order such that `+` respects `≤` and `*`
respects `<`.
* `LinearOrderedCommRing`: Nontrivial commutative ring with a linear order such that `+` respects
`≤` and `*` respects `<`.
* `CanonicallyOrderedCommSemiring`: Commutative semiring with a partial order such that `+`
respects `≤`, `*` respects `<`, and `a ≤ b ↔ ∃ c, b = a + c`.
## Hierarchy
The hardest part of proving order lemmas might be to figure out the correct generality and its
corresponding typeclass. Here's an attempt at demystifying it. For each typeclass, we list its
immediate predecessors and what conditions are added to each of them.
* `OrderedSemiring`
- `OrderedAddCommMonoid` & multiplication & `*` respects `≤`
- `Semiring` & partial order structure & `+` respects `≤` & `*` respects `≤`
* `StrictOrderedSemiring`
- `OrderedCancelAddCommMonoid` & multiplication & `*` respects `<` & nontriviality
- `OrderedSemiring` & `+` respects `<` & `*` respects `<` & nontriviality
* `OrderedCommSemiring`
- `OrderedSemiring` & commutativity of multiplication
- `CommSemiring` & partial order structure & `+` respects `≤` & `*` respects `<`
* `StrictOrderedCommSemiring`
- `StrictOrderedSemiring` & commutativity of multiplication
- `OrderedCommSemiring` & `+` respects `<` & `*` respects `<` & nontriviality
* `OrderedRing`
- `OrderedSemiring` & additive inverses
- `OrderedAddCommGroup` & multiplication & `*` respects `<`
- `Ring` & partial order structure & `+` respects `≤` & `*` respects `<`
* `StrictOrderedRing`
- `StrictOrderedSemiring` & additive inverses
- `OrderedSemiring` & `+` respects `<` & `*` respects `<` & nontriviality
* `OrderedCommRing`
- `OrderedRing` & commutativity of multiplication
- `OrderedCommSemiring` & additive inverses
- `CommRing` & partial order structure & `+` respects `≤` & `*` respects `<`
* `StrictOrderedCommRing`
- `StrictOrderedCommSemiring` & additive inverses
- `StrictOrderedRing` & commutativity of multiplication
- `OrderedCommRing` & `+` respects `<` & `*` respects `<` & nontriviality
* `LinearOrderedSemiring`
- `StrictOrderedSemiring` & totality of the order
- `LinearOrderedAddCommMonoid` & multiplication & nontriviality & `*` respects `<`
* `LinearOrderedCommSemiring`
- `StrictOrderedCommSemiring` & totality of the order
- `LinearOrderedSemiring` & commutativity of multiplication
* `LinearOrderedRing`
- `StrictOrderedRing` & totality of the order
- `LinearOrderedSemiring` & additive inverses
- `LinearOrderedAddCommGroup` & multiplication & `*` respects `<`
- `Ring` & `IsDomain` & linear order structure
* `LinearOrderedCommRing`
- `StrictOrderedCommRing` & totality of the order
- `LinearOrderedRing` & commutativity of multiplication
- `LinearOrderedCommSemiring` & additive inverses
- `CommRing` & `IsDomain` & linear order structure
-/
open Function
universe u
variable {α : Type u} {β : Type*}
/-! Note that `OrderDual` does not satisfy any of the ordered ring typeclasses due to the
`zero_le_one` field. -/
theorem add_one_le_two_mul [LE α] [Semiring α] [CovariantClass α α (· + ·) (· ≤ ·)] {a : α}
(a1 : 1 ≤ a) : a + 1 ≤ 2 * a :=
calc
a + 1 ≤ a + a := add_le_add_left a1 a
_ = 2 * a := (two_mul _).symm
#align add_one_le_two_mul add_one_le_two_mul
/-- An `OrderedSemiring` is a semiring with a partial order such that addition is monotone and
multiplication by a nonnegative number is monotone. -/
class OrderedSemiring (α : Type u) extends Semiring α, OrderedAddCommMonoid α where
/-- `0 ≤ 1` in any ordered semiring. -/
protected zero_le_one : (0 : α) ≤ 1
/-- In an ordered semiring, we can multiply an inequality `a ≤ b` on the left
by a non-negative element `0 ≤ c` to obtain `c * a ≤ c * b`. -/
protected mul_le_mul_of_nonneg_left : ∀ a b c : α, a ≤ b → 0 ≤ c → c * a ≤ c * b
/-- In an ordered semiring, we can multiply an inequality `a ≤ b` on the right
by a non-negative element `0 ≤ c` to obtain `a * c ≤ b * c`. -/
protected mul_le_mul_of_nonneg_right : ∀ a b c : α, a ≤ b → 0 ≤ c → a * c ≤ b * c
#align ordered_semiring OrderedSemiring
/-- An `OrderedCommSemiring` is a commutative semiring with a partial order such that addition is
monotone and multiplication by a nonnegative number is monotone. -/
class OrderedCommSemiring (α : Type u) extends OrderedSemiring α, CommSemiring α where
mul_le_mul_of_nonneg_right a b c ha hc :=
-- parentheses ensure this generates an `optParam` rather than an `autoParam`
(by simpa only [mul_comm] using mul_le_mul_of_nonneg_left a b c ha hc)
#align ordered_comm_semiring OrderedCommSemiring
/-- An `OrderedRing` is a ring with a partial order such that addition is monotone and
multiplication by a nonnegative number is monotone. -/
class OrderedRing (α : Type u) extends Ring α, OrderedAddCommGroup α where
/-- `0 ≤ 1` in any ordered ring. -/
protected zero_le_one : 0 ≤ (1 : α)
/-- The product of non-negative elements is non-negative. -/
protected mul_nonneg : ∀ a b : α, 0 ≤ a → 0 ≤ b → 0 ≤ a * b
#align ordered_ring OrderedRing
/-- An `OrderedCommRing` is a commutative ring with a partial order such that addition is monotone
and multiplication by a nonnegative number is monotone. -/
class OrderedCommRing (α : Type u) extends OrderedRing α, CommRing α
#align ordered_comm_ring OrderedCommRing
/-- A `StrictOrderedSemiring` is a nontrivial semiring with a partial order such that addition is
strictly monotone and multiplication by a positive number is strictly monotone. -/
class StrictOrderedSemiring (α : Type u) extends Semiring α, OrderedCancelAddCommMonoid α,
Nontrivial α where
/-- In a strict ordered semiring, `0 ≤ 1`. -/
protected zero_le_one : (0 : α) ≤ 1
/-- Left multiplication by a positive element is strictly monotone. -/
protected mul_lt_mul_of_pos_left : ∀ a b c : α, a < b → 0 < c → c * a < c * b
/-- Right multiplication by a positive element is strictly monotone. -/
protected mul_lt_mul_of_pos_right : ∀ a b c : α, a < b → 0 < c → a * c < b * c
#align strict_ordered_semiring StrictOrderedSemiring
/-- A `StrictOrderedCommSemiring` is a commutative semiring with a partial order such that
addition is strictly monotone and multiplication by a positive number is strictly monotone. -/
class StrictOrderedCommSemiring (α : Type u) extends StrictOrderedSemiring α, CommSemiring α
#align strict_ordered_comm_semiring StrictOrderedCommSemiring
/-- A `StrictOrderedRing` is a ring with a partial order such that addition is strictly monotone
and multiplication by a positive number is strictly monotone. -/
class StrictOrderedRing (α : Type u) extends Ring α, OrderedAddCommGroup α, Nontrivial α where
/-- In a strict ordered ring, `0 ≤ 1`. -/
protected zero_le_one : 0 ≤ (1 : α)
/-- The product of two positive elements is positive. -/
protected mul_pos : ∀ a b : α, 0 < a → 0 < b → 0 < a * b
#align strict_ordered_ring StrictOrderedRing
/-- A `StrictOrderedCommRing` is a commutative ring with a partial order such that addition is
strictly monotone and multiplication by a positive number is strictly monotone. -/
class StrictOrderedCommRing (α : Type*) extends StrictOrderedRing α, CommRing α
#align strict_ordered_comm_ring StrictOrderedCommRing
/- It's not entirely clear we should assume `Nontrivial` at this point; it would be reasonable to
explore changing this, but be warned that the instances involving `Domain` may cause typeclass
search loops. -/
/-- A `LinearOrderedSemiring` is a nontrivial semiring with a linear order such that
addition is monotone and multiplication by a positive number is strictly monotone. -/
class LinearOrderedSemiring (α : Type u) extends StrictOrderedSemiring α,
LinearOrderedAddCommMonoid α
#align linear_ordered_semiring LinearOrderedSemiring
/-- A `LinearOrderedCommSemiring` is a nontrivial commutative semiring with a linear order such
that addition is monotone and multiplication by a positive number is strictly monotone. -/
class LinearOrderedCommSemiring (α : Type*) extends StrictOrderedCommSemiring α,
LinearOrderedSemiring α
#align linear_ordered_comm_semiring LinearOrderedCommSemiring
/-- A `LinearOrderedRing` is a ring with a linear order such that addition is monotone and
multiplication by a positive number is strictly monotone. -/
class LinearOrderedRing (α : Type u) extends StrictOrderedRing α, LinearOrder α
#align linear_ordered_ring LinearOrderedRing
/-- A `LinearOrderedCommRing` is a commutative ring with a linear order such that addition is
monotone and multiplication by a positive number is strictly monotone. -/
class LinearOrderedCommRing (α : Type u) extends LinearOrderedRing α, CommMonoid α
#align linear_ordered_comm_ring LinearOrderedCommRing
section OrderedSemiring
variable [OrderedSemiring α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 100) OrderedSemiring.zeroLEOneClass : ZeroLEOneClass α :=
{ ‹OrderedSemiring α› with }
#align ordered_semiring.zero_le_one_class OrderedSemiring.zeroLEOneClass
-- see Note [lower instance priority]
instance (priority := 200) OrderedSemiring.toPosMulMono : PosMulMono α :=
⟨fun x _ _ h => OrderedSemiring.mul_le_mul_of_nonneg_left _ _ _ h x.2⟩
#align ordered_semiring.to_pos_mul_mono OrderedSemiring.toPosMulMono
-- see Note [lower instance priority]
instance (priority := 200) OrderedSemiring.toMulPosMono : MulPosMono α :=
⟨fun x _ _ h => OrderedSemiring.mul_le_mul_of_nonneg_right _ _ _ h x.2⟩
#align ordered_semiring.to_mul_pos_mono OrderedSemiring.toMulPosMono
set_option linter.deprecated false in
theorem bit1_mono : Monotone (bit1 : α → α) := fun _ _ h => add_le_add_right (bit0_mono h) _
#align bit1_mono bit1_mono
@[simp]
theorem pow_nonneg (H : 0 ≤ a) : ∀ n : ℕ, 0 ≤ a ^ n
| 0 => by
rw [pow_zero]
exact zero_le_one
| n + 1 => by
rw [pow_succ]
exact mul_nonneg (pow_nonneg H _) H
#align pow_nonneg pow_nonneg
lemma pow_le_pow_of_le_one (ha₀ : 0 ≤ a) (ha₁ : a ≤ 1) : ∀ {m n : ℕ}, m ≤ n → a ^ n ≤ a ^ m
| _, _, Nat.le.refl => le_rfl
| _, _, Nat.le.step h => by
rw [pow_succ']
exact (mul_le_of_le_one_left (pow_nonneg ha₀ _) ha₁).trans $ pow_le_pow_of_le_one ha₀ ha₁ h
#align pow_le_pow_of_le_one pow_le_pow_of_le_one
lemma pow_le_of_le_one (h₀ : 0 ≤ a) (h₁ : a ≤ 1) {n : ℕ} (hn : n ≠ 0) : a ^ n ≤ a :=
(pow_one a).subst (pow_le_pow_of_le_one h₀ h₁ (Nat.pos_of_ne_zero hn))
#align pow_le_of_le_one pow_le_of_le_one
lemma sq_le (h₀ : 0 ≤ a) (h₁ : a ≤ 1) : a ^ 2 ≤ a := pow_le_of_le_one h₀ h₁ two_ne_zero
#align sq_le sq_le
-- Porting note: it's unfortunate we need to write `(@one_le_two α)` here.
theorem add_le_mul_two_add (a2 : 2 ≤ a) (b0 : 0 ≤ b) : a + (2 + b) ≤ a * (2 + b) :=
calc
a + (2 + b) ≤ a + (a + a * b) :=
add_le_add_left (add_le_add a2 <| le_mul_of_one_le_left b0 <| (@one_le_two α).trans a2) a
_ ≤ a * (2 + b) := by rw [mul_add, mul_two, add_assoc]
#align add_le_mul_two_add add_le_mul_two_add
theorem one_le_mul_of_one_le_of_one_le (ha : 1 ≤ a) (hb : 1 ≤ b) : (1 : α) ≤ a * b :=
Left.one_le_mul_of_le_of_le ha hb <| zero_le_one.trans ha
#align one_le_mul_of_one_le_of_one_le one_le_mul_of_one_le_of_one_le
section Monotone
variable [Preorder β] {f g : β → α}
theorem monotone_mul_left_of_nonneg (ha : 0 ≤ a) : Monotone fun x => a * x := fun _ _ h =>
mul_le_mul_of_nonneg_left h ha
#align monotone_mul_left_of_nonneg monotone_mul_left_of_nonneg
theorem monotone_mul_right_of_nonneg (ha : 0 ≤ a) : Monotone fun x => x * a := fun _ _ h =>
mul_le_mul_of_nonneg_right h ha
#align monotone_mul_right_of_nonneg monotone_mul_right_of_nonneg
theorem Monotone.mul_const (hf : Monotone f) (ha : 0 ≤ a) : Monotone fun x => f x * a :=
(monotone_mul_right_of_nonneg ha).comp hf
#align monotone.mul_const Monotone.mul_const
theorem Monotone.const_mul (hf : Monotone f) (ha : 0 ≤ a) : Monotone fun x => a * f x :=
(monotone_mul_left_of_nonneg ha).comp hf
#align monotone.const_mul Monotone.const_mul
theorem Antitone.mul_const (hf : Antitone f) (ha : 0 ≤ a) : Antitone fun x => f x * a :=
(monotone_mul_right_of_nonneg ha).comp_antitone hf
#align antitone.mul_const Antitone.mul_const
theorem Antitone.const_mul (hf : Antitone f) (ha : 0 ≤ a) : Antitone fun x => a * f x :=
(monotone_mul_left_of_nonneg ha).comp_antitone hf
#align antitone.const_mul Antitone.const_mul
theorem Monotone.mul (hf : Monotone f) (hg : Monotone g) (hf₀ : ∀ x, 0 ≤ f x) (hg₀ : ∀ x, 0 ≤ g x) :
Monotone (f * g) := fun _ _ h => mul_le_mul (hf h) (hg h) (hg₀ _) (hf₀ _)
#align monotone.mul Monotone.mul
end Monotone
section
set_option linter.deprecated false
theorem bit1_pos [Nontrivial α] (h : 0 ≤ a) : 0 < bit1 a :=
zero_lt_one.trans_le <| bit1_zero.symm.trans_le <| bit1_mono h
#align bit1_pos bit1_pos
theorem bit1_pos' (h : 0 < a) : 0 < bit1 a := by
nontriviality
exact bit1_pos h.le
#align bit1_pos' bit1_pos'
end
theorem mul_le_one (ha : a ≤ 1) (hb' : 0 ≤ b) (hb : b ≤ 1) : a * b ≤ 1 :=
one_mul (1 : α) ▸ mul_le_mul ha hb hb' zero_le_one
#align mul_le_one mul_le_one
theorem one_lt_mul_of_le_of_lt (ha : 1 ≤ a) (hb : 1 < b) : 1 < a * b :=
hb.trans_le <| le_mul_of_one_le_left (zero_le_one.trans hb.le) ha
#align one_lt_mul_of_le_of_lt one_lt_mul_of_le_of_lt
theorem one_lt_mul_of_lt_of_le (ha : 1 < a) (hb : 1 ≤ b) : 1 < a * b :=
ha.trans_le <| le_mul_of_one_le_right (zero_le_one.trans ha.le) hb
#align one_lt_mul_of_lt_of_le one_lt_mul_of_lt_of_le
alias one_lt_mul := one_lt_mul_of_le_of_lt
#align one_lt_mul one_lt_mul
theorem mul_lt_one_of_nonneg_of_lt_one_left (ha₀ : 0 ≤ a) (ha : a < 1) (hb : b ≤ 1) : a * b < 1 :=
(mul_le_of_le_one_right ha₀ hb).trans_lt ha
#align mul_lt_one_of_nonneg_of_lt_one_left mul_lt_one_of_nonneg_of_lt_one_left
theorem mul_lt_one_of_nonneg_of_lt_one_right (ha : a ≤ 1) (hb₀ : 0 ≤ b) (hb : b < 1) : a * b < 1 :=
(mul_le_of_le_one_left hb₀ ha).trans_lt hb
#align mul_lt_one_of_nonneg_of_lt_one_right mul_lt_one_of_nonneg_of_lt_one_right
variable [ExistsAddOfLE α] [ContravariantClass α α (swap (· + ·)) (· ≤ ·)]
theorem mul_le_mul_of_nonpos_left (h : b ≤ a) (hc : c ≤ 0) : c * a ≤ c * b := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc
refine le_of_add_le_add_right (a := d * b + d * a) ?_
calc
_ = d * b := by rw [add_left_comm, ← add_mul, ← hcd, zero_mul, add_zero]
_ ≤ d * a := mul_le_mul_of_nonneg_left h <| hcd.trans_le <| add_le_of_nonpos_left hc
_ = _ := by rw [← add_assoc, ← add_mul, ← hcd, zero_mul, zero_add]
#align mul_le_mul_of_nonpos_left mul_le_mul_of_nonpos_left
theorem mul_le_mul_of_nonpos_right (h : b ≤ a) (hc : c ≤ 0) : a * c ≤ b * c := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc
refine le_of_add_le_add_right (a := b * d + a * d) ?_
calc
_ = b * d := by rw [add_left_comm, ← mul_add, ← hcd, mul_zero, add_zero]
_ ≤ a * d := mul_le_mul_of_nonneg_right h <| hcd.trans_le <| add_le_of_nonpos_left hc
_ = _ := by rw [← add_assoc, ← mul_add, ← hcd, mul_zero, zero_add]
#align mul_le_mul_of_nonpos_right mul_le_mul_of_nonpos_right
theorem mul_nonneg_of_nonpos_of_nonpos (ha : a ≤ 0) (hb : b ≤ 0) : 0 ≤ a * b := by
simpa only [zero_mul] using mul_le_mul_of_nonpos_right ha hb
#align mul_nonneg_of_nonpos_of_nonpos mul_nonneg_of_nonpos_of_nonpos
theorem mul_le_mul_of_nonneg_of_nonpos (hca : c ≤ a) (hbd : b ≤ d) (hc : 0 ≤ c) (hb : b ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonpos_right hca hb).trans <| mul_le_mul_of_nonneg_left hbd hc
#align mul_le_mul_of_nonneg_of_nonpos mul_le_mul_of_nonneg_of_nonpos
theorem mul_le_mul_of_nonneg_of_nonpos' (hca : c ≤ a) (hbd : b ≤ d) (ha : 0 ≤ a) (hd : d ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonneg_left hbd ha).trans <| mul_le_mul_of_nonpos_right hca hd
#align mul_le_mul_of_nonneg_of_nonpos' mul_le_mul_of_nonneg_of_nonpos'
theorem mul_le_mul_of_nonpos_of_nonneg (hac : a ≤ c) (hdb : d ≤ b) (hc : c ≤ 0) (hb : 0 ≤ b) :
a * b ≤ c * d :=
(mul_le_mul_of_nonneg_right hac hb).trans <| mul_le_mul_of_nonpos_left hdb hc
#align mul_le_mul_of_nonpos_of_nonneg mul_le_mul_of_nonpos_of_nonneg
theorem mul_le_mul_of_nonpos_of_nonneg' (hca : c ≤ a) (hbd : b ≤ d) (ha : 0 ≤ a) (hd : d ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonneg_left hbd ha).trans <| mul_le_mul_of_nonpos_right hca hd
#align mul_le_mul_of_nonpos_of_nonneg' mul_le_mul_of_nonpos_of_nonneg'
theorem mul_le_mul_of_nonpos_of_nonpos (hca : c ≤ a) (hdb : d ≤ b) (hc : c ≤ 0) (hb : b ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonpos_right hca hb).trans <| mul_le_mul_of_nonpos_left hdb hc
#align mul_le_mul_of_nonpos_of_nonpos mul_le_mul_of_nonpos_of_nonpos
theorem mul_le_mul_of_nonpos_of_nonpos' (hca : c ≤ a) (hdb : d ≤ b) (ha : a ≤ 0) (hd : d ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonpos_left hdb ha).trans <| mul_le_mul_of_nonpos_right hca hd
#align mul_le_mul_of_nonpos_of_nonpos' mul_le_mul_of_nonpos_of_nonpos'
/-- Variant of `mul_le_of_le_one_left` for `b` non-positive instead of non-negative. -/
theorem le_mul_of_le_one_left (hb : b ≤ 0) (h : a ≤ 1) : b ≤ a * b := by
simpa only [one_mul] using mul_le_mul_of_nonpos_right h hb
#align le_mul_of_le_one_left le_mul_of_le_one_left
/-- Variant of `le_mul_of_one_le_left` for `b` non-positive instead of non-negative. -/
theorem mul_le_of_one_le_left (hb : b ≤ 0) (h : 1 ≤ a) : a * b ≤ b := by
simpa only [one_mul] using mul_le_mul_of_nonpos_right h hb
#align mul_le_of_one_le_left mul_le_of_one_le_left
/-- Variant of `mul_le_of_le_one_right` for `a` non-positive instead of non-negative. -/
theorem le_mul_of_le_one_right (ha : a ≤ 0) (h : b ≤ 1) : a ≤ a * b := by
simpa only [mul_one] using mul_le_mul_of_nonpos_left h ha
#align le_mul_of_le_one_right le_mul_of_le_one_right
/-- Variant of `le_mul_of_one_le_right` for `a` non-positive instead of non-negative. -/
theorem mul_le_of_one_le_right (ha : a ≤ 0) (h : 1 ≤ b) : a * b ≤ a := by
simpa only [mul_one] using mul_le_mul_of_nonpos_left h ha
#align mul_le_of_one_le_right mul_le_of_one_le_right
section Monotone
variable [Preorder β] {f g : β → α}
theorem antitone_mul_left {a : α} (ha : a ≤ 0) : Antitone (a * ·) := fun _ _ b_le_c =>
mul_le_mul_of_nonpos_left b_le_c ha
#align antitone_mul_left antitone_mul_left
theorem antitone_mul_right {a : α} (ha : a ≤ 0) : Antitone fun x => x * a := fun _ _ b_le_c =>
mul_le_mul_of_nonpos_right b_le_c ha
#align antitone_mul_right antitone_mul_right
theorem Monotone.const_mul_of_nonpos (hf : Monotone f) (ha : a ≤ 0) : Antitone fun x => a * f x :=
(antitone_mul_left ha).comp_monotone hf
#align monotone.const_mul_of_nonpos Monotone.const_mul_of_nonpos
theorem Monotone.mul_const_of_nonpos (hf : Monotone f) (ha : a ≤ 0) : Antitone fun x => f x * a :=
(antitone_mul_right ha).comp_monotone hf
#align monotone.mul_const_of_nonpos Monotone.mul_const_of_nonpos
theorem Antitone.const_mul_of_nonpos (hf : Antitone f) (ha : a ≤ 0) : Monotone fun x => a * f x :=
(antitone_mul_left ha).comp hf
#align antitone.const_mul_of_nonpos Antitone.const_mul_of_nonpos
theorem Antitone.mul_const_of_nonpos (hf : Antitone f) (ha : a ≤ 0) : Monotone fun x => f x * a :=
(antitone_mul_right ha).comp hf
#align antitone.mul_const_of_nonpos Antitone.mul_const_of_nonpos
theorem Antitone.mul_monotone (hf : Antitone f) (hg : Monotone g) (hf₀ : ∀ x, f x ≤ 0)
(hg₀ : ∀ x, 0 ≤ g x) : Antitone (f * g) := fun _ _ h =>
mul_le_mul_of_nonpos_of_nonneg (hf h) (hg h) (hf₀ _) (hg₀ _)
#align antitone.mul_monotone Antitone.mul_monotone
theorem Monotone.mul_antitone (hf : Monotone f) (hg : Antitone g) (hf₀ : ∀ x, 0 ≤ f x)
(hg₀ : ∀ x, g x ≤ 0) : Antitone (f * g) := fun _ _ h =>
mul_le_mul_of_nonneg_of_nonpos (hf h) (hg h) (hf₀ _) (hg₀ _)
#align monotone.mul_antitone Monotone.mul_antitone
theorem Antitone.mul (hf : Antitone f) (hg : Antitone g) (hf₀ : ∀ x, f x ≤ 0) (hg₀ : ∀ x, g x ≤ 0) :
Monotone (f * g) := fun _ _ h => mul_le_mul_of_nonpos_of_nonpos (hf h) (hg h) (hf₀ _) (hg₀ _)
#align antitone.mul Antitone.mul
end Monotone
variable [ContravariantClass α α (· + ·) (· ≤ ·)]
lemma le_iff_exists_nonneg_add (a b : α) : a ≤ b ↔ ∃ c ≥ 0, b = a + c := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨c, rfl⟩ := exists_add_of_le h
exact ⟨c, nonneg_of_le_add_right h, rfl⟩
· rintro ⟨c, hc, rfl⟩
exact le_add_of_nonneg_right hc
#align le_iff_exists_nonneg_add le_iff_exists_nonneg_add
end OrderedSemiring
section OrderedRing
variable [OrderedRing α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 100) OrderedRing.toOrderedSemiring : OrderedSemiring α :=
{ ‹OrderedRing α›, (Ring.toSemiring : Semiring α) with
mul_le_mul_of_nonneg_left := fun a b c h hc => by
simpa only [mul_sub, sub_nonneg] using OrderedRing.mul_nonneg _ _ hc (sub_nonneg.2 h),
mul_le_mul_of_nonneg_right := fun a b c h hc => by
simpa only [sub_mul, sub_nonneg] using OrderedRing.mul_nonneg _ _ (sub_nonneg.2 h) hc }
#align ordered_ring.to_ordered_semiring OrderedRing.toOrderedSemiring
end OrderedRing
section OrderedCommRing
variable [OrderedCommRing α]
-- See note [lower instance priority]
instance (priority := 100) OrderedCommRing.toOrderedCommSemiring : OrderedCommSemiring α :=
{ OrderedRing.toOrderedSemiring, ‹OrderedCommRing α› with }
#align ordered_comm_ring.to_ordered_comm_semiring OrderedCommRing.toOrderedCommSemiring
end OrderedCommRing
section StrictOrderedSemiring
variable [StrictOrderedSemiring α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 200) StrictOrderedSemiring.toPosMulStrictMono : PosMulStrictMono α :=
⟨fun x _ _ h => StrictOrderedSemiring.mul_lt_mul_of_pos_left _ _ _ h x.prop⟩
#align strict_ordered_semiring.to_pos_mul_strict_mono StrictOrderedSemiring.toPosMulStrictMono
-- see Note [lower instance priority]
instance (priority := 200) StrictOrderedSemiring.toMulPosStrictMono : MulPosStrictMono α :=
⟨fun x _ _ h => StrictOrderedSemiring.mul_lt_mul_of_pos_right _ _ _ h x.prop⟩
#align strict_ordered_semiring.to_mul_pos_strict_mono StrictOrderedSemiring.toMulPosStrictMono
-- See note [reducible non-instances]
/-- A choice-free version of `StrictOrderedSemiring.toOrderedSemiring` to avoid using choice in
basic `Nat` lemmas. -/
abbrev StrictOrderedSemiring.toOrderedSemiring' [@DecidableRel α (· ≤ ·)] : OrderedSemiring α :=
{ ‹StrictOrderedSemiring α› with
mul_le_mul_of_nonneg_left := fun a b c hab hc => by
obtain rfl | hab := Decidable.eq_or_lt_of_le hab
· rfl
obtain rfl | hc := Decidable.eq_or_lt_of_le hc
· simp
· exact (mul_lt_mul_of_pos_left hab hc).le,
mul_le_mul_of_nonneg_right := fun a b c hab hc => by
obtain rfl | hab := Decidable.eq_or_lt_of_le hab
· rfl
obtain rfl | hc := Decidable.eq_or_lt_of_le hc
· simp
· exact (mul_lt_mul_of_pos_right hab hc).le }
#align strict_ordered_semiring.to_ordered_semiring' StrictOrderedSemiring.toOrderedSemiring'
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedSemiring.toOrderedSemiring : OrderedSemiring α :=
{ ‹StrictOrderedSemiring α› with
mul_le_mul_of_nonneg_left := fun _ _ _ =>
letI := @StrictOrderedSemiring.toOrderedSemiring' α _ (Classical.decRel _)
mul_le_mul_of_nonneg_left,
mul_le_mul_of_nonneg_right := fun _ _ _ =>
letI := @StrictOrderedSemiring.toOrderedSemiring' α _ (Classical.decRel _)
mul_le_mul_of_nonneg_right }
#align strict_ordered_semiring.to_ordered_semiring StrictOrderedSemiring.toOrderedSemiring
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedSemiring.toCharZero [StrictOrderedSemiring α] :
CharZero α where
cast_injective :=
(strictMono_nat_of_lt_succ fun n ↦ by rw [Nat.cast_succ]; apply lt_add_one).injective
#align strict_ordered_semiring.to_char_zero StrictOrderedSemiring.toCharZero
theorem mul_lt_mul (hac : a < c) (hbd : b ≤ d) (hb : 0 < b) (hc : 0 ≤ c) : a * b < c * d :=
(mul_lt_mul_of_pos_right hac hb).trans_le <| mul_le_mul_of_nonneg_left hbd hc
#align mul_lt_mul mul_lt_mul
theorem mul_lt_mul' (hac : a ≤ c) (hbd : b < d) (hb : 0 ≤ b) (hc : 0 < c) : a * b < c * d :=
(mul_le_mul_of_nonneg_right hac hb).trans_lt <| mul_lt_mul_of_pos_left hbd hc
#align mul_lt_mul' mul_lt_mul'
@[simp]
theorem pow_pos (H : 0 < a) : ∀ n : ℕ, 0 < a ^ n
| 0 => by
nontriviality
rw [pow_zero]
exact zero_lt_one
| n + 1 => by
rw [pow_succ]
exact mul_pos (pow_pos H _) H
#align pow_pos pow_pos
theorem mul_self_lt_mul_self (h1 : 0 ≤ a) (h2 : a < b) : a * a < b * b :=
mul_lt_mul' h2.le h2 h1 <| h1.trans_lt h2
#align mul_self_lt_mul_self mul_self_lt_mul_self
-- In the next lemma, we used to write `Set.Ici 0` instead of `{x | 0 ≤ x}`.
-- As this lemma is not used outside this file,
-- and the import for `Set.Ici` is not otherwise needed until later,
-- we choose not to use it here.
theorem strictMonoOn_mul_self : StrictMonoOn (fun x : α => x * x) { x | 0 ≤ x } :=
fun _ hx _ _ hxy => mul_self_lt_mul_self hx hxy
#align strict_mono_on_mul_self strictMonoOn_mul_self
-- See Note [decidable namespace]
protected theorem Decidable.mul_lt_mul'' [@DecidableRel α (· ≤ ·)] (h1 : a < c) (h2 : b < d)
(h3 : 0 ≤ a) (h4 : 0 ≤ b) : a * b < c * d :=
h4.lt_or_eq_dec.elim (fun b0 => mul_lt_mul h1 h2.le b0 <| h3.trans h1.le) fun b0 => by
rw [← b0, mul_zero]; exact mul_pos (h3.trans_lt h1) (h4.trans_lt h2)
#align decidable.mul_lt_mul'' Decidable.mul_lt_mul''
@[gcongr]
theorem mul_lt_mul'' : a < c → b < d → 0 ≤ a → 0 ≤ b → a * b < c * d := by classical
exact Decidable.mul_lt_mul''
#align mul_lt_mul'' mul_lt_mul''
theorem lt_mul_left (hn : 0 < a) (hm : 1 < b) : a < b * a := by
convert mul_lt_mul_of_pos_right hm hn
rw [one_mul]
#align lt_mul_left lt_mul_left
theorem lt_mul_right (hn : 0 < a) (hm : 1 < b) : a < a * b := by
convert mul_lt_mul_of_pos_left hm hn
rw [mul_one]
#align lt_mul_right lt_mul_right
theorem lt_mul_self (hn : 1 < a) : a < a * a :=
lt_mul_left (hn.trans_le' zero_le_one) hn
#align lt_mul_self lt_mul_self
section Monotone
variable [Preorder β] {f g : β → α}
theorem strictMono_mul_left_of_pos (ha : 0 < a) : StrictMono fun x => a * x := fun _ _ b_lt_c =>
mul_lt_mul_of_pos_left b_lt_c ha
#align strict_mono_mul_left_of_pos strictMono_mul_left_of_pos
theorem strictMono_mul_right_of_pos (ha : 0 < a) : StrictMono fun x => x * a := fun _ _ b_lt_c =>
mul_lt_mul_of_pos_right b_lt_c ha
#align strict_mono_mul_right_of_pos strictMono_mul_right_of_pos
theorem StrictMono.mul_const (hf : StrictMono f) (ha : 0 < a) : StrictMono fun x => f x * a :=
(strictMono_mul_right_of_pos ha).comp hf
#align strict_mono.mul_const StrictMono.mul_const
theorem StrictMono.const_mul (hf : StrictMono f) (ha : 0 < a) : StrictMono fun x => a * f x :=
(strictMono_mul_left_of_pos ha).comp hf
#align strict_mono.const_mul StrictMono.const_mul
theorem StrictAnti.mul_const (hf : StrictAnti f) (ha : 0 < a) : StrictAnti fun x => f x * a :=
(strictMono_mul_right_of_pos ha).comp_strictAnti hf
#align strict_anti.mul_const StrictAnti.mul_const
theorem StrictAnti.const_mul (hf : StrictAnti f) (ha : 0 < a) : StrictAnti fun x => a * f x :=
(strictMono_mul_left_of_pos ha).comp_strictAnti hf
#align strict_anti.const_mul StrictAnti.const_mul
theorem StrictMono.mul_monotone (hf : StrictMono f) (hg : Monotone g) (hf₀ : ∀ x, 0 ≤ f x)
(hg₀ : ∀ x, 0 < g x) : StrictMono (f * g) := fun _ _ h =>
mul_lt_mul (hf h) (hg h.le) (hg₀ _) (hf₀ _)
#align strict_mono.mul_monotone StrictMono.mul_monotone
theorem Monotone.mul_strictMono (hf : Monotone f) (hg : StrictMono g) (hf₀ : ∀ x, 0 < f x)
(hg₀ : ∀ x, 0 ≤ g x) : StrictMono (f * g) := fun _ _ h =>
mul_lt_mul' (hf h.le) (hg h) (hg₀ _) (hf₀ _)
#align monotone.mul_strict_mono Monotone.mul_strictMono
theorem StrictMono.mul (hf : StrictMono f) (hg : StrictMono g) (hf₀ : ∀ x, 0 ≤ f x)
(hg₀ : ∀ x, 0 ≤ g x) : StrictMono (f * g) := fun _ _ h =>
mul_lt_mul'' (hf h) (hg h) (hf₀ _) (hg₀ _)
#align strict_mono.mul StrictMono.mul
end Monotone
theorem lt_two_mul_self (ha : 0 < a) : a < 2 * a :=
lt_mul_of_one_lt_left ha one_lt_two
#align lt_two_mul_self lt_two_mul_self
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedSemiring.toNoMaxOrder : NoMaxOrder α :=
⟨fun a => ⟨a + 1, lt_add_of_pos_right _ one_pos⟩⟩
#align strict_ordered_semiring.to_no_max_order StrictOrderedSemiring.toNoMaxOrder
variable [ExistsAddOfLE α]
theorem mul_lt_mul_of_neg_left (h : b < a) (hc : c < 0) : c * a < c * b := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc.le
refine (add_lt_add_iff_right (d * b + d * a)).1 ?_
calc
_ = d * b := by rw [add_left_comm, ← add_mul, ← hcd, zero_mul, add_zero]
_ < d * a := mul_lt_mul_of_pos_left h <| hcd.trans_lt <| add_lt_of_neg_left _ hc
_ = _ := by rw [← add_assoc, ← add_mul, ← hcd, zero_mul, zero_add]
#align mul_lt_mul_of_neg_left mul_lt_mul_of_neg_left
| Mathlib/Algebra/Order/Ring/Defs.lean | 678 | 684 | theorem mul_lt_mul_of_neg_right (h : b < a) (hc : c < 0) : a * c < b * c := by |
obtain ⟨d, hcd⟩ := exists_add_of_le hc.le
refine (add_lt_add_iff_right (b * d + a * d)).1 ?_
calc
_ = b * d := by rw [add_left_comm, ← mul_add, ← hcd, mul_zero, add_zero]
_ < a * d := mul_lt_mul_of_pos_right h <| hcd.trans_lt <| add_lt_of_neg_left _ hc
_ = _ := by rw [← add_assoc, ← mul_add, ← hcd, mul_zero, zero_add]
|
/-
Copyright (c) 2022 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.LinearAlgebra.CliffordAlgebra.Conjugation
#align_import linear_algebra.clifford_algebra.star from "leanprover-community/mathlib"@"4d66277cfec381260ba05c68f9ae6ce2a118031d"
/-!
# Star structure on `CliffordAlgebra`
This file defines the "clifford conjugation", equal to `reverse (involute x)`, and assigns it the
`star` notation.
This choice is somewhat non-canonical; a star structure is also possible under `reverse` alone.
However, defining it gives us access to constructions like `unitary`.
Most results about `star` can be obtained by unfolding it via `CliffordAlgebra.star_def`.
## Main definitions
* `CliffordAlgebra.instStarRing`
-/
variable {R : Type*} [CommRing R]
variable {M : Type*} [AddCommGroup M] [Module R M]
variable {Q : QuadraticForm R M}
namespace CliffordAlgebra
instance instStarRing : StarRing (CliffordAlgebra Q) where
star x := reverse (involute x)
star_involutive x := by
simp only [reverse_involute_commute.eq, reverse_reverse, involute_involute]
star_mul x y := by simp only [map_mul, reverse.map_mul]
star_add x y := by simp only [map_add]
theorem star_def (x : CliffordAlgebra Q) : star x = reverse (involute x) :=
rfl
#align clifford_algebra.star_def CliffordAlgebra.star_def
theorem star_def' (x : CliffordAlgebra Q) : star x = involute (reverse x) :=
reverse_involute _
#align clifford_algebra.star_def' CliffordAlgebra.star_def'
@[simp]
theorem star_ι (m : M) : star (ι Q m) = -ι Q m := by rw [star_def, involute_ι, map_neg, reverse_ι]
#align clifford_algebra.star_ι CliffordAlgebra.star_ι
/-- Note that this not match the `star_smul` implied by `StarModule`; it certainly could if we
also conjugated all the scalars, but there appears to be nothing in the literature that advocates
doing this. -/
@[simp]
| Mathlib/LinearAlgebra/CliffordAlgebra/Star.lean | 57 | 58 | theorem star_smul (r : R) (x : CliffordAlgebra Q) : star (r • x) = r • star x := by |
rw [star_def, star_def, map_smul, map_smul]
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.CharP.Two
import Mathlib.Algebra.CharP.Reduced
import Mathlib.Algebra.NeZero
import Mathlib.Algebra.Polynomial.RingDivision
import Mathlib.GroupTheory.SpecificGroups.Cyclic
import Mathlib.NumberTheory.Divisors
import Mathlib.RingTheory.IntegralDomain
import Mathlib.Tactic.Zify
#align_import ring_theory.roots_of_unity.basic from "leanprover-community/mathlib"@"7fdeecc0d03cd40f7a165e6cf00a4d2286db599f"
/-!
# Roots of unity and primitive roots of unity
We define roots of unity in the context of an arbitrary commutative monoid,
as a subgroup of the group of units. We also define a predicate `IsPrimitiveRoot` on commutative
monoids, expressing that an element is a primitive root of unity.
## Main definitions
* `rootsOfUnity n M`, for `n : ℕ+` is the subgroup of the units of a commutative monoid `M`
consisting of elements `x` that satisfy `x ^ n = 1`.
* `IsPrimitiveRoot ζ k`: an element `ζ` is a primitive `k`-th root of unity if `ζ ^ k = 1`,
and if `l` satisfies `ζ ^ l = 1` then `k ∣ l`.
* `primitiveRoots k R`: the finset of primitive `k`-th roots of unity in an integral domain `R`.
* `IsPrimitiveRoot.autToPow`: the monoid hom that takes an automorphism of a ring to the power
it sends that specific primitive root, as a member of `(ZMod n)ˣ`.
## Main results
* `rootsOfUnity.isCyclic`: the roots of unity in an integral domain form a cyclic group.
* `IsPrimitiveRoot.zmodEquivZPowers`: `ZMod k` is equivalent to
the subgroup generated by a primitive `k`-th root of unity.
* `IsPrimitiveRoot.zpowers_eq`: in an integral domain, the subgroup generated by
a primitive `k`-th root of unity is equal to the `k`-th roots of unity.
* `IsPrimitiveRoot.card_primitiveRoots`: if an integral domain
has a primitive `k`-th root of unity, then it has `φ k` of them.
## Implementation details
It is desirable that `rootsOfUnity` is a subgroup,
and it will mainly be applied to rings (e.g. the ring of integers in a number field) and fields.
We therefore implement it as a subgroup of the units of a commutative monoid.
We have chosen to define `rootsOfUnity n` for `n : ℕ+`, instead of `n : ℕ`,
because almost all lemmas need the positivity assumption,
and in particular the type class instances for `Fintype` and `IsCyclic`.
On the other hand, for primitive roots of unity, it is desirable to have a predicate
not just on units, but directly on elements of the ring/field.
For example, we want to say that `exp (2 * pi * I / n)` is a primitive `n`-th root of unity
in the complex numbers, without having to turn that number into a unit first.
This creates a little bit of friction, but lemmas like `IsPrimitiveRoot.isUnit` and
`IsPrimitiveRoot.coe_units_iff` should provide the necessary glue.
-/
open scoped Classical Polynomial
noncomputable section
open Polynomial
open Finset
variable {M N G R S F : Type*}
variable [CommMonoid M] [CommMonoid N] [DivisionCommMonoid G]
section rootsOfUnity
variable {k l : ℕ+}
/-- `rootsOfUnity k M` is the subgroup of elements `m : Mˣ` that satisfy `m ^ k = 1`. -/
def rootsOfUnity (k : ℕ+) (M : Type*) [CommMonoid M] : Subgroup Mˣ where
carrier := {ζ | ζ ^ (k : ℕ) = 1}
one_mem' := one_pow _
mul_mem' _ _ := by simp_all only [Set.mem_setOf_eq, mul_pow, one_mul]
inv_mem' _ := by simp_all only [Set.mem_setOf_eq, inv_pow, inv_one]
#align roots_of_unity rootsOfUnity
@[simp]
theorem mem_rootsOfUnity (k : ℕ+) (ζ : Mˣ) : ζ ∈ rootsOfUnity k M ↔ ζ ^ (k : ℕ) = 1 :=
Iff.rfl
#align mem_roots_of_unity mem_rootsOfUnity
theorem mem_rootsOfUnity' (k : ℕ+) (ζ : Mˣ) : ζ ∈ rootsOfUnity k M ↔ (ζ : M) ^ (k : ℕ) = 1 := by
rw [mem_rootsOfUnity]; norm_cast
#align mem_roots_of_unity' mem_rootsOfUnity'
@[simp]
theorem rootsOfUnity_one (M : Type*) [CommMonoid M] : rootsOfUnity 1 M = ⊥ := by ext; simp
theorem rootsOfUnity.coe_injective {n : ℕ+} :
Function.Injective (fun x : rootsOfUnity n M ↦ x.val.val) :=
Units.ext.comp fun _ _ => Subtype.eq
#align roots_of_unity.coe_injective rootsOfUnity.coe_injective
/-- Make an element of `rootsOfUnity` from a member of the base ring, and a proof that it has
a positive power equal to one. -/
@[simps! coe_val]
def rootsOfUnity.mkOfPowEq (ζ : M) {n : ℕ+} (h : ζ ^ (n : ℕ) = 1) : rootsOfUnity n M :=
⟨Units.ofPowEqOne ζ n h n.ne_zero, Units.pow_ofPowEqOne _ _⟩
#align roots_of_unity.mk_of_pow_eq rootsOfUnity.mkOfPowEq
#align roots_of_unity.mk_of_pow_eq_coe_coe rootsOfUnity.val_mkOfPowEq_coe
@[simp]
theorem rootsOfUnity.coe_mkOfPowEq {ζ : M} {n : ℕ+} (h : ζ ^ (n : ℕ) = 1) :
((rootsOfUnity.mkOfPowEq _ h : Mˣ) : M) = ζ :=
rfl
#align roots_of_unity.coe_mk_of_pow_eq rootsOfUnity.coe_mkOfPowEq
theorem rootsOfUnity_le_of_dvd (h : k ∣ l) : rootsOfUnity k M ≤ rootsOfUnity l M := by
obtain ⟨d, rfl⟩ := h
intro ζ h
simp_all only [mem_rootsOfUnity, PNat.mul_coe, pow_mul, one_pow]
#align roots_of_unity_le_of_dvd rootsOfUnity_le_of_dvd
theorem map_rootsOfUnity (f : Mˣ →* Nˣ) (k : ℕ+) : (rootsOfUnity k M).map f ≤ rootsOfUnity k N := by
rintro _ ⟨ζ, h, rfl⟩
simp_all only [← map_pow, mem_rootsOfUnity, SetLike.mem_coe, MonoidHom.map_one]
#align map_roots_of_unity map_rootsOfUnity
@[norm_cast]
theorem rootsOfUnity.coe_pow [CommMonoid R] (ζ : rootsOfUnity k R) (m : ℕ) :
(((ζ ^ m :) : Rˣ) : R) = ((ζ : Rˣ) : R) ^ m := by
rw [Subgroup.coe_pow, Units.val_pow_eq_pow_val]
#align roots_of_unity.coe_pow rootsOfUnity.coe_pow
section CommMonoid
variable [CommMonoid R] [CommMonoid S] [FunLike F R S]
/-- Restrict a ring homomorphism to the nth roots of unity. -/
def restrictRootsOfUnity [MonoidHomClass F R S] (σ : F) (n : ℕ+) :
rootsOfUnity n R →* rootsOfUnity n S :=
let h : ∀ ξ : rootsOfUnity n R, (σ (ξ : Rˣ)) ^ (n : ℕ) = 1 := fun ξ => by
rw [← map_pow, ← Units.val_pow_eq_pow_val, show (ξ : Rˣ) ^ (n : ℕ) = 1 from ξ.2, Units.val_one,
map_one σ]
{ toFun := fun ξ =>
⟨@unitOfInvertible _ _ _ (invertibleOfPowEqOne _ _ (h ξ) n.ne_zero), by
ext; rw [Units.val_pow_eq_pow_val]; exact h ξ⟩
map_one' := by ext; exact map_one σ
map_mul' := fun ξ₁ ξ₂ => by ext; rw [Subgroup.coe_mul, Units.val_mul]; exact map_mul σ _ _ }
#align restrict_roots_of_unity restrictRootsOfUnity
@[simp]
theorem restrictRootsOfUnity_coe_apply [MonoidHomClass F R S] (σ : F) (ζ : rootsOfUnity k R) :
(restrictRootsOfUnity σ k ζ : Sˣ) = σ (ζ : Rˣ) :=
rfl
#align restrict_roots_of_unity_coe_apply restrictRootsOfUnity_coe_apply
/-- Restrict a monoid isomorphism to the nth roots of unity. -/
nonrec def MulEquiv.restrictRootsOfUnity (σ : R ≃* S) (n : ℕ+) :
rootsOfUnity n R ≃* rootsOfUnity n S where
toFun := restrictRootsOfUnity σ n
invFun := restrictRootsOfUnity σ.symm n
left_inv ξ := by ext; exact σ.symm_apply_apply (ξ : Rˣ)
right_inv ξ := by ext; exact σ.apply_symm_apply (ξ : Sˣ)
map_mul' := (restrictRootsOfUnity _ n).map_mul
#align ring_equiv.restrict_roots_of_unity MulEquiv.restrictRootsOfUnity
@[simp]
theorem MulEquiv.restrictRootsOfUnity_coe_apply (σ : R ≃* S) (ζ : rootsOfUnity k R) :
(σ.restrictRootsOfUnity k ζ : Sˣ) = σ (ζ : Rˣ) :=
rfl
#align ring_equiv.restrict_roots_of_unity_coe_apply MulEquiv.restrictRootsOfUnity_coe_apply
@[simp]
theorem MulEquiv.restrictRootsOfUnity_symm (σ : R ≃* S) :
(σ.restrictRootsOfUnity k).symm = σ.symm.restrictRootsOfUnity k :=
rfl
#align ring_equiv.restrict_roots_of_unity_symm MulEquiv.restrictRootsOfUnity_symm
end CommMonoid
section IsDomain
variable [CommRing R] [IsDomain R]
theorem mem_rootsOfUnity_iff_mem_nthRoots {ζ : Rˣ} :
ζ ∈ rootsOfUnity k R ↔ (ζ : R) ∈ nthRoots k (1 : R) := by
simp only [mem_rootsOfUnity, mem_nthRoots k.pos, Units.ext_iff, Units.val_one,
Units.val_pow_eq_pow_val]
#align mem_roots_of_unity_iff_mem_nth_roots mem_rootsOfUnity_iff_mem_nthRoots
variable (k R)
/-- Equivalence between the `k`-th roots of unity in `R` and the `k`-th roots of `1`.
This is implemented as equivalence of subtypes,
because `rootsOfUnity` is a subgroup of the group of units,
whereas `nthRoots` is a multiset. -/
def rootsOfUnityEquivNthRoots : rootsOfUnity k R ≃ { x // x ∈ nthRoots k (1 : R) } where
toFun x := ⟨(x : Rˣ), mem_rootsOfUnity_iff_mem_nthRoots.mp x.2⟩
invFun x := by
refine ⟨⟨x, ↑x ^ (k - 1 : ℕ), ?_, ?_⟩, ?_⟩
all_goals
rcases x with ⟨x, hx⟩; rw [mem_nthRoots k.pos] at hx
simp only [Subtype.coe_mk, ← pow_succ, ← pow_succ', hx,
tsub_add_cancel_of_le (show 1 ≤ (k : ℕ) from k.one_le)]
show (_ : Rˣ) ^ (k : ℕ) = 1
simp only [Units.ext_iff, hx, Units.val_mk, Units.val_one, Subtype.coe_mk,
Units.val_pow_eq_pow_val]
left_inv := by rintro ⟨x, hx⟩; ext; rfl
right_inv := by rintro ⟨x, hx⟩; ext; rfl
#align roots_of_unity_equiv_nth_roots rootsOfUnityEquivNthRoots
variable {k R}
@[simp]
theorem rootsOfUnityEquivNthRoots_apply (x : rootsOfUnity k R) :
(rootsOfUnityEquivNthRoots R k x : R) = ((x : Rˣ) : R) :=
rfl
#align roots_of_unity_equiv_nth_roots_apply rootsOfUnityEquivNthRoots_apply
@[simp]
theorem rootsOfUnityEquivNthRoots_symm_apply (x : { x // x ∈ nthRoots k (1 : R) }) :
(((rootsOfUnityEquivNthRoots R k).symm x : Rˣ) : R) = (x : R) :=
rfl
#align roots_of_unity_equiv_nth_roots_symm_apply rootsOfUnityEquivNthRoots_symm_apply
variable (k R)
instance rootsOfUnity.fintype : Fintype (rootsOfUnity k R) :=
Fintype.ofEquiv { x // x ∈ nthRoots k (1 : R) } <| (rootsOfUnityEquivNthRoots R k).symm
#align roots_of_unity.fintype rootsOfUnity.fintype
instance rootsOfUnity.isCyclic : IsCyclic (rootsOfUnity k R) :=
isCyclic_of_subgroup_isDomain ((Units.coeHom R).comp (rootsOfUnity k R).subtype)
(Units.ext.comp Subtype.val_injective)
#align roots_of_unity.is_cyclic rootsOfUnity.isCyclic
theorem card_rootsOfUnity : Fintype.card (rootsOfUnity k R) ≤ k :=
calc
Fintype.card (rootsOfUnity k R) = Fintype.card { x // x ∈ nthRoots k (1 : R) } :=
Fintype.card_congr (rootsOfUnityEquivNthRoots R k)
_ ≤ Multiset.card (nthRoots k (1 : R)).attach := Multiset.card_le_card (Multiset.dedup_le _)
_ = Multiset.card (nthRoots k (1 : R)) := Multiset.card_attach
_ ≤ k := card_nthRoots k 1
#align card_roots_of_unity card_rootsOfUnity
variable {k R}
theorem map_rootsOfUnity_eq_pow_self [FunLike F R R] [RingHomClass F R R] (σ : F)
(ζ : rootsOfUnity k R) :
∃ m : ℕ, σ (ζ : Rˣ) = ((ζ : Rˣ) : R) ^ m := by
obtain ⟨m, hm⟩ := MonoidHom.map_cyclic (restrictRootsOfUnity σ k)
rw [← restrictRootsOfUnity_coe_apply, hm, ← zpow_mod_orderOf, ← Int.toNat_of_nonneg
(m.emod_nonneg (Int.natCast_ne_zero.mpr (pos_iff_ne_zero.mp (orderOf_pos ζ)))),
zpow_natCast, rootsOfUnity.coe_pow]
exact ⟨(m % orderOf ζ).toNat, rfl⟩
#align map_root_of_unity_eq_pow_self map_rootsOfUnity_eq_pow_self
end IsDomain
section Reduced
variable (R) [CommRing R] [IsReduced R]
-- @[simp] -- Porting note: simp normal form is `mem_rootsOfUnity_prime_pow_mul_iff'`
theorem mem_rootsOfUnity_prime_pow_mul_iff (p k : ℕ) (m : ℕ+) [ExpChar R p]
{ζ : Rˣ} : ζ ∈ rootsOfUnity (⟨p, expChar_pos R p⟩ ^ k * m) R ↔ ζ ∈ rootsOfUnity m R := by
simp only [mem_rootsOfUnity', PNat.mul_coe, PNat.pow_coe, PNat.mk_coe,
ExpChar.pow_prime_pow_mul_eq_one_iff]
#align mem_roots_of_unity_prime_pow_mul_iff mem_rootsOfUnity_prime_pow_mul_iff
@[simp]
theorem mem_rootsOfUnity_prime_pow_mul_iff' (p k : ℕ) (m : ℕ+) [ExpChar R p]
{ζ : Rˣ} : ζ ^ (p ^ k * ↑m) = 1 ↔ ζ ∈ rootsOfUnity m R := by
rw [← PNat.mk_coe p (expChar_pos R p), ← PNat.pow_coe, ← PNat.mul_coe, ← mem_rootsOfUnity,
mem_rootsOfUnity_prime_pow_mul_iff]
end Reduced
end rootsOfUnity
/-- An element `ζ` is a primitive `k`-th root of unity if `ζ ^ k = 1`,
and if `l` satisfies `ζ ^ l = 1` then `k ∣ l`. -/
@[mk_iff IsPrimitiveRoot.iff_def]
structure IsPrimitiveRoot (ζ : M) (k : ℕ) : Prop where
pow_eq_one : ζ ^ (k : ℕ) = 1
dvd_of_pow_eq_one : ∀ l : ℕ, ζ ^ l = 1 → k ∣ l
#align is_primitive_root IsPrimitiveRoot
#align is_primitive_root.iff_def IsPrimitiveRoot.iff_def
/-- Turn a primitive root μ into a member of the `rootsOfUnity` subgroup. -/
@[simps!]
def IsPrimitiveRoot.toRootsOfUnity {μ : M} {n : ℕ+} (h : IsPrimitiveRoot μ n) : rootsOfUnity n M :=
rootsOfUnity.mkOfPowEq μ h.pow_eq_one
#align is_primitive_root.to_roots_of_unity IsPrimitiveRoot.toRootsOfUnity
#align is_primitive_root.coe_to_roots_of_unity_coe IsPrimitiveRoot.val_toRootsOfUnity_coe
#align is_primitive_root.coe_inv_to_roots_of_unity_coe IsPrimitiveRoot.val_inv_toRootsOfUnity_coe
section primitiveRoots
variable {k : ℕ}
/-- `primitiveRoots k R` is the finset of primitive `k`-th roots of unity
in the integral domain `R`. -/
def primitiveRoots (k : ℕ) (R : Type*) [CommRing R] [IsDomain R] : Finset R :=
(nthRoots k (1 : R)).toFinset.filter fun ζ => IsPrimitiveRoot ζ k
#align primitive_roots primitiveRoots
variable [CommRing R] [IsDomain R]
@[simp]
theorem mem_primitiveRoots {ζ : R} (h0 : 0 < k) : ζ ∈ primitiveRoots k R ↔ IsPrimitiveRoot ζ k := by
rw [primitiveRoots, mem_filter, Multiset.mem_toFinset, mem_nthRoots h0, and_iff_right_iff_imp]
exact IsPrimitiveRoot.pow_eq_one
#align mem_primitive_roots mem_primitiveRoots
@[simp]
theorem primitiveRoots_zero : primitiveRoots 0 R = ∅ := by
rw [primitiveRoots, nthRoots_zero, Multiset.toFinset_zero, Finset.filter_empty]
#align primitive_roots_zero primitiveRoots_zero
theorem isPrimitiveRoot_of_mem_primitiveRoots {ζ : R} (h : ζ ∈ primitiveRoots k R) :
IsPrimitiveRoot ζ k :=
k.eq_zero_or_pos.elim (fun hk => by simp [hk] at h) fun hk => (mem_primitiveRoots hk).1 h
#align is_primitive_root_of_mem_primitive_roots isPrimitiveRoot_of_mem_primitiveRoots
end primitiveRoots
namespace IsPrimitiveRoot
variable {k l : ℕ}
theorem mk_of_lt (ζ : M) (hk : 0 < k) (h1 : ζ ^ k = 1) (h : ∀ l : ℕ, 0 < l → l < k → ζ ^ l ≠ 1) :
IsPrimitiveRoot ζ k := by
refine ⟨h1, fun l hl => ?_⟩
suffices k.gcd l = k by exact this ▸ k.gcd_dvd_right l
rw [eq_iff_le_not_lt]
refine ⟨Nat.le_of_dvd hk (k.gcd_dvd_left l), ?_⟩
intro h'; apply h _ (Nat.gcd_pos_of_pos_left _ hk) h'
exact pow_gcd_eq_one _ h1 hl
#align is_primitive_root.mk_of_lt IsPrimitiveRoot.mk_of_lt
section CommMonoid
variable {ζ : M} {f : F} (h : IsPrimitiveRoot ζ k)
@[nontriviality]
theorem of_subsingleton [Subsingleton M] (x : M) : IsPrimitiveRoot x 1 :=
⟨Subsingleton.elim _ _, fun _ _ => one_dvd _⟩
#align is_primitive_root.of_subsingleton IsPrimitiveRoot.of_subsingleton
theorem pow_eq_one_iff_dvd (l : ℕ) : ζ ^ l = 1 ↔ k ∣ l :=
⟨h.dvd_of_pow_eq_one l, by
rintro ⟨i, rfl⟩; simp only [pow_mul, h.pow_eq_one, one_pow, PNat.mul_coe]⟩
#align is_primitive_root.pow_eq_one_iff_dvd IsPrimitiveRoot.pow_eq_one_iff_dvd
theorem isUnit (h : IsPrimitiveRoot ζ k) (h0 : 0 < k) : IsUnit ζ := by
apply isUnit_of_mul_eq_one ζ (ζ ^ (k - 1))
rw [← pow_succ', tsub_add_cancel_of_le h0.nat_succ_le, h.pow_eq_one]
#align is_primitive_root.is_unit IsPrimitiveRoot.isUnit
theorem pow_ne_one_of_pos_of_lt (h0 : 0 < l) (hl : l < k) : ζ ^ l ≠ 1 :=
mt (Nat.le_of_dvd h0 ∘ h.dvd_of_pow_eq_one _) <| not_le_of_lt hl
#align is_primitive_root.pow_ne_one_of_pos_of_lt IsPrimitiveRoot.pow_ne_one_of_pos_of_lt
theorem ne_one (hk : 1 < k) : ζ ≠ 1 :=
h.pow_ne_one_of_pos_of_lt zero_lt_one hk ∘ (pow_one ζ).trans
#align is_primitive_root.ne_one IsPrimitiveRoot.ne_one
theorem pow_inj (h : IsPrimitiveRoot ζ k) ⦃i j : ℕ⦄ (hi : i < k) (hj : j < k) (H : ζ ^ i = ζ ^ j) :
i = j := by
wlog hij : i ≤ j generalizing i j
· exact (this hj hi H.symm (le_of_not_le hij)).symm
apply le_antisymm hij
rw [← tsub_eq_zero_iff_le]
apply Nat.eq_zero_of_dvd_of_lt _ (lt_of_le_of_lt tsub_le_self hj)
apply h.dvd_of_pow_eq_one
rw [← ((h.isUnit (lt_of_le_of_lt (Nat.zero_le _) hi)).pow i).mul_left_inj, ← pow_add,
tsub_add_cancel_of_le hij, H, one_mul]
#align is_primitive_root.pow_inj IsPrimitiveRoot.pow_inj
theorem one : IsPrimitiveRoot (1 : M) 1 :=
{ pow_eq_one := pow_one _
dvd_of_pow_eq_one := fun _ _ => one_dvd _ }
#align is_primitive_root.one IsPrimitiveRoot.one
@[simp]
theorem one_right_iff : IsPrimitiveRoot ζ 1 ↔ ζ = 1 := by
clear h
constructor
· intro h; rw [← pow_one ζ, h.pow_eq_one]
· rintro rfl; exact one
#align is_primitive_root.one_right_iff IsPrimitiveRoot.one_right_iff
@[simp]
theorem coe_submonoidClass_iff {M B : Type*} [CommMonoid M] [SetLike B M] [SubmonoidClass B M]
{N : B} {ζ : N} : IsPrimitiveRoot (ζ : M) k ↔ IsPrimitiveRoot ζ k := by
simp_rw [iff_def]
norm_cast
#align is_primitive_root.coe_submonoid_class_iff IsPrimitiveRoot.coe_submonoidClass_iff
@[simp]
theorem coe_units_iff {ζ : Mˣ} : IsPrimitiveRoot (ζ : M) k ↔ IsPrimitiveRoot ζ k := by
simp only [iff_def, Units.ext_iff, Units.val_pow_eq_pow_val, Units.val_one]
#align is_primitive_root.coe_units_iff IsPrimitiveRoot.coe_units_iff
lemma isUnit_unit {ζ : M} {n} (hn) (hζ : IsPrimitiveRoot ζ n) :
IsPrimitiveRoot (hζ.isUnit hn).unit n := coe_units_iff.mp hζ
lemma isUnit_unit' {ζ : G} {n} (hn) (hζ : IsPrimitiveRoot ζ n) :
IsPrimitiveRoot (hζ.isUnit hn).unit' n := coe_units_iff.mp hζ
-- Porting note `variable` above already contains `(h : IsPrimitiveRoot ζ k)`
theorem pow_of_coprime (i : ℕ) (hi : i.Coprime k) : IsPrimitiveRoot (ζ ^ i) k := by
by_cases h0 : k = 0
· subst k; simp_all only [pow_one, Nat.coprime_zero_right]
rcases h.isUnit (Nat.pos_of_ne_zero h0) with ⟨ζ, rfl⟩
rw [← Units.val_pow_eq_pow_val]
rw [coe_units_iff] at h ⊢
refine
{ pow_eq_one := by rw [← pow_mul', pow_mul, h.pow_eq_one, one_pow]
dvd_of_pow_eq_one := ?_ }
intro l hl
apply h.dvd_of_pow_eq_one
rw [← pow_one ζ, ← zpow_natCast ζ, ← hi.gcd_eq_one, Nat.gcd_eq_gcd_ab, zpow_add, mul_pow,
← zpow_natCast, ← zpow_mul, mul_right_comm]
simp only [zpow_mul, hl, h.pow_eq_one, one_zpow, one_pow, one_mul, zpow_natCast]
#align is_primitive_root.pow_of_coprime IsPrimitiveRoot.pow_of_coprime
theorem pow_of_prime (h : IsPrimitiveRoot ζ k) {p : ℕ} (hprime : Nat.Prime p) (hdiv : ¬p ∣ k) :
IsPrimitiveRoot (ζ ^ p) k :=
h.pow_of_coprime p (hprime.coprime_iff_not_dvd.2 hdiv)
#align is_primitive_root.pow_of_prime IsPrimitiveRoot.pow_of_prime
theorem pow_iff_coprime (h : IsPrimitiveRoot ζ k) (h0 : 0 < k) (i : ℕ) :
IsPrimitiveRoot (ζ ^ i) k ↔ i.Coprime k := by
refine ⟨?_, h.pow_of_coprime i⟩
intro hi
obtain ⟨a, ha⟩ := i.gcd_dvd_left k
obtain ⟨b, hb⟩ := i.gcd_dvd_right k
suffices b = k by
-- Porting note: was `rwa [this, ← one_mul k, mul_left_inj' h0.ne', eq_comm] at hb`
rw [this, eq_comm, Nat.mul_left_eq_self_iff h0] at hb
rwa [Nat.Coprime]
rw [ha] at hi
rw [mul_comm] at hb
apply Nat.dvd_antisymm ⟨i.gcd k, hb⟩ (hi.dvd_of_pow_eq_one b _)
rw [← pow_mul', ← mul_assoc, ← hb, pow_mul, h.pow_eq_one, one_pow]
#align is_primitive_root.pow_iff_coprime IsPrimitiveRoot.pow_iff_coprime
protected theorem orderOf (ζ : M) : IsPrimitiveRoot ζ (orderOf ζ) :=
⟨pow_orderOf_eq_one ζ, fun _ => orderOf_dvd_of_pow_eq_one⟩
#align is_primitive_root.order_of IsPrimitiveRoot.orderOf
theorem unique {ζ : M} (hk : IsPrimitiveRoot ζ k) (hl : IsPrimitiveRoot ζ l) : k = l :=
Nat.dvd_antisymm (hk.2 _ hl.1) (hl.2 _ hk.1)
#align is_primitive_root.unique IsPrimitiveRoot.unique
theorem eq_orderOf : k = orderOf ζ :=
h.unique (IsPrimitiveRoot.orderOf ζ)
#align is_primitive_root.eq_order_of IsPrimitiveRoot.eq_orderOf
protected theorem iff (hk : 0 < k) :
IsPrimitiveRoot ζ k ↔ ζ ^ k = 1 ∧ ∀ l : ℕ, 0 < l → l < k → ζ ^ l ≠ 1 := by
refine ⟨fun h => ⟨h.pow_eq_one, fun l hl' hl => ?_⟩,
fun ⟨hζ, hl⟩ => IsPrimitiveRoot.mk_of_lt ζ hk hζ hl⟩
rw [h.eq_orderOf] at hl
exact pow_ne_one_of_lt_orderOf' hl'.ne' hl
#align is_primitive_root.iff IsPrimitiveRoot.iff
protected theorem not_iff : ¬IsPrimitiveRoot ζ k ↔ orderOf ζ ≠ k :=
⟨fun h hk => h <| hk ▸ IsPrimitiveRoot.orderOf ζ,
fun h hk => h.symm <| hk.unique <| IsPrimitiveRoot.orderOf ζ⟩
#align is_primitive_root.not_iff IsPrimitiveRoot.not_iff
theorem pow_mul_pow_lcm {ζ' : M} {k' : ℕ} (hζ : IsPrimitiveRoot ζ k) (hζ' : IsPrimitiveRoot ζ' k')
(hk : k ≠ 0) (hk' : k' ≠ 0) :
IsPrimitiveRoot
(ζ ^ (k / Nat.factorizationLCMLeft k k') * ζ' ^ (k' / Nat.factorizationLCMRight k k'))
(Nat.lcm k k') := by
convert IsPrimitiveRoot.orderOf _
convert ((Commute.all ζ ζ').orderOf_mul_pow_eq_lcm
(by simpa [← hζ.eq_orderOf]) (by simpa [← hζ'.eq_orderOf])).symm using 2
all_goals simp [hζ.eq_orderOf, hζ'.eq_orderOf]
theorem pow_of_dvd (h : IsPrimitiveRoot ζ k) {p : ℕ} (hp : p ≠ 0) (hdiv : p ∣ k) :
IsPrimitiveRoot (ζ ^ p) (k / p) := by
suffices orderOf (ζ ^ p) = k / p by exact this ▸ IsPrimitiveRoot.orderOf (ζ ^ p)
rw [orderOf_pow' _ hp, ← eq_orderOf h, Nat.gcd_eq_right hdiv]
#align is_primitive_root.pow_of_dvd IsPrimitiveRoot.pow_of_dvd
protected theorem mem_rootsOfUnity {ζ : Mˣ} {n : ℕ+} (h : IsPrimitiveRoot ζ n) :
ζ ∈ rootsOfUnity n M :=
h.pow_eq_one
#align is_primitive_root.mem_roots_of_unity IsPrimitiveRoot.mem_rootsOfUnity
/-- If there is an `n`-th primitive root of unity in `R` and `b` divides `n`,
then there is a `b`-th primitive root of unity in `R`. -/
theorem pow {n : ℕ} {a b : ℕ} (hn : 0 < n) (h : IsPrimitiveRoot ζ n) (hprod : n = a * b) :
IsPrimitiveRoot (ζ ^ a) b := by
subst n
simp only [iff_def, ← pow_mul, h.pow_eq_one, eq_self_iff_true, true_and_iff]
intro l hl
-- Porting note: was `by rintro rfl; simpa only [Nat.not_lt_zero, zero_mul] using hn`
have ha0 : a ≠ 0 := left_ne_zero_of_mul hn.ne'
rw [← mul_dvd_mul_iff_left ha0]
exact h.dvd_of_pow_eq_one _ hl
#align is_primitive_root.pow IsPrimitiveRoot.pow
lemma injOn_pow {n : ℕ} {ζ : M} (hζ : IsPrimitiveRoot ζ n) :
Set.InjOn (ζ ^ ·) (Finset.range n) := by
obtain (rfl|hn) := n.eq_zero_or_pos; · simp
intros i hi j hj e
rw [Finset.coe_range, Set.mem_Iio] at hi hj
have : (hζ.isUnit hn).unit ^ i = (hζ.isUnit hn).unit ^ j := Units.ext (by simpa using e)
rw [pow_inj_mod, ← orderOf_injective ⟨⟨Units.val, Units.val_one⟩, Units.val_mul⟩
Units.ext (hζ.isUnit hn).unit] at this
simpa [← hζ.eq_orderOf, Nat.mod_eq_of_lt, hi, hj] using this
section Maps
open Function
variable [FunLike F M N]
theorem map_of_injective [MonoidHomClass F M N] (h : IsPrimitiveRoot ζ k) (hf : Injective f) :
IsPrimitiveRoot (f ζ) k where
pow_eq_one := by rw [← map_pow, h.pow_eq_one, _root_.map_one]
dvd_of_pow_eq_one := by
rw [h.eq_orderOf]
intro l hl
rw [← map_pow, ← map_one f] at hl
exact orderOf_dvd_of_pow_eq_one (hf hl)
#align is_primitive_root.map_of_injective IsPrimitiveRoot.map_of_injective
theorem of_map_of_injective [MonoidHomClass F M N] (h : IsPrimitiveRoot (f ζ) k)
(hf : Injective f) : IsPrimitiveRoot ζ k where
pow_eq_one := by apply_fun f; rw [map_pow, _root_.map_one, h.pow_eq_one]
dvd_of_pow_eq_one := by
rw [h.eq_orderOf]
intro l hl
apply_fun f at hl
rw [map_pow, _root_.map_one] at hl
exact orderOf_dvd_of_pow_eq_one hl
#align is_primitive_root.of_map_of_injective IsPrimitiveRoot.of_map_of_injective
theorem map_iff_of_injective [MonoidHomClass F M N] (hf : Injective f) :
IsPrimitiveRoot (f ζ) k ↔ IsPrimitiveRoot ζ k :=
⟨fun h => h.of_map_of_injective hf, fun h => h.map_of_injective hf⟩
#align is_primitive_root.map_iff_of_injective IsPrimitiveRoot.map_iff_of_injective
end Maps
end CommMonoid
section CommMonoidWithZero
variable {M₀ : Type*} [CommMonoidWithZero M₀]
theorem zero [Nontrivial M₀] : IsPrimitiveRoot (0 : M₀) 0 :=
⟨pow_zero 0, fun l hl => by
simpa [zero_pow_eq, show ∀ p, ¬p → False ↔ p from @Classical.not_not] using hl⟩
#align is_primitive_root.zero IsPrimitiveRoot.zero
protected theorem ne_zero [Nontrivial M₀] {ζ : M₀} (h : IsPrimitiveRoot ζ k) : k ≠ 0 → ζ ≠ 0 :=
mt fun hn => h.unique (hn.symm ▸ IsPrimitiveRoot.zero)
#align is_primitive_root.ne_zero IsPrimitiveRoot.ne_zero
end CommMonoidWithZero
section CancelCommMonoidWithZero
variable {M₀ : Type*} [CancelCommMonoidWithZero M₀]
lemma injOn_pow_mul {n : ℕ} {ζ : M₀} (hζ : IsPrimitiveRoot ζ n)
{α : M₀} (hα : α ≠ 0) :
Set.InjOn (ζ ^ · * α) (Finset.range n) := fun i hi j hj e ↦
hζ.injOn_pow hi hj (by simpa [mul_eq_mul_right_iff, or_iff_left hα] using e)
end CancelCommMonoidWithZero
section DivisionCommMonoid
variable {ζ : G}
theorem zpow_eq_one (h : IsPrimitiveRoot ζ k) : ζ ^ (k : ℤ) = 1 := by
rw [zpow_natCast]; exact h.pow_eq_one
#align is_primitive_root.zpow_eq_one IsPrimitiveRoot.zpow_eq_one
theorem zpow_eq_one_iff_dvd (h : IsPrimitiveRoot ζ k) (l : ℤ) : ζ ^ l = 1 ↔ (k : ℤ) ∣ l := by
by_cases h0 : 0 ≤ l
· lift l to ℕ using h0; rw [zpow_natCast]; norm_cast; exact h.pow_eq_one_iff_dvd l
· have : 0 ≤ -l := by simp only [not_le, neg_nonneg] at h0 ⊢; exact le_of_lt h0
lift -l to ℕ using this with l' hl'
rw [← dvd_neg, ← hl']
norm_cast
rw [← h.pow_eq_one_iff_dvd, ← inv_inj, ← zpow_neg, ← hl', zpow_natCast, inv_one]
#align is_primitive_root.zpow_eq_one_iff_dvd IsPrimitiveRoot.zpow_eq_one_iff_dvd
theorem inv (h : IsPrimitiveRoot ζ k) : IsPrimitiveRoot ζ⁻¹ k :=
{ pow_eq_one := by simp only [h.pow_eq_one, inv_one, eq_self_iff_true, inv_pow]
dvd_of_pow_eq_one := by
intro l hl
apply h.dvd_of_pow_eq_one l
rw [← inv_inj, ← inv_pow, hl, inv_one] }
#align is_primitive_root.inv IsPrimitiveRoot.inv
@[simp]
theorem inv_iff : IsPrimitiveRoot ζ⁻¹ k ↔ IsPrimitiveRoot ζ k := by
refine ⟨?_, fun h => inv h⟩; intro h; rw [← inv_inv ζ]; exact inv h
#align is_primitive_root.inv_iff IsPrimitiveRoot.inv_iff
theorem zpow_of_gcd_eq_one (h : IsPrimitiveRoot ζ k) (i : ℤ) (hi : i.gcd k = 1) :
IsPrimitiveRoot (ζ ^ i) k := by
by_cases h0 : 0 ≤ i
· lift i to ℕ using h0
rw [zpow_natCast]
exact h.pow_of_coprime i hi
have : 0 ≤ -i := by simp only [not_le, neg_nonneg] at h0 ⊢; exact le_of_lt h0
lift -i to ℕ using this with i' hi'
rw [← inv_iff, ← zpow_neg, ← hi', zpow_natCast]
apply h.pow_of_coprime
rw [Int.gcd, ← Int.natAbs_neg, ← hi'] at hi
exact hi
#align is_primitive_root.zpow_of_gcd_eq_one IsPrimitiveRoot.zpow_of_gcd_eq_one
end DivisionCommMonoid
section CommRing
variable [CommRing R] {n : ℕ} (hn : 1 < n) {ζ : R} (hζ : IsPrimitiveRoot ζ n)
theorem sub_one_ne_zero : ζ - 1 ≠ 0 := sub_ne_zero.mpr <| hζ.ne_one hn
end CommRing
section IsDomain
variable {ζ : R}
variable [CommRing R] [IsDomain R]
@[simp]
theorem primitiveRoots_one : primitiveRoots 1 R = {(1 : R)} := by
apply Finset.eq_singleton_iff_unique_mem.2
constructor
· simp only [IsPrimitiveRoot.one_right_iff, mem_primitiveRoots zero_lt_one]
· intro x hx
rw [mem_primitiveRoots zero_lt_one, IsPrimitiveRoot.one_right_iff] at hx
exact hx
#align is_primitive_root.primitive_roots_one IsPrimitiveRoot.primitiveRoots_one
theorem neZero' {n : ℕ+} (hζ : IsPrimitiveRoot ζ n) : NeZero ((n : ℕ) : R) := by
let p := ringChar R
have hfin := multiplicity.finite_nat_iff.2 ⟨CharP.char_ne_one R p, n.pos⟩
obtain ⟨m, hm⟩ := multiplicity.exists_eq_pow_mul_and_not_dvd hfin
by_cases hp : p ∣ n
· obtain ⟨k, hk⟩ := Nat.exists_eq_succ_of_ne_zero (multiplicity.pos_of_dvd hfin hp).ne'
haveI : NeZero p := NeZero.of_pos (Nat.pos_of_dvd_of_pos hp n.pos)
haveI hpri : Fact p.Prime := CharP.char_is_prime_of_pos R p
have := hζ.pow_eq_one
rw [hm.1, hk, pow_succ', mul_assoc, pow_mul', ← frobenius_def, ← frobenius_one p] at this
exfalso
have hpos : 0 < p ^ k * m := by
refine mul_pos (pow_pos hpri.1.pos _) (Nat.pos_of_ne_zero fun h => ?_)
have H := hm.1
rw [h] at H
simp at H
refine hζ.pow_ne_one_of_pos_of_lt hpos ?_ (frobenius_inj R p this)
rw [hm.1, hk, pow_succ', mul_assoc, mul_comm p]
exact lt_mul_of_one_lt_right hpos hpri.1.one_lt
· exact NeZero.of_not_dvd R hp
#align is_primitive_root.ne_zero' IsPrimitiveRoot.neZero'
nonrec theorem mem_nthRootsFinset (hζ : IsPrimitiveRoot ζ k) (hk : 0 < k) :
ζ ∈ nthRootsFinset k R :=
(mem_nthRootsFinset hk).2 hζ.pow_eq_one
#align is_primitive_root.mem_nth_roots_finset IsPrimitiveRoot.mem_nthRootsFinset
end IsDomain
section IsDomain
variable [CommRing R]
variable {ζ : Rˣ} (h : IsPrimitiveRoot ζ k)
theorem eq_neg_one_of_two_right [NoZeroDivisors R] {ζ : R} (h : IsPrimitiveRoot ζ 2) : ζ = -1 := by
apply (eq_or_eq_neg_of_sq_eq_sq ζ 1 _).resolve_left
· rw [← pow_one ζ]; apply h.pow_ne_one_of_pos_of_lt <;> decide
· simp only [h.pow_eq_one, one_pow]
#align is_primitive_root.eq_neg_one_of_two_right IsPrimitiveRoot.eq_neg_one_of_two_right
theorem neg_one (p : ℕ) [Nontrivial R] [h : CharP R p] (hp : p ≠ 2) :
IsPrimitiveRoot (-1 : R) 2 := by
convert IsPrimitiveRoot.orderOf (-1 : R)
rw [orderOf_neg_one, if_neg]
rwa [ringChar.eq_iff.mpr h]
#align is_primitive_root.neg_one IsPrimitiveRoot.neg_one
/-- If `1 < k` then `(∑ i ∈ range k, ζ ^ i) = 0`. -/
theorem geom_sum_eq_zero [IsDomain R] {ζ : R} (hζ : IsPrimitiveRoot ζ k) (hk : 1 < k) :
∑ i ∈ range k, ζ ^ i = 0 := by
refine eq_zero_of_ne_zero_of_mul_left_eq_zero (sub_ne_zero_of_ne (hζ.ne_one hk).symm) ?_
rw [mul_neg_geom_sum, hζ.pow_eq_one, sub_self]
#align is_primitive_root.geom_sum_eq_zero IsPrimitiveRoot.geom_sum_eq_zero
/-- If `1 < k`, then `ζ ^ k.pred = -(∑ i ∈ range k.pred, ζ ^ i)`. -/
theorem pow_sub_one_eq [IsDomain R] {ζ : R} (hζ : IsPrimitiveRoot ζ k) (hk : 1 < k) :
ζ ^ k.pred = -∑ i ∈ range k.pred, ζ ^ i := by
rw [eq_neg_iff_add_eq_zero, add_comm, ← sum_range_succ, ← Nat.succ_eq_add_one,
Nat.succ_pred_eq_of_pos (pos_of_gt hk), hζ.geom_sum_eq_zero hk]
#align is_primitive_root.pow_sub_one_eq IsPrimitiveRoot.pow_sub_one_eq
/-- The (additive) monoid equivalence between `ZMod k`
and the powers of a primitive root of unity `ζ`. -/
def zmodEquivZPowers (h : IsPrimitiveRoot ζ k) : ZMod k ≃+ Additive (Subgroup.zpowers ζ) :=
AddEquiv.ofBijective
(AddMonoidHom.liftOfRightInverse (Int.castAddHom <| ZMod k) _ ZMod.intCast_rightInverse
⟨{ toFun := fun i => Additive.ofMul (⟨_, i, rfl⟩ : Subgroup.zpowers ζ)
map_zero' := by simp only [zpow_zero]; rfl
map_add' := by intro i j; simp only [zpow_add]; rfl }, fun i hi => by
simp only [AddMonoidHom.mem_ker, CharP.intCast_eq_zero_iff (ZMod k) k, AddMonoidHom.coe_mk,
Int.coe_castAddHom] at hi ⊢
obtain ⟨i, rfl⟩ := hi
simp [zpow_mul, h.pow_eq_one, one_zpow, zpow_natCast]⟩)
(by
constructor
· rw [injective_iff_map_eq_zero]
intro i hi
rw [Subtype.ext_iff] at hi
have := (h.zpow_eq_one_iff_dvd _).mp hi
rw [← (CharP.intCast_eq_zero_iff (ZMod k) k _).mpr this, eq_comm]
exact ZMod.intCast_rightInverse i
· rintro ⟨ξ, i, rfl⟩
refine ⟨Int.castAddHom (ZMod k) i, ?_⟩
rw [AddMonoidHom.liftOfRightInverse_comp_apply]
rfl)
#align is_primitive_root.zmod_equiv_zpowers IsPrimitiveRoot.zmodEquivZPowers
@[simp]
theorem zmodEquivZPowers_apply_coe_int (i : ℤ) :
h.zmodEquivZPowers i = Additive.ofMul (⟨ζ ^ i, i, rfl⟩ : Subgroup.zpowers ζ) := by
rw [zmodEquivZPowers, AddEquiv.ofBijective_apply] -- Porting note: Original proof didn't have `rw`
exact AddMonoidHom.liftOfRightInverse_comp_apply _ _ ZMod.intCast_rightInverse _ _
#align is_primitive_root.zmod_equiv_zpowers_apply_coe_int IsPrimitiveRoot.zmodEquivZPowers_apply_coe_int
@[simp]
theorem zmodEquivZPowers_apply_coe_nat (i : ℕ) :
h.zmodEquivZPowers i = Additive.ofMul (⟨ζ ^ i, i, rfl⟩ : Subgroup.zpowers ζ) := by
have : (i : ZMod k) = (i : ℤ) := by norm_cast
simp only [this, zmodEquivZPowers_apply_coe_int, zpow_natCast]
#align is_primitive_root.zmod_equiv_zpowers_apply_coe_nat IsPrimitiveRoot.zmodEquivZPowers_apply_coe_nat
@[simp]
theorem zmodEquivZPowers_symm_apply_zpow (i : ℤ) :
h.zmodEquivZPowers.symm (Additive.ofMul (⟨ζ ^ i, i, rfl⟩ : Subgroup.zpowers ζ)) = i := by
rw [← h.zmodEquivZPowers.symm_apply_apply i, zmodEquivZPowers_apply_coe_int]
#align is_primitive_root.zmod_equiv_zpowers_symm_apply_zpow IsPrimitiveRoot.zmodEquivZPowers_symm_apply_zpow
@[simp]
theorem zmodEquivZPowers_symm_apply_zpow' (i : ℤ) : h.zmodEquivZPowers.symm ⟨ζ ^ i, i, rfl⟩ = i :=
h.zmodEquivZPowers_symm_apply_zpow i
#align is_primitive_root.zmod_equiv_zpowers_symm_apply_zpow' IsPrimitiveRoot.zmodEquivZPowers_symm_apply_zpow'
@[simp]
theorem zmodEquivZPowers_symm_apply_pow (i : ℕ) :
h.zmodEquivZPowers.symm (Additive.ofMul (⟨ζ ^ i, i, rfl⟩ : Subgroup.zpowers ζ)) = i := by
rw [← h.zmodEquivZPowers.symm_apply_apply i, zmodEquivZPowers_apply_coe_nat]
#align is_primitive_root.zmod_equiv_zpowers_symm_apply_pow IsPrimitiveRoot.zmodEquivZPowers_symm_apply_pow
@[simp]
theorem zmodEquivZPowers_symm_apply_pow' (i : ℕ) : h.zmodEquivZPowers.symm ⟨ζ ^ i, i, rfl⟩ = i :=
h.zmodEquivZPowers_symm_apply_pow i
#align is_primitive_root.zmod_equiv_zpowers_symm_apply_pow' IsPrimitiveRoot.zmodEquivZPowers_symm_apply_pow'
variable [IsDomain R]
theorem zpowers_eq {k : ℕ+} {ζ : Rˣ} (h : IsPrimitiveRoot ζ k) :
Subgroup.zpowers ζ = rootsOfUnity k R := by
apply SetLike.coe_injective
haveI F : Fintype (Subgroup.zpowers ζ) := Fintype.ofEquiv _ h.zmodEquivZPowers.toEquiv
refine
@Set.eq_of_subset_of_card_le Rˣ (Subgroup.zpowers ζ) (rootsOfUnity k R) F
(rootsOfUnity.fintype R k)
(Subgroup.zpowers_le_of_mem <| show ζ ∈ rootsOfUnity k R from h.pow_eq_one) ?_
calc
Fintype.card (rootsOfUnity k R) ≤ k := card_rootsOfUnity R k
_ = Fintype.card (ZMod k) := (ZMod.card k).symm
_ = Fintype.card (Subgroup.zpowers ζ) := Fintype.card_congr h.zmodEquivZPowers.toEquiv
#align is_primitive_root.zpowers_eq IsPrimitiveRoot.zpowers_eq
lemma map_rootsOfUnity {S F} [CommRing S] [IsDomain S] [FunLike F R S] [MonoidHomClass F R S]
{ζ : R} {n : ℕ+} (hζ : IsPrimitiveRoot ζ n) {f : F} (hf : Function.Injective f) :
(rootsOfUnity n R).map (Units.map f) = rootsOfUnity n S := by
letI : CommMonoid Sˣ := inferInstance
replace hζ := hζ.isUnit_unit n.2
rw [← hζ.zpowers_eq,
← (hζ.map_of_injective (Units.map_injective (f := (f : R →* S)) hf)).zpowers_eq,
MonoidHom.map_zpowers]
/-- If `R` contains a `n`-th primitive root, and `S/R` is a ring extension,
then the `n`-th roots of unity in `R` and `S` are isomorphic.
Also see `IsPrimitiveRoot.map_rootsOfUnity` for the equality as `Subgroup Sˣ`. -/
@[simps! (config := .lemmasOnly) apply_coe_val apply_coe_inv_val]
noncomputable
def _root_.rootsOfUnityEquivOfPrimitiveRoots {S F} [CommRing S] [IsDomain S]
[FunLike F R S] [MonoidHomClass F R S]
{n : ℕ+} {f : F} (hf : Function.Injective f) (hζ : (primitiveRoots n R).Nonempty) :
(rootsOfUnity n R) ≃* rootsOfUnity n S :=
(Subgroup.equivMapOfInjective _ _ (Units.map_injective hf)).trans (MulEquiv.subgroupCongr
(((mem_primitiveRoots (k := n) n.2).mp hζ.choose_spec).map_rootsOfUnity hf))
lemma _root_.rootsOfUnityEquivOfPrimitiveRoots_symm_apply
{S F} [CommRing S] [IsDomain S] [FunLike F R S] [MonoidHomClass F R S]
{n : ℕ+} {f : F} (hf : Function.Injective f) (hζ : (primitiveRoots n R).Nonempty) (η) :
f ((rootsOfUnityEquivOfPrimitiveRoots hf hζ).symm η : Rˣ) = (η : Sˣ) := by
obtain ⟨ε, rfl⟩ := (rootsOfUnityEquivOfPrimitiveRoots hf hζ).surjective η
rw [MulEquiv.symm_apply_apply, val_rootsOfUnityEquivOfPrimitiveRoots_apply_coe]
-- Porting note: rephrased the next few lemmas to avoid `∃ (Prop)`
| Mathlib/RingTheory/RootsOfUnity/Basic.lean | 822 | 832 | theorem eq_pow_of_mem_rootsOfUnity {k : ℕ+} {ζ ξ : Rˣ} (h : IsPrimitiveRoot ζ k)
(hξ : ξ ∈ rootsOfUnity k R) : ∃ (i : ℕ), i < k ∧ ζ ^ i = ξ := by |
obtain ⟨n, rfl⟩ : ∃ n : ℤ, ζ ^ n = ξ := by rwa [← h.zpowers_eq] at hξ
have hk0 : (0 : ℤ) < k := mod_cast k.pos
let i := n % k
have hi0 : 0 ≤ i := Int.emod_nonneg _ (ne_of_gt hk0)
lift i to ℕ using hi0 with i₀ hi₀
refine ⟨i₀, ?_, ?_⟩
· zify; rw [hi₀]; exact Int.emod_lt_of_pos _ hk0
· rw [← zpow_natCast, hi₀, ← Int.emod_add_ediv n k, zpow_add, zpow_mul, h.zpow_eq_one, one_zpow,
mul_one]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Analysis.Calculus.ContDiff.Basic
import Mathlib.Data.Finset.Sym
import Mathlib.Data.Nat.Choose.Cast
import Mathlib.Data.Nat.Choose.Multinomial
#align_import analysis.calculus.cont_diff from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Bounds on higher derivatives
`norm_iteratedFDeriv_comp_le` gives the bound `n! * C * D ^ n` for the `n`-th derivative
of `g ∘ f` assuming that the derivatives of `g` are bounded by `C` and the `i`-th
derivative of `f` is bounded by `D ^ i`.
-/
noncomputable section
open scoped Classical NNReal Nat
universe u uD uE uF uG
open Set Fin Filter Function
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {D : Type uD} [NormedAddCommGroup D]
[NormedSpace 𝕜 D] {E : Type uE} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type uF}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
{s s₁ t u : Set E}
/-!## Quantitative bounds -/
/-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the
iterated derivatives of `f` and `g` when `B` is bilinear. This lemma is an auxiliary version
assuming all spaces live in the same universe, to enable an induction. Use instead
`ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear` that removes this assumption. -/
theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_aux {Du Eu Fu Gu : Type u}
[NormedAddCommGroup Du] [NormedSpace 𝕜 Du] [NormedAddCommGroup Eu] [NormedSpace 𝕜 Eu]
[NormedAddCommGroup Fu] [NormedSpace 𝕜 Fu] [NormedAddCommGroup Gu] [NormedSpace 𝕜 Gu]
(B : Eu →L[𝕜] Fu →L[𝕜] Gu) {f : Du → Eu} {g : Du → Fu} {n : ℕ} {s : Set Du} {x : Du}
(hf : ContDiffOn 𝕜 n f s) (hg : ContDiffOn 𝕜 n g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by
/- We argue by induction on `n`. The bound is trivial for `n = 0`. For `n + 1`, we write
the `(n+1)`-th derivative as the `n`-th derivative of the derivative `B f g' + B f' g`,
and apply the inductive assumption to each of those two terms. For this induction to make sense,
the spaces of linear maps that appear in the induction should be in the same universe as the
original spaces, which explains why we assume in the lemma that all spaces live in the same
universe. -/
induction' n with n IH generalizing Eu Fu Gu
· simp only [Nat.zero_eq, norm_iteratedFDerivWithin_zero, zero_add, Finset.range_one,
Finset.sum_singleton, Nat.choose_self, Nat.cast_one, one_mul, Nat.sub_zero, ← mul_assoc]
apply B.le_opNorm₂
· have In : (n : ℕ∞) + 1 ≤ n.succ := by simp only [Nat.cast_succ, le_refl]
-- Porting note: the next line is a hack allowing Lean to find the operator norm instance.
let norm := @ContinuousLinearMap.hasOpNorm _ _ Eu ((Du →L[𝕜] Fu) →L[𝕜] Du →L[𝕜] Gu) _ _ _ _ _ _
(RingHom.id 𝕜)
have I1 :
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n + 1 - i) g s x‖ := by
calc
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s x‖ ≤
‖B.precompR Du‖ * ∑ i ∈ Finset.range (n + 1),
n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 g s) s x‖ :=
IH _ (hf.of_le (Nat.cast_le.2 (Nat.le_succ n))) (hg.fderivWithin hs In)
_ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 g s) s x‖ :=
mul_le_mul_of_nonneg_right (B.norm_precompR_le Du) (by positivity)
_ = _ := by
congr 1
apply Finset.sum_congr rfl fun i hi => ?_
rw [Nat.succ_sub (Nat.lt_succ_iff.1 (Finset.mem_range.1 hi)),
← norm_iteratedFDerivWithin_fderivWithin hs hx]
-- Porting note: the next line is a hack allowing Lean to find the operator norm instance.
let norm := @ContinuousLinearMap.hasOpNorm _ _ (Du →L[𝕜] Eu) (Fu →L[𝕜] Du →L[𝕜] Gu) _ _ _ _ _ _
(RingHom.id 𝕜)
have I2 :
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 (i + 1) f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
calc
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x‖ ≤
‖B.precompL Du‖ * ∑ i ∈ Finset.range (n + 1),
n.choose i * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 f s) s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
IH _ (hf.fderivWithin hs In) (hg.of_le (Nat.cast_le.2 (Nat.le_succ n)))
_ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1),
n.choose i * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 f s) s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
mul_le_mul_of_nonneg_right (B.norm_precompL_le Du) (by positivity)
_ = _ := by
congr 1
apply Finset.sum_congr rfl fun i _ => ?_
rw [← norm_iteratedFDerivWithin_fderivWithin hs hx]
have J : iteratedFDerivWithin 𝕜 n
(fun y : Du => fderivWithin 𝕜 (fun y : Du => B (f y) (g y)) s y) s x =
iteratedFDerivWithin 𝕜 n (fun y => B.precompR Du (f y)
(fderivWithin 𝕜 g s y) + B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x := by
apply iteratedFDerivWithin_congr (fun y hy => ?_) hx
have L : (1 : ℕ∞) ≤ n.succ := by
simpa only [ENat.coe_one, Nat.one_le_cast] using Nat.succ_pos n
exact B.fderivWithin_of_bilinear (hf.differentiableOn L y hy) (hg.differentiableOn L y hy)
(hs y hy)
rw [← norm_iteratedFDerivWithin_fderivWithin hs hx, J]
have A : ContDiffOn 𝕜 n (fun y => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s :=
(B.precompR Du).isBoundedBilinearMap.contDiff.comp_contDiff_on₂
(hf.of_le (Nat.cast_le.2 (Nat.le_succ n))) (hg.fderivWithin hs In)
have A' : ContDiffOn 𝕜 n (fun y => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s :=
(B.precompL Du).isBoundedBilinearMap.contDiff.comp_contDiff_on₂ (hf.fderivWithin hs In)
(hg.of_le (Nat.cast_le.2 (Nat.le_succ n)))
rw [iteratedFDerivWithin_add_apply' A A' hs hx]
apply (norm_add_le _ _).trans ((add_le_add I1 I2).trans (le_of_eq ?_))
simp_rw [← mul_add, mul_assoc]
congr 1
exact (Finset.sum_choose_succ_mul
(fun i j => ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 j g s x‖) n).symm
#align continuous_linear_map.norm_iterated_fderiv_within_le_of_bilinear_aux ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_aux
/-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the
iterated derivatives of `f` and `g` when `B` is bilinear:
`‖D^n (x ↦ B (f x) (g x))‖ ≤ ‖B‖ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/
theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear (B : E →L[𝕜] F →L[𝕜] G)
{f : D → E} {g : D → F} {N : ℕ∞} {s : Set D} {x : D} (hf : ContDiffOn 𝕜 N f s)
(hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {n : ℕ} (hn : (n : ℕ∞) ≤ N) :
‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by
/- We reduce the bound to the case where all spaces live in the same universe (in which we
already have proved the result), by using linear isometries between the spaces and their `ULift`
to a common universe. These linear isometries preserve the norm of the iterated derivative. -/
let Du : Type max uD uE uF uG := ULift.{max uE uF uG, uD} D
let Eu : Type max uD uE uF uG := ULift.{max uD uF uG, uE} E
let Fu : Type max uD uE uF uG := ULift.{max uD uE uG, uF} F
let Gu : Type max uD uE uF uG := ULift.{max uD uE uF, uG} G
have isoD : Du ≃ₗᵢ[𝕜] D := LinearIsometryEquiv.ulift 𝕜 D
have isoE : Eu ≃ₗᵢ[𝕜] E := LinearIsometryEquiv.ulift 𝕜 E
have isoF : Fu ≃ₗᵢ[𝕜] F := LinearIsometryEquiv.ulift 𝕜 F
have isoG : Gu ≃ₗᵢ[𝕜] G := LinearIsometryEquiv.ulift 𝕜 G
-- lift `f` and `g` to versions `fu` and `gu` on the lifted spaces.
set fu : Du → Eu := isoE.symm ∘ f ∘ isoD with hfu
set gu : Du → Fu := isoF.symm ∘ g ∘ isoD with hgu
-- lift the bilinear map `B` to a bilinear map `Bu` on the lifted spaces.
set Bu₀ : Eu →L[𝕜] Fu →L[𝕜] G := ((B.comp (isoE : Eu →L[𝕜] E)).flip.comp (isoF : Fu →L[𝕜] F)).flip
with hBu₀
let Bu : Eu →L[𝕜] Fu →L[𝕜] Gu :=
ContinuousLinearMap.compL 𝕜 Eu (Fu →L[𝕜] G) (Fu →L[𝕜] Gu)
(ContinuousLinearMap.compL 𝕜 Fu G Gu (isoG.symm : G →L[𝕜] Gu)) Bu₀
have hBu : Bu = ContinuousLinearMap.compL 𝕜 Eu (Fu →L[𝕜] G) (Fu →L[𝕜] Gu)
(ContinuousLinearMap.compL 𝕜 Fu G Gu (isoG.symm : G →L[𝕜] Gu)) Bu₀ := rfl
have Bu_eq : (fun y => Bu (fu y) (gu y)) = isoG.symm ∘ (fun y => B (f y) (g y)) ∘ isoD := by
ext1 y
simp [hBu, hBu₀, hfu, hgu]
-- All norms are preserved by the lifting process.
have Bu_le : ‖Bu‖ ≤ ‖B‖ := by
refine' ContinuousLinearMap.opNorm_le_bound _ (norm_nonneg B) fun y => _
refine' ContinuousLinearMap.opNorm_le_bound _ (by positivity) fun x => _
simp only [hBu, hBu₀, compL_apply, coe_comp', Function.comp_apply,
ContinuousLinearEquiv.coe_coe, LinearIsometryEquiv.coe_coe, flip_apply,
LinearIsometryEquiv.norm_map]
calc
‖B (isoE y) (isoF x)‖ ≤ ‖B (isoE y)‖ * ‖isoF x‖ := ContinuousLinearMap.le_opNorm _ _
_ ≤ ‖B‖ * ‖isoE y‖ * ‖isoF x‖ := by gcongr; apply ContinuousLinearMap.le_opNorm
_ = ‖B‖ * ‖y‖ * ‖x‖ := by simp only [LinearIsometryEquiv.norm_map]
let su := isoD ⁻¹' s
have hsu : UniqueDiffOn 𝕜 su := isoD.toContinuousLinearEquiv.uniqueDiffOn_preimage_iff.2 hs
let xu := isoD.symm x
have hxu : xu ∈ su := by
simpa only [xu, su, Set.mem_preimage, LinearIsometryEquiv.apply_symm_apply] using hx
have xu_x : isoD xu = x := by simp only [xu, LinearIsometryEquiv.apply_symm_apply]
have hfu : ContDiffOn 𝕜 n fu su :=
isoE.symm.contDiff.comp_contDiffOn
((hf.of_le hn).comp_continuousLinearMap (isoD : Du →L[𝕜] D))
have hgu : ContDiffOn 𝕜 n gu su :=
isoF.symm.contDiff.comp_contDiffOn
((hg.of_le hn).comp_continuousLinearMap (isoD : Du →L[𝕜] D))
have Nfu : ∀ i, ‖iteratedFDerivWithin 𝕜 i fu su xu‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
intro i
rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hsu hxu]
rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ hs, xu_x]
rwa [← xu_x] at hx
have Ngu : ∀ i, ‖iteratedFDerivWithin 𝕜 i gu su xu‖ = ‖iteratedFDerivWithin 𝕜 i g s x‖ := by
intro i
rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hsu hxu]
rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ hs, xu_x]
rwa [← xu_x] at hx
have NBu :
‖iteratedFDerivWithin 𝕜 n (fun y => Bu (fu y) (gu y)) su xu‖ =
‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ := by
rw [Bu_eq]
rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hsu hxu]
rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ hs, xu_x]
rwa [← xu_x] at hx
-- state the bound for the lifted objects, and deduce the original bound from it.
have : ‖iteratedFDerivWithin 𝕜 n (fun y => Bu (fu y) (gu y)) su xu‖ ≤
‖Bu‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i fu su xu‖ *
‖iteratedFDerivWithin 𝕜 (n - i) gu su xu‖ :=
Bu.norm_iteratedFDerivWithin_le_of_bilinear_aux hfu hgu hsu hxu
simp only [Nfu, Ngu, NBu] at this
exact this.trans (mul_le_mul_of_nonneg_right Bu_le (by positivity))
#align continuous_linear_map.norm_iterated_fderiv_within_le_of_bilinear ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear
/-- Bounding the norm of the iterated derivative of `B (f x) (g x)` in terms of the
iterated derivatives of `f` and `g` when `B` is bilinear:
`‖D^n (x ↦ B (f x) (g x))‖ ≤ ‖B‖ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/
theorem ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear (B : E →L[𝕜] F →L[𝕜] G) {f : D → E}
{g : D → F} {N : ℕ∞} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : D) {n : ℕ}
(hn : (n : ℕ∞) ≤ N) :
‖iteratedFDeriv 𝕜 n (fun y => B (f y) (g y)) x‖ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1),
(n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by
simp_rw [← iteratedFDerivWithin_univ]
exact B.norm_iteratedFDerivWithin_le_of_bilinear hf.contDiffOn hg.contDiffOn uniqueDiffOn_univ
(mem_univ x) hn
#align continuous_linear_map.norm_iterated_fderiv_le_of_bilinear ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear
/-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the
iterated derivatives of `f` and `g` when `B` is bilinear of norm at most `1`:
`‖D^n (x ↦ B (f x) (g x))‖ ≤ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/
theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_of_le_one
(B : E →L[𝕜] F →L[𝕜] G) {f : D → E} {g : D → F} {N : ℕ∞} {s : Set D} {x : D}
(hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {n : ℕ}
(hn : (n : ℕ∞) ≤ N) (hB : ‖B‖ ≤ 1) : ‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤
∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by
apply (B.norm_iteratedFDerivWithin_le_of_bilinear hf hg hs hx hn).trans
exact mul_le_of_le_one_left (by positivity) hB
#align continuous_linear_map.norm_iterated_fderiv_within_le_of_bilinear_of_le_one ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_of_le_one
/-- Bounding the norm of the iterated derivative of `B (f x) (g x)` in terms of the
iterated derivatives of `f` and `g` when `B` is bilinear of norm at most `1`:
`‖D^n (x ↦ B (f x) (g x))‖ ≤ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/
theorem ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear_of_le_one (B : E →L[𝕜] F →L[𝕜] G)
{f : D → E} {g : D → F} {N : ℕ∞} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : D) {n : ℕ}
(hn : (n : ℕ∞) ≤ N) (hB : ‖B‖ ≤ 1) : ‖iteratedFDeriv 𝕜 n (fun y => B (f y) (g y)) x‖ ≤
∑ i ∈ Finset.range (n + 1),
(n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by
simp_rw [← iteratedFDerivWithin_univ]
exact B.norm_iteratedFDerivWithin_le_of_bilinear_of_le_one hf.contDiffOn hg.contDiffOn
uniqueDiffOn_univ (mem_univ x) hn hB
#align continuous_linear_map.norm_iterated_fderiv_le_of_bilinear_of_le_one ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear_of_le_one
section
variable {𝕜' : Type*} [NormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F]
[IsScalarTower 𝕜 𝕜' F]
theorem norm_iteratedFDerivWithin_smul_le {f : E → 𝕜'} {g : E → F} {N : ℕ∞}
(hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) {x : E} (hx : x ∈ s)
{n : ℕ} (hn : (n : ℕ∞) ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y => f y • g y) s x‖ ≤
∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
(ContinuousLinearMap.lsmul 𝕜 𝕜' :
𝕜' →L[𝕜] F →L[𝕜] F).norm_iteratedFDerivWithin_le_of_bilinear_of_le_one
hf hg hs hx hn ContinuousLinearMap.opNorm_lsmul_le
#align norm_iterated_fderiv_within_smul_le norm_iteratedFDerivWithin_smul_le
theorem norm_iteratedFDeriv_smul_le {f : E → 𝕜'} {g : E → F} {N : ℕ∞} (hf : ContDiff 𝕜 N f)
(hg : ContDiff 𝕜 N g) (x : E) {n : ℕ} (hn : (n : ℕ∞) ≤ N) :
‖iteratedFDeriv 𝕜 n (fun y => f y • g y) x‖ ≤ ∑ i ∈ Finset.range (n + 1),
(n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ :=
(ContinuousLinearMap.lsmul 𝕜 𝕜' : 𝕜' →L[𝕜] F →L[𝕜] F).norm_iteratedFDeriv_le_of_bilinear_of_le_one
hf hg x hn ContinuousLinearMap.opNorm_lsmul_le
#align norm_iterated_fderiv_smul_le norm_iteratedFDeriv_smul_le
end
section
variable {ι : Type*} {A : Type*} [NormedRing A] [NormedAlgebra 𝕜 A] {A' : Type*} [NormedCommRing A']
[NormedAlgebra 𝕜 A']
theorem norm_iteratedFDerivWithin_mul_le {f : E → A} {g : E → A} {N : ℕ∞} (hf : ContDiffOn 𝕜 N f s)
(hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) {x : E} (hx : x ∈ s) {n : ℕ}
(hn : (n : ℕ∞) ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y => f y * g y) s x‖ ≤
∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
(ContinuousLinearMap.mul 𝕜 A :
A →L[𝕜] A →L[𝕜] A).norm_iteratedFDerivWithin_le_of_bilinear_of_le_one
hf hg hs hx hn (ContinuousLinearMap.opNorm_mul_le _ _)
#align norm_iterated_fderiv_within_mul_le norm_iteratedFDerivWithin_mul_le
theorem norm_iteratedFDeriv_mul_le {f : E → A} {g : E → A} {N : ℕ∞} (hf : ContDiff 𝕜 N f)
(hg : ContDiff 𝕜 N g) (x : E) {n : ℕ} (hn : (n : ℕ∞) ≤ N) :
‖iteratedFDeriv 𝕜 n (fun y => f y * g y) x‖ ≤ ∑ i ∈ Finset.range (n + 1),
(n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by
simp_rw [← iteratedFDerivWithin_univ]
exact norm_iteratedFDerivWithin_mul_le
hf.contDiffOn hg.contDiffOn uniqueDiffOn_univ (mem_univ x) hn
#align norm_iterated_fderiv_mul_le norm_iteratedFDeriv_mul_le
-- TODO: Add `norm_iteratedFDeriv[Within]_list_prod_le` for non-commutative `NormedRing A`.
theorem norm_iteratedFDerivWithin_prod_le [DecidableEq ι] [NormOneClass A'] {u : Finset ι}
{f : ι → E → A'} {N : ℕ∞} (hf : ∀ i ∈ u, ContDiffOn 𝕜 N (f i) s) (hs : UniqueDiffOn 𝕜 s) {x : E}
(hx : x ∈ s) {n : ℕ} (hn : (n : ℕ∞) ≤ N) :
‖iteratedFDerivWithin 𝕜 n (∏ j ∈ u, f j ·) s x‖ ≤
∑ p ∈ u.sym n, (p : Multiset ι).multinomial *
∏ j ∈ u, ‖iteratedFDerivWithin 𝕜 (Multiset.count j p) (f j) s x‖ := by
induction u using Finset.induction generalizing n with
| empty =>
cases n with
| zero => simp [Sym.eq_nil_of_card_zero]
| succ n => simp [iteratedFDerivWithin_succ_const _ _ hs hx]
| @insert i u hi IH =>
conv => lhs; simp only [Finset.prod_insert hi]
simp only [Finset.mem_insert, forall_eq_or_imp] at hf
refine le_trans (norm_iteratedFDerivWithin_mul_le hf.1 (contDiffOn_prod hf.2) hs hx hn) ?_
rw [← Finset.sum_coe_sort (Finset.sym _ _)]
rw [Finset.sum_equiv (Finset.symInsertEquiv hi) (t := Finset.univ)
(g := (fun v ↦ v.multinomial *
∏ j ∈ insert i u, ‖iteratedFDerivWithin 𝕜 (v.count j) (f j) s x‖) ∘
Sym.toMultiset ∘ Subtype.val ∘ (Finset.symInsertEquiv hi).symm)
(by simp) (by simp only [← comp_apply (g := Finset.symInsertEquiv hi), comp.assoc]; simp)]
rw [← Finset.univ_sigma_univ, Finset.sum_sigma, Finset.sum_range]
simp only [comp_apply, Finset.symInsertEquiv_symm_apply_coe]
refine Finset.sum_le_sum ?_
intro m _
specialize IH hf.2 (n := n - m) (le_trans (WithTop.coe_le_coe.mpr (n.sub_le m)) hn)
refine le_trans (mul_le_mul_of_nonneg_left IH (by simp [mul_nonneg])) ?_
rw [Finset.mul_sum, ← Finset.sum_coe_sort]
refine Finset.sum_le_sum ?_
simp only [Finset.mem_univ, forall_true_left, Subtype.forall, Finset.mem_sym_iff]
intro p hp
refine le_of_eq ?_
rw [Finset.prod_insert hi]
have hip : i ∉ p := mt (hp i) hi
rw [Sym.count_coe_fill_self_of_not_mem hip, Sym.multinomial_coe_fill_of_not_mem hip]
suffices ∏ j ∈ u, ‖iteratedFDerivWithin 𝕜 (Multiset.count j p) (f j) s x‖ =
∏ j ∈ u, ‖iteratedFDerivWithin 𝕜 (Multiset.count j (Sym.fill i m p)) (f j) s x‖ by
rw [this, Nat.cast_mul]
ring
refine Finset.prod_congr rfl ?_
intro j hj
have hji : j ≠ i := mt (· ▸ hj) hi
rw [Sym.count_coe_fill_of_ne hji]
| Mathlib/Analysis/Calculus/ContDiff/Bounds.lean | 342 | 350 | theorem norm_iteratedFDeriv_prod_le [DecidableEq ι] [NormOneClass A'] {u : Finset ι}
{f : ι → E → A'} {N : ℕ∞} (hf : ∀ i ∈ u, ContDiff 𝕜 N (f i)) {x : E} {n : ℕ}
(hn : (n : ℕ∞) ≤ N) :
‖iteratedFDeriv 𝕜 n (∏ j ∈ u, f j ·) x‖ ≤
∑ p ∈ u.sym n, (p : Multiset ι).multinomial *
∏ j ∈ u, ‖iteratedFDeriv 𝕜 ((p : Multiset ι).count j) (f j) x‖ := by |
simpa [iteratedFDerivWithin_univ] using
norm_iteratedFDerivWithin_prod_le (fun i hi ↦ (hf i hi).contDiffOn) uniqueDiffOn_univ
(mem_univ x) hn
|
/-
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.Content
import Mathlib.MeasureTheory.Group.Prod
import Mathlib.Topology.Algebra.Group.Compact
#align_import measure_theory.measure.haar.basic from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Haar measure
In this file we prove the existence of Haar measure for a locally compact Hausdorff topological
group.
We follow the write-up by Jonathan Gleason, *Existence and Uniqueness of Haar Measure*.
This is essentially the same argument as in
https://en.wikipedia.org/wiki/Haar_measure#A_construction_using_compact_subsets.
We construct the Haar measure first on compact sets. For this we define `(K : U)` as the (smallest)
number of left-translates of `U` that are needed to cover `K` (`index` in the formalization).
Then we define a function `h` on compact sets as `lim_U (K : U) / (K₀ : U)`,
where `U` becomes a smaller and smaller open neighborhood of `1`, and `K₀` is a fixed compact set
with nonempty interior. This function is `chaar` in the formalization, and we define the limit
formally using Tychonoff's theorem.
This function `h` forms a content, which we can extend to an outer measure and then a measure
(`haarMeasure`).
We normalize the Haar measure so that the measure of `K₀` is `1`.
Note that `μ` need not coincide with `h` on compact sets, according to
[halmos1950measure, ch. X, §53 p.233]. However, we know that `h(K)` lies between `μ(Kᵒ)` and `μ(K)`,
where `ᵒ` denotes the interior.
We also give a form of uniqueness of Haar measure, for σ-finite measures on second-countable
locally compact groups. For more involved statements not assuming second-countability, see
the file `MeasureTheory.Measure.Haar.Unique`.
## Main Declarations
* `haarMeasure`: the Haar measure on a locally compact Hausdorff group. This is a left invariant
regular measure. It takes as argument a compact set of the group (with non-empty interior),
and is normalized so that the measure of the given set is 1.
* `haarMeasure_self`: the Haar measure is normalized.
* `isMulLeftInvariant_haarMeasure`: the Haar measure is left invariant.
* `regular_haarMeasure`: the Haar measure is a regular measure.
* `isHaarMeasure_haarMeasure`: the Haar measure satisfies the `IsHaarMeasure` typeclass, i.e.,
it is invariant and gives finite mass to compact sets and positive mass to nonempty open sets.
* `haar` : some choice of a Haar measure, on a locally compact Hausdorff group, constructed as
`haarMeasure K` where `K` is some arbitrary choice of a compact set with nonempty interior.
* `haarMeasure_unique`: Every σ-finite left invariant measure on a second-countable locally compact
Hausdorff group is a scalar multiple of the Haar measure.
## References
* Paul Halmos (1950), Measure Theory, §53
* Jonathan Gleason, Existence and Uniqueness of Haar Measure
- Note: step 9, page 8 contains a mistake: the last defined `μ` does not extend the `μ` on compact
sets, see Halmos (1950) p. 233, bottom of the page. This makes some other steps (like step 11)
invalid.
* https://en.wikipedia.org/wiki/Haar_measure
-/
noncomputable section
open Set Inv Function TopologicalSpace MeasurableSpace
open scoped NNReal Classical ENNReal Pointwise Topology
namespace MeasureTheory
namespace Measure
section Group
variable {G : Type*} [Group G]
/-! We put the internal functions in the construction of the Haar measure in a namespace,
so that the chosen names don't clash with other declarations.
We first define a couple of the functions before proving the properties (that require that `G`
is a topological group). -/
namespace haar
-- Porting note: Even in `noncomputable section`, a definition with `to_additive` require
-- `noncomputable` to generate an additive definition.
-- Please refer to leanprover/lean4#2077.
/-- The index or Haar covering number or ratio of `K` w.r.t. `V`, denoted `(K : V)`:
it is the smallest number of (left) translates of `V` that is necessary to cover `K`.
It is defined to be 0 if no finite number of translates cover `K`. -/
@[to_additive addIndex "additive version of `MeasureTheory.Measure.haar.index`"]
noncomputable def index (K V : Set G) : ℕ :=
sInf <| Finset.card '' { t : Finset G | K ⊆ ⋃ g ∈ t, (fun h => g * h) ⁻¹' V }
#align measure_theory.measure.haar.index MeasureTheory.Measure.haar.index
#align measure_theory.measure.haar.add_index MeasureTheory.Measure.haar.addIndex
@[to_additive addIndex_empty]
theorem index_empty {V : Set G} : index ∅ V = 0 := by
simp only [index, Nat.sInf_eq_zero]; left; use ∅
simp only [Finset.card_empty, empty_subset, mem_setOf_eq, eq_self_iff_true, and_self_iff]
#align measure_theory.measure.haar.index_empty MeasureTheory.Measure.haar.index_empty
#align measure_theory.measure.haar.add_index_empty MeasureTheory.Measure.haar.addIndex_empty
variable [TopologicalSpace G]
/-- `prehaar K₀ U K` is a weighted version of the index, defined as `(K : U)/(K₀ : U)`.
In the applications `K₀` is compact with non-empty interior, `U` is open containing `1`,
and `K` is any compact set.
The argument `K` is a (bundled) compact set, so that we can consider `prehaar K₀ U` as an
element of `haarProduct` (below). -/
@[to_additive "additive version of `MeasureTheory.Measure.haar.prehaar`"]
noncomputable def prehaar (K₀ U : Set G) (K : Compacts G) : ℝ :=
(index (K : Set G) U : ℝ) / index K₀ U
#align measure_theory.measure.haar.prehaar MeasureTheory.Measure.haar.prehaar
#align measure_theory.measure.haar.add_prehaar MeasureTheory.Measure.haar.addPrehaar
@[to_additive]
theorem prehaar_empty (K₀ : PositiveCompacts G) {U : Set G} : prehaar (K₀ : Set G) U ⊥ = 0 := by
rw [prehaar, Compacts.coe_bot, index_empty, Nat.cast_zero, zero_div]
#align measure_theory.measure.haar.prehaar_empty MeasureTheory.Measure.haar.prehaar_empty
#align measure_theory.measure.haar.add_prehaar_empty MeasureTheory.Measure.haar.addPrehaar_empty
@[to_additive]
theorem prehaar_nonneg (K₀ : PositiveCompacts G) {U : Set G} (K : Compacts G) :
0 ≤ prehaar (K₀ : Set G) U K := by apply div_nonneg <;> norm_cast <;> apply zero_le
#align measure_theory.measure.haar.prehaar_nonneg MeasureTheory.Measure.haar.prehaar_nonneg
#align measure_theory.measure.haar.add_prehaar_nonneg MeasureTheory.Measure.haar.addPrehaar_nonneg
/-- `haarProduct K₀` is the product of intervals `[0, (K : K₀)]`, for all compact sets `K`.
For all `U`, we can show that `prehaar K₀ U ∈ haarProduct K₀`. -/
@[to_additive "additive version of `MeasureTheory.Measure.haar.haarProduct`"]
def haarProduct (K₀ : Set G) : Set (Compacts G → ℝ) :=
pi univ fun K => Icc 0 <| index (K : Set G) K₀
#align measure_theory.measure.haar.haar_product MeasureTheory.Measure.haar.haarProduct
#align measure_theory.measure.haar.add_haar_product MeasureTheory.Measure.haar.addHaarProduct
@[to_additive (attr := simp)]
theorem mem_prehaar_empty {K₀ : Set G} {f : Compacts G → ℝ} :
f ∈ haarProduct K₀ ↔ ∀ K : Compacts G, f K ∈ Icc (0 : ℝ) (index (K : Set G) K₀) := by
simp only [haarProduct, Set.pi, forall_prop_of_true, mem_univ, mem_setOf_eq]
#align measure_theory.measure.haar.mem_prehaar_empty MeasureTheory.Measure.haar.mem_prehaar_empty
#align measure_theory.measure.haar.mem_add_prehaar_empty MeasureTheory.Measure.haar.mem_addPrehaar_empty
/-- The closure of the collection of elements of the form `prehaar K₀ U`,
for `U` open neighbourhoods of `1`, contained in `V`. The closure is taken in the space
`compacts G → ℝ`, with the topology of pointwise convergence.
We show that the intersection of all these sets is nonempty, and the Haar measure
on compact sets is defined to be an element in the closure of this intersection. -/
@[to_additive "additive version of `MeasureTheory.Measure.haar.clPrehaar`"]
def clPrehaar (K₀ : Set G) (V : OpenNhdsOf (1 : G)) : Set (Compacts G → ℝ) :=
closure <| prehaar K₀ '' { U : Set G | U ⊆ V.1 ∧ IsOpen U ∧ (1 : G) ∈ U }
#align measure_theory.measure.haar.cl_prehaar MeasureTheory.Measure.haar.clPrehaar
#align measure_theory.measure.haar.cl_add_prehaar MeasureTheory.Measure.haar.clAddPrehaar
variable [TopologicalGroup G]
/-!
### Lemmas about `index`
-/
/-- If `K` is compact and `V` has nonempty interior, then the index `(K : V)` is well-defined,
there is a finite set `t` satisfying the desired properties. -/
@[to_additive addIndex_defined
"If `K` is compact and `V` has nonempty interior, then the index `(K : V)` is well-defined, there is
a finite set `t` satisfying the desired properties."]
theorem index_defined {K V : Set G} (hK : IsCompact K) (hV : (interior V).Nonempty) :
∃ n : ℕ, n ∈ Finset.card '' { t : Finset G | K ⊆ ⋃ g ∈ t, (fun h => g * h) ⁻¹' V } := by
rcases compact_covered_by_mul_left_translates hK hV with ⟨t, ht⟩; exact ⟨t.card, t, ht, rfl⟩
#align measure_theory.measure.haar.index_defined MeasureTheory.Measure.haar.index_defined
#align measure_theory.measure.haar.add_index_defined MeasureTheory.Measure.haar.addIndex_defined
@[to_additive addIndex_elim]
theorem index_elim {K V : Set G} (hK : IsCompact K) (hV : (interior V).Nonempty) :
∃ t : Finset G, (K ⊆ ⋃ g ∈ t, (fun h => g * h) ⁻¹' V) ∧ Finset.card t = index K V := by
have := Nat.sInf_mem (index_defined hK hV); rwa [mem_image] at this
#align measure_theory.measure.haar.index_elim MeasureTheory.Measure.haar.index_elim
#align measure_theory.measure.haar.add_index_elim MeasureTheory.Measure.haar.addIndex_elim
@[to_additive le_addIndex_mul]
theorem le_index_mul (K₀ : PositiveCompacts G) (K : Compacts G) {V : Set G}
(hV : (interior V).Nonempty) :
index (K : Set G) V ≤ index (K : Set G) K₀ * index (K₀ : Set G) V := by
obtain ⟨s, h1s, h2s⟩ := index_elim K.isCompact K₀.interior_nonempty
obtain ⟨t, h1t, h2t⟩ := index_elim K₀.isCompact hV
rw [← h2s, ← h2t, mul_comm]
refine le_trans ?_ Finset.card_mul_le
apply Nat.sInf_le; refine ⟨_, ?_, rfl⟩; rw [mem_setOf_eq]; refine Subset.trans h1s ?_
apply iUnion₂_subset; intro g₁ hg₁; rw [preimage_subset_iff]; intro g₂ hg₂
have := h1t hg₂
rcases this with ⟨_, ⟨g₃, rfl⟩, A, ⟨hg₃, rfl⟩, h2V⟩; rw [mem_preimage, ← mul_assoc] at h2V
exact mem_biUnion (Finset.mul_mem_mul hg₃ hg₁) h2V
#align measure_theory.measure.haar.le_index_mul MeasureTheory.Measure.haar.le_index_mul
#align measure_theory.measure.haar.le_add_index_mul MeasureTheory.Measure.haar.le_addIndex_mul
@[to_additive addIndex_pos]
theorem index_pos (K : PositiveCompacts G) {V : Set G} (hV : (interior V).Nonempty) :
0 < index (K : Set G) V := by
unfold index; rw [Nat.sInf_def, Nat.find_pos, mem_image]
· rintro ⟨t, h1t, h2t⟩; rw [Finset.card_eq_zero] at h2t; subst h2t
obtain ⟨g, hg⟩ := K.interior_nonempty
show g ∈ (∅ : Set G)
convert h1t (interior_subset hg); symm
simp only [Finset.not_mem_empty, iUnion_of_empty, iUnion_empty]
· exact index_defined K.isCompact hV
#align measure_theory.measure.haar.index_pos MeasureTheory.Measure.haar.index_pos
#align measure_theory.measure.haar.add_index_pos MeasureTheory.Measure.haar.addIndex_pos
@[to_additive addIndex_mono]
theorem index_mono {K K' V : Set G} (hK' : IsCompact K') (h : K ⊆ K') (hV : (interior V).Nonempty) :
index K V ≤ index K' V := by
rcases index_elim hK' hV with ⟨s, h1s, h2s⟩
apply Nat.sInf_le; rw [mem_image]; exact ⟨s, Subset.trans h h1s, h2s⟩
#align measure_theory.measure.haar.index_mono MeasureTheory.Measure.haar.index_mono
#align measure_theory.measure.haar.add_index_mono MeasureTheory.Measure.haar.addIndex_mono
@[to_additive addIndex_union_le]
theorem index_union_le (K₁ K₂ : Compacts G) {V : Set G} (hV : (interior V).Nonempty) :
index (K₁.1 ∪ K₂.1) V ≤ index K₁.1 V + index K₂.1 V := by
rcases index_elim K₁.2 hV with ⟨s, h1s, h2s⟩
rcases index_elim K₂.2 hV with ⟨t, h1t, h2t⟩
rw [← h2s, ← h2t]
refine le_trans ?_ (Finset.card_union_le _ _)
apply Nat.sInf_le; refine ⟨_, ?_, rfl⟩; rw [mem_setOf_eq]
apply union_subset <;> refine Subset.trans (by assumption) ?_ <;>
apply biUnion_subset_biUnion_left <;> intro g hg <;> simp only [mem_def] at hg <;>
simp only [mem_def, Multiset.mem_union, Finset.union_val, hg, or_true_iff, true_or_iff]
#align measure_theory.measure.haar.index_union_le MeasureTheory.Measure.haar.index_union_le
#align measure_theory.measure.haar.add_index_union_le MeasureTheory.Measure.haar.addIndex_union_le
@[to_additive addIndex_union_eq]
theorem index_union_eq (K₁ K₂ : Compacts G) {V : Set G} (hV : (interior V).Nonempty)
(h : Disjoint (K₁.1 * V⁻¹) (K₂.1 * V⁻¹)) :
index (K₁.1 ∪ K₂.1) V = index K₁.1 V + index K₂.1 V := by
apply le_antisymm (index_union_le K₁ K₂ hV)
rcases index_elim (K₁.2.union K₂.2) hV with ⟨s, h1s, h2s⟩; rw [← h2s]
have :
∀ K : Set G,
(K ⊆ ⋃ g ∈ s, (fun h => g * h) ⁻¹' V) →
index K V ≤ (s.filter fun g => ((fun h : G => g * h) ⁻¹' V ∩ K).Nonempty).card := by
intro K hK; apply Nat.sInf_le; refine ⟨_, ?_, rfl⟩; rw [mem_setOf_eq]
intro g hg; rcases hK hg with ⟨_, ⟨g₀, rfl⟩, _, ⟨h1g₀, rfl⟩, h2g₀⟩
simp only [mem_preimage] at h2g₀
simp only [mem_iUnion]; use g₀; constructor; swap
· simp only [Finset.mem_filter, h1g₀, true_and_iff]; use g
simp only [hg, h2g₀, mem_inter_iff, mem_preimage, and_self_iff]
exact h2g₀
refine
le_trans
(add_le_add (this K₁.1 <| Subset.trans subset_union_left h1s)
(this K₂.1 <| Subset.trans subset_union_right h1s)) ?_
rw [← Finset.card_union_of_disjoint, Finset.filter_union_right]
· exact s.card_filter_le _
apply Finset.disjoint_filter.mpr
rintro g₁ _ ⟨g₂, h1g₂, h2g₂⟩ ⟨g₃, h1g₃, h2g₃⟩
simp only [mem_preimage] at h1g₃ h1g₂
refine h.le_bot (?_ : g₁⁻¹ ∈ _)
constructor <;> simp only [Set.mem_inv, Set.mem_mul, exists_exists_and_eq_and, exists_and_left]
· refine ⟨_, h2g₂, (g₁ * g₂)⁻¹, ?_, ?_⟩
· simp only [inv_inv, h1g₂]
· simp only [mul_inv_rev, mul_inv_cancel_left]
· refine ⟨_, h2g₃, (g₁ * g₃)⁻¹, ?_, ?_⟩
· simp only [inv_inv, h1g₃]
· simp only [mul_inv_rev, mul_inv_cancel_left]
#align measure_theory.measure.haar.index_union_eq MeasureTheory.Measure.haar.index_union_eq
#align measure_theory.measure.haar.add_index_union_eq MeasureTheory.Measure.haar.addIndex_union_eq
@[to_additive add_left_addIndex_le]
theorem mul_left_index_le {K : Set G} (hK : IsCompact K) {V : Set G} (hV : (interior V).Nonempty)
(g : G) : index ((fun h => g * h) '' K) V ≤ index K V := by
rcases index_elim hK hV with ⟨s, h1s, h2s⟩; rw [← h2s]
apply Nat.sInf_le; rw [mem_image]
refine ⟨s.map (Equiv.mulRight g⁻¹).toEmbedding, ?_, Finset.card_map _⟩
simp only [mem_setOf_eq]; refine Subset.trans (image_subset _ h1s) ?_
rintro _ ⟨g₁, ⟨_, ⟨g₂, rfl⟩, ⟨_, ⟨hg₂, rfl⟩, hg₁⟩⟩, rfl⟩
simp only [mem_preimage] at hg₁;
simp only [exists_prop, mem_iUnion, Finset.mem_map, Equiv.coe_mulRight,
exists_exists_and_eq_and, mem_preimage, Equiv.toEmbedding_apply]
refine ⟨_, hg₂, ?_⟩; simp only [mul_assoc, hg₁, inv_mul_cancel_left]
#align measure_theory.measure.haar.mul_left_index_le MeasureTheory.Measure.haar.mul_left_index_le
#align measure_theory.measure.haar.add_left_add_index_le MeasureTheory.Measure.haar.add_left_addIndex_le
@[to_additive is_left_invariant_addIndex]
theorem is_left_invariant_index {K : Set G} (hK : IsCompact K) (g : G) {V : Set G}
(hV : (interior V).Nonempty) : index ((fun h => g * h) '' K) V = index K V := by
refine le_antisymm (mul_left_index_le hK hV g) ?_
convert mul_left_index_le (hK.image <| continuous_mul_left g) hV g⁻¹
rw [image_image]; symm; convert image_id' _ with h; apply inv_mul_cancel_left
#align measure_theory.measure.haar.is_left_invariant_index MeasureTheory.Measure.haar.is_left_invariant_index
#align measure_theory.measure.haar.is_left_invariant_add_index MeasureTheory.Measure.haar.is_left_invariant_addIndex
/-!
### Lemmas about `prehaar`
-/
@[to_additive add_prehaar_le_addIndex]
theorem prehaar_le_index (K₀ : PositiveCompacts G) {U : Set G} (K : Compacts G)
(hU : (interior U).Nonempty) : prehaar (K₀ : Set G) U K ≤ index (K : Set G) K₀ := by
unfold prehaar; rw [div_le_iff] <;> norm_cast
· apply le_index_mul K₀ K hU
· exact index_pos K₀ hU
#align measure_theory.measure.haar.prehaar_le_index MeasureTheory.Measure.haar.prehaar_le_index
#align measure_theory.measure.haar.add_prehaar_le_add_index MeasureTheory.Measure.haar.add_prehaar_le_addIndex
@[to_additive]
theorem prehaar_pos (K₀ : PositiveCompacts G) {U : Set G} (hU : (interior U).Nonempty) {K : Set G}
(h1K : IsCompact K) (h2K : (interior K).Nonempty) : 0 < prehaar (K₀ : Set G) U ⟨K, h1K⟩ := by
apply div_pos <;> norm_cast
· apply index_pos ⟨⟨K, h1K⟩, h2K⟩ hU
· exact index_pos K₀ hU
#align measure_theory.measure.haar.prehaar_pos MeasureTheory.Measure.haar.prehaar_pos
#align measure_theory.measure.haar.add_prehaar_pos MeasureTheory.Measure.haar.addPrehaar_pos
@[to_additive]
theorem prehaar_mono {K₀ : PositiveCompacts G} {U : Set G} (hU : (interior U).Nonempty)
{K₁ K₂ : Compacts G} (h : (K₁ : Set G) ⊆ K₂.1) :
prehaar (K₀ : Set G) U K₁ ≤ prehaar (K₀ : Set G) U K₂ := by
simp only [prehaar]; rw [div_le_div_right]
· exact mod_cast index_mono K₂.2 h hU
· exact mod_cast index_pos K₀ hU
#align measure_theory.measure.haar.prehaar_mono MeasureTheory.Measure.haar.prehaar_mono
#align measure_theory.measure.haar.add_prehaar_mono MeasureTheory.Measure.haar.addPrehaar_mono
@[to_additive]
theorem prehaar_self {K₀ : PositiveCompacts G} {U : Set G} (hU : (interior U).Nonempty) :
prehaar (K₀ : Set G) U K₀.toCompacts = 1 :=
div_self <| ne_of_gt <| mod_cast index_pos K₀ hU
#align measure_theory.measure.haar.prehaar_self MeasureTheory.Measure.haar.prehaar_self
#align measure_theory.measure.haar.add_prehaar_self MeasureTheory.Measure.haar.addPrehaar_self
@[to_additive]
theorem prehaar_sup_le {K₀ : PositiveCompacts G} {U : Set G} (K₁ K₂ : Compacts G)
(hU : (interior U).Nonempty) :
prehaar (K₀ : Set G) U (K₁ ⊔ K₂) ≤ prehaar (K₀ : Set G) U K₁ + prehaar (K₀ : Set G) U K₂ := by
simp only [prehaar]; rw [div_add_div_same, div_le_div_right]
· exact mod_cast index_union_le K₁ K₂ hU
· exact mod_cast index_pos K₀ hU
#align measure_theory.measure.haar.prehaar_sup_le MeasureTheory.Measure.haar.prehaar_sup_le
#align measure_theory.measure.haar.add_prehaar_sup_le MeasureTheory.Measure.haar.addPrehaar_sup_le
@[to_additive]
theorem prehaar_sup_eq {K₀ : PositiveCompacts G} {U : Set G} {K₁ K₂ : Compacts G}
(hU : (interior U).Nonempty) (h : Disjoint (K₁.1 * U⁻¹) (K₂.1 * U⁻¹)) :
prehaar (K₀ : Set G) U (K₁ ⊔ K₂) = prehaar (K₀ : Set G) U K₁ + prehaar (K₀ : Set G) U K₂ := by
simp only [prehaar]; rw [div_add_div_same]
-- Porting note: Here was `congr`, but `to_additive` failed to generate a theorem.
refine congr_arg (fun x : ℝ => x / index K₀ U) ?_
exact mod_cast index_union_eq K₁ K₂ hU h
#align measure_theory.measure.haar.prehaar_sup_eq MeasureTheory.Measure.haar.prehaar_sup_eq
#align measure_theory.measure.haar.add_prehaar_sup_eq MeasureTheory.Measure.haar.addPrehaar_sup_eq
@[to_additive]
theorem is_left_invariant_prehaar {K₀ : PositiveCompacts G} {U : Set G} (hU : (interior U).Nonempty)
(g : G) (K : Compacts G) :
prehaar (K₀ : Set G) U (K.map _ <| continuous_mul_left g) = prehaar (K₀ : Set G) U K := by
simp only [prehaar, Compacts.coe_map, is_left_invariant_index K.isCompact _ hU]
#align measure_theory.measure.haar.is_left_invariant_prehaar MeasureTheory.Measure.haar.is_left_invariant_prehaar
#align measure_theory.measure.haar.is_left_invariant_add_prehaar MeasureTheory.Measure.haar.is_left_invariant_addPrehaar
/-!
### Lemmas about `haarProduct`
-/
@[to_additive]
theorem prehaar_mem_haarProduct (K₀ : PositiveCompacts G) {U : Set G} (hU : (interior U).Nonempty) :
prehaar (K₀ : Set G) U ∈ haarProduct (K₀ : Set G) := by
rintro ⟨K, hK⟩ _; rw [mem_Icc]; exact ⟨prehaar_nonneg K₀ _, prehaar_le_index K₀ _ hU⟩
#align measure_theory.measure.haar.prehaar_mem_haar_product MeasureTheory.Measure.haar.prehaar_mem_haarProduct
#align measure_theory.measure.haar.add_prehaar_mem_add_haar_product MeasureTheory.Measure.haar.addPrehaar_mem_addHaarProduct
@[to_additive]
theorem nonempty_iInter_clPrehaar (K₀ : PositiveCompacts G) :
(haarProduct (K₀ : Set G) ∩ ⋂ V : OpenNhdsOf (1 : G), clPrehaar K₀ V).Nonempty := by
have : IsCompact (haarProduct (K₀ : Set G)) := by
apply isCompact_univ_pi; intro K; apply isCompact_Icc
refine this.inter_iInter_nonempty (clPrehaar K₀) (fun s => isClosed_closure) fun t => ?_
let V₀ := ⋂ V ∈ t, (V : OpenNhdsOf (1 : G)).carrier
have h1V₀ : IsOpen V₀ := isOpen_biInter_finset <| by rintro ⟨⟨V, hV₁⟩, hV₂⟩ _; exact hV₁
have h2V₀ : (1 : G) ∈ V₀ := by simp only [V₀, mem_iInter]; rintro ⟨⟨V, hV₁⟩, hV₂⟩ _; exact hV₂
refine ⟨prehaar K₀ V₀, ?_⟩
constructor
· apply prehaar_mem_haarProduct K₀; use 1; rwa [h1V₀.interior_eq]
· simp only [mem_iInter]; rintro ⟨V, hV⟩ h2V; apply subset_closure
apply mem_image_of_mem; rw [mem_setOf_eq]
exact ⟨Subset.trans (iInter_subset _ ⟨V, hV⟩) (iInter_subset _ h2V), h1V₀, h2V₀⟩
#align measure_theory.measure.haar.nonempty_Inter_cl_prehaar MeasureTheory.Measure.haar.nonempty_iInter_clPrehaar
#align measure_theory.measure.haar.nonempty_Inter_cl_add_prehaar MeasureTheory.Measure.haar.nonempty_iInter_clAddPrehaar
/-!
### Lemmas about `chaar`
-/
-- Porting note: Even in `noncomputable section`, a definition with `to_additive` require
-- `noncomputable` to generate an additive definition.
-- Please refer to leanprover/lean4#2077.
/-- This is the "limit" of `prehaar K₀ U K` as `U` becomes a smaller and smaller open
neighborhood of `(1 : G)`. More precisely, it is defined to be an arbitrary element
in the intersection of all the sets `clPrehaar K₀ V` in `haarProduct K₀`.
This is roughly equal to the Haar measure on compact sets,
but it can differ slightly. We do know that
`haarMeasure K₀ (interior K) ≤ chaar K₀ K ≤ haarMeasure K₀ K`. -/
@[to_additive addCHaar "additive version of `MeasureTheory.Measure.haar.chaar`"]
noncomputable def chaar (K₀ : PositiveCompacts G) (K : Compacts G) : ℝ :=
Classical.choose (nonempty_iInter_clPrehaar K₀) K
#align measure_theory.measure.haar.chaar MeasureTheory.Measure.haar.chaar
#align measure_theory.measure.haar.add_chaar MeasureTheory.Measure.haar.addCHaar
@[to_additive addCHaar_mem_addHaarProduct]
theorem chaar_mem_haarProduct (K₀ : PositiveCompacts G) : chaar K₀ ∈ haarProduct (K₀ : Set G) :=
(Classical.choose_spec (nonempty_iInter_clPrehaar K₀)).1
#align measure_theory.measure.haar.chaar_mem_haar_product MeasureTheory.Measure.haar.chaar_mem_haarProduct
#align measure_theory.measure.haar.add_chaar_mem_add_haar_product MeasureTheory.Measure.haar.addCHaar_mem_addHaarProduct
@[to_additive addCHaar_mem_clAddPrehaar]
theorem chaar_mem_clPrehaar (K₀ : PositiveCompacts G) (V : OpenNhdsOf (1 : G)) :
chaar K₀ ∈ clPrehaar (K₀ : Set G) V := by
have := (Classical.choose_spec (nonempty_iInter_clPrehaar K₀)).2; rw [mem_iInter] at this
exact this V
#align measure_theory.measure.haar.chaar_mem_cl_prehaar MeasureTheory.Measure.haar.chaar_mem_clPrehaar
#align measure_theory.measure.haar.add_chaar_mem_cl_add_prehaar MeasureTheory.Measure.haar.addCHaar_mem_clAddPrehaar
@[to_additive addCHaar_nonneg]
theorem chaar_nonneg (K₀ : PositiveCompacts G) (K : Compacts G) : 0 ≤ chaar K₀ K := by
have := chaar_mem_haarProduct K₀ K (mem_univ _); rw [mem_Icc] at this; exact this.1
#align measure_theory.measure.haar.chaar_nonneg MeasureTheory.Measure.haar.chaar_nonneg
#align measure_theory.measure.haar.add_chaar_nonneg MeasureTheory.Measure.haar.addCHaar_nonneg
@[to_additive addCHaar_empty]
| Mathlib/MeasureTheory/Measure/Haar/Basic.lean | 436 | 443 | theorem chaar_empty (K₀ : PositiveCompacts G) : chaar K₀ ⊥ = 0 := by |
let eval : (Compacts G → ℝ) → ℝ := fun f => f ⊥
have : Continuous eval := continuous_apply ⊥
show chaar K₀ ∈ eval ⁻¹' {(0 : ℝ)}
apply mem_of_subset_of_mem _ (chaar_mem_clPrehaar K₀ ⊤)
unfold clPrehaar; rw [IsClosed.closure_subset_iff]
· rintro _ ⟨U, _, rfl⟩; apply prehaar_empty
· apply continuous_iff_isClosed.mp this; exact isClosed_singleton
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Thomas Read, Andrew Yang, Dagur Asgeirsson, Joël Riou
-/
import Mathlib.CategoryTheory.Adjunction.Basic
/-!
# Uniqueness of adjoints
This file shows that adjoints are unique up to natural isomorphism.
## Main results
* `Adjunction.natTransEquiv` and `Adjunction.natIsoEquiv` If `F ⊣ G` and `F' ⊣ G'` are adjunctions,
then there are equivalences `(G ⟶ G') ≃ (F' ⟶ F)` and `(G ≅ G') ≃ (F' ≅ F)`.
Everything else is deduced from this:
* `Adjunction.leftAdjointUniq` : If `F` and `F'` are both left adjoint to `G`, then they are
naturally isomorphic.
* `Adjunction.rightAdjointUniq` : If `G` and `G'` are both right adjoint to `F`, then they are
naturally isomorphic.
-/
open CategoryTheory
variable {C D : Type*} [Category C] [Category D]
namespace CategoryTheory.Adjunction
/--
If `F ⊣ G` and `F' ⊣ G'` are adjunctions, then giving a natural transformation `G ⟶ G'` is the
same as giving a natural transformation `F' ⟶ F`.
-/
@[simps]
def natTransEquiv {F F' : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G') :
(G ⟶ G') ≃ (F' ⟶ F) where
toFun f := {
app := fun X ↦ F'.map ((adj1.unit ≫ whiskerLeft F f).app X) ≫ adj2.counit.app _
naturality := by
intro X Y g
simp only [← Category.assoc, ← Functor.map_comp]
erw [(adj1.unit ≫ (whiskerLeft F f)).naturality]
simp
}
invFun f := {
app := fun X ↦ adj2.unit.app (G.obj X) ≫ G'.map (f.app (G.obj X) ≫ adj1.counit.app X)
naturality := by
intro X Y g
erw [← adj2.unit_naturality_assoc]
simp only [← Functor.map_comp]
simp
}
left_inv f := by
ext X
simp only [Functor.comp_obj, NatTrans.comp_app, Functor.id_obj, whiskerLeft_app,
Functor.map_comp, Category.assoc, unit_naturality_assoc, right_triangle_components_assoc]
erw [← f.naturality (adj1.counit.app X), ← Category.assoc]
simp
right_inv f := by
ext
simp
@[simp]
lemma natTransEquiv_id {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) :
natTransEquiv adj adj (𝟙 _) = 𝟙 _ := by ext; simp
@[simp]
lemma natTransEquiv_id_symm {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) :
(natTransEquiv adj adj).symm (𝟙 _) = 𝟙 _ := by ext; simp
@[simp]
lemma natTransEquiv_comp {F F' F'' : C ⥤ D} {G G' G'' : D ⥤ C}
(adj1 : F ⊣ G) (adj2 : F' ⊣ G') (adj3 : F'' ⊣ G'') (f : G ⟶ G') (g : G' ⟶ G'') :
natTransEquiv adj2 adj3 g ≫ natTransEquiv adj1 adj2 f = natTransEquiv adj1 adj3 (f ≫ g) := by
apply (natTransEquiv adj1 adj3).symm.injective
ext X
simp only [natTransEquiv_symm_apply_app, Functor.comp_obj, NatTrans.comp_app,
natTransEquiv_apply_app, Functor.id_obj, whiskerLeft_app, Functor.map_comp, Category.assoc,
unit_naturality_assoc, right_triangle_components_assoc, Equiv.symm_apply_apply,
← g.naturality_assoc, ← g.naturality]
simp only [← Category.assoc, unit_naturality, Functor.comp_obj, right_triangle_components,
Category.comp_id, ← f.naturality, Category.id_comp]
@[simp]
lemma natTransEquiv_comp_symm {F F' F'' : C ⥤ D} {G G' G'' : D ⥤ C}
(adj1 : F ⊣ G) (adj2 : F' ⊣ G') (adj3 : F'' ⊣ G'') (f : F' ⟶ F) (g : F'' ⟶ F') :
(natTransEquiv adj1 adj2).symm f ≫ (natTransEquiv adj2 adj3).symm g =
(natTransEquiv adj1 adj3).symm (g ≫ f) := by
apply (natTransEquiv adj1 adj3).injective
ext
simp
/--
If `F ⊣ G` and `F' ⊣ G'` are adjunctions, then giving a natural isomorphism `G ≅ G'` is the
same as giving a natural transformation `F' ≅ F`.
-/
@[simps]
def natIsoEquiv {F F' : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G') :
(G ≅ G') ≃ (F' ≅ F) where
toFun i := {
hom := natTransEquiv adj1 adj2 i.hom
inv := natTransEquiv adj2 adj1 i.inv
}
invFun i := {
hom := (natTransEquiv adj1 adj2).symm i.hom
inv := (natTransEquiv adj2 adj1).symm i.inv }
left_inv i := by simp
right_inv i := by simp
/-- If `F` and `F'` are both left adjoint to `G`, then they are naturally isomorphic. -/
def leftAdjointUniq {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) : F ≅ F' :=
(natIsoEquiv adj1 adj2 (Iso.refl _)).symm
#align category_theory.adjunction.left_adjoint_uniq CategoryTheory.Adjunction.leftAdjointUniq
-- Porting note (#10618): removed simp as simp can prove this
theorem homEquiv_leftAdjointUniq_hom_app {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(x : C) : adj1.homEquiv _ _ ((leftAdjointUniq adj1 adj2).hom.app x) = adj2.unit.app x := by
simp [leftAdjointUniq]
#align category_theory.adjunction.hom_equiv_left_adjoint_uniq_hom_app CategoryTheory.Adjunction.homEquiv_leftAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem unit_leftAdjointUniq_hom {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) :
adj1.unit ≫ whiskerRight (leftAdjointUniq adj1 adj2).hom G = adj2.unit := by
ext x
rw [NatTrans.comp_app, ← homEquiv_leftAdjointUniq_hom_app adj1 adj2]
simp [← G.map_comp]
#align category_theory.adjunction.unit_left_adjoint_uniq_hom CategoryTheory.Adjunction.unit_leftAdjointUniq_hom
@[reassoc (attr := simp)]
theorem unit_leftAdjointUniq_hom_app
{F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) (x : C) :
adj1.unit.app x ≫ G.map ((leftAdjointUniq adj1 adj2).hom.app x) = adj2.unit.app x := by
rw [← unit_leftAdjointUniq_hom adj1 adj2]; rfl
#align category_theory.adjunction.unit_left_adjoint_uniq_hom_app CategoryTheory.Adjunction.unit_leftAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem leftAdjointUniq_hom_counit {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) :
whiskerLeft G (leftAdjointUniq adj1 adj2).hom ≫ adj2.counit = adj1.counit := by
ext x
simp only [Functor.comp_obj, Functor.id_obj, leftAdjointUniq, Iso.symm_hom, natIsoEquiv_apply_inv,
Iso.refl_inv, NatTrans.comp_app, whiskerLeft_app, natTransEquiv_apply_app, whiskerLeft_id',
Category.comp_id, Category.assoc]
rw [← adj1.counit_naturality, ← Category.assoc, ← F.map_comp]
simp
#align category_theory.adjunction.left_adjoint_uniq_hom_counit CategoryTheory.Adjunction.leftAdjointUniq_hom_counit
@[reassoc (attr := simp)]
theorem leftAdjointUniq_hom_app_counit {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(x : D) :
(leftAdjointUniq adj1 adj2).hom.app (G.obj x) ≫ adj2.counit.app x = adj1.counit.app x := by
rw [← leftAdjointUniq_hom_counit adj1 adj2]
rfl
#align category_theory.adjunction.left_adjoint_uniq_hom_app_counit CategoryTheory.Adjunction.leftAdjointUniq_hom_app_counit
theorem leftAdjointUniq_inv_app {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) (x : C) :
(leftAdjointUniq adj1 adj2).inv.app x = (leftAdjointUniq adj2 adj1).hom.app x :=
rfl
#align category_theory.adjunction.left_adjoint_uniq_inv_app CategoryTheory.Adjunction.leftAdjointUniq_inv_app
@[reassoc (attr := simp)]
theorem leftAdjointUniq_trans {F F' F'' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(adj3 : F'' ⊣ G) :
(leftAdjointUniq adj1 adj2).hom ≫ (leftAdjointUniq adj2 adj3).hom =
(leftAdjointUniq adj1 adj3).hom := by
simp [leftAdjointUniq]
#align category_theory.adjunction.left_adjoint_uniq_trans CategoryTheory.Adjunction.leftAdjointUniq_trans
@[reassoc (attr := simp)]
theorem leftAdjointUniq_trans_app {F F' F'' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(adj3 : F'' ⊣ G) (x : C) :
(leftAdjointUniq adj1 adj2).hom.app x ≫ (leftAdjointUniq adj2 adj3).hom.app x =
(leftAdjointUniq adj1 adj3).hom.app x := by
rw [← leftAdjointUniq_trans adj1 adj2 adj3]
rfl
#align category_theory.adjunction.left_adjoint_uniq_trans_app CategoryTheory.Adjunction.leftAdjointUniq_trans_app
@[simp]
theorem leftAdjointUniq_refl {F : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) :
(leftAdjointUniq adj1 adj1).hom = 𝟙 _ := by
simp [leftAdjointUniq]
#align category_theory.adjunction.left_adjoint_uniq_refl CategoryTheory.Adjunction.leftAdjointUniq_refl
/-- If `G` and `G'` are both right adjoint to `F`, then they are naturally isomorphic. -/
def rightAdjointUniq {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G') : G ≅ G' :=
(natIsoEquiv adj1 adj2).symm (Iso.refl _)
#align category_theory.adjunction.right_adjoint_uniq CategoryTheory.Adjunction.rightAdjointUniq
-- Porting note (#10618): simp can prove this
theorem homEquiv_symm_rightAdjointUniq_hom_app {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G)
(adj2 : F ⊣ G') (x : D) :
(adj2.homEquiv _ _).symm ((rightAdjointUniq adj1 adj2).hom.app x) = adj1.counit.app x := by
simp [rightAdjointUniq]
#align category_theory.adjunction.hom_equiv_symm_right_adjoint_uniq_hom_app CategoryTheory.Adjunction.homEquiv_symm_rightAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem unit_rightAdjointUniq_hom_app {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G')
(x : C) : adj1.unit.app x ≫ (rightAdjointUniq adj1 adj2).hom.app (F.obj x) =
adj2.unit.app x := by
simp only [Functor.id_obj, Functor.comp_obj, rightAdjointUniq, natIsoEquiv_symm_apply_hom,
Iso.refl_hom, natTransEquiv_symm_apply_app, NatTrans.id_app, Category.id_comp]
rw [← adj2.unit_naturality_assoc, ← G'.map_comp]
simp
#align category_theory.adjunction.unit_right_adjoint_uniq_hom_app CategoryTheory.Adjunction.unit_rightAdjointUniq_hom_app
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Adjunction/Unique.lean | 207 | 210 | theorem unit_rightAdjointUniq_hom {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G') :
adj1.unit ≫ whiskerLeft F (rightAdjointUniq adj1 adj2).hom = adj2.unit := by |
ext x
simp
|
/-
Copyright (c) 2022 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll
-/
import Mathlib.Analysis.InnerProductSpace.Adjoint
import Mathlib.Topology.Algebra.Module.Basic
#align_import analysis.inner_product_space.linear_pmap from "leanprover-community/mathlib"@"8b981918a93bc45a8600de608cde7944a80d92b9"
/-!
# Partially defined linear operators on Hilbert spaces
We will develop the basics of the theory of unbounded operators on Hilbert spaces.
## Main definitions
* `LinearPMap.IsFormalAdjoint`: An operator `T` is a formal adjoint of `S` if for all `x` in the
domain of `T` and `y` in the domain of `S`, we have that `⟪T x, y⟫ = ⟪x, S y⟫`.
* `LinearPMap.adjoint`: The adjoint of a map `E →ₗ.[𝕜] F` as a map `F →ₗ.[𝕜] E`.
## Main statements
* `LinearPMap.adjoint_isFormalAdjoint`: The adjoint is a formal adjoint
* `LinearPMap.IsFormalAdjoint.le_adjoint`: Every formal adjoint is contained in the adjoint
* `ContinuousLinearMap.toPMap_adjoint_eq_adjoint_toPMap_of_dense`: The adjoint on
`ContinuousLinearMap` and `LinearPMap` coincide.
## Notation
* For `T : E →ₗ.[𝕜] F` the adjoint can be written as `T†`.
This notation is localized in `LinearPMap`.
## Implementation notes
We use the junk value pattern to define the adjoint for all `LinearPMap`s. In the case that
`T : E →ₗ.[𝕜] F` is not densely defined the adjoint `T†` is the zero map from `T.adjoint.domain` to
`E`.
## References
* [J. Weidmann, *Linear Operators in Hilbert Spaces*][weidmann_linear]
## Tags
Unbounded operators, closed operators
-/
noncomputable section
open RCLike
open scoped ComplexConjugate Classical
variable {𝕜 E F G : Type*} [RCLike 𝕜]
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
namespace LinearPMap
/-- An operator `T` is a formal adjoint of `S` if for all `x` in the domain of `T` and `y` in the
domain of `S`, we have that `⟪T x, y⟫ = ⟪x, S y⟫`. -/
def IsFormalAdjoint (T : E →ₗ.[𝕜] F) (S : F →ₗ.[𝕜] E) : Prop :=
∀ (x : T.domain) (y : S.domain), ⟪T x, y⟫ = ⟪(x : E), S y⟫
#align linear_pmap.is_formal_adjoint LinearPMap.IsFormalAdjoint
variable {T : E →ₗ.[𝕜] F} {S : F →ₗ.[𝕜] E}
@[symm]
protected theorem IsFormalAdjoint.symm (h : T.IsFormalAdjoint S) :
S.IsFormalAdjoint T := fun y _ => by
rw [← inner_conj_symm, ← inner_conj_symm (y : F), h]
#align linear_pmap.is_formal_adjoint.symm LinearPMap.IsFormalAdjoint.symm
variable (T)
/-- The domain of the adjoint operator.
This definition is needed to construct the adjoint operator and the preferred version to use is
`T.adjoint.domain` instead of `T.adjointDomain`. -/
def adjointDomain : Submodule 𝕜 F where
carrier := {y | Continuous ((innerₛₗ 𝕜 y).comp T.toFun)}
zero_mem' := by
rw [Set.mem_setOf_eq, LinearMap.map_zero, LinearMap.zero_comp]
exact continuous_zero
add_mem' hx hy := by rw [Set.mem_setOf_eq, LinearMap.map_add] at *; exact hx.add hy
smul_mem' a x hx := by
rw [Set.mem_setOf_eq, LinearMap.map_smulₛₗ] at *
exact hx.const_smul (conj a)
#align linear_pmap.adjoint_domain LinearPMap.adjointDomain
/-- The operator `fun x ↦ ⟪y, T x⟫` considered as a continuous linear operator
from `T.adjointDomain` to `𝕜`. -/
def adjointDomainMkCLM (y : T.adjointDomain) : T.domain →L[𝕜] 𝕜 :=
⟨(innerₛₗ 𝕜 (y : F)).comp T.toFun, y.prop⟩
#align linear_pmap.adjoint_domain_mk_clm LinearPMap.adjointDomainMkCLM
theorem adjointDomainMkCLM_apply (y : T.adjointDomain) (x : T.domain) :
adjointDomainMkCLM T y x = ⟪(y : F), T x⟫ :=
rfl
#align linear_pmap.adjoint_domain_mk_clm_apply LinearPMap.adjointDomainMkCLM_apply
variable {T}
variable (hT : Dense (T.domain : Set E))
/-- The unique continuous extension of the operator `adjointDomainMkCLM` to `E`. -/
def adjointDomainMkCLMExtend (y : T.adjointDomain) : E →L[𝕜] 𝕜 :=
(T.adjointDomainMkCLM y).extend (Submodule.subtypeL T.domain) hT.denseRange_val
uniformEmbedding_subtype_val.toUniformInducing
#align linear_pmap.adjoint_domain_mk_clm_extend LinearPMap.adjointDomainMkCLMExtend
@[simp]
theorem adjointDomainMkCLMExtend_apply (y : T.adjointDomain) (x : T.domain) :
adjointDomainMkCLMExtend hT y (x : E) = ⟪(y : F), T x⟫ :=
ContinuousLinearMap.extend_eq _ _ _ _ _
#align linear_pmap.adjoint_domain_mk_clm_extend_apply LinearPMap.adjointDomainMkCLMExtend_apply
variable [CompleteSpace E]
/-- The adjoint as a linear map from its domain to `E`.
This is an auxiliary definition needed to define the adjoint operator as a `LinearPMap` without
the assumption that `T.domain` is dense. -/
def adjointAux : T.adjointDomain →ₗ[𝕜] E where
toFun y := (InnerProductSpace.toDual 𝕜 E).symm (adjointDomainMkCLMExtend hT y)
map_add' x y :=
hT.eq_of_inner_left fun _ => by
simp only [inner_add_left, Submodule.coe_add, InnerProductSpace.toDual_symm_apply,
adjointDomainMkCLMExtend_apply]
map_smul' _ _ :=
hT.eq_of_inner_left fun _ => by
simp only [inner_smul_left, Submodule.coe_smul_of_tower, RingHom.id_apply,
InnerProductSpace.toDual_symm_apply, adjointDomainMkCLMExtend_apply]
#align linear_pmap.adjoint_aux LinearPMap.adjointAux
theorem adjointAux_inner (y : T.adjointDomain) (x : T.domain) :
⟪adjointAux hT y, x⟫ = ⟪(y : F), T x⟫ := by
simp only [adjointAux, LinearMap.coe_mk, InnerProductSpace.toDual_symm_apply,
adjointDomainMkCLMExtend_apply]
-- Porting note(https://github.com/leanprover-community/mathlib4/issues/5026):
-- mathlib3 was finished here
simp only [AddHom.coe_mk, InnerProductSpace.toDual_symm_apply]
rw [adjointDomainMkCLMExtend_apply]
#align linear_pmap.adjoint_aux_inner LinearPMap.adjointAux_inner
theorem adjointAux_unique (y : T.adjointDomain) {x₀ : E}
(hx₀ : ∀ x : T.domain, ⟪x₀, x⟫ = ⟪(y : F), T x⟫) : adjointAux hT y = x₀ :=
hT.eq_of_inner_left fun v => (adjointAux_inner hT _ _).trans (hx₀ v).symm
#align linear_pmap.adjoint_aux_unique LinearPMap.adjointAux_unique
variable (T)
/-- The adjoint operator as a partially defined linear operator. -/
def adjoint : F →ₗ.[𝕜] E where
domain := T.adjointDomain
toFun := if hT : Dense (T.domain : Set E) then adjointAux hT else 0
#align linear_pmap.adjoint LinearPMap.adjoint
scoped postfix:1024 "†" => LinearPMap.adjoint
theorem mem_adjoint_domain_iff (y : F) : y ∈ T†.domain ↔ Continuous ((innerₛₗ 𝕜 y).comp T.toFun) :=
Iff.rfl
#align linear_pmap.mem_adjoint_domain_iff LinearPMap.mem_adjoint_domain_iff
variable {T}
theorem mem_adjoint_domain_of_exists (y : F) (h : ∃ w : E, ∀ x : T.domain, ⟪w, x⟫ = ⟪y, T x⟫) :
y ∈ T†.domain := by
cases' h with w hw
rw [T.mem_adjoint_domain_iff]
-- Porting note: was `by continuity`
have : Continuous ((innerSL 𝕜 w).comp T.domain.subtypeL) := ContinuousLinearMap.continuous _
convert this using 1
exact funext fun x => (hw x).symm
#align linear_pmap.mem_adjoint_domain_of_exists LinearPMap.mem_adjoint_domain_of_exists
theorem adjoint_apply_of_not_dense (hT : ¬Dense (T.domain : Set E)) (y : T†.domain) : T† y = 0 := by
change (if hT : Dense (T.domain : Set E) then adjointAux hT else 0) y = _
simp only [hT, not_false_iff, dif_neg, LinearMap.zero_apply]
#align linear_pmap.adjoint_apply_of_not_dense LinearPMap.adjoint_apply_of_not_dense
theorem adjoint_apply_of_dense (y : T†.domain) : T† y = adjointAux hT y := by
change (if hT : Dense (T.domain : Set E) then adjointAux hT else 0) y = _
simp only [hT, dif_pos, LinearMap.coe_mk]
#align linear_pmap.adjoint_apply_of_dense LinearPMap.adjoint_apply_of_dense
theorem adjoint_apply_eq (y : T†.domain) {x₀ : E} (hx₀ : ∀ x : T.domain, ⟪x₀, x⟫ = ⟪(y : F), T x⟫) :
T† y = x₀ :=
(adjoint_apply_of_dense hT y).symm ▸ adjointAux_unique hT _ hx₀
#align linear_pmap.adjoint_apply_eq LinearPMap.adjoint_apply_eq
/-- The fundamental property of the adjoint. -/
theorem adjoint_isFormalAdjoint : T†.IsFormalAdjoint T := fun x =>
(adjoint_apply_of_dense hT x).symm ▸ adjointAux_inner hT x
#align linear_pmap.adjoint_is_formal_adjoint LinearPMap.adjoint_isFormalAdjoint
/-- The adjoint is maximal in the sense that it contains every formal adjoint. -/
theorem IsFormalAdjoint.le_adjoint (h : T.IsFormalAdjoint S) : S ≤ T† :=
⟨-- Trivially, every `x : S.domain` is in `T.adjoint.domain`
fun x hx =>
mem_adjoint_domain_of_exists _
⟨S ⟨x, hx⟩, h.symm ⟨x, hx⟩⟩,-- Equality on `S.domain` follows from equality
-- `⟪v, S x⟫ = ⟪v, T.adjoint y⟫` for all `v : T.domain`:
fun _ _ hxy => (adjoint_apply_eq hT _ fun _ => by rw [h.symm, hxy]).symm⟩
#align linear_pmap.is_formal_adjoint.le_adjoint LinearPMap.IsFormalAdjoint.le_adjoint
end LinearPMap
namespace ContinuousLinearMap
variable [CompleteSpace E] [CompleteSpace F]
variable (A : E →L[𝕜] F) {p : Submodule 𝕜 E}
/-- Restricting `A` to a dense submodule and taking the `LinearPMap.adjoint` is the same
as taking the `ContinuousLinearMap.adjoint` interpreted as a `LinearPMap`. -/
| Mathlib/Analysis/InnerProductSpace/LinearPMap.lean | 220 | 229 | theorem toPMap_adjoint_eq_adjoint_toPMap_of_dense (hp : Dense (p : Set E)) :
(A.toPMap p).adjoint = A.adjoint.toPMap ⊤ := by |
ext x y hxy
· simp only [LinearMap.toPMap_domain, Submodule.mem_top, iff_true_iff,
LinearPMap.mem_adjoint_domain_iff, LinearMap.coe_comp, innerₛₗ_apply_coe]
exact ((innerSL 𝕜 x).comp <| A.comp <| Submodule.subtypeL _).cont
refine LinearPMap.adjoint_apply_eq ?_ _ fun v => ?_
· -- Porting note: was simply `hp` as an argument above
simpa using hp
· simp only [adjoint_inner_left, hxy, LinearMap.toPMap_apply, coe_coe]
|
/-
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)]
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
#align finset.mul_dyson_e_transform_idem Finset.mulDysonETransform_idem
#align finset.add_dyson_e_transform_idem Finset.addDysonETransform_idem
variable {e x}
@[to_additive]
theorem mulDysonETransform.smul_finset_snd_subset_fst :
e • (mulDysonETransform e x).2 ⊆ (mulDysonETransform e x).1 := by
dsimp
rw [smul_finset_inter, smul_inv_smul, inter_comm]
exact inter_subset_union
#align finset.mul_dyson_e_transform.smul_finset_snd_subset_fst Finset.mulDysonETransform.smul_finset_snd_subset_fst
#align finset.add_dyson_e_transform.vadd_finset_snd_subset_fst Finset.addDysonETransform.vadd_finset_snd_subset_fst
end CommGroup
/-!
### Two unnamed e-transforms
The following two transforms both reduce the product/sum of the two sets. Further, one of them must
decrease the sum of the size of the sets (and then the other increases it).
This pair of transforms doesn't seem to be named in the literature. It is used by Sanders in his
bound on Roth numbers, and by DeVos in his proof of Cauchy-Davenport.
-/
section Group
variable [Group α] (e : α) (x : Finset α × Finset α)
/-- An **e-transform**. Turns `(s, t)` into `(s ∩ s • e, t ∪ e⁻¹ • t)`. This reduces the
product of the two sets. -/
@[to_additive (attr := simps) "An **e-transform**.
Turns `(s, t)` into `(s ∩ s +ᵥ e, t ∪ -e +ᵥ t)`. This reduces the sum of the two sets."]
def mulETransformLeft : Finset α × Finset α :=
(x.1 ∩ op e • x.1, x.2 ∪ e⁻¹ • x.2)
#align finset.mul_e_transform_left Finset.mulETransformLeft
#align finset.add_e_transform_left Finset.addETransformLeft
/-- An **e-transform**. Turns `(s, t)` into `(s ∪ s • e, t ∩ e⁻¹ • t)`. This reduces the
product of the two sets. -/
@[to_additive (attr := simps) "An **e-transform**.
Turns `(s, t)` into `(s ∪ s +ᵥ e, t ∩ -e +ᵥ t)`. This reduces the sum of the two sets."]
def mulETransformRight : Finset α × Finset α :=
(x.1 ∪ op e • x.1, x.2 ∩ e⁻¹ • x.2)
#align finset.mul_e_transform_right Finset.mulETransformRight
#align finset.add_e_transform_right Finset.addETransformRight
@[to_additive (attr := simp)]
theorem mulETransformLeft_one : mulETransformLeft 1 x = x := by simp [mulETransformLeft]
#align finset.mul_e_transform_left_one Finset.mulETransformLeft_one
#align finset.add_e_transform_left_zero Finset.addETransformLeft_zero
@[to_additive (attr := simp)]
theorem mulETransformRight_one : mulETransformRight 1 x = x := by simp [mulETransformRight]
#align finset.mul_e_transform_right_one Finset.mulETransformRight_one
#align finset.add_e_transform_right_zero Finset.addETransformRight_zero
@[to_additive]
theorem mulETransformLeft.fst_mul_snd_subset :
(mulETransformLeft e x).1 * (mulETransformLeft e x).2 ⊆ x.1 * x.2 := by
refine inter_mul_union_subset_union.trans (union_subset Subset.rfl ?_)
rw [op_smul_finset_mul_eq_mul_smul_finset, smul_inv_smul]
#align finset.mul_e_transform_left.fst_mul_snd_subset Finset.mulETransformLeft.fst_mul_snd_subset
#align finset.add_e_transform_left.fst_add_snd_subset Finset.addETransformLeft.fst_add_snd_subset
@[to_additive]
theorem mulETransformRight.fst_mul_snd_subset :
(mulETransformRight e x).1 * (mulETransformRight e x).2 ⊆ x.1 * x.2 := by
refine union_mul_inter_subset_union.trans (union_subset Subset.rfl ?_)
rw [op_smul_finset_mul_eq_mul_smul_finset, smul_inv_smul]
#align finset.mul_e_transform_right.fst_mul_snd_subset Finset.mulETransformRight.fst_mul_snd_subset
#align finset.add_e_transform_right.fst_add_snd_subset Finset.addETransformRight.fst_add_snd_subset
@[to_additive]
theorem mulETransformLeft.card :
(mulETransformLeft e x).1.card + (mulETransformRight e x).1.card = 2 * x.1.card :=
(card_inter_add_card_union _ _).trans <| by rw [card_smul_finset, two_mul]
#align finset.mul_e_transform_left.card Finset.mulETransformLeft.card
#align finset.add_e_transform_left.card Finset.addETransformLeft.card
@[to_additive]
theorem mulETransformRight.card :
(mulETransformLeft e x).2.card + (mulETransformRight e x).2.card = 2 * x.2.card :=
(card_union_add_card_inter _ _).trans <| by rw [card_smul_finset, two_mul]
#align finset.mul_e_transform_right.card Finset.mulETransformRight.card
#align finset.add_e_transform_right.card Finset.addETransformRight.card
/-- This statement is meant to be combined with `le_or_lt_of_add_le_add` and similar lemmas. -/
@[to_additive AddETransform.card "This statement is meant to be combined with
`le_or_lt_of_add_le_add` and similar lemmas."]
protected theorem MulETransform.card :
(mulETransformLeft e x).1.card + (mulETransformLeft e x).2.card +
((mulETransformRight e x).1.card + (mulETransformRight e x).2.card) =
x.1.card + x.2.card + (x.1.card + x.2.card) := by
rw [add_add_add_comm, mulETransformLeft.card, mulETransformRight.card, ← mul_add, two_mul]
#align finset.mul_e_transform.card Finset.MulETransform.card
#align finset.add_e_transform.card Finset.AddETransform.card
end Group
section CommGroup
variable [CommGroup α] (e : α) (x : Finset α × Finset α)
@[to_additive (attr := simp)]
| Mathlib/Combinatorics/Additive/ETransform.lean | 189 | 190 | theorem mulETransformLeft_inv : mulETransformLeft e⁻¹ x = (mulETransformRight e x.swap).swap := by |
simp [-op_inv, op_smul_eq_smul, mulETransformLeft, mulETransformRight]
|
/-
Copyright (c) 2020 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Algebra.Polynomial.Eval
import Mathlib.LinearAlgebra.Dimension.Constructions
#align_import algebra.linear_recurrence from "leanprover-community/mathlib"@"039a089d2a4b93c761b234f3e5f5aeb752bac60f"
/-!
# Linear recurrence
Informally, a "linear recurrence" is an assertion of the form
`∀ n : ℕ, u (n + d) = a 0 * u n + a 1 * u (n+1) + ... + a (d-1) * u (n+d-1)`,
where `u` is a sequence, `d` is the *order* of the recurrence and the `a i`
are its *coefficients*.
In this file, we define the structure `LinearRecurrence` so that
`LinearRecurrence.mk d a` represents the above relation, and we call
a sequence `u` which verifies it a *solution* of the linear recurrence.
We prove a few basic lemmas about this concept, such as :
* the space of solutions is a submodule of `(ℕ → α)` (i.e a vector space if `α`
is a field)
* the function that maps a solution `u` to its first `d` terms builds a `LinearEquiv`
between the solution space and `Fin d → α`, aka `α ^ d`. As a consequence, two
solutions are equal if and only if their first `d` terms are equals.
* a geometric sequence `q ^ n` is solution iff `q` is a root of a particular polynomial,
which we call the *characteristic polynomial* of the recurrence
Of course, although we can inductively generate solutions (cf `mkSol`), the
interesting part would be to determinate closed-forms for the solutions.
This is currently *not implemented*, as we are waiting for definition and
properties of eigenvalues and eigenvectors.
-/
noncomputable section
open Finset
open Polynomial
/-- A "linear recurrence relation" over a commutative semiring is given by its
order `n` and `n` coefficients. -/
structure LinearRecurrence (α : Type*) [CommSemiring α] where
order : ℕ
coeffs : Fin order → α
#align linear_recurrence LinearRecurrence
instance (α : Type*) [CommSemiring α] : Inhabited (LinearRecurrence α) :=
⟨⟨0, default⟩⟩
namespace LinearRecurrence
section CommSemiring
variable {α : Type*} [CommSemiring α] (E : LinearRecurrence α)
/-- We say that a sequence `u` is solution of `LinearRecurrence order coeffs` when we have
`u (n + order) = ∑ i : Fin order, coeffs i * u (n + i)` for any `n`. -/
def IsSolution (u : ℕ → α) :=
∀ n, u (n + E.order) = ∑ i, E.coeffs i * u (n + i)
#align linear_recurrence.is_solution LinearRecurrence.IsSolution
/-- A solution of a `LinearRecurrence` which satisfies certain initial conditions.
We will prove this is the only such solution. -/
def mkSol (init : Fin E.order → α) : ℕ → α
| n =>
if h : n < E.order then init ⟨n, h⟩
else
∑ k : Fin E.order,
have _ : n - E.order + k < n := by
rw [add_comm, ← add_tsub_assoc_of_le (not_lt.mp h), tsub_lt_iff_left]
· exact add_lt_add_right k.is_lt n
· convert add_le_add (zero_le (k : ℕ)) (not_lt.mp h)
simp only [zero_add]
E.coeffs k * mkSol init (n - E.order + k)
#align linear_recurrence.mk_sol LinearRecurrence.mkSol
/-- `E.mkSol` indeed gives solutions to `E`. -/
theorem is_sol_mkSol (init : Fin E.order → α) : E.IsSolution (E.mkSol init) := by
intro n
rw [mkSol]
simp
#align linear_recurrence.is_sol_mk_sol LinearRecurrence.is_sol_mkSol
/-- `E.mkSol init`'s first `E.order` terms are `init`. -/
theorem mkSol_eq_init (init : Fin E.order → α) : ∀ n : Fin E.order, E.mkSol init n = init n := by
intro n
rw [mkSol]
simp only [n.is_lt, dif_pos, Fin.mk_val, Fin.eta]
#align linear_recurrence.mk_sol_eq_init LinearRecurrence.mkSol_eq_init
/-- If `u` is a solution to `E` and `init` designates its first `E.order` values,
then `∀ n, u n = E.mkSol init n`. -/
theorem eq_mk_of_is_sol_of_eq_init {u : ℕ → α} {init : Fin E.order → α} (h : E.IsSolution u)
(heq : ∀ n : Fin E.order, u n = init n) : ∀ n, u n = E.mkSol init n := by
intro n
rw [mkSol]
split_ifs with h'
· exact mod_cast heq ⟨n, h'⟩
simp only
rw [← tsub_add_cancel_of_le (le_of_not_lt h'), h (n - E.order)]
congr with k
have : n - E.order + k < n := by
rw [add_comm, ← add_tsub_assoc_of_le (not_lt.mp h'), tsub_lt_iff_left]
· exact add_lt_add_right k.is_lt n
· convert add_le_add (zero_le (k : ℕ)) (not_lt.mp h')
simp only [zero_add]
rw [eq_mk_of_is_sol_of_eq_init h heq (n - E.order + k)]
simp
#align linear_recurrence.eq_mk_of_is_sol_of_eq_init LinearRecurrence.eq_mk_of_is_sol_of_eq_init
/-- If `u` is a solution to `E` and `init` designates its first `E.order` values,
then `u = E.mkSol init`. This proves that `E.mkSol init` is the only solution
of `E` whose first `E.order` values are given by `init`. -/
theorem eq_mk_of_is_sol_of_eq_init' {u : ℕ → α} {init : Fin E.order → α} (h : E.IsSolution u)
(heq : ∀ n : Fin E.order, u n = init n) : u = E.mkSol init :=
funext (E.eq_mk_of_is_sol_of_eq_init h heq)
#align linear_recurrence.eq_mk_of_is_sol_of_eq_init' LinearRecurrence.eq_mk_of_is_sol_of_eq_init'
/-- The space of solutions of `E`, as a `Submodule` over `α` of the module `ℕ → α`. -/
def solSpace : Submodule α (ℕ → α) where
carrier := { u | E.IsSolution u }
zero_mem' n := by simp
add_mem' {u v} hu hv n := by simp [mul_add, sum_add_distrib, hu n, hv n]
smul_mem' a u hu n := by simp [hu n, mul_sum]; congr; ext; ac_rfl
#align linear_recurrence.sol_space LinearRecurrence.solSpace
/-- Defining property of the solution space : `u` is a solution
iff it belongs to the solution space. -/
theorem is_sol_iff_mem_solSpace (u : ℕ → α) : E.IsSolution u ↔ u ∈ E.solSpace :=
Iff.rfl
#align linear_recurrence.is_sol_iff_mem_sol_space LinearRecurrence.is_sol_iff_mem_solSpace
/-- The function that maps a solution `u` of `E` to its first
`E.order` terms as a `LinearEquiv`. -/
def toInit : E.solSpace ≃ₗ[α] Fin E.order → α where
toFun u x := (u : ℕ → α) x
map_add' u v := by
ext
simp
map_smul' a u := by
ext
simp
invFun u := ⟨E.mkSol u, E.is_sol_mkSol u⟩
left_inv u := by ext n; symm; apply E.eq_mk_of_is_sol_of_eq_init u.2; intro k; rfl
right_inv u := Function.funext_iff.mpr fun n ↦ E.mkSol_eq_init u n
#align linear_recurrence.to_init LinearRecurrence.toInit
/-- Two solutions are equal iff they are equal on `range E.order`. -/
theorem sol_eq_of_eq_init (u v : ℕ → α) (hu : E.IsSolution u) (hv : E.IsSolution v) :
u = v ↔ Set.EqOn u v ↑(range E.order) := by
refine Iff.intro (fun h x _ ↦ h ▸ rfl) ?_
intro h
set u' : ↥E.solSpace := ⟨u, hu⟩
set v' : ↥E.solSpace := ⟨v, hv⟩
change u'.val = v'.val
suffices h' : u' = v' from h' ▸ rfl
rw [← E.toInit.toEquiv.apply_eq_iff_eq, LinearEquiv.coe_toEquiv]
ext x
exact mod_cast h (mem_range.mpr x.2)
#align linear_recurrence.sol_eq_of_eq_init LinearRecurrence.sol_eq_of_eq_init
/-! `E.tupleSucc` maps `![s₀, s₁, ..., sₙ]` to `![s₁, ..., sₙ, ∑ (E.coeffs i) * sᵢ]`,
where `n := E.order`. This operation is quite useful for determining closed-form
solutions of `E`. -/
/-- `E.tupleSucc` maps `![s₀, s₁, ..., sₙ]` to `![s₁, ..., sₙ, ∑ (E.coeffs i) * sᵢ]`,
where `n := E.order`. -/
def tupleSucc : (Fin E.order → α) →ₗ[α] Fin E.order → α where
toFun X i := if h : (i : ℕ) + 1 < E.order then X ⟨i + 1, h⟩ else ∑ i, E.coeffs i * X i
map_add' x y := by
ext i
simp only
split_ifs with h <;> simp [h, mul_add, sum_add_distrib]
map_smul' x y := by
ext i
simp only
split_ifs with h <;> simp [h, mul_sum]
exact sum_congr rfl fun x _ ↦ by ac_rfl
#align linear_recurrence.tuple_succ LinearRecurrence.tupleSucc
end CommSemiring
section StrongRankCondition
-- note: `StrongRankCondition` is the same as `Nontrivial` on `CommRing`s, but that result,
-- `commRing_strongRankCondition`, is in a much later file.
variable {α : Type*} [CommRing α] [StrongRankCondition α] (E : LinearRecurrence α)
/-- The dimension of `E.solSpace` is `E.order`. -/
theorem solSpace_rank : Module.rank α E.solSpace = E.order :=
letI := nontrivial_of_invariantBasisNumber α
@rank_fin_fun α _ _ E.order ▸ E.toInit.rank_eq
#align linear_recurrence.sol_space_rank LinearRecurrence.solSpace_rank
end StrongRankCondition
section CommRing
variable {α : Type*} [CommRing α] (E : LinearRecurrence α)
/-- The characteristic polynomial of `E` is
`X ^ E.order - ∑ i : Fin E.order, (E.coeffs i) * X ^ i`. -/
def charPoly : α[X] :=
Polynomial.monomial E.order 1 - ∑ i : Fin E.order, Polynomial.monomial i (E.coeffs i)
#align linear_recurrence.char_poly LinearRecurrence.charPoly
/-- The geometric sequence `q^n` is a solution of `E` iff
`q` is a root of `E`'s characteristic polynomial. -/
| Mathlib/Algebra/LinearRecurrence.lean | 217 | 227 | theorem geom_sol_iff_root_charPoly (q : α) :
(E.IsSolution fun n ↦ q ^ n) ↔ E.charPoly.IsRoot q := by |
rw [charPoly, Polynomial.IsRoot.def, Polynomial.eval]
simp only [Polynomial.eval₂_finset_sum, one_mul, RingHom.id_apply, Polynomial.eval₂_monomial,
Polynomial.eval₂_sub]
constructor
· intro h
simpa [sub_eq_zero] using h 0
· intro h n
simp only [pow_add, sub_eq_zero.mp h, mul_sum]
exact sum_congr rfl fun _ _ ↦ by ring
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Data.Countable.Basic
import Mathlib.Data.Fin.VecNotation
import Mathlib.Order.Disjointed
import Mathlib.MeasureTheory.OuterMeasure.Defs
#align_import measure_theory.measure.outer_measure from "leanprover-community/mathlib"@"343e80208d29d2d15f8050b929aa50fe4ce71b55"
/-!
# Outer Measures
An outer measure is a function `μ : Set α → ℝ≥0∞`, from the powerset of a type to the extended
nonnegative real numbers that satisfies the following conditions:
1. `μ ∅ = 0`;
2. `μ` is monotone;
3. `μ` is countably subadditive. This means that the outer measure of a countable union is at most
the sum of the outer measure on the individual sets.
Note that we do not need `α` to be measurable to define an outer measure.
## References
<https://en.wikipedia.org/wiki/Outer_measure>
## Tags
outer measure
-/
noncomputable section
open Set Function Filter
open scoped Classical NNReal Topology ENNReal
namespace MeasureTheory
section OuterMeasureClass
variable {α ι F : Type*} [FunLike F (Set α) ℝ≥0∞] [OuterMeasureClass F α]
{μ : F} {s t : Set α}
@[simp]
theorem measure_empty : μ ∅ = 0 := OuterMeasureClass.measure_empty μ
#align measure_theory.measure_empty MeasureTheory.measure_empty
@[mono, gcongr]
theorem measure_mono (h : s ⊆ t) : μ s ≤ μ t :=
OuterMeasureClass.measure_mono μ h
#align measure_theory.measure_mono MeasureTheory.measure_mono
theorem measure_mono_null (h : s ⊆ t) (ht : μ t = 0) : μ s = 0 :=
eq_bot_mono (measure_mono h) ht
#align measure_theory.measure_mono_null MeasureTheory.measure_mono_null
theorem measure_pos_of_superset (h : s ⊆ t) (hs : μ s ≠ 0) : 0 < μ t :=
hs.bot_lt.trans_le (measure_mono h)
theorem measure_iUnion_le [Countable ι] (s : ι → Set α) : μ (⋃ i, s i) ≤ ∑' i, μ (s i) := by
refine rel_iSup_tsum μ measure_empty (· ≤ ·) (fun t ↦ ?_) _
calc
μ (⋃ i, t i) = μ (⋃ i, disjointed t i) := by rw [iUnion_disjointed]
_ ≤ ∑' i, μ (disjointed t i) :=
OuterMeasureClass.measure_iUnion_nat_le _ _ (disjoint_disjointed _)
_ ≤ ∑' i, μ (t i) := by gcongr; apply disjointed_subset
#align measure_theory.measure_Union_le MeasureTheory.measure_iUnion_le
theorem measure_biUnion_le {I : Set ι} (μ : F) (hI : I.Countable) (s : ι → Set α) :
μ (⋃ i ∈ I, s i) ≤ ∑' i : I, μ (s i) := by
have := hI.to_subtype
rw [biUnion_eq_iUnion]
apply measure_iUnion_le
#align measure_theory.measure_bUnion_le MeasureTheory.measure_biUnion_le
theorem measure_biUnion_finset_le (I : Finset ι) (s : ι → Set α) :
μ (⋃ i ∈ I, s i) ≤ ∑ i ∈ I, μ (s i) :=
(measure_biUnion_le μ I.countable_toSet s).trans_eq <| I.tsum_subtype (μ <| s ·)
#align measure_theory.measure_bUnion_finset_le MeasureTheory.measure_biUnion_finset_le
| Mathlib/MeasureTheory/OuterMeasure/Basic.lean | 84 | 86 | theorem measure_iUnion_fintype_le [Fintype ι] (μ : F) (s : ι → Set α) :
μ (⋃ i, s i) ≤ ∑ i, μ (s i) := by |
simpa using measure_biUnion_finset_le Finset.univ s
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Julian Kuelshammer, Heather Macbeth, Mitchell Lee
-/
import Mathlib.Algebra.Polynomial.Derivative
import Mathlib.Tactic.LinearCombination
#align_import ring_theory.polynomial.chebyshev from "leanprover-community/mathlib"@"d774451114d6045faeb6751c396bea1eb9058946"
/-!
# Chebyshev polynomials
The Chebyshev polynomials are families of polynomials indexed by `ℤ`,
with integral coefficients.
## Main definitions
* `Polynomial.Chebyshev.T`: the Chebyshev polynomials of the first kind.
* `Polynomial.Chebyshev.U`: the Chebyshev polynomials of the second kind.
## Main statements
* The formal derivative of the Chebyshev polynomials of the first kind is a scalar multiple of the
Chebyshev polynomials of the second kind.
* `Polynomial.Chebyshev.mul_T`, twice the product of the `m`-th and `k`-th Chebyshev polynomials of
the first kind is the sum of the `m + k`-th and `m - k`-th Chebyshev polynomials of the first
kind.
* `Polynomial.Chebyshev.T_mul`, the `(m * n)`-th Chebyshev polynomial of the first kind is the
composition of the `m`-th and `n`-th Chebyshev polynomials of the first kind.
## Implementation details
Since Chebyshev polynomials have interesting behaviour over the complex numbers and modulo `p`,
we define them to have coefficients in an arbitrary commutative ring, even though
technically `ℤ` would suffice.
The benefit of allowing arbitrary coefficient rings, is that the statements afterwards are clean,
and do not have `map (Int.castRingHom R)` interfering all the time.
## References
[Lionel Ponton, _Roots of the Chebyshev polynomials: A purely algebraic approach_]
[ponton2020chebyshev]
## TODO
* Redefine and/or relate the definition of Chebyshev polynomials to `LinearRecurrence`.
* Add explicit formula involving square roots for Chebyshev polynomials
* Compute zeroes and extrema of Chebyshev polynomials.
* Prove that the roots of the Chebyshev polynomials (except 0) are irrational.
* Prove minimax properties of Chebyshev polynomials.
-/
namespace Polynomial.Chebyshev
set_option linter.uppercaseLean3 false -- `T` `U` `X`
open Polynomial
variable (R S : Type*) [CommRing R] [CommRing S]
/-- `T n` is the `n`-th Chebyshev polynomial of the first kind. -/
-- Well-founded definitions are now irreducible by default;
-- as this was implemented before this change,
-- we just set it back to semireducible to avoid needing to change any proofs.
@[semireducible] noncomputable def T : ℤ → R[X]
| 0 => 1
| 1 => X
| (n : ℕ) + 2 => 2 * X * T (n + 1) - T n
| -((n : ℕ) + 1) => 2 * X * T (-n) - T (-n + 1)
termination_by n => Int.natAbs n + Int.natAbs (n - 1)
#align polynomial.chebyshev.T Polynomial.Chebyshev.T
/-- Induction principle used for proving facts about Chebyshev polynomials. -/
@[elab_as_elim]
protected theorem induct (motive : ℤ → Prop)
(zero : motive 0)
(one : motive 1)
(add_two : ∀ (n : ℕ), motive (↑n + 1) → motive ↑n → motive (↑n + 2))
(neg_add_one : ∀ (n : ℕ), motive (-↑n) → motive (-↑n + 1) → motive (-↑n - 1)) :
∀ (a : ℤ), motive a :=
T.induct Unit motive zero one add_two fun n hn hnm => by
simpa only [Int.negSucc_eq, neg_add] using neg_add_one n hn hnm
@[simp]
theorem T_add_two : ∀ n, T R (n + 2) = 2 * X * T R (n + 1) - T R n
| (k : ℕ) => T.eq_3 R k
| -(k + 1 : ℕ) => by linear_combination (norm := (simp [Int.negSucc_eq]; ring_nf)) T.eq_4 R k
#align polynomial.chebyshev.T_add_two Polynomial.Chebyshev.T_add_two
theorem T_add_one (n : ℤ) : T R (n + 1) = 2 * X * T R n - T R (n - 1) := by
linear_combination (norm := ring_nf) T_add_two R (n - 1)
theorem T_sub_two (n : ℤ) : T R (n - 2) = 2 * X * T R (n - 1) - T R n := by
linear_combination (norm := ring_nf) T_add_two R (n - 2)
theorem T_sub_one (n : ℤ) : T R (n - 1) = 2 * X * T R n - T R (n + 1) := by
linear_combination (norm := ring_nf) T_add_two R (n - 1)
theorem T_eq (n : ℤ) : T R n = 2 * X * T R (n - 1) - T R (n - 2) := by
linear_combination (norm := ring_nf) T_add_two R (n - 2)
#align polynomial.chebyshev.T_of_two_le Polynomial.Chebyshev.T_eq
@[simp]
theorem T_zero : T R 0 = 1 := rfl
#align polynomial.chebyshev.T_zero Polynomial.Chebyshev.T_zero
@[simp]
theorem T_one : T R 1 = X := rfl
#align polynomial.chebyshev.T_one Polynomial.Chebyshev.T_one
theorem T_neg_one : T R (-1) = X := (by ring : 2 * X * 1 - X = X)
theorem T_two : T R 2 = 2 * X ^ 2 - 1 := by
simpa [pow_two, mul_assoc] using T_add_two R 0
#align polynomial.chebyshev.T_two Polynomial.Chebyshev.T_two
@[simp]
theorem T_neg (n : ℤ) : T R (-n) = T R n := by
induction n using Polynomial.Chebyshev.induct with
| zero => rfl
| one => show 2 * X * 1 - X = X; ring
| add_two n ih1 ih2 =>
have h₁ := T_add_two R n
have h₂ := T_sub_two R (-n)
linear_combination (norm := ring_nf) (2 * (X:R[X])) * ih1 - ih2 - h₁ + h₂
| neg_add_one n ih1 ih2 =>
have h₁ := T_add_one R n
have h₂ := T_sub_one R (-n)
linear_combination (norm := ring_nf) (2 * (X:R[X])) * ih1 - ih2 + h₁ - h₂
theorem T_natAbs (n : ℤ) : T R n.natAbs = T R n := by
obtain h | h := Int.natAbs_eq n <;> nth_rw 2 [h]; simp
theorem T_neg_two : T R (-2) = 2 * X ^ 2 - 1 := by simp [T_two]
/-- `U n` is the `n`-th Chebyshev polynomial of the second kind. -/
-- Well-founded definitions are now irreducible by default;
-- as this was implemented before this change,
-- we just set it back to semireducible to avoid needing to change any proofs.
@[semireducible] noncomputable def U : ℤ → R[X]
| 0 => 1
| 1 => 2 * X
| (n : ℕ) + 2 => 2 * X * U (n + 1) - U n
| -((n : ℕ) + 1) => 2 * X * U (-n) - U (-n + 1)
termination_by n => Int.natAbs n + Int.natAbs (n - 1)
#align polynomial.chebyshev.U Polynomial.Chebyshev.U
@[simp]
theorem U_add_two : ∀ n, U R (n + 2) = 2 * X * U R (n + 1) - U R n
| (k : ℕ) => U.eq_3 R k
| -(k + 1 : ℕ) => by linear_combination (norm := (simp [Int.negSucc_eq]; ring_nf)) U.eq_4 R k
theorem U_add_one (n : ℤ) : U R (n + 1) = 2 * X * U R n - U R (n - 1) := by
linear_combination (norm := ring_nf) U_add_two R (n - 1)
theorem U_sub_two (n : ℤ) : U R (n - 2) = 2 * X * U R (n - 1) - U R n := by
linear_combination (norm := ring_nf) U_add_two R (n - 2)
theorem U_sub_one (n : ℤ) : U R (n - 1) = 2 * X * U R n - U R (n + 1) := by
linear_combination (norm := ring_nf) U_add_two R (n - 1)
theorem U_eq (n : ℤ) : U R n = 2 * X * U R (n - 1) - U R (n - 2) := by
linear_combination (norm := ring_nf) U_add_two R (n - 2)
#align polynomial.chebyshev.U_of_two_le Polynomial.Chebyshev.U_eq
@[simp]
theorem U_zero : U R 0 = 1 := rfl
#align polynomial.chebyshev.U_zero Polynomial.Chebyshev.U_zero
@[simp]
theorem U_one : U R 1 = 2 * X := rfl
#align polynomial.chebyshev.U_one Polynomial.Chebyshev.U_one
@[simp]
theorem U_neg_one : U R (-1) = 0 := by simpa using U_sub_one R 0
theorem U_two : U R 2 = 4 * X ^ 2 - 1 := by
have := U_add_two R 0
simp only [zero_add, U_one, U_zero] at this
linear_combination this
#align polynomial.chebyshev.U_two Polynomial.Chebyshev.U_two
@[simp]
theorem U_neg_two : U R (-2) = -1 := by
simpa [zero_sub, Int.reduceNeg, U_neg_one, mul_zero, U_zero] using U_sub_two R 0
theorem U_neg_sub_one (n : ℤ) : U R (-n - 1) = -U R (n - 1) := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp
| one => simp
| add_two n ih1 ih2 =>
have h₁ := U_add_one R n
have h₂ := U_sub_two R (-n - 1)
linear_combination (norm := ring_nf) 2 * (X:R[X]) * ih1 - ih2 + h₁ + h₂
| neg_add_one n ih1 ih2 =>
have h₁ := U_eq R n
have h₂ := U_sub_two R (-n)
linear_combination (norm := ring_nf) 2 * (X:R[X]) * ih1 - ih2 + h₁ + h₂
| Mathlib/RingTheory/Polynomial/Chebyshev.lean | 200 | 200 | theorem U_neg (n : ℤ) : U R (-n) = -U R (n - 2) := by | simpa [sub_sub] using U_neg_sub_one R (n - 1)
|
/-
Copyright (c) 2023 Mantas Bakšys, Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mantas Bakšys, Yaël Dillies
-/
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Group.Basic
import Mathlib.Algebra.Order.Rearrangement
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.GroupTheory.Perm.Cycle.Basic
#align_import algebra.order.chebyshev from "leanprover-community/mathlib"@"b7399344324326918d65d0c74e9571e3a8cb9199"
/-!
# Chebyshev's sum inequality
This file proves the Chebyshev sum inequality.
Chebyshev's inequality states `(∑ i ∈ s, f i) * (∑ i ∈ s, g i) ≤ s.card * ∑ i ∈ s, f i * g i`
when `f g : ι → α` monovary, and the reverse inequality when `f` and `g` antivary.
## Main declarations
* `MonovaryOn.sum_mul_sum_le_card_mul_sum`: Chebyshev's inequality.
* `AntivaryOn.card_mul_sum_le_sum_mul_sum`: Chebyshev's inequality, dual version.
* `sq_sum_le_card_mul_sum_sq`: Special case of Chebyshev's inequality when `f = g`.
## Implementation notes
In fact, we don't need much compatibility between the addition and multiplication of `α`, so we can
actually decouple them by replacing multiplication with scalar multiplication and making `f` and `g`
land in different types.
As a bonus, this makes the dual statement trivial. The multiplication versions are provided for
convenience.
The case for `Monotone`/`Antitone` pairs of functions over a `LinearOrder` is not deduced in this
file because it is easily deducible from the `Monovary` API.
-/
open Equiv Equiv.Perm Finset Function OrderDual
variable {ι α β : Type*}
/-! ### Scalar multiplication versions -/
section SMul
variable [LinearOrderedRing α] [LinearOrderedAddCommGroup β] [Module α β] [OrderedSMul α β]
{s : Finset ι} {σ : Perm ι} {f : ι → α} {g : ι → β}
/-- **Chebyshev's Sum Inequality**: When `f` and `g` monovary together (eg they are both
monotone/antitone), the scalar product of their sum is less than the size of the set times their
scalar product. -/
theorem MonovaryOn.sum_smul_sum_le_card_smul_sum (hfg : MonovaryOn f g s) :
((∑ i ∈ s, f i) • ∑ i ∈ s, g i) ≤ s.card • ∑ i ∈ s, f i • g i := by
classical
obtain ⟨σ, hσ, hs⟩ := s.countable_toSet.exists_cycleOn
rw [← card_range s.card, sum_smul_sum_eq_sum_perm hσ]
exact
sum_le_card_nsmul _ _ _ fun n _ =>
hfg.sum_smul_comp_perm_le_sum_smul fun x hx => hs fun h => hx <| IsFixedPt.perm_pow h _
#align monovary_on.sum_smul_sum_le_card_smul_sum MonovaryOn.sum_smul_sum_le_card_smul_sum
/-- **Chebyshev's Sum Inequality**: When `f` and `g` antivary together (eg one is monotone, the
other is antitone), the scalar product of their sum is less than the size of the set times their
scalar product. -/
theorem AntivaryOn.card_smul_sum_le_sum_smul_sum (hfg : AntivaryOn f g s) :
(s.card • ∑ i ∈ s, f i • g i) ≤ (∑ i ∈ s, f i) • ∑ i ∈ s, g i := by
exact hfg.dual_right.sum_smul_sum_le_card_smul_sum
#align antivary_on.card_smul_sum_le_sum_smul_sum AntivaryOn.card_smul_sum_le_sum_smul_sum
variable [Fintype ι]
/-- **Chebyshev's Sum Inequality**: When `f` and `g` monovary together (eg they are both
monotone/antitone), the scalar product of their sum is less than the size of the set times their
scalar product. -/
theorem Monovary.sum_smul_sum_le_card_smul_sum (hfg : Monovary f g) :
((∑ i, f i) • ∑ i, g i) ≤ Fintype.card ι • ∑ i, f i • g i :=
(hfg.monovaryOn _).sum_smul_sum_le_card_smul_sum
#align monovary.sum_smul_sum_le_card_smul_sum Monovary.sum_smul_sum_le_card_smul_sum
/-- **Chebyshev's Sum Inequality**: When `f` and `g` antivary together (eg one is monotone, the
other is antitone), the scalar product of their sum is less than the size of the set times their
scalar product. -/
theorem Antivary.card_smul_sum_le_sum_smul_sum (hfg : Antivary f g) :
(Fintype.card ι • ∑ i, f i • g i) ≤ (∑ i, f i) • ∑ i, g i := by
exact (hfg.dual_right.monovaryOn _).sum_smul_sum_le_card_smul_sum
#align antivary.card_smul_sum_le_sum_smul_sum Antivary.card_smul_sum_le_sum_smul_sum
end SMul
/-!
### Multiplication versions
Special cases of the above when scalar multiplication is actually multiplication.
-/
section Mul
variable [LinearOrderedRing α] {s : Finset ι} {σ : Perm ι} {f g : ι → α}
/-- **Chebyshev's Sum Inequality**: When `f` and `g` monovary together (eg they are both
monotone/antitone), the product of their sum is less than the size of the set times their scalar
product. -/
theorem MonovaryOn.sum_mul_sum_le_card_mul_sum (hfg : MonovaryOn f g s) :
((∑ i ∈ s, f i) * ∑ i ∈ s, g i) ≤ s.card * ∑ i ∈ s, f i * g i := by
rw [← nsmul_eq_mul]
exact hfg.sum_smul_sum_le_card_smul_sum
#align monovary_on.sum_mul_sum_le_card_mul_sum MonovaryOn.sum_mul_sum_le_card_mul_sum
/-- **Chebyshev's Sum Inequality**: When `f` and `g` antivary together (eg one is monotone, the
other is antitone), the product of their sum is greater than the size of the set times their scalar
product. -/
theorem AntivaryOn.card_mul_sum_le_sum_mul_sum (hfg : AntivaryOn f g s) :
((s.card : α) * ∑ i ∈ s, f i * g i) ≤ (∑ i ∈ s, f i) * ∑ i ∈ s, g i := by
rw [← nsmul_eq_mul]
exact hfg.card_smul_sum_le_sum_smul_sum
#align antivary_on.card_mul_sum_le_sum_mul_sum AntivaryOn.card_mul_sum_le_sum_mul_sum
/-- Special case of **Chebyshev's Sum Inequality** or the **Cauchy-Schwarz Inequality**: The square
of the sum is less than the size of the set times the sum of the squares. -/
theorem sq_sum_le_card_mul_sum_sq : (∑ i ∈ s, f i) ^ 2 ≤ s.card * ∑ i ∈ s, f i ^ 2 := by
simp_rw [sq]
exact (monovaryOn_self _ _).sum_mul_sum_le_card_mul_sum
#align sq_sum_le_card_mul_sum_sq sq_sum_le_card_mul_sum_sq
variable [Fintype ι]
/-- **Chebyshev's Sum Inequality**: When `f` and `g` monovary together (eg they are both
monotone/antitone), the product of their sum is less than the size of the set times their scalar
product. -/
theorem Monovary.sum_mul_sum_le_card_mul_sum (hfg : Monovary f g) :
((∑ i, f i) * ∑ i, g i) ≤ Fintype.card ι * ∑ i, f i * g i :=
(hfg.monovaryOn _).sum_mul_sum_le_card_mul_sum
#align monovary.sum_mul_sum_le_card_mul_sum Monovary.sum_mul_sum_le_card_mul_sum
/-- **Chebyshev's Sum Inequality**: When `f` and `g` antivary together (eg one is monotone, the
other is antitone), the product of their sum is less than the size of the set times their scalar
product. -/
theorem Antivary.card_mul_sum_le_sum_mul_sum (hfg : Antivary f g) :
((Fintype.card ι : α) * ∑ i, f i * g i) ≤ (∑ i, f i) * ∑ i, g i :=
(hfg.antivaryOn _).card_mul_sum_le_sum_mul_sum
#align antivary.card_mul_sum_le_sum_mul_sum Antivary.card_mul_sum_le_sum_mul_sum
end Mul
variable [LinearOrderedField α] {s : Finset ι} {f : ι → α}
| Mathlib/Algebra/Order/Chebyshev.lean | 153 | 160 | theorem sum_div_card_sq_le_sum_sq_div_card :
((∑ i ∈ s, f i) / s.card) ^ 2 ≤ (∑ i ∈ s, f i ^ 2) / s.card := by |
obtain rfl | hs := s.eq_empty_or_nonempty
· simp
rw [← card_pos, ← @Nat.cast_pos α] at hs
rw [div_pow, div_le_div_iff (sq_pos_of_ne_zero hs.ne') hs, sq (s.card : α), mul_left_comm, ←
mul_assoc]
exact mul_le_mul_of_nonneg_right sq_sum_le_card_mul_sum_sq hs.le
|
/-
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.Topology.GDelta
import Mathlib.MeasureTheory.Group.Arithmetic
import Mathlib.Topology.Instances.EReal
import Mathlib.Analysis.Normed.Group.Basic
#align_import measure_theory.constructions.borel_space.basic from "leanprover-community/mathlib"@"9f55d0d4363ae59948c33864cbc52e0b12e0e8ce"
/-!
# Borel (measurable) space
## Main definitions
* `borel α` : the least `σ`-algebra that contains all open sets;
* `class BorelSpace` : a space with `TopologicalSpace` and `MeasurableSpace` structures
such that `‹MeasurableSpace α› = borel α`;
* `class OpensMeasurableSpace` : a space with `TopologicalSpace` and `MeasurableSpace`
structures such that all open sets are measurable; equivalently, `borel α ≤ ‹MeasurableSpace α›`.
* `BorelSpace` instances on `Empty`, `Unit`, `Bool`, `Nat`, `Int`, `Rat`;
* `MeasurableSpace` and `BorelSpace` instances on `ℝ`, `ℝ≥0`, `ℝ≥0∞`.
## Main statements
* `IsOpen.measurableSet`, `IsClosed.measurableSet`: open and closed sets are measurable;
* `Continuous.measurable` : a continuous function is measurable;
* `Continuous.measurable2` : if `f : α → β` and `g : α → γ` are measurable and `op : β × γ → δ`
is continuous, then `fun x => op (f x, g y)` is measurable;
* `Measurable.add` etc : dot notation for arithmetic operations on `Measurable` predicates,
and similarly for `dist` and `edist`;
* `AEMeasurable.add` : similar dot notation for almost everywhere measurable functions;
-/
noncomputable section
open Set Filter MeasureTheory
open scoped Classical Topology NNReal ENNReal MeasureTheory
universe u v w x y
variable {α β γ γ₂ δ : Type*} {ι : Sort y} {s t u : Set α}
open MeasurableSpace TopologicalSpace
/-- `MeasurableSpace` structure generated by `TopologicalSpace`. -/
def borel (α : Type u) [TopologicalSpace α] : MeasurableSpace α :=
generateFrom { s : Set α | IsOpen s }
#align borel borel
theorem borel_anti : Antitone (@borel α) := fun _ _ h =>
MeasurableSpace.generateFrom_le fun _ hs => .basic _ (h _ hs)
#align borel_anti borel_anti
theorem borel_eq_top_of_discrete [TopologicalSpace α] [DiscreteTopology α] : borel α = ⊤ :=
top_le_iff.1 fun s _ => GenerateMeasurable.basic s (isOpen_discrete s)
#align borel_eq_top_of_discrete borel_eq_top_of_discrete
theorem borel_eq_top_of_countable [TopologicalSpace α] [T1Space α] [Countable α] : borel α = ⊤ := by
refine top_le_iff.1 fun s _ => biUnion_of_singleton s ▸ ?_
apply MeasurableSet.biUnion s.to_countable
intro x _
apply MeasurableSet.of_compl
apply GenerateMeasurable.basic
exact isClosed_singleton.isOpen_compl
#align borel_eq_top_of_countable borel_eq_top_of_countable
theorem borel_eq_generateFrom_of_subbasis {s : Set (Set α)} [t : TopologicalSpace α]
[SecondCountableTopology α] (hs : t = .generateFrom s) : borel α = .generateFrom s :=
le_antisymm
(generateFrom_le fun u (hu : t.IsOpen u) => by
rw [hs] at hu
induction hu with
| basic u hu => exact GenerateMeasurable.basic u hu
| univ => exact @MeasurableSet.univ α (generateFrom s)
| inter s₁ s₂ _ _ hs₁ hs₂ => exact @MeasurableSet.inter α (generateFrom s) _ _ hs₁ hs₂
| sUnion f hf ih =>
rcases isOpen_sUnion_countable f (by rwa [hs]) with ⟨v, hv, vf, vu⟩
rw [← vu]
exact @MeasurableSet.sUnion α (generateFrom s) _ hv fun x xv => ih _ (vf xv))
(generateFrom_le fun u hu =>
GenerateMeasurable.basic _ <| show t.IsOpen u by rw [hs]; exact GenerateOpen.basic _ hu)
#align borel_eq_generate_from_of_subbasis borel_eq_generateFrom_of_subbasis
theorem TopologicalSpace.IsTopologicalBasis.borel_eq_generateFrom [TopologicalSpace α]
[SecondCountableTopology α] {s : Set (Set α)} (hs : IsTopologicalBasis s) :
borel α = .generateFrom s :=
borel_eq_generateFrom_of_subbasis hs.eq_generateFrom
#align topological_space.is_topological_basis.borel_eq_generate_from TopologicalSpace.IsTopologicalBasis.borel_eq_generateFrom
theorem isPiSystem_isOpen [TopologicalSpace α] : IsPiSystem ({s : Set α | IsOpen s}) :=
fun _s hs _t ht _ => IsOpen.inter hs ht
#align is_pi_system_is_open isPiSystem_isOpen
lemma isPiSystem_isClosed [TopologicalSpace α] : IsPiSystem ({s : Set α | IsClosed s}) :=
fun _s hs _t ht _ ↦ IsClosed.inter hs ht
theorem borel_eq_generateFrom_isClosed [TopologicalSpace α] :
borel α = .generateFrom { s | IsClosed s } :=
le_antisymm
(generateFrom_le fun _t ht =>
@MeasurableSet.of_compl α _ (generateFrom { s | IsClosed s })
(GenerateMeasurable.basic _ <| isClosed_compl_iff.2 ht))
(generateFrom_le fun _t ht =>
@MeasurableSet.of_compl α _ (borel α) (GenerateMeasurable.basic _ <| isOpen_compl_iff.2 ht))
#align borel_eq_generate_from_is_closed borel_eq_generateFrom_isClosed
theorem borel_comap {f : α → β} {t : TopologicalSpace β} :
@borel α (t.induced f) = (@borel β t).comap f :=
comap_generateFrom.symm
#align borel_comap borel_comap
theorem Continuous.borel_measurable [TopologicalSpace α] [TopologicalSpace β] {f : α → β}
(hf : Continuous f) : @Measurable α β (borel α) (borel β) f :=
Measurable.of_le_map <|
generateFrom_le fun s hs => GenerateMeasurable.basic (f ⁻¹' s) (hs.preimage hf)
#align continuous.borel_measurable Continuous.borel_measurable
/-- A space with `MeasurableSpace` and `TopologicalSpace` structures such that
all open sets are measurable. -/
class OpensMeasurableSpace (α : Type*) [TopologicalSpace α] [h : MeasurableSpace α] : Prop where
/-- Borel-measurable sets are measurable. -/
borel_le : borel α ≤ h
#align opens_measurable_space OpensMeasurableSpace
#align opens_measurable_space.borel_le OpensMeasurableSpace.borel_le
/-- A space with `MeasurableSpace` and `TopologicalSpace` structures such that
the `σ`-algebra of measurable sets is exactly the `σ`-algebra generated by open sets. -/
class BorelSpace (α : Type*) [TopologicalSpace α] [MeasurableSpace α] : Prop where
/-- The measurable sets are exactly the Borel-measurable sets. -/
measurable_eq : ‹MeasurableSpace α› = borel α
#align borel_space BorelSpace
#align borel_space.measurable_eq BorelSpace.measurable_eq
namespace Mathlib.Tactic.Borelize
open Lean Elab Term Tactic Meta
/-- The behaviour of `borelize α` depends on the existing assumptions on `α`.
- if `α` is a topological space with instances `[MeasurableSpace α] [BorelSpace α]`, then
`borelize α` replaces the former instance by `borel α`;
- otherwise, `borelize α` adds instances `borel α : MeasurableSpace α` and `⟨rfl⟩ : BorelSpace α`.
Finally, `borelize α β γ` runs `borelize α; borelize β; borelize γ`.
-/
syntax "borelize" (ppSpace colGt term:max)* : tactic
/-- Add instances `borel e : MeasurableSpace e` and `⟨rfl⟩ : BorelSpace e`. -/
def addBorelInstance (e : Expr) : TacticM Unit := do
let t ← Lean.Elab.Term.exprToSyntax e
evalTactic <| ← `(tactic|
refine_lift
letI : MeasurableSpace $t := borel $t
haveI : BorelSpace $t := ⟨rfl⟩
?_)
/-- Given a type `e`, an assumption `i : MeasurableSpace e`, and an instance `[BorelSpace e]`,
replace `i` with `borel e`. -/
def borelToRefl (e : Expr) (i : FVarId) : TacticM Unit := do
let te ← Lean.Elab.Term.exprToSyntax e
evalTactic <| ← `(tactic|
have := @BorelSpace.measurable_eq $te _ _ _)
try
liftMetaTactic fun m => return [← subst m i]
catch _ =>
let et ← synthInstance (← mkAppOptM ``TopologicalSpace #[e])
throwError m!"\
`‹TopologicalSpace {e}› := {et}\n\
depends on\n\
{Expr.fvar i} : MeasurableSpace {e}`\n\
so `borelize` isn't avaliable"
evalTactic <| ← `(tactic|
refine_lift
letI : MeasurableSpace $te := borel $te
?_)
/-- Given a type `$t`, if there is an assumption `[i : MeasurableSpace $t]`, then try to prove
`[BorelSpace $t]` and replace `i` with `borel $t`. Otherwise, add instances
`borel $t : MeasurableSpace $t` and `⟨rfl⟩ : BorelSpace $t`. -/
def borelize (t : Term) : TacticM Unit := withMainContext <| do
let u ← mkFreshLevelMVar
let e ← withoutRecover <| Tactic.elabTermEnsuringType t (mkSort (mkLevelSucc u))
let i? ← findLocalDeclWithType? (← mkAppOptM ``MeasurableSpace #[e])
i?.elim (addBorelInstance e) (borelToRefl e)
elab_rules : tactic
| `(tactic| borelize $[$t:term]*) => t.forM borelize
end Mathlib.Tactic.Borelize
instance (priority := 100) OrderDual.opensMeasurableSpace {α : Type*} [TopologicalSpace α]
[MeasurableSpace α] [h : OpensMeasurableSpace α] : OpensMeasurableSpace αᵒᵈ where
borel_le := h.borel_le
#align order_dual.opens_measurable_space OrderDual.opensMeasurableSpace
instance (priority := 100) OrderDual.borelSpace {α : Type*} [TopologicalSpace α]
[MeasurableSpace α] [h : BorelSpace α] : BorelSpace αᵒᵈ where
measurable_eq := h.measurable_eq
#align order_dual.borel_space OrderDual.borelSpace
/-- In a `BorelSpace` all open sets are measurable. -/
instance (priority := 100) BorelSpace.opensMeasurable {α : Type*} [TopologicalSpace α]
[MeasurableSpace α] [BorelSpace α] : OpensMeasurableSpace α :=
⟨ge_of_eq <| BorelSpace.measurable_eq⟩
#align borel_space.opens_measurable BorelSpace.opensMeasurable
instance Subtype.borelSpace {α : Type*} [TopologicalSpace α] [MeasurableSpace α]
[hα : BorelSpace α] (s : Set α) : BorelSpace s :=
⟨by borelize α; symm; apply borel_comap⟩
#align subtype.borel_space Subtype.borelSpace
instance Countable.instBorelSpace [Countable α] [MeasurableSpace α] [MeasurableSingletonClass α]
[TopologicalSpace α] [DiscreteTopology α] : BorelSpace α := by
have : ∀ s, @MeasurableSet α inferInstance s := fun s ↦ s.to_countable.measurableSet
have : ∀ s, @MeasurableSet α (borel α) s := fun s ↦ measurableSet_generateFrom (isOpen_discrete s)
exact ⟨by aesop⟩
instance Subtype.opensMeasurableSpace {α : Type*} [TopologicalSpace α] [MeasurableSpace α]
[h : OpensMeasurableSpace α] (s : Set α) : OpensMeasurableSpace s :=
⟨by
rw [borel_comap]
exact comap_mono h.1⟩
#align subtype.opens_measurable_space Subtype.opensMeasurableSpace
lemma opensMeasurableSpace_iff_forall_measurableSet
[TopologicalSpace α] [MeasurableSpace α] :
OpensMeasurableSpace α ↔ (∀ (s : Set α), IsOpen s → MeasurableSet s) := by
refine ⟨fun h s hs ↦ ?_, fun h ↦ ⟨generateFrom_le h⟩⟩
exact OpensMeasurableSpace.borel_le _ <| GenerateMeasurable.basic _ hs
instance (priority := 100) BorelSpace.countablyGenerated {α : Type*} [TopologicalSpace α]
[MeasurableSpace α] [BorelSpace α] [SecondCountableTopology α] : CountablyGenerated α := by
obtain ⟨b, bct, -, hb⟩ := exists_countable_basis α
refine ⟨⟨b, bct, ?_⟩⟩
borelize α
exact hb.borel_eq_generateFrom
#align borel_space.countably_generated BorelSpace.countablyGenerated
theorem MeasurableSet.induction_on_open [TopologicalSpace α] [MeasurableSpace α] [BorelSpace α]
{C : Set α → Prop} (h_open : ∀ U, IsOpen U → C U)
(h_compl : ∀ t, MeasurableSet t → C t → C tᶜ)
(h_union :
∀ f : ℕ → Set α,
Pairwise (Disjoint on f) → (∀ i, MeasurableSet (f i)) → (∀ i, C (f i)) → C (⋃ i, f i)) :
∀ ⦃t⦄, MeasurableSet t → C t :=
MeasurableSpace.induction_on_inter BorelSpace.measurable_eq isPiSystem_isOpen
(h_open _ isOpen_empty) h_open h_compl h_union
#align measurable_set.induction_on_open MeasurableSet.induction_on_open
section
variable [TopologicalSpace α] [MeasurableSpace α] [OpensMeasurableSpace α] [TopologicalSpace β]
[MeasurableSpace β] [OpensMeasurableSpace β] [TopologicalSpace γ] [MeasurableSpace γ]
[BorelSpace γ] [TopologicalSpace γ₂] [MeasurableSpace γ₂] [BorelSpace γ₂] [MeasurableSpace δ]
theorem IsOpen.measurableSet (h : IsOpen s) : MeasurableSet s :=
OpensMeasurableSpace.borel_le _ <| GenerateMeasurable.basic _ h
#align is_open.measurable_set IsOpen.measurableSet
instance (priority := 1000) {s : Set α} [h : HasCountableSeparatingOn α IsOpen s] :
CountablySeparated s := by
rw [CountablySeparated.subtype_iff]
exact .mono (fun _ ↦ IsOpen.measurableSet) Subset.rfl
@[measurability]
theorem measurableSet_interior : MeasurableSet (interior s) :=
isOpen_interior.measurableSet
#align measurable_set_interior measurableSet_interior
theorem IsGδ.measurableSet (h : IsGδ s) : MeasurableSet s := by
rcases h with ⟨S, hSo, hSc, rfl⟩
exact MeasurableSet.sInter hSc fun t ht => (hSo t ht).measurableSet
set_option linter.uppercaseLean3 false in
#align is_Gδ.measurable_set IsGδ.measurableSet
theorem measurableSet_of_continuousAt {β} [EMetricSpace β] (f : α → β) :
MeasurableSet { x | ContinuousAt f x } :=
(IsGδ.setOf_continuousAt f).measurableSet
#align measurable_set_of_continuous_at measurableSet_of_continuousAt
theorem IsClosed.measurableSet (h : IsClosed s) : MeasurableSet s :=
h.isOpen_compl.measurableSet.of_compl
#align is_closed.measurable_set IsClosed.measurableSet
theorem IsCompact.measurableSet [T2Space α] (h : IsCompact s) : MeasurableSet s :=
h.isClosed.measurableSet
#align is_compact.measurable_set IsCompact.measurableSet
/-- If two points are topologically inseparable,
then they can't be separated by a Borel measurable set. -/
theorem Inseparable.mem_measurableSet_iff {x y : γ} (h : Inseparable x y) {s : Set γ}
(hs : MeasurableSet s) : x ∈ s ↔ y ∈ s :=
hs.induction_on_open (C := fun s ↦ (x ∈ s ↔ y ∈ s)) (fun _ ↦ h.mem_open_iff) (fun s _ hs ↦ hs.not)
fun _ _ _ h ↦ by simp [h]
/-- If `K` is a compact set in an R₁ space and `s ⊇ K` is a Borel measurable superset,
then `s` includes the closure of `K` as well. -/
theorem IsCompact.closure_subset_measurableSet [R1Space γ] {K s : Set γ} (hK : IsCompact K)
(hs : MeasurableSet s) (hKs : K ⊆ s) : closure K ⊆ s := by
rw [hK.closure_eq_biUnion_inseparable, iUnion₂_subset_iff]
exact fun x hx y hy ↦ (hy.mem_measurableSet_iff hs).1 (hKs hx)
/-- In an R₁ topological space with Borel measure `μ`,
the measure of the closure of a compact set `K` is equal to the measure of `K`.
See also `MeasureTheory.Measure.OuterRegular.measure_closure_eq_of_isCompact`
for a version that assumes `μ` to be outer regular
but does not assume the `σ`-algebra to be Borel. -/
theorem IsCompact.measure_closure [R1Space γ] {K : Set γ} (hK : IsCompact K) (μ : Measure γ) :
μ (closure K) = μ K := by
refine le_antisymm ?_ (measure_mono subset_closure)
calc
μ (closure K) ≤ μ (toMeasurable μ K) := measure_mono <|
hK.closure_subset_measurableSet (measurableSet_toMeasurable ..) (subset_toMeasurable ..)
_ = μ K := measure_toMeasurable ..
@[measurability]
theorem measurableSet_closure : MeasurableSet (closure s) :=
isClosed_closure.measurableSet
#align measurable_set_closure measurableSet_closure
theorem measurable_of_isOpen {f : δ → γ} (hf : ∀ s, IsOpen s → MeasurableSet (f ⁻¹' s)) :
Measurable f := by
rw [‹BorelSpace γ›.measurable_eq]
exact measurable_generateFrom hf
#align measurable_of_is_open measurable_of_isOpen
theorem measurable_of_isClosed {f : δ → γ} (hf : ∀ s, IsClosed s → MeasurableSet (f ⁻¹' s)) :
Measurable f := by
apply measurable_of_isOpen; intro s hs
rw [← MeasurableSet.compl_iff, ← preimage_compl]; apply hf; rw [isClosed_compl_iff]; exact hs
#align measurable_of_is_closed measurable_of_isClosed
theorem measurable_of_isClosed' {f : δ → γ}
(hf : ∀ s, IsClosed s → s.Nonempty → s ≠ univ → MeasurableSet (f ⁻¹' s)) : Measurable f := by
apply measurable_of_isClosed; intro s hs
rcases eq_empty_or_nonempty s with h1 | h1
· simp [h1]
by_cases h2 : s = univ
· simp [h2]
exact hf s hs h1 h2
#align measurable_of_is_closed' measurable_of_isClosed'
instance nhds_isMeasurablyGenerated (a : α) : (𝓝 a).IsMeasurablyGenerated := by
rw [nhds, iInf_subtype']
refine @Filter.iInf_isMeasurablyGenerated α _ _ _ fun i => ?_
exact i.2.2.measurableSet.principal_isMeasurablyGenerated
#align nhds_is_measurably_generated nhds_isMeasurablyGenerated
/-- If `s` is a measurable set, then `𝓝[s] a` is a measurably generated filter for
each `a`. This cannot be an `instance` because it depends on a non-instance `hs : MeasurableSet s`.
-/
theorem MeasurableSet.nhdsWithin_isMeasurablyGenerated {s : Set α} (hs : MeasurableSet s) (a : α) :
(𝓝[s] a).IsMeasurablyGenerated :=
haveI := hs.principal_isMeasurablyGenerated
Filter.inf_isMeasurablyGenerated _ _
#align measurable_set.nhds_within_is_measurably_generated MeasurableSet.nhdsWithin_isMeasurablyGenerated
instance (priority := 100) OpensMeasurableSpace.separatesPoints [T0Space α] :
SeparatesPoints α := by
rw [separatesPoints_iff]
intro x y hxy
apply Inseparable.eq
rw [inseparable_iff_forall_open]
exact fun s hs => hxy _ hs.measurableSet
-- see Note [lower instance priority]
instance (priority := 100) OpensMeasurableSpace.toMeasurableSingletonClass [T1Space α] :
MeasurableSingletonClass α :=
⟨fun _ => isClosed_singleton.measurableSet⟩
#align opens_measurable_space.to_measurable_singleton_class OpensMeasurableSpace.toMeasurableSingletonClass
instance Pi.opensMeasurableSpace {ι : Type*} {π : ι → Type*} [Countable ι]
[t' : ∀ i, TopologicalSpace (π i)] [∀ i, MeasurableSpace (π i)]
[∀ i, SecondCountableTopology (π i)] [∀ i, OpensMeasurableSpace (π i)] :
OpensMeasurableSpace (∀ i, π i) := by
constructor
have : Pi.topologicalSpace = .generateFrom { t | ∃ (s : ∀ a, Set (π a)) (i : Finset ι),
(∀ a ∈ i, s a ∈ countableBasis (π a)) ∧ t = pi (↑i) s } := by
simp only [funext fun a => @eq_generateFrom_countableBasis (π a) _ _, pi_generateFrom_eq]
rw [borel_eq_generateFrom_of_subbasis this]
apply generateFrom_le
rintro _ ⟨s, i, hi, rfl⟩
refine MeasurableSet.pi i.countable_toSet fun a ha => IsOpen.measurableSet ?_
rw [eq_generateFrom_countableBasis (π a)]
exact .basic _ (hi a ha)
#align pi.opens_measurable_space Pi.opensMeasurableSpace
/-- The typeclass `SecondCountableTopologyEither α β` registers the fact that at least one of
the two spaces has second countable topology. This is the right assumption to ensure that continuous
maps from `α` to `β` are strongly measurable. -/
class SecondCountableTopologyEither (α β : Type*) [TopologicalSpace α] [TopologicalSpace β] :
Prop where
/-- The projection out of `SecondCountableTopologyEither` -/
out : SecondCountableTopology α ∨ SecondCountableTopology β
#align second_countable_topology_either SecondCountableTopologyEither
instance (priority := 100) secondCountableTopologyEither_of_left (α β : Type*) [TopologicalSpace α]
[TopologicalSpace β] [SecondCountableTopology α] : SecondCountableTopologyEither α β where
out := Or.inl (by infer_instance)
#align second_countable_topology_either_of_left secondCountableTopologyEither_of_left
instance (priority := 100) secondCountableTopologyEither_of_right (α β : Type*)
[TopologicalSpace α] [TopologicalSpace β] [SecondCountableTopology β] :
SecondCountableTopologyEither α β where
out := Or.inr (by infer_instance)
#align second_countable_topology_either_of_right secondCountableTopologyEither_of_right
/-- If either `α` or `β` has second-countable topology, then the open sets in `α × β` belong to the
product sigma-algebra. -/
instance Prod.opensMeasurableSpace [h : SecondCountableTopologyEither α β] :
OpensMeasurableSpace (α × β) := by
apply opensMeasurableSpace_iff_forall_measurableSet.2 (fun s hs ↦ ?_)
rcases h.out with hα|hβ
· let F : Set α → Set β := fun a ↦ {y | ∃ b, IsOpen b ∧ y ∈ b ∧ a ×ˢ b ⊆ s}
have A : ∀ a, IsOpen (F a) := by
intro a
apply isOpen_iff_forall_mem_open.2
rintro y ⟨b, b_open, yb, hb⟩
exact ⟨b, fun z zb ↦ ⟨b, b_open, zb, hb⟩, b_open, yb⟩
have : s = ⋃ a ∈ countableBasis α, a ×ˢ F a := by
apply Subset.antisymm
· rintro ⟨y1, y2⟩ hy
rcases isOpen_prod_iff.1 hs y1 y2 hy with ⟨u, v, u_open, v_open, yu, yv, huv⟩
obtain ⟨a, ha, ya, au⟩ : ∃ a ∈ countableBasis α, y1 ∈ a ∧ a ⊆ u :=
IsTopologicalBasis.exists_subset_of_mem_open (isBasis_countableBasis α) yu u_open
simp only [mem_iUnion, mem_prod, mem_setOf_eq, exists_and_left, exists_prop]
exact ⟨a, ya, ha, v, v_open, yv, (Set.prod_mono_left au).trans huv⟩
· rintro ⟨y1, y2⟩ hy
simp only [mem_iUnion, mem_prod, mem_setOf_eq, exists_and_left, exists_prop] at hy
rcases hy with ⟨a, ya, -, b, -, yb, hb⟩
exact hb (mem_prod.2 ⟨ya, yb⟩)
rw [this]
apply MeasurableSet.biUnion (countable_countableBasis α) (fun a ha ↦ ?_)
exact (isOpen_of_mem_countableBasis ha).measurableSet.prod (A a).measurableSet
· let F : Set β → Set α := fun a ↦ {y | ∃ b, IsOpen b ∧ y ∈ b ∧ b ×ˢ a ⊆ s}
have A : ∀ a, IsOpen (F a) := by
intro a
apply isOpen_iff_forall_mem_open.2
rintro y ⟨b, b_open, yb, hb⟩
exact ⟨b, fun z zb ↦ ⟨b, b_open, zb, hb⟩, b_open, yb⟩
have : s = ⋃ a ∈ countableBasis β, F a ×ˢ a := by
apply Subset.antisymm
· rintro ⟨y1, y2⟩ hy
rcases isOpen_prod_iff.1 hs y1 y2 hy with ⟨u, v, u_open, v_open, yu, yv, huv⟩
obtain ⟨a, ha, ya, au⟩ : ∃ a ∈ countableBasis β, y2 ∈ a ∧ a ⊆ v :=
IsTopologicalBasis.exists_subset_of_mem_open (isBasis_countableBasis β) yv v_open
simp only [mem_iUnion, mem_prod, mem_setOf_eq, exists_and_left, exists_prop]
exact ⟨a, ⟨u, u_open, yu, (Set.prod_mono_right au).trans huv⟩, ha, ya⟩
· rintro ⟨y1, y2⟩ hy
simp only [mem_iUnion, mem_prod, mem_setOf_eq, exists_and_left, exists_prop] at hy
rcases hy with ⟨a, ⟨b, -, yb, hb⟩, -, ya⟩
exact hb (mem_prod.2 ⟨yb, ya⟩)
rw [this]
apply MeasurableSet.biUnion (countable_countableBasis β) (fun a ha ↦ ?_)
exact (A a).measurableSet.prod (isOpen_of_mem_countableBasis ha).measurableSet
variable {α' : Type*} [TopologicalSpace α'] [MeasurableSpace α']
theorem interior_ae_eq_of_null_frontier {μ : Measure α'} {s : Set α'} (h : μ (frontier s) = 0) :
interior s =ᵐ[μ] s :=
interior_subset.eventuallyLE.antisymm <| subset_closure.eventuallyLE.trans (ae_le_set.2 h)
#align interior_ae_eq_of_null_frontier interior_ae_eq_of_null_frontier
theorem measure_interior_of_null_frontier {μ : Measure α'} {s : Set α'} (h : μ (frontier s) = 0) :
μ (interior s) = μ s :=
measure_congr (interior_ae_eq_of_null_frontier h)
#align measure_interior_of_null_frontier measure_interior_of_null_frontier
theorem nullMeasurableSet_of_null_frontier {s : Set α} {μ : Measure α} (h : μ (frontier s) = 0) :
NullMeasurableSet s μ :=
⟨interior s, isOpen_interior.measurableSet, (interior_ae_eq_of_null_frontier h).symm⟩
#align null_measurable_set_of_null_frontier nullMeasurableSet_of_null_frontier
theorem closure_ae_eq_of_null_frontier {μ : Measure α'} {s : Set α'} (h : μ (frontier s) = 0) :
closure s =ᵐ[μ] s :=
((ae_le_set.2 h).trans interior_subset.eventuallyLE).antisymm <| subset_closure.eventuallyLE
#align closure_ae_eq_of_null_frontier closure_ae_eq_of_null_frontier
theorem measure_closure_of_null_frontier {μ : Measure α'} {s : Set α'} (h : μ (frontier s) = 0) :
μ (closure s) = μ s :=
measure_congr (closure_ae_eq_of_null_frontier h)
#align measure_closure_of_null_frontier measure_closure_of_null_frontier
instance separatesPointsOfOpensMeasurableSpaceOfT0Space [T0Space α] :
MeasurableSpace.SeparatesPoints α where
separates x y := by
contrapose!
intro x_ne_y
obtain ⟨U, U_open, mem_U⟩ := exists_isOpen_xor'_mem x_ne_y
by_cases x_in_U : x ∈ U
· refine ⟨U, U_open.measurableSet, x_in_U, ?_⟩
simp_all only [ne_eq, xor_true, not_false_eq_true]
· refine ⟨Uᶜ, U_open.isClosed_compl.measurableSet, x_in_U, ?_⟩
simp_all only [ne_eq, xor_false, id_eq, mem_compl_iff, not_true_eq_false, not_false_eq_true]
/-- A continuous function from an `OpensMeasurableSpace` to a `BorelSpace`
is measurable. -/
theorem Continuous.measurable {f : α → γ} (hf : Continuous f) : Measurable f :=
hf.borel_measurable.mono OpensMeasurableSpace.borel_le (le_of_eq <| BorelSpace.measurable_eq)
#align continuous.measurable Continuous.measurable
/-- A continuous function from an `OpensMeasurableSpace` to a `BorelSpace`
is ae-measurable. -/
theorem Continuous.aemeasurable {f : α → γ} (h : Continuous f) {μ : Measure α} : AEMeasurable f μ :=
h.measurable.aemeasurable
#align continuous.ae_measurable Continuous.aemeasurable
theorem ClosedEmbedding.measurable {f : α → γ} (hf : ClosedEmbedding f) : Measurable f :=
hf.continuous.measurable
#align closed_embedding.measurable ClosedEmbedding.measurable
/-- If a function is defined piecewise in terms of functions which are continuous on their
respective pieces, then it is measurable. -/
theorem ContinuousOn.measurable_piecewise {f g : α → γ} {s : Set α} [∀ j : α, Decidable (j ∈ s)]
(hf : ContinuousOn f s) (hg : ContinuousOn g sᶜ) (hs : MeasurableSet s) :
Measurable (s.piecewise f g) := by
refine measurable_of_isOpen fun t ht => ?_
rw [piecewise_preimage, Set.ite]
apply MeasurableSet.union
· rcases _root_.continuousOn_iff'.1 hf t ht with ⟨u, u_open, hu⟩
rw [hu]
exact u_open.measurableSet.inter hs
· rcases _root_.continuousOn_iff'.1 hg t ht with ⟨u, u_open, hu⟩
rw [diff_eq_compl_inter, inter_comm, hu]
exact u_open.measurableSet.inter hs.compl
#align continuous_on.measurable_piecewise ContinuousOn.measurable_piecewise
@[to_additive]
instance (priority := 100) ContinuousMul.measurableMul [Mul γ] [ContinuousMul γ] :
MeasurableMul γ where
measurable_const_mul _ := (continuous_const.mul continuous_id).measurable
measurable_mul_const _ := (continuous_id.mul continuous_const).measurable
#align has_continuous_mul.has_measurable_mul ContinuousMul.measurableMul
#align has_continuous_add.has_measurable_add ContinuousAdd.measurableAdd
instance (priority := 100) ContinuousSub.measurableSub [Sub γ] [ContinuousSub γ] :
MeasurableSub γ where
measurable_const_sub _ := (continuous_const.sub continuous_id).measurable
measurable_sub_const _ := (continuous_id.sub continuous_const).measurable
#align has_continuous_sub.has_measurable_sub ContinuousSub.measurableSub
@[to_additive]
instance (priority := 100) TopologicalGroup.measurableInv [Group γ] [TopologicalGroup γ] :
MeasurableInv γ :=
⟨continuous_inv.measurable⟩
#align topological_group.has_measurable_inv TopologicalGroup.measurableInv
#align topological_add_group.has_measurable_neg TopologicalAddGroup.measurableNeg
instance (priority := 100) ContinuousSMul.measurableSMul {M α} [TopologicalSpace M]
[TopologicalSpace α] [MeasurableSpace M] [MeasurableSpace α] [OpensMeasurableSpace M]
[BorelSpace α] [SMul M α] [ContinuousSMul M α] : MeasurableSMul M α :=
⟨fun _ => (continuous_const_smul _).measurable, fun _ =>
(continuous_id.smul continuous_const).measurable⟩
#align has_continuous_smul.has_measurable_smul ContinuousSMul.measurableSMul
section Homeomorph
@[measurability]
protected theorem Homeomorph.measurable (h : α ≃ₜ γ) : Measurable h :=
h.continuous.measurable
#align homeomorph.measurable Homeomorph.measurable
/-- A homeomorphism between two Borel spaces is a measurable equivalence. -/
def Homeomorph.toMeasurableEquiv (h : γ ≃ₜ γ₂) : γ ≃ᵐ γ₂ where
measurable_toFun := h.measurable
measurable_invFun := h.symm.measurable
toEquiv := h.toEquiv
#align homeomorph.to_measurable_equiv Homeomorph.toMeasurableEquiv
lemma Homeomorph.measurableEmbedding (h : γ ≃ₜ γ₂) : MeasurableEmbedding h :=
h.toMeasurableEquiv.measurableEmbedding
@[simp]
theorem Homeomorph.toMeasurableEquiv_coe (h : γ ≃ₜ γ₂) : (h.toMeasurableEquiv : γ → γ₂) = h :=
rfl
#align homeomorph.to_measurable_equiv_coe Homeomorph.toMeasurableEquiv_coe
@[simp]
theorem Homeomorph.toMeasurableEquiv_symm_coe (h : γ ≃ₜ γ₂) :
(h.toMeasurableEquiv.symm : γ₂ → γ) = h.symm :=
rfl
#align homeomorph.to_measurable_equiv_symm_coe Homeomorph.toMeasurableEquiv_symm_coe
end Homeomorph
@[measurability]
theorem ContinuousMap.measurable (f : C(α, γ)) : Measurable f :=
f.continuous.measurable
#align continuous_map.measurable ContinuousMap.measurable
theorem measurable_of_continuousOn_compl_singleton [T1Space α] {f : α → γ} (a : α)
(hf : ContinuousOn f {a}ᶜ) : Measurable f :=
measurable_of_measurable_on_compl_singleton a
(continuousOn_iff_continuous_restrict.1 hf).measurable
#align measurable_of_continuous_on_compl_singleton measurable_of_continuousOn_compl_singleton
theorem Continuous.measurable2 [SecondCountableTopologyEither α β] {f : δ → α}
{g : δ → β} {c : α → β → γ} (h : Continuous fun p : α × β => c p.1 p.2) (hf : Measurable f)
(hg : Measurable g) : Measurable fun a => c (f a) (g a) :=
h.measurable.comp (hf.prod_mk hg)
#align continuous.measurable2 Continuous.measurable2
theorem Continuous.aemeasurable2 [SecondCountableTopologyEither α β]
{f : δ → α} {g : δ → β} {c : α → β → γ} {μ : Measure δ}
(h : Continuous fun p : α × β => c p.1 p.2) (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (fun a => c (f a) (g a)) μ :=
h.measurable.comp_aemeasurable (hf.prod_mk hg)
#align continuous.ae_measurable2 Continuous.aemeasurable2
instance (priority := 100) HasContinuousInv₀.measurableInv [GroupWithZero γ] [T1Space γ]
[HasContinuousInv₀ γ] : MeasurableInv γ :=
⟨measurable_of_continuousOn_compl_singleton 0 continuousOn_inv₀⟩
#align has_continuous_inv₀.has_measurable_inv HasContinuousInv₀.measurableInv
@[to_additive]
instance (priority := 100) ContinuousMul.measurableMul₂ [SecondCountableTopology γ] [Mul γ]
[ContinuousMul γ] : MeasurableMul₂ γ :=
⟨continuous_mul.measurable⟩
#align has_continuous_mul.has_measurable_mul₂ ContinuousMul.measurableMul₂
#align has_continuous_add.has_measurable_mul₂ ContinuousAdd.measurableMul₂
instance (priority := 100) ContinuousSub.measurableSub₂ [SecondCountableTopology γ] [Sub γ]
[ContinuousSub γ] : MeasurableSub₂ γ :=
⟨continuous_sub.measurable⟩
#align has_continuous_sub.has_measurable_sub₂ ContinuousSub.measurableSub₂
instance (priority := 100) ContinuousSMul.measurableSMul₂ {M α} [TopologicalSpace M]
[MeasurableSpace M] [OpensMeasurableSpace M] [TopologicalSpace α]
[SecondCountableTopologyEither M α] [MeasurableSpace α] [BorelSpace α] [SMul M α]
[ContinuousSMul M α] : MeasurableSMul₂ M α :=
⟨continuous_smul.measurable⟩
#align has_continuous_smul.has_measurable_smul₂ ContinuousSMul.measurableSMul₂
end
section BorelSpace
variable [TopologicalSpace α] [MeasurableSpace α] [BorelSpace α] [TopologicalSpace β]
[MeasurableSpace β] [BorelSpace β] [TopologicalSpace γ] [MeasurableSpace γ] [BorelSpace γ]
[MeasurableSpace δ]
theorem pi_le_borel_pi {ι : Type*} {π : ι → Type*} [∀ i, TopologicalSpace (π i)]
[∀ i, MeasurableSpace (π i)] [∀ i, BorelSpace (π i)] :
MeasurableSpace.pi ≤ borel (∀ i, π i) := by
have : ‹∀ i, MeasurableSpace (π i)› = fun i => borel (π i) :=
funext fun i => BorelSpace.measurable_eq
rw [this]
exact iSup_le fun i => comap_le_iff_le_map.2 <| (continuous_apply i).borel_measurable
#align pi_le_borel_pi pi_le_borel_pi
| Mathlib/MeasureTheory/Constructions/BorelSpace/Basic.lean | 657 | 661 | theorem prod_le_borel_prod : Prod.instMeasurableSpace ≤ borel (α × β) := by |
rw [‹BorelSpace α›.measurable_eq, ‹BorelSpace β›.measurable_eq]
refine sup_le ?_ ?_
· exact comap_le_iff_le_map.mpr continuous_fst.borel_measurable
· exact comap_le_iff_le_map.mpr continuous_snd.borel_measurable
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Kevin Buzzard, Yury Kudryashov, Frédéric Dupuis,
Heather Macbeth
-/
import Mathlib.Algebra.Module.Submodule.EqLocus
import Mathlib.Algebra.Module.Submodule.RestrictScalars
import Mathlib.Algebra.Ring.Idempotents
import Mathlib.Data.Set.Pointwise.SMul
import Mathlib.LinearAlgebra.Basic
import Mathlib.Order.CompactlyGenerated.Basic
import Mathlib.Order.OmegaCompletePartialOrder
#align_import linear_algebra.span from "leanprover-community/mathlib"@"10878f6bf1dab863445907ab23fbfcefcb5845d0"
/-!
# The span of a set of vectors, as a submodule
* `Submodule.span s` is defined to be the smallest submodule containing the set `s`.
## Notations
* We introduce the notation `R ∙ v` for the span of a singleton, `Submodule.span R {v}`. This is
`\span`, not the same as the scalar multiplication `•`/`\bub`.
-/
variable {R R₂ K M M₂ V S : Type*}
namespace Submodule
open Function Set
open Pointwise
section AddCommMonoid
variable [Semiring R] [AddCommMonoid M] [Module R M]
variable {x : M} (p p' : Submodule R M)
variable [Semiring R₂] {σ₁₂ : R →+* R₂}
variable [AddCommMonoid M₂] [Module R₂ M₂]
variable {F : Type*} [FunLike F M M₂] [SemilinearMapClass F σ₁₂ M M₂]
section
variable (R)
/-- The span of a set `s ⊆ M` is the smallest submodule of M that contains `s`. -/
def span (s : Set M) : Submodule R M :=
sInf { p | s ⊆ p }
#align submodule.span Submodule.span
variable {R}
-- Porting note: renamed field to `principal'` and added `principal` to fix explicit argument
/-- An `R`-submodule of `M` is principal if it is generated by one element. -/
@[mk_iff]
class IsPrincipal (S : Submodule R M) : Prop where
principal' : ∃ a, S = span R {a}
#align submodule.is_principal Submodule.IsPrincipal
theorem IsPrincipal.principal (S : Submodule R M) [S.IsPrincipal] :
∃ a, S = span R {a} :=
Submodule.IsPrincipal.principal'
#align submodule.is_principal.principal Submodule.IsPrincipal.principal
end
variable {s t : Set M}
theorem mem_span : x ∈ span R s ↔ ∀ p : Submodule R M, s ⊆ p → x ∈ p :=
mem_iInter₂
#align submodule.mem_span Submodule.mem_span
@[aesop safe 20 apply (rule_sets := [SetLike])]
theorem subset_span : s ⊆ span R s := fun _ h => mem_span.2 fun _ hp => hp h
#align submodule.subset_span Submodule.subset_span
theorem span_le {p} : span R s ≤ p ↔ s ⊆ p :=
⟨Subset.trans subset_span, fun ss _ h => mem_span.1 h _ ss⟩
#align submodule.span_le Submodule.span_le
theorem span_mono (h : s ⊆ t) : span R s ≤ span R t :=
span_le.2 <| Subset.trans h subset_span
#align submodule.span_mono Submodule.span_mono
theorem span_monotone : Monotone (span R : Set M → Submodule R M) := fun _ _ => span_mono
#align submodule.span_monotone Submodule.span_monotone
theorem span_eq_of_le (h₁ : s ⊆ p) (h₂ : p ≤ span R s) : span R s = p :=
le_antisymm (span_le.2 h₁) h₂
#align submodule.span_eq_of_le Submodule.span_eq_of_le
theorem span_eq : span R (p : Set M) = p :=
span_eq_of_le _ (Subset.refl _) subset_span
#align submodule.span_eq Submodule.span_eq
theorem span_eq_span (hs : s ⊆ span R t) (ht : t ⊆ span R s) : span R s = span R t :=
le_antisymm (span_le.2 hs) (span_le.2 ht)
#align submodule.span_eq_span Submodule.span_eq_span
/-- A version of `Submodule.span_eq` for subobjects closed under addition and scalar multiplication
and containing zero. In general, this should not be used directly, but can be used to quickly
generate proofs for specific types of subobjects. -/
lemma coe_span_eq_self [SetLike S M] [AddSubmonoidClass S M] [SMulMemClass S R M] (s : S) :
(span R (s : Set M) : Set M) = s := by
refine le_antisymm ?_ subset_span
let s' : Submodule R M :=
{ carrier := s
add_mem' := add_mem
zero_mem' := zero_mem _
smul_mem' := SMulMemClass.smul_mem }
exact span_le (p := s') |>.mpr le_rfl
/-- A version of `Submodule.span_eq` for when the span is by a smaller ring. -/
@[simp]
theorem span_coe_eq_restrictScalars [Semiring S] [SMul S R] [Module S M] [IsScalarTower S R M] :
span S (p : Set M) = p.restrictScalars S :=
span_eq (p.restrictScalars S)
#align submodule.span_coe_eq_restrict_scalars Submodule.span_coe_eq_restrictScalars
/-- A version of `Submodule.map_span_le` that does not require the `RingHomSurjective`
assumption. -/
theorem image_span_subset (f : F) (s : Set M) (N : Submodule R₂ M₂) :
f '' span R s ⊆ N ↔ ∀ m ∈ s, f m ∈ N := image_subset_iff.trans <| span_le (p := N.comap f)
theorem image_span_subset_span (f : F) (s : Set M) : f '' span R s ⊆ span R₂ (f '' s) :=
(image_span_subset f s _).2 fun x hx ↦ subset_span ⟨x, hx, rfl⟩
theorem map_span [RingHomSurjective σ₁₂] (f : F) (s : Set M) :
(span R s).map f = span R₂ (f '' s) :=
Eq.symm <| span_eq_of_le _ (Set.image_subset f subset_span) (image_span_subset_span f s)
#align submodule.map_span Submodule.map_span
alias _root_.LinearMap.map_span := Submodule.map_span
#align linear_map.map_span LinearMap.map_span
theorem map_span_le [RingHomSurjective σ₁₂] (f : F) (s : Set M) (N : Submodule R₂ M₂) :
map f (span R s) ≤ N ↔ ∀ m ∈ s, f m ∈ N := image_span_subset f s N
#align submodule.map_span_le Submodule.map_span_le
alias _root_.LinearMap.map_span_le := Submodule.map_span_le
#align linear_map.map_span_le LinearMap.map_span_le
@[simp]
theorem span_insert_zero : span R (insert (0 : M) s) = span R s := by
refine le_antisymm ?_ (Submodule.span_mono (Set.subset_insert 0 s))
rw [span_le, Set.insert_subset_iff]
exact ⟨by simp only [SetLike.mem_coe, Submodule.zero_mem], Submodule.subset_span⟩
#align submodule.span_insert_zero Submodule.span_insert_zero
-- See also `span_preimage_eq` below.
theorem span_preimage_le (f : F) (s : Set M₂) :
span R (f ⁻¹' s) ≤ (span R₂ s).comap f := by
rw [span_le, comap_coe]
exact preimage_mono subset_span
#align submodule.span_preimage_le Submodule.span_preimage_le
alias _root_.LinearMap.span_preimage_le := Submodule.span_preimage_le
#align linear_map.span_preimage_le LinearMap.span_preimage_le
theorem closure_subset_span {s : Set M} : (AddSubmonoid.closure s : Set M) ⊆ span R s :=
(@AddSubmonoid.closure_le _ _ _ (span R s).toAddSubmonoid).mpr subset_span
#align submodule.closure_subset_span Submodule.closure_subset_span
theorem closure_le_toAddSubmonoid_span {s : Set M} :
AddSubmonoid.closure s ≤ (span R s).toAddSubmonoid :=
closure_subset_span
#align submodule.closure_le_to_add_submonoid_span Submodule.closure_le_toAddSubmonoid_span
@[simp]
theorem span_closure {s : Set M} : span R (AddSubmonoid.closure s : Set M) = span R s :=
le_antisymm (span_le.mpr closure_subset_span) (span_mono AddSubmonoid.subset_closure)
#align submodule.span_closure Submodule.span_closure
/-- An induction principle for span membership. If `p` holds for 0 and all elements of `s`, and is
preserved under addition and scalar multiplication, then `p` holds for all elements of the span of
`s`. -/
@[elab_as_elim]
theorem span_induction {p : M → Prop} (h : x ∈ span R s) (mem : ∀ x ∈ s, p x) (zero : p 0)
(add : ∀ x y, p x → p y → p (x + y)) (smul : ∀ (a : R) (x), p x → p (a • x)) : p x :=
((@span_le (p := ⟨⟨⟨p, by intros x y; exact add x y⟩, zero⟩, smul⟩)) s).2 mem h
#align submodule.span_induction Submodule.span_induction
/-- An induction principle for span membership. This is a version of `Submodule.span_induction`
for binary predicates. -/
theorem span_induction₂ {p : M → M → Prop} {a b : M} (ha : a ∈ Submodule.span R s)
(hb : b ∈ Submodule.span R s) (mem_mem : ∀ x ∈ s, ∀ y ∈ s, p x y)
(zero_left : ∀ y, p 0 y) (zero_right : ∀ x, p x 0)
(add_left : ∀ x₁ x₂ y, p x₁ y → p x₂ y → p (x₁ + x₂) y)
(add_right : ∀ x y₁ y₂, p x y₁ → p x y₂ → p x (y₁ + y₂))
(smul_left : ∀ (r : R) x y, p x y → p (r • x) y)
(smul_right : ∀ (r : R) x y, p x y → p x (r • y)) : p a b :=
Submodule.span_induction ha
(fun x hx => Submodule.span_induction hb (mem_mem x hx) (zero_right x) (add_right x) fun r =>
smul_right r x)
(zero_left b) (fun x₁ x₂ => add_left x₁ x₂ b) fun r x => smul_left r x b
/-- A dependent version of `Submodule.span_induction`. -/
@[elab_as_elim]
theorem span_induction' {p : ∀ x, x ∈ span R s → Prop}
(mem : ∀ (x) (h : x ∈ s), p x (subset_span h))
(zero : p 0 (Submodule.zero_mem _))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›))
(smul : ∀ (a : R) (x hx), p x hx → p (a • x) (Submodule.smul_mem _ _ ‹_›)) {x}
(hx : x ∈ span R s) : p x hx := by
refine Exists.elim ?_ fun (hx : x ∈ span R s) (hc : p x hx) => hc
refine
span_induction hx (fun m hm => ⟨subset_span hm, mem m hm⟩) ⟨zero_mem _, zero⟩
(fun x y hx hy =>
Exists.elim hx fun hx' hx =>
Exists.elim hy fun hy' hy => ⟨add_mem hx' hy', add _ _ _ _ hx hy⟩)
fun r x hx => Exists.elim hx fun hx' hx => ⟨smul_mem _ _ hx', smul r _ _ hx⟩
#align submodule.span_induction' Submodule.span_induction'
open AddSubmonoid in
theorem span_eq_closure {s : Set M} : (span R s).toAddSubmonoid = closure (@univ R • s) := by
refine le_antisymm
(fun x hx ↦ span_induction hx (fun x hx ↦ subset_closure ⟨1, trivial, x, hx, one_smul R x⟩)
(zero_mem _) (fun _ _ ↦ add_mem) fun r m hm ↦ closure_induction hm ?_ ?_ fun _ _ h h' ↦ ?_)
(closure_le.2 ?_)
· rintro _ ⟨r, -, m, hm, rfl⟩; exact smul_mem _ _ (subset_span hm)
· rintro _ ⟨r', -, m, hm, rfl⟩; exact subset_closure ⟨r * r', trivial, m, hm, mul_smul r r' m⟩
· rw [smul_zero]; apply zero_mem
· rw [smul_add]; exact add_mem h h'
/-- A variant of `span_induction` that combines `∀ x ∈ s, p x` and `∀ r x, p x → p (r • x)`
into a single condition `∀ r, ∀ x ∈ s, p (r • x)`, which can be easier to verify. -/
@[elab_as_elim]
theorem closure_induction {p : M → Prop} (h : x ∈ span R s) (zero : p 0)
(add : ∀ x y, p x → p y → p (x + y)) (smul_mem : ∀ r : R, ∀ x ∈ s, p (r • x)) : p x := by
rw [← mem_toAddSubmonoid, span_eq_closure] at h
refine AddSubmonoid.closure_induction h ?_ zero add
rintro _ ⟨r, -, m, hm, rfl⟩
exact smul_mem r m hm
/-- A dependent version of `Submodule.closure_induction`. -/
@[elab_as_elim]
theorem closure_induction' {p : ∀ x, x ∈ span R s → Prop}
(zero : p 0 (Submodule.zero_mem _))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›))
(smul_mem : ∀ (r x) (h : x ∈ s), p (r • x) (Submodule.smul_mem _ _ <| subset_span h)) {x}
(hx : x ∈ span R s) : p x hx := by
refine Exists.elim ?_ fun (hx : x ∈ span R s) (hc : p x hx) ↦ hc
refine closure_induction hx ⟨zero_mem _, zero⟩
(fun x y hx hy ↦ Exists.elim hx fun hx' hx ↦
Exists.elim hy fun hy' hy ↦ ⟨add_mem hx' hy', add _ _ _ _ hx hy⟩)
fun r x hx ↦ ⟨Submodule.smul_mem _ _ (subset_span hx), smul_mem r x hx⟩
@[simp]
theorem span_span_coe_preimage : span R (((↑) : span R s → M) ⁻¹' s) = ⊤ :=
eq_top_iff.2 fun x ↦ Subtype.recOn x fun x hx _ ↦ by
refine span_induction' (p := fun x hx ↦ (⟨x, hx⟩ : span R s) ∈ span R (Subtype.val ⁻¹' s))
(fun x' hx' ↦ subset_span hx') ?_ (fun x _ y _ ↦ ?_) (fun r x _ ↦ ?_) hx
· exact zero_mem _
· exact add_mem
· exact smul_mem _ _
#align submodule.span_span_coe_preimage Submodule.span_span_coe_preimage
@[simp]
lemma span_setOf_mem_eq_top :
span R {x : span R s | (x : M) ∈ s} = ⊤ :=
span_span_coe_preimage
theorem span_nat_eq_addSubmonoid_closure (s : Set M) :
(span ℕ s).toAddSubmonoid = AddSubmonoid.closure s := by
refine Eq.symm (AddSubmonoid.closure_eq_of_le subset_span ?_)
apply (OrderIso.to_galoisConnection (AddSubmonoid.toNatSubmodule (M := M)).symm).l_le
(a := span ℕ s) (b := AddSubmonoid.closure s)
rw [span_le]
exact AddSubmonoid.subset_closure
#align submodule.span_nat_eq_add_submonoid_closure Submodule.span_nat_eq_addSubmonoid_closure
@[simp]
theorem span_nat_eq (s : AddSubmonoid M) : (span ℕ (s : Set M)).toAddSubmonoid = s := by
rw [span_nat_eq_addSubmonoid_closure, s.closure_eq]
#align submodule.span_nat_eq Submodule.span_nat_eq
theorem span_int_eq_addSubgroup_closure {M : Type*} [AddCommGroup M] (s : Set M) :
(span ℤ s).toAddSubgroup = AddSubgroup.closure s :=
Eq.symm <|
AddSubgroup.closure_eq_of_le _ subset_span fun x hx =>
span_induction hx (fun x hx => AddSubgroup.subset_closure hx) (AddSubgroup.zero_mem _)
(fun _ _ => AddSubgroup.add_mem _) fun _ _ _ => AddSubgroup.zsmul_mem _ ‹_› _
#align submodule.span_int_eq_add_subgroup_closure Submodule.span_int_eq_addSubgroup_closure
@[simp]
theorem span_int_eq {M : Type*} [AddCommGroup M] (s : AddSubgroup M) :
(span ℤ (s : Set M)).toAddSubgroup = s := by rw [span_int_eq_addSubgroup_closure, s.closure_eq]
#align submodule.span_int_eq Submodule.span_int_eq
section
variable (R M)
/-- `span` forms a Galois insertion with the coercion from submodule to set. -/
protected def gi : GaloisInsertion (@span R M _ _ _) (↑) where
choice s _ := span R s
gc _ _ := span_le
le_l_u _ := subset_span
choice_eq _ _ := rfl
#align submodule.gi Submodule.gi
end
@[simp]
theorem span_empty : span R (∅ : Set M) = ⊥ :=
(Submodule.gi R M).gc.l_bot
#align submodule.span_empty Submodule.span_empty
@[simp]
theorem span_univ : span R (univ : Set M) = ⊤ :=
eq_top_iff.2 <| SetLike.le_def.2 <| subset_span
#align submodule.span_univ Submodule.span_univ
theorem span_union (s t : Set M) : span R (s ∪ t) = span R s ⊔ span R t :=
(Submodule.gi R M).gc.l_sup
#align submodule.span_union Submodule.span_union
theorem span_iUnion {ι} (s : ι → Set M) : span R (⋃ i, s i) = ⨆ i, span R (s i) :=
(Submodule.gi R M).gc.l_iSup
#align submodule.span_Union Submodule.span_iUnion
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
/- ./././Mathport/Syntax/Translate/Expr.lean:107:6: warning: expanding binder group (i j) -/
theorem span_iUnion₂ {ι} {κ : ι → Sort*} (s : ∀ i, κ i → Set M) :
span R (⋃ (i) (j), s i j) = ⨆ (i) (j), span R (s i j) :=
(Submodule.gi R M).gc.l_iSup₂
#align submodule.span_Union₂ Submodule.span_iUnion₂
theorem span_attach_biUnion [DecidableEq M] {α : Type*} (s : Finset α) (f : s → Finset M) :
span R (s.attach.biUnion f : Set M) = ⨆ x, span R (f x) := by simp [span_iUnion]
#align submodule.span_attach_bUnion Submodule.span_attach_biUnion
| Mathlib/LinearAlgebra/Span.lean | 336 | 336 | theorem sup_span : p ⊔ span R s = span R (p ∪ s) := by | rw [Submodule.span_union, p.span_eq]
|
/-
Copyright (c) 2018 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Johannes Hölzl, Yaël Dillies
-/
import Mathlib.Analysis.Normed.Group.Seminorm
import Mathlib.Order.LiminfLimsup
import Mathlib.Topology.Instances.Rat
import Mathlib.Topology.MetricSpace.Algebra
import Mathlib.Topology.MetricSpace.IsometricSMul
import Mathlib.Topology.Sequences
#align_import analysis.normed.group.basic from "leanprover-community/mathlib"@"41bef4ae1254365bc190aee63b947674d2977f01"
/-!
# Normed (semi)groups
In this file we define 10 classes:
* `Norm`, `NNNorm`: auxiliary classes endowing a type `α` with a function `norm : α → ℝ`
(notation: `‖x‖`) and `nnnorm : α → ℝ≥0` (notation: `‖x‖₊`), respectively;
* `Seminormed...Group`: A seminormed (additive) (commutative) group is an (additive) (commutative)
group with a norm and a compatible pseudometric space structure:
`∀ x y, dist x y = ‖x / y‖` or `∀ x y, dist x y = ‖x - y‖`, depending on the group operation.
* `Normed...Group`: A normed (additive) (commutative) group is an (additive) (commutative) group
with a norm and a compatible metric space structure.
We also prove basic properties of (semi)normed groups and provide some instances.
## TODO
This file is huge; move material into separate files,
such as `Mathlib/Analysis/Normed/Group/Lemmas.lean`.
## Notes
The current convention `dist x y = ‖x - y‖` means that the distance is invariant under right
addition, but actions in mathlib are usually from the left. This means we might want to change it to
`dist x y = ‖-x + y‖`.
The normed group hierarchy would lend itself well to a mixin design (that is, having
`SeminormedGroup` and `SeminormedAddGroup` not extend `Group` and `AddGroup`), but we choose not
to for performance concerns.
## Tags
normed group
-/
variable {𝓕 𝕜 α ι κ E F G : Type*}
open Filter Function Metric Bornology
open ENNReal Filter NNReal Uniformity Pointwise Topology
/-- Auxiliary class, endowing a type `E` with a function `norm : E → ℝ` with notation `‖x‖`. This
class is designed to be extended in more interesting classes specifying the properties of the norm.
-/
@[notation_class]
class Norm (E : Type*) where
/-- the `ℝ`-valued norm function. -/
norm : E → ℝ
#align has_norm Norm
/-- Auxiliary class, endowing a type `α` with a function `nnnorm : α → ℝ≥0` with notation `‖x‖₊`. -/
@[notation_class]
class NNNorm (E : Type*) where
/-- the `ℝ≥0`-valued norm function. -/
nnnorm : E → ℝ≥0
#align has_nnnorm NNNorm
export Norm (norm)
export NNNorm (nnnorm)
@[inherit_doc]
notation "‖" e "‖" => norm e
@[inherit_doc]
notation "‖" e "‖₊" => nnnorm e
/-- A seminormed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖`
defines a pseudometric space structure. -/
class SeminormedAddGroup (E : Type*) extends Norm E, AddGroup E, PseudoMetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align seminormed_add_group SeminormedAddGroup
/-- A seminormed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a
pseudometric space structure. -/
@[to_additive]
class SeminormedGroup (E : Type*) extends Norm E, Group E, PseudoMetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align seminormed_group SeminormedGroup
/-- A normed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a
metric space structure. -/
class NormedAddGroup (E : Type*) extends Norm E, AddGroup E, MetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align normed_add_group NormedAddGroup
/-- A normed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a metric
space structure. -/
@[to_additive]
class NormedGroup (E : Type*) extends Norm E, Group E, MetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align normed_group NormedGroup
/-- A seminormed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖`
defines a pseudometric space structure. -/
class SeminormedAddCommGroup (E : Type*) extends Norm E, AddCommGroup E,
PseudoMetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align seminormed_add_comm_group SeminormedAddCommGroup
/-- A seminormed group is a group endowed with a norm for which `dist x y = ‖x / y‖`
defines a pseudometric space structure. -/
@[to_additive]
class SeminormedCommGroup (E : Type*) extends Norm E, CommGroup E, PseudoMetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align seminormed_comm_group SeminormedCommGroup
/-- A normed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a
metric space structure. -/
class NormedAddCommGroup (E : Type*) extends Norm E, AddCommGroup E, MetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align normed_add_comm_group NormedAddCommGroup
/-- A normed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a metric
space structure. -/
@[to_additive]
class NormedCommGroup (E : Type*) extends Norm E, CommGroup E, MetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align normed_comm_group NormedCommGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) NormedGroup.toSeminormedGroup [NormedGroup E] : SeminormedGroup E :=
{ ‹NormedGroup E› with }
#align normed_group.to_seminormed_group NormedGroup.toSeminormedGroup
#align normed_add_group.to_seminormed_add_group NormedAddGroup.toSeminormedAddGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) NormedCommGroup.toSeminormedCommGroup [NormedCommGroup E] :
SeminormedCommGroup E :=
{ ‹NormedCommGroup E› with }
#align normed_comm_group.to_seminormed_comm_group NormedCommGroup.toSeminormedCommGroup
#align normed_add_comm_group.to_seminormed_add_comm_group NormedAddCommGroup.toSeminormedAddCommGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) SeminormedCommGroup.toSeminormedGroup [SeminormedCommGroup E] :
SeminormedGroup E :=
{ ‹SeminormedCommGroup E› with }
#align seminormed_comm_group.to_seminormed_group SeminormedCommGroup.toSeminormedGroup
#align seminormed_add_comm_group.to_seminormed_add_group SeminormedAddCommGroup.toSeminormedAddGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) NormedCommGroup.toNormedGroup [NormedCommGroup E] : NormedGroup E :=
{ ‹NormedCommGroup E› with }
#align normed_comm_group.to_normed_group NormedCommGroup.toNormedGroup
#align normed_add_comm_group.to_normed_add_group NormedAddCommGroup.toNormedAddGroup
-- See note [reducible non-instances]
/-- Construct a `NormedGroup` from a `SeminormedGroup` satisfying `∀ x, ‖x‖ = 0 → x = 1`. This
avoids having to go back to the `(Pseudo)MetricSpace` level when declaring a `NormedGroup`
instance as a special case of a more general `SeminormedGroup` instance. -/
@[to_additive (attr := reducible) "Construct a `NormedAddGroup` from a `SeminormedAddGroup`
satisfying `∀ x, ‖x‖ = 0 → x = 0`. This avoids having to go back to the `(Pseudo)MetricSpace`
level when declaring a `NormedAddGroup` instance as a special case of a more general
`SeminormedAddGroup` instance."]
def NormedGroup.ofSeparation [SeminormedGroup E] (h : ∀ x : E, ‖x‖ = 0 → x = 1) :
NormedGroup E where
dist_eq := ‹SeminormedGroup E›.dist_eq
toMetricSpace :=
{ eq_of_dist_eq_zero := fun hxy =>
div_eq_one.1 <| h _ <| by exact (‹SeminormedGroup E›.dist_eq _ _).symm.trans hxy }
-- Porting note: the `rwa` no longer worked, but it was easy enough to provide the term.
-- however, notice that if you make `x` and `y` accessible, then the following does work:
-- `have := ‹SeminormedGroup E›.dist_eq x y; rwa [← this]`, so I'm not sure why the `rwa`
-- was broken.
#align normed_group.of_separation NormedGroup.ofSeparation
#align normed_add_group.of_separation NormedAddGroup.ofSeparation
-- See note [reducible non-instances]
/-- Construct a `NormedCommGroup` from a `SeminormedCommGroup` satisfying
`∀ x, ‖x‖ = 0 → x = 1`. This avoids having to go back to the `(Pseudo)MetricSpace` level when
declaring a `NormedCommGroup` instance as a special case of a more general `SeminormedCommGroup`
instance. -/
@[to_additive (attr := reducible) "Construct a `NormedAddCommGroup` from a
`SeminormedAddCommGroup` satisfying `∀ x, ‖x‖ = 0 → x = 0`. This avoids having to go back to the
`(Pseudo)MetricSpace` level when declaring a `NormedAddCommGroup` instance as a special case
of a more general `SeminormedAddCommGroup` instance."]
def NormedCommGroup.ofSeparation [SeminormedCommGroup E] (h : ∀ x : E, ‖x‖ = 0 → x = 1) :
NormedCommGroup E :=
{ ‹SeminormedCommGroup E›, NormedGroup.ofSeparation h with }
#align normed_comm_group.of_separation NormedCommGroup.ofSeparation
#align normed_add_comm_group.of_separation NormedAddCommGroup.ofSeparation
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant distance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant distance."]
def SeminormedGroup.ofMulDist [Norm E] [Group E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) :
SeminormedGroup E where
dist_eq x y := by
rw [h₁]; apply le_antisymm
· simpa only [div_eq_mul_inv, ← mul_right_inv y] using h₂ _ _ _
· simpa only [div_mul_cancel, one_mul] using h₂ (x / y) 1 y
#align seminormed_group.of_mul_dist SeminormedGroup.ofMulDist
#align seminormed_add_group.of_add_dist SeminormedAddGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant pseudodistance."]
def SeminormedGroup.ofMulDist' [Norm E] [Group E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) :
SeminormedGroup E where
dist_eq x y := by
rw [h₁]; apply le_antisymm
· simpa only [div_mul_cancel, one_mul] using h₂ (x / y) 1 y
· simpa only [div_eq_mul_inv, ← mul_right_inv y] using h₂ _ _ _
#align seminormed_group.of_mul_dist' SeminormedGroup.ofMulDist'
#align seminormed_add_group.of_add_dist' SeminormedAddGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant pseudodistance."]
def SeminormedCommGroup.ofMulDist [Norm E] [CommGroup E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) :
SeminormedCommGroup E :=
{ SeminormedGroup.ofMulDist h₁ h₂ with
mul_comm := mul_comm }
#align seminormed_comm_group.of_mul_dist SeminormedCommGroup.ofMulDist
#align seminormed_add_comm_group.of_add_dist SeminormedAddCommGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant pseudodistance."]
def SeminormedCommGroup.ofMulDist' [Norm E] [CommGroup E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) :
SeminormedCommGroup E :=
{ SeminormedGroup.ofMulDist' h₁ h₂ with
mul_comm := mul_comm }
#align seminormed_comm_group.of_mul_dist' SeminormedCommGroup.ofMulDist'
#align seminormed_add_comm_group.of_add_dist' SeminormedAddCommGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant distance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant distance."]
def NormedGroup.ofMulDist [Norm E] [Group E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1)
(h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) : NormedGroup E :=
{ SeminormedGroup.ofMulDist h₁ h₂ with
eq_of_dist_eq_zero := eq_of_dist_eq_zero }
#align normed_group.of_mul_dist NormedGroup.ofMulDist
#align normed_add_group.of_add_dist NormedAddGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant pseudodistance."]
def NormedGroup.ofMulDist' [Norm E] [Group E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1)
(h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) : NormedGroup E :=
{ SeminormedGroup.ofMulDist' h₁ h₂ with
eq_of_dist_eq_zero := eq_of_dist_eq_zero }
#align normed_group.of_mul_dist' NormedGroup.ofMulDist'
#align normed_add_group.of_add_dist' NormedAddGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant pseudodistance."]
def NormedCommGroup.ofMulDist [Norm E] [CommGroup E] [MetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) :
NormedCommGroup E :=
{ NormedGroup.ofMulDist h₁ h₂ with
mul_comm := mul_comm }
#align normed_comm_group.of_mul_dist NormedCommGroup.ofMulDist
#align normed_add_comm_group.of_add_dist NormedAddCommGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant pseudodistance."]
def NormedCommGroup.ofMulDist' [Norm E] [CommGroup E] [MetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) :
NormedCommGroup E :=
{ NormedGroup.ofMulDist' h₁ h₂ with
mul_comm := mul_comm }
#align normed_comm_group.of_mul_dist' NormedCommGroup.ofMulDist'
#align normed_add_comm_group.of_add_dist' NormedAddCommGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the
pseudometric space structure from the seminorm properties. Note that in most cases this instance
creates bad definitional equalities (e.g., it does not take into account a possibly existing
`UniformSpace` instance on `E`). -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a seminorm, i.e., registering the pseudodistance
and the pseudometric space structure from the seminorm properties. Note that in most cases this
instance creates bad definitional equalities (e.g., it does not take into account a possibly
existing `UniformSpace` instance on `E`)."]
def GroupSeminorm.toSeminormedGroup [Group E] (f : GroupSeminorm E) : SeminormedGroup E where
dist x y := f (x / y)
norm := f
dist_eq x y := rfl
dist_self x := by simp only [div_self', map_one_eq_zero]
dist_triangle := le_map_div_add_map_div f
dist_comm := map_div_rev f
edist_dist x y := by exact ENNReal.coe_nnreal_eq _
-- Porting note: how did `mathlib3` solve this automatically?
#align group_seminorm.to_seminormed_group GroupSeminorm.toSeminormedGroup
#align add_group_seminorm.to_seminormed_add_group AddGroupSeminorm.toSeminormedAddGroup
-- See note [reducible non-instances]
/-- Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the
pseudometric space structure from the seminorm properties. Note that in most cases this instance
creates bad definitional equalities (e.g., it does not take into account a possibly existing
`UniformSpace` instance on `E`). -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a seminorm, i.e., registering the pseudodistance
and the pseudometric space structure from the seminorm properties. Note that in most cases this
instance creates bad definitional equalities (e.g., it does not take into account a possibly
existing `UniformSpace` instance on `E`)."]
def GroupSeminorm.toSeminormedCommGroup [CommGroup E] (f : GroupSeminorm E) :
SeminormedCommGroup E :=
{ f.toSeminormedGroup with
mul_comm := mul_comm }
#align group_seminorm.to_seminormed_comm_group GroupSeminorm.toSeminormedCommGroup
#align add_group_seminorm.to_seminormed_add_comm_group AddGroupSeminorm.toSeminormedAddCommGroup
-- See note [reducible non-instances]
/-- Construct a normed group from a norm, i.e., registering the distance and the metric space
structure from the norm properties. Note that in most cases this instance creates bad definitional
equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on
`E`). -/
@[to_additive (attr := reducible)
"Construct a normed group from a norm, i.e., registering the distance and the metric
space structure from the norm properties. Note that in most cases this instance creates bad
definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace`
instance on `E`)."]
def GroupNorm.toNormedGroup [Group E] (f : GroupNorm E) : NormedGroup E :=
{ f.toGroupSeminorm.toSeminormedGroup with
eq_of_dist_eq_zero := fun h => div_eq_one.1 <| eq_one_of_map_eq_zero f h }
#align group_norm.to_normed_group GroupNorm.toNormedGroup
#align add_group_norm.to_normed_add_group AddGroupNorm.toNormedAddGroup
-- See note [reducible non-instances]
/-- Construct a normed group from a norm, i.e., registering the distance and the metric space
structure from the norm properties. Note that in most cases this instance creates bad definitional
equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on
`E`). -/
@[to_additive (attr := reducible)
"Construct a normed group from a norm, i.e., registering the distance and the metric
space structure from the norm properties. Note that in most cases this instance creates bad
definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace`
instance on `E`)."]
def GroupNorm.toNormedCommGroup [CommGroup E] (f : GroupNorm E) : NormedCommGroup E :=
{ f.toNormedGroup with
mul_comm := mul_comm }
#align group_norm.to_normed_comm_group GroupNorm.toNormedCommGroup
#align add_group_norm.to_normed_add_comm_group AddGroupNorm.toNormedAddCommGroup
instance PUnit.normedAddCommGroup : NormedAddCommGroup PUnit where
norm := Function.const _ 0
dist_eq _ _ := rfl
@[simp]
theorem PUnit.norm_eq_zero (r : PUnit) : ‖r‖ = 0 :=
rfl
#align punit.norm_eq_zero PUnit.norm_eq_zero
section SeminormedGroup
variable [SeminormedGroup E] [SeminormedGroup F] [SeminormedGroup G] {s : Set E}
{a a₁ a₂ b b₁ b₂ : E} {r r₁ r₂ : ℝ}
@[to_additive]
theorem dist_eq_norm_div (a b : E) : dist a b = ‖a / b‖ :=
SeminormedGroup.dist_eq _ _
#align dist_eq_norm_div dist_eq_norm_div
#align dist_eq_norm_sub dist_eq_norm_sub
@[to_additive]
| Mathlib/Analysis/Normed/Group/Basic.lean | 407 | 407 | theorem dist_eq_norm_div' (a b : E) : dist a b = ‖b / a‖ := by | rw [dist_comm, dist_eq_norm_div]
|
/-
Copyright (c) 2022 Floris van Doorn, Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Heather Macbeth
-/
import Mathlib.Geometry.Manifold.ContMDiff.Atlas
import Mathlib.Geometry.Manifold.VectorBundle.FiberwiseLinear
import Mathlib.Topology.VectorBundle.Constructions
#align_import geometry.manifold.vector_bundle.basic from "leanprover-community/mathlib"@"e473c3198bb41f68560cab68a0529c854b618833"
/-! # Smooth vector bundles
This file defines smooth vector bundles over a smooth manifold.
Let `E` be a topological vector bundle, with model fiber `F` and base space `B`. We consider `E` as
carrying a charted space structure given by its trivializations -- these are charts to `B × F`.
Then, by "composition", if `B` is itself a charted space over `H` (e.g. a smooth manifold), then `E`
is also a charted space over `H × F`.
Now, we define `SmoothVectorBundle` as the `Prop` of having smooth transition functions.
Recall the structure groupoid `smoothFiberwiseLinear` on `B × F` consisting of smooth, fiberwise
linear partial homeomorphisms. We show that our definition of "smooth vector bundle" implies
`HasGroupoid` for this groupoid, and show (by a "composition" of `HasGroupoid` instances) that
this means that a smooth vector bundle is a smooth manifold.
Since `SmoothVectorBundle` is a mixin, it should be easy to make variants and for many such
variants to coexist -- vector bundles can be smooth vector bundles over several different base
fields, they can also be C^k vector bundles, etc.
## Main definitions and constructions
* `FiberBundle.chartedSpace`: A fiber bundle `E` over a base `B` with model fiber `F` is naturally
a charted space modelled on `B × F`.
* `FiberBundle.chartedSpace'`: Let `B` be a charted space modelled on `HB`. Then a fiber bundle
`E` over a base `B` with model fiber `F` is naturally a charted space modelled on `HB.prod F`.
* `SmoothVectorBundle`: Mixin class stating that a (topological) `VectorBundle` is smooth, in the
sense of having smooth transition functions.
* `SmoothFiberwiseLinear.hasGroupoid`: For a smooth vector bundle `E` over `B` with fiber
modelled on `F`, the change-of-co-ordinates between two trivializations `e`, `e'` for `E`,
considered as charts to `B × F`, is smooth and fiberwise linear, in the sense of belonging to the
structure groupoid `smoothFiberwiseLinear`.
* `Bundle.TotalSpace.smoothManifoldWithCorners`: A smooth vector bundle is naturally a smooth
manifold.
* `VectorBundleCore.smoothVectorBundle`: If a (topological) `VectorBundleCore` is smooth,
in the sense of having smooth transition functions (cf. `VectorBundleCore.IsSmooth`),
then the vector bundle constructed from it is a smooth vector bundle.
* `VectorPrebundle.smoothVectorBundle`: If a `VectorPrebundle` is smooth,
in the sense of having smooth transition functions (cf. `VectorPrebundle.IsSmooth`),
then the vector bundle constructed from it is a smooth vector bundle.
* `Bundle.Prod.smoothVectorBundle`: The direct sum of two smooth vector bundles is a smooth vector
bundle.
-/
assert_not_exists mfderiv
open Bundle Set PartialHomeomorph
open Function (id_def)
open Filter
open scoped Manifold Bundle Topology
variable {𝕜 B B' F M : Type*} {E : B → Type*}
/-! ### Charted space structure on a fiber bundle -/
section
variable [TopologicalSpace F] [TopologicalSpace (TotalSpace F E)] [∀ x, TopologicalSpace (E x)]
{HB : Type*} [TopologicalSpace HB] [TopologicalSpace B] [ChartedSpace HB B] [FiberBundle F E]
/-- A fiber bundle `E` over a base `B` with model fiber `F` is naturally a charted space modelled on
`B × F`. -/
instance FiberBundle.chartedSpace' : ChartedSpace (B × F) (TotalSpace F E) where
atlas := (fun e : Trivialization F (π F E) => e.toPartialHomeomorph) '' trivializationAtlas F E
chartAt x := (trivializationAt F E x.proj).toPartialHomeomorph
mem_chart_source x :=
(trivializationAt F E x.proj).mem_source.mpr (mem_baseSet_trivializationAt F E x.proj)
chart_mem_atlas _ := mem_image_of_mem _ (trivialization_mem_atlas F E _)
#align fiber_bundle.charted_space FiberBundle.chartedSpace'
theorem FiberBundle.chartedSpace'_chartAt (x : TotalSpace F E) :
chartAt (B × F) x = (trivializationAt F E x.proj).toPartialHomeomorph :=
rfl
/- Porting note: In Lean 3, the next instance was inside a section with locally reducible
`ModelProd` and it used `ModelProd B F` as the intermediate space. Using `B × F` in the middle
gives the same instance.
-/
--attribute [local reducible] ModelProd
/-- Let `B` be a charted space modelled on `HB`. Then a fiber bundle `E` over a base `B` with model
fiber `F` is naturally a charted space modelled on `HB.prod F`. -/
instance FiberBundle.chartedSpace : ChartedSpace (ModelProd HB F) (TotalSpace F E) :=
ChartedSpace.comp _ (B × F) _
#align fiber_bundle.charted_space' FiberBundle.chartedSpace
theorem FiberBundle.chartedSpace_chartAt (x : TotalSpace F E) :
chartAt (ModelProd HB F) x =
(trivializationAt F E x.proj).toPartialHomeomorph ≫ₕ
(chartAt HB x.proj).prod (PartialHomeomorph.refl F) := by
dsimp only [chartAt_comp, prodChartedSpace_chartAt, FiberBundle.chartedSpace'_chartAt,
chartAt_self_eq]
rw [Trivialization.coe_coe, Trivialization.coe_fst' _ (mem_baseSet_trivializationAt F E x.proj)]
#align fiber_bundle.charted_space_chart_at FiberBundle.chartedSpace_chartAt
theorem FiberBundle.chartedSpace_chartAt_symm_fst (x : TotalSpace F E) (y : ModelProd HB F)
(hy : y ∈ (chartAt (ModelProd HB F) x).target) :
((chartAt (ModelProd HB F) x).symm y).proj = (chartAt HB x.proj).symm y.1 := by
simp only [FiberBundle.chartedSpace_chartAt, mfld_simps] at hy ⊢
exact (trivializationAt F E x.proj).proj_symm_apply hy.2
#align fiber_bundle.charted_space_chart_at_symm_fst FiberBundle.chartedSpace_chartAt_symm_fst
end
section
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup F] [NormedSpace 𝕜 F]
[TopologicalSpace (TotalSpace F E)] [∀ x, TopologicalSpace (E x)] {EB : Type*}
[NormedAddCommGroup EB] [NormedSpace 𝕜 EB] {HB : Type*} [TopologicalSpace HB]
(IB : ModelWithCorners 𝕜 EB HB) (E' : B → Type*) [∀ x, Zero (E' x)] {EM : Type*}
[NormedAddCommGroup EM] [NormedSpace 𝕜 EM] {HM : Type*} [TopologicalSpace HM]
{IM : ModelWithCorners 𝕜 EM HM} [TopologicalSpace M] [ChartedSpace HM M]
[Is : SmoothManifoldWithCorners IM M] {n : ℕ∞}
variable [TopologicalSpace B] [ChartedSpace HB B] [FiberBundle F E]
protected theorem FiberBundle.extChartAt (x : TotalSpace F E) :
extChartAt (IB.prod 𝓘(𝕜, F)) x =
(trivializationAt F E x.proj).toPartialEquiv ≫
(extChartAt IB x.proj).prod (PartialEquiv.refl F) := by
simp_rw [extChartAt, FiberBundle.chartedSpace_chartAt, extend]
simp only [PartialEquiv.trans_assoc, mfld_simps]
-- Porting note: should not be needed
rw [PartialEquiv.prod_trans, PartialEquiv.refl_trans]
#align fiber_bundle.ext_chart_at FiberBundle.extChartAt
protected theorem FiberBundle.extChartAt_target (x : TotalSpace F E) :
(extChartAt (IB.prod 𝓘(𝕜, F)) x).target =
((extChartAt IB x.proj).target ∩
(extChartAt IB x.proj).symm ⁻¹' (trivializationAt F E x.proj).baseSet) ×ˢ univ := by
rw [FiberBundle.extChartAt, PartialEquiv.trans_target, Trivialization.target_eq, inter_prod]
rfl
theorem FiberBundle.writtenInExtChartAt_trivializationAt {x : TotalSpace F E} {y}
(hy : y ∈ (extChartAt (IB.prod 𝓘(𝕜, F)) x).target) :
writtenInExtChartAt (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) x
(trivializationAt F E x.proj) y = y :=
writtenInExtChartAt_chartAt_comp _ _ hy
theorem FiberBundle.writtenInExtChartAt_trivializationAt_symm {x : TotalSpace F E} {y}
(hy : y ∈ (extChartAt (IB.prod 𝓘(𝕜, F)) x).target) :
writtenInExtChartAt (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) (trivializationAt F E x.proj x)
(trivializationAt F E x.proj).toPartialHomeomorph.symm y = y :=
writtenInExtChartAt_chartAt_symm_comp _ _ hy
/-! ### Smoothness of maps in/out fiber bundles
Note: For these results we don't need that the bundle is a smooth vector bundle, or even a vector
bundle at all, just that it is a fiber bundle over a charted base space.
-/
namespace Bundle
variable {IB}
/-- Characterization of C^n functions into a smooth vector bundle. -/
theorem contMDiffWithinAt_totalSpace (f : M → TotalSpace F E) {s : Set M} {x₀ : M} :
ContMDiffWithinAt IM (IB.prod 𝓘(𝕜, F)) n f s x₀ ↔
ContMDiffWithinAt IM IB n (fun x => (f x).proj) s x₀ ∧
ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun x ↦ (trivializationAt F E (f x₀).proj (f x)).2) s x₀ := by
simp (config := { singlePass := true }) only [contMDiffWithinAt_iff_target]
rw [and_and_and_comm, ← FiberBundle.continuousWithinAt_totalSpace, and_congr_right_iff]
intro hf
simp_rw [modelWithCornersSelf_prod, FiberBundle.extChartAt, Function.comp,
PartialEquiv.trans_apply, PartialEquiv.prod_coe, PartialEquiv.refl_coe,
extChartAt_self_apply, modelWithCornersSelf_coe, Function.id_def, ← chartedSpaceSelf_prod]
refine (contMDiffWithinAt_prod_iff _).trans (and_congr ?_ Iff.rfl)
have h1 : (fun x => (f x).proj) ⁻¹' (trivializationAt F E (f x₀).proj).baseSet ∈ 𝓝[s] x₀ :=
((FiberBundle.continuous_proj F E).continuousWithinAt.comp hf (mapsTo_image f s))
((Trivialization.open_baseSet _).mem_nhds (mem_baseSet_trivializationAt F E _))
refine EventuallyEq.contMDiffWithinAt_iff (eventually_of_mem h1 fun x hx => ?_) ?_
· simp_rw [Function.comp, PartialHomeomorph.coe_coe, Trivialization.coe_coe]
rw [Trivialization.coe_fst']
exact hx
· simp only [mfld_simps]
#align bundle.cont_mdiff_within_at_total_space Bundle.contMDiffWithinAt_totalSpace
/-- Characterization of C^n functions into a smooth vector bundle. -/
theorem contMDiffAt_totalSpace (f : M → TotalSpace F E) (x₀ : M) :
ContMDiffAt IM (IB.prod 𝓘(𝕜, F)) n f x₀ ↔
ContMDiffAt IM IB n (fun x => (f x).proj) x₀ ∧
ContMDiffAt IM 𝓘(𝕜, F) n (fun x => (trivializationAt F E (f x₀).proj (f x)).2) x₀ := by
simp_rw [← contMDiffWithinAt_univ]; exact contMDiffWithinAt_totalSpace f
#align bundle.cont_mdiff_at_total_space Bundle.contMDiffAt_totalSpace
/-- Characterization of C^n sections of a smooth vector bundle. -/
theorem contMDiffAt_section (s : ∀ x, E x) (x₀ : B) :
ContMDiffAt IB (IB.prod 𝓘(𝕜, F)) n (fun x => TotalSpace.mk' F x (s x)) x₀ ↔
ContMDiffAt IB 𝓘(𝕜, F) n (fun x ↦ (trivializationAt F E x₀ ⟨x, s x⟩).2) x₀ := by
simp_rw [contMDiffAt_totalSpace, and_iff_right_iff_imp]; intro; exact contMDiffAt_id
#align bundle.cont_mdiff_at_section Bundle.contMDiffAt_section
variable (E)
theorem contMDiff_proj : ContMDiff (IB.prod 𝓘(𝕜, F)) IB n (π F E) := fun x ↦ by
have : ContMDiffAt (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) n id x := contMDiffAt_id
rw [contMDiffAt_totalSpace] at this
exact this.1
#align bundle.cont_mdiff_proj Bundle.contMDiff_proj
theorem smooth_proj : Smooth (IB.prod 𝓘(𝕜, F)) IB (π F E) :=
contMDiff_proj E
#align bundle.smooth_proj Bundle.smooth_proj
theorem contMDiffOn_proj {s : Set (TotalSpace F E)} :
ContMDiffOn (IB.prod 𝓘(𝕜, F)) IB n (π F E) s :=
(Bundle.contMDiff_proj E).contMDiffOn
#align bundle.cont_mdiff_on_proj Bundle.contMDiffOn_proj
theorem smoothOn_proj {s : Set (TotalSpace F E)} : SmoothOn (IB.prod 𝓘(𝕜, F)) IB (π F E) s :=
contMDiffOn_proj E
#align bundle.smooth_on_proj Bundle.smoothOn_proj
theorem contMDiffAt_proj {p : TotalSpace F E} : ContMDiffAt (IB.prod 𝓘(𝕜, F)) IB n (π F E) p :=
(Bundle.contMDiff_proj E).contMDiffAt
#align bundle.cont_mdiff_at_proj Bundle.contMDiffAt_proj
theorem smoothAt_proj {p : TotalSpace F E} : SmoothAt (IB.prod 𝓘(𝕜, F)) IB (π F E) p :=
Bundle.contMDiffAt_proj E
#align bundle.smooth_at_proj Bundle.smoothAt_proj
theorem contMDiffWithinAt_proj {s : Set (TotalSpace F E)} {p : TotalSpace F E} :
ContMDiffWithinAt (IB.prod 𝓘(𝕜, F)) IB n (π F E) s p :=
(Bundle.contMDiffAt_proj E).contMDiffWithinAt
#align bundle.cont_mdiff_within_at_proj Bundle.contMDiffWithinAt_proj
theorem smoothWithinAt_proj {s : Set (TotalSpace F E)} {p : TotalSpace F E} :
SmoothWithinAt (IB.prod 𝓘(𝕜, F)) IB (π F E) s p :=
Bundle.contMDiffWithinAt_proj E
#align bundle.smooth_within_at_proj Bundle.smoothWithinAt_proj
variable (𝕜) [∀ x, AddCommMonoid (E x)]
variable [∀ x, Module 𝕜 (E x)] [VectorBundle 𝕜 F E]
theorem smooth_zeroSection : Smooth IB (IB.prod 𝓘(𝕜, F)) (zeroSection F E) := fun x ↦ by
unfold zeroSection
rw [Bundle.contMDiffAt_section]
apply (contMDiffAt_const (c := 0)).congr_of_eventuallyEq
filter_upwards [(trivializationAt F E x).open_baseSet.mem_nhds
(mem_baseSet_trivializationAt F E x)] with y hy
using congr_arg Prod.snd <| (trivializationAt F E x).zeroSection 𝕜 hy
#align bundle.smooth_zero_section Bundle.smooth_zeroSection
end Bundle
end
/-! ### Smooth vector bundles -/
variable [NontriviallyNormedField 𝕜] {EB : Type*} [NormedAddCommGroup EB] [NormedSpace 𝕜 EB]
{HB : Type*} [TopologicalSpace HB] (IB : ModelWithCorners 𝕜 EB HB) [TopologicalSpace B]
[ChartedSpace HB B] [SmoothManifoldWithCorners IB B] {EM : Type*} [NormedAddCommGroup EM]
[NormedSpace 𝕜 EM] {HM : Type*} [TopologicalSpace HM] {IM : ModelWithCorners 𝕜 EM HM}
[TopologicalSpace M] [ChartedSpace HM M] [Is : SmoothManifoldWithCorners IM M] {n : ℕ∞}
[∀ x, AddCommMonoid (E x)] [∀ x, Module 𝕜 (E x)] [NormedAddCommGroup F] [NormedSpace 𝕜 F]
section WithTopology
variable [TopologicalSpace (TotalSpace F E)] [∀ x, TopologicalSpace (E x)] (F E)
variable [FiberBundle F E] [VectorBundle 𝕜 F E]
/-- When `B` is a smooth manifold with corners with respect to a model `IB` and `E` is a
topological vector bundle over `B` with fibers isomorphic to `F`, then `SmoothVectorBundle F E IB`
registers that the bundle is smooth, in the sense of having smooth transition functions.
This is a mixin, not carrying any new data. -/
class SmoothVectorBundle : Prop where
protected smoothOn_coordChangeL :
∀ (e e' : Trivialization F (π F E)) [MemTrivializationAtlas e] [MemTrivializationAtlas e'],
SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) (fun b : B => (e.coordChangeL 𝕜 e' b : F →L[𝕜] F))
(e.baseSet ∩ e'.baseSet)
#align smooth_vector_bundle SmoothVectorBundle
#align smooth_vector_bundle.smooth_on_coord_change SmoothVectorBundle.smoothOn_coordChangeL
variable [SmoothVectorBundle F E IB]
section SmoothCoordChange
variable {F E}
variable (e e' : Trivialization F (π F E)) [MemTrivializationAtlas e] [MemTrivializationAtlas e']
theorem smoothOn_coordChangeL :
SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) (fun b : B => (e.coordChangeL 𝕜 e' b : F →L[𝕜] F))
(e.baseSet ∩ e'.baseSet) :=
SmoothVectorBundle.smoothOn_coordChangeL e e'
theorem smoothOn_symm_coordChangeL :
SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) (fun b : B => ((e.coordChangeL 𝕜 e' b).symm : F →L[𝕜] F))
(e.baseSet ∩ e'.baseSet) := by
rw [inter_comm]
refine (SmoothVectorBundle.smoothOn_coordChangeL e' e).congr fun b hb ↦ ?_
rw [e.symm_coordChangeL e' hb]
theorem contMDiffOn_coordChangeL :
ContMDiffOn IB 𝓘(𝕜, F →L[𝕜] F) n (fun b : B => (e.coordChangeL 𝕜 e' b : F →L[𝕜] F))
(e.baseSet ∩ e'.baseSet) :=
(smoothOn_coordChangeL IB e e').of_le le_top
theorem contMDiffOn_symm_coordChangeL :
ContMDiffOn IB 𝓘(𝕜, F →L[𝕜] F) n (fun b : B => ((e.coordChangeL 𝕜 e' b).symm : F →L[𝕜] F))
(e.baseSet ∩ e'.baseSet) :=
(smoothOn_symm_coordChangeL IB e e').of_le le_top
variable {e e'}
theorem contMDiffAt_coordChangeL {x : B} (h : x ∈ e.baseSet) (h' : x ∈ e'.baseSet) :
ContMDiffAt IB 𝓘(𝕜, F →L[𝕜] F) n (fun b : B => (e.coordChangeL 𝕜 e' b : F →L[𝕜] F)) x :=
(contMDiffOn_coordChangeL IB e e').contMDiffAt <|
(e.open_baseSet.inter e'.open_baseSet).mem_nhds ⟨h, h'⟩
theorem smoothAt_coordChangeL {x : B} (h : x ∈ e.baseSet) (h' : x ∈ e'.baseSet) :
SmoothAt IB 𝓘(𝕜, F →L[𝕜] F) (fun b : B => (e.coordChangeL 𝕜 e' b : F →L[𝕜] F)) x :=
contMDiffAt_coordChangeL IB h h'
variable {IB}
variable {s : Set M} {f : M → B} {g : M → F} {x : M}
protected theorem ContMDiffWithinAt.coordChangeL
(hf : ContMDiffWithinAt IM IB n f s x) (he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
ContMDiffWithinAt IM 𝓘(𝕜, F →L[𝕜] F) n (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) s x :=
(contMDiffAt_coordChangeL IB he he').comp_contMDiffWithinAt _ hf
protected nonrec theorem ContMDiffAt.coordChangeL
(hf : ContMDiffAt IM IB n f x) (he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
ContMDiffAt IM 𝓘(𝕜, F →L[𝕜] F) n (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) x :=
hf.coordChangeL he he'
protected theorem ContMDiffOn.coordChangeL
(hf : ContMDiffOn IM IB n f s) (he : MapsTo f s e.baseSet) (he' : MapsTo f s e'.baseSet) :
ContMDiffOn IM 𝓘(𝕜, F →L[𝕜] F) n (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) s :=
fun x hx ↦ (hf x hx).coordChangeL (he hx) (he' hx)
protected theorem ContMDiff.coordChangeL
(hf : ContMDiff IM IB n f) (he : ∀ x, f x ∈ e.baseSet) (he' : ∀ x, f x ∈ e'.baseSet) :
ContMDiff IM 𝓘(𝕜, F →L[𝕜] F) n (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) := fun x ↦
(hf x).coordChangeL (he x) (he' x)
protected nonrec theorem SmoothWithinAt.coordChangeL
(hf : SmoothWithinAt IM IB f s x) (he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
SmoothWithinAt IM 𝓘(𝕜, F →L[𝕜] F) (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) s x :=
hf.coordChangeL he he'
protected nonrec theorem SmoothAt.coordChangeL
(hf : SmoothAt IM IB f x) (he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
SmoothAt IM 𝓘(𝕜, F →L[𝕜] F) (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) x :=
hf.coordChangeL he he'
protected nonrec theorem SmoothOn.coordChangeL
(hf : SmoothOn IM IB f s) (he : MapsTo f s e.baseSet) (he' : MapsTo f s e'.baseSet) :
SmoothOn IM 𝓘(𝕜, F →L[𝕜] F) (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) s :=
hf.coordChangeL he he'
protected nonrec theorem Smooth.coordChangeL
(hf : Smooth IM IB f) (he : ∀ x, f x ∈ e.baseSet) (he' : ∀ x, f x ∈ e'.baseSet) :
Smooth IM 𝓘(𝕜, F →L[𝕜] F) (fun y ↦ (e.coordChangeL 𝕜 e' (f y) : F →L[𝕜] F)) :=
hf.coordChangeL he he'
protected theorem ContMDiffWithinAt.coordChange
(hf : ContMDiffWithinAt IM IB n f s x) (hg : ContMDiffWithinAt IM 𝓘(𝕜, F) n g s x)
(he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun y ↦ e.coordChange e' (f y) (g y)) s x := by
refine ((hf.coordChangeL he he').clm_apply hg).congr_of_eventuallyEq ?_ ?_
· have : e.baseSet ∩ e'.baseSet ∈ 𝓝 (f x) :=
(e.open_baseSet.inter e'.open_baseSet).mem_nhds ⟨he, he'⟩
filter_upwards [hf.continuousWithinAt this] with y hy
exact (Trivialization.coordChangeL_apply' e e' hy (g y)).symm
· exact (Trivialization.coordChangeL_apply' e e' ⟨he, he'⟩ (g x)).symm
protected nonrec theorem ContMDiffAt.coordChange
(hf : ContMDiffAt IM IB n f x) (hg : ContMDiffAt IM 𝓘(𝕜, F) n g x) (he : f x ∈ e.baseSet)
(he' : f x ∈ e'.baseSet) :
ContMDiffAt IM 𝓘(𝕜, F) n (fun y ↦ e.coordChange e' (f y) (g y)) x :=
hf.coordChange hg he he'
protected theorem ContMDiffOn.coordChange (hf : ContMDiffOn IM IB n f s)
(hg : ContMDiffOn IM 𝓘(𝕜, F) n g s) (he : MapsTo f s e.baseSet) (he' : MapsTo f s e'.baseSet) :
ContMDiffOn IM 𝓘(𝕜, F) n (fun y ↦ e.coordChange e' (f y) (g y)) s := fun x hx ↦
(hf x hx).coordChange (hg x hx) (he hx) (he' hx)
protected theorem ContMDiff.coordChange (hf : ContMDiff IM IB n f)
(hg : ContMDiff IM 𝓘(𝕜, F) n g) (he : ∀ x, f x ∈ e.baseSet) (he' : ∀ x, f x ∈ e'.baseSet) :
ContMDiff IM 𝓘(𝕜, F) n (fun y ↦ e.coordChange e' (f y) (g y)) := fun x ↦
(hf x).coordChange (hg x) (he x) (he' x)
protected nonrec theorem SmoothWithinAt.coordChange
(hf : SmoothWithinAt IM IB f s x) (hg : SmoothWithinAt IM 𝓘(𝕜, F) g s x)
(he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
SmoothWithinAt IM 𝓘(𝕜, F) (fun y ↦ e.coordChange e' (f y) (g y)) s x :=
hf.coordChange hg he he'
protected nonrec theorem SmoothAt.coordChange (hf : SmoothAt IM IB f x)
(hg : SmoothAt IM 𝓘(𝕜, F) g x) (he : f x ∈ e.baseSet) (he' : f x ∈ e'.baseSet) :
SmoothAt IM 𝓘(𝕜, F) (fun y ↦ e.coordChange e' (f y) (g y)) x :=
hf.coordChange hg he he'
protected nonrec theorem SmoothOn.coordChange (hf : SmoothOn IM IB f s)
(hg : SmoothOn IM 𝓘(𝕜, F) g s) (he : MapsTo f s e.baseSet) (he' : MapsTo f s e'.baseSet) :
SmoothOn IM 𝓘(𝕜, F) (fun y ↦ e.coordChange e' (f y) (g y)) s :=
hf.coordChange hg he he'
protected theorem Smooth.coordChange (hf : Smooth IM IB f)
(hg : Smooth IM 𝓘(𝕜, F) g) (he : ∀ x, f x ∈ e.baseSet) (he' : ∀ x, f x ∈ e'.baseSet) :
Smooth IM 𝓘(𝕜, F) (fun y ↦ e.coordChange e' (f y) (g y)) := fun x ↦
(hf x).coordChange (hg x) (he x) (he' x)
variable (IB e e')
theorem Trivialization.contMDiffOn_symm_trans :
ContMDiffOn (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) n
(e.toPartialHomeomorph.symm ≫ₕ e'.toPartialHomeomorph) (e.target ∩ e'.target) := by
have Hmaps : MapsTo Prod.fst (e.target ∩ e'.target) (e.baseSet ∩ e'.baseSet) := fun x hx ↦
⟨e.mem_target.1 hx.1, e'.mem_target.1 hx.2⟩
rw [mapsTo_inter] at Hmaps
-- TODO: drop `congr` #5473
refine (contMDiffOn_fst.prod_mk
(contMDiffOn_fst.coordChange contMDiffOn_snd Hmaps.1 Hmaps.2)).congr ?_
rintro ⟨b, x⟩ hb
refine Prod.ext ?_ rfl
have : (e.toPartialHomeomorph.symm (b, x)).1 ∈ e'.baseSet := by
simp_all only [Trivialization.mem_target, mfld_simps]
exact (e'.coe_fst' this).trans (e.proj_symm_apply hb.1)
variable {IB e e'}
theorem ContMDiffWithinAt.change_section_trivialization {f : M → TotalSpace F E}
(hp : ContMDiffWithinAt IM IB n (π F E ∘ f) s x)
(hf : ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun y ↦ (e (f y)).2) s x)
(he : f x ∈ e.source) (he' : f x ∈ e'.source) :
ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun y ↦ (e' (f y)).2) s x := by
rw [Trivialization.mem_source] at he he'
refine (hp.coordChange hf he he').congr_of_eventuallyEq ?_ ?_
· filter_upwards [hp.continuousWithinAt (e.open_baseSet.mem_nhds he)] with y hy
rw [Function.comp_apply, e.coordChange_apply_snd _ hy]
· rw [Function.comp_apply, e.coordChange_apply_snd _ he]
theorem Trivialization.contMDiffWithinAt_snd_comp_iff₂ {f : M → TotalSpace F E}
(hp : ContMDiffWithinAt IM IB n (π F E ∘ f) s x)
(he : f x ∈ e.source) (he' : f x ∈ e'.source) :
ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun y ↦ (e (f y)).2) s x ↔
ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun y ↦ (e' (f y)).2) s x :=
⟨(hp.change_section_trivialization · he he'), (hp.change_section_trivialization · he' he)⟩
end SmoothCoordChange
/-- For a smooth vector bundle `E` over `B` with fiber modelled on `F`, the change-of-co-ordinates
between two trivializations `e`, `e'` for `E`, considered as charts to `B × F`, is smooth and
fiberwise linear. -/
instance SmoothFiberwiseLinear.hasGroupoid :
HasGroupoid (TotalSpace F E) (smoothFiberwiseLinear B F IB) where
compatible := by
rintro _ _ ⟨e, he, rfl⟩ ⟨e', he', rfl⟩
haveI : MemTrivializationAtlas e := ⟨he⟩
haveI : MemTrivializationAtlas e' := ⟨he'⟩
rw [mem_smoothFiberwiseLinear_iff]
refine ⟨_, _, e.open_baseSet.inter e'.open_baseSet, smoothOn_coordChangeL IB e e',
smoothOn_symm_coordChangeL IB e e', ?_⟩
refine PartialHomeomorph.eqOnSourceSetoid.symm ⟨?_, ?_⟩
· simp only [e.symm_trans_source_eq e', FiberwiseLinear.partialHomeomorph, trans_toPartialEquiv,
symm_toPartialEquiv]
· rintro ⟨b, v⟩ hb
exact (e.apply_symm_apply_eq_coordChangeL e' hb.1 v).symm
#align smooth_fiberwise_linear.has_groupoid SmoothFiberwiseLinear.hasGroupoid
/-- A smooth vector bundle `E` is naturally a smooth manifold. -/
instance Bundle.TotalSpace.smoothManifoldWithCorners :
SmoothManifoldWithCorners (IB.prod 𝓘(𝕜, F)) (TotalSpace F E) := by
refine { StructureGroupoid.HasGroupoid.comp (smoothFiberwiseLinear B F IB) ?_ with }
intro e he
rw [mem_smoothFiberwiseLinear_iff] at he
obtain ⟨φ, U, hU, hφ, h2φ, heφ⟩ := he
rw [isLocalStructomorphOn_contDiffGroupoid_iff]
refine ⟨ContMDiffOn.congr ?_ (EqOnSource.eqOn heφ),
ContMDiffOn.congr ?_ (EqOnSource.eqOn (EqOnSource.symm' heφ))⟩
· rw [EqOnSource.source_eq heφ]
apply smoothOn_fst.prod_mk
exact (hφ.comp contMDiffOn_fst <| prod_subset_preimage_fst _ _).clm_apply contMDiffOn_snd
· rw [EqOnSource.target_eq heφ]
apply smoothOn_fst.prod_mk
exact (h2φ.comp contMDiffOn_fst <| prod_subset_preimage_fst _ _).clm_apply contMDiffOn_snd
#align bundle.total_space.smooth_manifold_with_corners Bundle.TotalSpace.smoothManifoldWithCorners
section
variable {F E}
variable {e e' : Trivialization F (π F E)} [MemTrivializationAtlas e] [MemTrivializationAtlas e']
theorem Trivialization.contMDiffWithinAt_iff {f : M → TotalSpace F E} {s : Set M} {x₀ : M}
(he : f x₀ ∈ e.source) :
ContMDiffWithinAt IM (IB.prod 𝓘(𝕜, F)) n f s x₀ ↔
ContMDiffWithinAt IM IB n (fun x => (f x).proj) s x₀ ∧
ContMDiffWithinAt IM 𝓘(𝕜, F) n (fun x ↦ (e (f x)).2) s x₀ :=
(contMDiffWithinAt_totalSpace _).trans <| and_congr_right fun h ↦
Trivialization.contMDiffWithinAt_snd_comp_iff₂ h FiberBundle.mem_trivializationAt_proj_source he
theorem Trivialization.contMDiffAt_iff {f : M → TotalSpace F E} {x₀ : M} (he : f x₀ ∈ e.source) :
ContMDiffAt IM (IB.prod 𝓘(𝕜, F)) n f x₀ ↔
ContMDiffAt IM IB n (fun x => (f x).proj) x₀ ∧
ContMDiffAt IM 𝓘(𝕜, F) n (fun x ↦ (e (f x)).2) x₀ :=
e.contMDiffWithinAt_iff _ he
theorem Trivialization.contMDiffOn_iff {f : M → TotalSpace F E} {s : Set M}
(he : MapsTo f s e.source) :
ContMDiffOn IM (IB.prod 𝓘(𝕜, F)) n f s ↔
ContMDiffOn IM IB n (fun x => (f x).proj) s ∧
ContMDiffOn IM 𝓘(𝕜, F) n (fun x ↦ (e (f x)).2) s := by
simp only [ContMDiffOn, ← forall_and]
exact forall₂_congr fun x hx ↦ e.contMDiffWithinAt_iff IB (he hx)
theorem Trivialization.contMDiff_iff {f : M → TotalSpace F E} (he : ∀ x, f x ∈ e.source) :
ContMDiff IM (IB.prod 𝓘(𝕜, F)) n f ↔
ContMDiff IM IB n (fun x => (f x).proj) ∧
ContMDiff IM 𝓘(𝕜, F) n (fun x ↦ (e (f x)).2) :=
(forall_congr' fun x ↦ e.contMDiffAt_iff IB (he x)).trans forall_and
theorem Trivialization.smoothWithinAt_iff {f : M → TotalSpace F E} {s : Set M} {x₀ : M}
(he : f x₀ ∈ e.source) :
SmoothWithinAt IM (IB.prod 𝓘(𝕜, F)) f s x₀ ↔
SmoothWithinAt IM IB (fun x => (f x).proj) s x₀ ∧
SmoothWithinAt IM 𝓘(𝕜, F) (fun x ↦ (e (f x)).2) s x₀ :=
e.contMDiffWithinAt_iff IB he
theorem Trivialization.smoothAt_iff {f : M → TotalSpace F E} {x₀ : M} (he : f x₀ ∈ e.source) :
SmoothAt IM (IB.prod 𝓘(𝕜, F)) f x₀ ↔
SmoothAt IM IB (fun x => (f x).proj) x₀ ∧ SmoothAt IM 𝓘(𝕜, F) (fun x ↦ (e (f x)).2) x₀ :=
e.contMDiffAt_iff IB he
theorem Trivialization.smoothOn_iff {f : M → TotalSpace F E} {s : Set M}
(he : MapsTo f s e.source) :
SmoothOn IM (IB.prod 𝓘(𝕜, F)) f s ↔
SmoothOn IM IB (fun x => (f x).proj) s ∧ SmoothOn IM 𝓘(𝕜, F) (fun x ↦ (e (f x)).2) s :=
e.contMDiffOn_iff IB he
theorem Trivialization.smooth_iff {f : M → TotalSpace F E} (he : ∀ x, f x ∈ e.source) :
Smooth IM (IB.prod 𝓘(𝕜, F)) f ↔
Smooth IM IB (fun x => (f x).proj) ∧ Smooth IM 𝓘(𝕜, F) (fun x ↦ (e (f x)).2) :=
e.contMDiff_iff IB he
theorem Trivialization.smoothOn (e : Trivialization F (π F E)) [MemTrivializationAtlas e] :
SmoothOn (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) e e.source := by
have : SmoothOn (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) id e.source := smoothOn_id
rw [e.smoothOn_iff IB (mapsTo_id _)] at this
exact (this.1.prod_mk this.2).congr fun x hx ↦ (e.mk_proj_snd hx).symm
theorem Trivialization.smoothOn_symm (e : Trivialization F (π F E)) [MemTrivializationAtlas e] :
SmoothOn (IB.prod 𝓘(𝕜, F)) (IB.prod 𝓘(𝕜, F)) e.toPartialHomeomorph.symm e.target := by
rw [e.smoothOn_iff IB e.toPartialHomeomorph.symm_mapsTo]
refine ⟨smoothOn_fst.congr fun x hx ↦ e.proj_symm_apply hx, smoothOn_snd.congr fun x hx ↦ ?_⟩
rw [e.apply_symm_apply hx]
end
/-! ### Core construction for smooth vector bundles -/
namespace VectorBundleCore
variable {ι : Type*} {F}
variable (Z : VectorBundleCore 𝕜 B F ι)
/-- Mixin for a `VectorBundleCore` stating smoothness (of transition functions). -/
class IsSmooth (IB : ModelWithCorners 𝕜 EB HB) : Prop where
smoothOn_coordChange :
∀ i j, SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) (Z.coordChange i j) (Z.baseSet i ∩ Z.baseSet j)
#align vector_bundle_core.is_smooth VectorBundleCore.IsSmooth
theorem smoothOn_coordChange (IB : ModelWithCorners 𝕜 EB HB) [h : Z.IsSmooth IB] (i j : ι) :
SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) (Z.coordChange i j) (Z.baseSet i ∩ Z.baseSet j) :=
h.1 i j
variable [Z.IsSmooth IB]
/-- If a `VectorBundleCore` has the `IsSmooth` mixin, then the vector bundle constructed from it
is a smooth vector bundle. -/
instance smoothVectorBundle : SmoothVectorBundle F Z.Fiber IB where
smoothOn_coordChangeL := by
rintro - - ⟨i, rfl⟩ ⟨i', rfl⟩
refine (Z.smoothOn_coordChange IB i i').congr fun b hb ↦ ?_
ext v
exact Z.localTriv_coordChange_eq i i' hb v
#align vector_bundle_core.smooth_vector_bundle VectorBundleCore.smoothVectorBundle
end VectorBundleCore
/-! ### The trivial smooth vector bundle -/
/-- A trivial vector bundle over a smooth manifold is a smooth vector bundle. -/
instance Bundle.Trivial.smoothVectorBundle : SmoothVectorBundle F (Bundle.Trivial B F) IB where
smoothOn_coordChangeL := by
intro e e' he he'
obtain rfl := Bundle.Trivial.eq_trivialization B F e
obtain rfl := Bundle.Trivial.eq_trivialization B F e'
simp_rw [Bundle.Trivial.trivialization.coordChangeL]
exact smooth_const.smoothOn
#align bundle.trivial.smooth_vector_bundle Bundle.Trivial.smoothVectorBundle
/-! ### Direct sums of smooth vector bundles -/
section Prod
variable (F₁ : Type*) [NormedAddCommGroup F₁] [NormedSpace 𝕜 F₁] (E₁ : B → Type*)
[TopologicalSpace (TotalSpace F₁ E₁)] [∀ x, AddCommMonoid (E₁ x)] [∀ x, Module 𝕜 (E₁ x)]
variable (F₂ : Type*) [NormedAddCommGroup F₂] [NormedSpace 𝕜 F₂] (E₂ : B → Type*)
[TopologicalSpace (TotalSpace F₂ E₂)] [∀ x, AddCommMonoid (E₂ x)] [∀ x, Module 𝕜 (E₂ x)]
variable [∀ x : B, TopologicalSpace (E₁ x)] [∀ x : B, TopologicalSpace (E₂ x)] [FiberBundle F₁ E₁]
[FiberBundle F₂ E₂] [VectorBundle 𝕜 F₁ E₁] [VectorBundle 𝕜 F₂ E₂] [SmoothVectorBundle F₁ E₁ IB]
[SmoothVectorBundle F₂ E₂ IB]
/-- The direct sum of two smooth vector bundles over the same base is a smooth vector bundle. -/
instance Bundle.Prod.smoothVectorBundle : SmoothVectorBundle (F₁ × F₂) (E₁ ×ᵇ E₂) IB where
smoothOn_coordChangeL := by
rintro _ _ ⟨e₁, e₂, i₁, i₂, rfl⟩ ⟨e₁', e₂', i₁', i₂', rfl⟩
rw [SmoothOn]
refine ContMDiffOn.congr ?_ (e₁.coordChangeL_prod 𝕜 e₁' e₂ e₂')
refine ContMDiffOn.clm_prodMap ?_ ?_
· refine (smoothOn_coordChangeL IB e₁ e₁').mono ?_
simp only [Trivialization.baseSet_prod, mfld_simps]
mfld_set_tac
· refine (smoothOn_coordChangeL IB e₂ e₂').mono ?_
simp only [Trivialization.baseSet_prod, mfld_simps]
mfld_set_tac
#align bundle.prod.smooth_vector_bundle Bundle.Prod.smoothVectorBundle
end Prod
end WithTopology
/-! ### Prebundle construction for smooth vector bundles -/
namespace VectorPrebundle
variable [∀ x, TopologicalSpace (E x)]
/-- Mixin for a `VectorPrebundle` stating smoothness of coordinate changes. -/
class IsSmooth (a : VectorPrebundle 𝕜 F E) : Prop where
exists_smoothCoordChange :
∀ᵉ (e ∈ a.pretrivializationAtlas) (e' ∈ a.pretrivializationAtlas),
∃ f : B → F →L[𝕜] F,
SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) f (e.baseSet ∩ e'.baseSet) ∧
∀ (b : B) (_ : b ∈ e.baseSet ∩ e'.baseSet) (v : F),
f b v = (e' ⟨b, e.symm b v⟩).2
#align vector_prebundle.is_smooth VectorPrebundle.IsSmooth
variable (a : VectorPrebundle 𝕜 F E) [ha : a.IsSmooth IB] {e e' : Pretrivialization F (π F E)}
/-- A randomly chosen coordinate change on a `SmoothVectorPrebundle`, given by
the field `exists_coordChange`. Note that `a.smoothCoordChange` need not be the same as
`a.coordChange`. -/
noncomputable def smoothCoordChange (he : e ∈ a.pretrivializationAtlas)
(he' : e' ∈ a.pretrivializationAtlas) (b : B) : F →L[𝕜] F :=
Classical.choose (ha.exists_smoothCoordChange e he e' he') b
#align vector_prebundle.smooth_coord_change VectorPrebundle.smoothCoordChange
variable {IB}
theorem smoothOn_smoothCoordChange (he : e ∈ a.pretrivializationAtlas)
(he' : e' ∈ a.pretrivializationAtlas) :
SmoothOn IB 𝓘(𝕜, F →L[𝕜] F) (a.smoothCoordChange IB he he') (e.baseSet ∩ e'.baseSet) :=
(Classical.choose_spec (ha.exists_smoothCoordChange e he e' he')).1
#align vector_prebundle.smooth_on_smooth_coord_change VectorPrebundle.smoothOn_smoothCoordChange
theorem smoothCoordChange_apply (he : e ∈ a.pretrivializationAtlas)
(he' : e' ∈ a.pretrivializationAtlas) {b : B} (hb : b ∈ e.baseSet ∩ e'.baseSet) (v : F) :
a.smoothCoordChange IB he he' b v = (e' ⟨b, e.symm b v⟩).2 :=
(Classical.choose_spec (ha.exists_smoothCoordChange e he e' he')).2 b hb v
#align vector_prebundle.smooth_coord_change_apply VectorPrebundle.smoothCoordChange_apply
| Mathlib/Geometry/Manifold/VectorBundle/Basic.lean | 690 | 696 | theorem mk_smoothCoordChange (he : e ∈ a.pretrivializationAtlas)
(he' : e' ∈ a.pretrivializationAtlas) {b : B} (hb : b ∈ e.baseSet ∩ e'.baseSet) (v : F) :
(b, a.smoothCoordChange IB he he' b v) = e' ⟨b, e.symm b v⟩ := by |
ext
· rw [e.mk_symm hb.1 v, e'.coe_fst', e.proj_symm_apply' hb.1]
rw [e.proj_symm_apply' hb.1]; exact hb.2
· exact a.smoothCoordChange_apply he he' hb v
|
/-
Copyright (c) 2021 Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Ines Wright, Joachim Breitner
-/
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.GroupTheory.Solvable
import Mathlib.GroupTheory.PGroup
import Mathlib.GroupTheory.Sylow
import Mathlib.Data.Nat.Factorization.Basic
import Mathlib.Tactic.TFAE
#align_import group_theory.nilpotent from "leanprover-community/mathlib"@"2bbc7e3884ba234309d2a43b19144105a753292e"
/-!
# Nilpotent groups
An API for nilpotent groups, that is, groups for which the upper central series
reaches `⊤`.
## Main definitions
Recall that if `H K : Subgroup G` then `⁅H, K⁆ : Subgroup G` is the subgroup of `G` generated
by the commutators `hkh⁻¹k⁻¹`. Recall also Lean's conventions that `⊤` denotes the
subgroup `G` of `G`, and `⊥` denotes the trivial subgroup `{1}`.
* `upperCentralSeries G : ℕ → Subgroup G` : the upper central series of a group `G`.
This is an increasing sequence of normal subgroups `H n` of `G` with `H 0 = ⊥` and
`H (n + 1) / H n` is the centre of `G / H n`.
* `lowerCentralSeries G : ℕ → Subgroup G` : the lower central series of a group `G`.
This is a decreasing sequence of normal subgroups `H n` of `G` with `H 0 = ⊤` and
`H (n + 1) = ⁅H n, G⁆`.
* `IsNilpotent` : A group G is nilpotent if its upper central series reaches `⊤`, or
equivalently if its lower central series reaches `⊥`.
* `nilpotency_class` : the length of the upper central series of a nilpotent group.
* `IsAscendingCentralSeries (H : ℕ → Subgroup G) : Prop` and
* `IsDescendingCentralSeries (H : ℕ → Subgroup G) : Prop` : Note that in the literature
a "central series" for a group is usually defined to be a *finite* sequence of normal subgroups
`H 0`, `H 1`, ..., starting at `⊤`, finishing at `⊥`, and with each `H n / H (n + 1)`
central in `G / H (n + 1)`. In this formalisation it is convenient to have two weaker predicates
on an infinite sequence of subgroups `H n` of `G`: we say a sequence is a *descending central
series* if it starts at `G` and `⁅H n, ⊤⁆ ⊆ H (n + 1)` for all `n`. Note that this series
may not terminate at `⊥`, and the `H i` need not be normal. Similarly a sequence is an
*ascending central series* if `H 0 = ⊥` and `⁅H (n + 1), ⊤⁆ ⊆ H n` for all `n`, again with no
requirement that the series reaches `⊤` or that the `H i` are normal.
## Main theorems
`G` is *defined* to be nilpotent if the upper central series reaches `⊤`.
* `nilpotent_iff_finite_ascending_central_series` : `G` is nilpotent iff some ascending central
series reaches `⊤`.
* `nilpotent_iff_finite_descending_central_series` : `G` is nilpotent iff some descending central
series reaches `⊥`.
* `nilpotent_iff_lower` : `G` is nilpotent iff the lower central series reaches `⊥`.
* The `nilpotency_class` can likewise be obtained from these equivalent
definitions, see `least_ascending_central_series_length_eq_nilpotencyClass`,
`least_descending_central_series_length_eq_nilpotencyClass` and
`lowerCentralSeries_length_eq_nilpotencyClass`.
* If `G` is nilpotent, then so are its subgroups, images, quotients and preimages.
Binary and finite products of nilpotent groups are nilpotent.
Infinite products are nilpotent if their nilpotent class is bounded.
Corresponding lemmas about the `nilpotency_class` are provided.
* The `nilpotency_class` of `G ⧸ center G` is given explicitly, and an induction principle
is derived from that.
* `IsNilpotent.to_isSolvable`: If `G` is nilpotent, it is solvable.
## Warning
A "central series" is usually defined to be a finite sequence of normal subgroups going
from `⊥` to `⊤` with the property that each subquotient is contained within the centre of
the associated quotient of `G`. This means that if `G` is not nilpotent, then
none of what we have called `upperCentralSeries G`, `lowerCentralSeries G` or
the sequences satisfying `IsAscendingCentralSeries` or `IsDescendingCentralSeries`
are actually central series. Note that the fact that the upper and lower central series
are not central series if `G` is not nilpotent is a standard abuse of notation.
-/
open Subgroup
section WithGroup
variable {G : Type*} [Group G] (H : Subgroup G) [Normal H]
/-- If `H` is a normal subgroup of `G`, then the set `{x : G | ∀ y : G, x*y*x⁻¹*y⁻¹ ∈ H}`
is a subgroup of `G` (because it is the preimage in `G` of the centre of the
quotient group `G/H`.)
-/
def upperCentralSeriesStep : Subgroup G where
carrier := { x : G | ∀ y : G, x * y * x⁻¹ * y⁻¹ ∈ H }
one_mem' y := by simp [Subgroup.one_mem]
mul_mem' {a b ha hb y} := by
convert Subgroup.mul_mem _ (ha (b * y * b⁻¹)) (hb y) using 1
group
inv_mem' {x hx y} := by
specialize hx y⁻¹
rw [mul_assoc, inv_inv] at hx ⊢
exact Subgroup.Normal.mem_comm inferInstance hx
#align upper_central_series_step upperCentralSeriesStep
theorem mem_upperCentralSeriesStep (x : G) :
x ∈ upperCentralSeriesStep H ↔ ∀ y, x * y * x⁻¹ * y⁻¹ ∈ H := Iff.rfl
#align mem_upper_central_series_step mem_upperCentralSeriesStep
open QuotientGroup
/-- The proof that `upperCentralSeriesStep H` is the preimage of the centre of `G/H` under
the canonical surjection. -/
theorem upperCentralSeriesStep_eq_comap_center :
upperCentralSeriesStep H = Subgroup.comap (mk' H) (center (G ⧸ H)) := by
ext
rw [mem_comap, mem_center_iff, forall_mk]
apply forall_congr'
intro y
rw [coe_mk', ← QuotientGroup.mk_mul, ← QuotientGroup.mk_mul, eq_comm, eq_iff_div_mem,
div_eq_mul_inv, mul_inv_rev, mul_assoc]
#align upper_central_series_step_eq_comap_center upperCentralSeriesStep_eq_comap_center
instance : Normal (upperCentralSeriesStep H) := by
rw [upperCentralSeriesStep_eq_comap_center]
infer_instance
variable (G)
/-- An auxiliary type-theoretic definition defining both the upper central series of
a group, and a proof that it is normal, all in one go. -/
def upperCentralSeriesAux : ℕ → Σ'H : Subgroup G, Normal H
| 0 => ⟨⊥, inferInstance⟩
| n + 1 =>
let un := upperCentralSeriesAux n
let _un_normal := un.2
⟨upperCentralSeriesStep un.1, inferInstance⟩
#align upper_central_series_aux upperCentralSeriesAux
/-- `upperCentralSeries G n` is the `n`th term in the upper central series of `G`. -/
def upperCentralSeries (n : ℕ) : Subgroup G :=
(upperCentralSeriesAux G n).1
#align upper_central_series upperCentralSeries
instance upperCentralSeries_normal (n : ℕ) : Normal (upperCentralSeries G n) :=
(upperCentralSeriesAux G n).2
@[simp]
theorem upperCentralSeries_zero : upperCentralSeries G 0 = ⊥ := rfl
#align upper_central_series_zero upperCentralSeries_zero
@[simp]
theorem upperCentralSeries_one : upperCentralSeries G 1 = center G := by
ext
simp only [upperCentralSeries, upperCentralSeriesAux, upperCentralSeriesStep,
Subgroup.mem_center_iff, mem_mk, mem_bot, Set.mem_setOf_eq]
exact forall_congr' fun y => by rw [mul_inv_eq_one, mul_inv_eq_iff_eq_mul, eq_comm]
#align upper_central_series_one upperCentralSeries_one
/-- The `n+1`st term of the upper central series `H i` has underlying set equal to the `x` such
that `⁅x,G⁆ ⊆ H n`-/
theorem mem_upperCentralSeries_succ_iff (n : ℕ) (x : G) :
x ∈ upperCentralSeries G (n + 1) ↔ ∀ y : G, x * y * x⁻¹ * y⁻¹ ∈ upperCentralSeries G n :=
Iff.rfl
#align mem_upper_central_series_succ_iff mem_upperCentralSeries_succ_iff
-- is_nilpotent is already defined in the root namespace (for elements of rings).
/-- A group `G` is nilpotent if its upper central series is eventually `G`. -/
class Group.IsNilpotent (G : Type*) [Group G] : Prop where
nilpotent' : ∃ n : ℕ, upperCentralSeries G n = ⊤
#align group.is_nilpotent Group.IsNilpotent
-- Porting note: add lemma since infer kinds are unsupported in the definition of `IsNilpotent`
lemma Group.IsNilpotent.nilpotent (G : Type*) [Group G] [IsNilpotent G] :
∃ n : ℕ, upperCentralSeries G n = ⊤ := Group.IsNilpotent.nilpotent'
open Group
variable {G}
/-- A sequence of subgroups of `G` is an ascending central series if `H 0` is trivial and
`⁅H (n + 1), G⁆ ⊆ H n` for all `n`. Note that we do not require that `H n = G` for some `n`. -/
def IsAscendingCentralSeries (H : ℕ → Subgroup G) : Prop :=
H 0 = ⊥ ∧ ∀ (x : G) (n : ℕ), x ∈ H (n + 1) → ∀ g, x * g * x⁻¹ * g⁻¹ ∈ H n
#align is_ascending_central_series IsAscendingCentralSeries
/-- A sequence of subgroups of `G` is a descending central series if `H 0` is `G` and
`⁅H n, G⁆ ⊆ H (n + 1)` for all `n`. Note that we do not require that `H n = {1}` for some `n`. -/
def IsDescendingCentralSeries (H : ℕ → Subgroup G) :=
H 0 = ⊤ ∧ ∀ (x : G) (n : ℕ), x ∈ H n → ∀ g, x * g * x⁻¹ * g⁻¹ ∈ H (n + 1)
#align is_descending_central_series IsDescendingCentralSeries
/-- Any ascending central series for a group is bounded above by the upper central series. -/
theorem ascending_central_series_le_upper (H : ℕ → Subgroup G) (hH : IsAscendingCentralSeries H) :
∀ n : ℕ, H n ≤ upperCentralSeries G n
| 0 => hH.1.symm ▸ le_refl ⊥
| n + 1 => by
intro x hx
rw [mem_upperCentralSeries_succ_iff]
exact fun y => ascending_central_series_le_upper H hH n (hH.2 x n hx y)
#align ascending_central_series_le_upper ascending_central_series_le_upper
variable (G)
/-- The upper central series of a group is an ascending central series. -/
theorem upperCentralSeries_isAscendingCentralSeries :
IsAscendingCentralSeries (upperCentralSeries G) :=
⟨rfl, fun _x _n h => h⟩
#align upper_central_series_is_ascending_central_series upperCentralSeries_isAscendingCentralSeries
theorem upperCentralSeries_mono : Monotone (upperCentralSeries G) := by
refine monotone_nat_of_le_succ ?_
intro n x hx y
rw [mul_assoc, mul_assoc, ← mul_assoc y x⁻¹ y⁻¹]
exact mul_mem hx (Normal.conj_mem (upperCentralSeries_normal G n) x⁻¹ (inv_mem hx) y)
#align upper_central_series_mono upperCentralSeries_mono
/-- A group `G` is nilpotent iff there exists an ascending central series which reaches `G` in
finitely many steps. -/
theorem nilpotent_iff_finite_ascending_central_series :
IsNilpotent G ↔ ∃ n : ℕ, ∃ H : ℕ → Subgroup G, IsAscendingCentralSeries H ∧ H n = ⊤ := by
constructor
· rintro ⟨n, nH⟩
exact ⟨_, _, upperCentralSeries_isAscendingCentralSeries G, nH⟩
· rintro ⟨n, H, hH, hn⟩
use n
rw [eq_top_iff, ← hn]
exact ascending_central_series_le_upper H hH n
#align nilpotent_iff_finite_ascending_central_series nilpotent_iff_finite_ascending_central_series
theorem is_decending_rev_series_of_is_ascending {H : ℕ → Subgroup G} {n : ℕ} (hn : H n = ⊤)
(hasc : IsAscendingCentralSeries H) : IsDescendingCentralSeries fun m : ℕ => H (n - m) := by
cases' hasc with h0 hH
refine ⟨hn, fun x m hx g => ?_⟩
dsimp at hx
by_cases hm : n ≤ m
· rw [tsub_eq_zero_of_le hm, h0, Subgroup.mem_bot] at hx
subst hx
rw [show (1 : G) * g * (1⁻¹ : G) * g⁻¹ = 1 by group]
exact Subgroup.one_mem _
· push_neg at hm
apply hH
convert hx using 1
rw [tsub_add_eq_add_tsub (Nat.succ_le_of_lt hm), Nat.succ_eq_add_one, Nat.add_sub_add_right]
#align is_decending_rev_series_of_is_ascending is_decending_rev_series_of_is_ascending
theorem is_ascending_rev_series_of_is_descending {H : ℕ → Subgroup G} {n : ℕ} (hn : H n = ⊥)
(hdesc : IsDescendingCentralSeries H) : IsAscendingCentralSeries fun m : ℕ => H (n - m) := by
cases' hdesc with h0 hH
refine ⟨hn, fun x m hx g => ?_⟩
dsimp only at hx ⊢
by_cases hm : n ≤ m
· have hnm : n - m = 0 := tsub_eq_zero_iff_le.mpr hm
rw [hnm, h0]
exact mem_top _
· push_neg at hm
convert hH x _ hx g using 1
rw [tsub_add_eq_add_tsub (Nat.succ_le_of_lt hm), Nat.succ_eq_add_one, Nat.add_sub_add_right]
#align is_ascending_rev_series_of_is_descending is_ascending_rev_series_of_is_descending
/-- A group `G` is nilpotent iff there exists a descending central series which reaches the
trivial group in a finite time. -/
theorem nilpotent_iff_finite_descending_central_series :
IsNilpotent G ↔ ∃ n : ℕ, ∃ H : ℕ → Subgroup G, IsDescendingCentralSeries H ∧ H n = ⊥ := by
rw [nilpotent_iff_finite_ascending_central_series]
constructor
· rintro ⟨n, H, hH, hn⟩
refine ⟨n, fun m => H (n - m), is_decending_rev_series_of_is_ascending G hn hH, ?_⟩
dsimp only
rw [tsub_self]
exact hH.1
· rintro ⟨n, H, hH, hn⟩
refine ⟨n, fun m => H (n - m), is_ascending_rev_series_of_is_descending G hn hH, ?_⟩
dsimp only
rw [tsub_self]
exact hH.1
#align nilpotent_iff_finite_descending_central_series nilpotent_iff_finite_descending_central_series
/-- The lower central series of a group `G` is a sequence `H n` of subgroups of `G`, defined
by `H 0` is all of `G` and for `n≥1`, `H (n + 1) = ⁅H n, G⁆` -/
def lowerCentralSeries (G : Type*) [Group G] : ℕ → Subgroup G
| 0 => ⊤
| n + 1 => ⁅lowerCentralSeries G n, ⊤⁆
#align lower_central_series lowerCentralSeries
variable {G}
@[simp]
theorem lowerCentralSeries_zero : lowerCentralSeries G 0 = ⊤ := rfl
#align lower_central_series_zero lowerCentralSeries_zero
@[simp]
theorem lowerCentralSeries_one : lowerCentralSeries G 1 = commutator G := rfl
#align lower_central_series_one lowerCentralSeries_one
theorem mem_lowerCentralSeries_succ_iff (n : ℕ) (q : G) :
q ∈ lowerCentralSeries G (n + 1) ↔
q ∈ closure { x | ∃ p ∈ lowerCentralSeries G n,
∃ q ∈ (⊤ : Subgroup G), p * q * p⁻¹ * q⁻¹ = x } := Iff.rfl
#align mem_lower_central_series_succ_iff mem_lowerCentralSeries_succ_iff
theorem lowerCentralSeries_succ (n : ℕ) :
lowerCentralSeries G (n + 1) =
closure { x | ∃ p ∈ lowerCentralSeries G n, ∃ q ∈ (⊤ : Subgroup G), p * q * p⁻¹ * q⁻¹ = x } :=
rfl
#align lower_central_series_succ lowerCentralSeries_succ
instance lowerCentralSeries_normal (n : ℕ) : Normal (lowerCentralSeries G n) := by
induction' n with d hd
· exact (⊤ : Subgroup G).normal_of_characteristic
· exact @Subgroup.commutator_normal _ _ (lowerCentralSeries G d) ⊤ hd _
theorem lowerCentralSeries_antitone : Antitone (lowerCentralSeries G) := by
refine antitone_nat_of_succ_le fun n x hx => ?_
simp only [mem_lowerCentralSeries_succ_iff, exists_prop, mem_top, exists_true_left,
true_and_iff] at hx
refine
closure_induction hx ?_ (Subgroup.one_mem _) (@Subgroup.mul_mem _ _ _) (@Subgroup.inv_mem _ _ _)
rintro y ⟨z, hz, a, ha⟩
rw [← ha, mul_assoc, mul_assoc, ← mul_assoc a z⁻¹ a⁻¹]
exact mul_mem hz (Normal.conj_mem (lowerCentralSeries_normal n) z⁻¹ (inv_mem hz) a)
#align lower_central_series_antitone lowerCentralSeries_antitone
/-- The lower central series of a group is a descending central series. -/
theorem lowerCentralSeries_isDescendingCentralSeries :
IsDescendingCentralSeries (lowerCentralSeries G) := by
constructor
· rfl
intro x n hxn g
exact commutator_mem_commutator hxn (mem_top g)
#align lower_central_series_is_descending_central_series lowerCentralSeries_isDescendingCentralSeries
/-- Any descending central series for a group is bounded below by the lower central series. -/
theorem descending_central_series_ge_lower (H : ℕ → Subgroup G) (hH : IsDescendingCentralSeries H) :
∀ n : ℕ, lowerCentralSeries G n ≤ H n
| 0 => hH.1.symm ▸ le_refl ⊤
| n + 1 => commutator_le.mpr fun x hx q _ =>
hH.2 x n (descending_central_series_ge_lower H hH n hx) q
#align descending_central_series_ge_lower descending_central_series_ge_lower
/-- A group is nilpotent if and only if its lower central series eventually reaches
the trivial subgroup. -/
theorem nilpotent_iff_lowerCentralSeries : IsNilpotent G ↔ ∃ n, lowerCentralSeries G n = ⊥ := by
rw [nilpotent_iff_finite_descending_central_series]
constructor
· rintro ⟨n, H, ⟨h0, hs⟩, hn⟩
use n
rw [eq_bot_iff, ← hn]
exact descending_central_series_ge_lower H ⟨h0, hs⟩ n
· rintro ⟨n, hn⟩
exact ⟨n, lowerCentralSeries G, lowerCentralSeries_isDescendingCentralSeries, hn⟩
#align nilpotent_iff_lower_central_series nilpotent_iff_lowerCentralSeries
section Classical
open scoped Classical
variable [hG : IsNilpotent G]
variable (G)
/-- The nilpotency class of a nilpotent group is the smallest natural `n` such that
the `n`'th term of the upper central series is `G`. -/
noncomputable def Group.nilpotencyClass : ℕ := Nat.find (IsNilpotent.nilpotent G)
#align group.nilpotency_class Group.nilpotencyClass
variable {G}
@[simp]
theorem upperCentralSeries_nilpotencyClass : upperCentralSeries G (Group.nilpotencyClass G) = ⊤ :=
Nat.find_spec (IsNilpotent.nilpotent G)
#align upper_central_series_nilpotency_class upperCentralSeries_nilpotencyClass
theorem upperCentralSeries_eq_top_iff_nilpotencyClass_le {n : ℕ} :
upperCentralSeries G n = ⊤ ↔ Group.nilpotencyClass G ≤ n := by
constructor
· intro h
exact Nat.find_le h
· intro h
rw [eq_top_iff, ← upperCentralSeries_nilpotencyClass]
exact upperCentralSeries_mono _ h
#align upper_central_series_eq_top_iff_nilpotency_class_le upperCentralSeries_eq_top_iff_nilpotencyClass_le
/-- The nilpotency class of a nilpotent `G` is equal to the smallest `n` for which an ascending
central series reaches `G` in its `n`'th term. -/
theorem least_ascending_central_series_length_eq_nilpotencyClass :
Nat.find ((nilpotent_iff_finite_ascending_central_series G).mp hG) =
Group.nilpotencyClass G := by
refine le_antisymm (Nat.find_mono ?_) (Nat.find_mono ?_)
· intro n hn
exact ⟨upperCentralSeries G, upperCentralSeries_isAscendingCentralSeries G, hn⟩
· rintro n ⟨H, ⟨hH, hn⟩⟩
rw [← top_le_iff, ← hn]
exact ascending_central_series_le_upper H hH n
#align least_ascending_central_series_length_eq_nilpotency_class least_ascending_central_series_length_eq_nilpotencyClass
/-- The nilpotency class of a nilpotent `G` is equal to the smallest `n` for which the descending
central series reaches `⊥` in its `n`'th term. -/
theorem least_descending_central_series_length_eq_nilpotencyClass :
Nat.find ((nilpotent_iff_finite_descending_central_series G).mp hG) =
Group.nilpotencyClass G := by
rw [← least_ascending_central_series_length_eq_nilpotencyClass]
refine le_antisymm (Nat.find_mono ?_) (Nat.find_mono ?_)
· rintro n ⟨H, ⟨hH, hn⟩⟩
refine ⟨fun m => H (n - m), is_decending_rev_series_of_is_ascending G hn hH, ?_⟩
dsimp only
rw [tsub_self]
exact hH.1
· rintro n ⟨H, ⟨hH, hn⟩⟩
refine ⟨fun m => H (n - m), is_ascending_rev_series_of_is_descending G hn hH, ?_⟩
dsimp only
rw [tsub_self]
exact hH.1
#align least_descending_central_series_length_eq_nilpotency_class least_descending_central_series_length_eq_nilpotencyClass
/-- The nilpotency class of a nilpotent `G` is equal to the length of the lower central series. -/
theorem lowerCentralSeries_length_eq_nilpotencyClass :
Nat.find (nilpotent_iff_lowerCentralSeries.mp hG) = Group.nilpotencyClass (G := G) := by
rw [← least_descending_central_series_length_eq_nilpotencyClass]
refine le_antisymm (Nat.find_mono ?_) (Nat.find_mono ?_)
· rintro n ⟨H, ⟨hH, hn⟩⟩
rw [← le_bot_iff, ← hn]
exact descending_central_series_ge_lower H hH n
· rintro n h
exact ⟨lowerCentralSeries G, ⟨lowerCentralSeries_isDescendingCentralSeries, h⟩⟩
#align lower_central_series_length_eq_nilpotency_class lowerCentralSeries_length_eq_nilpotencyClass
@[simp]
theorem lowerCentralSeries_nilpotencyClass :
lowerCentralSeries G (Group.nilpotencyClass G) = ⊥ := by
rw [← lowerCentralSeries_length_eq_nilpotencyClass]
exact Nat.find_spec (nilpotent_iff_lowerCentralSeries.mp hG)
#align lower_central_series_nilpotency_class lowerCentralSeries_nilpotencyClass
theorem lowerCentralSeries_eq_bot_iff_nilpotencyClass_le {n : ℕ} :
lowerCentralSeries G n = ⊥ ↔ Group.nilpotencyClass G ≤ n := by
constructor
· intro h
rw [← lowerCentralSeries_length_eq_nilpotencyClass]
exact Nat.find_le h
· intro h
rw [eq_bot_iff, ← lowerCentralSeries_nilpotencyClass]
exact lowerCentralSeries_antitone h
#align lower_central_series_eq_bot_iff_nilpotency_class_le lowerCentralSeries_eq_bot_iff_nilpotencyClass_le
end Classical
theorem lowerCentralSeries_map_subtype_le (H : Subgroup G) (n : ℕ) :
(lowerCentralSeries H n).map H.subtype ≤ lowerCentralSeries G n := by
induction' n with d hd
· simp
· rw [lowerCentralSeries_succ, lowerCentralSeries_succ, MonoidHom.map_closure]
apply Subgroup.closure_mono
rintro x1 ⟨x2, ⟨x3, hx3, x4, _hx4, rfl⟩, rfl⟩
exact ⟨x3, hd (mem_map.mpr ⟨x3, hx3, rfl⟩), x4, by simp⟩
#align lower_central_series_map_subtype_le lowerCentralSeries_map_subtype_le
/-- A subgroup of a nilpotent group is nilpotent -/
instance Subgroup.isNilpotent (H : Subgroup G) [hG : IsNilpotent G] : IsNilpotent H := by
rw [nilpotent_iff_lowerCentralSeries] at *
rcases hG with ⟨n, hG⟩
use n
have := lowerCentralSeries_map_subtype_le H n
simp only [hG, SetLike.le_def, mem_map, forall_apply_eq_imp_iff₂, exists_imp] at this
exact eq_bot_iff.mpr fun x hx => Subtype.ext (this x ⟨hx, rfl⟩)
#align subgroup.is_nilpotent Subgroup.isNilpotent
/-- The nilpotency class of a subgroup is less or equal to the nilpotency class of the group -/
theorem Subgroup.nilpotencyClass_le (H : Subgroup G) [hG : IsNilpotent G] :
Group.nilpotencyClass H ≤ Group.nilpotencyClass G := by
repeat rw [← lowerCentralSeries_length_eq_nilpotencyClass]
--- Porting note: Lean needs to be told that predicates are decidable
refine @Nat.find_mono _ _ (Classical.decPred _) (Classical.decPred _) ?_ _ _
intro n hG
have := lowerCentralSeries_map_subtype_le H n
simp only [hG, SetLike.le_def, mem_map, forall_apply_eq_imp_iff₂, exists_imp] at this
exact eq_bot_iff.mpr fun x hx => Subtype.ext (this x ⟨hx, rfl⟩)
#align subgroup.nilpotency_class_le Subgroup.nilpotencyClass_le
instance (priority := 100) Group.isNilpotent_of_subsingleton [Subsingleton G] : IsNilpotent G :=
nilpotent_iff_lowerCentralSeries.2 ⟨0, Subsingleton.elim ⊤ ⊥⟩
#align is_nilpotent_of_subsingleton Group.isNilpotent_of_subsingleton
theorem upperCentralSeries.map {H : Type*} [Group H] {f : G →* H} (h : Function.Surjective f)
(n : ℕ) : Subgroup.map f (upperCentralSeries G n) ≤ upperCentralSeries H n := by
induction' n with d hd
· simp
· rintro _ ⟨x, hx : x ∈ upperCentralSeries G d.succ, rfl⟩ y'
rcases h y' with ⟨y, rfl⟩
simpa using hd (mem_map_of_mem f (hx y))
#align upper_central_series.map upperCentralSeries.map
theorem lowerCentralSeries.map {H : Type*} [Group H] (f : G →* H) (n : ℕ) :
Subgroup.map f (lowerCentralSeries G n) ≤ lowerCentralSeries H n := by
induction' n with d hd
· simp [Nat.zero_eq]
· rintro a ⟨x, hx : x ∈ lowerCentralSeries G d.succ, rfl⟩
refine closure_induction hx ?_ (by simp [f.map_one, Subgroup.one_mem _])
(fun y z hy hz => by simp [MonoidHom.map_mul, Subgroup.mul_mem _ hy hz]) (fun y hy => by
rw [f.map_inv]; exact Subgroup.inv_mem _ hy)
rintro a ⟨y, hy, z, ⟨-, rfl⟩⟩
apply mem_closure.mpr
exact fun K hK => hK ⟨f y, hd (mem_map_of_mem f hy), by simp [commutatorElement_def]⟩
#align lower_central_series.map lowerCentralSeries.map
theorem lowerCentralSeries_succ_eq_bot {n : ℕ} (h : lowerCentralSeries G n ≤ center G) :
lowerCentralSeries G (n + 1) = ⊥ := by
rw [lowerCentralSeries_succ, closure_eq_bot_iff, Set.subset_singleton_iff]
rintro x ⟨y, hy1, z, ⟨⟩, rfl⟩
rw [mul_assoc, ← mul_inv_rev, mul_inv_eq_one, eq_comm]
exact mem_center_iff.mp (h hy1) z
#align lower_central_series_succ_eq_bot lowerCentralSeries_succ_eq_bot
/-- The preimage of a nilpotent group is nilpotent if the kernel of the homomorphism is contained
in the center -/
theorem isNilpotent_of_ker_le_center {H : Type*} [Group H] (f : G →* H) (hf1 : f.ker ≤ center G)
(hH : IsNilpotent H) : IsNilpotent G := by
rw [nilpotent_iff_lowerCentralSeries] at *
rcases hH with ⟨n, hn⟩
use n + 1
refine lowerCentralSeries_succ_eq_bot (le_trans ((Subgroup.map_eq_bot_iff _).mp ?_) hf1)
exact eq_bot_iff.mpr (hn ▸ lowerCentralSeries.map f n)
#align is_nilpotent_of_ker_le_center isNilpotent_of_ker_le_center
theorem nilpotencyClass_le_of_ker_le_center {H : Type*} [Group H] (f : G →* H)
(hf1 : f.ker ≤ center G) (hH : IsNilpotent H) :
Group.nilpotencyClass (hG := isNilpotent_of_ker_le_center f hf1 hH) ≤
Group.nilpotencyClass H + 1 := by
haveI : IsNilpotent G := isNilpotent_of_ker_le_center f hf1 hH
rw [← lowerCentralSeries_length_eq_nilpotencyClass]
-- Porting note: Lean needs to be told that predicates are decidable
refine @Nat.find_min' _ (Classical.decPred _) _ _ ?_
refine lowerCentralSeries_succ_eq_bot (le_trans ((Subgroup.map_eq_bot_iff _).mp ?_) hf1)
rw [eq_bot_iff]
apply le_trans (lowerCentralSeries.map f _)
simp only [lowerCentralSeries_nilpotencyClass, le_bot_iff]
#align nilpotency_class_le_of_ker_le_center nilpotencyClass_le_of_ker_le_center
/-- The range of a surjective homomorphism from a nilpotent group is nilpotent -/
theorem nilpotent_of_surjective {G' : Type*} [Group G'] [h : IsNilpotent G] (f : G →* G')
(hf : Function.Surjective f) : IsNilpotent G' := by
rcases h with ⟨n, hn⟩
use n
apply eq_top_iff.mpr
calc
⊤ = f.range := symm (f.range_top_of_surjective hf)
_ = Subgroup.map f ⊤ := MonoidHom.range_eq_map _
_ = Subgroup.map f (upperCentralSeries G n) := by rw [hn]
_ ≤ upperCentralSeries G' n := upperCentralSeries.map hf n
#align nilpotent_of_surjective nilpotent_of_surjective
/-- The nilpotency class of the range of a surjective homomorphism from a
nilpotent group is less or equal the nilpotency class of the domain -/
theorem nilpotencyClass_le_of_surjective {G' : Type*} [Group G'] (f : G →* G')
(hf : Function.Surjective f) [h : IsNilpotent G] :
Group.nilpotencyClass (hG := nilpotent_of_surjective _ hf) ≤ Group.nilpotencyClass G := by
-- Porting note: Lean needs to be told that predicates are decidable
refine @Nat.find_mono _ _ (Classical.decPred _) (Classical.decPred _) ?_ _ _
intro n hn
rw [eq_top_iff]
calc
⊤ = f.range := symm (f.range_top_of_surjective hf)
_ = Subgroup.map f ⊤ := MonoidHom.range_eq_map _
_ = Subgroup.map f (upperCentralSeries G n) := by rw [hn]
_ ≤ upperCentralSeries G' n := upperCentralSeries.map hf n
#align nilpotency_class_le_of_surjective nilpotencyClass_le_of_surjective
/-- Nilpotency respects isomorphisms -/
theorem nilpotent_of_mulEquiv {G' : Type*} [Group G'] [_h : IsNilpotent G] (f : G ≃* G') :
IsNilpotent G' :=
nilpotent_of_surjective f.toMonoidHom (MulEquiv.surjective f)
#align nilpotent_of_mul_equiv nilpotent_of_mulEquiv
/-- A quotient of a nilpotent group is nilpotent -/
instance nilpotent_quotient_of_nilpotent (H : Subgroup G) [H.Normal] [_h : IsNilpotent G] :
IsNilpotent (G ⧸ H) :=
nilpotent_of_surjective (QuotientGroup.mk' H) QuotientGroup.mk_surjective
#align nilpotent_quotient_of_nilpotent nilpotent_quotient_of_nilpotent
/-- The nilpotency class of a quotient of `G` is less or equal the nilpotency class of `G` -/
theorem nilpotencyClass_quotient_le (H : Subgroup G) [H.Normal] [_h : IsNilpotent G] :
Group.nilpotencyClass (G ⧸ H) ≤ Group.nilpotencyClass G :=
nilpotencyClass_le_of_surjective (QuotientGroup.mk' H) QuotientGroup.mk_surjective
#align nilpotency_class_quotient_le nilpotencyClass_quotient_le
-- This technical lemma helps with rewriting the subgroup, which occurs in indices
private theorem comap_center_subst {H₁ H₂ : Subgroup G} [Normal H₁] [Normal H₂] (h : H₁ = H₂) :
comap (mk' H₁) (center (G ⧸ H₁)) = comap (mk' H₂) (center (G ⧸ H₂)) := by subst h; rfl
theorem comap_upperCentralSeries_quotient_center (n : ℕ) :
comap (mk' (center G)) (upperCentralSeries (G ⧸ center G) n) = upperCentralSeries G n.succ := by
induction' n with n ih
· simp only [Nat.zero_eq, upperCentralSeries_zero, MonoidHom.comap_bot, ker_mk',
(upperCentralSeries_one G).symm]
· let Hn := upperCentralSeries (G ⧸ center G) n
calc
comap (mk' (center G)) (upperCentralSeriesStep Hn) =
comap (mk' (center G)) (comap (mk' Hn) (center ((G ⧸ center G) ⧸ Hn))) := by
rw [upperCentralSeriesStep_eq_comap_center]
_ = comap (mk' (comap (mk' (center G)) Hn)) (center (G ⧸ comap (mk' (center G)) Hn)) :=
QuotientGroup.comap_comap_center
_ = comap (mk' (upperCentralSeries G n.succ)) (center (G ⧸ upperCentralSeries G n.succ)) :=
(comap_center_subst ih)
_ = upperCentralSeriesStep (upperCentralSeries G n.succ) :=
symm (upperCentralSeriesStep_eq_comap_center _)
#align comap_upper_central_series_quotient_center comap_upperCentralSeries_quotient_center
theorem nilpotencyClass_zero_iff_subsingleton [IsNilpotent G] :
Group.nilpotencyClass G = 0 ↔ Subsingleton G := by
-- Porting note: Lean needs to be told that predicates are decidable
rw [Group.nilpotencyClass, @Nat.find_eq_zero _ (Classical.decPred _), upperCentralSeries_zero,
subsingleton_iff_bot_eq_top, Subgroup.subsingleton_iff]
#align nilpotency_class_zero_iff_subsingleton nilpotencyClass_zero_iff_subsingleton
/-- Quotienting the `center G` reduces the nilpotency class by 1 -/
theorem nilpotencyClass_quotient_center [hH : IsNilpotent G] :
Group.nilpotencyClass (G ⧸ center G) = Group.nilpotencyClass G - 1 := by
generalize hn : Group.nilpotencyClass G = n
rcases n with (rfl | n)
· simp [nilpotencyClass_zero_iff_subsingleton] at *
exact Quotient.instSubsingletonQuotient (leftRel (center G))
· suffices Group.nilpotencyClass (G ⧸ center G) = n by simpa
apply le_antisymm
· apply upperCentralSeries_eq_top_iff_nilpotencyClass_le.mp
apply comap_injective (f := (mk' (center G))) (surjective_quot_mk _)
rw [comap_upperCentralSeries_quotient_center, comap_top, Nat.succ_eq_add_one, ← hn]
exact upperCentralSeries_nilpotencyClass
· apply le_of_add_le_add_right
calc
n + 1 = Group.nilpotencyClass G := hn.symm
_ ≤ Group.nilpotencyClass (G ⧸ center G) + 1 :=
nilpotencyClass_le_of_ker_le_center _ (le_of_eq (ker_mk' _)) _
#align nilpotency_class_quotient_center nilpotencyClass_quotient_center
/-- The nilpotency class of a non-trivial group is one more than its quotient by the center -/
theorem nilpotencyClass_eq_quotient_center_plus_one [hH : IsNilpotent G] [Nontrivial G] :
Group.nilpotencyClass G = Group.nilpotencyClass (G ⧸ center G) + 1 := by
rw [nilpotencyClass_quotient_center]
rcases h : Group.nilpotencyClass G with ⟨⟩
· exfalso
rw [nilpotencyClass_zero_iff_subsingleton] at h
apply false_of_nontrivial_of_subsingleton G
· simp
#align nilpotency_class_eq_quotient_center_plus_one nilpotencyClass_eq_quotient_center_plus_one
/-- If the quotient by `center G` is nilpotent, then so is G. -/
theorem of_quotient_center_nilpotent (h : IsNilpotent (G ⧸ center G)) : IsNilpotent G := by
obtain ⟨n, hn⟩ := h.nilpotent
use n.succ
simp [← comap_upperCentralSeries_quotient_center, hn]
#align of_quotient_center_nilpotent of_quotient_center_nilpotent
/-- A custom induction principle for nilpotent groups. The base case is a trivial group
(`subsingleton G`), and in the induction step, one can assume the hypothesis for
the group quotiented by its center. -/
@[elab_as_elim]
theorem nilpotent_center_quotient_ind {P : ∀ (G) [Group G] [IsNilpotent G], Prop}
(G : Type*) [Group G] [IsNilpotent G]
(hbase : ∀ (G) [Group G] [Subsingleton G], P G)
(hstep : ∀ (G) [Group G] [IsNilpotent G], P (G ⧸ center G) → P G) : P G := by
obtain ⟨n, h⟩ : ∃ n, Group.nilpotencyClass G = n := ⟨_, rfl⟩
induction' n with n ih generalizing G
· haveI := nilpotencyClass_zero_iff_subsingleton.mp h
exact hbase _
· have hn : Group.nilpotencyClass (G ⧸ center G) = n := by
simp [nilpotencyClass_quotient_center, h]
exact hstep _ (ih _ hn)
#align nilpotent_center_quotient_ind nilpotent_center_quotient_ind
theorem derived_le_lower_central (n : ℕ) : derivedSeries G n ≤ lowerCentralSeries G n := by
induction' n with i ih
· simp
· apply commutator_mono ih
simp
#align derived_le_lower_central derived_le_lower_central
/-- Abelian groups are nilpotent -/
instance (priority := 100) CommGroup.isNilpotent {G : Type*} [CommGroup G] : IsNilpotent G := by
use 1
rw [upperCentralSeries_one]
apply CommGroup.center_eq_top
#align comm_group.is_nilpotent CommGroup.isNilpotent
/-- Abelian groups have nilpotency class at most one -/
theorem CommGroup.nilpotencyClass_le_one {G : Type*} [CommGroup G] :
Group.nilpotencyClass G ≤ 1 := by
rw [← upperCentralSeries_eq_top_iff_nilpotencyClass_le, upperCentralSeries_one]
apply CommGroup.center_eq_top
#align comm_group.nilpotency_class_le_one CommGroup.nilpotencyClass_le_one
/-- Groups with nilpotency class at most one are abelian -/
def commGroupOfNilpotencyClass [IsNilpotent G] (h : Group.nilpotencyClass G ≤ 1) : CommGroup G :=
Group.commGroupOfCenterEqTop <| by
rw [← upperCentralSeries_one]
exact upperCentralSeries_eq_top_iff_nilpotencyClass_le.mpr h
#align comm_group_of_nilpotency_class commGroupOfNilpotencyClass
section Prod
variable {G₁ G₂ : Type*} [Group G₁] [Group G₂]
theorem lowerCentralSeries_prod (n : ℕ) :
lowerCentralSeries (G₁ × G₂) n = (lowerCentralSeries G₁ n).prod (lowerCentralSeries G₂ n) := by
induction' n with n ih
· simp
· calc
lowerCentralSeries (G₁ × G₂) n.succ = ⁅lowerCentralSeries (G₁ × G₂) n, ⊤⁆ := rfl
_ = ⁅(lowerCentralSeries G₁ n).prod (lowerCentralSeries G₂ n), ⊤⁆ := by rw [ih]
_ = ⁅(lowerCentralSeries G₁ n).prod (lowerCentralSeries G₂ n), (⊤ : Subgroup G₁).prod ⊤⁆ := by
simp
_ = ⁅lowerCentralSeries G₁ n, (⊤ : Subgroup G₁)⁆.prod ⁅lowerCentralSeries G₂ n, ⊤⁆ :=
(commutator_prod_prod _ _ _ _)
_ = (lowerCentralSeries G₁ n.succ).prod (lowerCentralSeries G₂ n.succ) := rfl
#align lower_central_series_prod lowerCentralSeries_prod
/-- Products of nilpotent groups are nilpotent -/
instance isNilpotent_prod [IsNilpotent G₁] [IsNilpotent G₂] : IsNilpotent (G₁ × G₂) := by
rw [nilpotent_iff_lowerCentralSeries]
refine ⟨max (Group.nilpotencyClass G₁) (Group.nilpotencyClass G₂), ?_⟩
rw [lowerCentralSeries_prod,
lowerCentralSeries_eq_bot_iff_nilpotencyClass_le.mpr (le_max_left _ _),
lowerCentralSeries_eq_bot_iff_nilpotencyClass_le.mpr (le_max_right _ _), bot_prod_bot]
#align is_nilpotent_prod isNilpotent_prod
/-- The nilpotency class of a product is the max of the nilpotency classes of the factors -/
theorem nilpotencyClass_prod [IsNilpotent G₁] [IsNilpotent G₂] :
Group.nilpotencyClass (G₁ × G₂) =
max (Group.nilpotencyClass G₁) (Group.nilpotencyClass G₂) := by
refine eq_of_forall_ge_iff fun k => ?_
simp only [max_le_iff, ← lowerCentralSeries_eq_bot_iff_nilpotencyClass_le,
lowerCentralSeries_prod, prod_eq_bot_iff]
#align nilpotency_class_prod nilpotencyClass_prod
end Prod
section BoundedPi
-- First the case of infinite products with bounded nilpotency class
variable {η : Type*} {Gs : η → Type*} [∀ i, Group (Gs i)]
theorem lowerCentralSeries_pi_le (n : ℕ) :
lowerCentralSeries (∀ i, Gs i) n ≤ Subgroup.pi Set.univ
fun i => lowerCentralSeries (Gs i) n := by
let pi := fun f : ∀ i, Subgroup (Gs i) => Subgroup.pi Set.univ f
induction' n with n ih
· simp [pi_top]
· calc
lowerCentralSeries (∀ i, Gs i) n.succ = ⁅lowerCentralSeries (∀ i, Gs i) n, ⊤⁆ := rfl
_ ≤ ⁅pi fun i => lowerCentralSeries (Gs i) n, ⊤⁆ := commutator_mono ih (le_refl _)
_ = ⁅pi fun i => lowerCentralSeries (Gs i) n, pi fun i => ⊤⁆ := by simp [pi, pi_top]
_ ≤ pi fun i => ⁅lowerCentralSeries (Gs i) n, ⊤⁆ := commutator_pi_pi_le _ _
_ = pi fun i => lowerCentralSeries (Gs i) n.succ := rfl
#align lower_central_series_pi_le lowerCentralSeries_pi_le
/-- products of nilpotent groups are nilpotent if their nilpotency class is bounded -/
theorem isNilpotent_pi_of_bounded_class [∀ i, IsNilpotent (Gs i)] (n : ℕ)
(h : ∀ i, Group.nilpotencyClass (Gs i) ≤ n) : IsNilpotent (∀ i, Gs i) := by
rw [nilpotent_iff_lowerCentralSeries]
refine ⟨n, ?_⟩
rw [eq_bot_iff]
apply le_trans (lowerCentralSeries_pi_le _)
rw [← eq_bot_iff, pi_eq_bot_iff]
intro i
apply lowerCentralSeries_eq_bot_iff_nilpotencyClass_le.mpr (h i)
#align is_nilpotent_pi_of_bounded_class isNilpotent_pi_of_bounded_class
end BoundedPi
section FinitePi
-- Now for finite products
variable {η : Type*} {Gs : η → Type*} [∀ i, Group (Gs i)]
| Mathlib/GroupTheory/Nilpotent.lean | 778 | 789 | theorem lowerCentralSeries_pi_of_finite [Finite η] (n : ℕ) :
lowerCentralSeries (∀ i, Gs i) n = Subgroup.pi Set.univ
fun i => lowerCentralSeries (Gs i) n := by |
let pi := fun f : ∀ i, Subgroup (Gs i) => Subgroup.pi Set.univ f
induction' n with n ih
· simp [pi_top]
· calc
lowerCentralSeries (∀ i, Gs i) n.succ = ⁅lowerCentralSeries (∀ i, Gs i) n, ⊤⁆ := rfl
_ = ⁅pi fun i => lowerCentralSeries (Gs i) n, ⊤⁆ := by rw [ih]
_ = ⁅pi fun i => lowerCentralSeries (Gs i) n, pi fun i => ⊤⁆ := by simp [pi, pi_top]
_ = pi fun i => ⁅lowerCentralSeries (Gs i) n, ⊤⁆ := commutator_pi_pi_of_finite _ _
_ = pi fun i => lowerCentralSeries (Gs i) n.succ := rfl
|
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Kenny Lau
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.RingTheory.MvPowerSeries.Basic
#align_import ring_theory.power_series.basic from "leanprover-community/mathlib"@"2d5739b61641ee4e7e53eca5688a08f66f2e6a60"
/-!
# Formal power series (in one variable)
This file defines (univariate) formal power series
and develops the basic properties of these objects.
A formal power series is to a polynomial like an infinite sum is to a finite sum.
Formal power series in one variable are defined from multivariate
power series as `PowerSeries R := MvPowerSeries Unit R`.
The file sets up the (semi)ring structure on univariate power series.
We provide the natural inclusion from polynomials to formal power series.
Additional results can be found in:
* `Mathlib.RingTheory.PowerSeries.Trunc`, truncation of power series;
* `Mathlib.RingTheory.PowerSeries.Inverse`, about inverses of power series,
and the fact that power series over a local ring form a local ring;
* `Mathlib.RingTheory.PowerSeries.Order`, the order of a power series at 0,
and application to the fact that power series over an integral domain
form an integral domain.
## Implementation notes
Because of its definition,
`PowerSeries R := MvPowerSeries Unit R`.
a lot of proofs and properties from the multivariate case
can be ported to the single variable case.
However, it means that formal power series are indexed by `Unit →₀ ℕ`,
which is of course canonically isomorphic to `ℕ`.
We then build some glue to treat formal power series as if they were indexed by `ℕ`.
Occasionally this leads to proofs that are uglier than expected.
-/
noncomputable section
open Finset (antidiagonal mem_antidiagonal)
/-- Formal power series over a coefficient type `R` -/
def PowerSeries (R : Type*) :=
MvPowerSeries Unit R
#align power_series PowerSeries
namespace PowerSeries
open Finsupp (single)
variable {R : Type*}
section
-- Porting note: not available in Lean 4
-- local reducible PowerSeries
/--
`R⟦X⟧` is notation for `PowerSeries R`,
the semiring of formal power series in one variable over a semiring `R`.
-/
scoped notation:9000 R "⟦X⟧" => PowerSeries R
instance [Inhabited R] : Inhabited R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Zero R] : Zero R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddMonoid R] : AddMonoid R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddGroup R] : AddGroup R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddCommMonoid R] : AddCommMonoid R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddCommGroup R] : AddCommGroup R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Semiring R] : Semiring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [CommSemiring R] : CommSemiring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Ring R] : Ring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [CommRing R] : CommRing R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Nontrivial R] : Nontrivial R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance {A} [Semiring R] [AddCommMonoid A] [Module R A] : Module R A⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance {A S} [Semiring R] [Semiring S] [AddCommMonoid A] [Module R A] [Module S A] [SMul R S]
[IsScalarTower R S A] : IsScalarTower R S A⟦X⟧ :=
Pi.isScalarTower
instance {A} [Semiring A] [CommSemiring R] [Algebra R A] : Algebra R A⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
end
section Semiring
variable (R) [Semiring R]
/-- The `n`th coefficient of a formal power series. -/
def coeff (n : ℕ) : R⟦X⟧ →ₗ[R] R :=
MvPowerSeries.coeff R (single () n)
#align power_series.coeff PowerSeries.coeff
/-- The `n`th monomial with coefficient `a` as formal power series. -/
def monomial (n : ℕ) : R →ₗ[R] R⟦X⟧ :=
MvPowerSeries.monomial R (single () n)
#align power_series.monomial PowerSeries.monomial
variable {R}
theorem coeff_def {s : Unit →₀ ℕ} {n : ℕ} (h : s () = n) : coeff R n = MvPowerSeries.coeff R s := by
erw [coeff, ← h, ← Finsupp.unique_single s]
#align power_series.coeff_def PowerSeries.coeff_def
/-- Two formal power series are equal if all their coefficients are equal. -/
@[ext]
theorem ext {φ ψ : R⟦X⟧} (h : ∀ n, coeff R n φ = coeff R n ψ) : φ = ψ :=
MvPowerSeries.ext fun n => by
rw [← coeff_def]
· apply h
rfl
#align power_series.ext PowerSeries.ext
/-- Two formal power series are equal if all their coefficients are equal. -/
theorem ext_iff {φ ψ : R⟦X⟧} : φ = ψ ↔ ∀ n, coeff R n φ = coeff R n ψ :=
⟨fun h n => congr_arg (coeff R n) h, ext⟩
#align power_series.ext_iff PowerSeries.ext_iff
instance [Subsingleton R] : Subsingleton R⟦X⟧ := by
simp only [subsingleton_iff, ext_iff]
exact fun _ _ _ ↦ (subsingleton_iff).mp (by infer_instance) _ _
/-- Constructor for formal power series. -/
def mk {R} (f : ℕ → R) : R⟦X⟧ := fun s => f (s ())
#align power_series.mk PowerSeries.mk
@[simp]
theorem coeff_mk (n : ℕ) (f : ℕ → R) : coeff R n (mk f) = f n :=
congr_arg f Finsupp.single_eq_same
#align power_series.coeff_mk PowerSeries.coeff_mk
theorem coeff_monomial (m n : ℕ) (a : R) : coeff R m (monomial R n a) = if m = n then a else 0 :=
calc
coeff R m (monomial R n a) = _ := MvPowerSeries.coeff_monomial _ _ _
_ = if m = n then a else 0 := by simp only [Finsupp.unique_single_eq_iff]
#align power_series.coeff_monomial PowerSeries.coeff_monomial
theorem monomial_eq_mk (n : ℕ) (a : R) : monomial R n a = mk fun m => if m = n then a else 0 :=
ext fun m => by rw [coeff_monomial, coeff_mk]
#align power_series.monomial_eq_mk PowerSeries.monomial_eq_mk
@[simp]
theorem coeff_monomial_same (n : ℕ) (a : R) : coeff R n (monomial R n a) = a :=
MvPowerSeries.coeff_monomial_same _ _
#align power_series.coeff_monomial_same PowerSeries.coeff_monomial_same
@[simp]
theorem coeff_comp_monomial (n : ℕ) : (coeff R n).comp (monomial R n) = LinearMap.id :=
LinearMap.ext <| coeff_monomial_same n
#align power_series.coeff_comp_monomial PowerSeries.coeff_comp_monomial
variable (R)
/-- The constant coefficient of a formal power series. -/
def constantCoeff : R⟦X⟧ →+* R :=
MvPowerSeries.constantCoeff Unit R
#align power_series.constant_coeff PowerSeries.constantCoeff
/-- The constant formal power series. -/
def C : R →+* R⟦X⟧ :=
MvPowerSeries.C Unit R
set_option linter.uppercaseLean3 false in
#align power_series.C PowerSeries.C
variable {R}
/-- The variable of the formal power series ring. -/
def X : R⟦X⟧ :=
MvPowerSeries.X ()
set_option linter.uppercaseLean3 false in
#align power_series.X PowerSeries.X
theorem commute_X (φ : R⟦X⟧) : Commute φ X :=
MvPowerSeries.commute_X _ _
set_option linter.uppercaseLean3 false in
#align power_series.commute_X PowerSeries.commute_X
@[simp]
theorem coeff_zero_eq_constantCoeff : ⇑(coeff R 0) = constantCoeff R := by
rw [coeff, Finsupp.single_zero]
rfl
#align power_series.coeff_zero_eq_constant_coeff PowerSeries.coeff_zero_eq_constantCoeff
theorem coeff_zero_eq_constantCoeff_apply (φ : R⟦X⟧) : coeff R 0 φ = constantCoeff R φ := by
rw [coeff_zero_eq_constantCoeff]
#align power_series.coeff_zero_eq_constant_coeff_apply PowerSeries.coeff_zero_eq_constantCoeff_apply
@[simp]
| Mathlib/RingTheory/PowerSeries/Basic.lean | 239 | 241 | theorem monomial_zero_eq_C : ⇑(monomial R 0) = C R := by |
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [monomial, Finsupp.single_zero, MvPowerSeries.monomial_zero_eq_C]
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Logic.Equiv.Option
import Mathlib.Order.RelIso.Basic
import Mathlib.Order.Disjoint
import Mathlib.Order.WithBot
import Mathlib.Tactic.Monotonicity.Attr
import Mathlib.Util.AssertExists
#align_import order.hom.basic from "leanprover-community/mathlib"@"62a5626868683c104774de8d85b9855234ac807c"
/-!
# Order homomorphisms
This file defines order homomorphisms, which are bundled monotone functions. A preorder
homomorphism `f : α →o β` is a function `α → β` along with a proof that `∀ x y, x ≤ y → f x ≤ f y`.
## Main definitions
In this file we define the following bundled monotone maps:
* `OrderHom α β` a.k.a. `α →o β`: Preorder homomorphism.
An `OrderHom α β` is a function `f : α → β` such that `a₁ ≤ a₂ → f a₁ ≤ f a₂`
* `OrderEmbedding α β` a.k.a. `α ↪o β`: Relation embedding.
An `OrderEmbedding α β` is an embedding `f : α ↪ β` such that `a ≤ b ↔ f a ≤ f b`.
Defined as an abbreviation of `@RelEmbedding α β (≤) (≤)`.
* `OrderIso`: Relation isomorphism.
An `OrderIso α β` is an equivalence `f : α ≃ β` such that `a ≤ b ↔ f a ≤ f b`.
Defined as an abbreviation of `@RelIso α β (≤) (≤)`.
We also define many `OrderHom`s. In some cases we define two versions, one with `ₘ` suffix and
one without it (e.g., `OrderHom.compₘ` and `OrderHom.comp`). This means that the former
function is a "more bundled" version of the latter. We can't just drop the "less bundled" version
because the more bundled version usually does not work with dot notation.
* `OrderHom.id`: identity map as `α →o α`;
* `OrderHom.curry`: an order isomorphism between `α × β →o γ` and `α →o β →o γ`;
* `OrderHom.comp`: composition of two bundled monotone maps;
* `OrderHom.compₘ`: composition of bundled monotone maps as a bundled monotone map;
* `OrderHom.const`: constant function as a bundled monotone map;
* `OrderHom.prod`: combine `α →o β` and `α →o γ` into `α →o β × γ`;
* `OrderHom.prodₘ`: a more bundled version of `OrderHom.prod`;
* `OrderHom.prodIso`: order isomorphism between `α →o β × γ` and `(α →o β) × (α →o γ)`;
* `OrderHom.diag`: diagonal embedding of `α` into `α × α` as a bundled monotone map;
* `OrderHom.onDiag`: restrict a monotone map `α →o α →o β` to the diagonal;
* `OrderHom.fst`: projection `Prod.fst : α × β → α` as a bundled monotone map;
* `OrderHom.snd`: projection `Prod.snd : α × β → β` as a bundled monotone map;
* `OrderHom.prodMap`: `prod.map f g` as a bundled monotone map;
* `Pi.evalOrderHom`: evaluation of a function at a point `Function.eval i` as a bundled
monotone map;
* `OrderHom.coeFnHom`: coercion to function as a bundled monotone map;
* `OrderHom.apply`: application of an `OrderHom` at a point as a bundled monotone map;
* `OrderHom.pi`: combine a family of monotone maps `f i : α →o π i` into a monotone map
`α →o Π i, π i`;
* `OrderHom.piIso`: order isomorphism between `α →o Π i, π i` and `Π i, α →o π i`;
* `OrderHom.subtype.val`: embedding `Subtype.val : Subtype p → α` as a bundled monotone map;
* `OrderHom.dual`: reinterpret a monotone map `α →o β` as a monotone map `αᵒᵈ →o βᵒᵈ`;
* `OrderHom.dualIso`: order isomorphism between `α →o β` and `(αᵒᵈ →o βᵒᵈ)ᵒᵈ`;
* `OrderHom.compl`: order isomorphism `α ≃o αᵒᵈ` given by taking complements in a
boolean algebra;
We also define two functions to convert other bundled maps to `α →o β`:
* `OrderEmbedding.toOrderHom`: convert `α ↪o β` to `α →o β`;
* `RelHom.toOrderHom`: convert a `RelHom` between strict orders to an `OrderHom`.
## Tags
monotone map, bundled morphism
-/
open OrderDual
variable {F α β γ δ : Type*}
/-- Bundled monotone (aka, increasing) function -/
structure OrderHom (α β : Type*) [Preorder α] [Preorder β] where
/-- The underlying function of an `OrderHom`. -/
toFun : α → β
/-- The underlying function of an `OrderHom` is monotone. -/
monotone' : Monotone toFun
#align order_hom OrderHom
/-- Notation for an `OrderHom`. -/
infixr:25 " →o " => OrderHom
/-- An order embedding is an embedding `f : α ↪ β` such that `a ≤ b ↔ (f a) ≤ (f b)`.
This definition is an abbreviation of `RelEmbedding (≤) (≤)`. -/
abbrev OrderEmbedding (α β : Type*) [LE α] [LE β] :=
@RelEmbedding α β (· ≤ ·) (· ≤ ·)
#align order_embedding OrderEmbedding
/-- Notation for an `OrderEmbedding`. -/
infixl:25 " ↪o " => OrderEmbedding
/-- An order isomorphism is an equivalence such that `a ≤ b ↔ (f a) ≤ (f b)`.
This definition is an abbreviation of `RelIso (≤) (≤)`. -/
abbrev OrderIso (α β : Type*) [LE α] [LE β] :=
@RelIso α β (· ≤ ·) (· ≤ ·)
#align order_iso OrderIso
/-- Notation for an `OrderIso`. -/
infixl:25 " ≃o " => OrderIso
section
/-- `OrderHomClass F α b` asserts that `F` is a type of `≤`-preserving morphisms. -/
abbrev OrderHomClass (F : Type*) (α β : outParam Type*) [LE α] [LE β] [FunLike F α β] :=
RelHomClass F ((· ≤ ·) : α → α → Prop) ((· ≤ ·) : β → β → Prop)
#align order_hom_class OrderHomClass
/-- `OrderIsoClass F α β` states that `F` is a type of order isomorphisms.
You should extend this class when you extend `OrderIso`. -/
class OrderIsoClass (F α β : Type*) [LE α] [LE β] [EquivLike F α β] : Prop where
/-- An order isomorphism respects `≤`. -/
map_le_map_iff (f : F) {a b : α} : f a ≤ f b ↔ a ≤ b
#align order_iso_class OrderIsoClass
end
export OrderIsoClass (map_le_map_iff)
attribute [simp] map_le_map_iff
/-- Turn an element of a type `F` satisfying `OrderIsoClass F α β` into an actual
`OrderIso`. This is declared as the default coercion from `F` to `α ≃o β`. -/
@[coe]
def OrderIsoClass.toOrderIso [LE α] [LE β] [EquivLike F α β] [OrderIsoClass F α β] (f : F) :
α ≃o β :=
{ EquivLike.toEquiv f with map_rel_iff' := map_le_map_iff f }
/-- Any type satisfying `OrderIsoClass` can be cast into `OrderIso` via
`OrderIsoClass.toOrderIso`. -/
instance [LE α] [LE β] [EquivLike F α β] [OrderIsoClass F α β] : CoeTC F (α ≃o β) :=
⟨OrderIsoClass.toOrderIso⟩
-- See note [lower instance priority]
instance (priority := 100) OrderIsoClass.toOrderHomClass [LE α] [LE β]
[EquivLike F α β] [OrderIsoClass F α β] : OrderHomClass F α β :=
{ EquivLike.toEmbeddingLike (E := F) with
map_rel := fun f _ _ => (map_le_map_iff f).2 }
#align order_iso_class.to_order_hom_class OrderIsoClass.toOrderHomClass
namespace OrderHomClass
variable [Preorder α] [Preorder β] [FunLike F α β] [OrderHomClass F α β]
protected theorem monotone (f : F) : Monotone f := fun _ _ => map_rel f
#align order_hom_class.monotone OrderHomClass.monotone
protected theorem mono (f : F) : Monotone f := fun _ _ => map_rel f
#align order_hom_class.mono OrderHomClass.mono
/-- Turn an element of a type `F` satisfying `OrderHomClass F α β` into an actual
`OrderHom`. This is declared as the default coercion from `F` to `α →o β`. -/
@[coe]
def toOrderHom (f : F) : α →o β where
toFun := f
monotone' := OrderHomClass.monotone f
/-- Any type satisfying `OrderHomClass` can be cast into `OrderHom` via
`OrderHomClass.toOrderHom`. -/
instance : CoeTC F (α →o β) :=
⟨toOrderHom⟩
end OrderHomClass
section OrderIsoClass
section LE
variable [LE α] [LE β] [EquivLike F α β] [OrderIsoClass F α β]
-- Porting note: needed to add explicit arguments to map_le_map_iff
@[simp]
theorem map_inv_le_iff (f : F) {a : α} {b : β} : EquivLike.inv f b ≤ a ↔ b ≤ f a := by
convert (map_le_map_iff f (a := EquivLike.inv f b) (b := a)).symm
exact (EquivLike.right_inv f _).symm
#align map_inv_le_iff map_inv_le_iff
-- Porting note: needed to add explicit arguments to map_le_map_iff
@[simp]
theorem le_map_inv_iff (f : F) {a : α} {b : β} : a ≤ EquivLike.inv f b ↔ f a ≤ b := by
convert (map_le_map_iff f (a := a) (b := EquivLike.inv f b)).symm
exact (EquivLike.right_inv _ _).symm
#align le_map_inv_iff le_map_inv_iff
end LE
variable [Preorder α] [Preorder β] [EquivLike F α β] [OrderIsoClass F α β]
theorem map_lt_map_iff (f : F) {a b : α} : f a < f b ↔ a < b :=
lt_iff_lt_of_le_iff_le' (map_le_map_iff f) (map_le_map_iff f)
#align map_lt_map_iff map_lt_map_iff
@[simp]
theorem map_inv_lt_iff (f : F) {a : α} {b : β} : EquivLike.inv f b < a ↔ b < f a := by
rw [← map_lt_map_iff f]
simp only [EquivLike.apply_inv_apply]
#align map_inv_lt_iff map_inv_lt_iff
@[simp]
theorem lt_map_inv_iff (f : F) {a : α} {b : β} : a < EquivLike.inv f b ↔ f a < b := by
rw [← map_lt_map_iff f]
simp only [EquivLike.apply_inv_apply]
#align lt_map_inv_iff lt_map_inv_iff
end OrderIsoClass
namespace OrderHom
variable [Preorder α] [Preorder β] [Preorder γ] [Preorder δ]
instance : FunLike (α →o β) α β where
coe := toFun
coe_injective' f g h := by cases f; cases g; congr
instance : OrderHomClass (α →o β) α β where
map_rel f _ _ h := f.monotone' h
@[simp] theorem coe_mk (f : α → β) (hf : Monotone f) : ⇑(mk f hf) = f := rfl
#align order_hom.coe_fun_mk OrderHom.coe_mk
protected theorem monotone (f : α →o β) : Monotone f :=
f.monotone'
#align order_hom.monotone OrderHom.monotone
protected theorem mono (f : α →o β) : Monotone f :=
f.monotone
#align order_hom.mono OrderHom.mono
/-- See Note [custom simps projection]. We give this manually so that we use `toFun` as the
projection directly instead. -/
def Simps.coe (f : α →o β) : α → β := f
/- Porting note (#11215): TODO: all other DFunLike classes use `apply` instead of `coe`
for the projection names. Maybe we should change this. -/
initialize_simps_projections OrderHom (toFun → coe)
@[simp] theorem toFun_eq_coe (f : α →o β) : f.toFun = f := rfl
#align order_hom.to_fun_eq_coe OrderHom.toFun_eq_coe
-- See library note [partially-applied ext lemmas]
@[ext]
theorem ext (f g : α →o β) (h : (f : α → β) = g) : f = g :=
DFunLike.coe_injective h
#align order_hom.ext OrderHom.ext
@[simp] theorem coe_eq (f : α →o β) : OrderHomClass.toOrderHom f = f := rfl
@[simp] theorem _root_.OrderHomClass.coe_coe {F} [FunLike F α β] [OrderHomClass F α β] (f : F) :
⇑(f : α →o β) = f :=
rfl
/-- One can lift an unbundled monotone function to a bundled one. -/
protected instance canLift : CanLift (α → β) (α →o β) (↑) Monotone where
prf f h := ⟨⟨f, h⟩, rfl⟩
#align order_hom.monotone.can_lift OrderHom.canLift
/-- Copy of an `OrderHom` with a new `toFun` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (f : α →o β) (f' : α → β) (h : f' = f) : α →o β :=
⟨f', h.symm.subst f.monotone'⟩
#align order_hom.copy OrderHom.copy
@[simp]
theorem coe_copy (f : α →o β) (f' : α → β) (h : f' = f) : (f.copy f' h) = f' :=
rfl
#align order_hom.coe_copy OrderHom.coe_copy
theorem copy_eq (f : α →o β) (f' : α → β) (h : f' = f) : f.copy f' h = f :=
DFunLike.ext' h
#align order_hom.copy_eq OrderHom.copy_eq
/-- The identity function as bundled monotone function. -/
@[simps (config := .asFn)]
def id : α →o α :=
⟨_root_.id, monotone_id⟩
#align order_hom.id OrderHom.id
#align order_hom.id_coe OrderHom.id_coe
instance : Inhabited (α →o α) :=
⟨id⟩
/-- The preorder structure of `α →o β` is pointwise inequality: `f ≤ g ↔ ∀ a, f a ≤ g a`. -/
instance : Preorder (α →o β) :=
@Preorder.lift (α →o β) (α → β) _ toFun
instance {β : Type*} [PartialOrder β] : PartialOrder (α →o β) :=
@PartialOrder.lift (α →o β) (α → β) _ toFun ext
theorem le_def {f g : α →o β} : f ≤ g ↔ ∀ x, f x ≤ g x :=
Iff.rfl
#align order_hom.le_def OrderHom.le_def
@[simp, norm_cast]
theorem coe_le_coe {f g : α →o β} : (f : α → β) ≤ g ↔ f ≤ g :=
Iff.rfl
#align order_hom.coe_le_coe OrderHom.coe_le_coe
@[simp]
theorem mk_le_mk {f g : α → β} {hf hg} : mk f hf ≤ mk g hg ↔ f ≤ g :=
Iff.rfl
#align order_hom.mk_le_mk OrderHom.mk_le_mk
@[mono]
theorem apply_mono {f g : α →o β} {x y : α} (h₁ : f ≤ g) (h₂ : x ≤ y) : f x ≤ g y :=
(h₁ x).trans <| g.mono h₂
#align order_hom.apply_mono OrderHom.apply_mono
/-- Curry/uncurry as an order isomorphism between `α × β →o γ` and `α →o β →o γ`. -/
def curry : (α × β →o γ) ≃o (α →o β →o γ) where
toFun f := ⟨fun x ↦ ⟨Function.curry f x, fun _ _ h ↦ f.mono ⟨le_rfl, h⟩⟩, fun _ _ h _ =>
f.mono ⟨h, le_rfl⟩⟩
invFun f := ⟨Function.uncurry fun x ↦ f x, fun x y h ↦ (f.mono h.1 x.2).trans ((f y.1).mono h.2)⟩
left_inv _ := rfl
right_inv _ := rfl
map_rel_iff' := by simp [le_def]
#align order_hom.curry OrderHom.curry
@[simp]
theorem curry_apply (f : α × β →o γ) (x : α) (y : β) : curry f x y = f (x, y) :=
rfl
#align order_hom.curry_apply OrderHom.curry_apply
@[simp]
theorem curry_symm_apply (f : α →o β →o γ) (x : α × β) : curry.symm f x = f x.1 x.2 :=
rfl
#align order_hom.curry_symm_apply OrderHom.curry_symm_apply
/-- The composition of two bundled monotone functions. -/
@[simps (config := .asFn)]
def comp (g : β →o γ) (f : α →o β) : α →o γ :=
⟨g ∘ f, g.mono.comp f.mono⟩
#align order_hom.comp OrderHom.comp
#align order_hom.comp_coe OrderHom.comp_coe
@[mono]
theorem comp_mono ⦃g₁ g₂ : β →o γ⦄ (hg : g₁ ≤ g₂) ⦃f₁ f₂ : α →o β⦄ (hf : f₁ ≤ f₂) :
g₁.comp f₁ ≤ g₂.comp f₂ := fun _ => (hg _).trans (g₂.mono <| hf _)
#align order_hom.comp_mono OrderHom.comp_mono
/-- The composition of two bundled monotone functions, a fully bundled version. -/
@[simps! (config := .asFn)]
def compₘ : (β →o γ) →o (α →o β) →o α →o γ :=
curry ⟨fun f : (β →o γ) × (α →o β) => f.1.comp f.2, fun _ _ h => comp_mono h.1 h.2⟩
#align order_hom.compₘ OrderHom.compₘ
#align order_hom.compₘ_coe_coe_coe OrderHom.compₘ_coe_coe_coe
@[simp]
theorem comp_id (f : α →o β) : comp f id = f := by
ext
rfl
#align order_hom.comp_id OrderHom.comp_id
@[simp]
theorem id_comp (f : α →o β) : comp id f = f := by
ext
rfl
#align order_hom.id_comp OrderHom.id_comp
/-- Constant function bundled as an `OrderHom`. -/
@[simps (config := .asFn)]
def const (α : Type*) [Preorder α] {β : Type*} [Preorder β] : β →o α →o β where
toFun b := ⟨Function.const α b, fun _ _ _ => le_rfl⟩
monotone' _ _ h _ := h
#align order_hom.const OrderHom.const
#align order_hom.const_coe_coe OrderHom.const_coe_coe
@[simp]
theorem const_comp (f : α →o β) (c : γ) : (const β c).comp f = const α c :=
rfl
#align order_hom.const_comp OrderHom.const_comp
@[simp]
theorem comp_const (γ : Type*) [Preorder γ] (f : α →o β) (c : α) :
f.comp (const γ c) = const γ (f c) :=
rfl
#align order_hom.comp_const OrderHom.comp_const
/-- Given two bundled monotone maps `f`, `g`, `f.prod g` is the map `x ↦ (f x, g x)` bundled as a
`OrderHom`. -/
@[simps]
protected def prod (f : α →o β) (g : α →o γ) : α →o β × γ :=
⟨fun x => (f x, g x), fun _ _ h => ⟨f.mono h, g.mono h⟩⟩
#align order_hom.prod OrderHom.prod
#align order_hom.prod_coe OrderHom.prod_coe
@[mono]
theorem prod_mono {f₁ f₂ : α →o β} (hf : f₁ ≤ f₂) {g₁ g₂ : α →o γ} (hg : g₁ ≤ g₂) :
f₁.prod g₁ ≤ f₂.prod g₂ := fun _ => Prod.le_def.2 ⟨hf _, hg _⟩
#align order_hom.prod_mono OrderHom.prod_mono
theorem comp_prod_comp_same (f₁ f₂ : β →o γ) (g : α →o β) :
(f₁.comp g).prod (f₂.comp g) = (f₁.prod f₂).comp g :=
rfl
#align order_hom.comp_prod_comp_same OrderHom.comp_prod_comp_same
/-- Given two bundled monotone maps `f`, `g`, `f.prod g` is the map `x ↦ (f x, g x)` bundled as a
`OrderHom`. This is a fully bundled version. -/
@[simps!]
def prodₘ : (α →o β) →o (α →o γ) →o α →o β × γ :=
curry ⟨fun f : (α →o β) × (α →o γ) => f.1.prod f.2, fun _ _ h => prod_mono h.1 h.2⟩
#align order_hom.prodₘ OrderHom.prodₘ
#align order_hom.prodₘ_coe_coe_coe OrderHom.prodₘ_coe_coe_coe
/-- Diagonal embedding of `α` into `α × α` as an `OrderHom`. -/
@[simps!]
def diag : α →o α × α :=
id.prod id
#align order_hom.diag OrderHom.diag
#align order_hom.diag_coe OrderHom.diag_coe
/-- Restriction of `f : α →o α →o β` to the diagonal. -/
@[simps! (config := { simpRhs := true })]
def onDiag (f : α →o α →o β) : α →o β :=
(curry.symm f).comp diag
#align order_hom.on_diag OrderHom.onDiag
#align order_hom.on_diag_coe OrderHom.onDiag_coe
/-- `Prod.fst` as an `OrderHom`. -/
@[simps]
def fst : α × β →o α :=
⟨Prod.fst, fun _ _ h => h.1⟩
#align order_hom.fst OrderHom.fst
#align order_hom.fst_coe OrderHom.fst_coe
/-- `Prod.snd` as an `OrderHom`. -/
@[simps]
def snd : α × β →o β :=
⟨Prod.snd, fun _ _ h => h.2⟩
#align order_hom.snd OrderHom.snd
#align order_hom.snd_coe OrderHom.snd_coe
@[simp]
| Mathlib/Order/Hom/Basic.lean | 440 | 442 | theorem fst_prod_snd : (fst : α × β →o α).prod snd = id := by |
ext ⟨x, y⟩ : 2
rfl
|
/-
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.GroupTheory.CoprodI
import Mathlib.GroupTheory.Coprod.Basic
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.GroupTheory.Complement
/-!
## Pushouts of Monoids and Groups
This file defines wide pushouts of monoids and groups and proves some properties
of the amalgamated product of groups (i.e. the special case where all the maps
in the diagram are injective).
## Main definitions
- `Monoid.PushoutI`: the pushout of a diagram of monoids indexed by a type `ι`
- `Monoid.PushoutI.base`: the map from the amalgamating monoid to the pushout
- `Monoid.PushoutI.of`: the map from each Monoid in the family to the pushout
- `Monoid.PushoutI.lift`: the universal property used to define homomorphisms out of the pushout.
- `Monoid.PushoutI.NormalWord`: a normal form for words in the pushout
- `Monoid.PushoutI.of_injective`: if all the maps in the diagram are injective in a pushout of
groups then so is `of`
- `Monoid.PushoutI.Reduced.eq_empty_of_mem_range`: For any word `w` in the coproduct,
if `w` is reduced (i.e none its letters are in the image of the base monoid), and nonempty, then
`w` itself is not in the image of the base monoid.
## References
* The normal form theorem follows these [notes](https://webspace.maths.qmul.ac.uk/i.m.chiswell/ggt/lecture_notes/lecture2.pdf)
from Queen Mary University
## Tags
amalgamated product, pushout, group
-/
namespace Monoid
open CoprodI Subgroup Coprod Function List
variable {ι : Type*} {G : ι → Type*} {H : Type*} {K : Type*} [Monoid K]
/-- The relation we quotient by to form the pushout -/
def PushoutI.con [∀ i, Monoid (G i)] [Monoid H] (φ : ∀ i, H →* G i) :
Con (Coprod (CoprodI G) H) :=
conGen (fun x y : Coprod (CoprodI G) H =>
∃ i x', x = inl (of (φ i x')) ∧ y = inr x')
/-- The indexed pushout of monoids, which is the pushout in the category of monoids,
or the category of groups. -/
def PushoutI [∀ i, Monoid (G i)] [Monoid H] (φ : ∀ i, H →* G i) : Type _ :=
(PushoutI.con φ).Quotient
namespace PushoutI
section Monoid
variable [∀ i, Monoid (G i)] [Monoid H] {φ : ∀ i, H →* G i}
protected instance mul : Mul (PushoutI φ) := by
delta PushoutI; infer_instance
protected instance one : One (PushoutI φ) := by
delta PushoutI; infer_instance
instance monoid : Monoid (PushoutI φ) :=
{ Con.monoid _ with
toMul := PushoutI.mul
toOne := PushoutI.one }
/-- The map from each indexing group into the pushout -/
def of (i : ι) : G i →* PushoutI φ :=
(Con.mk' _).comp <| inl.comp CoprodI.of
variable (φ) in
/-- The map from the base monoid into the pushout -/
def base : H →* PushoutI φ :=
(Con.mk' _).comp inr
theorem of_comp_eq_base (i : ι) : (of i).comp (φ i) = (base φ) := by
ext x
apply (Con.eq _).2
refine ConGen.Rel.of _ _ ?_
simp only [MonoidHom.comp_apply, Set.mem_iUnion, Set.mem_range]
exact ⟨_, _, rfl, rfl⟩
variable (φ) in
theorem of_apply_eq_base (i : ι) (x : H) : of i (φ i x) = base φ x := by
rw [← MonoidHom.comp_apply, of_comp_eq_base]
/-- Define a homomorphism out of the pushout of monoids be defining it on each object in the
diagram -/
def lift (f : ∀ i, G i →* K) (k : H →* K)
(hf : ∀ i, (f i).comp (φ i) = k) :
PushoutI φ →* K :=
Con.lift _ (Coprod.lift (CoprodI.lift f) k) <| by
apply Con.conGen_le fun x y => ?_
rintro ⟨i, x', rfl, rfl⟩
simp only [DFunLike.ext_iff, MonoidHom.coe_comp, comp_apply] at hf
simp [hf]
@[simp]
theorem lift_of (f : ∀ i, G i →* K) (k : H →* K)
(hf : ∀ i, (f i).comp (φ i) = k)
{i : ι} (g : G i) : (lift f k hf) (of i g : PushoutI φ) = f i g := by
delta PushoutI lift of
simp only [MonoidHom.coe_comp, Con.coe_mk', comp_apply, Con.lift_coe,
lift_apply_inl, CoprodI.lift_of]
@[simp]
theorem lift_base (f : ∀ i, G i →* K) (k : H →* K)
(hf : ∀ i, (f i).comp (φ i) = k)
(g : H) : (lift f k hf) (base φ g : PushoutI φ) = k g := by
delta PushoutI lift base
simp only [MonoidHom.coe_comp, Con.coe_mk', comp_apply, Con.lift_coe, lift_apply_inr]
-- `ext` attribute should be lower priority then `hom_ext_nonempty`
@[ext 1199]
theorem hom_ext {f g : PushoutI φ →* K}
(h : ∀ i, f.comp (of i : G i →* _) = g.comp (of i : G i →* _))
(hbase : f.comp (base φ) = g.comp (base φ)) : f = g :=
(MonoidHom.cancel_right Con.mk'_surjective).mp <|
Coprod.hom_ext
(CoprodI.ext_hom _ _ h)
hbase
@[ext high]
theorem hom_ext_nonempty [hn : Nonempty ι]
{f g : PushoutI φ →* K}
(h : ∀ i, f.comp (of i : G i →* _) = g.comp (of i : G i →* _)) : f = g :=
hom_ext h <| by
cases hn with
| intro i =>
ext
rw [← of_comp_eq_base i, ← MonoidHom.comp_assoc, h, MonoidHom.comp_assoc]
/-- The equivalence that is part of the universal property of the pushout. A hom out of
the pushout is just a morphism out of all groups in the pushout that satisfies a commutativity
condition. -/
@[simps]
def homEquiv :
(PushoutI φ →* K) ≃ { f : (Π i, G i →* K) × (H →* K) // ∀ i, (f.1 i).comp (φ i) = f.2 } :=
{ toFun := fun f => ⟨(fun i => f.comp (of i), f.comp (base φ)),
fun i => by rw [MonoidHom.comp_assoc, of_comp_eq_base]⟩
invFun := fun f => lift f.1.1 f.1.2 f.2,
left_inv := fun _ => hom_ext (by simp [DFunLike.ext_iff])
(by simp [DFunLike.ext_iff])
right_inv := fun ⟨⟨_, _⟩, _⟩ => by simp [DFunLike.ext_iff, Function.funext_iff] }
/-- The map from the coproduct into the pushout -/
def ofCoprodI : CoprodI G →* PushoutI φ :=
CoprodI.lift of
@[simp]
theorem ofCoprodI_of (i : ι) (g : G i) :
(ofCoprodI (CoprodI.of g) : PushoutI φ) = of i g := by
simp [ofCoprodI]
theorem induction_on {motive : PushoutI φ → Prop}
(x : PushoutI φ)
(of : ∀ (i : ι) (g : G i), motive (of i g))
(base : ∀ h, motive (base φ h))
(mul : ∀ x y, motive x → motive y → motive (x * y)) : motive x := by
delta PushoutI PushoutI.of PushoutI.base at *
induction x using Con.induction_on with
| H x =>
induction x using Coprod.induction_on with
| inl g =>
induction g using CoprodI.induction_on with
| h_of i g => exact of i g
| h_mul x y ihx ihy =>
rw [map_mul]
exact mul _ _ ihx ihy
| h_one => simpa using base 1
| inr h => exact base h
| mul x y ihx ihy => exact mul _ _ ihx ihy
end Monoid
variable [∀ i, Group (G i)] [Group H] {φ : ∀ i, H →* G i}
instance : Group (PushoutI φ) :=
{ Con.group (PushoutI.con φ) with
toMonoid := PushoutI.monoid }
namespace NormalWord
/-
In this section we show that there is a normal form for words in the amalgamated product. To have a
normal form, we need to pick canonical choice of element of each right coset of the base group. The
choice of element in the base group itself is `1`. Given a choice of element of each right coset,
given by the type `Transversal φ` we can find a normal form. The normal form for an element is an
element of the base group, multiplied by a word in the coproduct, where each letter in the word is
the canonical choice of element of its coset. We then show that all groups in the diagram act
faithfully on the normal form. This implies that the maps into the coproduct are injective.
We demonstrate the action is faithful using the equivalence `equivPair`. We show that `G i` acts
faithfully on `Pair d i` and that `Pair d i` is isomorphic to `NormalWord d`. Here, `d` is a
`Transversal`. A `Pair d i` is a word in the coproduct, `Coprod G`, the `tail`, and an element
of the group `G i`, the `head`. The first letter of the `tail` must not be an element of `G i`.
Note that the `head` may be `1` Every letter in the `tail` must be in the transversal given by `d`.
We then show that the equivalence between `NormalWord` and `PushoutI`, between the set of normal
words and the elements of the amalgamated product. The key to this is the theorem `prod_smul_empty`,
which says that going from `NormalWord` to `PushoutI` and back is the identity. This is proven
by induction on the word using `consRecOn`.
-/
variable (φ)
/-- The data we need to pick a normal form for words in the pushout. We need to pick a
canonical element of each coset. We also need all the maps in the diagram to be injective -/
structure Transversal : Type _ where
/-- All maps in the diagram are injective -/
injective : ∀ i, Injective (φ i)
/-- The underlying set, containing exactly one element of each coset of the base group -/
set : ∀ i, Set (G i)
/-- The chosen element of the base group itself is the identity -/
one_mem : ∀ i, 1 ∈ set i
/-- We have exactly one element of each coset of the base group -/
compl : ∀ i, IsComplement (φ i).range (set i)
theorem transversal_nonempty (hφ : ∀ i, Injective (φ i)) : Nonempty (Transversal φ) := by
choose t ht using fun i => (φ i).range.exists_right_transversal 1
apply Nonempty.intro
exact
{ injective := hφ
set := t
one_mem := fun i => (ht i).2
compl := fun i => (ht i).1 }
variable {φ}
/-- The normal form for words in the pushout. Every element of the pushout is the product of an
element of the base group and a word made up of letters each of which is in the transversal. -/
structure _root_.Monoid.PushoutI.NormalWord (d : Transversal φ) extends CoprodI.Word G where
/-- Every `NormalWord` is the product of an element of the base group and a word made up
of letters each of which is in the transversal. `head` is that element of the base group. -/
head : H
/-- All letter in the word are in the transversal. -/
normalized : ∀ i g, ⟨i, g⟩ ∈ toList → g ∈ d.set i
/--
A `Pair d i` is a word in the coproduct, `Coprod G`, the `tail`, and an element of the group `G i`,
the `head`. The first letter of the `tail` must not be an element of `G i`.
Note that the `head` may be `1` Every letter in the `tail` must be in the transversal given by `d`.
Similar to `Monoid.CoprodI.Pair` except every letter must be in the transversal
(not including the head letter). -/
structure Pair (d : Transversal φ) (i : ι) extends CoprodI.Word.Pair G i where
/-- All letters in the word are in the transversal. -/
normalized : ∀ i g, ⟨i, g⟩ ∈ tail.toList → g ∈ d.set i
variable {d : Transversal φ}
/-- The empty normalized word, representing the identity element of the group. -/
@[simps!]
def empty : NormalWord d := ⟨CoprodI.Word.empty, 1, fun i g => by simp [CoprodI.Word.empty]⟩
instance : Inhabited (NormalWord d) := ⟨NormalWord.empty⟩
instance (i : ι) : Inhabited (Pair d i) :=
⟨{ (empty : NormalWord d) with
head := 1,
fstIdx_ne := fun h => by cases h }⟩
variable [DecidableEq ι] [∀ i, DecidableEq (G i)]
@[ext]
theorem ext {w₁ w₂ : NormalWord d} (hhead : w₁.head = w₂.head)
(hlist : w₁.toList = w₂.toList) : w₁ = w₂ := by
rcases w₁ with ⟨⟨_, _, _⟩, _, _⟩
rcases w₂ with ⟨⟨_, _, _⟩, _, _⟩
simp_all
theorem ext_iff {w₁ w₂ : NormalWord d} : w₁ = w₂ ↔ w₁.head = w₂.head ∧ w₁.toList = w₂.toList :=
⟨fun h => by simp [h], fun ⟨h₁, h₂⟩ => ext h₁ h₂⟩
open Subgroup.IsComplement
/-- Given a word in `CoprodI`, if every letter is in the transversal and when
we multiply by an element of the base group it still has this property,
then the element of the base group we multiplied by was one. -/
theorem eq_one_of_smul_normalized (w : CoprodI.Word G) {i : ι} (h : H)
(hw : ∀ i g, ⟨i, g⟩ ∈ w.toList → g ∈ d.set i)
(hφw : ∀ j g, ⟨j, g⟩ ∈ (CoprodI.of (φ i h) • w).toList → g ∈ d.set j) :
h = 1 := by
simp only [← (d.compl _).equiv_snd_eq_self_iff_mem (one_mem _)] at hw hφw
have hhead : ((d.compl i).equiv (Word.equivPair i w).head).2 =
(Word.equivPair i w).head := by
rw [Word.equivPair_head]
split_ifs with h
· rcases h with ⟨_, rfl⟩
exact hw _ _ (List.head_mem _)
· rw [equiv_one (d.compl i) (one_mem _) (d.one_mem _)]
by_contra hh1
have := hφw i (φ i h * (Word.equivPair i w).head) ?_
· apply hh1
rw [equiv_mul_left_of_mem (d.compl i) ⟨_, rfl⟩, hhead] at this
simpa [((injective_iff_map_eq_one' _).1 (d.injective i))] using this
· simp only [Word.mem_smul_iff, not_true, false_and, ne_eq, Option.mem_def, mul_right_inj,
exists_eq_right', mul_right_eq_self, exists_prop, true_and, false_or]
constructor
· intro h
apply_fun (d.compl i).equiv at h
simp only [Prod.ext_iff, equiv_one (d.compl i) (one_mem _) (d.one_mem _),
equiv_mul_left_of_mem (d.compl i) ⟨_, rfl⟩ , hhead, Subtype.ext_iff,
Prod.ext_iff, Subgroup.coe_mul] at h
rcases h with ⟨h₁, h₂⟩
rw [h₂, equiv_one (d.compl i) (one_mem _) (d.one_mem _), mul_one,
((injective_iff_map_eq_one' _).1 (d.injective i))] at h₁
contradiction
· rw [Word.equivPair_head]
dsimp
split_ifs with hep
· rcases hep with ⟨hnil, rfl⟩
rw [head?_eq_head _ hnil]
simp_all
· push_neg at hep
by_cases hw : w.toList = []
· simp [hw, Word.fstIdx]
· simp [head?_eq_head _ hw, Word.fstIdx, hep hw]
theorem ext_smul {w₁ w₂ : NormalWord d} (i : ι)
(h : CoprodI.of (φ i w₁.head) • w₁.toWord =
CoprodI.of (φ i w₂.head) • w₂.toWord) :
w₁ = w₂ := by
rcases w₁ with ⟨w₁, h₁, hw₁⟩
rcases w₂ with ⟨w₂, h₂, hw₂⟩
dsimp at *
rw [smul_eq_iff_eq_inv_smul, ← mul_smul] at h
subst h
simp only [← map_inv, ← map_mul] at hw₁
have : h₁⁻¹ * h₂ = 1 := eq_one_of_smul_normalized w₂ (h₁⁻¹ * h₂) hw₂ hw₁
rw [inv_mul_eq_one] at this; subst this
simp
/-- A constructor that multiplies a `NormalWord` by an element, with condition to make
sure the underlying list does get longer. -/
@[simps!]
noncomputable def cons {i} (g : G i) (w : NormalWord d) (hmw : w.fstIdx ≠ some i)
(hgr : g ∉ (φ i).range) : NormalWord d :=
letI n := (d.compl i).equiv (g * (φ i w.head))
letI w' := Word.cons (n.2 : G i) w.toWord hmw
(mt (coe_equiv_snd_eq_one_iff_mem _ (d.one_mem _)).1
(mt (mul_mem_cancel_right (by simp)).1 hgr))
{ toWord := w'
head := (MonoidHom.ofInjective (d.injective i)).symm n.1
normalized := fun i g hg => by
simp only [w', Word.cons, mem_cons, Sigma.mk.inj_iff] at hg
rcases hg with ⟨rfl, hg | hg⟩
· simp
· exact w.normalized _ _ (by assumption) }
/-- Given a pair `(head, tail)`, we can form a word by prepending `head` to `tail`, but
putting head into normal form first, by making sure it is expressed as an element
of the base group multiplied by an element of the transversal. -/
noncomputable def rcons (i : ι) (p : Pair d i) : NormalWord d :=
letI n := (d.compl i).equiv p.head
let w := (Word.equivPair i).symm { p.toPair with head := n.2 }
{ toWord := w
head := (MonoidHom.ofInjective (d.injective i)).symm n.1
normalized := fun i g hg => by
dsimp [w] at hg
rw [Word.equivPair_symm, Word.mem_rcons_iff] at hg
rcases hg with hg | ⟨_, rfl, rfl⟩
· exact p.normalized _ _ hg
· simp }
theorem rcons_injective {i : ι} : Function.Injective (rcons (d := d) i) := by
rintro ⟨⟨head₁, tail₁⟩, _⟩ ⟨⟨head₂, tail₂⟩, _⟩
simp only [rcons, NormalWord.mk.injEq, EmbeddingLike.apply_eq_iff_eq,
Word.Pair.mk.injEq, Pair.mk.injEq, and_imp]
intro h₁ h₂ h₃
subst h₂
rw [← equiv_fst_mul_equiv_snd (d.compl i) head₁,
← equiv_fst_mul_equiv_snd (d.compl i) head₂,
h₁, h₃]
simp
/-- The equivalence between `NormalWord`s and pairs. We can turn a `NormalWord` into a
pair by taking the head of the `List` if it is in `G i` and multiplying it by the element of the
base group. -/
noncomputable def equivPair (i) : NormalWord d ≃ Pair d i :=
letI toFun : NormalWord d → Pair d i :=
fun w =>
letI p := Word.equivPair i (CoprodI.of (φ i w.head) • w.toWord)
{ toPair := p
normalized := fun j g hg => by
dsimp only [p] at hg
rw [Word.of_smul_def, ← Word.equivPair_symm, Equiv.apply_symm_apply] at hg
dsimp at hg
exact w.normalized _ _ (Word.mem_of_mem_equivPair_tail _ hg) }
haveI leftInv : Function.LeftInverse (rcons i) toFun :=
fun w => ext_smul i <| by
simp only [rcons, Word.equivPair_symm,
Word.equivPair_smul_same, Word.equivPair_tail_eq_inv_smul, Word.rcons_eq_smul,
MonoidHom.apply_ofInjective_symm, equiv_fst_eq_mul_inv, mul_assoc, map_mul, map_inv,
mul_smul, inv_smul_smul, smul_inv_smul]
{ toFun := toFun
invFun := rcons i
left_inv := leftInv
right_inv := fun _ => rcons_injective (leftInv _) }
noncomputable instance summandAction (i : ι) : MulAction (G i) (NormalWord d) :=
{ smul := fun g w => (equivPair i).symm
{ equivPair i w with
head := g * (equivPair i w).head }
one_smul := fun _ => by
dsimp [instHSMul]
rw [one_mul]
exact (equivPair i).symm_apply_apply _
mul_smul := fun _ _ _ => by
dsimp [instHSMul]
simp [mul_assoc, Equiv.apply_symm_apply, Function.End.mul_def] }
instance baseAction : MulAction H (NormalWord d) :=
{ smul := fun h w => { w with head := h * w.head },
one_smul := by simp [instHSMul]
mul_smul := by simp [instHSMul, mul_assoc] }
theorem base_smul_def' (h : H) (w : NormalWord d) :
h • w = { w with head := h * w.head } := rfl
theorem summand_smul_def' {i : ι} (g : G i) (w : NormalWord d) :
g • w = (equivPair i).symm
{ equivPair i w with
head := g * (equivPair i w).head } := rfl
noncomputable instance mulAction : MulAction (PushoutI φ) (NormalWord d) :=
MulAction.ofEndHom <|
lift
(fun i => MulAction.toEndHom)
MulAction.toEndHom <| by
intro i
simp only [MulAction.toEndHom, DFunLike.ext_iff, MonoidHom.coe_comp, MonoidHom.coe_mk,
OneHom.coe_mk, comp_apply]
intro h
funext w
apply NormalWord.ext_smul i
simp only [summand_smul_def', equivPair, rcons, Word.equivPair_symm, Equiv.coe_fn_mk,
Equiv.coe_fn_symm_mk, Word.equivPair_smul_same, Word.equivPair_tail_eq_inv_smul,
Word.rcons_eq_smul, equiv_fst_eq_mul_inv, map_mul, map_inv, mul_smul, inv_smul_smul,
smul_inv_smul, base_smul_def', MonoidHom.apply_ofInjective_symm]
theorem base_smul_def (h : H) (w : NormalWord d) :
base φ h • w = { w with head := h * w.head } := by
dsimp [NormalWord.mulAction, instHSMul, SMul.smul]
rw [lift_base]
rfl
theorem summand_smul_def {i : ι} (g : G i) (w : NormalWord d) :
of (φ := φ) i g • w = (equivPair i).symm
{ equivPair i w with
head := g * (equivPair i w).head } := by
dsimp [NormalWord.mulAction, instHSMul, SMul.smul]
rw [lift_of]
rfl
theorem of_smul_eq_smul {i : ι} (g : G i) (w : NormalWord d) :
of (φ := φ) i g • w = g • w := by
rw [summand_smul_def, summand_smul_def']
theorem base_smul_eq_smul (h : H) (w : NormalWord d) :
base φ h • w = h • w := by
rw [base_smul_def, base_smul_def']
/-- Induction principle for `NormalWord`, that corresponds closely to inducting on
the underlying list. -/
@[elab_as_elim]
noncomputable def consRecOn {motive : NormalWord d → Sort _} (w : NormalWord d)
(h_empty : motive empty)
(h_cons : ∀ (i : ι) (g : G i) (w : NormalWord d) (hmw : w.fstIdx ≠ some i)
(_hgn : g ∈ d.set i) (hgr : g ∉ (φ i).range) (_hw1 : w.head = 1),
motive w → motive (cons g w hmw hgr))
(h_base : ∀ (h : H) (w : NormalWord d), w.head = 1 → motive w → motive
(base φ h • w)) : motive w := by
rcases w with ⟨w, head, h3⟩
convert h_base head ⟨w, 1, h3⟩ rfl ?_
· simp [base_smul_def]
· induction w using Word.consRecOn with
| h_empty => exact h_empty
| h_cons i g w h1 hg1 ih =>
convert h_cons i g ⟨w, 1, fun _ _ h => h3 _ _ (List.mem_cons_of_mem _ h)⟩
h1 (h3 _ _ (List.mem_cons_self _ _)) ?_ rfl
(ih ?_)
· ext
simp only [Word.cons, Option.mem_def, cons, map_one, mul_one,
(equiv_snd_eq_self_iff_mem (d.compl i) (one_mem _)).2
(h3 _ _ (List.mem_cons_self _ _))]
· apply d.injective i
simp only [cons, equiv_fst_eq_mul_inv, MonoidHom.apply_ofInjective_symm,
map_one, mul_one, mul_right_inv, (equiv_snd_eq_self_iff_mem (d.compl i) (one_mem _)).2
(h3 _ _ (List.mem_cons_self _ _))]
· rwa [← SetLike.mem_coe,
← coe_equiv_snd_eq_one_iff_mem (d.compl i) (d.one_mem _),
(equiv_snd_eq_self_iff_mem (d.compl i) (one_mem _)).2
(h3 _ _ (List.mem_cons_self _ _))]
/-- Take the product of a normal word as an element of the `PushoutI`. We show that this is
bijective, in `NormalWord.equiv`. -/
def prod (w : NormalWord d) : PushoutI φ :=
base φ w.head * ofCoprodI (w.toWord).prod
theorem cons_eq_smul {i : ι} (g : G i)
(w : NormalWord d) (hmw : w.fstIdx ≠ some i)
(hgr : g ∉ (φ i).range) : cons g w hmw hgr = of (φ := φ) i g • w := by
apply ext_smul i
simp only [cons, ne_eq, Word.cons_eq_smul, MonoidHom.apply_ofInjective_symm,
equiv_fst_eq_mul_inv, mul_assoc, map_mul, map_inv, mul_smul, inv_smul_smul, summand_smul_def,
equivPair, rcons, Word.equivPair_symm, Word.rcons_eq_smul, Equiv.coe_fn_mk,
Word.equivPair_tail_eq_inv_smul, Equiv.coe_fn_symm_mk, smul_inv_smul]
@[simp]
theorem prod_summand_smul {i : ι} (g : G i) (w : NormalWord d) :
(g • w).prod = of i g * w.prod := by
simp only [prod, summand_smul_def', equivPair, rcons, Word.equivPair_symm,
Equiv.coe_fn_mk, Equiv.coe_fn_symm_mk, Word.equivPair_smul_same,
Word.equivPair_tail_eq_inv_smul, Word.rcons_eq_smul, ← of_apply_eq_base φ i,
MonoidHom.apply_ofInjective_symm, equiv_fst_eq_mul_inv, mul_assoc, map_mul, map_inv,
Word.prod_smul, ofCoprodI_of, inv_mul_cancel_left, mul_inv_cancel_left]
@[simp]
theorem prod_base_smul (h : H) (w : NormalWord d) :
(h • w).prod = base φ h * w.prod := by
simp only [base_smul_def', prod, map_mul, mul_assoc]
@[simp]
theorem prod_smul (g : PushoutI φ) (w : NormalWord d) :
(g • w).prod = g * w.prod := by
induction g using PushoutI.induction_on generalizing w with
| of i g => rw [of_smul_eq_smul, prod_summand_smul]
| base h => rw [base_smul_eq_smul, prod_base_smul]
| mul x y ihx ihy => rw [mul_smul, ihx, ihy, mul_assoc]
@[simp]
theorem prod_empty : (empty : NormalWord d).prod = 1 := by
simp [prod, empty]
@[simp]
theorem prod_cons {i} (g : G i) (w : NormalWord d) (hmw : w.fstIdx ≠ some i)
(hgr : g ∉ (φ i).range) : (cons g w hmw hgr).prod = of i g * w.prod := by
simp only [prod, cons, Word.prod, List.map, ← of_apply_eq_base φ i, equiv_fst_eq_mul_inv,
mul_assoc, MonoidHom.apply_ofInjective_symm, List.prod_cons, map_mul, map_inv,
ofCoprodI_of, inv_mul_cancel_left]
| Mathlib/GroupTheory/PushoutI.lean | 554 | 560 | theorem prod_smul_empty (w : NormalWord d) : w.prod • empty = w := by |
induction w using consRecOn with
| h_empty => simp
| h_cons i g w _ _ _ _ ih =>
rw [prod_cons, mul_smul, ih, cons_eq_smul]
| h_base h w _ ih =>
rw [prod_smul, mul_smul, ih]
|
/-
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, Yury Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Field.Defs
import Mathlib.Algebra.Order.Group.Instances
import Mathlib.Algebra.Order.Group.MinMax
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.Data.Finset.Preimage
import Mathlib.Order.Interval.Set.Disjoint
import Mathlib.Order.Interval.Set.OrderIso
import Mathlib.Order.ConditionallyCompleteLattice.Basic
import Mathlib.Order.Filter.Bases
#align_import order.filter.at_top_bot from "leanprover-community/mathlib"@"1f0096e6caa61e9c849ec2adbd227e960e9dff58"
/-!
# `Filter.atTop` and `Filter.atBot` filters on preorders, monoids and groups.
In this file we define the filters
* `Filter.atTop`: corresponds to `n → +∞`;
* `Filter.atBot`: corresponds to `n → -∞`.
Then we prove many lemmas like “if `f → +∞`, then `f ± c → +∞`”.
-/
set_option autoImplicit true
variable {ι ι' α β γ : Type*}
open Set
namespace Filter
/-- `atTop` is the filter representing the limit `→ ∞` on an ordered set.
It is generated by the collection of up-sets `{b | a ≤ b}`.
(The preorder need not have a top element for this to be well defined,
and indeed is trivial when a top element exists.) -/
def atTop [Preorder α] : Filter α :=
⨅ a, 𝓟 (Ici a)
#align filter.at_top Filter.atTop
/-- `atBot` is the filter representing the limit `→ -∞` on an ordered set.
It is generated by the collection of down-sets `{b | b ≤ a}`.
(The preorder need not have a bottom element for this to be well defined,
and indeed is trivial when a bottom element exists.) -/
def atBot [Preorder α] : Filter α :=
⨅ a, 𝓟 (Iic a)
#align filter.at_bot Filter.atBot
theorem mem_atTop [Preorder α] (a : α) : { b : α | a ≤ b } ∈ @atTop α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_top Filter.mem_atTop
theorem Ici_mem_atTop [Preorder α] (a : α) : Ici a ∈ (atTop : Filter α) :=
mem_atTop a
#align filter.Ici_mem_at_top Filter.Ici_mem_atTop
theorem Ioi_mem_atTop [Preorder α] [NoMaxOrder α] (x : α) : Ioi x ∈ (atTop : Filter α) :=
let ⟨z, hz⟩ := exists_gt x
mem_of_superset (mem_atTop z) fun _ h => lt_of_lt_of_le hz h
#align filter.Ioi_mem_at_top Filter.Ioi_mem_atTop
theorem mem_atBot [Preorder α] (a : α) : { b : α | b ≤ a } ∈ @atBot α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_bot Filter.mem_atBot
theorem Iic_mem_atBot [Preorder α] (a : α) : Iic a ∈ (atBot : Filter α) :=
mem_atBot a
#align filter.Iic_mem_at_bot Filter.Iic_mem_atBot
theorem Iio_mem_atBot [Preorder α] [NoMinOrder α] (x : α) : Iio x ∈ (atBot : Filter α) :=
let ⟨z, hz⟩ := exists_lt x
mem_of_superset (mem_atBot z) fun _ h => lt_of_le_of_lt h hz
#align filter.Iio_mem_at_bot Filter.Iio_mem_atBot
theorem disjoint_atBot_principal_Ioi [Preorder α] (x : α) : Disjoint atBot (𝓟 (Ioi x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl) (Iic_mem_atBot x) (mem_principal_self _)
#align filter.disjoint_at_bot_principal_Ioi Filter.disjoint_atBot_principal_Ioi
theorem disjoint_atTop_principal_Iio [Preorder α] (x : α) : Disjoint atTop (𝓟 (Iio x)) :=
@disjoint_atBot_principal_Ioi αᵒᵈ _ _
#align filter.disjoint_at_top_principal_Iio Filter.disjoint_atTop_principal_Iio
theorem disjoint_atTop_principal_Iic [Preorder α] [NoMaxOrder α] (x : α) :
Disjoint atTop (𝓟 (Iic x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl).symm (Ioi_mem_atTop x)
(mem_principal_self _)
#align filter.disjoint_at_top_principal_Iic Filter.disjoint_atTop_principal_Iic
theorem disjoint_atBot_principal_Ici [Preorder α] [NoMinOrder α] (x : α) :
Disjoint atBot (𝓟 (Ici x)) :=
@disjoint_atTop_principal_Iic αᵒᵈ _ _ _
#align filter.disjoint_at_bot_principal_Ici Filter.disjoint_atBot_principal_Ici
theorem disjoint_pure_atTop [Preorder α] [NoMaxOrder α] (x : α) : Disjoint (pure x) atTop :=
Disjoint.symm <| (disjoint_atTop_principal_Iic x).mono_right <| le_principal_iff.2 <|
mem_pure.2 right_mem_Iic
#align filter.disjoint_pure_at_top Filter.disjoint_pure_atTop
theorem disjoint_pure_atBot [Preorder α] [NoMinOrder α] (x : α) : Disjoint (pure x) atBot :=
@disjoint_pure_atTop αᵒᵈ _ _ _
#align filter.disjoint_pure_at_bot Filter.disjoint_pure_atBot
theorem not_tendsto_const_atTop [Preorder α] [NoMaxOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atTop :=
tendsto_const_pure.not_tendsto (disjoint_pure_atTop x)
#align filter.not_tendsto_const_at_top Filter.not_tendsto_const_atTop
theorem not_tendsto_const_atBot [Preorder α] [NoMinOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atBot :=
tendsto_const_pure.not_tendsto (disjoint_pure_atBot x)
#align filter.not_tendsto_const_at_bot Filter.not_tendsto_const_atBot
theorem disjoint_atBot_atTop [PartialOrder α] [Nontrivial α] :
Disjoint (atBot : Filter α) atTop := by
rcases exists_pair_ne α with ⟨x, y, hne⟩
by_cases hle : x ≤ y
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot x) (Ici_mem_atTop y)
exact Iic_disjoint_Ici.2 (hle.lt_of_ne hne).not_le
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot y) (Ici_mem_atTop x)
exact Iic_disjoint_Ici.2 hle
#align filter.disjoint_at_bot_at_top Filter.disjoint_atBot_atTop
theorem disjoint_atTop_atBot [PartialOrder α] [Nontrivial α] : Disjoint (atTop : Filter α) atBot :=
disjoint_atBot_atTop.symm
#align filter.disjoint_at_top_at_bot Filter.disjoint_atTop_atBot
theorem hasAntitoneBasis_atTop [Nonempty α] [Preorder α] [IsDirected α (· ≤ ·)] :
(@atTop α _).HasAntitoneBasis Ici :=
.iInf_principal fun _ _ ↦ Ici_subset_Ici.2
theorem atTop_basis [Nonempty α] [SemilatticeSup α] : (@atTop α _).HasBasis (fun _ => True) Ici :=
hasAntitoneBasis_atTop.1
#align filter.at_top_basis Filter.atTop_basis
theorem atTop_eq_generate_Ici [SemilatticeSup α] : atTop = generate (range (Ici (α := α))) := by
rcases isEmpty_or_nonempty α with hα|hα
· simp only [eq_iff_true_of_subsingleton]
· simp [(atTop_basis (α := α)).eq_generate, range]
theorem atTop_basis' [SemilatticeSup α] (a : α) : (@atTop α _).HasBasis (fun x => a ≤ x) Ici :=
⟨fun _ =>
(@atTop_basis α ⟨a⟩ _).mem_iff.trans
⟨fun ⟨x, _, hx⟩ => ⟨x ⊔ a, le_sup_right, fun _y hy => hx (le_trans le_sup_left hy)⟩,
fun ⟨x, _, hx⟩ => ⟨x, trivial, hx⟩⟩⟩
#align filter.at_top_basis' Filter.atTop_basis'
theorem atBot_basis [Nonempty α] [SemilatticeInf α] : (@atBot α _).HasBasis (fun _ => True) Iic :=
@atTop_basis αᵒᵈ _ _
#align filter.at_bot_basis Filter.atBot_basis
theorem atBot_basis' [SemilatticeInf α] (a : α) : (@atBot α _).HasBasis (fun x => x ≤ a) Iic :=
@atTop_basis' αᵒᵈ _ _
#align filter.at_bot_basis' Filter.atBot_basis'
@[instance]
theorem atTop_neBot [Nonempty α] [SemilatticeSup α] : NeBot (atTop : Filter α) :=
atTop_basis.neBot_iff.2 fun _ => nonempty_Ici
#align filter.at_top_ne_bot Filter.atTop_neBot
@[instance]
theorem atBot_neBot [Nonempty α] [SemilatticeInf α] : NeBot (atBot : Filter α) :=
@atTop_neBot αᵒᵈ _ _
#align filter.at_bot_ne_bot Filter.atBot_neBot
@[simp]
theorem mem_atTop_sets [Nonempty α] [SemilatticeSup α] {s : Set α} :
s ∈ (atTop : Filter α) ↔ ∃ a : α, ∀ b ≥ a, b ∈ s :=
atTop_basis.mem_iff.trans <| exists_congr fun _ => true_and_iff _
#align filter.mem_at_top_sets Filter.mem_atTop_sets
@[simp]
theorem mem_atBot_sets [Nonempty α] [SemilatticeInf α] {s : Set α} :
s ∈ (atBot : Filter α) ↔ ∃ a : α, ∀ b ≤ a, b ∈ s :=
@mem_atTop_sets αᵒᵈ _ _ _
#align filter.mem_at_bot_sets Filter.mem_atBot_sets
@[simp]
theorem eventually_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ b ≥ a, p b :=
mem_atTop_sets
#align filter.eventually_at_top Filter.eventually_atTop
@[simp]
theorem eventually_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ b ≤ a, p b :=
mem_atBot_sets
#align filter.eventually_at_bot Filter.eventually_atBot
theorem eventually_ge_atTop [Preorder α] (a : α) : ∀ᶠ x in atTop, a ≤ x :=
mem_atTop a
#align filter.eventually_ge_at_top Filter.eventually_ge_atTop
theorem eventually_le_atBot [Preorder α] (a : α) : ∀ᶠ x in atBot, x ≤ a :=
mem_atBot a
#align filter.eventually_le_at_bot Filter.eventually_le_atBot
theorem eventually_gt_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, a < x :=
Ioi_mem_atTop a
#align filter.eventually_gt_at_top Filter.eventually_gt_atTop
theorem eventually_ne_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, x ≠ a :=
(eventually_gt_atTop a).mono fun _ => ne_of_gt
#align filter.eventually_ne_at_top Filter.eventually_ne_atTop
protected theorem Tendsto.eventually_gt_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c < f x :=
hf.eventually (eventually_gt_atTop c)
#align filter.tendsto.eventually_gt_at_top Filter.Tendsto.eventually_gt_atTop
protected theorem Tendsto.eventually_ge_atTop [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c ≤ f x :=
hf.eventually (eventually_ge_atTop c)
#align filter.tendsto.eventually_ge_at_top Filter.Tendsto.eventually_ge_atTop
protected theorem Tendsto.eventually_ne_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atTop c)
#align filter.tendsto.eventually_ne_at_top Filter.Tendsto.eventually_ne_atTop
protected theorem Tendsto.eventually_ne_atTop' [Preorder β] [NoMaxOrder β] {f : α → β}
{l : Filter α} (hf : Tendsto f l atTop) (c : α) : ∀ᶠ x in l, x ≠ c :=
(hf.eventually_ne_atTop (f c)).mono fun _ => ne_of_apply_ne f
#align filter.tendsto.eventually_ne_at_top' Filter.Tendsto.eventually_ne_atTop'
theorem eventually_lt_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x < a :=
Iio_mem_atBot a
#align filter.eventually_lt_at_bot Filter.eventually_lt_atBot
theorem eventually_ne_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x ≠ a :=
(eventually_lt_atBot a).mono fun _ => ne_of_lt
#align filter.eventually_ne_at_bot Filter.eventually_ne_atBot
protected theorem Tendsto.eventually_lt_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x < c :=
hf.eventually (eventually_lt_atBot c)
#align filter.tendsto.eventually_lt_at_bot Filter.Tendsto.eventually_lt_atBot
protected theorem Tendsto.eventually_le_atBot [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≤ c :=
hf.eventually (eventually_le_atBot c)
#align filter.tendsto.eventually_le_at_bot Filter.Tendsto.eventually_le_atBot
protected theorem Tendsto.eventually_ne_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atBot c)
#align filter.tendsto.eventually_ne_at_bot Filter.Tendsto.eventually_ne_atBot
theorem eventually_forall_ge_atTop [Preorder α] {p : α → Prop} :
(∀ᶠ x in atTop, ∀ y, x ≤ y → p y) ↔ ∀ᶠ x in atTop, p x := by
refine ⟨fun h ↦ h.mono fun x hx ↦ hx x le_rfl, fun h ↦ ?_⟩
rcases (hasBasis_iInf_principal_finite _).eventually_iff.1 h with ⟨S, hSf, hS⟩
refine mem_iInf_of_iInter hSf (V := fun x ↦ Ici x.1) (fun _ ↦ Subset.rfl) fun x hx y hy ↦ ?_
simp only [mem_iInter] at hS hx
exact hS fun z hz ↦ le_trans (hx ⟨z, hz⟩) hy
theorem eventually_forall_le_atBot [Preorder α] {p : α → Prop} :
(∀ᶠ x in atBot, ∀ y, y ≤ x → p y) ↔ ∀ᶠ x in atBot, p x :=
eventually_forall_ge_atTop (α := αᵒᵈ)
theorem Tendsto.eventually_forall_ge_atTop {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atTop) (h_evtl : ∀ᶠ x in atTop, p x) :
∀ᶠ x in l, ∀ y, f x ≤ y → p y := by
rw [← Filter.eventually_forall_ge_atTop] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem Tendsto.eventually_forall_le_atBot {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atBot) (h_evtl : ∀ᶠ x in atBot, p x) :
∀ᶠ x in l, ∀ y, y ≤ f x → p y := by
rw [← Filter.eventually_forall_le_atBot] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem atTop_basis_Ioi [Nonempty α] [SemilatticeSup α] [NoMaxOrder α] :
(@atTop α _).HasBasis (fun _ => True) Ioi :=
atTop_basis.to_hasBasis (fun a ha => ⟨a, ha, Ioi_subset_Ici_self⟩) fun a ha =>
(exists_gt a).imp fun _b hb => ⟨ha, Ici_subset_Ioi.2 hb⟩
#align filter.at_top_basis_Ioi Filter.atTop_basis_Ioi
lemma atTop_basis_Ioi' [SemilatticeSup α] [NoMaxOrder α] (a : α) : atTop.HasBasis (a < ·) Ioi :=
have : Nonempty α := ⟨a⟩
atTop_basis_Ioi.to_hasBasis (fun b _ ↦
let ⟨c, hc⟩ := exists_gt (a ⊔ b)
⟨c, le_sup_left.trans_lt hc, Ioi_subset_Ioi <| le_sup_right.trans hc.le⟩) fun b _ ↦
⟨b, trivial, Subset.rfl⟩
theorem atTop_countable_basis [Nonempty α] [SemilatticeSup α] [Countable α] :
HasCountableBasis (atTop : Filter α) (fun _ => True) Ici :=
{ atTop_basis with countable := to_countable _ }
#align filter.at_top_countable_basis Filter.atTop_countable_basis
theorem atBot_countable_basis [Nonempty α] [SemilatticeInf α] [Countable α] :
HasCountableBasis (atBot : Filter α) (fun _ => True) Iic :=
{ atBot_basis with countable := to_countable _ }
#align filter.at_bot_countable_basis Filter.atBot_countable_basis
instance (priority := 200) atTop.isCountablyGenerated [Preorder α] [Countable α] :
(atTop : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_top.is_countably_generated Filter.atTop.isCountablyGenerated
instance (priority := 200) atBot.isCountablyGenerated [Preorder α] [Countable α] :
(atBot : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_bot.is_countably_generated Filter.atBot.isCountablyGenerated
theorem _root_.IsTop.atTop_eq [Preorder α] {a : α} (ha : IsTop a) : atTop = 𝓟 (Ici a) :=
(iInf_le _ _).antisymm <| le_iInf fun b ↦ principal_mono.2 <| Ici_subset_Ici.2 <| ha b
theorem _root_.IsBot.atBot_eq [Preorder α] {a : α} (ha : IsBot a) : atBot = 𝓟 (Iic a) :=
ha.toDual.atTop_eq
theorem OrderTop.atTop_eq (α) [PartialOrder α] [OrderTop α] : (atTop : Filter α) = pure ⊤ := by
rw [isTop_top.atTop_eq, Ici_top, principal_singleton]
#align filter.order_top.at_top_eq Filter.OrderTop.atTop_eq
theorem OrderBot.atBot_eq (α) [PartialOrder α] [OrderBot α] : (atBot : Filter α) = pure ⊥ :=
@OrderTop.atTop_eq αᵒᵈ _ _
#align filter.order_bot.at_bot_eq Filter.OrderBot.atBot_eq
@[nontriviality]
theorem Subsingleton.atTop_eq (α) [Subsingleton α] [Preorder α] : (atTop : Filter α) = ⊤ := by
refine top_unique fun s hs x => ?_
rw [atTop, ciInf_subsingleton x, mem_principal] at hs
exact hs left_mem_Ici
#align filter.subsingleton.at_top_eq Filter.Subsingleton.atTop_eq
@[nontriviality]
theorem Subsingleton.atBot_eq (α) [Subsingleton α] [Preorder α] : (atBot : Filter α) = ⊤ :=
@Subsingleton.atTop_eq αᵒᵈ _ _
#align filter.subsingleton.at_bot_eq Filter.Subsingleton.atBot_eq
theorem tendsto_atTop_pure [PartialOrder α] [OrderTop α] (f : α → β) :
Tendsto f atTop (pure <| f ⊤) :=
(OrderTop.atTop_eq α).symm ▸ tendsto_pure_pure _ _
#align filter.tendsto_at_top_pure Filter.tendsto_atTop_pure
theorem tendsto_atBot_pure [PartialOrder α] [OrderBot α] (f : α → β) :
Tendsto f atBot (pure <| f ⊥) :=
@tendsto_atTop_pure αᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_pure Filter.tendsto_atBot_pure
theorem Eventually.exists_forall_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atTop, p x) : ∃ a, ∀ b ≥ a, p b :=
eventually_atTop.mp h
#align filter.eventually.exists_forall_of_at_top Filter.Eventually.exists_forall_of_atTop
theorem Eventually.exists_forall_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atBot, p x) : ∃ a, ∀ b ≤ a, p b :=
eventually_atBot.mp h
#align filter.eventually.exists_forall_of_at_bot Filter.Eventually.exists_forall_of_atBot
lemma exists_eventually_atTop [SemilatticeSup α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atTop, r a b) ↔ ∀ᶠ a₀ in atTop, ∃ b, ∀ a ≥ a₀, r a b := by
simp_rw [eventually_atTop, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_ge_iff <| Monotone.exists fun _ _ _ hb H n hn ↦
H n (hb.trans hn)
lemma exists_eventually_atBot [SemilatticeInf α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atBot, r a b) ↔ ∀ᶠ a₀ in atBot, ∃ b, ∀ a ≤ a₀, r a b := by
simp_rw [eventually_atBot, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_le_iff <| Antitone.exists fun _ _ _ hb H n hn ↦
H n (hn.trans hb)
theorem frequently_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b ≥ a, p b :=
atTop_basis.frequently_iff.trans <| by simp
#align filter.frequently_at_top Filter.frequently_atTop
theorem frequently_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b ≤ a, p b :=
@frequently_atTop αᵒᵈ _ _ _
#align filter.frequently_at_bot Filter.frequently_atBot
theorem frequently_atTop' [SemilatticeSup α] [Nonempty α] [NoMaxOrder α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b > a, p b :=
atTop_basis_Ioi.frequently_iff.trans <| by simp
#align filter.frequently_at_top' Filter.frequently_atTop'
theorem frequently_atBot' [SemilatticeInf α] [Nonempty α] [NoMinOrder α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b < a, p b :=
@frequently_atTop' αᵒᵈ _ _ _ _
#align filter.frequently_at_bot' Filter.frequently_atBot'
theorem Frequently.forall_exists_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atTop, p x) : ∀ a, ∃ b ≥ a, p b :=
frequently_atTop.mp h
#align filter.frequently.forall_exists_of_at_top Filter.Frequently.forall_exists_of_atTop
theorem Frequently.forall_exists_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atBot, p x) : ∀ a, ∃ b ≤ a, p b :=
frequently_atBot.mp h
#align filter.frequently.forall_exists_of_at_bot Filter.Frequently.forall_exists_of_atBot
theorem map_atTop_eq [Nonempty α] [SemilatticeSup α] {f : α → β} :
atTop.map f = ⨅ a, 𝓟 (f '' { a' | a ≤ a' }) :=
(atTop_basis.map f).eq_iInf
#align filter.map_at_top_eq Filter.map_atTop_eq
theorem map_atBot_eq [Nonempty α] [SemilatticeInf α] {f : α → β} :
atBot.map f = ⨅ a, 𝓟 (f '' { a' | a' ≤ a }) :=
@map_atTop_eq αᵒᵈ _ _ _ _
#align filter.map_at_bot_eq Filter.map_atBot_eq
theorem tendsto_atTop [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atTop ↔ ∀ b, ∀ᶠ a in f, b ≤ m a := by
simp only [atTop, tendsto_iInf, tendsto_principal, mem_Ici]
#align filter.tendsto_at_top Filter.tendsto_atTop
theorem tendsto_atBot [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atBot ↔ ∀ b, ∀ᶠ a in f, m a ≤ b :=
@tendsto_atTop α βᵒᵈ _ m f
#align filter.tendsto_at_bot Filter.tendsto_atBot
theorem tendsto_atTop_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂)
(h₁ : Tendsto f₁ l atTop) : Tendsto f₂ l atTop :=
tendsto_atTop.2 fun b => by filter_upwards [tendsto_atTop.1 h₁ b, h] with x using le_trans
#align filter.tendsto_at_top_mono' Filter.tendsto_atTop_mono'
theorem tendsto_atBot_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂) :
Tendsto f₂ l atBot → Tendsto f₁ l atBot :=
@tendsto_atTop_mono' _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono' Filter.tendsto_atBot_mono'
theorem tendsto_atTop_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto f l atTop → Tendsto g l atTop :=
tendsto_atTop_mono' l <| eventually_of_forall h
#align filter.tendsto_at_top_mono Filter.tendsto_atTop_mono
theorem tendsto_atBot_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto g l atBot → Tendsto f l atBot :=
@tendsto_atTop_mono _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono Filter.tendsto_atBot_mono
lemma atTop_eq_generate_of_forall_exists_le [LinearOrder α] {s : Set α} (hs : ∀ x, ∃ y ∈ s, x ≤ y) :
(atTop : Filter α) = generate (Ici '' s) := by
rw [atTop_eq_generate_Ici]
apply le_antisymm
· rw [le_generate_iff]
rintro - ⟨y, -, rfl⟩
exact mem_generate_of_mem ⟨y, rfl⟩
· rw [le_generate_iff]
rintro - ⟨x, -, -, rfl⟩
rcases hs x with ⟨y, ys, hy⟩
have A : Ici y ∈ generate (Ici '' s) := mem_generate_of_mem (mem_image_of_mem _ ys)
have B : Ici y ⊆ Ici x := Ici_subset_Ici.2 hy
exact sets_of_superset (generate (Ici '' s)) A B
lemma atTop_eq_generate_of_not_bddAbove [LinearOrder α] {s : Set α} (hs : ¬ BddAbove s) :
(atTop : Filter α) = generate (Ici '' s) := by
refine atTop_eq_generate_of_forall_exists_le fun x ↦ ?_
obtain ⟨y, hy, hy'⟩ := not_bddAbove_iff.mp hs x
exact ⟨y, hy, hy'.le⟩
end Filter
namespace OrderIso
open Filter
variable [Preorder α] [Preorder β]
@[simp]
theorem comap_atTop (e : α ≃o β) : comap e atTop = atTop := by
simp [atTop, ← e.surjective.iInf_comp]
#align order_iso.comap_at_top OrderIso.comap_atTop
@[simp]
theorem comap_atBot (e : α ≃o β) : comap e atBot = atBot :=
e.dual.comap_atTop
#align order_iso.comap_at_bot OrderIso.comap_atBot
@[simp]
theorem map_atTop (e : α ≃o β) : map (e : α → β) atTop = atTop := by
rw [← e.comap_atTop, map_comap_of_surjective e.surjective]
#align order_iso.map_at_top OrderIso.map_atTop
@[simp]
theorem map_atBot (e : α ≃o β) : map (e : α → β) atBot = atBot :=
e.dual.map_atTop
#align order_iso.map_at_bot OrderIso.map_atBot
theorem tendsto_atTop (e : α ≃o β) : Tendsto e atTop atTop :=
e.map_atTop.le
#align order_iso.tendsto_at_top OrderIso.tendsto_atTop
theorem tendsto_atBot (e : α ≃o β) : Tendsto e atBot atBot :=
e.map_atBot.le
#align order_iso.tendsto_at_bot OrderIso.tendsto_atBot
@[simp]
theorem tendsto_atTop_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atTop ↔ Tendsto f l atTop := by
rw [← e.comap_atTop, tendsto_comap_iff, Function.comp_def]
#align order_iso.tendsto_at_top_iff OrderIso.tendsto_atTop_iff
@[simp]
theorem tendsto_atBot_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atBot ↔ Tendsto f l atBot :=
e.dual.tendsto_atTop_iff
#align order_iso.tendsto_at_bot_iff OrderIso.tendsto_atBot_iff
end OrderIso
namespace Filter
/-!
### Sequences
-/
theorem inf_map_atTop_neBot_iff [SemilatticeSup α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atTop) ↔ ∀ U ∈ F, ∀ N, ∃ n ≥ N, u n ∈ U := by
simp_rw [inf_neBot_iff_frequently_left, frequently_map, frequently_atTop]; rfl
#align filter.inf_map_at_top_ne_bot_iff Filter.inf_map_atTop_neBot_iff
theorem inf_map_atBot_neBot_iff [SemilatticeInf α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atBot) ↔ ∀ U ∈ F, ∀ N, ∃ n ≤ N, u n ∈ U :=
@inf_map_atTop_neBot_iff αᵒᵈ _ _ _ _ _
#align filter.inf_map_at_bot_ne_bot_iff Filter.inf_map_atBot_neBot_iff
theorem extraction_of_frequently_atTop' {P : ℕ → Prop} (h : ∀ N, ∃ n > N, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
choose u hu hu' using h
refine ⟨fun n => u^[n + 1] 0, strictMono_nat_of_lt_succ fun n => ?_, fun n => ?_⟩
· exact Trans.trans (hu _) (Function.iterate_succ_apply' _ _ _).symm
· simpa only [Function.iterate_succ_apply'] using hu' _
#align filter.extraction_of_frequently_at_top' Filter.extraction_of_frequently_atTop'
theorem extraction_of_frequently_atTop {P : ℕ → Prop} (h : ∃ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
rw [frequently_atTop'] at h
exact extraction_of_frequently_atTop' h
#align filter.extraction_of_frequently_at_top Filter.extraction_of_frequently_atTop
theorem extraction_of_eventually_atTop {P : ℕ → Prop} (h : ∀ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) :=
extraction_of_frequently_atTop h.frequently
#align filter.extraction_of_eventually_at_top Filter.extraction_of_eventually_atTop
theorem extraction_forall_of_frequently {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) := by
simp only [frequently_atTop'] at h
choose u hu hu' using h
use (fun n => Nat.recOn n (u 0 0) fun n v => u (n + 1) v : ℕ → ℕ)
constructor
· apply strictMono_nat_of_lt_succ
intro n
apply hu
· intro n
cases n <;> simp [hu']
#align filter.extraction_forall_of_frequently Filter.extraction_forall_of_frequently
theorem extraction_forall_of_eventually {P : ℕ → ℕ → Prop} (h : ∀ n, ∀ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_frequently fun n => (h n).frequently
#align filter.extraction_forall_of_eventually Filter.extraction_forall_of_eventually
theorem extraction_forall_of_eventually' {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ N, ∀ k ≥ N, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_eventually (by simp [eventually_atTop, h])
#align filter.extraction_forall_of_eventually' Filter.extraction_forall_of_eventually'
theorem Eventually.atTop_of_arithmetic {p : ℕ → Prop} {n : ℕ} (hn : n ≠ 0)
(hp : ∀ k < n, ∀ᶠ a in atTop, p (n * a + k)) : ∀ᶠ a in atTop, p a := by
simp only [eventually_atTop] at hp ⊢
choose! N hN using hp
refine ⟨(Finset.range n).sup (n * N ·), fun b hb => ?_⟩
rw [← Nat.div_add_mod b n]
have hlt := Nat.mod_lt b hn.bot_lt
refine hN _ hlt _ ?_
rw [ge_iff_le, Nat.le_div_iff_mul_le hn.bot_lt, mul_comm]
exact (Finset.le_sup (f := (n * N ·)) (Finset.mem_range.2 hlt)).trans hb
theorem exists_le_of_tendsto_atTop [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b ≤ u a' := by
have : Nonempty α := ⟨a⟩
have : ∀ᶠ x in atTop, a ≤ x ∧ b ≤ u x :=
(eventually_ge_atTop a).and (h.eventually <| eventually_ge_atTop b)
exact this.exists
#align filter.exists_le_of_tendsto_at_top Filter.exists_le_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_le_of_tendsto_atBot [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' ≤ b :=
@exists_le_of_tendsto_atTop _ βᵒᵈ _ _ _ h
#align filter.exists_le_of_tendsto_at_bot Filter.exists_le_of_tendsto_atBot
theorem exists_lt_of_tendsto_atTop [SemilatticeSup α] [Preorder β] [NoMaxOrder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b < u a' := by
cases' exists_gt b with b' hb'
rcases exists_le_of_tendsto_atTop h a b' with ⟨a', ha', ha''⟩
exact ⟨a', ha', lt_of_lt_of_le hb' ha''⟩
#align filter.exists_lt_of_tendsto_at_top Filter.exists_lt_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_lt_of_tendsto_atBot [SemilatticeSup α] [Preorder β] [NoMinOrder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' < b :=
@exists_lt_of_tendsto_atTop _ βᵒᵈ _ _ _ _ h
#align filter.exists_lt_of_tendsto_at_bot Filter.exists_lt_of_tendsto_atBot
/-- If `u` is a sequence which is unbounded above,
then after any point, it reaches a value strictly greater than all previous values.
-/
theorem high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β} (hu : Tendsto u atTop atTop) :
∀ N, ∃ n ≥ N, ∀ k < n, u k < u n := by
intro N
obtain ⟨k : ℕ, - : k ≤ N, hku : ∀ l ≤ N, u l ≤ u k⟩ : ∃ k ≤ N, ∀ l ≤ N, u l ≤ u k :=
exists_max_image _ u (finite_le_nat N) ⟨N, le_refl N⟩
have ex : ∃ n ≥ N, u k < u n := exists_lt_of_tendsto_atTop hu _ _
obtain ⟨n : ℕ, hnN : n ≥ N, hnk : u k < u n, hn_min : ∀ m, m < n → N ≤ m → u m ≤ u k⟩ :
∃ n ≥ N, u k < u n ∧ ∀ m, m < n → N ≤ m → u m ≤ u k := by
rcases Nat.findX ex with ⟨n, ⟨hnN, hnk⟩, hn_min⟩
push_neg at hn_min
exact ⟨n, hnN, hnk, hn_min⟩
use n, hnN
rintro (l : ℕ) (hl : l < n)
have hlk : u l ≤ u k := by
cases' (le_total l N : l ≤ N ∨ N ≤ l) with H H
· exact hku l H
· exact hn_min l hl H
calc
u l ≤ u k := hlk
_ < u n := hnk
#align filter.high_scores Filter.high_scores
-- see Note [nolint_ge]
/-- If `u` is a sequence which is unbounded below,
then after any point, it reaches a value strictly smaller than all previous values.
-/
-- @[nolint ge_or_gt] Porting note: restore attribute
theorem low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β} (hu : Tendsto u atTop atBot) :
∀ N, ∃ n ≥ N, ∀ k < n, u n < u k :=
@high_scores βᵒᵈ _ _ _ hu
#align filter.low_scores Filter.low_scores
/-- If `u` is a sequence which is unbounded above,
then it `Frequently` reaches a value strictly greater than all previous values.
-/
theorem frequently_high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ᶠ n in atTop, ∀ k < n, u k < u n := by
simpa [frequently_atTop] using high_scores hu
#align filter.frequently_high_scores Filter.frequently_high_scores
/-- If `u` is a sequence which is unbounded below,
then it `Frequently` reaches a value strictly smaller than all previous values.
-/
theorem frequently_low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atBot) : ∃ᶠ n in atTop, ∀ k < n, u n < u k :=
@frequently_high_scores βᵒᵈ _ _ _ hu
#align filter.frequently_low_scores Filter.frequently_low_scores
theorem strictMono_subseq_of_tendsto_atTop {β : Type*} [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
let ⟨φ, h, h'⟩ := extraction_of_frequently_atTop (frequently_high_scores hu)
⟨φ, h, fun _ m hnm => h' m _ (h hnm)⟩
#align filter.strict_mono_subseq_of_tendsto_at_top Filter.strictMono_subseq_of_tendsto_atTop
theorem strictMono_subseq_of_id_le {u : ℕ → ℕ} (hu : ∀ n, n ≤ u n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
strictMono_subseq_of_tendsto_atTop (tendsto_atTop_mono hu tendsto_id)
#align filter.strict_mono_subseq_of_id_le Filter.strictMono_subseq_of_id_le
theorem _root_.StrictMono.tendsto_atTop {φ : ℕ → ℕ} (h : StrictMono φ) : Tendsto φ atTop atTop :=
tendsto_atTop_mono h.id_le tendsto_id
#align strict_mono.tendsto_at_top StrictMono.tendsto_atTop
section OrderedAddCommMonoid
variable [OrderedAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_add_nonneg_left' (hf : ∀ᶠ x in l, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (hf.mono fun _ => le_add_of_nonneg_left) hg
#align filter.tendsto_at_top_add_nonneg_left' Filter.tendsto_atTop_add_nonneg_left'
theorem tendsto_atBot_add_nonpos_left' (hf : ∀ᶠ x in l, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left' Filter.tendsto_atBot_add_nonpos_left'
theorem tendsto_atTop_add_nonneg_left (hf : ∀ x, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (eventually_of_forall hf) hg
#align filter.tendsto_at_top_add_nonneg_left Filter.tendsto_atTop_add_nonneg_left
theorem tendsto_atBot_add_nonpos_left (hf : ∀ x, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left Filter.tendsto_atBot_add_nonpos_left
theorem tendsto_atTop_add_nonneg_right' (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (monotone_mem (fun _ => le_add_of_nonneg_right) hg) hf
#align filter.tendsto_at_top_add_nonneg_right' Filter.tendsto_atTop_add_nonneg_right'
theorem tendsto_atBot_add_nonpos_right' (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right' Filter.tendsto_atBot_add_nonpos_right'
theorem tendsto_atTop_add_nonneg_right (hf : Tendsto f l atTop) (hg : ∀ x, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_right' hf (eventually_of_forall hg)
#align filter.tendsto_at_top_add_nonneg_right Filter.tendsto_atTop_add_nonneg_right
theorem tendsto_atBot_add_nonpos_right (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right Filter.tendsto_atBot_add_nonpos_right
theorem tendsto_atTop_add (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (tendsto_atTop.mp hf 0) hg
#align filter.tendsto_at_top_add Filter.tendsto_atTop_add
theorem tendsto_atBot_add (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add Filter.tendsto_atBot_add
theorem Tendsto.nsmul_atTop (hf : Tendsto f l atTop) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atTop :=
tendsto_atTop.2 fun y =>
(tendsto_atTop.1 hf y).mp <|
(tendsto_atTop.1 hf 0).mono fun x h₀ hy =>
calc
y ≤ f x := hy
_ = 1 • f x := (one_nsmul _).symm
_ ≤ n • f x := nsmul_le_nsmul_left h₀ hn
#align filter.tendsto.nsmul_at_top Filter.Tendsto.nsmul_atTop
theorem Tendsto.nsmul_atBot (hf : Tendsto f l atBot) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atBot :=
@Tendsto.nsmul_atTop α βᵒᵈ _ l f hf n hn
#align filter.tendsto.nsmul_at_bot Filter.Tendsto.nsmul_atBot
#noalign filter.tendsto_bit0_at_top
#noalign filter.tendsto_bit0_at_bot
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [OrderedCancelAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_top_of_add_const_left Filter.tendsto_atTop_of_add_const_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_bot_of_add_const_left Filter.tendsto_atBot_of_add_const_left
theorem tendsto_atTop_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_top_of_add_const_right Filter.tendsto_atTop_of_add_const_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_bot_of_add_const_right Filter.tendsto_atBot_of_add_const_right
theorem tendsto_atTop_of_add_bdd_above_left' (C) (hC : ∀ᶠ x in l, f x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto g l atTop :=
tendsto_atTop_of_add_const_left C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_left' Filter.tendsto_atTop_of_add_bdd_above_left'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left' (C) (hC : ∀ᶠ x in l, C ≤ f x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto g l atBot :=
tendsto_atBot_of_add_const_left C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_left' Filter.tendsto_atBot_of_add_bdd_below_left'
theorem tendsto_atTop_of_add_bdd_above_left (C) (hC : ∀ x, f x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto g l atTop :=
tendsto_atTop_of_add_bdd_above_left' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_left Filter.tendsto_atTop_of_add_bdd_above_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left (C) (hC : ∀ x, C ≤ f x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto g l atBot :=
tendsto_atBot_of_add_bdd_below_left' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_left Filter.tendsto_atBot_of_add_bdd_below_left
theorem tendsto_atTop_of_add_bdd_above_right' (C) (hC : ∀ᶠ x in l, g x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto f l atTop :=
tendsto_atTop_of_add_const_right C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_right' Filter.tendsto_atTop_of_add_bdd_above_right'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right' (C) (hC : ∀ᶠ x in l, C ≤ g x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto f l atBot :=
tendsto_atBot_of_add_const_right C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_right' Filter.tendsto_atBot_of_add_bdd_below_right'
theorem tendsto_atTop_of_add_bdd_above_right (C) (hC : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto f l atTop :=
tendsto_atTop_of_add_bdd_above_right' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_right Filter.tendsto_atTop_of_add_bdd_above_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right (C) (hC : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto f l atBot :=
tendsto_atBot_of_add_bdd_below_right' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_right Filter.tendsto_atBot_of_add_bdd_below_right
end OrderedCancelAddCommMonoid
section OrderedGroup
variable [OrderedAddCommGroup β] (l : Filter α) {f g : α → β}
theorem tendsto_atTop_add_left_of_le' (C : β) (hf : ∀ᶠ x in l, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_left' _ _ _ l (fun x => -f x) (fun x => f x + g x) (-C) (by simpa)
(by simpa)
#align filter.tendsto_at_top_add_left_of_le' Filter.tendsto_atTop_add_left_of_le'
theorem tendsto_atBot_add_left_of_ge' (C : β) (hf : ∀ᶠ x in l, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge' Filter.tendsto_atBot_add_left_of_ge'
theorem tendsto_atTop_add_left_of_le (C : β) (hf : ∀ x, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' hf) hg
#align filter.tendsto_at_top_add_left_of_le Filter.tendsto_atTop_add_left_of_le
theorem tendsto_atBot_add_left_of_ge (C : β) (hf : ∀ x, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge Filter.tendsto_atBot_add_left_of_ge
theorem tendsto_atTop_add_right_of_le' (C : β) (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_right' _ _ _ l (fun x => f x + g x) (fun x => -g x) (-C)
(by simp [hg]) (by simp [hf])
#align filter.tendsto_at_top_add_right_of_le' Filter.tendsto_atTop_add_right_of_le'
theorem tendsto_atBot_add_right_of_ge' (C : β) (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge' Filter.tendsto_atBot_add_right_of_ge'
theorem tendsto_atTop_add_right_of_le (C : β) (hf : Tendsto f l atTop) (hg : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' hg)
#align filter.tendsto_at_top_add_right_of_le Filter.tendsto_atTop_add_right_of_le
theorem tendsto_atBot_add_right_of_ge (C : β) (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge Filter.tendsto_atBot_add_right_of_ge
theorem tendsto_atTop_add_const_left (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => C + f x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' fun _ => le_refl C) hf
#align filter.tendsto_at_top_add_const_left Filter.tendsto_atTop_add_const_left
theorem tendsto_atBot_add_const_left (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => C + f x) l atBot :=
@tendsto_atTop_add_const_left _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_left Filter.tendsto_atBot_add_const_left
theorem tendsto_atTop_add_const_right (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x + C) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' fun _ => le_refl C)
#align filter.tendsto_at_top_add_const_right Filter.tendsto_atTop_add_const_right
theorem tendsto_atBot_add_const_right (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x + C) l atBot :=
@tendsto_atTop_add_const_right _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_right Filter.tendsto_atBot_add_const_right
theorem map_neg_atBot : map (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).map_atBot
#align filter.map_neg_at_bot Filter.map_neg_atBot
theorem map_neg_atTop : map (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).map_atTop
#align filter.map_neg_at_top Filter.map_neg_atTop
theorem comap_neg_atBot : comap (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).comap_atTop
#align filter.comap_neg_at_bot Filter.comap_neg_atBot
theorem comap_neg_atTop : comap (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).comap_atBot
#align filter.comap_neg_at_top Filter.comap_neg_atTop
theorem tendsto_neg_atTop_atBot : Tendsto (Neg.neg : β → β) atTop atBot :=
(OrderIso.neg β).tendsto_atTop
#align filter.tendsto_neg_at_top_at_bot Filter.tendsto_neg_atTop_atBot
theorem tendsto_neg_atBot_atTop : Tendsto (Neg.neg : β → β) atBot atTop :=
@tendsto_neg_atTop_atBot βᵒᵈ _
#align filter.tendsto_neg_at_bot_at_top Filter.tendsto_neg_atBot_atTop
variable {l}
@[simp]
theorem tendsto_neg_atTop_iff : Tendsto (fun x => -f x) l atTop ↔ Tendsto f l atBot :=
(OrderIso.neg β).tendsto_atBot_iff
#align filter.tendsto_neg_at_top_iff Filter.tendsto_neg_atTop_iff
@[simp]
theorem tendsto_neg_atBot_iff : Tendsto (fun x => -f x) l atBot ↔ Tendsto f l atTop :=
(OrderIso.neg β).tendsto_atTop_iff
#align filter.tendsto_neg_at_bot_iff Filter.tendsto_neg_atBot_iff
end OrderedGroup
section OrderedSemiring
variable [OrderedSemiring α] {l : Filter β} {f g : β → α}
#noalign filter.tendsto_bit1_at_top
theorem Tendsto.atTop_mul_atTop (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atTop := by
refine tendsto_atTop_mono' _ ?_ hg
filter_upwards [hg.eventually (eventually_ge_atTop 0),
hf.eventually (eventually_ge_atTop 1)] with _ using le_mul_of_one_le_left
#align filter.tendsto.at_top_mul_at_top Filter.Tendsto.atTop_mul_atTop
theorem tendsto_mul_self_atTop : Tendsto (fun x : α => x * x) atTop atTop :=
tendsto_id.atTop_mul_atTop tendsto_id
#align filter.tendsto_mul_self_at_top Filter.tendsto_mul_self_atTop
/-- The monomial function `x^n` tends to `+∞` at `+∞` for any positive natural `n`.
A version for positive real powers exists as `tendsto_rpow_atTop`. -/
theorem tendsto_pow_atTop {n : ℕ} (hn : n ≠ 0) : Tendsto (fun x : α => x ^ n) atTop atTop :=
tendsto_atTop_mono' _ ((eventually_ge_atTop 1).mono fun _x hx => le_self_pow hx hn) tendsto_id
#align filter.tendsto_pow_at_top Filter.tendsto_pow_atTop
end OrderedSemiring
theorem zero_pow_eventuallyEq [MonoidWithZero α] :
(fun n : ℕ => (0 : α) ^ n) =ᶠ[atTop] fun _ => 0 :=
eventually_atTop.2 ⟨1, fun _n hn ↦ zero_pow $ Nat.one_le_iff_ne_zero.1 hn⟩
#align filter.zero_pow_eventually_eq Filter.zero_pow_eventuallyEq
section OrderedRing
variable [OrderedRing α] {l : Filter β} {f g : β → α}
theorem Tendsto.atTop_mul_atBot (hf : Tendsto f l atTop) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atBot := by
have := hf.atTop_mul_atTop <| tendsto_neg_atBot_atTop.comp hg
simpa only [(· ∘ ·), neg_mul_eq_mul_neg, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_top_mul_at_bot Filter.Tendsto.atTop_mul_atBot
theorem Tendsto.atBot_mul_atTop (hf : Tendsto f l atBot) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atBot := by
have : Tendsto (fun x => -f x * g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop hg
simpa only [(· ∘ ·), neg_mul_eq_neg_mul, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_bot_mul_at_top Filter.Tendsto.atBot_mul_atTop
theorem Tendsto.atBot_mul_atBot (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atTop := by
have : Tendsto (fun x => -f x * -g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop (tendsto_neg_atBot_atTop.comp hg)
simpa only [neg_mul_neg] using this
#align filter.tendsto.at_bot_mul_at_bot Filter.Tendsto.atBot_mul_atBot
end OrderedRing
section LinearOrderedAddCommGroup
variable [LinearOrderedAddCommGroup α]
/-- $\lim_{x\to+\infty}|x|=+\infty$ -/
theorem tendsto_abs_atTop_atTop : Tendsto (abs : α → α) atTop atTop :=
tendsto_atTop_mono le_abs_self tendsto_id
#align filter.tendsto_abs_at_top_at_top Filter.tendsto_abs_atTop_atTop
/-- $\lim_{x\to-\infty}|x|=+\infty$ -/
theorem tendsto_abs_atBot_atTop : Tendsto (abs : α → α) atBot atTop :=
tendsto_atTop_mono neg_le_abs tendsto_neg_atBot_atTop
#align filter.tendsto_abs_at_bot_at_top Filter.tendsto_abs_atBot_atTop
@[simp]
theorem comap_abs_atTop : comap (abs : α → α) atTop = atBot ⊔ atTop := by
refine
le_antisymm (((atTop_basis.comap _).le_basis_iff (atBot_basis.sup atTop_basis)).2 ?_)
(sup_le tendsto_abs_atBot_atTop.le_comap tendsto_abs_atTop_atTop.le_comap)
rintro ⟨a, b⟩ -
refine ⟨max (-a) b, trivial, fun x hx => ?_⟩
rw [mem_preimage, mem_Ici, le_abs', max_le_iff, ← min_neg_neg, le_min_iff, neg_neg] at hx
exact hx.imp And.left And.right
#align filter.comap_abs_at_top Filter.comap_abs_atTop
end LinearOrderedAddCommGroup
section LinearOrderedSemiring
variable [LinearOrderedSemiring α] {l : Filter β} {f : β → α}
theorem Tendsto.atTop_of_const_mul {c : α} (hc : 0 < c) (hf : Tendsto (fun x => c * f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (c * b)).mono
fun _x hx => le_of_mul_le_mul_left hx hc
#align filter.tendsto.at_top_of_const_mul Filter.Tendsto.atTop_of_const_mul
theorem Tendsto.atTop_of_mul_const {c : α} (hc : 0 < c) (hf : Tendsto (fun x => f x * c) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b * c)).mono
fun _x hx => le_of_mul_le_mul_right hx hc
#align filter.tendsto.at_top_of_mul_const Filter.Tendsto.atTop_of_mul_const
@[simp]
theorem tendsto_pow_atTop_iff {n : ℕ} : Tendsto (fun x : α => x ^ n) atTop atTop ↔ n ≠ 0 :=
⟨fun h hn => by simp only [hn, pow_zero, not_tendsto_const_atTop] at h, tendsto_pow_atTop⟩
#align filter.tendsto_pow_at_top_iff Filter.tendsto_pow_atTop_iff
end LinearOrderedSemiring
theorem not_tendsto_pow_atTop_atBot [LinearOrderedRing α] :
∀ {n : ℕ}, ¬Tendsto (fun x : α => x ^ n) atTop atBot
| 0 => by simp [not_tendsto_const_atBot]
| n + 1 => (tendsto_pow_atTop n.succ_ne_zero).not_tendsto disjoint_atTop_atBot
#align filter.not_tendsto_pow_at_top_at_bot Filter.not_tendsto_pow_atTop_atBot
section LinearOrderedSemifield
variable [LinearOrderedSemifield α] {l : Filter β} {f : β → α} {r c : α} {n : ℕ}
/-!
### Multiplication by constant: iff lemmas
-/
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_const_mul_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atTop :=
⟨fun h => h.atTop_of_const_mul hr, fun h =>
Tendsto.atTop_of_const_mul (inv_pos.2 hr) <| by simpa only [inv_mul_cancel_left₀ hr.ne'] ⟩
#align filter.tendsto_const_mul_at_top_of_pos Filter.tendsto_const_mul_atTop_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_mul_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_mul_const_at_top_of_pos Filter.tendsto_mul_const_atTop_of_pos
/-- If `r` is a positive constant, `x ↦ f x / r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
lemma tendsto_div_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atTop := by
simpa only [div_eq_mul_inv] using tendsto_mul_const_atTop_of_pos (inv_pos.2 hr)
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r := by
refine ⟨fun hrf => not_le.mp fun hr => ?_, fun hr => (tendsto_const_mul_atTop_of_pos hr).mpr h⟩
rcases ((h.eventually_ge_atTop 0).and (hrf.eventually_gt_atTop 0)).exists with ⟨x, hx, hrx⟩
exact (mul_nonpos_of_nonpos_of_nonneg hr hx).not_lt hrx
#align filter.tendsto_const_mul_at_top_iff_pos Filter.tendsto_const_mul_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_pos h]
#align filter.tendsto_mul_const_at_top_iff_pos Filter.tendsto_mul_const_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r := by
simp only [div_eq_mul_inv, tendsto_mul_const_atTop_iff_pos h, inv_pos]
/-- If `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the left) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.const_mul_atTop'` instead. -/
theorem Tendsto.const_mul_atTop (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_top Filter.Tendsto.const_mul_atTop
/-- If a function `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the right) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.atTop_mul_const'` instead. -/
theorem Tendsto.atTop_mul_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_pos hr).2 hf
#align filter.tendsto.at_top_mul_const Filter.Tendsto.atTop_mul_const
/-- If a function `f` tends to infinity along a filter, then `f` divided by a positive
constant also tends to infinity. -/
theorem Tendsto.atTop_div_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x / r) l atTop := by
simpa only [div_eq_mul_inv] using hf.atTop_mul_const (inv_pos.2 hr)
#align filter.tendsto.at_top_div_const Filter.Tendsto.atTop_div_const
theorem tendsto_const_mul_pow_atTop (hn : n ≠ 0) (hc : 0 < c) :
Tendsto (fun x => c * x ^ n) atTop atTop :=
Tendsto.const_mul_atTop hc (tendsto_pow_atTop hn)
#align filter.tendsto_const_mul_pow_at_top Filter.tendsto_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atTop_iff :
Tendsto (fun x => c * x ^ n) atTop atTop ↔ n ≠ 0 ∧ 0 < c := by
refine ⟨fun h => ⟨?_, ?_⟩, fun h => tendsto_const_mul_pow_atTop h.1 h.2⟩
· rintro rfl
simp only [pow_zero, not_tendsto_const_atTop] at h
· rcases ((h.eventually_gt_atTop 0).and (eventually_ge_atTop 0)).exists with ⟨k, hck, hk⟩
exact pos_of_mul_pos_left hck (pow_nonneg hk _)
#align filter.tendsto_const_mul_pow_at_top_iff Filter.tendsto_const_mul_pow_atTop_iff
lemma tendsto_zpow_atTop_atTop {n : ℤ} (hn : 0 < n) : Tendsto (fun x : α ↦ x ^ n) atTop atTop := by
lift n to ℕ+ using hn; simp
#align tendsto_zpow_at_top_at_top Filter.tendsto_zpow_atTop_atTop
end LinearOrderedSemifield
section LinearOrderedField
variable [LinearOrderedField α] {l : Filter β} {f : β → α} {r : α}
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_const_mul_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atBot := by
simpa only [← mul_neg, ← tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_const_mul_at_bot_of_pos Filter.tendsto_const_mul_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_mul_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_pos hr
#align filter.tendsto_mul_const_at_bot_of_pos Filter.tendsto_mul_const_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x / r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
lemma tendsto_div_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_pos, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_const_mul_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atBot := by
simpa only [neg_mul, tendsto_neg_atBot_iff] using tendsto_const_mul_atBot_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_top_of_neg Filter.tendsto_const_mul_atTop_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_mul_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_neg hr
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
lemma tendsto_div_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_of_neg, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_const_mul_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atTop := by
simpa only [neg_mul, tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_bot_of_neg Filter.tendsto_const_mul_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_mul_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_neg hr
#align filter.tendsto_mul_const_at_bot_of_neg Filter.tendsto_mul_const_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
lemma tendsto_div_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_neg, hr]
/-- The function `fun x ↦ r * f x` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_const_mul_atTop_iff [NeBot l] :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
rcases lt_trichotomy r 0 with (hr | rfl | hr)
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_neg]
· simp [not_tendsto_const_atTop]
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_pos]
#align filter.tendsto_const_mul_at_top_iff Filter.tendsto_const_mul_atTop_iff
/-- The function `fun x ↦ f x * r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_mul_const_atTop_iff [NeBot l] :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff]
#align filter.tendsto_mul_const_at_top_iff Filter.tendsto_mul_const_atTop_iff
/-- The function `fun x ↦ f x / r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
lemma tendsto_div_const_atTop_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff]
/-- The function `fun x ↦ r * f x` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_const_mul_atBot_iff [NeBot l] :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [← tendsto_neg_atTop_iff, ← mul_neg, tendsto_const_mul_atTop_iff, neg_neg]
#align filter.tendsto_const_mul_at_bot_iff Filter.tendsto_const_mul_atBot_iff
/-- The function `fun x ↦ f x * r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_mul_const_atBot_iff [NeBot l] :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff]
#align filter.tendsto_mul_const_at_bot_iff Filter.tendsto_mul_const_atBot_iff
/-- The function `fun x ↦ f x / r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
lemma tendsto_div_const_atBot_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff]
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ r * f x` tends to infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop ↔ r < 0 := by
simp [tendsto_const_mul_atTop_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_top_iff_neg Filter.tendsto_const_mul_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x * r` tends to infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_neg h]
#align filter.tendsto_mul_const_at_top_iff_neg Filter.tendsto_mul_const_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x / r` tends to infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atTop ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff_neg h]
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_bot_iff_pos Filter.tendsto_const_mul_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_pos h]
#align filter.tendsto_mul_const_at_bot_iff_pos Filter.tendsto_mul_const_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x / r` tends to negative infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_pos h]
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ r * f x` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot ↔ r < 0 := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atTop_atBot]
#align filter.tendsto_const_mul_at_bot_iff_neg Filter.tendsto_const_mul_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x * r` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_neg h]
#align filter.tendsto_mul_const_at_bot_iff_neg Filter.tendsto_mul_const_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x / r` tends to negative infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_neg h]
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to negative infinity. -/
theorem Tendsto.const_mul_atTop_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_top Filter.Tendsto.const_mul_atTop_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to negative infinity. -/
theorem Tendsto.atTop_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_neg hr).2 hf
#align filter.tendsto.at_top_mul_neg_const Filter.Tendsto.atTop_mul_const_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` divided by a negative constant tends to negative infinity. -/
lemma Tendsto.atTop_div_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot := (tendsto_div_const_atBot_of_neg hr).2 hf
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the left) also tends to negative infinity. -/
theorem Tendsto.const_mul_atBot (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_bot Filter.Tendsto.const_mul_atBot
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the right) also tends to negative infinity. -/
theorem Tendsto.atBot_mul_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_mul_const Filter.Tendsto.atBot_mul_const
/-- If a function `f` tends to negative infinity along a filter, then `f` divided by
a positive constant also tends to negative infinity. -/
theorem Tendsto.atBot_div_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x / r) l atBot := (tendsto_div_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_div_const Filter.Tendsto.atBot_div_const
/-- If a function `f` tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to positive infinity. -/
theorem Tendsto.const_mul_atBot_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_bot Filter.Tendsto.const_mul_atBot_of_neg
/-- If a function tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to positive infinity. -/
theorem Tendsto.atBot_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_neg hr).2 hf
#align filter.tendsto.at_bot_mul_neg_const Filter.Tendsto.atBot_mul_const_of_neg
theorem tendsto_neg_const_mul_pow_atTop {c : α} {n : ℕ} (hn : n ≠ 0) (hc : c < 0) :
Tendsto (fun x => c * x ^ n) atTop atBot :=
(tendsto_pow_atTop hn).const_mul_atTop_of_neg hc
#align filter.tendsto_neg_const_mul_pow_at_top Filter.tendsto_neg_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atBot_iff {c : α} {n : ℕ} :
Tendsto (fun x => c * x ^ n) atTop atBot ↔ n ≠ 0 ∧ c < 0 := by
simp only [← tendsto_neg_atTop_iff, ← neg_mul, tendsto_const_mul_pow_atTop_iff, neg_pos]
#align filter.tendsto_const_mul_pow_at_bot_iff Filter.tendsto_const_mul_pow_atBot_iff
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atTop := Tendsto.const_mul_atTop_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atTop_mul_neg_const := Tendsto.atTop_mul_const_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atBot := Tendsto.const_mul_atBot_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atBot_mul_neg_const := Tendsto.atBot_mul_const_of_neg
end LinearOrderedField
open Filter
theorem tendsto_atTop' [Nonempty α] [SemilatticeSup α] {f : α → β} {l : Filter β} :
Tendsto f atTop l ↔ ∀ s ∈ l, ∃ a, ∀ b ≥ a, f b ∈ s := by
simp only [tendsto_def, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top' Filter.tendsto_atTop'
theorem tendsto_atBot' [Nonempty α] [SemilatticeInf α] {f : α → β} {l : Filter β} :
Tendsto f atBot l ↔ ∀ s ∈ l, ∃ a, ∀ b ≤ a, f b ∈ s :=
@tendsto_atTop' αᵒᵈ _ _ _ _ _
#align filter.tendsto_at_bot' Filter.tendsto_atBot'
theorem tendsto_atTop_principal [Nonempty β] [SemilatticeSup β] {f : β → α} {s : Set α} :
Tendsto f atTop (𝓟 s) ↔ ∃ N, ∀ n ≥ N, f n ∈ s := by
simp_rw [tendsto_iff_comap, comap_principal, le_principal_iff, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top_principal Filter.tendsto_atTop_principal
theorem tendsto_atBot_principal [Nonempty β] [SemilatticeInf β] {f : β → α} {s : Set α} :
Tendsto f atBot (𝓟 s) ↔ ∃ N, ∀ n ≤ N, f n ∈ s :=
@tendsto_atTop_principal _ βᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_principal Filter.tendsto_atBot_principal
/-- A function `f` grows to `+∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atTop_atTop [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → b ≤ f a :=
Iff.trans tendsto_iInf <| forall_congr' fun _ => tendsto_atTop_principal
#align filter.tendsto_at_top_at_top Filter.tendsto_atTop_atTop
theorem tendsto_atTop_atBot [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → f a ≤ b :=
@tendsto_atTop_atTop α βᵒᵈ _ _ _ f
#align filter.tendsto_at_top_at_bot Filter.tendsto_atTop_atBot
theorem tendsto_atBot_atTop [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → b ≤ f a :=
@tendsto_atTop_atTop αᵒᵈ β _ _ _ f
#align filter.tendsto_at_bot_at_top Filter.tendsto_atBot_atTop
theorem tendsto_atBot_atBot [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → f a ≤ b :=
@tendsto_atTop_atTop αᵒᵈ βᵒᵈ _ _ _ f
#align filter.tendsto_at_bot_at_bot Filter.tendsto_atBot_atBot
theorem tendsto_atTop_atTop_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atTop atTop :=
tendsto_iInf.2 fun b =>
tendsto_principal.2 <|
let ⟨a, ha⟩ := h b
mem_of_superset (mem_atTop a) fun _a' ha' => le_trans ha (hf ha')
#align filter.tendsto_at_top_at_top_of_monotone Filter.tendsto_atTop_atTop_of_monotone
theorem tendsto_atTop_atBot_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atTop atBot :=
@tendsto_atTop_atTop_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atBot_atBot_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atBot atBot :=
tendsto_iInf.2 fun b => tendsto_principal.2 <|
let ⟨a, ha⟩ := h b; mem_of_superset (mem_atBot a) fun _a' ha' => le_trans (hf ha') ha
#align filter.tendsto_at_bot_at_bot_of_monotone Filter.tendsto_atBot_atBot_of_monotone
theorem tendsto_atBot_atTop_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atBot atTop :=
@tendsto_atBot_atBot_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atTop_atTop_iff_of_monotone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atTop atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
tendsto_atTop_atTop.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans h <| hf ha'⟩
#align filter.tendsto_at_top_at_top_iff_of_monotone Filter.tendsto_atTop_atTop_iff_of_monotone
theorem tendsto_atTop_atBot_iff_of_antitone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atTop atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
@tendsto_atTop_atTop_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
theorem tendsto_atBot_atBot_iff_of_monotone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atBot atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
tendsto_atBot_atBot.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans (hf ha') h⟩
#align filter.tendsto_at_bot_at_bot_iff_of_monotone Filter.tendsto_atBot_atBot_iff_of_monotone
theorem tendsto_atBot_atTop_iff_of_antitone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atBot atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
@tendsto_atBot_atBot_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
alias _root_.Monotone.tendsto_atTop_atTop := tendsto_atTop_atTop_of_monotone
#align monotone.tendsto_at_top_at_top Monotone.tendsto_atTop_atTop
alias _root_.Monotone.tendsto_atBot_atBot := tendsto_atBot_atBot_of_monotone
#align monotone.tendsto_at_bot_at_bot Monotone.tendsto_atBot_atBot
alias _root_.Monotone.tendsto_atTop_atTop_iff := tendsto_atTop_atTop_iff_of_monotone
#align monotone.tendsto_at_top_at_top_iff Monotone.tendsto_atTop_atTop_iff
alias _root_.Monotone.tendsto_atBot_atBot_iff := tendsto_atBot_atBot_iff_of_monotone
#align monotone.tendsto_at_bot_at_bot_iff Monotone.tendsto_atBot_atBot_iff
theorem comap_embedding_atTop [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) : comap e atTop = atTop :=
le_antisymm
(le_iInf fun b =>
le_principal_iff.2 <| mem_comap.2 ⟨Ici (e b), mem_atTop _, fun _ => (hm _ _).1⟩)
(tendsto_atTop_atTop_of_monotone (fun _ _ => (hm _ _).2) hu).le_comap
#align filter.comap_embedding_at_top Filter.comap_embedding_atTop
theorem comap_embedding_atBot [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) : comap e atBot = atBot :=
@comap_embedding_atTop βᵒᵈ γᵒᵈ _ _ e (Function.swap hm) hu
#align filter.comap_embedding_at_bot Filter.comap_embedding_atBot
theorem tendsto_atTop_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) :
Tendsto (e ∘ f) l atTop ↔ Tendsto f l atTop := by
rw [← comap_embedding_atTop hm hu, tendsto_comap_iff]
#align filter.tendsto_at_top_embedding Filter.tendsto_atTop_embedding
/-- A function `f` goes to `-∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atBot_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) :
Tendsto (e ∘ f) l atBot ↔ Tendsto f l atBot :=
@tendsto_atTop_embedding α βᵒᵈ γᵒᵈ _ _ f e l (Function.swap hm) hu
#align filter.tendsto_at_bot_embedding Filter.tendsto_atBot_embedding
theorem tendsto_finset_range : Tendsto Finset.range atTop atTop :=
Finset.range_mono.tendsto_atTop_atTop Finset.exists_nat_subset_range
#align filter.tendsto_finset_range Filter.tendsto_finset_range
theorem atTop_finset_eq_iInf : (atTop : Filter (Finset α)) = ⨅ x : α, 𝓟 (Ici {x}) := by
refine le_antisymm (le_iInf fun i => le_principal_iff.2 <| mem_atTop ({i} : Finset α)) ?_
refine
le_iInf fun s =>
le_principal_iff.2 <| mem_iInf_of_iInter s.finite_toSet (fun i => mem_principal_self _) ?_
simp only [subset_def, mem_iInter, SetCoe.forall, mem_Ici, Finset.le_iff_subset,
Finset.mem_singleton, Finset.subset_iff, forall_eq]
exact fun t => id
#align filter.at_top_finset_eq_infi Filter.atTop_finset_eq_iInf
/-- If `f` is a monotone sequence of `Finset`s and each `x` belongs to one of `f n`, then
`Tendsto f atTop atTop`. -/
theorem tendsto_atTop_finset_of_monotone [Preorder β] {f : β → Finset α} (h : Monotone f)
(h' : ∀ x : α, ∃ n, x ∈ f n) : Tendsto f atTop atTop := by
simp only [atTop_finset_eq_iInf, tendsto_iInf, tendsto_principal]
intro a
rcases h' a with ⟨b, hb⟩
exact (eventually_ge_atTop b).mono fun b' hb' => (Finset.singleton_subset_iff.2 hb).trans (h hb')
#align filter.tendsto_at_top_finset_of_monotone Filter.tendsto_atTop_finset_of_monotone
alias _root_.Monotone.tendsto_atTop_finset := tendsto_atTop_finset_of_monotone
#align monotone.tendsto_at_top_finset Monotone.tendsto_atTop_finset
-- Porting note: add assumption `DecidableEq β` so that the lemma applies to any instance
theorem tendsto_finset_image_atTop_atTop [DecidableEq β] {i : β → γ} {j : γ → β}
(h : Function.LeftInverse j i) : Tendsto (Finset.image j) atTop atTop :=
(Finset.image_mono j).tendsto_atTop_finset fun a =>
⟨{i a}, by simp only [Finset.image_singleton, h a, Finset.mem_singleton]⟩
#align filter.tendsto_finset_image_at_top_at_top Filter.tendsto_finset_image_atTop_atTop
theorem tendsto_finset_preimage_atTop_atTop {f : α → β} (hf : Function.Injective f) :
Tendsto (fun s : Finset β => s.preimage f (hf.injOn)) atTop atTop :=
(Finset.monotone_preimage hf).tendsto_atTop_finset fun x =>
⟨{f x}, Finset.mem_preimage.2 <| Finset.mem_singleton_self _⟩
#align filter.tendsto_finset_preimage_at_top_at_top Filter.tendsto_finset_preimage_atTop_atTop
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atTop_atTop_eq [Preorder α] [Preorder β] :
(atTop : Filter α) ×ˢ (atTop : Filter β) = (atTop : Filter (α × β)) := by
cases isEmpty_or_nonempty α
· exact Subsingleton.elim _ _
cases isEmpty_or_nonempty β
· exact Subsingleton.elim _ _
simpa [atTop, prod_iInf_left, prod_iInf_right, iInf_prod] using iInf_comm
#align filter.prod_at_top_at_top_eq Filter.prod_atTop_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atBot_atBot_eq [Preorder β₁] [Preorder β₂] :
(atBot : Filter β₁) ×ˢ (atBot : Filter β₂) = (atBot : Filter (β₁ × β₂)) :=
@prod_atTop_atTop_eq β₁ᵒᵈ β₂ᵒᵈ _ _
#align filter.prod_at_bot_at_bot_eq Filter.prod_atBot_atBot_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atTop_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atTop ×ˢ map u₂ atTop = map (Prod.map u₁ u₂) atTop := by
rw [prod_map_map_eq, prod_atTop_atTop_eq, Prod.map_def]
#align filter.prod_map_at_top_eq Filter.prod_map_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atBot_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atBot ×ˢ map u₂ atBot = map (Prod.map u₁ u₂) atBot :=
@prod_map_atTop_eq _ _ β₁ᵒᵈ β₂ᵒᵈ _ _ _ _
#align filter.prod_map_at_bot_eq Filter.prod_map_atBot_eq
theorem Tendsto.subseq_mem {F : Filter α} {V : ℕ → Set α} (h : ∀ n, V n ∈ F) {u : ℕ → α}
(hu : Tendsto u atTop F) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, u (φ n) ∈ V n :=
extraction_forall_of_eventually'
(fun n => tendsto_atTop'.mp hu _ (h n) : ∀ n, ∃ N, ∀ k ≥ N, u k ∈ V n)
#align filter.tendsto.subseq_mem Filter.Tendsto.subseq_mem
theorem tendsto_atBot_diagonal [SemilatticeInf α] : Tendsto (fun a : α => (a, a)) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_bot_diagonal Filter.tendsto_atBot_diagonal
theorem tendsto_atTop_diagonal [SemilatticeSup α] : Tendsto (fun a : α => (a, a)) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_top_diagonal Filter.tendsto_atTop_diagonal
theorem Tendsto.prod_map_prod_atBot [SemilatticeInf γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atBot) (hg : Tendsto g G atBot) :
Tendsto (Prod.map f g) (F ×ˢ G) atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_bot Filter.Tendsto.prod_map_prod_atBot
theorem Tendsto.prod_map_prod_atTop [SemilatticeSup γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atTop) (hg : Tendsto g G atTop) :
Tendsto (Prod.map f g) (F ×ˢ G) atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_top Filter.Tendsto.prod_map_prod_atTop
theorem Tendsto.prod_atBot [SemilatticeInf α] [SemilatticeInf γ] {f g : α → γ}
(hf : Tendsto f atBot atBot) (hg : Tendsto g atBot atBot) :
Tendsto (Prod.map f g) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map_prod_atBot hg
#align filter.tendsto.prod_at_bot Filter.Tendsto.prod_atBot
theorem Tendsto.prod_atTop [SemilatticeSup α] [SemilatticeSup γ] {f g : α → γ}
(hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) :
Tendsto (Prod.map f g) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map_prod_atTop hg
#align filter.tendsto.prod_at_top Filter.Tendsto.prod_atTop
theorem eventually_atBot_prod_self [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k l, k ≤ a → l ≤ a → p (k, l) := by
simp [← prod_atBot_atBot_eq, (@atBot_basis α _ _).prod_self.eventually_iff]
#align filter.eventually_at_bot_prod_self Filter.eventually_atBot_prod_self
theorem eventually_atTop_prod_self [SemilatticeSup α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ k l, a ≤ k → a ≤ l → p (k, l) :=
eventually_atBot_prod_self (α := αᵒᵈ)
#align filter.eventually_at_top_prod_self Filter.eventually_atTop_prod_self
theorem eventually_atBot_prod_self' [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k ≤ a, ∀ l ≤ a, p (k, l) := by
simp only [eventually_atBot_prod_self, forall_cond_comm]
#align filter.eventually_at_bot_prod_self' Filter.eventually_atBot_prod_self'
theorem eventually_atTop_prod_self' [SemilatticeSup α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ k ≥ a, ∀ l ≥ a, p (k, l) := by
simp only [eventually_atTop_prod_self, forall_cond_comm]
#align filter.eventually_at_top_prod_self' Filter.eventually_atTop_prod_self'
theorem eventually_atTop_curry [SemilatticeSup α] [SemilatticeSup β] {p : α × β → Prop}
(hp : ∀ᶠ x : α × β in Filter.atTop, p x) : ∀ᶠ k in atTop, ∀ᶠ l in atTop, p (k, l) := by
rw [← prod_atTop_atTop_eq] at hp
exact hp.curry
#align filter.eventually_at_top_curry Filter.eventually_atTop_curry
theorem eventually_atBot_curry [SemilatticeInf α] [SemilatticeInf β] {p : α × β → Prop}
(hp : ∀ᶠ x : α × β in Filter.atBot, p x) : ∀ᶠ k in atBot, ∀ᶠ l in atBot, p (k, l) :=
@eventually_atTop_curry αᵒᵈ βᵒᵈ _ _ _ hp
#align filter.eventually_at_bot_curry Filter.eventually_atBot_curry
/-- A function `f` maps upwards closed sets (atTop sets) to upwards closed sets when it is a
Galois insertion. The Galois "insertion" and "connection" is weakened to only require it to be an
insertion and a connection above `b'`. -/
theorem map_atTop_eq_of_gc [SemilatticeSup α] [SemilatticeSup β] {f : α → β} (g : β → α) (b' : β)
(hf : Monotone f) (gc : ∀ a, ∀ b ≥ b', f a ≤ b ↔ a ≤ g b) (hgi : ∀ b ≥ b', b ≤ f (g b)) :
map f atTop = atTop := by
refine
le_antisymm
(hf.tendsto_atTop_atTop fun b => ⟨g (b ⊔ b'), le_sup_left.trans <| hgi _ le_sup_right⟩) ?_
rw [@map_atTop_eq _ _ ⟨g b'⟩]
refine le_iInf fun a => iInf_le_of_le (f a ⊔ b') <| principal_mono.2 fun b hb => ?_
rw [mem_Ici, sup_le_iff] at hb
exact ⟨g b, (gc _ _ hb.2).1 hb.1, le_antisymm ((gc _ _ hb.2).2 le_rfl) (hgi _ hb.2)⟩
#align filter.map_at_top_eq_of_gc Filter.map_atTop_eq_of_gc
theorem map_atBot_eq_of_gc [SemilatticeInf α] [SemilatticeInf β] {f : α → β} (g : β → α) (b' : β)
(hf : Monotone f) (gc : ∀ a, ∀ b ≤ b', b ≤ f a ↔ g b ≤ a) (hgi : ∀ b ≤ b', f (g b) ≤ b) :
map f atBot = atBot :=
@map_atTop_eq_of_gc αᵒᵈ βᵒᵈ _ _ _ _ _ hf.dual gc hgi
#align filter.map_at_bot_eq_of_gc Filter.map_atBot_eq_of_gc
theorem map_val_atTop_of_Ici_subset [SemilatticeSup α] {a : α} {s : Set α} (h : Ici a ⊆ s) :
map ((↑) : s → α) atTop = atTop := by
haveI : Nonempty s := ⟨⟨a, h le_rfl⟩⟩
have : Directed (· ≥ ·) fun x : s => 𝓟 (Ici x) := fun x y ↦ by
use ⟨x ⊔ y ⊔ a, h le_sup_right⟩
simp only [principal_mono, Ici_subset_Ici, ← Subtype.coe_le_coe, Subtype.coe_mk]
exact ⟨le_sup_left.trans le_sup_left, le_sup_right.trans le_sup_left⟩
simp only [le_antisymm_iff, atTop, le_iInf_iff, le_principal_iff, mem_map, mem_setOf_eq,
map_iInf_eq this, map_principal]
constructor
· intro x
refine mem_of_superset (mem_iInf_of_mem ⟨x ⊔ a, h le_sup_right⟩ (mem_principal_self _)) ?_
rintro _ ⟨y, hy, rfl⟩
exact le_trans le_sup_left (Subtype.coe_le_coe.2 hy)
· intro x
filter_upwards [mem_atTop (↑x ⊔ a)] with b hb
exact ⟨⟨b, h <| le_sup_right.trans hb⟩, Subtype.coe_le_coe.1 (le_sup_left.trans hb), rfl⟩
#align filter.map_coe_at_top_of_Ici_subset Filter.map_val_atTop_of_Ici_subset
/-- The image of the filter `atTop` on `Ici a` under the coercion equals `atTop`. -/
@[simp]
theorem map_val_Ici_atTop [SemilatticeSup α] (a : α) : map ((↑) : Ici a → α) atTop = atTop :=
map_val_atTop_of_Ici_subset (Subset.refl _)
#align filter.map_coe_Ici_at_top Filter.map_val_Ici_atTop
/-- The image of the filter `atTop` on `Ioi a` under the coercion equals `atTop`. -/
@[simp]
theorem map_val_Ioi_atTop [SemilatticeSup α] [NoMaxOrder α] (a : α) :
map ((↑) : Ioi a → α) atTop = atTop :=
let ⟨_b, hb⟩ := exists_gt a
map_val_atTop_of_Ici_subset <| Ici_subset_Ioi.2 hb
#align filter.map_coe_Ioi_at_top Filter.map_val_Ioi_atTop
/-- The `atTop` filter for an open interval `Ioi a` comes from the `atTop` filter in the ambient
order. -/
theorem atTop_Ioi_eq [SemilatticeSup α] (a : α) : atTop = comap ((↑) : Ioi a → α) atTop := by
rcases isEmpty_or_nonempty (Ioi a) with h|⟨⟨b, hb⟩⟩
· exact Subsingleton.elim _ _
· rw [← map_val_atTop_of_Ici_subset (Ici_subset_Ioi.2 hb), comap_map Subtype.coe_injective]
#align filter.at_top_Ioi_eq Filter.atTop_Ioi_eq
/-- The `atTop` filter for an open interval `Ici a` comes from the `atTop` filter in the ambient
order. -/
theorem atTop_Ici_eq [SemilatticeSup α] (a : α) : atTop = comap ((↑) : Ici a → α) atTop := by
rw [← map_val_Ici_atTop a, comap_map Subtype.coe_injective]
#align filter.at_top_Ici_eq Filter.atTop_Ici_eq
/-- The `atBot` filter for an open interval `Iio a` comes from the `atBot` filter in the ambient
order. -/
@[simp]
theorem map_val_Iio_atBot [SemilatticeInf α] [NoMinOrder α] (a : α) :
map ((↑) : Iio a → α) atBot = atBot :=
@map_val_Ioi_atTop αᵒᵈ _ _ _
#align filter.map_coe_Iio_at_bot Filter.map_val_Iio_atBot
/-- The `atBot` filter for an open interval `Iio a` comes from the `atBot` filter in the ambient
order. -/
theorem atBot_Iio_eq [SemilatticeInf α] (a : α) : atBot = comap ((↑) : Iio a → α) atBot :=
@atTop_Ioi_eq αᵒᵈ _ _
#align filter.at_bot_Iio_eq Filter.atBot_Iio_eq
/-- The `atBot` filter for an open interval `Iic a` comes from the `atBot` filter in the ambient
order. -/
@[simp]
theorem map_val_Iic_atBot [SemilatticeInf α] (a : α) : map ((↑) : Iic a → α) atBot = atBot :=
@map_val_Ici_atTop αᵒᵈ _ _
#align filter.map_coe_Iic_at_bot Filter.map_val_Iic_atBot
/-- The `atBot` filter for an open interval `Iic a` comes from the `atBot` filter in the ambient
order. -/
theorem atBot_Iic_eq [SemilatticeInf α] (a : α) : atBot = comap ((↑) : Iic a → α) atBot :=
@atTop_Ici_eq αᵒᵈ _ _
#align filter.at_bot_Iic_eq Filter.atBot_Iic_eq
theorem tendsto_Ioi_atTop [SemilatticeSup α] {a : α} {f : β → Ioi a} {l : Filter β} :
Tendsto f l atTop ↔ Tendsto (fun x => (f x : α)) l atTop := by
rw [atTop_Ioi_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Ioi_at_top Filter.tendsto_Ioi_atTop
theorem tendsto_Iio_atBot [SemilatticeInf α] {a : α} {f : β → Iio a} {l : Filter β} :
Tendsto f l atBot ↔ Tendsto (fun x => (f x : α)) l atBot := by
rw [atBot_Iio_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Iio_at_bot Filter.tendsto_Iio_atBot
theorem tendsto_Ici_atTop [SemilatticeSup α] {a : α} {f : β → Ici a} {l : Filter β} :
Tendsto f l atTop ↔ Tendsto (fun x => (f x : α)) l atTop := by
rw [atTop_Ici_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Ici_at_top Filter.tendsto_Ici_atTop
theorem tendsto_Iic_atBot [SemilatticeInf α] {a : α} {f : β → Iic a} {l : Filter β} :
Tendsto f l atBot ↔ Tendsto (fun x => (f x : α)) l atBot := by
rw [atBot_Iic_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Iic_at_bot Filter.tendsto_Iic_atBot
@[simp, nolint simpNF] -- Porting note: linter claims that LHS doesn't simplify. It does.
theorem tendsto_comp_val_Ioi_atTop [SemilatticeSup α] [NoMaxOrder α] {a : α} {f : α → β}
{l : Filter β} : Tendsto (fun x : Ioi a => f x) atTop l ↔ Tendsto f atTop l := by
rw [← map_val_Ioi_atTop a, tendsto_map'_iff, Function.comp_def]
#align filter.tendsto_comp_coe_Ioi_at_top Filter.tendsto_comp_val_Ioi_atTop
@[simp, nolint simpNF] -- Porting note: linter claims that LHS doesn't simplify. It does.
| Mathlib/Order/Filter/AtTopBot.lean | 1,761 | 1,763 | theorem tendsto_comp_val_Ici_atTop [SemilatticeSup α] {a : α} {f : α → β} {l : Filter β} :
Tendsto (fun x : Ici a => f x) atTop l ↔ Tendsto f atTop l := by |
rw [← map_val_Ici_atTop a, tendsto_map'_iff, Function.comp_def]
|
/-
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
| Mathlib/Topology/Order/ExtendFrom.lean | 23 | 33 | 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⟩
|
/-
Copyright (c) 2023 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Algebra.Order.Pointwise
import Mathlib.Analysis.NormedSpace.SphereNormEquiv
import Mathlib.Analysis.SpecialFunctions.Integrals
import Mathlib.MeasureTheory.Constructions.Prod.Integral
import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar
/-!
# Generalized polar coordinate change
Consider an `n`-dimensional normed space `E` and an additive Haar measure `μ` on `E`.
Then `μ.toSphere` is the measure on the unit sphere
such that `μ.toSphere s` equals `n • μ (Set.Ioo 0 1 • s)`.
If `n ≠ 0`, then `μ` can be represented (up to `homeomorphUnitSphereProd`)
as the product of `μ.toSphere`
and the Lebesgue measure on `(0, +∞)` taken with density `fun r ↦ r ^ n`.
One can think about this fact as a version of polar coordinate change formula
for a general nontrivial normed space.
-/
open Set Function Metric MeasurableSpace intervalIntegral
open scoped Pointwise ENNReal NNReal
local notation "dim" => FiniteDimensional.finrank ℝ
noncomputable section
namespace MeasureTheory
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [FiniteDimensional ℝ E]
[MeasurableSpace E] [BorelSpace E]
namespace Measure
/-- If `μ` is an additive Haar measure on a normed space `E`,
then `μ.toSphere` is the measure on the unit sphere in `E`
such that `μ.toSphere s = FiniteDimensional.finrank ℝ E • μ (Set.Ioo (0 : ℝ) 1 • s)`. -/
def toSphere (μ : Measure E) : Measure (sphere (0 : E) 1) :=
dim E • ((μ.comap (Subtype.val ∘ (homeomorphUnitSphereProd E).symm)).restrict
(univ ×ˢ Iio ⟨1, mem_Ioi.2 one_pos⟩)).fst
variable (μ : Measure E)
theorem toSphere_apply_aux (s : Set (sphere (0 : E) 1)) (r : Ioi (0 : ℝ)) :
μ ((↑) '' (homeomorphUnitSphereProd E ⁻¹' s ×ˢ Iio r)) = μ (Ioo (0 : ℝ) r • ((↑) '' s)) := by
rw [← image2_smul, image2_image_right, ← Homeomorph.image_symm, image_image,
← image_subtype_val_Ioi_Iio, image2_image_left, image2_swap, ← image_prod]
rfl
theorem toSphere_apply' {s : Set (sphere (0 : E) 1)} (hs : MeasurableSet s) :
μ.toSphere s = dim E * μ (Ioo (0 : ℝ) 1 • ((↑) '' s)) := by
rw [toSphere, smul_apply, fst_apply hs, restrict_apply (measurable_fst hs),
((MeasurableEmbedding.subtype_coe (measurableSet_singleton _).compl).comp
(Homeomorph.measurableEmbedding _)).comap_apply,
image_comp, Homeomorph.image_symm, univ_prod, ← Set.prod_eq, nsmul_eq_mul, toSphere_apply_aux]
| Mathlib/MeasureTheory/Constructions/HaarToSphere.lean | 62 | 63 | theorem toSphere_apply_univ' : μ.toSphere univ = dim E * μ (ball 0 1 \ {0}) := by |
rw [μ.toSphere_apply' .univ, image_univ, Subtype.range_coe, Ioo_smul_sphere_zero] <;> simp
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Complex.Module
import Mathlib.Data.Complex.Order
import Mathlib.Data.Complex.Exponential
import Mathlib.Analysis.RCLike.Basic
import Mathlib.Topology.Algebra.InfiniteSum.Module
import Mathlib.Topology.Instances.RealVectorSpace
#align_import analysis.complex.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Normed space structure on `ℂ`.
This file gathers basic facts on complex numbers of an analytic nature.
## Main results
This file registers `ℂ` as a normed field, expresses basic properties of the norm, and gives
tools on the real vector space structure of `ℂ`. Notably, in the namespace `Complex`,
it defines functions:
* `reCLM`
* `imCLM`
* `ofRealCLM`
* `conjCLE`
They are bundled versions of the real part, the imaginary part, the embedding of `ℝ` in `ℂ`, and
the complex conjugate as continuous `ℝ`-linear maps. The last two are also bundled as linear
isometries in `ofRealLI` and `conjLIE`.
We also register the fact that `ℂ` is an `RCLike` field.
-/
assert_not_exists Absorbs
noncomputable section
namespace Complex
variable {z : ℂ}
open ComplexConjugate Topology Filter
instance : Norm ℂ :=
⟨abs⟩
@[simp]
theorem norm_eq_abs (z : ℂ) : ‖z‖ = abs z :=
rfl
#align complex.norm_eq_abs Complex.norm_eq_abs
lemma norm_I : ‖I‖ = 1 := abs_I
| Mathlib/Analysis/Complex/Basic.lean | 58 | 59 | theorem norm_exp_ofReal_mul_I (t : ℝ) : ‖exp (t * I)‖ = 1 := by |
simp only [norm_eq_abs, abs_exp_ofReal_mul_I]
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.FieldTheory.Finiteness
import Mathlib.LinearAlgebra.Dimension.FreeAndStrongRankCondition
import Mathlib.LinearAlgebra.Dimension.DivisionRing
#align_import linear_algebra.finite_dimensional from "leanprover-community/mathlib"@"e95e4f92c8f8da3c7f693c3ec948bcf9b6683f51"
/-!
# Finite dimensional vector spaces
Definition and basic properties of finite dimensional vector spaces, of their dimensions, and
of linear maps on such spaces.
## Main definitions
Assume `V` is a vector space over a division ring `K`. There are (at least) three equivalent
definitions of finite-dimensionality of `V`:
- it admits a finite basis.
- it is finitely generated.
- it is noetherian, i.e., every subspace is finitely generated.
We introduce a typeclass `FiniteDimensional K V` capturing this property. For ease of transfer of
proof, it is defined using the second point of view, i.e., as `Finite`. However, we prove
that all these points of view are equivalent, with the following lemmas
(in the namespace `FiniteDimensional`):
- `fintypeBasisIndex` states that a finite-dimensional
vector space has a finite basis
- `FiniteDimensional.finBasis` and `FiniteDimensional.finBasisOfFinrankEq`
are bases for finite dimensional vector spaces, where the index type
is `Fin`
- `of_fintype_basis` states that the existence of a basis indexed by a
finite type implies finite-dimensionality
- `of_finite_basis` states that the existence of a basis indexed by a
finite set implies finite-dimensionality
- `IsNoetherian.iff_fg` states that the space is finite-dimensional if and only if
it is noetherian
We make use of `finrank`, the dimension of a finite dimensional space, returning a `Nat`, as
opposed to `Module.rank`, which returns a `Cardinal`. When the space has infinite dimension, its
`finrank` is by convention set to `0`. `finrank` is not defined using `FiniteDimensional`.
For basic results that do not need the `FiniteDimensional` class, import
`Mathlib.LinearAlgebra.Finrank`.
Preservation of finite-dimensionality and formulas for the dimension are given for
- submodules
- quotients (for the dimension of a quotient, see `finrank_quotient_add_finrank`)
- linear equivs, in `LinearEquiv.finiteDimensional`
- image under a linear map (the rank-nullity formula is in `finrank_range_add_finrank_ker`)
Basic properties of linear maps of a finite-dimensional vector space are given. Notably, the
equivalence of injectivity and surjectivity is proved in `LinearMap.injective_iff_surjective`,
and the equivalence between left-inverse and right-inverse in `LinearMap.mul_eq_one_comm`
and `LinearMap.comp_eq_id_comm`.
## Implementation notes
Most results are deduced from the corresponding results for the general dimension (as a cardinal),
in `Mathlib.LinearAlgebra.Dimension`. Not all results have been ported yet.
You should not assume that there has been any effort to state lemmas as generally as possible.
Plenty of the results hold for general fg modules or notherian modules, and they can be found in
`Mathlib.LinearAlgebra.FreeModule.Finite.Rank` and `Mathlib.RingTheory.Noetherian`.
-/
universe u v v' w
open Cardinal Submodule Module Function
/-- `FiniteDimensional` vector spaces are defined to be finite modules.
Use `FiniteDimensional.of_fintype_basis` to prove finite dimension from another definition. -/
abbrev FiniteDimensional (K V : Type*) [DivisionRing K] [AddCommGroup V] [Module K V] :=
Module.Finite K V
#align finite_dimensional FiniteDimensional
variable {K : Type u} {V : Type v}
namespace FiniteDimensional
open IsNoetherian
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- If the codomain of an injective linear map is finite dimensional, the domain must be as well. -/
theorem of_injective (f : V →ₗ[K] V₂) (w : Function.Injective f) [FiniteDimensional K V₂] :
FiniteDimensional K V :=
have : IsNoetherian K V₂ := IsNoetherian.iff_fg.mpr ‹_›
Module.Finite.of_injective f w
#align finite_dimensional.of_injective FiniteDimensional.of_injective
/-- If the domain of a surjective linear map is finite dimensional, the codomain must be as well. -/
theorem of_surjective (f : V →ₗ[K] V₂) (w : Function.Surjective f) [FiniteDimensional K V] :
FiniteDimensional K V₂ :=
Module.Finite.of_surjective f w
#align finite_dimensional.of_surjective FiniteDimensional.of_surjective
variable (K V)
instance finiteDimensional_pi {ι : Type*} [Finite ι] : FiniteDimensional K (ι → K) :=
Finite.pi
#align finite_dimensional.finite_dimensional_pi FiniteDimensional.finiteDimensional_pi
instance finiteDimensional_pi' {ι : Type*} [Finite ι] (M : ι → Type*) [∀ i, AddCommGroup (M i)]
[∀ i, Module K (M i)] [∀ i, FiniteDimensional K (M i)] : FiniteDimensional K (∀ i, M i) :=
Finite.pi
#align finite_dimensional.finite_dimensional_pi' FiniteDimensional.finiteDimensional_pi'
/-- A finite dimensional vector space over a finite field is finite -/
noncomputable def fintypeOfFintype [Fintype K] [FiniteDimensional K V] : Fintype V :=
Module.fintypeOfFintype (@finsetBasis K V _ _ _ (iff_fg.2 inferInstance))
#align finite_dimensional.fintype_of_fintype FiniteDimensional.fintypeOfFintype
theorem finite_of_finite [Finite K] [FiniteDimensional K V] : Finite V := by
cases nonempty_fintype K
haveI := fintypeOfFintype K V
infer_instance
#align finite_dimensional.finite_of_finite FiniteDimensional.finite_of_finite
variable {K V}
/-- If a vector space has a finite basis, then it is finite-dimensional. -/
theorem of_fintype_basis {ι : Type w} [Finite ι] (h : Basis ι K V) : FiniteDimensional K V :=
Module.Finite.of_basis h
#align finite_dimensional.of_fintype_basis FiniteDimensional.of_fintype_basis
/-- If a vector space is `FiniteDimensional`, all bases are indexed by a finite type -/
noncomputable def fintypeBasisIndex {ι : Type*} [FiniteDimensional K V] (b : Basis ι K V) :
Fintype ι :=
@Fintype.ofFinite _ (Module.Finite.finite_basis b)
#align finite_dimensional.fintype_basis_index FiniteDimensional.fintypeBasisIndex
/-- If a vector space is `FiniteDimensional`, `Basis.ofVectorSpace` is indexed by
a finite type. -/
noncomputable instance [FiniteDimensional K V] : Fintype (Basis.ofVectorSpaceIndex K V) := by
letI : IsNoetherian K V := IsNoetherian.iff_fg.2 inferInstance
infer_instance
/-- If a vector space has a basis indexed by elements of a finite set, then it is
finite-dimensional. -/
theorem of_finite_basis {ι : Type w} {s : Set ι} (h : Basis s K V) (hs : Set.Finite s) :
FiniteDimensional K V :=
haveI := hs.fintype
of_fintype_basis h
#align finite_dimensional.of_finite_basis FiniteDimensional.of_finite_basis
/-- A subspace of a finite-dimensional space is also finite-dimensional. -/
instance finiteDimensional_submodule [FiniteDimensional K V] (S : Submodule K V) :
FiniteDimensional K S := by
letI : IsNoetherian K V := iff_fg.2 ?_
· exact
iff_fg.1
(IsNoetherian.iff_rank_lt_aleph0.2
(lt_of_le_of_lt (rank_submodule_le _) (_root_.rank_lt_aleph0 K V)))
· infer_instance
#align finite_dimensional.finite_dimensional_submodule FiniteDimensional.finiteDimensional_submodule
/-- A quotient of a finite-dimensional space is also finite-dimensional. -/
instance finiteDimensional_quotient [FiniteDimensional K V] (S : Submodule K V) :
FiniteDimensional K (V ⧸ S) :=
Module.Finite.quotient K S
#align finite_dimensional.finite_dimensional_quotient FiniteDimensional.finiteDimensional_quotient
variable (K V)
/-- In a finite-dimensional space, its dimension (seen as a cardinal) coincides with its
`finrank`. This is a copy of `finrank_eq_rank _ _` which creates easier typeclass searches. -/
theorem finrank_eq_rank' [FiniteDimensional K V] : (finrank K V : Cardinal.{v}) = Module.rank K V :=
finrank_eq_rank _ _
#align finite_dimensional.finrank_eq_rank' FiniteDimensional.finrank_eq_rank'
variable {K V}
theorem finrank_of_infinite_dimensional (h : ¬FiniteDimensional K V) : finrank K V = 0 :=
FiniteDimensional.finrank_of_not_finite h
#align finite_dimensional.finrank_of_infinite_dimensional FiniteDimensional.finrank_of_infinite_dimensional
theorem of_finrank_pos (h : 0 < finrank K V) : FiniteDimensional K V :=
Module.finite_of_finrank_pos h
#align finite_dimensional.finite_dimensional_of_finrank FiniteDimensional.of_finrank_pos
theorem of_finrank_eq_succ {n : ℕ} (hn : finrank K V = n.succ) :
FiniteDimensional K V :=
Module.finite_of_finrank_eq_succ hn
#align finite_dimensional.finite_dimensional_of_finrank_eq_succ FiniteDimensional.of_finrank_eq_succ
/-- We can infer `FiniteDimensional K V` in the presence of `[Fact (finrank K V = n + 1)]`. Declare
this as a local instance where needed. -/
theorem of_fact_finrank_eq_succ (n : ℕ) [hn : Fact (finrank K V = n + 1)] :
FiniteDimensional K V :=
of_finrank_eq_succ hn.out
#align finite_dimensional.fact_finite_dimensional_of_finrank_eq_succ FiniteDimensional.of_fact_finrank_eq_succ
theorem finiteDimensional_iff_of_rank_eq_nsmul {W} [AddCommGroup W] [Module K W] {n : ℕ}
(hn : n ≠ 0) (hVW : Module.rank K V = n • Module.rank K W) :
FiniteDimensional K V ↔ FiniteDimensional K W :=
Module.finite_iff_of_rank_eq_nsmul hn hVW
#align finite_dimensional.finite_dimensional_iff_of_rank_eq_nsmul FiniteDimensional.finiteDimensional_iff_of_rank_eq_nsmul
/-- If a vector space is finite-dimensional, then the cardinality of any basis is equal to its
`finrank`. -/
theorem finrank_eq_card_basis' [FiniteDimensional K V] {ι : Type w} (h : Basis ι K V) :
(finrank K V : Cardinal.{w}) = #ι :=
Module.mk_finrank_eq_card_basis h
#align finite_dimensional.finrank_eq_card_basis' FiniteDimensional.finrank_eq_card_basis'
theorem _root_.LinearIndependent.lt_aleph0_of_finiteDimensional {ι : Type w} [FiniteDimensional K V]
{v : ι → V} (h : LinearIndependent K v) : #ι < ℵ₀ :=
h.lt_aleph0_of_finite
#align finite_dimensional.lt_aleph_0_of_linear_independent LinearIndependent.lt_aleph0_of_finiteDimensional
@[deprecated (since := "2023-12-27")]
alias lt_aleph0_of_linearIndependent := LinearIndependent.lt_aleph0_of_finiteDimensional
/-- If a submodule has maximal dimension in a finite dimensional space, then it is equal to the
whole space. -/
theorem _root_.Submodule.eq_top_of_finrank_eq [FiniteDimensional K V] {S : Submodule K V}
(h : finrank K S = finrank K V) : S = ⊤ := by
haveI : IsNoetherian K V := iff_fg.2 inferInstance
set bS := Basis.ofVectorSpace K S with bS_eq
have : LinearIndependent K ((↑) : ((↑) '' Basis.ofVectorSpaceIndex K S : Set V) → V) :=
LinearIndependent.image_subtype (f := Submodule.subtype S)
(by simpa [bS] using bS.linearIndependent) (by simp)
set b := Basis.extend this with b_eq
-- Porting note: `letI` now uses `this` so we need to give different names
letI i1 : Fintype (this.extend _) :=
(LinearIndependent.set_finite_of_isNoetherian (by simpa [b] using b.linearIndependent)).fintype
letI i2 : Fintype (((↑) : S → V) '' Basis.ofVectorSpaceIndex K S) :=
(LinearIndependent.set_finite_of_isNoetherian this).fintype
letI i3 : Fintype (Basis.ofVectorSpaceIndex K S) :=
(LinearIndependent.set_finite_of_isNoetherian
(by simpa [bS] using bS.linearIndependent)).fintype
have : (↑) '' Basis.ofVectorSpaceIndex K S = this.extend (Set.subset_univ _) :=
Set.eq_of_subset_of_card_le (this.subset_extend _)
(by
rw [Set.card_image_of_injective _ Subtype.coe_injective, ← finrank_eq_card_basis bS, ←
finrank_eq_card_basis b, h])
rw [← b.span_eq, b_eq, Basis.coe_extend, Subtype.range_coe, ← this, ← Submodule.coeSubtype,
span_image]
have := bS.span_eq
rw [bS_eq, Basis.coe_ofVectorSpace, Subtype.range_coe] at this
rw [this, Submodule.map_top (Submodule.subtype S), range_subtype]
#align finite_dimensional.eq_top_of_finrank_eq Submodule.eq_top_of_finrank_eq
#align submodule.eq_top_of_finrank_eq Submodule.eq_top_of_finrank_eq
variable (K)
instance finiteDimensional_self : FiniteDimensional K K := inferInstance
#align finite_dimensional.finite_dimensional_self FiniteDimensional.finiteDimensional_self
/-- The submodule generated by a finite set is finite-dimensional. -/
theorem span_of_finite {A : Set V} (hA : Set.Finite A) : FiniteDimensional K (Submodule.span K A) :=
Module.Finite.span_of_finite K hA
#align finite_dimensional.span_of_finite FiniteDimensional.span_of_finite
/-- The submodule generated by a single element is finite-dimensional. -/
instance span_singleton (x : V) : FiniteDimensional K (K ∙ x) :=
Module.Finite.span_singleton K x
#align finite_dimensional.span_singleton FiniteDimensional.span_singleton
/-- The submodule generated by a finset is finite-dimensional. -/
instance span_finset (s : Finset V) : FiniteDimensional K (span K (s : Set V)) :=
Module.Finite.span_finset K s
#align finite_dimensional.span_finset FiniteDimensional.span_finset
/-- Pushforwards of finite-dimensional submodules are finite-dimensional. -/
instance (f : V →ₗ[K] V₂) (p : Submodule K V) [FiniteDimensional K p] :
FiniteDimensional K (p.map f) :=
Module.Finite.map _ _
variable {K}
section
open Finset
section
variable {L : Type*} [LinearOrderedField L]
variable {W : Type v} [AddCommGroup W] [Module L W]
/-- A slight strengthening of `exists_nontrivial_relation_sum_zero_of_rank_succ_lt_card`
available when working over an ordered field:
we can ensure a positive coefficient, not just a nonzero coefficient.
-/
theorem exists_relation_sum_zero_pos_coefficient_of_finrank_succ_lt_card [FiniteDimensional L W]
{t : Finset W} (h : finrank L W + 1 < t.card) :
∃ f : W → L, ∑ e ∈ t, f e • e = 0 ∧ ∑ e ∈ t, f e = 0 ∧ ∃ x ∈ t, 0 < f x := by
obtain ⟨f, sum, total, nonzero⟩ :=
Module.exists_nontrivial_relation_sum_zero_of_finrank_succ_lt_card h
exact ⟨f, sum, total, exists_pos_of_sum_zero_of_exists_nonzero f total nonzero⟩
#align finite_dimensional.exists_relation_sum_zero_pos_coefficient_of_rank_succ_lt_card FiniteDimensional.exists_relation_sum_zero_pos_coefficient_of_finrank_succ_lt_card
end
end
/-- In a vector space with dimension 1, each set {v} is a basis for `v ≠ 0`. -/
@[simps repr_apply]
noncomputable def basisSingleton (ι : Type*) [Unique ι] (h : finrank K V = 1) (v : V)
(hv : v ≠ 0) : Basis ι K V :=
let b := FiniteDimensional.basisUnique ι h
let h : b.repr v default ≠ 0 := mt FiniteDimensional.basisUnique_repr_eq_zero_iff.mp hv
Basis.ofRepr
{ toFun := fun w => Finsupp.single default (b.repr w default / b.repr v default)
invFun := fun f => f default • v
map_add' := by simp [add_div]
map_smul' := by simp [mul_div]
left_inv := fun w => by
apply_fun b.repr using b.repr.toEquiv.injective
apply_fun Equiv.finsuppUnique
simp only [LinearEquiv.map_smulₛₗ, Finsupp.coe_smul, Finsupp.single_eq_same,
smul_eq_mul, Pi.smul_apply, Equiv.finsuppUnique_apply]
exact div_mul_cancel₀ _ h
right_inv := fun f => by
ext
simp only [LinearEquiv.map_smulₛₗ, Finsupp.coe_smul, Finsupp.single_eq_same,
RingHom.id_apply, smul_eq_mul, Pi.smul_apply]
exact mul_div_cancel_right₀ _ h }
#align finite_dimensional.basis_singleton FiniteDimensional.basisSingleton
@[simp]
theorem basisSingleton_apply (ι : Type*) [Unique ι] (h : finrank K V = 1) (v : V) (hv : v ≠ 0)
(i : ι) : basisSingleton ι h v hv i = v := by
cases Unique.uniq ‹Unique ι› i
simp [basisSingleton]
#align finite_dimensional.basis_singleton_apply FiniteDimensional.basisSingleton_apply
@[simp]
theorem range_basisSingleton (ι : Type*) [Unique ι] (h : finrank K V = 1) (v : V) (hv : v ≠ 0) :
Set.range (basisSingleton ι h v hv) = {v} := by rw [Set.range_unique, basisSingleton_apply]
#align finite_dimensional.range_basis_singleton FiniteDimensional.range_basisSingleton
end DivisionRing
section Tower
variable (F K A : Type*) [DivisionRing F] [DivisionRing K] [AddCommGroup A]
variable [Module F K] [Module K A] [Module F A] [IsScalarTower F K A]
theorem trans [FiniteDimensional F K] [FiniteDimensional K A] : FiniteDimensional F A :=
Module.Finite.trans K A
#align finite_dimensional.trans FiniteDimensional.trans
end Tower
end FiniteDimensional
section ZeroRank
variable [DivisionRing K] [AddCommGroup V] [Module K V]
open FiniteDimensional
theorem FiniteDimensional.of_rank_eq_nat {n : ℕ} (h : Module.rank K V = n) :
FiniteDimensional K V :=
Module.finite_of_rank_eq_nat h
#align finite_dimensional_of_rank_eq_nat FiniteDimensional.of_rank_eq_nat
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_rank_eq_nat := FiniteDimensional.of_rank_eq_nat
theorem FiniteDimensional.of_rank_eq_zero (h : Module.rank K V = 0) : FiniteDimensional K V :=
Module.finite_of_rank_eq_zero h
#align finite_dimensional_of_rank_eq_zero FiniteDimensional.of_rank_eq_zero
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_rank_eq_zero := FiniteDimensional.of_rank_eq_zero
theorem FiniteDimensional.of_rank_eq_one (h : Module.rank K V = 1) : FiniteDimensional K V :=
Module.finite_of_rank_eq_one h
#align finite_dimensional_of_rank_eq_one FiniteDimensional.of_rank_eq_one
@[deprecated (since := "2024-02-02")]
alias finiteDimensional_of_rank_eq_one := FiniteDimensional.of_rank_eq_one
variable (K V)
instance finiteDimensional_bot : FiniteDimensional K (⊥ : Submodule K V) :=
of_rank_eq_zero <| by simp
#align finite_dimensional_bot finiteDimensional_bot
variable {K V}
end ZeroRank
namespace Submodule
open IsNoetherian FiniteDimensional
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V]
/-- A submodule is finitely generated if and only if it is finite-dimensional -/
theorem fg_iff_finiteDimensional (s : Submodule K V) : s.FG ↔ FiniteDimensional K s :=
⟨fun h => Module.finite_def.2 <| (fg_top s).2 h, fun h => (fg_top s).1 <| Module.finite_def.1 h⟩
#align submodule.fg_iff_finite_dimensional Submodule.fg_iff_finiteDimensional
/-- A submodule contained in a finite-dimensional submodule is
finite-dimensional. -/
theorem finiteDimensional_of_le {S₁ S₂ : Submodule K V} [FiniteDimensional K S₂] (h : S₁ ≤ S₂) :
FiniteDimensional K S₁ :=
haveI : IsNoetherian K S₂ := iff_fg.2 inferInstance
iff_fg.1
(IsNoetherian.iff_rank_lt_aleph0.2
(lt_of_le_of_lt (rank_le_of_submodule _ _ h) (rank_lt_aleph0 K S₂)))
#align submodule.finite_dimensional_of_le Submodule.finiteDimensional_of_le
/-- The inf of two submodules, the first finite-dimensional, is
finite-dimensional. -/
instance finiteDimensional_inf_left (S₁ S₂ : Submodule K V) [FiniteDimensional K S₁] :
FiniteDimensional K (S₁ ⊓ S₂ : Submodule K V) :=
finiteDimensional_of_le inf_le_left
#align submodule.finite_dimensional_inf_left Submodule.finiteDimensional_inf_left
/-- The inf of two submodules, the second finite-dimensional, is
finite-dimensional. -/
instance finiteDimensional_inf_right (S₁ S₂ : Submodule K V) [FiniteDimensional K S₂] :
FiniteDimensional K (S₁ ⊓ S₂ : Submodule K V) :=
finiteDimensional_of_le inf_le_right
#align submodule.finite_dimensional_inf_right Submodule.finiteDimensional_inf_right
/-- The sup of two finite-dimensional submodules is
finite-dimensional. -/
instance finiteDimensional_sup (S₁ S₂ : Submodule K V) [h₁ : FiniteDimensional K S₁]
[h₂ : FiniteDimensional K S₂] : FiniteDimensional K (S₁ ⊔ S₂ : Submodule K V) := by
unfold FiniteDimensional at *
rw [finite_def] at *
exact (fg_top _).2 (((fg_top S₁).1 h₁).sup ((fg_top S₂).1 h₂))
#align submodule.finite_dimensional_sup Submodule.finiteDimensional_sup
/-- The submodule generated by a finite supremum of finite dimensional submodules is
finite-dimensional.
Note that strictly this only needs `∀ i ∈ s, FiniteDimensional K (S i)`, but that doesn't
work well with typeclass search. -/
instance finiteDimensional_finset_sup {ι : Type*} (s : Finset ι) (S : ι → Submodule K V)
[∀ i, FiniteDimensional K (S i)] : FiniteDimensional K (s.sup S : Submodule K V) := by
refine
@Finset.sup_induction _ _ _ _ s S (fun i => FiniteDimensional K ↑i) (finiteDimensional_bot K V)
?_ fun i _ => by infer_instance
intro S₁ hS₁ S₂ hS₂
exact Submodule.finiteDimensional_sup S₁ S₂
#align submodule.finite_dimensional_finset_sup Submodule.finiteDimensional_finset_sup
/-- The submodule generated by a supremum of finite dimensional submodules, indexed by a finite
sort is finite-dimensional. -/
instance finiteDimensional_iSup {ι : Sort*} [Finite ι] (S : ι → Submodule K V)
[∀ i, FiniteDimensional K (S i)] : FiniteDimensional K ↑(⨆ i, S i) := by
cases nonempty_fintype (PLift ι)
rw [← iSup_plift_down, ← Finset.sup_univ_eq_iSup]
exact Submodule.finiteDimensional_finset_sup _ _
#align submodule.finite_dimensional_supr Submodule.finiteDimensional_iSup
/-- In a finite-dimensional vector space, the dimensions of a submodule and of the corresponding
quotient add up to the dimension of the space. -/
theorem finrank_quotient_add_finrank [FiniteDimensional K V] (s : Submodule K V) :
finrank K (V ⧸ s) + finrank K s = finrank K V := by
have := rank_quotient_add_rank s
rw [← finrank_eq_rank, ← finrank_eq_rank, ← finrank_eq_rank] at this
exact mod_cast this
#align submodule.finrank_quotient_add_finrank Submodule.finrank_quotient_add_finrank
/-- The dimension of a strict submodule is strictly bounded by the dimension of the ambient
space. -/
theorem finrank_lt [FiniteDimensional K V] {s : Submodule K V} (h : s < ⊤) :
finrank K s < finrank K V := by
rw [← s.finrank_quotient_add_finrank, add_comm]
exact Nat.lt_add_of_pos_right (finrank_pos_iff.mpr (Quotient.nontrivial_of_lt_top _ h))
#align submodule.finrank_lt Submodule.finrank_lt
/-- The sum of the dimensions of s + t and s ∩ t is the sum of the dimensions of s and t -/
theorem finrank_sup_add_finrank_inf_eq (s t : Submodule K V) [FiniteDimensional K s]
[FiniteDimensional K t] :
finrank K ↑(s ⊔ t) + finrank K ↑(s ⊓ t) = finrank K ↑s + finrank K ↑t := by
have key : Module.rank K ↑(s ⊔ t) + Module.rank K ↑(s ⊓ t) = Module.rank K s + Module.rank K t :=
rank_sup_add_rank_inf_eq s t
repeat rw [← finrank_eq_rank] at key
norm_cast at key
#align submodule.finrank_sup_add_finrank_inf_eq Submodule.finrank_sup_add_finrank_inf_eq
theorem finrank_add_le_finrank_add_finrank (s t : Submodule K V) [FiniteDimensional K s]
[FiniteDimensional K t] : finrank K (s ⊔ t : Submodule K V) ≤ finrank K s + finrank K t := by
rw [← finrank_sup_add_finrank_inf_eq]
exact self_le_add_right _ _
#align submodule.finrank_add_le_finrank_add_finrank Submodule.finrank_add_le_finrank_add_finrank
theorem eq_top_of_disjoint [FiniteDimensional K V] (s t : Submodule K V)
(hdim : finrank K s + finrank K t = finrank K V) (hdisjoint : Disjoint s t) : s ⊔ t = ⊤ := by
have h_finrank_inf : finrank K ↑(s ⊓ t) = 0 := by
rw [disjoint_iff_inf_le, le_bot_iff] at hdisjoint
rw [hdisjoint, finrank_bot]
apply eq_top_of_finrank_eq
rw [← hdim]
convert s.finrank_sup_add_finrank_inf_eq t
rw [h_finrank_inf]
rfl
#align submodule.eq_top_of_disjoint Submodule.eq_top_of_disjoint
theorem finrank_add_finrank_le_of_disjoint [FiniteDimensional K V]
{s t : Submodule K V} (hdisjoint : Disjoint s t) :
finrank K s + finrank K t ≤ finrank K V := by
rw [← Submodule.finrank_sup_add_finrank_inf_eq s t, hdisjoint.eq_bot, finrank_bot, add_zero]
exact Submodule.finrank_le _
end DivisionRing
end Submodule
namespace LinearEquiv
open FiniteDimensional
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- Finite dimensionality is preserved under linear equivalence. -/
protected theorem finiteDimensional (f : V ≃ₗ[K] V₂) [FiniteDimensional K V] :
FiniteDimensional K V₂ :=
Module.Finite.equiv f
#align linear_equiv.finite_dimensional LinearEquiv.finiteDimensional
variable {R M M₂ : Type*} [Ring R] [AddCommGroup M] [AddCommGroup M₂]
variable [Module R M] [Module R M₂]
end LinearEquiv
section
variable [DivisionRing K] [AddCommGroup V] [Module K V]
instance finiteDimensional_finsupp {ι : Type*} [Finite ι] [FiniteDimensional K V] :
FiniteDimensional K (ι →₀ V) :=
Module.Finite.finsupp
#align finite_dimensional_finsupp finiteDimensional_finsupp
end
namespace FiniteDimensional
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- If a submodule is contained in a finite-dimensional
submodule with the same or smaller dimension, they are equal. -/
theorem eq_of_le_of_finrank_le {S₁ S₂ : Submodule K V} [FiniteDimensional K S₂] (hle : S₁ ≤ S₂)
(hd : finrank K S₂ ≤ finrank K S₁) : S₁ = S₂ := by
rw [← LinearEquiv.finrank_eq (Submodule.comapSubtypeEquivOfLe hle)] at hd
exact le_antisymm hle (Submodule.comap_subtype_eq_top.1
(eq_top_of_finrank_eq (le_antisymm (comap (Submodule.subtype S₂) S₁).finrank_le hd)))
#align finite_dimensional.eq_of_le_of_finrank_le FiniteDimensional.eq_of_le_of_finrank_le
/-- If a submodule is contained in a finite-dimensional
submodule with the same dimension, they are equal. -/
theorem eq_of_le_of_finrank_eq {S₁ S₂ : Submodule K V} [FiniteDimensional K S₂] (hle : S₁ ≤ S₂)
(hd : finrank K S₁ = finrank K S₂) : S₁ = S₂ :=
eq_of_le_of_finrank_le hle hd.ge
#align finite_dimensional.eq_of_le_of_finrank_eq FiniteDimensional.eq_of_le_of_finrank_eq
section Subalgebra
variable {K L : Type*} [Field K] [Ring L] [Algebra K L] {F E : Subalgebra K L}
[hfin : FiniteDimensional K E] (h_le : F ≤ E)
/-- If a subalgebra is contained in a finite-dimensional
subalgebra with the same or smaller dimension, they are equal. -/
theorem _root_.Subalgebra.eq_of_le_of_finrank_le (h_finrank : finrank K E ≤ finrank K F) : F = E :=
haveI : Module.Finite K (Subalgebra.toSubmodule E) := hfin
Subalgebra.toSubmodule_injective <| FiniteDimensional.eq_of_le_of_finrank_le h_le h_finrank
/-- If a subalgebra is contained in a finite-dimensional
subalgebra with the same dimension, they are equal. -/
theorem _root_.Subalgebra.eq_of_le_of_finrank_eq (h_finrank : finrank K F = finrank K E) : F = E :=
Subalgebra.eq_of_le_of_finrank_le h_le h_finrank.ge
end Subalgebra
variable [FiniteDimensional K V] [FiniteDimensional K V₂]
/-- Given isomorphic subspaces `p q` of vector spaces `V` and `V₁` respectively,
`p.quotient` is isomorphic to `q.quotient`. -/
noncomputable def LinearEquiv.quotEquivOfEquiv {p : Subspace K V} {q : Subspace K V₂}
(f₁ : p ≃ₗ[K] q) (f₂ : V ≃ₗ[K] V₂) : (V ⧸ p) ≃ₗ[K] V₂ ⧸ q :=
LinearEquiv.ofFinrankEq _ _
(by
rw [← @add_right_cancel_iff _ _ _ (finrank K p), Submodule.finrank_quotient_add_finrank,
LinearEquiv.finrank_eq f₁, Submodule.finrank_quotient_add_finrank,
LinearEquiv.finrank_eq f₂])
#align finite_dimensional.linear_equiv.quot_equiv_of_equiv FiniteDimensional.LinearEquiv.quotEquivOfEquiv
-- TODO: generalize to the case where one of `p` and `q` is finite-dimensional.
/-- Given the subspaces `p q`, if `p.quotient ≃ₗ[K] q`, then `q.quotient ≃ₗ[K] p` -/
noncomputable def LinearEquiv.quotEquivOfQuotEquiv {p q : Subspace K V} (f : (V ⧸ p) ≃ₗ[K] q) :
(V ⧸ q) ≃ₗ[K] p :=
LinearEquiv.ofFinrankEq _ _ <|
add_right_cancel <| by
rw [Submodule.finrank_quotient_add_finrank, ← LinearEquiv.finrank_eq f, add_comm,
Submodule.finrank_quotient_add_finrank]
#align finite_dimensional.linear_equiv.quot_equiv_of_quot_equiv FiniteDimensional.LinearEquiv.quotEquivOfQuotEquiv
end DivisionRing
end FiniteDimensional
namespace LinearMap
open FiniteDimensional
section DivisionRing
variable [DivisionRing K] [AddCommGroup V] [Module K V] {V₂ : Type v'} [AddCommGroup V₂]
[Module K V₂]
/-- On a finite-dimensional space, an injective linear map is surjective. -/
theorem surjective_of_injective [FiniteDimensional K V] {f : V →ₗ[K] V} (hinj : Injective f) :
Surjective f := by
have h := rank_range_of_injective _ hinj
rw [← finrank_eq_rank, ← finrank_eq_rank, natCast_inj] at h
exact range_eq_top.1 (eq_top_of_finrank_eq h)
#align linear_map.surjective_of_injective LinearMap.surjective_of_injective
/-- The image under an onto linear map of a finite-dimensional space is also finite-dimensional. -/
theorem finiteDimensional_of_surjective [FiniteDimensional K V] (f : V →ₗ[K] V₂)
(hf : LinearMap.range f = ⊤) : FiniteDimensional K V₂ :=
Module.Finite.of_surjective f <| range_eq_top.1 hf
#align linear_map.finite_dimensional_of_surjective LinearMap.finiteDimensional_of_surjective
/-- The range of a linear map defined on a finite-dimensional space is also finite-dimensional. -/
instance finiteDimensional_range [FiniteDimensional K V] (f : V →ₗ[K] V₂) :
FiniteDimensional K (LinearMap.range f) :=
Module.Finite.range f
#align linear_map.finite_dimensional_range LinearMap.finiteDimensional_range
/-- On a finite-dimensional space, a linear map is injective if and only if it is surjective. -/
theorem injective_iff_surjective [FiniteDimensional K V] {f : V →ₗ[K] V} :
Injective f ↔ Surjective f :=
⟨surjective_of_injective, fun hsurj =>
let ⟨g, hg⟩ := f.exists_rightInverse_of_surjective (range_eq_top.2 hsurj)
have : Function.RightInverse g f := LinearMap.ext_iff.1 hg
(leftInverse_of_surjective_of_rightInverse (surjective_of_injective this.injective)
this).injective⟩
#align linear_map.injective_iff_surjective LinearMap.injective_iff_surjective
lemma injOn_iff_surjOn {p : Submodule K V} [FiniteDimensional K p]
{f : V →ₗ[K] V} (h : ∀ x ∈ p, f x ∈ p) :
Set.InjOn f p ↔ Set.SurjOn f p p := by
rw [Set.injOn_iff_injective, ← Set.MapsTo.restrict_surjective_iff h]
change Injective (f.domRestrict p) ↔ Surjective (f.restrict h)
simp [disjoint_iff, ← injective_iff_surjective]
theorem ker_eq_bot_iff_range_eq_top [FiniteDimensional K V] {f : V →ₗ[K] V} :
LinearMap.ker f = ⊥ ↔ LinearMap.range f = ⊤ := by
rw [range_eq_top, ker_eq_bot, injective_iff_surjective]
#align linear_map.ker_eq_bot_iff_range_eq_top LinearMap.ker_eq_bot_iff_range_eq_top
/-- In a finite-dimensional space, if linear maps are inverse to each other on one side then they
are also inverse to each other on the other side. -/
theorem mul_eq_one_of_mul_eq_one [FiniteDimensional K V] {f g : V →ₗ[K] V} (hfg : f * g = 1) :
g * f = 1 := by
have ginj : Injective g :=
HasLeftInverse.injective ⟨f, fun x => show (f * g) x = (1 : V →ₗ[K] V) x by rw [hfg]⟩
let ⟨i, hi⟩ :=
g.exists_rightInverse_of_surjective (range_eq_top.2 (injective_iff_surjective.1 ginj))
have : f * (g * i) = f * 1 := congr_arg _ hi
rw [← mul_assoc, hfg, one_mul, mul_one] at this; rwa [← this]
#align linear_map.mul_eq_one_of_mul_eq_one LinearMap.mul_eq_one_of_mul_eq_one
/-- In a finite-dimensional space, linear maps are inverse to each other on one side if and only if
they are inverse to each other on the other side. -/
theorem mul_eq_one_comm [FiniteDimensional K V] {f g : V →ₗ[K] V} : f * g = 1 ↔ g * f = 1 :=
⟨mul_eq_one_of_mul_eq_one, mul_eq_one_of_mul_eq_one⟩
#align linear_map.mul_eq_one_comm LinearMap.mul_eq_one_comm
/-- In a finite-dimensional space, linear maps are inverse to each other on one side if and only if
they are inverse to each other on the other side. -/
theorem comp_eq_id_comm [FiniteDimensional K V] {f g : V →ₗ[K] V} : f.comp g = id ↔ g.comp f = id :=
mul_eq_one_comm
#align linear_map.comp_eq_id_comm LinearMap.comp_eq_id_comm
/-- rank-nullity theorem : the dimensions of the kernel and the range of a linear map add up to
the dimension of the source space. -/
theorem finrank_range_add_finrank_ker [FiniteDimensional K V] (f : V →ₗ[K] V₂) :
finrank K (LinearMap.range f) + finrank K (LinearMap.ker f) = finrank K V := by
rw [← f.quotKerEquivRange.finrank_eq]
exact Submodule.finrank_quotient_add_finrank _
#align linear_map.finrank_range_add_finrank_ker LinearMap.finrank_range_add_finrank_ker
lemma ker_ne_bot_of_finrank_lt [FiniteDimensional K V] [FiniteDimensional K V₂] {f : V →ₗ[K] V₂}
(h : finrank K V₂ < finrank K V) :
LinearMap.ker f ≠ ⊥ := by
have h₁ := f.finrank_range_add_finrank_ker
have h₂ : finrank K (LinearMap.range f) ≤ finrank K V₂ := (LinearMap.range f).finrank_le
suffices 0 < finrank K (LinearMap.ker f) from Submodule.one_le_finrank_iff.mp this
omega
theorem comap_eq_sup_ker_of_disjoint {p : Submodule K V} [FiniteDimensional K p] {f : V →ₗ[K] V}
(h : ∀ x ∈ p, f x ∈ p) (h' : Disjoint p (ker f)) :
p.comap f = p ⊔ ker f := by
refine le_antisymm (fun x hx ↦ ?_) (sup_le_iff.mpr ⟨h, ker_le_comap _⟩)
obtain ⟨⟨y, hy⟩, hxy⟩ :=
surjective_of_injective ((injective_restrict_iff_disjoint h).mpr h') ⟨f x, hx⟩
replace hxy : f y = f x := by simpa [Subtype.ext_iff] using hxy
exact Submodule.mem_sup.mpr ⟨y, hy, x - y, by simp [hxy], add_sub_cancel y x⟩
theorem ker_comp_eq_of_commute_of_disjoint_ker [FiniteDimensional K V] {f g : V →ₗ[K] V}
(h : Commute f g) (h' : Disjoint (ker f) (ker g)) :
ker (f ∘ₗ g) = ker f ⊔ ker g := by
suffices ∀ x, f x = 0 → f (g x) = 0 by rw [ker_comp, comap_eq_sup_ker_of_disjoint _ h']; simpa
intro x hx
rw [← comp_apply, ← mul_eq_comp, h.eq, mul_apply, hx, _root_.map_zero]
theorem ker_noncommProd_eq_of_supIndep_ker [FiniteDimensional K V] {ι : Type*} {f : ι → V →ₗ[K] V}
(s : Finset ι) (comm) (h : s.SupIndep fun i ↦ ker (f i)) :
ker (s.noncommProd f comm) = ⨆ i ∈ s, ker (f i) := by
classical
induction' s using Finset.induction_on with i s hi ih
· set_option tactic.skipAssignedInstances false in
simpa using LinearMap.ker_id
replace ih : ker (Finset.noncommProd s f <| Set.Pairwise.mono (s.subset_insert i) comm) =
⨆ x ∈ s, ker (f x) := ih _ (h.subset (s.subset_insert i))
rw [Finset.noncommProd_insert_of_not_mem _ _ _ _ hi, mul_eq_comp,
ker_comp_eq_of_commute_of_disjoint_ker]
· simp_rw [Finset.mem_insert_coe, iSup_insert, Finset.mem_coe, ih]
· exact s.noncommProd_commute _ _ _ fun j hj ↦
comm (s.mem_insert_self i) (Finset.mem_insert_of_mem hj) (by aesop)
· replace h := Finset.supIndep_iff_disjoint_erase.mp h i (s.mem_insert_self i)
simpa [ih, hi, Finset.sup_eq_iSup] using h
end DivisionRing
end LinearMap
namespace LinearEquiv
open FiniteDimensional
variable [DivisionRing K] [AddCommGroup V] [Module K V]
variable [FiniteDimensional K V]
/-- The linear equivalence corresponding to an injective endomorphism. -/
noncomputable def ofInjectiveEndo (f : V →ₗ[K] V) (h_inj : Injective f) : V ≃ₗ[K] V :=
LinearEquiv.ofBijective f ⟨h_inj, LinearMap.injective_iff_surjective.mp h_inj⟩
#align linear_equiv.of_injective_endo LinearEquiv.ofInjectiveEndo
@[simp]
theorem coe_ofInjectiveEndo (f : V →ₗ[K] V) (h_inj : Injective f) :
⇑(ofInjectiveEndo f h_inj) = f :=
rfl
#align linear_equiv.coe_of_injective_endo LinearEquiv.coe_ofInjectiveEndo
@[simp]
theorem ofInjectiveEndo_right_inv (f : V →ₗ[K] V) (h_inj : Injective f) :
f * (ofInjectiveEndo f h_inj).symm = 1 :=
LinearMap.ext <| (ofInjectiveEndo f h_inj).apply_symm_apply
#align linear_equiv.of_injective_endo_right_inv LinearEquiv.ofInjectiveEndo_right_inv
@[simp]
theorem ofInjectiveEndo_left_inv (f : V →ₗ[K] V) (h_inj : Injective f) :
((ofInjectiveEndo f h_inj).symm : V →ₗ[K] V) * f = 1 :=
LinearMap.ext <| (ofInjectiveEndo f h_inj).symm_apply_apply
#align linear_equiv.of_injective_endo_left_inv LinearEquiv.ofInjectiveEndo_left_inv
end LinearEquiv
namespace LinearMap
variable [DivisionRing K] [AddCommGroup V] [Module K V]
theorem isUnit_iff_ker_eq_bot [FiniteDimensional K V] (f : V →ₗ[K] V) :
IsUnit f ↔ (LinearMap.ker f) = ⊥ := by
constructor
· rintro ⟨u, rfl⟩
exact LinearMap.ker_eq_bot_of_inverse u.inv_mul
· intro h_inj
rw [ker_eq_bot] at h_inj
exact ⟨⟨f, (LinearEquiv.ofInjectiveEndo f h_inj).symm.toLinearMap,
LinearEquiv.ofInjectiveEndo_right_inv f h_inj, LinearEquiv.ofInjectiveEndo_left_inv f h_inj⟩,
rfl⟩
#align linear_map.is_unit_iff_ker_eq_bot LinearMap.isUnit_iff_ker_eq_bot
| Mathlib/LinearAlgebra/FiniteDimensional.lean | 793 | 795 | theorem isUnit_iff_range_eq_top [FiniteDimensional K V] (f : V →ₗ[K] V) :
IsUnit f ↔ (LinearMap.range f) = ⊤ := by |
rw [isUnit_iff_ker_eq_bot, ker_eq_bot_iff_range_eq_top]
|
/-
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.Data.Fintype.Parity
import Mathlib.NumberTheory.LegendreSymbol.ZModChar
import Mathlib.FieldTheory.Finite.Basic
#align_import number_theory.legendre_symbol.quadratic_char.basic from "leanprover-community/mathlib"@"5b2fe80501ff327b9109fb09b7cc8c325cd0d7d9"
/-!
# Quadratic characters of finite fields
This file defines the quadratic character on a finite field `F` and proves
some basic statements about it.
## Tags
quadratic character
-/
/-!
### Definition of the quadratic character
We define the quadratic character of a finite field `F` with values in ℤ.
-/
section Define
/-- Define the quadratic character with values in ℤ on a monoid with zero `α`.
It takes the value zero at zero; for non-zero argument `a : α`, it is `1`
if `a` is a square, otherwise it is `-1`.
This only deserves the name "character" when it is multiplicative,
e.g., when `α` is a finite field. See `quadraticCharFun_mul`.
We will later define `quadraticChar` to be a multiplicative character
of type `MulChar F ℤ`, when the domain is a finite field `F`.
-/
def quadraticCharFun (α : Type*) [MonoidWithZero α] [DecidableEq α]
[DecidablePred (IsSquare : α → Prop)] (a : α) : ℤ :=
if a = 0 then 0 else if IsSquare a then 1 else -1
#align quadratic_char_fun quadraticCharFun
end Define
/-!
### Basic properties of the quadratic character
We prove some properties of the quadratic character.
We work with a finite field `F` here.
The interesting case is when the characteristic of `F` is odd.
-/
section quadraticChar
open MulChar
variable {F : Type*} [Field F] [Fintype F] [DecidableEq F]
/-- Some basic API lemmas -/
theorem quadraticCharFun_eq_zero_iff {a : F} : quadraticCharFun F a = 0 ↔ a = 0 := by
simp only [quadraticCharFun]
by_cases ha : a = 0
· simp only [ha, eq_self_iff_true, if_true]
· simp only [ha, if_false, iff_false_iff]
split_ifs <;> simp only [neg_eq_zero, one_ne_zero, not_false_iff]
#align quadratic_char_fun_eq_zero_iff quadraticCharFun_eq_zero_iff
@[simp]
theorem quadraticCharFun_zero : quadraticCharFun F 0 = 0 := by
simp only [quadraticCharFun, eq_self_iff_true, if_true, id]
#align quadratic_char_fun_zero quadraticCharFun_zero
@[simp]
theorem quadraticCharFun_one : quadraticCharFun F 1 = 1 := by
simp only [quadraticCharFun, one_ne_zero, isSquare_one, if_true, if_false, id]
#align quadratic_char_fun_one quadraticCharFun_one
/-- If `ringChar F = 2`, then `quadraticCharFun F` takes the value `1` on nonzero elements. -/
theorem quadraticCharFun_eq_one_of_char_two (hF : ringChar F = 2) {a : F} (ha : a ≠ 0) :
quadraticCharFun F a = 1 := by
simp only [quadraticCharFun, ha, if_false, ite_eq_left_iff]
exact fun h => (h (FiniteField.isSquare_of_char_two hF a)).elim
#align quadratic_char_fun_eq_one_of_char_two quadraticCharFun_eq_one_of_char_two
/-- If `ringChar F` is odd, then `quadraticCharFun F a` can be computed in
terms of `a ^ (Fintype.card F / 2)`. -/
theorem quadraticCharFun_eq_pow_of_char_ne_two (hF : ringChar F ≠ 2) {a : F} (ha : a ≠ 0) :
quadraticCharFun F a = if a ^ (Fintype.card F / 2) = 1 then 1 else -1 := by
simp only [quadraticCharFun, ha, if_false]
simp_rw [FiniteField.isSquare_iff hF ha]
#align quadratic_char_fun_eq_pow_of_char_ne_two quadraticCharFun_eq_pow_of_char_ne_two
/-- The quadratic character is multiplicative. -/
theorem quadraticCharFun_mul (a b : F) :
quadraticCharFun F (a * b) = quadraticCharFun F a * quadraticCharFun F b := by
by_cases ha : a = 0
· rw [ha, zero_mul, quadraticCharFun_zero, zero_mul]
-- now `a ≠ 0`
by_cases hb : b = 0
· rw [hb, mul_zero, quadraticCharFun_zero, mul_zero]
-- now `a ≠ 0` and `b ≠ 0`
have hab := mul_ne_zero ha hb
by_cases hF : ringChar F = 2
·-- case `ringChar F = 2`
rw [quadraticCharFun_eq_one_of_char_two hF ha, quadraticCharFun_eq_one_of_char_two hF hb,
quadraticCharFun_eq_one_of_char_two hF hab, mul_one]
· -- case of odd characteristic
rw [quadraticCharFun_eq_pow_of_char_ne_two hF ha, quadraticCharFun_eq_pow_of_char_ne_two hF hb,
quadraticCharFun_eq_pow_of_char_ne_two hF hab, mul_pow]
cases' FiniteField.pow_dichotomy hF hb with hb' hb'
· simp only [hb', mul_one, eq_self_iff_true, if_true]
· have h := Ring.neg_one_ne_one_of_char_ne_two hF
-- `-1 ≠ 1`
simp only [hb', h, mul_neg, mul_one, if_false, ite_mul, neg_mul]
cases' FiniteField.pow_dichotomy hF ha with ha' ha' <;>
simp only [ha', h, neg_neg, eq_self_iff_true, if_true, if_false]
#align quadratic_char_fun_mul quadraticCharFun_mul
variable (F)
/-- The quadratic character as a multiplicative character. -/
@[simps]
def quadraticChar : MulChar F ℤ where
toFun := quadraticCharFun F
map_one' := quadraticCharFun_one
map_mul' := quadraticCharFun_mul
map_nonunit' a ha := by rw [of_not_not (mt Ne.isUnit ha)]; exact quadraticCharFun_zero
#align quadratic_char quadraticChar
variable {F}
/-- The value of the quadratic character on `a` is zero iff `a = 0`. -/
theorem quadraticChar_eq_zero_iff {a : F} : quadraticChar F a = 0 ↔ a = 0 :=
quadraticCharFun_eq_zero_iff
#align quadratic_char_eq_zero_iff quadraticChar_eq_zero_iff
-- @[simp] -- Porting note (#10618): simp can prove this
| Mathlib/NumberTheory/LegendreSymbol/QuadraticChar/Basic.lean | 144 | 145 | theorem quadraticChar_zero : quadraticChar F 0 = 0 := by |
simp only [quadraticChar_apply, quadraticCharFun_zero]
|
/-
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.Basic
#align_import data.multiset.locally_finite from "leanprover-community/mathlib"@"59694bd07f0a39c5beccba34bd9f413a160782bf"
/-!
# Intervals as multisets
This file defines intervals as multisets.
## Main declarations
In a `LocallyFiniteOrder`,
* `Multiset.Icc`: Closed-closed interval as a multiset.
* `Multiset.Ico`: Closed-open interval as a multiset.
* `Multiset.Ioc`: Open-closed interval as a multiset.
* `Multiset.Ioo`: Open-open interval as a multiset.
In a `LocallyFiniteOrderTop`,
* `Multiset.Ici`: Closed-infinite interval as a multiset.
* `Multiset.Ioi`: Open-infinite interval as a multiset.
In a `LocallyFiniteOrderBot`,
* `Multiset.Iic`: Infinite-open interval as a multiset.
* `Multiset.Iio`: Infinite-closed interval as a multiset.
## TODO
Do we really need this file at all? (March 2024)
-/
variable {α : Type*}
namespace Multiset
section LocallyFiniteOrder
variable [Preorder α] [LocallyFiniteOrder α] {a b x : α}
/-- The multiset of elements `x` such that `a ≤ x` and `x ≤ b`. Basically `Set.Icc a b` as a
multiset. -/
def Icc (a b : α) : Multiset α := (Finset.Icc a b).val
#align multiset.Icc Multiset.Icc
/-- The multiset of elements `x` such that `a ≤ x` and `x < b`. Basically `Set.Ico a b` as a
multiset. -/
def Ico (a b : α) : Multiset α := (Finset.Ico a b).val
#align multiset.Ico Multiset.Ico
/-- The multiset of elements `x` such that `a < x` and `x ≤ b`. Basically `Set.Ioc a b` as a
multiset. -/
def Ioc (a b : α) : Multiset α := (Finset.Ioc a b).val
#align multiset.Ioc Multiset.Ioc
/-- The multiset of elements `x` such that `a < x` and `x < b`. Basically `Set.Ioo a b` as a
multiset. -/
def Ioo (a b : α) : Multiset α := (Finset.Ioo a b).val
#align multiset.Ioo Multiset.Ioo
@[simp] lemma mem_Icc : x ∈ Icc a b ↔ a ≤ x ∧ x ≤ b := by rw [Icc, ← Finset.mem_def, Finset.mem_Icc]
#align multiset.mem_Icc Multiset.mem_Icc
@[simp] lemma mem_Ico : x ∈ Ico a b ↔ a ≤ x ∧ x < b := by rw [Ico, ← Finset.mem_def, Finset.mem_Ico]
#align multiset.mem_Ico Multiset.mem_Ico
@[simp] lemma mem_Ioc : x ∈ Ioc a b ↔ a < x ∧ x ≤ b := by rw [Ioc, ← Finset.mem_def, Finset.mem_Ioc]
#align multiset.mem_Ioc Multiset.mem_Ioc
@[simp] lemma mem_Ioo : x ∈ Ioo a b ↔ a < x ∧ x < b := by rw [Ioo, ← Finset.mem_def, Finset.mem_Ioo]
#align multiset.mem_Ioo Multiset.mem_Ioo
end LocallyFiniteOrder
section LocallyFiniteOrderTop
variable [Preorder α] [LocallyFiniteOrderTop α] {a x : α}
/-- The multiset of elements `x` such that `a ≤ x`. Basically `Set.Ici a` as a multiset. -/
def Ici (a : α) : Multiset α := (Finset.Ici a).val
#align multiset.Ici Multiset.Ici
/-- The multiset of elements `x` such that `a < x`. Basically `Set.Ioi a` as a multiset. -/
def Ioi (a : α) : Multiset α := (Finset.Ioi a).val
#align multiset.Ioi Multiset.Ioi
@[simp] lemma mem_Ici : x ∈ Ici a ↔ a ≤ x := by rw [Ici, ← Finset.mem_def, Finset.mem_Ici]
#align multiset.mem_Ici Multiset.mem_Ici
@[simp] lemma mem_Ioi : x ∈ Ioi a ↔ a < x := by rw [Ioi, ← Finset.mem_def, Finset.mem_Ioi]
#align multiset.mem_Ioi Multiset.mem_Ioi
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [Preorder α] [LocallyFiniteOrderBot α] {b x : α}
/-- The multiset of elements `x` such that `x ≤ b`. Basically `Set.Iic b` as a multiset. -/
def Iic (b : α) : Multiset α := (Finset.Iic b).val
#align multiset.Iic Multiset.Iic
/-- The multiset of elements `x` such that `x < b`. Basically `Set.Iio b` as a multiset. -/
def Iio (b : α) : Multiset α := (Finset.Iio b).val
#align multiset.Iio Multiset.Iio
@[simp] lemma mem_Iic : x ∈ Iic b ↔ x ≤ b := by rw [Iic, ← Finset.mem_def, Finset.mem_Iic]
#align multiset.mem_Iic Multiset.mem_Iic
@[simp] lemma mem_Iio : x ∈ Iio b ↔ x < b := by rw [Iio, ← Finset.mem_def, Finset.mem_Iio]
#align multiset.mem_Iio Multiset.mem_Iio
end LocallyFiniteOrderBot
section Preorder
variable [Preorder α] [LocallyFiniteOrder α] {a b c : α}
theorem nodup_Icc : (Icc a b).Nodup :=
Finset.nodup _
#align multiset.nodup_Icc Multiset.nodup_Icc
theorem nodup_Ico : (Ico a b).Nodup :=
Finset.nodup _
#align multiset.nodup_Ico Multiset.nodup_Ico
theorem nodup_Ioc : (Ioc a b).Nodup :=
Finset.nodup _
#align multiset.nodup_Ioc Multiset.nodup_Ioc
theorem nodup_Ioo : (Ioo a b).Nodup :=
Finset.nodup _
#align multiset.nodup_Ioo Multiset.nodup_Ioo
@[simp]
theorem Icc_eq_zero_iff : Icc a b = 0 ↔ ¬a ≤ b := by
rw [Icc, Finset.val_eq_zero, Finset.Icc_eq_empty_iff]
#align multiset.Icc_eq_zero_iff Multiset.Icc_eq_zero_iff
@[simp]
theorem Ico_eq_zero_iff : Ico a b = 0 ↔ ¬a < b := by
rw [Ico, Finset.val_eq_zero, Finset.Ico_eq_empty_iff]
#align multiset.Ico_eq_zero_iff Multiset.Ico_eq_zero_iff
@[simp]
theorem Ioc_eq_zero_iff : Ioc a b = 0 ↔ ¬a < b := by
rw [Ioc, Finset.val_eq_zero, Finset.Ioc_eq_empty_iff]
#align multiset.Ioc_eq_zero_iff Multiset.Ioc_eq_zero_iff
@[simp]
theorem Ioo_eq_zero_iff [DenselyOrdered α] : Ioo a b = 0 ↔ ¬a < b := by
rw [Ioo, Finset.val_eq_zero, Finset.Ioo_eq_empty_iff]
#align multiset.Ioo_eq_zero_iff Multiset.Ioo_eq_zero_iff
alias ⟨_, Icc_eq_zero⟩ := Icc_eq_zero_iff
#align multiset.Icc_eq_zero Multiset.Icc_eq_zero
alias ⟨_, Ico_eq_zero⟩ := Ico_eq_zero_iff
#align multiset.Ico_eq_zero Multiset.Ico_eq_zero
alias ⟨_, Ioc_eq_zero⟩ := Ioc_eq_zero_iff
#align multiset.Ioc_eq_zero Multiset.Ioc_eq_zero
@[simp]
theorem Ioo_eq_zero (h : ¬a < b) : Ioo a b = 0 :=
eq_zero_iff_forall_not_mem.2 fun _x hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2)
#align multiset.Ioo_eq_zero Multiset.Ioo_eq_zero
@[simp]
theorem Icc_eq_zero_of_lt (h : b < a) : Icc a b = 0 :=
Icc_eq_zero h.not_le
#align multiset.Icc_eq_zero_of_lt Multiset.Icc_eq_zero_of_lt
@[simp]
theorem Ico_eq_zero_of_le (h : b ≤ a) : Ico a b = 0 :=
Ico_eq_zero h.not_lt
#align multiset.Ico_eq_zero_of_le Multiset.Ico_eq_zero_of_le
@[simp]
theorem Ioc_eq_zero_of_le (h : b ≤ a) : Ioc a b = 0 :=
Ioc_eq_zero h.not_lt
#align multiset.Ioc_eq_zero_of_le Multiset.Ioc_eq_zero_of_le
@[simp]
theorem Ioo_eq_zero_of_le (h : b ≤ a) : Ioo a b = 0 :=
Ioo_eq_zero h.not_lt
#align multiset.Ioo_eq_zero_of_le Multiset.Ioo_eq_zero_of_le
variable (a)
-- Porting note (#10618): simp can prove this -- @[simp]
theorem Ico_self : Ico a a = 0 := by rw [Ico, Finset.Ico_self, Finset.empty_val]
#align multiset.Ico_self Multiset.Ico_self
-- Porting note (#10618): simp can prove this -- @[simp]
theorem Ioc_self : Ioc a a = 0 := by rw [Ioc, Finset.Ioc_self, Finset.empty_val]
#align multiset.Ioc_self Multiset.Ioc_self
-- Porting note (#10618): simp can prove this -- @[simp]
theorem Ioo_self : Ioo a a = 0 := by rw [Ioo, Finset.Ioo_self, Finset.empty_val]
#align multiset.Ioo_self Multiset.Ioo_self
variable {a}
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b :=
Finset.left_mem_Icc
#align multiset.left_mem_Icc Multiset.left_mem_Icc
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b :=
Finset.left_mem_Ico
#align multiset.left_mem_Ico Multiset.left_mem_Ico
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b :=
Finset.right_mem_Icc
#align multiset.right_mem_Icc Multiset.right_mem_Icc
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b :=
Finset.right_mem_Ioc
#align multiset.right_mem_Ioc Multiset.right_mem_Ioc
-- Porting note (#10618): simp can prove this -- @[simp]
theorem left_not_mem_Ioc : a ∉ Ioc a b :=
Finset.left_not_mem_Ioc
#align multiset.left_not_mem_Ioc Multiset.left_not_mem_Ioc
-- Porting note (#10618): simp can prove this -- @[simp]
theorem left_not_mem_Ioo : a ∉ Ioo a b :=
Finset.left_not_mem_Ioo
#align multiset.left_not_mem_Ioo Multiset.left_not_mem_Ioo
-- Porting note (#10618): simp can prove this -- @[simp]
theorem right_not_mem_Ico : b ∉ Ico a b :=
Finset.right_not_mem_Ico
#align multiset.right_not_mem_Ico Multiset.right_not_mem_Ico
-- Porting note (#10618): simp can prove this -- @[simp]
theorem right_not_mem_Ioo : b ∉ Ioo a b :=
Finset.right_not_mem_Ioo
#align multiset.right_not_mem_Ioo Multiset.right_not_mem_Ioo
| Mathlib/Order/Interval/Multiset.lean | 243 | 246 | theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) :
((Ico a b).filter fun x => x < c) = ∅ := by |
rw [Ico, ← Finset.filter_val, Finset.Ico_filter_lt_of_le_left hca]
rfl
|
/-
Copyright (c) 2019 Jean Lo. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jean Lo, Bhavik Mehta, Yaël Dillies
-/
import Mathlib.Analysis.Convex.Basic
import Mathlib.Analysis.Convex.Hull
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Topology.Bornology.Absorbs
#align_import analysis.locally_convex.basic from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Local convexity
This file defines absorbent and balanced sets.
An absorbent set is one that "surrounds" the origin. The idea is made precise by requiring that any
point belongs to all large enough scalings of the set. This is the vector world analog of a
topological neighborhood of the origin.
A balanced set is one that is everywhere around the origin. This means that `a • s ⊆ s` for all `a`
of norm less than `1`.
## Main declarations
For a module over a normed ring:
* `Absorbs`: A set `s` absorbs a set `t` if all large scalings of `s` contain `t`.
* `Absorbent`: A set `s` is absorbent if every point eventually belongs to all large scalings of
`s`.
* `Balanced`: A set `s` is balanced if `a • s ⊆ s` for all `a` of norm less than `1`.
## References
* [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966]
## Tags
absorbent, balanced, locally convex, LCTVS
-/
open Set
open Pointwise Topology
variable {𝕜 𝕝 E : Type*} {ι : Sort*} {κ : ι → Sort*}
section SeminormedRing
variable [SeminormedRing 𝕜]
section SMul
variable [SMul 𝕜 E] {s t u v A B : Set E}
variable (𝕜)
/-- A set `A` is balanced if `a • A` is contained in `A` whenever `a` has norm at most `1`. -/
def Balanced (A : Set E) :=
∀ a : 𝕜, ‖a‖ ≤ 1 → a • A ⊆ A
#align balanced Balanced
variable {𝕜}
lemma absorbs_iff_norm : Absorbs 𝕜 A B ↔ ∃ r, ∀ c : 𝕜, r ≤ ‖c‖ → B ⊆ c • A :=
Filter.atTop_basis.cobounded_of_norm.eventually_iff.trans <| by simp only [true_and]; rfl
alias ⟨_, Absorbs.of_norm⟩ := absorbs_iff_norm
lemma Absorbs.exists_pos (h : Absorbs 𝕜 A B) : ∃ r > 0, ∀ c : 𝕜, r ≤ ‖c‖ → B ⊆ c • A :=
let ⟨r, hr₁, hr⟩ := (Filter.atTop_basis' 1).cobounded_of_norm.eventually_iff.1 h
⟨r, one_pos.trans_le hr₁, hr⟩
theorem balanced_iff_smul_mem : Balanced 𝕜 s ↔ ∀ ⦃a : 𝕜⦄, ‖a‖ ≤ 1 → ∀ ⦃x : E⦄, x ∈ s → a • x ∈ s :=
forall₂_congr fun _a _ha => smul_set_subset_iff
#align balanced_iff_smul_mem balanced_iff_smul_mem
alias ⟨Balanced.smul_mem, _⟩ := balanced_iff_smul_mem
#align balanced.smul_mem Balanced.smul_mem
theorem balanced_iff_closedBall_smul : Balanced 𝕜 s ↔ Metric.closedBall (0 : 𝕜) 1 • s ⊆ s := by
simp [balanced_iff_smul_mem, smul_subset_iff]
@[simp]
theorem balanced_empty : Balanced 𝕜 (∅ : Set E) := fun _ _ => by rw [smul_set_empty]
#align balanced_empty balanced_empty
@[simp]
theorem balanced_univ : Balanced 𝕜 (univ : Set E) := fun _a _ha => subset_univ _
#align balanced_univ balanced_univ
theorem Balanced.union (hA : Balanced 𝕜 A) (hB : Balanced 𝕜 B) : Balanced 𝕜 (A ∪ B) := fun _a ha =>
smul_set_union.subset.trans <| union_subset_union (hA _ ha) <| hB _ ha
#align balanced.union Balanced.union
theorem Balanced.inter (hA : Balanced 𝕜 A) (hB : Balanced 𝕜 B) : Balanced 𝕜 (A ∩ B) := fun _a ha =>
smul_set_inter_subset.trans <| inter_subset_inter (hA _ ha) <| hB _ ha
#align balanced.inter Balanced.inter
theorem balanced_iUnion {f : ι → Set E} (h : ∀ i, Balanced 𝕜 (f i)) : Balanced 𝕜 (⋃ i, f i) :=
fun _a ha => (smul_set_iUnion _ _).subset.trans <| iUnion_mono fun _ => h _ _ ha
#align balanced_Union balanced_iUnion
theorem balanced_iUnion₂ {f : ∀ i, κ i → Set E} (h : ∀ i j, Balanced 𝕜 (f i j)) :
Balanced 𝕜 (⋃ (i) (j), f i j) :=
balanced_iUnion fun _ => balanced_iUnion <| h _
#align balanced_Union₂ balanced_iUnion₂
theorem balanced_iInter {f : ι → Set E} (h : ∀ i, Balanced 𝕜 (f i)) : Balanced 𝕜 (⋂ i, f i) :=
fun _a ha => (smul_set_iInter_subset _ _).trans <| iInter_mono fun _ => h _ _ ha
#align balanced_Inter balanced_iInter
theorem balanced_iInter₂ {f : ∀ i, κ i → Set E} (h : ∀ i j, Balanced 𝕜 (f i j)) :
Balanced 𝕜 (⋂ (i) (j), f i j) :=
balanced_iInter fun _ => balanced_iInter <| h _
#align balanced_Inter₂ balanced_iInter₂
variable [SMul 𝕝 E] [SMulCommClass 𝕜 𝕝 E]
theorem Balanced.smul (a : 𝕝) (hs : Balanced 𝕜 s) : Balanced 𝕜 (a • s) := fun _b hb =>
(smul_comm _ _ _).subset.trans <| smul_set_mono <| hs _ hb
#align balanced.smul Balanced.smul
end SMul
section Module
variable [AddCommGroup E] [Module 𝕜 E] {s s₁ s₂ t t₁ t₂ : Set E}
theorem Balanced.neg : Balanced 𝕜 s → Balanced 𝕜 (-s) :=
forall₂_imp fun _ _ h => (smul_set_neg _ _).subset.trans <| neg_subset_neg.2 h
#align balanced.neg Balanced.neg
@[simp]
theorem balanced_neg : Balanced 𝕜 (-s) ↔ Balanced 𝕜 s :=
⟨fun h ↦ neg_neg s ▸ h.neg, fun h ↦ h.neg⟩
theorem Balanced.neg_mem_iff [NormOneClass 𝕜] (h : Balanced 𝕜 s) {x : E} : -x ∈ s ↔ x ∈ s :=
⟨fun hx ↦ by simpa using h.smul_mem (a := -1) (by simp) hx,
fun hx ↦ by simpa using h.smul_mem (a := -1) (by simp) hx⟩
#align balanced.neg_mem_iff Balanced.neg_mem_iff
theorem Balanced.neg_eq [NormOneClass 𝕜] (h : Balanced 𝕜 s) : -s = s :=
Set.ext fun _ ↦ h.neg_mem_iff
theorem Balanced.add (hs : Balanced 𝕜 s) (ht : Balanced 𝕜 t) : Balanced 𝕜 (s + t) := fun _a ha =>
(smul_add _ _ _).subset.trans <| add_subset_add (hs _ ha) <| ht _ ha
#align balanced.add Balanced.add
theorem Balanced.sub (hs : Balanced 𝕜 s) (ht : Balanced 𝕜 t) : Balanced 𝕜 (s - t) := by
simp_rw [sub_eq_add_neg]
exact hs.add ht.neg
#align balanced.sub Balanced.sub
theorem balanced_zero : Balanced 𝕜 (0 : Set E) := fun _a _ha => (smul_zero _).subset
#align balanced_zero balanced_zero
end Module
end SeminormedRing
section NormedDivisionRing
variable [NormedDivisionRing 𝕜] [AddCommGroup E] [Module 𝕜 E] {s t : Set E} {x : E} {a b : 𝕜}
theorem absorbs_iff_eventually_nhdsWithin_zero :
Absorbs 𝕜 s t ↔ ∀ᶠ c : 𝕜 in 𝓝[≠] 0, MapsTo (c • ·) t s := by
rw [absorbs_iff_eventually_cobounded_mapsTo, ← Filter.inv_cobounded₀]; rfl
alias ⟨Absorbs.eventually_nhdsWithin_zero, _⟩ := absorbs_iff_eventually_nhdsWithin_zero
theorem absorbent_iff_eventually_nhdsWithin_zero :
Absorbent 𝕜 s ↔ ∀ x : E, ∀ᶠ c : 𝕜 in 𝓝[≠] 0, c • x ∈ s :=
forall_congr' fun x ↦ by simp only [absorbs_iff_eventually_nhdsWithin_zero, mapsTo_singleton]
alias ⟨Absorbent.eventually_nhdsWithin_zero, _⟩ := absorbent_iff_eventually_nhdsWithin_zero
theorem absorbs_iff_eventually_nhds_zero (h₀ : 0 ∈ s) :
Absorbs 𝕜 s t ↔ ∀ᶠ c : 𝕜 in 𝓝 0, MapsTo (c • ·) t s := by
rw [← nhdsWithin_compl_singleton_sup_pure, Filter.eventually_sup, Filter.eventually_pure,
← absorbs_iff_eventually_nhdsWithin_zero, and_iff_left]
intro x _
simpa only [zero_smul]
theorem Absorbs.eventually_nhds_zero (h : Absorbs 𝕜 s t) (h₀ : 0 ∈ s) :
∀ᶠ c : 𝕜 in 𝓝 0, MapsTo (c • ·) t s :=
(absorbs_iff_eventually_nhds_zero h₀).1 h
end NormedDivisionRing
section NormedField
variable [NormedField 𝕜] [NormedRing 𝕝] [NormedSpace 𝕜 𝕝] [AddCommGroup E] [Module 𝕜 E]
[SMulWithZero 𝕝 E] [IsScalarTower 𝕜 𝕝 E] {s t u v A B : Set E} {x : E} {a b : 𝕜}
/-- Scalar multiplication (by possibly different types) of a balanced set is monotone. -/
theorem Balanced.smul_mono (hs : Balanced 𝕝 s) {a : 𝕝} {b : 𝕜} (h : ‖a‖ ≤ ‖b‖) : a • s ⊆ b • s := by
obtain rfl | hb := eq_or_ne b 0
· rw [norm_zero, norm_le_zero_iff] at h
simp only [h, ← image_smul, zero_smul, Subset.rfl]
· calc
a • s = b • (b⁻¹ • a) • s := by rw [smul_assoc, smul_inv_smul₀ hb]
_ ⊆ b • s := smul_set_mono <| hs _ <| by
rw [norm_smul, norm_inv, ← div_eq_inv_mul]
exact div_le_one_of_le h (norm_nonneg _)
#align balanced.smul_mono Balanced.smul_mono
theorem Balanced.smul_mem_mono [SMulCommClass 𝕝 𝕜 E] (hs : Balanced 𝕝 s) {a : 𝕜} {b : 𝕝}
(ha : a • x ∈ s) (hba : ‖b‖ ≤ ‖a‖) : b • x ∈ s := by
rcases eq_or_ne a 0 with rfl | ha₀
· simp_all
· calc
b • x = (a⁻¹ • b) • a • x := by rw [smul_comm, smul_assoc, smul_inv_smul₀ ha₀]
_ ∈ s := by
refine hs.smul_mem ?_ ha
rw [norm_smul, norm_inv, ← div_eq_inv_mul]
exact div_le_one_of_le hba (norm_nonneg _)
theorem Balanced.subset_smul (hA : Balanced 𝕜 A) (ha : 1 ≤ ‖a‖) : A ⊆ a • A := by
rw [← @norm_one 𝕜] at ha; simpa using hA.smul_mono ha
#align balanced.subset_smul Balanced.subset_smul
theorem Balanced.smul_congr (hs : Balanced 𝕜 A) (h : ‖a‖ = ‖b‖) : a • A = b • A :=
(hs.smul_mono h.le).antisymm (hs.smul_mono h.ge)
theorem Balanced.smul_eq (hA : Balanced 𝕜 A) (ha : ‖a‖ = 1) : a • A = A :=
(hA _ ha.le).antisymm <| hA.subset_smul ha.ge
#align balanced.smul_eq Balanced.smul_eq
/-- A balanced set absorbs itself. -/
theorem Balanced.absorbs_self (hA : Balanced 𝕜 A) : Absorbs 𝕜 A A :=
.of_norm ⟨1, fun _ => hA.subset_smul⟩
#align balanced.absorbs_self Balanced.absorbs_self
theorem Balanced.smul_mem_iff (hs : Balanced 𝕜 s) (h : ‖a‖ = ‖b‖) : a • x ∈ s ↔ b • x ∈ s :=
⟨(hs.smul_mem_mono · h.ge), (hs.smul_mem_mono · h.le)⟩
#align balanced.mem_smul_iff Balanced.smul_mem_iff
@[deprecated (since := "2024-02-02")] alias Balanced.mem_smul_iff := Balanced.smul_mem_iff
variable [TopologicalSpace E] [ContinuousSMul 𝕜 E]
/-- Every neighbourhood of the origin is absorbent. -/
theorem absorbent_nhds_zero (hA : A ∈ 𝓝 (0 : E)) : Absorbent 𝕜 A :=
absorbent_iff_inv_smul.2 fun x ↦ Filter.tendsto_inv₀_cobounded.smul tendsto_const_nhds <| by
rwa [zero_smul]
#align absorbent_nhds_zero absorbent_nhds_zero
/-- The union of `{0}` with the interior of a balanced set is balanced. -/
theorem Balanced.zero_insert_interior (hA : Balanced 𝕜 A) :
Balanced 𝕜 (insert 0 (interior A)) := by
intro a ha
obtain rfl | h := eq_or_ne a 0
· rw [zero_smul_set]
exacts [subset_union_left, ⟨0, Or.inl rfl⟩]
· rw [← image_smul, image_insert_eq, smul_zero]
apply insert_subset_insert
exact ((isOpenMap_smul₀ h).mapsTo_interior <| hA.smul_mem ha).image_subset
#align balanced_zero_union_interior Balanced.zero_insert_interior
@[deprecated Balanced.zero_insert_interior]
theorem balanced_zero_union_interior (hA : Balanced 𝕜 A) : Balanced 𝕜 ((0 : Set E) ∪ interior A) :=
hA.zero_insert_interior
/-- The interior of a balanced set is balanced if it contains the origin. -/
protected theorem Balanced.interior (hA : Balanced 𝕜 A) (h : (0 : E) ∈ interior A) :
Balanced 𝕜 (interior A) := by
rw [← insert_eq_self.2 h]
exact hA.zero_insert_interior
#align balanced.interior Balanced.interior
protected theorem Balanced.closure (hA : Balanced 𝕜 A) : Balanced 𝕜 (closure A) := fun _a ha =>
(image_closure_subset_closure_image <| continuous_const_smul _).trans <|
closure_mono <| hA _ ha
#align balanced.closure Balanced.closure
end NormedField
section NontriviallyNormedField
variable [NontriviallyNormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] {s : Set E}
@[deprecated Absorbent.zero_mem (since := "2024-02-02")]
theorem Absorbent.zero_mem' (hs : Absorbent 𝕜 s) : (0 : E) ∈ s := hs.zero_mem
variable [Module ℝ E] [SMulCommClass ℝ 𝕜 E]
protected theorem Balanced.convexHull (hs : Balanced 𝕜 s) : Balanced 𝕜 (convexHull ℝ s) := by
suffices Convex ℝ { x | ∀ a : 𝕜, ‖a‖ ≤ 1 → a • x ∈ convexHull ℝ s } by
rw [balanced_iff_smul_mem] at hs ⊢
refine fun a ha x hx => convexHull_min ?_ this hx a ha
exact fun y hy a ha => subset_convexHull ℝ s (hs ha hy)
intro x hx y hy u v hu hv huv a ha
simp only [smul_add, ← smul_comm]
exact convex_convexHull ℝ s (hx a ha) (hy a ha) hu hv huv
#align balanced_convex_hull_of_balanced Balanced.convexHull
@[deprecated (since := "2024-02-02")] alias balanced_convexHull_of_balanced := Balanced.convexHull
end NontriviallyNormedField
section Real
variable [AddCommGroup E] [Module ℝ E] {s : Set E}
| Mathlib/Analysis/LocallyConvex/Basic.lean | 306 | 311 | theorem balanced_iff_neg_mem (hs : Convex ℝ s) : Balanced ℝ s ↔ ∀ ⦃x⦄, x ∈ s → -x ∈ s := by |
refine ⟨fun h x => h.neg_mem_iff.2, fun h a ha => smul_set_subset_iff.2 fun x hx => ?_⟩
rw [Real.norm_eq_abs, abs_le] at ha
rw [show a = -((1 - a) / 2) + (a - -1) / 2 by ring, add_smul, neg_smul, ← smul_neg]
exact hs (h hx) hx (div_nonneg (sub_nonneg_of_le ha.2) zero_le_two)
(div_nonneg (sub_nonneg_of_le ha.1) zero_le_two) (by ring)
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Yury Kudryashov
-/
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Algebra.BigOperators.Finsupp
#align_import algebra.algebra.hom from "leanprover-community/mathlib"@"e97cf15cd1aec9bd5c193b2ffac5a6dc9118912b"
/-!
# Homomorphisms of `R`-algebras
This file defines bundled homomorphisms of `R`-algebras.
## Main definitions
* `AlgHom R A B`: the type of `R`-algebra morphisms from `A` to `B`.
* `Algebra.ofId R A : R →ₐ[R] A`: the canonical map from `R` to `A`, as an `AlgHom`.
## Notations
* `A →ₐ[R] B` : `R`-algebra homomorphism from `A` to `B`.
-/
universe u v w u₁ v₁
/-- Defining the homomorphism in the category R-Alg. -/
-- @[nolint has_nonempty_instance] -- Porting note(#5171): linter not ported yet
structure AlgHom (R : Type u) (A : Type v) (B : Type w) [CommSemiring R] [Semiring A] [Semiring B]
[Algebra R A] [Algebra R B] extends RingHom A B where
commutes' : ∀ r : R, toFun (algebraMap R A r) = algebraMap R B r
#align alg_hom AlgHom
/-- Reinterpret an `AlgHom` as a `RingHom` -/
add_decl_doc AlgHom.toRingHom
@[inherit_doc AlgHom]
infixr:25 " →ₐ " => AlgHom _
@[inherit_doc]
notation:25 A " →ₐ[" R "] " B => AlgHom R A B
/-- `AlgHomClass F R A B` asserts `F` is a type of bundled algebra homomorphisms
from `A` to `B`. -/
class AlgHomClass (F : Type*) (R A B : outParam Type*)
[CommSemiring R] [Semiring A] [Semiring B] [Algebra R A] [Algebra R B]
[FunLike F A B] extends RingHomClass F A B : Prop where
commutes : ∀ (f : F) (r : R), f (algebraMap R A r) = algebraMap R B r
#align alg_hom_class AlgHomClass
-- Porting note: `dangerousInstance` linter has become smarter about `outParam`s
-- attribute [nolint dangerousInstance] AlgHomClass.toRingHomClass
-- Porting note (#10618): simp can prove this
-- attribute [simp] AlgHomClass.commutes
namespace AlgHomClass
variable {R A B F : Type*} [CommSemiring R] [Semiring A] [Semiring B]
[Algebra R A] [Algebra R B] [FunLike F A B]
-- see Note [lower instance priority]
instance (priority := 100) linearMapClass [AlgHomClass F R A B] : LinearMapClass F R A B :=
{ ‹AlgHomClass F R A B› with
map_smulₛₗ := fun f r x => by
simp only [Algebra.smul_def, map_mul, commutes, RingHom.id_apply] }
#align alg_hom_class.linear_map_class AlgHomClass.linearMapClass
-- Porting note (#11445): A new definition underlying a coercion `↑`.
/-- Turn an element of a type `F` satisfying `AlgHomClass F α β` into an actual
`AlgHom`. This is declared as the default coercion from `F` to `α →+* β`. -/
@[coe]
def toAlgHom {F : Type*} [FunLike F A B] [AlgHomClass F R A B] (f : F) : A →ₐ[R] B where
__ := (f : A →+* B)
toFun := f
commutes' := AlgHomClass.commutes f
instance coeTC {F : Type*} [FunLike F A B] [AlgHomClass F R A B] : CoeTC F (A →ₐ[R] B) :=
⟨AlgHomClass.toAlgHom⟩
#align alg_hom_class.alg_hom.has_coe_t AlgHomClass.coeTC
end AlgHomClass
namespace AlgHom
variable {R : Type u} {A : Type v} {B : Type w} {C : Type u₁} {D : Type v₁}
section Semiring
variable [CommSemiring R] [Semiring A] [Semiring B] [Semiring C] [Semiring D]
variable [Algebra R A] [Algebra R B] [Algebra R C] [Algebra R D]
-- Porting note: we don't port specialized `CoeFun` instances if there is `DFunLike` instead
#noalign alg_hom.has_coe_to_fun
instance funLike : FunLike (A →ₐ[R] B) A B where
coe f := f.toFun
coe_injective' f g h := by
rcases f with ⟨⟨⟨⟨_, _⟩, _⟩, _, _⟩, _⟩
rcases g with ⟨⟨⟨⟨_, _⟩, _⟩, _, _⟩, _⟩
congr
-- Porting note: This instance is moved.
instance algHomClass : AlgHomClass (A →ₐ[R] B) R A B where
map_add f := f.map_add'
map_zero f := f.map_zero'
map_mul f := f.map_mul'
map_one f := f.map_one'
commutes f := f.commutes'
#align alg_hom.alg_hom_class AlgHom.algHomClass
/-- See Note [custom simps projection] -/
def Simps.apply {R : Type u} {α : Type v} {β : Type w} [CommSemiring R]
[Semiring α] [Semiring β] [Algebra R α] [Algebra R β] (f : α →ₐ[R] β) : α → β := f
initialize_simps_projections AlgHom (toFun → apply)
@[simp]
protected theorem coe_coe {F : Type*} [FunLike F A B] [AlgHomClass F R A B] (f : F) :
⇑(f : A →ₐ[R] B) = f :=
rfl
#align alg_hom.coe_coe AlgHom.coe_coe
@[simp]
theorem toFun_eq_coe (f : A →ₐ[R] B) : f.toFun = f :=
rfl
#align alg_hom.to_fun_eq_coe AlgHom.toFun_eq_coe
#noalign alg_hom.coe_ring_hom
-- Porting note (#11445): A new definition underlying a coercion `↑`.
@[coe]
def toMonoidHom' (f : A →ₐ[R] B) : A →* B := (f : A →+* B)
instance coeOutMonoidHom : CoeOut (A →ₐ[R] B) (A →* B) :=
⟨AlgHom.toMonoidHom'⟩
#align alg_hom.coe_monoid_hom AlgHom.coeOutMonoidHom
-- Porting note (#11445): A new definition underlying a coercion `↑`.
@[coe]
def toAddMonoidHom' (f : A →ₐ[R] B) : A →+ B := (f : A →+* B)
instance coeOutAddMonoidHom : CoeOut (A →ₐ[R] B) (A →+ B) :=
⟨AlgHom.toAddMonoidHom'⟩
#align alg_hom.coe_add_monoid_hom AlgHom.coeOutAddMonoidHom
-- Porting note: Lean 3: `@[simp, norm_cast] coe_mk`
-- Lean 4: `@[simp] coe_mk` & `@[norm_cast] coe_mks`
@[simp]
theorem coe_mk {f : A →+* B} (h) : ((⟨f, h⟩ : A →ₐ[R] B) : A → B) = f :=
rfl
@[norm_cast]
theorem coe_mks {f : A → B} (h₁ h₂ h₃ h₄ h₅) : ⇑(⟨⟨⟨⟨f, h₁⟩, h₂⟩, h₃, h₄⟩, h₅⟩ : A →ₐ[R] B) = f :=
rfl
#align alg_hom.coe_mk AlgHom.coe_mks
-- Porting note: This theorem is new.
@[simp, norm_cast]
theorem coe_ringHom_mk {f : A →+* B} (h) : ((⟨f, h⟩ : A →ₐ[R] B) : A →+* B) = f :=
rfl
-- make the coercion the simp-normal form
@[simp]
theorem toRingHom_eq_coe (f : A →ₐ[R] B) : f.toRingHom = f :=
rfl
#align alg_hom.to_ring_hom_eq_coe AlgHom.toRingHom_eq_coe
@[simp, norm_cast]
theorem coe_toRingHom (f : A →ₐ[R] B) : ⇑(f : A →+* B) = f :=
rfl
#align alg_hom.coe_to_ring_hom AlgHom.coe_toRingHom
@[simp, norm_cast]
theorem coe_toMonoidHom (f : A →ₐ[R] B) : ⇑(f : A →* B) = f :=
rfl
#align alg_hom.coe_to_monoid_hom AlgHom.coe_toMonoidHom
@[simp, norm_cast]
theorem coe_toAddMonoidHom (f : A →ₐ[R] B) : ⇑(f : A →+ B) = f :=
rfl
#align alg_hom.coe_to_add_monoid_hom AlgHom.coe_toAddMonoidHom
variable (φ : A →ₐ[R] B)
theorem coe_fn_injective : @Function.Injective (A →ₐ[R] B) (A → B) (↑) :=
DFunLike.coe_injective
#align alg_hom.coe_fn_injective AlgHom.coe_fn_injective
theorem coe_fn_inj {φ₁ φ₂ : A →ₐ[R] B} : (φ₁ : A → B) = φ₂ ↔ φ₁ = φ₂ :=
DFunLike.coe_fn_eq
#align alg_hom.coe_fn_inj AlgHom.coe_fn_inj
theorem coe_ringHom_injective : Function.Injective ((↑) : (A →ₐ[R] B) → A →+* B) := fun φ₁ φ₂ H =>
coe_fn_injective <| show ((φ₁ : A →+* B) : A → B) = ((φ₂ : A →+* B) : A → B) from congr_arg _ H
#align alg_hom.coe_ring_hom_injective AlgHom.coe_ringHom_injective
theorem coe_monoidHom_injective : Function.Injective ((↑) : (A →ₐ[R] B) → A →* B) :=
RingHom.coe_monoidHom_injective.comp coe_ringHom_injective
#align alg_hom.coe_monoid_hom_injective AlgHom.coe_monoidHom_injective
theorem coe_addMonoidHom_injective : Function.Injective ((↑) : (A →ₐ[R] B) → A →+ B) :=
RingHom.coe_addMonoidHom_injective.comp coe_ringHom_injective
#align alg_hom.coe_add_monoid_hom_injective AlgHom.coe_addMonoidHom_injective
protected theorem congr_fun {φ₁ φ₂ : A →ₐ[R] B} (H : φ₁ = φ₂) (x : A) : φ₁ x = φ₂ x :=
DFunLike.congr_fun H x
#align alg_hom.congr_fun AlgHom.congr_fun
protected theorem congr_arg (φ : A →ₐ[R] B) {x y : A} (h : x = y) : φ x = φ y :=
DFunLike.congr_arg φ h
#align alg_hom.congr_arg AlgHom.congr_arg
@[ext]
theorem ext {φ₁ φ₂ : A →ₐ[R] B} (H : ∀ x, φ₁ x = φ₂ x) : φ₁ = φ₂ :=
DFunLike.ext _ _ H
#align alg_hom.ext AlgHom.ext
theorem ext_iff {φ₁ φ₂ : A →ₐ[R] B} : φ₁ = φ₂ ↔ ∀ x, φ₁ x = φ₂ x :=
DFunLike.ext_iff
#align alg_hom.ext_iff AlgHom.ext_iff
@[simp]
theorem mk_coe {f : A →ₐ[R] B} (h₁ h₂ h₃ h₄ h₅) : (⟨⟨⟨⟨f, h₁⟩, h₂⟩, h₃, h₄⟩, h₅⟩ : A →ₐ[R] B) = f :=
ext fun _ => rfl
#align alg_hom.mk_coe AlgHom.mk_coe
@[simp]
theorem commutes (r : R) : φ (algebraMap R A r) = algebraMap R B r :=
φ.commutes' r
#align alg_hom.commutes AlgHom.commutes
theorem comp_algebraMap : (φ : A →+* B).comp (algebraMap R A) = algebraMap R B :=
RingHom.ext <| φ.commutes
#align alg_hom.comp_algebra_map AlgHom.comp_algebraMap
protected theorem map_add (r s : A) : φ (r + s) = φ r + φ s :=
map_add _ _ _
#align alg_hom.map_add AlgHom.map_add
protected theorem map_zero : φ 0 = 0 :=
map_zero _
#align alg_hom.map_zero AlgHom.map_zero
protected theorem map_mul (x y) : φ (x * y) = φ x * φ y :=
map_mul _ _ _
#align alg_hom.map_mul AlgHom.map_mul
protected theorem map_one : φ 1 = 1 :=
map_one _
#align alg_hom.map_one AlgHom.map_one
protected theorem map_pow (x : A) (n : ℕ) : φ (x ^ n) = φ x ^ n :=
map_pow _ _ _
#align alg_hom.map_pow AlgHom.map_pow
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smul (r : R) (x : A) : φ (r • x) = r • φ x :=
map_smul _ _ _
#align alg_hom.map_smul AlgHom.map_smul
protected theorem map_sum {ι : Type*} (f : ι → A) (s : Finset ι) :
φ (∑ x ∈ s, f x) = ∑ x ∈ s, φ (f x) :=
map_sum _ _ _
#align alg_hom.map_sum AlgHom.map_sum
protected theorem map_finsupp_sum {α : Type*} [Zero α] {ι : Type*} (f : ι →₀ α) (g : ι → α → A) :
φ (f.sum g) = f.sum fun i a => φ (g i a) :=
map_finsupp_sum _ _ _
#align alg_hom.map_finsupp_sum AlgHom.map_finsupp_sum
#noalign alg_hom.map_bit0
#noalign alg_hom.map_bit1
/-- If a `RingHom` is `R`-linear, then it is an `AlgHom`. -/
def mk' (f : A →+* B) (h : ∀ (c : R) (x), f (c • x) = c • f x) : A →ₐ[R] B :=
{ f with
toFun := f
commutes' := fun c => by simp only [Algebra.algebraMap_eq_smul_one, h, f.map_one] }
#align alg_hom.mk' AlgHom.mk'
@[simp]
theorem coe_mk' (f : A →+* B) (h : ∀ (c : R) (x), f (c • x) = c • f x) : ⇑(mk' f h) = f :=
rfl
#align alg_hom.coe_mk' AlgHom.coe_mk'
section
variable (R A)
/-- Identity map as an `AlgHom`. -/
protected def id : A →ₐ[R] A :=
{ RingHom.id A with commutes' := fun _ => rfl }
#align alg_hom.id AlgHom.id
@[simp]
theorem coe_id : ⇑(AlgHom.id R A) = id :=
rfl
#align alg_hom.coe_id AlgHom.coe_id
@[simp]
theorem id_toRingHom : (AlgHom.id R A : A →+* A) = RingHom.id _ :=
rfl
#align alg_hom.id_to_ring_hom AlgHom.id_toRingHom
end
theorem id_apply (p : A) : AlgHom.id R A p = p :=
rfl
#align alg_hom.id_apply AlgHom.id_apply
/-- Composition of algebra homeomorphisms. -/
def comp (φ₁ : B →ₐ[R] C) (φ₂ : A →ₐ[R] B) : A →ₐ[R] C :=
{ φ₁.toRingHom.comp ↑φ₂ with
commutes' := fun r : R => by rw [← φ₁.commutes, ← φ₂.commutes]; rfl }
#align alg_hom.comp AlgHom.comp
@[simp]
theorem coe_comp (φ₁ : B →ₐ[R] C) (φ₂ : A →ₐ[R] B) : ⇑(φ₁.comp φ₂) = φ₁ ∘ φ₂ :=
rfl
#align alg_hom.coe_comp AlgHom.coe_comp
theorem comp_apply (φ₁ : B →ₐ[R] C) (φ₂ : A →ₐ[R] B) (p : A) : φ₁.comp φ₂ p = φ₁ (φ₂ p) :=
rfl
#align alg_hom.comp_apply AlgHom.comp_apply
theorem comp_toRingHom (φ₁ : B →ₐ[R] C) (φ₂ : A →ₐ[R] B) :
(φ₁.comp φ₂ : A →+* C) = (φ₁ : B →+* C).comp ↑φ₂ :=
rfl
#align alg_hom.comp_to_ring_hom AlgHom.comp_toRingHom
@[simp]
theorem comp_id : φ.comp (AlgHom.id R A) = φ :=
ext fun _x => rfl
#align alg_hom.comp_id AlgHom.comp_id
@[simp]
theorem id_comp : (AlgHom.id R B).comp φ = φ :=
ext fun _x => rfl
#align alg_hom.id_comp AlgHom.id_comp
theorem comp_assoc (φ₁ : C →ₐ[R] D) (φ₂ : B →ₐ[R] C) (φ₃ : A →ₐ[R] B) :
(φ₁.comp φ₂).comp φ₃ = φ₁.comp (φ₂.comp φ₃) :=
ext fun _x => rfl
#align alg_hom.comp_assoc AlgHom.comp_assoc
/-- R-Alg ⥤ R-Mod -/
def toLinearMap : A →ₗ[R] B where
toFun := φ
map_add' := map_add _
map_smul' := map_smul _
#align alg_hom.to_linear_map AlgHom.toLinearMap
@[simp]
theorem toLinearMap_apply (p : A) : φ.toLinearMap p = φ p :=
rfl
#align alg_hom.to_linear_map_apply AlgHom.toLinearMap_apply
theorem toLinearMap_injective :
Function.Injective (toLinearMap : _ → A →ₗ[R] B) := fun _φ₁ _φ₂ h =>
ext <| LinearMap.congr_fun h
#align alg_hom.to_linear_map_injective AlgHom.toLinearMap_injective
@[simp]
theorem comp_toLinearMap (f : A →ₐ[R] B) (g : B →ₐ[R] C) :
(g.comp f).toLinearMap = g.toLinearMap.comp f.toLinearMap :=
rfl
#align alg_hom.comp_to_linear_map AlgHom.comp_toLinearMap
@[simp]
theorem toLinearMap_id : toLinearMap (AlgHom.id R A) = LinearMap.id :=
LinearMap.ext fun _ => rfl
#align alg_hom.to_linear_map_id AlgHom.toLinearMap_id
/-- Promote a `LinearMap` to an `AlgHom` by supplying proofs about the behavior on `1` and `*`. -/
@[simps]
def ofLinearMap (f : A →ₗ[R] B) (map_one : f 1 = 1) (map_mul : ∀ x y, f (x * y) = f x * f y) :
A →ₐ[R] B :=
{ f.toAddMonoidHom with
toFun := f
map_one' := map_one
map_mul' := map_mul
commutes' := fun c => by simp only [Algebra.algebraMap_eq_smul_one, f.map_smul, map_one] }
#align alg_hom.of_linear_map AlgHom.ofLinearMap
@[simp]
| Mathlib/Algebra/Algebra/Hom.lean | 388 | 391 | theorem ofLinearMap_toLinearMap (map_one) (map_mul) :
ofLinearMap φ.toLinearMap map_one map_mul = φ := by |
ext
rfl
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Scott Morrison
-/
import Mathlib.CategoryTheory.Subobject.MonoOver
import Mathlib.CategoryTheory.Skeletal
import Mathlib.CategoryTheory.ConcreteCategory.Basic
import Mathlib.Tactic.ApplyFun
import Mathlib.Tactic.CategoryTheory.Elementwise
#align_import category_theory.subobject.basic from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Subobjects
We define `Subobject X` as the quotient (by isomorphisms) of
`MonoOver X := {f : Over X // Mono f.hom}`.
Here `MonoOver X` is a thin category (a pair of objects has at most one morphism between them),
so we can think of it as a preorder. However as it is not skeletal, it is not a partial order.
There is a coercion from `Subobject X` back to the ambient category `C`
(using choice to pick a representative), and for `P : Subobject X`,
`P.arrow : (P : C) ⟶ X` is the inclusion morphism.
We provide
* `def pullback [HasPullbacks C] (f : X ⟶ Y) : Subobject Y ⥤ Subobject X`
* `def map (f : X ⟶ Y) [Mono f] : Subobject X ⥤ Subobject Y`
* `def «exists_» [HasImages C] (f : X ⟶ Y) : Subobject X ⥤ Subobject Y`
and prove their basic properties and relationships.
These are all easy consequences of the earlier development
of the corresponding functors for `MonoOver`.
The subobjects of `X` form a preorder making them into a category. We have `X ≤ Y` if and only if
`X.arrow` factors through `Y.arrow`: see `ofLE`/`ofLEMk`/`ofMkLE`/`ofMkLEMk` and
`le_of_comm`. Similarly, to show that two subobjects are equal, we can supply an isomorphism between
the underlying objects that commutes with the arrows (`eq_of_comm`).
See also
* `CategoryTheory.Subobject.factorThru` :
an API describing factorization of morphisms through subobjects.
* `CategoryTheory.Subobject.lattice` :
the lattice structures on subobjects.
## Notes
This development originally appeared in Bhavik Mehta's "Topos theory for Lean" repository,
and was ported to mathlib by Scott Morrison.
### Implementation note
Currently we describe `pullback`, `map`, etc., as functors.
It may be better to just say that they are monotone functions,
and even avoid using categorical language entirely when describing `Subobject X`.
(It's worth keeping this in mind in future use; it should be a relatively easy change here
if it looks preferable.)
### Relation to pseudoelements
There is a separate development of pseudoelements in `CategoryTheory.Abelian.Pseudoelements`,
as a quotient (but not by isomorphism) of `Over X`.
When a morphism `f` has an image, the image represents the same pseudoelement.
In a category with images `Pseudoelements X` could be constructed as a quotient of `MonoOver X`.
In fact, in an abelian category (I'm not sure in what generality beyond that),
`Pseudoelements X` agrees with `Subobject X`, but we haven't developed this in mathlib yet.
-/
universe v₁ v₂ u₁ u₂
noncomputable section
namespace CategoryTheory
open CategoryTheory CategoryTheory.Category CategoryTheory.Limits
variable {C : Type u₁} [Category.{v₁} C] {X Y Z : C}
variable {D : Type u₂} [Category.{v₂} D]
/-!
We now construct the subobject lattice for `X : C`,
as the quotient by isomorphisms of `MonoOver X`.
Since `MonoOver X` is a thin category, we use `ThinSkeleton` to take the quotient.
Essentially all the structure defined above on `MonoOver X` descends to `Subobject X`,
with morphisms becoming inequalities, and isomorphisms becoming equations.
-/
/-- The category of subobjects of `X : C`, defined as isomorphism classes of monomorphisms into `X`.
-/
def Subobject (X : C) :=
ThinSkeleton (MonoOver X)
#align category_theory.subobject CategoryTheory.Subobject
instance (X : C) : PartialOrder (Subobject X) := by
dsimp only [Subobject]
infer_instance
namespace Subobject
-- Porting note: made it a def rather than an abbreviation
-- because Lean would make it too transparent
/-- Convenience constructor for a subobject. -/
def mk {X A : C} (f : A ⟶ X) [Mono f] : Subobject X :=
(toThinSkeleton _).obj (MonoOver.mk' f)
#align category_theory.subobject.mk CategoryTheory.Subobject.mk
section
attribute [local ext] CategoryTheory.Comma
protected theorem ind {X : C} (p : Subobject X → Prop)
(h : ∀ ⦃A : C⦄ (f : A ⟶ X) [Mono f], p (Subobject.mk f)) (P : Subobject X) : p P := by
apply Quotient.inductionOn'
intro a
exact h a.arrow
#align category_theory.subobject.ind CategoryTheory.Subobject.ind
protected theorem ind₂ {X : C} (p : Subobject X → Subobject X → Prop)
(h : ∀ ⦃A B : C⦄ (f : A ⟶ X) (g : B ⟶ X) [Mono f] [Mono g],
p (Subobject.mk f) (Subobject.mk g))
(P Q : Subobject X) : p P Q := by
apply Quotient.inductionOn₂'
intro a b
exact h a.arrow b.arrow
#align category_theory.subobject.ind₂ CategoryTheory.Subobject.ind₂
end
/-- Declare a function on subobjects of `X` by specifying a function on monomorphisms with
codomain `X`. -/
protected def lift {α : Sort*} {X : C} (F : ∀ ⦃A : C⦄ (f : A ⟶ X) [Mono f], α)
(h :
∀ ⦃A B : C⦄ (f : A ⟶ X) (g : B ⟶ X) [Mono f] [Mono g] (i : A ≅ B),
i.hom ≫ g = f → F f = F g) :
Subobject X → α := fun P =>
Quotient.liftOn' P (fun m => F m.arrow) fun m n ⟨i⟩ =>
h m.arrow n.arrow ((MonoOver.forget X ⋙ Over.forget X).mapIso i) (Over.w i.hom)
#align category_theory.subobject.lift CategoryTheory.Subobject.lift
@[simp]
protected theorem lift_mk {α : Sort*} {X : C} (F : ∀ ⦃A : C⦄ (f : A ⟶ X) [Mono f], α) {h A}
(f : A ⟶ X) [Mono f] : Subobject.lift F h (Subobject.mk f) = F f :=
rfl
#align category_theory.subobject.lift_mk CategoryTheory.Subobject.lift_mk
/-- The category of subobjects is equivalent to the `MonoOver` category. It is more convenient to
use the former due to the partial order instance, but oftentimes it is easier to define structures
on the latter. -/
noncomputable def equivMonoOver (X : C) : Subobject X ≌ MonoOver X :=
ThinSkeleton.equivalence _
#align category_theory.subobject.equiv_mono_over CategoryTheory.Subobject.equivMonoOver
/-- Use choice to pick a representative `MonoOver X` for each `Subobject X`.
-/
noncomputable def representative {X : C} : Subobject X ⥤ MonoOver X :=
(equivMonoOver X).functor
#align category_theory.subobject.representative CategoryTheory.Subobject.representative
/-- Starting with `A : MonoOver X`, we can take its equivalence class in `Subobject X`
then pick an arbitrary representative using `representative.obj`.
This is isomorphic (in `MonoOver X`) to the original `A`.
-/
noncomputable def representativeIso {X : C} (A : MonoOver X) :
representative.obj ((toThinSkeleton _).obj A) ≅ A :=
(equivMonoOver X).counitIso.app A
#align category_theory.subobject.representative_iso CategoryTheory.Subobject.representativeIso
/-- Use choice to pick a representative underlying object in `C` for any `Subobject X`.
Prefer to use the coercion `P : C` rather than explicitly writing `underlying.obj P`.
-/
noncomputable def underlying {X : C} : Subobject X ⥤ C :=
representative ⋙ MonoOver.forget _ ⋙ Over.forget _
#align category_theory.subobject.underlying CategoryTheory.Subobject.underlying
instance : CoeOut (Subobject X) C where coe Y := underlying.obj Y
-- Porting note: removed as it has become a syntactic tautology
-- @[simp]
-- theorem underlying_as_coe {X : C} (P : Subobject X) : underlying.obj P = P :=
-- rfl
-- #align category_theory.subobject.underlying_as_coe CategoryTheory.Subobject.underlying_as_coe
/-- If we construct a `Subobject Y` from an explicit `f : X ⟶ Y` with `[Mono f]`,
then pick an arbitrary choice of underlying object `(Subobject.mk f : C)` back in `C`,
it is isomorphic (in `C`) to the original `X`.
-/
noncomputable def underlyingIso {X Y : C} (f : X ⟶ Y) [Mono f] : (Subobject.mk f : C) ≅ X :=
(MonoOver.forget _ ⋙ Over.forget _).mapIso (representativeIso (MonoOver.mk' f))
#align category_theory.subobject.underlying_iso CategoryTheory.Subobject.underlyingIso
/-- The morphism in `C` from the arbitrarily chosen underlying object to the ambient object.
-/
noncomputable def arrow {X : C} (Y : Subobject X) : (Y : C) ⟶ X :=
(representative.obj Y).obj.hom
#align category_theory.subobject.arrow CategoryTheory.Subobject.arrow
instance arrow_mono {X : C} (Y : Subobject X) : Mono Y.arrow :=
(representative.obj Y).property
#align category_theory.subobject.arrow_mono CategoryTheory.Subobject.arrow_mono
@[simp]
theorem arrow_congr {A : C} (X Y : Subobject A) (h : X = Y) :
eqToHom (congr_arg (fun X : Subobject A => (X : C)) h) ≫ Y.arrow = X.arrow := by
induction h
simp
#align category_theory.subobject.arrow_congr CategoryTheory.Subobject.arrow_congr
@[simp]
theorem representative_coe (Y : Subobject X) : (representative.obj Y : C) = (Y : C) :=
rfl
#align category_theory.subobject.representative_coe CategoryTheory.Subobject.representative_coe
@[simp]
theorem representative_arrow (Y : Subobject X) : (representative.obj Y).arrow = Y.arrow :=
rfl
#align category_theory.subobject.representative_arrow CategoryTheory.Subobject.representative_arrow
@[reassoc (attr := simp)]
theorem underlying_arrow {X : C} {Y Z : Subobject X} (f : Y ⟶ Z) :
underlying.map f ≫ arrow Z = arrow Y :=
Over.w (representative.map f)
#align category_theory.subobject.underlying_arrow CategoryTheory.Subobject.underlying_arrow
@[reassoc (attr := simp), elementwise (attr := simp)]
theorem underlyingIso_arrow {X Y : C} (f : X ⟶ Y) [Mono f] :
(underlyingIso f).inv ≫ (Subobject.mk f).arrow = f :=
Over.w _
#align category_theory.subobject.underlying_iso_arrow CategoryTheory.Subobject.underlyingIso_arrow
@[reassoc (attr := simp)]
theorem underlyingIso_hom_comp_eq_mk {X Y : C} (f : X ⟶ Y) [Mono f] :
(underlyingIso f).hom ≫ f = (mk f).arrow :=
(Iso.eq_inv_comp _).1 (underlyingIso_arrow f).symm
#align category_theory.subobject.underlying_iso_hom_comp_eq_mk CategoryTheory.Subobject.underlyingIso_hom_comp_eq_mk
/-- Two morphisms into a subobject are equal exactly if
the morphisms into the ambient object are equal -/
@[ext]
theorem eq_of_comp_arrow_eq {X Y : C} {P : Subobject Y} {f g : X ⟶ P}
(h : f ≫ P.arrow = g ≫ P.arrow) : f = g :=
(cancel_mono P.arrow).mp h
#align category_theory.subobject.eq_of_comp_arrow_eq CategoryTheory.Subobject.eq_of_comp_arrow_eq
theorem mk_le_mk_of_comm {B A₁ A₂ : C} {f₁ : A₁ ⟶ B} {f₂ : A₂ ⟶ B} [Mono f₁] [Mono f₂] (g : A₁ ⟶ A₂)
(w : g ≫ f₂ = f₁) : mk f₁ ≤ mk f₂ :=
⟨MonoOver.homMk _ w⟩
#align category_theory.subobject.mk_le_mk_of_comm CategoryTheory.Subobject.mk_le_mk_of_comm
@[simp]
theorem mk_arrow (P : Subobject X) : mk P.arrow = P :=
Quotient.inductionOn' P fun Q => by
obtain ⟨e⟩ := @Quotient.mk_out' _ (isIsomorphicSetoid _) Q
exact Quotient.sound' ⟨MonoOver.isoMk (Iso.refl _) ≪≫ e⟩
#align category_theory.subobject.mk_arrow CategoryTheory.Subobject.mk_arrow
theorem le_of_comm {B : C} {X Y : Subobject B} (f : (X : C) ⟶ (Y : C)) (w : f ≫ Y.arrow = X.arrow) :
X ≤ Y := by
convert mk_le_mk_of_comm _ w <;> simp
#align category_theory.subobject.le_of_comm CategoryTheory.Subobject.le_of_comm
theorem le_mk_of_comm {B A : C} {X : Subobject B} {f : A ⟶ B} [Mono f] (g : (X : C) ⟶ A)
(w : g ≫ f = X.arrow) : X ≤ mk f :=
le_of_comm (g ≫ (underlyingIso f).inv) <| by simp [w]
#align category_theory.subobject.le_mk_of_comm CategoryTheory.Subobject.le_mk_of_comm
theorem mk_le_of_comm {B A : C} {X : Subobject B} {f : A ⟶ B} [Mono f] (g : A ⟶ (X : C))
(w : g ≫ X.arrow = f) : mk f ≤ X :=
le_of_comm ((underlyingIso f).hom ≫ g) <| by simp [w]
#align category_theory.subobject.mk_le_of_comm CategoryTheory.Subobject.mk_le_of_comm
/-- To show that two subobjects are equal, it suffices to exhibit an isomorphism commuting with
the arrows. -/
@[ext]
theorem eq_of_comm {B : C} {X Y : Subobject B} (f : (X : C) ≅ (Y : C))
(w : f.hom ≫ Y.arrow = X.arrow) : X = Y :=
le_antisymm (le_of_comm f.hom w) <| le_of_comm f.inv <| f.inv_comp_eq.2 w.symm
#align category_theory.subobject.eq_of_comm CategoryTheory.Subobject.eq_of_comm
-- Porting note (#11182): removed @[ext]
/-- To show that two subobjects are equal, it suffices to exhibit an isomorphism commuting with
the arrows. -/
theorem eq_mk_of_comm {B A : C} {X : Subobject B} (f : A ⟶ B) [Mono f] (i : (X : C) ≅ A)
(w : i.hom ≫ f = X.arrow) : X = mk f :=
eq_of_comm (i.trans (underlyingIso f).symm) <| by simp [w]
#align category_theory.subobject.eq_mk_of_comm CategoryTheory.Subobject.eq_mk_of_comm
-- Porting note (#11182): removed @[ext]
/-- To show that two subobjects are equal, it suffices to exhibit an isomorphism commuting with
the arrows. -/
theorem mk_eq_of_comm {B A : C} {X : Subobject B} (f : A ⟶ B) [Mono f] (i : A ≅ (X : C))
(w : i.hom ≫ X.arrow = f) : mk f = X :=
Eq.symm <| eq_mk_of_comm _ i.symm <| by rw [Iso.symm_hom, Iso.inv_comp_eq, w]
#align category_theory.subobject.mk_eq_of_comm CategoryTheory.Subobject.mk_eq_of_comm
-- Porting note (#11182): removed @[ext]
/-- To show that two subobjects are equal, it suffices to exhibit an isomorphism commuting with
the arrows. -/
theorem mk_eq_mk_of_comm {B A₁ A₂ : C} (f : A₁ ⟶ B) (g : A₂ ⟶ B) [Mono f] [Mono g] (i : A₁ ≅ A₂)
(w : i.hom ≫ g = f) : mk f = mk g :=
eq_mk_of_comm _ ((underlyingIso f).trans i) <| by simp [w]
#align category_theory.subobject.mk_eq_mk_of_comm CategoryTheory.Subobject.mk_eq_mk_of_comm
-- We make `X` and `Y` explicit arguments here so that when `ofLE` appears in goal statements
-- it is possible to see its source and target
-- (`h` will just display as `_`, because it is in `Prop`).
/-- An inequality of subobjects is witnessed by some morphism between the corresponding objects. -/
def ofLE {B : C} (X Y : Subobject B) (h : X ≤ Y) : (X : C) ⟶ (Y : C) :=
underlying.map <| h.hom
#align category_theory.subobject.of_le CategoryTheory.Subobject.ofLE
@[reassoc (attr := simp)]
theorem ofLE_arrow {B : C} {X Y : Subobject B} (h : X ≤ Y) : ofLE X Y h ≫ Y.arrow = X.arrow :=
underlying_arrow _
#align category_theory.subobject.of_le_arrow CategoryTheory.Subobject.ofLE_arrow
instance {B : C} (X Y : Subobject B) (h : X ≤ Y) : Mono (ofLE X Y h) := by
fconstructor
intro Z f g w
replace w := w =≫ Y.arrow
ext
simpa using w
theorem ofLE_mk_le_mk_of_comm {B A₁ A₂ : C} {f₁ : A₁ ⟶ B} {f₂ : A₂ ⟶ B} [Mono f₁] [Mono f₂]
(g : A₁ ⟶ A₂) (w : g ≫ f₂ = f₁) :
ofLE _ _ (mk_le_mk_of_comm g w) = (underlyingIso _).hom ≫ g ≫ (underlyingIso _).inv := by
ext
simp [w]
#align category_theory.subobject.of_le_mk_le_mk_of_comm CategoryTheory.Subobject.ofLE_mk_le_mk_of_comm
/-- An inequality of subobjects is witnessed by some morphism between the corresponding objects. -/
def ofLEMk {B A : C} (X : Subobject B) (f : A ⟶ B) [Mono f] (h : X ≤ mk f) : (X : C) ⟶ A :=
ofLE X (mk f) h ≫ (underlyingIso f).hom
#align category_theory.subobject.of_le_mk CategoryTheory.Subobject.ofLEMk
instance {B A : C} (X : Subobject B) (f : A ⟶ B) [Mono f] (h : X ≤ mk f) :
Mono (ofLEMk X f h) := by
dsimp only [ofLEMk]
infer_instance
@[simp]
theorem ofLEMk_comp {B A : C} {X : Subobject B} {f : A ⟶ B} [Mono f] (h : X ≤ mk f) :
ofLEMk X f h ≫ f = X.arrow := by simp [ofLEMk]
#align category_theory.subobject.of_le_mk_comp CategoryTheory.Subobject.ofLEMk_comp
/-- An inequality of subobjects is witnessed by some morphism between the corresponding objects. -/
def ofMkLE {B A : C} (f : A ⟶ B) [Mono f] (X : Subobject B) (h : mk f ≤ X) : A ⟶ (X : C) :=
(underlyingIso f).inv ≫ ofLE (mk f) X h
#align category_theory.subobject.of_mk_le CategoryTheory.Subobject.ofMkLE
instance {B A : C} (f : A ⟶ B) [Mono f] (X : Subobject B) (h : mk f ≤ X) :
Mono (ofMkLE f X h) := by
dsimp only [ofMkLE]
infer_instance
@[simp]
theorem ofMkLE_arrow {B A : C} {f : A ⟶ B} [Mono f] {X : Subobject B} (h : mk f ≤ X) :
ofMkLE f X h ≫ X.arrow = f := by simp [ofMkLE]
#align category_theory.subobject.of_mk_le_arrow CategoryTheory.Subobject.ofMkLE_arrow
/-- An inequality of subobjects is witnessed by some morphism between the corresponding objects. -/
def ofMkLEMk {B A₁ A₂ : C} (f : A₁ ⟶ B) (g : A₂ ⟶ B) [Mono f] [Mono g] (h : mk f ≤ mk g) :
A₁ ⟶ A₂ :=
(underlyingIso f).inv ≫ ofLE (mk f) (mk g) h ≫ (underlyingIso g).hom
#align category_theory.subobject.of_mk_le_mk CategoryTheory.Subobject.ofMkLEMk
instance {B A₁ A₂ : C} (f : A₁ ⟶ B) (g : A₂ ⟶ B) [Mono f] [Mono g] (h : mk f ≤ mk g) :
Mono (ofMkLEMk f g h) := by
dsimp only [ofMkLEMk]
infer_instance
@[simp]
theorem ofMkLEMk_comp {B A₁ A₂ : C} {f : A₁ ⟶ B} {g : A₂ ⟶ B} [Mono f] [Mono g] (h : mk f ≤ mk g) :
ofMkLEMk f g h ≫ g = f := by simp [ofMkLEMk]
#align category_theory.subobject.of_mk_le_mk_comp CategoryTheory.Subobject.ofMkLEMk_comp
@[reassoc (attr := simp)]
theorem ofLE_comp_ofLE {B : C} (X Y Z : Subobject B) (h₁ : X ≤ Y) (h₂ : Y ≤ Z) :
ofLE X Y h₁ ≫ ofLE Y Z h₂ = ofLE X Z (h₁.trans h₂) := by
simp only [ofLE, ← Functor.map_comp underlying]
congr 1
#align category_theory.subobject.of_le_comp_of_le CategoryTheory.Subobject.ofLE_comp_ofLE
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Subobject/Basic.lean | 392 | 395 | theorem ofLE_comp_ofLEMk {B A : C} (X Y : Subobject B) (f : A ⟶ B) [Mono f] (h₁ : X ≤ Y)
(h₂ : Y ≤ mk f) : ofLE X Y h₁ ≫ ofLEMk Y f h₂ = ofLEMk X f (h₁.trans h₂) := by |
simp only [ofMkLE, ofLEMk, ofLE, ← Functor.map_comp_assoc underlying]
congr 1
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Combinatorics.SimpleGraph.Connectivity
import Mathlib.Combinatorics.SimpleGraph.Operations
import Mathlib.Data.Finset.Pairwise
#align_import combinatorics.simple_graph.clique from "leanprover-community/mathlib"@"3365b20c2ffa7c35e47e5209b89ba9abdddf3ffe"
/-!
# Graph cliques
This file defines cliques in simple graphs. A clique is a set of vertices that are pairwise
adjacent.
## Main declarations
* `SimpleGraph.IsClique`: Predicate for a set of vertices to be a clique.
* `SimpleGraph.IsNClique`: Predicate for a set of vertices to be an `n`-clique.
* `SimpleGraph.cliqueFinset`: Finset of `n`-cliques of a graph.
* `SimpleGraph.CliqueFree`: Predicate for a graph to have no `n`-cliques.
## TODO
* Clique numbers
* Dualise all the API to get independent sets
-/
open Finset Fintype Function SimpleGraph.Walk
namespace SimpleGraph
variable {α β : Type*} (G H : SimpleGraph α)
/-! ### Cliques -/
section Clique
variable {s t : Set α}
/-- A clique in a graph is a set of vertices that are pairwise adjacent. -/
abbrev IsClique (s : Set α) : Prop :=
s.Pairwise G.Adj
#align simple_graph.is_clique SimpleGraph.IsClique
theorem isClique_iff : G.IsClique s ↔ s.Pairwise G.Adj :=
Iff.rfl
#align simple_graph.is_clique_iff SimpleGraph.isClique_iff
/-- A clique is a set of vertices whose induced graph is complete. -/
theorem isClique_iff_induce_eq : G.IsClique s ↔ G.induce s = ⊤ := by
rw [isClique_iff]
constructor
· intro h
ext ⟨v, hv⟩ ⟨w, hw⟩
simp only [comap_adj, Subtype.coe_mk, top_adj, Ne, Subtype.mk_eq_mk]
exact ⟨Adj.ne, h hv hw⟩
· intro h v hv w hw hne
have h2 : (G.induce s).Adj ⟨v, hv⟩ ⟨w, hw⟩ = _ := rfl
conv_lhs at h2 => rw [h]
simp only [top_adj, ne_eq, Subtype.mk.injEq, eq_iff_iff] at h2
exact h2.1 hne
#align simple_graph.is_clique_iff_induce_eq SimpleGraph.isClique_iff_induce_eq
instance [DecidableEq α] [DecidableRel G.Adj] {s : Finset α} : Decidable (G.IsClique s) :=
decidable_of_iff' _ G.isClique_iff
variable {G H} {a b : α}
lemma isClique_empty : G.IsClique ∅ := by simp
#align simple_graph.is_clique_empty SimpleGraph.isClique_empty
lemma isClique_singleton (a : α) : G.IsClique {a} := by simp
#align simple_graph.is_clique_singleton SimpleGraph.isClique_singleton
lemma isClique_pair : G.IsClique {a, b} ↔ a ≠ b → G.Adj a b := Set.pairwise_pair_of_symmetric G.symm
#align simple_graph.is_clique_pair SimpleGraph.isClique_pair
@[simp]
lemma isClique_insert : G.IsClique (insert a s) ↔ G.IsClique s ∧ ∀ b ∈ s, a ≠ b → G.Adj a b :=
Set.pairwise_insert_of_symmetric G.symm
#align simple_graph.is_clique_insert SimpleGraph.isClique_insert
lemma isClique_insert_of_not_mem (ha : a ∉ s) :
G.IsClique (insert a s) ↔ G.IsClique s ∧ ∀ b ∈ s, G.Adj a b :=
Set.pairwise_insert_of_symmetric_of_not_mem G.symm ha
#align simple_graph.is_clique_insert_of_not_mem SimpleGraph.isClique_insert_of_not_mem
lemma IsClique.insert (hs : G.IsClique s) (h : ∀ b ∈ s, a ≠ b → G.Adj a b) :
G.IsClique (insert a s) := hs.insert_of_symmetric G.symm h
#align simple_graph.is_clique.insert SimpleGraph.IsClique.insert
theorem IsClique.mono (h : G ≤ H) : G.IsClique s → H.IsClique s := Set.Pairwise.mono' h
#align simple_graph.is_clique.mono SimpleGraph.IsClique.mono
theorem IsClique.subset (h : t ⊆ s) : G.IsClique s → G.IsClique t := Set.Pairwise.mono h
#align simple_graph.is_clique.subset SimpleGraph.IsClique.subset
protected theorem IsClique.map {s : Set α} (h : G.IsClique s) {f : α ↪ β} :
(G.map f).IsClique (f '' s) := by
rintro _ ⟨a, ha, rfl⟩ _ ⟨b, hb, rfl⟩ hab
exact ⟨a, b, h ha hb <| ne_of_apply_ne _ hab, rfl, rfl⟩
#align simple_graph.is_clique.map SimpleGraph.IsClique.map
@[simp]
theorem isClique_bot_iff : (⊥ : SimpleGraph α).IsClique s ↔ (s : Set α).Subsingleton :=
Set.pairwise_bot_iff
#align simple_graph.is_clique_bot_iff SimpleGraph.isClique_bot_iff
alias ⟨IsClique.subsingleton, _⟩ := isClique_bot_iff
#align simple_graph.is_clique.subsingleton SimpleGraph.IsClique.subsingleton
end Clique
/-! ### `n`-cliques -/
section NClique
variable {n : ℕ} {s : Finset α}
/-- An `n`-clique in a graph is a set of `n` vertices which are pairwise connected. -/
structure IsNClique (n : ℕ) (s : Finset α) : Prop where
clique : G.IsClique s
card_eq : s.card = n
#align simple_graph.is_n_clique SimpleGraph.IsNClique
theorem isNClique_iff : G.IsNClique n s ↔ G.IsClique s ∧ s.card = n :=
⟨fun h ↦ ⟨h.1, h.2⟩, fun h ↦ ⟨h.1, h.2⟩⟩
#align simple_graph.is_n_clique_iff SimpleGraph.isNClique_iff
instance [DecidableEq α] [DecidableRel G.Adj] {n : ℕ} {s : Finset α} :
Decidable (G.IsNClique n s) :=
decidable_of_iff' _ G.isNClique_iff
variable {G H} {a b c : α}
@[simp] lemma isNClique_empty : G.IsNClique n ∅ ↔ n = 0 := by simp [isNClique_iff, eq_comm]
#align simple_graph.is_n_clique_empty SimpleGraph.isNClique_empty
@[simp]
lemma isNClique_singleton : G.IsNClique n {a} ↔ n = 1 := by simp [isNClique_iff, eq_comm]
#align simple_graph.is_n_clique_singleton SimpleGraph.isNClique_singleton
theorem IsNClique.mono (h : G ≤ H) : G.IsNClique n s → H.IsNClique n s := by
simp_rw [isNClique_iff]
exact And.imp_left (IsClique.mono h)
#align simple_graph.is_n_clique.mono SimpleGraph.IsNClique.mono
protected theorem IsNClique.map (h : G.IsNClique n s) {f : α ↪ β} :
(G.map f).IsNClique n (s.map f) :=
⟨by rw [coe_map]; exact h.1.map, (card_map _).trans h.2⟩
#align simple_graph.is_n_clique.map SimpleGraph.IsNClique.map
@[simp]
theorem isNClique_bot_iff : (⊥ : SimpleGraph α).IsNClique n s ↔ n ≤ 1 ∧ s.card = n := by
rw [isNClique_iff, isClique_bot_iff]
refine and_congr_left ?_
rintro rfl
exact card_le_one.symm
#align simple_graph.is_n_clique_bot_iff SimpleGraph.isNClique_bot_iff
@[simp]
theorem isNClique_zero : G.IsNClique 0 s ↔ s = ∅ := by
simp only [isNClique_iff, Finset.card_eq_zero, and_iff_right_iff_imp]; rintro rfl; simp
#align simple_graph.is_n_clique_zero SimpleGraph.isNClique_zero
@[simp]
theorem isNClique_one : G.IsNClique 1 s ↔ ∃ a, s = {a} := by
simp only [isNClique_iff, card_eq_one, and_iff_right_iff_imp]; rintro ⟨a, rfl⟩; simp
#align simple_graph.is_n_clique_one SimpleGraph.isNClique_one
section DecidableEq
variable [DecidableEq α]
theorem IsNClique.insert (hs : G.IsNClique n s) (h : ∀ b ∈ s, G.Adj a b) :
G.IsNClique (n + 1) (insert a s) := by
constructor
· push_cast
exact hs.1.insert fun b hb _ => h _ hb
· rw [card_insert_of_not_mem fun ha => (h _ ha).ne rfl, hs.2]
#align simple_graph.is_n_clique.insert SimpleGraph.IsNClique.insert
theorem is3Clique_triple_iff : G.IsNClique 3 {a, b, c} ↔ G.Adj a b ∧ G.Adj a c ∧ G.Adj b c := by
simp only [isNClique_iff, isClique_iff, Set.pairwise_insert_of_symmetric G.symm, coe_insert]
by_cases hab : a = b <;> by_cases hbc : b = c <;> by_cases hac : a = c <;> subst_vars <;>
simp [G.ne_of_adj, and_rotate, *]
#align simple_graph.is_3_clique_triple_iff SimpleGraph.is3Clique_triple_iff
theorem is3Clique_iff :
G.IsNClique 3 s ↔ ∃ a b c, G.Adj a b ∧ G.Adj a c ∧ G.Adj b c ∧ s = {a, b, c} := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, b, c, -, -, -, hs⟩ := card_eq_three.1 h.card_eq
refine ⟨a, b, c, ?_⟩
rwa [hs, eq_self_iff_true, and_true, is3Clique_triple_iff.symm, ← hs]
· rintro ⟨a, b, c, hab, hbc, hca, rfl⟩
exact is3Clique_triple_iff.2 ⟨hab, hbc, hca⟩
#align simple_graph.is_3_clique_iff SimpleGraph.is3Clique_iff
end DecidableEq
theorem is3Clique_iff_exists_cycle_length_three :
(∃ s : Finset α, G.IsNClique 3 s) ↔ ∃ (u : α) (w : G.Walk u u), w.IsCycle ∧ w.length = 3 := by
classical
simp_rw [is3Clique_iff, isCycle_def]
exact
⟨(fun ⟨_, a, _, _, hab, hac, hbc, _⟩ => ⟨a, cons hab (cons hbc (cons hac.symm nil)), by aesop⟩),
(fun ⟨_, .cons hab (.cons hbc (.cons hca nil)), _, _⟩ => ⟨_, _, _, _, hab, hca.symm, hbc, rfl⟩)⟩
end NClique
/-! ### Graphs without cliques -/
section CliqueFree
variable {m n : ℕ}
/-- `G.CliqueFree n` means that `G` has no `n`-cliques. -/
def CliqueFree (n : ℕ) : Prop :=
∀ t, ¬G.IsNClique n t
#align simple_graph.clique_free SimpleGraph.CliqueFree
variable {G H} {s : Finset α}
theorem IsNClique.not_cliqueFree (hG : G.IsNClique n s) : ¬G.CliqueFree n :=
fun h ↦ h _ hG
#align simple_graph.is_n_clique.not_clique_free SimpleGraph.IsNClique.not_cliqueFree
theorem not_cliqueFree_of_top_embedding {n : ℕ} (f : (⊤ : SimpleGraph (Fin n)) ↪g G) :
¬G.CliqueFree n := by
simp only [CliqueFree, isNClique_iff, isClique_iff_induce_eq, not_forall, Classical.not_not]
use Finset.univ.map f.toEmbedding
simp only [card_map, Finset.card_fin, eq_self_iff_true, and_true_iff]
ext ⟨v, hv⟩ ⟨w, hw⟩
simp only [coe_map, Set.mem_image, coe_univ, Set.mem_univ, true_and_iff] at hv hw
obtain ⟨v', rfl⟩ := hv
obtain ⟨w', rfl⟩ := hw
simp only [coe_sort_coe, RelEmbedding.coe_toEmbedding, comap_adj, Function.Embedding.coe_subtype,
f.map_adj_iff, top_adj, ne_eq, Subtype.mk.injEq, RelEmbedding.inj]
-- This used to be the end of the proof before leanprover/lean4#2644
erw [Function.Embedding.coe_subtype, f.map_adj_iff]
simp
#align simple_graph.not_clique_free_of_top_embedding SimpleGraph.not_cliqueFree_of_top_embedding
/-- An embedding of a complete graph that witnesses the fact that the graph is not clique-free. -/
noncomputable def topEmbeddingOfNotCliqueFree {n : ℕ} (h : ¬G.CliqueFree n) :
(⊤ : SimpleGraph (Fin n)) ↪g G := by
simp only [CliqueFree, isNClique_iff, isClique_iff_induce_eq, not_forall, Classical.not_not] at h
obtain ⟨ha, hb⟩ := h.choose_spec
have : (⊤ : SimpleGraph (Fin h.choose.card)) ≃g (⊤ : SimpleGraph h.choose) := by
apply Iso.completeGraph
simpa using (Fintype.equivFin h.choose).symm
rw [← ha] at this
convert (Embedding.induce ↑h.choose.toSet).comp this.toEmbedding
exact hb.symm
#align simple_graph.top_embedding_of_not_clique_free SimpleGraph.topEmbeddingOfNotCliqueFree
theorem not_cliqueFree_iff (n : ℕ) : ¬G.CliqueFree n ↔ Nonempty ((⊤ : SimpleGraph (Fin n)) ↪g G) :=
⟨fun h ↦ ⟨topEmbeddingOfNotCliqueFree h⟩, fun ⟨f⟩ ↦ not_cliqueFree_of_top_embedding f⟩
#align simple_graph.not_clique_free_iff SimpleGraph.not_cliqueFree_iff
theorem cliqueFree_iff {n : ℕ} : G.CliqueFree n ↔ IsEmpty ((⊤ : SimpleGraph (Fin n)) ↪g G) := by
rw [← not_iff_not, not_cliqueFree_iff, not_isEmpty_iff]
#align simple_graph.clique_free_iff SimpleGraph.cliqueFree_iff
theorem not_cliqueFree_card_of_top_embedding [Fintype α] (f : (⊤ : SimpleGraph α) ↪g G) :
¬G.CliqueFree (card α) := by
rw [not_cliqueFree_iff]
exact ⟨(Iso.completeGraph (Fintype.equivFin α)).symm.toEmbedding.trans f⟩
#align simple_graph.not_clique_free_card_of_top_embedding SimpleGraph.not_cliqueFree_card_of_top_embedding
@[simp]
theorem cliqueFree_bot (h : 2 ≤ n) : (⊥ : SimpleGraph α).CliqueFree n := by
intro t ht
have := le_trans h (isNClique_bot_iff.1 ht).1
contradiction
#align simple_graph.clique_free_bot SimpleGraph.cliqueFree_bot
theorem CliqueFree.mono (h : m ≤ n) : G.CliqueFree m → G.CliqueFree n := by
intro hG s hs
obtain ⟨t, hts, ht⟩ := s.exists_smaller_set _ (h.trans hs.card_eq.ge)
exact hG _ ⟨hs.clique.subset hts, ht⟩
#align simple_graph.clique_free.mono SimpleGraph.CliqueFree.mono
theorem CliqueFree.anti (h : G ≤ H) : H.CliqueFree n → G.CliqueFree n :=
forall_imp fun _ ↦ mt <| IsNClique.mono h
#align simple_graph.clique_free.anti SimpleGraph.CliqueFree.anti
/-- If a graph is cliquefree, any graph that embeds into it is also cliquefree. -/
theorem CliqueFree.comap {H : SimpleGraph β} (f : H ↪g G) : G.CliqueFree n → H.CliqueFree n := by
intro h; contrapose h
exact not_cliqueFree_of_top_embedding <| f.comp (topEmbeddingOfNotCliqueFree h)
/-- See `SimpleGraph.cliqueFree_of_chromaticNumber_lt` for a tighter bound. -/
theorem cliqueFree_of_card_lt [Fintype α] (hc : card α < n) : G.CliqueFree n := by
by_contra h
refine Nat.lt_le_asymm hc ?_
rw [cliqueFree_iff, not_isEmpty_iff] at h
simpa only [Fintype.card_fin] using Fintype.card_le_of_embedding h.some.toEmbedding
#align simple_graph.clique_free_of_card_lt SimpleGraph.cliqueFree_of_card_lt
/-- A complete `r`-partite graph has no `n`-cliques for `r < n`. -/
| Mathlib/Combinatorics/SimpleGraph/Clique.lean | 309 | 315 | theorem cliqueFree_completeMultipartiteGraph {ι : Type*} [Fintype ι] (V : ι → Type*)
(hc : card ι < n) : (completeMultipartiteGraph V).CliqueFree n := by |
rw [cliqueFree_iff, isEmpty_iff]
intro f
obtain ⟨v, w, hn, he⟩ := exists_ne_map_eq_of_card_lt (Sigma.fst ∘ f) (by simp [hc])
rw [← top_adj, ← f.map_adj_iff, comap_adj, top_adj] at hn
exact absurd he hn
|
/-
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`. -/
| Mathlib/MeasureTheory/Integral/IntervalIntegral.lean | 83 | 84 | theorem intervalIntegrable_iff : IntervalIntegrable f μ a b ↔ IntegrableOn f (Ι a b) μ := by |
rw [uIoc_eq_union, integrableOn_union, IntervalIntegrable]
|
/-
Copyright (c) 2018 Simon Hudon. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Simon Hudon, Patrick Massot
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.Algebra.Ring.Pi
import Mathlib.GroupTheory.GroupAction.Pi
#align_import algebra.big_operators.pi from "leanprover-community/mathlib"@"fa2309577c7009ea243cffdf990cd6c84f0ad497"
/-!
# Big operators for Pi Types
This file contains theorems relevant to big operators in binary and arbitrary product
of monoids and groups
-/
namespace Pi
@[to_additive]
theorem list_prod_apply {α : Type*} {β : α → Type*} [∀ a, Monoid (β a)] (a : α)
(l : List (∀ a, β a)) : l.prod a = (l.map fun f : ∀ a, β a ↦ f a).prod :=
map_list_prod (evalMonoidHom β a) _
#align pi.list_prod_apply Pi.list_prod_apply
#align pi.list_sum_apply Pi.list_sum_apply
@[to_additive]
theorem multiset_prod_apply {α : Type*} {β : α → Type*} [∀ a, CommMonoid (β a)] (a : α)
(s : Multiset (∀ a, β a)) : s.prod a = (s.map fun f : ∀ a, β a ↦ f a).prod :=
(evalMonoidHom β a).map_multiset_prod _
#align pi.multiset_prod_apply Pi.multiset_prod_apply
#align pi.multiset_sum_apply Pi.multiset_sum_apply
end Pi
@[to_additive (attr := simp)]
theorem Finset.prod_apply {α : Type*} {β : α → Type*} {γ} [∀ a, CommMonoid (β a)] (a : α)
(s : Finset γ) (g : γ → ∀ a, β a) : (∏ c ∈ s, g c) a = ∏ c ∈ s, g c a :=
map_prod (Pi.evalMonoidHom β a) _ _
#align finset.prod_apply Finset.prod_apply
#align finset.sum_apply Finset.sum_apply
/-- An 'unapplied' analogue of `Finset.prod_apply`. -/
@[to_additive "An 'unapplied' analogue of `Finset.sum_apply`."]
theorem Finset.prod_fn {α : Type*} {β : α → Type*} {γ} [∀ a, CommMonoid (β a)] (s : Finset γ)
(g : γ → ∀ a, β a) : ∏ c ∈ s, g c = fun a ↦ ∏ c ∈ s, g c a :=
funext fun _ ↦ Finset.prod_apply _ _ _
#align finset.prod_fn Finset.prod_fn
#align finset.sum_fn Finset.sum_fn
@[to_additive]
theorem Fintype.prod_apply {α : Type*} {β : α → Type*} {γ : Type*} [Fintype γ]
[∀ a, CommMonoid (β a)] (a : α) (g : γ → ∀ a, β a) : (∏ c, g c) a = ∏ c, g c a :=
Finset.prod_apply a Finset.univ g
#align fintype.prod_apply Fintype.prod_apply
#align fintype.sum_apply Fintype.sum_apply
@[to_additive prod_mk_sum]
theorem prod_mk_prod {α β γ : Type*} [CommMonoid α] [CommMonoid β] (s : Finset γ) (f : γ → α)
(g : γ → β) : (∏ x ∈ s, f x, ∏ x ∈ s, g x) = ∏ x ∈ s, (f x, g x) :=
haveI := Classical.decEq γ
Finset.induction_on s rfl (by simp (config := { contextual := true }) [Prod.ext_iff])
#align prod_mk_prod prod_mk_prod
#align prod_mk_sum prod_mk_sum
/-- decomposing `x : ι → R` as a sum along the canonical basis -/
theorem pi_eq_sum_univ {ι : Type*} [Fintype ι] [DecidableEq ι] {R : Type*} [Semiring R]
(x : ι → R) : x = ∑ i, (x i) • fun j => if i = j then (1 : R) else 0 := by
ext
simp
#align pi_eq_sum_univ pi_eq_sum_univ
section MulSingle
variable {I : Type*} [DecidableEq I] {Z : I → Type*}
variable [∀ i, CommMonoid (Z i)]
@[to_additive]
theorem Finset.univ_prod_mulSingle [Fintype I] (f : ∀ i, Z i) :
(∏ i, Pi.mulSingle i (f i)) = f := by
ext a
simp
#align finset.univ_prod_mul_single Finset.univ_prod_mulSingle
#align finset.univ_sum_single Finset.univ_sum_single
@[to_additive]
| Mathlib/Algebra/BigOperators/Pi.lean | 89 | 94 | theorem MonoidHom.functions_ext [Finite I] (G : Type*) [CommMonoid G] (g h : (∀ i, Z i) →* G)
(H : ∀ i x, g (Pi.mulSingle i x) = h (Pi.mulSingle i x)) : g = h := by |
cases nonempty_fintype I
ext k
rw [← Finset.univ_prod_mulSingle k, map_prod, map_prod]
simp only [H]
|
/-
Copyright (c) 2020 Kexing Ying and Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying, Kevin Buzzard, Yury Kudryashov
-/
import Mathlib.Algebra.BigOperators.GroupWithZero.Finset
import Mathlib.Algebra.Group.FiniteSupport
import Mathlib.Algebra.Module.Defs
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Data.Set.Subsingleton
#align_import algebra.big_operators.finprod from "leanprover-community/mathlib"@"d6fad0e5bf2d6f48da9175d25c3dc5706b3834ce"
/-!
# Finite products and sums over types and sets
We define products and sums over types and subsets of types, with no finiteness hypotheses.
All infinite products and sums are defined to be junk values (i.e. one or zero).
This approach is sometimes easier to use than `Finset.sum`,
when issues arise with `Finset` and `Fintype` being data.
## Main definitions
We use the following variables:
* `α`, `β` - types with no structure;
* `s`, `t` - sets
* `M`, `N` - additive or multiplicative commutative monoids
* `f`, `g` - functions
Definitions in this file:
* `finsum f : M` : the sum of `f x` as `x` ranges over the support of `f`, if it's finite.
Zero otherwise.
* `finprod f : M` : the product of `f x` as `x` ranges over the multiplicative support of `f`, if
it's finite. One otherwise.
## Notation
* `∑ᶠ i, f i` and `∑ᶠ i : α, f i` for `finsum f`
* `∏ᶠ i, f i` and `∏ᶠ i : α, f i` for `finprod f`
This notation works for functions `f : p → M`, where `p : Prop`, so the following works:
* `∑ᶠ i ∈ s, f i`, where `f : α → M`, `s : Set α` : sum over the set `s`;
* `∑ᶠ n < 5, f n`, where `f : ℕ → M` : same as `f 0 + f 1 + f 2 + f 3 + f 4`;
* `∏ᶠ (n >= -2) (hn : n < 3), f n`, where `f : ℤ → M` : same as `f (-2) * f (-1) * f 0 * f 1 * f 2`.
## Implementation notes
`finsum` and `finprod` is "yet another way of doing finite sums and products in Lean". However
experiments in the wild (e.g. with matroids) indicate that it is a helpful approach in settings
where the user is not interested in computability and wants to do reasoning without running into
typeclass diamonds caused by the constructive finiteness used in definitions such as `Finset` and
`Fintype`. By sticking solely to `Set.Finite` we avoid these problems. We are aware that there are
other solutions but for beginner mathematicians this approach is easier in practice.
Another application is the construction of a partition of unity from a collection of “bump”
function. In this case the finite set depends on the point and it's convenient to have a definition
that does not mention the set explicitly.
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.
We did not add `IsFinite (X : Type) : Prop`, because it is simply `Nonempty (Fintype X)`.
## Tags
finsum, finprod, finite sum, finite product
-/
open Function Set
/-!
### Definition and relation to `Finset.sum` and `Finset.prod`
-/
-- Porting note: Used to be section Sort
section sort
variable {G M N : Type*} {α β ι : Sort*} [CommMonoid M] [CommMonoid N]
section
/- Note: we use classical logic only for these definitions, to ensure that we do not write lemmas
with `Classical.dec` in their statement. -/
open scoped Classical
/-- Sum of `f x` as `x` ranges over the elements of the support of `f`, if it's finite. Zero
otherwise. -/
noncomputable irreducible_def finsum (lemma := finsum_def') [AddCommMonoid M] (f : α → M) : M :=
if h : (support (f ∘ PLift.down)).Finite then ∑ i ∈ h.toFinset, f i.down else 0
#align finsum finsum
/-- Product of `f x` as `x` ranges over the elements of the multiplicative support of `f`, if it's
finite. One otherwise. -/
@[to_additive existing]
noncomputable irreducible_def finprod (lemma := finprod_def') (f : α → M) : M :=
if h : (mulSupport (f ∘ PLift.down)).Finite then ∏ i ∈ h.toFinset, f i.down else 1
#align finprod finprod
attribute [to_additive existing] finprod_def'
end
open Batteries.ExtendedBinder
/-- `∑ᶠ x, f x` is notation for `finsum f`. It is the sum of `f x`, where `x` ranges over the
support of `f`, if it's finite, zero otherwise. Taking the sum over multiple arguments or
conditions is possible, e.g. `∏ᶠ (x) (y), f x y` and `∏ᶠ (x) (h: x ∈ s), f x`-/
notation3"∑ᶠ "(...)", "r:67:(scoped f => finsum f) => r
/-- `∏ᶠ x, f x` is notation for `finprod f`. It is the product of `f x`, where `x` ranges over the
multiplicative support of `f`, if it's finite, one otherwise. Taking the product over multiple
arguments or conditions is possible, e.g. `∏ᶠ (x) (y), f x y` and `∏ᶠ (x) (h: x ∈ s), f x`-/
notation3"∏ᶠ "(...)", "r:67:(scoped f => finprod f) => r
-- Porting note: The following ports the lean3 notation for this file, but is currently very fickle.
-- syntax (name := bigfinsum) "∑ᶠ" extBinders ", " term:67 : term
-- macro_rules (kind := bigfinsum)
-- | `(∑ᶠ $x:ident, $p) => `(finsum (fun $x:ident ↦ $p))
-- | `(∑ᶠ $x:ident : $t, $p) => `(finsum (fun $x:ident : $t ↦ $p))
-- | `(∑ᶠ $x:ident $b:binderPred, $p) =>
-- `(finsum fun $x => (finsum (α := satisfies_binder_pred% $x $b) (fun _ => $p)))
-- | `(∑ᶠ ($x:ident) ($h:ident : $t), $p) =>
-- `(finsum fun ($x) => finsum (α := $t) (fun $h => $p))
-- | `(∑ᶠ ($x:ident : $_) ($h:ident : $t), $p) =>
-- `(finsum fun ($x) => finsum (α := $t) (fun $h => $p))
-- | `(∑ᶠ ($x:ident) ($y:ident), $p) =>
-- `(finsum fun $x => (finsum fun $y => $p))
-- | `(∑ᶠ ($x:ident) ($y:ident) ($h:ident : $t), $p) =>
-- `(finsum fun $x => (finsum fun $y => (finsum (α := $t) fun $h => $p)))
-- | `(∑ᶠ ($x:ident) ($y:ident) ($z:ident), $p) =>
-- `(finsum fun $x => (finsum fun $y => (finsum fun $z => $p)))
-- | `(∑ᶠ ($x:ident) ($y:ident) ($z:ident) ($h:ident : $t), $p) =>
-- `(finsum fun $x => (finsum fun $y => (finsum fun $z => (finsum (α := $t) fun $h => $p))))
--
--
-- syntax (name := bigfinprod) "∏ᶠ " extBinders ", " term:67 : term
-- macro_rules (kind := bigfinprod)
-- | `(∏ᶠ $x:ident, $p) => `(finprod (fun $x:ident ↦ $p))
-- | `(∏ᶠ $x:ident : $t, $p) => `(finprod (fun $x:ident : $t ↦ $p))
-- | `(∏ᶠ $x:ident $b:binderPred, $p) =>
-- `(finprod fun $x => (finprod (α := satisfies_binder_pred% $x $b) (fun _ => $p)))
-- | `(∏ᶠ ($x:ident) ($h:ident : $t), $p) =>
-- `(finprod fun ($x) => finprod (α := $t) (fun $h => $p))
-- | `(∏ᶠ ($x:ident : $_) ($h:ident : $t), $p) =>
-- `(finprod fun ($x) => finprod (α := $t) (fun $h => $p))
-- | `(∏ᶠ ($x:ident) ($y:ident), $p) =>
-- `(finprod fun $x => (finprod fun $y => $p))
-- | `(∏ᶠ ($x:ident) ($y:ident) ($h:ident : $t), $p) =>
-- `(finprod fun $x => (finprod fun $y => (finprod (α := $t) fun $h => $p)))
-- | `(∏ᶠ ($x:ident) ($y:ident) ($z:ident), $p) =>
-- `(finprod fun $x => (finprod fun $y => (finprod fun $z => $p)))
-- | `(∏ᶠ ($x:ident) ($y:ident) ($z:ident) ($h:ident : $t), $p) =>
-- `(finprod fun $x => (finprod fun $y => (finprod fun $z =>
-- (finprod (α := $t) fun $h => $p))))
@[to_additive]
theorem finprod_eq_prod_plift_of_mulSupport_toFinset_subset {f : α → M}
(hf : (mulSupport (f ∘ PLift.down)).Finite) {s : Finset (PLift α)} (hs : hf.toFinset ⊆ s) :
∏ᶠ i, f i = ∏ i ∈ s, f i.down := by
rw [finprod, dif_pos]
refine Finset.prod_subset hs fun x _ hxf => ?_
rwa [hf.mem_toFinset, nmem_mulSupport] at hxf
#align finprod_eq_prod_plift_of_mul_support_to_finset_subset finprod_eq_prod_plift_of_mulSupport_toFinset_subset
#align finsum_eq_sum_plift_of_support_to_finset_subset finsum_eq_sum_plift_of_support_toFinset_subset
@[to_additive]
theorem finprod_eq_prod_plift_of_mulSupport_subset {f : α → M} {s : Finset (PLift α)}
(hs : mulSupport (f ∘ PLift.down) ⊆ s) : ∏ᶠ i, f i = ∏ i ∈ s, f i.down :=
finprod_eq_prod_plift_of_mulSupport_toFinset_subset (s.finite_toSet.subset hs) fun x hx => by
rw [Finite.mem_toFinset] at hx
exact hs hx
#align finprod_eq_prod_plift_of_mul_support_subset finprod_eq_prod_plift_of_mulSupport_subset
#align finsum_eq_sum_plift_of_support_subset finsum_eq_sum_plift_of_support_subset
@[to_additive (attr := simp)]
theorem finprod_one : (∏ᶠ _ : α, (1 : M)) = 1 := by
have : (mulSupport fun x : PLift α => (fun _ => 1 : α → M) x.down) ⊆ (∅ : Finset (PLift α)) :=
fun x h => by simp at h
rw [finprod_eq_prod_plift_of_mulSupport_subset this, Finset.prod_empty]
#align finprod_one finprod_one
#align finsum_zero finsum_zero
@[to_additive]
theorem finprod_of_isEmpty [IsEmpty α] (f : α → M) : ∏ᶠ i, f i = 1 := by
rw [← finprod_one]
congr
simp [eq_iff_true_of_subsingleton]
#align finprod_of_is_empty finprod_of_isEmpty
#align finsum_of_is_empty finsum_of_isEmpty
@[to_additive (attr := simp)]
theorem finprod_false (f : False → M) : ∏ᶠ i, f i = 1 :=
finprod_of_isEmpty _
#align finprod_false finprod_false
#align finsum_false finsum_false
@[to_additive]
theorem finprod_eq_single (f : α → M) (a : α) (ha : ∀ x, x ≠ a → f x = 1) :
∏ᶠ x, f x = f a := by
have : mulSupport (f ∘ PLift.down) ⊆ ({PLift.up a} : Finset (PLift α)) := by
intro x
contrapose
simpa [PLift.eq_up_iff_down_eq] using ha x.down
rw [finprod_eq_prod_plift_of_mulSupport_subset this, Finset.prod_singleton]
#align finprod_eq_single finprod_eq_single
#align finsum_eq_single finsum_eq_single
@[to_additive]
theorem finprod_unique [Unique α] (f : α → M) : ∏ᶠ i, f i = f default :=
finprod_eq_single f default fun _x hx => (hx <| Unique.eq_default _).elim
#align finprod_unique finprod_unique
#align finsum_unique finsum_unique
@[to_additive (attr := simp)]
theorem finprod_true (f : True → M) : ∏ᶠ i, f i = f trivial :=
@finprod_unique M True _ ⟨⟨trivial⟩, fun _ => rfl⟩ f
#align finprod_true finprod_true
#align finsum_true finsum_true
@[to_additive]
theorem finprod_eq_dif {p : Prop} [Decidable p] (f : p → M) :
∏ᶠ i, f i = if h : p then f h else 1 := by
split_ifs with h
· haveI : Unique p := ⟨⟨h⟩, fun _ => rfl⟩
exact finprod_unique f
· haveI : IsEmpty p := ⟨h⟩
exact finprod_of_isEmpty f
#align finprod_eq_dif finprod_eq_dif
#align finsum_eq_dif finsum_eq_dif
@[to_additive]
theorem finprod_eq_if {p : Prop} [Decidable p] {x : M} : ∏ᶠ _ : p, x = if p then x else 1 :=
finprod_eq_dif fun _ => x
#align finprod_eq_if finprod_eq_if
#align finsum_eq_if finsum_eq_if
@[to_additive]
theorem finprod_congr {f g : α → M} (h : ∀ x, f x = g x) : finprod f = finprod g :=
congr_arg _ <| funext h
#align finprod_congr finprod_congr
#align finsum_congr finsum_congr
@[to_additive (attr := congr)]
theorem finprod_congr_Prop {p q : Prop} {f : p → M} {g : q → M} (hpq : p = q)
(hfg : ∀ h : q, f (hpq.mpr h) = g h) : finprod f = finprod g := by
subst q
exact finprod_congr hfg
#align finprod_congr_Prop finprod_congr_Prop
#align finsum_congr_Prop finsum_congr_Prop
/-- To prove a property of a finite product, it suffices to prove that the property is
multiplicative and holds on the factors. -/
@[to_additive
"To prove a property of a finite sum, it suffices to prove that the property is
additive and holds on the summands."]
theorem finprod_induction {f : α → M} (p : M → Prop) (hp₀ : p 1)
(hp₁ : ∀ x y, p x → p y → p (x * y)) (hp₂ : ∀ i, p (f i)) : p (∏ᶠ i, f i) := by
rw [finprod]
split_ifs
exacts [Finset.prod_induction _ _ hp₁ hp₀ fun i _ => hp₂ _, hp₀]
#align finprod_induction finprod_induction
#align finsum_induction finsum_induction
theorem finprod_nonneg {R : Type*} [OrderedCommSemiring R] {f : α → R} (hf : ∀ x, 0 ≤ f x) :
0 ≤ ∏ᶠ x, f x :=
finprod_induction (fun x => 0 ≤ x) zero_le_one (fun _ _ => mul_nonneg) hf
#align finprod_nonneg finprod_nonneg
@[to_additive finsum_nonneg]
theorem one_le_finprod' {M : Type*} [OrderedCommMonoid M] {f : α → M} (hf : ∀ i, 1 ≤ f i) :
1 ≤ ∏ᶠ i, f i :=
finprod_induction _ le_rfl (fun _ _ => one_le_mul) hf
#align one_le_finprod' one_le_finprod'
#align finsum_nonneg finsum_nonneg
@[to_additive]
theorem MonoidHom.map_finprod_plift (f : M →* N) (g : α → M)
(h : (mulSupport <| g ∘ PLift.down).Finite) : f (∏ᶠ x, g x) = ∏ᶠ x, f (g x) := by
rw [finprod_eq_prod_plift_of_mulSupport_subset h.coe_toFinset.ge,
finprod_eq_prod_plift_of_mulSupport_subset, map_prod]
rw [h.coe_toFinset]
exact mulSupport_comp_subset f.map_one (g ∘ PLift.down)
#align monoid_hom.map_finprod_plift MonoidHom.map_finprod_plift
#align add_monoid_hom.map_finsum_plift AddMonoidHom.map_finsum_plift
@[to_additive]
theorem MonoidHom.map_finprod_Prop {p : Prop} (f : M →* N) (g : p → M) :
f (∏ᶠ x, g x) = ∏ᶠ x, f (g x) :=
f.map_finprod_plift g (Set.toFinite _)
#align monoid_hom.map_finprod_Prop MonoidHom.map_finprod_Prop
#align add_monoid_hom.map_finsum_Prop AddMonoidHom.map_finsum_Prop
@[to_additive]
theorem MonoidHom.map_finprod_of_preimage_one (f : M →* N) (hf : ∀ x, f x = 1 → x = 1) (g : α → M) :
f (∏ᶠ i, g i) = ∏ᶠ i, f (g i) := by
by_cases hg : (mulSupport <| g ∘ PLift.down).Finite; · exact f.map_finprod_plift g hg
rw [finprod, dif_neg, f.map_one, finprod, dif_neg]
exacts [Infinite.mono (fun x hx => mt (hf (g x.down)) hx) hg, hg]
#align monoid_hom.map_finprod_of_preimage_one MonoidHom.map_finprod_of_preimage_one
#align add_monoid_hom.map_finsum_of_preimage_zero AddMonoidHom.map_finsum_of_preimage_zero
@[to_additive]
theorem MonoidHom.map_finprod_of_injective (g : M →* N) (hg : Injective g) (f : α → M) :
g (∏ᶠ i, f i) = ∏ᶠ i, g (f i) :=
g.map_finprod_of_preimage_one (fun _ => (hg.eq_iff' g.map_one).mp) f
#align monoid_hom.map_finprod_of_injective MonoidHom.map_finprod_of_injective
#align add_monoid_hom.map_finsum_of_injective AddMonoidHom.map_finsum_of_injective
@[to_additive]
theorem MulEquiv.map_finprod (g : M ≃* N) (f : α → M) : g (∏ᶠ i, f i) = ∏ᶠ i, g (f i) :=
g.toMonoidHom.map_finprod_of_injective (EquivLike.injective g) f
#align mul_equiv.map_finprod MulEquiv.map_finprod
#align add_equiv.map_finsum AddEquiv.map_finsum
/-- The `NoZeroSMulDivisors` makes sure that the result holds even when the support of `f` is
infinite. For a more usual version assuming `(support f).Finite` instead, see `finsum_smul'`. -/
theorem finsum_smul {R M : Type*} [Ring R] [AddCommGroup M] [Module R M] [NoZeroSMulDivisors R M]
(f : ι → R) (x : M) : (∑ᶠ i, f i) • x = ∑ᶠ i, f i • x := by
rcases eq_or_ne x 0 with (rfl | hx)
· simp
· exact ((smulAddHom R M).flip x).map_finsum_of_injective (smul_left_injective R hx) _
#align finsum_smul finsum_smul
/-- The `NoZeroSMulDivisors` makes sure that the result holds even when the support of `f` is
infinite. For a more usual version assuming `(support f).Finite` instead, see `smul_finsum'`. -/
theorem smul_finsum {R M : Type*} [Ring R] [AddCommGroup M] [Module R M] [NoZeroSMulDivisors R M]
(c : R) (f : ι → M) : (c • ∑ᶠ i, f i) = ∑ᶠ i, c • f i := by
rcases eq_or_ne c 0 with (rfl | hc)
· simp
· exact (smulAddHom R M c).map_finsum_of_injective (smul_right_injective M hc) _
#align smul_finsum smul_finsum
@[to_additive]
theorem finprod_inv_distrib [DivisionCommMonoid G] (f : α → G) : (∏ᶠ x, (f x)⁻¹) = (∏ᶠ x, f x)⁻¹ :=
((MulEquiv.inv G).map_finprod f).symm
#align finprod_inv_distrib finprod_inv_distrib
#align finsum_neg_distrib finsum_neg_distrib
end sort
-- Porting note: Used to be section Type
section type
variable {α β ι G M N : Type*} [CommMonoid M] [CommMonoid N]
@[to_additive]
theorem finprod_eq_mulIndicator_apply (s : Set α) (f : α → M) (a : α) :
∏ᶠ _ : a ∈ s, f a = mulIndicator s f a := by
classical convert finprod_eq_if (M := M) (p := a ∈ s) (x := f a)
#align finprod_eq_mul_indicator_apply finprod_eq_mulIndicator_apply
#align finsum_eq_indicator_apply finsum_eq_indicator_apply
@[to_additive (attr := simp)]
theorem finprod_mem_mulSupport (f : α → M) (a : α) : ∏ᶠ _ : f a ≠ 1, f a = f a := by
rw [← mem_mulSupport, finprod_eq_mulIndicator_apply, mulIndicator_mulSupport]
#align finprod_mem_mul_support finprod_mem_mulSupport
#align finsum_mem_support finsum_mem_support
@[to_additive]
theorem finprod_mem_def (s : Set α) (f : α → M) : ∏ᶠ a ∈ s, f a = ∏ᶠ a, mulIndicator s f a :=
finprod_congr <| finprod_eq_mulIndicator_apply s f
#align finprod_mem_def finprod_mem_def
#align finsum_mem_def finsum_mem_def
@[to_additive]
theorem finprod_eq_prod_of_mulSupport_subset (f : α → M) {s : Finset α} (h : mulSupport f ⊆ s) :
∏ᶠ i, f i = ∏ i ∈ s, f i := by
have A : mulSupport (f ∘ PLift.down) = Equiv.plift.symm '' mulSupport f := by
rw [mulSupport_comp_eq_preimage]
exact (Equiv.plift.symm.image_eq_preimage _).symm
have : mulSupport (f ∘ PLift.down) ⊆ s.map Equiv.plift.symm.toEmbedding := by
rw [A, Finset.coe_map]
exact image_subset _ h
rw [finprod_eq_prod_plift_of_mulSupport_subset this]
simp only [Finset.prod_map, Equiv.coe_toEmbedding]
congr
#align finprod_eq_prod_of_mul_support_subset finprod_eq_prod_of_mulSupport_subset
#align finsum_eq_sum_of_support_subset finsum_eq_sum_of_support_subset
@[to_additive]
theorem finprod_eq_prod_of_mulSupport_toFinset_subset (f : α → M) (hf : (mulSupport f).Finite)
{s : Finset α} (h : hf.toFinset ⊆ s) : ∏ᶠ i, f i = ∏ i ∈ s, f i :=
finprod_eq_prod_of_mulSupport_subset _ fun _ hx => h <| hf.mem_toFinset.2 hx
#align finprod_eq_prod_of_mul_support_to_finset_subset finprod_eq_prod_of_mulSupport_toFinset_subset
#align finsum_eq_sum_of_support_to_finset_subset finsum_eq_sum_of_support_toFinset_subset
@[to_additive]
theorem finprod_eq_finset_prod_of_mulSupport_subset (f : α → M) {s : Finset α}
(h : mulSupport f ⊆ (s : Set α)) : ∏ᶠ i, f i = ∏ i ∈ s, f i :=
haveI h' : (s.finite_toSet.subset h).toFinset ⊆ s := by
simpa [← Finset.coe_subset, Set.coe_toFinset]
finprod_eq_prod_of_mulSupport_toFinset_subset _ _ h'
#align finprod_eq_finset_prod_of_mul_support_subset finprod_eq_finset_prod_of_mulSupport_subset
#align finsum_eq_finset_sum_of_support_subset finsum_eq_finset_sum_of_support_subset
@[to_additive]
theorem finprod_def (f : α → M) [Decidable (mulSupport f).Finite] :
∏ᶠ i : α, f i = if h : (mulSupport f).Finite then ∏ i ∈ h.toFinset, f i else 1 := by
split_ifs with h
· exact finprod_eq_prod_of_mulSupport_toFinset_subset _ h (Finset.Subset.refl _)
· rw [finprod, dif_neg]
rw [mulSupport_comp_eq_preimage]
exact mt (fun hf => hf.of_preimage Equiv.plift.surjective) h
#align finprod_def finprod_def
#align finsum_def finsum_def
@[to_additive]
theorem finprod_of_infinite_mulSupport {f : α → M} (hf : (mulSupport f).Infinite) :
∏ᶠ i, f i = 1 := by classical rw [finprod_def, dif_neg hf]
#align finprod_of_infinite_mul_support finprod_of_infinite_mulSupport
#align finsum_of_infinite_support finsum_of_infinite_support
@[to_additive]
theorem finprod_eq_prod (f : α → M) (hf : (mulSupport f).Finite) :
∏ᶠ i : α, f i = ∏ i ∈ hf.toFinset, f i := by classical rw [finprod_def, dif_pos hf]
#align finprod_eq_prod finprod_eq_prod
#align finsum_eq_sum finsum_eq_sum
@[to_additive]
theorem finprod_eq_prod_of_fintype [Fintype α] (f : α → M) : ∏ᶠ i : α, f i = ∏ i, f i :=
finprod_eq_prod_of_mulSupport_toFinset_subset _ (Set.toFinite _) <| Finset.subset_univ _
#align finprod_eq_prod_of_fintype finprod_eq_prod_of_fintype
#align finsum_eq_sum_of_fintype finsum_eq_sum_of_fintype
@[to_additive]
theorem finprod_cond_eq_prod_of_cond_iff (f : α → M) {p : α → Prop} {t : Finset α}
(h : ∀ {x}, f x ≠ 1 → (p x ↔ x ∈ t)) : (∏ᶠ (i) (_ : p i), f i) = ∏ i ∈ t, f i := by
set s := { x | p x }
have : mulSupport (s.mulIndicator f) ⊆ t := by
rw [Set.mulSupport_mulIndicator]
intro x hx
exact (h hx.2).1 hx.1
erw [finprod_mem_def, finprod_eq_prod_of_mulSupport_subset _ this]
refine Finset.prod_congr rfl fun x hx => mulIndicator_apply_eq_self.2 fun hxs => ?_
contrapose! hxs
exact (h hxs).2 hx
#align finprod_cond_eq_prod_of_cond_iff finprod_cond_eq_prod_of_cond_iff
#align finsum_cond_eq_sum_of_cond_iff finsum_cond_eq_sum_of_cond_iff
@[to_additive]
theorem finprod_cond_ne (f : α → M) (a : α) [DecidableEq α] (hf : (mulSupport f).Finite) :
(∏ᶠ (i) (_ : i ≠ a), f i) = ∏ i ∈ hf.toFinset.erase a, f i := by
apply finprod_cond_eq_prod_of_cond_iff
intro x hx
rw [Finset.mem_erase, Finite.mem_toFinset, mem_mulSupport]
exact ⟨fun h => And.intro h hx, fun h => h.1⟩
#align finprod_cond_ne finprod_cond_ne
#align finsum_cond_ne finsum_cond_ne
@[to_additive]
theorem finprod_mem_eq_prod_of_inter_mulSupport_eq (f : α → M) {s : Set α} {t : Finset α}
(h : s ∩ mulSupport f = t.toSet ∩ mulSupport f) : ∏ᶠ i ∈ s, f i = ∏ i ∈ t, f i :=
finprod_cond_eq_prod_of_cond_iff _ <| by
intro x hxf
rw [← mem_mulSupport] at hxf
refine ⟨fun hx => ?_, fun hx => ?_⟩
· refine ((mem_inter_iff x t (mulSupport f)).mp ?_).1
rw [← Set.ext_iff.mp h x, mem_inter_iff]
exact ⟨hx, hxf⟩
· refine ((mem_inter_iff x s (mulSupport f)).mp ?_).1
rw [Set.ext_iff.mp h x, mem_inter_iff]
exact ⟨hx, hxf⟩
#align finprod_mem_eq_prod_of_inter_mul_support_eq finprod_mem_eq_prod_of_inter_mulSupport_eq
#align finsum_mem_eq_sum_of_inter_support_eq finsum_mem_eq_sum_of_inter_support_eq
@[to_additive]
theorem finprod_mem_eq_prod_of_subset (f : α → M) {s : Set α} {t : Finset α}
(h₁ : s ∩ mulSupport f ⊆ t) (h₂ : ↑t ⊆ s) : ∏ᶠ i ∈ s, f i = ∏ i ∈ t, f i :=
finprod_cond_eq_prod_of_cond_iff _ fun hx => ⟨fun h => h₁ ⟨h, hx⟩, fun h => h₂ h⟩
#align finprod_mem_eq_prod_of_subset finprod_mem_eq_prod_of_subset
#align finsum_mem_eq_sum_of_subset finsum_mem_eq_sum_of_subset
@[to_additive]
theorem finprod_mem_eq_prod (f : α → M) {s : Set α} (hf : (s ∩ mulSupport f).Finite) :
∏ᶠ i ∈ s, f i = ∏ i ∈ hf.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by simp [inter_assoc]
#align finprod_mem_eq_prod finprod_mem_eq_prod
#align finsum_mem_eq_sum finsum_mem_eq_sum
@[to_additive]
theorem finprod_mem_eq_prod_filter (f : α → M) (s : Set α) [DecidablePred (· ∈ s)]
(hf : (mulSupport f).Finite) :
∏ᶠ i ∈ s, f i = ∏ i ∈ Finset.filter (· ∈ s) hf.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by
ext x
simp [and_comm]
#align finprod_mem_eq_prod_filter finprod_mem_eq_prod_filter
#align finsum_mem_eq_sum_filter finsum_mem_eq_sum_filter
@[to_additive]
theorem finprod_mem_eq_toFinset_prod (f : α → M) (s : Set α) [Fintype s] :
∏ᶠ i ∈ s, f i = ∏ i ∈ s.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by simp_rw [coe_toFinset s]
#align finprod_mem_eq_to_finset_prod finprod_mem_eq_toFinset_prod
#align finsum_mem_eq_to_finset_sum finsum_mem_eq_toFinset_sum
@[to_additive]
theorem finprod_mem_eq_finite_toFinset_prod (f : α → M) {s : Set α} (hs : s.Finite) :
∏ᶠ i ∈ s, f i = ∏ i ∈ hs.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by rw [hs.coe_toFinset]
#align finprod_mem_eq_finite_to_finset_prod finprod_mem_eq_finite_toFinset_prod
#align finsum_mem_eq_finite_to_finset_sum finsum_mem_eq_finite_toFinset_sum
@[to_additive]
theorem finprod_mem_finset_eq_prod (f : α → M) (s : Finset α) : ∏ᶠ i ∈ s, f i = ∏ i ∈ s, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ rfl
#align finprod_mem_finset_eq_prod finprod_mem_finset_eq_prod
#align finsum_mem_finset_eq_sum finsum_mem_finset_eq_sum
@[to_additive]
theorem finprod_mem_coe_finset (f : α → M) (s : Finset α) :
(∏ᶠ i ∈ (s : Set α), f i) = ∏ i ∈ s, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ rfl
#align finprod_mem_coe_finset finprod_mem_coe_finset
#align finsum_mem_coe_finset finsum_mem_coe_finset
@[to_additive]
theorem finprod_mem_eq_one_of_infinite {f : α → M} {s : Set α} (hs : (s ∩ mulSupport f).Infinite) :
∏ᶠ i ∈ s, f i = 1 := by
rw [finprod_mem_def]
apply finprod_of_infinite_mulSupport
rwa [← mulSupport_mulIndicator] at hs
#align finprod_mem_eq_one_of_infinite finprod_mem_eq_one_of_infinite
#align finsum_mem_eq_zero_of_infinite finsum_mem_eq_zero_of_infinite
@[to_additive]
theorem finprod_mem_eq_one_of_forall_eq_one {f : α → M} {s : Set α} (h : ∀ x ∈ s, f x = 1) :
∏ᶠ i ∈ s, f i = 1 := by simp (config := { contextual := true }) [h]
#align finprod_mem_eq_one_of_forall_eq_one finprod_mem_eq_one_of_forall_eq_one
#align finsum_mem_eq_zero_of_forall_eq_zero finsum_mem_eq_zero_of_forall_eq_zero
@[to_additive]
theorem finprod_mem_inter_mulSupport (f : α → M) (s : Set α) :
∏ᶠ i ∈ s ∩ mulSupport f, f i = ∏ᶠ i ∈ s, f i := by
rw [finprod_mem_def, finprod_mem_def, mulIndicator_inter_mulSupport]
#align finprod_mem_inter_mul_support finprod_mem_inter_mulSupport
#align finsum_mem_inter_support finsum_mem_inter_support
@[to_additive]
theorem finprod_mem_inter_mulSupport_eq (f : α → M) (s t : Set α)
(h : s ∩ mulSupport f = t ∩ mulSupport f) : ∏ᶠ i ∈ s, f i = ∏ᶠ i ∈ t, f i := by
rw [← finprod_mem_inter_mulSupport, h, finprod_mem_inter_mulSupport]
#align finprod_mem_inter_mul_support_eq finprod_mem_inter_mulSupport_eq
#align finsum_mem_inter_support_eq finsum_mem_inter_support_eq
@[to_additive]
theorem finprod_mem_inter_mulSupport_eq' (f : α → M) (s t : Set α)
(h : ∀ x ∈ mulSupport f, x ∈ s ↔ x ∈ t) : ∏ᶠ i ∈ s, f i = ∏ᶠ i ∈ t, f i := by
apply finprod_mem_inter_mulSupport_eq
ext x
exact and_congr_left (h x)
#align finprod_mem_inter_mul_support_eq' finprod_mem_inter_mulSupport_eq'
#align finsum_mem_inter_support_eq' finsum_mem_inter_support_eq'
@[to_additive]
theorem finprod_mem_univ (f : α → M) : ∏ᶠ i ∈ @Set.univ α, f i = ∏ᶠ i : α, f i :=
finprod_congr fun _ => finprod_true _
#align finprod_mem_univ finprod_mem_univ
#align finsum_mem_univ finsum_mem_univ
variable {f g : α → M} {a b : α} {s t : Set α}
@[to_additive]
theorem finprod_mem_congr (h₀ : s = t) (h₁ : ∀ x ∈ t, f x = g x) :
∏ᶠ i ∈ s, f i = ∏ᶠ i ∈ t, g i :=
h₀.symm ▸ finprod_congr fun i => finprod_congr_Prop rfl (h₁ i)
#align finprod_mem_congr finprod_mem_congr
#align finsum_mem_congr finsum_mem_congr
@[to_additive]
theorem finprod_eq_one_of_forall_eq_one {f : α → M} (h : ∀ x, f x = 1) : ∏ᶠ i, f i = 1 := by
simp (config := { contextual := true }) [h]
#align finprod_eq_one_of_forall_eq_one finprod_eq_one_of_forall_eq_one
#align finsum_eq_zero_of_forall_eq_zero finsum_eq_zero_of_forall_eq_zero
@[to_additive finsum_pos']
| Mathlib/Algebra/BigOperators/Finprod.lean | 591 | 596 | theorem one_lt_finprod' {M : Type*} [OrderedCancelCommMonoid M] {f : ι → M}
(h : ∀ i, 1 ≤ f i) (h' : ∃ i, 1 < f i) (hf : (mulSupport f).Finite) : 1 < ∏ᶠ i, f i := by |
rcases h' with ⟨i, hi⟩
rw [finprod_eq_prod _ hf]
refine Finset.one_lt_prod' (fun i _ ↦ h i) ⟨i, ?_, hi⟩
simpa only [Finite.mem_toFinset, mem_mulSupport] using ne_of_gt hi
|
/-
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.RatFunc.AsPolynomial
import Mathlib.RingTheory.EuclideanDomain
import Mathlib.RingTheory.Localization.FractionRing
import Mathlib.RingTheory.Polynomial.Content
/-!
# The degree of rational functions
## Main definitions
We define the degree of a rational function, with values in `ℤ`:
- `intDegree` is the degree of a rational function, defined as the difference between the
`natDegree` of its numerator and the `natDegree` of its denominator. In particular,
`intDegree 0 = 0`.
-/
noncomputable section
universe u
variable {K : Type u}
namespace RatFunc
section IntDegree
open Polynomial
variable [Field K]
/-- `intDegree x` is the degree of the rational function `x`, defined as the difference between
the `natDegree` of its numerator and the `natDegree` of its denominator. In particular,
`intDegree 0 = 0`. -/
def intDegree (x : RatFunc K) : ℤ :=
natDegree x.num - natDegree x.denom
#align ratfunc.int_degree RatFunc.intDegree
@[simp]
theorem intDegree_zero : intDegree (0 : RatFunc K) = 0 := by
rw [intDegree, num_zero, natDegree_zero, denom_zero, natDegree_one, sub_self]
#align ratfunc.int_degree_zero RatFunc.intDegree_zero
@[simp]
theorem intDegree_one : intDegree (1 : RatFunc K) = 0 := by
rw [intDegree, num_one, denom_one, sub_self]
#align ratfunc.int_degree_one RatFunc.intDegree_one
@[simp]
theorem intDegree_C (k : K) : intDegree (C k) = 0 := by
rw [intDegree, num_C, natDegree_C, denom_C, natDegree_one, sub_self]
set_option linter.uppercaseLean3 false in #align ratfunc.int_degree_C RatFunc.intDegree_C
@[simp]
theorem intDegree_X : intDegree (X : RatFunc K) = 1 := by
rw [intDegree, num_X, Polynomial.natDegree_X, denom_X, Polynomial.natDegree_one,
Int.ofNat_one, Int.ofNat_zero, sub_zero]
set_option linter.uppercaseLean3 false in #align ratfunc.int_degree_X RatFunc.intDegree_X
@[simp]
theorem intDegree_polynomial {p : K[X]} :
intDegree (algebraMap K[X] (RatFunc K) p) = natDegree p := by
rw [intDegree, RatFunc.num_algebraMap, RatFunc.denom_algebraMap, Polynomial.natDegree_one,
Int.ofNat_zero, sub_zero]
#align ratfunc.int_degree_polynomial RatFunc.intDegree_polynomial
theorem intDegree_mul {x y : RatFunc K} (hx : x ≠ 0) (hy : y ≠ 0) :
intDegree (x * y) = intDegree x + intDegree y := by
simp only [intDegree, add_sub, sub_add, sub_sub_eq_add_sub, sub_sub, sub_eq_sub_iff_add_eq_add]
norm_cast
rw [← Polynomial.natDegree_mul x.denom_ne_zero y.denom_ne_zero, ←
Polynomial.natDegree_mul (RatFunc.num_ne_zero (mul_ne_zero hx hy))
(mul_ne_zero x.denom_ne_zero y.denom_ne_zero),
← Polynomial.natDegree_mul (RatFunc.num_ne_zero hx) (RatFunc.num_ne_zero hy), ←
Polynomial.natDegree_mul (mul_ne_zero (RatFunc.num_ne_zero hx) (RatFunc.num_ne_zero hy))
(x * y).denom_ne_zero,
RatFunc.num_denom_mul]
#align ratfunc.int_degree_mul RatFunc.intDegree_mul
@[simp]
theorem intDegree_neg (x : RatFunc K) : intDegree (-x) = intDegree x := by
by_cases hx : x = 0
· rw [hx, neg_zero]
· rw [intDegree, intDegree, ← natDegree_neg x.num]
exact
natDegree_sub_eq_of_prod_eq (num_ne_zero (neg_ne_zero.mpr hx)) (denom_ne_zero (-x))
(neg_ne_zero.mpr (num_ne_zero hx)) (denom_ne_zero x) (num_denom_neg x)
#align ratfunc.int_degree_neg RatFunc.intDegree_neg
theorem intDegree_add {x y : RatFunc K} (hxy : x + y ≠ 0) :
(x + y).intDegree =
(x.num * y.denom + x.denom * y.num).natDegree - (x.denom * y.denom).natDegree :=
natDegree_sub_eq_of_prod_eq (num_ne_zero hxy) (x + y).denom_ne_zero
(num_mul_denom_add_denom_mul_num_ne_zero hxy) (mul_ne_zero x.denom_ne_zero y.denom_ne_zero)
(num_denom_add x y)
#align ratfunc.int_degree_add RatFunc.intDegree_add
| Mathlib/FieldTheory/RatFunc/Degree.lean | 102 | 107 | theorem natDegree_num_mul_right_sub_natDegree_denom_mul_left_eq_intDegree {x : RatFunc K}
(hx : x ≠ 0) {s : K[X]} (hs : s ≠ 0) :
((x.num * s).natDegree : ℤ) - (s * x.denom).natDegree = x.intDegree := by |
apply natDegree_sub_eq_of_prod_eq (mul_ne_zero (num_ne_zero hx) hs)
(mul_ne_zero hs x.denom_ne_zero) (num_ne_zero hx) x.denom_ne_zero
rw [mul_assoc]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang, Antoine Chambert-Loir
-/
import Mathlib.Algebra.Algebra.Subalgebra.Basic
import Mathlib.RingTheory.Ideal.Maps
#align_import algebra.algebra.subalgebra.basic from "leanprover-community/mathlib"@"b915e9392ecb2a861e1e766f0e1df6ac481188ca"
/-!
# More operations on subalgebras
In this file we relate the definitions in `Mathlib.RingTheory.Ideal.Operations` to subalgebras.
The contents of this file are somewhat random since both `Mathlib.Algebra.Algebra.Subalgebra.Basic`
and `Mathlib.RingTheory.Ideal.Operations` are somewhat of a grab-bag of definitions, and this is
whatever ends up in the intersection.
-/
namespace AlgHom
variable {R A B : Type*} [CommSemiring R] [Semiring A] [Algebra R A] [Semiring B] [Algebra R B]
theorem ker_rangeRestrict (f : A →ₐ[R] B) : RingHom.ker f.rangeRestrict = RingHom.ker f :=
Ideal.ext fun _ ↦ Subtype.ext_iff
end AlgHom
namespace Subalgebra
open Algebra
variable {R S : Type*} [CommSemiring R] [CommRing S] [Algebra R S]
variable (S' : Subalgebra R S)
/-- Suppose we are given `∑ i, lᵢ * sᵢ = 1` ∈ `S`, and `S'` a subalgebra of `S` that contains
`lᵢ` and `sᵢ`. To check that an `x : S` falls in `S'`, we only need to show that
`sᵢ ^ n • x ∈ S'` for some `n` for each `sᵢ`. -/
| Mathlib/Algebra/Algebra/Subalgebra/Operations.lean | 40 | 68 | theorem mem_of_finset_sum_eq_one_of_pow_smul_mem
{ι : Type*} (ι' : Finset ι) (s : ι → S) (l : ι → S)
(e : ∑ i ∈ ι', l i * s i = 1) (hs : ∀ i, s i ∈ S') (hl : ∀ i, l i ∈ S') (x : S)
(H : ∀ i, ∃ n : ℕ, (s i ^ n : S) • x ∈ S') : x ∈ S' := by |
-- Porting note: needed to add this instance
let _i : Algebra { x // x ∈ S' } { x // x ∈ S' } := Algebra.id _
suffices x ∈ Subalgebra.toSubmodule (Algebra.ofId S' S).range by
obtain ⟨x, rfl⟩ := this
exact x.2
choose n hn using H
let s' : ι → S' := fun x => ⟨s x, hs x⟩
let l' : ι → S' := fun x => ⟨l x, hl x⟩
have e' : ∑ i ∈ ι', l' i * s' i = 1 := by
ext
show S'.subtype (∑ i ∈ ι', l' i * s' i) = 1
simpa only [map_sum, map_mul] using e
have : Ideal.span (s' '' ι') = ⊤ := by
rw [Ideal.eq_top_iff_one, ← e']
apply sum_mem
intros i hi
exact Ideal.mul_mem_left _ _ <| Ideal.subset_span <| Set.mem_image_of_mem s' hi
let N := ι'.sup n
have hN := Ideal.span_pow_eq_top _ this N
apply (Algebra.ofId S' S).range.toSubmodule.mem_of_span_top_of_smul_mem _ hN
rintro ⟨_, _, ⟨i, hi, rfl⟩, rfl⟩
change s' i ^ N • x ∈ _
rw [← tsub_add_cancel_of_le (show n i ≤ N from Finset.le_sup hi), pow_add, mul_smul]
refine Submodule.smul_mem _ (⟨_, pow_mem (hs i) _⟩ : S') ?_
exact ⟨⟨_, hn i⟩, rfl⟩
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.ContDiff.Defs
#align_import analysis.calculus.iterated_deriv from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# One-dimensional iterated derivatives
We define the `n`-th derivative of a function `f : 𝕜 → F` as a function
`iteratedDeriv n f : 𝕜 → F`, as well as a version on domains `iteratedDerivWithin n f s : 𝕜 → F`,
and prove their basic properties.
## Main definitions and results
Let `𝕜` be a nontrivially normed field, and `F` a normed vector space over `𝕜`. Let `f : 𝕜 → F`.
* `iteratedDeriv n f` is the `n`-th derivative of `f`, seen as a function from `𝕜` to `F`.
It is defined as the `n`-th Fréchet derivative (which is a multilinear map) applied to the
vector `(1, ..., 1)`, to take advantage of all the existing framework, but we show that it
coincides with the naive iterative definition.
* `iteratedDeriv_eq_iterate` states that the `n`-th derivative of `f` is obtained by starting
from `f` and differentiating it `n` times.
* `iteratedDerivWithin n f s` is the `n`-th derivative of `f` within the domain `s`. It only
behaves well when `s` has the unique derivative property.
* `iteratedDerivWithin_eq_iterate` states that the `n`-th derivative of `f` in the domain `s` is
obtained by starting from `f` and differentiating it `n` times within `s`. This only holds when
`s` has the unique derivative property.
## Implementation details
The results are deduced from the corresponding results for the more general (multilinear) iterated
Fréchet derivative. For this, we write `iteratedDeriv n f` as the composition of
`iteratedFDeriv 𝕜 n f` and a continuous linear equiv. As continuous linear equivs respect
differentiability and commute with differentiation, this makes it possible to prove readily that
the derivative of the `n`-th derivative is the `n+1`-th derivative in `iteratedDerivWithin_succ`,
by translating the corresponding result `iteratedFDerivWithin_succ_apply_left` for the
iterated Fréchet derivative.
-/
noncomputable section
open scoped Classical Topology
open Filter Asymptotics Set
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
/-- The `n`-th iterated derivative of a function from `𝕜` to `F`, as a function from `𝕜` to `F`. -/
def iteratedDeriv (n : ℕ) (f : 𝕜 → F) (x : 𝕜) : F :=
(iteratedFDeriv 𝕜 n f x : (Fin n → 𝕜) → F) fun _ : Fin n => 1
#align iterated_deriv iteratedDeriv
/-- The `n`-th iterated derivative of a function from `𝕜` to `F` within a set `s`, as a function
from `𝕜` to `F`. -/
def iteratedDerivWithin (n : ℕ) (f : 𝕜 → F) (s : Set 𝕜) (x : 𝕜) : F :=
(iteratedFDerivWithin 𝕜 n f s x : (Fin n → 𝕜) → F) fun _ : Fin n => 1
#align iterated_deriv_within iteratedDerivWithin
variable {n : ℕ} {f : 𝕜 → F} {s : Set 𝕜} {x : 𝕜}
theorem iteratedDerivWithin_univ : iteratedDerivWithin n f univ = iteratedDeriv n f := by
ext x
rw [iteratedDerivWithin, iteratedDeriv, iteratedFDerivWithin_univ]
#align iterated_deriv_within_univ iteratedDerivWithin_univ
/-! ### Properties of the iterated derivative within a set -/
theorem iteratedDerivWithin_eq_iteratedFDerivWithin : iteratedDerivWithin n f s x =
(iteratedFDerivWithin 𝕜 n f s x : (Fin n → 𝕜) → F) fun _ : Fin n => 1 :=
rfl
#align iterated_deriv_within_eq_iterated_fderiv_within iteratedDerivWithin_eq_iteratedFDerivWithin
/-- Write the iterated derivative as the composition of a continuous linear equiv and the iterated
Fréchet derivative -/
theorem iteratedDerivWithin_eq_equiv_comp : iteratedDerivWithin n f s =
(ContinuousMultilinearMap.piFieldEquiv 𝕜 (Fin n) F).symm ∘ iteratedFDerivWithin 𝕜 n f s := by
ext x; rfl
#align iterated_deriv_within_eq_equiv_comp iteratedDerivWithin_eq_equiv_comp
/-- Write the iterated Fréchet derivative as the composition of a continuous linear equiv and the
iterated derivative. -/
theorem iteratedFDerivWithin_eq_equiv_comp :
iteratedFDerivWithin 𝕜 n f s =
ContinuousMultilinearMap.piFieldEquiv 𝕜 (Fin n) F ∘ iteratedDerivWithin n f s := by
rw [iteratedDerivWithin_eq_equiv_comp, ← Function.comp.assoc, LinearIsometryEquiv.self_comp_symm,
Function.id_comp]
#align iterated_fderiv_within_eq_equiv_comp iteratedFDerivWithin_eq_equiv_comp
/-- The `n`-th Fréchet derivative applied to a vector `(m 0, ..., m (n-1))` is the derivative
multiplied by the product of the `m i`s. -/
theorem iteratedFDerivWithin_apply_eq_iteratedDerivWithin_mul_prod {m : Fin n → 𝕜} :
(iteratedFDerivWithin 𝕜 n f s x : (Fin n → 𝕜) → F) m =
(∏ i, m i) • iteratedDerivWithin n f s x := by
rw [iteratedDerivWithin_eq_iteratedFDerivWithin, ← ContinuousMultilinearMap.map_smul_univ]
simp
#align iterated_fderiv_within_apply_eq_iterated_deriv_within_mul_prod iteratedFDerivWithin_apply_eq_iteratedDerivWithin_mul_prod
theorem norm_iteratedFDerivWithin_eq_norm_iteratedDerivWithin :
‖iteratedFDerivWithin 𝕜 n f s x‖ = ‖iteratedDerivWithin n f s x‖ := by
rw [iteratedDerivWithin_eq_equiv_comp, Function.comp_apply, LinearIsometryEquiv.norm_map]
#align norm_iterated_fderiv_within_eq_norm_iterated_deriv_within norm_iteratedFDerivWithin_eq_norm_iteratedDerivWithin
@[simp]
theorem iteratedDerivWithin_zero : iteratedDerivWithin 0 f s = f := by
ext x
simp [iteratedDerivWithin]
#align iterated_deriv_within_zero iteratedDerivWithin_zero
@[simp]
theorem iteratedDerivWithin_one {x : 𝕜} (h : UniqueDiffWithinAt 𝕜 s x) :
iteratedDerivWithin 1 f s x = derivWithin f s x := by
simp only [iteratedDerivWithin, iteratedFDerivWithin_one_apply h]; rfl
#align iterated_deriv_within_one iteratedDerivWithin_one
/-- If the first `n` derivatives within a set of a function are continuous, and its first `n-1`
derivatives are differentiable, then the function is `C^n`. This is not an equivalence in general,
but this is an equivalence when the set has unique derivatives, see
`contDiffOn_iff_continuousOn_differentiableOn_deriv`. -/
theorem contDiffOn_of_continuousOn_differentiableOn_deriv {n : ℕ∞}
(Hcont : ∀ m : ℕ, (m : ℕ∞) ≤ n → ContinuousOn (fun x => iteratedDerivWithin m f s x) s)
(Hdiff : ∀ m : ℕ, (m : ℕ∞) < n → DifferentiableOn 𝕜 (fun x => iteratedDerivWithin m f s x) s) :
ContDiffOn 𝕜 n f s := by
apply contDiffOn_of_continuousOn_differentiableOn
· simpa only [iteratedFDerivWithin_eq_equiv_comp, LinearIsometryEquiv.comp_continuousOn_iff]
· simpa only [iteratedFDerivWithin_eq_equiv_comp, LinearIsometryEquiv.comp_differentiableOn_iff]
#align cont_diff_on_of_continuous_on_differentiable_on_deriv contDiffOn_of_continuousOn_differentiableOn_deriv
/-- To check that a function is `n` times continuously differentiable, it suffices to check that its
first `n` derivatives are differentiable. This is slightly too strong as the condition we
require on the `n`-th derivative is differentiability instead of continuity, but it has the
advantage of avoiding the discussion of continuity in the proof (and for `n = ∞` this is optimal).
-/
theorem contDiffOn_of_differentiableOn_deriv {n : ℕ∞}
(h : ∀ m : ℕ, (m : ℕ∞) ≤ n → DifferentiableOn 𝕜 (iteratedDerivWithin m f s) s) :
ContDiffOn 𝕜 n f s := by
apply contDiffOn_of_differentiableOn
simpa only [iteratedFDerivWithin_eq_equiv_comp, LinearIsometryEquiv.comp_differentiableOn_iff]
#align cont_diff_on_of_differentiable_on_deriv contDiffOn_of_differentiableOn_deriv
/-- On a set with unique derivatives, a `C^n` function has derivatives up to `n` which are
continuous. -/
theorem ContDiffOn.continuousOn_iteratedDerivWithin {n : ℕ∞} {m : ℕ} (h : ContDiffOn 𝕜 n f s)
(hmn : (m : ℕ∞) ≤ n) (hs : UniqueDiffOn 𝕜 s) : ContinuousOn (iteratedDerivWithin m f s) s := by
simpa only [iteratedDerivWithin_eq_equiv_comp, LinearIsometryEquiv.comp_continuousOn_iff] using
h.continuousOn_iteratedFDerivWithin hmn hs
#align cont_diff_on.continuous_on_iterated_deriv_within ContDiffOn.continuousOn_iteratedDerivWithin
| Mathlib/Analysis/Calculus/IteratedDeriv/Defs.lean | 157 | 162 | theorem ContDiffWithinAt.differentiableWithinAt_iteratedDerivWithin {n : ℕ∞} {m : ℕ}
(h : ContDiffWithinAt 𝕜 n f s x) (hmn : (m : ℕ∞) < n) (hs : UniqueDiffOn 𝕜 (insert x s)) :
DifferentiableWithinAt 𝕜 (iteratedDerivWithin m f s) s x := by |
simpa only [iteratedDerivWithin_eq_equiv_comp,
LinearIsometryEquiv.comp_differentiableWithinAt_iff] using
h.differentiableWithinAt_iteratedFDerivWithin hmn hs
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Complex
import Qq
#align_import analysis.special_functions.pow.real from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-! # Power function on `ℝ`
We construct the power functions `x ^ y`, where `x` and `y` are real numbers.
-/
noncomputable section
open scoped Classical
open Real ComplexConjugate
open Finset Set
/-
## Definitions
-/
namespace Real
variable {x y z : ℝ}
/-- The real power function `x ^ y`, defined as the real part of the complex power function.
For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`, one sets `0 ^ 0=1` and `0 ^ y=0` for
`y ≠ 0`. For `x < 0`, the definition is somewhat arbitrary as it depends on the choice of a complex
determination of the logarithm. With our conventions, it is equal to `exp (y log x) cos (π y)`. -/
noncomputable def rpow (x y : ℝ) :=
((x : ℂ) ^ (y : ℂ)).re
#align real.rpow Real.rpow
noncomputable instance : Pow ℝ ℝ := ⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x y : ℝ) : rpow x y = x ^ y := rfl
#align real.rpow_eq_pow Real.rpow_eq_pow
theorem rpow_def (x y : ℝ) : x ^ y = ((x : ℂ) ^ (y : ℂ)).re := rfl
#align real.rpow_def Real.rpow_def
theorem rpow_def_of_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) := by
simp only [rpow_def, Complex.cpow_def]; split_ifs <;>
simp_all [(Complex.ofReal_log hx).symm, -Complex.ofReal_mul, -RCLike.ofReal_mul,
(Complex.ofReal_mul _ _).symm, Complex.exp_ofReal_re, Complex.ofReal_eq_zero]
#align real.rpow_def_of_nonneg Real.rpow_def_of_nonneg
theorem rpow_def_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : x ^ y = exp (log x * y) := by
rw [rpow_def_of_nonneg (le_of_lt hx), if_neg (ne_of_gt hx)]
#align real.rpow_def_of_pos Real.rpow_def_of_pos
theorem exp_mul (x y : ℝ) : exp (x * y) = exp x ^ y := by rw [rpow_def_of_pos (exp_pos _), log_exp]
#align real.exp_mul Real.exp_mul
@[simp, norm_cast]
theorem rpow_intCast (x : ℝ) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by
simp only [rpow_def, ← Complex.ofReal_zpow, Complex.cpow_intCast, Complex.ofReal_intCast,
Complex.ofReal_re]
#align real.rpow_int_cast Real.rpow_intCast
@[deprecated (since := "2024-04-17")]
alias rpow_int_cast := rpow_intCast
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by simpa using rpow_intCast x n
#align real.rpow_nat_cast Real.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
theorem exp_one_rpow (x : ℝ) : exp 1 ^ x = exp x := by rw [← exp_mul, one_mul]
#align real.exp_one_rpow Real.exp_one_rpow
@[simp] lemma exp_one_pow (n : ℕ) : exp 1 ^ n = exp n := by rw [← rpow_natCast, exp_one_rpow]
theorem rpow_eq_zero_iff_of_nonneg (hx : 0 ≤ x) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [rpow_def_of_nonneg hx]
split_ifs <;> simp [*, exp_ne_zero]
#align real.rpow_eq_zero_iff_of_nonneg Real.rpow_eq_zero_iff_of_nonneg
@[simp]
lemma rpow_eq_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y = 0 ↔ x = 0 := by
simp [rpow_eq_zero_iff_of_nonneg, *]
@[simp]
lemma rpow_ne_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y ≠ 0 ↔ x ≠ 0 :=
Real.rpow_eq_zero hx hy |>.not
open Real
theorem rpow_def_of_neg {x : ℝ} (hx : x < 0) (y : ℝ) : x ^ y = exp (log x * y) * cos (y * π) := by
rw [rpow_def, Complex.cpow_def, if_neg]
· have : Complex.log x * y = ↑(log (-x) * y) + ↑(y * π) * Complex.I := by
simp only [Complex.log, abs_of_neg hx, Complex.arg_ofReal_of_neg hx, Complex.abs_ofReal,
Complex.ofReal_mul]
ring
rw [this, Complex.exp_add_mul_I, ← Complex.ofReal_exp, ← Complex.ofReal_cos, ←
Complex.ofReal_sin, mul_add, ← Complex.ofReal_mul, ← mul_assoc, ← Complex.ofReal_mul,
Complex.add_re, Complex.ofReal_re, Complex.mul_re, Complex.I_re, Complex.ofReal_im,
Real.log_neg_eq_log]
ring
· rw [Complex.ofReal_eq_zero]
exact ne_of_lt hx
#align real.rpow_def_of_neg Real.rpow_def_of_neg
theorem rpow_def_of_nonpos {x : ℝ} (hx : x ≤ 0) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) * cos (y * π) := by
split_ifs with h <;> simp [rpow_def, *]; exact rpow_def_of_neg (lt_of_le_of_ne hx h) _
#align real.rpow_def_of_nonpos Real.rpow_def_of_nonpos
theorem rpow_pos_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : 0 < x ^ y := by
rw [rpow_def_of_pos hx]; apply exp_pos
#align real.rpow_pos_of_pos Real.rpow_pos_of_pos
@[simp]
theorem rpow_zero (x : ℝ) : x ^ (0 : ℝ) = 1 := by simp [rpow_def]
#align real.rpow_zero Real.rpow_zero
theorem rpow_zero_pos (x : ℝ) : 0 < x ^ (0 : ℝ) := by simp
@[simp]
theorem zero_rpow {x : ℝ} (h : x ≠ 0) : (0 : ℝ) ^ x = 0 := by simp [rpow_def, *]
#align real.zero_rpow Real.zero_rpow
theorem zero_rpow_eq_iff {x : ℝ} {a : ℝ} : 0 ^ x = a ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
constructor
· intro hyp
simp only [rpow_def, Complex.ofReal_zero] at hyp
by_cases h : x = 0
· subst h
simp only [Complex.one_re, Complex.ofReal_zero, Complex.cpow_zero] at hyp
exact Or.inr ⟨rfl, hyp.symm⟩
· rw [Complex.zero_cpow (Complex.ofReal_ne_zero.mpr h)] at hyp
exact Or.inl ⟨h, hyp.symm⟩
· rintro (⟨h, rfl⟩ | ⟨rfl, rfl⟩)
· exact zero_rpow h
· exact rpow_zero _
#align real.zero_rpow_eq_iff Real.zero_rpow_eq_iff
theorem eq_zero_rpow_iff {x : ℝ} {a : ℝ} : a = 0 ^ x ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
rw [← zero_rpow_eq_iff, eq_comm]
#align real.eq_zero_rpow_iff Real.eq_zero_rpow_iff
@[simp]
theorem rpow_one (x : ℝ) : x ^ (1 : ℝ) = x := by simp [rpow_def]
#align real.rpow_one Real.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ) ^ x = 1 := by simp [rpow_def]
#align real.one_rpow Real.one_rpow
theorem zero_rpow_le_one (x : ℝ) : (0 : ℝ) ^ x ≤ 1 := by
by_cases h : x = 0 <;> simp [h, zero_le_one]
#align real.zero_rpow_le_one Real.zero_rpow_le_one
theorem zero_rpow_nonneg (x : ℝ) : 0 ≤ (0 : ℝ) ^ x := by
by_cases h : x = 0 <;> simp [h, zero_le_one]
#align real.zero_rpow_nonneg Real.zero_rpow_nonneg
theorem rpow_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : 0 ≤ x ^ y := by
rw [rpow_def_of_nonneg hx]; split_ifs <;>
simp only [zero_le_one, le_refl, le_of_lt (exp_pos _)]
#align real.rpow_nonneg_of_nonneg Real.rpow_nonneg
theorem abs_rpow_of_nonneg {x y : ℝ} (hx_nonneg : 0 ≤ x) : |x ^ y| = |x| ^ y := by
have h_rpow_nonneg : 0 ≤ x ^ y := Real.rpow_nonneg hx_nonneg _
rw [abs_eq_self.mpr hx_nonneg, abs_eq_self.mpr h_rpow_nonneg]
#align real.abs_rpow_of_nonneg Real.abs_rpow_of_nonneg
theorem abs_rpow_le_abs_rpow (x y : ℝ) : |x ^ y| ≤ |x| ^ y := by
rcases le_or_lt 0 x with hx | hx
· rw [abs_rpow_of_nonneg hx]
· rw [abs_of_neg hx, rpow_def_of_neg hx, rpow_def_of_pos (neg_pos.2 hx), log_neg_eq_log, abs_mul,
abs_of_pos (exp_pos _)]
exact mul_le_of_le_one_right (exp_pos _).le (abs_cos_le_one _)
#align real.abs_rpow_le_abs_rpow Real.abs_rpow_le_abs_rpow
theorem abs_rpow_le_exp_log_mul (x y : ℝ) : |x ^ y| ≤ exp (log x * y) := by
refine (abs_rpow_le_abs_rpow x y).trans ?_
by_cases hx : x = 0
· by_cases hy : y = 0 <;> simp [hx, hy, zero_le_one]
· rw [rpow_def_of_pos (abs_pos.2 hx), log_abs]
#align real.abs_rpow_le_exp_log_mul Real.abs_rpow_le_exp_log_mul
theorem norm_rpow_of_nonneg {x y : ℝ} (hx_nonneg : 0 ≤ x) : ‖x ^ y‖ = ‖x‖ ^ y := by
simp_rw [Real.norm_eq_abs]
exact abs_rpow_of_nonneg hx_nonneg
#align real.norm_rpow_of_nonneg Real.norm_rpow_of_nonneg
variable {w x y z : ℝ}
theorem rpow_add (hx : 0 < x) (y z : ℝ) : x ^ (y + z) = x ^ y * x ^ z := by
simp only [rpow_def_of_pos hx, mul_add, exp_add]
#align real.rpow_add Real.rpow_add
theorem rpow_add' (hx : 0 ≤ x) (h : y + z ≠ 0) : x ^ (y + z) = x ^ y * x ^ z := by
rcases hx.eq_or_lt with (rfl | pos)
· rw [zero_rpow h, zero_eq_mul]
have : y ≠ 0 ∨ z ≠ 0 := not_and_or.1 fun ⟨hy, hz⟩ => h <| hy.symm ▸ hz.symm ▸ zero_add 0
exact this.imp zero_rpow zero_rpow
· exact rpow_add pos _ _
#align real.rpow_add' Real.rpow_add'
/-- Variant of `Real.rpow_add'` that avoids having to prove `y + z = w` twice. -/
lemma rpow_of_add_eq (hx : 0 ≤ x) (hw : w ≠ 0) (h : y + z = w) : x ^ w = x ^ y * x ^ z := by
rw [← h, rpow_add' hx]; rwa [h]
theorem rpow_add_of_nonneg (hx : 0 ≤ x) (hy : 0 ≤ y) (hz : 0 ≤ z) :
x ^ (y + z) = x ^ y * x ^ z := by
rcases hy.eq_or_lt with (rfl | hy)
· rw [zero_add, rpow_zero, one_mul]
exact rpow_add' hx (ne_of_gt <| add_pos_of_pos_of_nonneg hy hz)
#align real.rpow_add_of_nonneg Real.rpow_add_of_nonneg
/-- For `0 ≤ x`, the only problematic case in the equality `x ^ y * x ^ z = x ^ (y + z)` is for
`x = 0` and `y + z = 0`, where the right hand side is `1` while the left hand side can vanish.
The inequality is always true, though, and given in this lemma. -/
theorem le_rpow_add {x : ℝ} (hx : 0 ≤ x) (y z : ℝ) : x ^ y * x ^ z ≤ x ^ (y + z) := by
rcases le_iff_eq_or_lt.1 hx with (H | pos)
· by_cases h : y + z = 0
· simp only [H.symm, h, rpow_zero]
calc
(0 : ℝ) ^ y * 0 ^ z ≤ 1 * 1 :=
mul_le_mul (zero_rpow_le_one y) (zero_rpow_le_one z) (zero_rpow_nonneg z) zero_le_one
_ = 1 := by simp
· simp [rpow_add', ← H, h]
· simp [rpow_add pos]
#align real.le_rpow_add Real.le_rpow_add
theorem rpow_sum_of_pos {ι : Type*} {a : ℝ} (ha : 0 < a) (f : ι → ℝ) (s : Finset ι) :
(a ^ ∑ x ∈ s, f x) = ∏ x ∈ s, a ^ f x :=
map_sum (⟨⟨fun (x : ℝ) => (a ^ x : ℝ), rpow_zero a⟩, rpow_add ha⟩ : ℝ →+ (Additive ℝ)) f s
#align real.rpow_sum_of_pos Real.rpow_sum_of_pos
theorem rpow_sum_of_nonneg {ι : Type*} {a : ℝ} (ha : 0 ≤ a) {s : Finset ι} {f : ι → ℝ}
(h : ∀ x ∈ s, 0 ≤ f x) : (a ^ ∑ x ∈ s, f x) = ∏ x ∈ s, a ^ f x := by
induction' s using Finset.cons_induction with i s hi ihs
· rw [sum_empty, Finset.prod_empty, rpow_zero]
· rw [forall_mem_cons] at h
rw [sum_cons, prod_cons, ← ihs h.2, rpow_add_of_nonneg ha h.1 (sum_nonneg h.2)]
#align real.rpow_sum_of_nonneg Real.rpow_sum_of_nonneg
theorem rpow_neg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ := by
simp only [rpow_def_of_nonneg hx]; split_ifs <;> simp_all [exp_neg]
#align real.rpow_neg Real.rpow_neg
theorem rpow_sub {x : ℝ} (hx : 0 < x) (y z : ℝ) : x ^ (y - z) = x ^ y / x ^ z := by
simp only [sub_eq_add_neg, rpow_add hx, rpow_neg (le_of_lt hx), div_eq_mul_inv]
#align real.rpow_sub Real.rpow_sub
theorem rpow_sub' {x : ℝ} (hx : 0 ≤ x) {y z : ℝ} (h : y - z ≠ 0) : x ^ (y - z) = x ^ y / x ^ z := by
simp only [sub_eq_add_neg] at h ⊢
simp only [rpow_add' hx h, rpow_neg hx, div_eq_mul_inv]
#align real.rpow_sub' Real.rpow_sub'
end Real
/-!
## Comparing real and complex powers
-/
namespace Complex
| Mathlib/Analysis/SpecialFunctions/Pow/Real.lean | 275 | 277 | theorem ofReal_cpow {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : ((x ^ y : ℝ) : ℂ) = (x : ℂ) ^ (y : ℂ) := by |
simp only [Real.rpow_def_of_nonneg hx, Complex.cpow_def, ofReal_eq_zero]; split_ifs <;>
simp [Complex.ofReal_log hx]
|
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Sébastien Gouëzel
-/
import Mathlib.Analysis.Normed.Group.Hom
import Mathlib.Analysis.SpecialFunctions.Pow.Continuity
import Mathlib.Data.Set.Image
import Mathlib.MeasureTheory.Function.LpSeminorm.ChebyshevMarkov
import Mathlib.MeasureTheory.Function.LpSeminorm.CompareExp
import Mathlib.MeasureTheory.Function.LpSeminorm.TriangleInequality
import Mathlib.MeasureTheory.Measure.OpenPos
import Mathlib.Topology.ContinuousFunction.Compact
import Mathlib.Order.Filter.IndicatorFunction
#align_import measure_theory.function.lp_space from "leanprover-community/mathlib"@"c4015acc0a223449d44061e27ddac1835a3852b9"
/-!
# Lp space
This file provides the space `Lp E p μ` as the subtype of elements of `α →ₘ[μ] E` (see ae_eq_fun)
such that `snorm f p μ` is finite. For `1 ≤ p`, `snorm` defines a norm and `Lp` is a complete metric
space.
## Main definitions
* `Lp E p μ` : elements of `α →ₘ[μ] E` (see ae_eq_fun) such that `snorm f p μ` is finite. Defined
as an `AddSubgroup` of `α →ₘ[μ] E`.
Lipschitz functions vanishing at zero act by composition on `Lp`. We define this action, and prove
that it is continuous. In particular,
* `ContinuousLinearMap.compLp` defines the action on `Lp` of a continuous linear map.
* `Lp.posPart` is the positive part of an `Lp` function.
* `Lp.negPart` is the negative part of an `Lp` function.
When `α` is a topological space equipped with a finite Borel measure, there is a bounded linear map
from the normed space of bounded continuous functions (`α →ᵇ E`) to `Lp E p μ`. We construct this
as `BoundedContinuousFunction.toLp`.
## Notations
* `α →₁[μ] E` : the type `Lp E 1 μ`.
* `α →₂[μ] E` : the type `Lp E 2 μ`.
## Implementation
Since `Lp` is defined as an `AddSubgroup`, dot notation does not work. Use `Lp.Measurable f` to
say that the coercion of `f` to a genuine function is measurable, instead of the non-working
`f.Measurable`.
To prove that two `Lp` elements are equal, it suffices to show that their coercions to functions
coincide almost everywhere (this is registered as an `ext` rule). This can often be done using
`filter_upwards`. For instance, a proof from first principles that `f + (g + h) = (f + g) + h`
could read (in the `Lp` namespace)
```
example (f g h : Lp E p μ) : (f + g) + h = f + (g + h) := by
ext1
filter_upwards [coeFn_add (f + g) h, coeFn_add f g, coeFn_add f (g + h), coeFn_add g h]
with _ ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, add_assoc]
```
The lemma `coeFn_add` states that the coercion of `f + g` coincides almost everywhere with the sum
of the coercions of `f` and `g`. All such lemmas use `coeFn` in their name, to distinguish the
function coercion from the coercion to almost everywhere defined functions.
-/
noncomputable section
set_option linter.uppercaseLean3 false
open TopologicalSpace MeasureTheory Filter
open scoped NNReal ENNReal Topology MeasureTheory Uniformity
variable {α E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G]
namespace MeasureTheory
/-!
### Lp space
The space of equivalence classes of measurable functions for which `snorm f p μ < ∞`.
-/
@[simp]
theorem snorm_aeeqFun {α E : Type*} [MeasurableSpace α] {μ : Measure α} [NormedAddCommGroup E]
{p : ℝ≥0∞} {f : α → E} (hf : AEStronglyMeasurable f μ) :
snorm (AEEqFun.mk f hf) p μ = snorm f p μ :=
snorm_congr_ae (AEEqFun.coeFn_mk _ _)
#align measure_theory.snorm_ae_eq_fun MeasureTheory.snorm_aeeqFun
theorem Memℒp.snorm_mk_lt_top {α E : Type*} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] {p : ℝ≥0∞} {f : α → E} (hfp : Memℒp f p μ) :
snorm (AEEqFun.mk f hfp.1) p μ < ∞ := by simp [hfp.2]
#align measure_theory.mem_ℒp.snorm_mk_lt_top MeasureTheory.Memℒp.snorm_mk_lt_top
/-- Lp space -/
def Lp {α} (E : Type*) {m : MeasurableSpace α} [NormedAddCommGroup E] (p : ℝ≥0∞)
(μ : Measure α := by volume_tac) : AddSubgroup (α →ₘ[μ] E) where
carrier := { f | snorm f p μ < ∞ }
zero_mem' := by simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
add_mem' {f g} hf hg := by
simp [snorm_congr_ae (AEEqFun.coeFn_add f g),
snorm_add_lt_top ⟨f.aestronglyMeasurable, hf⟩ ⟨g.aestronglyMeasurable, hg⟩]
neg_mem' {f} hf := by rwa [Set.mem_setOf_eq, snorm_congr_ae (AEEqFun.coeFn_neg f), snorm_neg]
#align measure_theory.Lp MeasureTheory.Lp
-- Porting note: calling the first argument `α` breaks the `(α := ·)` notation
scoped notation:25 α' " →₁[" μ "] " E => MeasureTheory.Lp (α := α') E 1 μ
scoped notation:25 α' " →₂[" μ "] " E => MeasureTheory.Lp (α := α') E 2 μ
namespace Memℒp
/-- make an element of Lp from a function verifying `Memℒp` -/
def toLp (f : α → E) (h_mem_ℒp : Memℒp f p μ) : Lp E p μ :=
⟨AEEqFun.mk f h_mem_ℒp.1, h_mem_ℒp.snorm_mk_lt_top⟩
#align measure_theory.mem_ℒp.to_Lp MeasureTheory.Memℒp.toLp
theorem coeFn_toLp {f : α → E} (hf : Memℒp f p μ) : hf.toLp f =ᵐ[μ] f :=
AEEqFun.coeFn_mk _ _
#align measure_theory.mem_ℒp.coe_fn_to_Lp MeasureTheory.Memℒp.coeFn_toLp
theorem toLp_congr {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) (hfg : f =ᵐ[μ] g) :
hf.toLp f = hg.toLp g := by simp [toLp, hfg]
#align measure_theory.mem_ℒp.to_Lp_congr MeasureTheory.Memℒp.toLp_congr
@[simp]
theorem toLp_eq_toLp_iff {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
hf.toLp f = hg.toLp g ↔ f =ᵐ[μ] g := by simp [toLp]
#align measure_theory.mem_ℒp.to_Lp_eq_to_Lp_iff MeasureTheory.Memℒp.toLp_eq_toLp_iff
@[simp]
theorem toLp_zero (h : Memℒp (0 : α → E) p μ) : h.toLp 0 = 0 :=
rfl
#align measure_theory.mem_ℒp.to_Lp_zero MeasureTheory.Memℒp.toLp_zero
theorem toLp_add {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.add hg).toLp (f + g) = hf.toLp f + hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_add MeasureTheory.Memℒp.toLp_add
theorem toLp_neg {f : α → E} (hf : Memℒp f p μ) : hf.neg.toLp (-f) = -hf.toLp f :=
rfl
#align measure_theory.mem_ℒp.to_Lp_neg MeasureTheory.Memℒp.toLp_neg
theorem toLp_sub {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.sub hg).toLp (f - g) = hf.toLp f - hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_sub MeasureTheory.Memℒp.toLp_sub
end Memℒp
namespace Lp
instance instCoeFun : CoeFun (Lp E p μ) (fun _ => α → E) :=
⟨fun f => ((f : α →ₘ[μ] E) : α → E)⟩
#align measure_theory.Lp.has_coe_to_fun MeasureTheory.Lp.instCoeFun
@[ext high]
theorem ext {f g : Lp E p μ} (h : f =ᵐ[μ] g) : f = g := by
cases f
cases g
simp only [Subtype.mk_eq_mk]
exact AEEqFun.ext h
#align measure_theory.Lp.ext MeasureTheory.Lp.ext
theorem ext_iff {f g : Lp E p μ} : f = g ↔ f =ᵐ[μ] g :=
⟨fun h => by rw [h], fun h => ext h⟩
#align measure_theory.Lp.ext_iff MeasureTheory.Lp.ext_iff
theorem mem_Lp_iff_snorm_lt_top {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ snorm f p μ < ∞ := Iff.rfl
#align measure_theory.Lp.mem_Lp_iff_snorm_lt_top MeasureTheory.Lp.mem_Lp_iff_snorm_lt_top
theorem mem_Lp_iff_memℒp {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ Memℒp f p μ := by
simp [mem_Lp_iff_snorm_lt_top, Memℒp, f.stronglyMeasurable.aestronglyMeasurable]
#align measure_theory.Lp.mem_Lp_iff_mem_ℒp MeasureTheory.Lp.mem_Lp_iff_memℒp
protected theorem antitone [IsFiniteMeasure μ] {p q : ℝ≥0∞} (hpq : p ≤ q) : Lp E q μ ≤ Lp E p μ :=
fun f hf => (Memℒp.memℒp_of_exponent_le ⟨f.aestronglyMeasurable, hf⟩ hpq).2
#align measure_theory.Lp.antitone MeasureTheory.Lp.antitone
@[simp]
theorem coeFn_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α → E) = f :=
rfl
#align measure_theory.Lp.coe_fn_mk MeasureTheory.Lp.coeFn_mk
-- @[simp] -- Porting note (#10685): dsimp can prove this
theorem coe_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α →ₘ[μ] E) = f :=
rfl
#align measure_theory.Lp.coe_mk MeasureTheory.Lp.coe_mk
@[simp]
theorem toLp_coeFn (f : Lp E p μ) (hf : Memℒp f p μ) : hf.toLp f = f := by
cases f
simp [Memℒp.toLp]
#align measure_theory.Lp.to_Lp_coe_fn MeasureTheory.Lp.toLp_coeFn
theorem snorm_lt_top (f : Lp E p μ) : snorm f p μ < ∞ :=
f.prop
#align measure_theory.Lp.snorm_lt_top MeasureTheory.Lp.snorm_lt_top
theorem snorm_ne_top (f : Lp E p μ) : snorm f p μ ≠ ∞ :=
(snorm_lt_top f).ne
#align measure_theory.Lp.snorm_ne_top MeasureTheory.Lp.snorm_ne_top
@[measurability]
protected theorem stronglyMeasurable (f : Lp E p μ) : StronglyMeasurable f :=
f.val.stronglyMeasurable
#align measure_theory.Lp.strongly_measurable MeasureTheory.Lp.stronglyMeasurable
@[measurability]
protected theorem aestronglyMeasurable (f : Lp E p μ) : AEStronglyMeasurable f μ :=
f.val.aestronglyMeasurable
#align measure_theory.Lp.ae_strongly_measurable MeasureTheory.Lp.aestronglyMeasurable
protected theorem memℒp (f : Lp E p μ) : Memℒp f p μ :=
⟨Lp.aestronglyMeasurable f, f.prop⟩
#align measure_theory.Lp.mem_ℒp MeasureTheory.Lp.memℒp
variable (E p μ)
theorem coeFn_zero : ⇑(0 : Lp E p μ) =ᵐ[μ] 0 :=
AEEqFun.coeFn_zero
#align measure_theory.Lp.coe_fn_zero MeasureTheory.Lp.coeFn_zero
variable {E p μ}
theorem coeFn_neg (f : Lp E p μ) : ⇑(-f) =ᵐ[μ] -f :=
AEEqFun.coeFn_neg _
#align measure_theory.Lp.coe_fn_neg MeasureTheory.Lp.coeFn_neg
theorem coeFn_add (f g : Lp E p μ) : ⇑(f + g) =ᵐ[μ] f + g :=
AEEqFun.coeFn_add _ _
#align measure_theory.Lp.coe_fn_add MeasureTheory.Lp.coeFn_add
theorem coeFn_sub (f g : Lp E p μ) : ⇑(f - g) =ᵐ[μ] f - g :=
AEEqFun.coeFn_sub _ _
#align measure_theory.Lp.coe_fn_sub MeasureTheory.Lp.coeFn_sub
theorem const_mem_Lp (α) {_ : MeasurableSpace α} (μ : Measure α) (c : E) [IsFiniteMeasure μ] :
@AEEqFun.const α _ _ μ _ c ∈ Lp E p μ :=
(memℒp_const c).snorm_mk_lt_top
#align measure_theory.Lp.mem_Lp_const MeasureTheory.Lp.const_mem_Lp
instance instNorm : Norm (Lp E p μ) where norm f := ENNReal.toReal (snorm f p μ)
#align measure_theory.Lp.has_norm MeasureTheory.Lp.instNorm
-- note: we need this to be defeq to the instance from `SeminormedAddGroup.toNNNorm`, so
-- can't use `ENNReal.toNNReal (snorm f p μ)`
instance instNNNorm : NNNorm (Lp E p μ) where nnnorm f := ⟨‖f‖, ENNReal.toReal_nonneg⟩
#align measure_theory.Lp.has_nnnorm MeasureTheory.Lp.instNNNorm
instance instDist : Dist (Lp E p μ) where dist f g := ‖f - g‖
#align measure_theory.Lp.has_dist MeasureTheory.Lp.instDist
instance instEDist : EDist (Lp E p μ) where edist f g := snorm (⇑f - ⇑g) p μ
#align measure_theory.Lp.has_edist MeasureTheory.Lp.instEDist
theorem norm_def (f : Lp E p μ) : ‖f‖ = ENNReal.toReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.norm_def MeasureTheory.Lp.norm_def
theorem nnnorm_def (f : Lp E p μ) : ‖f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.nnnorm_def MeasureTheory.Lp.nnnorm_def
@[simp, norm_cast]
protected theorem coe_nnnorm (f : Lp E p μ) : (‖f‖₊ : ℝ) = ‖f‖ :=
rfl
#align measure_theory.Lp.coe_nnnorm MeasureTheory.Lp.coe_nnnorm
@[simp, norm_cast]
theorem nnnorm_coe_ennreal (f : Lp E p μ) : (‖f‖₊ : ℝ≥0∞) = snorm f p μ :=
ENNReal.coe_toNNReal <| Lp.snorm_ne_top f
@[simp]
theorem norm_toLp (f : α → E) (hf : Memℒp f p μ) : ‖hf.toLp f‖ = ENNReal.toReal (snorm f p μ) := by
erw [norm_def, snorm_congr_ae (Memℒp.coeFn_toLp hf)]
#align measure_theory.Lp.norm_to_Lp MeasureTheory.Lp.norm_toLp
@[simp]
theorem nnnorm_toLp (f : α → E) (hf : Memℒp f p μ) :
‖hf.toLp f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
NNReal.eq <| norm_toLp f hf
#align measure_theory.Lp.nnnorm_to_Lp MeasureTheory.Lp.nnnorm_toLp
theorem coe_nnnorm_toLp {f : α → E} (hf : Memℒp f p μ) : (‖hf.toLp f‖₊ : ℝ≥0∞) = snorm f p μ := by
rw [nnnorm_toLp f hf, ENNReal.coe_toNNReal hf.2.ne]
theorem dist_def (f g : Lp E p μ) : dist f g = (snorm (⇑f - ⇑g) p μ).toReal := by
simp_rw [dist, norm_def]
refine congr_arg _ ?_
apply snorm_congr_ae (coeFn_sub _ _)
#align measure_theory.Lp.dist_def MeasureTheory.Lp.dist_def
theorem edist_def (f g : Lp E p μ) : edist f g = snorm (⇑f - ⇑g) p μ :=
rfl
#align measure_theory.Lp.edist_def MeasureTheory.Lp.edist_def
protected theorem edist_dist (f g : Lp E p μ) : edist f g = .ofReal (dist f g) := by
rw [edist_def, dist_def, ← snorm_congr_ae (coeFn_sub _ _),
ENNReal.ofReal_toReal (snorm_ne_top (f - g))]
protected theorem dist_edist (f g : Lp E p μ) : dist f g = (edist f g).toReal :=
MeasureTheory.Lp.dist_def ..
theorem dist_eq_norm (f g : Lp E p μ) : dist f g = ‖f - g‖ := rfl
@[simp]
theorem edist_toLp_toLp (f g : α → E) (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
edist (hf.toLp f) (hg.toLp g) = snorm (f - g) p μ := by
rw [edist_def]
exact snorm_congr_ae (hf.coeFn_toLp.sub hg.coeFn_toLp)
#align measure_theory.Lp.edist_to_Lp_to_Lp MeasureTheory.Lp.edist_toLp_toLp
@[simp]
theorem edist_toLp_zero (f : α → E) (hf : Memℒp f p μ) : edist (hf.toLp f) 0 = snorm f p μ := by
convert edist_toLp_toLp f 0 hf zero_memℒp
simp
#align measure_theory.Lp.edist_to_Lp_zero MeasureTheory.Lp.edist_toLp_zero
@[simp]
theorem nnnorm_zero : ‖(0 : Lp E p μ)‖₊ = 0 := by
rw [nnnorm_def]
change (snorm (⇑(0 : α →ₘ[μ] E)) p μ).toNNReal = 0
simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
#align measure_theory.Lp.nnnorm_zero MeasureTheory.Lp.nnnorm_zero
@[simp]
theorem norm_zero : ‖(0 : Lp E p μ)‖ = 0 :=
congr_arg ((↑) : ℝ≥0 → ℝ) nnnorm_zero
#align measure_theory.Lp.norm_zero MeasureTheory.Lp.norm_zero
@[simp]
theorem norm_measure_zero (f : Lp E p (0 : MeasureTheory.Measure α)) : ‖f‖ = 0 := by
simp [norm_def]
@[simp] theorem norm_exponent_zero (f : Lp E 0 μ) : ‖f‖ = 0 := by simp [norm_def]
theorem nnnorm_eq_zero_iff {f : Lp E p μ} (hp : 0 < p) : ‖f‖₊ = 0 ↔ f = 0 := by
refine ⟨fun hf => ?_, fun hf => by simp [hf]⟩
rw [nnnorm_def, ENNReal.toNNReal_eq_zero_iff] at hf
cases hf with
| inl hf =>
rw [snorm_eq_zero_iff (Lp.aestronglyMeasurable f) hp.ne.symm] at hf
exact Subtype.eq (AEEqFun.ext (hf.trans AEEqFun.coeFn_zero.symm))
| inr hf =>
exact absurd hf (snorm_ne_top f)
#align measure_theory.Lp.nnnorm_eq_zero_iff MeasureTheory.Lp.nnnorm_eq_zero_iff
theorem norm_eq_zero_iff {f : Lp E p μ} (hp : 0 < p) : ‖f‖ = 0 ↔ f = 0 :=
NNReal.coe_eq_zero.trans (nnnorm_eq_zero_iff hp)
#align measure_theory.Lp.norm_eq_zero_iff MeasureTheory.Lp.norm_eq_zero_iff
theorem eq_zero_iff_ae_eq_zero {f : Lp E p μ} : f = 0 ↔ f =ᵐ[μ] 0 := by
rw [← (Lp.memℒp f).toLp_eq_toLp_iff zero_memℒp, Memℒp.toLp_zero, toLp_coeFn]
#align measure_theory.Lp.eq_zero_iff_ae_eq_zero MeasureTheory.Lp.eq_zero_iff_ae_eq_zero
@[simp]
theorem nnnorm_neg (f : Lp E p μ) : ‖-f‖₊ = ‖f‖₊ := by
rw [nnnorm_def, nnnorm_def, snorm_congr_ae (coeFn_neg _), snorm_neg]
#align measure_theory.Lp.nnnorm_neg MeasureTheory.Lp.nnnorm_neg
@[simp]
theorem norm_neg (f : Lp E p μ) : ‖-f‖ = ‖f‖ :=
congr_arg ((↑) : ℝ≥0 → ℝ) (nnnorm_neg f)
#align measure_theory.Lp.norm_neg MeasureTheory.Lp.norm_neg
theorem nnnorm_le_mul_nnnorm_of_ae_le_mul {c : ℝ≥0} {f : Lp E p μ} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ c * ‖g x‖₊) : ‖f‖₊ ≤ c * ‖g‖₊ := by
simp only [nnnorm_def]
have := snorm_le_nnreal_smul_snorm_of_ae_le_mul h p
rwa [← ENNReal.toNNReal_le_toNNReal, ENNReal.smul_def, smul_eq_mul, ENNReal.toNNReal_mul,
ENNReal.toNNReal_coe] at this
· exact (Lp.memℒp _).snorm_ne_top
· exact ENNReal.mul_ne_top ENNReal.coe_ne_top (Lp.memℒp _).snorm_ne_top
#align measure_theory.Lp.nnnorm_le_mul_nnnorm_of_ae_le_mul MeasureTheory.Lp.nnnorm_le_mul_nnnorm_of_ae_le_mul
theorem norm_le_mul_norm_of_ae_le_mul {c : ℝ} {f : Lp E p μ} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖ ≤ c * ‖g x‖) : ‖f‖ ≤ c * ‖g‖ := by
rcases le_or_lt 0 c with hc | hc
· lift c to ℝ≥0 using hc
exact NNReal.coe_le_coe.mpr (nnnorm_le_mul_nnnorm_of_ae_le_mul h)
· simp only [norm_def]
have := snorm_eq_zero_and_zero_of_ae_le_mul_neg h hc p
simp [this]
#align measure_theory.Lp.norm_le_mul_norm_of_ae_le_mul MeasureTheory.Lp.norm_le_mul_norm_of_ae_le_mul
theorem norm_le_norm_of_ae_le {f : Lp E p μ} {g : Lp F p μ} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
‖f‖ ≤ ‖g‖ := by
rw [norm_def, norm_def, ENNReal.toReal_le_toReal (snorm_ne_top _) (snorm_ne_top _)]
exact snorm_mono_ae h
#align measure_theory.Lp.norm_le_norm_of_ae_le MeasureTheory.Lp.norm_le_norm_of_ae_le
theorem mem_Lp_of_nnnorm_ae_le_mul {c : ℝ≥0} {f : α →ₘ[μ] E} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ c * ‖g x‖₊) : f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_nnnorm_le_mul (Lp.memℒp g) f.aestronglyMeasurable h
#align measure_theory.Lp.mem_Lp_of_nnnorm_ae_le_mul MeasureTheory.Lp.mem_Lp_of_nnnorm_ae_le_mul
theorem mem_Lp_of_ae_le_mul {c : ℝ} {f : α →ₘ[μ] E} {g : Lp F p μ}
(h : ∀ᵐ x ∂μ, ‖f x‖ ≤ c * ‖g x‖) : f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_le_mul (Lp.memℒp g) f.aestronglyMeasurable h
#align measure_theory.Lp.mem_Lp_of_ae_le_mul MeasureTheory.Lp.mem_Lp_of_ae_le_mul
theorem mem_Lp_of_nnnorm_ae_le {f : α →ₘ[μ] E} {g : Lp F p μ} (h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_le (Lp.memℒp g) f.aestronglyMeasurable h
#align measure_theory.Lp.mem_Lp_of_nnnorm_ae_le MeasureTheory.Lp.mem_Lp_of_nnnorm_ae_le
theorem mem_Lp_of_ae_le {f : α →ₘ[μ] E} {g : Lp F p μ} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
f ∈ Lp E p μ :=
mem_Lp_of_nnnorm_ae_le h
#align measure_theory.Lp.mem_Lp_of_ae_le MeasureTheory.Lp.mem_Lp_of_ae_le
theorem mem_Lp_of_ae_nnnorm_bound [IsFiniteMeasure μ] {f : α →ₘ[μ] E} (C : ℝ≥0)
(hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) : f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_bound f.aestronglyMeasurable _ hfC
#align measure_theory.Lp.mem_Lp_of_ae_nnnorm_bound MeasureTheory.Lp.mem_Lp_of_ae_nnnorm_bound
theorem mem_Lp_of_ae_bound [IsFiniteMeasure μ] {f : α →ₘ[μ] E} (C : ℝ) (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
f ∈ Lp E p μ :=
mem_Lp_iff_memℒp.2 <| Memℒp.of_bound f.aestronglyMeasurable _ hfC
#align measure_theory.Lp.mem_Lp_of_ae_bound MeasureTheory.Lp.mem_Lp_of_ae_bound
theorem nnnorm_le_of_ae_bound [IsFiniteMeasure μ] {f : Lp E p μ} {C : ℝ≥0}
(hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) : ‖f‖₊ ≤ measureUnivNNReal μ ^ p.toReal⁻¹ * C := by
by_cases hμ : μ = 0
· by_cases hp : p.toReal⁻¹ = 0
· simp [hp, hμ, nnnorm_def]
· simp [hμ, nnnorm_def, Real.zero_rpow hp]
rw [← ENNReal.coe_le_coe, nnnorm_def, ENNReal.coe_toNNReal (snorm_ne_top _)]
refine (snorm_le_of_ae_nnnorm_bound hfC).trans_eq ?_
rw [← coe_measureUnivNNReal μ, ENNReal.coe_rpow_of_ne_zero (measureUnivNNReal_pos hμ).ne',
ENNReal.coe_mul, mul_comm, ENNReal.smul_def, smul_eq_mul]
#align measure_theory.Lp.nnnorm_le_of_ae_bound MeasureTheory.Lp.nnnorm_le_of_ae_bound
theorem norm_le_of_ae_bound [IsFiniteMeasure μ] {f : Lp E p μ} {C : ℝ} (hC : 0 ≤ C)
(hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) : ‖f‖ ≤ measureUnivNNReal μ ^ p.toReal⁻¹ * C := by
lift C to ℝ≥0 using hC
have := nnnorm_le_of_ae_bound hfC
rwa [← NNReal.coe_le_coe, NNReal.coe_mul, NNReal.coe_rpow] at this
#align measure_theory.Lp.norm_le_of_ae_bound MeasureTheory.Lp.norm_le_of_ae_bound
instance instNormedAddCommGroup [hp : Fact (1 ≤ p)] : NormedAddCommGroup (Lp E p μ) :=
{ AddGroupNorm.toNormedAddCommGroup
{ toFun := (norm : Lp E p μ → ℝ)
map_zero' := norm_zero
neg' := by simp
add_le' := fun f g => by
suffices (‖f + g‖₊ : ℝ≥0∞) ≤ ‖f‖₊ + ‖g‖₊ from mod_cast this
simp only [Lp.nnnorm_coe_ennreal]
exact (snorm_congr_ae (AEEqFun.coeFn_add _ _)).trans_le
(snorm_add_le (Lp.aestronglyMeasurable _) (Lp.aestronglyMeasurable _) hp.out)
eq_zero_of_map_eq_zero' := fun f =>
(norm_eq_zero_iff <| zero_lt_one.trans_le hp.1).1 } with
edist := edist
edist_dist := Lp.edist_dist }
#align measure_theory.Lp.normed_add_comm_group MeasureTheory.Lp.instNormedAddCommGroup
-- check no diamond is created
example [Fact (1 ≤ p)] : PseudoEMetricSpace.toEDist = (Lp.instEDist : EDist (Lp E p μ)) := by
with_reducible_and_instances rfl
example [Fact (1 ≤ p)] : SeminormedAddGroup.toNNNorm = (Lp.instNNNorm : NNNorm (Lp E p μ)) := by
with_reducible_and_instances rfl
section BoundedSMul
variable {𝕜 𝕜' : Type*}
variable [NormedRing 𝕜] [NormedRing 𝕜'] [Module 𝕜 E] [Module 𝕜' E]
variable [BoundedSMul 𝕜 E] [BoundedSMul 𝕜' E]
theorem const_smul_mem_Lp (c : 𝕜) (f : Lp E p μ) : c • (f : α →ₘ[μ] E) ∈ Lp E p μ := by
rw [mem_Lp_iff_snorm_lt_top, snorm_congr_ae (AEEqFun.coeFn_smul _ _)]
refine (snorm_const_smul_le _ _).trans_lt ?_
rw [ENNReal.smul_def, smul_eq_mul, ENNReal.mul_lt_top_iff]
exact Or.inl ⟨ENNReal.coe_lt_top, f.prop⟩
#align measure_theory.Lp.mem_Lp_const_smul MeasureTheory.Lp.const_smul_mem_Lp
variable (E p μ 𝕜)
/-- The `𝕜`-submodule of elements of `α →ₘ[μ] E` whose `Lp` norm is finite. This is `Lp E p μ`,
with extra structure. -/
def LpSubmodule : Submodule 𝕜 (α →ₘ[μ] E) :=
{ Lp E p μ with smul_mem' := fun c f hf => by simpa using const_smul_mem_Lp c ⟨f, hf⟩ }
#align measure_theory.Lp.Lp_submodule MeasureTheory.Lp.LpSubmodule
variable {E p μ 𝕜}
theorem coe_LpSubmodule : (LpSubmodule E p μ 𝕜).toAddSubgroup = Lp E p μ :=
rfl
#align measure_theory.Lp.coe_Lp_submodule MeasureTheory.Lp.coe_LpSubmodule
instance instModule : Module 𝕜 (Lp E p μ) :=
{ (LpSubmodule E p μ 𝕜).module with }
#align measure_theory.Lp.module MeasureTheory.Lp.instModule
theorem coeFn_smul (c : 𝕜) (f : Lp E p μ) : ⇑(c • f) =ᵐ[μ] c • ⇑f :=
AEEqFun.coeFn_smul _ _
#align measure_theory.Lp.coe_fn_smul MeasureTheory.Lp.coeFn_smul
instance instIsCentralScalar [Module 𝕜ᵐᵒᵖ E] [BoundedSMul 𝕜ᵐᵒᵖ E] [IsCentralScalar 𝕜 E] :
IsCentralScalar 𝕜 (Lp E p μ) where
op_smul_eq_smul k f := Subtype.ext <| op_smul_eq_smul k (f : α →ₘ[μ] E)
#align measure_theory.Lp.is_central_scalar MeasureTheory.Lp.instIsCentralScalar
instance instSMulCommClass [SMulCommClass 𝕜 𝕜' E] : SMulCommClass 𝕜 𝕜' (Lp E p μ) where
smul_comm k k' f := Subtype.ext <| smul_comm k k' (f : α →ₘ[μ] E)
#align measure_theory.Lp.smul_comm_class MeasureTheory.Lp.instSMulCommClass
instance instIsScalarTower [SMul 𝕜 𝕜'] [IsScalarTower 𝕜 𝕜' E] : IsScalarTower 𝕜 𝕜' (Lp E p μ) where
smul_assoc k k' f := Subtype.ext <| smul_assoc k k' (f : α →ₘ[μ] E)
instance instBoundedSMul [Fact (1 ≤ p)] : BoundedSMul 𝕜 (Lp E p μ) :=
-- TODO: add `BoundedSMul.of_nnnorm_smul_le`
BoundedSMul.of_norm_smul_le fun r f => by
suffices (‖r • f‖₊ : ℝ≥0∞) ≤ ‖r‖₊ * ‖f‖₊ from mod_cast this
rw [nnnorm_def, nnnorm_def, ENNReal.coe_toNNReal (Lp.snorm_ne_top _),
snorm_congr_ae (coeFn_smul _ _), ENNReal.coe_toNNReal (Lp.snorm_ne_top _)]
exact snorm_const_smul_le r f
#align measure_theory.Lp.has_bounded_smul MeasureTheory.Lp.instBoundedSMul
end BoundedSMul
section NormedSpace
variable {𝕜 : Type*} [NormedField 𝕜] [NormedSpace 𝕜 E]
instance instNormedSpace [Fact (1 ≤ p)] : NormedSpace 𝕜 (Lp E p μ) where
norm_smul_le _ _ := norm_smul_le _ _
#align measure_theory.Lp.normed_space MeasureTheory.Lp.instNormedSpace
end NormedSpace
end Lp
namespace Memℒp
variable {𝕜 : Type*} [NormedRing 𝕜] [Module 𝕜 E] [BoundedSMul 𝕜 E]
theorem toLp_const_smul {f : α → E} (c : 𝕜) (hf : Memℒp f p μ) :
(hf.const_smul c).toLp (c • f) = c • hf.toLp f :=
rfl
#align measure_theory.mem_ℒp.to_Lp_const_smul MeasureTheory.Memℒp.toLp_const_smul
end Memℒp
/-! ### Indicator of a set as an element of Lᵖ
For a set `s` with `(hs : MeasurableSet s)` and `(hμs : μ s < ∞)`, we build
`indicatorConstLp p hs hμs c`, the element of `Lp` corresponding to `s.indicator (fun _ => c)`.
-/
section Indicator
variable {c : E} {f : α → E} {hf : AEStronglyMeasurable f μ} {s : Set α}
theorem snormEssSup_indicator_le (s : Set α) (f : α → G) :
snormEssSup (s.indicator f) μ ≤ snormEssSup f μ := by
refine essSup_mono_ae (eventually_of_forall fun x => ?_)
rw [ENNReal.coe_le_coe, nnnorm_indicator_eq_indicator_nnnorm]
exact Set.indicator_le_self s _ x
#align measure_theory.snorm_ess_sup_indicator_le MeasureTheory.snormEssSup_indicator_le
theorem snormEssSup_indicator_const_le (s : Set α) (c : G) :
snormEssSup (s.indicator fun _ : α => c) μ ≤ ‖c‖₊ := by
by_cases hμ0 : μ = 0
· rw [hμ0, snormEssSup_measure_zero]
exact zero_le _
· exact (snormEssSup_indicator_le s fun _ => c).trans (snormEssSup_const c hμ0).le
#align measure_theory.snorm_ess_sup_indicator_const_le MeasureTheory.snormEssSup_indicator_const_le
theorem snormEssSup_indicator_const_eq (s : Set α) (c : G) (hμs : μ s ≠ 0) :
snormEssSup (s.indicator fun _ : α => c) μ = ‖c‖₊ := by
refine le_antisymm (snormEssSup_indicator_const_le s c) ?_
by_contra! h
have h' := ae_iff.mp (ae_lt_of_essSup_lt h)
push_neg at h'
refine hμs (measure_mono_null (fun x hx_mem => ?_) h')
rw [Set.mem_setOf_eq, Set.indicator_of_mem hx_mem]
#align measure_theory.snorm_ess_sup_indicator_const_eq MeasureTheory.snormEssSup_indicator_const_eq
theorem snorm_indicator_le (f : α → E) : snorm (s.indicator f) p μ ≤ snorm f p μ := by
refine snorm_mono_ae (eventually_of_forall fun x => ?_)
suffices ‖s.indicator f x‖₊ ≤ ‖f x‖₊ by exact NNReal.coe_mono this
rw [nnnorm_indicator_eq_indicator_nnnorm]
exact s.indicator_le_self _ x
#align measure_theory.snorm_indicator_le MeasureTheory.snorm_indicator_le
theorem snorm_indicator_const₀ {c : G} (hs : NullMeasurableSet s μ) (hp : p ≠ 0) (hp_top : p ≠ ∞) :
snorm (s.indicator fun _ => c) p μ = ‖c‖₊ * μ s ^ (1 / p.toReal) :=
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp hp_top
calc
snorm (s.indicator fun _ => c) p μ
= (∫⁻ x, ((‖(s.indicator fun _ ↦ c) x‖₊ : ℝ≥0∞) ^ p.toReal) ∂μ) ^ (1 / p.toReal) :=
snorm_eq_lintegral_rpow_nnnorm hp hp_top
_ = (∫⁻ x, (s.indicator fun _ ↦ (‖c‖₊ : ℝ≥0∞) ^ p.toReal) x ∂μ) ^ (1 / p.toReal) := by
congr 2
refine (Set.comp_indicator_const c (fun x : G ↦ (‖x‖₊ : ℝ≥0∞) ^ p.toReal) ?_)
simp [hp_pos]
_ = ‖c‖₊ * μ s ^ (1 / p.toReal) := by
rw [lintegral_indicator_const₀ hs, ENNReal.mul_rpow_of_nonneg, ← ENNReal.rpow_mul,
mul_one_div_cancel hp_pos.ne', ENNReal.rpow_one]
positivity
theorem snorm_indicator_const {c : G} (hs : MeasurableSet s) (hp : p ≠ 0) (hp_top : p ≠ ∞) :
snorm (s.indicator fun _ => c) p μ = ‖c‖₊ * μ s ^ (1 / p.toReal) :=
snorm_indicator_const₀ hs.nullMeasurableSet hp hp_top
#align measure_theory.snorm_indicator_const MeasureTheory.snorm_indicator_const
theorem snorm_indicator_const' {c : G} (hs : MeasurableSet s) (hμs : μ s ≠ 0) (hp : p ≠ 0) :
snorm (s.indicator fun _ => c) p μ = ‖c‖₊ * μ s ^ (1 / p.toReal) := by
by_cases hp_top : p = ∞
· simp [hp_top, snormEssSup_indicator_const_eq s c hμs]
· exact snorm_indicator_const hs hp hp_top
#align measure_theory.snorm_indicator_const' MeasureTheory.snorm_indicator_const'
theorem snorm_indicator_const_le (c : G) (p : ℝ≥0∞) :
snorm (s.indicator fun _ => c) p μ ≤ ‖c‖₊ * μ s ^ (1 / p.toReal) := by
rcases eq_or_ne p 0 with (rfl | hp)
· simp only [snorm_exponent_zero, zero_le']
rcases eq_or_ne p ∞ with (rfl | h'p)
· simp only [snorm_exponent_top, ENNReal.top_toReal, _root_.div_zero, ENNReal.rpow_zero, mul_one]
exact snormEssSup_indicator_const_le _ _
let t := toMeasurable μ s
calc
snorm (s.indicator fun _ => c) p μ ≤ snorm (t.indicator fun _ => c) p μ :=
snorm_mono (norm_indicator_le_of_subset (subset_toMeasurable _ _) _)
_ = ‖c‖₊ * μ t ^ (1 / p.toReal) :=
(snorm_indicator_const (measurableSet_toMeasurable _ _) hp h'p)
_ = ‖c‖₊ * μ s ^ (1 / p.toReal) := by rw [measure_toMeasurable]
#align measure_theory.snorm_indicator_const_le MeasureTheory.snorm_indicator_const_le
theorem Memℒp.indicator (hs : MeasurableSet s) (hf : Memℒp f p μ) : Memℒp (s.indicator f) p μ :=
⟨hf.aestronglyMeasurable.indicator hs, lt_of_le_of_lt (snorm_indicator_le f) hf.snorm_lt_top⟩
#align measure_theory.mem_ℒp.indicator MeasureTheory.Memℒp.indicator
theorem snormEssSup_indicator_eq_snormEssSup_restrict {f : α → F} (hs : MeasurableSet s) :
snormEssSup (s.indicator f) μ = snormEssSup f (μ.restrict s) := by
simp_rw [snormEssSup, nnnorm_indicator_eq_indicator_nnnorm, ENNReal.coe_indicator,
ENNReal.essSup_indicator_eq_essSup_restrict hs]
#align measure_theory.snorm_ess_sup_indicator_eq_snorm_ess_sup_restrict MeasureTheory.snormEssSup_indicator_eq_snormEssSup_restrict
theorem snorm_indicator_eq_snorm_restrict {f : α → F} (hs : MeasurableSet s) :
snorm (s.indicator f) p μ = snorm f p (μ.restrict s) := by
by_cases hp_zero : p = 0
· simp only [hp_zero, snorm_exponent_zero]
by_cases hp_top : p = ∞
· simp_rw [hp_top, snorm_exponent_top]
exact snormEssSup_indicator_eq_snormEssSup_restrict hs
simp_rw [snorm_eq_lintegral_rpow_nnnorm hp_zero hp_top]
suffices (∫⁻ x, (‖s.indicator f x‖₊ : ℝ≥0∞) ^ p.toReal ∂μ) =
∫⁻ x in s, (‖f x‖₊ : ℝ≥0∞) ^ p.toReal ∂μ by rw [this]
rw [← lintegral_indicator _ hs]
congr
simp_rw [nnnorm_indicator_eq_indicator_nnnorm, ENNReal.coe_indicator]
have h_zero : (fun x => x ^ p.toReal) (0 : ℝ≥0∞) = 0 := by
simp [ENNReal.toReal_pos hp_zero hp_top]
-- Porting note: The implicit argument should be specified because the elaborator can't deal with
-- `∘` well.
exact (Set.indicator_comp_of_zero (g := fun x : ℝ≥0∞ => x ^ p.toReal) h_zero).symm
#align measure_theory.snorm_indicator_eq_snorm_restrict MeasureTheory.snorm_indicator_eq_snorm_restrict
theorem memℒp_indicator_iff_restrict (hs : MeasurableSet s) :
Memℒp (s.indicator f) p μ ↔ Memℒp f p (μ.restrict s) := by
simp [Memℒp, aestronglyMeasurable_indicator_iff hs, snorm_indicator_eq_snorm_restrict hs]
#align measure_theory.mem_ℒp_indicator_iff_restrict MeasureTheory.memℒp_indicator_iff_restrict
/-- If a function is supported on a finite-measure set and belongs to `ℒ^p`, then it belongs to
`ℒ^q` for any `q ≤ p`. -/
theorem Memℒp.memℒp_of_exponent_le_of_measure_support_ne_top
{p q : ℝ≥0∞} {f : α → E} (hfq : Memℒp f q μ) {s : Set α} (hf : ∀ x, x ∉ s → f x = 0)
(hs : μ s ≠ ∞) (hpq : p ≤ q) : Memℒp f p μ := by
have : (toMeasurable μ s).indicator f = f := by
apply Set.indicator_eq_self.2
apply Function.support_subset_iff'.2 (fun x hx ↦ hf x ?_)
contrapose! hx
exact subset_toMeasurable μ s hx
rw [← this, memℒp_indicator_iff_restrict (measurableSet_toMeasurable μ s)] at hfq ⊢
have : Fact (μ (toMeasurable μ s) < ∞) := ⟨by simpa [lt_top_iff_ne_top] using hs⟩
exact memℒp_of_exponent_le hfq hpq
theorem memℒp_indicator_const (p : ℝ≥0∞) (hs : MeasurableSet s) (c : E) (hμsc : c = 0 ∨ μ s ≠ ∞) :
Memℒp (s.indicator fun _ => c) p μ := by
rw [memℒp_indicator_iff_restrict hs]
rcases hμsc with rfl | hμ
· exact zero_memℒp
· have := Fact.mk hμ.lt_top
apply memℒp_const
#align measure_theory.mem_ℒp_indicator_const MeasureTheory.memℒp_indicator_const
/-- The `ℒ^p` norm of the indicator of a set is uniformly small if the set itself has small measure,
for any `p < ∞`. Given here as an existential `∀ ε > 0, ∃ η > 0, ...` to avoid later
management of `ℝ≥0∞`-arithmetic. -/
theorem exists_snorm_indicator_le (hp : p ≠ ∞) (c : E) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _ => c) p μ ≤ ε := by
rcases eq_or_ne p 0 with (rfl | h'p)
· exact ⟨1, zero_lt_one, fun s _ => by simp⟩
have hp₀ : 0 < p := bot_lt_iff_ne_bot.2 h'p
have hp₀' : 0 ≤ 1 / p.toReal := div_nonneg zero_le_one ENNReal.toReal_nonneg
have hp₀'' : 0 < p.toReal := ENNReal.toReal_pos hp₀.ne' hp
obtain ⟨η, hη_pos, hη_le⟩ :
∃ η : ℝ≥0, 0 < η ∧ (‖c‖₊ : ℝ≥0∞) * (η : ℝ≥0∞) ^ (1 / p.toReal) ≤ ε := by
have :
Filter.Tendsto (fun x : ℝ≥0 => ((‖c‖₊ * x ^ (1 / p.toReal) : ℝ≥0) : ℝ≥0∞)) (𝓝 0)
(𝓝 (0 : ℝ≥0)) := by
rw [ENNReal.tendsto_coe]
convert (NNReal.continuousAt_rpow_const (Or.inr hp₀')).tendsto.const_mul _
simp [hp₀''.ne']
have hε' : 0 < ε := hε.bot_lt
obtain ⟨δ, hδ, hδε'⟩ :=
NNReal.nhds_zero_basis.eventually_iff.mp (eventually_le_of_tendsto_lt hε' this)
obtain ⟨η, hη, hηδ⟩ := exists_between hδ
refine ⟨η, hη, ?_⟩
rw [ENNReal.coe_rpow_of_nonneg _ hp₀', ← ENNReal.coe_mul]
exact hδε' hηδ
refine ⟨η, hη_pos, fun s hs => ?_⟩
refine (snorm_indicator_const_le _ _).trans (le_trans ?_ hη_le)
exact mul_le_mul_left' (ENNReal.rpow_le_rpow hs hp₀') _
#align measure_theory.exists_snorm_indicator_le MeasureTheory.exists_snorm_indicator_le
protected lemma Memℒp.piecewise [DecidablePred (· ∈ s)] {g}
(hs : MeasurableSet s) (hf : Memℒp f p (μ.restrict s)) (hg : Memℒp g p (μ.restrict sᶜ)) :
Memℒp (s.piecewise f g) p μ := by
by_cases hp_zero : p = 0
· simp only [hp_zero, memℒp_zero_iff_aestronglyMeasurable]
exact AEStronglyMeasurable.piecewise hs hf.1 hg.1
refine ⟨AEStronglyMeasurable.piecewise hs hf.1 hg.1, ?_⟩
rcases eq_or_ne p ∞ with rfl | hp_top
· rw [snorm_top_piecewise f g hs]
exact max_lt hf.2 hg.2
rw [snorm_lt_top_iff_lintegral_rpow_nnnorm_lt_top hp_zero hp_top, ← lintegral_add_compl _ hs,
ENNReal.add_lt_top]
constructor
· have h : ∀ᵐ (x : α) ∂μ, x ∈ s →
(‖Set.piecewise s f g x‖₊ : ℝ≥0∞) ^ p.toReal = (‖f x‖₊ : ℝ≥0∞) ^ p.toReal := by
filter_upwards with a ha using by simp [ha]
rw [set_lintegral_congr_fun hs h]
exact lintegral_rpow_nnnorm_lt_top_of_snorm_lt_top hp_zero hp_top hf.2
· have h : ∀ᵐ (x : α) ∂μ, x ∈ sᶜ →
(‖Set.piecewise s f g x‖₊ : ℝ≥0∞) ^ p.toReal = (‖g x‖₊ : ℝ≥0∞) ^ p.toReal := by
filter_upwards with a ha
have ha' : a ∉ s := ha
simp [ha']
rw [set_lintegral_congr_fun hs.compl h]
exact lintegral_rpow_nnnorm_lt_top_of_snorm_lt_top hp_zero hp_top hg.2
end Indicator
section IndicatorConstLp
open Set Function
variable {s : Set α} {hs : MeasurableSet s} {hμs : μ s ≠ ∞} {c : E}
/-- Indicator of a set as an element of `Lp`. -/
def indicatorConstLp (p : ℝ≥0∞) (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : E) : Lp E p μ :=
Memℒp.toLp (s.indicator fun _ => c) (memℒp_indicator_const p hs c (Or.inr hμs))
#align measure_theory.indicator_const_Lp MeasureTheory.indicatorConstLp
/-- A version of `Set.indicator_add` for `MeasureTheory.indicatorConstLp`.-/
theorem indicatorConstLp_add {c' : E} :
indicatorConstLp p hs hμs c + indicatorConstLp p hs hμs c' =
indicatorConstLp p hs hμs (c + c') := by
simp_rw [indicatorConstLp, ← Memℒp.toLp_add, indicator_add]
rfl
/-- A version of `Set.indicator_sub` for `MeasureTheory.indicatorConstLp`.-/
theorem indicatorConstLp_sub {c' : E} :
indicatorConstLp p hs hμs c - indicatorConstLp p hs hμs c' =
indicatorConstLp p hs hμs (c - c') := by
simp_rw [indicatorConstLp, ← Memℒp.toLp_sub, indicator_sub]
rfl
theorem indicatorConstLp_coeFn : ⇑(indicatorConstLp p hs hμs c) =ᵐ[μ] s.indicator fun _ => c :=
Memℒp.coeFn_toLp (memℒp_indicator_const p hs c (Or.inr hμs))
#align measure_theory.indicator_const_Lp_coe_fn MeasureTheory.indicatorConstLp_coeFn
theorem indicatorConstLp_coeFn_mem : ∀ᵐ x : α ∂μ, x ∈ s → indicatorConstLp p hs hμs c x = c :=
indicatorConstLp_coeFn.mono fun _x hx hxs => hx.trans (Set.indicator_of_mem hxs _)
#align measure_theory.indicator_const_Lp_coe_fn_mem MeasureTheory.indicatorConstLp_coeFn_mem
theorem indicatorConstLp_coeFn_nmem : ∀ᵐ x : α ∂μ, x ∉ s → indicatorConstLp p hs hμs c x = 0 :=
indicatorConstLp_coeFn.mono fun _x hx hxs => hx.trans (Set.indicator_of_not_mem hxs _)
#align measure_theory.indicator_const_Lp_coe_fn_nmem MeasureTheory.indicatorConstLp_coeFn_nmem
theorem norm_indicatorConstLp (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
‖indicatorConstLp p hs hμs c‖ = ‖c‖ * (μ s).toReal ^ (1 / p.toReal) := by
rw [Lp.norm_def, snorm_congr_ae indicatorConstLp_coeFn,
snorm_indicator_const hs hp_ne_zero hp_ne_top, ENNReal.toReal_mul, ENNReal.toReal_rpow,
ENNReal.coe_toReal, coe_nnnorm]
#align measure_theory.norm_indicator_const_Lp MeasureTheory.norm_indicatorConstLp
theorem norm_indicatorConstLp_top (hμs_ne_zero : μ s ≠ 0) :
‖indicatorConstLp ∞ hs hμs c‖ = ‖c‖ := by
rw [Lp.norm_def, snorm_congr_ae indicatorConstLp_coeFn,
snorm_indicator_const' hs hμs_ne_zero ENNReal.top_ne_zero, ENNReal.top_toReal, _root_.div_zero,
ENNReal.rpow_zero, mul_one, ENNReal.coe_toReal, coe_nnnorm]
#align measure_theory.norm_indicator_const_Lp_top MeasureTheory.norm_indicatorConstLp_top
theorem norm_indicatorConstLp' (hp_pos : p ≠ 0) (hμs_pos : μ s ≠ 0) :
‖indicatorConstLp p hs hμs c‖ = ‖c‖ * (μ s).toReal ^ (1 / p.toReal) := by
by_cases hp_top : p = ∞
· rw [hp_top, ENNReal.top_toReal, _root_.div_zero, Real.rpow_zero, mul_one]
exact norm_indicatorConstLp_top hμs_pos
· exact norm_indicatorConstLp hp_pos hp_top
#align measure_theory.norm_indicator_const_Lp' MeasureTheory.norm_indicatorConstLp'
theorem norm_indicatorConstLp_le :
‖indicatorConstLp p hs hμs c‖ ≤ ‖c‖ * (μ s).toReal ^ (1 / p.toReal) := by
rw [indicatorConstLp, Lp.norm_toLp]
refine ENNReal.toReal_le_of_le_ofReal (by positivity) ?_
refine (snorm_indicator_const_le _ _).trans_eq ?_
rw [← coe_nnnorm, ENNReal.ofReal_mul (NNReal.coe_nonneg _), ENNReal.ofReal_coe_nnreal,
ENNReal.toReal_rpow, ENNReal.ofReal_toReal]
exact ENNReal.rpow_ne_top_of_nonneg (by positivity) hμs
theorem edist_indicatorConstLp_eq_nnnorm {t : Set α} {ht : MeasurableSet t} {hμt : μ t ≠ ∞} :
edist (indicatorConstLp p hs hμs c) (indicatorConstLp p ht hμt c) =
‖indicatorConstLp p (hs.symmDiff ht) (measure_symmDiff_ne_top hμs hμt) c‖₊ := by
unfold indicatorConstLp
rw [Lp.edist_toLp_toLp, snorm_indicator_sub_indicator, Lp.coe_nnnorm_toLp]
theorem dist_indicatorConstLp_eq_norm {t : Set α} {ht : MeasurableSet t} {hμt : μ t ≠ ∞} :
dist (indicatorConstLp p hs hμs c) (indicatorConstLp p ht hμt c) =
‖indicatorConstLp p (hs.symmDiff ht) (measure_symmDiff_ne_top hμs hμt) c‖ := by
rw [Lp.dist_edist, edist_indicatorConstLp_eq_nnnorm, ENNReal.coe_toReal, Lp.coe_nnnorm]
@[simp]
theorem indicatorConstLp_empty :
indicatorConstLp p MeasurableSet.empty (by simp : μ ∅ ≠ ∞) c = 0 := by
simp only [indicatorConstLp, Set.indicator_empty', Memℒp.toLp_zero]
#align measure_theory.indicator_const_empty MeasureTheory.indicatorConstLp_empty
theorem indicatorConstLp_inj {s t : Set α} (hs : MeasurableSet s) (hsμ : μ s ≠ ∞)
(ht : MeasurableSet t) (htμ : μ t ≠ ∞) {c : E} (hc : c ≠ 0)
(h : indicatorConstLp p hs hsμ c = indicatorConstLp p ht htμ c) : s =ᵐ[μ] t :=
.of_indicator_const hc <|
calc
s.indicator (fun _ ↦ c) =ᵐ[μ] indicatorConstLp p hs hsμ c := indicatorConstLp_coeFn.symm
_ = indicatorConstLp p ht htμ c := by rw [h]
_ =ᵐ[μ] t.indicator (fun _ ↦ c) := indicatorConstLp_coeFn
theorem memℒp_add_of_disjoint {f g : α → E} (h : Disjoint (support f) (support g))
(hf : StronglyMeasurable f) (hg : StronglyMeasurable g) :
Memℒp (f + g) p μ ↔ Memℒp f p μ ∧ Memℒp g p μ := by
borelize E
refine ⟨fun hfg => ⟨?_, ?_⟩, fun h => h.1.add h.2⟩
· rw [← Set.indicator_add_eq_left h]; exact hfg.indicator (measurableSet_support hf.measurable)
· rw [← Set.indicator_add_eq_right h]; exact hfg.indicator (measurableSet_support hg.measurable)
#align measure_theory.mem_ℒp_add_of_disjoint MeasureTheory.memℒp_add_of_disjoint
/-- The indicator of a disjoint union of two sets is the sum of the indicators of the sets. -/
theorem indicatorConstLp_disjoint_union {s t : Set α} (hs : MeasurableSet s) (ht : MeasurableSet t)
(hμs : μ s ≠ ∞) (hμt : μ t ≠ ∞) (hst : s ∩ t = ∅) (c : E) :
indicatorConstLp p (hs.union ht) (measure_union_ne_top hμs hμt) c =
indicatorConstLp p hs hμs c + indicatorConstLp p ht hμt c := by
ext1
refine indicatorConstLp_coeFn.trans (EventuallyEq.trans ?_ (Lp.coeFn_add _ _).symm)
refine
EventuallyEq.trans ?_
(EventuallyEq.add indicatorConstLp_coeFn.symm indicatorConstLp_coeFn.symm)
rw [Set.indicator_union_of_disjoint (Set.disjoint_iff_inter_eq_empty.mpr hst) _]
#align measure_theory.indicator_const_Lp_disjoint_union MeasureTheory.indicatorConstLp_disjoint_union
end IndicatorConstLp
section const
variable (μ p)
variable [IsFiniteMeasure μ] (c : E)
/-- Constant function as an element of `MeasureTheory.Lp` for a finite measure. -/
protected def Lp.const : E →+ Lp E p μ where
toFun c := ⟨AEEqFun.const α c, const_mem_Lp α μ c⟩
map_zero' := rfl
map_add' _ _ := rfl
lemma Lp.coeFn_const : Lp.const p μ c =ᵐ[μ] Function.const α c :=
AEEqFun.coeFn_const α c
@[simp] lemma Lp.const_val : (Lp.const p μ c).1 = AEEqFun.const α c := rfl
@[simp]
lemma Memℒp.toLp_const : Memℒp.toLp _ (memℒp_const c) = Lp.const p μ c := rfl
@[simp]
lemma indicatorConstLp_univ :
indicatorConstLp p .univ (measure_ne_top μ _) c = Lp.const p μ c := by
rw [← Memℒp.toLp_const, indicatorConstLp]
simp only [Set.indicator_univ, Function.const]
theorem Lp.norm_const [NeZero μ] (hp_zero : p ≠ 0) :
‖Lp.const p μ c‖ = ‖c‖ * (μ Set.univ).toReal ^ (1 / p.toReal) := by
have := NeZero.ne μ
rw [← Memℒp.toLp_const, Lp.norm_toLp, snorm_const] <;> try assumption
rw [ENNReal.toReal_mul, ENNReal.coe_toReal, ← ENNReal.toReal_rpow, coe_nnnorm]
theorem Lp.norm_const' (hp_zero : p ≠ 0) (hp_top : p ≠ ∞) :
‖Lp.const p μ c‖ = ‖c‖ * (μ Set.univ).toReal ^ (1 / p.toReal) := by
rw [← Memℒp.toLp_const, Lp.norm_toLp, snorm_const'] <;> try assumption
rw [ENNReal.toReal_mul, ENNReal.coe_toReal, ← ENNReal.toReal_rpow, coe_nnnorm]
theorem Lp.norm_const_le : ‖Lp.const p μ c‖ ≤ ‖c‖ * (μ Set.univ).toReal ^ (1 / p.toReal) := by
rw [← indicatorConstLp_univ]
exact norm_indicatorConstLp_le
/-- `MeasureTheory.Lp.const` as a `LinearMap`. -/
@[simps] protected def Lp.constₗ (𝕜 : Type*) [NormedRing 𝕜] [Module 𝕜 E] [BoundedSMul 𝕜 E] :
E →ₗ[𝕜] Lp E p μ where
toFun := Lp.const p μ
map_add' := map_add _
map_smul' _ _ := rfl
@[simps! apply]
protected def Lp.constL (𝕜 : Type*) [NormedField 𝕜] [NormedSpace 𝕜 E] [Fact (1 ≤ p)] :
E →L[𝕜] Lp E p μ :=
(Lp.constₗ p μ 𝕜).mkContinuous ((μ Set.univ).toReal ^ (1 / p.toReal)) fun _ ↦
(Lp.norm_const_le _ _ _).trans_eq (mul_comm _ _)
theorem Lp.norm_constL_le (𝕜 : Type*) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E]
[Fact (1 ≤ p)] :
‖(Lp.constL p μ 𝕜 : E →L[𝕜] Lp E p μ)‖ ≤ (μ Set.univ).toReal ^ (1 / p.toReal) :=
LinearMap.mkContinuous_norm_le _ (by positivity) _
end const
theorem Memℒp.norm_rpow_div {f : α → E} (hf : Memℒp f p μ) (q : ℝ≥0∞) :
Memℒp (fun x : α => ‖f x‖ ^ q.toReal) (p / q) μ := by
refine ⟨(hf.1.norm.aemeasurable.pow_const q.toReal).aestronglyMeasurable, ?_⟩
by_cases q_top : q = ∞
· simp [q_top]
by_cases q_zero : q = 0
· simp [q_zero]
by_cases p_zero : p = 0
· simp [p_zero]
rw [ENNReal.div_zero p_zero]
exact (memℒp_top_const (1 : ℝ)).2
rw [snorm_norm_rpow _ (ENNReal.toReal_pos q_zero q_top)]
apply ENNReal.rpow_lt_top_of_nonneg ENNReal.toReal_nonneg
rw [ENNReal.ofReal_toReal q_top, div_eq_mul_inv, mul_assoc, ENNReal.inv_mul_cancel q_zero q_top,
mul_one]
exact hf.2.ne
#align measure_theory.mem_ℒp.norm_rpow_div MeasureTheory.Memℒp.norm_rpow_div
theorem memℒp_norm_rpow_iff {q : ℝ≥0∞} {f : α → E} (hf : AEStronglyMeasurable f μ) (q_zero : q ≠ 0)
(q_top : q ≠ ∞) : Memℒp (fun x : α => ‖f x‖ ^ q.toReal) (p / q) μ ↔ Memℒp f p μ := by
refine ⟨fun h => ?_, fun h => h.norm_rpow_div q⟩
apply (memℒp_norm_iff hf).1
convert h.norm_rpow_div q⁻¹ using 1
· ext x
rw [Real.norm_eq_abs, Real.abs_rpow_of_nonneg (norm_nonneg _), ← Real.rpow_mul (abs_nonneg _),
ENNReal.toReal_inv, mul_inv_cancel, abs_of_nonneg (norm_nonneg _), Real.rpow_one]
simp [ENNReal.toReal_eq_zero_iff, not_or, q_zero, q_top]
· rw [div_eq_mul_inv, inv_inv, div_eq_mul_inv, mul_assoc, ENNReal.inv_mul_cancel q_zero q_top,
mul_one]
#align measure_theory.mem_ℒp_norm_rpow_iff MeasureTheory.memℒp_norm_rpow_iff
theorem Memℒp.norm_rpow {f : α → E} (hf : Memℒp f p μ) (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
Memℒp (fun x : α => ‖f x‖ ^ p.toReal) 1 μ := by
convert hf.norm_rpow_div p
rw [div_eq_mul_inv, ENNReal.mul_inv_cancel hp_ne_zero hp_ne_top]
#align measure_theory.mem_ℒp.norm_rpow MeasureTheory.Memℒp.norm_rpow
theorem AEEqFun.compMeasurePreserving_mem_Lp {β : Type*} [MeasurableSpace β]
{μb : MeasureTheory.Measure β} {g : β →ₘ[μb] E} (hg : g ∈ Lp E p μb) {f : α → β}
(hf : MeasurePreserving f μ μb) :
g.compMeasurePreserving f hf ∈ Lp E p μ := by
rw [Lp.mem_Lp_iff_snorm_lt_top] at hg ⊢
rwa [snorm_compMeasurePreserving]
namespace Lp
/-! ### Composition with a measure preserving function -/
variable {β : Type*} [MeasurableSpace β] {μb : MeasureTheory.Measure β} {f : α → β}
/-- Composition of an `L^p` function with a measure preserving function is an `L^p` function. -/
def compMeasurePreserving (f : α → β) (hf : MeasurePreserving f μ μb) :
Lp E p μb →+ Lp E p μ where
toFun g := ⟨g.1.compMeasurePreserving f hf, g.1.compMeasurePreserving_mem_Lp g.2 hf⟩
map_zero' := rfl
map_add' := by rintro ⟨⟨_⟩, _⟩ ⟨⟨_⟩, _⟩; rfl
@[simp]
theorem compMeasurePreserving_val (g : Lp E p μb) (hf : MeasurePreserving f μ μb) :
(compMeasurePreserving f hf g).1 = g.1.compMeasurePreserving f hf :=
rfl
theorem coeFn_compMeasurePreserving (g : Lp E p μb) (hf : MeasurePreserving f μ μb) :
compMeasurePreserving f hf g =ᵐ[μ] g ∘ f :=
g.1.coeFn_compMeasurePreserving hf
@[simp]
theorem norm_compMeasurePreserving (g : Lp E p μb) (hf : MeasurePreserving f μ μb) :
‖compMeasurePreserving f hf g‖ = ‖g‖ :=
congr_arg ENNReal.toReal <| g.1.snorm_compMeasurePreserving hf
variable (𝕜 : Type*) [NormedRing 𝕜] [Module 𝕜 E] [BoundedSMul 𝕜 E]
/-- `MeasureTheory.Lp.compMeasurePreserving` as a linear map. -/
@[simps]
def compMeasurePreservingₗ (f : α → β) (hf : MeasurePreserving f μ μb) :
Lp E p μb →ₗ[𝕜] Lp E p μ where
__ := compMeasurePreserving f hf
map_smul' c g := by rcases g with ⟨⟨_⟩, _⟩; rfl
/-- `MeasureTheory.Lp.compMeasurePreserving` as a linear isometry. -/
@[simps!]
def compMeasurePreservingₗᵢ [Fact (1 ≤ p)] (f : α → β) (hf : MeasurePreserving f μ μb) :
Lp E p μb →ₗᵢ[𝕜] Lp E p μ where
toLinearMap := compMeasurePreservingₗ 𝕜 f hf
norm_map' := (norm_compMeasurePreserving · hf)
end Lp
end MeasureTheory
open MeasureTheory
/-!
### Composition on `L^p`
We show that Lipschitz functions vanishing at zero act by composition on `L^p`, and specialize
this to the composition with continuous linear maps, and to the definition of the positive
part of an `L^p` function.
-/
section Composition
variable {g : E → F} {c : ℝ≥0}
theorem LipschitzWith.comp_memℒp {α E F} {K} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] {f : α → E} {g : E → F} (hg : LipschitzWith K g)
(g0 : g 0 = 0) (hL : Memℒp f p μ) : Memℒp (g ∘ f) p μ :=
have : ∀ x, ‖g (f x)‖ ≤ K * ‖f x‖ := fun x ↦ by
-- TODO: add `LipschitzWith.nnnorm_sub_le` and `LipschitzWith.nnnorm_le`
simpa [g0] using hg.norm_sub_le (f x) 0
hL.of_le_mul (hg.continuous.comp_aestronglyMeasurable hL.1) (eventually_of_forall this)
#align lipschitz_with.comp_mem_ℒp LipschitzWith.comp_memℒp
theorem MeasureTheory.Memℒp.of_comp_antilipschitzWith {α E F} {K'} [MeasurableSpace α]
{μ : Measure α} [NormedAddCommGroup E] [NormedAddCommGroup F] {f : α → E} {g : E → F}
(hL : Memℒp (g ∘ f) p μ) (hg : UniformContinuous g) (hg' : AntilipschitzWith K' g)
(g0 : g 0 = 0) : Memℒp f p μ := by
have A : ∀ x, ‖f x‖ ≤ K' * ‖g (f x)‖ := by
intro x
-- TODO: add `AntilipschitzWith.le_mul_nnnorm_sub` and `AntilipschitzWith.le_mul_norm`
rw [← dist_zero_right, ← dist_zero_right, ← g0]
apply hg'.le_mul_dist
have B : AEStronglyMeasurable f μ :=
(hg'.uniformEmbedding hg).embedding.aestronglyMeasurable_comp_iff.1 hL.1
exact hL.of_le_mul B (Filter.eventually_of_forall A)
#align measure_theory.mem_ℒp.of_comp_antilipschitz_with MeasureTheory.Memℒp.of_comp_antilipschitzWith
namespace LipschitzWith
theorem memℒp_comp_iff_of_antilipschitz {α E F} {K K'} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] {f : α → E} {g : E → F} (hg : LipschitzWith K g)
(hg' : AntilipschitzWith K' g) (g0 : g 0 = 0) : Memℒp (g ∘ f) p μ ↔ Memℒp f p μ :=
⟨fun h => h.of_comp_antilipschitzWith hg.uniformContinuous hg' g0, fun h => hg.comp_memℒp g0 h⟩
#align lipschitz_with.mem_ℒp_comp_iff_of_antilipschitz LipschitzWith.memℒp_comp_iff_of_antilipschitz
/-- When `g` is a Lipschitz function sending `0` to `0` and `f` is in `Lp`, then `g ∘ f` is well
defined as an element of `Lp`. -/
def compLp (hg : LipschitzWith c g) (g0 : g 0 = 0) (f : Lp E p μ) : Lp F p μ :=
⟨AEEqFun.comp g hg.continuous (f : α →ₘ[μ] E), by
suffices ∀ᵐ x ∂μ, ‖AEEqFun.comp g hg.continuous (f : α →ₘ[μ] E) x‖ ≤ c * ‖f x‖ from
Lp.mem_Lp_of_ae_le_mul this
filter_upwards [AEEqFun.coeFn_comp g hg.continuous (f : α →ₘ[μ] E)] with a ha
simp only [ha]
rw [← dist_zero_right, ← dist_zero_right, ← g0]
exact hg.dist_le_mul (f a) 0⟩
#align lipschitz_with.comp_Lp LipschitzWith.compLp
theorem coeFn_compLp (hg : LipschitzWith c g) (g0 : g 0 = 0) (f : Lp E p μ) :
hg.compLp g0 f =ᵐ[μ] g ∘ f :=
AEEqFun.coeFn_comp _ hg.continuous _
#align lipschitz_with.coe_fn_comp_Lp LipschitzWith.coeFn_compLp
@[simp]
theorem compLp_zero (hg : LipschitzWith c g) (g0 : g 0 = 0) : hg.compLp g0 (0 : Lp E p μ) = 0 := by
rw [Lp.eq_zero_iff_ae_eq_zero]
apply (coeFn_compLp _ _ _).trans
filter_upwards [Lp.coeFn_zero E p μ] with _ ha
simp only [ha, g0, Function.comp_apply, Pi.zero_apply]
#align lipschitz_with.comp_Lp_zero LipschitzWith.compLp_zero
theorem norm_compLp_sub_le (hg : LipschitzWith c g) (g0 : g 0 = 0) (f f' : Lp E p μ) :
‖hg.compLp g0 f - hg.compLp g0 f'‖ ≤ c * ‖f - f'‖ := by
apply Lp.norm_le_mul_norm_of_ae_le_mul
filter_upwards [hg.coeFn_compLp g0 f, hg.coeFn_compLp g0 f',
Lp.coeFn_sub (hg.compLp g0 f) (hg.compLp g0 f'), Lp.coeFn_sub f f'] with a ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, ← dist_eq_norm, Pi.sub_apply, Function.comp_apply]
exact hg.dist_le_mul (f a) (f' a)
#align lipschitz_with.norm_comp_Lp_sub_le LipschitzWith.norm_compLp_sub_le
theorem norm_compLp_le (hg : LipschitzWith c g) (g0 : g 0 = 0) (f : Lp E p μ) :
‖hg.compLp g0 f‖ ≤ c * ‖f‖ := by simpa using hg.norm_compLp_sub_le g0 f 0
#align lipschitz_with.norm_comp_Lp_le LipschitzWith.norm_compLp_le
theorem lipschitzWith_compLp [Fact (1 ≤ p)] (hg : LipschitzWith c g) (g0 : g 0 = 0) :
LipschitzWith c (hg.compLp g0 : Lp E p μ → Lp F p μ) :=
LipschitzWith.of_dist_le_mul fun f g => by simp [dist_eq_norm, norm_compLp_sub_le]
#align lipschitz_with.lipschitz_with_comp_Lp LipschitzWith.lipschitzWith_compLp
theorem continuous_compLp [Fact (1 ≤ p)] (hg : LipschitzWith c g) (g0 : g 0 = 0) :
Continuous (hg.compLp g0 : Lp E p μ → Lp F p μ) :=
(lipschitzWith_compLp hg g0).continuous
#align lipschitz_with.continuous_comp_Lp LipschitzWith.continuous_compLp
end LipschitzWith
namespace ContinuousLinearMap
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F]
/-- Composing `f : Lp` with `L : E →L[𝕜] F`. -/
def compLp (L : E →L[𝕜] F) (f : Lp E p μ) : Lp F p μ :=
L.lipschitz.compLp (map_zero L) f
#align continuous_linear_map.comp_Lp ContinuousLinearMap.compLp
theorem coeFn_compLp (L : E →L[𝕜] F) (f : Lp E p μ) : ∀ᵐ a ∂μ, (L.compLp f) a = L (f a) :=
LipschitzWith.coeFn_compLp _ _ _
#align continuous_linear_map.coe_fn_comp_Lp ContinuousLinearMap.coeFn_compLp
theorem coeFn_compLp' (L : E →L[𝕜] F) (f : Lp E p μ) : L.compLp f =ᵐ[μ] fun a => L (f a) :=
L.coeFn_compLp f
#align continuous_linear_map.coe_fn_comp_Lp' ContinuousLinearMap.coeFn_compLp'
theorem comp_memℒp (L : E →L[𝕜] F) (f : Lp E p μ) : Memℒp (L ∘ f) p μ :=
(Lp.memℒp (L.compLp f)).ae_eq (L.coeFn_compLp' f)
#align continuous_linear_map.comp_mem_ℒp ContinuousLinearMap.comp_memℒp
theorem comp_memℒp' (L : E →L[𝕜] F) {f : α → E} (hf : Memℒp f p μ) : Memℒp (L ∘ f) p μ :=
(L.comp_memℒp (hf.toLp f)).ae_eq (EventuallyEq.fun_comp hf.coeFn_toLp _)
#align continuous_linear_map.comp_mem_ℒp' ContinuousLinearMap.comp_memℒp'
section RCLike
variable {K : Type*} [RCLike K]
theorem _root_.MeasureTheory.Memℒp.ofReal {f : α → ℝ} (hf : Memℒp f p μ) :
Memℒp (fun x => (f x : K)) p μ :=
(@RCLike.ofRealCLM K _).comp_memℒp' hf
#align measure_theory.mem_ℒp.of_real MeasureTheory.Memℒp.ofReal
theorem _root_.MeasureTheory.memℒp_re_im_iff {f : α → K} :
Memℒp (fun x ↦ RCLike.re (f x)) p μ ∧ Memℒp (fun x ↦ RCLike.im (f x)) p μ ↔
Memℒp f p μ := by
refine ⟨?_, fun hf => ⟨hf.re, hf.im⟩⟩
rintro ⟨hre, him⟩
convert MeasureTheory.Memℒp.add (E := K) hre.ofReal (him.ofReal.const_mul RCLike.I)
ext1 x
rw [Pi.add_apply, mul_comm, RCLike.re_add_im]
#align measure_theory.mem_ℒp_re_im_iff MeasureTheory.memℒp_re_im_iff
end RCLike
theorem add_compLp (L L' : E →L[𝕜] F) (f : Lp E p μ) :
(L + L').compLp f = L.compLp f + L'.compLp f := by
ext1
refine (coeFn_compLp' (L + L') f).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_add _ _).symm
refine
EventuallyEq.trans ?_ (EventuallyEq.add (L.coeFn_compLp' f).symm (L'.coeFn_compLp' f).symm)
filter_upwards with x
rw [coe_add', Pi.add_def]
#align continuous_linear_map.add_comp_Lp ContinuousLinearMap.add_compLp
theorem smul_compLp {𝕜'} [NormedRing 𝕜'] [Module 𝕜' F] [BoundedSMul 𝕜' F] [SMulCommClass 𝕜 𝕜' F]
(c : 𝕜') (L : E →L[𝕜] F) (f : Lp E p μ) : (c • L).compLp f = c • L.compLp f := by
ext1
refine (coeFn_compLp' (c • L) f).trans ?_
refine EventuallyEq.trans ?_ (Lp.coeFn_smul _ _).symm
refine (L.coeFn_compLp' f).mono fun x hx => ?_
rw [Pi.smul_apply, hx, coe_smul', Pi.smul_def]
#align continuous_linear_map.smul_comp_Lp ContinuousLinearMap.smul_compLp
theorem norm_compLp_le (L : E →L[𝕜] F) (f : Lp E p μ) : ‖L.compLp f‖ ≤ ‖L‖ * ‖f‖ :=
LipschitzWith.norm_compLp_le _ _ _
#align continuous_linear_map.norm_comp_Lp_le ContinuousLinearMap.norm_compLp_le
variable (μ p)
/-- Composing `f : Lp E p μ` with `L : E →L[𝕜] F`, seen as a `𝕜`-linear map on `Lp E p μ`. -/
def compLpₗ (L : E →L[𝕜] F) : Lp E p μ →ₗ[𝕜] Lp F p μ where
toFun f := L.compLp f
map_add' f g := by
ext1
filter_upwards [Lp.coeFn_add f g, coeFn_compLp L (f + g), coeFn_compLp L f,
coeFn_compLp L g, Lp.coeFn_add (L.compLp f) (L.compLp g)]
intro a ha1 ha2 ha3 ha4 ha5
simp only [ha1, ha2, ha3, ha4, ha5, map_add, Pi.add_apply]
map_smul' c f := by
dsimp
ext1
filter_upwards [Lp.coeFn_smul c f, coeFn_compLp L (c • f), Lp.coeFn_smul c (L.compLp f),
coeFn_compLp L f] with _ ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, map_smul, Pi.smul_apply]
#align continuous_linear_map.comp_Lpₗ ContinuousLinearMap.compLpₗ
/-- Composing `f : Lp E p μ` with `L : E →L[𝕜] F`, seen as a continuous `𝕜`-linear map on
`Lp E p μ`. See also the similar
* `LinearMap.compLeft` for functions,
* `ContinuousLinearMap.compLeftContinuous` for continuous functions,
* `ContinuousLinearMap.compLeftContinuousBounded` for bounded continuous functions,
* `ContinuousLinearMap.compLeftContinuousCompact` for continuous functions on compact spaces.
-/
def compLpL [Fact (1 ≤ p)] (L : E →L[𝕜] F) : Lp E p μ →L[𝕜] Lp F p μ :=
LinearMap.mkContinuous (L.compLpₗ p μ) ‖L‖ L.norm_compLp_le
#align continuous_linear_map.comp_LpL ContinuousLinearMap.compLpL
variable {μ p}
theorem coeFn_compLpL [Fact (1 ≤ p)] (L : E →L[𝕜] F) (f : Lp E p μ) :
L.compLpL p μ f =ᵐ[μ] fun a => L (f a) :=
L.coeFn_compLp f
#align continuous_linear_map.coe_fn_comp_LpL ContinuousLinearMap.coeFn_compLpL
theorem add_compLpL [Fact (1 ≤ p)] (L L' : E →L[𝕜] F) :
(L + L').compLpL p μ = L.compLpL p μ + L'.compLpL p μ := by ext1 f; exact add_compLp L L' f
#align continuous_linear_map.add_comp_LpL ContinuousLinearMap.add_compLpL
theorem smul_compLpL [Fact (1 ≤ p)] {𝕜'} [NormedRing 𝕜'] [Module 𝕜' F] [BoundedSMul 𝕜' F]
[SMulCommClass 𝕜 𝕜' F] (c : 𝕜') (L : E →L[𝕜] F) : (c • L).compLpL p μ = c • L.compLpL p μ := by
ext1 f; exact smul_compLp c L f
#align continuous_linear_map.smul_comp_LpL ContinuousLinearMap.smul_compLpL
theorem norm_compLpL_le [Fact (1 ≤ p)] (L : E →L[𝕜] F) : ‖L.compLpL p μ‖ ≤ ‖L‖ :=
LinearMap.mkContinuous_norm_le _ (norm_nonneg _) _
#align continuous_linear_map.norm_compLpL_le ContinuousLinearMap.norm_compLpL_le
end ContinuousLinearMap
namespace MeasureTheory
theorem indicatorConstLp_eq_toSpanSingleton_compLp {s : Set α} [NormedSpace ℝ F]
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : F) :
indicatorConstLp 2 hs hμs x =
(ContinuousLinearMap.toSpanSingleton ℝ x).compLp (indicatorConstLp 2 hs hμs (1 : ℝ)) := by
ext1
refine indicatorConstLp_coeFn.trans ?_
have h_compLp :=
(ContinuousLinearMap.toSpanSingleton ℝ x).coeFn_compLp (indicatorConstLp 2 hs hμs (1 : ℝ))
rw [← EventuallyEq] at h_compLp
refine EventuallyEq.trans ?_ h_compLp.symm
refine (@indicatorConstLp_coeFn _ _ _ 2 μ _ s hs hμs (1 : ℝ)).mono fun y hy => ?_
dsimp only
rw [hy]
simp_rw [ContinuousLinearMap.toSpanSingleton_apply]
by_cases hy_mem : y ∈ s <;> simp [hy_mem, ContinuousLinearMap.lsmul_apply]
#align measure_theory.indicator_const_Lp_eq_to_span_singleton_comp_Lp MeasureTheory.indicatorConstLp_eq_toSpanSingleton_compLp
namespace Lp
section PosPart
theorem lipschitzWith_pos_part : LipschitzWith 1 fun x : ℝ => max x 0 :=
LipschitzWith.of_dist_le_mul fun x y => by simp [Real.dist_eq, abs_max_sub_max_le_abs]
#align measure_theory.Lp.lipschitz_with_pos_part MeasureTheory.Lp.lipschitzWith_pos_part
theorem _root_.MeasureTheory.Memℒp.pos_part {f : α → ℝ} (hf : Memℒp f p μ) :
Memℒp (fun x => max (f x) 0) p μ :=
lipschitzWith_pos_part.comp_memℒp (max_eq_right le_rfl) hf
#align measure_theory.mem_ℒp.pos_part MeasureTheory.Memℒp.pos_part
theorem _root_.MeasureTheory.Memℒp.neg_part {f : α → ℝ} (hf : Memℒp f p μ) :
Memℒp (fun x => max (-f x) 0) p μ :=
lipschitzWith_pos_part.comp_memℒp (max_eq_right le_rfl) hf.neg
#align measure_theory.mem_ℒp.neg_part MeasureTheory.Memℒp.neg_part
/-- Positive part of a function in `L^p`. -/
def posPart (f : Lp ℝ p μ) : Lp ℝ p μ :=
lipschitzWith_pos_part.compLp (max_eq_right le_rfl) f
#align measure_theory.Lp.pos_part MeasureTheory.Lp.posPart
/-- Negative part of a function in `L^p`. -/
def negPart (f : Lp ℝ p μ) : Lp ℝ p μ :=
posPart (-f)
#align measure_theory.Lp.neg_part MeasureTheory.Lp.negPart
@[norm_cast]
theorem coe_posPart (f : Lp ℝ p μ) : (posPart f : α →ₘ[μ] ℝ) = (f : α →ₘ[μ] ℝ).posPart :=
rfl
#align measure_theory.Lp.coe_pos_part MeasureTheory.Lp.coe_posPart
theorem coeFn_posPart (f : Lp ℝ p μ) : ⇑(posPart f) =ᵐ[μ] fun a => max (f a) 0 :=
AEEqFun.coeFn_posPart _
#align measure_theory.Lp.coe_fn_pos_part MeasureTheory.Lp.coeFn_posPart
theorem coeFn_negPart_eq_max (f : Lp ℝ p μ) : ∀ᵐ a ∂μ, negPart f a = max (-f a) 0 := by
rw [negPart]
filter_upwards [coeFn_posPart (-f), coeFn_neg f] with _ h₁ h₂
rw [h₁, h₂, Pi.neg_apply]
#align measure_theory.Lp.coe_fn_neg_part_eq_max MeasureTheory.Lp.coeFn_negPart_eq_max
theorem coeFn_negPart (f : Lp ℝ p μ) : ∀ᵐ a ∂μ, negPart f a = -min (f a) 0 :=
(coeFn_negPart_eq_max f).mono fun a h => by rw [h, ← max_neg_neg, neg_zero]
#align measure_theory.Lp.coe_fn_neg_part MeasureTheory.Lp.coeFn_negPart
theorem continuous_posPart [Fact (1 ≤ p)] : Continuous fun f : Lp ℝ p μ => posPart f :=
LipschitzWith.continuous_compLp _ _
#align measure_theory.Lp.continuous_pos_part MeasureTheory.Lp.continuous_posPart
theorem continuous_negPart [Fact (1 ≤ p)] : Continuous fun f : Lp ℝ p μ => negPart f := by
unfold negPart
exact continuous_posPart.comp continuous_neg
#align measure_theory.Lp.continuous_neg_part MeasureTheory.Lp.continuous_negPart
end PosPart
end Lp
end MeasureTheory
end Composition
/-!
## `L^p` is a complete space
We show that `L^p` is a complete space for `1 ≤ p`.
-/
section CompleteSpace
namespace MeasureTheory
namespace Lp
theorem snorm'_lim_eq_lintegral_liminf {ι} [Nonempty ι] [LinearOrder ι] {f : ι → α → G} {p : ℝ}
(hp_nonneg : 0 ≤ p) {f_lim : α → G}
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm' f_lim p μ = (∫⁻ a, atTop.liminf fun m => (‖f m a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) := by
suffices h_no_pow :
(∫⁻ a, (‖f_lim a‖₊ : ℝ≥0∞) ^ p ∂μ) = ∫⁻ a, atTop.liminf fun m => (‖f m a‖₊ : ℝ≥0∞) ^ p ∂μ by
rw [snorm', h_no_pow]
refine lintegral_congr_ae (h_lim.mono fun a ha => ?_)
dsimp only
rw [Tendsto.liminf_eq]
simp_rw [ENNReal.coe_rpow_of_nonneg _ hp_nonneg, ENNReal.tendsto_coe]
refine ((NNReal.continuous_rpow_const hp_nonneg).tendsto ‖f_lim a‖₊).comp ?_
exact (continuous_nnnorm.tendsto (f_lim a)).comp ha
#align measure_theory.Lp.snorm'_lim_eq_lintegral_liminf MeasureTheory.Lp.snorm'_lim_eq_lintegral_liminf
theorem snorm'_lim_le_liminf_snorm' {E} [NormedAddCommGroup E] {f : ℕ → α → E} {p : ℝ}
(hp_pos : 0 < p) (hf : ∀ n, AEStronglyMeasurable (f n) μ) {f_lim : α → E}
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm' f_lim p μ ≤ atTop.liminf fun n => snorm' (f n) p μ := by
rw [snorm'_lim_eq_lintegral_liminf hp_pos.le h_lim]
rw [← ENNReal.le_rpow_one_div_iff (by simp [hp_pos] : 0 < 1 / p), one_div_one_div]
refine (lintegral_liminf_le' fun m => (hf m).ennnorm.pow_const _).trans_eq ?_
have h_pow_liminf :
(atTop.liminf fun n => snorm' (f n) p μ) ^ p = atTop.liminf fun n => snorm' (f n) p μ ^ p := by
have h_rpow_mono := ENNReal.strictMono_rpow_of_pos hp_pos
have h_rpow_surj := (ENNReal.rpow_left_bijective hp_pos.ne.symm).2
refine (h_rpow_mono.orderIsoOfSurjective _ h_rpow_surj).liminf_apply ?_ ?_ ?_ ?_
all_goals isBoundedDefault
rw [h_pow_liminf]
simp_rw [snorm', ← ENNReal.rpow_mul, one_div, inv_mul_cancel hp_pos.ne.symm, ENNReal.rpow_one]
#align measure_theory.Lp.snorm'_lim_le_liminf_snorm' MeasureTheory.Lp.snorm'_lim_le_liminf_snorm'
theorem snorm_exponent_top_lim_eq_essSup_liminf {ι} [Nonempty ι] [LinearOrder ι] {f : ι → α → G}
{f_lim : α → G} (h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm f_lim ∞ μ = essSup (fun x => atTop.liminf fun m => (‖f m x‖₊ : ℝ≥0∞)) μ := by
rw [snorm_exponent_top, snormEssSup]
refine essSup_congr_ae (h_lim.mono fun x hx => ?_)
dsimp only
apply (Tendsto.liminf_eq ..).symm
rw [ENNReal.tendsto_coe]
exact (continuous_nnnorm.tendsto (f_lim x)).comp hx
#align measure_theory.Lp.snorm_exponent_top_lim_eq_ess_sup_liminf MeasureTheory.Lp.snorm_exponent_top_lim_eq_essSup_liminf
theorem snorm_exponent_top_lim_le_liminf_snorm_exponent_top {ι} [Nonempty ι] [Countable ι]
[LinearOrder ι] {f : ι → α → F} {f_lim : α → F}
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm f_lim ∞ μ ≤ atTop.liminf fun n => snorm (f n) ∞ μ := by
rw [snorm_exponent_top_lim_eq_essSup_liminf h_lim]
simp_rw [snorm_exponent_top, snormEssSup]
exact ENNReal.essSup_liminf_le fun n => fun x => (‖f n x‖₊ : ℝ≥0∞)
#align measure_theory.Lp.snorm_exponent_top_lim_le_liminf_snorm_exponent_top MeasureTheory.Lp.snorm_exponent_top_lim_le_liminf_snorm_exponent_top
theorem snorm_lim_le_liminf_snorm {E} [NormedAddCommGroup E] {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) (f_lim : α → E)
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
snorm f_lim p μ ≤ atTop.liminf fun n => snorm (f n) p μ := by
obtain rfl|hp0 := eq_or_ne p 0
· simp
by_cases hp_top : p = ∞
· simp_rw [hp_top]
exact snorm_exponent_top_lim_le_liminf_snorm_exponent_top h_lim
simp_rw [snorm_eq_snorm' hp0 hp_top]
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0 hp_top
exact snorm'_lim_le_liminf_snorm' hp_pos hf h_lim
#align measure_theory.Lp.snorm_lim_le_liminf_snorm MeasureTheory.Lp.snorm_lim_le_liminf_snorm
/-! ### `Lp` is complete iff Cauchy sequences of `ℒp` have limits in `ℒp` -/
theorem tendsto_Lp_iff_tendsto_ℒp' {ι} {fi : Filter ι} [Fact (1 ≤ p)] (f : ι → Lp E p μ)
(f_lim : Lp E p μ) :
fi.Tendsto f (𝓝 f_lim) ↔ fi.Tendsto (fun n => snorm (⇑(f n) - ⇑f_lim) p μ) (𝓝 0) := by
rw [tendsto_iff_dist_tendsto_zero]
simp_rw [dist_def]
rw [← ENNReal.zero_toReal, ENNReal.tendsto_toReal_iff (fun n => ?_) ENNReal.zero_ne_top]
rw [snorm_congr_ae (Lp.coeFn_sub _ _).symm]
exact Lp.snorm_ne_top _
#align measure_theory.Lp.tendsto_Lp_iff_tendsto_ℒp' MeasureTheory.Lp.tendsto_Lp_iff_tendsto_ℒp'
theorem tendsto_Lp_iff_tendsto_ℒp {ι} {fi : Filter ι} [Fact (1 ≤ p)] (f : ι → Lp E p μ)
(f_lim : α → E) (f_lim_ℒp : Memℒp f_lim p μ) :
fi.Tendsto f (𝓝 (f_lim_ℒp.toLp f_lim)) ↔
fi.Tendsto (fun n => snorm (⇑(f n) - f_lim) p μ) (𝓝 0) := by
rw [tendsto_Lp_iff_tendsto_ℒp']
suffices h_eq :
(fun n => snorm (⇑(f n) - ⇑(Memℒp.toLp f_lim f_lim_ℒp)) p μ) =
(fun n => snorm (⇑(f n) - f_lim) p μ) by
rw [h_eq]
exact funext fun n => snorm_congr_ae (EventuallyEq.rfl.sub (Memℒp.coeFn_toLp f_lim_ℒp))
#align measure_theory.Lp.tendsto_Lp_iff_tendsto_ℒp MeasureTheory.Lp.tendsto_Lp_iff_tendsto_ℒp
theorem tendsto_Lp_iff_tendsto_ℒp'' {ι} {fi : Filter ι} [Fact (1 ≤ p)] (f : ι → α → E)
(f_ℒp : ∀ n, Memℒp (f n) p μ) (f_lim : α → E) (f_lim_ℒp : Memℒp f_lim p μ) :
fi.Tendsto (fun n => (f_ℒp n).toLp (f n)) (𝓝 (f_lim_ℒp.toLp f_lim)) ↔
fi.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0) := by
rw [Lp.tendsto_Lp_iff_tendsto_ℒp' (fun n => (f_ℒp n).toLp (f n)) (f_lim_ℒp.toLp f_lim)]
refine Filter.tendsto_congr fun n => ?_
apply snorm_congr_ae
filter_upwards [((f_ℒp n).sub f_lim_ℒp).coeFn_toLp,
Lp.coeFn_sub ((f_ℒp n).toLp (f n)) (f_lim_ℒp.toLp f_lim)] with _ hx₁ hx₂
rw [← hx₂]
exact hx₁
#align measure_theory.Lp.tendsto_Lp_iff_tendsto_ℒp'' MeasureTheory.Lp.tendsto_Lp_iff_tendsto_ℒp''
theorem tendsto_Lp_of_tendsto_ℒp {ι} {fi : Filter ι} [Fact (1 ≤ p)] {f : ι → Lp E p μ}
(f_lim : α → E) (f_lim_ℒp : Memℒp f_lim p μ)
(h_tendsto : fi.Tendsto (fun n => snorm (⇑(f n) - f_lim) p μ) (𝓝 0)) :
fi.Tendsto f (𝓝 (f_lim_ℒp.toLp f_lim)) :=
(tendsto_Lp_iff_tendsto_ℒp f f_lim f_lim_ℒp).mpr h_tendsto
#align measure_theory.Lp.tendsto_Lp_of_tendsto_ℒp MeasureTheory.Lp.tendsto_Lp_of_tendsto_ℒp
theorem cauchySeq_Lp_iff_cauchySeq_ℒp {ι} [Nonempty ι] [SemilatticeSup ι] [hp : Fact (1 ≤ p)]
(f : ι → Lp E p μ) :
CauchySeq f ↔ Tendsto (fun n : ι × ι => snorm (⇑(f n.fst) - ⇑(f n.snd)) p μ) atTop (𝓝 0) := by
simp_rw [cauchySeq_iff_tendsto_dist_atTop_0, dist_def]
rw [← ENNReal.zero_toReal, ENNReal.tendsto_toReal_iff (fun n => ?_) ENNReal.zero_ne_top]
rw [snorm_congr_ae (Lp.coeFn_sub _ _).symm]
exact snorm_ne_top _
#align measure_theory.Lp.cauchy_seq_Lp_iff_cauchy_seq_ℒp MeasureTheory.Lp.cauchySeq_Lp_iff_cauchySeq_ℒp
theorem completeSpace_lp_of_cauchy_complete_ℒp [hp : Fact (1 ≤ p)]
(H :
∀ (f : ℕ → α → E) (hf : ∀ n, Memℒp (f n) p μ) (B : ℕ → ℝ≥0∞) (hB : ∑' i, B i < ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N),
∃ (f_lim : α → E), Memℒp f_lim p μ ∧
atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0)) :
CompleteSpace (Lp E p μ) := by
let B := fun n : ℕ => ((1 : ℝ) / 2) ^ n
have hB_pos : ∀ n, 0 < B n := fun n => pow_pos (div_pos zero_lt_one zero_lt_two) n
refine Metric.complete_of_convergent_controlled_sequences B hB_pos fun f hf => ?_
rsuffices ⟨f_lim, hf_lim_meas, h_tendsto⟩ :
∃ (f_lim : α → E), Memℒp f_lim p μ ∧
atTop.Tendsto (fun n => snorm (⇑(f n) - f_lim) p μ) (𝓝 0)
· exact ⟨hf_lim_meas.toLp f_lim, tendsto_Lp_of_tendsto_ℒp f_lim hf_lim_meas h_tendsto⟩
obtain ⟨M, hB⟩ : Summable B := summable_geometric_two
let B1 n := ENNReal.ofReal (B n)
have hB1_has : HasSum B1 (ENNReal.ofReal M) := by
have h_tsum_B1 : ∑' i, B1 i = ENNReal.ofReal M := by
change (∑' n : ℕ, ENNReal.ofReal (B n)) = ENNReal.ofReal M
rw [← hB.tsum_eq]
exact (ENNReal.ofReal_tsum_of_nonneg (fun n => le_of_lt (hB_pos n)) hB.summable).symm
have h_sum := (@ENNReal.summable _ B1).hasSum
rwa [h_tsum_B1] at h_sum
have hB1 : ∑' i, B1 i < ∞ := by
rw [hB1_has.tsum_eq]
exact ENNReal.ofReal_lt_top
let f1 : ℕ → α → E := fun n => f n
refine H f1 (fun n => Lp.memℒp (f n)) B1 hB1 fun N n m hn hm => ?_
specialize hf N n m hn hm
rw [dist_def] at hf
dsimp only [f1]
rwa [ENNReal.lt_ofReal_iff_toReal_lt]
rw [snorm_congr_ae (Lp.coeFn_sub _ _).symm]
exact Lp.snorm_ne_top _
#align measure_theory.Lp.complete_space_Lp_of_cauchy_complete_ℒp MeasureTheory.Lp.completeSpace_lp_of_cauchy_complete_ℒp
/-! ### Prove that controlled Cauchy sequences of `ℒp` have limits in `ℒp` -/
private theorem snorm'_sum_norm_sub_le_tsum_of_cauchy_snorm' {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) {p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞}
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm' (f n - f m) p μ < B N) (n : ℕ) :
snorm' (fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) p μ ≤ ∑' i, B i := by
let f_norm_diff i x := ‖f (i + 1) x - f i x‖
have hgf_norm_diff :
∀ n,
(fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) =
∑ i ∈ Finset.range (n + 1), f_norm_diff i :=
fun n => funext fun x => by simp
rw [hgf_norm_diff]
refine (snorm'_sum_le (fun i _ => ((hf (i + 1)).sub (hf i)).norm) hp1).trans ?_
simp_rw [snorm'_norm]
refine (Finset.sum_le_sum ?_).trans (sum_le_tsum _ (fun m _ => zero_le _) ENNReal.summable)
exact fun m _ => (h_cau m (m + 1) m (Nat.le_succ m) (le_refl m)).le
private theorem lintegral_rpow_sum_coe_nnnorm_sub_le_rpow_tsum
{f : ℕ → α → E} {p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞} (n : ℕ)
(hn : snorm' (fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) p μ ≤ ∑' i, B i) :
(∫⁻ a, (∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤
(∑' i, B i) ^ p := by
have hp_pos : 0 < p := zero_lt_one.trans_le hp1
rw [← one_div_one_div p, @ENNReal.le_rpow_one_div_iff _ _ (1 / p) (by simp [hp_pos]),
one_div_one_div p]
simp_rw [snorm'] at hn
have h_nnnorm_nonneg :
(fun a => (‖∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖‖₊ : ℝ≥0∞) ^ p) = fun a =>
(∑ i ∈ Finset.range (n + 1), (‖f (i + 1) a - f i a‖₊ : ℝ≥0∞)) ^ p := by
ext1 a
congr
simp_rw [← ofReal_norm_eq_coe_nnnorm]
rw [← ENNReal.ofReal_sum_of_nonneg]
· rw [Real.norm_of_nonneg _]
exact Finset.sum_nonneg fun x _ => norm_nonneg _
· exact fun x _ => norm_nonneg _
change
(∫⁻ a, (fun x => ↑‖∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖‖₊ ^ p) a ∂μ) ^ (1 / p) ≤
∑' i, B i at hn
rwa [h_nnnorm_nonneg] at hn
private theorem lintegral_rpow_tsum_coe_nnnorm_sub_le_tsum {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) {p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞}
(h :
∀ n,
(∫⁻ a, (∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤
(∑' i, B i) ^ p) :
(∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) ≤ ∑' i, B i := by
have hp_pos : 0 < p := zero_lt_one.trans_le hp1
suffices h_pow : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤ (∑' i, B i) ^ p by
rwa [← ENNReal.le_rpow_one_div_iff (by simp [hp_pos] : 0 < 1 / p), one_div_one_div]
have h_tsum_1 :
∀ g : ℕ → ℝ≥0∞, ∑' i, g i = atTop.liminf fun n => ∑ i ∈ Finset.range (n + 1), g i := by
intro g
rw [ENNReal.tsum_eq_liminf_sum_nat, ← liminf_nat_add _ 1]
simp_rw [h_tsum_1 _]
rw [← h_tsum_1]
have h_liminf_pow :
(∫⁻ a, (atTop.liminf
fun n => ∑ i ∈ Finset.range (n + 1), (‖f (i + 1) a - f i a‖₊ : ℝ≥0∞)) ^ p ∂μ) =
∫⁻ a, atTop.liminf
fun n => (∑ i ∈ Finset.range (n + 1), (‖f (i + 1) a - f i a‖₊ : ℝ≥0∞)) ^ p ∂μ := by
refine lintegral_congr fun x => ?_
have h_rpow_mono := ENNReal.strictMono_rpow_of_pos (zero_lt_one.trans_le hp1)
have h_rpow_surj := (ENNReal.rpow_left_bijective hp_pos.ne.symm).2
refine (h_rpow_mono.orderIsoOfSurjective _ h_rpow_surj).liminf_apply ?_ ?_ ?_ ?_
all_goals isBoundedDefault
rw [h_liminf_pow]
refine (lintegral_liminf_le' ?_).trans ?_
· exact fun n =>
(Finset.aemeasurable_sum (Finset.range (n + 1)) fun i _ =>
((hf (i + 1)).sub (hf i)).ennnorm).pow_const
_
· exact liminf_le_of_frequently_le' (frequently_of_forall h)
private theorem tsum_nnnorm_sub_ae_lt_top {f : ℕ → α → E} (hf : ∀ n, AEStronglyMeasurable (f n) μ)
{p : ℝ} (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) ≤ ∑' i, B i) :
∀ᵐ x ∂μ, (∑' i, ‖f (i + 1) x - f i x‖₊ : ℝ≥0∞) < ∞ := by
have hp_pos : 0 < p := zero_lt_one.trans_le hp1
have h_integral : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) < ∞ := by
have h_tsum_lt_top : (∑' i, B i) ^ p < ∞ := ENNReal.rpow_lt_top_of_nonneg hp_pos.le hB
refine lt_of_le_of_lt ?_ h_tsum_lt_top
rwa [← ENNReal.le_rpow_one_div_iff (by simp [hp_pos] : 0 < 1 / p), one_div_one_div] at h
have rpow_ae_lt_top : ∀ᵐ x ∂μ, (∑' i, ‖f (i + 1) x - f i x‖₊ : ℝ≥0∞) ^ p < ∞ := by
refine ae_lt_top' (AEMeasurable.pow_const ?_ _) h_integral.ne
exact AEMeasurable.ennreal_tsum fun n => ((hf (n + 1)).sub (hf n)).ennnorm
refine rpow_ae_lt_top.mono fun x hx => ?_
rwa [← ENNReal.lt_rpow_one_div_iff hp_pos,
ENNReal.top_rpow_of_pos (by simp [hp_pos] : 0 < 1 / p)] at hx
theorem ae_tendsto_of_cauchy_snorm' [CompleteSpace E] {f : ℕ → α → E} {p : ℝ}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) (hp1 : 1 ≤ p) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm' (f n - f m) p μ < B N) :
∀ᵐ x ∂μ, ∃ l : E, atTop.Tendsto (fun n => f n x) (𝓝 l) := by
have h_summable : ∀ᵐ x ∂μ, Summable fun i : ℕ => f (i + 1) x - f i x := by
have h1 :
∀ n, snorm' (fun x => ∑ i ∈ Finset.range (n + 1), ‖f (i + 1) x - f i x‖) p μ ≤ ∑' i, B i :=
snorm'_sum_norm_sub_le_tsum_of_cauchy_snorm' hf hp1 h_cau
have h2 :
∀ n,
(∫⁻ a, (∑ i ∈ Finset.range (n + 1), ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ≤
(∑' i, B i) ^ p :=
fun n => lintegral_rpow_sum_coe_nnnorm_sub_le_rpow_tsum hp1 n (h1 n)
have h3 : (∫⁻ a, (∑' i, ‖f (i + 1) a - f i a‖₊ : ℝ≥0∞) ^ p ∂μ) ^ (1 / p) ≤ ∑' i, B i :=
lintegral_rpow_tsum_coe_nnnorm_sub_le_tsum hf hp1 h2
have h4 : ∀ᵐ x ∂μ, (∑' i, ‖f (i + 1) x - f i x‖₊ : ℝ≥0∞) < ∞ :=
tsum_nnnorm_sub_ae_lt_top hf hp1 hB h3
exact h4.mono fun x hx => .of_nnnorm <| ENNReal.tsum_coe_ne_top_iff_summable.mp hx.ne
have h :
∀ᵐ x ∂μ, ∃ l : E,
atTop.Tendsto (fun n => ∑ i ∈ Finset.range n, (f (i + 1) x - f i x)) (𝓝 l) := by
refine h_summable.mono fun x hx => ?_
let hx_sum := hx.hasSum.tendsto_sum_nat
exact ⟨∑' i, (f (i + 1) x - f i x), hx_sum⟩
refine h.mono fun x hx => ?_
cases' hx with l hx
have h_rw_sum :
(fun n => ∑ i ∈ Finset.range n, (f (i + 1) x - f i x)) = fun n => f n x - f 0 x := by
ext1 n
change
(∑ i ∈ Finset.range n, ((fun m => f m x) (i + 1) - (fun m => f m x) i)) = f n x - f 0 x
rw [Finset.sum_range_sub (fun m => f m x)]
rw [h_rw_sum] at hx
have hf_rw : (fun n => f n x) = fun n => f n x - f 0 x + f 0 x := by
ext1 n
abel
rw [hf_rw]
exact ⟨l + f 0 x, Tendsto.add_const _ hx⟩
#align measure_theory.Lp.ae_tendsto_of_cauchy_snorm' MeasureTheory.Lp.ae_tendsto_of_cauchy_snorm'
theorem ae_tendsto_of_cauchy_snorm [CompleteSpace E] {f : ℕ → α → E}
(hf : ∀ n, AEStronglyMeasurable (f n) μ) (hp : 1 ≤ p) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N) :
∀ᵐ x ∂μ, ∃ l : E, atTop.Tendsto (fun n => f n x) (𝓝 l) := by
by_cases hp_top : p = ∞
· simp_rw [hp_top] at *
have h_cau_ae : ∀ᵐ x ∂μ, ∀ N n m, N ≤ n → N ≤ m → (‖(f n - f m) x‖₊ : ℝ≥0∞) < B N := by
simp_rw [ae_all_iff]
exact fun N n m hnN hmN => ae_lt_of_essSup_lt (h_cau N n m hnN hmN)
simp_rw [snorm_exponent_top, snormEssSup] at h_cau
refine h_cau_ae.mono fun x hx => cauchySeq_tendsto_of_complete ?_
refine cauchySeq_of_le_tendsto_0 (fun n => (B n).toReal) ?_ ?_
· intro n m N hnN hmN
specialize hx N n m hnN hmN
rw [_root_.dist_eq_norm, ← ENNReal.toReal_ofReal (norm_nonneg _),
ENNReal.toReal_le_toReal ENNReal.ofReal_ne_top (ENNReal.ne_top_of_tsum_ne_top hB N)]
rw [← ofReal_norm_eq_coe_nnnorm] at hx
exact hx.le
· rw [← ENNReal.zero_toReal]
exact
Tendsto.comp (g := ENNReal.toReal) (ENNReal.tendsto_toReal ENNReal.zero_ne_top)
(ENNReal.tendsto_atTop_zero_of_tsum_ne_top hB)
have hp1 : 1 ≤ p.toReal := by
rw [← ENNReal.ofReal_le_iff_le_toReal hp_top, ENNReal.ofReal_one]
exact hp
have h_cau' : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm' (f n - f m) p.toReal μ < B N := by
intro N n m hn hm
specialize h_cau N n m hn hm
rwa [snorm_eq_snorm' (zero_lt_one.trans_le hp).ne.symm hp_top] at h_cau
exact ae_tendsto_of_cauchy_snorm' hf hp1 hB h_cau'
#align measure_theory.Lp.ae_tendsto_of_cauchy_snorm MeasureTheory.Lp.ae_tendsto_of_cauchy_snorm
| Mathlib/MeasureTheory/Function/LpSpace.lean | 1,658 | 1,679 | theorem cauchy_tendsto_of_tendsto {f : ℕ → α → E} (hf : ∀ n, AEStronglyMeasurable (f n) μ)
(f_lim : α → E) {B : ℕ → ℝ≥0∞} (hB : ∑' i, B i ≠ ∞)
(h_cau : ∀ N n m : ℕ, N ≤ n → N ≤ m → snorm (f n - f m) p μ < B N)
(h_lim : ∀ᵐ x : α ∂μ, Tendsto (fun n => f n x) atTop (𝓝 (f_lim x))) :
atTop.Tendsto (fun n => snorm (f n - f_lim) p μ) (𝓝 0) := by |
rw [ENNReal.tendsto_atTop_zero]
intro ε hε
have h_B : ∃ N : ℕ, B N ≤ ε := by
suffices h_tendsto_zero : ∃ N : ℕ, ∀ n : ℕ, N ≤ n → B n ≤ ε from
⟨h_tendsto_zero.choose, h_tendsto_zero.choose_spec _ le_rfl⟩
exact (ENNReal.tendsto_atTop_zero.mp (ENNReal.tendsto_atTop_zero_of_tsum_ne_top hB)) ε hε
cases' h_B with N h_B
refine ⟨N, fun n hn => ?_⟩
have h_sub : snorm (f n - f_lim) p μ ≤ atTop.liminf fun m => snorm (f n - f m) p μ := by
refine snorm_lim_le_liminf_snorm (fun m => (hf n).sub (hf m)) (f n - f_lim) ?_
refine h_lim.mono fun x hx => ?_
simp_rw [sub_eq_add_neg]
exact Tendsto.add tendsto_const_nhds (Tendsto.neg hx)
refine h_sub.trans ?_
refine liminf_le_of_frequently_le' (frequently_atTop.mpr ?_)
refine fun N1 => ⟨max N N1, le_max_right _ _, ?_⟩
exact (h_cau N n (max N N1) hn (le_max_left _ _)).le.trans h_B
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Thomas Read, Andrew Yang, Dagur Asgeirsson, Joël Riou
-/
import Mathlib.CategoryTheory.Adjunction.Basic
/-!
# Uniqueness of adjoints
This file shows that adjoints are unique up to natural isomorphism.
## Main results
* `Adjunction.natTransEquiv` and `Adjunction.natIsoEquiv` If `F ⊣ G` and `F' ⊣ G'` are adjunctions,
then there are equivalences `(G ⟶ G') ≃ (F' ⟶ F)` and `(G ≅ G') ≃ (F' ≅ F)`.
Everything else is deduced from this:
* `Adjunction.leftAdjointUniq` : If `F` and `F'` are both left adjoint to `G`, then they are
naturally isomorphic.
* `Adjunction.rightAdjointUniq` : If `G` and `G'` are both right adjoint to `F`, then they are
naturally isomorphic.
-/
open CategoryTheory
variable {C D : Type*} [Category C] [Category D]
namespace CategoryTheory.Adjunction
/--
If `F ⊣ G` and `F' ⊣ G'` are adjunctions, then giving a natural transformation `G ⟶ G'` is the
same as giving a natural transformation `F' ⟶ F`.
-/
@[simps]
def natTransEquiv {F F' : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G') :
(G ⟶ G') ≃ (F' ⟶ F) where
toFun f := {
app := fun X ↦ F'.map ((adj1.unit ≫ whiskerLeft F f).app X) ≫ adj2.counit.app _
naturality := by
intro X Y g
simp only [← Category.assoc, ← Functor.map_comp]
erw [(adj1.unit ≫ (whiskerLeft F f)).naturality]
simp
}
invFun f := {
app := fun X ↦ adj2.unit.app (G.obj X) ≫ G'.map (f.app (G.obj X) ≫ adj1.counit.app X)
naturality := by
intro X Y g
erw [← adj2.unit_naturality_assoc]
simp only [← Functor.map_comp]
simp
}
left_inv f := by
ext X
simp only [Functor.comp_obj, NatTrans.comp_app, Functor.id_obj, whiskerLeft_app,
Functor.map_comp, Category.assoc, unit_naturality_assoc, right_triangle_components_assoc]
erw [← f.naturality (adj1.counit.app X), ← Category.assoc]
simp
right_inv f := by
ext
simp
@[simp]
lemma natTransEquiv_id {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) :
natTransEquiv adj adj (𝟙 _) = 𝟙 _ := by ext; simp
@[simp]
lemma natTransEquiv_id_symm {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) :
(natTransEquiv adj adj).symm (𝟙 _) = 𝟙 _ := by ext; simp
@[simp]
lemma natTransEquiv_comp {F F' F'' : C ⥤ D} {G G' G'' : D ⥤ C}
(adj1 : F ⊣ G) (adj2 : F' ⊣ G') (adj3 : F'' ⊣ G'') (f : G ⟶ G') (g : G' ⟶ G'') :
natTransEquiv adj2 adj3 g ≫ natTransEquiv adj1 adj2 f = natTransEquiv adj1 adj3 (f ≫ g) := by
apply (natTransEquiv adj1 adj3).symm.injective
ext X
simp only [natTransEquiv_symm_apply_app, Functor.comp_obj, NatTrans.comp_app,
natTransEquiv_apply_app, Functor.id_obj, whiskerLeft_app, Functor.map_comp, Category.assoc,
unit_naturality_assoc, right_triangle_components_assoc, Equiv.symm_apply_apply,
← g.naturality_assoc, ← g.naturality]
simp only [← Category.assoc, unit_naturality, Functor.comp_obj, right_triangle_components,
Category.comp_id, ← f.naturality, Category.id_comp]
@[simp]
lemma natTransEquiv_comp_symm {F F' F'' : C ⥤ D} {G G' G'' : D ⥤ C}
(adj1 : F ⊣ G) (adj2 : F' ⊣ G') (adj3 : F'' ⊣ G'') (f : F' ⟶ F) (g : F'' ⟶ F') :
(natTransEquiv adj1 adj2).symm f ≫ (natTransEquiv adj2 adj3).symm g =
(natTransEquiv adj1 adj3).symm (g ≫ f) := by
apply (natTransEquiv adj1 adj3).injective
ext
simp
/--
If `F ⊣ G` and `F' ⊣ G'` are adjunctions, then giving a natural isomorphism `G ≅ G'` is the
same as giving a natural transformation `F' ≅ F`.
-/
@[simps]
def natIsoEquiv {F F' : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G') :
(G ≅ G') ≃ (F' ≅ F) where
toFun i := {
hom := natTransEquiv adj1 adj2 i.hom
inv := natTransEquiv adj2 adj1 i.inv
}
invFun i := {
hom := (natTransEquiv adj1 adj2).symm i.hom
inv := (natTransEquiv adj2 adj1).symm i.inv }
left_inv i := by simp
right_inv i := by simp
/-- If `F` and `F'` are both left adjoint to `G`, then they are naturally isomorphic. -/
def leftAdjointUniq {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) : F ≅ F' :=
(natIsoEquiv adj1 adj2 (Iso.refl _)).symm
#align category_theory.adjunction.left_adjoint_uniq CategoryTheory.Adjunction.leftAdjointUniq
-- Porting note (#10618): removed simp as simp can prove this
theorem homEquiv_leftAdjointUniq_hom_app {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(x : C) : adj1.homEquiv _ _ ((leftAdjointUniq adj1 adj2).hom.app x) = adj2.unit.app x := by
simp [leftAdjointUniq]
#align category_theory.adjunction.hom_equiv_left_adjoint_uniq_hom_app CategoryTheory.Adjunction.homEquiv_leftAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem unit_leftAdjointUniq_hom {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) :
adj1.unit ≫ whiskerRight (leftAdjointUniq adj1 adj2).hom G = adj2.unit := by
ext x
rw [NatTrans.comp_app, ← homEquiv_leftAdjointUniq_hom_app adj1 adj2]
simp [← G.map_comp]
#align category_theory.adjunction.unit_left_adjoint_uniq_hom CategoryTheory.Adjunction.unit_leftAdjointUniq_hom
@[reassoc (attr := simp)]
theorem unit_leftAdjointUniq_hom_app
{F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) (x : C) :
adj1.unit.app x ≫ G.map ((leftAdjointUniq adj1 adj2).hom.app x) = adj2.unit.app x := by
rw [← unit_leftAdjointUniq_hom adj1 adj2]; rfl
#align category_theory.adjunction.unit_left_adjoint_uniq_hom_app CategoryTheory.Adjunction.unit_leftAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem leftAdjointUniq_hom_counit {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) :
whiskerLeft G (leftAdjointUniq adj1 adj2).hom ≫ adj2.counit = adj1.counit := by
ext x
simp only [Functor.comp_obj, Functor.id_obj, leftAdjointUniq, Iso.symm_hom, natIsoEquiv_apply_inv,
Iso.refl_inv, NatTrans.comp_app, whiskerLeft_app, natTransEquiv_apply_app, whiskerLeft_id',
Category.comp_id, Category.assoc]
rw [← adj1.counit_naturality, ← Category.assoc, ← F.map_comp]
simp
#align category_theory.adjunction.left_adjoint_uniq_hom_counit CategoryTheory.Adjunction.leftAdjointUniq_hom_counit
@[reassoc (attr := simp)]
theorem leftAdjointUniq_hom_app_counit {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(x : D) :
(leftAdjointUniq adj1 adj2).hom.app (G.obj x) ≫ adj2.counit.app x = adj1.counit.app x := by
rw [← leftAdjointUniq_hom_counit adj1 adj2]
rfl
#align category_theory.adjunction.left_adjoint_uniq_hom_app_counit CategoryTheory.Adjunction.leftAdjointUniq_hom_app_counit
theorem leftAdjointUniq_inv_app {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) (x : C) :
(leftAdjointUniq adj1 adj2).inv.app x = (leftAdjointUniq adj2 adj1).hom.app x :=
rfl
#align category_theory.adjunction.left_adjoint_uniq_inv_app CategoryTheory.Adjunction.leftAdjointUniq_inv_app
@[reassoc (attr := simp)]
theorem leftAdjointUniq_trans {F F' F'' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(adj3 : F'' ⊣ G) :
(leftAdjointUniq adj1 adj2).hom ≫ (leftAdjointUniq adj2 adj3).hom =
(leftAdjointUniq adj1 adj3).hom := by
simp [leftAdjointUniq]
#align category_theory.adjunction.left_adjoint_uniq_trans CategoryTheory.Adjunction.leftAdjointUniq_trans
@[reassoc (attr := simp)]
theorem leftAdjointUniq_trans_app {F F' F'' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(adj3 : F'' ⊣ G) (x : C) :
(leftAdjointUniq adj1 adj2).hom.app x ≫ (leftAdjointUniq adj2 adj3).hom.app x =
(leftAdjointUniq adj1 adj3).hom.app x := by
rw [← leftAdjointUniq_trans adj1 adj2 adj3]
rfl
#align category_theory.adjunction.left_adjoint_uniq_trans_app CategoryTheory.Adjunction.leftAdjointUniq_trans_app
@[simp]
theorem leftAdjointUniq_refl {F : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) :
(leftAdjointUniq adj1 adj1).hom = 𝟙 _ := by
simp [leftAdjointUniq]
#align category_theory.adjunction.left_adjoint_uniq_refl CategoryTheory.Adjunction.leftAdjointUniq_refl
/-- If `G` and `G'` are both right adjoint to `F`, then they are naturally isomorphic. -/
def rightAdjointUniq {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G') : G ≅ G' :=
(natIsoEquiv adj1 adj2).symm (Iso.refl _)
#align category_theory.adjunction.right_adjoint_uniq CategoryTheory.Adjunction.rightAdjointUniq
-- Porting note (#10618): simp can prove this
theorem homEquiv_symm_rightAdjointUniq_hom_app {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G)
(adj2 : F ⊣ G') (x : D) :
(adj2.homEquiv _ _).symm ((rightAdjointUniq adj1 adj2).hom.app x) = adj1.counit.app x := by
simp [rightAdjointUniq]
#align category_theory.adjunction.hom_equiv_symm_right_adjoint_uniq_hom_app CategoryTheory.Adjunction.homEquiv_symm_rightAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem unit_rightAdjointUniq_hom_app {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G')
(x : C) : adj1.unit.app x ≫ (rightAdjointUniq adj1 adj2).hom.app (F.obj x) =
adj2.unit.app x := by
simp only [Functor.id_obj, Functor.comp_obj, rightAdjointUniq, natIsoEquiv_symm_apply_hom,
Iso.refl_hom, natTransEquiv_symm_apply_app, NatTrans.id_app, Category.id_comp]
rw [← adj2.unit_naturality_assoc, ← G'.map_comp]
simp
#align category_theory.adjunction.unit_right_adjoint_uniq_hom_app CategoryTheory.Adjunction.unit_rightAdjointUniq_hom_app
@[reassoc (attr := simp)]
theorem unit_rightAdjointUniq_hom {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G') :
adj1.unit ≫ whiskerLeft F (rightAdjointUniq adj1 adj2).hom = adj2.unit := by
ext x
simp
#align category_theory.adjunction.unit_right_adjoint_uniq_hom CategoryTheory.Adjunction.unit_rightAdjointUniq_hom
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Adjunction/Unique.lean | 214 | 217 | theorem rightAdjointUniq_hom_app_counit {F : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F ⊣ G')
(x : D) :
F.map ((rightAdjointUniq adj1 adj2).hom.app x) ≫ adj2.counit.app x = adj1.counit.app x := by |
simp [rightAdjointUniq]
|
/-
Copyright (c) 2020 Paul van Wamelen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Paul van Wamelen
-/
import Mathlib.NumberTheory.FLT.Basic
import Mathlib.NumberTheory.PythagoreanTriples
import Mathlib.RingTheory.Coprime.Lemmas
import Mathlib.Tactic.LinearCombination
#align_import number_theory.fermat4 from "leanprover-community/mathlib"@"10b4e499f43088dd3bb7b5796184ad5216648ab1"
/-!
# Fermat's Last Theorem for the case n = 4
There are no non-zero integers `a`, `b` and `c` such that `a ^ 4 + b ^ 4 = c ^ 4`.
-/
noncomputable section
open scoped Classical
/-- Shorthand for three non-zero integers `a`, `b`, and `c` satisfying `a ^ 4 + b ^ 4 = c ^ 2`.
We will show that no integers satisfy this equation. Clearly Fermat's Last theorem for n = 4
follows. -/
def Fermat42 (a b c : ℤ) : Prop :=
a ≠ 0 ∧ b ≠ 0 ∧ a ^ 4 + b ^ 4 = c ^ 2
#align fermat_42 Fermat42
namespace Fermat42
theorem comm {a b c : ℤ} : Fermat42 a b c ↔ Fermat42 b a c := by
delta Fermat42
rw [add_comm]
tauto
#align fermat_42.comm Fermat42.comm
theorem mul {a b c k : ℤ} (hk0 : k ≠ 0) :
Fermat42 a b c ↔ Fermat42 (k * a) (k * b) (k ^ 2 * c) := by
delta Fermat42
constructor
· intro f42
constructor
· exact mul_ne_zero hk0 f42.1
constructor
· exact mul_ne_zero hk0 f42.2.1
· have H : a ^ 4 + b ^ 4 = c ^ 2 := f42.2.2
linear_combination k ^ 4 * H
· intro f42
constructor
· exact right_ne_zero_of_mul f42.1
constructor
· exact right_ne_zero_of_mul f42.2.1
apply (mul_right_inj' (pow_ne_zero 4 hk0)).mp
linear_combination f42.2.2
#align fermat_42.mul Fermat42.mul
theorem ne_zero {a b c : ℤ} (h : Fermat42 a b c) : c ≠ 0 := by
apply ne_zero_pow two_ne_zero _; apply ne_of_gt
rw [← h.2.2, (by ring : a ^ 4 + b ^ 4 = (a ^ 2) ^ 2 + (b ^ 2) ^ 2)]
exact
add_pos (sq_pos_of_ne_zero (pow_ne_zero 2 h.1)) (sq_pos_of_ne_zero (pow_ne_zero 2 h.2.1))
#align fermat_42.ne_zero Fermat42.ne_zero
/-- We say a solution to `a ^ 4 + b ^ 4 = c ^ 2` is minimal if there is no other solution with
a smaller `c` (in absolute value). -/
def Minimal (a b c : ℤ) : Prop :=
Fermat42 a b c ∧ ∀ a1 b1 c1 : ℤ, Fermat42 a1 b1 c1 → Int.natAbs c ≤ Int.natAbs c1
#align fermat_42.minimal Fermat42.Minimal
/-- if we have a solution to `a ^ 4 + b ^ 4 = c ^ 2` then there must be a minimal one. -/
| Mathlib/NumberTheory/FLT/Four.lean | 72 | 85 | theorem exists_minimal {a b c : ℤ} (h : Fermat42 a b c) : ∃ a0 b0 c0, Minimal a0 b0 c0 := by |
let S : Set ℕ := { n | ∃ s : ℤ × ℤ × ℤ, Fermat42 s.1 s.2.1 s.2.2 ∧ n = Int.natAbs s.2.2 }
have S_nonempty : S.Nonempty := by
use Int.natAbs c
rw [Set.mem_setOf_eq]
use ⟨a, ⟨b, c⟩⟩
let m : ℕ := Nat.find S_nonempty
have m_mem : m ∈ S := Nat.find_spec S_nonempty
rcases m_mem with ⟨s0, hs0, hs1⟩
use s0.1, s0.2.1, s0.2.2, hs0
intro a1 b1 c1 h1
rw [← hs1]
apply Nat.find_min'
use ⟨a1, ⟨b1, c1⟩⟩
|
/-
Copyright (c) 2018 Mario Carneiro, Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Kevin Buzzard
-/
import Mathlib.Order.Filter.EventuallyConst
import Mathlib.Order.PartialSups
import Mathlib.Algebra.Module.Submodule.IterateMapComap
import Mathlib.RingTheory.OrzechProperty
import Mathlib.RingTheory.Nilpotent.Lemmas
#align_import ring_theory.noetherian from "leanprover-community/mathlib"@"210657c4ea4a4a7b234392f70a3a2a83346dfa90"
/-!
# Noetherian rings and modules
The following are equivalent for a module M over a ring R:
1. Every increasing chain of submodules M₁ ⊆ M₂ ⊆ M₃ ⊆ ⋯ eventually stabilises.
2. Every submodule is finitely generated.
A module satisfying these equivalent conditions is said to be a *Noetherian* R-module.
A ring is a *Noetherian ring* if it is Noetherian as a module over itself.
(Note that we do not assume yet that our rings are commutative,
so perhaps this should be called "left Noetherian".
To avoid cumbersome names once we specialize to the commutative case,
we don't make this explicit in the declaration names.)
## Main definitions
Let `R` be a ring and let `M` and `P` be `R`-modules. Let `N` be an `R`-submodule of `M`.
* `IsNoetherian R M` is the proposition that `M` is a Noetherian `R`-module. It is a class,
implemented as the predicate that all `R`-submodules of `M` are finitely generated.
## Main statements
* `isNoetherian_iff_wellFounded` is the theorem that an R-module M is Noetherian iff
`>` is well-founded on `Submodule R M`.
Note that the Hilbert basis theorem, that if a commutative ring R is Noetherian then so is R[X],
is proved in `RingTheory.Polynomial`.
## References
* [M. F. Atiyah and I. G. Macdonald, *Introduction to commutative algebra*][atiyah-macdonald]
* [samuel1967]
## Tags
Noetherian, noetherian, Noetherian ring, Noetherian module, noetherian ring, noetherian module
-/
open Set Filter Pointwise
/-- `IsNoetherian R M` is the proposition that `M` is a Noetherian `R`-module,
implemented as the predicate that all `R`-submodules of `M` are finitely generated.
-/
-- Porting note: should this be renamed to `Noetherian`?
class IsNoetherian (R M) [Semiring R] [AddCommMonoid M] [Module R M] : Prop where
noetherian : ∀ s : Submodule R M, s.FG
#align is_noetherian IsNoetherian
attribute [inherit_doc IsNoetherian] IsNoetherian.noetherian
section
variable {R : Type*} {M : Type*} {P : Type*}
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid P]
variable [Module R M] [Module R P]
open IsNoetherian
/-- An R-module is Noetherian iff all its submodules are finitely-generated. -/
theorem isNoetherian_def : IsNoetherian R M ↔ ∀ s : Submodule R M, s.FG :=
⟨fun h => h.noetherian, IsNoetherian.mk⟩
#align is_noetherian_def isNoetherian_def
theorem isNoetherian_submodule {N : Submodule R M} :
IsNoetherian R N ↔ ∀ s : Submodule R M, s ≤ N → s.FG := by
refine ⟨fun ⟨hn⟩ => fun s hs =>
have : s ≤ LinearMap.range N.subtype := N.range_subtype.symm ▸ hs
Submodule.map_comap_eq_self this ▸ (hn _).map _,
fun h => ⟨fun s => ?_⟩⟩
have f := (Submodule.equivMapOfInjective N.subtype Subtype.val_injective s).symm
have h₁ := h (s.map N.subtype) (Submodule.map_subtype_le N s)
have h₂ : (⊤ : Submodule R (s.map N.subtype)).map f = ⊤ := by simp
have h₃ := ((Submodule.fg_top _).2 h₁).map (↑f : _ →ₗ[R] s)
exact (Submodule.fg_top _).1 (h₂ ▸ h₃)
#align is_noetherian_submodule isNoetherian_submodule
theorem isNoetherian_submodule_left {N : Submodule R M} :
IsNoetherian R N ↔ ∀ s : Submodule R M, (N ⊓ s).FG :=
isNoetherian_submodule.trans ⟨fun H _ => H _ inf_le_left, fun H _ hs => inf_of_le_right hs ▸ H _⟩
#align is_noetherian_submodule_left isNoetherian_submodule_left
theorem isNoetherian_submodule_right {N : Submodule R M} :
IsNoetherian R N ↔ ∀ s : Submodule R M, (s ⊓ N).FG :=
isNoetherian_submodule.trans ⟨fun H _ => H _ inf_le_right, fun H _ hs => inf_of_le_left hs ▸ H _⟩
#align is_noetherian_submodule_right isNoetherian_submodule_right
instance isNoetherian_submodule' [IsNoetherian R M] (N : Submodule R M) : IsNoetherian R N :=
isNoetherian_submodule.2 fun _ _ => IsNoetherian.noetherian _
#align is_noetherian_submodule' isNoetherian_submodule'
theorem isNoetherian_of_le {s t : Submodule R M} [ht : IsNoetherian R t] (h : s ≤ t) :
IsNoetherian R s :=
isNoetherian_submodule.mpr fun _ hs' => isNoetherian_submodule.mp ht _ (le_trans hs' h)
#align is_noetherian_of_le isNoetherian_of_le
variable (M)
theorem isNoetherian_of_surjective (f : M →ₗ[R] P) (hf : LinearMap.range f = ⊤) [IsNoetherian R M] :
IsNoetherian R P :=
⟨fun s =>
have : (s.comap f).map f = s := Submodule.map_comap_eq_self <| hf.symm ▸ le_top
this ▸ (noetherian _).map _⟩
#align is_noetherian_of_surjective isNoetherian_of_surjective
variable {M}
instance isNoetherian_quotient {R} [Ring R] {M} [AddCommGroup M] [Module R M]
(N : Submodule R M) [IsNoetherian R M] : IsNoetherian R (M ⧸ N) :=
isNoetherian_of_surjective _ _ (LinearMap.range_eq_top.mpr N.mkQ_surjective)
#align submodule.quotient.is_noetherian isNoetherian_quotient
@[deprecated (since := "2024-04-27"), nolint defLemma]
alias Submodule.Quotient.isNoetherian := isNoetherian_quotient
theorem isNoetherian_of_linearEquiv (f : M ≃ₗ[R] P) [IsNoetherian R M] : IsNoetherian R P :=
isNoetherian_of_surjective _ f.toLinearMap f.range
#align is_noetherian_of_linear_equiv isNoetherian_of_linearEquiv
theorem isNoetherian_top_iff : IsNoetherian R (⊤ : Submodule R M) ↔ IsNoetherian R M := by
constructor <;> intro h
· exact isNoetherian_of_linearEquiv (LinearEquiv.ofTop (⊤ : Submodule R M) rfl)
· exact isNoetherian_of_linearEquiv (LinearEquiv.ofTop (⊤ : Submodule R M) rfl).symm
#align is_noetherian_top_iff isNoetherian_top_iff
theorem isNoetherian_of_injective [IsNoetherian R P] (f : M →ₗ[R] P) (hf : Function.Injective f) :
IsNoetherian R M :=
isNoetherian_of_linearEquiv (LinearEquiv.ofInjective f hf).symm
#align is_noetherian_of_injective isNoetherian_of_injective
theorem fg_of_injective [IsNoetherian R P] {N : Submodule R M} (f : M →ₗ[R] P)
(hf : Function.Injective f) : N.FG :=
haveI := isNoetherian_of_injective f hf
IsNoetherian.noetherian N
#align fg_of_injective fg_of_injective
end
namespace Module
variable {R M N : Type*}
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid N] [Module R M] [Module R N]
variable (R M)
-- see Note [lower instance priority]
instance (priority := 100) IsNoetherian.finite [IsNoetherian R M] : Finite R M :=
⟨IsNoetherian.noetherian ⊤⟩
#align module.is_noetherian.finite Module.IsNoetherian.finite
instance {R₁ S : Type*} [CommSemiring R₁] [Semiring S] [Algebra R₁ S]
[IsNoetherian R₁ S] (I : Ideal S) : Finite R₁ I :=
IsNoetherian.finite R₁ ((I : Submodule S S).restrictScalars R₁)
variable {R M}
theorem Finite.of_injective [IsNoetherian R N] (f : M →ₗ[R] N) (hf : Function.Injective f) :
Finite R M :=
⟨fg_of_injective f hf⟩
#align module.finite.of_injective Module.Finite.of_injective
end Module
section
variable {R : Type*} {M : Type*} {P : Type*}
variable [Ring R] [AddCommGroup M] [AddCommGroup P]
variable [Module R M] [Module R P]
open IsNoetherian
theorem isNoetherian_of_ker_bot [IsNoetherian R P] (f : M →ₗ[R] P) (hf : LinearMap.ker f = ⊥) :
IsNoetherian R M :=
isNoetherian_of_linearEquiv (LinearEquiv.ofInjective f <| LinearMap.ker_eq_bot.mp hf).symm
#align is_noetherian_of_ker_bot isNoetherian_of_ker_bot
theorem fg_of_ker_bot [IsNoetherian R P] {N : Submodule R M} (f : M →ₗ[R] P)
(hf : LinearMap.ker f = ⊥) : N.FG :=
haveI := isNoetherian_of_ker_bot f hf
IsNoetherian.noetherian N
#align fg_of_ker_bot fg_of_ker_bot
instance isNoetherian_prod [IsNoetherian R M] [IsNoetherian R P] : IsNoetherian R (M × P) :=
⟨fun s =>
Submodule.fg_of_fg_map_of_fg_inf_ker (LinearMap.snd R M P) (noetherian _) <|
have : s ⊓ LinearMap.ker (LinearMap.snd R M P) ≤ LinearMap.range (LinearMap.inl R M P) :=
fun x ⟨_, hx2⟩ => ⟨x.1, Prod.ext rfl <| Eq.symm <| LinearMap.mem_ker.1 hx2⟩
Submodule.map_comap_eq_self this ▸ (noetherian _).map _⟩
#align is_noetherian_prod isNoetherian_prod
instance isNoetherian_pi {R ι : Type*} {M : ι → Type*}
[Ring R] [∀ i, AddCommGroup (M i)] [∀ i, Module R (M i)] [Finite ι]
[∀ i, IsNoetherian R (M i)] : IsNoetherian R (∀ i, M i) := by
cases nonempty_fintype ι
haveI := Classical.decEq ι
suffices on_finset : ∀ s : Finset ι, IsNoetherian R (∀ i : s, M i) by
let coe_e := Equiv.subtypeUnivEquiv <| @Finset.mem_univ ι _
letI : IsNoetherian R (∀ i : Finset.univ, M (coe_e i)) := on_finset Finset.univ
exact isNoetherian_of_linearEquiv (LinearEquiv.piCongrLeft R M coe_e)
intro s
induction' s using Finset.induction with a s has ih
· exact ⟨fun s => by
have : s = ⊥ := by simp only [eq_iff_true_of_subsingleton]
rw [this]
apply Submodule.fg_bot⟩
refine
@isNoetherian_of_linearEquiv R (M a × ((i : s) → M i)) _ _ _ _ _ _ ?_ <|
@isNoetherian_prod R (M a) _ _ _ _ _ _ _ ih
refine
{ toFun := fun f i =>
(Finset.mem_insert.1 i.2).by_cases
(fun h : i.1 = a => show M i.1 from Eq.recOn h.symm f.1)
(fun h : i.1 ∈ s => show M i.1 from f.2 ⟨i.1, h⟩),
invFun := fun f =>
(f ⟨a, Finset.mem_insert_self _ _⟩, fun i => f ⟨i.1, Finset.mem_insert_of_mem i.2⟩),
map_add' := ?_,
map_smul' := ?_
left_inv := ?_,
right_inv := ?_ }
· intro f g
ext i
unfold Or.by_cases
cases' i with i hi
rcases Finset.mem_insert.1 hi with (rfl | h)
· change _ = _ + _
simp only [dif_pos]
rfl
· change _ = _ + _
have : ¬i = a := by
rintro rfl
exact has h
simp only [dif_neg this, dif_pos h]
rfl
· intro c f
ext i
unfold Or.by_cases
cases' i with i hi
rcases Finset.mem_insert.1 hi with (rfl | h)
· dsimp
simp only [dif_pos]
· dsimp
have : ¬i = a := by
rintro rfl
exact has h
simp only [dif_neg this, dif_pos h]
· intro f
apply Prod.ext
· simp only [Or.by_cases, dif_pos]
· ext ⟨i, his⟩
have : ¬i = a := by
rintro rfl
exact has his
simp only [Or.by_cases, this, not_false_iff, dif_neg]
· intro f
ext ⟨i, hi⟩
rcases Finset.mem_insert.1 hi with (rfl | h)
· simp only [Or.by_cases, dif_pos]
· have : ¬i = a := by
rintro rfl
exact has h
simp only [Or.by_cases, dif_neg this, dif_pos h]
#align is_noetherian_pi isNoetherian_pi
/-- A version of `isNoetherian_pi` for non-dependent functions. We need this instance because
sometimes Lean fails to apply the dependent version in non-dependent settings (e.g., it fails to
prove that `ι → ℝ` is finite dimensional over `ℝ`). -/
instance isNoetherian_pi' {R ι M : Type*} [Ring R] [AddCommGroup M] [Module R M] [Finite ι]
[IsNoetherian R M] : IsNoetherian R (ι → M) :=
isNoetherian_pi
#align is_noetherian_pi' isNoetherian_pi'
end
section CommRing
variable (R M N : Type*) [CommRing R] [AddCommGroup M] [AddCommGroup N] [Module R M] [Module R N]
[IsNoetherian R M] [Module.Finite R N]
instance isNoetherian_linearMap_pi {ι : Type*} [Finite ι] : IsNoetherian R ((ι → R) →ₗ[R] M) :=
let _i : Fintype ι := Fintype.ofFinite ι; isNoetherian_of_linearEquiv (Module.piEquiv ι R M)
instance isNoetherian_linearMap : IsNoetherian R (N →ₗ[R] M) := by
obtain ⟨n, f, hf⟩ := Module.Finite.exists_fin' R N
let g : (N →ₗ[R] M) →ₗ[R] (Fin n → R) →ₗ[R] M := (LinearMap.llcomp R (Fin n → R) N M).flip f
exact isNoetherian_of_injective g hf.injective_linearMapComp_right
end CommRing
open IsNoetherian Submodule Function
section
universe w
variable {R M P : Type*} {N : Type w} [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid N]
[Module R N] [AddCommMonoid P] [Module R P]
theorem isNoetherian_iff_wellFounded :
IsNoetherian R M ↔ WellFounded ((· > ·) : Submodule R M → Submodule R M → Prop) := by
have := (CompleteLattice.wellFounded_characterisations <| Submodule R M).out 0 3
-- Porting note: inlining this makes rw complain about it being a metavariable
rw [this]
exact
⟨fun ⟨h⟩ => fun k => (fg_iff_compact k).mp (h k), fun h =>
⟨fun k => (fg_iff_compact k).mpr (h k)⟩⟩
#align is_noetherian_iff_well_founded isNoetherian_iff_wellFounded
theorem isNoetherian_iff_fg_wellFounded :
IsNoetherian R M ↔
WellFounded
((· > ·) : { N : Submodule R M // N.FG } → { N : Submodule R M // N.FG } → Prop) := by
let α := { N : Submodule R M // N.FG }
constructor
· intro H
let f : α ↪o Submodule R M := OrderEmbedding.subtype _
exact OrderEmbedding.wellFounded f.dual (isNoetherian_iff_wellFounded.mp H)
· intro H
constructor
intro N
obtain ⟨⟨N₀, h₁⟩, e : N₀ ≤ N, h₂⟩ :=
WellFounded.has_min H { N' : α | N'.1 ≤ N } ⟨⟨⊥, Submodule.fg_bot⟩, @bot_le _ _ _ N⟩
convert h₁
refine (e.antisymm ?_).symm
by_contra h₃
obtain ⟨x, hx₁ : x ∈ N, hx₂ : x ∉ N₀⟩ := Set.not_subset.mp h₃
apply hx₂
rw [eq_of_le_of_not_lt (le_sup_right : N₀ ≤ _) (h₂
⟨_, Submodule.FG.sup ⟨{x}, by rw [Finset.coe_singleton]⟩ h₁⟩ <|
sup_le ((Submodule.span_singleton_le_iff_mem _ _).mpr hx₁) e)]
exact (le_sup_left : (R ∙ x) ≤ _) (Submodule.mem_span_singleton_self _)
#align is_noetherian_iff_fg_well_founded isNoetherian_iff_fg_wellFounded
variable (R M)
theorem wellFounded_submodule_gt (R M) [Semiring R] [AddCommMonoid M] [Module R M] :
∀ [IsNoetherian R M], WellFounded ((· > ·) : Submodule R M → Submodule R M → Prop) :=
isNoetherian_iff_wellFounded.mp ‹_›
#align well_founded_submodule_gt wellFounded_submodule_gt
variable {R M}
/-- A module is Noetherian iff every nonempty set of submodules has a maximal submodule among them.
-/
theorem set_has_maximal_iff_noetherian :
(∀ a : Set <| Submodule R M, a.Nonempty → ∃ M' ∈ a, ∀ I ∈ a, ¬M' < I) ↔ IsNoetherian R M := by
rw [isNoetherian_iff_wellFounded, WellFounded.wellFounded_iff_has_min]
#align set_has_maximal_iff_noetherian set_has_maximal_iff_noetherian
/-- A module is Noetherian iff every increasing chain of submodules stabilizes. -/
| Mathlib/RingTheory/Noetherian.lean | 365 | 367 | theorem monotone_stabilizes_iff_noetherian :
(∀ f : ℕ →o Submodule R M, ∃ n, ∀ m, n ≤ m → f n = f m) ↔ IsNoetherian R M := by |
rw [isNoetherian_iff_wellFounded, WellFounded.monotone_chain_condition]
|
/-
Copyright (c) 2021 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.MvPolynomial.Equiv
import Mathlib.Algebra.MvPolynomial.Supported
import Mathlib.LinearAlgebra.LinearIndependent
import Mathlib.RingTheory.Adjoin.Basic
import Mathlib.RingTheory.Algebraic
import Mathlib.RingTheory.MvPolynomial.Basic
#align_import ring_theory.algebraic_independent from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69"
/-!
# Algebraic Independence
This file defines algebraic independence of a family of element of an `R` algebra.
## Main definitions
* `AlgebraicIndependent` - `AlgebraicIndependent R x` states the family of elements `x`
is algebraically independent over `R`, meaning that the canonical map out of the multivariable
polynomial ring is injective.
* `AlgebraicIndependent.repr` - The canonical map from the subalgebra generated by an
algebraic independent family into the polynomial ring.
## References
* [Stacks: Transcendence](https://stacks.math.columbia.edu/tag/030D)
## TODO
Define the transcendence degree and show it is independent of the choice of a
transcendence basis.
## Tags
transcendence basis, transcendence degree, transcendence
-/
noncomputable section
open Function Set Subalgebra MvPolynomial Algebra
open scoped Classical
universe x u v w
variable {ι : Type*} {ι' : Type*} (R : Type*) {K : Type*}
variable {A : Type*} {A' A'' : Type*} {V : Type u} {V' : Type*}
variable (x : ι → A)
variable [CommRing R] [CommRing A] [CommRing A'] [CommRing A'']
variable [Algebra R A] [Algebra R A'] [Algebra R A'']
variable {a b : R}
/-- `AlgebraicIndependent R x` states the family of elements `x`
is algebraically independent over `R`, meaning that the canonical
map out of the multivariable polynomial ring is injective. -/
def AlgebraicIndependent : Prop :=
Injective (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A)
#align algebraic_independent AlgebraicIndependent
variable {R} {x}
theorem algebraicIndependent_iff_ker_eq_bot :
AlgebraicIndependent R x ↔
RingHom.ker (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A).toRingHom = ⊥ :=
RingHom.injective_iff_ker_eq_bot _
#align algebraic_independent_iff_ker_eq_bot algebraicIndependent_iff_ker_eq_bot
theorem algebraicIndependent_iff :
AlgebraicIndependent R x ↔
∀ p : MvPolynomial ι R, MvPolynomial.aeval (x : ι → A) p = 0 → p = 0 :=
injective_iff_map_eq_zero _
#align algebraic_independent_iff algebraicIndependent_iff
theorem AlgebraicIndependent.eq_zero_of_aeval_eq_zero (h : AlgebraicIndependent R x) :
∀ p : MvPolynomial ι R, MvPolynomial.aeval (x : ι → A) p = 0 → p = 0 :=
algebraicIndependent_iff.1 h
#align algebraic_independent.eq_zero_of_aeval_eq_zero AlgebraicIndependent.eq_zero_of_aeval_eq_zero
theorem algebraicIndependent_iff_injective_aeval :
AlgebraicIndependent R x ↔ Injective (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A) :=
Iff.rfl
#align algebraic_independent_iff_injective_aeval algebraicIndependent_iff_injective_aeval
@[simp]
theorem algebraicIndependent_empty_type_iff [IsEmpty ι] :
AlgebraicIndependent R x ↔ Injective (algebraMap R A) := by
have : aeval x = (Algebra.ofId R A).comp (@isEmptyAlgEquiv R ι _ _).toAlgHom := by
ext i
exact IsEmpty.elim' ‹IsEmpty ι› i
rw [AlgebraicIndependent, this, ← Injective.of_comp_iff' _ (@isEmptyAlgEquiv R ι _ _).bijective]
rfl
#align algebraic_independent_empty_type_iff algebraicIndependent_empty_type_iff
namespace AlgebraicIndependent
variable (hx : AlgebraicIndependent R x)
theorem algebraMap_injective : Injective (algebraMap R A) := by
simpa [Function.comp] using
(Injective.of_comp_iff (algebraicIndependent_iff_injective_aeval.1 hx) MvPolynomial.C).2
(MvPolynomial.C_injective _ _)
#align algebraic_independent.algebra_map_injective AlgebraicIndependent.algebraMap_injective
theorem linearIndependent : LinearIndependent R x := by
rw [linearIndependent_iff_injective_total]
have : Finsupp.total ι A R x =
(MvPolynomial.aeval x).toLinearMap.comp (Finsupp.total ι _ R X) := by
ext
simp
rw [this]
refine hx.comp ?_
rw [← linearIndependent_iff_injective_total]
exact linearIndependent_X _ _
#align algebraic_independent.linear_independent AlgebraicIndependent.linearIndependent
protected theorem injective [Nontrivial R] : Injective x :=
hx.linearIndependent.injective
#align algebraic_independent.injective AlgebraicIndependent.injective
theorem ne_zero [Nontrivial R] (i : ι) : x i ≠ 0 :=
hx.linearIndependent.ne_zero i
#align algebraic_independent.ne_zero AlgebraicIndependent.ne_zero
theorem comp (f : ι' → ι) (hf : Function.Injective f) : AlgebraicIndependent R (x ∘ f) := by
intro p q
simpa [aeval_rename, (rename_injective f hf).eq_iff] using @hx (rename f p) (rename f q)
#align algebraic_independent.comp AlgebraicIndependent.comp
| Mathlib/RingTheory/AlgebraicIndependent.lean | 134 | 135 | theorem coe_range : AlgebraicIndependent R ((↑) : range x → A) := by |
simpa using hx.comp _ (rangeSplitting_injective x)
|
/-
Copyright (c) 2022 Benjamin Davidson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Benjamin Davidson, Devon Tuma, Eric Rodriguez, Oliver Nash
-/
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.Topology.Algebra.Field
import Mathlib.Topology.Algebra.Order.Group
#align_import topology.algebra.order.field from "leanprover-community/mathlib"@"9a59dcb7a2d06bf55da57b9030169219980660cd"
/-!
# Topologies on linear ordered fields
In this file we prove that a linear ordered field with order topology has continuous multiplication
and division (apart from zero in the denominator). We also prove theorems like
`Filter.Tendsto.mul_atTop`: if `f` tends to a positive number and `g` tends to positive infinity,
then `f * g` tends to positive infinity.
-/
open Set Filter TopologicalSpace Function
open scoped Pointwise Topology
open OrderDual (toDual ofDual)
/-- If a (possibly non-unital and/or non-associative) ring `R` admits a submultiplicative
nonnegative norm `norm : R → 𝕜`, where `𝕜` is a linear ordered field, and the open balls
`{ x | norm x < ε }`, `ε > 0`, form a basis of neighborhoods of zero, then `R` is a topological
ring. -/
theorem TopologicalRing.of_norm {R 𝕜 : Type*} [NonUnitalNonAssocRing R] [LinearOrderedField 𝕜]
[TopologicalSpace R] [TopologicalAddGroup R] (norm : R → 𝕜)
(norm_nonneg : ∀ x, 0 ≤ norm x) (norm_mul_le : ∀ x y, norm (x * y) ≤ norm x * norm y)
(nhds_basis : (𝓝 (0 : R)).HasBasis ((0 : 𝕜) < ·) (fun ε ↦ { x | norm x < ε })) :
TopologicalRing R := by
have h0 : ∀ f : R → R, ∀ c ≥ (0 : 𝕜), (∀ x, norm (f x) ≤ c * norm x) →
Tendsto f (𝓝 0) (𝓝 0) := by
refine fun f c c0 hf ↦ (nhds_basis.tendsto_iff nhds_basis).2 fun ε ε0 ↦ ?_
rcases exists_pos_mul_lt ε0 c with ⟨δ, δ0, hδ⟩
refine ⟨δ, δ0, fun x hx ↦ (hf _).trans_lt ?_⟩
exact (mul_le_mul_of_nonneg_left (le_of_lt hx) c0).trans_lt hδ
apply TopologicalRing.of_addGroup_of_nhds_zero
case hmul =>
refine ((nhds_basis.prod nhds_basis).tendsto_iff nhds_basis).2 fun ε ε0 ↦ ?_
refine ⟨(1, ε), ⟨one_pos, ε0⟩, fun (x, y) ⟨hx, hy⟩ => ?_⟩
simp only [sub_zero] at *
calc norm (x * y) ≤ norm x * norm y := norm_mul_le _ _
_ < ε := mul_lt_of_le_one_of_lt_of_nonneg hx.le hy (norm_nonneg _)
case hmul_left => exact fun x => h0 _ (norm x) (norm_nonneg _) (norm_mul_le x)
case hmul_right =>
exact fun y => h0 (· * y) (norm y) (norm_nonneg y) fun x =>
(norm_mul_le x y).trans_eq (mul_comm _ _)
variable {𝕜 α : Type*} [LinearOrderedField 𝕜] [TopologicalSpace 𝕜] [OrderTopology 𝕜]
{l : Filter α} {f g : α → 𝕜}
-- see Note [lower instance priority]
instance (priority := 100) LinearOrderedField.topologicalRing : TopologicalRing 𝕜 :=
.of_norm abs abs_nonneg (fun _ _ ↦ (abs_mul _ _).le) <| by
simpa using nhds_basis_abs_sub_lt (0 : 𝕜)
/-- In a linearly ordered field with the order topology, if `f` tends to `Filter.atTop` and `g`
tends to a positive constant `C` then `f * g` tends to `Filter.atTop`. -/
| Mathlib/Topology/Algebra/Order/Field.lean | 63 | 67 | theorem Filter.Tendsto.atTop_mul {C : 𝕜} (hC : 0 < C) (hf : Tendsto f l atTop)
(hg : Tendsto g l (𝓝 C)) : Tendsto (fun x => f x * g x) l atTop := by |
refine tendsto_atTop_mono' _ ?_ (hf.atTop_mul_const (half_pos hC))
filter_upwards [hg.eventually (lt_mem_nhds (half_lt_self hC)), hf.eventually_ge_atTop 0]
with x hg hf using mul_le_mul_of_nonneg_left hg.le hf
|
/-
Copyright (c) 2017 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Neil Strickland
-/
import Mathlib.Data.Nat.Prime
import Mathlib.Data.PNat.Basic
#align_import data.pnat.prime from "leanprover-community/mathlib"@"09597669f02422ed388036273d8848119699c22f"
/-!
# Primality and GCD on pnat
This file extends the theory of `ℕ+` with `gcd`, `lcm` and `Prime` functions, analogous to those on
`Nat`.
-/
namespace Nat.Primes
-- Porting note (#11445): new definition
/-- The canonical map from `Nat.Primes` to `ℕ+` -/
@[coe] def toPNat : Nat.Primes → ℕ+ :=
fun p => ⟨(p : ℕ), p.property.pos⟩
instance coePNat : Coe Nat.Primes ℕ+ :=
⟨toPNat⟩
#align nat.primes.coe_pnat Nat.Primes.coePNat
@[norm_cast]
theorem coe_pnat_nat (p : Nat.Primes) : ((p : ℕ+) : ℕ) = p :=
rfl
#align nat.primes.coe_pnat_nat Nat.Primes.coe_pnat_nat
theorem coe_pnat_injective : Function.Injective ((↑) : Nat.Primes → ℕ+) := fun p q h =>
Subtype.ext (by injection h)
#align nat.primes.coe_pnat_injective Nat.Primes.coe_pnat_injective
@[norm_cast]
theorem coe_pnat_inj (p q : Nat.Primes) : (p : ℕ+) = (q : ℕ+) ↔ p = q :=
coe_pnat_injective.eq_iff
#align nat.primes.coe_pnat_inj Nat.Primes.coe_pnat_inj
end Nat.Primes
namespace PNat
open Nat
/-- The greatest common divisor (gcd) of two positive natural numbers,
viewed as positive natural number. -/
def gcd (n m : ℕ+) : ℕ+ :=
⟨Nat.gcd (n : ℕ) (m : ℕ), Nat.gcd_pos_of_pos_left (m : ℕ) n.pos⟩
#align pnat.gcd PNat.gcd
/-- The least common multiple (lcm) of two positive natural numbers,
viewed as positive natural number. -/
def lcm (n m : ℕ+) : ℕ+ :=
⟨Nat.lcm (n : ℕ) (m : ℕ), by
let h := mul_pos n.pos m.pos
rw [← gcd_mul_lcm (n : ℕ) (m : ℕ), mul_comm] at h
exact pos_of_dvd_of_pos (Dvd.intro (Nat.gcd (n : ℕ) (m : ℕ)) rfl) h⟩
#align pnat.lcm PNat.lcm
@[simp, norm_cast]
theorem gcd_coe (n m : ℕ+) : (gcd n m : ℕ) = Nat.gcd n m :=
rfl
#align pnat.gcd_coe PNat.gcd_coe
@[simp, norm_cast]
theorem lcm_coe (n m : ℕ+) : (lcm n m : ℕ) = Nat.lcm n m :=
rfl
#align pnat.lcm_coe PNat.lcm_coe
theorem gcd_dvd_left (n m : ℕ+) : gcd n m ∣ n :=
dvd_iff.2 (Nat.gcd_dvd_left (n : ℕ) (m : ℕ))
#align pnat.gcd_dvd_left PNat.gcd_dvd_left
theorem gcd_dvd_right (n m : ℕ+) : gcd n m ∣ m :=
dvd_iff.2 (Nat.gcd_dvd_right (n : ℕ) (m : ℕ))
#align pnat.gcd_dvd_right PNat.gcd_dvd_right
theorem dvd_gcd {m n k : ℕ+} (hm : k ∣ m) (hn : k ∣ n) : k ∣ gcd m n :=
dvd_iff.2 (Nat.dvd_gcd (dvd_iff.1 hm) (dvd_iff.1 hn))
#align pnat.dvd_gcd PNat.dvd_gcd
theorem dvd_lcm_left (n m : ℕ+) : n ∣ lcm n m :=
dvd_iff.2 (Nat.dvd_lcm_left (n : ℕ) (m : ℕ))
#align pnat.dvd_lcm_left PNat.dvd_lcm_left
theorem dvd_lcm_right (n m : ℕ+) : m ∣ lcm n m :=
dvd_iff.2 (Nat.dvd_lcm_right (n : ℕ) (m : ℕ))
#align pnat.dvd_lcm_right PNat.dvd_lcm_right
theorem lcm_dvd {m n k : ℕ+} (hm : m ∣ k) (hn : n ∣ k) : lcm m n ∣ k :=
dvd_iff.2 (@Nat.lcm_dvd (m : ℕ) (n : ℕ) (k : ℕ) (dvd_iff.1 hm) (dvd_iff.1 hn))
#align pnat.lcm_dvd PNat.lcm_dvd
theorem gcd_mul_lcm (n m : ℕ+) : gcd n m * lcm n m = n * m :=
Subtype.eq (Nat.gcd_mul_lcm (n : ℕ) (m : ℕ))
#align pnat.gcd_mul_lcm PNat.gcd_mul_lcm
theorem eq_one_of_lt_two {n : ℕ+} : n < 2 → n = 1 := by
intro h; apply le_antisymm; swap
· apply PNat.one_le
· exact PNat.lt_add_one_iff.1 h
#align pnat.eq_one_of_lt_two PNat.eq_one_of_lt_two
section Prime
/-! ### Prime numbers -/
/-- Primality predicate for `ℕ+`, defined in terms of `Nat.Prime`. -/
def Prime (p : ℕ+) : Prop :=
(p : ℕ).Prime
#align pnat.prime PNat.Prime
theorem Prime.one_lt {p : ℕ+} : p.Prime → 1 < p :=
Nat.Prime.one_lt
#align pnat.prime.one_lt PNat.Prime.one_lt
theorem prime_two : (2 : ℕ+).Prime :=
Nat.prime_two
#align pnat.prime_two PNat.prime_two
instance {p : ℕ+} [h : Fact p.Prime] : Fact (p : ℕ).Prime := h
instance fact_prime_two : Fact (2 : ℕ+).Prime :=
⟨prime_two⟩
theorem prime_three : (3 : ℕ+).Prime :=
Nat.prime_three
instance fact_prime_three : Fact (3 : ℕ+).Prime :=
⟨prime_three⟩
theorem prime_five : (5 : ℕ+).Prime :=
Nat.prime_five
instance fact_prime_five : Fact (5 : ℕ+).Prime :=
⟨prime_five⟩
theorem dvd_prime {p m : ℕ+} (pp : p.Prime) : m ∣ p ↔ m = 1 ∨ m = p := by
rw [PNat.dvd_iff]
rw [Nat.dvd_prime pp]
simp
#align pnat.dvd_prime PNat.dvd_prime
theorem Prime.ne_one {p : ℕ+} : p.Prime → p ≠ 1 := by
intro pp
intro contra
apply Nat.Prime.ne_one pp
rw [PNat.coe_eq_one_iff]
apply contra
#align pnat.prime.ne_one PNat.Prime.ne_one
@[simp]
theorem not_prime_one : ¬(1 : ℕ+).Prime :=
Nat.not_prime_one
#align pnat.not_prime_one PNat.not_prime_one
theorem Prime.not_dvd_one {p : ℕ+} : p.Prime → ¬p ∣ 1 := fun pp : p.Prime => by
rw [dvd_iff]
apply Nat.Prime.not_dvd_one pp
#align pnat.prime.not_dvd_one PNat.Prime.not_dvd_one
theorem exists_prime_and_dvd {n : ℕ+} (hn : n ≠ 1) : ∃ p : ℕ+, p.Prime ∧ p ∣ n := by
obtain ⟨p, hp⟩ := Nat.exists_prime_and_dvd (mt coe_eq_one_iff.mp hn)
exists (⟨p, Nat.Prime.pos hp.left⟩ : ℕ+); rw [dvd_iff]; apply hp
#align pnat.exists_prime_and_dvd PNat.exists_prime_and_dvd
end Prime
section Coprime
/-! ### Coprime numbers and gcd -/
/-- Two pnats are coprime if their gcd is 1. -/
def Coprime (m n : ℕ+) : Prop :=
m.gcd n = 1
#align pnat.coprime PNat.Coprime
@[simp, norm_cast]
theorem coprime_coe {m n : ℕ+} : Nat.Coprime ↑m ↑n ↔ m.Coprime n := by
unfold Nat.Coprime Coprime
rw [← coe_inj]
simp
#align pnat.coprime_coe PNat.coprime_coe
theorem Coprime.mul {k m n : ℕ+} : m.Coprime k → n.Coprime k → (m * n).Coprime k := by
repeat rw [← coprime_coe]
rw [mul_coe]
apply Nat.Coprime.mul
#align pnat.coprime.mul PNat.Coprime.mul
theorem Coprime.mul_right {k m n : ℕ+} : k.Coprime m → k.Coprime n → k.Coprime (m * n) := by
repeat rw [← coprime_coe]
rw [mul_coe]
apply Nat.Coprime.mul_right
#align pnat.coprime.mul_right PNat.Coprime.mul_right
theorem gcd_comm {m n : ℕ+} : m.gcd n = n.gcd m := by
apply eq
simp only [gcd_coe]
apply Nat.gcd_comm
#align pnat.gcd_comm PNat.gcd_comm
theorem gcd_eq_left_iff_dvd {m n : ℕ+} : m ∣ n ↔ m.gcd n = m := by
rw [dvd_iff]
rw [Nat.gcd_eq_left_iff_dvd]
rw [← coe_inj]
simp
#align pnat.gcd_eq_left_iff_dvd PNat.gcd_eq_left_iff_dvd
theorem gcd_eq_right_iff_dvd {m n : ℕ+} : m ∣ n ↔ n.gcd m = m := by
rw [gcd_comm]
apply gcd_eq_left_iff_dvd
#align pnat.gcd_eq_right_iff_dvd PNat.gcd_eq_right_iff_dvd
theorem Coprime.gcd_mul_left_cancel (m : ℕ+) {n k : ℕ+} :
k.Coprime n → (k * m).gcd n = m.gcd n := by
intro h; apply eq; simp only [gcd_coe, mul_coe]
apply Nat.Coprime.gcd_mul_left_cancel; simpa
#align pnat.coprime.gcd_mul_left_cancel PNat.Coprime.gcd_mul_left_cancel
theorem Coprime.gcd_mul_right_cancel (m : ℕ+) {n k : ℕ+} :
k.Coprime n → (m * k).gcd n = m.gcd n := by rw [mul_comm]; apply Coprime.gcd_mul_left_cancel
#align pnat.coprime.gcd_mul_right_cancel PNat.Coprime.gcd_mul_right_cancel
theorem Coprime.gcd_mul_left_cancel_right (m : ℕ+) {n k : ℕ+} :
k.Coprime m → m.gcd (k * n) = m.gcd n := by
intro h; iterate 2 rw [gcd_comm]; symm;
apply Coprime.gcd_mul_left_cancel _ h
#align pnat.coprime.gcd_mul_left_cancel_right PNat.Coprime.gcd_mul_left_cancel_right
theorem Coprime.gcd_mul_right_cancel_right (m : ℕ+) {n k : ℕ+} :
k.Coprime m → m.gcd (n * k) = m.gcd n := by
rw [mul_comm];
apply Coprime.gcd_mul_left_cancel_right
#align pnat.coprime.gcd_mul_right_cancel_right PNat.Coprime.gcd_mul_right_cancel_right
@[simp]
theorem one_gcd {n : ℕ+} : gcd 1 n = 1 := by
rw [← gcd_eq_left_iff_dvd]
apply one_dvd
#align pnat.one_gcd PNat.one_gcd
@[simp]
theorem gcd_one {n : ℕ+} : gcd n 1 = 1 := by
rw [gcd_comm]
apply one_gcd
#align pnat.gcd_one PNat.gcd_one
@[symm]
theorem Coprime.symm {m n : ℕ+} : m.Coprime n → n.Coprime m := by
unfold Coprime
rw [gcd_comm]
simp
#align pnat.coprime.symm PNat.Coprime.symm
@[simp]
theorem one_coprime {n : ℕ+} : (1 : ℕ+).Coprime n :=
one_gcd
#align pnat.one_coprime PNat.one_coprime
@[simp]
theorem coprime_one {n : ℕ+} : n.Coprime 1 :=
Coprime.symm one_coprime
#align pnat.coprime_one PNat.coprime_one
theorem Coprime.coprime_dvd_left {m k n : ℕ+} : m ∣ k → k.Coprime n → m.Coprime n := by
rw [dvd_iff]
repeat rw [← coprime_coe]
apply Nat.Coprime.coprime_dvd_left
#align pnat.coprime.coprime_dvd_left PNat.Coprime.coprime_dvd_left
theorem Coprime.factor_eq_gcd_left {a b m n : ℕ+} (cop : m.Coprime n) (am : a ∣ m) (bn : b ∣ n) :
a = (a * b).gcd m := by
rw [gcd_eq_left_iff_dvd] at am
conv_lhs => rw [← am]
rw [eq_comm]
apply Coprime.gcd_mul_right_cancel a
apply Coprime.coprime_dvd_left bn cop.symm
#align pnat.coprime.factor_eq_gcd_left PNat.Coprime.factor_eq_gcd_left
| Mathlib/Data/PNat/Prime.lean | 288 | 289 | theorem Coprime.factor_eq_gcd_right {a b m n : ℕ+} (cop : m.Coprime n) (am : a ∣ m) (bn : b ∣ n) :
a = (b * a).gcd m := by | rw [mul_comm]; apply Coprime.factor_eq_gcd_left cop am bn
|
/-
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
-/
import Mathlib.Algebra.GroupPower.IterateHom
import Mathlib.Algebra.Polynomial.Eval
import Mathlib.GroupTheory.GroupAction.Ring
#align_import data.polynomial.derivative from "leanprover-community/mathlib"@"bbeb185db4ccee8ed07dc48449414ebfa39cb821"
/-!
# The derivative map on polynomials
## Main definitions
* `Polynomial.derivative`: The formal derivative of polynomials, expressed as a linear map.
-/
noncomputable section
open Finset
open Polynomial
namespace Polynomial
universe u v w y z
variable {R : Type u} {S : Type v} {T : Type w} {ι : Type y} {A : Type z} {a b : R} {n : ℕ}
section Derivative
section Semiring
variable [Semiring R]
/-- `derivative p` is the formal derivative of the polynomial `p` -/
def derivative : R[X] →ₗ[R] R[X] where
toFun p := p.sum fun n a => C (a * n) * X ^ (n - 1)
map_add' p q := by
dsimp only
rw [sum_add_index] <;>
simp only [add_mul, forall_const, RingHom.map_add, eq_self_iff_true, zero_mul,
RingHom.map_zero]
map_smul' a p := by
dsimp; rw [sum_smul_index] <;>
simp only [mul_sum, ← C_mul', mul_assoc, coeff_C_mul, RingHom.map_mul, forall_const, zero_mul,
RingHom.map_zero, sum]
#align polynomial.derivative Polynomial.derivative
theorem derivative_apply (p : R[X]) : derivative p = p.sum fun n a => C (a * n) * X ^ (n - 1) :=
rfl
#align polynomial.derivative_apply Polynomial.derivative_apply
theorem coeff_derivative (p : R[X]) (n : ℕ) :
coeff (derivative p) n = coeff p (n + 1) * (n + 1) := by
rw [derivative_apply]
simp only [coeff_X_pow, coeff_sum, coeff_C_mul]
rw [sum, Finset.sum_eq_single (n + 1)]
· simp only [Nat.add_succ_sub_one, add_zero, mul_one, if_true, eq_self_iff_true]; norm_cast
· intro b
cases b
· intros
rw [Nat.cast_zero, mul_zero, zero_mul]
· intro _ H
rw [Nat.add_one_sub_one, if_neg (mt (congr_arg Nat.succ) H.symm), mul_zero]
· rw [if_pos (add_tsub_cancel_right n 1).symm, mul_one, Nat.cast_add, Nat.cast_one,
mem_support_iff]
intro h
push_neg at h
simp [h]
#align polynomial.coeff_derivative Polynomial.coeff_derivative
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_zero : derivative (0 : R[X]) = 0 :=
derivative.map_zero
#align polynomial.derivative_zero Polynomial.derivative_zero
theorem iterate_derivative_zero {k : ℕ} : derivative^[k] (0 : R[X]) = 0 :=
iterate_map_zero derivative k
#align polynomial.iterate_derivative_zero Polynomial.iterate_derivative_zero
@[simp]
theorem derivative_monomial (a : R) (n : ℕ) :
derivative (monomial n a) = monomial (n - 1) (a * n) := by
rw [derivative_apply, sum_monomial_index, C_mul_X_pow_eq_monomial]
simp
#align polynomial.derivative_monomial Polynomial.derivative_monomial
theorem derivative_C_mul_X (a : R) : derivative (C a * X) = C a := by
simp [C_mul_X_eq_monomial, derivative_monomial, Nat.cast_one, mul_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C_mul_X Polynomial.derivative_C_mul_X
theorem derivative_C_mul_X_pow (a : R) (n : ℕ) :
derivative (C a * X ^ n) = C (a * n) * X ^ (n - 1) := by
rw [C_mul_X_pow_eq_monomial, C_mul_X_pow_eq_monomial, derivative_monomial]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C_mul_X_pow Polynomial.derivative_C_mul_X_pow
theorem derivative_C_mul_X_sq (a : R) : derivative (C a * X ^ 2) = C (a * 2) * X := by
rw [derivative_C_mul_X_pow, Nat.cast_two, pow_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C_mul_X_sq Polynomial.derivative_C_mul_X_sq
@[simp]
theorem derivative_X_pow (n : ℕ) : derivative (X ^ n : R[X]) = C (n : R) * X ^ (n - 1) := by
convert derivative_C_mul_X_pow (1 : R) n <;> simp
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_pow Polynomial.derivative_X_pow
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_X_sq : derivative (X ^ 2 : R[X]) = C 2 * X := by
rw [derivative_X_pow, Nat.cast_two, pow_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_sq Polynomial.derivative_X_sq
@[simp]
theorem derivative_C {a : R} : derivative (C a) = 0 := by simp [derivative_apply]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C Polynomial.derivative_C
theorem derivative_of_natDegree_zero {p : R[X]} (hp : p.natDegree = 0) : derivative p = 0 := by
rw [eq_C_of_natDegree_eq_zero hp, derivative_C]
#align polynomial.derivative_of_nat_degree_zero Polynomial.derivative_of_natDegree_zero
@[simp]
theorem derivative_X : derivative (X : R[X]) = 1 :=
(derivative_monomial _ _).trans <| by simp
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X Polynomial.derivative_X
@[simp]
theorem derivative_one : derivative (1 : R[X]) = 0 :=
derivative_C
#align polynomial.derivative_one Polynomial.derivative_one
#noalign polynomial.derivative_bit0
#noalign polynomial.derivative_bit1
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_add {f g : R[X]} : derivative (f + g) = derivative f + derivative g :=
derivative.map_add f g
#align polynomial.derivative_add Polynomial.derivative_add
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_X_add_C (c : R) : derivative (X + C c) = 1 := by
rw [derivative_add, derivative_X, derivative_C, add_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_add_C Polynomial.derivative_X_add_C
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_sum {s : Finset ι} {f : ι → R[X]} :
derivative (∑ b ∈ s, f b) = ∑ b ∈ s, derivative (f b) :=
map_sum ..
#align polynomial.derivative_sum Polynomial.derivative_sum
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_smul {S : Type*} [Monoid S] [DistribMulAction S R] [IsScalarTower S R R] (s : S)
(p : R[X]) : derivative (s • p) = s • derivative p :=
derivative.map_smul_of_tower s p
#align polynomial.derivative_smul Polynomial.derivative_smul
@[simp]
theorem iterate_derivative_smul {S : Type*} [Monoid S] [DistribMulAction S R] [IsScalarTower S R R]
(s : S) (p : R[X]) (k : ℕ) : derivative^[k] (s • p) = s • derivative^[k] p := by
induction' k with k ih generalizing p
· simp
· simp [ih]
#align polynomial.iterate_derivative_smul Polynomial.iterate_derivative_smul
@[simp]
theorem iterate_derivative_C_mul (a : R) (p : R[X]) (k : ℕ) :
derivative^[k] (C a * p) = C a * derivative^[k] p := by
simp_rw [← smul_eq_C_mul, iterate_derivative_smul]
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_C_mul Polynomial.iterate_derivative_C_mul
theorem of_mem_support_derivative {p : R[X]} {n : ℕ} (h : n ∈ p.derivative.support) :
n + 1 ∈ p.support :=
mem_support_iff.2 fun h1 : p.coeff (n + 1) = 0 =>
mem_support_iff.1 h <| show p.derivative.coeff n = 0 by rw [coeff_derivative, h1, zero_mul]
#align polynomial.of_mem_support_derivative Polynomial.of_mem_support_derivative
theorem degree_derivative_lt {p : R[X]} (hp : p ≠ 0) : p.derivative.degree < p.degree :=
(Finset.sup_lt_iff <| bot_lt_iff_ne_bot.2 <| mt degree_eq_bot.1 hp).2 fun n hp =>
lt_of_lt_of_le (WithBot.coe_lt_coe.2 n.lt_succ_self) <|
Finset.le_sup <| of_mem_support_derivative hp
#align polynomial.degree_derivative_lt Polynomial.degree_derivative_lt
theorem degree_derivative_le {p : R[X]} : p.derivative.degree ≤ p.degree :=
letI := Classical.decEq R
if H : p = 0 then le_of_eq <| by rw [H, derivative_zero] else (degree_derivative_lt H).le
#align polynomial.degree_derivative_le Polynomial.degree_derivative_le
theorem natDegree_derivative_lt {p : R[X]} (hp : p.natDegree ≠ 0) :
p.derivative.natDegree < p.natDegree := by
rcases eq_or_ne (derivative p) 0 with hp' | hp'
· rw [hp', Polynomial.natDegree_zero]
exact hp.bot_lt
· rw [natDegree_lt_natDegree_iff hp']
exact degree_derivative_lt fun h => hp (h.symm ▸ natDegree_zero)
#align polynomial.nat_degree_derivative_lt Polynomial.natDegree_derivative_lt
theorem natDegree_derivative_le (p : R[X]) : p.derivative.natDegree ≤ p.natDegree - 1 := by
by_cases p0 : p.natDegree = 0
· simp [p0, derivative_of_natDegree_zero]
· exact Nat.le_sub_one_of_lt (natDegree_derivative_lt p0)
#align polynomial.nat_degree_derivative_le Polynomial.natDegree_derivative_le
theorem natDegree_iterate_derivative (p : R[X]) (k : ℕ) :
(derivative^[k] p).natDegree ≤ p.natDegree - k := by
induction k with
| zero => rw [Function.iterate_zero_apply, Nat.sub_zero]
| succ d hd =>
rw [Function.iterate_succ_apply', Nat.sub_succ']
exact (natDegree_derivative_le _).trans <| Nat.sub_le_sub_right hd 1
@[simp]
theorem derivative_natCast {n : ℕ} : derivative (n : R[X]) = 0 := by
rw [← map_natCast C n]
exact derivative_C
#align polynomial.derivative_nat_cast Polynomial.derivative_natCast
@[deprecated (since := "2024-04-17")]
alias derivative_nat_cast := derivative_natCast
-- Porting note (#10756): new theorem
@[simp]
theorem derivative_ofNat (n : ℕ) [n.AtLeastTwo] :
derivative (no_index (OfNat.ofNat n) : R[X]) = 0 :=
derivative_natCast
theorem iterate_derivative_eq_zero {p : R[X]} {x : ℕ} (hx : p.natDegree < x) :
Polynomial.derivative^[x] p = 0 := by
induction' h : p.natDegree using Nat.strong_induction_on with _ ih generalizing p x
subst h
obtain ⟨t, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (pos_of_gt hx).ne'
rw [Function.iterate_succ_apply]
by_cases hp : p.natDegree = 0
· rw [derivative_of_natDegree_zero hp, iterate_derivative_zero]
have := natDegree_derivative_lt hp
exact ih _ this (this.trans_le <| Nat.le_of_lt_succ hx) rfl
#align polynomial.iterate_derivative_eq_zero Polynomial.iterate_derivative_eq_zero
@[simp]
theorem iterate_derivative_C {k} (h : 0 < k) : derivative^[k] (C a : R[X]) = 0 :=
iterate_derivative_eq_zero <| (natDegree_C _).trans_lt h
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_C Polynomial.iterate_derivative_C
@[simp]
theorem iterate_derivative_one {k} (h : 0 < k) : derivative^[k] (1 : R[X]) = 0 :=
iterate_derivative_C h
#align polynomial.iterate_derivative_one Polynomial.iterate_derivative_one
@[simp]
theorem iterate_derivative_X {k} (h : 1 < k) : derivative^[k] (X : R[X]) = 0 :=
iterate_derivative_eq_zero <| natDegree_X_le.trans_lt h
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_X Polynomial.iterate_derivative_X
theorem natDegree_eq_zero_of_derivative_eq_zero [NoZeroSMulDivisors ℕ R] {f : R[X]}
(h : derivative f = 0) : f.natDegree = 0 := by
rcases eq_or_ne f 0 with (rfl | hf)
· exact natDegree_zero
rw [natDegree_eq_zero_iff_degree_le_zero]
by_contra! f_nat_degree_pos
rw [← natDegree_pos_iff_degree_pos] at f_nat_degree_pos
let m := f.natDegree - 1
have hm : m + 1 = f.natDegree := tsub_add_cancel_of_le f_nat_degree_pos
have h2 := coeff_derivative f m
rw [Polynomial.ext_iff] at h
rw [h m, coeff_zero, ← Nat.cast_add_one, ← nsmul_eq_mul', eq_comm, smul_eq_zero] at h2
replace h2 := h2.resolve_left m.succ_ne_zero
rw [hm, ← leadingCoeff, leadingCoeff_eq_zero] at h2
exact hf h2
#align polynomial.nat_degree_eq_zero_of_derivative_eq_zero Polynomial.natDegree_eq_zero_of_derivative_eq_zero
theorem eq_C_of_derivative_eq_zero [NoZeroSMulDivisors ℕ R] {f : R[X]} (h : derivative f = 0) :
f = C (f.coeff 0) :=
eq_C_of_natDegree_eq_zero <| natDegree_eq_zero_of_derivative_eq_zero h
set_option linter.uppercaseLean3 false in
#align polynomial.eq_C_of_derivative_eq_zero Polynomial.eq_C_of_derivative_eq_zero
@[simp]
theorem derivative_mul {f g : R[X]} : derivative (f * g) = derivative f * g + f * derivative g := by
induction f using Polynomial.induction_on' with
| h_add => simp only [add_mul, map_add, add_assoc, add_left_comm, *]
| h_monomial m a =>
induction g using Polynomial.induction_on' with
| h_add => simp only [mul_add, map_add, add_assoc, add_left_comm, *]
| h_monomial n b =>
simp only [monomial_mul_monomial, derivative_monomial]
simp only [mul_assoc, (Nat.cast_commute _ _).eq, Nat.cast_add, mul_add, map_add]
cases m with
| zero => simp only [zero_add, Nat.cast_zero, mul_zero, map_zero]
| succ m =>
cases n with
| zero => simp only [add_zero, Nat.cast_zero, mul_zero, map_zero]
| succ n =>
simp only [Nat.add_succ_sub_one, add_tsub_cancel_right]
rw [add_assoc, add_comm n 1]
#align polynomial.derivative_mul Polynomial.derivative_mul
theorem derivative_eval (p : R[X]) (x : R) :
p.derivative.eval x = p.sum fun n a => a * n * x ^ (n - 1) := by
simp_rw [derivative_apply, eval_sum, eval_mul_X_pow, eval_C]
#align polynomial.derivative_eval Polynomial.derivative_eval
@[simp]
theorem derivative_map [Semiring S] (p : R[X]) (f : R →+* S) :
derivative (p.map f) = p.derivative.map f := by
let n := max p.natDegree (map f p).natDegree
rw [derivative_apply, derivative_apply]
rw [sum_over_range' _ _ (n + 1) ((le_max_left _ _).trans_lt (lt_add_one _))]
on_goal 1 => rw [sum_over_range' _ _ (n + 1) ((le_max_right _ _).trans_lt (lt_add_one _))]
· simp only [Polynomial.map_sum, Polynomial.map_mul, Polynomial.map_C, map_mul, coeff_map,
map_natCast, Polynomial.map_natCast, Polynomial.map_pow, map_X]
all_goals intro n; rw [zero_mul, C_0, zero_mul]
#align polynomial.derivative_map Polynomial.derivative_map
@[simp]
theorem iterate_derivative_map [Semiring S] (p : R[X]) (f : R →+* S) (k : ℕ) :
Polynomial.derivative^[k] (p.map f) = (Polynomial.derivative^[k] p).map f := by
induction' k with k ih generalizing p
· simp
· simp only [ih, Function.iterate_succ, Polynomial.derivative_map, Function.comp_apply]
#align polynomial.iterate_derivative_map Polynomial.iterate_derivative_map
theorem derivative_natCast_mul {n : ℕ} {f : R[X]} :
derivative ((n : R[X]) * f) = n * derivative f := by
simp
#align polynomial.derivative_nat_cast_mul Polynomial.derivative_natCast_mul
@[deprecated (since := "2024-04-17")]
alias derivative_nat_cast_mul := derivative_natCast_mul
@[simp]
| Mathlib/Algebra/Polynomial/Derivative.lean | 342 | 344 | theorem iterate_derivative_natCast_mul {n k : ℕ} {f : R[X]} :
derivative^[k] ((n : R[X]) * f) = n * derivative^[k] f := by |
induction' k with k ih generalizing f <;> simp [*]
|
/-
Copyright (c) 2022 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Yaël Dillies
-/
import Mathlib.MeasureTheory.Integral.SetIntegral
#align_import measure_theory.integral.average from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520"
/-!
# Integral average of a function
In this file we define `MeasureTheory.average μ f` (notation: `⨍ x, f x ∂μ`) to be the average
value of `f` with respect to measure `μ`. It is defined as `∫ x, f x ∂((μ univ)⁻¹ • μ)`, so it
is equal to zero if `f` is not integrable or if `μ` is an infinite measure. If `μ` is a probability
measure, then the average of any function is equal to its integral.
For the average on a set, we use `⨍ x in s, f x ∂μ` (notation for `⨍ x, f x ∂(μ.restrict s)`). For
average w.r.t. the volume, one can omit `∂volume`.
Both have a version for the Lebesgue integral rather than Bochner.
We prove several version of the first moment method: An integrable function is below/above its
average on a set of positive measure.
## Implementation notes
The average is defined as an integral over `(μ univ)⁻¹ • μ` so that all theorems about Bochner
integrals work for the average without modifications. For theorems that require integrability of a
function, we provide a convenience lemma `MeasureTheory.Integrable.to_average`.
## TODO
Provide the first moment method for the Lebesgue integral as well. A draft is available on branch
`first_moment_lintegral` in mathlib3 repository.
## Tags
integral, center mass, average value
-/
open ENNReal MeasureTheory MeasureTheory.Measure Metric Set Filter TopologicalSpace Function
open scoped Topology ENNReal Convex
variable {α E F : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E] [NormedSpace ℝ E]
[CompleteSpace E] [NormedAddCommGroup F] [NormedSpace ℝ F] [CompleteSpace F] {μ ν : Measure α}
{s t : Set α}
/-!
### Average value of a function w.r.t. a measure
The (Bochner, Lebesgue) average value of a function `f` w.r.t. a measure `μ` (notation:
`⨍ x, f x ∂μ`, `⨍⁻ x, f x ∂μ`) is defined as the (Bochner, Lebesgue) integral divided by the total
measure, so it is equal to zero if `μ` is an infinite measure, and (typically) equal to infinity if
`f` is not integrable. If `μ` is a probability measure, then the average of any function is equal to
its integral.
-/
namespace MeasureTheory
section ENNReal
variable (μ) {f g : α → ℝ≥0∞}
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`, denoted `⨍⁻ x, f x ∂μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def laverage (f : α → ℝ≥0∞) := ∫⁻ x, f x ∂(μ univ)⁻¹ • μ
#align measure_theory.laverage MeasureTheory.laverage
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => laverage μ r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure.
It is equal to `(volume univ)⁻¹ * ∫⁻ x, f x`, so it takes value zero if the space has infinite
measure. In a probability space, the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x`, defined as `⨍⁻ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => laverage volume f) => r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ s)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `s` has infinite measure. If `s`
has measure `1`, then the average of any function is equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => laverage (Measure.restrict μ s) r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume s)⁻¹ * ∫⁻ x, f x`, so it takes value zero if `s` has infinite measure. If
`s` has measure `1`, then the average of any function is equal to its integral. -/
notation3 (prettyPrint := false)
"⨍⁻ "(...)" in "s", "r:60:(scoped f => laverage Measure.restrict volume s f) => r
@[simp]
theorem laverage_zero : ⨍⁻ _x, (0 : ℝ≥0∞) ∂μ = 0 := by rw [laverage, lintegral_zero]
#align measure_theory.laverage_zero MeasureTheory.laverage_zero
@[simp]
theorem laverage_zero_measure (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂(0 : Measure α) = 0 := by simp [laverage]
#align measure_theory.laverage_zero_measure MeasureTheory.laverage_zero_measure
theorem laverage_eq' (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂(μ univ)⁻¹ • μ := rfl
#align measure_theory.laverage_eq' MeasureTheory.laverage_eq'
theorem laverage_eq (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = (∫⁻ x, f x ∂μ) / μ univ := by
rw [laverage_eq', lintegral_smul_measure, ENNReal.div_eq_inv_mul]
#align measure_theory.laverage_eq MeasureTheory.laverage_eq
theorem laverage_eq_lintegral [IsProbabilityMeasure μ] (f : α → ℝ≥0∞) :
⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by rw [laverage, measure_univ, inv_one, one_smul]
#align measure_theory.laverage_eq_lintegral MeasureTheory.laverage_eq_lintegral
@[simp]
theorem measure_mul_laverage [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
μ univ * ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, lintegral_zero_measure, laverage_zero_measure, mul_zero]
· rw [laverage_eq, ENNReal.mul_div_cancel' (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
#align measure_theory.measure_mul_laverage MeasureTheory.measure_mul_laverage
theorem setLaverage_eq (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = (∫⁻ x in s, f x ∂μ) / μ s := by rw [laverage_eq, restrict_apply_univ]
#align measure_theory.set_laverage_eq MeasureTheory.setLaverage_eq
theorem setLaverage_eq' (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = ∫⁻ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [laverage_eq', restrict_apply_univ]
#align measure_theory.set_laverage_eq' MeasureTheory.setLaverage_eq'
variable {μ}
theorem laverage_congr {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) : ⨍⁻ x, f x ∂μ = ⨍⁻ x, g x ∂μ := by
simp only [laverage_eq, lintegral_congr_ae h]
#align measure_theory.laverage_congr MeasureTheory.laverage_congr
theorem setLaverage_congr (h : s =ᵐ[μ] t) : ⨍⁻ x in s, f x ∂μ = ⨍⁻ x in t, f x ∂μ := by
simp only [setLaverage_eq, set_lintegral_congr h, measure_congr h]
#align measure_theory.set_laverage_congr MeasureTheory.setLaverage_congr
theorem setLaverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍⁻ x in s, f x ∂μ = ⨍⁻ x in s, g x ∂μ := by
simp only [laverage_eq, set_lintegral_congr_fun hs h]
#align measure_theory.set_laverage_congr_fun MeasureTheory.setLaverage_congr_fun
theorem laverage_lt_top (hf : ∫⁻ x, f x ∂μ ≠ ∞) : ⨍⁻ x, f x ∂μ < ∞ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq]
exact div_lt_top hf (measure_univ_ne_zero.2 hμ)
#align measure_theory.laverage_lt_top MeasureTheory.laverage_lt_top
theorem setLaverage_lt_top : ∫⁻ x in s, f x ∂μ ≠ ∞ → ⨍⁻ x in s, f x ∂μ < ∞ :=
laverage_lt_top
#align measure_theory.set_laverage_lt_top MeasureTheory.setLaverage_lt_top
theorem laverage_add_measure :
⨍⁻ x, f x ∂(μ + ν) =
μ univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂ν := by
by_cases hμ : IsFiniteMeasure μ; swap
· rw [not_isFiniteMeasure_iff] at hμ
simp [laverage_eq, hμ]
by_cases hν : IsFiniteMeasure ν; swap
· rw [not_isFiniteMeasure_iff] at hν
simp [laverage_eq, hν]
haveI := hμ; haveI := hν
simp only [← ENNReal.mul_div_right_comm, measure_mul_laverage, ← ENNReal.add_div,
← lintegral_add_measure, ← Measure.add_apply, ← laverage_eq]
#align measure_theory.laverage_add_measure MeasureTheory.laverage_add_measure
theorem measure_mul_setLaverage (f : α → ℝ≥0∞) (h : μ s ≠ ∞) :
μ s * ⨍⁻ x in s, f x ∂μ = ∫⁻ x in s, f x ∂μ := by
have := Fact.mk h.lt_top
rw [← measure_mul_laverage, restrict_apply_univ]
#align measure_theory.measure_mul_set_laverage MeasureTheory.measure_mul_setLaverage
theorem laverage_union (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ) :
⨍⁻ x in s ∪ t, f x ∂μ =
μ s / (μ s + μ t) * ⨍⁻ x in s, f x ∂μ + μ t / (μ s + μ t) * ⨍⁻ x in t, f x ∂μ := by
rw [restrict_union₀ hd ht, laverage_add_measure, restrict_apply_univ, restrict_apply_univ]
#align measure_theory.laverage_union MeasureTheory.laverage_union
theorem laverage_union_mem_openSegment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in t, f x ∂μ) := by
refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), ENNReal.div_pos hs₀ <| add_ne_top.2 ⟨hsμ, htμ⟩,
ENNReal.div_pos ht₀ <| add_ne_top.2 ⟨hsμ, htμ⟩, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
#align measure_theory.laverage_union_mem_open_segment MeasureTheory.laverage_union_mem_openSegment
theorem laverage_union_mem_segment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ [⨍⁻ x in s, f x ∂μ -[ℝ≥0∞] ⨍⁻ x in t, f x ∂μ] := by
by_cases hs₀ : μ s = 0
· rw [← ae_eq_empty] at hs₀
rw [restrict_congr_set (hs₀.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), zero_le _, zero_le _, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
#align measure_theory.laverage_union_mem_segment MeasureTheory.laverage_union_mem_segment
theorem laverage_mem_openSegment_compl_self [IsFiniteMeasure μ] (hs : NullMeasurableSet s μ)
(hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) :
⨍⁻ x, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
laverage_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _)
#align measure_theory.laverage_mem_open_segment_compl_self MeasureTheory.laverage_mem_openSegment_compl_self
@[simp]
theorem laverage_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : ℝ≥0∞) :
⨍⁻ _x, c ∂μ = c := by
simp only [laverage, lintegral_const, measure_univ, mul_one]
#align measure_theory.laverage_const MeasureTheory.laverage_const
theorem setLaverage_const (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : ℝ≥0∞) : ⨍⁻ _x in s, c ∂μ = c := by
simp only [setLaverage_eq, lintegral_const, Measure.restrict_apply, MeasurableSet.univ,
univ_inter, div_eq_mul_inv, mul_assoc, ENNReal.mul_inv_cancel hs₀ hs, mul_one]
#align measure_theory.set_laverage_const MeasureTheory.setLaverage_const
theorem laverage_one [IsFiniteMeasure μ] [NeZero μ] : ⨍⁻ _x, (1 : ℝ≥0∞) ∂μ = 1 :=
laverage_const _ _
#align measure_theory.laverage_one MeasureTheory.laverage_one
theorem setLaverage_one (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) : ⨍⁻ _x in s, (1 : ℝ≥0∞) ∂μ = 1 :=
setLaverage_const hs₀ hs _
#align measure_theory.set_laverage_one MeasureTheory.setLaverage_one
-- Porting note: Dropped `simp` because of `simp` seeing through `1 : α → ℝ≥0∞` and applying
-- `lintegral_const`. This is suboptimal.
theorem lintegral_laverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
∫⁻ _x, ⨍⁻ a, f a ∂μ ∂μ = ∫⁻ x, f x ∂μ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [lintegral_const, laverage_eq,
ENNReal.div_mul_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
#align measure_theory.lintegral_laverage MeasureTheory.lintegral_laverage
theorem setLintegral_setLaverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ _x in s, ⨍⁻ a in s, f a ∂μ ∂μ = ∫⁻ x in s, f x ∂μ :=
lintegral_laverage _ _
#align measure_theory.set_lintegral_set_laverage MeasureTheory.setLintegral_setLaverage
end ENNReal
section NormedAddCommGroup
variable (μ)
variable {f g : α → E}
/-- Average value of a function `f` w.r.t. a measure `μ`, denoted `⨍ x, f x ∂μ`.
It is equal to `(μ univ).toReal⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def average (f : α → E) :=
∫ x, f x ∂(μ univ)⁻¹ • μ
#align measure_theory.average MeasureTheory.average
/-- Average value of a function `f` w.r.t. a measure `μ`.
It is equal to `(μ univ).toReal⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => average μ r
/-- Average value of a function `f` w.r.t. to the standard measure.
It is equal to `(volume univ).toReal⁻¹ * ∫ x, f x`, so it takes value zero if `f` is not integrable
or if the space has infinite measure. In a probability space, the average of any function is equal
to its integral.
For the average on a set, use `⨍ x in s, f x`, defined as `⨍ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => average volume f) => r
/-- Average value of a function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ s).toReal⁻¹ * ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable on
`s` or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is
equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => average (Measure.restrict μ s) r
/-- Average value of a function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume s).toReal⁻¹ * ∫ x, f x`, so it takes value zero `f` is not integrable on `s`
or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is equal to
its integral. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => average (Measure.restrict volume s) f) => r
@[simp]
theorem average_zero : ⨍ _, (0 : E) ∂μ = 0 := by rw [average, integral_zero]
#align measure_theory.average_zero MeasureTheory.average_zero
@[simp]
theorem average_zero_measure (f : α → E) : ⨍ x, f x ∂(0 : Measure α) = 0 := by
rw [average, smul_zero, integral_zero_measure]
#align measure_theory.average_zero_measure MeasureTheory.average_zero_measure
@[simp]
theorem average_neg (f : α → E) : ⨍ x, -f x ∂μ = -⨍ x, f x ∂μ :=
integral_neg f
#align measure_theory.average_neg MeasureTheory.average_neg
theorem average_eq' (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂(μ univ)⁻¹ • μ :=
rfl
#align measure_theory.average_eq' MeasureTheory.average_eq'
theorem average_eq (f : α → E) : ⨍ x, f x ∂μ = (μ univ).toReal⁻¹ • ∫ x, f x ∂μ := by
rw [average_eq', integral_smul_measure, ENNReal.toReal_inv]
#align measure_theory.average_eq MeasureTheory.average_eq
theorem average_eq_integral [IsProbabilityMeasure μ] (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rw [average, measure_univ, inv_one, one_smul]
#align measure_theory.average_eq_integral MeasureTheory.average_eq_integral
@[simp]
theorem measure_smul_average [IsFiniteMeasure μ] (f : α → E) :
(μ univ).toReal • ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, integral_zero_measure, average_zero_measure, smul_zero]
· rw [average_eq, smul_inv_smul₀]
refine (ENNReal.toReal_pos ?_ <| measure_ne_top _ _).ne'
rwa [Ne, measure_univ_eq_zero]
#align measure_theory.measure_smul_average MeasureTheory.measure_smul_average
theorem setAverage_eq (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = (μ s).toReal⁻¹ • ∫ x in s, f x ∂μ := by rw [average_eq, restrict_apply_univ]
#align measure_theory.set_average_eq MeasureTheory.setAverage_eq
theorem setAverage_eq' (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = ∫ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [average_eq', restrict_apply_univ]
#align measure_theory.set_average_eq' MeasureTheory.setAverage_eq'
variable {μ}
theorem average_congr {f g : α → E} (h : f =ᵐ[μ] g) : ⨍ x, f x ∂μ = ⨍ x, g x ∂μ := by
simp only [average_eq, integral_congr_ae h]
#align measure_theory.average_congr MeasureTheory.average_congr
theorem setAverage_congr (h : s =ᵐ[μ] t) : ⨍ x in s, f x ∂μ = ⨍ x in t, f x ∂μ := by
simp only [setAverage_eq, setIntegral_congr_set_ae h, measure_congr h]
#align measure_theory.set_average_congr MeasureTheory.setAverage_congr
theorem setAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍ x in s, f x ∂μ = ⨍ x in s, g x ∂μ := by simp only [average_eq, setIntegral_congr_ae hs h]
#align measure_theory.set_average_congr_fun MeasureTheory.setAverage_congr_fun
theorem average_add_measure [IsFiniteMeasure μ] {ν : Measure α} [IsFiniteMeasure ν] {f : α → E}
(hμ : Integrable f μ) (hν : Integrable f ν) :
⨍ x, f x ∂(μ + ν) =
((μ univ).toReal / ((μ univ).toReal + (ν univ).toReal)) • ⨍ x, f x ∂μ +
((ν univ).toReal / ((μ univ).toReal + (ν univ).toReal)) • ⨍ x, f x ∂ν := by
simp only [div_eq_inv_mul, mul_smul, measure_smul_average, ← smul_add,
← integral_add_measure hμ hν, ← ENNReal.toReal_add (measure_ne_top μ _) (measure_ne_top ν _)]
rw [average_eq, Measure.add_apply]
#align measure_theory.average_add_measure MeasureTheory.average_add_measure
theorem average_pair {f : α → E} {g : α → F} (hfi : Integrable f μ) (hgi : Integrable g μ) :
⨍ x, (f x, g x) ∂μ = (⨍ x, f x ∂μ, ⨍ x, g x ∂μ) :=
integral_pair hfi.to_average hgi.to_average
#align measure_theory.average_pair MeasureTheory.average_pair
theorem measure_smul_setAverage (f : α → E) {s : Set α} (h : μ s ≠ ∞) :
(μ s).toReal • ⨍ x in s, f x ∂μ = ∫ x in s, f x ∂μ := by
haveI := Fact.mk h.lt_top
rw [← measure_smul_average, restrict_apply_univ]
#align measure_theory.measure_smul_set_average MeasureTheory.measure_smul_setAverage
theorem average_union {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ =
((μ s).toReal / ((μ s).toReal + (μ t).toReal)) • ⨍ x in s, f x ∂μ +
((μ t).toReal / ((μ s).toReal + (μ t).toReal)) • ⨍ x in t, f x ∂μ := by
haveI := Fact.mk hsμ.lt_top; haveI := Fact.mk htμ.lt_top
rw [restrict_union₀ hd ht, average_add_measure hfs hft, restrict_apply_univ, restrict_apply_univ]
#align measure_theory.average_union MeasureTheory.average_union
theorem average_union_mem_openSegment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞)
(hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in t, f x ∂μ) := by
replace hs₀ : 0 < (μ s).toReal := ENNReal.toReal_pos hs₀ hsμ
replace ht₀ : 0 < (μ t).toReal := ENNReal.toReal_pos ht₀ htμ
exact mem_openSegment_iff_div.mpr
⟨(μ s).toReal, (μ t).toReal, hs₀, ht₀, (average_union hd ht hsμ htμ hfs hft).symm⟩
#align measure_theory.average_union_mem_open_segment MeasureTheory.average_union_mem_openSegment
theorem average_union_mem_segment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ)
(hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ [⨍ x in s, f x ∂μ -[ℝ] ⨍ x in t, f x ∂μ] := by
by_cases hse : μ s = 0
· rw [← ae_eq_empty] at hse
rw [restrict_congr_set (hse.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
mem_segment_iff_div.mpr
⟨(μ s).toReal, (μ t).toReal, ENNReal.toReal_nonneg, ENNReal.toReal_nonneg, ?_,
(average_union hd ht hsμ htμ hfs hft).symm⟩
calc
0 < (μ s).toReal := ENNReal.toReal_pos hse hsμ
_ ≤ _ := le_add_of_nonneg_right ENNReal.toReal_nonneg
#align measure_theory.average_union_mem_segment MeasureTheory.average_union_mem_segment
theorem average_mem_openSegment_compl_self [IsFiniteMeasure μ] {f : α → E} {s : Set α}
(hs : NullMeasurableSet s μ) (hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) (hfi : Integrable f μ) :
⨍ x, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
average_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _) hfi.integrableOn hfi.integrableOn
#align measure_theory.average_mem_open_segment_compl_self MeasureTheory.average_mem_openSegment_compl_self
@[simp]
theorem average_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : E) :
⨍ _x, c ∂μ = c := by
rw [average, integral_const, measure_univ, ENNReal.one_toReal, one_smul]
#align measure_theory.average_const MeasureTheory.average_const
theorem setAverage_const {s : Set α} (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : E) :
⨍ _ in s, c ∂μ = c :=
have := NeZero.mk hs₀; have := Fact.mk hs.lt_top; average_const _ _
#align measure_theory.set_average_const MeasureTheory.setAverage_const
-- Porting note (#10618): was `@[simp]` but `simp` can prove it
theorem integral_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ _, ⨍ a, f a ∂μ ∂μ = ∫ x, f x ∂μ := by simp
#align measure_theory.integral_average MeasureTheory.integral_average
theorem setIntegral_setAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) (s : Set α) :
∫ _ in s, ⨍ a in s, f a ∂μ ∂μ = ∫ x in s, f x ∂μ :=
integral_average _ _
#align measure_theory.set_integral_set_average MeasureTheory.setIntegral_setAverage
theorem integral_sub_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ x, f x - ⨍ a, f a ∂μ ∂μ = 0 := by
by_cases hf : Integrable f μ
· rw [integral_sub hf (integrable_const _), integral_average, sub_self]
refine integral_undef fun h => hf ?_
convert h.add (integrable_const (⨍ a, f a ∂μ))
exact (sub_add_cancel _ _).symm
#align measure_theory.integral_sub_average MeasureTheory.integral_sub_average
theorem setAverage_sub_setAverage (hs : μ s ≠ ∞) (f : α → E) :
∫ x in s, f x - ⨍ a in s, f a ∂μ ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_sub_average _ _
#align measure_theory.set_integral_sub_set_average MeasureTheory.setAverage_sub_setAverage
theorem integral_average_sub [IsFiniteMeasure μ] (hf : Integrable f μ) :
∫ x, ⨍ a, f a ∂μ - f x ∂μ = 0 := by
rw [integral_sub (integrable_const _) hf, integral_average, sub_self]
#align measure_theory.integral_average_sub MeasureTheory.integral_average_sub
theorem setIntegral_setAverage_sub (hs : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∫ x in s, ⨍ a in s, f a ∂μ - f x ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_average_sub hf
#align measure_theory.set_integral_set_average_sub MeasureTheory.setIntegral_setAverage_sub
end NormedAddCommGroup
theorem ofReal_average {f : α → ℝ} (hf : Integrable f μ) (hf₀ : 0 ≤ᵐ[μ] f) :
ENNReal.ofReal (⨍ x, f x ∂μ) = (∫⁻ x, ENNReal.ofReal (f x) ∂μ) / μ univ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [average_eq, smul_eq_mul, ← toReal_inv, ofReal_mul toReal_nonneg,
ofReal_toReal (inv_ne_top.2 <| measure_univ_ne_zero.2 hμ),
ofReal_integral_eq_lintegral_ofReal hf hf₀, ENNReal.div_eq_inv_mul]
#align measure_theory.of_real_average MeasureTheory.ofReal_average
theorem ofReal_setAverage {f : α → ℝ} (hf : IntegrableOn f s μ) (hf₀ : 0 ≤ᵐ[μ.restrict s] f) :
ENNReal.ofReal (⨍ x in s, f x ∂μ) = (∫⁻ x in s, ENNReal.ofReal (f x) ∂μ) / μ s := by
simpa using ofReal_average hf hf₀
#align measure_theory.of_real_set_average MeasureTheory.ofReal_setAverage
theorem toReal_laverage {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (hf' : ∀ᵐ x ∂μ, f x ≠ ∞) :
(⨍⁻ x, f x ∂μ).toReal = ⨍ x, (f x).toReal ∂μ := by
rw [average_eq, laverage_eq, smul_eq_mul, toReal_div, div_eq_inv_mul, ←
integral_toReal hf (hf'.mono fun _ => lt_top_iff_ne_top.2)]
#align measure_theory.to_real_laverage MeasureTheory.toReal_laverage
theorem toReal_setLaverage {f : α → ℝ≥0∞} (hf : AEMeasurable f (μ.restrict s))
(hf' : ∀ᵐ x ∂μ.restrict s, f x ≠ ∞) :
(⨍⁻ x in s, f x ∂μ).toReal = ⨍ x in s, (f x).toReal ∂μ := by
simpa [laverage_eq] using toReal_laverage hf hf'
#align measure_theory.to_real_set_laverage MeasureTheory.toReal_setLaverage
/-! ### First moment method -/
section FirstMomentReal
variable {N : Set α} {f : α → ℝ}
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_setAverage_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | f x ≤ ⨍ a in s, f a ∂μ}) := by
refine pos_iff_ne_zero.2 fun H => ?_
replace H : (μ.restrict s) {x | f x ≤ ⨍ a in s, f a ∂μ} = 0 := by
rwa [restrict_apply₀, inter_comm]
exact AEStronglyMeasurable.nullMeasurableSet_le hf.1 aestronglyMeasurable_const
haveI := Fact.mk hμ₁.lt_top
refine (integral_sub_average (μ.restrict s) f).not_gt ?_
refine (setIntegral_pos_iff_support_of_nonneg_ae ?_ ?_).2 ?_
· refine measure_mono_null (fun x hx ↦ ?_) H
simp only [Pi.zero_apply, sub_nonneg, mem_compl_iff, mem_setOf_eq, not_le] at hx
exact hx.le
· exact hf.sub (integrableOn_const.2 <| Or.inr <| lt_top_iff_ne_top.2 hμ₁)
· rwa [pos_iff_ne_zero, inter_comm, ← diff_compl, ← diff_inter_self_eq_diff, measure_diff_null]
refine measure_mono_null ?_ (measure_inter_eq_zero_of_restrict H)
exact inter_subset_inter_left _ fun a ha => (sub_eq_zero.1 <| of_not_not ha).le
#align measure_theory.measure_le_set_average_pos MeasureTheory.measure_le_setAverage_pos
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_setAverage_le_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | ⨍ a in s, f a ∂μ ≤ f x}) := by
simpa [integral_neg, neg_div] using measure_le_setAverage_pos hμ hμ₁ hf.neg
#align measure_theory.measure_set_average_le_pos MeasureTheory.measure_setAverage_le_pos
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_setAverage (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, f x ≤ ⨍ a in s, f a ∂μ :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_le_setAverage_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
#align measure_theory.exists_le_set_average MeasureTheory.exists_le_setAverage
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_setAverage_le (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, ⨍ a in s, f a ∂μ ≤ f x :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_setAverage_le_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
#align measure_theory.exists_set_average_le MeasureTheory.exists_setAverage_le
section FiniteMeasure
variable [IsFiniteMeasure μ]
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_average_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | f x ≤ ⨍ a, f a ∂μ} := by
simpa using measure_le_setAverage_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
#align measure_theory.measure_le_average_pos MeasureTheory.measure_le_average_pos
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_average_le_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | ⨍ a, f a ∂μ ≤ f x} := by
simpa using measure_setAverage_le_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
#align measure_theory.measure_average_le_pos MeasureTheory.measure_average_le_pos
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, f x ≤ ⨍ a, f a ∂μ :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_le_average_pos hμ hf).ne'
⟨x, hx⟩
#align measure_theory.exists_le_average MeasureTheory.exists_le_average
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, ⨍ a, f a ∂μ ≤ f x :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_average_le_pos hμ hf).ne'
⟨x, hx⟩
#align measure_theory.exists_average_le MeasureTheory.exists_average_le
/-- **First moment method**. The minimum of an integrable function is smaller than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ f x ≤ ⨍ a, f a ∂μ := by
have := measure_le_average_pos hμ hf
rw [← measure_diff_null hN] at this
obtain ⟨x, hx, hxN⟩ := nonempty_of_measure_ne_zero this.ne'
exact ⟨x, hxN, hx⟩
#align measure_theory.exists_not_mem_null_le_average MeasureTheory.exists_not_mem_null_le_average
/-- **First moment method**. The maximum of an integrable function is greater than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ⨍ a, f a ∂μ ≤ f x := by
simpa [integral_neg, neg_div] using exists_not_mem_null_le_average hμ hf.neg hN
#align measure_theory.exists_not_mem_null_average_le MeasureTheory.exists_not_mem_null_average_le
end FiniteMeasure
section ProbabilityMeasure
variable [IsProbabilityMeasure μ]
/-- **First moment method**. An integrable function is smaller than its integral on a set of
positive measure. -/
| Mathlib/MeasureTheory/Integral/Average.lean | 616 | 618 | theorem measure_le_integral_pos (hf : Integrable f μ) : 0 < μ {x | f x ≤ ∫ a, f a ∂μ} := by |
simpa only [average_eq_integral] using
measure_le_average_pos (IsProbabilityMeasure.ne_zero μ) hf
|
/-
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]
| Mathlib/Topology/Algebra/InfiniteSum/Basic.lean | 445 | 448 | 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')
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Bundle
import Mathlib.Data.Set.Image
import Mathlib.Topology.PartialHomeomorph
import Mathlib.Topology.Order.Basic
#align_import topology.fiber_bundle.trivialization from "leanprover-community/mathlib"@"e473c3198bb41f68560cab68a0529c854b618833"
/-!
# Trivializations
## Main definitions
### Basic definitions
* `Trivialization F p` : structure extending partial homeomorphisms, defining a local
trivialization of a topological space `Z` with projection `p` and fiber `F`.
* `Pretrivialization F proj` : trivialization as a partial equivalence, mainly used when the
topology on the total space has not yet been defined.
### Operations on bundles
We provide the following operations on `Trivialization`s.
* `Trivialization.compHomeomorph`: given a local trivialization `e` of a fiber bundle
`p : Z → B` and a homeomorphism `h : Z' ≃ₜ Z`, returns a local trivialization of the fiber bundle
`p ∘ h`.
## Implementation notes
Previously, in mathlib, there was a structure `topological_vector_bundle.trivialization` which
extended another structure `topological_fiber_bundle.trivialization` by a linearity hypothesis. As
of PR leanprover-community/mathlib#17359, we have changed this to a single structure
`Trivialization` (no namespace), together with a mixin class `Trivialization.IsLinear`.
This permits all the *data* of a vector bundle to be held at the level of fiber bundles, so that the
same trivializations can underlie an object's structure as (say) a vector bundle over `ℂ` and as a
vector bundle over `ℝ`, as well as its structure simply as a fiber bundle.
This might be a little surprising, given the general trend of the library to ever-increased
bundling. But in this case the typical motivation for more bundling does not apply: there is no
algebraic or order structure on the whole type of linear (say) trivializations of a bundle.
Indeed, since trivializations only have meaning on their base sets (taking junk values outside), the
type of linear trivializations is not even particularly well-behaved.
-/
open TopologicalSpace Filter Set Bundle Function
open scoped Topology Classical Bundle
variable {ι : Type*} {B : Type*} {F : Type*} {E : B → Type*}
variable (F) {Z : Type*} [TopologicalSpace B] [TopologicalSpace F] {proj : Z → B}
/-- This structure contains the information left for a local trivialization (which is implemented
below as `Trivialization F proj`) if the total space has not been given a topology, but we
have a topology on both the fiber and the base space. Through the construction
`topological_fiber_prebundle F proj` it will be possible to promote a
`Pretrivialization F proj` to a `Trivialization F proj`. -/
structure Pretrivialization (proj : Z → B) extends PartialEquiv Z (B × F) where
open_target : IsOpen target
baseSet : Set B
open_baseSet : IsOpen baseSet
source_eq : source = proj ⁻¹' baseSet
target_eq : target = baseSet ×ˢ univ
proj_toFun : ∀ p ∈ source, (toFun p).1 = proj p
#align pretrivialization Pretrivialization
namespace Pretrivialization
variable {F}
variable (e : Pretrivialization F proj) {x : Z}
/-- Coercion of a pretrivialization to a function. We don't use `e.toFun` in the `CoeFun` instance
because it is actually `e.toPartialEquiv.toFun`, so `simp` will apply lemmas about
`toPartialEquiv`. While we may want to switch to this behavior later, doing it mid-port will break a
lot of proofs. -/
@[coe] def toFun' : Z → (B × F) := e.toFun
instance : CoeFun (Pretrivialization F proj) fun _ => Z → B × F := ⟨toFun'⟩
@[ext]
lemma ext' (e e' : Pretrivialization F proj) (h₁ : e.toPartialEquiv = e'.toPartialEquiv)
(h₂ : e.baseSet = e'.baseSet) : e = e' := by
cases e; cases e'; congr
#align pretrivialization.ext Pretrivialization.ext'
-- Porting note (#11215): TODO: move `ext` here?
lemma ext {e e' : Pretrivialization F proj} (h₁ : ∀ x, e x = e' x)
(h₂ : ∀ x, e.toPartialEquiv.symm x = e'.toPartialEquiv.symm x) (h₃ : e.baseSet = e'.baseSet) :
e = e' := by
ext1 <;> [ext1; exact h₃]
· apply h₁
· apply h₂
· rw [e.source_eq, e'.source_eq, h₃]
/-- If the fiber is nonempty, then the projection also is. -/
lemma toPartialEquiv_injective [Nonempty F] :
Injective (toPartialEquiv : Pretrivialization F proj → PartialEquiv Z (B × F)) := by
refine fun e e' h ↦ ext' _ _ h ?_
simpa only [fst_image_prod, univ_nonempty, target_eq]
using congr_arg (Prod.fst '' PartialEquiv.target ·) h
@[simp, mfld_simps]
theorem coe_coe : ⇑e.toPartialEquiv = e :=
rfl
#align pretrivialization.coe_coe Pretrivialization.coe_coe
@[simp, mfld_simps]
theorem coe_fst (ex : x ∈ e.source) : (e x).1 = proj x :=
e.proj_toFun x ex
#align pretrivialization.coe_fst Pretrivialization.coe_fst
theorem mem_source : x ∈ e.source ↔ proj x ∈ e.baseSet := by rw [e.source_eq, mem_preimage]
#align pretrivialization.mem_source Pretrivialization.mem_source
theorem coe_fst' (ex : proj x ∈ e.baseSet) : (e x).1 = proj x :=
e.coe_fst (e.mem_source.2 ex)
#align pretrivialization.coe_fst' Pretrivialization.coe_fst'
protected theorem eqOn : EqOn (Prod.fst ∘ e) proj e.source := fun _ hx => e.coe_fst hx
#align pretrivialization.eq_on Pretrivialization.eqOn
theorem mk_proj_snd (ex : x ∈ e.source) : (proj x, (e x).2) = e x :=
Prod.ext (e.coe_fst ex).symm rfl
#align pretrivialization.mk_proj_snd Pretrivialization.mk_proj_snd
theorem mk_proj_snd' (ex : proj x ∈ e.baseSet) : (proj x, (e x).2) = e x :=
Prod.ext (e.coe_fst' ex).symm rfl
#align pretrivialization.mk_proj_snd' Pretrivialization.mk_proj_snd'
/-- Composition of inverse and coercion from the subtype of the target. -/
def setSymm : e.target → Z :=
e.target.restrict e.toPartialEquiv.symm
#align pretrivialization.set_symm Pretrivialization.setSymm
theorem mem_target {x : B × F} : x ∈ e.target ↔ x.1 ∈ e.baseSet := by
rw [e.target_eq, prod_univ, mem_preimage]
#align pretrivialization.mem_target Pretrivialization.mem_target
theorem proj_symm_apply {x : B × F} (hx : x ∈ e.target) : proj (e.toPartialEquiv.symm x) = x.1 := by
have := (e.coe_fst (e.map_target hx)).symm
rwa [← e.coe_coe, e.right_inv hx] at this
#align pretrivialization.proj_symm_apply Pretrivialization.proj_symm_apply
theorem proj_symm_apply' {b : B} {x : F} (hx : b ∈ e.baseSet) :
proj (e.toPartialEquiv.symm (b, x)) = b :=
e.proj_symm_apply (e.mem_target.2 hx)
#align pretrivialization.proj_symm_apply' Pretrivialization.proj_symm_apply'
theorem proj_surjOn_baseSet [Nonempty F] : Set.SurjOn proj e.source e.baseSet := fun b hb =>
let ⟨y⟩ := ‹Nonempty F›
⟨e.toPartialEquiv.symm (b, y), e.toPartialEquiv.map_target <| e.mem_target.2 hb,
e.proj_symm_apply' hb⟩
#align pretrivialization.proj_surj_on_base_set Pretrivialization.proj_surjOn_baseSet
theorem apply_symm_apply {x : B × F} (hx : x ∈ e.target) : e (e.toPartialEquiv.symm x) = x :=
e.toPartialEquiv.right_inv hx
#align pretrivialization.apply_symm_apply Pretrivialization.apply_symm_apply
theorem apply_symm_apply' {b : B} {x : F} (hx : b ∈ e.baseSet) :
e (e.toPartialEquiv.symm (b, x)) = (b, x) :=
e.apply_symm_apply (e.mem_target.2 hx)
#align pretrivialization.apply_symm_apply' Pretrivialization.apply_symm_apply'
theorem symm_apply_apply {x : Z} (hx : x ∈ e.source) : e.toPartialEquiv.symm (e x) = x :=
e.toPartialEquiv.left_inv hx
#align pretrivialization.symm_apply_apply Pretrivialization.symm_apply_apply
@[simp, mfld_simps]
theorem symm_apply_mk_proj {x : Z} (ex : x ∈ e.source) :
e.toPartialEquiv.symm (proj x, (e x).2) = x := by
rw [← e.coe_fst ex, ← e.coe_coe, e.left_inv ex]
#align pretrivialization.symm_apply_mk_proj Pretrivialization.symm_apply_mk_proj
@[simp, mfld_simps]
theorem preimage_symm_proj_baseSet :
e.toPartialEquiv.symm ⁻¹' (proj ⁻¹' e.baseSet) ∩ e.target = e.target := by
refine inter_eq_right.mpr fun x hx => ?_
simp only [mem_preimage, PartialEquiv.invFun_as_coe, e.proj_symm_apply hx]
exact e.mem_target.mp hx
#align pretrivialization.preimage_symm_proj_base_set Pretrivialization.preimage_symm_proj_baseSet
@[simp, mfld_simps]
theorem preimage_symm_proj_inter (s : Set B) :
e.toPartialEquiv.symm ⁻¹' (proj ⁻¹' s) ∩ e.baseSet ×ˢ univ = (s ∩ e.baseSet) ×ˢ univ := by
ext ⟨x, y⟩
suffices x ∈ e.baseSet → (proj (e.toPartialEquiv.symm (x, y)) ∈ s ↔ x ∈ s) by
simpa only [prod_mk_mem_set_prod_eq, mem_inter_iff, and_true_iff, mem_univ, and_congr_left_iff]
intro h
rw [e.proj_symm_apply' h]
#align pretrivialization.preimage_symm_proj_inter Pretrivialization.preimage_symm_proj_inter
theorem target_inter_preimage_symm_source_eq (e f : Pretrivialization F proj) :
f.target ∩ f.toPartialEquiv.symm ⁻¹' e.source = (e.baseSet ∩ f.baseSet) ×ˢ univ := by
rw [inter_comm, f.target_eq, e.source_eq, f.preimage_symm_proj_inter]
#align pretrivialization.target_inter_preimage_symm_source_eq Pretrivialization.target_inter_preimage_symm_source_eq
theorem trans_source (e f : Pretrivialization F proj) :
(f.toPartialEquiv.symm.trans e.toPartialEquiv).source = (e.baseSet ∩ f.baseSet) ×ˢ univ := by
rw [PartialEquiv.trans_source, PartialEquiv.symm_source, e.target_inter_preimage_symm_source_eq]
#align pretrivialization.trans_source Pretrivialization.trans_source
theorem symm_trans_symm (e e' : Pretrivialization F proj) :
(e.toPartialEquiv.symm.trans e'.toPartialEquiv).symm
= e'.toPartialEquiv.symm.trans e.toPartialEquiv := by
rw [PartialEquiv.trans_symm_eq_symm_trans_symm, PartialEquiv.symm_symm]
#align pretrivialization.symm_trans_symm Pretrivialization.symm_trans_symm
theorem symm_trans_source_eq (e e' : Pretrivialization F proj) :
(e.toPartialEquiv.symm.trans e'.toPartialEquiv).source = (e.baseSet ∩ e'.baseSet) ×ˢ univ := by
rw [PartialEquiv.trans_source, e'.source_eq, PartialEquiv.symm_source, e.target_eq, inter_comm,
e.preimage_symm_proj_inter, inter_comm]
#align pretrivialization.symm_trans_source_eq Pretrivialization.symm_trans_source_eq
theorem symm_trans_target_eq (e e' : Pretrivialization F proj) :
(e.toPartialEquiv.symm.trans e'.toPartialEquiv).target = (e.baseSet ∩ e'.baseSet) ×ˢ univ := by
rw [← PartialEquiv.symm_source, symm_trans_symm, symm_trans_source_eq, inter_comm]
#align pretrivialization.symm_trans_target_eq Pretrivialization.symm_trans_target_eq
variable (e' : Pretrivialization F (π F E)) {x' : TotalSpace F E} {b : B} {y : E b}
@[simp]
theorem coe_mem_source : ↑y ∈ e'.source ↔ b ∈ e'.baseSet :=
e'.mem_source
#align pretrivialization.coe_mem_source Pretrivialization.coe_mem_source
@[simp, mfld_simps]
theorem coe_coe_fst (hb : b ∈ e'.baseSet) : (e' y).1 = b :=
e'.coe_fst (e'.mem_source.2 hb)
#align pretrivialization.coe_coe_fst Pretrivialization.coe_coe_fst
theorem mk_mem_target {x : B} {y : F} : (x, y) ∈ e'.target ↔ x ∈ e'.baseSet :=
e'.mem_target
#align pretrivialization.mk_mem_target Pretrivialization.mk_mem_target
theorem symm_coe_proj {x : B} {y : F} (e' : Pretrivialization F (π F E)) (h : x ∈ e'.baseSet) :
(e'.toPartialEquiv.symm (x, y)).1 = x :=
e'.proj_symm_apply' h
#align pretrivialization.symm_coe_proj Pretrivialization.symm_coe_proj
section Zero
variable [∀ x, Zero (E x)]
/-- A fiberwise inverse to `e`. This is the function `F → E b` that induces a local inverse
`B × F → TotalSpace F E` of `e` on `e.baseSet`. It is defined to be `0` outside `e.baseSet`. -/
protected noncomputable def symm (e : Pretrivialization F (π F E)) (b : B) (y : F) : E b :=
if hb : b ∈ e.baseSet then
cast (congr_arg E (e.proj_symm_apply' hb)) (e.toPartialEquiv.symm (b, y)).2
else 0
#align pretrivialization.symm Pretrivialization.symm
theorem symm_apply (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) :
e.symm b y = cast (congr_arg E (e.symm_coe_proj hb)) (e.toPartialEquiv.symm (b, y)).2 :=
dif_pos hb
#align pretrivialization.symm_apply Pretrivialization.symm_apply
theorem symm_apply_of_not_mem (e : Pretrivialization F (π F E)) {b : B} (hb : b ∉ e.baseSet)
(y : F) : e.symm b y = 0 :=
dif_neg hb
#align pretrivialization.symm_apply_of_not_mem Pretrivialization.symm_apply_of_not_mem
theorem coe_symm_of_not_mem (e : Pretrivialization F (π F E)) {b : B} (hb : b ∉ e.baseSet) :
(e.symm b : F → E b) = 0 :=
funext fun _ => dif_neg hb
#align pretrivialization.coe_symm_of_not_mem Pretrivialization.coe_symm_of_not_mem
theorem mk_symm (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) :
TotalSpace.mk b (e.symm b y) = e.toPartialEquiv.symm (b, y) := by
simp only [e.symm_apply hb, TotalSpace.mk_cast (e.proj_symm_apply' hb), TotalSpace.eta]
#align pretrivialization.mk_symm Pretrivialization.mk_symm
theorem symm_proj_apply (e : Pretrivialization F (π F E)) (z : TotalSpace F E)
(hz : z.proj ∈ e.baseSet) : e.symm z.proj (e z).2 = z.2 := by
rw [e.symm_apply hz, cast_eq_iff_heq, e.mk_proj_snd' hz, e.symm_apply_apply (e.mem_source.mpr hz)]
#align pretrivialization.symm_proj_apply Pretrivialization.symm_proj_apply
theorem symm_apply_apply_mk (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet)
(y : E b) : e.symm b (e ⟨b, y⟩).2 = y :=
e.symm_proj_apply ⟨b, y⟩ hb
#align pretrivialization.symm_apply_apply_mk Pretrivialization.symm_apply_apply_mk
theorem apply_mk_symm (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) :
e ⟨b, e.symm b y⟩ = (b, y) := by
rw [e.mk_symm hb, e.apply_symm_apply (e.mk_mem_target.mpr hb)]
#align pretrivialization.apply_mk_symm Pretrivialization.apply_mk_symm
end Zero
end Pretrivialization
variable [TopologicalSpace Z] [TopologicalSpace (TotalSpace F E)]
/-- A structure extending partial homeomorphisms, defining a local trivialization of a projection
`proj : Z → B` with fiber `F`, as a partial homeomorphism between `Z` and `B × F` defined between
two sets of the form `proj ⁻¹' baseSet` and `baseSet × F`, acting trivially on the first coordinate.
-/
-- Porting note (#5171): was @[nolint has_nonempty_instance]
structure Trivialization (proj : Z → B) extends PartialHomeomorph Z (B × F) where
baseSet : Set B
open_baseSet : IsOpen baseSet
source_eq : source = proj ⁻¹' baseSet
target_eq : target = baseSet ×ˢ univ
proj_toFun : ∀ p ∈ source, (toPartialHomeomorph p).1 = proj p
#align trivialization Trivialization
namespace Trivialization
variable {F}
variable (e : Trivialization F proj) {x : Z}
@[ext]
lemma ext' (e e' : Trivialization F proj) (h₁ : e.toPartialHomeomorph = e'.toPartialHomeomorph)
(h₂ : e.baseSet = e'.baseSet) : e = e' := by
cases e; cases e'; congr
#align trivialization.ext Trivialization.ext'
/-- Coercion of a trivialization to a function. We don't use `e.toFun` in the `CoeFun` instance
because it is actually `e.toPartialEquiv.toFun`, so `simp` will apply lemmas about
`toPartialEquiv`. While we may want to switch to this behavior later, doing it mid-port will break a
lot of proofs. -/
@[coe] def toFun' : Z → (B × F) := e.toFun
/-- Natural identification as a `Pretrivialization`. -/
def toPretrivialization : Pretrivialization F proj :=
{ e with }
#align trivialization.to_pretrivialization Trivialization.toPretrivialization
instance : CoeFun (Trivialization F proj) fun _ => Z → B × F := ⟨toFun'⟩
instance : Coe (Trivialization F proj) (Pretrivialization F proj) :=
⟨toPretrivialization⟩
theorem toPretrivialization_injective :
Function.Injective fun e : Trivialization F proj => e.toPretrivialization := fun e e' h => by
ext1
exacts [PartialHomeomorph.toPartialEquiv_injective (congr_arg Pretrivialization.toPartialEquiv h),
congr_arg Pretrivialization.baseSet h]
#align trivialization.to_pretrivialization_injective Trivialization.toPretrivialization_injective
@[simp, mfld_simps]
theorem coe_coe : ⇑e.toPartialHomeomorph = e :=
rfl
#align trivialization.coe_coe Trivialization.coe_coe
@[simp, mfld_simps]
theorem coe_fst (ex : x ∈ e.source) : (e x).1 = proj x :=
e.proj_toFun x ex
#align trivialization.coe_fst Trivialization.coe_fst
protected theorem eqOn : EqOn (Prod.fst ∘ e) proj e.source := fun _x hx => e.coe_fst hx
#align trivialization.eq_on Trivialization.eqOn
| Mathlib/Topology/FiberBundle/Trivialization.lean | 359 | 359 | theorem mem_source : x ∈ e.source ↔ proj x ∈ e.baseSet := by | rw [e.source_eq, mem_preimage]
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Mario Carneiro
-/
import Mathlib.Algebra.Associated
import Mathlib.Algebra.Order.Monoid.Unbundled.Pow
import Mathlib.Algebra.Ring.Int
import Mathlib.Data.Nat.Factorial.Basic
import Mathlib.Data.Nat.GCD.Basic
import Mathlib.Order.Bounds.Basic
#align_import data.nat.prime from "leanprover-community/mathlib"@"8631e2d5ea77f6c13054d9151d82b83069680cb1"
/-!
# Prime numbers
This file deals with prime numbers: natural numbers `p ≥ 2` whose only divisors are `p` and `1`.
## Important declarations
- `Nat.Prime`: the predicate that expresses that a natural number `p` is prime
- `Nat.Primes`: the subtype of natural numbers that are prime
- `Nat.minFac n`: the minimal prime factor of a natural number `n ≠ 1`
- `Nat.exists_infinite_primes`: Euclid's theorem that there exist infinitely many prime numbers.
This also appears as `Nat.not_bddAbove_setOf_prime` and `Nat.infinite_setOf_prime` (the latter
in `Data.Nat.PrimeFin`).
- `Nat.prime_iff`: `Nat.Prime` coincides with the general definition of `Prime`
- `Nat.irreducible_iff_nat_prime`: a non-unit natural number is
only divisible by `1` iff it is prime
-/
open Bool Subtype
open Nat
namespace Nat
variable {n : ℕ}
/-- `Nat.Prime p` means that `p` is a prime number, that is, a natural number
at least 2 whose only divisors are `p` and `1`. -/
-- Porting note (#11180): removed @[pp_nodot]
def Prime (p : ℕ) :=
Irreducible p
#align nat.prime Nat.Prime
theorem irreducible_iff_nat_prime (a : ℕ) : Irreducible a ↔ Nat.Prime a :=
Iff.rfl
#align irreducible_iff_nat_prime Nat.irreducible_iff_nat_prime
@[aesop safe destruct] theorem not_prime_zero : ¬Prime 0
| h => h.ne_zero rfl
#align nat.not_prime_zero Nat.not_prime_zero
@[aesop safe destruct] theorem not_prime_one : ¬Prime 1
| h => h.ne_one rfl
#align nat.not_prime_one Nat.not_prime_one
theorem Prime.ne_zero {n : ℕ} (h : Prime n) : n ≠ 0 :=
Irreducible.ne_zero h
#align nat.prime.ne_zero Nat.Prime.ne_zero
theorem Prime.pos {p : ℕ} (pp : Prime p) : 0 < p :=
Nat.pos_of_ne_zero pp.ne_zero
#align nat.prime.pos Nat.Prime.pos
theorem Prime.two_le : ∀ {p : ℕ}, Prime p → 2 ≤ p
| 0, h => (not_prime_zero h).elim
| 1, h => (not_prime_one h).elim
| _ + 2, _ => le_add_self
#align nat.prime.two_le Nat.Prime.two_le
theorem Prime.one_lt {p : ℕ} : Prime p → 1 < p :=
Prime.two_le
#align nat.prime.one_lt Nat.Prime.one_lt
lemma Prime.one_le {p : ℕ} (hp : p.Prime) : 1 ≤ p := hp.one_lt.le
instance Prime.one_lt' (p : ℕ) [hp : Fact p.Prime] : Fact (1 < p) :=
⟨hp.1.one_lt⟩
#align nat.prime.one_lt' Nat.Prime.one_lt'
theorem Prime.ne_one {p : ℕ} (hp : p.Prime) : p ≠ 1 :=
hp.one_lt.ne'
#align nat.prime.ne_one Nat.Prime.ne_one
theorem Prime.eq_one_or_self_of_dvd {p : ℕ} (pp : p.Prime) (m : ℕ) (hm : m ∣ p) :
m = 1 ∨ m = p := by
obtain ⟨n, hn⟩ := hm
have := pp.isUnit_or_isUnit hn
rw [Nat.isUnit_iff, Nat.isUnit_iff] at this
apply Or.imp_right _ this
rintro rfl
rw [hn, mul_one]
#align nat.prime.eq_one_or_self_of_dvd Nat.Prime.eq_one_or_self_of_dvd
theorem prime_def_lt'' {p : ℕ} : Prime p ↔ 2 ≤ p ∧ ∀ m, m ∣ p → m = 1 ∨ m = p := by
refine ⟨fun h => ⟨h.two_le, h.eq_one_or_self_of_dvd⟩, fun h => ?_⟩
-- Porting note: needed to make ℕ explicit
have h1 := (@one_lt_two ℕ ..).trans_le h.1
refine ⟨mt Nat.isUnit_iff.mp h1.ne', fun a b hab => ?_⟩
simp only [Nat.isUnit_iff]
apply Or.imp_right _ (h.2 a _)
· rintro rfl
rw [← mul_right_inj' (pos_of_gt h1).ne', ← hab, mul_one]
· rw [hab]
exact dvd_mul_right _ _
#align nat.prime_def_lt'' Nat.prime_def_lt''
theorem prime_def_lt {p : ℕ} : Prime p ↔ 2 ≤ p ∧ ∀ m < p, m ∣ p → m = 1 :=
prime_def_lt''.trans <|
and_congr_right fun p2 =>
forall_congr' fun _ =>
⟨fun h l d => (h d).resolve_right (ne_of_lt l), fun h d =>
(le_of_dvd (le_of_succ_le p2) d).lt_or_eq_dec.imp_left fun l => h l d⟩
#align nat.prime_def_lt Nat.prime_def_lt
theorem prime_def_lt' {p : ℕ} : Prime p ↔ 2 ≤ p ∧ ∀ m, 2 ≤ m → m < p → ¬m ∣ p :=
prime_def_lt.trans <|
and_congr_right fun p2 =>
forall_congr' fun m =>
⟨fun h m2 l d => not_lt_of_ge m2 ((h l d).symm ▸ by decide), fun h l d => by
rcases m with (_ | _ | m)
· rw [eq_zero_of_zero_dvd d] at p2
revert p2
decide
· rfl
· exact (h le_add_self l).elim d⟩
#align nat.prime_def_lt' Nat.prime_def_lt'
theorem prime_def_le_sqrt {p : ℕ} : Prime p ↔ 2 ≤ p ∧ ∀ m, 2 ≤ m → m ≤ sqrt p → ¬m ∣ p :=
prime_def_lt'.trans <|
and_congr_right fun p2 =>
⟨fun a m m2 l => a m m2 <| lt_of_le_of_lt l <| sqrt_lt_self p2, fun a =>
have : ∀ {m k : ℕ}, m ≤ k → 1 < m → p ≠ m * k := fun {m k} mk m1 e =>
a m m1 (le_sqrt.2 (e.symm ▸ Nat.mul_le_mul_left m mk)) ⟨k, e⟩
fun m m2 l ⟨k, e⟩ => by
rcases le_total m k with mk | km
· exact this mk m2 e
· rw [mul_comm] at e
refine this km (lt_of_mul_lt_mul_right ?_ (zero_le m)) e
rwa [one_mul, ← e]⟩
#align nat.prime_def_le_sqrt Nat.prime_def_le_sqrt
theorem prime_of_coprime (n : ℕ) (h1 : 1 < n) (h : ∀ m < n, m ≠ 0 → n.Coprime m) : Prime n := by
refine prime_def_lt.mpr ⟨h1, fun m mlt mdvd => ?_⟩
have hm : m ≠ 0 := by
rintro rfl
rw [zero_dvd_iff] at mdvd
exact mlt.ne' mdvd
exact (h m mlt hm).symm.eq_one_of_dvd mdvd
#align nat.prime_of_coprime Nat.prime_of_coprime
section
/-- This instance is slower than the instance `decidablePrime` defined below,
but has the advantage that it works in the kernel for small values.
If you need to prove that a particular number is prime, in any case
you should not use `by decide`, but rather `by norm_num`, which is
much faster.
-/
@[local instance]
def decidablePrime1 (p : ℕ) : Decidable (Prime p) :=
decidable_of_iff' _ prime_def_lt'
#align nat.decidable_prime_1 Nat.decidablePrime1
theorem prime_two : Prime 2 := by decide
#align nat.prime_two Nat.prime_two
theorem prime_three : Prime 3 := by decide
#align nat.prime_three Nat.prime_three
theorem prime_five : Prime 5 := by decide
theorem Prime.five_le_of_ne_two_of_ne_three {p : ℕ} (hp : p.Prime) (h_two : p ≠ 2)
(h_three : p ≠ 3) : 5 ≤ p := by
by_contra! h
revert h_two h_three hp
-- Porting note (#11043): was `decide!`
match p with
| 0 => decide
| 1 => decide
| 2 => decide
| 3 => decide
| 4 => decide
| n + 5 => exact (h.not_le le_add_self).elim
#align nat.prime.five_le_of_ne_two_of_ne_three Nat.Prime.five_le_of_ne_two_of_ne_three
end
theorem Prime.pred_pos {p : ℕ} (pp : Prime p) : 0 < pred p :=
lt_pred_iff.2 pp.one_lt
#align nat.prime.pred_pos Nat.Prime.pred_pos
theorem succ_pred_prime {p : ℕ} (pp : Prime p) : succ (pred p) = p :=
succ_pred_eq_of_pos pp.pos
#align nat.succ_pred_prime Nat.succ_pred_prime
theorem dvd_prime {p m : ℕ} (pp : Prime p) : m ∣ p ↔ m = 1 ∨ m = p :=
⟨fun d => pp.eq_one_or_self_of_dvd m d, fun h =>
h.elim (fun e => e.symm ▸ one_dvd _) fun e => e.symm ▸ dvd_rfl⟩
#align nat.dvd_prime Nat.dvd_prime
theorem dvd_prime_two_le {p m : ℕ} (pp : Prime p) (H : 2 ≤ m) : m ∣ p ↔ m = p :=
(dvd_prime pp).trans <| or_iff_right_of_imp <| Not.elim <| ne_of_gt H
#align nat.dvd_prime_two_le Nat.dvd_prime_two_le
theorem prime_dvd_prime_iff_eq {p q : ℕ} (pp : p.Prime) (qp : q.Prime) : p ∣ q ↔ p = q :=
dvd_prime_two_le qp (Prime.two_le pp)
#align nat.prime_dvd_prime_iff_eq Nat.prime_dvd_prime_iff_eq
theorem Prime.not_dvd_one {p : ℕ} (pp : Prime p) : ¬p ∣ 1 :=
Irreducible.not_dvd_one pp
#align nat.prime.not_dvd_one Nat.Prime.not_dvd_one
theorem prime_mul_iff {a b : ℕ} : Nat.Prime (a * b) ↔ a.Prime ∧ b = 1 ∨ b.Prime ∧ a = 1 := by
simp only [iff_self_iff, irreducible_mul_iff, ← irreducible_iff_nat_prime, Nat.isUnit_iff]
#align nat.prime_mul_iff Nat.prime_mul_iff
theorem not_prime_mul {a b : ℕ} (a1 : a ≠ 1) (b1 : b ≠ 1) : ¬Prime (a * b) := by
simp [prime_mul_iff, _root_.not_or, *]
#align nat.not_prime_mul Nat.not_prime_mul
theorem not_prime_mul' {a b n : ℕ} (h : a * b = n) (h₁ : a ≠ 1) (h₂ : b ≠ 1) : ¬Prime n :=
h ▸ not_prime_mul h₁ h₂
#align nat.not_prime_mul' Nat.not_prime_mul'
| Mathlib/Data/Nat/Prime.lean | 231 | 236 | theorem Prime.dvd_iff_eq {p a : ℕ} (hp : p.Prime) (a1 : a ≠ 1) : a ∣ p ↔ p = a := by |
refine ⟨?_, by rintro rfl; rfl⟩
rintro ⟨j, rfl⟩
rcases prime_mul_iff.mp hp with (⟨_, rfl⟩ | ⟨_, rfl⟩)
· exact mul_one _
· exact (a1 rfl).elim
|
/-
Copyright (c) 2020 Bryan Gin-ge Chen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Lacker, Bryan Gin-ge Chen
-/
import Mathlib.Data.Nat.Prime
#align_import data.int.nat_prime from "leanprover-community/mathlib"@"422e70f7ce183d2900c586a8cda8381e788a0c62"
/-!
# Lemmas about `Nat.Prime` using `Int`s
-/
open Nat
namespace Int
theorem not_prime_of_int_mul {a b : ℤ} {c : ℕ} (ha : a.natAbs ≠ 1) (hb : b.natAbs ≠ 1)
(hc : a * b = (c : ℤ)) : ¬Nat.Prime c :=
not_prime_mul' (natAbs_mul_natAbs_eq hc) ha hb
#align int.not_prime_of_int_mul Int.not_prime_of_int_mul
theorem succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul {p : ℕ} (p_prime : Nat.Prime p) {m n : ℤ}
{k l : ℕ} (hpm : ↑(p ^ k) ∣ m) (hpn : ↑(p ^ l) ∣ n) (hpmn : ↑(p ^ (k + l + 1)) ∣ m * n) :
↑(p ^ (k + 1)) ∣ m ∨ ↑(p ^ (l + 1)) ∣ n :=
have hpm' : p ^ k ∣ m.natAbs := Int.natCast_dvd_natCast.1 <| Int.dvd_natAbs.2 hpm
have hpn' : p ^ l ∣ n.natAbs := Int.natCast_dvd_natCast.1 <| Int.dvd_natAbs.2 hpn
have hpmn' : p ^ (k + l + 1) ∣ m.natAbs * n.natAbs := by
rw [← Int.natAbs_mul]; apply Int.natCast_dvd_natCast.1 <| Int.dvd_natAbs.2 hpmn
let hsd := Nat.succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul p_prime hpm' hpn' hpmn'
hsd.elim (fun hsd1 => Or.inl (by apply Int.dvd_natAbs.1; apply Int.natCast_dvd_natCast.2 hsd1))
fun hsd2 => Or.inr (by apply Int.dvd_natAbs.1; apply Int.natCast_dvd_natCast.2 hsd2)
#align int.succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul Int.succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul
| Mathlib/Data/Int/NatPrime.lean | 36 | 39 | theorem Prime.dvd_natAbs_of_coe_dvd_sq {p : ℕ} (hp : p.Prime) (k : ℤ) (h : (p : ℤ) ∣ k ^ 2) :
p ∣ k.natAbs := by |
apply @Nat.Prime.dvd_of_dvd_pow _ _ 2 hp
rwa [sq, ← natAbs_mul, ← natCast_dvd, ← sq]
|
/-
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
-/
import Mathlib.Algebra.Group.Even
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.GroupWithZero.Hom
import Mathlib.Algebra.Group.Commute.Units
import Mathlib.Algebra.Group.Units.Hom
import Mathlib.Algebra.Order.Monoid.Canonical.Defs
import Mathlib.Algebra.Ring.Units
#align_import algebra.associated from "leanprover-community/mathlib"@"2f3994e1b117b1e1da49bcfb67334f33460c3ce4"
/-!
# Associated, prime, and irreducible elements.
In this file we define the predicate `Prime p`
saying that an element of a commutative monoid with zero is prime.
Namely, `Prime p` means that `p` isn't zero, it isn't a unit,
and `p ∣ a * b → p ∣ a ∨ p ∣ b` for all `a`, `b`;
In decomposition monoids (e.g., `ℕ`, `ℤ`), this predicate is equivalent to `Irreducible`,
however this is not true in general.
We also define an equivalence relation `Associated`
saying that two elements of a monoid differ by a multiplication by a unit.
Then we show that the quotient type `Associates` is a monoid
and prove basic properties of this quotient.
-/
variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*}
section Prime
variable [CommMonoidWithZero α]
/-- An element `p` of a commutative monoid with zero (e.g., a ring) is called *prime*,
if it's not zero, not a unit, and `p ∣ a * b → p ∣ a ∨ p ∣ b` for all `a`, `b`. -/
def Prime (p : α) : Prop :=
p ≠ 0 ∧ ¬IsUnit p ∧ ∀ a b, p ∣ a * b → p ∣ a ∨ p ∣ b
#align prime Prime
namespace Prime
variable {p : α} (hp : Prime p)
theorem ne_zero : p ≠ 0 :=
hp.1
#align prime.ne_zero Prime.ne_zero
theorem not_unit : ¬IsUnit p :=
hp.2.1
#align prime.not_unit Prime.not_unit
theorem not_dvd_one : ¬p ∣ 1 :=
mt (isUnit_of_dvd_one ·) hp.not_unit
#align prime.not_dvd_one Prime.not_dvd_one
theorem ne_one : p ≠ 1 := fun h => hp.2.1 (h.symm ▸ isUnit_one)
#align prime.ne_one Prime.ne_one
theorem dvd_or_dvd (hp : Prime p) {a b : α} (h : p ∣ a * b) : p ∣ a ∨ p ∣ b :=
hp.2.2 a b h
#align prime.dvd_or_dvd Prime.dvd_or_dvd
theorem dvd_mul {a b : α} : p ∣ a * b ↔ p ∣ a ∨ p ∣ b :=
⟨hp.dvd_or_dvd, (Or.elim · (dvd_mul_of_dvd_left · _) (dvd_mul_of_dvd_right · _))⟩
theorem isPrimal (hp : Prime p) : IsPrimal p := fun _a _b dvd ↦ (hp.dvd_or_dvd dvd).elim
(fun h ↦ ⟨p, 1, h, one_dvd _, (mul_one p).symm⟩) fun h ↦ ⟨1, p, one_dvd _, h, (one_mul p).symm⟩
theorem not_dvd_mul {a b : α} (ha : ¬ p ∣ a) (hb : ¬ p ∣ b) : ¬ p ∣ a * b :=
hp.dvd_mul.not.mpr <| not_or.mpr ⟨ha, hb⟩
theorem dvd_of_dvd_pow (hp : Prime p) {a : α} {n : ℕ} (h : p ∣ a ^ n) : p ∣ a := by
induction' n with n ih
· rw [pow_zero] at h
have := isUnit_of_dvd_one h
have := not_unit hp
contradiction
rw [pow_succ'] at h
cases' dvd_or_dvd hp h with dvd_a dvd_pow
· assumption
exact ih dvd_pow
#align prime.dvd_of_dvd_pow Prime.dvd_of_dvd_pow
theorem dvd_pow_iff_dvd {a : α} {n : ℕ} (hn : n ≠ 0) : p ∣ a ^ n ↔ p ∣ a :=
⟨hp.dvd_of_dvd_pow, (dvd_pow · hn)⟩
end Prime
@[simp]
theorem not_prime_zero : ¬Prime (0 : α) := fun h => h.ne_zero rfl
#align not_prime_zero not_prime_zero
@[simp]
theorem not_prime_one : ¬Prime (1 : α) := fun h => h.not_unit isUnit_one
#align not_prime_one not_prime_one
section Map
variable [CommMonoidWithZero β] {F : Type*} {G : Type*} [FunLike F α β]
variable [MonoidWithZeroHomClass F α β] [FunLike G β α] [MulHomClass G β α]
variable (f : F) (g : G) {p : α}
theorem comap_prime (hinv : ∀ a, g (f a : β) = a) (hp : Prime (f p)) : Prime p :=
⟨fun h => hp.1 <| by simp [h], fun h => hp.2.1 <| h.map f, fun a b h => by
refine
(hp.2.2 (f a) (f b) <| by
convert map_dvd f h
simp).imp
?_ ?_ <;>
· intro h
convert ← map_dvd g h <;> apply hinv⟩
#align comap_prime comap_prime
theorem MulEquiv.prime_iff (e : α ≃* β) : Prime p ↔ Prime (e p) :=
⟨fun h => (comap_prime e.symm e fun a => by simp) <| (e.symm_apply_apply p).substr h,
comap_prime e e.symm fun a => by simp⟩
#align mul_equiv.prime_iff MulEquiv.prime_iff
end Map
end Prime
theorem Prime.left_dvd_or_dvd_right_of_dvd_mul [CancelCommMonoidWithZero α] {p : α} (hp : Prime p)
{a b : α} : a ∣ p * b → p ∣ a ∨ a ∣ b := by
rintro ⟨c, hc⟩
rcases hp.2.2 a c (hc ▸ dvd_mul_right _ _) with (h | ⟨x, rfl⟩)
· exact Or.inl h
· rw [mul_left_comm, mul_right_inj' hp.ne_zero] at hc
exact Or.inr (hc.symm ▸ dvd_mul_right _ _)
#align prime.left_dvd_or_dvd_right_of_dvd_mul Prime.left_dvd_or_dvd_right_of_dvd_mul
theorem Prime.pow_dvd_of_dvd_mul_left [CancelCommMonoidWithZero α] {p a b : α} (hp : Prime p)
(n : ℕ) (h : ¬p ∣ a) (h' : p ^ n ∣ a * b) : p ^ n ∣ b := by
induction' n with n ih
· rw [pow_zero]
exact one_dvd b
· obtain ⟨c, rfl⟩ := ih (dvd_trans (pow_dvd_pow p n.le_succ) h')
rw [pow_succ]
apply mul_dvd_mul_left _ ((hp.dvd_or_dvd _).resolve_left h)
rwa [← mul_dvd_mul_iff_left (pow_ne_zero n hp.ne_zero), ← pow_succ, mul_left_comm]
#align prime.pow_dvd_of_dvd_mul_left Prime.pow_dvd_of_dvd_mul_left
theorem Prime.pow_dvd_of_dvd_mul_right [CancelCommMonoidWithZero α] {p a b : α} (hp : Prime p)
(n : ℕ) (h : ¬p ∣ b) (h' : p ^ n ∣ a * b) : p ^ n ∣ a := by
rw [mul_comm] at h'
exact hp.pow_dvd_of_dvd_mul_left n h h'
#align prime.pow_dvd_of_dvd_mul_right Prime.pow_dvd_of_dvd_mul_right
theorem Prime.dvd_of_pow_dvd_pow_mul_pow_of_square_not_dvd [CancelCommMonoidWithZero α] {p a b : α}
{n : ℕ} (hp : Prime p) (hpow : p ^ n.succ ∣ a ^ n.succ * b ^ n) (hb : ¬p ^ 2 ∣ b) : p ∣ a := by
-- Suppose `p ∣ b`, write `b = p * x` and `hy : a ^ n.succ * b ^ n = p ^ n.succ * y`.
cases' hp.dvd_or_dvd ((dvd_pow_self p (Nat.succ_ne_zero n)).trans hpow) with H hbdiv
· exact hp.dvd_of_dvd_pow H
obtain ⟨x, rfl⟩ := hp.dvd_of_dvd_pow hbdiv
obtain ⟨y, hy⟩ := hpow
-- Then we can divide out a common factor of `p ^ n` from the equation `hy`.
have : a ^ n.succ * x ^ n = p * y := by
refine mul_left_cancel₀ (pow_ne_zero n hp.ne_zero) ?_
rw [← mul_assoc _ p, ← pow_succ, ← hy, mul_pow, ← mul_assoc (a ^ n.succ), mul_comm _ (p ^ n),
mul_assoc]
-- So `p ∣ a` (and we're done) or `p ∣ x`, which can't be the case since it implies `p^2 ∣ b`.
refine hp.dvd_of_dvd_pow ((hp.dvd_or_dvd ⟨_, this⟩).resolve_right fun hdvdx => hb ?_)
obtain ⟨z, rfl⟩ := hp.dvd_of_dvd_pow hdvdx
rw [pow_two, ← mul_assoc]
exact dvd_mul_right _ _
#align prime.dvd_of_pow_dvd_pow_mul_pow_of_square_not_dvd Prime.dvd_of_pow_dvd_pow_mul_pow_of_square_not_dvd
theorem prime_pow_succ_dvd_mul {α : Type*} [CancelCommMonoidWithZero α] {p x y : α} (h : Prime p)
{i : ℕ} (hxy : p ^ (i + 1) ∣ x * y) : p ^ (i + 1) ∣ x ∨ p ∣ y := by
rw [or_iff_not_imp_right]
intro hy
induction' i with i ih generalizing x
· rw [pow_one] at hxy ⊢
exact (h.dvd_or_dvd hxy).resolve_right hy
rw [pow_succ'] at hxy ⊢
obtain ⟨x', rfl⟩ := (h.dvd_or_dvd (dvd_of_mul_right_dvd hxy)).resolve_right hy
rw [mul_assoc] at hxy
exact mul_dvd_mul_left p (ih ((mul_dvd_mul_iff_left h.ne_zero).mp hxy))
#align prime_pow_succ_dvd_mul prime_pow_succ_dvd_mul
/-- `Irreducible p` states that `p` is non-unit and only factors into units.
We explicitly avoid stating that `p` is non-zero, this would require a semiring. Assuming only a
monoid allows us to reuse irreducible for associated elements.
-/
structure Irreducible [Monoid α] (p : α) : Prop where
/-- `p` is not a unit -/
not_unit : ¬IsUnit p
/-- if `p` factors then one factor is a unit -/
isUnit_or_isUnit' : ∀ a b, p = a * b → IsUnit a ∨ IsUnit b
#align irreducible Irreducible
namespace Irreducible
theorem not_dvd_one [CommMonoid α] {p : α} (hp : Irreducible p) : ¬p ∣ 1 :=
mt (isUnit_of_dvd_one ·) hp.not_unit
#align irreducible.not_dvd_one Irreducible.not_dvd_one
theorem isUnit_or_isUnit [Monoid α] {p : α} (hp : Irreducible p) {a b : α} (h : p = a * b) :
IsUnit a ∨ IsUnit b :=
hp.isUnit_or_isUnit' a b h
#align irreducible.is_unit_or_is_unit Irreducible.isUnit_or_isUnit
end Irreducible
theorem irreducible_iff [Monoid α] {p : α} :
Irreducible p ↔ ¬IsUnit p ∧ ∀ a b, p = a * b → IsUnit a ∨ IsUnit b :=
⟨fun h => ⟨h.1, h.2⟩, fun h => ⟨h.1, h.2⟩⟩
#align irreducible_iff irreducible_iff
@[simp]
theorem not_irreducible_one [Monoid α] : ¬Irreducible (1 : α) := by simp [irreducible_iff]
#align not_irreducible_one not_irreducible_one
theorem Irreducible.ne_one [Monoid α] : ∀ {p : α}, Irreducible p → p ≠ 1
| _, hp, rfl => not_irreducible_one hp
#align irreducible.ne_one Irreducible.ne_one
@[simp]
theorem not_irreducible_zero [MonoidWithZero α] : ¬Irreducible (0 : α)
| ⟨hn0, h⟩ =>
have : IsUnit (0 : α) ∨ IsUnit (0 : α) := h 0 0 (mul_zero 0).symm
this.elim hn0 hn0
#align not_irreducible_zero not_irreducible_zero
theorem Irreducible.ne_zero [MonoidWithZero α] : ∀ {p : α}, Irreducible p → p ≠ 0
| _, hp, rfl => not_irreducible_zero hp
#align irreducible.ne_zero Irreducible.ne_zero
theorem of_irreducible_mul {α} [Monoid α] {x y : α} : Irreducible (x * y) → IsUnit x ∨ IsUnit y
| ⟨_, h⟩ => h _ _ rfl
#align of_irreducible_mul of_irreducible_mul
theorem not_irreducible_pow {α} [Monoid α] {x : α} {n : ℕ} (hn : n ≠ 1) :
¬ Irreducible (x ^ n) := by
cases n with
| zero => simp
| succ n =>
intro ⟨h₁, h₂⟩
have := h₂ _ _ (pow_succ _ _)
rw [isUnit_pow_iff (Nat.succ_ne_succ.mp hn), or_self] at this
exact h₁ (this.pow _)
#noalign of_irreducible_pow
theorem irreducible_or_factor {α} [Monoid α] (x : α) (h : ¬IsUnit x) :
Irreducible x ∨ ∃ a b, ¬IsUnit a ∧ ¬IsUnit b ∧ a * b = x := by
haveI := Classical.dec
refine or_iff_not_imp_right.2 fun H => ?_
simp? [h, irreducible_iff] at H ⊢ says
simp only [exists_and_left, not_exists, not_and, irreducible_iff, h, not_false_eq_true,
true_and] at H ⊢
refine fun a b h => by_contradiction fun o => ?_
simp? [not_or] at o says simp only [not_or] at o
exact H _ o.1 _ o.2 h.symm
#align irreducible_or_factor irreducible_or_factor
/-- If `p` and `q` are irreducible, then `p ∣ q` implies `q ∣ p`. -/
theorem Irreducible.dvd_symm [Monoid α] {p q : α} (hp : Irreducible p) (hq : Irreducible q) :
p ∣ q → q ∣ p := by
rintro ⟨q', rfl⟩
rw [IsUnit.mul_right_dvd (Or.resolve_left (of_irreducible_mul hq) hp.not_unit)]
#align irreducible.dvd_symm Irreducible.dvd_symm
theorem Irreducible.dvd_comm [Monoid α] {p q : α} (hp : Irreducible p) (hq : Irreducible q) :
p ∣ q ↔ q ∣ p :=
⟨hp.dvd_symm hq, hq.dvd_symm hp⟩
#align irreducible.dvd_comm Irreducible.dvd_comm
section
variable [Monoid α]
theorem irreducible_units_mul (a : αˣ) (b : α) : Irreducible (↑a * b) ↔ Irreducible b := by
simp only [irreducible_iff, Units.isUnit_units_mul, and_congr_right_iff]
refine fun _ => ⟨fun h A B HAB => ?_, fun h A B HAB => ?_⟩
· rw [← a.isUnit_units_mul]
apply h
rw [mul_assoc, ← HAB]
· rw [← a⁻¹.isUnit_units_mul]
apply h
rw [mul_assoc, ← HAB, Units.inv_mul_cancel_left]
#align irreducible_units_mul irreducible_units_mul
theorem irreducible_isUnit_mul {a b : α} (h : IsUnit a) : Irreducible (a * b) ↔ Irreducible b :=
let ⟨a, ha⟩ := h
ha ▸ irreducible_units_mul a b
#align irreducible_is_unit_mul irreducible_isUnit_mul
theorem irreducible_mul_units (a : αˣ) (b : α) : Irreducible (b * ↑a) ↔ Irreducible b := by
simp only [irreducible_iff, Units.isUnit_mul_units, and_congr_right_iff]
refine fun _ => ⟨fun h A B HAB => ?_, fun h A B HAB => ?_⟩
· rw [← Units.isUnit_mul_units B a]
apply h
rw [← mul_assoc, ← HAB]
· rw [← Units.isUnit_mul_units B a⁻¹]
apply h
rw [← mul_assoc, ← HAB, Units.mul_inv_cancel_right]
#align irreducible_mul_units irreducible_mul_units
theorem irreducible_mul_isUnit {a b : α} (h : IsUnit a) : Irreducible (b * a) ↔ Irreducible b :=
let ⟨a, ha⟩ := h
ha ▸ irreducible_mul_units a b
#align irreducible_mul_is_unit irreducible_mul_isUnit
theorem irreducible_mul_iff {a b : α} :
Irreducible (a * b) ↔ Irreducible a ∧ IsUnit b ∨ Irreducible b ∧ IsUnit a := by
constructor
· refine fun h => Or.imp (fun h' => ⟨?_, h'⟩) (fun h' => ⟨?_, h'⟩) (h.isUnit_or_isUnit rfl).symm
· rwa [irreducible_mul_isUnit h'] at h
· rwa [irreducible_isUnit_mul h'] at h
· rintro (⟨ha, hb⟩ | ⟨hb, ha⟩)
· rwa [irreducible_mul_isUnit hb]
· rwa [irreducible_isUnit_mul ha]
#align irreducible_mul_iff irreducible_mul_iff
end
section CommMonoid
variable [CommMonoid α] {a : α}
theorem Irreducible.not_square (ha : Irreducible a) : ¬IsSquare a := by
rw [isSquare_iff_exists_sq]
rintro ⟨b, rfl⟩
exact not_irreducible_pow (by decide) ha
#align irreducible.not_square Irreducible.not_square
theorem IsSquare.not_irreducible (ha : IsSquare a) : ¬Irreducible a := fun h => h.not_square ha
#align is_square.not_irreducible IsSquare.not_irreducible
end CommMonoid
section CommMonoidWithZero
variable [CommMonoidWithZero α]
theorem Irreducible.prime_of_isPrimal {a : α}
(irr : Irreducible a) (primal : IsPrimal a) : Prime a :=
⟨irr.ne_zero, irr.not_unit, fun a b dvd ↦ by
obtain ⟨d₁, d₂, h₁, h₂, rfl⟩ := primal dvd
exact (of_irreducible_mul irr).symm.imp (·.mul_right_dvd.mpr h₁) (·.mul_left_dvd.mpr h₂)⟩
theorem Irreducible.prime [DecompositionMonoid α] {a : α} (irr : Irreducible a) : Prime a :=
irr.prime_of_isPrimal (DecompositionMonoid.primal a)
end CommMonoidWithZero
section CancelCommMonoidWithZero
variable [CancelCommMonoidWithZero α] {a p : α}
protected theorem Prime.irreducible (hp : Prime p) : Irreducible p :=
⟨hp.not_unit, fun a b ↦ by
rintro rfl
exact (hp.dvd_or_dvd dvd_rfl).symm.imp
(isUnit_of_dvd_one <| (mul_dvd_mul_iff_right <| right_ne_zero_of_mul hp.ne_zero).mp <|
dvd_mul_of_dvd_right · _)
(isUnit_of_dvd_one <| (mul_dvd_mul_iff_left <| left_ne_zero_of_mul hp.ne_zero).mp <|
dvd_mul_of_dvd_left · _)⟩
#align prime.irreducible Prime.irreducible
theorem irreducible_iff_prime [DecompositionMonoid α] {a : α} : Irreducible a ↔ Prime a :=
⟨Irreducible.prime, Prime.irreducible⟩
theorem succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul (hp : Prime p) {a b : α} {k l : ℕ} :
p ^ k ∣ a → p ^ l ∣ b → p ^ (k + l + 1) ∣ a * b → p ^ (k + 1) ∣ a ∨ p ^ (l + 1) ∣ b :=
fun ⟨x, hx⟩ ⟨y, hy⟩ ⟨z, hz⟩ =>
have h : p ^ (k + l) * (x * y) = p ^ (k + l) * (p * z) := by
simpa [mul_comm, pow_add, hx, hy, mul_assoc, mul_left_comm] using hz
have hp0 : p ^ (k + l) ≠ 0 := pow_ne_zero _ hp.ne_zero
have hpd : p ∣ x * y := ⟨z, by rwa [mul_right_inj' hp0] at h⟩
(hp.dvd_or_dvd hpd).elim
(fun ⟨d, hd⟩ => Or.inl ⟨d, by simp [*, pow_succ, mul_comm, mul_left_comm, mul_assoc]⟩)
fun ⟨d, hd⟩ => Or.inr ⟨d, by simp [*, pow_succ, mul_comm, mul_left_comm, mul_assoc]⟩
#align succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul succ_dvd_or_succ_dvd_of_succ_sum_dvd_mul
theorem Prime.not_square (hp : Prime p) : ¬IsSquare p :=
hp.irreducible.not_square
#align prime.not_square Prime.not_square
theorem IsSquare.not_prime (ha : IsSquare a) : ¬Prime a := fun h => h.not_square ha
#align is_square.not_prime IsSquare.not_prime
theorem not_prime_pow {n : ℕ} (hn : n ≠ 1) : ¬Prime (a ^ n) := fun hp =>
not_irreducible_pow hn hp.irreducible
#align pow_not_prime not_prime_pow
end CancelCommMonoidWithZero
/-- Two elements of a `Monoid` are `Associated` if one of them is another one
multiplied by a unit on the right. -/
def Associated [Monoid α] (x y : α) : Prop :=
∃ u : αˣ, x * u = y
#align associated Associated
/-- Notation for two elements of a monoid are associated, i.e.
if one of them is another one multiplied by a unit on the right. -/
local infixl:50 " ~ᵤ " => Associated
namespace Associated
@[refl]
protected theorem refl [Monoid α] (x : α) : x ~ᵤ x :=
⟨1, by simp⟩
#align associated.refl Associated.refl
protected theorem rfl [Monoid α] {x : α} : x ~ᵤ x :=
.refl x
instance [Monoid α] : IsRefl α Associated :=
⟨Associated.refl⟩
@[symm]
protected theorem symm [Monoid α] : ∀ {x y : α}, x ~ᵤ y → y ~ᵤ x
| x, _, ⟨u, rfl⟩ => ⟨u⁻¹, by rw [mul_assoc, Units.mul_inv, mul_one]⟩
#align associated.symm Associated.symm
instance [Monoid α] : IsSymm α Associated :=
⟨fun _ _ => Associated.symm⟩
protected theorem comm [Monoid α] {x y : α} : x ~ᵤ y ↔ y ~ᵤ x :=
⟨Associated.symm, Associated.symm⟩
#align associated.comm Associated.comm
@[trans]
protected theorem trans [Monoid α] : ∀ {x y z : α}, x ~ᵤ y → y ~ᵤ z → x ~ᵤ z
| x, _, _, ⟨u, rfl⟩, ⟨v, rfl⟩ => ⟨u * v, by rw [Units.val_mul, mul_assoc]⟩
#align associated.trans Associated.trans
instance [Monoid α] : IsTrans α Associated :=
⟨fun _ _ _ => Associated.trans⟩
/-- The setoid of the relation `x ~ᵤ y` iff there is a unit `u` such that `x * u = y` -/
protected def setoid (α : Type*) [Monoid α] :
Setoid α where
r := Associated
iseqv := ⟨Associated.refl, Associated.symm, Associated.trans⟩
#align associated.setoid Associated.setoid
theorem map {M N : Type*} [Monoid M] [Monoid N] {F : Type*} [FunLike F M N] [MonoidHomClass F M N]
(f : F) {x y : M} (ha : Associated x y) : Associated (f x) (f y) := by
obtain ⟨u, ha⟩ := ha
exact ⟨Units.map f u, by rw [← ha, map_mul, Units.coe_map, MonoidHom.coe_coe]⟩
end Associated
attribute [local instance] Associated.setoid
theorem unit_associated_one [Monoid α] {u : αˣ} : (u : α) ~ᵤ 1 :=
⟨u⁻¹, Units.mul_inv u⟩
#align unit_associated_one unit_associated_one
@[simp]
theorem associated_one_iff_isUnit [Monoid α] {a : α} : (a : α) ~ᵤ 1 ↔ IsUnit a :=
Iff.intro
(fun h =>
let ⟨c, h⟩ := h.symm
h ▸ ⟨c, (one_mul _).symm⟩)
fun ⟨c, h⟩ => Associated.symm ⟨c, by simp [h]⟩
#align associated_one_iff_is_unit associated_one_iff_isUnit
@[simp]
theorem associated_zero_iff_eq_zero [MonoidWithZero α] (a : α) : a ~ᵤ 0 ↔ a = 0 :=
Iff.intro
(fun h => by
let ⟨u, h⟩ := h.symm
simpa using h.symm)
fun h => h ▸ Associated.refl a
#align associated_zero_iff_eq_zero associated_zero_iff_eq_zero
theorem associated_one_of_mul_eq_one [CommMonoid α] {a : α} (b : α) (hab : a * b = 1) : a ~ᵤ 1 :=
show (Units.mkOfMulEqOne a b hab : α) ~ᵤ 1 from unit_associated_one
#align associated_one_of_mul_eq_one associated_one_of_mul_eq_one
theorem associated_one_of_associated_mul_one [CommMonoid α] {a b : α} : a * b ~ᵤ 1 → a ~ᵤ 1
| ⟨u, h⟩ => associated_one_of_mul_eq_one (b * u) <| by simpa [mul_assoc] using h
#align associated_one_of_associated_mul_one associated_one_of_associated_mul_one
theorem associated_mul_unit_left {β : Type*} [Monoid β] (a u : β) (hu : IsUnit u) :
Associated (a * u) a :=
let ⟨u', hu⟩ := hu
⟨u'⁻¹, hu ▸ Units.mul_inv_cancel_right _ _⟩
#align associated_mul_unit_left associated_mul_unit_left
theorem associated_unit_mul_left {β : Type*} [CommMonoid β] (a u : β) (hu : IsUnit u) :
Associated (u * a) a := by
rw [mul_comm]
exact associated_mul_unit_left _ _ hu
#align associated_unit_mul_left associated_unit_mul_left
theorem associated_mul_unit_right {β : Type*} [Monoid β] (a u : β) (hu : IsUnit u) :
Associated a (a * u) :=
(associated_mul_unit_left a u hu).symm
#align associated_mul_unit_right associated_mul_unit_right
theorem associated_unit_mul_right {β : Type*} [CommMonoid β] (a u : β) (hu : IsUnit u) :
Associated a (u * a) :=
(associated_unit_mul_left a u hu).symm
#align associated_unit_mul_right associated_unit_mul_right
theorem associated_mul_isUnit_left_iff {β : Type*} [Monoid β] {a u b : β} (hu : IsUnit u) :
Associated (a * u) b ↔ Associated a b :=
⟨(associated_mul_unit_right _ _ hu).trans, (associated_mul_unit_left _ _ hu).trans⟩
#align associated_mul_is_unit_left_iff associated_mul_isUnit_left_iff
theorem associated_isUnit_mul_left_iff {β : Type*} [CommMonoid β] {u a b : β} (hu : IsUnit u) :
Associated (u * a) b ↔ Associated a b := by
rw [mul_comm]
exact associated_mul_isUnit_left_iff hu
#align associated_is_unit_mul_left_iff associated_isUnit_mul_left_iff
theorem associated_mul_isUnit_right_iff {β : Type*} [Monoid β] {a b u : β} (hu : IsUnit u) :
Associated a (b * u) ↔ Associated a b :=
Associated.comm.trans <| (associated_mul_isUnit_left_iff hu).trans Associated.comm
#align associated_mul_is_unit_right_iff associated_mul_isUnit_right_iff
theorem associated_isUnit_mul_right_iff {β : Type*} [CommMonoid β] {a u b : β} (hu : IsUnit u) :
Associated a (u * b) ↔ Associated a b :=
Associated.comm.trans <| (associated_isUnit_mul_left_iff hu).trans Associated.comm
#align associated_is_unit_mul_right_iff associated_isUnit_mul_right_iff
@[simp]
theorem associated_mul_unit_left_iff {β : Type*} [Monoid β] {a b : β} {u : Units β} :
Associated (a * u) b ↔ Associated a b :=
associated_mul_isUnit_left_iff u.isUnit
#align associated_mul_unit_left_iff associated_mul_unit_left_iff
@[simp]
theorem associated_unit_mul_left_iff {β : Type*} [CommMonoid β] {a b : β} {u : Units β} :
Associated (↑u * a) b ↔ Associated a b :=
associated_isUnit_mul_left_iff u.isUnit
#align associated_unit_mul_left_iff associated_unit_mul_left_iff
@[simp]
theorem associated_mul_unit_right_iff {β : Type*} [Monoid β] {a b : β} {u : Units β} :
Associated a (b * u) ↔ Associated a b :=
associated_mul_isUnit_right_iff u.isUnit
#align associated_mul_unit_right_iff associated_mul_unit_right_iff
@[simp]
theorem associated_unit_mul_right_iff {β : Type*} [CommMonoid β] {a b : β} {u : Units β} :
Associated a (↑u * b) ↔ Associated a b :=
associated_isUnit_mul_right_iff u.isUnit
#align associated_unit_mul_right_iff associated_unit_mul_right_iff
theorem Associated.mul_left [Monoid α] (a : α) {b c : α} (h : b ~ᵤ c) : a * b ~ᵤ a * c := by
obtain ⟨d, rfl⟩ := h; exact ⟨d, mul_assoc _ _ _⟩
#align associated.mul_left Associated.mul_left
theorem Associated.mul_right [CommMonoid α] {a b : α} (h : a ~ᵤ b) (c : α) : a * c ~ᵤ b * c := by
obtain ⟨d, rfl⟩ := h; exact ⟨d, mul_right_comm _ _ _⟩
#align associated.mul_right Associated.mul_right
theorem Associated.mul_mul [CommMonoid α] {a₁ a₂ b₁ b₂ : α}
(h₁ : a₁ ~ᵤ b₁) (h₂ : a₂ ~ᵤ b₂) : a₁ * a₂ ~ᵤ b₁ * b₂ := (h₁.mul_right _).trans (h₂.mul_left _)
#align associated.mul_mul Associated.mul_mul
theorem Associated.pow_pow [CommMonoid α] {a b : α} {n : ℕ} (h : a ~ᵤ b) : a ^ n ~ᵤ b ^ n := by
induction' n with n ih
· simp [Associated.refl]
convert h.mul_mul ih <;> rw [pow_succ']
#align associated.pow_pow Associated.pow_pow
protected theorem Associated.dvd [Monoid α] {a b : α} : a ~ᵤ b → a ∣ b := fun ⟨u, hu⟩ =>
⟨u, hu.symm⟩
#align associated.dvd Associated.dvd
protected theorem Associated.dvd' [Monoid α] {a b : α} (h : a ~ᵤ b) : b ∣ a :=
h.symm.dvd
protected theorem Associated.dvd_dvd [Monoid α] {a b : α} (h : a ~ᵤ b) : a ∣ b ∧ b ∣ a :=
⟨h.dvd, h.symm.dvd⟩
#align associated.dvd_dvd Associated.dvd_dvd
theorem associated_of_dvd_dvd [CancelMonoidWithZero α] {a b : α} (hab : a ∣ b) (hba : b ∣ a) :
a ~ᵤ b := by
rcases hab with ⟨c, rfl⟩
rcases hba with ⟨d, a_eq⟩
by_cases ha0 : a = 0
· simp_all
have hac0 : a * c ≠ 0 := by
intro con
rw [con, zero_mul] at a_eq
apply ha0 a_eq
have : a * (c * d) = a * 1 := by rw [← mul_assoc, ← a_eq, mul_one]
have hcd : c * d = 1 := mul_left_cancel₀ ha0 this
have : a * c * (d * c) = a * c * 1 := by rw [← mul_assoc, ← a_eq, mul_one]
have hdc : d * c = 1 := mul_left_cancel₀ hac0 this
exact ⟨⟨c, d, hcd, hdc⟩, rfl⟩
#align associated_of_dvd_dvd associated_of_dvd_dvd
theorem dvd_dvd_iff_associated [CancelMonoidWithZero α] {a b : α} : a ∣ b ∧ b ∣ a ↔ a ~ᵤ b :=
⟨fun ⟨h1, h2⟩ => associated_of_dvd_dvd h1 h2, Associated.dvd_dvd⟩
#align dvd_dvd_iff_associated dvd_dvd_iff_associated
instance [CancelMonoidWithZero α] [DecidableRel ((· ∣ ·) : α → α → Prop)] :
DecidableRel ((· ~ᵤ ·) : α → α → Prop) := fun _ _ => decidable_of_iff _ dvd_dvd_iff_associated
theorem Associated.dvd_iff_dvd_left [Monoid α] {a b c : α} (h : a ~ᵤ b) : a ∣ c ↔ b ∣ c :=
let ⟨_, hu⟩ := h
hu ▸ Units.mul_right_dvd.symm
#align associated.dvd_iff_dvd_left Associated.dvd_iff_dvd_left
theorem Associated.dvd_iff_dvd_right [Monoid α] {a b c : α} (h : b ~ᵤ c) : a ∣ b ↔ a ∣ c :=
let ⟨_, hu⟩ := h
hu ▸ Units.dvd_mul_right.symm
#align associated.dvd_iff_dvd_right Associated.dvd_iff_dvd_right
theorem Associated.eq_zero_iff [MonoidWithZero α] {a b : α} (h : a ~ᵤ b) : a = 0 ↔ b = 0 := by
obtain ⟨u, rfl⟩ := h
rw [← Units.eq_mul_inv_iff_mul_eq, zero_mul]
#align associated.eq_zero_iff Associated.eq_zero_iff
theorem Associated.ne_zero_iff [MonoidWithZero α] {a b : α} (h : a ~ᵤ b) : a ≠ 0 ↔ b ≠ 0 :=
not_congr h.eq_zero_iff
#align associated.ne_zero_iff Associated.ne_zero_iff
theorem Associated.neg_left [Monoid α] [HasDistribNeg α] {a b : α} (h : Associated a b) :
Associated (-a) b :=
let ⟨u, hu⟩ := h; ⟨-u, by simp [hu]⟩
theorem Associated.neg_right [Monoid α] [HasDistribNeg α] {a b : α} (h : Associated a b) :
Associated a (-b) :=
h.symm.neg_left.symm
theorem Associated.neg_neg [Monoid α] [HasDistribNeg α] {a b : α} (h : Associated a b) :
Associated (-a) (-b) :=
h.neg_left.neg_right
protected theorem Associated.prime [CommMonoidWithZero α] {p q : α} (h : p ~ᵤ q) (hp : Prime p) :
Prime q :=
⟨h.ne_zero_iff.1 hp.ne_zero,
let ⟨u, hu⟩ := h
⟨fun ⟨v, hv⟩ => hp.not_unit ⟨v * u⁻¹, by simp [hv, hu.symm]⟩,
hu ▸ by
simp only [IsUnit.mul_iff, Units.isUnit, and_true, IsUnit.mul_right_dvd]
intro a b
exact hp.dvd_or_dvd⟩⟩
#align associated.prime Associated.prime
theorem prime_mul_iff [CancelCommMonoidWithZero α] {x y : α} :
Prime (x * y) ↔ (Prime x ∧ IsUnit y) ∨ (IsUnit x ∧ Prime y) := by
refine ⟨fun h ↦ ?_, ?_⟩
· rcases of_irreducible_mul h.irreducible with hx | hy
· exact Or.inr ⟨hx, (associated_unit_mul_left y x hx).prime h⟩
· exact Or.inl ⟨(associated_mul_unit_left x y hy).prime h, hy⟩
· rintro (⟨hx, hy⟩ | ⟨hx, hy⟩)
· exact (associated_mul_unit_left x y hy).symm.prime hx
· exact (associated_unit_mul_right y x hx).prime hy
@[simp]
lemma prime_pow_iff [CancelCommMonoidWithZero α] {p : α} {n : ℕ} :
Prime (p ^ n) ↔ Prime p ∧ n = 1 := by
refine ⟨fun hp ↦ ?_, fun ⟨hp, hn⟩ ↦ by simpa [hn]⟩
suffices n = 1 by aesop
cases' n with n
· simp at hp
· rw [Nat.succ.injEq]
rw [pow_succ', prime_mul_iff] at hp
rcases hp with ⟨hp, hpn⟩ | ⟨hp, hpn⟩
· by_contra contra
rw [isUnit_pow_iff contra] at hpn
exact hp.not_unit hpn
· exfalso
exact hpn.not_unit (hp.pow n)
theorem Irreducible.dvd_iff [Monoid α] {x y : α} (hx : Irreducible x) :
y ∣ x ↔ IsUnit y ∨ Associated x y := by
constructor
· rintro ⟨z, hz⟩
obtain (h|h) := hx.isUnit_or_isUnit hz
· exact Or.inl h
· rw [hz]
exact Or.inr (associated_mul_unit_left _ _ h)
· rintro (hy|h)
· exact hy.dvd
· exact h.symm.dvd
theorem Irreducible.associated_of_dvd [Monoid α] {p q : α} (p_irr : Irreducible p)
(q_irr : Irreducible q) (dvd : p ∣ q) : Associated p q :=
((q_irr.dvd_iff.mp dvd).resolve_left p_irr.not_unit).symm
#align irreducible.associated_of_dvd Irreducible.associated_of_dvdₓ
theorem Irreducible.dvd_irreducible_iff_associated [Monoid α] {p q : α}
(pp : Irreducible p) (qp : Irreducible q) : p ∣ q ↔ Associated p q :=
⟨Irreducible.associated_of_dvd pp qp, Associated.dvd⟩
#align irreducible.dvd_irreducible_iff_associated Irreducible.dvd_irreducible_iff_associated
theorem Prime.associated_of_dvd [CancelCommMonoidWithZero α] {p q : α} (p_prime : Prime p)
(q_prime : Prime q) (dvd : p ∣ q) : Associated p q :=
p_prime.irreducible.associated_of_dvd q_prime.irreducible dvd
#align prime.associated_of_dvd Prime.associated_of_dvd
theorem Prime.dvd_prime_iff_associated [CancelCommMonoidWithZero α] {p q : α} (pp : Prime p)
(qp : Prime q) : p ∣ q ↔ Associated p q :=
pp.irreducible.dvd_irreducible_iff_associated qp.irreducible
#align prime.dvd_prime_iff_associated Prime.dvd_prime_iff_associated
theorem Associated.prime_iff [CommMonoidWithZero α] {p q : α} (h : p ~ᵤ q) : Prime p ↔ Prime q :=
⟨h.prime, h.symm.prime⟩
#align associated.prime_iff Associated.prime_iff
protected theorem Associated.isUnit [Monoid α] {a b : α} (h : a ~ᵤ b) : IsUnit a → IsUnit b :=
let ⟨u, hu⟩ := h
fun ⟨v, hv⟩ => ⟨v * u, by simp [hv, hu.symm]⟩
#align associated.is_unit Associated.isUnit
theorem Associated.isUnit_iff [Monoid α] {a b : α} (h : a ~ᵤ b) : IsUnit a ↔ IsUnit b :=
⟨h.isUnit, h.symm.isUnit⟩
#align associated.is_unit_iff Associated.isUnit_iff
theorem Irreducible.isUnit_iff_not_associated_of_dvd [Monoid α]
{x y : α} (hx : Irreducible x) (hy : y ∣ x) : IsUnit y ↔ ¬ Associated x y :=
⟨fun hy hxy => hx.1 (hxy.symm.isUnit hy), (hx.dvd_iff.mp hy).resolve_right⟩
protected theorem Associated.irreducible [Monoid α] {p q : α} (h : p ~ᵤ q) (hp : Irreducible p) :
Irreducible q :=
⟨mt h.symm.isUnit hp.1,
let ⟨u, hu⟩ := h
fun a b hab =>
have hpab : p = a * (b * (u⁻¹ : αˣ)) :=
calc
p = p * u * (u⁻¹ : αˣ) := by simp
_ = _ := by rw [hu]; simp [hab, mul_assoc]
(hp.isUnit_or_isUnit hpab).elim Or.inl fun ⟨v, hv⟩ => Or.inr ⟨v * u, by simp [hv]⟩⟩
#align associated.irreducible Associated.irreducible
protected theorem Associated.irreducible_iff [Monoid α] {p q : α} (h : p ~ᵤ q) :
Irreducible p ↔ Irreducible q :=
⟨h.irreducible, h.symm.irreducible⟩
#align associated.irreducible_iff Associated.irreducible_iff
theorem Associated.of_mul_left [CancelCommMonoidWithZero α] {a b c d : α} (h : a * b ~ᵤ c * d)
(h₁ : a ~ᵤ c) (ha : a ≠ 0) : b ~ᵤ d :=
let ⟨u, hu⟩ := h
let ⟨v, hv⟩ := Associated.symm h₁
⟨u * (v : αˣ),
mul_left_cancel₀ ha
(by
rw [← hv, mul_assoc c (v : α) d, mul_left_comm c, ← hu]
simp [hv.symm, mul_assoc, mul_comm, mul_left_comm])⟩
#align associated.of_mul_left Associated.of_mul_left
theorem Associated.of_mul_right [CancelCommMonoidWithZero α] {a b c d : α} :
a * b ~ᵤ c * d → b ~ᵤ d → b ≠ 0 → a ~ᵤ c := by
rw [mul_comm a, mul_comm c]; exact Associated.of_mul_left
#align associated.of_mul_right Associated.of_mul_right
theorem Associated.of_pow_associated_of_prime [CancelCommMonoidWithZero α] {p₁ p₂ : α} {k₁ k₂ : ℕ}
(hp₁ : Prime p₁) (hp₂ : Prime p₂) (hk₁ : 0 < k₁) (h : p₁ ^ k₁ ~ᵤ p₂ ^ k₂) : p₁ ~ᵤ p₂ := by
have : p₁ ∣ p₂ ^ k₂ := by
rw [← h.dvd_iff_dvd_right]
apply dvd_pow_self _ hk₁.ne'
rw [← hp₁.dvd_prime_iff_associated hp₂]
exact hp₁.dvd_of_dvd_pow this
#align associated.of_pow_associated_of_prime Associated.of_pow_associated_of_prime
theorem Associated.of_pow_associated_of_prime' [CancelCommMonoidWithZero α] {p₁ p₂ : α} {k₁ k₂ : ℕ}
(hp₁ : Prime p₁) (hp₂ : Prime p₂) (hk₂ : 0 < k₂) (h : p₁ ^ k₁ ~ᵤ p₂ ^ k₂) : p₁ ~ᵤ p₂ :=
(h.symm.of_pow_associated_of_prime hp₂ hp₁ hk₂).symm
#align associated.of_pow_associated_of_prime' Associated.of_pow_associated_of_prime'
/-- See also `Irreducible.coprime_iff_not_dvd`. -/
lemma Irreducible.isRelPrime_iff_not_dvd [Monoid α] {p n : α} (hp : Irreducible p) :
IsRelPrime p n ↔ ¬ p ∣ n := by
refine ⟨fun h contra ↦ hp.not_unit (h dvd_rfl contra), fun hpn d hdp hdn ↦ ?_⟩
contrapose! hpn
suffices Associated p d from this.dvd.trans hdn
exact (hp.dvd_iff.mp hdp).resolve_left hpn
lemma Irreducible.dvd_or_isRelPrime [Monoid α] {p n : α} (hp : Irreducible p) :
p ∣ n ∨ IsRelPrime p n := Classical.or_iff_not_imp_left.mpr hp.isRelPrime_iff_not_dvd.2
section UniqueUnits
variable [Monoid α] [Unique αˣ]
theorem associated_iff_eq {x y : α} : x ~ᵤ y ↔ x = y := by
constructor
· rintro ⟨c, rfl⟩
rw [units_eq_one c, Units.val_one, mul_one]
· rintro rfl
rfl
#align associated_iff_eq associated_iff_eq
theorem associated_eq_eq : (Associated : α → α → Prop) = Eq := by
ext
rw [associated_iff_eq]
#align associated_eq_eq associated_eq_eq
theorem prime_dvd_prime_iff_eq {M : Type*} [CancelCommMonoidWithZero M] [Unique Mˣ] {p q : M}
(pp : Prime p) (qp : Prime q) : p ∣ q ↔ p = q := by
rw [pp.dvd_prime_iff_associated qp, ← associated_eq_eq]
#align prime_dvd_prime_iff_eq prime_dvd_prime_iff_eq
end UniqueUnits
section UniqueUnits₀
variable {R : Type*} [CancelCommMonoidWithZero R] [Unique Rˣ] {p₁ p₂ : R} {k₁ k₂ : ℕ}
theorem eq_of_prime_pow_eq (hp₁ : Prime p₁) (hp₂ : Prime p₂) (hk₁ : 0 < k₁)
(h : p₁ ^ k₁ = p₂ ^ k₂) : p₁ = p₂ := by
rw [← associated_iff_eq] at h ⊢
apply h.of_pow_associated_of_prime hp₁ hp₂ hk₁
#align eq_of_prime_pow_eq eq_of_prime_pow_eq
theorem eq_of_prime_pow_eq' (hp₁ : Prime p₁) (hp₂ : Prime p₂) (hk₁ : 0 < k₂)
(h : p₁ ^ k₁ = p₂ ^ k₂) : p₁ = p₂ := by
rw [← associated_iff_eq] at h ⊢
apply h.of_pow_associated_of_prime' hp₁ hp₂ hk₁
#align eq_of_prime_pow_eq' eq_of_prime_pow_eq'
end UniqueUnits₀
/-- The quotient of a monoid by the `Associated` relation. Two elements `x` and `y`
are associated iff there is a unit `u` such that `x * u = y`. There is a natural
monoid structure on `Associates α`. -/
abbrev Associates (α : Type*) [Monoid α] : Type _ :=
Quotient (Associated.setoid α)
#align associates Associates
namespace Associates
open Associated
/-- The canonical quotient map from a monoid `α` into the `Associates` of `α` -/
protected abbrev mk {α : Type*} [Monoid α] (a : α) : Associates α :=
⟦a⟧
#align associates.mk Associates.mk
instance [Monoid α] : Inhabited (Associates α) :=
⟨⟦1⟧⟩
theorem mk_eq_mk_iff_associated [Monoid α] {a b : α} : Associates.mk a = Associates.mk b ↔ a ~ᵤ b :=
Iff.intro Quotient.exact Quot.sound
#align associates.mk_eq_mk_iff_associated Associates.mk_eq_mk_iff_associated
theorem quotient_mk_eq_mk [Monoid α] (a : α) : ⟦a⟧ = Associates.mk a :=
rfl
#align associates.quotient_mk_eq_mk Associates.quotient_mk_eq_mk
theorem quot_mk_eq_mk [Monoid α] (a : α) : Quot.mk Setoid.r a = Associates.mk a :=
rfl
#align associates.quot_mk_eq_mk Associates.quot_mk_eq_mk
@[simp]
| Mathlib/Algebra/Associated.lean | 854 | 855 | theorem quot_out [Monoid α] (a : Associates α) : Associates.mk (Quot.out a) = a := by |
rw [← quot_mk_eq_mk, Quot.out_eq]
|
/-
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]
| Mathlib/Topology/Algebra/UniformGroup.lean | 187 | 192 | 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 }
|
/-
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]
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 1,490 | 1,493 | 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
|
/-
Copyright (c) 2022 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.RingTheory.EisensteinCriterion
import Mathlib.RingTheory.Polynomial.ScaleRoots
#align_import ring_theory.polynomial.eisenstein.basic from "leanprover-community/mathlib"@"2032a878972d5672e7c27c957e7a6e297b044973"
/-!
# Eisenstein polynomials
Given an ideal `𝓟` of a commutative semiring `R`, we say that a polynomial `f : R[X]` is
*Eisenstein at `𝓟`* if `f.leadingCoeff ∉ 𝓟`, `∀ n, n < f.natDegree → f.coeff n ∈ 𝓟` and
`f.coeff 0 ∉ 𝓟 ^ 2`. In this file we gather miscellaneous results about Eisenstein polynomials.
## Main definitions
* `Polynomial.IsEisensteinAt f 𝓟`: the property of being Eisenstein at `𝓟`.
## Main results
* `Polynomial.IsEisensteinAt.irreducible`: if a primitive `f` satisfies `f.IsEisensteinAt 𝓟`,
where `𝓟.IsPrime`, then `f` is irreducible.
## Implementation details
We also define a notion `IsWeaklyEisensteinAt` requiring only that
`∀ n < f.natDegree → f.coeff n ∈ 𝓟`. This makes certain results slightly more general and it is
useful since it is sometimes better behaved (for example it is stable under `Polynomial.map`).
-/
universe u v w z
variable {R : Type u}
open Ideal Algebra Finset
open Polynomial
namespace Polynomial
/-- Given an ideal `𝓟` of a commutative semiring `R`, we say that a polynomial `f : R[X]`
is *weakly Eisenstein at `𝓟`* if `∀ n, n < f.natDegree → f.coeff n ∈ 𝓟`. -/
@[mk_iff]
structure IsWeaklyEisensteinAt [CommSemiring R] (f : R[X]) (𝓟 : Ideal R) : Prop where
mem : ∀ {n}, n < f.natDegree → f.coeff n ∈ 𝓟
#align polynomial.is_weakly_eisenstein_at Polynomial.IsWeaklyEisensteinAt
/-- Given an ideal `𝓟` of a commutative semiring `R`, we say that a polynomial `f : R[X]`
is *Eisenstein at `𝓟`* if `f.leadingCoeff ∉ 𝓟`, `∀ n, n < f.natDegree → f.coeff n ∈ 𝓟` and
`f.coeff 0 ∉ 𝓟 ^ 2`. -/
@[mk_iff]
structure IsEisensteinAt [CommSemiring R] (f : R[X]) (𝓟 : Ideal R) : Prop where
leading : f.leadingCoeff ∉ 𝓟
mem : ∀ {n}, n < f.natDegree → f.coeff n ∈ 𝓟
not_mem : f.coeff 0 ∉ 𝓟 ^ 2
#align polynomial.is_eisenstein_at Polynomial.IsEisensteinAt
namespace IsWeaklyEisensteinAt
section CommSemiring
variable [CommSemiring R] {𝓟 : Ideal R} {f : R[X]} (hf : f.IsWeaklyEisensteinAt 𝓟)
theorem map {A : Type v} [CommRing A] (φ : R →+* A) : (f.map φ).IsWeaklyEisensteinAt (𝓟.map φ) := by
refine (isWeaklyEisensteinAt_iff _ _).2 fun hn => ?_
rw [coeff_map]
exact mem_map_of_mem _ (hf.mem (lt_of_lt_of_le hn (natDegree_map_le _ _)))
#align polynomial.is_weakly_eisenstein_at.map Polynomial.IsWeaklyEisensteinAt.map
end CommSemiring
section CommRing
variable [CommRing R] {𝓟 : Ideal R} {f : R[X]} (hf : f.IsWeaklyEisensteinAt 𝓟)
variable {S : Type v} [CommRing S] [Algebra R S]
section Principal
variable {p : R}
| Mathlib/RingTheory/Polynomial/Eisenstein/Basic.lean | 83 | 108 | theorem exists_mem_adjoin_mul_eq_pow_natDegree {x : S} (hx : aeval x f = 0) (hmo : f.Monic)
(hf : f.IsWeaklyEisensteinAt (Submodule.span R {p})) : ∃ y ∈ adjoin R ({x} : Set S),
(algebraMap R S) p * y = x ^ (f.map (algebraMap R S)).natDegree := by |
rw [aeval_def, Polynomial.eval₂_eq_eval_map, eval_eq_sum_range, range_add_one,
sum_insert not_mem_range_self, sum_range, (hmo.map (algebraMap R S)).coeff_natDegree,
one_mul] at hx
replace hx := eq_neg_of_add_eq_zero_left hx
have : ∀ n < f.natDegree, p ∣ f.coeff n := by
intro n hn
exact mem_span_singleton.1 (by simpa using hf.mem hn)
choose! φ hφ using this
conv_rhs at hx =>
congr
congr
· skip
ext i
rw [coeff_map, hφ i.1 (lt_of_lt_of_le i.2 (natDegree_map_le _ _)),
RingHom.map_mul, mul_assoc]
rw [hx, ← mul_sum, neg_eq_neg_one_mul, ← mul_assoc (-1 : S), mul_comm (-1 : S), mul_assoc]
refine
⟨-1 * ∑ i : Fin (f.map (algebraMap R S)).natDegree, (algebraMap R S) (φ i.1) * x ^ i.1, ?_, rfl⟩
exact
Subalgebra.mul_mem _ (Subalgebra.neg_mem _ (Subalgebra.one_mem _))
(Subalgebra.sum_mem _ fun i _ =>
Subalgebra.mul_mem _ (Subalgebra.algebraMap_mem _ _)
(Subalgebra.pow_mem _ (subset_adjoin (Set.mem_singleton x)) _))
|
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, François Dupuis
-/
import Mathlib.Analysis.Convex.Basic
import Mathlib.Order.Filter.Extr
import Mathlib.Tactic.GCongr
#align_import analysis.convex.function from "leanprover-community/mathlib"@"92ca63f0fb391a9ca5f22d2409a6080e786d99f7"
/-!
# Convex and concave functions
This file defines convex and concave functions in vector spaces and proves the finite Jensen
inequality. The integral version can be found in `Analysis.Convex.Integral`.
A function `f : E → β` is `ConvexOn` a set `s` if `s` is itself a convex set, and for any two
points `x y ∈ s`, the segment joining `(x, f x)` to `(y, f y)` is above the graph of `f`.
Equivalently, `ConvexOn 𝕜 f s` means that the epigraph `{p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2}` is
a convex set.
## Main declarations
* `ConvexOn 𝕜 s f`: The function `f` is convex on `s` with scalars `𝕜`.
* `ConcaveOn 𝕜 s f`: The function `f` is concave on `s` with scalars `𝕜`.
* `StrictConvexOn 𝕜 s f`: The function `f` is strictly convex on `s` with scalars `𝕜`.
* `StrictConcaveOn 𝕜 s f`: The function `f` is strictly concave on `s` with scalars `𝕜`.
-/
open scoped Classical
open LinearMap Set Convex Pointwise
variable {𝕜 E F α β ι : Type*}
section OrderedSemiring
variable [OrderedSemiring 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [AddCommMonoid F]
section OrderedAddCommMonoid
variable [OrderedAddCommMonoid α] [OrderedAddCommMonoid β]
section SMul
variable (𝕜) [SMul 𝕜 E] [SMul 𝕜 α] [SMul 𝕜 β] (s : Set E) (f : E → β) {g : β → α}
/-- Convexity of functions -/
def ConvexOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 →
f (a • x + b • y) ≤ a • f x + b • f y
#align convex_on ConvexOn
/-- Concavity of functions -/
def ConcaveOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y)
#align concave_on ConcaveOn
/-- Strict convexity of functions -/
def StrictConvexOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x ≠ y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) < a • f x + b • f y
#align strict_convex_on StrictConvexOn
/-- Strict concavity of functions -/
def StrictConcaveOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x ≠ y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y < f (a • x + b • y)
#align strict_concave_on StrictConcaveOn
variable {𝕜 s f}
open OrderDual (toDual ofDual)
theorem ConvexOn.dual (hf : ConvexOn 𝕜 s f) : ConcaveOn 𝕜 s (toDual ∘ f) := hf
#align convex_on.dual ConvexOn.dual
theorem ConcaveOn.dual (hf : ConcaveOn 𝕜 s f) : ConvexOn 𝕜 s (toDual ∘ f) := hf
#align concave_on.dual ConcaveOn.dual
theorem StrictConvexOn.dual (hf : StrictConvexOn 𝕜 s f) : StrictConcaveOn 𝕜 s (toDual ∘ f) := hf
#align strict_convex_on.dual StrictConvexOn.dual
theorem StrictConcaveOn.dual (hf : StrictConcaveOn 𝕜 s f) : StrictConvexOn 𝕜 s (toDual ∘ f) := hf
#align strict_concave_on.dual StrictConcaveOn.dual
theorem convexOn_id {s : Set β} (hs : Convex 𝕜 s) : ConvexOn 𝕜 s _root_.id :=
⟨hs, by
intros
rfl⟩
#align convex_on_id convexOn_id
theorem concaveOn_id {s : Set β} (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s _root_.id :=
⟨hs, by
intros
rfl⟩
#align concave_on_id concaveOn_id
theorem ConvexOn.subset {t : Set E} (hf : ConvexOn 𝕜 t f) (hst : s ⊆ t) (hs : Convex 𝕜 s) :
ConvexOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align convex_on.subset ConvexOn.subset
theorem ConcaveOn.subset {t : Set E} (hf : ConcaveOn 𝕜 t f) (hst : s ⊆ t) (hs : Convex 𝕜 s) :
ConcaveOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align concave_on.subset ConcaveOn.subset
theorem StrictConvexOn.subset {t : Set E} (hf : StrictConvexOn 𝕜 t f) (hst : s ⊆ t)
(hs : Convex 𝕜 s) : StrictConvexOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align strict_convex_on.subset StrictConvexOn.subset
theorem StrictConcaveOn.subset {t : Set E} (hf : StrictConcaveOn 𝕜 t f) (hst : s ⊆ t)
(hs : Convex 𝕜 s) : StrictConcaveOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
#align strict_concave_on.subset StrictConcaveOn.subset
theorem ConvexOn.comp (hg : ConvexOn 𝕜 (f '' s) g) (hf : ConvexOn 𝕜 s f)
(hg' : MonotoneOn g (f '' s)) : ConvexOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy _ _ ha hb hab =>
(hg' (mem_image_of_mem f <| hf.1 hx hy ha hb hab)
(hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab) <|
hf.2 hx hy ha hb hab).trans <|
hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab⟩
#align convex_on.comp ConvexOn.comp
theorem ConcaveOn.comp (hg : ConcaveOn 𝕜 (f '' s) g) (hf : ConcaveOn 𝕜 s f)
(hg' : MonotoneOn g (f '' s)) : ConcaveOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy _ _ ha hb hab =>
(hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab).trans <|
hg' (hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab)
(mem_image_of_mem f <| hf.1 hx hy ha hb hab) <|
hf.2 hx hy ha hb hab⟩
#align concave_on.comp ConcaveOn.comp
theorem ConvexOn.comp_concaveOn (hg : ConvexOn 𝕜 (f '' s) g) (hf : ConcaveOn 𝕜 s f)
(hg' : AntitoneOn g (f '' s)) : ConvexOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg'
#align convex_on.comp_concave_on ConvexOn.comp_concaveOn
theorem ConcaveOn.comp_convexOn (hg : ConcaveOn 𝕜 (f '' s) g) (hf : ConvexOn 𝕜 s f)
(hg' : AntitoneOn g (f '' s)) : ConcaveOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg'
#align concave_on.comp_convex_on ConcaveOn.comp_convexOn
theorem StrictConvexOn.comp (hg : StrictConvexOn 𝕜 (f '' s) g) (hf : StrictConvexOn 𝕜 s f)
(hg' : StrictMonoOn g (f '' s)) (hf' : s.InjOn f) : StrictConvexOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab =>
(hg' (mem_image_of_mem f <| hf.1 hx hy ha.le hb.le hab)
(hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha.le hb.le hab) <|
hf.2 hx hy hxy ha hb hab).trans <|
hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) (mt (hf' hx hy) hxy) ha hb hab⟩
#align strict_convex_on.comp StrictConvexOn.comp
theorem StrictConcaveOn.comp (hg : StrictConcaveOn 𝕜 (f '' s) g) (hf : StrictConcaveOn 𝕜 s f)
(hg' : StrictMonoOn g (f '' s)) (hf' : s.InjOn f) : StrictConcaveOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab =>
(hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) (mt (hf' hx hy) hxy) ha hb hab).trans <|
hg' (hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha.le hb.le hab)
(mem_image_of_mem f <| hf.1 hx hy ha.le hb.le hab) <|
hf.2 hx hy hxy ha hb hab⟩
#align strict_concave_on.comp StrictConcaveOn.comp
theorem StrictConvexOn.comp_strictConcaveOn (hg : StrictConvexOn 𝕜 (f '' s) g)
(hf : StrictConcaveOn 𝕜 s f) (hg' : StrictAntiOn g (f '' s)) (hf' : s.InjOn f) :
StrictConvexOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg' hf'
#align strict_convex_on.comp_strict_concave_on StrictConvexOn.comp_strictConcaveOn
theorem StrictConcaveOn.comp_strictConvexOn (hg : StrictConcaveOn 𝕜 (f '' s) g)
(hf : StrictConvexOn 𝕜 s f) (hg' : StrictAntiOn g (f '' s)) (hf' : s.InjOn f) :
StrictConcaveOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg' hf'
#align strict_concave_on.comp_strict_convex_on StrictConcaveOn.comp_strictConvexOn
end SMul
section DistribMulAction
variable [SMul 𝕜 E] [DistribMulAction 𝕜 β] {s : Set E} {f g : E → β}
theorem ConvexOn.add (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) : ConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) ≤ a • f x + b • f y + (a • g x + b • g y) :=
add_le_add (hf.2 hx hy ha hb hab) (hg.2 hx hy ha hb hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]
⟩
#align convex_on.add ConvexOn.add
theorem ConcaveOn.add (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) : ConcaveOn 𝕜 s (f + g) :=
hf.dual.add hg
#align concave_on.add ConcaveOn.add
end DistribMulAction
section Module
variable [SMul 𝕜 E] [Module 𝕜 β] {s : Set E} {f : E → β}
theorem convexOn_const (c : β) (hs : Convex 𝕜 s) : ConvexOn 𝕜 s fun _ : E => c :=
⟨hs, fun _ _ _ _ _ _ _ _ hab => (Convex.combo_self hab c).ge⟩
#align convex_on_const convexOn_const
theorem concaveOn_const (c : β) (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s fun _ => c :=
convexOn_const (β := βᵒᵈ) _ hs
#align concave_on_const concaveOn_const
theorem convexOn_of_convex_epigraph (h : Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 }) :
ConvexOn 𝕜 s f :=
⟨fun x hx y hy a b ha hb hab => (@h (x, f x) ⟨hx, le_rfl⟩ (y, f y) ⟨hy, le_rfl⟩ a b ha hb hab).1,
fun x hx y hy a b ha hb hab => (@h (x, f x) ⟨hx, le_rfl⟩ (y, f y) ⟨hy, le_rfl⟩ a b ha hb hab).2⟩
#align convex_on_of_convex_epigraph convexOn_of_convex_epigraph
theorem concaveOn_of_convex_hypograph (h : Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 }) :
ConcaveOn 𝕜 s f :=
convexOn_of_convex_epigraph (β := βᵒᵈ) h
#align concave_on_of_convex_hypograph concaveOn_of_convex_hypograph
end Module
section OrderedSMul
variable [SMul 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem ConvexOn.convex_le (hf : ConvexOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | f x ≤ r }) :=
fun x hx y hy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha hb hab,
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx.1 hy.1 ha hb hab
_ ≤ a • r + b • r := by
gcongr
· exact hx.2
· exact hy.2
_ = r := Convex.combo_self hab r
⟩
#align convex_on.convex_le ConvexOn.convex_le
theorem ConcaveOn.convex_ge (hf : ConcaveOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | r ≤ f x }) :=
hf.dual.convex_le r
#align concave_on.convex_ge ConcaveOn.convex_ge
theorem ConvexOn.convex_epigraph (hf : ConvexOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } := by
rintro ⟨x, r⟩ ⟨hx, hr⟩ ⟨y, t⟩ ⟨hy, ht⟩ a b ha hb hab
refine ⟨hf.1 hx hy ha hb hab, ?_⟩
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha hb hab
_ ≤ a • r + b • t := by gcongr
#align convex_on.convex_epigraph ConvexOn.convex_epigraph
theorem ConcaveOn.convex_hypograph (hf : ConcaveOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
hf.dual.convex_epigraph
#align concave_on.convex_hypograph ConcaveOn.convex_hypograph
theorem convexOn_iff_convex_epigraph :
ConvexOn 𝕜 s f ↔ Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } :=
⟨ConvexOn.convex_epigraph, convexOn_of_convex_epigraph⟩
#align convex_on_iff_convex_epigraph convexOn_iff_convex_epigraph
theorem concaveOn_iff_convex_hypograph :
ConcaveOn 𝕜 s f ↔ Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
convexOn_iff_convex_epigraph (β := βᵒᵈ)
#align concave_on_iff_convex_hypograph concaveOn_iff_convex_hypograph
end OrderedSMul
section Module
variable [Module 𝕜 E] [SMul 𝕜 β] {s : Set E} {f : E → β}
/-- Right translation preserves convexity. -/
theorem ConvexOn.translate_right (hf : ConvexOn 𝕜 s f) (c : E) :
ConvexOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => c + z) :=
⟨hf.1.translate_preimage_right _, fun x hx y hy a b ha hb hab =>
calc
f (c + (a • x + b • y)) = f (a • (c + x) + b • (c + y)) := by
rw [smul_add, smul_add, add_add_add_comm, Convex.combo_self hab]
_ ≤ a • f (c + x) + b • f (c + y) := hf.2 hx hy ha hb hab
⟩
#align convex_on.translate_right ConvexOn.translate_right
/-- Right translation preserves concavity. -/
theorem ConcaveOn.translate_right (hf : ConcaveOn 𝕜 s f) (c : E) :
ConcaveOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => c + z) :=
hf.dual.translate_right _
#align concave_on.translate_right ConcaveOn.translate_right
/-- Left translation preserves convexity. -/
theorem ConvexOn.translate_left (hf : ConvexOn 𝕜 s f) (c : E) :
ConvexOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => z + c) := by
simpa only [add_comm c] using hf.translate_right c
#align convex_on.translate_left ConvexOn.translate_left
/-- Left translation preserves concavity. -/
theorem ConcaveOn.translate_left (hf : ConcaveOn 𝕜 s f) (c : E) :
ConcaveOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => z + c) :=
hf.dual.translate_left _
#align concave_on.translate_left ConcaveOn.translate_left
end Module
section Module
variable [Module 𝕜 E] [Module 𝕜 β]
theorem convexOn_iff_forall_pos {s : Set E} {f : E → β} :
ConvexOn 𝕜 s f ↔ Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b →
a + b = 1 → f (a • x + b • y) ≤ a • f x + b • f y := by
refine and_congr_right'
⟨fun h x hx y hy a b ha hb hab => h hx hy ha.le hb.le hab, fun h x hx y hy a b ha hb hab => ?_⟩
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_add] at hab
subst b
simp_rw [zero_smul, zero_add, one_smul, le_rfl]
obtain rfl | hb' := hb.eq_or_lt
· rw [add_zero] at hab
subst a
simp_rw [zero_smul, add_zero, one_smul, le_rfl]
exact h hx hy ha' hb' hab
#align convex_on_iff_forall_pos convexOn_iff_forall_pos
theorem concaveOn_iff_forall_pos {s : Set E} {f : E → β} :
ConcaveOn 𝕜 s f ↔
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y) :=
convexOn_iff_forall_pos (β := βᵒᵈ)
#align concave_on_iff_forall_pos concaveOn_iff_forall_pos
theorem convexOn_iff_pairwise_pos {s : Set E} {f : E → β} :
ConvexOn 𝕜 s f ↔
Convex 𝕜 s ∧
s.Pairwise fun x y =>
∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → f (a • x + b • y) ≤ a • f x + b • f y := by
rw [convexOn_iff_forall_pos]
refine
and_congr_right'
⟨fun h x hx y hy _ a b ha hb hab => h hx hy ha hb hab, fun h x hx y hy a b ha hb hab => ?_⟩
obtain rfl | hxy := eq_or_ne x y
· rw [Convex.combo_self hab, Convex.combo_self hab]
exact h hx hy hxy ha hb hab
#align convex_on_iff_pairwise_pos convexOn_iff_pairwise_pos
theorem concaveOn_iff_pairwise_pos {s : Set E} {f : E → β} :
ConcaveOn 𝕜 s f ↔
Convex 𝕜 s ∧
s.Pairwise fun x y =>
∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → a • f x + b • f y ≤ f (a • x + b • y) :=
convexOn_iff_pairwise_pos (β := βᵒᵈ)
#align concave_on_iff_pairwise_pos concaveOn_iff_pairwise_pos
/-- A linear map is convex. -/
theorem LinearMap.convexOn (f : E →ₗ[𝕜] β) {s : Set E} (hs : Convex 𝕜 s) : ConvexOn 𝕜 s f :=
⟨hs, fun _ _ _ _ _ _ _ _ _ => by rw [f.map_add, f.map_smul, f.map_smul]⟩
#align linear_map.convex_on LinearMap.convexOn
/-- A linear map is concave. -/
theorem LinearMap.concaveOn (f : E →ₗ[𝕜] β) {s : Set E} (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s f :=
⟨hs, fun _ _ _ _ _ _ _ _ _ => by rw [f.map_add, f.map_smul, f.map_smul]⟩
#align linear_map.concave_on LinearMap.concaveOn
theorem StrictConvexOn.convexOn {s : Set E} {f : E → β} (hf : StrictConvexOn 𝕜 s f) :
ConvexOn 𝕜 s f :=
convexOn_iff_pairwise_pos.mpr
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab => (hf.2 hx hy hxy ha hb hab).le⟩
#align strict_convex_on.convex_on StrictConvexOn.convexOn
theorem StrictConcaveOn.concaveOn {s : Set E} {f : E → β} (hf : StrictConcaveOn 𝕜 s f) :
ConcaveOn 𝕜 s f :=
hf.dual.convexOn
#align strict_concave_on.concave_on StrictConcaveOn.concaveOn
section OrderedSMul
variable [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem StrictConvexOn.convex_lt (hf : StrictConvexOn 𝕜 s f) (r : β) :
Convex 𝕜 ({ x ∈ s | f x < r }) :=
convex_iff_pairwise_pos.2 fun x hx y hy hxy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha.le hb.le hab,
calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx.1 hy.1 hxy ha hb hab
_ ≤ a • r + b • r := by
gcongr
· exact hx.2.le
· exact hy.2.le
_ = r := Convex.combo_self hab r
⟩
#align strict_convex_on.convex_lt StrictConvexOn.convex_lt
theorem StrictConcaveOn.convex_gt (hf : StrictConcaveOn 𝕜 s f) (r : β) :
Convex 𝕜 ({ x ∈ s | r < f x }) :=
hf.dual.convex_lt r
#align strict_concave_on.convex_gt StrictConcaveOn.convex_gt
end OrderedSMul
section LinearOrder
variable [LinearOrder E] {s : Set E} {f : E → β}
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is convex, it suffices to
verify the inequality `f (a • x + b • y) ≤ a • f x + b • f y` only for `x < y` and positive `a`,
`b`. The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order.
-/
theorem LinearOrder.convexOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) ≤ a • f x + b • f y) :
ConvexOn 𝕜 s f := by
refine convexOn_iff_pairwise_pos.2 ⟨hs, fun x hx y hy hxy a b ha hb hab => ?_⟩
-- Porting note: without clearing the stray variables, `wlog` gives a bad term.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/wlog.20.2316495
clear! α F ι
wlog h : x < y
· rw [add_comm (a • x), add_comm (a • f x)]
rw [add_comm] at hab
exact this hs hf y hy x hx hxy.symm b a hb ha hab (hxy.lt_or_lt.resolve_left h)
exact hf hx hy h ha hb hab
#align linear_order.convex_on_of_lt LinearOrder.convexOn_of_lt
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is concave it suffices to
verify the inequality `a • f x + b • f y ≤ f (a • x + b • y)` for `x < y` and positive `a`, `b`. The
main use case is `E = ℝ` however one can apply it, e.g., to `ℝ^n` with lexicographic order. -/
theorem LinearOrder.concaveOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y)) :
ConcaveOn 𝕜 s f :=
LinearOrder.convexOn_of_lt (β := βᵒᵈ) hs hf
#align linear_order.concave_on_of_lt LinearOrder.concaveOn_of_lt
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is strictly convex, it suffices
to verify the inequality `f (a • x + b • y) < a • f x + b • f y` for `x < y` and positive `a`, `b`.
The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order. -/
theorem LinearOrder.strictConvexOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) < a • f x + b • f y) :
StrictConvexOn 𝕜 s f := by
refine ⟨hs, fun x hx y hy hxy a b ha hb hab => ?_⟩
-- Porting note: without clearing the stray variables, `wlog` gives a bad term.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/wlog.20.2316495
clear! α F ι
wlog h : x < y
· rw [add_comm (a • x), add_comm (a • f x)]
rw [add_comm] at hab
exact this hs hf y hy x hx hxy.symm b a hb ha hab (hxy.lt_or_lt.resolve_left h)
exact hf hx hy h ha hb hab
#align linear_order.strict_convex_on_of_lt LinearOrder.strictConvexOn_of_lt
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is strictly concave it suffices
to verify the inequality `a • f x + b • f y < f (a • x + b • y)` for `x < y` and positive `a`, `b`.
The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order. -/
theorem LinearOrder.strictConcaveOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y < f (a • x + b • y)) :
StrictConcaveOn 𝕜 s f :=
LinearOrder.strictConvexOn_of_lt (β := βᵒᵈ) hs hf
#align linear_order.strict_concave_on_of_lt LinearOrder.strictConcaveOn_of_lt
end LinearOrder
end Module
section Module
variable [Module 𝕜 E] [Module 𝕜 F] [SMul 𝕜 β]
/-- If `g` is convex on `s`, so is `(f ∘ g)` on `f ⁻¹' s` for a linear `f`. -/
theorem ConvexOn.comp_linearMap {f : F → β} {s : Set F} (hf : ConvexOn 𝕜 s f) (g : E →ₗ[𝕜] F) :
ConvexOn 𝕜 (g ⁻¹' s) (f ∘ g) :=
⟨hf.1.linear_preimage _, fun x hx y hy a b ha hb hab =>
calc
f (g (a • x + b • y)) = f (a • g x + b • g y) := by rw [g.map_add, g.map_smul, g.map_smul]
_ ≤ a • f (g x) + b • f (g y) := hf.2 hx hy ha hb hab⟩
#align convex_on.comp_linear_map ConvexOn.comp_linearMap
/-- If `g` is concave on `s`, so is `(g ∘ f)` on `f ⁻¹' s` for a linear `f`. -/
theorem ConcaveOn.comp_linearMap {f : F → β} {s : Set F} (hf : ConcaveOn 𝕜 s f) (g : E →ₗ[𝕜] F) :
ConcaveOn 𝕜 (g ⁻¹' s) (f ∘ g) :=
hf.dual.comp_linearMap g
#align concave_on.comp_linear_map ConcaveOn.comp_linearMap
end Module
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [OrderedCancelAddCommMonoid β]
section DistribMulAction
variable [SMul 𝕜 E] [DistribMulAction 𝕜 β] {s : Set E} {f g : E → β}
theorem StrictConvexOn.add_convexOn (hf : StrictConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) < a • f x + b • f y + (a • g x + b • g y) :=
add_lt_add_of_lt_of_le (hf.2 hx hy hxy ha hb hab) (hg.2 hx hy ha.le hb.le hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]⟩
#align strict_convex_on.add_convex_on StrictConvexOn.add_convexOn
theorem ConvexOn.add_strictConvexOn (hf : ConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
add_comm g f ▸ hg.add_convexOn hf
#align convex_on.add_strict_convex_on ConvexOn.add_strictConvexOn
theorem StrictConvexOn.add (hf : StrictConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) < a • f x + b • f y + (a • g x + b • g y) :=
add_lt_add (hf.2 hx hy hxy ha hb hab) (hg.2 hx hy hxy ha hb hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]⟩
#align strict_convex_on.add StrictConvexOn.add
theorem StrictConcaveOn.add_concaveOn (hf : StrictConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f + g) :=
hf.dual.add_convexOn hg.dual
#align strict_concave_on.add_concave_on StrictConcaveOn.add_concaveOn
theorem ConcaveOn.add_strictConcaveOn (hf : ConcaveOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f + g) :=
hf.dual.add_strictConvexOn hg.dual
#align concave_on.add_strict_concave_on ConcaveOn.add_strictConcaveOn
theorem StrictConcaveOn.add (hf : StrictConcaveOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f + g) :=
hf.dual.add hg
#align strict_concave_on.add StrictConcaveOn.add
end DistribMulAction
section Module
variable [Module 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem ConvexOn.convex_lt (hf : ConvexOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | f x < r }) :=
convex_iff_forall_pos.2 fun x hx y hy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha.le hb.le hab,
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx.1 hy.1 ha.le hb.le hab
_ < a • r + b • r :=
(add_lt_add_of_lt_of_le (smul_lt_smul_of_pos_left hx.2 ha)
(smul_le_smul_of_nonneg_left hy.2.le hb.le))
_ = r := Convex.combo_self hab _⟩
#align convex_on.convex_lt ConvexOn.convex_lt
theorem ConcaveOn.convex_gt (hf : ConcaveOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | r < f x }) :=
hf.dual.convex_lt r
#align concave_on.convex_gt ConcaveOn.convex_gt
theorem ConvexOn.openSegment_subset_strict_epigraph (hf : ConvexOn 𝕜 s f) (p q : E × β)
(hp : p.1 ∈ s ∧ f p.1 < p.2) (hq : q.1 ∈ s ∧ f q.1 ≤ q.2) :
openSegment 𝕜 p q ⊆ { p : E × β | p.1 ∈ s ∧ f p.1 < p.2 } := by
rintro _ ⟨a, b, ha, hb, hab, rfl⟩
refine ⟨hf.1 hp.1 hq.1 ha.le hb.le hab, ?_⟩
calc
f (a • p.1 + b • q.1) ≤ a • f p.1 + b • f q.1 := hf.2 hp.1 hq.1 ha.le hb.le hab
_ < a • p.2 + b • q.2 := add_lt_add_of_lt_of_le
(smul_lt_smul_of_pos_left hp.2 ha) (smul_le_smul_of_nonneg_left hq.2 hb.le)
#align convex_on.open_segment_subset_strict_epigraph ConvexOn.openSegment_subset_strict_epigraph
theorem ConcaveOn.openSegment_subset_strict_hypograph (hf : ConcaveOn 𝕜 s f) (p q : E × β)
(hp : p.1 ∈ s ∧ p.2 < f p.1) (hq : q.1 ∈ s ∧ q.2 ≤ f q.1) :
openSegment 𝕜 p q ⊆ { p : E × β | p.1 ∈ s ∧ p.2 < f p.1 } :=
hf.dual.openSegment_subset_strict_epigraph p q hp hq
#align concave_on.open_segment_subset_strict_hypograph ConcaveOn.openSegment_subset_strict_hypograph
theorem ConvexOn.convex_strict_epigraph (hf : ConvexOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 < p.2 } :=
convex_iff_openSegment_subset.mpr fun p hp q hq =>
hf.openSegment_subset_strict_epigraph p q hp ⟨hq.1, hq.2.le⟩
#align convex_on.convex_strict_epigraph ConvexOn.convex_strict_epigraph
theorem ConcaveOn.convex_strict_hypograph (hf : ConcaveOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 < f p.1 } :=
hf.dual.convex_strict_epigraph
#align concave_on.convex_strict_hypograph ConcaveOn.convex_strict_hypograph
end Module
end OrderedCancelAddCommMonoid
section LinearOrderedAddCommMonoid
variable [LinearOrderedAddCommMonoid β] [SMul 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E}
{f g : E → β}
/-- The pointwise maximum of convex functions is convex. -/
theorem ConvexOn.sup (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) : ConvexOn 𝕜 s (f ⊔ g) := by
refine ⟨hf.left, fun x hx y hy a b ha hb hab => sup_le ?_ ?_⟩
· calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.right hx hy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_left
· calc
g (a • x + b • y) ≤ a • g x + b • g y := hg.right hx hy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_right
#align convex_on.sup ConvexOn.sup
/-- The pointwise minimum of concave functions is concave. -/
theorem ConcaveOn.inf (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) : ConcaveOn 𝕜 s (f ⊓ g) :=
hf.dual.sup hg
#align concave_on.inf ConcaveOn.inf
/-- The pointwise maximum of strictly convex functions is strictly convex. -/
theorem StrictConvexOn.sup (hf : StrictConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f ⊔ g) :=
⟨hf.left, fun x hx y hy hxy a b ha hb hab =>
max_lt
(calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx hy hxy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_left)
(calc
g (a • x + b • y) < a • g x + b • g y := hg.2 hx hy hxy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_right)⟩
#align strict_convex_on.sup StrictConvexOn.sup
/-- The pointwise minimum of strictly concave functions is strictly concave. -/
theorem StrictConcaveOn.inf (hf : StrictConcaveOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f ⊓ g) :=
hf.dual.sup hg
#align strict_concave_on.inf StrictConcaveOn.inf
/-- A convex function on a segment is upper-bounded by the max of its endpoints. -/
theorem ConvexOn.le_on_segment' (hf : ConvexOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s) {a b : 𝕜}
(ha : 0 ≤ a) (hb : 0 ≤ b) (hab : a + b = 1) : f (a • x + b • y) ≤ max (f x) (f y) :=
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha hb hab
_ ≤ a • max (f x) (f y) + b • max (f x) (f y) := by
gcongr
· apply le_max_left
· apply le_max_right
_ = max (f x) (f y) := Convex.combo_self hab _
#align convex_on.le_on_segment' ConvexOn.le_on_segment'
/-- A concave function on a segment is lower-bounded by the min of its endpoints. -/
theorem ConcaveOn.ge_on_segment' (hf : ConcaveOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s)
{a b : 𝕜} (ha : 0 ≤ a) (hb : 0 ≤ b) (hab : a + b = 1) : min (f x) (f y) ≤ f (a • x + b • y) :=
hf.dual.le_on_segment' hx hy ha hb hab
#align concave_on.ge_on_segment' ConcaveOn.ge_on_segment'
/-- A convex function on a segment is upper-bounded by the max of its endpoints. -/
theorem ConvexOn.le_on_segment (hf : ConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ [x -[𝕜] y]) : f z ≤ max (f x) (f y) :=
let ⟨_, _, ha, hb, hab, hz⟩ := hz
hz ▸ hf.le_on_segment' hx hy ha hb hab
#align convex_on.le_on_segment ConvexOn.le_on_segment
/-- A concave function on a segment is lower-bounded by the min of its endpoints. -/
theorem ConcaveOn.ge_on_segment (hf : ConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ [x -[𝕜] y]) : min (f x) (f y) ≤ f z :=
hf.dual.le_on_segment hx hy hz
#align concave_on.ge_on_segment ConcaveOn.ge_on_segment
/-- A strictly convex function on an open segment is strictly upper-bounded by the max of its
endpoints. -/
| Mathlib/Analysis/Convex/Function.lean | 670 | 679 | theorem StrictConvexOn.lt_on_open_segment' (hf : StrictConvexOn 𝕜 s f) {x y : E} (hx : x ∈ s)
(hy : y ∈ s) (hxy : x ≠ y) {a b : 𝕜} (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) :
f (a • x + b • y) < max (f x) (f y) :=
calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx hy hxy ha hb hab
_ ≤ a • max (f x) (f y) + b • max (f x) (f y) := by |
gcongr
· apply le_max_left
· apply le_max_right
_ = max (f x) (f y) := Convex.combo_self hab _
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Analysis.Calculus.ContDiff.Defs
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Mul
import Mathlib.Analysis.Calculus.Deriv.Inverse
#align_import analysis.calculus.cont_diff from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Higher differentiability of usual operations
We prove that the usual operations (addition, multiplication, difference, composition, and
so on) preserve `C^n` functions. We also expand the API around `C^n` functions.
## Main results
* `ContDiff.comp` states that the composition of two `C^n` functions is `C^n`.
Similar results are given for `C^n` functions on domains.
## Notations
We use the notation `E [×n]→L[𝕜] F` for the space of continuous multilinear maps on `E^n` with
values in `F`. This is the space in which the `n`-th derivative of a function from `E` to `F` lives.
In this file, we denote `⊤ : ℕ∞` with `∞`.
## Tags
derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series
-/
noncomputable section
open scoped Classical NNReal Nat
local notation "∞" => (⊤ : ℕ∞)
universe u v w uD uE uF uG
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup NormedSpace.toModule' AddCommGroup.toAddCommMonoid
open Set Fin Filter Function
open scoped Topology
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {D : Type uD} [NormedAddCommGroup D]
[NormedSpace 𝕜 D] {E : Type uE} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type uF}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
{X : Type*} [NormedAddCommGroup X] [NormedSpace 𝕜 X] {s s₁ t u : Set E} {f f₁ : E → F}
{g : F → G} {x x₀ : E} {c : F} {b : E × F → G} {m n : ℕ∞} {p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Constants -/
@[simp]
theorem iteratedFDerivWithin_zero_fun (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} :
iteratedFDerivWithin 𝕜 i (fun _ : E ↦ (0 : F)) s x = 0 := by
induction i generalizing x with
| zero => ext; simp
| succ i IH =>
ext m
rw [iteratedFDerivWithin_succ_apply_left, fderivWithin_congr (fun _ ↦ IH) (IH hx)]
rw [fderivWithin_const_apply _ (hs x hx)]
rfl
@[simp]
theorem iteratedFDeriv_zero_fun {n : ℕ} : (iteratedFDeriv 𝕜 n fun _ : E ↦ (0 : F)) = 0 :=
funext fun x ↦ by simpa [← iteratedFDerivWithin_univ] using
iteratedFDerivWithin_zero_fun uniqueDiffOn_univ (mem_univ x)
#align iterated_fderiv_zero_fun iteratedFDeriv_zero_fun
theorem contDiff_zero_fun : ContDiff 𝕜 n fun _ : E => (0 : F) :=
contDiff_of_differentiable_iteratedFDeriv fun m _ => by
rw [iteratedFDeriv_zero_fun]
exact differentiable_const (0 : E[×m]→L[𝕜] F)
#align cont_diff_zero_fun contDiff_zero_fun
/-- Constants are `C^∞`.
-/
theorem contDiff_const {c : F} : ContDiff 𝕜 n fun _ : E => c := by
suffices h : ContDiff 𝕜 ∞ fun _ : E => c from h.of_le le_top
rw [contDiff_top_iff_fderiv]
refine ⟨differentiable_const c, ?_⟩
rw [fderiv_const]
exact contDiff_zero_fun
#align cont_diff_const contDiff_const
theorem contDiffOn_const {c : F} {s : Set E} : ContDiffOn 𝕜 n (fun _ : E => c) s :=
contDiff_const.contDiffOn
#align cont_diff_on_const contDiffOn_const
theorem contDiffAt_const {c : F} : ContDiffAt 𝕜 n (fun _ : E => c) x :=
contDiff_const.contDiffAt
#align cont_diff_at_const contDiffAt_const
theorem contDiffWithinAt_const {c : F} : ContDiffWithinAt 𝕜 n (fun _ : E => c) s x :=
contDiffAt_const.contDiffWithinAt
#align cont_diff_within_at_const contDiffWithinAt_const
@[nontriviality]
theorem contDiff_of_subsingleton [Subsingleton F] : ContDiff 𝕜 n f := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiff_const
#align cont_diff_of_subsingleton contDiff_of_subsingleton
@[nontriviality]
| Mathlib/Analysis/Calculus/ContDiff/Basic.lean | 112 | 113 | theorem contDiffAt_of_subsingleton [Subsingleton F] : ContDiffAt 𝕜 n f x := by |
rw [Subsingleton.elim f fun _ => 0]; exact contDiffAt_const
|
/-
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`. -/
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]
/-- A compositum of two purely inseparable extensions is purely inseparable. -/
instance isPurelyInseparable_sup (L1 L2 : IntermediateField F E)
[h1 : IsPurelyInseparable F L1] [h2 : IsPurelyInseparable F L2] :
IsPurelyInseparable F (L1 ⊔ L2 : IntermediateField F E) := by
rw [← le_perfectClosure_iff] at h1 h2 ⊢
exact sup_le h1 h2
/-- A compositum of purely inseparable extensions is purely inseparable. -/
instance isPurelyInseparable_iSup {ι : Sort*} {t : ι → IntermediateField F E}
[h : ∀ i, IsPurelyInseparable F (t i)] :
IsPurelyInseparable F (⨆ i, t i : IntermediateField F E) := by
simp_rw [← le_perfectClosure_iff] at h ⊢
exact iSup_le h
/-- If `F` is a field of exponential characteristic `q`, `F(S) / F` is separable, then
`F(S) = F(S ^ (q ^ n))` for any natural number `n`. -/
theorem adjoin_eq_adjoin_pow_expChar_pow_of_isSeparable (S : Set E) [IsSeparable F (adjoin F S)]
(q : ℕ) [ExpChar F q] (n : ℕ) : adjoin F S = adjoin F ((· ^ q ^ n) '' S) := by
set L := adjoin F S
set M := adjoin F ((· ^ q ^ n) '' S)
have hi : M ≤ L := by
rw [adjoin_le_iff]
rintro _ ⟨y, hy, rfl⟩
exact pow_mem (subset_adjoin F S hy) _
letI := (inclusion hi).toAlgebra
haveI : IsSeparable M (extendScalars hi) := isSeparable_tower_top_of_isSeparable F M L
haveI : IsPurelyInseparable M (extendScalars hi) := by
haveI := expChar_of_injective_algebraMap (algebraMap F M).injective q
rw [extendScalars_adjoin hi, isPurelyInseparable_adjoin_iff_pow_mem M _ q]
exact fun x hx ↦ ⟨n, ⟨x ^ q ^ n, subset_adjoin F _ ⟨x, hx, rfl⟩⟩, rfl⟩
simpa only [extendScalars_restrictScalars, restrictScalars_bot_eq_self] using congr_arg
(restrictScalars F) (extendScalars hi).eq_bot_of_isPurelyInseparable_of_isSeparable
/-- If `E / F` is a separable field extension of exponential characteristic `q`, then
`F(S) = F(S ^ (q ^ n))` for any subset `S` of `E` and any natural number `n`. -/
theorem adjoin_eq_adjoin_pow_expChar_pow_of_isSeparable' [IsSeparable F E] (S : Set E)
(q : ℕ) [ExpChar F q] (n : ℕ) : adjoin F S = adjoin F ((· ^ q ^ n) '' S) :=
haveI := isSeparable_tower_bot_of_isSeparable F (adjoin F S) E
adjoin_eq_adjoin_pow_expChar_pow_of_isSeparable F E S q n
-- TODO: prove the converse when `F(S) / F` is finite
/-- If `F` is a field of exponential characteristic `q`, `F(S) / F` is separable, then
`F(S) = F(S ^ q)`. -/
theorem adjoin_eq_adjoin_pow_expChar_of_isSeparable (S : Set E) [IsSeparable F (adjoin F S)]
(q : ℕ) [ExpChar F q] : adjoin F S = adjoin F ((· ^ q) '' S) :=
pow_one q ▸ adjoin_eq_adjoin_pow_expChar_pow_of_isSeparable F E S q 1
/-- If `E / F` is a separable field extension of exponential characteristic `q`, then
`F(S) = F(S ^ q)` for any subset `S` of `E`. -/
theorem adjoin_eq_adjoin_pow_expChar_of_isSeparable' [IsSeparable F E] (S : Set E)
(q : ℕ) [ExpChar F q] : adjoin F S = adjoin F ((· ^ q) '' S) :=
pow_one q ▸ adjoin_eq_adjoin_pow_expChar_pow_of_isSeparable' F E S q 1
end IntermediateField
section
variable (q n : ℕ) [hF : ExpChar F q] {ι : Type*} {v : ι → E} {F E}
/-- If `E / F` is a separable extension of exponential characteristic `q`, if `{ u_i }` is a family
of elements of `E` which `F`-linearly spans `E`, then `{ u_i ^ (q ^ n) }` also `F`-linearly spans
`E` for any natural number `n`. -/
theorem Field.span_map_pow_expChar_pow_eq_top_of_isSeparable [IsSeparable F E]
(h : Submodule.span F (Set.range v) = ⊤) :
Submodule.span F (Set.range (v · ^ q ^ n)) = ⊤ := by
erw [← Algebra.top_toSubmodule, ← top_toSubalgebra, ← adjoin_univ,
adjoin_eq_adjoin_pow_expChar_pow_of_isSeparable' F E _ q n,
adjoin_algebraic_toSubalgebra fun x _ ↦ Algebra.IsAlgebraic.isAlgebraic x,
Set.image_univ, Algebra.adjoin_eq_span, (powMonoidHom _).mrange.closure_eq]
refine (Submodule.span_mono <| Set.range_comp_subset_range _ _).antisymm (Submodule.span_le.2 ?_)
rw [Set.range_comp, ← Set.image_univ]
haveI := expChar_of_injective_algebraMap (algebraMap F E).injective q
apply h ▸ Submodule.image_span_subset_span (LinearMap.iterateFrobenius F E q n) _
/-- If `E / F` is a finite separable extension of exponential characteristic `q`, if `{ u_i }` is a
family of elements of `E` which is `F`-linearly independent, then `{ u_i ^ (q ^ n) }` is also
`F`-linearly independent for any natural number `n`. A special case of
`LinearIndependent.map_pow_expChar_pow_of_isSeparable`
and is an intermediate result used to prove it. -/
private theorem LinearIndependent.map_pow_expChar_pow_of_fd_isSeparable
[FiniteDimensional F E] [IsSeparable F E]
(h : LinearIndependent F v) : LinearIndependent F (v · ^ q ^ n) := by
have h' := h.coe_range
let ι' := h'.extend (Set.range v).subset_univ
let b : Basis ι' F E := Basis.extend h'
letI : Fintype ι' := fintypeBasisIndex b
have H := linearIndependent_of_top_le_span_of_card_eq_finrank
(span_map_pow_expChar_pow_eq_top_of_isSeparable q n b.span_eq).ge
(finrank_eq_card_basis b).symm
let f (i : ι) : ι' := ⟨v i, h'.subset_extend _ ⟨i, rfl⟩⟩
convert H.comp f fun _ _ heq ↦ h.injective (by simpa only [f, Subtype.mk.injEq] using heq)
simp_rw [Function.comp_apply, b, Basis.extend_apply_self]
/-- If `E / F` is a separable extension of exponential characteristic `q`, if `{ u_i }` is a
family of elements of `E` which is `F`-linearly independent, then `{ u_i ^ (q ^ n) }` is also
`F`-linearly independent for any natural number `n`. -/
theorem LinearIndependent.map_pow_expChar_pow_of_isSeparable [IsSeparable F E]
(h : LinearIndependent F v) : LinearIndependent F (v · ^ q ^ n) := by
classical
have halg := IsSeparable.isAlgebraic F E
rw [linearIndependent_iff_finset_linearIndependent] at h ⊢
intro s
let E' := adjoin F (s.image v : Set E)
haveI : FiniteDimensional F E' := finiteDimensional_adjoin
fun x _ ↦ Algebra.IsIntegral.isIntegral x
haveI : IsSeparable F E' := isSeparable_tower_bot_of_isSeparable F E' E
let v' (i : s) : E' := ⟨v i.1, subset_adjoin F _ (Finset.mem_image.2 ⟨i.1, i.2, rfl⟩)⟩
have h' : LinearIndependent F v' := (h s).of_comp E'.val.toLinearMap
exact (h'.map_pow_expChar_pow_of_fd_isSeparable q n).map'
E'.val.toLinearMap (LinearMap.ker_eq_bot_of_injective E'.val.injective)
/-- If `E / F` is a field extension of exponential characteristic `q`, if `{ u_i }` is a
family of separable elements of `E` which is `F`-linearly independent, then `{ u_i ^ (q ^ n) }`
is also `F`-linearly independent for any natural number `n`. -/
theorem LinearIndependent.map_pow_expChar_pow_of_separable
(hsep : ∀ i : ι, (minpoly F (v i)).Separable)
(h : LinearIndependent F v) : LinearIndependent F (v · ^ q ^ n) := by
let E' := adjoin F (Set.range v)
haveI : IsSeparable F E' := (isSeparable_adjoin_iff_separable F _).2 <| by
rintro _ ⟨y, rfl⟩; exact hsep y
let v' (i : ι) : E' := ⟨v i, subset_adjoin F _ ⟨i, rfl⟩⟩
have h' : LinearIndependent F v' := h.of_comp E'.val.toLinearMap
exact (h'.map_pow_expChar_pow_of_isSeparable q n).map'
E'.val.toLinearMap (LinearMap.ker_eq_bot_of_injective E'.val.injective)
/-- If `E / F` is a separable extension of exponential characteristic `q`, if `{ u_i }` is an
`F`-basis of `E`, then `{ u_i ^ (q ^ n) }` is also an `F`-basis of `E`
for any natural number `n`. -/
def Basis.mapPowExpCharPowOfIsSeparable [IsSeparable F E]
(b : Basis ι F E) : Basis ι F E :=
Basis.mk (b.linearIndependent.map_pow_expChar_pow_of_isSeparable q n)
(span_map_pow_expChar_pow_eq_top_of_isSeparable q n b.span_eq).ge
end
/-- If `E` is an algebraic closure of `F`, then `F` is separably closed if and only if `E / F` is
purely inseparable. -/
theorem isSepClosed_iff_isPurelyInseparable_algebraicClosure [IsAlgClosure F E] :
IsSepClosed F ↔ IsPurelyInseparable F E :=
⟨fun _ ↦ IsAlgClosure.algebraic.isPurelyInseparable_of_isSepClosed, fun H ↦ by
haveI := IsAlgClosure.alg_closed F (K := E)
rwa [← separableClosure.eq_bot_iff, IsSepClosed.separableClosure_eq_bot_iff] at H⟩
variable {F E} in
/-- If `E / F` is an algebraic extension, `F` is separably closed,
then `E` is also separably closed. -/
theorem Algebra.IsAlgebraic.isSepClosed [Algebra.IsAlgebraic F E]
[IsSepClosed F] : IsSepClosed E :=
have : Algebra.IsAlgebraic F (AlgebraicClosure E) := Algebra.IsAlgebraic.trans (L := E)
have : IsPurelyInseparable F (AlgebraicClosure E) := isPurelyInseparable_of_isSepClosed
(isSepClosed_iff_isPurelyInseparable_algebraicClosure E _).mpr
(IsPurelyInseparable.tower_top F E <| AlgebraicClosure E)
theorem perfectField_of_perfectClosure_eq_bot [h : PerfectField E] (eq : perfectClosure F E = ⊥) :
PerfectField F := by
let p := ringExpChar F
haveI := expChar_of_injective_algebraMap (algebraMap F E).injective p
haveI := PerfectRing.ofSurjective F p fun x ↦ by
obtain ⟨y, h⟩ := surjective_frobenius E p (algebraMap F E x)
have : y ∈ perfectClosure F E := ⟨1, x, by rw [← h, pow_one, frobenius_def, ringExpChar.eq F p]⟩
obtain ⟨z, rfl⟩ := eq ▸ this
exact ⟨z, (algebraMap F E).injective (by erw [RingHom.map_frobenius, h])⟩
exact PerfectRing.toPerfectField F p
/-- If `E / F` is a separable extension, `E` is perfect, then `F` is also prefect. -/
theorem perfectField_of_isSeparable_of_perfectField_top [IsSeparable F E] [PerfectField E] :
PerfectField F :=
perfectField_of_perfectClosure_eq_bot F E (perfectClosure.eq_bot_of_isSeparable F E)
/-- If `E` is an algebraic closure of `F`, then `F` is perfect if and only if `E / F` is
separable. -/
theorem perfectField_iff_isSeparable_algebraicClosure [IsAlgClosure F E] :
PerfectField F ↔ IsSeparable F E :=
⟨fun _ ↦ IsSepClosure.separable, fun _ ↦ haveI : IsAlgClosed E := IsAlgClosure.alg_closed F;
perfectField_of_isSeparable_of_perfectField_top F E⟩
namespace Field
/-- 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. -/
theorem finSepDegree_eq [Algebra.IsAlgebraic F E] :
finSepDegree F E = Cardinal.toNat (sepDegree F E) := by
have : Algebra.IsAlgebraic (separableClosure F E) E := Algebra.IsAlgebraic.tower_top (K := F) _
have h := finSepDegree_mul_finSepDegree_of_isAlgebraic F (separableClosure F E) E |>.symm
haveI := separableClosure.isSeparable F E
haveI := separableClosure.isPurelyInseparable F E
rwa [finSepDegree_eq_finrank_of_isSeparable F (separableClosure F E),
IsPurelyInseparable.finSepDegree_eq_one (separableClosure F E) E, mul_one] at h
/-- The finite separable degree multiply by the finite inseparable degree is equal
to the (finite) field extension degree. -/
theorem finSepDegree_mul_finInsepDegree : finSepDegree F E * finInsepDegree F E = finrank F E := by
by_cases halg : Algebra.IsAlgebraic F E
· have := congr_arg Cardinal.toNat (sepDegree_mul_insepDegree F E)
rwa [Cardinal.toNat_mul, ← finSepDegree_eq F E] at this
rw [finInsepDegree, finrank_of_infinite_dimensional (K := F) (V := E) fun _ ↦
halg (Algebra.IsAlgebraic.of_finite F E),
finrank_of_infinite_dimensional (K := separableClosure F E) (V := E) fun _ ↦
halg ((separableClosure.isAlgebraic F E).trans),
mul_zero]
end Field
namespace separableClosure
variable [Algebra E K] [IsScalarTower F E K] {F E}
/-- If `K / E / F` is a field extension tower, such that `E / F` is algebraic and `K / E`
is separable, then `E` adjoin `separableClosure F K` is equal to `K`. It is a special case of
`separableClosure.adjoin_eq_of_isAlgebraic`, and is an intermediate result used to prove it. -/
lemma adjoin_eq_of_isAlgebraic_of_isSeparable [Algebra.IsAlgebraic F E]
[IsSeparable E K] : adjoin E (separableClosure F K : Set K) = ⊤ := top_unique fun x _ ↦ by
set S := separableClosure F K
set L := adjoin E (S : Set K)
have := isSeparable_tower_top_of_isSeparable E L K
let i : S →+* L := Subsemiring.inclusion fun x hx ↦ subset_adjoin E (S : Set K) hx
let _ : Algebra S L := i.toAlgebra
let _ : SMul S L := Algebra.toSMul
have : IsScalarTower S L K := IsScalarTower.of_algebraMap_eq (congrFun rfl)
have : Algebra.IsAlgebraic F K := Algebra.IsAlgebraic.trans (L := E)
have : IsPurelyInseparable S K := separableClosure.isPurelyInseparable F K
have := IsPurelyInseparable.tower_top S L K
obtain ⟨y, rfl⟩ := IsPurelyInseparable.surjective_algebraMap_of_isSeparable L K x
exact y.2
/-- If `K / E / F` is a field extension tower, such that `E / F` is algebraic, then
`E` adjoin `separableClosure F K` is equal to `separableClosure E K`. -/
theorem adjoin_eq_of_isAlgebraic [Algebra.IsAlgebraic F E] :
adjoin E (separableClosure F K) = separableClosure E K := by
set S := separableClosure E K
have h := congr_arg lift (adjoin_eq_of_isAlgebraic_of_isSeparable (F := F) S)
rw [lift_top, lift_adjoin] at h
haveI : IsScalarTower F S K := IsScalarTower.of_algebraMap_eq (congrFun rfl)
rw [← h, ← map_eq_of_separableClosure_eq_bot F (separableClosure_eq_bot E K)]
simp only [coe_map, IsScalarTower.coe_toAlgHom', IntermediateField.algebraMap_apply]
end separableClosure
section TowerLaw
variable [Algebra E K] [IsScalarTower F E K]
variable {F K} in
/-- If `K / E / F` is a field extension tower such that `E / F` is purely inseparable,
if `{ u_i }` is a family of separable elements of `K` which is `F`-linearly independent,
then it is also `E`-linearly independent. -/
theorem LinearIndependent.map_of_isPurelyInseparable_of_separable [IsPurelyInseparable F E]
{ι : Type*} {v : ι → K} (hsep : ∀ i : ι, (minpoly F (v i)).Separable)
(h : LinearIndependent F v) : LinearIndependent E v := by
obtain ⟨q, _⟩ := ExpChar.exists F
haveI := expChar_of_injective_algebraMap (algebraMap F K).injective q
refine linearIndependent_iff.mpr fun l hl ↦ Finsupp.ext fun i ↦ ?_
choose f hf using fun i ↦ (isPurelyInseparable_iff_pow_mem F q).1 ‹_› (l i)
let n := l.support.sup f
have := (expChar_pow_pos F q n).ne'
replace hf (i : ι) : l i ^ q ^ n ∈ (algebraMap F E).range := by
by_cases hs : i ∈ l.support
· convert pow_mem (hf i) (q ^ (n - f i)) using 1
rw [← pow_mul, ← pow_add, Nat.add_sub_of_le (Finset.le_sup hs)]
exact ⟨0, by rw [map_zero, Finsupp.not_mem_support_iff.1 hs, zero_pow this]⟩
choose lF hlF using hf
let lF₀ := Finsupp.onFinset l.support lF fun i ↦ by
contrapose!
refine fun hs ↦ (injective_iff_map_eq_zero _).mp (algebraMap F E).injective _ ?_
rw [hlF, Finsupp.not_mem_support_iff.1 hs, zero_pow this]
replace h := linearIndependent_iff.1 (h.map_pow_expChar_pow_of_separable q n hsep) lF₀ <| by
replace hl := congr($hl ^ q ^ n)
rw [Finsupp.total_apply, Finsupp.sum, sum_pow_char_pow, zero_pow this] at hl
rw [← hl, Finsupp.total_apply, Finsupp.onFinset_sum _ (fun _ ↦ by exact zero_smul _ _)]
refine Finset.sum_congr rfl fun i _ ↦ ?_
simp_rw [Algebra.smul_def, mul_pow, IsScalarTower.algebraMap_apply F E K, hlF, map_pow]
refine pow_eq_zero ((hlF _).symm.trans ?_)
convert map_zero (algebraMap F E)
exact congr($h i)
namespace Field
/-- If `K / E / F` is a field extension tower, such that `E / F` is purely inseparable and `K / E`
is separable, then the separable degree of `K / F` is equal to the degree of `K / E`.
It is a special case of `Field.lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic`, and is an
intermediate result used to prove it. -/
lemma sepDegree_eq_of_isPurelyInseparable_of_isSeparable
[IsPurelyInseparable F E] [IsSeparable E K] : sepDegree F K = Module.rank E K := by
let S := separableClosure F K
have h := S.adjoin_rank_le_of_isAlgebraic_right E
rw [separableClosure.adjoin_eq_of_isAlgebraic_of_isSeparable K, rank_top'] at h
obtain ⟨ι, ⟨b⟩⟩ := Basis.exists_basis F S
exact h.antisymm' (b.mk_eq_rank'' ▸ (b.linearIndependent.map' S.val.toLinearMap
(LinearMap.ker_eq_bot_of_injective S.val.injective) |>.map_of_isPurelyInseparable_of_separable E
(fun i ↦ by simpa only [minpoly_eq] using IsSeparable.separable F (b i)) |>.cardinal_le_rank))
/-- If `K / E / F` is a field extension tower, such that `E / F` is separable,
then $[E:F] [K:E]_s = [K:F]_s$.
It is a special case of `Field.lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic`, and is an
intermediate result used to prove it. -/
lemma lift_rank_mul_lift_sepDegree_of_isSeparable [IsSeparable F E] :
Cardinal.lift.{w} (Module.rank F E) * Cardinal.lift.{v} (sepDegree E K) =
Cardinal.lift.{v} (sepDegree F K) := by
rw [sepDegree, sepDegree, separableClosure.eq_restrictScalars_of_isSeparable F E K]
exact lift_rank_mul_lift_rank F E (separableClosure E K)
/-- The same-universe version of `Field.lift_rank_mul_lift_sepDegree_of_isSeparable`. -/
lemma rank_mul_sepDegree_of_isSeparable (K : Type v) [Field K] [Algebra F K]
[Algebra E K] [IsScalarTower F E K] [IsSeparable F E] :
Module.rank F E * sepDegree E K = sepDegree F K := by
simpa only [Cardinal.lift_id] using lift_rank_mul_lift_sepDegree_of_isSeparable F E K
/-- If `K / E / F` is a field extension tower, such that `E / F` is purely inseparable,
then $[K:F]_s = [K:E]_s$.
It is a special case of `Field.lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic`, and is an
intermediate result used to prove it. -/
lemma sepDegree_eq_of_isPurelyInseparable [IsPurelyInseparable F E] :
sepDegree F K = sepDegree E K := by
convert sepDegree_eq_of_isPurelyInseparable_of_isSeparable F E (separableClosure E K)
haveI : IsScalarTower F (separableClosure E K) K := IsScalarTower.of_algebraMap_eq (congrFun rfl)
rw [sepDegree, ← separableClosure.map_eq_of_separableClosure_eq_bot F
(separableClosure.separableClosure_eq_bot E K)]
exact (separableClosure F (separableClosure E K)).equivMap
(IsScalarTower.toAlgHom F (separableClosure E K) K) |>.symm.toLinearEquiv.rank_eq
/-- If `K / E / F` is a field extension tower, such that `E / F` is algebraic, then their
separable degrees satisfy the tower law: $[E:F]_s [K:E]_s = [K:F]_s$. -/
theorem lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic [Algebra.IsAlgebraic F E] :
Cardinal.lift.{w} (sepDegree F E) * Cardinal.lift.{v} (sepDegree E K) =
Cardinal.lift.{v} (sepDegree F K) := by
have h := lift_rank_mul_lift_sepDegree_of_isSeparable F (separableClosure F E) K
haveI := separableClosure.isPurelyInseparable F E
rwa [sepDegree_eq_of_isPurelyInseparable (separableClosure F E) E K] at h
/-- The same-universe version of `Field.lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic`. -/
theorem sepDegree_mul_sepDegree_of_isAlgebraic (K : Type v) [Field K] [Algebra F K]
[Algebra E K] [IsScalarTower F E K] [Algebra.IsAlgebraic F E] :
sepDegree F E * sepDegree E K = sepDegree F K := by
simpa only [Cardinal.lift_id] using lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic F E K
end Field
variable {F K} in
/-- 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. -/
theorem IntermediateField.sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable
(S : Set K) [Algebra.IsAlgebraic F (adjoin F S)] [IsPurelyInseparable F E] :
sepDegree E (adjoin E S) = sepDegree F (adjoin F S) := by
set M := adjoin F S
set L := adjoin E S
let E' := (IsScalarTower.toAlgHom F E K).fieldRange
let j : E ≃ₐ[F] E' := AlgEquiv.ofInjectiveField (IsScalarTower.toAlgHom F E K)
have hi : M ≤ L.restrictScalars F := by
rw [restrictScalars_adjoin_of_algEquiv (E := K) j rfl, restrictScalars_adjoin]
exact adjoin.mono _ _ _ Set.subset_union_right
let i : M →+* L := Subsemiring.inclusion hi
letI : Algebra M L := i.toAlgebra
letI : SMul M L := Algebra.toSMul
haveI : IsScalarTower F M L := IsScalarTower.of_algebraMap_eq (congrFun rfl)
haveI : IsPurelyInseparable M L := by
change IsPurelyInseparable M (extendScalars hi)
obtain ⟨q, _⟩ := ExpChar.exists F
have : extendScalars hi = adjoin M (E' : Set K) := restrictScalars_injective F <| by
conv_lhs => rw [extendScalars_restrictScalars, restrictScalars_adjoin_of_algEquiv
(E := K) j rfl, ← adjoin_self F E', adjoin_adjoin_comm]
rw [this, isPurelyInseparable_adjoin_iff_pow_mem _ _ q]
rintro x ⟨y, hy⟩
obtain ⟨n, z, hz⟩ := IsPurelyInseparable.pow_mem F q y
refine ⟨n, algebraMap F M z, ?_⟩
rw [← IsScalarTower.algebraMap_apply, IsScalarTower.algebraMap_apply F E K, hz, ← hy, map_pow,
AlgHom.toRingHom_eq_coe, IsScalarTower.coe_toAlgHom]
have h := lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic F E L
rw [IsPurelyInseparable.sepDegree_eq_one F E, Cardinal.lift_one, one_mul] at h
rw [Cardinal.lift_injective h, ← sepDegree_mul_sepDegree_of_isAlgebraic F M L,
IsPurelyInseparable.sepDegree_eq_one M L, mul_one]
variable {F K} in
/-- If `K / E / F` is a field extension tower, such that `E / F` is purely inseparable, then
for any intermediate field `S` of `K / F` such that `S / F` is algebraic, the `E(S) / E` and
`S / F` have the same separable degree. -/
theorem IntermediateField.sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable'
(S : IntermediateField F K) [Algebra.IsAlgebraic F S] [IsPurelyInseparable F E] :
sepDegree E (adjoin E (S : Set K)) = sepDegree F S := by
have : Algebra.IsAlgebraic F (adjoin F (S : Set K)) := by rwa [adjoin_self]
have := sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable (F := F) E (S : Set K)
rwa [adjoin_self] at this
variable {F K} in
/-- 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`. -/
| Mathlib/FieldTheory/PurelyInseparable.lean | 1,039 | 1,054 | theorem minpoly.map_eq_of_separable_of_isPurelyInseparable (x : K)
(hsep : (minpoly F x).Separable) [IsPurelyInseparable F E] :
(minpoly F x).map (algebraMap F E) = minpoly E x := by |
have hi := hsep.isIntegral
have hi' : IsIntegral E x := IsIntegral.tower_top hi
refine eq_of_monic_of_dvd_of_natDegree_le (monic hi') ((monic hi).map (algebraMap F E))
(dvd_map_of_isScalarTower F E x) (le_of_eq ?_)
have hsep' := hsep.map_minpoly E
haveI := (isSeparable_adjoin_simple_iff_separable _ _).2 hsep
haveI := (isSeparable_adjoin_simple_iff_separable _ _).2 hsep'
have := IsSeparable.isAlgebraic F F⟮x⟯
have := IsSeparable.isAlgebraic E E⟮x⟯
rw [Polynomial.natDegree_map, ← adjoin.finrank hi, ← adjoin.finrank hi',
← finSepDegree_eq_finrank_of_isSeparable F _, ← finSepDegree_eq_finrank_of_isSeparable E _,
finSepDegree_eq, finSepDegree_eq,
sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable (F := F) E]
|
/-
Copyright (c) 2020 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp
-/
import Mathlib.Algebra.Algebra.Spectrum
import Mathlib.LinearAlgebra.GeneralLinearGroup
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.RingTheory.Nilpotent.Basic
#align_import linear_algebra.eigenspace.basic from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1"
/-!
# Eigenvectors and eigenvalues
This file defines eigenspaces, eigenvalues, and eigenvalues, as well as their generalized
counterparts. We follow Axler's approach [axler2015] because it allows us to derive many properties
without choosing a basis and without using matrices.
An eigenspace of a linear map `f` for a scalar `μ` is the kernel of the map `(f - μ • id)`. The
nonzero elements of an eigenspace are eigenvectors `x`. They have the property `f x = μ • x`. If
there are eigenvectors for a scalar `μ`, the scalar `μ` is called an eigenvalue.
There is no consensus in the literature whether `0` is an eigenvector. Our definition of
`HasEigenvector` permits only nonzero vectors. For an eigenvector `x` that may also be `0`, we
write `x ∈ f.eigenspace μ`.
A generalized eigenspace of a linear map `f` for a natural number `k` and a scalar `μ` is the kernel
of the map `(f - μ • id) ^ k`. The nonzero elements of a generalized eigenspace are generalized
eigenvectors `x`. If there are generalized eigenvectors for a natural number `k` and a scalar `μ`,
the scalar `μ` is called a generalized eigenvalue.
The fact that the eigenvalues are the roots of the minimal polynomial is proved in
`LinearAlgebra.Eigenspace.Minpoly`.
The existence of eigenvalues over an algebraically closed field
(and the fact that the generalized eigenspaces then span) is deferred to
`LinearAlgebra.Eigenspace.IsAlgClosed`.
## References
* [Sheldon Axler, *Linear Algebra Done Right*][axler2015]
* https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
## Tags
eigenspace, eigenvector, eigenvalue, eigen
-/
universe u v w
namespace Module
namespace End
open FiniteDimensional Set
variable {K R : Type v} {V M : Type w} [CommRing R] [AddCommGroup M] [Module R M] [Field K]
[AddCommGroup V] [Module K V]
/-- The submodule `eigenspace f μ` for a linear map `f` and a scalar `μ` consists of all vectors `x`
such that `f x = μ • x`. (Def 5.36 of [axler2015])-/
def eigenspace (f : End R M) (μ : R) : Submodule R M :=
LinearMap.ker (f - algebraMap R (End R M) μ)
#align module.End.eigenspace Module.End.eigenspace
@[simp]
theorem eigenspace_zero (f : End R M) : f.eigenspace 0 = LinearMap.ker f := by simp [eigenspace]
#align module.End.eigenspace_zero Module.End.eigenspace_zero
/-- A nonzero element of an eigenspace is an eigenvector. (Def 5.7 of [axler2015]) -/
def HasEigenvector (f : End R M) (μ : R) (x : M) : Prop :=
x ∈ eigenspace f μ ∧ x ≠ 0
#align module.End.has_eigenvector Module.End.HasEigenvector
/-- A scalar `μ` is an eigenvalue for a linear map `f` if there are nonzero vectors `x`
such that `f x = μ • x`. (Def 5.5 of [axler2015]) -/
def HasEigenvalue (f : End R M) (a : R) : Prop :=
eigenspace f a ≠ ⊥
#align module.End.has_eigenvalue Module.End.HasEigenvalue
/-- The eigenvalues of the endomorphism `f`, as a subtype of `R`. -/
def Eigenvalues (f : End R M) : Type _ :=
{ μ : R // f.HasEigenvalue μ }
#align module.End.eigenvalues Module.End.Eigenvalues
@[coe]
def Eigenvalues.val (f : Module.End R M) : Eigenvalues f → R := Subtype.val
instance Eigenvalues.instCoeOut {f : Module.End R M} : CoeOut (Eigenvalues f) R where
coe := Eigenvalues.val f
instance Eigenvalues.instDecidableEq [DecidableEq R] (f : Module.End R M) :
DecidableEq (Eigenvalues f) :=
inferInstanceAs (DecidableEq (Subtype (fun x : R => HasEigenvalue f x)))
theorem hasEigenvalue_of_hasEigenvector {f : End R M} {μ : R} {x : M} (h : HasEigenvector f μ x) :
HasEigenvalue f μ := by
rw [HasEigenvalue, Submodule.ne_bot_iff]
use x; exact h
#align module.End.has_eigenvalue_of_has_eigenvector Module.End.hasEigenvalue_of_hasEigenvector
theorem mem_eigenspace_iff {f : End R M} {μ : R} {x : M} : x ∈ eigenspace f μ ↔ f x = μ • x := by
rw [eigenspace, LinearMap.mem_ker, LinearMap.sub_apply, algebraMap_end_apply, sub_eq_zero]
#align module.End.mem_eigenspace_iff Module.End.mem_eigenspace_iff
theorem HasEigenvector.apply_eq_smul {f : End R M} {μ : R} {x : M} (hx : f.HasEigenvector μ x) :
f x = μ • x :=
mem_eigenspace_iff.mp hx.1
#align module.End.has_eigenvector.apply_eq_smul Module.End.HasEigenvector.apply_eq_smul
theorem HasEigenvector.pow_apply {f : End R M} {μ : R} {v : M} (hv : f.HasEigenvector μ v) (n : ℕ) :
(f ^ n) v = μ ^ n • v := by
induction n <;> simp [*, pow_succ f, hv.apply_eq_smul, smul_smul, pow_succ' μ]
theorem HasEigenvalue.exists_hasEigenvector {f : End R M} {μ : R} (hμ : f.HasEigenvalue μ) :
∃ v, f.HasEigenvector μ v :=
Submodule.exists_mem_ne_zero_of_ne_bot hμ
#align module.End.has_eigenvalue.exists_has_eigenvector Module.End.HasEigenvalue.exists_hasEigenvector
lemma HasEigenvalue.pow {f : End R M} {μ : R} (h : f.HasEigenvalue μ) (n : ℕ) :
(f ^ n).HasEigenvalue (μ ^ n) := by
rw [HasEigenvalue, Submodule.ne_bot_iff]
obtain ⟨m : M, hm⟩ := h.exists_hasEigenvector
exact ⟨m, by simpa [mem_eigenspace_iff] using hm.pow_apply n, hm.2⟩
/-- A nilpotent endomorphism has nilpotent eigenvalues.
See also `LinearMap.isNilpotent_trace_of_isNilpotent`. -/
lemma HasEigenvalue.isNilpotent_of_isNilpotent [NoZeroSMulDivisors R M] {f : End R M}
(hfn : IsNilpotent f) {μ : R} (hf : f.HasEigenvalue μ) :
IsNilpotent μ := by
obtain ⟨m : M, hm⟩ := hf.exists_hasEigenvector
obtain ⟨n : ℕ, hn : f ^ n = 0⟩ := hfn
exact ⟨n, by simpa [hn, hm.2, eq_comm (a := (0 : M))] using hm.pow_apply n⟩
theorem HasEigenvalue.mem_spectrum {f : End R M} {μ : R} (hμ : HasEigenvalue f μ) :
μ ∈ spectrum R f := by
refine spectrum.mem_iff.mpr fun h_unit => ?_
set f' := LinearMap.GeneralLinearGroup.toLinearEquiv h_unit.unit
rcases hμ.exists_hasEigenvector with ⟨v, hv⟩
refine hv.2 ((LinearMap.ker_eq_bot'.mp f'.ker) v (?_ : μ • v - f v = 0))
rw [hv.apply_eq_smul, sub_self]
#align module.End.mem_spectrum_of_has_eigenvalue Module.End.HasEigenvalue.mem_spectrum
theorem hasEigenvalue_iff_mem_spectrum [FiniteDimensional K V] {f : End K V} {μ : K} :
f.HasEigenvalue μ ↔ μ ∈ spectrum K f := by
rw [spectrum.mem_iff, IsUnit.sub_iff, LinearMap.isUnit_iff_ker_eq_bot, HasEigenvalue, eigenspace]
#align module.End.has_eigenvalue_iff_mem_spectrum Module.End.hasEigenvalue_iff_mem_spectrum
alias ⟨_, HasEigenvalue.of_mem_spectrum⟩ := hasEigenvalue_iff_mem_spectrum
theorem eigenspace_div (f : End K V) (a b : K) (hb : b ≠ 0) :
eigenspace f (a / b) = LinearMap.ker (b • f - algebraMap K (End K V) a) :=
calc
eigenspace f (a / b) = eigenspace f (b⁻¹ * a) := by rw [div_eq_mul_inv, mul_comm]
_ = LinearMap.ker (f - (b⁻¹ * a) • LinearMap.id) := by rw [eigenspace]; rfl
_ = LinearMap.ker (f - b⁻¹ • a • LinearMap.id) := by rw [smul_smul]
_ = LinearMap.ker (f - b⁻¹ • algebraMap K (End K V) a) := rfl
_ = LinearMap.ker (b • (f - b⁻¹ • algebraMap K (End K V) a)) := by
rw [LinearMap.ker_smul _ b hb]
_ = LinearMap.ker (b • f - algebraMap K (End K V) a) := by rw [smul_sub, smul_inv_smul₀ hb]
#align module.End.eigenspace_div Module.End.eigenspace_div
/-- The generalized eigenspace for a linear map `f`, a scalar `μ`, and an exponent `k ∈ ℕ` is the
kernel of `(f - μ • id) ^ k`. (Def 8.10 of [axler2015]). Furthermore, a generalized eigenspace for
some exponent `k` is contained in the generalized eigenspace for exponents larger than `k`. -/
def genEigenspace (f : End R M) (μ : R) : ℕ →o Submodule R M where
toFun k := LinearMap.ker ((f - algebraMap R (End R M) μ) ^ k)
monotone' k m hm := by
simp only [← pow_sub_mul_pow _ hm]
exact
LinearMap.ker_le_ker_comp ((f - algebraMap R (End R M) μ) ^ k)
((f - algebraMap R (End R M) μ) ^ (m - k))
#align module.End.generalized_eigenspace Module.End.genEigenspace
@[simp]
theorem mem_genEigenspace (f : End R M) (μ : R) (k : ℕ) (m : M) :
m ∈ f.genEigenspace μ k ↔ ((f - μ • (1 : End R M)) ^ k) m = 0 := Iff.rfl
#align module.End.mem_generalized_eigenspace Module.End.mem_genEigenspace
@[simp]
theorem genEigenspace_zero (f : End R M) (k : ℕ) :
f.genEigenspace 0 k = LinearMap.ker (f ^ k) := by
simp [Module.End.genEigenspace]
#align module.End.generalized_eigenspace_zero Module.End.genEigenspace_zero
/-- A nonzero element of a generalized eigenspace is a generalized eigenvector.
(Def 8.9 of [axler2015])-/
def HasGenEigenvector (f : End R M) (μ : R) (k : ℕ) (x : M) : Prop :=
x ≠ 0 ∧ x ∈ genEigenspace f μ k
#align module.End.has_generalized_eigenvector Module.End.HasGenEigenvector
/-- A scalar `μ` is a generalized eigenvalue for a linear map `f` and an exponent `k ∈ ℕ` if there
are generalized eigenvectors for `f`, `k`, and `μ`. -/
def HasGenEigenvalue (f : End R M) (μ : R) (k : ℕ) : Prop :=
genEigenspace f μ k ≠ ⊥
#align module.End.has_generalized_eigenvalue Module.End.HasGenEigenvalue
/-- The generalized eigenrange for a linear map `f`, a scalar `μ`, and an exponent `k ∈ ℕ` is the
range of `(f - μ • id) ^ k`. -/
def genEigenrange (f : End R M) (μ : R) (k : ℕ) : Submodule R M :=
LinearMap.range ((f - algebraMap R (End R M) μ) ^ k)
#align module.End.generalized_eigenrange Module.End.genEigenrange
/-- The exponent of a generalized eigenvalue is never 0. -/
theorem exp_ne_zero_of_hasGenEigenvalue {f : End R M} {μ : R} {k : ℕ}
(h : f.HasGenEigenvalue μ k) : k ≠ 0 := by
rintro rfl
exact h LinearMap.ker_id
#align module.End.exp_ne_zero_of_has_generalized_eigenvalue Module.End.exp_ne_zero_of_hasGenEigenvalue
/-- The union of the kernels of `(f - μ • id) ^ k` over all `k`. -/
def maxGenEigenspace (f : End R M) (μ : R) : Submodule R M :=
⨆ k, f.genEigenspace μ k
#align module.End.maximal_generalized_eigenspace Module.End.maxGenEigenspace
theorem genEigenspace_le_maximal (f : End R M) (μ : R) (k : ℕ) :
f.genEigenspace μ k ≤ f.maxGenEigenspace μ :=
le_iSup _ _
#align module.End.generalized_eigenspace_le_maximal Module.End.genEigenspace_le_maximal
@[simp]
theorem mem_maxGenEigenspace (f : End R M) (μ : R) (m : M) :
m ∈ f.maxGenEigenspace μ ↔ ∃ k : ℕ, ((f - μ • (1 : End R M)) ^ k) m = 0 := by
simp only [maxGenEigenspace, ← mem_genEigenspace, Submodule.mem_iSup_of_chain]
#align module.End.mem_maximal_generalized_eigenspace Module.End.mem_maxGenEigenspace
/-- If there exists a natural number `k` such that the kernel of `(f - μ • id) ^ k` is the
maximal generalized eigenspace, then this value is the least such `k`. If not, this value is not
meaningful. -/
noncomputable def maxGenEigenspaceIndex (f : End R M) (μ : R) :=
monotonicSequenceLimitIndex (f.genEigenspace μ)
#align module.End.maximal_generalized_eigenspace_index Module.End.maxGenEigenspaceIndex
/-- For an endomorphism of a Noetherian module, the maximal eigenspace is always of the form kernel
`(f - μ • id) ^ k` for some `k`. -/
| Mathlib/LinearAlgebra/Eigenspace/Basic.lean | 239 | 243 | theorem maxGenEigenspace_eq [h : IsNoetherian R M] (f : End R M) (μ : R) :
maxGenEigenspace f μ =
f.genEigenspace μ (maxGenEigenspaceIndex f μ) := by |
rw [isNoetherian_iff_wellFounded] at h
exact (WellFounded.iSup_eq_monotonicSequenceLimit h (f.genEigenspace μ) : _)
|
/-
Copyright (c) 2020 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Constructions.Prod.Basic
import Mathlib.MeasureTheory.Group.Measure
import Mathlib.Topology.Constructions
#align_import measure_theory.constructions.pi from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Product measures
In this file we define and prove properties about finite products of measures
(and at some point, countable products of measures).
## Main definition
* `MeasureTheory.Measure.pi`: The product of finitely many σ-finite measures.
Given `μ : (i : ι) → Measure (α i)` for `[Fintype ι]` it has type `Measure ((i : ι) → α i)`.
To apply Fubini's theorem or Tonelli's theorem along some subset, we recommend using the marginal
construction `MeasureTheory.lmarginal` and (todo) `MeasureTheory.marginal`. This allows you to
apply the theorems without any bookkeeping with measurable equivalences.
## Implementation Notes
We define `MeasureTheory.OuterMeasure.pi`, the product of finitely many outer measures, as the
maximal outer measure `n` with the property that `n (pi univ s) ≤ ∏ i, m i (s i)`,
where `pi univ s` is the product of the sets `{s i | i : ι}`.
We then show that this induces a product of measures, called `MeasureTheory.Measure.pi`.
For a collection of σ-finite measures `μ` and a collection of measurable sets `s` we show that
`Measure.pi μ (pi univ s) = ∏ i, m i (s i)`. To do this, we follow the following steps:
* We know that there is some ordering on `ι`, given by an element of `[Countable ι]`.
* Using this, we have an equivalence `MeasurableEquiv.piMeasurableEquivTProd` between
`∀ ι, α i` and an iterated product of `α i`, called `List.tprod α l` for some list `l`.
* On this iterated product we can easily define a product measure `MeasureTheory.Measure.tprod`
by iterating `MeasureTheory.Measure.prod`
* Using the previous two steps we construct `MeasureTheory.Measure.pi'` on `(i : ι) → α i` for
countable `ι`.
* We know that `MeasureTheory.Measure.pi'` sends products of sets to products of measures, and
since `MeasureTheory.Measure.pi` is the maximal such measure (or at least, it comes from an outer
measure which is the maximal such outer measure), we get the same rule for
`MeasureTheory.Measure.pi`.
## Tags
finitary product measure
-/
noncomputable section
open Function Set MeasureTheory.OuterMeasure Filter MeasurableSpace Encodable
open scoped Classical Topology ENNReal
universe u v
variable {ι ι' : Type*} {α : ι → Type*}
/-! We start with some measurability properties -/
/-- Boxes formed by π-systems form a π-system. -/
theorem IsPiSystem.pi {C : ∀ i, Set (Set (α i))} (hC : ∀ i, IsPiSystem (C i)) :
IsPiSystem (pi univ '' pi univ C) := by
rintro _ ⟨s₁, hs₁, rfl⟩ _ ⟨s₂, hs₂, rfl⟩ hst
rw [← pi_inter_distrib] at hst ⊢; rw [univ_pi_nonempty_iff] at hst
exact mem_image_of_mem _ fun i _ => hC i _ (hs₁ i (mem_univ i)) _ (hs₂ i (mem_univ i)) (hst i)
#align is_pi_system.pi IsPiSystem.pi
/-- Boxes form a π-system. -/
theorem isPiSystem_pi [∀ i, MeasurableSpace (α i)] :
IsPiSystem (pi univ '' pi univ fun i => { s : Set (α i) | MeasurableSet s }) :=
IsPiSystem.pi fun _ => isPiSystem_measurableSet
#align is_pi_system_pi isPiSystem_pi
section Finite
variable [Finite ι] [Finite ι']
/-- Boxes of countably spanning sets are countably spanning. -/
theorem IsCountablySpanning.pi {C : ∀ i, Set (Set (α i))} (hC : ∀ i, IsCountablySpanning (C i)) :
IsCountablySpanning (pi univ '' pi univ C) := by
choose s h1s h2s using hC
cases nonempty_encodable (ι → ℕ)
let e : ℕ → ι → ℕ := fun n => (@decode (ι → ℕ) _ n).iget
refine ⟨fun n => Set.pi univ fun i => s i (e n i), fun n =>
mem_image_of_mem _ fun i _ => h1s i _, ?_⟩
simp_rw [(surjective_decode_iget (ι → ℕ)).iUnion_comp fun x => Set.pi univ fun i => s i (x i),
iUnion_univ_pi s, h2s, pi_univ]
#align is_countably_spanning.pi IsCountablySpanning.pi
/-- The product of generated σ-algebras is the one generated by boxes, if both generating sets
are countably spanning. -/
theorem generateFrom_pi_eq {C : ∀ i, Set (Set (α i))} (hC : ∀ i, IsCountablySpanning (C i)) :
(@MeasurableSpace.pi _ _ fun i => generateFrom (C i)) =
generateFrom (pi univ '' pi univ C) := by
cases nonempty_encodable ι
apply le_antisymm
· refine iSup_le ?_; intro i; rw [comap_generateFrom]
apply generateFrom_le; rintro _ ⟨s, hs, rfl⟩; dsimp
choose t h1t h2t using hC
simp_rw [eval_preimage, ← h2t]
rw [← @iUnion_const _ ℕ _ s]
have : Set.pi univ (update (fun i' : ι => iUnion (t i')) i (⋃ _ : ℕ, s)) =
Set.pi univ fun k => ⋃ j : ℕ,
@update ι (fun i' => Set (α i')) _ (fun i' => t i' j) i s k := by
ext; simp_rw [mem_univ_pi]; apply forall_congr'; intro i'
by_cases h : i' = i
· subst h; simp
· rw [← Ne] at h; simp [h]
rw [this, ← iUnion_univ_pi]
apply MeasurableSet.iUnion
intro n; apply measurableSet_generateFrom
apply mem_image_of_mem; intro j _; dsimp only
by_cases h : j = i
· subst h; rwa [update_same]
· rw [update_noteq h]; apply h1t
· apply generateFrom_le; rintro _ ⟨s, hs, rfl⟩
rw [univ_pi_eq_iInter]; apply MeasurableSet.iInter; intro i
apply @measurable_pi_apply _ _ (fun i => generateFrom (C i))
exact measurableSet_generateFrom (hs i (mem_univ i))
#align generate_from_pi_eq generateFrom_pi_eq
/-- If `C` and `D` generate the σ-algebras on `α` resp. `β`, then rectangles formed by `C` and `D`
generate the σ-algebra on `α × β`. -/
theorem generateFrom_eq_pi [h : ∀ i, MeasurableSpace (α i)] {C : ∀ i, Set (Set (α i))}
(hC : ∀ i, generateFrom (C i) = h i) (h2C : ∀ i, IsCountablySpanning (C i)) :
generateFrom (pi univ '' pi univ C) = MeasurableSpace.pi := by
simp only [← funext hC, generateFrom_pi_eq h2C]
#align generate_from_eq_pi generateFrom_eq_pi
/-- The product σ-algebra is generated from boxes, i.e. `s ×ˢ t` for sets `s : set α` and
`t : set β`. -/
theorem generateFrom_pi [∀ i, MeasurableSpace (α i)] :
generateFrom (pi univ '' pi univ fun i => { s : Set (α i) | MeasurableSet s }) =
MeasurableSpace.pi :=
generateFrom_eq_pi (fun _ => generateFrom_measurableSet) fun _ =>
isCountablySpanning_measurableSet
#align generate_from_pi generateFrom_pi
end Finite
namespace MeasureTheory
variable [Fintype ι] {m : ∀ i, OuterMeasure (α i)}
/-- An upper bound for the measure in a finite product space.
It is defined to by taking the image of the set under all projections, and taking the product
of the measures of these images.
For measurable boxes it is equal to the correct measure. -/
@[simp]
def piPremeasure (m : ∀ i, OuterMeasure (α i)) (s : Set (∀ i, α i)) : ℝ≥0∞ :=
∏ i, m i (eval i '' s)
#align measure_theory.pi_premeasure MeasureTheory.piPremeasure
theorem piPremeasure_pi {s : ∀ i, Set (α i)} (hs : (pi univ s).Nonempty) :
piPremeasure m (pi univ s) = ∏ i, m i (s i) := by simp [hs, piPremeasure]
#align measure_theory.pi_premeasure_pi MeasureTheory.piPremeasure_pi
theorem piPremeasure_pi' {s : ∀ i, Set (α i)} : piPremeasure m (pi univ s) = ∏ i, m i (s i) := by
cases isEmpty_or_nonempty ι
· simp [piPremeasure]
rcases (pi univ s).eq_empty_or_nonempty with h | h
· rcases univ_pi_eq_empty_iff.mp h with ⟨i, hi⟩
have : ∃ i, m i (s i) = 0 := ⟨i, by simp [hi]⟩
simpa [h, Finset.card_univ, zero_pow Fintype.card_ne_zero, @eq_comm _ (0 : ℝ≥0∞),
Finset.prod_eq_zero_iff, piPremeasure]
· simp [h, piPremeasure]
#align measure_theory.pi_premeasure_pi' MeasureTheory.piPremeasure_pi'
theorem piPremeasure_pi_mono {s t : Set (∀ i, α i)} (h : s ⊆ t) :
piPremeasure m s ≤ piPremeasure m t :=
Finset.prod_le_prod' fun _ _ => measure_mono (image_subset _ h)
#align measure_theory.pi_premeasure_pi_mono MeasureTheory.piPremeasure_pi_mono
theorem piPremeasure_pi_eval {s : Set (∀ i, α i)} :
piPremeasure m (pi univ fun i => eval i '' s) = piPremeasure m s := by
simp only [eval, piPremeasure_pi']; rfl
#align measure_theory.pi_premeasure_pi_eval MeasureTheory.piPremeasure_pi_eval
namespace OuterMeasure
/-- `OuterMeasure.pi m` is the finite product of the outer measures `{m i | i : ι}`.
It is defined to be the maximal outer measure `n` with the property that
`n (pi univ s) ≤ ∏ i, m i (s i)`, where `pi univ s` is the product of the sets
`{s i | i : ι}`. -/
protected def pi (m : ∀ i, OuterMeasure (α i)) : OuterMeasure (∀ i, α i) :=
boundedBy (piPremeasure m)
#align measure_theory.outer_measure.pi MeasureTheory.OuterMeasure.pi
theorem pi_pi_le (m : ∀ i, OuterMeasure (α i)) (s : ∀ i, Set (α i)) :
OuterMeasure.pi m (pi univ s) ≤ ∏ i, m i (s i) := by
rcases (pi univ s).eq_empty_or_nonempty with h | h
· simp [h]
exact (boundedBy_le _).trans_eq (piPremeasure_pi h)
#align measure_theory.outer_measure.pi_pi_le MeasureTheory.OuterMeasure.pi_pi_le
theorem le_pi {m : ∀ i, OuterMeasure (α i)} {n : OuterMeasure (∀ i, α i)} :
n ≤ OuterMeasure.pi m ↔
∀ s : ∀ i, Set (α i), (pi univ s).Nonempty → n (pi univ s) ≤ ∏ i, m i (s i) := by
rw [OuterMeasure.pi, le_boundedBy']; constructor
· intro h s hs; refine (h _ hs).trans_eq (piPremeasure_pi hs)
· intro h s hs; refine le_trans (n.mono <| subset_pi_eval_image univ s) (h _ ?_)
simp [univ_pi_nonempty_iff, hs]
#align measure_theory.outer_measure.le_pi MeasureTheory.OuterMeasure.le_pi
end OuterMeasure
namespace Measure
variable [∀ i, MeasurableSpace (α i)] (μ : ∀ i, Measure (α i))
section Tprod
open List
variable {δ : Type*} {π : δ → Type*} [∀ x, MeasurableSpace (π x)]
-- for some reason the equation compiler doesn't like this definition
/-- A product of measures in `tprod α l`. -/
protected def tprod (l : List δ) (μ : ∀ i, Measure (π i)) : Measure (TProd π l) := by
induction' l with i l ih
· exact dirac PUnit.unit
· have := (μ i).prod (α := π i) ih
exact this
#align measure_theory.measure.tprod MeasureTheory.Measure.tprod
@[simp]
theorem tprod_nil (μ : ∀ i, Measure (π i)) : Measure.tprod [] μ = dirac PUnit.unit :=
rfl
#align measure_theory.measure.tprod_nil MeasureTheory.Measure.tprod_nil
@[simp]
theorem tprod_cons (i : δ) (l : List δ) (μ : ∀ i, Measure (π i)) :
Measure.tprod (i :: l) μ = (μ i).prod (Measure.tprod l μ) :=
rfl
#align measure_theory.measure.tprod_cons MeasureTheory.Measure.tprod_cons
instance sigmaFinite_tprod (l : List δ) (μ : ∀ i, Measure (π i)) [∀ i, SigmaFinite (μ i)] :
SigmaFinite (Measure.tprod l μ) := by
induction l with
| nil => rw [tprod_nil]; infer_instance
| cons i l ih => rw [tprod_cons]; exact @prod.instSigmaFinite _ _ _ _ _ _ _ ih
#align measure_theory.measure.sigma_finite_tprod MeasureTheory.Measure.sigmaFinite_tprod
theorem tprod_tprod (l : List δ) (μ : ∀ i, Measure (π i)) [∀ i, SigmaFinite (μ i)]
(s : ∀ i, Set (π i)) :
Measure.tprod l μ (Set.tprod l s) = (l.map fun i => (μ i) (s i)).prod := by
induction l with
| nil => simp
| cons a l ih =>
rw [tprod_cons, Set.tprod]
erw [prod_prod] -- TODO: why `rw` fails?
rw [map_cons, prod_cons, ih]
#align measure_theory.measure.tprod_tprod MeasureTheory.Measure.tprod_tprod
end Tprod
section Encodable
open List MeasurableEquiv
variable [Encodable ι]
/-- The product measure on an encodable finite type, defined by mapping `Measure.tprod` along the
equivalence `MeasurableEquiv.piMeasurableEquivTProd`.
The definition `MeasureTheory.Measure.pi` should be used instead of this one. -/
def pi' : Measure (∀ i, α i) :=
Measure.map (TProd.elim' mem_sortedUniv) (Measure.tprod (sortedUniv ι) μ)
#align measure_theory.measure.pi' MeasureTheory.Measure.pi'
theorem pi'_pi [∀ i, SigmaFinite (μ i)] (s : ∀ i, Set (α i)) :
pi' μ (pi univ s) = ∏ i, μ i (s i) := by
rw [pi']
rw [← MeasurableEquiv.piMeasurableEquivTProd_symm_apply, MeasurableEquiv.map_apply,
MeasurableEquiv.piMeasurableEquivTProd_symm_apply, elim_preimage_pi, tprod_tprod _ μ, ←
List.prod_toFinset, sortedUniv_toFinset] <;>
exact sortedUniv_nodup ι
#align measure_theory.measure.pi'_pi MeasureTheory.Measure.pi'_pi
end Encodable
theorem pi_caratheodory :
MeasurableSpace.pi ≤ (OuterMeasure.pi fun i => (μ i).toOuterMeasure).caratheodory := by
refine iSup_le ?_
intro i s hs
rw [MeasurableSpace.comap] at hs
rcases hs with ⟨s, hs, rfl⟩
apply boundedBy_caratheodory
intro t
simp_rw [piPremeasure]
refine Finset.prod_add_prod_le' (Finset.mem_univ i) ?_ ?_ ?_
· simp [image_inter_preimage, image_diff_preimage, measure_inter_add_diff _ hs, le_refl]
· rintro j - _; gcongr; apply inter_subset_left
· rintro j - _; gcongr; apply diff_subset
#align measure_theory.measure.pi_caratheodory MeasureTheory.Measure.pi_caratheodory
/-- `Measure.pi μ` is the finite product of the measures `{μ i | i : ι}`.
It is defined to be measure corresponding to `MeasureTheory.OuterMeasure.pi`. -/
protected irreducible_def pi : Measure (∀ i, α i) :=
toMeasure (OuterMeasure.pi fun i => (μ i).toOuterMeasure) (pi_caratheodory μ)
#align measure_theory.measure.pi MeasureTheory.Measure.pi
-- Porting note: moved from below so that instances about `Measure.pi` and `MeasureSpace.pi`
-- go together
instance _root_.MeasureTheory.MeasureSpace.pi {α : ι → Type*} [∀ i, MeasureSpace (α i)] :
MeasureSpace (∀ i, α i) :=
⟨Measure.pi fun _ => volume⟩
#align measure_theory.measure_space.pi MeasureTheory.MeasureSpace.pi
theorem pi_pi_aux [∀ i, SigmaFinite (μ i)] (s : ∀ i, Set (α i)) (hs : ∀ i, MeasurableSet (s i)) :
Measure.pi μ (pi univ s) = ∏ i, μ i (s i) := by
refine le_antisymm ?_ ?_
· rw [Measure.pi, toMeasure_apply _ _ (MeasurableSet.pi countable_univ fun i _ => hs i)]
apply OuterMeasure.pi_pi_le
· haveI : Encodable ι := Fintype.toEncodable ι
simp_rw [← pi'_pi μ s, Measure.pi,
toMeasure_apply _ _ (MeasurableSet.pi countable_univ fun i _ => hs i)]
suffices (pi' μ).toOuterMeasure ≤ OuterMeasure.pi fun i => (μ i).toOuterMeasure by exact this _
clear hs s
rw [OuterMeasure.le_pi]
intro s _
exact (pi'_pi μ s).le
#align measure_theory.measure.pi_pi_aux MeasureTheory.Measure.pi_pi_aux
variable {μ}
/-- `Measure.pi μ` has finite spanning sets in rectangles of finite spanning sets. -/
def FiniteSpanningSetsIn.pi {C : ∀ i, Set (Set (α i))}
(hμ : ∀ i, (μ i).FiniteSpanningSetsIn (C i)) :
(Measure.pi μ).FiniteSpanningSetsIn (pi univ '' pi univ C) := by
haveI := fun i => (hμ i).sigmaFinite
haveI := Fintype.toEncodable ι
refine ⟨fun n => Set.pi univ fun i => (hμ i).set ((@decode (ι → ℕ) _ n).iget i),
fun n => ?_, fun n => ?_, ?_⟩ <;>
-- TODO (kmill) If this let comes before the refine, while the noncomputability checker
-- correctly sees this definition is computable, the Lean VM fails to see the binding is
-- computationally irrelevant. The `noncomputable section` doesn't help because all it does
-- is insert `noncomputable` for you when necessary.
let e : ℕ → ι → ℕ := fun n => (@decode (ι → ℕ) _ n).iget
· refine mem_image_of_mem _ fun i _ => (hμ i).set_mem _
· calc
Measure.pi μ (Set.pi univ fun i => (hμ i).set (e n i)) ≤
Measure.pi μ (Set.pi univ fun i => toMeasurable (μ i) ((hμ i).set (e n i))) :=
measure_mono (pi_mono fun i _ => subset_toMeasurable _ _)
_ = ∏ i, μ i (toMeasurable (μ i) ((hμ i).set (e n i))) :=
(pi_pi_aux μ _ fun i => measurableSet_toMeasurable _ _)
_ = ∏ i, μ i ((hμ i).set (e n i)) := by simp only [measure_toMeasurable]
_ < ∞ := ENNReal.prod_lt_top fun i _ => ((hμ i).finite _).ne
· simp_rw [(surjective_decode_iget (ι → ℕ)).iUnion_comp fun x =>
Set.pi univ fun i => (hμ i).set (x i),
iUnion_univ_pi fun i => (hμ i).set, (hμ _).spanning, Set.pi_univ]
#align measure_theory.measure.finite_spanning_sets_in.pi MeasureTheory.Measure.FiniteSpanningSetsIn.pi
/-- A measure on a finite product space equals the product measure if they are equal on rectangles
with as sides sets that generate the corresponding σ-algebras. -/
theorem pi_eq_generateFrom {C : ∀ i, Set (Set (α i))}
(hC : ∀ i, generateFrom (C i) = by apply_assumption) (h2C : ∀ i, IsPiSystem (C i))
(h3C : ∀ i, (μ i).FiniteSpanningSetsIn (C i)) {μν : Measure (∀ i, α i)}
(h₁ : ∀ s : ∀ i, Set (α i), (∀ i, s i ∈ C i) → μν (pi univ s) = ∏ i, μ i (s i)) :
Measure.pi μ = μν := by
have h4C : ∀ (i) (s : Set (α i)), s ∈ C i → MeasurableSet s := by
intro i s hs; rw [← hC]; exact measurableSet_generateFrom hs
refine
(FiniteSpanningSetsIn.pi h3C).ext
(generateFrom_eq_pi hC fun i => (h3C i).isCountablySpanning).symm (IsPiSystem.pi h2C) ?_
rintro _ ⟨s, hs, rfl⟩
rw [mem_univ_pi] at hs
haveI := fun i => (h3C i).sigmaFinite
simp_rw [h₁ s hs, pi_pi_aux μ s fun i => h4C i _ (hs i)]
#align measure_theory.measure.pi_eq_generate_from MeasureTheory.Measure.pi_eq_generateFrom
variable [∀ i, SigmaFinite (μ i)]
/-- A measure on a finite product space equals the product measure if they are equal on
rectangles. -/
theorem pi_eq {μ' : Measure (∀ i, α i)}
(h : ∀ s : ∀ i, Set (α i), (∀ i, MeasurableSet (s i)) → μ' (pi univ s) = ∏ i, μ i (s i)) :
Measure.pi μ = μ' :=
pi_eq_generateFrom (fun _ => generateFrom_measurableSet) (fun _ => isPiSystem_measurableSet)
(fun i => (μ i).toFiniteSpanningSetsIn) h
#align measure_theory.measure.pi_eq MeasureTheory.Measure.pi_eq
variable (μ)
theorem pi'_eq_pi [Encodable ι] : pi' μ = Measure.pi μ :=
Eq.symm <| pi_eq fun s _ => pi'_pi μ s
#align measure_theory.measure.pi'_eq_pi MeasureTheory.Measure.pi'_eq_pi
@[simp]
| Mathlib/MeasureTheory/Constructions/Pi.lean | 397 | 399 | theorem pi_pi (s : ∀ i, Set (α i)) : Measure.pi μ (pi univ s) = ∏ i, μ i (s i) := by |
haveI : Encodable ι := Fintype.toEncodable ι
rw [← pi'_eq_pi, pi'_pi]
|
/-
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.GroupTheory.Coprod.Basic
import Mathlib.GroupTheory.Complement
/-!
## HNN Extensions of Groups
This file defines the HNN extension of a group `G`, `HNNExtension G A B φ`. Given a group `G`,
subgroups `A` and `B` and an isomorphism `φ` of `A` and `B`, we adjoin a letter `t` to `G`, such
that for any `a ∈ A`, the conjugate of `of a` by `t` is `of (φ a)`, where `of` is the canonical map
from `G` into the `HNNExtension`. This construction is named after Graham Higman, Bernhard Neumann
and Hanna Neumann.
## Main definitions
- `HNNExtension G A B φ` : The HNN Extension of a group `G`, where `A` and `B` are subgroups and `φ`
is an isomorphism between `A` and `B`.
- `HNNExtension.of` : The canonical embedding of `G` into `HNNExtension G A B φ`.
- `HNNExtension.t` : The stable letter of the HNN extension.
- `HNNExtension.lift` : Define a function `HNNExtension G A B φ →* H`, by defining it on `G` and `t`
- `HNNExtension.of_injective` : The canonical embedding `G →* HNNExtension G A B φ` is injective.
- `HNNExtension.ReducedWord.toList_eq_nil_of_mem_of_range` : Britton's Lemma. If an element of
`G` is represented by a reduced word, then this reduced word does not contain `t`.
-/
open Monoid Coprod Multiplicative Subgroup Function
/-- The relation we quotient the coproduct by to form an `HNNExtension`. -/
def HNNExtension.con (G : Type*) [Group G] (A B : Subgroup G) (φ : A ≃* B) :
Con (G ∗ Multiplicative ℤ) :=
conGen (fun x y => ∃ (a : A),
x = inr (ofAdd 1) * inl (a : G) ∧
y = inl (φ a : G) * inr (ofAdd 1))
/-- The HNN Extension of a group `G`, `HNNExtension G A B φ`. Given a group `G`, subgroups `A` and
`B` and an isomorphism `φ` of `A` and `B`, we adjoin a letter `t` to `G`, such that for
any `a ∈ A`, the conjugate of `of a` by `t` is `of (φ a)`, where `of` is the canonical
map from `G` into the `HNNExtension`. -/
def HNNExtension (G : Type*) [Group G] (A B : Subgroup G) (φ : A ≃* B) : Type _ :=
(HNNExtension.con G A B φ).Quotient
variable {G : Type*} [Group G] {A B : Subgroup G} {φ : A ≃* B} {H : Type*}
[Group H] {M : Type*} [Monoid M]
instance : Group (HNNExtension G A B φ) := by
delta HNNExtension; infer_instance
namespace HNNExtension
/-- The canonical embedding `G →* HNNExtension G A B φ` -/
def of : G →* HNNExtension G A B φ :=
(HNNExtension.con G A B φ).mk'.comp inl
/-- The stable letter of the `HNNExtension` -/
def t : HNNExtension G A B φ :=
(HNNExtension.con G A B φ).mk'.comp inr (ofAdd 1)
theorem t_mul_of (a : A) :
t * (of (a : G) : HNNExtension G A B φ) = of (φ a : G) * t :=
(Con.eq _).2 <| ConGen.Rel.of _ _ <| ⟨a, by simp⟩
theorem of_mul_t (b : B) :
(of (b : G) : HNNExtension G A B φ) * t = t * of (φ.symm b : G) := by
rw [t_mul_of]; simp
theorem equiv_eq_conj (a : A) :
(of (φ a : G) : HNNExtension G A B φ) = t * of (a : G) * t⁻¹ := by
rw [t_mul_of]; simp
theorem equiv_symm_eq_conj (b : B) :
(of (φ.symm b : G) : HNNExtension G A B φ) = t⁻¹ * of (b : G) * t := by
rw [mul_assoc, of_mul_t]; simp
| Mathlib/GroupTheory/HNNExtension.lean | 81 | 83 | theorem inv_t_mul_of (b : B) :
t⁻¹ * (of (b : G) : HNNExtension G A B φ) = of (φ.symm b : G) * t⁻¹ := by |
rw [equiv_symm_eq_conj]; simp
|
/-
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.Sub
import Mathlib.MeasureTheory.Decomposition.SignedHahn
import Mathlib.MeasureTheory.Function.AEEqOfIntegral
#align_import measure_theory.decomposition.lebesgue from "leanprover-community/mathlib"@"b2ff9a3d7a15fd5b0f060b135421d6a89a999c2f"
/-!
# Lebesgue decomposition
This file proves the Lebesgue decomposition theorem. The Lebesgue decomposition theorem states that,
given two σ-finite measures `μ` and `ν`, there exists a σ-finite measure `ξ` and a measurable
function `f` such that `μ = ξ + fν` and `ξ` is mutually singular with respect to `ν`.
The Lebesgue decomposition provides the Radon-Nikodym theorem readily.
## Main definitions
* `MeasureTheory.Measure.HaveLebesgueDecomposition` : A pair of measures `μ` and `ν` is said
to `HaveLebesgueDecomposition` if there exist a measure `ξ` and a measurable function `f`,
such that `ξ` is mutually singular with respect to `ν` and `μ = ξ + ν.withDensity f`
* `MeasureTheory.Measure.singularPart` : If a pair of measures `HaveLebesgueDecomposition`,
then `singularPart` chooses the measure from `HaveLebesgueDecomposition`, otherwise it
returns the zero measure.
* `MeasureTheory.Measure.rnDeriv`: If a pair of measures
`HaveLebesgueDecomposition`, then `rnDeriv` chooses the measurable function from
`HaveLebesgueDecomposition`, otherwise it returns the zero function.
## Main results
* `MeasureTheory.Measure.haveLebesgueDecomposition_of_sigmaFinite` :
the Lebesgue decomposition theorem.
* `MeasureTheory.Measure.eq_singularPart` : Given measures `μ` and `ν`, if `s` is a measure
mutually singular to `ν` and `f` is a measurable function such that `μ = s + fν`, then
`s = μ.singularPart ν`.
* `MeasureTheory.Measure.eq_rnDeriv` : Given measures `μ` and `ν`, if `s` is a
measure mutually singular to `ν` and `f` is a measurable function such that `μ = s + fν`,
then `f = μ.rnDeriv ν`.
## Tags
Lebesgue decomposition theorem
-/
open scoped MeasureTheory NNReal ENNReal
open Set
namespace MeasureTheory
namespace Measure
variable {α β : Type*} {m : MeasurableSpace α} {μ ν : Measure α}
/-- A pair of measures `μ` and `ν` is said to `HaveLebesgueDecomposition` if there exists a
measure `ξ` and a measurable function `f`, such that `ξ` is mutually singular with respect to
`ν` and `μ = ξ + ν.withDensity f`. -/
class HaveLebesgueDecomposition (μ ν : Measure α) : Prop where
lebesgue_decomposition :
∃ p : Measure α × (α → ℝ≥0∞), Measurable p.2 ∧ p.1 ⟂ₘ ν ∧ μ = p.1 + ν.withDensity p.2
#align measure_theory.measure.have_lebesgue_decomposition MeasureTheory.Measure.HaveLebesgueDecomposition
#align measure_theory.measure.have_lebesgue_decomposition.lebesgue_decomposition MeasureTheory.Measure.HaveLebesgueDecomposition.lebesgue_decomposition
open Classical in
/-- If a pair of measures `HaveLebesgueDecomposition`, then `singularPart` chooses the
measure from `HaveLebesgueDecomposition`, otherwise it returns the zero measure. For sigma-finite
measures, `μ = μ.singularPart ν + ν.withDensity (μ.rnDeriv ν)`. -/
noncomputable irreducible_def singularPart (μ ν : Measure α) : Measure α :=
if h : HaveLebesgueDecomposition μ ν then (Classical.choose h.lebesgue_decomposition).1 else 0
#align measure_theory.measure.singular_part MeasureTheory.Measure.singularPart
open Classical in
/-- If a pair of measures `HaveLebesgueDecomposition`, then `rnDeriv` chooses the
measurable function from `HaveLebesgueDecomposition`, otherwise it returns the zero function.
For sigma-finite measures, `μ = μ.singularPart ν + ν.withDensity (μ.rnDeriv ν)`. -/
noncomputable irreducible_def rnDeriv (μ ν : Measure α) : α → ℝ≥0∞ :=
if h : HaveLebesgueDecomposition μ ν then (Classical.choose h.lebesgue_decomposition).2 else 0
#align measure_theory.measure.rn_deriv MeasureTheory.Measure.rnDeriv
section ByDefinition
theorem haveLebesgueDecomposition_spec (μ ν : Measure α) [h : HaveLebesgueDecomposition μ ν] :
Measurable (μ.rnDeriv ν) ∧
μ.singularPart ν ⟂ₘ ν ∧ μ = μ.singularPart ν + ν.withDensity (μ.rnDeriv ν) := by
rw [singularPart, rnDeriv, dif_pos h, dif_pos h]
exact Classical.choose_spec h.lebesgue_decomposition
#align measure_theory.measure.have_lebesgue_decomposition_spec MeasureTheory.Measure.haveLebesgueDecomposition_spec
lemma rnDeriv_of_not_haveLebesgueDecomposition (h : ¬ HaveLebesgueDecomposition μ ν) :
μ.rnDeriv ν = 0 := by
rw [rnDeriv, dif_neg h]
lemma singularPart_of_not_haveLebesgueDecomposition (h : ¬ HaveLebesgueDecomposition μ ν) :
μ.singularPart ν = 0 := by
rw [singularPart, dif_neg h]
@[measurability]
theorem measurable_rnDeriv (μ ν : Measure α) : Measurable <| μ.rnDeriv ν := by
by_cases h : HaveLebesgueDecomposition μ ν
· exact (haveLebesgueDecomposition_spec μ ν).1
· rw [rnDeriv_of_not_haveLebesgueDecomposition h]
exact measurable_zero
#align measure_theory.measure.measurable_rn_deriv MeasureTheory.Measure.measurable_rnDeriv
theorem mutuallySingular_singularPart (μ ν : Measure α) : μ.singularPart ν ⟂ₘ ν := by
by_cases h : HaveLebesgueDecomposition μ ν
· exact (haveLebesgueDecomposition_spec μ ν).2.1
· rw [singularPart_of_not_haveLebesgueDecomposition h]
exact MutuallySingular.zero_left
#align measure_theory.measure.mutually_singular_singular_part MeasureTheory.Measure.mutuallySingular_singularPart
theorem haveLebesgueDecomposition_add (μ ν : Measure α) [HaveLebesgueDecomposition μ ν] :
μ = μ.singularPart ν + ν.withDensity (μ.rnDeriv ν) :=
(haveLebesgueDecomposition_spec μ ν).2.2
#align measure_theory.measure.have_lebesgue_decomposition_add MeasureTheory.Measure.haveLebesgueDecomposition_add
lemma singularPart_add_rnDeriv (μ ν : Measure α) [HaveLebesgueDecomposition μ ν] :
μ.singularPart ν + ν.withDensity (μ.rnDeriv ν) = μ := (haveLebesgueDecomposition_add μ ν).symm
lemma rnDeriv_add_singularPart (μ ν : Measure α) [HaveLebesgueDecomposition μ ν] :
ν.withDensity (μ.rnDeriv ν) + μ.singularPart ν = μ := by rw [add_comm, singularPart_add_rnDeriv]
end ByDefinition
section HaveLebesgueDecomposition
instance instHaveLebesgueDecompositionZeroLeft : HaveLebesgueDecomposition 0 ν where
lebesgue_decomposition := ⟨⟨0, 0⟩, measurable_zero, MutuallySingular.zero_left, by simp⟩
instance instHaveLebesgueDecompositionZeroRight : HaveLebesgueDecomposition μ 0 where
lebesgue_decomposition := ⟨⟨μ, 0⟩, measurable_zero, MutuallySingular.zero_right, by simp⟩
instance instHaveLebesgueDecompositionSelf : HaveLebesgueDecomposition μ μ where
lebesgue_decomposition := ⟨⟨0, 1⟩, measurable_const, MutuallySingular.zero_left, by simp⟩
instance haveLebesgueDecompositionSMul' (μ ν : Measure α) [HaveLebesgueDecomposition μ ν]
(r : ℝ≥0∞) : (r • μ).HaveLebesgueDecomposition ν where
lebesgue_decomposition := by
obtain ⟨hmeas, hsing, hadd⟩ := haveLebesgueDecomposition_spec μ ν
refine ⟨⟨r • μ.singularPart ν, r • μ.rnDeriv ν⟩, hmeas.const_smul _, hsing.smul _, ?_⟩
simp only [ENNReal.smul_def]
rw [withDensity_smul _ hmeas, ← smul_add, ← hadd]
instance haveLebesgueDecompositionSMul (μ ν : Measure α) [HaveLebesgueDecomposition μ ν]
(r : ℝ≥0) : (r • μ).HaveLebesgueDecomposition ν := by
rw [ENNReal.smul_def]; infer_instance
#align measure_theory.measure.have_lebesgue_decomposition_smul MeasureTheory.Measure.haveLebesgueDecompositionSMul
instance haveLebesgueDecompositionSMulRight (μ ν : Measure α) [HaveLebesgueDecomposition μ ν]
(r : ℝ≥0) :
μ.HaveLebesgueDecomposition (r • ν) where
lebesgue_decomposition := by
obtain ⟨hmeas, hsing, hadd⟩ := haveLebesgueDecomposition_spec μ ν
by_cases hr : r = 0
· exact ⟨⟨μ, 0⟩, measurable_const, by simp [hr], by simp⟩
refine ⟨⟨μ.singularPart ν, r⁻¹ • μ.rnDeriv ν⟩, hmeas.const_smul _,
hsing.mono_ac AbsolutelyContinuous.rfl smul_absolutelyContinuous, ?_⟩
have : r⁻¹ • rnDeriv μ ν = ((r⁻¹ : ℝ≥0) : ℝ≥0∞) • rnDeriv μ ν := by simp [ENNReal.smul_def]
rw [this, withDensity_smul _ hmeas, ENNReal.smul_def r, withDensity_smul_measure,
← smul_assoc, smul_eq_mul, ENNReal.coe_inv hr, ENNReal.inv_mul_cancel, one_smul]
· exact hadd
· simp [hr]
· exact ENNReal.coe_ne_top
theorem haveLebesgueDecomposition_withDensity (μ : Measure α) {f : α → ℝ≥0∞} (hf : Measurable f) :
(μ.withDensity f).HaveLebesgueDecomposition μ := ⟨⟨⟨0, f⟩, hf, .zero_left, (zero_add _).symm⟩⟩
instance haveLebesgueDecompositionRnDeriv (μ ν : Measure α) :
HaveLebesgueDecomposition (ν.withDensity (μ.rnDeriv ν)) ν :=
haveLebesgueDecomposition_withDensity ν (measurable_rnDeriv _ _)
instance instHaveLebesgueDecompositionSingularPart :
HaveLebesgueDecomposition (μ.singularPart ν) ν :=
⟨⟨μ.singularPart ν, 0⟩, measurable_zero, mutuallySingular_singularPart μ ν, by simp⟩
end HaveLebesgueDecomposition
theorem singularPart_le (μ ν : Measure α) : μ.singularPart ν ≤ μ := by
by_cases hl : HaveLebesgueDecomposition μ ν
· conv_rhs => rw [haveLebesgueDecomposition_add μ ν]
exact Measure.le_add_right le_rfl
· rw [singularPart, dif_neg hl]
exact Measure.zero_le μ
#align measure_theory.measure.singular_part_le MeasureTheory.Measure.singularPart_le
theorem withDensity_rnDeriv_le (μ ν : Measure α) : ν.withDensity (μ.rnDeriv ν) ≤ μ := by
by_cases hl : HaveLebesgueDecomposition μ ν
· conv_rhs => rw [haveLebesgueDecomposition_add μ ν]
exact Measure.le_add_left le_rfl
· rw [rnDeriv, dif_neg hl, withDensity_zero]
exact Measure.zero_le μ
#align measure_theory.measure.with_density_rn_deriv_le MeasureTheory.Measure.withDensity_rnDeriv_le
lemma _root_.AEMeasurable.singularPart {β : Type*} {_ : MeasurableSpace β} {f : α → β}
(hf : AEMeasurable f μ) (ν : Measure α) :
AEMeasurable f (μ.singularPart ν) :=
AEMeasurable.mono_measure hf (Measure.singularPart_le _ _)
lemma _root_.AEMeasurable.withDensity_rnDeriv {β : Type*} {_ : MeasurableSpace β} {f : α → β}
(hf : AEMeasurable f μ) (ν : Measure α) :
AEMeasurable f (ν.withDensity (μ.rnDeriv ν)) :=
AEMeasurable.mono_measure hf (Measure.withDensity_rnDeriv_le _ _)
lemma MutuallySingular.singularPart (h : μ ⟂ₘ ν) (ν' : Measure α) :
μ.singularPart ν' ⟂ₘ ν :=
h.mono (singularPart_le μ ν') le_rfl
lemma absolutelyContinuous_withDensity_rnDeriv [HaveLebesgueDecomposition ν μ] (hμν : μ ≪ ν) :
μ ≪ μ.withDensity (ν.rnDeriv μ) := by
rw [haveLebesgueDecomposition_add ν μ] at hμν
refine AbsolutelyContinuous.mk (fun s _ hνs ↦ ?_)
obtain ⟨t, _, ht1, ht2⟩ := mutuallySingular_singularPart ν μ
rw [← inter_union_compl s]
refine le_antisymm ((measure_union_le (s ∩ t) (s ∩ tᶜ)).trans ?_) (zero_le _)
simp only [nonpos_iff_eq_zero, add_eq_zero]
constructor
· refine hμν ?_
simp only [coe_add, Pi.add_apply, add_eq_zero]
constructor
· exact measure_mono_null Set.inter_subset_right ht1
· exact measure_mono_null Set.inter_subset_left hνs
· exact measure_mono_null Set.inter_subset_right ht2
lemma singularPart_eq_zero_of_ac (h : μ ≪ ν) : μ.singularPart ν = 0 := by
rw [← MutuallySingular.self_iff]
exact MutuallySingular.mono_ac (mutuallySingular_singularPart _ _)
AbsolutelyContinuous.rfl ((absolutelyContinuous_of_le (singularPart_le _ _)).trans h)
@[simp]
theorem singularPart_zero (ν : Measure α) : (0 : Measure α).singularPart ν = 0 :=
singularPart_eq_zero_of_ac (AbsolutelyContinuous.zero _)
#align measure_theory.measure.singular_part_zero MeasureTheory.Measure.singularPart_zero
@[simp]
lemma singularPart_zero_right (μ : Measure α) : μ.singularPart 0 = μ := by
conv_rhs => rw [haveLebesgueDecomposition_add μ 0]
simp
lemma singularPart_eq_zero (μ ν : Measure α) [μ.HaveLebesgueDecomposition ν] :
μ.singularPart ν = 0 ↔ μ ≪ ν := by
have h_dec := haveLebesgueDecomposition_add μ ν
refine ⟨fun h ↦ ?_, singularPart_eq_zero_of_ac⟩
rw [h, zero_add] at h_dec
rw [h_dec]
exact withDensity_absolutelyContinuous ν _
@[simp]
lemma withDensity_rnDeriv_eq_zero (μ ν : Measure α) [μ.HaveLebesgueDecomposition ν] :
ν.withDensity (μ.rnDeriv ν) = 0 ↔ μ ⟂ₘ ν := by
have h_dec := haveLebesgueDecomposition_add μ ν
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· rw [h, add_zero] at h_dec
rw [h_dec]
exact mutuallySingular_singularPart μ ν
· rw [← MutuallySingular.self_iff]
rw [h_dec, MutuallySingular.add_left_iff] at h
refine MutuallySingular.mono_ac h.2 AbsolutelyContinuous.rfl ?_
exact withDensity_absolutelyContinuous _ _
@[simp]
lemma rnDeriv_eq_zero (μ ν : Measure α) [μ.HaveLebesgueDecomposition ν] :
μ.rnDeriv ν =ᵐ[ν] 0 ↔ μ ⟂ₘ ν := by
rw [← withDensity_rnDeriv_eq_zero, withDensity_eq_zero_iff (measurable_rnDeriv _ _).aemeasurable]
lemma rnDeriv_zero (ν : Measure α) : (0 : Measure α).rnDeriv ν =ᵐ[ν] 0 := by
rw [rnDeriv_eq_zero]
exact MutuallySingular.zero_left
lemma MutuallySingular.rnDeriv_ae_eq_zero (hμν : μ ⟂ₘ ν) :
μ.rnDeriv ν =ᵐ[ν] 0 := by
by_cases h : μ.HaveLebesgueDecomposition ν
· rw [rnDeriv_eq_zero]
exact hμν
· rw [rnDeriv_of_not_haveLebesgueDecomposition h]
@[simp]
theorem singularPart_withDensity (ν : Measure α) (f : α → ℝ≥0∞) :
(ν.withDensity f).singularPart ν = 0 :=
singularPart_eq_zero_of_ac (withDensity_absolutelyContinuous _ _)
#align measure_theory.measure.singular_part_with_density MeasureTheory.Measure.singularPart_withDensity
lemma rnDeriv_singularPart (μ ν : Measure α) :
(μ.singularPart ν).rnDeriv ν =ᵐ[ν] 0 := by
rw [rnDeriv_eq_zero]
exact mutuallySingular_singularPart μ ν
@[simp]
lemma singularPart_self (μ : Measure α) : μ.singularPart μ = 0 :=
singularPart_eq_zero_of_ac Measure.AbsolutelyContinuous.rfl
lemma rnDeriv_self (μ : Measure α) [SigmaFinite μ] : μ.rnDeriv μ =ᵐ[μ] fun _ ↦ 1 := by
have h := rnDeriv_add_singularPart μ μ
rw [singularPart_self, add_zero] at h
have h_one : μ = μ.withDensity 1 := by simp
conv_rhs at h => rw [h_one]
rwa [withDensity_eq_iff_of_sigmaFinite (measurable_rnDeriv _ _).aemeasurable] at h
exact aemeasurable_const
lemma singularPart_eq_self [μ.HaveLebesgueDecomposition ν] : μ.singularPart ν = μ ↔ μ ⟂ₘ ν := by
have h_dec := haveLebesgueDecomposition_add μ ν
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· rw [← h]
exact mutuallySingular_singularPart _ _
· conv_rhs => rw [h_dec]
rw [(withDensity_rnDeriv_eq_zero _ _).mpr h, add_zero]
@[simp]
lemma singularPart_singularPart (μ ν : Measure α) :
(μ.singularPart ν).singularPart ν = μ.singularPart ν := by
rw [Measure.singularPart_eq_self]
exact Measure.mutuallySingular_singularPart _ _
instance singularPart.instIsFiniteMeasure [IsFiniteMeasure μ] :
IsFiniteMeasure (μ.singularPart ν) :=
isFiniteMeasure_of_le μ <| singularPart_le μ ν
#align measure_theory.measure.singular_part.measure_theory.is_finite_measure MeasureTheory.Measure.singularPart.instIsFiniteMeasure
instance singularPart.instSigmaFinite [SigmaFinite μ] : SigmaFinite (μ.singularPart ν) :=
sigmaFinite_of_le μ <| singularPart_le μ ν
#align measure_theory.measure.singular_part.measure_theory.sigma_finite MeasureTheory.Measure.singularPart.instSigmaFinite
instance singularPart.instIsLocallyFiniteMeasure [TopologicalSpace α] [IsLocallyFiniteMeasure μ] :
IsLocallyFiniteMeasure (μ.singularPart ν) :=
isLocallyFiniteMeasure_of_le <| singularPart_le μ ν
#align measure_theory.measure.singular_part.measure_theory.is_locally_finite_measure MeasureTheory.Measure.singularPart.instIsLocallyFiniteMeasure
instance withDensity.instIsFiniteMeasure [IsFiniteMeasure μ] :
IsFiniteMeasure (ν.withDensity <| μ.rnDeriv ν) :=
isFiniteMeasure_of_le μ <| withDensity_rnDeriv_le μ ν
#align measure_theory.measure.with_density.measure_theory.is_finite_measure MeasureTheory.Measure.withDensity.instIsFiniteMeasure
instance withDensity.instSigmaFinite [SigmaFinite μ] :
SigmaFinite (ν.withDensity <| μ.rnDeriv ν) :=
sigmaFinite_of_le μ <| withDensity_rnDeriv_le μ ν
#align measure_theory.measure.with_density.measure_theory.sigma_finite MeasureTheory.Measure.withDensity.instSigmaFinite
instance withDensity.instIsLocallyFiniteMeasure [TopologicalSpace α] [IsLocallyFiniteMeasure μ] :
IsLocallyFiniteMeasure (ν.withDensity <| μ.rnDeriv ν) :=
isLocallyFiniteMeasure_of_le <| withDensity_rnDeriv_le μ ν
#align measure_theory.measure.with_density.measure_theory.is_locally_finite_measure MeasureTheory.Measure.withDensity.instIsLocallyFiniteMeasure
section RNDerivFinite
| Mathlib/MeasureTheory/Decomposition/Lebesgue.lean | 348 | 358 | theorem lintegral_rnDeriv_lt_top_of_measure_ne_top (ν : Measure α) {s : Set α} (hs : μ s ≠ ∞) :
∫⁻ x in s, μ.rnDeriv ν x ∂ν < ∞ := by |
by_cases hl : HaveLebesgueDecomposition μ ν
· suffices (∫⁻ x in toMeasurable μ s, μ.rnDeriv ν x ∂ν) < ∞ from
lt_of_le_of_lt (lintegral_mono_set (subset_toMeasurable _ _)) this
rw [← withDensity_apply _ (measurableSet_toMeasurable _ _)]
calc
_ ≤ (singularPart μ ν) (toMeasurable μ s) + _ := le_add_self
_ = μ s := by rw [← Measure.add_apply, ← haveLebesgueDecomposition_add, measure_toMeasurable]
_ < ⊤ := hs.lt_top
· simp only [Measure.rnDeriv, dif_neg hl, Pi.zero_apply, lintegral_zero, ENNReal.zero_lt_top]
|
/-
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.MetricSpace.ProperSpace
import Mathlib.Topology.MetricSpace.Cauchy
/-!
## Boundedness in (pseudo)-metric spaces
This file contains one definition, and various results on boundedness in pseudo-metric spaces.
* `Metric.diam s` : The `iSup` of the distances of members of `s`.
Defined in terms of `EMetric.diam`, for better handling of the case when it should be infinite.
* `isBounded_iff_subset_closedBall`: a non-empty set is bounded if and only if
it is is included in some closed ball
* describing the cobounded filter, relating to the cocompact filter
* `IsCompact.isBounded`: compact sets are bounded
* `TotallyBounded.isBounded`: totally bounded sets are bounded
* `isCompact_iff_isClosed_bounded`, the **Heine–Borel theorem**:
in a proper space, a set is compact if and only if it is closed and bounded.
* `cobounded_eq_cocompact`: in a proper space, cobounded and compact sets are the same
diameter of a subset, and its relation to boundedness
## Tags
metric, pseudo_metric, bounded, diameter, Heine-Borel theorem
-/
open Set Filter Bornology
open scoped ENNReal Uniformity Topology Pointwise
universe u v w
variable {α : Type u} {β : Type v} {X ι : Type*}
variable [PseudoMetricSpace α]
namespace Metric
#align metric.bounded Bornology.IsBounded
section Bounded
variable {x : α} {s t : Set α} {r : ℝ}
#noalign metric.bounded_iff_is_bounded
#align metric.bounded_empty Bornology.isBounded_empty
#align metric.bounded_iff_mem_bounded Bornology.isBounded_iff_forall_mem
#align metric.bounded.mono Bornology.IsBounded.subset
/-- Closed balls are bounded -/
theorem isBounded_closedBall : IsBounded (closedBall x r) :=
isBounded_iff.2 ⟨r + r, fun y hy z hz =>
calc dist y z ≤ dist y x + dist z x := dist_triangle_right _ _ _
_ ≤ r + r := add_le_add hy hz⟩
#align metric.bounded_closed_ball Metric.isBounded_closedBall
/-- Open balls are bounded -/
theorem isBounded_ball : IsBounded (ball x r) :=
isBounded_closedBall.subset ball_subset_closedBall
#align metric.bounded_ball Metric.isBounded_ball
/-- Spheres are bounded -/
theorem isBounded_sphere : IsBounded (sphere x r) :=
isBounded_closedBall.subset sphere_subset_closedBall
#align metric.bounded_sphere Metric.isBounded_sphere
/-- Given a point, a bounded subset is included in some ball around this point -/
theorem isBounded_iff_subset_closedBall (c : α) : IsBounded s ↔ ∃ r, s ⊆ closedBall c r :=
⟨fun h ↦ (isBounded_iff.1 (h.insert c)).imp fun _r hr _x hx ↦ hr (.inr hx) (mem_insert _ _),
fun ⟨_r, hr⟩ ↦ isBounded_closedBall.subset hr⟩
#align metric.bounded_iff_subset_ball Metric.isBounded_iff_subset_closedBall
theorem _root_.Bornology.IsBounded.subset_closedBall (h : IsBounded s) (c : α) :
∃ r, s ⊆ closedBall c r :=
(isBounded_iff_subset_closedBall c).1 h
#align metric.bounded.subset_ball Bornology.IsBounded.subset_closedBall
theorem _root_.Bornology.IsBounded.subset_ball_lt (h : IsBounded s) (a : ℝ) (c : α) :
∃ r, a < r ∧ s ⊆ ball c r :=
let ⟨r, hr⟩ := h.subset_closedBall c
⟨max r a + 1, (le_max_right _ _).trans_lt (lt_add_one _), hr.trans <| closedBall_subset_ball <|
(le_max_left _ _).trans_lt (lt_add_one _)⟩
theorem _root_.Bornology.IsBounded.subset_ball (h : IsBounded s) (c : α) : ∃ r, s ⊆ ball c r :=
(h.subset_ball_lt 0 c).imp fun _ ↦ And.right
theorem isBounded_iff_subset_ball (c : α) : IsBounded s ↔ ∃ r, s ⊆ ball c r :=
⟨(IsBounded.subset_ball · c), fun ⟨_r, hr⟩ ↦ isBounded_ball.subset hr⟩
theorem _root_.Bornology.IsBounded.subset_closedBall_lt (h : IsBounded s) (a : ℝ) (c : α) :
∃ r, a < r ∧ s ⊆ closedBall c r :=
let ⟨r, har, hr⟩ := h.subset_ball_lt a c
⟨r, har, hr.trans ball_subset_closedBall⟩
#align metric.bounded.subset_ball_lt Bornology.IsBounded.subset_closedBall_lt
theorem isBounded_closure_of_isBounded (h : IsBounded s) : IsBounded (closure s) :=
let ⟨C, h⟩ := isBounded_iff.1 h
isBounded_iff.2 ⟨C, fun _a ha _b hb => isClosed_Iic.closure_subset <|
map_mem_closure₂ continuous_dist ha hb h⟩
#align metric.bounded_closure_of_bounded Metric.isBounded_closure_of_isBounded
protected theorem _root_.Bornology.IsBounded.closure (h : IsBounded s) : IsBounded (closure s) :=
isBounded_closure_of_isBounded h
#align metric.bounded.closure Bornology.IsBounded.closure
@[simp]
theorem isBounded_closure_iff : IsBounded (closure s) ↔ IsBounded s :=
⟨fun h => h.subset subset_closure, fun h => h.closure⟩
#align metric.bounded_closure_iff Metric.isBounded_closure_iff
#align metric.bounded_union Bornology.isBounded_union
#align metric.bounded.union Bornology.IsBounded.union
#align metric.bounded_bUnion Bornology.isBounded_biUnion
#align metric.bounded.prod Bornology.IsBounded.prod
theorem hasBasis_cobounded_compl_closedBall (c : α) :
(cobounded α).HasBasis (fun _ ↦ True) (fun r ↦ (closedBall c r)ᶜ) :=
⟨compl_surjective.forall.2 fun _ ↦ (isBounded_iff_subset_closedBall c).trans <| by simp⟩
theorem hasBasis_cobounded_compl_ball (c : α) :
(cobounded α).HasBasis (fun _ ↦ True) (fun r ↦ (ball c r)ᶜ) :=
⟨compl_surjective.forall.2 fun _ ↦ (isBounded_iff_subset_ball c).trans <| by simp⟩
@[simp]
theorem comap_dist_right_atTop (c : α) : comap (dist · c) atTop = cobounded α :=
(atTop_basis.comap _).eq_of_same_basis <| by
simpa only [compl_def, mem_ball, not_lt] using hasBasis_cobounded_compl_ball c
@[simp]
theorem comap_dist_left_atTop (c : α) : comap (dist c) atTop = cobounded α := by
simpa only [dist_comm _ c] using comap_dist_right_atTop c
@[simp]
theorem tendsto_dist_right_atTop_iff (c : α) {f : β → α} {l : Filter β} :
Tendsto (fun x ↦ dist (f x) c) l atTop ↔ Tendsto f l (cobounded α) := by
rw [← comap_dist_right_atTop c, tendsto_comap_iff, Function.comp_def]
@[simp]
theorem tendsto_dist_left_atTop_iff (c : α) {f : β → α} {l : Filter β} :
Tendsto (fun x ↦ dist c (f x)) l atTop ↔ Tendsto f l (cobounded α) := by
simp only [dist_comm c, tendsto_dist_right_atTop_iff]
theorem tendsto_dist_right_cobounded_atTop (c : α) : Tendsto (dist · c) (cobounded α) atTop :=
tendsto_iff_comap.2 (comap_dist_right_atTop c).ge
theorem tendsto_dist_left_cobounded_atTop (c : α) : Tendsto (dist c) (cobounded α) atTop :=
tendsto_iff_comap.2 (comap_dist_left_atTop c).ge
/-- A totally bounded set is bounded -/
theorem _root_.TotallyBounded.isBounded {s : Set α} (h : TotallyBounded s) : IsBounded s :=
-- We cover the totally bounded set by finitely many balls of radius 1,
-- and then argue that a finite union of bounded sets is bounded
let ⟨_t, fint, subs⟩ := (totallyBounded_iff.mp h) 1 zero_lt_one
((isBounded_biUnion fint).2 fun _ _ => isBounded_ball).subset subs
#align totally_bounded.bounded TotallyBounded.isBounded
/-- A compact set is bounded -/
theorem _root_.IsCompact.isBounded {s : Set α} (h : IsCompact s) : IsBounded s :=
-- A compact set is totally bounded, thus bounded
h.totallyBounded.isBounded
#align is_compact.bounded IsCompact.isBounded
#align metric.bounded_of_finite Set.Finite.isBounded
#align set.finite.bounded Set.Finite.isBounded
#align metric.bounded_singleton Bornology.isBounded_singleton
theorem cobounded_le_cocompact : cobounded α ≤ cocompact α :=
hasBasis_cocompact.ge_iff.2 fun _s hs ↦ hs.isBounded
#align comap_dist_right_at_top_le_cocompact Metric.cobounded_le_cocompactₓ
#align comap_dist_left_at_top_le_cocompact Metric.cobounded_le_cocompactₓ
| Mathlib/Topology/MetricSpace/Bounded.lean | 175 | 180 | theorem isCobounded_iff_closedBall_compl_subset {s : Set α} (c : α) :
IsCobounded s ↔ ∃ (r : ℝ), (Metric.closedBall c r)ᶜ ⊆ s := by |
rw [← isBounded_compl_iff, isBounded_iff_subset_closedBall c]
apply exists_congr
intro r
rw [compl_subset_comm]
|
/-
Copyright (c) 2018 Guy Leroy. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sangwoo Jo (aka Jason), Guy Leroy, Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Algebra.Group.Commute.Units
import Mathlib.Algebra.Group.Int
import Mathlib.Algebra.GroupWithZero.Semiconj
import Mathlib.Data.Nat.GCD.Basic
import Mathlib.Order.Bounds.Basic
#align_import data.int.gcd from "leanprover-community/mathlib"@"47a1a73351de8dd6c8d3d32b569c8e434b03ca47"
/-!
# Extended GCD and divisibility over ℤ
## Main definitions
* Given `x y : ℕ`, `xgcd x y` computes the pair of integers `(a, b)` such that
`gcd x y = x * a + y * b`. `gcdA x y` and `gcdB x y` are defined to be `a` and `b`,
respectively.
## Main statements
* `gcd_eq_gcd_ab`: Bézout's lemma, given `x y : ℕ`, `gcd x y = x * gcdA x y + y * gcdB x y`.
## Tags
Bézout's lemma, Bezout's lemma
-/
/-! ### Extended Euclidean algorithm -/
namespace Nat
/-- Helper function for the extended GCD algorithm (`Nat.xgcd`). -/
def xgcdAux : ℕ → ℤ → ℤ → ℕ → ℤ → ℤ → ℕ × ℤ × ℤ
| 0, _, _, r', s', t' => (r', s', t')
| succ k, s, t, r', s', t' =>
let q := r' / succ k
xgcdAux (r' % succ k) (s' - q * s) (t' - q * t) (succ k) s t
termination_by k => k
decreasing_by exact mod_lt _ <| (succ_pos _).gt
#align nat.xgcd_aux Nat.xgcdAux
@[simp]
theorem xgcd_zero_left {s t r' s' t'} : xgcdAux 0 s t r' s' t' = (r', s', t') := by simp [xgcdAux]
#align nat.xgcd_zero_left Nat.xgcd_zero_left
theorem xgcdAux_rec {r s t r' s' t'} (h : 0 < r) :
xgcdAux r s t r' s' t' = xgcdAux (r' % r) (s' - r' / r * s) (t' - r' / r * t) r s t := by
obtain ⟨r, rfl⟩ := Nat.exists_eq_succ_of_ne_zero h.ne'
simp [xgcdAux]
#align nat.xgcd_aux_rec Nat.xgcdAux_rec
/-- Use the extended GCD algorithm to generate the `a` and `b` values
satisfying `gcd x y = x * a + y * b`. -/
def xgcd (x y : ℕ) : ℤ × ℤ :=
(xgcdAux x 1 0 y 0 1).2
#align nat.xgcd Nat.xgcd
/-- The extended GCD `a` value in the equation `gcd x y = x * a + y * b`. -/
def gcdA (x y : ℕ) : ℤ :=
(xgcd x y).1
#align nat.gcd_a Nat.gcdA
/-- The extended GCD `b` value in the equation `gcd x y = x * a + y * b`. -/
def gcdB (x y : ℕ) : ℤ :=
(xgcd x y).2
#align nat.gcd_b Nat.gcdB
@[simp]
theorem gcdA_zero_left {s : ℕ} : gcdA 0 s = 0 := by
unfold gcdA
rw [xgcd, xgcd_zero_left]
#align nat.gcd_a_zero_left Nat.gcdA_zero_left
@[simp]
theorem gcdB_zero_left {s : ℕ} : gcdB 0 s = 1 := by
unfold gcdB
rw [xgcd, xgcd_zero_left]
#align nat.gcd_b_zero_left Nat.gcdB_zero_left
@[simp]
theorem gcdA_zero_right {s : ℕ} (h : s ≠ 0) : gcdA s 0 = 1 := by
unfold gcdA xgcd
obtain ⟨s, rfl⟩ := Nat.exists_eq_succ_of_ne_zero h
rw [xgcdAux]
simp
#align nat.gcd_a_zero_right Nat.gcdA_zero_right
@[simp]
theorem gcdB_zero_right {s : ℕ} (h : s ≠ 0) : gcdB s 0 = 0 := by
unfold gcdB xgcd
obtain ⟨s, rfl⟩ := Nat.exists_eq_succ_of_ne_zero h
rw [xgcdAux]
simp
#align nat.gcd_b_zero_right Nat.gcdB_zero_right
@[simp]
theorem xgcdAux_fst (x y) : ∀ s t s' t', (xgcdAux x s t y s' t').1 = gcd x y :=
gcd.induction x y (by simp) fun x y h IH s t s' t' => by
simp only [h, xgcdAux_rec, IH]
rw [← gcd_rec]
#align nat.xgcd_aux_fst Nat.xgcdAux_fst
theorem xgcdAux_val (x y) : xgcdAux x 1 0 y 0 1 = (gcd x y, xgcd x y) := by
rw [xgcd, ← xgcdAux_fst x y 1 0 0 1]
#align nat.xgcd_aux_val Nat.xgcdAux_val
theorem xgcd_val (x y) : xgcd x y = (gcdA x y, gcdB x y) := by
unfold gcdA gcdB; cases xgcd x y; rfl
#align nat.xgcd_val Nat.xgcd_val
section
variable (x y : ℕ)
private def P : ℕ × ℤ × ℤ → Prop
| (r, s, t) => (r : ℤ) = x * s + y * t
| Mathlib/Data/Int/GCD.lean | 123 | 132 | theorem xgcdAux_P {r r'} :
∀ {s t s' t'}, P x y (r, s, t) → P x y (r', s', t') → P x y (xgcdAux r s t r' s' t') := by |
induction r, r' using gcd.induction with
| H0 => simp
| H1 a b h IH =>
intro s t s' t' p p'
rw [xgcdAux_rec h]; refine IH ?_ p; dsimp [P] at *
rw [Int.emod_def]; generalize (b / a : ℤ) = k
rw [p, p', Int.mul_sub, sub_add_eq_add_sub, Int.mul_sub, Int.add_mul, mul_comm k t,
mul_comm k s, ← mul_assoc, ← mul_assoc, add_comm (x * s * k), ← add_sub_assoc, sub_sub]
|
/-
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.BigOperators.Group.List
import Mathlib.Data.Vector.Defs
import Mathlib.Data.List.Nodup
import Mathlib.Data.List.OfFn
import Mathlib.Data.List.InsertNth
import Mathlib.Control.Applicative
import Mathlib.Control.Traversable.Basic
#align_import data.vector.basic from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e"
/-!
# Additional theorems and definitions about the `Vector` type
This file introduces the infix notation `::ᵥ` for `Vector.cons`.
-/
set_option autoImplicit true
universe u
variable {n : ℕ}
namespace Vector
variable {α : Type*}
@[inherit_doc]
infixr:67 " ::ᵥ " => Vector.cons
attribute [simp] head_cons tail_cons
instance [Inhabited α] : Inhabited (Vector α n) :=
⟨ofFn default⟩
theorem toList_injective : Function.Injective (@toList α n) :=
Subtype.val_injective
#align vector.to_list_injective Vector.toList_injective
/-- Two `v w : Vector α n` are equal iff they are equal at every single index. -/
@[ext]
theorem ext : ∀ {v w : Vector α n} (_ : ∀ m : Fin n, Vector.get v m = Vector.get w m), v = w
| ⟨v, hv⟩, ⟨w, hw⟩, h =>
Subtype.eq (List.ext_get (by rw [hv, hw]) fun m hm _ => h ⟨m, hv ▸ hm⟩)
#align vector.ext Vector.ext
/-- The empty `Vector` is a `Subsingleton`. -/
instance zero_subsingleton : Subsingleton (Vector α 0) :=
⟨fun _ _ => Vector.ext fun m => Fin.elim0 m⟩
#align vector.zero_subsingleton Vector.zero_subsingleton
@[simp]
theorem cons_val (a : α) : ∀ v : Vector α n, (a ::ᵥ v).val = a :: v.val
| ⟨_, _⟩ => rfl
#align vector.cons_val Vector.cons_val
#align vector.cons_head Vector.head_cons
#align vector.cons_tail Vector.tail_cons
theorem eq_cons_iff (a : α) (v : Vector α n.succ) (v' : Vector α n) :
v = a ::ᵥ v' ↔ v.head = a ∧ v.tail = v' :=
⟨fun h => h.symm ▸ ⟨head_cons a v', tail_cons a v'⟩, fun h =>
_root_.trans (cons_head_tail v).symm (by rw [h.1, h.2])⟩
#align vector.eq_cons_iff Vector.eq_cons_iff
theorem ne_cons_iff (a : α) (v : Vector α n.succ) (v' : Vector α n) :
v ≠ a ::ᵥ v' ↔ v.head ≠ a ∨ v.tail ≠ v' := by rw [Ne, eq_cons_iff a v v', not_and_or]
#align vector.ne_cons_iff Vector.ne_cons_iff
theorem exists_eq_cons (v : Vector α n.succ) : ∃ (a : α) (as : Vector α n), v = a ::ᵥ as :=
⟨v.head, v.tail, (eq_cons_iff v.head v v.tail).2 ⟨rfl, rfl⟩⟩
#align vector.exists_eq_cons Vector.exists_eq_cons
@[simp]
theorem toList_ofFn : ∀ {n} (f : Fin n → α), toList (ofFn f) = List.ofFn f
| 0, f => by rw [ofFn, List.ofFn_zero, toList, nil]
| n + 1, f => by rw [ofFn, List.ofFn_succ, toList_cons, toList_ofFn]
#align vector.to_list_of_fn Vector.toList_ofFn
@[simp]
theorem mk_toList : ∀ (v : Vector α n) (h), (⟨toList v, h⟩ : Vector α n) = v
| ⟨_, _⟩, _ => rfl
#align vector.mk_to_list Vector.mk_toList
@[simp] theorem length_val (v : Vector α n) : v.val.length = n := v.2
-- Porting note: not used in mathlib and coercions done differently in Lean 4
-- @[simp]
-- theorem length_coe (v : Vector α n) :
-- ((coe : { l : List α // l.length = n } → List α) v).length = n :=
-- v.2
#noalign vector.length_coe
@[simp]
theorem toList_map {β : Type*} (v : Vector α n) (f : α → β) :
(v.map f).toList = v.toList.map f := by cases v; rfl
#align vector.to_list_map Vector.toList_map
@[simp]
theorem head_map {β : Type*} (v : Vector α (n + 1)) (f : α → β) : (v.map f).head = f v.head := by
obtain ⟨a, v', h⟩ := Vector.exists_eq_cons v
rw [h, map_cons, head_cons, head_cons]
#align vector.head_map Vector.head_map
@[simp]
theorem tail_map {β : Type*} (v : Vector α (n + 1)) (f : α → β) :
(v.map f).tail = v.tail.map f := by
obtain ⟨a, v', h⟩ := Vector.exists_eq_cons v
rw [h, map_cons, tail_cons, tail_cons]
#align vector.tail_map Vector.tail_map
theorem get_eq_get (v : Vector α n) (i : Fin n) :
v.get i = v.toList.get (Fin.cast v.toList_length.symm i) :=
rfl
#align vector.nth_eq_nth_le Vector.get_eq_getₓ
@[simp]
theorem get_replicate (a : α) (i : Fin n) : (Vector.replicate n a).get i = a := by
apply List.get_replicate
#align vector.nth_repeat Vector.get_replicate
@[simp]
theorem get_map {β : Type*} (v : Vector α n) (f : α → β) (i : Fin n) :
(v.map f).get i = f (v.get i) := by
cases v; simp [Vector.map, get_eq_get]; rfl
#align vector.nth_map Vector.get_map
@[simp]
theorem map₂_nil (f : α → β → γ) : Vector.map₂ f nil nil = nil :=
rfl
@[simp]
theorem map₂_cons (hd₁ : α) (tl₁ : Vector α n) (hd₂ : β) (tl₂ : Vector β n) (f : α → β → γ) :
Vector.map₂ f (hd₁ ::ᵥ tl₁) (hd₂ ::ᵥ tl₂) = f hd₁ hd₂ ::ᵥ (Vector.map₂ f tl₁ tl₂) :=
rfl
@[simp]
theorem get_ofFn {n} (f : Fin n → α) (i) : get (ofFn f) i = f i := by
conv_rhs => erw [← List.get_ofFn f ⟨i, by simp⟩]
simp only [get_eq_get]
congr <;> simp [Fin.heq_ext_iff]
#align vector.nth_of_fn Vector.get_ofFn
@[simp]
theorem ofFn_get (v : Vector α n) : ofFn (get v) = v := by
rcases v with ⟨l, rfl⟩
apply toList_injective
dsimp
simpa only [toList_ofFn] using List.ofFn_get _
#align vector.of_fn_nth Vector.ofFn_get
/-- The natural equivalence between length-`n` vectors and functions from `Fin n`. -/
def _root_.Equiv.vectorEquivFin (α : Type*) (n : ℕ) : Vector α n ≃ (Fin n → α) :=
⟨Vector.get, Vector.ofFn, Vector.ofFn_get, fun f => funext <| Vector.get_ofFn f⟩
#align equiv.vector_equiv_fin Equiv.vectorEquivFin
theorem get_tail (x : Vector α n) (i) : x.tail.get i = x.get ⟨i.1 + 1, by omega⟩ := by
cases' i with i ih; dsimp
rcases x with ⟨_ | _, h⟩ <;> try rfl
rw [List.length] at h
rw [← h] at ih
contradiction
#align vector.nth_tail Vector.get_tail
@[simp]
theorem get_tail_succ : ∀ (v : Vector α n.succ) (i : Fin n), get (tail v) i = get v i.succ
| ⟨a :: l, e⟩, ⟨i, h⟩ => by simp [get_eq_get]; rfl
#align vector.nth_tail_succ Vector.get_tail_succ
@[simp]
theorem tail_val : ∀ v : Vector α n.succ, v.tail.val = v.val.tail
| ⟨_ :: _, _⟩ => rfl
#align vector.tail_val Vector.tail_val
/-- The `tail` of a `nil` vector is `nil`. -/
@[simp]
theorem tail_nil : (@nil α).tail = nil :=
rfl
#align vector.tail_nil Vector.tail_nil
/-- The `tail` of a vector made up of one element is `nil`. -/
@[simp]
theorem singleton_tail : ∀ (v : Vector α 1), v.tail = Vector.nil
| ⟨[_], _⟩ => rfl
#align vector.singleton_tail Vector.singleton_tail
@[simp]
theorem tail_ofFn {n : ℕ} (f : Fin n.succ → α) : tail (ofFn f) = ofFn fun i => f i.succ :=
(ofFn_get _).symm.trans <| by
congr
funext i
rw [get_tail, get_ofFn]
rfl
#align vector.tail_of_fn Vector.tail_ofFn
@[simp]
theorem toList_empty (v : Vector α 0) : v.toList = [] :=
List.length_eq_zero.mp v.2
#align vector.to_list_empty Vector.toList_empty
/-- The list that makes up a `Vector` made up of a single element,
retrieved via `toList`, is equal to the list of that single element. -/
@[simp]
theorem toList_singleton (v : Vector α 1) : v.toList = [v.head] := by
rw [← v.cons_head_tail]
simp only [toList_cons, toList_nil, head_cons, eq_self_iff_true, and_self_iff, singleton_tail]
#align vector.to_list_singleton Vector.toList_singleton
@[simp]
theorem empty_toList_eq_ff (v : Vector α (n + 1)) : v.toList.isEmpty = false :=
match v with
| ⟨_ :: _, _⟩ => rfl
#align vector.empty_to_list_eq_ff Vector.empty_toList_eq_ff
| Mathlib/Data/Vector/Basic.lean | 221 | 222 | theorem not_empty_toList (v : Vector α (n + 1)) : ¬v.toList.isEmpty := by |
simp only [empty_toList_eq_ff, Bool.coe_sort_false, not_false_iff]
|
/-
Copyright (c) 2018 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis, Mario Carneiro, Johan Commelin
-/
import Mathlib.NumberTheory.Padics.PadicNumbers
import Mathlib.RingTheory.DiscreteValuationRing.Basic
#align_import number_theory.padics.padic_integers from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# p-adic integers
This file defines the `p`-adic integers `ℤ_[p]` as the subtype of `ℚ_[p]` with norm `≤ 1`.
We show that `ℤ_[p]`
* is complete,
* is nonarchimedean,
* is a normed ring,
* is a local ring, and
* is a discrete valuation ring.
The relation between `ℤ_[p]` and `ZMod p` is established in another file.
## Important definitions
* `PadicInt` : the type of `p`-adic integers
## Notation
We introduce the notation `ℤ_[p]` for the `p`-adic integers.
## Implementation notes
Much, but not all, of this file assumes that `p` is prime. This assumption is inferred automatically
by taking `[Fact p.Prime]` as a type class argument.
Coercions into `ℤ_[p]` are set up to work with the `norm_cast` tactic.
## References
* [F. Q. Gouvêa, *p-adic numbers*][gouvea1997]
* [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019]
* <https://en.wikipedia.org/wiki/P-adic_number>
## Tags
p-adic, p adic, padic, p-adic integer
-/
open Padic Metric LocalRing
noncomputable section
open scoped Classical
/-- The `p`-adic integers `ℤ_[p]` are the `p`-adic numbers with norm `≤ 1`. -/
def PadicInt (p : ℕ) [Fact p.Prime] :=
{ x : ℚ_[p] // ‖x‖ ≤ 1 }
#align padic_int PadicInt
/-- The ring of `p`-adic integers. -/
notation "ℤ_[" p "]" => PadicInt p
namespace PadicInt
/-! ### Ring structure and coercion to `ℚ_[p]` -/
variable {p : ℕ} [Fact p.Prime]
instance : Coe ℤ_[p] ℚ_[p] :=
⟨Subtype.val⟩
theorem ext {x y : ℤ_[p]} : (x : ℚ_[p]) = y → x = y :=
Subtype.ext
#align padic_int.ext PadicInt.ext
variable (p)
/-- The `p`-adic integers as a subring of `ℚ_[p]`. -/
def subring : Subring ℚ_[p] where
carrier := { x : ℚ_[p] | ‖x‖ ≤ 1 }
zero_mem' := by set_option tactic.skipAssignedInstances false in norm_num
one_mem' := by set_option tactic.skipAssignedInstances false in norm_num
add_mem' hx hy := (padicNormE.nonarchimedean _ _).trans <| max_le_iff.2 ⟨hx, hy⟩
mul_mem' hx hy := (padicNormE.mul _ _).trans_le <| mul_le_one hx (norm_nonneg _) hy
neg_mem' hx := (norm_neg _).trans_le hx
#align padic_int.subring PadicInt.subring
@[simp]
theorem mem_subring_iff {x : ℚ_[p]} : x ∈ subring p ↔ ‖x‖ ≤ 1 := Iff.rfl
#align padic_int.mem_subring_iff PadicInt.mem_subring_iff
variable {p}
/-- Addition on `ℤ_[p]` is inherited from `ℚ_[p]`. -/
instance : Add ℤ_[p] := (by infer_instance : Add (subring p))
/-- Multiplication on `ℤ_[p]` is inherited from `ℚ_[p]`. -/
instance : Mul ℤ_[p] := (by infer_instance : Mul (subring p))
/-- Negation on `ℤ_[p]` is inherited from `ℚ_[p]`. -/
instance : Neg ℤ_[p] := (by infer_instance : Neg (subring p))
/-- Subtraction on `ℤ_[p]` is inherited from `ℚ_[p]`. -/
instance : Sub ℤ_[p] := (by infer_instance : Sub (subring p))
/-- Zero on `ℤ_[p]` is inherited from `ℚ_[p]`. -/
instance : Zero ℤ_[p] := (by infer_instance : Zero (subring p))
instance : Inhabited ℤ_[p] := ⟨0⟩
/-- One on `ℤ_[p]` is inherited from `ℚ_[p]`. -/
instance : One ℤ_[p] := ⟨⟨1, by norm_num⟩⟩
@[simp]
theorem mk_zero {h} : (⟨0, h⟩ : ℤ_[p]) = (0 : ℤ_[p]) := rfl
#align padic_int.mk_zero PadicInt.mk_zero
@[simp, norm_cast]
theorem coe_add (z1 z2 : ℤ_[p]) : ((z1 + z2 : ℤ_[p]) : ℚ_[p]) = z1 + z2 := rfl
#align padic_int.coe_add PadicInt.coe_add
@[simp, norm_cast]
theorem coe_mul (z1 z2 : ℤ_[p]) : ((z1 * z2 : ℤ_[p]) : ℚ_[p]) = z1 * z2 := rfl
#align padic_int.coe_mul PadicInt.coe_mul
@[simp, norm_cast]
theorem coe_neg (z1 : ℤ_[p]) : ((-z1 : ℤ_[p]) : ℚ_[p]) = -z1 := rfl
#align padic_int.coe_neg PadicInt.coe_neg
@[simp, norm_cast]
theorem coe_sub (z1 z2 : ℤ_[p]) : ((z1 - z2 : ℤ_[p]) : ℚ_[p]) = z1 - z2 := rfl
#align padic_int.coe_sub PadicInt.coe_sub
@[simp, norm_cast]
theorem coe_one : ((1 : ℤ_[p]) : ℚ_[p]) = 1 := rfl
#align padic_int.coe_one PadicInt.coe_one
@[simp, norm_cast]
theorem coe_zero : ((0 : ℤ_[p]) : ℚ_[p]) = 0 := rfl
#align padic_int.coe_zero PadicInt.coe_zero
theorem coe_eq_zero (z : ℤ_[p]) : (z : ℚ_[p]) = 0 ↔ z = 0 := by rw [← coe_zero, Subtype.coe_inj]
#align padic_int.coe_eq_zero PadicInt.coe_eq_zero
theorem coe_ne_zero (z : ℤ_[p]) : (z : ℚ_[p]) ≠ 0 ↔ z ≠ 0 := z.coe_eq_zero.not
#align padic_int.coe_ne_zero PadicInt.coe_ne_zero
instance : AddCommGroup ℤ_[p] := (by infer_instance : AddCommGroup (subring p))
instance instCommRing : CommRing ℤ_[p] := (by infer_instance : CommRing (subring p))
@[simp, norm_cast]
theorem coe_natCast (n : ℕ) : ((n : ℤ_[p]) : ℚ_[p]) = n := rfl
#align padic_int.coe_nat_cast PadicInt.coe_natCast
@[deprecated (since := "2024-04-17")]
alias coe_nat_cast := coe_natCast
@[simp, norm_cast]
theorem coe_intCast (z : ℤ) : ((z : ℤ_[p]) : ℚ_[p]) = z := rfl
#align padic_int.coe_int_cast PadicInt.coe_intCast
@[deprecated (since := "2024-04-17")]
alias coe_int_cast := coe_intCast
/-- The coercion from `ℤ_[p]` to `ℚ_[p]` as a ring homomorphism. -/
def Coe.ringHom : ℤ_[p] →+* ℚ_[p] := (subring p).subtype
#align padic_int.coe.ring_hom PadicInt.Coe.ringHom
@[simp, norm_cast]
theorem coe_pow (x : ℤ_[p]) (n : ℕ) : (↑(x ^ n) : ℚ_[p]) = (↑x : ℚ_[p]) ^ n := rfl
#align padic_int.coe_pow PadicInt.coe_pow
-- @[simp] -- Porting note: not in simpNF
theorem mk_coe (k : ℤ_[p]) : (⟨k, k.2⟩ : ℤ_[p]) = k := Subtype.coe_eta _ _
#align padic_int.mk_coe PadicInt.mk_coe
/-- The inverse of a `p`-adic integer with norm equal to `1` is also a `p`-adic integer.
Otherwise, the inverse is defined to be `0`. -/
def inv : ℤ_[p] → ℤ_[p]
| ⟨k, _⟩ => if h : ‖k‖ = 1 then ⟨k⁻¹, by simp [h]⟩ else 0
#align padic_int.inv PadicInt.inv
instance : CharZero ℤ_[p] where
cast_injective m n h := Nat.cast_injective (by rw [Subtype.ext_iff] at h; norm_cast at h)
@[norm_cast] -- @[simp] -- Porting note: not in simpNF
theorem intCast_eq (z1 z2 : ℤ) : (z1 : ℤ_[p]) = z2 ↔ z1 = z2 := by
suffices (z1 : ℚ_[p]) = z2 ↔ z1 = z2 from Iff.trans (by norm_cast) this
norm_cast
#align padic_int.coe_int_eq PadicInt.intCast_eq
-- 2024-04-05
@[deprecated] alias coe_int_eq := intCast_eq
/-- A sequence of integers that is Cauchy with respect to the `p`-adic norm converges to a `p`-adic
integer. -/
def ofIntSeq (seq : ℕ → ℤ) (h : IsCauSeq (padicNorm p) fun n => seq n) : ℤ_[p] :=
⟨⟦⟨_, h⟩⟧,
show ↑(PadicSeq.norm _) ≤ (1 : ℝ) by
rw [PadicSeq.norm]
split_ifs with hne <;> norm_cast
apply padicNorm.of_int⟩
#align padic_int.of_int_seq PadicInt.ofIntSeq
end PadicInt
namespace PadicInt
/-! ### Instances
We now show that `ℤ_[p]` is a
* complete metric space
* normed ring
* integral domain
-/
variable (p : ℕ) [Fact p.Prime]
instance : MetricSpace ℤ_[p] := Subtype.metricSpace
instance completeSpace : CompleteSpace ℤ_[p] :=
have : IsClosed { x : ℚ_[p] | ‖x‖ ≤ 1 } := isClosed_le continuous_norm continuous_const
this.completeSpace_coe
#align padic_int.complete_space PadicInt.completeSpace
instance : Norm ℤ_[p] := ⟨fun z => ‖(z : ℚ_[p])‖⟩
variable {p}
theorem norm_def {z : ℤ_[p]} : ‖z‖ = ‖(z : ℚ_[p])‖ := rfl
#align padic_int.norm_def PadicInt.norm_def
variable (p)
instance : NormedCommRing ℤ_[p] :=
{ PadicInt.instCommRing with
dist_eq := fun ⟨_, _⟩ ⟨_, _⟩ => rfl
norm_mul := by simp [norm_def]
norm := norm }
instance : NormOneClass ℤ_[p] :=
⟨norm_def.trans norm_one⟩
instance isAbsoluteValue : IsAbsoluteValue fun z : ℤ_[p] => ‖z‖ where
abv_nonneg' := norm_nonneg
abv_eq_zero' := by simp [norm_eq_zero]
abv_add' := fun ⟨_, _⟩ ⟨_, _⟩ => norm_add_le _ _
abv_mul' _ _ := by simp only [norm_def, padicNormE.mul, PadicInt.coe_mul]
#align padic_int.is_absolute_value PadicInt.isAbsoluteValue
variable {p}
instance : IsDomain ℤ_[p] := Function.Injective.isDomain (subring p).subtype Subtype.coe_injective
end PadicInt
namespace PadicInt
/-! ### Norm -/
variable {p : ℕ} [Fact p.Prime]
theorem norm_le_one (z : ℤ_[p]) : ‖z‖ ≤ 1 := z.2
#align padic_int.norm_le_one PadicInt.norm_le_one
@[simp]
theorem norm_mul (z1 z2 : ℤ_[p]) : ‖z1 * z2‖ = ‖z1‖ * ‖z2‖ := by simp [norm_def]
#align padic_int.norm_mul PadicInt.norm_mul
@[simp]
theorem norm_pow (z : ℤ_[p]) : ∀ n : ℕ, ‖z ^ n‖ = ‖z‖ ^ n
| 0 => by simp
| k + 1 => by
rw [pow_succ, pow_succ, norm_mul]
congr
apply norm_pow
#align padic_int.norm_pow PadicInt.norm_pow
theorem nonarchimedean (q r : ℤ_[p]) : ‖q + r‖ ≤ max ‖q‖ ‖r‖ := padicNormE.nonarchimedean _ _
#align padic_int.nonarchimedean PadicInt.nonarchimedean
theorem norm_add_eq_max_of_ne {q r : ℤ_[p]} : ‖q‖ ≠ ‖r‖ → ‖q + r‖ = max ‖q‖ ‖r‖ :=
padicNormE.add_eq_max_of_ne
#align padic_int.norm_add_eq_max_of_ne PadicInt.norm_add_eq_max_of_ne
theorem norm_eq_of_norm_add_lt_right {z1 z2 : ℤ_[p]} (h : ‖z1 + z2‖ < ‖z2‖) : ‖z1‖ = ‖z2‖ :=
by_contra fun hne =>
not_lt_of_ge (by rw [norm_add_eq_max_of_ne hne]; apply le_max_right) h
#align padic_int.norm_eq_of_norm_add_lt_right PadicInt.norm_eq_of_norm_add_lt_right
theorem norm_eq_of_norm_add_lt_left {z1 z2 : ℤ_[p]} (h : ‖z1 + z2‖ < ‖z1‖) : ‖z1‖ = ‖z2‖ :=
by_contra fun hne =>
not_lt_of_ge (by rw [norm_add_eq_max_of_ne hne]; apply le_max_left) h
#align padic_int.norm_eq_of_norm_add_lt_left PadicInt.norm_eq_of_norm_add_lt_left
@[simp]
theorem padic_norm_e_of_padicInt (z : ℤ_[p]) : ‖(z : ℚ_[p])‖ = ‖z‖ := by simp [norm_def]
#align padic_int.padic_norm_e_of_padic_int PadicInt.padic_norm_e_of_padicInt
theorem norm_intCast_eq_padic_norm (z : ℤ) : ‖(z : ℤ_[p])‖ = ‖(z : ℚ_[p])‖ := by simp [norm_def]
#align padic_int.norm_int_cast_eq_padic_norm PadicInt.norm_intCast_eq_padic_norm
@[deprecated (since := "2024-04-17")]
alias norm_int_cast_eq_padic_norm := norm_intCast_eq_padic_norm
@[simp]
theorem norm_eq_padic_norm {q : ℚ_[p]} (hq : ‖q‖ ≤ 1) : @norm ℤ_[p] _ ⟨q, hq⟩ = ‖q‖ := rfl
#align padic_int.norm_eq_padic_norm PadicInt.norm_eq_padic_norm
@[simp]
theorem norm_p : ‖(p : ℤ_[p])‖ = (p : ℝ)⁻¹ := padicNormE.norm_p
#align padic_int.norm_p PadicInt.norm_p
-- @[simp] -- Porting note: not in simpNF
theorem norm_p_pow (n : ℕ) : ‖(p : ℤ_[p]) ^ n‖ = (p : ℝ) ^ (-n : ℤ) := padicNormE.norm_p_pow n
#align padic_int.norm_p_pow PadicInt.norm_p_pow
private def cauSeq_to_rat_cauSeq (f : CauSeq ℤ_[p] norm) : CauSeq ℚ_[p] fun a => ‖a‖ :=
⟨fun n => f n, fun _ hε => by simpa [norm, norm_def] using f.cauchy hε⟩
variable (p)
instance complete : CauSeq.IsComplete ℤ_[p] norm :=
⟨fun f =>
have hqn : ‖CauSeq.lim (cauSeq_to_rat_cauSeq f)‖ ≤ 1 :=
padicNormE_lim_le zero_lt_one fun _ => norm_le_one _
⟨⟨_, hqn⟩, fun ε => by
simpa [norm, norm_def] using CauSeq.equiv_lim (cauSeq_to_rat_cauSeq f) ε⟩⟩
#align padic_int.complete PadicInt.complete
end PadicInt
namespace PadicInt
variable (p : ℕ) [hp : Fact p.Prime]
theorem exists_pow_neg_lt {ε : ℝ} (hε : 0 < ε) : ∃ k : ℕ, (p : ℝ) ^ (-(k : ℤ)) < ε := by
obtain ⟨k, hk⟩ := exists_nat_gt ε⁻¹
use k
rw [← inv_lt_inv hε (_root_.zpow_pos_of_pos _ _)]
· rw [zpow_neg, inv_inv, zpow_natCast]
apply lt_of_lt_of_le hk
norm_cast
apply le_of_lt
convert Nat.lt_pow_self _ _ using 1
exact hp.1.one_lt
· exact mod_cast hp.1.pos
#align padic_int.exists_pow_neg_lt PadicInt.exists_pow_neg_lt
theorem exists_pow_neg_lt_rat {ε : ℚ} (hε : 0 < ε) : ∃ k : ℕ, (p : ℚ) ^ (-(k : ℤ)) < ε := by
obtain ⟨k, hk⟩ := @exists_pow_neg_lt p _ ε (mod_cast hε)
use k
rw [show (p : ℝ) = (p : ℚ) by simp] at hk
exact mod_cast hk
#align padic_int.exists_pow_neg_lt_rat PadicInt.exists_pow_neg_lt_rat
variable {p}
theorem norm_int_lt_one_iff_dvd (k : ℤ) : ‖(k : ℤ_[p])‖ < 1 ↔ (p : ℤ) ∣ k :=
suffices ‖(k : ℚ_[p])‖ < 1 ↔ ↑p ∣ k by rwa [norm_intCast_eq_padic_norm]
padicNormE.norm_int_lt_one_iff_dvd k
#align padic_int.norm_int_lt_one_iff_dvd PadicInt.norm_int_lt_one_iff_dvd
theorem norm_int_le_pow_iff_dvd {k : ℤ} {n : ℕ} :
‖(k : ℤ_[p])‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ (p ^ n : ℤ) ∣ k :=
suffices ‖(k : ℚ_[p])‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ (p ^ n : ℤ) ∣ k by
simpa [norm_intCast_eq_padic_norm]
padicNormE.norm_int_le_pow_iff_dvd _ _
#align padic_int.norm_int_le_pow_iff_dvd PadicInt.norm_int_le_pow_iff_dvd
/-! ### Valuation on `ℤ_[p]` -/
/-- `PadicInt.valuation` lifts the `p`-adic valuation on `ℚ` to `ℤ_[p]`. -/
def valuation (x : ℤ_[p]) :=
Padic.valuation (x : ℚ_[p])
#align padic_int.valuation PadicInt.valuation
theorem norm_eq_pow_val {x : ℤ_[p]} (hx : x ≠ 0) : ‖x‖ = (p : ℝ) ^ (-x.valuation) := by
refine @Padic.norm_eq_pow_val p hp x ?_
contrapose! hx
exact Subtype.val_injective hx
#align padic_int.norm_eq_pow_val PadicInt.norm_eq_pow_val
@[simp]
theorem valuation_zero : valuation (0 : ℤ_[p]) = 0 := Padic.valuation_zero
#align padic_int.valuation_zero PadicInt.valuation_zero
@[simp]
theorem valuation_one : valuation (1 : ℤ_[p]) = 0 := Padic.valuation_one
#align padic_int.valuation_one PadicInt.valuation_one
@[simp]
theorem valuation_p : valuation (p : ℤ_[p]) = 1 := by simp [valuation]
#align padic_int.valuation_p PadicInt.valuation_p
theorem valuation_nonneg (x : ℤ_[p]) : 0 ≤ x.valuation := by
by_cases hx : x = 0
· simp [hx]
have h : (1 : ℝ) < p := mod_cast hp.1.one_lt
rw [← neg_nonpos, ← (zpow_strictMono h).le_iff_le]
show (p : ℝ) ^ (-valuation x) ≤ (p : ℝ) ^ (0 : ℤ)
rw [← norm_eq_pow_val hx]
simpa using x.property
#align padic_int.valuation_nonneg PadicInt.valuation_nonneg
@[simp]
theorem valuation_p_pow_mul (n : ℕ) (c : ℤ_[p]) (hc : c ≠ 0) :
((p : ℤ_[p]) ^ n * c).valuation = n + c.valuation := by
have : ‖(p : ℤ_[p]) ^ n * c‖ = ‖(p : ℤ_[p]) ^ n‖ * ‖c‖ := norm_mul _ _
have aux : (p : ℤ_[p]) ^ n * c ≠ 0 := by
contrapose! hc
rw [mul_eq_zero] at hc
cases' hc with hc hc
· refine (hp.1.ne_zero ?_).elim
exact_mod_cast pow_eq_zero hc
· exact hc
rwa [norm_eq_pow_val aux, norm_p_pow, norm_eq_pow_val hc, ← zpow_add₀, ← neg_add,
zpow_inj, neg_inj] at this
· exact mod_cast hp.1.pos
· exact mod_cast hp.1.ne_one
· exact mod_cast hp.1.ne_zero
#align padic_int.valuation_p_pow_mul PadicInt.valuation_p_pow_mul
section Units
/-! ### Units of `ℤ_[p]` -/
-- Porting note: `reducible` cannot be local and making it global breaks a lot of things
-- attribute [local reducible] PadicInt
theorem mul_inv : ∀ {z : ℤ_[p]}, ‖z‖ = 1 → z * z.inv = 1
| ⟨k, _⟩, h => by
have hk : k ≠ 0 := fun h' => zero_ne_one' ℚ_[p] (by simp [h'] at h)
unfold PadicInt.inv
rw [norm_eq_padic_norm] at h
dsimp only
rw [dif_pos h]
apply Subtype.ext_iff_val.2
simp [mul_inv_cancel hk]
#align padic_int.mul_inv PadicInt.mul_inv
theorem inv_mul {z : ℤ_[p]} (hz : ‖z‖ = 1) : z.inv * z = 1 := by rw [mul_comm, mul_inv hz]
#align padic_int.inv_mul PadicInt.inv_mul
theorem isUnit_iff {z : ℤ_[p]} : IsUnit z ↔ ‖z‖ = 1 :=
⟨fun h => by
rcases isUnit_iff_dvd_one.1 h with ⟨w, eq⟩
refine le_antisymm (norm_le_one _) ?_
have := mul_le_mul_of_nonneg_left (norm_le_one w) (norm_nonneg z)
rwa [mul_one, ← norm_mul, ← eq, norm_one] at this, fun h =>
⟨⟨z, z.inv, mul_inv h, inv_mul h⟩, rfl⟩⟩
#align padic_int.is_unit_iff PadicInt.isUnit_iff
theorem norm_lt_one_add {z1 z2 : ℤ_[p]} (hz1 : ‖z1‖ < 1) (hz2 : ‖z2‖ < 1) : ‖z1 + z2‖ < 1 :=
lt_of_le_of_lt (nonarchimedean _ _) (max_lt hz1 hz2)
#align padic_int.norm_lt_one_add PadicInt.norm_lt_one_add
theorem norm_lt_one_mul {z1 z2 : ℤ_[p]} (hz2 : ‖z2‖ < 1) : ‖z1 * z2‖ < 1 :=
calc
‖z1 * z2‖ = ‖z1‖ * ‖z2‖ := by simp
_ < 1 := mul_lt_one_of_nonneg_of_lt_one_right (norm_le_one _) (norm_nonneg _) hz2
#align padic_int.norm_lt_one_mul PadicInt.norm_lt_one_mul
-- @[simp] -- Porting note: not in simpNF
theorem mem_nonunits {z : ℤ_[p]} : z ∈ nonunits ℤ_[p] ↔ ‖z‖ < 1 := by
rw [lt_iff_le_and_ne]; simp [norm_le_one z, nonunits, isUnit_iff]
#align padic_int.mem_nonunits PadicInt.mem_nonunits
/-- A `p`-adic number `u` with `‖u‖ = 1` is a unit of `ℤ_[p]`. -/
def mkUnits {u : ℚ_[p]} (h : ‖u‖ = 1) : ℤ_[p]ˣ :=
let z : ℤ_[p] := ⟨u, le_of_eq h⟩
⟨z, z.inv, mul_inv h, inv_mul h⟩
#align padic_int.mk_units PadicInt.mkUnits
@[simp]
theorem mkUnits_eq {u : ℚ_[p]} (h : ‖u‖ = 1) : ((mkUnits h : ℤ_[p]) : ℚ_[p]) = u := rfl
#align padic_int.mk_units_eq PadicInt.mkUnits_eq
@[simp]
theorem norm_units (u : ℤ_[p]ˣ) : ‖(u : ℤ_[p])‖ = 1 := isUnit_iff.mp <| by simp
#align padic_int.norm_units PadicInt.norm_units
/-- `unitCoeff hx` is the unit `u` in the unique representation `x = u * p ^ n`.
See `unitCoeff_spec`. -/
def unitCoeff {x : ℤ_[p]} (hx : x ≠ 0) : ℤ_[p]ˣ :=
let u : ℚ_[p] := x * (p : ℚ_[p]) ^ (-x.valuation)
have hu : ‖u‖ = 1 := by
simp [u, hx, Nat.zpow_ne_zero_of_pos (mod_cast hp.1.pos) x.valuation, norm_eq_pow_val,
zpow_neg, inv_mul_cancel]
mkUnits hu
#align padic_int.unit_coeff PadicInt.unitCoeff
@[simp]
theorem unitCoeff_coe {x : ℤ_[p]} (hx : x ≠ 0) :
(unitCoeff hx : ℚ_[p]) = x * (p : ℚ_[p]) ^ (-x.valuation) := rfl
#align padic_int.unit_coeff_coe PadicInt.unitCoeff_coe
theorem unitCoeff_spec {x : ℤ_[p]} (hx : x ≠ 0) :
x = (unitCoeff hx : ℤ_[p]) * (p : ℤ_[p]) ^ Int.natAbs (valuation x) := by
apply Subtype.coe_injective
push_cast
have repr : (x : ℚ_[p]) = unitCoeff hx * (p : ℚ_[p]) ^ x.valuation := by
rw [unitCoeff_coe, mul_assoc, ← zpow_add₀]
· simp
· exact mod_cast hp.1.ne_zero
convert repr using 2
rw [← zpow_natCast, Int.natAbs_of_nonneg (valuation_nonneg x)]
#align padic_int.unit_coeff_spec PadicInt.unitCoeff_spec
end Units
section NormLeIff
/-! ### Various characterizations of open unit balls -/
theorem norm_le_pow_iff_le_valuation (x : ℤ_[p]) (hx : x ≠ 0) (n : ℕ) :
‖x‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ ↑n ≤ x.valuation := by
rw [norm_eq_pow_val hx]
lift x.valuation to ℕ using x.valuation_nonneg with k
simp only [Int.ofNat_le, zpow_neg, zpow_natCast]
have aux : ∀ m : ℕ, 0 < (p : ℝ) ^ m := by
intro m
refine pow_pos ?_ m
exact mod_cast hp.1.pos
rw [inv_le_inv (aux _) (aux _)]
have : p ^ n ≤ p ^ k ↔ n ≤ k := (pow_right_strictMono hp.1.one_lt).le_iff_le
rw [← this]
norm_cast
#align padic_int.norm_le_pow_iff_le_valuation PadicInt.norm_le_pow_iff_le_valuation
theorem mem_span_pow_iff_le_valuation (x : ℤ_[p]) (hx : x ≠ 0) (n : ℕ) :
x ∈ (Ideal.span {(p : ℤ_[p]) ^ n} : Ideal ℤ_[p]) ↔ ↑n ≤ x.valuation := by
rw [Ideal.mem_span_singleton]
constructor
· rintro ⟨c, rfl⟩
suffices c ≠ 0 by
rw [valuation_p_pow_mul _ _ this, le_add_iff_nonneg_right]
apply valuation_nonneg
contrapose! hx
rw [hx, mul_zero]
· nth_rewrite 2 [unitCoeff_spec hx]
lift x.valuation to ℕ using x.valuation_nonneg with k
simp only [Int.natAbs_ofNat, Units.isUnit, IsUnit.dvd_mul_left, Int.ofNat_le]
intro H
obtain ⟨k, rfl⟩ := Nat.exists_eq_add_of_le H
simp only [pow_add, dvd_mul_right]
#align padic_int.mem_span_pow_iff_le_valuation PadicInt.mem_span_pow_iff_le_valuation
| Mathlib/NumberTheory/Padics/PadicIntegers.lean | 558 | 564 | theorem norm_le_pow_iff_mem_span_pow (x : ℤ_[p]) (n : ℕ) :
‖x‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ x ∈ (Ideal.span {(p : ℤ_[p]) ^ n} : Ideal ℤ_[p]) := by |
by_cases hx : x = 0
· subst hx
simp only [norm_zero, zpow_neg, zpow_natCast, inv_nonneg, iff_true_iff, Submodule.zero_mem]
exact mod_cast Nat.zero_le _
rw [norm_le_pow_iff_le_valuation x hx, mem_span_pow_iff_le_valuation x hx]
|
/-
Copyright (c) 2023 Michael Stoll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Geißer, Michael Stoll
-/
import Mathlib.Tactic.Qify
import Mathlib.Data.ZMod.Basic
import Mathlib.NumberTheory.DiophantineApproximation
import Mathlib.NumberTheory.Zsqrtd.Basic
#align_import number_theory.pell from "leanprover-community/mathlib"@"7ad820c4997738e2f542f8a20f32911f52020e26"
/-!
# Pell's Equation
*Pell's Equation* is the equation $x^2 - d y^2 = 1$, where $d$ is a positive integer
that is not a square, and one is interested in solutions in integers $x$ and $y$.
In this file, we aim at providing all of the essential theory of Pell's Equation for general $d$
(as opposed to the contents of `NumberTheory.PellMatiyasevic`, which is specific to the case
$d = a^2 - 1$ for some $a > 1$).
We begin by defining a type `Pell.Solution₁ d` for solutions of the equation,
show that it has a natural structure as an abelian group, and prove some basic
properties.
We then prove the following
**Theorem.** Let $d$ be a positive integer that is not a square. Then the equation
$x^2 - d y^2 = 1$ has a nontrivial (i.e., with $y \ne 0$) solution in integers.
See `Pell.exists_of_not_isSquare` and `Pell.Solution₁.exists_nontrivial_of_not_isSquare`.
We then define the *fundamental solution* to be the solution
with smallest $x$ among all solutions satisfying $x > 1$ and $y > 0$.
We show that every solution is a power (in the sense of the group structure mentioned above)
of the fundamental solution up to a (common) sign,
see `Pell.IsFundamental.eq_zpow_or_neg_zpow`, and that a (positive) solution has this property
if and only if it is fundamental, see `Pell.pos_generator_iff_fundamental`.
## References
* [K. Ireland, M. Rosen, *A classical introduction to modern number theory*
(Section 17.5)][IrelandRosen1990]
## Tags
Pell's equation
## TODO
* Extend to `x ^ 2 - d * y ^ 2 = -1` and further generalizations.
* Connect solutions to the continued fraction expansion of `√d`.
-/
namespace Pell
/-!
### Group structure of the solution set
We define a structure of a commutative multiplicative group with distributive negation
on the set of all solutions to the Pell equation `x^2 - d*y^2 = 1`.
The type of such solutions is `Pell.Solution₁ d`. It corresponds to a pair of integers `x` and `y`
and a proof that `(x, y)` is indeed a solution.
The multiplication is given by `(x, y) * (x', y') = (x*y' + d*y*y', x*y' + y*x')`.
This is obtained by mapping `(x, y)` to `x + y*√d` and multiplying the results.
In fact, we define `Pell.Solution₁ d` to be `↥(unitary (ℤ√d))` and transport
the "commutative group with distributive negation" structure from `↥(unitary (ℤ√d))`.
We then set up an API for `Pell.Solution₁ d`.
-/
open Zsqrtd
/-- An element of `ℤ√d` has norm one (i.e., `a.re^2 - d*a.im^2 = 1`) if and only if
it is contained in the submonoid of unitary elements.
TODO: merge this result with `Pell.isPell_iff_mem_unitary`. -/
theorem is_pell_solution_iff_mem_unitary {d : ℤ} {a : ℤ√d} :
a.re ^ 2 - d * a.im ^ 2 = 1 ↔ a ∈ unitary (ℤ√d) := by
rw [← norm_eq_one_iff_mem_unitary, norm_def, sq, sq, ← mul_assoc]
#align pell.is_pell_solution_iff_mem_unitary Pell.is_pell_solution_iff_mem_unitary
-- We use `solution₁ d` to allow for a more general structure `solution d m` that
-- encodes solutions to `x^2 - d*y^2 = m` to be added later.
/-- `Pell.Solution₁ d` is the type of solutions to the Pell equation `x^2 - d*y^2 = 1`.
We define this in terms of elements of `ℤ√d` of norm one.
-/
def Solution₁ (d : ℤ) : Type :=
↥(unitary (ℤ√d))
#align pell.solution₁ Pell.Solution₁
namespace Solution₁
variable {d : ℤ}
-- Porting note(https://github.com/leanprover-community/mathlib4/issues/5020): manual deriving
instance instCommGroup : CommGroup (Solution₁ d) :=
inferInstanceAs (CommGroup (unitary (ℤ√d)))
#align pell.solution₁.comm_group Pell.Solution₁.instCommGroup
instance instHasDistribNeg : HasDistribNeg (Solution₁ d) :=
inferInstanceAs (HasDistribNeg (unitary (ℤ√d)))
#align pell.solution₁.has_distrib_neg Pell.Solution₁.instHasDistribNeg
instance instInhabited : Inhabited (Solution₁ d) :=
inferInstanceAs (Inhabited (unitary (ℤ√d)))
#align pell.solution₁.inhabited Pell.Solution₁.instInhabited
instance : Coe (Solution₁ d) (ℤ√d) where coe := Subtype.val
/-- The `x` component of a solution to the Pell equation `x^2 - d*y^2 = 1` -/
protected def x (a : Solution₁ d) : ℤ :=
(a : ℤ√d).re
#align pell.solution₁.x Pell.Solution₁.x
/-- The `y` component of a solution to the Pell equation `x^2 - d*y^2 = 1` -/
protected def y (a : Solution₁ d) : ℤ :=
(a : ℤ√d).im
#align pell.solution₁.y Pell.Solution₁.y
/-- The proof that `a` is a solution to the Pell equation `x^2 - d*y^2 = 1` -/
theorem prop (a : Solution₁ d) : a.x ^ 2 - d * a.y ^ 2 = 1 :=
is_pell_solution_iff_mem_unitary.mpr a.property
#align pell.solution₁.prop Pell.Solution₁.prop
/-- An alternative form of the equation, suitable for rewriting `x^2`. -/
theorem prop_x (a : Solution₁ d) : a.x ^ 2 = 1 + d * a.y ^ 2 := by rw [← a.prop]; ring
#align pell.solution₁.prop_x Pell.Solution₁.prop_x
/-- An alternative form of the equation, suitable for rewriting `d * y^2`. -/
theorem prop_y (a : Solution₁ d) : d * a.y ^ 2 = a.x ^ 2 - 1 := by rw [← a.prop]; ring
#align pell.solution₁.prop_y Pell.Solution₁.prop_y
/-- Two solutions are equal if their `x` and `y` components are equal. -/
@[ext]
theorem ext {a b : Solution₁ d} (hx : a.x = b.x) (hy : a.y = b.y) : a = b :=
Subtype.ext <| Zsqrtd.ext _ _ hx hy
#align pell.solution₁.ext Pell.Solution₁.ext
/-- Construct a solution from `x`, `y` and a proof that the equation is satisfied. -/
def mk (x y : ℤ) (prop : x ^ 2 - d * y ^ 2 = 1) : Solution₁ d where
val := ⟨x, y⟩
property := is_pell_solution_iff_mem_unitary.mp prop
#align pell.solution₁.mk Pell.Solution₁.mk
@[simp]
theorem x_mk (x y : ℤ) (prop : x ^ 2 - d * y ^ 2 = 1) : (mk x y prop).x = x :=
rfl
#align pell.solution₁.x_mk Pell.Solution₁.x_mk
@[simp]
theorem y_mk (x y : ℤ) (prop : x ^ 2 - d * y ^ 2 = 1) : (mk x y prop).y = y :=
rfl
#align pell.solution₁.y_mk Pell.Solution₁.y_mk
@[simp]
theorem coe_mk (x y : ℤ) (prop : x ^ 2 - d * y ^ 2 = 1) : (↑(mk x y prop) : ℤ√d) = ⟨x, y⟩ :=
Zsqrtd.ext _ _ (x_mk x y prop) (y_mk x y prop)
#align pell.solution₁.coe_mk Pell.Solution₁.coe_mk
@[simp]
theorem x_one : (1 : Solution₁ d).x = 1 :=
rfl
#align pell.solution₁.x_one Pell.Solution₁.x_one
@[simp]
theorem y_one : (1 : Solution₁ d).y = 0 :=
rfl
#align pell.solution₁.y_one Pell.Solution₁.y_one
@[simp]
theorem x_mul (a b : Solution₁ d) : (a * b).x = a.x * b.x + d * (a.y * b.y) := by
rw [← mul_assoc]
rfl
#align pell.solution₁.x_mul Pell.Solution₁.x_mul
@[simp]
theorem y_mul (a b : Solution₁ d) : (a * b).y = a.x * b.y + a.y * b.x :=
rfl
#align pell.solution₁.y_mul Pell.Solution₁.y_mul
@[simp]
theorem x_inv (a : Solution₁ d) : a⁻¹.x = a.x :=
rfl
#align pell.solution₁.x_inv Pell.Solution₁.x_inv
@[simp]
theorem y_inv (a : Solution₁ d) : a⁻¹.y = -a.y :=
rfl
#align pell.solution₁.y_inv Pell.Solution₁.y_inv
@[simp]
theorem x_neg (a : Solution₁ d) : (-a).x = -a.x :=
rfl
#align pell.solution₁.x_neg Pell.Solution₁.x_neg
@[simp]
theorem y_neg (a : Solution₁ d) : (-a).y = -a.y :=
rfl
#align pell.solution₁.y_neg Pell.Solution₁.y_neg
/-- When `d` is negative, then `x` or `y` must be zero in a solution. -/
theorem eq_zero_of_d_neg (h₀ : d < 0) (a : Solution₁ d) : a.x = 0 ∨ a.y = 0 := by
have h := a.prop
contrapose! h
have h1 := sq_pos_of_ne_zero h.1
have h2 := sq_pos_of_ne_zero h.2
nlinarith
#align pell.solution₁.eq_zero_of_d_neg Pell.Solution₁.eq_zero_of_d_neg
/-- A solution has `x ≠ 0`. -/
theorem x_ne_zero (h₀ : 0 ≤ d) (a : Solution₁ d) : a.x ≠ 0 := by
intro hx
have h : 0 ≤ d * a.y ^ 2 := mul_nonneg h₀ (sq_nonneg _)
rw [a.prop_y, hx, sq, zero_mul, zero_sub] at h
exact not_le.mpr (neg_one_lt_zero : (-1 : ℤ) < 0) h
#align pell.solution₁.x_ne_zero Pell.Solution₁.x_ne_zero
/-- A solution with `x > 1` must have `y ≠ 0`. -/
theorem y_ne_zero_of_one_lt_x {a : Solution₁ d} (ha : 1 < a.x) : a.y ≠ 0 := by
intro hy
have prop := a.prop
rw [hy, sq (0 : ℤ), zero_mul, mul_zero, sub_zero] at prop
exact lt_irrefl _ (((one_lt_sq_iff <| zero_le_one.trans ha.le).mpr ha).trans_eq prop)
#align pell.solution₁.y_ne_zero_of_one_lt_x Pell.Solution₁.y_ne_zero_of_one_lt_x
/-- If a solution has `x > 1`, then `d` is positive. -/
theorem d_pos_of_one_lt_x {a : Solution₁ d} (ha : 1 < a.x) : 0 < d := by
refine pos_of_mul_pos_left ?_ (sq_nonneg a.y)
rw [a.prop_y, sub_pos]
exact one_lt_pow ha two_ne_zero
#align pell.solution₁.d_pos_of_one_lt_x Pell.Solution₁.d_pos_of_one_lt_x
/-- If a solution has `x > 1`, then `d` is not a square. -/
theorem d_nonsquare_of_one_lt_x {a : Solution₁ d} (ha : 1 < a.x) : ¬IsSquare d := by
have hp := a.prop
rintro ⟨b, rfl⟩
simp_rw [← sq, ← mul_pow, sq_sub_sq, Int.mul_eq_one_iff_eq_one_or_neg_one] at hp
rcases hp with (⟨hp₁, hp₂⟩ | ⟨hp₁, hp₂⟩) <;> omega
#align pell.solution₁.d_nonsquare_of_one_lt_x Pell.Solution₁.d_nonsquare_of_one_lt_x
/-- A solution with `x = 1` is trivial. -/
theorem eq_one_of_x_eq_one (h₀ : d ≠ 0) {a : Solution₁ d} (ha : a.x = 1) : a = 1 := by
have prop := a.prop_y
rw [ha, one_pow, sub_self, mul_eq_zero, or_iff_right h₀, sq_eq_zero_iff] at prop
exact ext ha prop
#align pell.solution₁.eq_one_of_x_eq_one Pell.Solution₁.eq_one_of_x_eq_one
/-- A solution is `1` or `-1` if and only if `y = 0`. -/
theorem eq_one_or_neg_one_iff_y_eq_zero {a : Solution₁ d} : a = 1 ∨ a = -1 ↔ a.y = 0 := by
refine ⟨fun H => H.elim (fun h => by simp [h]) fun h => by simp [h], fun H => ?_⟩
have prop := a.prop
rw [H, sq (0 : ℤ), mul_zero, mul_zero, sub_zero, sq_eq_one_iff] at prop
exact prop.imp (fun h => ext h H) fun h => ext h H
#align pell.solution₁.eq_one_or_neg_one_iff_y_eq_zero Pell.Solution₁.eq_one_or_neg_one_iff_y_eq_zero
/-- The set of solutions with `x > 0` is closed under multiplication. -/
theorem x_mul_pos {a b : Solution₁ d} (ha : 0 < a.x) (hb : 0 < b.x) : 0 < (a * b).x := by
simp only [x_mul]
refine neg_lt_iff_pos_add'.mp (abs_lt.mp ?_).1
rw [← abs_of_pos ha, ← abs_of_pos hb, ← abs_mul, ← sq_lt_sq, mul_pow a.x, a.prop_x, b.prop_x, ←
sub_pos]
ring_nf
rcases le_or_lt 0 d with h | h
· positivity
· rw [(eq_zero_of_d_neg h a).resolve_left ha.ne', (eq_zero_of_d_neg h b).resolve_left hb.ne']
-- Porting note: was
-- rw [zero_pow two_ne_zero, zero_add, zero_mul, zero_add]
-- exact one_pos
-- but this relied on the exact output of `ring_nf`
simp
#align pell.solution₁.x_mul_pos Pell.Solution₁.x_mul_pos
/-- The set of solutions with `x` and `y` positive is closed under multiplication. -/
theorem y_mul_pos {a b : Solution₁ d} (hax : 0 < a.x) (hay : 0 < a.y) (hbx : 0 < b.x)
(hby : 0 < b.y) : 0 < (a * b).y := by
simp only [y_mul]
positivity
#align pell.solution₁.y_mul_pos Pell.Solution₁.y_mul_pos
/-- If `(x, y)` is a solution with `x` positive, then all its powers with natural exponents
have positive `x`. -/
theorem x_pow_pos {a : Solution₁ d} (hax : 0 < a.x) (n : ℕ) : 0 < (a ^ n).x := by
induction' n with n ih
· simp only [Nat.zero_eq, pow_zero, x_one, zero_lt_one]
· rw [pow_succ]
exact x_mul_pos ih hax
#align pell.solution₁.x_pow_pos Pell.Solution₁.x_pow_pos
/-- If `(x, y)` is a solution with `x` and `y` positive, then all its powers with positive
natural exponents have positive `y`. -/
theorem y_pow_succ_pos {a : Solution₁ d} (hax : 0 < a.x) (hay : 0 < a.y) (n : ℕ) :
0 < (a ^ n.succ).y := by
induction' n with n ih
· simp only [Nat.zero_eq, ← Nat.one_eq_succ_zero, hay, pow_one]
· rw [pow_succ']
exact y_mul_pos hax hay (x_pow_pos hax _) ih
#align pell.solution₁.y_pow_succ_pos Pell.Solution₁.y_pow_succ_pos
/-- If `(x, y)` is a solution with `x` and `y` positive, then all its powers with positive
exponents have positive `y`. -/
theorem y_zpow_pos {a : Solution₁ d} (hax : 0 < a.x) (hay : 0 < a.y) {n : ℤ} (hn : 0 < n) :
0 < (a ^ n).y := by
lift n to ℕ using hn.le
norm_cast at hn ⊢
rw [← Nat.succ_pred_eq_of_pos hn]
exact y_pow_succ_pos hax hay _
#align pell.solution₁.y_zpow_pos Pell.Solution₁.y_zpow_pos
/-- If `(x, y)` is a solution with `x` positive, then all its powers have positive `x`. -/
theorem x_zpow_pos {a : Solution₁ d} (hax : 0 < a.x) (n : ℤ) : 0 < (a ^ n).x := by
cases n with
| ofNat n =>
rw [Int.ofNat_eq_coe, zpow_natCast]
exact x_pow_pos hax n
| negSucc n =>
rw [zpow_negSucc]
exact x_pow_pos hax (n + 1)
#align pell.solution₁.x_zpow_pos Pell.Solution₁.x_zpow_pos
/-- If `(x, y)` is a solution with `x` and `y` positive, then the `y` component of any power
has the same sign as the exponent. -/
theorem sign_y_zpow_eq_sign_of_x_pos_of_y_pos {a : Solution₁ d} (hax : 0 < a.x) (hay : 0 < a.y)
(n : ℤ) : (a ^ n).y.sign = n.sign := by
rcases n with ((_ | n) | n)
· rfl
· rw [Int.ofNat_eq_coe, zpow_natCast]
exact Int.sign_eq_one_of_pos (y_pow_succ_pos hax hay n)
· rw [zpow_negSucc]
exact Int.sign_eq_neg_one_of_neg (neg_neg_of_pos (y_pow_succ_pos hax hay n))
#align pell.solution₁.sign_y_zpow_eq_sign_of_x_pos_of_y_pos Pell.Solution₁.sign_y_zpow_eq_sign_of_x_pos_of_y_pos
/-- If `a` is any solution, then one of `a`, `a⁻¹`, `-a`, `-a⁻¹` has
positive `x` and nonnegative `y`. -/
theorem exists_pos_variant (h₀ : 0 < d) (a : Solution₁ d) :
∃ b : Solution₁ d, 0 < b.x ∧ 0 ≤ b.y ∧ a ∈ ({b, b⁻¹, -b, -b⁻¹} : Set (Solution₁ d)) := by
refine
(lt_or_gt_of_ne (a.x_ne_zero h₀.le)).elim
((le_total 0 a.y).elim (fun hy hx => ⟨-a⁻¹, ?_, ?_, ?_⟩) fun hy hx => ⟨-a, ?_, ?_, ?_⟩)
((le_total 0 a.y).elim (fun hy hx => ⟨a, hx, hy, ?_⟩) fun hy hx => ⟨a⁻¹, hx, ?_, ?_⟩) <;>
simp only [neg_neg, inv_inv, neg_inv, Set.mem_insert_iff, Set.mem_singleton_iff, true_or_iff,
eq_self_iff_true, x_neg, x_inv, y_neg, y_inv, neg_pos, neg_nonneg, or_true_iff] <;>
assumption
#align pell.solution₁.exists_pos_variant Pell.Solution₁.exists_pos_variant
end Solution₁
section Existence
/-!
### Existence of nontrivial solutions
-/
variable {d : ℤ}
open Set Real
/-- If `d` is a positive integer that is not a square, then there is a nontrivial solution
to the Pell equation `x^2 - d*y^2 = 1`. -/
theorem exists_of_not_isSquare (h₀ : 0 < d) (hd : ¬IsSquare d) :
∃ x y : ℤ, x ^ 2 - d * y ^ 2 = 1 ∧ y ≠ 0 := by
let ξ : ℝ := √d
have hξ : Irrational ξ := by
refine irrational_nrt_of_notint_nrt 2 d (sq_sqrt <| Int.cast_nonneg.mpr h₀.le) ?_ two_pos
rintro ⟨x, hx⟩
refine hd ⟨x, @Int.cast_injective ℝ _ _ d (x * x) ?_⟩
rw [← sq_sqrt <| Int.cast_nonneg.mpr h₀.le, Int.cast_mul, ← hx, sq]
obtain ⟨M, hM₁⟩ := exists_int_gt (2 * |ξ| + 1)
have hM : {q : ℚ | |q.1 ^ 2 - d * (q.2 : ℤ) ^ 2| < M}.Infinite := by
refine Infinite.mono (fun q h => ?_) (infinite_rat_abs_sub_lt_one_div_den_sq_of_irrational hξ)
have h0 : 0 < (q.2 : ℝ) ^ 2 := pow_pos (Nat.cast_pos.mpr q.pos) 2
have h1 : (q.num : ℝ) / (q.den : ℝ) = q := mod_cast q.num_div_den
rw [mem_setOf, abs_sub_comm, ← @Int.cast_lt ℝ, ← div_lt_div_right (abs_pos_of_pos h0)]
push_cast
rw [← abs_div, abs_sq, sub_div, mul_div_cancel_right₀ _ h0.ne', ← div_pow, h1, ←
sq_sqrt (Int.cast_pos.mpr h₀).le, sq_sub_sq, abs_mul, ← mul_one_div]
refine mul_lt_mul'' (((abs_add ξ q).trans ?_).trans_lt hM₁) h (abs_nonneg _) (abs_nonneg _)
rw [two_mul, add_assoc, add_le_add_iff_left, ← sub_le_iff_le_add']
rw [mem_setOf, abs_sub_comm] at h
refine (abs_sub_abs_le_abs_sub (q : ℝ) ξ).trans (h.le.trans ?_)
rw [div_le_one h0, one_le_sq_iff_one_le_abs, Nat.abs_cast, Nat.one_le_cast]
exact q.pos
obtain ⟨m, hm⟩ : ∃ m : ℤ, {q : ℚ | q.1 ^ 2 - d * (q.den : ℤ) ^ 2 = m}.Infinite := by
contrapose! hM
simp only [not_infinite] at hM ⊢
refine (congr_arg _ (ext fun x => ?_)).mp (Finite.biUnion (finite_Ioo (-M) M) fun m _ => hM m)
simp only [abs_lt, mem_setOf, mem_Ioo, mem_iUnion, exists_prop, exists_eq_right']
have hm₀ : m ≠ 0 := by
rintro rfl
obtain ⟨q, hq⟩ := hm.nonempty
rw [mem_setOf, sub_eq_zero, mul_comm] at hq
obtain ⟨a, ha⟩ := (Int.pow_dvd_pow_iff two_ne_zero).mp ⟨d, hq⟩
rw [ha, mul_pow, mul_right_inj' (pow_pos (Int.natCast_pos.mpr q.pos) 2).ne'] at hq
exact hd ⟨a, sq a ▸ hq.symm⟩
haveI := neZero_iff.mpr (Int.natAbs_ne_zero.mpr hm₀)
let f : ℚ → ZMod m.natAbs × ZMod m.natAbs := fun q => (q.num, q.den)
obtain ⟨q₁, h₁ : q₁.num ^ 2 - d * (q₁.den : ℤ) ^ 2 = m,
q₂, h₂ : q₂.num ^ 2 - d * (q₂.den : ℤ) ^ 2 = m, hne, hqf⟩ :=
hm.exists_ne_map_eq_of_mapsTo (mapsTo_univ f _) finite_univ
obtain ⟨hq1 : (q₁.num : ZMod m.natAbs) = q₂.num, hq2 : (q₁.den : ZMod m.natAbs) = q₂.den⟩ :=
Prod.ext_iff.mp hqf
have hd₁ : m ∣ q₁.num * q₂.num - d * (q₁.den * q₂.den) := by
rw [← Int.natAbs_dvd, ← ZMod.intCast_zmod_eq_zero_iff_dvd]
push_cast
rw [hq1, hq2, ← sq, ← sq]
norm_cast
rw [ZMod.intCast_zmod_eq_zero_iff_dvd, Int.natAbs_dvd, Nat.cast_pow, ← h₂]
have hd₂ : m ∣ q₁.num * q₂.den - q₂.num * q₁.den := by
rw [← Int.natAbs_dvd, ← ZMod.intCast_eq_intCast_iff_dvd_sub]
push_cast
rw [hq1, hq2]
replace hm₀ : (m : ℚ) ≠ 0 := Int.cast_ne_zero.mpr hm₀
refine ⟨(q₁.num * q₂.num - d * (q₁.den * q₂.den)) / m, (q₁.num * q₂.den - q₂.num * q₁.den) / m,
?_, ?_⟩
· qify [hd₁, hd₂]
field_simp [hm₀]
norm_cast
conv_rhs =>
rw [sq]
congr
· rw [← h₁]
· rw [← h₂]
push_cast
ring
· qify [hd₂]
refine div_ne_zero_iff.mpr ⟨?_, hm₀⟩
exact mod_cast mt sub_eq_zero.mp (mt Rat.eq_iff_mul_eq_mul.mpr hne)
#align pell.exists_of_not_is_square Pell.exists_of_not_isSquare
/-- If `d` is a positive integer, then there is a nontrivial solution
to the Pell equation `x^2 - d*y^2 = 1` if and only if `d` is not a square. -/
theorem exists_iff_not_isSquare (h₀ : 0 < d) :
(∃ x y : ℤ, x ^ 2 - d * y ^ 2 = 1 ∧ y ≠ 0) ↔ ¬IsSquare d := by
refine ⟨?_, exists_of_not_isSquare h₀⟩
rintro ⟨x, y, hxy, hy⟩ ⟨a, rfl⟩
rw [← sq, ← mul_pow, sq_sub_sq] at hxy
simpa [hy, mul_self_pos.mp h₀, sub_eq_add_neg, eq_neg_self_iff] using Int.eq_of_mul_eq_one hxy
#align pell.exists_iff_not_is_square Pell.exists_iff_not_isSquare
namespace Solution₁
/-- If `d` is a positive integer that is not a square, then there exists a nontrivial solution
to the Pell equation `x^2 - d*y^2 = 1`. -/
theorem exists_nontrivial_of_not_isSquare (h₀ : 0 < d) (hd : ¬IsSquare d) :
∃ a : Solution₁ d, a ≠ 1 ∧ a ≠ -1 := by
obtain ⟨x, y, prop, hy⟩ := exists_of_not_isSquare h₀ hd
refine ⟨mk x y prop, fun H => ?_, fun H => ?_⟩ <;> apply_fun Solution₁.y at H <;>
simp [hy] at H
#align pell.solution₁.exists_nontrivial_of_not_is_square Pell.Solution₁.exists_nontrivial_of_not_isSquare
/-- If `d` is a positive integer that is not a square, then there exists a solution
to the Pell equation `x^2 - d*y^2 = 1` with `x > 1` and `y > 0`. -/
theorem exists_pos_of_not_isSquare (h₀ : 0 < d) (hd : ¬IsSquare d) :
∃ a : Solution₁ d, 1 < a.x ∧ 0 < a.y := by
obtain ⟨x, y, h, hy⟩ := exists_of_not_isSquare h₀ hd
refine ⟨mk |x| |y| (by rwa [sq_abs, sq_abs]), ?_, abs_pos.mpr hy⟩
rw [x_mk, ← one_lt_sq_iff_one_lt_abs, eq_add_of_sub_eq h, lt_add_iff_pos_right]
exact mul_pos h₀ (sq_pos_of_ne_zero hy)
#align pell.solution₁.exists_pos_of_not_is_square Pell.Solution₁.exists_pos_of_not_isSquare
end Solution₁
end Existence
/-! ### Fundamental solutions
We define the notion of a *fundamental solution* of Pell's equation and
show that it exists and is unique (when `d` is positive and non-square)
and generates the group of solutions up to sign.
-/
variable {d : ℤ}
/-- We define a solution to be *fundamental* if it has `x > 1` and `y > 0`
and its `x` is the smallest possible among solutions with `x > 1`. -/
def IsFundamental (a : Solution₁ d) : Prop :=
1 < a.x ∧ 0 < a.y ∧ ∀ {b : Solution₁ d}, 1 < b.x → a.x ≤ b.x
#align pell.is_fundamental Pell.IsFundamental
namespace IsFundamental
open Solution₁
/-- A fundamental solution has positive `x`. -/
theorem x_pos {a : Solution₁ d} (h : IsFundamental a) : 0 < a.x :=
zero_lt_one.trans h.1
#align pell.is_fundamental.x_pos Pell.IsFundamental.x_pos
/-- If a fundamental solution exists, then `d` must be positive. -/
theorem d_pos {a : Solution₁ d} (h : IsFundamental a) : 0 < d :=
d_pos_of_one_lt_x h.1
#align pell.is_fundamental.d_pos Pell.IsFundamental.d_pos
/-- If a fundamental solution exists, then `d` must be a non-square. -/
theorem d_nonsquare {a : Solution₁ d} (h : IsFundamental a) : ¬IsSquare d :=
d_nonsquare_of_one_lt_x h.1
#align pell.is_fundamental.d_nonsquare Pell.IsFundamental.d_nonsquare
/-- If there is a fundamental solution, it is unique. -/
theorem subsingleton {a b : Solution₁ d} (ha : IsFundamental a) (hb : IsFundamental b) : a = b := by
have hx := le_antisymm (ha.2.2 hb.1) (hb.2.2 ha.1)
refine Solution₁.ext hx ?_
have : d * a.y ^ 2 = d * b.y ^ 2 := by rw [a.prop_y, b.prop_y, hx]
exact (sq_eq_sq ha.2.1.le hb.2.1.le).mp (Int.eq_of_mul_eq_mul_left ha.d_pos.ne' this)
#align pell.is_fundamental.subsingleton Pell.IsFundamental.subsingleton
/-- If `d` is positive and not a square, then a fundamental solution exists. -/
theorem exists_of_not_isSquare (h₀ : 0 < d) (hd : ¬IsSquare d) :
∃ a : Solution₁ d, IsFundamental a := by
obtain ⟨a, ha₁, ha₂⟩ := exists_pos_of_not_isSquare h₀ hd
-- convert to `x : ℕ` to be able to use `Nat.find`
have P : ∃ x' : ℕ, 1 < x' ∧ ∃ y' : ℤ, 0 < y' ∧ (x' : ℤ) ^ 2 - d * y' ^ 2 = 1 := by
have hax := a.prop
lift a.x to ℕ using by positivity with ax
norm_cast at ha₁
exact ⟨ax, ha₁, a.y, ha₂, hax⟩
classical
-- to avoid having to show that the predicate is decidable
let x₁ := Nat.find P
obtain ⟨hx, y₁, hy₀, hy₁⟩ := Nat.find_spec P
refine ⟨mk x₁ y₁ hy₁, by rw [x_mk]; exact mod_cast hx, hy₀, fun {b} hb => ?_⟩
rw [x_mk]
have hb' := (Int.toNat_of_nonneg <| zero_le_one.trans hb.le).symm
have hb'' := hb
rw [hb'] at hb ⊢
norm_cast at hb ⊢
refine Nat.find_min' P ⟨hb, |b.y|, abs_pos.mpr <| y_ne_zero_of_one_lt_x hb'', ?_⟩
rw [← hb', sq_abs]
exact b.prop
#align pell.is_fundamental.exists_of_not_is_square Pell.IsFundamental.exists_of_not_isSquare
/-- The map sending an integer `n` to the `y`-coordinate of `a^n` for a fundamental
solution `a` is stritcly increasing. -/
theorem y_strictMono {a : Solution₁ d} (h : IsFundamental a) :
StrictMono fun n : ℤ => (a ^ n).y := by
have H : ∀ n : ℤ, 0 ≤ n → (a ^ n).y < (a ^ (n + 1)).y := by
intro n hn
rw [← sub_pos, zpow_add, zpow_one, y_mul, add_sub_assoc]
rw [show (a ^ n).y * a.x - (a ^ n).y = (a ^ n).y * (a.x - 1) by ring]
refine
add_pos_of_pos_of_nonneg (mul_pos (x_zpow_pos h.x_pos _) h.2.1)
(mul_nonneg ?_ (by rw [sub_nonneg]; exact h.1.le))
rcases hn.eq_or_lt with (rfl | hn)
· simp only [zpow_zero, y_one, le_refl]
· exact (y_zpow_pos h.x_pos h.2.1 hn).le
refine strictMono_int_of_lt_succ fun n => ?_
rcases le_or_lt 0 n with hn | hn
· exact H n hn
· let m : ℤ := -n - 1
have hm : n = -m - 1 := by simp only [m, neg_sub, sub_neg_eq_add, add_tsub_cancel_left]
rw [hm, sub_add_cancel, ← neg_add', zpow_neg, zpow_neg, y_inv, y_inv, neg_lt_neg_iff]
exact H _ (by omega)
#align pell.is_fundamental.y_strict_mono Pell.IsFundamental.y_strictMono
/-- If `a` is a fundamental solution, then `(a^m).y < (a^n).y` if and only if `m < n`. -/
theorem zpow_y_lt_iff_lt {a : Solution₁ d} (h : IsFundamental a) (m n : ℤ) :
(a ^ m).y < (a ^ n).y ↔ m < n := by
refine ⟨fun H => ?_, fun H => h.y_strictMono H⟩
contrapose! H
exact h.y_strictMono.monotone H
#align pell.is_fundamental.zpow_y_lt_iff_lt Pell.IsFundamental.zpow_y_lt_iff_lt
/-- The `n`th power of a fundamental solution is trivial if and only if `n = 0`. -/
theorem zpow_eq_one_iff {a : Solution₁ d} (h : IsFundamental a) (n : ℤ) : a ^ n = 1 ↔ n = 0 := by
rw [← zpow_zero a]
exact ⟨fun H => h.y_strictMono.injective (congr_arg Solution₁.y H), fun H => H ▸ rfl⟩
#align pell.is_fundamental.zpow_eq_one_iff Pell.IsFundamental.zpow_eq_one_iff
/-- A power of a fundamental solution is never equal to the negative of a power of this
fundamental solution. -/
theorem zpow_ne_neg_zpow {a : Solution₁ d} (h : IsFundamental a) {n n' : ℤ} : a ^ n ≠ -a ^ n' := by
intro hf
apply_fun Solution₁.x at hf
have H := x_zpow_pos h.x_pos n
rw [hf, x_neg, lt_neg, neg_zero] at H
exact lt_irrefl _ ((x_zpow_pos h.x_pos n').trans H)
#align pell.is_fundamental.zpow_ne_neg_zpow Pell.IsFundamental.zpow_ne_neg_zpow
/-- The `x`-coordinate of a fundamental solution is a lower bound for the `x`-coordinate
of any positive solution. -/
theorem x_le_x {a₁ : Solution₁ d} (h : IsFundamental a₁) {a : Solution₁ d} (hax : 1 < a.x) :
a₁.x ≤ a.x :=
h.2.2 hax
#align pell.is_fundamental.x_le_x Pell.IsFundamental.x_le_x
/-- The `y`-coordinate of a fundamental solution is a lower bound for the `y`-coordinate
of any positive solution. -/
theorem y_le_y {a₁ : Solution₁ d} (h : IsFundamental a₁) {a : Solution₁ d} (hax : 1 < a.x)
(hay : 0 < a.y) : a₁.y ≤ a.y := by
have H : d * (a₁.y ^ 2 - a.y ^ 2) = a₁.x ^ 2 - a.x ^ 2 := by rw [a.prop_x, a₁.prop_x]; ring
rw [← abs_of_pos hay, ← abs_of_pos h.2.1, ← sq_le_sq, ← mul_le_mul_left h.d_pos, ← sub_nonpos, ←
mul_sub, H, sub_nonpos, sq_le_sq, abs_of_pos (zero_lt_one.trans h.1),
abs_of_pos (zero_lt_one.trans hax)]
exact h.x_le_x hax
#align pell.is_fundamental.y_le_y Pell.IsFundamental.y_le_y
-- helper lemma for the next three results
theorem x_mul_y_le_y_mul_x {a₁ : Solution₁ d} (h : IsFundamental a₁) {a : Solution₁ d}
(hax : 1 < a.x) (hay : 0 < a.y) : a.x * a₁.y ≤ a.y * a₁.x := by
rw [← abs_of_pos <| zero_lt_one.trans hax, ← abs_of_pos hay, ← abs_of_pos h.x_pos, ←
abs_of_pos h.2.1, ← abs_mul, ← abs_mul, ← sq_le_sq, mul_pow, mul_pow, a.prop_x, a₁.prop_x, ←
sub_nonneg]
ring_nf
rw [sub_nonneg, sq_le_sq, abs_of_pos hay, abs_of_pos h.2.1]
exact h.y_le_y hax hay
#align pell.is_fundamental.x_mul_y_le_y_mul_x Pell.IsFundamental.x_mul_y_le_y_mul_x
/-- If we multiply a positive solution with the inverse of a fundamental solution,
the `y`-coordinate remains nonnegative. -/
theorem mul_inv_y_nonneg {a₁ : Solution₁ d} (h : IsFundamental a₁) {a : Solution₁ d} (hax : 1 < a.x)
(hay : 0 < a.y) : 0 ≤ (a * a₁⁻¹).y := by
simpa only [y_inv, mul_neg, y_mul, le_neg_add_iff_add_le, add_zero] using
h.x_mul_y_le_y_mul_x hax hay
#align pell.is_fundamental.mul_inv_y_nonneg Pell.IsFundamental.mul_inv_y_nonneg
/-- If we multiply a positive solution with the inverse of a fundamental solution,
the `x`-coordinate stays positive. -/
theorem mul_inv_x_pos {a₁ : Solution₁ d} (h : IsFundamental a₁) {a : Solution₁ d} (hax : 1 < a.x)
(hay : 0 < a.y) : 0 < (a * a₁⁻¹).x := by
simp only [x_mul, x_inv, y_inv, mul_neg, lt_add_neg_iff_add_lt, zero_add]
refine (mul_lt_mul_left <| zero_lt_one.trans hax).mp ?_
rw [(by ring : a.x * (d * (a.y * a₁.y)) = d * a.y * (a.x * a₁.y))]
refine ((mul_le_mul_left <| mul_pos h.d_pos hay).mpr <| x_mul_y_le_y_mul_x h hax hay).trans_lt ?_
rw [← mul_assoc, mul_assoc d, ← sq, a.prop_y, ← sub_pos]
ring_nf
exact zero_lt_one.trans h.1
#align pell.is_fundamental.mul_inv_x_pos Pell.IsFundamental.mul_inv_x_pos
/-- If we multiply a positive solution with the inverse of a fundamental solution,
the `x`-coordinate decreases. -/
| Mathlib/NumberTheory/Pell.lean | 639 | 657 | theorem mul_inv_x_lt_x {a₁ : Solution₁ d} (h : IsFundamental a₁) {a : Solution₁ d} (hax : 1 < a.x)
(hay : 0 < a.y) : (a * a₁⁻¹).x < a.x := by |
simp only [x_mul, x_inv, y_inv, mul_neg, add_neg_lt_iff_le_add']
refine (mul_lt_mul_left h.2.1).mp ?_
rw [(by ring : a₁.y * (a.x * a₁.x) = a.x * a₁.y * a₁.x)]
refine
((mul_le_mul_right <| zero_lt_one.trans h.1).mpr <| x_mul_y_le_y_mul_x h hax hay).trans_lt ?_
rw [mul_assoc, ← sq, a₁.prop_x, ← sub_neg]
-- Porting note: was `ring_nf`
suffices a.y - a.x * a₁.y < 0 by convert this using 1; ring
rw [sub_neg, ← abs_of_pos hay, ← abs_of_pos h.2.1, ← abs_of_pos <| zero_lt_one.trans hax, ←
abs_mul, ← sq_lt_sq, mul_pow, a.prop_x]
calc
a.y ^ 2 = 1 * a.y ^ 2 := (one_mul _).symm
_ ≤ d * a.y ^ 2 := (mul_le_mul_right <| sq_pos_of_pos hay).mpr h.d_pos
_ < d * a.y ^ 2 + 1 := lt_add_one _
_ = (1 + d * a.y ^ 2) * 1 := by rw [add_comm, mul_one]
_ ≤ (1 + d * a.y ^ 2) * a₁.y ^ 2 :=
(mul_le_mul_left (by have := h.d_pos; positivity)).mpr (sq_pos_of_pos h.2.1)
|
/-
Copyright (c) 2022 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Analysis.LocallyConvex.Bounded
import Mathlib.Topology.Algebra.Module.StrongTopology
#align_import analysis.normed_space.compact_operator from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Compact operators
In this file we define compact linear operators between two topological vector spaces (TVS).
## Main definitions
* `IsCompactOperator` : predicate for compact operators
## Main statements
* `isCompactOperator_iff_isCompact_closure_image_ball` : the usual characterization of
compact operators from a normed space to a T2 TVS.
* `IsCompactOperator.comp_clm` : precomposing a compact operator by a continuous linear map gives
a compact operator
* `IsCompactOperator.clm_comp` : postcomposing a compact operator by a continuous linear map
gives a compact operator
* `IsCompactOperator.continuous` : compact operators are automatically continuous
* `isClosed_setOf_isCompactOperator` : the set of compact operators is closed for the operator
norm
## Implementation details
We define `IsCompactOperator` as a predicate, because the space of compact operators inherits all
of its structure from the space of continuous linear maps (e.g we want to have the usual operator
norm on compact operators).
The two natural options then would be to make it a predicate over linear maps or continuous linear
maps. Instead we define it as a predicate over bare functions, although it really only makes sense
for linear functions, because Lean is really good at finding coercions to bare functions (whereas
coercing from continuous linear maps to linear maps often needs type ascriptions).
## References
* [N. Bourbaki, *Théories Spectrales*, Chapitre 3][bourbaki2023]
## Tags
Compact operator
-/
open Function Set Filter Bornology Metric Pointwise Topology
/-- A compact operator between two topological vector spaces. This definition is usually
given as "there exists a neighborhood of zero whose image is contained in a compact set",
but we choose a definition which involves fewer existential quantifiers and replaces images
with preimages.
We prove the equivalence in `isCompactOperator_iff_exists_mem_nhds_image_subset_compact`. -/
def IsCompactOperator {M₁ M₂ : Type*} [Zero M₁] [TopologicalSpace M₁] [TopologicalSpace M₂]
(f : M₁ → M₂) : Prop :=
∃ K, IsCompact K ∧ f ⁻¹' K ∈ (𝓝 0 : Filter M₁)
#align is_compact_operator IsCompactOperator
theorem isCompactOperator_zero {M₁ M₂ : Type*} [Zero M₁] [TopologicalSpace M₁]
[TopologicalSpace M₂] [Zero M₂] : IsCompactOperator (0 : M₁ → M₂) :=
⟨{0}, isCompact_singleton, mem_of_superset univ_mem fun _ _ => rfl⟩
#align is_compact_operator_zero isCompactOperator_zero
section Characterizations
section
variable {R₁ R₂ : Type*} [Semiring R₁] [Semiring R₂] {σ₁₂ : R₁ →+* R₂} {M₁ M₂ : Type*}
[TopologicalSpace M₁] [AddCommMonoid M₁] [TopologicalSpace M₂]
theorem isCompactOperator_iff_exists_mem_nhds_image_subset_compact (f : M₁ → M₂) :
IsCompactOperator f ↔ ∃ V ∈ (𝓝 0 : Filter M₁), ∃ K : Set M₂, IsCompact K ∧ f '' V ⊆ K :=
⟨fun ⟨K, hK, hKf⟩ => ⟨f ⁻¹' K, hKf, K, hK, image_preimage_subset _ _⟩, fun ⟨_, hV, K, hK, hVK⟩ =>
⟨K, hK, mem_of_superset hV (image_subset_iff.mp hVK)⟩⟩
#align is_compact_operator_iff_exists_mem_nhds_image_subset_compact isCompactOperator_iff_exists_mem_nhds_image_subset_compact
| Mathlib/Analysis/NormedSpace/CompactOperator.lean | 84 | 89 | theorem isCompactOperator_iff_exists_mem_nhds_isCompact_closure_image [T2Space M₂] (f : M₁ → M₂) :
IsCompactOperator f ↔ ∃ V ∈ (𝓝 0 : Filter M₁), IsCompact (closure <| f '' V) := by |
rw [isCompactOperator_iff_exists_mem_nhds_image_subset_compact]
exact
⟨fun ⟨V, hV, K, hK, hKV⟩ => ⟨V, hV, hK.closure_of_subset hKV⟩,
fun ⟨V, hV, hVc⟩ => ⟨V, hV, closure (f '' V), hVc, subset_closure⟩⟩
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.Algebra.Tower
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.Regular.Pow
import Mathlib.Algebra.MonoidAlgebra.Support
import Mathlib.Data.Finsupp.Antidiagonal
import Mathlib.Order.SymmDiff
import Mathlib.RingTheory.Adjoin.Basic
#align_import data.mv_polynomial.basic from "leanprover-community/mathlib"@"c8734e8953e4b439147bd6f75c2163f6d27cdce6"
/-!
# Multivariate polynomials
This file defines polynomial rings over a base ring (or even semiring),
with variables from a general type `σ` (which could be infinite).
## Important definitions
Let `R` be a commutative ring (or a semiring) and let `σ` be an arbitrary
type. This file creates the type `MvPolynomial σ R`, which mathematicians
might denote $R[X_i : i \in σ]$. It is the type of multivariate
(a.k.a. multivariable) polynomials, with variables
corresponding to the terms in `σ`, and coefficients in `R`.
### Notation
In the definitions below, we use the following notation:
+ `σ : Type*` (indexing the variables)
+ `R : Type*` `[CommSemiring R]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `a : R`
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ R`
### Definitions
* `MvPolynomial σ R` : the type of polynomials with variables of type `σ` and coefficients
in the commutative semiring `R`
* `monomial s a` : the monomial which mathematically would be denoted `a * X^s`
* `C a` : the constant polynomial with value `a`
* `X i` : the degree one monomial corresponding to i; mathematically this might be denoted `Xᵢ`.
* `coeff s p` : the coefficient of `s` in `p`.
* `eval₂ (f : R → S₁) (g : σ → S₁) p` : given a semiring homomorphism from `R` to another
semiring `S₁`, and a map `σ → S₁`, evaluates `p` at this valuation, returning a term of type `S₁`.
Note that `eval₂` can be made using `eval` and `map` (see below), and it has been suggested
that sticking to `eval` and `map` might make the code less brittle.
* `eval (g : σ → R) p` : given a map `σ → R`, evaluates `p` at this valuation,
returning a term of type `R`
* `map (f : R → S₁) p` : returns the multivariate polynomial obtained from `p` by the change of
coefficient semiring corresponding to `f`
## Implementation notes
Recall that if `Y` has a zero, then `X →₀ Y` is the type of functions from `X` to `Y` with finite
support, i.e. such that only finitely many elements of `X` get sent to non-zero terms in `Y`.
The definition of `MvPolynomial σ R` is `(σ →₀ ℕ) →₀ R`; here `σ →₀ ℕ` denotes the space of all
monomials in the variables, and the function to `R` sends a monomial to its coefficient in
the polynomial being represented.
## Tags
polynomial, multivariate polynomial, multivariable polynomial
-/
noncomputable section
open Set Function Finsupp AddMonoidAlgebra
open scoped Pointwise
universe u v w x
variable {R : Type u} {S₁ : Type v} {S₂ : Type w} {S₃ : Type x}
/-- Multivariate polynomial, where `σ` is the index set of the variables and
`R` is the coefficient ring -/
def MvPolynomial (σ : Type*) (R : Type*) [CommSemiring R] :=
AddMonoidAlgebra R (σ →₀ ℕ)
#align mv_polynomial MvPolynomial
namespace MvPolynomial
-- Porting note: because of `MvPolynomial.C` and `MvPolynomial.X` this linter throws
-- tons of warnings in this file, and it's easier to just disable them globally in the file
set_option linter.uppercaseLean3 false
variable {σ : Type*} {a a' a₁ a₂ : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ}
section CommSemiring
section Instances
instance decidableEqMvPolynomial [CommSemiring R] [DecidableEq σ] [DecidableEq R] :
DecidableEq (MvPolynomial σ R) :=
Finsupp.instDecidableEq
#align mv_polynomial.decidable_eq_mv_polynomial MvPolynomial.decidableEqMvPolynomial
instance commSemiring [CommSemiring R] : CommSemiring (MvPolynomial σ R) :=
AddMonoidAlgebra.commSemiring
instance inhabited [CommSemiring R] : Inhabited (MvPolynomial σ R) :=
⟨0⟩
instance distribuMulAction [Monoid R] [CommSemiring S₁] [DistribMulAction R S₁] :
DistribMulAction R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.distribMulAction
instance smulZeroClass [CommSemiring S₁] [SMulZeroClass R S₁] :
SMulZeroClass R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.smulZeroClass
instance faithfulSMul [CommSemiring S₁] [SMulZeroClass R S₁] [FaithfulSMul R S₁] :
FaithfulSMul R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.faithfulSMul
instance module [Semiring R] [CommSemiring S₁] [Module R S₁] : Module R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.module
instance isScalarTower [CommSemiring S₂] [SMul R S₁] [SMulZeroClass R S₂] [SMulZeroClass S₁ S₂]
[IsScalarTower R S₁ S₂] : IsScalarTower R S₁ (MvPolynomial σ S₂) :=
AddMonoidAlgebra.isScalarTower
instance smulCommClass [CommSemiring S₂] [SMulZeroClass R S₂] [SMulZeroClass S₁ S₂]
[SMulCommClass R S₁ S₂] : SMulCommClass R S₁ (MvPolynomial σ S₂) :=
AddMonoidAlgebra.smulCommClass
instance isCentralScalar [CommSemiring S₁] [SMulZeroClass R S₁] [SMulZeroClass Rᵐᵒᵖ S₁]
[IsCentralScalar R S₁] : IsCentralScalar R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.isCentralScalar
instance algebra [CommSemiring R] [CommSemiring S₁] [Algebra R S₁] :
Algebra R (MvPolynomial σ S₁) :=
AddMonoidAlgebra.algebra
instance isScalarTower_right [CommSemiring S₁] [DistribSMul R S₁] [IsScalarTower R S₁ S₁] :
IsScalarTower R (MvPolynomial σ S₁) (MvPolynomial σ S₁) :=
AddMonoidAlgebra.isScalarTower_self _
#align mv_polynomial.is_scalar_tower_right MvPolynomial.isScalarTower_right
instance smulCommClass_right [CommSemiring S₁] [DistribSMul R S₁] [SMulCommClass R S₁ S₁] :
SMulCommClass R (MvPolynomial σ S₁) (MvPolynomial σ S₁) :=
AddMonoidAlgebra.smulCommClass_self _
#align mv_polynomial.smul_comm_class_right MvPolynomial.smulCommClass_right
/-- If `R` is a subsingleton, then `MvPolynomial σ R` has a unique element -/
instance unique [CommSemiring R] [Subsingleton R] : Unique (MvPolynomial σ R) :=
AddMonoidAlgebra.unique
#align mv_polynomial.unique MvPolynomial.unique
end Instances
variable [CommSemiring R] [CommSemiring S₁] {p q : MvPolynomial σ R}
/-- `monomial s a` is the monomial with coefficient `a` and exponents given by `s` -/
def monomial (s : σ →₀ ℕ) : R →ₗ[R] MvPolynomial σ R :=
lsingle s
#align mv_polynomial.monomial MvPolynomial.monomial
theorem single_eq_monomial (s : σ →₀ ℕ) (a : R) : Finsupp.single s a = monomial s a :=
rfl
#align mv_polynomial.single_eq_monomial MvPolynomial.single_eq_monomial
theorem mul_def : p * q = p.sum fun m a => q.sum fun n b => monomial (m + n) (a * b) :=
AddMonoidAlgebra.mul_def
#align mv_polynomial.mul_def MvPolynomial.mul_def
/-- `C a` is the constant polynomial with value `a` -/
def C : R →+* MvPolynomial σ R :=
{ singleZeroRingHom with toFun := monomial 0 }
#align mv_polynomial.C MvPolynomial.C
variable (R σ)
@[simp]
theorem algebraMap_eq : algebraMap R (MvPolynomial σ R) = C :=
rfl
#align mv_polynomial.algebra_map_eq MvPolynomial.algebraMap_eq
variable {R σ}
/-- `X n` is the degree `1` monomial $X_n$. -/
def X (n : σ) : MvPolynomial σ R :=
monomial (Finsupp.single n 1) 1
#align mv_polynomial.X MvPolynomial.X
theorem monomial_left_injective {r : R} (hr : r ≠ 0) :
Function.Injective fun s : σ →₀ ℕ => monomial s r :=
Finsupp.single_left_injective hr
#align mv_polynomial.monomial_left_injective MvPolynomial.monomial_left_injective
@[simp]
theorem monomial_left_inj {s t : σ →₀ ℕ} {r : R} (hr : r ≠ 0) :
monomial s r = monomial t r ↔ s = t :=
Finsupp.single_left_inj hr
#align mv_polynomial.monomial_left_inj MvPolynomial.monomial_left_inj
theorem C_apply : (C a : MvPolynomial σ R) = monomial 0 a :=
rfl
#align mv_polynomial.C_apply MvPolynomial.C_apply
-- Porting note (#10618): `simp` can prove this
theorem C_0 : C 0 = (0 : MvPolynomial σ R) := map_zero _
#align mv_polynomial.C_0 MvPolynomial.C_0
-- Porting note (#10618): `simp` can prove this
theorem C_1 : C 1 = (1 : MvPolynomial σ R) :=
rfl
#align mv_polynomial.C_1 MvPolynomial.C_1
theorem C_mul_monomial : C a * monomial s a' = monomial s (a * a') := by
-- Porting note: this `show` feels like defeq abuse, but I can't find the appropriate lemmas
show AddMonoidAlgebra.single _ _ * AddMonoidAlgebra.single _ _ = AddMonoidAlgebra.single _ _
simp [C_apply, single_mul_single]
#align mv_polynomial.C_mul_monomial MvPolynomial.C_mul_monomial
-- Porting note (#10618): `simp` can prove this
theorem C_add : (C (a + a') : MvPolynomial σ R) = C a + C a' :=
Finsupp.single_add _ _ _
#align mv_polynomial.C_add MvPolynomial.C_add
-- Porting note (#10618): `simp` can prove this
theorem C_mul : (C (a * a') : MvPolynomial σ R) = C a * C a' :=
C_mul_monomial.symm
#align mv_polynomial.C_mul MvPolynomial.C_mul
-- Porting note (#10618): `simp` can prove this
theorem C_pow (a : R) (n : ℕ) : (C (a ^ n) : MvPolynomial σ R) = C a ^ n :=
map_pow _ _ _
#align mv_polynomial.C_pow MvPolynomial.C_pow
theorem C_injective (σ : Type*) (R : Type*) [CommSemiring R] :
Function.Injective (C : R → MvPolynomial σ R) :=
Finsupp.single_injective _
#align mv_polynomial.C_injective MvPolynomial.C_injective
theorem C_surjective {R : Type*} [CommSemiring R] (σ : Type*) [IsEmpty σ] :
Function.Surjective (C : R → MvPolynomial σ R) := by
refine fun p => ⟨p.toFun 0, Finsupp.ext fun a => ?_⟩
simp only [C_apply, ← single_eq_monomial, (Finsupp.ext isEmptyElim (α := σ) : a = 0),
single_eq_same]
rfl
#align mv_polynomial.C_surjective MvPolynomial.C_surjective
@[simp]
theorem C_inj {σ : Type*} (R : Type*) [CommSemiring R] (r s : R) :
(C r : MvPolynomial σ R) = C s ↔ r = s :=
(C_injective σ R).eq_iff
#align mv_polynomial.C_inj MvPolynomial.C_inj
instance nontrivial_of_nontrivial (σ : Type*) (R : Type*) [CommSemiring R] [Nontrivial R] :
Nontrivial (MvPolynomial σ R) :=
inferInstanceAs (Nontrivial <| AddMonoidAlgebra R (σ →₀ ℕ))
instance infinite_of_infinite (σ : Type*) (R : Type*) [CommSemiring R] [Infinite R] :
Infinite (MvPolynomial σ R) :=
Infinite.of_injective C (C_injective _ _)
#align mv_polynomial.infinite_of_infinite MvPolynomial.infinite_of_infinite
instance infinite_of_nonempty (σ : Type*) (R : Type*) [Nonempty σ] [CommSemiring R]
[Nontrivial R] : Infinite (MvPolynomial σ R) :=
Infinite.of_injective ((fun s : σ →₀ ℕ => monomial s 1) ∘ Finsupp.single (Classical.arbitrary σ))
<| (monomial_left_injective one_ne_zero).comp (Finsupp.single_injective _)
#align mv_polynomial.infinite_of_nonempty MvPolynomial.infinite_of_nonempty
theorem C_eq_coe_nat (n : ℕ) : (C ↑n : MvPolynomial σ R) = n := by
induction n <;> simp [Nat.succ_eq_add_one, *]
#align mv_polynomial.C_eq_coe_nat MvPolynomial.C_eq_coe_nat
theorem C_mul' : MvPolynomial.C a * p = a • p :=
(Algebra.smul_def a p).symm
#align mv_polynomial.C_mul' MvPolynomial.C_mul'
theorem smul_eq_C_mul (p : MvPolynomial σ R) (a : R) : a • p = C a * p :=
C_mul'.symm
#align mv_polynomial.smul_eq_C_mul MvPolynomial.smul_eq_C_mul
theorem C_eq_smul_one : (C a : MvPolynomial σ R) = a • (1 : MvPolynomial σ R) := by
rw [← C_mul', mul_one]
#align mv_polynomial.C_eq_smul_one MvPolynomial.C_eq_smul_one
theorem smul_monomial {S₁ : Type*} [SMulZeroClass S₁ R] (r : S₁) :
r • monomial s a = monomial s (r • a) :=
Finsupp.smul_single _ _ _
#align mv_polynomial.smul_monomial MvPolynomial.smul_monomial
theorem X_injective [Nontrivial R] : Function.Injective (X : σ → MvPolynomial σ R) :=
(monomial_left_injective one_ne_zero).comp (Finsupp.single_left_injective one_ne_zero)
#align mv_polynomial.X_injective MvPolynomial.X_injective
@[simp]
theorem X_inj [Nontrivial R] (m n : σ) : X m = (X n : MvPolynomial σ R) ↔ m = n :=
X_injective.eq_iff
#align mv_polynomial.X_inj MvPolynomial.X_inj
theorem monomial_pow : monomial s a ^ e = monomial (e • s) (a ^ e) :=
AddMonoidAlgebra.single_pow e
#align mv_polynomial.monomial_pow MvPolynomial.monomial_pow
@[simp]
theorem monomial_mul {s s' : σ →₀ ℕ} {a b : R} :
monomial s a * monomial s' b = monomial (s + s') (a * b) :=
AddMonoidAlgebra.single_mul_single
#align mv_polynomial.monomial_mul MvPolynomial.monomial_mul
variable (σ R)
/-- `fun s ↦ monomial s 1` as a homomorphism. -/
def monomialOneHom : Multiplicative (σ →₀ ℕ) →* MvPolynomial σ R :=
AddMonoidAlgebra.of _ _
#align mv_polynomial.monomial_one_hom MvPolynomial.monomialOneHom
variable {σ R}
@[simp]
theorem monomialOneHom_apply : monomialOneHom R σ s = (monomial s 1 : MvPolynomial σ R) :=
rfl
#align mv_polynomial.monomial_one_hom_apply MvPolynomial.monomialOneHom_apply
theorem X_pow_eq_monomial : X n ^ e = monomial (Finsupp.single n e) (1 : R) := by
simp [X, monomial_pow]
#align mv_polynomial.X_pow_eq_monomial MvPolynomial.X_pow_eq_monomial
theorem monomial_add_single : monomial (s + Finsupp.single n e) a = monomial s a * X n ^ e := by
rw [X_pow_eq_monomial, monomial_mul, mul_one]
#align mv_polynomial.monomial_add_single MvPolynomial.monomial_add_single
theorem monomial_single_add : monomial (Finsupp.single n e + s) a = X n ^ e * monomial s a := by
rw [X_pow_eq_monomial, monomial_mul, one_mul]
#align mv_polynomial.monomial_single_add MvPolynomial.monomial_single_add
theorem C_mul_X_pow_eq_monomial {s : σ} {a : R} {n : ℕ} :
C a * X s ^ n = monomial (Finsupp.single s n) a := by
rw [← zero_add (Finsupp.single s n), monomial_add_single, C_apply]
#align mv_polynomial.C_mul_X_pow_eq_monomial MvPolynomial.C_mul_X_pow_eq_monomial
theorem C_mul_X_eq_monomial {s : σ} {a : R} : C a * X s = monomial (Finsupp.single s 1) a := by
rw [← C_mul_X_pow_eq_monomial, pow_one]
#align mv_polynomial.C_mul_X_eq_monomial MvPolynomial.C_mul_X_eq_monomial
-- Porting note (#10618): `simp` can prove this
theorem monomial_zero {s : σ →₀ ℕ} : monomial s (0 : R) = 0 :=
Finsupp.single_zero _
#align mv_polynomial.monomial_zero MvPolynomial.monomial_zero
@[simp]
theorem monomial_zero' : (monomial (0 : σ →₀ ℕ) : R → MvPolynomial σ R) = C :=
rfl
#align mv_polynomial.monomial_zero' MvPolynomial.monomial_zero'
@[simp]
theorem monomial_eq_zero {s : σ →₀ ℕ} {b : R} : monomial s b = 0 ↔ b = 0 :=
Finsupp.single_eq_zero
#align mv_polynomial.monomial_eq_zero MvPolynomial.monomial_eq_zero
@[simp]
theorem sum_monomial_eq {A : Type*} [AddCommMonoid A] {u : σ →₀ ℕ} {r : R} {b : (σ →₀ ℕ) → R → A}
(w : b u 0 = 0) : sum (monomial u r) b = b u r :=
Finsupp.sum_single_index w
#align mv_polynomial.sum_monomial_eq MvPolynomial.sum_monomial_eq
@[simp]
theorem sum_C {A : Type*} [AddCommMonoid A] {b : (σ →₀ ℕ) → R → A} (w : b 0 0 = 0) :
sum (C a) b = b 0 a :=
sum_monomial_eq w
#align mv_polynomial.sum_C MvPolynomial.sum_C
theorem monomial_sum_one {α : Type*} (s : Finset α) (f : α → σ →₀ ℕ) :
(monomial (∑ i ∈ s, f i) 1 : MvPolynomial σ R) = ∏ i ∈ s, monomial (f i) 1 :=
map_prod (monomialOneHom R σ) (fun i => Multiplicative.ofAdd (f i)) s
#align mv_polynomial.monomial_sum_one MvPolynomial.monomial_sum_one
theorem monomial_sum_index {α : Type*} (s : Finset α) (f : α → σ →₀ ℕ) (a : R) :
monomial (∑ i ∈ s, f i) a = C a * ∏ i ∈ s, monomial (f i) 1 := by
rw [← monomial_sum_one, C_mul', ← (monomial _).map_smul, smul_eq_mul, mul_one]
#align mv_polynomial.monomial_sum_index MvPolynomial.monomial_sum_index
theorem monomial_finsupp_sum_index {α β : Type*} [Zero β] (f : α →₀ β) (g : α → β → σ →₀ ℕ)
(a : R) : monomial (f.sum g) a = C a * f.prod fun a b => monomial (g a b) 1 :=
monomial_sum_index _ _ _
#align mv_polynomial.monomial_finsupp_sum_index MvPolynomial.monomial_finsupp_sum_index
theorem monomial_eq_monomial_iff {α : Type*} (a₁ a₂ : α →₀ ℕ) (b₁ b₂ : R) :
monomial a₁ b₁ = monomial a₂ b₂ ↔ a₁ = a₂ ∧ b₁ = b₂ ∨ b₁ = 0 ∧ b₂ = 0 :=
Finsupp.single_eq_single_iff _ _ _ _
#align mv_polynomial.monomial_eq_monomial_iff MvPolynomial.monomial_eq_monomial_iff
theorem monomial_eq : monomial s a = C a * (s.prod fun n e => X n ^ e : MvPolynomial σ R) := by
simp only [X_pow_eq_monomial, ← monomial_finsupp_sum_index, Finsupp.sum_single]
#align mv_polynomial.monomial_eq MvPolynomial.monomial_eq
@[simp]
lemma prod_X_pow_eq_monomial : ∏ x ∈ s.support, X x ^ s x = monomial s (1 : R) := by
simp only [monomial_eq, map_one, one_mul, Finsupp.prod]
theorem induction_on_monomial {M : MvPolynomial σ R → Prop} (h_C : ∀ a, M (C a))
(h_X : ∀ p n, M p → M (p * X n)) : ∀ s a, M (monomial s a) := by
intro s a
apply @Finsupp.induction σ ℕ _ _ s
· show M (monomial 0 a)
exact h_C a
· intro n e p _hpn _he ih
have : ∀ e : ℕ, M (monomial p a * X n ^ e) := by
intro e
induction e with
| zero => simp [ih]
| succ e e_ih => simp [ih, pow_succ, (mul_assoc _ _ _).symm, h_X, e_ih]
simp [add_comm, monomial_add_single, this]
#align mv_polynomial.induction_on_monomial MvPolynomial.induction_on_monomial
/-- Analog of `Polynomial.induction_on'`.
To prove something about mv_polynomials,
it suffices to show the condition is closed under taking sums,
and it holds for monomials. -/
@[elab_as_elim]
theorem induction_on' {P : MvPolynomial σ R → Prop} (p : MvPolynomial σ R)
(h1 : ∀ (u : σ →₀ ℕ) (a : R), P (monomial u a))
(h2 : ∀ p q : MvPolynomial σ R, P p → P q → P (p + q)) : P p :=
Finsupp.induction p
(suffices P (monomial 0 0) by rwa [monomial_zero] at this
show P (monomial 0 0) from h1 0 0)
fun a b f _ha _hb hPf => h2 _ _ (h1 _ _) hPf
#align mv_polynomial.induction_on' MvPolynomial.induction_on'
/-- Similar to `MvPolynomial.induction_on` but only a weak form of `h_add` is required. -/
theorem induction_on''' {M : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (h_C : ∀ a, M (C a))
(h_add_weak :
∀ (a : σ →₀ ℕ) (b : R) (f : (σ →₀ ℕ) →₀ R),
a ∉ f.support → b ≠ 0 → M f → M ((show (σ →₀ ℕ) →₀ R from monomial a b) + f)) :
M p :=
-- Porting note: I had to add the `show ... from ...` above, a type ascription was insufficient.
Finsupp.induction p (C_0.rec <| h_C 0) h_add_weak
#align mv_polynomial.induction_on''' MvPolynomial.induction_on'''
/-- Similar to `MvPolynomial.induction_on` but only a yet weaker form of `h_add` is required. -/
theorem induction_on'' {M : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (h_C : ∀ a, M (C a))
(h_add_weak :
∀ (a : σ →₀ ℕ) (b : R) (f : (σ →₀ ℕ) →₀ R),
a ∉ f.support → b ≠ 0 → M f → M (monomial a b) →
M ((show (σ →₀ ℕ) →₀ R from monomial a b) + f))
(h_X : ∀ (p : MvPolynomial σ R) (n : σ), M p → M (p * MvPolynomial.X n)) : M p :=
-- Porting note: I had to add the `show ... from ...` above, a type ascription was insufficient.
induction_on''' p h_C fun a b f ha hb hf =>
h_add_weak a b f ha hb hf <| induction_on_monomial h_C h_X a b
#align mv_polynomial.induction_on'' MvPolynomial.induction_on''
/-- Analog of `Polynomial.induction_on`. -/
@[recursor 5]
theorem induction_on {M : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (h_C : ∀ a, M (C a))
(h_add : ∀ p q, M p → M q → M (p + q)) (h_X : ∀ p n, M p → M (p * X n)) : M p :=
induction_on'' p h_C (fun a b f _ha _hb hf hm => h_add (monomial a b) f hm hf) h_X
#align mv_polynomial.induction_on MvPolynomial.induction_on
theorem ringHom_ext {A : Type*} [Semiring A] {f g : MvPolynomial σ R →+* A}
(hC : ∀ r, f (C r) = g (C r)) (hX : ∀ i, f (X i) = g (X i)) : f = g := by
refine AddMonoidAlgebra.ringHom_ext' ?_ ?_
-- Porting note: this has high priority, but Lean still chooses `RingHom.ext`, why?
-- probably because of the type synonym
· ext x
exact hC _
· apply Finsupp.mulHom_ext'; intros x
-- Porting note: `Finsupp.mulHom_ext'` needs to have increased priority
apply MonoidHom.ext_mnat
exact hX _
#align mv_polynomial.ring_hom_ext MvPolynomial.ringHom_ext
/-- See note [partially-applied ext lemmas]. -/
@[ext 1100]
theorem ringHom_ext' {A : Type*} [Semiring A] {f g : MvPolynomial σ R →+* A}
(hC : f.comp C = g.comp C) (hX : ∀ i, f (X i) = g (X i)) : f = g :=
ringHom_ext (RingHom.ext_iff.1 hC) hX
#align mv_polynomial.ring_hom_ext' MvPolynomial.ringHom_ext'
theorem hom_eq_hom [Semiring S₂] (f g : MvPolynomial σ R →+* S₂) (hC : f.comp C = g.comp C)
(hX : ∀ n : σ, f (X n) = g (X n)) (p : MvPolynomial σ R) : f p = g p :=
RingHom.congr_fun (ringHom_ext' hC hX) p
#align mv_polynomial.hom_eq_hom MvPolynomial.hom_eq_hom
theorem is_id (f : MvPolynomial σ R →+* MvPolynomial σ R) (hC : f.comp C = C)
(hX : ∀ n : σ, f (X n) = X n) (p : MvPolynomial σ R) : f p = p :=
hom_eq_hom f (RingHom.id _) hC hX p
#align mv_polynomial.is_id MvPolynomial.is_id
@[ext 1100]
theorem algHom_ext' {A B : Type*} [CommSemiring A] [CommSemiring B] [Algebra R A] [Algebra R B]
{f g : MvPolynomial σ A →ₐ[R] B}
(h₁ :
f.comp (IsScalarTower.toAlgHom R A (MvPolynomial σ A)) =
g.comp (IsScalarTower.toAlgHom R A (MvPolynomial σ A)))
(h₂ : ∀ i, f (X i) = g (X i)) : f = g :=
AlgHom.coe_ringHom_injective (MvPolynomial.ringHom_ext' (congr_arg AlgHom.toRingHom h₁) h₂)
#align mv_polynomial.alg_hom_ext' MvPolynomial.algHom_ext'
@[ext 1200]
theorem algHom_ext {A : Type*} [Semiring A] [Algebra R A] {f g : MvPolynomial σ R →ₐ[R] A}
(hf : ∀ i : σ, f (X i) = g (X i)) : f = g :=
AddMonoidAlgebra.algHom_ext' (mulHom_ext' fun X : σ => MonoidHom.ext_mnat (hf X))
#align mv_polynomial.alg_hom_ext MvPolynomial.algHom_ext
@[simp]
theorem algHom_C {τ : Type*} (f : MvPolynomial σ R →ₐ[R] MvPolynomial τ R) (r : R) :
f (C r) = C r :=
f.commutes r
#align mv_polynomial.alg_hom_C MvPolynomial.algHom_C
@[simp]
theorem adjoin_range_X : Algebra.adjoin R (range (X : σ → MvPolynomial σ R)) = ⊤ := by
set S := Algebra.adjoin R (range (X : σ → MvPolynomial σ R))
refine top_unique fun p hp => ?_; clear hp
induction p using MvPolynomial.induction_on with
| h_C => exact S.algebraMap_mem _
| h_add p q hp hq => exact S.add_mem hp hq
| h_X p i hp => exact S.mul_mem hp (Algebra.subset_adjoin <| mem_range_self _)
#align mv_polynomial.adjoin_range_X MvPolynomial.adjoin_range_X
@[ext]
theorem linearMap_ext {M : Type*} [AddCommMonoid M] [Module R M] {f g : MvPolynomial σ R →ₗ[R] M}
(h : ∀ s, f ∘ₗ monomial s = g ∘ₗ monomial s) : f = g :=
Finsupp.lhom_ext' h
#align mv_polynomial.linear_map_ext MvPolynomial.linearMap_ext
section Support
/-- The finite set of all `m : σ →₀ ℕ` such that `X^m` has a non-zero coefficient. -/
def support (p : MvPolynomial σ R) : Finset (σ →₀ ℕ) :=
Finsupp.support p
#align mv_polynomial.support MvPolynomial.support
theorem finsupp_support_eq_support (p : MvPolynomial σ R) : Finsupp.support p = p.support :=
rfl
#align mv_polynomial.finsupp_support_eq_support MvPolynomial.finsupp_support_eq_support
theorem support_monomial [h : Decidable (a = 0)] :
(monomial s a).support = if a = 0 then ∅ else {s} := by
rw [← Subsingleton.elim (Classical.decEq R a 0) h]
rfl
-- Porting note: the proof in Lean 3 wasn't fundamentally better and needed `by convert rfl`
-- the issue is the different decidability instances in the `ite` expressions
#align mv_polynomial.support_monomial MvPolynomial.support_monomial
theorem support_monomial_subset : (monomial s a).support ⊆ {s} :=
support_single_subset
#align mv_polynomial.support_monomial_subset MvPolynomial.support_monomial_subset
theorem support_add [DecidableEq σ] : (p + q).support ⊆ p.support ∪ q.support :=
Finsupp.support_add
#align mv_polynomial.support_add MvPolynomial.support_add
theorem support_X [Nontrivial R] : (X n : MvPolynomial σ R).support = {Finsupp.single n 1} := by
classical rw [X, support_monomial, if_neg]; exact one_ne_zero
#align mv_polynomial.support_X MvPolynomial.support_X
theorem support_X_pow [Nontrivial R] (s : σ) (n : ℕ) :
(X s ^ n : MvPolynomial σ R).support = {Finsupp.single s n} := by
classical
rw [X_pow_eq_monomial, support_monomial, if_neg (one_ne_zero' R)]
#align mv_polynomial.support_X_pow MvPolynomial.support_X_pow
@[simp]
theorem support_zero : (0 : MvPolynomial σ R).support = ∅ :=
rfl
#align mv_polynomial.support_zero MvPolynomial.support_zero
theorem support_smul {S₁ : Type*} [SMulZeroClass S₁ R] {a : S₁} {f : MvPolynomial σ R} :
(a • f).support ⊆ f.support :=
Finsupp.support_smul
#align mv_polynomial.support_smul MvPolynomial.support_smul
theorem support_sum {α : Type*} [DecidableEq σ] {s : Finset α} {f : α → MvPolynomial σ R} :
(∑ x ∈ s, f x).support ⊆ s.biUnion fun x => (f x).support :=
Finsupp.support_finset_sum
#align mv_polynomial.support_sum MvPolynomial.support_sum
end Support
section Coeff
/-- The coefficient of the monomial `m` in the multi-variable polynomial `p`. -/
def coeff (m : σ →₀ ℕ) (p : MvPolynomial σ R) : R :=
@DFunLike.coe ((σ →₀ ℕ) →₀ R) _ _ _ p m
-- Porting note: I changed this from `@CoeFun.coe _ _ (MonoidAlgebra.coeFun _ _) p m` because
-- I think it should work better syntactically. They are defeq.
#align mv_polynomial.coeff MvPolynomial.coeff
@[simp]
theorem mem_support_iff {p : MvPolynomial σ R} {m : σ →₀ ℕ} : m ∈ p.support ↔ p.coeff m ≠ 0 := by
simp [support, coeff]
#align mv_polynomial.mem_support_iff MvPolynomial.mem_support_iff
theorem not_mem_support_iff {p : MvPolynomial σ R} {m : σ →₀ ℕ} : m ∉ p.support ↔ p.coeff m = 0 :=
by simp
#align mv_polynomial.not_mem_support_iff MvPolynomial.not_mem_support_iff
theorem sum_def {A} [AddCommMonoid A] {p : MvPolynomial σ R} {b : (σ →₀ ℕ) → R → A} :
p.sum b = ∑ m ∈ p.support, b m (p.coeff m) := by simp [support, Finsupp.sum, coeff]
#align mv_polynomial.sum_def MvPolynomial.sum_def
theorem support_mul [DecidableEq σ] (p q : MvPolynomial σ R) :
(p * q).support ⊆ p.support + q.support :=
AddMonoidAlgebra.support_mul p q
#align mv_polynomial.support_mul MvPolynomial.support_mul
@[ext]
theorem ext (p q : MvPolynomial σ R) : (∀ m, coeff m p = coeff m q) → p = q :=
Finsupp.ext
#align mv_polynomial.ext MvPolynomial.ext
theorem ext_iff (p q : MvPolynomial σ R) : p = q ↔ ∀ m, coeff m p = coeff m q :=
⟨fun h m => by rw [h], ext p q⟩
#align mv_polynomial.ext_iff MvPolynomial.ext_iff
@[simp]
theorem coeff_add (m : σ →₀ ℕ) (p q : MvPolynomial σ R) : coeff m (p + q) = coeff m p + coeff m q :=
add_apply p q m
#align mv_polynomial.coeff_add MvPolynomial.coeff_add
@[simp]
theorem coeff_smul {S₁ : Type*} [SMulZeroClass S₁ R] (m : σ →₀ ℕ) (C : S₁) (p : MvPolynomial σ R) :
coeff m (C • p) = C • coeff m p :=
smul_apply C p m
#align mv_polynomial.coeff_smul MvPolynomial.coeff_smul
@[simp]
theorem coeff_zero (m : σ →₀ ℕ) : coeff m (0 : MvPolynomial σ R) = 0 :=
rfl
#align mv_polynomial.coeff_zero MvPolynomial.coeff_zero
@[simp]
theorem coeff_zero_X (i : σ) : coeff 0 (X i : MvPolynomial σ R) = 0 :=
single_eq_of_ne fun h => by cases Finsupp.single_eq_zero.1 h
#align mv_polynomial.coeff_zero_X MvPolynomial.coeff_zero_X
/-- `MvPolynomial.coeff m` but promoted to an `AddMonoidHom`. -/
@[simps]
def coeffAddMonoidHom (m : σ →₀ ℕ) : MvPolynomial σ R →+ R where
toFun := coeff m
map_zero' := coeff_zero m
map_add' := coeff_add m
#align mv_polynomial.coeff_add_monoid_hom MvPolynomial.coeffAddMonoidHom
variable (R) in
/-- `MvPolynomial.coeff m` but promoted to a `LinearMap`. -/
@[simps]
def lcoeff (m : σ →₀ ℕ) : MvPolynomial σ R →ₗ[R] R where
toFun := coeff m
map_add' := coeff_add m
map_smul' := coeff_smul m
theorem coeff_sum {X : Type*} (s : Finset X) (f : X → MvPolynomial σ R) (m : σ →₀ ℕ) :
coeff m (∑ x ∈ s, f x) = ∑ x ∈ s, coeff m (f x) :=
map_sum (@coeffAddMonoidHom R σ _ _) _ s
#align mv_polynomial.coeff_sum MvPolynomial.coeff_sum
theorem monic_monomial_eq (m) :
monomial m (1 : R) = (m.prod fun n e => X n ^ e : MvPolynomial σ R) := by simp [monomial_eq]
#align mv_polynomial.monic_monomial_eq MvPolynomial.monic_monomial_eq
@[simp]
theorem coeff_monomial [DecidableEq σ] (m n) (a) :
coeff m (monomial n a : MvPolynomial σ R) = if n = m then a else 0 :=
Finsupp.single_apply
#align mv_polynomial.coeff_monomial MvPolynomial.coeff_monomial
@[simp]
theorem coeff_C [DecidableEq σ] (m) (a) :
coeff m (C a : MvPolynomial σ R) = if 0 = m then a else 0 :=
Finsupp.single_apply
#align mv_polynomial.coeff_C MvPolynomial.coeff_C
lemma eq_C_of_isEmpty [IsEmpty σ] (p : MvPolynomial σ R) :
p = C (p.coeff 0) := by
obtain ⟨x, rfl⟩ := C_surjective σ p
simp
theorem coeff_one [DecidableEq σ] (m) : coeff m (1 : MvPolynomial σ R) = if 0 = m then 1 else 0 :=
coeff_C m 1
#align mv_polynomial.coeff_one MvPolynomial.coeff_one
@[simp]
theorem coeff_zero_C (a) : coeff 0 (C a : MvPolynomial σ R) = a :=
single_eq_same
#align mv_polynomial.coeff_zero_C MvPolynomial.coeff_zero_C
@[simp]
theorem coeff_zero_one : coeff 0 (1 : MvPolynomial σ R) = 1 :=
coeff_zero_C 1
#align mv_polynomial.coeff_zero_one MvPolynomial.coeff_zero_one
theorem coeff_X_pow [DecidableEq σ] (i : σ) (m) (k : ℕ) :
coeff m (X i ^ k : MvPolynomial σ R) = if Finsupp.single i k = m then 1 else 0 := by
have := coeff_monomial m (Finsupp.single i k) (1 : R)
rwa [@monomial_eq _ _ (1 : R) (Finsupp.single i k) _, C_1, one_mul, Finsupp.prod_single_index]
at this
exact pow_zero _
#align mv_polynomial.coeff_X_pow MvPolynomial.coeff_X_pow
theorem coeff_X' [DecidableEq σ] (i : σ) (m) :
coeff m (X i : MvPolynomial σ R) = if Finsupp.single i 1 = m then 1 else 0 := by
rw [← coeff_X_pow, pow_one]
#align mv_polynomial.coeff_X' MvPolynomial.coeff_X'
@[simp]
theorem coeff_X (i : σ) : coeff (Finsupp.single i 1) (X i : MvPolynomial σ R) = 1 := by
classical rw [coeff_X', if_pos rfl]
#align mv_polynomial.coeff_X MvPolynomial.coeff_X
@[simp]
theorem coeff_C_mul (m) (a : R) (p : MvPolynomial σ R) : coeff m (C a * p) = a * coeff m p := by
classical
rw [mul_def, sum_C]
· simp (config := { contextual := true }) [sum_def, coeff_sum]
simp
#align mv_polynomial.coeff_C_mul MvPolynomial.coeff_C_mul
theorem coeff_mul [DecidableEq σ] (p q : MvPolynomial σ R) (n : σ →₀ ℕ) :
coeff n (p * q) = ∑ x ∈ Finset.antidiagonal n, coeff x.1 p * coeff x.2 q :=
AddMonoidAlgebra.mul_apply_antidiagonal p q _ _ Finset.mem_antidiagonal
#align mv_polynomial.coeff_mul MvPolynomial.coeff_mul
@[simp]
theorem coeff_mul_monomial (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff (m + s) (p * monomial s r) = coeff m p * r :=
AddMonoidAlgebra.mul_single_apply_aux p _ _ _ _ fun _a => add_left_inj _
#align mv_polynomial.coeff_mul_monomial MvPolynomial.coeff_mul_monomial
@[simp]
theorem coeff_monomial_mul (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff (s + m) (monomial s r * p) = r * coeff m p :=
AddMonoidAlgebra.single_mul_apply_aux p _ _ _ _ fun _a => add_right_inj _
#align mv_polynomial.coeff_monomial_mul MvPolynomial.coeff_monomial_mul
@[simp]
theorem coeff_mul_X (m) (s : σ) (p : MvPolynomial σ R) :
coeff (m + Finsupp.single s 1) (p * X s) = coeff m p :=
(coeff_mul_monomial _ _ _ _).trans (mul_one _)
#align mv_polynomial.coeff_mul_X MvPolynomial.coeff_mul_X
@[simp]
theorem coeff_X_mul (m) (s : σ) (p : MvPolynomial σ R) :
coeff (Finsupp.single s 1 + m) (X s * p) = coeff m p :=
(coeff_monomial_mul _ _ _ _).trans (one_mul _)
#align mv_polynomial.coeff_X_mul MvPolynomial.coeff_X_mul
lemma coeff_single_X_pow [DecidableEq σ] (s s' : σ) (n n' : ℕ) :
(X (R := R) s ^ n).coeff (Finsupp.single s' n')
= if s = s' ∧ n = n' ∨ n = 0 ∧ n' = 0 then 1 else 0 := by
simp only [coeff_X_pow, single_eq_single_iff]
@[simp]
lemma coeff_single_X [DecidableEq σ] (s s' : σ) (n : ℕ) :
(X s).coeff (R := R) (Finsupp.single s' n) = if n = 1 ∧ s = s' then 1 else 0 := by
simpa [eq_comm, and_comm] using coeff_single_X_pow s s' 1 n
@[simp]
theorem support_mul_X (s : σ) (p : MvPolynomial σ R) :
(p * X s).support = p.support.map (addRightEmbedding (Finsupp.single s 1)) :=
AddMonoidAlgebra.support_mul_single p _ (by simp) _
#align mv_polynomial.support_mul_X MvPolynomial.support_mul_X
@[simp]
theorem support_X_mul (s : σ) (p : MvPolynomial σ R) :
(X s * p).support = p.support.map (addLeftEmbedding (Finsupp.single s 1)) :=
AddMonoidAlgebra.support_single_mul p _ (by simp) _
#align mv_polynomial.support_X_mul MvPolynomial.support_X_mul
@[simp]
theorem support_smul_eq {S₁ : Type*} [Semiring S₁] [Module S₁ R] [NoZeroSMulDivisors S₁ R] {a : S₁}
(h : a ≠ 0) (p : MvPolynomial σ R) : (a • p).support = p.support :=
Finsupp.support_smul_eq h
#align mv_polynomial.support_smul_eq MvPolynomial.support_smul_eq
theorem support_sdiff_support_subset_support_add [DecidableEq σ] (p q : MvPolynomial σ R) :
p.support \ q.support ⊆ (p + q).support := by
intro m hm
simp only [Classical.not_not, mem_support_iff, Finset.mem_sdiff, Ne] at hm
simp [hm.2, hm.1]
#align mv_polynomial.support_sdiff_support_subset_support_add MvPolynomial.support_sdiff_support_subset_support_add
open scoped symmDiff in
theorem support_symmDiff_support_subset_support_add [DecidableEq σ] (p q : MvPolynomial σ R) :
p.support ∆ q.support ⊆ (p + q).support := by
rw [symmDiff_def, Finset.sup_eq_union]
apply Finset.union_subset
· exact support_sdiff_support_subset_support_add p q
· rw [add_comm]
exact support_sdiff_support_subset_support_add q p
#align mv_polynomial.support_symm_diff_support_subset_support_add MvPolynomial.support_symmDiff_support_subset_support_add
theorem coeff_mul_monomial' (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff m (p * monomial s r) = if s ≤ m then coeff (m - s) p * r else 0 := by
classical
split_ifs with h
· conv_rhs => rw [← coeff_mul_monomial _ s]
congr with t
rw [tsub_add_cancel_of_le h]
· contrapose! h
rw [← mem_support_iff] at h
obtain ⟨j, -, rfl⟩ : ∃ j ∈ support p, j + s = m := by
simpa [Finset.add_singleton]
using Finset.add_subset_add_left support_monomial_subset <| support_mul _ _ h
exact le_add_left le_rfl
#align mv_polynomial.coeff_mul_monomial' MvPolynomial.coeff_mul_monomial'
theorem coeff_monomial_mul' (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) :
coeff m (monomial s r * p) = if s ≤ m then r * coeff (m - s) p else 0 := by
-- note that if we allow `R` to be non-commutative we will have to duplicate the proof above.
rw [mul_comm, mul_comm r]
exact coeff_mul_monomial' _ _ _ _
#align mv_polynomial.coeff_monomial_mul' MvPolynomial.coeff_monomial_mul'
theorem coeff_mul_X' [DecidableEq σ] (m) (s : σ) (p : MvPolynomial σ R) :
coeff m (p * X s) = if s ∈ m.support then coeff (m - Finsupp.single s 1) p else 0 := by
refine (coeff_mul_monomial' _ _ _ _).trans ?_
simp_rw [Finsupp.single_le_iff, Finsupp.mem_support_iff, Nat.succ_le_iff, pos_iff_ne_zero,
mul_one]
#align mv_polynomial.coeff_mul_X' MvPolynomial.coeff_mul_X'
theorem coeff_X_mul' [DecidableEq σ] (m) (s : σ) (p : MvPolynomial σ R) :
coeff m (X s * p) = if s ∈ m.support then coeff (m - Finsupp.single s 1) p else 0 := by
refine (coeff_monomial_mul' _ _ _ _).trans ?_
simp_rw [Finsupp.single_le_iff, Finsupp.mem_support_iff, Nat.succ_le_iff, pos_iff_ne_zero,
one_mul]
#align mv_polynomial.coeff_X_mul' MvPolynomial.coeff_X_mul'
theorem eq_zero_iff {p : MvPolynomial σ R} : p = 0 ↔ ∀ d, coeff d p = 0 := by
rw [ext_iff]
simp only [coeff_zero]
#align mv_polynomial.eq_zero_iff MvPolynomial.eq_zero_iff
theorem ne_zero_iff {p : MvPolynomial σ R} : p ≠ 0 ↔ ∃ d, coeff d p ≠ 0 := by
rw [Ne, eq_zero_iff]
push_neg
rfl
#align mv_polynomial.ne_zero_iff MvPolynomial.ne_zero_iff
@[simp]
theorem X_ne_zero [Nontrivial R] (s : σ) :
X (R := R) s ≠ 0 := by
rw [ne_zero_iff]
use Finsupp.single s 1
simp only [coeff_X, ne_eq, one_ne_zero, not_false_eq_true]
@[simp]
theorem support_eq_empty {p : MvPolynomial σ R} : p.support = ∅ ↔ p = 0 :=
Finsupp.support_eq_empty
#align mv_polynomial.support_eq_empty MvPolynomial.support_eq_empty
@[simp]
lemma support_nonempty {p : MvPolynomial σ R} : p.support.Nonempty ↔ p ≠ 0 := by
rw [Finset.nonempty_iff_ne_empty, ne_eq, support_eq_empty]
theorem exists_coeff_ne_zero {p : MvPolynomial σ R} (h : p ≠ 0) : ∃ d, coeff d p ≠ 0 :=
ne_zero_iff.mp h
#align mv_polynomial.exists_coeff_ne_zero MvPolynomial.exists_coeff_ne_zero
theorem C_dvd_iff_dvd_coeff (r : R) (φ : MvPolynomial σ R) : C r ∣ φ ↔ ∀ i, r ∣ φ.coeff i := by
constructor
· rintro ⟨φ, rfl⟩ c
rw [coeff_C_mul]
apply dvd_mul_right
· intro h
choose C hc using h
classical
let c' : (σ →₀ ℕ) → R := fun i => if i ∈ φ.support then C i else 0
let ψ : MvPolynomial σ R := ∑ i ∈ φ.support, monomial i (c' i)
use ψ
apply MvPolynomial.ext
intro i
simp only [ψ, c', coeff_C_mul, coeff_sum, coeff_monomial, Finset.sum_ite_eq']
split_ifs with hi
· rw [hc]
· rw [not_mem_support_iff] at hi
rwa [mul_zero]
#align mv_polynomial.C_dvd_iff_dvd_coeff MvPolynomial.C_dvd_iff_dvd_coeff
@[simp] lemma isRegular_X : IsRegular (X n : MvPolynomial σ R) := by
suffices IsLeftRegular (X n : MvPolynomial σ R) from
⟨this, this.right_of_commute <| Commute.all _⟩
intro P Q (hPQ : (X n) * P = (X n) * Q)
ext i
rw [← coeff_X_mul i n P, hPQ, coeff_X_mul i n Q]
@[simp] lemma isRegular_X_pow (k : ℕ) : IsRegular (X n ^ k : MvPolynomial σ R) := isRegular_X.pow k
@[simp] lemma isRegular_prod_X (s : Finset σ) :
IsRegular (∏ n ∈ s, X n : MvPolynomial σ R) :=
IsRegular.prod fun _ _ ↦ isRegular_X
/-- The finset of nonzero coefficients of a multivariate polynomial. -/
def coeffs (p : MvPolynomial σ R) : Finset R :=
letI := Classical.decEq R
Finset.image p.coeff p.support
@[simp]
lemma coeffs_zero : coeffs (0 : MvPolynomial σ R) = ∅ :=
rfl
lemma coeffs_one : coeffs (1 : MvPolynomial σ R) ⊆ {1} := by
classical
rw [coeffs, Finset.image_subset_iff]
simp_all [coeff_one]
@[nontriviality]
lemma coeffs_eq_empty_of_subsingleton [Subsingleton R] (p : MvPolynomial σ R) : p.coeffs = ∅ := by
simpa [coeffs] using Subsingleton.eq_zero p
@[simp]
lemma coeffs_one_of_nontrivial [Nontrivial R] : coeffs (1 : MvPolynomial σ R) = {1} := by
apply Finset.Subset.antisymm coeffs_one
simp only [coeffs, Finset.singleton_subset_iff, Finset.mem_image]
exact ⟨0, by simp⟩
lemma mem_coeffs_iff {p : MvPolynomial σ R} {c : R} :
c ∈ p.coeffs ↔ ∃ n ∈ p.support, c = p.coeff n := by
simp [coeffs, eq_comm, (Finset.mem_image)]
lemma coeff_mem_coeffs {p : MvPolynomial σ R} (m : σ →₀ ℕ)
(h : p.coeff m ≠ 0) : p.coeff m ∈ p.coeffs :=
letI := Classical.decEq R
Finset.mem_image_of_mem p.coeff (mem_support_iff.mpr h)
lemma zero_not_mem_coeffs (p : MvPolynomial σ R) : 0 ∉ p.coeffs := by
intro hz
obtain ⟨n, hnsupp, hn⟩ := mem_coeffs_iff.mp hz
exact (mem_support_iff.mp hnsupp) hn.symm
end Coeff
section ConstantCoeff
/-- `constantCoeff p` returns the constant term of the polynomial `p`, defined as `coeff 0 p`.
This is a ring homomorphism.
-/
def constantCoeff : MvPolynomial σ R →+* R where
toFun := coeff 0
map_one' := by simp [AddMonoidAlgebra.one_def]
map_mul' := by classical simp [coeff_mul, Finsupp.support_single_ne_zero]
map_zero' := coeff_zero _
map_add' := coeff_add _
#align mv_polynomial.constant_coeff MvPolynomial.constantCoeff
theorem constantCoeff_eq : (constantCoeff : MvPolynomial σ R → R) = coeff 0 :=
rfl
#align mv_polynomial.constant_coeff_eq MvPolynomial.constantCoeff_eq
variable (σ)
@[simp]
theorem constantCoeff_C (r : R) : constantCoeff (C r : MvPolynomial σ R) = r := by
classical simp [constantCoeff_eq]
#align mv_polynomial.constant_coeff_C MvPolynomial.constantCoeff_C
variable {σ}
variable (R)
@[simp]
theorem constantCoeff_X (i : σ) : constantCoeff (X i : MvPolynomial σ R) = 0 := by
simp [constantCoeff_eq]
#align mv_polynomial.constant_coeff_X MvPolynomial.constantCoeff_X
variable {R}
/- porting note: increased priority because otherwise `simp` time outs when trying to simplify
the left-hand side. `simpNF` linter indicated this and it was verified. -/
@[simp 1001]
theorem constantCoeff_smul {R : Type*} [SMulZeroClass R S₁] (a : R) (f : MvPolynomial σ S₁) :
constantCoeff (a • f) = a • constantCoeff f :=
rfl
#align mv_polynomial.constant_coeff_smul MvPolynomial.constantCoeff_smul
theorem constantCoeff_monomial [DecidableEq σ] (d : σ →₀ ℕ) (r : R) :
constantCoeff (monomial d r) = if d = 0 then r else 0 := by
rw [constantCoeff_eq, coeff_monomial]
#align mv_polynomial.constant_coeff_monomial MvPolynomial.constantCoeff_monomial
variable (σ R)
@[simp]
theorem constantCoeff_comp_C : constantCoeff.comp (C : R →+* MvPolynomial σ R) = RingHom.id R := by
ext x
exact constantCoeff_C σ x
#align mv_polynomial.constant_coeff_comp_C MvPolynomial.constantCoeff_comp_C
theorem constantCoeff_comp_algebraMap :
constantCoeff.comp (algebraMap R (MvPolynomial σ R)) = RingHom.id R :=
constantCoeff_comp_C _ _
#align mv_polynomial.constant_coeff_comp_algebra_map MvPolynomial.constantCoeff_comp_algebraMap
end ConstantCoeff
section AsSum
@[simp]
theorem support_sum_monomial_coeff (p : MvPolynomial σ R) :
(∑ v ∈ p.support, monomial v (coeff v p)) = p :=
Finsupp.sum_single p
#align mv_polynomial.support_sum_monomial_coeff MvPolynomial.support_sum_monomial_coeff
theorem as_sum (p : MvPolynomial σ R) : p = ∑ v ∈ p.support, monomial v (coeff v p) :=
(support_sum_monomial_coeff p).symm
#align mv_polynomial.as_sum MvPolynomial.as_sum
end AsSum
section Eval₂
variable (f : R →+* S₁) (g : σ → S₁)
/-- Evaluate a polynomial `p` given a valuation `g` of all the variables
and a ring hom `f` from the scalar ring to the target -/
def eval₂ (p : MvPolynomial σ R) : S₁ :=
p.sum fun s a => f a * s.prod fun n e => g n ^ e
#align mv_polynomial.eval₂ MvPolynomial.eval₂
theorem eval₂_eq (g : R →+* S₁) (X : σ → S₁) (f : MvPolynomial σ R) :
f.eval₂ g X = ∑ d ∈ f.support, g (f.coeff d) * ∏ i ∈ d.support, X i ^ d i :=
rfl
#align mv_polynomial.eval₂_eq MvPolynomial.eval₂_eq
theorem eval₂_eq' [Fintype σ] (g : R →+* S₁) (X : σ → S₁) (f : MvPolynomial σ R) :
f.eval₂ g X = ∑ d ∈ f.support, g (f.coeff d) * ∏ i, X i ^ d i := by
simp only [eval₂_eq, ← Finsupp.prod_pow]
rfl
#align mv_polynomial.eval₂_eq' MvPolynomial.eval₂_eq'
@[simp]
theorem eval₂_zero : (0 : MvPolynomial σ R).eval₂ f g = 0 :=
Finsupp.sum_zero_index
#align mv_polynomial.eval₂_zero MvPolynomial.eval₂_zero
section
@[simp]
theorem eval₂_add : (p + q).eval₂ f g = p.eval₂ f g + q.eval₂ f g := by
classical exact Finsupp.sum_add_index (by simp [f.map_zero]) (by simp [add_mul, f.map_add])
#align mv_polynomial.eval₂_add MvPolynomial.eval₂_add
@[simp]
theorem eval₂_monomial : (monomial s a).eval₂ f g = f a * s.prod fun n e => g n ^ e :=
Finsupp.sum_single_index (by simp [f.map_zero])
#align mv_polynomial.eval₂_monomial MvPolynomial.eval₂_monomial
@[simp]
theorem eval₂_C (a) : (C a).eval₂ f g = f a := by
rw [C_apply, eval₂_monomial, prod_zero_index, mul_one]
#align mv_polynomial.eval₂_C MvPolynomial.eval₂_C
@[simp]
theorem eval₂_one : (1 : MvPolynomial σ R).eval₂ f g = 1 :=
(eval₂_C _ _ _).trans f.map_one
#align mv_polynomial.eval₂_one MvPolynomial.eval₂_one
@[simp]
theorem eval₂_X (n) : (X n).eval₂ f g = g n := by
simp [eval₂_monomial, f.map_one, X, prod_single_index, pow_one]
#align mv_polynomial.eval₂_X MvPolynomial.eval₂_X
theorem eval₂_mul_monomial :
∀ {s a}, (p * monomial s a).eval₂ f g = p.eval₂ f g * f a * s.prod fun n e => g n ^ e := by
classical
apply MvPolynomial.induction_on p
· intro a' s a
simp [C_mul_monomial, eval₂_monomial, f.map_mul]
· intro p q ih_p ih_q
simp [add_mul, eval₂_add, ih_p, ih_q]
· intro p n ih s a
exact
calc (p * X n * monomial s a).eval₂ f g
_ = (p * monomial (Finsupp.single n 1 + s) a).eval₂ f g := by
rw [monomial_single_add, pow_one, mul_assoc]
_ = (p * monomial (Finsupp.single n 1) 1).eval₂ f g * f a * s.prod fun n e => g n ^ e := by
simp [ih, prod_single_index, prod_add_index, pow_one, pow_add, mul_assoc, mul_left_comm,
f.map_one]
#align mv_polynomial.eval₂_mul_monomial MvPolynomial.eval₂_mul_monomial
theorem eval₂_mul_C : (p * C a).eval₂ f g = p.eval₂ f g * f a :=
(eval₂_mul_monomial _ _).trans <| by simp
#align mv_polynomial.eval₂_mul_C MvPolynomial.eval₂_mul_C
@[simp]
theorem eval₂_mul : ∀ {p}, (p * q).eval₂ f g = p.eval₂ f g * q.eval₂ f g := by
apply MvPolynomial.induction_on q
· simp [eval₂_C, eval₂_mul_C]
· simp (config := { contextual := true }) [mul_add, eval₂_add]
· simp (config := { contextual := true }) [X, eval₂_monomial, eval₂_mul_monomial, ← mul_assoc]
#align mv_polynomial.eval₂_mul MvPolynomial.eval₂_mul
@[simp]
theorem eval₂_pow {p : MvPolynomial σ R} : ∀ {n : ℕ}, (p ^ n).eval₂ f g = p.eval₂ f g ^ n
| 0 => by
rw [pow_zero, pow_zero]
exact eval₂_one _ _
| n + 1 => by rw [pow_add, pow_one, pow_add, pow_one, eval₂_mul, eval₂_pow]
#align mv_polynomial.eval₂_pow MvPolynomial.eval₂_pow
/-- `MvPolynomial.eval₂` as a `RingHom`. -/
def eval₂Hom (f : R →+* S₁) (g : σ → S₁) : MvPolynomial σ R →+* S₁ where
toFun := eval₂ f g
map_one' := eval₂_one _ _
map_mul' _ _ := eval₂_mul _ _
map_zero' := eval₂_zero f g
map_add' _ _ := eval₂_add _ _
#align mv_polynomial.eval₂_hom MvPolynomial.eval₂Hom
@[simp]
theorem coe_eval₂Hom (f : R →+* S₁) (g : σ → S₁) : ⇑(eval₂Hom f g) = eval₂ f g :=
rfl
#align mv_polynomial.coe_eval₂_hom MvPolynomial.coe_eval₂Hom
theorem eval₂Hom_congr {f₁ f₂ : R →+* S₁} {g₁ g₂ : σ → S₁} {p₁ p₂ : MvPolynomial σ R} :
f₁ = f₂ → g₁ = g₂ → p₁ = p₂ → eval₂Hom f₁ g₁ p₁ = eval₂Hom f₂ g₂ p₂ := by
rintro rfl rfl rfl; rfl
#align mv_polynomial.eval₂_hom_congr MvPolynomial.eval₂Hom_congr
end
@[simp]
theorem eval₂Hom_C (f : R →+* S₁) (g : σ → S₁) (r : R) : eval₂Hom f g (C r) = f r :=
eval₂_C f g r
#align mv_polynomial.eval₂_hom_C MvPolynomial.eval₂Hom_C
@[simp]
theorem eval₂Hom_X' (f : R →+* S₁) (g : σ → S₁) (i : σ) : eval₂Hom f g (X i) = g i :=
eval₂_X f g i
#align mv_polynomial.eval₂_hom_X' MvPolynomial.eval₂Hom_X'
@[simp]
theorem comp_eval₂Hom [CommSemiring S₂] (f : R →+* S₁) (g : σ → S₁) (φ : S₁ →+* S₂) :
φ.comp (eval₂Hom f g) = eval₂Hom (φ.comp f) fun i => φ (g i) := by
apply MvPolynomial.ringHom_ext
· intro r
rw [RingHom.comp_apply, eval₂Hom_C, eval₂Hom_C, RingHom.comp_apply]
· intro i
rw [RingHom.comp_apply, eval₂Hom_X', eval₂Hom_X']
#align mv_polynomial.comp_eval₂_hom MvPolynomial.comp_eval₂Hom
theorem map_eval₂Hom [CommSemiring S₂] (f : R →+* S₁) (g : σ → S₁) (φ : S₁ →+* S₂)
(p : MvPolynomial σ R) : φ (eval₂Hom f g p) = eval₂Hom (φ.comp f) (fun i => φ (g i)) p := by
rw [← comp_eval₂Hom]
rfl
#align mv_polynomial.map_eval₂_hom MvPolynomial.map_eval₂Hom
theorem eval₂Hom_monomial (f : R →+* S₁) (g : σ → S₁) (d : σ →₀ ℕ) (r : R) :
eval₂Hom f g (monomial d r) = f r * d.prod fun i k => g i ^ k := by
simp only [monomial_eq, RingHom.map_mul, eval₂Hom_C, Finsupp.prod, map_prod,
RingHom.map_pow, eval₂Hom_X']
#align mv_polynomial.eval₂_hom_monomial MvPolynomial.eval₂Hom_monomial
section
theorem eval₂_comp_left {S₂} [CommSemiring S₂] (k : S₁ →+* S₂) (f : R →+* S₁) (g : σ → S₁) (p) :
k (eval₂ f g p) = eval₂ (k.comp f) (k ∘ g) p := by
apply MvPolynomial.induction_on p <;>
simp (config := { contextual := true }) [eval₂_add, k.map_add, eval₂_mul, k.map_mul]
#align mv_polynomial.eval₂_comp_left MvPolynomial.eval₂_comp_left
end
@[simp]
theorem eval₂_eta (p : MvPolynomial σ R) : eval₂ C X p = p := by
apply MvPolynomial.induction_on p <;>
simp (config := { contextual := true }) [eval₂_add, eval₂_mul]
#align mv_polynomial.eval₂_eta MvPolynomial.eval₂_eta
theorem eval₂_congr (g₁ g₂ : σ → S₁)
(h : ∀ {i : σ} {c : σ →₀ ℕ}, i ∈ c.support → coeff c p ≠ 0 → g₁ i = g₂ i) :
p.eval₂ f g₁ = p.eval₂ f g₂ := by
apply Finset.sum_congr rfl
intro C hc; dsimp; congr 1
apply Finset.prod_congr rfl
intro i hi; dsimp; congr 1
apply h hi
rwa [Finsupp.mem_support_iff] at hc
#align mv_polynomial.eval₂_congr MvPolynomial.eval₂_congr
theorem eval₂_sum (s : Finset S₂) (p : S₂ → MvPolynomial σ R) :
eval₂ f g (∑ x ∈ s, p x) = ∑ x ∈ s, eval₂ f g (p x) :=
map_sum (eval₂Hom f g) _ s
#align mv_polynomial.eval₂_sum MvPolynomial.eval₂_sum
@[to_additive existing (attr := simp)]
theorem eval₂_prod (s : Finset S₂) (p : S₂ → MvPolynomial σ R) :
eval₂ f g (∏ x ∈ s, p x) = ∏ x ∈ s, eval₂ f g (p x) :=
map_prod (eval₂Hom f g) _ s
#align mv_polynomial.eval₂_prod MvPolynomial.eval₂_prod
theorem eval₂_assoc (q : S₂ → MvPolynomial σ R) (p : MvPolynomial S₂ R) :
eval₂ f (fun t => eval₂ f g (q t)) p = eval₂ f g (eval₂ C q p) := by
show _ = eval₂Hom f g (eval₂ C q p)
rw [eval₂_comp_left (eval₂Hom f g)]; congr with a; simp
#align mv_polynomial.eval₂_assoc MvPolynomial.eval₂_assoc
end Eval₂
section Eval
variable {f : σ → R}
/-- Evaluate a polynomial `p` given a valuation `f` of all the variables -/
def eval (f : σ → R) : MvPolynomial σ R →+* R :=
eval₂Hom (RingHom.id _) f
#align mv_polynomial.eval MvPolynomial.eval
theorem eval_eq (X : σ → R) (f : MvPolynomial σ R) :
eval X f = ∑ d ∈ f.support, f.coeff d * ∏ i ∈ d.support, X i ^ d i :=
rfl
#align mv_polynomial.eval_eq MvPolynomial.eval_eq
theorem eval_eq' [Fintype σ] (X : σ → R) (f : MvPolynomial σ R) :
eval X f = ∑ d ∈ f.support, f.coeff d * ∏ i, X i ^ d i :=
eval₂_eq' (RingHom.id R) X f
#align mv_polynomial.eval_eq' MvPolynomial.eval_eq'
theorem eval_monomial : eval f (monomial s a) = a * s.prod fun n e => f n ^ e :=
eval₂_monomial _ _
#align mv_polynomial.eval_monomial MvPolynomial.eval_monomial
@[simp]
theorem eval_C : ∀ a, eval f (C a) = a :=
eval₂_C _ _
#align mv_polynomial.eval_C MvPolynomial.eval_C
@[simp]
theorem eval_X : ∀ n, eval f (X n) = f n :=
eval₂_X _ _
#align mv_polynomial.eval_X MvPolynomial.eval_X
@[simp]
theorem smul_eval (x) (p : MvPolynomial σ R) (s) : eval x (s • p) = s * eval x p := by
rw [smul_eq_C_mul, (eval x).map_mul, eval_C]
#align mv_polynomial.smul_eval MvPolynomial.smul_eval
theorem eval_add : eval f (p + q) = eval f p + eval f q :=
eval₂_add _ _
theorem eval_mul : eval f (p * q) = eval f p * eval f q :=
eval₂_mul _ _
theorem eval_pow : ∀ n, eval f (p ^ n) = eval f p ^ n :=
fun _ => eval₂_pow _ _
theorem eval_sum {ι : Type*} (s : Finset ι) (f : ι → MvPolynomial σ R) (g : σ → R) :
eval g (∑ i ∈ s, f i) = ∑ i ∈ s, eval g (f i) :=
map_sum (eval g) _ _
#align mv_polynomial.eval_sum MvPolynomial.eval_sum
@[to_additive existing]
theorem eval_prod {ι : Type*} (s : Finset ι) (f : ι → MvPolynomial σ R) (g : σ → R) :
eval g (∏ i ∈ s, f i) = ∏ i ∈ s, eval g (f i) :=
map_prod (eval g) _ _
#align mv_polynomial.eval_prod MvPolynomial.eval_prod
| Mathlib/Algebra/MvPolynomial/Basic.lean | 1,258 | 1,262 | theorem eval_assoc {τ} (f : σ → MvPolynomial τ R) (g : τ → R) (p : MvPolynomial σ R) :
eval (eval g ∘ f) p = eval g (eval₂ C f p) := by |
rw [eval₂_comp_left (eval g)]
unfold eval; simp only [coe_eval₂Hom]
congr with a; 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 G. Kudryashov, Scott Morrison
-/
import Mathlib.Algebra.Algebra.Equiv
import Mathlib.Algebra.Algebra.NonUnitalHom
import Mathlib.Algebra.BigOperators.Finsupp
import Mathlib.Algebra.Module.BigOperators
import Mathlib.Data.Finsupp.Basic
import Mathlib.LinearAlgebra.Finsupp
#align_import algebra.monoid_algebra.basic from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69"
/-!
# Monoid algebras
When the domain of a `Finsupp` has a multiplicative or additive structure, we can define
a convolution product. To mathematicians this structure is known as the "monoid algebra",
i.e. the finite formal linear combinations over a given semiring of elements of the monoid.
The "group ring" ℤ[G] or the "group algebra" k[G] are typical uses.
In fact the construction of the "monoid algebra" makes sense when `G` is not even a monoid, but
merely a magma, i.e., when `G` carries a multiplication which is not required to satisfy any
conditions at all. In this case the construction yields a not-necessarily-unital,
not-necessarily-associative algebra but it is still adjoint to the forgetful functor from such
algebras to magmas, and we prove this as `MonoidAlgebra.liftMagma`.
In this file we define `MonoidAlgebra k G := G →₀ k`, and `AddMonoidAlgebra k G`
in the same way, and then define the convolution product on these.
When the domain is additive, this is used to define polynomials:
```
Polynomial R := AddMonoidAlgebra R ℕ
MvPolynomial σ α := AddMonoidAlgebra R (σ →₀ ℕ)
```
When the domain is multiplicative, e.g. a group, this will be used to define the group ring.
## Notation
We introduce the notation `R[A]` for `AddMonoidAlgebra R A`.
## Implementation note
Unfortunately because additive and multiplicative structures both appear in both cases,
it doesn't appear to be possible to make much use of `to_additive`, and we just settle for
saying everything twice.
Similarly, I attempted to just define
`k[G] := MonoidAlgebra k (Multiplicative G)`, but the definitional equality
`Multiplicative G = G` leaks through everywhere, and seems impossible to use.
-/
noncomputable section
open Finset
open Finsupp hiding single mapDomain
universe u₁ u₂ u₃ u₄
variable (k : Type u₁) (G : Type u₂) (H : Type*) {R : Type*}
/-! ### Multiplicative monoids -/
section
variable [Semiring k]
/-- The monoid algebra over a semiring `k` generated by the monoid `G`.
It is the type of finite formal `k`-linear combinations of terms of `G`,
endowed with the convolution product.
-/
def MonoidAlgebra : Type max u₁ u₂ :=
G →₀ k
#align monoid_algebra MonoidAlgebra
-- Porting note: The compiler couldn't derive this.
instance MonoidAlgebra.inhabited : Inhabited (MonoidAlgebra k G) :=
inferInstanceAs (Inhabited (G →₀ k))
#align monoid_algebra.inhabited MonoidAlgebra.inhabited
-- Porting note: The compiler couldn't derive this.
instance MonoidAlgebra.addCommMonoid : AddCommMonoid (MonoidAlgebra k G) :=
inferInstanceAs (AddCommMonoid (G →₀ k))
#align monoid_algebra.add_comm_monoid MonoidAlgebra.addCommMonoid
instance MonoidAlgebra.instIsCancelAdd [IsCancelAdd k] : IsCancelAdd (MonoidAlgebra k G) :=
inferInstanceAs (IsCancelAdd (G →₀ k))
instance MonoidAlgebra.coeFun : CoeFun (MonoidAlgebra k G) fun _ => G → k :=
Finsupp.instCoeFun
#align monoid_algebra.has_coe_to_fun MonoidAlgebra.coeFun
end
namespace MonoidAlgebra
variable {k G}
section
variable [Semiring k] [NonUnitalNonAssocSemiring R]
-- Porting note: `reducible` cannot be `local`, so we replace some definitions and theorems with
-- new ones which have new types.
abbrev single (a : G) (b : k) : MonoidAlgebra k G := Finsupp.single a b
theorem single_zero (a : G) : (single a 0 : MonoidAlgebra k G) = 0 := Finsupp.single_zero a
theorem single_add (a : G) (b₁ b₂ : k) : single a (b₁ + b₂) = single a b₁ + single a b₂ :=
Finsupp.single_add a b₁ b₂
@[simp]
theorem sum_single_index {N} [AddCommMonoid N] {a : G} {b : k} {h : G → k → N}
(h_zero : h a 0 = 0) :
(single a b).sum h = h a b := Finsupp.sum_single_index h_zero
@[simp]
theorem sum_single (f : MonoidAlgebra k G) : f.sum single = f :=
Finsupp.sum_single f
theorem single_apply {a a' : G} {b : k} [Decidable (a = a')] :
single a b a' = if a = a' then b else 0 :=
Finsupp.single_apply
@[simp]
theorem single_eq_zero {a : G} {b : k} : single a b = 0 ↔ b = 0 := Finsupp.single_eq_zero
abbrev mapDomain {G' : Type*} (f : G → G') (v : MonoidAlgebra k G) : MonoidAlgebra k G' :=
Finsupp.mapDomain f v
theorem mapDomain_sum {k' G' : Type*} [Semiring k'] {f : G → G'} {s : MonoidAlgebra k' G}
{v : G → k' → MonoidAlgebra k G} :
mapDomain f (s.sum v) = s.sum fun a b => mapDomain f (v a b) :=
Finsupp.mapDomain_sum
/-- A non-commutative version of `MonoidAlgebra.lift`: given an additive homomorphism `f : k →+ R`
and a homomorphism `g : G → R`, returns the additive homomorphism from
`MonoidAlgebra k G` such that `liftNC f g (single a b) = f b * g a`. If `f` is a ring homomorphism
and the range of either `f` or `g` is in center of `R`, then the result is a ring homomorphism. If
`R` is a `k`-algebra and `f = algebraMap k R`, then the result is an algebra homomorphism called
`MonoidAlgebra.lift`. -/
def liftNC (f : k →+ R) (g : G → R) : MonoidAlgebra k G →+ R :=
liftAddHom fun x : G => (AddMonoidHom.mulRight (g x)).comp f
#align monoid_algebra.lift_nc MonoidAlgebra.liftNC
@[simp]
theorem liftNC_single (f : k →+ R) (g : G → R) (a : G) (b : k) :
liftNC f g (single a b) = f b * g a :=
liftAddHom_apply_single _ _ _
#align monoid_algebra.lift_nc_single MonoidAlgebra.liftNC_single
end
section Mul
variable [Semiring k] [Mul G]
/-- The multiplication in a monoid algebra. We make it irreducible so that Lean doesn't unfold
it trying to unify two things that are different. -/
@[irreducible] def mul' (f g : MonoidAlgebra k G) : MonoidAlgebra k G :=
f.sum fun a₁ b₁ => g.sum fun a₂ b₂ => single (a₁ * a₂) (b₁ * b₂)
/-- The product of `f g : MonoidAlgebra k G` is the finitely supported function
whose value at `a` is the sum of `f x * g y` over all pairs `x, y`
such that `x * y = a`. (Think of the group ring of a group.) -/
instance instMul : Mul (MonoidAlgebra k G) := ⟨MonoidAlgebra.mul'⟩
#align monoid_algebra.has_mul MonoidAlgebra.instMul
theorem mul_def {f g : MonoidAlgebra k G} :
f * g = f.sum fun a₁ b₁ => g.sum fun a₂ b₂ => single (a₁ * a₂) (b₁ * b₂) := by
with_unfolding_all rfl
#align monoid_algebra.mul_def MonoidAlgebra.mul_def
instance nonUnitalNonAssocSemiring : NonUnitalNonAssocSemiring (MonoidAlgebra k G) :=
{ Finsupp.instAddCommMonoid with
-- Porting note: `refine` & `exact` are required because `simp` behaves differently.
left_distrib := fun f g h => by
haveI := Classical.decEq G
simp only [mul_def]
refine Eq.trans (congr_arg (sum f) (funext₂ fun a₁ b₁ => sum_add_index ?_ ?_)) ?_ <;>
simp only [mul_add, mul_zero, single_zero, single_add, forall_true_iff, sum_add]
right_distrib := fun f g h => by
haveI := Classical.decEq G
simp only [mul_def]
refine Eq.trans (sum_add_index ?_ ?_) ?_ <;>
simp only [add_mul, zero_mul, single_zero, single_add, forall_true_iff, sum_zero, sum_add]
zero_mul := fun f => by
simp only [mul_def]
exact sum_zero_index
mul_zero := fun f => by
simp only [mul_def]
exact Eq.trans (congr_arg (sum f) (funext₂ fun a₁ b₁ => sum_zero_index)) sum_zero }
#align monoid_algebra.non_unital_non_assoc_semiring MonoidAlgebra.nonUnitalNonAssocSemiring
variable [Semiring R]
theorem liftNC_mul {g_hom : Type*} [FunLike g_hom G R] [MulHomClass g_hom G R]
(f : k →+* R) (g : g_hom) (a b : MonoidAlgebra k G)
(h_comm : ∀ {x y}, y ∈ a.support → Commute (f (b x)) (g y)) :
liftNC (f : k →+ R) g (a * b) = liftNC (f : k →+ R) g a * liftNC (f : k →+ R) g b := by
conv_rhs => rw [← sum_single a, ← sum_single b]
-- Porting note: `(liftNC _ g).map_finsupp_sum` → `map_finsupp_sum`
simp_rw [mul_def, map_finsupp_sum, liftNC_single, Finsupp.sum_mul, Finsupp.mul_sum]
refine Finset.sum_congr rfl fun y hy => Finset.sum_congr rfl fun x _hx => ?_
simp [mul_assoc, (h_comm hy).left_comm]
#align monoid_algebra.lift_nc_mul MonoidAlgebra.liftNC_mul
end Mul
section Semigroup
variable [Semiring k] [Semigroup G] [Semiring R]
instance nonUnitalSemiring : NonUnitalSemiring (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalNonAssocSemiring with
mul_assoc := fun f g h => by
-- Porting note: `reducible` cannot be `local` so proof gets long.
simp only [mul_def]
rw [sum_sum_index]; congr; ext a₁ b₁
rw [sum_sum_index, sum_sum_index]; congr; ext a₂ b₂
rw [sum_sum_index, sum_single_index]; congr; ext a₃ b₃
rw [sum_single_index, mul_assoc, mul_assoc]
all_goals simp only [single_zero, single_add, forall_true_iff, add_mul,
mul_add, zero_mul, mul_zero, sum_zero, sum_add] }
#align monoid_algebra.non_unital_semiring MonoidAlgebra.nonUnitalSemiring
end Semigroup
section One
variable [NonAssocSemiring R] [Semiring k] [One G]
/-- The unit of the multiplication is `single 1 1`, i.e. the function
that is `1` at `1` and zero elsewhere. -/
instance one : One (MonoidAlgebra k G) :=
⟨single 1 1⟩
#align monoid_algebra.has_one MonoidAlgebra.one
theorem one_def : (1 : MonoidAlgebra k G) = single 1 1 :=
rfl
#align monoid_algebra.one_def MonoidAlgebra.one_def
@[simp]
theorem liftNC_one {g_hom : Type*} [FunLike g_hom G R] [OneHomClass g_hom G R]
(f : k →+* R) (g : g_hom) :
liftNC (f : k →+ R) g 1 = 1 := by simp [one_def]
#align monoid_algebra.lift_nc_one MonoidAlgebra.liftNC_one
end One
section MulOneClass
variable [Semiring k] [MulOneClass G]
instance nonAssocSemiring : NonAssocSemiring (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalNonAssocSemiring with
natCast := fun n => single 1 n
natCast_zero := by simp
natCast_succ := fun _ => by simp; rfl
one_mul := fun f => by
simp only [mul_def, one_def, sum_single_index, zero_mul, single_zero, sum_zero, zero_add,
one_mul, sum_single]
mul_one := fun f => by
simp only [mul_def, one_def, sum_single_index, mul_zero, single_zero, sum_zero, add_zero,
mul_one, sum_single] }
#align monoid_algebra.non_assoc_semiring MonoidAlgebra.nonAssocSemiring
theorem natCast_def (n : ℕ) : (n : MonoidAlgebra k G) = single (1 : G) (n : k) :=
rfl
#align monoid_algebra.nat_cast_def MonoidAlgebra.natCast_def
@[deprecated (since := "2024-04-17")]
alias nat_cast_def := natCast_def
end MulOneClass
/-! #### Semiring structure -/
section Semiring
variable [Semiring k] [Monoid G]
instance semiring : Semiring (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalSemiring,
MonoidAlgebra.nonAssocSemiring with }
#align monoid_algebra.semiring MonoidAlgebra.semiring
variable [Semiring R]
/-- `liftNC` as a `RingHom`, for when `f x` and `g y` commute -/
def liftNCRingHom (f : k →+* R) (g : G →* R) (h_comm : ∀ x y, Commute (f x) (g y)) :
MonoidAlgebra k G →+* R :=
{ liftNC (f : k →+ R) g with
map_one' := liftNC_one _ _
map_mul' := fun _a _b => liftNC_mul _ _ _ _ fun {_ _} _ => h_comm _ _ }
#align monoid_algebra.lift_nc_ring_hom MonoidAlgebra.liftNCRingHom
end Semiring
instance nonUnitalCommSemiring [CommSemiring k] [CommSemigroup G] :
NonUnitalCommSemiring (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalSemiring with
mul_comm := fun f g => by
simp only [mul_def, Finsupp.sum, mul_comm]
rw [Finset.sum_comm]
simp only [mul_comm] }
#align monoid_algebra.non_unital_comm_semiring MonoidAlgebra.nonUnitalCommSemiring
instance nontrivial [Semiring k] [Nontrivial k] [Nonempty G] : Nontrivial (MonoidAlgebra k G) :=
Finsupp.instNontrivial
#align monoid_algebra.nontrivial MonoidAlgebra.nontrivial
/-! #### Derived instances -/
section DerivedInstances
instance commSemiring [CommSemiring k] [CommMonoid G] : CommSemiring (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalCommSemiring, MonoidAlgebra.semiring with }
#align monoid_algebra.comm_semiring MonoidAlgebra.commSemiring
instance unique [Semiring k] [Subsingleton k] : Unique (MonoidAlgebra k G) :=
Finsupp.uniqueOfRight
#align monoid_algebra.unique MonoidAlgebra.unique
instance addCommGroup [Ring k] : AddCommGroup (MonoidAlgebra k G) :=
Finsupp.instAddCommGroup
#align monoid_algebra.add_comm_group MonoidAlgebra.addCommGroup
instance nonUnitalNonAssocRing [Ring k] [Mul G] : NonUnitalNonAssocRing (MonoidAlgebra k G) :=
{ MonoidAlgebra.addCommGroup, MonoidAlgebra.nonUnitalNonAssocSemiring with }
#align monoid_algebra.non_unital_non_assoc_ring MonoidAlgebra.nonUnitalNonAssocRing
instance nonUnitalRing [Ring k] [Semigroup G] : NonUnitalRing (MonoidAlgebra k G) :=
{ MonoidAlgebra.addCommGroup, MonoidAlgebra.nonUnitalSemiring with }
#align monoid_algebra.non_unital_ring MonoidAlgebra.nonUnitalRing
instance nonAssocRing [Ring k] [MulOneClass G] : NonAssocRing (MonoidAlgebra k G) :=
{ MonoidAlgebra.addCommGroup,
MonoidAlgebra.nonAssocSemiring with
intCast := fun z => single 1 (z : k)
-- Porting note: Both were `simpa`.
intCast_ofNat := fun n => by simp; rfl
intCast_negSucc := fun n => by simp; rfl }
#align monoid_algebra.non_assoc_ring MonoidAlgebra.nonAssocRing
theorem intCast_def [Ring k] [MulOneClass G] (z : ℤ) :
(z : MonoidAlgebra k G) = single (1 : G) (z : k) :=
rfl
#align monoid_algebra.int_cast_def MonoidAlgebra.intCast_def
@[deprecated (since := "2024-04-17")]
alias int_cast_def := intCast_def
instance ring [Ring k] [Monoid G] : Ring (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonAssocRing, MonoidAlgebra.semiring with }
#align monoid_algebra.ring MonoidAlgebra.ring
instance nonUnitalCommRing [CommRing k] [CommSemigroup G] :
NonUnitalCommRing (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalCommSemiring, MonoidAlgebra.nonUnitalRing with }
#align monoid_algebra.non_unital_comm_ring MonoidAlgebra.nonUnitalCommRing
instance commRing [CommRing k] [CommMonoid G] : CommRing (MonoidAlgebra k G) :=
{ MonoidAlgebra.nonUnitalCommRing, MonoidAlgebra.ring with }
#align monoid_algebra.comm_ring MonoidAlgebra.commRing
variable {S : Type*}
instance smulZeroClass [Semiring k] [SMulZeroClass R k] : SMulZeroClass R (MonoidAlgebra k G) :=
Finsupp.smulZeroClass
#align monoid_algebra.smul_zero_class MonoidAlgebra.smulZeroClass
instance distribSMul [Semiring k] [DistribSMul R k] : DistribSMul R (MonoidAlgebra k G) :=
Finsupp.distribSMul _ _
#align monoid_algebra.distrib_smul MonoidAlgebra.distribSMul
instance distribMulAction [Monoid R] [Semiring k] [DistribMulAction R k] :
DistribMulAction R (MonoidAlgebra k G) :=
Finsupp.distribMulAction G k
#align monoid_algebra.distrib_mul_action MonoidAlgebra.distribMulAction
instance module [Semiring R] [Semiring k] [Module R k] : Module R (MonoidAlgebra k G) :=
Finsupp.module G k
#align monoid_algebra.module MonoidAlgebra.module
instance faithfulSMul [Semiring k] [SMulZeroClass R k] [FaithfulSMul R k] [Nonempty G] :
FaithfulSMul R (MonoidAlgebra k G) :=
Finsupp.faithfulSMul
#align monoid_algebra.has_faithful_smul MonoidAlgebra.faithfulSMul
instance isScalarTower [Semiring k] [SMulZeroClass R k] [SMulZeroClass S k] [SMul R S]
[IsScalarTower R S k] : IsScalarTower R S (MonoidAlgebra k G) :=
Finsupp.isScalarTower G k
#align monoid_algebra.is_scalar_tower MonoidAlgebra.isScalarTower
instance smulCommClass [Semiring k] [SMulZeroClass R k] [SMulZeroClass S k] [SMulCommClass R S k] :
SMulCommClass R S (MonoidAlgebra k G) :=
Finsupp.smulCommClass G k
#align monoid_algebra.smul_comm_tower MonoidAlgebra.smulCommClass
instance isCentralScalar [Semiring k] [SMulZeroClass R k] [SMulZeroClass Rᵐᵒᵖ k]
[IsCentralScalar R k] : IsCentralScalar R (MonoidAlgebra k G) :=
Finsupp.isCentralScalar G k
#align monoid_algebra.is_central_scalar MonoidAlgebra.isCentralScalar
/-- This is not an instance as it conflicts with `MonoidAlgebra.distribMulAction` when `G = kˣ`.
-/
def comapDistribMulActionSelf [Group G] [Semiring k] : DistribMulAction G (MonoidAlgebra k G) :=
Finsupp.comapDistribMulAction
#align monoid_algebra.comap_distrib_mul_action_self MonoidAlgebra.comapDistribMulActionSelf
end DerivedInstances
section MiscTheorems
variable [Semiring k]
-- attribute [local reducible] MonoidAlgebra -- Porting note: `reducible` cannot be `local`.
theorem mul_apply [DecidableEq G] [Mul G] (f g : MonoidAlgebra k G) (x : G) :
(f * g) x = f.sum fun a₁ b₁ => g.sum fun a₂ b₂ => if a₁ * a₂ = x then b₁ * b₂ else 0 := by
-- Porting note: `reducible` cannot be `local` so proof gets long.
rw [mul_def, Finsupp.sum_apply]; congr; ext
rw [Finsupp.sum_apply]; congr; ext
apply single_apply
#align monoid_algebra.mul_apply MonoidAlgebra.mul_apply
theorem mul_apply_antidiagonal [Mul G] (f g : MonoidAlgebra k G) (x : G) (s : Finset (G × G))
(hs : ∀ {p : G × G}, p ∈ s ↔ p.1 * p.2 = x) : (f * g) x = ∑ p ∈ s, f p.1 * g p.2 := by
classical exact
let F : G × G → k := fun p => if p.1 * p.2 = x then f p.1 * g p.2 else 0
calc
(f * g) x = ∑ a₁ ∈ f.support, ∑ a₂ ∈ g.support, F (a₁, a₂) := mul_apply f g x
_ = ∑ p ∈ f.support ×ˢ g.support, F p := Finset.sum_product.symm
_ = ∑ p ∈ (f.support ×ˢ g.support).filter fun p : G × G => p.1 * p.2 = x, f p.1 * g p.2 :=
(Finset.sum_filter _ _).symm
_ = ∑ p ∈ s.filter fun p : G × G => p.1 ∈ f.support ∧ p.2 ∈ g.support, f p.1 * g p.2 :=
(sum_congr
(by
ext
simp only [mem_filter, mem_product, hs, and_comm])
fun _ _ => rfl)
_ = ∑ p ∈ s, f p.1 * g p.2 :=
sum_subset (filter_subset _ _) fun p hps hp => by
simp only [mem_filter, mem_support_iff, not_and, Classical.not_not] at hp ⊢
by_cases h1 : f p.1 = 0
· rw [h1, zero_mul]
· rw [hp hps h1, mul_zero]
#align monoid_algebra.mul_apply_antidiagonal MonoidAlgebra.mul_apply_antidiagonal
@[simp]
theorem single_mul_single [Mul G] {a₁ a₂ : G} {b₁ b₂ : k} :
single a₁ b₁ * single a₂ b₂ = single (a₁ * a₂) (b₁ * b₂) := by
rw [mul_def]
exact (sum_single_index (by simp only [zero_mul, single_zero, sum_zero])).trans
(sum_single_index (by rw [mul_zero, single_zero]))
#align monoid_algebra.single_mul_single MonoidAlgebra.single_mul_single
theorem single_commute_single [Mul G] {a₁ a₂ : G} {b₁ b₂ : k}
(ha : Commute a₁ a₂) (hb : Commute b₁ b₂) :
Commute (single a₁ b₁) (single a₂ b₂) :=
single_mul_single.trans <| congr_arg₂ single ha hb |>.trans single_mul_single.symm
theorem single_commute [Mul G] {a : G} {b : k} (ha : ∀ a', Commute a a') (hb : ∀ b', Commute b b') :
∀ f : MonoidAlgebra k G, Commute (single a b) f :=
suffices AddMonoidHom.mulLeft (single a b) = AddMonoidHom.mulRight (single a b) from
DFunLike.congr_fun this
addHom_ext' fun a' => AddMonoidHom.ext fun b' => single_commute_single (ha a') (hb b')
@[simp]
theorem single_pow [Monoid G] {a : G} {b : k} : ∀ n : ℕ, single a b ^ n = single (a ^ n) (b ^ n)
| 0 => by
simp only [pow_zero]
rfl
| n + 1 => by simp only [pow_succ, single_pow n, single_mul_single]
#align monoid_algebra.single_pow MonoidAlgebra.single_pow
section
/-- Like `Finsupp.mapDomain_zero`, but for the `1` we define in this file -/
@[simp]
theorem mapDomain_one {α : Type*} {β : Type*} {α₂ : Type*} [Semiring β] [One α] [One α₂]
{F : Type*} [FunLike F α α₂] [OneHomClass F α α₂] (f : F) :
(mapDomain f (1 : MonoidAlgebra β α) : MonoidAlgebra β α₂) = (1 : MonoidAlgebra β α₂) := by
simp_rw [one_def, mapDomain_single, map_one]
#align monoid_algebra.map_domain_one MonoidAlgebra.mapDomain_one
/-- Like `Finsupp.mapDomain_add`, but for the convolutive multiplication we define in this file -/
theorem mapDomain_mul {α : Type*} {β : Type*} {α₂ : Type*} [Semiring β] [Mul α] [Mul α₂]
{F : Type*} [FunLike F α α₂] [MulHomClass F α α₂] (f : F) (x y : MonoidAlgebra β α) :
mapDomain f (x * y) = mapDomain f x * mapDomain f y := by
simp_rw [mul_def, mapDomain_sum, mapDomain_single, map_mul]
rw [Finsupp.sum_mapDomain_index]
· congr
ext a b
rw [Finsupp.sum_mapDomain_index]
· simp
· simp [mul_add]
· simp
· simp [add_mul]
#align monoid_algebra.map_domain_mul MonoidAlgebra.mapDomain_mul
variable (k G)
/-- The embedding of a magma into its magma algebra. -/
@[simps]
def ofMagma [Mul G] : G →ₙ* MonoidAlgebra k G where
toFun a := single a 1
map_mul' a b := by simp only [mul_def, mul_one, sum_single_index, single_eq_zero, mul_zero]
#align monoid_algebra.of_magma MonoidAlgebra.ofMagma
#align monoid_algebra.of_magma_apply MonoidAlgebra.ofMagma_apply
/-- The embedding of a unital magma into its magma algebra. -/
@[simps]
def of [MulOneClass G] : G →* MonoidAlgebra k G :=
{ ofMagma k G with
toFun := fun a => single a 1
map_one' := rfl }
#align monoid_algebra.of MonoidAlgebra.of
#align monoid_algebra.of_apply MonoidAlgebra.of_apply
end
theorem smul_of [MulOneClass G] (g : G) (r : k) : r • of k G g = single g r := by
-- porting note (#10745): was `simp`.
rw [of_apply, smul_single', mul_one]
#align monoid_algebra.smul_of MonoidAlgebra.smul_of
theorem of_injective [MulOneClass G] [Nontrivial k] :
Function.Injective (of k G) := fun a b h => by
simpa using (single_eq_single_iff _ _ _ _).mp h
#align monoid_algebra.of_injective MonoidAlgebra.of_injective
theorem of_commute [MulOneClass G] {a : G} (h : ∀ a', Commute a a') (f : MonoidAlgebra k G) :
Commute (of k G a) f :=
single_commute h Commute.one_left f
/-- `Finsupp.single` as a `MonoidHom` from the product type into the monoid algebra.
Note the order of the elements of the product are reversed compared to the arguments of
`Finsupp.single`.
-/
@[simps]
def singleHom [MulOneClass G] : k × G →* MonoidAlgebra k G where
toFun a := single a.2 a.1
map_one' := rfl
map_mul' _a _b := single_mul_single.symm
#align monoid_algebra.single_hom MonoidAlgebra.singleHom
#align monoid_algebra.single_hom_apply MonoidAlgebra.singleHom_apply
theorem mul_single_apply_aux [Mul G] (f : MonoidAlgebra k G) {r : k} {x y z : G}
(H : ∀ a, a * x = z ↔ a = y) : (f * single x r) z = f y * r := by
classical exact
have A :
∀ a₁ b₁,
((single x r).sum fun a₂ b₂ => ite (a₁ * a₂ = z) (b₁ * b₂) 0) =
ite (a₁ * x = z) (b₁ * r) 0 :=
fun a₁ b₁ => sum_single_index <| by simp
calc
(HMul.hMul (β := MonoidAlgebra k G) f (single x r)) z =
sum f fun a b => if a = y then b * r else 0 := by simp only [mul_apply, A, H]
_ = if y ∈ f.support then f y * r else 0 := f.support.sum_ite_eq' _ _
_ = f y * r := by split_ifs with h <;> simp at h <;> simp [h]
#align monoid_algebra.mul_single_apply_aux MonoidAlgebra.mul_single_apply_aux
theorem mul_single_one_apply [MulOneClass G] (f : MonoidAlgebra k G) (r : k) (x : G) :
(HMul.hMul (β := MonoidAlgebra k G) f (single 1 r)) x = f x * r :=
f.mul_single_apply_aux fun a => by rw [mul_one]
#align monoid_algebra.mul_single_one_apply MonoidAlgebra.mul_single_one_apply
theorem mul_single_apply_of_not_exists_mul [Mul G] (r : k) {g g' : G} (x : MonoidAlgebra k G)
(h : ¬∃ d, g' = d * g) : (x * single g r) g' = 0 := by
classical
rw [mul_apply, Finsupp.sum_comm, Finsupp.sum_single_index]
swap
· simp_rw [Finsupp.sum, mul_zero, ite_self, Finset.sum_const_zero]
· apply Finset.sum_eq_zero
simp_rw [ite_eq_right_iff]
rintro g'' _hg'' rfl
exfalso
exact h ⟨_, rfl⟩
#align monoid_algebra.mul_single_apply_of_not_exists_mul MonoidAlgebra.mul_single_apply_of_not_exists_mul
theorem single_mul_apply_aux [Mul G] (f : MonoidAlgebra k G) {r : k} {x y z : G}
(H : ∀ a, x * a = y ↔ a = z) : (single x r * f) y = r * f z := by
classical exact
have : (f.sum fun a b => ite (x * a = y) (0 * b) 0) = 0 := by simp
calc
(HMul.hMul (α := MonoidAlgebra k G) (single x r) f) y =
sum f fun a b => ite (x * a = y) (r * b) 0 :=
(mul_apply _ _ _).trans <| sum_single_index this
_ = f.sum fun a b => ite (a = z) (r * b) 0 := by simp only [H]
_ = if z ∈ f.support then r * f z else 0 := f.support.sum_ite_eq' _ _
_ = _ := by split_ifs with h <;> simp at h <;> simp [h]
#align monoid_algebra.single_mul_apply_aux MonoidAlgebra.single_mul_apply_aux
theorem single_one_mul_apply [MulOneClass G] (f : MonoidAlgebra k G) (r : k) (x : G) :
(single (1 : G) r * f) x = r * f x :=
f.single_mul_apply_aux fun a => by rw [one_mul]
#align monoid_algebra.single_one_mul_apply MonoidAlgebra.single_one_mul_apply
theorem single_mul_apply_of_not_exists_mul [Mul G] (r : k) {g g' : G} (x : MonoidAlgebra k G)
(h : ¬∃ d, g' = g * d) : (single g r * x) g' = 0 := by
classical
rw [mul_apply, Finsupp.sum_single_index]
swap
· simp_rw [Finsupp.sum, zero_mul, ite_self, Finset.sum_const_zero]
· apply Finset.sum_eq_zero
simp_rw [ite_eq_right_iff]
rintro g'' _hg'' rfl
exfalso
exact h ⟨_, rfl⟩
#align monoid_algebra.single_mul_apply_of_not_exists_mul MonoidAlgebra.single_mul_apply_of_not_exists_mul
theorem liftNC_smul [MulOneClass G] {R : Type*} [Semiring R] (f : k →+* R) (g : G →* R) (c : k)
(φ : MonoidAlgebra k G) : liftNC (f : k →+ R) g (c • φ) = f c * liftNC (f : k →+ R) g φ := by
suffices (liftNC (↑f) g).comp (smulAddHom k (MonoidAlgebra k G) c) =
(AddMonoidHom.mulLeft (f c)).comp (liftNC (↑f) g) from
DFunLike.congr_fun this φ
-- Porting note: `ext` couldn't a find appropriate theorem.
refine addHom_ext' fun a => AddMonoidHom.ext fun b => ?_
-- Porting note: `reducible` cannot be `local` so the proof gets more complex.
unfold MonoidAlgebra
simp only [AddMonoidHom.coe_comp, Function.comp_apply, singleAddHom_apply, smulAddHom_apply,
smul_single, smul_eq_mul, AddMonoidHom.coe_mulLeft]
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [liftNC_single, liftNC_single]; rw [AddMonoidHom.coe_coe, map_mul, mul_assoc]
#align monoid_algebra.lift_nc_smul MonoidAlgebra.liftNC_smul
end MiscTheorems
/-! #### Non-unital, non-associative algebra structure -/
section NonUnitalNonAssocAlgebra
variable (k) [Semiring k] [DistribSMul R k] [Mul G]
instance isScalarTower_self [IsScalarTower R k k] :
IsScalarTower R (MonoidAlgebra k G) (MonoidAlgebra k G) :=
⟨fun t a b => by
-- Porting note: `ext` → `refine Finsupp.ext fun _ => ?_`
refine Finsupp.ext fun m => ?_
-- Porting note: `refine` & `rw` are required because `simp` behaves differently.
classical
simp only [smul_eq_mul, mul_apply]
rw [coe_smul]
refine Eq.trans (sum_smul_index' (g := a) (b := t) ?_) ?_ <;>
simp only [mul_apply, Finsupp.smul_sum, smul_ite, smul_mul_assoc,
zero_mul, ite_self, imp_true_iff, sum_zero, Pi.smul_apply, smul_zero]⟩
#align monoid_algebra.is_scalar_tower_self MonoidAlgebra.isScalarTower_self
/-- Note that if `k` is a `CommSemiring` then we have `SMulCommClass k k k` and so we can take
`R = k` in the below. In other words, if the coefficients are commutative amongst themselves, they
also commute with the algebra multiplication. -/
instance smulCommClass_self [SMulCommClass R k k] :
SMulCommClass R (MonoidAlgebra k G) (MonoidAlgebra k G) :=
⟨fun t a b => by
-- Porting note: `ext` → `refine Finsupp.ext fun _ => ?_`
refine Finsupp.ext fun m => ?_
-- Porting note: `refine` & `rw` are required because `simp` behaves differently.
classical
simp only [smul_eq_mul, mul_apply]
rw [coe_smul]
refine Eq.symm (Eq.trans (congr_arg (sum a)
(funext₂ fun a₁ b₁ => sum_smul_index' (g := b) (b := t) ?_)) ?_) <;>
simp only [mul_apply, Finsupp.sum, Finset.smul_sum, smul_ite, mul_smul_comm,
imp_true_iff, ite_eq_right_iff, Pi.smul_apply, mul_zero, smul_zero]⟩
#align monoid_algebra.smul_comm_class_self MonoidAlgebra.smulCommClass_self
instance smulCommClass_symm_self [SMulCommClass k R k] :
SMulCommClass (MonoidAlgebra k G) R (MonoidAlgebra k G) :=
⟨fun t a b => by
haveI := SMulCommClass.symm k R k
rw [← smul_comm]⟩
#align monoid_algebra.smul_comm_class_symm_self MonoidAlgebra.smulCommClass_symm_self
variable {A : Type u₃} [NonUnitalNonAssocSemiring A]
/-- A non_unital `k`-algebra homomorphism from `MonoidAlgebra k G` is uniquely defined by its
values on the functions `single a 1`. -/
theorem nonUnitalAlgHom_ext [DistribMulAction k A] {φ₁ φ₂ : MonoidAlgebra k G →ₙₐ[k] A}
(h : ∀ x, φ₁ (single x 1) = φ₂ (single x 1)) : φ₁ = φ₂ :=
NonUnitalAlgHom.to_distribMulActionHom_injective <|
Finsupp.distribMulActionHom_ext' fun a => DistribMulActionHom.ext_ring (h a)
#align monoid_algebra.non_unital_alg_hom_ext MonoidAlgebra.nonUnitalAlgHom_ext
/-- See note [partially-applied ext lemmas]. -/
@[ext high]
theorem nonUnitalAlgHom_ext' [DistribMulAction k A] {φ₁ φ₂ : MonoidAlgebra k G →ₙₐ[k] A}
(h : φ₁.toMulHom.comp (ofMagma k G) = φ₂.toMulHom.comp (ofMagma k G)) : φ₁ = φ₂ :=
nonUnitalAlgHom_ext k <| DFunLike.congr_fun h
#align monoid_algebra.non_unital_alg_hom_ext' MonoidAlgebra.nonUnitalAlgHom_ext'
/-- The functor `G ↦ MonoidAlgebra k G`, from the category of magmas to the category of non-unital,
non-associative algebras over `k` is adjoint to the forgetful functor in the other direction. -/
@[simps apply_apply symm_apply]
def liftMagma [Module k A] [IsScalarTower k A A] [SMulCommClass k A A] :
(G →ₙ* A) ≃ (MonoidAlgebra k G →ₙₐ[k] A) where
toFun f :=
{ liftAddHom fun x => (smulAddHom k A).flip (f x) with
toFun := fun a => a.sum fun m t => t • f m
map_smul' := fun t' a => by
-- Porting note(#12129): additional beta reduction needed
beta_reduce
rw [Finsupp.smul_sum, sum_smul_index']
· simp_rw [smul_assoc, MonoidHom.id_apply]
· intro m
exact zero_smul k (f m)
map_mul' := fun a₁ a₂ => by
let g : G → k → A := fun m t => t • f m
have h₁ : ∀ m, g m 0 = 0 := by
intro m
exact zero_smul k (f m)
have h₂ : ∀ (m) (t₁ t₂ : k), g m (t₁ + t₂) = g m t₁ + g m t₂ := by
intros
rw [← add_smul]
-- Porting note: `reducible` cannot be `local` so proof gets long.
simp_rw [Finsupp.mul_sum, Finsupp.sum_mul, smul_mul_smul, ← f.map_mul, mul_def,
sum_comm a₂ a₁]
rw [sum_sum_index h₁ h₂]; congr; ext
rw [sum_sum_index h₁ h₂]; congr; ext
rw [sum_single_index (h₁ _)] }
invFun F := F.toMulHom.comp (ofMagma k G)
left_inv f := by
ext m
simp only [NonUnitalAlgHom.coe_mk, ofMagma_apply, NonUnitalAlgHom.toMulHom_eq_coe,
sum_single_index, Function.comp_apply, one_smul, zero_smul, MulHom.coe_comp,
NonUnitalAlgHom.coe_to_mulHom]
right_inv F := by
-- Porting note: `ext` → `refine nonUnitalAlgHom_ext' k (MulHom.ext fun m => ?_)`
refine nonUnitalAlgHom_ext' k (MulHom.ext fun m => ?_)
simp only [NonUnitalAlgHom.coe_mk, ofMagma_apply, NonUnitalAlgHom.toMulHom_eq_coe,
sum_single_index, Function.comp_apply, one_smul, zero_smul, MulHom.coe_comp,
NonUnitalAlgHom.coe_to_mulHom]
#align monoid_algebra.lift_magma MonoidAlgebra.liftMagma
#align monoid_algebra.lift_magma_apply_apply MonoidAlgebra.liftMagma_apply_apply
#align monoid_algebra.lift_magma_symm_apply MonoidAlgebra.liftMagma_symm_apply
end NonUnitalNonAssocAlgebra
/-! #### Algebra structure -/
section Algebra
-- attribute [local reducible] MonoidAlgebra -- Porting note: `reducible` cannot be `local`.
theorem single_one_comm [CommSemiring k] [MulOneClass G] (r : k) (f : MonoidAlgebra k G) :
single (1 : G) r * f = f * single (1 : G) r :=
single_commute Commute.one_left (Commute.all _) f
#align monoid_algebra.single_one_comm MonoidAlgebra.single_one_comm
/-- `Finsupp.single 1` as a `RingHom` -/
@[simps]
def singleOneRingHom [Semiring k] [MulOneClass G] : k →+* MonoidAlgebra k G :=
{ Finsupp.singleAddHom 1 with
map_one' := rfl
map_mul' := fun x y => by
-- Porting note (#10691): Was `rw`.
simp only [ZeroHom.toFun_eq_coe, AddMonoidHom.toZeroHom_coe, singleAddHom_apply,
single_mul_single, mul_one] }
#align monoid_algebra.single_one_ring_hom MonoidAlgebra.singleOneRingHom
#align monoid_algebra.single_one_ring_hom_apply MonoidAlgebra.singleOneRingHom_apply
/-- If `f : G → H` is a multiplicative homomorphism between two monoids, then
`Finsupp.mapDomain f` is a ring homomorphism between their monoid algebras. -/
@[simps]
def mapDomainRingHom (k : Type*) {H F : Type*} [Semiring k] [Monoid G] [Monoid H]
[FunLike F G H] [MonoidHomClass F G H] (f : F) : MonoidAlgebra k G →+* MonoidAlgebra k H :=
{ (Finsupp.mapDomain.addMonoidHom f : MonoidAlgebra k G →+ MonoidAlgebra k H) with
map_one' := mapDomain_one f
map_mul' := fun x y => mapDomain_mul f x y }
#align monoid_algebra.map_domain_ring_hom MonoidAlgebra.mapDomainRingHom
#align monoid_algebra.map_domain_ring_hom_apply MonoidAlgebra.mapDomainRingHom_apply
/-- If two ring homomorphisms from `MonoidAlgebra k G` are equal on all `single a 1`
and `single 1 b`, then they are equal. -/
theorem ringHom_ext {R} [Semiring k] [MulOneClass G] [Semiring R] {f g : MonoidAlgebra k G →+* R}
(h₁ : ∀ b, f (single 1 b) = g (single 1 b)) (h_of : ∀ a, f (single a 1) = g (single a 1)) :
f = g :=
RingHom.coe_addMonoidHom_injective <|
addHom_ext fun a b => by
rw [← single, ← one_mul a, ← mul_one b, ← single_mul_single]
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [AddMonoidHom.coe_coe f, AddMonoidHom.coe_coe g]; rw [f.map_mul, g.map_mul, h₁, h_of]
#align monoid_algebra.ring_hom_ext MonoidAlgebra.ringHom_ext
/-- If two ring homomorphisms from `MonoidAlgebra k G` are equal on all `single a 1`
and `single 1 b`, then they are equal.
See note [partially-applied ext lemmas]. -/
@[ext high]
theorem ringHom_ext' {R} [Semiring k] [MulOneClass G] [Semiring R] {f g : MonoidAlgebra k G →+* R}
(h₁ : f.comp singleOneRingHom = g.comp singleOneRingHom)
(h_of :
(f : MonoidAlgebra k G →* R).comp (of k G) = (g : MonoidAlgebra k G →* R).comp (of k G)) :
f = g :=
ringHom_ext (RingHom.congr_fun h₁) (DFunLike.congr_fun h_of)
#align monoid_algebra.ring_hom_ext' MonoidAlgebra.ringHom_ext'
/-- The instance `Algebra k (MonoidAlgebra A G)` whenever we have `Algebra k A`.
In particular this provides the instance `Algebra k (MonoidAlgebra k G)`.
-/
instance algebra {A : Type*} [CommSemiring k] [Semiring A] [Algebra k A] [Monoid G] :
Algebra k (MonoidAlgebra A G) :=
{ singleOneRingHom.comp (algebraMap k A) with
-- Porting note: `ext` → `refine Finsupp.ext fun _ => ?_`
smul_def' := fun r a => by
refine Finsupp.ext fun _ => ?_
-- Porting note: Newly required.
rw [Finsupp.coe_smul]
simp [single_one_mul_apply, Algebra.smul_def, Pi.smul_apply]
commutes' := fun r f => by
refine Finsupp.ext fun _ => ?_
simp [single_one_mul_apply, mul_single_one_apply, Algebra.commutes] }
/-- `Finsupp.single 1` as an `AlgHom` -/
@[simps! apply]
def singleOneAlgHom {A : Type*} [CommSemiring k] [Semiring A] [Algebra k A] [Monoid G] :
A →ₐ[k] MonoidAlgebra A G :=
{ singleOneRingHom with
commutes' := fun r => by
-- Porting note: `ext` → `refine Finsupp.ext fun _ => ?_`
refine Finsupp.ext fun _ => ?_
simp
rfl }
#align monoid_algebra.single_one_alg_hom MonoidAlgebra.singleOneAlgHom
#align monoid_algebra.single_one_alg_hom_apply MonoidAlgebra.singleOneAlgHom_apply
@[simp]
theorem coe_algebraMap {A : Type*} [CommSemiring k] [Semiring A] [Algebra k A] [Monoid G] :
⇑(algebraMap k (MonoidAlgebra A G)) = single 1 ∘ algebraMap k A :=
rfl
#align monoid_algebra.coe_algebra_map MonoidAlgebra.coe_algebraMap
theorem single_eq_algebraMap_mul_of [CommSemiring k] [Monoid G] (a : G) (b : k) :
single a b = algebraMap k (MonoidAlgebra k G) b * of k G a := by simp
#align monoid_algebra.single_eq_algebra_map_mul_of MonoidAlgebra.single_eq_algebraMap_mul_of
theorem single_algebraMap_eq_algebraMap_mul_of {A : Type*} [CommSemiring k] [Semiring A]
[Algebra k A] [Monoid G] (a : G) (b : k) :
single a (algebraMap k A b) = algebraMap k (MonoidAlgebra A G) b * of A G a := by simp
#align monoid_algebra.single_algebra_map_eq_algebra_map_mul_of MonoidAlgebra.single_algebraMap_eq_algebraMap_mul_of
theorem induction_on [Semiring k] [Monoid G] {p : MonoidAlgebra k G → Prop} (f : MonoidAlgebra k G)
(hM : ∀ g, p (of k G g)) (hadd : ∀ f g : MonoidAlgebra k G, p f → p g → p (f + g))
(hsmul : ∀ (r : k) (f), p f → p (r • f)) : p f := by
refine Finsupp.induction_linear f ?_ (fun f g hf hg => hadd f g hf hg) fun g r => ?_
· simpa using hsmul 0 (of k G 1) (hM 1)
· convert hsmul r (of k G g) (hM g)
-- Porting note: Was `simp only`.
rw [of_apply, smul_single', mul_one]
#align monoid_algebra.induction_on MonoidAlgebra.induction_on
end Algebra
section lift
variable [CommSemiring k] [Monoid G] [Monoid H]
variable {A : Type u₃} [Semiring A] [Algebra k A] {B : Type*} [Semiring B] [Algebra k B]
/-- `liftNCRingHom` as an `AlgHom`, for when `f` is an `AlgHom` -/
def liftNCAlgHom (f : A →ₐ[k] B) (g : G →* B) (h_comm : ∀ x y, Commute (f x) (g y)) :
MonoidAlgebra A G →ₐ[k] B :=
{ liftNCRingHom (f : A →+* B) g h_comm with
commutes' := by simp [liftNCRingHom] }
#align monoid_algebra.lift_nc_alg_hom MonoidAlgebra.liftNCAlgHom
/-- A `k`-algebra homomorphism from `MonoidAlgebra k G` is uniquely defined by its
values on the functions `single a 1`. -/
theorem algHom_ext ⦃φ₁ φ₂ : MonoidAlgebra k G →ₐ[k] A⦄
(h : ∀ x, φ₁ (single x 1) = φ₂ (single x 1)) : φ₁ = φ₂ :=
AlgHom.toLinearMap_injective <| Finsupp.lhom_ext' fun a => LinearMap.ext_ring (h a)
#align monoid_algebra.alg_hom_ext MonoidAlgebra.algHom_ext
-- Porting note: The priority must be `high`.
/-- See note [partially-applied ext lemmas]. -/
@[ext high]
theorem algHom_ext' ⦃φ₁ φ₂ : MonoidAlgebra k G →ₐ[k] A⦄
(h :
(φ₁ : MonoidAlgebra k G →* A).comp (of k G) = (φ₂ : MonoidAlgebra k G →* A).comp (of k G)) :
φ₁ = φ₂ :=
algHom_ext <| DFunLike.congr_fun h
#align monoid_algebra.alg_hom_ext' MonoidAlgebra.algHom_ext'
variable (k G A)
/-- Any monoid homomorphism `G →* A` can be lifted to an algebra homomorphism
`MonoidAlgebra k G →ₐ[k] A`. -/
def lift : (G →* A) ≃ (MonoidAlgebra k G →ₐ[k] A) where
invFun f := (f : MonoidAlgebra k G →* A).comp (of k G)
toFun F := liftNCAlgHom (Algebra.ofId k A) F fun _ _ => Algebra.commutes _ _
left_inv f := by
ext
simp [liftNCAlgHom, liftNCRingHom]
right_inv F := by
ext
simp [liftNCAlgHom, liftNCRingHom]
#align monoid_algebra.lift MonoidAlgebra.lift
variable {k G H A}
theorem lift_apply' (F : G →* A) (f : MonoidAlgebra k G) :
lift k G A F f = f.sum fun a b => algebraMap k A b * F a :=
rfl
#align monoid_algebra.lift_apply' MonoidAlgebra.lift_apply'
theorem lift_apply (F : G →* A) (f : MonoidAlgebra k G) :
lift k G A F f = f.sum fun a b => b • F a := by simp only [lift_apply', Algebra.smul_def]
#align monoid_algebra.lift_apply MonoidAlgebra.lift_apply
theorem lift_def (F : G →* A) : ⇑(lift k G A F) = liftNC ((algebraMap k A : k →+* A) : k →+ A) F :=
rfl
#align monoid_algebra.lift_def MonoidAlgebra.lift_def
@[simp]
theorem lift_symm_apply (F : MonoidAlgebra k G →ₐ[k] A) (x : G) :
(lift k G A).symm F x = F (single x 1) :=
rfl
#align monoid_algebra.lift_symm_apply MonoidAlgebra.lift_symm_apply
@[simp]
theorem lift_single (F : G →* A) (a b) : lift k G A F (single a b) = b • F a := by
rw [lift_def, liftNC_single, Algebra.smul_def, AddMonoidHom.coe_coe]
#align monoid_algebra.lift_single MonoidAlgebra.lift_single
theorem lift_of (F : G →* A) (x) : lift k G A F (of k G x) = F x := by simp
#align monoid_algebra.lift_of MonoidAlgebra.lift_of
theorem lift_unique' (F : MonoidAlgebra k G →ₐ[k] A) :
F = lift k G A ((F : MonoidAlgebra k G →* A).comp (of k G)) :=
((lift k G A).apply_symm_apply F).symm
#align monoid_algebra.lift_unique' MonoidAlgebra.lift_unique'
/-- Decomposition of a `k`-algebra homomorphism from `MonoidAlgebra k G` by
its values on `F (single a 1)`. -/
| Mathlib/Algebra/MonoidAlgebra/Basic.lean | 946 | 950 | theorem lift_unique (F : MonoidAlgebra k G →ₐ[k] A) (f : MonoidAlgebra k G) :
F f = f.sum fun a b => b • F (single a 1) := by |
conv_lhs =>
rw [lift_unique' F]
simp [lift_apply]
|
/-
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.BigOperators.NatAntidiagonal
import Mathlib.Topology.Algebra.InfiniteSum.Constructions
import Mathlib.Topology.Algebra.Ring.Basic
#align_import topology.algebra.infinite_sum.ring from "leanprover-community/mathlib"@"9a59dcb7a2d06bf55da57b9030169219980660cd"
/-!
# Infinite sum in a ring
This file provides lemmas about the interaction between infinite sums and multiplication.
## Main results
* `tsum_mul_tsum_eq_tsum_sum_antidiagonal`: Cauchy product formula
-/
open Filter Finset Function
open scoped Classical
variable {ι κ R α : Type*}
section NonUnitalNonAssocSemiring
variable [NonUnitalNonAssocSemiring α] [TopologicalSpace α] [TopologicalSemiring α] {f g : ι → α}
{a a₁ a₂ : α}
theorem HasSum.mul_left (a₂) (h : HasSum f a₁) : HasSum (fun i ↦ a₂ * f i) (a₂ * a₁) := by
simpa only using h.map (AddMonoidHom.mulLeft a₂) (continuous_const.mul continuous_id)
#align has_sum.mul_left HasSum.mul_left
theorem HasSum.mul_right (a₂) (hf : HasSum f a₁) : HasSum (fun i ↦ f i * a₂) (a₁ * a₂) := by
simpa only using hf.map (AddMonoidHom.mulRight a₂) (continuous_id.mul continuous_const)
#align has_sum.mul_right HasSum.mul_right
theorem Summable.mul_left (a) (hf : Summable f) : Summable fun i ↦ a * f i :=
(hf.hasSum.mul_left _).summable
#align summable.mul_left Summable.mul_left
theorem Summable.mul_right (a) (hf : Summable f) : Summable fun i ↦ f i * a :=
(hf.hasSum.mul_right _).summable
#align summable.mul_right Summable.mul_right
section tsum
variable [T2Space α]
theorem Summable.tsum_mul_left (a) (hf : Summable f) : ∑' i, a * f i = a * ∑' i, f i :=
(hf.hasSum.mul_left _).tsum_eq
#align summable.tsum_mul_left Summable.tsum_mul_left
theorem Summable.tsum_mul_right (a) (hf : Summable f) : ∑' i, f i * a = (∑' i, f i) * a :=
(hf.hasSum.mul_right _).tsum_eq
#align summable.tsum_mul_right Summable.tsum_mul_right
theorem Commute.tsum_right (a) (h : ∀ i, Commute a (f i)) : Commute a (∑' i, f i) :=
if hf : Summable f then
(hf.tsum_mul_left a).symm.trans ((congr_arg _ <| funext h).trans (hf.tsum_mul_right a))
else (tsum_eq_zero_of_not_summable hf).symm ▸ Commute.zero_right _
#align commute.tsum_right Commute.tsum_right
theorem Commute.tsum_left (a) (h : ∀ i, Commute (f i) a) : Commute (∑' i, f i) a :=
(Commute.tsum_right _ fun i ↦ (h i).symm).symm
#align commute.tsum_left Commute.tsum_left
end tsum
end NonUnitalNonAssocSemiring
section DivisionSemiring
variable [DivisionSemiring α] [TopologicalSpace α] [TopologicalSemiring α] {f g : ι → α}
{a a₁ a₂ : α}
theorem HasSum.div_const (h : HasSum f a) (b : α) : HasSum (fun i ↦ f i / b) (a / b) := by
simp only [div_eq_mul_inv, h.mul_right b⁻¹]
#align has_sum.div_const HasSum.div_const
theorem Summable.div_const (h : Summable f) (b : α) : Summable fun i ↦ f i / b :=
(h.hasSum.div_const _).summable
#align summable.div_const Summable.div_const
theorem hasSum_mul_left_iff (h : a₂ ≠ 0) : HasSum (fun i ↦ a₂ * f i) (a₂ * a₁) ↔ HasSum f a₁ :=
⟨fun H ↦ by simpa only [inv_mul_cancel_left₀ h] using H.mul_left a₂⁻¹, HasSum.mul_left _⟩
#align has_sum_mul_left_iff hasSum_mul_left_iff
theorem hasSum_mul_right_iff (h : a₂ ≠ 0) : HasSum (fun i ↦ f i * a₂) (a₁ * a₂) ↔ HasSum f a₁ :=
⟨fun H ↦ by simpa only [mul_inv_cancel_right₀ h] using H.mul_right a₂⁻¹, HasSum.mul_right _⟩
#align has_sum_mul_right_iff hasSum_mul_right_iff
theorem hasSum_div_const_iff (h : a₂ ≠ 0) : HasSum (fun i ↦ f i / a₂) (a₁ / a₂) ↔ HasSum f a₁ := by
simpa only [div_eq_mul_inv] using hasSum_mul_right_iff (inv_ne_zero h)
#align has_sum_div_const_iff hasSum_div_const_iff
theorem summable_mul_left_iff (h : a ≠ 0) : (Summable fun i ↦ a * f i) ↔ Summable f :=
⟨fun H ↦ by simpa only [inv_mul_cancel_left₀ h] using H.mul_left a⁻¹, fun H ↦ H.mul_left _⟩
#align summable_mul_left_iff summable_mul_left_iff
theorem summable_mul_right_iff (h : a ≠ 0) : (Summable fun i ↦ f i * a) ↔ Summable f :=
⟨fun H ↦ by simpa only [mul_inv_cancel_right₀ h] using H.mul_right a⁻¹, fun H ↦ H.mul_right _⟩
#align summable_mul_right_iff summable_mul_right_iff
| Mathlib/Topology/Algebra/InfiniteSum/Ring.lean | 109 | 110 | theorem summable_div_const_iff (h : a ≠ 0) : (Summable fun i ↦ f i / a) ↔ Summable f := by |
simpa only [div_eq_mul_inv] using summable_mul_right_iff (inv_ne_zero h)
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Combinatorics.SimpleGraph.Connectivity
import Mathlib.Combinatorics.SimpleGraph.Operations
import Mathlib.Data.Finset.Pairwise
#align_import combinatorics.simple_graph.clique from "leanprover-community/mathlib"@"3365b20c2ffa7c35e47e5209b89ba9abdddf3ffe"
/-!
# Graph cliques
This file defines cliques in simple graphs. A clique is a set of vertices that are pairwise
adjacent.
## Main declarations
* `SimpleGraph.IsClique`: Predicate for a set of vertices to be a clique.
* `SimpleGraph.IsNClique`: Predicate for a set of vertices to be an `n`-clique.
* `SimpleGraph.cliqueFinset`: Finset of `n`-cliques of a graph.
* `SimpleGraph.CliqueFree`: Predicate for a graph to have no `n`-cliques.
## TODO
* Clique numbers
* Dualise all the API to get independent sets
-/
open Finset Fintype Function SimpleGraph.Walk
namespace SimpleGraph
variable {α β : Type*} (G H : SimpleGraph α)
/-! ### Cliques -/
section Clique
variable {s t : Set α}
/-- A clique in a graph is a set of vertices that are pairwise adjacent. -/
abbrev IsClique (s : Set α) : Prop :=
s.Pairwise G.Adj
#align simple_graph.is_clique SimpleGraph.IsClique
theorem isClique_iff : G.IsClique s ↔ s.Pairwise G.Adj :=
Iff.rfl
#align simple_graph.is_clique_iff SimpleGraph.isClique_iff
/-- A clique is a set of vertices whose induced graph is complete. -/
theorem isClique_iff_induce_eq : G.IsClique s ↔ G.induce s = ⊤ := by
rw [isClique_iff]
constructor
· intro h
ext ⟨v, hv⟩ ⟨w, hw⟩
simp only [comap_adj, Subtype.coe_mk, top_adj, Ne, Subtype.mk_eq_mk]
exact ⟨Adj.ne, h hv hw⟩
· intro h v hv w hw hne
have h2 : (G.induce s).Adj ⟨v, hv⟩ ⟨w, hw⟩ = _ := rfl
conv_lhs at h2 => rw [h]
simp only [top_adj, ne_eq, Subtype.mk.injEq, eq_iff_iff] at h2
exact h2.1 hne
#align simple_graph.is_clique_iff_induce_eq SimpleGraph.isClique_iff_induce_eq
instance [DecidableEq α] [DecidableRel G.Adj] {s : Finset α} : Decidable (G.IsClique s) :=
decidable_of_iff' _ G.isClique_iff
variable {G H} {a b : α}
lemma isClique_empty : G.IsClique ∅ := by simp
#align simple_graph.is_clique_empty SimpleGraph.isClique_empty
lemma isClique_singleton (a : α) : G.IsClique {a} := by simp
#align simple_graph.is_clique_singleton SimpleGraph.isClique_singleton
lemma isClique_pair : G.IsClique {a, b} ↔ a ≠ b → G.Adj a b := Set.pairwise_pair_of_symmetric G.symm
#align simple_graph.is_clique_pair SimpleGraph.isClique_pair
@[simp]
lemma isClique_insert : G.IsClique (insert a s) ↔ G.IsClique s ∧ ∀ b ∈ s, a ≠ b → G.Adj a b :=
Set.pairwise_insert_of_symmetric G.symm
#align simple_graph.is_clique_insert SimpleGraph.isClique_insert
lemma isClique_insert_of_not_mem (ha : a ∉ s) :
G.IsClique (insert a s) ↔ G.IsClique s ∧ ∀ b ∈ s, G.Adj a b :=
Set.pairwise_insert_of_symmetric_of_not_mem G.symm ha
#align simple_graph.is_clique_insert_of_not_mem SimpleGraph.isClique_insert_of_not_mem
lemma IsClique.insert (hs : G.IsClique s) (h : ∀ b ∈ s, a ≠ b → G.Adj a b) :
G.IsClique (insert a s) := hs.insert_of_symmetric G.symm h
#align simple_graph.is_clique.insert SimpleGraph.IsClique.insert
theorem IsClique.mono (h : G ≤ H) : G.IsClique s → H.IsClique s := Set.Pairwise.mono' h
#align simple_graph.is_clique.mono SimpleGraph.IsClique.mono
theorem IsClique.subset (h : t ⊆ s) : G.IsClique s → G.IsClique t := Set.Pairwise.mono h
#align simple_graph.is_clique.subset SimpleGraph.IsClique.subset
protected theorem IsClique.map {s : Set α} (h : G.IsClique s) {f : α ↪ β} :
(G.map f).IsClique (f '' s) := by
rintro _ ⟨a, ha, rfl⟩ _ ⟨b, hb, rfl⟩ hab
exact ⟨a, b, h ha hb <| ne_of_apply_ne _ hab, rfl, rfl⟩
#align simple_graph.is_clique.map SimpleGraph.IsClique.map
@[simp]
theorem isClique_bot_iff : (⊥ : SimpleGraph α).IsClique s ↔ (s : Set α).Subsingleton :=
Set.pairwise_bot_iff
#align simple_graph.is_clique_bot_iff SimpleGraph.isClique_bot_iff
alias ⟨IsClique.subsingleton, _⟩ := isClique_bot_iff
#align simple_graph.is_clique.subsingleton SimpleGraph.IsClique.subsingleton
end Clique
/-! ### `n`-cliques -/
section NClique
variable {n : ℕ} {s : Finset α}
/-- An `n`-clique in a graph is a set of `n` vertices which are pairwise connected. -/
structure IsNClique (n : ℕ) (s : Finset α) : Prop where
clique : G.IsClique s
card_eq : s.card = n
#align simple_graph.is_n_clique SimpleGraph.IsNClique
theorem isNClique_iff : G.IsNClique n s ↔ G.IsClique s ∧ s.card = n :=
⟨fun h ↦ ⟨h.1, h.2⟩, fun h ↦ ⟨h.1, h.2⟩⟩
#align simple_graph.is_n_clique_iff SimpleGraph.isNClique_iff
instance [DecidableEq α] [DecidableRel G.Adj] {n : ℕ} {s : Finset α} :
Decidable (G.IsNClique n s) :=
decidable_of_iff' _ G.isNClique_iff
variable {G H} {a b c : α}
@[simp] lemma isNClique_empty : G.IsNClique n ∅ ↔ n = 0 := by simp [isNClique_iff, eq_comm]
#align simple_graph.is_n_clique_empty SimpleGraph.isNClique_empty
@[simp]
lemma isNClique_singleton : G.IsNClique n {a} ↔ n = 1 := by simp [isNClique_iff, eq_comm]
#align simple_graph.is_n_clique_singleton SimpleGraph.isNClique_singleton
theorem IsNClique.mono (h : G ≤ H) : G.IsNClique n s → H.IsNClique n s := by
simp_rw [isNClique_iff]
exact And.imp_left (IsClique.mono h)
#align simple_graph.is_n_clique.mono SimpleGraph.IsNClique.mono
protected theorem IsNClique.map (h : G.IsNClique n s) {f : α ↪ β} :
(G.map f).IsNClique n (s.map f) :=
⟨by rw [coe_map]; exact h.1.map, (card_map _).trans h.2⟩
#align simple_graph.is_n_clique.map SimpleGraph.IsNClique.map
@[simp]
theorem isNClique_bot_iff : (⊥ : SimpleGraph α).IsNClique n s ↔ n ≤ 1 ∧ s.card = n := by
rw [isNClique_iff, isClique_bot_iff]
refine and_congr_left ?_
rintro rfl
exact card_le_one.symm
#align simple_graph.is_n_clique_bot_iff SimpleGraph.isNClique_bot_iff
@[simp]
theorem isNClique_zero : G.IsNClique 0 s ↔ s = ∅ := by
simp only [isNClique_iff, Finset.card_eq_zero, and_iff_right_iff_imp]; rintro rfl; simp
#align simple_graph.is_n_clique_zero SimpleGraph.isNClique_zero
@[simp]
theorem isNClique_one : G.IsNClique 1 s ↔ ∃ a, s = {a} := by
simp only [isNClique_iff, card_eq_one, and_iff_right_iff_imp]; rintro ⟨a, rfl⟩; simp
#align simple_graph.is_n_clique_one SimpleGraph.isNClique_one
section DecidableEq
variable [DecidableEq α]
theorem IsNClique.insert (hs : G.IsNClique n s) (h : ∀ b ∈ s, G.Adj a b) :
G.IsNClique (n + 1) (insert a s) := by
constructor
· push_cast
exact hs.1.insert fun b hb _ => h _ hb
· rw [card_insert_of_not_mem fun ha => (h _ ha).ne rfl, hs.2]
#align simple_graph.is_n_clique.insert SimpleGraph.IsNClique.insert
theorem is3Clique_triple_iff : G.IsNClique 3 {a, b, c} ↔ G.Adj a b ∧ G.Adj a c ∧ G.Adj b c := by
simp only [isNClique_iff, isClique_iff, Set.pairwise_insert_of_symmetric G.symm, coe_insert]
by_cases hab : a = b <;> by_cases hbc : b = c <;> by_cases hac : a = c <;> subst_vars <;>
simp [G.ne_of_adj, and_rotate, *]
#align simple_graph.is_3_clique_triple_iff SimpleGraph.is3Clique_triple_iff
theorem is3Clique_iff :
G.IsNClique 3 s ↔ ∃ a b c, G.Adj a b ∧ G.Adj a c ∧ G.Adj b c ∧ s = {a, b, c} := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, b, c, -, -, -, hs⟩ := card_eq_three.1 h.card_eq
refine ⟨a, b, c, ?_⟩
rwa [hs, eq_self_iff_true, and_true, is3Clique_triple_iff.symm, ← hs]
· rintro ⟨a, b, c, hab, hbc, hca, rfl⟩
exact is3Clique_triple_iff.2 ⟨hab, hbc, hca⟩
#align simple_graph.is_3_clique_iff SimpleGraph.is3Clique_iff
end DecidableEq
theorem is3Clique_iff_exists_cycle_length_three :
(∃ s : Finset α, G.IsNClique 3 s) ↔ ∃ (u : α) (w : G.Walk u u), w.IsCycle ∧ w.length = 3 := by
classical
simp_rw [is3Clique_iff, isCycle_def]
exact
⟨(fun ⟨_, a, _, _, hab, hac, hbc, _⟩ => ⟨a, cons hab (cons hbc (cons hac.symm nil)), by aesop⟩),
(fun ⟨_, .cons hab (.cons hbc (.cons hca nil)), _, _⟩ => ⟨_, _, _, _, hab, hca.symm, hbc, rfl⟩)⟩
end NClique
/-! ### Graphs without cliques -/
section CliqueFree
variable {m n : ℕ}
/-- `G.CliqueFree n` means that `G` has no `n`-cliques. -/
def CliqueFree (n : ℕ) : Prop :=
∀ t, ¬G.IsNClique n t
#align simple_graph.clique_free SimpleGraph.CliqueFree
variable {G H} {s : Finset α}
theorem IsNClique.not_cliqueFree (hG : G.IsNClique n s) : ¬G.CliqueFree n :=
fun h ↦ h _ hG
#align simple_graph.is_n_clique.not_clique_free SimpleGraph.IsNClique.not_cliqueFree
theorem not_cliqueFree_of_top_embedding {n : ℕ} (f : (⊤ : SimpleGraph (Fin n)) ↪g G) :
¬G.CliqueFree n := by
simp only [CliqueFree, isNClique_iff, isClique_iff_induce_eq, not_forall, Classical.not_not]
use Finset.univ.map f.toEmbedding
simp only [card_map, Finset.card_fin, eq_self_iff_true, and_true_iff]
ext ⟨v, hv⟩ ⟨w, hw⟩
simp only [coe_map, Set.mem_image, coe_univ, Set.mem_univ, true_and_iff] at hv hw
obtain ⟨v', rfl⟩ := hv
obtain ⟨w', rfl⟩ := hw
simp only [coe_sort_coe, RelEmbedding.coe_toEmbedding, comap_adj, Function.Embedding.coe_subtype,
f.map_adj_iff, top_adj, ne_eq, Subtype.mk.injEq, RelEmbedding.inj]
-- This used to be the end of the proof before leanprover/lean4#2644
erw [Function.Embedding.coe_subtype, f.map_adj_iff]
simp
#align simple_graph.not_clique_free_of_top_embedding SimpleGraph.not_cliqueFree_of_top_embedding
/-- An embedding of a complete graph that witnesses the fact that the graph is not clique-free. -/
noncomputable def topEmbeddingOfNotCliqueFree {n : ℕ} (h : ¬G.CliqueFree n) :
(⊤ : SimpleGraph (Fin n)) ↪g G := by
simp only [CliqueFree, isNClique_iff, isClique_iff_induce_eq, not_forall, Classical.not_not] at h
obtain ⟨ha, hb⟩ := h.choose_spec
have : (⊤ : SimpleGraph (Fin h.choose.card)) ≃g (⊤ : SimpleGraph h.choose) := by
apply Iso.completeGraph
simpa using (Fintype.equivFin h.choose).symm
rw [← ha] at this
convert (Embedding.induce ↑h.choose.toSet).comp this.toEmbedding
exact hb.symm
#align simple_graph.top_embedding_of_not_clique_free SimpleGraph.topEmbeddingOfNotCliqueFree
theorem not_cliqueFree_iff (n : ℕ) : ¬G.CliqueFree n ↔ Nonempty ((⊤ : SimpleGraph (Fin n)) ↪g G) :=
⟨fun h ↦ ⟨topEmbeddingOfNotCliqueFree h⟩, fun ⟨f⟩ ↦ not_cliqueFree_of_top_embedding f⟩
#align simple_graph.not_clique_free_iff SimpleGraph.not_cliqueFree_iff
theorem cliqueFree_iff {n : ℕ} : G.CliqueFree n ↔ IsEmpty ((⊤ : SimpleGraph (Fin n)) ↪g G) := by
rw [← not_iff_not, not_cliqueFree_iff, not_isEmpty_iff]
#align simple_graph.clique_free_iff SimpleGraph.cliqueFree_iff
theorem not_cliqueFree_card_of_top_embedding [Fintype α] (f : (⊤ : SimpleGraph α) ↪g G) :
¬G.CliqueFree (card α) := by
rw [not_cliqueFree_iff]
exact ⟨(Iso.completeGraph (Fintype.equivFin α)).symm.toEmbedding.trans f⟩
#align simple_graph.not_clique_free_card_of_top_embedding SimpleGraph.not_cliqueFree_card_of_top_embedding
@[simp]
theorem cliqueFree_bot (h : 2 ≤ n) : (⊥ : SimpleGraph α).CliqueFree n := by
intro t ht
have := le_trans h (isNClique_bot_iff.1 ht).1
contradiction
#align simple_graph.clique_free_bot SimpleGraph.cliqueFree_bot
theorem CliqueFree.mono (h : m ≤ n) : G.CliqueFree m → G.CliqueFree n := by
intro hG s hs
obtain ⟨t, hts, ht⟩ := s.exists_smaller_set _ (h.trans hs.card_eq.ge)
exact hG _ ⟨hs.clique.subset hts, ht⟩
#align simple_graph.clique_free.mono SimpleGraph.CliqueFree.mono
theorem CliqueFree.anti (h : G ≤ H) : H.CliqueFree n → G.CliqueFree n :=
forall_imp fun _ ↦ mt <| IsNClique.mono h
#align simple_graph.clique_free.anti SimpleGraph.CliqueFree.anti
/-- If a graph is cliquefree, any graph that embeds into it is also cliquefree. -/
theorem CliqueFree.comap {H : SimpleGraph β} (f : H ↪g G) : G.CliqueFree n → H.CliqueFree n := by
intro h; contrapose h
exact not_cliqueFree_of_top_embedding <| f.comp (topEmbeddingOfNotCliqueFree h)
/-- See `SimpleGraph.cliqueFree_of_chromaticNumber_lt` for a tighter bound. -/
theorem cliqueFree_of_card_lt [Fintype α] (hc : card α < n) : G.CliqueFree n := by
by_contra h
refine Nat.lt_le_asymm hc ?_
rw [cliqueFree_iff, not_isEmpty_iff] at h
simpa only [Fintype.card_fin] using Fintype.card_le_of_embedding h.some.toEmbedding
#align simple_graph.clique_free_of_card_lt SimpleGraph.cliqueFree_of_card_lt
/-- A complete `r`-partite graph has no `n`-cliques for `r < n`. -/
theorem cliqueFree_completeMultipartiteGraph {ι : Type*} [Fintype ι] (V : ι → Type*)
(hc : card ι < n) : (completeMultipartiteGraph V).CliqueFree n := by
rw [cliqueFree_iff, isEmpty_iff]
intro f
obtain ⟨v, w, hn, he⟩ := exists_ne_map_eq_of_card_lt (Sigma.fst ∘ f) (by simp [hc])
rw [← top_adj, ← f.map_adj_iff, comap_adj, top_adj] at hn
exact absurd he hn
/-- Clique-freeness is preserved by `replaceVertex`. -/
protected theorem CliqueFree.replaceVertex [DecidableEq α] (h : G.CliqueFree n) (s t : α) :
(G.replaceVertex s t).CliqueFree n := by
contrapose h
obtain ⟨φ, hφ⟩ := topEmbeddingOfNotCliqueFree h
rw [not_cliqueFree_iff]
by_cases mt : t ∈ Set.range φ
· obtain ⟨x, hx⟩ := mt
by_cases ms : s ∈ Set.range φ
· obtain ⟨y, hy⟩ := ms
have e := @hφ x y
simp_rw [hx, hy, adj_comm, not_adj_replaceVertex_same, top_adj, false_iff, not_ne_iff] at e
rwa [← hx, e, hy, replaceVertex_self, not_cliqueFree_iff] at h
· unfold replaceVertex at hφ
use φ.setValue x s
intro a b
simp only [Embedding.coeFn_mk, Embedding.setValue, not_exists.mp ms, ite_false]
rw [apply_ite (G.Adj · _), apply_ite (G.Adj _ ·), apply_ite (G.Adj _ ·)]
convert @hφ a b <;> simp only [← φ.apply_eq_iff_eq, SimpleGraph.irrefl, hx]
· use φ
simp_rw [Set.mem_range, not_exists, ← ne_eq] at mt
conv at hφ => enter [a, b]; rw [G.adj_replaceVertex_iff_of_ne _ (mt a) (mt b)]
exact hφ
@[simp]
theorem cliqueFree_two : G.CliqueFree 2 ↔ G = ⊥ := by
classical
constructor
· simp_rw [← edgeSet_eq_empty, Set.eq_empty_iff_forall_not_mem, Sym2.forall, mem_edgeSet]
exact fun h a b hab => h _ ⟨by simpa [hab.ne], card_pair hab.ne⟩
· rintro rfl
exact cliqueFree_bot le_rfl
#align simple_graph.clique_free_two SimpleGraph.cliqueFree_two
/-- Adding an edge increases the clique number by at most one. -/
protected theorem CliqueFree.sup_edge (h : G.CliqueFree n) (v w : α) :
(G ⊔ edge v w).CliqueFree (n + 1) := by
contrapose h
obtain ⟨f, ha⟩ := topEmbeddingOfNotCliqueFree h
simp only [ne_eq, top_adj] at ha
rw [not_cliqueFree_iff]
by_cases mw : w ∈ Set.range f
· obtain ⟨x, hx⟩ := mw
use ⟨f ∘ x.succAboveEmb, f.2.comp Fin.succAbove_right_injective⟩
intro a b
simp_rw [Embedding.coeFn_mk, comp_apply, Fin.succAboveEmb_apply, top_adj]
have hs := @ha (x.succAbove a) (x.succAbove b)
have ia : w ≠ f (x.succAbove a) :=
(hx ▸ f.apply_eq_iff_eq x (x.succAbove a)).ne.mpr (x.succAbove_ne a).symm
have ib : w ≠ f (x.succAbove b) :=
(hx ▸ f.apply_eq_iff_eq x (x.succAbove b)).ne.mpr (x.succAbove_ne b).symm
rw [sup_adj, edge_adj] at hs
simp only [ia.symm, ib.symm, and_false, false_and, or_false] at hs
rw [hs, Fin.succAbove_right_inj]
· use ⟨f ∘ Fin.succEmb n, (f.2.of_comp_iff _).mpr (Fin.succ_injective _)⟩
intro a b
simp only [Fin.val_succEmb, Embedding.coeFn_mk, comp_apply, top_adj]
have hs := @ha a.succ b.succ
have ia : f a.succ ≠ w := by simp_all
have ib : f b.succ ≠ w := by simp_all
rw [sup_adj, edge_adj] at hs
simp only [ia, ib, and_false, false_and, or_false] at hs
rw [hs, Fin.succ_inj]
end CliqueFree
section CliqueFreeOn
variable {s s₁ s₂ : Set α} {t : Finset α} {a b : α} {m n : ℕ}
/-- `G.CliqueFreeOn s n` means that `G` has no `n`-cliques contained in `s`. -/
def CliqueFreeOn (G : SimpleGraph α) (s : Set α) (n : ℕ) : Prop :=
∀ ⦃t⦄, ↑t ⊆ s → ¬G.IsNClique n t
#align simple_graph.clique_free_on SimpleGraph.CliqueFreeOn
theorem CliqueFreeOn.subset (hs : s₁ ⊆ s₂) (h₂ : G.CliqueFreeOn s₂ n) : G.CliqueFreeOn s₁ n :=
fun _t hts => h₂ <| hts.trans hs
#align simple_graph.clique_free_on.subset SimpleGraph.CliqueFreeOn.subset
theorem CliqueFreeOn.mono (hmn : m ≤ n) (hG : G.CliqueFreeOn s m) : G.CliqueFreeOn s n := by
rintro t hts ht
obtain ⟨u, hut, hu⟩ := t.exists_smaller_set _ (hmn.trans ht.card_eq.ge)
exact hG ((coe_subset.2 hut).trans hts) ⟨ht.clique.subset hut, hu⟩
#align simple_graph.clique_free_on.mono SimpleGraph.CliqueFreeOn.mono
theorem CliqueFreeOn.anti (hGH : G ≤ H) (hH : H.CliqueFreeOn s n) : G.CliqueFreeOn s n :=
fun _t hts ht => hH hts <| ht.mono hGH
#align simple_graph.clique_free_on.anti SimpleGraph.CliqueFreeOn.anti
@[simp]
theorem cliqueFreeOn_empty : G.CliqueFreeOn ∅ n ↔ n ≠ 0 := by
simp [CliqueFreeOn, Set.subset_empty_iff]
#align simple_graph.clique_free_on_empty SimpleGraph.cliqueFreeOn_empty
@[simp]
theorem cliqueFreeOn_singleton : G.CliqueFreeOn {a} n ↔ 1 < n := by
obtain _ | _ | n := n <;>
simp [CliqueFreeOn, isNClique_iff, ← subset_singleton_iff', (Nat.succ_ne_zero _).symm]
#align simple_graph.clique_free_on_singleton SimpleGraph.cliqueFreeOn_singleton
@[simp]
theorem cliqueFreeOn_univ : G.CliqueFreeOn Set.univ n ↔ G.CliqueFree n := by
simp [CliqueFree, CliqueFreeOn]
#align simple_graph.clique_free_on_univ SimpleGraph.cliqueFreeOn_univ
protected theorem CliqueFree.cliqueFreeOn (hG : G.CliqueFree n) : G.CliqueFreeOn s n :=
fun _t _ ↦ hG _
#align simple_graph.clique_free.clique_free_on SimpleGraph.CliqueFree.cliqueFreeOn
theorem cliqueFreeOn_of_card_lt {s : Finset α} (h : s.card < n) : G.CliqueFreeOn s n :=
fun _t hts ht => h.not_le <| ht.2.symm.trans_le <| card_mono hts
#align simple_graph.clique_free_on_of_card_lt SimpleGraph.cliqueFreeOn_of_card_lt
-- TODO: Restate using `SimpleGraph.IndepSet` once we have it
@[simp]
theorem cliqueFreeOn_two : G.CliqueFreeOn s 2 ↔ s.Pairwise (G.Adjᶜ) := by
classical
refine ⟨fun h a ha b hb _ hab => h ?_ ⟨by simpa [hab.ne], card_pair hab.ne⟩, ?_⟩
· push_cast
exact Set.insert_subset_iff.2 ⟨ha, Set.singleton_subset_iff.2 hb⟩
simp only [CliqueFreeOn, isNClique_iff, card_eq_two, coe_subset, not_and, not_exists]
rintro h t hst ht a b hab rfl
simp only [coe_insert, coe_singleton, Set.insert_subset_iff, Set.singleton_subset_iff] at hst
refine h hst.1 hst.2 hab (ht ?_ ?_ hab) <;> simp
#align simple_graph.clique_free_on_two SimpleGraph.cliqueFreeOn_two
theorem CliqueFreeOn.of_succ (hs : G.CliqueFreeOn s (n + 1)) (ha : a ∈ s) :
G.CliqueFreeOn (s ∩ G.neighborSet a) n := by
classical
refine fun t hts ht => hs ?_ (ht.insert fun b hb => (hts hb).2)
push_cast
exact Set.insert_subset_iff.2 ⟨ha, hts.trans Set.inter_subset_left⟩
#align simple_graph.clique_free_on.of_succ SimpleGraph.CliqueFreeOn.of_succ
end CliqueFreeOn
/-! ### Set of cliques -/
section CliqueSet
variable {n : ℕ} {a b c : α} {s : Finset α}
/-- The `n`-cliques in a graph as a set. -/
def cliqueSet (n : ℕ) : Set (Finset α) :=
{ s | G.IsNClique n s }
#align simple_graph.clique_set SimpleGraph.cliqueSet
variable {G H}
@[simp]
theorem mem_cliqueSet_iff : s ∈ G.cliqueSet n ↔ G.IsNClique n s :=
Iff.rfl
#align simple_graph.mem_clique_set_iff SimpleGraph.mem_cliqueSet_iff
@[simp]
theorem cliqueSet_eq_empty_iff : G.cliqueSet n = ∅ ↔ G.CliqueFree n := by
simp_rw [CliqueFree, Set.eq_empty_iff_forall_not_mem, mem_cliqueSet_iff]
#align simple_graph.clique_set_eq_empty_iff SimpleGraph.cliqueSet_eq_empty_iff
protected alias ⟨_, CliqueFree.cliqueSet⟩ := cliqueSet_eq_empty_iff
#align simple_graph.clique_free.clique_set SimpleGraph.CliqueFree.cliqueSet
@[mono]
theorem cliqueSet_mono (h : G ≤ H) : G.cliqueSet n ⊆ H.cliqueSet n :=
fun _ ↦ IsNClique.mono h
#align simple_graph.clique_set_mono SimpleGraph.cliqueSet_mono
theorem cliqueSet_mono' (h : G ≤ H) : G.cliqueSet ≤ H.cliqueSet :=
fun _ ↦ cliqueSet_mono h
#align simple_graph.clique_set_mono' SimpleGraph.cliqueSet_mono'
@[simp]
theorem cliqueSet_zero (G : SimpleGraph α) : G.cliqueSet 0 = {∅} := Set.ext fun s => by simp
#align simple_graph.clique_set_zero SimpleGraph.cliqueSet_zero
@[simp]
theorem cliqueSet_one (G : SimpleGraph α) : G.cliqueSet 1 = Set.range singleton :=
Set.ext fun s => by simp [eq_comm]
#align simple_graph.clique_set_one SimpleGraph.cliqueSet_one
@[simp]
theorem cliqueSet_bot (hn : 1 < n) : (⊥ : SimpleGraph α).cliqueSet n = ∅ :=
(cliqueFree_bot hn).cliqueSet
#align simple_graph.clique_set_bot SimpleGraph.cliqueSet_bot
@[simp]
theorem cliqueSet_map (hn : n ≠ 1) (G : SimpleGraph α) (f : α ↪ β) :
(G.map f).cliqueSet n = map f '' G.cliqueSet n := by
ext s
constructor
· rintro ⟨hs, rfl⟩
have hs' : (s.preimage f f.injective.injOn).map f = s := by
classical
rw [map_eq_image, image_preimage, filter_true_of_mem]
rintro a ha
obtain ⟨b, hb, hba⟩ := exists_mem_ne (hn.lt_of_le' <| Finset.card_pos.2 ⟨a, ha⟩) a
obtain ⟨c, _, _, hc, _⟩ := hs ha hb hba.symm
exact ⟨c, hc⟩
refine ⟨s.preimage f f.injective.injOn, ⟨?_, by rw [← card_map f, hs']⟩, hs'⟩
rw [coe_preimage]
exact fun a ha b hb hab => map_adj_apply.1 (hs ha hb <| f.injective.ne hab)
· rintro ⟨s, hs, rfl⟩
exact hs.map
#align simple_graph.clique_set_map SimpleGraph.cliqueSet_map
@[simp]
theorem cliqueSet_map_of_equiv (G : SimpleGraph α) (e : α ≃ β) (n : ℕ) :
(G.map e.toEmbedding).cliqueSet n = map e.toEmbedding '' G.cliqueSet n := by
obtain rfl | hn := eq_or_ne n 1
· ext
simp [e.exists_congr_left]
· exact cliqueSet_map hn _ _
#align simple_graph.clique_set_map_of_equiv SimpleGraph.cliqueSet_map_of_equiv
end CliqueSet
/-! ### Finset of cliques -/
section CliqueFinset
variable [Fintype α] [DecidableEq α] [DecidableRel G.Adj] {n : ℕ} {a b c : α} {s : Finset α}
/-- The `n`-cliques in a graph as a finset. -/
def cliqueFinset (n : ℕ) : Finset (Finset α) :=
univ.filter <| G.IsNClique n
#align simple_graph.clique_finset SimpleGraph.cliqueFinset
variable {G} in
@[simp]
theorem mem_cliqueFinset_iff : s ∈ G.cliqueFinset n ↔ G.IsNClique n s :=
mem_filter.trans <| and_iff_right <| mem_univ _
#align simple_graph.mem_clique_finset_iff SimpleGraph.mem_cliqueFinset_iff
@[simp, norm_cast]
theorem coe_cliqueFinset (n : ℕ) : (G.cliqueFinset n : Set (Finset α)) = G.cliqueSet n :=
Set.ext fun _ ↦ mem_cliqueFinset_iff
#align simple_graph.coe_clique_finset SimpleGraph.coe_cliqueFinset
variable {G}
@[simp]
theorem cliqueFinset_eq_empty_iff : G.cliqueFinset n = ∅ ↔ G.CliqueFree n := by
simp_rw [CliqueFree, eq_empty_iff_forall_not_mem, mem_cliqueFinset_iff]
#align simple_graph.clique_finset_eq_empty_iff SimpleGraph.cliqueFinset_eq_empty_iff
protected alias ⟨_, CliqueFree.cliqueFinset⟩ := cliqueFinset_eq_empty_iff
#align simple_graph.clique_free.clique_finset SimpleGraph.CliqueFree.cliqueFinset
| Mathlib/Combinatorics/SimpleGraph/Clique.lean | 566 | 569 | theorem card_cliqueFinset_le : (G.cliqueFinset n).card ≤ (card α).choose n := by |
rw [← card_univ, ← card_powersetCard]
refine card_mono fun s => ?_
simpa [mem_powersetCard_univ] using IsNClique.card_eq
|
/-
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.MeasureTheory.Integral.ExpDecay
import Mathlib.Analysis.MellinTransform
#align_import analysis.special_functions.gamma.basic from "leanprover-community/mathlib"@"cca40788df1b8755d5baf17ab2f27dacc2e17acb"
/-!
# The Gamma function
This file defines the `Γ` function (of a real or complex variable `s`). We define this by Euler's
integral `Γ(s) = ∫ x in Ioi 0, exp (-x) * x ^ (s - 1)` in the range where this integral converges
(i.e., for `0 < s` in the real case, and `0 < re s` in the complex case).
We show that this integral satisfies `Γ(1) = 1` and `Γ(s + 1) = s * Γ(s)`; hence we can define
`Γ(s)` for all `s` as the unique function satisfying this recurrence and agreeing with Euler's
integral in the convergence range. (If `s = -n` for `n ∈ ℕ`, then the function is undefined, and we
set it to be `0` by convention.)
## Gamma function: main statements (complex case)
* `Complex.Gamma`: the `Γ` function (of a complex variable).
* `Complex.Gamma_eq_integral`: for `0 < re s`, `Γ(s)` agrees with Euler's integral.
* `Complex.Gamma_add_one`: for all `s : ℂ` with `s ≠ 0`, we have `Γ (s + 1) = s Γ(s)`.
* `Complex.Gamma_nat_eq_factorial`: for all `n : ℕ` we have `Γ (n + 1) = n!`.
* `Complex.differentiableAt_Gamma`: `Γ` is complex-differentiable at all `s : ℂ` with
`s ∉ {-n : n ∈ ℕ}`.
## Gamma function: main statements (real case)
* `Real.Gamma`: the `Γ` function (of a real variable).
* Real counterparts of all the properties of the complex Gamma function listed above:
`Real.Gamma_eq_integral`, `Real.Gamma_add_one`, `Real.Gamma_nat_eq_factorial`,
`Real.differentiableAt_Gamma`.
## Tags
Gamma
-/
noncomputable section
set_option linter.uppercaseLean3 false
open Filter intervalIntegral Set Real MeasureTheory Asymptotics
open scoped Nat Topology ComplexConjugate
namespace Real
/-- Asymptotic bound for the `Γ` function integrand. -/
theorem Gamma_integrand_isLittleO (s : ℝ) :
(fun x : ℝ => exp (-x) * x ^ s) =o[atTop] fun x : ℝ => exp (-(1 / 2) * x) := by
refine isLittleO_of_tendsto (fun x hx => ?_) ?_
· exfalso; exact (exp_pos (-(1 / 2) * x)).ne' hx
have : (fun x : ℝ => exp (-x) * x ^ s / exp (-(1 / 2) * x)) =
(fun x : ℝ => exp (1 / 2 * x) / x ^ s)⁻¹ := by
ext1 x
field_simp [exp_ne_zero, exp_neg, ← Real.exp_add]
left
ring
rw [this]
exact (tendsto_exp_mul_div_rpow_atTop s (1 / 2) one_half_pos).inv_tendsto_atTop
#align real.Gamma_integrand_is_o Real.Gamma_integrand_isLittleO
/-- The Euler integral for the `Γ` function converges for positive real `s`. -/
theorem GammaIntegral_convergent {s : ℝ} (h : 0 < s) :
IntegrableOn (fun x : ℝ => exp (-x) * x ^ (s - 1)) (Ioi 0) := by
rw [← Ioc_union_Ioi_eq_Ioi (@zero_le_one ℝ _ _ _ _), integrableOn_union]
constructor
· rw [← integrableOn_Icc_iff_integrableOn_Ioc]
refine IntegrableOn.continuousOn_mul continuousOn_id.neg.rexp ?_ isCompact_Icc
refine (intervalIntegrable_iff_integrableOn_Icc_of_le zero_le_one).mp ?_
exact intervalIntegrable_rpow' (by linarith)
· refine integrable_of_isBigO_exp_neg one_half_pos ?_ (Gamma_integrand_isLittleO _).isBigO
refine continuousOn_id.neg.rexp.mul (continuousOn_id.rpow_const ?_)
intro x hx
exact Or.inl ((zero_lt_one : (0 : ℝ) < 1).trans_le hx).ne'
#align real.Gamma_integral_convergent Real.GammaIntegral_convergent
end Real
namespace Complex
/- Technical note: In defining the Gamma integrand exp (-x) * x ^ (s - 1) for s complex, we have to
make a choice between ↑(Real.exp (-x)), Complex.exp (↑(-x)), and Complex.exp (-↑x), all of which are
equal but not definitionally so. We use the first of these throughout. -/
/-- The integral defining the `Γ` function converges for complex `s` with `0 < re s`.
This is proved by reduction to the real case. -/
theorem GammaIntegral_convergent {s : ℂ} (hs : 0 < s.re) :
IntegrableOn (fun x => (-x).exp * x ^ (s - 1) : ℝ → ℂ) (Ioi 0) := by
constructor
· refine ContinuousOn.aestronglyMeasurable ?_ measurableSet_Ioi
apply (continuous_ofReal.comp continuous_neg.rexp).continuousOn.mul
apply ContinuousAt.continuousOn
intro x hx
have : ContinuousAt (fun x : ℂ => x ^ (s - 1)) ↑x :=
continuousAt_cpow_const <| ofReal_mem_slitPlane.2 hx
exact ContinuousAt.comp this continuous_ofReal.continuousAt
· rw [← hasFiniteIntegral_norm_iff]
refine HasFiniteIntegral.congr (Real.GammaIntegral_convergent hs).2 ?_
apply (ae_restrict_iff' measurableSet_Ioi).mpr
filter_upwards with x hx
rw [norm_eq_abs, map_mul, abs_of_nonneg <| le_of_lt <| exp_pos <| -x,
abs_cpow_eq_rpow_re_of_pos hx _]
simp
#align complex.Gamma_integral_convergent Complex.GammaIntegral_convergent
/-- Euler's integral for the `Γ` function (of a complex variable `s`), defined as
`∫ x in Ioi 0, exp (-x) * x ^ (s - 1)`.
See `Complex.GammaIntegral_convergent` for a proof of the convergence of the integral for
`0 < re s`. -/
def GammaIntegral (s : ℂ) : ℂ :=
∫ x in Ioi (0 : ℝ), ↑(-x).exp * ↑x ^ (s - 1)
#align complex.Gamma_integral Complex.GammaIntegral
theorem GammaIntegral_conj (s : ℂ) : GammaIntegral (conj s) = conj (GammaIntegral s) := by
rw [GammaIntegral, GammaIntegral, ← integral_conj]
refine setIntegral_congr measurableSet_Ioi fun x hx => ?_
dsimp only
rw [RingHom.map_mul, conj_ofReal, cpow_def_of_ne_zero (ofReal_ne_zero.mpr (ne_of_gt hx)),
cpow_def_of_ne_zero (ofReal_ne_zero.mpr (ne_of_gt hx)), ← exp_conj, RingHom.map_mul, ←
ofReal_log (le_of_lt hx), conj_ofReal, RingHom.map_sub, RingHom.map_one]
#align complex.Gamma_integral_conj Complex.GammaIntegral_conj
theorem GammaIntegral_ofReal (s : ℝ) :
GammaIntegral ↑s = ↑(∫ x : ℝ in Ioi 0, Real.exp (-x) * x ^ (s - 1)) := by
have : ∀ r : ℝ, Complex.ofReal' r = @RCLike.ofReal ℂ _ r := fun r => rfl
rw [GammaIntegral]
conv_rhs => rw [this, ← _root_.integral_ofReal]
refine setIntegral_congr measurableSet_Ioi ?_
intro x hx; dsimp only
conv_rhs => rw [← this]
rw [ofReal_mul, ofReal_cpow (mem_Ioi.mp hx).le]
simp
#align complex.Gamma_integral_of_real Complex.GammaIntegral_ofReal
@[simp]
theorem GammaIntegral_one : GammaIntegral 1 = 1 := by
simpa only [← ofReal_one, GammaIntegral_ofReal, ofReal_inj, sub_self, rpow_zero,
mul_one] using integral_exp_neg_Ioi_zero
#align complex.Gamma_integral_one Complex.GammaIntegral_one
end Complex
/-! Now we establish the recurrence relation `Γ(s + 1) = s * Γ(s)` using integration by parts. -/
namespace Complex
section GammaRecurrence
/-- The indefinite version of the `Γ` function, `Γ(s, X) = ∫ x ∈ 0..X, exp(-x) x ^ (s - 1)`. -/
def partialGamma (s : ℂ) (X : ℝ) : ℂ :=
∫ x in (0)..X, (-x).exp * x ^ (s - 1)
#align complex.partial_Gamma Complex.partialGamma
theorem tendsto_partialGamma {s : ℂ} (hs : 0 < s.re) :
Tendsto (fun X : ℝ => partialGamma s X) atTop (𝓝 <| GammaIntegral s) :=
intervalIntegral_tendsto_integral_Ioi 0 (GammaIntegral_convergent hs) tendsto_id
#align complex.tendsto_partial_Gamma Complex.tendsto_partialGamma
private theorem Gamma_integrand_interval_integrable (s : ℂ) {X : ℝ} (hs : 0 < s.re) (hX : 0 ≤ X) :
IntervalIntegrable (fun x => (-x).exp * x ^ (s - 1) : ℝ → ℂ) volume 0 X := by
rw [intervalIntegrable_iff_integrableOn_Ioc_of_le hX]
exact IntegrableOn.mono_set (GammaIntegral_convergent hs) Ioc_subset_Ioi_self
private theorem Gamma_integrand_deriv_integrable_A {s : ℂ} (hs : 0 < s.re) {X : ℝ} (hX : 0 ≤ X) :
IntervalIntegrable (fun x => -((-x).exp * x ^ s) : ℝ → ℂ) volume 0 X := by
convert (Gamma_integrand_interval_integrable (s + 1) _ hX).neg
· simp only [ofReal_exp, ofReal_neg, add_sub_cancel_right]; rfl
· simp only [add_re, one_re]; linarith
private theorem Gamma_integrand_deriv_integrable_B {s : ℂ} (hs : 0 < s.re) {Y : ℝ} (hY : 0 ≤ Y) :
IntervalIntegrable (fun x : ℝ => (-x).exp * (s * x ^ (s - 1)) : ℝ → ℂ) volume 0 Y := by
have : (fun x => (-x).exp * (s * x ^ (s - 1)) : ℝ → ℂ) =
(fun x => s * ((-x).exp * x ^ (s - 1)) : ℝ → ℂ) := by ext1; ring
rw [this, intervalIntegrable_iff_integrableOn_Ioc_of_le hY]
constructor
· refine (continuousOn_const.mul ?_).aestronglyMeasurable measurableSet_Ioc
apply (continuous_ofReal.comp continuous_neg.rexp).continuousOn.mul
apply ContinuousAt.continuousOn
intro x hx
refine (?_ : ContinuousAt (fun x : ℂ => x ^ (s - 1)) _).comp continuous_ofReal.continuousAt
exact continuousAt_cpow_const <| ofReal_mem_slitPlane.2 hx.1
rw [← hasFiniteIntegral_norm_iff]
simp_rw [norm_eq_abs, map_mul]
refine (((Real.GammaIntegral_convergent hs).mono_set
Ioc_subset_Ioi_self).hasFiniteIntegral.congr ?_).const_mul _
rw [EventuallyEq, ae_restrict_iff']
· filter_upwards with x hx
rw [abs_of_nonneg (exp_pos _).le, abs_cpow_eq_rpow_re_of_pos hx.1]
simp
· exact measurableSet_Ioc
/-- The recurrence relation for the indefinite version of the `Γ` function. -/
theorem partialGamma_add_one {s : ℂ} (hs : 0 < s.re) {X : ℝ} (hX : 0 ≤ X) :
partialGamma (s + 1) X = s * partialGamma s X - (-X).exp * X ^ s := by
rw [partialGamma, partialGamma, add_sub_cancel_right]
have F_der_I : ∀ x : ℝ, x ∈ Ioo 0 X → HasDerivAt (fun x => (-x).exp * x ^ s : ℝ → ℂ)
(-((-x).exp * x ^ s) + (-x).exp * (s * x ^ (s - 1))) x := by
intro x hx
have d1 : HasDerivAt (fun y : ℝ => (-y).exp) (-(-x).exp) x := by
simpa using (hasDerivAt_neg x).exp
have d2 : HasDerivAt (fun y : ℝ => (y : ℂ) ^ s) (s * x ^ (s - 1)) x := by
have t := @HasDerivAt.cpow_const _ _ _ s (hasDerivAt_id ↑x) ?_
· simpa only [mul_one] using t.comp_ofReal
· exact ofReal_mem_slitPlane.2 hx.1
simpa only [ofReal_neg, neg_mul] using d1.ofReal_comp.mul d2
have cont := (continuous_ofReal.comp continuous_neg.rexp).mul (continuous_ofReal_cpow_const hs)
have der_ible :=
(Gamma_integrand_deriv_integrable_A hs hX).add (Gamma_integrand_deriv_integrable_B hs hX)
have int_eval := integral_eq_sub_of_hasDerivAt_of_le hX cont.continuousOn F_der_I der_ible
-- We are basically done here but manipulating the output into the right form is fiddly.
apply_fun fun x : ℂ => -x at int_eval
rw [intervalIntegral.integral_add (Gamma_integrand_deriv_integrable_A hs hX)
(Gamma_integrand_deriv_integrable_B hs hX),
intervalIntegral.integral_neg, neg_add, neg_neg] at int_eval
rw [eq_sub_of_add_eq int_eval, sub_neg_eq_add, neg_sub, add_comm, add_sub]
have : (fun x => (-x).exp * (s * x ^ (s - 1)) : ℝ → ℂ) =
(fun x => s * (-x).exp * x ^ (s - 1) : ℝ → ℂ) := by ext1; ring
rw [this]
have t := @integral_const_mul 0 X volume _ _ s fun x : ℝ => (-x).exp * x ^ (s - 1)
rw [← t, ofReal_zero, zero_cpow]
· rw [mul_zero, add_zero]; congr 2; ext1; ring
· contrapose! hs; rw [hs, zero_re]
#align complex.partial_Gamma_add_one Complex.partialGamma_add_one
/-- The recurrence relation for the `Γ` integral. -/
theorem GammaIntegral_add_one {s : ℂ} (hs : 0 < s.re) :
GammaIntegral (s + 1) = s * GammaIntegral s := by
suffices Tendsto (s + 1).partialGamma atTop (𝓝 <| s * GammaIntegral s) by
refine tendsto_nhds_unique ?_ this
apply tendsto_partialGamma; rw [add_re, one_re]; linarith
have : (fun X : ℝ => s * partialGamma s X - X ^ s * (-X).exp) =ᶠ[atTop]
(s + 1).partialGamma := by
apply eventuallyEq_of_mem (Ici_mem_atTop (0 : ℝ))
intro X hX
rw [partialGamma_add_one hs (mem_Ici.mp hX)]
ring_nf
refine Tendsto.congr' this ?_
suffices Tendsto (fun X => -X ^ s * (-X).exp : ℝ → ℂ) atTop (𝓝 0) by
simpa using Tendsto.add (Tendsto.const_mul s (tendsto_partialGamma hs)) this
rw [tendsto_zero_iff_norm_tendsto_zero]
have :
(fun e : ℝ => ‖-(e : ℂ) ^ s * (-e).exp‖) =ᶠ[atTop] fun e : ℝ => e ^ s.re * (-1 * e).exp := by
refine eventuallyEq_of_mem (Ioi_mem_atTop 0) ?_
intro x hx; dsimp only
rw [norm_eq_abs, map_mul, abs.map_neg, abs_cpow_eq_rpow_re_of_pos hx,
abs_of_nonneg (exp_pos (-x)).le, neg_mul, one_mul]
exact (tendsto_congr' this).mpr (tendsto_rpow_mul_exp_neg_mul_atTop_nhds_zero _ _ zero_lt_one)
#align complex.Gamma_integral_add_one Complex.GammaIntegral_add_one
end GammaRecurrence
/-! Now we define `Γ(s)` on the whole complex plane, by recursion. -/
section GammaDef
/-- The `n`th function in this family is `Γ(s)` if `-n < s.re`, and junk otherwise. -/
noncomputable def GammaAux : ℕ → ℂ → ℂ
| 0 => GammaIntegral
| n + 1 => fun s : ℂ => GammaAux n (s + 1) / s
#align complex.Gamma_aux Complex.GammaAux
theorem GammaAux_recurrence1 (s : ℂ) (n : ℕ) (h1 : -s.re < ↑n) :
GammaAux n s = GammaAux n (s + 1) / s := by
induction' n with n hn generalizing s
· simp only [Nat.zero_eq, CharP.cast_eq_zero, Left.neg_neg_iff] at h1
dsimp only [GammaAux]; rw [GammaIntegral_add_one h1]
rw [mul_comm, mul_div_cancel_right₀]; contrapose! h1; rw [h1]
simp
· dsimp only [GammaAux]
have hh1 : -(s + 1).re < n := by
rw [Nat.cast_add, Nat.cast_one] at h1
rw [add_re, one_re]; linarith
rw [← hn (s + 1) hh1]
#align complex.Gamma_aux_recurrence1 Complex.GammaAux_recurrence1
theorem GammaAux_recurrence2 (s : ℂ) (n : ℕ) (h1 : -s.re < ↑n) :
GammaAux n s = GammaAux (n + 1) s := by
cases' n with n n
· simp only [Nat.zero_eq, CharP.cast_eq_zero, Left.neg_neg_iff] at h1
dsimp only [GammaAux]
rw [GammaIntegral_add_one h1, mul_div_cancel_left₀]
rintro rfl
rw [zero_re] at h1
exact h1.false
· dsimp only [GammaAux]
have : GammaAux n (s + 1 + 1) / (s + 1) = GammaAux n (s + 1) := by
have hh1 : -(s + 1).re < n := by
rw [Nat.cast_add, Nat.cast_one] at h1
rw [add_re, one_re]; linarith
rw [GammaAux_recurrence1 (s + 1) n hh1]
rw [this]
#align complex.Gamma_aux_recurrence2 Complex.GammaAux_recurrence2
/-- The `Γ` function (of a complex variable `s`). -/
-- @[pp_nodot] -- Porting note: removed
irreducible_def Gamma (s : ℂ) : ℂ :=
GammaAux ⌊1 - s.re⌋₊ s
#align complex.Gamma Complex.Gamma
theorem Gamma_eq_GammaAux (s : ℂ) (n : ℕ) (h1 : -s.re < ↑n) : Gamma s = GammaAux n s := by
have u : ∀ k : ℕ, GammaAux (⌊1 - s.re⌋₊ + k) s = Gamma s := by
intro k; induction' k with k hk
· simp [Gamma]
· rw [← hk, ← add_assoc]
refine (GammaAux_recurrence2 s (⌊1 - s.re⌋₊ + k) ?_).symm
rw [Nat.cast_add]
have i0 := Nat.sub_one_lt_floor (1 - s.re)
simp only [sub_sub_cancel_left] at i0
refine lt_add_of_lt_of_nonneg i0 ?_
rw [← Nat.cast_zero, Nat.cast_le]; exact Nat.zero_le k
convert (u <| n - ⌊1 - s.re⌋₊).symm; rw [Nat.add_sub_of_le]
by_cases h : 0 ≤ 1 - s.re
· apply Nat.le_of_lt_succ
exact_mod_cast lt_of_le_of_lt (Nat.floor_le h) (by linarith : 1 - s.re < n + 1)
· rw [Nat.floor_of_nonpos]
· omega
· linarith
#align complex.Gamma_eq_Gamma_aux Complex.Gamma_eq_GammaAux
/-- The recurrence relation for the `Γ` function. -/
theorem Gamma_add_one (s : ℂ) (h2 : s ≠ 0) : Gamma (s + 1) = s * Gamma s := by
let n := ⌊1 - s.re⌋₊
have t1 : -s.re < n := by simpa only [sub_sub_cancel_left] using Nat.sub_one_lt_floor (1 - s.re)
have t2 : -(s + 1).re < n := by rw [add_re, one_re]; linarith
rw [Gamma_eq_GammaAux s n t1, Gamma_eq_GammaAux (s + 1) n t2, GammaAux_recurrence1 s n t1]
field_simp
#align complex.Gamma_add_one Complex.Gamma_add_one
theorem Gamma_eq_integral {s : ℂ} (hs : 0 < s.re) : Gamma s = GammaIntegral s :=
Gamma_eq_GammaAux s 0 (by norm_cast; linarith)
#align complex.Gamma_eq_integral Complex.Gamma_eq_integral
@[simp]
| Mathlib/Analysis/SpecialFunctions/Gamma/Basic.lean | 345 | 345 | theorem Gamma_one : Gamma 1 = 1 := by | rw [Gamma_eq_integral] <;> simp
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Mario Carneiro
-/
import Mathlib.Init.Order.LinearOrder
import Mathlib.Data.Prod.Basic
import Mathlib.Data.Subtype
import Mathlib.Tactic.Spread
import Mathlib.Tactic.Convert
import Mathlib.Tactic.SimpRw
import Mathlib.Tactic.Cases
import Mathlib.Order.Notation
#align_import order.basic from "leanprover-community/mathlib"@"90df25ded755a2cf9651ea850d1abe429b1e4eb1"
/-!
# Basic definitions about `≤` and `<`
This file proves basic results about orders, provides extensive dot notation, defines useful order
classes and allows to transfer order instances.
## Type synonyms
* `OrderDual α` : A type synonym reversing the meaning of all inequalities, with notation `αᵒᵈ`.
* `AsLinearOrder α`: A type synonym to promote `PartialOrder α` to `LinearOrder α` using
`IsTotal α (≤)`.
### Transferring orders
- `Order.Preimage`, `Preorder.lift`: Transfers a (pre)order on `β` to an order on `α`
using a function `f : α → β`.
- `PartialOrder.lift`, `LinearOrder.lift`: Transfers a partial (resp., linear) order on `β` to a
partial (resp., linear) order on `α` using an injective function `f`.
### Extra class
* `DenselyOrdered`: An order with no gap, i.e. for any two elements `a < b` there exists `c` such
that `a < c < b`.
## Notes
`≤` and `<` are highly favored over `≥` and `>` in mathlib. The reason is that we can formulate all
lemmas using `≤`/`<`, and `rw` has trouble unifying `≤` and `≥`. Hence choosing one direction spares
us useless duplication. This is enforced by a linter. See Note [nolint_ge] for more infos.
Dot notation is particularly useful on `≤` (`LE.le`) and `<` (`LT.lt`). To that end, we
provide many aliases to dot notation-less lemmas. For example, `le_trans` is aliased with
`LE.le.trans` and can be used to construct `hab.trans hbc : a ≤ c` when `hab : a ≤ b`,
`hbc : b ≤ c`, `lt_of_le_of_lt` is aliased as `LE.le.trans_lt` and can be used to construct
`hab.trans hbc : a < c` when `hab : a ≤ b`, `hbc : b < c`.
## TODO
- expand module docs
- automatic construction of dual definitions / theorems
## Tags
preorder, order, partial order, poset, linear order, chain
-/
open Function
variable {ι α β : Type*} {π : ι → Type*}
section Preorder
variable [Preorder α] {a b c : α}
theorem le_trans' : b ≤ c → a ≤ b → a ≤ c :=
flip le_trans
#align le_trans' le_trans'
theorem lt_trans' : b < c → a < b → a < c :=
flip lt_trans
#align lt_trans' lt_trans'
theorem lt_of_le_of_lt' : b ≤ c → a < b → a < c :=
flip lt_of_lt_of_le
#align lt_of_le_of_lt' lt_of_le_of_lt'
theorem lt_of_lt_of_le' : b < c → a ≤ b → a < c :=
flip lt_of_le_of_lt
#align lt_of_lt_of_le' lt_of_lt_of_le'
end Preorder
section PartialOrder
variable [PartialOrder α] {a b : α}
theorem ge_antisymm : a ≤ b → b ≤ a → b = a :=
flip le_antisymm
#align ge_antisymm ge_antisymm
theorem lt_of_le_of_ne' : a ≤ b → b ≠ a → a < b := fun h₁ h₂ ↦ lt_of_le_of_ne h₁ h₂.symm
#align lt_of_le_of_ne' lt_of_le_of_ne'
theorem Ne.lt_of_le : a ≠ b → a ≤ b → a < b :=
flip lt_of_le_of_ne
#align ne.lt_of_le Ne.lt_of_le
theorem Ne.lt_of_le' : b ≠ a → a ≤ b → a < b :=
flip lt_of_le_of_ne'
#align ne.lt_of_le' Ne.lt_of_le'
end PartialOrder
attribute [simp] le_refl
attribute [ext] LE
alias LE.le.trans := le_trans
alias LE.le.trans' := le_trans'
alias LE.le.trans_lt := lt_of_le_of_lt
alias LE.le.trans_lt' := lt_of_le_of_lt'
alias LE.le.antisymm := le_antisymm
alias LE.le.antisymm' := ge_antisymm
alias LE.le.lt_of_ne := lt_of_le_of_ne
alias LE.le.lt_of_ne' := lt_of_le_of_ne'
alias LE.le.lt_of_not_le := lt_of_le_not_le
alias LE.le.lt_or_eq := lt_or_eq_of_le
alias LE.le.lt_or_eq_dec := Decidable.lt_or_eq_of_le
alias LT.lt.le := le_of_lt
alias LT.lt.trans := lt_trans
alias LT.lt.trans' := lt_trans'
alias LT.lt.trans_le := lt_of_lt_of_le
alias LT.lt.trans_le' := lt_of_lt_of_le'
alias LT.lt.ne := ne_of_lt
#align has_lt.lt.ne LT.lt.ne
alias LT.lt.asymm := lt_asymm
alias LT.lt.not_lt := lt_asymm
alias Eq.le := le_of_eq
#align eq.le Eq.le
-- Porting note: no `decidable_classical` linter
-- attribute [nolint decidable_classical] LE.le.lt_or_eq_dec
section
variable [Preorder α] {a b c : α}
@[simp]
theorem lt_self_iff_false (x : α) : x < x ↔ False :=
⟨lt_irrefl x, False.elim⟩
#align lt_self_iff_false lt_self_iff_false
#align le_of_le_of_eq le_of_le_of_eq
#align le_of_eq_of_le le_of_eq_of_le
#align lt_of_lt_of_eq lt_of_lt_of_eq
#align lt_of_eq_of_lt lt_of_eq_of_lt
theorem le_of_le_of_eq' : b ≤ c → a = b → a ≤ c :=
flip le_of_eq_of_le
#align le_of_le_of_eq' le_of_le_of_eq'
theorem le_of_eq_of_le' : b = c → a ≤ b → a ≤ c :=
flip le_of_le_of_eq
#align le_of_eq_of_le' le_of_eq_of_le'
theorem lt_of_lt_of_eq' : b < c → a = b → a < c :=
flip lt_of_eq_of_lt
#align lt_of_lt_of_eq' lt_of_lt_of_eq'
theorem lt_of_eq_of_lt' : b = c → a < b → a < c :=
flip lt_of_lt_of_eq
#align lt_of_eq_of_lt' lt_of_eq_of_lt'
alias LE.le.trans_eq := le_of_le_of_eq
alias LE.le.trans_eq' := le_of_le_of_eq'
alias LT.lt.trans_eq := lt_of_lt_of_eq
alias LT.lt.trans_eq' := lt_of_lt_of_eq'
alias Eq.trans_le := le_of_eq_of_le
#align eq.trans_le Eq.trans_le
alias Eq.trans_ge := le_of_eq_of_le'
#align eq.trans_ge Eq.trans_ge
alias Eq.trans_lt := lt_of_eq_of_lt
#align eq.trans_lt Eq.trans_lt
alias Eq.trans_gt := lt_of_eq_of_lt'
#align eq.trans_gt Eq.trans_gt
end
namespace Eq
variable [Preorder α] {x y z : α}
/-- If `x = y` then `y ≤ x`. Note: this lemma uses `y ≤ x` instead of `x ≥ y`, because `le` is used
almost exclusively in mathlib. -/
protected theorem ge (h : x = y) : y ≤ x :=
h.symm.le
#align eq.ge Eq.ge
theorem not_lt (h : x = y) : ¬x < y := fun h' ↦ h'.ne h
#align eq.not_lt Eq.not_lt
theorem not_gt (h : x = y) : ¬y < x :=
h.symm.not_lt
#align eq.not_gt Eq.not_gt
end Eq
section
variable [Preorder α] {a b : α}
@[simp] lemma le_of_subsingleton [Subsingleton α] : a ≤ b := (Subsingleton.elim a b).le
-- Making this a @[simp] lemma causes confluences problems downstream.
lemma not_lt_of_subsingleton [Subsingleton α] : ¬a < b := (Subsingleton.elim a b).not_lt
end
namespace LE.le
-- see Note [nolint_ge]
-- Porting note: linter not found @[nolint ge_or_gt]
protected theorem ge [LE α] {x y : α} (h : x ≤ y) : y ≥ x :=
h
#align has_le.le.ge LE.le.ge
section PartialOrder
variable [PartialOrder α] {a b : α}
theorem lt_iff_ne (h : a ≤ b) : a < b ↔ a ≠ b :=
⟨fun h ↦ h.ne, h.lt_of_ne⟩
#align has_le.le.lt_iff_ne LE.le.lt_iff_ne
theorem gt_iff_ne (h : a ≤ b) : a < b ↔ b ≠ a :=
⟨fun h ↦ h.ne.symm, h.lt_of_ne'⟩
#align has_le.le.gt_iff_ne LE.le.gt_iff_ne
theorem not_lt_iff_eq (h : a ≤ b) : ¬a < b ↔ a = b :=
h.lt_iff_ne.not_left
#align has_le.le.not_lt_iff_eq LE.le.not_lt_iff_eq
theorem not_gt_iff_eq (h : a ≤ b) : ¬a < b ↔ b = a :=
h.gt_iff_ne.not_left
#align has_le.le.not_gt_iff_eq LE.le.not_gt_iff_eq
theorem le_iff_eq (h : a ≤ b) : b ≤ a ↔ b = a :=
⟨fun h' ↦ h'.antisymm h, Eq.le⟩
#align has_le.le.le_iff_eq LE.le.le_iff_eq
theorem ge_iff_eq (h : a ≤ b) : b ≤ a ↔ a = b :=
⟨h.antisymm, Eq.ge⟩
#align has_le.le.ge_iff_eq LE.le.ge_iff_eq
end PartialOrder
theorem lt_or_le [LinearOrder α] {a b : α} (h : a ≤ b) (c : α) : a < c ∨ c ≤ b :=
((lt_or_ge a c).imp id) fun hc ↦ le_trans hc h
#align has_le.le.lt_or_le LE.le.lt_or_le
theorem le_or_lt [LinearOrder α] {a b : α} (h : a ≤ b) (c : α) : a ≤ c ∨ c < b :=
((le_or_gt a c).imp id) fun hc ↦ lt_of_lt_of_le hc h
#align has_le.le.le_or_lt LE.le.le_or_lt
theorem le_or_le [LinearOrder α] {a b : α} (h : a ≤ b) (c : α) : a ≤ c ∨ c ≤ b :=
(h.le_or_lt c).elim Or.inl fun h ↦ Or.inr <| le_of_lt h
#align has_le.le.le_or_le LE.le.le_or_le
end LE.le
namespace LT.lt
-- see Note [nolint_ge]
-- Porting note: linter not found @[nolint ge_or_gt]
protected theorem gt [LT α] {x y : α} (h : x < y) : y > x :=
h
#align has_lt.lt.gt LT.lt.gt
protected theorem false [Preorder α] {x : α} : x < x → False :=
lt_irrefl x
#align has_lt.lt.false LT.lt.false
theorem ne' [Preorder α] {x y : α} (h : x < y) : y ≠ x :=
h.ne.symm
#align has_lt.lt.ne' LT.lt.ne'
theorem lt_or_lt [LinearOrder α] {x y : α} (h : x < y) (z : α) : x < z ∨ z < y :=
(lt_or_ge z y).elim Or.inr fun hz ↦ Or.inl <| h.trans_le hz
#align has_lt.lt.lt_or_lt LT.lt.lt_or_lt
end LT.lt
-- see Note [nolint_ge]
-- Porting note: linter not found @[nolint ge_or_gt]
protected theorem GE.ge.le [LE α] {x y : α} (h : x ≥ y) : y ≤ x :=
h
#align ge.le GE.ge.le
-- see Note [nolint_ge]
-- Porting note: linter not found @[nolint ge_or_gt]
protected theorem GT.gt.lt [LT α] {x y : α} (h : x > y) : y < x :=
h
#align gt.lt GT.gt.lt
-- see Note [nolint_ge]
-- Porting note: linter not found @[nolint ge_or_gt]
theorem ge_of_eq [Preorder α] {a b : α} (h : a = b) : a ≥ b :=
h.ge
#align ge_of_eq ge_of_eq
#align ge_iff_le ge_iff_le
#align gt_iff_lt gt_iff_lt
theorem not_le_of_lt [Preorder α] {a b : α} (h : a < b) : ¬b ≤ a :=
(le_not_le_of_lt h).right
#align not_le_of_lt not_le_of_lt
alias LT.lt.not_le := not_le_of_lt
theorem not_lt_of_le [Preorder α] {a b : α} (h : a ≤ b) : ¬b < a := fun hba ↦ hba.not_le h
#align not_lt_of_le not_lt_of_le
alias LE.le.not_lt := not_lt_of_le
theorem ne_of_not_le [Preorder α] {a b : α} (h : ¬a ≤ b) : a ≠ b := fun hab ↦ h (le_of_eq hab)
#align ne_of_not_le ne_of_not_le
-- See Note [decidable namespace]
protected theorem Decidable.le_iff_eq_or_lt [PartialOrder α] [@DecidableRel α (· ≤ ·)] {a b : α} :
a ≤ b ↔ a = b ∨ a < b :=
Decidable.le_iff_lt_or_eq.trans or_comm
#align decidable.le_iff_eq_or_lt Decidable.le_iff_eq_or_lt
theorem le_iff_eq_or_lt [PartialOrder α] {a b : α} : a ≤ b ↔ a = b ∨ a < b :=
le_iff_lt_or_eq.trans or_comm
#align le_iff_eq_or_lt le_iff_eq_or_lt
theorem lt_iff_le_and_ne [PartialOrder α] {a b : α} : a < b ↔ a ≤ b ∧ a ≠ b :=
⟨fun h ↦ ⟨le_of_lt h, ne_of_lt h⟩, fun ⟨h1, h2⟩ ↦ h1.lt_of_ne h2⟩
#align lt_iff_le_and_ne lt_iff_le_and_ne
theorem eq_iff_not_lt_of_le [PartialOrder α] {x y : α} : x ≤ y → y = x ↔ ¬x < y := by
rw [lt_iff_le_and_ne, not_and, Classical.not_not, eq_comm]
#align eq_iff_not_lt_of_le eq_iff_not_lt_of_le
-- See Note [decidable namespace]
protected theorem Decidable.eq_iff_le_not_lt [PartialOrder α] [@DecidableRel α (· ≤ ·)] {a b : α} :
a = b ↔ a ≤ b ∧ ¬a < b :=
⟨fun h ↦ ⟨h.le, h ▸ lt_irrefl _⟩, fun ⟨h₁, h₂⟩ ↦
h₁.antisymm <| Decidable.by_contradiction fun h₃ ↦ h₂ (h₁.lt_of_not_le h₃)⟩
#align decidable.eq_iff_le_not_lt Decidable.eq_iff_le_not_lt
theorem eq_iff_le_not_lt [PartialOrder α] {a b : α} : a = b ↔ a ≤ b ∧ ¬a < b :=
haveI := Classical.dec
Decidable.eq_iff_le_not_lt
#align eq_iff_le_not_lt eq_iff_le_not_lt
theorem eq_or_lt_of_le [PartialOrder α] {a b : α} (h : a ≤ b) : a = b ∨ a < b :=
h.lt_or_eq.symm
#align eq_or_lt_of_le eq_or_lt_of_le
theorem eq_or_gt_of_le [PartialOrder α] {a b : α} (h : a ≤ b) : b = a ∨ a < b :=
h.lt_or_eq.symm.imp Eq.symm id
#align eq_or_gt_of_le eq_or_gt_of_le
theorem gt_or_eq_of_le [PartialOrder α] {a b : α} (h : a ≤ b) : a < b ∨ b = a :=
(eq_or_gt_of_le h).symm
#align gt_or_eq_of_le gt_or_eq_of_le
alias LE.le.eq_or_lt_dec := Decidable.eq_or_lt_of_le
alias LE.le.eq_or_lt := eq_or_lt_of_le
alias LE.le.eq_or_gt := eq_or_gt_of_le
alias LE.le.gt_or_eq := gt_or_eq_of_le
-- Porting note: no `decidable_classical` linter
-- attribute [nolint decidable_classical] LE.le.eq_or_lt_dec
theorem eq_of_le_of_not_lt [PartialOrder α] {a b : α} (hab : a ≤ b) (hba : ¬a < b) : a = b :=
hab.eq_or_lt.resolve_right hba
#align eq_of_le_of_not_lt eq_of_le_of_not_lt
theorem eq_of_ge_of_not_gt [PartialOrder α] {a b : α} (hab : a ≤ b) (hba : ¬a < b) : b = a :=
(hab.eq_or_lt.resolve_right hba).symm
#align eq_of_ge_of_not_gt eq_of_ge_of_not_gt
alias LE.le.eq_of_not_lt := eq_of_le_of_not_lt
alias LE.le.eq_of_not_gt := eq_of_ge_of_not_gt
theorem Ne.le_iff_lt [PartialOrder α] {a b : α} (h : a ≠ b) : a ≤ b ↔ a < b :=
⟨fun h' ↦ lt_of_le_of_ne h' h, fun h ↦ h.le⟩
#align ne.le_iff_lt Ne.le_iff_lt
theorem Ne.not_le_or_not_le [PartialOrder α] {a b : α} (h : a ≠ b) : ¬a ≤ b ∨ ¬b ≤ a :=
not_and_or.1 <| le_antisymm_iff.not.1 h
#align ne.not_le_or_not_le Ne.not_le_or_not_le
-- See Note [decidable namespace]
protected theorem Decidable.ne_iff_lt_iff_le [PartialOrder α] [DecidableEq α] {a b : α} :
(a ≠ b ↔ a < b) ↔ a ≤ b :=
⟨fun h ↦ Decidable.byCases le_of_eq (le_of_lt ∘ h.mp), fun h ↦ ⟨lt_of_le_of_ne h, ne_of_lt⟩⟩
#align decidable.ne_iff_lt_iff_le Decidable.ne_iff_lt_iff_le
@[simp]
theorem ne_iff_lt_iff_le [PartialOrder α] {a b : α} : (a ≠ b ↔ a < b) ↔ a ≤ b :=
haveI := Classical.dec
Decidable.ne_iff_lt_iff_le
#align ne_iff_lt_iff_le ne_iff_lt_iff_le
-- Variant of `min_def` with the branches reversed.
theorem min_def' [LinearOrder α] (a b : α) : min a b = if b ≤ a then b else a := by
rw [min_def]
rcases lt_trichotomy a b with (lt | eq | gt)
· rw [if_pos lt.le, if_neg (not_le.mpr lt)]
· rw [if_pos eq.le, if_pos eq.ge, eq]
· rw [if_neg (not_le.mpr gt.gt), if_pos gt.le]
#align min_def' min_def'
-- Variant of `min_def` with the branches reversed.
-- This is sometimes useful as it used to be the default.
| Mathlib/Order/Basic.lean | 447 | 452 | theorem max_def' [LinearOrder α] (a b : α) : max a b = if b ≤ a then a else b := by |
rw [max_def]
rcases lt_trichotomy a b with (lt | eq | gt)
· rw [if_pos lt.le, if_neg (not_le.mpr lt)]
· rw [if_pos eq.le, if_pos eq.ge, eq]
· rw [if_neg (not_le.mpr gt.gt), if_pos gt.le]
|
/-
Copyright (c) 2022 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.CategoryTheory.Abelian.Basic
import Mathlib.CategoryTheory.Preadditive.FunctorCategory
import Mathlib.CategoryTheory.Limits.Shapes.FunctorCategory
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
#align_import category_theory.abelian.functor_category from "leanprover-community/mathlib"@"8abfb3ba5e211d8376b855dab5d67f9eba9e0774"
/-!
# If `D` is abelian, then the functor category `C ⥤ D` is also abelian.
-/
noncomputable section
namespace CategoryTheory
open CategoryTheory.Limits
namespace Abelian
section
universe z w v u
-- Porting note: removed restrictions on universes
variable {C : Type u} [Category.{v} C]
variable {D : Type w} [Category.{z} D] [Abelian D]
namespace FunctorCategory
variable {F G : C ⥤ D} (α : F ⟶ G) (X : C)
/-- The abelian coimage in a functor category can be calculated componentwise. -/
@[simps!]
def coimageObjIso : (Abelian.coimage α).obj X ≅ Abelian.coimage (α.app X) :=
PreservesCokernel.iso ((evaluation C D).obj X) _ ≪≫
cokernel.mapIso _ _ (PreservesKernel.iso ((evaluation C D).obj X) _) (Iso.refl _)
(by
dsimp
simp only [Category.comp_id, PreservesKernel.iso_hom]
exact (kernelComparison_comp_ι _ ((evaluation C D).obj X)).symm)
#align category_theory.abelian.functor_category.coimage_obj_iso CategoryTheory.Abelian.FunctorCategory.coimageObjIso
/-- The abelian image in a functor category can be calculated componentwise. -/
@[simps!]
def imageObjIso : (Abelian.image α).obj X ≅ Abelian.image (α.app X) :=
PreservesKernel.iso ((evaluation C D).obj X) _ ≪≫
kernel.mapIso _ _ (Iso.refl _) (PreservesCokernel.iso ((evaluation C D).obj X) _)
(by
apply (cancel_mono (PreservesCokernel.iso ((evaluation C D).obj X) α).inv).1
simp only [Category.assoc, Iso.hom_inv_id]
dsimp
simp only [PreservesCokernel.iso_inv, Category.id_comp, Category.comp_id]
exact (π_comp_cokernelComparison _ ((evaluation C D).obj X)).symm)
#align category_theory.abelian.functor_category.image_obj_iso CategoryTheory.Abelian.FunctorCategory.imageObjIso
| Mathlib/CategoryTheory/Abelian/FunctorCategory.lean | 64 | 76 | theorem coimageImageComparison_app :
coimageImageComparison (α.app X) =
(coimageObjIso α X).inv ≫ (coimageImageComparison α).app X ≫ (imageObjIso α X).hom := by |
ext
dsimp
dsimp [imageObjIso, coimageObjIso, cokernel.map]
simp only [coimage_image_factorisation, PreservesKernel.iso_hom, Category.assoc,
kernel.lift_ι, Category.comp_id, PreservesCokernel.iso_inv,
cokernel.π_desc_assoc, Category.id_comp]
erw [kernelComparison_comp_ι _ ((evaluation C D).obj X),
π_comp_cokernelComparison_assoc _ ((evaluation C D).obj X)]
conv_lhs => rw [← coimage_image_factorisation α]
rfl
|
/-
Copyright (c) 2023 Ali Ramsey. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Ali Ramsey, Eric Wieser
-/
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.Prod
import Mathlib.LinearAlgebra.TensorProduct.Basic
/-!
# Coalgebras
In this file we define `Coalgebra`, and provide instances for:
* Commutative semirings: `CommSemiring.toCoalgebra`
* Binary products: `Prod.instCoalgebra`
* Finitely supported functions: `Finsupp.instCoalgebra`
## References
* <https://en.wikipedia.org/wiki/Coalgebra>
-/
suppress_compilation
universe u v w
open scoped TensorProduct
/-- Data fields for `Coalgebra`, to allow API to be constructed before proving `Coalgebra.coassoc`.
See `Coalgebra` for documentation. -/
class CoalgebraStruct (R : Type u) (A : Type v)
[CommSemiring R] [AddCommMonoid A] [Module R A] where
/-- The comultiplication of the coalgebra -/
comul : A →ₗ[R] A ⊗[R] A
/-- The counit of the coalgebra -/
counit : A →ₗ[R] R
namespace Coalgebra
export CoalgebraStruct (comul counit)
end Coalgebra
/-- A coalgebra over a commutative (semi)ring `R` is an `R`-module equipped with a coassociative
comultiplication `Δ` and a counit `ε` obeying the left and right counitality laws. -/
class Coalgebra (R : Type u) (A : Type v)
[CommSemiring R] [AddCommMonoid A] [Module R A] extends CoalgebraStruct R A where
/-- The comultiplication is coassociative -/
coassoc : TensorProduct.assoc R A A A ∘ₗ comul.rTensor A ∘ₗ comul = comul.lTensor A ∘ₗ comul
/-- The counit satisfies the left counitality law -/
rTensor_counit_comp_comul : counit.rTensor A ∘ₗ comul = TensorProduct.mk R _ _ 1
/-- The counit satisfies the right counitality law -/
lTensor_counit_comp_comul : counit.lTensor A ∘ₗ comul = (TensorProduct.mk R _ _).flip 1
namespace Coalgebra
variable {R : Type u} {A : Type v}
variable [CommSemiring R] [AddCommMonoid A] [Module R A] [Coalgebra R A]
@[simp]
theorem coassoc_apply (a : A) :
TensorProduct.assoc R A A A (comul.rTensor A (comul a)) = comul.lTensor A (comul a) :=
LinearMap.congr_fun coassoc a
@[simp]
| Mathlib/RingTheory/Coalgebra/Basic.lean | 65 | 67 | theorem coassoc_symm_apply (a : A) :
(TensorProduct.assoc R A A A).symm (comul.lTensor A (comul a)) = comul.rTensor A (comul a) := by |
rw [(TensorProduct.assoc R A A A).symm_apply_eq, coassoc_apply a]
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta
-/
import Mathlib.CategoryTheory.Sites.Sieves
#align_import category_theory.sites.sheaf_of_types from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# The sheaf condition for a presieve
We define what it means for a presheaf `P : Cᵒᵖ ⥤ Type v` to be a sheaf *for* a particular
presieve `R` on `X`:
* A *family of elements* `x` for `P` at `R` is an element `x_f` of `P Y` for every `f : Y ⟶ X` in
`R`. See `FamilyOfElements`.
* The family `x` is *compatible* if, for any `f₁ : Y₁ ⟶ X` and `f₂ : Y₂ ⟶ X` both in `R`,
and any `g₁ : Z ⟶ Y₁` and `g₂ : Z ⟶ Y₂` such that `g₁ ≫ f₁ = g₂ ≫ f₂`, the restriction of
`x_f₁` along `g₁` agrees with the restriction of `x_f₂` along `g₂`.
See `FamilyOfElements.Compatible`.
* An *amalgamation* `t` for the family is an element of `P X` such that for every `f : Y ⟶ X` in
`R`, the restriction of `t` on `f` is `x_f`.
See `FamilyOfElements.IsAmalgamation`.
We then say `P` is *separated* for `R` if every compatible family has at most one amalgamation,
and it is a *sheaf* for `R` if every compatible family has a unique amalgamation.
See `IsSeparatedFor` and `IsSheafFor`.
In the special case where `R` is a sieve, the compatibility condition can be simplified:
* The family `x` is *compatible* if, for any `f : Y ⟶ X` in `R` and `g : Z ⟶ Y`, the restriction of
`x_f` along `g` agrees with `x_(g ≫ f)` (which is well defined since `g ≫ f` is in `R`).
See `FamilyOfElements.SieveCompatible` and `compatible_iff_sieveCompatible`.
In the special case where `C` has pullbacks, the compatibility condition can be simplified:
* The family `x` is *compatible* if, for any `f : Y ⟶ X` and `g : Z ⟶ X` both in `R`,
the restriction of `x_f` along `π₁ : pullback f g ⟶ Y` agrees with the restriction of `x_g`
along `π₂ : pullback f g ⟶ Z`.
See `FamilyOfElements.PullbackCompatible` and `pullbackCompatible_iff`.
We also provide equivalent conditions to satisfy alternate definitions given in the literature.
* Stacks: The condition of https://stacks.math.columbia.edu/tag/00Z8 is virtually identical to the
statement of `isSheafFor_iff_yonedaSheafCondition` (since the bijection described there carries
the same information as the unique existence.)
* Maclane-Moerdijk [MM92]: Using `compatible_iff_sieveCompatible`, the definitions of `IsSheaf`
are equivalent. There are also alternate definitions given:
- Yoneda condition: Defined in `yonedaSheafCondition` and equivalence in
`isSheafFor_iff_yonedaSheafCondition`.
- Matching family for presieves with pullback: `pullbackCompatible_iff`.
## Implementation
The sheaf condition is given as a proposition, rather than a subsingleton in `Type (max u₁ v)`.
This doesn't seem to make a big difference, other than making a couple of definitions noncomputable,
but it means that equivalent conditions can be given as `↔` statements rather than `≃` statements,
which can be convenient.
## References
* [MM92]: *Sheaves in geometry and logic*, Saunders MacLane, and Ieke Moerdijk:
Chapter III, Section 4.
* [Elephant]: *Sketches of an Elephant*, P. T. Johnstone: C2.1.
* https://stacks.math.columbia.edu/tag/00VL (sheaves on a pretopology or site)
* https://stacks.math.columbia.edu/tag/00ZB (sheaves on a topology)
-/
universe w v₁ v₂ u₁ u₂
namespace CategoryTheory
open Opposite CategoryTheory Category Limits Sieve
namespace Presieve
variable {C : Type u₁} [Category.{v₁} C]
variable {P Q U : Cᵒᵖ ⥤ Type w}
variable {X Y : C} {S : Sieve X} {R : Presieve X}
/-- A family of elements for a presheaf `P` given a collection of arrows `R` with fixed codomain `X`
consists of an element of `P Y` for every `f : Y ⟶ X` in `R`.
A presheaf is a sheaf (resp, separated) if every *compatible* family of elements has exactly one
(resp, at most one) amalgamation.
This data is referred to as a `family` in [MM92], Chapter III, Section 4. It is also a concrete
version of the elements of the middle object in https://stacks.math.columbia.edu/tag/00VM which is
more useful for direct calculations. It is also used implicitly in Definition C2.1.2 in [Elephant].
-/
def FamilyOfElements (P : Cᵒᵖ ⥤ Type w) (R : Presieve X) :=
∀ ⦃Y : C⦄ (f : Y ⟶ X), R f → P.obj (op Y)
#align category_theory.presieve.family_of_elements CategoryTheory.Presieve.FamilyOfElements
instance : Inhabited (FamilyOfElements P (⊥ : Presieve X)) :=
⟨fun _ _ => False.elim⟩
/-- A family of elements for a presheaf on the presieve `R₂` can be restricted to a smaller presieve
`R₁`.
-/
def FamilyOfElements.restrict {R₁ R₂ : Presieve X} (h : R₁ ≤ R₂) :
FamilyOfElements P R₂ → FamilyOfElements P R₁ := fun x _ f hf => x f (h _ hf)
#align category_theory.presieve.family_of_elements.restrict CategoryTheory.Presieve.FamilyOfElements.restrict
/-- The image of a family of elements by a morphism of presheaves. -/
def FamilyOfElements.map (p : FamilyOfElements P R) (φ : P ⟶ Q) :
FamilyOfElements Q R :=
fun _ f hf => φ.app _ (p f hf)
@[simp]
lemma FamilyOfElements.map_apply
(p : FamilyOfElements P R) (φ : P ⟶ Q) {Y : C} (f : Y ⟶ X) (hf : R f) :
p.map φ f hf = φ.app _ (p f hf) := rfl
lemma FamilyOfElements.restrict_map
(p : FamilyOfElements P R) (φ : P ⟶ Q) {R' : Presieve X} (h : R' ≤ R) :
(p.restrict h).map φ = (p.map φ).restrict h := rfl
/-- A family of elements for the arrow set `R` is *compatible* if for any `f₁ : Y₁ ⟶ X` and
`f₂ : Y₂ ⟶ X` in `R`, and any `g₁ : Z ⟶ Y₁` and `g₂ : Z ⟶ Y₂`, if the square `g₁ ≫ f₁ = g₂ ≫ f₂`
commutes then the elements of `P Z` obtained by restricting the element of `P Y₁` along `g₁` and
restricting the element of `P Y₂` along `g₂` are the same.
In special cases, this condition can be simplified, see `pullbackCompatible_iff` and
`compatible_iff_sieveCompatible`.
This is referred to as a "compatible family" in Definition C2.1.2 of [Elephant], and on nlab:
https://ncatlab.org/nlab/show/sheaf#GeneralDefinitionInComponents
For a more explicit version in the case where `R` is of the form `Presieve.ofArrows`, see
`CategoryTheory.Presieve.Arrows.Compatible`.
-/
def FamilyOfElements.Compatible (x : FamilyOfElements P R) : Prop :=
∀ ⦃Y₁ Y₂ Z⦄ (g₁ : Z ⟶ Y₁) (g₂ : Z ⟶ Y₂) ⦃f₁ : Y₁ ⟶ X⦄ ⦃f₂ : Y₂ ⟶ X⦄ (h₁ : R f₁) (h₂ : R f₂),
g₁ ≫ f₁ = g₂ ≫ f₂ → P.map g₁.op (x f₁ h₁) = P.map g₂.op (x f₂ h₂)
#align category_theory.presieve.family_of_elements.compatible CategoryTheory.Presieve.FamilyOfElements.Compatible
/--
If the category `C` has pullbacks, this is an alternative condition for a family of elements to be
compatible: For any `f : Y ⟶ X` and `g : Z ⟶ X` in the presieve `R`, the restriction of the
given elements for `f` and `g` to the pullback agree.
This is equivalent to being compatible (provided `C` has pullbacks), shown in
`pullbackCompatible_iff`.
This is the definition for a "matching" family given in [MM92], Chapter III, Section 4,
Equation (5). Viewing the type `FamilyOfElements` as the middle object of the fork in
https://stacks.math.columbia.edu/tag/00VM, this condition expresses that `pr₀* (x) = pr₁* (x)`,
using the notation defined there.
For a more explicit version in the case where `R` is of the form `Presieve.ofArrows`, see
`CategoryTheory.Presieve.Arrows.PullbackCompatible`.
-/
def FamilyOfElements.PullbackCompatible (x : FamilyOfElements P R) [R.hasPullbacks] : Prop :=
∀ ⦃Y₁ Y₂⦄ ⦃f₁ : Y₁ ⟶ X⦄ ⦃f₂ : Y₂ ⟶ X⦄ (h₁ : R f₁) (h₂ : R f₂),
haveI := hasPullbacks.has_pullbacks h₁ h₂
P.map (pullback.fst : Limits.pullback f₁ f₂ ⟶ _).op (x f₁ h₁) = P.map pullback.snd.op (x f₂ h₂)
#align category_theory.presieve.family_of_elements.pullback_compatible CategoryTheory.Presieve.FamilyOfElements.PullbackCompatible
theorem pullbackCompatible_iff (x : FamilyOfElements P R) [R.hasPullbacks] :
x.Compatible ↔ x.PullbackCompatible := by
constructor
· intro t Y₁ Y₂ f₁ f₂ hf₁ hf₂
apply t
haveI := hasPullbacks.has_pullbacks hf₁ hf₂
apply pullback.condition
· intro t Y₁ Y₂ Z g₁ g₂ f₁ f₂ hf₁ hf₂ comm
haveI := hasPullbacks.has_pullbacks hf₁ hf₂
rw [← pullback.lift_fst _ _ comm, op_comp, FunctorToTypes.map_comp_apply, t hf₁ hf₂,
← FunctorToTypes.map_comp_apply, ← op_comp, pullback.lift_snd]
#align category_theory.presieve.pullback_compatible_iff CategoryTheory.Presieve.pullbackCompatible_iff
/-- The restriction of a compatible family is compatible. -/
theorem FamilyOfElements.Compatible.restrict {R₁ R₂ : Presieve X} (h : R₁ ≤ R₂)
{x : FamilyOfElements P R₂} : x.Compatible → (x.restrict h).Compatible :=
fun q _ _ _ g₁ g₂ _ _ h₁ h₂ comm => q g₁ g₂ (h _ h₁) (h _ h₂) comm
#align category_theory.presieve.family_of_elements.compatible.restrict CategoryTheory.Presieve.FamilyOfElements.Compatible.restrict
/-- Extend a family of elements to the sieve generated by an arrow set.
This is the construction described as "easy" in Lemma C2.1.3 of [Elephant].
-/
noncomputable def FamilyOfElements.sieveExtend (x : FamilyOfElements P R) :
FamilyOfElements P (generate R : Presieve X) := fun _ _ hf =>
P.map hf.choose_spec.choose.op (x _ hf.choose_spec.choose_spec.choose_spec.1)
#align category_theory.presieve.family_of_elements.sieve_extend CategoryTheory.Presieve.FamilyOfElements.sieveExtend
/-- The extension of a compatible family to the generated sieve is compatible. -/
theorem FamilyOfElements.Compatible.sieveExtend {x : FamilyOfElements P R} (hx : x.Compatible) :
x.sieveExtend.Compatible := by
intro _ _ _ _ _ _ _ h₁ h₂ comm
iterate 2 erw [← FunctorToTypes.map_comp_apply]; rw [← op_comp]
apply hx
simp [comm, h₁.choose_spec.choose_spec.choose_spec.2, h₂.choose_spec.choose_spec.choose_spec.2]
#align category_theory.presieve.family_of_elements.compatible.sieve_extend CategoryTheory.Presieve.FamilyOfElements.Compatible.sieveExtend
/-- The extension of a family agrees with the original family. -/
theorem extend_agrees {x : FamilyOfElements P R} (t : x.Compatible) {f : Y ⟶ X} (hf : R f) :
x.sieveExtend f (le_generate R Y hf) = x f hf := by
have h := (le_generate R Y hf).choose_spec
unfold FamilyOfElements.sieveExtend
rw [t h.choose (𝟙 _) _ hf _]
· simp
· rw [id_comp]
exact h.choose_spec.choose_spec.2
#align category_theory.presieve.extend_agrees CategoryTheory.Presieve.extend_agrees
/-- The restriction of an extension is the original. -/
@[simp]
| Mathlib/CategoryTheory/Sites/IsSheafFor.lean | 207 | 210 | theorem restrict_extend {x : FamilyOfElements P R} (t : x.Compatible) :
x.sieveExtend.restrict (le_generate R) = x := by |
funext Y f hf
exact extend_agrees t hf
|
/-
Copyright (c) 2023 Jason Yuen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jason Yuen
-/
import Mathlib.Data.Real.ConjExponents
import Mathlib.Data.Real.Irrational
/-!
# Rayleigh's theorem on Beatty sequences
This file proves Rayleigh's theorem on Beatty sequences. We start by proving `compl_beattySeq`,
which is a generalization of Rayleigh's theorem, and eventually prove
`Irrational.beattySeq_symmDiff_beattySeq_pos`, which is Rayleigh's theorem.
## Main definitions
* `beattySeq`: In the Beatty sequence for real number `r`, the `k`th term is `⌊k * r⌋`.
* `beattySeq'`: In this variant of the Beatty sequence for `r`, the `k`th term is `⌈k * r⌉ - 1`.
## Main statements
Define the following Beatty sets, where `r` denotes a real number:
* `B_r := {⌊k * r⌋ | k ∈ ℤ}`
* `B'_r := {⌈k * r⌉ - 1 | k ∈ ℤ}`
* `B⁺_r := {⌊r⌋, ⌊2r⌋, ⌊3r⌋, ...}`
* `B⁺'_r := {⌈r⌉-1, ⌈2r⌉-1, ⌈3r⌉-1, ...}`
The main statements are:
* `compl_beattySeq`: Let `r` be a real number greater than 1, and `1/r + 1/s = 1`.
Then the complement of `B_r` is `B'_s`.
* `beattySeq_symmDiff_beattySeq'_pos`: Let `r` be a real number greater than 1, and `1/r + 1/s = 1`.
Then `B⁺_r` and `B⁺'_s` partition the positive integers.
* `Irrational.beattySeq_symmDiff_beattySeq_pos`: Let `r` be an irrational number greater than 1, and
`1/r + 1/s = 1`. Then `B⁺_r` and `B⁺_s` partition the positive integers.
## References
* [Wikipedia, *Beatty sequence*](https://en.wikipedia.org/wiki/Beatty_sequence)
## Tags
beatty, sequence, rayleigh, irrational, floor, positive
-/
/-- In the Beatty sequence for real number `r`, the `k`th term is `⌊k * r⌋`. -/
noncomputable def beattySeq (r : ℝ) : ℤ → ℤ :=
fun k ↦ ⌊k * r⌋
/-- In this variant of the Beatty sequence for `r`, the `k`th term is `⌈k * r⌉ - 1`. -/
noncomputable def beattySeq' (r : ℝ) : ℤ → ℤ :=
fun k ↦ ⌈k * r⌉ - 1
namespace Beatty
variable {r s : ℝ} (hrs : r.IsConjExponent s) {j k : ℤ}
/-- Let `r > 1` and `1/r + 1/s = 1`. Then `B_r` and `B'_s` are disjoint (i.e. no collision exists).
-/
private theorem no_collision : Disjoint {beattySeq r k | k} {beattySeq' s k | k} := by
rw [Set.disjoint_left]
intro j ⟨k, h₁⟩ ⟨m, h₂⟩
rw [beattySeq, Int.floor_eq_iff, ← div_le_iff hrs.pos, ← lt_div_iff hrs.pos] at h₁
rw [beattySeq', sub_eq_iff_eq_add, Int.ceil_eq_iff, Int.cast_add, Int.cast_one,
add_sub_cancel_right, ← div_lt_iff hrs.symm.pos, ← le_div_iff hrs.symm.pos] at h₂
have h₃ := add_lt_add_of_le_of_lt h₁.1 h₂.1
have h₄ := add_lt_add_of_lt_of_le h₁.2 h₂.2
simp_rw [div_eq_inv_mul, ← right_distrib, hrs.inv_add_inv_conj, one_mul] at h₃ h₄
rw [← Int.cast_one] at h₄
simp_rw [← Int.cast_add, Int.cast_lt, Int.lt_add_one_iff] at h₃ h₄
exact h₄.not_lt h₃
/-- Let `r > 1` and `1/r + 1/s = 1`. Suppose there is an integer `j` where `B_r` and `B'_s` both
jump over `j` (i.e. an anti-collision). Then this leads to a contradiction. -/
private theorem no_anticollision :
¬∃ j k m : ℤ, k < j / r ∧ (j + 1) / r ≤ k + 1 ∧ m ≤ j / s ∧ (j + 1) / s < m + 1 := by
intro ⟨j, k, m, h₁₁, h₁₂, h₂₁, h₂₂⟩
have h₃ := add_lt_add_of_lt_of_le h₁₁ h₂₁
have h₄ := add_lt_add_of_le_of_lt h₁₂ h₂₂
simp_rw [div_eq_inv_mul, ← right_distrib, hrs.inv_add_inv_conj, one_mul] at h₃ h₄
rw [← Int.cast_one, ← add_assoc, add_lt_add_iff_right, add_right_comm] at h₄
simp_rw [← Int.cast_add, Int.cast_lt, Int.lt_add_one_iff] at h₃ h₄
exact h₄.not_lt h₃
/-- Let `0 < r ∈ ℝ` and `j ∈ ℤ`. Then either `j ∈ B_r` or `B_r` jumps over `j`. -/
private theorem hit_or_miss (h : r > 0) :
j ∈ {beattySeq r k | k} ∨ ∃ k : ℤ, k < j / r ∧ (j + 1) / r ≤ k + 1 := by
-- for both cases, the candidate is `k = ⌈(j + 1) / r⌉ - 1`
cases lt_or_ge ((⌈(j + 1) / r⌉ - 1) * r) j
· refine Or.inr ⟨⌈(j + 1) / r⌉ - 1, ?_⟩
rw [Int.cast_sub, Int.cast_one, lt_div_iff h, sub_add_cancel]
exact ⟨‹_›, Int.le_ceil _⟩
· refine Or.inl ⟨⌈(j + 1) / r⌉ - 1, ?_⟩
rw [beattySeq, Int.floor_eq_iff, Int.cast_sub, Int.cast_one, ← lt_div_iff h, sub_lt_iff_lt_add]
exact ⟨‹_›, Int.ceil_lt_add_one _⟩
/-- Let `0 < r ∈ ℝ` and `j ∈ ℤ`. Then either `j ∈ B'_r` or `B'_r` jumps over `j`. -/
private theorem hit_or_miss' (h : r > 0) :
j ∈ {beattySeq' r k | k} ∨ ∃ k : ℤ, k ≤ j / r ∧ (j + 1) / r < k + 1 := by
-- for both cases, the candidate is `k = ⌊(j + 1) / r⌋`
cases le_or_gt (⌊(j + 1) / r⌋ * r) j
· exact Or.inr ⟨⌊(j + 1) / r⌋, (le_div_iff h).2 ‹_›, Int.lt_floor_add_one _⟩
· refine Or.inl ⟨⌊(j + 1) / r⌋, ?_⟩
rw [beattySeq', sub_eq_iff_eq_add, Int.ceil_eq_iff, Int.cast_add, Int.cast_one]
constructor
· rwa [add_sub_cancel_right]
exact sub_nonneg.1 (Int.sub_floor_div_mul_nonneg (j + 1 : ℝ) h)
end Beatty
/-- Generalization of Rayleigh's theorem on Beatty sequences. Let `r` be a real number greater
than 1, and `1/r + 1/s = 1`. Then the complement of `B_r` is `B'_s`. -/
| Mathlib/NumberTheory/Rayleigh.lean | 115 | 124 | theorem compl_beattySeq {r s : ℝ} (hrs : r.IsConjExponent s) :
{beattySeq r k | k}ᶜ = {beattySeq' s k | k} := by |
ext j
by_cases h₁ : j ∈ {beattySeq r k | k} <;> by_cases h₂ : j ∈ {beattySeq' s k | k}
· exact (Set.not_disjoint_iff.2 ⟨j, h₁, h₂⟩ (Beatty.no_collision hrs)).elim
· simp only [Set.mem_compl_iff, h₁, h₂, not_true_eq_false]
· simp only [Set.mem_compl_iff, h₁, h₂, not_false_eq_true]
· have ⟨k, h₁₁, h₁₂⟩ := (Beatty.hit_or_miss hrs.pos).resolve_left h₁
have ⟨m, h₂₁, h₂₂⟩ := (Beatty.hit_or_miss' hrs.symm.pos).resolve_left h₂
exact (Beatty.no_anticollision hrs ⟨j, k, m, h₁₁, h₁₂, h₂₁, h₂₂⟩).elim
|
/-
Copyright (c) 2020 Johan Commelin, Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Robert Y. Lewis
-/
import Mathlib.NumberTheory.Padics.PadicIntegers
import Mathlib.RingTheory.ZMod
#align_import number_theory.padics.ring_homs from "leanprover-community/mathlib"@"565eb991e264d0db702722b4bde52ee5173c9950"
/-!
# Relating `ℤ_[p]` to `ZMod (p ^ n)`
In this file we establish connections between the `p`-adic integers $\mathbb{Z}_p$
and the integers modulo powers of `p`, $\mathbb{Z}/p^n\mathbb{Z}$.
## Main declarations
We show that $\mathbb{Z}_p$ has a ring hom to $\mathbb{Z}/p^n\mathbb{Z}$ for each `n`.
The case for `n = 1` is handled separately, since it is used in the general construction
and we may want to use it without the `^1` getting in the way.
* `PadicInt.toZMod`: ring hom to `ZMod p`
* `PadicInt.toZModPow`: ring hom to `ZMod (p^n)`
* `PadicInt.ker_toZMod` / `PadicInt.ker_toZModPow`: the kernels of these maps are the ideals
generated by `p^n`
We also establish the universal property of $\mathbb{Z}_p$ as a projective limit.
Given a family of compatible ring homs $f_k : R \to \mathbb{Z}/p^n\mathbb{Z}$,
there is a unique limit $R \to \mathbb{Z}_p$.
* `PadicInt.lift`: the limit function
* `PadicInt.lift_spec` / `PadicInt.lift_unique`: the universal property
## Implementation notes
The ring hom constructions go through an auxiliary constructor `PadicInt.toZModHom`,
which removes some boilerplate code.
-/
noncomputable section
open scoped Classical
open Nat LocalRing Padic
namespace PadicInt
variable {p : ℕ} [hp_prime : Fact p.Prime]
section RingHoms
/-! ### Ring homomorphisms to `ZMod p` and `ZMod (p ^ n)` -/
variable (p) (r : ℚ)
/-- `modPart p r` is an integer that satisfies
`‖(r - modPart p r : ℚ_[p])‖ < 1` when `‖(r : ℚ_[p])‖ ≤ 1`,
see `PadicInt.norm_sub_modPart`.
It is the unique non-negative integer that is `< p` with this property.
(Note that this definition assumes `r : ℚ`.
See `PadicInt.zmodRepr` for a version that takes values in `ℕ`
and works for arbitrary `x : ℤ_[p]`.) -/
def modPart : ℤ :=
r.num * gcdA r.den p % p
#align padic_int.mod_part PadicInt.modPart
variable {p}
theorem modPart_lt_p : modPart p r < p := by
convert Int.emod_lt _ _
· simp
· exact mod_cast hp_prime.1.ne_zero
#align padic_int.mod_part_lt_p PadicInt.modPart_lt_p
theorem modPart_nonneg : 0 ≤ modPart p r :=
Int.emod_nonneg _ <| mod_cast hp_prime.1.ne_zero
#align padic_int.mod_part_nonneg PadicInt.modPart_nonneg
theorem isUnit_den (r : ℚ) (h : ‖(r : ℚ_[p])‖ ≤ 1) : IsUnit (r.den : ℤ_[p]) := by
rw [isUnit_iff]
apply le_antisymm (r.den : ℤ_[p]).2
rw [← not_lt, coe_natCast]
intro norm_denom_lt
have hr : ‖(r * r.den : ℚ_[p])‖ = ‖(r.num : ℚ_[p])‖ := by
congr
rw_mod_cast [@Rat.mul_den_eq_num r]
rw [padicNormE.mul] at hr
have key : ‖(r.num : ℚ_[p])‖ < 1 := by
calc
_ = _ := hr.symm
_ < 1 * 1 := mul_lt_mul' h norm_denom_lt (norm_nonneg _) zero_lt_one
_ = 1 := mul_one 1
have : ↑p ∣ r.num ∧ (p : ℤ) ∣ r.den := by
simp only [← norm_int_lt_one_iff_dvd, ← padic_norm_e_of_padicInt]
exact ⟨key, norm_denom_lt⟩
apply hp_prime.1.not_dvd_one
rwa [← r.reduced.gcd_eq_one, Nat.dvd_gcd_iff, ← Int.natCast_dvd, ← Int.natCast_dvd_natCast]
#align padic_int.is_unit_denom PadicInt.isUnit_den
theorem norm_sub_modPart_aux (r : ℚ) (h : ‖(r : ℚ_[p])‖ ≤ 1) :
↑p ∣ r.num - r.num * r.den.gcdA p % p * ↑r.den := by
rw [← ZMod.intCast_zmod_eq_zero_iff_dvd]
simp only [Int.cast_natCast, ZMod.natCast_mod, Int.cast_mul, Int.cast_sub]
have := congr_arg (fun x => x % p : ℤ → ZMod p) (gcd_eq_gcd_ab r.den p)
simp only [Int.cast_natCast, CharP.cast_eq_zero, EuclideanDomain.mod_zero, Int.cast_add,
Int.cast_mul, zero_mul, add_zero] at this
push_cast
rw [mul_right_comm, mul_assoc, ← this]
suffices rdcp : r.den.Coprime p by
rw [rdcp.gcd_eq_one]
simp only [mul_one, cast_one, sub_self]
apply Coprime.symm
apply (coprime_or_dvd_of_prime hp_prime.1 _).resolve_right
rw [← Int.natCast_dvd_natCast, ← norm_int_lt_one_iff_dvd, not_lt]
apply ge_of_eq
rw [← isUnit_iff]
exact isUnit_den r h
#align padic_int.norm_sub_mod_part_aux PadicInt.norm_sub_modPart_aux
theorem norm_sub_modPart (h : ‖(r : ℚ_[p])‖ ≤ 1) : ‖(⟨r, h⟩ - modPart p r : ℤ_[p])‖ < 1 := by
let n := modPart p r
rw [norm_lt_one_iff_dvd, ← (isUnit_den r h).dvd_mul_right]
suffices ↑p ∣ r.num - n * r.den by
convert (Int.castRingHom ℤ_[p]).map_dvd this
simp only [sub_mul, Int.cast_natCast, eq_intCast, Int.cast_mul, sub_left_inj, Int.cast_sub]
apply Subtype.coe_injective
simp only [coe_mul, Subtype.coe_mk, coe_natCast]
rw_mod_cast [@Rat.mul_den_eq_num r]
rfl
exact norm_sub_modPart_aux r h
#align padic_int.norm_sub_mod_part PadicInt.norm_sub_modPart
theorem exists_mem_range_of_norm_rat_le_one (h : ‖(r : ℚ_[p])‖ ≤ 1) :
∃ n : ℤ, 0 ≤ n ∧ n < p ∧ ‖(⟨r, h⟩ - n : ℤ_[p])‖ < 1 :=
⟨modPart p r, modPart_nonneg _, modPart_lt_p _, norm_sub_modPart _ h⟩
#align padic_int.exists_mem_range_of_norm_rat_le_one PadicInt.exists_mem_range_of_norm_rat_le_one
theorem zmod_congr_of_sub_mem_span_aux (n : ℕ) (x : ℤ_[p]) (a b : ℤ)
(ha : x - a ∈ (Ideal.span {(p : ℤ_[p]) ^ n}))
(hb : x - b ∈ (Ideal.span {(p : ℤ_[p]) ^ n})) : (a : ZMod (p ^ n)) = b := by
rw [Ideal.mem_span_singleton] at ha hb
rw [← sub_eq_zero, ← Int.cast_sub, ZMod.intCast_zmod_eq_zero_iff_dvd, Int.natCast_pow]
rw [← dvd_neg, neg_sub] at ha
have := dvd_add ha hb
rwa [sub_eq_add_neg, sub_eq_add_neg, add_assoc, neg_add_cancel_left, ← sub_eq_add_neg, ←
Int.cast_sub, pow_p_dvd_int_iff] at this
#align padic_int.zmod_congr_of_sub_mem_span_aux PadicInt.zmod_congr_of_sub_mem_span_aux
theorem zmod_congr_of_sub_mem_span (n : ℕ) (x : ℤ_[p]) (a b : ℕ)
(ha : x - a ∈ (Ideal.span {(p : ℤ_[p]) ^ n}))
(hb : x - b ∈ (Ideal.span {(p : ℤ_[p]) ^ n})) : (a : ZMod (p ^ n)) = b := by
simpa using zmod_congr_of_sub_mem_span_aux n x a b ha hb
#align padic_int.zmod_congr_of_sub_mem_span PadicInt.zmod_congr_of_sub_mem_span
theorem zmod_congr_of_sub_mem_max_ideal (x : ℤ_[p]) (m n : ℕ) (hm : x - m ∈ maximalIdeal ℤ_[p])
(hn : x - n ∈ maximalIdeal ℤ_[p]) : (m : ZMod p) = n := by
rw [maximalIdeal_eq_span_p] at hm hn
have := zmod_congr_of_sub_mem_span_aux 1 x m n
simp only [pow_one] at this
specialize this hm hn
apply_fun ZMod.castHom (show p ∣ p ^ 1 by rw [pow_one]) (ZMod p) at this
simp only [map_intCast] at this
simpa only [Int.cast_natCast] using this
#align padic_int.zmod_congr_of_sub_mem_max_ideal PadicInt.zmod_congr_of_sub_mem_max_ideal
variable (x : ℤ_[p])
theorem exists_mem_range : ∃ n : ℕ, n < p ∧ x - n ∈ maximalIdeal ℤ_[p] := by
simp only [maximalIdeal_eq_span_p, Ideal.mem_span_singleton, ← norm_lt_one_iff_dvd]
obtain ⟨r, hr⟩ := rat_dense p (x : ℚ_[p]) zero_lt_one
have H : ‖(r : ℚ_[p])‖ ≤ 1 := by
rw [norm_sub_rev] at hr
calc
_ = ‖(r : ℚ_[p]) - x + x‖ := by ring_nf
_ ≤ _ := padicNormE.nonarchimedean _ _
_ ≤ _ := max_le (le_of_lt hr) x.2
obtain ⟨n, hzn, hnp, hn⟩ := exists_mem_range_of_norm_rat_le_one r H
lift n to ℕ using hzn
use n
constructor
· exact mod_cast hnp
simp only [norm_def, coe_sub, Subtype.coe_mk, coe_natCast] at hn ⊢
rw [show (x - n : ℚ_[p]) = x - r + (r - n) by ring]
apply lt_of_le_of_lt (padicNormE.nonarchimedean _ _)
apply max_lt hr
simpa using hn
#align padic_int.exists_mem_range PadicInt.exists_mem_range
/-- `zmod_repr x` is the unique natural number smaller than `p`
satisfying `‖(x - zmod_repr x : ℤ_[p])‖ < 1`.
-/
def zmodRepr : ℕ :=
Classical.choose (exists_mem_range x)
#align padic_int.zmod_repr PadicInt.zmodRepr
theorem zmodRepr_spec : zmodRepr x < p ∧ x - zmodRepr x ∈ maximalIdeal ℤ_[p] :=
Classical.choose_spec (exists_mem_range x)
#align padic_int.zmod_repr_spec PadicInt.zmodRepr_spec
theorem zmodRepr_lt_p : zmodRepr x < p :=
(zmodRepr_spec _).1
#align padic_int.zmod_repr_lt_p PadicInt.zmodRepr_lt_p
theorem sub_zmodRepr_mem : x - zmodRepr x ∈ maximalIdeal ℤ_[p] :=
(zmodRepr_spec _).2
#align padic_int.sub_zmod_repr_mem PadicInt.sub_zmodRepr_mem
/-- `toZModHom` is an auxiliary constructor for creating ring homs from `ℤ_[p]` to `ZMod v`.
-/
def toZModHom (v : ℕ) (f : ℤ_[p] → ℕ) (f_spec : ∀ x, x - f x ∈ (Ideal.span {↑v} : Ideal ℤ_[p]))
(f_congr :
∀ (x : ℤ_[p]) (a b : ℕ),
x - a ∈ (Ideal.span {↑v} : Ideal ℤ_[p]) →
x - b ∈ (Ideal.span {↑v} : Ideal ℤ_[p]) → (a : ZMod v) = b) :
ℤ_[p] →+* ZMod v where
toFun x := f x
map_zero' := by
dsimp only
rw [f_congr (0 : ℤ_[p]) _ 0, cast_zero]
· exact f_spec _
· simp only [sub_zero, cast_zero, Submodule.zero_mem]
map_one' := by
dsimp only
rw [f_congr (1 : ℤ_[p]) _ 1, cast_one]
· exact f_spec _
· simp only [sub_self, cast_one, Submodule.zero_mem]
map_add' := by
intro x y
dsimp only
rw [f_congr (x + y) _ (f x + f y), cast_add]
· exact f_spec _
· convert Ideal.add_mem _ (f_spec x) (f_spec y) using 1
rw [cast_add]
ring
map_mul' := by
intro x y
dsimp only
rw [f_congr (x * y) _ (f x * f y), cast_mul]
· exact f_spec _
· let I : Ideal ℤ_[p] := Ideal.span {↑v}
convert I.add_mem (I.mul_mem_left x (f_spec y)) (I.mul_mem_right ↑(f y) (f_spec x)) using 1
rw [cast_mul]
ring
#align padic_int.to_zmod_hom PadicInt.toZModHom
/-- `toZMod` is a ring hom from `ℤ_[p]` to `ZMod p`,
with the equality `toZMod x = (zmodRepr x : ZMod p)`.
-/
def toZMod : ℤ_[p] →+* ZMod p :=
toZModHom p zmodRepr
(by
rw [← maximalIdeal_eq_span_p]
exact sub_zmodRepr_mem)
(by
rw [← maximalIdeal_eq_span_p]
exact zmod_congr_of_sub_mem_max_ideal)
#align padic_int.to_zmod PadicInt.toZMod
/-- `z - (toZMod z : ℤ_[p])` is contained in the maximal ideal of `ℤ_[p]`, for every `z : ℤ_[p]`.
The coercion from `ZMod p` to `ℤ_[p]` is `ZMod.cast`,
which coerces `ZMod p` into arbitrary rings.
This is unfortunate, but a consequence of the fact that we allow `ZMod p`
to coerce to rings of arbitrary characteristic, instead of only rings of characteristic `p`.
This coercion is only a ring homomorphism if it coerces into a ring whose characteristic divides
`p`. While this is not the case here we can still make use of the coercion.
-/
theorem toZMod_spec : x - (ZMod.cast (toZMod x) : ℤ_[p]) ∈ maximalIdeal ℤ_[p] := by
convert sub_zmodRepr_mem x using 2
dsimp [toZMod, toZModHom]
rcases Nat.exists_eq_add_of_lt hp_prime.1.pos with ⟨p', rfl⟩
change ↑((_ : ZMod (0 + p' + 1)).val) = (_ : ℤ_[0 + p' + 1])
simp only [ZMod.val_natCast, add_zero, add_def, Nat.cast_inj, zero_add]
apply mod_eq_of_lt
simpa only [zero_add] using zmodRepr_lt_p x
#align padic_int.to_zmod_spec PadicInt.toZMod_spec
theorem ker_toZMod : RingHom.ker (toZMod : ℤ_[p] →+* ZMod p) = maximalIdeal ℤ_[p] := by
ext x
rw [RingHom.mem_ker]
constructor
· intro h
simpa only [h, ZMod.cast_zero, sub_zero] using toZMod_spec x
· intro h
rw [← sub_zero x] at h
dsimp [toZMod, toZModHom]
convert zmod_congr_of_sub_mem_max_ideal x _ 0 _ h
· norm_cast
· apply sub_zmodRepr_mem
#align padic_int.ker_to_zmod PadicInt.ker_toZMod
/-- `appr n x` gives a value `v : ℕ` such that `x` and `↑v : ℤ_p` are congruent mod `p^n`.
See `appr_spec`. -/
-- Porting note: removing irreducible solves a lot of problems
noncomputable def appr : ℤ_[p] → ℕ → ℕ
| _x, 0 => 0
| x, n + 1 =>
let y := x - appr x n
if hy : y = 0 then appr x n
else
let u := (unitCoeff hy : ℤ_[p])
appr x n + p ^ n * (toZMod ((u * (p : ℤ_[p]) ^ (y.valuation - n).natAbs) : ℤ_[p])).val
#align padic_int.appr PadicInt.appr
theorem appr_lt (x : ℤ_[p]) (n : ℕ) : x.appr n < p ^ n := by
induction' n with n ih generalizing x
· simp only [appr, zero_eq, _root_.pow_zero, zero_lt_one]
simp only [appr, map_natCast, ZMod.natCast_self, RingHom.map_pow, Int.natAbs, RingHom.map_mul]
have hp : p ^ n < p ^ (n + 1) := by apply pow_lt_pow_right hp_prime.1.one_lt (lt_add_one n)
split_ifs with h
· apply lt_trans (ih _) hp
· calc
_ < p ^ n + p ^ n * (p - 1) := ?_
_ = p ^ (n + 1) := ?_
· apply add_lt_add_of_lt_of_le (ih _)
apply Nat.mul_le_mul_left
apply le_pred_of_lt
apply ZMod.val_lt
· rw [mul_tsub, mul_one, ← _root_.pow_succ]
apply add_tsub_cancel_of_le (le_of_lt hp)
#align padic_int.appr_lt PadicInt.appr_lt
theorem appr_mono (x : ℤ_[p]) : Monotone x.appr := by
apply monotone_nat_of_le_succ
intro n
dsimp [appr]
split_ifs; · rfl
apply Nat.le_add_right
#align padic_int.appr_mono PadicInt.appr_mono
theorem dvd_appr_sub_appr (x : ℤ_[p]) (m n : ℕ) (h : m ≤ n) : p ^ m ∣ x.appr n - x.appr m := by
obtain ⟨k, rfl⟩ := Nat.exists_eq_add_of_le h; clear h
induction' k with k ih
· simp only [zero_eq, add_zero, le_refl, tsub_eq_zero_of_le, ne_eq, Nat.isUnit_iff, dvd_zero]
rw [← add_assoc]
dsimp [appr]
split_ifs with h
· exact ih
rw [add_comm, add_tsub_assoc_of_le (appr_mono _ (Nat.le_add_right m k))]
apply dvd_add _ ih
apply dvd_mul_of_dvd_left
apply pow_dvd_pow _ (Nat.le_add_right m k)
#align padic_int.dvd_appr_sub_appr PadicInt.dvd_appr_sub_appr
theorem appr_spec (n : ℕ) : ∀ x : ℤ_[p], x - appr x n ∈ Ideal.span {(p : ℤ_[p]) ^ n} := by
simp only [Ideal.mem_span_singleton]
induction' n with n ih
· simp only [zero_eq, _root_.pow_zero, isUnit_one, IsUnit.dvd, forall_const]
intro x
dsimp only [appr]
split_ifs with h
· rw [h]
apply dvd_zero
push_cast
rw [sub_add_eq_sub_sub]
obtain ⟨c, hc⟩ := ih x
simp only [map_natCast, ZMod.natCast_self, RingHom.map_pow, RingHom.map_mul, ZMod.natCast_val]
have hc' : c ≠ 0 := by
rintro rfl
simp only [mul_zero] at hc
contradiction
conv_rhs =>
congr
simp only [hc]
rw [show (x - (appr x n : ℤ_[p])).valuation = ((p : ℤ_[p]) ^ n * c).valuation by rw [hc]]
rw [valuation_p_pow_mul _ _ hc', add_sub_cancel_left, _root_.pow_succ, ← mul_sub]
apply mul_dvd_mul_left
obtain hc0 | hc0 := eq_or_ne c.valuation.natAbs 0
· simp only [hc0, mul_one, _root_.pow_zero]
rw [mul_comm, unitCoeff_spec h] at hc
suffices c = unitCoeff h by
rw [← this, ← Ideal.mem_span_singleton, ← maximalIdeal_eq_span_p]
apply toZMod_spec
obtain ⟨c, rfl⟩ : IsUnit c := by
-- TODO: write a `CanLift` instance for units
rw [Int.natAbs_eq_zero] at hc0
rw [isUnit_iff, norm_eq_pow_val hc', hc0, neg_zero, zpow_zero]
rw [DiscreteValuationRing.unit_mul_pow_congr_unit _ _ _ _ _ hc]
exact irreducible_p
· simp only [zero_pow hc0, sub_zero, ZMod.cast_zero, mul_zero]
rw [unitCoeff_spec hc']
exact (dvd_pow_self (p : ℤ_[p]) hc0).mul_left _
#align padic_int.appr_spec PadicInt.appr_spec
/-- A ring hom from `ℤ_[p]` to `ZMod (p^n)`, with underlying function `PadicInt.appr n`. -/
def toZModPow (n : ℕ) : ℤ_[p] →+* ZMod (p ^ n) :=
toZModHom (p ^ n) (fun x => appr x n)
(by
intros
rw [Nat.cast_pow]
exact appr_spec n _)
(by
intro x a b ha hb
apply zmod_congr_of_sub_mem_span n x a b
· simpa using ha
· simpa using hb)
#align padic_int.to_zmod_pow PadicInt.toZModPow
theorem ker_toZModPow (n : ℕ) :
RingHom.ker (toZModPow n : ℤ_[p] →+* ZMod (p ^ n)) = Ideal.span {(p : ℤ_[p]) ^ n} := by
ext x
rw [RingHom.mem_ker]
constructor
· intro h
suffices x.appr n = 0 by
convert appr_spec n x
simp only [this, sub_zero, cast_zero]
dsimp [toZModPow, toZModHom] at h
rw [ZMod.natCast_zmod_eq_zero_iff_dvd] at h
apply eq_zero_of_dvd_of_lt h (appr_lt _ _)
· intro h
rw [← sub_zero x] at h
dsimp [toZModPow, toZModHom]
rw [zmod_congr_of_sub_mem_span n x _ 0 _ h, cast_zero]
apply appr_spec
#align padic_int.ker_to_zmod_pow PadicInt.ker_toZModPow
-- @[simp] -- Porting note: not in simpNF
theorem zmod_cast_comp_toZModPow (m n : ℕ) (h : m ≤ n) :
(ZMod.castHom (pow_dvd_pow p h) (ZMod (p ^ m))).comp (@toZModPow p _ n) = @toZModPow p _ m := by
apply ZMod.ringHom_eq_of_ker_eq
ext x
rw [RingHom.mem_ker, RingHom.mem_ker]
simp only [Function.comp_apply, ZMod.castHom_apply, RingHom.coe_comp]
simp only [toZModPow, toZModHom, RingHom.coe_mk]
dsimp
rw [ZMod.cast_natCast (pow_dvd_pow p h),
zmod_congr_of_sub_mem_span m (x.appr n) (x.appr n) (x.appr m)]
· rw [sub_self]
apply Ideal.zero_mem _
· rw [Ideal.mem_span_singleton]
rcases dvd_appr_sub_appr x m n h with ⟨c, hc⟩
use c
rw [← Nat.cast_sub (appr_mono _ h), hc, Nat.cast_mul, Nat.cast_pow]
#align padic_int.zmod_cast_comp_to_zmod_pow PadicInt.zmod_cast_comp_toZModPow
@[simp]
theorem cast_toZModPow (m n : ℕ) (h : m ≤ n) (x : ℤ_[p]) :
ZMod.cast (toZModPow n x) = toZModPow m x := by
rw [← zmod_cast_comp_toZModPow _ _ h]
rfl
#align padic_int.cast_to_zmod_pow PadicInt.cast_toZModPow
theorem denseRange_natCast : DenseRange (Nat.cast : ℕ → ℤ_[p]) := by
intro x
rw [Metric.mem_closure_range_iff]
intro ε hε
obtain ⟨n, hn⟩ := exists_pow_neg_lt p hε
use x.appr n
rw [dist_eq_norm]
apply lt_of_le_of_lt _ hn
rw [norm_le_pow_iff_mem_span_pow]
apply appr_spec
#align padic_int.dense_range_nat_cast PadicInt.denseRange_natCast
@[deprecated (since := "2024-04-17")]
alias denseRange_nat_cast := denseRange_natCast
| Mathlib/NumberTheory/Padics/RingHoms.lean | 465 | 471 | theorem denseRange_intCast : DenseRange (Int.cast : ℤ → ℤ_[p]) := by |
intro x
refine DenseRange.induction_on denseRange_natCast x ?_ ?_
· exact isClosed_closure
· intro a
apply subset_closure
exact Set.mem_range_self _
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Topology.Order.IsLUB
/-!
# Order topology on a densely ordered set
-/
open Set Filter TopologicalSpace Topology Function
open OrderDual (toDual ofDual)
variable {α β γ : Type*}
section DenselyOrdered
variable [TopologicalSpace α] [LinearOrder α] [OrderTopology α] [DenselyOrdered α] {a b : α}
{s : Set α}
/-- The closure of the interval `(a, +∞)` is the closed interval `[a, +∞)`, unless `a` is a top
element. -/
theorem closure_Ioi' {a : α} (h : (Ioi a).Nonempty) : closure (Ioi a) = Ici a := by
apply Subset.antisymm
· exact closure_minimal Ioi_subset_Ici_self isClosed_Ici
· rw [← diff_subset_closure_iff, Ici_diff_Ioi_same, singleton_subset_iff]
exact isGLB_Ioi.mem_closure h
#align closure_Ioi' closure_Ioi'
/-- The closure of the interval `(a, +∞)` is the closed interval `[a, +∞)`. -/
@[simp]
theorem closure_Ioi (a : α) [NoMaxOrder α] : closure (Ioi a) = Ici a :=
closure_Ioi' nonempty_Ioi
#align closure_Ioi closure_Ioi
/-- The closure of the interval `(-∞, a)` is the closed interval `(-∞, a]`, unless `a` is a bottom
element. -/
theorem closure_Iio' (h : (Iio a).Nonempty) : closure (Iio a) = Iic a :=
closure_Ioi' (α := αᵒᵈ) h
#align closure_Iio' closure_Iio'
/-- The closure of the interval `(-∞, a)` is the interval `(-∞, a]`. -/
@[simp]
theorem closure_Iio (a : α) [NoMinOrder α] : closure (Iio a) = Iic a :=
closure_Iio' nonempty_Iio
#align closure_Iio closure_Iio
/-- The closure of the open interval `(a, b)` is the closed interval `[a, b]`. -/
@[simp]
theorem closure_Ioo {a b : α} (hab : a ≠ b) : closure (Ioo a b) = Icc a b := by
apply Subset.antisymm
· exact closure_minimal Ioo_subset_Icc_self isClosed_Icc
· cases' hab.lt_or_lt with hab hab
· rw [← diff_subset_closure_iff, Icc_diff_Ioo_same hab.le]
have hab' : (Ioo a b).Nonempty := nonempty_Ioo.2 hab
simp only [insert_subset_iff, singleton_subset_iff]
exact ⟨(isGLB_Ioo hab).mem_closure hab', (isLUB_Ioo hab).mem_closure hab'⟩
· rw [Icc_eq_empty_of_lt hab]
exact empty_subset _
#align closure_Ioo closure_Ioo
/-- The closure of the interval `(a, b]` is the closed interval `[a, b]`. -/
@[simp]
theorem closure_Ioc {a b : α} (hab : a ≠ b) : closure (Ioc a b) = Icc a b := by
apply Subset.antisymm
· exact closure_minimal Ioc_subset_Icc_self isClosed_Icc
· apply Subset.trans _ (closure_mono Ioo_subset_Ioc_self)
rw [closure_Ioo hab]
#align closure_Ioc closure_Ioc
/-- The closure of the interval `[a, b)` is the closed interval `[a, b]`. -/
@[simp]
theorem closure_Ico {a b : α} (hab : a ≠ b) : closure (Ico a b) = Icc a b := by
apply Subset.antisymm
· exact closure_minimal Ico_subset_Icc_self isClosed_Icc
· apply Subset.trans _ (closure_mono Ioo_subset_Ico_self)
rw [closure_Ioo hab]
#align closure_Ico closure_Ico
@[simp]
theorem interior_Ici' {a : α} (ha : (Iio a).Nonempty) : interior (Ici a) = Ioi a := by
rw [← compl_Iio, interior_compl, closure_Iio' ha, compl_Iic]
#align interior_Ici' interior_Ici'
theorem interior_Ici [NoMinOrder α] {a : α} : interior (Ici a) = Ioi a :=
interior_Ici' nonempty_Iio
#align interior_Ici interior_Ici
@[simp]
theorem interior_Iic' {a : α} (ha : (Ioi a).Nonempty) : interior (Iic a) = Iio a :=
interior_Ici' (α := αᵒᵈ) ha
#align interior_Iic' interior_Iic'
theorem interior_Iic [NoMaxOrder α] {a : α} : interior (Iic a) = Iio a :=
interior_Iic' nonempty_Ioi
#align interior_Iic interior_Iic
@[simp]
theorem interior_Icc [NoMinOrder α] [NoMaxOrder α] {a b : α} : interior (Icc a b) = Ioo a b := by
rw [← Ici_inter_Iic, interior_inter, interior_Ici, interior_Iic, Ioi_inter_Iio]
#align interior_Icc interior_Icc
@[simp]
theorem Icc_mem_nhds_iff [NoMinOrder α] [NoMaxOrder α] {a b x : α} :
Icc a b ∈ 𝓝 x ↔ x ∈ Ioo a b := by
rw [← interior_Icc, mem_interior_iff_mem_nhds]
@[simp]
theorem interior_Ico [NoMinOrder α] {a b : α} : interior (Ico a b) = Ioo a b := by
rw [← Ici_inter_Iio, interior_inter, interior_Ici, interior_Iio, Ioi_inter_Iio]
#align interior_Ico interior_Ico
@[simp]
| Mathlib/Topology/Order/DenselyOrdered.lean | 116 | 117 | theorem Ico_mem_nhds_iff [NoMinOrder α] {a b x : α} : Ico a b ∈ 𝓝 x ↔ x ∈ Ioo a b := by |
rw [← interior_Ico, mem_interior_iff_mem_nhds]
|
/-
Copyright (c) 2019 Gabriel Ebner. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Gabriel Ebner, Anatole Dedecker, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.FDeriv.Mul
import Mathlib.Analysis.Calculus.FDeriv.Add
#align_import analysis.calculus.deriv.mul from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Derivative of `f x * g x`
In this file we prove formulas for `(f x * g x)'` and `(f x • g x)'`.
For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of
`Analysis/Calculus/Deriv/Basic`.
## Keywords
derivative, multiplication
-/
universe u v w
noncomputable section
open scoped Classical Topology Filter ENNReal
open Filter Asymptotics Set
open ContinuousLinearMap (smulRight smulRight_one_eq_iff)
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜]
variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {E : Type w} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
variable {f f₀ f₁ g : 𝕜 → F}
variable {f' f₀' f₁' g' : F}
variable {x : 𝕜}
variable {s t : Set 𝕜}
variable {L L₁ L₂ : Filter 𝕜}
/-! ### Derivative of bilinear maps -/
namespace ContinuousLinearMap
variable {B : E →L[𝕜] F →L[𝕜] G} {u : 𝕜 → E} {v : 𝕜 → F} {u' : E} {v' : F}
theorem hasDerivWithinAt_of_bilinear
(hu : HasDerivWithinAt u u' s x) (hv : HasDerivWithinAt v v' s x) :
HasDerivWithinAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) s x := by
simpa using (B.hasFDerivWithinAt_of_bilinear
hu.hasFDerivWithinAt hv.hasFDerivWithinAt).hasDerivWithinAt
theorem hasDerivAt_of_bilinear (hu : HasDerivAt u u' x) (hv : HasDerivAt v v' x) :
HasDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by
simpa using (B.hasFDerivAt_of_bilinear hu.hasFDerivAt hv.hasFDerivAt).hasDerivAt
theorem hasStrictDerivAt_of_bilinear (hu : HasStrictDerivAt u u' x) (hv : HasStrictDerivAt v v' x) :
HasStrictDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by
simpa using
(B.hasStrictFDerivAt_of_bilinear hu.hasStrictFDerivAt hv.hasStrictFDerivAt).hasStrictDerivAt
theorem derivWithin_of_bilinear (hxs : UniqueDiffWithinAt 𝕜 s x)
(hu : DifferentiableWithinAt 𝕜 u s x) (hv : DifferentiableWithinAt 𝕜 v s x) :
derivWithin (fun y => B (u y) (v y)) s x =
B (u x) (derivWithin v s x) + B (derivWithin u s x) (v x) :=
(B.hasDerivWithinAt_of_bilinear hu.hasDerivWithinAt hv.hasDerivWithinAt).derivWithin hxs
theorem deriv_of_bilinear (hu : DifferentiableAt 𝕜 u x) (hv : DifferentiableAt 𝕜 v x) :
deriv (fun y => B (u y) (v y)) x = B (u x) (deriv v x) + B (deriv u x) (v x) :=
(B.hasDerivAt_of_bilinear hu.hasDerivAt hv.hasDerivAt).deriv
end ContinuousLinearMap
section SMul
/-! ### Derivative of the multiplication of a scalar function and a vector function -/
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F]
[IsScalarTower 𝕜 𝕜' F] {c : 𝕜 → 𝕜'} {c' : 𝕜'}
theorem HasDerivWithinAt.smul (hc : HasDerivWithinAt c c' s x) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c y • f y) (c x • f' + c' • f x) s x := by
simpa using (HasFDerivWithinAt.smul hc hf).hasDerivWithinAt
#align has_deriv_within_at.smul HasDerivWithinAt.smul
theorem HasDerivAt.smul (hc : HasDerivAt c c' x) (hf : HasDerivAt f f' x) :
HasDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.smul hf
#align has_deriv_at.smul HasDerivAt.smul
nonrec theorem HasStrictDerivAt.smul (hc : HasStrictDerivAt c c' x) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by
simpa using (hc.smul hf).hasStrictDerivAt
#align has_strict_deriv_at.smul HasStrictDerivAt.smul
theorem derivWithin_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) :
derivWithin (fun y => c y • f y) s x = c x • derivWithin f s x + derivWithin c s x • f x :=
(hc.hasDerivWithinAt.smul hf.hasDerivWithinAt).derivWithin hxs
#align deriv_within_smul derivWithin_smul
theorem deriv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
deriv (fun y => c y • f y) x = c x • deriv f x + deriv c x • f x :=
(hc.hasDerivAt.smul hf.hasDerivAt).deriv
#align deriv_smul deriv_smul
theorem HasStrictDerivAt.smul_const (hc : HasStrictDerivAt c c' x) (f : F) :
HasStrictDerivAt (fun y => c y • f) (c' • f) x := by
have := hc.smul (hasStrictDerivAt_const x f)
rwa [smul_zero, zero_add] at this
#align has_strict_deriv_at.smul_const HasStrictDerivAt.smul_const
theorem HasDerivWithinAt.smul_const (hc : HasDerivWithinAt c c' s x) (f : F) :
HasDerivWithinAt (fun y => c y • f) (c' • f) s x := by
have := hc.smul (hasDerivWithinAt_const x s f)
rwa [smul_zero, zero_add] at this
#align has_deriv_within_at.smul_const HasDerivWithinAt.smul_const
theorem HasDerivAt.smul_const (hc : HasDerivAt c c' x) (f : F) :
HasDerivAt (fun y => c y • f) (c' • f) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.smul_const f
#align has_deriv_at.smul_const HasDerivAt.smul_const
theorem derivWithin_smul_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
derivWithin (fun y => c y • f) s x = derivWithin c s x • f :=
(hc.hasDerivWithinAt.smul_const f).derivWithin hxs
#align deriv_within_smul_const derivWithin_smul_const
theorem deriv_smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
deriv (fun y => c y • f) x = deriv c x • f :=
(hc.hasDerivAt.smul_const f).deriv
#align deriv_smul_const deriv_smul_const
end SMul
section ConstSMul
variable {R : Type*} [Semiring R] [Module R F] [SMulCommClass 𝕜 R F] [ContinuousConstSMul R F]
nonrec theorem HasStrictDerivAt.const_smul (c : R) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y => c • f y) (c • f') x := by
simpa using (hf.const_smul c).hasStrictDerivAt
#align has_strict_deriv_at.const_smul HasStrictDerivAt.const_smul
nonrec theorem HasDerivAtFilter.const_smul (c : R) (hf : HasDerivAtFilter f f' x L) :
HasDerivAtFilter (fun y => c • f y) (c • f') x L := by
simpa using (hf.const_smul c).hasDerivAtFilter
#align has_deriv_at_filter.const_smul HasDerivAtFilter.const_smul
nonrec theorem HasDerivWithinAt.const_smul (c : R) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c • f y) (c • f') s x :=
hf.const_smul c
#align has_deriv_within_at.const_smul HasDerivWithinAt.const_smul
nonrec theorem HasDerivAt.const_smul (c : R) (hf : HasDerivAt f f' x) :
HasDerivAt (fun y => c • f y) (c • f') x :=
hf.const_smul c
#align has_deriv_at.const_smul HasDerivAt.const_smul
theorem derivWithin_const_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (c : R)
(hf : DifferentiableWithinAt 𝕜 f s x) :
derivWithin (fun y => c • f y) s x = c • derivWithin f s x :=
(hf.hasDerivWithinAt.const_smul c).derivWithin hxs
#align deriv_within_const_smul derivWithin_const_smul
theorem deriv_const_smul (c : R) (hf : DifferentiableAt 𝕜 f x) :
deriv (fun y => c • f y) x = c • deriv f x :=
(hf.hasDerivAt.const_smul c).deriv
#align deriv_const_smul deriv_const_smul
/-- A variant of `deriv_const_smul` without differentiability assumption when the scalar
multiplication is by field elements. -/
lemma deriv_const_smul' {f : 𝕜 → F} {x : 𝕜} {R : Type*} [Field R] [Module R F] [SMulCommClass 𝕜 R F]
[ContinuousConstSMul R F] (c : R) :
deriv (fun y ↦ c • f y) x = c • deriv f x := by
by_cases hf : DifferentiableAt 𝕜 f x
· exact deriv_const_smul c hf
· rcases eq_or_ne c 0 with rfl | hc
· simp only [zero_smul, deriv_const']
· have H : ¬DifferentiableAt 𝕜 (fun y ↦ c • f y) x := by
contrapose! hf
change DifferentiableAt 𝕜 (fun y ↦ f y) x
conv => enter [2, y]; rw [← inv_smul_smul₀ hc (f y)]
exact DifferentiableAt.const_smul hf c⁻¹
rw [deriv_zero_of_not_differentiableAt hf, deriv_zero_of_not_differentiableAt H, smul_zero]
end ConstSMul
section Mul
/-! ### Derivative of the multiplication of two functions -/
variable {𝕜' 𝔸 : Type*} [NormedField 𝕜'] [NormedRing 𝔸] [NormedAlgebra 𝕜 𝕜'] [NormedAlgebra 𝕜 𝔸]
{c d : 𝕜 → 𝔸} {c' d' : 𝔸} {u v : 𝕜 → 𝕜'}
theorem HasDerivWithinAt.mul (hc : HasDerivWithinAt c c' s x) (hd : HasDerivWithinAt d d' s x) :
HasDerivWithinAt (fun y => c y * d y) (c' * d x + c x * d') s x := by
have := (HasFDerivWithinAt.mul' hc hd).hasDerivWithinAt
rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul,
add_comm] at this
#align has_deriv_within_at.mul HasDerivWithinAt.mul
theorem HasDerivAt.mul (hc : HasDerivAt c c' x) (hd : HasDerivAt d d' x) :
HasDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.mul hd
#align has_deriv_at.mul HasDerivAt.mul
theorem HasStrictDerivAt.mul (hc : HasStrictDerivAt c c' x) (hd : HasStrictDerivAt d d' x) :
HasStrictDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by
have := (HasStrictFDerivAt.mul' hc hd).hasStrictDerivAt
rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul,
add_comm] at this
#align has_strict_deriv_at.mul HasStrictDerivAt.mul
theorem derivWithin_mul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
derivWithin (fun y => c y * d y) s x = derivWithin c s x * d x + c x * derivWithin d s x :=
(hc.hasDerivWithinAt.mul hd.hasDerivWithinAt).derivWithin hxs
#align deriv_within_mul derivWithin_mul
@[simp]
theorem deriv_mul (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
deriv (fun y => c y * d y) x = deriv c x * d x + c x * deriv d x :=
(hc.hasDerivAt.mul hd.hasDerivAt).deriv
#align deriv_mul deriv_mul
theorem HasDerivWithinAt.mul_const (hc : HasDerivWithinAt c c' s x) (d : 𝔸) :
HasDerivWithinAt (fun y => c y * d) (c' * d) s x := by
convert hc.mul (hasDerivWithinAt_const x s d) using 1
rw [mul_zero, add_zero]
#align has_deriv_within_at.mul_const HasDerivWithinAt.mul_const
theorem HasDerivAt.mul_const (hc : HasDerivAt c c' x) (d : 𝔸) :
HasDerivAt (fun y => c y * d) (c' * d) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.mul_const d
#align has_deriv_at.mul_const HasDerivAt.mul_const
theorem hasDerivAt_mul_const (c : 𝕜) : HasDerivAt (fun x => x * c) c x := by
simpa only [one_mul] using (hasDerivAt_id' x).mul_const c
#align has_deriv_at_mul_const hasDerivAt_mul_const
theorem HasStrictDerivAt.mul_const (hc : HasStrictDerivAt c c' x) (d : 𝔸) :
HasStrictDerivAt (fun y => c y * d) (c' * d) x := by
convert hc.mul (hasStrictDerivAt_const x d) using 1
rw [mul_zero, add_zero]
#align has_strict_deriv_at.mul_const HasStrictDerivAt.mul_const
theorem derivWithin_mul_const (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(d : 𝔸) : derivWithin (fun y => c y * d) s x = derivWithin c s x * d :=
(hc.hasDerivWithinAt.mul_const d).derivWithin hxs
#align deriv_within_mul_const derivWithin_mul_const
theorem deriv_mul_const (hc : DifferentiableAt 𝕜 c x) (d : 𝔸) :
deriv (fun y => c y * d) x = deriv c x * d :=
(hc.hasDerivAt.mul_const d).deriv
#align deriv_mul_const deriv_mul_const
theorem deriv_mul_const_field (v : 𝕜') : deriv (fun y => u y * v) x = deriv u x * v := by
by_cases hu : DifferentiableAt 𝕜 u x
· exact deriv_mul_const hu v
· rw [deriv_zero_of_not_differentiableAt hu, zero_mul]
rcases eq_or_ne v 0 with (rfl | hd)
· simp only [mul_zero, deriv_const]
· refine deriv_zero_of_not_differentiableAt (mt (fun H => ?_) hu)
simpa only [mul_inv_cancel_right₀ hd] using H.mul_const v⁻¹
#align deriv_mul_const_field deriv_mul_const_field
@[simp]
theorem deriv_mul_const_field' (v : 𝕜') : (deriv fun x => u x * v) = fun x => deriv u x * v :=
funext fun _ => deriv_mul_const_field v
#align deriv_mul_const_field' deriv_mul_const_field'
theorem HasDerivWithinAt.const_mul (c : 𝔸) (hd : HasDerivWithinAt d d' s x) :
HasDerivWithinAt (fun y => c * d y) (c * d') s x := by
convert (hasDerivWithinAt_const x s c).mul hd using 1
rw [zero_mul, zero_add]
#align has_deriv_within_at.const_mul HasDerivWithinAt.const_mul
theorem HasDerivAt.const_mul (c : 𝔸) (hd : HasDerivAt d d' x) :
HasDerivAt (fun y => c * d y) (c * d') x := by
rw [← hasDerivWithinAt_univ] at *
exact hd.const_mul c
#align has_deriv_at.const_mul HasDerivAt.const_mul
theorem HasStrictDerivAt.const_mul (c : 𝔸) (hd : HasStrictDerivAt d d' x) :
HasStrictDerivAt (fun y => c * d y) (c * d') x := by
convert (hasStrictDerivAt_const _ _).mul hd using 1
rw [zero_mul, zero_add]
#align has_strict_deriv_at.const_mul HasStrictDerivAt.const_mul
theorem derivWithin_const_mul (hxs : UniqueDiffWithinAt 𝕜 s x) (c : 𝔸)
(hd : DifferentiableWithinAt 𝕜 d s x) :
derivWithin (fun y => c * d y) s x = c * derivWithin d s x :=
(hd.hasDerivWithinAt.const_mul c).derivWithin hxs
#align deriv_within_const_mul derivWithin_const_mul
theorem deriv_const_mul (c : 𝔸) (hd : DifferentiableAt 𝕜 d x) :
deriv (fun y => c * d y) x = c * deriv d x :=
(hd.hasDerivAt.const_mul c).deriv
#align deriv_const_mul deriv_const_mul
theorem deriv_const_mul_field (u : 𝕜') : deriv (fun y => u * v y) x = u * deriv v x := by
simp only [mul_comm u, deriv_mul_const_field]
#align deriv_const_mul_field deriv_const_mul_field
@[simp]
theorem deriv_const_mul_field' (u : 𝕜') : (deriv fun x => u * v x) = fun x => u * deriv v x :=
funext fun _ => deriv_const_mul_field u
#align deriv_const_mul_field' deriv_const_mul_field'
end Mul
section Prod
section HasDeriv
variable {ι : Type*} [DecidableEq ι] {𝔸' : Type*} [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸']
{u : Finset ι} {f : ι → 𝕜 → 𝔸'} {f' : ι → 𝔸'}
theorem HasDerivAt.finset_prod (hf : ∀ i ∈ u, HasDerivAt (f i) (f' i) x) :
HasDerivAt (∏ i ∈ u, f i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • f' i) x := by
simpa [ContinuousLinearMap.sum_apply, ContinuousLinearMap.smul_apply] using
(HasFDerivAt.finset_prod (fun i hi ↦ (hf i hi).hasFDerivAt)).hasDerivAt
| Mathlib/Analysis/Calculus/Deriv/Mul.lean | 341 | 344 | theorem HasDerivWithinAt.finset_prod (hf : ∀ i ∈ u, HasDerivWithinAt (f i) (f' i) s x) :
HasDerivWithinAt (∏ i ∈ u, f i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • f' i) s x := by |
simpa [ContinuousLinearMap.sum_apply, ContinuousLinearMap.smul_apply] using
(HasFDerivWithinAt.finset_prod (fun i hi ↦ (hf i hi).hasFDerivWithinAt)).hasDerivWithinAt
|
/-
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, Sander Dahmen, Scott Morrison, Chris Hughes, Anne Baanen
-/
import Mathlib.LinearAlgebra.Dimension.Free
import Mathlib.Algebra.Module.Torsion
#align_import linear_algebra.dimension from "leanprover-community/mathlib"@"47a5f8186becdbc826190ced4312f8199f9db6a5"
/-!
# Rank of various constructions
## Main statements
- `rank_quotient_add_rank_le` : `rank M/N + rank N ≤ rank M`.
- `lift_rank_add_lift_rank_le_rank_prod`: `rank M × N ≤ rank M + rank N`.
- `rank_span_le_of_finite`: `rank (span s) ≤ #s` for finite `s`.
For free modules, we have
- `rank_prod` : `rank M × N = rank M + rank N`.
- `rank_finsupp` : `rank (ι →₀ M) = #ι * rank M`
- `rank_directSum`: `rank (⨁ Mᵢ) = ∑ rank Mᵢ`
- `rank_tensorProduct`: `rank (M ⊗ N) = rank M * rank N`.
Lemmas for ranks of submodules and subalgebras are also provided.
We have finrank variants for most lemmas as well.
-/
noncomputable section
universe u v v' u₁' w w'
variable {R S : Type u} {M : Type v} {M' : Type v'} {M₁ : Type v}
variable {ι : Type w} {ι' : Type w'} {η : Type u₁'} {φ : η → Type*}
open Cardinal Basis Submodule Function Set FiniteDimensional DirectSum
variable [Ring R] [CommRing S] [AddCommGroup M] [AddCommGroup M'] [AddCommGroup M₁]
variable [Module R M] [Module R M'] [Module R M₁]
section Quotient
theorem LinearIndependent.sum_elim_of_quotient
{M' : Submodule R M} {ι₁ ι₂} {f : ι₁ → M'} (hf : LinearIndependent R f) (g : ι₂ → M)
(hg : LinearIndependent R (Submodule.Quotient.mk (p := M') ∘ g)) :
LinearIndependent R (Sum.elim (f · : ι₁ → M) g) := by
refine .sum_type (hf.map' M'.subtype M'.ker_subtype) (.of_comp M'.mkQ hg) ?_
refine disjoint_def.mpr fun x h₁ h₂ ↦ ?_
have : x ∈ M' := span_le.mpr (Set.range_subset_iff.mpr fun i ↦ (f i).prop) h₁
obtain ⟨c, rfl⟩ := Finsupp.mem_span_range_iff_exists_finsupp.mp h₂
simp_rw [← Quotient.mk_eq_zero, ← mkQ_apply, map_finsupp_sum, map_smul, mkQ_apply] at this
rw [linearIndependent_iff.mp hg _ this, Finsupp.sum_zero_index]
theorem LinearIndependent.union_of_quotient
{M' : Submodule R M} {s : Set M} (hs : s ⊆ M') (hs' : LinearIndependent (ι := s) R Subtype.val)
{t : Set M} (ht : LinearIndependent (ι := t) R (Submodule.Quotient.mk (p := M') ∘ Subtype.val)) :
LinearIndependent (ι := (s ∪ t : _)) R Subtype.val := by
refine (LinearIndependent.sum_elim_of_quotient (f := Set.embeddingOfSubset s M' hs)
(of_comp M'.subtype (by simpa using hs')) Subtype.val ht).to_subtype_range' ?_
simp only [embeddingOfSubset_apply_coe, Sum.elim_range, Subtype.range_val]
theorem rank_quotient_add_rank_le [Nontrivial R] (M' : Submodule R M) :
Module.rank R (M ⧸ M') + Module.rank R M' ≤ Module.rank R M := by
conv_lhs => simp only [Module.rank_def]
have := nonempty_linearIndependent_set R (M ⧸ M')
have := nonempty_linearIndependent_set R M'
rw [Cardinal.ciSup_add_ciSup _ (bddAbove_range.{v, v} _) _ (bddAbove_range.{v, v} _)]
refine ciSup_le fun ⟨s, hs⟩ ↦ ciSup_le fun ⟨t, ht⟩ ↦ ?_
choose f hf using Quotient.mk_surjective M'
simpa [add_comm] using (LinearIndependent.sum_elim_of_quotient ht (fun (i : s) ↦ f i)
(by simpa [Function.comp, hf] using hs)).cardinal_le_rank
theorem rank_quotient_le (p : Submodule R M) : Module.rank R (M ⧸ p) ≤ Module.rank R M :=
(mkQ p).rank_le_of_surjective (surjective_quot_mk _)
#align rank_quotient_le rank_quotient_le
theorem rank_quotient_eq_of_le_torsion {R M} [CommRing R] [AddCommGroup M] [Module R M]
{M' : Submodule R M} (hN : M' ≤ torsion R M) : Module.rank R (M ⧸ M') = Module.rank R M :=
(rank_quotient_le M').antisymm <| by
nontriviality R
rw [Module.rank]
have := nonempty_linearIndependent_set R M
refine ciSup_le fun ⟨s, hs⟩ ↦ LinearIndependent.cardinal_le_rank (v := (M'.mkQ ·)) ?_
rw [linearIndependent_iff'] at hs ⊢
simp_rw [← map_smul, ← map_sum, mkQ_apply, Quotient.mk_eq_zero]
intro t g hg i hi
obtain ⟨r, hg⟩ := hN hg
simp_rw [Finset.smul_sum, Submonoid.smul_def, smul_smul] at hg
exact r.prop _ (mul_comm (g i) r ▸ hs t _ hg i hi)
end Quotient
section ULift
@[simp]
theorem rank_ulift : Module.rank R (ULift.{w} M) = Cardinal.lift.{w} (Module.rank R M) :=
Cardinal.lift_injective.{v} <| Eq.symm <| (lift_lift _).trans ULift.moduleEquiv.symm.lift_rank_eq
@[simp]
theorem finrank_ulift : finrank R (ULift M) = finrank R M := by
simp_rw [finrank, rank_ulift, toNat_lift]
end ULift
section Prod
variable (R M M')
open LinearMap in
theorem lift_rank_add_lift_rank_le_rank_prod [Nontrivial R] :
lift.{v'} (Module.rank R M) + lift.{v} (Module.rank R M') ≤ Module.rank R (M × M') := by
convert rank_quotient_add_rank_le (ker <| LinearMap.fst R M M')
· refine Eq.trans ?_ (lift_id'.{v, v'} _)
rw [(quotKerEquivRange _).lift_rank_eq,
rank_range_of_surjective _ fst_surjective, lift_umax.{v, v'}]
· refine Eq.trans ?_ (lift_id'.{v', v} _)
rw [ker_fst, ← (LinearEquiv.ofInjective _ <| inr_injective (M := M) (M₂ := M')).lift_rank_eq,
lift_umax.{v', v}]
theorem rank_add_rank_le_rank_prod [Nontrivial R] :
Module.rank R M + Module.rank R M₁ ≤ Module.rank R (M × M₁) := by
convert ← lift_rank_add_lift_rank_le_rank_prod R M M₁ <;> apply lift_id
variable {R M M'}
variable [StrongRankCondition R] [Module.Free R M] [Module.Free R M'] [Module.Free R M₁]
open Module.Free
/-- If `M` and `M'` are free, then the rank of `M × M'` is
`(Module.rank R M).lift + (Module.rank R M').lift`. -/
@[simp]
| Mathlib/LinearAlgebra/Dimension/Constructions.lean | 136 | 139 | theorem rank_prod : Module.rank R (M × M') =
Cardinal.lift.{v'} (Module.rank R M) + Cardinal.lift.{v, v'} (Module.rank R M') := by |
simpa [rank_eq_card_chooseBasisIndex R M, rank_eq_card_chooseBasisIndex R M', lift_umax,
lift_umax'] using ((chooseBasis R M).prod (chooseBasis R M')).mk_eq_rank.symm
|
/-
Copyright (c) 2021 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Data.SetLike.Fintype
import Mathlib.Algebra.Divisibility.Prod
import Mathlib.RingTheory.Nakayama
import Mathlib.RingTheory.SimpleModule
import Mathlib.Tactic.RSuffices
#align_import ring_theory.artinian from "leanprover-community/mathlib"@"210657c4ea4a4a7b234392f70a3a2a83346dfa90"
/-!
# Artinian rings and modules
A module satisfying these equivalent conditions is said to be an *Artinian* R-module
if every decreasing chain of submodules is eventually constant, or equivalently,
if the relation `<` on submodules is well founded.
A ring is said to be left (or right) Artinian if it is Artinian as a left (or right) module over
itself, or simply Artinian if it is both left and right Artinian.
## Main definitions
Let `R` be a ring and let `M` and `P` be `R`-modules. Let `N` be an `R`-submodule of `M`.
* `IsArtinian R M` is the proposition that `M` is an Artinian `R`-module. It is a class,
implemented as the predicate that the `<` relation on submodules is well founded.
* `IsArtinianRing R` is the proposition that `R` is a left Artinian ring.
## Main results
* `IsArtinianRing.localization_surjective`: the canonical homomorphism from a commutative artinian
ring to any localization of itself is surjective.
* `IsArtinianRing.isNilpotent_jacobson_bot`: the Jacobson radical of a commutative artinian ring
is a nilpotent ideal. (TODO: generalize to noncommutative rings.)
* `IsArtinianRing.primeSpectrum_finite`, `IsArtinianRing.isMaximal_of_isPrime`: there are only
finitely prime ideals in a commutative artinian ring, and each of them is maximal.
* `IsArtinianRing.equivPi`: a reduced commutative artinian ring `R` is isomorphic to a finite
product of fields (and therefore is a semisimple ring and a decomposition monoid; moreover
`R[X]` is also a decomposition monoid).
## References
* [M. F. Atiyah and I. G. Macdonald, *Introduction to commutative algebra*][atiyah-macdonald]
* [samuel]
## Tags
Artinian, artinian, Artinian ring, Artinian module, artinian ring, artinian module
-/
open Set Filter Pointwise
/-- `IsArtinian R M` is the proposition that `M` is an Artinian `R`-module,
implemented as the well-foundedness of submodule inclusion. -/
class IsArtinian (R M) [Semiring R] [AddCommMonoid M] [Module R M] : Prop where
wellFounded_submodule_lt' : WellFounded ((· < ·) : Submodule R M → Submodule R M → Prop)
#align is_artinian IsArtinian
section
variable {R M P N : Type*}
variable [Ring R] [AddCommGroup M] [AddCommGroup P] [AddCommGroup N]
variable [Module R M] [Module R P] [Module R N]
open IsArtinian
/- Porting note: added this version with `R` and `M` explicit because infer kinds are unsupported in
Lean 4-/
theorem IsArtinian.wellFounded_submodule_lt (R M) [Semiring R] [AddCommMonoid M] [Module R M]
[IsArtinian R M] : WellFounded ((· < ·) : Submodule R M → Submodule R M → Prop) :=
IsArtinian.wellFounded_submodule_lt'
#align is_artinian.well_founded_submodule_lt IsArtinian.wellFounded_submodule_lt
theorem isArtinian_of_injective (f : M →ₗ[R] P) (h : Function.Injective f) [IsArtinian R P] :
IsArtinian R M :=
⟨Subrelation.wf
(fun {A B} hAB => show A.map f < B.map f from Submodule.map_strictMono_of_injective h hAB)
(InvImage.wf (Submodule.map f) (IsArtinian.wellFounded_submodule_lt R P))⟩
#align is_artinian_of_injective isArtinian_of_injective
instance isArtinian_submodule' [IsArtinian R M] (N : Submodule R M) : IsArtinian R N :=
isArtinian_of_injective N.subtype Subtype.val_injective
#align is_artinian_submodule' isArtinian_submodule'
theorem isArtinian_of_le {s t : Submodule R M} [IsArtinian R t] (h : s ≤ t) : IsArtinian R s :=
isArtinian_of_injective (Submodule.inclusion h) (Submodule.inclusion_injective h)
#align is_artinian_of_le isArtinian_of_le
variable (M)
theorem isArtinian_of_surjective (f : M →ₗ[R] P) (hf : Function.Surjective f) [IsArtinian R M] :
IsArtinian R P :=
⟨Subrelation.wf
(fun {A B} hAB =>
show A.comap f < B.comap f from Submodule.comap_strictMono_of_surjective hf hAB)
(InvImage.wf (Submodule.comap f) (IsArtinian.wellFounded_submodule_lt R M))⟩
#align is_artinian_of_surjective isArtinian_of_surjective
variable {M}
theorem isArtinian_of_linearEquiv (f : M ≃ₗ[R] P) [IsArtinian R M] : IsArtinian R P :=
isArtinian_of_surjective _ f.toLinearMap f.toEquiv.surjective
#align is_artinian_of_linear_equiv isArtinian_of_linearEquiv
theorem isArtinian_of_range_eq_ker [IsArtinian R M] [IsArtinian R P] (f : M →ₗ[R] N) (g : N →ₗ[R] P)
(hf : Function.Injective f) (hg : Function.Surjective g)
(h : LinearMap.range f = LinearMap.ker g) : IsArtinian R N :=
⟨wellFounded_lt_exact_sequence (IsArtinian.wellFounded_submodule_lt R M)
(IsArtinian.wellFounded_submodule_lt R P) (LinearMap.range f) (Submodule.map f)
(Submodule.comap f) (Submodule.comap g) (Submodule.map g) (Submodule.gciMapComap hf)
(Submodule.giMapComap hg)
(by simp [Submodule.map_comap_eq, inf_comm]) (by simp [Submodule.comap_map_eq, h])⟩
#align is_artinian_of_range_eq_ker isArtinian_of_range_eq_ker
instance isArtinian_prod [IsArtinian R M] [IsArtinian R P] : IsArtinian R (M × P) :=
isArtinian_of_range_eq_ker (LinearMap.inl R M P) (LinearMap.snd R M P) LinearMap.inl_injective
LinearMap.snd_surjective (LinearMap.range_inl R M P)
#align is_artinian_prod isArtinian_prod
instance (priority := 100) isArtinian_of_finite [Finite M] : IsArtinian R M :=
⟨Finite.wellFounded_of_trans_of_irrefl _⟩
#align is_artinian_of_finite isArtinian_of_finite
-- Porting note: elab_as_elim can only be global and cannot be changed on an imported decl
-- attribute [local elab_as_elim] Finite.induction_empty_option
instance isArtinian_pi {R ι : Type*} [Finite ι] :
∀ {M : ι → Type*} [Ring R] [∀ i, AddCommGroup (M i)],
∀ [∀ i, Module R (M i)], ∀ [∀ i, IsArtinian R (M i)], IsArtinian R (∀ i, M i) := by
apply Finite.induction_empty_option _ _ _ ι
· intro α β e hα M _ _ _ _
have := @hα
exact isArtinian_of_linearEquiv (LinearEquiv.piCongrLeft R M e)
· intro M _ _ _ _
infer_instance
· intro α _ ih M _ _ _ _
have := @ih
exact isArtinian_of_linearEquiv (LinearEquiv.piOptionEquivProd R).symm
#align is_artinian_pi isArtinian_pi
/-- A version of `isArtinian_pi` for non-dependent functions. We need this instance because
sometimes Lean fails to apply the dependent version in non-dependent settings (e.g., it fails to
prove that `ι → ℝ` is finite dimensional over `ℝ`). -/
instance isArtinian_pi' {R ι M : Type*} [Ring R] [AddCommGroup M] [Module R M] [Finite ι]
[IsArtinian R M] : IsArtinian R (ι → M) :=
isArtinian_pi
#align is_artinian_pi' isArtinian_pi'
--porting note (#10754): new instance
instance isArtinian_finsupp {R ι M : Type*} [Ring R] [AddCommGroup M] [Module R M] [Finite ι]
[IsArtinian R M] : IsArtinian R (ι →₀ M) :=
isArtinian_of_linearEquiv (Finsupp.linearEquivFunOnFinite _ _ _).symm
end
open IsArtinian Submodule Function
section Ring
variable {R M : Type*} [Ring R] [AddCommGroup M] [Module R M]
theorem isArtinian_iff_wellFounded :
IsArtinian R M ↔ WellFounded ((· < ·) : Submodule R M → Submodule R M → Prop) :=
⟨fun h => h.1, IsArtinian.mk⟩
#align is_artinian_iff_well_founded isArtinian_iff_wellFounded
theorem IsArtinian.finite_of_linearIndependent [Nontrivial R] [IsArtinian R M] {s : Set M}
(hs : LinearIndependent R ((↑) : s → M)) : s.Finite := by
refine by_contradiction fun hf => (RelEmbedding.wellFounded_iff_no_descending_seq.1
(wellFounded_submodule_lt (R := R) (M := M))).elim' ?_
have f : ℕ ↪ s := Set.Infinite.natEmbedding s hf
have : ∀ n, (↑) ∘ f '' { m | n ≤ m } ⊆ s := by
rintro n x ⟨y, _, rfl⟩
exact (f y).2
have : ∀ a b : ℕ, a ≤ b ↔
span R (Subtype.val ∘ f '' { m | b ≤ m }) ≤ span R (Subtype.val ∘ f '' { m | a ≤ m }) := by
intro a b
rw [span_le_span_iff hs (this b) (this a),
Set.image_subset_image_iff (Subtype.coe_injective.comp f.injective), Set.subset_def]
simp only [Set.mem_setOf_eq]
exact ⟨fun hab x => le_trans hab, fun h => h _ le_rfl⟩
exact ⟨⟨fun n => span R (Subtype.val ∘ f '' { m | n ≤ m }), fun x y => by
rw [le_antisymm_iff, ← this y x, ← this x y]
exact fun ⟨h₁, h₂⟩ => le_antisymm_iff.2 ⟨h₂, h₁⟩⟩, by
intro a b
conv_rhs => rw [GT.gt, lt_iff_le_not_le, this, this, ← lt_iff_le_not_le]
rfl⟩
#align is_artinian.finite_of_linear_independent IsArtinian.finite_of_linearIndependent
/-- A module is Artinian iff every nonempty set of submodules has a minimal submodule among them. -/
| Mathlib/RingTheory/Artinian.lean | 199 | 201 | theorem set_has_minimal_iff_artinian :
(∀ a : Set <| Submodule R M, a.Nonempty → ∃ M' ∈ a, ∀ I ∈ a, ¬I < M') ↔ IsArtinian R M := by |
rw [isArtinian_iff_wellFounded, WellFounded.wellFounded_iff_has_min]
|
/-
Copyright (c) 2021 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Sébastien Gouëzel
-/
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.MeasureTheory.Group.Pointwise
import Mathlib.MeasureTheory.Measure.Lebesgue.Basic
import Mathlib.MeasureTheory.Measure.Haar.Basic
import Mathlib.MeasureTheory.Measure.Doubling
import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric
#align_import measure_theory.measure.lebesgue.eq_haar from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Relationship between the Haar and Lebesgue measures
We prove that the Haar measure and Lebesgue measure are equal on `ℝ` and on `ℝ^ι`, in
`MeasureTheory.addHaarMeasure_eq_volume` and `MeasureTheory.addHaarMeasure_eq_volume_pi`.
We deduce basic properties of any Haar measure on a finite dimensional real vector space:
* `map_linearMap_addHaar_eq_smul_addHaar`: a linear map rescales the Haar measure by the
absolute value of its determinant.
* `addHaar_preimage_linearMap` : when `f` is a linear map with nonzero determinant, the measure
of `f ⁻¹' s` is the measure of `s` multiplied by the absolute value of the inverse of the
determinant of `f`.
* `addHaar_image_linearMap` : when `f` is a linear map, the measure of `f '' s` is the
measure of `s` multiplied by the absolute value of the determinant of `f`.
* `addHaar_submodule` : a strict submodule has measure `0`.
* `addHaar_smul` : the measure of `r • s` is `|r| ^ dim * μ s`.
* `addHaar_ball`: the measure of `ball x r` is `r ^ dim * μ (ball 0 1)`.
* `addHaar_closedBall`: the measure of `closedBall x r` is `r ^ dim * μ (ball 0 1)`.
* `addHaar_sphere`: spheres have zero measure.
This makes it possible to associate a Lebesgue measure to an `n`-alternating map in dimension `n`.
This measure is called `AlternatingMap.measure`. Its main property is
`ω.measure_parallelepiped v`, stating that the associated measure of the parallelepiped spanned
by vectors `v₁, ..., vₙ` is given by `|ω v|`.
We also show that a Lebesgue density point `x` of a set `s` (with respect to closed balls) has
density one for the rescaled copies `{x} + r • t` of a given set `t` with positive measure, in
`tendsto_addHaar_inter_smul_one_of_density_one`. In particular, `s` intersects `{x} + r • t` for
small `r`, see `eventually_nonempty_inter_smul_of_density_one`.
Statements on integrals of functions with respect to an additive Haar measure can be found in
`MeasureTheory.Measure.Haar.NormedSpace`.
-/
assert_not_exists MeasureTheory.integral
open TopologicalSpace Set Filter Metric Bornology
open scoped ENNReal Pointwise Topology NNReal
/-- The interval `[0,1]` as a compact set with non-empty interior. -/
def TopologicalSpace.PositiveCompacts.Icc01 : PositiveCompacts ℝ where
carrier := Icc 0 1
isCompact' := isCompact_Icc
interior_nonempty' := by simp_rw [interior_Icc, nonempty_Ioo, zero_lt_one]
#align topological_space.positive_compacts.Icc01 TopologicalSpace.PositiveCompacts.Icc01
universe u
/-- The set `[0,1]^ι` as a compact set with non-empty interior. -/
def TopologicalSpace.PositiveCompacts.piIcc01 (ι : Type*) [Finite ι] :
PositiveCompacts (ι → ℝ) where
carrier := pi univ fun _ => Icc 0 1
isCompact' := isCompact_univ_pi fun _ => isCompact_Icc
interior_nonempty' := by
simp only [interior_pi_set, Set.toFinite, interior_Icc, univ_pi_nonempty_iff, nonempty_Ioo,
imp_true_iff, zero_lt_one]
#align topological_space.positive_compacts.pi_Icc01 TopologicalSpace.PositiveCompacts.piIcc01
/-- The parallelepiped formed from the standard basis for `ι → ℝ` is `[0,1]^ι` -/
theorem Basis.parallelepiped_basisFun (ι : Type*) [Fintype ι] :
(Pi.basisFun ℝ ι).parallelepiped = TopologicalSpace.PositiveCompacts.piIcc01 ι :=
SetLike.coe_injective <| by
refine Eq.trans ?_ ((uIcc_of_le ?_).trans (Set.pi_univ_Icc _ _).symm)
· classical convert parallelepiped_single (ι := ι) 1
· exact zero_le_one
#align basis.parallelepiped_basis_fun Basis.parallelepiped_basisFun
/-- A parallelepiped can be expressed on the standard basis. -/
theorem Basis.parallelepiped_eq_map {ι E : Type*} [Fintype ι] [NormedAddCommGroup E]
[NormedSpace ℝ E] (b : Basis ι ℝ E) :
b.parallelepiped = (PositiveCompacts.piIcc01 ι).map b.equivFun.symm
b.equivFunL.symm.continuous b.equivFunL.symm.isOpenMap := by
classical
rw [← Basis.parallelepiped_basisFun, ← Basis.parallelepiped_map]
congr with x
simp
open MeasureTheory MeasureTheory.Measure
theorem Basis.map_addHaar {ι E F : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedAddCommGroup F]
[NormedSpace ℝ E] [NormedSpace ℝ F] [MeasurableSpace E] [MeasurableSpace F] [BorelSpace E]
[BorelSpace F] [SecondCountableTopology F] [SigmaCompactSpace F]
(b : Basis ι ℝ E) (f : E ≃L[ℝ] F) :
map f b.addHaar = (b.map f.toLinearEquiv).addHaar := by
have : IsAddHaarMeasure (map f b.addHaar) :=
AddEquiv.isAddHaarMeasure_map b.addHaar f.toAddEquiv f.continuous f.symm.continuous
rw [eq_comm, Basis.addHaar_eq_iff, Measure.map_apply f.continuous.measurable
(PositiveCompacts.isCompact _).measurableSet, Basis.coe_parallelepiped, Basis.coe_map]
erw [← image_parallelepiped, f.toEquiv.preimage_image, addHaar_self]
namespace MeasureTheory
open Measure TopologicalSpace.PositiveCompacts FiniteDimensional
/-!
### The Lebesgue measure is a Haar measure on `ℝ` and on `ℝ^ι`.
-/
/-- The Haar measure equals the Lebesgue measure on `ℝ`. -/
theorem addHaarMeasure_eq_volume : addHaarMeasure Icc01 = volume := by
convert (addHaarMeasure_unique volume Icc01).symm; simp [Icc01]
#align measure_theory.add_haar_measure_eq_volume MeasureTheory.addHaarMeasure_eq_volume
/-- The Haar measure equals the Lebesgue measure on `ℝ^ι`. -/
theorem addHaarMeasure_eq_volume_pi (ι : Type*) [Fintype ι] :
addHaarMeasure (piIcc01 ι) = volume := by
convert (addHaarMeasure_unique volume (piIcc01 ι)).symm
simp only [piIcc01, volume_pi_pi fun _ => Icc (0 : ℝ) 1, PositiveCompacts.coe_mk,
Compacts.coe_mk, Finset.prod_const_one, ENNReal.ofReal_one, Real.volume_Icc, one_smul, sub_zero]
#align measure_theory.add_haar_measure_eq_volume_pi MeasureTheory.addHaarMeasure_eq_volume_pi
-- Porting note (#11215): TODO: remove this instance?
instance isAddHaarMeasure_volume_pi (ι : Type*) [Fintype ι] :
IsAddHaarMeasure (volume : Measure (ι → ℝ)) :=
inferInstance
#align measure_theory.is_add_haar_measure_volume_pi MeasureTheory.isAddHaarMeasure_volume_pi
namespace Measure
/-!
### Strict subspaces have zero measure
-/
/-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure
zero. This auxiliary lemma proves this assuming additionally that the set is bounded. -/
theorem addHaar_eq_zero_of_disjoint_translates_aux {E : Type*} [NormedAddCommGroup E]
[NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E)
[IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (sb : IsBounded s) (hu : IsBounded (range u))
(hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by
by_contra h
apply lt_irrefl ∞
calc
∞ = ∑' _ : ℕ, μ s := (ENNReal.tsum_const_eq_top_of_ne_zero h).symm
_ = ∑' n : ℕ, μ ({u n} + s) := by
congr 1; ext1 n; simp only [image_add_left, measure_preimage_add, singleton_add]
_ = μ (⋃ n, {u n} + s) := Eq.symm <| measure_iUnion hs fun n => by
simpa only [image_add_left, singleton_add] using measurable_id.const_add _ h's
_ = μ (range u + s) := by rw [← iUnion_add, iUnion_singleton_eq_range]
_ < ∞ := (hu.add sb).measure_lt_top
#align measure_theory.measure.add_haar_eq_zero_of_disjoint_translates_aux MeasureTheory.Measure.addHaar_eq_zero_of_disjoint_translates_aux
/-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure
zero. -/
theorem addHaar_eq_zero_of_disjoint_translates {E : Type*} [NormedAddCommGroup E]
[NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E)
[IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (hu : IsBounded (range u))
(hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by
suffices H : ∀ R, μ (s ∩ closedBall 0 R) = 0 by
apply le_antisymm _ (zero_le _)
calc
μ s ≤ ∑' n : ℕ, μ (s ∩ closedBall 0 n) := by
conv_lhs => rw [← iUnion_inter_closedBall_nat s 0]
exact measure_iUnion_le _
_ = 0 := by simp only [H, tsum_zero]
intro R
apply addHaar_eq_zero_of_disjoint_translates_aux μ u
(isBounded_closedBall.subset inter_subset_right) hu _ (h's.inter measurableSet_closedBall)
refine pairwise_disjoint_mono hs fun n => ?_
exact add_subset_add Subset.rfl inter_subset_left
#align measure_theory.measure.add_haar_eq_zero_of_disjoint_translates MeasureTheory.Measure.addHaar_eq_zero_of_disjoint_translates
/-- A strict vector subspace has measure zero. -/
theorem addHaar_submodule {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E]
[BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] (s : Submodule ℝ E)
(hs : s ≠ ⊤) : μ s = 0 := by
obtain ⟨x, hx⟩ : ∃ x, x ∉ s := by
simpa only [Submodule.eq_top_iff', not_exists, Ne, not_forall] using hs
obtain ⟨c, cpos, cone⟩ : ∃ c : ℝ, 0 < c ∧ c < 1 := ⟨1 / 2, by norm_num, by norm_num⟩
have A : IsBounded (range fun n : ℕ => c ^ n • x) :=
have : Tendsto (fun n : ℕ => c ^ n • x) atTop (𝓝 ((0 : ℝ) • x)) :=
(tendsto_pow_atTop_nhds_zero_of_lt_one cpos.le cone).smul_const x
isBounded_range_of_tendsto _ this
apply addHaar_eq_zero_of_disjoint_translates μ _ A _
(Submodule.closed_of_finiteDimensional s).measurableSet
intro m n hmn
simp only [Function.onFun, image_add_left, singleton_add, disjoint_left, mem_preimage,
SetLike.mem_coe]
intro y hym hyn
have A : (c ^ n - c ^ m) • x ∈ s := by
convert s.sub_mem hym hyn using 1
simp only [sub_smul, neg_sub_neg, add_sub_add_right_eq_sub]
have H : c ^ n - c ^ m ≠ 0 := by
simpa only [sub_eq_zero, Ne] using (pow_right_strictAnti cpos cone).injective.ne hmn.symm
have : x ∈ s := by
convert s.smul_mem (c ^ n - c ^ m)⁻¹ A
rw [smul_smul, inv_mul_cancel H, one_smul]
exact hx this
#align measure_theory.measure.add_haar_submodule MeasureTheory.Measure.addHaar_submodule
/-- A strict affine subspace has measure zero. -/
theorem addHaar_affineSubspace {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ]
(s : AffineSubspace ℝ E) (hs : s ≠ ⊤) : μ s = 0 := by
rcases s.eq_bot_or_nonempty with (rfl | hne)
· rw [AffineSubspace.bot_coe, measure_empty]
rw [Ne, ← AffineSubspace.direction_eq_top_iff_of_nonempty hne] at hs
rcases hne with ⟨x, hx : x ∈ s⟩
simpa only [AffineSubspace.coe_direction_eq_vsub_set_right hx, vsub_eq_sub, sub_eq_add_neg,
image_add_right, neg_neg, measure_preimage_add_right] using addHaar_submodule μ s.direction hs
#align measure_theory.measure.add_haar_affine_subspace MeasureTheory.Measure.addHaar_affineSubspace
/-!
### Applying a linear map rescales Haar measure by the determinant
We first prove this on `ι → ℝ`, using that this is already known for the product Lebesgue
measure (thanks to matrices computations). Then, we extend this to any finite-dimensional real
vector space by using a linear equiv with a space of the form `ι → ℝ`, and arguing that such a
linear equiv maps Haar measure to Haar measure.
-/
theorem map_linearMap_addHaar_pi_eq_smul_addHaar {ι : Type*} [Finite ι] {f : (ι → ℝ) →ₗ[ℝ] ι → ℝ}
(hf : LinearMap.det f ≠ 0) (μ : Measure (ι → ℝ)) [IsAddHaarMeasure μ] :
Measure.map f μ = ENNReal.ofReal (abs (LinearMap.det f)⁻¹) • μ := by
cases nonempty_fintype ι
/- We have already proved the result for the Lebesgue product measure, using matrices.
We deduce it for any Haar measure by uniqueness (up to scalar multiplication). -/
have := addHaarMeasure_unique μ (piIcc01 ι)
rw [this, addHaarMeasure_eq_volume_pi, Measure.map_smul,
Real.map_linearMap_volume_pi_eq_smul_volume_pi hf, smul_comm]
#align measure_theory.measure.map_linear_map_add_haar_pi_eq_smul_add_haar MeasureTheory.Measure.map_linearMap_addHaar_pi_eq_smul_addHaar
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
[FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {F : Type*} [NormedAddCommGroup F]
[NormedSpace ℝ F] [CompleteSpace F]
theorem map_linearMap_addHaar_eq_smul_addHaar {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) :
Measure.map f μ = ENNReal.ofReal |(LinearMap.det f)⁻¹| • μ := by
-- we reduce to the case of `E = ι → ℝ`, for which we have already proved the result using
-- matrices in `map_linearMap_addHaar_pi_eq_smul_addHaar`.
let ι := Fin (finrank ℝ E)
haveI : FiniteDimensional ℝ (ι → ℝ) := by infer_instance
have : finrank ℝ E = finrank ℝ (ι → ℝ) := by simp [ι]
have e : E ≃ₗ[ℝ] ι → ℝ := LinearEquiv.ofFinrankEq E (ι → ℝ) this
-- next line is to avoid `g` getting reduced by `simp`.
obtain ⟨g, hg⟩ : ∃ g, g = (e : E →ₗ[ℝ] ι → ℝ).comp (f.comp (e.symm : (ι → ℝ) →ₗ[ℝ] E)) := ⟨_, rfl⟩
have gdet : LinearMap.det g = LinearMap.det f := by rw [hg]; exact LinearMap.det_conj f e
rw [← gdet] at hf ⊢
have fg : f = (e.symm : (ι → ℝ) →ₗ[ℝ] E).comp (g.comp (e : E →ₗ[ℝ] ι → ℝ)) := by
ext x
simp only [LinearEquiv.coe_coe, Function.comp_apply, LinearMap.coe_comp,
LinearEquiv.symm_apply_apply, hg]
simp only [fg, LinearEquiv.coe_coe, LinearMap.coe_comp]
have Ce : Continuous e := (e : E →ₗ[ℝ] ι → ℝ).continuous_of_finiteDimensional
have Cg : Continuous g := LinearMap.continuous_of_finiteDimensional g
have Cesymm : Continuous e.symm := (e.symm : (ι → ℝ) →ₗ[ℝ] E).continuous_of_finiteDimensional
rw [← map_map Cesymm.measurable (Cg.comp Ce).measurable, ← map_map Cg.measurable Ce.measurable]
haveI : IsAddHaarMeasure (map e μ) := (e : E ≃+ (ι → ℝ)).isAddHaarMeasure_map μ Ce Cesymm
have ecomp : e.symm ∘ e = id := by
ext x; simp only [id, Function.comp_apply, LinearEquiv.symm_apply_apply]
rw [map_linearMap_addHaar_pi_eq_smul_addHaar hf (map e μ), Measure.map_smul,
map_map Cesymm.measurable Ce.measurable, ecomp, Measure.map_id]
#align measure_theory.measure.map_linear_map_add_haar_eq_smul_add_haar MeasureTheory.Measure.map_linearMap_addHaar_eq_smul_addHaar
/-- The preimage of a set `s` under a linear map `f` with nonzero determinant has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_linearMap {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s :=
calc
μ (f ⁻¹' s) = Measure.map f μ s :=
((f.equivOfDetNeZero hf).toContinuousLinearEquiv.toHomeomorph.toMeasurableEquiv.map_apply
s).symm
_ = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s := by
rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]; rfl
#align measure_theory.measure.add_haar_preimage_linear_map MeasureTheory.Measure.addHaar_preimage_linearMap
/-- The preimage of a set `s` under a continuous linear map `f` with nonzero determinant has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_continuousLinearMap {f : E →L[ℝ] E}
(hf : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal (abs (LinearMap.det (f : E →ₗ[ℝ] E))⁻¹) * μ s :=
addHaar_preimage_linearMap μ hf s
#align measure_theory.measure.add_haar_preimage_continuous_linear_map MeasureTheory.Measure.addHaar_preimage_continuousLinearMap
/-- The preimage of a set `s` under a linear equiv `f` has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_linearEquiv (f : E ≃ₗ[ℝ] E) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s := by
have A : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0 := (LinearEquiv.isUnit_det' f).ne_zero
convert addHaar_preimage_linearMap μ A s
simp only [LinearEquiv.det_coe_symm]
#align measure_theory.measure.add_haar_preimage_linear_equiv MeasureTheory.Measure.addHaar_preimage_linearEquiv
/-- The preimage of a set `s` under a continuous linear equiv `f` has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s :=
addHaar_preimage_linearEquiv μ _ s
#align measure_theory.measure.add_haar_preimage_continuous_linear_equiv MeasureTheory.Measure.addHaar_preimage_continuousLinearEquiv
/-- The image of a set `s` under a linear map `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_linearMap (f : E →ₗ[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det f| * μ s := by
rcases ne_or_eq (LinearMap.det f) 0 with (hf | hf)
· let g := (f.equivOfDetNeZero hf).toContinuousLinearEquiv
change μ (g '' s) = _
rw [ContinuousLinearEquiv.image_eq_preimage g s, addHaar_preimage_continuousLinearEquiv]
congr
· simp only [hf, zero_mul, ENNReal.ofReal_zero, abs_zero]
have : μ (LinearMap.range f) = 0 :=
addHaar_submodule μ _ (LinearMap.range_lt_top_of_det_eq_zero hf).ne
exact le_antisymm (le_trans (measure_mono (image_subset_range _ _)) this.le) (zero_le _)
#align measure_theory.measure.add_haar_image_linear_map MeasureTheory.Measure.addHaar_image_linearMap
/-- The image of a set `s` under a continuous linear map `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_continuousLinearMap (f : E →L[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s :=
addHaar_image_linearMap μ _ s
#align measure_theory.measure.add_haar_image_continuous_linear_map MeasureTheory.Measure.addHaar_image_continuousLinearMap
/-- The image of a set `s` under a continuous linear equiv `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s :=
μ.addHaar_image_linearMap (f : E →ₗ[ℝ] E) s
#align measure_theory.measure.add_haar_image_continuous_linear_equiv MeasureTheory.Measure.addHaar_image_continuousLinearEquiv
theorem LinearMap.quasiMeasurePreserving (f : E →ₗ[ℝ] E) (hf : LinearMap.det f ≠ 0) :
QuasiMeasurePreserving f μ μ := by
refine ⟨f.continuous_of_finiteDimensional.measurable, ?_⟩
rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]
exact smul_absolutelyContinuous
theorem ContinuousLinearMap.quasiMeasurePreserving (f : E →L[ℝ] E) (hf : f.det ≠ 0) :
QuasiMeasurePreserving f μ μ :=
LinearMap.quasiMeasurePreserving μ (f : E →ₗ[ℝ] E) hf
/-!
### Basic properties of Haar measures on real vector spaces
-/
theorem map_addHaar_smul {r : ℝ} (hr : r ≠ 0) :
Measure.map (r • ·) μ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) • μ := by
let f : E →ₗ[ℝ] E := r • (1 : E →ₗ[ℝ] E)
change Measure.map f μ = _
have hf : LinearMap.det f ≠ 0 := by
simp only [f, mul_one, LinearMap.det_smul, Ne, MonoidHom.map_one]
intro h
exact hr (pow_eq_zero h)
simp only [f, map_linearMap_addHaar_eq_smul_addHaar μ hf, mul_one, LinearMap.det_smul, map_one]
#align measure_theory.measure.map_add_haar_smul MeasureTheory.Measure.map_addHaar_smul
| Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean | 368 | 372 | theorem quasiMeasurePreserving_smul {r : ℝ} (hr : r ≠ 0) :
QuasiMeasurePreserving (r • ·) μ μ := by |
refine ⟨measurable_const_smul r, ?_⟩
rw [map_addHaar_smul μ hr]
exact smul_absolutelyContinuous
|
/-
Copyright (c) 2017 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Logic.Relation
import Mathlib.Data.Option.Basic
import Mathlib.Data.Seq.Seq
#align_import data.seq.wseq from "leanprover-community/mathlib"@"a7e36e48519ab281320c4d192da6a7b348ce40ad"
/-!
# Partially defined possibly infinite lists
This file provides a `WSeq α` type representing partially defined possibly infinite lists
(referred here as weak sequences).
-/
namespace Stream'
open Function
universe u v w
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
/-- Weak sequences.
While the `Seq` structure allows for lists which may not be finite,
a weak sequence also allows the computation of each element to
involve an indeterminate amount of computation, including possibly
an infinite loop. This is represented as a regular `Seq` interspersed
with `none` elements to indicate that computation is ongoing.
This model is appropriate for Haskell style lazy lists, and is closed
under most interesting computation patterns on infinite lists,
but conversely it is difficult to extract elements from it. -/
def WSeq (α) :=
Seq (Option α)
#align stream.wseq Stream'.WSeq
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
namespace WSeq
variable {α : Type u} {β : Type v} {γ : Type w}
/-- Turn a sequence into a weak sequence -/
@[coe]
def ofSeq : Seq α → WSeq α :=
(· <$> ·) some
#align stream.wseq.of_seq Stream'.WSeq.ofSeq
/-- Turn a list into a weak sequence -/
@[coe]
def ofList (l : List α) : WSeq α :=
ofSeq l
#align stream.wseq.of_list Stream'.WSeq.ofList
/-- Turn a stream into a weak sequence -/
@[coe]
def ofStream (l : Stream' α) : WSeq α :=
ofSeq l
#align stream.wseq.of_stream Stream'.WSeq.ofStream
instance coeSeq : Coe (Seq α) (WSeq α) :=
⟨ofSeq⟩
#align stream.wseq.coe_seq Stream'.WSeq.coeSeq
instance coeList : Coe (List α) (WSeq α) :=
⟨ofList⟩
#align stream.wseq.coe_list Stream'.WSeq.coeList
instance coeStream : Coe (Stream' α) (WSeq α) :=
⟨ofStream⟩
#align stream.wseq.coe_stream Stream'.WSeq.coeStream
/-- The empty weak sequence -/
def nil : WSeq α :=
Seq.nil
#align stream.wseq.nil Stream'.WSeq.nil
instance inhabited : Inhabited (WSeq α) :=
⟨nil⟩
#align stream.wseq.inhabited Stream'.WSeq.inhabited
/-- Prepend an element to a weak sequence -/
def cons (a : α) : WSeq α → WSeq α :=
Seq.cons (some a)
#align stream.wseq.cons Stream'.WSeq.cons
/-- Compute for one tick, without producing any elements -/
def think : WSeq α → WSeq α :=
Seq.cons none
#align stream.wseq.think Stream'.WSeq.think
/-- Destruct a weak sequence, to (eventually possibly) produce either
`none` for `nil` or `some (a, s)` if an element is produced. -/
def destruct : WSeq α → Computation (Option (α × WSeq α)) :=
Computation.corec fun s =>
match Seq.destruct s with
| none => Sum.inl none
| some (none, s') => Sum.inr s'
| some (some a, s') => Sum.inl (some (a, s'))
#align stream.wseq.destruct Stream'.WSeq.destruct
/-- Recursion principle for weak sequences, compare with `List.recOn`. -/
def recOn {C : WSeq α → Sort v} (s : WSeq α) (h1 : C nil) (h2 : ∀ x s, C (cons x s))
(h3 : ∀ s, C (think s)) : C s :=
Seq.recOn s h1 fun o => Option.recOn o h3 h2
#align stream.wseq.rec_on Stream'.WSeq.recOn
/-- membership for weak sequences-/
protected def Mem (a : α) (s : WSeq α) :=
Seq.Mem (some a) s
#align stream.wseq.mem Stream'.WSeq.Mem
instance membership : Membership α (WSeq α) :=
⟨WSeq.Mem⟩
#align stream.wseq.has_mem Stream'.WSeq.membership
theorem not_mem_nil (a : α) : a ∉ @nil α :=
Seq.not_mem_nil (some a)
#align stream.wseq.not_mem_nil Stream'.WSeq.not_mem_nil
/-- Get the head of a weak sequence. This involves a possibly
infinite computation. -/
def head (s : WSeq α) : Computation (Option α) :=
Computation.map (Prod.fst <$> ·) (destruct s)
#align stream.wseq.head Stream'.WSeq.head
/-- Encode a computation yielding a weak sequence into additional
`think` constructors in a weak sequence -/
def flatten : Computation (WSeq α) → WSeq α :=
Seq.corec fun c =>
match Computation.destruct c with
| Sum.inl s => Seq.omap (return ·) (Seq.destruct s)
| Sum.inr c' => some (none, c')
#align stream.wseq.flatten Stream'.WSeq.flatten
/-- Get the tail of a weak sequence. This doesn't need a `Computation`
wrapper, unlike `head`, because `flatten` allows us to hide this
in the construction of the weak sequence itself. -/
def tail (s : WSeq α) : WSeq α :=
flatten <| (fun o => Option.recOn o nil Prod.snd) <$> destruct s
#align stream.wseq.tail Stream'.WSeq.tail
/-- drop the first `n` elements from `s`. -/
def drop (s : WSeq α) : ℕ → WSeq α
| 0 => s
| n + 1 => tail (drop s n)
#align stream.wseq.drop Stream'.WSeq.drop
/-- Get the nth element of `s`. -/
def get? (s : WSeq α) (n : ℕ) : Computation (Option α) :=
head (drop s n)
#align stream.wseq.nth Stream'.WSeq.get?
/-- Convert `s` to a list (if it is finite and completes in finite time). -/
def toList (s : WSeq α) : Computation (List α) :=
@Computation.corec (List α) (List α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s'))
([], s)
#align stream.wseq.to_list Stream'.WSeq.toList
/-- Get the length of `s` (if it is finite and completes in finite time). -/
def length (s : WSeq α) : Computation ℕ :=
@Computation.corec ℕ (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s with
| none => Sum.inl n
| some (none, s') => Sum.inr (n, s')
| some (some _, s') => Sum.inr (n + 1, s'))
(0, s)
#align stream.wseq.length Stream'.WSeq.length
/-- A weak sequence is finite if `toList s` terminates. Equivalently,
it is a finite number of `think` and `cons` applied to `nil`. -/
class IsFinite (s : WSeq α) : Prop where
out : (toList s).Terminates
#align stream.wseq.is_finite Stream'.WSeq.IsFinite
instance toList_terminates (s : WSeq α) [h : IsFinite s] : (toList s).Terminates :=
h.out
#align stream.wseq.to_list_terminates Stream'.WSeq.toList_terminates
/-- Get the list corresponding to a finite weak sequence. -/
def get (s : WSeq α) [IsFinite s] : List α :=
(toList s).get
#align stream.wseq.get Stream'.WSeq.get
/-- A weak sequence is *productive* if it never stalls forever - there are
always a finite number of `think`s between `cons` constructors.
The sequence itself is allowed to be infinite though. -/
class Productive (s : WSeq α) : Prop where
get?_terminates : ∀ n, (get? s n).Terminates
#align stream.wseq.productive Stream'.WSeq.Productive
#align stream.wseq.productive.nth_terminates Stream'.WSeq.Productive.get?_terminates
theorem productive_iff (s : WSeq α) : Productive s ↔ ∀ n, (get? s n).Terminates :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align stream.wseq.productive_iff Stream'.WSeq.productive_iff
instance get?_terminates (s : WSeq α) [h : Productive s] : ∀ n, (get? s n).Terminates :=
h.get?_terminates
#align stream.wseq.nth_terminates Stream'.WSeq.get?_terminates
instance head_terminates (s : WSeq α) [Productive s] : (head s).Terminates :=
s.get?_terminates 0
#align stream.wseq.head_terminates Stream'.WSeq.head_terminates
/-- Replace the `n`th element of `s` with `a`. -/
def updateNth (s : WSeq α) (n : ℕ) (a : α) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (some a, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.update_nth Stream'.WSeq.updateNth
/-- Remove the `n`th element of `s`. -/
def removeNth (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (none, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.remove_nth Stream'.WSeq.removeNth
/-- Map the elements of `s` over `f`, removing any values that yield `none`. -/
def filterMap (f : α → Option β) : WSeq α → WSeq β :=
Seq.corec fun s =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, s')
| some (some a, s') => some (f a, s')
#align stream.wseq.filter_map Stream'.WSeq.filterMap
/-- Select the elements of `s` that satisfy `p`. -/
def filter (p : α → Prop) [DecidablePred p] : WSeq α → WSeq α :=
filterMap fun a => if p a then some a else none
#align stream.wseq.filter Stream'.WSeq.filter
-- example of infinite list manipulations
/-- Get the first element of `s` satisfying `p`. -/
def find (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation (Option α) :=
head <| filter p s
#align stream.wseq.find Stream'.WSeq.find
/-- Zip a function over two weak sequences -/
def zipWith (f : α → β → γ) (s1 : WSeq α) (s2 : WSeq β) : WSeq γ :=
@Seq.corec (Option γ) (WSeq α × WSeq β)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some _, _), some (none, s2') => some (none, s1, s2')
| some (none, s1'), some (some _, _) => some (none, s1', s2)
| some (some a1, s1'), some (some a2, s2') => some (some (f a1 a2), s1', s2')
| _, _ => none)
(s1, s2)
#align stream.wseq.zip_with Stream'.WSeq.zipWith
/-- Zip two weak sequences into a single sequence of pairs -/
def zip : WSeq α → WSeq β → WSeq (α × β) :=
zipWith Prod.mk
#align stream.wseq.zip Stream'.WSeq.zip
/-- Get the list of indexes of elements of `s` satisfying `p` -/
def findIndexes (p : α → Prop) [DecidablePred p] (s : WSeq α) : WSeq ℕ :=
(zip s (Stream'.nats : WSeq ℕ)).filterMap fun ⟨a, n⟩ => if p a then some n else none
#align stream.wseq.find_indexes Stream'.WSeq.findIndexes
/-- Get the index of the first element of `s` satisfying `p` -/
def findIndex (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation ℕ :=
(fun o => Option.getD o 0) <$> head (findIndexes p s)
#align stream.wseq.find_index Stream'.WSeq.findIndex
/-- Get the index of the first occurrence of `a` in `s` -/
def indexOf [DecidableEq α] (a : α) : WSeq α → Computation ℕ :=
findIndex (Eq a)
#align stream.wseq.index_of Stream'.WSeq.indexOf
/-- Get the indexes of occurrences of `a` in `s` -/
def indexesOf [DecidableEq α] (a : α) : WSeq α → WSeq ℕ :=
findIndexes (Eq a)
#align stream.wseq.indexes_of Stream'.WSeq.indexesOf
/-- `union s1 s2` is a weak sequence which interleaves `s1` and `s2` in
some order (nondeterministically). -/
def union (s1 s2 : WSeq α) : WSeq α :=
@Seq.corec (Option α) (WSeq α × WSeq α)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| none, none => none
| some (a1, s1'), none => some (a1, s1', nil)
| none, some (a2, s2') => some (a2, nil, s2')
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some a1, s1'), some (none, s2') => some (some a1, s1', s2')
| some (none, s1'), some (some a2, s2') => some (some a2, s1', s2')
| some (some a1, s1'), some (some a2, s2') => some (some a1, cons a2 s1', s2'))
(s1, s2)
#align stream.wseq.union Stream'.WSeq.union
/-- Returns `true` if `s` is `nil` and `false` if `s` has an element -/
def isEmpty (s : WSeq α) : Computation Bool :=
Computation.map Option.isNone <| head s
#align stream.wseq.is_empty Stream'.WSeq.isEmpty
/-- Calculate one step of computation -/
def compute (s : WSeq α) : WSeq α :=
match Seq.destruct s with
| some (none, s') => s'
| _ => s
#align stream.wseq.compute Stream'.WSeq.compute
/-- Get the first `n` elements of a weak sequence -/
def take (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match n, Seq.destruct s with
| 0, _ => none
| _ + 1, none => none
| m + 1, some (none, s') => some (none, m + 1, s')
| m + 1, some (some a, s') => some (some a, m, s'))
(n, s)
#align stream.wseq.take Stream'.WSeq.take
/-- Split the sequence at position `n` into a finite initial segment
and the weak sequence tail -/
def splitAt (s : WSeq α) (n : ℕ) : Computation (List α × WSeq α) :=
@Computation.corec (List α × WSeq α) (ℕ × List α × WSeq α)
(fun ⟨n, l, s⟩ =>
match n, Seq.destruct s with
| 0, _ => Sum.inl (l.reverse, s)
| _ + 1, none => Sum.inl (l.reverse, s)
| _ + 1, some (none, s') => Sum.inr (n, l, s')
| m + 1, some (some a, s') => Sum.inr (m, a::l, s'))
(n, [], s)
#align stream.wseq.split_at Stream'.WSeq.splitAt
/-- Returns `true` if any element of `s` satisfies `p` -/
def any (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl false
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inl true else Sum.inr s')
s
#align stream.wseq.any Stream'.WSeq.any
/-- Returns `true` if every element of `s` satisfies `p` -/
def all (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl true
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inr s' else Sum.inl false)
s
#align stream.wseq.all Stream'.WSeq.all
/-- Apply a function to the elements of the sequence to produce a sequence
of partial results. (There is no `scanr` because this would require
working from the end of the sequence, which may not exist.) -/
def scanl (f : α → β → α) (a : α) (s : WSeq β) : WSeq α :=
cons a <|
@Seq.corec (Option α) (α × WSeq β)
(fun ⟨a, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, a, s')
| some (some b, s') =>
let a' := f a b
some (some a', a', s'))
(a, s)
#align stream.wseq.scanl Stream'.WSeq.scanl
/-- Get the weak sequence of initial segments of the input sequence -/
def inits (s : WSeq α) : WSeq (List α) :=
cons [] <|
@Seq.corec (Option (List α)) (Batteries.DList α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, l, s')
| some (some a, s') =>
let l' := l.push a
some (some l'.toList, l', s'))
(Batteries.DList.empty, s)
#align stream.wseq.inits Stream'.WSeq.inits
/-- Like take, but does not wait for a result. Calculates `n` steps of
computation and returns the sequence computed so far -/
def collect (s : WSeq α) (n : ℕ) : List α :=
(Seq.take n s).filterMap id
#align stream.wseq.collect Stream'.WSeq.collect
/-- Append two weak sequences. As with `Seq.append`, this may not use
the second sequence if the first one takes forever to compute -/
def append : WSeq α → WSeq α → WSeq α :=
Seq.append
#align stream.wseq.append Stream'.WSeq.append
/-- Map a function over a weak sequence -/
def map (f : α → β) : WSeq α → WSeq β :=
Seq.map (Option.map f)
#align stream.wseq.map Stream'.WSeq.map
/-- Flatten a sequence of weak sequences. (Note that this allows
empty sequences, unlike `Seq.join`.) -/
def join (S : WSeq (WSeq α)) : WSeq α :=
Seq.join
((fun o : Option (WSeq α) =>
match o with
| none => Seq1.ret none
| some s => (none, s)) <$>
S)
#align stream.wseq.join Stream'.WSeq.join
/-- Monadic bind operator for weak sequences -/
def bind (s : WSeq α) (f : α → WSeq β) : WSeq β :=
join (map f s)
#align stream.wseq.bind Stream'.WSeq.bind
/-- lift a relation to a relation over weak sequences -/
@[simp]
def LiftRelO (R : α → β → Prop) (C : WSeq α → WSeq β → Prop) :
Option (α × WSeq α) → Option (β × WSeq β) → Prop
| none, none => True
| some (a, s), some (b, t) => R a b ∧ C s t
| _, _ => False
#align stream.wseq.lift_rel_o Stream'.WSeq.LiftRelO
theorem LiftRelO.imp {R S : α → β → Prop} {C D : WSeq α → WSeq β → Prop} (H1 : ∀ a b, R a b → S a b)
(H2 : ∀ s t, C s t → D s t) : ∀ {o p}, LiftRelO R C o p → LiftRelO S D o p
| none, none, _ => trivial
| some (_, _), some (_, _), h => And.imp (H1 _ _) (H2 _ _) h
| none, some _, h => False.elim h
| some (_, _), none, h => False.elim h
#align stream.wseq.lift_rel_o.imp Stream'.WSeq.LiftRelO.imp
theorem LiftRelO.imp_right (R : α → β → Prop) {C D : WSeq α → WSeq β → Prop}
(H : ∀ s t, C s t → D s t) {o p} : LiftRelO R C o p → LiftRelO R D o p :=
LiftRelO.imp (fun _ _ => id) H
#align stream.wseq.lift_rel_o.imp_right Stream'.WSeq.LiftRelO.imp_right
/-- Definition of bisimilarity for weak sequences-/
@[simp]
def BisimO (R : WSeq α → WSeq α → Prop) : Option (α × WSeq α) → Option (α × WSeq α) → Prop :=
LiftRelO (· = ·) R
#align stream.wseq.bisim_o Stream'.WSeq.BisimO
theorem BisimO.imp {R S : WSeq α → WSeq α → Prop} (H : ∀ s t, R s t → S s t) {o p} :
BisimO R o p → BisimO S o p :=
LiftRelO.imp_right _ H
#align stream.wseq.bisim_o.imp Stream'.WSeq.BisimO.imp
/-- Two weak sequences are `LiftRel R` related if they are either both empty,
or they are both nonempty and the heads are `R` related and the tails are
`LiftRel R` related. (This is a coinductive definition.) -/
def LiftRel (R : α → β → Prop) (s : WSeq α) (t : WSeq β) : Prop :=
∃ C : WSeq α → WSeq β → Prop,
C s t ∧ ∀ {s t}, C s t → Computation.LiftRel (LiftRelO R C) (destruct s) (destruct t)
#align stream.wseq.lift_rel Stream'.WSeq.LiftRel
/-- If two sequences are equivalent, then they have the same values and
the same computational behavior (i.e. if one loops forever then so does
the other), although they may differ in the number of `think`s needed to
arrive at the answer. -/
def Equiv : WSeq α → WSeq α → Prop :=
LiftRel (· = ·)
#align stream.wseq.equiv Stream'.WSeq.Equiv
theorem liftRel_destruct {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t → Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t)
| ⟨R, h1, h2⟩ => by
refine Computation.LiftRel.imp ?_ _ _ (h2 h1)
apply LiftRelO.imp_right
exact fun s' t' h' => ⟨R, h', @h2⟩
#align stream.wseq.lift_rel_destruct Stream'.WSeq.liftRel_destruct
theorem liftRel_destruct_iff {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t ↔ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) :=
⟨liftRel_destruct, fun h =>
⟨fun s t =>
LiftRel R s t ∨ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t),
Or.inr h, fun {s t} h => by
have h : Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) := by
cases' h with h h
· exact liftRel_destruct h
· assumption
apply Computation.LiftRel.imp _ _ _ h
intro a b
apply LiftRelO.imp_right
intro s t
apply Or.inl⟩⟩
#align stream.wseq.lift_rel_destruct_iff Stream'.WSeq.liftRel_destruct_iff
-- Porting note: To avoid ambiguous notation, `~` became `~ʷ`.
infixl:50 " ~ʷ " => Equiv
theorem destruct_congr {s t : WSeq α} :
s ~ʷ t → Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct
#align stream.wseq.destruct_congr Stream'.WSeq.destruct_congr
theorem destruct_congr_iff {s t : WSeq α} :
s ~ʷ t ↔ Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct_iff
#align stream.wseq.destruct_congr_iff Stream'.WSeq.destruct_congr_iff
theorem LiftRel.refl (R : α → α → Prop) (H : Reflexive R) : Reflexive (LiftRel R) := fun s => by
refine ⟨(· = ·), rfl, fun {s t} (h : s = t) => ?_⟩
rw [← h]
apply Computation.LiftRel.refl
intro a
cases' a with a
· simp
· cases a
simp only [LiftRelO, and_true]
apply H
#align stream.wseq.lift_rel.refl Stream'.WSeq.LiftRel.refl
theorem LiftRelO.swap (R : α → β → Prop) (C) :
swap (LiftRelO R C) = LiftRelO (swap R) (swap C) := by
funext x y
rcases x with ⟨⟩ | ⟨hx, jx⟩ <;> rcases y with ⟨⟩ | ⟨hy, jy⟩ <;> rfl
#align stream.wseq.lift_rel_o.swap Stream'.WSeq.LiftRelO.swap
theorem LiftRel.swap_lem {R : α → β → Prop} {s1 s2} (h : LiftRel R s1 s2) :
LiftRel (swap R) s2 s1 := by
refine ⟨swap (LiftRel R), h, fun {s t} (h : LiftRel R t s) => ?_⟩
rw [← LiftRelO.swap, Computation.LiftRel.swap]
apply liftRel_destruct h
#align stream.wseq.lift_rel.swap_lem Stream'.WSeq.LiftRel.swap_lem
theorem LiftRel.swap (R : α → β → Prop) : swap (LiftRel R) = LiftRel (swap R) :=
funext fun _ => funext fun _ => propext ⟨LiftRel.swap_lem, LiftRel.swap_lem⟩
#align stream.wseq.lift_rel.swap Stream'.WSeq.LiftRel.swap
theorem LiftRel.symm (R : α → α → Prop) (H : Symmetric R) : Symmetric (LiftRel R) :=
fun s1 s2 (h : Function.swap (LiftRel R) s2 s1) => by rwa [LiftRel.swap, H.swap_eq] at h
#align stream.wseq.lift_rel.symm Stream'.WSeq.LiftRel.symm
theorem LiftRel.trans (R : α → α → Prop) (H : Transitive R) : Transitive (LiftRel R) :=
fun s t u h1 h2 => by
refine ⟨fun s u => ∃ t, LiftRel R s t ∧ LiftRel R t u, ⟨t, h1, h2⟩, fun {s u} h => ?_⟩
rcases h with ⟨t, h1, h2⟩
have h1 := liftRel_destruct h1
have h2 := liftRel_destruct h2
refine
Computation.liftRel_def.2
⟨(Computation.terminates_of_liftRel h1).trans (Computation.terminates_of_liftRel h2),
fun {a c} ha hc => ?_⟩
rcases h1.left ha with ⟨b, hb, t1⟩
have t2 := Computation.rel_of_liftRel h2 hb hc
cases' a with a <;> cases' c with c
· trivial
· cases b
· cases t2
· cases t1
· cases a
cases' b with b
· cases t1
· cases b
cases t2
· cases' a with a s
cases' b with b
· cases t1
cases' b with b t
cases' c with c u
cases' t1 with ab st
cases' t2 with bc tu
exact ⟨H ab bc, t, st, tu⟩
#align stream.wseq.lift_rel.trans Stream'.WSeq.LiftRel.trans
theorem LiftRel.equiv (R : α → α → Prop) : Equivalence R → Equivalence (LiftRel R)
| ⟨refl, symm, trans⟩ => ⟨LiftRel.refl R refl, @(LiftRel.symm R @symm), @(LiftRel.trans R @trans)⟩
#align stream.wseq.lift_rel.equiv Stream'.WSeq.LiftRel.equiv
@[refl]
theorem Equiv.refl : ∀ s : WSeq α, s ~ʷ s :=
LiftRel.refl (· = ·) Eq.refl
#align stream.wseq.equiv.refl Stream'.WSeq.Equiv.refl
@[symm]
theorem Equiv.symm : ∀ {s t : WSeq α}, s ~ʷ t → t ~ʷ s :=
@(LiftRel.symm (· = ·) (@Eq.symm _))
#align stream.wseq.equiv.symm Stream'.WSeq.Equiv.symm
@[trans]
theorem Equiv.trans : ∀ {s t u : WSeq α}, s ~ʷ t → t ~ʷ u → s ~ʷ u :=
@(LiftRel.trans (· = ·) (@Eq.trans _))
#align stream.wseq.equiv.trans Stream'.WSeq.Equiv.trans
theorem Equiv.equivalence : Equivalence (@Equiv α) :=
⟨@Equiv.refl _, @Equiv.symm _, @Equiv.trans _⟩
#align stream.wseq.equiv.equivalence Stream'.WSeq.Equiv.equivalence
open Computation
@[simp]
theorem destruct_nil : destruct (nil : WSeq α) = Computation.pure none :=
Computation.destruct_eq_pure rfl
#align stream.wseq.destruct_nil Stream'.WSeq.destruct_nil
@[simp]
theorem destruct_cons (a : α) (s) : destruct (cons a s) = Computation.pure (some (a, s)) :=
Computation.destruct_eq_pure <| by simp [destruct, cons, Computation.rmap]
#align stream.wseq.destruct_cons Stream'.WSeq.destruct_cons
@[simp]
theorem destruct_think (s : WSeq α) : destruct (think s) = (destruct s).think :=
Computation.destruct_eq_think <| by simp [destruct, think, Computation.rmap]
#align stream.wseq.destruct_think Stream'.WSeq.destruct_think
@[simp]
theorem seq_destruct_nil : Seq.destruct (nil : WSeq α) = none :=
Seq.destruct_nil
#align stream.wseq.seq_destruct_nil Stream'.WSeq.seq_destruct_nil
@[simp]
theorem seq_destruct_cons (a : α) (s) : Seq.destruct (cons a s) = some (some a, s) :=
Seq.destruct_cons _ _
#align stream.wseq.seq_destruct_cons Stream'.WSeq.seq_destruct_cons
@[simp]
theorem seq_destruct_think (s : WSeq α) : Seq.destruct (think s) = some (none, s) :=
Seq.destruct_cons _ _
#align stream.wseq.seq_destruct_think Stream'.WSeq.seq_destruct_think
@[simp]
theorem head_nil : head (nil : WSeq α) = Computation.pure none := by simp [head]
#align stream.wseq.head_nil Stream'.WSeq.head_nil
@[simp]
theorem head_cons (a : α) (s) : head (cons a s) = Computation.pure (some a) := by simp [head]
#align stream.wseq.head_cons Stream'.WSeq.head_cons
@[simp]
theorem head_think (s : WSeq α) : head (think s) = (head s).think := by simp [head]
#align stream.wseq.head_think Stream'.WSeq.head_think
@[simp]
theorem flatten_pure (s : WSeq α) : flatten (Computation.pure s) = s := by
refine Seq.eq_of_bisim (fun s1 s2 => flatten (Computation.pure s2) = s1) ?_ rfl
intro s' s h
rw [← h]
simp only [Seq.BisimO, flatten, Seq.omap, pure_def, Seq.corec_eq, destruct_pure]
cases Seq.destruct s with
| none => simp
| some val =>
cases' val with o s'
simp
#align stream.wseq.flatten_ret Stream'.WSeq.flatten_pure
@[simp]
theorem flatten_think (c : Computation (WSeq α)) : flatten c.think = think (flatten c) :=
Seq.destruct_eq_cons <| by simp [flatten, think]
#align stream.wseq.flatten_think Stream'.WSeq.flatten_think
@[simp]
theorem destruct_flatten (c : Computation (WSeq α)) : destruct (flatten c) = c >>= destruct := by
refine
Computation.eq_of_bisim
(fun c1 c2 => c1 = c2 ∨ ∃ c, c1 = destruct (flatten c) ∧ c2 = Computation.bind c destruct) ?_
(Or.inr ⟨c, rfl, rfl⟩)
intro c1 c2 h
exact
match c1, c2, h with
| c, _, Or.inl rfl => by cases c.destruct <;> simp
| _, _, Or.inr ⟨c, rfl, rfl⟩ => by
induction' c using Computation.recOn with a c' <;> simp
· cases (destruct a).destruct <;> simp
· exact Or.inr ⟨c', rfl, rfl⟩
#align stream.wseq.destruct_flatten Stream'.WSeq.destruct_flatten
theorem head_terminates_iff (s : WSeq α) : Terminates (head s) ↔ Terminates (destruct s) :=
terminates_map_iff _ (destruct s)
#align stream.wseq.head_terminates_iff Stream'.WSeq.head_terminates_iff
@[simp]
theorem tail_nil : tail (nil : WSeq α) = nil := by simp [tail]
#align stream.wseq.tail_nil Stream'.WSeq.tail_nil
@[simp]
theorem tail_cons (a : α) (s) : tail (cons a s) = s := by simp [tail]
#align stream.wseq.tail_cons Stream'.WSeq.tail_cons
@[simp]
theorem tail_think (s : WSeq α) : tail (think s) = (tail s).think := by simp [tail]
#align stream.wseq.tail_think Stream'.WSeq.tail_think
@[simp]
theorem dropn_nil (n) : drop (nil : WSeq α) n = nil := by induction n <;> simp [*, drop]
#align stream.wseq.dropn_nil Stream'.WSeq.dropn_nil
@[simp]
theorem dropn_cons (a : α) (s) (n) : drop (cons a s) (n + 1) = drop s n := by
induction n with
| zero => simp [drop]
| succ n n_ih =>
-- porting note (#10745): was `simp [*, drop]`.
simp [drop, ← n_ih]
#align stream.wseq.dropn_cons Stream'.WSeq.dropn_cons
@[simp]
theorem dropn_think (s : WSeq α) (n) : drop (think s) n = (drop s n).think := by
induction n <;> simp [*, drop]
#align stream.wseq.dropn_think Stream'.WSeq.dropn_think
theorem dropn_add (s : WSeq α) (m) : ∀ n, drop s (m + n) = drop (drop s m) n
| 0 => rfl
| n + 1 => congr_arg tail (dropn_add s m n)
#align stream.wseq.dropn_add Stream'.WSeq.dropn_add
theorem dropn_tail (s : WSeq α) (n) : drop (tail s) n = drop s (n + 1) := by
rw [Nat.add_comm]
symm
apply dropn_add
#align stream.wseq.dropn_tail Stream'.WSeq.dropn_tail
theorem get?_add (s : WSeq α) (m n) : get? s (m + n) = get? (drop s m) n :=
congr_arg head (dropn_add _ _ _)
#align stream.wseq.nth_add Stream'.WSeq.get?_add
theorem get?_tail (s : WSeq α) (n) : get? (tail s) n = get? s (n + 1) :=
congr_arg head (dropn_tail _ _)
#align stream.wseq.nth_tail Stream'.WSeq.get?_tail
@[simp]
theorem join_nil : join nil = (nil : WSeq α) :=
Seq.join_nil
#align stream.wseq.join_nil Stream'.WSeq.join_nil
@[simp]
theorem join_think (S : WSeq (WSeq α)) : join (think S) = think (join S) := by
simp only [join, think]
dsimp only [(· <$> ·)]
simp [join, Seq1.ret]
#align stream.wseq.join_think Stream'.WSeq.join_think
@[simp]
theorem join_cons (s : WSeq α) (S) : join (cons s S) = think (append s (join S)) := by
simp only [join, think]
dsimp only [(· <$> ·)]
simp [join, cons, append]
#align stream.wseq.join_cons Stream'.WSeq.join_cons
@[simp]
theorem nil_append (s : WSeq α) : append nil s = s :=
Seq.nil_append _
#align stream.wseq.nil_append Stream'.WSeq.nil_append
@[simp]
theorem cons_append (a : α) (s t) : append (cons a s) t = cons a (append s t) :=
Seq.cons_append _ _ _
#align stream.wseq.cons_append Stream'.WSeq.cons_append
@[simp]
theorem think_append (s t : WSeq α) : append (think s) t = think (append s t) :=
Seq.cons_append _ _ _
#align stream.wseq.think_append Stream'.WSeq.think_append
@[simp]
theorem append_nil (s : WSeq α) : append s nil = s :=
Seq.append_nil _
#align stream.wseq.append_nil Stream'.WSeq.append_nil
@[simp]
theorem append_assoc (s t u : WSeq α) : append (append s t) u = append s (append t u) :=
Seq.append_assoc _ _ _
#align stream.wseq.append_assoc Stream'.WSeq.append_assoc
/-- auxiliary definition of tail over weak sequences-/
@[simp]
def tail.aux : Option (α × WSeq α) → Computation (Option (α × WSeq α))
| none => Computation.pure none
| some (_, s) => destruct s
#align stream.wseq.tail.aux Stream'.WSeq.tail.aux
theorem destruct_tail (s : WSeq α) : destruct (tail s) = destruct s >>= tail.aux := by
simp only [tail, destruct_flatten, tail.aux]; rw [← bind_pure_comp, LawfulMonad.bind_assoc]
apply congr_arg; ext1 (_ | ⟨a, s⟩) <;> apply (@pure_bind Computation _ _ _ _ _ _).trans _ <;> simp
#align stream.wseq.destruct_tail Stream'.WSeq.destruct_tail
/-- auxiliary definition of drop over weak sequences-/
@[simp]
def drop.aux : ℕ → Option (α × WSeq α) → Computation (Option (α × WSeq α))
| 0 => Computation.pure
| n + 1 => fun a => tail.aux a >>= drop.aux n
#align stream.wseq.drop.aux Stream'.WSeq.drop.aux
theorem drop.aux_none : ∀ n, @drop.aux α n none = Computation.pure none
| 0 => rfl
| n + 1 =>
show Computation.bind (Computation.pure none) (drop.aux n) = Computation.pure none by
rw [ret_bind, drop.aux_none n]
#align stream.wseq.drop.aux_none Stream'.WSeq.drop.aux_none
theorem destruct_dropn : ∀ (s : WSeq α) (n), destruct (drop s n) = destruct s >>= drop.aux n
| s, 0 => (bind_pure' _).symm
| s, n + 1 => by
rw [← dropn_tail, destruct_dropn _ n, destruct_tail, LawfulMonad.bind_assoc]
rfl
#align stream.wseq.destruct_dropn Stream'.WSeq.destruct_dropn
theorem head_terminates_of_head_tail_terminates (s : WSeq α) [T : Terminates (head (tail s))] :
Terminates (head s) :=
(head_terminates_iff _).2 <| by
rcases (head_terminates_iff _).1 T with ⟨⟨a, h⟩⟩
simp? [tail] at h says simp only [tail, destruct_flatten] at h
rcases exists_of_mem_bind h with ⟨s', h1, _⟩
unfold Functor.map at h1
exact
let ⟨t, h3, _⟩ := Computation.exists_of_mem_map h1
Computation.terminates_of_mem h3
#align stream.wseq.head_terminates_of_head_tail_terminates Stream'.WSeq.head_terminates_of_head_tail_terminates
theorem destruct_some_of_destruct_tail_some {s : WSeq α} {a} (h : some a ∈ destruct (tail s)) :
∃ a', some a' ∈ destruct s := by
unfold tail Functor.map at h; simp only [destruct_flatten] at h
rcases exists_of_mem_bind h with ⟨t, tm, td⟩; clear h
rcases Computation.exists_of_mem_map tm with ⟨t', ht', ht2⟩; clear tm
cases' t' with t' <;> rw [← ht2] at td <;> simp only [destruct_nil] at td
· have := mem_unique td (ret_mem _)
contradiction
· exact ⟨_, ht'⟩
#align stream.wseq.destruct_some_of_destruct_tail_some Stream'.WSeq.destruct_some_of_destruct_tail_some
theorem head_some_of_head_tail_some {s : WSeq α} {a} (h : some a ∈ head (tail s)) :
∃ a', some a' ∈ head s := by
unfold head at h
rcases Computation.exists_of_mem_map h with ⟨o, md, e⟩; clear h
cases' o with o <;> [injection e; injection e with h']; clear h'
cases' destruct_some_of_destruct_tail_some md with a am
exact ⟨_, Computation.mem_map (@Prod.fst α (WSeq α) <$> ·) am⟩
#align stream.wseq.head_some_of_head_tail_some Stream'.WSeq.head_some_of_head_tail_some
theorem head_some_of_get?_some {s : WSeq α} {a n} (h : some a ∈ get? s n) :
∃ a', some a' ∈ head s := by
induction n generalizing a with
| zero => exact ⟨_, h⟩
| succ n IH =>
let ⟨a', h'⟩ := head_some_of_head_tail_some h
exact IH h'
#align stream.wseq.head_some_of_nth_some Stream'.WSeq.head_some_of_get?_some
instance productive_tail (s : WSeq α) [Productive s] : Productive (tail s) :=
⟨fun n => by rw [get?_tail]; infer_instance⟩
#align stream.wseq.productive_tail Stream'.WSeq.productive_tail
instance productive_dropn (s : WSeq α) [Productive s] (n) : Productive (drop s n) :=
⟨fun m => by rw [← get?_add]; infer_instance⟩
#align stream.wseq.productive_dropn Stream'.WSeq.productive_dropn
/-- Given a productive weak sequence, we can collapse all the `think`s to
produce a sequence. -/
def toSeq (s : WSeq α) [Productive s] : Seq α :=
⟨fun n => (get? s n).get,
fun {n} h => by
cases e : Computation.get (get? s (n + 1))
· assumption
have := Computation.mem_of_get_eq _ e
simp? [get?] at this h says simp only [get?] at this h
cases' head_some_of_head_tail_some this with a' h'
have := mem_unique h' (@Computation.mem_of_get_eq _ _ _ _ h)
contradiction⟩
#align stream.wseq.to_seq Stream'.WSeq.toSeq
theorem get?_terminates_le {s : WSeq α} {m n} (h : m ≤ n) :
Terminates (get? s n) → Terminates (get? s m) := by
induction' h with m' _ IH
exacts [id, fun T => IH (@head_terminates_of_head_tail_terminates _ _ T)]
#align stream.wseq.nth_terminates_le Stream'.WSeq.get?_terminates_le
theorem head_terminates_of_get?_terminates {s : WSeq α} {n} :
Terminates (get? s n) → Terminates (head s) :=
get?_terminates_le (Nat.zero_le n)
#align stream.wseq.head_terminates_of_nth_terminates Stream'.WSeq.head_terminates_of_get?_terminates
theorem destruct_terminates_of_get?_terminates {s : WSeq α} {n} (T : Terminates (get? s n)) :
Terminates (destruct s) :=
(head_terminates_iff _).1 <| head_terminates_of_get?_terminates T
#align stream.wseq.destruct_terminates_of_nth_terminates Stream'.WSeq.destruct_terminates_of_get?_terminates
theorem mem_rec_on {C : WSeq α → Prop} {a s} (M : a ∈ s) (h1 : ∀ b s', a = b ∨ C s' → C (cons b s'))
(h2 : ∀ s, C s → C (think s)) : C s := by
apply Seq.mem_rec_on M
intro o s' h; cases' o with b
· apply h2
cases h
· contradiction
· assumption
· apply h1
apply Or.imp_left _ h
intro h
injection h
#align stream.wseq.mem_rec_on Stream'.WSeq.mem_rec_on
@[simp]
theorem mem_think (s : WSeq α) (a) : a ∈ think s ↔ a ∈ s := by
cases' s with f al
change (some (some a) ∈ some none::f) ↔ some (some a) ∈ f
constructor <;> intro h
· apply (Stream'.eq_or_mem_of_mem_cons h).resolve_left
intro
injections
· apply Stream'.mem_cons_of_mem _ h
#align stream.wseq.mem_think Stream'.WSeq.mem_think
theorem eq_or_mem_iff_mem {s : WSeq α} {a a' s'} :
some (a', s') ∈ destruct s → (a ∈ s ↔ a = a' ∨ a ∈ s') := by
generalize e : destruct s = c; intro h
revert s
apply Computation.memRecOn h <;> [skip; intro c IH] <;> intro s <;>
induction' s using WSeq.recOn with x s s <;>
intro m <;>
have := congr_arg Computation.destruct m <;>
simp at this
· cases' this with i1 i2
rw [i1, i2]
cases' s' with f al
dsimp only [cons, (· ∈ ·), WSeq.Mem, Seq.Mem, Seq.cons]
have h_a_eq_a' : a = a' ↔ some (some a) = some (some a') := by simp
rw [h_a_eq_a']
refine ⟨Stream'.eq_or_mem_of_mem_cons, fun o => ?_⟩
· cases' o with e m
· rw [e]
apply Stream'.mem_cons
· exact Stream'.mem_cons_of_mem _ m
· simp [IH this]
#align stream.wseq.eq_or_mem_iff_mem Stream'.WSeq.eq_or_mem_iff_mem
@[simp]
theorem mem_cons_iff (s : WSeq α) (b) {a} : a ∈ cons b s ↔ a = b ∨ a ∈ s :=
eq_or_mem_iff_mem <| by simp [ret_mem]
#align stream.wseq.mem_cons_iff Stream'.WSeq.mem_cons_iff
theorem mem_cons_of_mem {s : WSeq α} (b) {a} (h : a ∈ s) : a ∈ cons b s :=
(mem_cons_iff _ _).2 (Or.inr h)
#align stream.wseq.mem_cons_of_mem Stream'.WSeq.mem_cons_of_mem
theorem mem_cons (s : WSeq α) (a) : a ∈ cons a s :=
(mem_cons_iff _ _).2 (Or.inl rfl)
#align stream.wseq.mem_cons Stream'.WSeq.mem_cons
theorem mem_of_mem_tail {s : WSeq α} {a} : a ∈ tail s → a ∈ s := by
intro h; have := h; cases' h with n e; revert s; simp only [Stream'.get]
induction' n with n IH <;> intro s <;> induction' s using WSeq.recOn with x s s <;>
simp <;> intro m e <;>
injections
· exact Or.inr m
· exact Or.inr m
· apply IH m
rw [e]
cases tail s
rfl
#align stream.wseq.mem_of_mem_tail Stream'.WSeq.mem_of_mem_tail
theorem mem_of_mem_dropn {s : WSeq α} {a} : ∀ {n}, a ∈ drop s n → a ∈ s
| 0, h => h
| n + 1, h => @mem_of_mem_dropn s a n (mem_of_mem_tail h)
#align stream.wseq.mem_of_mem_dropn Stream'.WSeq.mem_of_mem_dropn
theorem get?_mem {s : WSeq α} {a n} : some a ∈ get? s n → a ∈ s := by
revert s; induction' n with n IH <;> intro s h
· -- Porting note: This line is required to infer metavariables in
-- `Computation.exists_of_mem_map`.
dsimp only [get?, head] at h
rcases Computation.exists_of_mem_map h with ⟨o, h1, h2⟩
cases' o with o
· injection h2
injection h2 with h'
cases' o with a' s'
exact (eq_or_mem_iff_mem h1).2 (Or.inl h'.symm)
· have := @IH (tail s)
rw [get?_tail] at this
exact mem_of_mem_tail (this h)
#align stream.wseq.nth_mem Stream'.WSeq.get?_mem
theorem exists_get?_of_mem {s : WSeq α} {a} (h : a ∈ s) : ∃ n, some a ∈ get? s n := by
apply mem_rec_on h
· intro a' s' h
cases' h with h h
· exists 0
simp only [get?, drop, head_cons]
rw [h]
apply ret_mem
· cases' h with n h
exists n + 1
-- porting note (#10745): was `simp [get?]`.
simpa [get?]
· intro s' h
cases' h with n h
exists n
simp only [get?, dropn_think, head_think]
apply think_mem h
#align stream.wseq.exists_nth_of_mem Stream'.WSeq.exists_get?_of_mem
theorem exists_dropn_of_mem {s : WSeq α} {a} (h : a ∈ s) :
∃ n s', some (a, s') ∈ destruct (drop s n) :=
let ⟨n, h⟩ := exists_get?_of_mem h
⟨n, by
rcases (head_terminates_iff _).1 ⟨⟨_, h⟩⟩ with ⟨⟨o, om⟩⟩
have := Computation.mem_unique (Computation.mem_map _ om) h
cases' o with o
· injection this
injection this with i
cases' o with a' s'
dsimp at i
rw [i] at om
exact ⟨_, om⟩⟩
#align stream.wseq.exists_dropn_of_mem Stream'.WSeq.exists_dropn_of_mem
theorem liftRel_dropn_destruct {R : α → β → Prop} {s t} (H : LiftRel R s t) :
∀ n, Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct (drop s n)) (destruct (drop t n))
| 0 => liftRel_destruct H
| n + 1 => by
simp only [LiftRelO, drop, Nat.add_eq, Nat.add_zero, destruct_tail, tail.aux]
apply liftRel_bind
· apply liftRel_dropn_destruct H n
exact fun {a b} o =>
match a, b, o with
| none, none, _ => by
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
| some (a, s), some (b, t), ⟨_, h2⟩ => by simpa [tail.aux] using liftRel_destruct h2
#align stream.wseq.lift_rel_dropn_destruct Stream'.WSeq.liftRel_dropn_destruct
theorem exists_of_liftRel_left {R : α → β → Prop} {s t} (H : LiftRel R s t) {a} (h : a ∈ s) :
∃ b, b ∈ t ∧ R a b := by
let ⟨n, h⟩ := exists_get?_of_mem h
-- Porting note: This line is required to infer metavariables in
-- `Computation.exists_of_mem_map`.
dsimp only [get?, head] at h
let ⟨some (_, s'), sd, rfl⟩ := Computation.exists_of_mem_map h
let ⟨some (b, t'), td, ⟨ab, _⟩⟩ := (liftRel_dropn_destruct H n).left sd
exact ⟨b, get?_mem (Computation.mem_map (Prod.fst.{v, v} <$> ·) td), ab⟩
#align stream.wseq.exists_of_lift_rel_left Stream'.WSeq.exists_of_liftRel_left
theorem exists_of_liftRel_right {R : α → β → Prop} {s t} (H : LiftRel R s t) {b} (h : b ∈ t) :
∃ a, a ∈ s ∧ R a b := by rw [← LiftRel.swap] at H; exact exists_of_liftRel_left H h
#align stream.wseq.exists_of_lift_rel_right Stream'.WSeq.exists_of_liftRel_right
theorem head_terminates_of_mem {s : WSeq α} {a} (h : a ∈ s) : Terminates (head s) :=
let ⟨_, h⟩ := exists_get?_of_mem h
head_terminates_of_get?_terminates ⟨⟨_, h⟩⟩
#align stream.wseq.head_terminates_of_mem Stream'.WSeq.head_terminates_of_mem
theorem of_mem_append {s₁ s₂ : WSeq α} {a : α} : a ∈ append s₁ s₂ → a ∈ s₁ ∨ a ∈ s₂ :=
Seq.of_mem_append
#align stream.wseq.of_mem_append Stream'.WSeq.of_mem_append
theorem mem_append_left {s₁ s₂ : WSeq α} {a : α} : a ∈ s₁ → a ∈ append s₁ s₂ :=
Seq.mem_append_left
#align stream.wseq.mem_append_left Stream'.WSeq.mem_append_left
theorem exists_of_mem_map {f} {b : β} : ∀ {s : WSeq α}, b ∈ map f s → ∃ a, a ∈ s ∧ f a = b
| ⟨g, al⟩, h => by
let ⟨o, om, oe⟩ := Seq.exists_of_mem_map h
cases' o with a
· injection oe
injection oe with h'
exact ⟨a, om, h'⟩
#align stream.wseq.exists_of_mem_map Stream'.WSeq.exists_of_mem_map
@[simp]
theorem liftRel_nil (R : α → β → Prop) : LiftRel R nil nil := by
rw [liftRel_destruct_iff]
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
#align stream.wseq.lift_rel_nil Stream'.WSeq.liftRel_nil
@[simp]
theorem liftRel_cons (R : α → β → Prop) (a b s t) :
LiftRel R (cons a s) (cons b t) ↔ R a b ∧ LiftRel R s t := by
rw [liftRel_destruct_iff]
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
#align stream.wseq.lift_rel_cons Stream'.WSeq.liftRel_cons
@[simp]
theorem liftRel_think_left (R : α → β → Prop) (s t) : LiftRel R (think s) t ↔ LiftRel R s t := by
rw [liftRel_destruct_iff, liftRel_destruct_iff]; simp
#align stream.wseq.lift_rel_think_left Stream'.WSeq.liftRel_think_left
@[simp]
theorem liftRel_think_right (R : α → β → Prop) (s t) : LiftRel R s (think t) ↔ LiftRel R s t := by
rw [liftRel_destruct_iff, liftRel_destruct_iff]; simp
#align stream.wseq.lift_rel_think_right Stream'.WSeq.liftRel_think_right
theorem cons_congr {s t : WSeq α} (a : α) (h : s ~ʷ t) : cons a s ~ʷ cons a t := by
unfold Equiv; simpa using h
#align stream.wseq.cons_congr Stream'.WSeq.cons_congr
theorem think_equiv (s : WSeq α) : think s ~ʷ s := by unfold Equiv; simpa using Equiv.refl _
#align stream.wseq.think_equiv Stream'.WSeq.think_equiv
theorem think_congr {s t : WSeq α} (h : s ~ʷ t) : think s ~ʷ think t := by
unfold Equiv; simpa using h
#align stream.wseq.think_congr Stream'.WSeq.think_congr
| Mathlib/Data/Seq/WSeq.lean | 1,126 | 1,144 | theorem head_congr : ∀ {s t : WSeq α}, s ~ʷ t → head s ~ head t := by |
suffices ∀ {s t : WSeq α}, s ~ʷ t → ∀ {o}, o ∈ head s → o ∈ head t from fun s t h o =>
⟨this h, this h.symm⟩
intro s t h o ho
rcases @Computation.exists_of_mem_map _ _ _ _ (destruct s) ho with ⟨ds, dsm, dse⟩
rw [← dse]
cases' destruct_congr h with l r
rcases l dsm with ⟨dt, dtm, dst⟩
cases' ds with a <;> cases' dt with b
· apply Computation.mem_map _ dtm
· cases b
cases dst
· cases a
cases dst
· cases' a with a s'
cases' b with b t'
rw [dst.left]
exact @Computation.mem_map _ _ (@Functor.map _ _ (α × WSeq α) _ Prod.fst)
(some (b, t')) (destruct t) dtm
|
/-
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}
| Mathlib/MeasureTheory/Measure/VectorMeasure.lean | 146 | 178 | 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))
|
/-
Copyright (c) 2022 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.Orientation
import Mathlib.Data.Complex.Orientation
import Mathlib.Tactic.LinearCombination
#align_import analysis.inner_product_space.two_dim from "leanprover-community/mathlib"@"cd8fafa2fac98e1a67097e8a91ad9901cfde48af"
/-!
# Oriented two-dimensional real inner product spaces
This file defines constructions specific to the geometry of an oriented two-dimensional real inner
product space `E`.
## Main declarations
* `Orientation.areaForm`: an antisymmetric bilinear form `E →ₗ[ℝ] E →ₗ[ℝ] ℝ` (usual notation `ω`).
Morally, when `ω` is evaluated on two vectors, it gives the oriented area of the parallelogram
they span. (But mathlib does not yet have a construction of oriented area, and in fact the
construction of oriented area should pass through `ω`.)
* `Orientation.rightAngleRotation`: an isometric automorphism `E ≃ₗᵢ[ℝ] E` (usual notation `J`).
This automorphism squares to -1. In a later file, rotations (`Orientation.rotation`) are defined,
in such a way that this automorphism is equal to rotation by 90 degrees.
* `Orientation.basisRightAngleRotation`: for a nonzero vector `x` in `E`, the basis `![x, J x]`
for `E`.
* `Orientation.kahler`: a complex-valued real-bilinear map `E →ₗ[ℝ] E →ₗ[ℝ] ℂ`. Its real part is the
inner product and its imaginary part is `Orientation.areaForm`. For vectors `x` and `y` in `E`,
the complex number `o.kahler x y` has modulus `‖x‖ * ‖y‖`. In a later file, oriented angles
(`Orientation.oangle`) are defined, in such a way that the argument of `o.kahler x y` is the
oriented angle from `x` to `y`.
## Main results
* `Orientation.rightAngleRotation_rightAngleRotation`: the identity `J (J x) = - x`
* `Orientation.nonneg_inner_and_areaForm_eq_zero_iff_sameRay`: `x`, `y` are in the same ray, if
and only if `0 ≤ ⟪x, y⟫` and `ω x y = 0`
* `Orientation.kahler_mul`: the identity `o.kahler x a * o.kahler a y = ‖a‖ ^ 2 * o.kahler x y`
* `Complex.areaForm`, `Complex.rightAngleRotation`, `Complex.kahler`: the concrete
interpretations of `areaForm`, `rightAngleRotation`, `kahler` for the oriented real inner
product space `ℂ`
* `Orientation.areaForm_map_complex`, `Orientation.rightAngleRotation_map_complex`,
`Orientation.kahler_map_complex`: given an orientation-preserving isometry from `E` to `ℂ`,
expressions for `areaForm`, `rightAngleRotation`, `kahler` as the pullback of their concrete
interpretations on `ℂ`
## Implementation notes
Notation `ω` for `Orientation.areaForm` and `J` for `Orientation.rightAngleRotation` should be
defined locally in each file which uses them, since otherwise one would need a more cumbersome
notation which mentions the orientation explicitly (something like `ω[o]`). Write
```
local notation "ω" => o.areaForm
local notation "J" => o.rightAngleRotation
```
-/
noncomputable section
open scoped RealInnerProductSpace ComplexConjugate
open FiniteDimensional
lemma FiniteDimensional.of_fact_finrank_eq_two {K V : Type*} [DivisionRing K]
[AddCommGroup V] [Module K V] [Fact (finrank K V = 2)] : FiniteDimensional K V :=
.of_fact_finrank_eq_succ 1
attribute [local instance] FiniteDimensional.of_fact_finrank_eq_two
@[deprecated (since := "2024-02-02")]
alias FiniteDimensional.finiteDimensional_of_fact_finrank_eq_two :=
FiniteDimensional.of_fact_finrank_eq_two
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [Fact (finrank ℝ E = 2)]
(o : Orientation ℝ E (Fin 2))
namespace Orientation
/-- An antisymmetric bilinear form on an oriented real inner product space of dimension 2 (usual
notation `ω`). When evaluated on two vectors, it gives the oriented area of the parallelogram they
span. -/
irreducible_def areaForm : E →ₗ[ℝ] E →ₗ[ℝ] ℝ := by
let z : E [⋀^Fin 0]→ₗ[ℝ] ℝ ≃ₗ[ℝ] ℝ :=
AlternatingMap.constLinearEquivOfIsEmpty.symm
let y : E [⋀^Fin 1]→ₗ[ℝ] ℝ →ₗ[ℝ] E →ₗ[ℝ] ℝ :=
LinearMap.llcomp ℝ E (E [⋀^Fin 0]→ₗ[ℝ] ℝ) ℝ z ∘ₗ AlternatingMap.curryLeftLinearMap
exact y ∘ₗ AlternatingMap.curryLeftLinearMap (R' := ℝ) o.volumeForm
#align orientation.area_form Orientation.areaForm
local notation "ω" => o.areaForm
theorem areaForm_to_volumeForm (x y : E) : ω x y = o.volumeForm ![x, y] := by simp [areaForm]
#align orientation.area_form_to_volume_form Orientation.areaForm_to_volumeForm
@[simp]
theorem areaForm_apply_self (x : E) : ω x x = 0 := by
rw [areaForm_to_volumeForm]
refine o.volumeForm.map_eq_zero_of_eq ![x, x] ?_ (?_ : (0 : Fin 2) ≠ 1)
· simp
· norm_num
#align orientation.area_form_apply_self Orientation.areaForm_apply_self
theorem areaForm_swap (x y : E) : ω x y = -ω y x := by
simp only [areaForm_to_volumeForm]
convert o.volumeForm.map_swap ![y, x] (_ : (0 : Fin 2) ≠ 1)
· ext i
fin_cases i <;> rfl
· norm_num
#align orientation.area_form_swap Orientation.areaForm_swap
@[simp]
theorem areaForm_neg_orientation : (-o).areaForm = -o.areaForm := by
ext x y
simp [areaForm_to_volumeForm]
#align orientation.area_form_neg_orientation Orientation.areaForm_neg_orientation
/-- Continuous linear map version of `Orientation.areaForm`, useful for calculus. -/
def areaForm' : E →L[ℝ] E →L[ℝ] ℝ :=
LinearMap.toContinuousLinearMap
(↑(LinearMap.toContinuousLinearMap : (E →ₗ[ℝ] ℝ) ≃ₗ[ℝ] E →L[ℝ] ℝ) ∘ₗ o.areaForm)
#align orientation.area_form' Orientation.areaForm'
@[simp]
theorem areaForm'_apply (x : E) :
o.areaForm' x = LinearMap.toContinuousLinearMap (o.areaForm x) :=
rfl
#align orientation.area_form'_apply Orientation.areaForm'_apply
theorem abs_areaForm_le (x y : E) : |ω x y| ≤ ‖x‖ * ‖y‖ := by
simpa [areaForm_to_volumeForm, Fin.prod_univ_succ] using o.abs_volumeForm_apply_le ![x, y]
#align orientation.abs_area_form_le Orientation.abs_areaForm_le
theorem areaForm_le (x y : E) : ω x y ≤ ‖x‖ * ‖y‖ := by
simpa [areaForm_to_volumeForm, Fin.prod_univ_succ] using o.volumeForm_apply_le ![x, y]
#align orientation.area_form_le Orientation.areaForm_le
theorem abs_areaForm_of_orthogonal {x y : E} (h : ⟪x, y⟫ = 0) : |ω x y| = ‖x‖ * ‖y‖ := by
rw [o.areaForm_to_volumeForm, o.abs_volumeForm_apply_of_pairwise_orthogonal]
· simp [Fin.prod_univ_succ]
intro i j hij
fin_cases i <;> fin_cases j
· simp_all
· simpa using h
· simpa [real_inner_comm] using h
· simp_all
#align orientation.abs_area_form_of_orthogonal Orientation.abs_areaForm_of_orthogonal
theorem areaForm_map {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[hF : Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) (x y : F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).areaForm x y =
o.areaForm (φ.symm x) (φ.symm y) := by
have : φ.symm ∘ ![x, y] = ![φ.symm x, φ.symm y] := by
ext i
fin_cases i <;> rfl
simp [areaForm_to_volumeForm, volumeForm_map, this]
#align orientation.area_form_map Orientation.areaForm_map
/-- The area form is invariant under pullback by a positively-oriented isometric automorphism. -/
theorem areaForm_comp_linearIsometryEquiv (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) (x y : E) :
o.areaForm (φ x) (φ y) = o.areaForm x y := by
convert o.areaForm_map φ (φ x) (φ y)
· symm
rwa [← o.map_eq_iff_det_pos φ.toLinearEquiv] at hφ
rw [@Fact.out (finrank ℝ E = 2), Fintype.card_fin]
· simp
· simp
#align orientation.area_form_comp_linear_isometry_equiv Orientation.areaForm_comp_linearIsometryEquiv
/-- Auxiliary construction for `Orientation.rightAngleRotation`, rotation by 90 degrees in an
oriented real inner product space of dimension 2. -/
irreducible_def rightAngleRotationAux₁ : E →ₗ[ℝ] E :=
let to_dual : E ≃ₗ[ℝ] E →ₗ[ℝ] ℝ :=
(InnerProductSpace.toDual ℝ E).toLinearEquiv ≪≫ₗ LinearMap.toContinuousLinearMap.symm
↑to_dual.symm ∘ₗ ω
#align orientation.right_angle_rotation_aux₁ Orientation.rightAngleRotationAux₁
@[simp]
theorem inner_rightAngleRotationAux₁_left (x y : E) : ⟪o.rightAngleRotationAux₁ x, y⟫ = ω x y := by
-- Porting note: split `simp only` for greater proof control
simp only [rightAngleRotationAux₁, LinearEquiv.trans_symm, LinearIsometryEquiv.toLinearEquiv_symm,
LinearMap.coe_comp, LinearEquiv.coe_coe, Function.comp_apply, LinearEquiv.trans_apply,
LinearIsometryEquiv.coe_toLinearEquiv]
rw [InnerProductSpace.toDual_symm_apply]
norm_cast
#align orientation.inner_right_angle_rotation_aux₁_left Orientation.inner_rightAngleRotationAux₁_left
@[simp]
theorem inner_rightAngleRotationAux₁_right (x y : E) :
⟪x, o.rightAngleRotationAux₁ y⟫ = -ω x y := by
rw [real_inner_comm]
simp [o.areaForm_swap y x]
#align orientation.inner_right_angle_rotation_aux₁_right Orientation.inner_rightAngleRotationAux₁_right
/-- Auxiliary construction for `Orientation.rightAngleRotation`, rotation by 90 degrees in an
oriented real inner product space of dimension 2. -/
def rightAngleRotationAux₂ : E →ₗᵢ[ℝ] E :=
{ o.rightAngleRotationAux₁ with
norm_map' := fun x => by
dsimp
refine le_antisymm ?_ ?_
· cases' eq_or_lt_of_le (norm_nonneg (o.rightAngleRotationAux₁ x)) with h h
· rw [← h]
positivity
refine le_of_mul_le_mul_right ?_ h
rw [← real_inner_self_eq_norm_mul_norm, o.inner_rightAngleRotationAux₁_left]
exact o.areaForm_le x (o.rightAngleRotationAux₁ x)
· let K : Submodule ℝ E := ℝ ∙ x
have : Nontrivial Kᗮ := by
apply @FiniteDimensional.nontrivial_of_finrank_pos ℝ
have : finrank ℝ K ≤ Finset.card {x} := by
rw [← Set.toFinset_singleton]
exact finrank_span_le_card ({x} : Set E)
have : Finset.card {x} = 1 := Finset.card_singleton x
have : finrank ℝ K + finrank ℝ Kᗮ = finrank ℝ E := K.finrank_add_finrank_orthogonal
have : finrank ℝ E = 2 := Fact.out
linarith
obtain ⟨w, hw₀⟩ : ∃ w : Kᗮ, w ≠ 0 := exists_ne 0
have hw' : ⟪x, (w : E)⟫ = 0 := Submodule.mem_orthogonal_singleton_iff_inner_right.mp w.2
have hw : (w : E) ≠ 0 := fun h => hw₀ (Submodule.coe_eq_zero.mp h)
refine le_of_mul_le_mul_right ?_ (by rwa [norm_pos_iff] : 0 < ‖(w : E)‖)
rw [← o.abs_areaForm_of_orthogonal hw']
rw [← o.inner_rightAngleRotationAux₁_left x w]
exact abs_real_inner_le_norm (o.rightAngleRotationAux₁ x) w }
#align orientation.right_angle_rotation_aux₂ Orientation.rightAngleRotationAux₂
@[simp]
theorem rightAngleRotationAux₁_rightAngleRotationAux₁ (x : E) :
o.rightAngleRotationAux₁ (o.rightAngleRotationAux₁ x) = -x := by
apply ext_inner_left ℝ
intro y
have : ⟪o.rightAngleRotationAux₁ y, o.rightAngleRotationAux₁ x⟫ = ⟪y, x⟫ :=
LinearIsometry.inner_map_map o.rightAngleRotationAux₂ y x
rw [o.inner_rightAngleRotationAux₁_right, ← o.inner_rightAngleRotationAux₁_left, this,
inner_neg_right]
#align orientation.right_angle_rotation_aux₁_right_angle_rotation_aux₁ Orientation.rightAngleRotationAux₁_rightAngleRotationAux₁
/-- An isometric automorphism of an oriented real inner product space of dimension 2 (usual notation
`J`). This automorphism squares to -1. We will define rotations in such a way that this
automorphism is equal to rotation by 90 degrees. -/
irreducible_def rightAngleRotation : E ≃ₗᵢ[ℝ] E :=
LinearIsometryEquiv.ofLinearIsometry o.rightAngleRotationAux₂ (-o.rightAngleRotationAux₁)
(by ext; simp [rightAngleRotationAux₂]) (by ext; simp [rightAngleRotationAux₂])
#align orientation.right_angle_rotation Orientation.rightAngleRotation
local notation "J" => o.rightAngleRotation
@[simp]
theorem inner_rightAngleRotation_left (x y : E) : ⟪J x, y⟫ = ω x y := by
rw [rightAngleRotation]
exact o.inner_rightAngleRotationAux₁_left x y
#align orientation.inner_right_angle_rotation_left Orientation.inner_rightAngleRotation_left
@[simp]
theorem inner_rightAngleRotation_right (x y : E) : ⟪x, J y⟫ = -ω x y := by
rw [rightAngleRotation]
exact o.inner_rightAngleRotationAux₁_right x y
#align orientation.inner_right_angle_rotation_right Orientation.inner_rightAngleRotation_right
@[simp]
theorem rightAngleRotation_rightAngleRotation (x : E) : J (J x) = -x := by
rw [rightAngleRotation]
exact o.rightAngleRotationAux₁_rightAngleRotationAux₁ x
#align orientation.right_angle_rotation_right_angle_rotation Orientation.rightAngleRotation_rightAngleRotation
@[simp]
| Mathlib/Analysis/InnerProductSpace/TwoDim.lean | 280 | 283 | theorem rightAngleRotation_symm :
LinearIsometryEquiv.symm J = LinearIsometryEquiv.trans J (LinearIsometryEquiv.neg ℝ) := by |
rw [rightAngleRotation]
exact LinearIsometryEquiv.toLinearIsometry_injective rfl
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Floris van Doorn
-/
import Mathlib.Data.Fintype.BigOperators
import Mathlib.Data.Finsupp.Defs
import Mathlib.Data.Nat.Cast.Order
import Mathlib.Data.Set.Countable
import Mathlib.Logic.Small.Set
import Mathlib.Order.SuccPred.CompleteLinearOrder
import Mathlib.SetTheory.Cardinal.SchroederBernstein
#align_import set_theory.cardinal.basic from "leanprover-community/mathlib"@"3ff3f2d6a3118b8711063de7111a0d77a53219a8"
/-!
# Cardinal Numbers
We define cardinal numbers as a quotient of types under the equivalence relation of equinumerity.
## Main definitions
* `Cardinal` is the type of cardinal numbers (in a given universe).
* `Cardinal.mk α` or `#α` is the cardinality of `α`. The notation `#` lives in the locale
`Cardinal`.
* Addition `c₁ + c₂` is defined by `Cardinal.add_def α β : #α + #β = #(α ⊕ β)`.
* Multiplication `c₁ * c₂` is defined by `Cardinal.mul_def : #α * #β = #(α × β)`.
* The order `c₁ ≤ c₂` is defined by `Cardinal.le_def α β : #α ≤ #β ↔ Nonempty (α ↪ β)`.
* Exponentiation `c₁ ^ c₂` is defined by `Cardinal.power_def α β : #α ^ #β = #(β → α)`.
* `Cardinal.isLimit c` means that `c` is a (weak) limit cardinal: `c ≠ 0 ∧ ∀ x < c, succ x < c`.
* `Cardinal.aleph0` or `ℵ₀` is the cardinality of `ℕ`. This definition is universe polymorphic:
`Cardinal.aleph0.{u} : Cardinal.{u}` (contrast with `ℕ : Type`, which lives in a specific
universe). In some cases the universe level has to be given explicitly.
* `Cardinal.sum` is the sum of an indexed family of cardinals, i.e. the cardinality of the
corresponding sigma type.
* `Cardinal.prod` is the product of an indexed family of cardinals, i.e. the cardinality of the
corresponding pi type.
* `Cardinal.powerlt a b` or `a ^< b` is defined as the supremum of `a ^ c` for `c < b`.
## Main instances
* Cardinals form a `CanonicallyOrderedCommSemiring` with the aforementioned sum and product.
* Cardinals form a `SuccOrder`. Use `Order.succ c` for the smallest cardinal greater than `c`.
* The less than relation on cardinals forms a well-order.
* Cardinals form a `ConditionallyCompleteLinearOrderBot`. Bounded sets for cardinals in universe
`u` are precisely the sets indexed by some type in universe `u`, see
`Cardinal.bddAbove_iff_small`. One can use `sSup` for the cardinal supremum, and `sInf` for the
minimum of a set of cardinals.
## Main Statements
* Cantor's theorem: `Cardinal.cantor c : c < 2 ^ c`.
* König's theorem: `Cardinal.sum_lt_prod`
## Implementation notes
* There is a type of cardinal numbers in every universe level:
`Cardinal.{u} : Type (u + 1)` is the quotient of types in `Type u`.
The operation `Cardinal.lift` lifts cardinal numbers to a higher level.
* Cardinal arithmetic specifically for infinite cardinals (like `κ * κ = κ`) is in the file
`Mathlib/SetTheory/Cardinal/Ordinal.lean`.
* There is an instance `Pow Cardinal`, but this will only fire if Lean already knows that both
the base and the exponent live in the same universe. As a workaround, you can add
```
local infixr:80 " ^' " => @HPow.hPow Cardinal Cardinal Cardinal _
```
to a file. This notation will work even if Lean doesn't know yet that the base and the exponent
live in the same universe (but no exponents in other types can be used).
(Porting note: This last point might need to be updated.)
## References
* <https://en.wikipedia.org/wiki/Cardinal_number>
## Tags
cardinal number, cardinal arithmetic, cardinal exponentiation, aleph,
Cantor's theorem, König's theorem, Konig's theorem
-/
assert_not_exists Field
assert_not_exists Module
open scoped Classical
open Function Set Order
noncomputable section
universe u v w
variable {α β : Type u}
/-- The equivalence relation on types given by equivalence (bijective correspondence) of types.
Quotienting by this equivalence relation gives the cardinal numbers.
-/
instance Cardinal.isEquivalent : Setoid (Type u) where
r α β := Nonempty (α ≃ β)
iseqv := ⟨
fun α => ⟨Equiv.refl α⟩,
fun ⟨e⟩ => ⟨e.symm⟩,
fun ⟨e₁⟩ ⟨e₂⟩ => ⟨e₁.trans e₂⟩⟩
#align cardinal.is_equivalent Cardinal.isEquivalent
/-- `Cardinal.{u}` is the type of cardinal numbers in `Type u`,
defined as the quotient of `Type u` by existence of an equivalence
(a bijection with explicit inverse). -/
@[pp_with_univ]
def Cardinal : Type (u + 1) :=
Quotient Cardinal.isEquivalent
#align cardinal Cardinal
namespace Cardinal
/-- The cardinal number of a type -/
def mk : Type u → Cardinal :=
Quotient.mk'
#align cardinal.mk Cardinal.mk
@[inherit_doc]
scoped prefix:max "#" => Cardinal.mk
instance canLiftCardinalType : CanLift Cardinal.{u} (Type u) mk fun _ => True :=
⟨fun c _ => Quot.inductionOn c fun α => ⟨α, rfl⟩⟩
#align cardinal.can_lift_cardinal_Type Cardinal.canLiftCardinalType
@[elab_as_elim]
theorem inductionOn {p : Cardinal → Prop} (c : Cardinal) (h : ∀ α, p #α) : p c :=
Quotient.inductionOn c h
#align cardinal.induction_on Cardinal.inductionOn
@[elab_as_elim]
theorem inductionOn₂ {p : Cardinal → Cardinal → Prop} (c₁ : Cardinal) (c₂ : Cardinal)
(h : ∀ α β, p #α #β) : p c₁ c₂ :=
Quotient.inductionOn₂ c₁ c₂ h
#align cardinal.induction_on₂ Cardinal.inductionOn₂
@[elab_as_elim]
theorem inductionOn₃ {p : Cardinal → Cardinal → Cardinal → Prop} (c₁ : Cardinal) (c₂ : Cardinal)
(c₃ : Cardinal) (h : ∀ α β γ, p #α #β #γ) : p c₁ c₂ c₃ :=
Quotient.inductionOn₃ c₁ c₂ c₃ h
#align cardinal.induction_on₃ Cardinal.inductionOn₃
protected theorem eq : #α = #β ↔ Nonempty (α ≃ β) :=
Quotient.eq'
#align cardinal.eq Cardinal.eq
@[simp]
theorem mk'_def (α : Type u) : @Eq Cardinal ⟦α⟧ #α :=
rfl
#align cardinal.mk_def Cardinal.mk'_def
@[simp]
theorem mk_out (c : Cardinal) : #c.out = c :=
Quotient.out_eq _
#align cardinal.mk_out Cardinal.mk_out
/-- The representative of the cardinal of a type is equivalent to the original type. -/
def outMkEquiv {α : Type v} : (#α).out ≃ α :=
Nonempty.some <| Cardinal.eq.mp (by simp)
#align cardinal.out_mk_equiv Cardinal.outMkEquiv
theorem mk_congr (e : α ≃ β) : #α = #β :=
Quot.sound ⟨e⟩
#align cardinal.mk_congr Cardinal.mk_congr
alias _root_.Equiv.cardinal_eq := mk_congr
#align equiv.cardinal_eq Equiv.cardinal_eq
/-- Lift a function between `Type*`s to a function between `Cardinal`s. -/
def map (f : Type u → Type v) (hf : ∀ α β, α ≃ β → f α ≃ f β) : Cardinal.{u} → Cardinal.{v} :=
Quotient.map f fun α β ⟨e⟩ => ⟨hf α β e⟩
#align cardinal.map Cardinal.map
@[simp]
theorem map_mk (f : Type u → Type v) (hf : ∀ α β, α ≃ β → f α ≃ f β) (α : Type u) :
map f hf #α = #(f α) :=
rfl
#align cardinal.map_mk Cardinal.map_mk
/-- Lift a binary operation `Type* → Type* → Type*` to a binary operation on `Cardinal`s. -/
def map₂ (f : Type u → Type v → Type w) (hf : ∀ α β γ δ, α ≃ β → γ ≃ δ → f α γ ≃ f β δ) :
Cardinal.{u} → Cardinal.{v} → Cardinal.{w} :=
Quotient.map₂ f fun α β ⟨e₁⟩ γ δ ⟨e₂⟩ => ⟨hf α β γ δ e₁ e₂⟩
#align cardinal.map₂ Cardinal.map₂
/-- The universe lift operation on cardinals. You can specify the universes explicitly with
`lift.{u v} : Cardinal.{v} → Cardinal.{max v u}` -/
@[pp_with_univ]
def lift (c : Cardinal.{v}) : Cardinal.{max v u} :=
map ULift.{u, v} (fun _ _ e => Equiv.ulift.trans <| e.trans Equiv.ulift.symm) c
#align cardinal.lift Cardinal.lift
@[simp]
theorem mk_uLift (α) : #(ULift.{v, u} α) = lift.{v} #α :=
rfl
#align cardinal.mk_ulift Cardinal.mk_uLift
-- Porting note: simpNF is not happy with universe levels, but this is needed as simp lemma
-- further down in this file
/-- `lift.{max u v, u}` equals `lift.{v, u}`. -/
@[simp, nolint simpNF]
theorem lift_umax : lift.{max u v, u} = lift.{v, u} :=
funext fun a => inductionOn a fun _ => (Equiv.ulift.trans Equiv.ulift.symm).cardinal_eq
#align cardinal.lift_umax Cardinal.lift_umax
-- Porting note: simpNF is not happy with universe levels, but this is needed as simp lemma
-- further down in this file
/-- `lift.{max v u, u}` equals `lift.{v, u}`. -/
@[simp, nolint simpNF]
theorem lift_umax' : lift.{max v u, u} = lift.{v, u} :=
lift_umax
#align cardinal.lift_umax' Cardinal.lift_umax'
-- Porting note: simpNF is not happy with universe levels, but this is needed as simp lemma
-- further down in this file
/-- A cardinal lifted to a lower or equal universe equals itself. -/
@[simp, nolint simpNF]
theorem lift_id' (a : Cardinal.{max u v}) : lift.{u} a = a :=
inductionOn a fun _ => mk_congr Equiv.ulift
#align cardinal.lift_id' Cardinal.lift_id'
/-- A cardinal lifted to the same universe equals itself. -/
@[simp]
theorem lift_id (a : Cardinal) : lift.{u, u} a = a :=
lift_id'.{u, u} a
#align cardinal.lift_id Cardinal.lift_id
/-- A cardinal lifted to the zero universe equals itself. -/
-- porting note (#10618): simp can prove this
-- @[simp]
theorem lift_uzero (a : Cardinal.{u}) : lift.{0} a = a :=
lift_id'.{0, u} a
#align cardinal.lift_uzero Cardinal.lift_uzero
@[simp]
theorem lift_lift.{u_1} (a : Cardinal.{u_1}) : lift.{w} (lift.{v} a) = lift.{max v w} a :=
inductionOn a fun _ => (Equiv.ulift.trans <| Equiv.ulift.trans Equiv.ulift.symm).cardinal_eq
#align cardinal.lift_lift Cardinal.lift_lift
/-- We define the order on cardinal numbers by `#α ≤ #β` if and only if
there exists an embedding (injective function) from α to β. -/
instance : LE Cardinal.{u} :=
⟨fun q₁ q₂ =>
Quotient.liftOn₂ q₁ q₂ (fun α β => Nonempty <| α ↪ β) fun _ _ _ _ ⟨e₁⟩ ⟨e₂⟩ =>
propext ⟨fun ⟨e⟩ => ⟨e.congr e₁ e₂⟩, fun ⟨e⟩ => ⟨e.congr e₁.symm e₂.symm⟩⟩⟩
instance partialOrder : PartialOrder Cardinal.{u} where
le := (· ≤ ·)
le_refl := by
rintro ⟨α⟩
exact ⟨Embedding.refl _⟩
le_trans := by
rintro ⟨α⟩ ⟨β⟩ ⟨γ⟩ ⟨e₁⟩ ⟨e₂⟩
exact ⟨e₁.trans e₂⟩
le_antisymm := by
rintro ⟨α⟩ ⟨β⟩ ⟨e₁⟩ ⟨e₂⟩
exact Quotient.sound (e₁.antisymm e₂)
instance linearOrder : LinearOrder Cardinal.{u} :=
{ Cardinal.partialOrder with
le_total := by
rintro ⟨α⟩ ⟨β⟩
apply Embedding.total
decidableLE := Classical.decRel _ }
theorem le_def (α β : Type u) : #α ≤ #β ↔ Nonempty (α ↪ β) :=
Iff.rfl
#align cardinal.le_def Cardinal.le_def
theorem mk_le_of_injective {α β : Type u} {f : α → β} (hf : Injective f) : #α ≤ #β :=
⟨⟨f, hf⟩⟩
#align cardinal.mk_le_of_injective Cardinal.mk_le_of_injective
theorem _root_.Function.Embedding.cardinal_le {α β : Type u} (f : α ↪ β) : #α ≤ #β :=
⟨f⟩
#align function.embedding.cardinal_le Function.Embedding.cardinal_le
theorem mk_le_of_surjective {α β : Type u} {f : α → β} (hf : Surjective f) : #β ≤ #α :=
⟨Embedding.ofSurjective f hf⟩
#align cardinal.mk_le_of_surjective Cardinal.mk_le_of_surjective
theorem le_mk_iff_exists_set {c : Cardinal} {α : Type u} : c ≤ #α ↔ ∃ p : Set α, #p = c :=
⟨inductionOn c fun _ ⟨⟨f, hf⟩⟩ => ⟨Set.range f, (Equiv.ofInjective f hf).cardinal_eq.symm⟩,
fun ⟨_, e⟩ => e ▸ ⟨⟨Subtype.val, fun _ _ => Subtype.eq⟩⟩⟩
#align cardinal.le_mk_iff_exists_set Cardinal.le_mk_iff_exists_set
theorem mk_subtype_le {α : Type u} (p : α → Prop) : #(Subtype p) ≤ #α :=
⟨Embedding.subtype p⟩
#align cardinal.mk_subtype_le Cardinal.mk_subtype_le
theorem mk_set_le (s : Set α) : #s ≤ #α :=
mk_subtype_le s
#align cardinal.mk_set_le Cardinal.mk_set_le
@[simp]
lemma mk_preimage_down {s : Set α} : #(ULift.down.{v} ⁻¹' s) = lift.{v} (#s) := by
rw [← mk_uLift, Cardinal.eq]
constructor
let f : ULift.down ⁻¹' s → ULift s := fun x ↦ ULift.up (restrictPreimage s ULift.down x)
have : Function.Bijective f :=
ULift.up_bijective.comp (restrictPreimage_bijective _ (ULift.down_bijective))
exact Equiv.ofBijective f this
| Mathlib/SetTheory/Cardinal/Basic.lean | 304 | 307 | theorem out_embedding {c c' : Cardinal} : c ≤ c' ↔ Nonempty (c.out ↪ c'.out) := by |
trans
· rw [← Quotient.out_eq c, ← Quotient.out_eq c']
· rw [mk'_def, mk'_def, le_def]
|
/-
Copyright (c) 2023 Scott Carnahan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Carnahan
-/
import Mathlib.Algebra.Group.NatPowAssoc
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Induction
import Mathlib.Algebra.Polynomial.Eval
/-!
# Scalar-multiple polynomial evaluation
This file defines polynomial evaluation via scalar multiplication. Our polynomials have
coefficients in a semiring `R`, and we evaluate at a weak form of `R`-algebra, namely an additive
commutative monoid with an action of `R` and a notion of natural number power. This
is a generalization of `Algebra.Polynomial.Eval`.
## Main definitions
* `Polynomial.smeval`: function for evaluating a polynomial with coefficients in a `Semiring`
`R` at an element `x` of an `AddCommMonoid` `S` that has natural number powers and an `R`-action.
* `smeval.linearMap`: the `smeval` function as an `R`-linear map, when `S` is an `R`-module.
* `smeval.algebraMap`: the `smeval` function as an `R`-algebra map, when `S` is an `R`-algebra.
## Main results
* `smeval_monomial`: monomials evaluate as we expect.
* `smeval_add`, `smeval_smul`: linearity of evaluation, given an `R`-module.
* `smeval_mul`, `smeval_comp`: multiplicativity of evaluation, given power-associativity.
* `eval₂_eq_smeval`, `leval_eq_smeval.linearMap`, `aeval = smeval.algebraMap`, etc.: comparisons
## To do
* `smeval_neg` and `smeval_intCast` for `R` a ring and `S` an `AddCommGroup`.
* Nonunital evaluation for polynomials with vanishing constant term for `Pow S ℕ+` (different file?)
-/
namespace Polynomial
section MulActionWithZero
variable {R : Type*} [Semiring R] (r : R) (p : R[X]) {S : Type*} [AddCommMonoid S] [Pow S ℕ]
[MulActionWithZero R S] (x : S)
/-- Scalar multiplication together with taking a natural number power. -/
def smul_pow : ℕ → R → S := fun n r => r • x^n
/-- Evaluate a polynomial `p` in the scalar semiring `R` at an element `x` in the target `S` using
scalar multiple `R`-action. -/
irreducible_def smeval : S := p.sum (smul_pow x)
theorem smeval_eq_sum : p.smeval x = p.sum (smul_pow x) := by rw [smeval_def]
@[simp]
theorem smeval_C : (C r).smeval x = r • x ^ 0 := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_C_index]
@[simp]
theorem smeval_monomial (n : ℕ) :
(monomial n r).smeval x = r • x ^ n := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_monomial_index]
theorem eval_eq_smeval : p.eval r = p.smeval r := by
rw [eval_eq_sum, smeval_eq_sum]
rfl
theorem eval₂_eq_smeval (R : Type*) [Semiring R] {S : Type*} [Semiring S] (f : R →+* S) (p : R[X])
(x: S) : letI : Module R S := RingHom.toModule f
p.eval₂ f x = p.smeval x := by
letI : Module R S := RingHom.toModule f
rw [smeval_eq_sum, eval₂_eq_sum]
rfl
variable (R)
@[simp]
theorem smeval_zero : (0 : R[X]).smeval x = 0 := by
simp only [smeval_eq_sum, smul_pow, sum_zero_index]
@[simp]
theorem smeval_one : (1 : R[X]).smeval x = 1 • x ^ 0 := by
rw [← C_1, smeval_C]
simp only [Nat.cast_one, one_smul]
@[simp]
theorem smeval_X :
(X : R[X]).smeval x = x ^ 1 := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_X_index, one_smul]
@[simp]
theorem smeval_X_pow {n : ℕ} :
(X ^ n : R[X]).smeval x = x ^ n := by
simp only [smeval_eq_sum, smul_pow, X_pow_eq_monomial, zero_smul, sum_monomial_index, one_smul]
end MulActionWithZero
section Module
variable (R : Type*) [Semiring R] (p q : R[X]) {S : Type*} [AddCommMonoid S] [Pow S ℕ] [Module R S]
(x : S)
@[simp]
theorem smeval_add : (p + q).smeval x = p.smeval x + q.smeval x := by
simp only [smeval_eq_sum, smul_pow]
refine sum_add_index p q (smul_pow x) (fun _ ↦ ?_) (fun _ _ _ ↦ ?_)
· rw [smul_pow, zero_smul]
· rw [smul_pow, smul_pow, smul_pow, add_smul]
theorem smeval_natCast (n : ℕ) : (n : R[X]).smeval x = n • x ^ 0 := by
induction' n with n ih
· simp only [smeval_zero, Nat.cast_zero, Nat.zero_eq, zero_smul]
· rw [n.cast_succ, smeval_add, ih, smeval_one, ← add_nsmul]
@[deprecated (since := "2024-04-17")]
alias smeval_nat_cast := smeval_natCast
@[simp]
theorem smeval_smul (r : R) : (r • p).smeval x = r • p.smeval x := by
induction p using Polynomial.induction_on' with
| h_add p q ph qh =>
rw [smul_add, smeval_add, ph, qh, ← smul_add, smeval_add]
| h_monomial n a =>
rw [smul_monomial, smeval_monomial, smeval_monomial, smul_assoc]
/-- `Polynomial.smeval` as a linear map. -/
def smeval.linearMap : R[X] →ₗ[R] S where
toFun f := f.smeval x
map_add' f g := by simp only [smeval_add]
map_smul' c f := by simp only [smeval_smul, smul_eq_mul, RingHom.id_apply]
@[simp]
theorem smeval.linearMap_apply : smeval.linearMap R x p = p.smeval x := rfl
theorem leval_coe_eq_smeval {R : Type*} [Semiring R] (r : R) :
⇑(leval r) = fun p => p.smeval r := by
rw [Function.funext_iff]
intro
rw [leval_apply, smeval_def, eval_eq_sum]
rfl
theorem leval_eq_smeval.linearMap {R : Type*} [Semiring R] (r : R) :
leval r = smeval.linearMap R r := by
refine LinearMap.ext ?_
intro
rw [leval_apply, smeval.linearMap_apply, eval_eq_smeval]
end Module
section Neg
variable (R : Type*) [Ring R] {S : Type*} [AddCommGroup S] [Pow S ℕ] [Module R S] (p q : R[X])
(x : S)
@[simp]
theorem smeval_neg : (-p).smeval x = - p.smeval x := by
have h : (p + -p).smeval x = 0 := by rw [add_neg_self, smeval_zero]
rw [smeval_add, add_eq_zero_iff_neg_eq] at h
exact id h.symm
@[simp]
theorem smeval_sub : (p - q).smeval x = p.smeval x - q.smeval x := by
rw [sub_eq_add_neg, smeval_add, smeval_neg, sub_eq_add_neg]
end Neg
section NatPowAssoc
/-!
In the module docstring for algebras at `Mathlib.Algebra.Algebra.Basic`, we see that
`[CommSemiring R] [Semiring S] [Module R S] [IsScalarTower R S S] [SMulCommClass R S S]` is an
equivalent way to express `[CommSemiring R] [Semiring S] [Algebra R S]` that allows one to relax
the defining structures independently. For non-associative power-associative algebras (e.g.,
octonions), we replace the `[Semiring S]` with `[NonAssocSemiring S] [Pow S ℕ] [NatPowAssoc S]`.
-/
variable (R : Type*) [Semiring R] {p : R[X]} (r : R) (p q : R[X]) {S : Type*}
[NonAssocSemiring S] [Module R S] [IsScalarTower R S S] [SMulCommClass R S S] [Pow S ℕ]
[NatPowAssoc S] (x : S)
theorem smeval_at_natCast (q : ℕ[X]): ∀(n : ℕ), q.smeval (n : S) = q.smeval n := by
induction q using Polynomial.induction_on' with
| h_add p q ph qh =>
intro n
simp only [add_mul, smeval_add, ph, qh, Nat.cast_add]
| h_monomial n a =>
intro n
rw [smeval_monomial, smeval_monomial, nsmul_eq_mul, smul_eq_mul, Nat.cast_mul, Nat.cast_npow]
@[deprecated (since := "2024-04-17")]
alias smeval_at_nat_cast := smeval_at_natCast
theorem smeval_at_zero : p.smeval (0 : S) = (p.coeff 0) • (1 : S) := by
induction p using Polynomial.induction_on' with
| h_add p q ph qh =>
simp_all only [smeval_add, coeff_add, add_smul]
| h_monomial n a =>
cases n with
| zero => simp only [Nat.zero_eq, monomial_zero_left, smeval_C, npow_zero, coeff_C_zero]
| succ n => rw [coeff_monomial_succ, smeval_monomial, npow_add, npow_one, mul_zero, zero_smul,
smul_zero]
theorem smeval_mul_X : (p * X).smeval x = p.smeval x * x := by
induction p using Polynomial.induction_on' with
| h_add p q ph qh =>
simp only [add_mul, smeval_add, ph, qh]
| h_monomial n a =>
simp only [← monomial_one_one_eq_X, monomial_mul_monomial, smeval_monomial, mul_one, pow_succ',
mul_assoc, npow_add, smul_mul_assoc, npow_one]
| Mathlib/Algebra/Polynomial/Smeval.lean | 212 | 218 | theorem smeval_X_mul : (X * p).smeval x = x * p.smeval x := by |
induction p using Polynomial.induction_on' with
| h_add p q ph qh =>
simp only [smeval_add, ph, qh, mul_add]
| h_monomial n a =>
rw [← monomial_one_one_eq_X, monomial_mul_monomial, smeval_monomial, one_mul, npow_add,
npow_one, ← mul_smul_comm, smeval_monomial]
|
/-
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
-/
import Mathlib.Analysis.Complex.RealDeriv
import Mathlib.Analysis.Calculus.ContDiff.RCLike
import Mathlib.Analysis.Calculus.IteratedDeriv.Lemmas
#align_import analysis.special_functions.exp_deriv from "leanprover-community/mathlib"@"6a5c85000ab93fe5dcfdf620676f614ba8e18c26"
/-!
# Complex and real exponential
In this file we prove that `Complex.exp` and `Real.exp` are infinitely smooth functions.
## Tags
exp, derivative
-/
noncomputable section
open Filter Asymptotics Set Function
open scoped Classical Topology
/-! ## `Complex.exp` -/
namespace Complex
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedAlgebra 𝕜 ℂ]
/-- The complex exponential is everywhere differentiable, with the derivative `exp x`. -/
theorem hasDerivAt_exp (x : ℂ) : HasDerivAt exp (exp x) x := by
rw [hasDerivAt_iff_isLittleO_nhds_zero]
have : (1 : ℕ) < 2 := by norm_num
refine (IsBigO.of_bound ‖exp x‖ ?_).trans_isLittleO (isLittleO_pow_id this)
filter_upwards [Metric.ball_mem_nhds (0 : ℂ) zero_lt_one]
simp only [Metric.mem_ball, dist_zero_right, norm_pow]
exact fun z hz => exp_bound_sq x z hz.le
#align complex.has_deriv_at_exp Complex.hasDerivAt_exp
theorem differentiable_exp : Differentiable 𝕜 exp := fun x =>
(hasDerivAt_exp x).differentiableAt.restrictScalars 𝕜
#align complex.differentiable_exp Complex.differentiable_exp
theorem differentiableAt_exp {x : ℂ} : DifferentiableAt 𝕜 exp x :=
differentiable_exp x
#align complex.differentiable_at_exp Complex.differentiableAt_exp
@[simp]
theorem deriv_exp : deriv exp = exp :=
funext fun x => (hasDerivAt_exp x).deriv
#align complex.deriv_exp Complex.deriv_exp
@[simp]
theorem iter_deriv_exp : ∀ n : ℕ, deriv^[n] exp = exp
| 0 => rfl
| n + 1 => by rw [iterate_succ_apply, deriv_exp, iter_deriv_exp n]
#align complex.iter_deriv_exp Complex.iter_deriv_exp
theorem contDiff_exp : ∀ {n}, ContDiff 𝕜 n exp := by
-- Porting note: added `@` due to `∀ {n}` weirdness above
refine @(contDiff_all_iff_nat.2 fun n => ?_)
have : ContDiff ℂ (↑n) exp := by
induction' n with n ihn
· exact contDiff_zero.2 continuous_exp
· rw [contDiff_succ_iff_deriv]
use differentiable_exp
rwa [deriv_exp]
exact this.restrict_scalars 𝕜
#align complex.cont_diff_exp Complex.contDiff_exp
theorem hasStrictDerivAt_exp (x : ℂ) : HasStrictDerivAt exp (exp x) x :=
contDiff_exp.contDiffAt.hasStrictDerivAt' (hasDerivAt_exp x) le_rfl
#align complex.has_strict_deriv_at_exp Complex.hasStrictDerivAt_exp
theorem hasStrictFDerivAt_exp_real (x : ℂ) : HasStrictFDerivAt exp (exp x • (1 : ℂ →L[ℝ] ℂ)) x :=
(hasStrictDerivAt_exp x).complexToReal_fderiv
#align complex.has_strict_fderiv_at_exp_real Complex.hasStrictFDerivAt_exp_real
end Complex
section
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedAlgebra 𝕜 ℂ] {f : 𝕜 → ℂ} {f' : ℂ} {x : 𝕜}
{s : Set 𝕜}
theorem HasStrictDerivAt.cexp (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) * f') x :=
(Complex.hasStrictDerivAt_exp (f x)).comp x hf
#align has_strict_deriv_at.cexp HasStrictDerivAt.cexp
theorem HasDerivAt.cexp (hf : HasDerivAt f f' x) :
HasDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) * f') x :=
(Complex.hasDerivAt_exp (f x)).comp x hf
#align has_deriv_at.cexp HasDerivAt.cexp
theorem HasDerivWithinAt.cexp (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun x => Complex.exp (f x)) (Complex.exp (f x) * f') s x :=
(Complex.hasDerivAt_exp (f x)).comp_hasDerivWithinAt x hf
#align has_deriv_within_at.cexp HasDerivWithinAt.cexp
theorem derivWithin_cexp (hf : DifferentiableWithinAt 𝕜 f s x) (hxs : UniqueDiffWithinAt 𝕜 s x) :
derivWithin (fun x => Complex.exp (f x)) s x = Complex.exp (f x) * derivWithin f s x :=
hf.hasDerivWithinAt.cexp.derivWithin hxs
#align deriv_within_cexp derivWithin_cexp
@[simp]
theorem deriv_cexp (hc : DifferentiableAt 𝕜 f x) :
deriv (fun x => Complex.exp (f x)) x = Complex.exp (f x) * deriv f x :=
hc.hasDerivAt.cexp.deriv
#align deriv_cexp deriv_cexp
end
section
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedAlgebra 𝕜 ℂ] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {f : E → ℂ} {f' : E →L[𝕜] ℂ} {x : E} {s : Set E}
theorem HasStrictFDerivAt.cexp (hf : HasStrictFDerivAt f f' x) :
HasStrictFDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) • f') x :=
(Complex.hasStrictDerivAt_exp (f x)).comp_hasStrictFDerivAt x hf
#align has_strict_fderiv_at.cexp HasStrictFDerivAt.cexp
theorem HasFDerivWithinAt.cexp (hf : HasFDerivWithinAt f f' s x) :
HasFDerivWithinAt (fun x => Complex.exp (f x)) (Complex.exp (f x) • f') s x :=
(Complex.hasDerivAt_exp (f x)).comp_hasFDerivWithinAt x hf
#align has_fderiv_within_at.cexp HasFDerivWithinAt.cexp
theorem HasFDerivAt.cexp (hf : HasFDerivAt f f' x) :
HasFDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) • f') x :=
hasFDerivWithinAt_univ.1 <| hf.hasFDerivWithinAt.cexp
#align has_fderiv_at.cexp HasFDerivAt.cexp
theorem DifferentiableWithinAt.cexp (hf : DifferentiableWithinAt 𝕜 f s x) :
DifferentiableWithinAt 𝕜 (fun x => Complex.exp (f x)) s x :=
hf.hasFDerivWithinAt.cexp.differentiableWithinAt
#align differentiable_within_at.cexp DifferentiableWithinAt.cexp
@[simp]
theorem DifferentiableAt.cexp (hc : DifferentiableAt 𝕜 f x) :
DifferentiableAt 𝕜 (fun x => Complex.exp (f x)) x :=
hc.hasFDerivAt.cexp.differentiableAt
#align differentiable_at.cexp DifferentiableAt.cexp
theorem DifferentiableOn.cexp (hc : DifferentiableOn 𝕜 f s) :
DifferentiableOn 𝕜 (fun x => Complex.exp (f x)) s := fun x h => (hc x h).cexp
#align differentiable_on.cexp DifferentiableOn.cexp
@[simp]
theorem Differentiable.cexp (hc : Differentiable 𝕜 f) :
Differentiable 𝕜 fun x => Complex.exp (f x) := fun x => (hc x).cexp
#align differentiable.cexp Differentiable.cexp
theorem ContDiff.cexp {n} (h : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => Complex.exp (f x) :=
Complex.contDiff_exp.comp h
#align cont_diff.cexp ContDiff.cexp
theorem ContDiffAt.cexp {n} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => Complex.exp (f x)) x :=
Complex.contDiff_exp.contDiffAt.comp x hf
#align cont_diff_at.cexp ContDiffAt.cexp
theorem ContDiffOn.cexp {n} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => Complex.exp (f x)) s :=
Complex.contDiff_exp.comp_contDiffOn hf
#align cont_diff_on.cexp ContDiffOn.cexp
theorem ContDiffWithinAt.cexp {n} (hf : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n (fun x => Complex.exp (f x)) s x :=
Complex.contDiff_exp.contDiffAt.comp_contDiffWithinAt x hf
#align cont_diff_within_at.cexp ContDiffWithinAt.cexp
end
open Complex in
@[simp]
| Mathlib/Analysis/SpecialFunctions/ExpDeriv.lean | 182 | 184 | theorem iteratedDeriv_cexp_const_mul (n : ℕ) (c : ℂ) :
(iteratedDeriv n fun s : ℂ => exp (c * s)) = fun s => c ^ n * exp (c * s) := by |
rw [iteratedDeriv_const_mul contDiff_exp, iteratedDeriv_eq_iterate, iter_deriv_exp]
|
/-
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.RingTheory.FiniteType
#align_import ring_theory.rees_algebra from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Rees algebra
The Rees algebra of an ideal `I` is the subalgebra `R[It]` of `R[t]` defined as `R[It] = ⨁ₙ Iⁿ tⁿ`.
This is used to prove the Artin-Rees lemma, and will potentially enable us to calculate some
blowup in the future.
## Main definition
- `reesAlgebra` : The Rees algebra of an ideal `I`, defined as a subalgebra of `R[X]`.
- `adjoin_monomial_eq_reesAlgebra` : The Rees algebra is generated by the degree one elements.
- `reesAlgebra.fg` : The Rees algebra of a f.g. ideal is of finite type. In particular, this
implies that the rees algebra over a noetherian ring is still noetherian.
-/
universe u v
variable {R M : Type u} [CommRing R] [AddCommGroup M] [Module R M] (I : Ideal R)
open Polynomial
open Polynomial
/-- The Rees algebra of an ideal `I`, defined as the subalgebra of `R[X]` whose `i`-th coefficient
falls in `I ^ i`. -/
def reesAlgebra : Subalgebra R R[X] where
carrier := { f | ∀ i, f.coeff i ∈ I ^ i }
mul_mem' hf hg i := by
rw [coeff_mul]
apply Ideal.sum_mem
rintro ⟨j, k⟩ e
rw [← Finset.mem_antidiagonal.mp e, pow_add]
exact Ideal.mul_mem_mul (hf j) (hg k)
one_mem' i := by
rw [coeff_one]
split_ifs with h
· subst h
simp
· simp
add_mem' hf hg i := by
rw [coeff_add]
exact Ideal.add_mem _ (hf i) (hg i)
zero_mem' i := Ideal.zero_mem _
algebraMap_mem' r i := by
rw [algebraMap_apply, coeff_C]
split_ifs with h
· subst h
simp
· simp
#align rees_algebra reesAlgebra
theorem mem_reesAlgebra_iff (f : R[X]) : f ∈ reesAlgebra I ↔ ∀ i, f.coeff i ∈ I ^ i :=
Iff.rfl
#align mem_rees_algebra_iff mem_reesAlgebra_iff
theorem mem_reesAlgebra_iff_support (f : R[X]) :
f ∈ reesAlgebra I ↔ ∀ i ∈ f.support, f.coeff i ∈ I ^ i := by
apply forall_congr'
intro a
rw [mem_support_iff, Iff.comm, Classical.imp_iff_right_iff, Ne, ← imp_iff_not_or]
exact fun e => e.symm ▸ (I ^ a).zero_mem
#align mem_rees_algebra_iff_support mem_reesAlgebra_iff_support
theorem reesAlgebra.monomial_mem {I : Ideal R} {i : ℕ} {r : R} :
monomial i r ∈ reesAlgebra I ↔ r ∈ I ^ i := by
simp (config := { contextual := true }) [mem_reesAlgebra_iff_support, coeff_monomial, ←
imp_iff_not_or]
#align rees_algebra.monomial_mem reesAlgebra.monomial_mem
theorem monomial_mem_adjoin_monomial {I : Ideal R} {n : ℕ} {r : R} (hr : r ∈ I ^ n) :
monomial n r ∈ Algebra.adjoin R (Submodule.map (monomial 1 : R →ₗ[R] R[X]) I : Set R[X]) := by
induction' n with n hn generalizing r
· exact Subalgebra.algebraMap_mem _ _
· rw [pow_succ'] at hr
apply Submodule.smul_induction_on
-- Porting note: did not need help with motive previously
(p := fun r => (monomial (Nat.succ n)) r ∈ Algebra.adjoin R (Submodule.map (monomial 1) I)) hr
· intro r hr s hs
rw [Nat.succ_eq_one_add, smul_eq_mul, ← monomial_mul_monomial]
exact Subalgebra.mul_mem _ (Algebra.subset_adjoin (Set.mem_image_of_mem _ hr)) (hn hs)
· intro x y hx hy
rw [monomial_add]
exact Subalgebra.add_mem _ hx hy
#align monomial_mem_adjoin_monomial monomial_mem_adjoin_monomial
theorem adjoin_monomial_eq_reesAlgebra :
Algebra.adjoin R (Submodule.map (monomial 1 : R →ₗ[R] R[X]) I : Set R[X]) = reesAlgebra I := by
apply le_antisymm
· apply Algebra.adjoin_le _
rintro _ ⟨r, hr, rfl⟩
exact reesAlgebra.monomial_mem.mpr (by rwa [pow_one])
· intro p hp
rw [p.as_sum_support]
apply Subalgebra.sum_mem _ _
rintro i -
exact monomial_mem_adjoin_monomial (hp i)
#align adjoin_monomial_eq_rees_algebra adjoin_monomial_eq_reesAlgebra
variable {I}
| Mathlib/RingTheory/ReesAlgebra.lean | 113 | 123 | theorem reesAlgebra.fg (hI : I.FG) : (reesAlgebra I).FG := by |
classical
obtain ⟨s, hs⟩ := hI
rw [← adjoin_monomial_eq_reesAlgebra, ← hs]
use s.image (monomial 1)
rw [Finset.coe_image]
change
_ =
Algebra.adjoin R
(Submodule.map (monomial 1 : R →ₗ[R] R[X]) (Submodule.span R ↑s) : Set R[X])
rw [Submodule.map_span, Algebra.adjoin_span]
|
/-
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.List.Nodup
#align_import data.prod.tprod from "leanprover-community/mathlib"@"c227d107bbada5d0d9d20287e3282c0a7f1651a0"
/-!
# Finite products of types
This file defines the product of types over a list. For `l : List ι` and `α : ι → Type v` we define
`List.TProd α l = l.foldr (fun i β ↦ α i × β) PUnit`.
This type should not be used if `∀ i, α i` or `∀ i ∈ l, α i` can be used instead
(in the last expression, we could also replace the list `l` by a set or a finset).
This type is used as an intermediary between binary products and finitary products.
The application of this type is finitary product measures, but it could be used in any
construction/theorem that is easier to define/prove on binary products than on finitary products.
* Once we have the construction on binary products (like binary product measures in
`MeasureTheory.prod`), we can easily define a finitary version on the type `TProd l α`
by iterating. Properties can also be easily extended from the binary case to the finitary case
by iterating.
* Then we can use the equivalence `List.TProd.piEquivTProd` below (or enhanced versions of it,
like a `MeasurableEquiv` for product measures) to get the construction on `∀ i : ι, α i`, at
least when assuming `[Fintype ι] [Encodable ι]` (using `Encodable.sortedUniv`).
Using `attribute [local instance] Fintype.toEncodable` we can get rid of the argument
`[Encodable ι]`.
## Main definitions
* We have the equivalence `TProd.piEquivTProd : (∀ i, α i) ≃ TProd α l`
if `l` contains every element of `ι` exactly once.
* The product of sets is `Set.tprod : (∀ i, Set (α i)) → Set (TProd α l)`.
-/
open List Function
universe u v
variable {ι : Type u} {α : ι → Type v} {i j : ι} {l : List ι} {f : ∀ i, α i}
namespace List
variable (α)
/-- The product of a family of types over a list. -/
abbrev TProd (l : List ι) : Type v :=
l.foldr (fun i β => α i × β) PUnit
#align list.tprod List.TProd
variable {α}
namespace TProd
open List
/-- Turning a function `f : ∀ i, α i` into an element of the iterated product `TProd α l`. -/
protected def mk : ∀ (l : List ι) (_f : ∀ i, α i), TProd α l
| [] => fun _ => PUnit.unit
| i :: is => fun f => (f i, TProd.mk is f)
#align list.tprod.mk List.TProd.mk
instance [∀ i, Inhabited (α i)] : Inhabited (TProd α l) :=
⟨TProd.mk l default⟩
@[simp]
theorem fst_mk (i : ι) (l : List ι) (f : ∀ i, α i) : (TProd.mk (i :: l) f).1 = f i :=
rfl
#align list.tprod.fst_mk List.TProd.fst_mk
@[simp]
theorem snd_mk (i : ι) (l : List ι) (f : ∀ i, α i) :
(TProd.mk.{u,v} (i :: l) f).2 = TProd.mk.{u,v} l f :=
rfl
#align list.tprod.snd_mk List.TProd.snd_mk
variable [DecidableEq ι]
/-- Given an element of the iterated product `l.Prod α`, take a projection into direction `i`.
If `i` appears multiple times in `l`, this chooses the first component in direction `i`. -/
protected def elim : ∀ {l : List ι} (_ : TProd α l) {i : ι} (_ : i ∈ l), α i
| i :: is, v, j, hj =>
if hji : j = i then by
subst hji
exact v.1
else TProd.elim v.2 ((List.mem_cons.mp hj).resolve_left hji)
#align list.tprod.elim List.TProd.elim
@[simp]
| Mathlib/Data/Prod/TProd.lean | 90 | 90 | theorem elim_self (v : TProd α (i :: l)) : v.elim (l.mem_cons_self i) = v.1 := by | simp [TProd.elim]
|
/-
Copyright (c) 2023 Scott Carnahan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Carnahan
-/
import Mathlib.Algebra.Polynomial.Smeval
import Mathlib.GroupTheory.GroupAction.Ring
import Mathlib.RingTheory.Polynomial.Pochhammer
/-!
# Binomial rings
In this file we introduce the binomial property as a mixin, and define the `multichoose`
and `choose` functions generalizing binomial coefficients.
According to our main reference [elliott2006binomial] (which lists many equivalent conditions), a
binomial ring is a torsion-free commutative ring `R` such that for any `x ∈ R` and any `k ∈ ℕ`, the
product `x(x-1)⋯(x-k+1)` is divisible by `k!`. The torsion-free condition lets us divide by `k!`
unambiguously, so we get uniquely defined binomial coefficients.
The defining condition doesn't require commutativity or associativity, and we get a theory with
essentially the same power by replacing subtraction with addition. Thus, we consider any additive
commutative monoid with a notion of natural number exponents in which multiplication by positive
integers is injective, and demand that the evaluation of the ascending Pochhammer polynomial
`X(X+1)⋯(X+(k-1))` at any element is divisible by `k!`. The quotient is called `multichoose r k`,
because for `r` a natural number, it is the number of multisets of cardinality `k` taken from a type
of cardinality `n`.
## References
* [J. Elliott, *Binomial rings, integer-valued polynomials, and λ-rings*][elliott2006binomial]
## TODO
* Replace `Nat.multichoose` with `Ring.multichoose`.
Further results in Elliot's paper:
* A CommRing is binomial if and only if it admits a λ-ring structure with trivial Adams operations.
* The free commutative binomial ring on a set `X` is the ring of integer-valued polynomials in the
variables `X`. (also, noncommutative version?)
* Given a commutative binomial ring `A` and an `A`-algebra `B` that is complete with respect to an
ideal `I`, formal exponentiation induces an `A`-module structure on the multiplicative subgroup
`1 + I`.
-/
section Multichoose
open Function Polynomial
/-- A binomial ring is a ring for which ascending Pochhammer evaluations are uniquely divisible by
suitable factorials. We define this notion for a additive commutative monoids with natural number
powers, but retain the ring name. We introduce `Ring.multichoose` as the uniquely defined
quotient. -/
class BinomialRing (R : Type*) [AddCommMonoid R] [Pow R ℕ] where
/-- Scalar multiplication by positive integers is injective -/
nsmul_right_injective (n : ℕ) (h : n ≠ 0) : Injective (n • · : R → R)
/-- A multichoose function, giving the quotient of Pochhammer evaluations by factorials. -/
multichoose : R → ℕ → R
/-- The `n`th ascending Pochhammer polynomial evaluated at any element is divisible by n! -/
factorial_nsmul_multichoose (r : R) (n : ℕ) :
n.factorial • multichoose r n = (ascPochhammer ℕ n).smeval r
namespace Ring
variable {R : Type*} [AddCommMonoid R] [Pow R ℕ] [BinomialRing R]
theorem nsmul_right_injective (n : ℕ) (h : n ≠ 0) :
Injective (n • · : R → R) := BinomialRing.nsmul_right_injective n h
/-- The multichoose function is the quotient of ascending Pochhammer evaluation by the corresponding
factorial. When applied to natural numbers, `multichoose k n` describes choosing a multiset of `n`
items from a type of size `k`, i.e., choosing with replacement. -/
def multichoose (r : R) (n : ℕ) : R := BinomialRing.multichoose r n
@[simp]
theorem multichoose_eq_multichoose (r : R) (n : ℕ) :
BinomialRing.multichoose r n = multichoose r n := rfl
theorem factorial_nsmul_multichoose_eq_ascPochhammer (r : R) (n : ℕ) :
n.factorial • multichoose r n = (ascPochhammer ℕ n).smeval r :=
BinomialRing.factorial_nsmul_multichoose r n
end Ring
end Multichoose
section Pochhammer
namespace Polynomial
theorem ascPochhammer_smeval_cast (R : Type*) [Semiring R] {S : Type*} [NonAssocSemiring S]
[Pow S ℕ] [Module R S] [IsScalarTower R S S] [NatPowAssoc S]
(x : S) (n : ℕ) : (ascPochhammer R n).smeval x = (ascPochhammer ℕ n).smeval x := by
induction' n with n hn
· simp only [Nat.zero_eq, ascPochhammer_zero, smeval_one, one_smul]
· simp only [ascPochhammer_succ_right, mul_add, smeval_add, smeval_mul_X, ← Nat.cast_comm]
simp only [← C_eq_natCast, smeval_C_mul, hn, ← nsmul_eq_smul_cast R n]
exact rfl
variable {R S : Type*}
theorem ascPochhammer_smeval_eq_eval [Semiring R] (r : R) (n : ℕ) :
(ascPochhammer ℕ n).smeval r = (ascPochhammer R n).eval r := by
rw [eval_eq_smeval, ascPochhammer_smeval_cast R]
variable [NonAssocRing R] [Pow R ℕ] [NatPowAssoc R]
| Mathlib/RingTheory/Binomial.lean | 107 | 115 | theorem descPochhammer_smeval_eq_ascPochhammer (r : R) (n : ℕ) :
(descPochhammer ℤ n).smeval r = (ascPochhammer ℕ n).smeval (r - n + 1) := by |
induction n with
| zero => simp only [descPochhammer_zero, ascPochhammer_zero, smeval_one, npow_zero]
| succ n ih =>
rw [Nat.cast_succ, sub_add, add_sub_cancel_right, descPochhammer_succ_right, smeval_mul, ih,
ascPochhammer_succ_left, X_mul, smeval_mul_X, smeval_comp, smeval_sub, ← C_eq_natCast,
smeval_add, smeval_one, smeval_C]
simp only [smeval_X, npow_one, npow_zero, zsmul_one, Int.cast_natCast, one_smul]
|
/-
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
-/
import Mathlib.Analysis.Complex.Asymptotics
import Mathlib.Analysis.SpecificLimits.Normed
#align_import analysis.special_functions.exp from "leanprover-community/mathlib"@"ba5ff5ad5d120fb0ef094ad2994967e9bfaf5112"
/-!
# Complex and real exponential
In this file we prove continuity of `Complex.exp` and `Real.exp`. We also prove a few facts about
limits of `Real.exp` at infinity.
## Tags
exp
-/
noncomputable section
open Finset Filter Metric Asymptotics Set Function Bornology
open scoped Classical Topology Nat
namespace Complex
variable {z y x : ℝ}
theorem exp_bound_sq (x z : ℂ) (hz : ‖z‖ ≤ 1) :
‖exp (x + z) - exp x - z • exp x‖ ≤ ‖exp x‖ * ‖z‖ ^ 2 :=
calc
‖exp (x + z) - exp x - z * exp x‖ = ‖exp x * (exp z - 1 - z)‖ := by
congr
rw [exp_add]
ring
_ = ‖exp x‖ * ‖exp z - 1 - z‖ := norm_mul _ _
_ ≤ ‖exp x‖ * ‖z‖ ^ 2 :=
mul_le_mul_of_nonneg_left (abs_exp_sub_one_sub_id_le hz) (norm_nonneg _)
#align complex.exp_bound_sq Complex.exp_bound_sq
theorem locally_lipschitz_exp {r : ℝ} (hr_nonneg : 0 ≤ r) (hr_le : r ≤ 1) (x y : ℂ)
(hyx : ‖y - x‖ < r) : ‖exp y - exp x‖ ≤ (1 + r) * ‖exp x‖ * ‖y - x‖ := by
have hy_eq : y = x + (y - x) := by abel
have hyx_sq_le : ‖y - x‖ ^ 2 ≤ r * ‖y - x‖ := by
rw [pow_two]
exact mul_le_mul hyx.le le_rfl (norm_nonneg _) hr_nonneg
have h_sq : ∀ z, ‖z‖ ≤ 1 → ‖exp (x + z) - exp x‖ ≤ ‖z‖ * ‖exp x‖ + ‖exp x‖ * ‖z‖ ^ 2 := by
intro z hz
have : ‖exp (x + z) - exp x - z • exp x‖ ≤ ‖exp x‖ * ‖z‖ ^ 2 := exp_bound_sq x z hz
rw [← sub_le_iff_le_add', ← norm_smul z]
exact (norm_sub_norm_le _ _).trans this
calc
‖exp y - exp x‖ = ‖exp (x + (y - x)) - exp x‖ := by nth_rw 1 [hy_eq]
_ ≤ ‖y - x‖ * ‖exp x‖ + ‖exp x‖ * ‖y - x‖ ^ 2 := h_sq (y - x) (hyx.le.trans hr_le)
_ ≤ ‖y - x‖ * ‖exp x‖ + ‖exp x‖ * (r * ‖y - x‖) :=
(add_le_add_left (mul_le_mul le_rfl hyx_sq_le (sq_nonneg _) (norm_nonneg _)) _)
_ = (1 + r) * ‖exp x‖ * ‖y - x‖ := by ring
#align complex.locally_lipschitz_exp Complex.locally_lipschitz_exp
-- Porting note: proof by term mode `locally_lipschitz_exp zero_le_one le_rfl x`
-- doesn't work because `‖y - x‖` and `dist y x` don't unify
@[continuity]
theorem continuous_exp : Continuous exp :=
continuous_iff_continuousAt.mpr fun x =>
continuousAt_of_locally_lipschitz zero_lt_one (2 * ‖exp x‖)
(fun y ↦ by
convert locally_lipschitz_exp zero_le_one le_rfl x y using 2
congr
ring)
#align complex.continuous_exp Complex.continuous_exp
theorem continuousOn_exp {s : Set ℂ} : ContinuousOn exp s :=
continuous_exp.continuousOn
#align complex.continuous_on_exp Complex.continuousOn_exp
lemma exp_sub_sum_range_isBigO_pow (n : ℕ) :
(fun x ↦ exp x - ∑ i ∈ Finset.range n, x ^ i / i !) =O[𝓝 0] (· ^ n) := by
rcases (zero_le n).eq_or_lt with rfl | hn
· simpa using continuous_exp.continuousAt.norm.isBoundedUnder_le
· refine .of_bound (n.succ / (n ! * n)) ?_
rw [NormedAddCommGroup.nhds_zero_basis_norm_lt.eventually_iff]
refine ⟨1, one_pos, fun x hx ↦ ?_⟩
convert exp_bound hx.out.le hn using 1
field_simp [mul_comm]
lemma exp_sub_sum_range_succ_isLittleO_pow (n : ℕ) :
(fun x ↦ exp x - ∑ i ∈ Finset.range (n + 1), x ^ i / i !) =o[𝓝 0] (· ^ n) :=
(exp_sub_sum_range_isBigO_pow (n + 1)).trans_isLittleO <| isLittleO_pow_pow n.lt_succ_self
end Complex
section ComplexContinuousExpComp
variable {α : Type*}
open Complex
theorem Filter.Tendsto.cexp {l : Filter α} {f : α → ℂ} {z : ℂ} (hf : Tendsto f l (𝓝 z)) :
Tendsto (fun x => exp (f x)) l (𝓝 (exp z)) :=
(continuous_exp.tendsto _).comp hf
#align filter.tendsto.cexp Filter.Tendsto.cexp
variable [TopologicalSpace α] {f : α → ℂ} {s : Set α} {x : α}
nonrec
theorem ContinuousWithinAt.cexp (h : ContinuousWithinAt f s x) :
ContinuousWithinAt (fun y => exp (f y)) s x :=
h.cexp
#align continuous_within_at.cexp ContinuousWithinAt.cexp
@[fun_prop]
nonrec
theorem ContinuousAt.cexp (h : ContinuousAt f x) : ContinuousAt (fun y => exp (f y)) x :=
h.cexp
#align continuous_at.cexp ContinuousAt.cexp
@[fun_prop]
theorem ContinuousOn.cexp (h : ContinuousOn f s) : ContinuousOn (fun y => exp (f y)) s :=
fun x hx => (h x hx).cexp
#align continuous_on.cexp ContinuousOn.cexp
@[fun_prop]
theorem Continuous.cexp (h : Continuous f) : Continuous fun y => exp (f y) :=
continuous_iff_continuousAt.2 fun _ => h.continuousAt.cexp
#align continuous.cexp Continuous.cexp
end ComplexContinuousExpComp
namespace Real
@[continuity]
theorem continuous_exp : Continuous exp :=
Complex.continuous_re.comp Complex.continuous_ofReal.cexp
#align real.continuous_exp Real.continuous_exp
theorem continuousOn_exp {s : Set ℝ} : ContinuousOn exp s :=
continuous_exp.continuousOn
#align real.continuous_on_exp Real.continuousOn_exp
lemma exp_sub_sum_range_isBigO_pow (n : ℕ) :
(fun x ↦ exp x - ∑ i ∈ Finset.range n, x ^ i / i !) =O[𝓝 0] (· ^ n) := by
have := (Complex.exp_sub_sum_range_isBigO_pow n).comp_tendsto
(Complex.continuous_ofReal.tendsto' 0 0 rfl)
simp only [(· ∘ ·)] at this
norm_cast at this
lemma exp_sub_sum_range_succ_isLittleO_pow (n : ℕ) :
(fun x ↦ exp x - ∑ i ∈ Finset.range (n + 1), x ^ i / i !) =o[𝓝 0] (· ^ n) :=
(exp_sub_sum_range_isBigO_pow (n + 1)).trans_isLittleO <| isLittleO_pow_pow n.lt_succ_self
end Real
section RealContinuousExpComp
variable {α : Type*}
open Real
theorem Filter.Tendsto.rexp {l : Filter α} {f : α → ℝ} {z : ℝ} (hf : Tendsto f l (𝓝 z)) :
Tendsto (fun x => exp (f x)) l (𝓝 (exp z)) :=
(continuous_exp.tendsto _).comp hf
#align filter.tendsto.exp Filter.Tendsto.rexp
variable [TopologicalSpace α] {f : α → ℝ} {s : Set α} {x : α}
nonrec
theorem ContinuousWithinAt.rexp (h : ContinuousWithinAt f s x) :
ContinuousWithinAt (fun y ↦ exp (f y)) s x :=
h.rexp
#align continuous_within_at.exp ContinuousWithinAt.rexp
@[deprecated (since := "2024-05-09")] alias ContinuousWithinAt.exp := ContinuousWithinAt.rexp
@[fun_prop]
nonrec
theorem ContinuousAt.rexp (h : ContinuousAt f x) : ContinuousAt (fun y ↦ exp (f y)) x :=
h.rexp
#align continuous_at.exp ContinuousAt.rexp
@[deprecated (since := "2024-05-09")] alias ContinuousAt.exp := ContinuousAt.rexp
@[fun_prop]
theorem ContinuousOn.rexp (h : ContinuousOn f s) :
ContinuousOn (fun y ↦ exp (f y)) s :=
fun x hx ↦ (h x hx).rexp
#align continuous_on.exp ContinuousOn.rexp
@[deprecated (since := "2024-05-09")] alias ContinuousOn.exp := ContinuousOn.rexp
@[fun_prop]
theorem Continuous.rexp (h : Continuous f) : Continuous fun y ↦ exp (f y) :=
continuous_iff_continuousAt.2 fun _ ↦ h.continuousAt.rexp
#align continuous.exp Continuous.rexp
@[deprecated (since := "2024-05-09")] alias Continuous.exp := Continuous.rexp
end RealContinuousExpComp
namespace Real
variable {α : Type*} {x y z : ℝ} {l : Filter α}
theorem exp_half (x : ℝ) : exp (x / 2) = √(exp x) := by
rw [eq_comm, sqrt_eq_iff_sq_eq, sq, ← exp_add, add_halves] <;> exact (exp_pos _).le
#align real.exp_half Real.exp_half
/-- The real exponential function tends to `+∞` at `+∞`. -/
theorem tendsto_exp_atTop : Tendsto exp atTop atTop := by
have A : Tendsto (fun x : ℝ => x + 1) atTop atTop :=
tendsto_atTop_add_const_right atTop 1 tendsto_id
have B : ∀ᶠ x in atTop, x + 1 ≤ exp x := eventually_atTop.2 ⟨0, fun x _ => add_one_le_exp x⟩
exact tendsto_atTop_mono' atTop B A
#align real.tendsto_exp_at_top Real.tendsto_exp_atTop
/-- The real exponential function tends to `0` at `-∞` or, equivalently, `exp(-x)` tends to `0`
at `+∞` -/
theorem tendsto_exp_neg_atTop_nhds_zero : Tendsto (fun x => exp (-x)) atTop (𝓝 0) :=
(tendsto_inv_atTop_zero.comp tendsto_exp_atTop).congr fun x => (exp_neg x).symm
#align real.tendsto_exp_neg_at_top_nhds_0 Real.tendsto_exp_neg_atTop_nhds_zero
@[deprecated (since := "2024-01-31")]
alias tendsto_exp_neg_atTop_nhds_0 := tendsto_exp_neg_atTop_nhds_zero
/-- The real exponential function tends to `1` at `0`. -/
theorem tendsto_exp_nhds_zero_nhds_one : Tendsto exp (𝓝 0) (𝓝 1) := by
convert continuous_exp.tendsto 0
simp
#align real.tendsto_exp_nhds_0_nhds_1 Real.tendsto_exp_nhds_zero_nhds_one
@[deprecated (since := "2024-01-31")]
alias tendsto_exp_nhds_0_nhds_1 := tendsto_exp_nhds_zero_nhds_one
theorem tendsto_exp_atBot : Tendsto exp atBot (𝓝 0) :=
(tendsto_exp_neg_atTop_nhds_zero.comp tendsto_neg_atBot_atTop).congr fun x =>
congr_arg exp <| neg_neg x
#align real.tendsto_exp_at_bot Real.tendsto_exp_atBot
theorem tendsto_exp_atBot_nhdsWithin : Tendsto exp atBot (𝓝[>] 0) :=
tendsto_inf.2 ⟨tendsto_exp_atBot, tendsto_principal.2 <| eventually_of_forall exp_pos⟩
#align real.tendsto_exp_at_bot_nhds_within Real.tendsto_exp_atBot_nhdsWithin
@[simp]
theorem isBoundedUnder_ge_exp_comp (l : Filter α) (f : α → ℝ) :
IsBoundedUnder (· ≥ ·) l fun x => exp (f x) :=
isBoundedUnder_of ⟨0, fun _ => (exp_pos _).le⟩
#align real.is_bounded_under_ge_exp_comp Real.isBoundedUnder_ge_exp_comp
@[simp]
theorem isBoundedUnder_le_exp_comp {f : α → ℝ} :
(IsBoundedUnder (· ≤ ·) l fun x => exp (f x)) ↔ IsBoundedUnder (· ≤ ·) l f :=
exp_monotone.isBoundedUnder_le_comp_iff tendsto_exp_atTop
#align real.is_bounded_under_le_exp_comp Real.isBoundedUnder_le_exp_comp
/-- The function `exp(x)/x^n` tends to `+∞` at `+∞`, for any natural number `n` -/
theorem tendsto_exp_div_pow_atTop (n : ℕ) : Tendsto (fun x => exp x / x ^ n) atTop atTop := by
refine (atTop_basis_Ioi.tendsto_iff (atTop_basis' 1)).2 fun C hC₁ => ?_
have hC₀ : 0 < C := zero_lt_one.trans_le hC₁
have : 0 < (exp 1 * C)⁻¹ := inv_pos.2 (mul_pos (exp_pos _) hC₀)
obtain ⟨N, hN⟩ : ∃ N : ℕ, ∀ k ≥ N, (↑k : ℝ) ^ n / exp 1 ^ k < (exp 1 * C)⁻¹ :=
eventually_atTop.1
((tendsto_pow_const_div_const_pow_of_one_lt n (one_lt_exp_iff.2 zero_lt_one)).eventually
(gt_mem_nhds this))
simp only [← exp_nat_mul, mul_one, div_lt_iff, exp_pos, ← div_eq_inv_mul] at hN
refine ⟨N, trivial, fun x hx => ?_⟩
rw [Set.mem_Ioi] at hx
have hx₀ : 0 < x := (Nat.cast_nonneg N).trans_lt hx
rw [Set.mem_Ici, le_div_iff (pow_pos hx₀ _), ← le_div_iff' hC₀]
calc
x ^ n ≤ ⌈x⌉₊ ^ n := mod_cast pow_le_pow_left hx₀.le (Nat.le_ceil _) _
_ ≤ exp ⌈x⌉₊ / (exp 1 * C) := mod_cast (hN _ (Nat.lt_ceil.2 hx).le).le
_ ≤ exp (x + 1) / (exp 1 * C) := by gcongr; exact (Nat.ceil_lt_add_one hx₀.le).le
_ = exp x / C := by rw [add_comm, exp_add, mul_div_mul_left _ _ (exp_pos _).ne']
#align real.tendsto_exp_div_pow_at_top Real.tendsto_exp_div_pow_atTop
/-- The function `x^n * exp(-x)` tends to `0` at `+∞`, for any natural number `n`. -/
theorem tendsto_pow_mul_exp_neg_atTop_nhds_zero (n : ℕ) :
Tendsto (fun x => x ^ n * exp (-x)) atTop (𝓝 0) :=
(tendsto_inv_atTop_zero.comp (tendsto_exp_div_pow_atTop n)).congr fun x => by
rw [comp_apply, inv_eq_one_div, div_div_eq_mul_div, one_mul, div_eq_mul_inv, exp_neg]
#align real.tendsto_pow_mul_exp_neg_at_top_nhds_0 Real.tendsto_pow_mul_exp_neg_atTop_nhds_zero
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_mul_exp_neg_atTop_nhds_0 := tendsto_pow_mul_exp_neg_atTop_nhds_zero
/-- The function `(b * exp x + c) / (x ^ n)` tends to `+∞` at `+∞`, for any natural number
`n` and any real numbers `b` and `c` such that `b` is positive. -/
theorem tendsto_mul_exp_add_div_pow_atTop (b c : ℝ) (n : ℕ) (hb : 0 < b) :
Tendsto (fun x => (b * exp x + c) / x ^ n) atTop atTop := by
rcases eq_or_ne n 0 with (rfl | hn)
· simp only [pow_zero, div_one]
exact (tendsto_exp_atTop.const_mul_atTop hb).atTop_add tendsto_const_nhds
simp only [add_div, mul_div_assoc]
exact
((tendsto_exp_div_pow_atTop n).const_mul_atTop hb).atTop_add
(tendsto_const_nhds.div_atTop (tendsto_pow_atTop hn))
#align real.tendsto_mul_exp_add_div_pow_at_top Real.tendsto_mul_exp_add_div_pow_atTop
/-- The function `(x ^ n) / (b * exp x + c)` tends to `0` at `+∞`, for any natural number
`n` and any real numbers `b` and `c` such that `b` is nonzero. -/
theorem tendsto_div_pow_mul_exp_add_atTop (b c : ℝ) (n : ℕ) (hb : 0 ≠ b) :
Tendsto (fun x => x ^ n / (b * exp x + c)) atTop (𝓝 0) := by
have H : ∀ d e, 0 < d → Tendsto (fun x : ℝ => x ^ n / (d * exp x + e)) atTop (𝓝 0) := by
intro b' c' h
convert (tendsto_mul_exp_add_div_pow_atTop b' c' n h).inv_tendsto_atTop using 1
ext x
simp
cases' lt_or_gt_of_ne hb with h h
· exact H b c h
· convert (H (-b) (-c) (neg_pos.mpr h)).neg using 1
· ext x
field_simp
rw [← neg_add (b * exp x) c, neg_div_neg_eq]
· rw [neg_zero]
#align real.tendsto_div_pow_mul_exp_add_at_top Real.tendsto_div_pow_mul_exp_add_atTop
/-- `Real.exp` as an order isomorphism between `ℝ` and `(0, +∞)`. -/
def expOrderIso : ℝ ≃o Ioi (0 : ℝ) :=
StrictMono.orderIsoOfSurjective _ (exp_strictMono.codRestrict exp_pos) <|
(continuous_exp.subtype_mk _).surjective
(by simp only [tendsto_Ioi_atTop, Subtype.coe_mk, tendsto_exp_atTop])
(by simp [tendsto_exp_atBot_nhdsWithin])
#align real.exp_order_iso Real.expOrderIso
@[simp]
theorem coe_expOrderIso_apply (x : ℝ) : (expOrderIso x : ℝ) = exp x :=
rfl
#align real.coe_exp_order_iso_apply Real.coe_expOrderIso_apply
@[simp]
theorem coe_comp_expOrderIso : (↑) ∘ expOrderIso = exp :=
rfl
#align real.coe_comp_exp_order_iso Real.coe_comp_expOrderIso
@[simp]
theorem range_exp : range exp = Set.Ioi 0 := by
rw [← coe_comp_expOrderIso, range_comp, expOrderIso.range_eq, image_univ, Subtype.range_coe]
#align real.range_exp Real.range_exp
@[simp]
theorem map_exp_atTop : map exp atTop = atTop := by
rw [← coe_comp_expOrderIso, ← Filter.map_map, OrderIso.map_atTop, map_val_Ioi_atTop]
#align real.map_exp_at_top Real.map_exp_atTop
@[simp]
theorem comap_exp_atTop : comap exp atTop = atTop := by
rw [← map_exp_atTop, comap_map exp_injective, map_exp_atTop]
#align real.comap_exp_at_top Real.comap_exp_atTop
@[simp]
theorem tendsto_exp_comp_atTop {f : α → ℝ} :
Tendsto (fun x => exp (f x)) l atTop ↔ Tendsto f l atTop := by
simp_rw [← comp_apply (f := exp), ← tendsto_comap_iff, comap_exp_atTop]
#align real.tendsto_exp_comp_at_top Real.tendsto_exp_comp_atTop
theorem tendsto_comp_exp_atTop {f : ℝ → α} :
Tendsto (fun x => f (exp x)) atTop l ↔ Tendsto f atTop l := by
simp_rw [← comp_apply (g := exp), ← tendsto_map'_iff, map_exp_atTop]
#align real.tendsto_comp_exp_at_top Real.tendsto_comp_exp_atTop
@[simp]
theorem map_exp_atBot : map exp atBot = 𝓝[>] 0 := by
rw [← coe_comp_expOrderIso, ← Filter.map_map, expOrderIso.map_atBot, ← map_coe_Ioi_atBot]
#align real.map_exp_at_bot Real.map_exp_atBot
@[simp]
theorem comap_exp_nhdsWithin_Ioi_zero : comap exp (𝓝[>] 0) = atBot := by
rw [← map_exp_atBot, comap_map exp_injective]
#align real.comap_exp_nhds_within_Ioi_zero Real.comap_exp_nhdsWithin_Ioi_zero
theorem tendsto_comp_exp_atBot {f : ℝ → α} :
Tendsto (fun x => f (exp x)) atBot l ↔ Tendsto f (𝓝[>] 0) l := by
rw [← map_exp_atBot, tendsto_map'_iff]
rfl
#align real.tendsto_comp_exp_at_bot Real.tendsto_comp_exp_atBot
@[simp]
theorem comap_exp_nhds_zero : comap exp (𝓝 0) = atBot :=
(comap_nhdsWithin_range exp 0).symm.trans <| by simp
#align real.comap_exp_nhds_zero Real.comap_exp_nhds_zero
@[simp]
theorem tendsto_exp_comp_nhds_zero {f : α → ℝ} :
Tendsto (fun x => exp (f x)) l (𝓝 0) ↔ Tendsto f l atBot := by
simp_rw [← comp_apply (f := exp), ← tendsto_comap_iff, comap_exp_nhds_zero]
#align real.tendsto_exp_comp_nhds_zero Real.tendsto_exp_comp_nhds_zero
-- Porting note (#10756): new lemma
theorem openEmbedding_exp : OpenEmbedding exp :=
isOpen_Ioi.openEmbedding_subtype_val.comp expOrderIso.toHomeomorph.openEmbedding
-- Porting note (#10756): new lemma;
-- Porting note (#11215): TODO: backport & make `@[simp]`
theorem map_exp_nhds (x : ℝ) : map exp (𝓝 x) = 𝓝 (exp x) :=
openEmbedding_exp.map_nhds_eq x
-- Porting note (#10756): new lemma;
-- Porting note (#11215): TODO: backport & make `@[simp]`
theorem comap_exp_nhds_exp (x : ℝ) : comap exp (𝓝 (exp x)) = 𝓝 x :=
(openEmbedding_exp.nhds_eq_comap x).symm
theorem isLittleO_pow_exp_atTop {n : ℕ} : (fun x : ℝ => x ^ n) =o[atTop] Real.exp := by
simpa [isLittleO_iff_tendsto fun x hx => ((exp_pos x).ne' hx).elim] using
tendsto_div_pow_mul_exp_add_atTop 1 0 n zero_ne_one
#align real.is_o_pow_exp_at_top Real.isLittleO_pow_exp_atTop
@[simp]
theorem isBigO_exp_comp_exp_comp {f g : α → ℝ} :
((fun x => exp (f x)) =O[l] fun x => exp (g x)) ↔ IsBoundedUnder (· ≤ ·) l (f - g) :=
Iff.trans (isBigO_iff_isBoundedUnder_le_div <| eventually_of_forall fun x => exp_ne_zero _) <| by
simp only [norm_eq_abs, abs_exp, ← exp_sub, isBoundedUnder_le_exp_comp, Pi.sub_def]
set_option linter.uppercaseLean3 false in
#align real.is_O_exp_comp_exp_comp Real.isBigO_exp_comp_exp_comp
@[simp]
theorem isTheta_exp_comp_exp_comp {f g : α → ℝ} :
((fun x => exp (f x)) =Θ[l] fun x => exp (g x)) ↔
IsBoundedUnder (· ≤ ·) l fun x => |f x - g x| := by
simp only [isBoundedUnder_le_abs, ← isBoundedUnder_le_neg, neg_sub, IsTheta,
isBigO_exp_comp_exp_comp, Pi.sub_def]
set_option linter.uppercaseLean3 false in
#align real.is_Theta_exp_comp_exp_comp Real.isTheta_exp_comp_exp_comp
@[simp]
theorem isLittleO_exp_comp_exp_comp {f g : α → ℝ} :
((fun x => exp (f x)) =o[l] fun x => exp (g x)) ↔ Tendsto (fun x => g x - f x) l atTop := by
simp only [isLittleO_iff_tendsto, exp_ne_zero, ← exp_sub, ← tendsto_neg_atTop_iff, false_imp_iff,
imp_true_iff, tendsto_exp_comp_nhds_zero, neg_sub]
#align real.is_o_exp_comp_exp_comp Real.isLittleO_exp_comp_exp_comp
-- Porting note (#10618): @[simp] can prove: by simp only [@Asymptotics.isLittleO_one_left_iff,
-- Real.norm_eq_abs, Real.abs_exp, @Real.tendsto_exp_comp_atTop]
theorem isLittleO_one_exp_comp {f : α → ℝ} :
((fun _ => 1 : α → ℝ) =o[l] fun x => exp (f x)) ↔ Tendsto f l atTop := by
simp only [← exp_zero, isLittleO_exp_comp_exp_comp, sub_zero]
#align real.is_o_one_exp_comp Real.isLittleO_one_exp_comp
/-- `Real.exp (f x)` is bounded away from zero along a filter if and only if this filter is bounded
from below under `f`. -/
@[simp]
theorem isBigO_one_exp_comp {f : α → ℝ} :
((fun _ => 1 : α → ℝ) =O[l] fun x => exp (f x)) ↔ IsBoundedUnder (· ≥ ·) l f := by
simp only [← exp_zero, isBigO_exp_comp_exp_comp, Pi.sub_def, zero_sub, isBoundedUnder_le_neg]
set_option linter.uppercaseLean3 false in
#align real.is_O_one_exp_comp Real.isBigO_one_exp_comp
/-- `Real.exp (f x)` is bounded away from zero along a filter if and only if this filter is bounded
from below under `f`. -/
theorem isBigO_exp_comp_one {f : α → ℝ} :
(fun x => exp (f x)) =O[l] (fun _ => 1 : α → ℝ) ↔ IsBoundedUnder (· ≤ ·) l f := by
simp only [isBigO_one_iff, norm_eq_abs, abs_exp, isBoundedUnder_le_exp_comp]
set_option linter.uppercaseLean3 false in
#align real.is_O_exp_comp_one Real.isBigO_exp_comp_one
/-- `Real.exp (f x)` is bounded away from zero and infinity along a filter `l` if and only if
`|f x|` is bounded from above along this filter. -/
@[simp]
theorem isTheta_exp_comp_one {f : α → ℝ} :
(fun x => exp (f x)) =Θ[l] (fun _ => 1 : α → ℝ) ↔ IsBoundedUnder (· ≤ ·) l fun x => |f x| := by
simp only [← exp_zero, isTheta_exp_comp_exp_comp, sub_zero]
set_option linter.uppercaseLean3 false in
#align real.is_Theta_exp_comp_one Real.isTheta_exp_comp_one
lemma summable_exp_nat_mul_iff {a : ℝ} :
Summable (fun n : ℕ ↦ exp (n * a)) ↔ a < 0 := by
simp only [exp_nat_mul, summable_geometric_iff_norm_lt_one, norm_of_nonneg (exp_nonneg _),
exp_lt_one_iff]
lemma summable_exp_neg_nat : Summable fun n : ℕ ↦ exp (-n) := by
simpa only [mul_neg_one] using summable_exp_nat_mul_iff.mpr neg_one_lt_zero
lemma summable_pow_mul_exp_neg_nat_mul (k : ℕ) {r : ℝ} (hr : 0 < r) :
Summable fun n : ℕ ↦ n ^ k * exp (-r * n) := by
simp_rw [mul_comm (-r), exp_nat_mul]
apply summable_pow_mul_geometric_of_norm_lt_one
rwa [norm_of_nonneg (exp_nonneg _), exp_lt_one_iff, neg_lt_zero]
end Real
open Real in
/-- If `f` has sum `a`, then `exp ∘ f` has product `exp a`. -/
lemma HasSum.rexp {ι} {f : ι → ℝ} {a : ℝ} (h : HasSum f a) : HasProd (rexp ∘ f) (rexp a) :=
Tendsto.congr (fun s ↦ exp_sum s f) <| Tendsto.rexp h
namespace Complex
@[simp]
theorem comap_exp_cobounded : comap exp (cobounded ℂ) = comap re atTop :=
calc
comap exp (cobounded ℂ) = comap re (comap Real.exp atTop) := by
simp only [← comap_norm_atTop, Complex.norm_eq_abs, comap_comap, (· ∘ ·), abs_exp]
_ = comap re atTop := by rw [Real.comap_exp_atTop]
#align complex.comap_exp_comap_abs_at_top Complex.comap_exp_cobounded
@[simp]
| Mathlib/Analysis/SpecialFunctions/Exp.lean | 493 | 497 | theorem comap_exp_nhds_zero : comap exp (𝓝 0) = comap re atBot :=
calc
comap exp (𝓝 0) = comap re (comap Real.exp (𝓝 0)) := by |
simp only [comap_comap, ← comap_abs_nhds_zero, (· ∘ ·), abs_exp]
_ = comap re atBot := by rw [Real.comap_exp_nhds_zero]
|
/-
Copyright (c) 2023 Peter Nelson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Peter Nelson
-/
import Mathlib.SetTheory.Cardinal.Finite
#align_import data.set.ncard from "leanprover-community/mathlib"@"74c2af38a828107941029b03839882c5c6f87a04"
/-!
# Noncomputable Set Cardinality
We define the cardinality of set `s` as a term `Set.encard s : ℕ∞` and a term `Set.ncard s : ℕ`.
The latter takes the junk value of zero if `s` is infinite. Both functions are noncomputable, and
are defined in terms of `PartENat.card` (which takes a type as its argument); this file can be seen
as an API for the same function in the special case where the type is a coercion of a `Set`,
allowing for smoother interactions with the `Set` API.
`Set.encard` never takes junk values, so is more mathematically natural than `Set.ncard`, even
though it takes values in a less convenient type. It is probably the right choice in settings where
one is concerned with the cardinalities of sets that may or may not be infinite.
`Set.ncard` has a nicer codomain, but when using it, `Set.Finite` hypotheses are normally needed to
make sure its values are meaningful. More generally, `Set.ncard` is intended to be used over the
obvious alternative `Finset.card` when finiteness is 'propositional' rather than 'structural'.
When working with sets that are finite by virtue of their definition, then `Finset.card` probably
makes more sense. One setting where `Set.ncard` works nicely is in a type `α` with `[Finite α]`,
where every set is automatically finite. In this setting, we use default arguments and a simple
tactic so that finiteness goals are discharged automatically in `Set.ncard` theorems.
## Main Definitions
* `Set.encard s` is the cardinality of the set `s` as an extended natural number, with value `⊤` if
`s` is infinite.
* `Set.ncard s` is the cardinality of the set `s` as a natural number, provided `s` is Finite.
If `s` is Infinite, then `Set.ncard s = 0`.
* `toFinite_tac` is a tactic that tries to synthesize a `Set.Finite s` argument with
`Set.toFinite`. This will work for `s : Set α` where there is a `Finite α` instance.
## Implementation Notes
The theorems in this file are very similar to those in `Data.Finset.Card`, but with `Set` operations
instead of `Finset`. We first prove all the theorems for `Set.encard`, and then derive most of the
`Set.ncard` results as a consequence. Things are done this way to avoid reliance on the `Finset` API
for theorems about infinite sets, and to allow for a refactor that removes or modifies `Set.ncard`
in the future.
Nearly all the theorems for `Set.ncard` require finiteness of one or more of their arguments. We
provide this assumption with a default argument of the form `(hs : s.Finite := by toFinite_tac)`,
where `toFinite_tac` will find an `s.Finite` term in the cases where `s` is a set in a `Finite`
type.
Often, where there are two set arguments `s` and `t`, the finiteness of one follows from the other
in the context of the theorem, in which case we only include the ones that are needed, and derive
the other inside the proof. A few of the theorems, such as `ncard_union_le` do not require
finiteness arguments; they are true by coincidence due to junk values.
-/
namespace Set
variable {α β : Type*} {s t : Set α}
/-- The cardinality of a set as a term in `ℕ∞` -/
noncomputable def encard (s : Set α) : ℕ∞ := PartENat.withTopEquiv (PartENat.card s)
@[simp] theorem encard_univ_coe (s : Set α) : encard (univ : Set s) = encard s := by
rw [encard, encard, PartENat.card_congr (Equiv.Set.univ ↑s)]
theorem encard_univ (α : Type*) :
encard (univ : Set α) = PartENat.withTopEquiv (PartENat.card α) := by
rw [encard, PartENat.card_congr (Equiv.Set.univ α)]
theorem Finite.encard_eq_coe_toFinset_card (h : s.Finite) : s.encard = h.toFinset.card := by
have := h.fintype
rw [encard, PartENat.card_eq_coe_fintype_card,
PartENat.withTopEquiv_natCast, toFinite_toFinset, toFinset_card]
theorem encard_eq_coe_toFinset_card (s : Set α) [Fintype s] : encard s = s.toFinset.card := by
have h := toFinite s
rw [h.encard_eq_coe_toFinset_card, toFinite_toFinset]
theorem encard_coe_eq_coe_finsetCard (s : Finset α) : encard (s : Set α) = s.card := by
rw [Finite.encard_eq_coe_toFinset_card (Finset.finite_toSet s)]; simp
theorem Infinite.encard_eq {s : Set α} (h : s.Infinite) : s.encard = ⊤ := by
have := h.to_subtype
rw [encard, ← PartENat.withTopEquiv.symm.injective.eq_iff, Equiv.symm_apply_apply,
PartENat.withTopEquiv_symm_top, PartENat.card_eq_top_of_infinite]
@[simp] theorem encard_eq_zero : s.encard = 0 ↔ s = ∅ := by
rw [encard, ← PartENat.withTopEquiv.symm.injective.eq_iff, Equiv.symm_apply_apply,
PartENat.withTopEquiv_symm_zero, PartENat.card_eq_zero_iff_empty, isEmpty_subtype,
eq_empty_iff_forall_not_mem]
@[simp] theorem encard_empty : (∅ : Set α).encard = 0 := by
rw [encard_eq_zero]
theorem nonempty_of_encard_ne_zero (h : s.encard ≠ 0) : s.Nonempty := by
rwa [nonempty_iff_ne_empty, Ne, ← encard_eq_zero]
theorem encard_ne_zero : s.encard ≠ 0 ↔ s.Nonempty := by
rw [ne_eq, encard_eq_zero, nonempty_iff_ne_empty]
@[simp] theorem encard_pos : 0 < s.encard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, encard_ne_zero]
@[simp] theorem encard_singleton (e : α) : ({e} : Set α).encard = 1 := by
rw [encard, ← PartENat.withTopEquiv.symm.injective.eq_iff, Equiv.symm_apply_apply,
PartENat.card_eq_coe_fintype_card, Fintype.card_ofSubsingleton, Nat.cast_one]; rfl
theorem encard_union_eq (h : Disjoint s t) : (s ∪ t).encard = s.encard + t.encard := by
classical
have e := (Equiv.Set.union (by rwa [subset_empty_iff, ← disjoint_iff_inter_eq_empty])).symm
simp [encard, ← PartENat.card_congr e, PartENat.card_sum, PartENat.withTopEquiv]
theorem encard_insert_of_not_mem {a : α} (has : a ∉ s) : (insert a s).encard = s.encard + 1 := by
rw [← union_singleton, encard_union_eq (by simpa), encard_singleton]
theorem Finite.encard_lt_top (h : s.Finite) : s.encard < ⊤ := by
refine h.induction_on (by simp) ?_
rintro a t hat _ ht'
rw [encard_insert_of_not_mem hat]
exact lt_tsub_iff_right.1 ht'
theorem Finite.encard_eq_coe (h : s.Finite) : s.encard = ENat.toNat s.encard :=
(ENat.coe_toNat h.encard_lt_top.ne).symm
theorem Finite.exists_encard_eq_coe (h : s.Finite) : ∃ (n : ℕ), s.encard = n :=
⟨_, h.encard_eq_coe⟩
@[simp] theorem encard_lt_top_iff : s.encard < ⊤ ↔ s.Finite :=
⟨fun h ↦ by_contra fun h' ↦ h.ne (Infinite.encard_eq h'), Finite.encard_lt_top⟩
@[simp] theorem encard_eq_top_iff : s.encard = ⊤ ↔ s.Infinite := by
rw [← not_iff_not, ← Ne, ← lt_top_iff_ne_top, encard_lt_top_iff, not_infinite]
theorem encard_ne_top_iff : s.encard ≠ ⊤ ↔ s.Finite := by
simp
theorem finite_of_encard_le_coe {k : ℕ} (h : s.encard ≤ k) : s.Finite := by
rw [← encard_lt_top_iff]; exact h.trans_lt (WithTop.coe_lt_top _)
theorem finite_of_encard_eq_coe {k : ℕ} (h : s.encard = k) : s.Finite :=
finite_of_encard_le_coe h.le
theorem encard_le_coe_iff {k : ℕ} : s.encard ≤ k ↔ s.Finite ∧ ∃ (n₀ : ℕ), s.encard = n₀ ∧ n₀ ≤ k :=
⟨fun h ↦ ⟨finite_of_encard_le_coe h, by rwa [ENat.le_coe_iff] at h⟩,
fun ⟨_,⟨n₀,hs, hle⟩⟩ ↦ by rwa [hs, Nat.cast_le]⟩
section Lattice
theorem encard_le_card (h : s ⊆ t) : s.encard ≤ t.encard := by
rw [← union_diff_cancel h, encard_union_eq disjoint_sdiff_right]; exact le_self_add
theorem encard_mono {α : Type*} : Monotone (encard : Set α → ℕ∞) :=
fun _ _ ↦ encard_le_card
theorem encard_diff_add_encard_of_subset (h : s ⊆ t) : (t \ s).encard + s.encard = t.encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self, union_eq_self_of_subset_right h]
@[simp] theorem one_le_encard_iff_nonempty : 1 ≤ s.encard ↔ s.Nonempty := by
rw [nonempty_iff_ne_empty, Ne, ← encard_eq_zero, ENat.one_le_iff_ne_zero]
theorem encard_diff_add_encard_inter (s t : Set α) :
(s \ t).encard + (s ∩ t).encard = s.encard := by
rw [← encard_union_eq (disjoint_of_subset_right inter_subset_right disjoint_sdiff_left),
diff_union_inter]
theorem encard_union_add_encard_inter (s t : Set α) :
(s ∪ t).encard + (s ∩ t).encard = s.encard + t.encard := by
rw [← diff_union_self, encard_union_eq disjoint_sdiff_left, add_right_comm,
encard_diff_add_encard_inter]
theorem encard_eq_encard_iff_encard_diff_eq_encard_diff (h : (s ∩ t).Finite) :
s.encard = t.encard ↔ (s \ t).encard = (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_right_cancel_iff h.encard_lt_top.ne]
theorem encard_le_encard_iff_encard_diff_le_encard_diff (h : (s ∩ t).Finite) :
s.encard ≤ t.encard ↔ (s \ t).encard ≤ (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_le_add_iff_right h.encard_lt_top.ne]
theorem encard_lt_encard_iff_encard_diff_lt_encard_diff (h : (s ∩ t).Finite) :
s.encard < t.encard ↔ (s \ t).encard < (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_lt_add_iff_right h.encard_lt_top.ne]
theorem encard_union_le (s t : Set α) : (s ∪ t).encard ≤ s.encard + t.encard := by
rw [← encard_union_add_encard_inter]; exact le_self_add
theorem finite_iff_finite_of_encard_eq_encard (h : s.encard = t.encard) : s.Finite ↔ t.Finite := by
rw [← encard_lt_top_iff, ← encard_lt_top_iff, h]
theorem infinite_iff_infinite_of_encard_eq_encard (h : s.encard = t.encard) :
s.Infinite ↔ t.Infinite := by rw [← encard_eq_top_iff, h, encard_eq_top_iff]
theorem Finite.finite_of_encard_le {s : Set α} {t : Set β} (hs : s.Finite)
(h : t.encard ≤ s.encard) : t.Finite :=
encard_lt_top_iff.1 (h.trans_lt hs.encard_lt_top)
theorem Finite.eq_of_subset_of_encard_le (ht : t.Finite) (hst : s ⊆ t) (hts : t.encard ≤ s.encard) :
s = t := by
rw [← zero_add (a := encard s), ← encard_diff_add_encard_of_subset hst] at hts
have hdiff := WithTop.le_of_add_le_add_right (ht.subset hst).encard_lt_top.ne hts
rw [nonpos_iff_eq_zero, encard_eq_zero, diff_eq_empty] at hdiff
exact hst.antisymm hdiff
theorem Finite.eq_of_subset_of_encard_le' (hs : s.Finite) (hst : s ⊆ t)
(hts : t.encard ≤ s.encard) : s = t :=
(hs.finite_of_encard_le hts).eq_of_subset_of_encard_le hst hts
theorem Finite.encard_lt_encard (ht : t.Finite) (h : s ⊂ t) : s.encard < t.encard :=
(encard_mono h.subset).lt_of_ne (fun he ↦ h.ne (ht.eq_of_subset_of_encard_le h.subset he.symm.le))
theorem encard_strictMono [Finite α] : StrictMono (encard : Set α → ℕ∞) :=
fun _ _ h ↦ (toFinite _).encard_lt_encard h
theorem encard_diff_add_encard (s t : Set α) : (s \ t).encard + t.encard = (s ∪ t).encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self]
theorem encard_le_encard_diff_add_encard (s t : Set α) : s.encard ≤ (s \ t).encard + t.encard :=
(encard_mono subset_union_left).trans_eq (encard_diff_add_encard _ _).symm
theorem tsub_encard_le_encard_diff (s t : Set α) : s.encard - t.encard ≤ (s \ t).encard := by
rw [tsub_le_iff_left, add_comm]; apply encard_le_encard_diff_add_encard
theorem encard_add_encard_compl (s : Set α) : s.encard + sᶜ.encard = (univ : Set α).encard := by
rw [← encard_union_eq disjoint_compl_right, union_compl_self]
end Lattice
section InsertErase
variable {a b : α}
theorem encard_insert_le (s : Set α) (x : α) : (insert x s).encard ≤ s.encard + 1 := by
rw [← union_singleton, ← encard_singleton x]; apply encard_union_le
theorem encard_singleton_inter (s : Set α) (x : α) : ({x} ∩ s).encard ≤ 1 := by
rw [← encard_singleton x]; exact encard_le_card inter_subset_left
theorem encard_diff_singleton_add_one (h : a ∈ s) :
(s \ {a}).encard + 1 = s.encard := by
rw [← encard_insert_of_not_mem (fun h ↦ h.2 rfl), insert_diff_singleton, insert_eq_of_mem h]
theorem encard_diff_singleton_of_mem (h : a ∈ s) :
(s \ {a}).encard = s.encard - 1 := by
rw [← encard_diff_singleton_add_one h, ← WithTop.add_right_cancel_iff WithTop.one_ne_top,
tsub_add_cancel_of_le (self_le_add_left _ _)]
theorem encard_tsub_one_le_encard_diff_singleton (s : Set α) (x : α) :
s.encard - 1 ≤ (s \ {x}).encard := by
rw [← encard_singleton x]; apply tsub_encard_le_encard_diff
theorem encard_exchange (ha : a ∉ s) (hb : b ∈ s) : (insert a (s \ {b})).encard = s.encard := by
rw [encard_insert_of_not_mem, encard_diff_singleton_add_one hb]
simp_all only [not_true, mem_diff, mem_singleton_iff, false_and, not_false_eq_true]
theorem encard_exchange' (ha : a ∉ s) (hb : b ∈ s) : (insert a s \ {b}).encard = s.encard := by
rw [← insert_diff_singleton_comm (by rintro rfl; exact ha hb), encard_exchange ha hb]
theorem encard_eq_add_one_iff {k : ℕ∞} :
s.encard = k + 1 ↔ (∃ a t, ¬a ∈ t ∧ insert a t = s ∧ t.encard = k) := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, ha⟩ := nonempty_of_encard_ne_zero (s := s) (by simp [h])
refine ⟨a, s \ {a}, fun h ↦ h.2 rfl, by rwa [insert_diff_singleton, insert_eq_of_mem], ?_⟩
rw [← WithTop.add_right_cancel_iff WithTop.one_ne_top, ← h,
encard_diff_singleton_add_one ha]
rintro ⟨a, t, h, rfl, rfl⟩
rw [encard_insert_of_not_mem h]
/-- Every set is either empty, infinite, or can have its `encard` reduced by a removal. Intended
for well-founded induction on the value of `encard`. -/
theorem eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt (s : Set α) :
s = ∅ ∨ s.encard = ⊤ ∨ ∃ a ∈ s, (s \ {a}).encard < s.encard := by
refine s.eq_empty_or_nonempty.elim Or.inl (Or.inr ∘ fun ⟨a,ha⟩ ↦
(s.finite_or_infinite.elim (fun hfin ↦ Or.inr ⟨a, ha, ?_⟩) (Or.inl ∘ Infinite.encard_eq)))
rw [← encard_diff_singleton_add_one ha]; nth_rw 1 [← add_zero (encard _)]
exact WithTop.add_lt_add_left (hfin.diff _).encard_lt_top.ne zero_lt_one
end InsertErase
section SmallSets
theorem encard_pair {x y : α} (hne : x ≠ y) : ({x, y} : Set α).encard = 2 := by
rw [encard_insert_of_not_mem (by simpa), ← one_add_one_eq_two,
WithTop.add_right_cancel_iff WithTop.one_ne_top, encard_singleton]
theorem encard_eq_one : s.encard = 1 ↔ ∃ x, s = {x} := by
refine ⟨fun h ↦ ?_, fun ⟨x, hx⟩ ↦ by rw [hx, encard_singleton]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
exact ⟨x, ((finite_singleton x).eq_of_subset_of_encard_le' (by simpa) (by simp [h])).symm⟩
theorem encard_le_one_iff_eq : s.encard ≤ 1 ↔ s = ∅ ∨ ∃ x, s = {x} := by
rw [le_iff_lt_or_eq, lt_iff_not_le, ENat.one_le_iff_ne_zero, not_not, encard_eq_zero,
encard_eq_one]
theorem encard_le_one_iff : s.encard ≤ 1 ↔ ∀ a b, a ∈ s → b ∈ s → a = b := by
rw [encard_le_one_iff_eq, or_iff_not_imp_left, ← Ne, ← nonempty_iff_ne_empty]
refine ⟨fun h a b has hbs ↦ ?_,
fun h ⟨x, hx⟩ ↦ ⟨x, ((singleton_subset_iff.2 hx).antisymm' (fun y hy ↦ h _ _ hy hx))⟩⟩
obtain ⟨x, rfl⟩ := h ⟨_, has⟩
rw [(has : a = x), (hbs : b = x)]
theorem one_lt_encard_iff : 1 < s.encard ↔ ∃ a b, a ∈ s ∧ b ∈ s ∧ a ≠ b := by
rw [← not_iff_not, not_exists, not_lt, encard_le_one_iff]; aesop
theorem exists_ne_of_one_lt_encard (h : 1 < s.encard) (a : α) : ∃ b ∈ s, b ≠ a := by
by_contra! h'
obtain ⟨b, b', hb, hb', hne⟩ := one_lt_encard_iff.1 h
apply hne
rw [h' b hb, h' b' hb']
theorem encard_eq_two : s.encard = 2 ↔ ∃ x y, x ≠ y ∧ s = {x, y} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, hne, hs⟩ ↦ by rw [hs, encard_pair hne]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton, encard_insert_of_not_mem (fun h ↦ h.2 rfl),
← one_add_one_eq_two, WithTop.add_right_cancel_iff (WithTop.one_ne_top), encard_eq_one] at h
obtain ⟨y, h⟩ := h
refine ⟨x, y, by rintro rfl; exact (h.symm.subset rfl).2 rfl, ?_⟩
rw [← h, insert_diff_singleton, insert_eq_of_mem hx]
theorem encard_eq_three {α : Type u_1} {s : Set α} :
encard s = 3 ↔ ∃ x y z, x ≠ y ∧ x ≠ z ∧ y ≠ z ∧ s = {x, y, z} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, z, hxy, hyz, hxz, hs⟩ ↦ ?_⟩
· obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton,
encard_insert_of_not_mem (fun h ↦ h.2 rfl), (by exact rfl : (3 : ℕ∞) = 2 + 1),
WithTop.add_right_cancel_iff WithTop.one_ne_top, encard_eq_two] at h
obtain ⟨y, z, hne, hs⟩ := h
refine ⟨x, y, z, ?_, ?_, hne, ?_⟩
· rintro rfl; exact (hs.symm.subset (Or.inl rfl)).2 rfl
· rintro rfl; exact (hs.symm.subset (Or.inr rfl)).2 rfl
rw [← hs, insert_diff_singleton, insert_eq_of_mem hx]
rw [hs, encard_insert_of_not_mem, encard_insert_of_not_mem, encard_singleton] <;> aesop
theorem Nat.encard_range (k : ℕ) : {i | i < k}.encard = k := by
convert encard_coe_eq_coe_finsetCard (Finset.range k) using 1
· rw [Finset.coe_range, Iio_def]
rw [Finset.card_range]
end SmallSets
theorem Finite.eq_insert_of_subset_of_encard_eq_succ (hs : s.Finite) (h : s ⊆ t)
(hst : t.encard = s.encard + 1) : ∃ a, t = insert a s := by
rw [← encard_diff_add_encard_of_subset h, add_comm,
WithTop.add_left_cancel_iff hs.encard_lt_top.ne, encard_eq_one] at hst
obtain ⟨x, hx⟩ := hst; use x; rw [← diff_union_of_subset h, hx, singleton_union]
theorem exists_subset_encard_eq {k : ℕ∞} (hk : k ≤ s.encard) : ∃ t, t ⊆ s ∧ t.encard = k := by
revert hk
refine ENat.nat_induction k (fun _ ↦ ⟨∅, empty_subset _, by simp⟩) (fun n IH hle ↦ ?_) ?_
· obtain ⟨t₀, ht₀s, ht₀⟩ := IH (le_trans (by simp) hle)
simp only [Nat.cast_succ] at *
have hne : t₀ ≠ s := by
rintro rfl; rw [ht₀, ← Nat.cast_one, ← Nat.cast_add, Nat.cast_le] at hle; simp at hle
obtain ⟨x, hx⟩ := exists_of_ssubset (ht₀s.ssubset_of_ne hne)
exact ⟨insert x t₀, insert_subset hx.1 ht₀s, by rw [encard_insert_of_not_mem hx.2, ht₀]⟩
simp only [top_le_iff, encard_eq_top_iff]
exact fun _ hi ↦ ⟨s, Subset.rfl, hi⟩
theorem exists_superset_subset_encard_eq {k : ℕ∞}
(hst : s ⊆ t) (hsk : s.encard ≤ k) (hkt : k ≤ t.encard) :
∃ r, s ⊆ r ∧ r ⊆ t ∧ r.encard = k := by
obtain (hs | hs) := eq_or_ne s.encard ⊤
· rw [hs, top_le_iff] at hsk; subst hsk; exact ⟨s, Subset.rfl, hst, hs⟩
obtain ⟨k, rfl⟩ := exists_add_of_le hsk
obtain ⟨k', hk'⟩ := exists_add_of_le hkt
have hk : k ≤ encard (t \ s) := by
rw [← encard_diff_add_encard_of_subset hst, add_comm] at hkt
exact WithTop.le_of_add_le_add_right hs hkt
obtain ⟨r', hr', rfl⟩ := exists_subset_encard_eq hk
refine ⟨s ∪ r', subset_union_left, union_subset hst (hr'.trans diff_subset), ?_⟩
rw [encard_union_eq (disjoint_of_subset_right hr' disjoint_sdiff_right)]
section Function
variable {s : Set α} {t : Set β} {f : α → β}
theorem InjOn.encard_image (h : InjOn f s) : (f '' s).encard = s.encard := by
rw [encard, PartENat.card_image_of_injOn h, encard]
theorem encard_congr (e : s ≃ t) : s.encard = t.encard := by
rw [← encard_univ_coe, ← encard_univ_coe t, encard_univ, encard_univ, PartENat.card_congr e]
theorem _root_.Function.Injective.encard_image (hf : f.Injective) (s : Set α) :
(f '' s).encard = s.encard :=
hf.injOn.encard_image
theorem _root_.Function.Embedding.enccard_le (e : s ↪ t) : s.encard ≤ t.encard := by
rw [← encard_univ_coe, ← e.injective.encard_image, ← Subtype.coe_injective.encard_image]
exact encard_mono (by simp)
| Mathlib/Data/Set/Card.lean | 395 | 400 | theorem encard_image_le (f : α → β) (s : Set α) : (f '' s).encard ≤ s.encard := by |
obtain (h | h) := isEmpty_or_nonempty α
· rw [s.eq_empty_of_isEmpty]; simp
rw [← (f.invFunOn_injOn_image s).encard_image]
apply encard_le_card
exact f.invFunOn_image_image_subset s
|
/-
Copyright (c) 2023 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.JapaneseBracket
import Mathlib.Analysis.SpecialFunctions.Integrals
import Mathlib.MeasureTheory.Group.Integral
import Mathlib.MeasureTheory.Integral.IntegralEqImproper
import Mathlib.MeasureTheory.Measure.Lebesgue.Integral
#align_import analysis.special_functions.improper_integrals from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Evaluation of specific improper integrals
This file contains some integrability results, and evaluations of integrals, over `ℝ` or over
half-infinite intervals in `ℝ`.
## See also
- `Mathlib.Analysis.SpecialFunctions.Integrals` -- integrals over finite intervals
- `Mathlib.Analysis.SpecialFunctions.Gaussian` -- integral of `exp (-x ^ 2)`
- `Mathlib.Analysis.SpecialFunctions.JapaneseBracket`-- integrability of `(1+‖x‖)^(-r)`.
-/
open Real Set Filter MeasureTheory intervalIntegral
open scoped Topology
theorem integrableOn_exp_Iic (c : ℝ) : IntegrableOn exp (Iic c) := by
refine
integrableOn_Iic_of_intervalIntegral_norm_bounded (exp c) c
(fun y => intervalIntegrable_exp.1) tendsto_id
(eventually_of_mem (Iic_mem_atBot 0) fun y _ => ?_)
simp_rw [norm_of_nonneg (exp_pos _).le, integral_exp, sub_le_self_iff]
exact (exp_pos _).le
#align integrable_on_exp_Iic integrableOn_exp_Iic
theorem integral_exp_Iic (c : ℝ) : ∫ x : ℝ in Iic c, exp x = exp c := by
refine
tendsto_nhds_unique
(intervalIntegral_tendsto_integral_Iic _ (integrableOn_exp_Iic _) tendsto_id) ?_
simp_rw [integral_exp, show 𝓝 (exp c) = 𝓝 (exp c - 0) by rw [sub_zero]]
exact tendsto_exp_atBot.const_sub _
#align integral_exp_Iic integral_exp_Iic
theorem integral_exp_Iic_zero : ∫ x : ℝ in Iic 0, exp x = 1 :=
exp_zero ▸ integral_exp_Iic 0
#align integral_exp_Iic_zero integral_exp_Iic_zero
theorem integral_exp_neg_Ioi (c : ℝ) : (∫ x : ℝ in Ioi c, exp (-x)) = exp (-c) := by
simpa only [integral_comp_neg_Ioi] using integral_exp_Iic (-c)
#align integral_exp_neg_Ioi integral_exp_neg_Ioi
theorem integral_exp_neg_Ioi_zero : (∫ x : ℝ in Ioi 0, exp (-x)) = 1 := by
simpa only [neg_zero, exp_zero] using integral_exp_neg_Ioi 0
#align integral_exp_neg_Ioi_zero integral_exp_neg_Ioi_zero
/-- If `0 < c`, then `(fun t : ℝ ↦ t ^ a)` is integrable on `(c, ∞)` for all `a < -1`. -/
theorem integrableOn_Ioi_rpow_of_lt {a : ℝ} (ha : a < -1) {c : ℝ} (hc : 0 < c) :
IntegrableOn (fun t : ℝ => t ^ a) (Ioi c) := by
have hd : ∀ x ∈ Ici c, HasDerivAt (fun t => t ^ (a + 1) / (a + 1)) (x ^ a) x := by
intro x hx
-- Porting note: helped `convert` with explicit arguments
convert (hasDerivAt_rpow_const (p := a + 1) (Or.inl (hc.trans_le hx).ne')).div_const _ using 1
field_simp [show a + 1 ≠ 0 from ne_of_lt (by linarith), mul_comm]
have ht : Tendsto (fun t => t ^ (a + 1) / (a + 1)) atTop (𝓝 (0 / (a + 1))) := by
apply Tendsto.div_const
simpa only [neg_neg] using tendsto_rpow_neg_atTop (by linarith : 0 < -(a + 1))
exact
integrableOn_Ioi_deriv_of_nonneg' hd (fun t ht => rpow_nonneg (hc.trans ht).le a) ht
#align integrable_on_Ioi_rpow_of_lt integrableOn_Ioi_rpow_of_lt
theorem integrableOn_Ioi_rpow_iff {s t : ℝ} (ht : 0 < t) :
IntegrableOn (fun x ↦ x ^ s) (Ioi t) ↔ s < -1 := by
refine ⟨fun h ↦ ?_, fun h ↦ integrableOn_Ioi_rpow_of_lt h ht⟩
contrapose! h
intro H
have H' : IntegrableOn (fun x ↦ x ^ s) (Ioi (max 1 t)) :=
H.mono (Set.Ioi_subset_Ioi (le_max_right _ _)) le_rfl
have : IntegrableOn (fun x ↦ x⁻¹) (Ioi (max 1 t)) := by
apply H'.mono' measurable_inv.aestronglyMeasurable
filter_upwards [ae_restrict_mem measurableSet_Ioi] with x hx
have x_one : 1 ≤ x := ((le_max_left _ _).trans_lt (mem_Ioi.1 hx)).le
simp only [norm_inv, Real.norm_eq_abs, abs_of_nonneg (zero_le_one.trans x_one)]
rw [← Real.rpow_neg_one x]
exact Real.rpow_le_rpow_of_exponent_le x_one h
exact not_IntegrableOn_Ioi_inv this
/-- The real power function with any exponent is not integrable on `(0, +∞)`. -/
theorem not_integrableOn_Ioi_rpow (s : ℝ) : ¬ IntegrableOn (fun x ↦ x ^ s) (Ioi (0 : ℝ)) := by
intro h
rcases le_or_lt s (-1) with hs|hs
· have : IntegrableOn (fun x ↦ x ^ s) (Ioo (0 : ℝ) 1) := h.mono Ioo_subset_Ioi_self le_rfl
rw [integrableOn_Ioo_rpow_iff zero_lt_one] at this
exact hs.not_lt this
· have : IntegrableOn (fun x ↦ x ^ s) (Ioi (1 : ℝ)) := h.mono (Ioi_subset_Ioi zero_le_one) le_rfl
rw [integrableOn_Ioi_rpow_iff zero_lt_one] at this
exact hs.not_lt this
theorem setIntegral_Ioi_zero_rpow (s : ℝ) : ∫ x in Ioi (0 : ℝ), x ^ s = 0 :=
MeasureTheory.integral_undef (not_integrableOn_Ioi_rpow s)
theorem integral_Ioi_rpow_of_lt {a : ℝ} (ha : a < -1) {c : ℝ} (hc : 0 < c) :
∫ t : ℝ in Ioi c, t ^ a = -c ^ (a + 1) / (a + 1) := by
have hd : ∀ x ∈ Ici c, HasDerivAt (fun t => t ^ (a + 1) / (a + 1)) (x ^ a) x := by
intro x hx
convert (hasDerivAt_rpow_const (p := a + 1) (Or.inl (hc.trans_le hx).ne')).div_const _ using 1
field_simp [show a + 1 ≠ 0 from ne_of_lt (by linarith), mul_comm]
have ht : Tendsto (fun t => t ^ (a + 1) / (a + 1)) atTop (𝓝 (0 / (a + 1))) := by
apply Tendsto.div_const
simpa only [neg_neg] using tendsto_rpow_neg_atTop (by linarith : 0 < -(a + 1))
convert integral_Ioi_of_hasDerivAt_of_tendsto' hd (integrableOn_Ioi_rpow_of_lt ha hc) ht using 1
simp only [neg_div, zero_div, zero_sub]
#align integral_Ioi_rpow_of_lt integral_Ioi_rpow_of_lt
theorem integrableOn_Ioi_cpow_of_lt {a : ℂ} (ha : a.re < -1) {c : ℝ} (hc : 0 < c) :
IntegrableOn (fun t : ℝ => (t : ℂ) ^ a) (Ioi c) := by
rw [IntegrableOn, ← integrable_norm_iff, ← IntegrableOn]
· refine (integrableOn_Ioi_rpow_of_lt ha hc).congr_fun (fun x hx => ?_) measurableSet_Ioi
· dsimp only
rw [Complex.norm_eq_abs, Complex.abs_cpow_eq_rpow_re_of_pos (hc.trans hx)]
· refine ContinuousOn.aestronglyMeasurable (fun t ht => ?_) measurableSet_Ioi
exact
(Complex.continuousAt_ofReal_cpow_const _ _ (Or.inr (hc.trans ht).ne')).continuousWithinAt
#align integrable_on_Ioi_cpow_of_lt integrableOn_Ioi_cpow_of_lt
theorem integrableOn_Ioi_cpow_iff {s : ℂ} {t : ℝ} (ht : 0 < t) :
IntegrableOn (fun x : ℝ ↦ (x : ℂ) ^ s) (Ioi t) ↔ s.re < -1 := by
refine ⟨fun h ↦ ?_, fun h ↦ integrableOn_Ioi_cpow_of_lt h ht⟩
have B : IntegrableOn (fun a ↦ a ^ s.re) (Ioi t) := by
apply (integrableOn_congr_fun _ measurableSet_Ioi).1 h.norm
intro a ha
have : 0 < a := ht.trans ha
simp [Complex.abs_cpow_eq_rpow_re_of_pos this]
rwa [integrableOn_Ioi_rpow_iff ht] at B
/-- The complex power function with any exponent is not integrable on `(0, +∞)`. -/
theorem not_integrableOn_Ioi_cpow (s : ℂ) :
¬ IntegrableOn (fun x : ℝ ↦ (x : ℂ) ^ s) (Ioi (0 : ℝ)) := by
intro h
rcases le_or_lt s.re (-1) with hs|hs
· have : IntegrableOn (fun x : ℝ ↦ (x : ℂ) ^ s) (Ioo (0 : ℝ) 1) :=
h.mono Ioo_subset_Ioi_self le_rfl
rw [integrableOn_Ioo_cpow_iff zero_lt_one] at this
exact hs.not_lt this
· have : IntegrableOn (fun x : ℝ ↦ (x : ℂ) ^ s) (Ioi 1) :=
h.mono (Ioi_subset_Ioi zero_le_one) le_rfl
rw [integrableOn_Ioi_cpow_iff zero_lt_one] at this
exact hs.not_lt this
theorem setIntegral_Ioi_zero_cpow (s : ℂ) : ∫ x in Ioi (0 : ℝ), (x : ℂ) ^ s = 0 :=
MeasureTheory.integral_undef (not_integrableOn_Ioi_cpow s)
| Mathlib/Analysis/SpecialFunctions/ImproperIntegrals.lean | 157 | 179 | theorem integral_Ioi_cpow_of_lt {a : ℂ} (ha : a.re < -1) {c : ℝ} (hc : 0 < c) :
(∫ t : ℝ in Ioi c, (t : ℂ) ^ a) = -(c : ℂ) ^ (a + 1) / (a + 1) := by |
refine
tendsto_nhds_unique
(intervalIntegral_tendsto_integral_Ioi c (integrableOn_Ioi_cpow_of_lt ha hc) tendsto_id) ?_
suffices
Tendsto (fun x : ℝ => ((x : ℂ) ^ (a + 1) - (c : ℂ) ^ (a + 1)) / (a + 1)) atTop
(𝓝 <| -c ^ (a + 1) / (a + 1)) by
refine this.congr' ((eventually_gt_atTop 0).mp (eventually_of_forall fun x hx => ?_))
dsimp only
rw [integral_cpow, id]
refine Or.inr ⟨?_, not_mem_uIcc_of_lt hc hx⟩
apply_fun Complex.re
rw [Complex.neg_re, Complex.one_re]
exact ha.ne
simp_rw [← zero_sub, sub_div]
refine (Tendsto.div_const ?_ _).sub_const _
rw [tendsto_zero_iff_norm_tendsto_zero]
refine
(tendsto_rpow_neg_atTop (by linarith : 0 < -(a.re + 1))).congr'
((eventually_gt_atTop 0).mp (eventually_of_forall fun x hx => ?_))
simp_rw [neg_neg, Complex.norm_eq_abs, Complex.abs_cpow_eq_rpow_re_of_pos hx, Complex.add_re,
Complex.one_re]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.Ring.Prod
import Mathlib.GroupTheory.OrderOfElement
import Mathlib.Tactic.FinCases
#align_import data.zmod.basic from "leanprover-community/mathlib"@"74ad1c88c77e799d2fea62801d1dbbd698cff1b7"
/-!
# Integers mod `n`
Definition of the integers mod n, and the field structure on the integers mod p.
## Definitions
* `ZMod n`, which is for integers modulo a nat `n : ℕ`
* `val a` is defined as a natural number:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
* `valMinAbs` returns the integer closest to zero in the equivalence class.
* A coercion `cast` is defined from `ZMod n` into any ring.
This is a ring hom if the ring has characteristic dividing `n`
-/
assert_not_exists Submodule
open Function
namespace ZMod
instance charZero : CharZero (ZMod 0) := inferInstanceAs (CharZero ℤ)
/-- `val a` is a natural number defined as:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
See `ZMod.valMinAbs` for a variant that takes values in the integers.
-/
def val : ∀ {n : ℕ}, ZMod n → ℕ
| 0 => Int.natAbs
| n + 1 => ((↑) : Fin (n + 1) → ℕ)
#align zmod.val ZMod.val
theorem val_lt {n : ℕ} [NeZero n] (a : ZMod n) : a.val < n := by
cases n
· cases NeZero.ne 0 rfl
exact Fin.is_lt a
#align zmod.val_lt ZMod.val_lt
theorem val_le {n : ℕ} [NeZero n] (a : ZMod n) : a.val ≤ n :=
a.val_lt.le
#align zmod.val_le ZMod.val_le
@[simp]
theorem val_zero : ∀ {n}, (0 : ZMod n).val = 0
| 0 => rfl
| _ + 1 => rfl
#align zmod.val_zero ZMod.val_zero
@[simp]
theorem val_one' : (1 : ZMod 0).val = 1 :=
rfl
#align zmod.val_one' ZMod.val_one'
@[simp]
theorem val_neg' {n : ZMod 0} : (-n).val = n.val :=
Int.natAbs_neg n
#align zmod.val_neg' ZMod.val_neg'
@[simp]
theorem val_mul' {m n : ZMod 0} : (m * n).val = m.val * n.val :=
Int.natAbs_mul m n
#align zmod.val_mul' ZMod.val_mul'
@[simp]
theorem val_natCast {n : ℕ} (a : ℕ) : (a : ZMod n).val = a % n := by
cases n
· rw [Nat.mod_zero]
exact Int.natAbs_ofNat a
· apply Fin.val_natCast
#align zmod.val_nat_cast ZMod.val_natCast
@[deprecated (since := "2024-04-17")]
alias val_nat_cast := val_natCast
theorem val_unit' {n : ZMod 0} : IsUnit n ↔ n.val = 1 := by
simp only [val]
rw [Int.isUnit_iff, Int.natAbs_eq_iff, Nat.cast_one]
lemma eq_one_of_isUnit_natCast {n : ℕ} (h : IsUnit (n : ZMod 0)) : n = 1 := by
rw [← Nat.mod_zero n, ← val_natCast, val_unit'.mp h]
theorem val_natCast_of_lt {n a : ℕ} (h : a < n) : (a : ZMod n).val = a := by
rwa [val_natCast, Nat.mod_eq_of_lt]
@[deprecated (since := "2024-04-17")]
alias val_nat_cast_of_lt := val_natCast_of_lt
instance charP (n : ℕ) : CharP (ZMod n) n where
cast_eq_zero_iff' := by
intro k
cases' n with n
· simp [zero_dvd_iff, Int.natCast_eq_zero, Nat.zero_eq]
· exact Fin.natCast_eq_zero
@[simp]
theorem addOrderOf_one (n : ℕ) : addOrderOf (1 : ZMod n) = n :=
CharP.eq _ (CharP.addOrderOf_one _) (ZMod.charP n)
#align zmod.add_order_of_one ZMod.addOrderOf_one
/-- This lemma works in the case in which `ZMod n` is not infinite, i.e. `n ≠ 0`. The version
where `a ≠ 0` is `addOrderOf_coe'`. -/
@[simp]
theorem addOrderOf_coe (a : ℕ) {n : ℕ} (n0 : n ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
cases' a with a
· simp only [Nat.zero_eq, Nat.cast_zero, addOrderOf_zero, Nat.gcd_zero_right,
Nat.pos_of_ne_zero n0, Nat.div_self]
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a.succ_ne_zero, ZMod.addOrderOf_one]
#align zmod.add_order_of_coe ZMod.addOrderOf_coe
/-- This lemma works in the case in which `a ≠ 0`. The version where
`ZMod n` is not infinite, i.e. `n ≠ 0`, is `addOrderOf_coe`. -/
@[simp]
theorem addOrderOf_coe' {a : ℕ} (n : ℕ) (a0 : a ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a0, ZMod.addOrderOf_one]
#align zmod.add_order_of_coe' ZMod.addOrderOf_coe'
/-- We have that `ringChar (ZMod n) = n`. -/
theorem ringChar_zmod_n (n : ℕ) : ringChar (ZMod n) = n := by
rw [ringChar.eq_iff]
exact ZMod.charP n
#align zmod.ring_char_zmod_n ZMod.ringChar_zmod_n
-- @[simp] -- Porting note (#10618): simp can prove this
theorem natCast_self (n : ℕ) : (n : ZMod n) = 0 :=
CharP.cast_eq_zero (ZMod n) n
#align zmod.nat_cast_self ZMod.natCast_self
@[deprecated (since := "2024-04-17")]
alias nat_cast_self := natCast_self
@[simp]
theorem natCast_self' (n : ℕ) : (n + 1 : ZMod (n + 1)) = 0 := by
rw [← Nat.cast_add_one, natCast_self (n + 1)]
#align zmod.nat_cast_self' ZMod.natCast_self'
@[deprecated (since := "2024-04-17")]
alias nat_cast_self' := natCast_self'
section UniversalProperty
variable {n : ℕ} {R : Type*}
section
variable [AddGroupWithOne R]
/-- Cast an integer modulo `n` to another semiring.
This function is a morphism if the characteristic of `R` divides `n`.
See `ZMod.castHom` for a bundled version. -/
def cast : ∀ {n : ℕ}, ZMod n → R
| 0 => Int.cast
| _ + 1 => fun i => i.val
#align zmod.cast ZMod.cast
@[simp]
theorem cast_zero : (cast (0 : ZMod n) : R) = 0 := by
delta ZMod.cast
cases n
· exact Int.cast_zero
· simp
#align zmod.cast_zero ZMod.cast_zero
theorem cast_eq_val [NeZero n] (a : ZMod n) : (cast a : R) = a.val := by
cases n
· cases NeZero.ne 0 rfl
rfl
#align zmod.cast_eq_val ZMod.cast_eq_val
variable {S : Type*} [AddGroupWithOne S]
@[simp]
theorem _root_.Prod.fst_zmod_cast (a : ZMod n) : (cast a : R × S).fst = cast a := by
cases n
· rfl
· simp [ZMod.cast]
#align prod.fst_zmod_cast Prod.fst_zmod_cast
@[simp]
theorem _root_.Prod.snd_zmod_cast (a : ZMod n) : (cast a : R × S).snd = cast a := by
cases n
· rfl
· simp [ZMod.cast]
#align prod.snd_zmod_cast Prod.snd_zmod_cast
end
/-- So-named because the coercion is `Nat.cast` into `ZMod`. For `Nat.cast` into an arbitrary ring,
see `ZMod.natCast_val`. -/
theorem natCast_zmod_val {n : ℕ} [NeZero n] (a : ZMod n) : (a.val : ZMod n) = a := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.cast_val_eq_self
#align zmod.nat_cast_zmod_val ZMod.natCast_zmod_val
@[deprecated (since := "2024-04-17")]
alias nat_cast_zmod_val := natCast_zmod_val
theorem natCast_rightInverse [NeZero n] : Function.RightInverse val ((↑) : ℕ → ZMod n) :=
natCast_zmod_val
#align zmod.nat_cast_right_inverse ZMod.natCast_rightInverse
@[deprecated (since := "2024-04-17")]
alias nat_cast_rightInverse := natCast_rightInverse
theorem natCast_zmod_surjective [NeZero n] : Function.Surjective ((↑) : ℕ → ZMod n) :=
natCast_rightInverse.surjective
#align zmod.nat_cast_zmod_surjective ZMod.natCast_zmod_surjective
@[deprecated (since := "2024-04-17")]
alias nat_cast_zmod_surjective := natCast_zmod_surjective
/-- So-named because the outer coercion is `Int.cast` into `ZMod`. For `Int.cast` into an arbitrary
ring, see `ZMod.intCast_cast`. -/
@[norm_cast]
theorem intCast_zmod_cast (a : ZMod n) : ((cast a : ℤ) : ZMod n) = a := by
cases n
· simp [ZMod.cast, ZMod]
· dsimp [ZMod.cast, ZMod]
erw [Int.cast_natCast, Fin.cast_val_eq_self]
#align zmod.int_cast_zmod_cast ZMod.intCast_zmod_cast
@[deprecated (since := "2024-04-17")]
alias int_cast_zmod_cast := intCast_zmod_cast
theorem intCast_rightInverse : Function.RightInverse (cast : ZMod n → ℤ) ((↑) : ℤ → ZMod n) :=
intCast_zmod_cast
#align zmod.int_cast_right_inverse ZMod.intCast_rightInverse
@[deprecated (since := "2024-04-17")]
alias int_cast_rightInverse := intCast_rightInverse
theorem intCast_surjective : Function.Surjective ((↑) : ℤ → ZMod n) :=
intCast_rightInverse.surjective
#align zmod.int_cast_surjective ZMod.intCast_surjective
@[deprecated (since := "2024-04-17")]
alias int_cast_surjective := intCast_surjective
theorem cast_id : ∀ (n) (i : ZMod n), (ZMod.cast i : ZMod n) = i
| 0, _ => Int.cast_id
| _ + 1, i => natCast_zmod_val i
#align zmod.cast_id ZMod.cast_id
@[simp]
theorem cast_id' : (ZMod.cast : ZMod n → ZMod n) = id :=
funext (cast_id n)
#align zmod.cast_id' ZMod.cast_id'
variable (R) [Ring R]
/-- The coercions are respectively `Nat.cast` and `ZMod.cast`. -/
@[simp]
theorem natCast_comp_val [NeZero n] : ((↑) : ℕ → R) ∘ (val : ZMod n → ℕ) = cast := by
cases n
· cases NeZero.ne 0 rfl
rfl
#align zmod.nat_cast_comp_val ZMod.natCast_comp_val
@[deprecated (since := "2024-04-17")]
alias nat_cast_comp_val := natCast_comp_val
/-- The coercions are respectively `Int.cast`, `ZMod.cast`, and `ZMod.cast`. -/
@[simp]
theorem intCast_comp_cast : ((↑) : ℤ → R) ∘ (cast : ZMod n → ℤ) = cast := by
cases n
· exact congr_arg (Int.cast ∘ ·) ZMod.cast_id'
· ext
simp [ZMod, ZMod.cast]
#align zmod.int_cast_comp_cast ZMod.intCast_comp_cast
@[deprecated (since := "2024-04-17")]
alias int_cast_comp_cast := intCast_comp_cast
variable {R}
@[simp]
theorem natCast_val [NeZero n] (i : ZMod n) : (i.val : R) = cast i :=
congr_fun (natCast_comp_val R) i
#align zmod.nat_cast_val ZMod.natCast_val
@[deprecated (since := "2024-04-17")]
alias nat_cast_val := natCast_val
@[simp]
theorem intCast_cast (i : ZMod n) : ((cast i : ℤ) : R) = cast i :=
congr_fun (intCast_comp_cast R) i
#align zmod.int_cast_cast ZMod.intCast_cast
@[deprecated (since := "2024-04-17")]
alias int_cast_cast := intCast_cast
theorem cast_add_eq_ite {n : ℕ} (a b : ZMod n) :
(cast (a + b) : ℤ) =
if (n : ℤ) ≤ cast a + cast b then (cast a + cast b - n : ℤ) else cast a + cast b := by
cases' n with n
· simp; rfl
change Fin (n + 1) at a b
change ((((a + b) : Fin (n + 1)) : ℕ) : ℤ) = if ((n + 1 : ℕ) : ℤ) ≤ (a : ℕ) + b then _ else _
simp only [Fin.val_add_eq_ite, Int.ofNat_succ, Int.ofNat_le]
norm_cast
split_ifs with h
· rw [Nat.cast_sub h]
congr
· rfl
#align zmod.coe_add_eq_ite ZMod.cast_add_eq_ite
section CharDvd
/-! If the characteristic of `R` divides `n`, then `cast` is a homomorphism. -/
variable {m : ℕ} [CharP R m]
@[simp]
theorem cast_one (h : m ∣ n) : (cast (1 : ZMod n) : R) = 1 := by
cases' n with n
· exact Int.cast_one
show ((1 % (n + 1) : ℕ) : R) = 1
cases n;
· rw [Nat.dvd_one] at h
subst m
have : Subsingleton R := CharP.CharOne.subsingleton
apply Subsingleton.elim
rw [Nat.mod_eq_of_lt]
· exact Nat.cast_one
exact Nat.lt_of_sub_eq_succ rfl
#align zmod.cast_one ZMod.cast_one
theorem cast_add (h : m ∣ n) (a b : ZMod n) : (cast (a + b : ZMod n) : R) = cast a + cast b := by
cases n
· apply Int.cast_add
symm
dsimp [ZMod, ZMod.cast]
erw [← Nat.cast_add, ← sub_eq_zero, ← Nat.cast_sub (Nat.mod_le _ _),
@CharP.cast_eq_zero_iff R _ m]
exact h.trans (Nat.dvd_sub_mod _)
#align zmod.cast_add ZMod.cast_add
theorem cast_mul (h : m ∣ n) (a b : ZMod n) : (cast (a * b : ZMod n) : R) = cast a * cast b := by
cases n
· apply Int.cast_mul
symm
dsimp [ZMod, ZMod.cast]
erw [← Nat.cast_mul, ← sub_eq_zero, ← Nat.cast_sub (Nat.mod_le _ _),
@CharP.cast_eq_zero_iff R _ m]
exact h.trans (Nat.dvd_sub_mod _)
#align zmod.cast_mul ZMod.cast_mul
/-- The canonical ring homomorphism from `ZMod n` to a ring of characteristic dividing `n`.
See also `ZMod.lift` for a generalized version working in `AddGroup`s.
-/
def castHom (h : m ∣ n) (R : Type*) [Ring R] [CharP R m] : ZMod n →+* R where
toFun := cast
map_zero' := cast_zero
map_one' := cast_one h
map_add' := cast_add h
map_mul' := cast_mul h
#align zmod.cast_hom ZMod.castHom
@[simp]
theorem castHom_apply {h : m ∣ n} (i : ZMod n) : castHom h R i = cast i :=
rfl
#align zmod.cast_hom_apply ZMod.castHom_apply
@[simp]
theorem cast_sub (h : m ∣ n) (a b : ZMod n) : (cast (a - b : ZMod n) : R) = cast a - cast b :=
(castHom h R).map_sub a b
#align zmod.cast_sub ZMod.cast_sub
@[simp]
theorem cast_neg (h : m ∣ n) (a : ZMod n) : (cast (-a : ZMod n) : R) = -(cast a) :=
(castHom h R).map_neg a
#align zmod.cast_neg ZMod.cast_neg
@[simp]
theorem cast_pow (h : m ∣ n) (a : ZMod n) (k : ℕ) : (cast (a ^ k : ZMod n) : R) = (cast a) ^ k :=
(castHom h R).map_pow a k
#align zmod.cast_pow ZMod.cast_pow
@[simp, norm_cast]
theorem cast_natCast (h : m ∣ n) (k : ℕ) : (cast (k : ZMod n) : R) = k :=
map_natCast (castHom h R) k
#align zmod.cast_nat_cast ZMod.cast_natCast
@[deprecated (since := "2024-04-17")]
alias cast_nat_cast := cast_natCast
@[simp, norm_cast]
theorem cast_intCast (h : m ∣ n) (k : ℤ) : (cast (k : ZMod n) : R) = k :=
map_intCast (castHom h R) k
#align zmod.cast_int_cast ZMod.cast_intCast
@[deprecated (since := "2024-04-17")]
alias cast_int_cast := cast_intCast
end CharDvd
section CharEq
/-! Some specialised simp lemmas which apply when `R` has characteristic `n`. -/
variable [CharP R n]
@[simp]
theorem cast_one' : (cast (1 : ZMod n) : R) = 1 :=
cast_one dvd_rfl
#align zmod.cast_one' ZMod.cast_one'
@[simp]
theorem cast_add' (a b : ZMod n) : (cast (a + b : ZMod n) : R) = cast a + cast b :=
cast_add dvd_rfl a b
#align zmod.cast_add' ZMod.cast_add'
@[simp]
theorem cast_mul' (a b : ZMod n) : (cast (a * b : ZMod n) : R) = cast a * cast b :=
cast_mul dvd_rfl a b
#align zmod.cast_mul' ZMod.cast_mul'
@[simp]
theorem cast_sub' (a b : ZMod n) : (cast (a - b : ZMod n) : R) = cast a - cast b :=
cast_sub dvd_rfl a b
#align zmod.cast_sub' ZMod.cast_sub'
@[simp]
theorem cast_pow' (a : ZMod n) (k : ℕ) : (cast (a ^ k : ZMod n) : R) = (cast a : R) ^ k :=
cast_pow dvd_rfl a k
#align zmod.cast_pow' ZMod.cast_pow'
@[simp, norm_cast]
theorem cast_natCast' (k : ℕ) : (cast (k : ZMod n) : R) = k :=
cast_natCast dvd_rfl k
#align zmod.cast_nat_cast' ZMod.cast_natCast'
@[deprecated (since := "2024-04-17")]
alias cast_nat_cast' := cast_natCast'
@[simp, norm_cast]
theorem cast_intCast' (k : ℤ) : (cast (k : ZMod n) : R) = k :=
cast_intCast dvd_rfl k
#align zmod.cast_int_cast' ZMod.cast_intCast'
@[deprecated (since := "2024-04-17")]
alias cast_int_cast' := cast_intCast'
variable (R)
theorem castHom_injective : Function.Injective (ZMod.castHom (dvd_refl n) R) := by
rw [injective_iff_map_eq_zero]
intro x
obtain ⟨k, rfl⟩ := ZMod.intCast_surjective x
rw [map_intCast, CharP.intCast_eq_zero_iff R n, CharP.intCast_eq_zero_iff (ZMod n) n]
exact id
#align zmod.cast_hom_injective ZMod.castHom_injective
theorem castHom_bijective [Fintype R] (h : Fintype.card R = n) :
Function.Bijective (ZMod.castHom (dvd_refl n) R) := by
haveI : NeZero n :=
⟨by
intro hn
rw [hn] at h
exact (Fintype.card_eq_zero_iff.mp h).elim' 0⟩
rw [Fintype.bijective_iff_injective_and_card, ZMod.card, h, eq_self_iff_true, and_true_iff]
apply ZMod.castHom_injective
#align zmod.cast_hom_bijective ZMod.castHom_bijective
/-- The unique ring isomorphism between `ZMod n` and a ring `R`
of characteristic `n` and cardinality `n`. -/
noncomputable def ringEquiv [Fintype R] (h : Fintype.card R = n) : ZMod n ≃+* R :=
RingEquiv.ofBijective _ (ZMod.castHom_bijective R h)
#align zmod.ring_equiv ZMod.ringEquiv
/-- The identity between `ZMod m` and `ZMod n` when `m = n`, as a ring isomorphism. -/
def ringEquivCongr {m n : ℕ} (h : m = n) : ZMod m ≃+* ZMod n := by
cases' m with m <;> cases' n with n
· exact RingEquiv.refl _
· exfalso
exact n.succ_ne_zero h.symm
· exfalso
exact m.succ_ne_zero h
· exact
{ finCongr h with
map_mul' := fun a b => by
dsimp [ZMod]
ext
rw [Fin.coe_cast, Fin.coe_mul, Fin.coe_mul, Fin.coe_cast, Fin.coe_cast, ← h]
map_add' := fun a b => by
dsimp [ZMod]
ext
rw [Fin.coe_cast, Fin.val_add, Fin.val_add, Fin.coe_cast, Fin.coe_cast, ← h] }
#align zmod.ring_equiv_congr ZMod.ringEquivCongr
@[simp] lemma ringEquivCongr_refl (a : ℕ) : ringEquivCongr (rfl : a = a) = .refl _ := by
cases a <;> rfl
lemma ringEquivCongr_refl_apply {a : ℕ} (x : ZMod a) : ringEquivCongr rfl x = x := by
rw [ringEquivCongr_refl]
rfl
lemma ringEquivCongr_symm {a b : ℕ} (hab : a = b) :
(ringEquivCongr hab).symm = ringEquivCongr hab.symm := by
subst hab
cases a <;> rfl
lemma ringEquivCongr_trans {a b c : ℕ} (hab : a = b) (hbc : b = c) :
(ringEquivCongr hab).trans (ringEquivCongr hbc) = ringEquivCongr (hab.trans hbc) := by
subst hab hbc
cases a <;> rfl
lemma ringEquivCongr_ringEquivCongr_apply {a b c : ℕ} (hab : a = b) (hbc : b = c) (x : ZMod a) :
ringEquivCongr hbc (ringEquivCongr hab x) = ringEquivCongr (hab.trans hbc) x := by
rw [← ringEquivCongr_trans hab hbc]
rfl
lemma ringEquivCongr_val {a b : ℕ} (h : a = b) (x : ZMod a) :
ZMod.val ((ZMod.ringEquivCongr h) x) = ZMod.val x := by
subst h
cases a <;> rfl
lemma ringEquivCongr_intCast {a b : ℕ} (h : a = b) (z : ℤ) :
ZMod.ringEquivCongr h z = z := by
subst h
cases a <;> rfl
@[deprecated (since := "2024-05-25")] alias int_coe_ringEquivCongr := ringEquivCongr_intCast
end CharEq
end UniversalProperty
theorem intCast_eq_intCast_iff (a b : ℤ) (c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a ≡ b [ZMOD c] :=
CharP.intCast_eq_intCast (ZMod c) c
#align zmod.int_coe_eq_int_coe_iff ZMod.intCast_eq_intCast_iff
@[deprecated (since := "2024-04-17")]
alias int_cast_eq_int_cast_iff := intCast_eq_intCast_iff
theorem intCast_eq_intCast_iff' (a b : ℤ) (c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a % c = b % c :=
ZMod.intCast_eq_intCast_iff a b c
#align zmod.int_coe_eq_int_coe_iff' ZMod.intCast_eq_intCast_iff'
@[deprecated (since := "2024-04-17")]
alias int_cast_eq_int_cast_iff' := intCast_eq_intCast_iff'
theorem natCast_eq_natCast_iff (a b c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a ≡ b [MOD c] := by
simpa [Int.natCast_modEq_iff] using ZMod.intCast_eq_intCast_iff a b c
#align zmod.nat_coe_eq_nat_coe_iff ZMod.natCast_eq_natCast_iff
@[deprecated (since := "2024-04-17")]
alias nat_cast_eq_nat_cast_iff := natCast_eq_natCast_iff
theorem natCast_eq_natCast_iff' (a b c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a % c = b % c :=
ZMod.natCast_eq_natCast_iff a b c
#align zmod.nat_coe_eq_nat_coe_iff' ZMod.natCast_eq_natCast_iff'
@[deprecated (since := "2024-04-17")]
alias nat_cast_eq_nat_cast_iff' := natCast_eq_natCast_iff'
theorem intCast_zmod_eq_zero_iff_dvd (a : ℤ) (b : ℕ) : (a : ZMod b) = 0 ↔ (b : ℤ) ∣ a := by
rw [← Int.cast_zero, ZMod.intCast_eq_intCast_iff, Int.modEq_zero_iff_dvd]
#align zmod.int_coe_zmod_eq_zero_iff_dvd ZMod.intCast_zmod_eq_zero_iff_dvd
@[deprecated (since := "2024-04-17")]
alias int_cast_zmod_eq_zero_iff_dvd := intCast_zmod_eq_zero_iff_dvd
theorem intCast_eq_intCast_iff_dvd_sub (a b : ℤ) (c : ℕ) : (a : ZMod c) = ↑b ↔ ↑c ∣ b - a := by
rw [ZMod.intCast_eq_intCast_iff, Int.modEq_iff_dvd]
#align zmod.int_coe_eq_int_coe_iff_dvd_sub ZMod.intCast_eq_intCast_iff_dvd_sub
@[deprecated (since := "2024-04-17")]
alias int_cast_eq_int_cast_iff_dvd_sub := intCast_eq_intCast_iff_dvd_sub
theorem natCast_zmod_eq_zero_iff_dvd (a b : ℕ) : (a : ZMod b) = 0 ↔ b ∣ a := by
rw [← Nat.cast_zero, ZMod.natCast_eq_natCast_iff, Nat.modEq_zero_iff_dvd]
#align zmod.nat_coe_zmod_eq_zero_iff_dvd ZMod.natCast_zmod_eq_zero_iff_dvd
@[deprecated (since := "2024-04-17")]
alias nat_cast_zmod_eq_zero_iff_dvd := natCast_zmod_eq_zero_iff_dvd
theorem val_intCast {n : ℕ} (a : ℤ) [NeZero n] : ↑(a : ZMod n).val = a % n := by
have hle : (0 : ℤ) ≤ ↑(a : ZMod n).val := Int.natCast_nonneg _
have hlt : ↑(a : ZMod n).val < (n : ℤ) := Int.ofNat_lt.mpr (ZMod.val_lt a)
refine (Int.emod_eq_of_lt hle hlt).symm.trans ?_
rw [← ZMod.intCast_eq_intCast_iff', Int.cast_natCast, ZMod.natCast_val, ZMod.cast_id]
#align zmod.val_int_cast ZMod.val_intCast
@[deprecated (since := "2024-04-17")]
alias val_int_cast := val_intCast
theorem coe_intCast {n : ℕ} (a : ℤ) : cast (a : ZMod n) = a % n := by
cases n
· rw [Int.ofNat_zero, Int.emod_zero, Int.cast_id]; rfl
· rw [← val_intCast, val]; rfl
#align zmod.coe_int_cast ZMod.coe_intCast
@[deprecated (since := "2024-04-17")]
alias coe_int_cast := coe_intCast
@[simp]
theorem val_neg_one (n : ℕ) : (-1 : ZMod n.succ).val = n := by
dsimp [val, Fin.coe_neg]
cases n
· simp [Nat.mod_one]
· dsimp [ZMod, ZMod.cast]
rw [Fin.coe_neg_one]
#align zmod.val_neg_one ZMod.val_neg_one
/-- `-1 : ZMod n` lifts to `n - 1 : R`. This avoids the characteristic assumption in `cast_neg`. -/
theorem cast_neg_one {R : Type*} [Ring R] (n : ℕ) : cast (-1 : ZMod n) = (n - 1 : R) := by
cases' n with n
· dsimp [ZMod, ZMod.cast]; simp
· rw [← natCast_val, val_neg_one, Nat.cast_succ, add_sub_cancel_right]
#align zmod.cast_neg_one ZMod.cast_neg_one
theorem cast_sub_one {R : Type*} [Ring R] {n : ℕ} (k : ZMod n) :
(cast (k - 1 : ZMod n) : R) = (if k = 0 then (n : R) else cast k) - 1 := by
split_ifs with hk
· rw [hk, zero_sub, ZMod.cast_neg_one]
· cases n
· dsimp [ZMod, ZMod.cast]
rw [Int.cast_sub, Int.cast_one]
· dsimp [ZMod, ZMod.cast, ZMod.val]
rw [Fin.coe_sub_one, if_neg]
· rw [Nat.cast_sub, Nat.cast_one]
rwa [Fin.ext_iff, Fin.val_zero, ← Ne, ← Nat.one_le_iff_ne_zero] at hk
· exact hk
#align zmod.cast_sub_one ZMod.cast_sub_one
theorem natCast_eq_iff (p : ℕ) (n : ℕ) (z : ZMod p) [NeZero p] :
↑n = z ↔ ∃ k, n = z.val + p * k := by
constructor
· rintro rfl
refine ⟨n / p, ?_⟩
rw [val_natCast, Nat.mod_add_div]
· rintro ⟨k, rfl⟩
rw [Nat.cast_add, natCast_zmod_val, Nat.cast_mul, natCast_self, zero_mul,
add_zero]
#align zmod.nat_coe_zmod_eq_iff ZMod.natCast_eq_iff
theorem intCast_eq_iff (p : ℕ) (n : ℤ) (z : ZMod p) [NeZero p] :
↑n = z ↔ ∃ k, n = z.val + p * k := by
constructor
· rintro rfl
refine ⟨n / p, ?_⟩
rw [val_intCast, Int.emod_add_ediv]
· rintro ⟨k, rfl⟩
rw [Int.cast_add, Int.cast_mul, Int.cast_natCast, Int.cast_natCast, natCast_val,
ZMod.natCast_self, zero_mul, add_zero, cast_id]
#align zmod.int_coe_zmod_eq_iff ZMod.intCast_eq_iff
@[deprecated (since := "2024-05-25")] alias nat_coe_zmod_eq_iff := natCast_eq_iff
@[deprecated (since := "2024-05-25")] alias int_coe_zmod_eq_iff := intCast_eq_iff
@[push_cast, simp]
theorem intCast_mod (a : ℤ) (b : ℕ) : ((a % b : ℤ) : ZMod b) = (a : ZMod b) := by
rw [ZMod.intCast_eq_intCast_iff]
apply Int.mod_modEq
#align zmod.int_cast_mod ZMod.intCast_mod
@[deprecated (since := "2024-04-17")]
alias int_cast_mod := intCast_mod
theorem ker_intCastAddHom (n : ℕ) :
(Int.castAddHom (ZMod n)).ker = AddSubgroup.zmultiples (n : ℤ) := by
ext
rw [Int.mem_zmultiples_iff, AddMonoidHom.mem_ker, Int.coe_castAddHom,
intCast_zmod_eq_zero_iff_dvd]
#align zmod.ker_int_cast_add_hom ZMod.ker_intCastAddHom
@[deprecated (since := "2024-04-17")]
alias ker_int_castAddHom := ker_intCastAddHom
theorem cast_injective_of_le {m n : ℕ} [nzm : NeZero m] (h : m ≤ n) :
Function.Injective (@cast (ZMod n) _ m) := by
cases m with
| zero => cases nzm; simp_all
| succ m =>
rintro ⟨x, hx⟩ ⟨y, hy⟩ f
simp only [cast, val, natCast_eq_natCast_iff',
Nat.mod_eq_of_lt (hx.trans_le h), Nat.mod_eq_of_lt (hy.trans_le h)] at f
apply Fin.ext
exact f
theorem cast_zmod_eq_zero_iff_of_le {m n : ℕ} [NeZero m] (h : m ≤ n) (a : ZMod m) :
(cast a : ZMod n) = 0 ↔ a = 0 := by
rw [← ZMod.cast_zero (n := m)]
exact Injective.eq_iff' (cast_injective_of_le h) rfl
-- Porting note: commented
-- unseal Int.NonNeg
@[simp]
theorem natCast_toNat (p : ℕ) : ∀ {z : ℤ} (_h : 0 ≤ z), (z.toNat : ZMod p) = z
| (n : ℕ), _h => by simp only [Int.cast_natCast, Int.toNat_natCast]
| Int.negSucc n, h => by simp at h
#align zmod.nat_cast_to_nat ZMod.natCast_toNat
@[deprecated (since := "2024-04-17")]
alias nat_cast_toNat := natCast_toNat
theorem val_injective (n : ℕ) [NeZero n] : Function.Injective (val : ZMod n → ℕ) := by
cases n
· cases NeZero.ne 0 rfl
intro a b h
dsimp [ZMod]
ext
exact h
#align zmod.val_injective ZMod.val_injective
theorem val_one_eq_one_mod (n : ℕ) : (1 : ZMod n).val = 1 % n := by
rw [← Nat.cast_one, val_natCast]
#align zmod.val_one_eq_one_mod ZMod.val_one_eq_one_mod
theorem val_one (n : ℕ) [Fact (1 < n)] : (1 : ZMod n).val = 1 := by
rw [val_one_eq_one_mod]
exact Nat.mod_eq_of_lt Fact.out
#align zmod.val_one ZMod.val_one
theorem val_add {n : ℕ} [NeZero n] (a b : ZMod n) : (a + b).val = (a.val + b.val) % n := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.val_add
#align zmod.val_add ZMod.val_add
theorem val_add_of_lt {n : ℕ} {a b : ZMod n} (h : a.val + b.val < n) :
(a + b).val = a.val + b.val := by
have : NeZero n := by constructor; rintro rfl; simp at h
rw [ZMod.val_add, Nat.mod_eq_of_lt h]
theorem val_add_val_of_le {n : ℕ} [NeZero n] {a b : ZMod n} (h : n ≤ a.val + b.val) :
a.val + b.val = (a + b).val + n := by
rw [val_add, Nat.add_mod_add_of_le_add_mod, Nat.mod_eq_of_lt (val_lt _),
Nat.mod_eq_of_lt (val_lt _)]
rwa [Nat.mod_eq_of_lt (val_lt _), Nat.mod_eq_of_lt (val_lt _)]
theorem val_add_of_le {n : ℕ} [NeZero n] {a b : ZMod n} (h : n ≤ a.val + b.val) :
(a + b).val = a.val + b.val - n := by
rw [val_add_val_of_le h]
exact eq_tsub_of_add_eq rfl
theorem val_add_le {n : ℕ} (a b : ZMod n) : (a + b).val ≤ a.val + b.val := by
cases n
· simp [ZMod.val]; apply Int.natAbs_add_le
· simp [ZMod.val_add]; apply Nat.mod_le
theorem val_mul {n : ℕ} (a b : ZMod n) : (a * b).val = a.val * b.val % n := by
cases n
· rw [Nat.mod_zero]
apply Int.natAbs_mul
· apply Fin.val_mul
#align zmod.val_mul ZMod.val_mul
theorem val_mul_le {n : ℕ} (a b : ZMod n) : (a * b).val ≤ a.val * b.val := by
rw [val_mul]
apply Nat.mod_le
theorem val_mul_of_lt {n : ℕ} {a b : ZMod n} (h : a.val * b.val < n) :
(a * b).val = a.val * b.val := by
rw [val_mul]
apply Nat.mod_eq_of_lt h
instance nontrivial (n : ℕ) [Fact (1 < n)] : Nontrivial (ZMod n) :=
⟨⟨0, 1, fun h =>
zero_ne_one <|
calc
0 = (0 : ZMod n).val := by rw [val_zero]
_ = (1 : ZMod n).val := congr_arg ZMod.val h
_ = 1 := val_one n
⟩⟩
#align zmod.nontrivial ZMod.nontrivial
instance nontrivial' : Nontrivial (ZMod 0) := by
delta ZMod; infer_instance
#align zmod.nontrivial' ZMod.nontrivial'
/-- The inversion on `ZMod n`.
It is setup in such a way that `a * a⁻¹` is equal to `gcd a.val n`.
In particular, if `a` is coprime to `n`, and hence a unit, `a * a⁻¹ = 1`. -/
def inv : ∀ n : ℕ, ZMod n → ZMod n
| 0, i => Int.sign i
| n + 1, i => Nat.gcdA i.val (n + 1)
#align zmod.inv ZMod.inv
instance (n : ℕ) : Inv (ZMod n) :=
⟨inv n⟩
@[nolint unusedHavesSuffices]
theorem inv_zero : ∀ n : ℕ, (0 : ZMod n)⁻¹ = 0
| 0 => Int.sign_zero
| n + 1 =>
show (Nat.gcdA _ (n + 1) : ZMod (n + 1)) = 0 by
rw [val_zero]
unfold Nat.gcdA Nat.xgcd Nat.xgcdAux
rfl
#align zmod.inv_zero ZMod.inv_zero
theorem mul_inv_eq_gcd {n : ℕ} (a : ZMod n) : a * a⁻¹ = Nat.gcd a.val n := by
cases' n with n
· dsimp [ZMod] at a ⊢
calc
_ = a * Int.sign a := rfl
_ = a.natAbs := by rw [Int.mul_sign]
_ = a.natAbs.gcd 0 := by rw [Nat.gcd_zero_right]
· calc
a * a⁻¹ = a * a⁻¹ + n.succ * Nat.gcdB (val a) n.succ := by
rw [natCast_self, zero_mul, add_zero]
_ = ↑(↑a.val * Nat.gcdA (val a) n.succ + n.succ * Nat.gcdB (val a) n.succ) := by
push_cast
rw [natCast_zmod_val]
rfl
_ = Nat.gcd a.val n.succ := by rw [← Nat.gcd_eq_gcd_ab a.val n.succ]; rfl
#align zmod.mul_inv_eq_gcd ZMod.mul_inv_eq_gcd
@[simp]
theorem natCast_mod (a : ℕ) (n : ℕ) : ((a % n : ℕ) : ZMod n) = a := by
conv =>
rhs
rw [← Nat.mod_add_div a n]
simp
#align zmod.nat_cast_mod ZMod.natCast_mod
@[deprecated (since := "2024-04-17")]
alias nat_cast_mod := natCast_mod
theorem eq_iff_modEq_nat (n : ℕ) {a b : ℕ} : (a : ZMod n) = b ↔ a ≡ b [MOD n] := by
cases n
· simp [Nat.ModEq, Int.natCast_inj, Nat.mod_zero]
· rw [Fin.ext_iff, Nat.ModEq, ← val_natCast, ← val_natCast]
exact Iff.rfl
#align zmod.eq_iff_modeq_nat ZMod.eq_iff_modEq_nat
theorem coe_mul_inv_eq_one {n : ℕ} (x : ℕ) (h : Nat.Coprime x n) :
((x : ZMod n) * (x : ZMod n)⁻¹) = 1 := by
rw [Nat.Coprime, Nat.gcd_comm, Nat.gcd_rec] at h
rw [mul_inv_eq_gcd, val_natCast, h, Nat.cast_one]
#align zmod.coe_mul_inv_eq_one ZMod.coe_mul_inv_eq_one
/-- `unitOfCoprime` makes an element of `(ZMod n)ˣ` given
a natural number `x` and a proof that `x` is coprime to `n` -/
def unitOfCoprime {n : ℕ} (x : ℕ) (h : Nat.Coprime x n) : (ZMod n)ˣ :=
⟨x, x⁻¹, coe_mul_inv_eq_one x h, by rw [mul_comm, coe_mul_inv_eq_one x h]⟩
#align zmod.unit_of_coprime ZMod.unitOfCoprime
@[simp]
theorem coe_unitOfCoprime {n : ℕ} (x : ℕ) (h : Nat.Coprime x n) :
(unitOfCoprime x h : ZMod n) = x :=
rfl
#align zmod.coe_unit_of_coprime ZMod.coe_unitOfCoprime
theorem val_coe_unit_coprime {n : ℕ} (u : (ZMod n)ˣ) : Nat.Coprime (u : ZMod n).val n := by
cases' n with n
· rcases Int.units_eq_one_or u with (rfl | rfl) <;> simp
apply Nat.coprime_of_mul_modEq_one ((u⁻¹ : Units (ZMod (n + 1))) : ZMod (n + 1)).val
have := Units.ext_iff.1 (mul_right_inv u)
rw [Units.val_one] at this
rw [← eq_iff_modEq_nat, Nat.cast_one, ← this]; clear this
rw [← natCast_zmod_val ((u * u⁻¹ : Units (ZMod (n + 1))) : ZMod (n + 1))]
rw [Units.val_mul, val_mul, natCast_mod]
#align zmod.val_coe_unit_coprime ZMod.val_coe_unit_coprime
lemma isUnit_iff_coprime (m n : ℕ) : IsUnit (m : ZMod n) ↔ m.Coprime n := by
refine ⟨fun H ↦ ?_, fun H ↦ (unitOfCoprime m H).isUnit⟩
have H' := val_coe_unit_coprime H.unit
rw [IsUnit.unit_spec, val_natCast m, Nat.coprime_iff_gcd_eq_one] at H'
rw [Nat.coprime_iff_gcd_eq_one, Nat.gcd_comm, ← H']
exact Nat.gcd_rec n m
lemma isUnit_prime_iff_not_dvd {n p : ℕ} (hp : p.Prime) : IsUnit (p : ZMod n) ↔ ¬p ∣ n := by
rw [isUnit_iff_coprime, Nat.Prime.coprime_iff_not_dvd hp]
lemma isUnit_prime_of_not_dvd {n p : ℕ} (hp : p.Prime) (h : ¬ p ∣ n) : IsUnit (p : ZMod n) :=
(isUnit_prime_iff_not_dvd hp).mpr h
@[simp]
theorem inv_coe_unit {n : ℕ} (u : (ZMod n)ˣ) : (u : ZMod n)⁻¹ = (u⁻¹ : (ZMod n)ˣ) := by
have := congr_arg ((↑) : ℕ → ZMod n) (val_coe_unit_coprime u)
rw [← mul_inv_eq_gcd, Nat.cast_one] at this
let u' : (ZMod n)ˣ := ⟨u, (u : ZMod n)⁻¹, this, by rwa [mul_comm]⟩
have h : u = u' := by
apply Units.ext
rfl
rw [h]
rfl
#align zmod.inv_coe_unit ZMod.inv_coe_unit
theorem mul_inv_of_unit {n : ℕ} (a : ZMod n) (h : IsUnit a) : a * a⁻¹ = 1 := by
rcases h with ⟨u, rfl⟩
rw [inv_coe_unit, u.mul_inv]
#align zmod.mul_inv_of_unit ZMod.mul_inv_of_unit
theorem inv_mul_of_unit {n : ℕ} (a : ZMod n) (h : IsUnit a) : a⁻¹ * a = 1 := by
rw [mul_comm, mul_inv_of_unit a h]
#align zmod.inv_mul_of_unit ZMod.inv_mul_of_unit
-- TODO: If we changed `⁻¹` so that `ZMod n` is always a `DivisionMonoid`,
-- then we could use the general lemma `inv_eq_of_mul_eq_one`
protected theorem inv_eq_of_mul_eq_one (n : ℕ) (a b : ZMod n) (h : a * b = 1) : a⁻¹ = b :=
left_inv_eq_right_inv (inv_mul_of_unit a ⟨⟨a, b, h, mul_comm a b ▸ h⟩, rfl⟩) h
-- TODO: this equivalence is true for `ZMod 0 = ℤ`, but needs to use different functions.
/-- Equivalence between the units of `ZMod n` and
the subtype of terms `x : ZMod n` for which `x.val` is coprime to `n` -/
def unitsEquivCoprime {n : ℕ} [NeZero n] : (ZMod n)ˣ ≃ { x : ZMod n // Nat.Coprime x.val n } where
toFun x := ⟨x, val_coe_unit_coprime x⟩
invFun x := unitOfCoprime x.1.val x.2
left_inv := fun ⟨_, _, _, _⟩ => Units.ext (natCast_zmod_val _)
right_inv := fun ⟨_, _⟩ => by simp
#align zmod.units_equiv_coprime ZMod.unitsEquivCoprime
/-- The **Chinese remainder theorem**. For a pair of coprime natural numbers, `m` and `n`,
the rings `ZMod (m * n)` and `ZMod m × ZMod n` are isomorphic.
See `Ideal.quotientInfRingEquivPiQuotient` for the Chinese remainder theorem for ideals in any
ring.
-/
def chineseRemainder {m n : ℕ} (h : m.Coprime n) : ZMod (m * n) ≃+* ZMod m × ZMod n :=
let to_fun : ZMod (m * n) → ZMod m × ZMod n :=
ZMod.castHom (show m.lcm n ∣ m * n by simp [Nat.lcm_dvd_iff]) (ZMod m × ZMod n)
let inv_fun : ZMod m × ZMod n → ZMod (m * n) := fun x =>
if m * n = 0 then
if m = 1 then cast (RingHom.snd _ (ZMod n) x) else cast (RingHom.fst (ZMod m) _ x)
else Nat.chineseRemainder h x.1.val x.2.val
have inv : Function.LeftInverse inv_fun to_fun ∧ Function.RightInverse inv_fun to_fun :=
if hmn0 : m * n = 0 then by
rcases h.eq_of_mul_eq_zero hmn0 with (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩)
· constructor
· intro x; rfl
· rintro ⟨x, y⟩
fin_cases y
simp [to_fun, inv_fun, castHom, Prod.ext_iff, eq_iff_true_of_subsingleton]
· constructor
· intro x; rfl
· rintro ⟨x, y⟩
fin_cases x
simp [to_fun, inv_fun, castHom, Prod.ext_iff, eq_iff_true_of_subsingleton]
else by
haveI : NeZero (m * n) := ⟨hmn0⟩
haveI : NeZero m := ⟨left_ne_zero_of_mul hmn0⟩
haveI : NeZero n := ⟨right_ne_zero_of_mul hmn0⟩
have left_inv : Function.LeftInverse inv_fun to_fun := by
intro x
dsimp only [to_fun, inv_fun, ZMod.castHom_apply]
conv_rhs => rw [← ZMod.natCast_zmod_val x]
rw [if_neg hmn0, ZMod.eq_iff_modEq_nat, ← Nat.modEq_and_modEq_iff_modEq_mul h,
Prod.fst_zmod_cast, Prod.snd_zmod_cast]
refine
⟨(Nat.chineseRemainder h (cast x : ZMod m).val (cast x : ZMod n).val).2.left.trans ?_,
(Nat.chineseRemainder h (cast x : ZMod m).val (cast x : ZMod n).val).2.right.trans ?_⟩
· rw [← ZMod.eq_iff_modEq_nat, ZMod.natCast_zmod_val, ZMod.natCast_val]
· rw [← ZMod.eq_iff_modEq_nat, ZMod.natCast_zmod_val, ZMod.natCast_val]
exact ⟨left_inv, left_inv.rightInverse_of_card_le (by simp)⟩
{ toFun := to_fun,
invFun := inv_fun,
map_mul' := RingHom.map_mul _
map_add' := RingHom.map_add _
left_inv := inv.1
right_inv := inv.2 }
#align zmod.chinese_remainder ZMod.chineseRemainder
lemma subsingleton_iff {n : ℕ} : Subsingleton (ZMod n) ↔ n = 1 := by
constructor
· obtain (_ | _ | n) := n
· simpa [ZMod] using not_subsingleton _
· simp [ZMod]
· simpa [ZMod] using not_subsingleton _
· rintro rfl
infer_instance
lemma nontrivial_iff {n : ℕ} : Nontrivial (ZMod n) ↔ n ≠ 1 := by
rw [← not_subsingleton_iff_nontrivial, subsingleton_iff]
-- todo: this can be made a `Unique` instance.
instance subsingleton_units : Subsingleton (ZMod 2)ˣ :=
⟨by decide⟩
#align zmod.subsingleton_units ZMod.subsingleton_units
@[simp]
theorem add_self_eq_zero_iff_eq_zero {n : ℕ} (hn : Odd n) {a : ZMod n} :
a + a = 0 ↔ a = 0 := by
rw [Nat.odd_iff, ← Nat.two_dvd_ne_zero, ← Nat.prime_two.coprime_iff_not_dvd] at hn
rw [← mul_two, ← @Nat.cast_two (ZMod n), ← ZMod.coe_unitOfCoprime 2 hn, Units.mul_left_eq_zero]
theorem ne_neg_self {n : ℕ} (hn : Odd n) {a : ZMod n} (ha : a ≠ 0) : a ≠ -a := by
rwa [Ne, eq_neg_iff_add_eq_zero, add_self_eq_zero_iff_eq_zero hn]
#align zmod.ne_neg_self ZMod.ne_neg_self
theorem neg_one_ne_one {n : ℕ} [Fact (2 < n)] : (-1 : ZMod n) ≠ 1 :=
CharP.neg_one_ne_one (ZMod n) n
#align zmod.neg_one_ne_one ZMod.neg_one_ne_one
theorem neg_eq_self_mod_two (a : ZMod 2) : -a = a := by
fin_cases a <;> apply Fin.ext <;> simp [Fin.coe_neg, Int.natMod]; rfl
#align zmod.neg_eq_self_mod_two ZMod.neg_eq_self_mod_two
@[simp]
theorem natAbs_mod_two (a : ℤ) : (a.natAbs : ZMod 2) = a := by
cases a
· simp only [Int.natAbs_ofNat, Int.cast_natCast, Int.ofNat_eq_coe]
· simp only [neg_eq_self_mod_two, Nat.cast_succ, Int.natAbs, Int.cast_negSucc]
#align zmod.nat_abs_mod_two ZMod.natAbs_mod_two
@[simp]
theorem val_eq_zero : ∀ {n : ℕ} (a : ZMod n), a.val = 0 ↔ a = 0
| 0, a => Int.natAbs_eq_zero
| n + 1, a => by
rw [Fin.ext_iff]
exact Iff.rfl
#align zmod.val_eq_zero ZMod.val_eq_zero
theorem val_ne_zero {n : ℕ} (a : ZMod n) : a.val ≠ 0 ↔ a ≠ 0 :=
(val_eq_zero a).not
theorem neg_eq_self_iff {n : ℕ} (a : ZMod n) : -a = a ↔ a = 0 ∨ 2 * a.val = n := by
rw [neg_eq_iff_add_eq_zero, ← two_mul]
cases n
· erw [@mul_eq_zero ℤ, @mul_eq_zero ℕ, val_eq_zero]
exact
⟨fun h => h.elim (by simp) Or.inl, fun h =>
Or.inr (h.elim id fun h => h.elim (by simp) id)⟩
conv_lhs =>
rw [← a.natCast_zmod_val, ← Nat.cast_two, ← Nat.cast_mul, natCast_zmod_eq_zero_iff_dvd]
constructor
· rintro ⟨m, he⟩
cases' m with m
· erw [mul_zero, mul_eq_zero] at he
rcases he with (⟨⟨⟩⟩ | he)
exact Or.inl (a.val_eq_zero.1 he)
cases m
· right
rwa [show 0 + 1 = 1 from rfl, mul_one] at he
refine (a.val_lt.not_le <| Nat.le_of_mul_le_mul_left ?_ zero_lt_two).elim
rw [he, mul_comm]
apply Nat.mul_le_mul_left
erw [Nat.succ_le_succ_iff, Nat.succ_le_succ_iff]; simp
· rintro (rfl | h)
· rw [val_zero, mul_zero]
apply dvd_zero
· rw [h]
#align zmod.neg_eq_self_iff ZMod.neg_eq_self_iff
theorem val_cast_of_lt {n : ℕ} {a : ℕ} (h : a < n) : (a : ZMod n).val = a := by
rw [val_natCast, Nat.mod_eq_of_lt h]
#align zmod.val_cast_of_lt ZMod.val_cast_of_lt
theorem neg_val' {n : ℕ} [NeZero n] (a : ZMod n) : (-a).val = (n - a.val) % n :=
calc
(-a).val = val (-a) % n := by rw [Nat.mod_eq_of_lt (-a).val_lt]
_ = (n - val a) % n :=
Nat.ModEq.add_right_cancel' _
(by
rw [Nat.ModEq, ← val_add, add_left_neg, tsub_add_cancel_of_le a.val_le, Nat.mod_self,
val_zero])
#align zmod.neg_val' ZMod.neg_val'
theorem neg_val {n : ℕ} [NeZero n] (a : ZMod n) : (-a).val = if a = 0 then 0 else n - a.val := by
rw [neg_val']
by_cases h : a = 0; · rw [if_pos h, h, val_zero, tsub_zero, Nat.mod_self]
rw [if_neg h]
apply Nat.mod_eq_of_lt
apply Nat.sub_lt (NeZero.pos n)
contrapose! h
rwa [Nat.le_zero, val_eq_zero] at h
#align zmod.neg_val ZMod.neg_val
theorem val_neg_of_ne_zero {n : ℕ} [nz : NeZero n] (a : ZMod n) [na : NeZero a] :
(- a).val = n - a.val := by simp_all [neg_val a, na.out]
theorem val_sub {n : ℕ} [NeZero n] {a b : ZMod n} (h : b.val ≤ a.val) :
(a - b).val = a.val - b.val := by
by_cases hb : b = 0
· cases hb; simp
· have : NeZero b := ⟨hb⟩
rw [sub_eq_add_neg, val_add, val_neg_of_ne_zero, ← Nat.add_sub_assoc (le_of_lt (val_lt _)),
add_comm, Nat.add_sub_assoc h, Nat.add_mod_left]
apply Nat.mod_eq_of_lt (tsub_lt_of_lt (val_lt _))
theorem val_cast_eq_val_of_lt {m n : ℕ} [nzm : NeZero m] {a : ZMod m}
(h : a.val < n) : (a.cast : ZMod n).val = a.val := by
have nzn : NeZero n := by constructor; rintro rfl; simp at h
cases m with
| zero => cases nzm; simp_all
| succ m =>
cases n with
| zero => cases nzn; simp_all
| succ n => exact Fin.val_cast_of_lt h
theorem cast_cast_zmod_of_le {m n : ℕ} [hm : NeZero m] (h : m ≤ n) (a : ZMod m) :
(cast (cast a : ZMod n) : ZMod m) = a := by
have : NeZero n := ⟨((Nat.zero_lt_of_ne_zero hm.out).trans_le h).ne'⟩
rw [cast_eq_val, val_cast_eq_val_of_lt (a.val_lt.trans_le h), natCast_zmod_val]
/-- `valMinAbs x` returns the integer in the same equivalence class as `x` that is closest to `0`,
The result will be in the interval `(-n/2, n/2]`. -/
def valMinAbs : ∀ {n : ℕ}, ZMod n → ℤ
| 0, x => x
| n@(_ + 1), x => if x.val ≤ n / 2 then x.val else (x.val : ℤ) - n
#align zmod.val_min_abs ZMod.valMinAbs
@[simp]
theorem valMinAbs_def_zero (x : ZMod 0) : valMinAbs x = x :=
rfl
#align zmod.val_min_abs_def_zero ZMod.valMinAbs_def_zero
theorem valMinAbs_def_pos {n : ℕ} [NeZero n] (x : ZMod n) :
valMinAbs x = if x.val ≤ n / 2 then (x.val : ℤ) else x.val - n := by
cases n
· cases NeZero.ne 0 rfl
· rfl
#align zmod.val_min_abs_def_pos ZMod.valMinAbs_def_pos
@[simp, norm_cast]
theorem coe_valMinAbs : ∀ {n : ℕ} (x : ZMod n), (x.valMinAbs : ZMod n) = x
| 0, x => Int.cast_id
| k@(n + 1), x => by
rw [valMinAbs_def_pos]
split_ifs
· rw [Int.cast_natCast, natCast_zmod_val]
· rw [Int.cast_sub, Int.cast_natCast, natCast_zmod_val, Int.cast_natCast, natCast_self,
sub_zero]
#align zmod.coe_val_min_abs ZMod.coe_valMinAbs
theorem injective_valMinAbs {n : ℕ} : (valMinAbs : ZMod n → ℤ).Injective :=
Function.injective_iff_hasLeftInverse.2 ⟨_, coe_valMinAbs⟩
#align zmod.injective_val_min_abs ZMod.injective_valMinAbs
theorem _root_.Nat.le_div_two_iff_mul_two_le {n m : ℕ} : m ≤ n / 2 ↔ (m : ℤ) * 2 ≤ n := by
rw [Nat.le_div_iff_mul_le zero_lt_two, ← Int.ofNat_le, Int.ofNat_mul, Nat.cast_two]
#align nat.le_div_two_iff_mul_two_le Nat.le_div_two_iff_mul_two_le
theorem valMinAbs_nonneg_iff {n : ℕ} [NeZero n] (x : ZMod n) : 0 ≤ x.valMinAbs ↔ x.val ≤ n / 2 := by
rw [valMinAbs_def_pos]; split_ifs with h
· exact iff_of_true (Nat.cast_nonneg _) h
· exact iff_of_false (sub_lt_zero.2 <| Int.ofNat_lt.2 x.val_lt).not_le h
#align zmod.val_min_abs_nonneg_iff ZMod.valMinAbs_nonneg_iff
theorem valMinAbs_mul_two_eq_iff {n : ℕ} (a : ZMod n) : a.valMinAbs * 2 = n ↔ 2 * a.val = n := by
cases' n with n
· simp
by_cases h : a.val ≤ n.succ / 2
· dsimp [valMinAbs]
rw [if_pos h, ← Int.natCast_inj, Nat.cast_mul, Nat.cast_two, mul_comm]
apply iff_of_false _ (mt _ h)
· intro he
rw [← a.valMinAbs_nonneg_iff, ← mul_nonneg_iff_left_nonneg_of_pos, he] at h
exacts [h (Nat.cast_nonneg _), zero_lt_two]
· rw [mul_comm]
exact fun h => (Nat.le_div_iff_mul_le zero_lt_two).2 h.le
#align zmod.val_min_abs_mul_two_eq_iff ZMod.valMinAbs_mul_two_eq_iff
theorem valMinAbs_mem_Ioc {n : ℕ} [NeZero n] (x : ZMod n) :
x.valMinAbs * 2 ∈ Set.Ioc (-n : ℤ) n := by
simp_rw [valMinAbs_def_pos, Nat.le_div_two_iff_mul_two_le]; split_ifs with h
· refine ⟨(neg_lt_zero.2 <| mod_cast NeZero.pos n).trans_le (mul_nonneg ?_ ?_), h⟩
exacts [Nat.cast_nonneg _, zero_le_two]
· refine ⟨?_, le_trans (mul_nonpos_of_nonpos_of_nonneg ?_ zero_le_two) <| Nat.cast_nonneg _⟩
· linarith only [h]
· rw [sub_nonpos, Int.ofNat_le]
exact x.val_lt.le
#align zmod.val_min_abs_mem_Ioc ZMod.valMinAbs_mem_Ioc
theorem valMinAbs_spec {n : ℕ} [NeZero n] (x : ZMod n) (y : ℤ) :
x.valMinAbs = y ↔ x = y ∧ y * 2 ∈ Set.Ioc (-n : ℤ) n :=
⟨by
rintro rfl
exact ⟨x.coe_valMinAbs.symm, x.valMinAbs_mem_Ioc⟩, fun h =>
by
rw [← sub_eq_zero]
apply @Int.eq_zero_of_abs_lt_dvd n
· rw [← intCast_zmod_eq_zero_iff_dvd, Int.cast_sub, coe_valMinAbs, h.1, sub_self]
rw [← mul_lt_mul_right (@zero_lt_two ℤ _ _ _ _ _)]
nth_rw 1 [← abs_eq_self.2 (@zero_le_two ℤ _ _ _ _)]
rw [← abs_mul, sub_mul, abs_lt]
constructor <;> linarith only [x.valMinAbs_mem_Ioc.1, x.valMinAbs_mem_Ioc.2, h.2.1, h.2.2]⟩
#align zmod.val_min_abs_spec ZMod.valMinAbs_spec
theorem natAbs_valMinAbs_le {n : ℕ} [NeZero n] (x : ZMod n) : x.valMinAbs.natAbs ≤ n / 2 := by
rw [Nat.le_div_two_iff_mul_two_le]
cases' x.valMinAbs.natAbs_eq with h h
· rw [← h]
exact x.valMinAbs_mem_Ioc.2
· rw [← neg_le_neg_iff, ← neg_mul, ← h]
exact x.valMinAbs_mem_Ioc.1.le
#align zmod.nat_abs_val_min_abs_le ZMod.natAbs_valMinAbs_le
@[simp]
theorem valMinAbs_zero : ∀ n, (0 : ZMod n).valMinAbs = 0
| 0 => by simp only [valMinAbs_def_zero]
| n + 1 => by simp only [valMinAbs_def_pos, if_true, Int.ofNat_zero, zero_le, val_zero]
#align zmod.val_min_abs_zero ZMod.valMinAbs_zero
@[simp]
theorem valMinAbs_eq_zero {n : ℕ} (x : ZMod n) : x.valMinAbs = 0 ↔ x = 0 := by
cases' n with n
· simp
rw [← valMinAbs_zero n.succ]
apply injective_valMinAbs.eq_iff
#align zmod.val_min_abs_eq_zero ZMod.valMinAbs_eq_zero
theorem natCast_natAbs_valMinAbs {n : ℕ} [NeZero n] (a : ZMod n) :
(a.valMinAbs.natAbs : ZMod n) = if a.val ≤ (n : ℕ) / 2 then a else -a := by
have : (a.val : ℤ) - n ≤ 0 := by
erw [sub_nonpos, Int.ofNat_le]
exact a.val_le
rw [valMinAbs_def_pos]
split_ifs
· rw [Int.natAbs_ofNat, natCast_zmod_val]
· rw [← Int.cast_natCast, Int.ofNat_natAbs_of_nonpos this, Int.cast_neg, Int.cast_sub,
Int.cast_natCast, Int.cast_natCast, natCast_self, sub_zero, natCast_zmod_val]
#align zmod.nat_cast_nat_abs_val_min_abs ZMod.natCast_natAbs_valMinAbs
@[deprecated (since := "2024-04-17")]
alias nat_cast_natAbs_valMinAbs := natCast_natAbs_valMinAbs
theorem valMinAbs_neg_of_ne_half {n : ℕ} {a : ZMod n} (ha : 2 * a.val ≠ n) :
(-a).valMinAbs = -a.valMinAbs := by
cases' eq_zero_or_neZero n with h h
· subst h
rfl
refine (valMinAbs_spec _ _).2 ⟨?_, ?_, ?_⟩
· rw [Int.cast_neg, coe_valMinAbs]
· rw [neg_mul, neg_lt_neg_iff]
exact a.valMinAbs_mem_Ioc.2.lt_of_ne (mt a.valMinAbs_mul_two_eq_iff.1 ha)
· linarith only [a.valMinAbs_mem_Ioc.1]
#align zmod.val_min_abs_neg_of_ne_half ZMod.valMinAbs_neg_of_ne_half
@[simp]
theorem natAbs_valMinAbs_neg {n : ℕ} (a : ZMod n) : (-a).valMinAbs.natAbs = a.valMinAbs.natAbs := by
by_cases h2a : 2 * a.val = n
· rw [a.neg_eq_self_iff.2 (Or.inr h2a)]
· rw [valMinAbs_neg_of_ne_half h2a, Int.natAbs_neg]
#align zmod.nat_abs_val_min_abs_neg ZMod.natAbs_valMinAbs_neg
theorem val_eq_ite_valMinAbs {n : ℕ} [NeZero n] (a : ZMod n) :
(a.val : ℤ) = a.valMinAbs + if a.val ≤ n / 2 then 0 else n := by
rw [valMinAbs_def_pos]
split_ifs <;> simp [add_zero, sub_add_cancel]
#align zmod.val_eq_ite_val_min_abs ZMod.val_eq_ite_valMinAbs
theorem prime_ne_zero (p q : ℕ) [hp : Fact p.Prime] [hq : Fact q.Prime] (hpq : p ≠ q) :
(q : ZMod p) ≠ 0 := by
rwa [← Nat.cast_zero, Ne, eq_iff_modEq_nat, Nat.modEq_zero_iff_dvd, ←
hp.1.coprime_iff_not_dvd, Nat.coprime_primes hp.1 hq.1]
#align zmod.prime_ne_zero ZMod.prime_ne_zero
variable {n a : ℕ}
theorem valMinAbs_natAbs_eq_min {n : ℕ} [hpos : NeZero n] (a : ZMod n) :
a.valMinAbs.natAbs = min a.val (n - a.val) := by
rw [valMinAbs_def_pos]
split_ifs with h
· rw [Int.natAbs_ofNat]
symm
apply
min_eq_left (le_trans h (le_trans (Nat.half_le_of_sub_le_half _) (Nat.sub_le_sub_left h n)))
rw [Nat.sub_sub_self (Nat.div_le_self _ _)]
· rw [← Int.natAbs_neg, neg_sub, ← Nat.cast_sub a.val_le]
symm
apply
min_eq_right
(le_trans (le_trans (Nat.sub_le_sub_left (lt_of_not_ge h) n) (Nat.le_half_of_half_lt_sub _))
(le_of_not_ge h))
rw [Nat.sub_sub_self (Nat.div_lt_self (lt_of_le_of_ne' (Nat.zero_le _) hpos.1) one_lt_two)]
apply Nat.lt_succ_self
#align zmod.val_min_abs_nat_abs_eq_min ZMod.valMinAbs_natAbs_eq_min
theorem valMinAbs_natCast_of_le_half (ha : a ≤ n / 2) : (a : ZMod n).valMinAbs = a := by
cases n
· simp
· simp [valMinAbs_def_pos, val_natCast, Nat.mod_eq_of_lt (ha.trans_lt <| Nat.div_lt_self' _ 0),
ha]
#align zmod.val_min_abs_nat_cast_of_le_half ZMod.valMinAbs_natCast_of_le_half
theorem valMinAbs_natCast_of_half_lt (ha : n / 2 < a) (ha' : a < n) :
(a : ZMod n).valMinAbs = a - n := by
cases n
· cases not_lt_bot ha'
· simp [valMinAbs_def_pos, val_natCast, Nat.mod_eq_of_lt ha', ha.not_le]
#align zmod.val_min_abs_nat_cast_of_half_lt ZMod.valMinAbs_natCast_of_half_lt
-- Porting note: There was an extraneous `nat_` in the mathlib3 name
@[simp]
theorem valMinAbs_natCast_eq_self [NeZero n] : (a : ZMod n).valMinAbs = a ↔ a ≤ n / 2 := by
refine ⟨fun ha => ?_, valMinAbs_natCast_of_le_half⟩
rw [← Int.natAbs_ofNat a, ← ha]
exact natAbs_valMinAbs_le a
#align zmod.val_min_nat_abs_nat_cast_eq_self ZMod.valMinAbs_natCast_eq_self
| Mathlib/Data/ZMod/Basic.lean | 1,309 | 1,322 | theorem natAbs_min_of_le_div_two (n : ℕ) (x y : ℤ) (he : (x : ZMod n) = y) (hl : x.natAbs ≤ n / 2) :
x.natAbs ≤ y.natAbs := by |
rw [intCast_eq_intCast_iff_dvd_sub] at he
obtain ⟨m, he⟩ := he
rw [sub_eq_iff_eq_add] at he
subst he
obtain rfl | hm := eq_or_ne m 0
· rw [mul_zero, zero_add]
apply hl.trans
rw [← add_le_add_iff_right x.natAbs]
refine le_trans (le_trans ((add_le_add_iff_left _).2 hl) ?_) (Int.natAbs_sub_le _ _)
rw [add_sub_cancel_right, Int.natAbs_mul, Int.natAbs_ofNat]
refine le_trans ?_ (Nat.le_mul_of_pos_right _ <| Int.natAbs_pos.2 hm)
rw [← mul_two]; apply Nat.div_mul_le_self
|
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